From b2feda451ccfbeaed02dce9088d6dd228cf15861 Mon Sep 17 00:00:00 2001
From: Bonface
Date: Tue, 13 Feb 2024 23:52:26 -0600
Subject: Update dataset RTF Files.
---
general/datasets/AILPublish/specifics.rtf | 1 -
general/datasets/AILPublish/summary.rtf | 1 -
general/datasets/AXBXAGeno/acknowledgment.rtf | 15 -
general/datasets/AXBXAGeno/cases.rtf | 25 -
general/datasets/AXBXAGeno/summary.rtf | 1 -
general/datasets/Ailpublish/specifics.rtf | 1 +
general/datasets/Ailpublish/summary.rtf | 1 +
general/datasets/Akxdgeno/summary.rtf | 1 +
general/datasets/Axbxageno/acknowledgment.rtf | 15 +
general/datasets/Axbxageno/cases.rtf | 25 +
general/datasets/Axbxageno/summary.rtf | 1 +
general/datasets/B139_k_1206_m/citation.rtf | 1 +
general/datasets/B139_k_1206_m/contributors.rtf | 1 +
.../datasets/B139_k_1206_m/experiment-design.rtf | 3 +
general/datasets/B139_k_1206_m/experiment-type.rtf | 1 +
general/datasets/B139_k_1206_m/summary.rtf | 1 +
general/datasets/B139_k_1206_r/citation.rtf | 1 +
general/datasets/B139_k_1206_r/contributors.rtf | 1 +
.../datasets/B139_k_1206_r/experiment-design.rtf | 3 +
general/datasets/B139_k_1206_r/experiment-type.rtf | 1 +
general/datasets/B139_k_1206_r/summary.rtf | 1 +
general/datasets/B150_k_0406_r/citation.rtf | 1 +
general/datasets/B150_k_0406_r/contributors.rtf | 1 +
.../datasets/B150_k_0406_r/experiment-design.rtf | 3 +
general/datasets/B150_k_0406_r/experiment-type.rtf | 1 +
general/datasets/B150_k_0406_r/summary.rtf | 1 +
general/datasets/B1li0809m5/summary.rtf | 1 +
general/datasets/B1li0809r/summary.rtf | 1 +
general/datasets/B1mi0809m5/summary.rtf | 1 +
general/datasets/B1mi0809r/summary.rtf | 1 +
general/datasets/B30_k_1206_m/acknowledgment.rtf | 3 +
general/datasets/B30_k_1206_m/cases.rtf | 1748 ++
general/datasets/B30_k_1206_m/citation.rtf | 11 +
.../datasets/B30_k_1206_m/experiment-design.rtf | 62 +
general/datasets/B30_k_1206_m/experiment-type.rtf | 1 +
general/datasets/B30_k_1206_m/notes.rtf | 14 +
general/datasets/B30_k_1206_m/platform.rtf | 3 +
general/datasets/B30_k_1206_m/processing.rtf | 49 +
general/datasets/B30_k_1206_m/summary.rtf | 5 +
general/datasets/B30_k_1206_m/tissue.rtf | 9 +
general/datasets/B30_k_1206_r/acknowledgment.rtf | 3 +
general/datasets/B30_k_1206_r/cases.rtf | 1748 ++
general/datasets/B30_k_1206_r/citation.rtf | 11 +
.../datasets/B30_k_1206_r/experiment-design.rtf | 62 +
general/datasets/B30_k_1206_r/experiment-type.rtf | 1 +
general/datasets/B30_k_1206_r/notes.rtf | 14 +
general/datasets/B30_k_1206_r/platform.rtf | 3 +
general/datasets/B30_k_1206_r/processing.rtf | 49 +
general/datasets/B30_k_1206_r/summary.rtf | 5 +
general/datasets/B30_k_1206_r/tissue.rtf | 9 +
general/datasets/B30_k_1206_rn/acknowledgment.rtf | 3 +
general/datasets/B30_k_1206_rn/cases.rtf | 1748 ++
general/datasets/B30_k_1206_rn/citation.rtf | 11 +
.../datasets/B30_k_1206_rn/experiment-design.rtf | 62 +
general/datasets/B30_k_1206_rn/experiment-type.rtf | 1 +
general/datasets/B30_k_1206_rn/notes.rtf | 14 +
general/datasets/B30_k_1206_rn/platform.rtf | 3 +
general/datasets/B30_k_1206_rn/processing.rtf | 49 +
general/datasets/B30_k_1206_rn/summary.rtf | 5 +
general/datasets/B30_k_1206_rn/tissue.rtf | 9 +
general/datasets/B6D2ONCILM_0412/summary.rtf | 1 -
general/datasets/B6D2RIPublish/specifics.rtf | 1 -
general/datasets/B6D2RIPublish/summary.rtf | 1 -
.../datasets/B6btbrf2publish/acknowledgment.rtf | 1 +
general/datasets/B6btbrf2publish/summary.rtf | 5 +
.../datasets/B6d2oncilm_0412/experiment-type.rtf | 1 +
general/datasets/B6d2oncilm_0412/summary.rtf | 1 +
general/datasets/B6d2ripublish/specifics.rtf | 1 +
general/datasets/B6d2ripublish/summary.rtf | 1 +
general/datasets/BXDGeno/acknowledgment.rtf | 11 -
general/datasets/BXDGeno/summary.rtf | 59 -
general/datasets/BXDPublish/summary.rtf | 40 -
general/datasets/BXD_BonePublish/specifics.rtf | 1 -
general/datasets/BXD_BonePublish/summary.rtf | 1 -
.../datasets/BXD_HarvestedPublish/specifics.rtf | 1 -
general/datasets/BXD_HarvestedPublish/summary.rtf | 1 -
general/datasets/Bhhbf2geno/summary.rtf | 1 +
general/datasets/Br_m2_1106_r/acknowledgment.rtf | 3 +
general/datasets/Br_m2_1106_r/cases.rtf | 5 +
general/datasets/Br_m2_1106_r/contributors.rtf | 1 +
general/datasets/Br_m2_1106_r/notes.rtf | 2 +
general/datasets/Br_m2_1106_r/platform.rtf | 3 +
general/datasets/Br_m2_1106_r/processing.rtf | 7 +
general/datasets/Br_m2_1106_r/summary.rtf | 5 +
general/datasets/Br_m2_1106_r/tissue.rtf | 2751 ++
general/datasets/Br_u_0303_m/acknowledgment.rtf | 1 +
general/datasets/Br_u_0303_m/cases.rtf | 230 +
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general/datasets/Br_u_0303_m/processing.rtf | 27 +
general/datasets/Br_u_0303_m/summary.rtf | 1 +
general/datasets/Br_u_0303_m/tissue.rtf | 1 +
.../datasets/Br_u_0304_dpmmr/acknowledgment.rtf | 1 +
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general/datasets/Br_u_0304_dpmmr/summary.rtf | 1 +
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general/datasets/Br_u_0304_dpmr/cases.rtf | 232 +
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general/datasets/Br_u_0304_dpmr/platform.rtf | 14 +
general/datasets/Br_u_0304_dpmr/processing.rtf | 11 +
general/datasets/Br_u_0304_dpmr/summary.rtf | 1 +
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general/datasets/Br_u_0304_r/cases.rtf | 232 +
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general/datasets/Br_u_0304_r/platform.rtf | 14 +
general/datasets/Br_u_0304_r/processing.rtf | 11 +
general/datasets/Br_u_0304_r/summary.rtf | 1 +
general/datasets/Br_u_0304_r/tissue.rtf | 1 +
general/datasets/Br_u_0304_rr/acknowledgment.rtf | 1 +
general/datasets/Br_u_0304_rr/cases.rtf | 232 +
general/datasets/Br_u_0304_rr/notes.rtf | 1 +
general/datasets/Br_u_0304_rr/platform.rtf | 14 +
general/datasets/Br_u_0304_rr/processing.rtf | 11 +
general/datasets/Br_u_0304_rr/summary.rtf | 1 +
general/datasets/Br_u_0304_rr/tissue.rtf | 1 +
general/datasets/Br_u_0405_ss/acknowledgment.rtf | 1 +
general/datasets/Br_u_0405_ss/cases.rtf | 232 +
general/datasets/Br_u_0405_ss/notes.rtf | 1 +
general/datasets/Br_u_0405_ss/platform.rtf | 14 +
general/datasets/Br_u_0405_ss/processing.rtf | 11 +
general/datasets/Br_u_0405_ss/summary.rtf | 1 +
general/datasets/Br_u_0405_ss/tissue.rtf | 1 +
general/datasets/Br_u_0503_m/acknowledgment.rtf | 3 +
general/datasets/Br_u_0503_m/cases.rtf | 216 +
general/datasets/Br_u_0503_m/experiment-type.rtf | 1 +
general/datasets/Br_u_0503_m/notes.rtf | 5 +
general/datasets/Br_u_0503_m/platform.rtf | 16 +
general/datasets/Br_u_0503_m/processing.rtf | 14 +
general/datasets/Br_u_0503_m/summary.rtf | 1 +
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general/datasets/Br_u_0603_m/cases.rtf | 230 +
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general/datasets/Br_u_0805_p/acknowledgment.rtf | 1 +
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general/datasets/Br_u_0903_dpmm/cases.rtf | 230 +
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general/datasets/DoDTATRCRetMoGene2_0315/cases.rtf | 9 -
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general/datasets/DoDTATRCRetMoGene2_1313/cases.rtf | 1728 --
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.../specifics.rtf | 1 +
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general/datasets/Dodcmmrpretmogene2_0515/cases.rtf | 5 +
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.../datasets/Dodtatrcretblexmogene2_1213/cases.rtf | 1728 ++
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.../datasets/Dodtatrcretblmogene2_1213/cases.rtf | 1728 ++
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.../datasets/Dodtatrcretblmogene2e_0316/cases.rtf | 1728 ++
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general/datasets/Dodtatrcretmogene2_0315/cases.rtf | 9 +
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general/datasets/Dodtatrcretmogene2_1313/cases.rtf | 1728 ++
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general/datasets/EL_BXDCDHFDScWAT_0216/cases.rtf | 11 -
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general/datasets/EL_BXDCDHFDScWAT_0216/summary.rtf | 11 -
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general/datasets/EL_BXDCDScWAT_0216/platform.rtf | 5 -
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general/datasets/EPFLBXDprotCDRPN0214/cases.rtf | 1 -
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general/datasets/EPFLBXDprotRPN0513/cases.rtf | 1 -
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general/datasets/EPFLETHZBXDprotCD0514/notes.rtf | 16 -
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general/datasets/EPFLETHZBXDprotHFD0514/notes.rtf | 16 -
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.../Epflmouseliverhfdrma0818/specifics.rtf | 65 +
.../datasets/Epflmouseliverhfdrma0818/summary.rtf | 1 +
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general/datasets/Epflmouseliverrma0413/cases.rtf | 1 +
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.../datasets/Epflmousemusclecdrma1211/tissue.rtf | 25 +
.../Epflmousemusclecdrmaex1112/citation.rtf | 3 +
.../Epflmousemusclecdrmaex1112/summary.rtf | 10 +
.../datasets/Epflmousemusclecdrmaex1112/tissue.rtf | 25 +
.../Epflmousemusclehfdrma1211/citation.rtf | 3 +
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.../Epflmousemusclehfdrmaex1112/citation.rtf | 3 +
.../Epflmousemusclehfdrmaex1112/summary.rtf | 10 +
.../Epflmousemusclehfdrmaex1112/tissue.rtf | 25 +
.../datasets/Epflmousemusclerma1211/citation.rtf | 3 +
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general/datasets/Epflmousemusclerma1211/tissue.rtf | 25 +
.../Epflmousemusclerma_ex1112/citation.rtf | 3 +
.../datasets/Epflmousemusclerma_ex1112/summary.rtf | 10 +
.../datasets/Epflmousemusclerma_ex1112/tissue.rtf | 25 +
.../Eye_axbxa_1008_rankinv/acknowledgment.rtf | 11 +
general/datasets/Eye_axbxa_1008_rankinv/cases.rtf | 1 +
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.../datasets/Eye_axbxa_1008_rankinv/specifics.rtf | 1 +
.../datasets/Eye_axbxa_1008_rankinv/summary.rtf | 769 +
general/datasets/Eye_m2_0406_m/acknowledgment.rtf | 1 +
general/datasets/Eye_m2_0406_m/cases.rtf | 50 +
general/datasets/Eye_m2_0406_m/notes.rtf | 18 +
general/datasets/Eye_m2_0406_m/platform.rtf | 3 +
general/datasets/Eye_m2_0406_m/processing.rtf | 20 +
general/datasets/Eye_m2_0406_m/summary.rtf | 3 +
general/datasets/Eye_m2_0406_m/tissue.rtf | 7112 +++++
general/datasets/Eye_m2_0406_p/acknowledgment.rtf | 1 +
general/datasets/Eye_m2_0406_p/cases.rtf | 50 +
general/datasets/Eye_m2_0406_p/notes.rtf | 18 +
general/datasets/Eye_m2_0406_p/platform.rtf | 3 +
general/datasets/Eye_m2_0406_p/processing.rtf | 20 +
general/datasets/Eye_m2_0406_p/summary.rtf | 3 +
general/datasets/Eye_m2_0406_p/tissue.rtf | 7112 +++++
general/datasets/Eye_m2_0406_r/acknowledgment.rtf | 1 +
general/datasets/Eye_m2_0406_r/cases.rtf | 50 +
general/datasets/Eye_m2_0406_r/notes.rtf | 18 +
general/datasets/Eye_m2_0406_r/platform.rtf | 3 +
general/datasets/Eye_m2_0406_r/processing.rtf | 20 +
general/datasets/Eye_m2_0406_r/summary.rtf | 3 +
general/datasets/Eye_m2_0406_r/tissue.rtf | 7112 +++++
general/datasets/Eye_m2_0608_r/summary.rtf | 1 +
general/datasets/Eye_m2_0906_r/acknowledgment.rtf | 1 +
general/datasets/Eye_m2_0906_r/cases.rtf | 50 +
general/datasets/Eye_m2_0906_r/notes.rtf | 18 +
general/datasets/Eye_m2_0906_r/platform.rtf | 3 +
general/datasets/Eye_m2_0906_r/processing.rtf | 20 +
general/datasets/Eye_m2_0906_r/summary.rtf | 3 +
general/datasets/Eye_m2_0906_r/tissue.rtf | 7112 +++++
general/datasets/Eye_m2_0908_r/acknowledgment.rtf | 3 +
general/datasets/Eye_m2_0908_r/cases.rtf | 57 +
general/datasets/Eye_m2_0908_r/citation.rtf | 1 +
general/datasets/Eye_m2_0908_r/contributors.rtf | 1 +
.../datasets/Eye_m2_0908_r/experiment-design.rtf | 1 +
general/datasets/Eye_m2_0908_r/experiment-type.rtf | 1 +
general/datasets/Eye_m2_0908_r/notes.rtf | 1 +
general/datasets/Eye_m2_0908_r/platform.rtf | 11 +
general/datasets/Eye_m2_0908_r/processing.rtf | 3381 +++
general/datasets/Eye_m2_0908_r/summary.rtf | 12 +
general/datasets/Eye_m2_0908_r/tissue.rtf | 2058 ++
.../datasets/Eye_m2_0908_r_mt/acknowledgment.rtf | 3 +
general/datasets/Eye_m2_0908_r_mt/cases.rtf | 57 +
general/datasets/Eye_m2_0908_r_mt/citation.rtf | 1 +
general/datasets/Eye_m2_0908_r_mt/contributors.rtf | 1 +
.../Eye_m2_0908_r_mt/experiment-design.rtf | 1 +
general/datasets/Eye_m2_0908_r_mt/notes.rtf | 1 +
general/datasets/Eye_m2_0908_r_mt/platform.rtf | 11 +
general/datasets/Eye_m2_0908_r_mt/processing.rtf | 3381 +++
general/datasets/Eye_m2_0908_r_mt/summary.rtf | 12 +
general/datasets/Eye_m2_0908_r_mt/tissue.rtf | 2058 ++
.../datasets/Eye_m2_0908_r_nb/acknowledgment.rtf | 3 +
general/datasets/Eye_m2_0908_r_nb/cases.rtf | 57 +
general/datasets/Eye_m2_0908_r_nb/citation.rtf | 1 +
general/datasets/Eye_m2_0908_r_nb/contributors.rtf | 1 +
.../Eye_m2_0908_r_nb/experiment-design.rtf | 1 +
general/datasets/Eye_m2_0908_r_nb/notes.rtf | 1 +
general/datasets/Eye_m2_0908_r_nb/platform.rtf | 11 +
general/datasets/Eye_m2_0908_r_nb/processing.rtf | 3381 +++
general/datasets/Eye_m2_0908_r_nb/summary.rtf | 12 +
general/datasets/Eye_m2_0908_r_nb/tissue.rtf | 2058 ++
.../datasets/Eye_m2_0908_r_nd/acknowledgment.rtf | 3 +
general/datasets/Eye_m2_0908_r_nd/cases.rtf | 57 +
general/datasets/Eye_m2_0908_r_nd/citation.rtf | 1 +
general/datasets/Eye_m2_0908_r_nd/contributors.rtf | 1 +
.../Eye_m2_0908_r_nd/experiment-design.rtf | 1 +
general/datasets/Eye_m2_0908_r_nd/notes.rtf | 1 +
general/datasets/Eye_m2_0908_r_nd/platform.rtf | 11 +
general/datasets/Eye_m2_0908_r_nd/processing.rtf | 3381 +++
general/datasets/Eye_m2_0908_r_nd/summary.rtf | 12 +
general/datasets/Eye_m2_0908_r_nd/tissue.rtf | 2058 ++
.../datasets/Eye_m2_0908_r_wt/acknowledgment.rtf | 3 +
general/datasets/Eye_m2_0908_r_wt/cases.rtf | 57 +
general/datasets/Eye_m2_0908_r_wt/citation.rtf | 1 +
general/datasets/Eye_m2_0908_r_wt/contributors.rtf | 1 +
.../Eye_m2_0908_r_wt/experiment-design.rtf | 1 +
general/datasets/Eye_m2_0908_r_wt/notes.rtf | 1 +
general/datasets/Eye_m2_0908_r_wt/platform.rtf | 11 +
general/datasets/Eye_m2_0908_r_wt/processing.rtf | 3381 +++
general/datasets/Eye_m2_0908_r_wt/summary.rtf | 12 +
general/datasets/Eye_m2_0908_r_wt/tissue.rtf | 2058 ++
.../datasets/Eye_m2_0908_wtwt/acknowledgment.rtf | 3 +
general/datasets/Eye_m2_0908_wtwt/cases.rtf | 57 +
general/datasets/Eye_m2_0908_wtwt/citation.rtf | 1 +
general/datasets/Eye_m2_0908_wtwt/contributors.rtf | 1 +
.../Eye_m2_0908_wtwt/experiment-design.rtf | 1 +
general/datasets/Eye_m2_0908_wtwt/notes.rtf | 1 +
general/datasets/Eye_m2_0908_wtwt/platform.rtf | 11 +
general/datasets/Eye_m2_0908_wtwt/processing.rtf | 3381 +++
general/datasets/Eye_m2_0908_wtwt/summary.rtf | 12 +
general/datasets/Eye_m2_0908_wtwt/tissue.rtf | 2058 ++
general/datasets/Eye_m2_1105_m/acknowledgment.rtf | 1 +
general/datasets/Eye_m2_1105_m/cases.rtf | 51 +
general/datasets/Eye_m2_1105_m/notes.rtf | 7 +
general/datasets/Eye_m2_1105_m/platform.rtf | 3 +
general/datasets/Eye_m2_1105_m/processing.rtf | 11 +
general/datasets/Eye_m2_1105_m/summary.rtf | 3 +
general/datasets/Eye_m2_1105_m/tissue.rtf | 1554 ++
general/datasets/Eye_m2_1105_p/acknowledgment.rtf | 1 +
general/datasets/Eye_m2_1105_p/cases.rtf | 51 +
general/datasets/Eye_m2_1105_p/notes.rtf | 7 +
general/datasets/Eye_m2_1105_p/platform.rtf | 3 +
general/datasets/Eye_m2_1105_p/processing.rtf | 11 +
general/datasets/Eye_m2_1105_p/summary.rtf | 3 +
general/datasets/Eye_m2_1105_p/tissue.rtf | 1554 ++
general/datasets/Eye_m2_1105_r/acknowledgment.rtf | 1 +
general/datasets/Eye_m2_1105_r/cases.rtf | 51 +
general/datasets/Eye_m2_1105_r/notes.rtf | 7 +
general/datasets/Eye_m2_1105_r/platform.rtf | 3 +
general/datasets/Eye_m2_1105_r/processing.rtf | 11 +
general/datasets/Eye_m2_1105_r/summary.rtf | 3 +
general/datasets/Eye_m2_1105_r/tissue.rtf | 1554 ++
general/datasets/FGUCAS_BAdip0516/summary.rtf | 1 -
general/datasets/Fgucas_badip0516/summary.rtf | 1 +
general/datasets/Ft_2a_0605_rz/acknowledgment.rtf | 1 +
general/datasets/Ft_2a_0605_rz/cases.rtf | 7 +
general/datasets/Ft_2a_0605_rz/notes.rtf | 3 +
general/datasets/Ft_2a_0605_rz/platform.rtf | 1 +
general/datasets/Ft_2a_0605_rz/processing.rtf | 25 +
general/datasets/Ft_2a_0605_rz/summary.rtf | 16 +
general/datasets/Ft_2a_0605_rz/tissue.rtf | 542 +
general/datasets/Ft_2a_0805_m/acknowledgment.rtf | 1 +
general/datasets/Ft_2a_0805_m/cases.rtf | 7 +
general/datasets/Ft_2a_0805_m/notes.rtf | 3 +
general/datasets/Ft_2a_0805_m/platform.rtf | 1 +
general/datasets/Ft_2a_0805_m/processing.rtf | 25 +
general/datasets/Ft_2a_0805_m/summary.rtf | 16 +
general/datasets/Ft_2a_0805_m/tissue.rtf | 542 +
.../G2heioncretilm6_0911/acknowledgment.rtf | 13 +
general/datasets/G2heioncretilm6_0911/cases.rtf | 14 +
.../datasets/G2heioncretilm6_0911/contributors.rtf | 1 +
.../G2heioncretilm6_0911/experiment-design.rtf | 12 +
.../G2heioncretilm6_0911/experiment-type.rtf | 1 +
general/datasets/G2heioncretilm6_0911/notes.rtf | 1 +
general/datasets/G2heioncretilm6_0911/platform.rtf | 1 +
.../datasets/G2heioncretilm6_0911/processing.rtf | 2654 ++
general/datasets/G2heioncretilm6_0911/summary.rtf | 50 +
general/datasets/G2heioncretilm6_0911/tissue.rtf | 32 +
.../G2nei_ilm_retina_bxd_ri0410/acknowledgment.rtf | 13 +
.../datasets/G2nei_ilm_retina_bxd_ri0410/cases.rtf | 14 +
.../G2nei_ilm_retina_bxd_ri0410/contributors.rtf | 1 +
.../experiment-design.rtf | 12 +
.../experiment-type.rtf | 1 +
.../datasets/G2nei_ilm_retina_bxd_ri0410/notes.rtf | 1 +
.../G2nei_ilm_retina_bxd_ri0410/platform.rtf | 1 +
.../G2nei_ilm_retina_bxd_ri0410/processing.rtf | 2654 ++
.../G2nei_ilm_retina_bxd_ri0410/summary.rtf | 50 +
.../G2nei_ilm_retina_bxd_ri0410/tissue.rtf | 32 +
general/datasets/GITrMetPublish/summary.rtf | 1 -
general/datasets/GRNG_GSE23545HLT0613/summary.rtf | 15 -
.../GSE15745_GPL6104_Cer0510/experiment-design.rtf | 1 -
.../datasets/GSE15745_GPL6104_Cer0510/summary.rtf | 1 -
.../GSE15745_GPL6104_PFC0510/experiment-design.rtf | 1 -
.../datasets/GSE15745_GPL6104_PFC0510/summary.rtf | 1 -
.../GSE15745_GPL6104_Po0510/experiment-design.rtf | 1 -
.../datasets/GSE15745_GPL6104_Po0510/summary.rtf | 1 -
general/datasets/GSE23546HLT0613/summary.rtf | 15 -
general/datasets/GTEXv5_AdiVis_0915/cases.rtf | 5 -
.../GTEXv5_AdiVis_0915/experiment-design.rtf | 1 -
general/datasets/GTEXv5_AdiVis_0915/platform.rtf | 3 -
general/datasets/GTEXv5_AdiVis_0915/processing.rtf | 102 -
general/datasets/GTEXv5_AdiVis_0915/specifics.rtf | 1 -
general/datasets/GTEXv5_AdiVis_0915/summary.rtf | 3 -
general/datasets/GTEXv5_AdiVis_0915/tissue.rtf | 3 -
general/datasets/GTEXv5_AdipSub_0915/cases.rtf | 5 -
.../GTEXv5_AdipSub_0915/experiment-design.rtf | 1 -
general/datasets/GTEXv5_AdipSub_0915/platform.rtf | 3 -
.../datasets/GTEXv5_AdipSub_0915/processing.rtf | 102 -
general/datasets/GTEXv5_AdipSub_0915/specifics.rtf | 1 -
general/datasets/GTEXv5_AdipSub_0915/summary.rtf | 3 -
general/datasets/GTEXv5_AdipSub_0915/tissue.rtf | 3 -
general/datasets/GTEXv5_AdrGla_0915/cases.rtf | 5 -
.../GTEXv5_AdrGla_0915/experiment-design.rtf | 1 -
general/datasets/GTEXv5_AdrGla_0915/platform.rtf | 3 -
general/datasets/GTEXv5_AdrGla_0915/processing.rtf | 102 -
general/datasets/GTEXv5_AdrGla_0915/specifics.rtf | 10 -
general/datasets/GTEXv5_AdrGla_0915/summary.rtf | 3 -
general/datasets/GTEXv5_AdrGla_0915/tissue.rtf | 3 -
general/datasets/GTEXv5_Amy_0915/cases.rtf | 5 -
.../datasets/GTEXv5_Amy_0915/experiment-design.rtf | 1 -
general/datasets/GTEXv5_Amy_0915/platform.rtf | 3 -
general/datasets/GTEXv5_Amy_0915/processing.rtf | 102 -
general/datasets/GTEXv5_Amy_0915/specifics.rtf | 10 -
general/datasets/GTEXv5_Amy_0915/summary.rtf | 3 -
general/datasets/GTEXv5_Amy_0915/tissue.rtf | 3 -
general/datasets/GTEXv5_AntCtx_0915/cases.rtf | 5 -
.../GTEXv5_AntCtx_0915/experiment-design.rtf | 1 -
general/datasets/GTEXv5_AntCtx_0915/platform.rtf | 3 -
general/datasets/GTEXv5_AntCtx_0915/processing.rtf | 102 -
general/datasets/GTEXv5_AntCtx_0915/specifics.rtf | 10 -
general/datasets/GTEXv5_AntCtx_0915/summary.rtf | 3 -
general/datasets/GTEXv5_AntCtx_0915/tissue.rtf | 3 -
general/datasets/GTEXv5_ArtAor_0915/cases.rtf | 5 -
.../GTEXv5_ArtAor_0915/experiment-design.rtf | 1 -
general/datasets/GTEXv5_ArtAor_0915/platform.rtf | 3 -
general/datasets/GTEXv5_ArtAor_0915/processing.rtf | 102 -
general/datasets/GTEXv5_ArtAor_0915/specifics.rtf | 10 -
general/datasets/GTEXv5_ArtAor_0915/summary.rtf | 3 -
general/datasets/GTEXv5_ArtAor_0915/tissue.rtf | 3 -
general/datasets/GTEXv5_ArtCor_0915/cases.rtf | 5 -
.../GTEXv5_ArtCor_0915/experiment-design.rtf | 1 -
general/datasets/GTEXv5_ArtCor_0915/platform.rtf | 3 -
general/datasets/GTEXv5_ArtCor_0915/processing.rtf | 102 -
general/datasets/GTEXv5_ArtCor_0915/specifics.rtf | 1 -
general/datasets/GTEXv5_ArtCor_0915/summary.rtf | 3 -
general/datasets/GTEXv5_ArtCor_0915/tissue.rtf | 3 -
general/datasets/GTEXv5_BM_0915/cases.rtf | 5 -
.../datasets/GTEXv5_BM_0915/experiment-design.rtf | 1 -
general/datasets/GTEXv5_BM_0915/platform.rtf | 3 -
general/datasets/GTEXv5_BM_0915/processing.rtf | 102 -
general/datasets/GTEXv5_BM_0915/specifics.rtf | 10 -
general/datasets/GTEXv5_BM_0915/summary.rtf | 3 -
general/datasets/GTEXv5_BM_0915/tissue.rtf | 3 -
general/datasets/GTEXv5_BrCe_0915/cases.rtf | 5 -
.../GTEXv5_BrCe_0915/experiment-design.rtf | 1 -
general/datasets/GTEXv5_BrCe_0915/platform.rtf | 3 -
general/datasets/GTEXv5_BrCe_0915/processing.rtf | 102 -
general/datasets/GTEXv5_BrCe_0915/specifics.rtf | 10 -
general/datasets/GTEXv5_BrCe_0915/summary.rtf | 3 -
general/datasets/GTEXv5_BrCe_0915/tissue.rtf | 3 -
general/datasets/GTEXv5_BrMa_0915/cases.rtf | 5 -
.../GTEXv5_BrMa_0915/experiment-design.rtf | 1 -
general/datasets/GTEXv5_BrMa_0915/platform.rtf | 3 -
general/datasets/GTEXv5_BrMa_0915/processing.rtf | 102 -
general/datasets/GTEXv5_BrMa_0915/specifics.rtf | 10 -
general/datasets/GTEXv5_BrMa_0915/summary.rtf | 3 -
general/datasets/GTEXv5_BrMa_0915/tissue.rtf | 3 -
general/datasets/GTEXv5_CTF_0915/cases.rtf | 5 -
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.../datasets/Heioncvscretilm6_0911/processing.rtf | 2654 ++
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.../Hipp_illumina_rank_1006/experiment-design.rtf | 2123 ++
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.../experiment-design.rtf | 2123 ++
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.../Hqfneoc_0208_rankinv/experiment-design.rtf | 937 +
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.../Hqfneoc_1210_rankinv/experiment-design.rtf | 937 +
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.../Hqfneoc_1210v2_rankinv/experiment-design.rtf | 937 +
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.../datasets/Illum_lxs_hipp_quant0807/cases.rtf | 2140 ++
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.../Illum_lxs_hipp_quant0807/experiment-design.rtf | 1 +
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.../datasets/Illum_lxs_hipp_quant_nb0807/cases.rtf | 2140 ++
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general/datasets/Illum_lxs_hipp_rsn0807/cases.rtf | 2140 ++
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general/datasets/Illum_lxs_hipp_rsn0807/tissue.rtf | 9 +
.../Illum_lxs_hipp_rsn_nb0807/acknowledgment.rtf | 3 +
.../datasets/Illum_lxs_hipp_rsn_nb0807/cases.rtf | 2140 ++
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general/datasets/Inia_adrenal_rma_0612/cases.rtf | 771 +
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.../datasets/Inia_adrenal_rma_ex_0612/cases.rtf | 771 +
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general/datasets/Inia_adrenal_rma_f_0612/cases.rtf | 771 +
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general/datasets/Inia_adrenal_rma_m_0612/cases.rtf | 771 +
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.../Inia_uthsc_mid_affymta1_apr17/cases.rtf | 857 +
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.../Inia_uthsc_mid_affymta1_ex_may17/cases.rtf | 857 +
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general/datasets/Lvf2_m_0704_r/summary.rtf | 3 +
general/datasets/Lvf2_m_0704_r/tissue.rtf | 3 +
general/datasets/Lxsgeno/summary.rtf | 21 +
general/datasets/Lxspublish/acknowledgment.rtf | 1 +
general/datasets/Lxspublish/cases.rtf | 7 +
general/datasets/Lxspublish/summary.rtf | 1 +
general/datasets/Ma_m2_0706_p/acknowledgment.rtf | 24 +
general/datasets/Ma_m2_0706_p/cases.rtf | 44 +
.../datasets/Ma_m2_0706_p/experiment-design.rtf | 1864 ++
general/datasets/Ma_m2_0706_p/notes.rtf | 3 +
general/datasets/Ma_m2_0706_p/platform.rtf | 3 +
general/datasets/Ma_m2_0706_p/processing.rtf | 15 +
general/datasets/Ma_m2_0706_p/summary.rtf | 1 +
general/datasets/Ma_m2_0706_p/tissue.rtf | 3 +
general/datasets/Ma_m2_0706_r/acknowledgment.rtf | 24 +
general/datasets/Ma_m2_0706_r/cases.rtf | 44 +
.../datasets/Ma_m2_0706_r/experiment-design.rtf | 1864 ++
general/datasets/Ma_m2_0706_r/notes.rtf | 3 +
general/datasets/Ma_m2_0706_r/platform.rtf | 3 +
general/datasets/Ma_m2_0706_r/processing.rtf | 15 +
general/datasets/Ma_m2_0706_r/summary.rtf | 1 +
general/datasets/Ma_m2_0706_r/tissue.rtf | 3 +
general/datasets/Ma_m2_0806_p/acknowledgment.rtf | 24 +
general/datasets/Ma_m2_0806_p/cases.rtf | 44 +
.../datasets/Ma_m2_0806_p/experiment-design.rtf | 1864 ++
general/datasets/Ma_m2_0806_p/notes.rtf | 3 +
general/datasets/Ma_m2_0806_p/platform.rtf | 3 +
general/datasets/Ma_m2_0806_p/processing.rtf | 15 +
general/datasets/Ma_m2_0806_p/summary.rtf | 1 +
general/datasets/Ma_m2_0806_p/tissue.rtf | 3 +
general/datasets/Ma_m2_0806_r/acknowledgment.rtf | 24 +
general/datasets/Ma_m2_0806_r/cases.rtf | 44 +
.../datasets/Ma_m2_0806_r/experiment-design.rtf | 1864 ++
general/datasets/Ma_m2_0806_r/notes.rtf | 3 +
general/datasets/Ma_m2_0806_r/platform.rtf | 3 +
general/datasets/Ma_m2_0806_r/processing.rtf | 15 +
general/datasets/Ma_m2_0806_r/summary.rtf | 1 +
general/datasets/Ma_m2_0806_r/tissue.rtf | 3 +
general/datasets/Ma_m2f_0706_r/acknowledgment.rtf | 24 +
general/datasets/Ma_m2f_0706_r/cases.rtf | 44 +
.../datasets/Ma_m2f_0706_r/experiment-design.rtf | 1864 ++
general/datasets/Ma_m2f_0706_r/notes.rtf | 3 +
general/datasets/Ma_m2f_0706_r/platform.rtf | 3 +
general/datasets/Ma_m2f_0706_r/processing.rtf | 15 +
general/datasets/Ma_m2f_0706_r/summary.rtf | 1 +
general/datasets/Ma_m2f_0706_r/tissue.rtf | 3 +
general/datasets/Ma_m2m_0706_r/acknowledgment.rtf | 24 +
general/datasets/Ma_m2m_0706_r/cases.rtf | 44 +
.../datasets/Ma_m2m_0706_r/experiment-design.rtf | 1864 ++
general/datasets/Ma_m2m_0706_r/notes.rtf | 3 +
general/datasets/Ma_m2m_0706_r/platform.rtf | 3 +
general/datasets/Ma_m2m_0706_r/processing.rtf | 15 +
general/datasets/Ma_m2m_0706_r/summary.rtf | 1 +
general/datasets/Ma_m2m_0706_r/tissue.rtf | 3 +
general/datasets/Ma_m_0704_m/acknowledgment.rtf | 1 +
general/datasets/Ma_m_0704_m/cases.rtf | 4 +
general/datasets/Ma_m_0704_m/notes.rtf | 1 +
general/datasets/Ma_m_0704_m/platform.rtf | 643 +
general/datasets/Ma_m_0704_m/processing.rtf | 15 +
general/datasets/Ma_m_0704_m/summary.rtf | 1 +
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general/datasets/Ma_m_0704_r/notes.rtf | 1 +
general/datasets/Ma_m_0704_r/platform.rtf | 643 +
general/datasets/Ma_m_0704_r/processing.rtf | 15 +
general/datasets/Ma_m_0704_r/summary.rtf | 1 +
general/datasets/Ma_m_0704_r/tissue.rtf | 1 +
general/datasets/Mdppublish/citation.rtf | 17 +
general/datasets/Mdppublish/summary.rtf | 17 +
.../experiment-design.rtf | 3 -
.../processing.rtf | 9 -
.../specifics.rtf | 2770 --
.../tissue.rtf | 3 -
.../experiment-design.rtf | 3 -
.../processing.rtf | 9 -
.../specifics.rtf | 1758 --
.../tissue.rtf | 3 -
.../experiment-design.rtf | 3 -
.../processing.rtf | 9 -
.../specifics.rtf | 1 -
.../tissue.rtf | 3 -
.../experiment-design.rtf | 3 -
.../processing.rtf | 9 -
.../specifics.rtf | 1907 --
.../tissue.rtf | 3 -
.../experiment-design.rtf | 3 -
.../processing.rtf | 9 -
.../specifics.rtf | 2302 --
.../tissue.rtf | 3 -
.../NIAAA_BXD_Hip_CMS_DID_RNAseq1020/cases.rtf | 4848 ----
.../experiment-design.rtf | 7 -
.../processing.rtf | 9 -
.../NIAAA_BXD_Hip_CMS_DID_RNAseq1020/specifics.rtf | 1 -
.../NIAAA_BXD_Hip_CMS_DID_RNAseq1020/tissue.rtf | 7 -
.../NIAAA_BXD_Hip_CMS_RNAseq1020/cases.rtf | 4848 ----
.../experiment-design.rtf | 7 -
.../NIAAA_BXD_Hip_CMS_RNAseq1020/processing.rtf | 9 -
.../NIAAA_BXD_Hip_CMS_RNAseq1020/specifics.rtf | 1 -
.../NIAAA_BXD_Hip_CMS_RNAseq1020/tissue.rtf | 7 -
.../NIAAA_BXD_Hip_CTL_RNAseq1020/cases.rtf | 4848 ----
.../experiment-design.rtf | 7 -
.../NIAAA_BXD_Hip_CTL_RNAseq1020/processing.rtf | 9 -
.../NIAAA_BXD_Hip_CTL_RNAseq1020/specifics.rtf | 1 -
.../NIAAA_BXD_Hip_CTL_RNAseq1020/tissue.rtf | 7 -
.../NIAAA_BXD_Hip_DID_RNAseq1020/cases.rtf | 4848 ----
.../experiment-design.rtf | 7 -
.../NIAAA_BXD_Hip_DID_RNAseq1020/processing.rtf | 9 -
.../NIAAA_BXD_Hip_DID_RNAseq1020/specifics.rtf | 1 -
.../NIAAA_BXD_Hip_DID_RNAseq1020/tissue.rtf | 7 -
.../NIA_AgBXD_Liv_CDHFD_rna_seq_0818/specifics.rtf | 1 -
.../NIA_AgBXD_Liv_CDHFD_rna_seq_0818/summary.rtf | 1 -
.../NIA_AgBXD_Liv_CD_rna_seq_0818/specifics.rtf | 1 -
.../NIA_AgBXD_Liv_CD_rna_seq_0818/summary.rtf | 1 -
.../NIA_AgBXD_Liv_HFD_rna_seq_0818/specifics.rtf | 1 -
.../NIA_AgBXD_Liv_HFD_rna_seq_0818/summary.rtf | 1 -
.../datasets/Nci_agil_mam_tum_rma_0409/summary.rtf | 1 +
.../Nci_mam_tum_rma_0409/experiment-type.rtf | 1 +
general/datasets/Nci_mam_tum_rma_0409/summary.rtf | 1 +
.../Ncsu_droswb_lc_rma_0111/acknowledgment.rtf | 1 +
general/datasets/Ncsu_droswb_lc_rma_0111/cases.rtf | 3 +
.../datasets/Ncsu_droswb_lc_rma_0111/citation.rtf | 1 +
.../Ncsu_droswb_lc_rma_0111/contributors.rtf | 3 +
.../Ncsu_droswb_lc_rma_0111/experiment-design.rtf | 5 +
.../Ncsu_droswb_lc_rma_0111/experiment-type.rtf | 1 +
general/datasets/Ncsu_droswb_lc_rma_0111/notes.rtf | 3 +
.../datasets/Ncsu_droswb_lc_rma_0111/platform.rtf | 3 +
.../Ncsu_droswb_lc_rma_0111/processing.rtf | 3 +
.../datasets/Ncsu_droswb_lc_rma_0111/summary.rtf | 2 +
.../datasets/Ncsu_droswb_lc_rma_0111/tissue.rtf | 1 +
.../experiment-design.rtf | 3 +
.../processing.rtf | 9 +
.../specifics.rtf | 2770 ++
.../tissue.rtf | 3 +
.../experiment-design.rtf | 3 +
.../processing.rtf | 9 +
.../specifics.rtf | 1758 ++
.../tissue.rtf | 3 +
.../experiment-design.rtf | 3 +
.../processing.rtf | 9 +
.../specifics.rtf | 1 +
.../tissue.rtf | 3 +
.../experiment-design.rtf | 3 +
.../processing.rtf | 9 +
.../specifics.rtf | 1907 ++
.../tissue.rtf | 3 +
.../experiment-design.rtf | 3 +
.../processing.rtf | 9 +
.../specifics.rtf | 2302 ++
.../tissue.rtf | 3 +
.../Nia_agbxd_liv_cd_rna_seq_0818/specifics.rtf | 1 +
.../Nia_agbxd_liv_cd_rna_seq_0818/summary.rtf | 1 +
.../Nia_agbxd_liv_cdhfd_rna_seq_0818/specifics.rtf | 1 +
.../Nia_agbxd_liv_cdhfd_rna_seq_0818/summary.rtf | 1 +
.../Nia_agbxd_liv_hfd_rna_seq_0818/specifics.rtf | 1 +
.../Nia_agbxd_liv_hfd_rna_seq_0818/summary.rtf | 1 +
.../Niaaa_bxd_hip_cms_did_rnaseq1020/cases.rtf | 4848 ++++
.../experiment-design.rtf | 7 +
.../processing.rtf | 9 +
.../Niaaa_bxd_hip_cms_did_rnaseq1020/specifics.rtf | 1 +
.../Niaaa_bxd_hip_cms_did_rnaseq1020/tissue.rtf | 7 +
.../Niaaa_bxd_hip_cms_rnaseq1020/cases.rtf | 4848 ++++
.../experiment-design.rtf | 7 +
.../Niaaa_bxd_hip_cms_rnaseq1020/processing.rtf | 9 +
.../Niaaa_bxd_hip_cms_rnaseq1020/specifics.rtf | 1 +
.../Niaaa_bxd_hip_cms_rnaseq1020/tissue.rtf | 7 +
.../Niaaa_bxd_hip_ctl_rnaseq1020/cases.rtf | 4848 ++++
.../experiment-design.rtf | 7 +
.../Niaaa_bxd_hip_ctl_rnaseq1020/processing.rtf | 9 +
.../Niaaa_bxd_hip_ctl_rnaseq1020/specifics.rtf | 1 +
.../Niaaa_bxd_hip_ctl_rnaseq1020/tissue.rtf | 7 +
.../Niaaa_bxd_hip_did_rnaseq1020/cases.rtf | 4848 ++++
.../experiment-design.rtf | 7 +
.../Niaaa_bxd_hip_did_rnaseq1020/processing.rtf | 9 +
.../Niaaa_bxd_hip_did_rnaseq1020/specifics.rtf | 1 +
.../Niaaa_bxd_hip_did_rnaseq1020/tissue.rtf | 7 +
general/datasets/None/summary.rtf | 40 +
.../datasets/OHSU_HS-CC_ILMStr_0211/summary.rtf | 2 +
.../datasets/OHSU_HS_CC_ILMStr_0211/summary.rtf | 2 -
.../ONCRetExMoGene2_0413/acknowledgment.rtf | 1 -
general/datasets/ONCRetExMoGene2_0413/cases.rtf | 1728 --
general/datasets/ONCRetExMoGene2_0413/platform.rtf | 1 -
.../datasets/ONCRetExMoGene2_0413/processing.rtf | 1 -
general/datasets/ONCRetExMoGene2_0413/summary.rtf | 1 -
general/datasets/ONCRetExMoGene2_0413/tissue.rtf | 1 -
.../datasets/ONCRetMoGene2_0413/acknowledgment.rtf | 1 -
general/datasets/ONCRetMoGene2_0413/cases.rtf | 1728 --
general/datasets/ONCRetMoGene2_0413/platform.rtf | 1 -
general/datasets/ONCRetMoGene2_0413/processing.rtf | 1 -
general/datasets/ONCRetMoGene2_0413/summary.rtf | 1 -
general/datasets/ONCRetMoGene2_0413/tissue.rtf | 1 -
.../datasets/Ohsu_hs_cc_ilmstr_0211/summary.rtf | 2 +
.../Oncretexmogene2_0413/acknowledgment.rtf | 1 +
general/datasets/Oncretexmogene2_0413/cases.rtf | 1728 ++
general/datasets/Oncretexmogene2_0413/citation.rtf | 3 +
.../datasets/Oncretexmogene2_0413/contributors.rtf | 1 +
.../Oncretexmogene2_0413/experiment-type.rtf | 3 +
general/datasets/Oncretexmogene2_0413/platform.rtf | 1 +
.../datasets/Oncretexmogene2_0413/processing.rtf | 1 +
general/datasets/Oncretexmogene2_0413/summary.rtf | 1 +
general/datasets/Oncretexmogene2_0413/tissue.rtf | 1 +
.../datasets/Oncretilm6_0412/acknowledgment.rtf | 13 +
general/datasets/Oncretilm6_0412/cases.rtf | 14 +
general/datasets/Oncretilm6_0412/contributors.rtf | 1 +
.../datasets/Oncretilm6_0412/experiment-design.rtf | 12 +
.../datasets/Oncretilm6_0412/experiment-type.rtf | 1 +
general/datasets/Oncretilm6_0412/notes.rtf | 1 +
general/datasets/Oncretilm6_0412/platform.rtf | 1 +
general/datasets/Oncretilm6_0412/processing.rtf | 2654 ++
general/datasets/Oncretilm6_0412/summary.rtf | 50 +
general/datasets/Oncretilm6_0412/tissue.rtf | 32 +
.../datasets/Oncretmogene2_0413/acknowledgment.rtf | 1 +
general/datasets/Oncretmogene2_0413/cases.rtf | 1728 ++
general/datasets/Oncretmogene2_0413/citation.rtf | 3 +
.../datasets/Oncretmogene2_0413/contributors.rtf | 1 +
.../Oncretmogene2_0413/experiment-type.rtf | 3 +
general/datasets/Oncretmogene2_0413/platform.rtf | 1 +
general/datasets/Oncretmogene2_0413/processing.rtf | 1 +
general/datasets/Oncretmogene2_0413/summary.rtf | 1 +
general/datasets/Oncretmogene2_0413/tissue.rtf | 1 +
general/datasets/Oxukhs_ilmhipp_ri0510/cases.rtf | 1 +
.../datasets/Oxukhs_ilmhipp_ri0510/citation.rtf | 5 +
.../Oxukhs_ilmhipp_ri0510/experiment-type.rtf | 1 +
.../datasets/Oxukhs_ilmhipp_ri0510/platform.rtf | 1 +
general/datasets/Oxukhs_ilmhipp_ri0510/summary.rtf | 1 +
general/datasets/Oxukhs_ilmliver_ri0510/cases.rtf | 1 +
.../datasets/Oxukhs_ilmliver_ri0510/citation.rtf | 5 +
.../Oxukhs_ilmliver_ri0510/experiment-type.rtf | 1 +
.../datasets/Oxukhs_ilmliver_ri0510/platform.rtf | 1 +
.../datasets/Oxukhs_ilmliver_ri0510/summary.rtf | 1 +
general/datasets/Oxukhs_ilmlung_ri0510/cases.rtf | 1 +
.../datasets/Oxukhs_ilmlung_ri0510/citation.rtf | 5 +
.../datasets/Oxukhs_ilmlung_ri0510/platform.rtf | 1 +
general/datasets/Oxukhs_ilmlung_ri0510/summary.rtf | 1 +
.../PGenRatBrn_rna_0520/acknowledgment.rtf | 1 -
general/datasets/PGenRatBrn_rna_0520/cases.rtf | 1 -
.../PGenRatBrn_rna_0520/experiment-design.rtf | 1 -
general/datasets/PGenRatBrn_rna_0520/platform.rtf | 1 -
.../datasets/PGenRatBrn_rna_0520/processing.rtf | 3 -
general/datasets/PGenRatBrn_rna_0520/specifics.rtf | 1 -
general/datasets/PGenRatBrn_rna_0520/summary.rtf | 1 -
general/datasets/PGenRatBrn_rna_0520/tissue.rtf | 1 -
.../PGenRatBrn_rna_z_0520/acknowledgment.rtf | 1 -
general/datasets/PGenRatBrn_rna_z_0520/cases.rtf | 1 -
.../PGenRatBrn_rna_z_0520/experiment-design.rtf | 1 -
.../datasets/PGenRatBrn_rna_z_0520/platform.rtf | 1 -
.../datasets/PGenRatBrn_rna_z_0520/processing.rtf | 3 -
.../datasets/PGenRatBrn_rna_z_0520/specifics.rtf | 1 -
general/datasets/PGenRatBrn_rna_z_0520/summary.rtf | 1 -
general/datasets/PGenRatBrn_rna_z_0520/tissue.rtf | 1 -
.../PGenRatLiv_rna_0520/acknowledgment.rtf | 1 -
general/datasets/PGenRatLiv_rna_0520/cases.rtf | 1 -
.../PGenRatLiv_rna_0520/experiment-design.rtf | 1 -
general/datasets/PGenRatLiv_rna_0520/platform.rtf | 1 -
.../datasets/PGenRatLiv_rna_0520/processing.rtf | 3 -
general/datasets/PGenRatLiv_rna_0520/specifics.rtf | 1 -
general/datasets/PGenRatLiv_rna_0520/summary.rtf | 1 -
general/datasets/PGenRatLiv_rna_0520/tissue.rtf | 1 -
.../PGenRatLiv_rna_z_0520/acknowledgment.rtf | 1 -
general/datasets/PGenRatLiv_rna_z_0520/cases.rtf | 1 -
.../PGenRatLiv_rna_z_0520/experiment-design.rtf | 1 -
.../datasets/PGenRatLiv_rna_z_0520/platform.rtf | 1 -
.../datasets/PGenRatLiv_rna_z_0520/processing.rtf | 3 -
.../datasets/PGenRatLiv_rna_z_0520/specifics.rtf | 1 -
general/datasets/PGenRatLiv_rna_z_0520/summary.rtf | 1 -
general/datasets/PGenRatLiv_rna_z_0520/tissue.rtf | 1 -
general/datasets/PSU_B6D2F2_0812/platform.rtf | 1 -
general/datasets/PSU_B6D2F2_0812/summary.rtf | 1 -
general/datasets/PSU_B6D2F2_M0812/platform.rtf | 1 -
general/datasets/PSU_B6D2F2_M0812/summary.rtf | 1 -
.../Pgenratbrn_rna_0520/acknowledgment.rtf | 1 +
general/datasets/Pgenratbrn_rna_0520/cases.rtf | 1 +
general/datasets/Pgenratbrn_rna_0520/citation.rtf | 1 +
.../datasets/Pgenratbrn_rna_0520/contributors.rtf | 23 +
.../Pgenratbrn_rna_0520/experiment-design.rtf | 1 +
general/datasets/Pgenratbrn_rna_0520/platform.rtf | 1 +
.../datasets/Pgenratbrn_rna_0520/processing.rtf | 3 +
general/datasets/Pgenratbrn_rna_0520/specifics.rtf | 1 +
general/datasets/Pgenratbrn_rna_0520/summary.rtf | 1 +
general/datasets/Pgenratbrn_rna_0520/tissue.rtf | 1 +
.../Pgenratbrn_rna_z_0520/acknowledgment.rtf | 1 +
general/datasets/Pgenratbrn_rna_z_0520/cases.rtf | 1 +
.../datasets/Pgenratbrn_rna_z_0520/citation.rtf | 1 +
.../Pgenratbrn_rna_z_0520/contributors.rtf | 23 +
.../Pgenratbrn_rna_z_0520/experiment-design.rtf | 1 +
.../datasets/Pgenratbrn_rna_z_0520/platform.rtf | 1 +
.../datasets/Pgenratbrn_rna_z_0520/processing.rtf | 3 +
.../datasets/Pgenratbrn_rna_z_0520/specifics.rtf | 1 +
general/datasets/Pgenratbrn_rna_z_0520/summary.rtf | 1 +
general/datasets/Pgenratbrn_rna_z_0520/tissue.rtf | 1 +
.../Pgenratliv_rna_0520/acknowledgment.rtf | 1 +
general/datasets/Pgenratliv_rna_0520/cases.rtf | 1 +
general/datasets/Pgenratliv_rna_0520/citation.rtf | 1 +
.../datasets/Pgenratliv_rna_0520/contributors.rtf | 23 +
.../Pgenratliv_rna_0520/experiment-design.rtf | 1 +
general/datasets/Pgenratliv_rna_0520/platform.rtf | 1 +
.../datasets/Pgenratliv_rna_0520/processing.rtf | 3 +
general/datasets/Pgenratliv_rna_0520/specifics.rtf | 1 +
general/datasets/Pgenratliv_rna_0520/summary.rtf | 1 +
general/datasets/Pgenratliv_rna_0520/tissue.rtf | 1 +
.../Pgenratliv_rna_z_0520/acknowledgment.rtf | 1 +
general/datasets/Pgenratliv_rna_z_0520/cases.rtf | 1 +
.../datasets/Pgenratliv_rna_z_0520/citation.rtf | 1 +
.../Pgenratliv_rna_z_0520/contributors.rtf | 23 +
.../Pgenratliv_rna_z_0520/experiment-design.rtf | 1 +
.../datasets/Pgenratliv_rna_z_0520/platform.rtf | 1 +
.../datasets/Pgenratliv_rna_z_0520/processing.rtf | 3 +
.../datasets/Pgenratliv_rna_z_0520/specifics.rtf | 1 +
general/datasets/Pgenratliv_rna_z_0520/summary.rtf | 1 +
general/datasets/Pgenratliv_rna_z_0520/tissue.rtf | 1 +
general/datasets/PoplarPublish/acknowledgment.rtf | 1 -
general/datasets/PoplarPublish/platform.rtf | 1 -
general/datasets/PoplarPublish/processing.rtf | 1 -
general/datasets/PoplarPublish/summary.rtf | 8 -
general/datasets/Poplarpublish/acknowledgment.rtf | 1 +
general/datasets/Poplarpublish/citation.rtf | 3 +
general/datasets/Poplarpublish/platform.rtf | 1 +
general/datasets/Poplarpublish/processing.rtf | 1 +
general/datasets/Poplarpublish/summary.rtf | 8 +
.../datasets/Psu_b6d2f2_0812/experiment-type.rtf | 1 +
general/datasets/Psu_b6d2f2_0812/platform.rtf | 1 +
general/datasets/Psu_b6d2f2_0812/summary.rtf | 1 +
general/datasets/Psu_b6d2f2_m0812/platform.rtf | 1 +
general/datasets/Psu_b6d2f2_m0812/summary.rtf | 1 +
.../RTI_RCMRC_BXDFecMet0814/acknowledgment.rtf | 7 -
general/datasets/RTI_RCMRC_BXDFecMet0814/cases.rtf | 3 -
.../RTI_RCMRC_BXDFecMet0814/experiment-design.rtf | 17 -
general/datasets/RTI_RCMRC_BXDFecMet0814/notes.rtf | 5 -
.../datasets/RTI_RCMRC_BXDFecMet0814/platform.rtf | 1 -
.../datasets/RTI_RCMRC_BXDFecMet0814/summary.rtf | 11 -
.../datasets/RTI_RCMRC_BXDFecMet0814/tissue.rtf | 1 -
.../RTI_RCMRC_BXDFecMetHF0814/acknowledgment.rtf | 7 -
.../datasets/RTI_RCMRC_BXDFecMetHF0814/cases.rtf | 3 -
.../experiment-design.rtf | 17 -
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.../datasets/Ut_vgx_hel1014/experiment-design.rtf | 3 +
general/datasets/Ut_vgx_hel1014/platform.rtf | 1 +
general/datasets/Ut_vgx_hel1014/processing.rtf | 1 +
general/datasets/Ut_vgx_hel1014/summary.rtf | 1 +
general/datasets/Ut_vgx_hel1014/tissue.rtf | 9 +
general/datasets/Uthsc_1107_rankinv/summary.rtf | 1 +
general/datasets/Uthsc_b6d2ri_h_0912/summary.rtf | 1 +
.../experiment-design.rtf | 1 +
.../processing.rtf | 9 +
.../specifics.rtf | 4332 +++
.../tissue.rtf | 1 +
general/datasets/Uthsc_bxd_agehipp0515/cases.rtf | 1258 +
.../Uthsc_bxd_agehipp0515/experiment-design.rtf | 3 +
.../datasets/Uthsc_bxd_agehipp0515/processing.rtf | 3 +
.../datasets/Uthsc_bxd_agehipp0515/specifics.rtf | 1 +
general/datasets/Uthsc_bxd_agehipp0515/tissue.rtf | 3 +
.../experiment-design.rtf | 1 +
.../processing.rtf | 9 +
.../specifics.rtf | 1 +
.../tissue.rtf | 1 +
general/datasets/Uthsc_bxd_h_0912/cases.rtf | 1258 +
.../Uthsc_bxd_h_0912/experiment-design.rtf | 3 +
general/datasets/Uthsc_bxd_h_0912/processing.rtf | 3 +
general/datasets/Uthsc_bxd_h_0912/specifics.rtf | 1 +
general/datasets/Uthsc_bxd_h_0912/tissue.rtf | 3 +
general/datasets/Uthsc_bxd_harev3_0912/cases.rtf | 1258 +
.../Uthsc_bxd_harev3_0912/experiment-design.rtf | 3 +
.../datasets/Uthsc_bxd_harev3_0912/processing.rtf | 3 +
general/datasets/Uthsc_bxd_harev3_0912/tissue.rtf | 3 +
general/datasets/Uthsc_bxd_harv_liv_0118/cases.rtf | 1371 +
.../Uthsc_bxd_harv_liv_0118/processing.rtf | 26883 +++++++++++++++++++
.../datasets/Uthsc_bxd_harv_liv_0118/specifics.rtf | 1 +
.../datasets/Uthsc_bxd_harv_liv_0118/summary.rtf | 1 +
general/datasets/Uthsc_bxd_harv_liv_1019/cases.rtf | 1371 +
.../Uthsc_bxd_harv_liv_1019/processing.rtf | 26883 +++++++++++++++++++
.../datasets/Uthsc_bxd_harv_liv_1019/specifics.rtf | 1 +
.../datasets/Uthsc_bxd_harv_liv_1019/summary.rtf | 1 +
.../Uthsc_bxd_harv_liv_tpm_log2_1019/specifics.rtf | 1 +
.../Uthsc_bxd_harv_liv_tpm_log2_1019/summary.rtf | 1 +
.../Uthsc_bxd_hip_mirnaseq0214/specifics.rtf | 1 +
.../Uthsc_bxd_hip_mirnaseq0214/summary.rtf | 1 +
.../Uthsc_bxd_hip_postd7ctrlbs_1121/specifics.rtf | 1 +
.../Uthsc_bxd_hip_postd7ctrlbs_1121/summary.rtf | 1 +
.../Uthsc_bxd_hip_postd7etohbs_1121/specifics.rtf | 1 +
.../Uthsc_bxd_hip_postd7etohbs_1121/summary.rtf | 1 +
general/datasets/Uthsc_bxd_liv_0818/specifics.rtf | 1 +
general/datasets/Uthsc_bxd_liv_0818/summary.rtf | 1 +
general/datasets/Uthsc_bxd_liv_0917/specifics.rtf | 1 +
general/datasets/Uthsc_bxd_liv_0917/summary.rtf | 1 +
.../Uthsc_bxd_livcdnam_1119/experiment-design.rtf | 1 +
.../datasets/Uthsc_bxd_livcdnam_1119/platform.rtf | 1 +
.../Uthsc_bxd_livcdnam_1119/processing.rtf | 1 +
.../datasets/Uthsc_bxd_livcdnam_1119/specifics.rtf | 1 +
.../datasets/Uthsc_bxd_livcdnam_1119/summary.rtf | 1 +
.../Uthsc_bxd_livdnam_1119/experiment-design.rtf | 1 +
.../datasets/Uthsc_bxd_livdnam_1119/platform.rtf | 1 +
.../datasets/Uthsc_bxd_livdnam_1119/processing.rtf | 1 +
.../datasets/Uthsc_bxd_livdnam_1119/specifics.rtf | 1 +
.../datasets/Uthsc_bxd_livdnam_1119/summary.rtf | 1 +
.../Uthsc_bxd_livhfdnam_1119/experiment-design.rtf | 1 +
.../datasets/Uthsc_bxd_livhfdnam_1119/platform.rtf | 1 +
.../Uthsc_bxd_livhfdnam_1119/processing.rtf | 1 +
.../Uthsc_bxd_livhfdnam_1119/specifics.rtf | 1 +
.../datasets/Uthsc_bxd_livhfdnam_1119/summary.rtf | 1 +
.../Uthsc_bxd_mamgland_ca_0322/specifics.rtf | 1 +
.../Uthsc_bxd_mamgland_ca_0322/summary.rtf | 1 +
.../Uthsc_bxd_mamgland_cpm_0322/specifics.rtf | 1 +
.../Uthsc_bxd_mamgland_cpm_0322/summary.rtf | 1 +
.../Uthsc_bxd_mamgland_cpmntum_0322/specifics.rtf | 1 +
.../Uthsc_bxd_mamgland_cpmntum_0322/summary.rtf | 1 +
.../Uthsc_bxd_mamgland_tum_0322/specifics.rtf | 1 +
.../Uthsc_bxd_mamgland_tum_0322/summary.rtf | 1 +
general/datasets/Uthsc_bxd_wb_rnaseq1112/cases.rtf | 245 +
general/datasets/Uthsc_bxd_wb_rnaseq1112/notes.rtf | 23 +
.../datasets/Uthsc_bxd_wb_rnaseq1112/specifics.rtf | 1 +
.../datasets/Uthsc_bxd_wb_rnaseq1112/summary.rtf | 4 +
.../Uthsc_bxd_wb_rnaseqex1112/specifics.rtf | 1 +
.../datasets/Uthsc_bxd_wb_rnaseqex1112/summary.rtf | 1 +
.../datasets/Uthsc_bxd_wb_rnaseqtrim1112/cases.rtf | 245 +
.../datasets/Uthsc_bxd_wb_rnaseqtrim1112/notes.rtf | 23 +
.../Uthsc_bxd_wb_rnaseqtrim1112/summary.rtf | 4 +
.../Uthsc_bxd_wb_rnaseqtrim1_1112/cases.rtf | 245 +
.../Uthsc_bxd_wb_rnaseqtrim1_1112/notes.rtf | 23 +
.../Uthsc_bxd_wb_rnaseqtrim1_1112/summary.rtf | 4 +
.../experiment-design.rtf | 1 +
.../processing.rtf | 9 +
.../specifics.rtf | 3644 +++
.../tissue.rtf | 1 +
general/datasets/Uthsc_bxdaged_0615/cases.rtf | 1894 ++
general/datasets/Uthsc_bxdaged_0615/specifics.rtf | 1 +
general/datasets/Uthsc_bxdaged_0615/summary.rtf | 1 +
general/datasets/Uthsc_bxdagedex_1116/cases.rtf | 1894 ++
.../datasets/Uthsc_bxdagedex_1116/specifics.rtf | 1 +
general/datasets/Uthsc_bxdagedex_1116/summary.rtf | 1 +
.../cases.rtf | 4336 +++
.../experiment-design.rtf | 3 +
.../notes.rtf | 1 +
.../processing.rtf | 9 +
.../specifics.rtf | 1 +
.../tissue.rtf | 3 +
.../cases.rtf | 4336 +++
.../experiment-design.rtf | 3 +
.../notes.rtf | 1 +
.../processing.rtf | 9 +
.../tissue.rtf | 3 +
.../Uthsc_emsr_all_affymta1_mar17/specifics.rtf | 1 +
.../Uthsc_emsr_all_affymta1_mar17/summary.rtf | 1 +
.../Uthsc_emsr_et_affymta1_mar17/specifics.rtf | 1 +
.../Uthsc_emsr_et_affymta1_mar17/summary.rtf | 1 +
.../Uthsc_emsr_etst_affymta1_mar17/specifics.rtf | 1 +
.../Uthsc_emsr_etst_affymta1_mar17/summary.rtf | 1 +
.../Uthsc_emsr_sal_affymta1_mar17/specifics.rtf | 1 +
.../Uthsc_emsr_sal_affymta1_mar17/summary.rtf | 1 +
.../Uthsc_emsr_st_affymta1_mar17/specifics.rtf | 1 +
.../Uthsc_emsr_st_affymta1_mar17/summary.rtf | 1 +
general/datasets/Uthsc_gutexl_0414/cases.rtf | 1696 ++
general/datasets/Uthsc_gutexl_0414/platform.rtf | 1 +
general/datasets/Uthsc_gutexl_0414/processing.rtf | 1 +
general/datasets/Uthsc_gutexl_0414/specifics.rtf | 1 +
general/datasets/Uthsc_gutexl_0414/tissue.rtf | 1 +
general/datasets/Uthsc_gutgl_0414/cases.rtf | 1696 ++
general/datasets/Uthsc_gutgl_0414/platform.rtf | 1 +
general/datasets/Uthsc_gutgl_0414/processing.rtf | 1 +
general/datasets/Uthsc_gutgl_0414/specifics.rtf | 1 +
general/datasets/Uthsc_gutgl_0414/tissue.rtf | 1 +
general/datasets/Uthsc_huislets_mar17/platform.rtf | 1 +
general/datasets/Uthsc_huislets_mar17/summary.rtf | 1 +
.../Uthsc_ilm_bxd_hipp_noeb_0216/notes.rtf | 23 +
.../Uthsc_ilm_bxd_hipp_noeb_0216/summary.rtf | 39 +
.../Uthsc_ilm_bxd_hipp_noeb_0217/notes.rtf | 23 +
.../Uthsc_ilm_bxd_hipp_noeb_0217/specifics.rtf | 392 +
.../Uthsc_ilm_bxd_hipp_noeb_0217/summary.rtf | 39 +
.../Uthsc_ilm_bxd_hipp_nosb_0217/notes.rtf | 23 +
.../Uthsc_ilm_bxd_hipp_nosb_0217/specifics.rtf | 408 +
.../Uthsc_ilm_bxd_hipp_nosb_0217/summary.rtf | 39 +
.../Uthsc_ilm_bxd_hipp_rseb_0216/notes.rtf | 23 +
.../Uthsc_ilm_bxd_hipp_rseb_0216/summary.rtf | 39 +
.../Uthsc_ilm_bxd_hipp_rseb_0217/notes.rtf | 23 +
.../Uthsc_ilm_bxd_hipp_rseb_0217/specifics.rtf | 408 +
.../Uthsc_ilm_bxd_hipp_rseb_0217/summary.rtf | 39 +
.../Uthsc_ilm_bxd_hipp_rssb_0216/notes.rtf | 23 +
.../Uthsc_ilm_bxd_hipp_rssb_0216/summary.rtf | 39 +
.../Uthsc_ilm_bxd_hipp_rssb_0217/notes.rtf | 23 +
.../Uthsc_ilm_bxd_hipp_rssb_0217/specifics.rtf | 400 +
.../Uthsc_ilm_bxd_hipp_rssb_0217/summary.rtf | 39 +
.../experiment-design.rtf | 980 +
.../Uthsc_mm10_b6d2_ret_mirna_1116/specifics.rtf | 1 +
.../Uthsc_mm10_b6d2_ret_mirna_1116/summary.rtf | 9 +
general/datasets/Uthsc_mm9_b6d2_ret_0916/cases.rtf | 980 +
.../datasets/Uthsc_mm9_b6d2_ret_0916/summary.rtf | 9 +
.../datasets/Uthsc_mm9_b6d2_retex_0916/cases.rtf | 980 +
.../Uthsc_mm9_b6d2_retex_0916/specifics.rtf | 1 +
.../datasets/Uthsc_mm9_b6d2_retex_0916/summary.rtf | 9 +
.../datasets/Uthsc_neut_1014/experiment-design.rtf | 1 +
general/datasets/Uthsc_neut_1014/summary.rtf | 1 +
.../Uthsc_neut_el_1014/experiment-design.rtf | 1 +
general/datasets/Uthsc_neut_el_1014/summary.rtf | 1 +
general/datasets/Uthsc_spl_rma_1010/cases.rtf | 3 +
.../Uthsc_spl_rma_1010/experiment-design.rtf | 3 +
general/datasets/Uthsc_spl_rma_1010/notes.rtf | 4 +
general/datasets/Uthsc_spl_rma_1010/processing.rtf | 1932 ++
general/datasets/Uthsc_spl_rma_1010/summary.rtf | 3 +
general/datasets/Uthsc_spl_rma_1210/cases.rtf | 3 +
.../Uthsc_spl_rma_1210/experiment-design.rtf | 3 +
general/datasets/Uthsc_spl_rma_1210/notes.rtf | 4 +
general/datasets/Uthsc_spl_rma_1210/processing.rtf | 1932 ++
general/datasets/Uthsc_spl_rma_1210/summary.rtf | 3 +
general/datasets/Uthsc_spl_rma_1210f/cases.rtf | 3 +
.../Uthsc_spl_rma_1210f/experiment-design.rtf | 3 +
.../Uthsc_spl_rma_1210f/experiment-type.rtf | 1 +
general/datasets/Uthsc_spl_rma_1210f/notes.rtf | 4 +
.../datasets/Uthsc_spl_rma_1210f/processing.rtf | 1932 ++
general/datasets/Uthsc_spl_rma_1210f/summary.rtf | 3 +
general/datasets/Uthsc_spl_rma_1210m/cases.rtf | 3 +
.../Uthsc_spl_rma_1210m/experiment-design.rtf | 3 +
.../Uthsc_spl_rma_1210m/experiment-type.rtf | 1 +
general/datasets/Uthsc_spl_rma_1210m/notes.rtf | 4 +
.../datasets/Uthsc_spl_rma_1210m/processing.rtf | 1932 ++
general/datasets/Uthsc_spl_rma_1210m/summary.rtf | 3 +
general/datasets/Uthsc_spl_rmaex_1210/cases.rtf | 3 +
.../Uthsc_spl_rmaex_1210/experiment-design.rtf | 3 +
general/datasets/Uthsc_spl_rmaex_1210/notes.rtf | 4 +
.../datasets/Uthsc_spl_rmaex_1210/processing.rtf | 1932 ++
general/datasets/Uthsc_spl_rmaex_1210/summary.rtf | 3 +
general/datasets/Uthsc_spls1_rma_1210/cases.rtf | 3 +
.../Uthsc_spls1_rma_1210/experiment-design.rtf | 3 +
general/datasets/Uthsc_spls1_rma_1210/notes.rtf | 4 +
.../datasets/Uthsc_spls1_rma_1210/processing.rtf | 1932 ++
general/datasets/Uthsc_spls1_rma_1210/summary.rtf | 3 +
general/datasets/Uthsc_spls2_rma_1210/cases.rtf | 3 +
.../Uthsc_spls2_rma_1210/experiment-design.rtf | 3 +
general/datasets/Uthsc_spls2_rma_1210/notes.rtf | 4 +
.../datasets/Uthsc_spls2_rma_1210/processing.rtf | 1932 ++
general/datasets/Uthsc_spls2_rma_1210/summary.rtf | 3 +
.../datasets/Uthsc_str_rankinv_1210/summary.rtf | 1 +
.../Uthsc_striatum_rankinv_1210/summary.rtf | 1 +
.../acknowledgment.rtf | 1 +
.../Uthsc_vgx_mmbxdhepatocytesrma1014/cases.rtf | 266 +
.../Uthsc_vgx_mmbxdhepatocytesrma1014/citation.rtf | 1 +
.../contributors.rtf | 1 +
.../experiment-design.rtf | 3 +
.../Uthsc_vgx_mmbxdhepatocytesrma1014/platform.rtf | 1 +
.../processing.rtf | 1 +
.../Uthsc_vgx_mmbxdhepatocytesrma1014/summary.rtf | 1 +
.../Uthsc_vgx_mmbxdhepatocytesrma1014/tissue.rtf | 9 +
general/datasets/Uthscwgu88bfmg1013/summary.rtf | 1 +
.../datasets/Utk_bxdspl_vst_0110/contributors.rtf | 1 +
.../Utk_bxdspl_vst_0110/experiment-design.rtf | 1 +
general/datasets/Utk_bxdspl_vst_0110/summary.rtf | 1 +
.../Uva_hiv_1tg_hip_rlog_0720/acknowledgment.rtf | 1 +
.../datasets/Uva_hiv_1tg_hip_rlog_0720/cases.rtf | 1 +
.../Uva_hiv_1tg_hip_rlog_0720/citation.rtf | 4 +
.../Uva_hiv_1tg_hip_rlog_0720/contributors.rtf | 3 +
.../experiment-design.rtf | 1 +
.../datasets/Uva_hiv_1tg_hip_rlog_0720/notes.rtf | 1 +
.../Uva_hiv_1tg_hip_rlog_0720/platform.rtf | 1 +
.../Uva_hiv_1tg_hip_rlog_0720/processing.rtf | 5 +
.../Uva_hiv_1tg_hip_rlog_0720/specifics.rtf | 1 +
.../datasets/Uva_hiv_1tg_hip_rlog_0720/summary.rtf | 3 +
.../datasets/Uva_hiv_1tg_hip_rlog_0720/tissue.rtf | 1 +
.../Uva_hiv_1tg_pfc_rlog_0720/acknowledgment.rtf | 1 +
.../datasets/Uva_hiv_1tg_pfc_rlog_0720/cases.rtf | 1 +
.../Uva_hiv_1tg_pfc_rlog_0720/citation.rtf | 4 +
.../Uva_hiv_1tg_pfc_rlog_0720/contributors.rtf | 3 +
.../experiment-design.rtf | 1 +
.../datasets/Uva_hiv_1tg_pfc_rlog_0720/notes.rtf | 1 +
.../Uva_hiv_1tg_pfc_rlog_0720/platform.rtf | 1 +
.../Uva_hiv_1tg_pfc_rlog_0720/processing.rtf | 5 +
.../Uva_hiv_1tg_pfc_rlog_0720/specifics.rtf | 1 +
.../datasets/Uva_hiv_1tg_pfc_rlog_0720/summary.rtf | 3 +
.../datasets/Uva_hiv_1tg_pfc_rlog_0720/tissue.rtf | 1 +
.../Uva_hiv_1tg_str_rlog_0720/acknowledgment.rtf | 1 +
.../datasets/Uva_hiv_1tg_str_rlog_0720/cases.rtf | 1 +
.../Uva_hiv_1tg_str_rlog_0720/citation.rtf | 4 +
.../Uva_hiv_1tg_str_rlog_0720/contributors.rtf | 3 +
.../experiment-design.rtf | 1 +
.../datasets/Uva_hiv_1tg_str_rlog_0720/notes.rtf | 1 +
.../Uva_hiv_1tg_str_rlog_0720/platform.rtf | 1 +
.../Uva_hiv_1tg_str_rlog_0720/processing.rtf | 5 +
.../Uva_hiv_1tg_str_rlog_0720/specifics.rtf | 1 +
.../datasets/Uva_hiv_1tg_str_rlog_0720/summary.rtf | 3 +
.../datasets/Uva_hiv_1tg_str_rlog_0720/tissue.rtf | 1 +
.../datasets/VCU_BXD_Nac_CIE_AirZ_0416/summary.rtf | 1 -
.../datasets/VCU_BXD_Nac_CIE_Air_0416/summary.rtf | 1 -
.../datasets/VCU_BXD_Nac_CIE_EtZ_0416/summary.rtf | 1 -
.../datasets/VCU_BXD_Nac_CIE_Et_0416/summary.rtf | 1 -
.../VCU_BXD_PFC_CIE_AirZ_0416/acknowledgment.rtf | 1 -
.../datasets/VCU_BXD_PFC_CIE_AirZ_0416/cases.rtf | 1 -
.../experiment-design.rtf | 5 -
.../VCU_BXD_PFC_CIE_AirZ_0416/platform.rtf | 1 -
.../datasets/VCU_BXD_PFC_CIE_AirZ_0416/summary.rtf | 1 -
.../datasets/VCU_BXD_PFC_CIE_AirZ_0416/tissue.rtf | 3 -
.../VCU_BXD_PFC_CIE_Air_0416/acknowledgment.rtf | 1 -
.../datasets/VCU_BXD_PFC_CIE_Air_0416/cases.rtf | 1 -
.../VCU_BXD_PFC_CIE_Air_0416/experiment-design.rtf | 5 -
.../datasets/VCU_BXD_PFC_CIE_Air_0416/platform.rtf | 1 -
.../datasets/VCU_BXD_PFC_CIE_Air_0416/summary.rtf | 1 -
.../datasets/VCU_BXD_PFC_CIE_Air_0416/tissue.rtf | 3 -
.../VCU_BXD_PFC_CIE_EtZ_0416/acknowledgment.rtf | 1 -
.../datasets/VCU_BXD_PFC_CIE_EtZ_0416/cases.rtf | 1 -
.../VCU_BXD_PFC_CIE_EtZ_0416/experiment-design.rtf | 5 -
.../datasets/VCU_BXD_PFC_CIE_EtZ_0416/platform.rtf | 1 -
.../datasets/VCU_BXD_PFC_CIE_EtZ_0416/summary.rtf | 1 -
.../datasets/VCU_BXD_PFC_CIE_EtZ_0416/tissue.rtf | 3 -
.../VCU_BXD_PFC_CIE_Et_0416/acknowledgment.rtf | 1 -
general/datasets/VCU_BXD_PFC_CIE_Et_0416/cases.rtf | 1 -
.../VCU_BXD_PFC_CIE_Et_0416/experiment-design.rtf | 5 -
.../datasets/VCU_BXD_PFC_CIE_Et_0416/platform.rtf | 1 -
.../datasets/VCU_BXD_PFC_CIE_Et_0416/summary.rtf | 1 -
.../datasets/VCU_BXD_PFC_CIE_Et_0416/tissue.rtf | 3 -
general/datasets/VCU_NAc_Air_0113_R/summary.rtf | 1 -
general/datasets/VCU_NAc_Et_0113_R/summary.rtf | 1 -
.../datasets/Vcu_bxd_nac_cie_air_0416/summary.rtf | 1 +
.../datasets/Vcu_bxd_nac_cie_airz_0416/summary.rtf | 1 +
.../datasets/Vcu_bxd_nac_cie_et_0416/summary.rtf | 1 +
.../datasets/Vcu_bxd_nac_cie_etz_0416/summary.rtf | 1 +
.../Vcu_bxd_pfc_cie_air_0416/acknowledgment.rtf | 1 +
.../datasets/Vcu_bxd_pfc_cie_air_0416/cases.rtf | 1 +
.../Vcu_bxd_pfc_cie_air_0416/contributors.rtf | 1 +
.../Vcu_bxd_pfc_cie_air_0416/experiment-design.rtf | 5 +
.../datasets/Vcu_bxd_pfc_cie_air_0416/platform.rtf | 1 +
.../datasets/Vcu_bxd_pfc_cie_air_0416/summary.rtf | 1 +
.../datasets/Vcu_bxd_pfc_cie_air_0416/tissue.rtf | 3 +
.../Vcu_bxd_pfc_cie_airz_0416/acknowledgment.rtf | 1 +
.../datasets/Vcu_bxd_pfc_cie_airz_0416/cases.rtf | 1 +
.../Vcu_bxd_pfc_cie_airz_0416/contributors.rtf | 1 +
.../experiment-design.rtf | 5 +
.../Vcu_bxd_pfc_cie_airz_0416/platform.rtf | 1 +
.../datasets/Vcu_bxd_pfc_cie_airz_0416/summary.rtf | 1 +
.../datasets/Vcu_bxd_pfc_cie_airz_0416/tissue.rtf | 3 +
.../Vcu_bxd_pfc_cie_et_0416/acknowledgment.rtf | 1 +
general/datasets/Vcu_bxd_pfc_cie_et_0416/cases.rtf | 1 +
.../Vcu_bxd_pfc_cie_et_0416/contributors.rtf | 1 +
.../Vcu_bxd_pfc_cie_et_0416/experiment-design.rtf | 5 +
.../datasets/Vcu_bxd_pfc_cie_et_0416/platform.rtf | 1 +
.../datasets/Vcu_bxd_pfc_cie_et_0416/summary.rtf | 1 +
.../datasets/Vcu_bxd_pfc_cie_et_0416/tissue.rtf | 3 +
.../Vcu_bxd_pfc_cie_etz_0416/acknowledgment.rtf | 1 +
.../datasets/Vcu_bxd_pfc_cie_etz_0416/cases.rtf | 1 +
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create mode 100644 general/datasets/Uva_hiv_1tg_hip_rlog_0720/summary.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_hip_rlog_0720/tissue.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_pfc_rlog_0720/acknowledgment.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_pfc_rlog_0720/cases.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_pfc_rlog_0720/citation.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_pfc_rlog_0720/contributors.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_pfc_rlog_0720/experiment-design.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_pfc_rlog_0720/notes.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_pfc_rlog_0720/platform.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_pfc_rlog_0720/processing.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_pfc_rlog_0720/specifics.rtf
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create mode 100644 general/datasets/Uva_hiv_1tg_pfc_rlog_0720/tissue.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_str_rlog_0720/acknowledgment.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_str_rlog_0720/cases.rtf
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create mode 100644 general/datasets/Uva_hiv_1tg_str_rlog_0720/summary.rtf
create mode 100644 general/datasets/Uva_hiv_1tg_str_rlog_0720/tissue.rtf
delete mode 100644 general/datasets/VCU_BXD_Nac_CIE_AirZ_0416/summary.rtf
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create mode 100644 general/datasets/Vcu_bxd_nac_cie_air_0416/summary.rtf
create mode 100644 general/datasets/Vcu_bxd_nac_cie_airz_0416/summary.rtf
create mode 100644 general/datasets/Vcu_bxd_nac_cie_et_0416/summary.rtf
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create mode 100644 general/datasets/Vcu_pf_ave_0111_ss/tissue.rtf
create mode 100644 general/datasets/Vcu_pf_et_0111_r/acknowledgment.rtf
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create mode 100644 general/datasets/Vcu_pf_et_0111_r/experiment-design.rtf
create mode 100644 general/datasets/Vcu_pf_et_0111_r/experiment-type.rtf
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create mode 100644 general/datasets/Vcu_pf_et_0111_r/tissue.rtf
create mode 100644 general/datasets/Vcuet_vs_sal_0806_r/summary.rtf
create mode 100644 general/datasets/Vcuetoh_0609_r/experiment-type.rtf
create mode 100644 general/datasets/Vcuetoh_0609_r/notes.rtf
create mode 100644 general/datasets/Vcuetoh_0609_r/platform.rtf
create mode 100644 general/datasets/Vcuetoh_0609_r/specifics.rtf
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create mode 100644 general/datasets/Vcuetoh_0806_r/summary.rtf
create mode 100644 general/datasets/Vcuetoh_1007_r/experiment-design.rtf
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create mode 100644 general/datasets/Vcuetoh_1206_r/acknowledgment.rtf
create mode 100644 general/datasets/Vcuetoh_1206_r/cases.rtf
create mode 100644 general/datasets/Vcuetoh_1206_r/contributors.rtf
create mode 100644 general/datasets/Vcuetoh_1206_r/experiment-design.rtf
create mode 100644 general/datasets/Vcuetoh_1206_r/experiment-type.rtf
create mode 100644 general/datasets/Vcuetoh_1206_r/platform.rtf
create mode 100644 general/datasets/Vcuetoh_1206_r/summary.rtf
create mode 100644 general/datasets/Vcuetoh_1206_r/tissue.rtf
create mode 100644 general/datasets/Vcuetvssal_0609_r/experiment-type.rtf
create mode 100644 general/datasets/Vcuetvssal_0609_r/notes.rtf
create mode 100644 general/datasets/Vcuetvssal_0609_r/platform.rtf
create mode 100644 general/datasets/Vcuetvssal_0609_r/specifics.rtf
create mode 100644 general/datasets/Vcuetvssal_0609_r/summary.rtf
create mode 100644 general/datasets/Vcusal_0609_r/experiment-type.rtf
create mode 100644 general/datasets/Vcusal_0609_r/notes.rtf
create mode 100644 general/datasets/Vcusal_0609_r/platform.rtf
create mode 100644 general/datasets/Vcusal_0609_r/specifics.rtf
create mode 100644 general/datasets/Vcusal_0609_r/summary.rtf
create mode 100644 general/datasets/Vcusal_0806_r/summary.rtf
create mode 100644 general/datasets/Vcusal_1006_r/acknowledgment.rtf
create mode 100644 general/datasets/Vcusal_1006_r/cases.rtf
create mode 100644 general/datasets/Vcusal_1006_r/contributors.rtf
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create mode 100644 general/datasets/Vcusal_1006_r/experiment-type.rtf
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create mode 100644 general/datasets/Vcusal_1006_r/summary.rtf
create mode 100644 general/datasets/Vcusal_1006_r/tissue.rtf
create mode 100644 general/datasets/Vcusal_1007_r/experiment-design.rtf
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create mode 100644 general/datasets/Vcusal_1206_r/acknowledgment.rtf
create mode 100644 general/datasets/Vcusal_1206_r/cases.rtf
create mode 100644 general/datasets/Vcusal_1206_r/contributors.rtf
create mode 100644 general/datasets/Vcusal_1206_r/experiment-design.rtf
create mode 100644 general/datasets/Vcusal_1206_r/experiment-type.rtf
create mode 100644 general/datasets/Vcusal_1206_r/platform.rtf
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create mode 100644 general/datasets/Vcusalo_1007_r/processing.rtf
create mode 100644 general/datasets/Vcusalo_1007_r/summary.rtf
create mode 100644 general/datasets/Vubxdmousemidbrainq0512/cases.rtf
create mode 100644 general/datasets/Vubxdmousemidbrainq0512/experiment-type.rtf
create mode 100644 general/datasets/Vubxdmousemidbrainq0512/summary.rtf
delete mode 100644 general/datasets/gn10/acknowledgment.rtf
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delete mode 100644 general/datasets/luCA_GSE23352HLT0613/summary.rtf
delete mode 100644 general/datasets/none/summary.rtf
(limited to 'general')
diff --git a/general/datasets/AILPublish/specifics.rtf b/general/datasets/AILPublish/specifics.rtf
deleted file mode 100644
index ab45490..0000000
--- a/general/datasets/AILPublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Phenotypes
\ No newline at end of file
diff --git a/general/datasets/AILPublish/summary.rtf b/general/datasets/AILPublish/summary.rtf
deleted file mode 100644
index 1359271..0000000
--- a/general/datasets/AILPublish/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-AIL (Advanced Intercross Line) Phenotypes
diff --git a/general/datasets/AXBXAGeno/acknowledgment.rtf b/general/datasets/AXBXAGeno/acknowledgment.rtf
deleted file mode 100644
index e0afa35..0000000
--- a/general/datasets/AXBXAGeno/acknowledgment.rtf
+++ /dev/null
@@ -1,15 +0,0 @@
-The initial construction of this phenotype database was performed with the help of Ryan McNeive, Nathan Copeland, and Mary-Kathleen Sullivan at University of Tennessee Health Sciences Center with support by a Human Brain Project to RWW. The extension and curation of these RI phenotype files is managed by Elissa J. Chesler.
-
-References:
-
-Peleg L, Nesbitt MN (1984) Genetic control of thymus size in inbred mice. J Hered. 75:126-130.
-
-Skamene E, James SL, Meltzer MS, Nesbitt MN (1984) Genetic control of macrophage activation for killing of extracellular targets. J Leukoc Biol 35:65-69.
-
-Sampson SB, Higgins DC, Elliot RW, Taylor BA, Lueders KK, Koza RA, Paigen B (1998) An edited linkage map for the AXB and BXA recombinant inbred mouse strains. Mamm Genome 9:688-694.
-
-Williams RW, Gu J, Qi S, Lu L (2001) The genetic structure of recombinant inbred mice: High-resolution consensus maps for complex trait analysis. Genome Biology 2:RESEARCH0046.
-
-Information about this text file:
-
-This text file was originally written by EJC, March 2004. Updated by RWW, October 30, 2004, EJC June 6, 2005.
diff --git a/general/datasets/AXBXAGeno/cases.rtf b/general/datasets/AXBXAGeno/cases.rtf
deleted file mode 100644
index 9159468..0000000
--- a/general/datasets/AXBXAGeno/cases.rtf
+++ /dev/null
@@ -1,25 +0,0 @@
-The AXB and BXA recombinant inbred strains were derived from a reciprocal cross between A/J (A) and C57BL/6J (B6 or B). Both parental strains have been sequenced, making this a particularly powerful set of RI strains for functional and genetic analyses. Data acquired using AXB and BXA subsets should be combined; the only difference being the polarity of intercross matings that generated (A x B)F1s and (B x A)F1s. AXB and BXA strains were all produced by Muriel Nesbitt at UCSD in the mid and late 1970s and first used in the early 1980s (Skamene et al., 1984; Peleg and Nesbitt, 1984; Marshal and Paigen, 1993). The set was imported into The Jackson Laboratory by Beverly Paigen (Pgn) in the early 1990s. As of 2004, approximately 25 viable and fully independent AXB/BXA strains are available.
-
-Several nominally independent strains in the AXB and BXA sets are very closely related. These duplicates should not be used without special statistical precaution. The most obvious option is to combine and average data from these strains except when their phenotypes differ significantly (Taylor 1996; Williams et al., 2001).
-
-AXB13=AXB14: 92.74% identity in an analysis of 8429 markers. AXB14/PgnJ (JAX001684) was renamed AXB13a/PgnJ (see JAXNotes issue number 504, Winter 2006).
-AXB18=AXB19=AXB20: 97 to 99% identity (AXB18 to AXB19 = 98.16% identity, AXB18 to AXB20 = 95.72% identity, AXB19 to AXB20 = 97.34% identity n an analysis of 8429 markers). AXB18 (JAX001686) was renamed AXB19a; AXB19 (JAX001687) was NOT renamed and is still AXB19, and AXB20 (JAX001688) was renamed AXB19b (see JAXNotes issue number 504, Winter 2006).
-BXA8=BXA17: 99.79% identity in an analysis of 8429 markers. BXA17 has been discarded as a strain. The orginal BXA17 was lost between 1989 and 1990. (Updated from Williams et al. 2001; see JAXNotes issue number 504, Winter 2006).).
-
-About the genotypes associated with these strains:
-
-Please see The Genetic Structure of Recombinant Inbred Mice.
-
-About the acquisition these data:
-
-Published phenotypes were obtained through a literature search of all PubMed indexed journals. Whenever possible, exact values of graphically represented data were obtained from the authors. In all other cases graphs were measured using a vernier caliper. Additional published and unpublished phenotypes were submitted directly by investigators. These records have Record ID numbers less than 1.
-
-The special AXB/BXA genotype data set that we use in GeneNetwork may be download as a "AXBXA.geno" file and opened with any text editor or even a spreadsheet program. This file is tab-delimited and includes the approximately centimorgan and basepair (megabasepair) location of the marekers, as well as the genotypes. Genotypes for several sets of strains have been combined. To obtain the original uncombined genotypes, please link to http://www.well.ox.ac.uk/mouse/INBREDS/ .
-
-How to obtain these strains:
-
-Please see http://jaxmice.jax.org/jaxmicedb/html/rcbinbred.shtml
-
-Submitting data and reporting errors:
-
-The utility of the AXB/BXA phenotype database increases significantly as each new phenotype is incorporated. To submit new data or report errors, please contact Elissa J. Chesler and Robert W. Williams at University of Tennessee Health Science Center
diff --git a/general/datasets/AXBXAGeno/summary.rtf b/general/datasets/AXBXAGeno/summary.rtf
deleted file mode 100644
index f2f2497..0000000
--- a/general/datasets/AXBXAGeno/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Download the entire AXB/BXA genotype file used in GeneNetwork (n = 2446 unique strain distribution patterns based on a total of 8514 informative markers). We have modified the orginal Wellcome-CTC genotypes by adding selected microsatellite markers. We have also curate the data and have removed somewhat improbable double-recombinant haplotypes and by imputing genotypes for a few untyped strains using very tightly linked markers. This genotype "smoothing" may remove some genuine recombinations and may result in linkage maps that will be very slightly conservative.
diff --git a/general/datasets/Ailpublish/specifics.rtf b/general/datasets/Ailpublish/specifics.rtf
new file mode 100644
index 0000000..ab45490
--- /dev/null
+++ b/general/datasets/Ailpublish/specifics.rtf
@@ -0,0 +1 @@
+Phenotypes
\ No newline at end of file
diff --git a/general/datasets/Ailpublish/summary.rtf b/general/datasets/Ailpublish/summary.rtf
new file mode 100644
index 0000000..1359271
--- /dev/null
+++ b/general/datasets/Ailpublish/summary.rtf
@@ -0,0 +1 @@
+AIL (Advanced Intercross Line) Phenotypes
diff --git a/general/datasets/Akxdgeno/summary.rtf b/general/datasets/Akxdgeno/summary.rtf
new file mode 100644
index 0000000..c7df169
--- /dev/null
+++ b/general/datasets/Akxdgeno/summary.rtf
@@ -0,0 +1 @@
+Download the entire AKXD genotype file used in GeneNetwork (n = 1352 markers with useful strain distribution pattens from a total of 5448 informative markers). We have modified the orginal Wellcome-CTC genotypes by adding selected microsatellite markers. We have also curate the data and have removed somewhat improbable double-recombinant haplotypes and by imputing genotypes for a few untyped strains using very tightly linked markers. This genotype "smoothing" may remove some genuine recombinations and may result in linkage maps that will be very slightly conservative.
diff --git a/general/datasets/Axbxageno/acknowledgment.rtf b/general/datasets/Axbxageno/acknowledgment.rtf
new file mode 100644
index 0000000..e0afa35
--- /dev/null
+++ b/general/datasets/Axbxageno/acknowledgment.rtf
@@ -0,0 +1,15 @@
+The initial construction of this phenotype database was performed with the help of Ryan McNeive, Nathan Copeland, and Mary-Kathleen Sullivan at University of Tennessee Health Sciences Center with support by a Human Brain Project to RWW. The extension and curation of these RI phenotype files is managed by Elissa J. Chesler.
+
+References:
+
+Peleg L, Nesbitt MN (1984) Genetic control of thymus size in inbred mice. J Hered. 75:126-130.
+
+Skamene E, James SL, Meltzer MS, Nesbitt MN (1984) Genetic control of macrophage activation for killing of extracellular targets. J Leukoc Biol 35:65-69.
+
+Sampson SB, Higgins DC, Elliot RW, Taylor BA, Lueders KK, Koza RA, Paigen B (1998) An edited linkage map for the AXB and BXA recombinant inbred mouse strains. Mamm Genome 9:688-694.
+
+Williams RW, Gu J, Qi S, Lu L (2001) The genetic structure of recombinant inbred mice: High-resolution consensus maps for complex trait analysis. Genome Biology 2:RESEARCH0046.
+
+Information about this text file:
+
+This text file was originally written by EJC, March 2004. Updated by RWW, October 30, 2004, EJC June 6, 2005.
diff --git a/general/datasets/Axbxageno/cases.rtf b/general/datasets/Axbxageno/cases.rtf
new file mode 100644
index 0000000..9159468
--- /dev/null
+++ b/general/datasets/Axbxageno/cases.rtf
@@ -0,0 +1,25 @@
+The AXB and BXA recombinant inbred strains were derived from a reciprocal cross between A/J (A) and C57BL/6J (B6 or B). Both parental strains have been sequenced, making this a particularly powerful set of RI strains for functional and genetic analyses. Data acquired using AXB and BXA subsets should be combined; the only difference being the polarity of intercross matings that generated (A x B)F1s and (B x A)F1s. AXB and BXA strains were all produced by Muriel Nesbitt at UCSD in the mid and late 1970s and first used in the early 1980s (Skamene et al., 1984; Peleg and Nesbitt, 1984; Marshal and Paigen, 1993). The set was imported into The Jackson Laboratory by Beverly Paigen (Pgn) in the early 1990s. As of 2004, approximately 25 viable and fully independent AXB/BXA strains are available.
+
+Several nominally independent strains in the AXB and BXA sets are very closely related. These duplicates should not be used without special statistical precaution. The most obvious option is to combine and average data from these strains except when their phenotypes differ significantly (Taylor 1996; Williams et al., 2001).
+
+AXB13=AXB14: 92.74% identity in an analysis of 8429 markers. AXB14/PgnJ (JAX001684) was renamed AXB13a/PgnJ (see JAXNotes issue number 504, Winter 2006).
+AXB18=AXB19=AXB20: 97 to 99% identity (AXB18 to AXB19 = 98.16% identity, AXB18 to AXB20 = 95.72% identity, AXB19 to AXB20 = 97.34% identity n an analysis of 8429 markers). AXB18 (JAX001686) was renamed AXB19a; AXB19 (JAX001687) was NOT renamed and is still AXB19, and AXB20 (JAX001688) was renamed AXB19b (see JAXNotes issue number 504, Winter 2006).
+BXA8=BXA17: 99.79% identity in an analysis of 8429 markers. BXA17 has been discarded as a strain. The orginal BXA17 was lost between 1989 and 1990. (Updated from Williams et al. 2001; see JAXNotes issue number 504, Winter 2006).).
+
+About the genotypes associated with these strains:
+
+Please see The Genetic Structure of Recombinant Inbred Mice.
+
+About the acquisition these data:
+
+Published phenotypes were obtained through a literature search of all PubMed indexed journals. Whenever possible, exact values of graphically represented data were obtained from the authors. In all other cases graphs were measured using a vernier caliper. Additional published and unpublished phenotypes were submitted directly by investigators. These records have Record ID numbers less than 1.
+
+The special AXB/BXA genotype data set that we use in GeneNetwork may be download as a "AXBXA.geno" file and opened with any text editor or even a spreadsheet program. This file is tab-delimited and includes the approximately centimorgan and basepair (megabasepair) location of the marekers, as well as the genotypes. Genotypes for several sets of strains have been combined. To obtain the original uncombined genotypes, please link to http://www.well.ox.ac.uk/mouse/INBREDS/ .
+
+How to obtain these strains:
+
+Please see http://jaxmice.jax.org/jaxmicedb/html/rcbinbred.shtml
+
+Submitting data and reporting errors:
+
+The utility of the AXB/BXA phenotype database increases significantly as each new phenotype is incorporated. To submit new data or report errors, please contact Elissa J. Chesler and Robert W. Williams at University of Tennessee Health Science Center
diff --git a/general/datasets/Axbxageno/summary.rtf b/general/datasets/Axbxageno/summary.rtf
new file mode 100644
index 0000000..f2f2497
--- /dev/null
+++ b/general/datasets/Axbxageno/summary.rtf
@@ -0,0 +1 @@
+Download the entire AXB/BXA genotype file used in GeneNetwork (n = 2446 unique strain distribution patterns based on a total of 8514 informative markers). We have modified the orginal Wellcome-CTC genotypes by adding selected microsatellite markers. We have also curate the data and have removed somewhat improbable double-recombinant haplotypes and by imputing genotypes for a few untyped strains using very tightly linked markers. This genotype "smoothing" may remove some genuine recombinations and may result in linkage maps that will be very slightly conservative.
diff --git a/general/datasets/B139_k_1206_m/citation.rtf b/general/datasets/B139_k_1206_m/citation.rtf
new file mode 100644
index 0000000..9e38a8c
--- /dev/null
+++ b/general/datasets/B139_k_1206_m/citation.rtf
@@ -0,0 +1 @@
+Arnis Druka , Ilze Druka , Arthur G Centeno , Hongqiang Li , Zhaohui Sun , William TB Thomas , Nicola Bonar , Brian J Steffenson , Steven E Ullrich , Andris Kleinhofs , Roger P Wise , Timothy J Close , Elena Potokina , Zewei Luo , Carola Wagner , Gunther F Schweizer , David F Marshall , Michael J Kearsey , Robert W Williams and Robbie Waugh.Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork. BMC Genetics 2008, 9:73doi:10.1186/1471-2156-9-73. PUBMED: PMC2630324
diff --git a/general/datasets/B139_k_1206_m/contributors.rtf b/general/datasets/B139_k_1206_m/contributors.rtf
new file mode 100644
index 0000000..0103ff3
--- /dev/null
+++ b/general/datasets/B139_k_1206_m/contributors.rtf
@@ -0,0 +1 @@
+Arnis Druka , Ilze Druka , Arthur G Centeno , Hongqiang Li , Zhaohui Sun , William TB Thomas , Nicola Bonar , Brian J Steffenson , Steven E Ullrich , Andris Kleinhofs , Roger P Wise , Timothy J Close , Elena Potokina , Zewei Luo , Carola Wagner , Gunther F Schweizer , David F Marshall , Michael J Kearsey , Robert W Williams and Robbie Waugh.
diff --git a/general/datasets/B139_k_1206_m/experiment-design.rtf b/general/datasets/B139_k_1206_m/experiment-design.rtf
new file mode 100644
index 0000000..b80f1da
--- /dev/null
+++ b/general/datasets/B139_k_1206_m/experiment-design.rtf
@@ -0,0 +1,3 @@
+A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community.
+
+By integrating barley genotypic, phenotypic and mRNA abundance data sets directly within GeneNetwork's analytical environment we provide simple web access to the data for the research community. In this environment, a combination of correlation analysis and linkage mapping provides the potential to identify and substantiate gene targets for saturation mapping and positional cloning. By integrating datasets from an unsequenced crop plant (barley) in a database that has been designed for an animal model species (mouse) with a well established genome sequence, we prove the importance of the concept and practice of modular development and interoperability of software engineering for biological data sets.
diff --git a/general/datasets/B139_k_1206_m/experiment-type.rtf b/general/datasets/B139_k_1206_m/experiment-type.rtf
new file mode 100644
index 0000000..585c17b
--- /dev/null
+++ b/general/datasets/B139_k_1206_m/experiment-type.rtf
@@ -0,0 +1 @@
+A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community.
\ No newline at end of file
diff --git a/general/datasets/B139_k_1206_m/summary.rtf b/general/datasets/B139_k_1206_m/summary.rtf
new file mode 100644
index 0000000..54d0d52
--- /dev/null
+++ b/general/datasets/B139_k_1206_m/summary.rtf
@@ -0,0 +1 @@
+Using a reference population of 150 recombinant doubled haploid barley lines we generated novel phenotypic, mRNA abundance and SNP-based genotyping data sets, added them to a considerable volume of legacy trait data and entered them into the GeneNetwork http://www.genenetwork.org webcite. GeneNetwork is a unified on-line analytical environment that enables the user to test genetic hypotheses about how component traits, such as mRNA abundance, may interact to condition more complex biological phenotypes (higher-order traits). Here we describe these barley data sets and demonstrate some of the functionalities GeneNetwork provides as an easily accessible and integrated analytical environment for exploring them.
diff --git a/general/datasets/B139_k_1206_r/citation.rtf b/general/datasets/B139_k_1206_r/citation.rtf
new file mode 100644
index 0000000..9e38a8c
--- /dev/null
+++ b/general/datasets/B139_k_1206_r/citation.rtf
@@ -0,0 +1 @@
+Arnis Druka , Ilze Druka , Arthur G Centeno , Hongqiang Li , Zhaohui Sun , William TB Thomas , Nicola Bonar , Brian J Steffenson , Steven E Ullrich , Andris Kleinhofs , Roger P Wise , Timothy J Close , Elena Potokina , Zewei Luo , Carola Wagner , Gunther F Schweizer , David F Marshall , Michael J Kearsey , Robert W Williams and Robbie Waugh.Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork. BMC Genetics 2008, 9:73doi:10.1186/1471-2156-9-73. PUBMED: PMC2630324
diff --git a/general/datasets/B139_k_1206_r/contributors.rtf b/general/datasets/B139_k_1206_r/contributors.rtf
new file mode 100644
index 0000000..0103ff3
--- /dev/null
+++ b/general/datasets/B139_k_1206_r/contributors.rtf
@@ -0,0 +1 @@
+Arnis Druka , Ilze Druka , Arthur G Centeno , Hongqiang Li , Zhaohui Sun , William TB Thomas , Nicola Bonar , Brian J Steffenson , Steven E Ullrich , Andris Kleinhofs , Roger P Wise , Timothy J Close , Elena Potokina , Zewei Luo , Carola Wagner , Gunther F Schweizer , David F Marshall , Michael J Kearsey , Robert W Williams and Robbie Waugh.
diff --git a/general/datasets/B139_k_1206_r/experiment-design.rtf b/general/datasets/B139_k_1206_r/experiment-design.rtf
new file mode 100644
index 0000000..b80f1da
--- /dev/null
+++ b/general/datasets/B139_k_1206_r/experiment-design.rtf
@@ -0,0 +1,3 @@
+A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community.
+
+By integrating barley genotypic, phenotypic and mRNA abundance data sets directly within GeneNetwork's analytical environment we provide simple web access to the data for the research community. In this environment, a combination of correlation analysis and linkage mapping provides the potential to identify and substantiate gene targets for saturation mapping and positional cloning. By integrating datasets from an unsequenced crop plant (barley) in a database that has been designed for an animal model species (mouse) with a well established genome sequence, we prove the importance of the concept and practice of modular development and interoperability of software engineering for biological data sets.
diff --git a/general/datasets/B139_k_1206_r/experiment-type.rtf b/general/datasets/B139_k_1206_r/experiment-type.rtf
new file mode 100644
index 0000000..585c17b
--- /dev/null
+++ b/general/datasets/B139_k_1206_r/experiment-type.rtf
@@ -0,0 +1 @@
+A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community.
\ No newline at end of file
diff --git a/general/datasets/B139_k_1206_r/summary.rtf b/general/datasets/B139_k_1206_r/summary.rtf
new file mode 100644
index 0000000..54d0d52
--- /dev/null
+++ b/general/datasets/B139_k_1206_r/summary.rtf
@@ -0,0 +1 @@
+Using a reference population of 150 recombinant doubled haploid barley lines we generated novel phenotypic, mRNA abundance and SNP-based genotyping data sets, added them to a considerable volume of legacy trait data and entered them into the GeneNetwork http://www.genenetwork.org webcite. GeneNetwork is a unified on-line analytical environment that enables the user to test genetic hypotheses about how component traits, such as mRNA abundance, may interact to condition more complex biological phenotypes (higher-order traits). Here we describe these barley data sets and demonstrate some of the functionalities GeneNetwork provides as an easily accessible and integrated analytical environment for exploring them.
diff --git a/general/datasets/B150_k_0406_r/citation.rtf b/general/datasets/B150_k_0406_r/citation.rtf
new file mode 100644
index 0000000..9e38a8c
--- /dev/null
+++ b/general/datasets/B150_k_0406_r/citation.rtf
@@ -0,0 +1 @@
+Arnis Druka , Ilze Druka , Arthur G Centeno , Hongqiang Li , Zhaohui Sun , William TB Thomas , Nicola Bonar , Brian J Steffenson , Steven E Ullrich , Andris Kleinhofs , Roger P Wise , Timothy J Close , Elena Potokina , Zewei Luo , Carola Wagner , Gunther F Schweizer , David F Marshall , Michael J Kearsey , Robert W Williams and Robbie Waugh.Towards systems genetic analyses in barley: Integration of phenotypic, expression and genotype data into GeneNetwork. BMC Genetics 2008, 9:73doi:10.1186/1471-2156-9-73. PUBMED: PMC2630324
diff --git a/general/datasets/B150_k_0406_r/contributors.rtf b/general/datasets/B150_k_0406_r/contributors.rtf
new file mode 100644
index 0000000..0103ff3
--- /dev/null
+++ b/general/datasets/B150_k_0406_r/contributors.rtf
@@ -0,0 +1 @@
+Arnis Druka , Ilze Druka , Arthur G Centeno , Hongqiang Li , Zhaohui Sun , William TB Thomas , Nicola Bonar , Brian J Steffenson , Steven E Ullrich , Andris Kleinhofs , Roger P Wise , Timothy J Close , Elena Potokina , Zewei Luo , Carola Wagner , Gunther F Schweizer , David F Marshall , Michael J Kearsey , Robert W Williams and Robbie Waugh.
diff --git a/general/datasets/B150_k_0406_r/experiment-design.rtf b/general/datasets/B150_k_0406_r/experiment-design.rtf
new file mode 100644
index 0000000..b80f1da
--- /dev/null
+++ b/general/datasets/B150_k_0406_r/experiment-design.rtf
@@ -0,0 +1,3 @@
+A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community.
+
+By integrating barley genotypic, phenotypic and mRNA abundance data sets directly within GeneNetwork's analytical environment we provide simple web access to the data for the research community. In this environment, a combination of correlation analysis and linkage mapping provides the potential to identify and substantiate gene targets for saturation mapping and positional cloning. By integrating datasets from an unsequenced crop plant (barley) in a database that has been designed for an animal model species (mouse) with a well established genome sequence, we prove the importance of the concept and practice of modular development and interoperability of software engineering for biological data sets.
diff --git a/general/datasets/B150_k_0406_r/experiment-type.rtf b/general/datasets/B150_k_0406_r/experiment-type.rtf
new file mode 100644
index 0000000..585c17b
--- /dev/null
+++ b/general/datasets/B150_k_0406_r/experiment-type.rtf
@@ -0,0 +1 @@
+A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community.
\ No newline at end of file
diff --git a/general/datasets/B150_k_0406_r/summary.rtf b/general/datasets/B150_k_0406_r/summary.rtf
new file mode 100644
index 0000000..54d0d52
--- /dev/null
+++ b/general/datasets/B150_k_0406_r/summary.rtf
@@ -0,0 +1 @@
+Using a reference population of 150 recombinant doubled haploid barley lines we generated novel phenotypic, mRNA abundance and SNP-based genotyping data sets, added them to a considerable volume of legacy trait data and entered them into the GeneNetwork http://www.genenetwork.org webcite. GeneNetwork is a unified on-line analytical environment that enables the user to test genetic hypotheses about how component traits, such as mRNA abundance, may interact to condition more complex biological phenotypes (higher-order traits). Here we describe these barley data sets and demonstrate some of the functionalities GeneNetwork provides as an easily accessible and integrated analytical environment for exploring them.
diff --git a/general/datasets/B1li0809m5/summary.rtf b/general/datasets/B1li0809m5/summary.rtf
new file mode 100644
index 0000000..134e635
--- /dev/null
+++ b/general/datasets/B1li0809m5/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 79, Name: Barley1 Leaf INOC TTKS (Aug09)
\ No newline at end of file
diff --git a/general/datasets/B1li0809r/summary.rtf b/general/datasets/B1li0809r/summary.rtf
new file mode 100644
index 0000000..134e635
--- /dev/null
+++ b/general/datasets/B1li0809r/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 79, Name: Barley1 Leaf INOC TTKS (Aug09)
\ No newline at end of file
diff --git a/general/datasets/B1mi0809m5/summary.rtf b/general/datasets/B1mi0809m5/summary.rtf
new file mode 100644
index 0000000..134e635
--- /dev/null
+++ b/general/datasets/B1mi0809m5/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 79, Name: Barley1 Leaf INOC TTKS (Aug09)
\ No newline at end of file
diff --git a/general/datasets/B1mi0809r/summary.rtf b/general/datasets/B1mi0809r/summary.rtf
new file mode 100644
index 0000000..134e635
--- /dev/null
+++ b/general/datasets/B1mi0809r/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 79, Name: Barley1 Leaf INOC TTKS (Aug09)
\ No newline at end of file
diff --git a/general/datasets/B30_k_1206_m/acknowledgment.rtf b/general/datasets/B30_k_1206_m/acknowledgment.rtf
new file mode 100644
index 0000000..5d9cc73
--- /dev/null
+++ b/general/datasets/B30_k_1206_m/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Plant maintenance, tissue collection, RNA isolation, and data submission to ArrayExpress was done at SCRI by Arnis Druka with support from BBSRC/SEERAD grant SCR/910/04 The genetics of gene expression in barley' to Michael Kearsey (University of Birmingham, UK) and Robbie Waugh (SCRI, UK). Probe synthesis, labeling and hybridization were performed according to manufacturer’s protocols (Affymetrix, Santa Clara, CA) at the Iowa State University GeneChip Core facility (Rico Caldo and Roger Wise). ArrayExpress (EBI, UK) team members Tim Rayner, Helen Parkinson, and Alvis Brazma are acknowledged for excellent help with data submission to ArrayExpress.
+
diff --git a/general/datasets/B30_k_1206_m/cases.rtf b/general/datasets/B30_k_1206_m/cases.rtf
new file mode 100644
index 0000000..1425413
--- /dev/null
+++ b/general/datasets/B30_k_1206_m/cases.rtf
@@ -0,0 +1,1748 @@
+
+The SM cross was originally made to map barley grain quality traits; Steptoe is high-yielding barley cultivar used for animal feeding, but Morex has good malting barley characteristics (Hayes et al 1993). Many agronomic quality traits have been mapped using this population (for the lists see BeerGenes web-site http://gnome.agrenv.mcgill.ca/bg/).
+
+The sample used in this study consists of 150 Steptoe x Morex doubled haploid recombinant lines (Kleinhofs et al. 1993) was used to obtain embryo-derived tissue. For the seedling leaf tissue a subset of 35 lines was used. This subset was selected based on evenly spaced crossovers along each of seven barley chromosomes. The expression data of 11 DH lines has been removed from both, embryo and leaf, leaving for the analysis 129 lines with embryo expression data and a subset of 30 lines with seedling leaf expression data. The lines were removed from the analysis after error checking; discrepancies with genotyping data were found. We left all 150 lines in the embryo Apr06 data set and the full data set is available from the ArrayExpress. The following table lists line IDs and corresponding CEL file IDs, also indicating:
+1) pedigree; shows the direction of the cross that was used to produce the original F1. The parental plants were given letter codes of A - Z. For example, SM1 was derived from an F1 that was generated by crossing Steptoe plant "B" as a female with Morex plant "F" as a male.
+2) 'minimapper' subset - MINI;
+3) lines that have expression data removed - ERROR:
+
+
+
+
+ | Order # |
+ Line ID |
+ Permanent Oregon ID |
+ Cross direction |
+
+ CEL file names
+ |
+ Mini-mapper set |
+ Error check |
+
+
+ | embryo data-set |
+ leaf data-set |
+ embryo data-set |
+ leaf data-set |
+
+
+ | 1 |
+ SM001 |
+ 2907001 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_82.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 2 |
+ SM002 |
+ 2907002 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_1.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 3 |
+ SM003 |
+ 2907003 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_19.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 4 |
+ SM004 |
+ 2907004 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_3.CEL |
+ 0521-1_SetA1.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 5 |
+ SM005 |
+ 2907005 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_88.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 6 |
+ SM006 |
+ 2907006 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_48.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 7 |
+ SM007 |
+ 2907007 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_35.CEL |
+ 0521-2_SetA2.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 8 |
+ SM009 |
+ 2907009 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_2.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 9 |
+ SM010 |
+ 2907010 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_42.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 10 |
+ SM011 |
+ 2907011 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_10.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 11 |
+ SM012 |
+ 2907012 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_45.CEL |
+ 0521-3_SetA3.CEL |
+ SMmini |
+ ERROR |
+ ERROR |
+
+
+ | 12 |
+ SM013 |
+ 2907013 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_78.CEL |
+ 0521-4_SetA4.CEL |
+ SMmini |
+ ERROR |
+ ERROR |
+
+
+ | 13 |
+ SM014 |
+ 2907014 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_18.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 14 |
+ SM015 |
+ 2907015 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_5.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 15 |
+ SM016 |
+ 2907016 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_21.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 16 |
+ SM020 |
+ 2907020 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_77.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 17 |
+ SM021 |
+ 2907021 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_30.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 18 |
+ SM022 |
+ 2907022 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_31.CEL |
+ 0521-5_SetA5.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 19 |
+ SM023 |
+ 2907023 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_32.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 20 |
+ SM024 |
+ 2907024 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_33.CEL |
+ 0521-6_SetA6.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 21 |
+ SM025 |
+ 2907025 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_34.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 22 |
+ SM027 |
+ 2907027 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_12.CEL |
+ 0521-7_SetA7.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 23 |
+ SM030 |
+ 2907030 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_79.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 24 |
+ SM031 |
+ 2907031 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_16.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 25 |
+ SM032 |
+ 2907032 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_13.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 26 |
+ SM035 |
+ 2907035 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_15.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 27 |
+ SM039 |
+ 2907039 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_41.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 28 |
+ SM040 |
+ 2907040 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_83.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 29 |
+ SM041 |
+ 2907041 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_11_redo.CEL |
+ 0521-8_SetA8.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 30 |
+ SM042 |
+ 2907042 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_57.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 31 |
+ SM043 |
+ 2907043 |
+ Morex/Steptoe(JxE) |
+ AD_SCRI_49.CEL |
+ 0521-9_SetA9.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 32 |
+ SM044 |
+ 2907044 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_50.CEL |
+ 0521-10_SetA10.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 33 |
+ SM045 |
+ 2907045 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_51.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 34 |
+ SM046 |
+ 2907046 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_52.CEL |
+ 0521-11_SetA11.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 35 |
+ SM048 |
+ 2907048 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_53.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 36 |
+ SM050 |
+ 2907050 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_46.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 37 |
+ SM054 |
+ 2907054 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_60.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 38 |
+ SM055 |
+ 2907055 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_55.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 39 |
+ SM056 |
+ 2907056 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_23.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 40 |
+ SM057 |
+ 2907057 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_24.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 41 |
+ SM058 |
+ 2907058 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_22.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 42 |
+ SM059 |
+ 2907059 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_27.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 43 |
+ SM061 |
+ 2907061 |
+ Morex/Steptoe(LxF) |
+ AD_SCRI_81.CEL |
+ 0521-12_SetA12.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 44 |
+ SM062 |
+ 2907062 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_44.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 45 |
+ SM063 |
+ 2907063 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_40.CEL |
+ 0521-13_SetA13.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 46 |
+ SM064 |
+ 2907064 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_87_redo.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 47 |
+ SM065 |
+ 2907065 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_54.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 48 |
+ SM067 |
+ 2907067 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_73.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 49 |
+ SM068 |
+ 2907068 |
+ Steptoe/Morex(OxG) |
+ AD_SCRI_56.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 50 |
+ SM069 |
+ 2907069 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_71.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 51 |
+ SM070 |
+ 2907070 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_64.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 52 |
+ SM071 |
+ 2907071 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_58.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 53 |
+ SM072 |
+ 2907072 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_59.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 54 |
+ SM073 |
+ 2907073 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_74.CEL |
+ 0521-14_SetA14.CEL |
+ SMmini |
+ OK |
+ ERROR |
+
+
+ | 55 |
+ SM074 |
+ 2907074 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_25.CEL |
+ 0521-15_SetA15.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 56 |
+ SM075 |
+ 2907075 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_120.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 57 |
+ SM076 |
+ 2907076 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_112.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 58 |
+ SM077 |
+ 2907077 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_142.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 59 |
+ SM078 |
+ 2907078 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_86.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 60 |
+ SM079 |
+ 2907079 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_153.CEL |
+ 0521-16_SetA16.CEL |
+ SMmini |
+ OK |
+ ERROR |
+
+
+ | 61 |
+ SM080 |
+ 2907080 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_107.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 62 |
+ SM081 |
+ 2907081 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_105.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 63 |
+ SM082 |
+ 2907082 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_97.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 64 |
+ SM083 |
+ 2907083 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_89.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 65 |
+ SM084 |
+ 2907084 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_155.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 66 |
+ SM085 |
+ 2907085 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_149.CEL |
+ 0521-17_SetA17.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 67 |
+ SM087 |
+ 2907087 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_113.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 68 |
+ SM088 |
+ 2907088 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_93.CEL |
+ 0521-18_SetA18.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 69 |
+ SM089 |
+ 2907089 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_148.CEL |
+ 0521-19_SetA19.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 70 |
+ SM091 |
+ 2907091 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_110.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 71 |
+ SM092 |
+ 2907092 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_7.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 72 |
+ SM093 |
+ 2907093 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_122.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 73 |
+ SM094 |
+ 2907094 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_150.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 74 |
+ SM097 |
+ 2907097 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_158.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 75 |
+ SM098 |
+ 2907098 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_121.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 76 |
+ SM099 |
+ 2907099 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_137.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 77 |
+ SM103 |
+ 2907103 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_156.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 78 |
+ SM104 |
+ 2907104 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_70.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 79 |
+ SM105 |
+ 2907105 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_69.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 80 |
+ SM110 |
+ 2907110 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_75.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 81 |
+ SM112 |
+ 2907112 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_84.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 82 |
+ SM116 |
+ 2907116 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_117.CEL |
+ 0521-20_SetA20.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 83 |
+ SM120 |
+ 2907120 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_138.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 84 |
+ SM124 |
+ 2907124 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_146.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 85 |
+ SM125 |
+ 2907125 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_43.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 86 |
+ SM126 |
+ 2907126 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_144_redo.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 87 |
+ SM127 |
+ 2907127 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_129.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 88 |
+ SM129 |
+ 2907129 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_132.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 89 |
+ SM130 |
+ 2907130 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_101.CEL |
+ 0521-21_SetA21.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 90 |
+ SM131 |
+ 2907131 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_102.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 91 |
+ SM132 |
+ 2907132 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_4_redo.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 92 |
+ SM133 |
+ 2907133 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_157.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 93 |
+ SM134 |
+ 2907134 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_159.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 94 |
+ SM135 |
+ 2907135 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_72.CEL |
+ 0521-22_SetA22.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 95 |
+ SM136 |
+ 2907136 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_123.CEL |
+ 0521-23_SetA23.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 96 |
+ SM137 |
+ 2907137 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_39.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 97 |
+ SM139 |
+ 2907139 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_133.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 98 |
+ SM140 |
+ 2907140 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_134.CEL |
+ 0521-24_SetA24.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 99 |
+ SM141 |
+ 2907141 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_136.CEL |
+ 0521-25_SetA25.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 100 |
+ SM142 |
+ 2907142 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_6.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 101 |
+ SM143 |
+ 2907143 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_145.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 102 |
+ SM144 |
+ 2907144 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_103.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 103 |
+ SM145 |
+ 2907145 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_108.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 104 |
+ SM146 |
+ 2907146 |
+ Morex/Steptoe(BxF) |
+ AD_SCRI_91.CEL |
+ 0521-26_SetA26.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 105 |
+ SM147 |
+ 2907147 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_139.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 106 |
+ SM149 |
+ 2907149 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_131.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 107 |
+ SM150 |
+ 2907150 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_37.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 108 |
+ SM151 |
+ 2907151 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_28.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 109 |
+ SM152 |
+ 2907152 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_9_redo.CEL |
+ 0521-27_SetA27.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 110 |
+ SM153 |
+ 2907153 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_135.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 111 |
+ SM154 |
+ 2907154 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_114.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 112 |
+ SM155 |
+ 2907155 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_119.CEL |
+ 0521-28_SetA28.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 113 |
+ SM156 |
+ 2907156 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_140.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 114 |
+ SM157 |
+ 2907157 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_106_redo.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 115 |
+ SM158 |
+ 2907158 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_65.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 116 |
+ SM159 |
+ 2907159 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_168.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 117 |
+ SM160 |
+ 2907160 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_47.CEL |
+ 0521-29_SetA29.CEL |
+ SMmini |
+ OK |
+ ERROR |
+
+
+ | 118 |
+ SM161 |
+ 2907161 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_76.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 119 |
+ SM162 |
+ 2907162 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_147.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 120 |
+ SM164 |
+ 2907164 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_128.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 121 |
+ SM165 |
+ 2907165 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_143.CEL |
+ |
+ |
+ OK |
+ OK |
+
+
+ | 122 |
+ SM166 |
+ 2907166 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_115.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 123 |
+ SM167 |
+ 2907167 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_127.CEL |
+ 0521-30_SetA30.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 124 |
+ SM168 |
+ 2907168 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_130.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 125 |
+ SM169 |
+ 2907169 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_118.CEL |
+ 0521-31_SetA31.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 126 |
+ SM170 |
+ 2907170 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_151.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 127 |
+ SM171 |
+ 2907171 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_165.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 128 |
+ SM172 |
+ 2907172 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_152.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 129 |
+ SM173 |
+ 2907173 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_104.CEL |
+ 0521-32_SetA32.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 130 |
+ SM174 |
+ 2907174 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_154.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 131 |
+ SM176 |
+ 2907176 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_141.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 132 |
+ SM177 |
+ 2907177 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_111.CEL |
+ 0521-33_SetA33.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 133 |
+ SM179 |
+ 2907179 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_166.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 134 |
+ SM180 |
+ 2907180 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_161.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 135 |
+ SM181 |
+ 2907181 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_162.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 136 |
+ SM182 |
+ 2907182 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_163.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 137 |
+ SM183 |
+ 2907183 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_164.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 138 |
+ SM184 |
+ 2907184 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_160.CEL |
+ 0521-34_SetA34.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 139 |
+ SM185 |
+ 2907185 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_167.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 140 |
+ SM186 |
+ 2907186 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_62.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 141 |
+ SM187 |
+ 2907187 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_61.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 142 |
+ SM188 |
+ 2907188 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_63.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 143 |
+ SM189 |
+ 2907189 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_80.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 144 |
+ SM193 |
+ 2907193 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_36.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 145 |
+ SM194 |
+ 2907194 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_29.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 146 |
+ SM196 |
+ 2907196 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_26.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 147 |
+ SM197 |
+ 2907197 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_85.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 148 |
+ SM198 |
+ 2907198 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_8.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 149 |
+ SM199 |
+ 2907199 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_20.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 150 |
+ SM200 |
+ 2907200 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_38.CEL |
+ 0521-35_SetA35.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | parent |
+ Steptoe |
+ |
+ |
+ AD_SCRI_17.CEL |
+ 0521-36_SetA36.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Steptoe |
+ |
+ |
+ AD_SCRI_66.CEL |
+ 0521-37_SetA37.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Steptoe |
+ |
+ |
+ AD_SCRI_68.CEL |
+ 0521-38_SetA38.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Morex |
+ |
+ |
+ AD_SCRI_116.CEL |
+ 0521-39_SetA39.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Morex |
+ |
+ |
+ AD_SCRI_14.CEL |
+ 0521-40_SetA40.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Morex |
+ |
+ |
+ AD_SCRI_67.CEL |
+ 0521-41_SetA41.CEL |
+ |
+ |
+ |
+
+
+
+
+
+
diff --git a/general/datasets/B30_k_1206_m/citation.rtf b/general/datasets/B30_k_1206_m/citation.rtf
new file mode 100644
index 0000000..f6fcdda
--- /dev/null
+++ b/general/datasets/B30_k_1206_m/citation.rtf
@@ -0,0 +1,11 @@
+
+Druka A, Muehlbauer G, Druka I, Caldo R, Baumann U, Rostoks N, Schreiber A, Wise R, Close T, Kleinhofs A, Graner A, Schulman A, Langridge P, Sato K, Hayes P, McNicol J, Marshall D, Waugh R. (2006) An atlas of gene expression from seed to seed through barley development. Funct Integr Genomics, Jul;6(3):202-11.
+
+Kleinhofs A, Kilian A, Saghai Maroof M, Biyashev R, Hayes P, Chen F, Lapitan N, Fenwick A, Blake T, Kanazin V, Ananiev E, Dahleen L, Kudrna D, Bollinger J, Knapp SJ, Liu BH, Sorrells M, Heun M, Franckowiak J, Hoffman D, Skadsen R, Steffenson B (1993) A molecular, isozyme, and morphological map of the barley (Hordeum vulgare) genome. Theor Appl Genet 86:705-712.
+
+Caldo RA, Nettleton D, Wise RP (2004) Interaction-dependent gene expression in Mla-specified response to barley powdery mildew. Plant Cell 16:2514-2528.
+
+Close TJ, Wanamaker SI, Caldo RA, Turner SM, Ashlock DA, Dickerson JA, Wing RA, Muehlbauer GJ, Kleinhofs A, Wise RP. (2004) A new resource for cereal genomics: 22K barley GeneChip comes of age. Plant Physiol 134:960-968.
+
+Hayes PM, Liu BH, Knapp SJ, Chen F, Jones B, Blake T, Franckowiak J, Rasmusson D, Sorrells M, Ullrich SE, Wesenberg D, Kleinhofs A (1993) Quantitative trait locus effects and environmental interaction in a sample of North American barley germplasm. Theor Appl Genet 87:392-401
+
diff --git a/general/datasets/B30_k_1206_m/experiment-design.rtf b/general/datasets/B30_k_1206_m/experiment-design.rtf
new file mode 100644
index 0000000..e743086
--- /dev/null
+++ b/general/datasets/B30_k_1206_m/experiment-design.rtf
@@ -0,0 +1,62 @@
+
+RNA Sample Processing:
+
+Trizol RNA isolation and RNeasy clean up protocol for whole plants (embryo-derived tissue dissected from 4 days old germinating grains) and the seedling leaves (12 days after planting).
+
+
+☠Grind tissue (9 embryos) with a mortar and pestle in liquid nitrogen
+☠Add 5 ml TRIzol (pre-heated to 60oC) to all samples, vortex until all the tissue is thawed, place in the 60oC waterbath..
+☠Incubate samples at 60oC for 10 minutes, vortexing three times.
+☠Centrifuge @ 4000 x rpm @ 4C for 30 minutes (in Eppendorf 5810R).
+☠While centrifuging, label new set of 15 ml tubes
+☠Transfer supernatant to 15 ml centrifuge tube
+☠Add 1 ml of chloroform. Vortex the sample until color shade is uniform at least 5
+seconds, and incubate at room temperature for 5 minutes.
+☠Centrifuge @ 4000 x rpm for 30 minutes @ 4oC.
+☠While centrifuging, label new 15 ml tubes
+☠Collect the upper aqueous layer (there will be about 3 mls) and transfer to a new 15 ml tube.
+☠Add 0.6 volumes (2 ml) of isopropanol, mix gently, incubate at room temperature for 20 minutes.
+☠Centrifuge @ 4000 rpm for 30 minutes @ 4oC.
+☠Wash the pellet with 10 ml of cold 75% ethanol. Swirl & centrifuge at
+4000 rpm for 15 minutes @ 4oC.
+☠Discard supernatant, centrifuge for 5 min, remove the rest of the ethanol
+☠Air-dry the pellet for 10 minutes, inverted on a kimwipe.
+☠Dissolve pellet in 400 ul of DEPC-treated H2O. Resuspend by pipeting up & down a
+few times.
+☠Add 2 ul SuperaseIn. Incubate at 60oC for 10 minutes to resuspend.
+☠Set water bath to 37oC.
+☠Add 50 ul 10X DnaseI Buffer, 45 ul H2O and 5 ul of DnaseI, incubate at 37oC for 1 hr.
+☠Prepare Buffer RLT (Rneasy Clean-up Midi Kit) by adding b-mercaptoethanol (10ul/1ml RLT).
+☠Add 2.0 ml Buffer RLT to the RNA prep and mix thoroughly.
+☠Add 1.4 ml ethanol (96-100%) to the diluted RNA. Mix thoroughly.
+☠Label 15 ml tubes from the kit and place midi columns in them
+☠Apply sample to a Midi column, close tube gently and centrifuge for 20 min at 3000 rpm.
+☠Discard the flow-through.
+☠Add 2.5 ml Buffer RPE to the RNA easy column, close the centrifuge tube gently,
+incubate for 3 min
+☠Centrifuge for 10 min at 3000 rpm. Discard the flow-through.
+☠Add another 2.5 ml Buffer RPE to the RNeasy column. Close the centrifuge tube
+gently, incubate for 3 min
+☠Centrifuge for 10 min at 3000 rpm, remove flow-through
+☠Centrifuge again for another 5 min.
+☠Label new 15 ml tubes from the kit.
+☠Transfer the RNA easy column to a new tube and pipet 250 ul volume of
+RNase-free water directly onto the RNeasy silica-membrane incubate for 1 min
+☠Centrifuge for 5 min at 3000 rpm.
+☠To the same tube add again 250 ul H2O, incubate for 1 min.
+☠Centrifuge for 5 min at 3000 rpm.
+☠Label two sets of 1.5 ml Eppendorf tubes.
+☠Transfer 490 ul to the one tube and 10 ul to another one. Use 10 ul tube for the RNA
+
+Detailed descriptions of these procedures can be found under the ArrayExpress (http://www.ebi.ac.uk/aerep/?) protocol P-MEXP-4631 (Caldo et al. 2004).
+
+Replication and Sample Balance:
+
+3 independent replicates of both parental cultivars Steptoe and Morex were generated for both tissues, embryo and seedling leaf.
+
+Experimental Design and Batch Structure:
+
+
+
+The following are ArrayExpress (http://www.ebi.ac.uk/aerep/?) experiment IDs: E-TABM-111 (leaf, 41 chips) and E-TABM-112 (embryo derived, 156 chips).
+
diff --git a/general/datasets/B30_k_1206_m/experiment-type.rtf b/general/datasets/B30_k_1206_m/experiment-type.rtf
new file mode 100644
index 0000000..585c17b
--- /dev/null
+++ b/general/datasets/B30_k_1206_m/experiment-type.rtf
@@ -0,0 +1 @@
+A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community.
\ No newline at end of file
diff --git a/general/datasets/B30_k_1206_m/notes.rtf b/general/datasets/B30_k_1206_m/notes.rtf
new file mode 100644
index 0000000..46cff8f
--- /dev/null
+++ b/general/datasets/B30_k_1206_m/notes.rtf
@@ -0,0 +1,14 @@
+
+Arnis Druka
+Genetics Programme
+Scottish Crop Research Institute
+Invergowrie, Dundee DD2 5DA
+Angus, Scotland, United Kingdom
+Tel +44 01382 562731
+Fax +44 01382 568587
+adruka@scri.sari.ac.uk
+
+
+
+This text file originally generated by Arnis Druka on May 8, 2006. Modified Aug1 by AD. Entered by RWW Aug 4, 2006. Modified by AD Jan 29, 2007, Feb 01, 2007.
+
diff --git a/general/datasets/B30_k_1206_m/platform.rtf b/general/datasets/B30_k_1206_m/platform.rtf
new file mode 100644
index 0000000..a935318
--- /dev/null
+++ b/general/datasets/B30_k_1206_m/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix 22K Barley1 GeneChip probe array (http://www.affymetrix.com/products/arrays/specific/barley.affx ; Affymetrix product #900515 GeneChip Barley Genome Array) representing 21,439 non-redundant Barley1 exemplar sequences was derived from worldwide contribution of 350,000 high-quality ESTs from 84 cDNA libraries, in addition to 1,145 barley gene sequences from the National Center for Biotechnology Information non-redundant database (Close et al 2004). Abbreviated annotations were created based on the exemplar sequence homology by Arnis Druka using data from the Harvest (http://harvest.ucr.edu/) data depository.
+
diff --git a/general/datasets/B30_k_1206_m/processing.rtf b/general/datasets/B30_k_1206_m/processing.rtf
new file mode 100644
index 0000000..d8d039a
--- /dev/null
+++ b/general/datasets/B30_k_1206_m/processing.rtf
@@ -0,0 +1,49 @@
+
+
+
+
+ |
+ Types of the expression data-sets
+ |
+
+ Data processing description
+ |
+
+
+ Barley1 Embryo gcRMA SCRI (Dec 06)
+ Barley1 Leaf gcRMA SCRI (Dec 06) |
+
+
+
+ The Affymetrix' CEL files that were generated using MAS 5.0 Suite were imported into the GeneSpring GX 7.3 (Agilent Technologies, Palo Alto, CA) and processed using the RMA algorithm.
+
+
+ |
+
+
+ Barley1 Embryo MAS 5.0 SCRI (Dec 06)
+ Barley1 Leaf MAS 5.0 SCRI (Dec 06) |
+
+
+
+ The MAS 5.0 values were calculated from the DAT files using Affymetrix' MAS 5.0 Suite.
+
+
+ |
+
+
+ Barley1 Embryo0 gcRMA SCRI (Apr 06)
+ Barley1 Leaf gcRMAn SCRI (Dec 06) |
+
+ The Affymetrix' CEL files were imported into the GeneSpring GX 7.3 (Agilent Technologies, Palo Alto, CA) software and processed using the RMA algorithm. Per-chip and per-gene normalization was done following the standard GeneSpring procedure (citation of the GeneSpring normalization description):
+
+
+ - Values below 0.01 were set to 0.01.
+ - Each measurement was divided by the 50.0th percentile of all measurements in that sample.
+ - Each gene was divided by the median of its measurements in all samples. If the median of the raw values was below 10 then each measurement for that gene was divided by 10 if the numerator was above 10, otherwise the measurement was thrown out.
+
+ |
+
+
+
+
diff --git a/general/datasets/B30_k_1206_m/summary.rtf b/general/datasets/B30_k_1206_m/summary.rtf
new file mode 100644
index 0000000..67f4fab
--- /dev/null
+++ b/general/datasets/B30_k_1206_m/summary.rtf
@@ -0,0 +1,5 @@
+Barley1 Leaf MAS 5.0 SCRI (Dec 06) - integrated probe set value for each gene has been calculated using MAS 5.0 algorithm which uses pixel values from both, PM and MM probes. Descriptions of probe set signal calculation can be found on this page below, section 'About Data Processing'.
+
+
+The SCRI barley data set provides estimates of mRNA abundance in doubled haploid recombinant lines of cultivated barley. Embryo-derived tissues at four days after imbibition (150 lines) and seedling leaves at 12 days after imbibition (subset of 34 lines) and three biological replicates of each parental cultivar (Steptoe and Morex) for each tissue were used for the isolation of total RNA and hybridization to the Barley1 22K GeneChip (GEO GPL1340).
+
diff --git a/general/datasets/B30_k_1206_m/tissue.rtf b/general/datasets/B30_k_1206_m/tissue.rtf
new file mode 100644
index 0000000..a8351e8
--- /dev/null
+++ b/general/datasets/B30_k_1206_m/tissue.rtf
@@ -0,0 +1,9 @@
+
+Plant material according to the current plant ontologies: Embryo-derived tissues: whole plant (PO:0000003) at the development stage 1.05-coleoptile emerged from seed (GRO:0007056); Seedling leaves: primary shoot (PO:0006341) at the developmental stage 2.02-first leaf unfolded (GRO:0007060) (Druka et al. 2006).
+
+To obtain embryo-derived tissue, growth room#2, AN building, SCRI, with the standard laboratory bench positioned in the middle of the room was used to germinate sterilized seeds. Seeds were placed between three layers of wet 3MM filter paper in the 156 10 mm Petri plates. Thirty to fifty seeds per line (per Petri plate) were used. Germination was in the dark, 16 hours at 17 deg C and 8 hours at 12 deg C. After 96 hours, embryo-derived tissue (mesocotyl, coleoptile, and seminal roots) from three grains was dissected and flash frozen in the liquid nitrogen. Germination and collection was repeated two more times. Complete randomization of the Petri plates was done for each germination event. Tissues from all three germinations (collections) were bulked before RNA isolation. Three replicates of the parental cultivars were germinated for each collection.
+
+To obtain seedling leaves, three Microclima 1000 growth chambers (Snijders Scientific B.V., Tilburg, Holland) were used for the experiment. Each cabinet accomodated 40 (13x13 cm) pots. Humidity was set to 70%, with light conditions for 16 hours light at 17C and 8 hours dark at 12C. The cycle started at 10 am with lights on. Light intensity was 337-377 mmol m-2 s-1, measured at the beginning of the experiment, 11 cm from the light source. Measurement was done using Sky Quantium light sensor at 15oC. Plants were placed 55 cm from the light source (from the bulb to the surface of the vermiculite). Ten sterilized seeds per pot were planted and 3 pots per genotype / per cabinet were used. After 12 days, leaf blade and sheath from 5-7 the same size plants was cut off, bulked and flash frozen in the liquid nitrogen.
+
+
+
diff --git a/general/datasets/B30_k_1206_r/acknowledgment.rtf b/general/datasets/B30_k_1206_r/acknowledgment.rtf
new file mode 100644
index 0000000..5d9cc73
--- /dev/null
+++ b/general/datasets/B30_k_1206_r/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Plant maintenance, tissue collection, RNA isolation, and data submission to ArrayExpress was done at SCRI by Arnis Druka with support from BBSRC/SEERAD grant SCR/910/04 The genetics of gene expression in barley' to Michael Kearsey (University of Birmingham, UK) and Robbie Waugh (SCRI, UK). Probe synthesis, labeling and hybridization were performed according to manufacturer’s protocols (Affymetrix, Santa Clara, CA) at the Iowa State University GeneChip Core facility (Rico Caldo and Roger Wise). ArrayExpress (EBI, UK) team members Tim Rayner, Helen Parkinson, and Alvis Brazma are acknowledged for excellent help with data submission to ArrayExpress.
+
diff --git a/general/datasets/B30_k_1206_r/cases.rtf b/general/datasets/B30_k_1206_r/cases.rtf
new file mode 100644
index 0000000..1425413
--- /dev/null
+++ b/general/datasets/B30_k_1206_r/cases.rtf
@@ -0,0 +1,1748 @@
+
+The SM cross was originally made to map barley grain quality traits; Steptoe is high-yielding barley cultivar used for animal feeding, but Morex has good malting barley characteristics (Hayes et al 1993). Many agronomic quality traits have been mapped using this population (for the lists see BeerGenes web-site http://gnome.agrenv.mcgill.ca/bg/).
+
+The sample used in this study consists of 150 Steptoe x Morex doubled haploid recombinant lines (Kleinhofs et al. 1993) was used to obtain embryo-derived tissue. For the seedling leaf tissue a subset of 35 lines was used. This subset was selected based on evenly spaced crossovers along each of seven barley chromosomes. The expression data of 11 DH lines has been removed from both, embryo and leaf, leaving for the analysis 129 lines with embryo expression data and a subset of 30 lines with seedling leaf expression data. The lines were removed from the analysis after error checking; discrepancies with genotyping data were found. We left all 150 lines in the embryo Apr06 data set and the full data set is available from the ArrayExpress. The following table lists line IDs and corresponding CEL file IDs, also indicating:
+1) pedigree; shows the direction of the cross that was used to produce the original F1. The parental plants were given letter codes of A - Z. For example, SM1 was derived from an F1 that was generated by crossing Steptoe plant "B" as a female with Morex plant "F" as a male.
+2) 'minimapper' subset - MINI;
+3) lines that have expression data removed - ERROR:
+
+
+
+
+ | Order # |
+ Line ID |
+ Permanent Oregon ID |
+ Cross direction |
+
+ CEL file names
+ |
+ Mini-mapper set |
+ Error check |
+
+
+ | embryo data-set |
+ leaf data-set |
+ embryo data-set |
+ leaf data-set |
+
+
+ | 1 |
+ SM001 |
+ 2907001 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_82.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 2 |
+ SM002 |
+ 2907002 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_1.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 3 |
+ SM003 |
+ 2907003 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_19.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 4 |
+ SM004 |
+ 2907004 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_3.CEL |
+ 0521-1_SetA1.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 5 |
+ SM005 |
+ 2907005 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_88.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 6 |
+ SM006 |
+ 2907006 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_48.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 7 |
+ SM007 |
+ 2907007 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_35.CEL |
+ 0521-2_SetA2.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 8 |
+ SM009 |
+ 2907009 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_2.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 9 |
+ SM010 |
+ 2907010 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_42.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 10 |
+ SM011 |
+ 2907011 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_10.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 11 |
+ SM012 |
+ 2907012 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_45.CEL |
+ 0521-3_SetA3.CEL |
+ SMmini |
+ ERROR |
+ ERROR |
+
+
+ | 12 |
+ SM013 |
+ 2907013 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_78.CEL |
+ 0521-4_SetA4.CEL |
+ SMmini |
+ ERROR |
+ ERROR |
+
+
+ | 13 |
+ SM014 |
+ 2907014 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_18.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 14 |
+ SM015 |
+ 2907015 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_5.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 15 |
+ SM016 |
+ 2907016 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_21.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 16 |
+ SM020 |
+ 2907020 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_77.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 17 |
+ SM021 |
+ 2907021 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_30.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 18 |
+ SM022 |
+ 2907022 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_31.CEL |
+ 0521-5_SetA5.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 19 |
+ SM023 |
+ 2907023 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_32.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 20 |
+ SM024 |
+ 2907024 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_33.CEL |
+ 0521-6_SetA6.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 21 |
+ SM025 |
+ 2907025 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_34.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 22 |
+ SM027 |
+ 2907027 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_12.CEL |
+ 0521-7_SetA7.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 23 |
+ SM030 |
+ 2907030 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_79.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 24 |
+ SM031 |
+ 2907031 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_16.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 25 |
+ SM032 |
+ 2907032 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_13.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 26 |
+ SM035 |
+ 2907035 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_15.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 27 |
+ SM039 |
+ 2907039 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_41.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 28 |
+ SM040 |
+ 2907040 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_83.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 29 |
+ SM041 |
+ 2907041 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_11_redo.CEL |
+ 0521-8_SetA8.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 30 |
+ SM042 |
+ 2907042 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_57.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 31 |
+ SM043 |
+ 2907043 |
+ Morex/Steptoe(JxE) |
+ AD_SCRI_49.CEL |
+ 0521-9_SetA9.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 32 |
+ SM044 |
+ 2907044 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_50.CEL |
+ 0521-10_SetA10.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 33 |
+ SM045 |
+ 2907045 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_51.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 34 |
+ SM046 |
+ 2907046 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_52.CEL |
+ 0521-11_SetA11.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 35 |
+ SM048 |
+ 2907048 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_53.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 36 |
+ SM050 |
+ 2907050 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_46.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 37 |
+ SM054 |
+ 2907054 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_60.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 38 |
+ SM055 |
+ 2907055 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_55.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 39 |
+ SM056 |
+ 2907056 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_23.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 40 |
+ SM057 |
+ 2907057 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_24.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 41 |
+ SM058 |
+ 2907058 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_22.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 42 |
+ SM059 |
+ 2907059 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_27.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 43 |
+ SM061 |
+ 2907061 |
+ Morex/Steptoe(LxF) |
+ AD_SCRI_81.CEL |
+ 0521-12_SetA12.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 44 |
+ SM062 |
+ 2907062 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_44.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 45 |
+ SM063 |
+ 2907063 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_40.CEL |
+ 0521-13_SetA13.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 46 |
+ SM064 |
+ 2907064 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_87_redo.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 47 |
+ SM065 |
+ 2907065 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_54.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 48 |
+ SM067 |
+ 2907067 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_73.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 49 |
+ SM068 |
+ 2907068 |
+ Steptoe/Morex(OxG) |
+ AD_SCRI_56.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 50 |
+ SM069 |
+ 2907069 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_71.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 51 |
+ SM070 |
+ 2907070 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_64.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 52 |
+ SM071 |
+ 2907071 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_58.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 53 |
+ SM072 |
+ 2907072 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_59.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 54 |
+ SM073 |
+ 2907073 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_74.CEL |
+ 0521-14_SetA14.CEL |
+ SMmini |
+ OK |
+ ERROR |
+
+
+ | 55 |
+ SM074 |
+ 2907074 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_25.CEL |
+ 0521-15_SetA15.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 56 |
+ SM075 |
+ 2907075 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_120.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 57 |
+ SM076 |
+ 2907076 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_112.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 58 |
+ SM077 |
+ 2907077 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_142.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 59 |
+ SM078 |
+ 2907078 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_86.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 60 |
+ SM079 |
+ 2907079 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_153.CEL |
+ 0521-16_SetA16.CEL |
+ SMmini |
+ OK |
+ ERROR |
+
+
+ | 61 |
+ SM080 |
+ 2907080 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_107.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 62 |
+ SM081 |
+ 2907081 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_105.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 63 |
+ SM082 |
+ 2907082 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_97.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 64 |
+ SM083 |
+ 2907083 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_89.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 65 |
+ SM084 |
+ 2907084 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_155.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 66 |
+ SM085 |
+ 2907085 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_149.CEL |
+ 0521-17_SetA17.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 67 |
+ SM087 |
+ 2907087 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_113.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 68 |
+ SM088 |
+ 2907088 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_93.CEL |
+ 0521-18_SetA18.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 69 |
+ SM089 |
+ 2907089 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_148.CEL |
+ 0521-19_SetA19.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 70 |
+ SM091 |
+ 2907091 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_110.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 71 |
+ SM092 |
+ 2907092 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_7.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 72 |
+ SM093 |
+ 2907093 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_122.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 73 |
+ SM094 |
+ 2907094 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_150.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 74 |
+ SM097 |
+ 2907097 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_158.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 75 |
+ SM098 |
+ 2907098 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_121.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 76 |
+ SM099 |
+ 2907099 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_137.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 77 |
+ SM103 |
+ 2907103 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_156.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 78 |
+ SM104 |
+ 2907104 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_70.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 79 |
+ SM105 |
+ 2907105 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_69.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 80 |
+ SM110 |
+ 2907110 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_75.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 81 |
+ SM112 |
+ 2907112 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_84.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 82 |
+ SM116 |
+ 2907116 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_117.CEL |
+ 0521-20_SetA20.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 83 |
+ SM120 |
+ 2907120 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_138.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 84 |
+ SM124 |
+ 2907124 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_146.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 85 |
+ SM125 |
+ 2907125 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_43.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 86 |
+ SM126 |
+ 2907126 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_144_redo.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 87 |
+ SM127 |
+ 2907127 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_129.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 88 |
+ SM129 |
+ 2907129 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_132.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 89 |
+ SM130 |
+ 2907130 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_101.CEL |
+ 0521-21_SetA21.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 90 |
+ SM131 |
+ 2907131 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_102.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 91 |
+ SM132 |
+ 2907132 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_4_redo.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 92 |
+ SM133 |
+ 2907133 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_157.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 93 |
+ SM134 |
+ 2907134 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_159.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 94 |
+ SM135 |
+ 2907135 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_72.CEL |
+ 0521-22_SetA22.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 95 |
+ SM136 |
+ 2907136 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_123.CEL |
+ 0521-23_SetA23.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 96 |
+ SM137 |
+ 2907137 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_39.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 97 |
+ SM139 |
+ 2907139 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_133.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 98 |
+ SM140 |
+ 2907140 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_134.CEL |
+ 0521-24_SetA24.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 99 |
+ SM141 |
+ 2907141 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_136.CEL |
+ 0521-25_SetA25.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 100 |
+ SM142 |
+ 2907142 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_6.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 101 |
+ SM143 |
+ 2907143 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_145.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 102 |
+ SM144 |
+ 2907144 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_103.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 103 |
+ SM145 |
+ 2907145 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_108.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 104 |
+ SM146 |
+ 2907146 |
+ Morex/Steptoe(BxF) |
+ AD_SCRI_91.CEL |
+ 0521-26_SetA26.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 105 |
+ SM147 |
+ 2907147 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_139.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 106 |
+ SM149 |
+ 2907149 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_131.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 107 |
+ SM150 |
+ 2907150 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_37.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 108 |
+ SM151 |
+ 2907151 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_28.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 109 |
+ SM152 |
+ 2907152 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_9_redo.CEL |
+ 0521-27_SetA27.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 110 |
+ SM153 |
+ 2907153 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_135.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 111 |
+ SM154 |
+ 2907154 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_114.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 112 |
+ SM155 |
+ 2907155 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_119.CEL |
+ 0521-28_SetA28.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 113 |
+ SM156 |
+ 2907156 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_140.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 114 |
+ SM157 |
+ 2907157 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_106_redo.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 115 |
+ SM158 |
+ 2907158 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_65.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 116 |
+ SM159 |
+ 2907159 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_168.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 117 |
+ SM160 |
+ 2907160 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_47.CEL |
+ 0521-29_SetA29.CEL |
+ SMmini |
+ OK |
+ ERROR |
+
+
+ | 118 |
+ SM161 |
+ 2907161 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_76.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 119 |
+ SM162 |
+ 2907162 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_147.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 120 |
+ SM164 |
+ 2907164 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_128.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 121 |
+ SM165 |
+ 2907165 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_143.CEL |
+ |
+ |
+ OK |
+ OK |
+
+
+ | 122 |
+ SM166 |
+ 2907166 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_115.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 123 |
+ SM167 |
+ 2907167 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_127.CEL |
+ 0521-30_SetA30.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 124 |
+ SM168 |
+ 2907168 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_130.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 125 |
+ SM169 |
+ 2907169 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_118.CEL |
+ 0521-31_SetA31.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 126 |
+ SM170 |
+ 2907170 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_151.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 127 |
+ SM171 |
+ 2907171 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_165.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 128 |
+ SM172 |
+ 2907172 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_152.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 129 |
+ SM173 |
+ 2907173 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_104.CEL |
+ 0521-32_SetA32.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 130 |
+ SM174 |
+ 2907174 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_154.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 131 |
+ SM176 |
+ 2907176 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_141.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 132 |
+ SM177 |
+ 2907177 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_111.CEL |
+ 0521-33_SetA33.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 133 |
+ SM179 |
+ 2907179 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_166.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 134 |
+ SM180 |
+ 2907180 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_161.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 135 |
+ SM181 |
+ 2907181 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_162.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 136 |
+ SM182 |
+ 2907182 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_163.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 137 |
+ SM183 |
+ 2907183 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_164.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 138 |
+ SM184 |
+ 2907184 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_160.CEL |
+ 0521-34_SetA34.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 139 |
+ SM185 |
+ 2907185 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_167.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 140 |
+ SM186 |
+ 2907186 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_62.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 141 |
+ SM187 |
+ 2907187 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_61.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 142 |
+ SM188 |
+ 2907188 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_63.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 143 |
+ SM189 |
+ 2907189 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_80.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 144 |
+ SM193 |
+ 2907193 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_36.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 145 |
+ SM194 |
+ 2907194 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_29.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 146 |
+ SM196 |
+ 2907196 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_26.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 147 |
+ SM197 |
+ 2907197 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_85.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 148 |
+ SM198 |
+ 2907198 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_8.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 149 |
+ SM199 |
+ 2907199 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_20.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 150 |
+ SM200 |
+ 2907200 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_38.CEL |
+ 0521-35_SetA35.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | parent |
+ Steptoe |
+ |
+ |
+ AD_SCRI_17.CEL |
+ 0521-36_SetA36.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Steptoe |
+ |
+ |
+ AD_SCRI_66.CEL |
+ 0521-37_SetA37.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Steptoe |
+ |
+ |
+ AD_SCRI_68.CEL |
+ 0521-38_SetA38.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Morex |
+ |
+ |
+ AD_SCRI_116.CEL |
+ 0521-39_SetA39.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Morex |
+ |
+ |
+ AD_SCRI_14.CEL |
+ 0521-40_SetA40.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Morex |
+ |
+ |
+ AD_SCRI_67.CEL |
+ 0521-41_SetA41.CEL |
+ |
+ |
+ |
+
+
+
+
+
+
diff --git a/general/datasets/B30_k_1206_r/citation.rtf b/general/datasets/B30_k_1206_r/citation.rtf
new file mode 100644
index 0000000..f6fcdda
--- /dev/null
+++ b/general/datasets/B30_k_1206_r/citation.rtf
@@ -0,0 +1,11 @@
+
+Druka A, Muehlbauer G, Druka I, Caldo R, Baumann U, Rostoks N, Schreiber A, Wise R, Close T, Kleinhofs A, Graner A, Schulman A, Langridge P, Sato K, Hayes P, McNicol J, Marshall D, Waugh R. (2006) An atlas of gene expression from seed to seed through barley development. Funct Integr Genomics, Jul;6(3):202-11.
+
+Kleinhofs A, Kilian A, Saghai Maroof M, Biyashev R, Hayes P, Chen F, Lapitan N, Fenwick A, Blake T, Kanazin V, Ananiev E, Dahleen L, Kudrna D, Bollinger J, Knapp SJ, Liu BH, Sorrells M, Heun M, Franckowiak J, Hoffman D, Skadsen R, Steffenson B (1993) A molecular, isozyme, and morphological map of the barley (Hordeum vulgare) genome. Theor Appl Genet 86:705-712.
+
+Caldo RA, Nettleton D, Wise RP (2004) Interaction-dependent gene expression in Mla-specified response to barley powdery mildew. Plant Cell 16:2514-2528.
+
+Close TJ, Wanamaker SI, Caldo RA, Turner SM, Ashlock DA, Dickerson JA, Wing RA, Muehlbauer GJ, Kleinhofs A, Wise RP. (2004) A new resource for cereal genomics: 22K barley GeneChip comes of age. Plant Physiol 134:960-968.
+
+Hayes PM, Liu BH, Knapp SJ, Chen F, Jones B, Blake T, Franckowiak J, Rasmusson D, Sorrells M, Ullrich SE, Wesenberg D, Kleinhofs A (1993) Quantitative trait locus effects and environmental interaction in a sample of North American barley germplasm. Theor Appl Genet 87:392-401
+
diff --git a/general/datasets/B30_k_1206_r/experiment-design.rtf b/general/datasets/B30_k_1206_r/experiment-design.rtf
new file mode 100644
index 0000000..e743086
--- /dev/null
+++ b/general/datasets/B30_k_1206_r/experiment-design.rtf
@@ -0,0 +1,62 @@
+
+RNA Sample Processing:
+
+Trizol RNA isolation and RNeasy clean up protocol for whole plants (embryo-derived tissue dissected from 4 days old germinating grains) and the seedling leaves (12 days after planting).
+
+
+☠Grind tissue (9 embryos) with a mortar and pestle in liquid nitrogen
+☠Add 5 ml TRIzol (pre-heated to 60oC) to all samples, vortex until all the tissue is thawed, place in the 60oC waterbath..
+☠Incubate samples at 60oC for 10 minutes, vortexing three times.
+☠Centrifuge @ 4000 x rpm @ 4C for 30 minutes (in Eppendorf 5810R).
+☠While centrifuging, label new set of 15 ml tubes
+☠Transfer supernatant to 15 ml centrifuge tube
+☠Add 1 ml of chloroform. Vortex the sample until color shade is uniform at least 5
+seconds, and incubate at room temperature for 5 minutes.
+☠Centrifuge @ 4000 x rpm for 30 minutes @ 4oC.
+☠While centrifuging, label new 15 ml tubes
+☠Collect the upper aqueous layer (there will be about 3 mls) and transfer to a new 15 ml tube.
+☠Add 0.6 volumes (2 ml) of isopropanol, mix gently, incubate at room temperature for 20 minutes.
+☠Centrifuge @ 4000 rpm for 30 minutes @ 4oC.
+☠Wash the pellet with 10 ml of cold 75% ethanol. Swirl & centrifuge at
+4000 rpm for 15 minutes @ 4oC.
+☠Discard supernatant, centrifuge for 5 min, remove the rest of the ethanol
+☠Air-dry the pellet for 10 minutes, inverted on a kimwipe.
+☠Dissolve pellet in 400 ul of DEPC-treated H2O. Resuspend by pipeting up & down a
+few times.
+☠Add 2 ul SuperaseIn. Incubate at 60oC for 10 minutes to resuspend.
+☠Set water bath to 37oC.
+☠Add 50 ul 10X DnaseI Buffer, 45 ul H2O and 5 ul of DnaseI, incubate at 37oC for 1 hr.
+☠Prepare Buffer RLT (Rneasy Clean-up Midi Kit) by adding b-mercaptoethanol (10ul/1ml RLT).
+☠Add 2.0 ml Buffer RLT to the RNA prep and mix thoroughly.
+☠Add 1.4 ml ethanol (96-100%) to the diluted RNA. Mix thoroughly.
+☠Label 15 ml tubes from the kit and place midi columns in them
+☠Apply sample to a Midi column, close tube gently and centrifuge for 20 min at 3000 rpm.
+☠Discard the flow-through.
+☠Add 2.5 ml Buffer RPE to the RNA easy column, close the centrifuge tube gently,
+incubate for 3 min
+☠Centrifuge for 10 min at 3000 rpm. Discard the flow-through.
+☠Add another 2.5 ml Buffer RPE to the RNeasy column. Close the centrifuge tube
+gently, incubate for 3 min
+☠Centrifuge for 10 min at 3000 rpm, remove flow-through
+☠Centrifuge again for another 5 min.
+☠Label new 15 ml tubes from the kit.
+☠Transfer the RNA easy column to a new tube and pipet 250 ul volume of
+RNase-free water directly onto the RNeasy silica-membrane incubate for 1 min
+☠Centrifuge for 5 min at 3000 rpm.
+☠To the same tube add again 250 ul H2O, incubate for 1 min.
+☠Centrifuge for 5 min at 3000 rpm.
+☠Label two sets of 1.5 ml Eppendorf tubes.
+☠Transfer 490 ul to the one tube and 10 ul to another one. Use 10 ul tube for the RNA
+
+Detailed descriptions of these procedures can be found under the ArrayExpress (http://www.ebi.ac.uk/aerep/?) protocol P-MEXP-4631 (Caldo et al. 2004).
+
+Replication and Sample Balance:
+
+3 independent replicates of both parental cultivars Steptoe and Morex were generated for both tissues, embryo and seedling leaf.
+
+Experimental Design and Batch Structure:
+
+
+
+The following are ArrayExpress (http://www.ebi.ac.uk/aerep/?) experiment IDs: E-TABM-111 (leaf, 41 chips) and E-TABM-112 (embryo derived, 156 chips).
+
diff --git a/general/datasets/B30_k_1206_r/experiment-type.rtf b/general/datasets/B30_k_1206_r/experiment-type.rtf
new file mode 100644
index 0000000..585c17b
--- /dev/null
+++ b/general/datasets/B30_k_1206_r/experiment-type.rtf
@@ -0,0 +1 @@
+A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community.
\ No newline at end of file
diff --git a/general/datasets/B30_k_1206_r/notes.rtf b/general/datasets/B30_k_1206_r/notes.rtf
new file mode 100644
index 0000000..46cff8f
--- /dev/null
+++ b/general/datasets/B30_k_1206_r/notes.rtf
@@ -0,0 +1,14 @@
+
+Arnis Druka
+Genetics Programme
+Scottish Crop Research Institute
+Invergowrie, Dundee DD2 5DA
+Angus, Scotland, United Kingdom
+Tel +44 01382 562731
+Fax +44 01382 568587
+adruka@scri.sari.ac.uk
+
+
+
+This text file originally generated by Arnis Druka on May 8, 2006. Modified Aug1 by AD. Entered by RWW Aug 4, 2006. Modified by AD Jan 29, 2007, Feb 01, 2007.
+
diff --git a/general/datasets/B30_k_1206_r/platform.rtf b/general/datasets/B30_k_1206_r/platform.rtf
new file mode 100644
index 0000000..a935318
--- /dev/null
+++ b/general/datasets/B30_k_1206_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix 22K Barley1 GeneChip probe array (http://www.affymetrix.com/products/arrays/specific/barley.affx ; Affymetrix product #900515 GeneChip Barley Genome Array) representing 21,439 non-redundant Barley1 exemplar sequences was derived from worldwide contribution of 350,000 high-quality ESTs from 84 cDNA libraries, in addition to 1,145 barley gene sequences from the National Center for Biotechnology Information non-redundant database (Close et al 2004). Abbreviated annotations were created based on the exemplar sequence homology by Arnis Druka using data from the Harvest (http://harvest.ucr.edu/) data depository.
+
diff --git a/general/datasets/B30_k_1206_r/processing.rtf b/general/datasets/B30_k_1206_r/processing.rtf
new file mode 100644
index 0000000..d8d039a
--- /dev/null
+++ b/general/datasets/B30_k_1206_r/processing.rtf
@@ -0,0 +1,49 @@
+
+
+
+
+ |
+ Types of the expression data-sets
+ |
+
+ Data processing description
+ |
+
+
+ Barley1 Embryo gcRMA SCRI (Dec 06)
+ Barley1 Leaf gcRMA SCRI (Dec 06) |
+
+
+
+ The Affymetrix' CEL files that were generated using MAS 5.0 Suite were imported into the GeneSpring GX 7.3 (Agilent Technologies, Palo Alto, CA) and processed using the RMA algorithm.
+
+
+ |
+
+
+ Barley1 Embryo MAS 5.0 SCRI (Dec 06)
+ Barley1 Leaf MAS 5.0 SCRI (Dec 06) |
+
+
+
+ The MAS 5.0 values were calculated from the DAT files using Affymetrix' MAS 5.0 Suite.
+
+
+ |
+
+
+ Barley1 Embryo0 gcRMA SCRI (Apr 06)
+ Barley1 Leaf gcRMAn SCRI (Dec 06) |
+
+ The Affymetrix' CEL files were imported into the GeneSpring GX 7.3 (Agilent Technologies, Palo Alto, CA) software and processed using the RMA algorithm. Per-chip and per-gene normalization was done following the standard GeneSpring procedure (citation of the GeneSpring normalization description):
+
+
+ - Values below 0.01 were set to 0.01.
+ - Each measurement was divided by the 50.0th percentile of all measurements in that sample.
+ - Each gene was divided by the median of its measurements in all samples. If the median of the raw values was below 10 then each measurement for that gene was divided by 10 if the numerator was above 10, otherwise the measurement was thrown out.
+
+ |
+
+
+
+
diff --git a/general/datasets/B30_k_1206_r/summary.rtf b/general/datasets/B30_k_1206_r/summary.rtf
new file mode 100644
index 0000000..67f4fab
--- /dev/null
+++ b/general/datasets/B30_k_1206_r/summary.rtf
@@ -0,0 +1,5 @@
+Barley1 Leaf MAS 5.0 SCRI (Dec 06) - integrated probe set value for each gene has been calculated using MAS 5.0 algorithm which uses pixel values from both, PM and MM probes. Descriptions of probe set signal calculation can be found on this page below, section 'About Data Processing'.
+
+
+The SCRI barley data set provides estimates of mRNA abundance in doubled haploid recombinant lines of cultivated barley. Embryo-derived tissues at four days after imbibition (150 lines) and seedling leaves at 12 days after imbibition (subset of 34 lines) and three biological replicates of each parental cultivar (Steptoe and Morex) for each tissue were used for the isolation of total RNA and hybridization to the Barley1 22K GeneChip (GEO GPL1340).
+
diff --git a/general/datasets/B30_k_1206_r/tissue.rtf b/general/datasets/B30_k_1206_r/tissue.rtf
new file mode 100644
index 0000000..a8351e8
--- /dev/null
+++ b/general/datasets/B30_k_1206_r/tissue.rtf
@@ -0,0 +1,9 @@
+
+Plant material according to the current plant ontologies: Embryo-derived tissues: whole plant (PO:0000003) at the development stage 1.05-coleoptile emerged from seed (GRO:0007056); Seedling leaves: primary shoot (PO:0006341) at the developmental stage 2.02-first leaf unfolded (GRO:0007060) (Druka et al. 2006).
+
+To obtain embryo-derived tissue, growth room#2, AN building, SCRI, with the standard laboratory bench positioned in the middle of the room was used to germinate sterilized seeds. Seeds were placed between three layers of wet 3MM filter paper in the 156 10 mm Petri plates. Thirty to fifty seeds per line (per Petri plate) were used. Germination was in the dark, 16 hours at 17 deg C and 8 hours at 12 deg C. After 96 hours, embryo-derived tissue (mesocotyl, coleoptile, and seminal roots) from three grains was dissected and flash frozen in the liquid nitrogen. Germination and collection was repeated two more times. Complete randomization of the Petri plates was done for each germination event. Tissues from all three germinations (collections) were bulked before RNA isolation. Three replicates of the parental cultivars were germinated for each collection.
+
+To obtain seedling leaves, three Microclima 1000 growth chambers (Snijders Scientific B.V., Tilburg, Holland) were used for the experiment. Each cabinet accomodated 40 (13x13 cm) pots. Humidity was set to 70%, with light conditions for 16 hours light at 17C and 8 hours dark at 12C. The cycle started at 10 am with lights on. Light intensity was 337-377 mmol m-2 s-1, measured at the beginning of the experiment, 11 cm from the light source. Measurement was done using Sky Quantium light sensor at 15oC. Plants were placed 55 cm from the light source (from the bulb to the surface of the vermiculite). Ten sterilized seeds per pot were planted and 3 pots per genotype / per cabinet were used. After 12 days, leaf blade and sheath from 5-7 the same size plants was cut off, bulked and flash frozen in the liquid nitrogen.
+
+
+
diff --git a/general/datasets/B30_k_1206_rn/acknowledgment.rtf b/general/datasets/B30_k_1206_rn/acknowledgment.rtf
new file mode 100644
index 0000000..5d9cc73
--- /dev/null
+++ b/general/datasets/B30_k_1206_rn/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Plant maintenance, tissue collection, RNA isolation, and data submission to ArrayExpress was done at SCRI by Arnis Druka with support from BBSRC/SEERAD grant SCR/910/04 The genetics of gene expression in barley' to Michael Kearsey (University of Birmingham, UK) and Robbie Waugh (SCRI, UK). Probe synthesis, labeling and hybridization were performed according to manufacturer’s protocols (Affymetrix, Santa Clara, CA) at the Iowa State University GeneChip Core facility (Rico Caldo and Roger Wise). ArrayExpress (EBI, UK) team members Tim Rayner, Helen Parkinson, and Alvis Brazma are acknowledged for excellent help with data submission to ArrayExpress.
+
diff --git a/general/datasets/B30_k_1206_rn/cases.rtf b/general/datasets/B30_k_1206_rn/cases.rtf
new file mode 100644
index 0000000..1425413
--- /dev/null
+++ b/general/datasets/B30_k_1206_rn/cases.rtf
@@ -0,0 +1,1748 @@
+
+The SM cross was originally made to map barley grain quality traits; Steptoe is high-yielding barley cultivar used for animal feeding, but Morex has good malting barley characteristics (Hayes et al 1993). Many agronomic quality traits have been mapped using this population (for the lists see BeerGenes web-site http://gnome.agrenv.mcgill.ca/bg/).
+
+The sample used in this study consists of 150 Steptoe x Morex doubled haploid recombinant lines (Kleinhofs et al. 1993) was used to obtain embryo-derived tissue. For the seedling leaf tissue a subset of 35 lines was used. This subset was selected based on evenly spaced crossovers along each of seven barley chromosomes. The expression data of 11 DH lines has been removed from both, embryo and leaf, leaving for the analysis 129 lines with embryo expression data and a subset of 30 lines with seedling leaf expression data. The lines were removed from the analysis after error checking; discrepancies with genotyping data were found. We left all 150 lines in the embryo Apr06 data set and the full data set is available from the ArrayExpress. The following table lists line IDs and corresponding CEL file IDs, also indicating:
+1) pedigree; shows the direction of the cross that was used to produce the original F1. The parental plants were given letter codes of A - Z. For example, SM1 was derived from an F1 that was generated by crossing Steptoe plant "B" as a female with Morex plant "F" as a male.
+2) 'minimapper' subset - MINI;
+3) lines that have expression data removed - ERROR:
+
+
+
+
+ | Order # |
+ Line ID |
+ Permanent Oregon ID |
+ Cross direction |
+
+ CEL file names
+ |
+ Mini-mapper set |
+ Error check |
+
+
+ | embryo data-set |
+ leaf data-set |
+ embryo data-set |
+ leaf data-set |
+
+
+ | 1 |
+ SM001 |
+ 2907001 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_82.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 2 |
+ SM002 |
+ 2907002 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_1.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 3 |
+ SM003 |
+ 2907003 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_19.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 4 |
+ SM004 |
+ 2907004 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_3.CEL |
+ 0521-1_SetA1.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 5 |
+ SM005 |
+ 2907005 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_88.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 6 |
+ SM006 |
+ 2907006 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_48.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 7 |
+ SM007 |
+ 2907007 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_35.CEL |
+ 0521-2_SetA2.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 8 |
+ SM009 |
+ 2907009 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_2.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 9 |
+ SM010 |
+ 2907010 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_42.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 10 |
+ SM011 |
+ 2907011 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_10.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 11 |
+ SM012 |
+ 2907012 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_45.CEL |
+ 0521-3_SetA3.CEL |
+ SMmini |
+ ERROR |
+ ERROR |
+
+
+ | 12 |
+ SM013 |
+ 2907013 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_78.CEL |
+ 0521-4_SetA4.CEL |
+ SMmini |
+ ERROR |
+ ERROR |
+
+
+ | 13 |
+ SM014 |
+ 2907014 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_18.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 14 |
+ SM015 |
+ 2907015 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_5.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 15 |
+ SM016 |
+ 2907016 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_21.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 16 |
+ SM020 |
+ 2907020 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_77.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 17 |
+ SM021 |
+ 2907021 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_30.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 18 |
+ SM022 |
+ 2907022 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_31.CEL |
+ 0521-5_SetA5.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 19 |
+ SM023 |
+ 2907023 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_32.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 20 |
+ SM024 |
+ 2907024 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_33.CEL |
+ 0521-6_SetA6.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 21 |
+ SM025 |
+ 2907025 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_34.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 22 |
+ SM027 |
+ 2907027 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_12.CEL |
+ 0521-7_SetA7.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 23 |
+ SM030 |
+ 2907030 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_79.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 24 |
+ SM031 |
+ 2907031 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_16.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 25 |
+ SM032 |
+ 2907032 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_13.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 26 |
+ SM035 |
+ 2907035 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_15.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 27 |
+ SM039 |
+ 2907039 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_41.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 28 |
+ SM040 |
+ 2907040 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_83.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 29 |
+ SM041 |
+ 2907041 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_11_redo.CEL |
+ 0521-8_SetA8.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 30 |
+ SM042 |
+ 2907042 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_57.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 31 |
+ SM043 |
+ 2907043 |
+ Morex/Steptoe(JxE) |
+ AD_SCRI_49.CEL |
+ 0521-9_SetA9.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 32 |
+ SM044 |
+ 2907044 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_50.CEL |
+ 0521-10_SetA10.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 33 |
+ SM045 |
+ 2907045 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_51.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 34 |
+ SM046 |
+ 2907046 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_52.CEL |
+ 0521-11_SetA11.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 35 |
+ SM048 |
+ 2907048 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_53.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 36 |
+ SM050 |
+ 2907050 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_46.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 37 |
+ SM054 |
+ 2907054 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_60.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 38 |
+ SM055 |
+ 2907055 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_55.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 39 |
+ SM056 |
+ 2907056 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_23.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 40 |
+ SM057 |
+ 2907057 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_24.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 41 |
+ SM058 |
+ 2907058 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_22.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 42 |
+ SM059 |
+ 2907059 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_27.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 43 |
+ SM061 |
+ 2907061 |
+ Morex/Steptoe(LxF) |
+ AD_SCRI_81.CEL |
+ 0521-12_SetA12.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 44 |
+ SM062 |
+ 2907062 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_44.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 45 |
+ SM063 |
+ 2907063 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_40.CEL |
+ 0521-13_SetA13.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 46 |
+ SM064 |
+ 2907064 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_87_redo.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 47 |
+ SM065 |
+ 2907065 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_54.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 48 |
+ SM067 |
+ 2907067 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_73.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 49 |
+ SM068 |
+ 2907068 |
+ Steptoe/Morex(OxG) |
+ AD_SCRI_56.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 50 |
+ SM069 |
+ 2907069 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_71.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 51 |
+ SM070 |
+ 2907070 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_64.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 52 |
+ SM071 |
+ 2907071 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_58.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 53 |
+ SM072 |
+ 2907072 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_59.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 54 |
+ SM073 |
+ 2907073 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_74.CEL |
+ 0521-14_SetA14.CEL |
+ SMmini |
+ OK |
+ ERROR |
+
+
+ | 55 |
+ SM074 |
+ 2907074 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_25.CEL |
+ 0521-15_SetA15.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 56 |
+ SM075 |
+ 2907075 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_120.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 57 |
+ SM076 |
+ 2907076 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_112.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 58 |
+ SM077 |
+ 2907077 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_142.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 59 |
+ SM078 |
+ 2907078 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_86.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 60 |
+ SM079 |
+ 2907079 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_153.CEL |
+ 0521-16_SetA16.CEL |
+ SMmini |
+ OK |
+ ERROR |
+
+
+ | 61 |
+ SM080 |
+ 2907080 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_107.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 62 |
+ SM081 |
+ 2907081 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_105.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 63 |
+ SM082 |
+ 2907082 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_97.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 64 |
+ SM083 |
+ 2907083 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_89.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 65 |
+ SM084 |
+ 2907084 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_155.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 66 |
+ SM085 |
+ 2907085 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_149.CEL |
+ 0521-17_SetA17.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 67 |
+ SM087 |
+ 2907087 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_113.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 68 |
+ SM088 |
+ 2907088 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_93.CEL |
+ 0521-18_SetA18.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 69 |
+ SM089 |
+ 2907089 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_148.CEL |
+ 0521-19_SetA19.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 70 |
+ SM091 |
+ 2907091 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_110.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 71 |
+ SM092 |
+ 2907092 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_7.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 72 |
+ SM093 |
+ 2907093 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_122.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 73 |
+ SM094 |
+ 2907094 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_150.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 74 |
+ SM097 |
+ 2907097 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_158.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 75 |
+ SM098 |
+ 2907098 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_121.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 76 |
+ SM099 |
+ 2907099 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_137.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 77 |
+ SM103 |
+ 2907103 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_156.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 78 |
+ SM104 |
+ 2907104 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_70.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 79 |
+ SM105 |
+ 2907105 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_69.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 80 |
+ SM110 |
+ 2907110 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_75.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 81 |
+ SM112 |
+ 2907112 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_84.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 82 |
+ SM116 |
+ 2907116 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_117.CEL |
+ 0521-20_SetA20.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 83 |
+ SM120 |
+ 2907120 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_138.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 84 |
+ SM124 |
+ 2907124 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_146.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 85 |
+ SM125 |
+ 2907125 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_43.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 86 |
+ SM126 |
+ 2907126 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_144_redo.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 87 |
+ SM127 |
+ 2907127 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_129.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 88 |
+ SM129 |
+ 2907129 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_132.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 89 |
+ SM130 |
+ 2907130 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_101.CEL |
+ 0521-21_SetA21.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 90 |
+ SM131 |
+ 2907131 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_102.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 91 |
+ SM132 |
+ 2907132 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_4_redo.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 92 |
+ SM133 |
+ 2907133 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_157.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 93 |
+ SM134 |
+ 2907134 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_159.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 94 |
+ SM135 |
+ 2907135 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_72.CEL |
+ 0521-22_SetA22.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 95 |
+ SM136 |
+ 2907136 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_123.CEL |
+ 0521-23_SetA23.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 96 |
+ SM137 |
+ 2907137 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_39.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 97 |
+ SM139 |
+ 2907139 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_133.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 98 |
+ SM140 |
+ 2907140 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_134.CEL |
+ 0521-24_SetA24.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 99 |
+ SM141 |
+ 2907141 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_136.CEL |
+ 0521-25_SetA25.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 100 |
+ SM142 |
+ 2907142 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_6.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 101 |
+ SM143 |
+ 2907143 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_145.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 102 |
+ SM144 |
+ 2907144 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_103.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 103 |
+ SM145 |
+ 2907145 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_108.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 104 |
+ SM146 |
+ 2907146 |
+ Morex/Steptoe(BxF) |
+ AD_SCRI_91.CEL |
+ 0521-26_SetA26.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 105 |
+ SM147 |
+ 2907147 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_139.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 106 |
+ SM149 |
+ 2907149 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_131.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 107 |
+ SM150 |
+ 2907150 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_37.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 108 |
+ SM151 |
+ 2907151 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_28.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 109 |
+ SM152 |
+ 2907152 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_9_redo.CEL |
+ 0521-27_SetA27.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 110 |
+ SM153 |
+ 2907153 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_135.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 111 |
+ SM154 |
+ 2907154 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_114.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 112 |
+ SM155 |
+ 2907155 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_119.CEL |
+ 0521-28_SetA28.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 113 |
+ SM156 |
+ 2907156 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_140.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 114 |
+ SM157 |
+ 2907157 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_106_redo.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 115 |
+ SM158 |
+ 2907158 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_65.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 116 |
+ SM159 |
+ 2907159 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_168.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 117 |
+ SM160 |
+ 2907160 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_47.CEL |
+ 0521-29_SetA29.CEL |
+ SMmini |
+ OK |
+ ERROR |
+
+
+ | 118 |
+ SM161 |
+ 2907161 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_76.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 119 |
+ SM162 |
+ 2907162 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_147.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 120 |
+ SM164 |
+ 2907164 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_128.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 121 |
+ SM165 |
+ 2907165 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_143.CEL |
+ |
+ |
+ OK |
+ OK |
+
+
+ | 122 |
+ SM166 |
+ 2907166 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_115.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 123 |
+ SM167 |
+ 2907167 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_127.CEL |
+ 0521-30_SetA30.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 124 |
+ SM168 |
+ 2907168 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_130.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 125 |
+ SM169 |
+ 2907169 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_118.CEL |
+ 0521-31_SetA31.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 126 |
+ SM170 |
+ 2907170 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_151.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 127 |
+ SM171 |
+ 2907171 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_165.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 128 |
+ SM172 |
+ 2907172 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_152.CEL |
+ |
+ |
+ ERROR |
+ |
+
+
+ | 129 |
+ SM173 |
+ 2907173 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_104.CEL |
+ 0521-32_SetA32.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 130 |
+ SM174 |
+ 2907174 |
+ Steptoe/Morex(BxH) |
+ AD_SCRI_154.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 131 |
+ SM176 |
+ 2907176 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_141.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 132 |
+ SM177 |
+ 2907177 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_111.CEL |
+ 0521-33_SetA33.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 133 |
+ SM179 |
+ 2907179 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_166.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 134 |
+ SM180 |
+ 2907180 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_161.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 135 |
+ SM181 |
+ 2907181 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_162.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 136 |
+ SM182 |
+ 2907182 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_163.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 137 |
+ SM183 |
+ 2907183 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_164.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 138 |
+ SM184 |
+ 2907184 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_160.CEL |
+ 0521-34_SetA34.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | 139 |
+ SM185 |
+ 2907185 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_167.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 140 |
+ SM186 |
+ 2907186 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_62.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 141 |
+ SM187 |
+ 2907187 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_61.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 142 |
+ SM188 |
+ 2907188 |
+ Morex/Steptoe(CxF) |
+ AD_SCRI_63.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 143 |
+ SM189 |
+ 2907189 |
+ Steptoe/Morex(QxG) |
+ AD_SCRI_80.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 144 |
+ SM193 |
+ 2907193 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_36.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 145 |
+ SM194 |
+ 2907194 |
+ Steptoe/Morex(OxJ) |
+ AD_SCRI_29.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 146 |
+ SM196 |
+ 2907196 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_26.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 147 |
+ SM197 |
+ 2907197 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_85.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 148 |
+ SM198 |
+ 2907198 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_8.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 149 |
+ SM199 |
+ 2907199 |
+ Steptoe/Morex(BxF) |
+ AD_SCRI_20.CEL |
+ |
+ |
+ OK |
+ |
+
+
+ | 150 |
+ SM200 |
+ 2907200 |
+ Morex/Steptoe(IxE) |
+ AD_SCRI_38.CEL |
+ 0521-35_SetA35.CEL |
+ SMmini |
+ OK |
+ OK |
+
+
+ | parent |
+ Steptoe |
+ |
+ |
+ AD_SCRI_17.CEL |
+ 0521-36_SetA36.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Steptoe |
+ |
+ |
+ AD_SCRI_66.CEL |
+ 0521-37_SetA37.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Steptoe |
+ |
+ |
+ AD_SCRI_68.CEL |
+ 0521-38_SetA38.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Morex |
+ |
+ |
+ AD_SCRI_116.CEL |
+ 0521-39_SetA39.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Morex |
+ |
+ |
+ AD_SCRI_14.CEL |
+ 0521-40_SetA40.CEL |
+ |
+ |
+ |
+
+
+ | parent |
+ Morex |
+ |
+ |
+ AD_SCRI_67.CEL |
+ 0521-41_SetA41.CEL |
+ |
+ |
+ |
+
+
+
+
+
+
diff --git a/general/datasets/B30_k_1206_rn/citation.rtf b/general/datasets/B30_k_1206_rn/citation.rtf
new file mode 100644
index 0000000..f6fcdda
--- /dev/null
+++ b/general/datasets/B30_k_1206_rn/citation.rtf
@@ -0,0 +1,11 @@
+
+Druka A, Muehlbauer G, Druka I, Caldo R, Baumann U, Rostoks N, Schreiber A, Wise R, Close T, Kleinhofs A, Graner A, Schulman A, Langridge P, Sato K, Hayes P, McNicol J, Marshall D, Waugh R. (2006) An atlas of gene expression from seed to seed through barley development. Funct Integr Genomics, Jul;6(3):202-11.
+
+Kleinhofs A, Kilian A, Saghai Maroof M, Biyashev R, Hayes P, Chen F, Lapitan N, Fenwick A, Blake T, Kanazin V, Ananiev E, Dahleen L, Kudrna D, Bollinger J, Knapp SJ, Liu BH, Sorrells M, Heun M, Franckowiak J, Hoffman D, Skadsen R, Steffenson B (1993) A molecular, isozyme, and morphological map of the barley (Hordeum vulgare) genome. Theor Appl Genet 86:705-712.
+
+Caldo RA, Nettleton D, Wise RP (2004) Interaction-dependent gene expression in Mla-specified response to barley powdery mildew. Plant Cell 16:2514-2528.
+
+Close TJ, Wanamaker SI, Caldo RA, Turner SM, Ashlock DA, Dickerson JA, Wing RA, Muehlbauer GJ, Kleinhofs A, Wise RP. (2004) A new resource for cereal genomics: 22K barley GeneChip comes of age. Plant Physiol 134:960-968.
+
+Hayes PM, Liu BH, Knapp SJ, Chen F, Jones B, Blake T, Franckowiak J, Rasmusson D, Sorrells M, Ullrich SE, Wesenberg D, Kleinhofs A (1993) Quantitative trait locus effects and environmental interaction in a sample of North American barley germplasm. Theor Appl Genet 87:392-401
+
diff --git a/general/datasets/B30_k_1206_rn/experiment-design.rtf b/general/datasets/B30_k_1206_rn/experiment-design.rtf
new file mode 100644
index 0000000..e743086
--- /dev/null
+++ b/general/datasets/B30_k_1206_rn/experiment-design.rtf
@@ -0,0 +1,62 @@
+
+RNA Sample Processing:
+
+Trizol RNA isolation and RNeasy clean up protocol for whole plants (embryo-derived tissue dissected from 4 days old germinating grains) and the seedling leaves (12 days after planting).
+
+
+☠Grind tissue (9 embryos) with a mortar and pestle in liquid nitrogen
+☠Add 5 ml TRIzol (pre-heated to 60oC) to all samples, vortex until all the tissue is thawed, place in the 60oC waterbath..
+☠Incubate samples at 60oC for 10 minutes, vortexing three times.
+☠Centrifuge @ 4000 x rpm @ 4C for 30 minutes (in Eppendorf 5810R).
+☠While centrifuging, label new set of 15 ml tubes
+☠Transfer supernatant to 15 ml centrifuge tube
+☠Add 1 ml of chloroform. Vortex the sample until color shade is uniform at least 5
+seconds, and incubate at room temperature for 5 minutes.
+☠Centrifuge @ 4000 x rpm for 30 minutes @ 4oC.
+☠While centrifuging, label new 15 ml tubes
+☠Collect the upper aqueous layer (there will be about 3 mls) and transfer to a new 15 ml tube.
+☠Add 0.6 volumes (2 ml) of isopropanol, mix gently, incubate at room temperature for 20 minutes.
+☠Centrifuge @ 4000 rpm for 30 minutes @ 4oC.
+☠Wash the pellet with 10 ml of cold 75% ethanol. Swirl & centrifuge at
+4000 rpm for 15 minutes @ 4oC.
+☠Discard supernatant, centrifuge for 5 min, remove the rest of the ethanol
+☠Air-dry the pellet for 10 minutes, inverted on a kimwipe.
+☠Dissolve pellet in 400 ul of DEPC-treated H2O. Resuspend by pipeting up & down a
+few times.
+☠Add 2 ul SuperaseIn. Incubate at 60oC for 10 minutes to resuspend.
+☠Set water bath to 37oC.
+☠Add 50 ul 10X DnaseI Buffer, 45 ul H2O and 5 ul of DnaseI, incubate at 37oC for 1 hr.
+☠Prepare Buffer RLT (Rneasy Clean-up Midi Kit) by adding b-mercaptoethanol (10ul/1ml RLT).
+☠Add 2.0 ml Buffer RLT to the RNA prep and mix thoroughly.
+☠Add 1.4 ml ethanol (96-100%) to the diluted RNA. Mix thoroughly.
+☠Label 15 ml tubes from the kit and place midi columns in them
+☠Apply sample to a Midi column, close tube gently and centrifuge for 20 min at 3000 rpm.
+☠Discard the flow-through.
+☠Add 2.5 ml Buffer RPE to the RNA easy column, close the centrifuge tube gently,
+incubate for 3 min
+☠Centrifuge for 10 min at 3000 rpm. Discard the flow-through.
+☠Add another 2.5 ml Buffer RPE to the RNeasy column. Close the centrifuge tube
+gently, incubate for 3 min
+☠Centrifuge for 10 min at 3000 rpm, remove flow-through
+☠Centrifuge again for another 5 min.
+☠Label new 15 ml tubes from the kit.
+☠Transfer the RNA easy column to a new tube and pipet 250 ul volume of
+RNase-free water directly onto the RNeasy silica-membrane incubate for 1 min
+☠Centrifuge for 5 min at 3000 rpm.
+☠To the same tube add again 250 ul H2O, incubate for 1 min.
+☠Centrifuge for 5 min at 3000 rpm.
+☠Label two sets of 1.5 ml Eppendorf tubes.
+☠Transfer 490 ul to the one tube and 10 ul to another one. Use 10 ul tube for the RNA
+
+Detailed descriptions of these procedures can be found under the ArrayExpress (http://www.ebi.ac.uk/aerep/?) protocol P-MEXP-4631 (Caldo et al. 2004).
+
+Replication and Sample Balance:
+
+3 independent replicates of both parental cultivars Steptoe and Morex were generated for both tissues, embryo and seedling leaf.
+
+Experimental Design and Batch Structure:
+
+
+
+The following are ArrayExpress (http://www.ebi.ac.uk/aerep/?) experiment IDs: E-TABM-111 (leaf, 41 chips) and E-TABM-112 (embryo derived, 156 chips).
+
diff --git a/general/datasets/B30_k_1206_rn/experiment-type.rtf b/general/datasets/B30_k_1206_rn/experiment-type.rtf
new file mode 100644
index 0000000..585c17b
--- /dev/null
+++ b/general/datasets/B30_k_1206_rn/experiment-type.rtf
@@ -0,0 +1 @@
+A typical genetical genomics experiment results in four separate data sets; genotype, gene expression, higher-order phenotypic data and metadata that describe the protocols, processing and the array platform. Used in concert, these data sets provide the opportunity to perform genetic analysis at a systems level. Their predictive power is largely determined by the gene expression dataset where tens of millions of data points can be generated using currently available mRNA profiling technologies. Such large, multidimensional data sets often have value beyond that extracted during their initial analysis and interpretation, particularly if conducted on widely distributed reference genetic materials. Besides quality and scale, access to the data is of primary importance as accessibility potentially allows the extraction of considerable added value from the same primary dataset by the wider research community. Although the number of genetical genomics experiments in different plant species is rapidly increasing, none to date has been presented in a form that allows quick and efficient on-line testing for possible associations between genes, loci and traits of interest by an entire research community.
\ No newline at end of file
diff --git a/general/datasets/B30_k_1206_rn/notes.rtf b/general/datasets/B30_k_1206_rn/notes.rtf
new file mode 100644
index 0000000..46cff8f
--- /dev/null
+++ b/general/datasets/B30_k_1206_rn/notes.rtf
@@ -0,0 +1,14 @@
+
+Arnis Druka
+Genetics Programme
+Scottish Crop Research Institute
+Invergowrie, Dundee DD2 5DA
+Angus, Scotland, United Kingdom
+Tel +44 01382 562731
+Fax +44 01382 568587
+adruka@scri.sari.ac.uk
+
+
+
+This text file originally generated by Arnis Druka on May 8, 2006. Modified Aug1 by AD. Entered by RWW Aug 4, 2006. Modified by AD Jan 29, 2007, Feb 01, 2007.
+
diff --git a/general/datasets/B30_k_1206_rn/platform.rtf b/general/datasets/B30_k_1206_rn/platform.rtf
new file mode 100644
index 0000000..a935318
--- /dev/null
+++ b/general/datasets/B30_k_1206_rn/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix 22K Barley1 GeneChip probe array (http://www.affymetrix.com/products/arrays/specific/barley.affx ; Affymetrix product #900515 GeneChip Barley Genome Array) representing 21,439 non-redundant Barley1 exemplar sequences was derived from worldwide contribution of 350,000 high-quality ESTs from 84 cDNA libraries, in addition to 1,145 barley gene sequences from the National Center for Biotechnology Information non-redundant database (Close et al 2004). Abbreviated annotations were created based on the exemplar sequence homology by Arnis Druka using data from the Harvest (http://harvest.ucr.edu/) data depository.
+
diff --git a/general/datasets/B30_k_1206_rn/processing.rtf b/general/datasets/B30_k_1206_rn/processing.rtf
new file mode 100644
index 0000000..d8d039a
--- /dev/null
+++ b/general/datasets/B30_k_1206_rn/processing.rtf
@@ -0,0 +1,49 @@
+
+
+
+
+ |
+ Types of the expression data-sets
+ |
+
+ Data processing description
+ |
+
+
+ Barley1 Embryo gcRMA SCRI (Dec 06)
+ Barley1 Leaf gcRMA SCRI (Dec 06) |
+
+
+
+ The Affymetrix' CEL files that were generated using MAS 5.0 Suite were imported into the GeneSpring GX 7.3 (Agilent Technologies, Palo Alto, CA) and processed using the RMA algorithm.
+
+
+ |
+
+
+ Barley1 Embryo MAS 5.0 SCRI (Dec 06)
+ Barley1 Leaf MAS 5.0 SCRI (Dec 06) |
+
+
+
+ The MAS 5.0 values were calculated from the DAT files using Affymetrix' MAS 5.0 Suite.
+
+
+ |
+
+
+ Barley1 Embryo0 gcRMA SCRI (Apr 06)
+ Barley1 Leaf gcRMAn SCRI (Dec 06) |
+
+ The Affymetrix' CEL files were imported into the GeneSpring GX 7.3 (Agilent Technologies, Palo Alto, CA) software and processed using the RMA algorithm. Per-chip and per-gene normalization was done following the standard GeneSpring procedure (citation of the GeneSpring normalization description):
+
+
+ - Values below 0.01 were set to 0.01.
+ - Each measurement was divided by the 50.0th percentile of all measurements in that sample.
+ - Each gene was divided by the median of its measurements in all samples. If the median of the raw values was below 10 then each measurement for that gene was divided by 10 if the numerator was above 10, otherwise the measurement was thrown out.
+
+ |
+
+
+
+
diff --git a/general/datasets/B30_k_1206_rn/summary.rtf b/general/datasets/B30_k_1206_rn/summary.rtf
new file mode 100644
index 0000000..67f4fab
--- /dev/null
+++ b/general/datasets/B30_k_1206_rn/summary.rtf
@@ -0,0 +1,5 @@
+Barley1 Leaf MAS 5.0 SCRI (Dec 06) - integrated probe set value for each gene has been calculated using MAS 5.0 algorithm which uses pixel values from both, PM and MM probes. Descriptions of probe set signal calculation can be found on this page below, section 'About Data Processing'.
+
+
+The SCRI barley data set provides estimates of mRNA abundance in doubled haploid recombinant lines of cultivated barley. Embryo-derived tissues at four days after imbibition (150 lines) and seedling leaves at 12 days after imbibition (subset of 34 lines) and three biological replicates of each parental cultivar (Steptoe and Morex) for each tissue were used for the isolation of total RNA and hybridization to the Barley1 22K GeneChip (GEO GPL1340).
+
diff --git a/general/datasets/B30_k_1206_rn/tissue.rtf b/general/datasets/B30_k_1206_rn/tissue.rtf
new file mode 100644
index 0000000..a8351e8
--- /dev/null
+++ b/general/datasets/B30_k_1206_rn/tissue.rtf
@@ -0,0 +1,9 @@
+
+Plant material according to the current plant ontologies: Embryo-derived tissues: whole plant (PO:0000003) at the development stage 1.05-coleoptile emerged from seed (GRO:0007056); Seedling leaves: primary shoot (PO:0006341) at the developmental stage 2.02-first leaf unfolded (GRO:0007060) (Druka et al. 2006).
+
+To obtain embryo-derived tissue, growth room#2, AN building, SCRI, with the standard laboratory bench positioned in the middle of the room was used to germinate sterilized seeds. Seeds were placed between three layers of wet 3MM filter paper in the 156 10 mm Petri plates. Thirty to fifty seeds per line (per Petri plate) were used. Germination was in the dark, 16 hours at 17 deg C and 8 hours at 12 deg C. After 96 hours, embryo-derived tissue (mesocotyl, coleoptile, and seminal roots) from three grains was dissected and flash frozen in the liquid nitrogen. Germination and collection was repeated two more times. Complete randomization of the Petri plates was done for each germination event. Tissues from all three germinations (collections) were bulked before RNA isolation. Three replicates of the parental cultivars were germinated for each collection.
+
+To obtain seedling leaves, three Microclima 1000 growth chambers (Snijders Scientific B.V., Tilburg, Holland) were used for the experiment. Each cabinet accomodated 40 (13x13 cm) pots. Humidity was set to 70%, with light conditions for 16 hours light at 17C and 8 hours dark at 12C. The cycle started at 10 am with lights on. Light intensity was 337-377 mmol m-2 s-1, measured at the beginning of the experiment, 11 cm from the light source. Measurement was done using Sky Quantium light sensor at 15oC. Plants were placed 55 cm from the light source (from the bulb to the surface of the vermiculite). Ten sterilized seeds per pot were planted and 3 pots per genotype / per cabinet were used. After 12 days, leaf blade and sheath from 5-7 the same size plants was cut off, bulked and flash frozen in the liquid nitrogen.
+
+
+
diff --git a/general/datasets/B6D2ONCILM_0412/summary.rtf b/general/datasets/B6D2ONCILM_0412/summary.rtf
deleted file mode 100644
index fbe3924..0000000
--- a/general/datasets/B6D2ONCILM_0412/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 143, Name: B6D2 ONC Retina (April 2012) RankInv
\ No newline at end of file
diff --git a/general/datasets/B6D2RIPublish/specifics.rtf b/general/datasets/B6D2RIPublish/specifics.rtf
deleted file mode 100644
index 323c8d7..0000000
--- a/general/datasets/B6D2RIPublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Mapping Crosses (individual cases)
\ No newline at end of file
diff --git a/general/datasets/B6D2RIPublish/summary.rtf b/general/datasets/B6D2RIPublish/summary.rtf
deleted file mode 100644
index f15c54b..0000000
--- a/general/datasets/B6D2RIPublish/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-BXD Aged Hippocampus eQTL (Dresden UTHSC 2015)
diff --git a/general/datasets/B6btbrf2publish/acknowledgment.rtf b/general/datasets/B6btbrf2publish/acknowledgment.rtf
new file mode 100644
index 0000000..1405628
--- /dev/null
+++ b/general/datasets/B6btbrf2publish/acknowledgment.rtf
@@ -0,0 +1 @@
+This project was supported in part by NIH/NIDDK 5803701, NIH/NIDDK 66369-01 and American Diabetes Association 7-03-IG-01 to Alan D. Attie, USDA CSREES grants to the University of Wisconsin-Madison to Brian S. Yandell, and HHMI grant A-53-1200-4 to Christina Kendziorski.
diff --git a/general/datasets/B6btbrf2publish/summary.rtf b/general/datasets/B6btbrf2publish/summary.rtf
new file mode 100644
index 0000000..ec934ba
--- /dev/null
+++ b/general/datasets/B6btbrf2publish/summary.rtf
@@ -0,0 +1,5 @@
+The Phenotypes database of August 2005 provides quantitative trait data for 24 phenotypes from a set of 110 F2 animals generated by crossing strains C57BL/6J and BTBR. All F2s are homozygous for the obese (ob) allele of leptin (Lep) on Chr 6. Data were generated at the University of Wisconsin by Alan Attie and colleagues (Stoehr et al. 2000; Lan et al. 2003). This data release complement the liver transcriptome data described in the paper of Lan and colleagues (in submission, 2005). Traits include body weight, insulin and blood sugar levels, and rtPCR results. To review a complete list of the 24 phenotypes simply type in the wildcard character * in the ANY search field. This data set includes values for all 60 selected animals whose liver mRNA has been quantified using the Affymetrix M430A and B arrays, as well as an addition 50 F2 ob/ob animals from the same cross.
+
+The 110 F2-ob/ob mice were chosen from a larger mapping panel that we created to map diabetes related physiological phenotypes (Stoehr et al. 2000). All 110 of this subsetwere used to map mRNA abundance traits derived by quantitative real-time RT-PCR (Lan et al. 2003).
+
+
diff --git a/general/datasets/B6d2oncilm_0412/experiment-type.rtf b/general/datasets/B6d2oncilm_0412/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/B6d2oncilm_0412/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/B6d2oncilm_0412/summary.rtf b/general/datasets/B6d2oncilm_0412/summary.rtf
new file mode 100644
index 0000000..fbe3924
--- /dev/null
+++ b/general/datasets/B6d2oncilm_0412/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 143, Name: B6D2 ONC Retina (April 2012) RankInv
\ No newline at end of file
diff --git a/general/datasets/B6d2ripublish/specifics.rtf b/general/datasets/B6d2ripublish/specifics.rtf
new file mode 100644
index 0000000..323c8d7
--- /dev/null
+++ b/general/datasets/B6d2ripublish/specifics.rtf
@@ -0,0 +1 @@
+Mapping Crosses (individual cases)
\ No newline at end of file
diff --git a/general/datasets/B6d2ripublish/summary.rtf b/general/datasets/B6d2ripublish/summary.rtf
new file mode 100644
index 0000000..f15c54b
--- /dev/null
+++ b/general/datasets/B6d2ripublish/summary.rtf
@@ -0,0 +1 @@
+BXD Aged Hippocampus eQTL (Dresden UTHSC 2015)
diff --git a/general/datasets/BXDGeno/acknowledgment.rtf b/general/datasets/BXDGeno/acknowledgment.rtf
deleted file mode 100644
index d291eb6..0000000
--- a/general/datasets/BXDGeno/acknowledgment.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-The majority of SNP genotypes were generated at GeneSeek using the GigaMUGA array, at UNC using the Affymetrix mouse genotyping array, and at Illumina with support from the Wellcome Trust. The selection of markers to included in the final file was carried out by Robert W. Williams and Danny Arends in December 2017.
-
-Reference:
-
-Dietrich WF, Katz H, Lincoln SE (1992) A genetic map of the mouse suitable for typing in intraspecific crosses. Genetics 131:423-447.
-
-Taylor BA, Wnek C, Kotlus BS, Roemer N, MacTaggart T, Phillips SJ (1999) Genotyping new BXD recombinant inbred mouse strains and comparison of BXD and consensus maps. Mamm Genome 10:335-348.
-
-Williams RW, Gu J, Qi S, Lu L (2001) The genetic structure of recombinant inbred mice: High-resolution consensus maps for complex trait analysis. Genome Biology 2:RESEARCH0046
-
-Wiltshire T, Pletcher MT, Batalov S, Barnes SW, Tarantino LM, Cooke MP, Wu H, Smylie K, Santrosyan A, Copeland NG, Jenkins NA, Kalush F, Mural RJ, Glynne RJ, Kay SA, Adams MD, Fletcher CF (2003) Genome-wide single-nucleotide polymorphism analysis defines haplotype patterns in mouse. Proc Natl Acad Sci USA 100:3380-3385.
diff --git a/general/datasets/BXDGeno/summary.rtf b/general/datasets/BXDGeno/summary.rtf
deleted file mode 100644
index cdb56ad..0000000
--- a/general/datasets/BXDGeno/summary.rtf
+++ /dev/null
@@ -1,59 +0,0 @@
-(Updated July 1, 2022 by D. Ashbrook)
-
-All variants are publicly available for anyone to get whatever type and frequency of variant that they want to. The variant vcf is under analyses files in project PRJEB45429 https://www.ebi.ac.uk/ena/browser/view/PRJEB45429?show=analyses
-
-(Updated March 15, 2018 by RW Williams)
-
-BXD Genotypes file status (January 2017): From September 2016 to January 2017, Robert Williams, Jesse Ingels, Lu Lu, and Danny Arends released a new genotype file for the original BXD strains (BXD1 through BXD102) and for all of the new strains (BXD104 to BXD220). Version 1 of this genotype file (used from jan 2017 to March 13, 2018) contained data for 7324 markers and 198 strains. Version 2 of March 14, 2018 fixed some errors of marker location detected by Karl Broman (five markers were out of order in the latest mouse genome assembly). We deleted three markers and retained a final set of 7321 markers, now all in correct order based on the SNP position using the mm10 assembly.
-
-Of the 198 BXD strains, 191 are independent, whereas 7 are substrains (e.g., BXD48 and BXD48a). The file provides approximate locations of 10300 recombinations, an average of 52 per strain. Genotypes were generated using Affymetrix, MUGA, MegaMUGA, and GigaMUGA Illumina platforms. Microsatellites and eQTL genotypes were generated by the Williams/Lu laboratory. Unknown genotypes were imputed as B or D, or were called as H (heterozygous) if the genotype was uncertain. Genotypes were manually curated by RW Williams. Genotypes were smoothed to remove unlikely recombination events. Almost all recombinations are supported by multiple markers, although only one or two representative markers may be provided in this file. The original parent file (BXD_El_Grande_Master_Used_to_Proof_Final_Genotypes_2016.xlxs) contains data for approximately 37000 markers. Genotypes for Chr Y and Chr M are provisional and will be verified in 2017. As of 2016, many strains with higher numbers (BXD100 and above) are not fully inbred.
-
-
-
-A link to the genotype file is provide here
-
-
-
-Genotypes were generated at GeneSeek (Neogen Inc) with financial support from the University of Tennessee Center for Integrative and Translational Genomics. We thank Drs. Fernando Pardo-Manuel de Villena (University of North Carolina) and Gary Churchill (The Jackson Laboratory) for developing the GigaMUGA arreay.
-
-The new genotypes are now available in GeneNetwork as the 2017 Genotype file. All SNPs were mapped to the newer Dec 2011, mm10, GRCm38 assembly.
-
-As of Jan 2017 GeneNetwork uses mm10 coordinates for mapping functions. Older mm9 versions of GeneNetwork are available on the GN TimeMachine (see upper right side of Search page).
-
-BXD Genotype: The state of a gene or DNA sequence, usually used to describe a contrast between two or more states, such as that between the normal state (wildtype) and a mutant state (mutation) or between the alleles inherited from two parents. All species that are included in GeneNetwork are diploid (derived from two parents) and have two copies of most genes (genes located on the X and Y chromosomes are exceptions). As a result the genotype of a particular diploid individual is actually a pair of genotypes, one from each parents. For example, the offspring of a mating between strain A and strain B will have one copy of the A genotype and one copy of the B genotype and therefore have an A/B genotype. In contrast, offspring of a mating between a female strain A and a male strain A will inherit only A genotypes and have an A/A genotype.
-
-Genotypes can be measured or inferred in many different ways, even by visual inspection of animals (e.g. as Gregor Mendel did long before DNA was discovered). But now the typical method is to directly test DNA that has a well define chromosomal location that has been obtained from one or usually many cases using molecular tests that often rely on polymerase chain reaction steps and sequence analysis. Each case is genotyped at many chromosomal locations (loci, markers, or genes). The entire collection of genotypes (as many a 1 million for a single case) is also sometimes referred to as the cases genotype, but the word "genometype" might be more appropriate to highlight the fact that we are now dealing with a set of genotypes spanning the entire genome (all chromosomes) of the case.
-
-For gene mapping purposes, genotypes are often translated from letter codes (A/A, A/B, and B/B) to simple numerical codes that are more suitable for computation. A/A might be represented by the value -1, A/B by the value 0, and B/B by the value +1. This recoding makes it easy to determine if there is a statistically significant correlation between genotypes across of a set of cases (for example, an F2 population or a Genetic Reference Panel) and a variable phenotype measured in the same population. A sufficiently high correlation between genotypes and phenotypes is referred to as a quantitative trait locus (QTL). If the correlation is almost perfect (r > 0.9) then correlation is usually referred to as a Mendelian locus. Despite the fact that we use the term "correlation" in the preceding sentences, the genotype is actually the cause of the phenotype. More precisely, variation in the genotypes of individuals in the sample population cause the variation in the phenotype. The statistical confidence of this assertion of causality is often estimated using LOD and LRS scores and permutation methods. If the LOD score is above 10, then we can be extremely confident that we have located a genetic cause of variation in the phenotype. While the location is defined usually with a precision ranging from 10 million to 100 thousand basepairs (the locus), the individual sequence variant that is responsible may be quite difficult to extract. Think of this in terms of police work: we may know the neighborhood where the suspect lives, we may have clues as to identity and habits, but we still may have a large list of suspects.
-
-The BXD genotype file was initially upgraded in 2010-2011 using the new high density Affymetrix array (580,000 high quality SNPs) developed in the laboratories of Drs. Fernando Pardo-Manuel de Villena (University of North Carolina) and Gary Churchill (The Jackson Laboratory, see Yang H, Ding Y, Hutchins LN, Szatkiewicz J, Bell TA, Paigen BJ, Graber JH, Pardo-Manuel de Villena, F, Churchill GA (2009) A customized and verstatile high density genotyping array for the mouse. Nat Methods 6:663-666)
-
-The BXD genotype file used from June 2005 through December 2016 exploits a set of approximatey 3796 markers typed across 88 extant and extinct BXD strains (BXD1 through BXD102). The mean interval between informative markers is about 0.7 Mb. This genotype file includes all markers, both SNPs and microsatellites, with unique strain distribution patterns (SDPs), as well as pairs of markers for those SDPs represented by two or more markers. In those situations where three or more markers had the same SDP, we retained only the most proximal and distal marker in the genotype file. This particular file has also been smoothed to eliminate genotypes that are likely to be erroneous. We have also conservatively imputed a small number of missing genotypes (usually over very short intervals). Smoothing genotypes is this way reduces the total number of SDPs and also lowers the rate of false discovery. However, this procedure also may eliminate some genuine SDPs.
-
-The new smoothed BXD genotype data file (2017) can be downloaded from
-GeneNetwork at the URL http://www.genenetwork.org/genotypes/BXD.geno.
-
-Please Note: For a limited number of markers and strains, the genotypes of BXDs have been called heterozygous. This is usually done over comparatively short intervals in some of the newer strains that may not have been fully inbred when they were initially genotyped. Use of the genotype file above in external software packages such as R/qtl, requires careful treatment of this issue to prevent bias in empirical significance thresholds. It is recommended to treat these rare heterozygous loci as missing data and ensure that only the additive effects of B vs. D alleles are estimated by these packages. (note by Elissa Chesler, Dec 2010).
-
-Source of Genotypes:
-
-In collaboration with members of the CTC (Richard Mott, Jonathan Flint, and colleagues), we have helped genotype a total of 480 strains using a panel of 13,377 SNPs. These SNPs were combined with our previious microsatellite genotypes to produce the older "classic" consensus maps for the expanded set of BXD using the older mouse assemblies (Mouse Build 36 - UCSC mm8 and then mm9). (Files were updated from mm6 to mm8 in January 2007, and from mm9 to mm10 in January 2017).
-
-A total of 198 strains have be genotyped as of Jan 2017 using the full set of SNPs, and about 7324 of these are informative. Informative in this sense simply means that the C57BL/6J and DBA/2J parental strains have different alleles. To reduce false positive errors when mapping using this ultra dense map, we have eliminated most single genotypes that generate double-recombinant haplotypes that are most commonly produced by typing errors ("smoothed" genotypes). For this reason, the genotypes used in the GeneNetwork differ from those downloaded directly from Richard Mott's web site at the Wellcome Trust, Oxford or from the Jackson Laboratory.
-
-We have genotyped all available BXD strains from The Jackson Laboratory. BXD1 through BXD32 were produced by Benjamin Taylor starting in the late 1970s. BXD33 through BXD42 were produced by Taylor in the 1990s (Taylor et al., 1999). All BXD strains with numbers higher than BXD42 (BXD43 through BXD100) were generated by Lu Lu and Robert Williams at UTHSC, and by Jeremy Peirce and Lee Silver at Princeton University. We thank Guomin Zhou for generating the advanced intercross stock used to produce most of these advanced RI strains both at UTHSC and Princeton. There are approximately 48 of these advanced BXD strains, each of which archives approximately twice the recombinations present in a typical F2-derived recombinant inbred strain (Peirce et al. 2003).
-
-Mapping Algorithm:
-
-Due to the very high density of markers, the mapping algorithm used to map BXD data sets has been modified and is a mixture of simple marker regression, linear interpolation, and standard Haley-Knott interval mapping. When two adjacent markers have identical SDPs, they will have identical linkage statistics, as will the entire interval between these two markers (assuming complete and error-free haplotype data for all strains). On a physical map the LRS and the additive effect values will therefore be constant over this physical interval. Between neighboring markers that have different SDPs and that are separated by 1 cM or more, we use a conventional interval mapping method (Haley-Knott) combined with a Haldane estimate of genetic distance. When the interval is less than 1 cM, we simply interpolate linearly between markers based on a physical scale between those markers. The result of this mixture mapping algorithm is a linkage map of a trait that has an unusal profile that is particular striking on a physical (Mb) scale, with many plateaus, abrupt linear transitions between plateaus, and a few regions with the standard graceful curves typical of interval maps.
-
-Archival Genotypes:
-
-Archival BXD Genotype file: Prior to July 2005, the marker genotypes used to map all BXD data sets consisted of a set of 779 markers described by Williams and colleagues (2001) that also included a small number of additional SNPs from Tim Wiltshire and Mathew Pletcher (GNF, La Jolla), new microsatellite markers generated by Grant Morahan and Jing Gu (Msw type markers), and a few CTC markers by Jing Gu. This old marker data set was made obsolete by the ultra high density Illumina SNP genotype data generated Spring, 2005.
-
-Download Genotypes:
-
-The entire BXD genotype data set used for mapping traits can be downloaded at BXD.geno.
diff --git a/general/datasets/BXDPublish/summary.rtf b/general/datasets/BXDPublish/summary.rtf
deleted file mode 100644
index 5c22bc2..0000000
--- a/general/datasets/BXDPublish/summary.rtf
+++ /dev/null
@@ -1,40 +0,0 @@
-Question: I have generated some phenotype data that I would like to put into GeneNetwork. How should I name my traits?
-
-Answer: Phenotype trait names in GeneNetwork should have this general form when possible:
-
-
- - Your description should start with very short list of "approved" general category and ontology terms. These terms are used to subdivide the entire collection of phenotypes by system, organ, or level of analysis. Some examples may help: "Central nervous system", "Immune system", "Metabolism", "Development", or "Urogenital system". Capitalize this list as you would a standard English sentence. Separate terms by commas and then end the terms with a colon. For example, "Central nervous system, pharmacology, endocrinology:" is a valid set of three terms. These terms do not really describe your trait, but are used by you and other users to figure out how many traits there are in specific categories.
-
- Before making up your own terms, please review the current terms in GeneNetwork and find some terms/ontology categories that look good to you. If you have questions contact one of us on the GeneNetwork development team.
- - After the colon start with your description of the phenotype you have generated. For example: "Ethanol response..." or "Anxiety assay...", "Brain weight...". The first letter should almost always be capitalized.
- - Do not start with a generic uninformative word such as "Mean", "Maximum", "Mechanical", "Count", "Number", "Difference", "Baseline", "Induction", "Decrease", "New", "Adjusted", "Distance", "Right", "Left", "Bilateral", "Time", "Total", "Percentage", "Percent". The reason is that the traits should be alphabetized and categorized in a conceptually useful way; not by something "dumb" like the "total" or "percent".
- - Do not start with a specific instrumental assay such as "Morris water maze" or "Dowel test..." or "Porsolt test behavior". Many of these tests will be unknown to other users. Try to use a term that reflects the intent of the assay (Motor coordination test, Learning and memory assay, Allergic airway response). This may be difficult, particularly for tests such as the Porsolt swim test and the Morris water maze that measure aspects of many different traits (anxiety, activity level, spatial navigation, visual acuity etc). But in the interest of clarity of intent rather than precision of measurement, please follow this suggestion. The actual assay instrument can be listed after the primary and secondary trait descriptions.
- - Many traits can be difficult to categorize in a consistent way. For example a trait such as "ventral midbrain copper level in males" could be labeled "copper level in the ventral midbrain." There is no right or wrong way to do this, but the convention should be to choose the order that you think will be most useful to other users in terms of comprehension and consistency with other existing phenotypes. Review related phenotypes before you start naming your own. You will find good and bad examples.
- - Dose and route of drug delivery. If the phenotype is a pharmacological phenotype, whenever practical enter the doses and routes of injection in parentheses after the name of the general trait. For example, "Cocaine response (40 mg/kg ip)". We would prefer to use "ip" and "iv" rather than i.p. and i.v., but this is not a strong preference. If a protocol requires multiple treatments, please include them if possible. For example, "Cocaine response (3 x 3.2 mg/kg ip, Days 2, 3, 4),...").
- - Series of more precise definitions of the phenotype and the subject(s) will often follow with commas used as separators. If possible make this understandable to almost any user, even at the risk of being wordy.
-
For example, "Cocaine response (3 x 3.2 mg/kg ip, Days 2, 3, and 4), conditioned place preference (CPP), change in time in cocaine-paired compartment relative to baseline (Day 5 minus Day 1) for 50 to 90-day-old males and females [sec]"
-
- - Sex. If the data are for males please write out "in males" or "of male" or "for males". Do not just add a comma such as " , males" or "(M)". This should usually go at the end of the description.
- - Age and condition of subjects can be added if you think it is essential or helpful. However, do not bother with a generic addition "adult" since that is what most users will reasonably assume. If you would like to add an age range then use this format "in 100 to 200-day-old males and females" or "of 3 to 4-month-old males".
- - Mandatory units of measurement between square brackets [min] or [sec] or [n bream breaks/10 min test]. If you are using an ordinal scale, then describe the scale within the brackets. If the units are simply a ratio or percentage then use [ratio] or [%].
-
-
-Other advice on trait descriptions:
-
-
- - Do Not Capitalize Each Word in a Description. (e.g, Ethanol Response, Distance traveled after saline - Distance traveled after ethanol for males and females [cm in a 0-5 min test period] )
- - Do not use "-" as a minus sign. The dash is too confusing and may sometimes be used as a hyphen. Spell out "minus"
- - No not use ALL CAP in a trait description (e.g., TOTAL)
- - Do use commas when appropriate. For example, Morphine response severity of abdominal constriction for males needs a comma between "response" and "severity"
- - Do not use extraneous words such as "time SPENT on rotarod". "time on rotarod" is good enough.
- - Do not start with text or abbreviations that will not be understandable to all users, such as "RSS female and male..."
- - Please us a space between a number and the units: Prepulse inhibition at 70 dB for females (not 70db). Please use the correct form of the abbreviation.
- - Use American spelling. [RWW, September 10, 2009]
-
-
-Examples of accepted phenotype descriptions: (by Amelie Baud. Wellcome Trust Centre for Human Genetics, Oxford, UK.)
-
-
- - Central nervous system, behavior: Anxiety assay, locomotor activity in novel cage between minutes 25 and 30 in novel cage, normalized by Box-Cox transformation [cm]
- - Metabolism: Glycemia (intraperitoneal glucose tolerance test), area under the curve between minutes 0 and 120 after injection, normalized by Box-Cox transformation [mM.min-1]
-
diff --git a/general/datasets/BXD_BonePublish/specifics.rtf b/general/datasets/BXD_BonePublish/specifics.rtf
deleted file mode 100644
index c23ed10..0000000
--- a/general/datasets/BXD_BonePublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-BXD Bone Individual Data
\ No newline at end of file
diff --git a/general/datasets/BXD_BonePublish/summary.rtf b/general/datasets/BXD_BonePublish/summary.rtf
deleted file mode 100644
index 153d98d..0000000
--- a/general/datasets/BXD_BonePublish/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In working progress...
diff --git a/general/datasets/BXD_HarvestedPublish/specifics.rtf b/general/datasets/BXD_HarvestedPublish/specifics.rtf
deleted file mode 100644
index 7b317eb..0000000
--- a/general/datasets/BXD_HarvestedPublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-BXD-NIA-Longevity Phenotypes
\ No newline at end of file
diff --git a/general/datasets/BXD_HarvestedPublish/summary.rtf b/general/datasets/BXD_HarvestedPublish/summary.rtf
deleted file mode 100644
index 88d835c..0000000
--- a/general/datasets/BXD_HarvestedPublish/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-BXD-NIA-Longevity Phenotypes
diff --git a/general/datasets/Bhhbf2geno/summary.rtf b/general/datasets/Bhhbf2geno/summary.rtf
new file mode 100644
index 0000000..39d69d7
--- /dev/null
+++ b/general/datasets/Bhhbf2geno/summary.rtf
@@ -0,0 +1 @@
+No information is available, please refer to the contact information above.
diff --git a/general/datasets/Br_m2_1106_r/acknowledgment.rtf b/general/datasets/Br_m2_1106_r/acknowledgment.rtf
new file mode 100644
index 0000000..0912bce
--- /dev/null
+++ b/general/datasets/Br_m2_1106_r/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data was generated with funds from NIAAA for Gene Array Technology Center (AA013162) and from the NIAAA Integrated Neuroinformatics Resource for Alcoholism (AA013524).
+
diff --git a/general/datasets/Br_m2_1106_r/cases.rtf b/general/datasets/Br_m2_1106_r/cases.rtf
new file mode 100644
index 0000000..1d1f7d8
--- /dev/null
+++ b/general/datasets/Br_m2_1106_r/cases.rtf
@@ -0,0 +1,5 @@
+
+This data set includes estimates of gene expression for 50 genetically uniform lines of mice: C57BL/6J (B6 or simply B), DBA/2J (D2 or D), 30 BXD recombinant inbred (RI) strain derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations, and 18 other inbred strains of mice available from the Jackson Laboratory. All mice used were naïve males from 70-90 days old. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. Another significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+In this mRNA expression database we generally used stock obtained directly from The Jackson Laboratory between 2003 and 2005.
+
diff --git a/general/datasets/Br_m2_1106_r/contributors.rtf b/general/datasets/Br_m2_1106_r/contributors.rtf
new file mode 100644
index 0000000..c6a7e8a
--- /dev/null
+++ b/general/datasets/Br_m2_1106_r/contributors.rtf
@@ -0,0 +1 @@
+Saba L, Bhave SV, Grahame N, Bice P, Lapadat R, Belknap J, Hoffman PL, Tabakoff B.
diff --git a/general/datasets/Br_m2_1106_r/notes.rtf b/general/datasets/Br_m2_1106_r/notes.rtf
new file mode 100644
index 0000000..e379677
--- /dev/null
+++ b/general/datasets/Br_m2_1106_r/notes.rtf
@@ -0,0 +1,2 @@
+This text file originally generated by RWW, YHQ, August for UTHSC Brain mRNA U74Av2 (Aug05) RMA. Updated for UC Denver Whole Brain M430v2 BXD (Nov06) RMA Data by LMS, November 2006. Updated by RWW, Feb 2008.
+
diff --git a/general/datasets/Br_m2_1106_r/platform.rtf b/general/datasets/Br_m2_1106_r/platform.rtf
new file mode 100644
index 0000000..bf888fd
--- /dev/null
+++ b/general/datasets/Br_m2_1106_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix MOE430v2 GeneChip: The expression data were generated using 248 MOE430v2 arrays. The chromosomal locations of MOE430v2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6). This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
diff --git a/general/datasets/Br_m2_1106_r/processing.rtf b/general/datasets/Br_m2_1106_r/processing.rtf
new file mode 100644
index 0000000..96eb066
--- /dev/null
+++ b/general/datasets/Br_m2_1106_r/processing.rtf
@@ -0,0 +1,7 @@
+
+Probe set data: The expression data were processed by Laura Saba (UCDHSC). The original CEL files were read into the R environment (Ihaka and Gentleman 1996). Data were processed using the Robust Multichip Average (RMA) method (Irrizary et al. 2003). Values were log2 transformed within the rma function in R. This data set includes further normalization to produce final estimates of expression that can be compared directly to the other transforms.
+
+This includes an initial quantile normalization on the RMA normalized probe set data followed by a transformation to force an array average of 8 units and stabilized standard deviation of 2 units within each array. Please see Bolstad and colleagues (2003) for a helpful comparison of RMA and two other methods of processing Affymetrix array data sets.
+
+
+Expression estimates (strain averages) range from a low of about 3.8 for probe set 1457109_x_at to a high of 15 for Gapdh (probe set 1418625_s_at). The mean expression of 8.0 actually represents a relatively low value of expression (roughly 250 on the original scale) because it is the average of all transcripts on the array, including those that are not expressed. Nonetheless, it is possible to obtain good signal down to very low values. For example, probe set 1437432_a_at (Trim12) has an average expression of 4.56 (extremely low), but it still is associated with a strong QTL (LRS of 45) precisely at the location of the parent gene (Chr 7 at 104 Mb). This demonstrates unequivocally that the small strain differences in expression of Trim12 measured by probe set 1437432_a_at is not noise but is generated by true allelic differences in Trim12 mRNA binding to the arrays.
diff --git a/general/datasets/Br_m2_1106_r/summary.rtf b/general/datasets/Br_m2_1106_r/summary.rtf
new file mode 100644
index 0000000..c57e9ff
--- /dev/null
+++ b/general/datasets/Br_m2_1106_r/summary.rtf
@@ -0,0 +1,5 @@
+A PhenoGen Informatics data set. Please cite: Saba L, Bhave SV, Grahame N, Bice P, Lapadat R, Belknap J, Hoffman PL, Tabakoff B (2006) Candidate genes and their regulatory elements: alcohol preference and tolerance. Mammalian Genome 17:669-688 Full Text PDF Version, Full Text HTML Version
+
+This November 2006 data freeze provides estimates of mRNA expression in whole brains of BXD recombinant inbred mice measured using Affymetrix MOE 430 version 2 micorarrays. Data were generated at the University of Colorado at Denver and Health Science Center (UCDHSC). Single whole brain samples were hybridized to 248 individual arrays. Data were processed using the RMA protocol followed by a secondary quantile normalization at the probe set level and a scale and location adjustment to ensure an average expression level of 8 units and a standard deviation of 2 units for easy comparison to other transforms.
+
+The PhenoGen Informatics web site provides additional analytic tools and transforms associated with these data.
diff --git a/general/datasets/Br_m2_1106_r/tissue.rtf b/general/datasets/Br_m2_1106_r/tissue.rtf
new file mode 100644
index 0000000..0989cd0
--- /dev/null
+++ b/general/datasets/Br_m2_1106_r/tissue.rtf
@@ -0,0 +1,2751 @@
+
+Naïve male mice were euthanized by CO2 exposure, and whole brains were removed and frozen on dry ice. Brains were stored at -70 deg C until used. The RNeasy Midi kit for lipid-rich tissues (Qiagen, Valencia, CA) was used to extract total RNA, and the RNeasy Mini kit (Qiagen) was used for cleanup. Biotin-labeled cRNA was obtained by in vitro transcription of the double-stranded cDNA that was originally synthesized from the total RNA. Each whole brain sample of biotin-labeled cRNA was fragmented and hybridized to a separate oligonucleotide array. After hybridization, the chips were stained with streptavidin-phycoerythrin conjugate and scanned using an Affymetrix GeneArray scanner.
+
+
+
+
+
+
+ | Strain |
+ Sample Number |
+ Scale
+ factor |
+ Average
+ background |
+ Absent |
+ Marginal |
+ Present |
+ Affy-bActin |
+ Affy-GAPH |
+
+
+ | BXD1 |
+ 1 |
+ 0.343 |
+ 65.57 |
+ 45.5% |
+ 4.1% |
+ 50.4% |
+ 1.33 |
+ 0.74 |
+
+
+ | BXD1 |
+ 2 |
+ 0.362 |
+ 68.26 |
+ 46.9% |
+ 4.5% |
+ 48.6% |
+ 1.30 |
+ 0.76 |
+
+
+ | BXD1 |
+ 3 |
+ 0.375 |
+ 66.19 |
+ 46.9% |
+ 4.2% |
+ 48.9% |
+ 1.27 |
+ 0.77 |
+
+
+ | BXD1 |
+ 4 |
+ 0.408 |
+ 57.16 |
+ 45.0% |
+ 4.0% |
+ 51.1% |
+ 1.27 |
+ 0.80 |
+
+
+ | BXD2 |
+ 1 |
+ 0.270 |
+ 60.53 |
+ 44.0% |
+ 4.1% |
+ 51.8% |
+ 1.52 |
+ 0.87 |
+
+
+ | BXD2 |
+ 2 |
+ 0.280 |
+ 67.57 |
+ 45.0% |
+ 4.2% |
+ 50.8% |
+ 1.31 |
+ 0.75 |
+
+
+ | BXD2 |
+ 3 |
+ 0.295 |
+ 67.03 |
+ 45.2% |
+ 4.1% |
+ 50.7% |
+ 1.34 |
+ 0.76 |
+
+
+ | BXD2 |
+ 4 |
+ 0.209 |
+ 99.86 |
+ 50.0% |
+ 4.7% |
+ 45.3% |
+ 1.24 |
+ 0.73 |
+
+
+ | BXD2 |
+ 5 |
+ 0.246 |
+ 73.28 |
+ 46.2% |
+ 4.3% |
+ 49.5% |
+ 1.34 |
+ 0.73 |
+
+
+ | BXD5 |
+ 1 |
+ 0.249 |
+ 75.34 |
+ 47.3% |
+ 4.4% |
+ 48.3% |
+ 1.34 |
+ 0.73 |
+
+
+ | BXD5 |
+ 2 |
+ 0.306 |
+ 70.11 |
+ 47.5% |
+ 4.5% |
+ 47.9% |
+ 1.31 |
+ 0.77 |
+
+
+ | BXD5 |
+ 3 |
+ 0.265 |
+ 64.80 |
+ 44.8% |
+ 4.3% |
+ 50.9% |
+ 1.33 |
+ 0.74 |
+
+
+ | BXD5 |
+ 4 |
+ 0.282 |
+ 66.04 |
+ 45.5% |
+ 4.2% |
+ 50.4% |
+ 1.41 |
+ 0.76 |
+
+
+ | BXD5 |
+ 5 |
+ 0.216 |
+ 71.87 |
+ 46.0% |
+ 3.9% |
+ 50.1% |
+ 3.07 |
+ 1.01 |
+
+
+ | BXD6 |
+ 1 |
+ 0.294 |
+ 66.72 |
+ 45.8% |
+ 4.3% |
+ 49.9% |
+ 1.38 |
+ 0.75 |
+
+
+ | BXD6 |
+ 2 |
+ 0.304 |
+ 62.83 |
+ 45.8% |
+ 4.2% |
+ 50.0% |
+ 1.25 |
+ 0.72 |
+
+
+ | BXD6 |
+ 3 |
+ 0.301 |
+ 61.80 |
+ 45.3% |
+ 4.3% |
+ 50.5% |
+ 1.27 |
+ 0.76 |
+
+
+ | BXD6 |
+ 5 |
+ 0.273 |
+ 67.04 |
+ 44.4% |
+ 4.2% |
+ 51.4% |
+ 1.32 |
+ 0.76 |
+
+
+ | BXD6 |
+ 6 |
+ 0.272 |
+ 66.39 |
+ 45.4% |
+ 4.3% |
+ 50.3% |
+ 1.32 |
+ 0.75 |
+
+
+ | BXD8 |
+ 1 |
+ 0.207 |
+ 81.90 |
+ 44.0% |
+ 3.9% |
+ 52.1% |
+ 1.33 |
+ 0.74 |
+
+
+ | BXD8 |
+ 2 |
+ 0.254 |
+ 70.19 |
+ 44.0% |
+ 3.9% |
+ 52.0% |
+ 1.32 |
+ 0.72 |
+
+
+ | BXD8 |
+ 3 |
+ 0.300 |
+ 72.61 |
+ 46.0% |
+ 4.0% |
+ 50.0% |
+ 1.30 |
+ 0.74 |
+
+
+ | BXD8 |
+ 4 |
+ 0.457 |
+ 52.63 |
+ 39.5% |
+ 3.3% |
+ 57.2% |
+ 1.14 |
+ 0.79 |
+
+
+ | BXD8 |
+ 5 |
+ 0.381 |
+ 55.09 |
+ 41.2% |
+ 3.4% |
+ 55.4% |
+ 1.12 |
+ 0.79 |
+
+
+ | BXD9 |
+ 1 |
+ 0.349 |
+ 90.32 |
+ 48.5% |
+ 4.1% |
+ 47.4% |
+ 1.38 |
+ 0.78 |
+
+
+ | BXD9 |
+ 2 |
+ 0.241 |
+ 86.66 |
+ 51.2% |
+ 4.8% |
+ 44.0% |
+ 1.38 |
+ 0.75 |
+
+
+ | BXD9 |
+ 3 |
+ 0.284 |
+ 67.21 |
+ 47.2% |
+ 4.3% |
+ 48.5% |
+ 1.33 |
+ 0.78 |
+
+
+ | BXD9 |
+ 4 |
+ 0.303 |
+ 64.47 |
+ 46.9% |
+ 4.5% |
+ 48.6% |
+ 1.32 |
+ 0.77 |
+
+
+ | BXD9 |
+ 5 |
+ 0.351 |
+ 59.40 |
+ 47.4% |
+ 4.4% |
+ 48.2% |
+ 1.41 |
+ 0.80 |
+
+
+ | BXD9 |
+ 6 |
+ 0.312 |
+ 63.41 |
+ 46.3% |
+ 4.4% |
+ 49.4% |
+ 1.39 |
+ 0.76 |
+
+
+ | BXD11 |
+ 1 |
+ 0.267 |
+ 61.85 |
+ 44.6% |
+ 4.3% |
+ 51.1% |
+ 1.36 |
+ 0.75 |
+
+
+ | BXD11 |
+ 2 |
+ 0.317 |
+ 63.76 |
+ 45.3% |
+ 4.3% |
+ 50.4% |
+ 1.29 |
+ 0.79 |
+
+
+ | BXD11 |
+ 3 |
+ 0.306 |
+ 59.35 |
+ 44.8% |
+ 4.2% |
+ 51.0% |
+ 1.33 |
+ 0.79 |
+
+
+ | BXD11 |
+ 4 |
+ 0.223 |
+ 98.84 |
+ 51.1% |
+ 4.6% |
+ 44.3% |
+ 1.32 |
+ 0.73 |
+
+
+ | BXD11 |
+ 5 |
+ 0.292 |
+ 65.03 |
+ 45.4% |
+ 4.0% |
+ 50.5% |
+ 1.38 |
+ 0.78 |
+
+
+ | BXD12 |
+ 1 |
+ 0.357 |
+ 54.50 |
+ 42.5% |
+ 3.7% |
+ 53.8% |
+ 1.15 |
+ 0.76 |
+
+
+ | BXD12 |
+ 2 |
+ 0.379 |
+ 55.05 |
+ 42.7% |
+ 3.7% |
+ 53.6% |
+ 1.15 |
+ 0.76 |
+
+
+ | BXD12 |
+ 3 |
+ 0.347 |
+ 56.34 |
+ 43.2% |
+ 3.9% |
+ 52.9% |
+ 1.17 |
+ 0.74 |
+
+
+ | BXD12 |
+ 4 |
+ 0.541 |
+ 65.16 |
+ 43.1% |
+ 3.4% |
+ 53.6% |
+ 1.08 |
+ 0.79 |
+
+
+ | BXD12 |
+ 5 |
+ 0.178 |
+ 96.04 |
+ 43.4% |
+ 4.0% |
+ 52.7% |
+ 1.29 |
+ 0.74 |
+
+
+ | BXD12 |
+ 6 |
+ 0.234 |
+ 67.32 |
+ 43.0% |
+ 3.9% |
+ 53.0% |
+ 1.31 |
+ 0.75 |
+
+
+ | BXD12 |
+ 7 |
+ 0.255 |
+ 68.41 |
+ 42.7% |
+ 4.2% |
+ 53.2% |
+ 1.50 |
+ 0.76 |
+
+
+ | BXD13 |
+ 1 |
+ 0.285 |
+ 59.51 |
+ 45.8% |
+ 4.2% |
+ 49.9% |
+ 1.22 |
+ 0.75 |
+
+
+ | BXD13 |
+ 2 |
+ 0.275 |
+ 67.19 |
+ 44.9% |
+ 4.2% |
+ 50.9% |
+ 1.29 |
+ 0.76 |
+
+
+ | BXD13 |
+ 3 |
+ 0.277 |
+ 66.05 |
+ 45.7% |
+ 4.2% |
+ 50.2% |
+ 1.38 |
+ 0.79 |
+
+
+ | BXD13 |
+ 4 |
+ 0.214 |
+ 82.73 |
+ 48.6% |
+ 4.5% |
+ 46.9% |
+ 1.40 |
+ 0.78 |
+
+
+ | BXD13 |
+ 5 |
+ 0.237 |
+ 71.73 |
+ 46.0% |
+ 4.3% |
+ 49.7% |
+ 1.29 |
+ 0.77 |
+
+
+ | BXD13 |
+ 6 |
+ 0.308 |
+ 57.58 |
+ 47.2% |
+ 4.2% |
+ 48.6% |
+ 1.33 |
+ 0.74 |
+
+
+ | BXD14 |
+ 2 |
+ 0.372 |
+ 58.42 |
+ 46.8% |
+ 4.4% |
+ 48.8% |
+ 1.19 |
+ 0.74 |
+
+
+ | BXD14 |
+ 3 |
+ 0.354 |
+ 57.39 |
+ 45.0% |
+ 4.2% |
+ 50.8% |
+ 1.20 |
+ 0.72 |
+
+
+ | BXD14 |
+ 4 |
+ 0.296 |
+ 64.96 |
+ 45.7% |
+ 4.4% |
+ 49.9% |
+ 1.20 |
+ 0.69 |
+
+
+ | BXD14 |
+ 5 |
+ 0.257 |
+ 66.46 |
+ 44.9% |
+ 4.4% |
+ 50.8% |
+ 1.24 |
+ 0.72 |
+
+
+ | BXD14 |
+ 6 |
+ 0.418 |
+ 54.03 |
+ 47.4% |
+ 4.1% |
+ 48.5% |
+ 1.10 |
+ 0.74 |
+
+
+ | BXD15 |
+ 1 |
+ 0.396 |
+ 58.77 |
+ 43.6% |
+ 3.9% |
+ 52.5% |
+ 1.33 |
+ 0.78 |
+
+
+ | BXD15 |
+ 2 |
+ 0.270 |
+ 151.42 |
+ 52.7% |
+ 4.7% |
+ 42.6% |
+ 1.36 |
+ 0.73 |
+
+
+ | BXD15 |
+ 3 |
+ 0.366 |
+ 70.26 |
+ 44.7% |
+ 3.9% |
+ 51.4% |
+ 1.29 |
+ 0.79 |
+
+
+ | BXD15 |
+ 4 |
+ 0.407 |
+ 53.40 |
+ 43.6% |
+ 4.1% |
+ 52.4% |
+ 1.38 |
+ 0.79 |
+
+
+ | BXD16 |
+ 1 |
+ 0.388 |
+ 48.98 |
+ 43.7% |
+ 4.1% |
+ 52.2% |
+ 1.41 |
+ 0.79 |
+
+
+ | BXD16 |
+ 2 |
+ 0.353 |
+ 55.48 |
+ 43.7% |
+ 4.0% |
+ 52.3% |
+ 1.44 |
+ 0.82 |
+
+
+ | BXD16 |
+ 3 |
+ 0.339 |
+ 61.60 |
+ 45.3% |
+ 4.2% |
+ 50.5% |
+ 1.42 |
+ 0.80 |
+
+
+ | BXD16 |
+ 4 |
+ 0.240 |
+ 95.15 |
+ 50.4% |
+ 4.7% |
+ 44.9% |
+ 1.39 |
+ 0.73 |
+
+
+ | BXD16 |
+ 5 |
+ 0.270 |
+ 70.63 |
+ 46.3% |
+ 4.3% |
+ 49.4% |
+ 1.45 |
+ 0.75 |
+
+
+ | BXD16 |
+ 6 |
+ 0.281 |
+ 72.99 |
+ 47.0% |
+ 4.2% |
+ 48.8% |
+ 1.40 |
+ 0.77 |
+
+
+ | BXD18 |
+ 1 |
+ 0.384 |
+ 59.78 |
+ 45.4% |
+ 4.0% |
+ 50.6% |
+ 1.12 |
+ 0.71 |
+
+
+ | BXD18 |
+ 2 |
+ 0.288 |
+ 93.67 |
+ 49.5% |
+ 4.4% |
+ 46.1% |
+ 1.15 |
+ 0.70 |
+
+
+ | BXD18 |
+ 3 |
+ 0.286 |
+ 89.64 |
+ 45.2% |
+ 4.1% |
+ 50.8% |
+ 1.27 |
+ 0.71 |
+
+
+ | BXD18 |
+ 4 |
+ 0.294 |
+ 69.85 |
+ 44.0% |
+ 4.1% |
+ 51.8% |
+ 1.26 |
+ 0.70 |
+
+
+ | BXD18 |
+ 5 |
+ 0.417 |
+ 59.80 |
+ 47.0% |
+ 4.3% |
+ 48.7% |
+ 1.15 |
+ 0.72 |
+
+
+ | BXD18 |
+ 6 |
+ 0.373 |
+ 65.30 |
+ 45.9% |
+ 4.3% |
+ 49.8% |
+ 1.18 |
+ 0.74 |
+
+
+ | BXD19 |
+ 1 |
+ 0.364 |
+ 59.35 |
+ 46.7% |
+ 4.2% |
+ 49.1% |
+ 1.27 |
+ 0.73 |
+
+
+ | BXD19 |
+ 2 |
+ 0.419 |
+ 59.77 |
+ 46.8% |
+ 4.1% |
+ 49.1% |
+ 1.23 |
+ 0.74 |
+
+
+ | BXD19 |
+ 3 |
+ 0.303 |
+ 62.66 |
+ 46.0% |
+ 4.4% |
+ 49.6% |
+ 1.30 |
+ 0.74 |
+
+
+ | BXD19 |
+ 4 |
+ 0.280 |
+ 91.00 |
+ 51.8% |
+ 4.5% |
+ 43.7% |
+ 1.32 |
+ 0.68 |
+
+
+ | BXD19 |
+ 5 |
+ 0.303 |
+ 66.18 |
+ 47.1% |
+ 4.5% |
+ 48.4% |
+ 1.33 |
+ 0.72 |
+
+
+ | BXD19 |
+ 6 |
+ 0.389 |
+ 63.61 |
+ 47.5% |
+ 4.4% |
+ 48.1% |
+ 1.28 |
+ 0.73 |
+
+
+ | BXD21 |
+ 1 |
+ 0.350 |
+ 75.93 |
+ 44.9% |
+ 3.9% |
+ 51.3% |
+ 1.29 |
+ 0.77 |
+
+
+ | BXD21 |
+ 2 |
+ 0.338 |
+ 59.00 |
+ 43.8% |
+ 4.0% |
+ 52.1% |
+ 1.29 |
+ 0.77 |
+
+
+ | BXD21 |
+ 3 |
+ 0.304 |
+ 59.94 |
+ 44.9% |
+ 4.0% |
+ 51.2% |
+ 1.44 |
+ 0.77 |
+
+
+ | BXD21 |
+ 4 |
+ 0.235 |
+ 94.44 |
+ 51.0% |
+ 4.8% |
+ 44.2% |
+ 1.35 |
+ 0.73 |
+
+
+ | BXD21 |
+ 5 |
+ 0.310 |
+ 64.22 |
+ 46.9% |
+ 4.2% |
+ 48.9% |
+ 1.42 |
+ 0.77 |
+
+
+ | BXD22 |
+ 1 |
+ 0.363 |
+ 58.10 |
+ 45.3% |
+ 3.9% |
+ 50.8% |
+ 1.24 |
+ 0.80 |
+
+
+ | BXD22 |
+ 2 |
+ 0.385 |
+ 55.58 |
+ 44.5% |
+ 4.0% |
+ 51.5% |
+ 1.28 |
+ 0.80 |
+
+
+ | BXD22 |
+ 3 |
+ 0.345 |
+ 61.03 |
+ 46.8% |
+ 4.3% |
+ 48.9% |
+ 1.35 |
+ 0.81 |
+
+
+ | BXD22 |
+ 4 |
+ 0.242 |
+ 85.36 |
+ 53.6% |
+ 4.8% |
+ 41.6% |
+ 1.35 |
+ 0.75 |
+
+
+ | BXD22 |
+ 5 |
+ 0.316 |
+ 62.02 |
+ 47.3% |
+ 4.5% |
+ 48.2% |
+ 1.40 |
+ 0.77 |
+
+
+ | BXD22 |
+ 6 |
+ 0.325 |
+ 66.38 |
+ 47.5% |
+ 4.3% |
+ 48.2% |
+ 1.29 |
+ 0.78 |
+
+
+ | BXD23 |
+ 1 |
+ 0.276 |
+ 75.99 |
+ 45.3% |
+ 4.1% |
+ 50.6% |
+ 1.27 |
+ 0.75 |
+
+
+ | BXD23 |
+ 2 |
+ 0.333 |
+ 81.76 |
+ 47.9% |
+ 4.0% |
+ 48.1% |
+ 1.28 |
+ 0.78 |
+
+
+ | BXD23 |
+ 3 |
+ 0.275 |
+ 102.46 |
+ 47.4% |
+ 3.9% |
+ 48.8% |
+ 1.30 |
+ 0.77 |
+
+
+ | BXD23 |
+ 4 |
+ 0.178 |
+ 115.83 |
+ 50.2% |
+ 4.7% |
+ 45.2% |
+ 1.38 |
+ 0.73 |
+
+
+ | BXD23 |
+ 5 |
+ 0.258 |
+ 92.38 |
+ 47.6% |
+ 4.2% |
+ 48.2% |
+ 1.32 |
+ 0.77 |
+
+
+ | BXD23 |
+ 6 |
+ 0.256 |
+ 88.23 |
+ 46.3% |
+ 4.1% |
+ 49.5% |
+ 1.31 |
+ 0.74 |
+
+
+ | BXD24 |
+ 1 |
+ 0.348 |
+ 71.69 |
+ 44.9% |
+ 4.1% |
+ 51.1% |
+ 1.25 |
+ 0.74 |
+
+
+ | BXD24 |
+ 2 |
+ 0.324 |
+ 74.05 |
+ 44.3% |
+ 4.0% |
+ 51.7% |
+ 1.23 |
+ 0.80 |
+
+
+ | BXD24 |
+ 3 |
+ 0.401 |
+ 64.08 |
+ 45.6% |
+ 4.0% |
+ 50.4% |
+ 1.08 |
+ 0.74 |
+
+
+ | BXD24 |
+ 4 |
+ 0.246 |
+ 82.84 |
+ 45.7% |
+ 4.3% |
+ 50.0% |
+ 1.20 |
+ 0.75 |
+
+
+ | BXD24 |
+ 6 |
+ 0.389 |
+ 54.28 |
+ 44.3% |
+ 4.2% |
+ 51.5% |
+ 1.20 |
+ 0.67 |
+
+
+ | BXD27 |
+ 1 |
+ 0.507 |
+ 50.08 |
+ 43.6% |
+ 3.9% |
+ 52.5% |
+ 1.48 |
+ 0.81 |
+
+
+ | BXD27 |
+ 2 |
+ 0.468 |
+ 51.29 |
+ 44.0% |
+ 3.7% |
+ 52.3% |
+ 1.44 |
+ 0.90 |
+
+
+ | BXD27 |
+ 3 |
+ 0.526 |
+ 49.67 |
+ 43.5% |
+ 3.9% |
+ 52.6% |
+ 1.29 |
+ 0.94 |
+
+
+ | BXD27 |
+ 4 |
+ 0.537 |
+ 48.92 |
+ 43.5% |
+ 3.8% |
+ 52.8% |
+ 1.46 |
+ 0.91 |
+
+
+ | BXD28 |
+ 1 |
+ 0.284 |
+ 51.58 |
+ 44.6% |
+ 4.2% |
+ 51.2% |
+ 1.26 |
+ 0.80 |
+
+
+ | BXD28 |
+ 2 |
+ 0.322 |
+ 50.16 |
+ 44.9% |
+ 4.3% |
+ 50.8% |
+ 1.21 |
+ 0.76 |
+
+
+ | BXD28 |
+ 3 |
+ 0.397 |
+ 50.97 |
+ 45.9% |
+ 4.2% |
+ 49.9% |
+ 1.14 |
+ 0.78 |
+
+
+ | BXD28 |
+ 4 |
+ 0.330 |
+ 74.26 |
+ 51.4% |
+ 4.6% |
+ 44.0% |
+ 1.26 |
+ 0.72 |
+
+
+ | BXD28 |
+ 5 |
+ 0.284 |
+ 52.34 |
+ 44.3% |
+ 4.4% |
+ 51.3% |
+ 1.32 |
+ 0.73 |
+
+
+ | BXD28 |
+ 6 |
+ 0.349 |
+ 57.14 |
+ 47.8% |
+ 4.5% |
+ 47.7% |
+ 1.30 |
+ 0.79 |
+
+
+ | BXD29 |
+ 1 |
+ 0.422 |
+ 58.68 |
+ 44.0% |
+ 3.7% |
+ 52.3% |
+ 1.42 |
+ 0.86 |
+
+
+ | BXD29 |
+ 3 |
+ 0.400 |
+ 58.72 |
+ 43.1% |
+ 3.8% |
+ 53.2% |
+ 1.31 |
+ 0.89 |
+
+
+ | BXD29 |
+ 5 |
+ 0.365 |
+ 61.79 |
+ 46.9% |
+ 4.3% |
+ 48.8% |
+ 1.38 |
+ 0.91 |
+
+
+ | BXD31 |
+ 1 |
+ 0.379 |
+ 51.10 |
+ 45.8% |
+ 4.3% |
+ 50.0% |
+ 1.13 |
+ 0.75 |
+
+
+ | BXD31 |
+ 2 |
+ 0.333 |
+ 48.64 |
+ 43.7% |
+ 4.1% |
+ 52.2% |
+ 1.22 |
+ 0.71 |
+
+
+ | BXD31 |
+ 3 |
+ 0.519 |
+ 47.71 |
+ 48.2% |
+ 4.3% |
+ 47.5% |
+ 1.13 |
+ 0.72 |
+
+
+ | BXD31 |
+ 4 |
+ 0.243 |
+ 75.24 |
+ 48.6% |
+ 4.8% |
+ 46.6% |
+ 1.23 |
+ 0.71 |
+
+
+ | BXD31 |
+ 5 |
+ 0.325 |
+ 53.19 |
+ 46.9% |
+ 4.6% |
+ 48.6% |
+ 1.22 |
+ 0.75 |
+
+
+ | BXD31 |
+ 6 |
+ 0.320 |
+ 46.98 |
+ 44.5% |
+ 4.3% |
+ 51.2% |
+ 1.24 |
+ 0.74 |
+
+
+ | BXD32 |
+ 1 |
+ 0.256 |
+ 70.43 |
+ 45.4% |
+ 3.9% |
+ 50.8% |
+ 1.83 |
+ 0.87 |
+
+
+ | BXD32 |
+ 2 |
+ 0.288 |
+ 67.44 |
+ 44.5% |
+ 4.1% |
+ 51.4% |
+ 1.34 |
+ 0.77 |
+
+
+ | BXD32 |
+ 3 |
+ 0.361 |
+ 58.13 |
+ 44.4% |
+ 4.0% |
+ 51.6% |
+ 1.36 |
+ 0.77 |
+
+
+ | BXD32 |
+ 4 |
+ 0.367 |
+ 61.39 |
+ 44.7% |
+ 4.1% |
+ 51.2% |
+ 1.40 |
+ 0.78 |
+
+
+ | BXD32 |
+ 5 |
+ 0.324 |
+ 68.04 |
+ 45.6% |
+ 4.3% |
+ 50.1% |
+ 1.39 |
+ 0.75 |
+
+
+ | BXD32 |
+ 6 |
+ 0.266 |
+ 95.49 |
+ 50.8% |
+ 4.5% |
+ 44.6% |
+ 1.41 |
+ 0.73 |
+
+
+ | BXD33 |
+ 1 |
+ 0.344 |
+ 61.65 |
+ 44.9% |
+ 3.9% |
+ 51.2% |
+ 1.38 |
+ 0.82 |
+
+
+ | BXD33 |
+ 2 |
+ 0.356 |
+ 61.04 |
+ 44.7% |
+ 4.1% |
+ 51.2% |
+ 1.44 |
+ 0.79 |
+
+
+ | BXD33 |
+ 4 |
+ 0.385 |
+ 59.92 |
+ 44.1% |
+ 3.9% |
+ 52.0% |
+ 1.38 |
+ 0.82 |
+
+
+ | BXD34 |
+ 1 |
+ 0.297 |
+ 91.13 |
+ 52.1% |
+ 4.6% |
+ 43.3% |
+ 1.34 |
+ 0.70 |
+
+
+ | BXD34 |
+ 2 |
+ 0.508 |
+ 51.79 |
+ 44.8% |
+ 3.9% |
+ 51.3% |
+ 1.42 |
+ 0.76 |
+
+
+ | BXD34 |
+ 3 |
+ 0.284 |
+ 85.33 |
+ 50.7% |
+ 4.6% |
+ 44.7% |
+ 1.51 |
+ 0.72 |
+
+
+ | BXD34 |
+ 4 |
+ 0.297 |
+ 61.95 |
+ 44.9% |
+ 4.1% |
+ 51.0% |
+ 1.36 |
+ 0.77 |
+
+
+ | BXD34 |
+ 5 |
+ 0.516 |
+ 56.02 |
+ 46.3% |
+ 4.0% |
+ 49.7% |
+ 1.33 |
+ 0.74 |
+
+
+ | BXD34 |
+ 6 |
+ 0.545 |
+ 54.46 |
+ 45.2% |
+ 3.8% |
+ 51.0% |
+ 1.49 |
+ 0.87 |
+
+
+ | BXD36 |
+ 1 |
+ 0.435 |
+ 62.74 |
+ 48.1% |
+ 4.0% |
+ 47.8% |
+ 1.36 |
+ 0.73 |
+
+
+ | BXD36 |
+ 2 |
+ 0.333 |
+ 71.24 |
+ 48.8% |
+ 4.3% |
+ 46.8% |
+ 1.44 |
+ 0.72 |
+
+
+ | BXD36 |
+ 3 |
+ 0.320 |
+ 72.97 |
+ 48.3% |
+ 4.3% |
+ 47.4% |
+ 1.38 |
+ 0.74 |
+
+
+ | BXD36 |
+ 4 |
+ 0.391 |
+ 73.58 |
+ 49.5% |
+ 4.2% |
+ 46.3% |
+ 1.25 |
+ 0.75 |
+
+
+ | BXD38 |
+ 1 |
+ 0.303 |
+ 87.68 |
+ 39.2% |
+ 3.3% |
+ 57.5% |
+ 1.08 |
+ 0.82 |
+
+
+ | BXD38 |
+ 2 |
+ 0.343 |
+ 61.39 |
+ 39.7% |
+ 3.2% |
+ 57.1% |
+ 1.12 |
+ 0.82 |
+
+
+ | BXD38 |
+ 3 |
+ 0.453 |
+ 67.19 |
+ 41.2% |
+ 3.4% |
+ 55.4% |
+ 1.11 |
+ 0.83 |
+
+
+ | BXD38 |
+ 4 |
+ 0.424 |
+ 64.36 |
+ 41.6% |
+ 3.5% |
+ 55.0% |
+ 1.11 |
+ 0.82 |
+
+
+ | BXD39 |
+ 1 |
+ 0.357 |
+ 64.36 |
+ 47.3% |
+ 4.3% |
+ 48.3% |
+ 1.33 |
+ 0.78 |
+
+
+ | BXD39 |
+ 2 |
+ 0.332 |
+ 60.23 |
+ 46.5% |
+ 4.2% |
+ 49.3% |
+ 1.41 |
+ 0.80 |
+
+
+ | BXD39 |
+ 3 |
+ 0.331 |
+ 65.27 |
+ 46.2% |
+ 4.2% |
+ 49.6% |
+ 1.32 |
+ 0.75 |
+
+
+ | BXD39 |
+ 4 |
+ 0.362 |
+ 62.60 |
+ 45.5% |
+ 4.0% |
+ 50.5% |
+ 1.28 |
+ 0.80 |
+
+
+ | BXD39 |
+ 5 |
+ 0.347 |
+ 58.97 |
+ 46.1% |
+ 4.3% |
+ 49.7% |
+ 1.29 |
+ 0.79 |
+
+
+ | BXD39 |
+ 6 |
+ 0.327 |
+ 63.12 |
+ 46.2% |
+ 4.3% |
+ 49.6% |
+ 1.29 |
+ 0.77 |
+
+
+ | BXD40 |
+ 1 |
+ 0.371 |
+ 60.01 |
+ 45.2% |
+ 4.1% |
+ 50.7% |
+ 1.32 |
+ 0.77 |
+
+
+ | BXD40 |
+ 2 |
+ 0.245 |
+ 84.69 |
+ 49.1% |
+ 4.5% |
+ 46.4% |
+ 1.33 |
+ 0.72 |
+
+
+ | BXD40 |
+ 3 |
+ 0.324 |
+ 64.17 |
+ 46.8% |
+ 4.3% |
+ 48.8% |
+ 1.34 |
+ 0.73 |
+
+
+ | BXD40 |
+ 4 |
+ 0.280 |
+ 63.97 |
+ 45.1% |
+ 4.2% |
+ 50.7% |
+ 1.48 |
+ 0.74 |
+
+
+ | BXD40 |
+ 5 |
+ 0.271 |
+ 69.40 |
+ 45.9% |
+ 4.3% |
+ 49.8% |
+ 1.33 |
+ 0.74 |
+
+
+ | BXD40 |
+ 6 |
+ 0.307 |
+ 59.99 |
+ 45.5% |
+ 4.2% |
+ 50.4% |
+ 1.37 |
+ 0.76 |
+
+
+ | BXD42 |
+ 1 |
+ 0.424 |
+ 53.91 |
+ 45.1% |
+ 4.1% |
+ 50.8% |
+ 1.54 |
+ 0.83 |
+
+
+ | BXD42 |
+ 2 |
+ 0.216 |
+ 92.34 |
+ 46.7% |
+ 4.3% |
+ 49.1% |
+ 1.44 |
+ 0.76 |
+
+
+ | BXD42 |
+ 3 |
+ 0.249 |
+ 84.52 |
+ 45.7% |
+ 4.1% |
+ 50.2% |
+ 1.52 |
+ 0.80 |
+
+
+ | BXD42 |
+ 5 |
+ 0.236 |
+ 85.29 |
+ 46.2% |
+ 4.0% |
+ 49.8% |
+ 1.38 |
+ 0.77 |
+
+
+ | DBA/2J |
+ 1 |
+ 0.313 |
+ 79.69 |
+ 46.8% |
+ 4.2% |
+ 49.0% |
+ 1.24 |
+ 0.72 |
+
+
+ | DBA/2J |
+ 2 |
+ 0.294 |
+ 82.27 |
+ 46.5% |
+ 4.2% |
+ 49.3% |
+ 1.27 |
+ 0.73 |
+
+
+ | DBA/2J |
+ 3 |
+ 0.349 |
+ 78.58 |
+ 47.8% |
+ 4.3% |
+ 47.8% |
+ 1.31 |
+ 0.73 |
+
+
+ | DBA/2J |
+ 4 |
+ 0.389 |
+ 72.02 |
+ 48.0% |
+ 4.3% |
+ 47.7% |
+ 1.21 |
+ 0.77 |
+
+
+ | DBA/2J |
+ 5 |
+ 0.362 |
+ 66.73 |
+ 46.5% |
+ 4.4% |
+ 49.1% |
+ 1.23 |
+ 0.75 |
+
+
+ | DBA/2J |
+ 6 |
+ 0.341 |
+ 79.88 |
+ 46.7% |
+ 4.0% |
+ 49.4% |
+ 1.33 |
+ 0.74 |
+
+
+ | C57BL/6J |
+ 1 |
+ 0.294 |
+ 82.84 |
+ 46.7% |
+ 4.1% |
+ 49.2% |
+ 1.23 |
+ 0.76 |
+
+
+ | C57BL/6J |
+ 2 |
+ 0.242 |
+ 80.40 |
+ 43.1% |
+ 4.1% |
+ 52.8% |
+ 1.29 |
+ 0.76 |
+
+
+ | C57BL/6J |
+ 3 |
+ 0.250 |
+ 110.90 |
+ 47.8% |
+ 4.0% |
+ 48.2% |
+ 1.32 |
+ 0.76 |
+
+
+ | C57BL/6J |
+ 4 |
+ 0.289 |
+ 101.88 |
+ 47.5% |
+ 4.1% |
+ 48.4% |
+ 1.18 |
+ 0.75 |
+
+
+ | C57BL/6J |
+ 5 |
+ 0.299 |
+ 114.59 |
+ 48.7% |
+ 4.1% |
+ 47.3% |
+ 1.13 |
+ 0.74 |
+
+
+ | C57BL/6J |
+ 6 |
+ 0.251 |
+ 105.90 |
+ 45.8% |
+ 3.8% |
+ 50.4% |
+ 1.30 |
+ 0.76 |
+
+
+ | 129P3/J |
+ 1 |
+ 0.496 |
+ 59.26 |
+ 41.9% |
+ 3.5% |
+ 54.5% |
+ 1.28 |
+ 0.79 |
+
+
+ | 129P3/J |
+ 2 |
+ 0.550 |
+ 50.83 |
+ 42.0% |
+ 3.7% |
+ 54.3% |
+ 1.16 |
+ 0.78 |
+
+
+ | 129P3/J |
+ 3 |
+ 0.443 |
+ 56.08 |
+ 43.0% |
+ 3.8% |
+ 53.3% |
+ 1.22 |
+ 0.73 |
+
+
+ | 129P3/J |
+ 4 |
+ 0.521 |
+ 58.92 |
+ 44.8% |
+ 3.8% |
+ 51.4% |
+ 1.30 |
+ 0.74 |
+
+
+ | 129P3/J |
+ 5 |
+ 0.503 |
+ 58.26 |
+ 44.9% |
+ 3.8% |
+ 51.3% |
+ 1.32 |
+ 0.74 |
+
+
+ | 129S1/SvImJ |
+ 1 |
+ 0.311 |
+ 66.76 |
+ 47.8% |
+ 3.9% |
+ 48.3% |
+ 2.04 |
+ 0.97 |
+
+
+ | 129S1/SvImJ |
+ 2 |
+ 0.262 |
+ 57.63 |
+ 44.5% |
+ 3.9% |
+ 51.6% |
+ 1.61 |
+ 0.81 |
+
+
+ | 129S1/SvImJ |
+ 3 |
+ 0.322 |
+ 62.67 |
+ 45.3% |
+ 3.8% |
+ 50.9% |
+ 1.70 |
+ 0.83 |
+
+
+ | 129S1/SvImJ |
+ 4 |
+ 0.185 |
+ 119.02 |
+ 50.2% |
+ 4.4% |
+ 45.5% |
+ 1.66 |
+ 0.75 |
+
+
+ | A/J |
+ 1 |
+ 0.453 |
+ 51.85 |
+ 42.6% |
+ 3.6% |
+ 53.8% |
+ 1.20 |
+ 0.73 |
+
+
+ | A/J |
+ 2 |
+ 0.396 |
+ 56.61 |
+ 45.9% |
+ 3.9% |
+ 50.2% |
+ 1.21 |
+ 0.76 |
+
+
+ | A/J |
+ 3 |
+ 0.421 |
+ 62.34 |
+ 47.0% |
+ 4.1% |
+ 48.8% |
+ 1.29 |
+ 0.72 |
+
+
+ | A/J |
+ 4 |
+ 0.508 |
+ 61.52 |
+ 48.2% |
+ 4.1% |
+ 47.7% |
+ 1.22 |
+ 0.74 |
+
+
+ | AKR/J |
+ 1 |
+ 0.331 |
+ 54.70 |
+ 41.7% |
+ 3.9% |
+ 54.4% |
+ 1.22 |
+ 0.74 |
+
+
+ | AKR/J |
+ 2 |
+ 0.464 |
+ 55.46 |
+ 44.1% |
+ 3.7% |
+ 52.1% |
+ 1.30 |
+ 0.76 |
+
+
+ | AKR/J |
+ 4 |
+ 0.444 |
+ 53.62 |
+ 47.6% |
+ 4.0% |
+ 48.4% |
+ 1.23 |
+ 0.71 |
+
+
+ | AKR/J |
+ 5 |
+ 0.439 |
+ 58.62 |
+ 47.4% |
+ 4.3% |
+ 48.3% |
+ 1.23 |
+ 0.70 |
+
+
+ | BALB/cByJ |
+ 1 |
+ 0.336 |
+ 75.49 |
+ 50.0% |
+ 4.1% |
+ 45.9% |
+ 1.54 |
+ 0.82 |
+
+
+ | BALB/cByJ |
+ 2 |
+ 0.280 |
+ 67.93 |
+ 47.1% |
+ 4.3% |
+ 48.7% |
+ 1.43 |
+ 0.76 |
+
+
+ | BALB/cByJ |
+ 3 |
+ 0.312 |
+ 73.77 |
+ 47.7% |
+ 4.1% |
+ 48.2% |
+ 1.79 |
+ 0.92 |
+
+
+ | BALB/cByJ |
+ 4 |
+ 0.262 |
+ 79.97 |
+ 46.1% |
+ 4.1% |
+ 49.8% |
+ 1.38 |
+ 0.79 |
+
+
+ | BALB/cByJ |
+ 5 |
+ 0.276 |
+ 81.32 |
+ 46.3% |
+ 4.1% |
+ 49.6% |
+ 1.34 |
+ 0.79 |
+
+
+ | BALB/cJ |
+ 1 |
+ 0.591 |
+ 54.25 |
+ 43.2% |
+ 3.5% |
+ 53.3% |
+ 1.15 |
+ 0.80 |
+
+
+ | BALB/cJ |
+ 2 |
+ 0.346 |
+ 50.36 |
+ 39.9% |
+ 3.3% |
+ 56.8% |
+ 1.20 |
+ 0.77 |
+
+
+ | BALB/cJ |
+ 3 |
+ 0.333 |
+ 52.79 |
+ 40.4% |
+ 3.7% |
+ 55.9% |
+ 1.25 |
+ 0.77 |
+
+
+ | BALB/cJ |
+ 5 |
+ 0.495 |
+ 54.78 |
+ 45.0% |
+ 3.7% |
+ 51.3% |
+ 1.15 |
+ 0.72 |
+
+
+ | BTBR T+tf/J |
+ 3 |
+ 0.315 |
+ 62.83 |
+ 46.4% |
+ 4.1% |
+ 49.5% |
+ 1.38 |
+ 0.78 |
+
+
+ | BTBR T+tf/J |
+ 4 |
+ 0.243 |
+ 90.12 |
+ 51.6% |
+ 4.8% |
+ 43.6% |
+ 1.31 |
+ 0.75 |
+
+
+ | BTBR T+tf/J |
+ 5 |
+ 0.294 |
+ 71.21 |
+ 46.6% |
+ 4.3% |
+ 49.0% |
+ 1.41 |
+ 0.77 |
+
+
+ | BTBR T+tf/J |
+ 6 |
+ 0.268 |
+ 67.53 |
+ 46.6% |
+ 4.2% |
+ 49.2% |
+ 1.32 |
+ 0.75 |
+
+
+ | BTBR T+tf/J |
+ 1 |
+ 0.370 |
+ 55.40 |
+ 45.7% |
+ 4.1% |
+ 50.2% |
+ 1.41 |
+ 0.75 |
+
+
+ | BTBR T+tf/J |
+ 2 |
+ 0.488 |
+ 50.89 |
+ 47.2% |
+ 4.2% |
+ 48.6% |
+ 1.36 |
+ 0.75 |
+
+
+ | C3H/HeJ |
+ 1 |
+ 0.511 |
+ 59.20 |
+ 43.3% |
+ 3.4% |
+ 53.3% |
+ 1.17 |
+ 0.83 |
+
+
+ | C3H/HeJ |
+ 2 |
+ 0.405 |
+ 79.49 |
+ 41.3% |
+ 3.3% |
+ 55.5% |
+ 1.18 |
+ 0.83 |
+
+
+ | C3H/HeJ |
+ 3 |
+ 0.454 |
+ 59.47 |
+ 41.7% |
+ 3.5% |
+ 54.9% |
+ 1.16 |
+ 0.81 |
+
+
+ | C3H/HeJ |
+ 4 |
+ 0.448 |
+ 56.28 |
+ 41.5% |
+ 3.5% |
+ 55.0% |
+ 1.16 |
+ 0.79 |
+
+
+ | C3H/HeJ |
+ 5 |
+ 0.389 |
+ 50.17 |
+ 41.1% |
+ 3.6% |
+ 55.2% |
+ 1.24 |
+ 0.79 |
+
+
+ | C58/J |
+ 1 |
+ 0.336 |
+ 56.66 |
+ 46.0% |
+ 4.2% |
+ 49.8% |
+ 1.29 |
+ 0.73 |
+
+
+ | C58/J |
+ 2 |
+ 0.372 |
+ 58.61 |
+ 46.7% |
+ 4.3% |
+ 49.0% |
+ 1.21 |
+ 0.71 |
+
+
+ | C58/J |
+ 3 |
+ 0.366 |
+ 64.58 |
+ 46.8% |
+ 4.2% |
+ 49.0% |
+ 1.20 |
+ 0.72 |
+
+
+ | C58/J |
+ 4 |
+ 0.371 |
+ 52.72 |
+ 45.3% |
+ 4.1% |
+ 50.6% |
+ 1.24 |
+ 0.72 |
+
+
+ | CAST/EiJ |
+ 1 |
+ 0.467 |
+ 55.74 |
+ 47.1% |
+ 3.8% |
+ 49.1% |
+ 1.39 |
+ 0.79 |
+
+
+ | CAST/EiJ |
+ 2 |
+ 0.545 |
+ 50.29 |
+ 46.8% |
+ 3.8% |
+ 49.4% |
+ 1.34 |
+ 0.84 |
+
+
+ | CAST/EiJ |
+ 3 |
+ 0.469 |
+ 55.08 |
+ 47.4% |
+ 4.0% |
+ 48.5% |
+ 1.32 |
+ 0.76 |
+
+
+ | CAST/EiJ |
+ 4 |
+ 0.390 |
+ 83.05 |
+ 53.0% |
+ 4.4% |
+ 42.6% |
+ 1.36 |
+ 0.72 |
+
+
+ | CBA/J |
+ 1 |
+ 0.292 |
+ 67.25 |
+ 44.9% |
+ 4.0% |
+ 51.2% |
+ 1.22 |
+ 0.76 |
+
+
+ | CBA/J |
+ 2 |
+ 0.347 |
+ 61.99 |
+ 46.4% |
+ 4.0% |
+ 49.7% |
+ 1.25 |
+ 0.82 |
+
+
+ | CBA/J |
+ 3 |
+ 0.305 |
+ 62.16 |
+ 46.3% |
+ 4.3% |
+ 49.4% |
+ 1.31 |
+ 0.75 |
+
+
+ | CBA/J |
+ 4 |
+ 0.303 |
+ 64.82 |
+ 46.5% |
+ 4.0% |
+ 49.5% |
+ 1.34 |
+ 0.76 |
+
+
+ | CBA/J |
+ 5 |
+ 0.313 |
+ 64.15 |
+ 45.3% |
+ 4.1% |
+ 50.7% |
+ 1.37 |
+ 0.78 |
+
+
+ | CBA/J |
+ 6 |
+ 0.365 |
+ 56.84 |
+ 45.6% |
+ 4.1% |
+ 50.4% |
+ 1.31 |
+ 0.76 |
+
+
+ | FVB/NJ |
+ 1 |
+ 0.497 |
+ 63.99 |
+ 44.2% |
+ 3.5% |
+ 52.3% |
+ 1.33 |
+ 0.79 |
+
+
+ | FVB/NJ |
+ 2 |
+ 0.475 |
+ 55.24 |
+ 44.8% |
+ 3.8% |
+ 51.4% |
+ 1.33 |
+ 0.74 |
+
+
+ | FVB/NJ |
+ 3 |
+ 0.527 |
+ 56.07 |
+ 42.6% |
+ 3.5% |
+ 53.9% |
+ 1.31 |
+ 0.86 |
+
+
+ | FVB/NJ |
+ 4 |
+ 0.447 |
+ 62.56 |
+ 41.7% |
+ 3.5% |
+ 54.8% |
+ 1.24 |
+ 0.82 |
+
+
+ | KK/HIJ |
+ 1 |
+ 0.309 |
+ 93.54 |
+ 49.6% |
+ 4.3% |
+ 46.1% |
+ 1.57 |
+ 0.74 |
+
+
+ | KK/HIJ |
+ 2 |
+ 0.298 |
+ 63.24 |
+ 48.0% |
+ 4.4% |
+ 47.6% |
+ 1.37 |
+ 0.72 |
+
+
+ | KK/HIJ |
+ 4 |
+ 0.223 |
+ 93.03 |
+ 44.7% |
+ 4.0% |
+ 51.3% |
+ 1.39 |
+ 0.74 |
+
+
+ | KK/HIJ |
+ 5 |
+ 0.153 |
+ 136.67 |
+ 51.9% |
+ 4.6% |
+ 43.5% |
+ 1.24 |
+ 0.71 |
+
+
+ | MOLF/EiJ |
+ 1 |
+ 0.339 |
+ 67.11 |
+ 49.1% |
+ 4.3% |
+ 46.6% |
+ 1.55 |
+ 0.83 |
+
+
+ | MOLF/EiJ |
+ 2 |
+ 0.319 |
+ 80.73 |
+ 49.1% |
+ 4.2% |
+ 46.7% |
+ 1.52 |
+ 0.78 |
+
+
+ | MOLF/EiJ |
+ 3 |
+ 0.380 |
+ 69.03 |
+ 49.1% |
+ 4.2% |
+ 46.7% |
+ 1.29 |
+ 0.82 |
+
+
+ | MOLF/EiJ |
+ 4 |
+ 0.238 |
+ 95.19 |
+ 48.7% |
+ 4.1% |
+ 47.2% |
+ 1.35 |
+ 0.79 |
+
+
+ | NOD/LtJ |
+ 1 |
+ 0.356 |
+ 78.42 |
+ 49.1% |
+ 4.2% |
+ 46.7% |
+ 1.35 |
+ 0.76 |
+
+
+ | NOD/LtJ |
+ 2 |
+ 0.422 |
+ 59.71 |
+ 47.4% |
+ 4.0% |
+ 48.5% |
+ 1.25 |
+ 0.73 |
+
+
+ | NOD/LtJ |
+ 3 |
+ 0.377 |
+ 77.84 |
+ 49.8% |
+ 4.0% |
+ 46.2% |
+ 1.24 |
+ 0.75 |
+
+
+ | NOD/LtJ |
+ 4 |
+ 0.535 |
+ 60.86 |
+ 50.6% |
+ 4.4% |
+ 45.0% |
+ 1.28 |
+ 0.74 |
+
+
+ | NOD/LtJ |
+ 5 |
+ 0.336 |
+ 74.58 |
+ 46.6% |
+ 3.9% |
+ 49.5% |
+ 1.32 |
+ 0.72 |
+
+
+ | NZW/LacJ |
+ 2 |
+ 0.442 |
+ 50.31 |
+ 44.6% |
+ 4.1% |
+ 51.3% |
+ 1.33 |
+ 0.82 |
+
+
+ | NZW/LacJ |
+ 3 |
+ 0.331 |
+ 56.86 |
+ 44.2% |
+ 4.0% |
+ 51.7% |
+ 1.60 |
+ 0.78 |
+
+
+ | NZW/LacJ |
+ 4 |
+ 0.338 |
+ 55.23 |
+ 44.1% |
+ 4.0% |
+ 51.9% |
+ 1.31 |
+ 0.78 |
+
+
+ | NZW/LacJ |
+ 5 |
+ 0.351 |
+ 56.90 |
+ 49.3% |
+ 4.3% |
+ 46.5% |
+ 1.30 |
+ 0.75 |
+
+
+ | PWD/PhJ |
+ 1 |
+ 0.444 |
+ 57.65 |
+ 47.2% |
+ 3.9% |
+ 48.9% |
+ 1.62 |
+ 0.78 |
+
+
+ | PWD/PhJ |
+ 2 |
+ 0.328 |
+ 67.58 |
+ 47.3% |
+ 4.2% |
+ 48.5% |
+ 1.36 |
+ 0.76 |
+
+
+ | PWD/PhJ |
+ 3 |
+ 0.322 |
+ 73.90 |
+ 47.5% |
+ 4.0% |
+ 48.5% |
+ 1.46 |
+ 0.81 |
+
+
+ | PWD/PhJ |
+ 4 |
+ 0.271 |
+ 75.79 |
+ 46.1% |
+ 4.0% |
+ 50.0% |
+ 1.39 |
+ 0.79 |
+
+
+ | PWD/PhJ |
+ 5 |
+ 0.191 |
+ 144.73 |
+ 57.7% |
+ 5.0% |
+ 37.3% |
+ 1.36 |
+ 0.67 |
+
+
+ | SJL/J |
+ 1 |
+ 0.528 |
+ 54.58 |
+ 41.1% |
+ 3.4% |
+ 55.4% |
+ 1.16 |
+ 0.80 |
+
+
+ | SJL/J |
+ 3 |
+ 0.663 |
+ 56.21 |
+ 41.8% |
+ 3.3% |
+ 55.0% |
+ 1.22 |
+ 0.75 |
+
+
+ | SJL/J |
+ 4 |
+ 0.646 |
+ 52.96 |
+ 40.5% |
+ 3.2% |
+ 56.3% |
+ 1.13 |
+ 0.81 |
+
+
+ | SJL/J |
+ 5 |
+ 0.639 |
+ 61.91 |
+ 44.8% |
+ 3.4% |
+ 51.9% |
+ 1.37 |
+ 0.79 |
+
+
+
+
diff --git a/general/datasets/Br_u_0303_m/acknowledgment.rtf b/general/datasets/Br_u_0303_m/acknowledgment.rtf
new file mode 100644
index 0000000..1efbf49
--- /dev/null
+++ b/general/datasets/Br_u_0303_m/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0303_m/cases.rtf b/general/datasets/Br_u_0303_m/cases.rtf
new file mode 100644
index 0000000..38a782c
--- /dev/null
+++ b/general/datasets/Br_u_0303_m/cases.rtf
@@ -0,0 +1,230 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice. Note that this table includes six arrays dropped from the December 2003 data sets (BXD6, n=2; BXD12, BXD16, BXD40, and BXD67, n=1 each).
+
+
diff --git a/general/datasets/Br_u_0303_m/experiment-type.rtf b/general/datasets/Br_u_0303_m/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Br_u_0303_m/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Br_u_0303_m/notes.rtf b/general/datasets/Br_u_0303_m/notes.rtf
new file mode 100644
index 0000000..68a18e4
--- /dev/null
+++ b/general/datasets/Br_u_0303_m/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, EJC, and YHQ, August 2003. Updated by RWW, October 30, 2004.
diff --git a/general/datasets/Br_u_0303_m/platform.rtf b/general/datasets/Br_u_0303_m/platform.rtf
new file mode 100644
index 0000000..e8ac283
--- /dev/null
+++ b/general/datasets/Br_u_0303_m/platform.rtf
@@ -0,0 +1 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 100 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Br_u_0303_m/processing.rtf b/general/datasets/Br_u_0303_m/processing.rtf
new file mode 100644
index 0000000..9b386b5
--- /dev/null
+++ b/general/datasets/Br_u_0303_m/processing.rtf
@@ -0,0 +1,27 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal intensity.
+ - Step 3: We computed the Z score for each of these log2 cell signal intensity values within a single array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added a constant of 8 units to the value of the Z score. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units. The advantage of this modified Z score is that a 2-fold difference in expression level corresponds roughly to 1 unit.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each strain. We have not corrected for variance introduced by sex, age, source of animals, or any possible interaction. We have not corrected for background beyond that implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 106 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
+
+About the array probe set names:
+
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target): Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
diff --git a/general/datasets/Br_u_0303_m/summary.rtf b/general/datasets/Br_u_0303_m/summary.rtf
new file mode 100644
index 0000000..7826a5c
--- /dev/null
+++ b/general/datasets/Br_u_0303_m/summary.rtf
@@ -0,0 +1 @@
+This August 2003 freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. This is data set includes six arrays which are of marginal quality. New users are encouraged to use one of the more recent data sets (December 2003 or March 2004) from which these six arrays have been excluded. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 106 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. In general, the MAS 5 transform does not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0303_m/tissue.rtf b/general/datasets/Br_u_0303_m/tissue.rtf
new file mode 100644
index 0000000..6961982
--- /dev/null
+++ b/general/datasets/Br_u_0303_m/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 100 such pooled samples were arrayed: 74 from females and 26 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0304_dpmmr/acknowledgment.rtf b/general/datasets/Br_u_0304_dpmmr/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmmr/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0304_dpmmr/cases.rtf b/general/datasets/Br_u_0304_dpmmr/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmmr/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_0304_dpmmr/notes.rtf b/general/datasets/Br_u_0304_dpmmr/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmmr/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_0304_dpmmr/platform.rtf b/general/datasets/Br_u_0304_dpmmr/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmmr/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_0304_dpmmr/processing.rtf b/general/datasets/Br_u_0304_dpmmr/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmmr/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_0304_dpmmr/summary.rtf b/general/datasets/Br_u_0304_dpmmr/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmmr/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0304_dpmmr/tissue.rtf b/general/datasets/Br_u_0304_dpmmr/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmmr/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0304_dpmr/acknowledgment.rtf b/general/datasets/Br_u_0304_dpmr/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmr/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0304_dpmr/cases.rtf b/general/datasets/Br_u_0304_dpmr/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmr/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_0304_dpmr/notes.rtf b/general/datasets/Br_u_0304_dpmr/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmr/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_0304_dpmr/platform.rtf b/general/datasets/Br_u_0304_dpmr/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmr/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_0304_dpmr/processing.rtf b/general/datasets/Br_u_0304_dpmr/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmr/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_0304_dpmr/summary.rtf b/general/datasets/Br_u_0304_dpmr/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmr/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0304_dpmr/tissue.rtf b/general/datasets/Br_u_0304_dpmr/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_0304_dpmr/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0304_r/acknowledgment.rtf b/general/datasets/Br_u_0304_r/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_0304_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0304_r/cases.rtf b/general/datasets/Br_u_0304_r/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_0304_r/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_0304_r/notes.rtf b/general/datasets/Br_u_0304_r/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_0304_r/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_0304_r/platform.rtf b/general/datasets/Br_u_0304_r/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_0304_r/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_0304_r/processing.rtf b/general/datasets/Br_u_0304_r/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_0304_r/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_0304_r/summary.rtf b/general/datasets/Br_u_0304_r/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_0304_r/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0304_r/tissue.rtf b/general/datasets/Br_u_0304_r/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_0304_r/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0304_rr/acknowledgment.rtf b/general/datasets/Br_u_0304_rr/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_0304_rr/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0304_rr/cases.rtf b/general/datasets/Br_u_0304_rr/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_0304_rr/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_0304_rr/notes.rtf b/general/datasets/Br_u_0304_rr/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_0304_rr/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_0304_rr/platform.rtf b/general/datasets/Br_u_0304_rr/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_0304_rr/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_0304_rr/processing.rtf b/general/datasets/Br_u_0304_rr/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_0304_rr/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_0304_rr/summary.rtf b/general/datasets/Br_u_0304_rr/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_0304_rr/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0304_rr/tissue.rtf b/general/datasets/Br_u_0304_rr/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_0304_rr/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0405_ss/acknowledgment.rtf b/general/datasets/Br_u_0405_ss/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_0405_ss/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0405_ss/cases.rtf b/general/datasets/Br_u_0405_ss/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_0405_ss/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_0405_ss/notes.rtf b/general/datasets/Br_u_0405_ss/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_0405_ss/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_0405_ss/platform.rtf b/general/datasets/Br_u_0405_ss/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_0405_ss/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_0405_ss/processing.rtf b/general/datasets/Br_u_0405_ss/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_0405_ss/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_0405_ss/summary.rtf b/general/datasets/Br_u_0405_ss/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_0405_ss/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0405_ss/tissue.rtf b/general/datasets/Br_u_0405_ss/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_0405_ss/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0503_m/acknowledgment.rtf b/general/datasets/Br_u_0503_m/acknowledgment.rtf
new file mode 100644
index 0000000..5f21aed
--- /dev/null
+++ b/general/datasets/Br_u_0503_m/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
+
diff --git a/general/datasets/Br_u_0503_m/cases.rtf b/general/datasets/Br_u_0503_m/cases.rtf
new file mode 100644
index 0000000..bc98bcb
--- /dev/null
+++ b/general/datasets/Br_u_0503_m/cases.rtf
@@ -0,0 +1,216 @@
+The set of animals used for mapping (a mapping panel) consists of 30 groups of genetically uniform mice of the BXD type. The parental strains are C57BL/6J (B6 or B) and DBA/2J (D2 or D). The first generation hybrid is labeled F1. The F1 hybrids were made by crossing B6 females to D2 males. All other lines are recombinant inbred strains derived from C57BL/6J and DBA/2J crosses. BXD2 through BXD32 were produced by Dr. Benjamin Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Dr. Taylor, but they were generated in the 1990s. Lines BXD67 and BXD68 are two partially inbred advanced recombinant strains (F8 and F9) that are part of a large set of BXD-Advanced strains being produced by Drs. Robert Williams, Lu Lu, Lee Silver, and Jeremy Peirce. There will eventually be ~45 of these strains. For additional background on recombinant inbred strains, please see http://www.nervenet.org/papers/bxn.html.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from 3 mice.
+
+
+
+
+
+
+
+
+ | Strain |
+
+ Age
+ |
+ Strain |
+
+ Age
+ |
+
+
+ |
+ 8 Wks
+ |
+
+ 20 Wks
+ |
+
+ 52 Wks
+ |
+
+ 8 Wks
+ |
+
+ 20 Wks
+ |
+
+ 52 Wks
+ |
+
+
+ | C57BL/6J (B6) |
+ ♂♂♂ |
+ ♀ |
+ ♀ |
+ DBA/2J (D2) |
+ ♀ |
+ ♂♂♀ |
+ |
+
+
+ | B6D2F1 (F1) |
+ ♀ ♀ |
+ ♀ |
+ |
+ BXD1 |
+ ♀♀ |
+ |
+ ♀ |
+
+
+ | BXD2 |
+ ♂ |
+ ♀ |
+ ♀ |
+ BXD5 |
+ ♂♀ |
+ |
+ |
+
+
+ | BXD6 |
+ ♀ |
+ ♀ |
+ ♀ |
+ BXD8 |
+ ♀ |
+ ♂♀ |
+ |
+
+
+ | BXD9 |
+ ♂ |
+ ♀ |
+ ♀ |
+ BXD11 |
+ ♀♀ |
+ |
+ ♀ |
+
+
+ | BXD12 |
+ |
+ ♂♀ |
+ ♀ |
+ BXD13 |
+ ♀ |
+ |
+ |
+
+
+ | BXD14 |
+ |
+ ♀♀ |
+ ♀ |
+ BXD15 |
+ ♀ |
+ |
+ ♀ |
+
+
+ | BXD16 |
+ ♀ |
+ ♀♀ |
+ |
+ BXD18 |
+ ♀ |
+ ♂ |
+ ♀ |
+
+
+ | BXD19 |
+ ♀ |
+ ♀ |
+ ♀ |
+ BXD21 |
+ ♀ |
+ ♂♂ |
+ |
+
+
+ | BXD22 |
+ ♀ |
+ ♀♀ |
+ |
+ BXD24 |
+ ♀♀ |
+ |
+ ♀ |
+
+
+ | BXD25 |
+ ♀♀ |
+ ♀♀ |
+ |
+ BXD27 |
+ |
+ |
+ ♀♀ |
+
+
+ | BXD28 |
+ ♀ |
+ ♀ |
+ ♀ |
+ BXD29 |
+ ♂ |
+ |
+ ♀ |
+
+
+ | BXD31 |
+ ♀♀ |
+ ♀♀ |
+ |
+ BXD32 |
+ ♀ |
+ ♂♀ |
+ ♀ |
+
+
+ | BXD33 |
+ ♂♀ |
+ ♀ |
+ |
+ BXD34 |
+ ♂♀ |
+ ♀ |
+ |
+
+
+ | BXD39 |
+ ♂♀ |
+ ♂ |
+ |
+ BXD40 |
+ ♂♂♀♀ |
+ |
+ |
+
+
+ | BXD42 |
+ ♂♂ ♀ |
+ |
+ |
+ BXD67 |
+ ♀ |
+ |
+ |
+
+
+ | BXD68 (F9) |
+ ♀ ♀ |
+ |
+ |
+ |
+ |
+ |
+ |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Br_u_0503_m/experiment-type.rtf b/general/datasets/Br_u_0503_m/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Br_u_0503_m/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Br_u_0503_m/notes.rtf b/general/datasets/Br_u_0503_m/notes.rtf
new file mode 100644
index 0000000..d198112
--- /dev/null
+++ b/general/datasets/Br_u_0503_m/notes.rtf
@@ -0,0 +1,5 @@
+Information about this text file:
+
+
+This text file originally generated by RWW, EJC, and YHQ, May 2003. Updated by RWW, October 30, 2004.
+
diff --git a/general/datasets/Br_u_0503_m/platform.rtf b/general/datasets/Br_u_0503_m/platform.rtf
new file mode 100644
index 0000000..04f8269
--- /dev/null
+++ b/general/datasets/Br_u_0503_m/platform.rtf
@@ -0,0 +1,16 @@
+About the array probe set names:
+
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target): Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
diff --git a/general/datasets/Br_u_0503_m/processing.rtf b/general/datasets/Br_u_0503_m/processing.rtf
new file mode 100644
index 0000000..e763fc9
--- /dev/null
+++ b/general/datasets/Br_u_0503_m/processing.rtf
@@ -0,0 +1,14 @@
+Probe (cell) level data from the CEL file: These CEL values produced by MAS 5 are the 75% quantiles from a set of 36 pixel values per cell (the pixel with the 12th highest value represents the whole cell).
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell.
+ - Step 3: We computed the Z score for each cell.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each of the individual strains. We have not corrected for variance introduced by sex, age, or a sex-by-age interaction. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the .TXT file: These .TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefor represents roughly a 2-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers were initially determined by BLAT analysis using the Mouse Genome Sequencing Consortium OCT 2003 Assembly (see http://genome.ucsc.edu/). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Br_u_0503_m/summary.rtf b/general/datasets/Br_u_0503_m/summary.rtf
new file mode 100644
index 0000000..2d69c8a
--- /dev/null
+++ b/general/datasets/Br_u_0503_m/summary.rtf
@@ -0,0 +1 @@
+This May 2003 freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. New users are encouraged to use one of the more recent data sets (December 2003 or March 2004). Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 33 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. In general, these MAS 5 transforms do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0503_m/tissue.rtf b/general/datasets/Br_u_0503_m/tissue.rtf
new file mode 100644
index 0000000..045e2a2
--- /dev/null
+++ b/general/datasets/Br_u_0503_m/tissue.rtf
@@ -0,0 +1 @@
+Most expression data are averages based on three microarrays (U74Av2). Each individual array experiment involved a pool of brain tissue (forebrain plus the midbrain, but without the olfactory bulb) that was taken from three adult animals usually of the same age. A total of 97 arrays were used: 74 were female pools and 23 were male pools. Animals ranged in age from 56 to 441 days, usually with a balanced design (one pool at 8 weeks, one pool at ~20 weeks, one pool at approximately 1 year).
diff --git a/general/datasets/Br_u_0603_m/acknowledgment.rtf b/general/datasets/Br_u_0603_m/acknowledgment.rtf
new file mode 100644
index 0000000..1efbf49
--- /dev/null
+++ b/general/datasets/Br_u_0603_m/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0603_m/cases.rtf b/general/datasets/Br_u_0603_m/cases.rtf
new file mode 100644
index 0000000..38a782c
--- /dev/null
+++ b/general/datasets/Br_u_0603_m/cases.rtf
@@ -0,0 +1,230 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice. Note that this table includes six arrays dropped from the December 2003 data sets (BXD6, n=2; BXD12, BXD16, BXD40, and BXD67, n=1 each).
+
+
diff --git a/general/datasets/Br_u_0603_m/experiment-type.rtf b/general/datasets/Br_u_0603_m/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Br_u_0603_m/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Br_u_0603_m/notes.rtf b/general/datasets/Br_u_0603_m/notes.rtf
new file mode 100644
index 0000000..68a18e4
--- /dev/null
+++ b/general/datasets/Br_u_0603_m/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, EJC, and YHQ, August 2003. Updated by RWW, October 30, 2004.
diff --git a/general/datasets/Br_u_0603_m/platform.rtf b/general/datasets/Br_u_0603_m/platform.rtf
new file mode 100644
index 0000000..e8ac283
--- /dev/null
+++ b/general/datasets/Br_u_0603_m/platform.rtf
@@ -0,0 +1 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 100 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Br_u_0603_m/processing.rtf b/general/datasets/Br_u_0603_m/processing.rtf
new file mode 100644
index 0000000..9b386b5
--- /dev/null
+++ b/general/datasets/Br_u_0603_m/processing.rtf
@@ -0,0 +1,27 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal intensity.
+ - Step 3: We computed the Z score for each of these log2 cell signal intensity values within a single array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added a constant of 8 units to the value of the Z score. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units. The advantage of this modified Z score is that a 2-fold difference in expression level corresponds roughly to 1 unit.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each strain. We have not corrected for variance introduced by sex, age, source of animals, or any possible interaction. We have not corrected for background beyond that implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 106 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
+
+About the array probe set names:
+
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target): Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
diff --git a/general/datasets/Br_u_0603_m/summary.rtf b/general/datasets/Br_u_0603_m/summary.rtf
new file mode 100644
index 0000000..7826a5c
--- /dev/null
+++ b/general/datasets/Br_u_0603_m/summary.rtf
@@ -0,0 +1 @@
+This August 2003 freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. This is data set includes six arrays which are of marginal quality. New users are encouraged to use one of the more recent data sets (December 2003 or March 2004) from which these six arrays have been excluded. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 106 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. In general, the MAS 5 transform does not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0603_m/tissue.rtf b/general/datasets/Br_u_0603_m/tissue.rtf
new file mode 100644
index 0000000..6961982
--- /dev/null
+++ b/general/datasets/Br_u_0603_m/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 100 such pooled samples were arrayed: 74 from females and 26 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0803_m/acknowledgment.rtf b/general/datasets/Br_u_0803_m/acknowledgment.rtf
new file mode 100644
index 0000000..1efbf49
--- /dev/null
+++ b/general/datasets/Br_u_0803_m/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0803_m/cases.rtf b/general/datasets/Br_u_0803_m/cases.rtf
new file mode 100644
index 0000000..38a782c
--- /dev/null
+++ b/general/datasets/Br_u_0803_m/cases.rtf
@@ -0,0 +1,230 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice. Note that this table includes six arrays dropped from the December 2003 data sets (BXD6, n=2; BXD12, BXD16, BXD40, and BXD67, n=1 each).
+
+
diff --git a/general/datasets/Br_u_0803_m/experiment-type.rtf b/general/datasets/Br_u_0803_m/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Br_u_0803_m/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Br_u_0803_m/notes.rtf b/general/datasets/Br_u_0803_m/notes.rtf
new file mode 100644
index 0000000..68a18e4
--- /dev/null
+++ b/general/datasets/Br_u_0803_m/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, EJC, and YHQ, August 2003. Updated by RWW, October 30, 2004.
diff --git a/general/datasets/Br_u_0803_m/platform.rtf b/general/datasets/Br_u_0803_m/platform.rtf
new file mode 100644
index 0000000..e8ac283
--- /dev/null
+++ b/general/datasets/Br_u_0803_m/platform.rtf
@@ -0,0 +1 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 100 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Br_u_0803_m/processing.rtf b/general/datasets/Br_u_0803_m/processing.rtf
new file mode 100644
index 0000000..9b386b5
--- /dev/null
+++ b/general/datasets/Br_u_0803_m/processing.rtf
@@ -0,0 +1,27 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal intensity.
+ - Step 3: We computed the Z score for each of these log2 cell signal intensity values within a single array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added a constant of 8 units to the value of the Z score. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units. The advantage of this modified Z score is that a 2-fold difference in expression level corresponds roughly to 1 unit.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each strain. We have not corrected for variance introduced by sex, age, source of animals, or any possible interaction. We have not corrected for background beyond that implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 106 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
+
+About the array probe set names:
+
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target): Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
diff --git a/general/datasets/Br_u_0803_m/summary.rtf b/general/datasets/Br_u_0803_m/summary.rtf
new file mode 100644
index 0000000..7826a5c
--- /dev/null
+++ b/general/datasets/Br_u_0803_m/summary.rtf
@@ -0,0 +1 @@
+This August 2003 freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. This is data set includes six arrays which are of marginal quality. New users are encouraged to use one of the more recent data sets (December 2003 or March 2004) from which these six arrays have been excluded. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 106 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. In general, the MAS 5 transform does not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0803_m/tissue.rtf b/general/datasets/Br_u_0803_m/tissue.rtf
new file mode 100644
index 0000000..6961982
--- /dev/null
+++ b/general/datasets/Br_u_0803_m/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 100 such pooled samples were arrayed: 74 from females and 26 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0805_m/acknowledgment.rtf b/general/datasets/Br_u_0805_m/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_0805_m/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0805_m/cases.rtf b/general/datasets/Br_u_0805_m/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_0805_m/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_0805_m/notes.rtf b/general/datasets/Br_u_0805_m/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_0805_m/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_0805_m/platform.rtf b/general/datasets/Br_u_0805_m/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_0805_m/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_0805_m/processing.rtf b/general/datasets/Br_u_0805_m/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_0805_m/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_0805_m/summary.rtf b/general/datasets/Br_u_0805_m/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_0805_m/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0805_m/tissue.rtf b/general/datasets/Br_u_0805_m/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_0805_m/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0805_p/acknowledgment.rtf b/general/datasets/Br_u_0805_p/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_0805_p/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0805_p/cases.rtf b/general/datasets/Br_u_0805_p/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_0805_p/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_0805_p/notes.rtf b/general/datasets/Br_u_0805_p/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_0805_p/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_0805_p/platform.rtf b/general/datasets/Br_u_0805_p/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_0805_p/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_0805_p/processing.rtf b/general/datasets/Br_u_0805_p/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_0805_p/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_0805_p/summary.rtf b/general/datasets/Br_u_0805_p/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_0805_p/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0805_p/tissue.rtf b/general/datasets/Br_u_0805_p/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_0805_p/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0805_r/acknowledgment.rtf b/general/datasets/Br_u_0805_r/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_0805_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0805_r/cases.rtf b/general/datasets/Br_u_0805_r/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_0805_r/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_0805_r/notes.rtf b/general/datasets/Br_u_0805_r/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_0805_r/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_0805_r/platform.rtf b/general/datasets/Br_u_0805_r/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_0805_r/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_0805_r/processing.rtf b/general/datasets/Br_u_0805_r/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_0805_r/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_0805_r/summary.rtf b/general/datasets/Br_u_0805_r/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_0805_r/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0805_r/tissue.rtf b/general/datasets/Br_u_0805_r/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_0805_r/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0903_dpm/acknowledgment.rtf b/general/datasets/Br_u_0903_dpm/acknowledgment.rtf
new file mode 100644
index 0000000..1efbf49
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpm/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0903_dpm/cases.rtf b/general/datasets/Br_u_0903_dpm/cases.rtf
new file mode 100644
index 0000000..38a782c
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpm/cases.rtf
@@ -0,0 +1,230 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice. Note that this table includes six arrays dropped from the December 2003 data sets (BXD6, n=2; BXD12, BXD16, BXD40, and BXD67, n=1 each).
+
+
diff --git a/general/datasets/Br_u_0903_dpm/notes.rtf b/general/datasets/Br_u_0903_dpm/notes.rtf
new file mode 100644
index 0000000..68a18e4
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpm/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, EJC, and YHQ, August 2003. Updated by RWW, October 30, 2004.
diff --git a/general/datasets/Br_u_0903_dpm/platform.rtf b/general/datasets/Br_u_0903_dpm/platform.rtf
new file mode 100644
index 0000000..e8ac283
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpm/platform.rtf
@@ -0,0 +1 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 100 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Br_u_0903_dpm/processing.rtf b/general/datasets/Br_u_0903_dpm/processing.rtf
new file mode 100644
index 0000000..9b386b5
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpm/processing.rtf
@@ -0,0 +1,27 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal intensity.
+ - Step 3: We computed the Z score for each of these log2 cell signal intensity values within a single array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added a constant of 8 units to the value of the Z score. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units. The advantage of this modified Z score is that a 2-fold difference in expression level corresponds roughly to 1 unit.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each strain. We have not corrected for variance introduced by sex, age, source of animals, or any possible interaction. We have not corrected for background beyond that implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 106 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
+
+About the array probe set names:
+
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target): Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
diff --git a/general/datasets/Br_u_0903_dpm/summary.rtf b/general/datasets/Br_u_0903_dpm/summary.rtf
new file mode 100644
index 0000000..7826a5c
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpm/summary.rtf
@@ -0,0 +1 @@
+This August 2003 freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. This is data set includes six arrays which are of marginal quality. New users are encouraged to use one of the more recent data sets (December 2003 or March 2004) from which these six arrays have been excluded. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 106 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. In general, the MAS 5 transform does not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0903_dpm/tissue.rtf b/general/datasets/Br_u_0903_dpm/tissue.rtf
new file mode 100644
index 0000000..6961982
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpm/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 100 such pooled samples were arrayed: 74 from females and 26 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0903_dpmm/acknowledgment.rtf b/general/datasets/Br_u_0903_dpmm/acknowledgment.rtf
new file mode 100644
index 0000000..1efbf49
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpmm/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0903_dpmm/cases.rtf b/general/datasets/Br_u_0903_dpmm/cases.rtf
new file mode 100644
index 0000000..38a782c
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpmm/cases.rtf
@@ -0,0 +1,230 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice. Note that this table includes six arrays dropped from the December 2003 data sets (BXD6, n=2; BXD12, BXD16, BXD40, and BXD67, n=1 each).
+
+
diff --git a/general/datasets/Br_u_0903_dpmm/notes.rtf b/general/datasets/Br_u_0903_dpmm/notes.rtf
new file mode 100644
index 0000000..68a18e4
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpmm/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, EJC, and YHQ, August 2003. Updated by RWW, October 30, 2004.
diff --git a/general/datasets/Br_u_0903_dpmm/platform.rtf b/general/datasets/Br_u_0903_dpmm/platform.rtf
new file mode 100644
index 0000000..e8ac283
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpmm/platform.rtf
@@ -0,0 +1 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 100 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Br_u_0903_dpmm/processing.rtf b/general/datasets/Br_u_0903_dpmm/processing.rtf
new file mode 100644
index 0000000..9b386b5
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpmm/processing.rtf
@@ -0,0 +1,27 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal intensity.
+ - Step 3: We computed the Z score for each of these log2 cell signal intensity values within a single array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added a constant of 8 units to the value of the Z score. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units. The advantage of this modified Z score is that a 2-fold difference in expression level corresponds roughly to 1 unit.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each strain. We have not corrected for variance introduced by sex, age, source of animals, or any possible interaction. We have not corrected for background beyond that implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 106 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
+
+About the array probe set names:
+
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target): Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
diff --git a/general/datasets/Br_u_0903_dpmm/summary.rtf b/general/datasets/Br_u_0903_dpmm/summary.rtf
new file mode 100644
index 0000000..7826a5c
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpmm/summary.rtf
@@ -0,0 +1 @@
+This August 2003 freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. This is data set includes six arrays which are of marginal quality. New users are encouraged to use one of the more recent data sets (December 2003 or March 2004) from which these six arrays have been excluded. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 106 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. In general, the MAS 5 transform does not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0903_dpmm/tissue.rtf b/general/datasets/Br_u_0903_dpmm/tissue.rtf
new file mode 100644
index 0000000..6961982
--- /dev/null
+++ b/general/datasets/Br_u_0903_dpmm/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 100 such pooled samples were arrayed: 74 from females and 26 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0903_m/acknowledgment.rtf b/general/datasets/Br_u_0903_m/acknowledgment.rtf
new file mode 100644
index 0000000..1efbf49
--- /dev/null
+++ b/general/datasets/Br_u_0903_m/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0903_m/cases.rtf b/general/datasets/Br_u_0903_m/cases.rtf
new file mode 100644
index 0000000..38a782c
--- /dev/null
+++ b/general/datasets/Br_u_0903_m/cases.rtf
@@ -0,0 +1,230 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice. Note that this table includes six arrays dropped from the December 2003 data sets (BXD6, n=2; BXD12, BXD16, BXD40, and BXD67, n=1 each).
+
+
diff --git a/general/datasets/Br_u_0903_m/notes.rtf b/general/datasets/Br_u_0903_m/notes.rtf
new file mode 100644
index 0000000..68a18e4
--- /dev/null
+++ b/general/datasets/Br_u_0903_m/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, EJC, and YHQ, August 2003. Updated by RWW, October 30, 2004.
diff --git a/general/datasets/Br_u_0903_m/platform.rtf b/general/datasets/Br_u_0903_m/platform.rtf
new file mode 100644
index 0000000..e8ac283
--- /dev/null
+++ b/general/datasets/Br_u_0903_m/platform.rtf
@@ -0,0 +1 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 100 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Br_u_0903_m/processing.rtf b/general/datasets/Br_u_0903_m/processing.rtf
new file mode 100644
index 0000000..9b386b5
--- /dev/null
+++ b/general/datasets/Br_u_0903_m/processing.rtf
@@ -0,0 +1,27 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal intensity.
+ - Step 3: We computed the Z score for each of these log2 cell signal intensity values within a single array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added a constant of 8 units to the value of the Z score. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units. The advantage of this modified Z score is that a 2-fold difference in expression level corresponds roughly to 1 unit.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each strain. We have not corrected for variance introduced by sex, age, source of animals, or any possible interaction. We have not corrected for background beyond that implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 106 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
+
+About the array probe set names:
+
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target): Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
diff --git a/general/datasets/Br_u_0903_m/summary.rtf b/general/datasets/Br_u_0903_m/summary.rtf
new file mode 100644
index 0000000..7826a5c
--- /dev/null
+++ b/general/datasets/Br_u_0903_m/summary.rtf
@@ -0,0 +1 @@
+This August 2003 freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. This is data set includes six arrays which are of marginal quality. New users are encouraged to use one of the more recent data sets (December 2003 or March 2004) from which these six arrays have been excluded. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 106 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. In general, the MAS 5 transform does not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0903_m/tissue.rtf b/general/datasets/Br_u_0903_m/tissue.rtf
new file mode 100644
index 0000000..6961982
--- /dev/null
+++ b/general/datasets/Br_u_0903_m/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 100 such pooled samples were arrayed: 74 from females and 26 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0903_p/acknowledgment.rtf b/general/datasets/Br_u_0903_p/acknowledgment.rtf
new file mode 100644
index 0000000..1efbf49
--- /dev/null
+++ b/general/datasets/Br_u_0903_p/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0903_p/cases.rtf b/general/datasets/Br_u_0903_p/cases.rtf
new file mode 100644
index 0000000..38a782c
--- /dev/null
+++ b/general/datasets/Br_u_0903_p/cases.rtf
@@ -0,0 +1,230 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice. Note that this table includes six arrays dropped from the December 2003 data sets (BXD6, n=2; BXD12, BXD16, BXD40, and BXD67, n=1 each).
+
+
diff --git a/general/datasets/Br_u_0903_p/experiment-type.rtf b/general/datasets/Br_u_0903_p/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Br_u_0903_p/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Br_u_0903_p/notes.rtf b/general/datasets/Br_u_0903_p/notes.rtf
new file mode 100644
index 0000000..68a18e4
--- /dev/null
+++ b/general/datasets/Br_u_0903_p/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, EJC, and YHQ, August 2003. Updated by RWW, October 30, 2004.
diff --git a/general/datasets/Br_u_0903_p/platform.rtf b/general/datasets/Br_u_0903_p/platform.rtf
new file mode 100644
index 0000000..e8ac283
--- /dev/null
+++ b/general/datasets/Br_u_0903_p/platform.rtf
@@ -0,0 +1 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 100 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Br_u_0903_p/processing.rtf b/general/datasets/Br_u_0903_p/processing.rtf
new file mode 100644
index 0000000..9b386b5
--- /dev/null
+++ b/general/datasets/Br_u_0903_p/processing.rtf
@@ -0,0 +1,27 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal intensity.
+ - Step 3: We computed the Z score for each of these log2 cell signal intensity values within a single array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added a constant of 8 units to the value of the Z score. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units. The advantage of this modified Z score is that a 2-fold difference in expression level corresponds roughly to 1 unit.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each strain. We have not corrected for variance introduced by sex, age, source of animals, or any possible interaction. We have not corrected for background beyond that implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 106 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
+
+About the array probe set names:
+
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target): Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
diff --git a/general/datasets/Br_u_0903_p/summary.rtf b/general/datasets/Br_u_0903_p/summary.rtf
new file mode 100644
index 0000000..7826a5c
--- /dev/null
+++ b/general/datasets/Br_u_0903_p/summary.rtf
@@ -0,0 +1 @@
+This August 2003 freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. This is data set includes six arrays which are of marginal quality. New users are encouraged to use one of the more recent data sets (December 2003 or March 2004) from which these six arrays have been excluded. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 106 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. In general, the MAS 5 transform does not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0903_p/tissue.rtf b/general/datasets/Br_u_0903_p/tissue.rtf
new file mode 100644
index 0000000..6961982
--- /dev/null
+++ b/general/datasets/Br_u_0903_p/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 100 such pooled samples were arrayed: 74 from females and 26 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_0903_r/acknowledgment.rtf b/general/datasets/Br_u_0903_r/acknowledgment.rtf
new file mode 100644
index 0000000..1efbf49
--- /dev/null
+++ b/general/datasets/Br_u_0903_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_0903_r/cases.rtf b/general/datasets/Br_u_0903_r/cases.rtf
new file mode 100644
index 0000000..38a782c
--- /dev/null
+++ b/general/datasets/Br_u_0903_r/cases.rtf
@@ -0,0 +1,230 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice. Note that this table includes six arrays dropped from the December 2003 data sets (BXD6, n=2; BXD12, BXD16, BXD40, and BXD67, n=1 each).
+
+
diff --git a/general/datasets/Br_u_0903_r/notes.rtf b/general/datasets/Br_u_0903_r/notes.rtf
new file mode 100644
index 0000000..68a18e4
--- /dev/null
+++ b/general/datasets/Br_u_0903_r/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, EJC, and YHQ, August 2003. Updated by RWW, October 30, 2004.
diff --git a/general/datasets/Br_u_0903_r/platform.rtf b/general/datasets/Br_u_0903_r/platform.rtf
new file mode 100644
index 0000000..e8ac283
--- /dev/null
+++ b/general/datasets/Br_u_0903_r/platform.rtf
@@ -0,0 +1 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 100 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Br_u_0903_r/processing.rtf b/general/datasets/Br_u_0903_r/processing.rtf
new file mode 100644
index 0000000..9b386b5
--- /dev/null
+++ b/general/datasets/Br_u_0903_r/processing.rtf
@@ -0,0 +1,27 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal intensity.
+ - Step 3: We computed the Z score for each of these log2 cell signal intensity values within a single array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added a constant of 8 units to the value of the Z score. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units. The advantage of this modified Z score is that a 2-fold difference in expression level corresponds roughly to 1 unit.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each strain. We have not corrected for variance introduced by sex, age, source of animals, or any possible interaction. We have not corrected for background beyond that implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 106 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
+
+About the array probe set names:
+
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target): Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
diff --git a/general/datasets/Br_u_0903_r/summary.rtf b/general/datasets/Br_u_0903_r/summary.rtf
new file mode 100644
index 0000000..7826a5c
--- /dev/null
+++ b/general/datasets/Br_u_0903_r/summary.rtf
@@ -0,0 +1 @@
+This August 2003 freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. This is data set includes six arrays which are of marginal quality. New users are encouraged to use one of the more recent data sets (December 2003 or March 2004) from which these six arrays have been excluded. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 106 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. In general, the MAS 5 transform does not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_0903_r/tissue.rtf b/general/datasets/Br_u_0903_r/tissue.rtf
new file mode 100644
index 0000000..6961982
--- /dev/null
+++ b/general/datasets/Br_u_0903_r/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 100 such pooled samples were arrayed: 74 from females and 26 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1105_p/acknowledgment.rtf b/general/datasets/Br_u_1105_p/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1105_p/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1105_p/cases.rtf b/general/datasets/Br_u_1105_p/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1105_p/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1105_p/notes.rtf b/general/datasets/Br_u_1105_p/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1105_p/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1105_p/platform.rtf b/general/datasets/Br_u_1105_p/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1105_p/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1105_p/processing.rtf b/general/datasets/Br_u_1105_p/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1105_p/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1105_p/summary.rtf b/general/datasets/Br_u_1105_p/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1105_p/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1105_p/tissue.rtf b/general/datasets/Br_u_1105_p/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1105_p/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1105_r/acknowledgment.rtf b/general/datasets/Br_u_1105_r/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1105_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1105_r/cases.rtf b/general/datasets/Br_u_1105_r/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1105_r/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1105_r/notes.rtf b/general/datasets/Br_u_1105_r/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1105_r/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1105_r/platform.rtf b/general/datasets/Br_u_1105_r/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1105_r/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1105_r/processing.rtf b/general/datasets/Br_u_1105_r/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1105_r/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1105_r/summary.rtf b/general/datasets/Br_u_1105_r/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1105_r/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1105_r/tissue.rtf b/general/datasets/Br_u_1105_r/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1105_r/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1203_dpm/acknowledgment.rtf b/general/datasets/Br_u_1203_dpm/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpm/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1203_dpm/cases.rtf b/general/datasets/Br_u_1203_dpm/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpm/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1203_dpm/notes.rtf b/general/datasets/Br_u_1203_dpm/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpm/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1203_dpm/platform.rtf b/general/datasets/Br_u_1203_dpm/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpm/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1203_dpm/processing.rtf b/general/datasets/Br_u_1203_dpm/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpm/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1203_dpm/summary.rtf b/general/datasets/Br_u_1203_dpm/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpm/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1203_dpm/tissue.rtf b/general/datasets/Br_u_1203_dpm/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpm/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1203_dpmm/acknowledgment.rtf b/general/datasets/Br_u_1203_dpmm/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmm/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1203_dpmm/cases.rtf b/general/datasets/Br_u_1203_dpmm/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmm/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1203_dpmm/notes.rtf b/general/datasets/Br_u_1203_dpmm/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmm/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1203_dpmm/platform.rtf b/general/datasets/Br_u_1203_dpmm/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmm/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1203_dpmm/processing.rtf b/general/datasets/Br_u_1203_dpmm/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmm/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1203_dpmm/summary.rtf b/general/datasets/Br_u_1203_dpmm/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmm/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1203_dpmm/tissue.rtf b/general/datasets/Br_u_1203_dpmm/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmm/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1203_dpmmr/acknowledgment.rtf b/general/datasets/Br_u_1203_dpmmr/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmmr/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1203_dpmmr/cases.rtf b/general/datasets/Br_u_1203_dpmmr/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmmr/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1203_dpmmr/notes.rtf b/general/datasets/Br_u_1203_dpmmr/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmmr/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1203_dpmmr/platform.rtf b/general/datasets/Br_u_1203_dpmmr/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmmr/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1203_dpmmr/processing.rtf b/general/datasets/Br_u_1203_dpmmr/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmmr/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1203_dpmmr/summary.rtf b/general/datasets/Br_u_1203_dpmmr/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmmr/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1203_dpmmr/tissue.rtf b/general/datasets/Br_u_1203_dpmmr/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmmr/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1203_dpmr/acknowledgment.rtf b/general/datasets/Br_u_1203_dpmr/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmr/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1203_dpmr/cases.rtf b/general/datasets/Br_u_1203_dpmr/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmr/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1203_dpmr/notes.rtf b/general/datasets/Br_u_1203_dpmr/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmr/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1203_dpmr/platform.rtf b/general/datasets/Br_u_1203_dpmr/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmr/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1203_dpmr/processing.rtf b/general/datasets/Br_u_1203_dpmr/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmr/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1203_dpmr/summary.rtf b/general/datasets/Br_u_1203_dpmr/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmr/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1203_dpmr/tissue.rtf b/general/datasets/Br_u_1203_dpmr/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1203_dpmr/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1203_h2/acknowledgment.rtf b/general/datasets/Br_u_1203_h2/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1203_h2/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1203_h2/cases.rtf b/general/datasets/Br_u_1203_h2/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1203_h2/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1203_h2/notes.rtf b/general/datasets/Br_u_1203_h2/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1203_h2/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1203_h2/platform.rtf b/general/datasets/Br_u_1203_h2/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1203_h2/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1203_h2/processing.rtf b/general/datasets/Br_u_1203_h2/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1203_h2/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1203_h2/summary.rtf b/general/datasets/Br_u_1203_h2/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1203_h2/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1203_h2/tissue.rtf b/general/datasets/Br_u_1203_h2/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1203_h2/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1203_m/acknowledgment.rtf b/general/datasets/Br_u_1203_m/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1203_m/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1203_m/cases.rtf b/general/datasets/Br_u_1203_m/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1203_m/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1203_m/notes.rtf b/general/datasets/Br_u_1203_m/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1203_m/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1203_m/platform.rtf b/general/datasets/Br_u_1203_m/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1203_m/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1203_m/processing.rtf b/general/datasets/Br_u_1203_m/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1203_m/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1203_m/summary.rtf b/general/datasets/Br_u_1203_m/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1203_m/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1203_m/tissue.rtf b/general/datasets/Br_u_1203_m/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1203_m/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1203_mr/acknowledgment.rtf b/general/datasets/Br_u_1203_mr/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1203_mr/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1203_mr/cases.rtf b/general/datasets/Br_u_1203_mr/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1203_mr/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1203_mr/notes.rtf b/general/datasets/Br_u_1203_mr/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1203_mr/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1203_mr/platform.rtf b/general/datasets/Br_u_1203_mr/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1203_mr/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1203_mr/processing.rtf b/general/datasets/Br_u_1203_mr/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1203_mr/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1203_mr/summary.rtf b/general/datasets/Br_u_1203_mr/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1203_mr/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1203_mr/tissue.rtf b/general/datasets/Br_u_1203_mr/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1203_mr/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1203_p/acknowledgment.rtf b/general/datasets/Br_u_1203_p/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1203_p/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1203_p/cases.rtf b/general/datasets/Br_u_1203_p/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1203_p/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1203_p/notes.rtf b/general/datasets/Br_u_1203_p/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1203_p/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1203_p/platform.rtf b/general/datasets/Br_u_1203_p/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1203_p/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1203_p/processing.rtf b/general/datasets/Br_u_1203_p/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1203_p/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1203_p/summary.rtf b/general/datasets/Br_u_1203_p/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1203_p/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1203_p/tissue.rtf b/general/datasets/Br_u_1203_p/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1203_p/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1203_pr/acknowledgment.rtf b/general/datasets/Br_u_1203_pr/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1203_pr/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1203_pr/cases.rtf b/general/datasets/Br_u_1203_pr/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1203_pr/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1203_pr/notes.rtf b/general/datasets/Br_u_1203_pr/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1203_pr/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1203_pr/platform.rtf b/general/datasets/Br_u_1203_pr/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1203_pr/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1203_pr/processing.rtf b/general/datasets/Br_u_1203_pr/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1203_pr/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1203_pr/summary.rtf b/general/datasets/Br_u_1203_pr/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1203_pr/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1203_pr/tissue.rtf b/general/datasets/Br_u_1203_pr/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1203_pr/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1203_r/acknowledgment.rtf b/general/datasets/Br_u_1203_r/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1203_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1203_r/cases.rtf b/general/datasets/Br_u_1203_r/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1203_r/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1203_r/notes.rtf b/general/datasets/Br_u_1203_r/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1203_r/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1203_r/platform.rtf b/general/datasets/Br_u_1203_r/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1203_r/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1203_r/processing.rtf b/general/datasets/Br_u_1203_r/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1203_r/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1203_r/summary.rtf b/general/datasets/Br_u_1203_r/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1203_r/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1203_r/tissue.rtf b/general/datasets/Br_u_1203_r/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1203_r/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Br_u_1203_rr/acknowledgment.rtf b/general/datasets/Br_u_1203_rr/acknowledgment.rtf
new file mode 100644
index 0000000..b1a98cb
--- /dev/null
+++ b/general/datasets/Br_u_1203_rr/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to RWW from the Dunavant Chair of Excellence, University of Tennessee Health Science Center, Department of Pediatrics. The majority of arrays were processed at Genome Explorations by Dr. Divyen Patel. We thank Guomin Zhou for generating advanced intercross stock used to produce most of the new BXD RI strains.
diff --git a/general/datasets/Br_u_1203_rr/cases.rtf b/general/datasets/Br_u_1203_rr/cases.rtf
new file mode 100644
index 0000000..9076285
--- /dev/null
+++ b/general/datasets/Br_u_1203_rr/cases.rtf
@@ -0,0 +1,232 @@
+This data set includes estimate of gene expression for 35 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), their B6D2 F1 intercross, and 32 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because many of these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period. A significant advantage of this RI set is that the two parental strains (B6 and D2) have both been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Only two of these incipient strains are included in the current database (BXD67 and BXD68).
+
+In this mRNA expression database we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from three mice.
+
+
diff --git a/general/datasets/Br_u_1203_rr/notes.rtf b/general/datasets/Br_u_1203_rr/notes.rtf
new file mode 100644
index 0000000..1b8fd3d
--- /dev/null
+++ b/general/datasets/Br_u_1203_rr/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, December 2003. Updated by RWW, October 29, 2004.
diff --git a/general/datasets/Br_u_1203_rr/platform.rtf b/general/datasets/Br_u_1203_rr/platform.rtf
new file mode 100644
index 0000000..c6f6d68
--- /dev/null
+++ b/general/datasets/Br_u_1203_rr/platform.rtf
@@ -0,0 +1,14 @@
+Affymetrix U74Av2 GeneChip: The expression data were generated using 97 U74Av2 arrays. The chromosomal locations of U74Av2 probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium Mar 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target) : Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
diff --git a/general/datasets/Br_u_1203_rr/processing.rtf b/general/datasets/Br_u_1203_rr/processing.rtf
new file mode 100644
index 0000000..2a34d5e
--- /dev/null
+++ b/general/datasets/Br_u_1203_rr/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: Probe signal intensity estimates in the Affymetrix CEL files are the 75% quantile value taken from a set of 36 (6x6) pixels per probe cell in the DAT image file.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 97 arrays (all seven batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by seven batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all seven batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the seven batches is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data from the CHP file: Probe set estimates of expression were initially generated using the standard Affymetrix MAS 5 algorithm. The CHP values were then processed following precisely the same six steps listed above to normalize expression and stabilize the variance of all 97 arrays. The mean expression within each array is therefore 8 units with a standard deviation of 2 units. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the background noise level. While a value of 8 unit is nominally the average expression, this average includes all those transcripts with negligible expression in the brain that would often be eliminated from subsequent analysis (so-called "absent" and "marginal" calls in the CHP file).
diff --git a/general/datasets/Br_u_1203_rr/summary.rtf b/general/datasets/Br_u_1203_rr/summary.rtf
new file mode 100644
index 0000000..e2d448f
--- /dev/null
+++ b/general/datasets/Br_u_1203_rr/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimates of mRNA expression in brains of BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the University of Tennessee Health Science Center (UTHSC). Over 300 brain samples from 35 strains were hybridized in small pools (n=3) to 97 arrays. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA, PDNN, or the new heritability weighted transforms (HW1PM).
diff --git a/general/datasets/Br_u_1203_rr/tissue.rtf b/general/datasets/Br_u_1203_rr/tissue.rtf
new file mode 100644
index 0000000..1f09431
--- /dev/null
+++ b/general/datasets/Br_u_1203_rr/tissue.rtf
@@ -0,0 +1 @@
+Each array was hybridized with labeled cRNA generated from a pool of three brains from adult animals usually of the same age and always of the same sex. The brain region included most of the forebrain and midbrain, bilaterally. However, the sample excluded the olfactory bulbs, retinas, or the posterior pituitary (all formally part of the forebrain). A total of 97 such pooled samples were arrayed: 73 from females and 24 from males. Animals ranged in age from 56 to 441 days, usually with a balanced design: one pool at approximately 8 weeks, one pool at approximately 20 weeks, and one pool at approximately 1 year. Strain averages of mRNA expression level are therefore typically based on three pooled biological replicate arrays. This data set does not incorporate statistical adjustment for possible effects of age and sex. Users can select the strain symbol in the table above to review details about the specific cases and array processing center (DP = Divyen Patel at Genome Explorations, Inc; TS = Thomas Sutter at University of Memphis). You can also click on the individual symbols (males or females) to view the array image.
diff --git a/general/datasets/Brf2_m_0304_m/acknowledgment.rtf b/general/datasets/Brf2_m_0304_m/acknowledgment.rtf
new file mode 100644
index 0000000..e67d66a
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_m/acknowledgment.rtf
@@ -0,0 +1,3 @@
+This project was supported by two Department of Veterans Affairs Merit Review Awards (to JK Belknap and R Hitzemann, respectively), AA10760 (Portland Alcohol Research Center), AA06243, AA13484, AA11034, DA05228 and MH51372.
+
+Please contact either John Belknap or Robert Hitzemann at the Dept. of Behavioral Neuroscience, Oregon Health & Science University (L470), or Research Service (R&D5), Portland VA Medical Ctr., Portland, OR 97239 USA.
diff --git a/general/datasets/Brf2_m_0304_m/cases.rtf b/general/datasets/Brf2_m_0304_m/cases.rtf
new file mode 100644
index 0000000..3d9dd38
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_m/cases.rtf
@@ -0,0 +1,3 @@
+Fifty-six B6D2F2 samples, each taken from a single brain hemisphere from an individual mouse, were assayed using 56 M430A Affymetrix short oligomer microarrays. [The remaining hemisphere will be used later for an anaysis of specific brain regions.] Each array ID (see table below) includes a three letter code; the first letter usually denotes sex of the case (note that we have made a few corrections and there are therefore several sex-discordant IDs), the second letter denotes the hemisphere (R or L), and the third letter is the mouse number within each cell. The F2 mice were experimentally naive, born within a 3-day period from second litters of each dam, and housed at weaning (20- to 24-days-of-age) in like-sex groups of 3 to 4 mice for females and 2 to 3 mice for males in standard mouse shoebox cages within Thoren racks. All 56 F2 mice were killed at 77 to 79 days-of-age by cervical dislocation on December 17, 2003. The brains were immediately split at the midline and then quickly frozen on dry ice. The brains were stored for about two weeks at -80 degrees C until further use.
+
+The F2 was derived as follows: C57BL/6J (B6) and DBA/2J (D2) breeders were obtained from The Jackson Laboratory, and two generations later their progeny were crossed to produce B6D2F1 and D2B6F1 hybrid at the Portland VA Veterinary Medical Unit (AAALAC approved). The reciprocal F1s were mated to create an F2 population with both progenitor X and Y chromosomes about equally represented.
diff --git a/general/datasets/Brf2_m_0304_m/citation.rtf b/general/datasets/Brf2_m_0304_m/citation.rtf
new file mode 100644
index 0000000..3c5403c
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_m/citation.rtf
@@ -0,0 +1,21 @@
+
+Hitzemann, R, McWeeney, S, Harrington, S, Malmanger, B, Lawler, M, Belknap, JK (2004) Brain gene expression among four inbred mouse strains: The development of an analysis strategy for the integration of QTL and gene expression data. Submitted.
+
+
+
+Irizarry, RA, Bolstad, BM, Collin, F, Cope, LM, Hobbs, B, Speed, TP (2003) Summaries of Affymetrix GeneChip probe level data. Nuc Acids Res 31:1-15.
+
+
+
+Lincoln, SE, Lander, ES (1992) Systematic detection of errors in genetic linkage data. Genomics 14:604-610.
+
+
+
+Zhang, L, Miles, MF, Aldape, KD (2003) A model of molecular interactions on short oligonucleotide microarrays. Nat Biotech 21:818-821.
+
+
+ Information about this text file:
+
+
+This text file was originally generated by John Belknap, March 2004. Updated by RWW, October 31, 2004, EJC June 21, 2005. Updated with reference, NOV 2014 BY RWW.
+
diff --git a/general/datasets/Brf2_m_0304_m/contributors.rtf b/general/datasets/Brf2_m_0304_m/contributors.rtf
new file mode 100644
index 0000000..92da9ca
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_m/contributors.rtf
@@ -0,0 +1,7 @@
+PMID: 15597075
+
+Hitzemann R, Reed C, Malmanger B, Lawler M, Hitzemann B, Cunningham B, McWeeney S, Belknap J, Harrington C, Buck K, Phillips T, Crabbe J (2004) On the integration of alcohol-related quantitative trait loci and gene expression analyses. Alcohol Clin Exp Res. ;28(10):1437-1448.
+
+
+
+
diff --git a/general/datasets/Brf2_m_0304_m/experiment-design.rtf b/general/datasets/Brf2_m_0304_m/experiment-design.rtf
new file mode 100644
index 0000000..2829934
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_m/experiment-design.rtf
@@ -0,0 +1 @@
+Conventional F2 intercross.
diff --git a/general/datasets/Brf2_m_0304_m/notes.rtf b/general/datasets/Brf2_m_0304_m/notes.rtf
new file mode 100644
index 0000000..c4a728d
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_m/notes.rtf
@@ -0,0 +1,5 @@
+Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA or PDNN transforms.
+
+Data were processed using the Position-Dependent Nearest Neighbor (PDNN) method developed by Zhang and colleagues (2003. To simplify comparison between transforms, PDNN values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run as a single large batch with careful consideration to balancing samples by sex, age, and environment.
+
+Data were processed using the RMA protocol and are presented with secondary normalization to an average expression value of 8 units. To simplify comparison between transforms, RMA values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run as a single large batch with effort to balance samples by sex, age, and environment.
diff --git a/general/datasets/Brf2_m_0304_m/platform.rtf b/general/datasets/Brf2_m_0304_m/platform.rtf
new file mode 100644
index 0000000..ecb86bc
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_m/platform.rtf
@@ -0,0 +1,1154 @@
+All 56 430A arrays used in this project were purchased at one time and had the same Affymetrix lot number. The table below lists the arrays by Case ID, Array ID, Side, Cage ID and Sex.
+
+
+
+
+
+
+
+
+ |
+ Order
+ |
+
+ CaseID
+ |
+
+ ArrayID
+ |
+
+ Side
+ |
+
+ CageID
+ |
+
+ Sex
+ |
+
+
+ |
+ 1
+ |
+
+ 20
+ |
+
+ FL10
+ |
+
+ L
+ |
+
+ H1
+ |
+
+ F
+ |
+
+
+ |
+ 2
+ |
+
+ 2
+ |
+
+ FL11
+ |
+
+ L
+ |
+
+ H2
+ |
+
+ F
+ |
+
+
+ |
+ 3
+ |
+
+ 5
+ |
+
+ FL12
+ |
+
+ L
+ |
+
+ H3
+ |
+
+ F
+ |
+
+
+ |
+ 4
+ |
+
+ 63
+ |
+
+ FL13
+ |
+
+ L
+ |
+
+ H4
+ |
+
+ F
+ |
+
+
+ |
+ 5
+ |
+
+ 6
+ |
+
+ FL14
+ |
+
+ L
+ |
+
+ K2
+ |
+
+ F
+ |
+
+
+ |
+ 6
+ |
+
+ 10
+ |
+
+ FL15
+ |
+
+ L
+ |
+
+ Q2
+ |
+
+ F
+ |
+
+
+ |
+ 7
+ |
+
+ 52
+ |
+
+ FL2
+ |
+
+ L
+ |
+
+ E1
+ |
+
+ F
+ |
+
+
+ |
+ 8
+ |
+
+ 53
+ |
+
+ FL3
+ |
+
+ L
+ |
+
+ E2
+ |
+
+ F
+ |
+
+
+ |
+ 9
+ |
+
+ 42
+ |
+
+ FL4
+ |
+
+ L
+ |
+
+ E3
+ |
+
+ F
+ |
+
+
+ |
+ 10
+ |
+
+ 31
+ |
+
+ FL5
+ |
+
+ L
+ |
+
+ E4
+ |
+
+ F
+ |
+
+
+ |
+ 11
+ |
+
+ 14
+ |
+
+ FL6
+ |
+
+ L
+ |
+
+ F1
+ |
+
+ M
+ |
+
+
+ |
+ 12
+ |
+
+ 48
+ |
+
+ FL7
+ |
+
+ L
+ |
+
+ F2
+ |
+
+ F
+ |
+
+
+ |
+ 13
+ |
+
+ 60
+ |
+
+ FL8
+ |
+
+ L
+ |
+
+ F3
+ |
+
+ M
+ |
+
+
+ |
+ 14
+ |
+
+ 54
+ |
+
+ FL9
+ |
+
+ L
+ |
+
+ F4
+ |
+
+ F
+ |
+
+
+ |
+ 15
+ |
+
+ 35
+ |
+
+ FR10
+ |
+
+ R
+ |
+
+ K3
+ |
+
+ F
+ |
+
+
+ |
+ 16
+ |
+
+ 11
+ |
+
+ FR11
+ |
+
+ R
+ |
+
+ O1
+ |
+
+ F
+ |
+
+
+ |
+ 17
+ |
+
+ 21
+ |
+
+ FR12
+ |
+
+ R
+ |
+
+ O2
+ |
+
+ F
+ |
+
+
+ |
+ 18
+ |
+
+ 23
+ |
+
+ FR13
+ |
+
+ R
+ |
+
+ Q1
+ |
+
+ F
+ |
+
+
+ |
+ 19
+ |
+
+ 15
+ |
+
+ FR14
+ |
+
+ R
+ |
+
+ Q3
+ |
+
+ F
+ |
+
+
+ |
+ 20
+ |
+
+ 4
+ |
+
+ FR15
+ |
+
+ R
+ |
+
+ Q4
+ |
+
+ F
+ |
+
+
+ |
+ 21
+ |
+
+ 41
+ |
+
+ FR2
+ |
+
+ R
+ |
+
+ A2
+ |
+
+ F
+ |
+
+
+ |
+ 22
+ |
+
+ 44
+ |
+
+ FR3
+ |
+
+ R
+ |
+
+ A3
+ |
+
+ F
+ |
+
+
+ |
+ 23
+ |
+
+ 37
+ |
+
+ FR4
+ |
+
+ R
+ |
+
+ C1
+ |
+
+ F
+ |
+
+
+ |
+ 24
+ |
+
+ 8
+ |
+
+ FR5
+ |
+
+ R
+ |
+
+ C2
+ |
+
+ F
+ |
+
+
+ |
+ 25
+ |
+
+ 19
+ |
+
+ FR6
+ |
+
+ R
+ |
+
+ C3
+ |
+
+ F
+ |
+
+
+ |
+ 26
+ |
+
+ 40
+ |
+
+ FR7
+ |
+
+ R
+ |
+
+ C4
+ |
+
+ F
+ |
+
+
+ |
+ 27
+ |
+
+ 62
+ |
+
+ FR8
+ |
+
+ R
+ |
+
+ D2
+ |
+
+ M
+ |
+
+
+ |
+ 28
+ |
+
+ 39
+ |
+
+ FR9
+ |
+
+ R
+ |
+
+ D3
+ |
+
+ F
+ |
+
+
+ |
+ 29
+ |
+
+ 13
+ |
+
+ ML1
+ |
+
+ L
+ |
+
+ B1
+ |
+
+ M
+ |
+
+
+ |
+ 30
+ |
+
+ 22
+ |
+
+ ML10
+ |
+
+ L
+ |
+
+ L2
+ |
+
+ M
+ |
+
+
+ |
+ 31
+ |
+
+ 38
+ |
+
+ ML11
+ |
+
+ L
+ |
+
+ L4
+ |
+
+ M
+ |
+
+
+ |
+ 32
+ |
+
+ 43
+ |
+
+ ML12
+ |
+
+ L
+ |
+
+ M1
+ |
+
+ M
+ |
+
+
+ |
+ 33
+ |
+
+ 58
+ |
+
+ ML13
+ |
+
+ L
+ |
+
+ N2
+ |
+
+ M
+ |
+
+
+ |
+ 34
+ |
+
+ 7
+ |
+
+ ML14
+ |
+
+ L
+ |
+
+ R1
+ |
+
+ M
+ |
+
+
+ |
+ 35
+ |
+
+ 30
+ |
+
+ ML15
+ |
+
+ L
+ |
+
+ R3
+ |
+
+ M
+ |
+
+
+ |
+ 36
+ |
+
+ 46
+ |
+
+ ML3
+ |
+
+ L
+ |
+
+ G1
+ |
+
+ M
+ |
+
+
+ |
+ 37
+ |
+
+ 57
+ |
+
+ ML4
+ |
+
+ L
+ |
+
+ G2
+ |
+
+ M
+ |
+
+
+ |
+ 38
+ |
+
+ 51
+ |
+
+ ML5
+ |
+
+ L
+ |
+
+ I1
+ |
+
+ M
+ |
+
+
+ |
+ 39
+ |
+
+ 27
+ |
+
+ ML6
+ |
+
+ L
+ |
+
+ I2
+ |
+
+ M
+ |
+
+
+ |
+ 40
+ |
+
+ 50
+ |
+
+ ML7
+ |
+
+ L
+ |
+
+ J2
+ |
+
+ M
+ |
+
+
+ |
+ 41
+ |
+
+ 16
+ |
+
+ FL1
+ |
+
+ L
+ |
+
+ O2
+ |
+
+ M
+ |
+
+
+ |
+ 42
+ |
+
+ 3
+ |
+
+ ML9
+ |
+
+ L
+ |
+
+ L1
+ |
+
+ M
+ |
+
+
+ |
+ 43
+ |
+
+ 47
+ |
+
+ MR10
+ |
+
+ R
+ |
+
+ R2
+ |
+
+ M
+ |
+
+
+ |
+ 44
+ |
+
+ 56
+ |
+
+ MR11
+ |
+
+ R
+ |
+
+ S1
+ |
+
+ M
+ |
+
+
+ |
+ 45
+ |
+
+ 1
+ |
+
+ MR12
+ |
+
+ R
+ |
+
+ S2
+ |
+
+ M
+ |
+
+
+ |
+ 46
+ |
+
+ 55
+ |
+
+ MR13
+ |
+
+ R
+ |
+
+ T1
+ |
+
+ M
+ |
+
+
+ |
+ 47
+ |
+
+ 34
+ |
+
+ MR14
+ |
+
+ R
+ |
+
+ U1
+ |
+
+ M
+ |
+
+
+ |
+ 48
+ |
+
+ 25
+ |
+
+ MR15
+ |
+
+ R
+ |
+
+ U2
+ |
+
+ M
+ |
+
+
+ |
+ 49
+ |
+
+ 59
+ |
+
+ MR2
+ |
+
+ R
+ |
+
+ J1
+ |
+
+ M
+ |
+
+
+ |
+ 50
+ |
+
+ 32
+ |
+
+ MR3
+ |
+
+ R
+ |
+
+ M2
+ |
+
+ M
+ |
+
+
+ |
+ 51
+ |
+
+ 24
+ |
+
+ MR4
+ |
+
+ R
+ |
+
+ M3
+ |
+
+ M
+ |
+
+
+ |
+ 52
+ |
+
+ 12
+ |
+
+ MR5
+ |
+
+ R
+ |
+
+ M4
+ |
+
+ M
+ |
+
+
+ |
+ 53
+ |
+
+ 9
+ |
+
+ MR6
+ |
+
+ R
+ |
+
+ N1
+ |
+
+ M
+ |
+
+
+ |
+ 54
+ |
+
+ 36
+ |
+
+ MR7
+ |
+
+ R
+ |
+
+ N3
+ |
+
+ M
+ |
+
+
+ |
+ 55
+ |
+
+ 28
+ |
+
+ MR8
+ |
+
+ R
+ |
+
+ P1
+ |
+
+ M
+ |
+
+
+ |
+ 56
+ |
+
+ 33
+ |
+
+ MR9
+ |
+
+ R
+ |
+
+ P2
+ |
+
+ M
+ |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Brf2_m_0304_m/processing.rtf b/general/datasets/Brf2_m_0304_m/processing.rtf
new file mode 100644
index 0000000..002c868
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_m/processing.rtf
@@ -0,0 +1,16 @@
+The 56 mice were each genotyped at 309 MIT microsatellite markers distributed across the genome, including the Y chromosome. The genotyping error check routine (Lincoln and Lander, 1992) implemented within R/qtl (Broman et al., 2003) showed no likely errors at p <.01 probability. Initial genotypes were generated at OHSU. Approximately 200 genotypes were generated at UTHSC by Jing Gu and Shuhua Qi.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are the 75% quantiles from a set of 91 pixel values per cell. Probe values were processed as follows:
+
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each probe signal.
+ - Step 3: We computed the Z score for each signal within array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each of the individual strains.
+
+
+Probe set data from the TXT file: These TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+The chromosomal locations of M430A and M430B probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Brf2_m_0304_m/summary.rtf b/general/datasets/Brf2_m_0304_m/summary.rtf
new file mode 100644
index 0000000..8c926cd
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_m/summary.rtf
@@ -0,0 +1 @@
+This March 2004 data freeze provides estimate of mRNA expression in adult brains of F2 intercross mice (C57BL/6J x DBA/2J F2) measured using Affymetrix M430A microarrays. Data were generated at The Oregon Health Sciences University (OHSU) in Portland, Oregon, by John Belknap and Robert Hitzemann. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA or PDNN transforms.
diff --git a/general/datasets/Brf2_m_0304_m/tissue.rtf b/general/datasets/Brf2_m_0304_m/tissue.rtf
new file mode 100644
index 0000000..863b8e6
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_m/tissue.rtf
@@ -0,0 +1 @@
+Brain samples were from 31 male and 25 females and between 28 right and 28 left hemispheres distributed with good balance across the two sexes. The tissue arrayed included the forebrain, midbrain, one olfactory bulb, the cerebellum; and the rostral part of the medulla. The medulla was trimmed transversely at the caudal aspect of the cerebellum. The sagittal cut was made from a dorsal to ventral direction. (Note that several of the other brain transcriptome databases do not include olfactory bulb or cerebellum.) Total RNA was isolated with TRIZOL Reagent (Life Technologies Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer’s protocol. The extracted RNA was then purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for purity; only samples with an A260/280 ratio greater than 1.8 were used. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. Samples containing at least 10 micrograms of total RNA were sent to the OHSU Gene Microarray Shared Resource facility for analysis. The procedures used at the facility precisely follow the manufacturer’s specifications. Details can be found at http://www.ohsu.edu/gmsr/amc. Following labeling, all samples were hybridized to the GeneChip Test3 array for quality control. If target performance did not meet recommended thresholds, the sample would have been discarded. All labeled samples passed the threshold and were hybridized to the 430A array.
diff --git a/general/datasets/Brf2_m_0304_p/acknowledgment.rtf b/general/datasets/Brf2_m_0304_p/acknowledgment.rtf
new file mode 100644
index 0000000..e67d66a
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_p/acknowledgment.rtf
@@ -0,0 +1,3 @@
+This project was supported by two Department of Veterans Affairs Merit Review Awards (to JK Belknap and R Hitzemann, respectively), AA10760 (Portland Alcohol Research Center), AA06243, AA13484, AA11034, DA05228 and MH51372.
+
+Please contact either John Belknap or Robert Hitzemann at the Dept. of Behavioral Neuroscience, Oregon Health & Science University (L470), or Research Service (R&D5), Portland VA Medical Ctr., Portland, OR 97239 USA.
diff --git a/general/datasets/Brf2_m_0304_p/cases.rtf b/general/datasets/Brf2_m_0304_p/cases.rtf
new file mode 100644
index 0000000..3d9dd38
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_p/cases.rtf
@@ -0,0 +1,3 @@
+Fifty-six B6D2F2 samples, each taken from a single brain hemisphere from an individual mouse, were assayed using 56 M430A Affymetrix short oligomer microarrays. [The remaining hemisphere will be used later for an anaysis of specific brain regions.] Each array ID (see table below) includes a three letter code; the first letter usually denotes sex of the case (note that we have made a few corrections and there are therefore several sex-discordant IDs), the second letter denotes the hemisphere (R or L), and the third letter is the mouse number within each cell. The F2 mice were experimentally naive, born within a 3-day period from second litters of each dam, and housed at weaning (20- to 24-days-of-age) in like-sex groups of 3 to 4 mice for females and 2 to 3 mice for males in standard mouse shoebox cages within Thoren racks. All 56 F2 mice were killed at 77 to 79 days-of-age by cervical dislocation on December 17, 2003. The brains were immediately split at the midline and then quickly frozen on dry ice. The brains were stored for about two weeks at -80 degrees C until further use.
+
+The F2 was derived as follows: C57BL/6J (B6) and DBA/2J (D2) breeders were obtained from The Jackson Laboratory, and two generations later their progeny were crossed to produce B6D2F1 and D2B6F1 hybrid at the Portland VA Veterinary Medical Unit (AAALAC approved). The reciprocal F1s were mated to create an F2 population with both progenitor X and Y chromosomes about equally represented.
diff --git a/general/datasets/Brf2_m_0304_p/citation.rtf b/general/datasets/Brf2_m_0304_p/citation.rtf
new file mode 100644
index 0000000..3c5403c
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_p/citation.rtf
@@ -0,0 +1,21 @@
+
+Hitzemann, R, McWeeney, S, Harrington, S, Malmanger, B, Lawler, M, Belknap, JK (2004) Brain gene expression among four inbred mouse strains: The development of an analysis strategy for the integration of QTL and gene expression data. Submitted.
+
+
+
+Irizarry, RA, Bolstad, BM, Collin, F, Cope, LM, Hobbs, B, Speed, TP (2003) Summaries of Affymetrix GeneChip probe level data. Nuc Acids Res 31:1-15.
+
+
+
+Lincoln, SE, Lander, ES (1992) Systematic detection of errors in genetic linkage data. Genomics 14:604-610.
+
+
+
+Zhang, L, Miles, MF, Aldape, KD (2003) A model of molecular interactions on short oligonucleotide microarrays. Nat Biotech 21:818-821.
+
+
+ Information about this text file:
+
+
+This text file was originally generated by John Belknap, March 2004. Updated by RWW, October 31, 2004, EJC June 21, 2005. Updated with reference, NOV 2014 BY RWW.
+
diff --git a/general/datasets/Brf2_m_0304_p/contributors.rtf b/general/datasets/Brf2_m_0304_p/contributors.rtf
new file mode 100644
index 0000000..92da9ca
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_p/contributors.rtf
@@ -0,0 +1,7 @@
+PMID: 15597075
+
+Hitzemann R, Reed C, Malmanger B, Lawler M, Hitzemann B, Cunningham B, McWeeney S, Belknap J, Harrington C, Buck K, Phillips T, Crabbe J (2004) On the integration of alcohol-related quantitative trait loci and gene expression analyses. Alcohol Clin Exp Res. ;28(10):1437-1448.
+
+
+
+
diff --git a/general/datasets/Brf2_m_0304_p/experiment-design.rtf b/general/datasets/Brf2_m_0304_p/experiment-design.rtf
new file mode 100644
index 0000000..2829934
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_p/experiment-design.rtf
@@ -0,0 +1 @@
+Conventional F2 intercross.
diff --git a/general/datasets/Brf2_m_0304_p/notes.rtf b/general/datasets/Brf2_m_0304_p/notes.rtf
new file mode 100644
index 0000000..c4a728d
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_p/notes.rtf
@@ -0,0 +1,5 @@
+Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA or PDNN transforms.
+
+Data were processed using the Position-Dependent Nearest Neighbor (PDNN) method developed by Zhang and colleagues (2003. To simplify comparison between transforms, PDNN values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run as a single large batch with careful consideration to balancing samples by sex, age, and environment.
+
+Data were processed using the RMA protocol and are presented with secondary normalization to an average expression value of 8 units. To simplify comparison between transforms, RMA values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run as a single large batch with effort to balance samples by sex, age, and environment.
diff --git a/general/datasets/Brf2_m_0304_p/platform.rtf b/general/datasets/Brf2_m_0304_p/platform.rtf
new file mode 100644
index 0000000..ecb86bc
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_p/platform.rtf
@@ -0,0 +1,1154 @@
+All 56 430A arrays used in this project were purchased at one time and had the same Affymetrix lot number. The table below lists the arrays by Case ID, Array ID, Side, Cage ID and Sex.
+
+
+
+
+
+
+
+
+ |
+ Order
+ |
+
+ CaseID
+ |
+
+ ArrayID
+ |
+
+ Side
+ |
+
+ CageID
+ |
+
+ Sex
+ |
+
+
+ |
+ 1
+ |
+
+ 20
+ |
+
+ FL10
+ |
+
+ L
+ |
+
+ H1
+ |
+
+ F
+ |
+
+
+ |
+ 2
+ |
+
+ 2
+ |
+
+ FL11
+ |
+
+ L
+ |
+
+ H2
+ |
+
+ F
+ |
+
+
+ |
+ 3
+ |
+
+ 5
+ |
+
+ FL12
+ |
+
+ L
+ |
+
+ H3
+ |
+
+ F
+ |
+
+
+ |
+ 4
+ |
+
+ 63
+ |
+
+ FL13
+ |
+
+ L
+ |
+
+ H4
+ |
+
+ F
+ |
+
+
+ |
+ 5
+ |
+
+ 6
+ |
+
+ FL14
+ |
+
+ L
+ |
+
+ K2
+ |
+
+ F
+ |
+
+
+ |
+ 6
+ |
+
+ 10
+ |
+
+ FL15
+ |
+
+ L
+ |
+
+ Q2
+ |
+
+ F
+ |
+
+
+ |
+ 7
+ |
+
+ 52
+ |
+
+ FL2
+ |
+
+ L
+ |
+
+ E1
+ |
+
+ F
+ |
+
+
+ |
+ 8
+ |
+
+ 53
+ |
+
+ FL3
+ |
+
+ L
+ |
+
+ E2
+ |
+
+ F
+ |
+
+
+ |
+ 9
+ |
+
+ 42
+ |
+
+ FL4
+ |
+
+ L
+ |
+
+ E3
+ |
+
+ F
+ |
+
+
+ |
+ 10
+ |
+
+ 31
+ |
+
+ FL5
+ |
+
+ L
+ |
+
+ E4
+ |
+
+ F
+ |
+
+
+ |
+ 11
+ |
+
+ 14
+ |
+
+ FL6
+ |
+
+ L
+ |
+
+ F1
+ |
+
+ M
+ |
+
+
+ |
+ 12
+ |
+
+ 48
+ |
+
+ FL7
+ |
+
+ L
+ |
+
+ F2
+ |
+
+ F
+ |
+
+
+ |
+ 13
+ |
+
+ 60
+ |
+
+ FL8
+ |
+
+ L
+ |
+
+ F3
+ |
+
+ M
+ |
+
+
+ |
+ 14
+ |
+
+ 54
+ |
+
+ FL9
+ |
+
+ L
+ |
+
+ F4
+ |
+
+ F
+ |
+
+
+ |
+ 15
+ |
+
+ 35
+ |
+
+ FR10
+ |
+
+ R
+ |
+
+ K3
+ |
+
+ F
+ |
+
+
+ |
+ 16
+ |
+
+ 11
+ |
+
+ FR11
+ |
+
+ R
+ |
+
+ O1
+ |
+
+ F
+ |
+
+
+ |
+ 17
+ |
+
+ 21
+ |
+
+ FR12
+ |
+
+ R
+ |
+
+ O2
+ |
+
+ F
+ |
+
+
+ |
+ 18
+ |
+
+ 23
+ |
+
+ FR13
+ |
+
+ R
+ |
+
+ Q1
+ |
+
+ F
+ |
+
+
+ |
+ 19
+ |
+
+ 15
+ |
+
+ FR14
+ |
+
+ R
+ |
+
+ Q3
+ |
+
+ F
+ |
+
+
+ |
+ 20
+ |
+
+ 4
+ |
+
+ FR15
+ |
+
+ R
+ |
+
+ Q4
+ |
+
+ F
+ |
+
+
+ |
+ 21
+ |
+
+ 41
+ |
+
+ FR2
+ |
+
+ R
+ |
+
+ A2
+ |
+
+ F
+ |
+
+
+ |
+ 22
+ |
+
+ 44
+ |
+
+ FR3
+ |
+
+ R
+ |
+
+ A3
+ |
+
+ F
+ |
+
+
+ |
+ 23
+ |
+
+ 37
+ |
+
+ FR4
+ |
+
+ R
+ |
+
+ C1
+ |
+
+ F
+ |
+
+
+ |
+ 24
+ |
+
+ 8
+ |
+
+ FR5
+ |
+
+ R
+ |
+
+ C2
+ |
+
+ F
+ |
+
+
+ |
+ 25
+ |
+
+ 19
+ |
+
+ FR6
+ |
+
+ R
+ |
+
+ C3
+ |
+
+ F
+ |
+
+
+ |
+ 26
+ |
+
+ 40
+ |
+
+ FR7
+ |
+
+ R
+ |
+
+ C4
+ |
+
+ F
+ |
+
+
+ |
+ 27
+ |
+
+ 62
+ |
+
+ FR8
+ |
+
+ R
+ |
+
+ D2
+ |
+
+ M
+ |
+
+
+ |
+ 28
+ |
+
+ 39
+ |
+
+ FR9
+ |
+
+ R
+ |
+
+ D3
+ |
+
+ F
+ |
+
+
+ |
+ 29
+ |
+
+ 13
+ |
+
+ ML1
+ |
+
+ L
+ |
+
+ B1
+ |
+
+ M
+ |
+
+
+ |
+ 30
+ |
+
+ 22
+ |
+
+ ML10
+ |
+
+ L
+ |
+
+ L2
+ |
+
+ M
+ |
+
+
+ |
+ 31
+ |
+
+ 38
+ |
+
+ ML11
+ |
+
+ L
+ |
+
+ L4
+ |
+
+ M
+ |
+
+
+ |
+ 32
+ |
+
+ 43
+ |
+
+ ML12
+ |
+
+ L
+ |
+
+ M1
+ |
+
+ M
+ |
+
+
+ |
+ 33
+ |
+
+ 58
+ |
+
+ ML13
+ |
+
+ L
+ |
+
+ N2
+ |
+
+ M
+ |
+
+
+ |
+ 34
+ |
+
+ 7
+ |
+
+ ML14
+ |
+
+ L
+ |
+
+ R1
+ |
+
+ M
+ |
+
+
+ |
+ 35
+ |
+
+ 30
+ |
+
+ ML15
+ |
+
+ L
+ |
+
+ R3
+ |
+
+ M
+ |
+
+
+ |
+ 36
+ |
+
+ 46
+ |
+
+ ML3
+ |
+
+ L
+ |
+
+ G1
+ |
+
+ M
+ |
+
+
+ |
+ 37
+ |
+
+ 57
+ |
+
+ ML4
+ |
+
+ L
+ |
+
+ G2
+ |
+
+ M
+ |
+
+
+ |
+ 38
+ |
+
+ 51
+ |
+
+ ML5
+ |
+
+ L
+ |
+
+ I1
+ |
+
+ M
+ |
+
+
+ |
+ 39
+ |
+
+ 27
+ |
+
+ ML6
+ |
+
+ L
+ |
+
+ I2
+ |
+
+ M
+ |
+
+
+ |
+ 40
+ |
+
+ 50
+ |
+
+ ML7
+ |
+
+ L
+ |
+
+ J2
+ |
+
+ M
+ |
+
+
+ |
+ 41
+ |
+
+ 16
+ |
+
+ FL1
+ |
+
+ L
+ |
+
+ O2
+ |
+
+ M
+ |
+
+
+ |
+ 42
+ |
+
+ 3
+ |
+
+ ML9
+ |
+
+ L
+ |
+
+ L1
+ |
+
+ M
+ |
+
+
+ |
+ 43
+ |
+
+ 47
+ |
+
+ MR10
+ |
+
+ R
+ |
+
+ R2
+ |
+
+ M
+ |
+
+
+ |
+ 44
+ |
+
+ 56
+ |
+
+ MR11
+ |
+
+ R
+ |
+
+ S1
+ |
+
+ M
+ |
+
+
+ |
+ 45
+ |
+
+ 1
+ |
+
+ MR12
+ |
+
+ R
+ |
+
+ S2
+ |
+
+ M
+ |
+
+
+ |
+ 46
+ |
+
+ 55
+ |
+
+ MR13
+ |
+
+ R
+ |
+
+ T1
+ |
+
+ M
+ |
+
+
+ |
+ 47
+ |
+
+ 34
+ |
+
+ MR14
+ |
+
+ R
+ |
+
+ U1
+ |
+
+ M
+ |
+
+
+ |
+ 48
+ |
+
+ 25
+ |
+
+ MR15
+ |
+
+ R
+ |
+
+ U2
+ |
+
+ M
+ |
+
+
+ |
+ 49
+ |
+
+ 59
+ |
+
+ MR2
+ |
+
+ R
+ |
+
+ J1
+ |
+
+ M
+ |
+
+
+ |
+ 50
+ |
+
+ 32
+ |
+
+ MR3
+ |
+
+ R
+ |
+
+ M2
+ |
+
+ M
+ |
+
+
+ |
+ 51
+ |
+
+ 24
+ |
+
+ MR4
+ |
+
+ R
+ |
+
+ M3
+ |
+
+ M
+ |
+
+
+ |
+ 52
+ |
+
+ 12
+ |
+
+ MR5
+ |
+
+ R
+ |
+
+ M4
+ |
+
+ M
+ |
+
+
+ |
+ 53
+ |
+
+ 9
+ |
+
+ MR6
+ |
+
+ R
+ |
+
+ N1
+ |
+
+ M
+ |
+
+
+ |
+ 54
+ |
+
+ 36
+ |
+
+ MR7
+ |
+
+ R
+ |
+
+ N3
+ |
+
+ M
+ |
+
+
+ |
+ 55
+ |
+
+ 28
+ |
+
+ MR8
+ |
+
+ R
+ |
+
+ P1
+ |
+
+ M
+ |
+
+
+ |
+ 56
+ |
+
+ 33
+ |
+
+ MR9
+ |
+
+ R
+ |
+
+ P2
+ |
+
+ M
+ |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Brf2_m_0304_p/processing.rtf b/general/datasets/Brf2_m_0304_p/processing.rtf
new file mode 100644
index 0000000..002c868
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_p/processing.rtf
@@ -0,0 +1,16 @@
+The 56 mice were each genotyped at 309 MIT microsatellite markers distributed across the genome, including the Y chromosome. The genotyping error check routine (Lincoln and Lander, 1992) implemented within R/qtl (Broman et al., 2003) showed no likely errors at p <.01 probability. Initial genotypes were generated at OHSU. Approximately 200 genotypes were generated at UTHSC by Jing Gu and Shuhua Qi.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are the 75% quantiles from a set of 91 pixel values per cell. Probe values were processed as follows:
+
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each probe signal.
+ - Step 3: We computed the Z score for each signal within array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each of the individual strains.
+
+
+Probe set data from the TXT file: These TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+The chromosomal locations of M430A and M430B probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Brf2_m_0304_p/summary.rtf b/general/datasets/Brf2_m_0304_p/summary.rtf
new file mode 100644
index 0000000..8c926cd
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_p/summary.rtf
@@ -0,0 +1 @@
+This March 2004 data freeze provides estimate of mRNA expression in adult brains of F2 intercross mice (C57BL/6J x DBA/2J F2) measured using Affymetrix M430A microarrays. Data were generated at The Oregon Health Sciences University (OHSU) in Portland, Oregon, by John Belknap and Robert Hitzemann. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA or PDNN transforms.
diff --git a/general/datasets/Brf2_m_0304_p/tissue.rtf b/general/datasets/Brf2_m_0304_p/tissue.rtf
new file mode 100644
index 0000000..863b8e6
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_p/tissue.rtf
@@ -0,0 +1 @@
+Brain samples were from 31 male and 25 females and between 28 right and 28 left hemispheres distributed with good balance across the two sexes. The tissue arrayed included the forebrain, midbrain, one olfactory bulb, the cerebellum; and the rostral part of the medulla. The medulla was trimmed transversely at the caudal aspect of the cerebellum. The sagittal cut was made from a dorsal to ventral direction. (Note that several of the other brain transcriptome databases do not include olfactory bulb or cerebellum.) Total RNA was isolated with TRIZOL Reagent (Life Technologies Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer’s protocol. The extracted RNA was then purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for purity; only samples with an A260/280 ratio greater than 1.8 were used. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. Samples containing at least 10 micrograms of total RNA were sent to the OHSU Gene Microarray Shared Resource facility for analysis. The procedures used at the facility precisely follow the manufacturer’s specifications. Details can be found at http://www.ohsu.edu/gmsr/amc. Following labeling, all samples were hybridized to the GeneChip Test3 array for quality control. If target performance did not meet recommended thresholds, the sample would have been discarded. All labeled samples passed the threshold and were hybridized to the 430A array.
diff --git a/general/datasets/Brf2_m_0304_r/acknowledgment.rtf b/general/datasets/Brf2_m_0304_r/acknowledgment.rtf
new file mode 100644
index 0000000..e67d66a
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_r/acknowledgment.rtf
@@ -0,0 +1,3 @@
+This project was supported by two Department of Veterans Affairs Merit Review Awards (to JK Belknap and R Hitzemann, respectively), AA10760 (Portland Alcohol Research Center), AA06243, AA13484, AA11034, DA05228 and MH51372.
+
+Please contact either John Belknap or Robert Hitzemann at the Dept. of Behavioral Neuroscience, Oregon Health & Science University (L470), or Research Service (R&D5), Portland VA Medical Ctr., Portland, OR 97239 USA.
diff --git a/general/datasets/Brf2_m_0304_r/cases.rtf b/general/datasets/Brf2_m_0304_r/cases.rtf
new file mode 100644
index 0000000..3d9dd38
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_r/cases.rtf
@@ -0,0 +1,3 @@
+Fifty-six B6D2F2 samples, each taken from a single brain hemisphere from an individual mouse, were assayed using 56 M430A Affymetrix short oligomer microarrays. [The remaining hemisphere will be used later for an anaysis of specific brain regions.] Each array ID (see table below) includes a three letter code; the first letter usually denotes sex of the case (note that we have made a few corrections and there are therefore several sex-discordant IDs), the second letter denotes the hemisphere (R or L), and the third letter is the mouse number within each cell. The F2 mice were experimentally naive, born within a 3-day period from second litters of each dam, and housed at weaning (20- to 24-days-of-age) in like-sex groups of 3 to 4 mice for females and 2 to 3 mice for males in standard mouse shoebox cages within Thoren racks. All 56 F2 mice were killed at 77 to 79 days-of-age by cervical dislocation on December 17, 2003. The brains were immediately split at the midline and then quickly frozen on dry ice. The brains were stored for about two weeks at -80 degrees C until further use.
+
+The F2 was derived as follows: C57BL/6J (B6) and DBA/2J (D2) breeders were obtained from The Jackson Laboratory, and two generations later their progeny were crossed to produce B6D2F1 and D2B6F1 hybrid at the Portland VA Veterinary Medical Unit (AAALAC approved). The reciprocal F1s were mated to create an F2 population with both progenitor X and Y chromosomes about equally represented.
diff --git a/general/datasets/Brf2_m_0304_r/citation.rtf b/general/datasets/Brf2_m_0304_r/citation.rtf
new file mode 100644
index 0000000..3c5403c
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_r/citation.rtf
@@ -0,0 +1,21 @@
+
+Hitzemann, R, McWeeney, S, Harrington, S, Malmanger, B, Lawler, M, Belknap, JK (2004) Brain gene expression among four inbred mouse strains: The development of an analysis strategy for the integration of QTL and gene expression data. Submitted.
+
+
+
+Irizarry, RA, Bolstad, BM, Collin, F, Cope, LM, Hobbs, B, Speed, TP (2003) Summaries of Affymetrix GeneChip probe level data. Nuc Acids Res 31:1-15.
+
+
+
+Lincoln, SE, Lander, ES (1992) Systematic detection of errors in genetic linkage data. Genomics 14:604-610.
+
+
+
+Zhang, L, Miles, MF, Aldape, KD (2003) A model of molecular interactions on short oligonucleotide microarrays. Nat Biotech 21:818-821.
+
+
+ Information about this text file:
+
+
+This text file was originally generated by John Belknap, March 2004. Updated by RWW, October 31, 2004, EJC June 21, 2005. Updated with reference, NOV 2014 BY RWW.
+
diff --git a/general/datasets/Brf2_m_0304_r/contributors.rtf b/general/datasets/Brf2_m_0304_r/contributors.rtf
new file mode 100644
index 0000000..92da9ca
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_r/contributors.rtf
@@ -0,0 +1,7 @@
+PMID: 15597075
+
+Hitzemann R, Reed C, Malmanger B, Lawler M, Hitzemann B, Cunningham B, McWeeney S, Belknap J, Harrington C, Buck K, Phillips T, Crabbe J (2004) On the integration of alcohol-related quantitative trait loci and gene expression analyses. Alcohol Clin Exp Res. ;28(10):1437-1448.
+
+
+
+
diff --git a/general/datasets/Brf2_m_0304_r/experiment-design.rtf b/general/datasets/Brf2_m_0304_r/experiment-design.rtf
new file mode 100644
index 0000000..2829934
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_r/experiment-design.rtf
@@ -0,0 +1 @@
+Conventional F2 intercross.
diff --git a/general/datasets/Brf2_m_0304_r/notes.rtf b/general/datasets/Brf2_m_0304_r/notes.rtf
new file mode 100644
index 0000000..c4a728d
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_r/notes.rtf
@@ -0,0 +1,5 @@
+Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA or PDNN transforms.
+
+Data were processed using the Position-Dependent Nearest Neighbor (PDNN) method developed by Zhang and colleagues (2003. To simplify comparison between transforms, PDNN values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run as a single large batch with careful consideration to balancing samples by sex, age, and environment.
+
+Data were processed using the RMA protocol and are presented with secondary normalization to an average expression value of 8 units. To simplify comparison between transforms, RMA values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run as a single large batch with effort to balance samples by sex, age, and environment.
diff --git a/general/datasets/Brf2_m_0304_r/platform.rtf b/general/datasets/Brf2_m_0304_r/platform.rtf
new file mode 100644
index 0000000..ecb86bc
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_r/platform.rtf
@@ -0,0 +1,1154 @@
+All 56 430A arrays used in this project were purchased at one time and had the same Affymetrix lot number. The table below lists the arrays by Case ID, Array ID, Side, Cage ID and Sex.
+
+
+
+
+
+
+
+
+ |
+ Order
+ |
+
+ CaseID
+ |
+
+ ArrayID
+ |
+
+ Side
+ |
+
+ CageID
+ |
+
+ Sex
+ |
+
+
+ |
+ 1
+ |
+
+ 20
+ |
+
+ FL10
+ |
+
+ L
+ |
+
+ H1
+ |
+
+ F
+ |
+
+
+ |
+ 2
+ |
+
+ 2
+ |
+
+ FL11
+ |
+
+ L
+ |
+
+ H2
+ |
+
+ F
+ |
+
+
+ |
+ 3
+ |
+
+ 5
+ |
+
+ FL12
+ |
+
+ L
+ |
+
+ H3
+ |
+
+ F
+ |
+
+
+ |
+ 4
+ |
+
+ 63
+ |
+
+ FL13
+ |
+
+ L
+ |
+
+ H4
+ |
+
+ F
+ |
+
+
+ |
+ 5
+ |
+
+ 6
+ |
+
+ FL14
+ |
+
+ L
+ |
+
+ K2
+ |
+
+ F
+ |
+
+
+ |
+ 6
+ |
+
+ 10
+ |
+
+ FL15
+ |
+
+ L
+ |
+
+ Q2
+ |
+
+ F
+ |
+
+
+ |
+ 7
+ |
+
+ 52
+ |
+
+ FL2
+ |
+
+ L
+ |
+
+ E1
+ |
+
+ F
+ |
+
+
+ |
+ 8
+ |
+
+ 53
+ |
+
+ FL3
+ |
+
+ L
+ |
+
+ E2
+ |
+
+ F
+ |
+
+
+ |
+ 9
+ |
+
+ 42
+ |
+
+ FL4
+ |
+
+ L
+ |
+
+ E3
+ |
+
+ F
+ |
+
+
+ |
+ 10
+ |
+
+ 31
+ |
+
+ FL5
+ |
+
+ L
+ |
+
+ E4
+ |
+
+ F
+ |
+
+
+ |
+ 11
+ |
+
+ 14
+ |
+
+ FL6
+ |
+
+ L
+ |
+
+ F1
+ |
+
+ M
+ |
+
+
+ |
+ 12
+ |
+
+ 48
+ |
+
+ FL7
+ |
+
+ L
+ |
+
+ F2
+ |
+
+ F
+ |
+
+
+ |
+ 13
+ |
+
+ 60
+ |
+
+ FL8
+ |
+
+ L
+ |
+
+ F3
+ |
+
+ M
+ |
+
+
+ |
+ 14
+ |
+
+ 54
+ |
+
+ FL9
+ |
+
+ L
+ |
+
+ F4
+ |
+
+ F
+ |
+
+
+ |
+ 15
+ |
+
+ 35
+ |
+
+ FR10
+ |
+
+ R
+ |
+
+ K3
+ |
+
+ F
+ |
+
+
+ |
+ 16
+ |
+
+ 11
+ |
+
+ FR11
+ |
+
+ R
+ |
+
+ O1
+ |
+
+ F
+ |
+
+
+ |
+ 17
+ |
+
+ 21
+ |
+
+ FR12
+ |
+
+ R
+ |
+
+ O2
+ |
+
+ F
+ |
+
+
+ |
+ 18
+ |
+
+ 23
+ |
+
+ FR13
+ |
+
+ R
+ |
+
+ Q1
+ |
+
+ F
+ |
+
+
+ |
+ 19
+ |
+
+ 15
+ |
+
+ FR14
+ |
+
+ R
+ |
+
+ Q3
+ |
+
+ F
+ |
+
+
+ |
+ 20
+ |
+
+ 4
+ |
+
+ FR15
+ |
+
+ R
+ |
+
+ Q4
+ |
+
+ F
+ |
+
+
+ |
+ 21
+ |
+
+ 41
+ |
+
+ FR2
+ |
+
+ R
+ |
+
+ A2
+ |
+
+ F
+ |
+
+
+ |
+ 22
+ |
+
+ 44
+ |
+
+ FR3
+ |
+
+ R
+ |
+
+ A3
+ |
+
+ F
+ |
+
+
+ |
+ 23
+ |
+
+ 37
+ |
+
+ FR4
+ |
+
+ R
+ |
+
+ C1
+ |
+
+ F
+ |
+
+
+ |
+ 24
+ |
+
+ 8
+ |
+
+ FR5
+ |
+
+ R
+ |
+
+ C2
+ |
+
+ F
+ |
+
+
+ |
+ 25
+ |
+
+ 19
+ |
+
+ FR6
+ |
+
+ R
+ |
+
+ C3
+ |
+
+ F
+ |
+
+
+ |
+ 26
+ |
+
+ 40
+ |
+
+ FR7
+ |
+
+ R
+ |
+
+ C4
+ |
+
+ F
+ |
+
+
+ |
+ 27
+ |
+
+ 62
+ |
+
+ FR8
+ |
+
+ R
+ |
+
+ D2
+ |
+
+ M
+ |
+
+
+ |
+ 28
+ |
+
+ 39
+ |
+
+ FR9
+ |
+
+ R
+ |
+
+ D3
+ |
+
+ F
+ |
+
+
+ |
+ 29
+ |
+
+ 13
+ |
+
+ ML1
+ |
+
+ L
+ |
+
+ B1
+ |
+
+ M
+ |
+
+
+ |
+ 30
+ |
+
+ 22
+ |
+
+ ML10
+ |
+
+ L
+ |
+
+ L2
+ |
+
+ M
+ |
+
+
+ |
+ 31
+ |
+
+ 38
+ |
+
+ ML11
+ |
+
+ L
+ |
+
+ L4
+ |
+
+ M
+ |
+
+
+ |
+ 32
+ |
+
+ 43
+ |
+
+ ML12
+ |
+
+ L
+ |
+
+ M1
+ |
+
+ M
+ |
+
+
+ |
+ 33
+ |
+
+ 58
+ |
+
+ ML13
+ |
+
+ L
+ |
+
+ N2
+ |
+
+ M
+ |
+
+
+ |
+ 34
+ |
+
+ 7
+ |
+
+ ML14
+ |
+
+ L
+ |
+
+ R1
+ |
+
+ M
+ |
+
+
+ |
+ 35
+ |
+
+ 30
+ |
+
+ ML15
+ |
+
+ L
+ |
+
+ R3
+ |
+
+ M
+ |
+
+
+ |
+ 36
+ |
+
+ 46
+ |
+
+ ML3
+ |
+
+ L
+ |
+
+ G1
+ |
+
+ M
+ |
+
+
+ |
+ 37
+ |
+
+ 57
+ |
+
+ ML4
+ |
+
+ L
+ |
+
+ G2
+ |
+
+ M
+ |
+
+
+ |
+ 38
+ |
+
+ 51
+ |
+
+ ML5
+ |
+
+ L
+ |
+
+ I1
+ |
+
+ M
+ |
+
+
+ |
+ 39
+ |
+
+ 27
+ |
+
+ ML6
+ |
+
+ L
+ |
+
+ I2
+ |
+
+ M
+ |
+
+
+ |
+ 40
+ |
+
+ 50
+ |
+
+ ML7
+ |
+
+ L
+ |
+
+ J2
+ |
+
+ M
+ |
+
+
+ |
+ 41
+ |
+
+ 16
+ |
+
+ FL1
+ |
+
+ L
+ |
+
+ O2
+ |
+
+ M
+ |
+
+
+ |
+ 42
+ |
+
+ 3
+ |
+
+ ML9
+ |
+
+ L
+ |
+
+ L1
+ |
+
+ M
+ |
+
+
+ |
+ 43
+ |
+
+ 47
+ |
+
+ MR10
+ |
+
+ R
+ |
+
+ R2
+ |
+
+ M
+ |
+
+
+ |
+ 44
+ |
+
+ 56
+ |
+
+ MR11
+ |
+
+ R
+ |
+
+ S1
+ |
+
+ M
+ |
+
+
+ |
+ 45
+ |
+
+ 1
+ |
+
+ MR12
+ |
+
+ R
+ |
+
+ S2
+ |
+
+ M
+ |
+
+
+ |
+ 46
+ |
+
+ 55
+ |
+
+ MR13
+ |
+
+ R
+ |
+
+ T1
+ |
+
+ M
+ |
+
+
+ |
+ 47
+ |
+
+ 34
+ |
+
+ MR14
+ |
+
+ R
+ |
+
+ U1
+ |
+
+ M
+ |
+
+
+ |
+ 48
+ |
+
+ 25
+ |
+
+ MR15
+ |
+
+ R
+ |
+
+ U2
+ |
+
+ M
+ |
+
+
+ |
+ 49
+ |
+
+ 59
+ |
+
+ MR2
+ |
+
+ R
+ |
+
+ J1
+ |
+
+ M
+ |
+
+
+ |
+ 50
+ |
+
+ 32
+ |
+
+ MR3
+ |
+
+ R
+ |
+
+ M2
+ |
+
+ M
+ |
+
+
+ |
+ 51
+ |
+
+ 24
+ |
+
+ MR4
+ |
+
+ R
+ |
+
+ M3
+ |
+
+ M
+ |
+
+
+ |
+ 52
+ |
+
+ 12
+ |
+
+ MR5
+ |
+
+ R
+ |
+
+ M4
+ |
+
+ M
+ |
+
+
+ |
+ 53
+ |
+
+ 9
+ |
+
+ MR6
+ |
+
+ R
+ |
+
+ N1
+ |
+
+ M
+ |
+
+
+ |
+ 54
+ |
+
+ 36
+ |
+
+ MR7
+ |
+
+ R
+ |
+
+ N3
+ |
+
+ M
+ |
+
+
+ |
+ 55
+ |
+
+ 28
+ |
+
+ MR8
+ |
+
+ R
+ |
+
+ P1
+ |
+
+ M
+ |
+
+
+ |
+ 56
+ |
+
+ 33
+ |
+
+ MR9
+ |
+
+ R
+ |
+
+ P2
+ |
+
+ M
+ |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Brf2_m_0304_r/processing.rtf b/general/datasets/Brf2_m_0304_r/processing.rtf
new file mode 100644
index 0000000..002c868
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_r/processing.rtf
@@ -0,0 +1,16 @@
+The 56 mice were each genotyped at 309 MIT microsatellite markers distributed across the genome, including the Y chromosome. The genotyping error check routine (Lincoln and Lander, 1992) implemented within R/qtl (Broman et al., 2003) showed no likely errors at p <.01 probability. Initial genotypes were generated at OHSU. Approximately 200 genotypes were generated at UTHSC by Jing Gu and Shuhua Qi.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are the 75% quantiles from a set of 91 pixel values per cell. Probe values were processed as follows:
+
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each probe signal.
+ - Step 3: We computed the Z score for each signal within array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each of the individual strains.
+
+
+Probe set data from the TXT file: These TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+The chromosomal locations of M430A and M430B probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Brf2_m_0304_r/summary.rtf b/general/datasets/Brf2_m_0304_r/summary.rtf
new file mode 100644
index 0000000..8c926cd
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_r/summary.rtf
@@ -0,0 +1 @@
+This March 2004 data freeze provides estimate of mRNA expression in adult brains of F2 intercross mice (C57BL/6J x DBA/2J F2) measured using Affymetrix M430A microarrays. Data were generated at The Oregon Health Sciences University (OHSU) in Portland, Oregon, by John Belknap and Robert Hitzemann. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA or PDNN transforms.
diff --git a/general/datasets/Brf2_m_0304_r/tissue.rtf b/general/datasets/Brf2_m_0304_r/tissue.rtf
new file mode 100644
index 0000000..863b8e6
--- /dev/null
+++ b/general/datasets/Brf2_m_0304_r/tissue.rtf
@@ -0,0 +1 @@
+Brain samples were from 31 male and 25 females and between 28 right and 28 left hemispheres distributed with good balance across the two sexes. The tissue arrayed included the forebrain, midbrain, one olfactory bulb, the cerebellum; and the rostral part of the medulla. The medulla was trimmed transversely at the caudal aspect of the cerebellum. The sagittal cut was made from a dorsal to ventral direction. (Note that several of the other brain transcriptome databases do not include olfactory bulb or cerebellum.) Total RNA was isolated with TRIZOL Reagent (Life Technologies Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer’s protocol. The extracted RNA was then purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for purity; only samples with an A260/280 ratio greater than 1.8 were used. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. Samples containing at least 10 micrograms of total RNA were sent to the OHSU Gene Microarray Shared Resource facility for analysis. The procedures used at the facility precisely follow the manufacturer’s specifications. Details can be found at http://www.ohsu.edu/gmsr/amc. Following labeling, all samples were hybridized to the GeneChip Test3 array for quality control. If target performance did not meet recommended thresholds, the sample would have been discarded. All labeled samples passed the threshold and were hybridized to the 430A array.
diff --git a/general/datasets/Brf2_m_0805_m/acknowledgment.rtf b/general/datasets/Brf2_m_0805_m/acknowledgment.rtf
new file mode 100644
index 0000000..e7f05c1
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_m/acknowledgment.rtf
@@ -0,0 +1,5 @@
+
+This project was supported by two Department of Veterans Affairs Merit Review Awards (to JK Belknap and R Hitzemann, respectively), AA10760 (Portland Alcohol Research Center), AA06243, AA13484, AA11034, DA05228 and MH51372.
+
+Please contact either John Belknap or Robert Hitzemann at the Dept. of Behavioral Neuroscience, Oregon Health & Science University (L470), or Research Service (R&D5), Portland VA Medical Ctr., Portland, OR 97239 USA.
+
diff --git a/general/datasets/Brf2_m_0805_m/cases.rtf b/general/datasets/Brf2_m_0805_m/cases.rtf
new file mode 100644
index 0000000..4f69ca9
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_m/cases.rtf
@@ -0,0 +1,3 @@
+Fifty-six B6D2F2 samples, each taken from a single brain hemisphere from an individual mouse, were assayed using 56 M430A&B Affymetrix short oligomer microarrays. [The remaining hemisphere will be used later for an anaysis of specific brain regions.] Each array ID (see table below) includes a three letter code; the first letter usually denotes sex of the case (note that we have made a few corrections and there are therefore several sex-discordant IDs), the second letter denotes the hemisphere (R or L), and the third letter is the mouse number within each cell. The F2 mice were experimentally naive, born within a 3-day period from second litters of each dam, and housed at weaning (20- to 24-days-of-age) in like-sex groups of 3 to 4 mice for females and 2 to 3 mice for males in standard mouse shoebox cages within Thoren racks. All 56 F2 mice were killed at 77 to 79 days-of-age by cervical dislocation on December 17, 2003. The brains were immediately split at the midline and then quickly frozen on dry ice. The brains were stored for about two weeks at -80 degrees C until further use.
+
+The F2 was derived as follows: C57BL/6J (B6) and DBA/2J (D2) breeders were obtained from The Jackson Laboratory, and two generations later their progeny were crossed to produce B6D2F1 and D2B6F1 hybrid at the Portland VA Veterinary Medical Unit (AAALAC approved). The reciprocal F1s were mated to create an F2 population with both progenitor X and Y chromosomes about equally represented.
diff --git a/general/datasets/Brf2_m_0805_m/citation.rtf b/general/datasets/Brf2_m_0805_m/citation.rtf
new file mode 100644
index 0000000..8e8e73d
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_m/citation.rtf
@@ -0,0 +1,15 @@
+
+Hitzemann R, Reed C, Malmanger B, Lawler M, Hitzemann B, Cunningham B, McWeeney S, Belknap J, Harrington C, Buck K, Phillips T, Crabbe J. (2004) On the integration of alcohol-related quantitative trait loci and gene expression analyses.. Alcohol Clin Exp Res. 2004 Oct;28(10):1437-48. PMID:15597075
+
+
+
+Irizarry, RA, Bolstad, BM, Collin, F, Cope, LM, Hobbs, B, Speed, TP (2003) Summaries of Affymetrix GeneChip probe level data. Nuc Acids Res 31:1-15.
+
+
+
+Lincoln, SE, Lander, ES (1992) Systematic detection of errors in genetic linkage data. Genomics 14:604-610.
+
+
+
+Zhang, L, Miles, MF, Aldape, KD (2003) A model of molecular interactions on short oligonucleotide microarrays. Nat Biotech 21:818-821.
+
diff --git a/general/datasets/Brf2_m_0805_m/contributors.rtf b/general/datasets/Brf2_m_0805_m/contributors.rtf
new file mode 100644
index 0000000..fa18035
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_m/contributors.rtf
@@ -0,0 +1,7 @@
+BACKGROUND:Quantitative trait loci (QTLs) have been detected for a wide variety of ethanol-related phenotypes, including acute and chronic ethanol withdrawal, acute locomotor activation, and ethanol preference. This study was undertaken to determine whether the process of moving from QTL to quantitative trait gene (QTG) could be accelerated by the integration of functional genomics (gene expression) into the analysis strategy.
+
+METHODS:Six ethanol-related QTLs, all detected in C57BL/6J and DBA/2J intercrosses were entered into the analysis. Each of the QTLs had been confirmed in independent genetic models at least once; the cumulative probabilities for QTL existence ranged from 10 to 10. Brain gene expression data for the C57BL/6 and DBA/2 strains (n = 6 per strain) and an F2 intercross sample (n = 56) derived from these strains were obtained by using the Affymetrix U74Av2 and 430A arrays; additional data with the U74Av2 array were available for the extended amygdala, dorsomedial striatum, and hippocampus. Low-level analysis was performed by using multiple methods to determine the likelihood that a transcript was truly differentially expressed. For the 430A array data, the F2 sample was used to determine which of the differentially expressed transcripts within the QTL intervals were cis-regulated and, thus, strong candidates for QTGs.
+
+RESULTS:Within the 6 QTL intervals, 39 transcripts (430A array) were identified as being highly likely to be differentially expressed between the C57BL/6 and DBA/2 strains at a false discovery rate of 0.01 or better. Twenty-eight of these transcripts showed significant (logarithm of odds > or =3.6) to highly significant (logarithm of odds >7) cis-regulation. The process correctly detected Mpdz (chromosome 4) as a candidate QTG for acute withdrawal.
+
+CONCLUSIONS:Although improvements are needed in the expression databases, the integration of QTL and gene expression analyses seems to have potential as a high-throughput strategy for moving from QTL to QTG.
diff --git a/general/datasets/Brf2_m_0805_m/notes.rtf b/general/datasets/Brf2_m_0805_m/notes.rtf
new file mode 100644
index 0000000..7fafba3
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_m/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file was originally generated by John Belknap, March 2004. Updated by RWW, October 31, 2004, EJC June 21, 2005.
+
diff --git a/general/datasets/Brf2_m_0805_m/platform.rtf b/general/datasets/Brf2_m_0805_m/platform.rtf
new file mode 100644
index 0000000..f0ee528
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_m/platform.rtf
@@ -0,0 +1,1154 @@
+All 56 430A&B arrays used in this project were purchased at one time and had the same Affymetrix lot number. The table below lists the arrays by Case ID, Array ID, Side, Cage ID and Sex.
+
+
+
+
+
+
+
+
+ |
+ Order
+ |
+
+ CaseID
+ |
+
+ ArrayID
+ |
+
+ Side
+ |
+
+ CageID
+ |
+
+ Sex
+ |
+
+
+ |
+ 1
+ |
+
+ 20
+ |
+
+ FL10
+ |
+
+ L
+ |
+
+ H1
+ |
+
+ F
+ |
+
+
+ |
+ 2
+ |
+
+ 2
+ |
+
+ FL11
+ |
+
+ L
+ |
+
+ H2
+ |
+
+ F
+ |
+
+
+ |
+ 3
+ |
+
+ 5
+ |
+
+ FL12
+ |
+
+ L
+ |
+
+ H3
+ |
+
+ F
+ |
+
+
+ |
+ 4
+ |
+
+ 63
+ |
+
+ FL13
+ |
+
+ L
+ |
+
+ H4
+ |
+
+ F
+ |
+
+
+ |
+ 5
+ |
+
+ 6
+ |
+
+ FL14
+ |
+
+ L
+ |
+
+ K2
+ |
+
+ F
+ |
+
+
+ |
+ 6
+ |
+
+ 10
+ |
+
+ FL15
+ |
+
+ L
+ |
+
+ Q2
+ |
+
+ F
+ |
+
+
+ |
+ 7
+ |
+
+ 52
+ |
+
+ FL2
+ |
+
+ L
+ |
+
+ E1
+ |
+
+ F
+ |
+
+
+ |
+ 8
+ |
+
+ 53
+ |
+
+ FL3
+ |
+
+ L
+ |
+
+ E2
+ |
+
+ F
+ |
+
+
+ |
+ 9
+ |
+
+ 42
+ |
+
+ FL4
+ |
+
+ L
+ |
+
+ E3
+ |
+
+ F
+ |
+
+
+ |
+ 10
+ |
+
+ 31
+ |
+
+ FL5
+ |
+
+ L
+ |
+
+ E4
+ |
+
+ F
+ |
+
+
+ |
+ 11
+ |
+
+ 14
+ |
+
+ FL6
+ |
+
+ L
+ |
+
+ F1
+ |
+
+ M
+ |
+
+
+ |
+ 12
+ |
+
+ 48
+ |
+
+ FL7
+ |
+
+ L
+ |
+
+ F2
+ |
+
+ F
+ |
+
+
+ |
+ 13
+ |
+
+ 60
+ |
+
+ FL8
+ |
+
+ L
+ |
+
+ F3
+ |
+
+ M
+ |
+
+
+ |
+ 14
+ |
+
+ 54
+ |
+
+ FL9
+ |
+
+ L
+ |
+
+ F4
+ |
+
+ F
+ |
+
+
+ |
+ 15
+ |
+
+ 35
+ |
+
+ FR10
+ |
+
+ R
+ |
+
+ K3
+ |
+
+ F
+ |
+
+
+ |
+ 16
+ |
+
+ 11
+ |
+
+ FR11
+ |
+
+ R
+ |
+
+ O1
+ |
+
+ F
+ |
+
+
+ |
+ 17
+ |
+
+ 21
+ |
+
+ FR12
+ |
+
+ R
+ |
+
+ O2
+ |
+
+ F
+ |
+
+
+ |
+ 18
+ |
+
+ 23
+ |
+
+ FR13
+ |
+
+ R
+ |
+
+ Q1
+ |
+
+ F
+ |
+
+
+ |
+ 19
+ |
+
+ 15
+ |
+
+ FR14
+ |
+
+ R
+ |
+
+ Q3
+ |
+
+ F
+ |
+
+
+ |
+ 20
+ |
+
+ 4
+ |
+
+ FR15
+ |
+
+ R
+ |
+
+ Q4
+ |
+
+ F
+ |
+
+
+ |
+ 21
+ |
+
+ 41
+ |
+
+ FR2
+ |
+
+ R
+ |
+
+ A2
+ |
+
+ F
+ |
+
+
+ |
+ 22
+ |
+
+ 44
+ |
+
+ FR3
+ |
+
+ R
+ |
+
+ A3
+ |
+
+ F
+ |
+
+
+ |
+ 23
+ |
+
+ 37
+ |
+
+ FR4
+ |
+
+ R
+ |
+
+ C1
+ |
+
+ F
+ |
+
+
+ |
+ 24
+ |
+
+ 8
+ |
+
+ FR5
+ |
+
+ R
+ |
+
+ C2
+ |
+
+ F
+ |
+
+
+ |
+ 25
+ |
+
+ 19
+ |
+
+ FR6
+ |
+
+ R
+ |
+
+ C3
+ |
+
+ F
+ |
+
+
+ |
+ 26
+ |
+
+ 40
+ |
+
+ FR7
+ |
+
+ R
+ |
+
+ C4
+ |
+
+ F
+ |
+
+
+ |
+ 27
+ |
+
+ 62
+ |
+
+ FR8
+ |
+
+ R
+ |
+
+ D2
+ |
+
+ M
+ |
+
+
+ |
+ 28
+ |
+
+ 39
+ |
+
+ FR9
+ |
+
+ R
+ |
+
+ D3
+ |
+
+ F
+ |
+
+
+ |
+ 29
+ |
+
+ 13
+ |
+
+ ML1
+ |
+
+ L
+ |
+
+ B1
+ |
+
+ M
+ |
+
+
+ |
+ 30
+ |
+
+ 22
+ |
+
+ ML10
+ |
+
+ L
+ |
+
+ L2
+ |
+
+ M
+ |
+
+
+ |
+ 31
+ |
+
+ 38
+ |
+
+ ML11
+ |
+
+ L
+ |
+
+ L4
+ |
+
+ M
+ |
+
+
+ |
+ 32
+ |
+
+ 43
+ |
+
+ ML12
+ |
+
+ L
+ |
+
+ M1
+ |
+
+ M
+ |
+
+
+ |
+ 33
+ |
+
+ 58
+ |
+
+ ML13
+ |
+
+ L
+ |
+
+ N2
+ |
+
+ M
+ |
+
+
+ |
+ 34
+ |
+
+ 7
+ |
+
+ ML14
+ |
+
+ L
+ |
+
+ R1
+ |
+
+ M
+ |
+
+
+ |
+ 35
+ |
+
+ 30
+ |
+
+ ML15
+ |
+
+ L
+ |
+
+ R3
+ |
+
+ M
+ |
+
+
+ |
+ 36
+ |
+
+ 46
+ |
+
+ ML3
+ |
+
+ L
+ |
+
+ G1
+ |
+
+ M
+ |
+
+
+ |
+ 37
+ |
+
+ 57
+ |
+
+ ML4
+ |
+
+ L
+ |
+
+ G2
+ |
+
+ M
+ |
+
+
+ |
+ 38
+ |
+
+ 51
+ |
+
+ ML5
+ |
+
+ L
+ |
+
+ I1
+ |
+
+ M
+ |
+
+
+ |
+ 39
+ |
+
+ 27
+ |
+
+ ML6
+ |
+
+ L
+ |
+
+ I2
+ |
+
+ M
+ |
+
+
+ |
+ 40
+ |
+
+ 50
+ |
+
+ ML7
+ |
+
+ L
+ |
+
+ J2
+ |
+
+ M
+ |
+
+
+ |
+ 41
+ |
+
+ 16
+ |
+
+ FL1
+ |
+
+ L
+ |
+
+ O2
+ |
+
+ M
+ |
+
+
+ |
+ 42
+ |
+
+ 3
+ |
+
+ ML9
+ |
+
+ L
+ |
+
+ L1
+ |
+
+ M
+ |
+
+
+ |
+ 43
+ |
+
+ 47
+ |
+
+ MR10
+ |
+
+ R
+ |
+
+ R2
+ |
+
+ M
+ |
+
+
+ |
+ 44
+ |
+
+ 56
+ |
+
+ MR11
+ |
+
+ R
+ |
+
+ S1
+ |
+
+ M
+ |
+
+
+ |
+ 45
+ |
+
+ 1
+ |
+
+ MR12
+ |
+
+ R
+ |
+
+ S2
+ |
+
+ M
+ |
+
+
+ |
+ 46
+ |
+
+ 55
+ |
+
+ MR13
+ |
+
+ R
+ |
+
+ T1
+ |
+
+ M
+ |
+
+
+ |
+ 47
+ |
+
+ 34
+ |
+
+ MR14
+ |
+
+ R
+ |
+
+ U1
+ |
+
+ M
+ |
+
+
+ |
+ 48
+ |
+
+ 25
+ |
+
+ MR15
+ |
+
+ R
+ |
+
+ U2
+ |
+
+ M
+ |
+
+
+ |
+ 49
+ |
+
+ 59
+ |
+
+ MR2
+ |
+
+ R
+ |
+
+ J1
+ |
+
+ M
+ |
+
+
+ |
+ 50
+ |
+
+ 32
+ |
+
+ MR3
+ |
+
+ R
+ |
+
+ M2
+ |
+
+ M
+ |
+
+
+ |
+ 51
+ |
+
+ 24
+ |
+
+ MR4
+ |
+
+ R
+ |
+
+ M3
+ |
+
+ M
+ |
+
+
+ |
+ 52
+ |
+
+ 12
+ |
+
+ MR5
+ |
+
+ R
+ |
+
+ M4
+ |
+
+ M
+ |
+
+
+ |
+ 53
+ |
+
+ 9
+ |
+
+ MR6
+ |
+
+ R
+ |
+
+ N1
+ |
+
+ M
+ |
+
+
+ |
+ 54
+ |
+
+ 36
+ |
+
+ MR7
+ |
+
+ R
+ |
+
+ N3
+ |
+
+ M
+ |
+
+
+ |
+ 55
+ |
+
+ 28
+ |
+
+ MR8
+ |
+
+ R
+ |
+
+ P1
+ |
+
+ M
+ |
+
+
+ |
+ 56
+ |
+
+ 33
+ |
+
+ MR9
+ |
+
+ R
+ |
+
+ P2
+ |
+
+ M
+ |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Brf2_m_0805_m/processing.rtf b/general/datasets/Brf2_m_0805_m/processing.rtf
new file mode 100644
index 0000000..8a23d84
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_m/processing.rtf
@@ -0,0 +1,26 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are the 75% quantiles from a set of 91 pixel values per cell. Probe values were processed as follows:
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We took the log base 2 of each probe signal.
+ - Step 3: We computed the Z scores for each probe signal.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B arrays include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes provide a way to calibrate expression of the A and B arrays to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+
+
+Probe set data from the TXT file: These TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+
+About the marker set:
+
+
+The 56 mice were each genotyped at 309 MIT microsatellite markers distributed across the genome, including the Y chromosome. The genotyping error check routine (Lincoln and Lander, 1992) implemented within R/qtl (Broman et al., 2003) showed no likely errors at p <.01 probability. Initial genotypes were generated at OHSU. Approximately 200 genotypes were generated at UTHSC by Jing Gu and Shuhua Qi.
+
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of M430A and M430B probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium March 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
+
diff --git a/general/datasets/Brf2_m_0805_m/summary.rtf b/general/datasets/Brf2_m_0805_m/summary.rtf
new file mode 100644
index 0000000..6f477fe
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_m/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimate of mRNA expression in adult brains of F2 intercross mice (C57BL/6J x DBA/2J F2) measured using Affymetrix M430A and M430B microarray pairs. Data were generated at The Oregon Health Sciences University (OHSU) in Portland, Oregon, by John Belknap and Robert Hitzemann. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA or PDNN transforms.
diff --git a/general/datasets/Brf2_m_0805_m/tissue.rtf b/general/datasets/Brf2_m_0805_m/tissue.rtf
new file mode 100644
index 0000000..ef85488
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_m/tissue.rtf
@@ -0,0 +1 @@
+Brain samples were from 31 male and 25 females and between 28 right and 28 left hemispheres distributed with good balance across the two sexes. The tissue arrayed included the forebrain, midbrain, one olfactory bulb, the cerebellum; and the rostral part of the medulla. The medulla was trimmed transversely at the caudal aspect of the cerebellum. The sagittal cut was made from a dorsal to ventral direction. (Note that several of the other brain transcriptome databases do not include olfactory bulb or cerebellum.) Total RNA was isolated with TRIZOL Reagent (Life Technologies Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer’s protocol. The extracted RNA was then purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for purity; only samples with an A260/280 ratio greater than 1.8 were used. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. Samples containing at least 10 micrograms of total RNA were sent to the OHSU Gene Microarray Shared Resource facility for analysis. The procedures used at the facility precisely follow the manufacturer’s specifications. Details can be found at http://www.ohsu.edu/gmsr/amc. Following labeling, all samples were hybridized to the GeneChip Test3 array for quality control. If target performance did not meet recommended thresholds, the sample would have been discarded. All labeled samples passed the threshold and were hybridized to the 430A and 430B array pairs.
diff --git a/general/datasets/Brf2_m_0805_p/acknowledgment.rtf b/general/datasets/Brf2_m_0805_p/acknowledgment.rtf
new file mode 100644
index 0000000..e7f05c1
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_p/acknowledgment.rtf
@@ -0,0 +1,5 @@
+
+This project was supported by two Department of Veterans Affairs Merit Review Awards (to JK Belknap and R Hitzemann, respectively), AA10760 (Portland Alcohol Research Center), AA06243, AA13484, AA11034, DA05228 and MH51372.
+
+Please contact either John Belknap or Robert Hitzemann at the Dept. of Behavioral Neuroscience, Oregon Health & Science University (L470), or Research Service (R&D5), Portland VA Medical Ctr., Portland, OR 97239 USA.
+
diff --git a/general/datasets/Brf2_m_0805_p/cases.rtf b/general/datasets/Brf2_m_0805_p/cases.rtf
new file mode 100644
index 0000000..4f69ca9
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_p/cases.rtf
@@ -0,0 +1,3 @@
+Fifty-six B6D2F2 samples, each taken from a single brain hemisphere from an individual mouse, were assayed using 56 M430A&B Affymetrix short oligomer microarrays. [The remaining hemisphere will be used later for an anaysis of specific brain regions.] Each array ID (see table below) includes a three letter code; the first letter usually denotes sex of the case (note that we have made a few corrections and there are therefore several sex-discordant IDs), the second letter denotes the hemisphere (R or L), and the third letter is the mouse number within each cell. The F2 mice were experimentally naive, born within a 3-day period from second litters of each dam, and housed at weaning (20- to 24-days-of-age) in like-sex groups of 3 to 4 mice for females and 2 to 3 mice for males in standard mouse shoebox cages within Thoren racks. All 56 F2 mice were killed at 77 to 79 days-of-age by cervical dislocation on December 17, 2003. The brains were immediately split at the midline and then quickly frozen on dry ice. The brains were stored for about two weeks at -80 degrees C until further use.
+
+The F2 was derived as follows: C57BL/6J (B6) and DBA/2J (D2) breeders were obtained from The Jackson Laboratory, and two generations later their progeny were crossed to produce B6D2F1 and D2B6F1 hybrid at the Portland VA Veterinary Medical Unit (AAALAC approved). The reciprocal F1s were mated to create an F2 population with both progenitor X and Y chromosomes about equally represented.
diff --git a/general/datasets/Brf2_m_0805_p/citation.rtf b/general/datasets/Brf2_m_0805_p/citation.rtf
new file mode 100644
index 0000000..8e8e73d
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_p/citation.rtf
@@ -0,0 +1,15 @@
+
+Hitzemann R, Reed C, Malmanger B, Lawler M, Hitzemann B, Cunningham B, McWeeney S, Belknap J, Harrington C, Buck K, Phillips T, Crabbe J. (2004) On the integration of alcohol-related quantitative trait loci and gene expression analyses.. Alcohol Clin Exp Res. 2004 Oct;28(10):1437-48. PMID:15597075
+
+
+
+Irizarry, RA, Bolstad, BM, Collin, F, Cope, LM, Hobbs, B, Speed, TP (2003) Summaries of Affymetrix GeneChip probe level data. Nuc Acids Res 31:1-15.
+
+
+
+Lincoln, SE, Lander, ES (1992) Systematic detection of errors in genetic linkage data. Genomics 14:604-610.
+
+
+
+Zhang, L, Miles, MF, Aldape, KD (2003) A model of molecular interactions on short oligonucleotide microarrays. Nat Biotech 21:818-821.
+
diff --git a/general/datasets/Brf2_m_0805_p/contributors.rtf b/general/datasets/Brf2_m_0805_p/contributors.rtf
new file mode 100644
index 0000000..fa18035
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_p/contributors.rtf
@@ -0,0 +1,7 @@
+BACKGROUND:Quantitative trait loci (QTLs) have been detected for a wide variety of ethanol-related phenotypes, including acute and chronic ethanol withdrawal, acute locomotor activation, and ethanol preference. This study was undertaken to determine whether the process of moving from QTL to quantitative trait gene (QTG) could be accelerated by the integration of functional genomics (gene expression) into the analysis strategy.
+
+METHODS:Six ethanol-related QTLs, all detected in C57BL/6J and DBA/2J intercrosses were entered into the analysis. Each of the QTLs had been confirmed in independent genetic models at least once; the cumulative probabilities for QTL existence ranged from 10 to 10. Brain gene expression data for the C57BL/6 and DBA/2 strains (n = 6 per strain) and an F2 intercross sample (n = 56) derived from these strains were obtained by using the Affymetrix U74Av2 and 430A arrays; additional data with the U74Av2 array were available for the extended amygdala, dorsomedial striatum, and hippocampus. Low-level analysis was performed by using multiple methods to determine the likelihood that a transcript was truly differentially expressed. For the 430A array data, the F2 sample was used to determine which of the differentially expressed transcripts within the QTL intervals were cis-regulated and, thus, strong candidates for QTGs.
+
+RESULTS:Within the 6 QTL intervals, 39 transcripts (430A array) were identified as being highly likely to be differentially expressed between the C57BL/6 and DBA/2 strains at a false discovery rate of 0.01 or better. Twenty-eight of these transcripts showed significant (logarithm of odds > or =3.6) to highly significant (logarithm of odds >7) cis-regulation. The process correctly detected Mpdz (chromosome 4) as a candidate QTG for acute withdrawal.
+
+CONCLUSIONS:Although improvements are needed in the expression databases, the integration of QTL and gene expression analyses seems to have potential as a high-throughput strategy for moving from QTL to QTG.
diff --git a/general/datasets/Brf2_m_0805_p/notes.rtf b/general/datasets/Brf2_m_0805_p/notes.rtf
new file mode 100644
index 0000000..7fafba3
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_p/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file was originally generated by John Belknap, March 2004. Updated by RWW, October 31, 2004, EJC June 21, 2005.
+
diff --git a/general/datasets/Brf2_m_0805_p/platform.rtf b/general/datasets/Brf2_m_0805_p/platform.rtf
new file mode 100644
index 0000000..f0ee528
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_p/platform.rtf
@@ -0,0 +1,1154 @@
+All 56 430A&B arrays used in this project were purchased at one time and had the same Affymetrix lot number. The table below lists the arrays by Case ID, Array ID, Side, Cage ID and Sex.
+
+
+
+
+
+
+
+
+ |
+ Order
+ |
+
+ CaseID
+ |
+
+ ArrayID
+ |
+
+ Side
+ |
+
+ CageID
+ |
+
+ Sex
+ |
+
+
+ |
+ 1
+ |
+
+ 20
+ |
+
+ FL10
+ |
+
+ L
+ |
+
+ H1
+ |
+
+ F
+ |
+
+
+ |
+ 2
+ |
+
+ 2
+ |
+
+ FL11
+ |
+
+ L
+ |
+
+ H2
+ |
+
+ F
+ |
+
+
+ |
+ 3
+ |
+
+ 5
+ |
+
+ FL12
+ |
+
+ L
+ |
+
+ H3
+ |
+
+ F
+ |
+
+
+ |
+ 4
+ |
+
+ 63
+ |
+
+ FL13
+ |
+
+ L
+ |
+
+ H4
+ |
+
+ F
+ |
+
+
+ |
+ 5
+ |
+
+ 6
+ |
+
+ FL14
+ |
+
+ L
+ |
+
+ K2
+ |
+
+ F
+ |
+
+
+ |
+ 6
+ |
+
+ 10
+ |
+
+ FL15
+ |
+
+ L
+ |
+
+ Q2
+ |
+
+ F
+ |
+
+
+ |
+ 7
+ |
+
+ 52
+ |
+
+ FL2
+ |
+
+ L
+ |
+
+ E1
+ |
+
+ F
+ |
+
+
+ |
+ 8
+ |
+
+ 53
+ |
+
+ FL3
+ |
+
+ L
+ |
+
+ E2
+ |
+
+ F
+ |
+
+
+ |
+ 9
+ |
+
+ 42
+ |
+
+ FL4
+ |
+
+ L
+ |
+
+ E3
+ |
+
+ F
+ |
+
+
+ |
+ 10
+ |
+
+ 31
+ |
+
+ FL5
+ |
+
+ L
+ |
+
+ E4
+ |
+
+ F
+ |
+
+
+ |
+ 11
+ |
+
+ 14
+ |
+
+ FL6
+ |
+
+ L
+ |
+
+ F1
+ |
+
+ M
+ |
+
+
+ |
+ 12
+ |
+
+ 48
+ |
+
+ FL7
+ |
+
+ L
+ |
+
+ F2
+ |
+
+ F
+ |
+
+
+ |
+ 13
+ |
+
+ 60
+ |
+
+ FL8
+ |
+
+ L
+ |
+
+ F3
+ |
+
+ M
+ |
+
+
+ |
+ 14
+ |
+
+ 54
+ |
+
+ FL9
+ |
+
+ L
+ |
+
+ F4
+ |
+
+ F
+ |
+
+
+ |
+ 15
+ |
+
+ 35
+ |
+
+ FR10
+ |
+
+ R
+ |
+
+ K3
+ |
+
+ F
+ |
+
+
+ |
+ 16
+ |
+
+ 11
+ |
+
+ FR11
+ |
+
+ R
+ |
+
+ O1
+ |
+
+ F
+ |
+
+
+ |
+ 17
+ |
+
+ 21
+ |
+
+ FR12
+ |
+
+ R
+ |
+
+ O2
+ |
+
+ F
+ |
+
+
+ |
+ 18
+ |
+
+ 23
+ |
+
+ FR13
+ |
+
+ R
+ |
+
+ Q1
+ |
+
+ F
+ |
+
+
+ |
+ 19
+ |
+
+ 15
+ |
+
+ FR14
+ |
+
+ R
+ |
+
+ Q3
+ |
+
+ F
+ |
+
+
+ |
+ 20
+ |
+
+ 4
+ |
+
+ FR15
+ |
+
+ R
+ |
+
+ Q4
+ |
+
+ F
+ |
+
+
+ |
+ 21
+ |
+
+ 41
+ |
+
+ FR2
+ |
+
+ R
+ |
+
+ A2
+ |
+
+ F
+ |
+
+
+ |
+ 22
+ |
+
+ 44
+ |
+
+ FR3
+ |
+
+ R
+ |
+
+ A3
+ |
+
+ F
+ |
+
+
+ |
+ 23
+ |
+
+ 37
+ |
+
+ FR4
+ |
+
+ R
+ |
+
+ C1
+ |
+
+ F
+ |
+
+
+ |
+ 24
+ |
+
+ 8
+ |
+
+ FR5
+ |
+
+ R
+ |
+
+ C2
+ |
+
+ F
+ |
+
+
+ |
+ 25
+ |
+
+ 19
+ |
+
+ FR6
+ |
+
+ R
+ |
+
+ C3
+ |
+
+ F
+ |
+
+
+ |
+ 26
+ |
+
+ 40
+ |
+
+ FR7
+ |
+
+ R
+ |
+
+ C4
+ |
+
+ F
+ |
+
+
+ |
+ 27
+ |
+
+ 62
+ |
+
+ FR8
+ |
+
+ R
+ |
+
+ D2
+ |
+
+ M
+ |
+
+
+ |
+ 28
+ |
+
+ 39
+ |
+
+ FR9
+ |
+
+ R
+ |
+
+ D3
+ |
+
+ F
+ |
+
+
+ |
+ 29
+ |
+
+ 13
+ |
+
+ ML1
+ |
+
+ L
+ |
+
+ B1
+ |
+
+ M
+ |
+
+
+ |
+ 30
+ |
+
+ 22
+ |
+
+ ML10
+ |
+
+ L
+ |
+
+ L2
+ |
+
+ M
+ |
+
+
+ |
+ 31
+ |
+
+ 38
+ |
+
+ ML11
+ |
+
+ L
+ |
+
+ L4
+ |
+
+ M
+ |
+
+
+ |
+ 32
+ |
+
+ 43
+ |
+
+ ML12
+ |
+
+ L
+ |
+
+ M1
+ |
+
+ M
+ |
+
+
+ |
+ 33
+ |
+
+ 58
+ |
+
+ ML13
+ |
+
+ L
+ |
+
+ N2
+ |
+
+ M
+ |
+
+
+ |
+ 34
+ |
+
+ 7
+ |
+
+ ML14
+ |
+
+ L
+ |
+
+ R1
+ |
+
+ M
+ |
+
+
+ |
+ 35
+ |
+
+ 30
+ |
+
+ ML15
+ |
+
+ L
+ |
+
+ R3
+ |
+
+ M
+ |
+
+
+ |
+ 36
+ |
+
+ 46
+ |
+
+ ML3
+ |
+
+ L
+ |
+
+ G1
+ |
+
+ M
+ |
+
+
+ |
+ 37
+ |
+
+ 57
+ |
+
+ ML4
+ |
+
+ L
+ |
+
+ G2
+ |
+
+ M
+ |
+
+
+ |
+ 38
+ |
+
+ 51
+ |
+
+ ML5
+ |
+
+ L
+ |
+
+ I1
+ |
+
+ M
+ |
+
+
+ |
+ 39
+ |
+
+ 27
+ |
+
+ ML6
+ |
+
+ L
+ |
+
+ I2
+ |
+
+ M
+ |
+
+
+ |
+ 40
+ |
+
+ 50
+ |
+
+ ML7
+ |
+
+ L
+ |
+
+ J2
+ |
+
+ M
+ |
+
+
+ |
+ 41
+ |
+
+ 16
+ |
+
+ FL1
+ |
+
+ L
+ |
+
+ O2
+ |
+
+ M
+ |
+
+
+ |
+ 42
+ |
+
+ 3
+ |
+
+ ML9
+ |
+
+ L
+ |
+
+ L1
+ |
+
+ M
+ |
+
+
+ |
+ 43
+ |
+
+ 47
+ |
+
+ MR10
+ |
+
+ R
+ |
+
+ R2
+ |
+
+ M
+ |
+
+
+ |
+ 44
+ |
+
+ 56
+ |
+
+ MR11
+ |
+
+ R
+ |
+
+ S1
+ |
+
+ M
+ |
+
+
+ |
+ 45
+ |
+
+ 1
+ |
+
+ MR12
+ |
+
+ R
+ |
+
+ S2
+ |
+
+ M
+ |
+
+
+ |
+ 46
+ |
+
+ 55
+ |
+
+ MR13
+ |
+
+ R
+ |
+
+ T1
+ |
+
+ M
+ |
+
+
+ |
+ 47
+ |
+
+ 34
+ |
+
+ MR14
+ |
+
+ R
+ |
+
+ U1
+ |
+
+ M
+ |
+
+
+ |
+ 48
+ |
+
+ 25
+ |
+
+ MR15
+ |
+
+ R
+ |
+
+ U2
+ |
+
+ M
+ |
+
+
+ |
+ 49
+ |
+
+ 59
+ |
+
+ MR2
+ |
+
+ R
+ |
+
+ J1
+ |
+
+ M
+ |
+
+
+ |
+ 50
+ |
+
+ 32
+ |
+
+ MR3
+ |
+
+ R
+ |
+
+ M2
+ |
+
+ M
+ |
+
+
+ |
+ 51
+ |
+
+ 24
+ |
+
+ MR4
+ |
+
+ R
+ |
+
+ M3
+ |
+
+ M
+ |
+
+
+ |
+ 52
+ |
+
+ 12
+ |
+
+ MR5
+ |
+
+ R
+ |
+
+ M4
+ |
+
+ M
+ |
+
+
+ |
+ 53
+ |
+
+ 9
+ |
+
+ MR6
+ |
+
+ R
+ |
+
+ N1
+ |
+
+ M
+ |
+
+
+ |
+ 54
+ |
+
+ 36
+ |
+
+ MR7
+ |
+
+ R
+ |
+
+ N3
+ |
+
+ M
+ |
+
+
+ |
+ 55
+ |
+
+ 28
+ |
+
+ MR8
+ |
+
+ R
+ |
+
+ P1
+ |
+
+ M
+ |
+
+
+ |
+ 56
+ |
+
+ 33
+ |
+
+ MR9
+ |
+
+ R
+ |
+
+ P2
+ |
+
+ M
+ |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Brf2_m_0805_p/processing.rtf b/general/datasets/Brf2_m_0805_p/processing.rtf
new file mode 100644
index 0000000..8a23d84
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_p/processing.rtf
@@ -0,0 +1,26 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are the 75% quantiles from a set of 91 pixel values per cell. Probe values were processed as follows:
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We took the log base 2 of each probe signal.
+ - Step 3: We computed the Z scores for each probe signal.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B arrays include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes provide a way to calibrate expression of the A and B arrays to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+
+
+Probe set data from the TXT file: These TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+
+About the marker set:
+
+
+The 56 mice were each genotyped at 309 MIT microsatellite markers distributed across the genome, including the Y chromosome. The genotyping error check routine (Lincoln and Lander, 1992) implemented within R/qtl (Broman et al., 2003) showed no likely errors at p <.01 probability. Initial genotypes were generated at OHSU. Approximately 200 genotypes were generated at UTHSC by Jing Gu and Shuhua Qi.
+
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of M430A and M430B probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium March 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
+
diff --git a/general/datasets/Brf2_m_0805_p/summary.rtf b/general/datasets/Brf2_m_0805_p/summary.rtf
new file mode 100644
index 0000000..6f477fe
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_p/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimate of mRNA expression in adult brains of F2 intercross mice (C57BL/6J x DBA/2J F2) measured using Affymetrix M430A and M430B microarray pairs. Data were generated at The Oregon Health Sciences University (OHSU) in Portland, Oregon, by John Belknap and Robert Hitzemann. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA or PDNN transforms.
diff --git a/general/datasets/Brf2_m_0805_p/tissue.rtf b/general/datasets/Brf2_m_0805_p/tissue.rtf
new file mode 100644
index 0000000..ef85488
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_p/tissue.rtf
@@ -0,0 +1 @@
+Brain samples were from 31 male and 25 females and between 28 right and 28 left hemispheres distributed with good balance across the two sexes. The tissue arrayed included the forebrain, midbrain, one olfactory bulb, the cerebellum; and the rostral part of the medulla. The medulla was trimmed transversely at the caudal aspect of the cerebellum. The sagittal cut was made from a dorsal to ventral direction. (Note that several of the other brain transcriptome databases do not include olfactory bulb or cerebellum.) Total RNA was isolated with TRIZOL Reagent (Life Technologies Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer’s protocol. The extracted RNA was then purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for purity; only samples with an A260/280 ratio greater than 1.8 were used. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. Samples containing at least 10 micrograms of total RNA were sent to the OHSU Gene Microarray Shared Resource facility for analysis. The procedures used at the facility precisely follow the manufacturer’s specifications. Details can be found at http://www.ohsu.edu/gmsr/amc. Following labeling, all samples were hybridized to the GeneChip Test3 array for quality control. If target performance did not meet recommended thresholds, the sample would have been discarded. All labeled samples passed the threshold and were hybridized to the 430A and 430B array pairs.
diff --git a/general/datasets/Brf2_m_0805_r/acknowledgment.rtf b/general/datasets/Brf2_m_0805_r/acknowledgment.rtf
new file mode 100644
index 0000000..e7f05c1
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_r/acknowledgment.rtf
@@ -0,0 +1,5 @@
+
+This project was supported by two Department of Veterans Affairs Merit Review Awards (to JK Belknap and R Hitzemann, respectively), AA10760 (Portland Alcohol Research Center), AA06243, AA13484, AA11034, DA05228 and MH51372.
+
+Please contact either John Belknap or Robert Hitzemann at the Dept. of Behavioral Neuroscience, Oregon Health & Science University (L470), or Research Service (R&D5), Portland VA Medical Ctr., Portland, OR 97239 USA.
+
diff --git a/general/datasets/Brf2_m_0805_r/cases.rtf b/general/datasets/Brf2_m_0805_r/cases.rtf
new file mode 100644
index 0000000..4f69ca9
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_r/cases.rtf
@@ -0,0 +1,3 @@
+Fifty-six B6D2F2 samples, each taken from a single brain hemisphere from an individual mouse, were assayed using 56 M430A&B Affymetrix short oligomer microarrays. [The remaining hemisphere will be used later for an anaysis of specific brain regions.] Each array ID (see table below) includes a three letter code; the first letter usually denotes sex of the case (note that we have made a few corrections and there are therefore several sex-discordant IDs), the second letter denotes the hemisphere (R or L), and the third letter is the mouse number within each cell. The F2 mice were experimentally naive, born within a 3-day period from second litters of each dam, and housed at weaning (20- to 24-days-of-age) in like-sex groups of 3 to 4 mice for females and 2 to 3 mice for males in standard mouse shoebox cages within Thoren racks. All 56 F2 mice were killed at 77 to 79 days-of-age by cervical dislocation on December 17, 2003. The brains were immediately split at the midline and then quickly frozen on dry ice. The brains were stored for about two weeks at -80 degrees C until further use.
+
+The F2 was derived as follows: C57BL/6J (B6) and DBA/2J (D2) breeders were obtained from The Jackson Laboratory, and two generations later their progeny were crossed to produce B6D2F1 and D2B6F1 hybrid at the Portland VA Veterinary Medical Unit (AAALAC approved). The reciprocal F1s were mated to create an F2 population with both progenitor X and Y chromosomes about equally represented.
diff --git a/general/datasets/Brf2_m_0805_r/citation.rtf b/general/datasets/Brf2_m_0805_r/citation.rtf
new file mode 100644
index 0000000..8e8e73d
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_r/citation.rtf
@@ -0,0 +1,15 @@
+
+Hitzemann R, Reed C, Malmanger B, Lawler M, Hitzemann B, Cunningham B, McWeeney S, Belknap J, Harrington C, Buck K, Phillips T, Crabbe J. (2004) On the integration of alcohol-related quantitative trait loci and gene expression analyses.. Alcohol Clin Exp Res. 2004 Oct;28(10):1437-48. PMID:15597075
+
+
+
+Irizarry, RA, Bolstad, BM, Collin, F, Cope, LM, Hobbs, B, Speed, TP (2003) Summaries of Affymetrix GeneChip probe level data. Nuc Acids Res 31:1-15.
+
+
+
+Lincoln, SE, Lander, ES (1992) Systematic detection of errors in genetic linkage data. Genomics 14:604-610.
+
+
+
+Zhang, L, Miles, MF, Aldape, KD (2003) A model of molecular interactions on short oligonucleotide microarrays. Nat Biotech 21:818-821.
+
diff --git a/general/datasets/Brf2_m_0805_r/contributors.rtf b/general/datasets/Brf2_m_0805_r/contributors.rtf
new file mode 100644
index 0000000..fa18035
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_r/contributors.rtf
@@ -0,0 +1,7 @@
+BACKGROUND:Quantitative trait loci (QTLs) have been detected for a wide variety of ethanol-related phenotypes, including acute and chronic ethanol withdrawal, acute locomotor activation, and ethanol preference. This study was undertaken to determine whether the process of moving from QTL to quantitative trait gene (QTG) could be accelerated by the integration of functional genomics (gene expression) into the analysis strategy.
+
+METHODS:Six ethanol-related QTLs, all detected in C57BL/6J and DBA/2J intercrosses were entered into the analysis. Each of the QTLs had been confirmed in independent genetic models at least once; the cumulative probabilities for QTL existence ranged from 10 to 10. Brain gene expression data for the C57BL/6 and DBA/2 strains (n = 6 per strain) and an F2 intercross sample (n = 56) derived from these strains were obtained by using the Affymetrix U74Av2 and 430A arrays; additional data with the U74Av2 array were available for the extended amygdala, dorsomedial striatum, and hippocampus. Low-level analysis was performed by using multiple methods to determine the likelihood that a transcript was truly differentially expressed. For the 430A array data, the F2 sample was used to determine which of the differentially expressed transcripts within the QTL intervals were cis-regulated and, thus, strong candidates for QTGs.
+
+RESULTS:Within the 6 QTL intervals, 39 transcripts (430A array) were identified as being highly likely to be differentially expressed between the C57BL/6 and DBA/2 strains at a false discovery rate of 0.01 or better. Twenty-eight of these transcripts showed significant (logarithm of odds > or =3.6) to highly significant (logarithm of odds >7) cis-regulation. The process correctly detected Mpdz (chromosome 4) as a candidate QTG for acute withdrawal.
+
+CONCLUSIONS:Although improvements are needed in the expression databases, the integration of QTL and gene expression analyses seems to have potential as a high-throughput strategy for moving from QTL to QTG.
diff --git a/general/datasets/Brf2_m_0805_r/notes.rtf b/general/datasets/Brf2_m_0805_r/notes.rtf
new file mode 100644
index 0000000..7fafba3
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file was originally generated by John Belknap, March 2004. Updated by RWW, October 31, 2004, EJC June 21, 2005.
+
diff --git a/general/datasets/Brf2_m_0805_r/platform.rtf b/general/datasets/Brf2_m_0805_r/platform.rtf
new file mode 100644
index 0000000..f0ee528
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_r/platform.rtf
@@ -0,0 +1,1154 @@
+All 56 430A&B arrays used in this project were purchased at one time and had the same Affymetrix lot number. The table below lists the arrays by Case ID, Array ID, Side, Cage ID and Sex.
+
+
+
+
+
+
+
+
+ |
+ Order
+ |
+
+ CaseID
+ |
+
+ ArrayID
+ |
+
+ Side
+ |
+
+ CageID
+ |
+
+ Sex
+ |
+
+
+ |
+ 1
+ |
+
+ 20
+ |
+
+ FL10
+ |
+
+ L
+ |
+
+ H1
+ |
+
+ F
+ |
+
+
+ |
+ 2
+ |
+
+ 2
+ |
+
+ FL11
+ |
+
+ L
+ |
+
+ H2
+ |
+
+ F
+ |
+
+
+ |
+ 3
+ |
+
+ 5
+ |
+
+ FL12
+ |
+
+ L
+ |
+
+ H3
+ |
+
+ F
+ |
+
+
+ |
+ 4
+ |
+
+ 63
+ |
+
+ FL13
+ |
+
+ L
+ |
+
+ H4
+ |
+
+ F
+ |
+
+
+ |
+ 5
+ |
+
+ 6
+ |
+
+ FL14
+ |
+
+ L
+ |
+
+ K2
+ |
+
+ F
+ |
+
+
+ |
+ 6
+ |
+
+ 10
+ |
+
+ FL15
+ |
+
+ L
+ |
+
+ Q2
+ |
+
+ F
+ |
+
+
+ |
+ 7
+ |
+
+ 52
+ |
+
+ FL2
+ |
+
+ L
+ |
+
+ E1
+ |
+
+ F
+ |
+
+
+ |
+ 8
+ |
+
+ 53
+ |
+
+ FL3
+ |
+
+ L
+ |
+
+ E2
+ |
+
+ F
+ |
+
+
+ |
+ 9
+ |
+
+ 42
+ |
+
+ FL4
+ |
+
+ L
+ |
+
+ E3
+ |
+
+ F
+ |
+
+
+ |
+ 10
+ |
+
+ 31
+ |
+
+ FL5
+ |
+
+ L
+ |
+
+ E4
+ |
+
+ F
+ |
+
+
+ |
+ 11
+ |
+
+ 14
+ |
+
+ FL6
+ |
+
+ L
+ |
+
+ F1
+ |
+
+ M
+ |
+
+
+ |
+ 12
+ |
+
+ 48
+ |
+
+ FL7
+ |
+
+ L
+ |
+
+ F2
+ |
+
+ F
+ |
+
+
+ |
+ 13
+ |
+
+ 60
+ |
+
+ FL8
+ |
+
+ L
+ |
+
+ F3
+ |
+
+ M
+ |
+
+
+ |
+ 14
+ |
+
+ 54
+ |
+
+ FL9
+ |
+
+ L
+ |
+
+ F4
+ |
+
+ F
+ |
+
+
+ |
+ 15
+ |
+
+ 35
+ |
+
+ FR10
+ |
+
+ R
+ |
+
+ K3
+ |
+
+ F
+ |
+
+
+ |
+ 16
+ |
+
+ 11
+ |
+
+ FR11
+ |
+
+ R
+ |
+
+ O1
+ |
+
+ F
+ |
+
+
+ |
+ 17
+ |
+
+ 21
+ |
+
+ FR12
+ |
+
+ R
+ |
+
+ O2
+ |
+
+ F
+ |
+
+
+ |
+ 18
+ |
+
+ 23
+ |
+
+ FR13
+ |
+
+ R
+ |
+
+ Q1
+ |
+
+ F
+ |
+
+
+ |
+ 19
+ |
+
+ 15
+ |
+
+ FR14
+ |
+
+ R
+ |
+
+ Q3
+ |
+
+ F
+ |
+
+
+ |
+ 20
+ |
+
+ 4
+ |
+
+ FR15
+ |
+
+ R
+ |
+
+ Q4
+ |
+
+ F
+ |
+
+
+ |
+ 21
+ |
+
+ 41
+ |
+
+ FR2
+ |
+
+ R
+ |
+
+ A2
+ |
+
+ F
+ |
+
+
+ |
+ 22
+ |
+
+ 44
+ |
+
+ FR3
+ |
+
+ R
+ |
+
+ A3
+ |
+
+ F
+ |
+
+
+ |
+ 23
+ |
+
+ 37
+ |
+
+ FR4
+ |
+
+ R
+ |
+
+ C1
+ |
+
+ F
+ |
+
+
+ |
+ 24
+ |
+
+ 8
+ |
+
+ FR5
+ |
+
+ R
+ |
+
+ C2
+ |
+
+ F
+ |
+
+
+ |
+ 25
+ |
+
+ 19
+ |
+
+ FR6
+ |
+
+ R
+ |
+
+ C3
+ |
+
+ F
+ |
+
+
+ |
+ 26
+ |
+
+ 40
+ |
+
+ FR7
+ |
+
+ R
+ |
+
+ C4
+ |
+
+ F
+ |
+
+
+ |
+ 27
+ |
+
+ 62
+ |
+
+ FR8
+ |
+
+ R
+ |
+
+ D2
+ |
+
+ M
+ |
+
+
+ |
+ 28
+ |
+
+ 39
+ |
+
+ FR9
+ |
+
+ R
+ |
+
+ D3
+ |
+
+ F
+ |
+
+
+ |
+ 29
+ |
+
+ 13
+ |
+
+ ML1
+ |
+
+ L
+ |
+
+ B1
+ |
+
+ M
+ |
+
+
+ |
+ 30
+ |
+
+ 22
+ |
+
+ ML10
+ |
+
+ L
+ |
+
+ L2
+ |
+
+ M
+ |
+
+
+ |
+ 31
+ |
+
+ 38
+ |
+
+ ML11
+ |
+
+ L
+ |
+
+ L4
+ |
+
+ M
+ |
+
+
+ |
+ 32
+ |
+
+ 43
+ |
+
+ ML12
+ |
+
+ L
+ |
+
+ M1
+ |
+
+ M
+ |
+
+
+ |
+ 33
+ |
+
+ 58
+ |
+
+ ML13
+ |
+
+ L
+ |
+
+ N2
+ |
+
+ M
+ |
+
+
+ |
+ 34
+ |
+
+ 7
+ |
+
+ ML14
+ |
+
+ L
+ |
+
+ R1
+ |
+
+ M
+ |
+
+
+ |
+ 35
+ |
+
+ 30
+ |
+
+ ML15
+ |
+
+ L
+ |
+
+ R3
+ |
+
+ M
+ |
+
+
+ |
+ 36
+ |
+
+ 46
+ |
+
+ ML3
+ |
+
+ L
+ |
+
+ G1
+ |
+
+ M
+ |
+
+
+ |
+ 37
+ |
+
+ 57
+ |
+
+ ML4
+ |
+
+ L
+ |
+
+ G2
+ |
+
+ M
+ |
+
+
+ |
+ 38
+ |
+
+ 51
+ |
+
+ ML5
+ |
+
+ L
+ |
+
+ I1
+ |
+
+ M
+ |
+
+
+ |
+ 39
+ |
+
+ 27
+ |
+
+ ML6
+ |
+
+ L
+ |
+
+ I2
+ |
+
+ M
+ |
+
+
+ |
+ 40
+ |
+
+ 50
+ |
+
+ ML7
+ |
+
+ L
+ |
+
+ J2
+ |
+
+ M
+ |
+
+
+ |
+ 41
+ |
+
+ 16
+ |
+
+ FL1
+ |
+
+ L
+ |
+
+ O2
+ |
+
+ M
+ |
+
+
+ |
+ 42
+ |
+
+ 3
+ |
+
+ ML9
+ |
+
+ L
+ |
+
+ L1
+ |
+
+ M
+ |
+
+
+ |
+ 43
+ |
+
+ 47
+ |
+
+ MR10
+ |
+
+ R
+ |
+
+ R2
+ |
+
+ M
+ |
+
+
+ |
+ 44
+ |
+
+ 56
+ |
+
+ MR11
+ |
+
+ R
+ |
+
+ S1
+ |
+
+ M
+ |
+
+
+ |
+ 45
+ |
+
+ 1
+ |
+
+ MR12
+ |
+
+ R
+ |
+
+ S2
+ |
+
+ M
+ |
+
+
+ |
+ 46
+ |
+
+ 55
+ |
+
+ MR13
+ |
+
+ R
+ |
+
+ T1
+ |
+
+ M
+ |
+
+
+ |
+ 47
+ |
+
+ 34
+ |
+
+ MR14
+ |
+
+ R
+ |
+
+ U1
+ |
+
+ M
+ |
+
+
+ |
+ 48
+ |
+
+ 25
+ |
+
+ MR15
+ |
+
+ R
+ |
+
+ U2
+ |
+
+ M
+ |
+
+
+ |
+ 49
+ |
+
+ 59
+ |
+
+ MR2
+ |
+
+ R
+ |
+
+ J1
+ |
+
+ M
+ |
+
+
+ |
+ 50
+ |
+
+ 32
+ |
+
+ MR3
+ |
+
+ R
+ |
+
+ M2
+ |
+
+ M
+ |
+
+
+ |
+ 51
+ |
+
+ 24
+ |
+
+ MR4
+ |
+
+ R
+ |
+
+ M3
+ |
+
+ M
+ |
+
+
+ |
+ 52
+ |
+
+ 12
+ |
+
+ MR5
+ |
+
+ R
+ |
+
+ M4
+ |
+
+ M
+ |
+
+
+ |
+ 53
+ |
+
+ 9
+ |
+
+ MR6
+ |
+
+ R
+ |
+
+ N1
+ |
+
+ M
+ |
+
+
+ |
+ 54
+ |
+
+ 36
+ |
+
+ MR7
+ |
+
+ R
+ |
+
+ N3
+ |
+
+ M
+ |
+
+
+ |
+ 55
+ |
+
+ 28
+ |
+
+ MR8
+ |
+
+ R
+ |
+
+ P1
+ |
+
+ M
+ |
+
+
+ |
+ 56
+ |
+
+ 33
+ |
+
+ MR9
+ |
+
+ R
+ |
+
+ P2
+ |
+
+ M
+ |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Brf2_m_0805_r/processing.rtf b/general/datasets/Brf2_m_0805_r/processing.rtf
new file mode 100644
index 0000000..8a23d84
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_r/processing.rtf
@@ -0,0 +1,26 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are the 75% quantiles from a set of 91 pixel values per cell. Probe values were processed as follows:
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We took the log base 2 of each probe signal.
+ - Step 3: We computed the Z scores for each probe signal.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B arrays include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes provide a way to calibrate expression of the A and B arrays to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+
+
+Probe set data from the TXT file: These TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+
+About the marker set:
+
+
+The 56 mice were each genotyped at 309 MIT microsatellite markers distributed across the genome, including the Y chromosome. The genotyping error check routine (Lincoln and Lander, 1992) implemented within R/qtl (Broman et al., 2003) showed no likely errors at p <.01 probability. Initial genotypes were generated at OHSU. Approximately 200 genotypes were generated at UTHSC by Jing Gu and Shuhua Qi.
+
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of M430A and M430B probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium March 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
+
diff --git a/general/datasets/Brf2_m_0805_r/summary.rtf b/general/datasets/Brf2_m_0805_r/summary.rtf
new file mode 100644
index 0000000..6f477fe
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_r/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimate of mRNA expression in adult brains of F2 intercross mice (C57BL/6J x DBA/2J F2) measured using Affymetrix M430A and M430B microarray pairs. Data were generated at The Oregon Health Sciences University (OHSU) in Portland, Oregon, by John Belknap and Robert Hitzemann. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA or PDNN transforms.
diff --git a/general/datasets/Brf2_m_0805_r/tissue.rtf b/general/datasets/Brf2_m_0805_r/tissue.rtf
new file mode 100644
index 0000000..ef85488
--- /dev/null
+++ b/general/datasets/Brf2_m_0805_r/tissue.rtf
@@ -0,0 +1 @@
+Brain samples were from 31 male and 25 females and between 28 right and 28 left hemispheres distributed with good balance across the two sexes. The tissue arrayed included the forebrain, midbrain, one olfactory bulb, the cerebellum; and the rostral part of the medulla. The medulla was trimmed transversely at the caudal aspect of the cerebellum. The sagittal cut was made from a dorsal to ventral direction. (Note that several of the other brain transcriptome databases do not include olfactory bulb or cerebellum.) Total RNA was isolated with TRIZOL Reagent (Life Technologies Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer’s protocol. The extracted RNA was then purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for purity; only samples with an A260/280 ratio greater than 1.8 were used. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. Samples containing at least 10 micrograms of total RNA were sent to the OHSU Gene Microarray Shared Resource facility for analysis. The procedures used at the facility precisely follow the manufacturer’s specifications. Details can be found at http://www.ohsu.edu/gmsr/amc. Following labeling, all samples were hybridized to the GeneChip Test3 array for quality control. If target performance did not meet recommended thresholds, the sample would have been discarded. All labeled samples passed the threshold and were hybridized to the 430A and 430B array pairs.
diff --git a/general/datasets/Bxd_bonepublish/specifics.rtf b/general/datasets/Bxd_bonepublish/specifics.rtf
new file mode 100644
index 0000000..c23ed10
--- /dev/null
+++ b/general/datasets/Bxd_bonepublish/specifics.rtf
@@ -0,0 +1 @@
+BXD Bone Individual Data
\ No newline at end of file
diff --git a/general/datasets/Bxd_bonepublish/summary.rtf b/general/datasets/Bxd_bonepublish/summary.rtf
new file mode 100644
index 0000000..153d98d
--- /dev/null
+++ b/general/datasets/Bxd_bonepublish/summary.rtf
@@ -0,0 +1 @@
+In working progress...
diff --git a/general/datasets/Bxd_gla_0911/experiment-design.rtf b/general/datasets/Bxd_gla_0911/experiment-design.rtf
new file mode 100644
index 0000000..f01b888
--- /dev/null
+++ b/general/datasets/Bxd_gla_0911/experiment-design.rtf
@@ -0,0 +1,9 @@
+TEXT FROM GEO
+
+Genome-wide assessment of gene expression changes was performed in DBA/2J mice. The optic nerve head and retina from 40 DBA/2J eyes at 10.5 months of age were separately profiled. These eyes were selected as they encompassed a range of glaucoma severity. Two control groups were also included; 10 eyes from 10.5 months old D2-Gpnmb+ mice (age and strain matched, no glaucoma control) and 10 eyes from 4.5 months old DBA/2J mice (young, pre-glaucoma).
+
+In this study that was specifically designed to identify early stages of glaucoma in DBA/2J mice, we used genome-wide expression profiling and a series of computational methods. Our methods successfully subdivided eyes with no detectable glaucoma by conventional assays into molecularly defined stages of disease. These stages represent a temporally ordered sequence of glaucoma states. Using an array of tools, we then determined networks and biological processes that are altered at these early stages. Our strategy proved very sensitive, suggesting that similar approaches will be valuable for uncovering early processes in other complex, later-onset diseases. Early changes included upregulation of both the complement cascade and endothelin system, and so we tested the therapeutic value of separately inhibiting them. Mice with a mutation in the complement component 1a gene (C1qa) were robustly protected from glaucoma with the protection being among the greatest reported. Similarly, inhibition of the endothelin system was strongly protective. Since EDN2 is potently vasoconstrictive and was produced by microglial/macrophages, our data provide a novel link between these cell types and vascular dysfunction in glaucoma. Targeting early events such as the upregulation of the complement and endothelin pathways may provide effective new treatments for human glaucoma. (text above from GEO http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26299)
+
+
+
+
diff --git a/general/datasets/Bxd_gla_0911/summary.rtf b/general/datasets/Bxd_gla_0911/summary.rtf
new file mode 100644
index 0000000..09c8a43
--- /dev/null
+++ b/general/datasets/Bxd_gla_0911/summary.rtf
@@ -0,0 +1,58 @@
+This is an experimental glaucoma gene expression data set of retinal tissue entered into GeneNetwork by Dr. Eldon Geisert and Robert Williams in which BXD strains have been "highjacked" with experimental and control gene expression data generated by Drs Gareth Howell, Simon John, and colleagues at the Jackson Laboratory. These data were originally entered into GeneNetwork Sept 20, 2011.
+
+Please see the original paper by Howell et al (2011): http://www.jci.org/articles/view/44646 and GEO data at NCBI.
+
+Gareth R. Howell, Danilo G. Macalinao, Gregory L. Sousa, Michael Walden, Ileana Soto, Stephen C. Kneeland, Jessica M. Barbay, Benjamin L. King, Jeffrey K. Marchant, Matthew Hibbs, Beth Stevens, Ben A. Barres, Abbot F. Clark, Richard T. Libby, Simon S (2011) Molecular clustering identifies complement and endothelin induction as early events in a mouse model of glaucoma. J Clin Invest. 121:1429–1444
+
+Each strain corresponds to a particular retinal sample as shown below (note that we have not included ten "preglaucoma control" samples, see http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26299
+
+
+ - BXD1 D2-Gpnmb+ control rep1 (retina)
+ - BXD2 D2-Gpnmb+ control rep2 (retina)
+ - BXD5 D2-Gpnmb+ control rep3 (retina)
+ - BXD6 D2-Gpnmb+ control rep4 (retina)
+ - BXD8 D2-Gpnmb+ control rep5 (retina)
+ - BXD9 D2-Gpnmb+ control rep6 (retina)
+ - BXD11 D2-Gpnmb+ control rep7 (retina)
+ - BXD12 D2-Gpnmb+ control rep8 (retina)
+ - BXD13 D2-Gpnmb+ control rep9 (retina)
+ - BXD14 D2-Gpnmb+ control rep10 (retina)
+ - BXD15 No or early 1 rep1 (retina)
+ - BXD16 No or early 1 rep2 (retina)
+ - BXD18 No or early 1 rep3 (retina)
+ - BXD19 No or early 1 rep4 (retina)
+ - BXD20 No or early 1 rep5 (retina)
+ - BXD22 No or early 1 rep6 (retina)
+ - BXD23 No or early 1 rep7 (retina)
+ - BXD25 No or early 1 rep8 (retina)
+ - BXD27 No or early 1 rep9 (retina)
+ - BXD28 No or early 1 rep10 (retina)
+ - BXD29 No or early 2 rep1 (retina)
+ - BXD30 No or early 2 rep2 (retina)
+ - BXD31 No or early 2 rep3 (retina)
+ - BXD32 No or early 2 rep4 (retina)
+ - BXD33 No or early 2 rep5 (retina)
+ - BXD34 No or early 2 rep6 (retina)
+ - BXD35 No or early 2 rep7 (retina)
+ - BXD36 No or early 2 rep8 (retina)
+ - BXD37 No or early 2 rep9 (retina)
+ - BXD38 No or early 2 rep10 (retina)
+ - BXD39 Moderate rep1 (retina)
+ - BXD40 Moderate rep2 (retina)
+ - BXD41 Moderate rep3 (retina)
+ - BXD42 Moderate rep4 (retina)
+ - BXD43 Moderate rep7 (retina)
+ - BXD44 Moderate rep8 (retina)
+ - BXD45 Moderate rep9 (retina)
+ - BXD48 Moderate rep10 (retina)
+ - BXD49 Severe rep1 (retina)
+ - BXD50 Severe rep2 (retina)
+ - BXD51 Severe rep3 (retina)
+ - BXD52 Severe rep4 (retina)
+ - BXD53 Severe rep5 (retina)
+ - BXD54 Severe rep6 (retina)
+ - BXD55 Severe rep7 (retina)
+ - BXD56 Severe rep8 (retina)
+ - BXD59 Severe rep9 (retina)
+ - BXD60 Severe rep10 (retina)
+
diff --git a/general/datasets/Bxd_harvestedpublish/specifics.rtf b/general/datasets/Bxd_harvestedpublish/specifics.rtf
new file mode 100644
index 0000000..7b317eb
--- /dev/null
+++ b/general/datasets/Bxd_harvestedpublish/specifics.rtf
@@ -0,0 +1 @@
+BXD-NIA-Longevity Phenotypes
\ No newline at end of file
diff --git a/general/datasets/Bxd_harvestedpublish/summary.rtf b/general/datasets/Bxd_harvestedpublish/summary.rtf
new file mode 100644
index 0000000..88d835c
--- /dev/null
+++ b/general/datasets/Bxd_harvestedpublish/summary.rtf
@@ -0,0 +1 @@
+BXD-NIA-Longevity Phenotypes
diff --git a/general/datasets/Bxdgeno/acknowledgment.rtf b/general/datasets/Bxdgeno/acknowledgment.rtf
new file mode 100644
index 0000000..d291eb6
--- /dev/null
+++ b/general/datasets/Bxdgeno/acknowledgment.rtf
@@ -0,0 +1,11 @@
+The majority of SNP genotypes were generated at GeneSeek using the GigaMUGA array, at UNC using the Affymetrix mouse genotyping array, and at Illumina with support from the Wellcome Trust. The selection of markers to included in the final file was carried out by Robert W. Williams and Danny Arends in December 2017.
+
+Reference:
+
+Dietrich WF, Katz H, Lincoln SE (1992) A genetic map of the mouse suitable for typing in intraspecific crosses. Genetics 131:423-447.
+
+Taylor BA, Wnek C, Kotlus BS, Roemer N, MacTaggart T, Phillips SJ (1999) Genotyping new BXD recombinant inbred mouse strains and comparison of BXD and consensus maps. Mamm Genome 10:335-348.
+
+Williams RW, Gu J, Qi S, Lu L (2001) The genetic structure of recombinant inbred mice: High-resolution consensus maps for complex trait analysis. Genome Biology 2:RESEARCH0046
+
+Wiltshire T, Pletcher MT, Batalov S, Barnes SW, Tarantino LM, Cooke MP, Wu H, Smylie K, Santrosyan A, Copeland NG, Jenkins NA, Kalush F, Mural RJ, Glynne RJ, Kay SA, Adams MD, Fletcher CF (2003) Genome-wide single-nucleotide polymorphism analysis defines haplotype patterns in mouse. Proc Natl Acad Sci USA 100:3380-3385.
diff --git a/general/datasets/Bxdgeno/summary.rtf b/general/datasets/Bxdgeno/summary.rtf
new file mode 100644
index 0000000..cdb56ad
--- /dev/null
+++ b/general/datasets/Bxdgeno/summary.rtf
@@ -0,0 +1,59 @@
+(Updated July 1, 2022 by D. Ashbrook)
+
+All variants are publicly available for anyone to get whatever type and frequency of variant that they want to. The variant vcf is under analyses files in project PRJEB45429 https://www.ebi.ac.uk/ena/browser/view/PRJEB45429?show=analyses
+
+(Updated March 15, 2018 by RW Williams)
+
+BXD Genotypes file status (January 2017): From September 2016 to January 2017, Robert Williams, Jesse Ingels, Lu Lu, and Danny Arends released a new genotype file for the original BXD strains (BXD1 through BXD102) and for all of the new strains (BXD104 to BXD220). Version 1 of this genotype file (used from jan 2017 to March 13, 2018) contained data for 7324 markers and 198 strains. Version 2 of March 14, 2018 fixed some errors of marker location detected by Karl Broman (five markers were out of order in the latest mouse genome assembly). We deleted three markers and retained a final set of 7321 markers, now all in correct order based on the SNP position using the mm10 assembly.
+
+Of the 198 BXD strains, 191 are independent, whereas 7 are substrains (e.g., BXD48 and BXD48a). The file provides approximate locations of 10300 recombinations, an average of 52 per strain. Genotypes were generated using Affymetrix, MUGA, MegaMUGA, and GigaMUGA Illumina platforms. Microsatellites and eQTL genotypes were generated by the Williams/Lu laboratory. Unknown genotypes were imputed as B or D, or were called as H (heterozygous) if the genotype was uncertain. Genotypes were manually curated by RW Williams. Genotypes were smoothed to remove unlikely recombination events. Almost all recombinations are supported by multiple markers, although only one or two representative markers may be provided in this file. The original parent file (BXD_El_Grande_Master_Used_to_Proof_Final_Genotypes_2016.xlxs) contains data for approximately 37000 markers. Genotypes for Chr Y and Chr M are provisional and will be verified in 2017. As of 2016, many strains with higher numbers (BXD100 and above) are not fully inbred.
+
+
+
+A link to the genotype file is provide here
+
+
+
+Genotypes were generated at GeneSeek (Neogen Inc) with financial support from the University of Tennessee Center for Integrative and Translational Genomics. We thank Drs. Fernando Pardo-Manuel de Villena (University of North Carolina) and Gary Churchill (The Jackson Laboratory) for developing the GigaMUGA arreay.
+
+The new genotypes are now available in GeneNetwork as the 2017 Genotype file. All SNPs were mapped to the newer Dec 2011, mm10, GRCm38 assembly.
+
+As of Jan 2017 GeneNetwork uses mm10 coordinates for mapping functions. Older mm9 versions of GeneNetwork are available on the GN TimeMachine (see upper right side of Search page).
+
+BXD Genotype: The state of a gene or DNA sequence, usually used to describe a contrast between two or more states, such as that between the normal state (wildtype) and a mutant state (mutation) or between the alleles inherited from two parents. All species that are included in GeneNetwork are diploid (derived from two parents) and have two copies of most genes (genes located on the X and Y chromosomes are exceptions). As a result the genotype of a particular diploid individual is actually a pair of genotypes, one from each parents. For example, the offspring of a mating between strain A and strain B will have one copy of the A genotype and one copy of the B genotype and therefore have an A/B genotype. In contrast, offspring of a mating between a female strain A and a male strain A will inherit only A genotypes and have an A/A genotype.
+
+Genotypes can be measured or inferred in many different ways, even by visual inspection of animals (e.g. as Gregor Mendel did long before DNA was discovered). But now the typical method is to directly test DNA that has a well define chromosomal location that has been obtained from one or usually many cases using molecular tests that often rely on polymerase chain reaction steps and sequence analysis. Each case is genotyped at many chromosomal locations (loci, markers, or genes). The entire collection of genotypes (as many a 1 million for a single case) is also sometimes referred to as the cases genotype, but the word "genometype" might be more appropriate to highlight the fact that we are now dealing with a set of genotypes spanning the entire genome (all chromosomes) of the case.
+
+For gene mapping purposes, genotypes are often translated from letter codes (A/A, A/B, and B/B) to simple numerical codes that are more suitable for computation. A/A might be represented by the value -1, A/B by the value 0, and B/B by the value +1. This recoding makes it easy to determine if there is a statistically significant correlation between genotypes across of a set of cases (for example, an F2 population or a Genetic Reference Panel) and a variable phenotype measured in the same population. A sufficiently high correlation between genotypes and phenotypes is referred to as a quantitative trait locus (QTL). If the correlation is almost perfect (r > 0.9) then correlation is usually referred to as a Mendelian locus. Despite the fact that we use the term "correlation" in the preceding sentences, the genotype is actually the cause of the phenotype. More precisely, variation in the genotypes of individuals in the sample population cause the variation in the phenotype. The statistical confidence of this assertion of causality is often estimated using LOD and LRS scores and permutation methods. If the LOD score is above 10, then we can be extremely confident that we have located a genetic cause of variation in the phenotype. While the location is defined usually with a precision ranging from 10 million to 100 thousand basepairs (the locus), the individual sequence variant that is responsible may be quite difficult to extract. Think of this in terms of police work: we may know the neighborhood where the suspect lives, we may have clues as to identity and habits, but we still may have a large list of suspects.
+
+The BXD genotype file was initially upgraded in 2010-2011 using the new high density Affymetrix array (580,000 high quality SNPs) developed in the laboratories of Drs. Fernando Pardo-Manuel de Villena (University of North Carolina) and Gary Churchill (The Jackson Laboratory, see Yang H, Ding Y, Hutchins LN, Szatkiewicz J, Bell TA, Paigen BJ, Graber JH, Pardo-Manuel de Villena, F, Churchill GA (2009) A customized and verstatile high density genotyping array for the mouse. Nat Methods 6:663-666)
+
+The BXD genotype file used from June 2005 through December 2016 exploits a set of approximatey 3796 markers typed across 88 extant and extinct BXD strains (BXD1 through BXD102). The mean interval between informative markers is about 0.7 Mb. This genotype file includes all markers, both SNPs and microsatellites, with unique strain distribution patterns (SDPs), as well as pairs of markers for those SDPs represented by two or more markers. In those situations where three or more markers had the same SDP, we retained only the most proximal and distal marker in the genotype file. This particular file has also been smoothed to eliminate genotypes that are likely to be erroneous. We have also conservatively imputed a small number of missing genotypes (usually over very short intervals). Smoothing genotypes is this way reduces the total number of SDPs and also lowers the rate of false discovery. However, this procedure also may eliminate some genuine SDPs.
+
+The new smoothed BXD genotype data file (2017) can be downloaded from
+GeneNetwork at the URL http://www.genenetwork.org/genotypes/BXD.geno.
+
+Please Note: For a limited number of markers and strains, the genotypes of BXDs have been called heterozygous. This is usually done over comparatively short intervals in some of the newer strains that may not have been fully inbred when they were initially genotyped. Use of the genotype file above in external software packages such as R/qtl, requires careful treatment of this issue to prevent bias in empirical significance thresholds. It is recommended to treat these rare heterozygous loci as missing data and ensure that only the additive effects of B vs. D alleles are estimated by these packages. (note by Elissa Chesler, Dec 2010).
+
+Source of Genotypes:
+
+In collaboration with members of the CTC (Richard Mott, Jonathan Flint, and colleagues), we have helped genotype a total of 480 strains using a panel of 13,377 SNPs. These SNPs were combined with our previious microsatellite genotypes to produce the older "classic" consensus maps for the expanded set of BXD using the older mouse assemblies (Mouse Build 36 - UCSC mm8 and then mm9). (Files were updated from mm6 to mm8 in January 2007, and from mm9 to mm10 in January 2017).
+
+A total of 198 strains have be genotyped as of Jan 2017 using the full set of SNPs, and about 7324 of these are informative. Informative in this sense simply means that the C57BL/6J and DBA/2J parental strains have different alleles. To reduce false positive errors when mapping using this ultra dense map, we have eliminated most single genotypes that generate double-recombinant haplotypes that are most commonly produced by typing errors ("smoothed" genotypes). For this reason, the genotypes used in the GeneNetwork differ from those downloaded directly from Richard Mott's web site at the Wellcome Trust, Oxford or from the Jackson Laboratory.
+
+We have genotyped all available BXD strains from The Jackson Laboratory. BXD1 through BXD32 were produced by Benjamin Taylor starting in the late 1970s. BXD33 through BXD42 were produced by Taylor in the 1990s (Taylor et al., 1999). All BXD strains with numbers higher than BXD42 (BXD43 through BXD100) were generated by Lu Lu and Robert Williams at UTHSC, and by Jeremy Peirce and Lee Silver at Princeton University. We thank Guomin Zhou for generating the advanced intercross stock used to produce most of these advanced RI strains both at UTHSC and Princeton. There are approximately 48 of these advanced BXD strains, each of which archives approximately twice the recombinations present in a typical F2-derived recombinant inbred strain (Peirce et al. 2003).
+
+Mapping Algorithm:
+
+Due to the very high density of markers, the mapping algorithm used to map BXD data sets has been modified and is a mixture of simple marker regression, linear interpolation, and standard Haley-Knott interval mapping. When two adjacent markers have identical SDPs, they will have identical linkage statistics, as will the entire interval between these two markers (assuming complete and error-free haplotype data for all strains). On a physical map the LRS and the additive effect values will therefore be constant over this physical interval. Between neighboring markers that have different SDPs and that are separated by 1 cM or more, we use a conventional interval mapping method (Haley-Knott) combined with a Haldane estimate of genetic distance. When the interval is less than 1 cM, we simply interpolate linearly between markers based on a physical scale between those markers. The result of this mixture mapping algorithm is a linkage map of a trait that has an unusal profile that is particular striking on a physical (Mb) scale, with many plateaus, abrupt linear transitions between plateaus, and a few regions with the standard graceful curves typical of interval maps.
+
+Archival Genotypes:
+
+Archival BXD Genotype file: Prior to July 2005, the marker genotypes used to map all BXD data sets consisted of a set of 779 markers described by Williams and colleagues (2001) that also included a small number of additional SNPs from Tim Wiltshire and Mathew Pletcher (GNF, La Jolla), new microsatellite markers generated by Grant Morahan and Jing Gu (Msw type markers), and a few CTC markers by Jing Gu. This old marker data set was made obsolete by the ultra high density Illumina SNP genotype data generated Spring, 2005.
+
+Download Genotypes:
+
+The entire BXD genotype data set used for mapping traits can be downloaded at BXD.geno.
diff --git a/general/datasets/Bxdpublish/summary.rtf b/general/datasets/Bxdpublish/summary.rtf
new file mode 100644
index 0000000..5c22bc2
--- /dev/null
+++ b/general/datasets/Bxdpublish/summary.rtf
@@ -0,0 +1,40 @@
+Question: I have generated some phenotype data that I would like to put into GeneNetwork. How should I name my traits?
+
+Answer: Phenotype trait names in GeneNetwork should have this general form when possible:
+
+
+ - Your description should start with very short list of "approved" general category and ontology terms. These terms are used to subdivide the entire collection of phenotypes by system, organ, or level of analysis. Some examples may help: "Central nervous system", "Immune system", "Metabolism", "Development", or "Urogenital system". Capitalize this list as you would a standard English sentence. Separate terms by commas and then end the terms with a colon. For example, "Central nervous system, pharmacology, endocrinology:" is a valid set of three terms. These terms do not really describe your trait, but are used by you and other users to figure out how many traits there are in specific categories.
+
+ Before making up your own terms, please review the current terms in GeneNetwork and find some terms/ontology categories that look good to you. If you have questions contact one of us on the GeneNetwork development team.
+ - After the colon start with your description of the phenotype you have generated. For example: "Ethanol response..." or "Anxiety assay...", "Brain weight...". The first letter should almost always be capitalized.
+ - Do not start with a generic uninformative word such as "Mean", "Maximum", "Mechanical", "Count", "Number", "Difference", "Baseline", "Induction", "Decrease", "New", "Adjusted", "Distance", "Right", "Left", "Bilateral", "Time", "Total", "Percentage", "Percent". The reason is that the traits should be alphabetized and categorized in a conceptually useful way; not by something "dumb" like the "total" or "percent".
+ - Do not start with a specific instrumental assay such as "Morris water maze" or "Dowel test..." or "Porsolt test behavior". Many of these tests will be unknown to other users. Try to use a term that reflects the intent of the assay (Motor coordination test, Learning and memory assay, Allergic airway response). This may be difficult, particularly for tests such as the Porsolt swim test and the Morris water maze that measure aspects of many different traits (anxiety, activity level, spatial navigation, visual acuity etc). But in the interest of clarity of intent rather than precision of measurement, please follow this suggestion. The actual assay instrument can be listed after the primary and secondary trait descriptions.
+ - Many traits can be difficult to categorize in a consistent way. For example a trait such as "ventral midbrain copper level in males" could be labeled "copper level in the ventral midbrain." There is no right or wrong way to do this, but the convention should be to choose the order that you think will be most useful to other users in terms of comprehension and consistency with other existing phenotypes. Review related phenotypes before you start naming your own. You will find good and bad examples.
+ - Dose and route of drug delivery. If the phenotype is a pharmacological phenotype, whenever practical enter the doses and routes of injection in parentheses after the name of the general trait. For example, "Cocaine response (40 mg/kg ip)". We would prefer to use "ip" and "iv" rather than i.p. and i.v., but this is not a strong preference. If a protocol requires multiple treatments, please include them if possible. For example, "Cocaine response (3 x 3.2 mg/kg ip, Days 2, 3, 4),...").
+ - Series of more precise definitions of the phenotype and the subject(s) will often follow with commas used as separators. If possible make this understandable to almost any user, even at the risk of being wordy.
+
For example, "Cocaine response (3 x 3.2 mg/kg ip, Days 2, 3, and 4), conditioned place preference (CPP), change in time in cocaine-paired compartment relative to baseline (Day 5 minus Day 1) for 50 to 90-day-old males and females [sec]"
+
+ - Sex. If the data are for males please write out "in males" or "of male" or "for males". Do not just add a comma such as " , males" or "(M)". This should usually go at the end of the description.
+ - Age and condition of subjects can be added if you think it is essential or helpful. However, do not bother with a generic addition "adult" since that is what most users will reasonably assume. If you would like to add an age range then use this format "in 100 to 200-day-old males and females" or "of 3 to 4-month-old males".
+ - Mandatory units of measurement between square brackets [min] or [sec] or [n bream breaks/10 min test]. If you are using an ordinal scale, then describe the scale within the brackets. If the units are simply a ratio or percentage then use [ratio] or [%].
+
+
+Other advice on trait descriptions:
+
+
+ - Do Not Capitalize Each Word in a Description. (e.g, Ethanol Response, Distance traveled after saline - Distance traveled after ethanol for males and females [cm in a 0-5 min test period] )
+ - Do not use "-" as a minus sign. The dash is too confusing and may sometimes be used as a hyphen. Spell out "minus"
+ - No not use ALL CAP in a trait description (e.g., TOTAL)
+ - Do use commas when appropriate. For example, Morphine response severity of abdominal constriction for males needs a comma between "response" and "severity"
+ - Do not use extraneous words such as "time SPENT on rotarod". "time on rotarod" is good enough.
+ - Do not start with text or abbreviations that will not be understandable to all users, such as "RSS female and male..."
+ - Please us a space between a number and the units: Prepulse inhibition at 70 dB for females (not 70db). Please use the correct form of the abbreviation.
+ - Use American spelling. [RWW, September 10, 2009]
+
+
+Examples of accepted phenotype descriptions: (by Amelie Baud. Wellcome Trust Centre for Human Genetics, Oxford, UK.)
+
+
+ - Central nervous system, behavior: Anxiety assay, locomotor activity in novel cage between minutes 25 and 30 in novel cage, normalized by Box-Cox transformation [cm]
+ - Metabolism: Glycemia (intraperitoneal glucose tolerance test), area under the curve between minutes 0 and 120 after injection, normalized by Box-Cox transformation [mM.min-1]
+
diff --git a/general/datasets/CANDLE_Meth27_0313/platform.rtf b/general/datasets/CANDLE_Meth27_0313/platform.rtf
deleted file mode 100644
index 760018d..0000000
--- a/general/datasets/CANDLE_Meth27_0313/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Illumina Infinium HumanMethylation27 BeadChip
diff --git a/general/datasets/CANDLE_Meth27_0313/processing.rtf b/general/datasets/CANDLE_Meth27_0313/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/CANDLE_Meth27_0313/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/CANDLE_Meth_0313/platform.rtf b/general/datasets/CANDLE_Meth_0313/platform.rtf
deleted file mode 100644
index 760018d..0000000
--- a/general/datasets/CANDLE_Meth_0313/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Illumina Infinium HumanMethylation27 BeadChip
diff --git a/general/datasets/CANDLE_Meth_0313/processing.rtf b/general/datasets/CANDLE_Meth_0313/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/CANDLE_Meth_0313/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/CCGeno/cases.rtf b/general/datasets/CCGeno/cases.rtf
deleted file mode 100644
index 6159322..0000000
--- a/general/datasets/CCGeno/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Mice were bred by Dr. Klaus Schughart at the HZI, Braunschweig, Germany.
diff --git a/general/datasets/CCGeno/platform.rtf b/general/datasets/CCGeno/platform.rtf
deleted file mode 100644
index 0fa1383..0000000
--- a/general/datasets/CCGeno/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-MegaMUGA
diff --git a/general/datasets/CCGeno/specifics.rtf b/general/datasets/CCGeno/specifics.rtf
deleted file mode 100644
index 30efa6a..0000000
--- a/general/datasets/CCGeno/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Genotypes
\ No newline at end of file
diff --git a/general/datasets/CCGeno/summary.rtf b/general/datasets/CCGeno/summary.rtf
deleted file mode 100644
index 2533382..0000000
--- a/general/datasets/CCGeno/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Genotypes of 32 cc strains.
-
-Downloaded from http://csbio.unc.edu/CCstatus/CCGenomes/ and processed by Arthur Centeno and Zachary Sloan at the University of Tennessee.
-
-Team of Investigators:
-
-Lasse Sinkkkonen, Manuel Buttini, Yujuan Gui, and Melanie Thomas at the University of Luxembourg
-
-Data entered into GeneNetwork December 2019 by Arthur Centeno, Robert W. Williams, Yujuan Gui
diff --git a/general/datasets/CCGeno/tissue.rtf b/general/datasets/CCGeno/tissue.rtf
deleted file mode 100644
index b4ef238..0000000
--- a/general/datasets/CCGeno/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Ventral midbrain
diff --git a/general/datasets/CCPublish/acknowledgment.rtf b/general/datasets/CCPublish/acknowledgment.rtf
deleted file mode 100644
index c6129ca..0000000
--- a/general/datasets/CCPublish/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-LS and MB would like to thank the Luxembourg National Research Fund (FNR) for the support 663 (FNR CORE C15/BM/10406131 grant).
diff --git a/general/datasets/CCPublish/cases.rtf b/general/datasets/CCPublish/cases.rtf
deleted file mode 100644
index 4a36b15..0000000
--- a/general/datasets/CCPublish/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-CC mice were bred by Dr. Klaus Schughart at the HZI, Braunschweig, Germany.
-
-C57BL/6J, A/J, and DBA/2J were bred by University of Luxembourg
diff --git a/general/datasets/CCPublish/experiment-design.rtf b/general/datasets/CCPublish/experiment-design.rtf
deleted file mode 100644
index e0fbda8..0000000
--- a/general/datasets/CCPublish/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Gas chromatography-mass spectrometry (GC-MS), immunofluorescent staining, RT-PCR
diff --git a/general/datasets/CCPublish/specifics.rtf b/general/datasets/CCPublish/specifics.rtf
deleted file mode 100644
index fc3ed76..0000000
--- a/general/datasets/CCPublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-CC Phenotypes
\ No newline at end of file
diff --git a/general/datasets/CCPublish/summary.rtf b/general/datasets/CCPublish/summary.rtf
deleted file mode 100644
index d4904aa..0000000
--- a/general/datasets/CCPublish/summary.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-Dopamine concentration measurements [pmol/mg]: Dorsal striatums of 32 CC strains. Each strain has around 5 male and 5 female animals, 3-month old; Dorsal striatums
-
-Neuropathology: The dorsal striatum was sectioned and stained with TH or DAT. Two metrics were measured: mean grey value [mean grey value/image] and % area occupied [% area occupied/image]. Measurements were done on dorsal striatums of C57BL/6J, A/J and DBA/2J 3, 9, 15-month-old animals.
-
-RT-PCR: The total RNA was extracted from ventral midbrains and quantified by RT-PCR with markers Th, Dat, Vmat, Nr4a2, Sox6 and Otx2 [-delta Ct]. Measurements were done on dorsal striatums of C57BL/6J, A/J and DBA/2J 3, 9, 15-month-old animals.
-
-Team of Investigators:
-
-Lasse Sinkkkonen, Manuel Buttini, Yujuan Gui, and Melanie Thomas at the University of Luxembourg
-
-Data entered into GeneNetwork December 2019 by Arthur Centeno, Robert W. Williams, Yujuan Gui.
diff --git a/general/datasets/CCPublish/tissue.rtf b/general/datasets/CCPublish/tissue.rtf
deleted file mode 100644
index 9869ae6..0000000
--- a/general/datasets/CCPublish/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Dorsal Striatum, ventral midbrain
diff --git a/general/datasets/CMMTUBCBXDCerILM0513/summary.rtf b/general/datasets/CMMTUBCBXDCerILM0513/summary.rtf
deleted file mode 100644
index 751de1d..0000000
--- a/general/datasets/CMMTUBCBXDCerILM0513/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/CMMTUBCBXDG12CerILM0513/summary.rtf b/general/datasets/CMMTUBCBXDG12CerILM0513/summary.rtf
deleted file mode 100644
index 751de1d..0000000
--- a/general/datasets/CMMTUBCBXDG12CerILM0513/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/CMMTUBCBXDG15CerILM0513/summary.rtf b/general/datasets/CMMTUBCBXDG15CerILM0513/summary.rtf
deleted file mode 100644
index 751de1d..0000000
--- a/general/datasets/CMMTUBCBXDG15CerILM0513/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/CMMTUBCBXDG18CerILM0513/summary.rtf b/general/datasets/CMMTUBCBXDG18CerILM0513/summary.rtf
deleted file mode 100644
index 751de1d..0000000
--- a/general/datasets/CMMTUBCBXDG18CerILM0513/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/CMMTUBCBXDP03CerILM0513/summary.rtf b/general/datasets/CMMTUBCBXDP03CerILM0513/summary.rtf
deleted file mode 100644
index 751de1d..0000000
--- a/general/datasets/CMMTUBCBXDP03CerILM0513/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/CMMTUBCBXDP06CerILM0513/summary.rtf b/general/datasets/CMMTUBCBXDP06CerILM0513/summary.rtf
deleted file mode 100644
index 751de1d..0000000
--- a/general/datasets/CMMTUBCBXDP06CerILM0513/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/CMMTUBCBXDP09CerILM0513/summary.rtf b/general/datasets/CMMTUBCBXDP09CerILM0513/summary.rtf
deleted file mode 100644
index 751de1d..0000000
--- a/general/datasets/CMMTUBCBXDP09CerILM0513/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/CMS_Hipp1115/cases.rtf b/general/datasets/CMS_Hipp1115/cases.rtf
deleted file mode 100644
index c201f08..0000000
--- a/general/datasets/CMS_Hipp1115/cases.rtf
+++ /dev/null
@@ -1,992 +0,0 @@
-The original data set included four individuals of each strain under baseline (B) conditions and eight individuals from each strain for each of the treatment groups, chronic mild stress (C), acute restraint (R), and chronic mild stress followed by acute retraint (CR). However, some samples have been removed due to technical problems with tissue collection or microarray performance.
-
-
-
-
- | MTA_ID |
- MTA prefix |
- GN_ID |
- FM_ID |
- Mouse_ID |
- CaseId |
- Strain |
- Strain_Code |
- Treatment code |
- NanoDrop, ng/ul |
- NanoDrop, 260/280 |
- NanoDrop, 260/230 |
- Agilent, ng/µl |
- RIN |
- Notes |
-
-
- | 1 |
- BCJ 1.CMS_ |
- D-B-215-1 |
- CMS_000215 |
- 215 |
- 020615.01 |
- DBA/2J |
- D |
- B |
- 163.61 |
- 1.9 |
- 2.31 |
- 130 |
- 8.6 |
- |
-
-
- | 2 |
- BCJ 2.CMS_ |
- D-C-86-1 |
- CMS_000086 |
- 86 |
- 012115.23 |
- DBA/2J |
- D |
- C |
- 98.51 |
- 1.79 |
- 2.4 |
- 329 |
- 8.8 |
- |
-
-
- | 3 |
- BCJ 3.CMS_ |
- D-CR-94-1 |
- CMS_000094 |
- 94 |
- 012115.16 |
- DBA/2J |
- D |
- CR |
- 162.78 |
- 1.87 |
- 2.38 |
- 166 |
- 9.2 |
- |
-
-
- | 4 |
- BCJ 4.CMS_ |
- D-R-133-1 |
- CMS_000133 |
- 133 |
- 012115.14 |
- DBA/2J |
- D |
- R |
- 88.95 |
- 1.82 |
- 2.45 |
- 90 |
- 8.2 |
- |
-
-
- | 5 |
- BCJ 5.CMS_ |
- B-B-208-1 |
- CMS_000208 |
- 208 |
- 012215.04 |
- C57BL/6J |
- B |
- B |
- 129.24 |
- 1.86 |
- 2.41 |
- 223 |
- 8.1 |
- |
-
-
- | 6 |
- BCJ 6.CMS_ |
- B-C-101-1 |
- CMS_000101 |
- 101 |
- 012115.25 |
- C57BL/6J |
- B |
- C |
- 72.29 |
- 1.86 |
- 2.26 |
- 135 |
- 9.2 |
- |
-
-
- | 7 |
- BCJ 7.CMS_ |
- B-CR-109-1 |
- CMS_000109 |
- 109 |
- 012115.21 |
- C57BL/6J |
- B |
- CR |
- 158.56 |
- 1.7 |
- 2.46 |
- 305 |
- 8.8 |
- Microarray outlier; sample removed. |
-
-
- | 8 |
- BCJ 8.CMS_ |
- B-R-143-1 |
- CMS_000143 |
- 143 |
- 012215.08 |
- C57BL/6J |
- B |
- R |
- 161.57 |
- 1.86 |
- 2.38 |
- 217 |
- 9.3 |
- |
-
-
- | 9 |
- BCJ 9.CMS_ |
- N-B-210-1 |
- CMS_000210 |
- 210 |
- 012115.04 |
- C57BL/6NJ |
- N |
- B |
- 132.39 |
- 1.89 |
- 2.3 |
- 192 |
- 8.5 |
- |
-
-
- | 10 |
- BCJ 10.CMS_ |
- N-C-117-1 |
- CMS_000117 |
- 117 |
- 012115.30 |
- C57BL/6NJ |
- N |
- C |
- 151.43 |
- 1.91 |
- 2.38 |
- 187 |
- 8.8 |
- |
-
-
- | 11 |
- BCJ 11.CMS_ |
- N-CR-126-1 |
- CMS_000126 |
- 126 |
- 012115.33 |
- C57BL/6NJ |
- N |
- CR |
- 137.87 |
- 1.88 |
- 2.29 |
- 76 |
- 9 |
- |
-
-
- | 12 |
- BCJ 12.CMS_ |
- N-R-152-1 |
- CMS_000152 |
- 152 |
- 012215.29 |
- C57BL/6NJ |
- N |
- R |
- 197.95 |
- 1.88 |
- 2.35 |
- 150 |
- 9.1 |
- |
-
-
- | 13 |
- BCJ 13.CMS_ |
- D-B-216-1 |
- CMS_000216 |
- 216 |
- 020615.02 |
- DBA/2J |
- D |
- B |
- 98.64 |
- 1.91 |
- 2.03 |
- 60 |
- 8.6 |
- |
-
-
- | 15 |
- BCJ 15.CMS_ |
- D-CR-93-1 |
- CMS_000093 |
- 93 |
- 012115.11 |
- DBA/2J |
- D |
- CR |
- 71.36 |
- 1.83 |
- 2.25 |
- 109 |
- 8.5 |
- |
-
-
- | 16 |
- BCJ 16.CMS_ |
- D-R-134-1 |
- CMS_000134 |
- 134 |
- 012115.17 |
- DBA/2J |
- D |
- R |
- 73.49 |
- 1.85 |
- 2.43 |
- 149 |
- 8.2 |
- |
-
-
- | 17 |
- BCJ 17.CMS_ |
- B-B-205-1 |
- CMS_000205 |
- 205 |
- 012015.02 |
- C57BL/6J |
- B |
- B |
- 174.78 |
- 2.02 |
- 2.21 |
- 266 |
- 8.9 |
- |
-
-
- | 18 |
- BCJ 18.CMS_ |
- B-C-104-1 |
- CMS_000104 |
- 104 |
- 012215.30 |
- C57BL/6J |
- B |
- C |
- 84.7 |
- 2.64 |
- 2.01 |
- 168 |
- 9.2 |
- |
-
-
- | 19 |
- BCJ 19.CMS_ |
- B-CR-110-1 |
- CMS_000110 |
- 110 |
- 012115.26 |
- C57BL/6J |
- B |
- CR |
- 136.7 |
- 1.96 |
- 2.16 |
- 178 |
- 9.5 |
- |
-
-
- | 20 |
- BCJ 20.CMS_ |
- B-R-141-1 |
- CMS_000141 |
- 141 |
- 012115.22 |
- C57BL/6J |
- B |
- R |
- 86.04 |
- 20.2 |
- 2.53 |
- 208 |
- 8.9 |
- |
-
-
- | 21 |
- BCJ 21.CMS_ |
- N-B-209-1 |
- CMS_000209 |
- 209 |
- 012015.04 |
- C57BL/6NJ |
- N |
- B |
- 98.3 |
- 1.99 |
- 2.35 |
- 169 |
- 8.8 |
- |
-
-
- | 22 |
- BCJ 22.CMS_ |
- N-C-119-1 |
- CMS_000119 |
- 119 |
- 012215.18 |
- C57BL/6NJ |
- N |
- C |
- 94.63 |
- 1.96 |
- 2.36 |
- 179 |
- 8.5 |
- |
-
-
- | 24 |
- BCJ 24.CMS_ |
- N-R-150-1 |
- CMS_000150 |
- 150 |
- 012115.29 |
- C57BL/6NJ |
- N |
- R |
- 407.34 |
- 1.98 |
- 2.24 |
- 425 |
- 7.5 |
- Microarray outlier; sample removed. |
-
-
- | 25 |
- BCJ 25.CMS_ |
- D-B-217-1 |
- CMS_000217 |
- 217 |
- 020615.03 |
- DBA/2J |
- D |
- B |
- 84.61 |
- 1.82 |
- 2.18 |
- 177 |
- 7.9 |
- |
-
-
- | 26 |
- BCJ 26.CMS_ |
- D-C-85-1 |
- CMS_000085 |
- 85 |
- 012115.20 |
- DBA/2J |
- D |
- C |
- 172.86 |
- 1.98 |
- 2.27 |
- 288 |
- 8.9 |
- |
-
-
- | 27 |
- BCJ 27.CMS_ |
- D-CR-95-1 |
- CMS_000095 |
- 95 |
- 012215.16 |
- DBA/2J |
- D |
- CR |
- 109.8 |
- 1.98 |
- 2.47 |
- 157 |
- 8.9 |
- |
-
-
- | 28 |
- BCJ 28.CMS_ |
- D-R-132-1 |
- CMS_000132 |
- 132 |
- 012015.29 |
- DBA/2J |
- D |
- R |
- 140.82 |
- 1.91 |
- 2.47 |
- 318 |
- 9 |
- |
-
-
- | 29 |
- BCJ 29.CMS_ |
- B-B-207-1 |
- CMS_000207 |
- 207 |
- 012215.02 |
- C57BL/6J |
- B |
- B |
- 96.25 |
- 1.89 |
- 2.67 |
- 176 |
- 8.5 |
- |
-
-
- | 30 |
- BCJ 30.CMS_ |
- B-C-102-1 |
- CMS_000102 |
- 102 |
- 012115.28 |
- C57BL/6J |
- B |
- C |
- 129.69 |
- 1.89 |
- 2.32 |
- 105 |
- 8.7 |
- |
-
-
- | 31 |
- BCJ 31.CMS_ |
- B-CR-111-1 |
- CMS_000111 |
- 111 |
- 012215.26 |
- C57BL/6J |
- B |
- CR |
- 165.67 |
- 1.84 |
- 2.31 |
- 176 |
- 9.5 |
- |
-
-
- | 32 |
- BCJ 32.CMS_ |
- B-R-142-1 |
- CMS_000142 |
- 142 |
- 012115.24 |
- C57BL/6J |
- B |
- R |
- 116.93 |
- 1.84 |
- 2.22 |
- 96 |
- 9.4 |
- |
-
-
- | 33 |
- BCJ 33.CMS_ |
- N-B-211-1 |
- CMS_000211 |
- 211 |
- 012315.02 |
- C57BL/6NJ |
- N |
- B |
- 106 |
- 2.09 |
- 2.29 |
- 156 |
- 7.4 |
- |
-
-
- | 34 |
- BCJ 34.CMS_ |
- N-C-118-1 |
- CMS_000118 |
- 118 |
- 012115.32 |
- C57BL/6NJ |
- N |
- C |
- 219.2 |
- 1.91 |
- 2.34 |
- 197 |
- 9.2 |
- |
-
-
- | 35 |
- BCJ 35.CMS_ |
- N-CR-127-1 |
- CMS_000127 |
- 127 |
- 012215.33 |
- C57BL/6NJ |
- N |
- CR |
- 89 |
- 2 |
- 2.56 |
- 157 |
- 9.4 |
- |
-
-
- | 36 |
- BCJ 36.CMS_ |
- N-R-149-1 |
- CMS_000149 |
- 149 |
- 012115.27 |
- C57BL/6NJ |
- N |
- R |
- 72.91 |
- 1.84 |
- 2.14 |
- 107 |
- 8.6 |
- |
-
-
- | 37 |
- BCJ 37.CMS_ |
- D-B-218-1 |
- CMS_000218 |
- 218 |
- 020615.04 |
- DBA/2J |
- D |
- B |
- 154.34 |
- 1.99 |
- 1.99 |
- 119 |
- 9.3 |
- |
-
-
- | 38 |
- BCJ 38.CMS_ |
- D-C-87-1 |
- CMS_000087 |
- 87 |
- 012215.13 |
- DBA/2J |
- D |
- C |
- 105.3 |
- 1.98 |
- 2.21 |
- 109 |
- 7.4 |
- |
-
-
- | 39 |
- BCJ 39.CMS_ |
- D-CR-97-1 |
- CMS_000097 |
- 97 |
- 012315.05 |
- DBA/2J |
- D |
- CR |
- 55.85 |
- 1.89 |
- 2.41 |
- 85 |
- 8.3 |
- |
-
-
- | 40 |
- BCJ 40.CMS_ |
- D-R-137-1 |
- CMS_000137 |
- 137 |
- 012315.06 |
- DBA/2J |
- D |
- R |
- 128.97 |
- 2.01 |
- 2.24 |
- 159 |
- 8.1 |
- Microarray outlier; sample removed. |
-
-
- | 41 |
- BCJ 41.CMS_ |
- B-B-206-1 |
- CMS_000206 |
- 206 |
- 012115.02 |
- C57BL/6J |
- B |
- B |
- 159.89 |
- 2.03 |
- 2.1 |
- 273 |
- 7.8 |
- |
-
-
- | 42 |
- BCJ 42.CMS_ |
- B-C-103-1 |
- CMS_000103 |
- 103 |
- 012215.15 |
- C57BL/6J |
- B |
- C |
- 111.79 |
- 1.87 |
- 2.45 |
- 160 |
- 8.9 |
- |
-
-
- | 43 |
- BCJ 43.CMS_ |
- B-CR-112-1 |
- CMS_000112 |
- 112 |
- 012215.31 |
- C57BL/6J |
- B |
- CR |
- 172.14 |
- 1.86 |
- 2.22 |
- 180 |
- 9.4 |
- |
-
-
- | 44 |
- BCJ 44.CMS_ |
- B-R-145-1 |
- CMS_000145 |
- 145 |
- 012315.12 |
- C57BL/6J |
- B |
- R |
- 103.74 |
- 2.06 |
- 2.17 |
- 99 |
- 8.9 |
- |
-
-
- | 45 |
- BCJ 45.CMS_ |
- N-B-212-1 |
- CMS_000212 |
- 212 |
- 012315.04 |
- C57BL/6NJ |
- N |
- B |
- 189.5 |
- 1.9 |
- 2.4 |
- 248 |
- 8.5 |
- |
-
-
- | 47 |
- BCJ 47.CMS_ |
- N-CR-128-1 |
- CMS_000128 |
- 128 |
- 012215.34 |
- C57BL/6NJ |
- N |
- CR |
- 90.65 |
- 2.07 |
- 2.25 |
- 189 |
- 9.3 |
- |
-
-
- | 48 |
- BCJ 48.CMS_ |
- N-R-154-1 |
- CMS_000154 |
- 154 |
- 012315.29 |
- C57BL/6NJ |
- N |
- R |
- 114.73 |
- 1.94 |
- 2.34 |
- 167 |
- 8.8 |
- |
-
-
- | 49 |
- BCJ 49.CMS_ |
- D-C-88-1 |
- CMS_000088 |
- 88 |
- 012215.28 |
- DBA/2J |
- D |
- C |
- 96 |
- 1.76 |
- 2.55 |
- 158 |
- 8.5 |
- |
-
-
- | 50 |
- BCJ 50.CMS_ |
- D-CR-96-1 |
- CMS_000096 |
- 96 |
- 012215.21 |
- DBA/2J |
- D |
- CR |
- 133.66 |
- 1.78 |
- 2.36 |
- 203 |
- 8.3 |
- |
-
-
- | 51 |
- BCJ 51.CMS_ |
- D-R-138-1 |
- CMS_000138 |
- 138 |
- 012315.22 |
- DBA/2J |
- D |
- R |
- 127.13 |
- 1.76 |
- 2.24 |
- 81 |
- 9.3 |
- |
-
-
- | 52 |
- BCJ 52.CMS_ |
- B-C-105-1 |
- CMS_000105 |
- 105 |
- 012315.13 |
- C57BL/6J |
- B |
- C |
- 203.24 |
- 1.92 |
- 2.35 |
- 310 |
- 7 |
- |
-
-
- | 53 |
- BCJ 53.CMS_ |
- B-CR-113-1 |
- CMS_000113 |
- 113 |
- 012315.09 |
- C57BL/6J |
- B |
- CR |
- 168.67 |
- 1.82 |
- 2.41 |
- 240 |
- 9.1 |
- |
-
-
- | 55 |
- BCJ 55.CMS_ |
- N-C-120-1 |
- CMS_000120 |
- 120 |
- 012215.32 |
- C57BL/6NJ |
- N |
- C |
- 73.67 |
- 1.93 |
- 2.31 |
- 371 |
- 8.4 |
- |
-
-
- | 56 |
- BCJ 56.CMS_ |
- N-CR-125-1 |
- CMS_000125 |
- 125 |
- 012115.31 |
- C57BL/6NJ |
- N |
- CR |
- 121.93 |
- 1.92 |
- 2.26 |
- 73 |
- 8.3 |
- |
-
-
- | 59 |
- BCJ 59.CMS_ |
- N-C-122-1 |
- CMS_000122 |
- 122 |
- 012315.30 |
- C57BL/6NJ |
- N |
- C |
- 131.74 |
- 1.85 |
- 2.42 |
- 186 |
- 9.4 |
- |
-
-
- | 60 |
- BCJ 60.CMS_ |
- D-C-89-1 |
- CMS_000089 |
- 89 |
- 012315.10 |
- DBA/2J |
- D |
- C |
- 78 |
- 1.77 |
- 2.32 |
- 74 |
- 8.9 |
- |
-
-
- | 62 |
- BCJ 62.CMS_ |
- N-CR-130-1 |
- CMS_000130 |
- 130 |
- 012315.34 |
- C57BL/6NJ |
- N |
- CR |
- 100.74 |
- 1.71 |
- 2.36 |
- 113 |
- 8.8 |
- |
-
-
- | 65 |
- BCJ 65.CMS_ |
- B-R-144-1 |
- CMS_000144 |
- 144 |
- 012215.27 |
- C57BL/6J |
- B |
- R |
- 80.1 |
- 1.81 |
- 2.3 |
- 95 |
- 8.9 |
- |
-
-
- | 66 |
- BCJ 66.CMS_ |
- N-R-151-1 |
- CMS_000151 |
- 151 |
- 012215.12 |
- C57BL/6NJ |
- N |
- R |
- 80.22 |
- 1.77 |
- 2.2 |
- 116 |
- 8.6 |
- |
-
-
-
diff --git a/general/datasets/CMS_Hipp1115/experiment-design.rtf b/general/datasets/CMS_Hipp1115/experiment-design.rtf
deleted file mode 100644
index f2d6c93..0000000
--- a/general/datasets/CMS_Hipp1115/experiment-design.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-This data set includes four experimental conditions, B (baseline, untreated), C (chronic mild stress), CR (chronic mild stress followed by acute restraint), and R (acute restraint only).
-
-B = untreated
-
-C = 7 weeks of chronic unpredictable stress
-
-R = 30 minutes of restraint
-
-CR = 7 weeks of chronic unpredictable stress followed by 30 minutes of restraint
diff --git a/general/datasets/CMS_Hipp1115/processing.rtf b/general/datasets/CMS_Hipp1115/processing.rtf
deleted file mode 100644
index 1b6ca30..0000000
--- a/general/datasets/CMS_Hipp1115/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Outlier Detection. Samples 7 (J-CR-21), 24 (N-R-29), and 40 (D-R-6) were detected as outliers and have abnormal expression profiles (i.e. they do not cluster with other samples and have abnormal median and quartile ranges after normalization. These samples have been removed from the analysis.
-
-RMA Algorithm. The Robust Multichip Analysis (RMA) algorithm fits a robust linear model at the probe level to minimize the effect of probe-specific affinity differences. This approach: n Increases sensitivity to small changes between experiment and control samples. n Minimizes variance across the dynamic range, but does compress calculated fold change values. RMA consists of three steps: 1. Background adjustment 2. Quantile normalization 3. Summarization This is a multi-chip analysis approach. Therefore, all arrays intended for comparison should be included together in the summarization step. For a more detailed description of the RMA algorithm, see the publication, Exploration, Normalization, and Summaries of High Density Oligonucleotide Array Probe Level Data, Biostatistics, April 2003; Vol. 4; Number 2: 249–264.
diff --git a/general/datasets/CMS_Hipp1115/summary.rtf b/general/datasets/CMS_Hipp1115/summary.rtf
deleted file mode 100644
index 1fededf..0000000
--- a/general/datasets/CMS_Hipp1115/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set was generated to study the effects of strain and stress on hippocampal gene expression in female mice. The data set includes three inbred strains of mice and four treatment groups.
diff --git a/general/datasets/CMS_Hipp1115/tissue.rtf b/general/datasets/CMS_Hipp1115/tissue.rtf
deleted file mode 100644
index 25b50be..0000000
--- a/general/datasets/CMS_Hipp1115/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set includes expression data from mouse hippocampus.
diff --git a/general/datasets/CMS_Hipp_ZScr_1115/cases.rtf b/general/datasets/CMS_Hipp_ZScr_1115/cases.rtf
deleted file mode 100644
index c201f08..0000000
--- a/general/datasets/CMS_Hipp_ZScr_1115/cases.rtf
+++ /dev/null
@@ -1,992 +0,0 @@
-The original data set included four individuals of each strain under baseline (B) conditions and eight individuals from each strain for each of the treatment groups, chronic mild stress (C), acute restraint (R), and chronic mild stress followed by acute retraint (CR). However, some samples have been removed due to technical problems with tissue collection or microarray performance.
-
-
-
-
- | MTA_ID |
- MTA prefix |
- GN_ID |
- FM_ID |
- Mouse_ID |
- CaseId |
- Strain |
- Strain_Code |
- Treatment code |
- NanoDrop, ng/ul |
- NanoDrop, 260/280 |
- NanoDrop, 260/230 |
- Agilent, ng/µl |
- RIN |
- Notes |
-
-
- | 1 |
- BCJ 1.CMS_ |
- D-B-215-1 |
- CMS_000215 |
- 215 |
- 020615.01 |
- DBA/2J |
- D |
- B |
- 163.61 |
- 1.9 |
- 2.31 |
- 130 |
- 8.6 |
- |
-
-
- | 2 |
- BCJ 2.CMS_ |
- D-C-86-1 |
- CMS_000086 |
- 86 |
- 012115.23 |
- DBA/2J |
- D |
- C |
- 98.51 |
- 1.79 |
- 2.4 |
- 329 |
- 8.8 |
- |
-
-
- | 3 |
- BCJ 3.CMS_ |
- D-CR-94-1 |
- CMS_000094 |
- 94 |
- 012115.16 |
- DBA/2J |
- D |
- CR |
- 162.78 |
- 1.87 |
- 2.38 |
- 166 |
- 9.2 |
- |
-
-
- | 4 |
- BCJ 4.CMS_ |
- D-R-133-1 |
- CMS_000133 |
- 133 |
- 012115.14 |
- DBA/2J |
- D |
- R |
- 88.95 |
- 1.82 |
- 2.45 |
- 90 |
- 8.2 |
- |
-
-
- | 5 |
- BCJ 5.CMS_ |
- B-B-208-1 |
- CMS_000208 |
- 208 |
- 012215.04 |
- C57BL/6J |
- B |
- B |
- 129.24 |
- 1.86 |
- 2.41 |
- 223 |
- 8.1 |
- |
-
-
- | 6 |
- BCJ 6.CMS_ |
- B-C-101-1 |
- CMS_000101 |
- 101 |
- 012115.25 |
- C57BL/6J |
- B |
- C |
- 72.29 |
- 1.86 |
- 2.26 |
- 135 |
- 9.2 |
- |
-
-
- | 7 |
- BCJ 7.CMS_ |
- B-CR-109-1 |
- CMS_000109 |
- 109 |
- 012115.21 |
- C57BL/6J |
- B |
- CR |
- 158.56 |
- 1.7 |
- 2.46 |
- 305 |
- 8.8 |
- Microarray outlier; sample removed. |
-
-
- | 8 |
- BCJ 8.CMS_ |
- B-R-143-1 |
- CMS_000143 |
- 143 |
- 012215.08 |
- C57BL/6J |
- B |
- R |
- 161.57 |
- 1.86 |
- 2.38 |
- 217 |
- 9.3 |
- |
-
-
- | 9 |
- BCJ 9.CMS_ |
- N-B-210-1 |
- CMS_000210 |
- 210 |
- 012115.04 |
- C57BL/6NJ |
- N |
- B |
- 132.39 |
- 1.89 |
- 2.3 |
- 192 |
- 8.5 |
- |
-
-
- | 10 |
- BCJ 10.CMS_ |
- N-C-117-1 |
- CMS_000117 |
- 117 |
- 012115.30 |
- C57BL/6NJ |
- N |
- C |
- 151.43 |
- 1.91 |
- 2.38 |
- 187 |
- 8.8 |
- |
-
-
- | 11 |
- BCJ 11.CMS_ |
- N-CR-126-1 |
- CMS_000126 |
- 126 |
- 012115.33 |
- C57BL/6NJ |
- N |
- CR |
- 137.87 |
- 1.88 |
- 2.29 |
- 76 |
- 9 |
- |
-
-
- | 12 |
- BCJ 12.CMS_ |
- N-R-152-1 |
- CMS_000152 |
- 152 |
- 012215.29 |
- C57BL/6NJ |
- N |
- R |
- 197.95 |
- 1.88 |
- 2.35 |
- 150 |
- 9.1 |
- |
-
-
- | 13 |
- BCJ 13.CMS_ |
- D-B-216-1 |
- CMS_000216 |
- 216 |
- 020615.02 |
- DBA/2J |
- D |
- B |
- 98.64 |
- 1.91 |
- 2.03 |
- 60 |
- 8.6 |
- |
-
-
- | 15 |
- BCJ 15.CMS_ |
- D-CR-93-1 |
- CMS_000093 |
- 93 |
- 012115.11 |
- DBA/2J |
- D |
- CR |
- 71.36 |
- 1.83 |
- 2.25 |
- 109 |
- 8.5 |
- |
-
-
- | 16 |
- BCJ 16.CMS_ |
- D-R-134-1 |
- CMS_000134 |
- 134 |
- 012115.17 |
- DBA/2J |
- D |
- R |
- 73.49 |
- 1.85 |
- 2.43 |
- 149 |
- 8.2 |
- |
-
-
- | 17 |
- BCJ 17.CMS_ |
- B-B-205-1 |
- CMS_000205 |
- 205 |
- 012015.02 |
- C57BL/6J |
- B |
- B |
- 174.78 |
- 2.02 |
- 2.21 |
- 266 |
- 8.9 |
- |
-
-
- | 18 |
- BCJ 18.CMS_ |
- B-C-104-1 |
- CMS_000104 |
- 104 |
- 012215.30 |
- C57BL/6J |
- B |
- C |
- 84.7 |
- 2.64 |
- 2.01 |
- 168 |
- 9.2 |
- |
-
-
- | 19 |
- BCJ 19.CMS_ |
- B-CR-110-1 |
- CMS_000110 |
- 110 |
- 012115.26 |
- C57BL/6J |
- B |
- CR |
- 136.7 |
- 1.96 |
- 2.16 |
- 178 |
- 9.5 |
- |
-
-
- | 20 |
- BCJ 20.CMS_ |
- B-R-141-1 |
- CMS_000141 |
- 141 |
- 012115.22 |
- C57BL/6J |
- B |
- R |
- 86.04 |
- 20.2 |
- 2.53 |
- 208 |
- 8.9 |
- |
-
-
- | 21 |
- BCJ 21.CMS_ |
- N-B-209-1 |
- CMS_000209 |
- 209 |
- 012015.04 |
- C57BL/6NJ |
- N |
- B |
- 98.3 |
- 1.99 |
- 2.35 |
- 169 |
- 8.8 |
- |
-
-
- | 22 |
- BCJ 22.CMS_ |
- N-C-119-1 |
- CMS_000119 |
- 119 |
- 012215.18 |
- C57BL/6NJ |
- N |
- C |
- 94.63 |
- 1.96 |
- 2.36 |
- 179 |
- 8.5 |
- |
-
-
- | 24 |
- BCJ 24.CMS_ |
- N-R-150-1 |
- CMS_000150 |
- 150 |
- 012115.29 |
- C57BL/6NJ |
- N |
- R |
- 407.34 |
- 1.98 |
- 2.24 |
- 425 |
- 7.5 |
- Microarray outlier; sample removed. |
-
-
- | 25 |
- BCJ 25.CMS_ |
- D-B-217-1 |
- CMS_000217 |
- 217 |
- 020615.03 |
- DBA/2J |
- D |
- B |
- 84.61 |
- 1.82 |
- 2.18 |
- 177 |
- 7.9 |
- |
-
-
- | 26 |
- BCJ 26.CMS_ |
- D-C-85-1 |
- CMS_000085 |
- 85 |
- 012115.20 |
- DBA/2J |
- D |
- C |
- 172.86 |
- 1.98 |
- 2.27 |
- 288 |
- 8.9 |
- |
-
-
- | 27 |
- BCJ 27.CMS_ |
- D-CR-95-1 |
- CMS_000095 |
- 95 |
- 012215.16 |
- DBA/2J |
- D |
- CR |
- 109.8 |
- 1.98 |
- 2.47 |
- 157 |
- 8.9 |
- |
-
-
- | 28 |
- BCJ 28.CMS_ |
- D-R-132-1 |
- CMS_000132 |
- 132 |
- 012015.29 |
- DBA/2J |
- D |
- R |
- 140.82 |
- 1.91 |
- 2.47 |
- 318 |
- 9 |
- |
-
-
- | 29 |
- BCJ 29.CMS_ |
- B-B-207-1 |
- CMS_000207 |
- 207 |
- 012215.02 |
- C57BL/6J |
- B |
- B |
- 96.25 |
- 1.89 |
- 2.67 |
- 176 |
- 8.5 |
- |
-
-
- | 30 |
- BCJ 30.CMS_ |
- B-C-102-1 |
- CMS_000102 |
- 102 |
- 012115.28 |
- C57BL/6J |
- B |
- C |
- 129.69 |
- 1.89 |
- 2.32 |
- 105 |
- 8.7 |
- |
-
-
- | 31 |
- BCJ 31.CMS_ |
- B-CR-111-1 |
- CMS_000111 |
- 111 |
- 012215.26 |
- C57BL/6J |
- B |
- CR |
- 165.67 |
- 1.84 |
- 2.31 |
- 176 |
- 9.5 |
- |
-
-
- | 32 |
- BCJ 32.CMS_ |
- B-R-142-1 |
- CMS_000142 |
- 142 |
- 012115.24 |
- C57BL/6J |
- B |
- R |
- 116.93 |
- 1.84 |
- 2.22 |
- 96 |
- 9.4 |
- |
-
-
- | 33 |
- BCJ 33.CMS_ |
- N-B-211-1 |
- CMS_000211 |
- 211 |
- 012315.02 |
- C57BL/6NJ |
- N |
- B |
- 106 |
- 2.09 |
- 2.29 |
- 156 |
- 7.4 |
- |
-
-
- | 34 |
- BCJ 34.CMS_ |
- N-C-118-1 |
- CMS_000118 |
- 118 |
- 012115.32 |
- C57BL/6NJ |
- N |
- C |
- 219.2 |
- 1.91 |
- 2.34 |
- 197 |
- 9.2 |
- |
-
-
- | 35 |
- BCJ 35.CMS_ |
- N-CR-127-1 |
- CMS_000127 |
- 127 |
- 012215.33 |
- C57BL/6NJ |
- N |
- CR |
- 89 |
- 2 |
- 2.56 |
- 157 |
- 9.4 |
- |
-
-
- | 36 |
- BCJ 36.CMS_ |
- N-R-149-1 |
- CMS_000149 |
- 149 |
- 012115.27 |
- C57BL/6NJ |
- N |
- R |
- 72.91 |
- 1.84 |
- 2.14 |
- 107 |
- 8.6 |
- |
-
-
- | 37 |
- BCJ 37.CMS_ |
- D-B-218-1 |
- CMS_000218 |
- 218 |
- 020615.04 |
- DBA/2J |
- D |
- B |
- 154.34 |
- 1.99 |
- 1.99 |
- 119 |
- 9.3 |
- |
-
-
- | 38 |
- BCJ 38.CMS_ |
- D-C-87-1 |
- CMS_000087 |
- 87 |
- 012215.13 |
- DBA/2J |
- D |
- C |
- 105.3 |
- 1.98 |
- 2.21 |
- 109 |
- 7.4 |
- |
-
-
- | 39 |
- BCJ 39.CMS_ |
- D-CR-97-1 |
- CMS_000097 |
- 97 |
- 012315.05 |
- DBA/2J |
- D |
- CR |
- 55.85 |
- 1.89 |
- 2.41 |
- 85 |
- 8.3 |
- |
-
-
- | 40 |
- BCJ 40.CMS_ |
- D-R-137-1 |
- CMS_000137 |
- 137 |
- 012315.06 |
- DBA/2J |
- D |
- R |
- 128.97 |
- 2.01 |
- 2.24 |
- 159 |
- 8.1 |
- Microarray outlier; sample removed. |
-
-
- | 41 |
- BCJ 41.CMS_ |
- B-B-206-1 |
- CMS_000206 |
- 206 |
- 012115.02 |
- C57BL/6J |
- B |
- B |
- 159.89 |
- 2.03 |
- 2.1 |
- 273 |
- 7.8 |
- |
-
-
- | 42 |
- BCJ 42.CMS_ |
- B-C-103-1 |
- CMS_000103 |
- 103 |
- 012215.15 |
- C57BL/6J |
- B |
- C |
- 111.79 |
- 1.87 |
- 2.45 |
- 160 |
- 8.9 |
- |
-
-
- | 43 |
- BCJ 43.CMS_ |
- B-CR-112-1 |
- CMS_000112 |
- 112 |
- 012215.31 |
- C57BL/6J |
- B |
- CR |
- 172.14 |
- 1.86 |
- 2.22 |
- 180 |
- 9.4 |
- |
-
-
- | 44 |
- BCJ 44.CMS_ |
- B-R-145-1 |
- CMS_000145 |
- 145 |
- 012315.12 |
- C57BL/6J |
- B |
- R |
- 103.74 |
- 2.06 |
- 2.17 |
- 99 |
- 8.9 |
- |
-
-
- | 45 |
- BCJ 45.CMS_ |
- N-B-212-1 |
- CMS_000212 |
- 212 |
- 012315.04 |
- C57BL/6NJ |
- N |
- B |
- 189.5 |
- 1.9 |
- 2.4 |
- 248 |
- 8.5 |
- |
-
-
- | 47 |
- BCJ 47.CMS_ |
- N-CR-128-1 |
- CMS_000128 |
- 128 |
- 012215.34 |
- C57BL/6NJ |
- N |
- CR |
- 90.65 |
- 2.07 |
- 2.25 |
- 189 |
- 9.3 |
- |
-
-
- | 48 |
- BCJ 48.CMS_ |
- N-R-154-1 |
- CMS_000154 |
- 154 |
- 012315.29 |
- C57BL/6NJ |
- N |
- R |
- 114.73 |
- 1.94 |
- 2.34 |
- 167 |
- 8.8 |
- |
-
-
- | 49 |
- BCJ 49.CMS_ |
- D-C-88-1 |
- CMS_000088 |
- 88 |
- 012215.28 |
- DBA/2J |
- D |
- C |
- 96 |
- 1.76 |
- 2.55 |
- 158 |
- 8.5 |
- |
-
-
- | 50 |
- BCJ 50.CMS_ |
- D-CR-96-1 |
- CMS_000096 |
- 96 |
- 012215.21 |
- DBA/2J |
- D |
- CR |
- 133.66 |
- 1.78 |
- 2.36 |
- 203 |
- 8.3 |
- |
-
-
- | 51 |
- BCJ 51.CMS_ |
- D-R-138-1 |
- CMS_000138 |
- 138 |
- 012315.22 |
- DBA/2J |
- D |
- R |
- 127.13 |
- 1.76 |
- 2.24 |
- 81 |
- 9.3 |
- |
-
-
- | 52 |
- BCJ 52.CMS_ |
- B-C-105-1 |
- CMS_000105 |
- 105 |
- 012315.13 |
- C57BL/6J |
- B |
- C |
- 203.24 |
- 1.92 |
- 2.35 |
- 310 |
- 7 |
- |
-
-
- | 53 |
- BCJ 53.CMS_ |
- B-CR-113-1 |
- CMS_000113 |
- 113 |
- 012315.09 |
- C57BL/6J |
- B |
- CR |
- 168.67 |
- 1.82 |
- 2.41 |
- 240 |
- 9.1 |
- |
-
-
- | 55 |
- BCJ 55.CMS_ |
- N-C-120-1 |
- CMS_000120 |
- 120 |
- 012215.32 |
- C57BL/6NJ |
- N |
- C |
- 73.67 |
- 1.93 |
- 2.31 |
- 371 |
- 8.4 |
- |
-
-
- | 56 |
- BCJ 56.CMS_ |
- N-CR-125-1 |
- CMS_000125 |
- 125 |
- 012115.31 |
- C57BL/6NJ |
- N |
- CR |
- 121.93 |
- 1.92 |
- 2.26 |
- 73 |
- 8.3 |
- |
-
-
- | 59 |
- BCJ 59.CMS_ |
- N-C-122-1 |
- CMS_000122 |
- 122 |
- 012315.30 |
- C57BL/6NJ |
- N |
- C |
- 131.74 |
- 1.85 |
- 2.42 |
- 186 |
- 9.4 |
- |
-
-
- | 60 |
- BCJ 60.CMS_ |
- D-C-89-1 |
- CMS_000089 |
- 89 |
- 012315.10 |
- DBA/2J |
- D |
- C |
- 78 |
- 1.77 |
- 2.32 |
- 74 |
- 8.9 |
- |
-
-
- | 62 |
- BCJ 62.CMS_ |
- N-CR-130-1 |
- CMS_000130 |
- 130 |
- 012315.34 |
- C57BL/6NJ |
- N |
- CR |
- 100.74 |
- 1.71 |
- 2.36 |
- 113 |
- 8.8 |
- |
-
-
- | 65 |
- BCJ 65.CMS_ |
- B-R-144-1 |
- CMS_000144 |
- 144 |
- 012215.27 |
- C57BL/6J |
- B |
- R |
- 80.1 |
- 1.81 |
- 2.3 |
- 95 |
- 8.9 |
- |
-
-
- | 66 |
- BCJ 66.CMS_ |
- N-R-151-1 |
- CMS_000151 |
- 151 |
- 012215.12 |
- C57BL/6NJ |
- N |
- R |
- 80.22 |
- 1.77 |
- 2.2 |
- 116 |
- 8.6 |
- |
-
-
-
diff --git a/general/datasets/CMS_Hipp_ZScr_1115/experiment-design.rtf b/general/datasets/CMS_Hipp_ZScr_1115/experiment-design.rtf
deleted file mode 100644
index f2d6c93..0000000
--- a/general/datasets/CMS_Hipp_ZScr_1115/experiment-design.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-This data set includes four experimental conditions, B (baseline, untreated), C (chronic mild stress), CR (chronic mild stress followed by acute restraint), and R (acute restraint only).
-
-B = untreated
-
-C = 7 weeks of chronic unpredictable stress
-
-R = 30 minutes of restraint
-
-CR = 7 weeks of chronic unpredictable stress followed by 30 minutes of restraint
diff --git a/general/datasets/CMS_Hipp_ZScr_1115/processing.rtf b/general/datasets/CMS_Hipp_ZScr_1115/processing.rtf
deleted file mode 100644
index 1b6ca30..0000000
--- a/general/datasets/CMS_Hipp_ZScr_1115/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Outlier Detection. Samples 7 (J-CR-21), 24 (N-R-29), and 40 (D-R-6) were detected as outliers and have abnormal expression profiles (i.e. they do not cluster with other samples and have abnormal median and quartile ranges after normalization. These samples have been removed from the analysis.
-
-RMA Algorithm. The Robust Multichip Analysis (RMA) algorithm fits a robust linear model at the probe level to minimize the effect of probe-specific affinity differences. This approach: n Increases sensitivity to small changes between experiment and control samples. n Minimizes variance across the dynamic range, but does compress calculated fold change values. RMA consists of three steps: 1. Background adjustment 2. Quantile normalization 3. Summarization This is a multi-chip analysis approach. Therefore, all arrays intended for comparison should be included together in the summarization step. For a more detailed description of the RMA algorithm, see the publication, Exploration, Normalization, and Summaries of High Density Oligonucleotide Array Probe Level Data, Biostatistics, April 2003; Vol. 4; Number 2: 249–264.
diff --git a/general/datasets/CMS_Hipp_ZScr_1115/specifics.rtf b/general/datasets/CMS_Hipp_ZScr_1115/specifics.rtf
deleted file mode 100644
index 5d45792..0000000
--- a/general/datasets/CMS_Hipp_ZScr_1115/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Z-Score. In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/CMS_Hipp_ZScr_1115/summary.rtf b/general/datasets/CMS_Hipp_ZScr_1115/summary.rtf
deleted file mode 100644
index 1fededf..0000000
--- a/general/datasets/CMS_Hipp_ZScr_1115/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set was generated to study the effects of strain and stress on hippocampal gene expression in female mice. The data set includes three inbred strains of mice and four treatment groups.
diff --git a/general/datasets/CMS_Hipp_ZScr_1115/tissue.rtf b/general/datasets/CMS_Hipp_ZScr_1115/tissue.rtf
deleted file mode 100644
index 25b50be..0000000
--- a/general/datasets/CMS_Hipp_ZScr_1115/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set includes expression data from mouse hippocampus.
diff --git a/general/datasets/CRTD_HipPreCell1214/acknowledgment.rtf b/general/datasets/CRTD_HipPreCell1214/acknowledgment.rtf
deleted file mode 100644
index 71728a6..0000000
--- a/general/datasets/CRTD_HipPreCell1214/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Financial support covering the breeding and supply of BXD mice was provided by the Helmholtz Virtual Institute GENESYS (German Network of Systems Genetics, VH-VI-242)
diff --git a/general/datasets/CRTD_HipPreCell1214/cases.rtf b/general/datasets/CRTD_HipPreCell1214/cases.rtf
deleted file mode 100644
index 8116156..0000000
--- a/general/datasets/CRTD_HipPreCell1214/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 8 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 10 inbred (F20+) BXD lines generated by Lu and Peirce. In addition, the parental strains C57BL/6J and DBA/2J were used to yield a total of 20 genetically unique cell lines. All of these strains have been genotyped at 13,377 SNPs.
diff --git a/general/datasets/CRTD_HipPreCell1214/experiment-design.rtf b/general/datasets/CRTD_HipPreCell1214/experiment-design.rtf
deleted file mode 100644
index c266448..0000000
--- a/general/datasets/CRTD_HipPreCell1214/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Each culture was derived from between 6 and 12 mice of c. 6 weeks old and of mixed sexes. Sex ratios in each batch varied. Triplicate cultures, from the same line but of different passage numbers, were used for RNA collection. Quantile normalisation of probe-level values was performed, and data for all probes mapping to the same Entrez GeneID were merged as means. No further adjustment of the data was done.
diff --git a/general/datasets/CRTD_HipPreCell1214/notes.rtf b/general/datasets/CRTD_HipPreCell1214/notes.rtf
deleted file mode 100644
index f2b1272..0000000
--- a/general/datasets/CRTD_HipPreCell1214/notes.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-This study is associated with the following records from the BXD Phenotype Database:
-
-17347, 17348, 17349
diff --git a/general/datasets/CRTD_HipPreCell1214/platform.rtf b/general/datasets/CRTD_HipPreCell1214/platform.rtf
deleted file mode 100644
index bbe0b51..0000000
--- a/general/datasets/CRTD_HipPreCell1214/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Illumina MouseWG-6 array with custom probe mapping: This data set uses a custom mapping of probes to Entrez GeneIDs. Each probe sequence on the MouseWG-6 v. 2.0 array was queried against the mm9 mouse genome using Jim Kent's BLAT program. The genomic position of probes returning a single hit was then used to assign the probe to an NCBI Entrez GeneID. Probes targeting the same GeneID were collapsed as means to yield data for 21155 unique genes.
diff --git a/general/datasets/CRTD_HipPreCell1214/processing.rtf b/general/datasets/CRTD_HipPreCell1214/processing.rtf
deleted file mode 100644
index 51df24a..0000000
--- a/general/datasets/CRTD_HipPreCell1214/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Raw data were preprocessed with quantile normalisation in R/Bioconductor using the package beadarray. After probe reannotation, data from probes targeting the same GeneID were collapsed as means. This results in a single unique probe set associated with each of the Entrez GeneIDs covered.
diff --git a/general/datasets/CRTD_HipPreCell1214/summary.rtf b/general/datasets/CRTD_HipPreCell1214/summary.rtf
deleted file mode 100644
index be648f2..0000000
--- a/general/datasets/CRTD_HipPreCell1214/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set was generated from proliferating adherent cultures of adult hippocampus-derived precursor cells from 20 BXD strains. The dentate gyrus of the mouse hippocampus is the site of continued neural precursor proliferation and generation of new neurons in adulthood as a distinct process from the widespread embryonic and juvenile neurogenesis during development. Adult-derived precursors can be isolated and maintained in adherent culture (Babu et al., 2007, 2011) and can be differentiated into neurons, astrocytes and oligodendrocytes. In this study, cultures were established from 20 BXD strains obtained through the authors’ involvement in the GeNeSys Consortium. This data set was obtained from cultures actively proliferating in the presence of growth factors.
diff --git a/general/datasets/CRTD_HipPreCell1214/tissue.rtf b/general/datasets/CRTD_HipPreCell1214/tissue.rtf
deleted file mode 100644
index f45211e..0000000
--- a/general/datasets/CRTD_HipPreCell1214/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The mice used in this study were bred at Harlan () for the GeNeSys Consortium and were delivered to the study site in Dresden at c. 6 weeks of age. Some animals were the 1st generation offspring of the Harlan stock which were bred and raised locally at the CRTD (housed at the Medizinisch-Theoretisches Zentrum of the Technische Universität Dresden). Animals were killed the day after delivery (or at 6 weeks of age if locally bred) and the hippocampi dissected and processed for precursor cell culture (Babu et al., 2011). Proliferating cultures were maintained in the presence of EGF and FGF-2 and passaged every 3-4 days. For microarray analysis, c. 1 million cells were harvested by on-plate lysis and total RNA prepared using the RNEasy mini kit (Qiagen) following the manufacturer’s protocol (including optional on-column DNase treatment). Each strain was assayed in triplicate (from 3 different passages).
diff --git a/general/datasets/CUBr_rna_0219/experiment-design.rtf b/general/datasets/CUBr_rna_0219/experiment-design.rtf
deleted file mode 100644
index 8ba40f7..0000000
--- a/general/datasets/CUBr_rna_0219/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset includes small RNA NGS sequencing data from 59 strains from the Inbred Long Sleep (ILS) and Inbred Short Sleep (ISS) Recombinant inbred mouse whole brain RNA samples. 175 mice (2-3 from each strain) were untreated (naive). The naive samples were provided by Boris Tabakoff, University of Colorado Anschutz Medical Campus. All expression data generation and analysis were conducted by the Kechris Group, University of Colorado Anschutz Medical Campus.
diff --git a/general/datasets/CUBr_rna_0219/notes.rtf b/general/datasets/CUBr_rna_0219/notes.rtf
deleted file mode 100644
index 84096b8..0000000
--- a/general/datasets/CUBr_rna_0219/notes.rtf
+++ /dev/null
@@ -1 +0,0 @@
-miRNA expression variance stabilized
diff --git a/general/datasets/CUBr_rna_0219/specifics.rtf b/general/datasets/CUBr_rna_0219/specifics.rtf
deleted file mode 100644
index d301f7e..0000000
--- a/general/datasets/CUBr_rna_0219/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-based on ens_mirna_expression_variance_stabilized
\ No newline at end of file
diff --git a/general/datasets/CUBr_rna_0219/summary.rtf b/general/datasets/CUBr_rna_0219/summary.rtf
deleted file mode 100644
index 57e5529..0000000
--- a/general/datasets/CUBr_rna_0219/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We conducted a high-throughput sequencing study to measure whole brain miRNA expression levels in alcohol naïve animals in the LXS panel of recombinant inbred (RI) mouse strains. We then combined the sequencing data with genotype data, microarray gene expression data, and data on alcohol-related behavioral phenotypes such as 'Drinking in the dark', 'Sleep time', and 'Low dose activation' from the same RI panel.
diff --git a/general/datasets/Candle_meth27_0313/platform.rtf b/general/datasets/Candle_meth27_0313/platform.rtf
new file mode 100644
index 0000000..760018d
--- /dev/null
+++ b/general/datasets/Candle_meth27_0313/platform.rtf
@@ -0,0 +1 @@
+Illumina Infinium HumanMethylation27 BeadChip
diff --git a/general/datasets/Candle_meth27_0313/processing.rtf b/general/datasets/Candle_meth27_0313/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Candle_meth27_0313/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Candle_meth_0313/platform.rtf b/general/datasets/Candle_meth_0313/platform.rtf
new file mode 100644
index 0000000..760018d
--- /dev/null
+++ b/general/datasets/Candle_meth_0313/platform.rtf
@@ -0,0 +1 @@
+Illumina Infinium HumanMethylation27 BeadChip
diff --git a/general/datasets/Candle_meth_0313/processing.rtf b/general/datasets/Candle_meth_0313/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Candle_meth_0313/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Candle_nb_0711/acknowledgment.rtf b/general/datasets/Candle_nb_0711/acknowledgment.rtf
new file mode 100644
index 0000000..ea399b5
--- /dev/null
+++ b/general/datasets/Candle_nb_0711/acknowledgment.rtf
@@ -0,0 +1,14 @@
+Data Owner: Dr. Robert W. Williams, Dr. Ron Adkins, UTHSC Department of Pediatrics
+
+Expression data generated by the UTHSC Molecular Resources Center with funding from the Center for Integrative and Translational Genomics
+
+Data processing by Drs. Ron Adkins and Julia Krushkal. Data entry into GeneNetwork by Arthur Centeno and Robert W. Williams.
+
+
+ - background subtraction (using Illumina's GenomeStudio)
+ - VST transform (using lumi in Bioconductor)
+ - quantile normalization (also using lumi)
+ - [any outliers that did not pass QC were removed using sample clustering, MA plots, boxplots, etc.] correction for batch effects using COMBAT
+
+
+Please refer to information provided by Drs. Williams or Adkins with the data that specifies exactly which of these steps (or all of them) were included in the final data set that he provided to you.
diff --git a/general/datasets/Candle_nb_0711/cases.rtf b/general/datasets/Candle_nb_0711/cases.rtf
new file mode 100644
index 0000000..c7fe664
--- /dev/null
+++ b/general/datasets/Candle_nb_0711/cases.rtf
@@ -0,0 +1 @@
+A subset of neonatal cord blood samples from the CANDLE cohort.
diff --git a/general/datasets/Candle_nb_0711/citation.rtf b/general/datasets/Candle_nb_0711/citation.rtf
new file mode 100644
index 0000000..941dbc5
--- /dev/null
+++ b/general/datasets/Candle_nb_0711/citation.rtf
@@ -0,0 +1,9 @@
+Associated References:
+
+
+ - Adkins RM, Tylavsky FA, Krushkal J (2012) Newborn umbilical blood DNA methylation and gene expression levels exhibit limited association with birth weight. Chemistry & Biodiversity 9: 888-899
+ - Adkins RM, Thomas F, Tylavsky FA, Krushkal J (2011) Parental ages and levels of DNA methylation in the newborn are correlated. BMC Med Genet 12: 47
+ - Adkins RM, Krushkal J, Tylavsky FA, Thomas F (2011) Racial differences in gene-specific DNA methylation levels are present at birth. Birth Defects Res A Clin Mol Teratol 91: 728-736
+
+
+
diff --git a/general/datasets/Candle_nb_0711/experiment-type.rtf b/general/datasets/Candle_nb_0711/experiment-type.rtf
new file mode 100644
index 0000000..8224239
--- /dev/null
+++ b/general/datasets/Candle_nb_0711/experiment-type.rtf
@@ -0,0 +1 @@
+See Ref 1
\ No newline at end of file
diff --git a/general/datasets/Candle_nb_0711/summary.rtf b/general/datasets/Candle_nb_0711/summary.rtf
new file mode 100644
index 0000000..df02b8b
--- /dev/null
+++ b/general/datasets/Candle_nb_0711/summary.rtf
@@ -0,0 +1,9 @@
+The CANDLE Study is a large multidisciplinary study of early child development that involves genetic, genomic, environmental, and large-scale behavioral evaluation of children and their families from the second trimester of development through to 4 years of age. The full study involves more than 1000 children and their mothers and fathers.
+
+For information on genomic and genetic studies related to CANDLE, please contact: Dr. Robert W. Williams (rwilliams@uthsc.edu). These data were originally generated by Drs. Ronald M. Adkins and Julia Krushkal at UTHSC.
+
+For information on the composition of neonatal cord blood, please see the review article by Jose N Tolosa and colleagues (2010).
+
+For information on the overall design of CANDLE, please contact: Dr. Frances A. Tylavsky (ftylavsk at uthsc.edu).
+
+Summary from The Urban Child Institute: "The primary goal of the CANDLE study is to study factors that affect brain development in young children. To this end, the current study will test specific hypotheses regarding factors that may negatively influence cognitive development in children. Participants in this cohort study will include 1,500 mother-child dyads, recruited during the second trimester of pregnancy and followed from birth to age 3. Data on a wide range of possible influences on children's cognitive outcomes will be collected from numerous sources, including questionnaires, interviews, psychosocial assessments, medical chart abstraction, environmental samples from the child's home environment, blood and urine samples from the mother, cord blood, and placental tissue. The primary outcomes of the current study are those associated with a poor cognitive outcome in the child. Outcomes will be measured using standardized cognitive assessments conducted at 12 months, 24 months, and 36 months of age. Epidemiological, clinical, and laboratory-based research may be undertaken using data from the project, with sub-studies including, but not limited to, molecular genetics, environmental exposure assessments, and micronutrient deficiency analyses. Results of this cohort study may provide information that will ultimately lead to improvements in the health, development, and well-being of children in Shelby County, Tennessee through interventions and policy enforcement and/or development. Full participant recruitment and complete data collection began in November 2006."
diff --git a/general/datasets/Candle_nb_0711/tissue.rtf b/general/datasets/Candle_nb_0711/tissue.rtf
new file mode 100644
index 0000000..736f786
--- /dev/null
+++ b/general/datasets/Candle_nb_0711/tissue.rtf
@@ -0,0 +1 @@
+Neonatal cord blood.
diff --git a/general/datasets/Cb_m_0104_m/acknowledgment.rtf b/general/datasets/Cb_m_0104_m/acknowledgment.rtf
new file mode 100644
index 0000000..b048bb0
--- /dev/null
+++ b/general/datasets/Cb_m_0104_m/acknowledgment.rtf
@@ -0,0 +1,15 @@
+Data were generated with funds contributed equally by The UTHSC-SJCRH Cerebellum Transcriptome Profiling Consortium. Our members include:
+
+ - Tom Curran
+ - Dan Goldowitz
+ - Kristin Hamre
+ - Lu Lu
+ - Peter McKinnon
+ - James Morgan
+ - Clayton Naeve
+ - Richard Smeyne
+ - Robert W. Williams
+ - The Center of Genomics and Bioinformatics at UTHSC
+ - The Hartwell Center at SJCRH
+
+
diff --git a/general/datasets/Cb_m_0104_m/cases.rtf b/general/datasets/Cb_m_0104_m/cases.rtf
new file mode 100644
index 0000000..f5e6bdf
--- /dev/null
+++ b/general/datasets/Cb_m_0104_m/cases.rtf
@@ -0,0 +1,7 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems). Chromosomes of the two parental strains have been recombined and fixed randomly in the many different BXD strains. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine.
+
+
+In this mRNA expression data set we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+
+The set of mouse strains used for mapping (a mapping panel) consists of groups of genetically unique BXD recombinant inbred strains. The ancestral strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6, and 1.5x coverage for D by Celera Genomics). Chromosomes of the two parental strains are recombined randomly in the many different BXD strains. BXD lines 2 through 32 were produced by Dr. Benjamin Taylor starting in the late 1970s. BXD33 through 42 were also produced by Dr. Taylor, but they were generated in the 1990s. All of these strains are available from The Jackson Laboratory. Lines such as BXD67, BXD68, etc. are BXD Advanced recombinant inbred strains that are part of a large set now being produced by Drs. Lu Lu, Guomin Zhou, Lee Silver, Jeremy Peirce, and Robert Williams. There will eventually be 45 of these BXD strains. For additional background on recombinant inbred strains, please see http://www.nervenet.org/papers/bxn.html.
diff --git a/general/datasets/Cb_m_0104_m/notes.rtf b/general/datasets/Cb_m_0104_m/notes.rtf
new file mode 100644
index 0000000..5d4ac24
--- /dev/null
+++ b/general/datasets/Cb_m_0104_m/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW and YHQ, September 2003. Updated by RWW, October 30, 2004.
+
diff --git a/general/datasets/Cb_m_0104_m/platform.rtf b/general/datasets/Cb_m_0104_m/platform.rtf
new file mode 100644
index 0000000..188038b
--- /dev/null
+++ b/general/datasets/Cb_m_0104_m/platform.rtf
@@ -0,0 +1,3 @@
+Affymetrix Mouse Expression 430 GeneChip set: The expression data were generated using 430A and 430B arrays. Chromosomal positions of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
diff --git a/general/datasets/Cb_m_0104_m/processing.rtf b/general/datasets/Cb_m_0104_m/processing.rtf
new file mode 100644
index 0000000..cdfa27a
--- /dev/null
+++ b/general/datasets/Cb_m_0104_m/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added a constant offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal level.
+ - Step 3: We computed the Z scores for each cell within its array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units.
+ - Step 6a: The 430A and 430B GeneChips include a set of 100 shared probe sets that have identical sequences. These 100 probe sets and 2200 probes provide a good way to adjust expression of the two GeneChips to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array (the A array contains the more commonly expressed transcripts). To bring the two arrays into numerical alignment, we regressed Z scores of the common set of 2200 probes to obtain linear regression corrections to rescale the 430B arrays to values that match the 430A array. This involved multiplying all 430B Z scores by the slope of the regression and adding a very small offset (the regression intercept). The result of this adjustment is that the mean of the 430A array expression is fixed at a value of 8, whereas that of the 430B chip is typically 7.
+ - Step 6b: We recentered the entire combined set of 430A and 430B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: No batch correction was applied.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have only a very modest number of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that this data set does not provide any correction for variance introduced by differences in sex, age, tissue source, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+Probe set data from the CHP file: These CHP files were generated using MAS 5. The same simple steps described above were also applied to these values. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the noise level.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers on the 430A and 430B microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium Oct 2003 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Cb_m_0104_m/summary.rtf b/general/datasets/Cb_m_0104_m/summary.rtf
new file mode 100644
index 0000000..8a59cc3
--- /dev/null
+++ b/general/datasets/Cb_m_0104_m/summary.rtf
@@ -0,0 +1,3 @@
+
+This October 2003 freeze provides estimates of mRNA expression in cerebellum of 26 adult BXD recombinant inbred strains, as well as C57BL/6J, DBA/2J, and their F1 hybrid, measured using the Affymetrix M430A and B microarrays. Data were generated by a small consortium of investigators at St. Jude Children's Research Hospital (SJ) and the University of Tennessee Health Science Center (UT). Data were processed using the Microarray Suite 5 (<a data-cke-saved-href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" _blank"="" class="fs14">MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run in two large batches with careful consideration to balancing samples by sex and age. Eighteen strains have been profiled using two or three independent samples. All other strains were sampled once.
+
diff --git a/general/datasets/Cb_m_0104_m/tissue.rtf b/general/datasets/Cb_m_0104_m/tissue.rtf
new file mode 100644
index 0000000..4f8e5ed
--- /dev/null
+++ b/general/datasets/Cb_m_0104_m/tissue.rtf
@@ -0,0 +1,376 @@
+
+The October 2003 data set was processed in two large batches. The first batch (the May 2003 data set) consists of 20 pooled samples from 20 strains run on pairs of Affymetrix 430A and 430B arrays (40 arrays total). The second batch consists of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of whole cerebellum taken from three adult animals of the same age and sex. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+RNA was extracted at UTHSC by Zhiping Jia and Hongtao Zhai.
+
+All samples were subsequently processed at the Hartwell Center Affymetrix laboratory at SJCRH by Jay Morris.
+
+
+The January04 data were processed in two large batches. The first batch (the May03 data set) consisted of samples from 20 samples and 20 strains run on Affymetrix MOE 430A and MOE430B GeneChip pairs (40 arrays total). The second batch of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of brain tissue (intact whole cerebellum) taken from three adult animals usually of the same age. RNA was extracted at UTHSC and all samples were processed at the Hartwell Center (SJCRH, Memphis). We will eventually achieve a sample with good, but not perfect, balance of samples by sex and age. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+The table below summarizes informaton on strain, sex, age, sample name, and batch number.
+
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Batch |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 766-C1 |
+ 2 |
+
+
+ | B6D2F1 |
+ M |
+ 94 |
+ S347-1C1 |
+ 1 |
+
+
+ | C57BL/6J |
+ F |
+ 116 |
+ 773-C1 |
+ 2 |
+
+
+ | C57BL/6J |
+ M |
+ 109 |
+ S054-1C2 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 71 |
+ S175-1C1 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 91 |
+ 782-C1 |
+ 2 |
+
+
+ | BXD1 |
+ F |
+ 57 |
+ 813-C1 |
+ 2 |
+
+
+ | BXD2 |
+ F |
+ 142 |
+ 751-C1 |
+ 1 |
+
+
+ | BXD2 |
+ F |
+ 78 |
+ 774-C1 |
+ 2 |
+
+
+ | BXD5 |
+ F |
+ 56 |
+ 802-C1 |
+ 2 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 752-C1 |
+ 1 |
+
+
+ | BXD6 |
+ F |
+ 92 |
+ 719-C1 |
+ 1 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S173-1C1 |
+ 1 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 737-C1 |
+ 1 |
+
+
+ | BXD11 |
+ F |
+ 441 |
+ S200-1C1 |
+ 1 |
+
+
+ | BXD11 |
+ M |
+ 92 |
+ 790-C1 |
+ 2 |
+
+
+ | BXD12 |
+ F |
+ 130 |
+ 776-C1 |
+ 2 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 756-C1 |
+ 2 |
+
+
+ | BXD14 |
+ F |
+ 190 |
+ 794-C1 |
+ 2 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 758-C1 |
+ 2 |
+
+
+ | BXD16 |
+ F |
+ 163 |
+ 750-C1 |
+ 1 |
+
+
+ | BXD19 |
+ F |
+ 61 |
+ 772-C1 |
+ 2 |
+
+
+ | BXD21 |
+ F |
+ 116 |
+ 711-C1 |
+ 1 |
+
+
+ | BXD21 |
+ M |
+ 64 |
+ 803-C1 |
+ 2 |
+
+
+ | BXD22 |
+ F |
+ 65 |
+ S174-1C1 |
+ 1 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 814-C1 |
+ 2 |
+
+
+ | BXD24 |
+ F |
+ 71 |
+ 805-C1 |
+ 2 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 759-C1 |
+ 2 |
+
+
+ | BXD25 |
+ M |
+ 90 |
+ S429-1C1 |
+ 1 |
+
+
+ | BXD28 |
+ F |
+ 113 |
+ 785-C1 |
+ 2 |
+
+
+ | BXD28 |
+ F |
+ 427 |
+ S203-1C1 |
+ 1 |
+
+
+ | BXD29 |
+ F |
+ 82 |
+ 777-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 1 |
+
+
+ | BXD31 |
+ F |
+ 142 |
+ 816-C1 |
+ 2 |
+
+
+ | BXD32 |
+ F |
+ 62 |
+ 778-C1 |
+ 2 |
+
+
+ | BXD32 |
+ M |
+ 218 |
+ 786-C1 |
+ 2 |
+
+
+ | BXD33 |
+ F |
+ 184 |
+ 793-C1 |
+ 2 |
+
+
+ | BXD33 |
+ M |
+ 124 |
+ 715-C1 |
+ 1 |
+
+
+ | BXD34 |
+ F |
+ 56 |
+ 725-C1 |
+ 1 |
+
+
+ | BXD34 |
+ M |
+ 91 |
+ 789-C1 |
+ 2 |
+
+
+ | BXD38 |
+ F |
+ 55 |
+ 781-C1 |
+ 2 |
+
+
+ | BXD38 |
+ M |
+ 65 |
+ 761-C1 |
+ 2 |
+
+
+ | BXD39 |
+ M |
+ 165 |
+ 723-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 2 |
+
+
+ | BXD40 |
+ M |
+ 73 |
+ 812-C1 |
+ 2 |
+
+
+ | BXD42 |
+ F |
+ 100 |
+ 799-C1 |
+ 2 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 709-C1 |
+ 1 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Cb_m_0104_p/acknowledgment.rtf b/general/datasets/Cb_m_0104_p/acknowledgment.rtf
new file mode 100644
index 0000000..b048bb0
--- /dev/null
+++ b/general/datasets/Cb_m_0104_p/acknowledgment.rtf
@@ -0,0 +1,15 @@
+Data were generated with funds contributed equally by The UTHSC-SJCRH Cerebellum Transcriptome Profiling Consortium. Our members include:
+
+ - Tom Curran
+ - Dan Goldowitz
+ - Kristin Hamre
+ - Lu Lu
+ - Peter McKinnon
+ - James Morgan
+ - Clayton Naeve
+ - Richard Smeyne
+ - Robert W. Williams
+ - The Center of Genomics and Bioinformatics at UTHSC
+ - The Hartwell Center at SJCRH
+
+
diff --git a/general/datasets/Cb_m_0104_p/cases.rtf b/general/datasets/Cb_m_0104_p/cases.rtf
new file mode 100644
index 0000000..f5e6bdf
--- /dev/null
+++ b/general/datasets/Cb_m_0104_p/cases.rtf
@@ -0,0 +1,7 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems). Chromosomes of the two parental strains have been recombined and fixed randomly in the many different BXD strains. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine.
+
+
+In this mRNA expression data set we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+
+The set of mouse strains used for mapping (a mapping panel) consists of groups of genetically unique BXD recombinant inbred strains. The ancestral strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6, and 1.5x coverage for D by Celera Genomics). Chromosomes of the two parental strains are recombined randomly in the many different BXD strains. BXD lines 2 through 32 were produced by Dr. Benjamin Taylor starting in the late 1970s. BXD33 through 42 were also produced by Dr. Taylor, but they were generated in the 1990s. All of these strains are available from The Jackson Laboratory. Lines such as BXD67, BXD68, etc. are BXD Advanced recombinant inbred strains that are part of a large set now being produced by Drs. Lu Lu, Guomin Zhou, Lee Silver, Jeremy Peirce, and Robert Williams. There will eventually be 45 of these BXD strains. For additional background on recombinant inbred strains, please see http://www.nervenet.org/papers/bxn.html.
diff --git a/general/datasets/Cb_m_0104_p/notes.rtf b/general/datasets/Cb_m_0104_p/notes.rtf
new file mode 100644
index 0000000..5d4ac24
--- /dev/null
+++ b/general/datasets/Cb_m_0104_p/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW and YHQ, September 2003. Updated by RWW, October 30, 2004.
+
diff --git a/general/datasets/Cb_m_0104_p/platform.rtf b/general/datasets/Cb_m_0104_p/platform.rtf
new file mode 100644
index 0000000..188038b
--- /dev/null
+++ b/general/datasets/Cb_m_0104_p/platform.rtf
@@ -0,0 +1,3 @@
+Affymetrix Mouse Expression 430 GeneChip set: The expression data were generated using 430A and 430B arrays. Chromosomal positions of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
diff --git a/general/datasets/Cb_m_0104_p/processing.rtf b/general/datasets/Cb_m_0104_p/processing.rtf
new file mode 100644
index 0000000..cdfa27a
--- /dev/null
+++ b/general/datasets/Cb_m_0104_p/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added a constant offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal level.
+ - Step 3: We computed the Z scores for each cell within its array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units.
+ - Step 6a: The 430A and 430B GeneChips include a set of 100 shared probe sets that have identical sequences. These 100 probe sets and 2200 probes provide a good way to adjust expression of the two GeneChips to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array (the A array contains the more commonly expressed transcripts). To bring the two arrays into numerical alignment, we regressed Z scores of the common set of 2200 probes to obtain linear regression corrections to rescale the 430B arrays to values that match the 430A array. This involved multiplying all 430B Z scores by the slope of the regression and adding a very small offset (the regression intercept). The result of this adjustment is that the mean of the 430A array expression is fixed at a value of 8, whereas that of the 430B chip is typically 7.
+ - Step 6b: We recentered the entire combined set of 430A and 430B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: No batch correction was applied.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have only a very modest number of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that this data set does not provide any correction for variance introduced by differences in sex, age, tissue source, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+Probe set data from the CHP file: These CHP files were generated using MAS 5. The same simple steps described above were also applied to these values. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the noise level.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers on the 430A and 430B microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium Oct 2003 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Cb_m_0104_p/summary.rtf b/general/datasets/Cb_m_0104_p/summary.rtf
new file mode 100644
index 0000000..8a59cc3
--- /dev/null
+++ b/general/datasets/Cb_m_0104_p/summary.rtf
@@ -0,0 +1,3 @@
+
+This October 2003 freeze provides estimates of mRNA expression in cerebellum of 26 adult BXD recombinant inbred strains, as well as C57BL/6J, DBA/2J, and their F1 hybrid, measured using the Affymetrix M430A and B microarrays. Data were generated by a small consortium of investigators at St. Jude Children's Research Hospital (SJ) and the University of Tennessee Health Science Center (UT). Data were processed using the Microarray Suite 5 (<a data-cke-saved-href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" _blank"="" class="fs14">MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run in two large batches with careful consideration to balancing samples by sex and age. Eighteen strains have been profiled using two or three independent samples. All other strains were sampled once.
+
diff --git a/general/datasets/Cb_m_0104_p/tissue.rtf b/general/datasets/Cb_m_0104_p/tissue.rtf
new file mode 100644
index 0000000..4f8e5ed
--- /dev/null
+++ b/general/datasets/Cb_m_0104_p/tissue.rtf
@@ -0,0 +1,376 @@
+
+The October 2003 data set was processed in two large batches. The first batch (the May 2003 data set) consists of 20 pooled samples from 20 strains run on pairs of Affymetrix 430A and 430B arrays (40 arrays total). The second batch consists of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of whole cerebellum taken from three adult animals of the same age and sex. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+RNA was extracted at UTHSC by Zhiping Jia and Hongtao Zhai.
+
+All samples were subsequently processed at the Hartwell Center Affymetrix laboratory at SJCRH by Jay Morris.
+
+
+The January04 data were processed in two large batches. The first batch (the May03 data set) consisted of samples from 20 samples and 20 strains run on Affymetrix MOE 430A and MOE430B GeneChip pairs (40 arrays total). The second batch of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of brain tissue (intact whole cerebellum) taken from three adult animals usually of the same age. RNA was extracted at UTHSC and all samples were processed at the Hartwell Center (SJCRH, Memphis). We will eventually achieve a sample with good, but not perfect, balance of samples by sex and age. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+The table below summarizes informaton on strain, sex, age, sample name, and batch number.
+
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Batch |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 766-C1 |
+ 2 |
+
+
+ | B6D2F1 |
+ M |
+ 94 |
+ S347-1C1 |
+ 1 |
+
+
+ | C57BL/6J |
+ F |
+ 116 |
+ 773-C1 |
+ 2 |
+
+
+ | C57BL/6J |
+ M |
+ 109 |
+ S054-1C2 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 71 |
+ S175-1C1 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 91 |
+ 782-C1 |
+ 2 |
+
+
+ | BXD1 |
+ F |
+ 57 |
+ 813-C1 |
+ 2 |
+
+
+ | BXD2 |
+ F |
+ 142 |
+ 751-C1 |
+ 1 |
+
+
+ | BXD2 |
+ F |
+ 78 |
+ 774-C1 |
+ 2 |
+
+
+ | BXD5 |
+ F |
+ 56 |
+ 802-C1 |
+ 2 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 752-C1 |
+ 1 |
+
+
+ | BXD6 |
+ F |
+ 92 |
+ 719-C1 |
+ 1 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S173-1C1 |
+ 1 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 737-C1 |
+ 1 |
+
+
+ | BXD11 |
+ F |
+ 441 |
+ S200-1C1 |
+ 1 |
+
+
+ | BXD11 |
+ M |
+ 92 |
+ 790-C1 |
+ 2 |
+
+
+ | BXD12 |
+ F |
+ 130 |
+ 776-C1 |
+ 2 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 756-C1 |
+ 2 |
+
+
+ | BXD14 |
+ F |
+ 190 |
+ 794-C1 |
+ 2 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 758-C1 |
+ 2 |
+
+
+ | BXD16 |
+ F |
+ 163 |
+ 750-C1 |
+ 1 |
+
+
+ | BXD19 |
+ F |
+ 61 |
+ 772-C1 |
+ 2 |
+
+
+ | BXD21 |
+ F |
+ 116 |
+ 711-C1 |
+ 1 |
+
+
+ | BXD21 |
+ M |
+ 64 |
+ 803-C1 |
+ 2 |
+
+
+ | BXD22 |
+ F |
+ 65 |
+ S174-1C1 |
+ 1 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 814-C1 |
+ 2 |
+
+
+ | BXD24 |
+ F |
+ 71 |
+ 805-C1 |
+ 2 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 759-C1 |
+ 2 |
+
+
+ | BXD25 |
+ M |
+ 90 |
+ S429-1C1 |
+ 1 |
+
+
+ | BXD28 |
+ F |
+ 113 |
+ 785-C1 |
+ 2 |
+
+
+ | BXD28 |
+ F |
+ 427 |
+ S203-1C1 |
+ 1 |
+
+
+ | BXD29 |
+ F |
+ 82 |
+ 777-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 1 |
+
+
+ | BXD31 |
+ F |
+ 142 |
+ 816-C1 |
+ 2 |
+
+
+ | BXD32 |
+ F |
+ 62 |
+ 778-C1 |
+ 2 |
+
+
+ | BXD32 |
+ M |
+ 218 |
+ 786-C1 |
+ 2 |
+
+
+ | BXD33 |
+ F |
+ 184 |
+ 793-C1 |
+ 2 |
+
+
+ | BXD33 |
+ M |
+ 124 |
+ 715-C1 |
+ 1 |
+
+
+ | BXD34 |
+ F |
+ 56 |
+ 725-C1 |
+ 1 |
+
+
+ | BXD34 |
+ M |
+ 91 |
+ 789-C1 |
+ 2 |
+
+
+ | BXD38 |
+ F |
+ 55 |
+ 781-C1 |
+ 2 |
+
+
+ | BXD38 |
+ M |
+ 65 |
+ 761-C1 |
+ 2 |
+
+
+ | BXD39 |
+ M |
+ 165 |
+ 723-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 2 |
+
+
+ | BXD40 |
+ M |
+ 73 |
+ 812-C1 |
+ 2 |
+
+
+ | BXD42 |
+ F |
+ 100 |
+ 799-C1 |
+ 2 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 709-C1 |
+ 1 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Cb_m_0104_r/acknowledgment.rtf b/general/datasets/Cb_m_0104_r/acknowledgment.rtf
new file mode 100644
index 0000000..b048bb0
--- /dev/null
+++ b/general/datasets/Cb_m_0104_r/acknowledgment.rtf
@@ -0,0 +1,15 @@
+Data were generated with funds contributed equally by The UTHSC-SJCRH Cerebellum Transcriptome Profiling Consortium. Our members include:
+
+ - Tom Curran
+ - Dan Goldowitz
+ - Kristin Hamre
+ - Lu Lu
+ - Peter McKinnon
+ - James Morgan
+ - Clayton Naeve
+ - Richard Smeyne
+ - Robert W. Williams
+ - The Center of Genomics and Bioinformatics at UTHSC
+ - The Hartwell Center at SJCRH
+
+
diff --git a/general/datasets/Cb_m_0104_r/cases.rtf b/general/datasets/Cb_m_0104_r/cases.rtf
new file mode 100644
index 0000000..f5e6bdf
--- /dev/null
+++ b/general/datasets/Cb_m_0104_r/cases.rtf
@@ -0,0 +1,7 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems). Chromosomes of the two parental strains have been recombined and fixed randomly in the many different BXD strains. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine.
+
+
+In this mRNA expression data set we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+
+The set of mouse strains used for mapping (a mapping panel) consists of groups of genetically unique BXD recombinant inbred strains. The ancestral strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6, and 1.5x coverage for D by Celera Genomics). Chromosomes of the two parental strains are recombined randomly in the many different BXD strains. BXD lines 2 through 32 were produced by Dr. Benjamin Taylor starting in the late 1970s. BXD33 through 42 were also produced by Dr. Taylor, but they were generated in the 1990s. All of these strains are available from The Jackson Laboratory. Lines such as BXD67, BXD68, etc. are BXD Advanced recombinant inbred strains that are part of a large set now being produced by Drs. Lu Lu, Guomin Zhou, Lee Silver, Jeremy Peirce, and Robert Williams. There will eventually be 45 of these BXD strains. For additional background on recombinant inbred strains, please see http://www.nervenet.org/papers/bxn.html.
diff --git a/general/datasets/Cb_m_0104_r/notes.rtf b/general/datasets/Cb_m_0104_r/notes.rtf
new file mode 100644
index 0000000..5d4ac24
--- /dev/null
+++ b/general/datasets/Cb_m_0104_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW and YHQ, September 2003. Updated by RWW, October 30, 2004.
+
diff --git a/general/datasets/Cb_m_0104_r/platform.rtf b/general/datasets/Cb_m_0104_r/platform.rtf
new file mode 100644
index 0000000..188038b
--- /dev/null
+++ b/general/datasets/Cb_m_0104_r/platform.rtf
@@ -0,0 +1,3 @@
+Affymetrix Mouse Expression 430 GeneChip set: The expression data were generated using 430A and 430B arrays. Chromosomal positions of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
diff --git a/general/datasets/Cb_m_0104_r/processing.rtf b/general/datasets/Cb_m_0104_r/processing.rtf
new file mode 100644
index 0000000..cdfa27a
--- /dev/null
+++ b/general/datasets/Cb_m_0104_r/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added a constant offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal level.
+ - Step 3: We computed the Z scores for each cell within its array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units.
+ - Step 6a: The 430A and 430B GeneChips include a set of 100 shared probe sets that have identical sequences. These 100 probe sets and 2200 probes provide a good way to adjust expression of the two GeneChips to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array (the A array contains the more commonly expressed transcripts). To bring the two arrays into numerical alignment, we regressed Z scores of the common set of 2200 probes to obtain linear regression corrections to rescale the 430B arrays to values that match the 430A array. This involved multiplying all 430B Z scores by the slope of the regression and adding a very small offset (the regression intercept). The result of this adjustment is that the mean of the 430A array expression is fixed at a value of 8, whereas that of the 430B chip is typically 7.
+ - Step 6b: We recentered the entire combined set of 430A and 430B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: No batch correction was applied.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have only a very modest number of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that this data set does not provide any correction for variance introduced by differences in sex, age, tissue source, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+Probe set data from the CHP file: These CHP files were generated using MAS 5. The same simple steps described above were also applied to these values. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the noise level.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers on the 430A and 430B microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium Oct 2003 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Cb_m_0104_r/summary.rtf b/general/datasets/Cb_m_0104_r/summary.rtf
new file mode 100644
index 0000000..8a59cc3
--- /dev/null
+++ b/general/datasets/Cb_m_0104_r/summary.rtf
@@ -0,0 +1,3 @@
+
+This October 2003 freeze provides estimates of mRNA expression in cerebellum of 26 adult BXD recombinant inbred strains, as well as C57BL/6J, DBA/2J, and their F1 hybrid, measured using the Affymetrix M430A and B microarrays. Data were generated by a small consortium of investigators at St. Jude Children's Research Hospital (SJ) and the University of Tennessee Health Science Center (UT). Data were processed using the Microarray Suite 5 (<a data-cke-saved-href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" _blank"="" class="fs14">MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run in two large batches with careful consideration to balancing samples by sex and age. Eighteen strains have been profiled using two or three independent samples. All other strains were sampled once.
+
diff --git a/general/datasets/Cb_m_0104_r/tissue.rtf b/general/datasets/Cb_m_0104_r/tissue.rtf
new file mode 100644
index 0000000..4f8e5ed
--- /dev/null
+++ b/general/datasets/Cb_m_0104_r/tissue.rtf
@@ -0,0 +1,376 @@
+
+The October 2003 data set was processed in two large batches. The first batch (the May 2003 data set) consists of 20 pooled samples from 20 strains run on pairs of Affymetrix 430A and 430B arrays (40 arrays total). The second batch consists of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of whole cerebellum taken from three adult animals of the same age and sex. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+RNA was extracted at UTHSC by Zhiping Jia and Hongtao Zhai.
+
+All samples were subsequently processed at the Hartwell Center Affymetrix laboratory at SJCRH by Jay Morris.
+
+
+The January04 data were processed in two large batches. The first batch (the May03 data set) consisted of samples from 20 samples and 20 strains run on Affymetrix MOE 430A and MOE430B GeneChip pairs (40 arrays total). The second batch of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of brain tissue (intact whole cerebellum) taken from three adult animals usually of the same age. RNA was extracted at UTHSC and all samples were processed at the Hartwell Center (SJCRH, Memphis). We will eventually achieve a sample with good, but not perfect, balance of samples by sex and age. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+The table below summarizes informaton on strain, sex, age, sample name, and batch number.
+
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Batch |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 766-C1 |
+ 2 |
+
+
+ | B6D2F1 |
+ M |
+ 94 |
+ S347-1C1 |
+ 1 |
+
+
+ | C57BL/6J |
+ F |
+ 116 |
+ 773-C1 |
+ 2 |
+
+
+ | C57BL/6J |
+ M |
+ 109 |
+ S054-1C2 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 71 |
+ S175-1C1 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 91 |
+ 782-C1 |
+ 2 |
+
+
+ | BXD1 |
+ F |
+ 57 |
+ 813-C1 |
+ 2 |
+
+
+ | BXD2 |
+ F |
+ 142 |
+ 751-C1 |
+ 1 |
+
+
+ | BXD2 |
+ F |
+ 78 |
+ 774-C1 |
+ 2 |
+
+
+ | BXD5 |
+ F |
+ 56 |
+ 802-C1 |
+ 2 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 752-C1 |
+ 1 |
+
+
+ | BXD6 |
+ F |
+ 92 |
+ 719-C1 |
+ 1 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S173-1C1 |
+ 1 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 737-C1 |
+ 1 |
+
+
+ | BXD11 |
+ F |
+ 441 |
+ S200-1C1 |
+ 1 |
+
+
+ | BXD11 |
+ M |
+ 92 |
+ 790-C1 |
+ 2 |
+
+
+ | BXD12 |
+ F |
+ 130 |
+ 776-C1 |
+ 2 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 756-C1 |
+ 2 |
+
+
+ | BXD14 |
+ F |
+ 190 |
+ 794-C1 |
+ 2 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 758-C1 |
+ 2 |
+
+
+ | BXD16 |
+ F |
+ 163 |
+ 750-C1 |
+ 1 |
+
+
+ | BXD19 |
+ F |
+ 61 |
+ 772-C1 |
+ 2 |
+
+
+ | BXD21 |
+ F |
+ 116 |
+ 711-C1 |
+ 1 |
+
+
+ | BXD21 |
+ M |
+ 64 |
+ 803-C1 |
+ 2 |
+
+
+ | BXD22 |
+ F |
+ 65 |
+ S174-1C1 |
+ 1 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 814-C1 |
+ 2 |
+
+
+ | BXD24 |
+ F |
+ 71 |
+ 805-C1 |
+ 2 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 759-C1 |
+ 2 |
+
+
+ | BXD25 |
+ M |
+ 90 |
+ S429-1C1 |
+ 1 |
+
+
+ | BXD28 |
+ F |
+ 113 |
+ 785-C1 |
+ 2 |
+
+
+ | BXD28 |
+ F |
+ 427 |
+ S203-1C1 |
+ 1 |
+
+
+ | BXD29 |
+ F |
+ 82 |
+ 777-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 1 |
+
+
+ | BXD31 |
+ F |
+ 142 |
+ 816-C1 |
+ 2 |
+
+
+ | BXD32 |
+ F |
+ 62 |
+ 778-C1 |
+ 2 |
+
+
+ | BXD32 |
+ M |
+ 218 |
+ 786-C1 |
+ 2 |
+
+
+ | BXD33 |
+ F |
+ 184 |
+ 793-C1 |
+ 2 |
+
+
+ | BXD33 |
+ M |
+ 124 |
+ 715-C1 |
+ 1 |
+
+
+ | BXD34 |
+ F |
+ 56 |
+ 725-C1 |
+ 1 |
+
+
+ | BXD34 |
+ M |
+ 91 |
+ 789-C1 |
+ 2 |
+
+
+ | BXD38 |
+ F |
+ 55 |
+ 781-C1 |
+ 2 |
+
+
+ | BXD38 |
+ M |
+ 65 |
+ 761-C1 |
+ 2 |
+
+
+ | BXD39 |
+ M |
+ 165 |
+ 723-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 2 |
+
+
+ | BXD40 |
+ M |
+ 73 |
+ 812-C1 |
+ 2 |
+
+
+ | BXD42 |
+ F |
+ 100 |
+ 799-C1 |
+ 2 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 709-C1 |
+ 1 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Cb_m_0204_p/acknowledgment.rtf b/general/datasets/Cb_m_0204_p/acknowledgment.rtf
new file mode 100644
index 0000000..7b62a11
--- /dev/null
+++ b/general/datasets/Cb_m_0204_p/acknowledgment.rtf
@@ -0,0 +1 @@
+Data for the microarrays were generously provided by support from NIAAA INIA grants to RWW and Thomas Sutter. Support for sample acquistion and WebQTL have been provided by NIMH Human Brain Project, and the Dunavant Chair of Excellence, University of Tennessee Health Science Center. All arrays were processed at the University of Memphis by Dr. Thomas Sutter and colleagues with support of the INIA Bioanalytical Core.
diff --git a/general/datasets/Cb_m_0204_p/cases.rtf b/general/datasets/Cb_m_0204_p/cases.rtf
new file mode 100644
index 0000000..9dc5cbe
--- /dev/null
+++ b/general/datasets/Cb_m_0204_p/cases.rtf
@@ -0,0 +1,3 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B) and DBA/2J (D). Both B and D strains have been almost fully sequence (8x coverage for B by a public consortium and approximately 1.5x coverage for D by Celera).
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine.
diff --git a/general/datasets/Cb_m_0204_p/notes.rtf b/general/datasets/Cb_m_0204_p/notes.rtf
new file mode 100644
index 0000000..f3ea488
--- /dev/null
+++ b/general/datasets/Cb_m_0204_p/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, Oct 2004. Updated by RWW, Nov 5, 2004.
diff --git a/general/datasets/Cb_m_0204_p/platform.rtf b/general/datasets/Cb_m_0204_p/platform.rtf
new file mode 100644
index 0000000..51cbff2
--- /dev/null
+++ b/general/datasets/Cb_m_0204_p/platform.rtf
@@ -0,0 +1 @@
+Affymetrix 430A and 430B GeneChip Set: Expression data were generated using 430AB array pairs. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on either the Verify UCSC and Verify Ensembl links in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Cb_m_0204_p/processing.rtf b/general/datasets/Cb_m_0204_p/processing.rtf
new file mode 100644
index 0000000..4663b88
--- /dev/null
+++ b/general/datasets/Cb_m_0204_p/processing.rtf
@@ -0,0 +1,29 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each probe signal.
+ - Step 3: We computed the Z scores for each probe signal.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B arrays include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes provide a way to calibrate expression of the A and B arrays to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: We corrected for technical variance introduced by two batches. Means separated by the first batch for each gene are corrected same as means of the second batch.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have modest numbers of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+
+
+
+Probe set data: The original expression values in the Affymetrix CEL files were read into PerfectMatch to generate the normalized PDNN data set.
+
+PDNN values of each array were subsequently normalized to a achieve a mean value of 8 units and a variance of 2 units.
+
+When necessary, we computed the arithmetic mean for technical replicates and treated these as single samples. We then computed the arithmetic mean for the set of 2 to 5 biological replicates for each strain.
+
+
+About the array probe sets names:
+
+
+Most probe sets on the mouse 430A and 430B arrays consist of a total of 22 probes, divided into 11 perfect match(PM) probes and 11 mismatch (MM) controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, several suffix characters that highlight design features, a a final A or B character to specify the array pair member. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene.
+
diff --git a/general/datasets/Cb_m_0204_p/summary.rtf b/general/datasets/Cb_m_0204_p/summary.rtf
new file mode 100644
index 0000000..c32676a
--- /dev/null
+++ b/general/datasets/Cb_m_0204_p/summary.rtf
@@ -0,0 +1 @@
+This October 2004 data freeze provides initial estimates of mRNA expression in brains of adult BXD recombinant inbred mice measured using Affymetrix M430AB microarrays. In contast to the U74Av2 array, this new data set provides broader coverage (~45,000 transcripts) but does not include replicates or as many strains (25 vs 35). Data were generated at UTHSC and the University of Memphis with support from grants from the NIAAA Integrative Neuroscience Initiative on Alcoholism (INIA). Data were processed using the PDNN method of Zhang. To simplify comparison among transforms, PDNN values of each array were adjusted to an average of 8 units and a variance of 2 units.
diff --git a/general/datasets/Cb_m_0204_p/tissue.rtf b/general/datasets/Cb_m_0204_p/tissue.rtf
new file mode 100644
index 0000000..cac878a
--- /dev/null
+++ b/general/datasets/Cb_m_0204_p/tissue.rtf
@@ -0,0 +1,261 @@
+The data set consists of a single batch of Affymetrix mouse expression 430A and 430B GeneChip array pairs. Each AB pair was hybridized in sequence (A array first, B array second) with a pool of brain tissue (forebrain minus olfactory bulb, plus the entire midbrain) taken from three adult animals of closely matched age and the same sex. RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai. All samples were subsequently processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center of Excellence by Thomas R. Sutter and colleagues at the University of Memphis. Before running the main batch of 30 pairs of array, we ran four "test" samples (one male and one female pool from each of the two parental strains, C57BL/6J and DBA/2J). The main set of 30 array pairs includes the same four samples (in other words we have four technical replicates), two F1 hybrid sample (each run two times for a within-batch technical replication), and 22 BXD strains. The data set therefore consists of one male and one female pool from C57BL/6J, DBA/2J, the B6D2F1 hybrid, 11 female BXD samples, and 11 male BXD samples. We should note that the four technical replicates between batches were eventually combined with a correction for a highly significant batch effect. This was done at both the probe and probe set levels to "align" the test batch values with the two main batches. (The ratio of the probe average in the four test arrays to the average of the same probe in the four corresponding main batch arrays was used as a correction factor.) The F1 within-batch technical replicates were simply averaged. In the next batch we will reverse the sex of the BXD samples to achieve a balance with at least 22 BXD strains with one male and one female sample each.
+
+The table below lists the arrays by strain, sex, age, sample identifier, and data results were obtained from the Bioanalytical Core at the University of Memphis. Each array was hybridized to a pool of mRNA from three mice.
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Date |
+
+
+ | B6D2F1 |
+ F |
+ 127 |
+ 919-F1 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ F |
+ 127 |
+ 919-F2 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 920-F1 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 920-F2 |
+ Jan04 |
+
+
+ | C57BL/6J |
+ F |
+ 65 |
+ 903-F1 |
+ Nov03 |
+
+
+ | C57BL/6J |
+ F |
+ 65 |
+ 903-F2 |
+ Jan03 |
+
+
+ | C57BL/6J |
+ M |
+ 66 |
+ 906-F1 |
+ Nov03 |
+
+
+ | C57BL/6J |
+ M |
+ 66 |
+ 906-F2 |
+ Jan04 |
+
+
+ | DBA/2J |
+ F |
+ 60 |
+ 917-F1 |
+ Nov03 |
+
+
+ | DBA/2J |
+ F |
+ 60 |
+ 917-F2 |
+ Jan04 |
+
+
+ | DBA/2J |
+ M |
+ 60 |
+ 918-F1 |
+ Nov03 |
+
+
+ | DBA/2J |
+ M |
+ 60 |
+ 918-F2 |
+ Jan04 |
+
+
+ | BXD1 |
+ F |
+ 95 |
+ 895-F1 |
+ Jan04 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 728-F1 |
+ Jan04 |
+
+
+ | BXD6 |
+ M |
+ 92 |
+ 902-F1 |
+ Jan04 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S167-F1 |
+ Jan04 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 909-F1 |
+ Jan04 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 897-F1 |
+ Jan04 |
+
+
+ | BXD13 |
+ F |
+ 86 |
+ 748-F1 |
+ Jan04 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 912-F1 |
+ Jan04 |
+
+
+ | BXD18 |
+ F |
+ 108 |
+ 771-F1 |
+ Jan04 |
+
+
+ | BXD19 |
+ F |
+ 56 |
+ S236-F1 |
+ Jan04 |
+
+
+ | BXD21 |
+ F |
+ 67 |
+ 740-F1 |
+ Jan04 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 815-F1 |
+ Jan04 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 913-F1 |
+ Jan04 |
+
+
+ | BXD25 |
+ F |
+ 74 |
+ S373-F1 |
+ Jan04 |
+
+
+ | BXD28 |
+ F |
+ 79 |
+ 910-F1 |
+ Jan04 |
+
+
+ | BXD29 |
+ F |
+ 76 |
+ 693-F1 |
+ Jan04 |
+
+
+ | BXD32 |
+ F |
+ 93 |
+ 898-F1 |
+ Jan04 |
+
+
+ | BXD33 |
+ M |
+ 77 |
+ 915-F1 |
+ Jan04 |
+
+
+ | BXD34 |
+ M |
+ 72 |
+ 916-F1 |
+ Jan04 |
+
+
+ | BXD36 |
+ M |
+ 77 |
+ 926-F1 |
+ Jan04 |
+
+
+ | BXD38 |
+ M |
+ 69 |
+ 731-F1 |
+ Jan04 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 936-F1 |
+ Jan04 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Cb_m_0204_r/acknowledgment.rtf b/general/datasets/Cb_m_0204_r/acknowledgment.rtf
new file mode 100644
index 0000000..7b62a11
--- /dev/null
+++ b/general/datasets/Cb_m_0204_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data for the microarrays were generously provided by support from NIAAA INIA grants to RWW and Thomas Sutter. Support for sample acquistion and WebQTL have been provided by NIMH Human Brain Project, and the Dunavant Chair of Excellence, University of Tennessee Health Science Center. All arrays were processed at the University of Memphis by Dr. Thomas Sutter and colleagues with support of the INIA Bioanalytical Core.
diff --git a/general/datasets/Cb_m_0204_r/cases.rtf b/general/datasets/Cb_m_0204_r/cases.rtf
new file mode 100644
index 0000000..9dc5cbe
--- /dev/null
+++ b/general/datasets/Cb_m_0204_r/cases.rtf
@@ -0,0 +1,3 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B) and DBA/2J (D). Both B and D strains have been almost fully sequence (8x coverage for B by a public consortium and approximately 1.5x coverage for D by Celera).
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine.
diff --git a/general/datasets/Cb_m_0204_r/notes.rtf b/general/datasets/Cb_m_0204_r/notes.rtf
new file mode 100644
index 0000000..f3ea488
--- /dev/null
+++ b/general/datasets/Cb_m_0204_r/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, Oct 2004. Updated by RWW, Nov 5, 2004.
diff --git a/general/datasets/Cb_m_0204_r/platform.rtf b/general/datasets/Cb_m_0204_r/platform.rtf
new file mode 100644
index 0000000..51cbff2
--- /dev/null
+++ b/general/datasets/Cb_m_0204_r/platform.rtf
@@ -0,0 +1 @@
+Affymetrix 430A and 430B GeneChip Set: Expression data were generated using 430AB array pairs. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on either the Verify UCSC and Verify Ensembl links in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Cb_m_0204_r/processing.rtf b/general/datasets/Cb_m_0204_r/processing.rtf
new file mode 100644
index 0000000..4663b88
--- /dev/null
+++ b/general/datasets/Cb_m_0204_r/processing.rtf
@@ -0,0 +1,29 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each probe signal.
+ - Step 3: We computed the Z scores for each probe signal.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B arrays include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes provide a way to calibrate expression of the A and B arrays to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: We corrected for technical variance introduced by two batches. Means separated by the first batch for each gene are corrected same as means of the second batch.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have modest numbers of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+
+
+
+Probe set data: The original expression values in the Affymetrix CEL files were read into PerfectMatch to generate the normalized PDNN data set.
+
+PDNN values of each array were subsequently normalized to a achieve a mean value of 8 units and a variance of 2 units.
+
+When necessary, we computed the arithmetic mean for technical replicates and treated these as single samples. We then computed the arithmetic mean for the set of 2 to 5 biological replicates for each strain.
+
+
+About the array probe sets names:
+
+
+Most probe sets on the mouse 430A and 430B arrays consist of a total of 22 probes, divided into 11 perfect match(PM) probes and 11 mismatch (MM) controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, several suffix characters that highlight design features, a a final A or B character to specify the array pair member. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene.
+
diff --git a/general/datasets/Cb_m_0204_r/summary.rtf b/general/datasets/Cb_m_0204_r/summary.rtf
new file mode 100644
index 0000000..c32676a
--- /dev/null
+++ b/general/datasets/Cb_m_0204_r/summary.rtf
@@ -0,0 +1 @@
+This October 2004 data freeze provides initial estimates of mRNA expression in brains of adult BXD recombinant inbred mice measured using Affymetrix M430AB microarrays. In contast to the U74Av2 array, this new data set provides broader coverage (~45,000 transcripts) but does not include replicates or as many strains (25 vs 35). Data were generated at UTHSC and the University of Memphis with support from grants from the NIAAA Integrative Neuroscience Initiative on Alcoholism (INIA). Data were processed using the PDNN method of Zhang. To simplify comparison among transforms, PDNN values of each array were adjusted to an average of 8 units and a variance of 2 units.
diff --git a/general/datasets/Cb_m_0204_r/tissue.rtf b/general/datasets/Cb_m_0204_r/tissue.rtf
new file mode 100644
index 0000000..cac878a
--- /dev/null
+++ b/general/datasets/Cb_m_0204_r/tissue.rtf
@@ -0,0 +1,261 @@
+The data set consists of a single batch of Affymetrix mouse expression 430A and 430B GeneChip array pairs. Each AB pair was hybridized in sequence (A array first, B array second) with a pool of brain tissue (forebrain minus olfactory bulb, plus the entire midbrain) taken from three adult animals of closely matched age and the same sex. RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai. All samples were subsequently processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center of Excellence by Thomas R. Sutter and colleagues at the University of Memphis. Before running the main batch of 30 pairs of array, we ran four "test" samples (one male and one female pool from each of the two parental strains, C57BL/6J and DBA/2J). The main set of 30 array pairs includes the same four samples (in other words we have four technical replicates), two F1 hybrid sample (each run two times for a within-batch technical replication), and 22 BXD strains. The data set therefore consists of one male and one female pool from C57BL/6J, DBA/2J, the B6D2F1 hybrid, 11 female BXD samples, and 11 male BXD samples. We should note that the four technical replicates between batches were eventually combined with a correction for a highly significant batch effect. This was done at both the probe and probe set levels to "align" the test batch values with the two main batches. (The ratio of the probe average in the four test arrays to the average of the same probe in the four corresponding main batch arrays was used as a correction factor.) The F1 within-batch technical replicates were simply averaged. In the next batch we will reverse the sex of the BXD samples to achieve a balance with at least 22 BXD strains with one male and one female sample each.
+
+The table below lists the arrays by strain, sex, age, sample identifier, and data results were obtained from the Bioanalytical Core at the University of Memphis. Each array was hybridized to a pool of mRNA from three mice.
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Date |
+
+
+ | B6D2F1 |
+ F |
+ 127 |
+ 919-F1 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ F |
+ 127 |
+ 919-F2 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 920-F1 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 920-F2 |
+ Jan04 |
+
+
+ | C57BL/6J |
+ F |
+ 65 |
+ 903-F1 |
+ Nov03 |
+
+
+ | C57BL/6J |
+ F |
+ 65 |
+ 903-F2 |
+ Jan03 |
+
+
+ | C57BL/6J |
+ M |
+ 66 |
+ 906-F1 |
+ Nov03 |
+
+
+ | C57BL/6J |
+ M |
+ 66 |
+ 906-F2 |
+ Jan04 |
+
+
+ | DBA/2J |
+ F |
+ 60 |
+ 917-F1 |
+ Nov03 |
+
+
+ | DBA/2J |
+ F |
+ 60 |
+ 917-F2 |
+ Jan04 |
+
+
+ | DBA/2J |
+ M |
+ 60 |
+ 918-F1 |
+ Nov03 |
+
+
+ | DBA/2J |
+ M |
+ 60 |
+ 918-F2 |
+ Jan04 |
+
+
+ | BXD1 |
+ F |
+ 95 |
+ 895-F1 |
+ Jan04 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 728-F1 |
+ Jan04 |
+
+
+ | BXD6 |
+ M |
+ 92 |
+ 902-F1 |
+ Jan04 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S167-F1 |
+ Jan04 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 909-F1 |
+ Jan04 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 897-F1 |
+ Jan04 |
+
+
+ | BXD13 |
+ F |
+ 86 |
+ 748-F1 |
+ Jan04 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 912-F1 |
+ Jan04 |
+
+
+ | BXD18 |
+ F |
+ 108 |
+ 771-F1 |
+ Jan04 |
+
+
+ | BXD19 |
+ F |
+ 56 |
+ S236-F1 |
+ Jan04 |
+
+
+ | BXD21 |
+ F |
+ 67 |
+ 740-F1 |
+ Jan04 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 815-F1 |
+ Jan04 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 913-F1 |
+ Jan04 |
+
+
+ | BXD25 |
+ F |
+ 74 |
+ S373-F1 |
+ Jan04 |
+
+
+ | BXD28 |
+ F |
+ 79 |
+ 910-F1 |
+ Jan04 |
+
+
+ | BXD29 |
+ F |
+ 76 |
+ 693-F1 |
+ Jan04 |
+
+
+ | BXD32 |
+ F |
+ 93 |
+ 898-F1 |
+ Jan04 |
+
+
+ | BXD33 |
+ M |
+ 77 |
+ 915-F1 |
+ Jan04 |
+
+
+ | BXD34 |
+ M |
+ 72 |
+ 916-F1 |
+ Jan04 |
+
+
+ | BXD36 |
+ M |
+ 77 |
+ 926-F1 |
+ Jan04 |
+
+
+ | BXD38 |
+ M |
+ 69 |
+ 731-F1 |
+ Jan04 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 936-F1 |
+ Jan04 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Cb_m_0305_m/acknowledgment.rtf b/general/datasets/Cb_m_0305_m/acknowledgment.rtf
new file mode 100644
index 0000000..4fa1990
--- /dev/null
+++ b/general/datasets/Cb_m_0305_m/acknowledgment.rtf
@@ -0,0 +1,15 @@
+Data were generated with funds contributed by members of the UTHSC-SJCRH Cerebellum Transcriptome Profiling Consortium. Our members include:
+
+ - Tom Curran
+ - Dan Goldowitz
+ - Kristin Hamre
+ - Lu Lu
+ - Peter McKinnon
+ - Jim Morgan
+ - Clayton Naeve
+ - Richard Smeyne
+ - Robert Williams
+ - The Center of Genomics and Bioinformatics at UTHSC
+ - The Hartwell Center at SJCRH
+
+
diff --git a/general/datasets/Cb_m_0305_m/cases.rtf b/general/datasets/Cb_m_0305_m/cases.rtf
new file mode 100644
index 0000000..7c1e52c
--- /dev/null
+++ b/general/datasets/Cb_m_0305_m/cases.rtf
@@ -0,0 +1,5 @@
+We have exploited a set of BXD recombinant inbred strains. All BXD lines are derived crossed between C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D parental strains have been almost fully sequenced (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems) and data for 1.75 millioin B vs D SNPs are incorporated into WebQTLs genetic maps for the BXDs. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004).
+
+
+Most BXD animals were generated in-house at the University of Tennessee Health Science Center by Lu Lu and Robert Williams using stock obtained from The Jackson Laboratory between 1999 and 2004. All BXD strains with numbers above 42 are new advanced intecross type BXDs (Peirce et al. 2004) that are current available from UTHSC. Additional cases were provided by Glenn Rosen, John Mountz, and Hui-Chen Hsu. These cases were bred either at The Jackson Laboratory (GR) or at the University of Alabama (JM and HCH).
+
diff --git a/general/datasets/Cb_m_0305_m/notes.rtf b/general/datasets/Cb_m_0305_m/notes.rtf
new file mode 100644
index 0000000..73487ea
--- /dev/null
+++ b/general/datasets/Cb_m_0305_m/notes.rtf
@@ -0,0 +1,5 @@
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets included on the microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium March 2005 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
+
+This text file originally generated by RWW and YHQ, March 21, 2005. Updated by RWW, March 23, 2005; RWW April 8.
diff --git a/general/datasets/Cb_m_0305_m/platform.rtf b/general/datasets/Cb_m_0305_m/platform.rtf
new file mode 100644
index 0000000..39256be
--- /dev/null
+++ b/general/datasets/Cb_m_0305_m/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430A and B array pairs: The 430A and B array pairs consist of 992936 25-nucleotide probes that collectively estimate the expression of approximately 39,000 transcripts. The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequences as the 430 2.0 series. However, we have found that roughy 75000 probes differ from those on A and B arrays and those on the 430 2.0
diff --git a/general/datasets/Cb_m_0305_m/processing.rtf b/general/datasets/Cb_m_0305_m/processing.rtf
new file mode 100644
index 0000000..f7b4668
--- /dev/null
+++ b/general/datasets/Cb_m_0305_m/processing.rtf
@@ -0,0 +1,13 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 104 arrays (all three batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by three large batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all three batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the three batches is the same.
+ - Step 7a: The 430A and 430B arrays include a set of 100 shared probe sets (a total of 2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the 430A and 430B arrays to a common scale. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression correction to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a small offset. The result of this step is that the mean of the 430A expression is fixed at a value of 8, whereas that of the 430B chip is typically reduced to 7. The average of the merged 430A and 430B array data set is approximately 7.5.
+ - Step 7b: We recentered the merged 430A and 430B data sets to a mean of 8 and a standard deviation of 2. This involved reapplying Steps 3 through 5.
+ - Step 8: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
diff --git a/general/datasets/Cb_m_0305_m/summary.rtf b/general/datasets/Cb_m_0305_m/summary.rtf
new file mode 100644
index 0000000..34c7e0d
--- /dev/null
+++ b/general/datasets/Cb_m_0305_m/summary.rtf
@@ -0,0 +1 @@
+This March 2005 data freeze provides estimates of mRNA expression in adult cerebellum of 48 lines of mice including 45 BXD recombinant inbred strains, C57BL/6J, DBA/2J, and F1 hybrids. Data were generated by a consortium of investigators at St. Jude Children's Research Hospital (SJ) and the University of Tennessee Health Science Center (UT). Cerebellar samples were hybridized in small pools (n = 3) to Affymetrix M430A and B arrays. This particular data set was processed using the Microarray Suite 5 (<a data-cke-saved-href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" _blank"="" class="fs14">MAS 5) protocol. To simplify comparisons among transforms, MAS5 values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Cb_m_0305_m/tissue.rtf b/general/datasets/Cb_m_0305_m/tissue.rtf
new file mode 100644
index 0000000..e803a45
--- /dev/null
+++ b/general/datasets/Cb_m_0305_m/tissue.rtf
@@ -0,0 +1,1370 @@
+
+The March 2005 data set consists of a total of 102 array pairs (Affymetrix 430A and 430B) from 49 different genotypes. Each sample consists of whole cerebellum taken from three adult animals of the same age and sex. Two sets of technical replicates (BXD14 n = 2; BXD29 n = 3) were combined before generating group means; giving a total of 101 biologically independent data sets. The two reciprocal F1s (D2B6F1 and B6D2F1) were combined to give a single F1 mean estimate of gene expression. 430A and 430B arrays were processed in three large batches. The first batch (May03 data) consists of 17 samples from 17 strains balanced by sex (8M and 9F). The second batch consists of 29 samples, and includes biological replicates, 2 technical replicates, and data for 9 new strains. The third batch consists of 56 samples, and also includes biological replicates, 2 technical replicates, and data for 15 additional strains.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from both sexes for each strain. Six of 48 genotypes are still represented by single samples: BXD5, BXD13, BXD20, BXD23, BXD27 are female-only strains, whereas BXD25, BXD77, BXD90 are male-only. Ten strains are represented by three independent samples with the following breakdown by sex: C57BL/6J (1F 2M), DBA/2J (2F 1M), B6D2F1 (1F 2M), BXD2 (2F 1M), BXD11 (2F 1M), BXD28 (2F 1M), BXD40 (2F 1M), BXD51 (1F 2M), BXD60 (1F 2M), BXD92 (2F 1M).
+
+The age range of samples is relatively narrow. Only 18 samples were taken from animals older than 99 days and only two samples are older than 7 months of age. BXD11 includes an extra (third) 441-day-old female sample and the BXD28 includes an extra 427-day-old sample.
+
+RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai.
+
+All samples were subsequently processed at the Hartwell Center Affymetrix laboratory at SJCRH by Jay Morris.
+
+
+The table below summarizes information on strain, sex, age, sample name, and batch number.
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Age |
+
+ SampleName
+ |
+
+ BatchID
+ |
+ Source |
+
+
+ | 1 |
+ C57BL/6J |
+ F |
+ 116 |
+
+ R0773C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 2 |
+ C57BL/6J |
+ M |
+ 109 |
+
+ R0054C
+ |
+
+ 1
+ |
+ JAX |
+
+
+ | 3 |
+ C57BL/6J |
+ M |
+ 71 |
+
+ R1450C
+ |
+
+ 3
+ |
+ UTM DG |
+
+
+ | 4 |
+ DBA/2J |
+ F |
+ 71 |
+
+ R0175C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 5 |
+ DBA/2J |
+ F |
+ 91 |
+
+ R0782C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 6 |
+ DBA/2J |
+ M |
+ 62 |
+
+ R1121C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 7 |
+ B6D2F1 |
+ F |
+ 60 |
+
+ R1115C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 8 |
+ B6D2F1 |
+ M |
+ 94 |
+
+ R0347C
+ |
+
+ 1
+ |
+ JAX |
+
+
+ | 9 |
+ B6D2F1 |
+ M |
+ 127 |
+
+ R0766C
+ |
+
+ 2
+ |
+ UTM JB |
+
+
+ | 10 |
+ D2B6F1 |
+ F |
+ 57 |
+
+ R1067C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 11 |
+ D2B6F1 |
+ M |
+ 60 |
+
+ R1387C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 12 |
+ BXD1 |
+ F |
+ 57 |
+
+ R0813C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 13 |
+ BXD1 |
+ M |
+ 181 |
+
+ R1151C
+ |
+
+ 3
+ |
+ UTM JB |
+
+
+ | 14 |
+ BXD2 |
+ F |
+ 142 |
+
+ R0751C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 15 |
+ BXD2 |
+ F |
+ 78 |
+
+ R0774C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 16 |
+ BXD2 |
+ M |
+ 61 |
+
+ R1503C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 17 |
+ BXD5 |
+ F |
+ 56 |
+
+ R0802C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+
+ | 18 |
+ BXD6 |
+ F |
+ 92 |
+
+ R0719C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 19 |
+ BXD6 |
+ M |
+ 92 |
+
+ R0720C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 20 |
+ BXD8 |
+ F |
+ 72 |
+
+ R0173C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 21 |
+ BXD8 |
+ M |
+ 59 |
+
+ R1484C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 22 |
+ BXD9 |
+ F |
+ 86 |
+
+ R0736C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 23 |
+ BXD9 |
+ M |
+ 86 |
+
+ R0737C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 24 |
+ BXD11 |
+ F |
+ 441 |
+
+ R0200C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 25 |
+ BXD11 |
+ F |
+ 97 |
+
+ R0791C
+ |
+
+ 3
+ |
+ UAB |
+
+
+ | 26 |
+ BXD11 |
+ M |
+ 92 |
+
+ R0790C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 27 |
+ BXD12 |
+ F |
+ 130 |
+
+ R0776C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 28 |
+ BXD12 |
+ M |
+ 64 |
+
+ R0756C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 29 |
+ BXD13 |
+ F |
+ 86 |
+
+ R1144C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 30 |
+ BXD14 |
+ F |
+ 190 |
+
+ R0794C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 31 |
+ BXD14 |
+ F |
+ 190 |
+
+ R0794C
+ |
+
+ 3
+ |
+ UAB |
+
+
+ | 32 |
+ BXD14 |
+ M |
+ 91 |
+
+ R0758C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 33 |
+ BXD14 |
+ M |
+ 65 |
+
+ R1130C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+
+ | 34 |
+ BXD15 |
+ F |
+ 60 |
+
+ R1491C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 35 |
+ BXD15 |
+ M |
+ 61 |
+
+ R1499C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 36 |
+ BXD16 |
+ F |
+ 163 |
+
+ R0750C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 37 |
+ BXD16 |
+ M |
+ 61 |
+
+ R1572C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 38 |
+ BXD19 |
+ F |
+ 61 |
+
+ R0772C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 39 |
+ BXD19 |
+ M |
+ 157 |
+
+ R1230C
+ |
+
+ 3
+ |
+ UTM JB |
+
+
+ | 40 |
+ BXD20 |
+ F |
+ 59 |
+
+ R1488C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 41 |
+ BXD21 |
+ F |
+ 116 |
+
+ R0711C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 42 |
+ BXD21 |
+ M |
+ 64 |
+
+ R0803C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 43 |
+ BXD22 |
+ F |
+ 65 |
+
+ R0174C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 44 |
+ BXD22 |
+ M |
+ 59 |
+
+ R1489C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 45 |
+ BXD23 |
+ F |
+ 88 |
+
+ R0814C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 46 |
+ BXD24 |
+ F |
+ 71 |
+
+ R0805C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 47 |
+ BXD24 |
+ M |
+ 71 |
+
+ R0759C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 48 |
+ BXD25 |
+ M |
+ 90 |
+
+ R0429C
+ |
+
+ 1
+ |
+ UTM RW |
+
+
+ | 49 |
+ BXD27 |
+ F |
+ 60 |
+
+ R1496C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 50 |
+ BXD28 |
+ F |
+ 113 |
+
+ R0785C
+ |
+
+ 2
+ |
+ UTM RW |
+
+
+ | 51 |
+ BXD28 |
+ M |
+ 79 |
+
+ R0739C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 52 |
+ BXD29 |
+ F |
+ 82 |
+
+ R0777C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 53 |
+ BXD29 |
+ M |
+ 76 |
+
+ R0714C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 54 |
+ BXD29 |
+ M |
+ 76 |
+
+ R0714C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 55 |
+ BXD29 |
+ M |
+ 76 |
+
+ R0714C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 56 |
+ BXD31 |
+ F |
+ 142 |
+
+ R0816C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 57 |
+ BXD31 |
+ M |
+ 61 |
+
+ R1142C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 58 |
+ BXD32 |
+ F |
+ 62 |
+
+ R0778C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 59 |
+ BXD32 |
+ M |
+ 218 |
+
+ R0786C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 60 |
+ BXD33 |
+ F |
+ 184 |
+
+ R0793C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 61 |
+ BXD33 |
+ M |
+ 124 |
+
+ R0715C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 62 |
+ BXD34 |
+ F |
+ 56 |
+
+ R0725C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 63 |
+ BXD34 |
+ M |
+ 91 |
+
+ R0789C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+
+ | 64 |
+ BXD36 |
+ F |
+ 64 |
+
+ R1667C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 65 |
+ BXD36 |
+ M |
+ 61 |
+
+ R1212C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 66 |
+ BXD38 |
+ F |
+ 55 |
+
+ R0781C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 67 |
+ BXD38 |
+ M |
+ 65 |
+
+ R0761C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 68 |
+ BXD39 |
+ F |
+ 59 |
+
+ R1490C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 69 |
+ BXD39 |
+ M |
+ 165 |
+
+ R0723C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 70 |
+ BXD40 |
+ F |
+ 56 |
+
+ R0718C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 71 |
+ BXD40 |
+ M |
+ 73 |
+
+ R0812C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 72 |
+ BXD42 |
+ F |
+ 100 |
+
+ R0799C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 73 |
+ BXD42 |
+ M |
+ 97 |
+
+ R0709C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 74 |
+ BXD43 |
+ F |
+ 61 |
+
+ R1200C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 75 |
+ BXD43 |
+ M |
+ 63 |
+
+ R1182C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 76 |
+ BXD44 |
+ F |
+ 61 |
+
+ R1188C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 77 |
+ BXD44 |
+ M |
+ 58 |
+
+ R1073C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 78 |
+ BXD45 |
+ F |
+ 63 |
+
+ R1404C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 79 |
+ BXD45 |
+ M |
+ 93 |
+
+ R1506C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 80 |
+ BXD48 |
+ F |
+ 64 |
+
+ R1158C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 81 |
+ BXD48 |
+ M |
+ 65 |
+
+ R1165C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 82 |
+ BXD51 |
+ F |
+ 66 |
+
+ R1666C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 83 |
+ BXD51 |
+ M |
+ 62 |
+
+ R1180C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 84 |
+ BXD51 |
+ M |
+ 79 |
+
+ R1671C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 85 |
+ BXD60 |
+ F |
+ 64 |
+
+ R1160C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 86 |
+ BXD60 |
+ M |
+ 61 |
+
+ R1103C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 87 |
+ BXD60 |
+ M |
+ 99 |
+
+ R1669C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 88 |
+ BXD62 |
+ M |
+ 61 |
+
+ R1149C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 89 |
+ BXD62 |
+ M |
+ 60 |
+
+ R1668C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 90 |
+ BXD69 |
+ F |
+ 60 |
+
+ R1440C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 91 |
+ BXD69 |
+ M |
+ 64 |
+
+ R1197C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 92 |
+ BXD73 |
+ F |
+ 60 |
+
+ R1276C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 93 |
+ BXD73 |
+ M |
+ 77 |
+
+ R1665C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 94 |
+ BXD77 |
+ M |
+ 62 |
+
+ R1424C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 95 |
+ BXD85 |
+ F |
+ 79 |
+
+ R1486C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 96 |
+ BXD85 |
+ M |
+ 79 |
+
+ R1487C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 97 |
+ BXD86 |
+ F |
+ 58 |
+
+ R1408C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 98 |
+ BXD86 |
+ M |
+ 58 |
+
+ R1412C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 99 |
+ BXD90 |
+ M |
+ 74 |
+
+ R1664C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 100 |
+ BXD92 |
+ F |
+ 62 |
+
+ R1391C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 101 |
+ BXD92 |
+ F |
+ 63 |
+
+ R1670C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 102 |
+ BXD92 |
+ M |
+ 59 |
+
+ R1308C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Cb_m_0305_p/acknowledgment.rtf b/general/datasets/Cb_m_0305_p/acknowledgment.rtf
new file mode 100644
index 0000000..4fa1990
--- /dev/null
+++ b/general/datasets/Cb_m_0305_p/acknowledgment.rtf
@@ -0,0 +1,15 @@
+Data were generated with funds contributed by members of the UTHSC-SJCRH Cerebellum Transcriptome Profiling Consortium. Our members include:
+
+ - Tom Curran
+ - Dan Goldowitz
+ - Kristin Hamre
+ - Lu Lu
+ - Peter McKinnon
+ - Jim Morgan
+ - Clayton Naeve
+ - Richard Smeyne
+ - Robert Williams
+ - The Center of Genomics and Bioinformatics at UTHSC
+ - The Hartwell Center at SJCRH
+
+
diff --git a/general/datasets/Cb_m_0305_p/cases.rtf b/general/datasets/Cb_m_0305_p/cases.rtf
new file mode 100644
index 0000000..7c1e52c
--- /dev/null
+++ b/general/datasets/Cb_m_0305_p/cases.rtf
@@ -0,0 +1,5 @@
+We have exploited a set of BXD recombinant inbred strains. All BXD lines are derived crossed between C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D parental strains have been almost fully sequenced (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems) and data for 1.75 millioin B vs D SNPs are incorporated into WebQTLs genetic maps for the BXDs. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004).
+
+
+Most BXD animals were generated in-house at the University of Tennessee Health Science Center by Lu Lu and Robert Williams using stock obtained from The Jackson Laboratory between 1999 and 2004. All BXD strains with numbers above 42 are new advanced intecross type BXDs (Peirce et al. 2004) that are current available from UTHSC. Additional cases were provided by Glenn Rosen, John Mountz, and Hui-Chen Hsu. These cases were bred either at The Jackson Laboratory (GR) or at the University of Alabama (JM and HCH).
+
diff --git a/general/datasets/Cb_m_0305_p/notes.rtf b/general/datasets/Cb_m_0305_p/notes.rtf
new file mode 100644
index 0000000..73487ea
--- /dev/null
+++ b/general/datasets/Cb_m_0305_p/notes.rtf
@@ -0,0 +1,5 @@
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets included on the microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium March 2005 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
+
+This text file originally generated by RWW and YHQ, March 21, 2005. Updated by RWW, March 23, 2005; RWW April 8.
diff --git a/general/datasets/Cb_m_0305_p/platform.rtf b/general/datasets/Cb_m_0305_p/platform.rtf
new file mode 100644
index 0000000..39256be
--- /dev/null
+++ b/general/datasets/Cb_m_0305_p/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430A and B array pairs: The 430A and B array pairs consist of 992936 25-nucleotide probes that collectively estimate the expression of approximately 39,000 transcripts. The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequences as the 430 2.0 series. However, we have found that roughy 75000 probes differ from those on A and B arrays and those on the 430 2.0
diff --git a/general/datasets/Cb_m_0305_p/processing.rtf b/general/datasets/Cb_m_0305_p/processing.rtf
new file mode 100644
index 0000000..f7b4668
--- /dev/null
+++ b/general/datasets/Cb_m_0305_p/processing.rtf
@@ -0,0 +1,13 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 104 arrays (all three batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by three large batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all three batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the three batches is the same.
+ - Step 7a: The 430A and 430B arrays include a set of 100 shared probe sets (a total of 2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the 430A and 430B arrays to a common scale. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression correction to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a small offset. The result of this step is that the mean of the 430A expression is fixed at a value of 8, whereas that of the 430B chip is typically reduced to 7. The average of the merged 430A and 430B array data set is approximately 7.5.
+ - Step 7b: We recentered the merged 430A and 430B data sets to a mean of 8 and a standard deviation of 2. This involved reapplying Steps 3 through 5.
+ - Step 8: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
diff --git a/general/datasets/Cb_m_0305_p/summary.rtf b/general/datasets/Cb_m_0305_p/summary.rtf
new file mode 100644
index 0000000..34c7e0d
--- /dev/null
+++ b/general/datasets/Cb_m_0305_p/summary.rtf
@@ -0,0 +1 @@
+This March 2005 data freeze provides estimates of mRNA expression in adult cerebellum of 48 lines of mice including 45 BXD recombinant inbred strains, C57BL/6J, DBA/2J, and F1 hybrids. Data were generated by a consortium of investigators at St. Jude Children's Research Hospital (SJ) and the University of Tennessee Health Science Center (UT). Cerebellar samples were hybridized in small pools (n = 3) to Affymetrix M430A and B arrays. This particular data set was processed using the Microarray Suite 5 (<a data-cke-saved-href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" _blank"="" class="fs14">MAS 5) protocol. To simplify comparisons among transforms, MAS5 values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Cb_m_0305_p/tissue.rtf b/general/datasets/Cb_m_0305_p/tissue.rtf
new file mode 100644
index 0000000..e803a45
--- /dev/null
+++ b/general/datasets/Cb_m_0305_p/tissue.rtf
@@ -0,0 +1,1370 @@
+
+The March 2005 data set consists of a total of 102 array pairs (Affymetrix 430A and 430B) from 49 different genotypes. Each sample consists of whole cerebellum taken from three adult animals of the same age and sex. Two sets of technical replicates (BXD14 n = 2; BXD29 n = 3) were combined before generating group means; giving a total of 101 biologically independent data sets. The two reciprocal F1s (D2B6F1 and B6D2F1) were combined to give a single F1 mean estimate of gene expression. 430A and 430B arrays were processed in three large batches. The first batch (May03 data) consists of 17 samples from 17 strains balanced by sex (8M and 9F). The second batch consists of 29 samples, and includes biological replicates, 2 technical replicates, and data for 9 new strains. The third batch consists of 56 samples, and also includes biological replicates, 2 technical replicates, and data for 15 additional strains.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from both sexes for each strain. Six of 48 genotypes are still represented by single samples: BXD5, BXD13, BXD20, BXD23, BXD27 are female-only strains, whereas BXD25, BXD77, BXD90 are male-only. Ten strains are represented by three independent samples with the following breakdown by sex: C57BL/6J (1F 2M), DBA/2J (2F 1M), B6D2F1 (1F 2M), BXD2 (2F 1M), BXD11 (2F 1M), BXD28 (2F 1M), BXD40 (2F 1M), BXD51 (1F 2M), BXD60 (1F 2M), BXD92 (2F 1M).
+
+The age range of samples is relatively narrow. Only 18 samples were taken from animals older than 99 days and only two samples are older than 7 months of age. BXD11 includes an extra (third) 441-day-old female sample and the BXD28 includes an extra 427-day-old sample.
+
+RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai.
+
+All samples were subsequently processed at the Hartwell Center Affymetrix laboratory at SJCRH by Jay Morris.
+
+
+The table below summarizes information on strain, sex, age, sample name, and batch number.
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Age |
+
+ SampleName
+ |
+
+ BatchID
+ |
+ Source |
+
+
+ | 1 |
+ C57BL/6J |
+ F |
+ 116 |
+
+ R0773C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 2 |
+ C57BL/6J |
+ M |
+ 109 |
+
+ R0054C
+ |
+
+ 1
+ |
+ JAX |
+
+
+ | 3 |
+ C57BL/6J |
+ M |
+ 71 |
+
+ R1450C
+ |
+
+ 3
+ |
+ UTM DG |
+
+
+ | 4 |
+ DBA/2J |
+ F |
+ 71 |
+
+ R0175C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 5 |
+ DBA/2J |
+ F |
+ 91 |
+
+ R0782C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 6 |
+ DBA/2J |
+ M |
+ 62 |
+
+ R1121C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 7 |
+ B6D2F1 |
+ F |
+ 60 |
+
+ R1115C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 8 |
+ B6D2F1 |
+ M |
+ 94 |
+
+ R0347C
+ |
+
+ 1
+ |
+ JAX |
+
+
+ | 9 |
+ B6D2F1 |
+ M |
+ 127 |
+
+ R0766C
+ |
+
+ 2
+ |
+ UTM JB |
+
+
+ | 10 |
+ D2B6F1 |
+ F |
+ 57 |
+
+ R1067C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 11 |
+ D2B6F1 |
+ M |
+ 60 |
+
+ R1387C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 12 |
+ BXD1 |
+ F |
+ 57 |
+
+ R0813C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 13 |
+ BXD1 |
+ M |
+ 181 |
+
+ R1151C
+ |
+
+ 3
+ |
+ UTM JB |
+
+
+ | 14 |
+ BXD2 |
+ F |
+ 142 |
+
+ R0751C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 15 |
+ BXD2 |
+ F |
+ 78 |
+
+ R0774C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 16 |
+ BXD2 |
+ M |
+ 61 |
+
+ R1503C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 17 |
+ BXD5 |
+ F |
+ 56 |
+
+ R0802C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+
+ | 18 |
+ BXD6 |
+ F |
+ 92 |
+
+ R0719C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 19 |
+ BXD6 |
+ M |
+ 92 |
+
+ R0720C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 20 |
+ BXD8 |
+ F |
+ 72 |
+
+ R0173C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 21 |
+ BXD8 |
+ M |
+ 59 |
+
+ R1484C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 22 |
+ BXD9 |
+ F |
+ 86 |
+
+ R0736C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 23 |
+ BXD9 |
+ M |
+ 86 |
+
+ R0737C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 24 |
+ BXD11 |
+ F |
+ 441 |
+
+ R0200C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 25 |
+ BXD11 |
+ F |
+ 97 |
+
+ R0791C
+ |
+
+ 3
+ |
+ UAB |
+
+
+ | 26 |
+ BXD11 |
+ M |
+ 92 |
+
+ R0790C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 27 |
+ BXD12 |
+ F |
+ 130 |
+
+ R0776C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 28 |
+ BXD12 |
+ M |
+ 64 |
+
+ R0756C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 29 |
+ BXD13 |
+ F |
+ 86 |
+
+ R1144C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 30 |
+ BXD14 |
+ F |
+ 190 |
+
+ R0794C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 31 |
+ BXD14 |
+ F |
+ 190 |
+
+ R0794C
+ |
+
+ 3
+ |
+ UAB |
+
+
+ | 32 |
+ BXD14 |
+ M |
+ 91 |
+
+ R0758C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 33 |
+ BXD14 |
+ M |
+ 65 |
+
+ R1130C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+
+ | 34 |
+ BXD15 |
+ F |
+ 60 |
+
+ R1491C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 35 |
+ BXD15 |
+ M |
+ 61 |
+
+ R1499C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 36 |
+ BXD16 |
+ F |
+ 163 |
+
+ R0750C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 37 |
+ BXD16 |
+ M |
+ 61 |
+
+ R1572C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 38 |
+ BXD19 |
+ F |
+ 61 |
+
+ R0772C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 39 |
+ BXD19 |
+ M |
+ 157 |
+
+ R1230C
+ |
+
+ 3
+ |
+ UTM JB |
+
+
+ | 40 |
+ BXD20 |
+ F |
+ 59 |
+
+ R1488C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 41 |
+ BXD21 |
+ F |
+ 116 |
+
+ R0711C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 42 |
+ BXD21 |
+ M |
+ 64 |
+
+ R0803C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 43 |
+ BXD22 |
+ F |
+ 65 |
+
+ R0174C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 44 |
+ BXD22 |
+ M |
+ 59 |
+
+ R1489C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 45 |
+ BXD23 |
+ F |
+ 88 |
+
+ R0814C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 46 |
+ BXD24 |
+ F |
+ 71 |
+
+ R0805C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 47 |
+ BXD24 |
+ M |
+ 71 |
+
+ R0759C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 48 |
+ BXD25 |
+ M |
+ 90 |
+
+ R0429C
+ |
+
+ 1
+ |
+ UTM RW |
+
+
+ | 49 |
+ BXD27 |
+ F |
+ 60 |
+
+ R1496C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 50 |
+ BXD28 |
+ F |
+ 113 |
+
+ R0785C
+ |
+
+ 2
+ |
+ UTM RW |
+
+
+ | 51 |
+ BXD28 |
+ M |
+ 79 |
+
+ R0739C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 52 |
+ BXD29 |
+ F |
+ 82 |
+
+ R0777C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 53 |
+ BXD29 |
+ M |
+ 76 |
+
+ R0714C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 54 |
+ BXD29 |
+ M |
+ 76 |
+
+ R0714C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 55 |
+ BXD29 |
+ M |
+ 76 |
+
+ R0714C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 56 |
+ BXD31 |
+ F |
+ 142 |
+
+ R0816C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 57 |
+ BXD31 |
+ M |
+ 61 |
+
+ R1142C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 58 |
+ BXD32 |
+ F |
+ 62 |
+
+ R0778C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 59 |
+ BXD32 |
+ M |
+ 218 |
+
+ R0786C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 60 |
+ BXD33 |
+ F |
+ 184 |
+
+ R0793C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 61 |
+ BXD33 |
+ M |
+ 124 |
+
+ R0715C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 62 |
+ BXD34 |
+ F |
+ 56 |
+
+ R0725C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 63 |
+ BXD34 |
+ M |
+ 91 |
+
+ R0789C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+
+ | 64 |
+ BXD36 |
+ F |
+ 64 |
+
+ R1667C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 65 |
+ BXD36 |
+ M |
+ 61 |
+
+ R1212C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 66 |
+ BXD38 |
+ F |
+ 55 |
+
+ R0781C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 67 |
+ BXD38 |
+ M |
+ 65 |
+
+ R0761C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 68 |
+ BXD39 |
+ F |
+ 59 |
+
+ R1490C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 69 |
+ BXD39 |
+ M |
+ 165 |
+
+ R0723C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 70 |
+ BXD40 |
+ F |
+ 56 |
+
+ R0718C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 71 |
+ BXD40 |
+ M |
+ 73 |
+
+ R0812C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 72 |
+ BXD42 |
+ F |
+ 100 |
+
+ R0799C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 73 |
+ BXD42 |
+ M |
+ 97 |
+
+ R0709C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 74 |
+ BXD43 |
+ F |
+ 61 |
+
+ R1200C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 75 |
+ BXD43 |
+ M |
+ 63 |
+
+ R1182C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 76 |
+ BXD44 |
+ F |
+ 61 |
+
+ R1188C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 77 |
+ BXD44 |
+ M |
+ 58 |
+
+ R1073C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 78 |
+ BXD45 |
+ F |
+ 63 |
+
+ R1404C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 79 |
+ BXD45 |
+ M |
+ 93 |
+
+ R1506C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 80 |
+ BXD48 |
+ F |
+ 64 |
+
+ R1158C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 81 |
+ BXD48 |
+ M |
+ 65 |
+
+ R1165C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 82 |
+ BXD51 |
+ F |
+ 66 |
+
+ R1666C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 83 |
+ BXD51 |
+ M |
+ 62 |
+
+ R1180C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 84 |
+ BXD51 |
+ M |
+ 79 |
+
+ R1671C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 85 |
+ BXD60 |
+ F |
+ 64 |
+
+ R1160C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 86 |
+ BXD60 |
+ M |
+ 61 |
+
+ R1103C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 87 |
+ BXD60 |
+ M |
+ 99 |
+
+ R1669C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 88 |
+ BXD62 |
+ M |
+ 61 |
+
+ R1149C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 89 |
+ BXD62 |
+ M |
+ 60 |
+
+ R1668C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 90 |
+ BXD69 |
+ F |
+ 60 |
+
+ R1440C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 91 |
+ BXD69 |
+ M |
+ 64 |
+
+ R1197C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 92 |
+ BXD73 |
+ F |
+ 60 |
+
+ R1276C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 93 |
+ BXD73 |
+ M |
+ 77 |
+
+ R1665C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 94 |
+ BXD77 |
+ M |
+ 62 |
+
+ R1424C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 95 |
+ BXD85 |
+ F |
+ 79 |
+
+ R1486C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 96 |
+ BXD85 |
+ M |
+ 79 |
+
+ R1487C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 97 |
+ BXD86 |
+ F |
+ 58 |
+
+ R1408C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 98 |
+ BXD86 |
+ M |
+ 58 |
+
+ R1412C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 99 |
+ BXD90 |
+ M |
+ 74 |
+
+ R1664C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 100 |
+ BXD92 |
+ F |
+ 62 |
+
+ R1391C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 101 |
+ BXD92 |
+ F |
+ 63 |
+
+ R1670C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 102 |
+ BXD92 |
+ M |
+ 59 |
+
+ R1308C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Cb_m_0305_r/acknowledgment.rtf b/general/datasets/Cb_m_0305_r/acknowledgment.rtf
new file mode 100644
index 0000000..4fa1990
--- /dev/null
+++ b/general/datasets/Cb_m_0305_r/acknowledgment.rtf
@@ -0,0 +1,15 @@
+Data were generated with funds contributed by members of the UTHSC-SJCRH Cerebellum Transcriptome Profiling Consortium. Our members include:
+
+ - Tom Curran
+ - Dan Goldowitz
+ - Kristin Hamre
+ - Lu Lu
+ - Peter McKinnon
+ - Jim Morgan
+ - Clayton Naeve
+ - Richard Smeyne
+ - Robert Williams
+ - The Center of Genomics and Bioinformatics at UTHSC
+ - The Hartwell Center at SJCRH
+
+
diff --git a/general/datasets/Cb_m_0305_r/cases.rtf b/general/datasets/Cb_m_0305_r/cases.rtf
new file mode 100644
index 0000000..7c1e52c
--- /dev/null
+++ b/general/datasets/Cb_m_0305_r/cases.rtf
@@ -0,0 +1,5 @@
+We have exploited a set of BXD recombinant inbred strains. All BXD lines are derived crossed between C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D parental strains have been almost fully sequenced (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems) and data for 1.75 millioin B vs D SNPs are incorporated into WebQTLs genetic maps for the BXDs. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004).
+
+
+Most BXD animals were generated in-house at the University of Tennessee Health Science Center by Lu Lu and Robert Williams using stock obtained from The Jackson Laboratory between 1999 and 2004. All BXD strains with numbers above 42 are new advanced intecross type BXDs (Peirce et al. 2004) that are current available from UTHSC. Additional cases were provided by Glenn Rosen, John Mountz, and Hui-Chen Hsu. These cases were bred either at The Jackson Laboratory (GR) or at the University of Alabama (JM and HCH).
+
diff --git a/general/datasets/Cb_m_0305_r/notes.rtf b/general/datasets/Cb_m_0305_r/notes.rtf
new file mode 100644
index 0000000..73487ea
--- /dev/null
+++ b/general/datasets/Cb_m_0305_r/notes.rtf
@@ -0,0 +1,5 @@
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets included on the microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium March 2005 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
+
+This text file originally generated by RWW and YHQ, March 21, 2005. Updated by RWW, March 23, 2005; RWW April 8.
diff --git a/general/datasets/Cb_m_0305_r/platform.rtf b/general/datasets/Cb_m_0305_r/platform.rtf
new file mode 100644
index 0000000..39256be
--- /dev/null
+++ b/general/datasets/Cb_m_0305_r/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430A and B array pairs: The 430A and B array pairs consist of 992936 25-nucleotide probes that collectively estimate the expression of approximately 39,000 transcripts. The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequences as the 430 2.0 series. However, we have found that roughy 75000 probes differ from those on A and B arrays and those on the 430 2.0
diff --git a/general/datasets/Cb_m_0305_r/processing.rtf b/general/datasets/Cb_m_0305_r/processing.rtf
new file mode 100644
index 0000000..f7b4668
--- /dev/null
+++ b/general/datasets/Cb_m_0305_r/processing.rtf
@@ -0,0 +1,13 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 104 arrays (all three batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We corrected for technical variance introduced by three large batches at the probe level. To do this we determined the ratio of the batch mean to the mean of all three batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each of the three batches is the same.
+ - Step 7a: The 430A and 430B arrays include a set of 100 shared probe sets (a total of 2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the 430A and 430B arrays to a common scale. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression correction to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a small offset. The result of this step is that the mean of the 430A expression is fixed at a value of 8, whereas that of the 430B chip is typically reduced to 7. The average of the merged 430A and 430B array data set is approximately 7.5.
+ - Step 7b: We recentered the merged 430A and 430B data sets to a mean of 8 and a standard deviation of 2. This involved reapplying Steps 3 through 5.
+ - Step 8: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
diff --git a/general/datasets/Cb_m_0305_r/summary.rtf b/general/datasets/Cb_m_0305_r/summary.rtf
new file mode 100644
index 0000000..34c7e0d
--- /dev/null
+++ b/general/datasets/Cb_m_0305_r/summary.rtf
@@ -0,0 +1 @@
+This March 2005 data freeze provides estimates of mRNA expression in adult cerebellum of 48 lines of mice including 45 BXD recombinant inbred strains, C57BL/6J, DBA/2J, and F1 hybrids. Data were generated by a consortium of investigators at St. Jude Children's Research Hospital (SJ) and the University of Tennessee Health Science Center (UT). Cerebellar samples were hybridized in small pools (n = 3) to Affymetrix M430A and B arrays. This particular data set was processed using the Microarray Suite 5 (<a data-cke-saved-href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" _blank"="" class="fs14">MAS 5) protocol. To simplify comparisons among transforms, MAS5 values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Cb_m_0305_r/tissue.rtf b/general/datasets/Cb_m_0305_r/tissue.rtf
new file mode 100644
index 0000000..e803a45
--- /dev/null
+++ b/general/datasets/Cb_m_0305_r/tissue.rtf
@@ -0,0 +1,1370 @@
+
+The March 2005 data set consists of a total of 102 array pairs (Affymetrix 430A and 430B) from 49 different genotypes. Each sample consists of whole cerebellum taken from three adult animals of the same age and sex. Two sets of technical replicates (BXD14 n = 2; BXD29 n = 3) were combined before generating group means; giving a total of 101 biologically independent data sets. The two reciprocal F1s (D2B6F1 and B6D2F1) were combined to give a single F1 mean estimate of gene expression. 430A and 430B arrays were processed in three large batches. The first batch (May03 data) consists of 17 samples from 17 strains balanced by sex (8M and 9F). The second batch consists of 29 samples, and includes biological replicates, 2 technical replicates, and data for 9 new strains. The third batch consists of 56 samples, and also includes biological replicates, 2 technical replicates, and data for 15 additional strains.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from both sexes for each strain. Six of 48 genotypes are still represented by single samples: BXD5, BXD13, BXD20, BXD23, BXD27 are female-only strains, whereas BXD25, BXD77, BXD90 are male-only. Ten strains are represented by three independent samples with the following breakdown by sex: C57BL/6J (1F 2M), DBA/2J (2F 1M), B6D2F1 (1F 2M), BXD2 (2F 1M), BXD11 (2F 1M), BXD28 (2F 1M), BXD40 (2F 1M), BXD51 (1F 2M), BXD60 (1F 2M), BXD92 (2F 1M).
+
+The age range of samples is relatively narrow. Only 18 samples were taken from animals older than 99 days and only two samples are older than 7 months of age. BXD11 includes an extra (third) 441-day-old female sample and the BXD28 includes an extra 427-day-old sample.
+
+RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai.
+
+All samples were subsequently processed at the Hartwell Center Affymetrix laboratory at SJCRH by Jay Morris.
+
+
+The table below summarizes information on strain, sex, age, sample name, and batch number.
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Age |
+
+ SampleName
+ |
+
+ BatchID
+ |
+ Source |
+
+
+ | 1 |
+ C57BL/6J |
+ F |
+ 116 |
+
+ R0773C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 2 |
+ C57BL/6J |
+ M |
+ 109 |
+
+ R0054C
+ |
+
+ 1
+ |
+ JAX |
+
+
+ | 3 |
+ C57BL/6J |
+ M |
+ 71 |
+
+ R1450C
+ |
+
+ 3
+ |
+ UTM DG |
+
+
+ | 4 |
+ DBA/2J |
+ F |
+ 71 |
+
+ R0175C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 5 |
+ DBA/2J |
+ F |
+ 91 |
+
+ R0782C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 6 |
+ DBA/2J |
+ M |
+ 62 |
+
+ R1121C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 7 |
+ B6D2F1 |
+ F |
+ 60 |
+
+ R1115C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 8 |
+ B6D2F1 |
+ M |
+ 94 |
+
+ R0347C
+ |
+
+ 1
+ |
+ JAX |
+
+
+ | 9 |
+ B6D2F1 |
+ M |
+ 127 |
+
+ R0766C
+ |
+
+ 2
+ |
+ UTM JB |
+
+
+ | 10 |
+ D2B6F1 |
+ F |
+ 57 |
+
+ R1067C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 11 |
+ D2B6F1 |
+ M |
+ 60 |
+
+ R1387C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 12 |
+ BXD1 |
+ F |
+ 57 |
+
+ R0813C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 13 |
+ BXD1 |
+ M |
+ 181 |
+
+ R1151C
+ |
+
+ 3
+ |
+ UTM JB |
+
+
+ | 14 |
+ BXD2 |
+ F |
+ 142 |
+
+ R0751C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 15 |
+ BXD2 |
+ F |
+ 78 |
+
+ R0774C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 16 |
+ BXD2 |
+ M |
+ 61 |
+
+ R1503C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 17 |
+ BXD5 |
+ F |
+ 56 |
+
+ R0802C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+
+ | 18 |
+ BXD6 |
+ F |
+ 92 |
+
+ R0719C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 19 |
+ BXD6 |
+ M |
+ 92 |
+
+ R0720C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 20 |
+ BXD8 |
+ F |
+ 72 |
+
+ R0173C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 21 |
+ BXD8 |
+ M |
+ 59 |
+
+ R1484C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 22 |
+ BXD9 |
+ F |
+ 86 |
+
+ R0736C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 23 |
+ BXD9 |
+ M |
+ 86 |
+
+ R0737C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 24 |
+ BXD11 |
+ F |
+ 441 |
+
+ R0200C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 25 |
+ BXD11 |
+ F |
+ 97 |
+
+ R0791C
+ |
+
+ 3
+ |
+ UAB |
+
+
+ | 26 |
+ BXD11 |
+ M |
+ 92 |
+
+ R0790C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 27 |
+ BXD12 |
+ F |
+ 130 |
+
+ R0776C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 28 |
+ BXD12 |
+ M |
+ 64 |
+
+ R0756C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 29 |
+ BXD13 |
+ F |
+ 86 |
+
+ R1144C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 30 |
+ BXD14 |
+ F |
+ 190 |
+
+ R0794C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 31 |
+ BXD14 |
+ F |
+ 190 |
+
+ R0794C
+ |
+
+ 3
+ |
+ UAB |
+
+
+ | 32 |
+ BXD14 |
+ M |
+ 91 |
+
+ R0758C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 33 |
+ BXD14 |
+ M |
+ 65 |
+
+ R1130C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+
+ | 34 |
+ BXD15 |
+ F |
+ 60 |
+
+ R1491C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 35 |
+ BXD15 |
+ M |
+ 61 |
+
+ R1499C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 36 |
+ BXD16 |
+ F |
+ 163 |
+
+ R0750C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 37 |
+ BXD16 |
+ M |
+ 61 |
+
+ R1572C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 38 |
+ BXD19 |
+ F |
+ 61 |
+
+ R0772C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 39 |
+ BXD19 |
+ M |
+ 157 |
+
+ R1230C
+ |
+
+ 3
+ |
+ UTM JB |
+
+
+ | 40 |
+ BXD20 |
+ F |
+ 59 |
+
+ R1488C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 41 |
+ BXD21 |
+ F |
+ 116 |
+
+ R0711C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 42 |
+ BXD21 |
+ M |
+ 64 |
+
+ R0803C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 43 |
+ BXD22 |
+ F |
+ 65 |
+
+ R0174C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 44 |
+ BXD22 |
+ M |
+ 59 |
+
+ R1489C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 45 |
+ BXD23 |
+ F |
+ 88 |
+
+ R0814C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 46 |
+ BXD24 |
+ F |
+ 71 |
+
+ R0805C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 47 |
+ BXD24 |
+ M |
+ 71 |
+
+ R0759C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 48 |
+ BXD25 |
+ M |
+ 90 |
+
+ R0429C
+ |
+
+ 1
+ |
+ UTM RW |
+
+
+ | 49 |
+ BXD27 |
+ F |
+ 60 |
+
+ R1496C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 50 |
+ BXD28 |
+ F |
+ 113 |
+
+ R0785C
+ |
+
+ 2
+ |
+ UTM RW |
+
+
+ | 51 |
+ BXD28 |
+ M |
+ 79 |
+
+ R0739C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 52 |
+ BXD29 |
+ F |
+ 82 |
+
+ R0777C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 53 |
+ BXD29 |
+ M |
+ 76 |
+
+ R0714C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 54 |
+ BXD29 |
+ M |
+ 76 |
+
+ R0714C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 55 |
+ BXD29 |
+ M |
+ 76 |
+
+ R0714C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 56 |
+ BXD31 |
+ F |
+ 142 |
+
+ R0816C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 57 |
+ BXD31 |
+ M |
+ 61 |
+
+ R1142C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 58 |
+ BXD32 |
+ F |
+ 62 |
+
+ R0778C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 59 |
+ BXD32 |
+ M |
+ 218 |
+
+ R0786C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 60 |
+ BXD33 |
+ F |
+ 184 |
+
+ R0793C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 61 |
+ BXD33 |
+ M |
+ 124 |
+
+ R0715C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 62 |
+ BXD34 |
+ F |
+ 56 |
+
+ R0725C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 63 |
+ BXD34 |
+ M |
+ 91 |
+
+ R0789C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+
+ | 64 |
+ BXD36 |
+ F |
+ 64 |
+
+ R1667C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 65 |
+ BXD36 |
+ M |
+ 61 |
+
+ R1212C
+ |
+
+ 3
+ |
+ UMemphis |
+
+
+ | 66 |
+ BXD38 |
+ F |
+ 55 |
+
+ R0781C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 67 |
+ BXD38 |
+ M |
+ 65 |
+
+ R0761C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 68 |
+ BXD39 |
+ F |
+ 59 |
+
+ R1490C
+ |
+
+ 3
+ |
+ HarvardU GR |
+
+
+ | 69 |
+ BXD39 |
+ M |
+ 165 |
+
+ R0723C
+ |
+
+ 1
+ |
+ UAB |
+
+
+ | 70 |
+ BXD40 |
+ F |
+ 56 |
+
+ R0718C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 71 |
+ BXD40 |
+ M |
+ 73 |
+
+ R0812C
+ |
+
+ 2
+ |
+ UMemphis |
+
+
+ | 72 |
+ BXD42 |
+ F |
+ 100 |
+
+ R0799C
+ |
+
+ 2
+ |
+ UAB |
+
+
+ | 73 |
+ BXD42 |
+ M |
+ 97 |
+
+ R0709C
+ |
+
+ 1
+ |
+ UMemphis |
+
+
+ | 74 |
+ BXD43 |
+ F |
+ 61 |
+
+ R1200C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 75 |
+ BXD43 |
+ M |
+ 63 |
+
+ R1182C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 76 |
+ BXD44 |
+ F |
+ 61 |
+
+ R1188C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 77 |
+ BXD44 |
+ M |
+ 58 |
+
+ R1073C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 78 |
+ BXD45 |
+ F |
+ 63 |
+
+ R1404C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 79 |
+ BXD45 |
+ M |
+ 93 |
+
+ R1506C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 80 |
+ BXD48 |
+ F |
+ 64 |
+
+ R1158C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 81 |
+ BXD48 |
+ M |
+ 65 |
+
+ R1165C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 82 |
+ BXD51 |
+ F |
+ 66 |
+
+ R1666C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 83 |
+ BXD51 |
+ M |
+ 62 |
+
+ R1180C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 84 |
+ BXD51 |
+ M |
+ 79 |
+
+ R1671C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 85 |
+ BXD60 |
+ F |
+ 64 |
+
+ R1160C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 86 |
+ BXD60 |
+ M |
+ 61 |
+
+ R1103C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 87 |
+ BXD60 |
+ M |
+ 99 |
+
+ R1669C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 88 |
+ BXD62 |
+ M |
+ 61 |
+
+ R1149C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 89 |
+ BXD62 |
+ M |
+ 60 |
+
+ R1668C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 90 |
+ BXD69 |
+ F |
+ 60 |
+
+ R1440C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 91 |
+ BXD69 |
+ M |
+ 64 |
+
+ R1197C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 92 |
+ BXD73 |
+ F |
+ 60 |
+
+ R1276C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 93 |
+ BXD73 |
+ M |
+ 77 |
+
+ R1665C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 94 |
+ BXD77 |
+ M |
+ 62 |
+
+ R1424C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 95 |
+ BXD85 |
+ F |
+ 79 |
+
+ R1486C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 96 |
+ BXD85 |
+ M |
+ 79 |
+
+ R1487C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 97 |
+ BXD86 |
+ F |
+ 58 |
+
+ R1408C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 98 |
+ BXD86 |
+ M |
+ 58 |
+
+ R1412C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 99 |
+ BXD90 |
+ M |
+ 74 |
+
+ R1664C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 100 |
+ BXD92 |
+ F |
+ 62 |
+
+ R1391C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 101 |
+ BXD92 |
+ F |
+ 63 |
+
+ R1670C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+ | 102 |
+ BXD92 |
+ M |
+ 59 |
+
+ R1308C
+ |
+
+ 3
+ |
+ UTM RW |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Cb_m_1003_m/acknowledgment.rtf b/general/datasets/Cb_m_1003_m/acknowledgment.rtf
new file mode 100644
index 0000000..b048bb0
--- /dev/null
+++ b/general/datasets/Cb_m_1003_m/acknowledgment.rtf
@@ -0,0 +1,15 @@
+Data were generated with funds contributed equally by The UTHSC-SJCRH Cerebellum Transcriptome Profiling Consortium. Our members include:
+
+ - Tom Curran
+ - Dan Goldowitz
+ - Kristin Hamre
+ - Lu Lu
+ - Peter McKinnon
+ - James Morgan
+ - Clayton Naeve
+ - Richard Smeyne
+ - Robert W. Williams
+ - The Center of Genomics and Bioinformatics at UTHSC
+ - The Hartwell Center at SJCRH
+
+
diff --git a/general/datasets/Cb_m_1003_m/cases.rtf b/general/datasets/Cb_m_1003_m/cases.rtf
new file mode 100644
index 0000000..f5e6bdf
--- /dev/null
+++ b/general/datasets/Cb_m_1003_m/cases.rtf
@@ -0,0 +1,7 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems). Chromosomes of the two parental strains have been recombined and fixed randomly in the many different BXD strains. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine.
+
+
+In this mRNA expression data set we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+
+The set of mouse strains used for mapping (a mapping panel) consists of groups of genetically unique BXD recombinant inbred strains. The ancestral strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6, and 1.5x coverage for D by Celera Genomics). Chromosomes of the two parental strains are recombined randomly in the many different BXD strains. BXD lines 2 through 32 were produced by Dr. Benjamin Taylor starting in the late 1970s. BXD33 through 42 were also produced by Dr. Taylor, but they were generated in the 1990s. All of these strains are available from The Jackson Laboratory. Lines such as BXD67, BXD68, etc. are BXD Advanced recombinant inbred strains that are part of a large set now being produced by Drs. Lu Lu, Guomin Zhou, Lee Silver, Jeremy Peirce, and Robert Williams. There will eventually be 45 of these BXD strains. For additional background on recombinant inbred strains, please see http://www.nervenet.org/papers/bxn.html.
diff --git a/general/datasets/Cb_m_1003_m/notes.rtf b/general/datasets/Cb_m_1003_m/notes.rtf
new file mode 100644
index 0000000..5d4ac24
--- /dev/null
+++ b/general/datasets/Cb_m_1003_m/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW and YHQ, September 2003. Updated by RWW, October 30, 2004.
+
diff --git a/general/datasets/Cb_m_1003_m/platform.rtf b/general/datasets/Cb_m_1003_m/platform.rtf
new file mode 100644
index 0000000..188038b
--- /dev/null
+++ b/general/datasets/Cb_m_1003_m/platform.rtf
@@ -0,0 +1,3 @@
+Affymetrix Mouse Expression 430 GeneChip set: The expression data were generated using 430A and 430B arrays. Chromosomal positions of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
diff --git a/general/datasets/Cb_m_1003_m/processing.rtf b/general/datasets/Cb_m_1003_m/processing.rtf
new file mode 100644
index 0000000..cdfa27a
--- /dev/null
+++ b/general/datasets/Cb_m_1003_m/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added a constant offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal level.
+ - Step 3: We computed the Z scores for each cell within its array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units.
+ - Step 6a: The 430A and 430B GeneChips include a set of 100 shared probe sets that have identical sequences. These 100 probe sets and 2200 probes provide a good way to adjust expression of the two GeneChips to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array (the A array contains the more commonly expressed transcripts). To bring the two arrays into numerical alignment, we regressed Z scores of the common set of 2200 probes to obtain linear regression corrections to rescale the 430B arrays to values that match the 430A array. This involved multiplying all 430B Z scores by the slope of the regression and adding a very small offset (the regression intercept). The result of this adjustment is that the mean of the 430A array expression is fixed at a value of 8, whereas that of the 430B chip is typically 7.
+ - Step 6b: We recentered the entire combined set of 430A and 430B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: No batch correction was applied.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have only a very modest number of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that this data set does not provide any correction for variance introduced by differences in sex, age, tissue source, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+Probe set data from the CHP file: These CHP files were generated using MAS 5. The same simple steps described above were also applied to these values. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the noise level.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers on the 430A and 430B microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium Oct 2003 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Cb_m_1003_m/summary.rtf b/general/datasets/Cb_m_1003_m/summary.rtf
new file mode 100644
index 0000000..8a59cc3
--- /dev/null
+++ b/general/datasets/Cb_m_1003_m/summary.rtf
@@ -0,0 +1,3 @@
+
+This October 2003 freeze provides estimates of mRNA expression in cerebellum of 26 adult BXD recombinant inbred strains, as well as C57BL/6J, DBA/2J, and their F1 hybrid, measured using the Affymetrix M430A and B microarrays. Data were generated by a small consortium of investigators at St. Jude Children's Research Hospital (SJ) and the University of Tennessee Health Science Center (UT). Data were processed using the Microarray Suite 5 (<a data-cke-saved-href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" _blank"="" class="fs14">MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run in two large batches with careful consideration to balancing samples by sex and age. Eighteen strains have been profiled using two or three independent samples. All other strains were sampled once.
+
diff --git a/general/datasets/Cb_m_1003_m/tissue.rtf b/general/datasets/Cb_m_1003_m/tissue.rtf
new file mode 100644
index 0000000..4f8e5ed
--- /dev/null
+++ b/general/datasets/Cb_m_1003_m/tissue.rtf
@@ -0,0 +1,376 @@
+
+The October 2003 data set was processed in two large batches. The first batch (the May 2003 data set) consists of 20 pooled samples from 20 strains run on pairs of Affymetrix 430A and 430B arrays (40 arrays total). The second batch consists of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of whole cerebellum taken from three adult animals of the same age and sex. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+RNA was extracted at UTHSC by Zhiping Jia and Hongtao Zhai.
+
+All samples were subsequently processed at the Hartwell Center Affymetrix laboratory at SJCRH by Jay Morris.
+
+
+The January04 data were processed in two large batches. The first batch (the May03 data set) consisted of samples from 20 samples and 20 strains run on Affymetrix MOE 430A and MOE430B GeneChip pairs (40 arrays total). The second batch of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of brain tissue (intact whole cerebellum) taken from three adult animals usually of the same age. RNA was extracted at UTHSC and all samples were processed at the Hartwell Center (SJCRH, Memphis). We will eventually achieve a sample with good, but not perfect, balance of samples by sex and age. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+The table below summarizes informaton on strain, sex, age, sample name, and batch number.
+
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Batch |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 766-C1 |
+ 2 |
+
+
+ | B6D2F1 |
+ M |
+ 94 |
+ S347-1C1 |
+ 1 |
+
+
+ | C57BL/6J |
+ F |
+ 116 |
+ 773-C1 |
+ 2 |
+
+
+ | C57BL/6J |
+ M |
+ 109 |
+ S054-1C2 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 71 |
+ S175-1C1 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 91 |
+ 782-C1 |
+ 2 |
+
+
+ | BXD1 |
+ F |
+ 57 |
+ 813-C1 |
+ 2 |
+
+
+ | BXD2 |
+ F |
+ 142 |
+ 751-C1 |
+ 1 |
+
+
+ | BXD2 |
+ F |
+ 78 |
+ 774-C1 |
+ 2 |
+
+
+ | BXD5 |
+ F |
+ 56 |
+ 802-C1 |
+ 2 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 752-C1 |
+ 1 |
+
+
+ | BXD6 |
+ F |
+ 92 |
+ 719-C1 |
+ 1 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S173-1C1 |
+ 1 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 737-C1 |
+ 1 |
+
+
+ | BXD11 |
+ F |
+ 441 |
+ S200-1C1 |
+ 1 |
+
+
+ | BXD11 |
+ M |
+ 92 |
+ 790-C1 |
+ 2 |
+
+
+ | BXD12 |
+ F |
+ 130 |
+ 776-C1 |
+ 2 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 756-C1 |
+ 2 |
+
+
+ | BXD14 |
+ F |
+ 190 |
+ 794-C1 |
+ 2 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 758-C1 |
+ 2 |
+
+
+ | BXD16 |
+ F |
+ 163 |
+ 750-C1 |
+ 1 |
+
+
+ | BXD19 |
+ F |
+ 61 |
+ 772-C1 |
+ 2 |
+
+
+ | BXD21 |
+ F |
+ 116 |
+ 711-C1 |
+ 1 |
+
+
+ | BXD21 |
+ M |
+ 64 |
+ 803-C1 |
+ 2 |
+
+
+ | BXD22 |
+ F |
+ 65 |
+ S174-1C1 |
+ 1 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 814-C1 |
+ 2 |
+
+
+ | BXD24 |
+ F |
+ 71 |
+ 805-C1 |
+ 2 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 759-C1 |
+ 2 |
+
+
+ | BXD25 |
+ M |
+ 90 |
+ S429-1C1 |
+ 1 |
+
+
+ | BXD28 |
+ F |
+ 113 |
+ 785-C1 |
+ 2 |
+
+
+ | BXD28 |
+ F |
+ 427 |
+ S203-1C1 |
+ 1 |
+
+
+ | BXD29 |
+ F |
+ 82 |
+ 777-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 1 |
+
+
+ | BXD31 |
+ F |
+ 142 |
+ 816-C1 |
+ 2 |
+
+
+ | BXD32 |
+ F |
+ 62 |
+ 778-C1 |
+ 2 |
+
+
+ | BXD32 |
+ M |
+ 218 |
+ 786-C1 |
+ 2 |
+
+
+ | BXD33 |
+ F |
+ 184 |
+ 793-C1 |
+ 2 |
+
+
+ | BXD33 |
+ M |
+ 124 |
+ 715-C1 |
+ 1 |
+
+
+ | BXD34 |
+ F |
+ 56 |
+ 725-C1 |
+ 1 |
+
+
+ | BXD34 |
+ M |
+ 91 |
+ 789-C1 |
+ 2 |
+
+
+ | BXD38 |
+ F |
+ 55 |
+ 781-C1 |
+ 2 |
+
+
+ | BXD38 |
+ M |
+ 65 |
+ 761-C1 |
+ 2 |
+
+
+ | BXD39 |
+ M |
+ 165 |
+ 723-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 2 |
+
+
+ | BXD40 |
+ M |
+ 73 |
+ 812-C1 |
+ 2 |
+
+
+ | BXD42 |
+ F |
+ 100 |
+ 799-C1 |
+ 2 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 709-C1 |
+ 1 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Cb_m_1004_m/acknowledgment.rtf b/general/datasets/Cb_m_1004_m/acknowledgment.rtf
new file mode 100644
index 0000000..b048bb0
--- /dev/null
+++ b/general/datasets/Cb_m_1004_m/acknowledgment.rtf
@@ -0,0 +1,15 @@
+Data were generated with funds contributed equally by The UTHSC-SJCRH Cerebellum Transcriptome Profiling Consortium. Our members include:
+
+ - Tom Curran
+ - Dan Goldowitz
+ - Kristin Hamre
+ - Lu Lu
+ - Peter McKinnon
+ - James Morgan
+ - Clayton Naeve
+ - Richard Smeyne
+ - Robert W. Williams
+ - The Center of Genomics and Bioinformatics at UTHSC
+ - The Hartwell Center at SJCRH
+
+
diff --git a/general/datasets/Cb_m_1004_m/cases.rtf b/general/datasets/Cb_m_1004_m/cases.rtf
new file mode 100644
index 0000000..f5e6bdf
--- /dev/null
+++ b/general/datasets/Cb_m_1004_m/cases.rtf
@@ -0,0 +1,7 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems). Chromosomes of the two parental strains have been recombined and fixed randomly in the many different BXD strains. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine.
+
+
+In this mRNA expression data set we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+
+The set of mouse strains used for mapping (a mapping panel) consists of groups of genetically unique BXD recombinant inbred strains. The ancestral strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6, and 1.5x coverage for D by Celera Genomics). Chromosomes of the two parental strains are recombined randomly in the many different BXD strains. BXD lines 2 through 32 were produced by Dr. Benjamin Taylor starting in the late 1970s. BXD33 through 42 were also produced by Dr. Taylor, but they were generated in the 1990s. All of these strains are available from The Jackson Laboratory. Lines such as BXD67, BXD68, etc. are BXD Advanced recombinant inbred strains that are part of a large set now being produced by Drs. Lu Lu, Guomin Zhou, Lee Silver, Jeremy Peirce, and Robert Williams. There will eventually be 45 of these BXD strains. For additional background on recombinant inbred strains, please see http://www.nervenet.org/papers/bxn.html.
diff --git a/general/datasets/Cb_m_1004_m/notes.rtf b/general/datasets/Cb_m_1004_m/notes.rtf
new file mode 100644
index 0000000..5d4ac24
--- /dev/null
+++ b/general/datasets/Cb_m_1004_m/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW and YHQ, September 2003. Updated by RWW, October 30, 2004.
+
diff --git a/general/datasets/Cb_m_1004_m/platform.rtf b/general/datasets/Cb_m_1004_m/platform.rtf
new file mode 100644
index 0000000..188038b
--- /dev/null
+++ b/general/datasets/Cb_m_1004_m/platform.rtf
@@ -0,0 +1,3 @@
+Affymetrix Mouse Expression 430 GeneChip set: The expression data were generated using 430A and 430B arrays. Chromosomal positions of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
diff --git a/general/datasets/Cb_m_1004_m/processing.rtf b/general/datasets/Cb_m_1004_m/processing.rtf
new file mode 100644
index 0000000..cdfa27a
--- /dev/null
+++ b/general/datasets/Cb_m_1004_m/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added a constant offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal level.
+ - Step 3: We computed the Z scores for each cell within its array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units.
+ - Step 6a: The 430A and 430B GeneChips include a set of 100 shared probe sets that have identical sequences. These 100 probe sets and 2200 probes provide a good way to adjust expression of the two GeneChips to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array (the A array contains the more commonly expressed transcripts). To bring the two arrays into numerical alignment, we regressed Z scores of the common set of 2200 probes to obtain linear regression corrections to rescale the 430B arrays to values that match the 430A array. This involved multiplying all 430B Z scores by the slope of the regression and adding a very small offset (the regression intercept). The result of this adjustment is that the mean of the 430A array expression is fixed at a value of 8, whereas that of the 430B chip is typically 7.
+ - Step 6b: We recentered the entire combined set of 430A and 430B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: No batch correction was applied.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have only a very modest number of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that this data set does not provide any correction for variance introduced by differences in sex, age, tissue source, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+Probe set data from the CHP file: These CHP files were generated using MAS 5. The same simple steps described above were also applied to these values. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the noise level.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers on the 430A and 430B microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium Oct 2003 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Cb_m_1004_m/summary.rtf b/general/datasets/Cb_m_1004_m/summary.rtf
new file mode 100644
index 0000000..8a59cc3
--- /dev/null
+++ b/general/datasets/Cb_m_1004_m/summary.rtf
@@ -0,0 +1,3 @@
+
+This October 2003 freeze provides estimates of mRNA expression in cerebellum of 26 adult BXD recombinant inbred strains, as well as C57BL/6J, DBA/2J, and their F1 hybrid, measured using the Affymetrix M430A and B microarrays. Data were generated by a small consortium of investigators at St. Jude Children's Research Hospital (SJ) and the University of Tennessee Health Science Center (UT). Data were processed using the Microarray Suite 5 (<a data-cke-saved-href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" _blank"="" class="fs14">MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run in two large batches with careful consideration to balancing samples by sex and age. Eighteen strains have been profiled using two or three independent samples. All other strains were sampled once.
+
diff --git a/general/datasets/Cb_m_1004_m/tissue.rtf b/general/datasets/Cb_m_1004_m/tissue.rtf
new file mode 100644
index 0000000..4f8e5ed
--- /dev/null
+++ b/general/datasets/Cb_m_1004_m/tissue.rtf
@@ -0,0 +1,376 @@
+
+The October 2003 data set was processed in two large batches. The first batch (the May 2003 data set) consists of 20 pooled samples from 20 strains run on pairs of Affymetrix 430A and 430B arrays (40 arrays total). The second batch consists of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of whole cerebellum taken from three adult animals of the same age and sex. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+RNA was extracted at UTHSC by Zhiping Jia and Hongtao Zhai.
+
+All samples were subsequently processed at the Hartwell Center Affymetrix laboratory at SJCRH by Jay Morris.
+
+
+The January04 data were processed in two large batches. The first batch (the May03 data set) consisted of samples from 20 samples and 20 strains run on Affymetrix MOE 430A and MOE430B GeneChip pairs (40 arrays total). The second batch of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of brain tissue (intact whole cerebellum) taken from three adult animals usually of the same age. RNA was extracted at UTHSC and all samples were processed at the Hartwell Center (SJCRH, Memphis). We will eventually achieve a sample with good, but not perfect, balance of samples by sex and age. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+The table below summarizes informaton on strain, sex, age, sample name, and batch number.
+
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Batch |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 766-C1 |
+ 2 |
+
+
+ | B6D2F1 |
+ M |
+ 94 |
+ S347-1C1 |
+ 1 |
+
+
+ | C57BL/6J |
+ F |
+ 116 |
+ 773-C1 |
+ 2 |
+
+
+ | C57BL/6J |
+ M |
+ 109 |
+ S054-1C2 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 71 |
+ S175-1C1 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 91 |
+ 782-C1 |
+ 2 |
+
+
+ | BXD1 |
+ F |
+ 57 |
+ 813-C1 |
+ 2 |
+
+
+ | BXD2 |
+ F |
+ 142 |
+ 751-C1 |
+ 1 |
+
+
+ | BXD2 |
+ F |
+ 78 |
+ 774-C1 |
+ 2 |
+
+
+ | BXD5 |
+ F |
+ 56 |
+ 802-C1 |
+ 2 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 752-C1 |
+ 1 |
+
+
+ | BXD6 |
+ F |
+ 92 |
+ 719-C1 |
+ 1 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S173-1C1 |
+ 1 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 737-C1 |
+ 1 |
+
+
+ | BXD11 |
+ F |
+ 441 |
+ S200-1C1 |
+ 1 |
+
+
+ | BXD11 |
+ M |
+ 92 |
+ 790-C1 |
+ 2 |
+
+
+ | BXD12 |
+ F |
+ 130 |
+ 776-C1 |
+ 2 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 756-C1 |
+ 2 |
+
+
+ | BXD14 |
+ F |
+ 190 |
+ 794-C1 |
+ 2 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 758-C1 |
+ 2 |
+
+
+ | BXD16 |
+ F |
+ 163 |
+ 750-C1 |
+ 1 |
+
+
+ | BXD19 |
+ F |
+ 61 |
+ 772-C1 |
+ 2 |
+
+
+ | BXD21 |
+ F |
+ 116 |
+ 711-C1 |
+ 1 |
+
+
+ | BXD21 |
+ M |
+ 64 |
+ 803-C1 |
+ 2 |
+
+
+ | BXD22 |
+ F |
+ 65 |
+ S174-1C1 |
+ 1 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 814-C1 |
+ 2 |
+
+
+ | BXD24 |
+ F |
+ 71 |
+ 805-C1 |
+ 2 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 759-C1 |
+ 2 |
+
+
+ | BXD25 |
+ M |
+ 90 |
+ S429-1C1 |
+ 1 |
+
+
+ | BXD28 |
+ F |
+ 113 |
+ 785-C1 |
+ 2 |
+
+
+ | BXD28 |
+ F |
+ 427 |
+ S203-1C1 |
+ 1 |
+
+
+ | BXD29 |
+ F |
+ 82 |
+ 777-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 1 |
+
+
+ | BXD31 |
+ F |
+ 142 |
+ 816-C1 |
+ 2 |
+
+
+ | BXD32 |
+ F |
+ 62 |
+ 778-C1 |
+ 2 |
+
+
+ | BXD32 |
+ M |
+ 218 |
+ 786-C1 |
+ 2 |
+
+
+ | BXD33 |
+ F |
+ 184 |
+ 793-C1 |
+ 2 |
+
+
+ | BXD33 |
+ M |
+ 124 |
+ 715-C1 |
+ 1 |
+
+
+ | BXD34 |
+ F |
+ 56 |
+ 725-C1 |
+ 1 |
+
+
+ | BXD34 |
+ M |
+ 91 |
+ 789-C1 |
+ 2 |
+
+
+ | BXD38 |
+ F |
+ 55 |
+ 781-C1 |
+ 2 |
+
+
+ | BXD38 |
+ M |
+ 65 |
+ 761-C1 |
+ 2 |
+
+
+ | BXD39 |
+ M |
+ 165 |
+ 723-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 2 |
+
+
+ | BXD40 |
+ M |
+ 73 |
+ 812-C1 |
+ 2 |
+
+
+ | BXD42 |
+ F |
+ 100 |
+ 799-C1 |
+ 2 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 709-C1 |
+ 1 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Cb_m_1004_p/acknowledgment.rtf b/general/datasets/Cb_m_1004_p/acknowledgment.rtf
new file mode 100644
index 0000000..b048bb0
--- /dev/null
+++ b/general/datasets/Cb_m_1004_p/acknowledgment.rtf
@@ -0,0 +1,15 @@
+Data were generated with funds contributed equally by The UTHSC-SJCRH Cerebellum Transcriptome Profiling Consortium. Our members include:
+
+ - Tom Curran
+ - Dan Goldowitz
+ - Kristin Hamre
+ - Lu Lu
+ - Peter McKinnon
+ - James Morgan
+ - Clayton Naeve
+ - Richard Smeyne
+ - Robert W. Williams
+ - The Center of Genomics and Bioinformatics at UTHSC
+ - The Hartwell Center at SJCRH
+
+
diff --git a/general/datasets/Cb_m_1004_p/cases.rtf b/general/datasets/Cb_m_1004_p/cases.rtf
new file mode 100644
index 0000000..f5e6bdf
--- /dev/null
+++ b/general/datasets/Cb_m_1004_p/cases.rtf
@@ -0,0 +1,7 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems). Chromosomes of the two parental strains have been recombined and fixed randomly in the many different BXD strains. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine.
+
+
+In this mRNA expression data set we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+
+The set of mouse strains used for mapping (a mapping panel) consists of groups of genetically unique BXD recombinant inbred strains. The ancestral strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6, and 1.5x coverage for D by Celera Genomics). Chromosomes of the two parental strains are recombined randomly in the many different BXD strains. BXD lines 2 through 32 were produced by Dr. Benjamin Taylor starting in the late 1970s. BXD33 through 42 were also produced by Dr. Taylor, but they were generated in the 1990s. All of these strains are available from The Jackson Laboratory. Lines such as BXD67, BXD68, etc. are BXD Advanced recombinant inbred strains that are part of a large set now being produced by Drs. Lu Lu, Guomin Zhou, Lee Silver, Jeremy Peirce, and Robert Williams. There will eventually be 45 of these BXD strains. For additional background on recombinant inbred strains, please see http://www.nervenet.org/papers/bxn.html.
diff --git a/general/datasets/Cb_m_1004_p/notes.rtf b/general/datasets/Cb_m_1004_p/notes.rtf
new file mode 100644
index 0000000..5d4ac24
--- /dev/null
+++ b/general/datasets/Cb_m_1004_p/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW and YHQ, September 2003. Updated by RWW, October 30, 2004.
+
diff --git a/general/datasets/Cb_m_1004_p/platform.rtf b/general/datasets/Cb_m_1004_p/platform.rtf
new file mode 100644
index 0000000..188038b
--- /dev/null
+++ b/general/datasets/Cb_m_1004_p/platform.rtf
@@ -0,0 +1,3 @@
+Affymetrix Mouse Expression 430 GeneChip set: The expression data were generated using 430A and 430B arrays. Chromosomal positions of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
diff --git a/general/datasets/Cb_m_1004_p/processing.rtf b/general/datasets/Cb_m_1004_p/processing.rtf
new file mode 100644
index 0000000..cdfa27a
--- /dev/null
+++ b/general/datasets/Cb_m_1004_p/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added a constant offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal level.
+ - Step 3: We computed the Z scores for each cell within its array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units.
+ - Step 6a: The 430A and 430B GeneChips include a set of 100 shared probe sets that have identical sequences. These 100 probe sets and 2200 probes provide a good way to adjust expression of the two GeneChips to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array (the A array contains the more commonly expressed transcripts). To bring the two arrays into numerical alignment, we regressed Z scores of the common set of 2200 probes to obtain linear regression corrections to rescale the 430B arrays to values that match the 430A array. This involved multiplying all 430B Z scores by the slope of the regression and adding a very small offset (the regression intercept). The result of this adjustment is that the mean of the 430A array expression is fixed at a value of 8, whereas that of the 430B chip is typically 7.
+ - Step 6b: We recentered the entire combined set of 430A and 430B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: No batch correction was applied.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have only a very modest number of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that this data set does not provide any correction for variance introduced by differences in sex, age, tissue source, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+Probe set data from the CHP file: These CHP files were generated using MAS 5. The same simple steps described above were also applied to these values. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the noise level.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers on the 430A and 430B microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium Oct 2003 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Cb_m_1004_p/summary.rtf b/general/datasets/Cb_m_1004_p/summary.rtf
new file mode 100644
index 0000000..8a59cc3
--- /dev/null
+++ b/general/datasets/Cb_m_1004_p/summary.rtf
@@ -0,0 +1,3 @@
+
+This October 2003 freeze provides estimates of mRNA expression in cerebellum of 26 adult BXD recombinant inbred strains, as well as C57BL/6J, DBA/2J, and their F1 hybrid, measured using the Affymetrix M430A and B microarrays. Data were generated by a small consortium of investigators at St. Jude Children's Research Hospital (SJ) and the University of Tennessee Health Science Center (UT). Data were processed using the Microarray Suite 5 (<a data-cke-saved-href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" _blank"="" class="fs14">MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run in two large batches with careful consideration to balancing samples by sex and age. Eighteen strains have been profiled using two or three independent samples. All other strains were sampled once.
+
diff --git a/general/datasets/Cb_m_1004_p/tissue.rtf b/general/datasets/Cb_m_1004_p/tissue.rtf
new file mode 100644
index 0000000..4f8e5ed
--- /dev/null
+++ b/general/datasets/Cb_m_1004_p/tissue.rtf
@@ -0,0 +1,376 @@
+
+The October 2003 data set was processed in two large batches. The first batch (the May 2003 data set) consists of 20 pooled samples from 20 strains run on pairs of Affymetrix 430A and 430B arrays (40 arrays total). The second batch consists of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of whole cerebellum taken from three adult animals of the same age and sex. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+RNA was extracted at UTHSC by Zhiping Jia and Hongtao Zhai.
+
+All samples were subsequently processed at the Hartwell Center Affymetrix laboratory at SJCRH by Jay Morris.
+
+
+The January04 data were processed in two large batches. The first batch (the May03 data set) consisted of samples from 20 samples and 20 strains run on Affymetrix MOE 430A and MOE430B GeneChip pairs (40 arrays total). The second batch of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of brain tissue (intact whole cerebellum) taken from three adult animals usually of the same age. RNA was extracted at UTHSC and all samples were processed at the Hartwell Center (SJCRH, Memphis). We will eventually achieve a sample with good, but not perfect, balance of samples by sex and age. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+The table below summarizes informaton on strain, sex, age, sample name, and batch number.
+
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Batch |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 766-C1 |
+ 2 |
+
+
+ | B6D2F1 |
+ M |
+ 94 |
+ S347-1C1 |
+ 1 |
+
+
+ | C57BL/6J |
+ F |
+ 116 |
+ 773-C1 |
+ 2 |
+
+
+ | C57BL/6J |
+ M |
+ 109 |
+ S054-1C2 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 71 |
+ S175-1C1 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 91 |
+ 782-C1 |
+ 2 |
+
+
+ | BXD1 |
+ F |
+ 57 |
+ 813-C1 |
+ 2 |
+
+
+ | BXD2 |
+ F |
+ 142 |
+ 751-C1 |
+ 1 |
+
+
+ | BXD2 |
+ F |
+ 78 |
+ 774-C1 |
+ 2 |
+
+
+ | BXD5 |
+ F |
+ 56 |
+ 802-C1 |
+ 2 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 752-C1 |
+ 1 |
+
+
+ | BXD6 |
+ F |
+ 92 |
+ 719-C1 |
+ 1 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S173-1C1 |
+ 1 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 737-C1 |
+ 1 |
+
+
+ | BXD11 |
+ F |
+ 441 |
+ S200-1C1 |
+ 1 |
+
+
+ | BXD11 |
+ M |
+ 92 |
+ 790-C1 |
+ 2 |
+
+
+ | BXD12 |
+ F |
+ 130 |
+ 776-C1 |
+ 2 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 756-C1 |
+ 2 |
+
+
+ | BXD14 |
+ F |
+ 190 |
+ 794-C1 |
+ 2 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 758-C1 |
+ 2 |
+
+
+ | BXD16 |
+ F |
+ 163 |
+ 750-C1 |
+ 1 |
+
+
+ | BXD19 |
+ F |
+ 61 |
+ 772-C1 |
+ 2 |
+
+
+ | BXD21 |
+ F |
+ 116 |
+ 711-C1 |
+ 1 |
+
+
+ | BXD21 |
+ M |
+ 64 |
+ 803-C1 |
+ 2 |
+
+
+ | BXD22 |
+ F |
+ 65 |
+ S174-1C1 |
+ 1 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 814-C1 |
+ 2 |
+
+
+ | BXD24 |
+ F |
+ 71 |
+ 805-C1 |
+ 2 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 759-C1 |
+ 2 |
+
+
+ | BXD25 |
+ M |
+ 90 |
+ S429-1C1 |
+ 1 |
+
+
+ | BXD28 |
+ F |
+ 113 |
+ 785-C1 |
+ 2 |
+
+
+ | BXD28 |
+ F |
+ 427 |
+ S203-1C1 |
+ 1 |
+
+
+ | BXD29 |
+ F |
+ 82 |
+ 777-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 1 |
+
+
+ | BXD31 |
+ F |
+ 142 |
+ 816-C1 |
+ 2 |
+
+
+ | BXD32 |
+ F |
+ 62 |
+ 778-C1 |
+ 2 |
+
+
+ | BXD32 |
+ M |
+ 218 |
+ 786-C1 |
+ 2 |
+
+
+ | BXD33 |
+ F |
+ 184 |
+ 793-C1 |
+ 2 |
+
+
+ | BXD33 |
+ M |
+ 124 |
+ 715-C1 |
+ 1 |
+
+
+ | BXD34 |
+ F |
+ 56 |
+ 725-C1 |
+ 1 |
+
+
+ | BXD34 |
+ M |
+ 91 |
+ 789-C1 |
+ 2 |
+
+
+ | BXD38 |
+ F |
+ 55 |
+ 781-C1 |
+ 2 |
+
+
+ | BXD38 |
+ M |
+ 65 |
+ 761-C1 |
+ 2 |
+
+
+ | BXD39 |
+ M |
+ 165 |
+ 723-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 2 |
+
+
+ | BXD40 |
+ M |
+ 73 |
+ 812-C1 |
+ 2 |
+
+
+ | BXD42 |
+ F |
+ 100 |
+ 799-C1 |
+ 2 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 709-C1 |
+ 1 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Cb_m_1004_r/acknowledgment.rtf b/general/datasets/Cb_m_1004_r/acknowledgment.rtf
new file mode 100644
index 0000000..b048bb0
--- /dev/null
+++ b/general/datasets/Cb_m_1004_r/acknowledgment.rtf
@@ -0,0 +1,15 @@
+Data were generated with funds contributed equally by The UTHSC-SJCRH Cerebellum Transcriptome Profiling Consortium. Our members include:
+
+ - Tom Curran
+ - Dan Goldowitz
+ - Kristin Hamre
+ - Lu Lu
+ - Peter McKinnon
+ - James Morgan
+ - Clayton Naeve
+ - Richard Smeyne
+ - Robert W. Williams
+ - The Center of Genomics and Bioinformatics at UTHSC
+ - The Hartwell Center at SJCRH
+
+
diff --git a/general/datasets/Cb_m_1004_r/cases.rtf b/general/datasets/Cb_m_1004_r/cases.rtf
new file mode 100644
index 0000000..f5e6bdf
--- /dev/null
+++ b/general/datasets/Cb_m_1004_r/cases.rtf
@@ -0,0 +1,7 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems). Chromosomes of the two parental strains have been recombined and fixed randomly in the many different BXD strains. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine.
+
+
+In this mRNA expression data set we generally used progeny of stock obtained from The Jackson Laboratory between 1999 and 2001. Animals were generated in-house at the University of Alabama by John Mountz and Hui-Chen Hsu and at the University of Tennessee Health Science Center by Lu Lu and Robert Williams.
+
+
+The set of mouse strains used for mapping (a mapping panel) consists of groups of genetically unique BXD recombinant inbred strains. The ancestral strains from which all BXD lines are derived are C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D strains have been almost fully sequence (8x coverage for B6, and 1.5x coverage for D by Celera Genomics). Chromosomes of the two parental strains are recombined randomly in the many different BXD strains. BXD lines 2 through 32 were produced by Dr. Benjamin Taylor starting in the late 1970s. BXD33 through 42 were also produced by Dr. Taylor, but they were generated in the 1990s. All of these strains are available from The Jackson Laboratory. Lines such as BXD67, BXD68, etc. are BXD Advanced recombinant inbred strains that are part of a large set now being produced by Drs. Lu Lu, Guomin Zhou, Lee Silver, Jeremy Peirce, and Robert Williams. There will eventually be 45 of these BXD strains. For additional background on recombinant inbred strains, please see http://www.nervenet.org/papers/bxn.html.
diff --git a/general/datasets/Cb_m_1004_r/notes.rtf b/general/datasets/Cb_m_1004_r/notes.rtf
new file mode 100644
index 0000000..5d4ac24
--- /dev/null
+++ b/general/datasets/Cb_m_1004_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW and YHQ, September 2003. Updated by RWW, October 30, 2004.
+
diff --git a/general/datasets/Cb_m_1004_r/platform.rtf b/general/datasets/Cb_m_1004_r/platform.rtf
new file mode 100644
index 0000000..188038b
--- /dev/null
+++ b/general/datasets/Cb_m_1004_r/platform.rtf
@@ -0,0 +1,3 @@
+Affymetrix Mouse Expression 430 GeneChip set: The expression data were generated using 430A and 430B arrays. Chromosomal positions of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possiible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
diff --git a/general/datasets/Cb_m_1004_r/processing.rtf b/general/datasets/Cb_m_1004_r/processing.rtf
new file mode 100644
index 0000000..cdfa27a
--- /dev/null
+++ b/general/datasets/Cb_m_1004_r/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added a constant offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell signal level.
+ - Step 3: We computed the Z scores for each cell within its array.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8 units, a variance of 4 units, and a standard deviation of 2 units.
+ - Step 6a: The 430A and 430B GeneChips include a set of 100 shared probe sets that have identical sequences. These 100 probe sets and 2200 probes provide a good way to adjust expression of the two GeneChips to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array (the A array contains the more commonly expressed transcripts). To bring the two arrays into numerical alignment, we regressed Z scores of the common set of 2200 probes to obtain linear regression corrections to rescale the 430B arrays to values that match the 430A array. This involved multiplying all 430B Z scores by the slope of the regression and adding a very small offset (the regression intercept). The result of this adjustment is that the mean of the 430A array expression is fixed at a value of 8, whereas that of the 430B chip is typically 7.
+ - Step 6b: We recentered the entire combined set of 430A and 430B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: No batch correction was applied.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have only a very modest number of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that this data set does not provide any correction for variance introduced by differences in sex, age, tissue source, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+Probe set data from the CHP file: These CHP files were generated using MAS 5. The same simple steps described above were also applied to these values. A 1-unit difference represents roughly a 2-fold difference in expression level. Expression levels below 5 are close to the noise level.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers on the 430A and 430B microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium Oct 2003 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Cb_m_1004_r/summary.rtf b/general/datasets/Cb_m_1004_r/summary.rtf
new file mode 100644
index 0000000..8a59cc3
--- /dev/null
+++ b/general/datasets/Cb_m_1004_r/summary.rtf
@@ -0,0 +1,3 @@
+
+This October 2003 freeze provides estimates of mRNA expression in cerebellum of 26 adult BXD recombinant inbred strains, as well as C57BL/6J, DBA/2J, and their F1 hybrid, measured using the Affymetrix M430A and B microarrays. Data were generated by a small consortium of investigators at St. Jude Children's Research Hospital (SJ) and the University of Tennessee Health Science Center (UT). Data were processed using the Microarray Suite 5 (<a data-cke-saved-href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" href="http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf" _blank"="" class="fs14">MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were adjusted to an average of 8 units and a variance of 2 units. This data set was run in two large batches with careful consideration to balancing samples by sex and age. Eighteen strains have been profiled using two or three independent samples. All other strains were sampled once.
+
diff --git a/general/datasets/Cb_m_1004_r/tissue.rtf b/general/datasets/Cb_m_1004_r/tissue.rtf
new file mode 100644
index 0000000..4f8e5ed
--- /dev/null
+++ b/general/datasets/Cb_m_1004_r/tissue.rtf
@@ -0,0 +1,376 @@
+
+The October 2003 data set was processed in two large batches. The first batch (the May 2003 data set) consists of 20 pooled samples from 20 strains run on pairs of Affymetrix 430A and 430B arrays (40 arrays total). The second batch consists of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of whole cerebellum taken from three adult animals of the same age and sex. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+RNA was extracted at UTHSC by Zhiping Jia and Hongtao Zhai.
+
+All samples were subsequently processed at the Hartwell Center Affymetrix laboratory at SJCRH by Jay Morris.
+
+
+The January04 data were processed in two large batches. The first batch (the May03 data set) consisted of samples from 20 samples and 20 strains run on Affymetrix MOE 430A and MOE430B GeneChip pairs (40 arrays total). The second batch of 29 samples, included may biological replicates, 2 technical replicates, and data for 9 new strains. Each individual array experiment involved a pool of brain tissue (intact whole cerebellum) taken from three adult animals usually of the same age. RNA was extracted at UTHSC and all samples were processed at the Hartwell Center (SJCRH, Memphis). We will eventually achieve a sample with good, but not perfect, balance of samples by sex and age. The age range may look broad, but translated into human terms corresponds to a range from about 20 years to 50 years.
+
+The table below summarizes informaton on strain, sex, age, sample name, and batch number.
+
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Batch |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 766-C1 |
+ 2 |
+
+
+ | B6D2F1 |
+ M |
+ 94 |
+ S347-1C1 |
+ 1 |
+
+
+ | C57BL/6J |
+ F |
+ 116 |
+ 773-C1 |
+ 2 |
+
+
+ | C57BL/6J |
+ M |
+ 109 |
+ S054-1C2 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 71 |
+ S175-1C1 |
+ 1 |
+
+
+ | DBA/2J |
+ F |
+ 91 |
+ 782-C1 |
+ 2 |
+
+
+ | BXD1 |
+ F |
+ 57 |
+ 813-C1 |
+ 2 |
+
+
+ | BXD2 |
+ F |
+ 142 |
+ 751-C1 |
+ 1 |
+
+
+ | BXD2 |
+ F |
+ 78 |
+ 774-C1 |
+ 2 |
+
+
+ | BXD5 |
+ F |
+ 56 |
+ 802-C1 |
+ 2 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 752-C1 |
+ 1 |
+
+
+ | BXD6 |
+ F |
+ 92 |
+ 719-C1 |
+ 1 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S173-1C1 |
+ 1 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 737-C1 |
+ 1 |
+
+
+ | BXD11 |
+ F |
+ 441 |
+ S200-1C1 |
+ 1 |
+
+
+ | BXD11 |
+ M |
+ 92 |
+ 790-C1 |
+ 2 |
+
+
+ | BXD12 |
+ F |
+ 130 |
+ 776-C1 |
+ 2 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 756-C1 |
+ 2 |
+
+
+ | BXD14 |
+ F |
+ 190 |
+ 794-C1 |
+ 2 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 758-C1 |
+ 2 |
+
+
+ | BXD16 |
+ F |
+ 163 |
+ 750-C1 |
+ 1 |
+
+
+ | BXD19 |
+ F |
+ 61 |
+ 772-C1 |
+ 2 |
+
+
+ | BXD21 |
+ F |
+ 116 |
+ 711-C1 |
+ 1 |
+
+
+ | BXD21 |
+ M |
+ 64 |
+ 803-C1 |
+ 2 |
+
+
+ | BXD22 |
+ F |
+ 65 |
+ S174-1C1 |
+ 1 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 814-C1 |
+ 2 |
+
+
+ | BXD24 |
+ F |
+ 71 |
+ 805-C1 |
+ 2 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 759-C1 |
+ 2 |
+
+
+ | BXD25 |
+ M |
+ 90 |
+ S429-1C1 |
+ 1 |
+
+
+ | BXD28 |
+ F |
+ 113 |
+ 785-C1 |
+ 2 |
+
+
+ | BXD28 |
+ F |
+ 427 |
+ S203-1C1 |
+ 1 |
+
+
+ | BXD29 |
+ F |
+ 82 |
+ 777-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 2 |
+
+
+ | BXD29 |
+ M |
+ 76 |
+ 714-C1 |
+ 1 |
+
+
+ | BXD31 |
+ F |
+ 142 |
+ 816-C1 |
+ 2 |
+
+
+ | BXD32 |
+ F |
+ 62 |
+ 778-C1 |
+ 2 |
+
+
+ | BXD32 |
+ M |
+ 218 |
+ 786-C1 |
+ 2 |
+
+
+ | BXD33 |
+ F |
+ 184 |
+ 793-C1 |
+ 2 |
+
+
+ | BXD33 |
+ M |
+ 124 |
+ 715-C1 |
+ 1 |
+
+
+ | BXD34 |
+ F |
+ 56 |
+ 725-C1 |
+ 1 |
+
+
+ | BXD34 |
+ M |
+ 91 |
+ 789-C1 |
+ 2 |
+
+
+ | BXD38 |
+ F |
+ 55 |
+ 781-C1 |
+ 2 |
+
+
+ | BXD38 |
+ M |
+ 65 |
+ 761-C1 |
+ 2 |
+
+
+ | BXD39 |
+ M |
+ 165 |
+ 723-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 1 |
+
+
+ | BXD40 |
+ F |
+ 56 |
+ 718-C1 |
+ 2 |
+
+
+ | BXD40 |
+ M |
+ 73 |
+ 812-C1 |
+ 2 |
+
+
+ | BXD42 |
+ F |
+ 100 |
+ 799-C1 |
+ 2 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 709-C1 |
+ 1 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Ccgeno/cases.rtf b/general/datasets/Ccgeno/cases.rtf
new file mode 100644
index 0000000..6159322
--- /dev/null
+++ b/general/datasets/Ccgeno/cases.rtf
@@ -0,0 +1 @@
+Mice were bred by Dr. Klaus Schughart at the HZI, Braunschweig, Germany.
diff --git a/general/datasets/Ccgeno/contributors.rtf b/general/datasets/Ccgeno/contributors.rtf
new file mode 100644
index 0000000..7f7f3fd
--- /dev/null
+++ b/general/datasets/Ccgeno/contributors.rtf
@@ -0,0 +1 @@
+http://csbio.unc.edu/CCstatus/CCGenomes/
diff --git a/general/datasets/Ccgeno/platform.rtf b/general/datasets/Ccgeno/platform.rtf
new file mode 100644
index 0000000..0fa1383
--- /dev/null
+++ b/general/datasets/Ccgeno/platform.rtf
@@ -0,0 +1 @@
+MegaMUGA
diff --git a/general/datasets/Ccgeno/specifics.rtf b/general/datasets/Ccgeno/specifics.rtf
new file mode 100644
index 0000000..30efa6a
--- /dev/null
+++ b/general/datasets/Ccgeno/specifics.rtf
@@ -0,0 +1 @@
+Genotypes
\ No newline at end of file
diff --git a/general/datasets/Ccgeno/summary.rtf b/general/datasets/Ccgeno/summary.rtf
new file mode 100644
index 0000000..2533382
--- /dev/null
+++ b/general/datasets/Ccgeno/summary.rtf
@@ -0,0 +1,9 @@
+Genotypes of 32 cc strains.
+
+Downloaded from http://csbio.unc.edu/CCstatus/CCGenomes/ and processed by Arthur Centeno and Zachary Sloan at the University of Tennessee.
+
+Team of Investigators:
+
+Lasse Sinkkkonen, Manuel Buttini, Yujuan Gui, and Melanie Thomas at the University of Luxembourg
+
+Data entered into GeneNetwork December 2019 by Arthur Centeno, Robert W. Williams, Yujuan Gui
diff --git a/general/datasets/Ccgeno/tissue.rtf b/general/datasets/Ccgeno/tissue.rtf
new file mode 100644
index 0000000..b4ef238
--- /dev/null
+++ b/general/datasets/Ccgeno/tissue.rtf
@@ -0,0 +1 @@
+Ventral midbrain
diff --git a/general/datasets/Ccpublish/acknowledgment.rtf b/general/datasets/Ccpublish/acknowledgment.rtf
new file mode 100644
index 0000000..c6129ca
--- /dev/null
+++ b/general/datasets/Ccpublish/acknowledgment.rtf
@@ -0,0 +1 @@
+LS and MB would like to thank the Luxembourg National Research Fund (FNR) for the support 663 (FNR CORE C15/BM/10406131 grant).
diff --git a/general/datasets/Ccpublish/cases.rtf b/general/datasets/Ccpublish/cases.rtf
new file mode 100644
index 0000000..4a36b15
--- /dev/null
+++ b/general/datasets/Ccpublish/cases.rtf
@@ -0,0 +1,3 @@
+CC mice were bred by Dr. Klaus Schughart at the HZI, Braunschweig, Germany.
+
+C57BL/6J, A/J, and DBA/2J were bred by University of Luxembourg
diff --git a/general/datasets/Ccpublish/contributors.rtf b/general/datasets/Ccpublish/contributors.rtf
new file mode 100644
index 0000000..c0e81ee
--- /dev/null
+++ b/general/datasets/Ccpublish/contributors.rtf
@@ -0,0 +1,5 @@
+manuel.buttini@uni.lu
+
+lasse.sinkkonen@uni.lu
+
+yujuan.gui@uni.lu
diff --git a/general/datasets/Ccpublish/experiment-design.rtf b/general/datasets/Ccpublish/experiment-design.rtf
new file mode 100644
index 0000000..e0fbda8
--- /dev/null
+++ b/general/datasets/Ccpublish/experiment-design.rtf
@@ -0,0 +1 @@
+Gas chromatography-mass spectrometry (GC-MS), immunofluorescent staining, RT-PCR
diff --git a/general/datasets/Ccpublish/specifics.rtf b/general/datasets/Ccpublish/specifics.rtf
new file mode 100644
index 0000000..fc3ed76
--- /dev/null
+++ b/general/datasets/Ccpublish/specifics.rtf
@@ -0,0 +1 @@
+CC Phenotypes
\ No newline at end of file
diff --git a/general/datasets/Ccpublish/summary.rtf b/general/datasets/Ccpublish/summary.rtf
new file mode 100644
index 0000000..d4904aa
--- /dev/null
+++ b/general/datasets/Ccpublish/summary.rtf
@@ -0,0 +1,11 @@
+Dopamine concentration measurements [pmol/mg]: Dorsal striatums of 32 CC strains. Each strain has around 5 male and 5 female animals, 3-month old; Dorsal striatums
+
+Neuropathology: The dorsal striatum was sectioned and stained with TH or DAT. Two metrics were measured: mean grey value [mean grey value/image] and % area occupied [% area occupied/image]. Measurements were done on dorsal striatums of C57BL/6J, A/J and DBA/2J 3, 9, 15-month-old animals.
+
+RT-PCR: The total RNA was extracted from ventral midbrains and quantified by RT-PCR with markers Th, Dat, Vmat, Nr4a2, Sox6 and Otx2 [-delta Ct]. Measurements were done on dorsal striatums of C57BL/6J, A/J and DBA/2J 3, 9, 15-month-old animals.
+
+Team of Investigators:
+
+Lasse Sinkkkonen, Manuel Buttini, Yujuan Gui, and Melanie Thomas at the University of Luxembourg
+
+Data entered into GeneNetwork December 2019 by Arthur Centeno, Robert W. Williams, Yujuan Gui.
diff --git a/general/datasets/Ccpublish/tissue.rtf b/general/datasets/Ccpublish/tissue.rtf
new file mode 100644
index 0000000..9869ae6
--- /dev/null
+++ b/general/datasets/Ccpublish/tissue.rtf
@@ -0,0 +1 @@
+Dorsal Striatum, ventral midbrain
diff --git a/general/datasets/Cmmtubcbxdcerilm0513/summary.rtf b/general/datasets/Cmmtubcbxdcerilm0513/summary.rtf
new file mode 100644
index 0000000..751de1d
--- /dev/null
+++ b/general/datasets/Cmmtubcbxdcerilm0513/summary.rtf
@@ -0,0 +1 @@
+This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/Cmmtubcbxdg12cerilm0513/summary.rtf b/general/datasets/Cmmtubcbxdg12cerilm0513/summary.rtf
new file mode 100644
index 0000000..751de1d
--- /dev/null
+++ b/general/datasets/Cmmtubcbxdg12cerilm0513/summary.rtf
@@ -0,0 +1 @@
+This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/Cmmtubcbxdg15cerilm0513/summary.rtf b/general/datasets/Cmmtubcbxdg15cerilm0513/summary.rtf
new file mode 100644
index 0000000..751de1d
--- /dev/null
+++ b/general/datasets/Cmmtubcbxdg15cerilm0513/summary.rtf
@@ -0,0 +1 @@
+This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/Cmmtubcbxdg18cerilm0513/summary.rtf b/general/datasets/Cmmtubcbxdg18cerilm0513/summary.rtf
new file mode 100644
index 0000000..751de1d
--- /dev/null
+++ b/general/datasets/Cmmtubcbxdg18cerilm0513/summary.rtf
@@ -0,0 +1 @@
+This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/Cmmtubcbxdp03cerilm0513/summary.rtf b/general/datasets/Cmmtubcbxdp03cerilm0513/summary.rtf
new file mode 100644
index 0000000..751de1d
--- /dev/null
+++ b/general/datasets/Cmmtubcbxdp03cerilm0513/summary.rtf
@@ -0,0 +1 @@
+This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/Cmmtubcbxdp06cerilm0513/summary.rtf b/general/datasets/Cmmtubcbxdp06cerilm0513/summary.rtf
new file mode 100644
index 0000000..751de1d
--- /dev/null
+++ b/general/datasets/Cmmtubcbxdp06cerilm0513/summary.rtf
@@ -0,0 +1 @@
+This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/Cmmtubcbxdp09cerilm0513/summary.rtf b/general/datasets/Cmmtubcbxdp09cerilm0513/summary.rtf
new file mode 100644
index 0000000..751de1d
--- /dev/null
+++ b/general/datasets/Cmmtubcbxdp09cerilm0513/summary.rtf
@@ -0,0 +1 @@
+This dataset is private. Contact information above is available if you have questions regarding the status of data
diff --git a/general/datasets/Cms_hipp1115/cases.rtf b/general/datasets/Cms_hipp1115/cases.rtf
new file mode 100644
index 0000000..c201f08
--- /dev/null
+++ b/general/datasets/Cms_hipp1115/cases.rtf
@@ -0,0 +1,992 @@
+The original data set included four individuals of each strain under baseline (B) conditions and eight individuals from each strain for each of the treatment groups, chronic mild stress (C), acute restraint (R), and chronic mild stress followed by acute retraint (CR). However, some samples have been removed due to technical problems with tissue collection or microarray performance.
+
+
+
+
+ | MTA_ID |
+ MTA prefix |
+ GN_ID |
+ FM_ID |
+ Mouse_ID |
+ CaseId |
+ Strain |
+ Strain_Code |
+ Treatment code |
+ NanoDrop, ng/ul |
+ NanoDrop, 260/280 |
+ NanoDrop, 260/230 |
+ Agilent, ng/µl |
+ RIN |
+ Notes |
+
+
+ | 1 |
+ BCJ 1.CMS_ |
+ D-B-215-1 |
+ CMS_000215 |
+ 215 |
+ 020615.01 |
+ DBA/2J |
+ D |
+ B |
+ 163.61 |
+ 1.9 |
+ 2.31 |
+ 130 |
+ 8.6 |
+ |
+
+
+ | 2 |
+ BCJ 2.CMS_ |
+ D-C-86-1 |
+ CMS_000086 |
+ 86 |
+ 012115.23 |
+ DBA/2J |
+ D |
+ C |
+ 98.51 |
+ 1.79 |
+ 2.4 |
+ 329 |
+ 8.8 |
+ |
+
+
+ | 3 |
+ BCJ 3.CMS_ |
+ D-CR-94-1 |
+ CMS_000094 |
+ 94 |
+ 012115.16 |
+ DBA/2J |
+ D |
+ CR |
+ 162.78 |
+ 1.87 |
+ 2.38 |
+ 166 |
+ 9.2 |
+ |
+
+
+ | 4 |
+ BCJ 4.CMS_ |
+ D-R-133-1 |
+ CMS_000133 |
+ 133 |
+ 012115.14 |
+ DBA/2J |
+ D |
+ R |
+ 88.95 |
+ 1.82 |
+ 2.45 |
+ 90 |
+ 8.2 |
+ |
+
+
+ | 5 |
+ BCJ 5.CMS_ |
+ B-B-208-1 |
+ CMS_000208 |
+ 208 |
+ 012215.04 |
+ C57BL/6J |
+ B |
+ B |
+ 129.24 |
+ 1.86 |
+ 2.41 |
+ 223 |
+ 8.1 |
+ |
+
+
+ | 6 |
+ BCJ 6.CMS_ |
+ B-C-101-1 |
+ CMS_000101 |
+ 101 |
+ 012115.25 |
+ C57BL/6J |
+ B |
+ C |
+ 72.29 |
+ 1.86 |
+ 2.26 |
+ 135 |
+ 9.2 |
+ |
+
+
+ | 7 |
+ BCJ 7.CMS_ |
+ B-CR-109-1 |
+ CMS_000109 |
+ 109 |
+ 012115.21 |
+ C57BL/6J |
+ B |
+ CR |
+ 158.56 |
+ 1.7 |
+ 2.46 |
+ 305 |
+ 8.8 |
+ Microarray outlier; sample removed. |
+
+
+ | 8 |
+ BCJ 8.CMS_ |
+ B-R-143-1 |
+ CMS_000143 |
+ 143 |
+ 012215.08 |
+ C57BL/6J |
+ B |
+ R |
+ 161.57 |
+ 1.86 |
+ 2.38 |
+ 217 |
+ 9.3 |
+ |
+
+
+ | 9 |
+ BCJ 9.CMS_ |
+ N-B-210-1 |
+ CMS_000210 |
+ 210 |
+ 012115.04 |
+ C57BL/6NJ |
+ N |
+ B |
+ 132.39 |
+ 1.89 |
+ 2.3 |
+ 192 |
+ 8.5 |
+ |
+
+
+ | 10 |
+ BCJ 10.CMS_ |
+ N-C-117-1 |
+ CMS_000117 |
+ 117 |
+ 012115.30 |
+ C57BL/6NJ |
+ N |
+ C |
+ 151.43 |
+ 1.91 |
+ 2.38 |
+ 187 |
+ 8.8 |
+ |
+
+
+ | 11 |
+ BCJ 11.CMS_ |
+ N-CR-126-1 |
+ CMS_000126 |
+ 126 |
+ 012115.33 |
+ C57BL/6NJ |
+ N |
+ CR |
+ 137.87 |
+ 1.88 |
+ 2.29 |
+ 76 |
+ 9 |
+ |
+
+
+ | 12 |
+ BCJ 12.CMS_ |
+ N-R-152-1 |
+ CMS_000152 |
+ 152 |
+ 012215.29 |
+ C57BL/6NJ |
+ N |
+ R |
+ 197.95 |
+ 1.88 |
+ 2.35 |
+ 150 |
+ 9.1 |
+ |
+
+
+ | 13 |
+ BCJ 13.CMS_ |
+ D-B-216-1 |
+ CMS_000216 |
+ 216 |
+ 020615.02 |
+ DBA/2J |
+ D |
+ B |
+ 98.64 |
+ 1.91 |
+ 2.03 |
+ 60 |
+ 8.6 |
+ |
+
+
+ | 15 |
+ BCJ 15.CMS_ |
+ D-CR-93-1 |
+ CMS_000093 |
+ 93 |
+ 012115.11 |
+ DBA/2J |
+ D |
+ CR |
+ 71.36 |
+ 1.83 |
+ 2.25 |
+ 109 |
+ 8.5 |
+ |
+
+
+ | 16 |
+ BCJ 16.CMS_ |
+ D-R-134-1 |
+ CMS_000134 |
+ 134 |
+ 012115.17 |
+ DBA/2J |
+ D |
+ R |
+ 73.49 |
+ 1.85 |
+ 2.43 |
+ 149 |
+ 8.2 |
+ |
+
+
+ | 17 |
+ BCJ 17.CMS_ |
+ B-B-205-1 |
+ CMS_000205 |
+ 205 |
+ 012015.02 |
+ C57BL/6J |
+ B |
+ B |
+ 174.78 |
+ 2.02 |
+ 2.21 |
+ 266 |
+ 8.9 |
+ |
+
+
+ | 18 |
+ BCJ 18.CMS_ |
+ B-C-104-1 |
+ CMS_000104 |
+ 104 |
+ 012215.30 |
+ C57BL/6J |
+ B |
+ C |
+ 84.7 |
+ 2.64 |
+ 2.01 |
+ 168 |
+ 9.2 |
+ |
+
+
+ | 19 |
+ BCJ 19.CMS_ |
+ B-CR-110-1 |
+ CMS_000110 |
+ 110 |
+ 012115.26 |
+ C57BL/6J |
+ B |
+ CR |
+ 136.7 |
+ 1.96 |
+ 2.16 |
+ 178 |
+ 9.5 |
+ |
+
+
+ | 20 |
+ BCJ 20.CMS_ |
+ B-R-141-1 |
+ CMS_000141 |
+ 141 |
+ 012115.22 |
+ C57BL/6J |
+ B |
+ R |
+ 86.04 |
+ 20.2 |
+ 2.53 |
+ 208 |
+ 8.9 |
+ |
+
+
+ | 21 |
+ BCJ 21.CMS_ |
+ N-B-209-1 |
+ CMS_000209 |
+ 209 |
+ 012015.04 |
+ C57BL/6NJ |
+ N |
+ B |
+ 98.3 |
+ 1.99 |
+ 2.35 |
+ 169 |
+ 8.8 |
+ |
+
+
+ | 22 |
+ BCJ 22.CMS_ |
+ N-C-119-1 |
+ CMS_000119 |
+ 119 |
+ 012215.18 |
+ C57BL/6NJ |
+ N |
+ C |
+ 94.63 |
+ 1.96 |
+ 2.36 |
+ 179 |
+ 8.5 |
+ |
+
+
+ | 24 |
+ BCJ 24.CMS_ |
+ N-R-150-1 |
+ CMS_000150 |
+ 150 |
+ 012115.29 |
+ C57BL/6NJ |
+ N |
+ R |
+ 407.34 |
+ 1.98 |
+ 2.24 |
+ 425 |
+ 7.5 |
+ Microarray outlier; sample removed. |
+
+
+ | 25 |
+ BCJ 25.CMS_ |
+ D-B-217-1 |
+ CMS_000217 |
+ 217 |
+ 020615.03 |
+ DBA/2J |
+ D |
+ B |
+ 84.61 |
+ 1.82 |
+ 2.18 |
+ 177 |
+ 7.9 |
+ |
+
+
+ | 26 |
+ BCJ 26.CMS_ |
+ D-C-85-1 |
+ CMS_000085 |
+ 85 |
+ 012115.20 |
+ DBA/2J |
+ D |
+ C |
+ 172.86 |
+ 1.98 |
+ 2.27 |
+ 288 |
+ 8.9 |
+ |
+
+
+ | 27 |
+ BCJ 27.CMS_ |
+ D-CR-95-1 |
+ CMS_000095 |
+ 95 |
+ 012215.16 |
+ DBA/2J |
+ D |
+ CR |
+ 109.8 |
+ 1.98 |
+ 2.47 |
+ 157 |
+ 8.9 |
+ |
+
+
+ | 28 |
+ BCJ 28.CMS_ |
+ D-R-132-1 |
+ CMS_000132 |
+ 132 |
+ 012015.29 |
+ DBA/2J |
+ D |
+ R |
+ 140.82 |
+ 1.91 |
+ 2.47 |
+ 318 |
+ 9 |
+ |
+
+
+ | 29 |
+ BCJ 29.CMS_ |
+ B-B-207-1 |
+ CMS_000207 |
+ 207 |
+ 012215.02 |
+ C57BL/6J |
+ B |
+ B |
+ 96.25 |
+ 1.89 |
+ 2.67 |
+ 176 |
+ 8.5 |
+ |
+
+
+ | 30 |
+ BCJ 30.CMS_ |
+ B-C-102-1 |
+ CMS_000102 |
+ 102 |
+ 012115.28 |
+ C57BL/6J |
+ B |
+ C |
+ 129.69 |
+ 1.89 |
+ 2.32 |
+ 105 |
+ 8.7 |
+ |
+
+
+ | 31 |
+ BCJ 31.CMS_ |
+ B-CR-111-1 |
+ CMS_000111 |
+ 111 |
+ 012215.26 |
+ C57BL/6J |
+ B |
+ CR |
+ 165.67 |
+ 1.84 |
+ 2.31 |
+ 176 |
+ 9.5 |
+ |
+
+
+ | 32 |
+ BCJ 32.CMS_ |
+ B-R-142-1 |
+ CMS_000142 |
+ 142 |
+ 012115.24 |
+ C57BL/6J |
+ B |
+ R |
+ 116.93 |
+ 1.84 |
+ 2.22 |
+ 96 |
+ 9.4 |
+ |
+
+
+ | 33 |
+ BCJ 33.CMS_ |
+ N-B-211-1 |
+ CMS_000211 |
+ 211 |
+ 012315.02 |
+ C57BL/6NJ |
+ N |
+ B |
+ 106 |
+ 2.09 |
+ 2.29 |
+ 156 |
+ 7.4 |
+ |
+
+
+ | 34 |
+ BCJ 34.CMS_ |
+ N-C-118-1 |
+ CMS_000118 |
+ 118 |
+ 012115.32 |
+ C57BL/6NJ |
+ N |
+ C |
+ 219.2 |
+ 1.91 |
+ 2.34 |
+ 197 |
+ 9.2 |
+ |
+
+
+ | 35 |
+ BCJ 35.CMS_ |
+ N-CR-127-1 |
+ CMS_000127 |
+ 127 |
+ 012215.33 |
+ C57BL/6NJ |
+ N |
+ CR |
+ 89 |
+ 2 |
+ 2.56 |
+ 157 |
+ 9.4 |
+ |
+
+
+ | 36 |
+ BCJ 36.CMS_ |
+ N-R-149-1 |
+ CMS_000149 |
+ 149 |
+ 012115.27 |
+ C57BL/6NJ |
+ N |
+ R |
+ 72.91 |
+ 1.84 |
+ 2.14 |
+ 107 |
+ 8.6 |
+ |
+
+
+ | 37 |
+ BCJ 37.CMS_ |
+ D-B-218-1 |
+ CMS_000218 |
+ 218 |
+ 020615.04 |
+ DBA/2J |
+ D |
+ B |
+ 154.34 |
+ 1.99 |
+ 1.99 |
+ 119 |
+ 9.3 |
+ |
+
+
+ | 38 |
+ BCJ 38.CMS_ |
+ D-C-87-1 |
+ CMS_000087 |
+ 87 |
+ 012215.13 |
+ DBA/2J |
+ D |
+ C |
+ 105.3 |
+ 1.98 |
+ 2.21 |
+ 109 |
+ 7.4 |
+ |
+
+
+ | 39 |
+ BCJ 39.CMS_ |
+ D-CR-97-1 |
+ CMS_000097 |
+ 97 |
+ 012315.05 |
+ DBA/2J |
+ D |
+ CR |
+ 55.85 |
+ 1.89 |
+ 2.41 |
+ 85 |
+ 8.3 |
+ |
+
+
+ | 40 |
+ BCJ 40.CMS_ |
+ D-R-137-1 |
+ CMS_000137 |
+ 137 |
+ 012315.06 |
+ DBA/2J |
+ D |
+ R |
+ 128.97 |
+ 2.01 |
+ 2.24 |
+ 159 |
+ 8.1 |
+ Microarray outlier; sample removed. |
+
+
+ | 41 |
+ BCJ 41.CMS_ |
+ B-B-206-1 |
+ CMS_000206 |
+ 206 |
+ 012115.02 |
+ C57BL/6J |
+ B |
+ B |
+ 159.89 |
+ 2.03 |
+ 2.1 |
+ 273 |
+ 7.8 |
+ |
+
+
+ | 42 |
+ BCJ 42.CMS_ |
+ B-C-103-1 |
+ CMS_000103 |
+ 103 |
+ 012215.15 |
+ C57BL/6J |
+ B |
+ C |
+ 111.79 |
+ 1.87 |
+ 2.45 |
+ 160 |
+ 8.9 |
+ |
+
+
+ | 43 |
+ BCJ 43.CMS_ |
+ B-CR-112-1 |
+ CMS_000112 |
+ 112 |
+ 012215.31 |
+ C57BL/6J |
+ B |
+ CR |
+ 172.14 |
+ 1.86 |
+ 2.22 |
+ 180 |
+ 9.4 |
+ |
+
+
+ | 44 |
+ BCJ 44.CMS_ |
+ B-R-145-1 |
+ CMS_000145 |
+ 145 |
+ 012315.12 |
+ C57BL/6J |
+ B |
+ R |
+ 103.74 |
+ 2.06 |
+ 2.17 |
+ 99 |
+ 8.9 |
+ |
+
+
+ | 45 |
+ BCJ 45.CMS_ |
+ N-B-212-1 |
+ CMS_000212 |
+ 212 |
+ 012315.04 |
+ C57BL/6NJ |
+ N |
+ B |
+ 189.5 |
+ 1.9 |
+ 2.4 |
+ 248 |
+ 8.5 |
+ |
+
+
+ | 47 |
+ BCJ 47.CMS_ |
+ N-CR-128-1 |
+ CMS_000128 |
+ 128 |
+ 012215.34 |
+ C57BL/6NJ |
+ N |
+ CR |
+ 90.65 |
+ 2.07 |
+ 2.25 |
+ 189 |
+ 9.3 |
+ |
+
+
+ | 48 |
+ BCJ 48.CMS_ |
+ N-R-154-1 |
+ CMS_000154 |
+ 154 |
+ 012315.29 |
+ C57BL/6NJ |
+ N |
+ R |
+ 114.73 |
+ 1.94 |
+ 2.34 |
+ 167 |
+ 8.8 |
+ |
+
+
+ | 49 |
+ BCJ 49.CMS_ |
+ D-C-88-1 |
+ CMS_000088 |
+ 88 |
+ 012215.28 |
+ DBA/2J |
+ D |
+ C |
+ 96 |
+ 1.76 |
+ 2.55 |
+ 158 |
+ 8.5 |
+ |
+
+
+ | 50 |
+ BCJ 50.CMS_ |
+ D-CR-96-1 |
+ CMS_000096 |
+ 96 |
+ 012215.21 |
+ DBA/2J |
+ D |
+ CR |
+ 133.66 |
+ 1.78 |
+ 2.36 |
+ 203 |
+ 8.3 |
+ |
+
+
+ | 51 |
+ BCJ 51.CMS_ |
+ D-R-138-1 |
+ CMS_000138 |
+ 138 |
+ 012315.22 |
+ DBA/2J |
+ D |
+ R |
+ 127.13 |
+ 1.76 |
+ 2.24 |
+ 81 |
+ 9.3 |
+ |
+
+
+ | 52 |
+ BCJ 52.CMS_ |
+ B-C-105-1 |
+ CMS_000105 |
+ 105 |
+ 012315.13 |
+ C57BL/6J |
+ B |
+ C |
+ 203.24 |
+ 1.92 |
+ 2.35 |
+ 310 |
+ 7 |
+ |
+
+
+ | 53 |
+ BCJ 53.CMS_ |
+ B-CR-113-1 |
+ CMS_000113 |
+ 113 |
+ 012315.09 |
+ C57BL/6J |
+ B |
+ CR |
+ 168.67 |
+ 1.82 |
+ 2.41 |
+ 240 |
+ 9.1 |
+ |
+
+
+ | 55 |
+ BCJ 55.CMS_ |
+ N-C-120-1 |
+ CMS_000120 |
+ 120 |
+ 012215.32 |
+ C57BL/6NJ |
+ N |
+ C |
+ 73.67 |
+ 1.93 |
+ 2.31 |
+ 371 |
+ 8.4 |
+ |
+
+
+ | 56 |
+ BCJ 56.CMS_ |
+ N-CR-125-1 |
+ CMS_000125 |
+ 125 |
+ 012115.31 |
+ C57BL/6NJ |
+ N |
+ CR |
+ 121.93 |
+ 1.92 |
+ 2.26 |
+ 73 |
+ 8.3 |
+ |
+
+
+ | 59 |
+ BCJ 59.CMS_ |
+ N-C-122-1 |
+ CMS_000122 |
+ 122 |
+ 012315.30 |
+ C57BL/6NJ |
+ N |
+ C |
+ 131.74 |
+ 1.85 |
+ 2.42 |
+ 186 |
+ 9.4 |
+ |
+
+
+ | 60 |
+ BCJ 60.CMS_ |
+ D-C-89-1 |
+ CMS_000089 |
+ 89 |
+ 012315.10 |
+ DBA/2J |
+ D |
+ C |
+ 78 |
+ 1.77 |
+ 2.32 |
+ 74 |
+ 8.9 |
+ |
+
+
+ | 62 |
+ BCJ 62.CMS_ |
+ N-CR-130-1 |
+ CMS_000130 |
+ 130 |
+ 012315.34 |
+ C57BL/6NJ |
+ N |
+ CR |
+ 100.74 |
+ 1.71 |
+ 2.36 |
+ 113 |
+ 8.8 |
+ |
+
+
+ | 65 |
+ BCJ 65.CMS_ |
+ B-R-144-1 |
+ CMS_000144 |
+ 144 |
+ 012215.27 |
+ C57BL/6J |
+ B |
+ R |
+ 80.1 |
+ 1.81 |
+ 2.3 |
+ 95 |
+ 8.9 |
+ |
+
+
+ | 66 |
+ BCJ 66.CMS_ |
+ N-R-151-1 |
+ CMS_000151 |
+ 151 |
+ 012215.12 |
+ C57BL/6NJ |
+ N |
+ R |
+ 80.22 |
+ 1.77 |
+ 2.2 |
+ 116 |
+ 8.6 |
+ |
+
+
+
diff --git a/general/datasets/Cms_hipp1115/contributors.rtf b/general/datasets/Cms_hipp1115/contributors.rtf
new file mode 100644
index 0000000..3ac780e
--- /dev/null
+++ b/general/datasets/Cms_hipp1115/contributors.rtf
@@ -0,0 +1 @@
+This data set is part of a collaborative effort between UTHSC investigators Byron Jones, Rob Williams, Megan Mulligan, and Lu Lu and collaborators at I.N.R.A Centre de recherche de Toulouse Terenina, Pierre Mormede and Elena Terenina.
diff --git a/general/datasets/Cms_hipp1115/experiment-design.rtf b/general/datasets/Cms_hipp1115/experiment-design.rtf
new file mode 100644
index 0000000..f2d6c93
--- /dev/null
+++ b/general/datasets/Cms_hipp1115/experiment-design.rtf
@@ -0,0 +1,9 @@
+This data set includes four experimental conditions, B (baseline, untreated), C (chronic mild stress), CR (chronic mild stress followed by acute restraint), and R (acute restraint only).
+
+B = untreated
+
+C = 7 weeks of chronic unpredictable stress
+
+R = 30 minutes of restraint
+
+CR = 7 weeks of chronic unpredictable stress followed by 30 minutes of restraint
diff --git a/general/datasets/Cms_hipp1115/processing.rtf b/general/datasets/Cms_hipp1115/processing.rtf
new file mode 100644
index 0000000..1b6ca30
--- /dev/null
+++ b/general/datasets/Cms_hipp1115/processing.rtf
@@ -0,0 +1,3 @@
+Outlier Detection. Samples 7 (J-CR-21), 24 (N-R-29), and 40 (D-R-6) were detected as outliers and have abnormal expression profiles (i.e. they do not cluster with other samples and have abnormal median and quartile ranges after normalization. These samples have been removed from the analysis.
+
+RMA Algorithm. The Robust Multichip Analysis (RMA) algorithm fits a robust linear model at the probe level to minimize the effect of probe-specific affinity differences. This approach: n Increases sensitivity to small changes between experiment and control samples. n Minimizes variance across the dynamic range, but does compress calculated fold change values. RMA consists of three steps: 1. Background adjustment 2. Quantile normalization 3. Summarization This is a multi-chip analysis approach. Therefore, all arrays intended for comparison should be included together in the summarization step. For a more detailed description of the RMA algorithm, see the publication, Exploration, Normalization, and Summaries of High Density Oligonucleotide Array Probe Level Data, Biostatistics, April 2003; Vol. 4; Number 2: 249–264.
diff --git a/general/datasets/Cms_hipp1115/summary.rtf b/general/datasets/Cms_hipp1115/summary.rtf
new file mode 100644
index 0000000..1fededf
--- /dev/null
+++ b/general/datasets/Cms_hipp1115/summary.rtf
@@ -0,0 +1 @@
+This data set was generated to study the effects of strain and stress on hippocampal gene expression in female mice. The data set includes three inbred strains of mice and four treatment groups.
diff --git a/general/datasets/Cms_hipp1115/tissue.rtf b/general/datasets/Cms_hipp1115/tissue.rtf
new file mode 100644
index 0000000..25b50be
--- /dev/null
+++ b/general/datasets/Cms_hipp1115/tissue.rtf
@@ -0,0 +1 @@
+This data set includes expression data from mouse hippocampus.
diff --git a/general/datasets/Cms_hipp_zscr_1115/cases.rtf b/general/datasets/Cms_hipp_zscr_1115/cases.rtf
new file mode 100644
index 0000000..c201f08
--- /dev/null
+++ b/general/datasets/Cms_hipp_zscr_1115/cases.rtf
@@ -0,0 +1,992 @@
+The original data set included four individuals of each strain under baseline (B) conditions and eight individuals from each strain for each of the treatment groups, chronic mild stress (C), acute restraint (R), and chronic mild stress followed by acute retraint (CR). However, some samples have been removed due to technical problems with tissue collection or microarray performance.
+
+
+
+
+ | MTA_ID |
+ MTA prefix |
+ GN_ID |
+ FM_ID |
+ Mouse_ID |
+ CaseId |
+ Strain |
+ Strain_Code |
+ Treatment code |
+ NanoDrop, ng/ul |
+ NanoDrop, 260/280 |
+ NanoDrop, 260/230 |
+ Agilent, ng/µl |
+ RIN |
+ Notes |
+
+
+ | 1 |
+ BCJ 1.CMS_ |
+ D-B-215-1 |
+ CMS_000215 |
+ 215 |
+ 020615.01 |
+ DBA/2J |
+ D |
+ B |
+ 163.61 |
+ 1.9 |
+ 2.31 |
+ 130 |
+ 8.6 |
+ |
+
+
+ | 2 |
+ BCJ 2.CMS_ |
+ D-C-86-1 |
+ CMS_000086 |
+ 86 |
+ 012115.23 |
+ DBA/2J |
+ D |
+ C |
+ 98.51 |
+ 1.79 |
+ 2.4 |
+ 329 |
+ 8.8 |
+ |
+
+
+ | 3 |
+ BCJ 3.CMS_ |
+ D-CR-94-1 |
+ CMS_000094 |
+ 94 |
+ 012115.16 |
+ DBA/2J |
+ D |
+ CR |
+ 162.78 |
+ 1.87 |
+ 2.38 |
+ 166 |
+ 9.2 |
+ |
+
+
+ | 4 |
+ BCJ 4.CMS_ |
+ D-R-133-1 |
+ CMS_000133 |
+ 133 |
+ 012115.14 |
+ DBA/2J |
+ D |
+ R |
+ 88.95 |
+ 1.82 |
+ 2.45 |
+ 90 |
+ 8.2 |
+ |
+
+
+ | 5 |
+ BCJ 5.CMS_ |
+ B-B-208-1 |
+ CMS_000208 |
+ 208 |
+ 012215.04 |
+ C57BL/6J |
+ B |
+ B |
+ 129.24 |
+ 1.86 |
+ 2.41 |
+ 223 |
+ 8.1 |
+ |
+
+
+ | 6 |
+ BCJ 6.CMS_ |
+ B-C-101-1 |
+ CMS_000101 |
+ 101 |
+ 012115.25 |
+ C57BL/6J |
+ B |
+ C |
+ 72.29 |
+ 1.86 |
+ 2.26 |
+ 135 |
+ 9.2 |
+ |
+
+
+ | 7 |
+ BCJ 7.CMS_ |
+ B-CR-109-1 |
+ CMS_000109 |
+ 109 |
+ 012115.21 |
+ C57BL/6J |
+ B |
+ CR |
+ 158.56 |
+ 1.7 |
+ 2.46 |
+ 305 |
+ 8.8 |
+ Microarray outlier; sample removed. |
+
+
+ | 8 |
+ BCJ 8.CMS_ |
+ B-R-143-1 |
+ CMS_000143 |
+ 143 |
+ 012215.08 |
+ C57BL/6J |
+ B |
+ R |
+ 161.57 |
+ 1.86 |
+ 2.38 |
+ 217 |
+ 9.3 |
+ |
+
+
+ | 9 |
+ BCJ 9.CMS_ |
+ N-B-210-1 |
+ CMS_000210 |
+ 210 |
+ 012115.04 |
+ C57BL/6NJ |
+ N |
+ B |
+ 132.39 |
+ 1.89 |
+ 2.3 |
+ 192 |
+ 8.5 |
+ |
+
+
+ | 10 |
+ BCJ 10.CMS_ |
+ N-C-117-1 |
+ CMS_000117 |
+ 117 |
+ 012115.30 |
+ C57BL/6NJ |
+ N |
+ C |
+ 151.43 |
+ 1.91 |
+ 2.38 |
+ 187 |
+ 8.8 |
+ |
+
+
+ | 11 |
+ BCJ 11.CMS_ |
+ N-CR-126-1 |
+ CMS_000126 |
+ 126 |
+ 012115.33 |
+ C57BL/6NJ |
+ N |
+ CR |
+ 137.87 |
+ 1.88 |
+ 2.29 |
+ 76 |
+ 9 |
+ |
+
+
+ | 12 |
+ BCJ 12.CMS_ |
+ N-R-152-1 |
+ CMS_000152 |
+ 152 |
+ 012215.29 |
+ C57BL/6NJ |
+ N |
+ R |
+ 197.95 |
+ 1.88 |
+ 2.35 |
+ 150 |
+ 9.1 |
+ |
+
+
+ | 13 |
+ BCJ 13.CMS_ |
+ D-B-216-1 |
+ CMS_000216 |
+ 216 |
+ 020615.02 |
+ DBA/2J |
+ D |
+ B |
+ 98.64 |
+ 1.91 |
+ 2.03 |
+ 60 |
+ 8.6 |
+ |
+
+
+ | 15 |
+ BCJ 15.CMS_ |
+ D-CR-93-1 |
+ CMS_000093 |
+ 93 |
+ 012115.11 |
+ DBA/2J |
+ D |
+ CR |
+ 71.36 |
+ 1.83 |
+ 2.25 |
+ 109 |
+ 8.5 |
+ |
+
+
+ | 16 |
+ BCJ 16.CMS_ |
+ D-R-134-1 |
+ CMS_000134 |
+ 134 |
+ 012115.17 |
+ DBA/2J |
+ D |
+ R |
+ 73.49 |
+ 1.85 |
+ 2.43 |
+ 149 |
+ 8.2 |
+ |
+
+
+ | 17 |
+ BCJ 17.CMS_ |
+ B-B-205-1 |
+ CMS_000205 |
+ 205 |
+ 012015.02 |
+ C57BL/6J |
+ B |
+ B |
+ 174.78 |
+ 2.02 |
+ 2.21 |
+ 266 |
+ 8.9 |
+ |
+
+
+ | 18 |
+ BCJ 18.CMS_ |
+ B-C-104-1 |
+ CMS_000104 |
+ 104 |
+ 012215.30 |
+ C57BL/6J |
+ B |
+ C |
+ 84.7 |
+ 2.64 |
+ 2.01 |
+ 168 |
+ 9.2 |
+ |
+
+
+ | 19 |
+ BCJ 19.CMS_ |
+ B-CR-110-1 |
+ CMS_000110 |
+ 110 |
+ 012115.26 |
+ C57BL/6J |
+ B |
+ CR |
+ 136.7 |
+ 1.96 |
+ 2.16 |
+ 178 |
+ 9.5 |
+ |
+
+
+ | 20 |
+ BCJ 20.CMS_ |
+ B-R-141-1 |
+ CMS_000141 |
+ 141 |
+ 012115.22 |
+ C57BL/6J |
+ B |
+ R |
+ 86.04 |
+ 20.2 |
+ 2.53 |
+ 208 |
+ 8.9 |
+ |
+
+
+ | 21 |
+ BCJ 21.CMS_ |
+ N-B-209-1 |
+ CMS_000209 |
+ 209 |
+ 012015.04 |
+ C57BL/6NJ |
+ N |
+ B |
+ 98.3 |
+ 1.99 |
+ 2.35 |
+ 169 |
+ 8.8 |
+ |
+
+
+ | 22 |
+ BCJ 22.CMS_ |
+ N-C-119-1 |
+ CMS_000119 |
+ 119 |
+ 012215.18 |
+ C57BL/6NJ |
+ N |
+ C |
+ 94.63 |
+ 1.96 |
+ 2.36 |
+ 179 |
+ 8.5 |
+ |
+
+
+ | 24 |
+ BCJ 24.CMS_ |
+ N-R-150-1 |
+ CMS_000150 |
+ 150 |
+ 012115.29 |
+ C57BL/6NJ |
+ N |
+ R |
+ 407.34 |
+ 1.98 |
+ 2.24 |
+ 425 |
+ 7.5 |
+ Microarray outlier; sample removed. |
+
+
+ | 25 |
+ BCJ 25.CMS_ |
+ D-B-217-1 |
+ CMS_000217 |
+ 217 |
+ 020615.03 |
+ DBA/2J |
+ D |
+ B |
+ 84.61 |
+ 1.82 |
+ 2.18 |
+ 177 |
+ 7.9 |
+ |
+
+
+ | 26 |
+ BCJ 26.CMS_ |
+ D-C-85-1 |
+ CMS_000085 |
+ 85 |
+ 012115.20 |
+ DBA/2J |
+ D |
+ C |
+ 172.86 |
+ 1.98 |
+ 2.27 |
+ 288 |
+ 8.9 |
+ |
+
+
+ | 27 |
+ BCJ 27.CMS_ |
+ D-CR-95-1 |
+ CMS_000095 |
+ 95 |
+ 012215.16 |
+ DBA/2J |
+ D |
+ CR |
+ 109.8 |
+ 1.98 |
+ 2.47 |
+ 157 |
+ 8.9 |
+ |
+
+
+ | 28 |
+ BCJ 28.CMS_ |
+ D-R-132-1 |
+ CMS_000132 |
+ 132 |
+ 012015.29 |
+ DBA/2J |
+ D |
+ R |
+ 140.82 |
+ 1.91 |
+ 2.47 |
+ 318 |
+ 9 |
+ |
+
+
+ | 29 |
+ BCJ 29.CMS_ |
+ B-B-207-1 |
+ CMS_000207 |
+ 207 |
+ 012215.02 |
+ C57BL/6J |
+ B |
+ B |
+ 96.25 |
+ 1.89 |
+ 2.67 |
+ 176 |
+ 8.5 |
+ |
+
+
+ | 30 |
+ BCJ 30.CMS_ |
+ B-C-102-1 |
+ CMS_000102 |
+ 102 |
+ 012115.28 |
+ C57BL/6J |
+ B |
+ C |
+ 129.69 |
+ 1.89 |
+ 2.32 |
+ 105 |
+ 8.7 |
+ |
+
+
+ | 31 |
+ BCJ 31.CMS_ |
+ B-CR-111-1 |
+ CMS_000111 |
+ 111 |
+ 012215.26 |
+ C57BL/6J |
+ B |
+ CR |
+ 165.67 |
+ 1.84 |
+ 2.31 |
+ 176 |
+ 9.5 |
+ |
+
+
+ | 32 |
+ BCJ 32.CMS_ |
+ B-R-142-1 |
+ CMS_000142 |
+ 142 |
+ 012115.24 |
+ C57BL/6J |
+ B |
+ R |
+ 116.93 |
+ 1.84 |
+ 2.22 |
+ 96 |
+ 9.4 |
+ |
+
+
+ | 33 |
+ BCJ 33.CMS_ |
+ N-B-211-1 |
+ CMS_000211 |
+ 211 |
+ 012315.02 |
+ C57BL/6NJ |
+ N |
+ B |
+ 106 |
+ 2.09 |
+ 2.29 |
+ 156 |
+ 7.4 |
+ |
+
+
+ | 34 |
+ BCJ 34.CMS_ |
+ N-C-118-1 |
+ CMS_000118 |
+ 118 |
+ 012115.32 |
+ C57BL/6NJ |
+ N |
+ C |
+ 219.2 |
+ 1.91 |
+ 2.34 |
+ 197 |
+ 9.2 |
+ |
+
+
+ | 35 |
+ BCJ 35.CMS_ |
+ N-CR-127-1 |
+ CMS_000127 |
+ 127 |
+ 012215.33 |
+ C57BL/6NJ |
+ N |
+ CR |
+ 89 |
+ 2 |
+ 2.56 |
+ 157 |
+ 9.4 |
+ |
+
+
+ | 36 |
+ BCJ 36.CMS_ |
+ N-R-149-1 |
+ CMS_000149 |
+ 149 |
+ 012115.27 |
+ C57BL/6NJ |
+ N |
+ R |
+ 72.91 |
+ 1.84 |
+ 2.14 |
+ 107 |
+ 8.6 |
+ |
+
+
+ | 37 |
+ BCJ 37.CMS_ |
+ D-B-218-1 |
+ CMS_000218 |
+ 218 |
+ 020615.04 |
+ DBA/2J |
+ D |
+ B |
+ 154.34 |
+ 1.99 |
+ 1.99 |
+ 119 |
+ 9.3 |
+ |
+
+
+ | 38 |
+ BCJ 38.CMS_ |
+ D-C-87-1 |
+ CMS_000087 |
+ 87 |
+ 012215.13 |
+ DBA/2J |
+ D |
+ C |
+ 105.3 |
+ 1.98 |
+ 2.21 |
+ 109 |
+ 7.4 |
+ |
+
+
+ | 39 |
+ BCJ 39.CMS_ |
+ D-CR-97-1 |
+ CMS_000097 |
+ 97 |
+ 012315.05 |
+ DBA/2J |
+ D |
+ CR |
+ 55.85 |
+ 1.89 |
+ 2.41 |
+ 85 |
+ 8.3 |
+ |
+
+
+ | 40 |
+ BCJ 40.CMS_ |
+ D-R-137-1 |
+ CMS_000137 |
+ 137 |
+ 012315.06 |
+ DBA/2J |
+ D |
+ R |
+ 128.97 |
+ 2.01 |
+ 2.24 |
+ 159 |
+ 8.1 |
+ Microarray outlier; sample removed. |
+
+
+ | 41 |
+ BCJ 41.CMS_ |
+ B-B-206-1 |
+ CMS_000206 |
+ 206 |
+ 012115.02 |
+ C57BL/6J |
+ B |
+ B |
+ 159.89 |
+ 2.03 |
+ 2.1 |
+ 273 |
+ 7.8 |
+ |
+
+
+ | 42 |
+ BCJ 42.CMS_ |
+ B-C-103-1 |
+ CMS_000103 |
+ 103 |
+ 012215.15 |
+ C57BL/6J |
+ B |
+ C |
+ 111.79 |
+ 1.87 |
+ 2.45 |
+ 160 |
+ 8.9 |
+ |
+
+
+ | 43 |
+ BCJ 43.CMS_ |
+ B-CR-112-1 |
+ CMS_000112 |
+ 112 |
+ 012215.31 |
+ C57BL/6J |
+ B |
+ CR |
+ 172.14 |
+ 1.86 |
+ 2.22 |
+ 180 |
+ 9.4 |
+ |
+
+
+ | 44 |
+ BCJ 44.CMS_ |
+ B-R-145-1 |
+ CMS_000145 |
+ 145 |
+ 012315.12 |
+ C57BL/6J |
+ B |
+ R |
+ 103.74 |
+ 2.06 |
+ 2.17 |
+ 99 |
+ 8.9 |
+ |
+
+
+ | 45 |
+ BCJ 45.CMS_ |
+ N-B-212-1 |
+ CMS_000212 |
+ 212 |
+ 012315.04 |
+ C57BL/6NJ |
+ N |
+ B |
+ 189.5 |
+ 1.9 |
+ 2.4 |
+ 248 |
+ 8.5 |
+ |
+
+
+ | 47 |
+ BCJ 47.CMS_ |
+ N-CR-128-1 |
+ CMS_000128 |
+ 128 |
+ 012215.34 |
+ C57BL/6NJ |
+ N |
+ CR |
+ 90.65 |
+ 2.07 |
+ 2.25 |
+ 189 |
+ 9.3 |
+ |
+
+
+ | 48 |
+ BCJ 48.CMS_ |
+ N-R-154-1 |
+ CMS_000154 |
+ 154 |
+ 012315.29 |
+ C57BL/6NJ |
+ N |
+ R |
+ 114.73 |
+ 1.94 |
+ 2.34 |
+ 167 |
+ 8.8 |
+ |
+
+
+ | 49 |
+ BCJ 49.CMS_ |
+ D-C-88-1 |
+ CMS_000088 |
+ 88 |
+ 012215.28 |
+ DBA/2J |
+ D |
+ C |
+ 96 |
+ 1.76 |
+ 2.55 |
+ 158 |
+ 8.5 |
+ |
+
+
+ | 50 |
+ BCJ 50.CMS_ |
+ D-CR-96-1 |
+ CMS_000096 |
+ 96 |
+ 012215.21 |
+ DBA/2J |
+ D |
+ CR |
+ 133.66 |
+ 1.78 |
+ 2.36 |
+ 203 |
+ 8.3 |
+ |
+
+
+ | 51 |
+ BCJ 51.CMS_ |
+ D-R-138-1 |
+ CMS_000138 |
+ 138 |
+ 012315.22 |
+ DBA/2J |
+ D |
+ R |
+ 127.13 |
+ 1.76 |
+ 2.24 |
+ 81 |
+ 9.3 |
+ |
+
+
+ | 52 |
+ BCJ 52.CMS_ |
+ B-C-105-1 |
+ CMS_000105 |
+ 105 |
+ 012315.13 |
+ C57BL/6J |
+ B |
+ C |
+ 203.24 |
+ 1.92 |
+ 2.35 |
+ 310 |
+ 7 |
+ |
+
+
+ | 53 |
+ BCJ 53.CMS_ |
+ B-CR-113-1 |
+ CMS_000113 |
+ 113 |
+ 012315.09 |
+ C57BL/6J |
+ B |
+ CR |
+ 168.67 |
+ 1.82 |
+ 2.41 |
+ 240 |
+ 9.1 |
+ |
+
+
+ | 55 |
+ BCJ 55.CMS_ |
+ N-C-120-1 |
+ CMS_000120 |
+ 120 |
+ 012215.32 |
+ C57BL/6NJ |
+ N |
+ C |
+ 73.67 |
+ 1.93 |
+ 2.31 |
+ 371 |
+ 8.4 |
+ |
+
+
+ | 56 |
+ BCJ 56.CMS_ |
+ N-CR-125-1 |
+ CMS_000125 |
+ 125 |
+ 012115.31 |
+ C57BL/6NJ |
+ N |
+ CR |
+ 121.93 |
+ 1.92 |
+ 2.26 |
+ 73 |
+ 8.3 |
+ |
+
+
+ | 59 |
+ BCJ 59.CMS_ |
+ N-C-122-1 |
+ CMS_000122 |
+ 122 |
+ 012315.30 |
+ C57BL/6NJ |
+ N |
+ C |
+ 131.74 |
+ 1.85 |
+ 2.42 |
+ 186 |
+ 9.4 |
+ |
+
+
+ | 60 |
+ BCJ 60.CMS_ |
+ D-C-89-1 |
+ CMS_000089 |
+ 89 |
+ 012315.10 |
+ DBA/2J |
+ D |
+ C |
+ 78 |
+ 1.77 |
+ 2.32 |
+ 74 |
+ 8.9 |
+ |
+
+
+ | 62 |
+ BCJ 62.CMS_ |
+ N-CR-130-1 |
+ CMS_000130 |
+ 130 |
+ 012315.34 |
+ C57BL/6NJ |
+ N |
+ CR |
+ 100.74 |
+ 1.71 |
+ 2.36 |
+ 113 |
+ 8.8 |
+ |
+
+
+ | 65 |
+ BCJ 65.CMS_ |
+ B-R-144-1 |
+ CMS_000144 |
+ 144 |
+ 012215.27 |
+ C57BL/6J |
+ B |
+ R |
+ 80.1 |
+ 1.81 |
+ 2.3 |
+ 95 |
+ 8.9 |
+ |
+
+
+ | 66 |
+ BCJ 66.CMS_ |
+ N-R-151-1 |
+ CMS_000151 |
+ 151 |
+ 012215.12 |
+ C57BL/6NJ |
+ N |
+ R |
+ 80.22 |
+ 1.77 |
+ 2.2 |
+ 116 |
+ 8.6 |
+ |
+
+
+
diff --git a/general/datasets/Cms_hipp_zscr_1115/contributors.rtf b/general/datasets/Cms_hipp_zscr_1115/contributors.rtf
new file mode 100644
index 0000000..3ac780e
--- /dev/null
+++ b/general/datasets/Cms_hipp_zscr_1115/contributors.rtf
@@ -0,0 +1 @@
+This data set is part of a collaborative effort between UTHSC investigators Byron Jones, Rob Williams, Megan Mulligan, and Lu Lu and collaborators at I.N.R.A Centre de recherche de Toulouse Terenina, Pierre Mormede and Elena Terenina.
diff --git a/general/datasets/Cms_hipp_zscr_1115/experiment-design.rtf b/general/datasets/Cms_hipp_zscr_1115/experiment-design.rtf
new file mode 100644
index 0000000..f2d6c93
--- /dev/null
+++ b/general/datasets/Cms_hipp_zscr_1115/experiment-design.rtf
@@ -0,0 +1,9 @@
+This data set includes four experimental conditions, B (baseline, untreated), C (chronic mild stress), CR (chronic mild stress followed by acute restraint), and R (acute restraint only).
+
+B = untreated
+
+C = 7 weeks of chronic unpredictable stress
+
+R = 30 minutes of restraint
+
+CR = 7 weeks of chronic unpredictable stress followed by 30 minutes of restraint
diff --git a/general/datasets/Cms_hipp_zscr_1115/processing.rtf b/general/datasets/Cms_hipp_zscr_1115/processing.rtf
new file mode 100644
index 0000000..1b6ca30
--- /dev/null
+++ b/general/datasets/Cms_hipp_zscr_1115/processing.rtf
@@ -0,0 +1,3 @@
+Outlier Detection. Samples 7 (J-CR-21), 24 (N-R-29), and 40 (D-R-6) were detected as outliers and have abnormal expression profiles (i.e. they do not cluster with other samples and have abnormal median and quartile ranges after normalization. These samples have been removed from the analysis.
+
+RMA Algorithm. The Robust Multichip Analysis (RMA) algorithm fits a robust linear model at the probe level to minimize the effect of probe-specific affinity differences. This approach: n Increases sensitivity to small changes between experiment and control samples. n Minimizes variance across the dynamic range, but does compress calculated fold change values. RMA consists of three steps: 1. Background adjustment 2. Quantile normalization 3. Summarization This is a multi-chip analysis approach. Therefore, all arrays intended for comparison should be included together in the summarization step. For a more detailed description of the RMA algorithm, see the publication, Exploration, Normalization, and Summaries of High Density Oligonucleotide Array Probe Level Data, Biostatistics, April 2003; Vol. 4; Number 2: 249–264.
diff --git a/general/datasets/Cms_hipp_zscr_1115/specifics.rtf b/general/datasets/Cms_hipp_zscr_1115/specifics.rtf
new file mode 100644
index 0000000..5d45792
--- /dev/null
+++ b/general/datasets/Cms_hipp_zscr_1115/specifics.rtf
@@ -0,0 +1 @@
+Z-Score. In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Cms_hipp_zscr_1115/summary.rtf b/general/datasets/Cms_hipp_zscr_1115/summary.rtf
new file mode 100644
index 0000000..1fededf
--- /dev/null
+++ b/general/datasets/Cms_hipp_zscr_1115/summary.rtf
@@ -0,0 +1 @@
+This data set was generated to study the effects of strain and stress on hippocampal gene expression in female mice. The data set includes three inbred strains of mice and four treatment groups.
diff --git a/general/datasets/Cms_hipp_zscr_1115/tissue.rtf b/general/datasets/Cms_hipp_zscr_1115/tissue.rtf
new file mode 100644
index 0000000..25b50be
--- /dev/null
+++ b/general/datasets/Cms_hipp_zscr_1115/tissue.rtf
@@ -0,0 +1 @@
+This data set includes expression data from mouse hippocampus.
diff --git a/general/datasets/Crtd_hipprecell1214/acknowledgment.rtf b/general/datasets/Crtd_hipprecell1214/acknowledgment.rtf
new file mode 100644
index 0000000..71728a6
--- /dev/null
+++ b/general/datasets/Crtd_hipprecell1214/acknowledgment.rtf
@@ -0,0 +1 @@
+Financial support covering the breeding and supply of BXD mice was provided by the Helmholtz Virtual Institute GENESYS (German Network of Systems Genetics, VH-VI-242)
diff --git a/general/datasets/Crtd_hipprecell1214/cases.rtf b/general/datasets/Crtd_hipprecell1214/cases.rtf
new file mode 100644
index 0000000..8116156
--- /dev/null
+++ b/general/datasets/Crtd_hipprecell1214/cases.rtf
@@ -0,0 +1 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 8 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 10 inbred (F20+) BXD lines generated by Lu and Peirce. In addition, the parental strains C57BL/6J and DBA/2J were used to yield a total of 20 genetically unique cell lines. All of these strains have been genotyped at 13,377 SNPs.
diff --git a/general/datasets/Crtd_hipprecell1214/citation.rtf b/general/datasets/Crtd_hipprecell1214/citation.rtf
new file mode 100644
index 0000000..32c44ca
--- /dev/null
+++ b/general/datasets/Crtd_hipprecell1214/citation.rtf
@@ -0,0 +1 @@
+Please cite: Kannan S, Nicola Z, Overall RW, Ichwan M, Ramírez-Rodríguez G, Grzyb A, Patone G, Saar K, Hübner N, Kempermann G (2016). Systems Genetics Analysis of a Recombinant Inbred Mouse Cell Culture Panel Reveals Wnt Pathway Member Lrp6 as a Regulator of Adult Hippocampal Precursor Cell Proliferation. Stem Cells 34(3):674–84. PMID: 26840599.
diff --git a/general/datasets/Crtd_hipprecell1214/contributors.rtf b/general/datasets/Crtd_hipprecell1214/contributors.rtf
new file mode 100644
index 0000000..2f3a8bd
--- /dev/null
+++ b/general/datasets/Crtd_hipprecell1214/contributors.rtf
@@ -0,0 +1 @@
+Gerd Kempermann CRTD – Center for Regenerative Therapies Dresden Technische Universität Dresden 01307 Dresden Germany
diff --git a/general/datasets/Crtd_hipprecell1214/experiment-design.rtf b/general/datasets/Crtd_hipprecell1214/experiment-design.rtf
new file mode 100644
index 0000000..c266448
--- /dev/null
+++ b/general/datasets/Crtd_hipprecell1214/experiment-design.rtf
@@ -0,0 +1 @@
+Each culture was derived from between 6 and 12 mice of c. 6 weeks old and of mixed sexes. Sex ratios in each batch varied. Triplicate cultures, from the same line but of different passage numbers, were used for RNA collection. Quantile normalisation of probe-level values was performed, and data for all probes mapping to the same Entrez GeneID were merged as means. No further adjustment of the data was done.
diff --git a/general/datasets/Crtd_hipprecell1214/notes.rtf b/general/datasets/Crtd_hipprecell1214/notes.rtf
new file mode 100644
index 0000000..f2b1272
--- /dev/null
+++ b/general/datasets/Crtd_hipprecell1214/notes.rtf
@@ -0,0 +1,3 @@
+This study is associated with the following records from the BXD Phenotype Database:
+
+17347, 17348, 17349
diff --git a/general/datasets/Crtd_hipprecell1214/platform.rtf b/general/datasets/Crtd_hipprecell1214/platform.rtf
new file mode 100644
index 0000000..bbe0b51
--- /dev/null
+++ b/general/datasets/Crtd_hipprecell1214/platform.rtf
@@ -0,0 +1 @@
+Illumina MouseWG-6 array with custom probe mapping: This data set uses a custom mapping of probes to Entrez GeneIDs. Each probe sequence on the MouseWG-6 v. 2.0 array was queried against the mm9 mouse genome using Jim Kent's BLAT program. The genomic position of probes returning a single hit was then used to assign the probe to an NCBI Entrez GeneID. Probes targeting the same GeneID were collapsed as means to yield data for 21155 unique genes.
diff --git a/general/datasets/Crtd_hipprecell1214/processing.rtf b/general/datasets/Crtd_hipprecell1214/processing.rtf
new file mode 100644
index 0000000..51df24a
--- /dev/null
+++ b/general/datasets/Crtd_hipprecell1214/processing.rtf
@@ -0,0 +1 @@
+Raw data were preprocessed with quantile normalisation in R/Bioconductor using the package beadarray. After probe reannotation, data from probes targeting the same GeneID were collapsed as means. This results in a single unique probe set associated with each of the Entrez GeneIDs covered.
diff --git a/general/datasets/Crtd_hipprecell1214/summary.rtf b/general/datasets/Crtd_hipprecell1214/summary.rtf
new file mode 100644
index 0000000..be648f2
--- /dev/null
+++ b/general/datasets/Crtd_hipprecell1214/summary.rtf
@@ -0,0 +1 @@
+This data set was generated from proliferating adherent cultures of adult hippocampus-derived precursor cells from 20 BXD strains. The dentate gyrus of the mouse hippocampus is the site of continued neural precursor proliferation and generation of new neurons in adulthood as a distinct process from the widespread embryonic and juvenile neurogenesis during development. Adult-derived precursors can be isolated and maintained in adherent culture (Babu et al., 2007, 2011) and can be differentiated into neurons, astrocytes and oligodendrocytes. In this study, cultures were established from 20 BXD strains obtained through the authors’ involvement in the GeNeSys Consortium. This data set was obtained from cultures actively proliferating in the presence of growth factors.
diff --git a/general/datasets/Crtd_hipprecell1214/tissue.rtf b/general/datasets/Crtd_hipprecell1214/tissue.rtf
new file mode 100644
index 0000000..f45211e
--- /dev/null
+++ b/general/datasets/Crtd_hipprecell1214/tissue.rtf
@@ -0,0 +1 @@
+The mice used in this study were bred at Harlan () for the GeNeSys Consortium and were delivered to the study site in Dresden at c. 6 weeks of age. Some animals were the 1st generation offspring of the Harlan stock which were bred and raised locally at the CRTD (housed at the Medizinisch-Theoretisches Zentrum of the Technische Universität Dresden). Animals were killed the day after delivery (or at 6 weeks of age if locally bred) and the hippocampi dissected and processed for precursor cell culture (Babu et al., 2011). Proliferating cultures were maintained in the presence of EGF and FGF-2 and passaged every 3-4 days. For microarray analysis, c. 1 million cells were harvested by on-plate lysis and total RNA prepared using the RNEasy mini kit (Qiagen) following the manufacturer’s protocol (including optional on-column DNase treatment). Each strain was assayed in triplicate (from 3 different passages).
diff --git a/general/datasets/Cubr_rna_0219/citation.rtf b/general/datasets/Cubr_rna_0219/citation.rtf
new file mode 100644
index 0000000..9406271
--- /dev/null
+++ b/general/datasets/Cubr_rna_0219/citation.rtf
@@ -0,0 +1,5 @@
+
+ - Rudra P, Shi WJ, Russell P, Vestal B et al. Predictive modeling of miRNA-mediated predisposition to alcohol-related phenotypes in mouse. BMC Genomics 2018 Aug 29;19(1):639. PMID: 30157779
+ - Russell PH, Vestal B, Shi W, Rudra PD et al. miR-MaGiC improves quantification accuracy for small RNA-seq. BMC Res Notes 2018 May 15;11(1):296. PMID: 29764489
+ - Rudra P, Shi WJ, Vestal B, Russell PH et al. Model based heritability scores for high-throughput sequencing data. BMC Bioinformatics 2017 Mar 2;18(1):143. PMID: 28253840
+
diff --git a/general/datasets/Cubr_rna_0219/contributors.rtf b/general/datasets/Cubr_rna_0219/contributors.rtf
new file mode 100644
index 0000000..a5ce46b
--- /dev/null
+++ b/general/datasets/Cubr_rna_0219/contributors.rtf
@@ -0,0 +1 @@
+Kechris K, Tabakoff B
diff --git a/general/datasets/Cubr_rna_0219/experiment-design.rtf b/general/datasets/Cubr_rna_0219/experiment-design.rtf
new file mode 100644
index 0000000..8ba40f7
--- /dev/null
+++ b/general/datasets/Cubr_rna_0219/experiment-design.rtf
@@ -0,0 +1 @@
+This dataset includes small RNA NGS sequencing data from 59 strains from the Inbred Long Sleep (ILS) and Inbred Short Sleep (ISS) Recombinant inbred mouse whole brain RNA samples. 175 mice (2-3 from each strain) were untreated (naive). The naive samples were provided by Boris Tabakoff, University of Colorado Anschutz Medical Campus. All expression data generation and analysis were conducted by the Kechris Group, University of Colorado Anschutz Medical Campus.
diff --git a/general/datasets/Cubr_rna_0219/notes.rtf b/general/datasets/Cubr_rna_0219/notes.rtf
new file mode 100644
index 0000000..84096b8
--- /dev/null
+++ b/general/datasets/Cubr_rna_0219/notes.rtf
@@ -0,0 +1 @@
+miRNA expression variance stabilized
diff --git a/general/datasets/Cubr_rna_0219/specifics.rtf b/general/datasets/Cubr_rna_0219/specifics.rtf
new file mode 100644
index 0000000..d301f7e
--- /dev/null
+++ b/general/datasets/Cubr_rna_0219/specifics.rtf
@@ -0,0 +1 @@
+based on ens_mirna_expression_variance_stabilized
\ No newline at end of file
diff --git a/general/datasets/Cubr_rna_0219/summary.rtf b/general/datasets/Cubr_rna_0219/summary.rtf
new file mode 100644
index 0000000..57e5529
--- /dev/null
+++ b/general/datasets/Cubr_rna_0219/summary.rtf
@@ -0,0 +1 @@
+We conducted a high-throughput sequencing study to measure whole brain miRNA expression levels in alcohol naïve animals in the LXS panel of recombinant inbred (RI) mouse strains. We then combined the sequencing data with genotype data, microarray gene expression data, and data on alcohol-related behavioral phenotypes such as 'Drinking in the dark', 'Sleep time', and 'Low dose activation' from the same RI panel.
diff --git a/general/datasets/DBA2J-ONH-1212/experiment-design.rtf b/general/datasets/DBA2J-ONH-1212/experiment-design.rtf
new file mode 100644
index 0000000..f01b888
--- /dev/null
+++ b/general/datasets/DBA2J-ONH-1212/experiment-design.rtf
@@ -0,0 +1,9 @@
+TEXT FROM GEO
+
+Genome-wide assessment of gene expression changes was performed in DBA/2J mice. The optic nerve head and retina from 40 DBA/2J eyes at 10.5 months of age were separately profiled. These eyes were selected as they encompassed a range of glaucoma severity. Two control groups were also included; 10 eyes from 10.5 months old D2-Gpnmb+ mice (age and strain matched, no glaucoma control) and 10 eyes from 4.5 months old DBA/2J mice (young, pre-glaucoma).
+
+In this study that was specifically designed to identify early stages of glaucoma in DBA/2J mice, we used genome-wide expression profiling and a series of computational methods. Our methods successfully subdivided eyes with no detectable glaucoma by conventional assays into molecularly defined stages of disease. These stages represent a temporally ordered sequence of glaucoma states. Using an array of tools, we then determined networks and biological processes that are altered at these early stages. Our strategy proved very sensitive, suggesting that similar approaches will be valuable for uncovering early processes in other complex, later-onset diseases. Early changes included upregulation of both the complement cascade and endothelin system, and so we tested the therapeutic value of separately inhibiting them. Mice with a mutation in the complement component 1a gene (C1qa) were robustly protected from glaucoma with the protection being among the greatest reported. Similarly, inhibition of the endothelin system was strongly protective. Since EDN2 is potently vasoconstrictive and was produced by microglial/macrophages, our data provide a novel link between these cell types and vascular dysfunction in glaucoma. Targeting early events such as the upregulation of the complement and endothelin pathways may provide effective new treatments for human glaucoma. (text above from GEO http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26299)
+
+
+
+
diff --git a/general/datasets/DBA2J-ONH-1212/summary.rtf b/general/datasets/DBA2J-ONH-1212/summary.rtf
new file mode 100644
index 0000000..09c8a43
--- /dev/null
+++ b/general/datasets/DBA2J-ONH-1212/summary.rtf
@@ -0,0 +1,58 @@
+This is an experimental glaucoma gene expression data set of retinal tissue entered into GeneNetwork by Dr. Eldon Geisert and Robert Williams in which BXD strains have been "highjacked" with experimental and control gene expression data generated by Drs Gareth Howell, Simon John, and colleagues at the Jackson Laboratory. These data were originally entered into GeneNetwork Sept 20, 2011.
+
+Please see the original paper by Howell et al (2011): http://www.jci.org/articles/view/44646 and GEO data at NCBI.
+
+Gareth R. Howell, Danilo G. Macalinao, Gregory L. Sousa, Michael Walden, Ileana Soto, Stephen C. Kneeland, Jessica M. Barbay, Benjamin L. King, Jeffrey K. Marchant, Matthew Hibbs, Beth Stevens, Ben A. Barres, Abbot F. Clark, Richard T. Libby, Simon S (2011) Molecular clustering identifies complement and endothelin induction as early events in a mouse model of glaucoma. J Clin Invest. 121:1429–1444
+
+Each strain corresponds to a particular retinal sample as shown below (note that we have not included ten "preglaucoma control" samples, see http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26299
+
+
+ - BXD1 D2-Gpnmb+ control rep1 (retina)
+ - BXD2 D2-Gpnmb+ control rep2 (retina)
+ - BXD5 D2-Gpnmb+ control rep3 (retina)
+ - BXD6 D2-Gpnmb+ control rep4 (retina)
+ - BXD8 D2-Gpnmb+ control rep5 (retina)
+ - BXD9 D2-Gpnmb+ control rep6 (retina)
+ - BXD11 D2-Gpnmb+ control rep7 (retina)
+ - BXD12 D2-Gpnmb+ control rep8 (retina)
+ - BXD13 D2-Gpnmb+ control rep9 (retina)
+ - BXD14 D2-Gpnmb+ control rep10 (retina)
+ - BXD15 No or early 1 rep1 (retina)
+ - BXD16 No or early 1 rep2 (retina)
+ - BXD18 No or early 1 rep3 (retina)
+ - BXD19 No or early 1 rep4 (retina)
+ - BXD20 No or early 1 rep5 (retina)
+ - BXD22 No or early 1 rep6 (retina)
+ - BXD23 No or early 1 rep7 (retina)
+ - BXD25 No or early 1 rep8 (retina)
+ - BXD27 No or early 1 rep9 (retina)
+ - BXD28 No or early 1 rep10 (retina)
+ - BXD29 No or early 2 rep1 (retina)
+ - BXD30 No or early 2 rep2 (retina)
+ - BXD31 No or early 2 rep3 (retina)
+ - BXD32 No or early 2 rep4 (retina)
+ - BXD33 No or early 2 rep5 (retina)
+ - BXD34 No or early 2 rep6 (retina)
+ - BXD35 No or early 2 rep7 (retina)
+ - BXD36 No or early 2 rep8 (retina)
+ - BXD37 No or early 2 rep9 (retina)
+ - BXD38 No or early 2 rep10 (retina)
+ - BXD39 Moderate rep1 (retina)
+ - BXD40 Moderate rep2 (retina)
+ - BXD41 Moderate rep3 (retina)
+ - BXD42 Moderate rep4 (retina)
+ - BXD43 Moderate rep7 (retina)
+ - BXD44 Moderate rep8 (retina)
+ - BXD45 Moderate rep9 (retina)
+ - BXD48 Moderate rep10 (retina)
+ - BXD49 Severe rep1 (retina)
+ - BXD50 Severe rep2 (retina)
+ - BXD51 Severe rep3 (retina)
+ - BXD52 Severe rep4 (retina)
+ - BXD53 Severe rep5 (retina)
+ - BXD54 Severe rep6 (retina)
+ - BXD55 Severe rep7 (retina)
+ - BXD56 Severe rep8 (retina)
+ - BXD59 Severe rep9 (retina)
+ - BXD60 Severe rep10 (retina)
+
diff --git a/general/datasets/DBA2J_ONH_1212/experiment-design.rtf b/general/datasets/DBA2J_ONH_1212/experiment-design.rtf
deleted file mode 100644
index f01b888..0000000
--- a/general/datasets/DBA2J_ONH_1212/experiment-design.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-TEXT FROM GEO
-
-Genome-wide assessment of gene expression changes was performed in DBA/2J mice. The optic nerve head and retina from 40 DBA/2J eyes at 10.5 months of age were separately profiled. These eyes were selected as they encompassed a range of glaucoma severity. Two control groups were also included; 10 eyes from 10.5 months old D2-Gpnmb+ mice (age and strain matched, no glaucoma control) and 10 eyes from 4.5 months old DBA/2J mice (young, pre-glaucoma).
-
-In this study that was specifically designed to identify early stages of glaucoma in DBA/2J mice, we used genome-wide expression profiling and a series of computational methods. Our methods successfully subdivided eyes with no detectable glaucoma by conventional assays into molecularly defined stages of disease. These stages represent a temporally ordered sequence of glaucoma states. Using an array of tools, we then determined networks and biological processes that are altered at these early stages. Our strategy proved very sensitive, suggesting that similar approaches will be valuable for uncovering early processes in other complex, later-onset diseases. Early changes included upregulation of both the complement cascade and endothelin system, and so we tested the therapeutic value of separately inhibiting them. Mice with a mutation in the complement component 1a gene (C1qa) were robustly protected from glaucoma with the protection being among the greatest reported. Similarly, inhibition of the endothelin system was strongly protective. Since EDN2 is potently vasoconstrictive and was produced by microglial/macrophages, our data provide a novel link between these cell types and vascular dysfunction in glaucoma. Targeting early events such as the upregulation of the complement and endothelin pathways may provide effective new treatments for human glaucoma. (text above from GEO http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26299)
-
-
-
-
diff --git a/general/datasets/DBA2J_ONH_1212/summary.rtf b/general/datasets/DBA2J_ONH_1212/summary.rtf
deleted file mode 100644
index 09c8a43..0000000
--- a/general/datasets/DBA2J_ONH_1212/summary.rtf
+++ /dev/null
@@ -1,58 +0,0 @@
-This is an experimental glaucoma gene expression data set of retinal tissue entered into GeneNetwork by Dr. Eldon Geisert and Robert Williams in which BXD strains have been "highjacked" with experimental and control gene expression data generated by Drs Gareth Howell, Simon John, and colleagues at the Jackson Laboratory. These data were originally entered into GeneNetwork Sept 20, 2011.
-
-Please see the original paper by Howell et al (2011): http://www.jci.org/articles/view/44646 and GEO data at NCBI.
-
-Gareth R. Howell, Danilo G. Macalinao, Gregory L. Sousa, Michael Walden, Ileana Soto, Stephen C. Kneeland, Jessica M. Barbay, Benjamin L. King, Jeffrey K. Marchant, Matthew Hibbs, Beth Stevens, Ben A. Barres, Abbot F. Clark, Richard T. Libby, Simon S (2011) Molecular clustering identifies complement and endothelin induction as early events in a mouse model of glaucoma. J Clin Invest. 121:1429–1444
-
-Each strain corresponds to a particular retinal sample as shown below (note that we have not included ten "preglaucoma control" samples, see http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26299
-
-
- - BXD1 D2-Gpnmb+ control rep1 (retina)
- - BXD2 D2-Gpnmb+ control rep2 (retina)
- - BXD5 D2-Gpnmb+ control rep3 (retina)
- - BXD6 D2-Gpnmb+ control rep4 (retina)
- - BXD8 D2-Gpnmb+ control rep5 (retina)
- - BXD9 D2-Gpnmb+ control rep6 (retina)
- - BXD11 D2-Gpnmb+ control rep7 (retina)
- - BXD12 D2-Gpnmb+ control rep8 (retina)
- - BXD13 D2-Gpnmb+ control rep9 (retina)
- - BXD14 D2-Gpnmb+ control rep10 (retina)
- - BXD15 No or early 1 rep1 (retina)
- - BXD16 No or early 1 rep2 (retina)
- - BXD18 No or early 1 rep3 (retina)
- - BXD19 No or early 1 rep4 (retina)
- - BXD20 No or early 1 rep5 (retina)
- - BXD22 No or early 1 rep6 (retina)
- - BXD23 No or early 1 rep7 (retina)
- - BXD25 No or early 1 rep8 (retina)
- - BXD27 No or early 1 rep9 (retina)
- - BXD28 No or early 1 rep10 (retina)
- - BXD29 No or early 2 rep1 (retina)
- - BXD30 No or early 2 rep2 (retina)
- - BXD31 No or early 2 rep3 (retina)
- - BXD32 No or early 2 rep4 (retina)
- - BXD33 No or early 2 rep5 (retina)
- - BXD34 No or early 2 rep6 (retina)
- - BXD35 No or early 2 rep7 (retina)
- - BXD36 No or early 2 rep8 (retina)
- - BXD37 No or early 2 rep9 (retina)
- - BXD38 No or early 2 rep10 (retina)
- - BXD39 Moderate rep1 (retina)
- - BXD40 Moderate rep2 (retina)
- - BXD41 Moderate rep3 (retina)
- - BXD42 Moderate rep4 (retina)
- - BXD43 Moderate rep7 (retina)
- - BXD44 Moderate rep8 (retina)
- - BXD45 Moderate rep9 (retina)
- - BXD48 Moderate rep10 (retina)
- - BXD49 Severe rep1 (retina)
- - BXD50 Severe rep2 (retina)
- - BXD51 Severe rep3 (retina)
- - BXD52 Severe rep4 (retina)
- - BXD53 Severe rep5 (retina)
- - BXD54 Severe rep6 (retina)
- - BXD55 Severe rep7 (retina)
- - BXD56 Severe rep8 (retina)
- - BXD59 Severe rep9 (retina)
- - BXD60 Severe rep10 (retina)
-
diff --git a/general/datasets/DOD_BXD_Ind_PFC_CD_RNA_Seq_1019/specifics.rtf b/general/datasets/DOD_BXD_Ind_PFC_CD_RNA_Seq_1019/specifics.rtf
deleted file mode 100644
index e64a89f..0000000
--- a/general/datasets/DOD_BXD_Ind_PFC_CD_RNA_Seq_1019/specifics.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-DOD BXD Individual PFC GWI CD RNA-Seq (Oct19) TPM Log2
-
-Download data here: http://ipfs.genenetwork.org/ipfs/QmUxTJ6qW3eHQeVoyc4tYgooxYiYN6G6eekV1iLMh8EF5k/GN880
diff --git a/general/datasets/DOD_BXD_Ind_PFC_CD_RNA_Seq_1019/summary.rtf b/general/datasets/DOD_BXD_Ind_PFC_CD_RNA_Seq_1019/summary.rtf
deleted file mode 100644
index 7378ad9..0000000
--- a/general/datasets/DOD_BXD_Ind_PFC_CD_RNA_Seq_1019/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
-
-D=diisopropylflurophosphate treatment
-
-CD= corticosterone + diisopropylflurophosphate treatment.
-
-Data are log2 gene expression for D or CD vs saline control
-
-This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/DOD_BXD_Ind_PFC_CD_RNA_Seq_ComB_1019/specifics.rtf b/general/datasets/DOD_BXD_Ind_PFC_CD_RNA_Seq_ComB_1019/specifics.rtf
deleted file mode 100644
index 45296b8..0000000
--- a/general/datasets/DOD_BXD_Ind_PFC_CD_RNA_Seq_ComB_1019/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DOD BXD INDV PFC GWI CD RNA-Seq ComB (Dec19) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/DOD_BXD_Ind_PFC_CD_RNA_Seq_ComB_1019/summary.rtf b/general/datasets/DOD_BXD_Ind_PFC_CD_RNA_Seq_ComB_1019/summary.rtf
deleted file mode 100644
index 7378ad9..0000000
--- a/general/datasets/DOD_BXD_Ind_PFC_CD_RNA_Seq_ComB_1019/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
-
-D=diisopropylflurophosphate treatment
-
-CD= corticosterone + diisopropylflurophosphate treatment.
-
-Data are log2 gene expression for D or CD vs saline control
-
-This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/DOD_BXD_Ind_PFC_CTL_RNA_Seq_1019/specifics.rtf b/general/datasets/DOD_BXD_Ind_PFC_CTL_RNA_Seq_1019/specifics.rtf
deleted file mode 100644
index 79182c3..0000000
--- a/general/datasets/DOD_BXD_Ind_PFC_CTL_RNA_Seq_1019/specifics.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-DOD BXD Individual PFC GWI CTL RNA-Seq (Oct19) TPM Log2
-
-Download data here: http://ipfs.genenetwork.org/ipfs/QmUxTJ6qW3eHQeVoyc4tYgooxYiYN6G6eekV1iLMh8EF5k/GN881
diff --git a/general/datasets/DOD_BXD_Ind_PFC_CTL_RNA_Seq_1019/summary.rtf b/general/datasets/DOD_BXD_Ind_PFC_CTL_RNA_Seq_1019/summary.rtf
deleted file mode 100644
index 7378ad9..0000000
--- a/general/datasets/DOD_BXD_Ind_PFC_CTL_RNA_Seq_1019/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
-
-D=diisopropylflurophosphate treatment
-
-CD= corticosterone + diisopropylflurophosphate treatment.
-
-Data are log2 gene expression for D or CD vs saline control
-
-This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/DOD_BXD_Ind_PFC_CTL_RNA_Seq_ComB_1019/specifics.rtf b/general/datasets/DOD_BXD_Ind_PFC_CTL_RNA_Seq_ComB_1019/specifics.rtf
deleted file mode 100644
index 5c05883..0000000
--- a/general/datasets/DOD_BXD_Ind_PFC_CTL_RNA_Seq_ComB_1019/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DOD BXD INDV PFC GWI CTL RNA-Seq ComB (Dec19) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/DOD_BXD_Ind_PFC_CTL_RNA_Seq_ComB_1019/summary.rtf b/general/datasets/DOD_BXD_Ind_PFC_CTL_RNA_Seq_ComB_1019/summary.rtf
deleted file mode 100644
index 7378ad9..0000000
--- a/general/datasets/DOD_BXD_Ind_PFC_CTL_RNA_Seq_ComB_1019/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
-
-D=diisopropylflurophosphate treatment
-
-CD= corticosterone + diisopropylflurophosphate treatment.
-
-Data are log2 gene expression for D or CD vs saline control
-
-This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/DOD_BXD_Ind_PFC_DFP_RNA_Seq_1019/specifics.rtf b/general/datasets/DOD_BXD_Ind_PFC_DFP_RNA_Seq_1019/specifics.rtf
deleted file mode 100644
index d77d879..0000000
--- a/general/datasets/DOD_BXD_Ind_PFC_DFP_RNA_Seq_1019/specifics.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-DOD BXD Individual PFC GWI DFP RNA-Seq (Oct19) TPM Log2
-
-Download data here: http://ipfs.genenetwork.org/ipfs/QmUxTJ6qW3eHQeVoyc4tYgooxYiYN6G6eekV1iLMh8EF5k/GN882
diff --git a/general/datasets/DOD_BXD_Ind_PFC_DFP_RNA_Seq_1019/summary.rtf b/general/datasets/DOD_BXD_Ind_PFC_DFP_RNA_Seq_1019/summary.rtf
deleted file mode 100644
index 7378ad9..0000000
--- a/general/datasets/DOD_BXD_Ind_PFC_DFP_RNA_Seq_1019/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
-
-D=diisopropylflurophosphate treatment
-
-CD= corticosterone + diisopropylflurophosphate treatment.
-
-Data are log2 gene expression for D or CD vs saline control
-
-This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/DOD_BXD_Ind_PFC_DFP_RNA_Seq_ComB_1019/specifics.rtf b/general/datasets/DOD_BXD_Ind_PFC_DFP_RNA_Seq_ComB_1019/specifics.rtf
deleted file mode 100644
index 577b618..0000000
--- a/general/datasets/DOD_BXD_Ind_PFC_DFP_RNA_Seq_ComB_1019/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DOD BXD INDV PFC GWI DFP RNA-Seq ComB (Dec19) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/DOD_BXD_Ind_PFC_DFP_RNA_Seq_ComB_1019/summary.rtf b/general/datasets/DOD_BXD_Ind_PFC_DFP_RNA_Seq_ComB_1019/summary.rtf
deleted file mode 100644
index 7378ad9..0000000
--- a/general/datasets/DOD_BXD_Ind_PFC_DFP_RNA_Seq_ComB_1019/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
-
-D=diisopropylflurophosphate treatment
-
-CD= corticosterone + diisopropylflurophosphate treatment.
-
-Data are log2 gene expression for D or CD vs saline control
-
-This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/DOD_BXD_PFC_CD_RNA_Seq_1019/specifics.rtf b/general/datasets/DOD_BXD_PFC_CD_RNA_Seq_1019/specifics.rtf
deleted file mode 100644
index e8f6c71..0000000
--- a/general/datasets/DOD_BXD_PFC_CD_RNA_Seq_1019/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DOD BXD PFC GWI CD RNA-Seq (Oct19) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/DOD_BXD_PFC_CD_RNA_Seq_1019/summary.rtf b/general/datasets/DOD_BXD_PFC_CD_RNA_Seq_1019/summary.rtf
deleted file mode 100644
index 7378ad9..0000000
--- a/general/datasets/DOD_BXD_PFC_CD_RNA_Seq_1019/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
-
-D=diisopropylflurophosphate treatment
-
-CD= corticosterone + diisopropylflurophosphate treatment.
-
-Data are log2 gene expression for D or CD vs saline control
-
-This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/DOD_BXD_PFC_CD_RNA_Seq_ComB_1019/specifics.rtf b/general/datasets/DOD_BXD_PFC_CD_RNA_Seq_ComB_1019/specifics.rtf
deleted file mode 100644
index 082f0ef..0000000
--- a/general/datasets/DOD_BXD_PFC_CD_RNA_Seq_ComB_1019/specifics.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-DOD BXD PFC GWI CD RNA-Seq ComB (Dec19) TPM Log2
-
-DOWNLOAD DATA HERE: http://ipfs.genenetwork.org/ipfs/QmUxTJ6qW3eHQeVoyc4tYgooxYiYN6G6eekV1iLMh8EF5k/GN898
diff --git a/general/datasets/DOD_BXD_PFC_CD_RNA_Seq_ComB_1019/summary.rtf b/general/datasets/DOD_BXD_PFC_CD_RNA_Seq_ComB_1019/summary.rtf
deleted file mode 100644
index 7378ad9..0000000
--- a/general/datasets/DOD_BXD_PFC_CD_RNA_Seq_ComB_1019/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
-
-D=diisopropylflurophosphate treatment
-
-CD= corticosterone + diisopropylflurophosphate treatment.
-
-Data are log2 gene expression for D or CD vs saline control
-
-This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/DOD_BXD_PFC_CTL_RNA_Seq_1019/specifics.rtf b/general/datasets/DOD_BXD_PFC_CTL_RNA_Seq_1019/specifics.rtf
deleted file mode 100644
index 052b038..0000000
--- a/general/datasets/DOD_BXD_PFC_CTL_RNA_Seq_1019/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DOD BXD PFC GWI CTL RNA-Seq (Oct19)
\ No newline at end of file
diff --git a/general/datasets/DOD_BXD_PFC_CTL_RNA_Seq_1019/summary.rtf b/general/datasets/DOD_BXD_PFC_CTL_RNA_Seq_1019/summary.rtf
deleted file mode 100644
index 7378ad9..0000000
--- a/general/datasets/DOD_BXD_PFC_CTL_RNA_Seq_1019/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
-
-D=diisopropylflurophosphate treatment
-
-CD= corticosterone + diisopropylflurophosphate treatment.
-
-Data are log2 gene expression for D or CD vs saline control
-
-This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/DOD_BXD_PFC_CTL_RNA_Seq_ComB_1019/specifics.rtf b/general/datasets/DOD_BXD_PFC_CTL_RNA_Seq_ComB_1019/specifics.rtf
deleted file mode 100644
index 57e85c6..0000000
--- a/general/datasets/DOD_BXD_PFC_CTL_RNA_Seq_ComB_1019/specifics.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-DOD BXD PFC GWI CTL RNA-Seq ComB (Dec19) TPM Log2
-
-DOWNLOAD DATA HERE: http://ipfs.genenetwork.org/ipfs/QmUxTJ6qW3eHQeVoyc4tYgooxYiYN6G6eekV1iLMh8EF5k/GN899
diff --git a/general/datasets/DOD_BXD_PFC_CTL_RNA_Seq_ComB_1019/summary.rtf b/general/datasets/DOD_BXD_PFC_CTL_RNA_Seq_ComB_1019/summary.rtf
deleted file mode 100644
index 7378ad9..0000000
--- a/general/datasets/DOD_BXD_PFC_CTL_RNA_Seq_ComB_1019/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
-
-D=diisopropylflurophosphate treatment
-
-CD= corticosterone + diisopropylflurophosphate treatment.
-
-Data are log2 gene expression for D or CD vs saline control
-
-This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/DOD_BXD_PFC_DFP_RNA_Seq_1019/specifics.rtf b/general/datasets/DOD_BXD_PFC_DFP_RNA_Seq_1019/specifics.rtf
deleted file mode 100644
index d6ad7e8..0000000
--- a/general/datasets/DOD_BXD_PFC_DFP_RNA_Seq_1019/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DOD BXD PFC GWI DFP RNA-Seq (Oct19) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/DOD_BXD_PFC_DFP_RNA_Seq_1019/summary.rtf b/general/datasets/DOD_BXD_PFC_DFP_RNA_Seq_1019/summary.rtf
deleted file mode 100644
index 7378ad9..0000000
--- a/general/datasets/DOD_BXD_PFC_DFP_RNA_Seq_1019/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
-
-D=diisopropylflurophosphate treatment
-
-CD= corticosterone + diisopropylflurophosphate treatment.
-
-Data are log2 gene expression for D or CD vs saline control
-
-This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/DOD_BXD_PFC_DFP_RNA_Seq_ComB_1019/specifics.rtf b/general/datasets/DOD_BXD_PFC_DFP_RNA_Seq_ComB_1019/specifics.rtf
deleted file mode 100644
index 476fd21..0000000
--- a/general/datasets/DOD_BXD_PFC_DFP_RNA_Seq_ComB_1019/specifics.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-DOD BXD PFC GWI DFP RNA-Seq ComB (Dec19) TPM Log2
-
-DOWNLOAD DATA HERE: http://ipfs.genenetwork.org/ipfs/QmUxTJ6qW3eHQeVoyc4tYgooxYiYN6G6eekV1iLMh8EF5k/GN900
diff --git a/general/datasets/DOD_BXD_PFC_DFP_RNA_Seq_ComB_1019/summary.rtf b/general/datasets/DOD_BXD_PFC_DFP_RNA_Seq_ComB_1019/summary.rtf
deleted file mode 100644
index 7378ad9..0000000
--- a/general/datasets/DOD_BXD_PFC_DFP_RNA_Seq_ComB_1019/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
-
-D=diisopropylflurophosphate treatment
-
-CD= corticosterone + diisopropylflurophosphate treatment.
-
-Data are log2 gene expression for D or CD vs saline control
-
-This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dba2j_onh_1212/experiment-design.rtf b/general/datasets/Dba2j_onh_1212/experiment-design.rtf
new file mode 100644
index 0000000..f01b888
--- /dev/null
+++ b/general/datasets/Dba2j_onh_1212/experiment-design.rtf
@@ -0,0 +1,9 @@
+TEXT FROM GEO
+
+Genome-wide assessment of gene expression changes was performed in DBA/2J mice. The optic nerve head and retina from 40 DBA/2J eyes at 10.5 months of age were separately profiled. These eyes were selected as they encompassed a range of glaucoma severity. Two control groups were also included; 10 eyes from 10.5 months old D2-Gpnmb+ mice (age and strain matched, no glaucoma control) and 10 eyes from 4.5 months old DBA/2J mice (young, pre-glaucoma).
+
+In this study that was specifically designed to identify early stages of glaucoma in DBA/2J mice, we used genome-wide expression profiling and a series of computational methods. Our methods successfully subdivided eyes with no detectable glaucoma by conventional assays into molecularly defined stages of disease. These stages represent a temporally ordered sequence of glaucoma states. Using an array of tools, we then determined networks and biological processes that are altered at these early stages. Our strategy proved very sensitive, suggesting that similar approaches will be valuable for uncovering early processes in other complex, later-onset diseases. Early changes included upregulation of both the complement cascade and endothelin system, and so we tested the therapeutic value of separately inhibiting them. Mice with a mutation in the complement component 1a gene (C1qa) were robustly protected from glaucoma with the protection being among the greatest reported. Similarly, inhibition of the endothelin system was strongly protective. Since EDN2 is potently vasoconstrictive and was produced by microglial/macrophages, our data provide a novel link between these cell types and vascular dysfunction in glaucoma. Targeting early events such as the upregulation of the complement and endothelin pathways may provide effective new treatments for human glaucoma. (text above from GEO http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26299)
+
+
+
+
diff --git a/general/datasets/Dba2j_onh_1212/summary.rtf b/general/datasets/Dba2j_onh_1212/summary.rtf
new file mode 100644
index 0000000..09c8a43
--- /dev/null
+++ b/general/datasets/Dba2j_onh_1212/summary.rtf
@@ -0,0 +1,58 @@
+This is an experimental glaucoma gene expression data set of retinal tissue entered into GeneNetwork by Dr. Eldon Geisert and Robert Williams in which BXD strains have been "highjacked" with experimental and control gene expression data generated by Drs Gareth Howell, Simon John, and colleagues at the Jackson Laboratory. These data were originally entered into GeneNetwork Sept 20, 2011.
+
+Please see the original paper by Howell et al (2011): http://www.jci.org/articles/view/44646 and GEO data at NCBI.
+
+Gareth R. Howell, Danilo G. Macalinao, Gregory L. Sousa, Michael Walden, Ileana Soto, Stephen C. Kneeland, Jessica M. Barbay, Benjamin L. King, Jeffrey K. Marchant, Matthew Hibbs, Beth Stevens, Ben A. Barres, Abbot F. Clark, Richard T. Libby, Simon S (2011) Molecular clustering identifies complement and endothelin induction as early events in a mouse model of glaucoma. J Clin Invest. 121:1429–1444
+
+Each strain corresponds to a particular retinal sample as shown below (note that we have not included ten "preglaucoma control" samples, see http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26299
+
+
+ - BXD1 D2-Gpnmb+ control rep1 (retina)
+ - BXD2 D2-Gpnmb+ control rep2 (retina)
+ - BXD5 D2-Gpnmb+ control rep3 (retina)
+ - BXD6 D2-Gpnmb+ control rep4 (retina)
+ - BXD8 D2-Gpnmb+ control rep5 (retina)
+ - BXD9 D2-Gpnmb+ control rep6 (retina)
+ - BXD11 D2-Gpnmb+ control rep7 (retina)
+ - BXD12 D2-Gpnmb+ control rep8 (retina)
+ - BXD13 D2-Gpnmb+ control rep9 (retina)
+ - BXD14 D2-Gpnmb+ control rep10 (retina)
+ - BXD15 No or early 1 rep1 (retina)
+ - BXD16 No or early 1 rep2 (retina)
+ - BXD18 No or early 1 rep3 (retina)
+ - BXD19 No or early 1 rep4 (retina)
+ - BXD20 No or early 1 rep5 (retina)
+ - BXD22 No or early 1 rep6 (retina)
+ - BXD23 No or early 1 rep7 (retina)
+ - BXD25 No or early 1 rep8 (retina)
+ - BXD27 No or early 1 rep9 (retina)
+ - BXD28 No or early 1 rep10 (retina)
+ - BXD29 No or early 2 rep1 (retina)
+ - BXD30 No or early 2 rep2 (retina)
+ - BXD31 No or early 2 rep3 (retina)
+ - BXD32 No or early 2 rep4 (retina)
+ - BXD33 No or early 2 rep5 (retina)
+ - BXD34 No or early 2 rep6 (retina)
+ - BXD35 No or early 2 rep7 (retina)
+ - BXD36 No or early 2 rep8 (retina)
+ - BXD37 No or early 2 rep9 (retina)
+ - BXD38 No or early 2 rep10 (retina)
+ - BXD39 Moderate rep1 (retina)
+ - BXD40 Moderate rep2 (retina)
+ - BXD41 Moderate rep3 (retina)
+ - BXD42 Moderate rep4 (retina)
+ - BXD43 Moderate rep7 (retina)
+ - BXD44 Moderate rep8 (retina)
+ - BXD45 Moderate rep9 (retina)
+ - BXD48 Moderate rep10 (retina)
+ - BXD49 Severe rep1 (retina)
+ - BXD50 Severe rep2 (retina)
+ - BXD51 Severe rep3 (retina)
+ - BXD52 Severe rep4 (retina)
+ - BXD53 Severe rep5 (retina)
+ - BXD54 Severe rep6 (retina)
+ - BXD55 Severe rep7 (retina)
+ - BXD56 Severe rep8 (retina)
+ - BXD59 Severe rep9 (retina)
+ - BXD60 Severe rep10 (retina)
+
diff --git a/general/datasets/DevNeocortex_ILM6.2P14RInv_1110/cases.rtf b/general/datasets/DevNeocortex_ILM6.2P14RInv_1110/cases.rtf
new file mode 100644
index 0000000..70216c8
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P14RInv_1110/cases.rtf
@@ -0,0 +1,3 @@
+About the strains used to generate this set of data
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevNeocortex_ILM6.2P14RInv_1110/experiment-design.rtf b/general/datasets/DevNeocortex_ILM6.2P14RInv_1110/experiment-design.rtf
new file mode 100644
index 0000000..616db01
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P14RInv_1110/experiment-design.rtf
@@ -0,0 +1,3 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevNeocortex_ILM6.2P14RInv_1110/summary.rtf b/general/datasets/DevNeocortex_ILM6.2P14RInv_1110/summary.rtf
new file mode 100644
index 0000000..70d7451
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P14RInv_1110/summary.rtf
@@ -0,0 +1,16 @@
+Data generated by Dr. Glenn D. Rosen and colleagues
+
+The Neocortex Developmental data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+Some of these data were used in
+Gaglani SM, Lu L, Williams RW, Rosen GD (2009) The genetic control of neocortex volume and covariation with patterns of gene expression in mice. BMC Neuroscience 10:44 Full Text HTML Version, Full Text PDF Version
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the Striatal Developmental Transcriptome data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Developmental data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse neocortex data may also find the following complementary resources and papers useful:
+
+Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. ABOUT THE NEOCORTEX
diff --git a/general/datasets/DevNeocortex_ILM6.2P14RInv_1110/tissue.rtf b/general/datasets/DevNeocortex_ILM6.2P14RInv_1110/tissue.rtf
new file mode 100644
index 0000000..51f6e74
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P14RInv_1110/tissue.rtf
@@ -0,0 +1,536 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected neocortical tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn D. Rosen and colleagues.
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 2 |
+ 5384138018_F |
+ 236 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 3 |
+ 5384138058_A |
+ 239 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 2 |
+ 5384138018_C |
+ 168 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 1 |
+ 5448576044_F |
+ 167 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 7 |
+ 5384138020_A |
+ 273 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 4 |
+ 5452241022_C |
+ 267 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 3 |
+ 5384138048_A |
+ 107 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 4 |
+ 5452241007_A |
+ 108 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 6 |
+ 5384138009_A |
+ 113 |
+
+
+ | 10 |
+ BXD8 |
+ P3 |
+ 7 |
+ 5384138021_C |
+ 115 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 5 |
+ 5452241004_F |
+ 289 |
+
+
+ | 12 |
+ BXD9 |
+ P3 |
+ 4 |
+ 5452241022_D |
+ 288 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 8 |
+ 5237939010_A |
+ 117 |
+
+
+ | 14 |
+ BXD11 |
+ P3 |
+ 1 |
+ 5448576044_D |
+ 120 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 6 |
+ 5384138009_B |
+ 130 |
+
+
+ | 16 |
+ BXD12 |
+ P3 |
+ 7 |
+ 5384138021_B |
+ 132 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 7 |
+ 5384138020_F |
+ 161 |
+
+
+ | 18 |
+ BXD13 |
+ P3 |
+ 5 |
+ 5452241004_C |
+ 164 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241004_B |
+ 158 |
+
+
+ | 20 |
+ BXD14 |
+ P3 |
+ 6 |
+ 5452241033_D |
+ 424 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 3 |
+ 5452241008_C |
+ 437 |
+
+
+ | 22 |
+ BXD15 |
+ P3 |
+ 4 |
+ 5452241023_D |
+ 438 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 3 |
+ 5384138048_D |
+ 170 |
+
+
+ | 24 |
+ BXD16 |
+ P3 |
+ 4 |
+ 5452241007_D |
+ 172 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 8 |
+ 5448576010_A |
+ 390 |
+
+
+ | 26 |
+ BXD18 |
+ P3 |
+ 1 |
+ 5448576045_E |
+ 392 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 8 |
+ 5237939010_E |
+ 210 |
+
+
+ | 28 |
+ BXD19 |
+ P3 |
+ 1 |
+ 5448576045_A |
+ 211 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 5 |
+ 5452241017_B |
+ 439 |
+
+
+ | 30 |
+ BXD20 |
+ P3 |
+ 6 |
+ 5452241033_E |
+ 441 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 7 |
+ 5384138021_F |
+ 341 |
+
+
+ | 32 |
+ BXD21 |
+ P3 |
+ 6 |
+ 5384138053_F |
+ 315 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 8 |
+ 5237939012_B |
+ 251 |
+
+
+ | 34 |
+ BXD24a |
+ P3 |
+ 7 |
+ 5384138020_B |
+ 250 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 8 |
+ 5237939012_D |
+ 298 |
+
+
+ | 36 |
+ BXD27 |
+ P3 |
+ 1 |
+ 5448576045_C |
+ 300 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 2 |
+ 5384138049_B |
+ 550 |
+
+
+ | 38 |
+ BXD28 |
+ P3 |
+ 1 |
+ 5448576029_F |
+ 548 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 2 |
+ 5384138047_F |
+ 502 |
+
+
+ | 40 |
+ BXD29 |
+ P3 |
+ 1 |
+ 5448576029_D |
+ 501 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 5 |
+ 5452241024_D |
+ 579 |
+
+
+ | 42 |
+ BXD31 |
+ P3 |
+ 6 |
+ 5452241035_D |
+ 582 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_F |
+ 407 |
+
+
+ | 44 |
+ BXD32 |
+ P3 |
+ 6 |
+ 5452241033_C |
+ 408 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 8 |
+ 5237939012_F |
+ 345 |
+
+
+ | 46 |
+ BXD34 |
+ P3 |
+ 4 |
+ 5452241022_F |
+ 355 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 7 |
+ 5384138016_A |
+ 429 |
+
+
+ | 48 |
+ BXD36 |
+ P3 |
+ 8 |
+ 5448576010_D |
+ 430 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 2 |
+ 5384138041_F |
+ 327 |
+
+
+ | 50 |
+ BXD38 |
+ P3 |
+ 3 |
+ 5384138058_E |
+ 328 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 7 |
+ 5384138016_E |
+ 515 |
+
+
+ | 52 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241024_A |
+ 518 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 2 |
+ 5384138041_C |
+ 373 |
+
+
+ | 54 |
+ BXD40 |
+ P3 |
+ 3 |
+ 5452241008_A |
+ 375 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 3 |
+ 5452241008_E |
+ 485 |
+
+
+ | 56 |
+ BXD42 |
+ P3 |
+ 4 |
+ 5452241023_F |
+ 486 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 5 |
+ 5452241024_F |
+ 621 |
+
+
+ | 58 |
+ BXD51 |
+ P3 |
+ 6 |
+ 5452241035_F |
+ 622 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 4 |
+ 5452241031_C |
+ 554 |
+
+
+ | 60 |
+ BXD61 |
+ P3 |
+ 3 |
+ 5452241034_A |
+ 552 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 2 |
+ 5384138049_D |
+ 590 |
+
+
+ | 62 |
+ BXD70 |
+ P3 |
+ 1 |
+ 5448576044_B |
+ 589 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 2 |
+ 5384138049_E |
+ 603 |
+
+
+ | 64 |
+ BXD73 |
+ P3 |
+ 8 |
+ 5448576011_E |
+ 605 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/DevNeocortex_ILM6.2P14RInv_1111/cases.rtf b/general/datasets/DevNeocortex_ILM6.2P14RInv_1111/cases.rtf
new file mode 100644
index 0000000..70216c8
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P14RInv_1111/cases.rtf
@@ -0,0 +1,3 @@
+About the strains used to generate this set of data
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevNeocortex_ILM6.2P14RInv_1111/experiment-design.rtf b/general/datasets/DevNeocortex_ILM6.2P14RInv_1111/experiment-design.rtf
new file mode 100644
index 0000000..616db01
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P14RInv_1111/experiment-design.rtf
@@ -0,0 +1,3 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevNeocortex_ILM6.2P14RInv_1111/summary.rtf b/general/datasets/DevNeocortex_ILM6.2P14RInv_1111/summary.rtf
new file mode 100644
index 0000000..70d7451
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P14RInv_1111/summary.rtf
@@ -0,0 +1,16 @@
+Data generated by Dr. Glenn D. Rosen and colleagues
+
+The Neocortex Developmental data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+Some of these data were used in
+Gaglani SM, Lu L, Williams RW, Rosen GD (2009) The genetic control of neocortex volume and covariation with patterns of gene expression in mice. BMC Neuroscience 10:44 Full Text HTML Version, Full Text PDF Version
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the Striatal Developmental Transcriptome data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Developmental data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse neocortex data may also find the following complementary resources and papers useful:
+
+Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. ABOUT THE NEOCORTEX
diff --git a/general/datasets/DevNeocortex_ILM6.2P14RInv_1111/tissue.rtf b/general/datasets/DevNeocortex_ILM6.2P14RInv_1111/tissue.rtf
new file mode 100644
index 0000000..51f6e74
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P14RInv_1111/tissue.rtf
@@ -0,0 +1,536 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected neocortical tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn D. Rosen and colleagues.
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 2 |
+ 5384138018_F |
+ 236 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 3 |
+ 5384138058_A |
+ 239 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 2 |
+ 5384138018_C |
+ 168 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 1 |
+ 5448576044_F |
+ 167 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 7 |
+ 5384138020_A |
+ 273 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 4 |
+ 5452241022_C |
+ 267 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 3 |
+ 5384138048_A |
+ 107 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 4 |
+ 5452241007_A |
+ 108 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 6 |
+ 5384138009_A |
+ 113 |
+
+
+ | 10 |
+ BXD8 |
+ P3 |
+ 7 |
+ 5384138021_C |
+ 115 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 5 |
+ 5452241004_F |
+ 289 |
+
+
+ | 12 |
+ BXD9 |
+ P3 |
+ 4 |
+ 5452241022_D |
+ 288 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 8 |
+ 5237939010_A |
+ 117 |
+
+
+ | 14 |
+ BXD11 |
+ P3 |
+ 1 |
+ 5448576044_D |
+ 120 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 6 |
+ 5384138009_B |
+ 130 |
+
+
+ | 16 |
+ BXD12 |
+ P3 |
+ 7 |
+ 5384138021_B |
+ 132 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 7 |
+ 5384138020_F |
+ 161 |
+
+
+ | 18 |
+ BXD13 |
+ P3 |
+ 5 |
+ 5452241004_C |
+ 164 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241004_B |
+ 158 |
+
+
+ | 20 |
+ BXD14 |
+ P3 |
+ 6 |
+ 5452241033_D |
+ 424 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 3 |
+ 5452241008_C |
+ 437 |
+
+
+ | 22 |
+ BXD15 |
+ P3 |
+ 4 |
+ 5452241023_D |
+ 438 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 3 |
+ 5384138048_D |
+ 170 |
+
+
+ | 24 |
+ BXD16 |
+ P3 |
+ 4 |
+ 5452241007_D |
+ 172 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 8 |
+ 5448576010_A |
+ 390 |
+
+
+ | 26 |
+ BXD18 |
+ P3 |
+ 1 |
+ 5448576045_E |
+ 392 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 8 |
+ 5237939010_E |
+ 210 |
+
+
+ | 28 |
+ BXD19 |
+ P3 |
+ 1 |
+ 5448576045_A |
+ 211 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 5 |
+ 5452241017_B |
+ 439 |
+
+
+ | 30 |
+ BXD20 |
+ P3 |
+ 6 |
+ 5452241033_E |
+ 441 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 7 |
+ 5384138021_F |
+ 341 |
+
+
+ | 32 |
+ BXD21 |
+ P3 |
+ 6 |
+ 5384138053_F |
+ 315 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 8 |
+ 5237939012_B |
+ 251 |
+
+
+ | 34 |
+ BXD24a |
+ P3 |
+ 7 |
+ 5384138020_B |
+ 250 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 8 |
+ 5237939012_D |
+ 298 |
+
+
+ | 36 |
+ BXD27 |
+ P3 |
+ 1 |
+ 5448576045_C |
+ 300 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 2 |
+ 5384138049_B |
+ 550 |
+
+
+ | 38 |
+ BXD28 |
+ P3 |
+ 1 |
+ 5448576029_F |
+ 548 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 2 |
+ 5384138047_F |
+ 502 |
+
+
+ | 40 |
+ BXD29 |
+ P3 |
+ 1 |
+ 5448576029_D |
+ 501 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 5 |
+ 5452241024_D |
+ 579 |
+
+
+ | 42 |
+ BXD31 |
+ P3 |
+ 6 |
+ 5452241035_D |
+ 582 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_F |
+ 407 |
+
+
+ | 44 |
+ BXD32 |
+ P3 |
+ 6 |
+ 5452241033_C |
+ 408 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 8 |
+ 5237939012_F |
+ 345 |
+
+
+ | 46 |
+ BXD34 |
+ P3 |
+ 4 |
+ 5452241022_F |
+ 355 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 7 |
+ 5384138016_A |
+ 429 |
+
+
+ | 48 |
+ BXD36 |
+ P3 |
+ 8 |
+ 5448576010_D |
+ 430 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 2 |
+ 5384138041_F |
+ 327 |
+
+
+ | 50 |
+ BXD38 |
+ P3 |
+ 3 |
+ 5384138058_E |
+ 328 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 7 |
+ 5384138016_E |
+ 515 |
+
+
+ | 52 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241024_A |
+ 518 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 2 |
+ 5384138041_C |
+ 373 |
+
+
+ | 54 |
+ BXD40 |
+ P3 |
+ 3 |
+ 5452241008_A |
+ 375 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 3 |
+ 5452241008_E |
+ 485 |
+
+
+ | 56 |
+ BXD42 |
+ P3 |
+ 4 |
+ 5452241023_F |
+ 486 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 5 |
+ 5452241024_F |
+ 621 |
+
+
+ | 58 |
+ BXD51 |
+ P3 |
+ 6 |
+ 5452241035_F |
+ 622 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 4 |
+ 5452241031_C |
+ 554 |
+
+
+ | 60 |
+ BXD61 |
+ P3 |
+ 3 |
+ 5452241034_A |
+ 552 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 2 |
+ 5384138049_D |
+ 590 |
+
+
+ | 62 |
+ BXD70 |
+ P3 |
+ 1 |
+ 5448576044_B |
+ 589 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 2 |
+ 5384138049_E |
+ 603 |
+
+
+ | 64 |
+ BXD73 |
+ P3 |
+ 8 |
+ 5448576011_E |
+ 605 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/DevNeocortex_ILM6.2P3RInv_1110/cases.rtf b/general/datasets/DevNeocortex_ILM6.2P3RInv_1110/cases.rtf
new file mode 100644
index 0000000..70216c8
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P3RInv_1110/cases.rtf
@@ -0,0 +1,3 @@
+About the strains used to generate this set of data
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevNeocortex_ILM6.2P3RInv_1110/experiment-design.rtf b/general/datasets/DevNeocortex_ILM6.2P3RInv_1110/experiment-design.rtf
new file mode 100644
index 0000000..616db01
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P3RInv_1110/experiment-design.rtf
@@ -0,0 +1,3 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevNeocortex_ILM6.2P3RInv_1110/summary.rtf b/general/datasets/DevNeocortex_ILM6.2P3RInv_1110/summary.rtf
new file mode 100644
index 0000000..70d7451
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P3RInv_1110/summary.rtf
@@ -0,0 +1,16 @@
+Data generated by Dr. Glenn D. Rosen and colleagues
+
+The Neocortex Developmental data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+Some of these data were used in
+Gaglani SM, Lu L, Williams RW, Rosen GD (2009) The genetic control of neocortex volume and covariation with patterns of gene expression in mice. BMC Neuroscience 10:44 Full Text HTML Version, Full Text PDF Version
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the Striatal Developmental Transcriptome data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Developmental data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse neocortex data may also find the following complementary resources and papers useful:
+
+Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. ABOUT THE NEOCORTEX
diff --git a/general/datasets/DevNeocortex_ILM6.2P3RInv_1110/tissue.rtf b/general/datasets/DevNeocortex_ILM6.2P3RInv_1110/tissue.rtf
new file mode 100644
index 0000000..51f6e74
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P3RInv_1110/tissue.rtf
@@ -0,0 +1,536 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected neocortical tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn D. Rosen and colleagues.
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 2 |
+ 5384138018_F |
+ 236 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 3 |
+ 5384138058_A |
+ 239 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 2 |
+ 5384138018_C |
+ 168 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 1 |
+ 5448576044_F |
+ 167 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 7 |
+ 5384138020_A |
+ 273 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 4 |
+ 5452241022_C |
+ 267 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 3 |
+ 5384138048_A |
+ 107 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 4 |
+ 5452241007_A |
+ 108 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 6 |
+ 5384138009_A |
+ 113 |
+
+
+ | 10 |
+ BXD8 |
+ P3 |
+ 7 |
+ 5384138021_C |
+ 115 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 5 |
+ 5452241004_F |
+ 289 |
+
+
+ | 12 |
+ BXD9 |
+ P3 |
+ 4 |
+ 5452241022_D |
+ 288 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 8 |
+ 5237939010_A |
+ 117 |
+
+
+ | 14 |
+ BXD11 |
+ P3 |
+ 1 |
+ 5448576044_D |
+ 120 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 6 |
+ 5384138009_B |
+ 130 |
+
+
+ | 16 |
+ BXD12 |
+ P3 |
+ 7 |
+ 5384138021_B |
+ 132 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 7 |
+ 5384138020_F |
+ 161 |
+
+
+ | 18 |
+ BXD13 |
+ P3 |
+ 5 |
+ 5452241004_C |
+ 164 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241004_B |
+ 158 |
+
+
+ | 20 |
+ BXD14 |
+ P3 |
+ 6 |
+ 5452241033_D |
+ 424 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 3 |
+ 5452241008_C |
+ 437 |
+
+
+ | 22 |
+ BXD15 |
+ P3 |
+ 4 |
+ 5452241023_D |
+ 438 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 3 |
+ 5384138048_D |
+ 170 |
+
+
+ | 24 |
+ BXD16 |
+ P3 |
+ 4 |
+ 5452241007_D |
+ 172 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 8 |
+ 5448576010_A |
+ 390 |
+
+
+ | 26 |
+ BXD18 |
+ P3 |
+ 1 |
+ 5448576045_E |
+ 392 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 8 |
+ 5237939010_E |
+ 210 |
+
+
+ | 28 |
+ BXD19 |
+ P3 |
+ 1 |
+ 5448576045_A |
+ 211 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 5 |
+ 5452241017_B |
+ 439 |
+
+
+ | 30 |
+ BXD20 |
+ P3 |
+ 6 |
+ 5452241033_E |
+ 441 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 7 |
+ 5384138021_F |
+ 341 |
+
+
+ | 32 |
+ BXD21 |
+ P3 |
+ 6 |
+ 5384138053_F |
+ 315 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 8 |
+ 5237939012_B |
+ 251 |
+
+
+ | 34 |
+ BXD24a |
+ P3 |
+ 7 |
+ 5384138020_B |
+ 250 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 8 |
+ 5237939012_D |
+ 298 |
+
+
+ | 36 |
+ BXD27 |
+ P3 |
+ 1 |
+ 5448576045_C |
+ 300 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 2 |
+ 5384138049_B |
+ 550 |
+
+
+ | 38 |
+ BXD28 |
+ P3 |
+ 1 |
+ 5448576029_F |
+ 548 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 2 |
+ 5384138047_F |
+ 502 |
+
+
+ | 40 |
+ BXD29 |
+ P3 |
+ 1 |
+ 5448576029_D |
+ 501 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 5 |
+ 5452241024_D |
+ 579 |
+
+
+ | 42 |
+ BXD31 |
+ P3 |
+ 6 |
+ 5452241035_D |
+ 582 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_F |
+ 407 |
+
+
+ | 44 |
+ BXD32 |
+ P3 |
+ 6 |
+ 5452241033_C |
+ 408 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 8 |
+ 5237939012_F |
+ 345 |
+
+
+ | 46 |
+ BXD34 |
+ P3 |
+ 4 |
+ 5452241022_F |
+ 355 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 7 |
+ 5384138016_A |
+ 429 |
+
+
+ | 48 |
+ BXD36 |
+ P3 |
+ 8 |
+ 5448576010_D |
+ 430 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 2 |
+ 5384138041_F |
+ 327 |
+
+
+ | 50 |
+ BXD38 |
+ P3 |
+ 3 |
+ 5384138058_E |
+ 328 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 7 |
+ 5384138016_E |
+ 515 |
+
+
+ | 52 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241024_A |
+ 518 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 2 |
+ 5384138041_C |
+ 373 |
+
+
+ | 54 |
+ BXD40 |
+ P3 |
+ 3 |
+ 5452241008_A |
+ 375 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 3 |
+ 5452241008_E |
+ 485 |
+
+
+ | 56 |
+ BXD42 |
+ P3 |
+ 4 |
+ 5452241023_F |
+ 486 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 5 |
+ 5452241024_F |
+ 621 |
+
+
+ | 58 |
+ BXD51 |
+ P3 |
+ 6 |
+ 5452241035_F |
+ 622 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 4 |
+ 5452241031_C |
+ 554 |
+
+
+ | 60 |
+ BXD61 |
+ P3 |
+ 3 |
+ 5452241034_A |
+ 552 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 2 |
+ 5384138049_D |
+ 590 |
+
+
+ | 62 |
+ BXD70 |
+ P3 |
+ 1 |
+ 5448576044_B |
+ 589 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 2 |
+ 5384138049_E |
+ 603 |
+
+
+ | 64 |
+ BXD73 |
+ P3 |
+ 8 |
+ 5448576011_E |
+ 605 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/DevNeocortex_ILM6.2P3RInv_1111/cases.rtf b/general/datasets/DevNeocortex_ILM6.2P3RInv_1111/cases.rtf
new file mode 100644
index 0000000..70216c8
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P3RInv_1111/cases.rtf
@@ -0,0 +1,3 @@
+About the strains used to generate this set of data
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevNeocortex_ILM6.2P3RInv_1111/experiment-design.rtf b/general/datasets/DevNeocortex_ILM6.2P3RInv_1111/experiment-design.rtf
new file mode 100644
index 0000000..616db01
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P3RInv_1111/experiment-design.rtf
@@ -0,0 +1,3 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevNeocortex_ILM6.2P3RInv_1111/summary.rtf b/general/datasets/DevNeocortex_ILM6.2P3RInv_1111/summary.rtf
new file mode 100644
index 0000000..70d7451
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P3RInv_1111/summary.rtf
@@ -0,0 +1,16 @@
+Data generated by Dr. Glenn D. Rosen and colleagues
+
+The Neocortex Developmental data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+Some of these data were used in
+Gaglani SM, Lu L, Williams RW, Rosen GD (2009) The genetic control of neocortex volume and covariation with patterns of gene expression in mice. BMC Neuroscience 10:44 Full Text HTML Version, Full Text PDF Version
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the Striatal Developmental Transcriptome data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Developmental data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse neocortex data may also find the following complementary resources and papers useful:
+
+Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. ABOUT THE NEOCORTEX
diff --git a/general/datasets/DevNeocortex_ILM6.2P3RInv_1111/tissue.rtf b/general/datasets/DevNeocortex_ILM6.2P3RInv_1111/tissue.rtf
new file mode 100644
index 0000000..51f6e74
--- /dev/null
+++ b/general/datasets/DevNeocortex_ILM6.2P3RInv_1111/tissue.rtf
@@ -0,0 +1,536 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected neocortical tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn D. Rosen and colleagues.
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 2 |
+ 5384138018_F |
+ 236 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 3 |
+ 5384138058_A |
+ 239 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 2 |
+ 5384138018_C |
+ 168 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 1 |
+ 5448576044_F |
+ 167 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 7 |
+ 5384138020_A |
+ 273 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 4 |
+ 5452241022_C |
+ 267 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 3 |
+ 5384138048_A |
+ 107 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 4 |
+ 5452241007_A |
+ 108 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 6 |
+ 5384138009_A |
+ 113 |
+
+
+ | 10 |
+ BXD8 |
+ P3 |
+ 7 |
+ 5384138021_C |
+ 115 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 5 |
+ 5452241004_F |
+ 289 |
+
+
+ | 12 |
+ BXD9 |
+ P3 |
+ 4 |
+ 5452241022_D |
+ 288 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 8 |
+ 5237939010_A |
+ 117 |
+
+
+ | 14 |
+ BXD11 |
+ P3 |
+ 1 |
+ 5448576044_D |
+ 120 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 6 |
+ 5384138009_B |
+ 130 |
+
+
+ | 16 |
+ BXD12 |
+ P3 |
+ 7 |
+ 5384138021_B |
+ 132 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 7 |
+ 5384138020_F |
+ 161 |
+
+
+ | 18 |
+ BXD13 |
+ P3 |
+ 5 |
+ 5452241004_C |
+ 164 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241004_B |
+ 158 |
+
+
+ | 20 |
+ BXD14 |
+ P3 |
+ 6 |
+ 5452241033_D |
+ 424 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 3 |
+ 5452241008_C |
+ 437 |
+
+
+ | 22 |
+ BXD15 |
+ P3 |
+ 4 |
+ 5452241023_D |
+ 438 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 3 |
+ 5384138048_D |
+ 170 |
+
+
+ | 24 |
+ BXD16 |
+ P3 |
+ 4 |
+ 5452241007_D |
+ 172 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 8 |
+ 5448576010_A |
+ 390 |
+
+
+ | 26 |
+ BXD18 |
+ P3 |
+ 1 |
+ 5448576045_E |
+ 392 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 8 |
+ 5237939010_E |
+ 210 |
+
+
+ | 28 |
+ BXD19 |
+ P3 |
+ 1 |
+ 5448576045_A |
+ 211 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 5 |
+ 5452241017_B |
+ 439 |
+
+
+ | 30 |
+ BXD20 |
+ P3 |
+ 6 |
+ 5452241033_E |
+ 441 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 7 |
+ 5384138021_F |
+ 341 |
+
+
+ | 32 |
+ BXD21 |
+ P3 |
+ 6 |
+ 5384138053_F |
+ 315 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 8 |
+ 5237939012_B |
+ 251 |
+
+
+ | 34 |
+ BXD24a |
+ P3 |
+ 7 |
+ 5384138020_B |
+ 250 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 8 |
+ 5237939012_D |
+ 298 |
+
+
+ | 36 |
+ BXD27 |
+ P3 |
+ 1 |
+ 5448576045_C |
+ 300 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 2 |
+ 5384138049_B |
+ 550 |
+
+
+ | 38 |
+ BXD28 |
+ P3 |
+ 1 |
+ 5448576029_F |
+ 548 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 2 |
+ 5384138047_F |
+ 502 |
+
+
+ | 40 |
+ BXD29 |
+ P3 |
+ 1 |
+ 5448576029_D |
+ 501 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 5 |
+ 5452241024_D |
+ 579 |
+
+
+ | 42 |
+ BXD31 |
+ P3 |
+ 6 |
+ 5452241035_D |
+ 582 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_F |
+ 407 |
+
+
+ | 44 |
+ BXD32 |
+ P3 |
+ 6 |
+ 5452241033_C |
+ 408 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 8 |
+ 5237939012_F |
+ 345 |
+
+
+ | 46 |
+ BXD34 |
+ P3 |
+ 4 |
+ 5452241022_F |
+ 355 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 7 |
+ 5384138016_A |
+ 429 |
+
+
+ | 48 |
+ BXD36 |
+ P3 |
+ 8 |
+ 5448576010_D |
+ 430 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 2 |
+ 5384138041_F |
+ 327 |
+
+
+ | 50 |
+ BXD38 |
+ P3 |
+ 3 |
+ 5384138058_E |
+ 328 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 7 |
+ 5384138016_E |
+ 515 |
+
+
+ | 52 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241024_A |
+ 518 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 2 |
+ 5384138041_C |
+ 373 |
+
+
+ | 54 |
+ BXD40 |
+ P3 |
+ 3 |
+ 5452241008_A |
+ 375 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 3 |
+ 5452241008_E |
+ 485 |
+
+
+ | 56 |
+ BXD42 |
+ P3 |
+ 4 |
+ 5452241023_F |
+ 486 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 5 |
+ 5452241024_F |
+ 621 |
+
+
+ | 58 |
+ BXD51 |
+ P3 |
+ 6 |
+ 5452241035_F |
+ 622 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 4 |
+ 5452241031_C |
+ 554 |
+
+
+ | 60 |
+ BXD61 |
+ P3 |
+ 3 |
+ 5452241034_A |
+ 552 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 2 |
+ 5384138049_D |
+ 590 |
+
+
+ | 62 |
+ BXD70 |
+ P3 |
+ 1 |
+ 5448576044_B |
+ 589 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 2 |
+ 5384138049_E |
+ 603 |
+
+
+ | 64 |
+ BXD73 |
+ P3 |
+ 8 |
+ 5448576011_E |
+ 605 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/DevNeocortex_ILM6_2P14RInv_1110/cases.rtf b/general/datasets/DevNeocortex_ILM6_2P14RInv_1110/cases.rtf
deleted file mode 100644
index 70216c8..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P14RInv_1110/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-About the strains used to generate this set of data
-
-The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevNeocortex_ILM6_2P14RInv_1110/experiment-design.rtf b/general/datasets/DevNeocortex_ILM6_2P14RInv_1110/experiment-design.rtf
deleted file mode 100644
index 616db01..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P14RInv_1110/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
-
-This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevNeocortex_ILM6_2P14RInv_1110/summary.rtf b/general/datasets/DevNeocortex_ILM6_2P14RInv_1110/summary.rtf
deleted file mode 100644
index 70d7451..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P14RInv_1110/summary.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-Data generated by Dr. Glenn D. Rosen and colleagues
-
-The Neocortex Developmental data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
-
-Some of these data were used in
-Gaglani SM, Lu L, Williams RW, Rosen GD (2009) The genetic control of neocortex volume and covariation with patterns of gene expression in mice. BMC Neuroscience 10:44 Full Text HTML Version, Full Text PDF Version
-
-All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the Striatal Developmental Transcriptome data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
-
-As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Developmental data set, xxxx probes have LRS values >46 (LOD >10).
-
-Users of these mouse neocortex data may also find the following complementary resources and papers useful:
-
-Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
-
-A movie of the dissection of the brain by Dr. Glenn Rosen. ABOUT THE NEOCORTEX
diff --git a/general/datasets/DevNeocortex_ILM6_2P14RInv_1110/tissue.rtf b/general/datasets/DevNeocortex_ILM6_2P14RInv_1110/tissue.rtf
deleted file mode 100644
index 51f6e74..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P14RInv_1110/tissue.rtf
+++ /dev/null
@@ -1,536 +0,0 @@
-All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
-
-All animals used in this study were either 3 or 14 days of age. A pool of dissected neocortical tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn D. Rosen and colleagues.
-
-
-
-
-
-
-
-
- | Index |
- Strain |
- Age |
- Batch ID |
- Sample ID |
- Tube ID |
-
-
- | 1 |
- BXD1 |
- P3 |
- 2 |
- 5384138018_F |
- 236 |
-
-
- | 2 |
- BXD1 |
- P3 |
- 3 |
- 5384138058_A |
- 239 |
-
-
- | 3 |
- BXD2 |
- P3 |
- 2 |
- 5384138018_C |
- 168 |
-
-
- | 4 |
- BXD2 |
- P3 |
- 1 |
- 5448576044_F |
- 167 |
-
-
- | 5 |
- BXD5 |
- P3 |
- 7 |
- 5384138020_A |
- 273 |
-
-
- | 6 |
- BXD5 |
- P3 |
- 4 |
- 5452241022_C |
- 267 |
-
-
- | 7 |
- BXD6 |
- P3 |
- 3 |
- 5384138048_A |
- 107 |
-
-
- | 8 |
- BXD6 |
- P3 |
- 4 |
- 5452241007_A |
- 108 |
-
-
- | 9 |
- BXD8 |
- P3 |
- 6 |
- 5384138009_A |
- 113 |
-
-
- | 10 |
- BXD8 |
- P3 |
- 7 |
- 5384138021_C |
- 115 |
-
-
- | 11 |
- BXD9 |
- P3 |
- 5 |
- 5452241004_F |
- 289 |
-
-
- | 12 |
- BXD9 |
- P3 |
- 4 |
- 5452241022_D |
- 288 |
-
-
- | 13 |
- BXD11 |
- P3 |
- 8 |
- 5237939010_A |
- 117 |
-
-
- | 14 |
- BXD11 |
- P3 |
- 1 |
- 5448576044_D |
- 120 |
-
-
- | 15 |
- BXD12 |
- P3 |
- 6 |
- 5384138009_B |
- 130 |
-
-
- | 16 |
- BXD12 |
- P3 |
- 7 |
- 5384138021_B |
- 132 |
-
-
- | 17 |
- BXD13 |
- P3 |
- 7 |
- 5384138020_F |
- 161 |
-
-
- | 18 |
- BXD13 |
- P3 |
- 5 |
- 5452241004_C |
- 164 |
-
-
- | 19 |
- BXD14 |
- P3 |
- 5 |
- 5452241004_B |
- 158 |
-
-
- | 20 |
- BXD14 |
- P3 |
- 6 |
- 5452241033_D |
- 424 |
-
-
- | 21 |
- BXD15 |
- P3 |
- 3 |
- 5452241008_C |
- 437 |
-
-
- | 22 |
- BXD15 |
- P3 |
- 4 |
- 5452241023_D |
- 438 |
-
-
- | 23 |
- BXD16 |
- P3 |
- 3 |
- 5384138048_D |
- 170 |
-
-
- | 24 |
- BXD16 |
- P3 |
- 4 |
- 5452241007_D |
- 172 |
-
-
- | 25 |
- BXD18 |
- P3 |
- 8 |
- 5448576010_A |
- 390 |
-
-
- | 26 |
- BXD18 |
- P3 |
- 1 |
- 5448576045_E |
- 392 |
-
-
- | 27 |
- BXD19 |
- P3 |
- 8 |
- 5237939010_E |
- 210 |
-
-
- | 28 |
- BXD19 |
- P3 |
- 1 |
- 5448576045_A |
- 211 |
-
-
- | 29 |
- BXD20 |
- P3 |
- 5 |
- 5452241017_B |
- 439 |
-
-
- | 30 |
- BXD20 |
- P3 |
- 6 |
- 5452241033_E |
- 441 |
-
-
- | 31 |
- BXD21 |
- P3 |
- 7 |
- 5384138021_F |
- 341 |
-
-
- | 32 |
- BXD21 |
- P3 |
- 6 |
- 5384138053_F |
- 315 |
-
-
- | 33 |
- BXD24a |
- P3 |
- 8 |
- 5237939012_B |
- 251 |
-
-
- | 34 |
- BXD24a |
- P3 |
- 7 |
- 5384138020_B |
- 250 |
-
-
- | 35 |
- BXD27 |
- P3 |
- 8 |
- 5237939012_D |
- 298 |
-
-
- | 36 |
- BXD27 |
- P3 |
- 1 |
- 5448576045_C |
- 300 |
-
-
- | 37 |
- BXD28 |
- P3 |
- 2 |
- 5384138049_B |
- 550 |
-
-
- | 38 |
- BXD28 |
- P3 |
- 1 |
- 5448576029_F |
- 548 |
-
-
- | 39 |
- BXD29 |
- P3 |
- 2 |
- 5384138047_F |
- 502 |
-
-
- | 40 |
- BXD29 |
- P3 |
- 1 |
- 5448576029_D |
- 501 |
-
-
- | 41 |
- BXD31 |
- P3 |
- 5 |
- 5452241024_D |
- 579 |
-
-
- | 42 |
- BXD31 |
- P3 |
- 6 |
- 5452241035_D |
- 582 |
-
-
- | 43 |
- BXD32 |
- P3 |
- 5 |
- 5452241006_F |
- 407 |
-
-
- | 44 |
- BXD32 |
- P3 |
- 6 |
- 5452241033_C |
- 408 |
-
-
- | 45 |
- BXD34 |
- P3 |
- 8 |
- 5237939012_F |
- 345 |
-
-
- | 46 |
- BXD34 |
- P3 |
- 4 |
- 5452241022_F |
- 355 |
-
-
- | 47 |
- BXD36 |
- P3 |
- 7 |
- 5384138016_A |
- 429 |
-
-
- | 48 |
- BXD36 |
- P3 |
- 8 |
- 5448576010_D |
- 430 |
-
-
- | 49 |
- BXD38 |
- P3 |
- 2 |
- 5384138041_F |
- 327 |
-
-
- | 50 |
- BXD38 |
- P3 |
- 3 |
- 5384138058_E |
- 328 |
-
-
- | 51 |
- BXD39 |
- P3 |
- 7 |
- 5384138016_E |
- 515 |
-
-
- | 52 |
- BXD39 |
- P3 |
- 5 |
- 5452241024_A |
- 518 |
-
-
- | 53 |
- BXD40 |
- P3 |
- 2 |
- 5384138041_C |
- 373 |
-
-
- | 54 |
- BXD40 |
- P3 |
- 3 |
- 5452241008_A |
- 375 |
-
-
- | 55 |
- BXD42 |
- P3 |
- 3 |
- 5452241008_E |
- 485 |
-
-
- | 56 |
- BXD42 |
- P3 |
- 4 |
- 5452241023_F |
- 486 |
-
-
- | 57 |
- BXD51 |
- P3 |
- 5 |
- 5452241024_F |
- 621 |
-
-
- | 58 |
- BXD51 |
- P3 |
- 6 |
- 5452241035_F |
- 622 |
-
-
- | 59 |
- BXD61 |
- P3 |
- 4 |
- 5452241031_C |
- 554 |
-
-
- | 60 |
- BXD61 |
- P3 |
- 3 |
- 5452241034_A |
- 552 |
-
-
- | 61 |
- BXD70 |
- P3 |
- 2 |
- 5384138049_D |
- 590 |
-
-
- | 62 |
- BXD70 |
- P3 |
- 1 |
- 5448576044_B |
- 589 |
-
-
- | 63 |
- BXD73 |
- P3 |
- 2 |
- 5384138049_E |
- 603 |
-
-
- | 64 |
- BXD73 |
- P3 |
- 8 |
- 5448576011_E |
- 605 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/DevNeocortex_ILM6_2P14RInv_1111/cases.rtf b/general/datasets/DevNeocortex_ILM6_2P14RInv_1111/cases.rtf
deleted file mode 100644
index 70216c8..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P14RInv_1111/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-About the strains used to generate this set of data
-
-The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevNeocortex_ILM6_2P14RInv_1111/experiment-design.rtf b/general/datasets/DevNeocortex_ILM6_2P14RInv_1111/experiment-design.rtf
deleted file mode 100644
index 616db01..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P14RInv_1111/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
-
-This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevNeocortex_ILM6_2P14RInv_1111/summary.rtf b/general/datasets/DevNeocortex_ILM6_2P14RInv_1111/summary.rtf
deleted file mode 100644
index 70d7451..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P14RInv_1111/summary.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-Data generated by Dr. Glenn D. Rosen and colleagues
-
-The Neocortex Developmental data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
-
-Some of these data were used in
-Gaglani SM, Lu L, Williams RW, Rosen GD (2009) The genetic control of neocortex volume and covariation with patterns of gene expression in mice. BMC Neuroscience 10:44 Full Text HTML Version, Full Text PDF Version
-
-All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the Striatal Developmental Transcriptome data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
-
-As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Developmental data set, xxxx probes have LRS values >46 (LOD >10).
-
-Users of these mouse neocortex data may also find the following complementary resources and papers useful:
-
-Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
-
-A movie of the dissection of the brain by Dr. Glenn Rosen. ABOUT THE NEOCORTEX
diff --git a/general/datasets/DevNeocortex_ILM6_2P14RInv_1111/tissue.rtf b/general/datasets/DevNeocortex_ILM6_2P14RInv_1111/tissue.rtf
deleted file mode 100644
index 51f6e74..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P14RInv_1111/tissue.rtf
+++ /dev/null
@@ -1,536 +0,0 @@
-All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
-
-All animals used in this study were either 3 or 14 days of age. A pool of dissected neocortical tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn D. Rosen and colleagues.
-
-
-
-
-
-
-
-
- | Index |
- Strain |
- Age |
- Batch ID |
- Sample ID |
- Tube ID |
-
-
- | 1 |
- BXD1 |
- P3 |
- 2 |
- 5384138018_F |
- 236 |
-
-
- | 2 |
- BXD1 |
- P3 |
- 3 |
- 5384138058_A |
- 239 |
-
-
- | 3 |
- BXD2 |
- P3 |
- 2 |
- 5384138018_C |
- 168 |
-
-
- | 4 |
- BXD2 |
- P3 |
- 1 |
- 5448576044_F |
- 167 |
-
-
- | 5 |
- BXD5 |
- P3 |
- 7 |
- 5384138020_A |
- 273 |
-
-
- | 6 |
- BXD5 |
- P3 |
- 4 |
- 5452241022_C |
- 267 |
-
-
- | 7 |
- BXD6 |
- P3 |
- 3 |
- 5384138048_A |
- 107 |
-
-
- | 8 |
- BXD6 |
- P3 |
- 4 |
- 5452241007_A |
- 108 |
-
-
- | 9 |
- BXD8 |
- P3 |
- 6 |
- 5384138009_A |
- 113 |
-
-
- | 10 |
- BXD8 |
- P3 |
- 7 |
- 5384138021_C |
- 115 |
-
-
- | 11 |
- BXD9 |
- P3 |
- 5 |
- 5452241004_F |
- 289 |
-
-
- | 12 |
- BXD9 |
- P3 |
- 4 |
- 5452241022_D |
- 288 |
-
-
- | 13 |
- BXD11 |
- P3 |
- 8 |
- 5237939010_A |
- 117 |
-
-
- | 14 |
- BXD11 |
- P3 |
- 1 |
- 5448576044_D |
- 120 |
-
-
- | 15 |
- BXD12 |
- P3 |
- 6 |
- 5384138009_B |
- 130 |
-
-
- | 16 |
- BXD12 |
- P3 |
- 7 |
- 5384138021_B |
- 132 |
-
-
- | 17 |
- BXD13 |
- P3 |
- 7 |
- 5384138020_F |
- 161 |
-
-
- | 18 |
- BXD13 |
- P3 |
- 5 |
- 5452241004_C |
- 164 |
-
-
- | 19 |
- BXD14 |
- P3 |
- 5 |
- 5452241004_B |
- 158 |
-
-
- | 20 |
- BXD14 |
- P3 |
- 6 |
- 5452241033_D |
- 424 |
-
-
- | 21 |
- BXD15 |
- P3 |
- 3 |
- 5452241008_C |
- 437 |
-
-
- | 22 |
- BXD15 |
- P3 |
- 4 |
- 5452241023_D |
- 438 |
-
-
- | 23 |
- BXD16 |
- P3 |
- 3 |
- 5384138048_D |
- 170 |
-
-
- | 24 |
- BXD16 |
- P3 |
- 4 |
- 5452241007_D |
- 172 |
-
-
- | 25 |
- BXD18 |
- P3 |
- 8 |
- 5448576010_A |
- 390 |
-
-
- | 26 |
- BXD18 |
- P3 |
- 1 |
- 5448576045_E |
- 392 |
-
-
- | 27 |
- BXD19 |
- P3 |
- 8 |
- 5237939010_E |
- 210 |
-
-
- | 28 |
- BXD19 |
- P3 |
- 1 |
- 5448576045_A |
- 211 |
-
-
- | 29 |
- BXD20 |
- P3 |
- 5 |
- 5452241017_B |
- 439 |
-
-
- | 30 |
- BXD20 |
- P3 |
- 6 |
- 5452241033_E |
- 441 |
-
-
- | 31 |
- BXD21 |
- P3 |
- 7 |
- 5384138021_F |
- 341 |
-
-
- | 32 |
- BXD21 |
- P3 |
- 6 |
- 5384138053_F |
- 315 |
-
-
- | 33 |
- BXD24a |
- P3 |
- 8 |
- 5237939012_B |
- 251 |
-
-
- | 34 |
- BXD24a |
- P3 |
- 7 |
- 5384138020_B |
- 250 |
-
-
- | 35 |
- BXD27 |
- P3 |
- 8 |
- 5237939012_D |
- 298 |
-
-
- | 36 |
- BXD27 |
- P3 |
- 1 |
- 5448576045_C |
- 300 |
-
-
- | 37 |
- BXD28 |
- P3 |
- 2 |
- 5384138049_B |
- 550 |
-
-
- | 38 |
- BXD28 |
- P3 |
- 1 |
- 5448576029_F |
- 548 |
-
-
- | 39 |
- BXD29 |
- P3 |
- 2 |
- 5384138047_F |
- 502 |
-
-
- | 40 |
- BXD29 |
- P3 |
- 1 |
- 5448576029_D |
- 501 |
-
-
- | 41 |
- BXD31 |
- P3 |
- 5 |
- 5452241024_D |
- 579 |
-
-
- | 42 |
- BXD31 |
- P3 |
- 6 |
- 5452241035_D |
- 582 |
-
-
- | 43 |
- BXD32 |
- P3 |
- 5 |
- 5452241006_F |
- 407 |
-
-
- | 44 |
- BXD32 |
- P3 |
- 6 |
- 5452241033_C |
- 408 |
-
-
- | 45 |
- BXD34 |
- P3 |
- 8 |
- 5237939012_F |
- 345 |
-
-
- | 46 |
- BXD34 |
- P3 |
- 4 |
- 5452241022_F |
- 355 |
-
-
- | 47 |
- BXD36 |
- P3 |
- 7 |
- 5384138016_A |
- 429 |
-
-
- | 48 |
- BXD36 |
- P3 |
- 8 |
- 5448576010_D |
- 430 |
-
-
- | 49 |
- BXD38 |
- P3 |
- 2 |
- 5384138041_F |
- 327 |
-
-
- | 50 |
- BXD38 |
- P3 |
- 3 |
- 5384138058_E |
- 328 |
-
-
- | 51 |
- BXD39 |
- P3 |
- 7 |
- 5384138016_E |
- 515 |
-
-
- | 52 |
- BXD39 |
- P3 |
- 5 |
- 5452241024_A |
- 518 |
-
-
- | 53 |
- BXD40 |
- P3 |
- 2 |
- 5384138041_C |
- 373 |
-
-
- | 54 |
- BXD40 |
- P3 |
- 3 |
- 5452241008_A |
- 375 |
-
-
- | 55 |
- BXD42 |
- P3 |
- 3 |
- 5452241008_E |
- 485 |
-
-
- | 56 |
- BXD42 |
- P3 |
- 4 |
- 5452241023_F |
- 486 |
-
-
- | 57 |
- BXD51 |
- P3 |
- 5 |
- 5452241024_F |
- 621 |
-
-
- | 58 |
- BXD51 |
- P3 |
- 6 |
- 5452241035_F |
- 622 |
-
-
- | 59 |
- BXD61 |
- P3 |
- 4 |
- 5452241031_C |
- 554 |
-
-
- | 60 |
- BXD61 |
- P3 |
- 3 |
- 5452241034_A |
- 552 |
-
-
- | 61 |
- BXD70 |
- P3 |
- 2 |
- 5384138049_D |
- 590 |
-
-
- | 62 |
- BXD70 |
- P3 |
- 1 |
- 5448576044_B |
- 589 |
-
-
- | 63 |
- BXD73 |
- P3 |
- 2 |
- 5384138049_E |
- 603 |
-
-
- | 64 |
- BXD73 |
- P3 |
- 8 |
- 5448576011_E |
- 605 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/DevNeocortex_ILM6_2P3RInv_1110/cases.rtf b/general/datasets/DevNeocortex_ILM6_2P3RInv_1110/cases.rtf
deleted file mode 100644
index 70216c8..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P3RInv_1110/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-About the strains used to generate this set of data
-
-The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevNeocortex_ILM6_2P3RInv_1110/experiment-design.rtf b/general/datasets/DevNeocortex_ILM6_2P3RInv_1110/experiment-design.rtf
deleted file mode 100644
index 616db01..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P3RInv_1110/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
-
-This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevNeocortex_ILM6_2P3RInv_1110/summary.rtf b/general/datasets/DevNeocortex_ILM6_2P3RInv_1110/summary.rtf
deleted file mode 100644
index 70d7451..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P3RInv_1110/summary.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-Data generated by Dr. Glenn D. Rosen and colleagues
-
-The Neocortex Developmental data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
-
-Some of these data were used in
-Gaglani SM, Lu L, Williams RW, Rosen GD (2009) The genetic control of neocortex volume and covariation with patterns of gene expression in mice. BMC Neuroscience 10:44 Full Text HTML Version, Full Text PDF Version
-
-All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the Striatal Developmental Transcriptome data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
-
-As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Developmental data set, xxxx probes have LRS values >46 (LOD >10).
-
-Users of these mouse neocortex data may also find the following complementary resources and papers useful:
-
-Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
-
-A movie of the dissection of the brain by Dr. Glenn Rosen. ABOUT THE NEOCORTEX
diff --git a/general/datasets/DevNeocortex_ILM6_2P3RInv_1110/tissue.rtf b/general/datasets/DevNeocortex_ILM6_2P3RInv_1110/tissue.rtf
deleted file mode 100644
index 51f6e74..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P3RInv_1110/tissue.rtf
+++ /dev/null
@@ -1,536 +0,0 @@
-All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
-
-All animals used in this study were either 3 or 14 days of age. A pool of dissected neocortical tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn D. Rosen and colleagues.
-
-
-
-
-
-
-
-
- | Index |
- Strain |
- Age |
- Batch ID |
- Sample ID |
- Tube ID |
-
-
- | 1 |
- BXD1 |
- P3 |
- 2 |
- 5384138018_F |
- 236 |
-
-
- | 2 |
- BXD1 |
- P3 |
- 3 |
- 5384138058_A |
- 239 |
-
-
- | 3 |
- BXD2 |
- P3 |
- 2 |
- 5384138018_C |
- 168 |
-
-
- | 4 |
- BXD2 |
- P3 |
- 1 |
- 5448576044_F |
- 167 |
-
-
- | 5 |
- BXD5 |
- P3 |
- 7 |
- 5384138020_A |
- 273 |
-
-
- | 6 |
- BXD5 |
- P3 |
- 4 |
- 5452241022_C |
- 267 |
-
-
- | 7 |
- BXD6 |
- P3 |
- 3 |
- 5384138048_A |
- 107 |
-
-
- | 8 |
- BXD6 |
- P3 |
- 4 |
- 5452241007_A |
- 108 |
-
-
- | 9 |
- BXD8 |
- P3 |
- 6 |
- 5384138009_A |
- 113 |
-
-
- | 10 |
- BXD8 |
- P3 |
- 7 |
- 5384138021_C |
- 115 |
-
-
- | 11 |
- BXD9 |
- P3 |
- 5 |
- 5452241004_F |
- 289 |
-
-
- | 12 |
- BXD9 |
- P3 |
- 4 |
- 5452241022_D |
- 288 |
-
-
- | 13 |
- BXD11 |
- P3 |
- 8 |
- 5237939010_A |
- 117 |
-
-
- | 14 |
- BXD11 |
- P3 |
- 1 |
- 5448576044_D |
- 120 |
-
-
- | 15 |
- BXD12 |
- P3 |
- 6 |
- 5384138009_B |
- 130 |
-
-
- | 16 |
- BXD12 |
- P3 |
- 7 |
- 5384138021_B |
- 132 |
-
-
- | 17 |
- BXD13 |
- P3 |
- 7 |
- 5384138020_F |
- 161 |
-
-
- | 18 |
- BXD13 |
- P3 |
- 5 |
- 5452241004_C |
- 164 |
-
-
- | 19 |
- BXD14 |
- P3 |
- 5 |
- 5452241004_B |
- 158 |
-
-
- | 20 |
- BXD14 |
- P3 |
- 6 |
- 5452241033_D |
- 424 |
-
-
- | 21 |
- BXD15 |
- P3 |
- 3 |
- 5452241008_C |
- 437 |
-
-
- | 22 |
- BXD15 |
- P3 |
- 4 |
- 5452241023_D |
- 438 |
-
-
- | 23 |
- BXD16 |
- P3 |
- 3 |
- 5384138048_D |
- 170 |
-
-
- | 24 |
- BXD16 |
- P3 |
- 4 |
- 5452241007_D |
- 172 |
-
-
- | 25 |
- BXD18 |
- P3 |
- 8 |
- 5448576010_A |
- 390 |
-
-
- | 26 |
- BXD18 |
- P3 |
- 1 |
- 5448576045_E |
- 392 |
-
-
- | 27 |
- BXD19 |
- P3 |
- 8 |
- 5237939010_E |
- 210 |
-
-
- | 28 |
- BXD19 |
- P3 |
- 1 |
- 5448576045_A |
- 211 |
-
-
- | 29 |
- BXD20 |
- P3 |
- 5 |
- 5452241017_B |
- 439 |
-
-
- | 30 |
- BXD20 |
- P3 |
- 6 |
- 5452241033_E |
- 441 |
-
-
- | 31 |
- BXD21 |
- P3 |
- 7 |
- 5384138021_F |
- 341 |
-
-
- | 32 |
- BXD21 |
- P3 |
- 6 |
- 5384138053_F |
- 315 |
-
-
- | 33 |
- BXD24a |
- P3 |
- 8 |
- 5237939012_B |
- 251 |
-
-
- | 34 |
- BXD24a |
- P3 |
- 7 |
- 5384138020_B |
- 250 |
-
-
- | 35 |
- BXD27 |
- P3 |
- 8 |
- 5237939012_D |
- 298 |
-
-
- | 36 |
- BXD27 |
- P3 |
- 1 |
- 5448576045_C |
- 300 |
-
-
- | 37 |
- BXD28 |
- P3 |
- 2 |
- 5384138049_B |
- 550 |
-
-
- | 38 |
- BXD28 |
- P3 |
- 1 |
- 5448576029_F |
- 548 |
-
-
- | 39 |
- BXD29 |
- P3 |
- 2 |
- 5384138047_F |
- 502 |
-
-
- | 40 |
- BXD29 |
- P3 |
- 1 |
- 5448576029_D |
- 501 |
-
-
- | 41 |
- BXD31 |
- P3 |
- 5 |
- 5452241024_D |
- 579 |
-
-
- | 42 |
- BXD31 |
- P3 |
- 6 |
- 5452241035_D |
- 582 |
-
-
- | 43 |
- BXD32 |
- P3 |
- 5 |
- 5452241006_F |
- 407 |
-
-
- | 44 |
- BXD32 |
- P3 |
- 6 |
- 5452241033_C |
- 408 |
-
-
- | 45 |
- BXD34 |
- P3 |
- 8 |
- 5237939012_F |
- 345 |
-
-
- | 46 |
- BXD34 |
- P3 |
- 4 |
- 5452241022_F |
- 355 |
-
-
- | 47 |
- BXD36 |
- P3 |
- 7 |
- 5384138016_A |
- 429 |
-
-
- | 48 |
- BXD36 |
- P3 |
- 8 |
- 5448576010_D |
- 430 |
-
-
- | 49 |
- BXD38 |
- P3 |
- 2 |
- 5384138041_F |
- 327 |
-
-
- | 50 |
- BXD38 |
- P3 |
- 3 |
- 5384138058_E |
- 328 |
-
-
- | 51 |
- BXD39 |
- P3 |
- 7 |
- 5384138016_E |
- 515 |
-
-
- | 52 |
- BXD39 |
- P3 |
- 5 |
- 5452241024_A |
- 518 |
-
-
- | 53 |
- BXD40 |
- P3 |
- 2 |
- 5384138041_C |
- 373 |
-
-
- | 54 |
- BXD40 |
- P3 |
- 3 |
- 5452241008_A |
- 375 |
-
-
- | 55 |
- BXD42 |
- P3 |
- 3 |
- 5452241008_E |
- 485 |
-
-
- | 56 |
- BXD42 |
- P3 |
- 4 |
- 5452241023_F |
- 486 |
-
-
- | 57 |
- BXD51 |
- P3 |
- 5 |
- 5452241024_F |
- 621 |
-
-
- | 58 |
- BXD51 |
- P3 |
- 6 |
- 5452241035_F |
- 622 |
-
-
- | 59 |
- BXD61 |
- P3 |
- 4 |
- 5452241031_C |
- 554 |
-
-
- | 60 |
- BXD61 |
- P3 |
- 3 |
- 5452241034_A |
- 552 |
-
-
- | 61 |
- BXD70 |
- P3 |
- 2 |
- 5384138049_D |
- 590 |
-
-
- | 62 |
- BXD70 |
- P3 |
- 1 |
- 5448576044_B |
- 589 |
-
-
- | 63 |
- BXD73 |
- P3 |
- 2 |
- 5384138049_E |
- 603 |
-
-
- | 64 |
- BXD73 |
- P3 |
- 8 |
- 5448576011_E |
- 605 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/DevNeocortex_ILM6_2P3RInv_1111/cases.rtf b/general/datasets/DevNeocortex_ILM6_2P3RInv_1111/cases.rtf
deleted file mode 100644
index 70216c8..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P3RInv_1111/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-About the strains used to generate this set of data
-
-The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevNeocortex_ILM6_2P3RInv_1111/experiment-design.rtf b/general/datasets/DevNeocortex_ILM6_2P3RInv_1111/experiment-design.rtf
deleted file mode 100644
index 616db01..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P3RInv_1111/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
-
-This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevNeocortex_ILM6_2P3RInv_1111/summary.rtf b/general/datasets/DevNeocortex_ILM6_2P3RInv_1111/summary.rtf
deleted file mode 100644
index 70d7451..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P3RInv_1111/summary.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-Data generated by Dr. Glenn D. Rosen and colleagues
-
-The Neocortex Developmental data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
-
-Some of these data were used in
-Gaglani SM, Lu L, Williams RW, Rosen GD (2009) The genetic control of neocortex volume and covariation with patterns of gene expression in mice. BMC Neuroscience 10:44 Full Text HTML Version, Full Text PDF Version
-
-All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the Striatal Developmental Transcriptome data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
-
-As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Developmental data set, xxxx probes have LRS values >46 (LOD >10).
-
-Users of these mouse neocortex data may also find the following complementary resources and papers useful:
-
-Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
-
-A movie of the dissection of the brain by Dr. Glenn Rosen. ABOUT THE NEOCORTEX
diff --git a/general/datasets/DevNeocortex_ILM6_2P3RInv_1111/tissue.rtf b/general/datasets/DevNeocortex_ILM6_2P3RInv_1111/tissue.rtf
deleted file mode 100644
index 51f6e74..0000000
--- a/general/datasets/DevNeocortex_ILM6_2P3RInv_1111/tissue.rtf
+++ /dev/null
@@ -1,536 +0,0 @@
-All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
-
-All animals used in this study were either 3 or 14 days of age. A pool of dissected neocortical tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn D. Rosen and colleagues.
-
-
-
-
-
-
-
-
- | Index |
- Strain |
- Age |
- Batch ID |
- Sample ID |
- Tube ID |
-
-
- | 1 |
- BXD1 |
- P3 |
- 2 |
- 5384138018_F |
- 236 |
-
-
- | 2 |
- BXD1 |
- P3 |
- 3 |
- 5384138058_A |
- 239 |
-
-
- | 3 |
- BXD2 |
- P3 |
- 2 |
- 5384138018_C |
- 168 |
-
-
- | 4 |
- BXD2 |
- P3 |
- 1 |
- 5448576044_F |
- 167 |
-
-
- | 5 |
- BXD5 |
- P3 |
- 7 |
- 5384138020_A |
- 273 |
-
-
- | 6 |
- BXD5 |
- P3 |
- 4 |
- 5452241022_C |
- 267 |
-
-
- | 7 |
- BXD6 |
- P3 |
- 3 |
- 5384138048_A |
- 107 |
-
-
- | 8 |
- BXD6 |
- P3 |
- 4 |
- 5452241007_A |
- 108 |
-
-
- | 9 |
- BXD8 |
- P3 |
- 6 |
- 5384138009_A |
- 113 |
-
-
- | 10 |
- BXD8 |
- P3 |
- 7 |
- 5384138021_C |
- 115 |
-
-
- | 11 |
- BXD9 |
- P3 |
- 5 |
- 5452241004_F |
- 289 |
-
-
- | 12 |
- BXD9 |
- P3 |
- 4 |
- 5452241022_D |
- 288 |
-
-
- | 13 |
- BXD11 |
- P3 |
- 8 |
- 5237939010_A |
- 117 |
-
-
- | 14 |
- BXD11 |
- P3 |
- 1 |
- 5448576044_D |
- 120 |
-
-
- | 15 |
- BXD12 |
- P3 |
- 6 |
- 5384138009_B |
- 130 |
-
-
- | 16 |
- BXD12 |
- P3 |
- 7 |
- 5384138021_B |
- 132 |
-
-
- | 17 |
- BXD13 |
- P3 |
- 7 |
- 5384138020_F |
- 161 |
-
-
- | 18 |
- BXD13 |
- P3 |
- 5 |
- 5452241004_C |
- 164 |
-
-
- | 19 |
- BXD14 |
- P3 |
- 5 |
- 5452241004_B |
- 158 |
-
-
- | 20 |
- BXD14 |
- P3 |
- 6 |
- 5452241033_D |
- 424 |
-
-
- | 21 |
- BXD15 |
- P3 |
- 3 |
- 5452241008_C |
- 437 |
-
-
- | 22 |
- BXD15 |
- P3 |
- 4 |
- 5452241023_D |
- 438 |
-
-
- | 23 |
- BXD16 |
- P3 |
- 3 |
- 5384138048_D |
- 170 |
-
-
- | 24 |
- BXD16 |
- P3 |
- 4 |
- 5452241007_D |
- 172 |
-
-
- | 25 |
- BXD18 |
- P3 |
- 8 |
- 5448576010_A |
- 390 |
-
-
- | 26 |
- BXD18 |
- P3 |
- 1 |
- 5448576045_E |
- 392 |
-
-
- | 27 |
- BXD19 |
- P3 |
- 8 |
- 5237939010_E |
- 210 |
-
-
- | 28 |
- BXD19 |
- P3 |
- 1 |
- 5448576045_A |
- 211 |
-
-
- | 29 |
- BXD20 |
- P3 |
- 5 |
- 5452241017_B |
- 439 |
-
-
- | 30 |
- BXD20 |
- P3 |
- 6 |
- 5452241033_E |
- 441 |
-
-
- | 31 |
- BXD21 |
- P3 |
- 7 |
- 5384138021_F |
- 341 |
-
-
- | 32 |
- BXD21 |
- P3 |
- 6 |
- 5384138053_F |
- 315 |
-
-
- | 33 |
- BXD24a |
- P3 |
- 8 |
- 5237939012_B |
- 251 |
-
-
- | 34 |
- BXD24a |
- P3 |
- 7 |
- 5384138020_B |
- 250 |
-
-
- | 35 |
- BXD27 |
- P3 |
- 8 |
- 5237939012_D |
- 298 |
-
-
- | 36 |
- BXD27 |
- P3 |
- 1 |
- 5448576045_C |
- 300 |
-
-
- | 37 |
- BXD28 |
- P3 |
- 2 |
- 5384138049_B |
- 550 |
-
-
- | 38 |
- BXD28 |
- P3 |
- 1 |
- 5448576029_F |
- 548 |
-
-
- | 39 |
- BXD29 |
- P3 |
- 2 |
- 5384138047_F |
- 502 |
-
-
- | 40 |
- BXD29 |
- P3 |
- 1 |
- 5448576029_D |
- 501 |
-
-
- | 41 |
- BXD31 |
- P3 |
- 5 |
- 5452241024_D |
- 579 |
-
-
- | 42 |
- BXD31 |
- P3 |
- 6 |
- 5452241035_D |
- 582 |
-
-
- | 43 |
- BXD32 |
- P3 |
- 5 |
- 5452241006_F |
- 407 |
-
-
- | 44 |
- BXD32 |
- P3 |
- 6 |
- 5452241033_C |
- 408 |
-
-
- | 45 |
- BXD34 |
- P3 |
- 8 |
- 5237939012_F |
- 345 |
-
-
- | 46 |
- BXD34 |
- P3 |
- 4 |
- 5452241022_F |
- 355 |
-
-
- | 47 |
- BXD36 |
- P3 |
- 7 |
- 5384138016_A |
- 429 |
-
-
- | 48 |
- BXD36 |
- P3 |
- 8 |
- 5448576010_D |
- 430 |
-
-
- | 49 |
- BXD38 |
- P3 |
- 2 |
- 5384138041_F |
- 327 |
-
-
- | 50 |
- BXD38 |
- P3 |
- 3 |
- 5384138058_E |
- 328 |
-
-
- | 51 |
- BXD39 |
- P3 |
- 7 |
- 5384138016_E |
- 515 |
-
-
- | 52 |
- BXD39 |
- P3 |
- 5 |
- 5452241024_A |
- 518 |
-
-
- | 53 |
- BXD40 |
- P3 |
- 2 |
- 5384138041_C |
- 373 |
-
-
- | 54 |
- BXD40 |
- P3 |
- 3 |
- 5452241008_A |
- 375 |
-
-
- | 55 |
- BXD42 |
- P3 |
- 3 |
- 5452241008_E |
- 485 |
-
-
- | 56 |
- BXD42 |
- P3 |
- 4 |
- 5452241023_F |
- 486 |
-
-
- | 57 |
- BXD51 |
- P3 |
- 5 |
- 5452241024_F |
- 621 |
-
-
- | 58 |
- BXD51 |
- P3 |
- 6 |
- 5452241035_F |
- 622 |
-
-
- | 59 |
- BXD61 |
- P3 |
- 4 |
- 5452241031_C |
- 554 |
-
-
- | 60 |
- BXD61 |
- P3 |
- 3 |
- 5452241034_A |
- 552 |
-
-
- | 61 |
- BXD70 |
- P3 |
- 2 |
- 5384138049_D |
- 590 |
-
-
- | 62 |
- BXD70 |
- P3 |
- 1 |
- 5448576044_B |
- 589 |
-
-
- | 63 |
- BXD73 |
- P3 |
- 2 |
- 5384138049_E |
- 603 |
-
-
- | 64 |
- BXD73 |
- P3 |
- 8 |
- 5448576011_E |
- 605 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/DevStriatum_ILM6.2P14RInv_1110/cases.rtf b/general/datasets/DevStriatum_ILM6.2P14RInv_1110/cases.rtf
new file mode 100644
index 0000000..74c0f5e
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P14RInv_1110/cases.rtf
@@ -0,0 +1 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevStriatum_ILM6.2P14RInv_1110/experiment-design.rtf b/general/datasets/DevStriatum_ILM6.2P14RInv_1110/experiment-design.rtf
new file mode 100644
index 0000000..cfea6b0
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P14RInv_1110/experiment-design.rtf
@@ -0,0 +1 @@
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevStriatum_ILM6.2P14RInv_1110/processing.rtf b/general/datasets/DevStriatum_ILM6.2P14RInv_1110/processing.rtf
new file mode 100644
index 0000000..aee498f
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P14RInv_1110/processing.rtf
@@ -0,0 +1 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
diff --git a/general/datasets/DevStriatum_ILM6.2P14RInv_1110/summary.rtf b/general/datasets/DevStriatum_ILM6.2P14RInv_1110/summary.rtf
new file mode 100644
index 0000000..3515533
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P14RInv_1110/summary.rtf
@@ -0,0 +1,10 @@
+The BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv ** data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv ** data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse striatum data set may also find the following complementary resources and papers useful:
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. www.rosenlab.net/Movie/P3.mov
+www.rosenlab.net/Movie/P14.mov
diff --git a/general/datasets/DevStriatum_ILM6.2P14RInv_1110/tissue.rtf b/general/datasets/DevStriatum_ILM6.2P14RInv_1110/tissue.rtf
new file mode 100644
index 0000000..e9e6151
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P14RInv_1110/tissue.rtf
@@ -0,0 +1,534 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Care was taken to assure that samples were comprised of the dorsal striatum, although it is possible that ventral striatum (accumbens) was occasionally included.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected striatal tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues.
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 8 |
+ 5237939012_A |
+ 232 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 1 |
+ 5448576016_C |
+ 234 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 7 |
+ 5384138020_C |
+ 230 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 6 |
+ 5384138053_A |
+ 228 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 6 |
+ 5384138053_D |
+ 270 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 5 |
+ 5452241004_E |
+ 268 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 2 |
+ 5384138018_A |
+ 102 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 1 |
+ 5448576016_A |
+ 101 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 3 |
+ 5384138048_B |
+ 110 |
+
+
+ | 10 |
+ BXD9 |
+ P3 |
+ 2 |
+ 5384138041_A |
+ 280 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 3 |
+ 5384138058_C |
+ 278 |
+
+
+ | 12 |
+ BXD11 |
+ P3 |
+ 2 |
+ 5384138018_B |
+ 121 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 3 |
+ 5384138048_C |
+ 123 |
+
+
+ | 14 |
+ BXD12 |
+ P3 |
+ 5 |
+ 5452241004_A |
+ 127 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 4 |
+ 5452241007_B |
+ 125 |
+
+
+ | 16 |
+ BXD13 |
+ P3 |
+ 8 |
+ 5237939010_D |
+ 181 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 1 |
+ 5448576016_B |
+ 183 |
+
+
+ | 18 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241017_A |
+ 420 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 4 |
+ 5452241023_C |
+ 419 |
+
+
+ | 20 |
+ BXD15 |
+ P3 |
+ 7 |
+ 5384138016_C |
+ 475 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 8 |
+ 5448576010_F |
+ 476 |
+
+
+ | 22 |
+ BXD16 |
+ P3 |
+ 6 |
+ 5384138009_F |
+ 204 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 7 |
+ 5384138020_D |
+ 205 |
+
+
+ | 24 |
+ BXD18 |
+ P3 |
+ 7 |
+ 5384138017_B |
+ 388 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 3 |
+ 5452241008_B |
+ 385 |
+
+
+ | 26 |
+ BXD19 |
+ P3 |
+ 2 |
+ 5384138018_E |
+ 212 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 3 |
+ 5384138048_F |
+ 213 |
+
+
+ | 28 |
+ BXD20 |
+ P3 |
+ 2 |
+ 5384138047_C |
+ 431 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 1 |
+ 5448576029_A |
+ 431 |
+
+
+ | 30 |
+ BXD21 |
+ P3 |
+ 5 |
+ 5452241006_A |
+ 311 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 4 |
+ 5452241022_E |
+ 309 |
+
+
+ | 32 |
+ BXD24a |
+ P3 |
+ 6 |
+ 5384138053_B |
+ 247 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 4 |
+ 5452241022_B |
+ 244 |
+
+
+ | 34 |
+ BXD27 |
+ P3 |
+ 7 |
+ 5384138021_D |
+ 294 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 6 |
+ 5384138053_E |
+ 293 |
+
+
+ | 36 |
+ BXD28 |
+ P3 |
+ 7 |
+ 5384138016_F |
+ 543 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 8 |
+ 5448576011_B |
+ 545 |
+
+
+ | 38 |
+ BXD29 |
+ P3 |
+ 7 |
+ 5384138016_D |
+ 495 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 8 |
+ 5448576011_A |
+ 498 |
+
+
+ | 40 |
+ BXD31 |
+ P3 |
+ 4 |
+ 5452241031_D |
+ 577 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 3 |
+ 5452241034_D |
+ 575 |
+
+
+ | 42 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_E |
+ 402 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 4 |
+ 5452241023_B |
+ 401 |
+
+
+ | 44 |
+ BXD34 |
+ P3 |
+ 2 |
+ 5384138041_D |
+ 348 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 1 |
+ 5448576016_E |
+ 347 |
+
+
+ | 46 |
+ BXD36 |
+ P3 |
+ 2 |
+ 5384138047_B |
+ 417 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 3 |
+ 5452241008_D |
+ 418 |
+
+
+ | 48 |
+ BXD38 |
+ P3 |
+ 8 |
+ 5237939012_E |
+ 321 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 1 |
+ 5448576016_D |
+ 322 |
+
+
+ | 50 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241017_F |
+ 511 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 4 |
+ 5452241031_A |
+ 512 |
+
+
+ | 52 |
+ BXD40 |
+ P3 |
+ 8 |
+ 5448576010_B |
+ 368 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 1 |
+ 5448576016_F |
+ 371 |
+
+
+ | 54 |
+ BXD42 |
+ P3 |
+ 2 |
+ 5384138047_E |
+ 481 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 1 |
+ 5448576029_C |
+ 479 |
+
+
+ | 56 |
+ BXD51 |
+ P3 |
+ 4 |
+ 5452241031_F |
+ 616 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 3 |
+ 5452241034_F |
+ 615 |
+
+
+ | 58 |
+ BXD61 |
+ P3 |
+ 5 |
+ 5452241024_C |
+ 555 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 6 |
+ 5452241035_B |
+ 557 |
+
+
+ | 60 |
+ BXD70 |
+ P3 |
+ 7 |
+ 5384138017_E |
+ 584 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 8 |
+ 5448576011_D |
+ 585 |
+
+
+ | 62 |
+ BXD73 |
+ P3 |
+ 5 |
+ 5452241024_E |
+ 600 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 6 |
+ 5452241035_E |
+ 601 |
+
+
+
+ |
+
+
+
+
+
+
diff --git a/general/datasets/DevStriatum_ILM6.2P14RInv_1111/cases.rtf b/general/datasets/DevStriatum_ILM6.2P14RInv_1111/cases.rtf
new file mode 100644
index 0000000..74c0f5e
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P14RInv_1111/cases.rtf
@@ -0,0 +1 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevStriatum_ILM6.2P14RInv_1111/experiment-design.rtf b/general/datasets/DevStriatum_ILM6.2P14RInv_1111/experiment-design.rtf
new file mode 100644
index 0000000..cfea6b0
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P14RInv_1111/experiment-design.rtf
@@ -0,0 +1 @@
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevStriatum_ILM6.2P14RInv_1111/processing.rtf b/general/datasets/DevStriatum_ILM6.2P14RInv_1111/processing.rtf
new file mode 100644
index 0000000..aee498f
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P14RInv_1111/processing.rtf
@@ -0,0 +1 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
diff --git a/general/datasets/DevStriatum_ILM6.2P14RInv_1111/summary.rtf b/general/datasets/DevStriatum_ILM6.2P14RInv_1111/summary.rtf
new file mode 100644
index 0000000..3515533
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P14RInv_1111/summary.rtf
@@ -0,0 +1,10 @@
+The BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv ** data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv ** data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse striatum data set may also find the following complementary resources and papers useful:
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. www.rosenlab.net/Movie/P3.mov
+www.rosenlab.net/Movie/P14.mov
diff --git a/general/datasets/DevStriatum_ILM6.2P14RInv_1111/tissue.rtf b/general/datasets/DevStriatum_ILM6.2P14RInv_1111/tissue.rtf
new file mode 100644
index 0000000..e9e6151
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P14RInv_1111/tissue.rtf
@@ -0,0 +1,534 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Care was taken to assure that samples were comprised of the dorsal striatum, although it is possible that ventral striatum (accumbens) was occasionally included.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected striatal tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues.
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 8 |
+ 5237939012_A |
+ 232 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 1 |
+ 5448576016_C |
+ 234 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 7 |
+ 5384138020_C |
+ 230 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 6 |
+ 5384138053_A |
+ 228 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 6 |
+ 5384138053_D |
+ 270 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 5 |
+ 5452241004_E |
+ 268 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 2 |
+ 5384138018_A |
+ 102 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 1 |
+ 5448576016_A |
+ 101 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 3 |
+ 5384138048_B |
+ 110 |
+
+
+ | 10 |
+ BXD9 |
+ P3 |
+ 2 |
+ 5384138041_A |
+ 280 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 3 |
+ 5384138058_C |
+ 278 |
+
+
+ | 12 |
+ BXD11 |
+ P3 |
+ 2 |
+ 5384138018_B |
+ 121 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 3 |
+ 5384138048_C |
+ 123 |
+
+
+ | 14 |
+ BXD12 |
+ P3 |
+ 5 |
+ 5452241004_A |
+ 127 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 4 |
+ 5452241007_B |
+ 125 |
+
+
+ | 16 |
+ BXD13 |
+ P3 |
+ 8 |
+ 5237939010_D |
+ 181 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 1 |
+ 5448576016_B |
+ 183 |
+
+
+ | 18 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241017_A |
+ 420 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 4 |
+ 5452241023_C |
+ 419 |
+
+
+ | 20 |
+ BXD15 |
+ P3 |
+ 7 |
+ 5384138016_C |
+ 475 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 8 |
+ 5448576010_F |
+ 476 |
+
+
+ | 22 |
+ BXD16 |
+ P3 |
+ 6 |
+ 5384138009_F |
+ 204 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 7 |
+ 5384138020_D |
+ 205 |
+
+
+ | 24 |
+ BXD18 |
+ P3 |
+ 7 |
+ 5384138017_B |
+ 388 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 3 |
+ 5452241008_B |
+ 385 |
+
+
+ | 26 |
+ BXD19 |
+ P3 |
+ 2 |
+ 5384138018_E |
+ 212 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 3 |
+ 5384138048_F |
+ 213 |
+
+
+ | 28 |
+ BXD20 |
+ P3 |
+ 2 |
+ 5384138047_C |
+ 431 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 1 |
+ 5448576029_A |
+ 431 |
+
+
+ | 30 |
+ BXD21 |
+ P3 |
+ 5 |
+ 5452241006_A |
+ 311 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 4 |
+ 5452241022_E |
+ 309 |
+
+
+ | 32 |
+ BXD24a |
+ P3 |
+ 6 |
+ 5384138053_B |
+ 247 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 4 |
+ 5452241022_B |
+ 244 |
+
+
+ | 34 |
+ BXD27 |
+ P3 |
+ 7 |
+ 5384138021_D |
+ 294 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 6 |
+ 5384138053_E |
+ 293 |
+
+
+ | 36 |
+ BXD28 |
+ P3 |
+ 7 |
+ 5384138016_F |
+ 543 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 8 |
+ 5448576011_B |
+ 545 |
+
+
+ | 38 |
+ BXD29 |
+ P3 |
+ 7 |
+ 5384138016_D |
+ 495 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 8 |
+ 5448576011_A |
+ 498 |
+
+
+ | 40 |
+ BXD31 |
+ P3 |
+ 4 |
+ 5452241031_D |
+ 577 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 3 |
+ 5452241034_D |
+ 575 |
+
+
+ | 42 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_E |
+ 402 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 4 |
+ 5452241023_B |
+ 401 |
+
+
+ | 44 |
+ BXD34 |
+ P3 |
+ 2 |
+ 5384138041_D |
+ 348 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 1 |
+ 5448576016_E |
+ 347 |
+
+
+ | 46 |
+ BXD36 |
+ P3 |
+ 2 |
+ 5384138047_B |
+ 417 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 3 |
+ 5452241008_D |
+ 418 |
+
+
+ | 48 |
+ BXD38 |
+ P3 |
+ 8 |
+ 5237939012_E |
+ 321 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 1 |
+ 5448576016_D |
+ 322 |
+
+
+ | 50 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241017_F |
+ 511 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 4 |
+ 5452241031_A |
+ 512 |
+
+
+ | 52 |
+ BXD40 |
+ P3 |
+ 8 |
+ 5448576010_B |
+ 368 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 1 |
+ 5448576016_F |
+ 371 |
+
+
+ | 54 |
+ BXD42 |
+ P3 |
+ 2 |
+ 5384138047_E |
+ 481 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 1 |
+ 5448576029_C |
+ 479 |
+
+
+ | 56 |
+ BXD51 |
+ P3 |
+ 4 |
+ 5452241031_F |
+ 616 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 3 |
+ 5452241034_F |
+ 615 |
+
+
+ | 58 |
+ BXD61 |
+ P3 |
+ 5 |
+ 5452241024_C |
+ 555 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 6 |
+ 5452241035_B |
+ 557 |
+
+
+ | 60 |
+ BXD70 |
+ P3 |
+ 7 |
+ 5384138017_E |
+ 584 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 8 |
+ 5448576011_D |
+ 585 |
+
+
+ | 62 |
+ BXD73 |
+ P3 |
+ 5 |
+ 5452241024_E |
+ 600 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 6 |
+ 5452241035_E |
+ 601 |
+
+
+
+ |
+
+
+
+
+
+
diff --git a/general/datasets/DevStriatum_ILM6.2P3RInv_1110/cases.rtf b/general/datasets/DevStriatum_ILM6.2P3RInv_1110/cases.rtf
new file mode 100644
index 0000000..74c0f5e
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P3RInv_1110/cases.rtf
@@ -0,0 +1 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevStriatum_ILM6.2P3RInv_1110/experiment-design.rtf b/general/datasets/DevStriatum_ILM6.2P3RInv_1110/experiment-design.rtf
new file mode 100644
index 0000000..cfea6b0
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P3RInv_1110/experiment-design.rtf
@@ -0,0 +1 @@
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevStriatum_ILM6.2P3RInv_1110/processing.rtf b/general/datasets/DevStriatum_ILM6.2P3RInv_1110/processing.rtf
new file mode 100644
index 0000000..aee498f
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P3RInv_1110/processing.rtf
@@ -0,0 +1 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
diff --git a/general/datasets/DevStriatum_ILM6.2P3RInv_1110/summary.rtf b/general/datasets/DevStriatum_ILM6.2P3RInv_1110/summary.rtf
new file mode 100644
index 0000000..3515533
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P3RInv_1110/summary.rtf
@@ -0,0 +1,10 @@
+The BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv ** data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv ** data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse striatum data set may also find the following complementary resources and papers useful:
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. www.rosenlab.net/Movie/P3.mov
+www.rosenlab.net/Movie/P14.mov
diff --git a/general/datasets/DevStriatum_ILM6.2P3RInv_1110/tissue.rtf b/general/datasets/DevStriatum_ILM6.2P3RInv_1110/tissue.rtf
new file mode 100644
index 0000000..e9e6151
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P3RInv_1110/tissue.rtf
@@ -0,0 +1,534 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Care was taken to assure that samples were comprised of the dorsal striatum, although it is possible that ventral striatum (accumbens) was occasionally included.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected striatal tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues.
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 8 |
+ 5237939012_A |
+ 232 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 1 |
+ 5448576016_C |
+ 234 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 7 |
+ 5384138020_C |
+ 230 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 6 |
+ 5384138053_A |
+ 228 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 6 |
+ 5384138053_D |
+ 270 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 5 |
+ 5452241004_E |
+ 268 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 2 |
+ 5384138018_A |
+ 102 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 1 |
+ 5448576016_A |
+ 101 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 3 |
+ 5384138048_B |
+ 110 |
+
+
+ | 10 |
+ BXD9 |
+ P3 |
+ 2 |
+ 5384138041_A |
+ 280 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 3 |
+ 5384138058_C |
+ 278 |
+
+
+ | 12 |
+ BXD11 |
+ P3 |
+ 2 |
+ 5384138018_B |
+ 121 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 3 |
+ 5384138048_C |
+ 123 |
+
+
+ | 14 |
+ BXD12 |
+ P3 |
+ 5 |
+ 5452241004_A |
+ 127 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 4 |
+ 5452241007_B |
+ 125 |
+
+
+ | 16 |
+ BXD13 |
+ P3 |
+ 8 |
+ 5237939010_D |
+ 181 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 1 |
+ 5448576016_B |
+ 183 |
+
+
+ | 18 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241017_A |
+ 420 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 4 |
+ 5452241023_C |
+ 419 |
+
+
+ | 20 |
+ BXD15 |
+ P3 |
+ 7 |
+ 5384138016_C |
+ 475 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 8 |
+ 5448576010_F |
+ 476 |
+
+
+ | 22 |
+ BXD16 |
+ P3 |
+ 6 |
+ 5384138009_F |
+ 204 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 7 |
+ 5384138020_D |
+ 205 |
+
+
+ | 24 |
+ BXD18 |
+ P3 |
+ 7 |
+ 5384138017_B |
+ 388 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 3 |
+ 5452241008_B |
+ 385 |
+
+
+ | 26 |
+ BXD19 |
+ P3 |
+ 2 |
+ 5384138018_E |
+ 212 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 3 |
+ 5384138048_F |
+ 213 |
+
+
+ | 28 |
+ BXD20 |
+ P3 |
+ 2 |
+ 5384138047_C |
+ 431 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 1 |
+ 5448576029_A |
+ 431 |
+
+
+ | 30 |
+ BXD21 |
+ P3 |
+ 5 |
+ 5452241006_A |
+ 311 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 4 |
+ 5452241022_E |
+ 309 |
+
+
+ | 32 |
+ BXD24a |
+ P3 |
+ 6 |
+ 5384138053_B |
+ 247 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 4 |
+ 5452241022_B |
+ 244 |
+
+
+ | 34 |
+ BXD27 |
+ P3 |
+ 7 |
+ 5384138021_D |
+ 294 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 6 |
+ 5384138053_E |
+ 293 |
+
+
+ | 36 |
+ BXD28 |
+ P3 |
+ 7 |
+ 5384138016_F |
+ 543 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 8 |
+ 5448576011_B |
+ 545 |
+
+
+ | 38 |
+ BXD29 |
+ P3 |
+ 7 |
+ 5384138016_D |
+ 495 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 8 |
+ 5448576011_A |
+ 498 |
+
+
+ | 40 |
+ BXD31 |
+ P3 |
+ 4 |
+ 5452241031_D |
+ 577 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 3 |
+ 5452241034_D |
+ 575 |
+
+
+ | 42 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_E |
+ 402 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 4 |
+ 5452241023_B |
+ 401 |
+
+
+ | 44 |
+ BXD34 |
+ P3 |
+ 2 |
+ 5384138041_D |
+ 348 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 1 |
+ 5448576016_E |
+ 347 |
+
+
+ | 46 |
+ BXD36 |
+ P3 |
+ 2 |
+ 5384138047_B |
+ 417 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 3 |
+ 5452241008_D |
+ 418 |
+
+
+ | 48 |
+ BXD38 |
+ P3 |
+ 8 |
+ 5237939012_E |
+ 321 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 1 |
+ 5448576016_D |
+ 322 |
+
+
+ | 50 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241017_F |
+ 511 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 4 |
+ 5452241031_A |
+ 512 |
+
+
+ | 52 |
+ BXD40 |
+ P3 |
+ 8 |
+ 5448576010_B |
+ 368 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 1 |
+ 5448576016_F |
+ 371 |
+
+
+ | 54 |
+ BXD42 |
+ P3 |
+ 2 |
+ 5384138047_E |
+ 481 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 1 |
+ 5448576029_C |
+ 479 |
+
+
+ | 56 |
+ BXD51 |
+ P3 |
+ 4 |
+ 5452241031_F |
+ 616 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 3 |
+ 5452241034_F |
+ 615 |
+
+
+ | 58 |
+ BXD61 |
+ P3 |
+ 5 |
+ 5452241024_C |
+ 555 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 6 |
+ 5452241035_B |
+ 557 |
+
+
+ | 60 |
+ BXD70 |
+ P3 |
+ 7 |
+ 5384138017_E |
+ 584 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 8 |
+ 5448576011_D |
+ 585 |
+
+
+ | 62 |
+ BXD73 |
+ P3 |
+ 5 |
+ 5452241024_E |
+ 600 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 6 |
+ 5452241035_E |
+ 601 |
+
+
+
+ |
+
+
+
+
+
+
diff --git a/general/datasets/DevStriatum_ILM6.2P3RInv_1111/cases.rtf b/general/datasets/DevStriatum_ILM6.2P3RInv_1111/cases.rtf
new file mode 100644
index 0000000..74c0f5e
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P3RInv_1111/cases.rtf
@@ -0,0 +1 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevStriatum_ILM6.2P3RInv_1111/experiment-design.rtf b/general/datasets/DevStriatum_ILM6.2P3RInv_1111/experiment-design.rtf
new file mode 100644
index 0000000..cfea6b0
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P3RInv_1111/experiment-design.rtf
@@ -0,0 +1 @@
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevStriatum_ILM6.2P3RInv_1111/processing.rtf b/general/datasets/DevStriatum_ILM6.2P3RInv_1111/processing.rtf
new file mode 100644
index 0000000..aee498f
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P3RInv_1111/processing.rtf
@@ -0,0 +1 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
diff --git a/general/datasets/DevStriatum_ILM6.2P3RInv_1111/summary.rtf b/general/datasets/DevStriatum_ILM6.2P3RInv_1111/summary.rtf
new file mode 100644
index 0000000..3515533
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P3RInv_1111/summary.rtf
@@ -0,0 +1,10 @@
+The BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv ** data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv ** data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse striatum data set may also find the following complementary resources and papers useful:
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. www.rosenlab.net/Movie/P3.mov
+www.rosenlab.net/Movie/P14.mov
diff --git a/general/datasets/DevStriatum_ILM6.2P3RInv_1111/tissue.rtf b/general/datasets/DevStriatum_ILM6.2P3RInv_1111/tissue.rtf
new file mode 100644
index 0000000..e9e6151
--- /dev/null
+++ b/general/datasets/DevStriatum_ILM6.2P3RInv_1111/tissue.rtf
@@ -0,0 +1,534 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Care was taken to assure that samples were comprised of the dorsal striatum, although it is possible that ventral striatum (accumbens) was occasionally included.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected striatal tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues.
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 8 |
+ 5237939012_A |
+ 232 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 1 |
+ 5448576016_C |
+ 234 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 7 |
+ 5384138020_C |
+ 230 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 6 |
+ 5384138053_A |
+ 228 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 6 |
+ 5384138053_D |
+ 270 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 5 |
+ 5452241004_E |
+ 268 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 2 |
+ 5384138018_A |
+ 102 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 1 |
+ 5448576016_A |
+ 101 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 3 |
+ 5384138048_B |
+ 110 |
+
+
+ | 10 |
+ BXD9 |
+ P3 |
+ 2 |
+ 5384138041_A |
+ 280 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 3 |
+ 5384138058_C |
+ 278 |
+
+
+ | 12 |
+ BXD11 |
+ P3 |
+ 2 |
+ 5384138018_B |
+ 121 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 3 |
+ 5384138048_C |
+ 123 |
+
+
+ | 14 |
+ BXD12 |
+ P3 |
+ 5 |
+ 5452241004_A |
+ 127 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 4 |
+ 5452241007_B |
+ 125 |
+
+
+ | 16 |
+ BXD13 |
+ P3 |
+ 8 |
+ 5237939010_D |
+ 181 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 1 |
+ 5448576016_B |
+ 183 |
+
+
+ | 18 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241017_A |
+ 420 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 4 |
+ 5452241023_C |
+ 419 |
+
+
+ | 20 |
+ BXD15 |
+ P3 |
+ 7 |
+ 5384138016_C |
+ 475 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 8 |
+ 5448576010_F |
+ 476 |
+
+
+ | 22 |
+ BXD16 |
+ P3 |
+ 6 |
+ 5384138009_F |
+ 204 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 7 |
+ 5384138020_D |
+ 205 |
+
+
+ | 24 |
+ BXD18 |
+ P3 |
+ 7 |
+ 5384138017_B |
+ 388 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 3 |
+ 5452241008_B |
+ 385 |
+
+
+ | 26 |
+ BXD19 |
+ P3 |
+ 2 |
+ 5384138018_E |
+ 212 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 3 |
+ 5384138048_F |
+ 213 |
+
+
+ | 28 |
+ BXD20 |
+ P3 |
+ 2 |
+ 5384138047_C |
+ 431 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 1 |
+ 5448576029_A |
+ 431 |
+
+
+ | 30 |
+ BXD21 |
+ P3 |
+ 5 |
+ 5452241006_A |
+ 311 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 4 |
+ 5452241022_E |
+ 309 |
+
+
+ | 32 |
+ BXD24a |
+ P3 |
+ 6 |
+ 5384138053_B |
+ 247 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 4 |
+ 5452241022_B |
+ 244 |
+
+
+ | 34 |
+ BXD27 |
+ P3 |
+ 7 |
+ 5384138021_D |
+ 294 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 6 |
+ 5384138053_E |
+ 293 |
+
+
+ | 36 |
+ BXD28 |
+ P3 |
+ 7 |
+ 5384138016_F |
+ 543 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 8 |
+ 5448576011_B |
+ 545 |
+
+
+ | 38 |
+ BXD29 |
+ P3 |
+ 7 |
+ 5384138016_D |
+ 495 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 8 |
+ 5448576011_A |
+ 498 |
+
+
+ | 40 |
+ BXD31 |
+ P3 |
+ 4 |
+ 5452241031_D |
+ 577 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 3 |
+ 5452241034_D |
+ 575 |
+
+
+ | 42 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_E |
+ 402 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 4 |
+ 5452241023_B |
+ 401 |
+
+
+ | 44 |
+ BXD34 |
+ P3 |
+ 2 |
+ 5384138041_D |
+ 348 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 1 |
+ 5448576016_E |
+ 347 |
+
+
+ | 46 |
+ BXD36 |
+ P3 |
+ 2 |
+ 5384138047_B |
+ 417 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 3 |
+ 5452241008_D |
+ 418 |
+
+
+ | 48 |
+ BXD38 |
+ P3 |
+ 8 |
+ 5237939012_E |
+ 321 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 1 |
+ 5448576016_D |
+ 322 |
+
+
+ | 50 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241017_F |
+ 511 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 4 |
+ 5452241031_A |
+ 512 |
+
+
+ | 52 |
+ BXD40 |
+ P3 |
+ 8 |
+ 5448576010_B |
+ 368 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 1 |
+ 5448576016_F |
+ 371 |
+
+
+ | 54 |
+ BXD42 |
+ P3 |
+ 2 |
+ 5384138047_E |
+ 481 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 1 |
+ 5448576029_C |
+ 479 |
+
+
+ | 56 |
+ BXD51 |
+ P3 |
+ 4 |
+ 5452241031_F |
+ 616 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 3 |
+ 5452241034_F |
+ 615 |
+
+
+ | 58 |
+ BXD61 |
+ P3 |
+ 5 |
+ 5452241024_C |
+ 555 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 6 |
+ 5452241035_B |
+ 557 |
+
+
+ | 60 |
+ BXD70 |
+ P3 |
+ 7 |
+ 5384138017_E |
+ 584 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 8 |
+ 5448576011_D |
+ 585 |
+
+
+ | 62 |
+ BXD73 |
+ P3 |
+ 5 |
+ 5452241024_E |
+ 600 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 6 |
+ 5452241035_E |
+ 601 |
+
+
+
+ |
+
+
+
+
+
+
diff --git a/general/datasets/DevStriatum_ILM6_2P14RInv_1110/cases.rtf b/general/datasets/DevStriatum_ILM6_2P14RInv_1110/cases.rtf
deleted file mode 100644
index 74c0f5e..0000000
--- a/general/datasets/DevStriatum_ILM6_2P14RInv_1110/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevStriatum_ILM6_2P14RInv_1110/experiment-design.rtf b/general/datasets/DevStriatum_ILM6_2P14RInv_1110/experiment-design.rtf
deleted file mode 100644
index cfea6b0..0000000
--- a/general/datasets/DevStriatum_ILM6_2P14RInv_1110/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevStriatum_ILM6_2P14RInv_1110/processing.rtf b/general/datasets/DevStriatum_ILM6_2P14RInv_1110/processing.rtf
deleted file mode 100644
index aee498f..0000000
--- a/general/datasets/DevStriatum_ILM6_2P14RInv_1110/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
diff --git a/general/datasets/DevStriatum_ILM6_2P14RInv_1110/summary.rtf b/general/datasets/DevStriatum_ILM6_2P14RInv_1110/summary.rtf
deleted file mode 100644
index 3515533..0000000
--- a/general/datasets/DevStriatum_ILM6_2P14RInv_1110/summary.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-The BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv ** data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
-
-All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv ** data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
-
-As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this data set, xxxx probes have LRS values >46 (LOD >10).
-
-Users of these mouse striatum data set may also find the following complementary resources and papers useful:
-
-A movie of the dissection of the brain by Dr. Glenn Rosen. www.rosenlab.net/Movie/P3.mov
-www.rosenlab.net/Movie/P14.mov
diff --git a/general/datasets/DevStriatum_ILM6_2P14RInv_1110/tissue.rtf b/general/datasets/DevStriatum_ILM6_2P14RInv_1110/tissue.rtf
deleted file mode 100644
index e9e6151..0000000
--- a/general/datasets/DevStriatum_ILM6_2P14RInv_1110/tissue.rtf
+++ /dev/null
@@ -1,534 +0,0 @@
-All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Care was taken to assure that samples were comprised of the dorsal striatum, although it is possible that ventral striatum (accumbens) was occasionally included.
-
-All animals used in this study were either 3 or 14 days of age. A pool of dissected striatal tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues.
-
-
-
-
-
-
-
-
-
-
-
- | Index |
- Strain |
- Age |
- Batch ID |
- Sample ID |
- Tube ID |
-
-
- | 1 |
- BXD1 |
- P3 |
- 8 |
- 5237939012_A |
- 232 |
-
-
- | 2 |
- BXD1 |
- P3 |
- 1 |
- 5448576016_C |
- 234 |
-
-
- | 3 |
- BXD2 |
- P3 |
- 7 |
- 5384138020_C |
- 230 |
-
-
- | 4 |
- BXD2 |
- P3 |
- 6 |
- 5384138053_A |
- 228 |
-
-
- | 5 |
- BXD5 |
- P3 |
- 6 |
- 5384138053_D |
- 270 |
-
-
- | 6 |
- BXD5 |
- P3 |
- 5 |
- 5452241004_E |
- 268 |
-
-
- | 7 |
- BXD6 |
- P3 |
- 2 |
- 5384138018_A |
- 102 |
-
-
- | 8 |
- BXD6 |
- P3 |
- 1 |
- 5448576016_A |
- 101 |
-
-
- | 9 |
- BXD8 |
- P3 |
- 3 |
- 5384138048_B |
- 110 |
-
-
- | 10 |
- BXD9 |
- P3 |
- 2 |
- 5384138041_A |
- 280 |
-
-
- | 11 |
- BXD9 |
- P3 |
- 3 |
- 5384138058_C |
- 278 |
-
-
- | 12 |
- BXD11 |
- P3 |
- 2 |
- 5384138018_B |
- 121 |
-
-
- | 13 |
- BXD11 |
- P3 |
- 3 |
- 5384138048_C |
- 123 |
-
-
- | 14 |
- BXD12 |
- P3 |
- 5 |
- 5452241004_A |
- 127 |
-
-
- | 15 |
- BXD12 |
- P3 |
- 4 |
- 5452241007_B |
- 125 |
-
-
- | 16 |
- BXD13 |
- P3 |
- 8 |
- 5237939010_D |
- 181 |
-
-
- | 17 |
- BXD13 |
- P3 |
- 1 |
- 5448576016_B |
- 183 |
-
-
- | 18 |
- BXD14 |
- P3 |
- 5 |
- 5452241017_A |
- 420 |
-
-
- | 19 |
- BXD14 |
- P3 |
- 4 |
- 5452241023_C |
- 419 |
-
-
- | 20 |
- BXD15 |
- P3 |
- 7 |
- 5384138016_C |
- 475 |
-
-
- | 21 |
- BXD15 |
- P3 |
- 8 |
- 5448576010_F |
- 476 |
-
-
- | 22 |
- BXD16 |
- P3 |
- 6 |
- 5384138009_F |
- 204 |
-
-
- | 23 |
- BXD16 |
- P3 |
- 7 |
- 5384138020_D |
- 205 |
-
-
- | 24 |
- BXD18 |
- P3 |
- 7 |
- 5384138017_B |
- 388 |
-
-
- | 25 |
- BXD18 |
- P3 |
- 3 |
- 5452241008_B |
- 385 |
-
-
- | 26 |
- BXD19 |
- P3 |
- 2 |
- 5384138018_E |
- 212 |
-
-
- | 27 |
- BXD19 |
- P3 |
- 3 |
- 5384138048_F |
- 213 |
-
-
- | 28 |
- BXD20 |
- P3 |
- 2 |
- 5384138047_C |
- 431 |
-
-
- | 29 |
- BXD20 |
- P3 |
- 1 |
- 5448576029_A |
- 431 |
-
-
- | 30 |
- BXD21 |
- P3 |
- 5 |
- 5452241006_A |
- 311 |
-
-
- | 31 |
- BXD21 |
- P3 |
- 4 |
- 5452241022_E |
- 309 |
-
-
- | 32 |
- BXD24a |
- P3 |
- 6 |
- 5384138053_B |
- 247 |
-
-
- | 33 |
- BXD24a |
- P3 |
- 4 |
- 5452241022_B |
- 244 |
-
-
- | 34 |
- BXD27 |
- P3 |
- 7 |
- 5384138021_D |
- 294 |
-
-
- | 35 |
- BXD27 |
- P3 |
- 6 |
- 5384138053_E |
- 293 |
-
-
- | 36 |
- BXD28 |
- P3 |
- 7 |
- 5384138016_F |
- 543 |
-
-
- | 37 |
- BXD28 |
- P3 |
- 8 |
- 5448576011_B |
- 545 |
-
-
- | 38 |
- BXD29 |
- P3 |
- 7 |
- 5384138016_D |
- 495 |
-
-
- | 39 |
- BXD29 |
- P3 |
- 8 |
- 5448576011_A |
- 498 |
-
-
- | 40 |
- BXD31 |
- P3 |
- 4 |
- 5452241031_D |
- 577 |
-
-
- | 41 |
- BXD31 |
- P3 |
- 3 |
- 5452241034_D |
- 575 |
-
-
- | 42 |
- BXD32 |
- P3 |
- 5 |
- 5452241006_E |
- 402 |
-
-
- | 43 |
- BXD32 |
- P3 |
- 4 |
- 5452241023_B |
- 401 |
-
-
- | 44 |
- BXD34 |
- P3 |
- 2 |
- 5384138041_D |
- 348 |
-
-
- | 45 |
- BXD34 |
- P3 |
- 1 |
- 5448576016_E |
- 347 |
-
-
- | 46 |
- BXD36 |
- P3 |
- 2 |
- 5384138047_B |
- 417 |
-
-
- | 47 |
- BXD36 |
- P3 |
- 3 |
- 5452241008_D |
- 418 |
-
-
- | 48 |
- BXD38 |
- P3 |
- 8 |
- 5237939012_E |
- 321 |
-
-
- | 49 |
- BXD38 |
- P3 |
- 1 |
- 5448576016_D |
- 322 |
-
-
- | 50 |
- BXD39 |
- P3 |
- 5 |
- 5452241017_F |
- 511 |
-
-
- | 51 |
- BXD39 |
- P3 |
- 4 |
- 5452241031_A |
- 512 |
-
-
- | 52 |
- BXD40 |
- P3 |
- 8 |
- 5448576010_B |
- 368 |
-
-
- | 53 |
- BXD40 |
- P3 |
- 1 |
- 5448576016_F |
- 371 |
-
-
- | 54 |
- BXD42 |
- P3 |
- 2 |
- 5384138047_E |
- 481 |
-
-
- | 55 |
- BXD42 |
- P3 |
- 1 |
- 5448576029_C |
- 479 |
-
-
- | 56 |
- BXD51 |
- P3 |
- 4 |
- 5452241031_F |
- 616 |
-
-
- | 57 |
- BXD51 |
- P3 |
- 3 |
- 5452241034_F |
- 615 |
-
-
- | 58 |
- BXD61 |
- P3 |
- 5 |
- 5452241024_C |
- 555 |
-
-
- | 59 |
- BXD61 |
- P3 |
- 6 |
- 5452241035_B |
- 557 |
-
-
- | 60 |
- BXD70 |
- P3 |
- 7 |
- 5384138017_E |
- 584 |
-
-
- | 61 |
- BXD70 |
- P3 |
- 8 |
- 5448576011_D |
- 585 |
-
-
- | 62 |
- BXD73 |
- P3 |
- 5 |
- 5452241024_E |
- 600 |
-
-
- | 63 |
- BXD73 |
- P3 |
- 6 |
- 5452241035_E |
- 601 |
-
-
-
- |
-
-
-
-
-
-
diff --git a/general/datasets/DevStriatum_ILM6_2P14RInv_1111/cases.rtf b/general/datasets/DevStriatum_ILM6_2P14RInv_1111/cases.rtf
deleted file mode 100644
index 74c0f5e..0000000
--- a/general/datasets/DevStriatum_ILM6_2P14RInv_1111/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevStriatum_ILM6_2P14RInv_1111/experiment-design.rtf b/general/datasets/DevStriatum_ILM6_2P14RInv_1111/experiment-design.rtf
deleted file mode 100644
index cfea6b0..0000000
--- a/general/datasets/DevStriatum_ILM6_2P14RInv_1111/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevStriatum_ILM6_2P14RInv_1111/processing.rtf b/general/datasets/DevStriatum_ILM6_2P14RInv_1111/processing.rtf
deleted file mode 100644
index aee498f..0000000
--- a/general/datasets/DevStriatum_ILM6_2P14RInv_1111/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
diff --git a/general/datasets/DevStriatum_ILM6_2P14RInv_1111/summary.rtf b/general/datasets/DevStriatum_ILM6_2P14RInv_1111/summary.rtf
deleted file mode 100644
index 3515533..0000000
--- a/general/datasets/DevStriatum_ILM6_2P14RInv_1111/summary.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-The BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv ** data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
-
-All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv ** data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
-
-As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this data set, xxxx probes have LRS values >46 (LOD >10).
-
-Users of these mouse striatum data set may also find the following complementary resources and papers useful:
-
-A movie of the dissection of the brain by Dr. Glenn Rosen. www.rosenlab.net/Movie/P3.mov
-www.rosenlab.net/Movie/P14.mov
diff --git a/general/datasets/DevStriatum_ILM6_2P14RInv_1111/tissue.rtf b/general/datasets/DevStriatum_ILM6_2P14RInv_1111/tissue.rtf
deleted file mode 100644
index e9e6151..0000000
--- a/general/datasets/DevStriatum_ILM6_2P14RInv_1111/tissue.rtf
+++ /dev/null
@@ -1,534 +0,0 @@
-All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Care was taken to assure that samples were comprised of the dorsal striatum, although it is possible that ventral striatum (accumbens) was occasionally included.
-
-All animals used in this study were either 3 or 14 days of age. A pool of dissected striatal tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues.
-
-
-
-
-
-
-
-
-
-
-
- | Index |
- Strain |
- Age |
- Batch ID |
- Sample ID |
- Tube ID |
-
-
- | 1 |
- BXD1 |
- P3 |
- 8 |
- 5237939012_A |
- 232 |
-
-
- | 2 |
- BXD1 |
- P3 |
- 1 |
- 5448576016_C |
- 234 |
-
-
- | 3 |
- BXD2 |
- P3 |
- 7 |
- 5384138020_C |
- 230 |
-
-
- | 4 |
- BXD2 |
- P3 |
- 6 |
- 5384138053_A |
- 228 |
-
-
- | 5 |
- BXD5 |
- P3 |
- 6 |
- 5384138053_D |
- 270 |
-
-
- | 6 |
- BXD5 |
- P3 |
- 5 |
- 5452241004_E |
- 268 |
-
-
- | 7 |
- BXD6 |
- P3 |
- 2 |
- 5384138018_A |
- 102 |
-
-
- | 8 |
- BXD6 |
- P3 |
- 1 |
- 5448576016_A |
- 101 |
-
-
- | 9 |
- BXD8 |
- P3 |
- 3 |
- 5384138048_B |
- 110 |
-
-
- | 10 |
- BXD9 |
- P3 |
- 2 |
- 5384138041_A |
- 280 |
-
-
- | 11 |
- BXD9 |
- P3 |
- 3 |
- 5384138058_C |
- 278 |
-
-
- | 12 |
- BXD11 |
- P3 |
- 2 |
- 5384138018_B |
- 121 |
-
-
- | 13 |
- BXD11 |
- P3 |
- 3 |
- 5384138048_C |
- 123 |
-
-
- | 14 |
- BXD12 |
- P3 |
- 5 |
- 5452241004_A |
- 127 |
-
-
- | 15 |
- BXD12 |
- P3 |
- 4 |
- 5452241007_B |
- 125 |
-
-
- | 16 |
- BXD13 |
- P3 |
- 8 |
- 5237939010_D |
- 181 |
-
-
- | 17 |
- BXD13 |
- P3 |
- 1 |
- 5448576016_B |
- 183 |
-
-
- | 18 |
- BXD14 |
- P3 |
- 5 |
- 5452241017_A |
- 420 |
-
-
- | 19 |
- BXD14 |
- P3 |
- 4 |
- 5452241023_C |
- 419 |
-
-
- | 20 |
- BXD15 |
- P3 |
- 7 |
- 5384138016_C |
- 475 |
-
-
- | 21 |
- BXD15 |
- P3 |
- 8 |
- 5448576010_F |
- 476 |
-
-
- | 22 |
- BXD16 |
- P3 |
- 6 |
- 5384138009_F |
- 204 |
-
-
- | 23 |
- BXD16 |
- P3 |
- 7 |
- 5384138020_D |
- 205 |
-
-
- | 24 |
- BXD18 |
- P3 |
- 7 |
- 5384138017_B |
- 388 |
-
-
- | 25 |
- BXD18 |
- P3 |
- 3 |
- 5452241008_B |
- 385 |
-
-
- | 26 |
- BXD19 |
- P3 |
- 2 |
- 5384138018_E |
- 212 |
-
-
- | 27 |
- BXD19 |
- P3 |
- 3 |
- 5384138048_F |
- 213 |
-
-
- | 28 |
- BXD20 |
- P3 |
- 2 |
- 5384138047_C |
- 431 |
-
-
- | 29 |
- BXD20 |
- P3 |
- 1 |
- 5448576029_A |
- 431 |
-
-
- | 30 |
- BXD21 |
- P3 |
- 5 |
- 5452241006_A |
- 311 |
-
-
- | 31 |
- BXD21 |
- P3 |
- 4 |
- 5452241022_E |
- 309 |
-
-
- | 32 |
- BXD24a |
- P3 |
- 6 |
- 5384138053_B |
- 247 |
-
-
- | 33 |
- BXD24a |
- P3 |
- 4 |
- 5452241022_B |
- 244 |
-
-
- | 34 |
- BXD27 |
- P3 |
- 7 |
- 5384138021_D |
- 294 |
-
-
- | 35 |
- BXD27 |
- P3 |
- 6 |
- 5384138053_E |
- 293 |
-
-
- | 36 |
- BXD28 |
- P3 |
- 7 |
- 5384138016_F |
- 543 |
-
-
- | 37 |
- BXD28 |
- P3 |
- 8 |
- 5448576011_B |
- 545 |
-
-
- | 38 |
- BXD29 |
- P3 |
- 7 |
- 5384138016_D |
- 495 |
-
-
- | 39 |
- BXD29 |
- P3 |
- 8 |
- 5448576011_A |
- 498 |
-
-
- | 40 |
- BXD31 |
- P3 |
- 4 |
- 5452241031_D |
- 577 |
-
-
- | 41 |
- BXD31 |
- P3 |
- 3 |
- 5452241034_D |
- 575 |
-
-
- | 42 |
- BXD32 |
- P3 |
- 5 |
- 5452241006_E |
- 402 |
-
-
- | 43 |
- BXD32 |
- P3 |
- 4 |
- 5452241023_B |
- 401 |
-
-
- | 44 |
- BXD34 |
- P3 |
- 2 |
- 5384138041_D |
- 348 |
-
-
- | 45 |
- BXD34 |
- P3 |
- 1 |
- 5448576016_E |
- 347 |
-
-
- | 46 |
- BXD36 |
- P3 |
- 2 |
- 5384138047_B |
- 417 |
-
-
- | 47 |
- BXD36 |
- P3 |
- 3 |
- 5452241008_D |
- 418 |
-
-
- | 48 |
- BXD38 |
- P3 |
- 8 |
- 5237939012_E |
- 321 |
-
-
- | 49 |
- BXD38 |
- P3 |
- 1 |
- 5448576016_D |
- 322 |
-
-
- | 50 |
- BXD39 |
- P3 |
- 5 |
- 5452241017_F |
- 511 |
-
-
- | 51 |
- BXD39 |
- P3 |
- 4 |
- 5452241031_A |
- 512 |
-
-
- | 52 |
- BXD40 |
- P3 |
- 8 |
- 5448576010_B |
- 368 |
-
-
- | 53 |
- BXD40 |
- P3 |
- 1 |
- 5448576016_F |
- 371 |
-
-
- | 54 |
- BXD42 |
- P3 |
- 2 |
- 5384138047_E |
- 481 |
-
-
- | 55 |
- BXD42 |
- P3 |
- 1 |
- 5448576029_C |
- 479 |
-
-
- | 56 |
- BXD51 |
- P3 |
- 4 |
- 5452241031_F |
- 616 |
-
-
- | 57 |
- BXD51 |
- P3 |
- 3 |
- 5452241034_F |
- 615 |
-
-
- | 58 |
- BXD61 |
- P3 |
- 5 |
- 5452241024_C |
- 555 |
-
-
- | 59 |
- BXD61 |
- P3 |
- 6 |
- 5452241035_B |
- 557 |
-
-
- | 60 |
- BXD70 |
- P3 |
- 7 |
- 5384138017_E |
- 584 |
-
-
- | 61 |
- BXD70 |
- P3 |
- 8 |
- 5448576011_D |
- 585 |
-
-
- | 62 |
- BXD73 |
- P3 |
- 5 |
- 5452241024_E |
- 600 |
-
-
- | 63 |
- BXD73 |
- P3 |
- 6 |
- 5452241035_E |
- 601 |
-
-
-
- |
-
-
-
-
-
-
diff --git a/general/datasets/DevStriatum_ILM6_2P3RInv_1110/cases.rtf b/general/datasets/DevStriatum_ILM6_2P3RInv_1110/cases.rtf
deleted file mode 100644
index 74c0f5e..0000000
--- a/general/datasets/DevStriatum_ILM6_2P3RInv_1110/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevStriatum_ILM6_2P3RInv_1110/experiment-design.rtf b/general/datasets/DevStriatum_ILM6_2P3RInv_1110/experiment-design.rtf
deleted file mode 100644
index cfea6b0..0000000
--- a/general/datasets/DevStriatum_ILM6_2P3RInv_1110/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevStriatum_ILM6_2P3RInv_1110/processing.rtf b/general/datasets/DevStriatum_ILM6_2P3RInv_1110/processing.rtf
deleted file mode 100644
index aee498f..0000000
--- a/general/datasets/DevStriatum_ILM6_2P3RInv_1110/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
diff --git a/general/datasets/DevStriatum_ILM6_2P3RInv_1110/summary.rtf b/general/datasets/DevStriatum_ILM6_2P3RInv_1110/summary.rtf
deleted file mode 100644
index 3515533..0000000
--- a/general/datasets/DevStriatum_ILM6_2P3RInv_1110/summary.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-The BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv ** data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
-
-All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv ** data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
-
-As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this data set, xxxx probes have LRS values >46 (LOD >10).
-
-Users of these mouse striatum data set may also find the following complementary resources and papers useful:
-
-A movie of the dissection of the brain by Dr. Glenn Rosen. www.rosenlab.net/Movie/P3.mov
-www.rosenlab.net/Movie/P14.mov
diff --git a/general/datasets/DevStriatum_ILM6_2P3RInv_1110/tissue.rtf b/general/datasets/DevStriatum_ILM6_2P3RInv_1110/tissue.rtf
deleted file mode 100644
index e9e6151..0000000
--- a/general/datasets/DevStriatum_ILM6_2P3RInv_1110/tissue.rtf
+++ /dev/null
@@ -1,534 +0,0 @@
-All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Care was taken to assure that samples were comprised of the dorsal striatum, although it is possible that ventral striatum (accumbens) was occasionally included.
-
-All animals used in this study were either 3 or 14 days of age. A pool of dissected striatal tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues.
-
-
-
-
-
-
-
-
-
-
-
- | Index |
- Strain |
- Age |
- Batch ID |
- Sample ID |
- Tube ID |
-
-
- | 1 |
- BXD1 |
- P3 |
- 8 |
- 5237939012_A |
- 232 |
-
-
- | 2 |
- BXD1 |
- P3 |
- 1 |
- 5448576016_C |
- 234 |
-
-
- | 3 |
- BXD2 |
- P3 |
- 7 |
- 5384138020_C |
- 230 |
-
-
- | 4 |
- BXD2 |
- P3 |
- 6 |
- 5384138053_A |
- 228 |
-
-
- | 5 |
- BXD5 |
- P3 |
- 6 |
- 5384138053_D |
- 270 |
-
-
- | 6 |
- BXD5 |
- P3 |
- 5 |
- 5452241004_E |
- 268 |
-
-
- | 7 |
- BXD6 |
- P3 |
- 2 |
- 5384138018_A |
- 102 |
-
-
- | 8 |
- BXD6 |
- P3 |
- 1 |
- 5448576016_A |
- 101 |
-
-
- | 9 |
- BXD8 |
- P3 |
- 3 |
- 5384138048_B |
- 110 |
-
-
- | 10 |
- BXD9 |
- P3 |
- 2 |
- 5384138041_A |
- 280 |
-
-
- | 11 |
- BXD9 |
- P3 |
- 3 |
- 5384138058_C |
- 278 |
-
-
- | 12 |
- BXD11 |
- P3 |
- 2 |
- 5384138018_B |
- 121 |
-
-
- | 13 |
- BXD11 |
- P3 |
- 3 |
- 5384138048_C |
- 123 |
-
-
- | 14 |
- BXD12 |
- P3 |
- 5 |
- 5452241004_A |
- 127 |
-
-
- | 15 |
- BXD12 |
- P3 |
- 4 |
- 5452241007_B |
- 125 |
-
-
- | 16 |
- BXD13 |
- P3 |
- 8 |
- 5237939010_D |
- 181 |
-
-
- | 17 |
- BXD13 |
- P3 |
- 1 |
- 5448576016_B |
- 183 |
-
-
- | 18 |
- BXD14 |
- P3 |
- 5 |
- 5452241017_A |
- 420 |
-
-
- | 19 |
- BXD14 |
- P3 |
- 4 |
- 5452241023_C |
- 419 |
-
-
- | 20 |
- BXD15 |
- P3 |
- 7 |
- 5384138016_C |
- 475 |
-
-
- | 21 |
- BXD15 |
- P3 |
- 8 |
- 5448576010_F |
- 476 |
-
-
- | 22 |
- BXD16 |
- P3 |
- 6 |
- 5384138009_F |
- 204 |
-
-
- | 23 |
- BXD16 |
- P3 |
- 7 |
- 5384138020_D |
- 205 |
-
-
- | 24 |
- BXD18 |
- P3 |
- 7 |
- 5384138017_B |
- 388 |
-
-
- | 25 |
- BXD18 |
- P3 |
- 3 |
- 5452241008_B |
- 385 |
-
-
- | 26 |
- BXD19 |
- P3 |
- 2 |
- 5384138018_E |
- 212 |
-
-
- | 27 |
- BXD19 |
- P3 |
- 3 |
- 5384138048_F |
- 213 |
-
-
- | 28 |
- BXD20 |
- P3 |
- 2 |
- 5384138047_C |
- 431 |
-
-
- | 29 |
- BXD20 |
- P3 |
- 1 |
- 5448576029_A |
- 431 |
-
-
- | 30 |
- BXD21 |
- P3 |
- 5 |
- 5452241006_A |
- 311 |
-
-
- | 31 |
- BXD21 |
- P3 |
- 4 |
- 5452241022_E |
- 309 |
-
-
- | 32 |
- BXD24a |
- P3 |
- 6 |
- 5384138053_B |
- 247 |
-
-
- | 33 |
- BXD24a |
- P3 |
- 4 |
- 5452241022_B |
- 244 |
-
-
- | 34 |
- BXD27 |
- P3 |
- 7 |
- 5384138021_D |
- 294 |
-
-
- | 35 |
- BXD27 |
- P3 |
- 6 |
- 5384138053_E |
- 293 |
-
-
- | 36 |
- BXD28 |
- P3 |
- 7 |
- 5384138016_F |
- 543 |
-
-
- | 37 |
- BXD28 |
- P3 |
- 8 |
- 5448576011_B |
- 545 |
-
-
- | 38 |
- BXD29 |
- P3 |
- 7 |
- 5384138016_D |
- 495 |
-
-
- | 39 |
- BXD29 |
- P3 |
- 8 |
- 5448576011_A |
- 498 |
-
-
- | 40 |
- BXD31 |
- P3 |
- 4 |
- 5452241031_D |
- 577 |
-
-
- | 41 |
- BXD31 |
- P3 |
- 3 |
- 5452241034_D |
- 575 |
-
-
- | 42 |
- BXD32 |
- P3 |
- 5 |
- 5452241006_E |
- 402 |
-
-
- | 43 |
- BXD32 |
- P3 |
- 4 |
- 5452241023_B |
- 401 |
-
-
- | 44 |
- BXD34 |
- P3 |
- 2 |
- 5384138041_D |
- 348 |
-
-
- | 45 |
- BXD34 |
- P3 |
- 1 |
- 5448576016_E |
- 347 |
-
-
- | 46 |
- BXD36 |
- P3 |
- 2 |
- 5384138047_B |
- 417 |
-
-
- | 47 |
- BXD36 |
- P3 |
- 3 |
- 5452241008_D |
- 418 |
-
-
- | 48 |
- BXD38 |
- P3 |
- 8 |
- 5237939012_E |
- 321 |
-
-
- | 49 |
- BXD38 |
- P3 |
- 1 |
- 5448576016_D |
- 322 |
-
-
- | 50 |
- BXD39 |
- P3 |
- 5 |
- 5452241017_F |
- 511 |
-
-
- | 51 |
- BXD39 |
- P3 |
- 4 |
- 5452241031_A |
- 512 |
-
-
- | 52 |
- BXD40 |
- P3 |
- 8 |
- 5448576010_B |
- 368 |
-
-
- | 53 |
- BXD40 |
- P3 |
- 1 |
- 5448576016_F |
- 371 |
-
-
- | 54 |
- BXD42 |
- P3 |
- 2 |
- 5384138047_E |
- 481 |
-
-
- | 55 |
- BXD42 |
- P3 |
- 1 |
- 5448576029_C |
- 479 |
-
-
- | 56 |
- BXD51 |
- P3 |
- 4 |
- 5452241031_F |
- 616 |
-
-
- | 57 |
- BXD51 |
- P3 |
- 3 |
- 5452241034_F |
- 615 |
-
-
- | 58 |
- BXD61 |
- P3 |
- 5 |
- 5452241024_C |
- 555 |
-
-
- | 59 |
- BXD61 |
- P3 |
- 6 |
- 5452241035_B |
- 557 |
-
-
- | 60 |
- BXD70 |
- P3 |
- 7 |
- 5384138017_E |
- 584 |
-
-
- | 61 |
- BXD70 |
- P3 |
- 8 |
- 5448576011_D |
- 585 |
-
-
- | 62 |
- BXD73 |
- P3 |
- 5 |
- 5452241024_E |
- 600 |
-
-
- | 63 |
- BXD73 |
- P3 |
- 6 |
- 5452241035_E |
- 601 |
-
-
-
- |
-
-
-
-
-
-
diff --git a/general/datasets/DevStriatum_ILM6_2P3RInv_1111/cases.rtf b/general/datasets/DevStriatum_ILM6_2P3RInv_1111/cases.rtf
deleted file mode 100644
index 74c0f5e..0000000
--- a/general/datasets/DevStriatum_ILM6_2P3RInv_1111/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/DevStriatum_ILM6_2P3RInv_1111/experiment-design.rtf b/general/datasets/DevStriatum_ILM6_2P3RInv_1111/experiment-design.rtf
deleted file mode 100644
index cfea6b0..0000000
--- a/general/datasets/DevStriatum_ILM6_2P3RInv_1111/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/DevStriatum_ILM6_2P3RInv_1111/processing.rtf b/general/datasets/DevStriatum_ILM6_2P3RInv_1111/processing.rtf
deleted file mode 100644
index aee498f..0000000
--- a/general/datasets/DevStriatum_ILM6_2P3RInv_1111/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
diff --git a/general/datasets/DevStriatum_ILM6_2P3RInv_1111/summary.rtf b/general/datasets/DevStriatum_ILM6_2P3RInv_1111/summary.rtf
deleted file mode 100644
index 3515533..0000000
--- a/general/datasets/DevStriatum_ILM6_2P3RInv_1111/summary.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-The BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv ** data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
-
-All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv ** data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
-
-As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this data set, xxxx probes have LRS values >46 (LOD >10).
-
-Users of these mouse striatum data set may also find the following complementary resources and papers useful:
-
-A movie of the dissection of the brain by Dr. Glenn Rosen. www.rosenlab.net/Movie/P3.mov
-www.rosenlab.net/Movie/P14.mov
diff --git a/general/datasets/DevStriatum_ILM6_2P3RInv_1111/tissue.rtf b/general/datasets/DevStriatum_ILM6_2P3RInv_1111/tissue.rtf
deleted file mode 100644
index e9e6151..0000000
--- a/general/datasets/DevStriatum_ILM6_2P3RInv_1111/tissue.rtf
+++ /dev/null
@@ -1,534 +0,0 @@
-All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Care was taken to assure that samples were comprised of the dorsal striatum, although it is possible that ventral striatum (accumbens) was occasionally included.
-
-All animals used in this study were either 3 or 14 days of age. A pool of dissected striatal tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues.
-
-
-
-
-
-
-
-
-
-
-
- | Index |
- Strain |
- Age |
- Batch ID |
- Sample ID |
- Tube ID |
-
-
- | 1 |
- BXD1 |
- P3 |
- 8 |
- 5237939012_A |
- 232 |
-
-
- | 2 |
- BXD1 |
- P3 |
- 1 |
- 5448576016_C |
- 234 |
-
-
- | 3 |
- BXD2 |
- P3 |
- 7 |
- 5384138020_C |
- 230 |
-
-
- | 4 |
- BXD2 |
- P3 |
- 6 |
- 5384138053_A |
- 228 |
-
-
- | 5 |
- BXD5 |
- P3 |
- 6 |
- 5384138053_D |
- 270 |
-
-
- | 6 |
- BXD5 |
- P3 |
- 5 |
- 5452241004_E |
- 268 |
-
-
- | 7 |
- BXD6 |
- P3 |
- 2 |
- 5384138018_A |
- 102 |
-
-
- | 8 |
- BXD6 |
- P3 |
- 1 |
- 5448576016_A |
- 101 |
-
-
- | 9 |
- BXD8 |
- P3 |
- 3 |
- 5384138048_B |
- 110 |
-
-
- | 10 |
- BXD9 |
- P3 |
- 2 |
- 5384138041_A |
- 280 |
-
-
- | 11 |
- BXD9 |
- P3 |
- 3 |
- 5384138058_C |
- 278 |
-
-
- | 12 |
- BXD11 |
- P3 |
- 2 |
- 5384138018_B |
- 121 |
-
-
- | 13 |
- BXD11 |
- P3 |
- 3 |
- 5384138048_C |
- 123 |
-
-
- | 14 |
- BXD12 |
- P3 |
- 5 |
- 5452241004_A |
- 127 |
-
-
- | 15 |
- BXD12 |
- P3 |
- 4 |
- 5452241007_B |
- 125 |
-
-
- | 16 |
- BXD13 |
- P3 |
- 8 |
- 5237939010_D |
- 181 |
-
-
- | 17 |
- BXD13 |
- P3 |
- 1 |
- 5448576016_B |
- 183 |
-
-
- | 18 |
- BXD14 |
- P3 |
- 5 |
- 5452241017_A |
- 420 |
-
-
- | 19 |
- BXD14 |
- P3 |
- 4 |
- 5452241023_C |
- 419 |
-
-
- | 20 |
- BXD15 |
- P3 |
- 7 |
- 5384138016_C |
- 475 |
-
-
- | 21 |
- BXD15 |
- P3 |
- 8 |
- 5448576010_F |
- 476 |
-
-
- | 22 |
- BXD16 |
- P3 |
- 6 |
- 5384138009_F |
- 204 |
-
-
- | 23 |
- BXD16 |
- P3 |
- 7 |
- 5384138020_D |
- 205 |
-
-
- | 24 |
- BXD18 |
- P3 |
- 7 |
- 5384138017_B |
- 388 |
-
-
- | 25 |
- BXD18 |
- P3 |
- 3 |
- 5452241008_B |
- 385 |
-
-
- | 26 |
- BXD19 |
- P3 |
- 2 |
- 5384138018_E |
- 212 |
-
-
- | 27 |
- BXD19 |
- P3 |
- 3 |
- 5384138048_F |
- 213 |
-
-
- | 28 |
- BXD20 |
- P3 |
- 2 |
- 5384138047_C |
- 431 |
-
-
- | 29 |
- BXD20 |
- P3 |
- 1 |
- 5448576029_A |
- 431 |
-
-
- | 30 |
- BXD21 |
- P3 |
- 5 |
- 5452241006_A |
- 311 |
-
-
- | 31 |
- BXD21 |
- P3 |
- 4 |
- 5452241022_E |
- 309 |
-
-
- | 32 |
- BXD24a |
- P3 |
- 6 |
- 5384138053_B |
- 247 |
-
-
- | 33 |
- BXD24a |
- P3 |
- 4 |
- 5452241022_B |
- 244 |
-
-
- | 34 |
- BXD27 |
- P3 |
- 7 |
- 5384138021_D |
- 294 |
-
-
- | 35 |
- BXD27 |
- P3 |
- 6 |
- 5384138053_E |
- 293 |
-
-
- | 36 |
- BXD28 |
- P3 |
- 7 |
- 5384138016_F |
- 543 |
-
-
- | 37 |
- BXD28 |
- P3 |
- 8 |
- 5448576011_B |
- 545 |
-
-
- | 38 |
- BXD29 |
- P3 |
- 7 |
- 5384138016_D |
- 495 |
-
-
- | 39 |
- BXD29 |
- P3 |
- 8 |
- 5448576011_A |
- 498 |
-
-
- | 40 |
- BXD31 |
- P3 |
- 4 |
- 5452241031_D |
- 577 |
-
-
- | 41 |
- BXD31 |
- P3 |
- 3 |
- 5452241034_D |
- 575 |
-
-
- | 42 |
- BXD32 |
- P3 |
- 5 |
- 5452241006_E |
- 402 |
-
-
- | 43 |
- BXD32 |
- P3 |
- 4 |
- 5452241023_B |
- 401 |
-
-
- | 44 |
- BXD34 |
- P3 |
- 2 |
- 5384138041_D |
- 348 |
-
-
- | 45 |
- BXD34 |
- P3 |
- 1 |
- 5448576016_E |
- 347 |
-
-
- | 46 |
- BXD36 |
- P3 |
- 2 |
- 5384138047_B |
- 417 |
-
-
- | 47 |
- BXD36 |
- P3 |
- 3 |
- 5452241008_D |
- 418 |
-
-
- | 48 |
- BXD38 |
- P3 |
- 8 |
- 5237939012_E |
- 321 |
-
-
- | 49 |
- BXD38 |
- P3 |
- 1 |
- 5448576016_D |
- 322 |
-
-
- | 50 |
- BXD39 |
- P3 |
- 5 |
- 5452241017_F |
- 511 |
-
-
- | 51 |
- BXD39 |
- P3 |
- 4 |
- 5452241031_A |
- 512 |
-
-
- | 52 |
- BXD40 |
- P3 |
- 8 |
- 5448576010_B |
- 368 |
-
-
- | 53 |
- BXD40 |
- P3 |
- 1 |
- 5448576016_F |
- 371 |
-
-
- | 54 |
- BXD42 |
- P3 |
- 2 |
- 5384138047_E |
- 481 |
-
-
- | 55 |
- BXD42 |
- P3 |
- 1 |
- 5448576029_C |
- 479 |
-
-
- | 56 |
- BXD51 |
- P3 |
- 4 |
- 5452241031_F |
- 616 |
-
-
- | 57 |
- BXD51 |
- P3 |
- 3 |
- 5452241034_F |
- 615 |
-
-
- | 58 |
- BXD61 |
- P3 |
- 5 |
- 5452241024_C |
- 555 |
-
-
- | 59 |
- BXD61 |
- P3 |
- 6 |
- 5452241035_B |
- 557 |
-
-
- | 60 |
- BXD70 |
- P3 |
- 7 |
- 5384138017_E |
- 584 |
-
-
- | 61 |
- BXD70 |
- P3 |
- 8 |
- 5448576011_D |
- 585 |
-
-
- | 62 |
- BXD73 |
- P3 |
- 5 |
- 5452241024_E |
- 600 |
-
-
- | 63 |
- BXD73 |
- P3 |
- 6 |
- 5452241035_E |
- 601 |
-
-
-
- |
-
-
-
-
-
-
diff --git a/general/datasets/Devneocortex_ilm6_2p14rinv_1110/cases.rtf b/general/datasets/Devneocortex_ilm6_2p14rinv_1110/cases.rtf
new file mode 100644
index 0000000..70216c8
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p14rinv_1110/cases.rtf
@@ -0,0 +1,3 @@
+About the strains used to generate this set of data
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/Devneocortex_ilm6_2p14rinv_1110/experiment-design.rtf b/general/datasets/Devneocortex_ilm6_2p14rinv_1110/experiment-design.rtf
new file mode 100644
index 0000000..616db01
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p14rinv_1110/experiment-design.rtf
@@ -0,0 +1,3 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Devneocortex_ilm6_2p14rinv_1110/summary.rtf b/general/datasets/Devneocortex_ilm6_2p14rinv_1110/summary.rtf
new file mode 100644
index 0000000..70d7451
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p14rinv_1110/summary.rtf
@@ -0,0 +1,16 @@
+Data generated by Dr. Glenn D. Rosen and colleagues
+
+The Neocortex Developmental data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+Some of these data were used in
+Gaglani SM, Lu L, Williams RW, Rosen GD (2009) The genetic control of neocortex volume and covariation with patterns of gene expression in mice. BMC Neuroscience 10:44 Full Text HTML Version, Full Text PDF Version
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the Striatal Developmental Transcriptome data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Developmental data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse neocortex data may also find the following complementary resources and papers useful:
+
+Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. ABOUT THE NEOCORTEX
diff --git a/general/datasets/Devneocortex_ilm6_2p14rinv_1110/tissue.rtf b/general/datasets/Devneocortex_ilm6_2p14rinv_1110/tissue.rtf
new file mode 100644
index 0000000..51f6e74
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p14rinv_1110/tissue.rtf
@@ -0,0 +1,536 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected neocortical tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn D. Rosen and colleagues.
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 2 |
+ 5384138018_F |
+ 236 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 3 |
+ 5384138058_A |
+ 239 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 2 |
+ 5384138018_C |
+ 168 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 1 |
+ 5448576044_F |
+ 167 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 7 |
+ 5384138020_A |
+ 273 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 4 |
+ 5452241022_C |
+ 267 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 3 |
+ 5384138048_A |
+ 107 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 4 |
+ 5452241007_A |
+ 108 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 6 |
+ 5384138009_A |
+ 113 |
+
+
+ | 10 |
+ BXD8 |
+ P3 |
+ 7 |
+ 5384138021_C |
+ 115 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 5 |
+ 5452241004_F |
+ 289 |
+
+
+ | 12 |
+ BXD9 |
+ P3 |
+ 4 |
+ 5452241022_D |
+ 288 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 8 |
+ 5237939010_A |
+ 117 |
+
+
+ | 14 |
+ BXD11 |
+ P3 |
+ 1 |
+ 5448576044_D |
+ 120 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 6 |
+ 5384138009_B |
+ 130 |
+
+
+ | 16 |
+ BXD12 |
+ P3 |
+ 7 |
+ 5384138021_B |
+ 132 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 7 |
+ 5384138020_F |
+ 161 |
+
+
+ | 18 |
+ BXD13 |
+ P3 |
+ 5 |
+ 5452241004_C |
+ 164 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241004_B |
+ 158 |
+
+
+ | 20 |
+ BXD14 |
+ P3 |
+ 6 |
+ 5452241033_D |
+ 424 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 3 |
+ 5452241008_C |
+ 437 |
+
+
+ | 22 |
+ BXD15 |
+ P3 |
+ 4 |
+ 5452241023_D |
+ 438 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 3 |
+ 5384138048_D |
+ 170 |
+
+
+ | 24 |
+ BXD16 |
+ P3 |
+ 4 |
+ 5452241007_D |
+ 172 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 8 |
+ 5448576010_A |
+ 390 |
+
+
+ | 26 |
+ BXD18 |
+ P3 |
+ 1 |
+ 5448576045_E |
+ 392 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 8 |
+ 5237939010_E |
+ 210 |
+
+
+ | 28 |
+ BXD19 |
+ P3 |
+ 1 |
+ 5448576045_A |
+ 211 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 5 |
+ 5452241017_B |
+ 439 |
+
+
+ | 30 |
+ BXD20 |
+ P3 |
+ 6 |
+ 5452241033_E |
+ 441 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 7 |
+ 5384138021_F |
+ 341 |
+
+
+ | 32 |
+ BXD21 |
+ P3 |
+ 6 |
+ 5384138053_F |
+ 315 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 8 |
+ 5237939012_B |
+ 251 |
+
+
+ | 34 |
+ BXD24a |
+ P3 |
+ 7 |
+ 5384138020_B |
+ 250 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 8 |
+ 5237939012_D |
+ 298 |
+
+
+ | 36 |
+ BXD27 |
+ P3 |
+ 1 |
+ 5448576045_C |
+ 300 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 2 |
+ 5384138049_B |
+ 550 |
+
+
+ | 38 |
+ BXD28 |
+ P3 |
+ 1 |
+ 5448576029_F |
+ 548 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 2 |
+ 5384138047_F |
+ 502 |
+
+
+ | 40 |
+ BXD29 |
+ P3 |
+ 1 |
+ 5448576029_D |
+ 501 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 5 |
+ 5452241024_D |
+ 579 |
+
+
+ | 42 |
+ BXD31 |
+ P3 |
+ 6 |
+ 5452241035_D |
+ 582 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_F |
+ 407 |
+
+
+ | 44 |
+ BXD32 |
+ P3 |
+ 6 |
+ 5452241033_C |
+ 408 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 8 |
+ 5237939012_F |
+ 345 |
+
+
+ | 46 |
+ BXD34 |
+ P3 |
+ 4 |
+ 5452241022_F |
+ 355 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 7 |
+ 5384138016_A |
+ 429 |
+
+
+ | 48 |
+ BXD36 |
+ P3 |
+ 8 |
+ 5448576010_D |
+ 430 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 2 |
+ 5384138041_F |
+ 327 |
+
+
+ | 50 |
+ BXD38 |
+ P3 |
+ 3 |
+ 5384138058_E |
+ 328 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 7 |
+ 5384138016_E |
+ 515 |
+
+
+ | 52 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241024_A |
+ 518 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 2 |
+ 5384138041_C |
+ 373 |
+
+
+ | 54 |
+ BXD40 |
+ P3 |
+ 3 |
+ 5452241008_A |
+ 375 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 3 |
+ 5452241008_E |
+ 485 |
+
+
+ | 56 |
+ BXD42 |
+ P3 |
+ 4 |
+ 5452241023_F |
+ 486 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 5 |
+ 5452241024_F |
+ 621 |
+
+
+ | 58 |
+ BXD51 |
+ P3 |
+ 6 |
+ 5452241035_F |
+ 622 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 4 |
+ 5452241031_C |
+ 554 |
+
+
+ | 60 |
+ BXD61 |
+ P3 |
+ 3 |
+ 5452241034_A |
+ 552 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 2 |
+ 5384138049_D |
+ 590 |
+
+
+ | 62 |
+ BXD70 |
+ P3 |
+ 1 |
+ 5448576044_B |
+ 589 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 2 |
+ 5384138049_E |
+ 603 |
+
+
+ | 64 |
+ BXD73 |
+ P3 |
+ 8 |
+ 5448576011_E |
+ 605 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Devneocortex_ilm6_2p14rinv_1111/cases.rtf b/general/datasets/Devneocortex_ilm6_2p14rinv_1111/cases.rtf
new file mode 100644
index 0000000..70216c8
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p14rinv_1111/cases.rtf
@@ -0,0 +1,3 @@
+About the strains used to generate this set of data
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/Devneocortex_ilm6_2p14rinv_1111/experiment-design.rtf b/general/datasets/Devneocortex_ilm6_2p14rinv_1111/experiment-design.rtf
new file mode 100644
index 0000000..616db01
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p14rinv_1111/experiment-design.rtf
@@ -0,0 +1,3 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Devneocortex_ilm6_2p14rinv_1111/summary.rtf b/general/datasets/Devneocortex_ilm6_2p14rinv_1111/summary.rtf
new file mode 100644
index 0000000..70d7451
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p14rinv_1111/summary.rtf
@@ -0,0 +1,16 @@
+Data generated by Dr. Glenn D. Rosen and colleagues
+
+The Neocortex Developmental data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+Some of these data were used in
+Gaglani SM, Lu L, Williams RW, Rosen GD (2009) The genetic control of neocortex volume and covariation with patterns of gene expression in mice. BMC Neuroscience 10:44 Full Text HTML Version, Full Text PDF Version
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the Striatal Developmental Transcriptome data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Developmental data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse neocortex data may also find the following complementary resources and papers useful:
+
+Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. ABOUT THE NEOCORTEX
diff --git a/general/datasets/Devneocortex_ilm6_2p14rinv_1111/tissue.rtf b/general/datasets/Devneocortex_ilm6_2p14rinv_1111/tissue.rtf
new file mode 100644
index 0000000..51f6e74
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p14rinv_1111/tissue.rtf
@@ -0,0 +1,536 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected neocortical tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn D. Rosen and colleagues.
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 2 |
+ 5384138018_F |
+ 236 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 3 |
+ 5384138058_A |
+ 239 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 2 |
+ 5384138018_C |
+ 168 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 1 |
+ 5448576044_F |
+ 167 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 7 |
+ 5384138020_A |
+ 273 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 4 |
+ 5452241022_C |
+ 267 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 3 |
+ 5384138048_A |
+ 107 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 4 |
+ 5452241007_A |
+ 108 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 6 |
+ 5384138009_A |
+ 113 |
+
+
+ | 10 |
+ BXD8 |
+ P3 |
+ 7 |
+ 5384138021_C |
+ 115 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 5 |
+ 5452241004_F |
+ 289 |
+
+
+ | 12 |
+ BXD9 |
+ P3 |
+ 4 |
+ 5452241022_D |
+ 288 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 8 |
+ 5237939010_A |
+ 117 |
+
+
+ | 14 |
+ BXD11 |
+ P3 |
+ 1 |
+ 5448576044_D |
+ 120 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 6 |
+ 5384138009_B |
+ 130 |
+
+
+ | 16 |
+ BXD12 |
+ P3 |
+ 7 |
+ 5384138021_B |
+ 132 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 7 |
+ 5384138020_F |
+ 161 |
+
+
+ | 18 |
+ BXD13 |
+ P3 |
+ 5 |
+ 5452241004_C |
+ 164 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241004_B |
+ 158 |
+
+
+ | 20 |
+ BXD14 |
+ P3 |
+ 6 |
+ 5452241033_D |
+ 424 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 3 |
+ 5452241008_C |
+ 437 |
+
+
+ | 22 |
+ BXD15 |
+ P3 |
+ 4 |
+ 5452241023_D |
+ 438 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 3 |
+ 5384138048_D |
+ 170 |
+
+
+ | 24 |
+ BXD16 |
+ P3 |
+ 4 |
+ 5452241007_D |
+ 172 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 8 |
+ 5448576010_A |
+ 390 |
+
+
+ | 26 |
+ BXD18 |
+ P3 |
+ 1 |
+ 5448576045_E |
+ 392 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 8 |
+ 5237939010_E |
+ 210 |
+
+
+ | 28 |
+ BXD19 |
+ P3 |
+ 1 |
+ 5448576045_A |
+ 211 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 5 |
+ 5452241017_B |
+ 439 |
+
+
+ | 30 |
+ BXD20 |
+ P3 |
+ 6 |
+ 5452241033_E |
+ 441 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 7 |
+ 5384138021_F |
+ 341 |
+
+
+ | 32 |
+ BXD21 |
+ P3 |
+ 6 |
+ 5384138053_F |
+ 315 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 8 |
+ 5237939012_B |
+ 251 |
+
+
+ | 34 |
+ BXD24a |
+ P3 |
+ 7 |
+ 5384138020_B |
+ 250 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 8 |
+ 5237939012_D |
+ 298 |
+
+
+ | 36 |
+ BXD27 |
+ P3 |
+ 1 |
+ 5448576045_C |
+ 300 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 2 |
+ 5384138049_B |
+ 550 |
+
+
+ | 38 |
+ BXD28 |
+ P3 |
+ 1 |
+ 5448576029_F |
+ 548 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 2 |
+ 5384138047_F |
+ 502 |
+
+
+ | 40 |
+ BXD29 |
+ P3 |
+ 1 |
+ 5448576029_D |
+ 501 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 5 |
+ 5452241024_D |
+ 579 |
+
+
+ | 42 |
+ BXD31 |
+ P3 |
+ 6 |
+ 5452241035_D |
+ 582 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_F |
+ 407 |
+
+
+ | 44 |
+ BXD32 |
+ P3 |
+ 6 |
+ 5452241033_C |
+ 408 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 8 |
+ 5237939012_F |
+ 345 |
+
+
+ | 46 |
+ BXD34 |
+ P3 |
+ 4 |
+ 5452241022_F |
+ 355 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 7 |
+ 5384138016_A |
+ 429 |
+
+
+ | 48 |
+ BXD36 |
+ P3 |
+ 8 |
+ 5448576010_D |
+ 430 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 2 |
+ 5384138041_F |
+ 327 |
+
+
+ | 50 |
+ BXD38 |
+ P3 |
+ 3 |
+ 5384138058_E |
+ 328 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 7 |
+ 5384138016_E |
+ 515 |
+
+
+ | 52 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241024_A |
+ 518 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 2 |
+ 5384138041_C |
+ 373 |
+
+
+ | 54 |
+ BXD40 |
+ P3 |
+ 3 |
+ 5452241008_A |
+ 375 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 3 |
+ 5452241008_E |
+ 485 |
+
+
+ | 56 |
+ BXD42 |
+ P3 |
+ 4 |
+ 5452241023_F |
+ 486 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 5 |
+ 5452241024_F |
+ 621 |
+
+
+ | 58 |
+ BXD51 |
+ P3 |
+ 6 |
+ 5452241035_F |
+ 622 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 4 |
+ 5452241031_C |
+ 554 |
+
+
+ | 60 |
+ BXD61 |
+ P3 |
+ 3 |
+ 5452241034_A |
+ 552 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 2 |
+ 5384138049_D |
+ 590 |
+
+
+ | 62 |
+ BXD70 |
+ P3 |
+ 1 |
+ 5448576044_B |
+ 589 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 2 |
+ 5384138049_E |
+ 603 |
+
+
+ | 64 |
+ BXD73 |
+ P3 |
+ 8 |
+ 5448576011_E |
+ 605 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Devneocortex_ilm6_2p3rinv_1110/cases.rtf b/general/datasets/Devneocortex_ilm6_2p3rinv_1110/cases.rtf
new file mode 100644
index 0000000..70216c8
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p3rinv_1110/cases.rtf
@@ -0,0 +1,3 @@
+About the strains used to generate this set of data
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/Devneocortex_ilm6_2p3rinv_1110/experiment-design.rtf b/general/datasets/Devneocortex_ilm6_2p3rinv_1110/experiment-design.rtf
new file mode 100644
index 0000000..616db01
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p3rinv_1110/experiment-design.rtf
@@ -0,0 +1,3 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Devneocortex_ilm6_2p3rinv_1110/summary.rtf b/general/datasets/Devneocortex_ilm6_2p3rinv_1110/summary.rtf
new file mode 100644
index 0000000..70d7451
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p3rinv_1110/summary.rtf
@@ -0,0 +1,16 @@
+Data generated by Dr. Glenn D. Rosen and colleagues
+
+The Neocortex Developmental data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+Some of these data were used in
+Gaglani SM, Lu L, Williams RW, Rosen GD (2009) The genetic control of neocortex volume and covariation with patterns of gene expression in mice. BMC Neuroscience 10:44 Full Text HTML Version, Full Text PDF Version
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the Striatal Developmental Transcriptome data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Developmental data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse neocortex data may also find the following complementary resources and papers useful:
+
+Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. ABOUT THE NEOCORTEX
diff --git a/general/datasets/Devneocortex_ilm6_2p3rinv_1110/tissue.rtf b/general/datasets/Devneocortex_ilm6_2p3rinv_1110/tissue.rtf
new file mode 100644
index 0000000..51f6e74
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p3rinv_1110/tissue.rtf
@@ -0,0 +1,536 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected neocortical tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn D. Rosen and colleagues.
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 2 |
+ 5384138018_F |
+ 236 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 3 |
+ 5384138058_A |
+ 239 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 2 |
+ 5384138018_C |
+ 168 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 1 |
+ 5448576044_F |
+ 167 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 7 |
+ 5384138020_A |
+ 273 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 4 |
+ 5452241022_C |
+ 267 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 3 |
+ 5384138048_A |
+ 107 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 4 |
+ 5452241007_A |
+ 108 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 6 |
+ 5384138009_A |
+ 113 |
+
+
+ | 10 |
+ BXD8 |
+ P3 |
+ 7 |
+ 5384138021_C |
+ 115 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 5 |
+ 5452241004_F |
+ 289 |
+
+
+ | 12 |
+ BXD9 |
+ P3 |
+ 4 |
+ 5452241022_D |
+ 288 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 8 |
+ 5237939010_A |
+ 117 |
+
+
+ | 14 |
+ BXD11 |
+ P3 |
+ 1 |
+ 5448576044_D |
+ 120 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 6 |
+ 5384138009_B |
+ 130 |
+
+
+ | 16 |
+ BXD12 |
+ P3 |
+ 7 |
+ 5384138021_B |
+ 132 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 7 |
+ 5384138020_F |
+ 161 |
+
+
+ | 18 |
+ BXD13 |
+ P3 |
+ 5 |
+ 5452241004_C |
+ 164 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241004_B |
+ 158 |
+
+
+ | 20 |
+ BXD14 |
+ P3 |
+ 6 |
+ 5452241033_D |
+ 424 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 3 |
+ 5452241008_C |
+ 437 |
+
+
+ | 22 |
+ BXD15 |
+ P3 |
+ 4 |
+ 5452241023_D |
+ 438 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 3 |
+ 5384138048_D |
+ 170 |
+
+
+ | 24 |
+ BXD16 |
+ P3 |
+ 4 |
+ 5452241007_D |
+ 172 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 8 |
+ 5448576010_A |
+ 390 |
+
+
+ | 26 |
+ BXD18 |
+ P3 |
+ 1 |
+ 5448576045_E |
+ 392 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 8 |
+ 5237939010_E |
+ 210 |
+
+
+ | 28 |
+ BXD19 |
+ P3 |
+ 1 |
+ 5448576045_A |
+ 211 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 5 |
+ 5452241017_B |
+ 439 |
+
+
+ | 30 |
+ BXD20 |
+ P3 |
+ 6 |
+ 5452241033_E |
+ 441 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 7 |
+ 5384138021_F |
+ 341 |
+
+
+ | 32 |
+ BXD21 |
+ P3 |
+ 6 |
+ 5384138053_F |
+ 315 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 8 |
+ 5237939012_B |
+ 251 |
+
+
+ | 34 |
+ BXD24a |
+ P3 |
+ 7 |
+ 5384138020_B |
+ 250 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 8 |
+ 5237939012_D |
+ 298 |
+
+
+ | 36 |
+ BXD27 |
+ P3 |
+ 1 |
+ 5448576045_C |
+ 300 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 2 |
+ 5384138049_B |
+ 550 |
+
+
+ | 38 |
+ BXD28 |
+ P3 |
+ 1 |
+ 5448576029_F |
+ 548 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 2 |
+ 5384138047_F |
+ 502 |
+
+
+ | 40 |
+ BXD29 |
+ P3 |
+ 1 |
+ 5448576029_D |
+ 501 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 5 |
+ 5452241024_D |
+ 579 |
+
+
+ | 42 |
+ BXD31 |
+ P3 |
+ 6 |
+ 5452241035_D |
+ 582 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_F |
+ 407 |
+
+
+ | 44 |
+ BXD32 |
+ P3 |
+ 6 |
+ 5452241033_C |
+ 408 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 8 |
+ 5237939012_F |
+ 345 |
+
+
+ | 46 |
+ BXD34 |
+ P3 |
+ 4 |
+ 5452241022_F |
+ 355 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 7 |
+ 5384138016_A |
+ 429 |
+
+
+ | 48 |
+ BXD36 |
+ P3 |
+ 8 |
+ 5448576010_D |
+ 430 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 2 |
+ 5384138041_F |
+ 327 |
+
+
+ | 50 |
+ BXD38 |
+ P3 |
+ 3 |
+ 5384138058_E |
+ 328 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 7 |
+ 5384138016_E |
+ 515 |
+
+
+ | 52 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241024_A |
+ 518 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 2 |
+ 5384138041_C |
+ 373 |
+
+
+ | 54 |
+ BXD40 |
+ P3 |
+ 3 |
+ 5452241008_A |
+ 375 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 3 |
+ 5452241008_E |
+ 485 |
+
+
+ | 56 |
+ BXD42 |
+ P3 |
+ 4 |
+ 5452241023_F |
+ 486 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 5 |
+ 5452241024_F |
+ 621 |
+
+
+ | 58 |
+ BXD51 |
+ P3 |
+ 6 |
+ 5452241035_F |
+ 622 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 4 |
+ 5452241031_C |
+ 554 |
+
+
+ | 60 |
+ BXD61 |
+ P3 |
+ 3 |
+ 5452241034_A |
+ 552 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 2 |
+ 5384138049_D |
+ 590 |
+
+
+ | 62 |
+ BXD70 |
+ P3 |
+ 1 |
+ 5448576044_B |
+ 589 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 2 |
+ 5384138049_E |
+ 603 |
+
+
+ | 64 |
+ BXD73 |
+ P3 |
+ 8 |
+ 5448576011_E |
+ 605 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Devneocortex_ilm6_2p3rinv_1111/cases.rtf b/general/datasets/Devneocortex_ilm6_2p3rinv_1111/cases.rtf
new file mode 100644
index 0000000..70216c8
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p3rinv_1111/cases.rtf
@@ -0,0 +1,3 @@
+About the strains used to generate this set of data
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/Devneocortex_ilm6_2p3rinv_1111/experiment-design.rtf b/general/datasets/Devneocortex_ilm6_2p3rinv_1111/experiment-design.rtf
new file mode 100644
index 0000000..616db01
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p3rinv_1111/experiment-design.rtf
@@ -0,0 +1,3 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Devneocortex_ilm6_2p3rinv_1111/summary.rtf b/general/datasets/Devneocortex_ilm6_2p3rinv_1111/summary.rtf
new file mode 100644
index 0000000..70d7451
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p3rinv_1111/summary.rtf
@@ -0,0 +1,16 @@
+Data generated by Dr. Glenn D. Rosen and colleagues
+
+The Neocortex Developmental data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+Some of these data were used in
+Gaglani SM, Lu L, Williams RW, Rosen GD (2009) The genetic control of neocortex volume and covariation with patterns of gene expression in mice. BMC Neuroscience 10:44 Full Text HTML Version, Full Text PDF Version
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the Striatal Developmental Transcriptome data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Developmental data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse neocortex data may also find the following complementary resources and papers useful:
+
+Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. ABOUT THE NEOCORTEX
diff --git a/general/datasets/Devneocortex_ilm6_2p3rinv_1111/tissue.rtf b/general/datasets/Devneocortex_ilm6_2p3rinv_1111/tissue.rtf
new file mode 100644
index 0000000..51f6e74
--- /dev/null
+++ b/general/datasets/Devneocortex_ilm6_2p3rinv_1111/tissue.rtf
@@ -0,0 +1,536 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected neocortical tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn D. Rosen and colleagues.
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 2 |
+ 5384138018_F |
+ 236 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 3 |
+ 5384138058_A |
+ 239 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 2 |
+ 5384138018_C |
+ 168 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 1 |
+ 5448576044_F |
+ 167 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 7 |
+ 5384138020_A |
+ 273 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 4 |
+ 5452241022_C |
+ 267 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 3 |
+ 5384138048_A |
+ 107 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 4 |
+ 5452241007_A |
+ 108 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 6 |
+ 5384138009_A |
+ 113 |
+
+
+ | 10 |
+ BXD8 |
+ P3 |
+ 7 |
+ 5384138021_C |
+ 115 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 5 |
+ 5452241004_F |
+ 289 |
+
+
+ | 12 |
+ BXD9 |
+ P3 |
+ 4 |
+ 5452241022_D |
+ 288 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 8 |
+ 5237939010_A |
+ 117 |
+
+
+ | 14 |
+ BXD11 |
+ P3 |
+ 1 |
+ 5448576044_D |
+ 120 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 6 |
+ 5384138009_B |
+ 130 |
+
+
+ | 16 |
+ BXD12 |
+ P3 |
+ 7 |
+ 5384138021_B |
+ 132 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 7 |
+ 5384138020_F |
+ 161 |
+
+
+ | 18 |
+ BXD13 |
+ P3 |
+ 5 |
+ 5452241004_C |
+ 164 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241004_B |
+ 158 |
+
+
+ | 20 |
+ BXD14 |
+ P3 |
+ 6 |
+ 5452241033_D |
+ 424 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 3 |
+ 5452241008_C |
+ 437 |
+
+
+ | 22 |
+ BXD15 |
+ P3 |
+ 4 |
+ 5452241023_D |
+ 438 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 3 |
+ 5384138048_D |
+ 170 |
+
+
+ | 24 |
+ BXD16 |
+ P3 |
+ 4 |
+ 5452241007_D |
+ 172 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 8 |
+ 5448576010_A |
+ 390 |
+
+
+ | 26 |
+ BXD18 |
+ P3 |
+ 1 |
+ 5448576045_E |
+ 392 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 8 |
+ 5237939010_E |
+ 210 |
+
+
+ | 28 |
+ BXD19 |
+ P3 |
+ 1 |
+ 5448576045_A |
+ 211 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 5 |
+ 5452241017_B |
+ 439 |
+
+
+ | 30 |
+ BXD20 |
+ P3 |
+ 6 |
+ 5452241033_E |
+ 441 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 7 |
+ 5384138021_F |
+ 341 |
+
+
+ | 32 |
+ BXD21 |
+ P3 |
+ 6 |
+ 5384138053_F |
+ 315 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 8 |
+ 5237939012_B |
+ 251 |
+
+
+ | 34 |
+ BXD24a |
+ P3 |
+ 7 |
+ 5384138020_B |
+ 250 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 8 |
+ 5237939012_D |
+ 298 |
+
+
+ | 36 |
+ BXD27 |
+ P3 |
+ 1 |
+ 5448576045_C |
+ 300 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 2 |
+ 5384138049_B |
+ 550 |
+
+
+ | 38 |
+ BXD28 |
+ P3 |
+ 1 |
+ 5448576029_F |
+ 548 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 2 |
+ 5384138047_F |
+ 502 |
+
+
+ | 40 |
+ BXD29 |
+ P3 |
+ 1 |
+ 5448576029_D |
+ 501 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 5 |
+ 5452241024_D |
+ 579 |
+
+
+ | 42 |
+ BXD31 |
+ P3 |
+ 6 |
+ 5452241035_D |
+ 582 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_F |
+ 407 |
+
+
+ | 44 |
+ BXD32 |
+ P3 |
+ 6 |
+ 5452241033_C |
+ 408 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 8 |
+ 5237939012_F |
+ 345 |
+
+
+ | 46 |
+ BXD34 |
+ P3 |
+ 4 |
+ 5452241022_F |
+ 355 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 7 |
+ 5384138016_A |
+ 429 |
+
+
+ | 48 |
+ BXD36 |
+ P3 |
+ 8 |
+ 5448576010_D |
+ 430 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 2 |
+ 5384138041_F |
+ 327 |
+
+
+ | 50 |
+ BXD38 |
+ P3 |
+ 3 |
+ 5384138058_E |
+ 328 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 7 |
+ 5384138016_E |
+ 515 |
+
+
+ | 52 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241024_A |
+ 518 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 2 |
+ 5384138041_C |
+ 373 |
+
+
+ | 54 |
+ BXD40 |
+ P3 |
+ 3 |
+ 5452241008_A |
+ 375 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 3 |
+ 5452241008_E |
+ 485 |
+
+
+ | 56 |
+ BXD42 |
+ P3 |
+ 4 |
+ 5452241023_F |
+ 486 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 5 |
+ 5452241024_F |
+ 621 |
+
+
+ | 58 |
+ BXD51 |
+ P3 |
+ 6 |
+ 5452241035_F |
+ 622 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 4 |
+ 5452241031_C |
+ 554 |
+
+
+ | 60 |
+ BXD61 |
+ P3 |
+ 3 |
+ 5452241034_A |
+ 552 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 2 |
+ 5384138049_D |
+ 590 |
+
+
+ | 62 |
+ BXD70 |
+ P3 |
+ 1 |
+ 5448576044_B |
+ 589 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 2 |
+ 5384138049_E |
+ 603 |
+
+
+ | 64 |
+ BXD73 |
+ P3 |
+ 8 |
+ 5448576011_E |
+ 605 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Devstriatum_ilm6_2p14rinv_1110/cases.rtf b/general/datasets/Devstriatum_ilm6_2p14rinv_1110/cases.rtf
new file mode 100644
index 0000000..74c0f5e
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p14rinv_1110/cases.rtf
@@ -0,0 +1 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/Devstriatum_ilm6_2p14rinv_1110/experiment-design.rtf b/general/datasets/Devstriatum_ilm6_2p14rinv_1110/experiment-design.rtf
new file mode 100644
index 0000000..cfea6b0
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p14rinv_1110/experiment-design.rtf
@@ -0,0 +1 @@
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Devstriatum_ilm6_2p14rinv_1110/processing.rtf b/general/datasets/Devstriatum_ilm6_2p14rinv_1110/processing.rtf
new file mode 100644
index 0000000..aee498f
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p14rinv_1110/processing.rtf
@@ -0,0 +1 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
diff --git a/general/datasets/Devstriatum_ilm6_2p14rinv_1110/summary.rtf b/general/datasets/Devstriatum_ilm6_2p14rinv_1110/summary.rtf
new file mode 100644
index 0000000..3515533
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p14rinv_1110/summary.rtf
@@ -0,0 +1,10 @@
+The BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv ** data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv ** data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse striatum data set may also find the following complementary resources and papers useful:
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. www.rosenlab.net/Movie/P3.mov
+www.rosenlab.net/Movie/P14.mov
diff --git a/general/datasets/Devstriatum_ilm6_2p14rinv_1110/tissue.rtf b/general/datasets/Devstriatum_ilm6_2p14rinv_1110/tissue.rtf
new file mode 100644
index 0000000..e9e6151
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p14rinv_1110/tissue.rtf
@@ -0,0 +1,534 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Care was taken to assure that samples were comprised of the dorsal striatum, although it is possible that ventral striatum (accumbens) was occasionally included.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected striatal tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues.
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 8 |
+ 5237939012_A |
+ 232 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 1 |
+ 5448576016_C |
+ 234 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 7 |
+ 5384138020_C |
+ 230 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 6 |
+ 5384138053_A |
+ 228 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 6 |
+ 5384138053_D |
+ 270 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 5 |
+ 5452241004_E |
+ 268 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 2 |
+ 5384138018_A |
+ 102 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 1 |
+ 5448576016_A |
+ 101 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 3 |
+ 5384138048_B |
+ 110 |
+
+
+ | 10 |
+ BXD9 |
+ P3 |
+ 2 |
+ 5384138041_A |
+ 280 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 3 |
+ 5384138058_C |
+ 278 |
+
+
+ | 12 |
+ BXD11 |
+ P3 |
+ 2 |
+ 5384138018_B |
+ 121 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 3 |
+ 5384138048_C |
+ 123 |
+
+
+ | 14 |
+ BXD12 |
+ P3 |
+ 5 |
+ 5452241004_A |
+ 127 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 4 |
+ 5452241007_B |
+ 125 |
+
+
+ | 16 |
+ BXD13 |
+ P3 |
+ 8 |
+ 5237939010_D |
+ 181 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 1 |
+ 5448576016_B |
+ 183 |
+
+
+ | 18 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241017_A |
+ 420 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 4 |
+ 5452241023_C |
+ 419 |
+
+
+ | 20 |
+ BXD15 |
+ P3 |
+ 7 |
+ 5384138016_C |
+ 475 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 8 |
+ 5448576010_F |
+ 476 |
+
+
+ | 22 |
+ BXD16 |
+ P3 |
+ 6 |
+ 5384138009_F |
+ 204 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 7 |
+ 5384138020_D |
+ 205 |
+
+
+ | 24 |
+ BXD18 |
+ P3 |
+ 7 |
+ 5384138017_B |
+ 388 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 3 |
+ 5452241008_B |
+ 385 |
+
+
+ | 26 |
+ BXD19 |
+ P3 |
+ 2 |
+ 5384138018_E |
+ 212 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 3 |
+ 5384138048_F |
+ 213 |
+
+
+ | 28 |
+ BXD20 |
+ P3 |
+ 2 |
+ 5384138047_C |
+ 431 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 1 |
+ 5448576029_A |
+ 431 |
+
+
+ | 30 |
+ BXD21 |
+ P3 |
+ 5 |
+ 5452241006_A |
+ 311 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 4 |
+ 5452241022_E |
+ 309 |
+
+
+ | 32 |
+ BXD24a |
+ P3 |
+ 6 |
+ 5384138053_B |
+ 247 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 4 |
+ 5452241022_B |
+ 244 |
+
+
+ | 34 |
+ BXD27 |
+ P3 |
+ 7 |
+ 5384138021_D |
+ 294 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 6 |
+ 5384138053_E |
+ 293 |
+
+
+ | 36 |
+ BXD28 |
+ P3 |
+ 7 |
+ 5384138016_F |
+ 543 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 8 |
+ 5448576011_B |
+ 545 |
+
+
+ | 38 |
+ BXD29 |
+ P3 |
+ 7 |
+ 5384138016_D |
+ 495 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 8 |
+ 5448576011_A |
+ 498 |
+
+
+ | 40 |
+ BXD31 |
+ P3 |
+ 4 |
+ 5452241031_D |
+ 577 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 3 |
+ 5452241034_D |
+ 575 |
+
+
+ | 42 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_E |
+ 402 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 4 |
+ 5452241023_B |
+ 401 |
+
+
+ | 44 |
+ BXD34 |
+ P3 |
+ 2 |
+ 5384138041_D |
+ 348 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 1 |
+ 5448576016_E |
+ 347 |
+
+
+ | 46 |
+ BXD36 |
+ P3 |
+ 2 |
+ 5384138047_B |
+ 417 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 3 |
+ 5452241008_D |
+ 418 |
+
+
+ | 48 |
+ BXD38 |
+ P3 |
+ 8 |
+ 5237939012_E |
+ 321 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 1 |
+ 5448576016_D |
+ 322 |
+
+
+ | 50 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241017_F |
+ 511 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 4 |
+ 5452241031_A |
+ 512 |
+
+
+ | 52 |
+ BXD40 |
+ P3 |
+ 8 |
+ 5448576010_B |
+ 368 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 1 |
+ 5448576016_F |
+ 371 |
+
+
+ | 54 |
+ BXD42 |
+ P3 |
+ 2 |
+ 5384138047_E |
+ 481 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 1 |
+ 5448576029_C |
+ 479 |
+
+
+ | 56 |
+ BXD51 |
+ P3 |
+ 4 |
+ 5452241031_F |
+ 616 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 3 |
+ 5452241034_F |
+ 615 |
+
+
+ | 58 |
+ BXD61 |
+ P3 |
+ 5 |
+ 5452241024_C |
+ 555 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 6 |
+ 5452241035_B |
+ 557 |
+
+
+ | 60 |
+ BXD70 |
+ P3 |
+ 7 |
+ 5384138017_E |
+ 584 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 8 |
+ 5448576011_D |
+ 585 |
+
+
+ | 62 |
+ BXD73 |
+ P3 |
+ 5 |
+ 5452241024_E |
+ 600 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 6 |
+ 5452241035_E |
+ 601 |
+
+
+
+ |
+
+
+
+
+
+
diff --git a/general/datasets/Devstriatum_ilm6_2p14rinv_1111/cases.rtf b/general/datasets/Devstriatum_ilm6_2p14rinv_1111/cases.rtf
new file mode 100644
index 0000000..74c0f5e
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p14rinv_1111/cases.rtf
@@ -0,0 +1 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/Devstriatum_ilm6_2p14rinv_1111/experiment-design.rtf b/general/datasets/Devstriatum_ilm6_2p14rinv_1111/experiment-design.rtf
new file mode 100644
index 0000000..cfea6b0
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p14rinv_1111/experiment-design.rtf
@@ -0,0 +1 @@
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Devstriatum_ilm6_2p14rinv_1111/processing.rtf b/general/datasets/Devstriatum_ilm6_2p14rinv_1111/processing.rtf
new file mode 100644
index 0000000..aee498f
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p14rinv_1111/processing.rtf
@@ -0,0 +1 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
diff --git a/general/datasets/Devstriatum_ilm6_2p14rinv_1111/summary.rtf b/general/datasets/Devstriatum_ilm6_2p14rinv_1111/summary.rtf
new file mode 100644
index 0000000..3515533
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p14rinv_1111/summary.rtf
@@ -0,0 +1,10 @@
+The BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv ** data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv ** data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse striatum data set may also find the following complementary resources and papers useful:
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. www.rosenlab.net/Movie/P3.mov
+www.rosenlab.net/Movie/P14.mov
diff --git a/general/datasets/Devstriatum_ilm6_2p14rinv_1111/tissue.rtf b/general/datasets/Devstriatum_ilm6_2p14rinv_1111/tissue.rtf
new file mode 100644
index 0000000..e9e6151
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p14rinv_1111/tissue.rtf
@@ -0,0 +1,534 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Care was taken to assure that samples were comprised of the dorsal striatum, although it is possible that ventral striatum (accumbens) was occasionally included.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected striatal tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues.
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 8 |
+ 5237939012_A |
+ 232 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 1 |
+ 5448576016_C |
+ 234 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 7 |
+ 5384138020_C |
+ 230 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 6 |
+ 5384138053_A |
+ 228 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 6 |
+ 5384138053_D |
+ 270 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 5 |
+ 5452241004_E |
+ 268 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 2 |
+ 5384138018_A |
+ 102 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 1 |
+ 5448576016_A |
+ 101 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 3 |
+ 5384138048_B |
+ 110 |
+
+
+ | 10 |
+ BXD9 |
+ P3 |
+ 2 |
+ 5384138041_A |
+ 280 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 3 |
+ 5384138058_C |
+ 278 |
+
+
+ | 12 |
+ BXD11 |
+ P3 |
+ 2 |
+ 5384138018_B |
+ 121 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 3 |
+ 5384138048_C |
+ 123 |
+
+
+ | 14 |
+ BXD12 |
+ P3 |
+ 5 |
+ 5452241004_A |
+ 127 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 4 |
+ 5452241007_B |
+ 125 |
+
+
+ | 16 |
+ BXD13 |
+ P3 |
+ 8 |
+ 5237939010_D |
+ 181 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 1 |
+ 5448576016_B |
+ 183 |
+
+
+ | 18 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241017_A |
+ 420 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 4 |
+ 5452241023_C |
+ 419 |
+
+
+ | 20 |
+ BXD15 |
+ P3 |
+ 7 |
+ 5384138016_C |
+ 475 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 8 |
+ 5448576010_F |
+ 476 |
+
+
+ | 22 |
+ BXD16 |
+ P3 |
+ 6 |
+ 5384138009_F |
+ 204 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 7 |
+ 5384138020_D |
+ 205 |
+
+
+ | 24 |
+ BXD18 |
+ P3 |
+ 7 |
+ 5384138017_B |
+ 388 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 3 |
+ 5452241008_B |
+ 385 |
+
+
+ | 26 |
+ BXD19 |
+ P3 |
+ 2 |
+ 5384138018_E |
+ 212 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 3 |
+ 5384138048_F |
+ 213 |
+
+
+ | 28 |
+ BXD20 |
+ P3 |
+ 2 |
+ 5384138047_C |
+ 431 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 1 |
+ 5448576029_A |
+ 431 |
+
+
+ | 30 |
+ BXD21 |
+ P3 |
+ 5 |
+ 5452241006_A |
+ 311 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 4 |
+ 5452241022_E |
+ 309 |
+
+
+ | 32 |
+ BXD24a |
+ P3 |
+ 6 |
+ 5384138053_B |
+ 247 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 4 |
+ 5452241022_B |
+ 244 |
+
+
+ | 34 |
+ BXD27 |
+ P3 |
+ 7 |
+ 5384138021_D |
+ 294 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 6 |
+ 5384138053_E |
+ 293 |
+
+
+ | 36 |
+ BXD28 |
+ P3 |
+ 7 |
+ 5384138016_F |
+ 543 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 8 |
+ 5448576011_B |
+ 545 |
+
+
+ | 38 |
+ BXD29 |
+ P3 |
+ 7 |
+ 5384138016_D |
+ 495 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 8 |
+ 5448576011_A |
+ 498 |
+
+
+ | 40 |
+ BXD31 |
+ P3 |
+ 4 |
+ 5452241031_D |
+ 577 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 3 |
+ 5452241034_D |
+ 575 |
+
+
+ | 42 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_E |
+ 402 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 4 |
+ 5452241023_B |
+ 401 |
+
+
+ | 44 |
+ BXD34 |
+ P3 |
+ 2 |
+ 5384138041_D |
+ 348 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 1 |
+ 5448576016_E |
+ 347 |
+
+
+ | 46 |
+ BXD36 |
+ P3 |
+ 2 |
+ 5384138047_B |
+ 417 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 3 |
+ 5452241008_D |
+ 418 |
+
+
+ | 48 |
+ BXD38 |
+ P3 |
+ 8 |
+ 5237939012_E |
+ 321 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 1 |
+ 5448576016_D |
+ 322 |
+
+
+ | 50 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241017_F |
+ 511 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 4 |
+ 5452241031_A |
+ 512 |
+
+
+ | 52 |
+ BXD40 |
+ P3 |
+ 8 |
+ 5448576010_B |
+ 368 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 1 |
+ 5448576016_F |
+ 371 |
+
+
+ | 54 |
+ BXD42 |
+ P3 |
+ 2 |
+ 5384138047_E |
+ 481 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 1 |
+ 5448576029_C |
+ 479 |
+
+
+ | 56 |
+ BXD51 |
+ P3 |
+ 4 |
+ 5452241031_F |
+ 616 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 3 |
+ 5452241034_F |
+ 615 |
+
+
+ | 58 |
+ BXD61 |
+ P3 |
+ 5 |
+ 5452241024_C |
+ 555 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 6 |
+ 5452241035_B |
+ 557 |
+
+
+ | 60 |
+ BXD70 |
+ P3 |
+ 7 |
+ 5384138017_E |
+ 584 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 8 |
+ 5448576011_D |
+ 585 |
+
+
+ | 62 |
+ BXD73 |
+ P3 |
+ 5 |
+ 5452241024_E |
+ 600 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 6 |
+ 5452241035_E |
+ 601 |
+
+
+
+ |
+
+
+
+
+
+
diff --git a/general/datasets/Devstriatum_ilm6_2p3rinv_1110/cases.rtf b/general/datasets/Devstriatum_ilm6_2p3rinv_1110/cases.rtf
new file mode 100644
index 0000000..74c0f5e
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p3rinv_1110/cases.rtf
@@ -0,0 +1 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/Devstriatum_ilm6_2p3rinv_1110/experiment-design.rtf b/general/datasets/Devstriatum_ilm6_2p3rinv_1110/experiment-design.rtf
new file mode 100644
index 0000000..cfea6b0
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p3rinv_1110/experiment-design.rtf
@@ -0,0 +1 @@
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Devstriatum_ilm6_2p3rinv_1110/processing.rtf b/general/datasets/Devstriatum_ilm6_2p3rinv_1110/processing.rtf
new file mode 100644
index 0000000..aee498f
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p3rinv_1110/processing.rtf
@@ -0,0 +1 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
diff --git a/general/datasets/Devstriatum_ilm6_2p3rinv_1110/summary.rtf b/general/datasets/Devstriatum_ilm6_2p3rinv_1110/summary.rtf
new file mode 100644
index 0000000..3515533
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p3rinv_1110/summary.rtf
@@ -0,0 +1,10 @@
+The BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv ** data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv ** data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse striatum data set may also find the following complementary resources and papers useful:
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. www.rosenlab.net/Movie/P3.mov
+www.rosenlab.net/Movie/P14.mov
diff --git a/general/datasets/Devstriatum_ilm6_2p3rinv_1110/tissue.rtf b/general/datasets/Devstriatum_ilm6_2p3rinv_1110/tissue.rtf
new file mode 100644
index 0000000..e9e6151
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p3rinv_1110/tissue.rtf
@@ -0,0 +1,534 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Care was taken to assure that samples were comprised of the dorsal striatum, although it is possible that ventral striatum (accumbens) was occasionally included.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected striatal tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues.
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 8 |
+ 5237939012_A |
+ 232 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 1 |
+ 5448576016_C |
+ 234 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 7 |
+ 5384138020_C |
+ 230 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 6 |
+ 5384138053_A |
+ 228 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 6 |
+ 5384138053_D |
+ 270 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 5 |
+ 5452241004_E |
+ 268 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 2 |
+ 5384138018_A |
+ 102 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 1 |
+ 5448576016_A |
+ 101 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 3 |
+ 5384138048_B |
+ 110 |
+
+
+ | 10 |
+ BXD9 |
+ P3 |
+ 2 |
+ 5384138041_A |
+ 280 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 3 |
+ 5384138058_C |
+ 278 |
+
+
+ | 12 |
+ BXD11 |
+ P3 |
+ 2 |
+ 5384138018_B |
+ 121 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 3 |
+ 5384138048_C |
+ 123 |
+
+
+ | 14 |
+ BXD12 |
+ P3 |
+ 5 |
+ 5452241004_A |
+ 127 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 4 |
+ 5452241007_B |
+ 125 |
+
+
+ | 16 |
+ BXD13 |
+ P3 |
+ 8 |
+ 5237939010_D |
+ 181 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 1 |
+ 5448576016_B |
+ 183 |
+
+
+ | 18 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241017_A |
+ 420 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 4 |
+ 5452241023_C |
+ 419 |
+
+
+ | 20 |
+ BXD15 |
+ P3 |
+ 7 |
+ 5384138016_C |
+ 475 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 8 |
+ 5448576010_F |
+ 476 |
+
+
+ | 22 |
+ BXD16 |
+ P3 |
+ 6 |
+ 5384138009_F |
+ 204 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 7 |
+ 5384138020_D |
+ 205 |
+
+
+ | 24 |
+ BXD18 |
+ P3 |
+ 7 |
+ 5384138017_B |
+ 388 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 3 |
+ 5452241008_B |
+ 385 |
+
+
+ | 26 |
+ BXD19 |
+ P3 |
+ 2 |
+ 5384138018_E |
+ 212 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 3 |
+ 5384138048_F |
+ 213 |
+
+
+ | 28 |
+ BXD20 |
+ P3 |
+ 2 |
+ 5384138047_C |
+ 431 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 1 |
+ 5448576029_A |
+ 431 |
+
+
+ | 30 |
+ BXD21 |
+ P3 |
+ 5 |
+ 5452241006_A |
+ 311 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 4 |
+ 5452241022_E |
+ 309 |
+
+
+ | 32 |
+ BXD24a |
+ P3 |
+ 6 |
+ 5384138053_B |
+ 247 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 4 |
+ 5452241022_B |
+ 244 |
+
+
+ | 34 |
+ BXD27 |
+ P3 |
+ 7 |
+ 5384138021_D |
+ 294 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 6 |
+ 5384138053_E |
+ 293 |
+
+
+ | 36 |
+ BXD28 |
+ P3 |
+ 7 |
+ 5384138016_F |
+ 543 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 8 |
+ 5448576011_B |
+ 545 |
+
+
+ | 38 |
+ BXD29 |
+ P3 |
+ 7 |
+ 5384138016_D |
+ 495 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 8 |
+ 5448576011_A |
+ 498 |
+
+
+ | 40 |
+ BXD31 |
+ P3 |
+ 4 |
+ 5452241031_D |
+ 577 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 3 |
+ 5452241034_D |
+ 575 |
+
+
+ | 42 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_E |
+ 402 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 4 |
+ 5452241023_B |
+ 401 |
+
+
+ | 44 |
+ BXD34 |
+ P3 |
+ 2 |
+ 5384138041_D |
+ 348 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 1 |
+ 5448576016_E |
+ 347 |
+
+
+ | 46 |
+ BXD36 |
+ P3 |
+ 2 |
+ 5384138047_B |
+ 417 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 3 |
+ 5452241008_D |
+ 418 |
+
+
+ | 48 |
+ BXD38 |
+ P3 |
+ 8 |
+ 5237939012_E |
+ 321 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 1 |
+ 5448576016_D |
+ 322 |
+
+
+ | 50 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241017_F |
+ 511 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 4 |
+ 5452241031_A |
+ 512 |
+
+
+ | 52 |
+ BXD40 |
+ P3 |
+ 8 |
+ 5448576010_B |
+ 368 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 1 |
+ 5448576016_F |
+ 371 |
+
+
+ | 54 |
+ BXD42 |
+ P3 |
+ 2 |
+ 5384138047_E |
+ 481 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 1 |
+ 5448576029_C |
+ 479 |
+
+
+ | 56 |
+ BXD51 |
+ P3 |
+ 4 |
+ 5452241031_F |
+ 616 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 3 |
+ 5452241034_F |
+ 615 |
+
+
+ | 58 |
+ BXD61 |
+ P3 |
+ 5 |
+ 5452241024_C |
+ 555 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 6 |
+ 5452241035_B |
+ 557 |
+
+
+ | 60 |
+ BXD70 |
+ P3 |
+ 7 |
+ 5384138017_E |
+ 584 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 8 |
+ 5448576011_D |
+ 585 |
+
+
+ | 62 |
+ BXD73 |
+ P3 |
+ 5 |
+ 5452241024_E |
+ 600 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 6 |
+ 5452241035_E |
+ 601 |
+
+
+
+ |
+
+
+
+
+
+
diff --git a/general/datasets/Devstriatum_ilm6_2p3rinv_1111/cases.rtf b/general/datasets/Devstriatum_ilm6_2p3rinv_1111/cases.rtf
new file mode 100644
index 0000000..74c0f5e
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p3rinv_1111/cases.rtf
@@ -0,0 +1 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 28 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 4 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/Devstriatum_ilm6_2p3rinv_1111/experiment-design.rtf b/general/datasets/Devstriatum_ilm6_2p3rinv_1111/experiment-design.rtf
new file mode 100644
index 0000000..cfea6b0
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p3rinv_1111/experiment-design.rtf
@@ -0,0 +1 @@
+This data set consists arrays processed in 8 groups over a 2 month period (from July-August 2010). All groups consisted of 24 samples. All arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Lorne Rose. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Devstriatum_ilm6_2p3rinv_1111/processing.rtf b/general/datasets/Devstriatum_ilm6_2p3rinv_1111/processing.rtf
new file mode 100644
index 0000000..aee498f
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p3rinv_1111/processing.rtf
@@ -0,0 +1 @@
+Samples were processed by Lorne Rose and colleagues in the Illumina Core at UTHSC between July and August 2010. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
diff --git a/general/datasets/Devstriatum_ilm6_2p3rinv_1111/summary.rtf b/general/datasets/Devstriatum_ilm6_2p3rinv_1111/summary.rtf
new file mode 100644
index 0000000..3515533
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p3rinv_1111/summary.rtf
@@ -0,0 +1,10 @@
+The BIDMC/UTHSC Dev Striatum P3 ILMv6.2 (Nov10) RankInv ** data set provides estimates of mRNA expression during two developmental ages (postnatal days 3 and 14) in the cerebral cortex from 32 BXD strains. All samples are from normal animals raised and bred in a standard laboratory environment.
+
+All samples were processed using 32 Illumina Sentrix v6.2 BeadArray slides. All samples passed stringent quality control and error checking. This data set is a companion to the BIDMC/UTHSC Dev Neocortex P3 ILMv6.2 (Nov10) RankInv ** data set and was processed using identical methods and the same strains. This data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this data set, xxxx probes have LRS values >46 (LOD >10).
+
+Users of these mouse striatum data set may also find the following complementary resources and papers useful:
+
+A movie of the dissection of the brain by Dr. Glenn Rosen. www.rosenlab.net/Movie/P3.mov
+www.rosenlab.net/Movie/P14.mov
diff --git a/general/datasets/Devstriatum_ilm6_2p3rinv_1111/tissue.rtf b/general/datasets/Devstriatum_ilm6_2p3rinv_1111/tissue.rtf
new file mode 100644
index 0000000..e9e6151
--- /dev/null
+++ b/general/datasets/Devstriatum_ilm6_2p3rinv_1111/tissue.rtf
@@ -0,0 +1,534 @@
+All animals were raised at Beth Israel Deaconess Medical Center in SPF facilities from stock obtained from either Jackson Laboratory or UTHSC. All mice were killed by decapitation. Whole brain dissections were performed at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues. Care was taken to assure that samples were comprised of the dorsal striatum, although it is possible that ventral striatum (accumbens) was occasionally included.
+
+All animals used in this study were either 3 or 14 days of age. A pool of dissected striatal tissue from three naive animals of the same strain and age were collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at Beth Israel Deaconess Medical Center by Glenn Rosen and colleagues.
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Age |
+ Batch ID |
+ Sample ID |
+ Tube ID |
+
+
+ | 1 |
+ BXD1 |
+ P3 |
+ 8 |
+ 5237939012_A |
+ 232 |
+
+
+ | 2 |
+ BXD1 |
+ P3 |
+ 1 |
+ 5448576016_C |
+ 234 |
+
+
+ | 3 |
+ BXD2 |
+ P3 |
+ 7 |
+ 5384138020_C |
+ 230 |
+
+
+ | 4 |
+ BXD2 |
+ P3 |
+ 6 |
+ 5384138053_A |
+ 228 |
+
+
+ | 5 |
+ BXD5 |
+ P3 |
+ 6 |
+ 5384138053_D |
+ 270 |
+
+
+ | 6 |
+ BXD5 |
+ P3 |
+ 5 |
+ 5452241004_E |
+ 268 |
+
+
+ | 7 |
+ BXD6 |
+ P3 |
+ 2 |
+ 5384138018_A |
+ 102 |
+
+
+ | 8 |
+ BXD6 |
+ P3 |
+ 1 |
+ 5448576016_A |
+ 101 |
+
+
+ | 9 |
+ BXD8 |
+ P3 |
+ 3 |
+ 5384138048_B |
+ 110 |
+
+
+ | 10 |
+ BXD9 |
+ P3 |
+ 2 |
+ 5384138041_A |
+ 280 |
+
+
+ | 11 |
+ BXD9 |
+ P3 |
+ 3 |
+ 5384138058_C |
+ 278 |
+
+
+ | 12 |
+ BXD11 |
+ P3 |
+ 2 |
+ 5384138018_B |
+ 121 |
+
+
+ | 13 |
+ BXD11 |
+ P3 |
+ 3 |
+ 5384138048_C |
+ 123 |
+
+
+ | 14 |
+ BXD12 |
+ P3 |
+ 5 |
+ 5452241004_A |
+ 127 |
+
+
+ | 15 |
+ BXD12 |
+ P3 |
+ 4 |
+ 5452241007_B |
+ 125 |
+
+
+ | 16 |
+ BXD13 |
+ P3 |
+ 8 |
+ 5237939010_D |
+ 181 |
+
+
+ | 17 |
+ BXD13 |
+ P3 |
+ 1 |
+ 5448576016_B |
+ 183 |
+
+
+ | 18 |
+ BXD14 |
+ P3 |
+ 5 |
+ 5452241017_A |
+ 420 |
+
+
+ | 19 |
+ BXD14 |
+ P3 |
+ 4 |
+ 5452241023_C |
+ 419 |
+
+
+ | 20 |
+ BXD15 |
+ P3 |
+ 7 |
+ 5384138016_C |
+ 475 |
+
+
+ | 21 |
+ BXD15 |
+ P3 |
+ 8 |
+ 5448576010_F |
+ 476 |
+
+
+ | 22 |
+ BXD16 |
+ P3 |
+ 6 |
+ 5384138009_F |
+ 204 |
+
+
+ | 23 |
+ BXD16 |
+ P3 |
+ 7 |
+ 5384138020_D |
+ 205 |
+
+
+ | 24 |
+ BXD18 |
+ P3 |
+ 7 |
+ 5384138017_B |
+ 388 |
+
+
+ | 25 |
+ BXD18 |
+ P3 |
+ 3 |
+ 5452241008_B |
+ 385 |
+
+
+ | 26 |
+ BXD19 |
+ P3 |
+ 2 |
+ 5384138018_E |
+ 212 |
+
+
+ | 27 |
+ BXD19 |
+ P3 |
+ 3 |
+ 5384138048_F |
+ 213 |
+
+
+ | 28 |
+ BXD20 |
+ P3 |
+ 2 |
+ 5384138047_C |
+ 431 |
+
+
+ | 29 |
+ BXD20 |
+ P3 |
+ 1 |
+ 5448576029_A |
+ 431 |
+
+
+ | 30 |
+ BXD21 |
+ P3 |
+ 5 |
+ 5452241006_A |
+ 311 |
+
+
+ | 31 |
+ BXD21 |
+ P3 |
+ 4 |
+ 5452241022_E |
+ 309 |
+
+
+ | 32 |
+ BXD24a |
+ P3 |
+ 6 |
+ 5384138053_B |
+ 247 |
+
+
+ | 33 |
+ BXD24a |
+ P3 |
+ 4 |
+ 5452241022_B |
+ 244 |
+
+
+ | 34 |
+ BXD27 |
+ P3 |
+ 7 |
+ 5384138021_D |
+ 294 |
+
+
+ | 35 |
+ BXD27 |
+ P3 |
+ 6 |
+ 5384138053_E |
+ 293 |
+
+
+ | 36 |
+ BXD28 |
+ P3 |
+ 7 |
+ 5384138016_F |
+ 543 |
+
+
+ | 37 |
+ BXD28 |
+ P3 |
+ 8 |
+ 5448576011_B |
+ 545 |
+
+
+ | 38 |
+ BXD29 |
+ P3 |
+ 7 |
+ 5384138016_D |
+ 495 |
+
+
+ | 39 |
+ BXD29 |
+ P3 |
+ 8 |
+ 5448576011_A |
+ 498 |
+
+
+ | 40 |
+ BXD31 |
+ P3 |
+ 4 |
+ 5452241031_D |
+ 577 |
+
+
+ | 41 |
+ BXD31 |
+ P3 |
+ 3 |
+ 5452241034_D |
+ 575 |
+
+
+ | 42 |
+ BXD32 |
+ P3 |
+ 5 |
+ 5452241006_E |
+ 402 |
+
+
+ | 43 |
+ BXD32 |
+ P3 |
+ 4 |
+ 5452241023_B |
+ 401 |
+
+
+ | 44 |
+ BXD34 |
+ P3 |
+ 2 |
+ 5384138041_D |
+ 348 |
+
+
+ | 45 |
+ BXD34 |
+ P3 |
+ 1 |
+ 5448576016_E |
+ 347 |
+
+
+ | 46 |
+ BXD36 |
+ P3 |
+ 2 |
+ 5384138047_B |
+ 417 |
+
+
+ | 47 |
+ BXD36 |
+ P3 |
+ 3 |
+ 5452241008_D |
+ 418 |
+
+
+ | 48 |
+ BXD38 |
+ P3 |
+ 8 |
+ 5237939012_E |
+ 321 |
+
+
+ | 49 |
+ BXD38 |
+ P3 |
+ 1 |
+ 5448576016_D |
+ 322 |
+
+
+ | 50 |
+ BXD39 |
+ P3 |
+ 5 |
+ 5452241017_F |
+ 511 |
+
+
+ | 51 |
+ BXD39 |
+ P3 |
+ 4 |
+ 5452241031_A |
+ 512 |
+
+
+ | 52 |
+ BXD40 |
+ P3 |
+ 8 |
+ 5448576010_B |
+ 368 |
+
+
+ | 53 |
+ BXD40 |
+ P3 |
+ 1 |
+ 5448576016_F |
+ 371 |
+
+
+ | 54 |
+ BXD42 |
+ P3 |
+ 2 |
+ 5384138047_E |
+ 481 |
+
+
+ | 55 |
+ BXD42 |
+ P3 |
+ 1 |
+ 5448576029_C |
+ 479 |
+
+
+ | 56 |
+ BXD51 |
+ P3 |
+ 4 |
+ 5452241031_F |
+ 616 |
+
+
+ | 57 |
+ BXD51 |
+ P3 |
+ 3 |
+ 5452241034_F |
+ 615 |
+
+
+ | 58 |
+ BXD61 |
+ P3 |
+ 5 |
+ 5452241024_C |
+ 555 |
+
+
+ | 59 |
+ BXD61 |
+ P3 |
+ 6 |
+ 5452241035_B |
+ 557 |
+
+
+ | 60 |
+ BXD70 |
+ P3 |
+ 7 |
+ 5384138017_E |
+ 584 |
+
+
+ | 61 |
+ BXD70 |
+ P3 |
+ 8 |
+ 5448576011_D |
+ 585 |
+
+
+ | 62 |
+ BXD73 |
+ P3 |
+ 5 |
+ 5452241024_E |
+ 600 |
+
+
+ | 63 |
+ BXD73 |
+ P3 |
+ 6 |
+ 5452241035_E |
+ 601 |
+
+
+
+ |
+
+
+
+
+
+
diff --git a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/acknowledgment.rtf b/general/datasets/DoDCMMRPRetMoGene2Ex_0515/acknowledgment.rtf
deleted file mode 100644
index 760f47e..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This work was supported by DoD CDMRP Grant W81XWH1210255 from the USA Army Medical Research & Materiel Command and the Telemedicine and Advanced Technology (EEG), NIH Grant R01EY017841 (EEG), Vision Core Grant P30EY006360 (P. Michael Iuvone), and Unrestricted Funds from Research to Prevent Blindness (Emory University). We thank XiangDi Wang and Arthur Centeno for their technical assistance in this project. This study was supported in part by the Emory Integrated Genomics Core (EIGC), which is subsidized by the Emory University School of Medicine and is one of the Emory Integrated Core Facilities.
diff --git a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/cases.rtf b/general/datasets/DoDCMMRPRetMoGene2Ex_0515/cases.rtf
deleted file mode 100644
index 443b427..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Almost all animals are young adults between 60 and 100 days of age (Table 1, minimum age is 60 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
-
-
-
-BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. BXD43 and higher were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. Several strains were specifically excluded from the dataset. For the BXD43 and higher, the DBA/2J parent carried both the Tyrp-1 mutation and the Gpnmb mutation and these two mutations produce pigment dispersion glaucoma. All of the mice carrying these two mutations were not included in the dataset: BXD53, BXD55, BXD62, BXD66, BXD68, BXD74, BXD77, BXD81, BXD88, BXD89, BXD95 and BXD98. In addition BXD 24 was omitted, since it developed a spontaneous mutation, rd16 (Cep290) which resulted in retinal degeneration and was renamed BXD24b/TyJ (ref). Several additional strains were excluded due to abnormally high Gfap levels observed in our Full HEI Retina (April 2010) dataset, these include: BXD32, BXD49, BXD70, BXD83 and BXD89.
diff --git a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/experiment-design.rtf b/general/datasets/DoDCMMRPRetMoGene2Ex_0515/experiment-design.rtf
deleted file mode 100644
index 6256015..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-ll of the procedures used involving mice were approved by IACUC at the Emory University and adhered to the ARVO Statement for the Use of Animals in Research. The Department of Defense (DoD) Congressionally Directed Medical Research Programs (CDMRP) Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array (May 15, 2015). Robust multiarray average (RMA) analysis and scaling were conducted by Arthur Centeno. This data set consists of 52 BXD strains, C57BL/6J, DBA/2J, and an F1 cross between C57BL/6J and DBA/2J. A total of 55 strains were quantified. There is a total of 222 microarrays. All data from each microarray used in this data set is publicly available on GeneNetwork.
-
-These are RMA expression data that have been normalized using what we call a 2z+8 scale, but without corrections for batch effects. The data for each strain were computed as the mean of four samples per strain. The expression values on the log2 scale ranged from 3.81 to 14.25 (10.26 units), a nominal range of approximately 1,000-fold. After taking the log2 of the original non-logged expression estimates, we converted the data within an array to a z-score. We then multiplied the z-score by 2. Finally, we added 8 units to ensure that no values were negative. The result was a scale with the mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A twofold difference in expression is equivalent to roughly 1 unit on this scale. The lowest level of expression was 3.81 (Olfr1186) from the DoD CDMRP (the Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array, May 15, 2015). The highest level of expression was rhodopsin for 17462036 (Rho). The highest single value was 14.25.
diff --git a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/notes.rtf b/general/datasets/DoDCMMRPRetMoGene2Ex_0515/notes.rtf
deleted file mode 100644
index 7f9ba5d..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/notes.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study includes Gene level and Exon level analysis.
diff --git a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/platform.rtf b/general/datasets/DoDCMMRPRetMoGene2Ex_0515/platform.rtf
deleted file mode 100644
index 26dde86..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Affymetrix Mouse Gene 2.0 ST Array: These expression arrays have been designed with a median of 22 unique probes per transcript. Each unique probe is 25 bases in length, which means that the array measures a median of 550 bases per transcript. The arrays provide comprehensive transcriptome coverage with over 30,000 coding and non-coding transcripts. In addition there is coverage for over 600 microRNAs. For some arrays the RNA was pooled from two retinas and for other arrays were run on a single retina. Dr. XiangDi Wang (UTHSC) and Becky King (Emory) were involved in the retinal extractions and isolation of RNA. The Affymetrix arrays were run by two different research cores: the Molecular Resource Center at UTHSC (Dr. William Taylor Director) and the Integrated Genomics Core at Emory University by Robert B Isett (Dr. Michael E. Zwick, Director). In a separate set of experiments we tested a set of arrays from C57BL/6J retinas run at each facility to determine if there were batch effects or other confounding differences in the results. We could not detect any significant difference in the arrays run at UTHSC or at Emory University. Thus, we have included both sets of data into the analysis.
diff --git a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/specifics.rtf b/general/datasets/DoDCMMRPRetMoGene2Ex_0515/specifics.rtf
deleted file mode 100644
index ce43067..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This is the normal exon level dataset
diff --git a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/summary.rtf b/general/datasets/DoDCMMRPRetMoGene2Ex_0515/summary.rtf
deleted file mode 100644
index c79428d..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The DoD (Department of Defense) CDMRP (Congressionally Directed Medical Research Programs) Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array (May 15 2015) The RMA analysis and scaling was conducted by Arthur Centeno. This data set consists of 55 BXD strains, C57BL/6J, DBA/2J, a F1 cross between C57BL/6J and DBA/2J. A total of 58 strains were quantified. There is a total of 222 microarrays.
-
-This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strain was computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.81 to 14.25 (10.26 units), a nominal range of approximately 1,000-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale. The lowest level of expression is 3.81 (Olfr1186) from DoD CDMRP (Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array (May 15 2015) The highest level of expression is Rhodopsin for 17462036 (Rho). Highest single value is about 14.25.
diff --git a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/tissue.rtf b/general/datasets/DoDCMMRPRetMoGene2Ex_0515/tissue.rtf
deleted file mode 100644
index 4f3c475..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2Ex_0515/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Tissue preparation protocol. Mice were killed by rapid cervical dislocation. Retinas were removed immediately and placed in 1 ml of 160 U/ml Ribolock for 1 min at room temperature. The retinas were removed from the eye and placed in Hank’s Balanced Salt solution with RiboLock in 50µl Ribolock (Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) and stored in -80°C. The RNA was isolated using a QiaCube and the in column DNAse procedure. All RNA samples were checked for quality before running microarrays. The samples were analyzed using the Agilent 2100 Bioanalyzer. The RNA integrity values for ranged from 7.0 to 10. Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/DoDCMMRPRetMoGene2_0515/acknowledgment.rtf b/general/datasets/DoDCMMRPRetMoGene2_0515/acknowledgment.rtf
deleted file mode 100644
index 760f47e..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2_0515/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This work was supported by DoD CDMRP Grant W81XWH1210255 from the USA Army Medical Research & Materiel Command and the Telemedicine and Advanced Technology (EEG), NIH Grant R01EY017841 (EEG), Vision Core Grant P30EY006360 (P. Michael Iuvone), and Unrestricted Funds from Research to Prevent Blindness (Emory University). We thank XiangDi Wang and Arthur Centeno for their technical assistance in this project. This study was supported in part by the Emory Integrated Genomics Core (EIGC), which is subsidized by the Emory University School of Medicine and is one of the Emory Integrated Core Facilities.
diff --git a/general/datasets/DoDCMMRPRetMoGene2_0515/cases.rtf b/general/datasets/DoDCMMRPRetMoGene2_0515/cases.rtf
deleted file mode 100644
index 443b427..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2_0515/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Almost all animals are young adults between 60 and 100 days of age (Table 1, minimum age is 60 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
-
-
-
-BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. BXD43 and higher were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. Several strains were specifically excluded from the dataset. For the BXD43 and higher, the DBA/2J parent carried both the Tyrp-1 mutation and the Gpnmb mutation and these two mutations produce pigment dispersion glaucoma. All of the mice carrying these two mutations were not included in the dataset: BXD53, BXD55, BXD62, BXD66, BXD68, BXD74, BXD77, BXD81, BXD88, BXD89, BXD95 and BXD98. In addition BXD 24 was omitted, since it developed a spontaneous mutation, rd16 (Cep290) which resulted in retinal degeneration and was renamed BXD24b/TyJ (ref). Several additional strains were excluded due to abnormally high Gfap levels observed in our Full HEI Retina (April 2010) dataset, these include: BXD32, BXD49, BXD70, BXD83 and BXD89.
diff --git a/general/datasets/DoDCMMRPRetMoGene2_0515/experiment-design.rtf b/general/datasets/DoDCMMRPRetMoGene2_0515/experiment-design.rtf
deleted file mode 100644
index 6256015..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2_0515/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-ll of the procedures used involving mice were approved by IACUC at the Emory University and adhered to the ARVO Statement for the Use of Animals in Research. The Department of Defense (DoD) Congressionally Directed Medical Research Programs (CDMRP) Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array (May 15, 2015). Robust multiarray average (RMA) analysis and scaling were conducted by Arthur Centeno. This data set consists of 52 BXD strains, C57BL/6J, DBA/2J, and an F1 cross between C57BL/6J and DBA/2J. A total of 55 strains were quantified. There is a total of 222 microarrays. All data from each microarray used in this data set is publicly available on GeneNetwork.
-
-These are RMA expression data that have been normalized using what we call a 2z+8 scale, but without corrections for batch effects. The data for each strain were computed as the mean of four samples per strain. The expression values on the log2 scale ranged from 3.81 to 14.25 (10.26 units), a nominal range of approximately 1,000-fold. After taking the log2 of the original non-logged expression estimates, we converted the data within an array to a z-score. We then multiplied the z-score by 2. Finally, we added 8 units to ensure that no values were negative. The result was a scale with the mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A twofold difference in expression is equivalent to roughly 1 unit on this scale. The lowest level of expression was 3.81 (Olfr1186) from the DoD CDMRP (the Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array, May 15, 2015). The highest level of expression was rhodopsin for 17462036 (Rho). The highest single value was 14.25.
diff --git a/general/datasets/DoDCMMRPRetMoGene2_0515/notes.rtf b/general/datasets/DoDCMMRPRetMoGene2_0515/notes.rtf
deleted file mode 100644
index 7f9ba5d..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2_0515/notes.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study includes Gene level and Exon level analysis.
diff --git a/general/datasets/DoDCMMRPRetMoGene2_0515/platform.rtf b/general/datasets/DoDCMMRPRetMoGene2_0515/platform.rtf
deleted file mode 100644
index 26dde86..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2_0515/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Affymetrix Mouse Gene 2.0 ST Array: These expression arrays have been designed with a median of 22 unique probes per transcript. Each unique probe is 25 bases in length, which means that the array measures a median of 550 bases per transcript. The arrays provide comprehensive transcriptome coverage with over 30,000 coding and non-coding transcripts. In addition there is coverage for over 600 microRNAs. For some arrays the RNA was pooled from two retinas and for other arrays were run on a single retina. Dr. XiangDi Wang (UTHSC) and Becky King (Emory) were involved in the retinal extractions and isolation of RNA. The Affymetrix arrays were run by two different research cores: the Molecular Resource Center at UTHSC (Dr. William Taylor Director) and the Integrated Genomics Core at Emory University by Robert B Isett (Dr. Michael E. Zwick, Director). In a separate set of experiments we tested a set of arrays from C57BL/6J retinas run at each facility to determine if there were batch effects or other confounding differences in the results. We could not detect any significant difference in the arrays run at UTHSC or at Emory University. Thus, we have included both sets of data into the analysis.
diff --git a/general/datasets/DoDCMMRPRetMoGene2_0515/summary.rtf b/general/datasets/DoDCMMRPRetMoGene2_0515/summary.rtf
deleted file mode 100644
index c79428d..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2_0515/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The DoD (Department of Defense) CDMRP (Congressionally Directed Medical Research Programs) Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array (May 15 2015) The RMA analysis and scaling was conducted by Arthur Centeno. This data set consists of 55 BXD strains, C57BL/6J, DBA/2J, a F1 cross between C57BL/6J and DBA/2J. A total of 58 strains were quantified. There is a total of 222 microarrays.
-
-This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strain was computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.81 to 14.25 (10.26 units), a nominal range of approximately 1,000-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale. The lowest level of expression is 3.81 (Olfr1186) from DoD CDMRP (Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array (May 15 2015) The highest level of expression is Rhodopsin for 17462036 (Rho). Highest single value is about 14.25.
diff --git a/general/datasets/DoDCMMRPRetMoGene2_0515/tissue.rtf b/general/datasets/DoDCMMRPRetMoGene2_0515/tissue.rtf
deleted file mode 100644
index 4f3c475..0000000
--- a/general/datasets/DoDCMMRPRetMoGene2_0515/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Tissue preparation protocol. Mice were killed by rapid cervical dislocation. Retinas were removed immediately and placed in 1 ml of 160 U/ml Ribolock for 1 min at room temperature. The retinas were removed from the eye and placed in Hank’s Balanced Salt solution with RiboLock in 50µl Ribolock (Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) and stored in -80°C. The RNA was isolated using a QiaCube and the in column DNAse procedure. All RNA samples were checked for quality before running microarrays. The samples were analyzed using the Agilent 2100 Bioanalyzer. The RNA integrity values for ranged from 7.0 to 10. Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/DoDRetBlastvsNormalEx_0416/cases.rtf b/general/datasets/DoDRetBlastvsNormalEx_0416/cases.rtf
deleted file mode 100644
index 34f9530..0000000
--- a/general/datasets/DoDRetBlastvsNormalEx_0416/cases.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Almost all animals are young adults between 60 and 100 days of age (Table 1, minimum age is 60 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
-
-BXD strains:
-
-
- - The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s.
- - In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset.
- - The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
-
diff --git a/general/datasets/DoDRetBlastvsNormalEx_0416/experiment-design.rtf b/general/datasets/DoDRetBlastvsNormalEx_0416/experiment-design.rtf
deleted file mode 100644
index b43e509..0000000
--- a/general/datasets/DoDRetBlastvsNormalEx_0416/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Sample Processing: Dr. XiangDi Wang (UTHSC) and Becky King (Emory) were involved in the retinal extractions and isolation of RNA. The Affymetrix arrays were run by two different research cores: the Molecular Resource Center at UTHSC (Dr. William Taylor Director) and the Integrated Genomics Core at Emory University by Robert B Isett (Dr. Michael E. Zwick, Director). In a separate set of experiments we could not detect any significant difference in the arrays run at UTHSC or at Emory University.
-
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/DoDRetBlastvsNormalEx_0416/notes.rtf b/general/datasets/DoDRetBlastvsNormalEx_0416/notes.rtf
deleted file mode 100644
index cb14c74..0000000
--- a/general/datasets/DoDRetBlastvsNormalEx_0416/notes.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
-
-
- - NEIBank collection of ESTs and SAGE data.
- - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
- - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
- - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
- - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
- - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
-
diff --git a/general/datasets/DoDRetBlastvsNormalEx_0416/platform.rtf b/general/datasets/DoDRetBlastvsNormalEx_0416/platform.rtf
deleted file mode 100644
index cb5e1b8..0000000
--- a/general/datasets/DoDRetBlastvsNormalEx_0416/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Affymetrix Mouse Gene 2.0 ST Array: These expression arrays have been designed with a median of 22 unique probes per transcript. Each unique probe is 25 bases in length, which means that the array measures a median of 550 bases per transcript. The arrays provide comprehensive transcriptome coverage with over 30,000 coding and non-coding transcripts. In addition there is coverage for 592 microRNAs. For some arrays the RNA was pooled from two retinas and for other arrays were run on a single retina.
diff --git a/general/datasets/DoDRetBlastvsNormalEx_0416/specifics.rtf b/general/datasets/DoDRetBlastvsNormalEx_0416/specifics.rtf
deleted file mode 100644
index 7c1a914..0000000
--- a/general/datasets/DoDRetBlastvsNormalEx_0416/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Exon Level
\ No newline at end of file
diff --git a/general/datasets/DoDRetBlastvsNormalEx_0416/summary.rtf b/general/datasets/DoDRetBlastvsNormalEx_0416/summary.rtf
deleted file mode 100644
index b6cf222..0000000
--- a/general/datasets/DoDRetBlastvsNormalEx_0416/summary.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-DoD TATRC Retina Dataset Affymetrix MouseGene 2.0 ST Array (____ 2015) RMA analysis and scaling by Arthur Centeno. This data set consists of 75 BXD strains, C57BL/6J, DBA/2J, both reciprocal F1s, and BALB/cByJ. A total of 80 strains were quantified. The data are now open and available for analysis.
-
-This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strain was computed as the mean of four samples per strain. Expression values on a log2 scale range from 6.25 to 18.08 (11.83 units), a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
-
-The lowest level of expression is 6.254 for ILMN_2747167 (Arhgap11a) from HEI Retina Illumina V6.2 (April 2010) RankInv **. Lowest single data about 5.842. The highest level of expression is 18.077 for ILMN_2516699 (Ubb). Highest single value is about 18.934.
diff --git a/general/datasets/DoDRetBlastvsNormalEx_0416/tissue.rtf b/general/datasets/DoDRetBlastvsNormalEx_0416/tissue.rtf
deleted file mode 100644
index 87eb144..0000000
--- a/general/datasets/DoDRetBlastvsNormalEx_0416/tissue.rtf
+++ /dev/null
@@ -1,13 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in 1 ml of 160 U/ml Ribolock for 1 min at room temperature. Dissecting and preparing eyes for RNA extraction Retinas for RNA removed from the eye and placed in Hank’s Balanced Salt solution with RiboLock (Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) and processed per manufacturer’s instructions (in brief form below).
-
-1) Sample collection for RNA isolation.
-
-2) Quickly remove the retinas with clean curved forceps after cervical dislocation of the mouse.
-
-3) Put each retina in 1 ml of 160 U/ml Ribolock for 1 min in RT.
-
-4) Move the retina to another tube with 50µl Ribolock, store in -80°C.
-
-5) The RNA was isolated using a QiaCube and the in column DNAse procedure.
-
-Quality Control: All RNA samples were checked for quality before running microarrays. The samples were analyzed using the Agilent 2100 Bioanalyzer. The RNA integrity values for each sample are presented in Table 1 below.
diff --git a/general/datasets/DoDRetBlastvsNormal_0416/acknowledgment.rtf b/general/datasets/DoDRetBlastvsNormal_0416/acknowledgment.rtf
deleted file mode 100644
index 13c6b1e..0000000
--- a/general/datasets/DoDRetBlastvsNormal_0416/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/DoDRetBlastvsNormal_0416/cases.rtf b/general/datasets/DoDRetBlastvsNormal_0416/cases.rtf
deleted file mode 100644
index 6b36c70..0000000
--- a/general/datasets/DoDRetBlastvsNormal_0416/cases.rtf
+++ /dev/null
@@ -1,1728 +0,0 @@
-Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
-
-
-
-
-
-
-
-
-
- | Index |
- EIGC ID (LIMS ID) |
- Strain |
- Sex |
- Age at harvest |
- RIN Score |
-
-
- | 1 |
- 602 |
- BXD9 |
- F |
- 133 |
- 9.1 |
-
-
- | 2 |
- 603 |
- BXD9 |
- M |
- 100 |
- 9.5 |
-
-
- | 3 |
- 604 |
- BXD40 |
- F |
- 100 |
- 9.4 |
-
-
- | 4 |
- 605 |
- BXD40 |
- M |
- 100 |
- 9.1 |
-
-
- | 5 |
- 606 |
- BXD48 |
- F |
- 75 |
- 9.1 |
-
-
- | 6 |
- 607 |
- BXD48 |
- M |
- 75 |
- 8.6 |
-
-
- | 7 |
- 608 |
- BXD63 |
- F |
- 75 |
- 9.2 |
-
-
- | 8 |
- 609 |
- BXD63 |
- M |
- 61 |
- 9.4 |
-
-
- | 9 |
- 612 |
- BXD73 |
- M |
- 108 |
- 10 |
-
-
- | 10 |
- 614 |
- BXD87 |
- M |
- 85 |
- 9.2 |
-
-
- | 11 |
- 615 |
- BXD87 |
- F |
- 85 |
- 9.9 |
-
-
- | 12 |
- 616 |
- BXD69 |
- F |
- 76 |
- 9.3 |
-
-
- | 13 |
- 617 |
- BXD69 |
- M |
- 100 |
- 10 |
-
-
- | 14 |
- 618 |
- BXD51 |
- M |
- 82 |
- 8.9 |
-
-
- | 15 |
- 619 |
- BXD92 (BXD65b) |
- M |
- 82 |
- 8.8 |
-
-
- | 16 |
- 620 |
- BXD92 (BXD65b) |
- F |
- 82 |
- 8.8 |
-
-
- | 17 |
- 635 |
- BXD100 |
- M |
- 70 |
- 9 |
-
-
- | 18 |
- 636 |
- BXD100 |
- M |
- 70 |
- 8.8 |
-
-
- | 19 |
- 652 |
- BXD92 (BXD65b) |
- F |
- 64 |
- 9 |
-
-
- | 20 |
- 653 |
- BXD87 |
- F |
- 67 |
- 9.7 |
-
-
- | 21 |
- 654 |
- BXD87 |
- M |
- 67 |
- 8.9 |
-
-
- | 22 |
- 655 |
- BXD63 |
- M |
- 71 |
- 9 |
-
-
- | 23 |
- 660 |
- BXD69 |
- M |
- 97 |
- 10 |
-
-
- | 24 |
- 687 |
- BXD6 |
- M |
- 85 |
- 7.7 |
-
-
- | 25 |
- 688 |
- BXD6 |
- M |
- 85 |
- 9.4 |
-
-
- | 26 |
- 690 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 27 |
- 691 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 28 |
- 692 |
- BXD12 |
- M |
- 83 |
- 10 |
-
-
- | 29 |
- 695 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 30 |
- 696 |
- BXD5 |
- M |
- 77 |
- 10 |
-
-
- | 31 |
- 698 |
- BXD5 |
- F |
- 77 |
- 9.9 |
-
-
- | 32 |
- 699 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 33 |
- 701 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 34 |
- 702 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 35 |
- 705 |
- BXD8 |
- F |
- 77 |
- 9.2 |
-
-
- | 36 |
- 707 |
- BXD15 |
- F |
- 77 |
- 9.4 |
-
-
- | 37 |
- 708 |
- BXD15 |
- F |
- 77 |
- 9.1 |
-
-
- | 38 |
- 710 |
- BXD15 |
- M |
- 77 |
- 9.1 |
-
-
- | 39 |
- 713 |
- BXD22 |
- F |
- 71 |
- 9.5 |
-
-
- | 40 |
- 714 |
- BXD22 |
- F |
- 71 |
- 9.7 |
-
-
- | 41 |
- 716 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 42 |
- 717 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 43 |
- 719 |
- BXD14 |
- F |
- 70 |
- 9.2 |
-
-
- | 44 |
- 722 |
- BXD14 |
- M |
- 70 |
- 8.9 |
-
-
- | 45 |
- 723 |
- BXD14 |
- M |
- 70 |
- 9.2 |
-
-
- | 46 |
- 725 |
- BXD18 |
- F |
- 70 |
- 9 |
-
-
- | 47 |
- 726 |
- BXD18 |
- F |
- 70 |
- 9.1 |
-
-
- | 48 |
- 728 |
- BXD18 |
- M |
- 70 |
- 9.1 |
-
-
- | 49 |
- 729 |
- BXD18 |
- M |
- 70 |
- 9.2 |
-
-
- | 50 |
- 731 |
- BXD19 |
- F |
- 66 |
- 9.3 |
-
-
- | 51 |
- 732 |
- BXD19 |
- F |
- 66 |
- 9.4 |
-
-
- | 52 |
- 734 |
- BXD19 |
- M |
- 66 |
- 9.8 |
-
-
- | 53 |
- 735 |
- BXD19 |
- M |
- 66 |
- 9.4 |
-
-
- | 54 |
- 737 |
- BXD21 |
- F |
- 71 |
- 9.7 |
-
-
- | 55 |
- 738 |
- BXD21 |
- F |
- 71 |
- 9.6 |
-
-
- | 56 |
- 740 |
- BXD21 |
- M |
- 71 |
- 9.1 |
-
-
- | 57 |
- 741 |
- BXD21 |
- M |
- 71 |
- 9.7 |
-
-
- | 58 |
- 743 |
- BXD2 |
- F |
- 70 |
- 8.3 |
-
-
- | 59 |
- 744 |
- BXD2 |
- F |
- 70 |
- 8.6 |
-
-
- | 60 |
- 746 |
- BXD2 |
- M |
- 70 |
- 7.5 |
-
-
- | 61 |
- 747 |
- BXD2 |
- M |
- 77 |
- 8.6 |
-
-
- | 62 |
- 768 |
- BXD48 |
- M |
- 121 |
- 9.4 |
-
-
- | 63 |
- 770 |
- BXD92 (BXD65b) |
- M |
- 65 |
- 10 |
-
-
- | 64 |
- 771 |
- BXD101 |
- F |
- 85 |
- 8.3 |
-
-
- | 65 |
- 772 |
- BXD101 |
- F |
- 85 |
- 9.3 |
-
-
- | 66 |
- 773 |
- BXD101 |
- M |
- 86 |
- 9.5 |
-
-
- | 67 |
- 774 |
- BXD101 |
- M |
- 86 |
- 9.8 |
-
-
- | 68 |
- 775 |
- BXD102 |
- F |
- 66 |
- 9.5 |
-
-
- | 69 |
- 776 |
- BXD102 |
- F |
- 66 |
- 10 |
-
-
- | 70 |
- 777 |
- BXD102 |
- M |
- 84 |
- 9.6 |
-
-
- | 71 |
- 787 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 72 |
- 788 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 73 |
- 789 |
- BXD63 |
- F |
- 115 |
- 9.7 |
-
-
- | 74 |
- 790 |
- BXD100 |
- F |
- 72 |
- 9.8 |
-
-
- | 75 |
- 791 |
- BXD100 |
- F |
- 72 |
- 10 |
-
-
- | 76 |
- 818 |
- BXD51 |
- F |
- 77 |
- 9.7 |
-
-
- | 77 |
- 819 |
- BXD51 |
- F |
- 77 |
- 9.6 |
-
-
- | 78 |
- 820 |
- BXD51 |
- M |
- 72 |
- 9.7 |
-
-
- | 79 |
- 821 |
- BXD65 |
- M |
- 72 |
- 9.6 |
-
-
- | 80 |
- 822 |
- BXD65 |
- M |
- 65 |
- 9.5 |
-
-
- | 81 |
- 825 |
- BXD65 |
- F |
- 72 |
- 9.5 |
-
-
- | 82 |
- 827 |
- BXD86 |
- M |
- 69 |
- 9.1 |
-
-
- | 83 |
- 828 |
- BXD86 |
- M |
- 69 |
- 9.4 |
-
-
- | 84 |
- 829 |
- BXD90 |
- F |
- 69 |
- 9.6 |
-
-
- | 85 |
- 831 |
- BXD9 |
- M |
- 127 |
- 9.7 |
-
-
- | 86 |
- 832 |
- BXD39 |
- F |
- 99 |
- 9.4 |
-
-
- | 87 |
- 833 |
- BXD39 |
- F |
- 107 |
- 9.3 |
-
-
- | 88 |
- 834 |
- BXD60 |
- F |
- 107 |
- 9.5 |
-
-
- | 89 |
- 836 |
- BXD84 |
- M |
- 103 |
- 9.7 |
-
-
- | 90 |
- 846 |
- BXD39 |
- M |
- 63 |
- 9.7 |
-
-
- | 91 |
- 847 |
- BXD39 |
- M |
- 63 |
- 9.8 |
-
-
- | 92 |
- 849 |
- BXD20 |
- F |
- 70 |
- 10 |
-
-
- | 93 |
- 850 |
- BXD20 |
- M |
- 70 |
- 10 |
-
-
- | 94 |
- 851 |
- BXD20 |
- * |
- 70 |
- 9.5 |
-
-
- | 95 |
- 855 |
- DBA/2J |
- F |
- 78 |
- 9.7 |
-
-
- | 96 |
- 856 |
- DBA/2J |
- F |
- 78 |
- 10 |
-
-
- | 97 |
- 857 |
- DBA/2J |
- M |
- 78 |
- 10 |
-
-
- | 98 |
- 858 |
- DBA/2J |
- M |
- 78 |
- 9.9 |
-
-
- | 99 |
- 859 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 100 |
- 860 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 101 |
- 861 |
- C57BL/6J |
- M |
- 78 |
- 10 |
-
-
- | 102 |
- 862 |
- C57BL/6J |
- M |
- 78 |
- 9.6 |
-
-
- | 103 |
- EGE10907-0172_890_20844 |
- BXD28 |
- M |
- 75 |
- 10 |
-
-
- | 104 |
- EGE10907-0173_891_20845 |
- BXD28 |
- M |
- 75 |
- 9.7 |
-
-
- | 105 |
- EGE10907-0174_892_20846 |
- BXD28 |
- F |
- 75 |
- 9.7 |
-
-
- | 106 |
- EGE10907-0176_895_20848 |
- BXD33 |
- M |
- 75 |
- 9.88 |
-
-
- | 107 |
- EGE10907-0177_896_20849 |
- BXD33 |
- F |
- 75 |
- 10 |
-
-
- | 108 |
- EGE10907-0178_897_20850 |
- BXD33 |
- F |
- 75 |
- 9.4 |
-
-
- | 109 |
- EGE10907-0179_898_20851 |
- BXD36 |
- M |
- 75 |
- 9.4 |
-
-
- | 110 |
- EGE10907-0180_899_20852 |
- BXD36 |
- F |
- 75 |
- 9.5 |
-
-
- | 111 |
- EGE10907-0181_900_20853 |
- BXD36 |
- F |
- 75 |
- 9.1 |
-
-
- | 112 |
- EGE10907-0182_910_20854 |
- BXD27 |
- M |
- 70 |
- 9.7 |
-
-
- | 113 |
- EGE10907-0183_990_20855 |
- BXD9 |
- F |
- 98 |
- 9.4 |
-
-
- | 114 |
- EGE10907-0184_991_20856 |
- BXD16 |
- F |
- 113 |
- 10 |
-
-
- | 115 |
- EGE10907-0185_992_20857 |
- BXD16 |
- M |
- 113 |
- 9 |
-
-
- | 116 |
- EGE10907-0186_993_20858 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 117 |
- EGE10907-0187_994_20859 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 118 |
- EGE10907-0188_996_20860 |
- BXD48 |
- F |
- 98 |
- 9.4 |
-
-
- | 119 |
- EGE10907-0189_997_20861 |
- BXD73 |
- M |
- 106 |
- 10 |
-
-
- | 120 |
- EGE10907-0190_999_20862 |
- BXD11 |
- F |
- 121 |
- 9.6 |
-
-
- | 121 |
- EGE10907-0191_100_20863 |
- BXD11 |
- F |
- 121 |
- 9.9 |
-
-
- | 122 |
- EGE10907-0192_1010_21276 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 123 |
- EGE10907-0193_1011_21277 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 124 |
- EGE10907-0194_1012_21278 |
- BXD16 |
- F |
- 65 |
- 10 |
-
-
- | 125 |
- EGE10907-0195_1015_21279 |
- BXD16 |
- M |
- 65 |
- 10 |
-
-
- | 126 |
- EGE10907-0196_1019_21280 |
- BXD33 |
- M |
- 75 |
- 10 |
-
-
- | 127 |
- EGE10907-0197_1020_21281 |
- BXD36 |
- M |
- 78 |
- 10 |
-
-
- | 128 |
- EGE10907-0198_1021_21282 |
- BXD38 |
- F |
- 70 |
- 9.8 |
-
-
- | 129 |
- EGE10907-0199_1022_21283 |
- BXD38 |
- F |
- 70 |
- 10 |
-
-
- | 130 |
- EGE10907-0200_1023_21284 |
- BXD38 |
- M |
- 70 |
- 9.7 |
-
-
- | 131 |
- EGE10907-0201_1047_21285 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 132 |
- EGE10907-0202_1048_21286 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 133 |
- EGE10907-0203_1049_21287 |
- BXD38 |
- M |
- 77 |
- 10 |
-
-
- | 134 |
- EGE10907-0204_1050_21288 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 135 |
- EGE10907-0205_1051_21289 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 136 |
- EGE10907-0206_1052_21290 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 137 |
- EGE10907-0207_1053_21291 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 138 |
- EGE10907-0208_1054_21292 |
- BXD90 |
- F |
- 71 |
- 10 |
-
-
- | 139 |
- EGE10907-0209_1055_21293 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 140 |
- EGE10907-0210_1056_21294 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 141 |
- EGE10907-0211_1148_21295 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 142 |
- EGE10907-0212_1149_21296 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 143 |
- EGE10907-0213_1150_21297 |
- BXD31 |
- M |
- 90 |
- 10 |
-
-
- | 144 |
- EGE10907-0214_1151_21298 |
- BXD31 |
- M |
- 90 |
- 9.9 |
-
-
- | 145 |
- EGE10907-0215_1152_21299 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 146 |
- EGE10907-0216_21429 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 147 |
- EGE10907-0217_21430 |
- BXD42 |
- M |
- 83 |
- 10 |
-
-
- | 148 |
- EGE10907-0218_21431 |
- BXD42 |
- M |
- 83 |
- 9.3 |
-
-
- | 149 |
- EGE10907-0219_21432 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 150 |
- EGE10907-0220_21433 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 151 |
- EGE10907-0221_21434 |
- BXD50 |
- F |
- 92 |
- 10 |
-
-
- | 152 |
- EGE10907-0222_21435 |
- BXD1 |
- M |
- 73 |
- 9.6 |
-
-
- | 153 |
- EGE10907-0223_21436 |
- BXD13 |
- F |
- 71 |
- 9.7 |
-
-
- | 154 |
- EGE10907-0224_21437 |
- BXD1 |
- M |
- 71 |
- 9.5 |
-
-
- | 155 |
- EGE10907-0225_21438 |
- BXD13 |
- F |
- 71 |
- 9.6 |
-
-
- | 156 |
- EGE10907-0226_21439 |
- BXD43 |
- F |
- 85 |
- 10 |
-
-
- | 157 |
- EGE10907-0227_21452 |
- BXD43 |
- F |
- 85 |
- 9.6 |
-
-
- | 158 |
- EGE10907-0229_21442 |
- BXD43 |
- M |
- 85 |
- 8.2 |
-
-
- | 159 |
- EGE10907-0230_21443 |
- BXD50 |
- M |
- 69 |
- 9.4 |
-
-
- | 160 |
- EGE10907-0231_21444 |
- BXD1 |
- F |
- 68 |
- 9.4 |
-
-
- | 161 |
- EGE10907-0232_21445 |
- BXD1 |
- F |
- 68 |
- 9.6 |
-
-
- | 162 |
- EGE10907-0233_21446 |
- BXD29 |
- M |
- 65 |
- 9.5 |
-
-
- | 163 |
- EGE10907-0234_21447 |
- BXD29 |
- M |
- 65 |
- 10 |
-
-
- | 164 |
- EGE10907-0235_21448 |
- BXD75 |
- F |
- 68 |
- 10 |
-
-
- | 165 |
- EGE10907-0236_21449 |
- BXD75 |
- M |
- 68 |
- 10 |
-
-
- | 166 |
- EGE10907-0237_21450 |
- BXD96 |
- F |
- 67 |
- 9.9 |
-
-
- | 167 |
- EGE10907-0238_21931 |
- BXD99 |
- M |
- 71 |
- 7.9 |
-
-
- | 168 |
- EGE10907-0239_21932 |
- BXD99 |
- M |
- 71 |
- 9.7 |
-
-
- | 169 |
- EGE10907-0240_21933 |
- BXD67 |
- F |
- 68 |
- 8.8 |
-
-
- | 170 |
- EGE10907-0241_21934 |
- BXD67 |
- F |
- 68 |
- 8.5 |
-
-
- | 171 |
- EGE10907-0242_21935 |
- BXD67 |
- M |
- 68 |
- 9.5 |
-
-
- | 172 |
- EGE10907-0243_21936 |
- BXD67 |
- M |
- 68 |
- 9.6 |
-
-
- | 173 |
- EGE10907-0244_21937 |
- BXD6 |
- F |
- 68 |
- 9.6 |
-
-
- | 174 |
- EGE10907-0245_21938 |
- BXD12 |
- M |
- 82 |
- 9.5 |
-
-
- | 175 |
- EGE10907-0246_21939 |
- BXD60 |
- F |
- 72 |
- 9.6 |
-
-
- | 176 |
- EGE10907-0247_21940 |
- BXD65 |
- F |
- 75 |
- 9.1 |
-
-
- | 177 |
- EGE10907-0248_21941 |
- BXD75 |
- F |
- 69 |
- 8.8 |
-
-
- | 178 |
- EGE10907-0249_21942_(MoGene-2_0-st) |
- BXD75 |
- M |
- 69 |
- 9.2 |
-
-
- | 179 |
- EGE10907-0250_21943 |
- BXD8 |
- F |
- 97 |
- 9.1 |
-
-
- | 180 |
- EGE10907-0251_21944 |
- BXD85 |
- F |
- 79 |
- 8.6 |
-
-
- | 181 |
- EGE10907-0252_21945 |
- BXD85 |
- M |
- 79 |
- 9.1 |
-
-
- | 182 |
- EGE10907-0253_21946 |
- BXD85 |
- M |
- 79 |
- 9.4 |
-
-
- | 183 |
- EGE10907-0254_21947 |
- BXD102 |
- M |
- 94 |
- 8.6 |
-
-
- | 184 |
- EGE10907-0255_21948 |
- BXD99 |
- F |
- 83 |
- 9 |
-
-
- | 185 |
- EGE10907-0256_21949 |
- BXD69 |
- F |
- 68 |
- 9 |
-
-
- | 186 |
- EGE10907-0257_21950 |
- BXD84 |
- F |
- 74 |
- 9.5 |
-
-
- | 187 |
- EGE10907-0258_21951 |
- BXD84 |
- F |
- 74 |
- 9.4 |
-
-
- | 188 |
- EGE10907-0259_21952 |
- BXD84 |
- M |
- 74 |
- 8.6 |
-
-
- | 189 |
- EGE10907-0260_21451 |
- BXD96 |
- M |
- 67 |
- 9.2 |
-
-
- | 190 |
- EGE10907-0261_21452 |
- BXD99 |
- F |
- 71 |
- 8.9 |
-
-
- | 191 |
- EGE10907-0262_21931 |
- BXD6 |
- F |
- 66 |
- 9.4 |
-
-
- | 192 |
- EGE10907-0263_21932 |
- BXD14 |
- F |
- 69 |
- 8.5 |
-
-
- | 193 |
- EGE10907-0264_21933 |
- BXD34 |
- M |
- 79 |
- 9.1 |
-
-
- | 194 |
- EGE10907-0265_21934 |
- BXD34 |
- M |
- 79 |
- 9.9 |
-
-
- | 195 |
- EGE10907-0266_21935 |
- BXD40 |
- F |
- 75 |
- 9.6 |
-
-
- | 196 |
- EGE10907-0267_21936 |
- BXD40 |
- M |
- 78 |
- 9.7 |
-
-
- | 197 |
- EGE10907-0268_21937 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 198 |
- EGE10907-0269_21938 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 199 |
- EGE10907-0270_21939 |
- BXD56 |
- M |
- 72 |
- 9.6 |
-
-
- | 200 |
- EGE10907-0271_21940 |
- BXD56 |
- M |
- 72 |
- 9.4 |
-
-
- | 201 |
- EGE10907-0272_21941 |
- BXD71 |
- F |
- 72 |
- 9.9 |
-
-
- | 202 |
- EGE10907-0273_21942 |
- BXD71 |
- F |
- 75 |
- 9.4 |
-
-
- | 203 |
- EGE10907-0274_21943 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 204 |
- EGE10907-0275_21944 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 205 |
- EGE10907-0276_21945 |
- BXD27 |
- M |
- 65 |
- 10 |
-
-
- | 206 |
- EGE10907-0277_21946 |
- BXD15 |
- M |
- 65 |
- 10 |
-
-
- | 207 |
- EGE10907-0278_21947 |
- BXD20 |
- F |
- 125 |
- 10 |
-
-
- | 208 |
- EGE10907-0279_21948 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 209 |
- EGE10907-0280_21949 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 210 |
- EGE10907-0281_21950 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 211 |
- EGE10907-0282_21951 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 212 |
- EGE10907-0283_21952 |
- BXD85 |
- F |
- 87 |
- 10 |
-
-
- | 213 |
- EGE10907-0284_21451 |
- BXD43 |
- M |
- 75 |
- 9.8 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/DoDRetBlastvsNormal_0416/platform.rtf b/general/datasets/DoDRetBlastvsNormal_0416/platform.rtf
deleted file mode 100644
index 19fc38c..0000000
--- a/general/datasets/DoDRetBlastvsNormal_0416/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/DoDRetBlastvsNormal_0416/processing.rtf b/general/datasets/DoDRetBlastvsNormal_0416/processing.rtf
deleted file mode 100644
index a7b767e..0000000
--- a/general/datasets/DoDRetBlastvsNormal_0416/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/DoDRetBlastvsNormal_0416/specifics.rtf b/general/datasets/DoDRetBlastvsNormal_0416/specifics.rtf
deleted file mode 100644
index 0d1a5a5..0000000
--- a/general/datasets/DoDRetBlastvsNormal_0416/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This is a subtractive dataset. The Normal retina dataset was subtracted from the blast data set probe by probe to create a data set of the changes occurring following a blast injury to the eye. This data set can be used to define gene changes following blast. It is not compatible with most of the bioinformatic tools available on GeneNetwork.
\ No newline at end of file
diff --git a/general/datasets/DoDRetBlastvsNormal_0416/summary.rtf b/general/datasets/DoDRetBlastvsNormal_0416/summary.rtf
deleted file mode 100644
index 96a87e5..0000000
--- a/general/datasets/DoDRetBlastvsNormal_0416/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/DoDRetBlastvsNormal_0416/tissue.rtf b/general/datasets/DoDRetBlastvsNormal_0416/tissue.rtf
deleted file mode 100644
index 056d7eb..0000000
--- a/general/datasets/DoDRetBlastvsNormal_0416/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/DoDTATRCRetBLExMoGene2_1213/acknowledgment.rtf b/general/datasets/DoDTATRCRetBLExMoGene2_1213/acknowledgment.rtf
deleted file mode 100644
index 13c6b1e..0000000
--- a/general/datasets/DoDTATRCRetBLExMoGene2_1213/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/DoDTATRCRetBLExMoGene2_1213/cases.rtf b/general/datasets/DoDTATRCRetBLExMoGene2_1213/cases.rtf
deleted file mode 100644
index 6b36c70..0000000
--- a/general/datasets/DoDTATRCRetBLExMoGene2_1213/cases.rtf
+++ /dev/null
@@ -1,1728 +0,0 @@
-Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
-
-
-
-
-
-
-
-
-
- | Index |
- EIGC ID (LIMS ID) |
- Strain |
- Sex |
- Age at harvest |
- RIN Score |
-
-
- | 1 |
- 602 |
- BXD9 |
- F |
- 133 |
- 9.1 |
-
-
- | 2 |
- 603 |
- BXD9 |
- M |
- 100 |
- 9.5 |
-
-
- | 3 |
- 604 |
- BXD40 |
- F |
- 100 |
- 9.4 |
-
-
- | 4 |
- 605 |
- BXD40 |
- M |
- 100 |
- 9.1 |
-
-
- | 5 |
- 606 |
- BXD48 |
- F |
- 75 |
- 9.1 |
-
-
- | 6 |
- 607 |
- BXD48 |
- M |
- 75 |
- 8.6 |
-
-
- | 7 |
- 608 |
- BXD63 |
- F |
- 75 |
- 9.2 |
-
-
- | 8 |
- 609 |
- BXD63 |
- M |
- 61 |
- 9.4 |
-
-
- | 9 |
- 612 |
- BXD73 |
- M |
- 108 |
- 10 |
-
-
- | 10 |
- 614 |
- BXD87 |
- M |
- 85 |
- 9.2 |
-
-
- | 11 |
- 615 |
- BXD87 |
- F |
- 85 |
- 9.9 |
-
-
- | 12 |
- 616 |
- BXD69 |
- F |
- 76 |
- 9.3 |
-
-
- | 13 |
- 617 |
- BXD69 |
- M |
- 100 |
- 10 |
-
-
- | 14 |
- 618 |
- BXD51 |
- M |
- 82 |
- 8.9 |
-
-
- | 15 |
- 619 |
- BXD92 (BXD65b) |
- M |
- 82 |
- 8.8 |
-
-
- | 16 |
- 620 |
- BXD92 (BXD65b) |
- F |
- 82 |
- 8.8 |
-
-
- | 17 |
- 635 |
- BXD100 |
- M |
- 70 |
- 9 |
-
-
- | 18 |
- 636 |
- BXD100 |
- M |
- 70 |
- 8.8 |
-
-
- | 19 |
- 652 |
- BXD92 (BXD65b) |
- F |
- 64 |
- 9 |
-
-
- | 20 |
- 653 |
- BXD87 |
- F |
- 67 |
- 9.7 |
-
-
- | 21 |
- 654 |
- BXD87 |
- M |
- 67 |
- 8.9 |
-
-
- | 22 |
- 655 |
- BXD63 |
- M |
- 71 |
- 9 |
-
-
- | 23 |
- 660 |
- BXD69 |
- M |
- 97 |
- 10 |
-
-
- | 24 |
- 687 |
- BXD6 |
- M |
- 85 |
- 7.7 |
-
-
- | 25 |
- 688 |
- BXD6 |
- M |
- 85 |
- 9.4 |
-
-
- | 26 |
- 690 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 27 |
- 691 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 28 |
- 692 |
- BXD12 |
- M |
- 83 |
- 10 |
-
-
- | 29 |
- 695 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 30 |
- 696 |
- BXD5 |
- M |
- 77 |
- 10 |
-
-
- | 31 |
- 698 |
- BXD5 |
- F |
- 77 |
- 9.9 |
-
-
- | 32 |
- 699 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 33 |
- 701 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 34 |
- 702 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 35 |
- 705 |
- BXD8 |
- F |
- 77 |
- 9.2 |
-
-
- | 36 |
- 707 |
- BXD15 |
- F |
- 77 |
- 9.4 |
-
-
- | 37 |
- 708 |
- BXD15 |
- F |
- 77 |
- 9.1 |
-
-
- | 38 |
- 710 |
- BXD15 |
- M |
- 77 |
- 9.1 |
-
-
- | 39 |
- 713 |
- BXD22 |
- F |
- 71 |
- 9.5 |
-
-
- | 40 |
- 714 |
- BXD22 |
- F |
- 71 |
- 9.7 |
-
-
- | 41 |
- 716 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 42 |
- 717 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 43 |
- 719 |
- BXD14 |
- F |
- 70 |
- 9.2 |
-
-
- | 44 |
- 722 |
- BXD14 |
- M |
- 70 |
- 8.9 |
-
-
- | 45 |
- 723 |
- BXD14 |
- M |
- 70 |
- 9.2 |
-
-
- | 46 |
- 725 |
- BXD18 |
- F |
- 70 |
- 9 |
-
-
- | 47 |
- 726 |
- BXD18 |
- F |
- 70 |
- 9.1 |
-
-
- | 48 |
- 728 |
- BXD18 |
- M |
- 70 |
- 9.1 |
-
-
- | 49 |
- 729 |
- BXD18 |
- M |
- 70 |
- 9.2 |
-
-
- | 50 |
- 731 |
- BXD19 |
- F |
- 66 |
- 9.3 |
-
-
- | 51 |
- 732 |
- BXD19 |
- F |
- 66 |
- 9.4 |
-
-
- | 52 |
- 734 |
- BXD19 |
- M |
- 66 |
- 9.8 |
-
-
- | 53 |
- 735 |
- BXD19 |
- M |
- 66 |
- 9.4 |
-
-
- | 54 |
- 737 |
- BXD21 |
- F |
- 71 |
- 9.7 |
-
-
- | 55 |
- 738 |
- BXD21 |
- F |
- 71 |
- 9.6 |
-
-
- | 56 |
- 740 |
- BXD21 |
- M |
- 71 |
- 9.1 |
-
-
- | 57 |
- 741 |
- BXD21 |
- M |
- 71 |
- 9.7 |
-
-
- | 58 |
- 743 |
- BXD2 |
- F |
- 70 |
- 8.3 |
-
-
- | 59 |
- 744 |
- BXD2 |
- F |
- 70 |
- 8.6 |
-
-
- | 60 |
- 746 |
- BXD2 |
- M |
- 70 |
- 7.5 |
-
-
- | 61 |
- 747 |
- BXD2 |
- M |
- 77 |
- 8.6 |
-
-
- | 62 |
- 768 |
- BXD48 |
- M |
- 121 |
- 9.4 |
-
-
- | 63 |
- 770 |
- BXD92 (BXD65b) |
- M |
- 65 |
- 10 |
-
-
- | 64 |
- 771 |
- BXD101 |
- F |
- 85 |
- 8.3 |
-
-
- | 65 |
- 772 |
- BXD101 |
- F |
- 85 |
- 9.3 |
-
-
- | 66 |
- 773 |
- BXD101 |
- M |
- 86 |
- 9.5 |
-
-
- | 67 |
- 774 |
- BXD101 |
- M |
- 86 |
- 9.8 |
-
-
- | 68 |
- 775 |
- BXD102 |
- F |
- 66 |
- 9.5 |
-
-
- | 69 |
- 776 |
- BXD102 |
- F |
- 66 |
- 10 |
-
-
- | 70 |
- 777 |
- BXD102 |
- M |
- 84 |
- 9.6 |
-
-
- | 71 |
- 787 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 72 |
- 788 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 73 |
- 789 |
- BXD63 |
- F |
- 115 |
- 9.7 |
-
-
- | 74 |
- 790 |
- BXD100 |
- F |
- 72 |
- 9.8 |
-
-
- | 75 |
- 791 |
- BXD100 |
- F |
- 72 |
- 10 |
-
-
- | 76 |
- 818 |
- BXD51 |
- F |
- 77 |
- 9.7 |
-
-
- | 77 |
- 819 |
- BXD51 |
- F |
- 77 |
- 9.6 |
-
-
- | 78 |
- 820 |
- BXD51 |
- M |
- 72 |
- 9.7 |
-
-
- | 79 |
- 821 |
- BXD65 |
- M |
- 72 |
- 9.6 |
-
-
- | 80 |
- 822 |
- BXD65 |
- M |
- 65 |
- 9.5 |
-
-
- | 81 |
- 825 |
- BXD65 |
- F |
- 72 |
- 9.5 |
-
-
- | 82 |
- 827 |
- BXD86 |
- M |
- 69 |
- 9.1 |
-
-
- | 83 |
- 828 |
- BXD86 |
- M |
- 69 |
- 9.4 |
-
-
- | 84 |
- 829 |
- BXD90 |
- F |
- 69 |
- 9.6 |
-
-
- | 85 |
- 831 |
- BXD9 |
- M |
- 127 |
- 9.7 |
-
-
- | 86 |
- 832 |
- BXD39 |
- F |
- 99 |
- 9.4 |
-
-
- | 87 |
- 833 |
- BXD39 |
- F |
- 107 |
- 9.3 |
-
-
- | 88 |
- 834 |
- BXD60 |
- F |
- 107 |
- 9.5 |
-
-
- | 89 |
- 836 |
- BXD84 |
- M |
- 103 |
- 9.7 |
-
-
- | 90 |
- 846 |
- BXD39 |
- M |
- 63 |
- 9.7 |
-
-
- | 91 |
- 847 |
- BXD39 |
- M |
- 63 |
- 9.8 |
-
-
- | 92 |
- 849 |
- BXD20 |
- F |
- 70 |
- 10 |
-
-
- | 93 |
- 850 |
- BXD20 |
- M |
- 70 |
- 10 |
-
-
- | 94 |
- 851 |
- BXD20 |
- * |
- 70 |
- 9.5 |
-
-
- | 95 |
- 855 |
- DBA/2J |
- F |
- 78 |
- 9.7 |
-
-
- | 96 |
- 856 |
- DBA/2J |
- F |
- 78 |
- 10 |
-
-
- | 97 |
- 857 |
- DBA/2J |
- M |
- 78 |
- 10 |
-
-
- | 98 |
- 858 |
- DBA/2J |
- M |
- 78 |
- 9.9 |
-
-
- | 99 |
- 859 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 100 |
- 860 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 101 |
- 861 |
- C57BL/6J |
- M |
- 78 |
- 10 |
-
-
- | 102 |
- 862 |
- C57BL/6J |
- M |
- 78 |
- 9.6 |
-
-
- | 103 |
- EGE10907-0172_890_20844 |
- BXD28 |
- M |
- 75 |
- 10 |
-
-
- | 104 |
- EGE10907-0173_891_20845 |
- BXD28 |
- M |
- 75 |
- 9.7 |
-
-
- | 105 |
- EGE10907-0174_892_20846 |
- BXD28 |
- F |
- 75 |
- 9.7 |
-
-
- | 106 |
- EGE10907-0176_895_20848 |
- BXD33 |
- M |
- 75 |
- 9.88 |
-
-
- | 107 |
- EGE10907-0177_896_20849 |
- BXD33 |
- F |
- 75 |
- 10 |
-
-
- | 108 |
- EGE10907-0178_897_20850 |
- BXD33 |
- F |
- 75 |
- 9.4 |
-
-
- | 109 |
- EGE10907-0179_898_20851 |
- BXD36 |
- M |
- 75 |
- 9.4 |
-
-
- | 110 |
- EGE10907-0180_899_20852 |
- BXD36 |
- F |
- 75 |
- 9.5 |
-
-
- | 111 |
- EGE10907-0181_900_20853 |
- BXD36 |
- F |
- 75 |
- 9.1 |
-
-
- | 112 |
- EGE10907-0182_910_20854 |
- BXD27 |
- M |
- 70 |
- 9.7 |
-
-
- | 113 |
- EGE10907-0183_990_20855 |
- BXD9 |
- F |
- 98 |
- 9.4 |
-
-
- | 114 |
- EGE10907-0184_991_20856 |
- BXD16 |
- F |
- 113 |
- 10 |
-
-
- | 115 |
- EGE10907-0185_992_20857 |
- BXD16 |
- M |
- 113 |
- 9 |
-
-
- | 116 |
- EGE10907-0186_993_20858 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 117 |
- EGE10907-0187_994_20859 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 118 |
- EGE10907-0188_996_20860 |
- BXD48 |
- F |
- 98 |
- 9.4 |
-
-
- | 119 |
- EGE10907-0189_997_20861 |
- BXD73 |
- M |
- 106 |
- 10 |
-
-
- | 120 |
- EGE10907-0190_999_20862 |
- BXD11 |
- F |
- 121 |
- 9.6 |
-
-
- | 121 |
- EGE10907-0191_100_20863 |
- BXD11 |
- F |
- 121 |
- 9.9 |
-
-
- | 122 |
- EGE10907-0192_1010_21276 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 123 |
- EGE10907-0193_1011_21277 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 124 |
- EGE10907-0194_1012_21278 |
- BXD16 |
- F |
- 65 |
- 10 |
-
-
- | 125 |
- EGE10907-0195_1015_21279 |
- BXD16 |
- M |
- 65 |
- 10 |
-
-
- | 126 |
- EGE10907-0196_1019_21280 |
- BXD33 |
- M |
- 75 |
- 10 |
-
-
- | 127 |
- EGE10907-0197_1020_21281 |
- BXD36 |
- M |
- 78 |
- 10 |
-
-
- | 128 |
- EGE10907-0198_1021_21282 |
- BXD38 |
- F |
- 70 |
- 9.8 |
-
-
- | 129 |
- EGE10907-0199_1022_21283 |
- BXD38 |
- F |
- 70 |
- 10 |
-
-
- | 130 |
- EGE10907-0200_1023_21284 |
- BXD38 |
- M |
- 70 |
- 9.7 |
-
-
- | 131 |
- EGE10907-0201_1047_21285 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 132 |
- EGE10907-0202_1048_21286 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 133 |
- EGE10907-0203_1049_21287 |
- BXD38 |
- M |
- 77 |
- 10 |
-
-
- | 134 |
- EGE10907-0204_1050_21288 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 135 |
- EGE10907-0205_1051_21289 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 136 |
- EGE10907-0206_1052_21290 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 137 |
- EGE10907-0207_1053_21291 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 138 |
- EGE10907-0208_1054_21292 |
- BXD90 |
- F |
- 71 |
- 10 |
-
-
- | 139 |
- EGE10907-0209_1055_21293 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 140 |
- EGE10907-0210_1056_21294 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 141 |
- EGE10907-0211_1148_21295 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 142 |
- EGE10907-0212_1149_21296 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 143 |
- EGE10907-0213_1150_21297 |
- BXD31 |
- M |
- 90 |
- 10 |
-
-
- | 144 |
- EGE10907-0214_1151_21298 |
- BXD31 |
- M |
- 90 |
- 9.9 |
-
-
- | 145 |
- EGE10907-0215_1152_21299 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 146 |
- EGE10907-0216_21429 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 147 |
- EGE10907-0217_21430 |
- BXD42 |
- M |
- 83 |
- 10 |
-
-
- | 148 |
- EGE10907-0218_21431 |
- BXD42 |
- M |
- 83 |
- 9.3 |
-
-
- | 149 |
- EGE10907-0219_21432 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 150 |
- EGE10907-0220_21433 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 151 |
- EGE10907-0221_21434 |
- BXD50 |
- F |
- 92 |
- 10 |
-
-
- | 152 |
- EGE10907-0222_21435 |
- BXD1 |
- M |
- 73 |
- 9.6 |
-
-
- | 153 |
- EGE10907-0223_21436 |
- BXD13 |
- F |
- 71 |
- 9.7 |
-
-
- | 154 |
- EGE10907-0224_21437 |
- BXD1 |
- M |
- 71 |
- 9.5 |
-
-
- | 155 |
- EGE10907-0225_21438 |
- BXD13 |
- F |
- 71 |
- 9.6 |
-
-
- | 156 |
- EGE10907-0226_21439 |
- BXD43 |
- F |
- 85 |
- 10 |
-
-
- | 157 |
- EGE10907-0227_21452 |
- BXD43 |
- F |
- 85 |
- 9.6 |
-
-
- | 158 |
- EGE10907-0229_21442 |
- BXD43 |
- M |
- 85 |
- 8.2 |
-
-
- | 159 |
- EGE10907-0230_21443 |
- BXD50 |
- M |
- 69 |
- 9.4 |
-
-
- | 160 |
- EGE10907-0231_21444 |
- BXD1 |
- F |
- 68 |
- 9.4 |
-
-
- | 161 |
- EGE10907-0232_21445 |
- BXD1 |
- F |
- 68 |
- 9.6 |
-
-
- | 162 |
- EGE10907-0233_21446 |
- BXD29 |
- M |
- 65 |
- 9.5 |
-
-
- | 163 |
- EGE10907-0234_21447 |
- BXD29 |
- M |
- 65 |
- 10 |
-
-
- | 164 |
- EGE10907-0235_21448 |
- BXD75 |
- F |
- 68 |
- 10 |
-
-
- | 165 |
- EGE10907-0236_21449 |
- BXD75 |
- M |
- 68 |
- 10 |
-
-
- | 166 |
- EGE10907-0237_21450 |
- BXD96 |
- F |
- 67 |
- 9.9 |
-
-
- | 167 |
- EGE10907-0238_21931 |
- BXD99 |
- M |
- 71 |
- 7.9 |
-
-
- | 168 |
- EGE10907-0239_21932 |
- BXD99 |
- M |
- 71 |
- 9.7 |
-
-
- | 169 |
- EGE10907-0240_21933 |
- BXD67 |
- F |
- 68 |
- 8.8 |
-
-
- | 170 |
- EGE10907-0241_21934 |
- BXD67 |
- F |
- 68 |
- 8.5 |
-
-
- | 171 |
- EGE10907-0242_21935 |
- BXD67 |
- M |
- 68 |
- 9.5 |
-
-
- | 172 |
- EGE10907-0243_21936 |
- BXD67 |
- M |
- 68 |
- 9.6 |
-
-
- | 173 |
- EGE10907-0244_21937 |
- BXD6 |
- F |
- 68 |
- 9.6 |
-
-
- | 174 |
- EGE10907-0245_21938 |
- BXD12 |
- M |
- 82 |
- 9.5 |
-
-
- | 175 |
- EGE10907-0246_21939 |
- BXD60 |
- F |
- 72 |
- 9.6 |
-
-
- | 176 |
- EGE10907-0247_21940 |
- BXD65 |
- F |
- 75 |
- 9.1 |
-
-
- | 177 |
- EGE10907-0248_21941 |
- BXD75 |
- F |
- 69 |
- 8.8 |
-
-
- | 178 |
- EGE10907-0249_21942_(MoGene-2_0-st) |
- BXD75 |
- M |
- 69 |
- 9.2 |
-
-
- | 179 |
- EGE10907-0250_21943 |
- BXD8 |
- F |
- 97 |
- 9.1 |
-
-
- | 180 |
- EGE10907-0251_21944 |
- BXD85 |
- F |
- 79 |
- 8.6 |
-
-
- | 181 |
- EGE10907-0252_21945 |
- BXD85 |
- M |
- 79 |
- 9.1 |
-
-
- | 182 |
- EGE10907-0253_21946 |
- BXD85 |
- M |
- 79 |
- 9.4 |
-
-
- | 183 |
- EGE10907-0254_21947 |
- BXD102 |
- M |
- 94 |
- 8.6 |
-
-
- | 184 |
- EGE10907-0255_21948 |
- BXD99 |
- F |
- 83 |
- 9 |
-
-
- | 185 |
- EGE10907-0256_21949 |
- BXD69 |
- F |
- 68 |
- 9 |
-
-
- | 186 |
- EGE10907-0257_21950 |
- BXD84 |
- F |
- 74 |
- 9.5 |
-
-
- | 187 |
- EGE10907-0258_21951 |
- BXD84 |
- F |
- 74 |
- 9.4 |
-
-
- | 188 |
- EGE10907-0259_21952 |
- BXD84 |
- M |
- 74 |
- 8.6 |
-
-
- | 189 |
- EGE10907-0260_21451 |
- BXD96 |
- M |
- 67 |
- 9.2 |
-
-
- | 190 |
- EGE10907-0261_21452 |
- BXD99 |
- F |
- 71 |
- 8.9 |
-
-
- | 191 |
- EGE10907-0262_21931 |
- BXD6 |
- F |
- 66 |
- 9.4 |
-
-
- | 192 |
- EGE10907-0263_21932 |
- BXD14 |
- F |
- 69 |
- 8.5 |
-
-
- | 193 |
- EGE10907-0264_21933 |
- BXD34 |
- M |
- 79 |
- 9.1 |
-
-
- | 194 |
- EGE10907-0265_21934 |
- BXD34 |
- M |
- 79 |
- 9.9 |
-
-
- | 195 |
- EGE10907-0266_21935 |
- BXD40 |
- F |
- 75 |
- 9.6 |
-
-
- | 196 |
- EGE10907-0267_21936 |
- BXD40 |
- M |
- 78 |
- 9.7 |
-
-
- | 197 |
- EGE10907-0268_21937 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 198 |
- EGE10907-0269_21938 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 199 |
- EGE10907-0270_21939 |
- BXD56 |
- M |
- 72 |
- 9.6 |
-
-
- | 200 |
- EGE10907-0271_21940 |
- BXD56 |
- M |
- 72 |
- 9.4 |
-
-
- | 201 |
- EGE10907-0272_21941 |
- BXD71 |
- F |
- 72 |
- 9.9 |
-
-
- | 202 |
- EGE10907-0273_21942 |
- BXD71 |
- F |
- 75 |
- 9.4 |
-
-
- | 203 |
- EGE10907-0274_21943 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 204 |
- EGE10907-0275_21944 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 205 |
- EGE10907-0276_21945 |
- BXD27 |
- M |
- 65 |
- 10 |
-
-
- | 206 |
- EGE10907-0277_21946 |
- BXD15 |
- M |
- 65 |
- 10 |
-
-
- | 207 |
- EGE10907-0278_21947 |
- BXD20 |
- F |
- 125 |
- 10 |
-
-
- | 208 |
- EGE10907-0279_21948 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 209 |
- EGE10907-0280_21949 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 210 |
- EGE10907-0281_21950 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 211 |
- EGE10907-0282_21951 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 212 |
- EGE10907-0283_21952 |
- BXD85 |
- F |
- 87 |
- 10 |
-
-
- | 213 |
- EGE10907-0284_21451 |
- BXD43 |
- M |
- 75 |
- 9.8 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/DoDTATRCRetBLExMoGene2_1213/platform.rtf b/general/datasets/DoDTATRCRetBLExMoGene2_1213/platform.rtf
deleted file mode 100644
index 19fc38c..0000000
--- a/general/datasets/DoDTATRCRetBLExMoGene2_1213/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/DoDTATRCRetBLExMoGene2_1213/processing.rtf b/general/datasets/DoDTATRCRetBLExMoGene2_1213/processing.rtf
deleted file mode 100644
index a7b767e..0000000
--- a/general/datasets/DoDTATRCRetBLExMoGene2_1213/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/DoDTATRCRetBLExMoGene2_1213/summary.rtf b/general/datasets/DoDTATRCRetBLExMoGene2_1213/summary.rtf
deleted file mode 100644
index 96a87e5..0000000
--- a/general/datasets/DoDTATRCRetBLExMoGene2_1213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/DoDTATRCRetBLExMoGene2_1213/tissue.rtf b/general/datasets/DoDTATRCRetBLExMoGene2_1213/tissue.rtf
deleted file mode 100644
index 056d7eb..0000000
--- a/general/datasets/DoDTATRCRetBLExMoGene2_1213/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/DoDTATRCRetBLMoGene2E_0316/acknowledgment.rtf b/general/datasets/DoDTATRCRetBLMoGene2E_0316/acknowledgment.rtf
deleted file mode 100644
index 13c6b1e..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2E_0316/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/DoDTATRCRetBLMoGene2E_0316/cases.rtf b/general/datasets/DoDTATRCRetBLMoGene2E_0316/cases.rtf
deleted file mode 100644
index 6b36c70..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2E_0316/cases.rtf
+++ /dev/null
@@ -1,1728 +0,0 @@
-Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
-
-
-
-
-
-
-
-
-
- | Index |
- EIGC ID (LIMS ID) |
- Strain |
- Sex |
- Age at harvest |
- RIN Score |
-
-
- | 1 |
- 602 |
- BXD9 |
- F |
- 133 |
- 9.1 |
-
-
- | 2 |
- 603 |
- BXD9 |
- M |
- 100 |
- 9.5 |
-
-
- | 3 |
- 604 |
- BXD40 |
- F |
- 100 |
- 9.4 |
-
-
- | 4 |
- 605 |
- BXD40 |
- M |
- 100 |
- 9.1 |
-
-
- | 5 |
- 606 |
- BXD48 |
- F |
- 75 |
- 9.1 |
-
-
- | 6 |
- 607 |
- BXD48 |
- M |
- 75 |
- 8.6 |
-
-
- | 7 |
- 608 |
- BXD63 |
- F |
- 75 |
- 9.2 |
-
-
- | 8 |
- 609 |
- BXD63 |
- M |
- 61 |
- 9.4 |
-
-
- | 9 |
- 612 |
- BXD73 |
- M |
- 108 |
- 10 |
-
-
- | 10 |
- 614 |
- BXD87 |
- M |
- 85 |
- 9.2 |
-
-
- | 11 |
- 615 |
- BXD87 |
- F |
- 85 |
- 9.9 |
-
-
- | 12 |
- 616 |
- BXD69 |
- F |
- 76 |
- 9.3 |
-
-
- | 13 |
- 617 |
- BXD69 |
- M |
- 100 |
- 10 |
-
-
- | 14 |
- 618 |
- BXD51 |
- M |
- 82 |
- 8.9 |
-
-
- | 15 |
- 619 |
- BXD92 (BXD65b) |
- M |
- 82 |
- 8.8 |
-
-
- | 16 |
- 620 |
- BXD92 (BXD65b) |
- F |
- 82 |
- 8.8 |
-
-
- | 17 |
- 635 |
- BXD100 |
- M |
- 70 |
- 9 |
-
-
- | 18 |
- 636 |
- BXD100 |
- M |
- 70 |
- 8.8 |
-
-
- | 19 |
- 652 |
- BXD92 (BXD65b) |
- F |
- 64 |
- 9 |
-
-
- | 20 |
- 653 |
- BXD87 |
- F |
- 67 |
- 9.7 |
-
-
- | 21 |
- 654 |
- BXD87 |
- M |
- 67 |
- 8.9 |
-
-
- | 22 |
- 655 |
- BXD63 |
- M |
- 71 |
- 9 |
-
-
- | 23 |
- 660 |
- BXD69 |
- M |
- 97 |
- 10 |
-
-
- | 24 |
- 687 |
- BXD6 |
- M |
- 85 |
- 7.7 |
-
-
- | 25 |
- 688 |
- BXD6 |
- M |
- 85 |
- 9.4 |
-
-
- | 26 |
- 690 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 27 |
- 691 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 28 |
- 692 |
- BXD12 |
- M |
- 83 |
- 10 |
-
-
- | 29 |
- 695 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 30 |
- 696 |
- BXD5 |
- M |
- 77 |
- 10 |
-
-
- | 31 |
- 698 |
- BXD5 |
- F |
- 77 |
- 9.9 |
-
-
- | 32 |
- 699 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 33 |
- 701 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 34 |
- 702 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 35 |
- 705 |
- BXD8 |
- F |
- 77 |
- 9.2 |
-
-
- | 36 |
- 707 |
- BXD15 |
- F |
- 77 |
- 9.4 |
-
-
- | 37 |
- 708 |
- BXD15 |
- F |
- 77 |
- 9.1 |
-
-
- | 38 |
- 710 |
- BXD15 |
- M |
- 77 |
- 9.1 |
-
-
- | 39 |
- 713 |
- BXD22 |
- F |
- 71 |
- 9.5 |
-
-
- | 40 |
- 714 |
- BXD22 |
- F |
- 71 |
- 9.7 |
-
-
- | 41 |
- 716 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 42 |
- 717 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 43 |
- 719 |
- BXD14 |
- F |
- 70 |
- 9.2 |
-
-
- | 44 |
- 722 |
- BXD14 |
- M |
- 70 |
- 8.9 |
-
-
- | 45 |
- 723 |
- BXD14 |
- M |
- 70 |
- 9.2 |
-
-
- | 46 |
- 725 |
- BXD18 |
- F |
- 70 |
- 9 |
-
-
- | 47 |
- 726 |
- BXD18 |
- F |
- 70 |
- 9.1 |
-
-
- | 48 |
- 728 |
- BXD18 |
- M |
- 70 |
- 9.1 |
-
-
- | 49 |
- 729 |
- BXD18 |
- M |
- 70 |
- 9.2 |
-
-
- | 50 |
- 731 |
- BXD19 |
- F |
- 66 |
- 9.3 |
-
-
- | 51 |
- 732 |
- BXD19 |
- F |
- 66 |
- 9.4 |
-
-
- | 52 |
- 734 |
- BXD19 |
- M |
- 66 |
- 9.8 |
-
-
- | 53 |
- 735 |
- BXD19 |
- M |
- 66 |
- 9.4 |
-
-
- | 54 |
- 737 |
- BXD21 |
- F |
- 71 |
- 9.7 |
-
-
- | 55 |
- 738 |
- BXD21 |
- F |
- 71 |
- 9.6 |
-
-
- | 56 |
- 740 |
- BXD21 |
- M |
- 71 |
- 9.1 |
-
-
- | 57 |
- 741 |
- BXD21 |
- M |
- 71 |
- 9.7 |
-
-
- | 58 |
- 743 |
- BXD2 |
- F |
- 70 |
- 8.3 |
-
-
- | 59 |
- 744 |
- BXD2 |
- F |
- 70 |
- 8.6 |
-
-
- | 60 |
- 746 |
- BXD2 |
- M |
- 70 |
- 7.5 |
-
-
- | 61 |
- 747 |
- BXD2 |
- M |
- 77 |
- 8.6 |
-
-
- | 62 |
- 768 |
- BXD48 |
- M |
- 121 |
- 9.4 |
-
-
- | 63 |
- 770 |
- BXD92 (BXD65b) |
- M |
- 65 |
- 10 |
-
-
- | 64 |
- 771 |
- BXD101 |
- F |
- 85 |
- 8.3 |
-
-
- | 65 |
- 772 |
- BXD101 |
- F |
- 85 |
- 9.3 |
-
-
- | 66 |
- 773 |
- BXD101 |
- M |
- 86 |
- 9.5 |
-
-
- | 67 |
- 774 |
- BXD101 |
- M |
- 86 |
- 9.8 |
-
-
- | 68 |
- 775 |
- BXD102 |
- F |
- 66 |
- 9.5 |
-
-
- | 69 |
- 776 |
- BXD102 |
- F |
- 66 |
- 10 |
-
-
- | 70 |
- 777 |
- BXD102 |
- M |
- 84 |
- 9.6 |
-
-
- | 71 |
- 787 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 72 |
- 788 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 73 |
- 789 |
- BXD63 |
- F |
- 115 |
- 9.7 |
-
-
- | 74 |
- 790 |
- BXD100 |
- F |
- 72 |
- 9.8 |
-
-
- | 75 |
- 791 |
- BXD100 |
- F |
- 72 |
- 10 |
-
-
- | 76 |
- 818 |
- BXD51 |
- F |
- 77 |
- 9.7 |
-
-
- | 77 |
- 819 |
- BXD51 |
- F |
- 77 |
- 9.6 |
-
-
- | 78 |
- 820 |
- BXD51 |
- M |
- 72 |
- 9.7 |
-
-
- | 79 |
- 821 |
- BXD65 |
- M |
- 72 |
- 9.6 |
-
-
- | 80 |
- 822 |
- BXD65 |
- M |
- 65 |
- 9.5 |
-
-
- | 81 |
- 825 |
- BXD65 |
- F |
- 72 |
- 9.5 |
-
-
- | 82 |
- 827 |
- BXD86 |
- M |
- 69 |
- 9.1 |
-
-
- | 83 |
- 828 |
- BXD86 |
- M |
- 69 |
- 9.4 |
-
-
- | 84 |
- 829 |
- BXD90 |
- F |
- 69 |
- 9.6 |
-
-
- | 85 |
- 831 |
- BXD9 |
- M |
- 127 |
- 9.7 |
-
-
- | 86 |
- 832 |
- BXD39 |
- F |
- 99 |
- 9.4 |
-
-
- | 87 |
- 833 |
- BXD39 |
- F |
- 107 |
- 9.3 |
-
-
- | 88 |
- 834 |
- BXD60 |
- F |
- 107 |
- 9.5 |
-
-
- | 89 |
- 836 |
- BXD84 |
- M |
- 103 |
- 9.7 |
-
-
- | 90 |
- 846 |
- BXD39 |
- M |
- 63 |
- 9.7 |
-
-
- | 91 |
- 847 |
- BXD39 |
- M |
- 63 |
- 9.8 |
-
-
- | 92 |
- 849 |
- BXD20 |
- F |
- 70 |
- 10 |
-
-
- | 93 |
- 850 |
- BXD20 |
- M |
- 70 |
- 10 |
-
-
- | 94 |
- 851 |
- BXD20 |
- * |
- 70 |
- 9.5 |
-
-
- | 95 |
- 855 |
- DBA/2J |
- F |
- 78 |
- 9.7 |
-
-
- | 96 |
- 856 |
- DBA/2J |
- F |
- 78 |
- 10 |
-
-
- | 97 |
- 857 |
- DBA/2J |
- M |
- 78 |
- 10 |
-
-
- | 98 |
- 858 |
- DBA/2J |
- M |
- 78 |
- 9.9 |
-
-
- | 99 |
- 859 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 100 |
- 860 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 101 |
- 861 |
- C57BL/6J |
- M |
- 78 |
- 10 |
-
-
- | 102 |
- 862 |
- C57BL/6J |
- M |
- 78 |
- 9.6 |
-
-
- | 103 |
- EGE10907-0172_890_20844 |
- BXD28 |
- M |
- 75 |
- 10 |
-
-
- | 104 |
- EGE10907-0173_891_20845 |
- BXD28 |
- M |
- 75 |
- 9.7 |
-
-
- | 105 |
- EGE10907-0174_892_20846 |
- BXD28 |
- F |
- 75 |
- 9.7 |
-
-
- | 106 |
- EGE10907-0176_895_20848 |
- BXD33 |
- M |
- 75 |
- 9.88 |
-
-
- | 107 |
- EGE10907-0177_896_20849 |
- BXD33 |
- F |
- 75 |
- 10 |
-
-
- | 108 |
- EGE10907-0178_897_20850 |
- BXD33 |
- F |
- 75 |
- 9.4 |
-
-
- | 109 |
- EGE10907-0179_898_20851 |
- BXD36 |
- M |
- 75 |
- 9.4 |
-
-
- | 110 |
- EGE10907-0180_899_20852 |
- BXD36 |
- F |
- 75 |
- 9.5 |
-
-
- | 111 |
- EGE10907-0181_900_20853 |
- BXD36 |
- F |
- 75 |
- 9.1 |
-
-
- | 112 |
- EGE10907-0182_910_20854 |
- BXD27 |
- M |
- 70 |
- 9.7 |
-
-
- | 113 |
- EGE10907-0183_990_20855 |
- BXD9 |
- F |
- 98 |
- 9.4 |
-
-
- | 114 |
- EGE10907-0184_991_20856 |
- BXD16 |
- F |
- 113 |
- 10 |
-
-
- | 115 |
- EGE10907-0185_992_20857 |
- BXD16 |
- M |
- 113 |
- 9 |
-
-
- | 116 |
- EGE10907-0186_993_20858 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 117 |
- EGE10907-0187_994_20859 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 118 |
- EGE10907-0188_996_20860 |
- BXD48 |
- F |
- 98 |
- 9.4 |
-
-
- | 119 |
- EGE10907-0189_997_20861 |
- BXD73 |
- M |
- 106 |
- 10 |
-
-
- | 120 |
- EGE10907-0190_999_20862 |
- BXD11 |
- F |
- 121 |
- 9.6 |
-
-
- | 121 |
- EGE10907-0191_100_20863 |
- BXD11 |
- F |
- 121 |
- 9.9 |
-
-
- | 122 |
- EGE10907-0192_1010_21276 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 123 |
- EGE10907-0193_1011_21277 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 124 |
- EGE10907-0194_1012_21278 |
- BXD16 |
- F |
- 65 |
- 10 |
-
-
- | 125 |
- EGE10907-0195_1015_21279 |
- BXD16 |
- M |
- 65 |
- 10 |
-
-
- | 126 |
- EGE10907-0196_1019_21280 |
- BXD33 |
- M |
- 75 |
- 10 |
-
-
- | 127 |
- EGE10907-0197_1020_21281 |
- BXD36 |
- M |
- 78 |
- 10 |
-
-
- | 128 |
- EGE10907-0198_1021_21282 |
- BXD38 |
- F |
- 70 |
- 9.8 |
-
-
- | 129 |
- EGE10907-0199_1022_21283 |
- BXD38 |
- F |
- 70 |
- 10 |
-
-
- | 130 |
- EGE10907-0200_1023_21284 |
- BXD38 |
- M |
- 70 |
- 9.7 |
-
-
- | 131 |
- EGE10907-0201_1047_21285 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 132 |
- EGE10907-0202_1048_21286 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 133 |
- EGE10907-0203_1049_21287 |
- BXD38 |
- M |
- 77 |
- 10 |
-
-
- | 134 |
- EGE10907-0204_1050_21288 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 135 |
- EGE10907-0205_1051_21289 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 136 |
- EGE10907-0206_1052_21290 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 137 |
- EGE10907-0207_1053_21291 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 138 |
- EGE10907-0208_1054_21292 |
- BXD90 |
- F |
- 71 |
- 10 |
-
-
- | 139 |
- EGE10907-0209_1055_21293 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 140 |
- EGE10907-0210_1056_21294 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 141 |
- EGE10907-0211_1148_21295 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 142 |
- EGE10907-0212_1149_21296 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 143 |
- EGE10907-0213_1150_21297 |
- BXD31 |
- M |
- 90 |
- 10 |
-
-
- | 144 |
- EGE10907-0214_1151_21298 |
- BXD31 |
- M |
- 90 |
- 9.9 |
-
-
- | 145 |
- EGE10907-0215_1152_21299 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 146 |
- EGE10907-0216_21429 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 147 |
- EGE10907-0217_21430 |
- BXD42 |
- M |
- 83 |
- 10 |
-
-
- | 148 |
- EGE10907-0218_21431 |
- BXD42 |
- M |
- 83 |
- 9.3 |
-
-
- | 149 |
- EGE10907-0219_21432 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 150 |
- EGE10907-0220_21433 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 151 |
- EGE10907-0221_21434 |
- BXD50 |
- F |
- 92 |
- 10 |
-
-
- | 152 |
- EGE10907-0222_21435 |
- BXD1 |
- M |
- 73 |
- 9.6 |
-
-
- | 153 |
- EGE10907-0223_21436 |
- BXD13 |
- F |
- 71 |
- 9.7 |
-
-
- | 154 |
- EGE10907-0224_21437 |
- BXD1 |
- M |
- 71 |
- 9.5 |
-
-
- | 155 |
- EGE10907-0225_21438 |
- BXD13 |
- F |
- 71 |
- 9.6 |
-
-
- | 156 |
- EGE10907-0226_21439 |
- BXD43 |
- F |
- 85 |
- 10 |
-
-
- | 157 |
- EGE10907-0227_21452 |
- BXD43 |
- F |
- 85 |
- 9.6 |
-
-
- | 158 |
- EGE10907-0229_21442 |
- BXD43 |
- M |
- 85 |
- 8.2 |
-
-
- | 159 |
- EGE10907-0230_21443 |
- BXD50 |
- M |
- 69 |
- 9.4 |
-
-
- | 160 |
- EGE10907-0231_21444 |
- BXD1 |
- F |
- 68 |
- 9.4 |
-
-
- | 161 |
- EGE10907-0232_21445 |
- BXD1 |
- F |
- 68 |
- 9.6 |
-
-
- | 162 |
- EGE10907-0233_21446 |
- BXD29 |
- M |
- 65 |
- 9.5 |
-
-
- | 163 |
- EGE10907-0234_21447 |
- BXD29 |
- M |
- 65 |
- 10 |
-
-
- | 164 |
- EGE10907-0235_21448 |
- BXD75 |
- F |
- 68 |
- 10 |
-
-
- | 165 |
- EGE10907-0236_21449 |
- BXD75 |
- M |
- 68 |
- 10 |
-
-
- | 166 |
- EGE10907-0237_21450 |
- BXD96 |
- F |
- 67 |
- 9.9 |
-
-
- | 167 |
- EGE10907-0238_21931 |
- BXD99 |
- M |
- 71 |
- 7.9 |
-
-
- | 168 |
- EGE10907-0239_21932 |
- BXD99 |
- M |
- 71 |
- 9.7 |
-
-
- | 169 |
- EGE10907-0240_21933 |
- BXD67 |
- F |
- 68 |
- 8.8 |
-
-
- | 170 |
- EGE10907-0241_21934 |
- BXD67 |
- F |
- 68 |
- 8.5 |
-
-
- | 171 |
- EGE10907-0242_21935 |
- BXD67 |
- M |
- 68 |
- 9.5 |
-
-
- | 172 |
- EGE10907-0243_21936 |
- BXD67 |
- M |
- 68 |
- 9.6 |
-
-
- | 173 |
- EGE10907-0244_21937 |
- BXD6 |
- F |
- 68 |
- 9.6 |
-
-
- | 174 |
- EGE10907-0245_21938 |
- BXD12 |
- M |
- 82 |
- 9.5 |
-
-
- | 175 |
- EGE10907-0246_21939 |
- BXD60 |
- F |
- 72 |
- 9.6 |
-
-
- | 176 |
- EGE10907-0247_21940 |
- BXD65 |
- F |
- 75 |
- 9.1 |
-
-
- | 177 |
- EGE10907-0248_21941 |
- BXD75 |
- F |
- 69 |
- 8.8 |
-
-
- | 178 |
- EGE10907-0249_21942_(MoGene-2_0-st) |
- BXD75 |
- M |
- 69 |
- 9.2 |
-
-
- | 179 |
- EGE10907-0250_21943 |
- BXD8 |
- F |
- 97 |
- 9.1 |
-
-
- | 180 |
- EGE10907-0251_21944 |
- BXD85 |
- F |
- 79 |
- 8.6 |
-
-
- | 181 |
- EGE10907-0252_21945 |
- BXD85 |
- M |
- 79 |
- 9.1 |
-
-
- | 182 |
- EGE10907-0253_21946 |
- BXD85 |
- M |
- 79 |
- 9.4 |
-
-
- | 183 |
- EGE10907-0254_21947 |
- BXD102 |
- M |
- 94 |
- 8.6 |
-
-
- | 184 |
- EGE10907-0255_21948 |
- BXD99 |
- F |
- 83 |
- 9 |
-
-
- | 185 |
- EGE10907-0256_21949 |
- BXD69 |
- F |
- 68 |
- 9 |
-
-
- | 186 |
- EGE10907-0257_21950 |
- BXD84 |
- F |
- 74 |
- 9.5 |
-
-
- | 187 |
- EGE10907-0258_21951 |
- BXD84 |
- F |
- 74 |
- 9.4 |
-
-
- | 188 |
- EGE10907-0259_21952 |
- BXD84 |
- M |
- 74 |
- 8.6 |
-
-
- | 189 |
- EGE10907-0260_21451 |
- BXD96 |
- M |
- 67 |
- 9.2 |
-
-
- | 190 |
- EGE10907-0261_21452 |
- BXD99 |
- F |
- 71 |
- 8.9 |
-
-
- | 191 |
- EGE10907-0262_21931 |
- BXD6 |
- F |
- 66 |
- 9.4 |
-
-
- | 192 |
- EGE10907-0263_21932 |
- BXD14 |
- F |
- 69 |
- 8.5 |
-
-
- | 193 |
- EGE10907-0264_21933 |
- BXD34 |
- M |
- 79 |
- 9.1 |
-
-
- | 194 |
- EGE10907-0265_21934 |
- BXD34 |
- M |
- 79 |
- 9.9 |
-
-
- | 195 |
- EGE10907-0266_21935 |
- BXD40 |
- F |
- 75 |
- 9.6 |
-
-
- | 196 |
- EGE10907-0267_21936 |
- BXD40 |
- M |
- 78 |
- 9.7 |
-
-
- | 197 |
- EGE10907-0268_21937 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 198 |
- EGE10907-0269_21938 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 199 |
- EGE10907-0270_21939 |
- BXD56 |
- M |
- 72 |
- 9.6 |
-
-
- | 200 |
- EGE10907-0271_21940 |
- BXD56 |
- M |
- 72 |
- 9.4 |
-
-
- | 201 |
- EGE10907-0272_21941 |
- BXD71 |
- F |
- 72 |
- 9.9 |
-
-
- | 202 |
- EGE10907-0273_21942 |
- BXD71 |
- F |
- 75 |
- 9.4 |
-
-
- | 203 |
- EGE10907-0274_21943 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 204 |
- EGE10907-0275_21944 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 205 |
- EGE10907-0276_21945 |
- BXD27 |
- M |
- 65 |
- 10 |
-
-
- | 206 |
- EGE10907-0277_21946 |
- BXD15 |
- M |
- 65 |
- 10 |
-
-
- | 207 |
- EGE10907-0278_21947 |
- BXD20 |
- F |
- 125 |
- 10 |
-
-
- | 208 |
- EGE10907-0279_21948 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 209 |
- EGE10907-0280_21949 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 210 |
- EGE10907-0281_21950 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 211 |
- EGE10907-0282_21951 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 212 |
- EGE10907-0283_21952 |
- BXD85 |
- F |
- 87 |
- 10 |
-
-
- | 213 |
- EGE10907-0284_21451 |
- BXD43 |
- M |
- 75 |
- 9.8 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/DoDTATRCRetBLMoGene2E_0316/platform.rtf b/general/datasets/DoDTATRCRetBLMoGene2E_0316/platform.rtf
deleted file mode 100644
index 19fc38c..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2E_0316/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/DoDTATRCRetBLMoGene2E_0316/processing.rtf b/general/datasets/DoDTATRCRetBLMoGene2E_0316/processing.rtf
deleted file mode 100644
index a7b767e..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2E_0316/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/DoDTATRCRetBLMoGene2E_0316/summary.rtf b/general/datasets/DoDTATRCRetBLMoGene2E_0316/summary.rtf
deleted file mode 100644
index 96a87e5..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2E_0316/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/DoDTATRCRetBLMoGene2E_0316/tissue.rtf b/general/datasets/DoDTATRCRetBLMoGene2E_0316/tissue.rtf
deleted file mode 100644
index 056d7eb..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2E_0316/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/DoDTATRCRetBLMoGene2_0316/acknowledgment.rtf b/general/datasets/DoDTATRCRetBLMoGene2_0316/acknowledgment.rtf
deleted file mode 100644
index 13c6b1e..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2_0316/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/DoDTATRCRetBLMoGene2_0316/cases.rtf b/general/datasets/DoDTATRCRetBLMoGene2_0316/cases.rtf
deleted file mode 100644
index 6b36c70..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2_0316/cases.rtf
+++ /dev/null
@@ -1,1728 +0,0 @@
-Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
-
-
-
-
-
-
-
-
-
- | Index |
- EIGC ID (LIMS ID) |
- Strain |
- Sex |
- Age at harvest |
- RIN Score |
-
-
- | 1 |
- 602 |
- BXD9 |
- F |
- 133 |
- 9.1 |
-
-
- | 2 |
- 603 |
- BXD9 |
- M |
- 100 |
- 9.5 |
-
-
- | 3 |
- 604 |
- BXD40 |
- F |
- 100 |
- 9.4 |
-
-
- | 4 |
- 605 |
- BXD40 |
- M |
- 100 |
- 9.1 |
-
-
- | 5 |
- 606 |
- BXD48 |
- F |
- 75 |
- 9.1 |
-
-
- | 6 |
- 607 |
- BXD48 |
- M |
- 75 |
- 8.6 |
-
-
- | 7 |
- 608 |
- BXD63 |
- F |
- 75 |
- 9.2 |
-
-
- | 8 |
- 609 |
- BXD63 |
- M |
- 61 |
- 9.4 |
-
-
- | 9 |
- 612 |
- BXD73 |
- M |
- 108 |
- 10 |
-
-
- | 10 |
- 614 |
- BXD87 |
- M |
- 85 |
- 9.2 |
-
-
- | 11 |
- 615 |
- BXD87 |
- F |
- 85 |
- 9.9 |
-
-
- | 12 |
- 616 |
- BXD69 |
- F |
- 76 |
- 9.3 |
-
-
- | 13 |
- 617 |
- BXD69 |
- M |
- 100 |
- 10 |
-
-
- | 14 |
- 618 |
- BXD51 |
- M |
- 82 |
- 8.9 |
-
-
- | 15 |
- 619 |
- BXD92 (BXD65b) |
- M |
- 82 |
- 8.8 |
-
-
- | 16 |
- 620 |
- BXD92 (BXD65b) |
- F |
- 82 |
- 8.8 |
-
-
- | 17 |
- 635 |
- BXD100 |
- M |
- 70 |
- 9 |
-
-
- | 18 |
- 636 |
- BXD100 |
- M |
- 70 |
- 8.8 |
-
-
- | 19 |
- 652 |
- BXD92 (BXD65b) |
- F |
- 64 |
- 9 |
-
-
- | 20 |
- 653 |
- BXD87 |
- F |
- 67 |
- 9.7 |
-
-
- | 21 |
- 654 |
- BXD87 |
- M |
- 67 |
- 8.9 |
-
-
- | 22 |
- 655 |
- BXD63 |
- M |
- 71 |
- 9 |
-
-
- | 23 |
- 660 |
- BXD69 |
- M |
- 97 |
- 10 |
-
-
- | 24 |
- 687 |
- BXD6 |
- M |
- 85 |
- 7.7 |
-
-
- | 25 |
- 688 |
- BXD6 |
- M |
- 85 |
- 9.4 |
-
-
- | 26 |
- 690 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 27 |
- 691 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 28 |
- 692 |
- BXD12 |
- M |
- 83 |
- 10 |
-
-
- | 29 |
- 695 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 30 |
- 696 |
- BXD5 |
- M |
- 77 |
- 10 |
-
-
- | 31 |
- 698 |
- BXD5 |
- F |
- 77 |
- 9.9 |
-
-
- | 32 |
- 699 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 33 |
- 701 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 34 |
- 702 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 35 |
- 705 |
- BXD8 |
- F |
- 77 |
- 9.2 |
-
-
- | 36 |
- 707 |
- BXD15 |
- F |
- 77 |
- 9.4 |
-
-
- | 37 |
- 708 |
- BXD15 |
- F |
- 77 |
- 9.1 |
-
-
- | 38 |
- 710 |
- BXD15 |
- M |
- 77 |
- 9.1 |
-
-
- | 39 |
- 713 |
- BXD22 |
- F |
- 71 |
- 9.5 |
-
-
- | 40 |
- 714 |
- BXD22 |
- F |
- 71 |
- 9.7 |
-
-
- | 41 |
- 716 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 42 |
- 717 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 43 |
- 719 |
- BXD14 |
- F |
- 70 |
- 9.2 |
-
-
- | 44 |
- 722 |
- BXD14 |
- M |
- 70 |
- 8.9 |
-
-
- | 45 |
- 723 |
- BXD14 |
- M |
- 70 |
- 9.2 |
-
-
- | 46 |
- 725 |
- BXD18 |
- F |
- 70 |
- 9 |
-
-
- | 47 |
- 726 |
- BXD18 |
- F |
- 70 |
- 9.1 |
-
-
- | 48 |
- 728 |
- BXD18 |
- M |
- 70 |
- 9.1 |
-
-
- | 49 |
- 729 |
- BXD18 |
- M |
- 70 |
- 9.2 |
-
-
- | 50 |
- 731 |
- BXD19 |
- F |
- 66 |
- 9.3 |
-
-
- | 51 |
- 732 |
- BXD19 |
- F |
- 66 |
- 9.4 |
-
-
- | 52 |
- 734 |
- BXD19 |
- M |
- 66 |
- 9.8 |
-
-
- | 53 |
- 735 |
- BXD19 |
- M |
- 66 |
- 9.4 |
-
-
- | 54 |
- 737 |
- BXD21 |
- F |
- 71 |
- 9.7 |
-
-
- | 55 |
- 738 |
- BXD21 |
- F |
- 71 |
- 9.6 |
-
-
- | 56 |
- 740 |
- BXD21 |
- M |
- 71 |
- 9.1 |
-
-
- | 57 |
- 741 |
- BXD21 |
- M |
- 71 |
- 9.7 |
-
-
- | 58 |
- 743 |
- BXD2 |
- F |
- 70 |
- 8.3 |
-
-
- | 59 |
- 744 |
- BXD2 |
- F |
- 70 |
- 8.6 |
-
-
- | 60 |
- 746 |
- BXD2 |
- M |
- 70 |
- 7.5 |
-
-
- | 61 |
- 747 |
- BXD2 |
- M |
- 77 |
- 8.6 |
-
-
- | 62 |
- 768 |
- BXD48 |
- M |
- 121 |
- 9.4 |
-
-
- | 63 |
- 770 |
- BXD92 (BXD65b) |
- M |
- 65 |
- 10 |
-
-
- | 64 |
- 771 |
- BXD101 |
- F |
- 85 |
- 8.3 |
-
-
- | 65 |
- 772 |
- BXD101 |
- F |
- 85 |
- 9.3 |
-
-
- | 66 |
- 773 |
- BXD101 |
- M |
- 86 |
- 9.5 |
-
-
- | 67 |
- 774 |
- BXD101 |
- M |
- 86 |
- 9.8 |
-
-
- | 68 |
- 775 |
- BXD102 |
- F |
- 66 |
- 9.5 |
-
-
- | 69 |
- 776 |
- BXD102 |
- F |
- 66 |
- 10 |
-
-
- | 70 |
- 777 |
- BXD102 |
- M |
- 84 |
- 9.6 |
-
-
- | 71 |
- 787 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 72 |
- 788 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 73 |
- 789 |
- BXD63 |
- F |
- 115 |
- 9.7 |
-
-
- | 74 |
- 790 |
- BXD100 |
- F |
- 72 |
- 9.8 |
-
-
- | 75 |
- 791 |
- BXD100 |
- F |
- 72 |
- 10 |
-
-
- | 76 |
- 818 |
- BXD51 |
- F |
- 77 |
- 9.7 |
-
-
- | 77 |
- 819 |
- BXD51 |
- F |
- 77 |
- 9.6 |
-
-
- | 78 |
- 820 |
- BXD51 |
- M |
- 72 |
- 9.7 |
-
-
- | 79 |
- 821 |
- BXD65 |
- M |
- 72 |
- 9.6 |
-
-
- | 80 |
- 822 |
- BXD65 |
- M |
- 65 |
- 9.5 |
-
-
- | 81 |
- 825 |
- BXD65 |
- F |
- 72 |
- 9.5 |
-
-
- | 82 |
- 827 |
- BXD86 |
- M |
- 69 |
- 9.1 |
-
-
- | 83 |
- 828 |
- BXD86 |
- M |
- 69 |
- 9.4 |
-
-
- | 84 |
- 829 |
- BXD90 |
- F |
- 69 |
- 9.6 |
-
-
- | 85 |
- 831 |
- BXD9 |
- M |
- 127 |
- 9.7 |
-
-
- | 86 |
- 832 |
- BXD39 |
- F |
- 99 |
- 9.4 |
-
-
- | 87 |
- 833 |
- BXD39 |
- F |
- 107 |
- 9.3 |
-
-
- | 88 |
- 834 |
- BXD60 |
- F |
- 107 |
- 9.5 |
-
-
- | 89 |
- 836 |
- BXD84 |
- M |
- 103 |
- 9.7 |
-
-
- | 90 |
- 846 |
- BXD39 |
- M |
- 63 |
- 9.7 |
-
-
- | 91 |
- 847 |
- BXD39 |
- M |
- 63 |
- 9.8 |
-
-
- | 92 |
- 849 |
- BXD20 |
- F |
- 70 |
- 10 |
-
-
- | 93 |
- 850 |
- BXD20 |
- M |
- 70 |
- 10 |
-
-
- | 94 |
- 851 |
- BXD20 |
- * |
- 70 |
- 9.5 |
-
-
- | 95 |
- 855 |
- DBA/2J |
- F |
- 78 |
- 9.7 |
-
-
- | 96 |
- 856 |
- DBA/2J |
- F |
- 78 |
- 10 |
-
-
- | 97 |
- 857 |
- DBA/2J |
- M |
- 78 |
- 10 |
-
-
- | 98 |
- 858 |
- DBA/2J |
- M |
- 78 |
- 9.9 |
-
-
- | 99 |
- 859 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 100 |
- 860 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 101 |
- 861 |
- C57BL/6J |
- M |
- 78 |
- 10 |
-
-
- | 102 |
- 862 |
- C57BL/6J |
- M |
- 78 |
- 9.6 |
-
-
- | 103 |
- EGE10907-0172_890_20844 |
- BXD28 |
- M |
- 75 |
- 10 |
-
-
- | 104 |
- EGE10907-0173_891_20845 |
- BXD28 |
- M |
- 75 |
- 9.7 |
-
-
- | 105 |
- EGE10907-0174_892_20846 |
- BXD28 |
- F |
- 75 |
- 9.7 |
-
-
- | 106 |
- EGE10907-0176_895_20848 |
- BXD33 |
- M |
- 75 |
- 9.88 |
-
-
- | 107 |
- EGE10907-0177_896_20849 |
- BXD33 |
- F |
- 75 |
- 10 |
-
-
- | 108 |
- EGE10907-0178_897_20850 |
- BXD33 |
- F |
- 75 |
- 9.4 |
-
-
- | 109 |
- EGE10907-0179_898_20851 |
- BXD36 |
- M |
- 75 |
- 9.4 |
-
-
- | 110 |
- EGE10907-0180_899_20852 |
- BXD36 |
- F |
- 75 |
- 9.5 |
-
-
- | 111 |
- EGE10907-0181_900_20853 |
- BXD36 |
- F |
- 75 |
- 9.1 |
-
-
- | 112 |
- EGE10907-0182_910_20854 |
- BXD27 |
- M |
- 70 |
- 9.7 |
-
-
- | 113 |
- EGE10907-0183_990_20855 |
- BXD9 |
- F |
- 98 |
- 9.4 |
-
-
- | 114 |
- EGE10907-0184_991_20856 |
- BXD16 |
- F |
- 113 |
- 10 |
-
-
- | 115 |
- EGE10907-0185_992_20857 |
- BXD16 |
- M |
- 113 |
- 9 |
-
-
- | 116 |
- EGE10907-0186_993_20858 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 117 |
- EGE10907-0187_994_20859 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 118 |
- EGE10907-0188_996_20860 |
- BXD48 |
- F |
- 98 |
- 9.4 |
-
-
- | 119 |
- EGE10907-0189_997_20861 |
- BXD73 |
- M |
- 106 |
- 10 |
-
-
- | 120 |
- EGE10907-0190_999_20862 |
- BXD11 |
- F |
- 121 |
- 9.6 |
-
-
- | 121 |
- EGE10907-0191_100_20863 |
- BXD11 |
- F |
- 121 |
- 9.9 |
-
-
- | 122 |
- EGE10907-0192_1010_21276 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 123 |
- EGE10907-0193_1011_21277 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 124 |
- EGE10907-0194_1012_21278 |
- BXD16 |
- F |
- 65 |
- 10 |
-
-
- | 125 |
- EGE10907-0195_1015_21279 |
- BXD16 |
- M |
- 65 |
- 10 |
-
-
- | 126 |
- EGE10907-0196_1019_21280 |
- BXD33 |
- M |
- 75 |
- 10 |
-
-
- | 127 |
- EGE10907-0197_1020_21281 |
- BXD36 |
- M |
- 78 |
- 10 |
-
-
- | 128 |
- EGE10907-0198_1021_21282 |
- BXD38 |
- F |
- 70 |
- 9.8 |
-
-
- | 129 |
- EGE10907-0199_1022_21283 |
- BXD38 |
- F |
- 70 |
- 10 |
-
-
- | 130 |
- EGE10907-0200_1023_21284 |
- BXD38 |
- M |
- 70 |
- 9.7 |
-
-
- | 131 |
- EGE10907-0201_1047_21285 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 132 |
- EGE10907-0202_1048_21286 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 133 |
- EGE10907-0203_1049_21287 |
- BXD38 |
- M |
- 77 |
- 10 |
-
-
- | 134 |
- EGE10907-0204_1050_21288 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 135 |
- EGE10907-0205_1051_21289 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 136 |
- EGE10907-0206_1052_21290 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 137 |
- EGE10907-0207_1053_21291 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 138 |
- EGE10907-0208_1054_21292 |
- BXD90 |
- F |
- 71 |
- 10 |
-
-
- | 139 |
- EGE10907-0209_1055_21293 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 140 |
- EGE10907-0210_1056_21294 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 141 |
- EGE10907-0211_1148_21295 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 142 |
- EGE10907-0212_1149_21296 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 143 |
- EGE10907-0213_1150_21297 |
- BXD31 |
- M |
- 90 |
- 10 |
-
-
- | 144 |
- EGE10907-0214_1151_21298 |
- BXD31 |
- M |
- 90 |
- 9.9 |
-
-
- | 145 |
- EGE10907-0215_1152_21299 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 146 |
- EGE10907-0216_21429 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 147 |
- EGE10907-0217_21430 |
- BXD42 |
- M |
- 83 |
- 10 |
-
-
- | 148 |
- EGE10907-0218_21431 |
- BXD42 |
- M |
- 83 |
- 9.3 |
-
-
- | 149 |
- EGE10907-0219_21432 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 150 |
- EGE10907-0220_21433 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 151 |
- EGE10907-0221_21434 |
- BXD50 |
- F |
- 92 |
- 10 |
-
-
- | 152 |
- EGE10907-0222_21435 |
- BXD1 |
- M |
- 73 |
- 9.6 |
-
-
- | 153 |
- EGE10907-0223_21436 |
- BXD13 |
- F |
- 71 |
- 9.7 |
-
-
- | 154 |
- EGE10907-0224_21437 |
- BXD1 |
- M |
- 71 |
- 9.5 |
-
-
- | 155 |
- EGE10907-0225_21438 |
- BXD13 |
- F |
- 71 |
- 9.6 |
-
-
- | 156 |
- EGE10907-0226_21439 |
- BXD43 |
- F |
- 85 |
- 10 |
-
-
- | 157 |
- EGE10907-0227_21452 |
- BXD43 |
- F |
- 85 |
- 9.6 |
-
-
- | 158 |
- EGE10907-0229_21442 |
- BXD43 |
- M |
- 85 |
- 8.2 |
-
-
- | 159 |
- EGE10907-0230_21443 |
- BXD50 |
- M |
- 69 |
- 9.4 |
-
-
- | 160 |
- EGE10907-0231_21444 |
- BXD1 |
- F |
- 68 |
- 9.4 |
-
-
- | 161 |
- EGE10907-0232_21445 |
- BXD1 |
- F |
- 68 |
- 9.6 |
-
-
- | 162 |
- EGE10907-0233_21446 |
- BXD29 |
- M |
- 65 |
- 9.5 |
-
-
- | 163 |
- EGE10907-0234_21447 |
- BXD29 |
- M |
- 65 |
- 10 |
-
-
- | 164 |
- EGE10907-0235_21448 |
- BXD75 |
- F |
- 68 |
- 10 |
-
-
- | 165 |
- EGE10907-0236_21449 |
- BXD75 |
- M |
- 68 |
- 10 |
-
-
- | 166 |
- EGE10907-0237_21450 |
- BXD96 |
- F |
- 67 |
- 9.9 |
-
-
- | 167 |
- EGE10907-0238_21931 |
- BXD99 |
- M |
- 71 |
- 7.9 |
-
-
- | 168 |
- EGE10907-0239_21932 |
- BXD99 |
- M |
- 71 |
- 9.7 |
-
-
- | 169 |
- EGE10907-0240_21933 |
- BXD67 |
- F |
- 68 |
- 8.8 |
-
-
- | 170 |
- EGE10907-0241_21934 |
- BXD67 |
- F |
- 68 |
- 8.5 |
-
-
- | 171 |
- EGE10907-0242_21935 |
- BXD67 |
- M |
- 68 |
- 9.5 |
-
-
- | 172 |
- EGE10907-0243_21936 |
- BXD67 |
- M |
- 68 |
- 9.6 |
-
-
- | 173 |
- EGE10907-0244_21937 |
- BXD6 |
- F |
- 68 |
- 9.6 |
-
-
- | 174 |
- EGE10907-0245_21938 |
- BXD12 |
- M |
- 82 |
- 9.5 |
-
-
- | 175 |
- EGE10907-0246_21939 |
- BXD60 |
- F |
- 72 |
- 9.6 |
-
-
- | 176 |
- EGE10907-0247_21940 |
- BXD65 |
- F |
- 75 |
- 9.1 |
-
-
- | 177 |
- EGE10907-0248_21941 |
- BXD75 |
- F |
- 69 |
- 8.8 |
-
-
- | 178 |
- EGE10907-0249_21942_(MoGene-2_0-st) |
- BXD75 |
- M |
- 69 |
- 9.2 |
-
-
- | 179 |
- EGE10907-0250_21943 |
- BXD8 |
- F |
- 97 |
- 9.1 |
-
-
- | 180 |
- EGE10907-0251_21944 |
- BXD85 |
- F |
- 79 |
- 8.6 |
-
-
- | 181 |
- EGE10907-0252_21945 |
- BXD85 |
- M |
- 79 |
- 9.1 |
-
-
- | 182 |
- EGE10907-0253_21946 |
- BXD85 |
- M |
- 79 |
- 9.4 |
-
-
- | 183 |
- EGE10907-0254_21947 |
- BXD102 |
- M |
- 94 |
- 8.6 |
-
-
- | 184 |
- EGE10907-0255_21948 |
- BXD99 |
- F |
- 83 |
- 9 |
-
-
- | 185 |
- EGE10907-0256_21949 |
- BXD69 |
- F |
- 68 |
- 9 |
-
-
- | 186 |
- EGE10907-0257_21950 |
- BXD84 |
- F |
- 74 |
- 9.5 |
-
-
- | 187 |
- EGE10907-0258_21951 |
- BXD84 |
- F |
- 74 |
- 9.4 |
-
-
- | 188 |
- EGE10907-0259_21952 |
- BXD84 |
- M |
- 74 |
- 8.6 |
-
-
- | 189 |
- EGE10907-0260_21451 |
- BXD96 |
- M |
- 67 |
- 9.2 |
-
-
- | 190 |
- EGE10907-0261_21452 |
- BXD99 |
- F |
- 71 |
- 8.9 |
-
-
- | 191 |
- EGE10907-0262_21931 |
- BXD6 |
- F |
- 66 |
- 9.4 |
-
-
- | 192 |
- EGE10907-0263_21932 |
- BXD14 |
- F |
- 69 |
- 8.5 |
-
-
- | 193 |
- EGE10907-0264_21933 |
- BXD34 |
- M |
- 79 |
- 9.1 |
-
-
- | 194 |
- EGE10907-0265_21934 |
- BXD34 |
- M |
- 79 |
- 9.9 |
-
-
- | 195 |
- EGE10907-0266_21935 |
- BXD40 |
- F |
- 75 |
- 9.6 |
-
-
- | 196 |
- EGE10907-0267_21936 |
- BXD40 |
- M |
- 78 |
- 9.7 |
-
-
- | 197 |
- EGE10907-0268_21937 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 198 |
- EGE10907-0269_21938 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 199 |
- EGE10907-0270_21939 |
- BXD56 |
- M |
- 72 |
- 9.6 |
-
-
- | 200 |
- EGE10907-0271_21940 |
- BXD56 |
- M |
- 72 |
- 9.4 |
-
-
- | 201 |
- EGE10907-0272_21941 |
- BXD71 |
- F |
- 72 |
- 9.9 |
-
-
- | 202 |
- EGE10907-0273_21942 |
- BXD71 |
- F |
- 75 |
- 9.4 |
-
-
- | 203 |
- EGE10907-0274_21943 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 204 |
- EGE10907-0275_21944 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 205 |
- EGE10907-0276_21945 |
- BXD27 |
- M |
- 65 |
- 10 |
-
-
- | 206 |
- EGE10907-0277_21946 |
- BXD15 |
- M |
- 65 |
- 10 |
-
-
- | 207 |
- EGE10907-0278_21947 |
- BXD20 |
- F |
- 125 |
- 10 |
-
-
- | 208 |
- EGE10907-0279_21948 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 209 |
- EGE10907-0280_21949 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 210 |
- EGE10907-0281_21950 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 211 |
- EGE10907-0282_21951 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 212 |
- EGE10907-0283_21952 |
- BXD85 |
- F |
- 87 |
- 10 |
-
-
- | 213 |
- EGE10907-0284_21451 |
- BXD43 |
- M |
- 75 |
- 9.8 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/DoDTATRCRetBLMoGene2_0316/platform.rtf b/general/datasets/DoDTATRCRetBLMoGene2_0316/platform.rtf
deleted file mode 100644
index 19fc38c..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2_0316/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/DoDTATRCRetBLMoGene2_0316/processing.rtf b/general/datasets/DoDTATRCRetBLMoGene2_0316/processing.rtf
deleted file mode 100644
index a7b767e..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2_0316/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/DoDTATRCRetBLMoGene2_0316/summary.rtf b/general/datasets/DoDTATRCRetBLMoGene2_0316/summary.rtf
deleted file mode 100644
index 96a87e5..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2_0316/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/DoDTATRCRetBLMoGene2_0316/tissue.rtf b/general/datasets/DoDTATRCRetBLMoGene2_0316/tissue.rtf
deleted file mode 100644
index 056d7eb..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2_0316/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/DoDTATRCRetBLMoGene2_1213/acknowledgment.rtf b/general/datasets/DoDTATRCRetBLMoGene2_1213/acknowledgment.rtf
deleted file mode 100644
index 13c6b1e..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2_1213/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/DoDTATRCRetBLMoGene2_1213/cases.rtf b/general/datasets/DoDTATRCRetBLMoGene2_1213/cases.rtf
deleted file mode 100644
index 6b36c70..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2_1213/cases.rtf
+++ /dev/null
@@ -1,1728 +0,0 @@
-Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
-
-
-
-
-
-
-
-
-
- | Index |
- EIGC ID (LIMS ID) |
- Strain |
- Sex |
- Age at harvest |
- RIN Score |
-
-
- | 1 |
- 602 |
- BXD9 |
- F |
- 133 |
- 9.1 |
-
-
- | 2 |
- 603 |
- BXD9 |
- M |
- 100 |
- 9.5 |
-
-
- | 3 |
- 604 |
- BXD40 |
- F |
- 100 |
- 9.4 |
-
-
- | 4 |
- 605 |
- BXD40 |
- M |
- 100 |
- 9.1 |
-
-
- | 5 |
- 606 |
- BXD48 |
- F |
- 75 |
- 9.1 |
-
-
- | 6 |
- 607 |
- BXD48 |
- M |
- 75 |
- 8.6 |
-
-
- | 7 |
- 608 |
- BXD63 |
- F |
- 75 |
- 9.2 |
-
-
- | 8 |
- 609 |
- BXD63 |
- M |
- 61 |
- 9.4 |
-
-
- | 9 |
- 612 |
- BXD73 |
- M |
- 108 |
- 10 |
-
-
- | 10 |
- 614 |
- BXD87 |
- M |
- 85 |
- 9.2 |
-
-
- | 11 |
- 615 |
- BXD87 |
- F |
- 85 |
- 9.9 |
-
-
- | 12 |
- 616 |
- BXD69 |
- F |
- 76 |
- 9.3 |
-
-
- | 13 |
- 617 |
- BXD69 |
- M |
- 100 |
- 10 |
-
-
- | 14 |
- 618 |
- BXD51 |
- M |
- 82 |
- 8.9 |
-
-
- | 15 |
- 619 |
- BXD92 (BXD65b) |
- M |
- 82 |
- 8.8 |
-
-
- | 16 |
- 620 |
- BXD92 (BXD65b) |
- F |
- 82 |
- 8.8 |
-
-
- | 17 |
- 635 |
- BXD100 |
- M |
- 70 |
- 9 |
-
-
- | 18 |
- 636 |
- BXD100 |
- M |
- 70 |
- 8.8 |
-
-
- | 19 |
- 652 |
- BXD92 (BXD65b) |
- F |
- 64 |
- 9 |
-
-
- | 20 |
- 653 |
- BXD87 |
- F |
- 67 |
- 9.7 |
-
-
- | 21 |
- 654 |
- BXD87 |
- M |
- 67 |
- 8.9 |
-
-
- | 22 |
- 655 |
- BXD63 |
- M |
- 71 |
- 9 |
-
-
- | 23 |
- 660 |
- BXD69 |
- M |
- 97 |
- 10 |
-
-
- | 24 |
- 687 |
- BXD6 |
- M |
- 85 |
- 7.7 |
-
-
- | 25 |
- 688 |
- BXD6 |
- M |
- 85 |
- 9.4 |
-
-
- | 26 |
- 690 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 27 |
- 691 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 28 |
- 692 |
- BXD12 |
- M |
- 83 |
- 10 |
-
-
- | 29 |
- 695 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 30 |
- 696 |
- BXD5 |
- M |
- 77 |
- 10 |
-
-
- | 31 |
- 698 |
- BXD5 |
- F |
- 77 |
- 9.9 |
-
-
- | 32 |
- 699 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 33 |
- 701 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 34 |
- 702 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 35 |
- 705 |
- BXD8 |
- F |
- 77 |
- 9.2 |
-
-
- | 36 |
- 707 |
- BXD15 |
- F |
- 77 |
- 9.4 |
-
-
- | 37 |
- 708 |
- BXD15 |
- F |
- 77 |
- 9.1 |
-
-
- | 38 |
- 710 |
- BXD15 |
- M |
- 77 |
- 9.1 |
-
-
- | 39 |
- 713 |
- BXD22 |
- F |
- 71 |
- 9.5 |
-
-
- | 40 |
- 714 |
- BXD22 |
- F |
- 71 |
- 9.7 |
-
-
- | 41 |
- 716 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 42 |
- 717 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 43 |
- 719 |
- BXD14 |
- F |
- 70 |
- 9.2 |
-
-
- | 44 |
- 722 |
- BXD14 |
- M |
- 70 |
- 8.9 |
-
-
- | 45 |
- 723 |
- BXD14 |
- M |
- 70 |
- 9.2 |
-
-
- | 46 |
- 725 |
- BXD18 |
- F |
- 70 |
- 9 |
-
-
- | 47 |
- 726 |
- BXD18 |
- F |
- 70 |
- 9.1 |
-
-
- | 48 |
- 728 |
- BXD18 |
- M |
- 70 |
- 9.1 |
-
-
- | 49 |
- 729 |
- BXD18 |
- M |
- 70 |
- 9.2 |
-
-
- | 50 |
- 731 |
- BXD19 |
- F |
- 66 |
- 9.3 |
-
-
- | 51 |
- 732 |
- BXD19 |
- F |
- 66 |
- 9.4 |
-
-
- | 52 |
- 734 |
- BXD19 |
- M |
- 66 |
- 9.8 |
-
-
- | 53 |
- 735 |
- BXD19 |
- M |
- 66 |
- 9.4 |
-
-
- | 54 |
- 737 |
- BXD21 |
- F |
- 71 |
- 9.7 |
-
-
- | 55 |
- 738 |
- BXD21 |
- F |
- 71 |
- 9.6 |
-
-
- | 56 |
- 740 |
- BXD21 |
- M |
- 71 |
- 9.1 |
-
-
- | 57 |
- 741 |
- BXD21 |
- M |
- 71 |
- 9.7 |
-
-
- | 58 |
- 743 |
- BXD2 |
- F |
- 70 |
- 8.3 |
-
-
- | 59 |
- 744 |
- BXD2 |
- F |
- 70 |
- 8.6 |
-
-
- | 60 |
- 746 |
- BXD2 |
- M |
- 70 |
- 7.5 |
-
-
- | 61 |
- 747 |
- BXD2 |
- M |
- 77 |
- 8.6 |
-
-
- | 62 |
- 768 |
- BXD48 |
- M |
- 121 |
- 9.4 |
-
-
- | 63 |
- 770 |
- BXD92 (BXD65b) |
- M |
- 65 |
- 10 |
-
-
- | 64 |
- 771 |
- BXD101 |
- F |
- 85 |
- 8.3 |
-
-
- | 65 |
- 772 |
- BXD101 |
- F |
- 85 |
- 9.3 |
-
-
- | 66 |
- 773 |
- BXD101 |
- M |
- 86 |
- 9.5 |
-
-
- | 67 |
- 774 |
- BXD101 |
- M |
- 86 |
- 9.8 |
-
-
- | 68 |
- 775 |
- BXD102 |
- F |
- 66 |
- 9.5 |
-
-
- | 69 |
- 776 |
- BXD102 |
- F |
- 66 |
- 10 |
-
-
- | 70 |
- 777 |
- BXD102 |
- M |
- 84 |
- 9.6 |
-
-
- | 71 |
- 787 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 72 |
- 788 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 73 |
- 789 |
- BXD63 |
- F |
- 115 |
- 9.7 |
-
-
- | 74 |
- 790 |
- BXD100 |
- F |
- 72 |
- 9.8 |
-
-
- | 75 |
- 791 |
- BXD100 |
- F |
- 72 |
- 10 |
-
-
- | 76 |
- 818 |
- BXD51 |
- F |
- 77 |
- 9.7 |
-
-
- | 77 |
- 819 |
- BXD51 |
- F |
- 77 |
- 9.6 |
-
-
- | 78 |
- 820 |
- BXD51 |
- M |
- 72 |
- 9.7 |
-
-
- | 79 |
- 821 |
- BXD65 |
- M |
- 72 |
- 9.6 |
-
-
- | 80 |
- 822 |
- BXD65 |
- M |
- 65 |
- 9.5 |
-
-
- | 81 |
- 825 |
- BXD65 |
- F |
- 72 |
- 9.5 |
-
-
- | 82 |
- 827 |
- BXD86 |
- M |
- 69 |
- 9.1 |
-
-
- | 83 |
- 828 |
- BXD86 |
- M |
- 69 |
- 9.4 |
-
-
- | 84 |
- 829 |
- BXD90 |
- F |
- 69 |
- 9.6 |
-
-
- | 85 |
- 831 |
- BXD9 |
- M |
- 127 |
- 9.7 |
-
-
- | 86 |
- 832 |
- BXD39 |
- F |
- 99 |
- 9.4 |
-
-
- | 87 |
- 833 |
- BXD39 |
- F |
- 107 |
- 9.3 |
-
-
- | 88 |
- 834 |
- BXD60 |
- F |
- 107 |
- 9.5 |
-
-
- | 89 |
- 836 |
- BXD84 |
- M |
- 103 |
- 9.7 |
-
-
- | 90 |
- 846 |
- BXD39 |
- M |
- 63 |
- 9.7 |
-
-
- | 91 |
- 847 |
- BXD39 |
- M |
- 63 |
- 9.8 |
-
-
- | 92 |
- 849 |
- BXD20 |
- F |
- 70 |
- 10 |
-
-
- | 93 |
- 850 |
- BXD20 |
- M |
- 70 |
- 10 |
-
-
- | 94 |
- 851 |
- BXD20 |
- * |
- 70 |
- 9.5 |
-
-
- | 95 |
- 855 |
- DBA/2J |
- F |
- 78 |
- 9.7 |
-
-
- | 96 |
- 856 |
- DBA/2J |
- F |
- 78 |
- 10 |
-
-
- | 97 |
- 857 |
- DBA/2J |
- M |
- 78 |
- 10 |
-
-
- | 98 |
- 858 |
- DBA/2J |
- M |
- 78 |
- 9.9 |
-
-
- | 99 |
- 859 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 100 |
- 860 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 101 |
- 861 |
- C57BL/6J |
- M |
- 78 |
- 10 |
-
-
- | 102 |
- 862 |
- C57BL/6J |
- M |
- 78 |
- 9.6 |
-
-
- | 103 |
- EGE10907-0172_890_20844 |
- BXD28 |
- M |
- 75 |
- 10 |
-
-
- | 104 |
- EGE10907-0173_891_20845 |
- BXD28 |
- M |
- 75 |
- 9.7 |
-
-
- | 105 |
- EGE10907-0174_892_20846 |
- BXD28 |
- F |
- 75 |
- 9.7 |
-
-
- | 106 |
- EGE10907-0176_895_20848 |
- BXD33 |
- M |
- 75 |
- 9.88 |
-
-
- | 107 |
- EGE10907-0177_896_20849 |
- BXD33 |
- F |
- 75 |
- 10 |
-
-
- | 108 |
- EGE10907-0178_897_20850 |
- BXD33 |
- F |
- 75 |
- 9.4 |
-
-
- | 109 |
- EGE10907-0179_898_20851 |
- BXD36 |
- M |
- 75 |
- 9.4 |
-
-
- | 110 |
- EGE10907-0180_899_20852 |
- BXD36 |
- F |
- 75 |
- 9.5 |
-
-
- | 111 |
- EGE10907-0181_900_20853 |
- BXD36 |
- F |
- 75 |
- 9.1 |
-
-
- | 112 |
- EGE10907-0182_910_20854 |
- BXD27 |
- M |
- 70 |
- 9.7 |
-
-
- | 113 |
- EGE10907-0183_990_20855 |
- BXD9 |
- F |
- 98 |
- 9.4 |
-
-
- | 114 |
- EGE10907-0184_991_20856 |
- BXD16 |
- F |
- 113 |
- 10 |
-
-
- | 115 |
- EGE10907-0185_992_20857 |
- BXD16 |
- M |
- 113 |
- 9 |
-
-
- | 116 |
- EGE10907-0186_993_20858 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 117 |
- EGE10907-0187_994_20859 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 118 |
- EGE10907-0188_996_20860 |
- BXD48 |
- F |
- 98 |
- 9.4 |
-
-
- | 119 |
- EGE10907-0189_997_20861 |
- BXD73 |
- M |
- 106 |
- 10 |
-
-
- | 120 |
- EGE10907-0190_999_20862 |
- BXD11 |
- F |
- 121 |
- 9.6 |
-
-
- | 121 |
- EGE10907-0191_100_20863 |
- BXD11 |
- F |
- 121 |
- 9.9 |
-
-
- | 122 |
- EGE10907-0192_1010_21276 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 123 |
- EGE10907-0193_1011_21277 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 124 |
- EGE10907-0194_1012_21278 |
- BXD16 |
- F |
- 65 |
- 10 |
-
-
- | 125 |
- EGE10907-0195_1015_21279 |
- BXD16 |
- M |
- 65 |
- 10 |
-
-
- | 126 |
- EGE10907-0196_1019_21280 |
- BXD33 |
- M |
- 75 |
- 10 |
-
-
- | 127 |
- EGE10907-0197_1020_21281 |
- BXD36 |
- M |
- 78 |
- 10 |
-
-
- | 128 |
- EGE10907-0198_1021_21282 |
- BXD38 |
- F |
- 70 |
- 9.8 |
-
-
- | 129 |
- EGE10907-0199_1022_21283 |
- BXD38 |
- F |
- 70 |
- 10 |
-
-
- | 130 |
- EGE10907-0200_1023_21284 |
- BXD38 |
- M |
- 70 |
- 9.7 |
-
-
- | 131 |
- EGE10907-0201_1047_21285 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 132 |
- EGE10907-0202_1048_21286 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 133 |
- EGE10907-0203_1049_21287 |
- BXD38 |
- M |
- 77 |
- 10 |
-
-
- | 134 |
- EGE10907-0204_1050_21288 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 135 |
- EGE10907-0205_1051_21289 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 136 |
- EGE10907-0206_1052_21290 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 137 |
- EGE10907-0207_1053_21291 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 138 |
- EGE10907-0208_1054_21292 |
- BXD90 |
- F |
- 71 |
- 10 |
-
-
- | 139 |
- EGE10907-0209_1055_21293 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 140 |
- EGE10907-0210_1056_21294 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 141 |
- EGE10907-0211_1148_21295 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 142 |
- EGE10907-0212_1149_21296 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 143 |
- EGE10907-0213_1150_21297 |
- BXD31 |
- M |
- 90 |
- 10 |
-
-
- | 144 |
- EGE10907-0214_1151_21298 |
- BXD31 |
- M |
- 90 |
- 9.9 |
-
-
- | 145 |
- EGE10907-0215_1152_21299 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 146 |
- EGE10907-0216_21429 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 147 |
- EGE10907-0217_21430 |
- BXD42 |
- M |
- 83 |
- 10 |
-
-
- | 148 |
- EGE10907-0218_21431 |
- BXD42 |
- M |
- 83 |
- 9.3 |
-
-
- | 149 |
- EGE10907-0219_21432 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 150 |
- EGE10907-0220_21433 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 151 |
- EGE10907-0221_21434 |
- BXD50 |
- F |
- 92 |
- 10 |
-
-
- | 152 |
- EGE10907-0222_21435 |
- BXD1 |
- M |
- 73 |
- 9.6 |
-
-
- | 153 |
- EGE10907-0223_21436 |
- BXD13 |
- F |
- 71 |
- 9.7 |
-
-
- | 154 |
- EGE10907-0224_21437 |
- BXD1 |
- M |
- 71 |
- 9.5 |
-
-
- | 155 |
- EGE10907-0225_21438 |
- BXD13 |
- F |
- 71 |
- 9.6 |
-
-
- | 156 |
- EGE10907-0226_21439 |
- BXD43 |
- F |
- 85 |
- 10 |
-
-
- | 157 |
- EGE10907-0227_21452 |
- BXD43 |
- F |
- 85 |
- 9.6 |
-
-
- | 158 |
- EGE10907-0229_21442 |
- BXD43 |
- M |
- 85 |
- 8.2 |
-
-
- | 159 |
- EGE10907-0230_21443 |
- BXD50 |
- M |
- 69 |
- 9.4 |
-
-
- | 160 |
- EGE10907-0231_21444 |
- BXD1 |
- F |
- 68 |
- 9.4 |
-
-
- | 161 |
- EGE10907-0232_21445 |
- BXD1 |
- F |
- 68 |
- 9.6 |
-
-
- | 162 |
- EGE10907-0233_21446 |
- BXD29 |
- M |
- 65 |
- 9.5 |
-
-
- | 163 |
- EGE10907-0234_21447 |
- BXD29 |
- M |
- 65 |
- 10 |
-
-
- | 164 |
- EGE10907-0235_21448 |
- BXD75 |
- F |
- 68 |
- 10 |
-
-
- | 165 |
- EGE10907-0236_21449 |
- BXD75 |
- M |
- 68 |
- 10 |
-
-
- | 166 |
- EGE10907-0237_21450 |
- BXD96 |
- F |
- 67 |
- 9.9 |
-
-
- | 167 |
- EGE10907-0238_21931 |
- BXD99 |
- M |
- 71 |
- 7.9 |
-
-
- | 168 |
- EGE10907-0239_21932 |
- BXD99 |
- M |
- 71 |
- 9.7 |
-
-
- | 169 |
- EGE10907-0240_21933 |
- BXD67 |
- F |
- 68 |
- 8.8 |
-
-
- | 170 |
- EGE10907-0241_21934 |
- BXD67 |
- F |
- 68 |
- 8.5 |
-
-
- | 171 |
- EGE10907-0242_21935 |
- BXD67 |
- M |
- 68 |
- 9.5 |
-
-
- | 172 |
- EGE10907-0243_21936 |
- BXD67 |
- M |
- 68 |
- 9.6 |
-
-
- | 173 |
- EGE10907-0244_21937 |
- BXD6 |
- F |
- 68 |
- 9.6 |
-
-
- | 174 |
- EGE10907-0245_21938 |
- BXD12 |
- M |
- 82 |
- 9.5 |
-
-
- | 175 |
- EGE10907-0246_21939 |
- BXD60 |
- F |
- 72 |
- 9.6 |
-
-
- | 176 |
- EGE10907-0247_21940 |
- BXD65 |
- F |
- 75 |
- 9.1 |
-
-
- | 177 |
- EGE10907-0248_21941 |
- BXD75 |
- F |
- 69 |
- 8.8 |
-
-
- | 178 |
- EGE10907-0249_21942_(MoGene-2_0-st) |
- BXD75 |
- M |
- 69 |
- 9.2 |
-
-
- | 179 |
- EGE10907-0250_21943 |
- BXD8 |
- F |
- 97 |
- 9.1 |
-
-
- | 180 |
- EGE10907-0251_21944 |
- BXD85 |
- F |
- 79 |
- 8.6 |
-
-
- | 181 |
- EGE10907-0252_21945 |
- BXD85 |
- M |
- 79 |
- 9.1 |
-
-
- | 182 |
- EGE10907-0253_21946 |
- BXD85 |
- M |
- 79 |
- 9.4 |
-
-
- | 183 |
- EGE10907-0254_21947 |
- BXD102 |
- M |
- 94 |
- 8.6 |
-
-
- | 184 |
- EGE10907-0255_21948 |
- BXD99 |
- F |
- 83 |
- 9 |
-
-
- | 185 |
- EGE10907-0256_21949 |
- BXD69 |
- F |
- 68 |
- 9 |
-
-
- | 186 |
- EGE10907-0257_21950 |
- BXD84 |
- F |
- 74 |
- 9.5 |
-
-
- | 187 |
- EGE10907-0258_21951 |
- BXD84 |
- F |
- 74 |
- 9.4 |
-
-
- | 188 |
- EGE10907-0259_21952 |
- BXD84 |
- M |
- 74 |
- 8.6 |
-
-
- | 189 |
- EGE10907-0260_21451 |
- BXD96 |
- M |
- 67 |
- 9.2 |
-
-
- | 190 |
- EGE10907-0261_21452 |
- BXD99 |
- F |
- 71 |
- 8.9 |
-
-
- | 191 |
- EGE10907-0262_21931 |
- BXD6 |
- F |
- 66 |
- 9.4 |
-
-
- | 192 |
- EGE10907-0263_21932 |
- BXD14 |
- F |
- 69 |
- 8.5 |
-
-
- | 193 |
- EGE10907-0264_21933 |
- BXD34 |
- M |
- 79 |
- 9.1 |
-
-
- | 194 |
- EGE10907-0265_21934 |
- BXD34 |
- M |
- 79 |
- 9.9 |
-
-
- | 195 |
- EGE10907-0266_21935 |
- BXD40 |
- F |
- 75 |
- 9.6 |
-
-
- | 196 |
- EGE10907-0267_21936 |
- BXD40 |
- M |
- 78 |
- 9.7 |
-
-
- | 197 |
- EGE10907-0268_21937 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 198 |
- EGE10907-0269_21938 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 199 |
- EGE10907-0270_21939 |
- BXD56 |
- M |
- 72 |
- 9.6 |
-
-
- | 200 |
- EGE10907-0271_21940 |
- BXD56 |
- M |
- 72 |
- 9.4 |
-
-
- | 201 |
- EGE10907-0272_21941 |
- BXD71 |
- F |
- 72 |
- 9.9 |
-
-
- | 202 |
- EGE10907-0273_21942 |
- BXD71 |
- F |
- 75 |
- 9.4 |
-
-
- | 203 |
- EGE10907-0274_21943 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 204 |
- EGE10907-0275_21944 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 205 |
- EGE10907-0276_21945 |
- BXD27 |
- M |
- 65 |
- 10 |
-
-
- | 206 |
- EGE10907-0277_21946 |
- BXD15 |
- M |
- 65 |
- 10 |
-
-
- | 207 |
- EGE10907-0278_21947 |
- BXD20 |
- F |
- 125 |
- 10 |
-
-
- | 208 |
- EGE10907-0279_21948 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 209 |
- EGE10907-0280_21949 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 210 |
- EGE10907-0281_21950 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 211 |
- EGE10907-0282_21951 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 212 |
- EGE10907-0283_21952 |
- BXD85 |
- F |
- 87 |
- 10 |
-
-
- | 213 |
- EGE10907-0284_21451 |
- BXD43 |
- M |
- 75 |
- 9.8 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/DoDTATRCRetBLMoGene2_1213/platform.rtf b/general/datasets/DoDTATRCRetBLMoGene2_1213/platform.rtf
deleted file mode 100644
index 19fc38c..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2_1213/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/DoDTATRCRetBLMoGene2_1213/processing.rtf b/general/datasets/DoDTATRCRetBLMoGene2_1213/processing.rtf
deleted file mode 100644
index a7b767e..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2_1213/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/DoDTATRCRetBLMoGene2_1213/summary.rtf b/general/datasets/DoDTATRCRetBLMoGene2_1213/summary.rtf
deleted file mode 100644
index 96a87e5..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2_1213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/DoDTATRCRetBLMoGene2_1213/tissue.rtf b/general/datasets/DoDTATRCRetBLMoGene2_1213/tissue.rtf
deleted file mode 100644
index 056d7eb..0000000
--- a/general/datasets/DoDTATRCRetBLMoGene2_1213/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/DoDTATRCRetExMoGene2_0315/cases.rtf b/general/datasets/DoDTATRCRetExMoGene2_0315/cases.rtf
deleted file mode 100644
index 34f9530..0000000
--- a/general/datasets/DoDTATRCRetExMoGene2_0315/cases.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Almost all animals are young adults between 60 and 100 days of age (Table 1, minimum age is 60 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
-
-BXD strains:
-
-
- - The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s.
- - In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset.
- - The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
-
diff --git a/general/datasets/DoDTATRCRetExMoGene2_0315/experiment-design.rtf b/general/datasets/DoDTATRCRetExMoGene2_0315/experiment-design.rtf
deleted file mode 100644
index b43e509..0000000
--- a/general/datasets/DoDTATRCRetExMoGene2_0315/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Sample Processing: Dr. XiangDi Wang (UTHSC) and Becky King (Emory) were involved in the retinal extractions and isolation of RNA. The Affymetrix arrays were run by two different research cores: the Molecular Resource Center at UTHSC (Dr. William Taylor Director) and the Integrated Genomics Core at Emory University by Robert B Isett (Dr. Michael E. Zwick, Director). In a separate set of experiments we could not detect any significant difference in the arrays run at UTHSC or at Emory University.
-
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/DoDTATRCRetExMoGene2_0315/notes.rtf b/general/datasets/DoDTATRCRetExMoGene2_0315/notes.rtf
deleted file mode 100644
index cb14c74..0000000
--- a/general/datasets/DoDTATRCRetExMoGene2_0315/notes.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
-
-
- - NEIBank collection of ESTs and SAGE data.
- - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
- - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
- - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
- - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
- - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
-
diff --git a/general/datasets/DoDTATRCRetExMoGene2_0315/platform.rtf b/general/datasets/DoDTATRCRetExMoGene2_0315/platform.rtf
deleted file mode 100644
index cb5e1b8..0000000
--- a/general/datasets/DoDTATRCRetExMoGene2_0315/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Affymetrix Mouse Gene 2.0 ST Array: These expression arrays have been designed with a median of 22 unique probes per transcript. Each unique probe is 25 bases in length, which means that the array measures a median of 550 bases per transcript. The arrays provide comprehensive transcriptome coverage with over 30,000 coding and non-coding transcripts. In addition there is coverage for 592 microRNAs. For some arrays the RNA was pooled from two retinas and for other arrays were run on a single retina.
diff --git a/general/datasets/DoDTATRCRetExMoGene2_0315/summary.rtf b/general/datasets/DoDTATRCRetExMoGene2_0315/summary.rtf
deleted file mode 100644
index b6cf222..0000000
--- a/general/datasets/DoDTATRCRetExMoGene2_0315/summary.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-DoD TATRC Retina Dataset Affymetrix MouseGene 2.0 ST Array (____ 2015) RMA analysis and scaling by Arthur Centeno. This data set consists of 75 BXD strains, C57BL/6J, DBA/2J, both reciprocal F1s, and BALB/cByJ. A total of 80 strains were quantified. The data are now open and available for analysis.
-
-This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strain was computed as the mean of four samples per strain. Expression values on a log2 scale range from 6.25 to 18.08 (11.83 units), a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
-
-The lowest level of expression is 6.254 for ILMN_2747167 (Arhgap11a) from HEI Retina Illumina V6.2 (April 2010) RankInv **. Lowest single data about 5.842. The highest level of expression is 18.077 for ILMN_2516699 (Ubb). Highest single value is about 18.934.
diff --git a/general/datasets/DoDTATRCRetExMoGene2_0315/tissue.rtf b/general/datasets/DoDTATRCRetExMoGene2_0315/tissue.rtf
deleted file mode 100644
index 87eb144..0000000
--- a/general/datasets/DoDTATRCRetExMoGene2_0315/tissue.rtf
+++ /dev/null
@@ -1,13 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in 1 ml of 160 U/ml Ribolock for 1 min at room temperature. Dissecting and preparing eyes for RNA extraction Retinas for RNA removed from the eye and placed in Hank’s Balanced Salt solution with RiboLock (Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) and processed per manufacturer’s instructions (in brief form below).
-
-1) Sample collection for RNA isolation.
-
-2) Quickly remove the retinas with clean curved forceps after cervical dislocation of the mouse.
-
-3) Put each retina in 1 ml of 160 U/ml Ribolock for 1 min in RT.
-
-4) Move the retina to another tube with 50µl Ribolock, store in -80°C.
-
-5) The RNA was isolated using a QiaCube and the in column DNAse procedure.
-
-Quality Control: All RNA samples were checked for quality before running microarrays. The samples were analyzed using the Agilent 2100 Bioanalyzer. The RNA integrity values for each sample are presented in Table 1 below.
diff --git a/general/datasets/DoDTATRCRetExMoGene2_1313/acknowledgment.rtf b/general/datasets/DoDTATRCRetExMoGene2_1313/acknowledgment.rtf
deleted file mode 100644
index 13c6b1e..0000000
--- a/general/datasets/DoDTATRCRetExMoGene2_1313/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/DoDTATRCRetExMoGene2_1313/cases.rtf b/general/datasets/DoDTATRCRetExMoGene2_1313/cases.rtf
deleted file mode 100644
index 6b36c70..0000000
--- a/general/datasets/DoDTATRCRetExMoGene2_1313/cases.rtf
+++ /dev/null
@@ -1,1728 +0,0 @@
-Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
-
-
-
-
-
-
-
-
-
- | Index |
- EIGC ID (LIMS ID) |
- Strain |
- Sex |
- Age at harvest |
- RIN Score |
-
-
- | 1 |
- 602 |
- BXD9 |
- F |
- 133 |
- 9.1 |
-
-
- | 2 |
- 603 |
- BXD9 |
- M |
- 100 |
- 9.5 |
-
-
- | 3 |
- 604 |
- BXD40 |
- F |
- 100 |
- 9.4 |
-
-
- | 4 |
- 605 |
- BXD40 |
- M |
- 100 |
- 9.1 |
-
-
- | 5 |
- 606 |
- BXD48 |
- F |
- 75 |
- 9.1 |
-
-
- | 6 |
- 607 |
- BXD48 |
- M |
- 75 |
- 8.6 |
-
-
- | 7 |
- 608 |
- BXD63 |
- F |
- 75 |
- 9.2 |
-
-
- | 8 |
- 609 |
- BXD63 |
- M |
- 61 |
- 9.4 |
-
-
- | 9 |
- 612 |
- BXD73 |
- M |
- 108 |
- 10 |
-
-
- | 10 |
- 614 |
- BXD87 |
- M |
- 85 |
- 9.2 |
-
-
- | 11 |
- 615 |
- BXD87 |
- F |
- 85 |
- 9.9 |
-
-
- | 12 |
- 616 |
- BXD69 |
- F |
- 76 |
- 9.3 |
-
-
- | 13 |
- 617 |
- BXD69 |
- M |
- 100 |
- 10 |
-
-
- | 14 |
- 618 |
- BXD51 |
- M |
- 82 |
- 8.9 |
-
-
- | 15 |
- 619 |
- BXD92 (BXD65b) |
- M |
- 82 |
- 8.8 |
-
-
- | 16 |
- 620 |
- BXD92 (BXD65b) |
- F |
- 82 |
- 8.8 |
-
-
- | 17 |
- 635 |
- BXD100 |
- M |
- 70 |
- 9 |
-
-
- | 18 |
- 636 |
- BXD100 |
- M |
- 70 |
- 8.8 |
-
-
- | 19 |
- 652 |
- BXD92 (BXD65b) |
- F |
- 64 |
- 9 |
-
-
- | 20 |
- 653 |
- BXD87 |
- F |
- 67 |
- 9.7 |
-
-
- | 21 |
- 654 |
- BXD87 |
- M |
- 67 |
- 8.9 |
-
-
- | 22 |
- 655 |
- BXD63 |
- M |
- 71 |
- 9 |
-
-
- | 23 |
- 660 |
- BXD69 |
- M |
- 97 |
- 10 |
-
-
- | 24 |
- 687 |
- BXD6 |
- M |
- 85 |
- 7.7 |
-
-
- | 25 |
- 688 |
- BXD6 |
- M |
- 85 |
- 9.4 |
-
-
- | 26 |
- 690 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 27 |
- 691 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 28 |
- 692 |
- BXD12 |
- M |
- 83 |
- 10 |
-
-
- | 29 |
- 695 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 30 |
- 696 |
- BXD5 |
- M |
- 77 |
- 10 |
-
-
- | 31 |
- 698 |
- BXD5 |
- F |
- 77 |
- 9.9 |
-
-
- | 32 |
- 699 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 33 |
- 701 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 34 |
- 702 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 35 |
- 705 |
- BXD8 |
- F |
- 77 |
- 9.2 |
-
-
- | 36 |
- 707 |
- BXD15 |
- F |
- 77 |
- 9.4 |
-
-
- | 37 |
- 708 |
- BXD15 |
- F |
- 77 |
- 9.1 |
-
-
- | 38 |
- 710 |
- BXD15 |
- M |
- 77 |
- 9.1 |
-
-
- | 39 |
- 713 |
- BXD22 |
- F |
- 71 |
- 9.5 |
-
-
- | 40 |
- 714 |
- BXD22 |
- F |
- 71 |
- 9.7 |
-
-
- | 41 |
- 716 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 42 |
- 717 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 43 |
- 719 |
- BXD14 |
- F |
- 70 |
- 9.2 |
-
-
- | 44 |
- 722 |
- BXD14 |
- M |
- 70 |
- 8.9 |
-
-
- | 45 |
- 723 |
- BXD14 |
- M |
- 70 |
- 9.2 |
-
-
- | 46 |
- 725 |
- BXD18 |
- F |
- 70 |
- 9 |
-
-
- | 47 |
- 726 |
- BXD18 |
- F |
- 70 |
- 9.1 |
-
-
- | 48 |
- 728 |
- BXD18 |
- M |
- 70 |
- 9.1 |
-
-
- | 49 |
- 729 |
- BXD18 |
- M |
- 70 |
- 9.2 |
-
-
- | 50 |
- 731 |
- BXD19 |
- F |
- 66 |
- 9.3 |
-
-
- | 51 |
- 732 |
- BXD19 |
- F |
- 66 |
- 9.4 |
-
-
- | 52 |
- 734 |
- BXD19 |
- M |
- 66 |
- 9.8 |
-
-
- | 53 |
- 735 |
- BXD19 |
- M |
- 66 |
- 9.4 |
-
-
- | 54 |
- 737 |
- BXD21 |
- F |
- 71 |
- 9.7 |
-
-
- | 55 |
- 738 |
- BXD21 |
- F |
- 71 |
- 9.6 |
-
-
- | 56 |
- 740 |
- BXD21 |
- M |
- 71 |
- 9.1 |
-
-
- | 57 |
- 741 |
- BXD21 |
- M |
- 71 |
- 9.7 |
-
-
- | 58 |
- 743 |
- BXD2 |
- F |
- 70 |
- 8.3 |
-
-
- | 59 |
- 744 |
- BXD2 |
- F |
- 70 |
- 8.6 |
-
-
- | 60 |
- 746 |
- BXD2 |
- M |
- 70 |
- 7.5 |
-
-
- | 61 |
- 747 |
- BXD2 |
- M |
- 77 |
- 8.6 |
-
-
- | 62 |
- 768 |
- BXD48 |
- M |
- 121 |
- 9.4 |
-
-
- | 63 |
- 770 |
- BXD92 (BXD65b) |
- M |
- 65 |
- 10 |
-
-
- | 64 |
- 771 |
- BXD101 |
- F |
- 85 |
- 8.3 |
-
-
- | 65 |
- 772 |
- BXD101 |
- F |
- 85 |
- 9.3 |
-
-
- | 66 |
- 773 |
- BXD101 |
- M |
- 86 |
- 9.5 |
-
-
- | 67 |
- 774 |
- BXD101 |
- M |
- 86 |
- 9.8 |
-
-
- | 68 |
- 775 |
- BXD102 |
- F |
- 66 |
- 9.5 |
-
-
- | 69 |
- 776 |
- BXD102 |
- F |
- 66 |
- 10 |
-
-
- | 70 |
- 777 |
- BXD102 |
- M |
- 84 |
- 9.6 |
-
-
- | 71 |
- 787 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 72 |
- 788 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 73 |
- 789 |
- BXD63 |
- F |
- 115 |
- 9.7 |
-
-
- | 74 |
- 790 |
- BXD100 |
- F |
- 72 |
- 9.8 |
-
-
- | 75 |
- 791 |
- BXD100 |
- F |
- 72 |
- 10 |
-
-
- | 76 |
- 818 |
- BXD51 |
- F |
- 77 |
- 9.7 |
-
-
- | 77 |
- 819 |
- BXD51 |
- F |
- 77 |
- 9.6 |
-
-
- | 78 |
- 820 |
- BXD51 |
- M |
- 72 |
- 9.7 |
-
-
- | 79 |
- 821 |
- BXD65 |
- M |
- 72 |
- 9.6 |
-
-
- | 80 |
- 822 |
- BXD65 |
- M |
- 65 |
- 9.5 |
-
-
- | 81 |
- 825 |
- BXD65 |
- F |
- 72 |
- 9.5 |
-
-
- | 82 |
- 827 |
- BXD86 |
- M |
- 69 |
- 9.1 |
-
-
- | 83 |
- 828 |
- BXD86 |
- M |
- 69 |
- 9.4 |
-
-
- | 84 |
- 829 |
- BXD90 |
- F |
- 69 |
- 9.6 |
-
-
- | 85 |
- 831 |
- BXD9 |
- M |
- 127 |
- 9.7 |
-
-
- | 86 |
- 832 |
- BXD39 |
- F |
- 99 |
- 9.4 |
-
-
- | 87 |
- 833 |
- BXD39 |
- F |
- 107 |
- 9.3 |
-
-
- | 88 |
- 834 |
- BXD60 |
- F |
- 107 |
- 9.5 |
-
-
- | 89 |
- 836 |
- BXD84 |
- M |
- 103 |
- 9.7 |
-
-
- | 90 |
- 846 |
- BXD39 |
- M |
- 63 |
- 9.7 |
-
-
- | 91 |
- 847 |
- BXD39 |
- M |
- 63 |
- 9.8 |
-
-
- | 92 |
- 849 |
- BXD20 |
- F |
- 70 |
- 10 |
-
-
- | 93 |
- 850 |
- BXD20 |
- M |
- 70 |
- 10 |
-
-
- | 94 |
- 851 |
- BXD20 |
- * |
- 70 |
- 9.5 |
-
-
- | 95 |
- 855 |
- DBA/2J |
- F |
- 78 |
- 9.7 |
-
-
- | 96 |
- 856 |
- DBA/2J |
- F |
- 78 |
- 10 |
-
-
- | 97 |
- 857 |
- DBA/2J |
- M |
- 78 |
- 10 |
-
-
- | 98 |
- 858 |
- DBA/2J |
- M |
- 78 |
- 9.9 |
-
-
- | 99 |
- 859 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 100 |
- 860 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 101 |
- 861 |
- C57BL/6J |
- M |
- 78 |
- 10 |
-
-
- | 102 |
- 862 |
- C57BL/6J |
- M |
- 78 |
- 9.6 |
-
-
- | 103 |
- EGE10907-0172_890_20844 |
- BXD28 |
- M |
- 75 |
- 10 |
-
-
- | 104 |
- EGE10907-0173_891_20845 |
- BXD28 |
- M |
- 75 |
- 9.7 |
-
-
- | 105 |
- EGE10907-0174_892_20846 |
- BXD28 |
- F |
- 75 |
- 9.7 |
-
-
- | 106 |
- EGE10907-0176_895_20848 |
- BXD33 |
- M |
- 75 |
- 9.88 |
-
-
- | 107 |
- EGE10907-0177_896_20849 |
- BXD33 |
- F |
- 75 |
- 10 |
-
-
- | 108 |
- EGE10907-0178_897_20850 |
- BXD33 |
- F |
- 75 |
- 9.4 |
-
-
- | 109 |
- EGE10907-0179_898_20851 |
- BXD36 |
- M |
- 75 |
- 9.4 |
-
-
- | 110 |
- EGE10907-0180_899_20852 |
- BXD36 |
- F |
- 75 |
- 9.5 |
-
-
- | 111 |
- EGE10907-0181_900_20853 |
- BXD36 |
- F |
- 75 |
- 9.1 |
-
-
- | 112 |
- EGE10907-0182_910_20854 |
- BXD27 |
- M |
- 70 |
- 9.7 |
-
-
- | 113 |
- EGE10907-0183_990_20855 |
- BXD9 |
- F |
- 98 |
- 9.4 |
-
-
- | 114 |
- EGE10907-0184_991_20856 |
- BXD16 |
- F |
- 113 |
- 10 |
-
-
- | 115 |
- EGE10907-0185_992_20857 |
- BXD16 |
- M |
- 113 |
- 9 |
-
-
- | 116 |
- EGE10907-0186_993_20858 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 117 |
- EGE10907-0187_994_20859 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 118 |
- EGE10907-0188_996_20860 |
- BXD48 |
- F |
- 98 |
- 9.4 |
-
-
- | 119 |
- EGE10907-0189_997_20861 |
- BXD73 |
- M |
- 106 |
- 10 |
-
-
- | 120 |
- EGE10907-0190_999_20862 |
- BXD11 |
- F |
- 121 |
- 9.6 |
-
-
- | 121 |
- EGE10907-0191_100_20863 |
- BXD11 |
- F |
- 121 |
- 9.9 |
-
-
- | 122 |
- EGE10907-0192_1010_21276 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 123 |
- EGE10907-0193_1011_21277 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 124 |
- EGE10907-0194_1012_21278 |
- BXD16 |
- F |
- 65 |
- 10 |
-
-
- | 125 |
- EGE10907-0195_1015_21279 |
- BXD16 |
- M |
- 65 |
- 10 |
-
-
- | 126 |
- EGE10907-0196_1019_21280 |
- BXD33 |
- M |
- 75 |
- 10 |
-
-
- | 127 |
- EGE10907-0197_1020_21281 |
- BXD36 |
- M |
- 78 |
- 10 |
-
-
- | 128 |
- EGE10907-0198_1021_21282 |
- BXD38 |
- F |
- 70 |
- 9.8 |
-
-
- | 129 |
- EGE10907-0199_1022_21283 |
- BXD38 |
- F |
- 70 |
- 10 |
-
-
- | 130 |
- EGE10907-0200_1023_21284 |
- BXD38 |
- M |
- 70 |
- 9.7 |
-
-
- | 131 |
- EGE10907-0201_1047_21285 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 132 |
- EGE10907-0202_1048_21286 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 133 |
- EGE10907-0203_1049_21287 |
- BXD38 |
- M |
- 77 |
- 10 |
-
-
- | 134 |
- EGE10907-0204_1050_21288 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 135 |
- EGE10907-0205_1051_21289 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 136 |
- EGE10907-0206_1052_21290 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 137 |
- EGE10907-0207_1053_21291 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 138 |
- EGE10907-0208_1054_21292 |
- BXD90 |
- F |
- 71 |
- 10 |
-
-
- | 139 |
- EGE10907-0209_1055_21293 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 140 |
- EGE10907-0210_1056_21294 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 141 |
- EGE10907-0211_1148_21295 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 142 |
- EGE10907-0212_1149_21296 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 143 |
- EGE10907-0213_1150_21297 |
- BXD31 |
- M |
- 90 |
- 10 |
-
-
- | 144 |
- EGE10907-0214_1151_21298 |
- BXD31 |
- M |
- 90 |
- 9.9 |
-
-
- | 145 |
- EGE10907-0215_1152_21299 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 146 |
- EGE10907-0216_21429 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 147 |
- EGE10907-0217_21430 |
- BXD42 |
- M |
- 83 |
- 10 |
-
-
- | 148 |
- EGE10907-0218_21431 |
- BXD42 |
- M |
- 83 |
- 9.3 |
-
-
- | 149 |
- EGE10907-0219_21432 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 150 |
- EGE10907-0220_21433 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 151 |
- EGE10907-0221_21434 |
- BXD50 |
- F |
- 92 |
- 10 |
-
-
- | 152 |
- EGE10907-0222_21435 |
- BXD1 |
- M |
- 73 |
- 9.6 |
-
-
- | 153 |
- EGE10907-0223_21436 |
- BXD13 |
- F |
- 71 |
- 9.7 |
-
-
- | 154 |
- EGE10907-0224_21437 |
- BXD1 |
- M |
- 71 |
- 9.5 |
-
-
- | 155 |
- EGE10907-0225_21438 |
- BXD13 |
- F |
- 71 |
- 9.6 |
-
-
- | 156 |
- EGE10907-0226_21439 |
- BXD43 |
- F |
- 85 |
- 10 |
-
-
- | 157 |
- EGE10907-0227_21452 |
- BXD43 |
- F |
- 85 |
- 9.6 |
-
-
- | 158 |
- EGE10907-0229_21442 |
- BXD43 |
- M |
- 85 |
- 8.2 |
-
-
- | 159 |
- EGE10907-0230_21443 |
- BXD50 |
- M |
- 69 |
- 9.4 |
-
-
- | 160 |
- EGE10907-0231_21444 |
- BXD1 |
- F |
- 68 |
- 9.4 |
-
-
- | 161 |
- EGE10907-0232_21445 |
- BXD1 |
- F |
- 68 |
- 9.6 |
-
-
- | 162 |
- EGE10907-0233_21446 |
- BXD29 |
- M |
- 65 |
- 9.5 |
-
-
- | 163 |
- EGE10907-0234_21447 |
- BXD29 |
- M |
- 65 |
- 10 |
-
-
- | 164 |
- EGE10907-0235_21448 |
- BXD75 |
- F |
- 68 |
- 10 |
-
-
- | 165 |
- EGE10907-0236_21449 |
- BXD75 |
- M |
- 68 |
- 10 |
-
-
- | 166 |
- EGE10907-0237_21450 |
- BXD96 |
- F |
- 67 |
- 9.9 |
-
-
- | 167 |
- EGE10907-0238_21931 |
- BXD99 |
- M |
- 71 |
- 7.9 |
-
-
- | 168 |
- EGE10907-0239_21932 |
- BXD99 |
- M |
- 71 |
- 9.7 |
-
-
- | 169 |
- EGE10907-0240_21933 |
- BXD67 |
- F |
- 68 |
- 8.8 |
-
-
- | 170 |
- EGE10907-0241_21934 |
- BXD67 |
- F |
- 68 |
- 8.5 |
-
-
- | 171 |
- EGE10907-0242_21935 |
- BXD67 |
- M |
- 68 |
- 9.5 |
-
-
- | 172 |
- EGE10907-0243_21936 |
- BXD67 |
- M |
- 68 |
- 9.6 |
-
-
- | 173 |
- EGE10907-0244_21937 |
- BXD6 |
- F |
- 68 |
- 9.6 |
-
-
- | 174 |
- EGE10907-0245_21938 |
- BXD12 |
- M |
- 82 |
- 9.5 |
-
-
- | 175 |
- EGE10907-0246_21939 |
- BXD60 |
- F |
- 72 |
- 9.6 |
-
-
- | 176 |
- EGE10907-0247_21940 |
- BXD65 |
- F |
- 75 |
- 9.1 |
-
-
- | 177 |
- EGE10907-0248_21941 |
- BXD75 |
- F |
- 69 |
- 8.8 |
-
-
- | 178 |
- EGE10907-0249_21942_(MoGene-2_0-st) |
- BXD75 |
- M |
- 69 |
- 9.2 |
-
-
- | 179 |
- EGE10907-0250_21943 |
- BXD8 |
- F |
- 97 |
- 9.1 |
-
-
- | 180 |
- EGE10907-0251_21944 |
- BXD85 |
- F |
- 79 |
- 8.6 |
-
-
- | 181 |
- EGE10907-0252_21945 |
- BXD85 |
- M |
- 79 |
- 9.1 |
-
-
- | 182 |
- EGE10907-0253_21946 |
- BXD85 |
- M |
- 79 |
- 9.4 |
-
-
- | 183 |
- EGE10907-0254_21947 |
- BXD102 |
- M |
- 94 |
- 8.6 |
-
-
- | 184 |
- EGE10907-0255_21948 |
- BXD99 |
- F |
- 83 |
- 9 |
-
-
- | 185 |
- EGE10907-0256_21949 |
- BXD69 |
- F |
- 68 |
- 9 |
-
-
- | 186 |
- EGE10907-0257_21950 |
- BXD84 |
- F |
- 74 |
- 9.5 |
-
-
- | 187 |
- EGE10907-0258_21951 |
- BXD84 |
- F |
- 74 |
- 9.4 |
-
-
- | 188 |
- EGE10907-0259_21952 |
- BXD84 |
- M |
- 74 |
- 8.6 |
-
-
- | 189 |
- EGE10907-0260_21451 |
- BXD96 |
- M |
- 67 |
- 9.2 |
-
-
- | 190 |
- EGE10907-0261_21452 |
- BXD99 |
- F |
- 71 |
- 8.9 |
-
-
- | 191 |
- EGE10907-0262_21931 |
- BXD6 |
- F |
- 66 |
- 9.4 |
-
-
- | 192 |
- EGE10907-0263_21932 |
- BXD14 |
- F |
- 69 |
- 8.5 |
-
-
- | 193 |
- EGE10907-0264_21933 |
- BXD34 |
- M |
- 79 |
- 9.1 |
-
-
- | 194 |
- EGE10907-0265_21934 |
- BXD34 |
- M |
- 79 |
- 9.9 |
-
-
- | 195 |
- EGE10907-0266_21935 |
- BXD40 |
- F |
- 75 |
- 9.6 |
-
-
- | 196 |
- EGE10907-0267_21936 |
- BXD40 |
- M |
- 78 |
- 9.7 |
-
-
- | 197 |
- EGE10907-0268_21937 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 198 |
- EGE10907-0269_21938 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 199 |
- EGE10907-0270_21939 |
- BXD56 |
- M |
- 72 |
- 9.6 |
-
-
- | 200 |
- EGE10907-0271_21940 |
- BXD56 |
- M |
- 72 |
- 9.4 |
-
-
- | 201 |
- EGE10907-0272_21941 |
- BXD71 |
- F |
- 72 |
- 9.9 |
-
-
- | 202 |
- EGE10907-0273_21942 |
- BXD71 |
- F |
- 75 |
- 9.4 |
-
-
- | 203 |
- EGE10907-0274_21943 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 204 |
- EGE10907-0275_21944 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 205 |
- EGE10907-0276_21945 |
- BXD27 |
- M |
- 65 |
- 10 |
-
-
- | 206 |
- EGE10907-0277_21946 |
- BXD15 |
- M |
- 65 |
- 10 |
-
-
- | 207 |
- EGE10907-0278_21947 |
- BXD20 |
- F |
- 125 |
- 10 |
-
-
- | 208 |
- EGE10907-0279_21948 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 209 |
- EGE10907-0280_21949 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 210 |
- EGE10907-0281_21950 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 211 |
- EGE10907-0282_21951 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 212 |
- EGE10907-0283_21952 |
- BXD85 |
- F |
- 87 |
- 10 |
-
-
- | 213 |
- EGE10907-0284_21451 |
- BXD43 |
- M |
- 75 |
- 9.8 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/DoDTATRCRetExMoGene2_1313/platform.rtf b/general/datasets/DoDTATRCRetExMoGene2_1313/platform.rtf
deleted file mode 100644
index 19fc38c..0000000
--- a/general/datasets/DoDTATRCRetExMoGene2_1313/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/DoDTATRCRetExMoGene2_1313/processing.rtf b/general/datasets/DoDTATRCRetExMoGene2_1313/processing.rtf
deleted file mode 100644
index a7b767e..0000000
--- a/general/datasets/DoDTATRCRetExMoGene2_1313/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/DoDTATRCRetExMoGene2_1313/summary.rtf b/general/datasets/DoDTATRCRetExMoGene2_1313/summary.rtf
deleted file mode 100644
index 96a87e5..0000000
--- a/general/datasets/DoDTATRCRetExMoGene2_1313/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/DoDTATRCRetExMoGene2_1313/tissue.rtf b/general/datasets/DoDTATRCRetExMoGene2_1313/tissue.rtf
deleted file mode 100644
index 056d7eb..0000000
--- a/general/datasets/DoDTATRCRetExMoGene2_1313/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/DoDTATRCRetMoGene2_0315/cases.rtf b/general/datasets/DoDTATRCRetMoGene2_0315/cases.rtf
deleted file mode 100644
index 34f9530..0000000
--- a/general/datasets/DoDTATRCRetMoGene2_0315/cases.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Almost all animals are young adults between 60 and 100 days of age (Table 1, minimum age is 60 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
-
-BXD strains:
-
-
- - The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s.
- - In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset.
- - The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
-
diff --git a/general/datasets/DoDTATRCRetMoGene2_0315/experiment-design.rtf b/general/datasets/DoDTATRCRetMoGene2_0315/experiment-design.rtf
deleted file mode 100644
index b43e509..0000000
--- a/general/datasets/DoDTATRCRetMoGene2_0315/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Sample Processing: Dr. XiangDi Wang (UTHSC) and Becky King (Emory) were involved in the retinal extractions and isolation of RNA. The Affymetrix arrays were run by two different research cores: the Molecular Resource Center at UTHSC (Dr. William Taylor Director) and the Integrated Genomics Core at Emory University by Robert B Isett (Dr. Michael E. Zwick, Director). In a separate set of experiments we could not detect any significant difference in the arrays run at UTHSC or at Emory University.
-
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/DoDTATRCRetMoGene2_0315/notes.rtf b/general/datasets/DoDTATRCRetMoGene2_0315/notes.rtf
deleted file mode 100644
index cb14c74..0000000
--- a/general/datasets/DoDTATRCRetMoGene2_0315/notes.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
-
-
- - NEIBank collection of ESTs and SAGE data.
- - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
- - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
- - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
- - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
- - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
-
diff --git a/general/datasets/DoDTATRCRetMoGene2_0315/platform.rtf b/general/datasets/DoDTATRCRetMoGene2_0315/platform.rtf
deleted file mode 100644
index cb5e1b8..0000000
--- a/general/datasets/DoDTATRCRetMoGene2_0315/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Affymetrix Mouse Gene 2.0 ST Array: These expression arrays have been designed with a median of 22 unique probes per transcript. Each unique probe is 25 bases in length, which means that the array measures a median of 550 bases per transcript. The arrays provide comprehensive transcriptome coverage with over 30,000 coding and non-coding transcripts. In addition there is coverage for 592 microRNAs. For some arrays the RNA was pooled from two retinas and for other arrays were run on a single retina.
diff --git a/general/datasets/DoDTATRCRetMoGene2_0315/summary.rtf b/general/datasets/DoDTATRCRetMoGene2_0315/summary.rtf
deleted file mode 100644
index b6cf222..0000000
--- a/general/datasets/DoDTATRCRetMoGene2_0315/summary.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-DoD TATRC Retina Dataset Affymetrix MouseGene 2.0 ST Array (____ 2015) RMA analysis and scaling by Arthur Centeno. This data set consists of 75 BXD strains, C57BL/6J, DBA/2J, both reciprocal F1s, and BALB/cByJ. A total of 80 strains were quantified. The data are now open and available for analysis.
-
-This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strain was computed as the mean of four samples per strain. Expression values on a log2 scale range from 6.25 to 18.08 (11.83 units), a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
-
-The lowest level of expression is 6.254 for ILMN_2747167 (Arhgap11a) from HEI Retina Illumina V6.2 (April 2010) RankInv **. Lowest single data about 5.842. The highest level of expression is 18.077 for ILMN_2516699 (Ubb). Highest single value is about 18.934.
diff --git a/general/datasets/DoDTATRCRetMoGene2_0315/tissue.rtf b/general/datasets/DoDTATRCRetMoGene2_0315/tissue.rtf
deleted file mode 100644
index 87eb144..0000000
--- a/general/datasets/DoDTATRCRetMoGene2_0315/tissue.rtf
+++ /dev/null
@@ -1,13 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in 1 ml of 160 U/ml Ribolock for 1 min at room temperature. Dissecting and preparing eyes for RNA extraction Retinas for RNA removed from the eye and placed in Hank’s Balanced Salt solution with RiboLock (Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) and processed per manufacturer’s instructions (in brief form below).
-
-1) Sample collection for RNA isolation.
-
-2) Quickly remove the retinas with clean curved forceps after cervical dislocation of the mouse.
-
-3) Put each retina in 1 ml of 160 U/ml Ribolock for 1 min in RT.
-
-4) Move the retina to another tube with 50µl Ribolock, store in -80°C.
-
-5) The RNA was isolated using a QiaCube and the in column DNAse procedure.
-
-Quality Control: All RNA samples were checked for quality before running microarrays. The samples were analyzed using the Agilent 2100 Bioanalyzer. The RNA integrity values for each sample are presented in Table 1 below.
diff --git a/general/datasets/DoDTATRCRetMoGene2_1313/acknowledgment.rtf b/general/datasets/DoDTATRCRetMoGene2_1313/acknowledgment.rtf
deleted file mode 100644
index 13c6b1e..0000000
--- a/general/datasets/DoDTATRCRetMoGene2_1313/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/DoDTATRCRetMoGene2_1313/cases.rtf b/general/datasets/DoDTATRCRetMoGene2_1313/cases.rtf
deleted file mode 100644
index 6b36c70..0000000
--- a/general/datasets/DoDTATRCRetMoGene2_1313/cases.rtf
+++ /dev/null
@@ -1,1728 +0,0 @@
-Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
-
-
-
-
-
-
-
-
-
- | Index |
- EIGC ID (LIMS ID) |
- Strain |
- Sex |
- Age at harvest |
- RIN Score |
-
-
- | 1 |
- 602 |
- BXD9 |
- F |
- 133 |
- 9.1 |
-
-
- | 2 |
- 603 |
- BXD9 |
- M |
- 100 |
- 9.5 |
-
-
- | 3 |
- 604 |
- BXD40 |
- F |
- 100 |
- 9.4 |
-
-
- | 4 |
- 605 |
- BXD40 |
- M |
- 100 |
- 9.1 |
-
-
- | 5 |
- 606 |
- BXD48 |
- F |
- 75 |
- 9.1 |
-
-
- | 6 |
- 607 |
- BXD48 |
- M |
- 75 |
- 8.6 |
-
-
- | 7 |
- 608 |
- BXD63 |
- F |
- 75 |
- 9.2 |
-
-
- | 8 |
- 609 |
- BXD63 |
- M |
- 61 |
- 9.4 |
-
-
- | 9 |
- 612 |
- BXD73 |
- M |
- 108 |
- 10 |
-
-
- | 10 |
- 614 |
- BXD87 |
- M |
- 85 |
- 9.2 |
-
-
- | 11 |
- 615 |
- BXD87 |
- F |
- 85 |
- 9.9 |
-
-
- | 12 |
- 616 |
- BXD69 |
- F |
- 76 |
- 9.3 |
-
-
- | 13 |
- 617 |
- BXD69 |
- M |
- 100 |
- 10 |
-
-
- | 14 |
- 618 |
- BXD51 |
- M |
- 82 |
- 8.9 |
-
-
- | 15 |
- 619 |
- BXD92 (BXD65b) |
- M |
- 82 |
- 8.8 |
-
-
- | 16 |
- 620 |
- BXD92 (BXD65b) |
- F |
- 82 |
- 8.8 |
-
-
- | 17 |
- 635 |
- BXD100 |
- M |
- 70 |
- 9 |
-
-
- | 18 |
- 636 |
- BXD100 |
- M |
- 70 |
- 8.8 |
-
-
- | 19 |
- 652 |
- BXD92 (BXD65b) |
- F |
- 64 |
- 9 |
-
-
- | 20 |
- 653 |
- BXD87 |
- F |
- 67 |
- 9.7 |
-
-
- | 21 |
- 654 |
- BXD87 |
- M |
- 67 |
- 8.9 |
-
-
- | 22 |
- 655 |
- BXD63 |
- M |
- 71 |
- 9 |
-
-
- | 23 |
- 660 |
- BXD69 |
- M |
- 97 |
- 10 |
-
-
- | 24 |
- 687 |
- BXD6 |
- M |
- 85 |
- 7.7 |
-
-
- | 25 |
- 688 |
- BXD6 |
- M |
- 85 |
- 9.4 |
-
-
- | 26 |
- 690 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 27 |
- 691 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 28 |
- 692 |
- BXD12 |
- M |
- 83 |
- 10 |
-
-
- | 29 |
- 695 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 30 |
- 696 |
- BXD5 |
- M |
- 77 |
- 10 |
-
-
- | 31 |
- 698 |
- BXD5 |
- F |
- 77 |
- 9.9 |
-
-
- | 32 |
- 699 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 33 |
- 701 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 34 |
- 702 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 35 |
- 705 |
- BXD8 |
- F |
- 77 |
- 9.2 |
-
-
- | 36 |
- 707 |
- BXD15 |
- F |
- 77 |
- 9.4 |
-
-
- | 37 |
- 708 |
- BXD15 |
- F |
- 77 |
- 9.1 |
-
-
- | 38 |
- 710 |
- BXD15 |
- M |
- 77 |
- 9.1 |
-
-
- | 39 |
- 713 |
- BXD22 |
- F |
- 71 |
- 9.5 |
-
-
- | 40 |
- 714 |
- BXD22 |
- F |
- 71 |
- 9.7 |
-
-
- | 41 |
- 716 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 42 |
- 717 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 43 |
- 719 |
- BXD14 |
- F |
- 70 |
- 9.2 |
-
-
- | 44 |
- 722 |
- BXD14 |
- M |
- 70 |
- 8.9 |
-
-
- | 45 |
- 723 |
- BXD14 |
- M |
- 70 |
- 9.2 |
-
-
- | 46 |
- 725 |
- BXD18 |
- F |
- 70 |
- 9 |
-
-
- | 47 |
- 726 |
- BXD18 |
- F |
- 70 |
- 9.1 |
-
-
- | 48 |
- 728 |
- BXD18 |
- M |
- 70 |
- 9.1 |
-
-
- | 49 |
- 729 |
- BXD18 |
- M |
- 70 |
- 9.2 |
-
-
- | 50 |
- 731 |
- BXD19 |
- F |
- 66 |
- 9.3 |
-
-
- | 51 |
- 732 |
- BXD19 |
- F |
- 66 |
- 9.4 |
-
-
- | 52 |
- 734 |
- BXD19 |
- M |
- 66 |
- 9.8 |
-
-
- | 53 |
- 735 |
- BXD19 |
- M |
- 66 |
- 9.4 |
-
-
- | 54 |
- 737 |
- BXD21 |
- F |
- 71 |
- 9.7 |
-
-
- | 55 |
- 738 |
- BXD21 |
- F |
- 71 |
- 9.6 |
-
-
- | 56 |
- 740 |
- BXD21 |
- M |
- 71 |
- 9.1 |
-
-
- | 57 |
- 741 |
- BXD21 |
- M |
- 71 |
- 9.7 |
-
-
- | 58 |
- 743 |
- BXD2 |
- F |
- 70 |
- 8.3 |
-
-
- | 59 |
- 744 |
- BXD2 |
- F |
- 70 |
- 8.6 |
-
-
- | 60 |
- 746 |
- BXD2 |
- M |
- 70 |
- 7.5 |
-
-
- | 61 |
- 747 |
- BXD2 |
- M |
- 77 |
- 8.6 |
-
-
- | 62 |
- 768 |
- BXD48 |
- M |
- 121 |
- 9.4 |
-
-
- | 63 |
- 770 |
- BXD92 (BXD65b) |
- M |
- 65 |
- 10 |
-
-
- | 64 |
- 771 |
- BXD101 |
- F |
- 85 |
- 8.3 |
-
-
- | 65 |
- 772 |
- BXD101 |
- F |
- 85 |
- 9.3 |
-
-
- | 66 |
- 773 |
- BXD101 |
- M |
- 86 |
- 9.5 |
-
-
- | 67 |
- 774 |
- BXD101 |
- M |
- 86 |
- 9.8 |
-
-
- | 68 |
- 775 |
- BXD102 |
- F |
- 66 |
- 9.5 |
-
-
- | 69 |
- 776 |
- BXD102 |
- F |
- 66 |
- 10 |
-
-
- | 70 |
- 777 |
- BXD102 |
- M |
- 84 |
- 9.6 |
-
-
- | 71 |
- 787 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 72 |
- 788 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 73 |
- 789 |
- BXD63 |
- F |
- 115 |
- 9.7 |
-
-
- | 74 |
- 790 |
- BXD100 |
- F |
- 72 |
- 9.8 |
-
-
- | 75 |
- 791 |
- BXD100 |
- F |
- 72 |
- 10 |
-
-
- | 76 |
- 818 |
- BXD51 |
- F |
- 77 |
- 9.7 |
-
-
- | 77 |
- 819 |
- BXD51 |
- F |
- 77 |
- 9.6 |
-
-
- | 78 |
- 820 |
- BXD51 |
- M |
- 72 |
- 9.7 |
-
-
- | 79 |
- 821 |
- BXD65 |
- M |
- 72 |
- 9.6 |
-
-
- | 80 |
- 822 |
- BXD65 |
- M |
- 65 |
- 9.5 |
-
-
- | 81 |
- 825 |
- BXD65 |
- F |
- 72 |
- 9.5 |
-
-
- | 82 |
- 827 |
- BXD86 |
- M |
- 69 |
- 9.1 |
-
-
- | 83 |
- 828 |
- BXD86 |
- M |
- 69 |
- 9.4 |
-
-
- | 84 |
- 829 |
- BXD90 |
- F |
- 69 |
- 9.6 |
-
-
- | 85 |
- 831 |
- BXD9 |
- M |
- 127 |
- 9.7 |
-
-
- | 86 |
- 832 |
- BXD39 |
- F |
- 99 |
- 9.4 |
-
-
- | 87 |
- 833 |
- BXD39 |
- F |
- 107 |
- 9.3 |
-
-
- | 88 |
- 834 |
- BXD60 |
- F |
- 107 |
- 9.5 |
-
-
- | 89 |
- 836 |
- BXD84 |
- M |
- 103 |
- 9.7 |
-
-
- | 90 |
- 846 |
- BXD39 |
- M |
- 63 |
- 9.7 |
-
-
- | 91 |
- 847 |
- BXD39 |
- M |
- 63 |
- 9.8 |
-
-
- | 92 |
- 849 |
- BXD20 |
- F |
- 70 |
- 10 |
-
-
- | 93 |
- 850 |
- BXD20 |
- M |
- 70 |
- 10 |
-
-
- | 94 |
- 851 |
- BXD20 |
- * |
- 70 |
- 9.5 |
-
-
- | 95 |
- 855 |
- DBA/2J |
- F |
- 78 |
- 9.7 |
-
-
- | 96 |
- 856 |
- DBA/2J |
- F |
- 78 |
- 10 |
-
-
- | 97 |
- 857 |
- DBA/2J |
- M |
- 78 |
- 10 |
-
-
- | 98 |
- 858 |
- DBA/2J |
- M |
- 78 |
- 9.9 |
-
-
- | 99 |
- 859 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 100 |
- 860 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 101 |
- 861 |
- C57BL/6J |
- M |
- 78 |
- 10 |
-
-
- | 102 |
- 862 |
- C57BL/6J |
- M |
- 78 |
- 9.6 |
-
-
- | 103 |
- EGE10907-0172_890_20844 |
- BXD28 |
- M |
- 75 |
- 10 |
-
-
- | 104 |
- EGE10907-0173_891_20845 |
- BXD28 |
- M |
- 75 |
- 9.7 |
-
-
- | 105 |
- EGE10907-0174_892_20846 |
- BXD28 |
- F |
- 75 |
- 9.7 |
-
-
- | 106 |
- EGE10907-0176_895_20848 |
- BXD33 |
- M |
- 75 |
- 9.88 |
-
-
- | 107 |
- EGE10907-0177_896_20849 |
- BXD33 |
- F |
- 75 |
- 10 |
-
-
- | 108 |
- EGE10907-0178_897_20850 |
- BXD33 |
- F |
- 75 |
- 9.4 |
-
-
- | 109 |
- EGE10907-0179_898_20851 |
- BXD36 |
- M |
- 75 |
- 9.4 |
-
-
- | 110 |
- EGE10907-0180_899_20852 |
- BXD36 |
- F |
- 75 |
- 9.5 |
-
-
- | 111 |
- EGE10907-0181_900_20853 |
- BXD36 |
- F |
- 75 |
- 9.1 |
-
-
- | 112 |
- EGE10907-0182_910_20854 |
- BXD27 |
- M |
- 70 |
- 9.7 |
-
-
- | 113 |
- EGE10907-0183_990_20855 |
- BXD9 |
- F |
- 98 |
- 9.4 |
-
-
- | 114 |
- EGE10907-0184_991_20856 |
- BXD16 |
- F |
- 113 |
- 10 |
-
-
- | 115 |
- EGE10907-0185_992_20857 |
- BXD16 |
- M |
- 113 |
- 9 |
-
-
- | 116 |
- EGE10907-0186_993_20858 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 117 |
- EGE10907-0187_994_20859 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 118 |
- EGE10907-0188_996_20860 |
- BXD48 |
- F |
- 98 |
- 9.4 |
-
-
- | 119 |
- EGE10907-0189_997_20861 |
- BXD73 |
- M |
- 106 |
- 10 |
-
-
- | 120 |
- EGE10907-0190_999_20862 |
- BXD11 |
- F |
- 121 |
- 9.6 |
-
-
- | 121 |
- EGE10907-0191_100_20863 |
- BXD11 |
- F |
- 121 |
- 9.9 |
-
-
- | 122 |
- EGE10907-0192_1010_21276 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 123 |
- EGE10907-0193_1011_21277 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 124 |
- EGE10907-0194_1012_21278 |
- BXD16 |
- F |
- 65 |
- 10 |
-
-
- | 125 |
- EGE10907-0195_1015_21279 |
- BXD16 |
- M |
- 65 |
- 10 |
-
-
- | 126 |
- EGE10907-0196_1019_21280 |
- BXD33 |
- M |
- 75 |
- 10 |
-
-
- | 127 |
- EGE10907-0197_1020_21281 |
- BXD36 |
- M |
- 78 |
- 10 |
-
-
- | 128 |
- EGE10907-0198_1021_21282 |
- BXD38 |
- F |
- 70 |
- 9.8 |
-
-
- | 129 |
- EGE10907-0199_1022_21283 |
- BXD38 |
- F |
- 70 |
- 10 |
-
-
- | 130 |
- EGE10907-0200_1023_21284 |
- BXD38 |
- M |
- 70 |
- 9.7 |
-
-
- | 131 |
- EGE10907-0201_1047_21285 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 132 |
- EGE10907-0202_1048_21286 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 133 |
- EGE10907-0203_1049_21287 |
- BXD38 |
- M |
- 77 |
- 10 |
-
-
- | 134 |
- EGE10907-0204_1050_21288 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 135 |
- EGE10907-0205_1051_21289 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 136 |
- EGE10907-0206_1052_21290 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 137 |
- EGE10907-0207_1053_21291 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 138 |
- EGE10907-0208_1054_21292 |
- BXD90 |
- F |
- 71 |
- 10 |
-
-
- | 139 |
- EGE10907-0209_1055_21293 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 140 |
- EGE10907-0210_1056_21294 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 141 |
- EGE10907-0211_1148_21295 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 142 |
- EGE10907-0212_1149_21296 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 143 |
- EGE10907-0213_1150_21297 |
- BXD31 |
- M |
- 90 |
- 10 |
-
-
- | 144 |
- EGE10907-0214_1151_21298 |
- BXD31 |
- M |
- 90 |
- 9.9 |
-
-
- | 145 |
- EGE10907-0215_1152_21299 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 146 |
- EGE10907-0216_21429 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 147 |
- EGE10907-0217_21430 |
- BXD42 |
- M |
- 83 |
- 10 |
-
-
- | 148 |
- EGE10907-0218_21431 |
- BXD42 |
- M |
- 83 |
- 9.3 |
-
-
- | 149 |
- EGE10907-0219_21432 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 150 |
- EGE10907-0220_21433 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 151 |
- EGE10907-0221_21434 |
- BXD50 |
- F |
- 92 |
- 10 |
-
-
- | 152 |
- EGE10907-0222_21435 |
- BXD1 |
- M |
- 73 |
- 9.6 |
-
-
- | 153 |
- EGE10907-0223_21436 |
- BXD13 |
- F |
- 71 |
- 9.7 |
-
-
- | 154 |
- EGE10907-0224_21437 |
- BXD1 |
- M |
- 71 |
- 9.5 |
-
-
- | 155 |
- EGE10907-0225_21438 |
- BXD13 |
- F |
- 71 |
- 9.6 |
-
-
- | 156 |
- EGE10907-0226_21439 |
- BXD43 |
- F |
- 85 |
- 10 |
-
-
- | 157 |
- EGE10907-0227_21452 |
- BXD43 |
- F |
- 85 |
- 9.6 |
-
-
- | 158 |
- EGE10907-0229_21442 |
- BXD43 |
- M |
- 85 |
- 8.2 |
-
-
- | 159 |
- EGE10907-0230_21443 |
- BXD50 |
- M |
- 69 |
- 9.4 |
-
-
- | 160 |
- EGE10907-0231_21444 |
- BXD1 |
- F |
- 68 |
- 9.4 |
-
-
- | 161 |
- EGE10907-0232_21445 |
- BXD1 |
- F |
- 68 |
- 9.6 |
-
-
- | 162 |
- EGE10907-0233_21446 |
- BXD29 |
- M |
- 65 |
- 9.5 |
-
-
- | 163 |
- EGE10907-0234_21447 |
- BXD29 |
- M |
- 65 |
- 10 |
-
-
- | 164 |
- EGE10907-0235_21448 |
- BXD75 |
- F |
- 68 |
- 10 |
-
-
- | 165 |
- EGE10907-0236_21449 |
- BXD75 |
- M |
- 68 |
- 10 |
-
-
- | 166 |
- EGE10907-0237_21450 |
- BXD96 |
- F |
- 67 |
- 9.9 |
-
-
- | 167 |
- EGE10907-0238_21931 |
- BXD99 |
- M |
- 71 |
- 7.9 |
-
-
- | 168 |
- EGE10907-0239_21932 |
- BXD99 |
- M |
- 71 |
- 9.7 |
-
-
- | 169 |
- EGE10907-0240_21933 |
- BXD67 |
- F |
- 68 |
- 8.8 |
-
-
- | 170 |
- EGE10907-0241_21934 |
- BXD67 |
- F |
- 68 |
- 8.5 |
-
-
- | 171 |
- EGE10907-0242_21935 |
- BXD67 |
- M |
- 68 |
- 9.5 |
-
-
- | 172 |
- EGE10907-0243_21936 |
- BXD67 |
- M |
- 68 |
- 9.6 |
-
-
- | 173 |
- EGE10907-0244_21937 |
- BXD6 |
- F |
- 68 |
- 9.6 |
-
-
- | 174 |
- EGE10907-0245_21938 |
- BXD12 |
- M |
- 82 |
- 9.5 |
-
-
- | 175 |
- EGE10907-0246_21939 |
- BXD60 |
- F |
- 72 |
- 9.6 |
-
-
- | 176 |
- EGE10907-0247_21940 |
- BXD65 |
- F |
- 75 |
- 9.1 |
-
-
- | 177 |
- EGE10907-0248_21941 |
- BXD75 |
- F |
- 69 |
- 8.8 |
-
-
- | 178 |
- EGE10907-0249_21942_(MoGene-2_0-st) |
- BXD75 |
- M |
- 69 |
- 9.2 |
-
-
- | 179 |
- EGE10907-0250_21943 |
- BXD8 |
- F |
- 97 |
- 9.1 |
-
-
- | 180 |
- EGE10907-0251_21944 |
- BXD85 |
- F |
- 79 |
- 8.6 |
-
-
- | 181 |
- EGE10907-0252_21945 |
- BXD85 |
- M |
- 79 |
- 9.1 |
-
-
- | 182 |
- EGE10907-0253_21946 |
- BXD85 |
- M |
- 79 |
- 9.4 |
-
-
- | 183 |
- EGE10907-0254_21947 |
- BXD102 |
- M |
- 94 |
- 8.6 |
-
-
- | 184 |
- EGE10907-0255_21948 |
- BXD99 |
- F |
- 83 |
- 9 |
-
-
- | 185 |
- EGE10907-0256_21949 |
- BXD69 |
- F |
- 68 |
- 9 |
-
-
- | 186 |
- EGE10907-0257_21950 |
- BXD84 |
- F |
- 74 |
- 9.5 |
-
-
- | 187 |
- EGE10907-0258_21951 |
- BXD84 |
- F |
- 74 |
- 9.4 |
-
-
- | 188 |
- EGE10907-0259_21952 |
- BXD84 |
- M |
- 74 |
- 8.6 |
-
-
- | 189 |
- EGE10907-0260_21451 |
- BXD96 |
- M |
- 67 |
- 9.2 |
-
-
- | 190 |
- EGE10907-0261_21452 |
- BXD99 |
- F |
- 71 |
- 8.9 |
-
-
- | 191 |
- EGE10907-0262_21931 |
- BXD6 |
- F |
- 66 |
- 9.4 |
-
-
- | 192 |
- EGE10907-0263_21932 |
- BXD14 |
- F |
- 69 |
- 8.5 |
-
-
- | 193 |
- EGE10907-0264_21933 |
- BXD34 |
- M |
- 79 |
- 9.1 |
-
-
- | 194 |
- EGE10907-0265_21934 |
- BXD34 |
- M |
- 79 |
- 9.9 |
-
-
- | 195 |
- EGE10907-0266_21935 |
- BXD40 |
- F |
- 75 |
- 9.6 |
-
-
- | 196 |
- EGE10907-0267_21936 |
- BXD40 |
- M |
- 78 |
- 9.7 |
-
-
- | 197 |
- EGE10907-0268_21937 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 198 |
- EGE10907-0269_21938 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 199 |
- EGE10907-0270_21939 |
- BXD56 |
- M |
- 72 |
- 9.6 |
-
-
- | 200 |
- EGE10907-0271_21940 |
- BXD56 |
- M |
- 72 |
- 9.4 |
-
-
- | 201 |
- EGE10907-0272_21941 |
- BXD71 |
- F |
- 72 |
- 9.9 |
-
-
- | 202 |
- EGE10907-0273_21942 |
- BXD71 |
- F |
- 75 |
- 9.4 |
-
-
- | 203 |
- EGE10907-0274_21943 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 204 |
- EGE10907-0275_21944 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 205 |
- EGE10907-0276_21945 |
- BXD27 |
- M |
- 65 |
- 10 |
-
-
- | 206 |
- EGE10907-0277_21946 |
- BXD15 |
- M |
- 65 |
- 10 |
-
-
- | 207 |
- EGE10907-0278_21947 |
- BXD20 |
- F |
- 125 |
- 10 |
-
-
- | 208 |
- EGE10907-0279_21948 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 209 |
- EGE10907-0280_21949 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 210 |
- EGE10907-0281_21950 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 211 |
- EGE10907-0282_21951 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 212 |
- EGE10907-0283_21952 |
- BXD85 |
- F |
- 87 |
- 10 |
-
-
- | 213 |
- EGE10907-0284_21451 |
- BXD43 |
- M |
- 75 |
- 9.8 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/DoDTATRCRetMoGene2_1313/platform.rtf b/general/datasets/DoDTATRCRetMoGene2_1313/platform.rtf
deleted file mode 100644
index 19fc38c..0000000
--- a/general/datasets/DoDTATRCRetMoGene2_1313/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/DoDTATRCRetMoGene2_1313/processing.rtf b/general/datasets/DoDTATRCRetMoGene2_1313/processing.rtf
deleted file mode 100644
index a7b767e..0000000
--- a/general/datasets/DoDTATRCRetMoGene2_1313/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/DoDTATRCRetMoGene2_1313/summary.rtf b/general/datasets/DoDTATRCRetMoGene2_1313/summary.rtf
deleted file mode 100644
index 96a87e5..0000000
--- a/general/datasets/DoDTATRCRetMoGene2_1313/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/DoDTATRCRetMoGene2_1313/tissue.rtf b/general/datasets/DoDTATRCRetMoGene2_1313/tissue.rtf
deleted file mode 100644
index 056d7eb..0000000
--- a/general/datasets/DoDTATRCRetMoGene2_1313/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/Dod_bxd_ind_pfc_cd_rna_seq_1019/specifics.rtf b/general/datasets/Dod_bxd_ind_pfc_cd_rna_seq_1019/specifics.rtf
new file mode 100644
index 0000000..e64a89f
--- /dev/null
+++ b/general/datasets/Dod_bxd_ind_pfc_cd_rna_seq_1019/specifics.rtf
@@ -0,0 +1,3 @@
+DOD BXD Individual PFC GWI CD RNA-Seq (Oct19) TPM Log2
+
+Download data here: http://ipfs.genenetwork.org/ipfs/QmUxTJ6qW3eHQeVoyc4tYgooxYiYN6G6eekV1iLMh8EF5k/GN880
diff --git a/general/datasets/Dod_bxd_ind_pfc_cd_rna_seq_1019/summary.rtf b/general/datasets/Dod_bxd_ind_pfc_cd_rna_seq_1019/summary.rtf
new file mode 100644
index 0000000..7378ad9
--- /dev/null
+++ b/general/datasets/Dod_bxd_ind_pfc_cd_rna_seq_1019/summary.rtf
@@ -0,0 +1,9 @@
+The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
+
+D=diisopropylflurophosphate treatment
+
+CD= corticosterone + diisopropylflurophosphate treatment.
+
+Data are log2 gene expression for D or CD vs saline control
+
+This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dod_bxd_ind_pfc_cd_rna_seq_comb_1019/specifics.rtf b/general/datasets/Dod_bxd_ind_pfc_cd_rna_seq_comb_1019/specifics.rtf
new file mode 100644
index 0000000..45296b8
--- /dev/null
+++ b/general/datasets/Dod_bxd_ind_pfc_cd_rna_seq_comb_1019/specifics.rtf
@@ -0,0 +1 @@
+DOD BXD INDV PFC GWI CD RNA-Seq ComB (Dec19) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/Dod_bxd_ind_pfc_cd_rna_seq_comb_1019/summary.rtf b/general/datasets/Dod_bxd_ind_pfc_cd_rna_seq_comb_1019/summary.rtf
new file mode 100644
index 0000000..7378ad9
--- /dev/null
+++ b/general/datasets/Dod_bxd_ind_pfc_cd_rna_seq_comb_1019/summary.rtf
@@ -0,0 +1,9 @@
+The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
+
+D=diisopropylflurophosphate treatment
+
+CD= corticosterone + diisopropylflurophosphate treatment.
+
+Data are log2 gene expression for D or CD vs saline control
+
+This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dod_bxd_ind_pfc_ctl_rna_seq_1019/specifics.rtf b/general/datasets/Dod_bxd_ind_pfc_ctl_rna_seq_1019/specifics.rtf
new file mode 100644
index 0000000..79182c3
--- /dev/null
+++ b/general/datasets/Dod_bxd_ind_pfc_ctl_rna_seq_1019/specifics.rtf
@@ -0,0 +1,3 @@
+DOD BXD Individual PFC GWI CTL RNA-Seq (Oct19) TPM Log2
+
+Download data here: http://ipfs.genenetwork.org/ipfs/QmUxTJ6qW3eHQeVoyc4tYgooxYiYN6G6eekV1iLMh8EF5k/GN881
diff --git a/general/datasets/Dod_bxd_ind_pfc_ctl_rna_seq_1019/summary.rtf b/general/datasets/Dod_bxd_ind_pfc_ctl_rna_seq_1019/summary.rtf
new file mode 100644
index 0000000..7378ad9
--- /dev/null
+++ b/general/datasets/Dod_bxd_ind_pfc_ctl_rna_seq_1019/summary.rtf
@@ -0,0 +1,9 @@
+The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
+
+D=diisopropylflurophosphate treatment
+
+CD= corticosterone + diisopropylflurophosphate treatment.
+
+Data are log2 gene expression for D or CD vs saline control
+
+This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dod_bxd_ind_pfc_ctl_rna_seq_comb_1019/specifics.rtf b/general/datasets/Dod_bxd_ind_pfc_ctl_rna_seq_comb_1019/specifics.rtf
new file mode 100644
index 0000000..5c05883
--- /dev/null
+++ b/general/datasets/Dod_bxd_ind_pfc_ctl_rna_seq_comb_1019/specifics.rtf
@@ -0,0 +1 @@
+DOD BXD INDV PFC GWI CTL RNA-Seq ComB (Dec19) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/Dod_bxd_ind_pfc_ctl_rna_seq_comb_1019/summary.rtf b/general/datasets/Dod_bxd_ind_pfc_ctl_rna_seq_comb_1019/summary.rtf
new file mode 100644
index 0000000..7378ad9
--- /dev/null
+++ b/general/datasets/Dod_bxd_ind_pfc_ctl_rna_seq_comb_1019/summary.rtf
@@ -0,0 +1,9 @@
+The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
+
+D=diisopropylflurophosphate treatment
+
+CD= corticosterone + diisopropylflurophosphate treatment.
+
+Data are log2 gene expression for D or CD vs saline control
+
+This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dod_bxd_ind_pfc_dfp_rna_seq_1019/specifics.rtf b/general/datasets/Dod_bxd_ind_pfc_dfp_rna_seq_1019/specifics.rtf
new file mode 100644
index 0000000..d77d879
--- /dev/null
+++ b/general/datasets/Dod_bxd_ind_pfc_dfp_rna_seq_1019/specifics.rtf
@@ -0,0 +1,3 @@
+DOD BXD Individual PFC GWI DFP RNA-Seq (Oct19) TPM Log2
+
+Download data here: http://ipfs.genenetwork.org/ipfs/QmUxTJ6qW3eHQeVoyc4tYgooxYiYN6G6eekV1iLMh8EF5k/GN882
diff --git a/general/datasets/Dod_bxd_ind_pfc_dfp_rna_seq_1019/summary.rtf b/general/datasets/Dod_bxd_ind_pfc_dfp_rna_seq_1019/summary.rtf
new file mode 100644
index 0000000..7378ad9
--- /dev/null
+++ b/general/datasets/Dod_bxd_ind_pfc_dfp_rna_seq_1019/summary.rtf
@@ -0,0 +1,9 @@
+The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
+
+D=diisopropylflurophosphate treatment
+
+CD= corticosterone + diisopropylflurophosphate treatment.
+
+Data are log2 gene expression for D or CD vs saline control
+
+This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dod_bxd_ind_pfc_dfp_rna_seq_comb_1019/specifics.rtf b/general/datasets/Dod_bxd_ind_pfc_dfp_rna_seq_comb_1019/specifics.rtf
new file mode 100644
index 0000000..577b618
--- /dev/null
+++ b/general/datasets/Dod_bxd_ind_pfc_dfp_rna_seq_comb_1019/specifics.rtf
@@ -0,0 +1 @@
+DOD BXD INDV PFC GWI DFP RNA-Seq ComB (Dec19) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/Dod_bxd_ind_pfc_dfp_rna_seq_comb_1019/summary.rtf b/general/datasets/Dod_bxd_ind_pfc_dfp_rna_seq_comb_1019/summary.rtf
new file mode 100644
index 0000000..7378ad9
--- /dev/null
+++ b/general/datasets/Dod_bxd_ind_pfc_dfp_rna_seq_comb_1019/summary.rtf
@@ -0,0 +1,9 @@
+The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
+
+D=diisopropylflurophosphate treatment
+
+CD= corticosterone + diisopropylflurophosphate treatment.
+
+Data are log2 gene expression for D or CD vs saline control
+
+This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dod_bxd_pfc_cd_rna_seq_1019/specifics.rtf b/general/datasets/Dod_bxd_pfc_cd_rna_seq_1019/specifics.rtf
new file mode 100644
index 0000000..e8f6c71
--- /dev/null
+++ b/general/datasets/Dod_bxd_pfc_cd_rna_seq_1019/specifics.rtf
@@ -0,0 +1 @@
+DOD BXD PFC GWI CD RNA-Seq (Oct19) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/Dod_bxd_pfc_cd_rna_seq_1019/summary.rtf b/general/datasets/Dod_bxd_pfc_cd_rna_seq_1019/summary.rtf
new file mode 100644
index 0000000..7378ad9
--- /dev/null
+++ b/general/datasets/Dod_bxd_pfc_cd_rna_seq_1019/summary.rtf
@@ -0,0 +1,9 @@
+The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
+
+D=diisopropylflurophosphate treatment
+
+CD= corticosterone + diisopropylflurophosphate treatment.
+
+Data are log2 gene expression for D or CD vs saline control
+
+This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dod_bxd_pfc_cd_rna_seq_comb_1019/specifics.rtf b/general/datasets/Dod_bxd_pfc_cd_rna_seq_comb_1019/specifics.rtf
new file mode 100644
index 0000000..082f0ef
--- /dev/null
+++ b/general/datasets/Dod_bxd_pfc_cd_rna_seq_comb_1019/specifics.rtf
@@ -0,0 +1,3 @@
+DOD BXD PFC GWI CD RNA-Seq ComB (Dec19) TPM Log2
+
+DOWNLOAD DATA HERE: http://ipfs.genenetwork.org/ipfs/QmUxTJ6qW3eHQeVoyc4tYgooxYiYN6G6eekV1iLMh8EF5k/GN898
diff --git a/general/datasets/Dod_bxd_pfc_cd_rna_seq_comb_1019/summary.rtf b/general/datasets/Dod_bxd_pfc_cd_rna_seq_comb_1019/summary.rtf
new file mode 100644
index 0000000..7378ad9
--- /dev/null
+++ b/general/datasets/Dod_bxd_pfc_cd_rna_seq_comb_1019/summary.rtf
@@ -0,0 +1,9 @@
+The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
+
+D=diisopropylflurophosphate treatment
+
+CD= corticosterone + diisopropylflurophosphate treatment.
+
+Data are log2 gene expression for D or CD vs saline control
+
+This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dod_bxd_pfc_ctl_rna_seq_1019/specifics.rtf b/general/datasets/Dod_bxd_pfc_ctl_rna_seq_1019/specifics.rtf
new file mode 100644
index 0000000..052b038
--- /dev/null
+++ b/general/datasets/Dod_bxd_pfc_ctl_rna_seq_1019/specifics.rtf
@@ -0,0 +1 @@
+DOD BXD PFC GWI CTL RNA-Seq (Oct19)
\ No newline at end of file
diff --git a/general/datasets/Dod_bxd_pfc_ctl_rna_seq_1019/summary.rtf b/general/datasets/Dod_bxd_pfc_ctl_rna_seq_1019/summary.rtf
new file mode 100644
index 0000000..7378ad9
--- /dev/null
+++ b/general/datasets/Dod_bxd_pfc_ctl_rna_seq_1019/summary.rtf
@@ -0,0 +1,9 @@
+The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
+
+D=diisopropylflurophosphate treatment
+
+CD= corticosterone + diisopropylflurophosphate treatment.
+
+Data are log2 gene expression for D or CD vs saline control
+
+This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dod_bxd_pfc_ctl_rna_seq_comb_1019/specifics.rtf b/general/datasets/Dod_bxd_pfc_ctl_rna_seq_comb_1019/specifics.rtf
new file mode 100644
index 0000000..57e85c6
--- /dev/null
+++ b/general/datasets/Dod_bxd_pfc_ctl_rna_seq_comb_1019/specifics.rtf
@@ -0,0 +1,3 @@
+DOD BXD PFC GWI CTL RNA-Seq ComB (Dec19) TPM Log2
+
+DOWNLOAD DATA HERE: http://ipfs.genenetwork.org/ipfs/QmUxTJ6qW3eHQeVoyc4tYgooxYiYN6G6eekV1iLMh8EF5k/GN899
diff --git a/general/datasets/Dod_bxd_pfc_ctl_rna_seq_comb_1019/summary.rtf b/general/datasets/Dod_bxd_pfc_ctl_rna_seq_comb_1019/summary.rtf
new file mode 100644
index 0000000..7378ad9
--- /dev/null
+++ b/general/datasets/Dod_bxd_pfc_ctl_rna_seq_comb_1019/summary.rtf
@@ -0,0 +1,9 @@
+The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
+
+D=diisopropylflurophosphate treatment
+
+CD= corticosterone + diisopropylflurophosphate treatment.
+
+Data are log2 gene expression for D or CD vs saline control
+
+This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dod_bxd_pfc_dfp_rna_seq_1019/specifics.rtf b/general/datasets/Dod_bxd_pfc_dfp_rna_seq_1019/specifics.rtf
new file mode 100644
index 0000000..d6ad7e8
--- /dev/null
+++ b/general/datasets/Dod_bxd_pfc_dfp_rna_seq_1019/specifics.rtf
@@ -0,0 +1 @@
+DOD BXD PFC GWI DFP RNA-Seq (Oct19) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/Dod_bxd_pfc_dfp_rna_seq_1019/summary.rtf b/general/datasets/Dod_bxd_pfc_dfp_rna_seq_1019/summary.rtf
new file mode 100644
index 0000000..7378ad9
--- /dev/null
+++ b/general/datasets/Dod_bxd_pfc_dfp_rna_seq_1019/summary.rtf
@@ -0,0 +1,9 @@
+The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
+
+D=diisopropylflurophosphate treatment
+
+CD= corticosterone + diisopropylflurophosphate treatment.
+
+Data are log2 gene expression for D or CD vs saline control
+
+This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dod_bxd_pfc_dfp_rna_seq_comb_1019/specifics.rtf b/general/datasets/Dod_bxd_pfc_dfp_rna_seq_comb_1019/specifics.rtf
new file mode 100644
index 0000000..476fd21
--- /dev/null
+++ b/general/datasets/Dod_bxd_pfc_dfp_rna_seq_comb_1019/specifics.rtf
@@ -0,0 +1,3 @@
+DOD BXD PFC GWI DFP RNA-Seq ComB (Dec19) TPM Log2
+
+DOWNLOAD DATA HERE: http://ipfs.genenetwork.org/ipfs/QmUxTJ6qW3eHQeVoyc4tYgooxYiYN6G6eekV1iLMh8EF5k/GN900
diff --git a/general/datasets/Dod_bxd_pfc_dfp_rna_seq_comb_1019/summary.rtf b/general/datasets/Dod_bxd_pfc_dfp_rna_seq_comb_1019/summary.rtf
new file mode 100644
index 0000000..7378ad9
--- /dev/null
+++ b/general/datasets/Dod_bxd_pfc_dfp_rna_seq_comb_1019/summary.rtf
@@ -0,0 +1,9 @@
+The study consisted of treating BXD male and female mice to 20mg% corticosterone in the drinking water for 7 days. On the 8th day they were injected i.p. with 4mg/kg diisopropylflurophosphate, an irreversible cholinesterase inhibitor. Six hours after injection the prefrontal cortex was harvested to analyze gene expression for Il1b, Tnfa, Il6 by rtPCR.
+
+D=diisopropylflurophosphate treatment
+
+CD= corticosterone + diisopropylflurophosphate treatment.
+
+Data are log2 gene expression for D or CD vs saline control
+
+This dataset is confidential. Please refer to the contact information above to use the data.
diff --git a/general/datasets/Dodcmmrpretmogene2_0515/acknowledgment.rtf b/general/datasets/Dodcmmrpretmogene2_0515/acknowledgment.rtf
new file mode 100644
index 0000000..760f47e
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2_0515/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported by DoD CDMRP Grant W81XWH1210255 from the USA Army Medical Research & Materiel Command and the Telemedicine and Advanced Technology (EEG), NIH Grant R01EY017841 (EEG), Vision Core Grant P30EY006360 (P. Michael Iuvone), and Unrestricted Funds from Research to Prevent Blindness (Emory University). We thank XiangDi Wang and Arthur Centeno for their technical assistance in this project. This study was supported in part by the Emory Integrated Genomics Core (EIGC), which is subsidized by the Emory University School of Medicine and is one of the Emory Integrated Core Facilities.
diff --git a/general/datasets/Dodcmmrpretmogene2_0515/cases.rtf b/general/datasets/Dodcmmrpretmogene2_0515/cases.rtf
new file mode 100644
index 0000000..443b427
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2_0515/cases.rtf
@@ -0,0 +1,5 @@
+Almost all animals are young adults between 60 and 100 days of age (Table 1, minimum age is 60 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
+
+
+
+BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. BXD43 and higher were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. Several strains were specifically excluded from the dataset. For the BXD43 and higher, the DBA/2J parent carried both the Tyrp-1 mutation and the Gpnmb mutation and these two mutations produce pigment dispersion glaucoma. All of the mice carrying these two mutations were not included in the dataset: BXD53, BXD55, BXD62, BXD66, BXD68, BXD74, BXD77, BXD81, BXD88, BXD89, BXD95 and BXD98. In addition BXD 24 was omitted, since it developed a spontaneous mutation, rd16 (Cep290) which resulted in retinal degeneration and was renamed BXD24b/TyJ (ref). Several additional strains were excluded due to abnormally high Gfap levels observed in our Full HEI Retina (April 2010) dataset, these include: BXD32, BXD49, BXD70, BXD83 and BXD89.
diff --git a/general/datasets/Dodcmmrpretmogene2_0515/citation.rtf b/general/datasets/Dodcmmrpretmogene2_0515/citation.rtf
new file mode 100644
index 0000000..f803cee
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2_0515/citation.rtf
@@ -0,0 +1,36 @@
+Transcriptome networks in the mouse retina: An exon level BXD RI database
+
+Rebecca King,1 Lu Lu,2 Robert W. Williams,2 Eldon E. Geisert1
+
+1Department of Ophthalmology and Emory Eye Center, Emory University, Atlanta, GA; 2Department of Anatomy and Neurobiology and Center for Integrative and Translational Genomics, University of Tennessee Health Science Center, Memphis, TN
+
+Molecular Vision 2015; 21:1235-1251 http://www.molvis.org/molvis/v21/1235
+Received 07 July 2015 | Accepted 22 October 2015 | Published 26 October 2015
+
+Other Related Publications
+
+1 Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link)
+
+2. Freeman NE, Templeton JP, Orr WE, Lu L, Williams RW, Geisert EE (2011) Genetic networks in the mouse retina: Growth Associated Protein 43 and Phosphate Tensin Homology network. Molecular Vision 17:1355-1372.
+
+3 Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674
+
+4 Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link)
+
+5 Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.(Link)
+
+
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
+
+1 NEIBank collection of ESTs and SAGE data.
+
+2 RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+
+3 Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+
+4 Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+
+5 Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+
+6 Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
diff --git a/general/datasets/Dodcmmrpretmogene2_0515/contributors.rtf b/general/datasets/Dodcmmrpretmogene2_0515/contributors.rtf
new file mode 100644
index 0000000..ab95248
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2_0515/contributors.rtf
@@ -0,0 +1 @@
+Rebecca King, Lu Lu, Robert W. Williams, Eldon E. Geisert
diff --git a/general/datasets/Dodcmmrpretmogene2_0515/experiment-design.rtf b/general/datasets/Dodcmmrpretmogene2_0515/experiment-design.rtf
new file mode 100644
index 0000000..6256015
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2_0515/experiment-design.rtf
@@ -0,0 +1,3 @@
+ll of the procedures used involving mice were approved by IACUC at the Emory University and adhered to the ARVO Statement for the Use of Animals in Research. The Department of Defense (DoD) Congressionally Directed Medical Research Programs (CDMRP) Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array (May 15, 2015). Robust multiarray average (RMA) analysis and scaling were conducted by Arthur Centeno. This data set consists of 52 BXD strains, C57BL/6J, DBA/2J, and an F1 cross between C57BL/6J and DBA/2J. A total of 55 strains were quantified. There is a total of 222 microarrays. All data from each microarray used in this data set is publicly available on GeneNetwork.
+
+These are RMA expression data that have been normalized using what we call a 2z+8 scale, but without corrections for batch effects. The data for each strain were computed as the mean of four samples per strain. The expression values on the log2 scale ranged from 3.81 to 14.25 (10.26 units), a nominal range of approximately 1,000-fold. After taking the log2 of the original non-logged expression estimates, we converted the data within an array to a z-score. We then multiplied the z-score by 2. Finally, we added 8 units to ensure that no values were negative. The result was a scale with the mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A twofold difference in expression is equivalent to roughly 1 unit on this scale. The lowest level of expression was 3.81 (Olfr1186) from the DoD CDMRP (the Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array, May 15, 2015). The highest level of expression was rhodopsin for 17462036 (Rho). The highest single value was 14.25.
diff --git a/general/datasets/Dodcmmrpretmogene2_0515/notes.rtf b/general/datasets/Dodcmmrpretmogene2_0515/notes.rtf
new file mode 100644
index 0000000..7f9ba5d
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2_0515/notes.rtf
@@ -0,0 +1 @@
+This study includes Gene level and Exon level analysis.
diff --git a/general/datasets/Dodcmmrpretmogene2_0515/platform.rtf b/general/datasets/Dodcmmrpretmogene2_0515/platform.rtf
new file mode 100644
index 0000000..26dde86
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2_0515/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Gene 2.0 ST Array: These expression arrays have been designed with a median of 22 unique probes per transcript. Each unique probe is 25 bases in length, which means that the array measures a median of 550 bases per transcript. The arrays provide comprehensive transcriptome coverage with over 30,000 coding and non-coding transcripts. In addition there is coverage for over 600 microRNAs. For some arrays the RNA was pooled from two retinas and for other arrays were run on a single retina. Dr. XiangDi Wang (UTHSC) and Becky King (Emory) were involved in the retinal extractions and isolation of RNA. The Affymetrix arrays were run by two different research cores: the Molecular Resource Center at UTHSC (Dr. William Taylor Director) and the Integrated Genomics Core at Emory University by Robert B Isett (Dr. Michael E. Zwick, Director). In a separate set of experiments we tested a set of arrays from C57BL/6J retinas run at each facility to determine if there were batch effects or other confounding differences in the results. We could not detect any significant difference in the arrays run at UTHSC or at Emory University. Thus, we have included both sets of data into the analysis.
diff --git a/general/datasets/Dodcmmrpretmogene2_0515/summary.rtf b/general/datasets/Dodcmmrpretmogene2_0515/summary.rtf
new file mode 100644
index 0000000..c79428d
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2_0515/summary.rtf
@@ -0,0 +1,3 @@
+The DoD (Department of Defense) CDMRP (Congressionally Directed Medical Research Programs) Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array (May 15 2015) The RMA analysis and scaling was conducted by Arthur Centeno. This data set consists of 55 BXD strains, C57BL/6J, DBA/2J, a F1 cross between C57BL/6J and DBA/2J. A total of 58 strains were quantified. There is a total of 222 microarrays.
+
+This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strain was computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.81 to 14.25 (10.26 units), a nominal range of approximately 1,000-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale. The lowest level of expression is 3.81 (Olfr1186) from DoD CDMRP (Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array (May 15 2015) The highest level of expression is Rhodopsin for 17462036 (Rho). Highest single value is about 14.25.
diff --git a/general/datasets/Dodcmmrpretmogene2_0515/tissue.rtf b/general/datasets/Dodcmmrpretmogene2_0515/tissue.rtf
new file mode 100644
index 0000000..4f3c475
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2_0515/tissue.rtf
@@ -0,0 +1 @@
+Tissue preparation protocol. Mice were killed by rapid cervical dislocation. Retinas were removed immediately and placed in 1 ml of 160 U/ml Ribolock for 1 min at room temperature. The retinas were removed from the eye and placed in Hank’s Balanced Salt solution with RiboLock in 50µl Ribolock (Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) and stored in -80°C. The RNA was isolated using a QiaCube and the in column DNAse procedure. All RNA samples were checked for quality before running microarrays. The samples were analyzed using the Agilent 2100 Bioanalyzer. The RNA integrity values for ranged from 7.0 to 10. Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Dodcmmrpretmogene2ex_0515/acknowledgment.rtf b/general/datasets/Dodcmmrpretmogene2ex_0515/acknowledgment.rtf
new file mode 100644
index 0000000..760f47e
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2ex_0515/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported by DoD CDMRP Grant W81XWH1210255 from the USA Army Medical Research & Materiel Command and the Telemedicine and Advanced Technology (EEG), NIH Grant R01EY017841 (EEG), Vision Core Grant P30EY006360 (P. Michael Iuvone), and Unrestricted Funds from Research to Prevent Blindness (Emory University). We thank XiangDi Wang and Arthur Centeno for their technical assistance in this project. This study was supported in part by the Emory Integrated Genomics Core (EIGC), which is subsidized by the Emory University School of Medicine and is one of the Emory Integrated Core Facilities.
diff --git a/general/datasets/Dodcmmrpretmogene2ex_0515/cases.rtf b/general/datasets/Dodcmmrpretmogene2ex_0515/cases.rtf
new file mode 100644
index 0000000..443b427
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2ex_0515/cases.rtf
@@ -0,0 +1,5 @@
+Almost all animals are young adults between 60 and 100 days of age (Table 1, minimum age is 60 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
+
+
+
+BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. BXD43 and higher were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. Several strains were specifically excluded from the dataset. For the BXD43 and higher, the DBA/2J parent carried both the Tyrp-1 mutation and the Gpnmb mutation and these two mutations produce pigment dispersion glaucoma. All of the mice carrying these two mutations were not included in the dataset: BXD53, BXD55, BXD62, BXD66, BXD68, BXD74, BXD77, BXD81, BXD88, BXD89, BXD95 and BXD98. In addition BXD 24 was omitted, since it developed a spontaneous mutation, rd16 (Cep290) which resulted in retinal degeneration and was renamed BXD24b/TyJ (ref). Several additional strains were excluded due to abnormally high Gfap levels observed in our Full HEI Retina (April 2010) dataset, these include: BXD32, BXD49, BXD70, BXD83 and BXD89.
diff --git a/general/datasets/Dodcmmrpretmogene2ex_0515/citation.rtf b/general/datasets/Dodcmmrpretmogene2ex_0515/citation.rtf
new file mode 100644
index 0000000..f803cee
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2ex_0515/citation.rtf
@@ -0,0 +1,36 @@
+Transcriptome networks in the mouse retina: An exon level BXD RI database
+
+Rebecca King,1 Lu Lu,2 Robert W. Williams,2 Eldon E. Geisert1
+
+1Department of Ophthalmology and Emory Eye Center, Emory University, Atlanta, GA; 2Department of Anatomy and Neurobiology and Center for Integrative and Translational Genomics, University of Tennessee Health Science Center, Memphis, TN
+
+Molecular Vision 2015; 21:1235-1251 http://www.molvis.org/molvis/v21/1235
+Received 07 July 2015 | Accepted 22 October 2015 | Published 26 October 2015
+
+Other Related Publications
+
+1 Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link)
+
+2. Freeman NE, Templeton JP, Orr WE, Lu L, Williams RW, Geisert EE (2011) Genetic networks in the mouse retina: Growth Associated Protein 43 and Phosphate Tensin Homology network. Molecular Vision 17:1355-1372.
+
+3 Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674
+
+4 Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link)
+
+5 Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.(Link)
+
+
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
+
+1 NEIBank collection of ESTs and SAGE data.
+
+2 RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+
+3 Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+
+4 Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+
+5 Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+
+6 Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
diff --git a/general/datasets/Dodcmmrpretmogene2ex_0515/contributors.rtf b/general/datasets/Dodcmmrpretmogene2ex_0515/contributors.rtf
new file mode 100644
index 0000000..ab95248
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2ex_0515/contributors.rtf
@@ -0,0 +1 @@
+Rebecca King, Lu Lu, Robert W. Williams, Eldon E. Geisert
diff --git a/general/datasets/Dodcmmrpretmogene2ex_0515/experiment-design.rtf b/general/datasets/Dodcmmrpretmogene2ex_0515/experiment-design.rtf
new file mode 100644
index 0000000..6256015
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2ex_0515/experiment-design.rtf
@@ -0,0 +1,3 @@
+ll of the procedures used involving mice were approved by IACUC at the Emory University and adhered to the ARVO Statement for the Use of Animals in Research. The Department of Defense (DoD) Congressionally Directed Medical Research Programs (CDMRP) Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array (May 15, 2015). Robust multiarray average (RMA) analysis and scaling were conducted by Arthur Centeno. This data set consists of 52 BXD strains, C57BL/6J, DBA/2J, and an F1 cross between C57BL/6J and DBA/2J. A total of 55 strains were quantified. There is a total of 222 microarrays. All data from each microarray used in this data set is publicly available on GeneNetwork.
+
+These are RMA expression data that have been normalized using what we call a 2z+8 scale, but without corrections for batch effects. The data for each strain were computed as the mean of four samples per strain. The expression values on the log2 scale ranged from 3.81 to 14.25 (10.26 units), a nominal range of approximately 1,000-fold. After taking the log2 of the original non-logged expression estimates, we converted the data within an array to a z-score. We then multiplied the z-score by 2. Finally, we added 8 units to ensure that no values were negative. The result was a scale with the mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A twofold difference in expression is equivalent to roughly 1 unit on this scale. The lowest level of expression was 3.81 (Olfr1186) from the DoD CDMRP (the Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array, May 15, 2015). The highest level of expression was rhodopsin for 17462036 (Rho). The highest single value was 14.25.
diff --git a/general/datasets/Dodcmmrpretmogene2ex_0515/notes.rtf b/general/datasets/Dodcmmrpretmogene2ex_0515/notes.rtf
new file mode 100644
index 0000000..7f9ba5d
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2ex_0515/notes.rtf
@@ -0,0 +1 @@
+This study includes Gene level and Exon level analysis.
diff --git a/general/datasets/Dodcmmrpretmogene2ex_0515/platform.rtf b/general/datasets/Dodcmmrpretmogene2ex_0515/platform.rtf
new file mode 100644
index 0000000..26dde86
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2ex_0515/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Gene 2.0 ST Array: These expression arrays have been designed with a median of 22 unique probes per transcript. Each unique probe is 25 bases in length, which means that the array measures a median of 550 bases per transcript. The arrays provide comprehensive transcriptome coverage with over 30,000 coding and non-coding transcripts. In addition there is coverage for over 600 microRNAs. For some arrays the RNA was pooled from two retinas and for other arrays were run on a single retina. Dr. XiangDi Wang (UTHSC) and Becky King (Emory) were involved in the retinal extractions and isolation of RNA. The Affymetrix arrays were run by two different research cores: the Molecular Resource Center at UTHSC (Dr. William Taylor Director) and the Integrated Genomics Core at Emory University by Robert B Isett (Dr. Michael E. Zwick, Director). In a separate set of experiments we tested a set of arrays from C57BL/6J retinas run at each facility to determine if there were batch effects or other confounding differences in the results. We could not detect any significant difference in the arrays run at UTHSC or at Emory University. Thus, we have included both sets of data into the analysis.
diff --git a/general/datasets/Dodcmmrpretmogene2ex_0515/specifics.rtf b/general/datasets/Dodcmmrpretmogene2ex_0515/specifics.rtf
new file mode 100644
index 0000000..ce43067
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2ex_0515/specifics.rtf
@@ -0,0 +1 @@
+This is the normal exon level dataset
diff --git a/general/datasets/Dodcmmrpretmogene2ex_0515/summary.rtf b/general/datasets/Dodcmmrpretmogene2ex_0515/summary.rtf
new file mode 100644
index 0000000..c79428d
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2ex_0515/summary.rtf
@@ -0,0 +1,3 @@
+The DoD (Department of Defense) CDMRP (Congressionally Directed Medical Research Programs) Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array (May 15 2015) The RMA analysis and scaling was conducted by Arthur Centeno. This data set consists of 55 BXD strains, C57BL/6J, DBA/2J, a F1 cross between C57BL/6J and DBA/2J. A total of 58 strains were quantified. There is a total of 222 microarrays.
+
+This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strain was computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.81 to 14.25 (10.26 units), a nominal range of approximately 1,000-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale. The lowest level of expression is 3.81 (Olfr1186) from DoD CDMRP (Normal Retina Database uses the Affymetrix MouseGene 2.0 ST Array (May 15 2015) The highest level of expression is Rhodopsin for 17462036 (Rho). Highest single value is about 14.25.
diff --git a/general/datasets/Dodcmmrpretmogene2ex_0515/tissue.rtf b/general/datasets/Dodcmmrpretmogene2ex_0515/tissue.rtf
new file mode 100644
index 0000000..4f3c475
--- /dev/null
+++ b/general/datasets/Dodcmmrpretmogene2ex_0515/tissue.rtf
@@ -0,0 +1 @@
+Tissue preparation protocol. Mice were killed by rapid cervical dislocation. Retinas were removed immediately and placed in 1 ml of 160 U/ml Ribolock for 1 min at room temperature. The retinas were removed from the eye and placed in Hank’s Balanced Salt solution with RiboLock in 50µl Ribolock (Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) and stored in -80°C. The RNA was isolated using a QiaCube and the in column DNAse procedure. All RNA samples were checked for quality before running microarrays. The samples were analyzed using the Agilent 2100 Bioanalyzer. The RNA integrity values for ranged from 7.0 to 10. Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Dodretblastvsnormal_0416/acknowledgment.rtf b/general/datasets/Dodretblastvsnormal_0416/acknowledgment.rtf
new file mode 100644
index 0000000..13c6b1e
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormal_0416/acknowledgment.rtf
@@ -0,0 +1 @@
+DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/Dodretblastvsnormal_0416/cases.rtf b/general/datasets/Dodretblastvsnormal_0416/cases.rtf
new file mode 100644
index 0000000..6b36c70
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormal_0416/cases.rtf
@@ -0,0 +1,1728 @@
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+
+
+
+
+
+ | Index |
+ EIGC ID (LIMS ID) |
+ Strain |
+ Sex |
+ Age at harvest |
+ RIN Score |
+
+
+ | 1 |
+ 602 |
+ BXD9 |
+ F |
+ 133 |
+ 9.1 |
+
+
+ | 2 |
+ 603 |
+ BXD9 |
+ M |
+ 100 |
+ 9.5 |
+
+
+ | 3 |
+ 604 |
+ BXD40 |
+ F |
+ 100 |
+ 9.4 |
+
+
+ | 4 |
+ 605 |
+ BXD40 |
+ M |
+ 100 |
+ 9.1 |
+
+
+ | 5 |
+ 606 |
+ BXD48 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 6 |
+ 607 |
+ BXD48 |
+ M |
+ 75 |
+ 8.6 |
+
+
+ | 7 |
+ 608 |
+ BXD63 |
+ F |
+ 75 |
+ 9.2 |
+
+
+ | 8 |
+ 609 |
+ BXD63 |
+ M |
+ 61 |
+ 9.4 |
+
+
+ | 9 |
+ 612 |
+ BXD73 |
+ M |
+ 108 |
+ 10 |
+
+
+ | 10 |
+ 614 |
+ BXD87 |
+ M |
+ 85 |
+ 9.2 |
+
+
+ | 11 |
+ 615 |
+ BXD87 |
+ F |
+ 85 |
+ 9.9 |
+
+
+ | 12 |
+ 616 |
+ BXD69 |
+ F |
+ 76 |
+ 9.3 |
+
+
+ | 13 |
+ 617 |
+ BXD69 |
+ M |
+ 100 |
+ 10 |
+
+
+ | 14 |
+ 618 |
+ BXD51 |
+ M |
+ 82 |
+ 8.9 |
+
+
+ | 15 |
+ 619 |
+ BXD92 (BXD65b) |
+ M |
+ 82 |
+ 8.8 |
+
+
+ | 16 |
+ 620 |
+ BXD92 (BXD65b) |
+ F |
+ 82 |
+ 8.8 |
+
+
+ | 17 |
+ 635 |
+ BXD100 |
+ M |
+ 70 |
+ 9 |
+
+
+ | 18 |
+ 636 |
+ BXD100 |
+ M |
+ 70 |
+ 8.8 |
+
+
+ | 19 |
+ 652 |
+ BXD92 (BXD65b) |
+ F |
+ 64 |
+ 9 |
+
+
+ | 20 |
+ 653 |
+ BXD87 |
+ F |
+ 67 |
+ 9.7 |
+
+
+ | 21 |
+ 654 |
+ BXD87 |
+ M |
+ 67 |
+ 8.9 |
+
+
+ | 22 |
+ 655 |
+ BXD63 |
+ M |
+ 71 |
+ 9 |
+
+
+ | 23 |
+ 660 |
+ BXD69 |
+ M |
+ 97 |
+ 10 |
+
+
+ | 24 |
+ 687 |
+ BXD6 |
+ M |
+ 85 |
+ 7.7 |
+
+
+ | 25 |
+ 688 |
+ BXD6 |
+ M |
+ 85 |
+ 9.4 |
+
+
+ | 26 |
+ 690 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 27 |
+ 691 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 28 |
+ 692 |
+ BXD12 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 29 |
+ 695 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 30 |
+ 696 |
+ BXD5 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 31 |
+ 698 |
+ BXD5 |
+ F |
+ 77 |
+ 9.9 |
+
+
+ | 32 |
+ 699 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 33 |
+ 701 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 34 |
+ 702 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 35 |
+ 705 |
+ BXD8 |
+ F |
+ 77 |
+ 9.2 |
+
+
+ | 36 |
+ 707 |
+ BXD15 |
+ F |
+ 77 |
+ 9.4 |
+
+
+ | 37 |
+ 708 |
+ BXD15 |
+ F |
+ 77 |
+ 9.1 |
+
+
+ | 38 |
+ 710 |
+ BXD15 |
+ M |
+ 77 |
+ 9.1 |
+
+
+ | 39 |
+ 713 |
+ BXD22 |
+ F |
+ 71 |
+ 9.5 |
+
+
+ | 40 |
+ 714 |
+ BXD22 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 41 |
+ 716 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 42 |
+ 717 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 43 |
+ 719 |
+ BXD14 |
+ F |
+ 70 |
+ 9.2 |
+
+
+ | 44 |
+ 722 |
+ BXD14 |
+ M |
+ 70 |
+ 8.9 |
+
+
+ | 45 |
+ 723 |
+ BXD14 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 46 |
+ 725 |
+ BXD18 |
+ F |
+ 70 |
+ 9 |
+
+
+ | 47 |
+ 726 |
+ BXD18 |
+ F |
+ 70 |
+ 9.1 |
+
+
+ | 48 |
+ 728 |
+ BXD18 |
+ M |
+ 70 |
+ 9.1 |
+
+
+ | 49 |
+ 729 |
+ BXD18 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 50 |
+ 731 |
+ BXD19 |
+ F |
+ 66 |
+ 9.3 |
+
+
+ | 51 |
+ 732 |
+ BXD19 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 52 |
+ 734 |
+ BXD19 |
+ M |
+ 66 |
+ 9.8 |
+
+
+ | 53 |
+ 735 |
+ BXD19 |
+ M |
+ 66 |
+ 9.4 |
+
+
+ | 54 |
+ 737 |
+ BXD21 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 55 |
+ 738 |
+ BXD21 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 56 |
+ 740 |
+ BXD21 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 57 |
+ 741 |
+ BXD21 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 58 |
+ 743 |
+ BXD2 |
+ F |
+ 70 |
+ 8.3 |
+
+
+ | 59 |
+ 744 |
+ BXD2 |
+ F |
+ 70 |
+ 8.6 |
+
+
+ | 60 |
+ 746 |
+ BXD2 |
+ M |
+ 70 |
+ 7.5 |
+
+
+ | 61 |
+ 747 |
+ BXD2 |
+ M |
+ 77 |
+ 8.6 |
+
+
+ | 62 |
+ 768 |
+ BXD48 |
+ M |
+ 121 |
+ 9.4 |
+
+
+ | 63 |
+ 770 |
+ BXD92 (BXD65b) |
+ M |
+ 65 |
+ 10 |
+
+
+ | 64 |
+ 771 |
+ BXD101 |
+ F |
+ 85 |
+ 8.3 |
+
+
+ | 65 |
+ 772 |
+ BXD101 |
+ F |
+ 85 |
+ 9.3 |
+
+
+ | 66 |
+ 773 |
+ BXD101 |
+ M |
+ 86 |
+ 9.5 |
+
+
+ | 67 |
+ 774 |
+ BXD101 |
+ M |
+ 86 |
+ 9.8 |
+
+
+ | 68 |
+ 775 |
+ BXD102 |
+ F |
+ 66 |
+ 9.5 |
+
+
+ | 69 |
+ 776 |
+ BXD102 |
+ F |
+ 66 |
+ 10 |
+
+
+ | 70 |
+ 777 |
+ BXD102 |
+ M |
+ 84 |
+ 9.6 |
+
+
+ | 71 |
+ 787 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 72 |
+ 788 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 73 |
+ 789 |
+ BXD63 |
+ F |
+ 115 |
+ 9.7 |
+
+
+ | 74 |
+ 790 |
+ BXD100 |
+ F |
+ 72 |
+ 9.8 |
+
+
+ | 75 |
+ 791 |
+ BXD100 |
+ F |
+ 72 |
+ 10 |
+
+
+ | 76 |
+ 818 |
+ BXD51 |
+ F |
+ 77 |
+ 9.7 |
+
+
+ | 77 |
+ 819 |
+ BXD51 |
+ F |
+ 77 |
+ 9.6 |
+
+
+ | 78 |
+ 820 |
+ BXD51 |
+ M |
+ 72 |
+ 9.7 |
+
+
+ | 79 |
+ 821 |
+ BXD65 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 80 |
+ 822 |
+ BXD65 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 81 |
+ 825 |
+ BXD65 |
+ F |
+ 72 |
+ 9.5 |
+
+
+ | 82 |
+ 827 |
+ BXD86 |
+ M |
+ 69 |
+ 9.1 |
+
+
+ | 83 |
+ 828 |
+ BXD86 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 84 |
+ 829 |
+ BXD90 |
+ F |
+ 69 |
+ 9.6 |
+
+
+ | 85 |
+ 831 |
+ BXD9 |
+ M |
+ 127 |
+ 9.7 |
+
+
+ | 86 |
+ 832 |
+ BXD39 |
+ F |
+ 99 |
+ 9.4 |
+
+
+ | 87 |
+ 833 |
+ BXD39 |
+ F |
+ 107 |
+ 9.3 |
+
+
+ | 88 |
+ 834 |
+ BXD60 |
+ F |
+ 107 |
+ 9.5 |
+
+
+ | 89 |
+ 836 |
+ BXD84 |
+ M |
+ 103 |
+ 9.7 |
+
+
+ | 90 |
+ 846 |
+ BXD39 |
+ M |
+ 63 |
+ 9.7 |
+
+
+ | 91 |
+ 847 |
+ BXD39 |
+ M |
+ 63 |
+ 9.8 |
+
+
+ | 92 |
+ 849 |
+ BXD20 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 93 |
+ 850 |
+ BXD20 |
+ M |
+ 70 |
+ 10 |
+
+
+ | 94 |
+ 851 |
+ BXD20 |
+ * |
+ 70 |
+ 9.5 |
+
+
+ | 95 |
+ 855 |
+ DBA/2J |
+ F |
+ 78 |
+ 9.7 |
+
+
+ | 96 |
+ 856 |
+ DBA/2J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 97 |
+ 857 |
+ DBA/2J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 98 |
+ 858 |
+ DBA/2J |
+ M |
+ 78 |
+ 9.9 |
+
+
+ | 99 |
+ 859 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 100 |
+ 860 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 101 |
+ 861 |
+ C57BL/6J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 102 |
+ 862 |
+ C57BL/6J |
+ M |
+ 78 |
+ 9.6 |
+
+
+ | 103 |
+ EGE10907-0172_890_20844 |
+ BXD28 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 104 |
+ EGE10907-0173_891_20845 |
+ BXD28 |
+ M |
+ 75 |
+ 9.7 |
+
+
+ | 105 |
+ EGE10907-0174_892_20846 |
+ BXD28 |
+ F |
+ 75 |
+ 9.7 |
+
+
+ | 106 |
+ EGE10907-0176_895_20848 |
+ BXD33 |
+ M |
+ 75 |
+ 9.88 |
+
+
+ | 107 |
+ EGE10907-0177_896_20849 |
+ BXD33 |
+ F |
+ 75 |
+ 10 |
+
+
+ | 108 |
+ EGE10907-0178_897_20850 |
+ BXD33 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 109 |
+ EGE10907-0179_898_20851 |
+ BXD36 |
+ M |
+ 75 |
+ 9.4 |
+
+
+ | 110 |
+ EGE10907-0180_899_20852 |
+ BXD36 |
+ F |
+ 75 |
+ 9.5 |
+
+
+ | 111 |
+ EGE10907-0181_900_20853 |
+ BXD36 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 112 |
+ EGE10907-0182_910_20854 |
+ BXD27 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 113 |
+ EGE10907-0183_990_20855 |
+ BXD9 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 114 |
+ EGE10907-0184_991_20856 |
+ BXD16 |
+ F |
+ 113 |
+ 10 |
+
+
+ | 115 |
+ EGE10907-0185_992_20857 |
+ BXD16 |
+ M |
+ 113 |
+ 9 |
+
+
+ | 116 |
+ EGE10907-0186_993_20858 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 117 |
+ EGE10907-0187_994_20859 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 118 |
+ EGE10907-0188_996_20860 |
+ BXD48 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 119 |
+ EGE10907-0189_997_20861 |
+ BXD73 |
+ M |
+ 106 |
+ 10 |
+
+
+ | 120 |
+ EGE10907-0190_999_20862 |
+ BXD11 |
+ F |
+ 121 |
+ 9.6 |
+
+
+ | 121 |
+ EGE10907-0191_100_20863 |
+ BXD11 |
+ F |
+ 121 |
+ 9.9 |
+
+
+ | 122 |
+ EGE10907-0192_1010_21276 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 123 |
+ EGE10907-0193_1011_21277 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 124 |
+ EGE10907-0194_1012_21278 |
+ BXD16 |
+ F |
+ 65 |
+ 10 |
+
+
+ | 125 |
+ EGE10907-0195_1015_21279 |
+ BXD16 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 126 |
+ EGE10907-0196_1019_21280 |
+ BXD33 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 127 |
+ EGE10907-0197_1020_21281 |
+ BXD36 |
+ M |
+ 78 |
+ 10 |
+
+
+ | 128 |
+ EGE10907-0198_1021_21282 |
+ BXD38 |
+ F |
+ 70 |
+ 9.8 |
+
+
+ | 129 |
+ EGE10907-0199_1022_21283 |
+ BXD38 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 130 |
+ EGE10907-0200_1023_21284 |
+ BXD38 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 131 |
+ EGE10907-0201_1047_21285 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 132 |
+ EGE10907-0202_1048_21286 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 133 |
+ EGE10907-0203_1049_21287 |
+ BXD38 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 134 |
+ EGE10907-0204_1050_21288 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 135 |
+ EGE10907-0205_1051_21289 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 136 |
+ EGE10907-0206_1052_21290 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 137 |
+ EGE10907-0207_1053_21291 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 138 |
+ EGE10907-0208_1054_21292 |
+ BXD90 |
+ F |
+ 71 |
+ 10 |
+
+
+ | 139 |
+ EGE10907-0209_1055_21293 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 140 |
+ EGE10907-0210_1056_21294 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 141 |
+ EGE10907-0211_1148_21295 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 142 |
+ EGE10907-0212_1149_21296 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 143 |
+ EGE10907-0213_1150_21297 |
+ BXD31 |
+ M |
+ 90 |
+ 10 |
+
+
+ | 144 |
+ EGE10907-0214_1151_21298 |
+ BXD31 |
+ M |
+ 90 |
+ 9.9 |
+
+
+ | 145 |
+ EGE10907-0215_1152_21299 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 146 |
+ EGE10907-0216_21429 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 147 |
+ EGE10907-0217_21430 |
+ BXD42 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 148 |
+ EGE10907-0218_21431 |
+ BXD42 |
+ M |
+ 83 |
+ 9.3 |
+
+
+ | 149 |
+ EGE10907-0219_21432 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 150 |
+ EGE10907-0220_21433 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 151 |
+ EGE10907-0221_21434 |
+ BXD50 |
+ F |
+ 92 |
+ 10 |
+
+
+ | 152 |
+ EGE10907-0222_21435 |
+ BXD1 |
+ M |
+ 73 |
+ 9.6 |
+
+
+ | 153 |
+ EGE10907-0223_21436 |
+ BXD13 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 154 |
+ EGE10907-0224_21437 |
+ BXD1 |
+ M |
+ 71 |
+ 9.5 |
+
+
+ | 155 |
+ EGE10907-0225_21438 |
+ BXD13 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 156 |
+ EGE10907-0226_21439 |
+ BXD43 |
+ F |
+ 85 |
+ 10 |
+
+
+ | 157 |
+ EGE10907-0227_21452 |
+ BXD43 |
+ F |
+ 85 |
+ 9.6 |
+
+
+ | 158 |
+ EGE10907-0229_21442 |
+ BXD43 |
+ M |
+ 85 |
+ 8.2 |
+
+
+ | 159 |
+ EGE10907-0230_21443 |
+ BXD50 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 160 |
+ EGE10907-0231_21444 |
+ BXD1 |
+ F |
+ 68 |
+ 9.4 |
+
+
+ | 161 |
+ EGE10907-0232_21445 |
+ BXD1 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 162 |
+ EGE10907-0233_21446 |
+ BXD29 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 163 |
+ EGE10907-0234_21447 |
+ BXD29 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 164 |
+ EGE10907-0235_21448 |
+ BXD75 |
+ F |
+ 68 |
+ 10 |
+
+
+ | 165 |
+ EGE10907-0236_21449 |
+ BXD75 |
+ M |
+ 68 |
+ 10 |
+
+
+ | 166 |
+ EGE10907-0237_21450 |
+ BXD96 |
+ F |
+ 67 |
+ 9.9 |
+
+
+ | 167 |
+ EGE10907-0238_21931 |
+ BXD99 |
+ M |
+ 71 |
+ 7.9 |
+
+
+ | 168 |
+ EGE10907-0239_21932 |
+ BXD99 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 169 |
+ EGE10907-0240_21933 |
+ BXD67 |
+ F |
+ 68 |
+ 8.8 |
+
+
+ | 170 |
+ EGE10907-0241_21934 |
+ BXD67 |
+ F |
+ 68 |
+ 8.5 |
+
+
+ | 171 |
+ EGE10907-0242_21935 |
+ BXD67 |
+ M |
+ 68 |
+ 9.5 |
+
+
+ | 172 |
+ EGE10907-0243_21936 |
+ BXD67 |
+ M |
+ 68 |
+ 9.6 |
+
+
+ | 173 |
+ EGE10907-0244_21937 |
+ BXD6 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 174 |
+ EGE10907-0245_21938 |
+ BXD12 |
+ M |
+ 82 |
+ 9.5 |
+
+
+ | 175 |
+ EGE10907-0246_21939 |
+ BXD60 |
+ F |
+ 72 |
+ 9.6 |
+
+
+ | 176 |
+ EGE10907-0247_21940 |
+ BXD65 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 177 |
+ EGE10907-0248_21941 |
+ BXD75 |
+ F |
+ 69 |
+ 8.8 |
+
+
+ | 178 |
+ EGE10907-0249_21942_(MoGene-2_0-st) |
+ BXD75 |
+ M |
+ 69 |
+ 9.2 |
+
+
+ | 179 |
+ EGE10907-0250_21943 |
+ BXD8 |
+ F |
+ 97 |
+ 9.1 |
+
+
+ | 180 |
+ EGE10907-0251_21944 |
+ BXD85 |
+ F |
+ 79 |
+ 8.6 |
+
+
+ | 181 |
+ EGE10907-0252_21945 |
+ BXD85 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 182 |
+ EGE10907-0253_21946 |
+ BXD85 |
+ M |
+ 79 |
+ 9.4 |
+
+
+ | 183 |
+ EGE10907-0254_21947 |
+ BXD102 |
+ M |
+ 94 |
+ 8.6 |
+
+
+ | 184 |
+ EGE10907-0255_21948 |
+ BXD99 |
+ F |
+ 83 |
+ 9 |
+
+
+ | 185 |
+ EGE10907-0256_21949 |
+ BXD69 |
+ F |
+ 68 |
+ 9 |
+
+
+ | 186 |
+ EGE10907-0257_21950 |
+ BXD84 |
+ F |
+ 74 |
+ 9.5 |
+
+
+ | 187 |
+ EGE10907-0258_21951 |
+ BXD84 |
+ F |
+ 74 |
+ 9.4 |
+
+
+ | 188 |
+ EGE10907-0259_21952 |
+ BXD84 |
+ M |
+ 74 |
+ 8.6 |
+
+
+ | 189 |
+ EGE10907-0260_21451 |
+ BXD96 |
+ M |
+ 67 |
+ 9.2 |
+
+
+ | 190 |
+ EGE10907-0261_21452 |
+ BXD99 |
+ F |
+ 71 |
+ 8.9 |
+
+
+ | 191 |
+ EGE10907-0262_21931 |
+ BXD6 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 192 |
+ EGE10907-0263_21932 |
+ BXD14 |
+ F |
+ 69 |
+ 8.5 |
+
+
+ | 193 |
+ EGE10907-0264_21933 |
+ BXD34 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 194 |
+ EGE10907-0265_21934 |
+ BXD34 |
+ M |
+ 79 |
+ 9.9 |
+
+
+ | 195 |
+ EGE10907-0266_21935 |
+ BXD40 |
+ F |
+ 75 |
+ 9.6 |
+
+
+ | 196 |
+ EGE10907-0267_21936 |
+ BXD40 |
+ M |
+ 78 |
+ 9.7 |
+
+
+ | 197 |
+ EGE10907-0268_21937 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 198 |
+ EGE10907-0269_21938 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 199 |
+ EGE10907-0270_21939 |
+ BXD56 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 200 |
+ EGE10907-0271_21940 |
+ BXD56 |
+ M |
+ 72 |
+ 9.4 |
+
+
+ | 201 |
+ EGE10907-0272_21941 |
+ BXD71 |
+ F |
+ 72 |
+ 9.9 |
+
+
+ | 202 |
+ EGE10907-0273_21942 |
+ BXD71 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 203 |
+ EGE10907-0274_21943 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 204 |
+ EGE10907-0275_21944 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 205 |
+ EGE10907-0276_21945 |
+ BXD27 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 206 |
+ EGE10907-0277_21946 |
+ BXD15 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 207 |
+ EGE10907-0278_21947 |
+ BXD20 |
+ F |
+ 125 |
+ 10 |
+
+
+ | 208 |
+ EGE10907-0279_21948 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 209 |
+ EGE10907-0280_21949 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 210 |
+ EGE10907-0281_21950 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 211 |
+ EGE10907-0282_21951 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 212 |
+ EGE10907-0283_21952 |
+ BXD85 |
+ F |
+ 87 |
+ 10 |
+
+
+ | 213 |
+ EGE10907-0284_21451 |
+ BXD43 |
+ M |
+ 75 |
+ 9.8 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Dodretblastvsnormal_0416/citation.rtf b/general/datasets/Dodretblastvsnormal_0416/citation.rtf
new file mode 100644
index 0000000..d84717d
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormal_0416/citation.rtf
@@ -0,0 +1,3 @@
+Related Publications: Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link) Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674 Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link) Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful: NEIBank collection of ESTs and SAGE data. RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases.
diff --git a/general/datasets/Dodretblastvsnormal_0416/contributors.rtf b/general/datasets/Dodretblastvsnormal_0416/contributors.rtf
new file mode 100644
index 0000000..11fece2
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormal_0416/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, XiangDi Wang, Justin P. Templeton and Robert W. Williams.
diff --git a/general/datasets/Dodretblastvsnormal_0416/platform.rtf b/general/datasets/Dodretblastvsnormal_0416/platform.rtf
new file mode 100644
index 0000000..19fc38c
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormal_0416/platform.rtf
@@ -0,0 +1 @@
+The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/Dodretblastvsnormal_0416/processing.rtf b/general/datasets/Dodretblastvsnormal_0416/processing.rtf
new file mode 100644
index 0000000..a7b767e
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormal_0416/processing.rtf
@@ -0,0 +1 @@
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Dodretblastvsnormal_0416/specifics.rtf b/general/datasets/Dodretblastvsnormal_0416/specifics.rtf
new file mode 100644
index 0000000..0d1a5a5
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormal_0416/specifics.rtf
@@ -0,0 +1 @@
+This is a subtractive dataset. The Normal retina dataset was subtracted from the blast data set probe by probe to create a data set of the changes occurring following a blast injury to the eye. This data set can be used to define gene changes following blast. It is not compatible with most of the bioinformatic tools available on GeneNetwork.
\ No newline at end of file
diff --git a/general/datasets/Dodretblastvsnormal_0416/summary.rtf b/general/datasets/Dodretblastvsnormal_0416/summary.rtf
new file mode 100644
index 0000000..96a87e5
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormal_0416/summary.rtf
@@ -0,0 +1 @@
+The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/Dodretblastvsnormal_0416/tissue.rtf b/general/datasets/Dodretblastvsnormal_0416/tissue.rtf
new file mode 100644
index 0000000..056d7eb
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormal_0416/tissue.rtf
@@ -0,0 +1 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/Dodretblastvsnormalex_0416/cases.rtf b/general/datasets/Dodretblastvsnormalex_0416/cases.rtf
new file mode 100644
index 0000000..34f9530
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormalex_0416/cases.rtf
@@ -0,0 +1,9 @@
+Almost all animals are young adults between 60 and 100 days of age (Table 1, minimum age is 60 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
+
+BXD strains:
+
+
+ - The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s.
+ - In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset.
+ - The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
diff --git a/general/datasets/Dodretblastvsnormalex_0416/contributors.rtf b/general/datasets/Dodretblastvsnormalex_0416/contributors.rtf
new file mode 100644
index 0000000..814bf91
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormalex_0416/contributors.rtf
@@ -0,0 +1,9 @@
+Other Related Publications
+
+
+ - Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link)
+ - Freeman NE, Templeton JP, Orr WE, Lu L, Williams RW, Geisert EE (2011) Genetic networks in the mouse retina: Growth Associated Protein 43 and Phosphate Tensin Homology network. Molecular Vision 17:1355-1372.
+ - Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674
+ - Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link)
+ - Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.(Link)
+
diff --git a/general/datasets/Dodretblastvsnormalex_0416/experiment-design.rtf b/general/datasets/Dodretblastvsnormalex_0416/experiment-design.rtf
new file mode 100644
index 0000000..b43e509
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormalex_0416/experiment-design.rtf
@@ -0,0 +1,3 @@
+Sample Processing: Dr. XiangDi Wang (UTHSC) and Becky King (Emory) were involved in the retinal extractions and isolation of RNA. The Affymetrix arrays were run by two different research cores: the Molecular Resource Center at UTHSC (Dr. William Taylor Director) and the Integrated Genomics Core at Emory University by Robert B Isett (Dr. Michael E. Zwick, Director). In a separate set of experiments we could not detect any significant difference in the arrays run at UTHSC or at Emory University.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Dodretblastvsnormalex_0416/notes.rtf b/general/datasets/Dodretblastvsnormalex_0416/notes.rtf
new file mode 100644
index 0000000..cb14c74
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormalex_0416/notes.rtf
@@ -0,0 +1,10 @@
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
diff --git a/general/datasets/Dodretblastvsnormalex_0416/platform.rtf b/general/datasets/Dodretblastvsnormalex_0416/platform.rtf
new file mode 100644
index 0000000..cb5e1b8
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormalex_0416/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Gene 2.0 ST Array: These expression arrays have been designed with a median of 22 unique probes per transcript. Each unique probe is 25 bases in length, which means that the array measures a median of 550 bases per transcript. The arrays provide comprehensive transcriptome coverage with over 30,000 coding and non-coding transcripts. In addition there is coverage for 592 microRNAs. For some arrays the RNA was pooled from two retinas and for other arrays were run on a single retina.
diff --git a/general/datasets/Dodretblastvsnormalex_0416/specifics.rtf b/general/datasets/Dodretblastvsnormalex_0416/specifics.rtf
new file mode 100644
index 0000000..7c1a914
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormalex_0416/specifics.rtf
@@ -0,0 +1 @@
+Exon Level
\ No newline at end of file
diff --git a/general/datasets/Dodretblastvsnormalex_0416/summary.rtf b/general/datasets/Dodretblastvsnormalex_0416/summary.rtf
new file mode 100644
index 0000000..b6cf222
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormalex_0416/summary.rtf
@@ -0,0 +1,5 @@
+DoD TATRC Retina Dataset Affymetrix MouseGene 2.0 ST Array (____ 2015) RMA analysis and scaling by Arthur Centeno. This data set consists of 75 BXD strains, C57BL/6J, DBA/2J, both reciprocal F1s, and BALB/cByJ. A total of 80 strains were quantified. The data are now open and available for analysis.
+
+This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strain was computed as the mean of four samples per strain. Expression values on a log2 scale range from 6.25 to 18.08 (11.83 units), a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
+
+The lowest level of expression is 6.254 for ILMN_2747167 (Arhgap11a) from HEI Retina Illumina V6.2 (April 2010) RankInv **. Lowest single data about 5.842. The highest level of expression is 18.077 for ILMN_2516699 (Ubb). Highest single value is about 18.934.
diff --git a/general/datasets/Dodretblastvsnormalex_0416/tissue.rtf b/general/datasets/Dodretblastvsnormalex_0416/tissue.rtf
new file mode 100644
index 0000000..87eb144
--- /dev/null
+++ b/general/datasets/Dodretblastvsnormalex_0416/tissue.rtf
@@ -0,0 +1,13 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in 1 ml of 160 U/ml Ribolock for 1 min at room temperature. Dissecting and preparing eyes for RNA extraction Retinas for RNA removed from the eye and placed in Hank’s Balanced Salt solution with RiboLock (Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) and processed per manufacturer’s instructions (in brief form below).
+
+1) Sample collection for RNA isolation.
+
+2) Quickly remove the retinas with clean curved forceps after cervical dislocation of the mouse.
+
+3) Put each retina in 1 ml of 160 U/ml Ribolock for 1 min in RT.
+
+4) Move the retina to another tube with 50µl Ribolock, store in -80°C.
+
+5) The RNA was isolated using a QiaCube and the in column DNAse procedure.
+
+Quality Control: All RNA samples were checked for quality before running microarrays. The samples were analyzed using the Agilent 2100 Bioanalyzer. The RNA integrity values for each sample are presented in Table 1 below.
diff --git a/general/datasets/Dodtatrcretblexmogene2_1213/acknowledgment.rtf b/general/datasets/Dodtatrcretblexmogene2_1213/acknowledgment.rtf
new file mode 100644
index 0000000..13c6b1e
--- /dev/null
+++ b/general/datasets/Dodtatrcretblexmogene2_1213/acknowledgment.rtf
@@ -0,0 +1 @@
+DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/Dodtatrcretblexmogene2_1213/cases.rtf b/general/datasets/Dodtatrcretblexmogene2_1213/cases.rtf
new file mode 100644
index 0000000..6b36c70
--- /dev/null
+++ b/general/datasets/Dodtatrcretblexmogene2_1213/cases.rtf
@@ -0,0 +1,1728 @@
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+
+
+
+
+
+ | Index |
+ EIGC ID (LIMS ID) |
+ Strain |
+ Sex |
+ Age at harvest |
+ RIN Score |
+
+
+ | 1 |
+ 602 |
+ BXD9 |
+ F |
+ 133 |
+ 9.1 |
+
+
+ | 2 |
+ 603 |
+ BXD9 |
+ M |
+ 100 |
+ 9.5 |
+
+
+ | 3 |
+ 604 |
+ BXD40 |
+ F |
+ 100 |
+ 9.4 |
+
+
+ | 4 |
+ 605 |
+ BXD40 |
+ M |
+ 100 |
+ 9.1 |
+
+
+ | 5 |
+ 606 |
+ BXD48 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 6 |
+ 607 |
+ BXD48 |
+ M |
+ 75 |
+ 8.6 |
+
+
+ | 7 |
+ 608 |
+ BXD63 |
+ F |
+ 75 |
+ 9.2 |
+
+
+ | 8 |
+ 609 |
+ BXD63 |
+ M |
+ 61 |
+ 9.4 |
+
+
+ | 9 |
+ 612 |
+ BXD73 |
+ M |
+ 108 |
+ 10 |
+
+
+ | 10 |
+ 614 |
+ BXD87 |
+ M |
+ 85 |
+ 9.2 |
+
+
+ | 11 |
+ 615 |
+ BXD87 |
+ F |
+ 85 |
+ 9.9 |
+
+
+ | 12 |
+ 616 |
+ BXD69 |
+ F |
+ 76 |
+ 9.3 |
+
+
+ | 13 |
+ 617 |
+ BXD69 |
+ M |
+ 100 |
+ 10 |
+
+
+ | 14 |
+ 618 |
+ BXD51 |
+ M |
+ 82 |
+ 8.9 |
+
+
+ | 15 |
+ 619 |
+ BXD92 (BXD65b) |
+ M |
+ 82 |
+ 8.8 |
+
+
+ | 16 |
+ 620 |
+ BXD92 (BXD65b) |
+ F |
+ 82 |
+ 8.8 |
+
+
+ | 17 |
+ 635 |
+ BXD100 |
+ M |
+ 70 |
+ 9 |
+
+
+ | 18 |
+ 636 |
+ BXD100 |
+ M |
+ 70 |
+ 8.8 |
+
+
+ | 19 |
+ 652 |
+ BXD92 (BXD65b) |
+ F |
+ 64 |
+ 9 |
+
+
+ | 20 |
+ 653 |
+ BXD87 |
+ F |
+ 67 |
+ 9.7 |
+
+
+ | 21 |
+ 654 |
+ BXD87 |
+ M |
+ 67 |
+ 8.9 |
+
+
+ | 22 |
+ 655 |
+ BXD63 |
+ M |
+ 71 |
+ 9 |
+
+
+ | 23 |
+ 660 |
+ BXD69 |
+ M |
+ 97 |
+ 10 |
+
+
+ | 24 |
+ 687 |
+ BXD6 |
+ M |
+ 85 |
+ 7.7 |
+
+
+ | 25 |
+ 688 |
+ BXD6 |
+ M |
+ 85 |
+ 9.4 |
+
+
+ | 26 |
+ 690 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 27 |
+ 691 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 28 |
+ 692 |
+ BXD12 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 29 |
+ 695 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 30 |
+ 696 |
+ BXD5 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 31 |
+ 698 |
+ BXD5 |
+ F |
+ 77 |
+ 9.9 |
+
+
+ | 32 |
+ 699 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 33 |
+ 701 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 34 |
+ 702 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 35 |
+ 705 |
+ BXD8 |
+ F |
+ 77 |
+ 9.2 |
+
+
+ | 36 |
+ 707 |
+ BXD15 |
+ F |
+ 77 |
+ 9.4 |
+
+
+ | 37 |
+ 708 |
+ BXD15 |
+ F |
+ 77 |
+ 9.1 |
+
+
+ | 38 |
+ 710 |
+ BXD15 |
+ M |
+ 77 |
+ 9.1 |
+
+
+ | 39 |
+ 713 |
+ BXD22 |
+ F |
+ 71 |
+ 9.5 |
+
+
+ | 40 |
+ 714 |
+ BXD22 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 41 |
+ 716 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 42 |
+ 717 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 43 |
+ 719 |
+ BXD14 |
+ F |
+ 70 |
+ 9.2 |
+
+
+ | 44 |
+ 722 |
+ BXD14 |
+ M |
+ 70 |
+ 8.9 |
+
+
+ | 45 |
+ 723 |
+ BXD14 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 46 |
+ 725 |
+ BXD18 |
+ F |
+ 70 |
+ 9 |
+
+
+ | 47 |
+ 726 |
+ BXD18 |
+ F |
+ 70 |
+ 9.1 |
+
+
+ | 48 |
+ 728 |
+ BXD18 |
+ M |
+ 70 |
+ 9.1 |
+
+
+ | 49 |
+ 729 |
+ BXD18 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 50 |
+ 731 |
+ BXD19 |
+ F |
+ 66 |
+ 9.3 |
+
+
+ | 51 |
+ 732 |
+ BXD19 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 52 |
+ 734 |
+ BXD19 |
+ M |
+ 66 |
+ 9.8 |
+
+
+ | 53 |
+ 735 |
+ BXD19 |
+ M |
+ 66 |
+ 9.4 |
+
+
+ | 54 |
+ 737 |
+ BXD21 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 55 |
+ 738 |
+ BXD21 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 56 |
+ 740 |
+ BXD21 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 57 |
+ 741 |
+ BXD21 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 58 |
+ 743 |
+ BXD2 |
+ F |
+ 70 |
+ 8.3 |
+
+
+ | 59 |
+ 744 |
+ BXD2 |
+ F |
+ 70 |
+ 8.6 |
+
+
+ | 60 |
+ 746 |
+ BXD2 |
+ M |
+ 70 |
+ 7.5 |
+
+
+ | 61 |
+ 747 |
+ BXD2 |
+ M |
+ 77 |
+ 8.6 |
+
+
+ | 62 |
+ 768 |
+ BXD48 |
+ M |
+ 121 |
+ 9.4 |
+
+
+ | 63 |
+ 770 |
+ BXD92 (BXD65b) |
+ M |
+ 65 |
+ 10 |
+
+
+ | 64 |
+ 771 |
+ BXD101 |
+ F |
+ 85 |
+ 8.3 |
+
+
+ | 65 |
+ 772 |
+ BXD101 |
+ F |
+ 85 |
+ 9.3 |
+
+
+ | 66 |
+ 773 |
+ BXD101 |
+ M |
+ 86 |
+ 9.5 |
+
+
+ | 67 |
+ 774 |
+ BXD101 |
+ M |
+ 86 |
+ 9.8 |
+
+
+ | 68 |
+ 775 |
+ BXD102 |
+ F |
+ 66 |
+ 9.5 |
+
+
+ | 69 |
+ 776 |
+ BXD102 |
+ F |
+ 66 |
+ 10 |
+
+
+ | 70 |
+ 777 |
+ BXD102 |
+ M |
+ 84 |
+ 9.6 |
+
+
+ | 71 |
+ 787 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 72 |
+ 788 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 73 |
+ 789 |
+ BXD63 |
+ F |
+ 115 |
+ 9.7 |
+
+
+ | 74 |
+ 790 |
+ BXD100 |
+ F |
+ 72 |
+ 9.8 |
+
+
+ | 75 |
+ 791 |
+ BXD100 |
+ F |
+ 72 |
+ 10 |
+
+
+ | 76 |
+ 818 |
+ BXD51 |
+ F |
+ 77 |
+ 9.7 |
+
+
+ | 77 |
+ 819 |
+ BXD51 |
+ F |
+ 77 |
+ 9.6 |
+
+
+ | 78 |
+ 820 |
+ BXD51 |
+ M |
+ 72 |
+ 9.7 |
+
+
+ | 79 |
+ 821 |
+ BXD65 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 80 |
+ 822 |
+ BXD65 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 81 |
+ 825 |
+ BXD65 |
+ F |
+ 72 |
+ 9.5 |
+
+
+ | 82 |
+ 827 |
+ BXD86 |
+ M |
+ 69 |
+ 9.1 |
+
+
+ | 83 |
+ 828 |
+ BXD86 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 84 |
+ 829 |
+ BXD90 |
+ F |
+ 69 |
+ 9.6 |
+
+
+ | 85 |
+ 831 |
+ BXD9 |
+ M |
+ 127 |
+ 9.7 |
+
+
+ | 86 |
+ 832 |
+ BXD39 |
+ F |
+ 99 |
+ 9.4 |
+
+
+ | 87 |
+ 833 |
+ BXD39 |
+ F |
+ 107 |
+ 9.3 |
+
+
+ | 88 |
+ 834 |
+ BXD60 |
+ F |
+ 107 |
+ 9.5 |
+
+
+ | 89 |
+ 836 |
+ BXD84 |
+ M |
+ 103 |
+ 9.7 |
+
+
+ | 90 |
+ 846 |
+ BXD39 |
+ M |
+ 63 |
+ 9.7 |
+
+
+ | 91 |
+ 847 |
+ BXD39 |
+ M |
+ 63 |
+ 9.8 |
+
+
+ | 92 |
+ 849 |
+ BXD20 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 93 |
+ 850 |
+ BXD20 |
+ M |
+ 70 |
+ 10 |
+
+
+ | 94 |
+ 851 |
+ BXD20 |
+ * |
+ 70 |
+ 9.5 |
+
+
+ | 95 |
+ 855 |
+ DBA/2J |
+ F |
+ 78 |
+ 9.7 |
+
+
+ | 96 |
+ 856 |
+ DBA/2J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 97 |
+ 857 |
+ DBA/2J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 98 |
+ 858 |
+ DBA/2J |
+ M |
+ 78 |
+ 9.9 |
+
+
+ | 99 |
+ 859 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 100 |
+ 860 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 101 |
+ 861 |
+ C57BL/6J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 102 |
+ 862 |
+ C57BL/6J |
+ M |
+ 78 |
+ 9.6 |
+
+
+ | 103 |
+ EGE10907-0172_890_20844 |
+ BXD28 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 104 |
+ EGE10907-0173_891_20845 |
+ BXD28 |
+ M |
+ 75 |
+ 9.7 |
+
+
+ | 105 |
+ EGE10907-0174_892_20846 |
+ BXD28 |
+ F |
+ 75 |
+ 9.7 |
+
+
+ | 106 |
+ EGE10907-0176_895_20848 |
+ BXD33 |
+ M |
+ 75 |
+ 9.88 |
+
+
+ | 107 |
+ EGE10907-0177_896_20849 |
+ BXD33 |
+ F |
+ 75 |
+ 10 |
+
+
+ | 108 |
+ EGE10907-0178_897_20850 |
+ BXD33 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 109 |
+ EGE10907-0179_898_20851 |
+ BXD36 |
+ M |
+ 75 |
+ 9.4 |
+
+
+ | 110 |
+ EGE10907-0180_899_20852 |
+ BXD36 |
+ F |
+ 75 |
+ 9.5 |
+
+
+ | 111 |
+ EGE10907-0181_900_20853 |
+ BXD36 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 112 |
+ EGE10907-0182_910_20854 |
+ BXD27 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 113 |
+ EGE10907-0183_990_20855 |
+ BXD9 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 114 |
+ EGE10907-0184_991_20856 |
+ BXD16 |
+ F |
+ 113 |
+ 10 |
+
+
+ | 115 |
+ EGE10907-0185_992_20857 |
+ BXD16 |
+ M |
+ 113 |
+ 9 |
+
+
+ | 116 |
+ EGE10907-0186_993_20858 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 117 |
+ EGE10907-0187_994_20859 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 118 |
+ EGE10907-0188_996_20860 |
+ BXD48 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 119 |
+ EGE10907-0189_997_20861 |
+ BXD73 |
+ M |
+ 106 |
+ 10 |
+
+
+ | 120 |
+ EGE10907-0190_999_20862 |
+ BXD11 |
+ F |
+ 121 |
+ 9.6 |
+
+
+ | 121 |
+ EGE10907-0191_100_20863 |
+ BXD11 |
+ F |
+ 121 |
+ 9.9 |
+
+
+ | 122 |
+ EGE10907-0192_1010_21276 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 123 |
+ EGE10907-0193_1011_21277 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 124 |
+ EGE10907-0194_1012_21278 |
+ BXD16 |
+ F |
+ 65 |
+ 10 |
+
+
+ | 125 |
+ EGE10907-0195_1015_21279 |
+ BXD16 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 126 |
+ EGE10907-0196_1019_21280 |
+ BXD33 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 127 |
+ EGE10907-0197_1020_21281 |
+ BXD36 |
+ M |
+ 78 |
+ 10 |
+
+
+ | 128 |
+ EGE10907-0198_1021_21282 |
+ BXD38 |
+ F |
+ 70 |
+ 9.8 |
+
+
+ | 129 |
+ EGE10907-0199_1022_21283 |
+ BXD38 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 130 |
+ EGE10907-0200_1023_21284 |
+ BXD38 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 131 |
+ EGE10907-0201_1047_21285 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 132 |
+ EGE10907-0202_1048_21286 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 133 |
+ EGE10907-0203_1049_21287 |
+ BXD38 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 134 |
+ EGE10907-0204_1050_21288 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 135 |
+ EGE10907-0205_1051_21289 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 136 |
+ EGE10907-0206_1052_21290 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 137 |
+ EGE10907-0207_1053_21291 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 138 |
+ EGE10907-0208_1054_21292 |
+ BXD90 |
+ F |
+ 71 |
+ 10 |
+
+
+ | 139 |
+ EGE10907-0209_1055_21293 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 140 |
+ EGE10907-0210_1056_21294 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 141 |
+ EGE10907-0211_1148_21295 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 142 |
+ EGE10907-0212_1149_21296 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 143 |
+ EGE10907-0213_1150_21297 |
+ BXD31 |
+ M |
+ 90 |
+ 10 |
+
+
+ | 144 |
+ EGE10907-0214_1151_21298 |
+ BXD31 |
+ M |
+ 90 |
+ 9.9 |
+
+
+ | 145 |
+ EGE10907-0215_1152_21299 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 146 |
+ EGE10907-0216_21429 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 147 |
+ EGE10907-0217_21430 |
+ BXD42 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 148 |
+ EGE10907-0218_21431 |
+ BXD42 |
+ M |
+ 83 |
+ 9.3 |
+
+
+ | 149 |
+ EGE10907-0219_21432 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 150 |
+ EGE10907-0220_21433 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 151 |
+ EGE10907-0221_21434 |
+ BXD50 |
+ F |
+ 92 |
+ 10 |
+
+
+ | 152 |
+ EGE10907-0222_21435 |
+ BXD1 |
+ M |
+ 73 |
+ 9.6 |
+
+
+ | 153 |
+ EGE10907-0223_21436 |
+ BXD13 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 154 |
+ EGE10907-0224_21437 |
+ BXD1 |
+ M |
+ 71 |
+ 9.5 |
+
+
+ | 155 |
+ EGE10907-0225_21438 |
+ BXD13 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 156 |
+ EGE10907-0226_21439 |
+ BXD43 |
+ F |
+ 85 |
+ 10 |
+
+
+ | 157 |
+ EGE10907-0227_21452 |
+ BXD43 |
+ F |
+ 85 |
+ 9.6 |
+
+
+ | 158 |
+ EGE10907-0229_21442 |
+ BXD43 |
+ M |
+ 85 |
+ 8.2 |
+
+
+ | 159 |
+ EGE10907-0230_21443 |
+ BXD50 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 160 |
+ EGE10907-0231_21444 |
+ BXD1 |
+ F |
+ 68 |
+ 9.4 |
+
+
+ | 161 |
+ EGE10907-0232_21445 |
+ BXD1 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 162 |
+ EGE10907-0233_21446 |
+ BXD29 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 163 |
+ EGE10907-0234_21447 |
+ BXD29 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 164 |
+ EGE10907-0235_21448 |
+ BXD75 |
+ F |
+ 68 |
+ 10 |
+
+
+ | 165 |
+ EGE10907-0236_21449 |
+ BXD75 |
+ M |
+ 68 |
+ 10 |
+
+
+ | 166 |
+ EGE10907-0237_21450 |
+ BXD96 |
+ F |
+ 67 |
+ 9.9 |
+
+
+ | 167 |
+ EGE10907-0238_21931 |
+ BXD99 |
+ M |
+ 71 |
+ 7.9 |
+
+
+ | 168 |
+ EGE10907-0239_21932 |
+ BXD99 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 169 |
+ EGE10907-0240_21933 |
+ BXD67 |
+ F |
+ 68 |
+ 8.8 |
+
+
+ | 170 |
+ EGE10907-0241_21934 |
+ BXD67 |
+ F |
+ 68 |
+ 8.5 |
+
+
+ | 171 |
+ EGE10907-0242_21935 |
+ BXD67 |
+ M |
+ 68 |
+ 9.5 |
+
+
+ | 172 |
+ EGE10907-0243_21936 |
+ BXD67 |
+ M |
+ 68 |
+ 9.6 |
+
+
+ | 173 |
+ EGE10907-0244_21937 |
+ BXD6 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 174 |
+ EGE10907-0245_21938 |
+ BXD12 |
+ M |
+ 82 |
+ 9.5 |
+
+
+ | 175 |
+ EGE10907-0246_21939 |
+ BXD60 |
+ F |
+ 72 |
+ 9.6 |
+
+
+ | 176 |
+ EGE10907-0247_21940 |
+ BXD65 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 177 |
+ EGE10907-0248_21941 |
+ BXD75 |
+ F |
+ 69 |
+ 8.8 |
+
+
+ | 178 |
+ EGE10907-0249_21942_(MoGene-2_0-st) |
+ BXD75 |
+ M |
+ 69 |
+ 9.2 |
+
+
+ | 179 |
+ EGE10907-0250_21943 |
+ BXD8 |
+ F |
+ 97 |
+ 9.1 |
+
+
+ | 180 |
+ EGE10907-0251_21944 |
+ BXD85 |
+ F |
+ 79 |
+ 8.6 |
+
+
+ | 181 |
+ EGE10907-0252_21945 |
+ BXD85 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 182 |
+ EGE10907-0253_21946 |
+ BXD85 |
+ M |
+ 79 |
+ 9.4 |
+
+
+ | 183 |
+ EGE10907-0254_21947 |
+ BXD102 |
+ M |
+ 94 |
+ 8.6 |
+
+
+ | 184 |
+ EGE10907-0255_21948 |
+ BXD99 |
+ F |
+ 83 |
+ 9 |
+
+
+ | 185 |
+ EGE10907-0256_21949 |
+ BXD69 |
+ F |
+ 68 |
+ 9 |
+
+
+ | 186 |
+ EGE10907-0257_21950 |
+ BXD84 |
+ F |
+ 74 |
+ 9.5 |
+
+
+ | 187 |
+ EGE10907-0258_21951 |
+ BXD84 |
+ F |
+ 74 |
+ 9.4 |
+
+
+ | 188 |
+ EGE10907-0259_21952 |
+ BXD84 |
+ M |
+ 74 |
+ 8.6 |
+
+
+ | 189 |
+ EGE10907-0260_21451 |
+ BXD96 |
+ M |
+ 67 |
+ 9.2 |
+
+
+ | 190 |
+ EGE10907-0261_21452 |
+ BXD99 |
+ F |
+ 71 |
+ 8.9 |
+
+
+ | 191 |
+ EGE10907-0262_21931 |
+ BXD6 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 192 |
+ EGE10907-0263_21932 |
+ BXD14 |
+ F |
+ 69 |
+ 8.5 |
+
+
+ | 193 |
+ EGE10907-0264_21933 |
+ BXD34 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 194 |
+ EGE10907-0265_21934 |
+ BXD34 |
+ M |
+ 79 |
+ 9.9 |
+
+
+ | 195 |
+ EGE10907-0266_21935 |
+ BXD40 |
+ F |
+ 75 |
+ 9.6 |
+
+
+ | 196 |
+ EGE10907-0267_21936 |
+ BXD40 |
+ M |
+ 78 |
+ 9.7 |
+
+
+ | 197 |
+ EGE10907-0268_21937 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 198 |
+ EGE10907-0269_21938 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 199 |
+ EGE10907-0270_21939 |
+ BXD56 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 200 |
+ EGE10907-0271_21940 |
+ BXD56 |
+ M |
+ 72 |
+ 9.4 |
+
+
+ | 201 |
+ EGE10907-0272_21941 |
+ BXD71 |
+ F |
+ 72 |
+ 9.9 |
+
+
+ | 202 |
+ EGE10907-0273_21942 |
+ BXD71 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 203 |
+ EGE10907-0274_21943 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 204 |
+ EGE10907-0275_21944 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 205 |
+ EGE10907-0276_21945 |
+ BXD27 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 206 |
+ EGE10907-0277_21946 |
+ BXD15 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 207 |
+ EGE10907-0278_21947 |
+ BXD20 |
+ F |
+ 125 |
+ 10 |
+
+
+ | 208 |
+ EGE10907-0279_21948 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 209 |
+ EGE10907-0280_21949 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 210 |
+ EGE10907-0281_21950 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 211 |
+ EGE10907-0282_21951 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 212 |
+ EGE10907-0283_21952 |
+ BXD85 |
+ F |
+ 87 |
+ 10 |
+
+
+ | 213 |
+ EGE10907-0284_21451 |
+ BXD43 |
+ M |
+ 75 |
+ 9.8 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Dodtatrcretblexmogene2_1213/citation.rtf b/general/datasets/Dodtatrcretblexmogene2_1213/citation.rtf
new file mode 100644
index 0000000..d84717d
--- /dev/null
+++ b/general/datasets/Dodtatrcretblexmogene2_1213/citation.rtf
@@ -0,0 +1,3 @@
+Related Publications: Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link) Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674 Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link) Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful: NEIBank collection of ESTs and SAGE data. RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases.
diff --git a/general/datasets/Dodtatrcretblexmogene2_1213/contributors.rtf b/general/datasets/Dodtatrcretblexmogene2_1213/contributors.rtf
new file mode 100644
index 0000000..11fece2
--- /dev/null
+++ b/general/datasets/Dodtatrcretblexmogene2_1213/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, XiangDi Wang, Justin P. Templeton and Robert W. Williams.
diff --git a/general/datasets/Dodtatrcretblexmogene2_1213/platform.rtf b/general/datasets/Dodtatrcretblexmogene2_1213/platform.rtf
new file mode 100644
index 0000000..19fc38c
--- /dev/null
+++ b/general/datasets/Dodtatrcretblexmogene2_1213/platform.rtf
@@ -0,0 +1 @@
+The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/Dodtatrcretblexmogene2_1213/processing.rtf b/general/datasets/Dodtatrcretblexmogene2_1213/processing.rtf
new file mode 100644
index 0000000..a7b767e
--- /dev/null
+++ b/general/datasets/Dodtatrcretblexmogene2_1213/processing.rtf
@@ -0,0 +1 @@
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Dodtatrcretblexmogene2_1213/summary.rtf b/general/datasets/Dodtatrcretblexmogene2_1213/summary.rtf
new file mode 100644
index 0000000..96a87e5
--- /dev/null
+++ b/general/datasets/Dodtatrcretblexmogene2_1213/summary.rtf
@@ -0,0 +1 @@
+The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/Dodtatrcretblexmogene2_1213/tissue.rtf b/general/datasets/Dodtatrcretblexmogene2_1213/tissue.rtf
new file mode 100644
index 0000000..056d7eb
--- /dev/null
+++ b/general/datasets/Dodtatrcretblexmogene2_1213/tissue.rtf
@@ -0,0 +1 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/Dodtatrcretblmogene2_0316/acknowledgment.rtf b/general/datasets/Dodtatrcretblmogene2_0316/acknowledgment.rtf
new file mode 100644
index 0000000..13c6b1e
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_0316/acknowledgment.rtf
@@ -0,0 +1 @@
+DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/Dodtatrcretblmogene2_0316/cases.rtf b/general/datasets/Dodtatrcretblmogene2_0316/cases.rtf
new file mode 100644
index 0000000..6b36c70
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_0316/cases.rtf
@@ -0,0 +1,1728 @@
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+
+
+
+
+
+ | Index |
+ EIGC ID (LIMS ID) |
+ Strain |
+ Sex |
+ Age at harvest |
+ RIN Score |
+
+
+ | 1 |
+ 602 |
+ BXD9 |
+ F |
+ 133 |
+ 9.1 |
+
+
+ | 2 |
+ 603 |
+ BXD9 |
+ M |
+ 100 |
+ 9.5 |
+
+
+ | 3 |
+ 604 |
+ BXD40 |
+ F |
+ 100 |
+ 9.4 |
+
+
+ | 4 |
+ 605 |
+ BXD40 |
+ M |
+ 100 |
+ 9.1 |
+
+
+ | 5 |
+ 606 |
+ BXD48 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 6 |
+ 607 |
+ BXD48 |
+ M |
+ 75 |
+ 8.6 |
+
+
+ | 7 |
+ 608 |
+ BXD63 |
+ F |
+ 75 |
+ 9.2 |
+
+
+ | 8 |
+ 609 |
+ BXD63 |
+ M |
+ 61 |
+ 9.4 |
+
+
+ | 9 |
+ 612 |
+ BXD73 |
+ M |
+ 108 |
+ 10 |
+
+
+ | 10 |
+ 614 |
+ BXD87 |
+ M |
+ 85 |
+ 9.2 |
+
+
+ | 11 |
+ 615 |
+ BXD87 |
+ F |
+ 85 |
+ 9.9 |
+
+
+ | 12 |
+ 616 |
+ BXD69 |
+ F |
+ 76 |
+ 9.3 |
+
+
+ | 13 |
+ 617 |
+ BXD69 |
+ M |
+ 100 |
+ 10 |
+
+
+ | 14 |
+ 618 |
+ BXD51 |
+ M |
+ 82 |
+ 8.9 |
+
+
+ | 15 |
+ 619 |
+ BXD92 (BXD65b) |
+ M |
+ 82 |
+ 8.8 |
+
+
+ | 16 |
+ 620 |
+ BXD92 (BXD65b) |
+ F |
+ 82 |
+ 8.8 |
+
+
+ | 17 |
+ 635 |
+ BXD100 |
+ M |
+ 70 |
+ 9 |
+
+
+ | 18 |
+ 636 |
+ BXD100 |
+ M |
+ 70 |
+ 8.8 |
+
+
+ | 19 |
+ 652 |
+ BXD92 (BXD65b) |
+ F |
+ 64 |
+ 9 |
+
+
+ | 20 |
+ 653 |
+ BXD87 |
+ F |
+ 67 |
+ 9.7 |
+
+
+ | 21 |
+ 654 |
+ BXD87 |
+ M |
+ 67 |
+ 8.9 |
+
+
+ | 22 |
+ 655 |
+ BXD63 |
+ M |
+ 71 |
+ 9 |
+
+
+ | 23 |
+ 660 |
+ BXD69 |
+ M |
+ 97 |
+ 10 |
+
+
+ | 24 |
+ 687 |
+ BXD6 |
+ M |
+ 85 |
+ 7.7 |
+
+
+ | 25 |
+ 688 |
+ BXD6 |
+ M |
+ 85 |
+ 9.4 |
+
+
+ | 26 |
+ 690 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 27 |
+ 691 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 28 |
+ 692 |
+ BXD12 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 29 |
+ 695 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 30 |
+ 696 |
+ BXD5 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 31 |
+ 698 |
+ BXD5 |
+ F |
+ 77 |
+ 9.9 |
+
+
+ | 32 |
+ 699 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 33 |
+ 701 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 34 |
+ 702 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 35 |
+ 705 |
+ BXD8 |
+ F |
+ 77 |
+ 9.2 |
+
+
+ | 36 |
+ 707 |
+ BXD15 |
+ F |
+ 77 |
+ 9.4 |
+
+
+ | 37 |
+ 708 |
+ BXD15 |
+ F |
+ 77 |
+ 9.1 |
+
+
+ | 38 |
+ 710 |
+ BXD15 |
+ M |
+ 77 |
+ 9.1 |
+
+
+ | 39 |
+ 713 |
+ BXD22 |
+ F |
+ 71 |
+ 9.5 |
+
+
+ | 40 |
+ 714 |
+ BXD22 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 41 |
+ 716 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 42 |
+ 717 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 43 |
+ 719 |
+ BXD14 |
+ F |
+ 70 |
+ 9.2 |
+
+
+ | 44 |
+ 722 |
+ BXD14 |
+ M |
+ 70 |
+ 8.9 |
+
+
+ | 45 |
+ 723 |
+ BXD14 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 46 |
+ 725 |
+ BXD18 |
+ F |
+ 70 |
+ 9 |
+
+
+ | 47 |
+ 726 |
+ BXD18 |
+ F |
+ 70 |
+ 9.1 |
+
+
+ | 48 |
+ 728 |
+ BXD18 |
+ M |
+ 70 |
+ 9.1 |
+
+
+ | 49 |
+ 729 |
+ BXD18 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 50 |
+ 731 |
+ BXD19 |
+ F |
+ 66 |
+ 9.3 |
+
+
+ | 51 |
+ 732 |
+ BXD19 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 52 |
+ 734 |
+ BXD19 |
+ M |
+ 66 |
+ 9.8 |
+
+
+ | 53 |
+ 735 |
+ BXD19 |
+ M |
+ 66 |
+ 9.4 |
+
+
+ | 54 |
+ 737 |
+ BXD21 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 55 |
+ 738 |
+ BXD21 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 56 |
+ 740 |
+ BXD21 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 57 |
+ 741 |
+ BXD21 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 58 |
+ 743 |
+ BXD2 |
+ F |
+ 70 |
+ 8.3 |
+
+
+ | 59 |
+ 744 |
+ BXD2 |
+ F |
+ 70 |
+ 8.6 |
+
+
+ | 60 |
+ 746 |
+ BXD2 |
+ M |
+ 70 |
+ 7.5 |
+
+
+ | 61 |
+ 747 |
+ BXD2 |
+ M |
+ 77 |
+ 8.6 |
+
+
+ | 62 |
+ 768 |
+ BXD48 |
+ M |
+ 121 |
+ 9.4 |
+
+
+ | 63 |
+ 770 |
+ BXD92 (BXD65b) |
+ M |
+ 65 |
+ 10 |
+
+
+ | 64 |
+ 771 |
+ BXD101 |
+ F |
+ 85 |
+ 8.3 |
+
+
+ | 65 |
+ 772 |
+ BXD101 |
+ F |
+ 85 |
+ 9.3 |
+
+
+ | 66 |
+ 773 |
+ BXD101 |
+ M |
+ 86 |
+ 9.5 |
+
+
+ | 67 |
+ 774 |
+ BXD101 |
+ M |
+ 86 |
+ 9.8 |
+
+
+ | 68 |
+ 775 |
+ BXD102 |
+ F |
+ 66 |
+ 9.5 |
+
+
+ | 69 |
+ 776 |
+ BXD102 |
+ F |
+ 66 |
+ 10 |
+
+
+ | 70 |
+ 777 |
+ BXD102 |
+ M |
+ 84 |
+ 9.6 |
+
+
+ | 71 |
+ 787 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 72 |
+ 788 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 73 |
+ 789 |
+ BXD63 |
+ F |
+ 115 |
+ 9.7 |
+
+
+ | 74 |
+ 790 |
+ BXD100 |
+ F |
+ 72 |
+ 9.8 |
+
+
+ | 75 |
+ 791 |
+ BXD100 |
+ F |
+ 72 |
+ 10 |
+
+
+ | 76 |
+ 818 |
+ BXD51 |
+ F |
+ 77 |
+ 9.7 |
+
+
+ | 77 |
+ 819 |
+ BXD51 |
+ F |
+ 77 |
+ 9.6 |
+
+
+ | 78 |
+ 820 |
+ BXD51 |
+ M |
+ 72 |
+ 9.7 |
+
+
+ | 79 |
+ 821 |
+ BXD65 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 80 |
+ 822 |
+ BXD65 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 81 |
+ 825 |
+ BXD65 |
+ F |
+ 72 |
+ 9.5 |
+
+
+ | 82 |
+ 827 |
+ BXD86 |
+ M |
+ 69 |
+ 9.1 |
+
+
+ | 83 |
+ 828 |
+ BXD86 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 84 |
+ 829 |
+ BXD90 |
+ F |
+ 69 |
+ 9.6 |
+
+
+ | 85 |
+ 831 |
+ BXD9 |
+ M |
+ 127 |
+ 9.7 |
+
+
+ | 86 |
+ 832 |
+ BXD39 |
+ F |
+ 99 |
+ 9.4 |
+
+
+ | 87 |
+ 833 |
+ BXD39 |
+ F |
+ 107 |
+ 9.3 |
+
+
+ | 88 |
+ 834 |
+ BXD60 |
+ F |
+ 107 |
+ 9.5 |
+
+
+ | 89 |
+ 836 |
+ BXD84 |
+ M |
+ 103 |
+ 9.7 |
+
+
+ | 90 |
+ 846 |
+ BXD39 |
+ M |
+ 63 |
+ 9.7 |
+
+
+ | 91 |
+ 847 |
+ BXD39 |
+ M |
+ 63 |
+ 9.8 |
+
+
+ | 92 |
+ 849 |
+ BXD20 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 93 |
+ 850 |
+ BXD20 |
+ M |
+ 70 |
+ 10 |
+
+
+ | 94 |
+ 851 |
+ BXD20 |
+ * |
+ 70 |
+ 9.5 |
+
+
+ | 95 |
+ 855 |
+ DBA/2J |
+ F |
+ 78 |
+ 9.7 |
+
+
+ | 96 |
+ 856 |
+ DBA/2J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 97 |
+ 857 |
+ DBA/2J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 98 |
+ 858 |
+ DBA/2J |
+ M |
+ 78 |
+ 9.9 |
+
+
+ | 99 |
+ 859 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 100 |
+ 860 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 101 |
+ 861 |
+ C57BL/6J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 102 |
+ 862 |
+ C57BL/6J |
+ M |
+ 78 |
+ 9.6 |
+
+
+ | 103 |
+ EGE10907-0172_890_20844 |
+ BXD28 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 104 |
+ EGE10907-0173_891_20845 |
+ BXD28 |
+ M |
+ 75 |
+ 9.7 |
+
+
+ | 105 |
+ EGE10907-0174_892_20846 |
+ BXD28 |
+ F |
+ 75 |
+ 9.7 |
+
+
+ | 106 |
+ EGE10907-0176_895_20848 |
+ BXD33 |
+ M |
+ 75 |
+ 9.88 |
+
+
+ | 107 |
+ EGE10907-0177_896_20849 |
+ BXD33 |
+ F |
+ 75 |
+ 10 |
+
+
+ | 108 |
+ EGE10907-0178_897_20850 |
+ BXD33 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 109 |
+ EGE10907-0179_898_20851 |
+ BXD36 |
+ M |
+ 75 |
+ 9.4 |
+
+
+ | 110 |
+ EGE10907-0180_899_20852 |
+ BXD36 |
+ F |
+ 75 |
+ 9.5 |
+
+
+ | 111 |
+ EGE10907-0181_900_20853 |
+ BXD36 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 112 |
+ EGE10907-0182_910_20854 |
+ BXD27 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 113 |
+ EGE10907-0183_990_20855 |
+ BXD9 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 114 |
+ EGE10907-0184_991_20856 |
+ BXD16 |
+ F |
+ 113 |
+ 10 |
+
+
+ | 115 |
+ EGE10907-0185_992_20857 |
+ BXD16 |
+ M |
+ 113 |
+ 9 |
+
+
+ | 116 |
+ EGE10907-0186_993_20858 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 117 |
+ EGE10907-0187_994_20859 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 118 |
+ EGE10907-0188_996_20860 |
+ BXD48 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 119 |
+ EGE10907-0189_997_20861 |
+ BXD73 |
+ M |
+ 106 |
+ 10 |
+
+
+ | 120 |
+ EGE10907-0190_999_20862 |
+ BXD11 |
+ F |
+ 121 |
+ 9.6 |
+
+
+ | 121 |
+ EGE10907-0191_100_20863 |
+ BXD11 |
+ F |
+ 121 |
+ 9.9 |
+
+
+ | 122 |
+ EGE10907-0192_1010_21276 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 123 |
+ EGE10907-0193_1011_21277 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 124 |
+ EGE10907-0194_1012_21278 |
+ BXD16 |
+ F |
+ 65 |
+ 10 |
+
+
+ | 125 |
+ EGE10907-0195_1015_21279 |
+ BXD16 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 126 |
+ EGE10907-0196_1019_21280 |
+ BXD33 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 127 |
+ EGE10907-0197_1020_21281 |
+ BXD36 |
+ M |
+ 78 |
+ 10 |
+
+
+ | 128 |
+ EGE10907-0198_1021_21282 |
+ BXD38 |
+ F |
+ 70 |
+ 9.8 |
+
+
+ | 129 |
+ EGE10907-0199_1022_21283 |
+ BXD38 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 130 |
+ EGE10907-0200_1023_21284 |
+ BXD38 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 131 |
+ EGE10907-0201_1047_21285 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 132 |
+ EGE10907-0202_1048_21286 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 133 |
+ EGE10907-0203_1049_21287 |
+ BXD38 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 134 |
+ EGE10907-0204_1050_21288 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 135 |
+ EGE10907-0205_1051_21289 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 136 |
+ EGE10907-0206_1052_21290 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 137 |
+ EGE10907-0207_1053_21291 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 138 |
+ EGE10907-0208_1054_21292 |
+ BXD90 |
+ F |
+ 71 |
+ 10 |
+
+
+ | 139 |
+ EGE10907-0209_1055_21293 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 140 |
+ EGE10907-0210_1056_21294 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 141 |
+ EGE10907-0211_1148_21295 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 142 |
+ EGE10907-0212_1149_21296 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 143 |
+ EGE10907-0213_1150_21297 |
+ BXD31 |
+ M |
+ 90 |
+ 10 |
+
+
+ | 144 |
+ EGE10907-0214_1151_21298 |
+ BXD31 |
+ M |
+ 90 |
+ 9.9 |
+
+
+ | 145 |
+ EGE10907-0215_1152_21299 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 146 |
+ EGE10907-0216_21429 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 147 |
+ EGE10907-0217_21430 |
+ BXD42 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 148 |
+ EGE10907-0218_21431 |
+ BXD42 |
+ M |
+ 83 |
+ 9.3 |
+
+
+ | 149 |
+ EGE10907-0219_21432 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 150 |
+ EGE10907-0220_21433 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 151 |
+ EGE10907-0221_21434 |
+ BXD50 |
+ F |
+ 92 |
+ 10 |
+
+
+ | 152 |
+ EGE10907-0222_21435 |
+ BXD1 |
+ M |
+ 73 |
+ 9.6 |
+
+
+ | 153 |
+ EGE10907-0223_21436 |
+ BXD13 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 154 |
+ EGE10907-0224_21437 |
+ BXD1 |
+ M |
+ 71 |
+ 9.5 |
+
+
+ | 155 |
+ EGE10907-0225_21438 |
+ BXD13 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 156 |
+ EGE10907-0226_21439 |
+ BXD43 |
+ F |
+ 85 |
+ 10 |
+
+
+ | 157 |
+ EGE10907-0227_21452 |
+ BXD43 |
+ F |
+ 85 |
+ 9.6 |
+
+
+ | 158 |
+ EGE10907-0229_21442 |
+ BXD43 |
+ M |
+ 85 |
+ 8.2 |
+
+
+ | 159 |
+ EGE10907-0230_21443 |
+ BXD50 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 160 |
+ EGE10907-0231_21444 |
+ BXD1 |
+ F |
+ 68 |
+ 9.4 |
+
+
+ | 161 |
+ EGE10907-0232_21445 |
+ BXD1 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 162 |
+ EGE10907-0233_21446 |
+ BXD29 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 163 |
+ EGE10907-0234_21447 |
+ BXD29 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 164 |
+ EGE10907-0235_21448 |
+ BXD75 |
+ F |
+ 68 |
+ 10 |
+
+
+ | 165 |
+ EGE10907-0236_21449 |
+ BXD75 |
+ M |
+ 68 |
+ 10 |
+
+
+ | 166 |
+ EGE10907-0237_21450 |
+ BXD96 |
+ F |
+ 67 |
+ 9.9 |
+
+
+ | 167 |
+ EGE10907-0238_21931 |
+ BXD99 |
+ M |
+ 71 |
+ 7.9 |
+
+
+ | 168 |
+ EGE10907-0239_21932 |
+ BXD99 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 169 |
+ EGE10907-0240_21933 |
+ BXD67 |
+ F |
+ 68 |
+ 8.8 |
+
+
+ | 170 |
+ EGE10907-0241_21934 |
+ BXD67 |
+ F |
+ 68 |
+ 8.5 |
+
+
+ | 171 |
+ EGE10907-0242_21935 |
+ BXD67 |
+ M |
+ 68 |
+ 9.5 |
+
+
+ | 172 |
+ EGE10907-0243_21936 |
+ BXD67 |
+ M |
+ 68 |
+ 9.6 |
+
+
+ | 173 |
+ EGE10907-0244_21937 |
+ BXD6 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 174 |
+ EGE10907-0245_21938 |
+ BXD12 |
+ M |
+ 82 |
+ 9.5 |
+
+
+ | 175 |
+ EGE10907-0246_21939 |
+ BXD60 |
+ F |
+ 72 |
+ 9.6 |
+
+
+ | 176 |
+ EGE10907-0247_21940 |
+ BXD65 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 177 |
+ EGE10907-0248_21941 |
+ BXD75 |
+ F |
+ 69 |
+ 8.8 |
+
+
+ | 178 |
+ EGE10907-0249_21942_(MoGene-2_0-st) |
+ BXD75 |
+ M |
+ 69 |
+ 9.2 |
+
+
+ | 179 |
+ EGE10907-0250_21943 |
+ BXD8 |
+ F |
+ 97 |
+ 9.1 |
+
+
+ | 180 |
+ EGE10907-0251_21944 |
+ BXD85 |
+ F |
+ 79 |
+ 8.6 |
+
+
+ | 181 |
+ EGE10907-0252_21945 |
+ BXD85 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 182 |
+ EGE10907-0253_21946 |
+ BXD85 |
+ M |
+ 79 |
+ 9.4 |
+
+
+ | 183 |
+ EGE10907-0254_21947 |
+ BXD102 |
+ M |
+ 94 |
+ 8.6 |
+
+
+ | 184 |
+ EGE10907-0255_21948 |
+ BXD99 |
+ F |
+ 83 |
+ 9 |
+
+
+ | 185 |
+ EGE10907-0256_21949 |
+ BXD69 |
+ F |
+ 68 |
+ 9 |
+
+
+ | 186 |
+ EGE10907-0257_21950 |
+ BXD84 |
+ F |
+ 74 |
+ 9.5 |
+
+
+ | 187 |
+ EGE10907-0258_21951 |
+ BXD84 |
+ F |
+ 74 |
+ 9.4 |
+
+
+ | 188 |
+ EGE10907-0259_21952 |
+ BXD84 |
+ M |
+ 74 |
+ 8.6 |
+
+
+ | 189 |
+ EGE10907-0260_21451 |
+ BXD96 |
+ M |
+ 67 |
+ 9.2 |
+
+
+ | 190 |
+ EGE10907-0261_21452 |
+ BXD99 |
+ F |
+ 71 |
+ 8.9 |
+
+
+ | 191 |
+ EGE10907-0262_21931 |
+ BXD6 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 192 |
+ EGE10907-0263_21932 |
+ BXD14 |
+ F |
+ 69 |
+ 8.5 |
+
+
+ | 193 |
+ EGE10907-0264_21933 |
+ BXD34 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 194 |
+ EGE10907-0265_21934 |
+ BXD34 |
+ M |
+ 79 |
+ 9.9 |
+
+
+ | 195 |
+ EGE10907-0266_21935 |
+ BXD40 |
+ F |
+ 75 |
+ 9.6 |
+
+
+ | 196 |
+ EGE10907-0267_21936 |
+ BXD40 |
+ M |
+ 78 |
+ 9.7 |
+
+
+ | 197 |
+ EGE10907-0268_21937 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 198 |
+ EGE10907-0269_21938 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 199 |
+ EGE10907-0270_21939 |
+ BXD56 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 200 |
+ EGE10907-0271_21940 |
+ BXD56 |
+ M |
+ 72 |
+ 9.4 |
+
+
+ | 201 |
+ EGE10907-0272_21941 |
+ BXD71 |
+ F |
+ 72 |
+ 9.9 |
+
+
+ | 202 |
+ EGE10907-0273_21942 |
+ BXD71 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 203 |
+ EGE10907-0274_21943 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 204 |
+ EGE10907-0275_21944 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 205 |
+ EGE10907-0276_21945 |
+ BXD27 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 206 |
+ EGE10907-0277_21946 |
+ BXD15 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 207 |
+ EGE10907-0278_21947 |
+ BXD20 |
+ F |
+ 125 |
+ 10 |
+
+
+ | 208 |
+ EGE10907-0279_21948 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 209 |
+ EGE10907-0280_21949 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 210 |
+ EGE10907-0281_21950 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 211 |
+ EGE10907-0282_21951 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 212 |
+ EGE10907-0283_21952 |
+ BXD85 |
+ F |
+ 87 |
+ 10 |
+
+
+ | 213 |
+ EGE10907-0284_21451 |
+ BXD43 |
+ M |
+ 75 |
+ 9.8 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Dodtatrcretblmogene2_0316/citation.rtf b/general/datasets/Dodtatrcretblmogene2_0316/citation.rtf
new file mode 100644
index 0000000..d84717d
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_0316/citation.rtf
@@ -0,0 +1,3 @@
+Related Publications: Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link) Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674 Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link) Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful: NEIBank collection of ESTs and SAGE data. RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases.
diff --git a/general/datasets/Dodtatrcretblmogene2_0316/contributors.rtf b/general/datasets/Dodtatrcretblmogene2_0316/contributors.rtf
new file mode 100644
index 0000000..11fece2
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_0316/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, XiangDi Wang, Justin P. Templeton and Robert W. Williams.
diff --git a/general/datasets/Dodtatrcretblmogene2_0316/platform.rtf b/general/datasets/Dodtatrcretblmogene2_0316/platform.rtf
new file mode 100644
index 0000000..19fc38c
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_0316/platform.rtf
@@ -0,0 +1 @@
+The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/Dodtatrcretblmogene2_0316/processing.rtf b/general/datasets/Dodtatrcretblmogene2_0316/processing.rtf
new file mode 100644
index 0000000..a7b767e
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_0316/processing.rtf
@@ -0,0 +1 @@
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Dodtatrcretblmogene2_0316/summary.rtf b/general/datasets/Dodtatrcretblmogene2_0316/summary.rtf
new file mode 100644
index 0000000..96a87e5
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_0316/summary.rtf
@@ -0,0 +1 @@
+The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/Dodtatrcretblmogene2_0316/tissue.rtf b/general/datasets/Dodtatrcretblmogene2_0316/tissue.rtf
new file mode 100644
index 0000000..056d7eb
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_0316/tissue.rtf
@@ -0,0 +1 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/Dodtatrcretblmogene2_1213/acknowledgment.rtf b/general/datasets/Dodtatrcretblmogene2_1213/acknowledgment.rtf
new file mode 100644
index 0000000..13c6b1e
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_1213/acknowledgment.rtf
@@ -0,0 +1 @@
+DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/Dodtatrcretblmogene2_1213/cases.rtf b/general/datasets/Dodtatrcretblmogene2_1213/cases.rtf
new file mode 100644
index 0000000..6b36c70
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_1213/cases.rtf
@@ -0,0 +1,1728 @@
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+
+
+
+
+
+ | Index |
+ EIGC ID (LIMS ID) |
+ Strain |
+ Sex |
+ Age at harvest |
+ RIN Score |
+
+
+ | 1 |
+ 602 |
+ BXD9 |
+ F |
+ 133 |
+ 9.1 |
+
+
+ | 2 |
+ 603 |
+ BXD9 |
+ M |
+ 100 |
+ 9.5 |
+
+
+ | 3 |
+ 604 |
+ BXD40 |
+ F |
+ 100 |
+ 9.4 |
+
+
+ | 4 |
+ 605 |
+ BXD40 |
+ M |
+ 100 |
+ 9.1 |
+
+
+ | 5 |
+ 606 |
+ BXD48 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 6 |
+ 607 |
+ BXD48 |
+ M |
+ 75 |
+ 8.6 |
+
+
+ | 7 |
+ 608 |
+ BXD63 |
+ F |
+ 75 |
+ 9.2 |
+
+
+ | 8 |
+ 609 |
+ BXD63 |
+ M |
+ 61 |
+ 9.4 |
+
+
+ | 9 |
+ 612 |
+ BXD73 |
+ M |
+ 108 |
+ 10 |
+
+
+ | 10 |
+ 614 |
+ BXD87 |
+ M |
+ 85 |
+ 9.2 |
+
+
+ | 11 |
+ 615 |
+ BXD87 |
+ F |
+ 85 |
+ 9.9 |
+
+
+ | 12 |
+ 616 |
+ BXD69 |
+ F |
+ 76 |
+ 9.3 |
+
+
+ | 13 |
+ 617 |
+ BXD69 |
+ M |
+ 100 |
+ 10 |
+
+
+ | 14 |
+ 618 |
+ BXD51 |
+ M |
+ 82 |
+ 8.9 |
+
+
+ | 15 |
+ 619 |
+ BXD92 (BXD65b) |
+ M |
+ 82 |
+ 8.8 |
+
+
+ | 16 |
+ 620 |
+ BXD92 (BXD65b) |
+ F |
+ 82 |
+ 8.8 |
+
+
+ | 17 |
+ 635 |
+ BXD100 |
+ M |
+ 70 |
+ 9 |
+
+
+ | 18 |
+ 636 |
+ BXD100 |
+ M |
+ 70 |
+ 8.8 |
+
+
+ | 19 |
+ 652 |
+ BXD92 (BXD65b) |
+ F |
+ 64 |
+ 9 |
+
+
+ | 20 |
+ 653 |
+ BXD87 |
+ F |
+ 67 |
+ 9.7 |
+
+
+ | 21 |
+ 654 |
+ BXD87 |
+ M |
+ 67 |
+ 8.9 |
+
+
+ | 22 |
+ 655 |
+ BXD63 |
+ M |
+ 71 |
+ 9 |
+
+
+ | 23 |
+ 660 |
+ BXD69 |
+ M |
+ 97 |
+ 10 |
+
+
+ | 24 |
+ 687 |
+ BXD6 |
+ M |
+ 85 |
+ 7.7 |
+
+
+ | 25 |
+ 688 |
+ BXD6 |
+ M |
+ 85 |
+ 9.4 |
+
+
+ | 26 |
+ 690 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 27 |
+ 691 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 28 |
+ 692 |
+ BXD12 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 29 |
+ 695 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 30 |
+ 696 |
+ BXD5 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 31 |
+ 698 |
+ BXD5 |
+ F |
+ 77 |
+ 9.9 |
+
+
+ | 32 |
+ 699 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 33 |
+ 701 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 34 |
+ 702 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 35 |
+ 705 |
+ BXD8 |
+ F |
+ 77 |
+ 9.2 |
+
+
+ | 36 |
+ 707 |
+ BXD15 |
+ F |
+ 77 |
+ 9.4 |
+
+
+ | 37 |
+ 708 |
+ BXD15 |
+ F |
+ 77 |
+ 9.1 |
+
+
+ | 38 |
+ 710 |
+ BXD15 |
+ M |
+ 77 |
+ 9.1 |
+
+
+ | 39 |
+ 713 |
+ BXD22 |
+ F |
+ 71 |
+ 9.5 |
+
+
+ | 40 |
+ 714 |
+ BXD22 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 41 |
+ 716 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 42 |
+ 717 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 43 |
+ 719 |
+ BXD14 |
+ F |
+ 70 |
+ 9.2 |
+
+
+ | 44 |
+ 722 |
+ BXD14 |
+ M |
+ 70 |
+ 8.9 |
+
+
+ | 45 |
+ 723 |
+ BXD14 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 46 |
+ 725 |
+ BXD18 |
+ F |
+ 70 |
+ 9 |
+
+
+ | 47 |
+ 726 |
+ BXD18 |
+ F |
+ 70 |
+ 9.1 |
+
+
+ | 48 |
+ 728 |
+ BXD18 |
+ M |
+ 70 |
+ 9.1 |
+
+
+ | 49 |
+ 729 |
+ BXD18 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 50 |
+ 731 |
+ BXD19 |
+ F |
+ 66 |
+ 9.3 |
+
+
+ | 51 |
+ 732 |
+ BXD19 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 52 |
+ 734 |
+ BXD19 |
+ M |
+ 66 |
+ 9.8 |
+
+
+ | 53 |
+ 735 |
+ BXD19 |
+ M |
+ 66 |
+ 9.4 |
+
+
+ | 54 |
+ 737 |
+ BXD21 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 55 |
+ 738 |
+ BXD21 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 56 |
+ 740 |
+ BXD21 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 57 |
+ 741 |
+ BXD21 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 58 |
+ 743 |
+ BXD2 |
+ F |
+ 70 |
+ 8.3 |
+
+
+ | 59 |
+ 744 |
+ BXD2 |
+ F |
+ 70 |
+ 8.6 |
+
+
+ | 60 |
+ 746 |
+ BXD2 |
+ M |
+ 70 |
+ 7.5 |
+
+
+ | 61 |
+ 747 |
+ BXD2 |
+ M |
+ 77 |
+ 8.6 |
+
+
+ | 62 |
+ 768 |
+ BXD48 |
+ M |
+ 121 |
+ 9.4 |
+
+
+ | 63 |
+ 770 |
+ BXD92 (BXD65b) |
+ M |
+ 65 |
+ 10 |
+
+
+ | 64 |
+ 771 |
+ BXD101 |
+ F |
+ 85 |
+ 8.3 |
+
+
+ | 65 |
+ 772 |
+ BXD101 |
+ F |
+ 85 |
+ 9.3 |
+
+
+ | 66 |
+ 773 |
+ BXD101 |
+ M |
+ 86 |
+ 9.5 |
+
+
+ | 67 |
+ 774 |
+ BXD101 |
+ M |
+ 86 |
+ 9.8 |
+
+
+ | 68 |
+ 775 |
+ BXD102 |
+ F |
+ 66 |
+ 9.5 |
+
+
+ | 69 |
+ 776 |
+ BXD102 |
+ F |
+ 66 |
+ 10 |
+
+
+ | 70 |
+ 777 |
+ BXD102 |
+ M |
+ 84 |
+ 9.6 |
+
+
+ | 71 |
+ 787 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 72 |
+ 788 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 73 |
+ 789 |
+ BXD63 |
+ F |
+ 115 |
+ 9.7 |
+
+
+ | 74 |
+ 790 |
+ BXD100 |
+ F |
+ 72 |
+ 9.8 |
+
+
+ | 75 |
+ 791 |
+ BXD100 |
+ F |
+ 72 |
+ 10 |
+
+
+ | 76 |
+ 818 |
+ BXD51 |
+ F |
+ 77 |
+ 9.7 |
+
+
+ | 77 |
+ 819 |
+ BXD51 |
+ F |
+ 77 |
+ 9.6 |
+
+
+ | 78 |
+ 820 |
+ BXD51 |
+ M |
+ 72 |
+ 9.7 |
+
+
+ | 79 |
+ 821 |
+ BXD65 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 80 |
+ 822 |
+ BXD65 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 81 |
+ 825 |
+ BXD65 |
+ F |
+ 72 |
+ 9.5 |
+
+
+ | 82 |
+ 827 |
+ BXD86 |
+ M |
+ 69 |
+ 9.1 |
+
+
+ | 83 |
+ 828 |
+ BXD86 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 84 |
+ 829 |
+ BXD90 |
+ F |
+ 69 |
+ 9.6 |
+
+
+ | 85 |
+ 831 |
+ BXD9 |
+ M |
+ 127 |
+ 9.7 |
+
+
+ | 86 |
+ 832 |
+ BXD39 |
+ F |
+ 99 |
+ 9.4 |
+
+
+ | 87 |
+ 833 |
+ BXD39 |
+ F |
+ 107 |
+ 9.3 |
+
+
+ | 88 |
+ 834 |
+ BXD60 |
+ F |
+ 107 |
+ 9.5 |
+
+
+ | 89 |
+ 836 |
+ BXD84 |
+ M |
+ 103 |
+ 9.7 |
+
+
+ | 90 |
+ 846 |
+ BXD39 |
+ M |
+ 63 |
+ 9.7 |
+
+
+ | 91 |
+ 847 |
+ BXD39 |
+ M |
+ 63 |
+ 9.8 |
+
+
+ | 92 |
+ 849 |
+ BXD20 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 93 |
+ 850 |
+ BXD20 |
+ M |
+ 70 |
+ 10 |
+
+
+ | 94 |
+ 851 |
+ BXD20 |
+ * |
+ 70 |
+ 9.5 |
+
+
+ | 95 |
+ 855 |
+ DBA/2J |
+ F |
+ 78 |
+ 9.7 |
+
+
+ | 96 |
+ 856 |
+ DBA/2J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 97 |
+ 857 |
+ DBA/2J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 98 |
+ 858 |
+ DBA/2J |
+ M |
+ 78 |
+ 9.9 |
+
+
+ | 99 |
+ 859 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 100 |
+ 860 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 101 |
+ 861 |
+ C57BL/6J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 102 |
+ 862 |
+ C57BL/6J |
+ M |
+ 78 |
+ 9.6 |
+
+
+ | 103 |
+ EGE10907-0172_890_20844 |
+ BXD28 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 104 |
+ EGE10907-0173_891_20845 |
+ BXD28 |
+ M |
+ 75 |
+ 9.7 |
+
+
+ | 105 |
+ EGE10907-0174_892_20846 |
+ BXD28 |
+ F |
+ 75 |
+ 9.7 |
+
+
+ | 106 |
+ EGE10907-0176_895_20848 |
+ BXD33 |
+ M |
+ 75 |
+ 9.88 |
+
+
+ | 107 |
+ EGE10907-0177_896_20849 |
+ BXD33 |
+ F |
+ 75 |
+ 10 |
+
+
+ | 108 |
+ EGE10907-0178_897_20850 |
+ BXD33 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 109 |
+ EGE10907-0179_898_20851 |
+ BXD36 |
+ M |
+ 75 |
+ 9.4 |
+
+
+ | 110 |
+ EGE10907-0180_899_20852 |
+ BXD36 |
+ F |
+ 75 |
+ 9.5 |
+
+
+ | 111 |
+ EGE10907-0181_900_20853 |
+ BXD36 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 112 |
+ EGE10907-0182_910_20854 |
+ BXD27 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 113 |
+ EGE10907-0183_990_20855 |
+ BXD9 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 114 |
+ EGE10907-0184_991_20856 |
+ BXD16 |
+ F |
+ 113 |
+ 10 |
+
+
+ | 115 |
+ EGE10907-0185_992_20857 |
+ BXD16 |
+ M |
+ 113 |
+ 9 |
+
+
+ | 116 |
+ EGE10907-0186_993_20858 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 117 |
+ EGE10907-0187_994_20859 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 118 |
+ EGE10907-0188_996_20860 |
+ BXD48 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 119 |
+ EGE10907-0189_997_20861 |
+ BXD73 |
+ M |
+ 106 |
+ 10 |
+
+
+ | 120 |
+ EGE10907-0190_999_20862 |
+ BXD11 |
+ F |
+ 121 |
+ 9.6 |
+
+
+ | 121 |
+ EGE10907-0191_100_20863 |
+ BXD11 |
+ F |
+ 121 |
+ 9.9 |
+
+
+ | 122 |
+ EGE10907-0192_1010_21276 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 123 |
+ EGE10907-0193_1011_21277 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 124 |
+ EGE10907-0194_1012_21278 |
+ BXD16 |
+ F |
+ 65 |
+ 10 |
+
+
+ | 125 |
+ EGE10907-0195_1015_21279 |
+ BXD16 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 126 |
+ EGE10907-0196_1019_21280 |
+ BXD33 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 127 |
+ EGE10907-0197_1020_21281 |
+ BXD36 |
+ M |
+ 78 |
+ 10 |
+
+
+ | 128 |
+ EGE10907-0198_1021_21282 |
+ BXD38 |
+ F |
+ 70 |
+ 9.8 |
+
+
+ | 129 |
+ EGE10907-0199_1022_21283 |
+ BXD38 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 130 |
+ EGE10907-0200_1023_21284 |
+ BXD38 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 131 |
+ EGE10907-0201_1047_21285 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 132 |
+ EGE10907-0202_1048_21286 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 133 |
+ EGE10907-0203_1049_21287 |
+ BXD38 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 134 |
+ EGE10907-0204_1050_21288 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 135 |
+ EGE10907-0205_1051_21289 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 136 |
+ EGE10907-0206_1052_21290 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 137 |
+ EGE10907-0207_1053_21291 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 138 |
+ EGE10907-0208_1054_21292 |
+ BXD90 |
+ F |
+ 71 |
+ 10 |
+
+
+ | 139 |
+ EGE10907-0209_1055_21293 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 140 |
+ EGE10907-0210_1056_21294 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 141 |
+ EGE10907-0211_1148_21295 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 142 |
+ EGE10907-0212_1149_21296 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 143 |
+ EGE10907-0213_1150_21297 |
+ BXD31 |
+ M |
+ 90 |
+ 10 |
+
+
+ | 144 |
+ EGE10907-0214_1151_21298 |
+ BXD31 |
+ M |
+ 90 |
+ 9.9 |
+
+
+ | 145 |
+ EGE10907-0215_1152_21299 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 146 |
+ EGE10907-0216_21429 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 147 |
+ EGE10907-0217_21430 |
+ BXD42 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 148 |
+ EGE10907-0218_21431 |
+ BXD42 |
+ M |
+ 83 |
+ 9.3 |
+
+
+ | 149 |
+ EGE10907-0219_21432 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 150 |
+ EGE10907-0220_21433 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 151 |
+ EGE10907-0221_21434 |
+ BXD50 |
+ F |
+ 92 |
+ 10 |
+
+
+ | 152 |
+ EGE10907-0222_21435 |
+ BXD1 |
+ M |
+ 73 |
+ 9.6 |
+
+
+ | 153 |
+ EGE10907-0223_21436 |
+ BXD13 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 154 |
+ EGE10907-0224_21437 |
+ BXD1 |
+ M |
+ 71 |
+ 9.5 |
+
+
+ | 155 |
+ EGE10907-0225_21438 |
+ BXD13 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 156 |
+ EGE10907-0226_21439 |
+ BXD43 |
+ F |
+ 85 |
+ 10 |
+
+
+ | 157 |
+ EGE10907-0227_21452 |
+ BXD43 |
+ F |
+ 85 |
+ 9.6 |
+
+
+ | 158 |
+ EGE10907-0229_21442 |
+ BXD43 |
+ M |
+ 85 |
+ 8.2 |
+
+
+ | 159 |
+ EGE10907-0230_21443 |
+ BXD50 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 160 |
+ EGE10907-0231_21444 |
+ BXD1 |
+ F |
+ 68 |
+ 9.4 |
+
+
+ | 161 |
+ EGE10907-0232_21445 |
+ BXD1 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 162 |
+ EGE10907-0233_21446 |
+ BXD29 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 163 |
+ EGE10907-0234_21447 |
+ BXD29 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 164 |
+ EGE10907-0235_21448 |
+ BXD75 |
+ F |
+ 68 |
+ 10 |
+
+
+ | 165 |
+ EGE10907-0236_21449 |
+ BXD75 |
+ M |
+ 68 |
+ 10 |
+
+
+ | 166 |
+ EGE10907-0237_21450 |
+ BXD96 |
+ F |
+ 67 |
+ 9.9 |
+
+
+ | 167 |
+ EGE10907-0238_21931 |
+ BXD99 |
+ M |
+ 71 |
+ 7.9 |
+
+
+ | 168 |
+ EGE10907-0239_21932 |
+ BXD99 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 169 |
+ EGE10907-0240_21933 |
+ BXD67 |
+ F |
+ 68 |
+ 8.8 |
+
+
+ | 170 |
+ EGE10907-0241_21934 |
+ BXD67 |
+ F |
+ 68 |
+ 8.5 |
+
+
+ | 171 |
+ EGE10907-0242_21935 |
+ BXD67 |
+ M |
+ 68 |
+ 9.5 |
+
+
+ | 172 |
+ EGE10907-0243_21936 |
+ BXD67 |
+ M |
+ 68 |
+ 9.6 |
+
+
+ | 173 |
+ EGE10907-0244_21937 |
+ BXD6 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 174 |
+ EGE10907-0245_21938 |
+ BXD12 |
+ M |
+ 82 |
+ 9.5 |
+
+
+ | 175 |
+ EGE10907-0246_21939 |
+ BXD60 |
+ F |
+ 72 |
+ 9.6 |
+
+
+ | 176 |
+ EGE10907-0247_21940 |
+ BXD65 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 177 |
+ EGE10907-0248_21941 |
+ BXD75 |
+ F |
+ 69 |
+ 8.8 |
+
+
+ | 178 |
+ EGE10907-0249_21942_(MoGene-2_0-st) |
+ BXD75 |
+ M |
+ 69 |
+ 9.2 |
+
+
+ | 179 |
+ EGE10907-0250_21943 |
+ BXD8 |
+ F |
+ 97 |
+ 9.1 |
+
+
+ | 180 |
+ EGE10907-0251_21944 |
+ BXD85 |
+ F |
+ 79 |
+ 8.6 |
+
+
+ | 181 |
+ EGE10907-0252_21945 |
+ BXD85 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 182 |
+ EGE10907-0253_21946 |
+ BXD85 |
+ M |
+ 79 |
+ 9.4 |
+
+
+ | 183 |
+ EGE10907-0254_21947 |
+ BXD102 |
+ M |
+ 94 |
+ 8.6 |
+
+
+ | 184 |
+ EGE10907-0255_21948 |
+ BXD99 |
+ F |
+ 83 |
+ 9 |
+
+
+ | 185 |
+ EGE10907-0256_21949 |
+ BXD69 |
+ F |
+ 68 |
+ 9 |
+
+
+ | 186 |
+ EGE10907-0257_21950 |
+ BXD84 |
+ F |
+ 74 |
+ 9.5 |
+
+
+ | 187 |
+ EGE10907-0258_21951 |
+ BXD84 |
+ F |
+ 74 |
+ 9.4 |
+
+
+ | 188 |
+ EGE10907-0259_21952 |
+ BXD84 |
+ M |
+ 74 |
+ 8.6 |
+
+
+ | 189 |
+ EGE10907-0260_21451 |
+ BXD96 |
+ M |
+ 67 |
+ 9.2 |
+
+
+ | 190 |
+ EGE10907-0261_21452 |
+ BXD99 |
+ F |
+ 71 |
+ 8.9 |
+
+
+ | 191 |
+ EGE10907-0262_21931 |
+ BXD6 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 192 |
+ EGE10907-0263_21932 |
+ BXD14 |
+ F |
+ 69 |
+ 8.5 |
+
+
+ | 193 |
+ EGE10907-0264_21933 |
+ BXD34 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 194 |
+ EGE10907-0265_21934 |
+ BXD34 |
+ M |
+ 79 |
+ 9.9 |
+
+
+ | 195 |
+ EGE10907-0266_21935 |
+ BXD40 |
+ F |
+ 75 |
+ 9.6 |
+
+
+ | 196 |
+ EGE10907-0267_21936 |
+ BXD40 |
+ M |
+ 78 |
+ 9.7 |
+
+
+ | 197 |
+ EGE10907-0268_21937 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 198 |
+ EGE10907-0269_21938 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 199 |
+ EGE10907-0270_21939 |
+ BXD56 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 200 |
+ EGE10907-0271_21940 |
+ BXD56 |
+ M |
+ 72 |
+ 9.4 |
+
+
+ | 201 |
+ EGE10907-0272_21941 |
+ BXD71 |
+ F |
+ 72 |
+ 9.9 |
+
+
+ | 202 |
+ EGE10907-0273_21942 |
+ BXD71 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 203 |
+ EGE10907-0274_21943 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 204 |
+ EGE10907-0275_21944 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 205 |
+ EGE10907-0276_21945 |
+ BXD27 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 206 |
+ EGE10907-0277_21946 |
+ BXD15 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 207 |
+ EGE10907-0278_21947 |
+ BXD20 |
+ F |
+ 125 |
+ 10 |
+
+
+ | 208 |
+ EGE10907-0279_21948 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 209 |
+ EGE10907-0280_21949 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 210 |
+ EGE10907-0281_21950 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 211 |
+ EGE10907-0282_21951 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 212 |
+ EGE10907-0283_21952 |
+ BXD85 |
+ F |
+ 87 |
+ 10 |
+
+
+ | 213 |
+ EGE10907-0284_21451 |
+ BXD43 |
+ M |
+ 75 |
+ 9.8 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Dodtatrcretblmogene2_1213/citation.rtf b/general/datasets/Dodtatrcretblmogene2_1213/citation.rtf
new file mode 100644
index 0000000..d84717d
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_1213/citation.rtf
@@ -0,0 +1,3 @@
+Related Publications: Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link) Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674 Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link) Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful: NEIBank collection of ESTs and SAGE data. RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases.
diff --git a/general/datasets/Dodtatrcretblmogene2_1213/contributors.rtf b/general/datasets/Dodtatrcretblmogene2_1213/contributors.rtf
new file mode 100644
index 0000000..11fece2
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_1213/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, XiangDi Wang, Justin P. Templeton and Robert W. Williams.
diff --git a/general/datasets/Dodtatrcretblmogene2_1213/platform.rtf b/general/datasets/Dodtatrcretblmogene2_1213/platform.rtf
new file mode 100644
index 0000000..19fc38c
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_1213/platform.rtf
@@ -0,0 +1 @@
+The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/Dodtatrcretblmogene2_1213/processing.rtf b/general/datasets/Dodtatrcretblmogene2_1213/processing.rtf
new file mode 100644
index 0000000..a7b767e
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_1213/processing.rtf
@@ -0,0 +1 @@
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Dodtatrcretblmogene2_1213/summary.rtf b/general/datasets/Dodtatrcretblmogene2_1213/summary.rtf
new file mode 100644
index 0000000..96a87e5
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_1213/summary.rtf
@@ -0,0 +1 @@
+The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/Dodtatrcretblmogene2_1213/tissue.rtf b/general/datasets/Dodtatrcretblmogene2_1213/tissue.rtf
new file mode 100644
index 0000000..056d7eb
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2_1213/tissue.rtf
@@ -0,0 +1 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/Dodtatrcretblmogene2e_0316/acknowledgment.rtf b/general/datasets/Dodtatrcretblmogene2e_0316/acknowledgment.rtf
new file mode 100644
index 0000000..13c6b1e
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2e_0316/acknowledgment.rtf
@@ -0,0 +1 @@
+DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/Dodtatrcretblmogene2e_0316/cases.rtf b/general/datasets/Dodtatrcretblmogene2e_0316/cases.rtf
new file mode 100644
index 0000000..6b36c70
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2e_0316/cases.rtf
@@ -0,0 +1,1728 @@
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+
+
+
+
+
+ | Index |
+ EIGC ID (LIMS ID) |
+ Strain |
+ Sex |
+ Age at harvest |
+ RIN Score |
+
+
+ | 1 |
+ 602 |
+ BXD9 |
+ F |
+ 133 |
+ 9.1 |
+
+
+ | 2 |
+ 603 |
+ BXD9 |
+ M |
+ 100 |
+ 9.5 |
+
+
+ | 3 |
+ 604 |
+ BXD40 |
+ F |
+ 100 |
+ 9.4 |
+
+
+ | 4 |
+ 605 |
+ BXD40 |
+ M |
+ 100 |
+ 9.1 |
+
+
+ | 5 |
+ 606 |
+ BXD48 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 6 |
+ 607 |
+ BXD48 |
+ M |
+ 75 |
+ 8.6 |
+
+
+ | 7 |
+ 608 |
+ BXD63 |
+ F |
+ 75 |
+ 9.2 |
+
+
+ | 8 |
+ 609 |
+ BXD63 |
+ M |
+ 61 |
+ 9.4 |
+
+
+ | 9 |
+ 612 |
+ BXD73 |
+ M |
+ 108 |
+ 10 |
+
+
+ | 10 |
+ 614 |
+ BXD87 |
+ M |
+ 85 |
+ 9.2 |
+
+
+ | 11 |
+ 615 |
+ BXD87 |
+ F |
+ 85 |
+ 9.9 |
+
+
+ | 12 |
+ 616 |
+ BXD69 |
+ F |
+ 76 |
+ 9.3 |
+
+
+ | 13 |
+ 617 |
+ BXD69 |
+ M |
+ 100 |
+ 10 |
+
+
+ | 14 |
+ 618 |
+ BXD51 |
+ M |
+ 82 |
+ 8.9 |
+
+
+ | 15 |
+ 619 |
+ BXD92 (BXD65b) |
+ M |
+ 82 |
+ 8.8 |
+
+
+ | 16 |
+ 620 |
+ BXD92 (BXD65b) |
+ F |
+ 82 |
+ 8.8 |
+
+
+ | 17 |
+ 635 |
+ BXD100 |
+ M |
+ 70 |
+ 9 |
+
+
+ | 18 |
+ 636 |
+ BXD100 |
+ M |
+ 70 |
+ 8.8 |
+
+
+ | 19 |
+ 652 |
+ BXD92 (BXD65b) |
+ F |
+ 64 |
+ 9 |
+
+
+ | 20 |
+ 653 |
+ BXD87 |
+ F |
+ 67 |
+ 9.7 |
+
+
+ | 21 |
+ 654 |
+ BXD87 |
+ M |
+ 67 |
+ 8.9 |
+
+
+ | 22 |
+ 655 |
+ BXD63 |
+ M |
+ 71 |
+ 9 |
+
+
+ | 23 |
+ 660 |
+ BXD69 |
+ M |
+ 97 |
+ 10 |
+
+
+ | 24 |
+ 687 |
+ BXD6 |
+ M |
+ 85 |
+ 7.7 |
+
+
+ | 25 |
+ 688 |
+ BXD6 |
+ M |
+ 85 |
+ 9.4 |
+
+
+ | 26 |
+ 690 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 27 |
+ 691 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 28 |
+ 692 |
+ BXD12 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 29 |
+ 695 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 30 |
+ 696 |
+ BXD5 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 31 |
+ 698 |
+ BXD5 |
+ F |
+ 77 |
+ 9.9 |
+
+
+ | 32 |
+ 699 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 33 |
+ 701 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 34 |
+ 702 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 35 |
+ 705 |
+ BXD8 |
+ F |
+ 77 |
+ 9.2 |
+
+
+ | 36 |
+ 707 |
+ BXD15 |
+ F |
+ 77 |
+ 9.4 |
+
+
+ | 37 |
+ 708 |
+ BXD15 |
+ F |
+ 77 |
+ 9.1 |
+
+
+ | 38 |
+ 710 |
+ BXD15 |
+ M |
+ 77 |
+ 9.1 |
+
+
+ | 39 |
+ 713 |
+ BXD22 |
+ F |
+ 71 |
+ 9.5 |
+
+
+ | 40 |
+ 714 |
+ BXD22 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 41 |
+ 716 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 42 |
+ 717 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 43 |
+ 719 |
+ BXD14 |
+ F |
+ 70 |
+ 9.2 |
+
+
+ | 44 |
+ 722 |
+ BXD14 |
+ M |
+ 70 |
+ 8.9 |
+
+
+ | 45 |
+ 723 |
+ BXD14 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 46 |
+ 725 |
+ BXD18 |
+ F |
+ 70 |
+ 9 |
+
+
+ | 47 |
+ 726 |
+ BXD18 |
+ F |
+ 70 |
+ 9.1 |
+
+
+ | 48 |
+ 728 |
+ BXD18 |
+ M |
+ 70 |
+ 9.1 |
+
+
+ | 49 |
+ 729 |
+ BXD18 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 50 |
+ 731 |
+ BXD19 |
+ F |
+ 66 |
+ 9.3 |
+
+
+ | 51 |
+ 732 |
+ BXD19 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 52 |
+ 734 |
+ BXD19 |
+ M |
+ 66 |
+ 9.8 |
+
+
+ | 53 |
+ 735 |
+ BXD19 |
+ M |
+ 66 |
+ 9.4 |
+
+
+ | 54 |
+ 737 |
+ BXD21 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 55 |
+ 738 |
+ BXD21 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 56 |
+ 740 |
+ BXD21 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 57 |
+ 741 |
+ BXD21 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 58 |
+ 743 |
+ BXD2 |
+ F |
+ 70 |
+ 8.3 |
+
+
+ | 59 |
+ 744 |
+ BXD2 |
+ F |
+ 70 |
+ 8.6 |
+
+
+ | 60 |
+ 746 |
+ BXD2 |
+ M |
+ 70 |
+ 7.5 |
+
+
+ | 61 |
+ 747 |
+ BXD2 |
+ M |
+ 77 |
+ 8.6 |
+
+
+ | 62 |
+ 768 |
+ BXD48 |
+ M |
+ 121 |
+ 9.4 |
+
+
+ | 63 |
+ 770 |
+ BXD92 (BXD65b) |
+ M |
+ 65 |
+ 10 |
+
+
+ | 64 |
+ 771 |
+ BXD101 |
+ F |
+ 85 |
+ 8.3 |
+
+
+ | 65 |
+ 772 |
+ BXD101 |
+ F |
+ 85 |
+ 9.3 |
+
+
+ | 66 |
+ 773 |
+ BXD101 |
+ M |
+ 86 |
+ 9.5 |
+
+
+ | 67 |
+ 774 |
+ BXD101 |
+ M |
+ 86 |
+ 9.8 |
+
+
+ | 68 |
+ 775 |
+ BXD102 |
+ F |
+ 66 |
+ 9.5 |
+
+
+ | 69 |
+ 776 |
+ BXD102 |
+ F |
+ 66 |
+ 10 |
+
+
+ | 70 |
+ 777 |
+ BXD102 |
+ M |
+ 84 |
+ 9.6 |
+
+
+ | 71 |
+ 787 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 72 |
+ 788 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 73 |
+ 789 |
+ BXD63 |
+ F |
+ 115 |
+ 9.7 |
+
+
+ | 74 |
+ 790 |
+ BXD100 |
+ F |
+ 72 |
+ 9.8 |
+
+
+ | 75 |
+ 791 |
+ BXD100 |
+ F |
+ 72 |
+ 10 |
+
+
+ | 76 |
+ 818 |
+ BXD51 |
+ F |
+ 77 |
+ 9.7 |
+
+
+ | 77 |
+ 819 |
+ BXD51 |
+ F |
+ 77 |
+ 9.6 |
+
+
+ | 78 |
+ 820 |
+ BXD51 |
+ M |
+ 72 |
+ 9.7 |
+
+
+ | 79 |
+ 821 |
+ BXD65 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 80 |
+ 822 |
+ BXD65 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 81 |
+ 825 |
+ BXD65 |
+ F |
+ 72 |
+ 9.5 |
+
+
+ | 82 |
+ 827 |
+ BXD86 |
+ M |
+ 69 |
+ 9.1 |
+
+
+ | 83 |
+ 828 |
+ BXD86 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 84 |
+ 829 |
+ BXD90 |
+ F |
+ 69 |
+ 9.6 |
+
+
+ | 85 |
+ 831 |
+ BXD9 |
+ M |
+ 127 |
+ 9.7 |
+
+
+ | 86 |
+ 832 |
+ BXD39 |
+ F |
+ 99 |
+ 9.4 |
+
+
+ | 87 |
+ 833 |
+ BXD39 |
+ F |
+ 107 |
+ 9.3 |
+
+
+ | 88 |
+ 834 |
+ BXD60 |
+ F |
+ 107 |
+ 9.5 |
+
+
+ | 89 |
+ 836 |
+ BXD84 |
+ M |
+ 103 |
+ 9.7 |
+
+
+ | 90 |
+ 846 |
+ BXD39 |
+ M |
+ 63 |
+ 9.7 |
+
+
+ | 91 |
+ 847 |
+ BXD39 |
+ M |
+ 63 |
+ 9.8 |
+
+
+ | 92 |
+ 849 |
+ BXD20 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 93 |
+ 850 |
+ BXD20 |
+ M |
+ 70 |
+ 10 |
+
+
+ | 94 |
+ 851 |
+ BXD20 |
+ * |
+ 70 |
+ 9.5 |
+
+
+ | 95 |
+ 855 |
+ DBA/2J |
+ F |
+ 78 |
+ 9.7 |
+
+
+ | 96 |
+ 856 |
+ DBA/2J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 97 |
+ 857 |
+ DBA/2J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 98 |
+ 858 |
+ DBA/2J |
+ M |
+ 78 |
+ 9.9 |
+
+
+ | 99 |
+ 859 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 100 |
+ 860 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 101 |
+ 861 |
+ C57BL/6J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 102 |
+ 862 |
+ C57BL/6J |
+ M |
+ 78 |
+ 9.6 |
+
+
+ | 103 |
+ EGE10907-0172_890_20844 |
+ BXD28 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 104 |
+ EGE10907-0173_891_20845 |
+ BXD28 |
+ M |
+ 75 |
+ 9.7 |
+
+
+ | 105 |
+ EGE10907-0174_892_20846 |
+ BXD28 |
+ F |
+ 75 |
+ 9.7 |
+
+
+ | 106 |
+ EGE10907-0176_895_20848 |
+ BXD33 |
+ M |
+ 75 |
+ 9.88 |
+
+
+ | 107 |
+ EGE10907-0177_896_20849 |
+ BXD33 |
+ F |
+ 75 |
+ 10 |
+
+
+ | 108 |
+ EGE10907-0178_897_20850 |
+ BXD33 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 109 |
+ EGE10907-0179_898_20851 |
+ BXD36 |
+ M |
+ 75 |
+ 9.4 |
+
+
+ | 110 |
+ EGE10907-0180_899_20852 |
+ BXD36 |
+ F |
+ 75 |
+ 9.5 |
+
+
+ | 111 |
+ EGE10907-0181_900_20853 |
+ BXD36 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 112 |
+ EGE10907-0182_910_20854 |
+ BXD27 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 113 |
+ EGE10907-0183_990_20855 |
+ BXD9 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 114 |
+ EGE10907-0184_991_20856 |
+ BXD16 |
+ F |
+ 113 |
+ 10 |
+
+
+ | 115 |
+ EGE10907-0185_992_20857 |
+ BXD16 |
+ M |
+ 113 |
+ 9 |
+
+
+ | 116 |
+ EGE10907-0186_993_20858 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 117 |
+ EGE10907-0187_994_20859 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 118 |
+ EGE10907-0188_996_20860 |
+ BXD48 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 119 |
+ EGE10907-0189_997_20861 |
+ BXD73 |
+ M |
+ 106 |
+ 10 |
+
+
+ | 120 |
+ EGE10907-0190_999_20862 |
+ BXD11 |
+ F |
+ 121 |
+ 9.6 |
+
+
+ | 121 |
+ EGE10907-0191_100_20863 |
+ BXD11 |
+ F |
+ 121 |
+ 9.9 |
+
+
+ | 122 |
+ EGE10907-0192_1010_21276 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 123 |
+ EGE10907-0193_1011_21277 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 124 |
+ EGE10907-0194_1012_21278 |
+ BXD16 |
+ F |
+ 65 |
+ 10 |
+
+
+ | 125 |
+ EGE10907-0195_1015_21279 |
+ BXD16 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 126 |
+ EGE10907-0196_1019_21280 |
+ BXD33 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 127 |
+ EGE10907-0197_1020_21281 |
+ BXD36 |
+ M |
+ 78 |
+ 10 |
+
+
+ | 128 |
+ EGE10907-0198_1021_21282 |
+ BXD38 |
+ F |
+ 70 |
+ 9.8 |
+
+
+ | 129 |
+ EGE10907-0199_1022_21283 |
+ BXD38 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 130 |
+ EGE10907-0200_1023_21284 |
+ BXD38 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 131 |
+ EGE10907-0201_1047_21285 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 132 |
+ EGE10907-0202_1048_21286 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 133 |
+ EGE10907-0203_1049_21287 |
+ BXD38 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 134 |
+ EGE10907-0204_1050_21288 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 135 |
+ EGE10907-0205_1051_21289 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 136 |
+ EGE10907-0206_1052_21290 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 137 |
+ EGE10907-0207_1053_21291 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 138 |
+ EGE10907-0208_1054_21292 |
+ BXD90 |
+ F |
+ 71 |
+ 10 |
+
+
+ | 139 |
+ EGE10907-0209_1055_21293 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 140 |
+ EGE10907-0210_1056_21294 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 141 |
+ EGE10907-0211_1148_21295 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 142 |
+ EGE10907-0212_1149_21296 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 143 |
+ EGE10907-0213_1150_21297 |
+ BXD31 |
+ M |
+ 90 |
+ 10 |
+
+
+ | 144 |
+ EGE10907-0214_1151_21298 |
+ BXD31 |
+ M |
+ 90 |
+ 9.9 |
+
+
+ | 145 |
+ EGE10907-0215_1152_21299 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 146 |
+ EGE10907-0216_21429 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 147 |
+ EGE10907-0217_21430 |
+ BXD42 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 148 |
+ EGE10907-0218_21431 |
+ BXD42 |
+ M |
+ 83 |
+ 9.3 |
+
+
+ | 149 |
+ EGE10907-0219_21432 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 150 |
+ EGE10907-0220_21433 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 151 |
+ EGE10907-0221_21434 |
+ BXD50 |
+ F |
+ 92 |
+ 10 |
+
+
+ | 152 |
+ EGE10907-0222_21435 |
+ BXD1 |
+ M |
+ 73 |
+ 9.6 |
+
+
+ | 153 |
+ EGE10907-0223_21436 |
+ BXD13 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 154 |
+ EGE10907-0224_21437 |
+ BXD1 |
+ M |
+ 71 |
+ 9.5 |
+
+
+ | 155 |
+ EGE10907-0225_21438 |
+ BXD13 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 156 |
+ EGE10907-0226_21439 |
+ BXD43 |
+ F |
+ 85 |
+ 10 |
+
+
+ | 157 |
+ EGE10907-0227_21452 |
+ BXD43 |
+ F |
+ 85 |
+ 9.6 |
+
+
+ | 158 |
+ EGE10907-0229_21442 |
+ BXD43 |
+ M |
+ 85 |
+ 8.2 |
+
+
+ | 159 |
+ EGE10907-0230_21443 |
+ BXD50 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 160 |
+ EGE10907-0231_21444 |
+ BXD1 |
+ F |
+ 68 |
+ 9.4 |
+
+
+ | 161 |
+ EGE10907-0232_21445 |
+ BXD1 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 162 |
+ EGE10907-0233_21446 |
+ BXD29 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 163 |
+ EGE10907-0234_21447 |
+ BXD29 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 164 |
+ EGE10907-0235_21448 |
+ BXD75 |
+ F |
+ 68 |
+ 10 |
+
+
+ | 165 |
+ EGE10907-0236_21449 |
+ BXD75 |
+ M |
+ 68 |
+ 10 |
+
+
+ | 166 |
+ EGE10907-0237_21450 |
+ BXD96 |
+ F |
+ 67 |
+ 9.9 |
+
+
+ | 167 |
+ EGE10907-0238_21931 |
+ BXD99 |
+ M |
+ 71 |
+ 7.9 |
+
+
+ | 168 |
+ EGE10907-0239_21932 |
+ BXD99 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 169 |
+ EGE10907-0240_21933 |
+ BXD67 |
+ F |
+ 68 |
+ 8.8 |
+
+
+ | 170 |
+ EGE10907-0241_21934 |
+ BXD67 |
+ F |
+ 68 |
+ 8.5 |
+
+
+ | 171 |
+ EGE10907-0242_21935 |
+ BXD67 |
+ M |
+ 68 |
+ 9.5 |
+
+
+ | 172 |
+ EGE10907-0243_21936 |
+ BXD67 |
+ M |
+ 68 |
+ 9.6 |
+
+
+ | 173 |
+ EGE10907-0244_21937 |
+ BXD6 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 174 |
+ EGE10907-0245_21938 |
+ BXD12 |
+ M |
+ 82 |
+ 9.5 |
+
+
+ | 175 |
+ EGE10907-0246_21939 |
+ BXD60 |
+ F |
+ 72 |
+ 9.6 |
+
+
+ | 176 |
+ EGE10907-0247_21940 |
+ BXD65 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 177 |
+ EGE10907-0248_21941 |
+ BXD75 |
+ F |
+ 69 |
+ 8.8 |
+
+
+ | 178 |
+ EGE10907-0249_21942_(MoGene-2_0-st) |
+ BXD75 |
+ M |
+ 69 |
+ 9.2 |
+
+
+ | 179 |
+ EGE10907-0250_21943 |
+ BXD8 |
+ F |
+ 97 |
+ 9.1 |
+
+
+ | 180 |
+ EGE10907-0251_21944 |
+ BXD85 |
+ F |
+ 79 |
+ 8.6 |
+
+
+ | 181 |
+ EGE10907-0252_21945 |
+ BXD85 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 182 |
+ EGE10907-0253_21946 |
+ BXD85 |
+ M |
+ 79 |
+ 9.4 |
+
+
+ | 183 |
+ EGE10907-0254_21947 |
+ BXD102 |
+ M |
+ 94 |
+ 8.6 |
+
+
+ | 184 |
+ EGE10907-0255_21948 |
+ BXD99 |
+ F |
+ 83 |
+ 9 |
+
+
+ | 185 |
+ EGE10907-0256_21949 |
+ BXD69 |
+ F |
+ 68 |
+ 9 |
+
+
+ | 186 |
+ EGE10907-0257_21950 |
+ BXD84 |
+ F |
+ 74 |
+ 9.5 |
+
+
+ | 187 |
+ EGE10907-0258_21951 |
+ BXD84 |
+ F |
+ 74 |
+ 9.4 |
+
+
+ | 188 |
+ EGE10907-0259_21952 |
+ BXD84 |
+ M |
+ 74 |
+ 8.6 |
+
+
+ | 189 |
+ EGE10907-0260_21451 |
+ BXD96 |
+ M |
+ 67 |
+ 9.2 |
+
+
+ | 190 |
+ EGE10907-0261_21452 |
+ BXD99 |
+ F |
+ 71 |
+ 8.9 |
+
+
+ | 191 |
+ EGE10907-0262_21931 |
+ BXD6 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 192 |
+ EGE10907-0263_21932 |
+ BXD14 |
+ F |
+ 69 |
+ 8.5 |
+
+
+ | 193 |
+ EGE10907-0264_21933 |
+ BXD34 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 194 |
+ EGE10907-0265_21934 |
+ BXD34 |
+ M |
+ 79 |
+ 9.9 |
+
+
+ | 195 |
+ EGE10907-0266_21935 |
+ BXD40 |
+ F |
+ 75 |
+ 9.6 |
+
+
+ | 196 |
+ EGE10907-0267_21936 |
+ BXD40 |
+ M |
+ 78 |
+ 9.7 |
+
+
+ | 197 |
+ EGE10907-0268_21937 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 198 |
+ EGE10907-0269_21938 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 199 |
+ EGE10907-0270_21939 |
+ BXD56 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 200 |
+ EGE10907-0271_21940 |
+ BXD56 |
+ M |
+ 72 |
+ 9.4 |
+
+
+ | 201 |
+ EGE10907-0272_21941 |
+ BXD71 |
+ F |
+ 72 |
+ 9.9 |
+
+
+ | 202 |
+ EGE10907-0273_21942 |
+ BXD71 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 203 |
+ EGE10907-0274_21943 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 204 |
+ EGE10907-0275_21944 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 205 |
+ EGE10907-0276_21945 |
+ BXD27 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 206 |
+ EGE10907-0277_21946 |
+ BXD15 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 207 |
+ EGE10907-0278_21947 |
+ BXD20 |
+ F |
+ 125 |
+ 10 |
+
+
+ | 208 |
+ EGE10907-0279_21948 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 209 |
+ EGE10907-0280_21949 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 210 |
+ EGE10907-0281_21950 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 211 |
+ EGE10907-0282_21951 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 212 |
+ EGE10907-0283_21952 |
+ BXD85 |
+ F |
+ 87 |
+ 10 |
+
+
+ | 213 |
+ EGE10907-0284_21451 |
+ BXD43 |
+ M |
+ 75 |
+ 9.8 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Dodtatrcretblmogene2e_0316/citation.rtf b/general/datasets/Dodtatrcretblmogene2e_0316/citation.rtf
new file mode 100644
index 0000000..d84717d
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2e_0316/citation.rtf
@@ -0,0 +1,3 @@
+Related Publications: Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link) Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674 Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link) Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful: NEIBank collection of ESTs and SAGE data. RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases.
diff --git a/general/datasets/Dodtatrcretblmogene2e_0316/contributors.rtf b/general/datasets/Dodtatrcretblmogene2e_0316/contributors.rtf
new file mode 100644
index 0000000..11fece2
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2e_0316/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, XiangDi Wang, Justin P. Templeton and Robert W. Williams.
diff --git a/general/datasets/Dodtatrcretblmogene2e_0316/platform.rtf b/general/datasets/Dodtatrcretblmogene2e_0316/platform.rtf
new file mode 100644
index 0000000..19fc38c
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2e_0316/platform.rtf
@@ -0,0 +1 @@
+The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/Dodtatrcretblmogene2e_0316/processing.rtf b/general/datasets/Dodtatrcretblmogene2e_0316/processing.rtf
new file mode 100644
index 0000000..a7b767e
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2e_0316/processing.rtf
@@ -0,0 +1 @@
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Dodtatrcretblmogene2e_0316/summary.rtf b/general/datasets/Dodtatrcretblmogene2e_0316/summary.rtf
new file mode 100644
index 0000000..96a87e5
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2e_0316/summary.rtf
@@ -0,0 +1 @@
+The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/Dodtatrcretblmogene2e_0316/tissue.rtf b/general/datasets/Dodtatrcretblmogene2e_0316/tissue.rtf
new file mode 100644
index 0000000..056d7eb
--- /dev/null
+++ b/general/datasets/Dodtatrcretblmogene2e_0316/tissue.rtf
@@ -0,0 +1 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/Dodtatrcretexmogene2_0315/cases.rtf b/general/datasets/Dodtatrcretexmogene2_0315/cases.rtf
new file mode 100644
index 0000000..34f9530
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_0315/cases.rtf
@@ -0,0 +1,9 @@
+Almost all animals are young adults between 60 and 100 days of age (Table 1, minimum age is 60 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
+
+BXD strains:
+
+
+ - The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s.
+ - In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset.
+ - The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
diff --git a/general/datasets/Dodtatrcretexmogene2_0315/contributors.rtf b/general/datasets/Dodtatrcretexmogene2_0315/contributors.rtf
new file mode 100644
index 0000000..814bf91
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_0315/contributors.rtf
@@ -0,0 +1,9 @@
+Other Related Publications
+
+
+ - Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link)
+ - Freeman NE, Templeton JP, Orr WE, Lu L, Williams RW, Geisert EE (2011) Genetic networks in the mouse retina: Growth Associated Protein 43 and Phosphate Tensin Homology network. Molecular Vision 17:1355-1372.
+ - Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674
+ - Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link)
+ - Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.(Link)
+
diff --git a/general/datasets/Dodtatrcretexmogene2_0315/experiment-design.rtf b/general/datasets/Dodtatrcretexmogene2_0315/experiment-design.rtf
new file mode 100644
index 0000000..b43e509
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_0315/experiment-design.rtf
@@ -0,0 +1,3 @@
+Sample Processing: Dr. XiangDi Wang (UTHSC) and Becky King (Emory) were involved in the retinal extractions and isolation of RNA. The Affymetrix arrays were run by two different research cores: the Molecular Resource Center at UTHSC (Dr. William Taylor Director) and the Integrated Genomics Core at Emory University by Robert B Isett (Dr. Michael E. Zwick, Director). In a separate set of experiments we could not detect any significant difference in the arrays run at UTHSC or at Emory University.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Dodtatrcretexmogene2_0315/notes.rtf b/general/datasets/Dodtatrcretexmogene2_0315/notes.rtf
new file mode 100644
index 0000000..cb14c74
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_0315/notes.rtf
@@ -0,0 +1,10 @@
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
diff --git a/general/datasets/Dodtatrcretexmogene2_0315/platform.rtf b/general/datasets/Dodtatrcretexmogene2_0315/platform.rtf
new file mode 100644
index 0000000..cb5e1b8
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_0315/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Gene 2.0 ST Array: These expression arrays have been designed with a median of 22 unique probes per transcript. Each unique probe is 25 bases in length, which means that the array measures a median of 550 bases per transcript. The arrays provide comprehensive transcriptome coverage with over 30,000 coding and non-coding transcripts. In addition there is coverage for 592 microRNAs. For some arrays the RNA was pooled from two retinas and for other arrays were run on a single retina.
diff --git a/general/datasets/Dodtatrcretexmogene2_0315/summary.rtf b/general/datasets/Dodtatrcretexmogene2_0315/summary.rtf
new file mode 100644
index 0000000..b6cf222
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_0315/summary.rtf
@@ -0,0 +1,5 @@
+DoD TATRC Retina Dataset Affymetrix MouseGene 2.0 ST Array (____ 2015) RMA analysis and scaling by Arthur Centeno. This data set consists of 75 BXD strains, C57BL/6J, DBA/2J, both reciprocal F1s, and BALB/cByJ. A total of 80 strains were quantified. The data are now open and available for analysis.
+
+This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strain was computed as the mean of four samples per strain. Expression values on a log2 scale range from 6.25 to 18.08 (11.83 units), a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
+
+The lowest level of expression is 6.254 for ILMN_2747167 (Arhgap11a) from HEI Retina Illumina V6.2 (April 2010) RankInv **. Lowest single data about 5.842. The highest level of expression is 18.077 for ILMN_2516699 (Ubb). Highest single value is about 18.934.
diff --git a/general/datasets/Dodtatrcretexmogene2_0315/tissue.rtf b/general/datasets/Dodtatrcretexmogene2_0315/tissue.rtf
new file mode 100644
index 0000000..87eb144
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_0315/tissue.rtf
@@ -0,0 +1,13 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in 1 ml of 160 U/ml Ribolock for 1 min at room temperature. Dissecting and preparing eyes for RNA extraction Retinas for RNA removed from the eye and placed in Hank’s Balanced Salt solution with RiboLock (Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) and processed per manufacturer’s instructions (in brief form below).
+
+1) Sample collection for RNA isolation.
+
+2) Quickly remove the retinas with clean curved forceps after cervical dislocation of the mouse.
+
+3) Put each retina in 1 ml of 160 U/ml Ribolock for 1 min in RT.
+
+4) Move the retina to another tube with 50µl Ribolock, store in -80°C.
+
+5) The RNA was isolated using a QiaCube and the in column DNAse procedure.
+
+Quality Control: All RNA samples were checked for quality before running microarrays. The samples were analyzed using the Agilent 2100 Bioanalyzer. The RNA integrity values for each sample are presented in Table 1 below.
diff --git a/general/datasets/Dodtatrcretexmogene2_1313/acknowledgment.rtf b/general/datasets/Dodtatrcretexmogene2_1313/acknowledgment.rtf
new file mode 100644
index 0000000..13c6b1e
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_1313/acknowledgment.rtf
@@ -0,0 +1 @@
+DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/Dodtatrcretexmogene2_1313/cases.rtf b/general/datasets/Dodtatrcretexmogene2_1313/cases.rtf
new file mode 100644
index 0000000..6b36c70
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_1313/cases.rtf
@@ -0,0 +1,1728 @@
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+
+
+
+
+
+ | Index |
+ EIGC ID (LIMS ID) |
+ Strain |
+ Sex |
+ Age at harvest |
+ RIN Score |
+
+
+ | 1 |
+ 602 |
+ BXD9 |
+ F |
+ 133 |
+ 9.1 |
+
+
+ | 2 |
+ 603 |
+ BXD9 |
+ M |
+ 100 |
+ 9.5 |
+
+
+ | 3 |
+ 604 |
+ BXD40 |
+ F |
+ 100 |
+ 9.4 |
+
+
+ | 4 |
+ 605 |
+ BXD40 |
+ M |
+ 100 |
+ 9.1 |
+
+
+ | 5 |
+ 606 |
+ BXD48 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 6 |
+ 607 |
+ BXD48 |
+ M |
+ 75 |
+ 8.6 |
+
+
+ | 7 |
+ 608 |
+ BXD63 |
+ F |
+ 75 |
+ 9.2 |
+
+
+ | 8 |
+ 609 |
+ BXD63 |
+ M |
+ 61 |
+ 9.4 |
+
+
+ | 9 |
+ 612 |
+ BXD73 |
+ M |
+ 108 |
+ 10 |
+
+
+ | 10 |
+ 614 |
+ BXD87 |
+ M |
+ 85 |
+ 9.2 |
+
+
+ | 11 |
+ 615 |
+ BXD87 |
+ F |
+ 85 |
+ 9.9 |
+
+
+ | 12 |
+ 616 |
+ BXD69 |
+ F |
+ 76 |
+ 9.3 |
+
+
+ | 13 |
+ 617 |
+ BXD69 |
+ M |
+ 100 |
+ 10 |
+
+
+ | 14 |
+ 618 |
+ BXD51 |
+ M |
+ 82 |
+ 8.9 |
+
+
+ | 15 |
+ 619 |
+ BXD92 (BXD65b) |
+ M |
+ 82 |
+ 8.8 |
+
+
+ | 16 |
+ 620 |
+ BXD92 (BXD65b) |
+ F |
+ 82 |
+ 8.8 |
+
+
+ | 17 |
+ 635 |
+ BXD100 |
+ M |
+ 70 |
+ 9 |
+
+
+ | 18 |
+ 636 |
+ BXD100 |
+ M |
+ 70 |
+ 8.8 |
+
+
+ | 19 |
+ 652 |
+ BXD92 (BXD65b) |
+ F |
+ 64 |
+ 9 |
+
+
+ | 20 |
+ 653 |
+ BXD87 |
+ F |
+ 67 |
+ 9.7 |
+
+
+ | 21 |
+ 654 |
+ BXD87 |
+ M |
+ 67 |
+ 8.9 |
+
+
+ | 22 |
+ 655 |
+ BXD63 |
+ M |
+ 71 |
+ 9 |
+
+
+ | 23 |
+ 660 |
+ BXD69 |
+ M |
+ 97 |
+ 10 |
+
+
+ | 24 |
+ 687 |
+ BXD6 |
+ M |
+ 85 |
+ 7.7 |
+
+
+ | 25 |
+ 688 |
+ BXD6 |
+ M |
+ 85 |
+ 9.4 |
+
+
+ | 26 |
+ 690 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 27 |
+ 691 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 28 |
+ 692 |
+ BXD12 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 29 |
+ 695 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 30 |
+ 696 |
+ BXD5 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 31 |
+ 698 |
+ BXD5 |
+ F |
+ 77 |
+ 9.9 |
+
+
+ | 32 |
+ 699 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 33 |
+ 701 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 34 |
+ 702 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 35 |
+ 705 |
+ BXD8 |
+ F |
+ 77 |
+ 9.2 |
+
+
+ | 36 |
+ 707 |
+ BXD15 |
+ F |
+ 77 |
+ 9.4 |
+
+
+ | 37 |
+ 708 |
+ BXD15 |
+ F |
+ 77 |
+ 9.1 |
+
+
+ | 38 |
+ 710 |
+ BXD15 |
+ M |
+ 77 |
+ 9.1 |
+
+
+ | 39 |
+ 713 |
+ BXD22 |
+ F |
+ 71 |
+ 9.5 |
+
+
+ | 40 |
+ 714 |
+ BXD22 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 41 |
+ 716 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 42 |
+ 717 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 43 |
+ 719 |
+ BXD14 |
+ F |
+ 70 |
+ 9.2 |
+
+
+ | 44 |
+ 722 |
+ BXD14 |
+ M |
+ 70 |
+ 8.9 |
+
+
+ | 45 |
+ 723 |
+ BXD14 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 46 |
+ 725 |
+ BXD18 |
+ F |
+ 70 |
+ 9 |
+
+
+ | 47 |
+ 726 |
+ BXD18 |
+ F |
+ 70 |
+ 9.1 |
+
+
+ | 48 |
+ 728 |
+ BXD18 |
+ M |
+ 70 |
+ 9.1 |
+
+
+ | 49 |
+ 729 |
+ BXD18 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 50 |
+ 731 |
+ BXD19 |
+ F |
+ 66 |
+ 9.3 |
+
+
+ | 51 |
+ 732 |
+ BXD19 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 52 |
+ 734 |
+ BXD19 |
+ M |
+ 66 |
+ 9.8 |
+
+
+ | 53 |
+ 735 |
+ BXD19 |
+ M |
+ 66 |
+ 9.4 |
+
+
+ | 54 |
+ 737 |
+ BXD21 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 55 |
+ 738 |
+ BXD21 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 56 |
+ 740 |
+ BXD21 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 57 |
+ 741 |
+ BXD21 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 58 |
+ 743 |
+ BXD2 |
+ F |
+ 70 |
+ 8.3 |
+
+
+ | 59 |
+ 744 |
+ BXD2 |
+ F |
+ 70 |
+ 8.6 |
+
+
+ | 60 |
+ 746 |
+ BXD2 |
+ M |
+ 70 |
+ 7.5 |
+
+
+ | 61 |
+ 747 |
+ BXD2 |
+ M |
+ 77 |
+ 8.6 |
+
+
+ | 62 |
+ 768 |
+ BXD48 |
+ M |
+ 121 |
+ 9.4 |
+
+
+ | 63 |
+ 770 |
+ BXD92 (BXD65b) |
+ M |
+ 65 |
+ 10 |
+
+
+ | 64 |
+ 771 |
+ BXD101 |
+ F |
+ 85 |
+ 8.3 |
+
+
+ | 65 |
+ 772 |
+ BXD101 |
+ F |
+ 85 |
+ 9.3 |
+
+
+ | 66 |
+ 773 |
+ BXD101 |
+ M |
+ 86 |
+ 9.5 |
+
+
+ | 67 |
+ 774 |
+ BXD101 |
+ M |
+ 86 |
+ 9.8 |
+
+
+ | 68 |
+ 775 |
+ BXD102 |
+ F |
+ 66 |
+ 9.5 |
+
+
+ | 69 |
+ 776 |
+ BXD102 |
+ F |
+ 66 |
+ 10 |
+
+
+ | 70 |
+ 777 |
+ BXD102 |
+ M |
+ 84 |
+ 9.6 |
+
+
+ | 71 |
+ 787 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 72 |
+ 788 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 73 |
+ 789 |
+ BXD63 |
+ F |
+ 115 |
+ 9.7 |
+
+
+ | 74 |
+ 790 |
+ BXD100 |
+ F |
+ 72 |
+ 9.8 |
+
+
+ | 75 |
+ 791 |
+ BXD100 |
+ F |
+ 72 |
+ 10 |
+
+
+ | 76 |
+ 818 |
+ BXD51 |
+ F |
+ 77 |
+ 9.7 |
+
+
+ | 77 |
+ 819 |
+ BXD51 |
+ F |
+ 77 |
+ 9.6 |
+
+
+ | 78 |
+ 820 |
+ BXD51 |
+ M |
+ 72 |
+ 9.7 |
+
+
+ | 79 |
+ 821 |
+ BXD65 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 80 |
+ 822 |
+ BXD65 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 81 |
+ 825 |
+ BXD65 |
+ F |
+ 72 |
+ 9.5 |
+
+
+ | 82 |
+ 827 |
+ BXD86 |
+ M |
+ 69 |
+ 9.1 |
+
+
+ | 83 |
+ 828 |
+ BXD86 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 84 |
+ 829 |
+ BXD90 |
+ F |
+ 69 |
+ 9.6 |
+
+
+ | 85 |
+ 831 |
+ BXD9 |
+ M |
+ 127 |
+ 9.7 |
+
+
+ | 86 |
+ 832 |
+ BXD39 |
+ F |
+ 99 |
+ 9.4 |
+
+
+ | 87 |
+ 833 |
+ BXD39 |
+ F |
+ 107 |
+ 9.3 |
+
+
+ | 88 |
+ 834 |
+ BXD60 |
+ F |
+ 107 |
+ 9.5 |
+
+
+ | 89 |
+ 836 |
+ BXD84 |
+ M |
+ 103 |
+ 9.7 |
+
+
+ | 90 |
+ 846 |
+ BXD39 |
+ M |
+ 63 |
+ 9.7 |
+
+
+ | 91 |
+ 847 |
+ BXD39 |
+ M |
+ 63 |
+ 9.8 |
+
+
+ | 92 |
+ 849 |
+ BXD20 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 93 |
+ 850 |
+ BXD20 |
+ M |
+ 70 |
+ 10 |
+
+
+ | 94 |
+ 851 |
+ BXD20 |
+ * |
+ 70 |
+ 9.5 |
+
+
+ | 95 |
+ 855 |
+ DBA/2J |
+ F |
+ 78 |
+ 9.7 |
+
+
+ | 96 |
+ 856 |
+ DBA/2J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 97 |
+ 857 |
+ DBA/2J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 98 |
+ 858 |
+ DBA/2J |
+ M |
+ 78 |
+ 9.9 |
+
+
+ | 99 |
+ 859 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 100 |
+ 860 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 101 |
+ 861 |
+ C57BL/6J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 102 |
+ 862 |
+ C57BL/6J |
+ M |
+ 78 |
+ 9.6 |
+
+
+ | 103 |
+ EGE10907-0172_890_20844 |
+ BXD28 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 104 |
+ EGE10907-0173_891_20845 |
+ BXD28 |
+ M |
+ 75 |
+ 9.7 |
+
+
+ | 105 |
+ EGE10907-0174_892_20846 |
+ BXD28 |
+ F |
+ 75 |
+ 9.7 |
+
+
+ | 106 |
+ EGE10907-0176_895_20848 |
+ BXD33 |
+ M |
+ 75 |
+ 9.88 |
+
+
+ | 107 |
+ EGE10907-0177_896_20849 |
+ BXD33 |
+ F |
+ 75 |
+ 10 |
+
+
+ | 108 |
+ EGE10907-0178_897_20850 |
+ BXD33 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 109 |
+ EGE10907-0179_898_20851 |
+ BXD36 |
+ M |
+ 75 |
+ 9.4 |
+
+
+ | 110 |
+ EGE10907-0180_899_20852 |
+ BXD36 |
+ F |
+ 75 |
+ 9.5 |
+
+
+ | 111 |
+ EGE10907-0181_900_20853 |
+ BXD36 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 112 |
+ EGE10907-0182_910_20854 |
+ BXD27 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 113 |
+ EGE10907-0183_990_20855 |
+ BXD9 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 114 |
+ EGE10907-0184_991_20856 |
+ BXD16 |
+ F |
+ 113 |
+ 10 |
+
+
+ | 115 |
+ EGE10907-0185_992_20857 |
+ BXD16 |
+ M |
+ 113 |
+ 9 |
+
+
+ | 116 |
+ EGE10907-0186_993_20858 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 117 |
+ EGE10907-0187_994_20859 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 118 |
+ EGE10907-0188_996_20860 |
+ BXD48 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 119 |
+ EGE10907-0189_997_20861 |
+ BXD73 |
+ M |
+ 106 |
+ 10 |
+
+
+ | 120 |
+ EGE10907-0190_999_20862 |
+ BXD11 |
+ F |
+ 121 |
+ 9.6 |
+
+
+ | 121 |
+ EGE10907-0191_100_20863 |
+ BXD11 |
+ F |
+ 121 |
+ 9.9 |
+
+
+ | 122 |
+ EGE10907-0192_1010_21276 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 123 |
+ EGE10907-0193_1011_21277 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 124 |
+ EGE10907-0194_1012_21278 |
+ BXD16 |
+ F |
+ 65 |
+ 10 |
+
+
+ | 125 |
+ EGE10907-0195_1015_21279 |
+ BXD16 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 126 |
+ EGE10907-0196_1019_21280 |
+ BXD33 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 127 |
+ EGE10907-0197_1020_21281 |
+ BXD36 |
+ M |
+ 78 |
+ 10 |
+
+
+ | 128 |
+ EGE10907-0198_1021_21282 |
+ BXD38 |
+ F |
+ 70 |
+ 9.8 |
+
+
+ | 129 |
+ EGE10907-0199_1022_21283 |
+ BXD38 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 130 |
+ EGE10907-0200_1023_21284 |
+ BXD38 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 131 |
+ EGE10907-0201_1047_21285 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 132 |
+ EGE10907-0202_1048_21286 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 133 |
+ EGE10907-0203_1049_21287 |
+ BXD38 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 134 |
+ EGE10907-0204_1050_21288 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 135 |
+ EGE10907-0205_1051_21289 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 136 |
+ EGE10907-0206_1052_21290 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 137 |
+ EGE10907-0207_1053_21291 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 138 |
+ EGE10907-0208_1054_21292 |
+ BXD90 |
+ F |
+ 71 |
+ 10 |
+
+
+ | 139 |
+ EGE10907-0209_1055_21293 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 140 |
+ EGE10907-0210_1056_21294 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 141 |
+ EGE10907-0211_1148_21295 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 142 |
+ EGE10907-0212_1149_21296 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 143 |
+ EGE10907-0213_1150_21297 |
+ BXD31 |
+ M |
+ 90 |
+ 10 |
+
+
+ | 144 |
+ EGE10907-0214_1151_21298 |
+ BXD31 |
+ M |
+ 90 |
+ 9.9 |
+
+
+ | 145 |
+ EGE10907-0215_1152_21299 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 146 |
+ EGE10907-0216_21429 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 147 |
+ EGE10907-0217_21430 |
+ BXD42 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 148 |
+ EGE10907-0218_21431 |
+ BXD42 |
+ M |
+ 83 |
+ 9.3 |
+
+
+ | 149 |
+ EGE10907-0219_21432 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 150 |
+ EGE10907-0220_21433 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 151 |
+ EGE10907-0221_21434 |
+ BXD50 |
+ F |
+ 92 |
+ 10 |
+
+
+ | 152 |
+ EGE10907-0222_21435 |
+ BXD1 |
+ M |
+ 73 |
+ 9.6 |
+
+
+ | 153 |
+ EGE10907-0223_21436 |
+ BXD13 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 154 |
+ EGE10907-0224_21437 |
+ BXD1 |
+ M |
+ 71 |
+ 9.5 |
+
+
+ | 155 |
+ EGE10907-0225_21438 |
+ BXD13 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 156 |
+ EGE10907-0226_21439 |
+ BXD43 |
+ F |
+ 85 |
+ 10 |
+
+
+ | 157 |
+ EGE10907-0227_21452 |
+ BXD43 |
+ F |
+ 85 |
+ 9.6 |
+
+
+ | 158 |
+ EGE10907-0229_21442 |
+ BXD43 |
+ M |
+ 85 |
+ 8.2 |
+
+
+ | 159 |
+ EGE10907-0230_21443 |
+ BXD50 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 160 |
+ EGE10907-0231_21444 |
+ BXD1 |
+ F |
+ 68 |
+ 9.4 |
+
+
+ | 161 |
+ EGE10907-0232_21445 |
+ BXD1 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 162 |
+ EGE10907-0233_21446 |
+ BXD29 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 163 |
+ EGE10907-0234_21447 |
+ BXD29 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 164 |
+ EGE10907-0235_21448 |
+ BXD75 |
+ F |
+ 68 |
+ 10 |
+
+
+ | 165 |
+ EGE10907-0236_21449 |
+ BXD75 |
+ M |
+ 68 |
+ 10 |
+
+
+ | 166 |
+ EGE10907-0237_21450 |
+ BXD96 |
+ F |
+ 67 |
+ 9.9 |
+
+
+ | 167 |
+ EGE10907-0238_21931 |
+ BXD99 |
+ M |
+ 71 |
+ 7.9 |
+
+
+ | 168 |
+ EGE10907-0239_21932 |
+ BXD99 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 169 |
+ EGE10907-0240_21933 |
+ BXD67 |
+ F |
+ 68 |
+ 8.8 |
+
+
+ | 170 |
+ EGE10907-0241_21934 |
+ BXD67 |
+ F |
+ 68 |
+ 8.5 |
+
+
+ | 171 |
+ EGE10907-0242_21935 |
+ BXD67 |
+ M |
+ 68 |
+ 9.5 |
+
+
+ | 172 |
+ EGE10907-0243_21936 |
+ BXD67 |
+ M |
+ 68 |
+ 9.6 |
+
+
+ | 173 |
+ EGE10907-0244_21937 |
+ BXD6 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 174 |
+ EGE10907-0245_21938 |
+ BXD12 |
+ M |
+ 82 |
+ 9.5 |
+
+
+ | 175 |
+ EGE10907-0246_21939 |
+ BXD60 |
+ F |
+ 72 |
+ 9.6 |
+
+
+ | 176 |
+ EGE10907-0247_21940 |
+ BXD65 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 177 |
+ EGE10907-0248_21941 |
+ BXD75 |
+ F |
+ 69 |
+ 8.8 |
+
+
+ | 178 |
+ EGE10907-0249_21942_(MoGene-2_0-st) |
+ BXD75 |
+ M |
+ 69 |
+ 9.2 |
+
+
+ | 179 |
+ EGE10907-0250_21943 |
+ BXD8 |
+ F |
+ 97 |
+ 9.1 |
+
+
+ | 180 |
+ EGE10907-0251_21944 |
+ BXD85 |
+ F |
+ 79 |
+ 8.6 |
+
+
+ | 181 |
+ EGE10907-0252_21945 |
+ BXD85 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 182 |
+ EGE10907-0253_21946 |
+ BXD85 |
+ M |
+ 79 |
+ 9.4 |
+
+
+ | 183 |
+ EGE10907-0254_21947 |
+ BXD102 |
+ M |
+ 94 |
+ 8.6 |
+
+
+ | 184 |
+ EGE10907-0255_21948 |
+ BXD99 |
+ F |
+ 83 |
+ 9 |
+
+
+ | 185 |
+ EGE10907-0256_21949 |
+ BXD69 |
+ F |
+ 68 |
+ 9 |
+
+
+ | 186 |
+ EGE10907-0257_21950 |
+ BXD84 |
+ F |
+ 74 |
+ 9.5 |
+
+
+ | 187 |
+ EGE10907-0258_21951 |
+ BXD84 |
+ F |
+ 74 |
+ 9.4 |
+
+
+ | 188 |
+ EGE10907-0259_21952 |
+ BXD84 |
+ M |
+ 74 |
+ 8.6 |
+
+
+ | 189 |
+ EGE10907-0260_21451 |
+ BXD96 |
+ M |
+ 67 |
+ 9.2 |
+
+
+ | 190 |
+ EGE10907-0261_21452 |
+ BXD99 |
+ F |
+ 71 |
+ 8.9 |
+
+
+ | 191 |
+ EGE10907-0262_21931 |
+ BXD6 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 192 |
+ EGE10907-0263_21932 |
+ BXD14 |
+ F |
+ 69 |
+ 8.5 |
+
+
+ | 193 |
+ EGE10907-0264_21933 |
+ BXD34 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 194 |
+ EGE10907-0265_21934 |
+ BXD34 |
+ M |
+ 79 |
+ 9.9 |
+
+
+ | 195 |
+ EGE10907-0266_21935 |
+ BXD40 |
+ F |
+ 75 |
+ 9.6 |
+
+
+ | 196 |
+ EGE10907-0267_21936 |
+ BXD40 |
+ M |
+ 78 |
+ 9.7 |
+
+
+ | 197 |
+ EGE10907-0268_21937 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 198 |
+ EGE10907-0269_21938 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 199 |
+ EGE10907-0270_21939 |
+ BXD56 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 200 |
+ EGE10907-0271_21940 |
+ BXD56 |
+ M |
+ 72 |
+ 9.4 |
+
+
+ | 201 |
+ EGE10907-0272_21941 |
+ BXD71 |
+ F |
+ 72 |
+ 9.9 |
+
+
+ | 202 |
+ EGE10907-0273_21942 |
+ BXD71 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 203 |
+ EGE10907-0274_21943 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 204 |
+ EGE10907-0275_21944 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 205 |
+ EGE10907-0276_21945 |
+ BXD27 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 206 |
+ EGE10907-0277_21946 |
+ BXD15 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 207 |
+ EGE10907-0278_21947 |
+ BXD20 |
+ F |
+ 125 |
+ 10 |
+
+
+ | 208 |
+ EGE10907-0279_21948 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 209 |
+ EGE10907-0280_21949 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 210 |
+ EGE10907-0281_21950 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 211 |
+ EGE10907-0282_21951 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 212 |
+ EGE10907-0283_21952 |
+ BXD85 |
+ F |
+ 87 |
+ 10 |
+
+
+ | 213 |
+ EGE10907-0284_21451 |
+ BXD43 |
+ M |
+ 75 |
+ 9.8 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Dodtatrcretexmogene2_1313/citation.rtf b/general/datasets/Dodtatrcretexmogene2_1313/citation.rtf
new file mode 100644
index 0000000..d84717d
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_1313/citation.rtf
@@ -0,0 +1,3 @@
+Related Publications: Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link) Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674 Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link) Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful: NEIBank collection of ESTs and SAGE data. RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases.
diff --git a/general/datasets/Dodtatrcretexmogene2_1313/contributors.rtf b/general/datasets/Dodtatrcretexmogene2_1313/contributors.rtf
new file mode 100644
index 0000000..11fece2
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_1313/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, XiangDi Wang, Justin P. Templeton and Robert W. Williams.
diff --git a/general/datasets/Dodtatrcretexmogene2_1313/platform.rtf b/general/datasets/Dodtatrcretexmogene2_1313/platform.rtf
new file mode 100644
index 0000000..19fc38c
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_1313/platform.rtf
@@ -0,0 +1 @@
+The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/Dodtatrcretexmogene2_1313/processing.rtf b/general/datasets/Dodtatrcretexmogene2_1313/processing.rtf
new file mode 100644
index 0000000..a7b767e
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_1313/processing.rtf
@@ -0,0 +1 @@
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Dodtatrcretexmogene2_1313/summary.rtf b/general/datasets/Dodtatrcretexmogene2_1313/summary.rtf
new file mode 100644
index 0000000..96a87e5
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_1313/summary.rtf
@@ -0,0 +1 @@
+The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/Dodtatrcretexmogene2_1313/tissue.rtf b/general/datasets/Dodtatrcretexmogene2_1313/tissue.rtf
new file mode 100644
index 0000000..056d7eb
--- /dev/null
+++ b/general/datasets/Dodtatrcretexmogene2_1313/tissue.rtf
@@ -0,0 +1 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/Dodtatrcretmogene2_0315/cases.rtf b/general/datasets/Dodtatrcretmogene2_0315/cases.rtf
new file mode 100644
index 0000000..34f9530
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_0315/cases.rtf
@@ -0,0 +1,9 @@
+Almost all animals are young adults between 60 and 100 days of age (Table 1, minimum age is 60 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
+
+BXD strains:
+
+
+ - The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s.
+ - In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset.
+ - The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
diff --git a/general/datasets/Dodtatrcretmogene2_0315/contributors.rtf b/general/datasets/Dodtatrcretmogene2_0315/contributors.rtf
new file mode 100644
index 0000000..814bf91
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_0315/contributors.rtf
@@ -0,0 +1,9 @@
+Other Related Publications
+
+
+ - Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link)
+ - Freeman NE, Templeton JP, Orr WE, Lu L, Williams RW, Geisert EE (2011) Genetic networks in the mouse retina: Growth Associated Protein 43 and Phosphate Tensin Homology network. Molecular Vision 17:1355-1372.
+ - Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674
+ - Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link)
+ - Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.(Link)
+
diff --git a/general/datasets/Dodtatrcretmogene2_0315/experiment-design.rtf b/general/datasets/Dodtatrcretmogene2_0315/experiment-design.rtf
new file mode 100644
index 0000000..b43e509
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_0315/experiment-design.rtf
@@ -0,0 +1,3 @@
+Sample Processing: Dr. XiangDi Wang (UTHSC) and Becky King (Emory) were involved in the retinal extractions and isolation of RNA. The Affymetrix arrays were run by two different research cores: the Molecular Resource Center at UTHSC (Dr. William Taylor Director) and the Integrated Genomics Core at Emory University by Robert B Isett (Dr. Michael E. Zwick, Director). In a separate set of experiments we could not detect any significant difference in the arrays run at UTHSC or at Emory University.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Dodtatrcretmogene2_0315/notes.rtf b/general/datasets/Dodtatrcretmogene2_0315/notes.rtf
new file mode 100644
index 0000000..cb14c74
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_0315/notes.rtf
@@ -0,0 +1,10 @@
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
diff --git a/general/datasets/Dodtatrcretmogene2_0315/platform.rtf b/general/datasets/Dodtatrcretmogene2_0315/platform.rtf
new file mode 100644
index 0000000..cb5e1b8
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_0315/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Gene 2.0 ST Array: These expression arrays have been designed with a median of 22 unique probes per transcript. Each unique probe is 25 bases in length, which means that the array measures a median of 550 bases per transcript. The arrays provide comprehensive transcriptome coverage with over 30,000 coding and non-coding transcripts. In addition there is coverage for 592 microRNAs. For some arrays the RNA was pooled from two retinas and for other arrays were run on a single retina.
diff --git a/general/datasets/Dodtatrcretmogene2_0315/summary.rtf b/general/datasets/Dodtatrcretmogene2_0315/summary.rtf
new file mode 100644
index 0000000..b6cf222
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_0315/summary.rtf
@@ -0,0 +1,5 @@
+DoD TATRC Retina Dataset Affymetrix MouseGene 2.0 ST Array (____ 2015) RMA analysis and scaling by Arthur Centeno. This data set consists of 75 BXD strains, C57BL/6J, DBA/2J, both reciprocal F1s, and BALB/cByJ. A total of 80 strains were quantified. The data are now open and available for analysis.
+
+This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strain was computed as the mean of four samples per strain. Expression values on a log2 scale range from 6.25 to 18.08 (11.83 units), a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean expression of the probes on the array of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
+
+The lowest level of expression is 6.254 for ILMN_2747167 (Arhgap11a) from HEI Retina Illumina V6.2 (April 2010) RankInv **. Lowest single data about 5.842. The highest level of expression is 18.077 for ILMN_2516699 (Ubb). Highest single value is about 18.934.
diff --git a/general/datasets/Dodtatrcretmogene2_0315/tissue.rtf b/general/datasets/Dodtatrcretmogene2_0315/tissue.rtf
new file mode 100644
index 0000000..87eb144
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_0315/tissue.rtf
@@ -0,0 +1,13 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in 1 ml of 160 U/ml Ribolock for 1 min at room temperature. Dissecting and preparing eyes for RNA extraction Retinas for RNA removed from the eye and placed in Hank’s Balanced Salt solution with RiboLock (Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) and processed per manufacturer’s instructions (in brief form below).
+
+1) Sample collection for RNA isolation.
+
+2) Quickly remove the retinas with clean curved forceps after cervical dislocation of the mouse.
+
+3) Put each retina in 1 ml of 160 U/ml Ribolock for 1 min in RT.
+
+4) Move the retina to another tube with 50µl Ribolock, store in -80°C.
+
+5) The RNA was isolated using a QiaCube and the in column DNAse procedure.
+
+Quality Control: All RNA samples were checked for quality before running microarrays. The samples were analyzed using the Agilent 2100 Bioanalyzer. The RNA integrity values for each sample are presented in Table 1 below.
diff --git a/general/datasets/Dodtatrcretmogene2_1313/acknowledgment.rtf b/general/datasets/Dodtatrcretmogene2_1313/acknowledgment.rtf
new file mode 100644
index 0000000..13c6b1e
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_1313/acknowledgment.rtf
@@ -0,0 +1 @@
+DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/Dodtatrcretmogene2_1313/cases.rtf b/general/datasets/Dodtatrcretmogene2_1313/cases.rtf
new file mode 100644
index 0000000..6b36c70
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_1313/cases.rtf
@@ -0,0 +1,1728 @@
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+
+
+
+
+
+ | Index |
+ EIGC ID (LIMS ID) |
+ Strain |
+ Sex |
+ Age at harvest |
+ RIN Score |
+
+
+ | 1 |
+ 602 |
+ BXD9 |
+ F |
+ 133 |
+ 9.1 |
+
+
+ | 2 |
+ 603 |
+ BXD9 |
+ M |
+ 100 |
+ 9.5 |
+
+
+ | 3 |
+ 604 |
+ BXD40 |
+ F |
+ 100 |
+ 9.4 |
+
+
+ | 4 |
+ 605 |
+ BXD40 |
+ M |
+ 100 |
+ 9.1 |
+
+
+ | 5 |
+ 606 |
+ BXD48 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 6 |
+ 607 |
+ BXD48 |
+ M |
+ 75 |
+ 8.6 |
+
+
+ | 7 |
+ 608 |
+ BXD63 |
+ F |
+ 75 |
+ 9.2 |
+
+
+ | 8 |
+ 609 |
+ BXD63 |
+ M |
+ 61 |
+ 9.4 |
+
+
+ | 9 |
+ 612 |
+ BXD73 |
+ M |
+ 108 |
+ 10 |
+
+
+ | 10 |
+ 614 |
+ BXD87 |
+ M |
+ 85 |
+ 9.2 |
+
+
+ | 11 |
+ 615 |
+ BXD87 |
+ F |
+ 85 |
+ 9.9 |
+
+
+ | 12 |
+ 616 |
+ BXD69 |
+ F |
+ 76 |
+ 9.3 |
+
+
+ | 13 |
+ 617 |
+ BXD69 |
+ M |
+ 100 |
+ 10 |
+
+
+ | 14 |
+ 618 |
+ BXD51 |
+ M |
+ 82 |
+ 8.9 |
+
+
+ | 15 |
+ 619 |
+ BXD92 (BXD65b) |
+ M |
+ 82 |
+ 8.8 |
+
+
+ | 16 |
+ 620 |
+ BXD92 (BXD65b) |
+ F |
+ 82 |
+ 8.8 |
+
+
+ | 17 |
+ 635 |
+ BXD100 |
+ M |
+ 70 |
+ 9 |
+
+
+ | 18 |
+ 636 |
+ BXD100 |
+ M |
+ 70 |
+ 8.8 |
+
+
+ | 19 |
+ 652 |
+ BXD92 (BXD65b) |
+ F |
+ 64 |
+ 9 |
+
+
+ | 20 |
+ 653 |
+ BXD87 |
+ F |
+ 67 |
+ 9.7 |
+
+
+ | 21 |
+ 654 |
+ BXD87 |
+ M |
+ 67 |
+ 8.9 |
+
+
+ | 22 |
+ 655 |
+ BXD63 |
+ M |
+ 71 |
+ 9 |
+
+
+ | 23 |
+ 660 |
+ BXD69 |
+ M |
+ 97 |
+ 10 |
+
+
+ | 24 |
+ 687 |
+ BXD6 |
+ M |
+ 85 |
+ 7.7 |
+
+
+ | 25 |
+ 688 |
+ BXD6 |
+ M |
+ 85 |
+ 9.4 |
+
+
+ | 26 |
+ 690 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 27 |
+ 691 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 28 |
+ 692 |
+ BXD12 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 29 |
+ 695 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 30 |
+ 696 |
+ BXD5 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 31 |
+ 698 |
+ BXD5 |
+ F |
+ 77 |
+ 9.9 |
+
+
+ | 32 |
+ 699 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 33 |
+ 701 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 34 |
+ 702 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 35 |
+ 705 |
+ BXD8 |
+ F |
+ 77 |
+ 9.2 |
+
+
+ | 36 |
+ 707 |
+ BXD15 |
+ F |
+ 77 |
+ 9.4 |
+
+
+ | 37 |
+ 708 |
+ BXD15 |
+ F |
+ 77 |
+ 9.1 |
+
+
+ | 38 |
+ 710 |
+ BXD15 |
+ M |
+ 77 |
+ 9.1 |
+
+
+ | 39 |
+ 713 |
+ BXD22 |
+ F |
+ 71 |
+ 9.5 |
+
+
+ | 40 |
+ 714 |
+ BXD22 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 41 |
+ 716 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 42 |
+ 717 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 43 |
+ 719 |
+ BXD14 |
+ F |
+ 70 |
+ 9.2 |
+
+
+ | 44 |
+ 722 |
+ BXD14 |
+ M |
+ 70 |
+ 8.9 |
+
+
+ | 45 |
+ 723 |
+ BXD14 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 46 |
+ 725 |
+ BXD18 |
+ F |
+ 70 |
+ 9 |
+
+
+ | 47 |
+ 726 |
+ BXD18 |
+ F |
+ 70 |
+ 9.1 |
+
+
+ | 48 |
+ 728 |
+ BXD18 |
+ M |
+ 70 |
+ 9.1 |
+
+
+ | 49 |
+ 729 |
+ BXD18 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 50 |
+ 731 |
+ BXD19 |
+ F |
+ 66 |
+ 9.3 |
+
+
+ | 51 |
+ 732 |
+ BXD19 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 52 |
+ 734 |
+ BXD19 |
+ M |
+ 66 |
+ 9.8 |
+
+
+ | 53 |
+ 735 |
+ BXD19 |
+ M |
+ 66 |
+ 9.4 |
+
+
+ | 54 |
+ 737 |
+ BXD21 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 55 |
+ 738 |
+ BXD21 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 56 |
+ 740 |
+ BXD21 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 57 |
+ 741 |
+ BXD21 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 58 |
+ 743 |
+ BXD2 |
+ F |
+ 70 |
+ 8.3 |
+
+
+ | 59 |
+ 744 |
+ BXD2 |
+ F |
+ 70 |
+ 8.6 |
+
+
+ | 60 |
+ 746 |
+ BXD2 |
+ M |
+ 70 |
+ 7.5 |
+
+
+ | 61 |
+ 747 |
+ BXD2 |
+ M |
+ 77 |
+ 8.6 |
+
+
+ | 62 |
+ 768 |
+ BXD48 |
+ M |
+ 121 |
+ 9.4 |
+
+
+ | 63 |
+ 770 |
+ BXD92 (BXD65b) |
+ M |
+ 65 |
+ 10 |
+
+
+ | 64 |
+ 771 |
+ BXD101 |
+ F |
+ 85 |
+ 8.3 |
+
+
+ | 65 |
+ 772 |
+ BXD101 |
+ F |
+ 85 |
+ 9.3 |
+
+
+ | 66 |
+ 773 |
+ BXD101 |
+ M |
+ 86 |
+ 9.5 |
+
+
+ | 67 |
+ 774 |
+ BXD101 |
+ M |
+ 86 |
+ 9.8 |
+
+
+ | 68 |
+ 775 |
+ BXD102 |
+ F |
+ 66 |
+ 9.5 |
+
+
+ | 69 |
+ 776 |
+ BXD102 |
+ F |
+ 66 |
+ 10 |
+
+
+ | 70 |
+ 777 |
+ BXD102 |
+ M |
+ 84 |
+ 9.6 |
+
+
+ | 71 |
+ 787 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 72 |
+ 788 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 73 |
+ 789 |
+ BXD63 |
+ F |
+ 115 |
+ 9.7 |
+
+
+ | 74 |
+ 790 |
+ BXD100 |
+ F |
+ 72 |
+ 9.8 |
+
+
+ | 75 |
+ 791 |
+ BXD100 |
+ F |
+ 72 |
+ 10 |
+
+
+ | 76 |
+ 818 |
+ BXD51 |
+ F |
+ 77 |
+ 9.7 |
+
+
+ | 77 |
+ 819 |
+ BXD51 |
+ F |
+ 77 |
+ 9.6 |
+
+
+ | 78 |
+ 820 |
+ BXD51 |
+ M |
+ 72 |
+ 9.7 |
+
+
+ | 79 |
+ 821 |
+ BXD65 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 80 |
+ 822 |
+ BXD65 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 81 |
+ 825 |
+ BXD65 |
+ F |
+ 72 |
+ 9.5 |
+
+
+ | 82 |
+ 827 |
+ BXD86 |
+ M |
+ 69 |
+ 9.1 |
+
+
+ | 83 |
+ 828 |
+ BXD86 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 84 |
+ 829 |
+ BXD90 |
+ F |
+ 69 |
+ 9.6 |
+
+
+ | 85 |
+ 831 |
+ BXD9 |
+ M |
+ 127 |
+ 9.7 |
+
+
+ | 86 |
+ 832 |
+ BXD39 |
+ F |
+ 99 |
+ 9.4 |
+
+
+ | 87 |
+ 833 |
+ BXD39 |
+ F |
+ 107 |
+ 9.3 |
+
+
+ | 88 |
+ 834 |
+ BXD60 |
+ F |
+ 107 |
+ 9.5 |
+
+
+ | 89 |
+ 836 |
+ BXD84 |
+ M |
+ 103 |
+ 9.7 |
+
+
+ | 90 |
+ 846 |
+ BXD39 |
+ M |
+ 63 |
+ 9.7 |
+
+
+ | 91 |
+ 847 |
+ BXD39 |
+ M |
+ 63 |
+ 9.8 |
+
+
+ | 92 |
+ 849 |
+ BXD20 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 93 |
+ 850 |
+ BXD20 |
+ M |
+ 70 |
+ 10 |
+
+
+ | 94 |
+ 851 |
+ BXD20 |
+ * |
+ 70 |
+ 9.5 |
+
+
+ | 95 |
+ 855 |
+ DBA/2J |
+ F |
+ 78 |
+ 9.7 |
+
+
+ | 96 |
+ 856 |
+ DBA/2J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 97 |
+ 857 |
+ DBA/2J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 98 |
+ 858 |
+ DBA/2J |
+ M |
+ 78 |
+ 9.9 |
+
+
+ | 99 |
+ 859 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 100 |
+ 860 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 101 |
+ 861 |
+ C57BL/6J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 102 |
+ 862 |
+ C57BL/6J |
+ M |
+ 78 |
+ 9.6 |
+
+
+ | 103 |
+ EGE10907-0172_890_20844 |
+ BXD28 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 104 |
+ EGE10907-0173_891_20845 |
+ BXD28 |
+ M |
+ 75 |
+ 9.7 |
+
+
+ | 105 |
+ EGE10907-0174_892_20846 |
+ BXD28 |
+ F |
+ 75 |
+ 9.7 |
+
+
+ | 106 |
+ EGE10907-0176_895_20848 |
+ BXD33 |
+ M |
+ 75 |
+ 9.88 |
+
+
+ | 107 |
+ EGE10907-0177_896_20849 |
+ BXD33 |
+ F |
+ 75 |
+ 10 |
+
+
+ | 108 |
+ EGE10907-0178_897_20850 |
+ BXD33 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 109 |
+ EGE10907-0179_898_20851 |
+ BXD36 |
+ M |
+ 75 |
+ 9.4 |
+
+
+ | 110 |
+ EGE10907-0180_899_20852 |
+ BXD36 |
+ F |
+ 75 |
+ 9.5 |
+
+
+ | 111 |
+ EGE10907-0181_900_20853 |
+ BXD36 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 112 |
+ EGE10907-0182_910_20854 |
+ BXD27 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 113 |
+ EGE10907-0183_990_20855 |
+ BXD9 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 114 |
+ EGE10907-0184_991_20856 |
+ BXD16 |
+ F |
+ 113 |
+ 10 |
+
+
+ | 115 |
+ EGE10907-0185_992_20857 |
+ BXD16 |
+ M |
+ 113 |
+ 9 |
+
+
+ | 116 |
+ EGE10907-0186_993_20858 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 117 |
+ EGE10907-0187_994_20859 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 118 |
+ EGE10907-0188_996_20860 |
+ BXD48 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 119 |
+ EGE10907-0189_997_20861 |
+ BXD73 |
+ M |
+ 106 |
+ 10 |
+
+
+ | 120 |
+ EGE10907-0190_999_20862 |
+ BXD11 |
+ F |
+ 121 |
+ 9.6 |
+
+
+ | 121 |
+ EGE10907-0191_100_20863 |
+ BXD11 |
+ F |
+ 121 |
+ 9.9 |
+
+
+ | 122 |
+ EGE10907-0192_1010_21276 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 123 |
+ EGE10907-0193_1011_21277 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 124 |
+ EGE10907-0194_1012_21278 |
+ BXD16 |
+ F |
+ 65 |
+ 10 |
+
+
+ | 125 |
+ EGE10907-0195_1015_21279 |
+ BXD16 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 126 |
+ EGE10907-0196_1019_21280 |
+ BXD33 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 127 |
+ EGE10907-0197_1020_21281 |
+ BXD36 |
+ M |
+ 78 |
+ 10 |
+
+
+ | 128 |
+ EGE10907-0198_1021_21282 |
+ BXD38 |
+ F |
+ 70 |
+ 9.8 |
+
+
+ | 129 |
+ EGE10907-0199_1022_21283 |
+ BXD38 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 130 |
+ EGE10907-0200_1023_21284 |
+ BXD38 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 131 |
+ EGE10907-0201_1047_21285 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 132 |
+ EGE10907-0202_1048_21286 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 133 |
+ EGE10907-0203_1049_21287 |
+ BXD38 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 134 |
+ EGE10907-0204_1050_21288 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 135 |
+ EGE10907-0205_1051_21289 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 136 |
+ EGE10907-0206_1052_21290 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 137 |
+ EGE10907-0207_1053_21291 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 138 |
+ EGE10907-0208_1054_21292 |
+ BXD90 |
+ F |
+ 71 |
+ 10 |
+
+
+ | 139 |
+ EGE10907-0209_1055_21293 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 140 |
+ EGE10907-0210_1056_21294 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 141 |
+ EGE10907-0211_1148_21295 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 142 |
+ EGE10907-0212_1149_21296 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 143 |
+ EGE10907-0213_1150_21297 |
+ BXD31 |
+ M |
+ 90 |
+ 10 |
+
+
+ | 144 |
+ EGE10907-0214_1151_21298 |
+ BXD31 |
+ M |
+ 90 |
+ 9.9 |
+
+
+ | 145 |
+ EGE10907-0215_1152_21299 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 146 |
+ EGE10907-0216_21429 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 147 |
+ EGE10907-0217_21430 |
+ BXD42 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 148 |
+ EGE10907-0218_21431 |
+ BXD42 |
+ M |
+ 83 |
+ 9.3 |
+
+
+ | 149 |
+ EGE10907-0219_21432 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 150 |
+ EGE10907-0220_21433 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 151 |
+ EGE10907-0221_21434 |
+ BXD50 |
+ F |
+ 92 |
+ 10 |
+
+
+ | 152 |
+ EGE10907-0222_21435 |
+ BXD1 |
+ M |
+ 73 |
+ 9.6 |
+
+
+ | 153 |
+ EGE10907-0223_21436 |
+ BXD13 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 154 |
+ EGE10907-0224_21437 |
+ BXD1 |
+ M |
+ 71 |
+ 9.5 |
+
+
+ | 155 |
+ EGE10907-0225_21438 |
+ BXD13 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 156 |
+ EGE10907-0226_21439 |
+ BXD43 |
+ F |
+ 85 |
+ 10 |
+
+
+ | 157 |
+ EGE10907-0227_21452 |
+ BXD43 |
+ F |
+ 85 |
+ 9.6 |
+
+
+ | 158 |
+ EGE10907-0229_21442 |
+ BXD43 |
+ M |
+ 85 |
+ 8.2 |
+
+
+ | 159 |
+ EGE10907-0230_21443 |
+ BXD50 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 160 |
+ EGE10907-0231_21444 |
+ BXD1 |
+ F |
+ 68 |
+ 9.4 |
+
+
+ | 161 |
+ EGE10907-0232_21445 |
+ BXD1 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 162 |
+ EGE10907-0233_21446 |
+ BXD29 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 163 |
+ EGE10907-0234_21447 |
+ BXD29 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 164 |
+ EGE10907-0235_21448 |
+ BXD75 |
+ F |
+ 68 |
+ 10 |
+
+
+ | 165 |
+ EGE10907-0236_21449 |
+ BXD75 |
+ M |
+ 68 |
+ 10 |
+
+
+ | 166 |
+ EGE10907-0237_21450 |
+ BXD96 |
+ F |
+ 67 |
+ 9.9 |
+
+
+ | 167 |
+ EGE10907-0238_21931 |
+ BXD99 |
+ M |
+ 71 |
+ 7.9 |
+
+
+ | 168 |
+ EGE10907-0239_21932 |
+ BXD99 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 169 |
+ EGE10907-0240_21933 |
+ BXD67 |
+ F |
+ 68 |
+ 8.8 |
+
+
+ | 170 |
+ EGE10907-0241_21934 |
+ BXD67 |
+ F |
+ 68 |
+ 8.5 |
+
+
+ | 171 |
+ EGE10907-0242_21935 |
+ BXD67 |
+ M |
+ 68 |
+ 9.5 |
+
+
+ | 172 |
+ EGE10907-0243_21936 |
+ BXD67 |
+ M |
+ 68 |
+ 9.6 |
+
+
+ | 173 |
+ EGE10907-0244_21937 |
+ BXD6 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 174 |
+ EGE10907-0245_21938 |
+ BXD12 |
+ M |
+ 82 |
+ 9.5 |
+
+
+ | 175 |
+ EGE10907-0246_21939 |
+ BXD60 |
+ F |
+ 72 |
+ 9.6 |
+
+
+ | 176 |
+ EGE10907-0247_21940 |
+ BXD65 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 177 |
+ EGE10907-0248_21941 |
+ BXD75 |
+ F |
+ 69 |
+ 8.8 |
+
+
+ | 178 |
+ EGE10907-0249_21942_(MoGene-2_0-st) |
+ BXD75 |
+ M |
+ 69 |
+ 9.2 |
+
+
+ | 179 |
+ EGE10907-0250_21943 |
+ BXD8 |
+ F |
+ 97 |
+ 9.1 |
+
+
+ | 180 |
+ EGE10907-0251_21944 |
+ BXD85 |
+ F |
+ 79 |
+ 8.6 |
+
+
+ | 181 |
+ EGE10907-0252_21945 |
+ BXD85 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 182 |
+ EGE10907-0253_21946 |
+ BXD85 |
+ M |
+ 79 |
+ 9.4 |
+
+
+ | 183 |
+ EGE10907-0254_21947 |
+ BXD102 |
+ M |
+ 94 |
+ 8.6 |
+
+
+ | 184 |
+ EGE10907-0255_21948 |
+ BXD99 |
+ F |
+ 83 |
+ 9 |
+
+
+ | 185 |
+ EGE10907-0256_21949 |
+ BXD69 |
+ F |
+ 68 |
+ 9 |
+
+
+ | 186 |
+ EGE10907-0257_21950 |
+ BXD84 |
+ F |
+ 74 |
+ 9.5 |
+
+
+ | 187 |
+ EGE10907-0258_21951 |
+ BXD84 |
+ F |
+ 74 |
+ 9.4 |
+
+
+ | 188 |
+ EGE10907-0259_21952 |
+ BXD84 |
+ M |
+ 74 |
+ 8.6 |
+
+
+ | 189 |
+ EGE10907-0260_21451 |
+ BXD96 |
+ M |
+ 67 |
+ 9.2 |
+
+
+ | 190 |
+ EGE10907-0261_21452 |
+ BXD99 |
+ F |
+ 71 |
+ 8.9 |
+
+
+ | 191 |
+ EGE10907-0262_21931 |
+ BXD6 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 192 |
+ EGE10907-0263_21932 |
+ BXD14 |
+ F |
+ 69 |
+ 8.5 |
+
+
+ | 193 |
+ EGE10907-0264_21933 |
+ BXD34 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 194 |
+ EGE10907-0265_21934 |
+ BXD34 |
+ M |
+ 79 |
+ 9.9 |
+
+
+ | 195 |
+ EGE10907-0266_21935 |
+ BXD40 |
+ F |
+ 75 |
+ 9.6 |
+
+
+ | 196 |
+ EGE10907-0267_21936 |
+ BXD40 |
+ M |
+ 78 |
+ 9.7 |
+
+
+ | 197 |
+ EGE10907-0268_21937 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 198 |
+ EGE10907-0269_21938 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 199 |
+ EGE10907-0270_21939 |
+ BXD56 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 200 |
+ EGE10907-0271_21940 |
+ BXD56 |
+ M |
+ 72 |
+ 9.4 |
+
+
+ | 201 |
+ EGE10907-0272_21941 |
+ BXD71 |
+ F |
+ 72 |
+ 9.9 |
+
+
+ | 202 |
+ EGE10907-0273_21942 |
+ BXD71 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 203 |
+ EGE10907-0274_21943 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 204 |
+ EGE10907-0275_21944 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 205 |
+ EGE10907-0276_21945 |
+ BXD27 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 206 |
+ EGE10907-0277_21946 |
+ BXD15 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 207 |
+ EGE10907-0278_21947 |
+ BXD20 |
+ F |
+ 125 |
+ 10 |
+
+
+ | 208 |
+ EGE10907-0279_21948 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 209 |
+ EGE10907-0280_21949 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 210 |
+ EGE10907-0281_21950 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 211 |
+ EGE10907-0282_21951 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 212 |
+ EGE10907-0283_21952 |
+ BXD85 |
+ F |
+ 87 |
+ 10 |
+
+
+ | 213 |
+ EGE10907-0284_21451 |
+ BXD43 |
+ M |
+ 75 |
+ 9.8 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Dodtatrcretmogene2_1313/citation.rtf b/general/datasets/Dodtatrcretmogene2_1313/citation.rtf
new file mode 100644
index 0000000..d84717d
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_1313/citation.rtf
@@ -0,0 +1,3 @@
+Related Publications: Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link) Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674 Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link) Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful: NEIBank collection of ESTs and SAGE data. RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases.
diff --git a/general/datasets/Dodtatrcretmogene2_1313/contributors.rtf b/general/datasets/Dodtatrcretmogene2_1313/contributors.rtf
new file mode 100644
index 0000000..11fece2
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_1313/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, XiangDi Wang, Justin P. Templeton and Robert W. Williams.
diff --git a/general/datasets/Dodtatrcretmogene2_1313/platform.rtf b/general/datasets/Dodtatrcretmogene2_1313/platform.rtf
new file mode 100644
index 0000000..19fc38c
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_1313/platform.rtf
@@ -0,0 +1 @@
+The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/Dodtatrcretmogene2_1313/processing.rtf b/general/datasets/Dodtatrcretmogene2_1313/processing.rtf
new file mode 100644
index 0000000..a7b767e
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_1313/processing.rtf
@@ -0,0 +1 @@
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Dodtatrcretmogene2_1313/summary.rtf b/general/datasets/Dodtatrcretmogene2_1313/summary.rtf
new file mode 100644
index 0000000..96a87e5
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_1313/summary.rtf
@@ -0,0 +1 @@
+The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/Dodtatrcretmogene2_1313/tissue.rtf b/general/datasets/Dodtatrcretmogene2_1313/tissue.rtf
new file mode 100644
index 0000000..056d7eb
--- /dev/null
+++ b/general/datasets/Dodtatrcretmogene2_1313/tissue.rtf
@@ -0,0 +1 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/EBI_MKK_Liv_TPM_Log2_0621/acknowledgment.rtf b/general/datasets/EBI_MKK_Liv_TPM_Log2_0621/acknowledgment.rtf
deleted file mode 100644
index 44b9d93..0000000
--- a/general/datasets/EBI_MKK_Liv_TPM_Log2_0621/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors acknowledge Thomas Seitz, and Irina Oks and Marzena Majewski for supporting the fish husbandry, and Alicia Günthel, Rachel Müller and Beate Wittbrodt for laboratory assistance. F.L. dedicates this paper to Sabine and Rolf Loosli-Walther. The work was funded by the Helmholtz funding programme BIFTM to F. Loosli, N. Wolf, N. Kusminski, C. Herder and N. Aadepu. E. Birney, T. Fitzgerald, A. Leger, C. Barton, J. Monahan and I. Brettell were funded by the EMBL European Bioinformatics Institute (EMBL-EBI). This work was supported by Heidelberg University Core Funding to T. Tavhelidse, T. Thumberger and J. Wittbrodt. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 810172), from the NIH UH-3338-03 (JW), the German Ministry for Research (BMBF: HIGH-life 05K19VH1, Code-Vita 05K16VH1, JW) and the German Center for Heart Diseases DZHK (JW, JG).
diff --git a/general/datasets/EBI_MKK_Liv_TPM_Log2_0621/specifics.rtf b/general/datasets/EBI_MKK_Liv_TPM_Log2_0621/specifics.rtf
deleted file mode 100644
index 16aad9e..0000000
--- a/general/datasets/EBI_MKK_Liv_TPM_Log2_0621/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-EBI MIKK Liver Male RNA-Seq (May 21) Log2 TPM
\ No newline at end of file
diff --git a/general/datasets/EBI_MKK_Liv_TPM_Log2_0621/summary.rtf b/general/datasets/EBI_MKK_Liv_TPM_Log2_0621/summary.rtf
deleted file mode 100644
index d931cbf..0000000
--- a/general/datasets/EBI_MKK_Liv_TPM_Log2_0621/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Full paper available at https://www.biorxiv.org/content/10.1101/2021.05.17.444412v2.full
-
-Unraveling the relationship between genetic variation and phenotypic traits remains a fundamental challenge in biology. Mapping variants underlying complex traits while controlling for confounding environmental factors is often problematic. To address this, we have established a vertebrate genetic resource specifically to allow for robust genotype-to-phenotype investigations. The teleost medaka (Oryzias latipes) is an established genetic model system with a long history of genetic research and a high tolerance to inbreeding from the wild. Here we present the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel: the first near-isogenic panel of 80 inbred lines in a vertebrate model derived from a wild founder population. Inbred lines provide fixed genomes that are a prerequisite for the replication of studies, studies which vary both the genetics and environment in a controlled manner and functional testing. The MIKK panel will therefore enable phenotype-to-genotype association studies of complex genetic traits while allowing for careful control of interacting factors, with numerous applications in genetic research, human health, and drug development and fundamental biology. Here we present a detailed characterisation of the genetic variation across the MIKK panel, which provides a rich and unique genetic resource to the community by enabling large-scale experiments for mapping complex traits.
diff --git a/general/datasets/EBI_MKK_Liv_TPM_Log2_0621/tissue.rtf b/general/datasets/EBI_MKK_Liv_TPM_Log2_0621/tissue.rtf
deleted file mode 100644
index 4e277e5..0000000
--- a/general/datasets/EBI_MKK_Liv_TPM_Log2_0621/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-For whole genome sequencing, medaka organs were dissected from 6-month-old male adults. Fish were sacrificed by hypothermic shock. The brain was dissected and shock frozen in liquid nitrogen. For RNAseq analysis 12 month old adults that were kept at either 14 light:10 dark (summer condition) or 10 light:14 dark (winter condition) light cycles respectively were sacrificed by hypothermic shock and the organs after dissection were shock frozen in liquid nitrogen.
diff --git a/general/datasets/EL_BXDCDHFDScWAT_0216/acknowledgment.rtf b/general/datasets/EL_BXDCDHFDScWAT_0216/acknowledgment.rtf
deleted file mode 100644
index 3fc4fc5..0000000
--- a/general/datasets/EL_BXDCDHFDScWAT_0216/acknowledgment.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDCDHFDScWAT_0216/cases.rtf b/general/datasets/EL_BXDCDHFDScWAT_0216/cases.rtf
deleted file mode 100644
index f54f4f2..0000000
--- a/general/datasets/EL_BXDCDHFDScWAT_0216/cases.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- 40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Subcuteaneous white adipose tissue was collected near the end of the sacrifice pipeline, occurring an estimated 10±2 minutes after sacrifice. The tissue was weighed and then placed in a storage tube in liquid nitrogen.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDCDHFDScWAT_0216/experiment-design.rtf b/general/datasets/EL_BXDCDHFDScWAT_0216/experiment-design.rtf
deleted file mode 100644
index b417b79..0000000
--- a/general/datasets/EL_BXDCDHFDScWAT_0216/experiment-design.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDCDHFDScWAT_0216/platform.rtf b/general/datasets/EL_BXDCDHFDScWAT_0216/platform.rtf
deleted file mode 100644
index 066be8d..0000000
--- a/general/datasets/EL_BXDCDHFDScWAT_0216/platform.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-GeneChip Mouse Transcriptome Assay 1.0
-
-All arrays were Affymetrix Mouse Transcriptome Assay 1.0, prepared and run simultaneously in a single batch in January 2016 by Lorne Rose at the University of Tennessee Health Science Center.
-
-Data error checked by RW Williams and David Ashbrook (March 2019). Numerous strain assignment corrections to HFD limb of study. Finally eQTL analysis validates both CD and HFD components.
diff --git a/general/datasets/EL_BXDCDHFDScWAT_0216/processing.rtf b/general/datasets/EL_BXDCDHFDScWAT_0216/processing.rtf
deleted file mode 100644
index 5dbb444..0000000
--- a/general/datasets/EL_BXDCDHFDScWAT_0216/processing.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDCDHFDScWAT_0216/specifics.rtf b/general/datasets/EL_BXDCDHFDScWAT_0216/specifics.rtf
deleted file mode 100644
index e6f6b94..0000000
--- a/general/datasets/EL_BXDCDHFDScWAT_0216/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Note: As of March 2019, this data set also affected by strain assignment errors in HFD limb. Needs to be fixed by Evan Williams, Arthur Centeno, and Rob Williams
diff --git a/general/datasets/EL_BXDCDHFDScWAT_0216/summary.rtf b/general/datasets/EL_BXDCDHFDScWAT_0216/summary.rtf
deleted file mode 100644
index 6c2d77a..0000000
--- a/general/datasets/EL_BXDCDHFDScWAT_0216/summary.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
- Microarray data for four other tissues in the exact same cohorts was processed and is in GeneNetwork: Heart, Liver, Muscle [Quadriceps], and Adipose [Brown]. Proteomic data for one other tissue in the exact same cohorts was processed and is in GeneNetwork: Liver. Metabolomic data for two tissues in the same cohorts was processed and is in GeneNetwork: Liver and Muscle [Quadriceps]. Brown Adipose was only run in CD cohorts, while all other datasets were run on both diets. All phenotype data associated with these animals can be found by searching Phenotypes for the code “LISP3”. Note that some traits are still private, while others have been published. |
-
-
-
-
diff --git a/general/datasets/EL_BXDCDHFDScWAT_0216/tissue.rtf b/general/datasets/EL_BXDCDHFDScWAT_0216/tissue.rtf
deleted file mode 100644
index e595c55..0000000
--- a/general/datasets/EL_BXDCDHFDScWAT_0216/tissue.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- Subcuteaneous WAT was later shattered in liquid nitrogen, and around 100 mg was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0. RNA was prepared in the summer of 2013, while the RNEasy cleanup occurred in the winter of 2015; unlike the other tissues run as a part of this study, these RNA samples spent a significant time in the -80° freezers. However, the samples only underwent one freeze—thaw cycle.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDCDScWAT_0216/acknowledgment.rtf b/general/datasets/EL_BXDCDScWAT_0216/acknowledgment.rtf
deleted file mode 100644
index 3fc4fc5..0000000
--- a/general/datasets/EL_BXDCDScWAT_0216/acknowledgment.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDCDScWAT_0216/cases.rtf b/general/datasets/EL_BXDCDScWAT_0216/cases.rtf
deleted file mode 100644
index f54f4f2..0000000
--- a/general/datasets/EL_BXDCDScWAT_0216/cases.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- 40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Subcuteaneous white adipose tissue was collected near the end of the sacrifice pipeline, occurring an estimated 10±2 minutes after sacrifice. The tissue was weighed and then placed in a storage tube in liquid nitrogen.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDCDScWAT_0216/experiment-design.rtf b/general/datasets/EL_BXDCDScWAT_0216/experiment-design.rtf
deleted file mode 100644
index b417b79..0000000
--- a/general/datasets/EL_BXDCDScWAT_0216/experiment-design.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDCDScWAT_0216/platform.rtf b/general/datasets/EL_BXDCDScWAT_0216/platform.rtf
deleted file mode 100644
index 066be8d..0000000
--- a/general/datasets/EL_BXDCDScWAT_0216/platform.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-GeneChip Mouse Transcriptome Assay 1.0
-
-All arrays were Affymetrix Mouse Transcriptome Assay 1.0, prepared and run simultaneously in a single batch in January 2016 by Lorne Rose at the University of Tennessee Health Science Center.
-
-Data error checked by RW Williams and David Ashbrook (March 2019). Numerous strain assignment corrections to HFD limb of study. Finally eQTL analysis validates both CD and HFD components.
diff --git a/general/datasets/EL_BXDCDScWAT_0216/processing.rtf b/general/datasets/EL_BXDCDScWAT_0216/processing.rtf
deleted file mode 100644
index 5dbb444..0000000
--- a/general/datasets/EL_BXDCDScWAT_0216/processing.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDCDScWAT_0216/summary.rtf b/general/datasets/EL_BXDCDScWAT_0216/summary.rtf
deleted file mode 100644
index 6c2d77a..0000000
--- a/general/datasets/EL_BXDCDScWAT_0216/summary.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
- Microarray data for four other tissues in the exact same cohorts was processed and is in GeneNetwork: Heart, Liver, Muscle [Quadriceps], and Adipose [Brown]. Proteomic data for one other tissue in the exact same cohorts was processed and is in GeneNetwork: Liver. Metabolomic data for two tissues in the same cohorts was processed and is in GeneNetwork: Liver and Muscle [Quadriceps]. Brown Adipose was only run in CD cohorts, while all other datasets were run on both diets. All phenotype data associated with these animals can be found by searching Phenotypes for the code “LISP3”. Note that some traits are still private, while others have been published. |
-
-
-
-
diff --git a/general/datasets/EL_BXDCDScWAT_0216/tissue.rtf b/general/datasets/EL_BXDCDScWAT_0216/tissue.rtf
deleted file mode 100644
index e595c55..0000000
--- a/general/datasets/EL_BXDCDScWAT_0216/tissue.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- Subcuteaneous WAT was later shattered in liquid nitrogen, and around 100 mg was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0. RNA was prepared in the summer of 2013, while the RNEasy cleanup occurred in the winter of 2015; unlike the other tissues run as a part of this study, these RNA samples spent a significant time in the -80° freezers. However, the samples only underwent one freeze—thaw cycle.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDHFDScWAT_0216/acknowledgment.rtf b/general/datasets/EL_BXDHFDScWAT_0216/acknowledgment.rtf
deleted file mode 100644
index 3fc4fc5..0000000
--- a/general/datasets/EL_BXDHFDScWAT_0216/acknowledgment.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDHFDScWAT_0216/cases.rtf b/general/datasets/EL_BXDHFDScWAT_0216/cases.rtf
deleted file mode 100644
index f54f4f2..0000000
--- a/general/datasets/EL_BXDHFDScWAT_0216/cases.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- 40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Subcuteaneous white adipose tissue was collected near the end of the sacrifice pipeline, occurring an estimated 10±2 minutes after sacrifice. The tissue was weighed and then placed in a storage tube in liquid nitrogen.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDHFDScWAT_0216/experiment-design.rtf b/general/datasets/EL_BXDHFDScWAT_0216/experiment-design.rtf
deleted file mode 100644
index b417b79..0000000
--- a/general/datasets/EL_BXDHFDScWAT_0216/experiment-design.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDHFDScWAT_0216/platform.rtf b/general/datasets/EL_BXDHFDScWAT_0216/platform.rtf
deleted file mode 100644
index 066be8d..0000000
--- a/general/datasets/EL_BXDHFDScWAT_0216/platform.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-GeneChip Mouse Transcriptome Assay 1.0
-
-All arrays were Affymetrix Mouse Transcriptome Assay 1.0, prepared and run simultaneously in a single batch in January 2016 by Lorne Rose at the University of Tennessee Health Science Center.
-
-Data error checked by RW Williams and David Ashbrook (March 2019). Numerous strain assignment corrections to HFD limb of study. Finally eQTL analysis validates both CD and HFD components.
diff --git a/general/datasets/EL_BXDHFDScWAT_0216/processing.rtf b/general/datasets/EL_BXDHFDScWAT_0216/processing.rtf
deleted file mode 100644
index 5dbb444..0000000
--- a/general/datasets/EL_BXDHFDScWAT_0216/processing.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
- |
-
-
-
-
diff --git a/general/datasets/EL_BXDHFDScWAT_0216/specifics.rtf b/general/datasets/EL_BXDHFDScWAT_0216/specifics.rtf
deleted file mode 100644
index 276d19a..0000000
--- a/general/datasets/EL_BXDHFDScWAT_0216/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Note: Prior to March 2019, the HFD component of this data set had strain assignment error. Now fully corrected.
diff --git a/general/datasets/EL_BXDHFDScWAT_0216/summary.rtf b/general/datasets/EL_BXDHFDScWAT_0216/summary.rtf
deleted file mode 100644
index 6c2d77a..0000000
--- a/general/datasets/EL_BXDHFDScWAT_0216/summary.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
- Microarray data for four other tissues in the exact same cohorts was processed and is in GeneNetwork: Heart, Liver, Muscle [Quadriceps], and Adipose [Brown]. Proteomic data for one other tissue in the exact same cohorts was processed and is in GeneNetwork: Liver. Metabolomic data for two tissues in the same cohorts was processed and is in GeneNetwork: Liver and Muscle [Quadriceps]. Brown Adipose was only run in CD cohorts, while all other datasets were run on both diets. All phenotype data associated with these animals can be found by searching Phenotypes for the code “LISP3”. Note that some traits are still private, while others have been published. |
-
-
-
-
diff --git a/general/datasets/EL_BXDHFDScWAT_0216/tissue.rtf b/general/datasets/EL_BXDHFDScWAT_0216/tissue.rtf
deleted file mode 100644
index e595c55..0000000
--- a/general/datasets/EL_BXDHFDScWAT_0216/tissue.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
- |
- Subcuteaneous WAT was later shattered in liquid nitrogen, and around 100 mg was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0. RNA was prepared in the summer of 2013, while the RNEasy cleanup occurred in the winter of 2015; unlike the other tissues run as a part of this study, these RNA samples spent a significant time in the -80° freezers. However, the samples only underwent one freeze—thaw cycle.
- |
-
-
-
-
diff --git a/general/datasets/EPFLADEL1013/acknowledgment.rtf b/general/datasets/EPFLADEL1013/acknowledgment.rtf
deleted file mode 100644
index 291baee..0000000
--- a/general/datasets/EPFLADEL1013/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice, Jesse Ingels who genotyped the congenic AHR line. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays. Thanks to Ian Duncan for supplying the mutant ss D. melanogaster lines. Discussions with Prof. Stephan Morgenthaler (EPFL) are also acknowledged.
diff --git a/general/datasets/EPFLADEL1013/cases.rtf b/general/datasets/EPFLADEL1013/cases.rtf
deleted file mode 100644
index 0e2dfc2..0000000
--- a/general/datasets/EPFLADEL1013/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-42 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The quadriceps were the last tissue frozen in liquid nitrogen during the sacrifice, about 15 minutes after perfusion. Quadriceps were taken by cutting laterally at the knee.
diff --git a/general/datasets/EPFLADEL1013/experiment-design.rtf b/general/datasets/EPFLADEL1013/experiment-design.rtf
deleted file mode 100644
index 6329851..0000000
--- a/general/datasets/EPFLADEL1013/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
diff --git a/general/datasets/EPFLADEL1013/platform.rtf b/general/datasets/EPFLADEL1013/platform.rtf
deleted file mode 100644
index a8a63c9..0000000
--- a/general/datasets/EPFLADEL1013/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All arrays were Affymetrix Mouse Gene 2.0 ST, prepared and run simultaneously in a single batch in October 2013 by Lorne Rose at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLADEL1013/processing.rtf b/general/datasets/EPFLADEL1013/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFLADEL1013/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFLADEL1013/summary.rtf b/general/datasets/EPFLADEL1013/summary.rtf
deleted file mode 100644
index 07c710f..0000000
--- a/general/datasets/EPFLADEL1013/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. We here phenotype 43 BXD strains and observe they have large variation (~5-fold) in their spontaneous activity during waking hours. QTL analyses indicate that ~40% of this variance is attributable to a narrow locus containing the aryl hydrocarbon receptor (Ahr), a basic helix-loop-helix transcription factor with well-established roles in development and xenobiotic metabolism. Strains with the D2 allele of Ahr have reduced gene expression compared to those with the B6 allele, and have significantly higher spontaneous activity. This effect was also observed in B6 mice with a congenic D2 Ahr interval, and in B6 mice with a humanized AHR allele which, like the D2 allele, is expressed much less and has less enzymatic activity than the B6 allele. Ahr is highly conserved in invertebrates, and strikingly inhibition of its orthologs in D. melanogaster and C. elegans (spineless and ahr-1) leads to marked increases in basal activity. In mammals, Ahr has numerous ligands, but most are either non-selective (e.g. resveratrol) or highly toxic (e.g. 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)). Thus, we chose to examine a major environmental influence—long term feeding with high fat diet (HFD)—to see if the effects of Ahr are dependent on major metabolic differences. Interestingly, while HFD robustly halved movement across all strains, the QTL position and effects of Ahr remained unchanged, indicating that the effects are independent. The highly consistent effects of Ahr on movement indicate that changes in its constitutive activity have a role on spontaneous movement and may influence human behavior.
diff --git a/general/datasets/EPFLADEL1013/tissue.rtf b/general/datasets/EPFLADEL1013/tissue.rtf
deleted file mode 100644
index f2bfb07..0000000
--- a/general/datasets/EPFLADEL1013/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Brown adipose was later shattered in liquid nitrogen and about half was taken for each sample, although the size of the BAT varied dramatically. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLADGL1013/acknowledgment.rtf b/general/datasets/EPFLADGL1013/acknowledgment.rtf
deleted file mode 100644
index 291baee..0000000
--- a/general/datasets/EPFLADGL1013/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice, Jesse Ingels who genotyped the congenic AHR line. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays. Thanks to Ian Duncan for supplying the mutant ss D. melanogaster lines. Discussions with Prof. Stephan Morgenthaler (EPFL) are also acknowledged.
diff --git a/general/datasets/EPFLADGL1013/cases.rtf b/general/datasets/EPFLADGL1013/cases.rtf
deleted file mode 100644
index 0e2dfc2..0000000
--- a/general/datasets/EPFLADGL1013/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-42 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The quadriceps were the last tissue frozen in liquid nitrogen during the sacrifice, about 15 minutes after perfusion. Quadriceps were taken by cutting laterally at the knee.
diff --git a/general/datasets/EPFLADGL1013/experiment-design.rtf b/general/datasets/EPFLADGL1013/experiment-design.rtf
deleted file mode 100644
index 6329851..0000000
--- a/general/datasets/EPFLADGL1013/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
diff --git a/general/datasets/EPFLADGL1013/platform.rtf b/general/datasets/EPFLADGL1013/platform.rtf
deleted file mode 100644
index a8a63c9..0000000
--- a/general/datasets/EPFLADGL1013/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All arrays were Affymetrix Mouse Gene 2.0 ST, prepared and run simultaneously in a single batch in October 2013 by Lorne Rose at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLADGL1013/processing.rtf b/general/datasets/EPFLADGL1013/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFLADGL1013/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFLADGL1013/summary.rtf b/general/datasets/EPFLADGL1013/summary.rtf
deleted file mode 100644
index 07c710f..0000000
--- a/general/datasets/EPFLADGL1013/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. We here phenotype 43 BXD strains and observe they have large variation (~5-fold) in their spontaneous activity during waking hours. QTL analyses indicate that ~40% of this variance is attributable to a narrow locus containing the aryl hydrocarbon receptor (Ahr), a basic helix-loop-helix transcription factor with well-established roles in development and xenobiotic metabolism. Strains with the D2 allele of Ahr have reduced gene expression compared to those with the B6 allele, and have significantly higher spontaneous activity. This effect was also observed in B6 mice with a congenic D2 Ahr interval, and in B6 mice with a humanized AHR allele which, like the D2 allele, is expressed much less and has less enzymatic activity than the B6 allele. Ahr is highly conserved in invertebrates, and strikingly inhibition of its orthologs in D. melanogaster and C. elegans (spineless and ahr-1) leads to marked increases in basal activity. In mammals, Ahr has numerous ligands, but most are either non-selective (e.g. resveratrol) or highly toxic (e.g. 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)). Thus, we chose to examine a major environmental influence—long term feeding with high fat diet (HFD)—to see if the effects of Ahr are dependent on major metabolic differences. Interestingly, while HFD robustly halved movement across all strains, the QTL position and effects of Ahr remained unchanged, indicating that the effects are independent. The highly consistent effects of Ahr on movement indicate that changes in its constitutive activity have a role on spontaneous movement and may influence human behavior.
diff --git a/general/datasets/EPFLADGL1013/tissue.rtf b/general/datasets/EPFLADGL1013/tissue.rtf
deleted file mode 100644
index f2bfb07..0000000
--- a/general/datasets/EPFLADGL1013/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Brown adipose was later shattered in liquid nitrogen and about half was taken for each sample, although the size of the BAT varied dramatically. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLBXDprotCDRPN0214/cases.rtf b/general/datasets/EPFLBXDprotCDRPN0214/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLBXDprotCDRPN0214/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLBXDprotCDRPN0214/notes.rtf b/general/datasets/EPFLBXDprotCDRPN0214/notes.rtf
deleted file mode 100644
index ecdae60..0000000
--- a/general/datasets/EPFLBXDprotCDRPN0214/notes.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-SWATH
-
-SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
-
-The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
-
-In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
-
-References
-
-
- - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
- - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
- - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
- - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
-
diff --git a/general/datasets/EPFLBXDprotCDRPN0214/platform.rtf b/general/datasets/EPFLBXDprotCDRPN0214/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLBXDprotCDRPN0214/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLBXDprotCDRPN0214/summary.rtf b/general/datasets/EPFLBXDprotCDRPN0214/summary.rtf
deleted file mode 100644
index 8797309..0000000
--- a/general/datasets/EPFLBXDprotCDRPN0214/summary.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
-
-Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
-
-Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/EPFLBXDprotCDRPN0214/tissue.rtf b/general/datasets/EPFLBXDprotCDRPN0214/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLBXDprotCDRPN0214/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/cases.rtf b/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/notes.rtf b/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/notes.rtf
deleted file mode 100644
index ecdae60..0000000
--- a/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/notes.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-SWATH
-
-SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
-
-The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
-
-In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
-
-References
-
-
- - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
- - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
- - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
- - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
-
diff --git a/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/platform.rtf b/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/summary.rtf b/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/summary.rtf
deleted file mode 100644
index 8797309..0000000
--- a/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/summary.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
-
-Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
-
-Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/tissue.rtf b/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLBXDprotCD_CDHFDRPN0214/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLBXDprotHFDRPN0214/cases.rtf b/general/datasets/EPFLBXDprotHFDRPN0214/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLBXDprotHFDRPN0214/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLBXDprotHFDRPN0214/notes.rtf b/general/datasets/EPFLBXDprotHFDRPN0214/notes.rtf
deleted file mode 100644
index ecdae60..0000000
--- a/general/datasets/EPFLBXDprotHFDRPN0214/notes.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-SWATH
-
-SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
-
-The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
-
-In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
-
-References
-
-
- - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
- - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
- - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
- - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
-
diff --git a/general/datasets/EPFLBXDprotHFDRPN0214/platform.rtf b/general/datasets/EPFLBXDprotHFDRPN0214/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLBXDprotHFDRPN0214/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLBXDprotHFDRPN0214/summary.rtf b/general/datasets/EPFLBXDprotHFDRPN0214/summary.rtf
deleted file mode 100644
index 8797309..0000000
--- a/general/datasets/EPFLBXDprotHFDRPN0214/summary.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
-
-Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
-
-Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/EPFLBXDprotHFDRPN0214/tissue.rtf b/general/datasets/EPFLBXDprotHFDRPN0214/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLBXDprotHFDRPN0214/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLBXDprotRPN0513/cases.rtf b/general/datasets/EPFLBXDprotRPN0513/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLBXDprotRPN0513/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLBXDprotRPN0513/notes.rtf b/general/datasets/EPFLBXDprotRPN0513/notes.rtf
deleted file mode 100644
index ecdae60..0000000
--- a/general/datasets/EPFLBXDprotRPN0513/notes.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-SWATH
-
-SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
-
-The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
-
-In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
-
-References
-
-
- - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
- - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
- - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
- - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
-
diff --git a/general/datasets/EPFLBXDprotRPN0513/platform.rtf b/general/datasets/EPFLBXDprotRPN0513/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLBXDprotRPN0513/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLBXDprotRPN0513/summary.rtf b/general/datasets/EPFLBXDprotRPN0513/summary.rtf
deleted file mode 100644
index 8797309..0000000
--- a/general/datasets/EPFLBXDprotRPN0513/summary.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
-
-Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
-
-Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/EPFLBXDprotRPN0513/tissue.rtf b/general/datasets/EPFLBXDprotRPN0513/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLBXDprotRPN0513/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLETHZBXDprotCD0514/notes.rtf b/general/datasets/EPFLETHZBXDprotCD0514/notes.rtf
deleted file mode 100644
index ecdae60..0000000
--- a/general/datasets/EPFLETHZBXDprotCD0514/notes.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-SWATH
-
-SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
-
-The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
-
-In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
-
-References
-
-
- - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
- - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
- - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
- - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
-
diff --git a/general/datasets/EPFLETHZBXDprotCD_LS1114/notes.rtf b/general/datasets/EPFLETHZBXDprotCD_LS1114/notes.rtf
deleted file mode 100644
index ecdae60..0000000
--- a/general/datasets/EPFLETHZBXDprotCD_LS1114/notes.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-SWATH
-
-SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
-
-The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
-
-In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
-
-References
-
-
- - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
- - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
- - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
- - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
-
diff --git a/general/datasets/EPFLETHZBXDprotHFD0514/notes.rtf b/general/datasets/EPFLETHZBXDprotHFD0514/notes.rtf
deleted file mode 100644
index ecdae60..0000000
--- a/general/datasets/EPFLETHZBXDprotHFD0514/notes.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-SWATH
-
-SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
-
-The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
-
-In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
-
-References
-
-
- - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
- - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
- - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
- - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
-
diff --git a/general/datasets/EPFLETHZBXDprotHF_LS1114/notes.rtf b/general/datasets/EPFLETHZBXDprotHF_LS1114/notes.rtf
deleted file mode 100644
index ecdae60..0000000
--- a/general/datasets/EPFLETHZBXDprotHF_LS1114/notes.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-SWATH
-
-SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
-
-The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
-
-In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
-
-References
-
-
- - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
- - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
- - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
- - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
-
diff --git a/general/datasets/EPFLMouseLiverBothExRMA0413/acknowledgment.rtf b/general/datasets/EPFLMouseLiverBothExRMA0413/acknowledgment.rtf
deleted file mode 100644
index 3a26b41..0000000
--- a/general/datasets/EPFLMouseLiverBothExRMA0413/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/EPFLMouseLiverBothExRMA0413/cases.rtf b/general/datasets/EPFLMouseLiverBothExRMA0413/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLMouseLiverBothExRMA0413/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLMouseLiverBothExRMA0413/platform.rtf b/general/datasets/EPFLMouseLiverBothExRMA0413/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLMouseLiverBothExRMA0413/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLMouseLiverBothExRMA0413/processing.rtf b/general/datasets/EPFLMouseLiverBothExRMA0413/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFLMouseLiverBothExRMA0413/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFLMouseLiverBothExRMA0413/summary.rtf b/general/datasets/EPFLMouseLiverBothExRMA0413/summary.rtf
deleted file mode 100644
index 77c5606..0000000
--- a/general/datasets/EPFLMouseLiverBothExRMA0413/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/EPFLMouseLiverBothExRMA0413/tissue.rtf b/general/datasets/EPFLMouseLiverBothExRMA0413/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLMouseLiverBothExRMA0413/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLMouseLiverCDEx0413/acknowledgment.rtf b/general/datasets/EPFLMouseLiverCDEx0413/acknowledgment.rtf
deleted file mode 100644
index 3a26b41..0000000
--- a/general/datasets/EPFLMouseLiverCDEx0413/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/EPFLMouseLiverCDEx0413/cases.rtf b/general/datasets/EPFLMouseLiverCDEx0413/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLMouseLiverCDEx0413/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLMouseLiverCDEx0413/platform.rtf b/general/datasets/EPFLMouseLiverCDEx0413/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLMouseLiverCDEx0413/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLMouseLiverCDEx0413/processing.rtf b/general/datasets/EPFLMouseLiverCDEx0413/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFLMouseLiverCDEx0413/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFLMouseLiverCDEx0413/specifics.rtf b/general/datasets/EPFLMouseLiverCDEx0413/specifics.rtf
deleted file mode 100644
index 7c1a914..0000000
--- a/general/datasets/EPFLMouseLiverCDEx0413/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Exon Level
\ No newline at end of file
diff --git a/general/datasets/EPFLMouseLiverCDEx0413/summary.rtf b/general/datasets/EPFLMouseLiverCDEx0413/summary.rtf
deleted file mode 100644
index 77c5606..0000000
--- a/general/datasets/EPFLMouseLiverCDEx0413/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/EPFLMouseLiverCDEx0413/tissue.rtf b/general/datasets/EPFLMouseLiverCDEx0413/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLMouseLiverCDEx0413/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLMouseLiverCDHFDRMA0818/acknowledgment.rtf b/general/datasets/EPFLMouseLiverCDHFDRMA0818/acknowledgment.rtf
deleted file mode 100644
index 3a26b41..0000000
--- a/general/datasets/EPFLMouseLiverCDHFDRMA0818/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/EPFLMouseLiverCDHFDRMA0818/cases.rtf b/general/datasets/EPFLMouseLiverCDHFDRMA0818/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLMouseLiverCDHFDRMA0818/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLMouseLiverCDHFDRMA0818/platform.rtf b/general/datasets/EPFLMouseLiverCDHFDRMA0818/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLMouseLiverCDHFDRMA0818/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLMouseLiverCDHFDRMA0818/processing.rtf b/general/datasets/EPFLMouseLiverCDHFDRMA0818/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFLMouseLiverCDHFDRMA0818/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFLMouseLiverCDHFDRMA0818/specifics.rtf b/general/datasets/EPFLMouseLiverCDHFDRMA0818/specifics.rtf
deleted file mode 100644
index 7bcb4de..0000000
--- a/general/datasets/EPFLMouseLiverCDHFDRMA0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-RMA Normalization CD + HFD combined
\ No newline at end of file
diff --git a/general/datasets/EPFLMouseLiverCDHFDRMA0818/summary.rtf b/general/datasets/EPFLMouseLiverCDHFDRMA0818/summary.rtf
deleted file mode 100644
index 77c5606..0000000
--- a/general/datasets/EPFLMouseLiverCDHFDRMA0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/EPFLMouseLiverCDHFDRMA0818/tissue.rtf b/general/datasets/EPFLMouseLiverCDHFDRMA0818/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLMouseLiverCDHFDRMA0818/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLMouseLiverCDRMA0413/acknowledgment.rtf b/general/datasets/EPFLMouseLiverCDRMA0413/acknowledgment.rtf
deleted file mode 100644
index 3a26b41..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0413/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/EPFLMouseLiverCDRMA0413/cases.rtf b/general/datasets/EPFLMouseLiverCDRMA0413/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0413/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLMouseLiverCDRMA0413/platform.rtf b/general/datasets/EPFLMouseLiverCDRMA0413/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0413/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLMouseLiverCDRMA0413/processing.rtf b/general/datasets/EPFLMouseLiverCDRMA0413/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0413/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFLMouseLiverCDRMA0413/summary.rtf b/general/datasets/EPFLMouseLiverCDRMA0413/summary.rtf
deleted file mode 100644
index 77c5606..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0413/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/EPFLMouseLiverCDRMA0413/tissue.rtf b/general/datasets/EPFLMouseLiverCDRMA0413/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0413/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLMouseLiverCDRMA0818/acknowledgment.rtf b/general/datasets/EPFLMouseLiverCDRMA0818/acknowledgment.rtf
deleted file mode 100644
index 3a26b41..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0818/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/EPFLMouseLiverCDRMA0818/cases.rtf b/general/datasets/EPFLMouseLiverCDRMA0818/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0818/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLMouseLiverCDRMA0818/platform.rtf b/general/datasets/EPFLMouseLiverCDRMA0818/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0818/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLMouseLiverCDRMA0818/processing.rtf b/general/datasets/EPFLMouseLiverCDRMA0818/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0818/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFLMouseLiverCDRMA0818/specifics.rtf b/general/datasets/EPFLMouseLiverCDRMA0818/specifics.rtf
deleted file mode 100644
index 8e24baa..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-original rma normalization CD + HFD combined
diff --git a/general/datasets/EPFLMouseLiverCDRMA0818/summary.rtf b/general/datasets/EPFLMouseLiverCDRMA0818/summary.rtf
deleted file mode 100644
index 77c5606..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/EPFLMouseLiverCDRMA0818/tissue.rtf b/general/datasets/EPFLMouseLiverCDRMA0818/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLMouseLiverCDRMA0818/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLMouseLiverHFCEx0413/acknowledgment.rtf b/general/datasets/EPFLMouseLiverHFCEx0413/acknowledgment.rtf
deleted file mode 100644
index 3a26b41..0000000
--- a/general/datasets/EPFLMouseLiverHFCEx0413/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/EPFLMouseLiverHFCEx0413/cases.rtf b/general/datasets/EPFLMouseLiverHFCEx0413/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLMouseLiverHFCEx0413/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLMouseLiverHFCEx0413/platform.rtf b/general/datasets/EPFLMouseLiverHFCEx0413/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLMouseLiverHFCEx0413/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLMouseLiverHFCEx0413/processing.rtf b/general/datasets/EPFLMouseLiverHFCEx0413/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFLMouseLiverHFCEx0413/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFLMouseLiverHFCEx0413/specifics.rtf b/general/datasets/EPFLMouseLiverHFCEx0413/specifics.rtf
deleted file mode 100644
index 7c1a914..0000000
--- a/general/datasets/EPFLMouseLiverHFCEx0413/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Exon Level
\ No newline at end of file
diff --git a/general/datasets/EPFLMouseLiverHFCEx0413/summary.rtf b/general/datasets/EPFLMouseLiverHFCEx0413/summary.rtf
deleted file mode 100644
index 77c5606..0000000
--- a/general/datasets/EPFLMouseLiverHFCEx0413/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/EPFLMouseLiverHFCEx0413/tissue.rtf b/general/datasets/EPFLMouseLiverHFCEx0413/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLMouseLiverHFCEx0413/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0413/acknowledgment.rtf b/general/datasets/EPFLMouseLiverHFDRMA0413/acknowledgment.rtf
deleted file mode 100644
index 3a26b41..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0413/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0413/cases.rtf b/general/datasets/EPFLMouseLiverHFDRMA0413/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0413/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0413/platform.rtf b/general/datasets/EPFLMouseLiverHFDRMA0413/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0413/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0413/processing.rtf b/general/datasets/EPFLMouseLiverHFDRMA0413/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0413/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0413/specifics.rtf b/general/datasets/EPFLMouseLiverHFDRMA0413/specifics.rtf
deleted file mode 100644
index 9f581ab..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0413/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-High Fat Diet Only
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0413/summary.rtf b/general/datasets/EPFLMouseLiverHFDRMA0413/summary.rtf
deleted file mode 100644
index 77c5606..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0413/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0413/tissue.rtf b/general/datasets/EPFLMouseLiverHFDRMA0413/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0413/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0818/acknowledgment.rtf b/general/datasets/EPFLMouseLiverHFDRMA0818/acknowledgment.rtf
deleted file mode 100644
index 3a26b41..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0818/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0818/cases.rtf b/general/datasets/EPFLMouseLiverHFDRMA0818/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0818/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0818/platform.rtf b/general/datasets/EPFLMouseLiverHFDRMA0818/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0818/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0818/processing.rtf b/general/datasets/EPFLMouseLiverHFDRMA0818/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0818/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0818/specifics.rtf b/general/datasets/EPFLMouseLiverHFDRMA0818/specifics.rtf
deleted file mode 100644
index 521f92a..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0818/specifics.rtf
+++ /dev/null
@@ -1,65 +0,0 @@
-HFD strain assignment errors to be fixed March 2019
-
-original rma normalization CD + HFD combined
-
-David Ashbrook analyzed strain assignment errors in March 2019. "I've more than doubled the number of markers up to 33, and can be pretty confident that a number of strains are labelled incorrectly, and what strains they should be. I've included a '?' if I'm not confident, or if I couldn't find a good match."
-
-BXD100?
-
-BXD51 > BXD55
-
-BXD55 > BXD51
-
-BXD63 > BXD43
-
-BXD73 > BXD79?
-
-BXD73a > BXD83
-
-BXD75 > BXD73a
-
-BXD79 > BXD81
-
-BXD81 > BXD84
-
-BXD83 > BXD85
-
-BXD84 > BXD87
-
-BXD85? > BXD89
-
-BXD87 > BXD90?
-
-BXD89 > BXD95
-
-BXD90 > BXD73
-
-BXD95 > BXD75
-
-
-
-
-
-I will try and add a few more markers to try and clear up the last few, but this hopefully gives you an idea of the extent of the problem. It also agrees with the strains that Rob highlighted as potential outliers in his e-mail.
-
-
-
-Best,
-
-David
-
-
-
-
-
-David Ashbrook, PhD
-Postdoctoral Fellow
-
-Department of Genetics, Genomics and Informatics
-Translational Science Research Building, Room 415
-University of Tennessee Health Science Center
-71 S Manassas St
-Memphis, TN, 38103
-
-https://davidashbrook.wordpress.com/
-dashbrook@uthsc.edu
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0818/summary.rtf b/general/datasets/EPFLMouseLiverHFDRMA0818/summary.rtf
deleted file mode 100644
index 77c5606..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/EPFLMouseLiverHFDRMA0818/tissue.rtf b/general/datasets/EPFLMouseLiverHFDRMA0818/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLMouseLiverHFDRMA0818/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLMouseLiverRMA0413/acknowledgment.rtf b/general/datasets/EPFLMouseLiverRMA0413/acknowledgment.rtf
deleted file mode 100644
index 3a26b41..0000000
--- a/general/datasets/EPFLMouseLiverRMA0413/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/EPFLMouseLiverRMA0413/cases.rtf b/general/datasets/EPFLMouseLiverRMA0413/cases.rtf
deleted file mode 100644
index ed4ced8..0000000
--- a/general/datasets/EPFLMouseLiverRMA0413/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/EPFLMouseLiverRMA0413/platform.rtf b/general/datasets/EPFLMouseLiverRMA0413/platform.rtf
deleted file mode 100644
index 4a33b7c..0000000
--- a/general/datasets/EPFLMouseLiverRMA0413/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFLMouseLiverRMA0413/processing.rtf b/general/datasets/EPFLMouseLiverRMA0413/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFLMouseLiverRMA0413/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFLMouseLiverRMA0413/summary.rtf b/general/datasets/EPFLMouseLiverRMA0413/summary.rtf
deleted file mode 100644
index 77c5606..0000000
--- a/general/datasets/EPFLMouseLiverRMA0413/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/EPFLMouseLiverRMA0413/tissue.rtf b/general/datasets/EPFLMouseLiverRMA0413/tissue.rtf
deleted file mode 100644
index f95e2c4..0000000
--- a/general/datasets/EPFLMouseLiverRMA0413/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFLMouseMuscleCDRMAEx1112/summary.rtf b/general/datasets/EPFLMouseMuscleCDRMAEx1112/summary.rtf
deleted file mode 100644
index e63dd95..0000000
--- a/general/datasets/EPFLMouseMuscleCDRMAEx1112/summary.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-Highlights
-
-
- - Inhibition of poly(ADP-ribose) polymerases (PARPs) enhances endurance performance
- - Inhibition of PARPs improves mitochondrial function in skeletal muscle
- - Parp-1 correlates with energy expenditure in heterogeneous mouse populations
- - Genetic and acquired mitochondrial defects can be rescued by PARP inhibition
-
-
-We previously demonstrated that the deletion of the poly(ADP-ribose)polymerase (Parp)-1 gene in mice enhances oxidative metabolism, thereby protecting against diet-induced obesity. However, the therapeutic use of PARP inhibitors to enhance mitochondrial function remains to be explored. Here, we show tight negative correlation between Parp-1 expression and energy expenditure in heterogeneous mouse populations, indicating that variations in PARP-1 activity have an impact on metabolic homeostasis. Notably, these genetic correlations can be translated into pharmacological applications. Long-term treatment with PARP inhibitors enhances fitness in mice by increasing the abundance of mitochondrial respiratory complexes and boosting mitochondrial respiratory capacity. Furthermore, PARP inhibitors reverse mitochondrial defects in primary myotubes of obese humans and attenuate genetic defects of mitochondrial metabolism in human fibroblasts and C. elegans. Overall, our work validates in worm, mouse, and human models that PARP inhibition may be used to treat both genetic and acquired muscle dysfunction linked to defective mitochondrial function.
diff --git a/general/datasets/EPFLMouseMuscleCDRMAEx1112/tissue.rtf b/general/datasets/EPFLMouseMuscleCDRMAEx1112/tissue.rtf
deleted file mode 100644
index c40574c..0000000
--- a/general/datasets/EPFLMouseMuscleCDRMAEx1112/tissue.rtf
+++ /dev/null
@@ -1,25 +0,0 @@
-
-
-
-
- The muscle datasets are all generated from quadriceps muscles. These animals were born, raised, phenotyped, and sacrificed at the EPFL in the group of Johan Auwerx. Animals were all approximately 29 weeks of age and were all male. Chow diet cohorts ("CD") were fed Harlan 2018 (6% kcal/fat, 20% protein, 74% carbohydrate). High fat diet ("HFD") cohorts were fed Harlan 06414 (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. After an overnight fasting and isoflurane anesthesia, animals were sacrificed following a blood draw and perfusion. Quadriceps were cut horizontally from the femur bone and then frozen in liquid nitrogen for an extended period. Cohorts were sacrificed in a staggered fashion, with approximately 1 cohort per week over a period of 2-3 years. mRNA was prepared for the quadriceps in two distinct batches approximately one year apart (Batch 1: late spring 2011; Batch 2: late spring 2012). Microarrays were run on the samples in two distinct batches shortly after being prepared and received.
-
-
-
- Batch 1 is the following cohorts: C57HFD 100HFD 62HFD 83CD C57CD 70CD 75CD 96CD 44HFD 45CD 61HFD 73CD DBACD 45HFD 63CD 87CD 89CD 90HFD 62CD 75HFD DBAHFD 44CD 66CD 87HFD 66HFD 55HFD 55CD 70HFD 51CD 83HFD 80CD 51HFD 73HFD 96HFD 61CD 90CD 80HFD 63HFD
-
-
-
- Batch 2 is the following cohorts: 49HFD 43CD 50CD 89HFD 84CD 100CD 81HFD 98HFD 103CD 68CD 79CD 99CD 71CD 48HFD 64HFD 84HFD 101CD 103HFD 60CD 79HFD 68HFD 48CD 71HFD 65CD 85HFD 99HFD 81CD 49CD 56HFD 97CD 97HFD 92CD 69CD 64CD 69HFD 56CD 65HFD 43HFD 85CD 95CD 98CD
-
-
-
- For all cohorts in these datasets, roughly 2-5 animals (typically around 4) had mRNA extracted separately, and then mRNA were pooled equally for each individual in a cohort. After the mRNA were pooled for the individuals within a cohort—a cohort meaning the same diet, sex, strain, and littermate—the samples were purified using RNEasy.
-
-
-
- Once both cohorts were completed, the two batches were re-normalized together using RMAExpress and the two batches were logged and z-normalized. The mean was set to 8 units and standard deviation was set to 2 units for all samples. This removes negative values from the samples, and reduces the batch effect between the two groups.
- |
-
-
-
diff --git a/general/datasets/EPFLMouseMuscleHFDRMAEx1112/summary.rtf b/general/datasets/EPFLMouseMuscleHFDRMAEx1112/summary.rtf
deleted file mode 100644
index e63dd95..0000000
--- a/general/datasets/EPFLMouseMuscleHFDRMAEx1112/summary.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-Highlights
-
-
- - Inhibition of poly(ADP-ribose) polymerases (PARPs) enhances endurance performance
- - Inhibition of PARPs improves mitochondrial function in skeletal muscle
- - Parp-1 correlates with energy expenditure in heterogeneous mouse populations
- - Genetic and acquired mitochondrial defects can be rescued by PARP inhibition
-
-
-We previously demonstrated that the deletion of the poly(ADP-ribose)polymerase (Parp)-1 gene in mice enhances oxidative metabolism, thereby protecting against diet-induced obesity. However, the therapeutic use of PARP inhibitors to enhance mitochondrial function remains to be explored. Here, we show tight negative correlation between Parp-1 expression and energy expenditure in heterogeneous mouse populations, indicating that variations in PARP-1 activity have an impact on metabolic homeostasis. Notably, these genetic correlations can be translated into pharmacological applications. Long-term treatment with PARP inhibitors enhances fitness in mice by increasing the abundance of mitochondrial respiratory complexes and boosting mitochondrial respiratory capacity. Furthermore, PARP inhibitors reverse mitochondrial defects in primary myotubes of obese humans and attenuate genetic defects of mitochondrial metabolism in human fibroblasts and C. elegans. Overall, our work validates in worm, mouse, and human models that PARP inhibition may be used to treat both genetic and acquired muscle dysfunction linked to defective mitochondrial function.
diff --git a/general/datasets/EPFLMouseMuscleHFDRMAEx1112/tissue.rtf b/general/datasets/EPFLMouseMuscleHFDRMAEx1112/tissue.rtf
deleted file mode 100644
index c40574c..0000000
--- a/general/datasets/EPFLMouseMuscleHFDRMAEx1112/tissue.rtf
+++ /dev/null
@@ -1,25 +0,0 @@
-
-
-
-
- The muscle datasets are all generated from quadriceps muscles. These animals were born, raised, phenotyped, and sacrificed at the EPFL in the group of Johan Auwerx. Animals were all approximately 29 weeks of age and were all male. Chow diet cohorts ("CD") were fed Harlan 2018 (6% kcal/fat, 20% protein, 74% carbohydrate). High fat diet ("HFD") cohorts were fed Harlan 06414 (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. After an overnight fasting and isoflurane anesthesia, animals were sacrificed following a blood draw and perfusion. Quadriceps were cut horizontally from the femur bone and then frozen in liquid nitrogen for an extended period. Cohorts were sacrificed in a staggered fashion, with approximately 1 cohort per week over a period of 2-3 years. mRNA was prepared for the quadriceps in two distinct batches approximately one year apart (Batch 1: late spring 2011; Batch 2: late spring 2012). Microarrays were run on the samples in two distinct batches shortly after being prepared and received.
-
-
-
- Batch 1 is the following cohorts: C57HFD 100HFD 62HFD 83CD C57CD 70CD 75CD 96CD 44HFD 45CD 61HFD 73CD DBACD 45HFD 63CD 87CD 89CD 90HFD 62CD 75HFD DBAHFD 44CD 66CD 87HFD 66HFD 55HFD 55CD 70HFD 51CD 83HFD 80CD 51HFD 73HFD 96HFD 61CD 90CD 80HFD 63HFD
-
-
-
- Batch 2 is the following cohorts: 49HFD 43CD 50CD 89HFD 84CD 100CD 81HFD 98HFD 103CD 68CD 79CD 99CD 71CD 48HFD 64HFD 84HFD 101CD 103HFD 60CD 79HFD 68HFD 48CD 71HFD 65CD 85HFD 99HFD 81CD 49CD 56HFD 97CD 97HFD 92CD 69CD 64CD 69HFD 56CD 65HFD 43HFD 85CD 95CD 98CD
-
-
-
- For all cohorts in these datasets, roughly 2-5 animals (typically around 4) had mRNA extracted separately, and then mRNA were pooled equally for each individual in a cohort. After the mRNA were pooled for the individuals within a cohort—a cohort meaning the same diet, sex, strain, and littermate—the samples were purified using RNEasy.
-
-
-
- Once both cohorts were completed, the two batches were re-normalized together using RMAExpress and the two batches were logged and z-normalized. The mean was set to 8 units and standard deviation was set to 2 units for all samples. This removes negative values from the samples, and reduces the batch effect between the two groups.
- |
-
-
-
diff --git a/general/datasets/EPFL_AdiMitPro0416/summary.rtf b/general/datasets/EPFL_AdiMitPro0416/summary.rtf
deleted file mode 100644
index 18527b0..0000000
--- a/general/datasets/EPFL_AdiMitPro0416/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Currently these datasets are private, please refer to the contact information if you want to use this data set.
diff --git a/general/datasets/EPFL_AdiPro0416/summary.rtf b/general/datasets/EPFL_AdiPro0416/summary.rtf
deleted file mode 100644
index 18527b0..0000000
--- a/general/datasets/EPFL_AdiPro0416/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Currently these datasets are private, please refer to the contact information if you want to use this data set.
diff --git a/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_CD_1119/specifics.rtf b/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_CD_1119/specifics.rtf
deleted file mode 100644
index c1ddd29..0000000
--- a/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_CD_1119/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-CD
\ No newline at end of file
diff --git a/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_CD_1119/summary.rtf b/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_CD_1119/summary.rtf
deleted file mode 100644
index c443a46..0000000
--- a/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_CD_1119/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-EPFL/ETHZ BXD Liver Proteome CD-HFD (Nov19)
diff --git a/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_CD_HF_1119/specifics.rtf b/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_CD_HF_1119/specifics.rtf
deleted file mode 100644
index 107347f..0000000
--- a/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_CD_HF_1119/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-CD + HFD
\ No newline at end of file
diff --git a/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_CD_HF_1119/summary.rtf b/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_CD_HF_1119/summary.rtf
deleted file mode 100644
index c443a46..0000000
--- a/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_CD_HF_1119/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-EPFL/ETHZ BXD Liver Proteome CD-HFD (Nov19)
diff --git a/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_HFD_1119/specifics.rtf b/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_HFD_1119/specifics.rtf
deleted file mode 100644
index 0ba1ca4..0000000
--- a/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_HFD_1119/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HFD
\ No newline at end of file
diff --git a/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_HFD_1119/summary.rtf b/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_HFD_1119/summary.rtf
deleted file mode 100644
index c443a46..0000000
--- a/general/datasets/EPFL_ETHZ_BXD_LivProtAvg_HFD_1119/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-EPFL/ETHZ BXD Liver Proteome CD-HFD (Nov19)
diff --git a/general/datasets/EPFL_ETHZ_BXD_LivProtCD_HF_1119/specifics.rtf b/general/datasets/EPFL_ETHZ_BXD_LivProtCD_HF_1119/specifics.rtf
deleted file mode 100644
index 409654b..0000000
--- a/general/datasets/EPFL_ETHZ_BXD_LivProtCD_HF_1119/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Individual samples
\ No newline at end of file
diff --git a/general/datasets/EPFL_ETHZ_BXD_LivProtCD_HF_1119/summary.rtf b/general/datasets/EPFL_ETHZ_BXD_LivProtCD_HF_1119/summary.rtf
deleted file mode 100644
index c443a46..0000000
--- a/general/datasets/EPFL_ETHZ_BXD_LivProtCD_HF_1119/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-EPFL/ETHZ BXD Liver Proteome CD-HFD (Nov19)
diff --git a/general/datasets/EPFL_LISPBXDHeCD0114/acknowledgment.rtf b/general/datasets/EPFL_LISPBXDHeCD0114/acknowledgment.rtf
deleted file mode 100644
index 91d3c6b..0000000
--- a/general/datasets/EPFL_LISPBXDHeCD0114/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
diff --git a/general/datasets/EPFL_LISPBXDHeCD0114/cases.rtf b/general/datasets/EPFL_LISPBXDHeCD0114/cases.rtf
deleted file mode 100644
index d43280d..0000000
--- a/general/datasets/EPFL_LISPBXDHeCD0114/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Hearts were taken immediately after perfusion of the animal, weighed, and then frozen in liquid nitrogen no more than a minute after sacrifice.
diff --git a/general/datasets/EPFL_LISPBXDHeCD0114/experiment-design.rtf b/general/datasets/EPFL_LISPBXDHeCD0114/experiment-design.rtf
deleted file mode 100644
index 7516c73..0000000
--- a/general/datasets/EPFL_LISPBXDHeCD0114/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
diff --git a/general/datasets/EPFL_LISPBXDHeCD0114/platform.rtf b/general/datasets/EPFL_LISPBXDHeCD0114/platform.rtf
deleted file mode 100644
index ee667b4..0000000
--- a/general/datasets/EPFL_LISPBXDHeCD0114/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All arrays were Affymetrix Mouse Gene 2.0 ST, prepared and run simultaneously in a single batch in January 2014 by Lorne Rose at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFL_LISPBXDHeCD0114/processing.rtf b/general/datasets/EPFL_LISPBXDHeCD0114/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFL_LISPBXDHeCD0114/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFL_LISPBXDHeCD0114/summary.rtf b/general/datasets/EPFL_LISPBXDHeCD0114/summary.rtf
deleted file mode 100644
index 7fcc1a9..0000000
--- a/general/datasets/EPFL_LISPBXDHeCD0114/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
diff --git a/general/datasets/EPFL_LISPBXDHeCD0114/tissue.rtf b/general/datasets/EPFL_LISPBXDHeCD0114/tissue.rtf
deleted file mode 100644
index eebcb20..0000000
--- a/general/datasets/EPFL_LISPBXDHeCD0114/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Hearts were later shattered in liquid nitrogen, usually broken into 2-4 pieces, and around half of the sample (at random) was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort, thus differences due to different segments of the heart being taken should be mitigated, although not eliminated, and researchers examining extremely specific transcriptional regulation in the heart should keep this in mind. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFL_LISPBXDHeCDEx0114/acknowledgment.rtf b/general/datasets/EPFL_LISPBXDHeCDEx0114/acknowledgment.rtf
deleted file mode 100644
index 91d3c6b..0000000
--- a/general/datasets/EPFL_LISPBXDHeCDEx0114/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
diff --git a/general/datasets/EPFL_LISPBXDHeCDEx0114/cases.rtf b/general/datasets/EPFL_LISPBXDHeCDEx0114/cases.rtf
deleted file mode 100644
index d43280d..0000000
--- a/general/datasets/EPFL_LISPBXDHeCDEx0114/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Hearts were taken immediately after perfusion of the animal, weighed, and then frozen in liquid nitrogen no more than a minute after sacrifice.
diff --git a/general/datasets/EPFL_LISPBXDHeCDEx0114/experiment-design.rtf b/general/datasets/EPFL_LISPBXDHeCDEx0114/experiment-design.rtf
deleted file mode 100644
index 7516c73..0000000
--- a/general/datasets/EPFL_LISPBXDHeCDEx0114/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
diff --git a/general/datasets/EPFL_LISPBXDHeCDEx0114/platform.rtf b/general/datasets/EPFL_LISPBXDHeCDEx0114/platform.rtf
deleted file mode 100644
index ee667b4..0000000
--- a/general/datasets/EPFL_LISPBXDHeCDEx0114/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All arrays were Affymetrix Mouse Gene 2.0 ST, prepared and run simultaneously in a single batch in January 2014 by Lorne Rose at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFL_LISPBXDHeCDEx0114/processing.rtf b/general/datasets/EPFL_LISPBXDHeCDEx0114/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFL_LISPBXDHeCDEx0114/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFL_LISPBXDHeCDEx0114/summary.rtf b/general/datasets/EPFL_LISPBXDHeCDEx0114/summary.rtf
deleted file mode 100644
index 7fcc1a9..0000000
--- a/general/datasets/EPFL_LISPBXDHeCDEx0114/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
diff --git a/general/datasets/EPFL_LISPBXDHeCDEx0114/tissue.rtf b/general/datasets/EPFL_LISPBXDHeCDEx0114/tissue.rtf
deleted file mode 100644
index eebcb20..0000000
--- a/general/datasets/EPFL_LISPBXDHeCDEx0114/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Hearts were later shattered in liquid nitrogen, usually broken into 2-4 pieces, and around half of the sample (at random) was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort, thus differences due to different segments of the heart being taken should be mitigated, although not eliminated, and researchers examining extremely specific transcriptional regulation in the heart should keep this in mind. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFL_LISPBXDHeHFD0114/acknowledgment.rtf b/general/datasets/EPFL_LISPBXDHeHFD0114/acknowledgment.rtf
deleted file mode 100644
index 91d3c6b..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFD0114/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
diff --git a/general/datasets/EPFL_LISPBXDHeHFD0114/cases.rtf b/general/datasets/EPFL_LISPBXDHeHFD0114/cases.rtf
deleted file mode 100644
index d43280d..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFD0114/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Hearts were taken immediately after perfusion of the animal, weighed, and then frozen in liquid nitrogen no more than a minute after sacrifice.
diff --git a/general/datasets/EPFL_LISPBXDHeHFD0114/experiment-design.rtf b/general/datasets/EPFL_LISPBXDHeHFD0114/experiment-design.rtf
deleted file mode 100644
index 7516c73..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFD0114/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
diff --git a/general/datasets/EPFL_LISPBXDHeHFD0114/platform.rtf b/general/datasets/EPFL_LISPBXDHeHFD0114/platform.rtf
deleted file mode 100644
index ee667b4..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFD0114/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All arrays were Affymetrix Mouse Gene 2.0 ST, prepared and run simultaneously in a single batch in January 2014 by Lorne Rose at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFL_LISPBXDHeHFD0114/processing.rtf b/general/datasets/EPFL_LISPBXDHeHFD0114/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFD0114/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFL_LISPBXDHeHFD0114/summary.rtf b/general/datasets/EPFL_LISPBXDHeHFD0114/summary.rtf
deleted file mode 100644
index 7fcc1a9..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFD0114/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
diff --git a/general/datasets/EPFL_LISPBXDHeHFD0114/tissue.rtf b/general/datasets/EPFL_LISPBXDHeHFD0114/tissue.rtf
deleted file mode 100644
index eebcb20..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFD0114/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Hearts were later shattered in liquid nitrogen, usually broken into 2-4 pieces, and around half of the sample (at random) was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort, thus differences due to different segments of the heart being taken should be mitigated, although not eliminated, and researchers examining extremely specific transcriptional regulation in the heart should keep this in mind. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFL_LISPBXDHeHFDEx0114/acknowledgment.rtf b/general/datasets/EPFL_LISPBXDHeHFDEx0114/acknowledgment.rtf
deleted file mode 100644
index 91d3c6b..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFDEx0114/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
diff --git a/general/datasets/EPFL_LISPBXDHeHFDEx0114/cases.rtf b/general/datasets/EPFL_LISPBXDHeHFDEx0114/cases.rtf
deleted file mode 100644
index d43280d..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFDEx0114/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Hearts were taken immediately after perfusion of the animal, weighed, and then frozen in liquid nitrogen no more than a minute after sacrifice.
diff --git a/general/datasets/EPFL_LISPBXDHeHFDEx0114/experiment-design.rtf b/general/datasets/EPFL_LISPBXDHeHFDEx0114/experiment-design.rtf
deleted file mode 100644
index 7516c73..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFDEx0114/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
diff --git a/general/datasets/EPFL_LISPBXDHeHFDEx0114/platform.rtf b/general/datasets/EPFL_LISPBXDHeHFDEx0114/platform.rtf
deleted file mode 100644
index ee667b4..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFDEx0114/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All arrays were Affymetrix Mouse Gene 2.0 ST, prepared and run simultaneously in a single batch in January 2014 by Lorne Rose at the University of Tennessee Health Science Center.
diff --git a/general/datasets/EPFL_LISPBXDHeHFDEx0114/processing.rtf b/general/datasets/EPFL_LISPBXDHeHFDEx0114/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFDEx0114/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFL_LISPBXDHeHFDEx0114/summary.rtf b/general/datasets/EPFL_LISPBXDHeHFDEx0114/summary.rtf
deleted file mode 100644
index 7fcc1a9..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFDEx0114/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
diff --git a/general/datasets/EPFL_LISPBXDHeHFDEx0114/tissue.rtf b/general/datasets/EPFL_LISPBXDHeHFDEx0114/tissue.rtf
deleted file mode 100644
index eebcb20..0000000
--- a/general/datasets/EPFL_LISPBXDHeHFDEx0114/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Hearts were later shattered in liquid nitrogen, usually broken into 2-4 pieces, and around half of the sample (at random) was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort, thus differences due to different segments of the heart being taken should be mitigated, although not eliminated, and researchers examining extremely specific transcriptional regulation in the heart should keep this in mind. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/EPFL_LISP_BXD_Col_CD0917/specifics.rtf b/general/datasets/EPFL_LISP_BXD_Col_CD0917/specifics.rtf
deleted file mode 100644
index c1ddd29..0000000
--- a/general/datasets/EPFL_LISP_BXD_Col_CD0917/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-CD
\ No newline at end of file
diff --git a/general/datasets/EPFL_LISP_BXD_Col_CD0917/summary.rtf b/general/datasets/EPFL_LISP_BXD_Col_CD0917/summary.rtf
deleted file mode 100644
index 3ec986b..0000000
--- a/general/datasets/EPFL_LISP_BXD_Col_CD0917/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Unpublished dataset
diff --git a/general/datasets/EPFL_LISP_BXD_Col_CD_HFD0917/specifics.rtf b/general/datasets/EPFL_LISP_BXD_Col_CD_HFD0917/specifics.rtf
deleted file mode 100644
index 107347f..0000000
--- a/general/datasets/EPFL_LISP_BXD_Col_CD_HFD0917/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-CD + HFD
\ No newline at end of file
diff --git a/general/datasets/EPFL_LISP_BXD_Col_CD_HFD0917/summary.rtf b/general/datasets/EPFL_LISP_BXD_Col_CD_HFD0917/summary.rtf
deleted file mode 100644
index 3ec986b..0000000
--- a/general/datasets/EPFL_LISP_BXD_Col_CD_HFD0917/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Unpublished dataset
diff --git a/general/datasets/EPFL_LISP_BXD_Col_HFD0917/specifics.rtf b/general/datasets/EPFL_LISP_BXD_Col_HFD0917/specifics.rtf
deleted file mode 100644
index 0ba1ca4..0000000
--- a/general/datasets/EPFL_LISP_BXD_Col_HFD0917/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HFD
\ No newline at end of file
diff --git a/general/datasets/EPFL_LISP_BXD_Col_HFD0917/summary.rtf b/general/datasets/EPFL_LISP_BXD_Col_HFD0917/summary.rtf
deleted file mode 100644
index 3ec986b..0000000
--- a/general/datasets/EPFL_LISP_BXD_Col_HFD0917/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Unpublished dataset
diff --git a/general/datasets/EPFL_LISP_LivPMetCD1213/cases.rtf b/general/datasets/EPFL_LISP_LivPMetCD1213/cases.rtf
deleted file mode 100644
index 7d496bc..0000000
--- a/general/datasets/EPFL_LISP_LivPMetCD1213/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-For liver metabolites, livers were perfused, frozen in liquid nitrogen, and then shattered in liquid nitrogen with a mortar and pestle at a later date. Several pieces of shattered liver totalling ~100 milligrams were collected then homogenized in 1mL 70% Ethanol at -20°C. Metabolites were extracted by adding 7mL 70% Ethanol at 75°C for 2 min. Extracts were centrifuged for 10 minutes at 4,000 rpm at 4°C. Clean metabolites extracts were dried in a vacuum centrifuge and re-suspended in double-distilled H2O with volume according to the weight of the extracted liver piece. Quantification of metabolites was performed on an Agilent 6550 QTOF instrument by flow injection analysis time-of-flight mass spectrometry (see: PMID 21830798). All samples were injected in duplicates. Ions were annotated based on their accurate mass and the Human Metabolome Database reference list (see: PMID 23161693) allowing a tolerance of 0.001 Da. Unknown ions and those annotated as adducts were discarded. Theoretical m/z ratios—beyond the significant digits from the measurement sensitivity—are used as the unique index in the online data on GeneNetwork. For example, deprotonated fumarate corresponds to 115.0036897_MZ, malate to 133.0142794_MZ, α-ketoglutarate to 145.0141831_MZ, and D2HG to 147.0298102_MZ.
diff --git a/general/datasets/EPFL_LISP_LivPMetCD1213/processing.rtf b/general/datasets/EPFL_LISP_LivPMetCD1213/processing.rtf
deleted file mode 100644
index 671c357..0000000
--- a/general/datasets/EPFL_LISP_LivPMetCD1213/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GeneNetwork displays only the strain averages ± SEM for each metabolite. To obtain the individual data for each animal, please use the link above under (Download datasets and supplementary data files). Note that this contains two entries for each animal: these are technical replicates.
-
-The very raw spectral data from the mass spectrometer can be downloaded on MassIVE ( http://massive.ucsd.edu/ProteoSAFe/static/massive.jsp?redirect=auth ) under the identifier MSV000079411. This spectral data is for all 290 individual animals, and it includes two technical replicates for each individual, for a total of 580 runs. The file size is 102 GB and we do not recommend downloading this unless you are specifically interested in re-analyzing the spectra from scratch and looking into the granular details of mass spectrometry metabolomics.
diff --git a/general/datasets/EPFL_LISP_LivPMetCD1213/summary.rtf b/general/datasets/EPFL_LISP_LivPMetCD1213/summary.rtf
deleted file mode 100644
index 5f92c0e..0000000
--- a/general/datasets/EPFL_LISP_LivPMetCD1213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We identified 979 unique metabolite features based on mass-charge ratios (m/z) using flow-injection ToF-MS, respectively. Of these features, 699 could be attributed to a single metabolite, including in cases where of the two “possible” enantiomers, one is clearly far more predominant than the other (e.g. L versus D amino acids). The remaining 280 metabolites were “clusters” with no clear predominant feature—for example, the “glucose” metabolite measurements could not be separated from fructose, galactose, or mannose measurements, as all share the same m/z. The “main” metabolite, as well as all possible alternatives are listed with the data on GeneNetwork.org for the raw file download (press the “INFO” button next to the dataset on the main search page and download the dataset and supplemental data files).
diff --git a/general/datasets/EPFL_LISP_LivPMetCDHFD1213/cases.rtf b/general/datasets/EPFL_LISP_LivPMetCDHFD1213/cases.rtf
deleted file mode 100644
index 7d496bc..0000000
--- a/general/datasets/EPFL_LISP_LivPMetCDHFD1213/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-For liver metabolites, livers were perfused, frozen in liquid nitrogen, and then shattered in liquid nitrogen with a mortar and pestle at a later date. Several pieces of shattered liver totalling ~100 milligrams were collected then homogenized in 1mL 70% Ethanol at -20°C. Metabolites were extracted by adding 7mL 70% Ethanol at 75°C for 2 min. Extracts were centrifuged for 10 minutes at 4,000 rpm at 4°C. Clean metabolites extracts were dried in a vacuum centrifuge and re-suspended in double-distilled H2O with volume according to the weight of the extracted liver piece. Quantification of metabolites was performed on an Agilent 6550 QTOF instrument by flow injection analysis time-of-flight mass spectrometry (see: PMID 21830798). All samples were injected in duplicates. Ions were annotated based on their accurate mass and the Human Metabolome Database reference list (see: PMID 23161693) allowing a tolerance of 0.001 Da. Unknown ions and those annotated as adducts were discarded. Theoretical m/z ratios—beyond the significant digits from the measurement sensitivity—are used as the unique index in the online data on GeneNetwork. For example, deprotonated fumarate corresponds to 115.0036897_MZ, malate to 133.0142794_MZ, α-ketoglutarate to 145.0141831_MZ, and D2HG to 147.0298102_MZ.
diff --git a/general/datasets/EPFL_LISP_LivPMetCDHFD1213/processing.rtf b/general/datasets/EPFL_LISP_LivPMetCDHFD1213/processing.rtf
deleted file mode 100644
index 671c357..0000000
--- a/general/datasets/EPFL_LISP_LivPMetCDHFD1213/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GeneNetwork displays only the strain averages ± SEM for each metabolite. To obtain the individual data for each animal, please use the link above under (Download datasets and supplementary data files). Note that this contains two entries for each animal: these are technical replicates.
-
-The very raw spectral data from the mass spectrometer can be downloaded on MassIVE ( http://massive.ucsd.edu/ProteoSAFe/static/massive.jsp?redirect=auth ) under the identifier MSV000079411. This spectral data is for all 290 individual animals, and it includes two technical replicates for each individual, for a total of 580 runs. The file size is 102 GB and we do not recommend downloading this unless you are specifically interested in re-analyzing the spectra from scratch and looking into the granular details of mass spectrometry metabolomics.
diff --git a/general/datasets/EPFL_LISP_LivPMetCDHFD1213/summary.rtf b/general/datasets/EPFL_LISP_LivPMetCDHFD1213/summary.rtf
deleted file mode 100644
index 5f92c0e..0000000
--- a/general/datasets/EPFL_LISP_LivPMetCDHFD1213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We identified 979 unique metabolite features based on mass-charge ratios (m/z) using flow-injection ToF-MS, respectively. Of these features, 699 could be attributed to a single metabolite, including in cases where of the two “possible” enantiomers, one is clearly far more predominant than the other (e.g. L versus D amino acids). The remaining 280 metabolites were “clusters” with no clear predominant feature—for example, the “glucose” metabolite measurements could not be separated from fructose, galactose, or mannose measurements, as all share the same m/z. The “main” metabolite, as well as all possible alternatives are listed with the data on GeneNetwork.org for the raw file download (press the “INFO” button next to the dataset on the main search page and download the dataset and supplemental data files).
diff --git a/general/datasets/EPFL_LISP_LivPMetHFD1213/cases.rtf b/general/datasets/EPFL_LISP_LivPMetHFD1213/cases.rtf
deleted file mode 100644
index 7d496bc..0000000
--- a/general/datasets/EPFL_LISP_LivPMetHFD1213/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-For liver metabolites, livers were perfused, frozen in liquid nitrogen, and then shattered in liquid nitrogen with a mortar and pestle at a later date. Several pieces of shattered liver totalling ~100 milligrams were collected then homogenized in 1mL 70% Ethanol at -20°C. Metabolites were extracted by adding 7mL 70% Ethanol at 75°C for 2 min. Extracts were centrifuged for 10 minutes at 4,000 rpm at 4°C. Clean metabolites extracts were dried in a vacuum centrifuge and re-suspended in double-distilled H2O with volume according to the weight of the extracted liver piece. Quantification of metabolites was performed on an Agilent 6550 QTOF instrument by flow injection analysis time-of-flight mass spectrometry (see: PMID 21830798). All samples were injected in duplicates. Ions were annotated based on their accurate mass and the Human Metabolome Database reference list (see: PMID 23161693) allowing a tolerance of 0.001 Da. Unknown ions and those annotated as adducts were discarded. Theoretical m/z ratios—beyond the significant digits from the measurement sensitivity—are used as the unique index in the online data on GeneNetwork. For example, deprotonated fumarate corresponds to 115.0036897_MZ, malate to 133.0142794_MZ, α-ketoglutarate to 145.0141831_MZ, and D2HG to 147.0298102_MZ.
diff --git a/general/datasets/EPFL_LISP_LivPMetHFD1213/processing.rtf b/general/datasets/EPFL_LISP_LivPMetHFD1213/processing.rtf
deleted file mode 100644
index 671c357..0000000
--- a/general/datasets/EPFL_LISP_LivPMetHFD1213/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GeneNetwork displays only the strain averages ± SEM for each metabolite. To obtain the individual data for each animal, please use the link above under (Download datasets and supplementary data files). Note that this contains two entries for each animal: these are technical replicates.
-
-The very raw spectral data from the mass spectrometer can be downloaded on MassIVE ( http://massive.ucsd.edu/ProteoSAFe/static/massive.jsp?redirect=auth ) under the identifier MSV000079411. This spectral data is for all 290 individual animals, and it includes two technical replicates for each individual, for a total of 580 runs. The file size is 102 GB and we do not recommend downloading this unless you are specifically interested in re-analyzing the spectra from scratch and looking into the granular details of mass spectrometry metabolomics.
diff --git a/general/datasets/EPFL_LISP_LivPMetHFD1213/summary.rtf b/general/datasets/EPFL_LISP_LivPMetHFD1213/summary.rtf
deleted file mode 100644
index 5f92c0e..0000000
--- a/general/datasets/EPFL_LISP_LivPMetHFD1213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We identified 979 unique metabolite features based on mass-charge ratios (m/z) using flow-injection ToF-MS, respectively. Of these features, 699 could be attributed to a single metabolite, including in cases where of the two “possible” enantiomers, one is clearly far more predominant than the other (e.g. L versus D amino acids). The remaining 280 metabolites were “clusters” with no clear predominant feature—for example, the “glucose” metabolite measurements could not be separated from fructose, galactose, or mannose measurements, as all share the same m/z. The “main” metabolite, as well as all possible alternatives are listed with the data on GeneNetwork.org for the raw file download (press the “INFO” button next to the dataset on the main search page and download the dataset and supplemental data files).
diff --git a/general/datasets/EPFL_LISP_LivPMetlog2CD1213/cases.rtf b/general/datasets/EPFL_LISP_LivPMetlog2CD1213/cases.rtf
deleted file mode 100644
index 7d496bc..0000000
--- a/general/datasets/EPFL_LISP_LivPMetlog2CD1213/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-For liver metabolites, livers were perfused, frozen in liquid nitrogen, and then shattered in liquid nitrogen with a mortar and pestle at a later date. Several pieces of shattered liver totalling ~100 milligrams were collected then homogenized in 1mL 70% Ethanol at -20°C. Metabolites were extracted by adding 7mL 70% Ethanol at 75°C for 2 min. Extracts were centrifuged for 10 minutes at 4,000 rpm at 4°C. Clean metabolites extracts were dried in a vacuum centrifuge and re-suspended in double-distilled H2O with volume according to the weight of the extracted liver piece. Quantification of metabolites was performed on an Agilent 6550 QTOF instrument by flow injection analysis time-of-flight mass spectrometry (see: PMID 21830798). All samples were injected in duplicates. Ions were annotated based on their accurate mass and the Human Metabolome Database reference list (see: PMID 23161693) allowing a tolerance of 0.001 Da. Unknown ions and those annotated as adducts were discarded. Theoretical m/z ratios—beyond the significant digits from the measurement sensitivity—are used as the unique index in the online data on GeneNetwork. For example, deprotonated fumarate corresponds to 115.0036897_MZ, malate to 133.0142794_MZ, α-ketoglutarate to 145.0141831_MZ, and D2HG to 147.0298102_MZ.
diff --git a/general/datasets/EPFL_LISP_LivPMetlog2CD1213/processing.rtf b/general/datasets/EPFL_LISP_LivPMetlog2CD1213/processing.rtf
deleted file mode 100644
index 671c357..0000000
--- a/general/datasets/EPFL_LISP_LivPMetlog2CD1213/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GeneNetwork displays only the strain averages ± SEM for each metabolite. To obtain the individual data for each animal, please use the link above under (Download datasets and supplementary data files). Note that this contains two entries for each animal: these are technical replicates.
-
-The very raw spectral data from the mass spectrometer can be downloaded on MassIVE ( http://massive.ucsd.edu/ProteoSAFe/static/massive.jsp?redirect=auth ) under the identifier MSV000079411. This spectral data is for all 290 individual animals, and it includes two technical replicates for each individual, for a total of 580 runs. The file size is 102 GB and we do not recommend downloading this unless you are specifically interested in re-analyzing the spectra from scratch and looking into the granular details of mass spectrometry metabolomics.
diff --git a/general/datasets/EPFL_LISP_LivPMetlog2CD1213/summary.rtf b/general/datasets/EPFL_LISP_LivPMetlog2CD1213/summary.rtf
deleted file mode 100644
index 5f92c0e..0000000
--- a/general/datasets/EPFL_LISP_LivPMetlog2CD1213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We identified 979 unique metabolite features based on mass-charge ratios (m/z) using flow-injection ToF-MS, respectively. Of these features, 699 could be attributed to a single metabolite, including in cases where of the two “possible” enantiomers, one is clearly far more predominant than the other (e.g. L versus D amino acids). The remaining 280 metabolites were “clusters” with no clear predominant feature—for example, the “glucose” metabolite measurements could not be separated from fructose, galactose, or mannose measurements, as all share the same m/z. The “main” metabolite, as well as all possible alternatives are listed with the data on GeneNetwork.org for the raw file download (press the “INFO” button next to the dataset on the main search page and download the dataset and supplemental data files).
diff --git a/general/datasets/EPFL_LISP_LivPMetlog2HFD1213/cases.rtf b/general/datasets/EPFL_LISP_LivPMetlog2HFD1213/cases.rtf
deleted file mode 100644
index 7d496bc..0000000
--- a/general/datasets/EPFL_LISP_LivPMetlog2HFD1213/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-For liver metabolites, livers were perfused, frozen in liquid nitrogen, and then shattered in liquid nitrogen with a mortar and pestle at a later date. Several pieces of shattered liver totalling ~100 milligrams were collected then homogenized in 1mL 70% Ethanol at -20°C. Metabolites were extracted by adding 7mL 70% Ethanol at 75°C for 2 min. Extracts were centrifuged for 10 minutes at 4,000 rpm at 4°C. Clean metabolites extracts were dried in a vacuum centrifuge and re-suspended in double-distilled H2O with volume according to the weight of the extracted liver piece. Quantification of metabolites was performed on an Agilent 6550 QTOF instrument by flow injection analysis time-of-flight mass spectrometry (see: PMID 21830798). All samples were injected in duplicates. Ions were annotated based on their accurate mass and the Human Metabolome Database reference list (see: PMID 23161693) allowing a tolerance of 0.001 Da. Unknown ions and those annotated as adducts were discarded. Theoretical m/z ratios—beyond the significant digits from the measurement sensitivity—are used as the unique index in the online data on GeneNetwork. For example, deprotonated fumarate corresponds to 115.0036897_MZ, malate to 133.0142794_MZ, α-ketoglutarate to 145.0141831_MZ, and D2HG to 147.0298102_MZ.
diff --git a/general/datasets/EPFL_LISP_LivPMetlog2HFD1213/processing.rtf b/general/datasets/EPFL_LISP_LivPMetlog2HFD1213/processing.rtf
deleted file mode 100644
index 671c357..0000000
--- a/general/datasets/EPFL_LISP_LivPMetlog2HFD1213/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GeneNetwork displays only the strain averages ± SEM for each metabolite. To obtain the individual data for each animal, please use the link above under (Download datasets and supplementary data files). Note that this contains two entries for each animal: these are technical replicates.
-
-The very raw spectral data from the mass spectrometer can be downloaded on MassIVE ( http://massive.ucsd.edu/ProteoSAFe/static/massive.jsp?redirect=auth ) under the identifier MSV000079411. This spectral data is for all 290 individual animals, and it includes two technical replicates for each individual, for a total of 580 runs. The file size is 102 GB and we do not recommend downloading this unless you are specifically interested in re-analyzing the spectra from scratch and looking into the granular details of mass spectrometry metabolomics.
diff --git a/general/datasets/EPFL_LISP_LivPMetlog2HFD1213/summary.rtf b/general/datasets/EPFL_LISP_LivPMetlog2HFD1213/summary.rtf
deleted file mode 100644
index 5f92c0e..0000000
--- a/general/datasets/EPFL_LISP_LivPMetlog2HFD1213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We identified 979 unique metabolite features based on mass-charge ratios (m/z) using flow-injection ToF-MS, respectively. Of these features, 699 could be attributed to a single metabolite, including in cases where of the two “possible” enantiomers, one is clearly far more predominant than the other (e.g. L versus D amino acids). The remaining 280 metabolites were “clusters” with no clear predominant feature—for example, the “glucose” metabolite measurements could not be separated from fructose, galactose, or mannose measurements, as all share the same m/z. The “main” metabolite, as well as all possible alternatives are listed with the data on GeneNetwork.org for the raw file download (press the “INFO” button next to the dataset on the main search page and download the dataset and supplemental data files).
diff --git a/general/datasets/EPFL_LISP_MusPMetCD1213/acknowledgment.rtf b/general/datasets/EPFL_LISP_MusPMetCD1213/acknowledgment.rtf
deleted file mode 100644
index cdb89a8..0000000
--- a/general/datasets/EPFL_LISP_MusPMetCD1213/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We would like to thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays. The work in the Auwerx lab was supported by the Ecole Polytechnique Federale de Lausanne, the EU Ideas program (AdG-23138 and AdG-322424), the NIH (R01HL106511-01A and R01AG043930), and the Swiss National Science Foundation (31003A- 124713 and 31003A-125487 and CSRII3-1362).
diff --git a/general/datasets/EPFL_LISP_MusPMetCD1213/cases.rtf b/general/datasets/EPFL_LISP_MusPMetCD1213/cases.rtf
deleted file mode 100644
index ced8242..0000000
--- a/general/datasets/EPFL_LISP_MusPMetCD1213/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, roughly 10 male animals were born and weaned at 3 weeks of age. These cohorts were then separated evenly into two cohorts at 8 weeks of age: up to 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and up to 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). A total of 195 CD animals and 189 HFD animals comprised these original 82 cohorts (42 on CD, 40 on HFD, all 40 overlap except for 2 strains, BXD60 and BXD92a (aka BXD65b), which are unique to CD). For the next 8 weeks, animals adjusted to the diet and housing situation. From 16 to 24 weeks of age, animals were phenotyped for respiration, oral glucose response, cold tolerance, basal activity, VO2max exercise, and voluntary exercise. Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest, undisturbed except for a weekly cage change and weighing. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion.
diff --git a/general/datasets/EPFL_LISP_MusPMetCD1213/platform.rtf b/general/datasets/EPFL_LISP_MusPMetCD1213/platform.rtf
deleted file mode 100644
index e123fe2..0000000
--- a/general/datasets/EPFL_LISP_MusPMetCD1213/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All arrays were Affymetrix Mouse Gene 1.0 ST, run in either October 2011 or August 2012 at the University of Tennessee Health Science Center. All .CEL files were normalized together after the second batch of data was collected.
diff --git a/general/datasets/EPFL_LISP_MusPMetCD1213/processing.rtf b/general/datasets/EPFL_LISP_MusPMetCD1213/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFL_LISP_MusPMetCD1213/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFL_LISP_MusPMetCD1213/summary.rtf b/general/datasets/EPFL_LISP_MusPMetCD1213/summary.rtf
deleted file mode 100644
index a785372..0000000
--- a/general/datasets/EPFL_LISP_MusPMetCD1213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. It is difficult to say whether the major muscle phenotypes were broadly affected by HFD directly, or whether the phenotypic variance was as a consequence of the induced weight gain and other deleterious effects of the HFD (e.g. see phenotype traits ID 17717 and 17718 for nighttime activity in CD and HFD cohorts, respectively).
diff --git a/general/datasets/EPFL_LISP_MusPMetCD1213/tissue.rtf b/general/datasets/EPFL_LISP_MusPMetCD1213/tissue.rtf
deleted file mode 100644
index c4913a4..0000000
--- a/general/datasets/EPFL_LISP_MusPMetCD1213/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The quadriceps were taken near the end of the pipeline, roughly 6–10 minutes after completion of perfusion. Quadriceps were collected by cutting evenly across the upper axis of the femoral bone. Quadriceps muscle lying below or beside this femoral axis was not taken. The quadriceps was then placed in liquid nitrogen. At a later date, quadriceps were retrieved from -80 storage and shattered in liquid nitrogen. Roughly ~100 mg fragments were taken at random for mRNA preparation for every individual. To account potential differences in the tissue taken (as the tissue was not pulverized into powder), all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
-
-Tissue preparation was done in two different steps: the first half of the cohorts were run in October 2011, while the second half was run in August 2012. This tissue was the first microarray run at this platform, and thus the quadriceps served as a pilot to ensure that data quality would be good. The first half of the cohorts are: CD: C57, DBA, 44, 45, 51, 55, 61, 62, 63, 66, 70, 73, 75, 80, 83, 87, 89, 90, 96. HFD: C57, DBA, 44, 45, 51, 55, 61, 62, 63, 66, 70, 73, 75, 80, 83, 87, 90, 96, 100. The second half of the cohorts were the remainder. The preparation of all samples was done by the same technician with the same technique, other than the year time differential
diff --git a/general/datasets/EPFL_LISP_MusPMetCDHFD1213/acknowledgment.rtf b/general/datasets/EPFL_LISP_MusPMetCDHFD1213/acknowledgment.rtf
deleted file mode 100644
index cdb89a8..0000000
--- a/general/datasets/EPFL_LISP_MusPMetCDHFD1213/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We would like to thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays. The work in the Auwerx lab was supported by the Ecole Polytechnique Federale de Lausanne, the EU Ideas program (AdG-23138 and AdG-322424), the NIH (R01HL106511-01A and R01AG043930), and the Swiss National Science Foundation (31003A- 124713 and 31003A-125487 and CSRII3-1362).
diff --git a/general/datasets/EPFL_LISP_MusPMetCDHFD1213/cases.rtf b/general/datasets/EPFL_LISP_MusPMetCDHFD1213/cases.rtf
deleted file mode 100644
index ced8242..0000000
--- a/general/datasets/EPFL_LISP_MusPMetCDHFD1213/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, roughly 10 male animals were born and weaned at 3 weeks of age. These cohorts were then separated evenly into two cohorts at 8 weeks of age: up to 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and up to 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). A total of 195 CD animals and 189 HFD animals comprised these original 82 cohorts (42 on CD, 40 on HFD, all 40 overlap except for 2 strains, BXD60 and BXD92a (aka BXD65b), which are unique to CD). For the next 8 weeks, animals adjusted to the diet and housing situation. From 16 to 24 weeks of age, animals were phenotyped for respiration, oral glucose response, cold tolerance, basal activity, VO2max exercise, and voluntary exercise. Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest, undisturbed except for a weekly cage change and weighing. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion.
diff --git a/general/datasets/EPFL_LISP_MusPMetCDHFD1213/platform.rtf b/general/datasets/EPFL_LISP_MusPMetCDHFD1213/platform.rtf
deleted file mode 100644
index e123fe2..0000000
--- a/general/datasets/EPFL_LISP_MusPMetCDHFD1213/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All arrays were Affymetrix Mouse Gene 1.0 ST, run in either October 2011 or August 2012 at the University of Tennessee Health Science Center. All .CEL files were normalized together after the second batch of data was collected.
diff --git a/general/datasets/EPFL_LISP_MusPMetCDHFD1213/processing.rtf b/general/datasets/EPFL_LISP_MusPMetCDHFD1213/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFL_LISP_MusPMetCDHFD1213/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFL_LISP_MusPMetCDHFD1213/summary.rtf b/general/datasets/EPFL_LISP_MusPMetCDHFD1213/summary.rtf
deleted file mode 100644
index a785372..0000000
--- a/general/datasets/EPFL_LISP_MusPMetCDHFD1213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. It is difficult to say whether the major muscle phenotypes were broadly affected by HFD directly, or whether the phenotypic variance was as a consequence of the induced weight gain and other deleterious effects of the HFD (e.g. see phenotype traits ID 17717 and 17718 for nighttime activity in CD and HFD cohorts, respectively).
diff --git a/general/datasets/EPFL_LISP_MusPMetCDHFD1213/tissue.rtf b/general/datasets/EPFL_LISP_MusPMetCDHFD1213/tissue.rtf
deleted file mode 100644
index c4913a4..0000000
--- a/general/datasets/EPFL_LISP_MusPMetCDHFD1213/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The quadriceps were taken near the end of the pipeline, roughly 6–10 minutes after completion of perfusion. Quadriceps were collected by cutting evenly across the upper axis of the femoral bone. Quadriceps muscle lying below or beside this femoral axis was not taken. The quadriceps was then placed in liquid nitrogen. At a later date, quadriceps were retrieved from -80 storage and shattered in liquid nitrogen. Roughly ~100 mg fragments were taken at random for mRNA preparation for every individual. To account potential differences in the tissue taken (as the tissue was not pulverized into powder), all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
-
-Tissue preparation was done in two different steps: the first half of the cohorts were run in October 2011, while the second half was run in August 2012. This tissue was the first microarray run at this platform, and thus the quadriceps served as a pilot to ensure that data quality would be good. The first half of the cohorts are: CD: C57, DBA, 44, 45, 51, 55, 61, 62, 63, 66, 70, 73, 75, 80, 83, 87, 89, 90, 96. HFD: C57, DBA, 44, 45, 51, 55, 61, 62, 63, 66, 70, 73, 75, 80, 83, 87, 90, 96, 100. The second half of the cohorts were the remainder. The preparation of all samples was done by the same technician with the same technique, other than the year time differential
diff --git a/general/datasets/EPFL_LISP_MusPMetHFD1213/acknowledgment.rtf b/general/datasets/EPFL_LISP_MusPMetHFD1213/acknowledgment.rtf
deleted file mode 100644
index cdb89a8..0000000
--- a/general/datasets/EPFL_LISP_MusPMetHFD1213/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We would like to thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays. The work in the Auwerx lab was supported by the Ecole Polytechnique Federale de Lausanne, the EU Ideas program (AdG-23138 and AdG-322424), the NIH (R01HL106511-01A and R01AG043930), and the Swiss National Science Foundation (31003A- 124713 and 31003A-125487 and CSRII3-1362).
diff --git a/general/datasets/EPFL_LISP_MusPMetHFD1213/cases.rtf b/general/datasets/EPFL_LISP_MusPMetHFD1213/cases.rtf
deleted file mode 100644
index ced8242..0000000
--- a/general/datasets/EPFL_LISP_MusPMetHFD1213/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, roughly 10 male animals were born and weaned at 3 weeks of age. These cohorts were then separated evenly into two cohorts at 8 weeks of age: up to 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and up to 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). A total of 195 CD animals and 189 HFD animals comprised these original 82 cohorts (42 on CD, 40 on HFD, all 40 overlap except for 2 strains, BXD60 and BXD92a (aka BXD65b), which are unique to CD). For the next 8 weeks, animals adjusted to the diet and housing situation. From 16 to 24 weeks of age, animals were phenotyped for respiration, oral glucose response, cold tolerance, basal activity, VO2max exercise, and voluntary exercise. Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest, undisturbed except for a weekly cage change and weighing. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion.
diff --git a/general/datasets/EPFL_LISP_MusPMetHFD1213/platform.rtf b/general/datasets/EPFL_LISP_MusPMetHFD1213/platform.rtf
deleted file mode 100644
index e123fe2..0000000
--- a/general/datasets/EPFL_LISP_MusPMetHFD1213/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All arrays were Affymetrix Mouse Gene 1.0 ST, run in either October 2011 or August 2012 at the University of Tennessee Health Science Center. All .CEL files were normalized together after the second batch of data was collected.
diff --git a/general/datasets/EPFL_LISP_MusPMetHFD1213/processing.rtf b/general/datasets/EPFL_LISP_MusPMetHFD1213/processing.rtf
deleted file mode 100644
index 8cc5d58..0000000
--- a/general/datasets/EPFL_LISP_MusPMetHFD1213/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/EPFL_LISP_MusPMetHFD1213/summary.rtf b/general/datasets/EPFL_LISP_MusPMetHFD1213/summary.rtf
deleted file mode 100644
index a785372..0000000
--- a/general/datasets/EPFL_LISP_MusPMetHFD1213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. It is difficult to say whether the major muscle phenotypes were broadly affected by HFD directly, or whether the phenotypic variance was as a consequence of the induced weight gain and other deleterious effects of the HFD (e.g. see phenotype traits ID 17717 and 17718 for nighttime activity in CD and HFD cohorts, respectively).
diff --git a/general/datasets/EPFL_LISP_MusPMetHFD1213/tissue.rtf b/general/datasets/EPFL_LISP_MusPMetHFD1213/tissue.rtf
deleted file mode 100644
index c4913a4..0000000
--- a/general/datasets/EPFL_LISP_MusPMetHFD1213/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The quadriceps were taken near the end of the pipeline, roughly 6–10 minutes after completion of perfusion. Quadriceps were collected by cutting evenly across the upper axis of the femoral bone. Quadriceps muscle lying below or beside this femoral axis was not taken. The quadriceps was then placed in liquid nitrogen. At a later date, quadriceps were retrieved from -80 storage and shattered in liquid nitrogen. Roughly ~100 mg fragments were taken at random for mRNA preparation for every individual. To account potential differences in the tissue taken (as the tissue was not pulverized into powder), all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
-
-Tissue preparation was done in two different steps: the first half of the cohorts were run in October 2011, while the second half was run in August 2012. This tissue was the first microarray run at this platform, and thus the quadriceps served as a pilot to ensure that data quality would be good. The first half of the cohorts are: CD: C57, DBA, 44, 45, 51, 55, 61, 62, 63, 66, 70, 73, 75, 80, 83, 87, 89, 90, 96. HFD: C57, DBA, 44, 45, 51, 55, 61, 62, 63, 66, 70, 73, 75, 80, 83, 87, 90, 96, 100. The second half of the cohorts were the remainder. The preparation of all samples was done by the same technician with the same technique, other than the year time differential
diff --git a/general/datasets/Ebi_mkk_liv_tpm_log2_0621/acknowledgment.rtf b/general/datasets/Ebi_mkk_liv_tpm_log2_0621/acknowledgment.rtf
new file mode 100644
index 0000000..44b9d93
--- /dev/null
+++ b/general/datasets/Ebi_mkk_liv_tpm_log2_0621/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors acknowledge Thomas Seitz, and Irina Oks and Marzena Majewski for supporting the fish husbandry, and Alicia Günthel, Rachel Müller and Beate Wittbrodt for laboratory assistance. F.L. dedicates this paper to Sabine and Rolf Loosli-Walther. The work was funded by the Helmholtz funding programme BIFTM to F. Loosli, N. Wolf, N. Kusminski, C. Herder and N. Aadepu. E. Birney, T. Fitzgerald, A. Leger, C. Barton, J. Monahan and I. Brettell were funded by the EMBL European Bioinformatics Institute (EMBL-EBI). This work was supported by Heidelberg University Core Funding to T. Tavhelidse, T. Thumberger and J. Wittbrodt. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 810172), from the NIH UH-3338-03 (JW), the German Ministry for Research (BMBF: HIGH-life 05K19VH1, Code-Vita 05K16VH1, JW) and the German Center for Heart Diseases DZHK (JW, JG).
diff --git a/general/datasets/Ebi_mkk_liv_tpm_log2_0621/specifics.rtf b/general/datasets/Ebi_mkk_liv_tpm_log2_0621/specifics.rtf
new file mode 100644
index 0000000..16aad9e
--- /dev/null
+++ b/general/datasets/Ebi_mkk_liv_tpm_log2_0621/specifics.rtf
@@ -0,0 +1 @@
+EBI MIKK Liver Male RNA-Seq (May 21) Log2 TPM
\ No newline at end of file
diff --git a/general/datasets/Ebi_mkk_liv_tpm_log2_0621/summary.rtf b/general/datasets/Ebi_mkk_liv_tpm_log2_0621/summary.rtf
new file mode 100644
index 0000000..d931cbf
--- /dev/null
+++ b/general/datasets/Ebi_mkk_liv_tpm_log2_0621/summary.rtf
@@ -0,0 +1,3 @@
+Full paper available at https://www.biorxiv.org/content/10.1101/2021.05.17.444412v2.full
+
+Unraveling the relationship between genetic variation and phenotypic traits remains a fundamental challenge in biology. Mapping variants underlying complex traits while controlling for confounding environmental factors is often problematic. To address this, we have established a vertebrate genetic resource specifically to allow for robust genotype-to-phenotype investigations. The teleost medaka (Oryzias latipes) is an established genetic model system with a long history of genetic research and a high tolerance to inbreeding from the wild. Here we present the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel: the first near-isogenic panel of 80 inbred lines in a vertebrate model derived from a wild founder population. Inbred lines provide fixed genomes that are a prerequisite for the replication of studies, studies which vary both the genetics and environment in a controlled manner and functional testing. The MIKK panel will therefore enable phenotype-to-genotype association studies of complex genetic traits while allowing for careful control of interacting factors, with numerous applications in genetic research, human health, and drug development and fundamental biology. Here we present a detailed characterisation of the genetic variation across the MIKK panel, which provides a rich and unique genetic resource to the community by enabling large-scale experiments for mapping complex traits.
diff --git a/general/datasets/Ebi_mkk_liv_tpm_log2_0621/tissue.rtf b/general/datasets/Ebi_mkk_liv_tpm_log2_0621/tissue.rtf
new file mode 100644
index 0000000..4e277e5
--- /dev/null
+++ b/general/datasets/Ebi_mkk_liv_tpm_log2_0621/tissue.rtf
@@ -0,0 +1 @@
+For whole genome sequencing, medaka organs were dissected from 6-month-old male adults. Fish were sacrificed by hypothermic shock. The brain was dissected and shock frozen in liquid nitrogen. For RNAseq analysis 12 month old adults that were kept at either 14 light:10 dark (summer condition) or 10 light:14 dark (winter condition) light cycles respectively were sacrificed by hypothermic shock and the organs after dissection were shock frozen in liquid nitrogen.
diff --git a/general/datasets/El_bxdcdhfdscwat_0216/acknowledgment.rtf b/general/datasets/El_bxdcdhfdscwat_0216/acknowledgment.rtf
new file mode 100644
index 0000000..3fc4fc5
--- /dev/null
+++ b/general/datasets/El_bxdcdhfdscwat_0216/acknowledgment.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdhfdscwat_0216/cases.rtf b/general/datasets/El_bxdcdhfdscwat_0216/cases.rtf
new file mode 100644
index 0000000..f54f4f2
--- /dev/null
+++ b/general/datasets/El_bxdcdhfdscwat_0216/cases.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ 40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Subcuteaneous white adipose tissue was collected near the end of the sacrifice pipeline, occurring an estimated 10±2 minutes after sacrifice. The tissue was weighed and then placed in a storage tube in liquid nitrogen.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdhfdscwat_0216/citation.rtf b/general/datasets/El_bxdcdhfdscwat_0216/citation.rtf
new file mode 100644
index 0000000..249a454
--- /dev/null
+++ b/general/datasets/El_bxdcdhfdscwat_0216/citation.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ Unpublished data. Please contact the laboratory of Johan Auwerx at the EPFL (http://auwerx-lab.epfl.ch/) for early access.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdhfdscwat_0216/contributors.rtf b/general/datasets/El_bxdcdhfdscwat_0216/contributors.rtf
new file mode 100644
index 0000000..ae951c8
--- /dev/null
+++ b/general/datasets/El_bxdcdhfdscwat_0216/contributors.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ Williams EG, Jha P, Hao L, Andreux PA, Auwerx J
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdhfdscwat_0216/experiment-design.rtf b/general/datasets/El_bxdcdhfdscwat_0216/experiment-design.rtf
new file mode 100644
index 0000000..b417b79
--- /dev/null
+++ b/general/datasets/El_bxdcdhfdscwat_0216/experiment-design.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdhfdscwat_0216/platform.rtf b/general/datasets/El_bxdcdhfdscwat_0216/platform.rtf
new file mode 100644
index 0000000..066be8d
--- /dev/null
+++ b/general/datasets/El_bxdcdhfdscwat_0216/platform.rtf
@@ -0,0 +1,5 @@
+GeneChip Mouse Transcriptome Assay 1.0
+
+All arrays were Affymetrix Mouse Transcriptome Assay 1.0, prepared and run simultaneously in a single batch in January 2016 by Lorne Rose at the University of Tennessee Health Science Center.
+
+Data error checked by RW Williams and David Ashbrook (March 2019). Numerous strain assignment corrections to HFD limb of study. Finally eQTL analysis validates both CD and HFD components.
diff --git a/general/datasets/El_bxdcdhfdscwat_0216/processing.rtf b/general/datasets/El_bxdcdhfdscwat_0216/processing.rtf
new file mode 100644
index 0000000..5dbb444
--- /dev/null
+++ b/general/datasets/El_bxdcdhfdscwat_0216/processing.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdhfdscwat_0216/specifics.rtf b/general/datasets/El_bxdcdhfdscwat_0216/specifics.rtf
new file mode 100644
index 0000000..e6f6b94
--- /dev/null
+++ b/general/datasets/El_bxdcdhfdscwat_0216/specifics.rtf
@@ -0,0 +1 @@
+Note: As of March 2019, this data set also affected by strain assignment errors in HFD limb. Needs to be fixed by Evan Williams, Arthur Centeno, and Rob Williams
diff --git a/general/datasets/El_bxdcdhfdscwat_0216/summary.rtf b/general/datasets/El_bxdcdhfdscwat_0216/summary.rtf
new file mode 100644
index 0000000..6c2d77a
--- /dev/null
+++ b/general/datasets/El_bxdcdhfdscwat_0216/summary.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
+ Microarray data for four other tissues in the exact same cohorts was processed and is in GeneNetwork: Heart, Liver, Muscle [Quadriceps], and Adipose [Brown]. Proteomic data for one other tissue in the exact same cohorts was processed and is in GeneNetwork: Liver. Metabolomic data for two tissues in the same cohorts was processed and is in GeneNetwork: Liver and Muscle [Quadriceps]. Brown Adipose was only run in CD cohorts, while all other datasets were run on both diets. All phenotype data associated with these animals can be found by searching Phenotypes for the code “LISP3”. Note that some traits are still private, while others have been published. |
+
+
+
+
diff --git a/general/datasets/El_bxdcdhfdscwat_0216/tissue.rtf b/general/datasets/El_bxdcdhfdscwat_0216/tissue.rtf
new file mode 100644
index 0000000..e595c55
--- /dev/null
+++ b/general/datasets/El_bxdcdhfdscwat_0216/tissue.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ Subcuteaneous WAT was later shattered in liquid nitrogen, and around 100 mg was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0. RNA was prepared in the summer of 2013, while the RNEasy cleanup occurred in the winter of 2015; unlike the other tissues run as a part of this study, these RNA samples spent a significant time in the -80° freezers. However, the samples only underwent one freeze—thaw cycle.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdscwat_0216/acknowledgment.rtf b/general/datasets/El_bxdcdscwat_0216/acknowledgment.rtf
new file mode 100644
index 0000000..3fc4fc5
--- /dev/null
+++ b/general/datasets/El_bxdcdscwat_0216/acknowledgment.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdscwat_0216/cases.rtf b/general/datasets/El_bxdcdscwat_0216/cases.rtf
new file mode 100644
index 0000000..f54f4f2
--- /dev/null
+++ b/general/datasets/El_bxdcdscwat_0216/cases.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ 40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Subcuteaneous white adipose tissue was collected near the end of the sacrifice pipeline, occurring an estimated 10±2 minutes after sacrifice. The tissue was weighed and then placed in a storage tube in liquid nitrogen.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdscwat_0216/citation.rtf b/general/datasets/El_bxdcdscwat_0216/citation.rtf
new file mode 100644
index 0000000..249a454
--- /dev/null
+++ b/general/datasets/El_bxdcdscwat_0216/citation.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ Unpublished data. Please contact the laboratory of Johan Auwerx at the EPFL (http://auwerx-lab.epfl.ch/) for early access.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdscwat_0216/contributors.rtf b/general/datasets/El_bxdcdscwat_0216/contributors.rtf
new file mode 100644
index 0000000..ae951c8
--- /dev/null
+++ b/general/datasets/El_bxdcdscwat_0216/contributors.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ Williams EG, Jha P, Hao L, Andreux PA, Auwerx J
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdscwat_0216/experiment-design.rtf b/general/datasets/El_bxdcdscwat_0216/experiment-design.rtf
new file mode 100644
index 0000000..b417b79
--- /dev/null
+++ b/general/datasets/El_bxdcdscwat_0216/experiment-design.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdscwat_0216/platform.rtf b/general/datasets/El_bxdcdscwat_0216/platform.rtf
new file mode 100644
index 0000000..066be8d
--- /dev/null
+++ b/general/datasets/El_bxdcdscwat_0216/platform.rtf
@@ -0,0 +1,5 @@
+GeneChip Mouse Transcriptome Assay 1.0
+
+All arrays were Affymetrix Mouse Transcriptome Assay 1.0, prepared and run simultaneously in a single batch in January 2016 by Lorne Rose at the University of Tennessee Health Science Center.
+
+Data error checked by RW Williams and David Ashbrook (March 2019). Numerous strain assignment corrections to HFD limb of study. Finally eQTL analysis validates both CD and HFD components.
diff --git a/general/datasets/El_bxdcdscwat_0216/processing.rtf b/general/datasets/El_bxdcdscwat_0216/processing.rtf
new file mode 100644
index 0000000..5dbb444
--- /dev/null
+++ b/general/datasets/El_bxdcdscwat_0216/processing.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdcdscwat_0216/summary.rtf b/general/datasets/El_bxdcdscwat_0216/summary.rtf
new file mode 100644
index 0000000..6c2d77a
--- /dev/null
+++ b/general/datasets/El_bxdcdscwat_0216/summary.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
+ Microarray data for four other tissues in the exact same cohorts was processed and is in GeneNetwork: Heart, Liver, Muscle [Quadriceps], and Adipose [Brown]. Proteomic data for one other tissue in the exact same cohorts was processed and is in GeneNetwork: Liver. Metabolomic data for two tissues in the same cohorts was processed and is in GeneNetwork: Liver and Muscle [Quadriceps]. Brown Adipose was only run in CD cohorts, while all other datasets were run on both diets. All phenotype data associated with these animals can be found by searching Phenotypes for the code “LISP3”. Note that some traits are still private, while others have been published. |
+
+
+
+
diff --git a/general/datasets/El_bxdcdscwat_0216/tissue.rtf b/general/datasets/El_bxdcdscwat_0216/tissue.rtf
new file mode 100644
index 0000000..e595c55
--- /dev/null
+++ b/general/datasets/El_bxdcdscwat_0216/tissue.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ Subcuteaneous WAT was later shattered in liquid nitrogen, and around 100 mg was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0. RNA was prepared in the summer of 2013, while the RNEasy cleanup occurred in the winter of 2015; unlike the other tissues run as a part of this study, these RNA samples spent a significant time in the -80° freezers. However, the samples only underwent one freeze—thaw cycle.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdhfdscwat_0216/acknowledgment.rtf b/general/datasets/El_bxdhfdscwat_0216/acknowledgment.rtf
new file mode 100644
index 0000000..3fc4fc5
--- /dev/null
+++ b/general/datasets/El_bxdhfdscwat_0216/acknowledgment.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdhfdscwat_0216/cases.rtf b/general/datasets/El_bxdhfdscwat_0216/cases.rtf
new file mode 100644
index 0000000..f54f4f2
--- /dev/null
+++ b/general/datasets/El_bxdhfdscwat_0216/cases.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ 40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Subcuteaneous white adipose tissue was collected near the end of the sacrifice pipeline, occurring an estimated 10±2 minutes after sacrifice. The tissue was weighed and then placed in a storage tube in liquid nitrogen.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdhfdscwat_0216/citation.rtf b/general/datasets/El_bxdhfdscwat_0216/citation.rtf
new file mode 100644
index 0000000..249a454
--- /dev/null
+++ b/general/datasets/El_bxdhfdscwat_0216/citation.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ Unpublished data. Please contact the laboratory of Johan Auwerx at the EPFL (http://auwerx-lab.epfl.ch/) for early access.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdhfdscwat_0216/contributors.rtf b/general/datasets/El_bxdhfdscwat_0216/contributors.rtf
new file mode 100644
index 0000000..ae951c8
--- /dev/null
+++ b/general/datasets/El_bxdhfdscwat_0216/contributors.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ Williams EG, Jha P, Hao L, Andreux PA, Auwerx J
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdhfdscwat_0216/experiment-design.rtf b/general/datasets/El_bxdhfdscwat_0216/experiment-design.rtf
new file mode 100644
index 0000000..b417b79
--- /dev/null
+++ b/general/datasets/El_bxdhfdscwat_0216/experiment-design.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdhfdscwat_0216/platform.rtf b/general/datasets/El_bxdhfdscwat_0216/platform.rtf
new file mode 100644
index 0000000..066be8d
--- /dev/null
+++ b/general/datasets/El_bxdhfdscwat_0216/platform.rtf
@@ -0,0 +1,5 @@
+GeneChip Mouse Transcriptome Assay 1.0
+
+All arrays were Affymetrix Mouse Transcriptome Assay 1.0, prepared and run simultaneously in a single batch in January 2016 by Lorne Rose at the University of Tennessee Health Science Center.
+
+Data error checked by RW Williams and David Ashbrook (March 2019). Numerous strain assignment corrections to HFD limb of study. Finally eQTL analysis validates both CD and HFD components.
diff --git a/general/datasets/El_bxdhfdscwat_0216/processing.rtf b/general/datasets/El_bxdhfdscwat_0216/processing.rtf
new file mode 100644
index 0000000..5dbb444
--- /dev/null
+++ b/general/datasets/El_bxdhfdscwat_0216/processing.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
+ |
+
+
+
+
diff --git a/general/datasets/El_bxdhfdscwat_0216/specifics.rtf b/general/datasets/El_bxdhfdscwat_0216/specifics.rtf
new file mode 100644
index 0000000..276d19a
--- /dev/null
+++ b/general/datasets/El_bxdhfdscwat_0216/specifics.rtf
@@ -0,0 +1 @@
+Note: Prior to March 2019, the HFD component of this data set had strain assignment error. Now fully corrected.
diff --git a/general/datasets/El_bxdhfdscwat_0216/summary.rtf b/general/datasets/El_bxdhfdscwat_0216/summary.rtf
new file mode 100644
index 0000000..6c2d77a
--- /dev/null
+++ b/general/datasets/El_bxdhfdscwat_0216/summary.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
+ Microarray data for four other tissues in the exact same cohorts was processed and is in GeneNetwork: Heart, Liver, Muscle [Quadriceps], and Adipose [Brown]. Proteomic data for one other tissue in the exact same cohorts was processed and is in GeneNetwork: Liver. Metabolomic data for two tissues in the same cohorts was processed and is in GeneNetwork: Liver and Muscle [Quadriceps]. Brown Adipose was only run in CD cohorts, while all other datasets were run on both diets. All phenotype data associated with these animals can be found by searching Phenotypes for the code “LISP3”. Note that some traits are still private, while others have been published. |
+
+
+
+
diff --git a/general/datasets/El_bxdhfdscwat_0216/tissue.rtf b/general/datasets/El_bxdhfdscwat_0216/tissue.rtf
new file mode 100644
index 0000000..e595c55
--- /dev/null
+++ b/general/datasets/El_bxdhfdscwat_0216/tissue.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+ |
+ Subcuteaneous WAT was later shattered in liquid nitrogen, and around 100 mg was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0. RNA was prepared in the summer of 2013, while the RNEasy cleanup occurred in the winter of 2015; unlike the other tissues run as a part of this study, these RNA samples spent a significant time in the -80° freezers. However, the samples only underwent one freeze—thaw cycle.
+ |
+
+
+
+
diff --git a/general/datasets/Epfl_adimitpro0416/summary.rtf b/general/datasets/Epfl_adimitpro0416/summary.rtf
new file mode 100644
index 0000000..18527b0
--- /dev/null
+++ b/general/datasets/Epfl_adimitpro0416/summary.rtf
@@ -0,0 +1 @@
+Currently these datasets are private, please refer to the contact information if you want to use this data set.
diff --git a/general/datasets/Epfl_adipro0416/summary.rtf b/general/datasets/Epfl_adipro0416/summary.rtf
new file mode 100644
index 0000000..18527b0
--- /dev/null
+++ b/general/datasets/Epfl_adipro0416/summary.rtf
@@ -0,0 +1 @@
+Currently these datasets are private, please refer to the contact information if you want to use this data set.
diff --git a/general/datasets/Epfl_ethz_bxd_livprotavg_cd_1119/specifics.rtf b/general/datasets/Epfl_ethz_bxd_livprotavg_cd_1119/specifics.rtf
new file mode 100644
index 0000000..c1ddd29
--- /dev/null
+++ b/general/datasets/Epfl_ethz_bxd_livprotavg_cd_1119/specifics.rtf
@@ -0,0 +1 @@
+CD
\ No newline at end of file
diff --git a/general/datasets/Epfl_ethz_bxd_livprotavg_cd_1119/summary.rtf b/general/datasets/Epfl_ethz_bxd_livprotavg_cd_1119/summary.rtf
new file mode 100644
index 0000000..c443a46
--- /dev/null
+++ b/general/datasets/Epfl_ethz_bxd_livprotavg_cd_1119/summary.rtf
@@ -0,0 +1 @@
+EPFL/ETHZ BXD Liver Proteome CD-HFD (Nov19)
diff --git a/general/datasets/Epfl_ethz_bxd_livprotavg_cd_hf_1119/specifics.rtf b/general/datasets/Epfl_ethz_bxd_livprotavg_cd_hf_1119/specifics.rtf
new file mode 100644
index 0000000..107347f
--- /dev/null
+++ b/general/datasets/Epfl_ethz_bxd_livprotavg_cd_hf_1119/specifics.rtf
@@ -0,0 +1 @@
+CD + HFD
\ No newline at end of file
diff --git a/general/datasets/Epfl_ethz_bxd_livprotavg_cd_hf_1119/summary.rtf b/general/datasets/Epfl_ethz_bxd_livprotavg_cd_hf_1119/summary.rtf
new file mode 100644
index 0000000..c443a46
--- /dev/null
+++ b/general/datasets/Epfl_ethz_bxd_livprotavg_cd_hf_1119/summary.rtf
@@ -0,0 +1 @@
+EPFL/ETHZ BXD Liver Proteome CD-HFD (Nov19)
diff --git a/general/datasets/Epfl_ethz_bxd_livprotavg_hfd_1119/specifics.rtf b/general/datasets/Epfl_ethz_bxd_livprotavg_hfd_1119/specifics.rtf
new file mode 100644
index 0000000..0ba1ca4
--- /dev/null
+++ b/general/datasets/Epfl_ethz_bxd_livprotavg_hfd_1119/specifics.rtf
@@ -0,0 +1 @@
+HFD
\ No newline at end of file
diff --git a/general/datasets/Epfl_ethz_bxd_livprotavg_hfd_1119/summary.rtf b/general/datasets/Epfl_ethz_bxd_livprotavg_hfd_1119/summary.rtf
new file mode 100644
index 0000000..c443a46
--- /dev/null
+++ b/general/datasets/Epfl_ethz_bxd_livprotavg_hfd_1119/summary.rtf
@@ -0,0 +1 @@
+EPFL/ETHZ BXD Liver Proteome CD-HFD (Nov19)
diff --git a/general/datasets/Epfl_ethz_bxd_livprotcd_hf_1119/specifics.rtf b/general/datasets/Epfl_ethz_bxd_livprotcd_hf_1119/specifics.rtf
new file mode 100644
index 0000000..409654b
--- /dev/null
+++ b/general/datasets/Epfl_ethz_bxd_livprotcd_hf_1119/specifics.rtf
@@ -0,0 +1 @@
+Individual samples
\ No newline at end of file
diff --git a/general/datasets/Epfl_ethz_bxd_livprotcd_hf_1119/summary.rtf b/general/datasets/Epfl_ethz_bxd_livprotcd_hf_1119/summary.rtf
new file mode 100644
index 0000000..c443a46
--- /dev/null
+++ b/general/datasets/Epfl_ethz_bxd_livprotcd_hf_1119/summary.rtf
@@ -0,0 +1 @@
+EPFL/ETHZ BXD Liver Proteome CD-HFD (Nov19)
diff --git a/general/datasets/Epfl_lisp_bxd_col_cd0917/specifics.rtf b/general/datasets/Epfl_lisp_bxd_col_cd0917/specifics.rtf
new file mode 100644
index 0000000..c1ddd29
--- /dev/null
+++ b/general/datasets/Epfl_lisp_bxd_col_cd0917/specifics.rtf
@@ -0,0 +1 @@
+CD
\ No newline at end of file
diff --git a/general/datasets/Epfl_lisp_bxd_col_cd0917/summary.rtf b/general/datasets/Epfl_lisp_bxd_col_cd0917/summary.rtf
new file mode 100644
index 0000000..3ec986b
--- /dev/null
+++ b/general/datasets/Epfl_lisp_bxd_col_cd0917/summary.rtf
@@ -0,0 +1 @@
+Unpublished dataset
diff --git a/general/datasets/Epfl_lisp_bxd_col_cd_hfd0917/specifics.rtf b/general/datasets/Epfl_lisp_bxd_col_cd_hfd0917/specifics.rtf
new file mode 100644
index 0000000..107347f
--- /dev/null
+++ b/general/datasets/Epfl_lisp_bxd_col_cd_hfd0917/specifics.rtf
@@ -0,0 +1 @@
+CD + HFD
\ No newline at end of file
diff --git a/general/datasets/Epfl_lisp_bxd_col_cd_hfd0917/summary.rtf b/general/datasets/Epfl_lisp_bxd_col_cd_hfd0917/summary.rtf
new file mode 100644
index 0000000..3ec986b
--- /dev/null
+++ b/general/datasets/Epfl_lisp_bxd_col_cd_hfd0917/summary.rtf
@@ -0,0 +1 @@
+Unpublished dataset
diff --git a/general/datasets/Epfl_lisp_bxd_col_hfd0917/specifics.rtf b/general/datasets/Epfl_lisp_bxd_col_hfd0917/specifics.rtf
new file mode 100644
index 0000000..0ba1ca4
--- /dev/null
+++ b/general/datasets/Epfl_lisp_bxd_col_hfd0917/specifics.rtf
@@ -0,0 +1 @@
+HFD
\ No newline at end of file
diff --git a/general/datasets/Epfl_lisp_bxd_col_hfd0917/summary.rtf b/general/datasets/Epfl_lisp_bxd_col_hfd0917/summary.rtf
new file mode 100644
index 0000000..3ec986b
--- /dev/null
+++ b/general/datasets/Epfl_lisp_bxd_col_hfd0917/summary.rtf
@@ -0,0 +1 @@
+Unpublished dataset
diff --git a/general/datasets/Epfl_lisp_livpmetcd1213/cases.rtf b/general/datasets/Epfl_lisp_livpmetcd1213/cases.rtf
new file mode 100644
index 0000000..7d496bc
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmetcd1213/cases.rtf
@@ -0,0 +1 @@
+For liver metabolites, livers were perfused, frozen in liquid nitrogen, and then shattered in liquid nitrogen with a mortar and pestle at a later date. Several pieces of shattered liver totalling ~100 milligrams were collected then homogenized in 1mL 70% Ethanol at -20°C. Metabolites were extracted by adding 7mL 70% Ethanol at 75°C for 2 min. Extracts were centrifuged for 10 minutes at 4,000 rpm at 4°C. Clean metabolites extracts were dried in a vacuum centrifuge and re-suspended in double-distilled H2O with volume according to the weight of the extracted liver piece. Quantification of metabolites was performed on an Agilent 6550 QTOF instrument by flow injection analysis time-of-flight mass spectrometry (see: PMID 21830798). All samples were injected in duplicates. Ions were annotated based on their accurate mass and the Human Metabolome Database reference list (see: PMID 23161693) allowing a tolerance of 0.001 Da. Unknown ions and those annotated as adducts were discarded. Theoretical m/z ratios—beyond the significant digits from the measurement sensitivity—are used as the unique index in the online data on GeneNetwork. For example, deprotonated fumarate corresponds to 115.0036897_MZ, malate to 133.0142794_MZ, α-ketoglutarate to 145.0141831_MZ, and D2HG to 147.0298102_MZ.
diff --git a/general/datasets/Epfl_lisp_livpmetcd1213/processing.rtf b/general/datasets/Epfl_lisp_livpmetcd1213/processing.rtf
new file mode 100644
index 0000000..671c357
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmetcd1213/processing.rtf
@@ -0,0 +1,3 @@
+GeneNetwork displays only the strain averages ± SEM for each metabolite. To obtain the individual data for each animal, please use the link above under (Download datasets and supplementary data files). Note that this contains two entries for each animal: these are technical replicates.
+
+The very raw spectral data from the mass spectrometer can be downloaded on MassIVE ( http://massive.ucsd.edu/ProteoSAFe/static/massive.jsp?redirect=auth ) under the identifier MSV000079411. This spectral data is for all 290 individual animals, and it includes two technical replicates for each individual, for a total of 580 runs. The file size is 102 GB and we do not recommend downloading this unless you are specifically interested in re-analyzing the spectra from scratch and looking into the granular details of mass spectrometry metabolomics.
diff --git a/general/datasets/Epfl_lisp_livpmetcd1213/summary.rtf b/general/datasets/Epfl_lisp_livpmetcd1213/summary.rtf
new file mode 100644
index 0000000..5f92c0e
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmetcd1213/summary.rtf
@@ -0,0 +1 @@
+We identified 979 unique metabolite features based on mass-charge ratios (m/z) using flow-injection ToF-MS, respectively. Of these features, 699 could be attributed to a single metabolite, including in cases where of the two “possible” enantiomers, one is clearly far more predominant than the other (e.g. L versus D amino acids). The remaining 280 metabolites were “clusters” with no clear predominant feature—for example, the “glucose” metabolite measurements could not be separated from fructose, galactose, or mannose measurements, as all share the same m/z. The “main” metabolite, as well as all possible alternatives are listed with the data on GeneNetwork.org for the raw file download (press the “INFO” button next to the dataset on the main search page and download the dataset and supplemental data files).
diff --git a/general/datasets/Epfl_lisp_livpmetcdhfd1213/cases.rtf b/general/datasets/Epfl_lisp_livpmetcdhfd1213/cases.rtf
new file mode 100644
index 0000000..7d496bc
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmetcdhfd1213/cases.rtf
@@ -0,0 +1 @@
+For liver metabolites, livers were perfused, frozen in liquid nitrogen, and then shattered in liquid nitrogen with a mortar and pestle at a later date. Several pieces of shattered liver totalling ~100 milligrams were collected then homogenized in 1mL 70% Ethanol at -20°C. Metabolites were extracted by adding 7mL 70% Ethanol at 75°C for 2 min. Extracts were centrifuged for 10 minutes at 4,000 rpm at 4°C. Clean metabolites extracts were dried in a vacuum centrifuge and re-suspended in double-distilled H2O with volume according to the weight of the extracted liver piece. Quantification of metabolites was performed on an Agilent 6550 QTOF instrument by flow injection analysis time-of-flight mass spectrometry (see: PMID 21830798). All samples were injected in duplicates. Ions were annotated based on their accurate mass and the Human Metabolome Database reference list (see: PMID 23161693) allowing a tolerance of 0.001 Da. Unknown ions and those annotated as adducts were discarded. Theoretical m/z ratios—beyond the significant digits from the measurement sensitivity—are used as the unique index in the online data on GeneNetwork. For example, deprotonated fumarate corresponds to 115.0036897_MZ, malate to 133.0142794_MZ, α-ketoglutarate to 145.0141831_MZ, and D2HG to 147.0298102_MZ.
diff --git a/general/datasets/Epfl_lisp_livpmetcdhfd1213/processing.rtf b/general/datasets/Epfl_lisp_livpmetcdhfd1213/processing.rtf
new file mode 100644
index 0000000..671c357
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmetcdhfd1213/processing.rtf
@@ -0,0 +1,3 @@
+GeneNetwork displays only the strain averages ± SEM for each metabolite. To obtain the individual data for each animal, please use the link above under (Download datasets and supplementary data files). Note that this contains two entries for each animal: these are technical replicates.
+
+The very raw spectral data from the mass spectrometer can be downloaded on MassIVE ( http://massive.ucsd.edu/ProteoSAFe/static/massive.jsp?redirect=auth ) under the identifier MSV000079411. This spectral data is for all 290 individual animals, and it includes two technical replicates for each individual, for a total of 580 runs. The file size is 102 GB and we do not recommend downloading this unless you are specifically interested in re-analyzing the spectra from scratch and looking into the granular details of mass spectrometry metabolomics.
diff --git a/general/datasets/Epfl_lisp_livpmetcdhfd1213/summary.rtf b/general/datasets/Epfl_lisp_livpmetcdhfd1213/summary.rtf
new file mode 100644
index 0000000..5f92c0e
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmetcdhfd1213/summary.rtf
@@ -0,0 +1 @@
+We identified 979 unique metabolite features based on mass-charge ratios (m/z) using flow-injection ToF-MS, respectively. Of these features, 699 could be attributed to a single metabolite, including in cases where of the two “possible” enantiomers, one is clearly far more predominant than the other (e.g. L versus D amino acids). The remaining 280 metabolites were “clusters” with no clear predominant feature—for example, the “glucose” metabolite measurements could not be separated from fructose, galactose, or mannose measurements, as all share the same m/z. The “main” metabolite, as well as all possible alternatives are listed with the data on GeneNetwork.org for the raw file download (press the “INFO” button next to the dataset on the main search page and download the dataset and supplemental data files).
diff --git a/general/datasets/Epfl_lisp_livpmethfd1213/cases.rtf b/general/datasets/Epfl_lisp_livpmethfd1213/cases.rtf
new file mode 100644
index 0000000..7d496bc
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmethfd1213/cases.rtf
@@ -0,0 +1 @@
+For liver metabolites, livers were perfused, frozen in liquid nitrogen, and then shattered in liquid nitrogen with a mortar and pestle at a later date. Several pieces of shattered liver totalling ~100 milligrams were collected then homogenized in 1mL 70% Ethanol at -20°C. Metabolites were extracted by adding 7mL 70% Ethanol at 75°C for 2 min. Extracts were centrifuged for 10 minutes at 4,000 rpm at 4°C. Clean metabolites extracts were dried in a vacuum centrifuge and re-suspended in double-distilled H2O with volume according to the weight of the extracted liver piece. Quantification of metabolites was performed on an Agilent 6550 QTOF instrument by flow injection analysis time-of-flight mass spectrometry (see: PMID 21830798). All samples were injected in duplicates. Ions were annotated based on their accurate mass and the Human Metabolome Database reference list (see: PMID 23161693) allowing a tolerance of 0.001 Da. Unknown ions and those annotated as adducts were discarded. Theoretical m/z ratios—beyond the significant digits from the measurement sensitivity—are used as the unique index in the online data on GeneNetwork. For example, deprotonated fumarate corresponds to 115.0036897_MZ, malate to 133.0142794_MZ, α-ketoglutarate to 145.0141831_MZ, and D2HG to 147.0298102_MZ.
diff --git a/general/datasets/Epfl_lisp_livpmethfd1213/processing.rtf b/general/datasets/Epfl_lisp_livpmethfd1213/processing.rtf
new file mode 100644
index 0000000..671c357
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmethfd1213/processing.rtf
@@ -0,0 +1,3 @@
+GeneNetwork displays only the strain averages ± SEM for each metabolite. To obtain the individual data for each animal, please use the link above under (Download datasets and supplementary data files). Note that this contains two entries for each animal: these are technical replicates.
+
+The very raw spectral data from the mass spectrometer can be downloaded on MassIVE ( http://massive.ucsd.edu/ProteoSAFe/static/massive.jsp?redirect=auth ) under the identifier MSV000079411. This spectral data is for all 290 individual animals, and it includes two technical replicates for each individual, for a total of 580 runs. The file size is 102 GB and we do not recommend downloading this unless you are specifically interested in re-analyzing the spectra from scratch and looking into the granular details of mass spectrometry metabolomics.
diff --git a/general/datasets/Epfl_lisp_livpmethfd1213/summary.rtf b/general/datasets/Epfl_lisp_livpmethfd1213/summary.rtf
new file mode 100644
index 0000000..5f92c0e
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmethfd1213/summary.rtf
@@ -0,0 +1 @@
+We identified 979 unique metabolite features based on mass-charge ratios (m/z) using flow-injection ToF-MS, respectively. Of these features, 699 could be attributed to a single metabolite, including in cases where of the two “possible” enantiomers, one is clearly far more predominant than the other (e.g. L versus D amino acids). The remaining 280 metabolites were “clusters” with no clear predominant feature—for example, the “glucose” metabolite measurements could not be separated from fructose, galactose, or mannose measurements, as all share the same m/z. The “main” metabolite, as well as all possible alternatives are listed with the data on GeneNetwork.org for the raw file download (press the “INFO” button next to the dataset on the main search page and download the dataset and supplemental data files).
diff --git a/general/datasets/Epfl_lisp_livpmetlog2cd1213/cases.rtf b/general/datasets/Epfl_lisp_livpmetlog2cd1213/cases.rtf
new file mode 100644
index 0000000..7d496bc
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmetlog2cd1213/cases.rtf
@@ -0,0 +1 @@
+For liver metabolites, livers were perfused, frozen in liquid nitrogen, and then shattered in liquid nitrogen with a mortar and pestle at a later date. Several pieces of shattered liver totalling ~100 milligrams were collected then homogenized in 1mL 70% Ethanol at -20°C. Metabolites were extracted by adding 7mL 70% Ethanol at 75°C for 2 min. Extracts were centrifuged for 10 minutes at 4,000 rpm at 4°C. Clean metabolites extracts were dried in a vacuum centrifuge and re-suspended in double-distilled H2O with volume according to the weight of the extracted liver piece. Quantification of metabolites was performed on an Agilent 6550 QTOF instrument by flow injection analysis time-of-flight mass spectrometry (see: PMID 21830798). All samples were injected in duplicates. Ions were annotated based on their accurate mass and the Human Metabolome Database reference list (see: PMID 23161693) allowing a tolerance of 0.001 Da. Unknown ions and those annotated as adducts were discarded. Theoretical m/z ratios—beyond the significant digits from the measurement sensitivity—are used as the unique index in the online data on GeneNetwork. For example, deprotonated fumarate corresponds to 115.0036897_MZ, malate to 133.0142794_MZ, α-ketoglutarate to 145.0141831_MZ, and D2HG to 147.0298102_MZ.
diff --git a/general/datasets/Epfl_lisp_livpmetlog2cd1213/processing.rtf b/general/datasets/Epfl_lisp_livpmetlog2cd1213/processing.rtf
new file mode 100644
index 0000000..671c357
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmetlog2cd1213/processing.rtf
@@ -0,0 +1,3 @@
+GeneNetwork displays only the strain averages ± SEM for each metabolite. To obtain the individual data for each animal, please use the link above under (Download datasets and supplementary data files). Note that this contains two entries for each animal: these are technical replicates.
+
+The very raw spectral data from the mass spectrometer can be downloaded on MassIVE ( http://massive.ucsd.edu/ProteoSAFe/static/massive.jsp?redirect=auth ) under the identifier MSV000079411. This spectral data is for all 290 individual animals, and it includes two technical replicates for each individual, for a total of 580 runs. The file size is 102 GB and we do not recommend downloading this unless you are specifically interested in re-analyzing the spectra from scratch and looking into the granular details of mass spectrometry metabolomics.
diff --git a/general/datasets/Epfl_lisp_livpmetlog2cd1213/summary.rtf b/general/datasets/Epfl_lisp_livpmetlog2cd1213/summary.rtf
new file mode 100644
index 0000000..5f92c0e
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmetlog2cd1213/summary.rtf
@@ -0,0 +1 @@
+We identified 979 unique metabolite features based on mass-charge ratios (m/z) using flow-injection ToF-MS, respectively. Of these features, 699 could be attributed to a single metabolite, including in cases where of the two “possible” enantiomers, one is clearly far more predominant than the other (e.g. L versus D amino acids). The remaining 280 metabolites were “clusters” with no clear predominant feature—for example, the “glucose” metabolite measurements could not be separated from fructose, galactose, or mannose measurements, as all share the same m/z. The “main” metabolite, as well as all possible alternatives are listed with the data on GeneNetwork.org for the raw file download (press the “INFO” button next to the dataset on the main search page and download the dataset and supplemental data files).
diff --git a/general/datasets/Epfl_lisp_livpmetlog2hfd1213/cases.rtf b/general/datasets/Epfl_lisp_livpmetlog2hfd1213/cases.rtf
new file mode 100644
index 0000000..7d496bc
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmetlog2hfd1213/cases.rtf
@@ -0,0 +1 @@
+For liver metabolites, livers were perfused, frozen in liquid nitrogen, and then shattered in liquid nitrogen with a mortar and pestle at a later date. Several pieces of shattered liver totalling ~100 milligrams were collected then homogenized in 1mL 70% Ethanol at -20°C. Metabolites were extracted by adding 7mL 70% Ethanol at 75°C for 2 min. Extracts were centrifuged for 10 minutes at 4,000 rpm at 4°C. Clean metabolites extracts were dried in a vacuum centrifuge and re-suspended in double-distilled H2O with volume according to the weight of the extracted liver piece. Quantification of metabolites was performed on an Agilent 6550 QTOF instrument by flow injection analysis time-of-flight mass spectrometry (see: PMID 21830798). All samples were injected in duplicates. Ions were annotated based on their accurate mass and the Human Metabolome Database reference list (see: PMID 23161693) allowing a tolerance of 0.001 Da. Unknown ions and those annotated as adducts were discarded. Theoretical m/z ratios—beyond the significant digits from the measurement sensitivity—are used as the unique index in the online data on GeneNetwork. For example, deprotonated fumarate corresponds to 115.0036897_MZ, malate to 133.0142794_MZ, α-ketoglutarate to 145.0141831_MZ, and D2HG to 147.0298102_MZ.
diff --git a/general/datasets/Epfl_lisp_livpmetlog2hfd1213/processing.rtf b/general/datasets/Epfl_lisp_livpmetlog2hfd1213/processing.rtf
new file mode 100644
index 0000000..671c357
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmetlog2hfd1213/processing.rtf
@@ -0,0 +1,3 @@
+GeneNetwork displays only the strain averages ± SEM for each metabolite. To obtain the individual data for each animal, please use the link above under (Download datasets and supplementary data files). Note that this contains two entries for each animal: these are technical replicates.
+
+The very raw spectral data from the mass spectrometer can be downloaded on MassIVE ( http://massive.ucsd.edu/ProteoSAFe/static/massive.jsp?redirect=auth ) under the identifier MSV000079411. This spectral data is for all 290 individual animals, and it includes two technical replicates for each individual, for a total of 580 runs. The file size is 102 GB and we do not recommend downloading this unless you are specifically interested in re-analyzing the spectra from scratch and looking into the granular details of mass spectrometry metabolomics.
diff --git a/general/datasets/Epfl_lisp_livpmetlog2hfd1213/summary.rtf b/general/datasets/Epfl_lisp_livpmetlog2hfd1213/summary.rtf
new file mode 100644
index 0000000..5f92c0e
--- /dev/null
+++ b/general/datasets/Epfl_lisp_livpmetlog2hfd1213/summary.rtf
@@ -0,0 +1 @@
+We identified 979 unique metabolite features based on mass-charge ratios (m/z) using flow-injection ToF-MS, respectively. Of these features, 699 could be attributed to a single metabolite, including in cases where of the two “possible” enantiomers, one is clearly far more predominant than the other (e.g. L versus D amino acids). The remaining 280 metabolites were “clusters” with no clear predominant feature—for example, the “glucose” metabolite measurements could not be separated from fructose, galactose, or mannose measurements, as all share the same m/z. The “main” metabolite, as well as all possible alternatives are listed with the data on GeneNetwork.org for the raw file download (press the “INFO” button next to the dataset on the main search page and download the dataset and supplemental data files).
diff --git a/general/datasets/Epfl_lisp_muspmetcd1213/acknowledgment.rtf b/general/datasets/Epfl_lisp_muspmetcd1213/acknowledgment.rtf
new file mode 100644
index 0000000..cdb89a8
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcd1213/acknowledgment.rtf
@@ -0,0 +1 @@
+We would like to thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays. The work in the Auwerx lab was supported by the Ecole Polytechnique Federale de Lausanne, the EU Ideas program (AdG-23138 and AdG-322424), the NIH (R01HL106511-01A and R01AG043930), and the Swiss National Science Foundation (31003A- 124713 and 31003A-125487 and CSRII3-1362).
diff --git a/general/datasets/Epfl_lisp_muspmetcd1213/cases.rtf b/general/datasets/Epfl_lisp_muspmetcd1213/cases.rtf
new file mode 100644
index 0000000..ced8242
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcd1213/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, roughly 10 male animals were born and weaned at 3 weeks of age. These cohorts were then separated evenly into two cohorts at 8 weeks of age: up to 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and up to 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). A total of 195 CD animals and 189 HFD animals comprised these original 82 cohorts (42 on CD, 40 on HFD, all 40 overlap except for 2 strains, BXD60 and BXD92a (aka BXD65b), which are unique to CD). For the next 8 weeks, animals adjusted to the diet and housing situation. From 16 to 24 weeks of age, animals were phenotyped for respiration, oral glucose response, cold tolerance, basal activity, VO2max exercise, and voluntary exercise. Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest, undisturbed except for a weekly cage change and weighing. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion.
diff --git a/general/datasets/Epfl_lisp_muspmetcd1213/citation.rtf b/general/datasets/Epfl_lisp_muspmetcd1213/citation.rtf
new file mode 100644
index 0000000..f946bb0
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcd1213/citation.rtf
@@ -0,0 +1,3 @@
+Pirinen et al., Cell Metabolism 2014. Pharmacological inhibition of poly(ADP-ribose) polymerases improves fitness and mitochondrial function in skeletal muscle. PMID 24814482.
+
+Williams et al., PLoS Genetics 2014. An evolutionarily conserved role for the aryl hydrocarbon receptor in the regulation of movement. PMID 25255223.
diff --git a/general/datasets/Epfl_lisp_muspmetcd1213/contributors.rtf b/general/datasets/Epfl_lisp_muspmetcd1213/contributors.rtf
new file mode 100644
index 0000000..fd98a7c
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcd1213/contributors.rtf
@@ -0,0 +1 @@
+Williams EG, Andreux P, Auwerx J
diff --git a/general/datasets/Epfl_lisp_muspmetcd1213/platform.rtf b/general/datasets/Epfl_lisp_muspmetcd1213/platform.rtf
new file mode 100644
index 0000000..e123fe2
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcd1213/platform.rtf
@@ -0,0 +1 @@
+All arrays were Affymetrix Mouse Gene 1.0 ST, run in either October 2011 or August 2012 at the University of Tennessee Health Science Center. All .CEL files were normalized together after the second batch of data was collected.
diff --git a/general/datasets/Epfl_lisp_muspmetcd1213/processing.rtf b/general/datasets/Epfl_lisp_muspmetcd1213/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcd1213/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epfl_lisp_muspmetcd1213/summary.rtf b/general/datasets/Epfl_lisp_muspmetcd1213/summary.rtf
new file mode 100644
index 0000000..a785372
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcd1213/summary.rtf
@@ -0,0 +1 @@
+The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. It is difficult to say whether the major muscle phenotypes were broadly affected by HFD directly, or whether the phenotypic variance was as a consequence of the induced weight gain and other deleterious effects of the HFD (e.g. see phenotype traits ID 17717 and 17718 for nighttime activity in CD and HFD cohorts, respectively).
diff --git a/general/datasets/Epfl_lisp_muspmetcd1213/tissue.rtf b/general/datasets/Epfl_lisp_muspmetcd1213/tissue.rtf
new file mode 100644
index 0000000..c4913a4
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcd1213/tissue.rtf
@@ -0,0 +1,3 @@
+The quadriceps were taken near the end of the pipeline, roughly 6–10 minutes after completion of perfusion. Quadriceps were collected by cutting evenly across the upper axis of the femoral bone. Quadriceps muscle lying below or beside this femoral axis was not taken. The quadriceps was then placed in liquid nitrogen. At a later date, quadriceps were retrieved from -80 storage and shattered in liquid nitrogen. Roughly ~100 mg fragments were taken at random for mRNA preparation for every individual. To account potential differences in the tissue taken (as the tissue was not pulverized into powder), all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
+
+Tissue preparation was done in two different steps: the first half of the cohorts were run in October 2011, while the second half was run in August 2012. This tissue was the first microarray run at this platform, and thus the quadriceps served as a pilot to ensure that data quality would be good. The first half of the cohorts are: CD: C57, DBA, 44, 45, 51, 55, 61, 62, 63, 66, 70, 73, 75, 80, 83, 87, 89, 90, 96. HFD: C57, DBA, 44, 45, 51, 55, 61, 62, 63, 66, 70, 73, 75, 80, 83, 87, 90, 96, 100. The second half of the cohorts were the remainder. The preparation of all samples was done by the same technician with the same technique, other than the year time differential
diff --git a/general/datasets/Epfl_lisp_muspmetcdhfd1213/acknowledgment.rtf b/general/datasets/Epfl_lisp_muspmetcdhfd1213/acknowledgment.rtf
new file mode 100644
index 0000000..cdb89a8
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcdhfd1213/acknowledgment.rtf
@@ -0,0 +1 @@
+We would like to thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays. The work in the Auwerx lab was supported by the Ecole Polytechnique Federale de Lausanne, the EU Ideas program (AdG-23138 and AdG-322424), the NIH (R01HL106511-01A and R01AG043930), and the Swiss National Science Foundation (31003A- 124713 and 31003A-125487 and CSRII3-1362).
diff --git a/general/datasets/Epfl_lisp_muspmetcdhfd1213/cases.rtf b/general/datasets/Epfl_lisp_muspmetcdhfd1213/cases.rtf
new file mode 100644
index 0000000..ced8242
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcdhfd1213/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, roughly 10 male animals were born and weaned at 3 weeks of age. These cohorts were then separated evenly into two cohorts at 8 weeks of age: up to 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and up to 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). A total of 195 CD animals and 189 HFD animals comprised these original 82 cohorts (42 on CD, 40 on HFD, all 40 overlap except for 2 strains, BXD60 and BXD92a (aka BXD65b), which are unique to CD). For the next 8 weeks, animals adjusted to the diet and housing situation. From 16 to 24 weeks of age, animals were phenotyped for respiration, oral glucose response, cold tolerance, basal activity, VO2max exercise, and voluntary exercise. Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest, undisturbed except for a weekly cage change and weighing. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion.
diff --git a/general/datasets/Epfl_lisp_muspmetcdhfd1213/citation.rtf b/general/datasets/Epfl_lisp_muspmetcdhfd1213/citation.rtf
new file mode 100644
index 0000000..f946bb0
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcdhfd1213/citation.rtf
@@ -0,0 +1,3 @@
+Pirinen et al., Cell Metabolism 2014. Pharmacological inhibition of poly(ADP-ribose) polymerases improves fitness and mitochondrial function in skeletal muscle. PMID 24814482.
+
+Williams et al., PLoS Genetics 2014. An evolutionarily conserved role for the aryl hydrocarbon receptor in the regulation of movement. PMID 25255223.
diff --git a/general/datasets/Epfl_lisp_muspmetcdhfd1213/contributors.rtf b/general/datasets/Epfl_lisp_muspmetcdhfd1213/contributors.rtf
new file mode 100644
index 0000000..fd98a7c
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcdhfd1213/contributors.rtf
@@ -0,0 +1 @@
+Williams EG, Andreux P, Auwerx J
diff --git a/general/datasets/Epfl_lisp_muspmetcdhfd1213/platform.rtf b/general/datasets/Epfl_lisp_muspmetcdhfd1213/platform.rtf
new file mode 100644
index 0000000..e123fe2
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcdhfd1213/platform.rtf
@@ -0,0 +1 @@
+All arrays were Affymetrix Mouse Gene 1.0 ST, run in either October 2011 or August 2012 at the University of Tennessee Health Science Center. All .CEL files were normalized together after the second batch of data was collected.
diff --git a/general/datasets/Epfl_lisp_muspmetcdhfd1213/processing.rtf b/general/datasets/Epfl_lisp_muspmetcdhfd1213/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcdhfd1213/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epfl_lisp_muspmetcdhfd1213/summary.rtf b/general/datasets/Epfl_lisp_muspmetcdhfd1213/summary.rtf
new file mode 100644
index 0000000..a785372
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcdhfd1213/summary.rtf
@@ -0,0 +1 @@
+The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. It is difficult to say whether the major muscle phenotypes were broadly affected by HFD directly, or whether the phenotypic variance was as a consequence of the induced weight gain and other deleterious effects of the HFD (e.g. see phenotype traits ID 17717 and 17718 for nighttime activity in CD and HFD cohorts, respectively).
diff --git a/general/datasets/Epfl_lisp_muspmetcdhfd1213/tissue.rtf b/general/datasets/Epfl_lisp_muspmetcdhfd1213/tissue.rtf
new file mode 100644
index 0000000..c4913a4
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmetcdhfd1213/tissue.rtf
@@ -0,0 +1,3 @@
+The quadriceps were taken near the end of the pipeline, roughly 6–10 minutes after completion of perfusion. Quadriceps were collected by cutting evenly across the upper axis of the femoral bone. Quadriceps muscle lying below or beside this femoral axis was not taken. The quadriceps was then placed in liquid nitrogen. At a later date, quadriceps were retrieved from -80 storage and shattered in liquid nitrogen. Roughly ~100 mg fragments were taken at random for mRNA preparation for every individual. To account potential differences in the tissue taken (as the tissue was not pulverized into powder), all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
+
+Tissue preparation was done in two different steps: the first half of the cohorts were run in October 2011, while the second half was run in August 2012. This tissue was the first microarray run at this platform, and thus the quadriceps served as a pilot to ensure that data quality would be good. The first half of the cohorts are: CD: C57, DBA, 44, 45, 51, 55, 61, 62, 63, 66, 70, 73, 75, 80, 83, 87, 89, 90, 96. HFD: C57, DBA, 44, 45, 51, 55, 61, 62, 63, 66, 70, 73, 75, 80, 83, 87, 90, 96, 100. The second half of the cohorts were the remainder. The preparation of all samples was done by the same technician with the same technique, other than the year time differential
diff --git a/general/datasets/Epfl_lisp_muspmethfd1213/acknowledgment.rtf b/general/datasets/Epfl_lisp_muspmethfd1213/acknowledgment.rtf
new file mode 100644
index 0000000..cdb89a8
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmethfd1213/acknowledgment.rtf
@@ -0,0 +1 @@
+We would like to thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays. The work in the Auwerx lab was supported by the Ecole Polytechnique Federale de Lausanne, the EU Ideas program (AdG-23138 and AdG-322424), the NIH (R01HL106511-01A and R01AG043930), and the Swiss National Science Foundation (31003A- 124713 and 31003A-125487 and CSRII3-1362).
diff --git a/general/datasets/Epfl_lisp_muspmethfd1213/cases.rtf b/general/datasets/Epfl_lisp_muspmethfd1213/cases.rtf
new file mode 100644
index 0000000..ced8242
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmethfd1213/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, roughly 10 male animals were born and weaned at 3 weeks of age. These cohorts were then separated evenly into two cohorts at 8 weeks of age: up to 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and up to 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). A total of 195 CD animals and 189 HFD animals comprised these original 82 cohorts (42 on CD, 40 on HFD, all 40 overlap except for 2 strains, BXD60 and BXD92a (aka BXD65b), which are unique to CD). For the next 8 weeks, animals adjusted to the diet and housing situation. From 16 to 24 weeks of age, animals were phenotyped for respiration, oral glucose response, cold tolerance, basal activity, VO2max exercise, and voluntary exercise. Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest, undisturbed except for a weekly cage change and weighing. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion.
diff --git a/general/datasets/Epfl_lisp_muspmethfd1213/citation.rtf b/general/datasets/Epfl_lisp_muspmethfd1213/citation.rtf
new file mode 100644
index 0000000..f946bb0
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmethfd1213/citation.rtf
@@ -0,0 +1,3 @@
+Pirinen et al., Cell Metabolism 2014. Pharmacological inhibition of poly(ADP-ribose) polymerases improves fitness and mitochondrial function in skeletal muscle. PMID 24814482.
+
+Williams et al., PLoS Genetics 2014. An evolutionarily conserved role for the aryl hydrocarbon receptor in the regulation of movement. PMID 25255223.
diff --git a/general/datasets/Epfl_lisp_muspmethfd1213/contributors.rtf b/general/datasets/Epfl_lisp_muspmethfd1213/contributors.rtf
new file mode 100644
index 0000000..fd98a7c
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmethfd1213/contributors.rtf
@@ -0,0 +1 @@
+Williams EG, Andreux P, Auwerx J
diff --git a/general/datasets/Epfl_lisp_muspmethfd1213/platform.rtf b/general/datasets/Epfl_lisp_muspmethfd1213/platform.rtf
new file mode 100644
index 0000000..e123fe2
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmethfd1213/platform.rtf
@@ -0,0 +1 @@
+All arrays were Affymetrix Mouse Gene 1.0 ST, run in either October 2011 or August 2012 at the University of Tennessee Health Science Center. All .CEL files were normalized together after the second batch of data was collected.
diff --git a/general/datasets/Epfl_lisp_muspmethfd1213/processing.rtf b/general/datasets/Epfl_lisp_muspmethfd1213/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmethfd1213/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epfl_lisp_muspmethfd1213/summary.rtf b/general/datasets/Epfl_lisp_muspmethfd1213/summary.rtf
new file mode 100644
index 0000000..a785372
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmethfd1213/summary.rtf
@@ -0,0 +1 @@
+The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. It is difficult to say whether the major muscle phenotypes were broadly affected by HFD directly, or whether the phenotypic variance was as a consequence of the induced weight gain and other deleterious effects of the HFD (e.g. see phenotype traits ID 17717 and 17718 for nighttime activity in CD and HFD cohorts, respectively).
diff --git a/general/datasets/Epfl_lisp_muspmethfd1213/tissue.rtf b/general/datasets/Epfl_lisp_muspmethfd1213/tissue.rtf
new file mode 100644
index 0000000..c4913a4
--- /dev/null
+++ b/general/datasets/Epfl_lisp_muspmethfd1213/tissue.rtf
@@ -0,0 +1,3 @@
+The quadriceps were taken near the end of the pipeline, roughly 6–10 minutes after completion of perfusion. Quadriceps were collected by cutting evenly across the upper axis of the femoral bone. Quadriceps muscle lying below or beside this femoral axis was not taken. The quadriceps was then placed in liquid nitrogen. At a later date, quadriceps were retrieved from -80 storage and shattered in liquid nitrogen. Roughly ~100 mg fragments were taken at random for mRNA preparation for every individual. To account potential differences in the tissue taken (as the tissue was not pulverized into powder), all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
+
+Tissue preparation was done in two different steps: the first half of the cohorts were run in October 2011, while the second half was run in August 2012. This tissue was the first microarray run at this platform, and thus the quadriceps served as a pilot to ensure that data quality would be good. The first half of the cohorts are: CD: C57, DBA, 44, 45, 51, 55, 61, 62, 63, 66, 70, 73, 75, 80, 83, 87, 89, 90, 96. HFD: C57, DBA, 44, 45, 51, 55, 61, 62, 63, 66, 70, 73, 75, 80, 83, 87, 90, 96, 100. The second half of the cohorts were the remainder. The preparation of all samples was done by the same technician with the same technique, other than the year time differential
diff --git a/general/datasets/Epfl_lispbxdhecd0114/acknowledgment.rtf b/general/datasets/Epfl_lispbxdhecd0114/acknowledgment.rtf
new file mode 100644
index 0000000..91d3c6b
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecd0114/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
diff --git a/general/datasets/Epfl_lispbxdhecd0114/cases.rtf b/general/datasets/Epfl_lispbxdhecd0114/cases.rtf
new file mode 100644
index 0000000..d43280d
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecd0114/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Hearts were taken immediately after perfusion of the animal, weighed, and then frozen in liquid nitrogen no more than a minute after sacrifice.
diff --git a/general/datasets/Epfl_lispbxdhecd0114/citation.rtf b/general/datasets/Epfl_lispbxdhecd0114/citation.rtf
new file mode 100644
index 0000000..7073738
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecd0114/citation.rtf
@@ -0,0 +1 @@
+Please contact the laboratory of Rob Williams at the UTHSC
diff --git a/general/datasets/Epfl_lispbxdhecd0114/contributors.rtf b/general/datasets/Epfl_lispbxdhecd0114/contributors.rtf
new file mode 100644
index 0000000..2d4632a
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecd0114/contributors.rtf
@@ -0,0 +1 @@
+Williams EG, Andreux PA, Auwerx J, Lu L, Williams RW
diff --git a/general/datasets/Epfl_lispbxdhecd0114/experiment-design.rtf b/general/datasets/Epfl_lispbxdhecd0114/experiment-design.rtf
new file mode 100644
index 0000000..7516c73
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecd0114/experiment-design.rtf
@@ -0,0 +1 @@
+All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
diff --git a/general/datasets/Epfl_lispbxdhecd0114/platform.rtf b/general/datasets/Epfl_lispbxdhecd0114/platform.rtf
new file mode 100644
index 0000000..ee667b4
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecd0114/platform.rtf
@@ -0,0 +1 @@
+All arrays were Affymetrix Mouse Gene 2.0 ST, prepared and run simultaneously in a single batch in January 2014 by Lorne Rose at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epfl_lispbxdhecd0114/processing.rtf b/general/datasets/Epfl_lispbxdhecd0114/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecd0114/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epfl_lispbxdhecd0114/summary.rtf b/general/datasets/Epfl_lispbxdhecd0114/summary.rtf
new file mode 100644
index 0000000..7fcc1a9
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecd0114/summary.rtf
@@ -0,0 +1 @@
+The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
diff --git a/general/datasets/Epfl_lispbxdhecd0114/tissue.rtf b/general/datasets/Epfl_lispbxdhecd0114/tissue.rtf
new file mode 100644
index 0000000..eebcb20
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecd0114/tissue.rtf
@@ -0,0 +1 @@
+Hearts were later shattered in liquid nitrogen, usually broken into 2-4 pieces, and around half of the sample (at random) was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort, thus differences due to different segments of the heart being taken should be mitigated, although not eliminated, and researchers examining extremely specific transcriptional regulation in the heart should keep this in mind. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epfl_lispbxdhecdex0114/acknowledgment.rtf b/general/datasets/Epfl_lispbxdhecdex0114/acknowledgment.rtf
new file mode 100644
index 0000000..91d3c6b
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecdex0114/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
diff --git a/general/datasets/Epfl_lispbxdhecdex0114/cases.rtf b/general/datasets/Epfl_lispbxdhecdex0114/cases.rtf
new file mode 100644
index 0000000..d43280d
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecdex0114/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Hearts were taken immediately after perfusion of the animal, weighed, and then frozen in liquid nitrogen no more than a minute after sacrifice.
diff --git a/general/datasets/Epfl_lispbxdhecdex0114/citation.rtf b/general/datasets/Epfl_lispbxdhecdex0114/citation.rtf
new file mode 100644
index 0000000..7073738
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecdex0114/citation.rtf
@@ -0,0 +1 @@
+Please contact the laboratory of Rob Williams at the UTHSC
diff --git a/general/datasets/Epfl_lispbxdhecdex0114/contributors.rtf b/general/datasets/Epfl_lispbxdhecdex0114/contributors.rtf
new file mode 100644
index 0000000..2d4632a
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecdex0114/contributors.rtf
@@ -0,0 +1 @@
+Williams EG, Andreux PA, Auwerx J, Lu L, Williams RW
diff --git a/general/datasets/Epfl_lispbxdhecdex0114/experiment-design.rtf b/general/datasets/Epfl_lispbxdhecdex0114/experiment-design.rtf
new file mode 100644
index 0000000..7516c73
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecdex0114/experiment-design.rtf
@@ -0,0 +1 @@
+All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
diff --git a/general/datasets/Epfl_lispbxdhecdex0114/platform.rtf b/general/datasets/Epfl_lispbxdhecdex0114/platform.rtf
new file mode 100644
index 0000000..ee667b4
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecdex0114/platform.rtf
@@ -0,0 +1 @@
+All arrays were Affymetrix Mouse Gene 2.0 ST, prepared and run simultaneously in a single batch in January 2014 by Lorne Rose at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epfl_lispbxdhecdex0114/processing.rtf b/general/datasets/Epfl_lispbxdhecdex0114/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecdex0114/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epfl_lispbxdhecdex0114/summary.rtf b/general/datasets/Epfl_lispbxdhecdex0114/summary.rtf
new file mode 100644
index 0000000..7fcc1a9
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecdex0114/summary.rtf
@@ -0,0 +1 @@
+The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
diff --git a/general/datasets/Epfl_lispbxdhecdex0114/tissue.rtf b/general/datasets/Epfl_lispbxdhecdex0114/tissue.rtf
new file mode 100644
index 0000000..eebcb20
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhecdex0114/tissue.rtf
@@ -0,0 +1 @@
+Hearts were later shattered in liquid nitrogen, usually broken into 2-4 pieces, and around half of the sample (at random) was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort, thus differences due to different segments of the heart being taken should be mitigated, although not eliminated, and researchers examining extremely specific transcriptional regulation in the heart should keep this in mind. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epfl_lispbxdhehfd0114/acknowledgment.rtf b/general/datasets/Epfl_lispbxdhehfd0114/acknowledgment.rtf
new file mode 100644
index 0000000..91d3c6b
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfd0114/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
diff --git a/general/datasets/Epfl_lispbxdhehfd0114/cases.rtf b/general/datasets/Epfl_lispbxdhehfd0114/cases.rtf
new file mode 100644
index 0000000..d43280d
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfd0114/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Hearts were taken immediately after perfusion of the animal, weighed, and then frozen in liquid nitrogen no more than a minute after sacrifice.
diff --git a/general/datasets/Epfl_lispbxdhehfd0114/citation.rtf b/general/datasets/Epfl_lispbxdhehfd0114/citation.rtf
new file mode 100644
index 0000000..7073738
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfd0114/citation.rtf
@@ -0,0 +1 @@
+Please contact the laboratory of Rob Williams at the UTHSC
diff --git a/general/datasets/Epfl_lispbxdhehfd0114/contributors.rtf b/general/datasets/Epfl_lispbxdhehfd0114/contributors.rtf
new file mode 100644
index 0000000..2d4632a
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfd0114/contributors.rtf
@@ -0,0 +1 @@
+Williams EG, Andreux PA, Auwerx J, Lu L, Williams RW
diff --git a/general/datasets/Epfl_lispbxdhehfd0114/experiment-design.rtf b/general/datasets/Epfl_lispbxdhehfd0114/experiment-design.rtf
new file mode 100644
index 0000000..7516c73
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfd0114/experiment-design.rtf
@@ -0,0 +1 @@
+All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
diff --git a/general/datasets/Epfl_lispbxdhehfd0114/platform.rtf b/general/datasets/Epfl_lispbxdhehfd0114/platform.rtf
new file mode 100644
index 0000000..ee667b4
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfd0114/platform.rtf
@@ -0,0 +1 @@
+All arrays were Affymetrix Mouse Gene 2.0 ST, prepared and run simultaneously in a single batch in January 2014 by Lorne Rose at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epfl_lispbxdhehfd0114/processing.rtf b/general/datasets/Epfl_lispbxdhehfd0114/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfd0114/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epfl_lispbxdhehfd0114/summary.rtf b/general/datasets/Epfl_lispbxdhehfd0114/summary.rtf
new file mode 100644
index 0000000..7fcc1a9
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfd0114/summary.rtf
@@ -0,0 +1 @@
+The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
diff --git a/general/datasets/Epfl_lispbxdhehfd0114/tissue.rtf b/general/datasets/Epfl_lispbxdhehfd0114/tissue.rtf
new file mode 100644
index 0000000..eebcb20
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfd0114/tissue.rtf
@@ -0,0 +1 @@
+Hearts were later shattered in liquid nitrogen, usually broken into 2-4 pieces, and around half of the sample (at random) was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort, thus differences due to different segments of the heart being taken should be mitigated, although not eliminated, and researchers examining extremely specific transcriptional regulation in the heart should keep this in mind. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epfl_lispbxdhehfdex0114/acknowledgment.rtf b/general/datasets/Epfl_lispbxdhehfdex0114/acknowledgment.rtf
new file mode 100644
index 0000000..91d3c6b
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfdex0114/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays.
diff --git a/general/datasets/Epfl_lispbxdhehfdex0114/cases.rtf b/general/datasets/Epfl_lispbxdhehfdex0114/cases.rtf
new file mode 100644
index 0000000..d43280d
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfdex0114/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, allowing the animals to rest and reduce the direct expression effects of the phenotyping tests. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. Hearts were taken immediately after perfusion of the animal, weighed, and then frozen in liquid nitrogen no more than a minute after sacrifice.
diff --git a/general/datasets/Epfl_lispbxdhehfdex0114/citation.rtf b/general/datasets/Epfl_lispbxdhehfdex0114/citation.rtf
new file mode 100644
index 0000000..7073738
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfdex0114/citation.rtf
@@ -0,0 +1 @@
+Please contact the laboratory of Rob Williams at the UTHSC
diff --git a/general/datasets/Epfl_lispbxdhehfdex0114/contributors.rtf b/general/datasets/Epfl_lispbxdhehfdex0114/contributors.rtf
new file mode 100644
index 0000000..2d4632a
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfdex0114/contributors.rtf
@@ -0,0 +1 @@
+Williams EG, Andreux PA, Auwerx J, Lu L, Williams RW
diff --git a/general/datasets/Epfl_lispbxdhehfdex0114/experiment-design.rtf b/general/datasets/Epfl_lispbxdhehfdex0114/experiment-design.rtf
new file mode 100644
index 0000000..7516c73
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfdex0114/experiment-design.rtf
@@ -0,0 +1 @@
+All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning until sacrifice at around 29 weeks of age, or a high fat diet (HFD; Harlan TD.06414 60% kcal/fat, 20% protein, 20% carbohydrate) after 8 weeks of age until sacrifice around 29 weeks of age. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. C57BL/6J and DBA/2J were sourced from Janvier, which re-sources its “J” lines every 10 generations from The Jackson Laboratory. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
diff --git a/general/datasets/Epfl_lispbxdhehfdex0114/platform.rtf b/general/datasets/Epfl_lispbxdhehfdex0114/platform.rtf
new file mode 100644
index 0000000..ee667b4
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfdex0114/platform.rtf
@@ -0,0 +1 @@
+All arrays were Affymetrix Mouse Gene 2.0 ST, prepared and run simultaneously in a single batch in January 2014 by Lorne Rose at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epfl_lispbxdhehfdex0114/processing.rtf b/general/datasets/Epfl_lispbxdhehfdex0114/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfdex0114/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epfl_lispbxdhehfdex0114/summary.rtf b/general/datasets/Epfl_lispbxdhehfdex0114/summary.rtf
new file mode 100644
index 0000000..7fcc1a9
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfdex0114/summary.rtf
@@ -0,0 +1 @@
+The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. In this study, we examined both genetic variants across 40 strains of BXD and the two founder lines, in addition to a major environmental influence—long term feeding with chow diet (CD) or high fat diet (HFD)—to see how metabolic gene expression varies by genotype and environment, and gene-by-environment interactions. The basic heart phenotypes quantified in these cohorts were not affected by HFD feeding (e.g. blood pressure and heart rate).
diff --git a/general/datasets/Epfl_lispbxdhehfdex0114/tissue.rtf b/general/datasets/Epfl_lispbxdhehfdex0114/tissue.rtf
new file mode 100644
index 0000000..eebcb20
--- /dev/null
+++ b/general/datasets/Epfl_lispbxdhehfdex0114/tissue.rtf
@@ -0,0 +1 @@
+Hearts were later shattered in liquid nitrogen, usually broken into 2-4 pieces, and around half of the sample (at random) was taken for preparation. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort, thus differences due to different segments of the heart being taken should be mitigated, although not eliminated, and researchers examining extremely specific transcriptional regulation in the heart should keep this in mind. The pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epfladel1013/acknowledgment.rtf b/general/datasets/Epfladel1013/acknowledgment.rtf
new file mode 100644
index 0000000..291baee
--- /dev/null
+++ b/general/datasets/Epfladel1013/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice, Jesse Ingels who genotyped the congenic AHR line. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays. Thanks to Ian Duncan for supplying the mutant ss D. melanogaster lines. Discussions with Prof. Stephan Morgenthaler (EPFL) are also acknowledged.
diff --git a/general/datasets/Epfladel1013/cases.rtf b/general/datasets/Epfladel1013/cases.rtf
new file mode 100644
index 0000000..0e2dfc2
--- /dev/null
+++ b/general/datasets/Epfladel1013/cases.rtf
@@ -0,0 +1 @@
+42 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The quadriceps were the last tissue frozen in liquid nitrogen during the sacrifice, about 15 minutes after perfusion. Quadriceps were taken by cutting laterally at the knee.
diff --git a/general/datasets/Epfladel1013/citation.rtf b/general/datasets/Epfladel1013/citation.rtf
new file mode 100644
index 0000000..060cb36
--- /dev/null
+++ b/general/datasets/Epfladel1013/citation.rtf
@@ -0,0 +1 @@
+Williams EG, Mouchiroud L, Frochaux M, Pandey A, Andreux PA, Deplancke B, Auwerx J, An evolutionarily conserved role for the aryl hydrocarbon receptor in the regulation of movement. PLoS Genetics, 2014.
diff --git a/general/datasets/Epfladel1013/contributors.rtf b/general/datasets/Epfladel1013/contributors.rtf
new file mode 100644
index 0000000..182ad24
--- /dev/null
+++ b/general/datasets/Epfladel1013/contributors.rtf
@@ -0,0 +1 @@
+Williams EG, Mouchiroud L, Frochaux M, Pandey A, Andreux PA, Deplancke B, Auwerx J
diff --git a/general/datasets/Epfladel1013/experiment-design.rtf b/general/datasets/Epfladel1013/experiment-design.rtf
new file mode 100644
index 0000000..6329851
--- /dev/null
+++ b/general/datasets/Epfladel1013/experiment-design.rtf
@@ -0,0 +1 @@
+All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
diff --git a/general/datasets/Epfladel1013/platform.rtf b/general/datasets/Epfladel1013/platform.rtf
new file mode 100644
index 0000000..a8a63c9
--- /dev/null
+++ b/general/datasets/Epfladel1013/platform.rtf
@@ -0,0 +1 @@
+All arrays were Affymetrix Mouse Gene 2.0 ST, prepared and run simultaneously in a single batch in October 2013 by Lorne Rose at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epfladel1013/processing.rtf b/general/datasets/Epfladel1013/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epfladel1013/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epfladel1013/summary.rtf b/general/datasets/Epfladel1013/summary.rtf
new file mode 100644
index 0000000..07c710f
--- /dev/null
+++ b/general/datasets/Epfladel1013/summary.rtf
@@ -0,0 +1 @@
+The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. We here phenotype 43 BXD strains and observe they have large variation (~5-fold) in their spontaneous activity during waking hours. QTL analyses indicate that ~40% of this variance is attributable to a narrow locus containing the aryl hydrocarbon receptor (Ahr), a basic helix-loop-helix transcription factor with well-established roles in development and xenobiotic metabolism. Strains with the D2 allele of Ahr have reduced gene expression compared to those with the B6 allele, and have significantly higher spontaneous activity. This effect was also observed in B6 mice with a congenic D2 Ahr interval, and in B6 mice with a humanized AHR allele which, like the D2 allele, is expressed much less and has less enzymatic activity than the B6 allele. Ahr is highly conserved in invertebrates, and strikingly inhibition of its orthologs in D. melanogaster and C. elegans (spineless and ahr-1) leads to marked increases in basal activity. In mammals, Ahr has numerous ligands, but most are either non-selective (e.g. resveratrol) or highly toxic (e.g. 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)). Thus, we chose to examine a major environmental influence—long term feeding with high fat diet (HFD)—to see if the effects of Ahr are dependent on major metabolic differences. Interestingly, while HFD robustly halved movement across all strains, the QTL position and effects of Ahr remained unchanged, indicating that the effects are independent. The highly consistent effects of Ahr on movement indicate that changes in its constitutive activity have a role on spontaneous movement and may influence human behavior.
diff --git a/general/datasets/Epfladel1013/tissue.rtf b/general/datasets/Epfladel1013/tissue.rtf
new file mode 100644
index 0000000..f2bfb07
--- /dev/null
+++ b/general/datasets/Epfladel1013/tissue.rtf
@@ -0,0 +1 @@
+Brown adipose was later shattered in liquid nitrogen and about half was taken for each sample, although the size of the BAT varied dramatically. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epfladgl1013/acknowledgment.rtf b/general/datasets/Epfladgl1013/acknowledgment.rtf
new file mode 100644
index 0000000..291baee
--- /dev/null
+++ b/general/datasets/Epfladgl1013/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank Cristina Cartoni, Sébastien Lamy, and Charles Thomas at the Center of Phenogenomics (CPG, EPFL) for help in establishing and phenotyping the BXD mice, Jesse Ingels who genotyped the congenic AHR line. We thank the Molecular Resource Center of Excellence at The University of Tennessee Health Science Center processing all microarrays. Thanks to Ian Duncan for supplying the mutant ss D. melanogaster lines. Discussions with Prof. Stephan Morgenthaler (EPFL) are also acknowledged.
diff --git a/general/datasets/Epfladgl1013/cases.rtf b/general/datasets/Epfladgl1013/cases.rtf
new file mode 100644
index 0000000..0e2dfc2
--- /dev/null
+++ b/general/datasets/Epfladgl1013/cases.rtf
@@ -0,0 +1 @@
+42 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The quadriceps were the last tissue frozen in liquid nitrogen during the sacrifice, about 15 minutes after perfusion. Quadriceps were taken by cutting laterally at the knee.
diff --git a/general/datasets/Epfladgl1013/citation.rtf b/general/datasets/Epfladgl1013/citation.rtf
new file mode 100644
index 0000000..060cb36
--- /dev/null
+++ b/general/datasets/Epfladgl1013/citation.rtf
@@ -0,0 +1 @@
+Williams EG, Mouchiroud L, Frochaux M, Pandey A, Andreux PA, Deplancke B, Auwerx J, An evolutionarily conserved role for the aryl hydrocarbon receptor in the regulation of movement. PLoS Genetics, 2014.
diff --git a/general/datasets/Epfladgl1013/contributors.rtf b/general/datasets/Epfladgl1013/contributors.rtf
new file mode 100644
index 0000000..182ad24
--- /dev/null
+++ b/general/datasets/Epfladgl1013/contributors.rtf
@@ -0,0 +1 @@
+Williams EG, Mouchiroud L, Frochaux M, Pandey A, Andreux PA, Deplancke B, Auwerx J
diff --git a/general/datasets/Epfladgl1013/experiment-design.rtf b/general/datasets/Epfladgl1013/experiment-design.rtf
new file mode 100644
index 0000000..6329851
--- /dev/null
+++ b/general/datasets/Epfladgl1013/experiment-design.rtf
@@ -0,0 +1 @@
+All animals were communally housed by strain until phenotyping and fed a chow diet (CD; (Harlan 2018; 6% kCal/fat, 20% kCal/protein, 74% kCal/carbohydrate) throughout life after weaning. All BXD strains (BXD43–103) were originally sourced from the vivarium at the University of Tennessee Health Science Center (Memphis, TN, USA) then bred for two or more generations until progeny entered the phenotyping colony. For tissue collection on CD and HFD BXD cohorts, animals were sacrificed under isoflurane anesthesia and cardiac perfusion after an overnight fast. High fat diet treatment and two day isolation for the recording experiment were considered as having low impact on the animals’ welfare, while all other measurements and conditions were considered as having no negative impact. All research was approved by the Swiss cantonal veterinary authorities of Vaud under licenses 2257.0 and 2257.1.
diff --git a/general/datasets/Epfladgl1013/platform.rtf b/general/datasets/Epfladgl1013/platform.rtf
new file mode 100644
index 0000000..a8a63c9
--- /dev/null
+++ b/general/datasets/Epfladgl1013/platform.rtf
@@ -0,0 +1 @@
+All arrays were Affymetrix Mouse Gene 2.0 ST, prepared and run simultaneously in a single batch in October 2013 by Lorne Rose at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epfladgl1013/processing.rtf b/general/datasets/Epfladgl1013/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epfladgl1013/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epfladgl1013/summary.rtf b/general/datasets/Epfladgl1013/summary.rtf
new file mode 100644
index 0000000..07c710f
--- /dev/null
+++ b/general/datasets/Epfladgl1013/summary.rtf
@@ -0,0 +1 @@
+The BXD genetic reference population is a recombinant inbred panel descended from crosses between the C57BL/6 (B6) and DBA/2 (D2) strains of mice, which segregate for about 5 million sequence variants. Recently, some these variants have been established with effects on general metabolic phenotypes such as glucose response and bone strength. We here phenotype 43 BXD strains and observe they have large variation (~5-fold) in their spontaneous activity during waking hours. QTL analyses indicate that ~40% of this variance is attributable to a narrow locus containing the aryl hydrocarbon receptor (Ahr), a basic helix-loop-helix transcription factor with well-established roles in development and xenobiotic metabolism. Strains with the D2 allele of Ahr have reduced gene expression compared to those with the B6 allele, and have significantly higher spontaneous activity. This effect was also observed in B6 mice with a congenic D2 Ahr interval, and in B6 mice with a humanized AHR allele which, like the D2 allele, is expressed much less and has less enzymatic activity than the B6 allele. Ahr is highly conserved in invertebrates, and strikingly inhibition of its orthologs in D. melanogaster and C. elegans (spineless and ahr-1) leads to marked increases in basal activity. In mammals, Ahr has numerous ligands, but most are either non-selective (e.g. resveratrol) or highly toxic (e.g. 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD)). Thus, we chose to examine a major environmental influence—long term feeding with high fat diet (HFD)—to see if the effects of Ahr are dependent on major metabolic differences. Interestingly, while HFD robustly halved movement across all strains, the QTL position and effects of Ahr remained unchanged, indicating that the effects are independent. The highly consistent effects of Ahr on movement indicate that changes in its constitutive activity have a role on spontaneous movement and may influence human behavior.
diff --git a/general/datasets/Epfladgl1013/tissue.rtf b/general/datasets/Epfladgl1013/tissue.rtf
new file mode 100644
index 0000000..f2bfb07
--- /dev/null
+++ b/general/datasets/Epfladgl1013/tissue.rtf
@@ -0,0 +1 @@
+Brown adipose was later shattered in liquid nitrogen and about half was taken for each sample, although the size of the BAT varied dramatically. All ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflbxdprot0513/cases.rtf b/general/datasets/Epflbxdprot0513/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflbxdprot0513/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflbxdprot0513/contributors.rtf b/general/datasets/Epflbxdprot0513/contributors.rtf
new file mode 100644
index 0000000..e0d9702
--- /dev/null
+++ b/general/datasets/Epflbxdprot0513/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Houten SM, Argmann CA, Wolski W, Auwerx J, Aebersold R.
diff --git a/general/datasets/Epflbxdprot0513/notes.rtf b/general/datasets/Epflbxdprot0513/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflbxdprot0513/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflbxdprot0513/platform.rtf b/general/datasets/Epflbxdprot0513/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflbxdprot0513/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflbxdprot0513/summary.rtf b/general/datasets/Epflbxdprot0513/summary.rtf
new file mode 100644
index 0000000..8797309
--- /dev/null
+++ b/general/datasets/Epflbxdprot0513/summary.rtf
@@ -0,0 +1,5 @@
+Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
+
+Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
+
+Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/Epflbxdprot0513/tissue.rtf b/general/datasets/Epflbxdprot0513/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflbxdprot0513/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflbxdprotcd0513/cases.rtf b/general/datasets/Epflbxdprotcd0513/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflbxdprotcd0513/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflbxdprotcd0513/contributors.rtf b/general/datasets/Epflbxdprotcd0513/contributors.rtf
new file mode 100644
index 0000000..e0d9702
--- /dev/null
+++ b/general/datasets/Epflbxdprotcd0513/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Houten SM, Argmann CA, Wolski W, Auwerx J, Aebersold R.
diff --git a/general/datasets/Epflbxdprotcd0513/notes.rtf b/general/datasets/Epflbxdprotcd0513/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflbxdprotcd0513/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflbxdprotcd0513/platform.rtf b/general/datasets/Epflbxdprotcd0513/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflbxdprotcd0513/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflbxdprotcd0513/summary.rtf b/general/datasets/Epflbxdprotcd0513/summary.rtf
new file mode 100644
index 0000000..8797309
--- /dev/null
+++ b/general/datasets/Epflbxdprotcd0513/summary.rtf
@@ -0,0 +1,5 @@
+Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
+
+Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
+
+Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/Epflbxdprotcd0513/tissue.rtf b/general/datasets/Epflbxdprotcd0513/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflbxdprotcd0513/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflbxdprotcd_cdhfdrpn0214/cases.rtf b/general/datasets/Epflbxdprotcd_cdhfdrpn0214/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflbxdprotcd_cdhfdrpn0214/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflbxdprotcd_cdhfdrpn0214/contributors.rtf b/general/datasets/Epflbxdprotcd_cdhfdrpn0214/contributors.rtf
new file mode 100644
index 0000000..e0d9702
--- /dev/null
+++ b/general/datasets/Epflbxdprotcd_cdhfdrpn0214/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Houten SM, Argmann CA, Wolski W, Auwerx J, Aebersold R.
diff --git a/general/datasets/Epflbxdprotcd_cdhfdrpn0214/notes.rtf b/general/datasets/Epflbxdprotcd_cdhfdrpn0214/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflbxdprotcd_cdhfdrpn0214/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflbxdprotcd_cdhfdrpn0214/platform.rtf b/general/datasets/Epflbxdprotcd_cdhfdrpn0214/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflbxdprotcd_cdhfdrpn0214/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflbxdprotcd_cdhfdrpn0214/summary.rtf b/general/datasets/Epflbxdprotcd_cdhfdrpn0214/summary.rtf
new file mode 100644
index 0000000..8797309
--- /dev/null
+++ b/general/datasets/Epflbxdprotcd_cdhfdrpn0214/summary.rtf
@@ -0,0 +1,5 @@
+Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
+
+Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
+
+Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/Epflbxdprotcd_cdhfdrpn0214/tissue.rtf b/general/datasets/Epflbxdprotcd_cdhfdrpn0214/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflbxdprotcd_cdhfdrpn0214/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflbxdprotcdrpn0214/cases.rtf b/general/datasets/Epflbxdprotcdrpn0214/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflbxdprotcdrpn0214/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflbxdprotcdrpn0214/contributors.rtf b/general/datasets/Epflbxdprotcdrpn0214/contributors.rtf
new file mode 100644
index 0000000..e0d9702
--- /dev/null
+++ b/general/datasets/Epflbxdprotcdrpn0214/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Houten SM, Argmann CA, Wolski W, Auwerx J, Aebersold R.
diff --git a/general/datasets/Epflbxdprotcdrpn0214/notes.rtf b/general/datasets/Epflbxdprotcdrpn0214/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflbxdprotcdrpn0214/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflbxdprotcdrpn0214/platform.rtf b/general/datasets/Epflbxdprotcdrpn0214/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflbxdprotcdrpn0214/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflbxdprotcdrpn0214/summary.rtf b/general/datasets/Epflbxdprotcdrpn0214/summary.rtf
new file mode 100644
index 0000000..8797309
--- /dev/null
+++ b/general/datasets/Epflbxdprotcdrpn0214/summary.rtf
@@ -0,0 +1,5 @@
+Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
+
+Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
+
+Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/Epflbxdprotcdrpn0214/tissue.rtf b/general/datasets/Epflbxdprotcdrpn0214/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflbxdprotcdrpn0214/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflbxdprotcdrpn0513/cases.rtf b/general/datasets/Epflbxdprotcdrpn0513/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflbxdprotcdrpn0513/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflbxdprotcdrpn0513/contributors.rtf b/general/datasets/Epflbxdprotcdrpn0513/contributors.rtf
new file mode 100644
index 0000000..e0d9702
--- /dev/null
+++ b/general/datasets/Epflbxdprotcdrpn0513/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Houten SM, Argmann CA, Wolski W, Auwerx J, Aebersold R.
diff --git a/general/datasets/Epflbxdprotcdrpn0513/notes.rtf b/general/datasets/Epflbxdprotcdrpn0513/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflbxdprotcdrpn0513/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflbxdprotcdrpn0513/platform.rtf b/general/datasets/Epflbxdprotcdrpn0513/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflbxdprotcdrpn0513/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflbxdprotcdrpn0513/summary.rtf b/general/datasets/Epflbxdprotcdrpn0513/summary.rtf
new file mode 100644
index 0000000..8797309
--- /dev/null
+++ b/general/datasets/Epflbxdprotcdrpn0513/summary.rtf
@@ -0,0 +1,5 @@
+Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
+
+Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
+
+Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/Epflbxdprotcdrpn0513/tissue.rtf b/general/datasets/Epflbxdprotcdrpn0513/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflbxdprotcdrpn0513/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflbxdprothfd0513/cases.rtf b/general/datasets/Epflbxdprothfd0513/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflbxdprothfd0513/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflbxdprothfd0513/contributors.rtf b/general/datasets/Epflbxdprothfd0513/contributors.rtf
new file mode 100644
index 0000000..e0d9702
--- /dev/null
+++ b/general/datasets/Epflbxdprothfd0513/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Houten SM, Argmann CA, Wolski W, Auwerx J, Aebersold R.
diff --git a/general/datasets/Epflbxdprothfd0513/notes.rtf b/general/datasets/Epflbxdprothfd0513/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflbxdprothfd0513/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflbxdprothfd0513/platform.rtf b/general/datasets/Epflbxdprothfd0513/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflbxdprothfd0513/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflbxdprothfd0513/summary.rtf b/general/datasets/Epflbxdprothfd0513/summary.rtf
new file mode 100644
index 0000000..8797309
--- /dev/null
+++ b/general/datasets/Epflbxdprothfd0513/summary.rtf
@@ -0,0 +1,5 @@
+Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
+
+Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
+
+Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/Epflbxdprothfd0513/tissue.rtf b/general/datasets/Epflbxdprothfd0513/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflbxdprothfd0513/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflbxdprothfdrpn0214/cases.rtf b/general/datasets/Epflbxdprothfdrpn0214/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflbxdprothfdrpn0214/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflbxdprothfdrpn0214/contributors.rtf b/general/datasets/Epflbxdprothfdrpn0214/contributors.rtf
new file mode 100644
index 0000000..e0d9702
--- /dev/null
+++ b/general/datasets/Epflbxdprothfdrpn0214/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Houten SM, Argmann CA, Wolski W, Auwerx J, Aebersold R.
diff --git a/general/datasets/Epflbxdprothfdrpn0214/notes.rtf b/general/datasets/Epflbxdprothfdrpn0214/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflbxdprothfdrpn0214/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflbxdprothfdrpn0214/platform.rtf b/general/datasets/Epflbxdprothfdrpn0214/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflbxdprothfdrpn0214/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflbxdprothfdrpn0214/summary.rtf b/general/datasets/Epflbxdprothfdrpn0214/summary.rtf
new file mode 100644
index 0000000..8797309
--- /dev/null
+++ b/general/datasets/Epflbxdprothfdrpn0214/summary.rtf
@@ -0,0 +1,5 @@
+Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
+
+Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
+
+Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/Epflbxdprothfdrpn0214/tissue.rtf b/general/datasets/Epflbxdprothfdrpn0214/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflbxdprothfdrpn0214/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflbxdprothfdrpn0513/cases.rtf b/general/datasets/Epflbxdprothfdrpn0513/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflbxdprothfdrpn0513/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflbxdprothfdrpn0513/contributors.rtf b/general/datasets/Epflbxdprothfdrpn0513/contributors.rtf
new file mode 100644
index 0000000..e0d9702
--- /dev/null
+++ b/general/datasets/Epflbxdprothfdrpn0513/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Houten SM, Argmann CA, Wolski W, Auwerx J, Aebersold R.
diff --git a/general/datasets/Epflbxdprothfdrpn0513/notes.rtf b/general/datasets/Epflbxdprothfdrpn0513/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflbxdprothfdrpn0513/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflbxdprothfdrpn0513/platform.rtf b/general/datasets/Epflbxdprothfdrpn0513/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflbxdprothfdrpn0513/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflbxdprothfdrpn0513/summary.rtf b/general/datasets/Epflbxdprothfdrpn0513/summary.rtf
new file mode 100644
index 0000000..8797309
--- /dev/null
+++ b/general/datasets/Epflbxdprothfdrpn0513/summary.rtf
@@ -0,0 +1,5 @@
+Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
+
+Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
+
+Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/Epflbxdprothfdrpn0513/tissue.rtf b/general/datasets/Epflbxdprothfdrpn0513/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflbxdprothfdrpn0513/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflbxdprotrpn0513/cases.rtf b/general/datasets/Epflbxdprotrpn0513/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflbxdprotrpn0513/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflbxdprotrpn0513/contributors.rtf b/general/datasets/Epflbxdprotrpn0513/contributors.rtf
new file mode 100644
index 0000000..e0d9702
--- /dev/null
+++ b/general/datasets/Epflbxdprotrpn0513/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Houten SM, Argmann CA, Wolski W, Auwerx J, Aebersold R.
diff --git a/general/datasets/Epflbxdprotrpn0513/notes.rtf b/general/datasets/Epflbxdprotrpn0513/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflbxdprotrpn0513/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflbxdprotrpn0513/platform.rtf b/general/datasets/Epflbxdprotrpn0513/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflbxdprotrpn0513/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflbxdprotrpn0513/summary.rtf b/general/datasets/Epflbxdprotrpn0513/summary.rtf
new file mode 100644
index 0000000..8797309
--- /dev/null
+++ b/general/datasets/Epflbxdprotrpn0513/summary.rtf
@@ -0,0 +1,5 @@
+Quantitative changes in transcriptome and proteome patterns relate genomic variation to specific phenotypes. Here we applied selected reaction monitoring (SRM), a targeted mass spectrometry method that supports the reliable and reproducible quantification of predetermined sets of proteins across a broad abundance range in complex samples to quantify 157 metabolic proteins in liver extracts from 40 genetically-diverse strains of the BXD mouse genetic reference population, after chow or high fat diet. We observed significant biological variation in protein levels, which were linked to transcript variation in ~30% of the cases. 14 genes mapped to quantitative trait loci (QTLs) at both the transcript and protein level, while a further 18 mapped only as transcripts (eQTLs), and 24 only as proteins (pQTLs). 79% of eQTLs were regulated by cis-mechanisms, as opposed to only 31% of pQTLs, indicating a more direct genetic connection between genes and their transcripts than between genes and their protein products. In some cases, QTLs could be linked to phenotypic changes across the BXDs. One such case indicates a novel animal model for an inborn error of metabolism that has been observed in humans; BXD mice with deficient DHTKD1 protein also exhibit 2-aminoadipic and 2-oxoadipic aciduria like seen in affected patients. Together, these findings show that quantitative, multi-layered genomic, transcriptomic, and proteomic analyses provide more power for connecting genetic variance to phenotypes in complex systems than each layer alone, and provide complementary information to identify novel regulatory networks of metabolic diseases.
+
+Note: please see associated dataset “Liver Proteome” EPFL/LISP BXD Liver, Hepatocytes, Soluable Proteins CD+HFD (Jul13) RPN” for protein data in the same animals. [NB: Data in review, but still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
+
+Note: please see associated dataset “LISP2” in BXD phenotypes for phenotype data on the same animals. [NB: Still unpublished as of Nov 2013, please contact admin.auwerx@epfl.ch for access]
diff --git a/general/datasets/Epflbxdprotrpn0513/tissue.rtf b/general/datasets/Epflbxdprotrpn0513/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflbxdprotrpn0513/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflethzbxdprotcd0514/notes.rtf b/general/datasets/Epflethzbxdprotcd0514/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflethzbxdprotcd0514/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflethzbxdprotcd_ls1114/notes.rtf b/general/datasets/Epflethzbxdprotcd_ls1114/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflethzbxdprotcd_ls1114/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflethzbxdprothf_ls1114/notes.rtf b/general/datasets/Epflethzbxdprothf_ls1114/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflethzbxdprothf_ls1114/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflethzbxdprothfd0514/notes.rtf b/general/datasets/Epflethzbxdprothfd0514/notes.rtf
new file mode 100644
index 0000000..ecdae60
--- /dev/null
+++ b/general/datasets/Epflethzbxdprothfd0514/notes.rtf
@@ -0,0 +1,16 @@
+SWATH
+
+SWATH MS is a novel technique that is based on data-independent acquisition (DIA) which aims to complement traditional mass spectrometry-based proteomics techniques such as shotgun and SRM methods. In principal, it allows a complete and permanent recording of all fragment ions of all peptide precursors in a biological sample and can thus potentially combine the advantages of shotgun (high throughput) with those of SRM (high reproducibility and sensitivity).
+
+The method uniquely combines a DIA methods with a innovative data analysis approach based on targeted data extraction developed in the Aebersold lab. Like in other DIA methods, the mass spectrometer cycles through precursor acquisition windows designed to cover the whole range of 400-1200 m/z - in which most of the proteotypic peptide precursors of an organism fall - within 2-4 seconds. During each cycle, the mass spectrometer will fragment all precursors from a given precursors window (e.g. 475 - 500 m/z for 25 Da windows) and record a complete, high accuracy fragment ion spectrum. The same range will be fragmented again in the next cycle, thus providing a time-resolved recording of fragment ions that elute on the chromatography. Thus the SWATH method provides highly multiplexed fragment ion spectra that are deterministically recorded over the complete chromatographic time.
+
+In the Malmstroem group, we are interested in the data-analysis challenge that is posed by DIA / SWATH data. Traditionally, DIA methods have been analyzed by trying to reconstruct the lineage of precursor and fragment ions based on their chromatographic elution profile, and then analysing the data in a workflow similar to those used in shotgun proteomics. However, these approaches suffered from low sensitivity and propagation of errors due to mis-assignment of fragment ions to precursor ions. We are thus working on automating targeted methods that are conceptually similar to SRM and allow querying the data multiple times with specific hypothesis, thus giving the researcher more control and specificity in the bioinformatic data analysis step. With these novel algorithms, it is potentially possible to explore a much larger part of the data that is present and obtain a nearly complete picture of a proteome.
+
+References
+
+
+ - Gillet, L. C., P. Navarro, S. Tate, H. Röst, N. Selevsek, L. Reiter, R. Bonner, and R. Aebersold (2012, June). Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: A new concept for consistent and accurate proteome analysis. Molecular & cellular proteomics : MCP 11 (6). PMID 22261725
+ - Purvine, S., J.-T. T. Eppel, E. C. Yi, and D. R. Goodlett (2003, June). Shotgun collision-induced dissociation of peptides using a time of flight mass analyzer. Proteomics 3 (6), 847-850.
+ - Plumb, R. S., K. A. Johnson, P. Rainville, B. W. Smith, I. D. Wilson, J. M. Castro-Perez, and J. K. Nicholson (2006). UPLC/MS(e); a new approach for generating molecular fragment information for biomarker structure elucidation. Rapid communications in mass spectrometry : RCM 20 (13), 1989-1994.
+ - Panchaud, A., A. Scherl, S. A. Shaffer, P. D. von Haller, H. D. Kulasekara, S. I. Miller, and D. R. Goodlett (2009, August). Precursor acquisition independent from ion count: how to dive deeper into the proteomics ocean. Analytical chemistry 81 (15), 6481-6488.
+
diff --git a/general/datasets/Epflmouseliverbothexrma0413/acknowledgment.rtf b/general/datasets/Epflmouseliverbothexrma0413/acknowledgment.rtf
new file mode 100644
index 0000000..3a26b41
--- /dev/null
+++ b/general/datasets/Epflmouseliverbothexrma0413/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/Epflmouseliverbothexrma0413/cases.rtf b/general/datasets/Epflmouseliverbothexrma0413/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflmouseliverbothexrma0413/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflmouseliverbothexrma0413/citation.rtf b/general/datasets/Epflmouseliverbothexrma0413/citation.rtf
new file mode 100644
index 0000000..46be451
--- /dev/null
+++ b/general/datasets/Epflmouseliverbothexrma0413/citation.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, and Aebersold R, Multilayered genetics and omics dissection of mitochondrial activity in a mouse reference population. Cell, 158(6), 2014.
diff --git a/general/datasets/Epflmouseliverbothexrma0413/contributors.rtf b/general/datasets/Epflmouseliverbothexrma0413/contributors.rtf
new file mode 100644
index 0000000..d3b16c7
--- /dev/null
+++ b/general/datasets/Epflmouseliverbothexrma0413/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, Aebersold R
diff --git a/general/datasets/Epflmouseliverbothexrma0413/platform.rtf b/general/datasets/Epflmouseliverbothexrma0413/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflmouseliverbothexrma0413/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflmouseliverbothexrma0413/processing.rtf b/general/datasets/Epflmouseliverbothexrma0413/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epflmouseliverbothexrma0413/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epflmouseliverbothexrma0413/summary.rtf b/general/datasets/Epflmouseliverbothexrma0413/summary.rtf
new file mode 100644
index 0000000..77c5606
--- /dev/null
+++ b/general/datasets/Epflmouseliverbothexrma0413/summary.rtf
@@ -0,0 +1 @@
+The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/Epflmouseliverbothexrma0413/tissue.rtf b/general/datasets/Epflmouseliverbothexrma0413/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflmouseliverbothexrma0413/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflmouselivercdex0413/acknowledgment.rtf b/general/datasets/Epflmouselivercdex0413/acknowledgment.rtf
new file mode 100644
index 0000000..3a26b41
--- /dev/null
+++ b/general/datasets/Epflmouselivercdex0413/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/Epflmouselivercdex0413/cases.rtf b/general/datasets/Epflmouselivercdex0413/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflmouselivercdex0413/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflmouselivercdex0413/citation.rtf b/general/datasets/Epflmouselivercdex0413/citation.rtf
new file mode 100644
index 0000000..46be451
--- /dev/null
+++ b/general/datasets/Epflmouselivercdex0413/citation.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, and Aebersold R, Multilayered genetics and omics dissection of mitochondrial activity in a mouse reference population. Cell, 158(6), 2014.
diff --git a/general/datasets/Epflmouselivercdex0413/contributors.rtf b/general/datasets/Epflmouselivercdex0413/contributors.rtf
new file mode 100644
index 0000000..d3b16c7
--- /dev/null
+++ b/general/datasets/Epflmouselivercdex0413/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, Aebersold R
diff --git a/general/datasets/Epflmouselivercdex0413/platform.rtf b/general/datasets/Epflmouselivercdex0413/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflmouselivercdex0413/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflmouselivercdex0413/processing.rtf b/general/datasets/Epflmouselivercdex0413/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epflmouselivercdex0413/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epflmouselivercdex0413/specifics.rtf b/general/datasets/Epflmouselivercdex0413/specifics.rtf
new file mode 100644
index 0000000..7c1a914
--- /dev/null
+++ b/general/datasets/Epflmouselivercdex0413/specifics.rtf
@@ -0,0 +1 @@
+Exon Level
\ No newline at end of file
diff --git a/general/datasets/Epflmouselivercdex0413/summary.rtf b/general/datasets/Epflmouselivercdex0413/summary.rtf
new file mode 100644
index 0000000..77c5606
--- /dev/null
+++ b/general/datasets/Epflmouselivercdex0413/summary.rtf
@@ -0,0 +1 @@
+The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/Epflmouselivercdex0413/tissue.rtf b/general/datasets/Epflmouselivercdex0413/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflmouselivercdex0413/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflmouselivercdhfdrma0818/acknowledgment.rtf b/general/datasets/Epflmouselivercdhfdrma0818/acknowledgment.rtf
new file mode 100644
index 0000000..3a26b41
--- /dev/null
+++ b/general/datasets/Epflmouselivercdhfdrma0818/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/Epflmouselivercdhfdrma0818/cases.rtf b/general/datasets/Epflmouselivercdhfdrma0818/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflmouselivercdhfdrma0818/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflmouselivercdhfdrma0818/citation.rtf b/general/datasets/Epflmouselivercdhfdrma0818/citation.rtf
new file mode 100644
index 0000000..46be451
--- /dev/null
+++ b/general/datasets/Epflmouselivercdhfdrma0818/citation.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, and Aebersold R, Multilayered genetics and omics dissection of mitochondrial activity in a mouse reference population. Cell, 158(6), 2014.
diff --git a/general/datasets/Epflmouselivercdhfdrma0818/contributors.rtf b/general/datasets/Epflmouselivercdhfdrma0818/contributors.rtf
new file mode 100644
index 0000000..d3b16c7
--- /dev/null
+++ b/general/datasets/Epflmouselivercdhfdrma0818/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, Aebersold R
diff --git a/general/datasets/Epflmouselivercdhfdrma0818/platform.rtf b/general/datasets/Epflmouselivercdhfdrma0818/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflmouselivercdhfdrma0818/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflmouselivercdhfdrma0818/processing.rtf b/general/datasets/Epflmouselivercdhfdrma0818/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epflmouselivercdhfdrma0818/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epflmouselivercdhfdrma0818/specifics.rtf b/general/datasets/Epflmouselivercdhfdrma0818/specifics.rtf
new file mode 100644
index 0000000..7bcb4de
--- /dev/null
+++ b/general/datasets/Epflmouselivercdhfdrma0818/specifics.rtf
@@ -0,0 +1 @@
+RMA Normalization CD + HFD combined
\ No newline at end of file
diff --git a/general/datasets/Epflmouselivercdhfdrma0818/summary.rtf b/general/datasets/Epflmouselivercdhfdrma0818/summary.rtf
new file mode 100644
index 0000000..77c5606
--- /dev/null
+++ b/general/datasets/Epflmouselivercdhfdrma0818/summary.rtf
@@ -0,0 +1 @@
+The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/Epflmouselivercdhfdrma0818/tissue.rtf b/general/datasets/Epflmouselivercdhfdrma0818/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflmouselivercdhfdrma0818/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflmouselivercdrma0413/acknowledgment.rtf b/general/datasets/Epflmouselivercdrma0413/acknowledgment.rtf
new file mode 100644
index 0000000..3a26b41
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0413/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/Epflmouselivercdrma0413/cases.rtf b/general/datasets/Epflmouselivercdrma0413/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0413/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflmouselivercdrma0413/citation.rtf b/general/datasets/Epflmouselivercdrma0413/citation.rtf
new file mode 100644
index 0000000..46be451
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0413/citation.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, and Aebersold R, Multilayered genetics and omics dissection of mitochondrial activity in a mouse reference population. Cell, 158(6), 2014.
diff --git a/general/datasets/Epflmouselivercdrma0413/contributors.rtf b/general/datasets/Epflmouselivercdrma0413/contributors.rtf
new file mode 100644
index 0000000..d3b16c7
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0413/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, Aebersold R
diff --git a/general/datasets/Epflmouselivercdrma0413/platform.rtf b/general/datasets/Epflmouselivercdrma0413/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0413/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflmouselivercdrma0413/processing.rtf b/general/datasets/Epflmouselivercdrma0413/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0413/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epflmouselivercdrma0413/summary.rtf b/general/datasets/Epflmouselivercdrma0413/summary.rtf
new file mode 100644
index 0000000..77c5606
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0413/summary.rtf
@@ -0,0 +1 @@
+The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/Epflmouselivercdrma0413/tissue.rtf b/general/datasets/Epflmouselivercdrma0413/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0413/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflmouselivercdrma0818/acknowledgment.rtf b/general/datasets/Epflmouselivercdrma0818/acknowledgment.rtf
new file mode 100644
index 0000000..3a26b41
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0818/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/Epflmouselivercdrma0818/cases.rtf b/general/datasets/Epflmouselivercdrma0818/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0818/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflmouselivercdrma0818/citation.rtf b/general/datasets/Epflmouselivercdrma0818/citation.rtf
new file mode 100644
index 0000000..46be451
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0818/citation.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, and Aebersold R, Multilayered genetics and omics dissection of mitochondrial activity in a mouse reference population. Cell, 158(6), 2014.
diff --git a/general/datasets/Epflmouselivercdrma0818/contributors.rtf b/general/datasets/Epflmouselivercdrma0818/contributors.rtf
new file mode 100644
index 0000000..d3b16c7
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0818/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, Aebersold R
diff --git a/general/datasets/Epflmouselivercdrma0818/platform.rtf b/general/datasets/Epflmouselivercdrma0818/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0818/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflmouselivercdrma0818/processing.rtf b/general/datasets/Epflmouselivercdrma0818/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0818/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epflmouselivercdrma0818/specifics.rtf b/general/datasets/Epflmouselivercdrma0818/specifics.rtf
new file mode 100644
index 0000000..8e24baa
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0818/specifics.rtf
@@ -0,0 +1 @@
+original rma normalization CD + HFD combined
diff --git a/general/datasets/Epflmouselivercdrma0818/summary.rtf b/general/datasets/Epflmouselivercdrma0818/summary.rtf
new file mode 100644
index 0000000..77c5606
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0818/summary.rtf
@@ -0,0 +1 @@
+The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/Epflmouselivercdrma0818/tissue.rtf b/general/datasets/Epflmouselivercdrma0818/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflmouselivercdrma0818/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflmouseliverhfcex0413/acknowledgment.rtf b/general/datasets/Epflmouseliverhfcex0413/acknowledgment.rtf
new file mode 100644
index 0000000..3a26b41
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfcex0413/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/Epflmouseliverhfcex0413/cases.rtf b/general/datasets/Epflmouseliverhfcex0413/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfcex0413/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflmouseliverhfcex0413/citation.rtf b/general/datasets/Epflmouseliverhfcex0413/citation.rtf
new file mode 100644
index 0000000..46be451
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfcex0413/citation.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, and Aebersold R, Multilayered genetics and omics dissection of mitochondrial activity in a mouse reference population. Cell, 158(6), 2014.
diff --git a/general/datasets/Epflmouseliverhfcex0413/contributors.rtf b/general/datasets/Epflmouseliverhfcex0413/contributors.rtf
new file mode 100644
index 0000000..d3b16c7
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfcex0413/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, Aebersold R
diff --git a/general/datasets/Epflmouseliverhfcex0413/platform.rtf b/general/datasets/Epflmouseliverhfcex0413/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfcex0413/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflmouseliverhfcex0413/processing.rtf b/general/datasets/Epflmouseliverhfcex0413/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfcex0413/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epflmouseliverhfcex0413/specifics.rtf b/general/datasets/Epflmouseliverhfcex0413/specifics.rtf
new file mode 100644
index 0000000..7c1a914
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfcex0413/specifics.rtf
@@ -0,0 +1 @@
+Exon Level
\ No newline at end of file
diff --git a/general/datasets/Epflmouseliverhfcex0413/summary.rtf b/general/datasets/Epflmouseliverhfcex0413/summary.rtf
new file mode 100644
index 0000000..77c5606
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfcex0413/summary.rtf
@@ -0,0 +1 @@
+The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/Epflmouseliverhfcex0413/tissue.rtf b/general/datasets/Epflmouseliverhfcex0413/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfcex0413/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflmouseliverhfdrma0413/acknowledgment.rtf b/general/datasets/Epflmouseliverhfdrma0413/acknowledgment.rtf
new file mode 100644
index 0000000..3a26b41
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0413/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/Epflmouseliverhfdrma0413/cases.rtf b/general/datasets/Epflmouseliverhfdrma0413/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0413/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflmouseliverhfdrma0413/citation.rtf b/general/datasets/Epflmouseliverhfdrma0413/citation.rtf
new file mode 100644
index 0000000..46be451
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0413/citation.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, and Aebersold R, Multilayered genetics and omics dissection of mitochondrial activity in a mouse reference population. Cell, 158(6), 2014.
diff --git a/general/datasets/Epflmouseliverhfdrma0413/contributors.rtf b/general/datasets/Epflmouseliverhfdrma0413/contributors.rtf
new file mode 100644
index 0000000..d3b16c7
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0413/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, Aebersold R
diff --git a/general/datasets/Epflmouseliverhfdrma0413/platform.rtf b/general/datasets/Epflmouseliverhfdrma0413/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0413/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflmouseliverhfdrma0413/processing.rtf b/general/datasets/Epflmouseliverhfdrma0413/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0413/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epflmouseliverhfdrma0413/specifics.rtf b/general/datasets/Epflmouseliverhfdrma0413/specifics.rtf
new file mode 100644
index 0000000..9f581ab
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0413/specifics.rtf
@@ -0,0 +1 @@
+High Fat Diet Only
diff --git a/general/datasets/Epflmouseliverhfdrma0413/summary.rtf b/general/datasets/Epflmouseliverhfdrma0413/summary.rtf
new file mode 100644
index 0000000..77c5606
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0413/summary.rtf
@@ -0,0 +1 @@
+The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/Epflmouseliverhfdrma0413/tissue.rtf b/general/datasets/Epflmouseliverhfdrma0413/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0413/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflmouseliverhfdrma0818/acknowledgment.rtf b/general/datasets/Epflmouseliverhfdrma0818/acknowledgment.rtf
new file mode 100644
index 0000000..3a26b41
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0818/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/Epflmouseliverhfdrma0818/cases.rtf b/general/datasets/Epflmouseliverhfdrma0818/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0818/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflmouseliverhfdrma0818/citation.rtf b/general/datasets/Epflmouseliverhfdrma0818/citation.rtf
new file mode 100644
index 0000000..46be451
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0818/citation.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, and Aebersold R, Multilayered genetics and omics dissection of mitochondrial activity in a mouse reference population. Cell, 158(6), 2014.
diff --git a/general/datasets/Epflmouseliverhfdrma0818/contributors.rtf b/general/datasets/Epflmouseliverhfdrma0818/contributors.rtf
new file mode 100644
index 0000000..d3b16c7
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0818/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, Aebersold R
diff --git a/general/datasets/Epflmouseliverhfdrma0818/platform.rtf b/general/datasets/Epflmouseliverhfdrma0818/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0818/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflmouseliverhfdrma0818/processing.rtf b/general/datasets/Epflmouseliverhfdrma0818/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0818/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epflmouseliverhfdrma0818/specifics.rtf b/general/datasets/Epflmouseliverhfdrma0818/specifics.rtf
new file mode 100644
index 0000000..521f92a
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0818/specifics.rtf
@@ -0,0 +1,65 @@
+HFD strain assignment errors to be fixed March 2019
+
+original rma normalization CD + HFD combined
+
+David Ashbrook analyzed strain assignment errors in March 2019. "I've more than doubled the number of markers up to 33, and can be pretty confident that a number of strains are labelled incorrectly, and what strains they should be. I've included a '?' if I'm not confident, or if I couldn't find a good match."
+
+BXD100?
+
+BXD51 > BXD55
+
+BXD55 > BXD51
+
+BXD63 > BXD43
+
+BXD73 > BXD79?
+
+BXD73a > BXD83
+
+BXD75 > BXD73a
+
+BXD79 > BXD81
+
+BXD81 > BXD84
+
+BXD83 > BXD85
+
+BXD84 > BXD87
+
+BXD85? > BXD89
+
+BXD87 > BXD90?
+
+BXD89 > BXD95
+
+BXD90 > BXD73
+
+BXD95 > BXD75
+
+
+
+
+
+I will try and add a few more markers to try and clear up the last few, but this hopefully gives you an idea of the extent of the problem. It also agrees with the strains that Rob highlighted as potential outliers in his e-mail.
+
+
+
+Best,
+
+David
+
+
+
+
+
+David Ashbrook, PhD
+Postdoctoral Fellow
+
+Department of Genetics, Genomics and Informatics
+Translational Science Research Building, Room 415
+University of Tennessee Health Science Center
+71 S Manassas St
+Memphis, TN, 38103
+
+https://davidashbrook.wordpress.com/
+dashbrook@uthsc.edu
diff --git a/general/datasets/Epflmouseliverhfdrma0818/summary.rtf b/general/datasets/Epflmouseliverhfdrma0818/summary.rtf
new file mode 100644
index 0000000..77c5606
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0818/summary.rtf
@@ -0,0 +1 @@
+The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/Epflmouseliverhfdrma0818/tissue.rtf b/general/datasets/Epflmouseliverhfdrma0818/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflmouseliverhfdrma0818/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflmouseliverrma0413/acknowledgment.rtf b/general/datasets/Epflmouseliverrma0413/acknowledgment.rtf
new file mode 100644
index 0000000..3a26b41
--- /dev/null
+++ b/general/datasets/Epflmouseliverrma0413/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors thank A. van Cruchten and W. Smit for the serum analysis of 2-AA. The CoLaus study received financial contributions from GlaxoSmithKline, the Faculty of Biology and Medicine of Lausanne, and the Swiss National Science Foundation (SNSF; 33CSCO-122661). The authors thank P. Vollenweider, G. Waeber, V. Mooser and D. Waterworth, Co-PIs of the CoLaus study. Special thanks to M. Bochud, Y. Barreau, M. Firmann, V. Mayor, A. Bastian, B. Ramic, M. Moranville, M. Baumer, M. Sagette, J. Ecoffey and S. Mermoud for data collection. YW was supported by the ERC (Proteomics v3.0; AdG-233226 to RA), and the LiverX program and EGW by a fellowship from the Fondation Romande pour la Recherche sur le Diabète. JA is the Nestlé Chair in Energy Metabolism. Research was supported by the EPFL, ETHZ, ERC (Sirtuins; AdG-231138 and Proteomics v3.0; AdG-233226), Velux Stiftung, LiverX and AgingX programs of the Swiss Initiative for Systems Biology (51RTP0-151019 and 2013/153), SNSF (31003A-140780, 31003A-143914, and CSRII3-136201), and the NIH (R01AG043930).
diff --git a/general/datasets/Epflmouseliverrma0413/cases.rtf b/general/datasets/Epflmouseliverrma0413/cases.rtf
new file mode 100644
index 0000000..ed4ced8
--- /dev/null
+++ b/general/datasets/Epflmouseliverrma0413/cases.rtf
@@ -0,0 +1 @@
+40 strains of the BXD family (BXD43 – BXD103) and both parental strains (C57BL/6 and DBA/2) were born and raised at the EPFL in Switzerland prior to inclusion in this study. For each strain, 10 male animals were born and then separated evenly into two cohorts at 8 weeks of age: 5 animals per strain on a chow diet (6% kcal/fat, 20% protein, 74% carbohydrate) and 5 animals per strain on high fat diet (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. Animals were fasted overnight prior to sacrifice, which occurred between 9am and 11am after isoflurane anesthesia and perfusion. The gall bladder was removed, and then the livers were immediately frozen in liquid nitrogen.
diff --git a/general/datasets/Epflmouseliverrma0413/citation.rtf b/general/datasets/Epflmouseliverrma0413/citation.rtf
new file mode 100644
index 0000000..46be451
--- /dev/null
+++ b/general/datasets/Epflmouseliverrma0413/citation.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, and Aebersold R, Multilayered genetics and omics dissection of mitochondrial activity in a mouse reference population. Cell, 158(6), 2014.
diff --git a/general/datasets/Epflmouseliverrma0413/contributors.rtf b/general/datasets/Epflmouseliverrma0413/contributors.rtf
new file mode 100644
index 0000000..d3b16c7
--- /dev/null
+++ b/general/datasets/Epflmouseliverrma0413/contributors.rtf
@@ -0,0 +1 @@
+Wu Y, Williams EG, Dubuis S, Mottis A, Jovaisaite V, Houten SM, Argmann CA, Faridi P, Wolski W, Kutalik Z, Zamboni N, Auwerx J, Aebersold R
diff --git a/general/datasets/Epflmouseliverrma0413/platform.rtf b/general/datasets/Epflmouseliverrma0413/platform.rtf
new file mode 100644
index 0000000..4a33b7c
--- /dev/null
+++ b/general/datasets/Epflmouseliverrma0413/platform.rtf
@@ -0,0 +1 @@
+All 81 arrays were Affymetrix Mouse Gene 1.0 ST, run together in a single batch in March/April 2013 at the University of Tennessee Health Science Center.
diff --git a/general/datasets/Epflmouseliverrma0413/processing.rtf b/general/datasets/Epflmouseliverrma0413/processing.rtf
new file mode 100644
index 0000000..8cc5d58
--- /dev/null
+++ b/general/datasets/Epflmouseliverrma0413/processing.rtf
@@ -0,0 +1 @@
+In general, the array data that we put in GeneNetwork has be logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Epflmouseliverrma0413/summary.rtf b/general/datasets/Epflmouseliverrma0413/summary.rtf
new file mode 100644
index 0000000..77c5606
--- /dev/null
+++ b/general/datasets/Epflmouseliverrma0413/summary.rtf
@@ -0,0 +1 @@
+The manner by which genotype and environment affect complex phenotypes is one of the fundamental questions in biology. In this study we quantified the transcriptome, a subset of the metabolome, and using targeted proteomics, a subset of the liver proteome from 40 strains of the BXD mouse genetic reference population on two diverse diets. We discovered dozens of transcript, protein and metabolite QTLs, several of which linked to metabolic phenotypes. Most prominently, Dhtkd1 was identified as a primary regulator of 2-aminoadipate, explaining variance in fasted glucose and diabetes status in both mice and humans. We further used the integrated molecular profiles to characterize complex pathways, as illustrated with the mitochondrial unfolded protein response (UPRmt). UPRmt shows strikingly variant responses at the transcript and protein level that are remarkably conserved between C.elegans, mice, and humans. Overall, these examples demonstrate the value of an integrated multilayered omics approach to characterize complex metabolic phenotypes.
diff --git a/general/datasets/Epflmouseliverrma0413/tissue.rtf b/general/datasets/Epflmouseliverrma0413/tissue.rtf
new file mode 100644
index 0000000..f95e2c4
--- /dev/null
+++ b/general/datasets/Epflmouseliverrma0413/tissue.rtf
@@ -0,0 +1 @@
+Livers were later shattered in liquid nitrogen and ~100 mg fragments were taken at random from the left, right, or caudate lobes. To account for this discrepancy, all ~5 animals per cohort had their RNA prepared, and then were pooled evenly (by µg of RNA) into a single RNA sample for each cohort. These pooled RNA samples of approximately 30 µg RNA were then purified using RNEasy, then sent out for array analysis. All RIN values were > 8.0.
diff --git a/general/datasets/Epflmousemusclecdrma1211/citation.rtf b/general/datasets/Epflmousemusclecdrma1211/citation.rtf
new file mode 100644
index 0000000..19ca502
--- /dev/null
+++ b/general/datasets/Epflmousemusclecdrma1211/citation.rtf
@@ -0,0 +1,3 @@
+Pirinen et al., Cell Metabolism 2014, Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle.
+
+Citation: The chow diet data were first published in the paper "Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle" in June 2014. The complete dataset was published in the paper "An evolutionarily conserved role for the aryl hydrocarbon receptor in the regulation of movement" in September 2014. If you are using exclusively the chow diet data, please cite the former paper, but if you are using both diets, or if you are only using high fat data, please cite just the latter paper. The complete phenotyping data for these individuals was published in 2016 in the paper "Systems proteomics of liver mitochondria function". Note that the animals used in that 2016 paper are exactly the same ones as the September 2014 paper. Note that in addition to quadriceps transcriptome data on these individuals, liver mRNA, liver SRM proteomics (200 proteins), liver SWATH proteomics (2600 proteins), liver metabolomics, plasma metabolomics (under "Phenotypes" in GeneNetwork), brown adipose mRNA (CD only), and heart mRNA are all published and openly available here in GeneNetwork. Liver and plasma lipidomics, gastrointestinal mRNA and white adipose tissue mRNA have also been completed and are expected to be published in the future but remain under active work (January 2018 note).
diff --git a/general/datasets/Epflmousemusclecdrma1211/summary.rtf b/general/datasets/Epflmousemusclecdrma1211/summary.rtf
new file mode 100644
index 0000000..e63dd95
--- /dev/null
+++ b/general/datasets/Epflmousemusclecdrma1211/summary.rtf
@@ -0,0 +1,10 @@
+Highlights
+
+
+ - Inhibition of poly(ADP-ribose) polymerases (PARPs) enhances endurance performance
+ - Inhibition of PARPs improves mitochondrial function in skeletal muscle
+ - Parp-1 correlates with energy expenditure in heterogeneous mouse populations
+ - Genetic and acquired mitochondrial defects can be rescued by PARP inhibition
+
+
+We previously demonstrated that the deletion of the poly(ADP-ribose)polymerase (Parp)-1 gene in mice enhances oxidative metabolism, thereby protecting against diet-induced obesity. However, the therapeutic use of PARP inhibitors to enhance mitochondrial function remains to be explored. Here, we show tight negative correlation between Parp-1 expression and energy expenditure in heterogeneous mouse populations, indicating that variations in PARP-1 activity have an impact on metabolic homeostasis. Notably, these genetic correlations can be translated into pharmacological applications. Long-term treatment with PARP inhibitors enhances fitness in mice by increasing the abundance of mitochondrial respiratory complexes and boosting mitochondrial respiratory capacity. Furthermore, PARP inhibitors reverse mitochondrial defects in primary myotubes of obese humans and attenuate genetic defects of mitochondrial metabolism in human fibroblasts and C. elegans. Overall, our work validates in worm, mouse, and human models that PARP inhibition may be used to treat both genetic and acquired muscle dysfunction linked to defective mitochondrial function.
diff --git a/general/datasets/Epflmousemusclecdrma1211/tissue.rtf b/general/datasets/Epflmousemusclecdrma1211/tissue.rtf
new file mode 100644
index 0000000..c40574c
--- /dev/null
+++ b/general/datasets/Epflmousemusclecdrma1211/tissue.rtf
@@ -0,0 +1,25 @@
+
+
+
+
+ The muscle datasets are all generated from quadriceps muscles. These animals were born, raised, phenotyped, and sacrificed at the EPFL in the group of Johan Auwerx. Animals were all approximately 29 weeks of age and were all male. Chow diet cohorts ("CD") were fed Harlan 2018 (6% kcal/fat, 20% protein, 74% carbohydrate). High fat diet ("HFD") cohorts were fed Harlan 06414 (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. After an overnight fasting and isoflurane anesthesia, animals were sacrificed following a blood draw and perfusion. Quadriceps were cut horizontally from the femur bone and then frozen in liquid nitrogen for an extended period. Cohorts were sacrificed in a staggered fashion, with approximately 1 cohort per week over a period of 2-3 years. mRNA was prepared for the quadriceps in two distinct batches approximately one year apart (Batch 1: late spring 2011; Batch 2: late spring 2012). Microarrays were run on the samples in two distinct batches shortly after being prepared and received.
+
+
+
+ Batch 1 is the following cohorts: C57HFD 100HFD 62HFD 83CD C57CD 70CD 75CD 96CD 44HFD 45CD 61HFD 73CD DBACD 45HFD 63CD 87CD 89CD 90HFD 62CD 75HFD DBAHFD 44CD 66CD 87HFD 66HFD 55HFD 55CD 70HFD 51CD 83HFD 80CD 51HFD 73HFD 96HFD 61CD 90CD 80HFD 63HFD
+
+
+
+ Batch 2 is the following cohorts: 49HFD 43CD 50CD 89HFD 84CD 100CD 81HFD 98HFD 103CD 68CD 79CD 99CD 71CD 48HFD 64HFD 84HFD 101CD 103HFD 60CD 79HFD 68HFD 48CD 71HFD 65CD 85HFD 99HFD 81CD 49CD 56HFD 97CD 97HFD 92CD 69CD 64CD 69HFD 56CD 65HFD 43HFD 85CD 95CD 98CD
+
+
+
+ For all cohorts in these datasets, roughly 2-5 animals (typically around 4) had mRNA extracted separately, and then mRNA were pooled equally for each individual in a cohort. After the mRNA were pooled for the individuals within a cohort—a cohort meaning the same diet, sex, strain, and littermate—the samples were purified using RNEasy.
+
+
+
+ Once both cohorts were completed, the two batches were re-normalized together using RMAExpress and the two batches were logged and z-normalized. The mean was set to 8 units and standard deviation was set to 2 units for all samples. This removes negative values from the samples, and reduces the batch effect between the two groups.
+ |
+
+
+
diff --git a/general/datasets/Epflmousemusclecdrmaex1112/citation.rtf b/general/datasets/Epflmousemusclecdrmaex1112/citation.rtf
new file mode 100644
index 0000000..19ca502
--- /dev/null
+++ b/general/datasets/Epflmousemusclecdrmaex1112/citation.rtf
@@ -0,0 +1,3 @@
+Pirinen et al., Cell Metabolism 2014, Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle.
+
+Citation: The chow diet data were first published in the paper "Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle" in June 2014. The complete dataset was published in the paper "An evolutionarily conserved role for the aryl hydrocarbon receptor in the regulation of movement" in September 2014. If you are using exclusively the chow diet data, please cite the former paper, but if you are using both diets, or if you are only using high fat data, please cite just the latter paper. The complete phenotyping data for these individuals was published in 2016 in the paper "Systems proteomics of liver mitochondria function". Note that the animals used in that 2016 paper are exactly the same ones as the September 2014 paper. Note that in addition to quadriceps transcriptome data on these individuals, liver mRNA, liver SRM proteomics (200 proteins), liver SWATH proteomics (2600 proteins), liver metabolomics, plasma metabolomics (under "Phenotypes" in GeneNetwork), brown adipose mRNA (CD only), and heart mRNA are all published and openly available here in GeneNetwork. Liver and plasma lipidomics, gastrointestinal mRNA and white adipose tissue mRNA have also been completed and are expected to be published in the future but remain under active work (January 2018 note).
diff --git a/general/datasets/Epflmousemusclecdrmaex1112/summary.rtf b/general/datasets/Epflmousemusclecdrmaex1112/summary.rtf
new file mode 100644
index 0000000..e63dd95
--- /dev/null
+++ b/general/datasets/Epflmousemusclecdrmaex1112/summary.rtf
@@ -0,0 +1,10 @@
+Highlights
+
+
+ - Inhibition of poly(ADP-ribose) polymerases (PARPs) enhances endurance performance
+ - Inhibition of PARPs improves mitochondrial function in skeletal muscle
+ - Parp-1 correlates with energy expenditure in heterogeneous mouse populations
+ - Genetic and acquired mitochondrial defects can be rescued by PARP inhibition
+
+
+We previously demonstrated that the deletion of the poly(ADP-ribose)polymerase (Parp)-1 gene in mice enhances oxidative metabolism, thereby protecting against diet-induced obesity. However, the therapeutic use of PARP inhibitors to enhance mitochondrial function remains to be explored. Here, we show tight negative correlation between Parp-1 expression and energy expenditure in heterogeneous mouse populations, indicating that variations in PARP-1 activity have an impact on metabolic homeostasis. Notably, these genetic correlations can be translated into pharmacological applications. Long-term treatment with PARP inhibitors enhances fitness in mice by increasing the abundance of mitochondrial respiratory complexes and boosting mitochondrial respiratory capacity. Furthermore, PARP inhibitors reverse mitochondrial defects in primary myotubes of obese humans and attenuate genetic defects of mitochondrial metabolism in human fibroblasts and C. elegans. Overall, our work validates in worm, mouse, and human models that PARP inhibition may be used to treat both genetic and acquired muscle dysfunction linked to defective mitochondrial function.
diff --git a/general/datasets/Epflmousemusclecdrmaex1112/tissue.rtf b/general/datasets/Epflmousemusclecdrmaex1112/tissue.rtf
new file mode 100644
index 0000000..c40574c
--- /dev/null
+++ b/general/datasets/Epflmousemusclecdrmaex1112/tissue.rtf
@@ -0,0 +1,25 @@
+
+
+
+
+ The muscle datasets are all generated from quadriceps muscles. These animals were born, raised, phenotyped, and sacrificed at the EPFL in the group of Johan Auwerx. Animals were all approximately 29 weeks of age and were all male. Chow diet cohorts ("CD") were fed Harlan 2018 (6% kcal/fat, 20% protein, 74% carbohydrate). High fat diet ("HFD") cohorts were fed Harlan 06414 (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. After an overnight fasting and isoflurane anesthesia, animals were sacrificed following a blood draw and perfusion. Quadriceps were cut horizontally from the femur bone and then frozen in liquid nitrogen for an extended period. Cohorts were sacrificed in a staggered fashion, with approximately 1 cohort per week over a period of 2-3 years. mRNA was prepared for the quadriceps in two distinct batches approximately one year apart (Batch 1: late spring 2011; Batch 2: late spring 2012). Microarrays were run on the samples in two distinct batches shortly after being prepared and received.
+
+
+
+ Batch 1 is the following cohorts: C57HFD 100HFD 62HFD 83CD C57CD 70CD 75CD 96CD 44HFD 45CD 61HFD 73CD DBACD 45HFD 63CD 87CD 89CD 90HFD 62CD 75HFD DBAHFD 44CD 66CD 87HFD 66HFD 55HFD 55CD 70HFD 51CD 83HFD 80CD 51HFD 73HFD 96HFD 61CD 90CD 80HFD 63HFD
+
+
+
+ Batch 2 is the following cohorts: 49HFD 43CD 50CD 89HFD 84CD 100CD 81HFD 98HFD 103CD 68CD 79CD 99CD 71CD 48HFD 64HFD 84HFD 101CD 103HFD 60CD 79HFD 68HFD 48CD 71HFD 65CD 85HFD 99HFD 81CD 49CD 56HFD 97CD 97HFD 92CD 69CD 64CD 69HFD 56CD 65HFD 43HFD 85CD 95CD 98CD
+
+
+
+ For all cohorts in these datasets, roughly 2-5 animals (typically around 4) had mRNA extracted separately, and then mRNA were pooled equally for each individual in a cohort. After the mRNA were pooled for the individuals within a cohort—a cohort meaning the same diet, sex, strain, and littermate—the samples were purified using RNEasy.
+
+
+
+ Once both cohorts were completed, the two batches were re-normalized together using RMAExpress and the two batches were logged and z-normalized. The mean was set to 8 units and standard deviation was set to 2 units for all samples. This removes negative values from the samples, and reduces the batch effect between the two groups.
+ |
+
+
+
diff --git a/general/datasets/Epflmousemusclehfdrma1211/citation.rtf b/general/datasets/Epflmousemusclehfdrma1211/citation.rtf
new file mode 100644
index 0000000..19ca502
--- /dev/null
+++ b/general/datasets/Epflmousemusclehfdrma1211/citation.rtf
@@ -0,0 +1,3 @@
+Pirinen et al., Cell Metabolism 2014, Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle.
+
+Citation: The chow diet data were first published in the paper "Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle" in June 2014. The complete dataset was published in the paper "An evolutionarily conserved role for the aryl hydrocarbon receptor in the regulation of movement" in September 2014. If you are using exclusively the chow diet data, please cite the former paper, but if you are using both diets, or if you are only using high fat data, please cite just the latter paper. The complete phenotyping data for these individuals was published in 2016 in the paper "Systems proteomics of liver mitochondria function". Note that the animals used in that 2016 paper are exactly the same ones as the September 2014 paper. Note that in addition to quadriceps transcriptome data on these individuals, liver mRNA, liver SRM proteomics (200 proteins), liver SWATH proteomics (2600 proteins), liver metabolomics, plasma metabolomics (under "Phenotypes" in GeneNetwork), brown adipose mRNA (CD only), and heart mRNA are all published and openly available here in GeneNetwork. Liver and plasma lipidomics, gastrointestinal mRNA and white adipose tissue mRNA have also been completed and are expected to be published in the future but remain under active work (January 2018 note).
diff --git a/general/datasets/Epflmousemusclehfdrma1211/summary.rtf b/general/datasets/Epflmousemusclehfdrma1211/summary.rtf
new file mode 100644
index 0000000..e63dd95
--- /dev/null
+++ b/general/datasets/Epflmousemusclehfdrma1211/summary.rtf
@@ -0,0 +1,10 @@
+Highlights
+
+
+ - Inhibition of poly(ADP-ribose) polymerases (PARPs) enhances endurance performance
+ - Inhibition of PARPs improves mitochondrial function in skeletal muscle
+ - Parp-1 correlates with energy expenditure in heterogeneous mouse populations
+ - Genetic and acquired mitochondrial defects can be rescued by PARP inhibition
+
+
+We previously demonstrated that the deletion of the poly(ADP-ribose)polymerase (Parp)-1 gene in mice enhances oxidative metabolism, thereby protecting against diet-induced obesity. However, the therapeutic use of PARP inhibitors to enhance mitochondrial function remains to be explored. Here, we show tight negative correlation between Parp-1 expression and energy expenditure in heterogeneous mouse populations, indicating that variations in PARP-1 activity have an impact on metabolic homeostasis. Notably, these genetic correlations can be translated into pharmacological applications. Long-term treatment with PARP inhibitors enhances fitness in mice by increasing the abundance of mitochondrial respiratory complexes and boosting mitochondrial respiratory capacity. Furthermore, PARP inhibitors reverse mitochondrial defects in primary myotubes of obese humans and attenuate genetic defects of mitochondrial metabolism in human fibroblasts and C. elegans. Overall, our work validates in worm, mouse, and human models that PARP inhibition may be used to treat both genetic and acquired muscle dysfunction linked to defective mitochondrial function.
diff --git a/general/datasets/Epflmousemusclehfdrma1211/tissue.rtf b/general/datasets/Epflmousemusclehfdrma1211/tissue.rtf
new file mode 100644
index 0000000..c40574c
--- /dev/null
+++ b/general/datasets/Epflmousemusclehfdrma1211/tissue.rtf
@@ -0,0 +1,25 @@
+
+
+
+
+ The muscle datasets are all generated from quadriceps muscles. These animals were born, raised, phenotyped, and sacrificed at the EPFL in the group of Johan Auwerx. Animals were all approximately 29 weeks of age and were all male. Chow diet cohorts ("CD") were fed Harlan 2018 (6% kcal/fat, 20% protein, 74% carbohydrate). High fat diet ("HFD") cohorts were fed Harlan 06414 (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. After an overnight fasting and isoflurane anesthesia, animals were sacrificed following a blood draw and perfusion. Quadriceps were cut horizontally from the femur bone and then frozen in liquid nitrogen for an extended period. Cohorts were sacrificed in a staggered fashion, with approximately 1 cohort per week over a period of 2-3 years. mRNA was prepared for the quadriceps in two distinct batches approximately one year apart (Batch 1: late spring 2011; Batch 2: late spring 2012). Microarrays were run on the samples in two distinct batches shortly after being prepared and received.
+
+
+
+ Batch 1 is the following cohorts: C57HFD 100HFD 62HFD 83CD C57CD 70CD 75CD 96CD 44HFD 45CD 61HFD 73CD DBACD 45HFD 63CD 87CD 89CD 90HFD 62CD 75HFD DBAHFD 44CD 66CD 87HFD 66HFD 55HFD 55CD 70HFD 51CD 83HFD 80CD 51HFD 73HFD 96HFD 61CD 90CD 80HFD 63HFD
+
+
+
+ Batch 2 is the following cohorts: 49HFD 43CD 50CD 89HFD 84CD 100CD 81HFD 98HFD 103CD 68CD 79CD 99CD 71CD 48HFD 64HFD 84HFD 101CD 103HFD 60CD 79HFD 68HFD 48CD 71HFD 65CD 85HFD 99HFD 81CD 49CD 56HFD 97CD 97HFD 92CD 69CD 64CD 69HFD 56CD 65HFD 43HFD 85CD 95CD 98CD
+
+
+
+ For all cohorts in these datasets, roughly 2-5 animals (typically around 4) had mRNA extracted separately, and then mRNA were pooled equally for each individual in a cohort. After the mRNA were pooled for the individuals within a cohort—a cohort meaning the same diet, sex, strain, and littermate—the samples were purified using RNEasy.
+
+
+
+ Once both cohorts were completed, the two batches were re-normalized together using RMAExpress and the two batches were logged and z-normalized. The mean was set to 8 units and standard deviation was set to 2 units for all samples. This removes negative values from the samples, and reduces the batch effect between the two groups.
+ |
+
+
+
diff --git a/general/datasets/Epflmousemusclehfdrmaex1112/citation.rtf b/general/datasets/Epflmousemusclehfdrmaex1112/citation.rtf
new file mode 100644
index 0000000..19ca502
--- /dev/null
+++ b/general/datasets/Epflmousemusclehfdrmaex1112/citation.rtf
@@ -0,0 +1,3 @@
+Pirinen et al., Cell Metabolism 2014, Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle.
+
+Citation: The chow diet data were first published in the paper "Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle" in June 2014. The complete dataset was published in the paper "An evolutionarily conserved role for the aryl hydrocarbon receptor in the regulation of movement" in September 2014. If you are using exclusively the chow diet data, please cite the former paper, but if you are using both diets, or if you are only using high fat data, please cite just the latter paper. The complete phenotyping data for these individuals was published in 2016 in the paper "Systems proteomics of liver mitochondria function". Note that the animals used in that 2016 paper are exactly the same ones as the September 2014 paper. Note that in addition to quadriceps transcriptome data on these individuals, liver mRNA, liver SRM proteomics (200 proteins), liver SWATH proteomics (2600 proteins), liver metabolomics, plasma metabolomics (under "Phenotypes" in GeneNetwork), brown adipose mRNA (CD only), and heart mRNA are all published and openly available here in GeneNetwork. Liver and plasma lipidomics, gastrointestinal mRNA and white adipose tissue mRNA have also been completed and are expected to be published in the future but remain under active work (January 2018 note).
diff --git a/general/datasets/Epflmousemusclehfdrmaex1112/summary.rtf b/general/datasets/Epflmousemusclehfdrmaex1112/summary.rtf
new file mode 100644
index 0000000..e63dd95
--- /dev/null
+++ b/general/datasets/Epflmousemusclehfdrmaex1112/summary.rtf
@@ -0,0 +1,10 @@
+Highlights
+
+
+ - Inhibition of poly(ADP-ribose) polymerases (PARPs) enhances endurance performance
+ - Inhibition of PARPs improves mitochondrial function in skeletal muscle
+ - Parp-1 correlates with energy expenditure in heterogeneous mouse populations
+ - Genetic and acquired mitochondrial defects can be rescued by PARP inhibition
+
+
+We previously demonstrated that the deletion of the poly(ADP-ribose)polymerase (Parp)-1 gene in mice enhances oxidative metabolism, thereby protecting against diet-induced obesity. However, the therapeutic use of PARP inhibitors to enhance mitochondrial function remains to be explored. Here, we show tight negative correlation between Parp-1 expression and energy expenditure in heterogeneous mouse populations, indicating that variations in PARP-1 activity have an impact on metabolic homeostasis. Notably, these genetic correlations can be translated into pharmacological applications. Long-term treatment with PARP inhibitors enhances fitness in mice by increasing the abundance of mitochondrial respiratory complexes and boosting mitochondrial respiratory capacity. Furthermore, PARP inhibitors reverse mitochondrial defects in primary myotubes of obese humans and attenuate genetic defects of mitochondrial metabolism in human fibroblasts and C. elegans. Overall, our work validates in worm, mouse, and human models that PARP inhibition may be used to treat both genetic and acquired muscle dysfunction linked to defective mitochondrial function.
diff --git a/general/datasets/Epflmousemusclehfdrmaex1112/tissue.rtf b/general/datasets/Epflmousemusclehfdrmaex1112/tissue.rtf
new file mode 100644
index 0000000..c40574c
--- /dev/null
+++ b/general/datasets/Epflmousemusclehfdrmaex1112/tissue.rtf
@@ -0,0 +1,25 @@
+
+
+
+
+ The muscle datasets are all generated from quadriceps muscles. These animals were born, raised, phenotyped, and sacrificed at the EPFL in the group of Johan Auwerx. Animals were all approximately 29 weeks of age and were all male. Chow diet cohorts ("CD") were fed Harlan 2018 (6% kcal/fat, 20% protein, 74% carbohydrate). High fat diet ("HFD") cohorts were fed Harlan 06414 (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. After an overnight fasting and isoflurane anesthesia, animals were sacrificed following a blood draw and perfusion. Quadriceps were cut horizontally from the femur bone and then frozen in liquid nitrogen for an extended period. Cohorts were sacrificed in a staggered fashion, with approximately 1 cohort per week over a period of 2-3 years. mRNA was prepared for the quadriceps in two distinct batches approximately one year apart (Batch 1: late spring 2011; Batch 2: late spring 2012). Microarrays were run on the samples in two distinct batches shortly after being prepared and received.
+
+
+
+ Batch 1 is the following cohorts: C57HFD 100HFD 62HFD 83CD C57CD 70CD 75CD 96CD 44HFD 45CD 61HFD 73CD DBACD 45HFD 63CD 87CD 89CD 90HFD 62CD 75HFD DBAHFD 44CD 66CD 87HFD 66HFD 55HFD 55CD 70HFD 51CD 83HFD 80CD 51HFD 73HFD 96HFD 61CD 90CD 80HFD 63HFD
+
+
+
+ Batch 2 is the following cohorts: 49HFD 43CD 50CD 89HFD 84CD 100CD 81HFD 98HFD 103CD 68CD 79CD 99CD 71CD 48HFD 64HFD 84HFD 101CD 103HFD 60CD 79HFD 68HFD 48CD 71HFD 65CD 85HFD 99HFD 81CD 49CD 56HFD 97CD 97HFD 92CD 69CD 64CD 69HFD 56CD 65HFD 43HFD 85CD 95CD 98CD
+
+
+
+ For all cohorts in these datasets, roughly 2-5 animals (typically around 4) had mRNA extracted separately, and then mRNA were pooled equally for each individual in a cohort. After the mRNA were pooled for the individuals within a cohort—a cohort meaning the same diet, sex, strain, and littermate—the samples were purified using RNEasy.
+
+
+
+ Once both cohorts were completed, the two batches were re-normalized together using RMAExpress and the two batches were logged and z-normalized. The mean was set to 8 units and standard deviation was set to 2 units for all samples. This removes negative values from the samples, and reduces the batch effect between the two groups.
+ |
+
+
+
diff --git a/general/datasets/Epflmousemusclerma1211/citation.rtf b/general/datasets/Epflmousemusclerma1211/citation.rtf
new file mode 100644
index 0000000..19ca502
--- /dev/null
+++ b/general/datasets/Epflmousemusclerma1211/citation.rtf
@@ -0,0 +1,3 @@
+Pirinen et al., Cell Metabolism 2014, Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle.
+
+Citation: The chow diet data were first published in the paper "Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle" in June 2014. The complete dataset was published in the paper "An evolutionarily conserved role for the aryl hydrocarbon receptor in the regulation of movement" in September 2014. If you are using exclusively the chow diet data, please cite the former paper, but if you are using both diets, or if you are only using high fat data, please cite just the latter paper. The complete phenotyping data for these individuals was published in 2016 in the paper "Systems proteomics of liver mitochondria function". Note that the animals used in that 2016 paper are exactly the same ones as the September 2014 paper. Note that in addition to quadriceps transcriptome data on these individuals, liver mRNA, liver SRM proteomics (200 proteins), liver SWATH proteomics (2600 proteins), liver metabolomics, plasma metabolomics (under "Phenotypes" in GeneNetwork), brown adipose mRNA (CD only), and heart mRNA are all published and openly available here in GeneNetwork. Liver and plasma lipidomics, gastrointestinal mRNA and white adipose tissue mRNA have also been completed and are expected to be published in the future but remain under active work (January 2018 note).
diff --git a/general/datasets/Epflmousemusclerma1211/summary.rtf b/general/datasets/Epflmousemusclerma1211/summary.rtf
new file mode 100644
index 0000000..e63dd95
--- /dev/null
+++ b/general/datasets/Epflmousemusclerma1211/summary.rtf
@@ -0,0 +1,10 @@
+Highlights
+
+
+ - Inhibition of poly(ADP-ribose) polymerases (PARPs) enhances endurance performance
+ - Inhibition of PARPs improves mitochondrial function in skeletal muscle
+ - Parp-1 correlates with energy expenditure in heterogeneous mouse populations
+ - Genetic and acquired mitochondrial defects can be rescued by PARP inhibition
+
+
+We previously demonstrated that the deletion of the poly(ADP-ribose)polymerase (Parp)-1 gene in mice enhances oxidative metabolism, thereby protecting against diet-induced obesity. However, the therapeutic use of PARP inhibitors to enhance mitochondrial function remains to be explored. Here, we show tight negative correlation between Parp-1 expression and energy expenditure in heterogeneous mouse populations, indicating that variations in PARP-1 activity have an impact on metabolic homeostasis. Notably, these genetic correlations can be translated into pharmacological applications. Long-term treatment with PARP inhibitors enhances fitness in mice by increasing the abundance of mitochondrial respiratory complexes and boosting mitochondrial respiratory capacity. Furthermore, PARP inhibitors reverse mitochondrial defects in primary myotubes of obese humans and attenuate genetic defects of mitochondrial metabolism in human fibroblasts and C. elegans. Overall, our work validates in worm, mouse, and human models that PARP inhibition may be used to treat both genetic and acquired muscle dysfunction linked to defective mitochondrial function.
diff --git a/general/datasets/Epflmousemusclerma1211/tissue.rtf b/general/datasets/Epflmousemusclerma1211/tissue.rtf
new file mode 100644
index 0000000..c40574c
--- /dev/null
+++ b/general/datasets/Epflmousemusclerma1211/tissue.rtf
@@ -0,0 +1,25 @@
+
+
+
+
+ The muscle datasets are all generated from quadriceps muscles. These animals were born, raised, phenotyped, and sacrificed at the EPFL in the group of Johan Auwerx. Animals were all approximately 29 weeks of age and were all male. Chow diet cohorts ("CD") were fed Harlan 2018 (6% kcal/fat, 20% protein, 74% carbohydrate). High fat diet ("HFD") cohorts were fed Harlan 06414 (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. After an overnight fasting and isoflurane anesthesia, animals were sacrificed following a blood draw and perfusion. Quadriceps were cut horizontally from the femur bone and then frozen in liquid nitrogen for an extended period. Cohorts were sacrificed in a staggered fashion, with approximately 1 cohort per week over a period of 2-3 years. mRNA was prepared for the quadriceps in two distinct batches approximately one year apart (Batch 1: late spring 2011; Batch 2: late spring 2012). Microarrays were run on the samples in two distinct batches shortly after being prepared and received.
+
+
+
+ Batch 1 is the following cohorts: C57HFD 100HFD 62HFD 83CD C57CD 70CD 75CD 96CD 44HFD 45CD 61HFD 73CD DBACD 45HFD 63CD 87CD 89CD 90HFD 62CD 75HFD DBAHFD 44CD 66CD 87HFD 66HFD 55HFD 55CD 70HFD 51CD 83HFD 80CD 51HFD 73HFD 96HFD 61CD 90CD 80HFD 63HFD
+
+
+
+ Batch 2 is the following cohorts: 49HFD 43CD 50CD 89HFD 84CD 100CD 81HFD 98HFD 103CD 68CD 79CD 99CD 71CD 48HFD 64HFD 84HFD 101CD 103HFD 60CD 79HFD 68HFD 48CD 71HFD 65CD 85HFD 99HFD 81CD 49CD 56HFD 97CD 97HFD 92CD 69CD 64CD 69HFD 56CD 65HFD 43HFD 85CD 95CD 98CD
+
+
+
+ For all cohorts in these datasets, roughly 2-5 animals (typically around 4) had mRNA extracted separately, and then mRNA were pooled equally for each individual in a cohort. After the mRNA were pooled for the individuals within a cohort—a cohort meaning the same diet, sex, strain, and littermate—the samples were purified using RNEasy.
+
+
+
+ Once both cohorts were completed, the two batches were re-normalized together using RMAExpress and the two batches were logged and z-normalized. The mean was set to 8 units and standard deviation was set to 2 units for all samples. This removes negative values from the samples, and reduces the batch effect between the two groups.
+ |
+
+
+
diff --git a/general/datasets/Epflmousemusclerma_ex1112/citation.rtf b/general/datasets/Epflmousemusclerma_ex1112/citation.rtf
new file mode 100644
index 0000000..19ca502
--- /dev/null
+++ b/general/datasets/Epflmousemusclerma_ex1112/citation.rtf
@@ -0,0 +1,3 @@
+Pirinen et al., Cell Metabolism 2014, Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle.
+
+Citation: The chow diet data were first published in the paper "Pharmacological Inhibition of Poly(ADP-Ribose) Polymerases Improves Fitness and Mitochondrial Function in Skeletal Muscle" in June 2014. The complete dataset was published in the paper "An evolutionarily conserved role for the aryl hydrocarbon receptor in the regulation of movement" in September 2014. If you are using exclusively the chow diet data, please cite the former paper, but if you are using both diets, or if you are only using high fat data, please cite just the latter paper. The complete phenotyping data for these individuals was published in 2016 in the paper "Systems proteomics of liver mitochondria function". Note that the animals used in that 2016 paper are exactly the same ones as the September 2014 paper. Note that in addition to quadriceps transcriptome data on these individuals, liver mRNA, liver SRM proteomics (200 proteins), liver SWATH proteomics (2600 proteins), liver metabolomics, plasma metabolomics (under "Phenotypes" in GeneNetwork), brown adipose mRNA (CD only), and heart mRNA are all published and openly available here in GeneNetwork. Liver and plasma lipidomics, gastrointestinal mRNA and white adipose tissue mRNA have also been completed and are expected to be published in the future but remain under active work (January 2018 note).
diff --git a/general/datasets/Epflmousemusclerma_ex1112/summary.rtf b/general/datasets/Epflmousemusclerma_ex1112/summary.rtf
new file mode 100644
index 0000000..e63dd95
--- /dev/null
+++ b/general/datasets/Epflmousemusclerma_ex1112/summary.rtf
@@ -0,0 +1,10 @@
+Highlights
+
+
+ - Inhibition of poly(ADP-ribose) polymerases (PARPs) enhances endurance performance
+ - Inhibition of PARPs improves mitochondrial function in skeletal muscle
+ - Parp-1 correlates with energy expenditure in heterogeneous mouse populations
+ - Genetic and acquired mitochondrial defects can be rescued by PARP inhibition
+
+
+We previously demonstrated that the deletion of the poly(ADP-ribose)polymerase (Parp)-1 gene in mice enhances oxidative metabolism, thereby protecting against diet-induced obesity. However, the therapeutic use of PARP inhibitors to enhance mitochondrial function remains to be explored. Here, we show tight negative correlation between Parp-1 expression and energy expenditure in heterogeneous mouse populations, indicating that variations in PARP-1 activity have an impact on metabolic homeostasis. Notably, these genetic correlations can be translated into pharmacological applications. Long-term treatment with PARP inhibitors enhances fitness in mice by increasing the abundance of mitochondrial respiratory complexes and boosting mitochondrial respiratory capacity. Furthermore, PARP inhibitors reverse mitochondrial defects in primary myotubes of obese humans and attenuate genetic defects of mitochondrial metabolism in human fibroblasts and C. elegans. Overall, our work validates in worm, mouse, and human models that PARP inhibition may be used to treat both genetic and acquired muscle dysfunction linked to defective mitochondrial function.
diff --git a/general/datasets/Epflmousemusclerma_ex1112/tissue.rtf b/general/datasets/Epflmousemusclerma_ex1112/tissue.rtf
new file mode 100644
index 0000000..c40574c
--- /dev/null
+++ b/general/datasets/Epflmousemusclerma_ex1112/tissue.rtf
@@ -0,0 +1,25 @@
+
+
+
+
+ The muscle datasets are all generated from quadriceps muscles. These animals were born, raised, phenotyped, and sacrificed at the EPFL in the group of Johan Auwerx. Animals were all approximately 29 weeks of age and were all male. Chow diet cohorts ("CD") were fed Harlan 2018 (6% kcal/fat, 20% protein, 74% carbohydrate). High fat diet ("HFD") cohorts were fed Harlan 06414 (60% kcal/fat, 20% protein, 20% carbohydrate). Animals adjusted to the diet for 8 weeks, and then an intensive phenotyping metabolic phenotyping protocol was followed from 16 to 24 weeks of age (respiration, cold tolerance, oral glucose response, VO2max exercise, voluntary exercise, basal activity). Animals were communally housed until the last 5 weeks of the experiment, when the animals could rest. After an overnight fasting and isoflurane anesthesia, animals were sacrificed following a blood draw and perfusion. Quadriceps were cut horizontally from the femur bone and then frozen in liquid nitrogen for an extended period. Cohorts were sacrificed in a staggered fashion, with approximately 1 cohort per week over a period of 2-3 years. mRNA was prepared for the quadriceps in two distinct batches approximately one year apart (Batch 1: late spring 2011; Batch 2: late spring 2012). Microarrays were run on the samples in two distinct batches shortly after being prepared and received.
+
+
+
+ Batch 1 is the following cohorts: C57HFD 100HFD 62HFD 83CD C57CD 70CD 75CD 96CD 44HFD 45CD 61HFD 73CD DBACD 45HFD 63CD 87CD 89CD 90HFD 62CD 75HFD DBAHFD 44CD 66CD 87HFD 66HFD 55HFD 55CD 70HFD 51CD 83HFD 80CD 51HFD 73HFD 96HFD 61CD 90CD 80HFD 63HFD
+
+
+
+ Batch 2 is the following cohorts: 49HFD 43CD 50CD 89HFD 84CD 100CD 81HFD 98HFD 103CD 68CD 79CD 99CD 71CD 48HFD 64HFD 84HFD 101CD 103HFD 60CD 79HFD 68HFD 48CD 71HFD 65CD 85HFD 99HFD 81CD 49CD 56HFD 97CD 97HFD 92CD 69CD 64CD 69HFD 56CD 65HFD 43HFD 85CD 95CD 98CD
+
+
+
+ For all cohorts in these datasets, roughly 2-5 animals (typically around 4) had mRNA extracted separately, and then mRNA were pooled equally for each individual in a cohort. After the mRNA were pooled for the individuals within a cohort—a cohort meaning the same diet, sex, strain, and littermate—the samples were purified using RNEasy.
+
+
+
+ Once both cohorts were completed, the two batches were re-normalized together using RMAExpress and the two batches were logged and z-normalized. The mean was set to 8 units and standard deviation was set to 2 units for all samples. This removes negative values from the samples, and reduces the batch effect between the two groups.
+ |
+
+
+
diff --git a/general/datasets/Eye_axbxa_1008_rankinv/acknowledgment.rtf b/general/datasets/Eye_axbxa_1008_rankinv/acknowledgment.rtf
new file mode 100644
index 0000000..5cbb536
--- /dev/null
+++ b/general/datasets/Eye_axbxa_1008_rankinv/acknowledgment.rtf
@@ -0,0 +1,11 @@
+
+All array data were generated with funds from Dr. Benjamin Reese to RW Williams and Lu Lu as part of NIH NEI grant EY011087 (Dispersion Patterns for Retinal Neuroblasts). Arrays were scanned in the UTHSC NEI Vision Core with support from P30 EY013080. Some informatics support, including annotation of the array, was provided by NIDA and NIAAA grants to RWW and LL (NIH U01AA13499, U24AA13513 Lu Lu, PI).
+
+
+ About this text file:
+
+
+Data uploaded by Arthur Centeno, Oct 1, 2008. This text file originally generated by RWW on Oct 10, 2008. Updated by RWW, May 11, 2009, May 26, 2009.
+
+
+
diff --git a/general/datasets/Eye_axbxa_1008_rankinv/cases.rtf b/general/datasets/Eye_axbxa_1008_rankinv/cases.rtf
new file mode 100644
index 0000000..864f3b6
--- /dev/null
+++ b/general/datasets/Eye_axbxa_1008_rankinv/cases.rtf
@@ -0,0 +1 @@
+The AXB/BXA genetic reference panel of recombinant inbred strains consists of just about 26 fully independent strains. All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
diff --git a/general/datasets/Eye_axbxa_1008_rankinv/citation.rtf b/general/datasets/Eye_axbxa_1008_rankinv/citation.rtf
new file mode 100644
index 0000000..3977075
--- /dev/null
+++ b/general/datasets/Eye_axbxa_1008_rankinv/citation.rtf
@@ -0,0 +1,9 @@
+A QTL on chromosome 10 modulates cone photoreceptor number in the mouse retina.
+
+Whitney IE, Raven MA, Lu L, Williams RW, Reese BE.
+Invest Ophthalmol Vis Sci. 2011 May 16;52(6):3228-36.
+
+Pituitary tumor-transforming gene 1 regulates the patterning of retinal mosaics.
+
+Keeley PW, Zhou C, Lu L, Williams RW, Melmed S, Reese BE.
+Proc Natl Acad Sci U S A. 2014 Jun 24;111(25):9295-300.
diff --git a/general/datasets/Eye_axbxa_1008_rankinv/platform.rtf b/general/datasets/Eye_axbxa_1008_rankinv/platform.rtf
new file mode 100644
index 0000000..23268bc
--- /dev/null
+++ b/general/datasets/Eye_axbxa_1008_rankinv/platform.rtf
@@ -0,0 +1,7 @@
+
+Illumina Sentrix MouseWG-6 v2 BeadChip: This array consists of 45,281 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+ANNOTATION: In the summer of 2008, Xusheng Wang and Robert W. Williams reannotated all three Illumina Mouse 6 BeadChips, including the array used to process the AXB/BXA eye samples. This new annotation is now incorporated into GeneNetwork. The annotation file can be accessed at http://www.genenetwork.org/share/annotations/, by selecting "Illumina Mouse WG-6 v2.0 (GPL6887)".
+
+Position data for the 50-mer Illumina probe sequences were aligned to the mm8 mouse genome build by Xusheng Wang as part of his master annotation of all Illumina mouse arrays. Manual annotation of this array was usually done by RW Williams.
+
diff --git a/general/datasets/Eye_axbxa_1008_rankinv/processing.rtf b/general/datasets/Eye_axbxa_1008_rankinv/processing.rtf
new file mode 100644
index 0000000..7d79970
--- /dev/null
+++ b/general/datasets/Eye_axbxa_1008_rankinv/processing.rtf
@@ -0,0 +1,5 @@
+
+Sample Processing: Samples were processed by Lu Lu and colleagues in the Illumina Core at UTHSC between August 2008 and September 2008. All processing steps were performed by Dr. David Li. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (approximately 10% failed and new RNA samples had to be acquired and processed) were immediately used on BeadChips. The slides were hybridized and washed following standard Illumina protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from 25 of the 28 strains. Three strains are represented by samples from a single sex.
+
diff --git a/general/datasets/Eye_axbxa_1008_rankinv/specifics.rtf b/general/datasets/Eye_axbxa_1008_rankinv/specifics.rtf
new file mode 100644
index 0000000..0cf2818
--- /dev/null
+++ b/general/datasets/Eye_axbxa_1008_rankinv/specifics.rtf
@@ -0,0 +1 @@
+AXB/BXA
\ No newline at end of file
diff --git a/general/datasets/Eye_axbxa_1008_rankinv/summary.rtf b/general/datasets/Eye_axbxa_1008_rankinv/summary.rtf
new file mode 100644
index 0000000..0bf1369
--- /dev/null
+++ b/general/datasets/Eye_axbxa_1008_rankinv/summary.rtf
@@ -0,0 +1,769 @@
+
+FINAL RECOMMENDED AXB/BXA EYE DATA SET. The Eye AXBXA Illumina Illumina V6.2 (Oct08) data set provides estimates of mRNA expression for whole eyes of 28 strains of mice, including 26 AXB/BXA recombinant inbred strains, and two parental strains, A/J and C57BL/6J. All eye samples were obtained from normal adult control animals raised in a standard laboratory environment at the Jackson Laboratory. We used the Illumina Sentrix MouseWG-6 v2 BeadChip (despite the nomenclature, this is actually the third version of the Illumina Mouse-6 platform).
+
+Users of these mouse eye data may also find the following complementary resources extremely useful:
+
+
+ - NEIBank collection of ESTs and SAGE data
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
+
+
+ About the cases used to generate this set of data:
+
+
+
+
+A total of 54 pooled whole eye samples were processed using approximately 10 Illumina Sentrix Mouse WG-6 v2 oligomer BeadChip slides. All 10 slides and a total of 54 samples passed stringent quality control and error checking. This particular data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed. Variance of each array was stabilized to 4 units (SD of 2 units) and recentered to a mean of 8. values range from a low of 6.3 (e.g., ILMN_1225143, no expression) to a high of about 19.7 for ILMN_2772482 (Crygd, extremely highly expressed). Data were entered by Arthur Centeno, Hongqiang Li, Robert W. Williams, and Lu Lu, October 1, 2008.
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10. In this data set, 255 probes have LRS values >46 (LOD >10). The maximum LOD score achieved in this data set is 27.7 for Zfp330 (LRS of 127.9 using ILMN_2825109).
+
+The probe ILMN_2475156 can be used to check sex assignment. With three exceptions, all 28 strains are represented by one male sample and one female sample. The three exceptions are are follows: both AXB13/14 cases are males, BXA25 is represented by a single male sample or a mixed sex sample, and BXA11 is represented by a single female sample.
+
+
+
+Legend: Bar chart of the expression of Xist probe ILMN_2475156 in the AXB/BXA eye data set. This probe is used to check sex. Strains represented by equal numbers of male and female arrays (usually one of each) should have intermediate values and a high error term. Strains represented only by males will have very low values (for example, AXB13/14 is represented by only one male) and strains represented by only females will have very high expression (for example, BXA11 is represented by only one female).
+
+ About the animals and tissue used to generate this set of data:
+
+
+AXB/BXA animals were obtained directly from The Jackson Laboratory. Animals were housed at UTHSC before sacrifice. Mice were killed by cervical dislocation and eyes and brains were removed and placed in RNAlater.
+
+Animals used in this study were between 51 and 90 days of age (see Table 1 below). All animals were sacrifice between 9 AM and 5 PM during the light phase.
+
+
+Experimental Design and Batch Structure: This data set consists arrays processed September 2008 and all arrays in this data set were processed using a single protocol by a single operator. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute in September 2008. Details on sample assignment to slides and batches is provide in the table below.
+
+
+ Data Table 1:
+
+
+
+This table lists all arrays by order of strain (index) and includes data on tube ID, strain, age, sex, number of animals in each sample pool (pool size), slide ID, slide position (A through F), batch by slide number (1 or 2), and Source of animals.
+
+
+
+
+
+
+
+
+
+ | Index |
+ Tube ID |
+ Strain |
+ Age |
+ Sex |
+ Pool size |
+ Slide Id |
+ Slide Position |
+ Batch Id |
+ Source |
+
+
+ | 1 |
+ R4893E1 |
+ A/J |
+ 59 |
+ F |
+ 0 |
+ 4252491010 |
+ A |
+ 1 |
+ JAX |
+
+
+ | 2 |
+ R4982E1 |
+ A/J |
+ 79 |
+ M |
+ 2 |
+ 4252491006 |
+ A |
+ 1 |
+ JAX |
+
+
+ | 3 |
+ R4894E1 |
+ A/J |
+ 59 |
+ M |
+ 0 |
+ 4252491011 |
+ A |
+ 1 |
+ JAX |
+
+
+ | 4 |
+ R3655E1 |
+ A/J |
+ 86 |
+ M |
+ 0 |
+ 4252491031 |
+ A |
+ 2 |
+ JAX |
+
+
+ | 5 |
+ R4897E1 |
+ AXB1 |
+ 90 |
+ F |
+ 0 |
+ 4252491005 |
+ C |
+ 1 |
+ JAX |
+
+
+ | 6 |
+ R5005E1 |
+ AXB1 |
+ 56 |
+ M |
+ 0 |
+ 4252491008 |
+ A |
+ 1 |
+ JAX |
+
+
+ | 7 |
+ R5001E1 |
+ AXB10 |
+ 63 |
+ F |
+ 2 |
+ 4252491008 |
+ B |
+ 1 |
+ JAX |
+
+
+ | 8 |
+ R5002E1 |
+ AXB10 |
+ 63 |
+ M |
+ 2 |
+ 4252491021 |
+ B |
+ 1 |
+ JAX |
+
+
+ | 9 |
+ R4891E1 |
+ AXB12 |
+ 63 |
+ F |
+ 0 |
+ 4252491009 |
+ A |
+ 1 |
+ JAX |
+
+
+ | 10 |
+ R4999E1 |
+ AXB12 |
+ 57 |
+ M |
+ 2 |
+ 4252491005 |
+ D |
+ 1 |
+ JAX |
+
+
+ | 11 |
+ R5000E1 |
+ AXB13 |
+ 57 |
+ M |
+ 2 |
+ 4252491008 |
+ C |
+ 1 |
+ JAX |
+
+
+ | 12 |
+ R5003E1 |
+ AXB15 |
+ 63 |
+ F |
+ 2 |
+ 4252491005 |
+ E |
+ 1 |
+ JAX |
+
+
+ | 13 |
+ R4963E1 |
+ AXB15 |
+ 63 |
+ M |
+ 2 |
+ 4252491031 |
+ B |
+ 1 |
+ JAX |
+
+
+ | 14 |
+ R3661E1 |
+ AXB19 |
+ 89 |
+ F |
+ 0 |
+ 4252491008 |
+ D |
+ 1 |
+ JAX |
+
+
+ | 15 |
+ R4962E1 |
+ AXB19 |
+ 62 |
+ M |
+ 0 |
+ 4252491005 |
+ F |
+ 1 |
+ JAX |
+
+
+ | 16 |
+ R4975E1 |
+ AXB2 |
+ 79 |
+ F |
+ 2 |
+ 4252491006 |
+ C |
+ 1 |
+ JAX |
+
+
+ | 17 |
+ R4976E1 |
+ AXB2 |
+ 79 |
+ M |
+ 2 |
+ 4252491021 |
+ C |
+ 1 |
+ JAX |
+
+
+ | 18 |
+ R4973E1 |
+ AXB23 |
+ 66 |
+ F |
+ 2 |
+ 4252491009 |
+ E |
+ 1 |
+ JAX |
+
+
+ | 19 |
+ R4972E1 |
+ AXB23 |
+ 66 |
+ M |
+ 2 |
+ 4252491006 |
+ D |
+ 1 |
+ JAX |
+
+
+ | 20 |
+ R4959E1 |
+ AXB24 |
+ 100 |
+ F |
+ 2 |
+ 4252491006 |
+ E |
+ 1 |
+ JAX |
+
+
+ | 21 |
+ R4960E1 |
+ AXB24 |
+ 100 |
+ M |
+ 2 |
+ 4252491019 |
+ A |
+ 1 |
+ JAX |
+
+
+ | 22 |
+ R4994E1 |
+ AXB4 |
+ 54 |
+ F |
+ 2 |
+ 4252491031 |
+ C |
+ 1 |
+ JAX |
+
+
+ | 23 |
+ R5007E1 |
+ AXB4 |
+ 54 |
+ M |
+ 2 |
+ 4252491006 |
+ F |
+ 1 |
+ JAX |
+
+
+ | 24 |
+ R4995E1 |
+ AXB5 |
+ 61 |
+ F |
+ 2 |
+ 4252491021 |
+ F |
+ 1 |
+ JAX |
+
+
+ | 25 |
+ R4996E1 |
+ AXB5 |
+ 61 |
+ M |
+ 2 |
+ 4252491009 |
+ F |
+ 1 |
+ JAX |
+
+
+ | 26 |
+ R4997E1 |
+ AXB6 |
+ 60 |
+ F |
+ 2 |
+ 4252491010 |
+ C |
+ 1 |
+ JAX |
+
+
+ | 27 |
+ R4998E1 |
+ AXB6 |
+ 60 |
+ M |
+ 2 |
+ 4252491021 |
+ D |
+ 1 |
+ JAX |
+
+
+ | 28 |
+ R4958E1 |
+ AXB8 |
+ 52 |
+ F |
+ 2 |
+ 4252491019 |
+ D |
+ 1 |
+ JAX |
+
+
+ | 29 |
+ R4957E1 |
+ AXB8 |
+ 52 |
+ M |
+ 2 |
+ 4252491010 |
+ D |
+ 1 |
+ JAX |
+
+
+ | 30 |
+ R4991E1 |
+ BXA1 |
+ 54 |
+ F |
+ 2 |
+ 4252491010 |
+ E |
+ 1 |
+ JAX |
+
+
+ | 31 |
+ R4990E1 |
+ BXA1 |
+ 54 |
+ M |
+ 2 |
+ 4252491009 |
+ B |
+ 1 |
+ JAX |
+
+
+ | 32 |
+ R4980E1 |
+ BXA11 |
+ 52 |
+ F |
+ 0 |
+ 4252491020 |
+ A |
+ 1 |
+ JAX |
+
+
+ | 33 |
+ R5006E1 |
+ BXA12 |
+ 48 |
+ F |
+ 2 |
+ 4252491011 |
+ C |
+ 2 |
+ JAX |
+
+
+ | 34 |
+ R4993E1 |
+ BXA12 |
+ 48 |
+ M |
+ 2 |
+ 4252491031 |
+ D |
+ 1 |
+ JAX |
+
+
+ | 35 |
+ R4968E1 |
+ BXA13 |
+ 61 |
+ F |
+ 2 |
+ 4252491011 |
+ D |
+ 1 |
+ JAX |
+
+
+ | 36 |
+ R4969E1 |
+ BXA13 |
+ 61 |
+ M |
+ 2 |
+ 4252491008 |
+ E |
+ 1 |
+ JAX |
+
+
+ | 37 |
+ R4966E1 |
+ BXA14 |
+ 56 |
+ F |
+ 2 |
+ 4252491031 |
+ E |
+ 1 |
+ JAX |
+
+
+ | 38 |
+ R4967E1 |
+ BXA14 |
+ 56 |
+ M |
+ 2 |
+ 4252491011 |
+ E |
+ 1 |
+ JAX |
+
+
+ | 39 |
+ R4970E1 |
+ BXA16 |
+ 51 |
+ F |
+ 2 |
+ 4252491011 |
+ F |
+ 1 |
+ JAX |
+
+
+ | 40 |
+ R5004E1 |
+ BXA16 |
+ 51 |
+ M |
+ 2 |
+ 4252491031 |
+ F |
+ 1 |
+ JAX |
+
+
+ | 41 |
+ R4981E1 |
+ BXA2 |
+ 50 |
+ F |
+ 2 |
+ 4252491008 |
+ F |
+ 1 |
+ JAX |
+
+
+ | 42 |
+ R4965E1 |
+ BXA2 |
+ 54 |
+ M |
+ 0 |
+ 4252491020 |
+ B |
+ 1 |
+ JAX |
+
+
+ | 43 |
+ R4984E1 |
+ BXA24 |
+ 54 |
+ F |
+ 2 |
+ 4252491021 |
+ E |
+ 1 |
+ JAX |
+
+
+ | 44 |
+ R4974E1 |
+ BXA24 |
+ 54 |
+ M |
+ 2 |
+ 4252491019 |
+ C |
+ 1 |
+ JAX |
+
+
+ | 45 |
+ R4988E1 |
+ BXA25 |
+ 70 |
+ M |
+ 0 |
+ 4252491020 |
+ F |
+ 1 |
+ JAX |
+
+
+ | 46 |
+ R4964E1 |
+ BXA26 |
+ 54 |
+ F |
+ 0 |
+ 4252491019 |
+ B |
+ 1 |
+ JAX |
+
+
+ | 47 |
+ R3636E1 |
+ BXA26 |
+ 87 |
+ M |
+ 0 |
+ 4252491009 |
+ D |
+ 1 |
+ JAX |
+
+
+ | 48 |
+ R4977E1 |
+ BXA4 |
+ 65 |
+ F |
+ 0 |
+ 4252491020 |
+ C |
+ 1 |
+ JAX |
+
+
+ | 49 |
+ R3638E1 |
+ BXA4 |
+ 87 |
+ M |
+ 0 |
+ 4252491019 |
+ E |
+ 1 |
+ JAX |
+
+
+ | 50 |
+ R4978E1 |
+ BXA7 |
+ 65 |
+ F |
+ 2 |
+ 4252491019 |
+ F |
+ 1 |
+ JAX |
+
+
+ | 51 |
+ R4979E1 |
+ BXA7 |
+ 65 |
+ M |
+ 2 |
+ 4252491021 |
+ A |
+ 1 |
+ JAX |
+
+
+ | 52 |
+ R5008E1 |
+ BXA8 |
+ 52 |
+ F |
+ 2 |
+ 4252491020 |
+ E |
+ 1 |
+ JAX |
+
+
+ | 53 |
+ R4983E1 |
+ BXA8 |
+ 52 |
+ M |
+ 2 |
+ 4252491020 |
+ D |
+ 1 |
+ JAX |
+
+
+ | 54 |
+ R5012E1 |
+ C57BL/6J |
+ 87 |
+ F |
+ 2 |
+ 4252491006 |
+ B |
+ 1 |
+ UTHSC RW |
+
+
+ | 55 |
+ R5010E1 |
+ C57BL/6J |
+ 87 |
+ F |
+ 2 |
+ 4252491011 |
+ B |
+ 1 |
+ UTHSC RW |
+
+
+ | 56 |
+ R5011E1 |
+ C57BL/6J |
+ 79 |
+ M |
+ 2 |
+ 4252491005 |
+ B |
+ 1 |
+ UTHSC RW |
+
+
+ | 57 |
+ R5009E1 |
+ C57BL/6J |
+ 79 |
+ M |
+ 2 |
+ 4252491010 |
+ B |
+ 1 |
+ UTHSC RW |
+
+
+
+
+ Downloading all data:
+
+
+ All data links (right-most column above) will be made active as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact RW Williams if you have any questions on the use of these open data.
+
+
+ About data processing:
+
+
+ This data set uses the standard Rank Invariant method developed by Illumina and described in their BeadStation Studio documentation.
+
+ |
+
+
+
+
+
+
diff --git a/general/datasets/Eye_m2_0406_m/acknowledgment.rtf b/general/datasets/Eye_m2_0406_m/acknowledgment.rtf
new file mode 100644
index 0000000..3f040d2
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_m/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant. All arrays were processed at the VA Medical Center, Memphis by Weikuan Gu.
diff --git a/general/datasets/Eye_m2_0406_m/cases.rtf b/general/datasets/Eye_m2_0406_m/cases.rtf
new file mode 100644
index 0000000..5cb5539
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_m/cases.rtf
@@ -0,0 +1,50 @@
+We used a set of 55 BXD recombinant inbred strains, 14 conventional inbred strains including C57BL/6J (B6) and DBA/2J (D2), and their reciprocal F1s. BXD strains were generated by crossing C57BL/6J with DBA/2J. The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage of D2). Physical maps in WebQTL incorporate approximately 2 million B6 vs D2 SNPs from Celera Genomics and from the Perlegen-NIEHS sequencing effort. BXD1 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+Please note that BXD24/TyJ (JAX stock number 000031) used in this study is also known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 stock that has now been rederived, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control.
+
+BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues.
+
+Mouse Diversity Panel (MDP). In addition to the BXD strains, we have profiled a MDP consisting 14 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/LtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ) have been included in the MDP. Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) also carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene.
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase-negative albino (c) mutant
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list. A tyrosinase-negative albino (c) mutant
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list. Important to note for this Eye dataset, C3H/HeJ is a Pdeb6 mutant with near total photoreceptor loss at maturity.
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1, aka F1 in some graphs and tables
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J. These reciprocal F1 can be used to detect some imprinted genes.
+
diff --git a/general/datasets/Eye_m2_0406_m/notes.rtf b/general/datasets/Eye_m2_0406_m/notes.rtf
new file mode 100644
index 0000000..39475ab
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_m/notes.rtf
@@ -0,0 +1,18 @@
+This study includes the following datasets:
+
+
+ -
+
Eye M430v2 (Apr06) RMA
+
+ -
+
Eye M430v2 (Apr06) PDNN
+
+ -
+
Eye M430v2 (Apr06) MAS5
+
+ -
+
Eye M430v2 (Sep06) RMA
+
+
+
+This text file originally generated by RWW, May 26, 2006. Updated by RWW, May 27, 2006.
diff --git a/general/datasets/Eye_m2_0406_m/platform.rtf b/general/datasets/Eye_m2_0406_m/platform.rtf
new file mode 100644
index 0000000..ac743ee
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_m/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are near duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequences as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
diff --git a/general/datasets/Eye_m2_0406_m/processing.rtf b/general/datasets/Eye_m2_0406_m/processing.rtf
new file mode 100644
index 0000000..d23bc47
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_m/processing.rtf
@@ -0,0 +1,20 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. The CEL files were processed using the RMA protocol. We processed the two batches together in RMA.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 7: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
+After RMA processing all arrays were rank-order normalized. This second round of quantile normalization removes much residual non-linearity across arrays and forces every array to have the same distribution of values as the mean of all arrays. Comparative array data quality was then evaluated in DataDesk. Outlier arrays were flagged by visual inspection in DataDesk, usually by means of an analysis of scatter plots and more quantitatively by generating a correlation matrix of all arrays. Those arrays with mean correlation <0.96 versus all other arrays indicates trouble or a biological outlier). In some cases, outliers were expected, such as samples from strains with retinal degeneration (C3H/HeJ and BXD24) and samples from wild subspecies such as CAST/Ei, PWD/Ph, and PWK/Ph. However, when arrays were anomolous both within strain and across strains, they were often simply discarded. We tended to keep arrays that "conformed" to the expectation. The assumption in these cases is that anomolous data are much more likely due to experimental problem and errors than to informative biological variation. Approximately 8 arrays total were discarded in batches 1 and 2 combined.
+
+After this process, the acceptable set of arrays was renormalized using all step as above, starting with the original RMA procedure, etc.
+
+We then categorized arrays into XXX major "technical groups" depending on expression patterns as noted in scatterplots. This process of defining technical groups was done in DataDesk by manually "typing" arrays. These technical groups are apparently due to subtle within-batch effect that we do not yet understand and that cannot be corrected by quantile normalization. These XXX major technical groups are not obviously related to strain, sex, age, or any other known biological effect or variable. They are also not obviously related to any of the Affymetrix QC data types (3'/5' ratios, gain, etc.). Once the technical groups were defined, we forced the means of each probe set in the XX technical groups to the same value. This simple process partially removes a technical error of unknown origin in large expression array data sets.
+
+We reviewed the final data set using a new method developed by RW Williams, Jeremy Peirce, and Hongqiang Li. For the full set of 140 arrays that passed standard QC protocols described above, we computed the strain means for the BXD strains, B6, D2, and F1s. Using this set of strain means we then computed LRS scores for all 45101 probe sets and counted the number of transcripts that generated QTLs with LRS values greater than 50. This value (e.g. 1000) represented the QTL harvest for the full data set. We then dropped a single array from the data set (n = 139 arrays), recomputed strain means, and recomputed the number of transcripts with LRS scores great than 50. This value is expected to typically reduce the number of QTLs that reach the criterion level (e.g., 950 QTLs > 50). This process was repeated for every array to obtain an array-specific difference value--the effect of removing that array on the total QTL count. For example, the loss of a single array might cause a decrease in 50 QTLs (1000-950). Values ranged from -90 (good0 to +38 (bad). This procedure is similar in some ways to a jackknife protocol, although we are not using this procedure to esimate an error term, but rather as a final method to polish a data set. By applying this procedure we discovered that a set of XX (7?) arrays could be excluded while simultaneously improving the total number of QTLs with values above 50.
+
+During this final process we discovered that nearly XX arrays in the second batch had been mislabeled at some point in processing. We computed the correct strain membership of each array using a large number of Mendelian probe sets (more than 50) and comparing their match to standard SNP and microsatellite markers and the original array data set of November 2005. This allowed us to rescue a large number of arrays that were of very high quality.
+
diff --git a/general/datasets/Eye_m2_0406_m/summary.rtf b/general/datasets/Eye_m2_0406_m/summary.rtf
new file mode 100644
index 0000000..68a4484
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_m/summary.rtf
@@ -0,0 +1,3 @@
+
+SUPERCEDED EYE DATA SET. The HEIMED April 2006 data set provides estimates of mRNA expression in whole eyes of 71 lines of young adult mice generated using 132 Affymetrix M430 2.0 arrays. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). We used pooled RNA samples, usually two independent pools; one male, one female, for each straion. This data set was processed using the RMA protocol. To simplify comparison among different transforms, RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Eye_m2_0406_m/tissue.rtf b/general/datasets/Eye_m2_0406_m/tissue.rtf
new file mode 100644
index 0000000..d8d345f
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_m/tissue.rtf
@@ -0,0 +1,7112 @@
+
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of RNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. Samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center lead by Drs. John Stuart and Weikuan Gu. All processing steps were performed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. centrigrade until use (one third roughly) or were immediately used for hybridization.
+
+Dealing with Ocular Pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations taken from brown and beige colored mice tend to have faint residual pigmentation that affects hybridization signal. The key determinant of this interesting effect is the Tyrp1 (brown) locus on Chr 4 at about 80 Mb. Loci on Chr 4 that map at this location should be considered with skepticism and reviewed carefully. To address this problem Yan Jiao purified total RNA a second time using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204). This was done for 8 colored samples (R2534E2, R2578E2, R1441E2, R2537E2, R2536E2, R2589E2, R2539E2) in the first batch of arrays (the November 05 data set) of which 5 were finally included in this data set (cases in which the strain ID is labeled with asterisks in the table). This same protocol was used for all samples in the second batch added in April 2006.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. The first and second batches of array data, collectively represents a reasonably well balanced sample of males and females belonging to 62 strains, but without within-strain-by-sex replication. Six strains are represented only by male sample pools (BXD15, 28, 29, 55, 98, and DBA/2J. Four strains are represented only by a female pool sample (BXD1, 27, 73 and 86). Please use the probe sets 1427262_at (Xist, high in females) and probe set 1426438_at (Ddx3y, high in males) as quantitative surrogates for the sex balance in this data set.
+
+Batch Structure: This data set consists of a two batches: the original batch that makes up the November 2005 data set and a new batch of 63 arrays (R0857E through R2649E, and R2682E through R2742E, non-consecutive identifiers) run in January 2006 by Dr. Yan Jiao. The arrays in the two batches are from two different lots. All arrays in the second batch were from Lot 4016879 (expiration date 12.28.06). We started working with a total of 140 arrays that passed initial crude quality control based on RNA quality and initial Affymetrix report file information such as 3'/5' ratio, scale factor, and percent present calls. A total of 130 arrays were finally approved for inclusion in this April 2006 data set. The complex normalization procedure is described below.
+
+The table below summarizes information on strain, age, sex, original CEL filename, Affymetrix quality control values, and source of mice. Columns labeled "PDNN 2Z outlier" and "RMA 2Z outlier" list the fraction of probe sets with values that deviated more than 2 z units from the mean. Scale factor, background average, present, absent, marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+IN PROGRESS: PLEASE NOTE THAT THIS TABLE IS NOW BEING UPDATED TO INCLUDE BATCH 2 OF EARLY 2006.
+
+
+
+
+
+ | ID |
+
+ tube ID
+ |
+
+ group_type
+ |
+
+ Strain
+ |
+
+ age
+ |
+
+ Sex
+ |
+
+ original
+
+ CEL
+
+ filename
+ |
+
+ PDNN
+
+ 2Z
+
+ outlier
+ |
+
+ RMA
+
+ 2Z
+
+ outlier
+ |
+
+ scale
+
+ factor
+ |
+
+ background
+
+ average
+ |
+
+ present
+ |
+
+ absent
+ |
+
+ marginal
+ |
+
+ AFFX-b-
+
+ ActinMur(3'/5')
+ |
+
+ AFFX-
+
+ GapdhMur(3'/5')
+ |
+
+ Source
+ |
+
+
+ |
+ 1
+ |
+
+ R2533E1
+ |
+
+ GDP
+ |
+
+ 129S1/SvImJ
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2533E.CEL
+ |
+
+ 0.025
+ |
+
+ 0.028
+ |
+
+ 2.11
+ |
+
+ 94
+ |
+
+ 57.90%
+ |
+
+ 40.50%
+ |
+
+ 1.60%
+ |
+
+ 1.37
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 2
+ |
+
+ R2595E1
+ |
+
+ GDP
+ |
+
+ 129S1/SvImJ
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2595E.CEL
+ |
+
+ 0.033
+ |
+
+ 0.036
+ |
+
+ 1.79
+ |
+
+ 115
+ |
+
+ 61.00%
+ |
+
+ 37.50%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 3
+ |
+
+ R0754E2
+ |
+
+ GDP
+ |
+
+ A/J
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R0754E.CEL
+ |
+
+ 0.027
+ |
+
+ 0.03
+ |
+
+ 2.72
+ |
+
+ 86
+ |
+
+ 59.80%
+ |
+
+ 38.70%
+ |
+
+ 1.50%
+ |
+
+ 1.36
+ |
+
+ 0.76
+ |
+
+ JAX
+ |
+
+
+ |
+ 4
+ |
+
+ R2546E1
+ |
+
+ GDP
+ |
+
+ A/J
+ |
+
+ 66
+ |
+
+ F
+ |
+
+ R2545E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.029
+ |
+
+ 1.99
+ |
+
+ 96
+ |
+
+ 58.60%
+ |
+
+ 39.70%
+ |
+
+ 1.70%
+ |
+
+ 1.47
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 5
+ |
+
+ R2601E1
+ |
+
+ GDP BXD
+ |
+
+ B6D2F1
+ |
+
+ 73
+ |
+
+ F
+ |
+
+ R2601E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.008
+ |
+
+ 2.55
+ |
+
+ 92
+ |
+
+ 58.90%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.44
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 6
+ |
+
+ R2602E1
+ |
+
+ GDP BXD
+ |
+
+ B6D2F1
+ |
+
+ 73
+ |
+
+ M
+ |
+
+ R2602E.CEL
+ |
+
+ 0.003
+ |
+
+ 0.008
+ |
+
+ 2.60
+ |
+
+ 84
+ |
+
+ 59.70%
+ |
+
+ 38.80%
+ |
+
+ 1.50%
+ |
+
+ 1.37
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 7
+ |
+
+ R1672E1
+ |
+
+ GDP
+ |
+
+ BALB/cByJ
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R1672E.CEL
+ |
+
+ 0.043
+ |
+
+ 0.039
+ |
+
+ 2.22
+ |
+
+ 111
+ |
+
+ 59.90%
+ |
+
+ 38.60%
+ |
+
+ 1.50%
+ |
+
+ 1.26
+ |
+
+ 0.80
+ |
+
+ JAX
+ |
+
+
+ |
+ 8
+ |
+
+ R1676E1
+ |
+
+ GDP
+ |
+
+ BALB/cByJ
+ |
+
+ 83
+ |
+
+ F
+ |
+
+ R1676E.CEL
+ |
+
+ 0.083
+ |
+
+ 0.085
+ |
+
+ 2.69
+ |
+
+ 98
+ |
+
+ 58.90%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.74
+ |
+
+ JAX
+ |
+
+
+ |
+ 9
+ |
+
+ R2581E1
+ |
+
+ BXD
+ |
+
+ BXD11
+ |
+
+ 65
+ |
+
+ F
+ |
+
+ R2581E.CEL
+ |
+
+ 0.009
+ |
+
+ 0.021
+ |
+
+ 1.94
+ |
+
+ 89
+ |
+
+ 62.10%
+ |
+
+ 36.40%
+ |
+
+ 1.60%
+ |
+
+ 1.55
+ |
+
+ 0.81
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 10
+ |
+
+ R2543E1
+ |
+
+ BXD
+ |
+
+ BXD12
+ |
+
+ 63
+ |
+
+ M
+ |
+
+ R2543E.CEL
+ |
+
+ 0.018
+ |
+
+ 0.017
+ |
+
+ 1.61
+ |
+
+ 118
+ |
+
+ 58.60%
+ |
+
+ 39.90%
+ |
+
+ 1.60%
+ |
+
+ 1.43
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 11
+ |
+
+ R2586E1
+ |
+
+ BXD
+ |
+
+ BXD13
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2586E.CEL
+ |
+
+ 0.259
+ |
+
+ 0.258
+ |
+
+ 2.01
+ |
+
+ 74
+ |
+
+ 56.40%
+ |
+
+ 42.00%
+ |
+
+ 1.60%
+ |
+
+ 2.85
+ |
+
+ 3.81
+ |
+
+ Glenn
+ |
+
+
+ |
+ 12
+ |
+
+ R2557E1
+ |
+
+ BXD
+ |
+
+ BXD14
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2557E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.027
+ |
+
+ 1.83
+ |
+
+ 99
+ |
+
+ 62.50%
+ |
+
+ 36.10%
+ |
+
+ 1.40%
+ |
+
+ 1.31
+ |
+
+ 0.78
+ |
+
+ Glenn
+ |
+
+
+ |
+ 13
+ |
+
+ R2567E1
+ |
+
+ BXD
+ |
+
+ BXD16
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2567E.CEL
+ |
+
+ 0.048
+ |
+
+ 0.058
+ |
+
+ 2.24
+ |
+
+ 82
+ |
+
+ 56.70%
+ |
+
+ 41.60%
+ |
+
+ 1.70%
+ |
+
+ 1.37
+ |
+
+ 0.75
+ |
+
+ Glenn
+ |
+
+
+ |
+ 14
+ |
+
+ R2559E1
+ |
+
+ BXD
+ |
+
+ BXD18
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2559E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.012
+ |
+
+ 1.65
+ |
+
+ 104
+ |
+
+ 60.80%
+ |
+
+ 37.70%
+ |
+
+ 1.50%
+ |
+
+ 1.27
+ |
+
+ 0.78
+ |
+
+ Glenn
+ |
+
+
+ |
+ 15
+ |
+
+ R2560E1
+ |
+
+ BXD
+ |
+
+ BXD19
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2560E.CEL
+ |
+
+ 0.009
+ |
+
+ 0.012
+ |
+
+ 1.79
+ |
+
+ 98
+ |
+
+ 60.90%
+ |
+
+ 37.50%
+ |
+
+ 1.60%
+ |
+
+ 1.35
+ |
+
+ 0.80
+ |
+
+ Glenn
+ |
+
+
+ |
+ 16
+ |
+
+ R2597E1
+ |
+
+ BXD
+ |
+
+ BXD2
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2597E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.012
+ |
+
+ 2.37
+ |
+
+ 94
+ |
+
+ 60.30%
+ |
+
+ 38.30%
+ |
+
+ 1.50%
+ |
+
+ 1.34
+ |
+
+ 0.77
+ |
+
+ Glenn
+ |
+
+
+ |
+ 17
+ |
+
+ R2584E1
+ |
+
+ BXD
+ |
+
+ BXD20
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2584E.CEL
+ |
+
+ 0.011
+ |
+
+ 0.017
+ |
+
+ 2.07
+ |
+
+ 84
+ |
+
+ 59.30%
+ |
+
+ 39.10%
+ |
+
+ 1.60%
+ |
+
+ 1.40
+ |
+
+ 0.76
+ |
+
+ Glenn
+ |
+
+
+ |
+ 18
+ |
+
+ R2541E2
+ |
+
+ BXD
+ |
+
+ BXD21
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2541E2.CEL
+ |
+
+ 0.049
+ |
+
+ 0.084
+ |
+
+ 2.63
+ |
+
+ 125
+ |
+
+ 56.00%
+ |
+
+ 42.40%
+ |
+
+ 1.50%
+ |
+
+ 1.29
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 19
+ |
+
+ R2553E1
+ |
+
+ BXD
+ |
+
+ BXD22
+ |
+
+ 58
+ |
+
+ F
+ |
+
+ R2553E.CEL
+ |
+
+ 0.004
+ |
+
+ 0.01
+ |
+
+ 1.95
+ |
+
+ 111
+ |
+
+ 59.90%
+ |
+
+ 38.50%
+ |
+
+ 1.50%
+ |
+
+ 1.28
+ |
+
+ 0.76
+ |
+
+ Glenn
+ |
+
+
+ |
+ 20
+ |
+
+ R2558E1
+ |
+
+ BXD
+ |
+
+ BXD23
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2558E-2.CEL
+ |
+
+ 0.018
+ |
+
+ 0.027
+ |
+
+ 1.91
+ |
+
+ 115
+ |
+
+ 59.90%
+ |
+
+ 38.80%
+ |
+
+ 1.40%
+ |
+
+ 1.20
+ |
+
+ 0.82
+ |
+
+ Glenn
+ |
+
+
+ |
+ 21
+ |
+
+ R2589E2
+ |
+
+ BXD
+ |
+
+ BXD24
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2589E2.CEL
+ |
+
+ 0.132
+ |
+
+ 0.176
+ |
+
+ 2.61
+ |
+
+ 112
+ |
+
+ 57.50%
+ |
+
+ 40.90%
+ |
+
+ 1.60%
+ |
+
+ 1.24
+ |
+
+ 0.80
+ |
+
+ Glenn
+ |
+
+
+ |
+ 22
+ |
+
+ R2573E1
+ |
+
+ BXD
+ |
+
+ BXD25
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2573E-2.CEL
+ |
+
+ 0.055
+ |
+
+ 0.063
+ |
+
+ 3.15
+ |
+
+ 72
+ |
+
+ 57.90%
+ |
+
+ 40.70%
+ |
+
+ 1.40%
+ |
+
+ 1.77
+ |
+
+ 0.97
+ |
+
+ UAB
+ |
+
+
+ |
+ 23
+ |
+
+ R2562E1
+ |
+
+ BXD
+ |
+
+ BXD29
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2562E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.01
+ |
+
+ 1.65
+ |
+
+ 116
+ |
+
+ 59.90%
+ |
+
+ 38.40%
+ |
+
+ 1.70%
+ |
+
+ 1.37
+ |
+
+ 0.79
+ |
+
+ Glenn
+ |
+
+
+ |
+ 24
+ |
+
+ R2598E1
+ |
+
+ BXD
+ |
+
+ BXD31
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2598E.CEL
+ |
+
+ 0.006
+ |
+
+ 0.013
+ |
+
+ 1.99
+ |
+
+ 106
+ |
+
+ 60.90%
+ |
+
+ 37.60%
+ |
+
+ 1.50%
+ |
+
+ 1.27
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 25
+ |
+
+ R2563E1
+ |
+
+ BXD
+ |
+
+ BXD32
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2563E.CEL
+ |
+
+ 0.023
+ |
+
+ 0.025
+ |
+
+ 1.55
+ |
+
+ 102
+ |
+
+ 61.90%
+ |
+
+ 36.70%
+ |
+
+ 1.40%
+ |
+
+ 1.50
+ |
+
+ 0.80
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 26
+ |
+
+ R2542E1
+ |
+
+ BXD
+ |
+
+ BXD33
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2542E.CEL
+ |
+
+ 0.058
+ |
+
+ 0.062
+ |
+
+ 2.13
+ |
+
+ 97
+ |
+
+ 56.50%
+ |
+
+ 41.80%
+ |
+
+ 1.60%
+ |
+
+ 1.91
+ |
+
+ 0.93
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 27
+ |
+
+ R2585E1
+ |
+
+ BXD
+ |
+
+ BXD34
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2585E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.032
+ |
+
+ 2.64
+ |
+
+ 75
+ |
+
+ 58.30%
+ |
+
+ 40.00%
+ |
+
+ 1.70%
+ |
+
+ 1.25
+ |
+
+ 0.77
+ |
+
+ Glenn
+ |
+
+
+ |
+ 28
+ |
+
+ R2532E1
+ |
+
+ BXD
+ |
+
+ BXD38
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2532E.CEL
+ |
+
+ 0.002
+ |
+
+ 0.006
+ |
+
+ 2.04
+ |
+
+ 94
+ |
+
+ 59.80%
+ |
+
+ 38.70%
+ |
+
+ 1.50%
+ |
+
+ 1.37
+ |
+
+ 0.80
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 29
+ |
+
+ R2574E1
+ |
+
+ BXD
+ |
+
+ BXD39
+ |
+
+ 70
+ |
+
+ F
+ |
+
+ R2574E.CEL
+ |
+
+ 0.003
+ |
+
+ 0.008
+ |
+
+ 1.98
+ |
+
+ 91
+ |
+
+ 61.20%
+ |
+
+ 37.30%
+ |
+
+ 1.50%
+ |
+
+ 1.39
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 30
+ |
+
+ R2590E1
+ |
+
+ BXD
+ |
+
+ BXD40
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2590E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.012
+ |
+
+ 2.71
+ |
+
+ 77
+ |
+
+ 59.10%
+ |
+
+ 39.30%
+ |
+
+ 1.50%
+ |
+
+ 1.40
+ |
+
+ 0.77
+ |
+
+ Glenn
+ |
+
+
+ |
+ 31
+ |
+
+ R2596E1
+ |
+
+ BXD
+ |
+
+ BXD42
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2596E.CEL
+ |
+
+ 0.016
+ |
+
+ 0.03
+ |
+
+ 2.63
+ |
+
+ 108
+ |
+
+ 59.00%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.24
+ |
+
+ 0.80
+ |
+
+ Glenn
+ |
+
+
+ |
+ 32
+ |
+
+ R2605E1
+ |
+
+ BXD
+ |
+
+ BXD43
+ |
+
+ 79
+ |
+
+ M
+ |
+
+ R2607E.CEL
+ |
+
+ 0.006
+ |
+
+ 0.01
+ |
+
+ 1.82
+ |
+
+ 131
+ |
+
+ 60.50%
+ |
+
+ 38.20%
+ |
+
+ 1.30%
+ |
+
+ 1.32
+ |
+
+ 0.80
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 33
+ |
+
+ R2594E1
+ |
+
+ BXD
+ |
+
+ BXD44
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2594E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.024
+ |
+
+ 1.77
+ |
+
+ 117
+ |
+
+ 59.80%
+ |
+
+ 38.80%
+ |
+
+ 1.40%
+ |
+
+ 1.35
+ |
+
+ 0.85
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 34
+ |
+
+ R2592E1
+ |
+
+ BXD
+ |
+
+ BXD45
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2592E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.011
+ |
+
+ 1.85
+ |
+
+ 106
+ |
+
+ 60.10%
+ |
+
+ 38.60%
+ |
+
+ 1.30%
+ |
+
+ 1.43
+ |
+
+ 0.85
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 35
+ |
+
+ R2606E1
+ |
+
+ BXD
+ |
+
+ BXD48
+ |
+
+ 78
+ |
+
+ M
+ |
+
+ R2606E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.015
+ |
+
+ 2.56
+ |
+
+ 106
+ |
+
+ 58.90%
+ |
+
+ 39.70%
+ |
+
+ 1.40%
+ |
+
+ 1.35
+ |
+
+ 0.83
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 36
+ |
+
+ R2591E1
+ |
+
+ BXD
+ |
+
+ BXD5
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2591E.CEL
+ |
+
+ 0.052
+ |
+
+ 0.014
+ |
+
+ 1.70
+ |
+
+ 136
+ |
+
+ 58.50%
+ |
+
+ 40.00%
+ |
+
+ 1.50%
+ |
+
+ 1.33
+ |
+
+ 0.78
+ |
+
+ Glenn
+ |
+
+
+ |
+ 37
+ |
+
+ R2603E1
+ |
+
+ BXD
+ |
+
+ BXD51
+ |
+
+ 66
+ |
+
+ F
+ |
+
+ R2603E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.02
+ |
+
+ 2.49
+ |
+
+ 115
+ |
+
+ 57.70%
+ |
+
+ 40.80%
+ |
+
+ 1.50%
+ |
+
+ 1.24
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 38
+ |
+
+ R2570E1
+ |
+
+ BXD
+ |
+
+ BXD6
+ |
+
+ 65
+ |
+
+ F
+ |
+
+ R2570E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.017
+ |
+
+ 1.99
+ |
+
+ 87
+ |
+
+ 58.50%
+ |
+
+ 40.00%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.76
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 39
+ |
+
+ R2534E2
+ |
+
+ BXD
+ |
+
+ BXD61
+ |
+
+ 70
+ |
+
+ F
+ |
+
+ R2534E2.CEL
+ |
+
+ 0.03
+ |
+
+ 0.058
+ |
+
+ 2.47
+ |
+
+ 118
+ |
+
+ 57.90%
+ |
+
+ 40.60%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 40
+ |
+
+ R2611E1
+ |
+
+ BXD
+ |
+
+ BXD64
+ |
+
+ 68
+ |
+
+ M
+ |
+
+ R2611E.CEL
+ |
+
+ 0.067
+ |
+
+ 0.068
+ |
+
+ 2.29
+ |
+
+ 92
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.50%
+ |
+
+ 1.57
+ |
+
+ 1.06
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 41
+ |
+
+ R2583E1
+ |
+
+ BXD
+ |
+
+ BXD65
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2583E.CEL
+ |
+
+ 0.027
+ |
+
+ 0.03
+ |
+
+ 2.49
+ |
+
+ 70
+ |
+
+ 56.90%
+ |
+
+ 41.50%
+ |
+
+ 1.60%
+ |
+
+ 1.67
+ |
+
+ 1.01
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 42
+ |
+
+ R2536E2
+ |
+
+ BXD
+ |
+
+ BXD66
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2536E2.CEL
+ |
+
+ 0.067
+ |
+
+ 0.139
+ |
+
+ 2.74
+ |
+
+ 109
+ |
+
+ 56.10%
+ |
+
+ 42.30%
+ |
+
+ 1.70%
+ |
+
+ 1.28
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 43
+ |
+
+ R2551E1
+ |
+
+ BXD
+ |
+
+ BXD68
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2551E.CEL
+ |
+
+ 0.294
+ |
+
+ 0.291
+ |
+
+ 2.49
+ |
+
+ 92
+ |
+
+ 54.30%
+ |
+
+ 44.10%
+ |
+
+ 1.60%
+ |
+
+ 2.91
+ |
+
+ 1.55
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 44
+ |
+
+ R2593E1
+ |
+
+ BXD
+ |
+
+ BXD69
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2593E.CEL
+ |
+
+ 0.027
+ |
+
+ 0.038
+ |
+
+ 1.67
+ |
+
+ 128
+ |
+
+ 59.20%
+ |
+
+ 39.50%
+ |
+
+ 1.30%
+ |
+
+ 1.47
+ |
+
+ 0.92
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 45
+ |
+
+ R2537E2
+ |
+
+ BXD
+ |
+
+ BXD70
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2537E2.CEL
+ |
+
+ 0.049
+ |
+
+ 0.092
+ |
+
+ 2.93
+ |
+
+ 99
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.60%
+ |
+
+ 1.29
+ |
+
+ 0.75
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 46
+ |
+
+ R2565E1
+ |
+
+ BXD
+ |
+
+ BXD75
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R2565E.CEL
+ |
+
+ 0.118
+ |
+
+ 0.124
+ |
+
+ 1.79
+ |
+
+ 102
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.50%
+ |
+
+ 2.31
+ |
+
+ 3.47
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 47
+ |
+
+ R2538E1
+ |
+
+ BXD
+ |
+
+ BXD8
+ |
+
+ 77
+ |
+
+ F
+ |
+
+ R2538E.CEL
+ |
+
+ 0.033
+ |
+
+ 0.056
+ |
+
+ 1.91
+ |
+
+ 102
+ |
+
+ 61.20%
+ |
+
+ 37.30%
+ |
+
+ 1.50%
+ |
+
+ 1.52
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 48
+ |
+
+ R2579E1
+ |
+
+ BXD
+ |
+
+ BXD80
+ |
+
+ 65
+ |
+
+ F
+ |
+
+ R2579E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.026
+ |
+
+ 2.42
+ |
+
+ 72
+ |
+
+ 59.20%
+ |
+
+ 39.40%
+ |
+
+ 1.50%
+ |
+
+ 1.73
+ |
+
+ 0.82
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 49
+ |
+
+ R2540E1
+ |
+
+ BXD
+ |
+
+ BXD87
+ |
+
+ 63
+ |
+
+ M
+ |
+
+ R2540E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.034
+ |
+
+ 2.33
+ |
+
+ 93
+ |
+
+ 61.10%
+ |
+
+ 37.40%
+ |
+
+ 1.40%
+ |
+
+ 1.22
+ |
+
+ 0.81
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 50
+ |
+
+ R2545E1
+ |
+
+ BXD
+ |
+
+ BXD89
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2546E.CEL
+ |
+
+ 0.266
+ |
+
+ 0.257
+ |
+
+ 1.67
+ |
+
+ 105
+ |
+
+ 56.20%
+ |
+
+ 42.30%
+ |
+
+ 1.50%
+ |
+
+ 3.60
+ |
+
+ 9.84
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 51
+ |
+
+ R2569E1
+ |
+
+ BXD
+ |
+
+ BXD9
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2569E.CEL
+ |
+
+ 0.256
+ |
+
+ 0.239
+ |
+
+ 1.75
+ |
+
+ 87
+ |
+
+ 55.10%
+ |
+
+ 43.40%
+ |
+
+ 1.50%
+ |
+
+ 2.82
+ |
+
+ 3.14
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 52
+ |
+
+ R2578E2
+ |
+
+ BXD
+ |
+
+ BXD90
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R2578E2.CEL
+ |
+
+ 0.041
+ |
+
+ 0.062
+ |
+
+ 2.79
+ |
+
+ 92
+ |
+
+ 58.60%
+ |
+
+ 39.80%
+ |
+
+ 1.60%
+ |
+
+ 1.52
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 53
+ |
+
+ R2554E1
+ |
+
+ BXD
+ |
+
+ BXD96
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2554E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.008
+ |
+
+ 2.18
+ |
+
+ 93
+ |
+
+ 60.20%
+ |
+
+ 38.30%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 54
+ |
+
+ R2577E1
+ |
+
+ BXD
+ |
+
+ BXD97
+ |
+
+ 55
+ |
+
+ M
+ |
+
+ R2577E.CEL
+ |
+
+ 0.065
+ |
+
+ 0.069
+ |
+
+ 2.07
+ |
+
+ 77
+ |
+
+ 59.50%
+ |
+
+ 39.10%
+ |
+
+ 1.40%
+ |
+
+ 1.87
+ |
+
+ 1.29
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 55
+ |
+
+ R1700E1
+ |
+
+ GDP
+ |
+
+ C3H/HeJ
+ |
+
+ 83
+ |
+
+ F
+ |
+
+ R1700E.CEL
+ |
+
+ 0.152
+ |
+
+ 0.168
+ |
+
+ 2.98
+ |
+
+ 69
+ |
+
+ 60.80%
+ |
+
+ 37.90%
+ |
+
+ 1.40%
+ |
+
+ 1.48
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 56
+ |
+
+ R1704E1
+ |
+
+ GDP
+ |
+
+ C3H/HeJ
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R1704E.CEL
+ |
+
+ 0.154
+ |
+
+ 0.165
+ |
+
+ 2.58
+ |
+
+ 88
+ |
+
+ 60.10%
+ |
+
+ 38.60%
+ |
+
+ 1.30%
+ |
+
+ 1.38
+ |
+
+ 0.84
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 57
+ |
+
+ R0872E2
+ |
+
+ GDP BXD
+ |
+
+ C57BL/6J
+ |
+
+ 66
+ |
+
+ M
+ |
+
+ R0872E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.023
+ |
+
+ 3.13
+ |
+
+ 89
+ |
+
+ 58.90%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.30
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 58
+ |
+
+ R2607E1
+ |
+
+ GDP BXD
+ |
+
+ C57BL/6J
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2605E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.018
+ |
+
+ 2.43
+ |
+
+ 115
+ |
+
+ 58.60%
+ |
+
+ 40.00%
+ |
+
+ 1.40%
+ |
+
+ 1.31
+ |
+
+ 0.76
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 59
+ |
+
+ R2564E1
+ |
+
+ GDP
+ |
+
+ CAST/Ei
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2564E.CEL
+ |
+
+ 0.124
+ |
+
+ 0.105
+ |
+
+ 1.94
+ |
+
+ 89
+ |
+
+ 58.50%
+ |
+
+ 39.90%
+ |
+
+ 1.60%
+ |
+
+ 1.60
+ |
+
+ 0.77
+ |
+
+ JAX
+ |
+
+
+ |
+ 60
+ |
+
+ R2580E1
+ |
+
+ GDP
+ |
+
+ CAST/Ei
+ |
+
+ 64
+ |
+
+ M
+ |
+
+ R2580E.CEL
+ |
+
+ 0.123
+ |
+
+ 0.109
+ |
+
+ 2.09
+ |
+
+ 95
+ |
+
+ 58.20%
+ |
+
+ 40.10%
+ |
+
+ 1.70%
+ |
+
+ 1.40
+ |
+
+ 0.76
+ |
+
+ JAX
+ |
+
+
+ |
+ 61
+ |
+
+ R2600E1
+ |
+
+ GDP BXD
+ |
+
+ D2B6F1
+ |
+
+ 72
+ |
+
+ F
+ |
+
+ R2600E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.02
+ |
+
+ 2.47
+ |
+
+ 95
+ |
+
+ 58.10%
+ |
+
+ 40.20%
+ |
+
+ 1.70%
+ |
+
+ 1.41
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 62
+ |
+
+ R2604E1
+ |
+
+ GDP BXD
+ |
+
+ D2B6F1
+ |
+
+ 69
+ |
+
+ M
+ |
+
+ R2604E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.014
+ |
+
+ 2.66
+ |
+
+ 90
+ |
+
+ 59.40%
+ |
+
+ 39.20%
+ |
+
+ 1.50%
+ |
+
+ 1.28
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 63
+ |
+
+ R2572E1
+ |
+
+ GDP BXD
+ |
+
+ DBA/2J
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R2572E.CEL
+ |
+
+ 0.091
+ |
+
+ 0.106
+ |
+
+ 2.41
+ |
+
+ 79
+ |
+
+ 55.50%
+ |
+
+ 42.90%
+ |
+
+ 1.60%
+ |
+
+ 1.37
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 64
+ |
+
+ R2636E1
+ |
+
+ GDP
+ |
+
+ KK/HIJ
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2636E.CEL
+ |
+
+ 0.044
+ |
+
+ 0.043
+ |
+
+ 2.61
+ |
+
+ 93
+ |
+
+ 58.90%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.39
+ |
+
+ 0.76
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 65
+ |
+
+ R2637E1
+ |
+
+ GDP
+ |
+
+ KK/HIJ
+ |
+
+ 64
+ |
+
+ M
+ |
+
+ R2637E.CEL
+ |
+
+ 0.056
+ |
+
+ 0.036
+ |
+
+ 2.19
+ |
+
+ 103
+ |
+
+ 59.40%
+ |
+
+ 39.00%
+ |
+
+ 1.50%
+ |
+
+ 1.30
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 66
+ |
+
+ R0999E1
+ |
+
+ GDP
+ |
+
+ LG/J
+ |
+
+ 57
+ |
+
+ F
+ |
+
+ R0999E.CEL
+ |
+
+ 0.021
+ |
+
+ 0.023
+ |
+
+ 2.45
+ |
+
+ 82
+ |
+
+ 59.40%
+ |
+
+ 39.10%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 67
+ |
+
+ R1004E1
+ |
+
+ GDP
+ |
+
+ LG/J
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R1004E.CEL
+ |
+
+ 0.025
+ |
+
+ 0.028
+ |
+
+ 2.44
+ |
+
+ 92
+ |
+
+ 58.70%
+ |
+
+ 39.80%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 68
+ |
+
+ R1688E1
+ |
+
+ GDP
+ |
+
+ NOD/LtJ
+ |
+
+ 66
+ |
+
+ F
+ |
+
+ R1688E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.033
+ |
+
+ 2.66
+ |
+
+ 98
+ |
+
+ 58.60%
+ |
+
+ 39.90%
+ |
+
+ 1.50%
+ |
+
+ 1.26
+ |
+
+ 0.80
+ |
+
+ JAX
+ |
+
+
+ |
+ 69
+ |
+
+ R2566E1
+ |
+
+ GDP
+ |
+
+ NOD/LtJ
+ |
+
+ 76
+ |
+
+ M
+ |
+
+ R2566E-2.CEL
+ |
+
+ 0.036
+ |
+
+ 0.04
+ |
+
+ 3.03
+ |
+
+ 69
+ |
+
+ 59.80%
+ |
+
+ 38.80%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.75
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 70
+ |
+
+ R2535E1
+ |
+
+ GDP
+ |
+
+ NZO/H1LtJ
+ |
+
+ 62
+ |
+
+ F
+ |
+
+ R2535E.CEL
+ |
+
+ 0.037
+ |
+
+ 0.062
+ |
+
+ 1.89
+ |
+
+ 86
+ |
+
+ 60.40%
+ |
+
+ 38.20%
+ |
+
+ 1.40%
+ |
+
+ 1.41
+ |
+
+ 0.85
+ |
+
+ JAX
+ |
+
+
+ |
+ 71
+ |
+
+ R2550E1
+ |
+
+ GDP
+ |
+
+ NZO/HILtJ
+ |
+
+ 96
+ |
+
+ M
+ |
+
+ R2550E.CEL
+ |
+
+ 0.025
+ |
+
+ 0.029
+ |
+
+ 1.79
+ |
+
+ 87
+ |
+
+ 60.70%
+ |
+
+ 37.80%
+ |
+
+ 1.50%
+ |
+
+ 1.52
+ |
+
+ 0.82
+ |
+
+ JAX
+ |
+
+
+ |
+ 72
+ |
+
+ R2634E1
+ |
+
+ GDP
+ |
+
+ PWD/PhJ
+ |
+
+ 62
+ |
+
+ F
+ |
+
+ R2635E.CEL
+ |
+
+ 0.126
+ |
+
+ 0.114
+ |
+
+ 3.29
+ |
+
+ 90
+ |
+
+ 55.90%
+ |
+
+ 42.50%
+ |
+
+ 1.60%
+ |
+
+ 1.57
+ |
+
+ 0.81
+ |
+
+ JAX
+ |
+
+
+ |
+ 73
+ |
+
+ R2635E1
+ |
+
+ GDP
+ |
+
+ PWD/PhJ
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2634E.CEL
+ |
+
+ 0.15
+ |
+
+ 0.137
+ |
+
+ 3.72
+ |
+
+ 80
+ |
+
+ 54.20%
+ |
+
+ 44.10%
+ |
+
+ 1.70%
+ |
+
+ 1.53
+ |
+
+ 0.85
+ |
+
+ JAX
+ |
+
+
+ |
+ 74
+ |
+
+ R2544E1
+ |
+
+ GDP
+ |
+
+ PWK/PhJ
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2544E.CEL
+ |
+
+ 0.174
+ |
+
+ 0.175
+ |
+
+ 2.20
+ |
+
+ 108
+ |
+
+ 54.90%
+ |
+
+ 43.50%
+ |
+
+ 1.70%
+ |
+
+ 1.36
+ |
+
+ 0.82
+ |
+
+ JAX
+ |
+
+
+ |
+ 75
+ |
+
+ R2549E1
+ |
+
+ GDP
+ |
+
+ PWK/PhJ
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R2549E.CEL
+ |
+
+ 0.103
+ |
+
+ 0.087
+ |
+
+ 2.28
+ |
+
+ 84
+ |
+
+ 57.30%
+ |
+
+ 41.20%
+ |
+
+ 1.50%
+ |
+
+ 1.57
+ |
+
+ 0.83
+ |
+
+ JAX
+ |
+
+
+ |
+ 76
+ |
+
+ R2368E1
+ |
+
+ GDP
+ |
+
+ WSB/EI
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2368E.CEL
+ |
+
+ 0.041
+ |
+
+ 0.047
+ |
+
+ 2.57
+ |
+
+ 86
+ |
+
+ 59.50%
+ |
+
+ 39.10%
+ |
+
+ 1.40%
+ |
+
+ 1.29
+ |
+
+ 0.74
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 77
+ |
+
+ R2704E
+ |
+
+ BXD
+ |
+
+ BXD1
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2704E.CEL
+ |
+
+ 0.029
+ |
+
+ 0.03
+ |
+
+ 2.066
+ |
+
+ 139.61
+ |
+
+ 56.60%
+ |
+
+ 41.90%
+ |
+
+ 1.50%
+ |
+
+ 1.31
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 78
+ |
+
+ R2612E
+ |
+
+ BXD
+ |
+
+ BXD11
+ |
+
+ 70
+ |
+
+ M
+ |
+
+ R2612E.CEL
+ |
+
+ 0.101
+ |
+
+ 0.112
+ |
+
+ 1.83
+ |
+
+ 142.03
+ |
+
+ 58.20%
+ |
+
+ 40.50%
+ |
+
+ 1.40%
+ |
+
+ 1.78
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 79
+ |
+
+ R2742E
+ |
+
+ BXD
+ |
+
+ BXD12
+ |
+
+ 71
+ |
+
+ F
+ |
+
+ R2742E.CEL
+ |
+
+ 0.073
+ |
+
+ 0.077
+ |
+
+ 2.127
+ |
+
+ 134.14
+ |
+
+ 57.00%
+ |
+
+ 41.60%
+ |
+
+ 1.40%
+ |
+
+ 1.64
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 80
+ |
+
+ R1086E
+ |
+
+ BXD
+ |
+
+ BXD23
+ |
+
+ 55
+ |
+
+ M
+ |
+
+ R1086E.CEL
+ |
+
+ 0.043
+ |
+
+ 0.034
+ |
+
+ 2.233
+ |
+
+ 125.05
+ |
+
+ 58.60%
+ |
+
+ 39.90%
+ |
+
+ 1.50%
+ |
+
+ 1.43
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 81
+ |
+
+ R2716E
+ |
+
+ BXD
+ |
+
+ BXD15
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2716E.CEL
+ |
+
+ 0.035
+ |
+
+ 0.037
+ |
+
+ 2.015
+ |
+
+ 150.83
+ |
+
+ 56.40%
+ |
+
+ 42.10%
+ |
+
+ 1.60%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 82
+ |
+
+ R2711E
+ |
+
+ BXD
+ |
+
+ BXD16
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R2711E.CEL
+ |
+
+ 0.032
+ |
+
+ 0.021
+ |
+
+ 1.953
+ |
+
+ 118.53
+ |
+
+ 59.00%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.45
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 83
+ |
+
+ R2720E
+ |
+
+ BXD
+ |
+
+ BXD18
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2720E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.019
+ |
+
+ 2.32
+ |
+
+ 99.93
+ |
+
+ 59.50%
+ |
+
+ 39.00%
+ |
+
+ 1.50%
+ |
+
+ 1.33
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 84
+ |
+
+ R2713E
+ |
+
+ BXD
+ |
+
+ BXD19
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2713E.CEL
+ |
+
+ 0.055
+ |
+
+ 0.021
+ |
+
+ 1.67
+ |
+
+ 120.82
+ |
+
+ 60.20%
+ |
+
+ 38.30%
+ |
+
+ 1.50%
+ |
+
+ 1.45
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 85
+ |
+
+ R1231E
+ |
+
+ BXD
+ |
+
+ BXD2
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R1231E.CEL
+ |
+
+ 0.044
+ |
+
+ 0.037
+ |
+
+ 2.197
+ |
+
+ 138.73
+ |
+
+ 57.30%
+ |
+
+ 41.30%
+ |
+
+ 1.40%
+ |
+
+ 1.41
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 86
+ |
+
+ R2731E
+ |
+
+ BXD
+ |
+
+ BXD20
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2731E.CEL
+ |
+
+ 0.017
+ |
+
+ 0.019
+ |
+
+ 1.825
+ |
+
+ 147
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.4
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 87
+ |
+
+ R2702E
+ |
+
+ BXD
+ |
+
+ BXD21
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2702E.CEL
+ |
+
+ 0.009
+ |
+
+ 0.008
+ |
+
+ 1.811
+ |
+
+ 128.65
+ |
+
+ 59.40%
+ |
+
+ 39.10%
+ |
+
+ 1.40%
+ |
+
+ 1.26
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 88
+ |
+
+ R2700E
+ |
+
+ BXD
+ |
+
+ BXD22
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2700E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.015
+ |
+
+ 1.858
+ |
+
+ 102.96
+ |
+
+ 61.50%
+ |
+
+ 37.10%
+ |
+
+ 1.30%
+ |
+
+ 1.48
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 89
+ |
+
+ R1128E
+ |
+
+ BXD
+ |
+
+ BXD14
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R1128E.CEL
+ |
+
+ 0.037
+ |
+
+ 0.038
+ |
+
+ 2.366
+ |
+
+ 118.39
+ |
+
+ 57.30%
+ |
+
+ 41.30%
+ |
+
+ 1.40%
+ |
+
+ 1.45
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 90
+ |
+
+ R2719E
+ |
+
+ BXD
+ |
+
+ BXD24
+ |
+
+ 123
+ |
+
+ F
+ |
+
+ R2719E.CEL
+ |
+
+ 0.112
+ |
+
+ 0.111
+ |
+
+ 1.47
+ |
+
+ 140.38
+ |
+
+ 61.50%
+ |
+
+ 37.20%
+ |
+
+ 1.30%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 91
+ |
+
+ R2683E
+ |
+
+ BXD
+ |
+
+ BXD25
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R2683E.CEL
+ |
+
+ 0.068
+ |
+
+ 0.068
+ |
+
+ 1.777
+ |
+
+ 115.64
+ |
+
+ 58.30%
+ |
+
+ 40.30%
+ |
+
+ 1.40%
+ |
+
+ 2.01
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 92
+ |
+
+ R2703E
+ |
+
+ BXD
+ |
+
+ BXD27
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2703E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.012
+ |
+
+ 1.263
+ |
+
+ 134.78
+ |
+
+ 62.60%
+ |
+
+ 36.10%
+ |
+
+ 1.40%
+ |
+
+ 1.44
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 93
+ |
+
+ R2721E
+ |
+
+ BXD
+ |
+
+ BXD28
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2721E.CEL
+ |
+
+ 0.04
+ |
+
+ 0.048
+ |
+
+ 2.065
+ |
+
+ 157.39
+ |
+
+ 56.10%
+ |
+
+ 42.40%
+ |
+
+ 1.50%
+ |
+
+ 1.31
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 94
+ |
+
+ R1258E
+ |
+
+ BXD
+ |
+
+ BXD31
+ |
+
+ 57
+ |
+
+ F
+ |
+
+ R1258E.CEL
+ |
+
+ 0.037
+ |
+
+ 0.036
+ |
+
+ 2.063
+ |
+
+ 117.09
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.54
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 95
+ |
+
+ R1216E
+ |
+
+ BXD
+ |
+
+ BXD32
+ |
+
+ 76
+ |
+
+ M
+ |
+
+ R1216E.CEL
+ |
+
+ 0.05
+ |
+
+ 0.049
+ |
+
+ 2.23
+ |
+
+ 111.99
+ |
+
+ 58.80%
+ |
+
+ 39.80%
+ |
+
+ 1.40%
+ |
+
+ 1.35
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 96
+ |
+
+ R857E
+ |
+
+ BXD
+ |
+
+ BXD33
+ |
+
+ 77
+ |
+
+ M
+ |
+
+ R857E.CEL
+ |
+
+ 0.078
+ |
+
+ 0.108
+ |
+
+ 1.737
+ |
+
+ 113.98
+ |
+
+ 61.90%
+ |
+
+ 36.70%
+ |
+
+ 1.30%
+ |
+
+ 1.6
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 97
+ |
+
+ R859E
+ |
+
+ BXD
+ |
+
+ BXD90
+ |
+
+ 72
+ |
+
+ M
+ |
+
+ R859E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.02
+ |
+
+ 1.847
+ |
+
+ 152.22
+ |
+
+ 57.90%
+ |
+
+ 40.70%
+ |
+
+ 1.40%
+ |
+
+ 1.36
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 98
+ |
+
+ R1207E
+ |
+
+ BXD
+ |
+
+ BXD66
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R1207E.CEL
+ |
+
+ 0.017
+ |
+
+ 0.012
+ |
+
+ 1.681
+ |
+
+ 136.86
+ |
+
+ 60.40%
+ |
+
+ 38.10%
+ |
+
+ 1.50%
+ |
+
+ 1.45
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 99
+ |
+
+ R2710E
+ |
+
+ BXD
+ |
+
+ BXD38
+ |
+
+ 55
+ |
+
+ F
+ |
+
+ R2710E.CEL
+ |
+
+ 0.033
+ |
+
+ 0.031
+ |
+
+ 2.112
+ |
+
+ 122.1
+ |
+
+ 58.80%
+ |
+
+ 39.80%
+ |
+
+ 1.40%
+ |
+
+ 1.37
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 100
+ |
+
+ R2695E
+ |
+
+ BXD
+ |
+
+ BXD39
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2695E.CEL
+ |
+
+ 0.018
+ |
+
+ 0.016
+ |
+
+ 1.638
+ |
+
+ 122.7
+ |
+
+ 60.80%
+ |
+
+ 37.80%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 101
+ |
+
+ R2699E
+ |
+
+ BXD
+ |
+
+ BXD40
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2699E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.015
+ |
+
+ 1.827
+ |
+
+ 105.23
+ |
+
+ 61.70%
+ |
+
+ 36.90%
+ |
+
+ 1.40%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 102
+ |
+
+ R2696E
+ |
+
+ BXD
+ |
+
+ BXD42
+ |
+
+ 58
+ |
+
+ F
+ |
+
+ R2696E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.017
+ |
+
+ 1.622
+ |
+
+ 118.95
+ |
+
+ 62.00%
+ |
+
+ 36.60%
+ |
+
+ 1.50%
+ |
+
+ 1.53
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 103
+ |
+
+ R943E-2
+ |
+
+ BXD
+ |
+
+ BXD64
+ |
+
+ 56
+ |
+
+ F
+ |
+
+ R943E-2.CEL
+ |
+
+ 0.024
+ |
+
+ 0.021
+ |
+
+ 1.591
+ |
+
+ 141.34
+ |
+
+ 60.10%
+ |
+
+ 38.40%
+ |
+
+ 1.50%
+ |
+
+ 1.32
+ |
+
+ 0.76
+ |
+
+ GU
+ |
+
+
+ |
+ 104
+ |
+
+ R967E
+ |
+
+ BXD
+ |
+
+ BXD48
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R967E.CEL
+ |
+
+ 0.101
+ |
+
+ 0.052
+ |
+
+ 1.948
+ |
+
+ 130.95
+ |
+
+ 57.30%
+ |
+
+ 41.20%
+ |
+
+ 1.50%
+ |
+
+ 1.63
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 105
+ |
+
+ R2714E
+ |
+
+ BXD
+ |
+
+ BXD5
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R2714E.CEL
+ |
+
+ 0.047
+ |
+
+ 0.014
+ |
+
+ 1.404
+ |
+
+ 144.35
+ |
+
+ 60.60%
+ |
+
+ 37.90%
+ |
+
+ 1.50%
+ |
+
+ 1.43
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 106
+ |
+
+ R1042E
+ |
+
+ BXD
+ |
+
+ BXD51
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R1042E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.027
+ |
+
+ 2.352
+ |
+
+ 104.12
+ |
+
+ 58.70%
+ |
+
+ 39.90%
+ |
+
+ 1.40%
+ |
+
+ 1.53
+ |
+
+ 0.82
+ |
+
+ GU
+ |
+
+
+ |
+ 107
+ |
+
+ R2690E
+ |
+
+ BXD
+ |
+
+ BXD55
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R2690E.CEL
+ |
+
+ 0.081
+ |
+
+ 0.067
+ |
+
+ 1.887
+ |
+
+ 164.01
+ |
+
+ 56.10%
+ |
+
+ 42.30%
+ |
+
+ 1.60%
+ |
+
+ 1.43
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 108
+ |
+
+ R2694E
+ |
+
+ BXD
+ |
+
+ BXD6
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R2694E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.018
+ |
+
+ 1.983
+ |
+
+ 97.23
+ |
+
+ 61.60%
+ |
+
+ 37.10%
+ |
+
+ 1.30%
+ |
+
+ 1.39
+ |
+
+ 0.82
+ |
+
+ GU
+ |
+
+
+ |
+ 109
+ |
+
+ R975E
+ |
+
+ BXD
+ |
+
+ BXD70
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R975E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.024
+ |
+
+ 1.841
+ |
+
+ 137.97
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.40%
+ |
+
+ 1.36
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 110
+ |
+
+ R2684E
+ |
+
+ BXD
+ |
+
+ BXD61
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2684E.CEL
+ |
+
+ 0.031
+ |
+
+ 0.032
+ |
+
+ 2.01
+ |
+
+ 131.03
+ |
+
+ 57.00%
+ |
+
+ 41.50%
+ |
+
+ 1.50%
+ |
+
+ 1.34
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 111
+ |
+
+ R994E
+ |
+
+ BXD
+ |
+
+ BXD43
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R994E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.014
+ |
+
+ 1.966
+ |
+
+ 113.12
+ |
+
+ 60.80%
+ |
+
+ 37.80%
+ |
+
+ 1.40%
+ |
+
+ 1.66
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 112
+ |
+
+ R2610E
+ |
+
+ BXD
+ |
+
+ BXD44
+ |
+
+ 68
+ |
+
+ M
+ |
+
+ R2610E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.009
+ |
+
+ 1.814
+ |
+
+ 142.91
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.35
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 113
+ |
+
+ R2689E
+ |
+
+ BXD
+ |
+
+ BXD65
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2689E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.008
+ |
+
+ 1.721
+ |
+
+ 142.44
+ |
+
+ 59.90%
+ |
+
+ 38.60%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.76
+ |
+
+ GU
+ |
+
+
+ |
+ 114
+ |
+
+ R2727E
+ |
+
+ BXD
+ |
+
+ BXD69
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R2727E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.008
+ |
+
+ 1.578
+ |
+
+ 143.86
+ |
+
+ 60.30%
+ |
+
+ 38.30%
+ |
+
+ 1.40%
+ |
+
+ 1.34
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 115
+ |
+
+ R2726E
+ |
+
+ BXD
+ |
+
+ BXD68
+ |
+
+ 64
+ |
+
+ M
+ |
+
+ R2726E.CEL
+ |
+
+ 0.125
+ |
+
+ 0.025
+ |
+
+ 1.811
+ |
+
+ 153.09
+ |
+
+ 58.70%
+ |
+
+ 39.80%
+ |
+
+ 1.50%
+ |
+
+ 1.39
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 116
+ |
+
+ R2732E
+ |
+
+ BXD
+ |
+
+ BXD45
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2732E.CEL
+ |
+
+ 0.039
+ |
+
+ 0.036
+ |
+
+ 2.154
+ |
+
+ 122.45
+ |
+
+ 56.50%
+ |
+
+ 42.10%
+ |
+
+ 1.40%
+ |
+
+ 1.8
+ |
+
+ 0.83
+ |
+
+ GU
+ |
+
+
+ |
+ 117
+ |
+
+ R2709E
+ |
+
+ BXD
+ |
+
+ BXD8
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2709E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.011
+ |
+
+ 1.99
+ |
+
+ 99.79
+ |
+
+ 60.90%
+ |
+
+ 37.60%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.76
+ |
+
+ GU
+ |
+
+
+ |
+ 118
+ |
+
+ R2686E
+ |
+
+ BXD
+ |
+
+ BXD80
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2686E.CEL
+ |
+
+ 0.046
+ |
+
+ 0.05
+ |
+
+ 2.342
+ |
+
+ 119.63
+ |
+
+ 56.00%
+ |
+
+ 42.60%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 119
+ |
+
+ R2692E
+ |
+
+ BXD
+ |
+
+ BXD85
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2692E.CEL
+ |
+
+ 0.006
+ |
+
+ 0.007
+ |
+
+ 1.423
+ |
+
+ 160.87
+ |
+
+ 60.20%
+ |
+
+ 38.30%
+ |
+
+ 1.40%
+ |
+
+ 1.46
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 120
+ |
+
+ R2715E
+ |
+
+ BXD
+ |
+
+ BXD85
+ |
+
+ 91
+ |
+
+ M
+ |
+
+ R2715E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.008
+ |
+
+ 1.488
+ |
+
+ 142.6
+ |
+
+ 61.20%
+ |
+
+ 37.30%
+ |
+
+ 1.40%
+ |
+
+ 1.5
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 121
+ |
+
+ R1405E
+ |
+
+ BXD
+ |
+
+ BXD86
+ |
+
+ 58
+ |
+
+ F
+ |
+
+ R1405E.CEL
+ |
+
+ 0.053
+ |
+
+ 0.052
+ |
+
+ 2.351
+ |
+
+ 119.34
+ |
+
+ 56.40%
+ |
+
+ 42.20%
+ |
+
+ 1.40%
+ |
+
+ 1.64
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 122
+ |
+
+ R2724E
+ |
+
+ BXD
+ |
+
+ BXD87
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2724E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.019
+ |
+
+ 1.906
+ |
+
+ 113.71
+ |
+
+ 60.70%
+ |
+
+ 37.90%
+ |
+
+ 1.40%
+ |
+
+ 1.45
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 123
+ |
+
+ R1451E
+ |
+
+ BXD
+ |
+
+ BXD34
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R1451E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.009
+ |
+
+ 1.843
+ |
+
+ 140.05
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 124
+ |
+
+ R1433E
+ |
+
+ BXD
+ |
+
+ BXD89
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R1433E.CEL
+ |
+
+ 0.029
+ |
+
+ 0.026
+ |
+
+ 2.241
+ |
+
+ 115.86
+ |
+
+ 57.70%
+ |
+
+ 40.80%
+ |
+
+ 1.50%
+ |
+
+ 1.41
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 125
+ |
+
+ R2733E
+ |
+
+ BXD
+ |
+
+ BXD96
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2733E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.054
+ |
+
+ 1.7
+ |
+
+ 113.99
+ |
+
+ 62.10%
+ |
+
+ 36.60%
+ |
+
+ 1.30%
+ |
+
+ 1.4
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 126
+ |
+
+ R2649E
+ |
+
+ BXD
+ |
+
+ BXD97
+ |
+
+ 74
+ |
+
+ F
+ |
+
+ R2649E.CEL
+ |
+
+ 0.029
+ |
+
+ 0.032
+ |
+
+ 2.343
+ |
+
+ 119.04
+ |
+
+ 57.50%
+ |
+
+ 41.20%
+ |
+
+ 1.40%
+ |
+
+ 1.53
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 127
+ |
+
+ R2688E
+ |
+
+ BXD
+ |
+
+ BXD98
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2688E.CEL
+ |
+
+ 0.032
+ |
+
+ 0.03
+ |
+
+ 1.772
+ |
+
+ 145.24
+ |
+
+ 58.50%
+ |
+
+ 40.00%
+ |
+
+ 1.50%
+ |
+
+ 1.48
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 128
+ |
+
+ R877E
+ |
+
+ BXD
+ |
+
+ BXD13
+ |
+
+ 76
+ |
+
+ M
+ |
+
+ R877E.CEL
+ |
+
+ 0.026
+ |
+
+ 0.067
+ |
+
+ 1.558
+ |
+
+ 125.63
+ |
+
+ 61.20%
+ |
+
+ 37.50%
+ |
+
+ 1.20%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 129
+ |
+
+ R1397E-re
+ |
+
+ BXD
+ |
+
+ BXD75
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R1397E-re.CEL
+ |
+
+ 0.032
+ |
+
+ 0.01
+ |
+
+ 1.449
+ |
+
+ 189.71
+ |
+
+ 59.60%
+ |
+
+ 39.00%
+ |
+
+ 1.40%
+ |
+
+ 1.39
+ |
+
+ 0.82
+ |
+
+ GU
+ |
+
+
+ |
+ 130
+ |
+
+ R2779E
+ |
+
+ BXD
+ |
+
+ BXD73
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2779E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.038
+ |
+
+ 1.746
+ |
+
+ 121.11
+ |
+
+ 59.60%
+ |
+
+ 39.00%
+ |
+
+ 1.40%
+ |
+
+ 1.5
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 131
+ |
+
+ R2708E
+ |
+
+ BXD
+ |
+
+ BXD9
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2708E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.045
+ |
+
+ 1.966
+ |
+
+ 126.46
+ |
+
+ 57.70%
+ |
+
+ 40.70%
+ |
+
+ 1.50%
+ |
+
+ 1.4
+ |
+
+ 0.84
+ |
+
+ GU
+ |
+
+
+ |
+ 132
+ |
+
+ R2547E1
+ |
+
+ GDP
+ |
+
+ WSB/Ei
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2547E.CEL
+ |
+
+ 0.041
+ |
+
+ 0.039
+ |
+
+ 2.14
+ |
+
+ 90
+ |
+
+ 58.20%
+ |
+
+ 40.10%
+ |
+
+ 1.60%
+ |
+
+ 1.32
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0406_p/acknowledgment.rtf b/general/datasets/Eye_m2_0406_p/acknowledgment.rtf
new file mode 100644
index 0000000..3f040d2
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_p/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant. All arrays were processed at the VA Medical Center, Memphis by Weikuan Gu.
diff --git a/general/datasets/Eye_m2_0406_p/cases.rtf b/general/datasets/Eye_m2_0406_p/cases.rtf
new file mode 100644
index 0000000..5cb5539
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_p/cases.rtf
@@ -0,0 +1,50 @@
+We used a set of 55 BXD recombinant inbred strains, 14 conventional inbred strains including C57BL/6J (B6) and DBA/2J (D2), and their reciprocal F1s. BXD strains were generated by crossing C57BL/6J with DBA/2J. The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage of D2). Physical maps in WebQTL incorporate approximately 2 million B6 vs D2 SNPs from Celera Genomics and from the Perlegen-NIEHS sequencing effort. BXD1 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+Please note that BXD24/TyJ (JAX stock number 000031) used in this study is also known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 stock that has now been rederived, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control.
+
+BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues.
+
+Mouse Diversity Panel (MDP). In addition to the BXD strains, we have profiled a MDP consisting 14 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/LtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ) have been included in the MDP. Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) also carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene.
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase-negative albino (c) mutant
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list. A tyrosinase-negative albino (c) mutant
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list. Important to note for this Eye dataset, C3H/HeJ is a Pdeb6 mutant with near total photoreceptor loss at maturity.
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1, aka F1 in some graphs and tables
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J. These reciprocal F1 can be used to detect some imprinted genes.
+
diff --git a/general/datasets/Eye_m2_0406_p/notes.rtf b/general/datasets/Eye_m2_0406_p/notes.rtf
new file mode 100644
index 0000000..39475ab
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_p/notes.rtf
@@ -0,0 +1,18 @@
+This study includes the following datasets:
+
+
+ -
+
Eye M430v2 (Apr06) RMA
+
+ -
+
Eye M430v2 (Apr06) PDNN
+
+ -
+
Eye M430v2 (Apr06) MAS5
+
+ -
+
Eye M430v2 (Sep06) RMA
+
+
+
+This text file originally generated by RWW, May 26, 2006. Updated by RWW, May 27, 2006.
diff --git a/general/datasets/Eye_m2_0406_p/platform.rtf b/general/datasets/Eye_m2_0406_p/platform.rtf
new file mode 100644
index 0000000..ac743ee
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_p/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are near duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequences as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
diff --git a/general/datasets/Eye_m2_0406_p/processing.rtf b/general/datasets/Eye_m2_0406_p/processing.rtf
new file mode 100644
index 0000000..d23bc47
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_p/processing.rtf
@@ -0,0 +1,20 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. The CEL files were processed using the RMA protocol. We processed the two batches together in RMA.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 7: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
+After RMA processing all arrays were rank-order normalized. This second round of quantile normalization removes much residual non-linearity across arrays and forces every array to have the same distribution of values as the mean of all arrays. Comparative array data quality was then evaluated in DataDesk. Outlier arrays were flagged by visual inspection in DataDesk, usually by means of an analysis of scatter plots and more quantitatively by generating a correlation matrix of all arrays. Those arrays with mean correlation <0.96 versus all other arrays indicates trouble or a biological outlier). In some cases, outliers were expected, such as samples from strains with retinal degeneration (C3H/HeJ and BXD24) and samples from wild subspecies such as CAST/Ei, PWD/Ph, and PWK/Ph. However, when arrays were anomolous both within strain and across strains, they were often simply discarded. We tended to keep arrays that "conformed" to the expectation. The assumption in these cases is that anomolous data are much more likely due to experimental problem and errors than to informative biological variation. Approximately 8 arrays total were discarded in batches 1 and 2 combined.
+
+After this process, the acceptable set of arrays was renormalized using all step as above, starting with the original RMA procedure, etc.
+
+We then categorized arrays into XXX major "technical groups" depending on expression patterns as noted in scatterplots. This process of defining technical groups was done in DataDesk by manually "typing" arrays. These technical groups are apparently due to subtle within-batch effect that we do not yet understand and that cannot be corrected by quantile normalization. These XXX major technical groups are not obviously related to strain, sex, age, or any other known biological effect or variable. They are also not obviously related to any of the Affymetrix QC data types (3'/5' ratios, gain, etc.). Once the technical groups were defined, we forced the means of each probe set in the XX technical groups to the same value. This simple process partially removes a technical error of unknown origin in large expression array data sets.
+
+We reviewed the final data set using a new method developed by RW Williams, Jeremy Peirce, and Hongqiang Li. For the full set of 140 arrays that passed standard QC protocols described above, we computed the strain means for the BXD strains, B6, D2, and F1s. Using this set of strain means we then computed LRS scores for all 45101 probe sets and counted the number of transcripts that generated QTLs with LRS values greater than 50. This value (e.g. 1000) represented the QTL harvest for the full data set. We then dropped a single array from the data set (n = 139 arrays), recomputed strain means, and recomputed the number of transcripts with LRS scores great than 50. This value is expected to typically reduce the number of QTLs that reach the criterion level (e.g., 950 QTLs > 50). This process was repeated for every array to obtain an array-specific difference value--the effect of removing that array on the total QTL count. For example, the loss of a single array might cause a decrease in 50 QTLs (1000-950). Values ranged from -90 (good0 to +38 (bad). This procedure is similar in some ways to a jackknife protocol, although we are not using this procedure to esimate an error term, but rather as a final method to polish a data set. By applying this procedure we discovered that a set of XX (7?) arrays could be excluded while simultaneously improving the total number of QTLs with values above 50.
+
+During this final process we discovered that nearly XX arrays in the second batch had been mislabeled at some point in processing. We computed the correct strain membership of each array using a large number of Mendelian probe sets (more than 50) and comparing their match to standard SNP and microsatellite markers and the original array data set of November 2005. This allowed us to rescue a large number of arrays that were of very high quality.
+
diff --git a/general/datasets/Eye_m2_0406_p/summary.rtf b/general/datasets/Eye_m2_0406_p/summary.rtf
new file mode 100644
index 0000000..68a4484
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_p/summary.rtf
@@ -0,0 +1,3 @@
+
+SUPERCEDED EYE DATA SET. The HEIMED April 2006 data set provides estimates of mRNA expression in whole eyes of 71 lines of young adult mice generated using 132 Affymetrix M430 2.0 arrays. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). We used pooled RNA samples, usually two independent pools; one male, one female, for each straion. This data set was processed using the RMA protocol. To simplify comparison among different transforms, RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Eye_m2_0406_p/tissue.rtf b/general/datasets/Eye_m2_0406_p/tissue.rtf
new file mode 100644
index 0000000..d8d345f
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_p/tissue.rtf
@@ -0,0 +1,7112 @@
+
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of RNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. Samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center lead by Drs. John Stuart and Weikuan Gu. All processing steps were performed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. centrigrade until use (one third roughly) or were immediately used for hybridization.
+
+Dealing with Ocular Pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations taken from brown and beige colored mice tend to have faint residual pigmentation that affects hybridization signal. The key determinant of this interesting effect is the Tyrp1 (brown) locus on Chr 4 at about 80 Mb. Loci on Chr 4 that map at this location should be considered with skepticism and reviewed carefully. To address this problem Yan Jiao purified total RNA a second time using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204). This was done for 8 colored samples (R2534E2, R2578E2, R1441E2, R2537E2, R2536E2, R2589E2, R2539E2) in the first batch of arrays (the November 05 data set) of which 5 were finally included in this data set (cases in which the strain ID is labeled with asterisks in the table). This same protocol was used for all samples in the second batch added in April 2006.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. The first and second batches of array data, collectively represents a reasonably well balanced sample of males and females belonging to 62 strains, but without within-strain-by-sex replication. Six strains are represented only by male sample pools (BXD15, 28, 29, 55, 98, and DBA/2J. Four strains are represented only by a female pool sample (BXD1, 27, 73 and 86). Please use the probe sets 1427262_at (Xist, high in females) and probe set 1426438_at (Ddx3y, high in males) as quantitative surrogates for the sex balance in this data set.
+
+Batch Structure: This data set consists of a two batches: the original batch that makes up the November 2005 data set and a new batch of 63 arrays (R0857E through R2649E, and R2682E through R2742E, non-consecutive identifiers) run in January 2006 by Dr. Yan Jiao. The arrays in the two batches are from two different lots. All arrays in the second batch were from Lot 4016879 (expiration date 12.28.06). We started working with a total of 140 arrays that passed initial crude quality control based on RNA quality and initial Affymetrix report file information such as 3'/5' ratio, scale factor, and percent present calls. A total of 130 arrays were finally approved for inclusion in this April 2006 data set. The complex normalization procedure is described below.
+
+The table below summarizes information on strain, age, sex, original CEL filename, Affymetrix quality control values, and source of mice. Columns labeled "PDNN 2Z outlier" and "RMA 2Z outlier" list the fraction of probe sets with values that deviated more than 2 z units from the mean. Scale factor, background average, present, absent, marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+IN PROGRESS: PLEASE NOTE THAT THIS TABLE IS NOW BEING UPDATED TO INCLUDE BATCH 2 OF EARLY 2006.
+
+
+
+
+
+ | ID |
+
+ tube ID
+ |
+
+ group_type
+ |
+
+ Strain
+ |
+
+ age
+ |
+
+ Sex
+ |
+
+ original
+
+ CEL
+
+ filename
+ |
+
+ PDNN
+
+ 2Z
+
+ outlier
+ |
+
+ RMA
+
+ 2Z
+
+ outlier
+ |
+
+ scale
+
+ factor
+ |
+
+ background
+
+ average
+ |
+
+ present
+ |
+
+ absent
+ |
+
+ marginal
+ |
+
+ AFFX-b-
+
+ ActinMur(3'/5')
+ |
+
+ AFFX-
+
+ GapdhMur(3'/5')
+ |
+
+ Source
+ |
+
+
+ |
+ 1
+ |
+
+ R2533E1
+ |
+
+ GDP
+ |
+
+ 129S1/SvImJ
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2533E.CEL
+ |
+
+ 0.025
+ |
+
+ 0.028
+ |
+
+ 2.11
+ |
+
+ 94
+ |
+
+ 57.90%
+ |
+
+ 40.50%
+ |
+
+ 1.60%
+ |
+
+ 1.37
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 2
+ |
+
+ R2595E1
+ |
+
+ GDP
+ |
+
+ 129S1/SvImJ
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2595E.CEL
+ |
+
+ 0.033
+ |
+
+ 0.036
+ |
+
+ 1.79
+ |
+
+ 115
+ |
+
+ 61.00%
+ |
+
+ 37.50%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 3
+ |
+
+ R0754E2
+ |
+
+ GDP
+ |
+
+ A/J
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R0754E.CEL
+ |
+
+ 0.027
+ |
+
+ 0.03
+ |
+
+ 2.72
+ |
+
+ 86
+ |
+
+ 59.80%
+ |
+
+ 38.70%
+ |
+
+ 1.50%
+ |
+
+ 1.36
+ |
+
+ 0.76
+ |
+
+ JAX
+ |
+
+
+ |
+ 4
+ |
+
+ R2546E1
+ |
+
+ GDP
+ |
+
+ A/J
+ |
+
+ 66
+ |
+
+ F
+ |
+
+ R2545E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.029
+ |
+
+ 1.99
+ |
+
+ 96
+ |
+
+ 58.60%
+ |
+
+ 39.70%
+ |
+
+ 1.70%
+ |
+
+ 1.47
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 5
+ |
+
+ R2601E1
+ |
+
+ GDP BXD
+ |
+
+ B6D2F1
+ |
+
+ 73
+ |
+
+ F
+ |
+
+ R2601E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.008
+ |
+
+ 2.55
+ |
+
+ 92
+ |
+
+ 58.90%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.44
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 6
+ |
+
+ R2602E1
+ |
+
+ GDP BXD
+ |
+
+ B6D2F1
+ |
+
+ 73
+ |
+
+ M
+ |
+
+ R2602E.CEL
+ |
+
+ 0.003
+ |
+
+ 0.008
+ |
+
+ 2.60
+ |
+
+ 84
+ |
+
+ 59.70%
+ |
+
+ 38.80%
+ |
+
+ 1.50%
+ |
+
+ 1.37
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 7
+ |
+
+ R1672E1
+ |
+
+ GDP
+ |
+
+ BALB/cByJ
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R1672E.CEL
+ |
+
+ 0.043
+ |
+
+ 0.039
+ |
+
+ 2.22
+ |
+
+ 111
+ |
+
+ 59.90%
+ |
+
+ 38.60%
+ |
+
+ 1.50%
+ |
+
+ 1.26
+ |
+
+ 0.80
+ |
+
+ JAX
+ |
+
+
+ |
+ 8
+ |
+
+ R1676E1
+ |
+
+ GDP
+ |
+
+ BALB/cByJ
+ |
+
+ 83
+ |
+
+ F
+ |
+
+ R1676E.CEL
+ |
+
+ 0.083
+ |
+
+ 0.085
+ |
+
+ 2.69
+ |
+
+ 98
+ |
+
+ 58.90%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.74
+ |
+
+ JAX
+ |
+
+
+ |
+ 9
+ |
+
+ R2581E1
+ |
+
+ BXD
+ |
+
+ BXD11
+ |
+
+ 65
+ |
+
+ F
+ |
+
+ R2581E.CEL
+ |
+
+ 0.009
+ |
+
+ 0.021
+ |
+
+ 1.94
+ |
+
+ 89
+ |
+
+ 62.10%
+ |
+
+ 36.40%
+ |
+
+ 1.60%
+ |
+
+ 1.55
+ |
+
+ 0.81
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 10
+ |
+
+ R2543E1
+ |
+
+ BXD
+ |
+
+ BXD12
+ |
+
+ 63
+ |
+
+ M
+ |
+
+ R2543E.CEL
+ |
+
+ 0.018
+ |
+
+ 0.017
+ |
+
+ 1.61
+ |
+
+ 118
+ |
+
+ 58.60%
+ |
+
+ 39.90%
+ |
+
+ 1.60%
+ |
+
+ 1.43
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 11
+ |
+
+ R2586E1
+ |
+
+ BXD
+ |
+
+ BXD13
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2586E.CEL
+ |
+
+ 0.259
+ |
+
+ 0.258
+ |
+
+ 2.01
+ |
+
+ 74
+ |
+
+ 56.40%
+ |
+
+ 42.00%
+ |
+
+ 1.60%
+ |
+
+ 2.85
+ |
+
+ 3.81
+ |
+
+ Glenn
+ |
+
+
+ |
+ 12
+ |
+
+ R2557E1
+ |
+
+ BXD
+ |
+
+ BXD14
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2557E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.027
+ |
+
+ 1.83
+ |
+
+ 99
+ |
+
+ 62.50%
+ |
+
+ 36.10%
+ |
+
+ 1.40%
+ |
+
+ 1.31
+ |
+
+ 0.78
+ |
+
+ Glenn
+ |
+
+
+ |
+ 13
+ |
+
+ R2567E1
+ |
+
+ BXD
+ |
+
+ BXD16
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2567E.CEL
+ |
+
+ 0.048
+ |
+
+ 0.058
+ |
+
+ 2.24
+ |
+
+ 82
+ |
+
+ 56.70%
+ |
+
+ 41.60%
+ |
+
+ 1.70%
+ |
+
+ 1.37
+ |
+
+ 0.75
+ |
+
+ Glenn
+ |
+
+
+ |
+ 14
+ |
+
+ R2559E1
+ |
+
+ BXD
+ |
+
+ BXD18
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2559E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.012
+ |
+
+ 1.65
+ |
+
+ 104
+ |
+
+ 60.80%
+ |
+
+ 37.70%
+ |
+
+ 1.50%
+ |
+
+ 1.27
+ |
+
+ 0.78
+ |
+
+ Glenn
+ |
+
+
+ |
+ 15
+ |
+
+ R2560E1
+ |
+
+ BXD
+ |
+
+ BXD19
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2560E.CEL
+ |
+
+ 0.009
+ |
+
+ 0.012
+ |
+
+ 1.79
+ |
+
+ 98
+ |
+
+ 60.90%
+ |
+
+ 37.50%
+ |
+
+ 1.60%
+ |
+
+ 1.35
+ |
+
+ 0.80
+ |
+
+ Glenn
+ |
+
+
+ |
+ 16
+ |
+
+ R2597E1
+ |
+
+ BXD
+ |
+
+ BXD2
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2597E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.012
+ |
+
+ 2.37
+ |
+
+ 94
+ |
+
+ 60.30%
+ |
+
+ 38.30%
+ |
+
+ 1.50%
+ |
+
+ 1.34
+ |
+
+ 0.77
+ |
+
+ Glenn
+ |
+
+
+ |
+ 17
+ |
+
+ R2584E1
+ |
+
+ BXD
+ |
+
+ BXD20
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2584E.CEL
+ |
+
+ 0.011
+ |
+
+ 0.017
+ |
+
+ 2.07
+ |
+
+ 84
+ |
+
+ 59.30%
+ |
+
+ 39.10%
+ |
+
+ 1.60%
+ |
+
+ 1.40
+ |
+
+ 0.76
+ |
+
+ Glenn
+ |
+
+
+ |
+ 18
+ |
+
+ R2541E2
+ |
+
+ BXD
+ |
+
+ BXD21
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2541E2.CEL
+ |
+
+ 0.049
+ |
+
+ 0.084
+ |
+
+ 2.63
+ |
+
+ 125
+ |
+
+ 56.00%
+ |
+
+ 42.40%
+ |
+
+ 1.50%
+ |
+
+ 1.29
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 19
+ |
+
+ R2553E1
+ |
+
+ BXD
+ |
+
+ BXD22
+ |
+
+ 58
+ |
+
+ F
+ |
+
+ R2553E.CEL
+ |
+
+ 0.004
+ |
+
+ 0.01
+ |
+
+ 1.95
+ |
+
+ 111
+ |
+
+ 59.90%
+ |
+
+ 38.50%
+ |
+
+ 1.50%
+ |
+
+ 1.28
+ |
+
+ 0.76
+ |
+
+ Glenn
+ |
+
+
+ |
+ 20
+ |
+
+ R2558E1
+ |
+
+ BXD
+ |
+
+ BXD23
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2558E-2.CEL
+ |
+
+ 0.018
+ |
+
+ 0.027
+ |
+
+ 1.91
+ |
+
+ 115
+ |
+
+ 59.90%
+ |
+
+ 38.80%
+ |
+
+ 1.40%
+ |
+
+ 1.20
+ |
+
+ 0.82
+ |
+
+ Glenn
+ |
+
+
+ |
+ 21
+ |
+
+ R2589E2
+ |
+
+ BXD
+ |
+
+ BXD24
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2589E2.CEL
+ |
+
+ 0.132
+ |
+
+ 0.176
+ |
+
+ 2.61
+ |
+
+ 112
+ |
+
+ 57.50%
+ |
+
+ 40.90%
+ |
+
+ 1.60%
+ |
+
+ 1.24
+ |
+
+ 0.80
+ |
+
+ Glenn
+ |
+
+
+ |
+ 22
+ |
+
+ R2573E1
+ |
+
+ BXD
+ |
+
+ BXD25
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2573E-2.CEL
+ |
+
+ 0.055
+ |
+
+ 0.063
+ |
+
+ 3.15
+ |
+
+ 72
+ |
+
+ 57.90%
+ |
+
+ 40.70%
+ |
+
+ 1.40%
+ |
+
+ 1.77
+ |
+
+ 0.97
+ |
+
+ UAB
+ |
+
+
+ |
+ 23
+ |
+
+ R2562E1
+ |
+
+ BXD
+ |
+
+ BXD29
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2562E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.01
+ |
+
+ 1.65
+ |
+
+ 116
+ |
+
+ 59.90%
+ |
+
+ 38.40%
+ |
+
+ 1.70%
+ |
+
+ 1.37
+ |
+
+ 0.79
+ |
+
+ Glenn
+ |
+
+
+ |
+ 24
+ |
+
+ R2598E1
+ |
+
+ BXD
+ |
+
+ BXD31
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2598E.CEL
+ |
+
+ 0.006
+ |
+
+ 0.013
+ |
+
+ 1.99
+ |
+
+ 106
+ |
+
+ 60.90%
+ |
+
+ 37.60%
+ |
+
+ 1.50%
+ |
+
+ 1.27
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 25
+ |
+
+ R2563E1
+ |
+
+ BXD
+ |
+
+ BXD32
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2563E.CEL
+ |
+
+ 0.023
+ |
+
+ 0.025
+ |
+
+ 1.55
+ |
+
+ 102
+ |
+
+ 61.90%
+ |
+
+ 36.70%
+ |
+
+ 1.40%
+ |
+
+ 1.50
+ |
+
+ 0.80
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 26
+ |
+
+ R2542E1
+ |
+
+ BXD
+ |
+
+ BXD33
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2542E.CEL
+ |
+
+ 0.058
+ |
+
+ 0.062
+ |
+
+ 2.13
+ |
+
+ 97
+ |
+
+ 56.50%
+ |
+
+ 41.80%
+ |
+
+ 1.60%
+ |
+
+ 1.91
+ |
+
+ 0.93
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 27
+ |
+
+ R2585E1
+ |
+
+ BXD
+ |
+
+ BXD34
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2585E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.032
+ |
+
+ 2.64
+ |
+
+ 75
+ |
+
+ 58.30%
+ |
+
+ 40.00%
+ |
+
+ 1.70%
+ |
+
+ 1.25
+ |
+
+ 0.77
+ |
+
+ Glenn
+ |
+
+
+ |
+ 28
+ |
+
+ R2532E1
+ |
+
+ BXD
+ |
+
+ BXD38
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2532E.CEL
+ |
+
+ 0.002
+ |
+
+ 0.006
+ |
+
+ 2.04
+ |
+
+ 94
+ |
+
+ 59.80%
+ |
+
+ 38.70%
+ |
+
+ 1.50%
+ |
+
+ 1.37
+ |
+
+ 0.80
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 29
+ |
+
+ R2574E1
+ |
+
+ BXD
+ |
+
+ BXD39
+ |
+
+ 70
+ |
+
+ F
+ |
+
+ R2574E.CEL
+ |
+
+ 0.003
+ |
+
+ 0.008
+ |
+
+ 1.98
+ |
+
+ 91
+ |
+
+ 61.20%
+ |
+
+ 37.30%
+ |
+
+ 1.50%
+ |
+
+ 1.39
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 30
+ |
+
+ R2590E1
+ |
+
+ BXD
+ |
+
+ BXD40
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2590E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.012
+ |
+
+ 2.71
+ |
+
+ 77
+ |
+
+ 59.10%
+ |
+
+ 39.30%
+ |
+
+ 1.50%
+ |
+
+ 1.40
+ |
+
+ 0.77
+ |
+
+ Glenn
+ |
+
+
+ |
+ 31
+ |
+
+ R2596E1
+ |
+
+ BXD
+ |
+
+ BXD42
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2596E.CEL
+ |
+
+ 0.016
+ |
+
+ 0.03
+ |
+
+ 2.63
+ |
+
+ 108
+ |
+
+ 59.00%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.24
+ |
+
+ 0.80
+ |
+
+ Glenn
+ |
+
+
+ |
+ 32
+ |
+
+ R2605E1
+ |
+
+ BXD
+ |
+
+ BXD43
+ |
+
+ 79
+ |
+
+ M
+ |
+
+ R2607E.CEL
+ |
+
+ 0.006
+ |
+
+ 0.01
+ |
+
+ 1.82
+ |
+
+ 131
+ |
+
+ 60.50%
+ |
+
+ 38.20%
+ |
+
+ 1.30%
+ |
+
+ 1.32
+ |
+
+ 0.80
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 33
+ |
+
+ R2594E1
+ |
+
+ BXD
+ |
+
+ BXD44
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2594E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.024
+ |
+
+ 1.77
+ |
+
+ 117
+ |
+
+ 59.80%
+ |
+
+ 38.80%
+ |
+
+ 1.40%
+ |
+
+ 1.35
+ |
+
+ 0.85
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 34
+ |
+
+ R2592E1
+ |
+
+ BXD
+ |
+
+ BXD45
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2592E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.011
+ |
+
+ 1.85
+ |
+
+ 106
+ |
+
+ 60.10%
+ |
+
+ 38.60%
+ |
+
+ 1.30%
+ |
+
+ 1.43
+ |
+
+ 0.85
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 35
+ |
+
+ R2606E1
+ |
+
+ BXD
+ |
+
+ BXD48
+ |
+
+ 78
+ |
+
+ M
+ |
+
+ R2606E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.015
+ |
+
+ 2.56
+ |
+
+ 106
+ |
+
+ 58.90%
+ |
+
+ 39.70%
+ |
+
+ 1.40%
+ |
+
+ 1.35
+ |
+
+ 0.83
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 36
+ |
+
+ R2591E1
+ |
+
+ BXD
+ |
+
+ BXD5
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2591E.CEL
+ |
+
+ 0.052
+ |
+
+ 0.014
+ |
+
+ 1.70
+ |
+
+ 136
+ |
+
+ 58.50%
+ |
+
+ 40.00%
+ |
+
+ 1.50%
+ |
+
+ 1.33
+ |
+
+ 0.78
+ |
+
+ Glenn
+ |
+
+
+ |
+ 37
+ |
+
+ R2603E1
+ |
+
+ BXD
+ |
+
+ BXD51
+ |
+
+ 66
+ |
+
+ F
+ |
+
+ R2603E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.02
+ |
+
+ 2.49
+ |
+
+ 115
+ |
+
+ 57.70%
+ |
+
+ 40.80%
+ |
+
+ 1.50%
+ |
+
+ 1.24
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 38
+ |
+
+ R2570E1
+ |
+
+ BXD
+ |
+
+ BXD6
+ |
+
+ 65
+ |
+
+ F
+ |
+
+ R2570E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.017
+ |
+
+ 1.99
+ |
+
+ 87
+ |
+
+ 58.50%
+ |
+
+ 40.00%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.76
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 39
+ |
+
+ R2534E2
+ |
+
+ BXD
+ |
+
+ BXD61
+ |
+
+ 70
+ |
+
+ F
+ |
+
+ R2534E2.CEL
+ |
+
+ 0.03
+ |
+
+ 0.058
+ |
+
+ 2.47
+ |
+
+ 118
+ |
+
+ 57.90%
+ |
+
+ 40.60%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 40
+ |
+
+ R2611E1
+ |
+
+ BXD
+ |
+
+ BXD64
+ |
+
+ 68
+ |
+
+ M
+ |
+
+ R2611E.CEL
+ |
+
+ 0.067
+ |
+
+ 0.068
+ |
+
+ 2.29
+ |
+
+ 92
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.50%
+ |
+
+ 1.57
+ |
+
+ 1.06
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 41
+ |
+
+ R2583E1
+ |
+
+ BXD
+ |
+
+ BXD65
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2583E.CEL
+ |
+
+ 0.027
+ |
+
+ 0.03
+ |
+
+ 2.49
+ |
+
+ 70
+ |
+
+ 56.90%
+ |
+
+ 41.50%
+ |
+
+ 1.60%
+ |
+
+ 1.67
+ |
+
+ 1.01
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 42
+ |
+
+ R2536E2
+ |
+
+ BXD
+ |
+
+ BXD66
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2536E2.CEL
+ |
+
+ 0.067
+ |
+
+ 0.139
+ |
+
+ 2.74
+ |
+
+ 109
+ |
+
+ 56.10%
+ |
+
+ 42.30%
+ |
+
+ 1.70%
+ |
+
+ 1.28
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 43
+ |
+
+ R2551E1
+ |
+
+ BXD
+ |
+
+ BXD68
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2551E.CEL
+ |
+
+ 0.294
+ |
+
+ 0.291
+ |
+
+ 2.49
+ |
+
+ 92
+ |
+
+ 54.30%
+ |
+
+ 44.10%
+ |
+
+ 1.60%
+ |
+
+ 2.91
+ |
+
+ 1.55
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 44
+ |
+
+ R2593E1
+ |
+
+ BXD
+ |
+
+ BXD69
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2593E.CEL
+ |
+
+ 0.027
+ |
+
+ 0.038
+ |
+
+ 1.67
+ |
+
+ 128
+ |
+
+ 59.20%
+ |
+
+ 39.50%
+ |
+
+ 1.30%
+ |
+
+ 1.47
+ |
+
+ 0.92
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 45
+ |
+
+ R2537E2
+ |
+
+ BXD
+ |
+
+ BXD70
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2537E2.CEL
+ |
+
+ 0.049
+ |
+
+ 0.092
+ |
+
+ 2.93
+ |
+
+ 99
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.60%
+ |
+
+ 1.29
+ |
+
+ 0.75
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 46
+ |
+
+ R2565E1
+ |
+
+ BXD
+ |
+
+ BXD75
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R2565E.CEL
+ |
+
+ 0.118
+ |
+
+ 0.124
+ |
+
+ 1.79
+ |
+
+ 102
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.50%
+ |
+
+ 2.31
+ |
+
+ 3.47
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 47
+ |
+
+ R2538E1
+ |
+
+ BXD
+ |
+
+ BXD8
+ |
+
+ 77
+ |
+
+ F
+ |
+
+ R2538E.CEL
+ |
+
+ 0.033
+ |
+
+ 0.056
+ |
+
+ 1.91
+ |
+
+ 102
+ |
+
+ 61.20%
+ |
+
+ 37.30%
+ |
+
+ 1.50%
+ |
+
+ 1.52
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 48
+ |
+
+ R2579E1
+ |
+
+ BXD
+ |
+
+ BXD80
+ |
+
+ 65
+ |
+
+ F
+ |
+
+ R2579E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.026
+ |
+
+ 2.42
+ |
+
+ 72
+ |
+
+ 59.20%
+ |
+
+ 39.40%
+ |
+
+ 1.50%
+ |
+
+ 1.73
+ |
+
+ 0.82
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 49
+ |
+
+ R2540E1
+ |
+
+ BXD
+ |
+
+ BXD87
+ |
+
+ 63
+ |
+
+ M
+ |
+
+ R2540E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.034
+ |
+
+ 2.33
+ |
+
+ 93
+ |
+
+ 61.10%
+ |
+
+ 37.40%
+ |
+
+ 1.40%
+ |
+
+ 1.22
+ |
+
+ 0.81
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 50
+ |
+
+ R2545E1
+ |
+
+ BXD
+ |
+
+ BXD89
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2546E.CEL
+ |
+
+ 0.266
+ |
+
+ 0.257
+ |
+
+ 1.67
+ |
+
+ 105
+ |
+
+ 56.20%
+ |
+
+ 42.30%
+ |
+
+ 1.50%
+ |
+
+ 3.60
+ |
+
+ 9.84
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 51
+ |
+
+ R2569E1
+ |
+
+ BXD
+ |
+
+ BXD9
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2569E.CEL
+ |
+
+ 0.256
+ |
+
+ 0.239
+ |
+
+ 1.75
+ |
+
+ 87
+ |
+
+ 55.10%
+ |
+
+ 43.40%
+ |
+
+ 1.50%
+ |
+
+ 2.82
+ |
+
+ 3.14
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 52
+ |
+
+ R2578E2
+ |
+
+ BXD
+ |
+
+ BXD90
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R2578E2.CEL
+ |
+
+ 0.041
+ |
+
+ 0.062
+ |
+
+ 2.79
+ |
+
+ 92
+ |
+
+ 58.60%
+ |
+
+ 39.80%
+ |
+
+ 1.60%
+ |
+
+ 1.52
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 53
+ |
+
+ R2554E1
+ |
+
+ BXD
+ |
+
+ BXD96
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2554E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.008
+ |
+
+ 2.18
+ |
+
+ 93
+ |
+
+ 60.20%
+ |
+
+ 38.30%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 54
+ |
+
+ R2577E1
+ |
+
+ BXD
+ |
+
+ BXD97
+ |
+
+ 55
+ |
+
+ M
+ |
+
+ R2577E.CEL
+ |
+
+ 0.065
+ |
+
+ 0.069
+ |
+
+ 2.07
+ |
+
+ 77
+ |
+
+ 59.50%
+ |
+
+ 39.10%
+ |
+
+ 1.40%
+ |
+
+ 1.87
+ |
+
+ 1.29
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 55
+ |
+
+ R1700E1
+ |
+
+ GDP
+ |
+
+ C3H/HeJ
+ |
+
+ 83
+ |
+
+ F
+ |
+
+ R1700E.CEL
+ |
+
+ 0.152
+ |
+
+ 0.168
+ |
+
+ 2.98
+ |
+
+ 69
+ |
+
+ 60.80%
+ |
+
+ 37.90%
+ |
+
+ 1.40%
+ |
+
+ 1.48
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 56
+ |
+
+ R1704E1
+ |
+
+ GDP
+ |
+
+ C3H/HeJ
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R1704E.CEL
+ |
+
+ 0.154
+ |
+
+ 0.165
+ |
+
+ 2.58
+ |
+
+ 88
+ |
+
+ 60.10%
+ |
+
+ 38.60%
+ |
+
+ 1.30%
+ |
+
+ 1.38
+ |
+
+ 0.84
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 57
+ |
+
+ R0872E2
+ |
+
+ GDP BXD
+ |
+
+ C57BL/6J
+ |
+
+ 66
+ |
+
+ M
+ |
+
+ R0872E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.023
+ |
+
+ 3.13
+ |
+
+ 89
+ |
+
+ 58.90%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.30
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 58
+ |
+
+ R2607E1
+ |
+
+ GDP BXD
+ |
+
+ C57BL/6J
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2605E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.018
+ |
+
+ 2.43
+ |
+
+ 115
+ |
+
+ 58.60%
+ |
+
+ 40.00%
+ |
+
+ 1.40%
+ |
+
+ 1.31
+ |
+
+ 0.76
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 59
+ |
+
+ R2564E1
+ |
+
+ GDP
+ |
+
+ CAST/Ei
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2564E.CEL
+ |
+
+ 0.124
+ |
+
+ 0.105
+ |
+
+ 1.94
+ |
+
+ 89
+ |
+
+ 58.50%
+ |
+
+ 39.90%
+ |
+
+ 1.60%
+ |
+
+ 1.60
+ |
+
+ 0.77
+ |
+
+ JAX
+ |
+
+
+ |
+ 60
+ |
+
+ R2580E1
+ |
+
+ GDP
+ |
+
+ CAST/Ei
+ |
+
+ 64
+ |
+
+ M
+ |
+
+ R2580E.CEL
+ |
+
+ 0.123
+ |
+
+ 0.109
+ |
+
+ 2.09
+ |
+
+ 95
+ |
+
+ 58.20%
+ |
+
+ 40.10%
+ |
+
+ 1.70%
+ |
+
+ 1.40
+ |
+
+ 0.76
+ |
+
+ JAX
+ |
+
+
+ |
+ 61
+ |
+
+ R2600E1
+ |
+
+ GDP BXD
+ |
+
+ D2B6F1
+ |
+
+ 72
+ |
+
+ F
+ |
+
+ R2600E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.02
+ |
+
+ 2.47
+ |
+
+ 95
+ |
+
+ 58.10%
+ |
+
+ 40.20%
+ |
+
+ 1.70%
+ |
+
+ 1.41
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 62
+ |
+
+ R2604E1
+ |
+
+ GDP BXD
+ |
+
+ D2B6F1
+ |
+
+ 69
+ |
+
+ M
+ |
+
+ R2604E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.014
+ |
+
+ 2.66
+ |
+
+ 90
+ |
+
+ 59.40%
+ |
+
+ 39.20%
+ |
+
+ 1.50%
+ |
+
+ 1.28
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 63
+ |
+
+ R2572E1
+ |
+
+ GDP BXD
+ |
+
+ DBA/2J
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R2572E.CEL
+ |
+
+ 0.091
+ |
+
+ 0.106
+ |
+
+ 2.41
+ |
+
+ 79
+ |
+
+ 55.50%
+ |
+
+ 42.90%
+ |
+
+ 1.60%
+ |
+
+ 1.37
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 64
+ |
+
+ R2636E1
+ |
+
+ GDP
+ |
+
+ KK/HIJ
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2636E.CEL
+ |
+
+ 0.044
+ |
+
+ 0.043
+ |
+
+ 2.61
+ |
+
+ 93
+ |
+
+ 58.90%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.39
+ |
+
+ 0.76
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 65
+ |
+
+ R2637E1
+ |
+
+ GDP
+ |
+
+ KK/HIJ
+ |
+
+ 64
+ |
+
+ M
+ |
+
+ R2637E.CEL
+ |
+
+ 0.056
+ |
+
+ 0.036
+ |
+
+ 2.19
+ |
+
+ 103
+ |
+
+ 59.40%
+ |
+
+ 39.00%
+ |
+
+ 1.50%
+ |
+
+ 1.30
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 66
+ |
+
+ R0999E1
+ |
+
+ GDP
+ |
+
+ LG/J
+ |
+
+ 57
+ |
+
+ F
+ |
+
+ R0999E.CEL
+ |
+
+ 0.021
+ |
+
+ 0.023
+ |
+
+ 2.45
+ |
+
+ 82
+ |
+
+ 59.40%
+ |
+
+ 39.10%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 67
+ |
+
+ R1004E1
+ |
+
+ GDP
+ |
+
+ LG/J
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R1004E.CEL
+ |
+
+ 0.025
+ |
+
+ 0.028
+ |
+
+ 2.44
+ |
+
+ 92
+ |
+
+ 58.70%
+ |
+
+ 39.80%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 68
+ |
+
+ R1688E1
+ |
+
+ GDP
+ |
+
+ NOD/LtJ
+ |
+
+ 66
+ |
+
+ F
+ |
+
+ R1688E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.033
+ |
+
+ 2.66
+ |
+
+ 98
+ |
+
+ 58.60%
+ |
+
+ 39.90%
+ |
+
+ 1.50%
+ |
+
+ 1.26
+ |
+
+ 0.80
+ |
+
+ JAX
+ |
+
+
+ |
+ 69
+ |
+
+ R2566E1
+ |
+
+ GDP
+ |
+
+ NOD/LtJ
+ |
+
+ 76
+ |
+
+ M
+ |
+
+ R2566E-2.CEL
+ |
+
+ 0.036
+ |
+
+ 0.04
+ |
+
+ 3.03
+ |
+
+ 69
+ |
+
+ 59.80%
+ |
+
+ 38.80%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.75
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 70
+ |
+
+ R2535E1
+ |
+
+ GDP
+ |
+
+ NZO/H1LtJ
+ |
+
+ 62
+ |
+
+ F
+ |
+
+ R2535E.CEL
+ |
+
+ 0.037
+ |
+
+ 0.062
+ |
+
+ 1.89
+ |
+
+ 86
+ |
+
+ 60.40%
+ |
+
+ 38.20%
+ |
+
+ 1.40%
+ |
+
+ 1.41
+ |
+
+ 0.85
+ |
+
+ JAX
+ |
+
+
+ |
+ 71
+ |
+
+ R2550E1
+ |
+
+ GDP
+ |
+
+ NZO/HILtJ
+ |
+
+ 96
+ |
+
+ M
+ |
+
+ R2550E.CEL
+ |
+
+ 0.025
+ |
+
+ 0.029
+ |
+
+ 1.79
+ |
+
+ 87
+ |
+
+ 60.70%
+ |
+
+ 37.80%
+ |
+
+ 1.50%
+ |
+
+ 1.52
+ |
+
+ 0.82
+ |
+
+ JAX
+ |
+
+
+ |
+ 72
+ |
+
+ R2634E1
+ |
+
+ GDP
+ |
+
+ PWD/PhJ
+ |
+
+ 62
+ |
+
+ F
+ |
+
+ R2635E.CEL
+ |
+
+ 0.126
+ |
+
+ 0.114
+ |
+
+ 3.29
+ |
+
+ 90
+ |
+
+ 55.90%
+ |
+
+ 42.50%
+ |
+
+ 1.60%
+ |
+
+ 1.57
+ |
+
+ 0.81
+ |
+
+ JAX
+ |
+
+
+ |
+ 73
+ |
+
+ R2635E1
+ |
+
+ GDP
+ |
+
+ PWD/PhJ
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2634E.CEL
+ |
+
+ 0.15
+ |
+
+ 0.137
+ |
+
+ 3.72
+ |
+
+ 80
+ |
+
+ 54.20%
+ |
+
+ 44.10%
+ |
+
+ 1.70%
+ |
+
+ 1.53
+ |
+
+ 0.85
+ |
+
+ JAX
+ |
+
+
+ |
+ 74
+ |
+
+ R2544E1
+ |
+
+ GDP
+ |
+
+ PWK/PhJ
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2544E.CEL
+ |
+
+ 0.174
+ |
+
+ 0.175
+ |
+
+ 2.20
+ |
+
+ 108
+ |
+
+ 54.90%
+ |
+
+ 43.50%
+ |
+
+ 1.70%
+ |
+
+ 1.36
+ |
+
+ 0.82
+ |
+
+ JAX
+ |
+
+
+ |
+ 75
+ |
+
+ R2549E1
+ |
+
+ GDP
+ |
+
+ PWK/PhJ
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R2549E.CEL
+ |
+
+ 0.103
+ |
+
+ 0.087
+ |
+
+ 2.28
+ |
+
+ 84
+ |
+
+ 57.30%
+ |
+
+ 41.20%
+ |
+
+ 1.50%
+ |
+
+ 1.57
+ |
+
+ 0.83
+ |
+
+ JAX
+ |
+
+
+ |
+ 76
+ |
+
+ R2368E1
+ |
+
+ GDP
+ |
+
+ WSB/EI
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2368E.CEL
+ |
+
+ 0.041
+ |
+
+ 0.047
+ |
+
+ 2.57
+ |
+
+ 86
+ |
+
+ 59.50%
+ |
+
+ 39.10%
+ |
+
+ 1.40%
+ |
+
+ 1.29
+ |
+
+ 0.74
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 77
+ |
+
+ R2704E
+ |
+
+ BXD
+ |
+
+ BXD1
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2704E.CEL
+ |
+
+ 0.029
+ |
+
+ 0.03
+ |
+
+ 2.066
+ |
+
+ 139.61
+ |
+
+ 56.60%
+ |
+
+ 41.90%
+ |
+
+ 1.50%
+ |
+
+ 1.31
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 78
+ |
+
+ R2612E
+ |
+
+ BXD
+ |
+
+ BXD11
+ |
+
+ 70
+ |
+
+ M
+ |
+
+ R2612E.CEL
+ |
+
+ 0.101
+ |
+
+ 0.112
+ |
+
+ 1.83
+ |
+
+ 142.03
+ |
+
+ 58.20%
+ |
+
+ 40.50%
+ |
+
+ 1.40%
+ |
+
+ 1.78
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 79
+ |
+
+ R2742E
+ |
+
+ BXD
+ |
+
+ BXD12
+ |
+
+ 71
+ |
+
+ F
+ |
+
+ R2742E.CEL
+ |
+
+ 0.073
+ |
+
+ 0.077
+ |
+
+ 2.127
+ |
+
+ 134.14
+ |
+
+ 57.00%
+ |
+
+ 41.60%
+ |
+
+ 1.40%
+ |
+
+ 1.64
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 80
+ |
+
+ R1086E
+ |
+
+ BXD
+ |
+
+ BXD23
+ |
+
+ 55
+ |
+
+ M
+ |
+
+ R1086E.CEL
+ |
+
+ 0.043
+ |
+
+ 0.034
+ |
+
+ 2.233
+ |
+
+ 125.05
+ |
+
+ 58.60%
+ |
+
+ 39.90%
+ |
+
+ 1.50%
+ |
+
+ 1.43
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 81
+ |
+
+ R2716E
+ |
+
+ BXD
+ |
+
+ BXD15
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2716E.CEL
+ |
+
+ 0.035
+ |
+
+ 0.037
+ |
+
+ 2.015
+ |
+
+ 150.83
+ |
+
+ 56.40%
+ |
+
+ 42.10%
+ |
+
+ 1.60%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 82
+ |
+
+ R2711E
+ |
+
+ BXD
+ |
+
+ BXD16
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R2711E.CEL
+ |
+
+ 0.032
+ |
+
+ 0.021
+ |
+
+ 1.953
+ |
+
+ 118.53
+ |
+
+ 59.00%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.45
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 83
+ |
+
+ R2720E
+ |
+
+ BXD
+ |
+
+ BXD18
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2720E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.019
+ |
+
+ 2.32
+ |
+
+ 99.93
+ |
+
+ 59.50%
+ |
+
+ 39.00%
+ |
+
+ 1.50%
+ |
+
+ 1.33
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 84
+ |
+
+ R2713E
+ |
+
+ BXD
+ |
+
+ BXD19
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2713E.CEL
+ |
+
+ 0.055
+ |
+
+ 0.021
+ |
+
+ 1.67
+ |
+
+ 120.82
+ |
+
+ 60.20%
+ |
+
+ 38.30%
+ |
+
+ 1.50%
+ |
+
+ 1.45
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 85
+ |
+
+ R1231E
+ |
+
+ BXD
+ |
+
+ BXD2
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R1231E.CEL
+ |
+
+ 0.044
+ |
+
+ 0.037
+ |
+
+ 2.197
+ |
+
+ 138.73
+ |
+
+ 57.30%
+ |
+
+ 41.30%
+ |
+
+ 1.40%
+ |
+
+ 1.41
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 86
+ |
+
+ R2731E
+ |
+
+ BXD
+ |
+
+ BXD20
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2731E.CEL
+ |
+
+ 0.017
+ |
+
+ 0.019
+ |
+
+ 1.825
+ |
+
+ 147
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.4
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 87
+ |
+
+ R2702E
+ |
+
+ BXD
+ |
+
+ BXD21
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2702E.CEL
+ |
+
+ 0.009
+ |
+
+ 0.008
+ |
+
+ 1.811
+ |
+
+ 128.65
+ |
+
+ 59.40%
+ |
+
+ 39.10%
+ |
+
+ 1.40%
+ |
+
+ 1.26
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 88
+ |
+
+ R2700E
+ |
+
+ BXD
+ |
+
+ BXD22
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2700E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.015
+ |
+
+ 1.858
+ |
+
+ 102.96
+ |
+
+ 61.50%
+ |
+
+ 37.10%
+ |
+
+ 1.30%
+ |
+
+ 1.48
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 89
+ |
+
+ R1128E
+ |
+
+ BXD
+ |
+
+ BXD14
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R1128E.CEL
+ |
+
+ 0.037
+ |
+
+ 0.038
+ |
+
+ 2.366
+ |
+
+ 118.39
+ |
+
+ 57.30%
+ |
+
+ 41.30%
+ |
+
+ 1.40%
+ |
+
+ 1.45
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 90
+ |
+
+ R2719E
+ |
+
+ BXD
+ |
+
+ BXD24
+ |
+
+ 123
+ |
+
+ F
+ |
+
+ R2719E.CEL
+ |
+
+ 0.112
+ |
+
+ 0.111
+ |
+
+ 1.47
+ |
+
+ 140.38
+ |
+
+ 61.50%
+ |
+
+ 37.20%
+ |
+
+ 1.30%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 91
+ |
+
+ R2683E
+ |
+
+ BXD
+ |
+
+ BXD25
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R2683E.CEL
+ |
+
+ 0.068
+ |
+
+ 0.068
+ |
+
+ 1.777
+ |
+
+ 115.64
+ |
+
+ 58.30%
+ |
+
+ 40.30%
+ |
+
+ 1.40%
+ |
+
+ 2.01
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 92
+ |
+
+ R2703E
+ |
+
+ BXD
+ |
+
+ BXD27
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2703E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.012
+ |
+
+ 1.263
+ |
+
+ 134.78
+ |
+
+ 62.60%
+ |
+
+ 36.10%
+ |
+
+ 1.40%
+ |
+
+ 1.44
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 93
+ |
+
+ R2721E
+ |
+
+ BXD
+ |
+
+ BXD28
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2721E.CEL
+ |
+
+ 0.04
+ |
+
+ 0.048
+ |
+
+ 2.065
+ |
+
+ 157.39
+ |
+
+ 56.10%
+ |
+
+ 42.40%
+ |
+
+ 1.50%
+ |
+
+ 1.31
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 94
+ |
+
+ R1258E
+ |
+
+ BXD
+ |
+
+ BXD31
+ |
+
+ 57
+ |
+
+ F
+ |
+
+ R1258E.CEL
+ |
+
+ 0.037
+ |
+
+ 0.036
+ |
+
+ 2.063
+ |
+
+ 117.09
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.54
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 95
+ |
+
+ R1216E
+ |
+
+ BXD
+ |
+
+ BXD32
+ |
+
+ 76
+ |
+
+ M
+ |
+
+ R1216E.CEL
+ |
+
+ 0.05
+ |
+
+ 0.049
+ |
+
+ 2.23
+ |
+
+ 111.99
+ |
+
+ 58.80%
+ |
+
+ 39.80%
+ |
+
+ 1.40%
+ |
+
+ 1.35
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 96
+ |
+
+ R857E
+ |
+
+ BXD
+ |
+
+ BXD33
+ |
+
+ 77
+ |
+
+ M
+ |
+
+ R857E.CEL
+ |
+
+ 0.078
+ |
+
+ 0.108
+ |
+
+ 1.737
+ |
+
+ 113.98
+ |
+
+ 61.90%
+ |
+
+ 36.70%
+ |
+
+ 1.30%
+ |
+
+ 1.6
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 97
+ |
+
+ R859E
+ |
+
+ BXD
+ |
+
+ BXD90
+ |
+
+ 72
+ |
+
+ M
+ |
+
+ R859E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.02
+ |
+
+ 1.847
+ |
+
+ 152.22
+ |
+
+ 57.90%
+ |
+
+ 40.70%
+ |
+
+ 1.40%
+ |
+
+ 1.36
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 98
+ |
+
+ R1207E
+ |
+
+ BXD
+ |
+
+ BXD66
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R1207E.CEL
+ |
+
+ 0.017
+ |
+
+ 0.012
+ |
+
+ 1.681
+ |
+
+ 136.86
+ |
+
+ 60.40%
+ |
+
+ 38.10%
+ |
+
+ 1.50%
+ |
+
+ 1.45
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 99
+ |
+
+ R2710E
+ |
+
+ BXD
+ |
+
+ BXD38
+ |
+
+ 55
+ |
+
+ F
+ |
+
+ R2710E.CEL
+ |
+
+ 0.033
+ |
+
+ 0.031
+ |
+
+ 2.112
+ |
+
+ 122.1
+ |
+
+ 58.80%
+ |
+
+ 39.80%
+ |
+
+ 1.40%
+ |
+
+ 1.37
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 100
+ |
+
+ R2695E
+ |
+
+ BXD
+ |
+
+ BXD39
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2695E.CEL
+ |
+
+ 0.018
+ |
+
+ 0.016
+ |
+
+ 1.638
+ |
+
+ 122.7
+ |
+
+ 60.80%
+ |
+
+ 37.80%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 101
+ |
+
+ R2699E
+ |
+
+ BXD
+ |
+
+ BXD40
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2699E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.015
+ |
+
+ 1.827
+ |
+
+ 105.23
+ |
+
+ 61.70%
+ |
+
+ 36.90%
+ |
+
+ 1.40%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 102
+ |
+
+ R2696E
+ |
+
+ BXD
+ |
+
+ BXD42
+ |
+
+ 58
+ |
+
+ F
+ |
+
+ R2696E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.017
+ |
+
+ 1.622
+ |
+
+ 118.95
+ |
+
+ 62.00%
+ |
+
+ 36.60%
+ |
+
+ 1.50%
+ |
+
+ 1.53
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 103
+ |
+
+ R943E-2
+ |
+
+ BXD
+ |
+
+ BXD64
+ |
+
+ 56
+ |
+
+ F
+ |
+
+ R943E-2.CEL
+ |
+
+ 0.024
+ |
+
+ 0.021
+ |
+
+ 1.591
+ |
+
+ 141.34
+ |
+
+ 60.10%
+ |
+
+ 38.40%
+ |
+
+ 1.50%
+ |
+
+ 1.32
+ |
+
+ 0.76
+ |
+
+ GU
+ |
+
+
+ |
+ 104
+ |
+
+ R967E
+ |
+
+ BXD
+ |
+
+ BXD48
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R967E.CEL
+ |
+
+ 0.101
+ |
+
+ 0.052
+ |
+
+ 1.948
+ |
+
+ 130.95
+ |
+
+ 57.30%
+ |
+
+ 41.20%
+ |
+
+ 1.50%
+ |
+
+ 1.63
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 105
+ |
+
+ R2714E
+ |
+
+ BXD
+ |
+
+ BXD5
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R2714E.CEL
+ |
+
+ 0.047
+ |
+
+ 0.014
+ |
+
+ 1.404
+ |
+
+ 144.35
+ |
+
+ 60.60%
+ |
+
+ 37.90%
+ |
+
+ 1.50%
+ |
+
+ 1.43
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 106
+ |
+
+ R1042E
+ |
+
+ BXD
+ |
+
+ BXD51
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R1042E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.027
+ |
+
+ 2.352
+ |
+
+ 104.12
+ |
+
+ 58.70%
+ |
+
+ 39.90%
+ |
+
+ 1.40%
+ |
+
+ 1.53
+ |
+
+ 0.82
+ |
+
+ GU
+ |
+
+
+ |
+ 107
+ |
+
+ R2690E
+ |
+
+ BXD
+ |
+
+ BXD55
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R2690E.CEL
+ |
+
+ 0.081
+ |
+
+ 0.067
+ |
+
+ 1.887
+ |
+
+ 164.01
+ |
+
+ 56.10%
+ |
+
+ 42.30%
+ |
+
+ 1.60%
+ |
+
+ 1.43
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 108
+ |
+
+ R2694E
+ |
+
+ BXD
+ |
+
+ BXD6
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R2694E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.018
+ |
+
+ 1.983
+ |
+
+ 97.23
+ |
+
+ 61.60%
+ |
+
+ 37.10%
+ |
+
+ 1.30%
+ |
+
+ 1.39
+ |
+
+ 0.82
+ |
+
+ GU
+ |
+
+
+ |
+ 109
+ |
+
+ R975E
+ |
+
+ BXD
+ |
+
+ BXD70
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R975E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.024
+ |
+
+ 1.841
+ |
+
+ 137.97
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.40%
+ |
+
+ 1.36
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 110
+ |
+
+ R2684E
+ |
+
+ BXD
+ |
+
+ BXD61
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2684E.CEL
+ |
+
+ 0.031
+ |
+
+ 0.032
+ |
+
+ 2.01
+ |
+
+ 131.03
+ |
+
+ 57.00%
+ |
+
+ 41.50%
+ |
+
+ 1.50%
+ |
+
+ 1.34
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 111
+ |
+
+ R994E
+ |
+
+ BXD
+ |
+
+ BXD43
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R994E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.014
+ |
+
+ 1.966
+ |
+
+ 113.12
+ |
+
+ 60.80%
+ |
+
+ 37.80%
+ |
+
+ 1.40%
+ |
+
+ 1.66
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 112
+ |
+
+ R2610E
+ |
+
+ BXD
+ |
+
+ BXD44
+ |
+
+ 68
+ |
+
+ M
+ |
+
+ R2610E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.009
+ |
+
+ 1.814
+ |
+
+ 142.91
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.35
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 113
+ |
+
+ R2689E
+ |
+
+ BXD
+ |
+
+ BXD65
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2689E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.008
+ |
+
+ 1.721
+ |
+
+ 142.44
+ |
+
+ 59.90%
+ |
+
+ 38.60%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.76
+ |
+
+ GU
+ |
+
+
+ |
+ 114
+ |
+
+ R2727E
+ |
+
+ BXD
+ |
+
+ BXD69
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R2727E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.008
+ |
+
+ 1.578
+ |
+
+ 143.86
+ |
+
+ 60.30%
+ |
+
+ 38.30%
+ |
+
+ 1.40%
+ |
+
+ 1.34
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 115
+ |
+
+ R2726E
+ |
+
+ BXD
+ |
+
+ BXD68
+ |
+
+ 64
+ |
+
+ M
+ |
+
+ R2726E.CEL
+ |
+
+ 0.125
+ |
+
+ 0.025
+ |
+
+ 1.811
+ |
+
+ 153.09
+ |
+
+ 58.70%
+ |
+
+ 39.80%
+ |
+
+ 1.50%
+ |
+
+ 1.39
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 116
+ |
+
+ R2732E
+ |
+
+ BXD
+ |
+
+ BXD45
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2732E.CEL
+ |
+
+ 0.039
+ |
+
+ 0.036
+ |
+
+ 2.154
+ |
+
+ 122.45
+ |
+
+ 56.50%
+ |
+
+ 42.10%
+ |
+
+ 1.40%
+ |
+
+ 1.8
+ |
+
+ 0.83
+ |
+
+ GU
+ |
+
+
+ |
+ 117
+ |
+
+ R2709E
+ |
+
+ BXD
+ |
+
+ BXD8
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2709E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.011
+ |
+
+ 1.99
+ |
+
+ 99.79
+ |
+
+ 60.90%
+ |
+
+ 37.60%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.76
+ |
+
+ GU
+ |
+
+
+ |
+ 118
+ |
+
+ R2686E
+ |
+
+ BXD
+ |
+
+ BXD80
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2686E.CEL
+ |
+
+ 0.046
+ |
+
+ 0.05
+ |
+
+ 2.342
+ |
+
+ 119.63
+ |
+
+ 56.00%
+ |
+
+ 42.60%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 119
+ |
+
+ R2692E
+ |
+
+ BXD
+ |
+
+ BXD85
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2692E.CEL
+ |
+
+ 0.006
+ |
+
+ 0.007
+ |
+
+ 1.423
+ |
+
+ 160.87
+ |
+
+ 60.20%
+ |
+
+ 38.30%
+ |
+
+ 1.40%
+ |
+
+ 1.46
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 120
+ |
+
+ R2715E
+ |
+
+ BXD
+ |
+
+ BXD85
+ |
+
+ 91
+ |
+
+ M
+ |
+
+ R2715E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.008
+ |
+
+ 1.488
+ |
+
+ 142.6
+ |
+
+ 61.20%
+ |
+
+ 37.30%
+ |
+
+ 1.40%
+ |
+
+ 1.5
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 121
+ |
+
+ R1405E
+ |
+
+ BXD
+ |
+
+ BXD86
+ |
+
+ 58
+ |
+
+ F
+ |
+
+ R1405E.CEL
+ |
+
+ 0.053
+ |
+
+ 0.052
+ |
+
+ 2.351
+ |
+
+ 119.34
+ |
+
+ 56.40%
+ |
+
+ 42.20%
+ |
+
+ 1.40%
+ |
+
+ 1.64
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 122
+ |
+
+ R2724E
+ |
+
+ BXD
+ |
+
+ BXD87
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2724E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.019
+ |
+
+ 1.906
+ |
+
+ 113.71
+ |
+
+ 60.70%
+ |
+
+ 37.90%
+ |
+
+ 1.40%
+ |
+
+ 1.45
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 123
+ |
+
+ R1451E
+ |
+
+ BXD
+ |
+
+ BXD34
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R1451E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.009
+ |
+
+ 1.843
+ |
+
+ 140.05
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 124
+ |
+
+ R1433E
+ |
+
+ BXD
+ |
+
+ BXD89
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R1433E.CEL
+ |
+
+ 0.029
+ |
+
+ 0.026
+ |
+
+ 2.241
+ |
+
+ 115.86
+ |
+
+ 57.70%
+ |
+
+ 40.80%
+ |
+
+ 1.50%
+ |
+
+ 1.41
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 125
+ |
+
+ R2733E
+ |
+
+ BXD
+ |
+
+ BXD96
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2733E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.054
+ |
+
+ 1.7
+ |
+
+ 113.99
+ |
+
+ 62.10%
+ |
+
+ 36.60%
+ |
+
+ 1.30%
+ |
+
+ 1.4
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 126
+ |
+
+ R2649E
+ |
+
+ BXD
+ |
+
+ BXD97
+ |
+
+ 74
+ |
+
+ F
+ |
+
+ R2649E.CEL
+ |
+
+ 0.029
+ |
+
+ 0.032
+ |
+
+ 2.343
+ |
+
+ 119.04
+ |
+
+ 57.50%
+ |
+
+ 41.20%
+ |
+
+ 1.40%
+ |
+
+ 1.53
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 127
+ |
+
+ R2688E
+ |
+
+ BXD
+ |
+
+ BXD98
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2688E.CEL
+ |
+
+ 0.032
+ |
+
+ 0.03
+ |
+
+ 1.772
+ |
+
+ 145.24
+ |
+
+ 58.50%
+ |
+
+ 40.00%
+ |
+
+ 1.50%
+ |
+
+ 1.48
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 128
+ |
+
+ R877E
+ |
+
+ BXD
+ |
+
+ BXD13
+ |
+
+ 76
+ |
+
+ M
+ |
+
+ R877E.CEL
+ |
+
+ 0.026
+ |
+
+ 0.067
+ |
+
+ 1.558
+ |
+
+ 125.63
+ |
+
+ 61.20%
+ |
+
+ 37.50%
+ |
+
+ 1.20%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 129
+ |
+
+ R1397E-re
+ |
+
+ BXD
+ |
+
+ BXD75
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R1397E-re.CEL
+ |
+
+ 0.032
+ |
+
+ 0.01
+ |
+
+ 1.449
+ |
+
+ 189.71
+ |
+
+ 59.60%
+ |
+
+ 39.00%
+ |
+
+ 1.40%
+ |
+
+ 1.39
+ |
+
+ 0.82
+ |
+
+ GU
+ |
+
+
+ |
+ 130
+ |
+
+ R2779E
+ |
+
+ BXD
+ |
+
+ BXD73
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2779E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.038
+ |
+
+ 1.746
+ |
+
+ 121.11
+ |
+
+ 59.60%
+ |
+
+ 39.00%
+ |
+
+ 1.40%
+ |
+
+ 1.5
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 131
+ |
+
+ R2708E
+ |
+
+ BXD
+ |
+
+ BXD9
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2708E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.045
+ |
+
+ 1.966
+ |
+
+ 126.46
+ |
+
+ 57.70%
+ |
+
+ 40.70%
+ |
+
+ 1.50%
+ |
+
+ 1.4
+ |
+
+ 0.84
+ |
+
+ GU
+ |
+
+
+ |
+ 132
+ |
+
+ R2547E1
+ |
+
+ GDP
+ |
+
+ WSB/Ei
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2547E.CEL
+ |
+
+ 0.041
+ |
+
+ 0.039
+ |
+
+ 2.14
+ |
+
+ 90
+ |
+
+ 58.20%
+ |
+
+ 40.10%
+ |
+
+ 1.60%
+ |
+
+ 1.32
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0406_r/acknowledgment.rtf b/general/datasets/Eye_m2_0406_r/acknowledgment.rtf
new file mode 100644
index 0000000..3f040d2
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant. All arrays were processed at the VA Medical Center, Memphis by Weikuan Gu.
diff --git a/general/datasets/Eye_m2_0406_r/cases.rtf b/general/datasets/Eye_m2_0406_r/cases.rtf
new file mode 100644
index 0000000..5cb5539
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_r/cases.rtf
@@ -0,0 +1,50 @@
+We used a set of 55 BXD recombinant inbred strains, 14 conventional inbred strains including C57BL/6J (B6) and DBA/2J (D2), and their reciprocal F1s. BXD strains were generated by crossing C57BL/6J with DBA/2J. The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage of D2). Physical maps in WebQTL incorporate approximately 2 million B6 vs D2 SNPs from Celera Genomics and from the Perlegen-NIEHS sequencing effort. BXD1 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+Please note that BXD24/TyJ (JAX stock number 000031) used in this study is also known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 stock that has now been rederived, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control.
+
+BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues.
+
+Mouse Diversity Panel (MDP). In addition to the BXD strains, we have profiled a MDP consisting 14 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/LtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ) have been included in the MDP. Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) also carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene.
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase-negative albino (c) mutant
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list. A tyrosinase-negative albino (c) mutant
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list. Important to note for this Eye dataset, C3H/HeJ is a Pdeb6 mutant with near total photoreceptor loss at maturity.
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1, aka F1 in some graphs and tables
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J. These reciprocal F1 can be used to detect some imprinted genes.
+
diff --git a/general/datasets/Eye_m2_0406_r/notes.rtf b/general/datasets/Eye_m2_0406_r/notes.rtf
new file mode 100644
index 0000000..39475ab
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_r/notes.rtf
@@ -0,0 +1,18 @@
+This study includes the following datasets:
+
+
+ -
+
Eye M430v2 (Apr06) RMA
+
+ -
+
Eye M430v2 (Apr06) PDNN
+
+ -
+
Eye M430v2 (Apr06) MAS5
+
+ -
+
Eye M430v2 (Sep06) RMA
+
+
+
+This text file originally generated by RWW, May 26, 2006. Updated by RWW, May 27, 2006.
diff --git a/general/datasets/Eye_m2_0406_r/platform.rtf b/general/datasets/Eye_m2_0406_r/platform.rtf
new file mode 100644
index 0000000..ac743ee
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are near duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequences as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
diff --git a/general/datasets/Eye_m2_0406_r/processing.rtf b/general/datasets/Eye_m2_0406_r/processing.rtf
new file mode 100644
index 0000000..d23bc47
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_r/processing.rtf
@@ -0,0 +1,20 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. The CEL files were processed using the RMA protocol. We processed the two batches together in RMA.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 7: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
+After RMA processing all arrays were rank-order normalized. This second round of quantile normalization removes much residual non-linearity across arrays and forces every array to have the same distribution of values as the mean of all arrays. Comparative array data quality was then evaluated in DataDesk. Outlier arrays were flagged by visual inspection in DataDesk, usually by means of an analysis of scatter plots and more quantitatively by generating a correlation matrix of all arrays. Those arrays with mean correlation <0.96 versus all other arrays indicates trouble or a biological outlier). In some cases, outliers were expected, such as samples from strains with retinal degeneration (C3H/HeJ and BXD24) and samples from wild subspecies such as CAST/Ei, PWD/Ph, and PWK/Ph. However, when arrays were anomolous both within strain and across strains, they were often simply discarded. We tended to keep arrays that "conformed" to the expectation. The assumption in these cases is that anomolous data are much more likely due to experimental problem and errors than to informative biological variation. Approximately 8 arrays total were discarded in batches 1 and 2 combined.
+
+After this process, the acceptable set of arrays was renormalized using all step as above, starting with the original RMA procedure, etc.
+
+We then categorized arrays into XXX major "technical groups" depending on expression patterns as noted in scatterplots. This process of defining technical groups was done in DataDesk by manually "typing" arrays. These technical groups are apparently due to subtle within-batch effect that we do not yet understand and that cannot be corrected by quantile normalization. These XXX major technical groups are not obviously related to strain, sex, age, or any other known biological effect or variable. They are also not obviously related to any of the Affymetrix QC data types (3'/5' ratios, gain, etc.). Once the technical groups were defined, we forced the means of each probe set in the XX technical groups to the same value. This simple process partially removes a technical error of unknown origin in large expression array data sets.
+
+We reviewed the final data set using a new method developed by RW Williams, Jeremy Peirce, and Hongqiang Li. For the full set of 140 arrays that passed standard QC protocols described above, we computed the strain means for the BXD strains, B6, D2, and F1s. Using this set of strain means we then computed LRS scores for all 45101 probe sets and counted the number of transcripts that generated QTLs with LRS values greater than 50. This value (e.g. 1000) represented the QTL harvest for the full data set. We then dropped a single array from the data set (n = 139 arrays), recomputed strain means, and recomputed the number of transcripts with LRS scores great than 50. This value is expected to typically reduce the number of QTLs that reach the criterion level (e.g., 950 QTLs > 50). This process was repeated for every array to obtain an array-specific difference value--the effect of removing that array on the total QTL count. For example, the loss of a single array might cause a decrease in 50 QTLs (1000-950). Values ranged from -90 (good0 to +38 (bad). This procedure is similar in some ways to a jackknife protocol, although we are not using this procedure to esimate an error term, but rather as a final method to polish a data set. By applying this procedure we discovered that a set of XX (7?) arrays could be excluded while simultaneously improving the total number of QTLs with values above 50.
+
+During this final process we discovered that nearly XX arrays in the second batch had been mislabeled at some point in processing. We computed the correct strain membership of each array using a large number of Mendelian probe sets (more than 50) and comparing their match to standard SNP and microsatellite markers and the original array data set of November 2005. This allowed us to rescue a large number of arrays that were of very high quality.
+
diff --git a/general/datasets/Eye_m2_0406_r/summary.rtf b/general/datasets/Eye_m2_0406_r/summary.rtf
new file mode 100644
index 0000000..68a4484
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_r/summary.rtf
@@ -0,0 +1,3 @@
+
+SUPERCEDED EYE DATA SET. The HEIMED April 2006 data set provides estimates of mRNA expression in whole eyes of 71 lines of young adult mice generated using 132 Affymetrix M430 2.0 arrays. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). We used pooled RNA samples, usually two independent pools; one male, one female, for each straion. This data set was processed using the RMA protocol. To simplify comparison among different transforms, RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Eye_m2_0406_r/tissue.rtf b/general/datasets/Eye_m2_0406_r/tissue.rtf
new file mode 100644
index 0000000..d8d345f
--- /dev/null
+++ b/general/datasets/Eye_m2_0406_r/tissue.rtf
@@ -0,0 +1,7112 @@
+
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of RNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. Samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center lead by Drs. John Stuart and Weikuan Gu. All processing steps were performed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. centrigrade until use (one third roughly) or were immediately used for hybridization.
+
+Dealing with Ocular Pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations taken from brown and beige colored mice tend to have faint residual pigmentation that affects hybridization signal. The key determinant of this interesting effect is the Tyrp1 (brown) locus on Chr 4 at about 80 Mb. Loci on Chr 4 that map at this location should be considered with skepticism and reviewed carefully. To address this problem Yan Jiao purified total RNA a second time using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204). This was done for 8 colored samples (R2534E2, R2578E2, R1441E2, R2537E2, R2536E2, R2589E2, R2539E2) in the first batch of arrays (the November 05 data set) of which 5 were finally included in this data set (cases in which the strain ID is labeled with asterisks in the table). This same protocol was used for all samples in the second batch added in April 2006.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. The first and second batches of array data, collectively represents a reasonably well balanced sample of males and females belonging to 62 strains, but without within-strain-by-sex replication. Six strains are represented only by male sample pools (BXD15, 28, 29, 55, 98, and DBA/2J. Four strains are represented only by a female pool sample (BXD1, 27, 73 and 86). Please use the probe sets 1427262_at (Xist, high in females) and probe set 1426438_at (Ddx3y, high in males) as quantitative surrogates for the sex balance in this data set.
+
+Batch Structure: This data set consists of a two batches: the original batch that makes up the November 2005 data set and a new batch of 63 arrays (R0857E through R2649E, and R2682E through R2742E, non-consecutive identifiers) run in January 2006 by Dr. Yan Jiao. The arrays in the two batches are from two different lots. All arrays in the second batch were from Lot 4016879 (expiration date 12.28.06). We started working with a total of 140 arrays that passed initial crude quality control based on RNA quality and initial Affymetrix report file information such as 3'/5' ratio, scale factor, and percent present calls. A total of 130 arrays were finally approved for inclusion in this April 2006 data set. The complex normalization procedure is described below.
+
+The table below summarizes information on strain, age, sex, original CEL filename, Affymetrix quality control values, and source of mice. Columns labeled "PDNN 2Z outlier" and "RMA 2Z outlier" list the fraction of probe sets with values that deviated more than 2 z units from the mean. Scale factor, background average, present, absent, marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+IN PROGRESS: PLEASE NOTE THAT THIS TABLE IS NOW BEING UPDATED TO INCLUDE BATCH 2 OF EARLY 2006.
+
+
+
+
+
+ | ID |
+
+ tube ID
+ |
+
+ group_type
+ |
+
+ Strain
+ |
+
+ age
+ |
+
+ Sex
+ |
+
+ original
+
+ CEL
+
+ filename
+ |
+
+ PDNN
+
+ 2Z
+
+ outlier
+ |
+
+ RMA
+
+ 2Z
+
+ outlier
+ |
+
+ scale
+
+ factor
+ |
+
+ background
+
+ average
+ |
+
+ present
+ |
+
+ absent
+ |
+
+ marginal
+ |
+
+ AFFX-b-
+
+ ActinMur(3'/5')
+ |
+
+ AFFX-
+
+ GapdhMur(3'/5')
+ |
+
+ Source
+ |
+
+
+ |
+ 1
+ |
+
+ R2533E1
+ |
+
+ GDP
+ |
+
+ 129S1/SvImJ
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2533E.CEL
+ |
+
+ 0.025
+ |
+
+ 0.028
+ |
+
+ 2.11
+ |
+
+ 94
+ |
+
+ 57.90%
+ |
+
+ 40.50%
+ |
+
+ 1.60%
+ |
+
+ 1.37
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 2
+ |
+
+ R2595E1
+ |
+
+ GDP
+ |
+
+ 129S1/SvImJ
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2595E.CEL
+ |
+
+ 0.033
+ |
+
+ 0.036
+ |
+
+ 1.79
+ |
+
+ 115
+ |
+
+ 61.00%
+ |
+
+ 37.50%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 3
+ |
+
+ R0754E2
+ |
+
+ GDP
+ |
+
+ A/J
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R0754E.CEL
+ |
+
+ 0.027
+ |
+
+ 0.03
+ |
+
+ 2.72
+ |
+
+ 86
+ |
+
+ 59.80%
+ |
+
+ 38.70%
+ |
+
+ 1.50%
+ |
+
+ 1.36
+ |
+
+ 0.76
+ |
+
+ JAX
+ |
+
+
+ |
+ 4
+ |
+
+ R2546E1
+ |
+
+ GDP
+ |
+
+ A/J
+ |
+
+ 66
+ |
+
+ F
+ |
+
+ R2545E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.029
+ |
+
+ 1.99
+ |
+
+ 96
+ |
+
+ 58.60%
+ |
+
+ 39.70%
+ |
+
+ 1.70%
+ |
+
+ 1.47
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 5
+ |
+
+ R2601E1
+ |
+
+ GDP BXD
+ |
+
+ B6D2F1
+ |
+
+ 73
+ |
+
+ F
+ |
+
+ R2601E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.008
+ |
+
+ 2.55
+ |
+
+ 92
+ |
+
+ 58.90%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.44
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 6
+ |
+
+ R2602E1
+ |
+
+ GDP BXD
+ |
+
+ B6D2F1
+ |
+
+ 73
+ |
+
+ M
+ |
+
+ R2602E.CEL
+ |
+
+ 0.003
+ |
+
+ 0.008
+ |
+
+ 2.60
+ |
+
+ 84
+ |
+
+ 59.70%
+ |
+
+ 38.80%
+ |
+
+ 1.50%
+ |
+
+ 1.37
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 7
+ |
+
+ R1672E1
+ |
+
+ GDP
+ |
+
+ BALB/cByJ
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R1672E.CEL
+ |
+
+ 0.043
+ |
+
+ 0.039
+ |
+
+ 2.22
+ |
+
+ 111
+ |
+
+ 59.90%
+ |
+
+ 38.60%
+ |
+
+ 1.50%
+ |
+
+ 1.26
+ |
+
+ 0.80
+ |
+
+ JAX
+ |
+
+
+ |
+ 8
+ |
+
+ R1676E1
+ |
+
+ GDP
+ |
+
+ BALB/cByJ
+ |
+
+ 83
+ |
+
+ F
+ |
+
+ R1676E.CEL
+ |
+
+ 0.083
+ |
+
+ 0.085
+ |
+
+ 2.69
+ |
+
+ 98
+ |
+
+ 58.90%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.74
+ |
+
+ JAX
+ |
+
+
+ |
+ 9
+ |
+
+ R2581E1
+ |
+
+ BXD
+ |
+
+ BXD11
+ |
+
+ 65
+ |
+
+ F
+ |
+
+ R2581E.CEL
+ |
+
+ 0.009
+ |
+
+ 0.021
+ |
+
+ 1.94
+ |
+
+ 89
+ |
+
+ 62.10%
+ |
+
+ 36.40%
+ |
+
+ 1.60%
+ |
+
+ 1.55
+ |
+
+ 0.81
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 10
+ |
+
+ R2543E1
+ |
+
+ BXD
+ |
+
+ BXD12
+ |
+
+ 63
+ |
+
+ M
+ |
+
+ R2543E.CEL
+ |
+
+ 0.018
+ |
+
+ 0.017
+ |
+
+ 1.61
+ |
+
+ 118
+ |
+
+ 58.60%
+ |
+
+ 39.90%
+ |
+
+ 1.60%
+ |
+
+ 1.43
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 11
+ |
+
+ R2586E1
+ |
+
+ BXD
+ |
+
+ BXD13
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2586E.CEL
+ |
+
+ 0.259
+ |
+
+ 0.258
+ |
+
+ 2.01
+ |
+
+ 74
+ |
+
+ 56.40%
+ |
+
+ 42.00%
+ |
+
+ 1.60%
+ |
+
+ 2.85
+ |
+
+ 3.81
+ |
+
+ Glenn
+ |
+
+
+ |
+ 12
+ |
+
+ R2557E1
+ |
+
+ BXD
+ |
+
+ BXD14
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2557E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.027
+ |
+
+ 1.83
+ |
+
+ 99
+ |
+
+ 62.50%
+ |
+
+ 36.10%
+ |
+
+ 1.40%
+ |
+
+ 1.31
+ |
+
+ 0.78
+ |
+
+ Glenn
+ |
+
+
+ |
+ 13
+ |
+
+ R2567E1
+ |
+
+ BXD
+ |
+
+ BXD16
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2567E.CEL
+ |
+
+ 0.048
+ |
+
+ 0.058
+ |
+
+ 2.24
+ |
+
+ 82
+ |
+
+ 56.70%
+ |
+
+ 41.60%
+ |
+
+ 1.70%
+ |
+
+ 1.37
+ |
+
+ 0.75
+ |
+
+ Glenn
+ |
+
+
+ |
+ 14
+ |
+
+ R2559E1
+ |
+
+ BXD
+ |
+
+ BXD18
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2559E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.012
+ |
+
+ 1.65
+ |
+
+ 104
+ |
+
+ 60.80%
+ |
+
+ 37.70%
+ |
+
+ 1.50%
+ |
+
+ 1.27
+ |
+
+ 0.78
+ |
+
+ Glenn
+ |
+
+
+ |
+ 15
+ |
+
+ R2560E1
+ |
+
+ BXD
+ |
+
+ BXD19
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2560E.CEL
+ |
+
+ 0.009
+ |
+
+ 0.012
+ |
+
+ 1.79
+ |
+
+ 98
+ |
+
+ 60.90%
+ |
+
+ 37.50%
+ |
+
+ 1.60%
+ |
+
+ 1.35
+ |
+
+ 0.80
+ |
+
+ Glenn
+ |
+
+
+ |
+ 16
+ |
+
+ R2597E1
+ |
+
+ BXD
+ |
+
+ BXD2
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2597E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.012
+ |
+
+ 2.37
+ |
+
+ 94
+ |
+
+ 60.30%
+ |
+
+ 38.30%
+ |
+
+ 1.50%
+ |
+
+ 1.34
+ |
+
+ 0.77
+ |
+
+ Glenn
+ |
+
+
+ |
+ 17
+ |
+
+ R2584E1
+ |
+
+ BXD
+ |
+
+ BXD20
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2584E.CEL
+ |
+
+ 0.011
+ |
+
+ 0.017
+ |
+
+ 2.07
+ |
+
+ 84
+ |
+
+ 59.30%
+ |
+
+ 39.10%
+ |
+
+ 1.60%
+ |
+
+ 1.40
+ |
+
+ 0.76
+ |
+
+ Glenn
+ |
+
+
+ |
+ 18
+ |
+
+ R2541E2
+ |
+
+ BXD
+ |
+
+ BXD21
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2541E2.CEL
+ |
+
+ 0.049
+ |
+
+ 0.084
+ |
+
+ 2.63
+ |
+
+ 125
+ |
+
+ 56.00%
+ |
+
+ 42.40%
+ |
+
+ 1.50%
+ |
+
+ 1.29
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 19
+ |
+
+ R2553E1
+ |
+
+ BXD
+ |
+
+ BXD22
+ |
+
+ 58
+ |
+
+ F
+ |
+
+ R2553E.CEL
+ |
+
+ 0.004
+ |
+
+ 0.01
+ |
+
+ 1.95
+ |
+
+ 111
+ |
+
+ 59.90%
+ |
+
+ 38.50%
+ |
+
+ 1.50%
+ |
+
+ 1.28
+ |
+
+ 0.76
+ |
+
+ Glenn
+ |
+
+
+ |
+ 20
+ |
+
+ R2558E1
+ |
+
+ BXD
+ |
+
+ BXD23
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2558E-2.CEL
+ |
+
+ 0.018
+ |
+
+ 0.027
+ |
+
+ 1.91
+ |
+
+ 115
+ |
+
+ 59.90%
+ |
+
+ 38.80%
+ |
+
+ 1.40%
+ |
+
+ 1.20
+ |
+
+ 0.82
+ |
+
+ Glenn
+ |
+
+
+ |
+ 21
+ |
+
+ R2589E2
+ |
+
+ BXD
+ |
+
+ BXD24
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2589E2.CEL
+ |
+
+ 0.132
+ |
+
+ 0.176
+ |
+
+ 2.61
+ |
+
+ 112
+ |
+
+ 57.50%
+ |
+
+ 40.90%
+ |
+
+ 1.60%
+ |
+
+ 1.24
+ |
+
+ 0.80
+ |
+
+ Glenn
+ |
+
+
+ |
+ 22
+ |
+
+ R2573E1
+ |
+
+ BXD
+ |
+
+ BXD25
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2573E-2.CEL
+ |
+
+ 0.055
+ |
+
+ 0.063
+ |
+
+ 3.15
+ |
+
+ 72
+ |
+
+ 57.90%
+ |
+
+ 40.70%
+ |
+
+ 1.40%
+ |
+
+ 1.77
+ |
+
+ 0.97
+ |
+
+ UAB
+ |
+
+
+ |
+ 23
+ |
+
+ R2562E1
+ |
+
+ BXD
+ |
+
+ BXD29
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2562E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.01
+ |
+
+ 1.65
+ |
+
+ 116
+ |
+
+ 59.90%
+ |
+
+ 38.40%
+ |
+
+ 1.70%
+ |
+
+ 1.37
+ |
+
+ 0.79
+ |
+
+ Glenn
+ |
+
+
+ |
+ 24
+ |
+
+ R2598E1
+ |
+
+ BXD
+ |
+
+ BXD31
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2598E.CEL
+ |
+
+ 0.006
+ |
+
+ 0.013
+ |
+
+ 1.99
+ |
+
+ 106
+ |
+
+ 60.90%
+ |
+
+ 37.60%
+ |
+
+ 1.50%
+ |
+
+ 1.27
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 25
+ |
+
+ R2563E1
+ |
+
+ BXD
+ |
+
+ BXD32
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2563E.CEL
+ |
+
+ 0.023
+ |
+
+ 0.025
+ |
+
+ 1.55
+ |
+
+ 102
+ |
+
+ 61.90%
+ |
+
+ 36.70%
+ |
+
+ 1.40%
+ |
+
+ 1.50
+ |
+
+ 0.80
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 26
+ |
+
+ R2542E1
+ |
+
+ BXD
+ |
+
+ BXD33
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2542E.CEL
+ |
+
+ 0.058
+ |
+
+ 0.062
+ |
+
+ 2.13
+ |
+
+ 97
+ |
+
+ 56.50%
+ |
+
+ 41.80%
+ |
+
+ 1.60%
+ |
+
+ 1.91
+ |
+
+ 0.93
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 27
+ |
+
+ R2585E1
+ |
+
+ BXD
+ |
+
+ BXD34
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2585E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.032
+ |
+
+ 2.64
+ |
+
+ 75
+ |
+
+ 58.30%
+ |
+
+ 40.00%
+ |
+
+ 1.70%
+ |
+
+ 1.25
+ |
+
+ 0.77
+ |
+
+ Glenn
+ |
+
+
+ |
+ 28
+ |
+
+ R2532E1
+ |
+
+ BXD
+ |
+
+ BXD38
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2532E.CEL
+ |
+
+ 0.002
+ |
+
+ 0.006
+ |
+
+ 2.04
+ |
+
+ 94
+ |
+
+ 59.80%
+ |
+
+ 38.70%
+ |
+
+ 1.50%
+ |
+
+ 1.37
+ |
+
+ 0.80
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 29
+ |
+
+ R2574E1
+ |
+
+ BXD
+ |
+
+ BXD39
+ |
+
+ 70
+ |
+
+ F
+ |
+
+ R2574E.CEL
+ |
+
+ 0.003
+ |
+
+ 0.008
+ |
+
+ 1.98
+ |
+
+ 91
+ |
+
+ 61.20%
+ |
+
+ 37.30%
+ |
+
+ 1.50%
+ |
+
+ 1.39
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 30
+ |
+
+ R2590E1
+ |
+
+ BXD
+ |
+
+ BXD40
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2590E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.012
+ |
+
+ 2.71
+ |
+
+ 77
+ |
+
+ 59.10%
+ |
+
+ 39.30%
+ |
+
+ 1.50%
+ |
+
+ 1.40
+ |
+
+ 0.77
+ |
+
+ Glenn
+ |
+
+
+ |
+ 31
+ |
+
+ R2596E1
+ |
+
+ BXD
+ |
+
+ BXD42
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2596E.CEL
+ |
+
+ 0.016
+ |
+
+ 0.03
+ |
+
+ 2.63
+ |
+
+ 108
+ |
+
+ 59.00%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.24
+ |
+
+ 0.80
+ |
+
+ Glenn
+ |
+
+
+ |
+ 32
+ |
+
+ R2605E1
+ |
+
+ BXD
+ |
+
+ BXD43
+ |
+
+ 79
+ |
+
+ M
+ |
+
+ R2607E.CEL
+ |
+
+ 0.006
+ |
+
+ 0.01
+ |
+
+ 1.82
+ |
+
+ 131
+ |
+
+ 60.50%
+ |
+
+ 38.20%
+ |
+
+ 1.30%
+ |
+
+ 1.32
+ |
+
+ 0.80
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 33
+ |
+
+ R2594E1
+ |
+
+ BXD
+ |
+
+ BXD44
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2594E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.024
+ |
+
+ 1.77
+ |
+
+ 117
+ |
+
+ 59.80%
+ |
+
+ 38.80%
+ |
+
+ 1.40%
+ |
+
+ 1.35
+ |
+
+ 0.85
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 34
+ |
+
+ R2592E1
+ |
+
+ BXD
+ |
+
+ BXD45
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2592E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.011
+ |
+
+ 1.85
+ |
+
+ 106
+ |
+
+ 60.10%
+ |
+
+ 38.60%
+ |
+
+ 1.30%
+ |
+
+ 1.43
+ |
+
+ 0.85
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 35
+ |
+
+ R2606E1
+ |
+
+ BXD
+ |
+
+ BXD48
+ |
+
+ 78
+ |
+
+ M
+ |
+
+ R2606E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.015
+ |
+
+ 2.56
+ |
+
+ 106
+ |
+
+ 58.90%
+ |
+
+ 39.70%
+ |
+
+ 1.40%
+ |
+
+ 1.35
+ |
+
+ 0.83
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 36
+ |
+
+ R2591E1
+ |
+
+ BXD
+ |
+
+ BXD5
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2591E.CEL
+ |
+
+ 0.052
+ |
+
+ 0.014
+ |
+
+ 1.70
+ |
+
+ 136
+ |
+
+ 58.50%
+ |
+
+ 40.00%
+ |
+
+ 1.50%
+ |
+
+ 1.33
+ |
+
+ 0.78
+ |
+
+ Glenn
+ |
+
+
+ |
+ 37
+ |
+
+ R2603E1
+ |
+
+ BXD
+ |
+
+ BXD51
+ |
+
+ 66
+ |
+
+ F
+ |
+
+ R2603E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.02
+ |
+
+ 2.49
+ |
+
+ 115
+ |
+
+ 57.70%
+ |
+
+ 40.80%
+ |
+
+ 1.50%
+ |
+
+ 1.24
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 38
+ |
+
+ R2570E1
+ |
+
+ BXD
+ |
+
+ BXD6
+ |
+
+ 65
+ |
+
+ F
+ |
+
+ R2570E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.017
+ |
+
+ 1.99
+ |
+
+ 87
+ |
+
+ 58.50%
+ |
+
+ 40.00%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.76
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 39
+ |
+
+ R2534E2
+ |
+
+ BXD
+ |
+
+ BXD61
+ |
+
+ 70
+ |
+
+ F
+ |
+
+ R2534E2.CEL
+ |
+
+ 0.03
+ |
+
+ 0.058
+ |
+
+ 2.47
+ |
+
+ 118
+ |
+
+ 57.90%
+ |
+
+ 40.60%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 40
+ |
+
+ R2611E1
+ |
+
+ BXD
+ |
+
+ BXD64
+ |
+
+ 68
+ |
+
+ M
+ |
+
+ R2611E.CEL
+ |
+
+ 0.067
+ |
+
+ 0.068
+ |
+
+ 2.29
+ |
+
+ 92
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.50%
+ |
+
+ 1.57
+ |
+
+ 1.06
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 41
+ |
+
+ R2583E1
+ |
+
+ BXD
+ |
+
+ BXD65
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2583E.CEL
+ |
+
+ 0.027
+ |
+
+ 0.03
+ |
+
+ 2.49
+ |
+
+ 70
+ |
+
+ 56.90%
+ |
+
+ 41.50%
+ |
+
+ 1.60%
+ |
+
+ 1.67
+ |
+
+ 1.01
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 42
+ |
+
+ R2536E2
+ |
+
+ BXD
+ |
+
+ BXD66
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2536E2.CEL
+ |
+
+ 0.067
+ |
+
+ 0.139
+ |
+
+ 2.74
+ |
+
+ 109
+ |
+
+ 56.10%
+ |
+
+ 42.30%
+ |
+
+ 1.70%
+ |
+
+ 1.28
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 43
+ |
+
+ R2551E1
+ |
+
+ BXD
+ |
+
+ BXD68
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2551E.CEL
+ |
+
+ 0.294
+ |
+
+ 0.291
+ |
+
+ 2.49
+ |
+
+ 92
+ |
+
+ 54.30%
+ |
+
+ 44.10%
+ |
+
+ 1.60%
+ |
+
+ 2.91
+ |
+
+ 1.55
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 44
+ |
+
+ R2593E1
+ |
+
+ BXD
+ |
+
+ BXD69
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2593E.CEL
+ |
+
+ 0.027
+ |
+
+ 0.038
+ |
+
+ 1.67
+ |
+
+ 128
+ |
+
+ 59.20%
+ |
+
+ 39.50%
+ |
+
+ 1.30%
+ |
+
+ 1.47
+ |
+
+ 0.92
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 45
+ |
+
+ R2537E2
+ |
+
+ BXD
+ |
+
+ BXD70
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2537E2.CEL
+ |
+
+ 0.049
+ |
+
+ 0.092
+ |
+
+ 2.93
+ |
+
+ 99
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.60%
+ |
+
+ 1.29
+ |
+
+ 0.75
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 46
+ |
+
+ R2565E1
+ |
+
+ BXD
+ |
+
+ BXD75
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R2565E.CEL
+ |
+
+ 0.118
+ |
+
+ 0.124
+ |
+
+ 1.79
+ |
+
+ 102
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.50%
+ |
+
+ 2.31
+ |
+
+ 3.47
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 47
+ |
+
+ R2538E1
+ |
+
+ BXD
+ |
+
+ BXD8
+ |
+
+ 77
+ |
+
+ F
+ |
+
+ R2538E.CEL
+ |
+
+ 0.033
+ |
+
+ 0.056
+ |
+
+ 1.91
+ |
+
+ 102
+ |
+
+ 61.20%
+ |
+
+ 37.30%
+ |
+
+ 1.50%
+ |
+
+ 1.52
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 48
+ |
+
+ R2579E1
+ |
+
+ BXD
+ |
+
+ BXD80
+ |
+
+ 65
+ |
+
+ F
+ |
+
+ R2579E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.026
+ |
+
+ 2.42
+ |
+
+ 72
+ |
+
+ 59.20%
+ |
+
+ 39.40%
+ |
+
+ 1.50%
+ |
+
+ 1.73
+ |
+
+ 0.82
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 49
+ |
+
+ R2540E1
+ |
+
+ BXD
+ |
+
+ BXD87
+ |
+
+ 63
+ |
+
+ M
+ |
+
+ R2540E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.034
+ |
+
+ 2.33
+ |
+
+ 93
+ |
+
+ 61.10%
+ |
+
+ 37.40%
+ |
+
+ 1.40%
+ |
+
+ 1.22
+ |
+
+ 0.81
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 50
+ |
+
+ R2545E1
+ |
+
+ BXD
+ |
+
+ BXD89
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2546E.CEL
+ |
+
+ 0.266
+ |
+
+ 0.257
+ |
+
+ 1.67
+ |
+
+ 105
+ |
+
+ 56.20%
+ |
+
+ 42.30%
+ |
+
+ 1.50%
+ |
+
+ 3.60
+ |
+
+ 9.84
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 51
+ |
+
+ R2569E1
+ |
+
+ BXD
+ |
+
+ BXD9
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2569E.CEL
+ |
+
+ 0.256
+ |
+
+ 0.239
+ |
+
+ 1.75
+ |
+
+ 87
+ |
+
+ 55.10%
+ |
+
+ 43.40%
+ |
+
+ 1.50%
+ |
+
+ 2.82
+ |
+
+ 3.14
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 52
+ |
+
+ R2578E2
+ |
+
+ BXD
+ |
+
+ BXD90
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R2578E2.CEL
+ |
+
+ 0.041
+ |
+
+ 0.062
+ |
+
+ 2.79
+ |
+
+ 92
+ |
+
+ 58.60%
+ |
+
+ 39.80%
+ |
+
+ 1.60%
+ |
+
+ 1.52
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 53
+ |
+
+ R2554E1
+ |
+
+ BXD
+ |
+
+ BXD96
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2554E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.008
+ |
+
+ 2.18
+ |
+
+ 93
+ |
+
+ 60.20%
+ |
+
+ 38.30%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 54
+ |
+
+ R2577E1
+ |
+
+ BXD
+ |
+
+ BXD97
+ |
+
+ 55
+ |
+
+ M
+ |
+
+ R2577E.CEL
+ |
+
+ 0.065
+ |
+
+ 0.069
+ |
+
+ 2.07
+ |
+
+ 77
+ |
+
+ 59.50%
+ |
+
+ 39.10%
+ |
+
+ 1.40%
+ |
+
+ 1.87
+ |
+
+ 1.29
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 55
+ |
+
+ R1700E1
+ |
+
+ GDP
+ |
+
+ C3H/HeJ
+ |
+
+ 83
+ |
+
+ F
+ |
+
+ R1700E.CEL
+ |
+
+ 0.152
+ |
+
+ 0.168
+ |
+
+ 2.98
+ |
+
+ 69
+ |
+
+ 60.80%
+ |
+
+ 37.90%
+ |
+
+ 1.40%
+ |
+
+ 1.48
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 56
+ |
+
+ R1704E1
+ |
+
+ GDP
+ |
+
+ C3H/HeJ
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R1704E.CEL
+ |
+
+ 0.154
+ |
+
+ 0.165
+ |
+
+ 2.58
+ |
+
+ 88
+ |
+
+ 60.10%
+ |
+
+ 38.60%
+ |
+
+ 1.30%
+ |
+
+ 1.38
+ |
+
+ 0.84
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 57
+ |
+
+ R0872E2
+ |
+
+ GDP BXD
+ |
+
+ C57BL/6J
+ |
+
+ 66
+ |
+
+ M
+ |
+
+ R0872E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.023
+ |
+
+ 3.13
+ |
+
+ 89
+ |
+
+ 58.90%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.30
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 58
+ |
+
+ R2607E1
+ |
+
+ GDP BXD
+ |
+
+ C57BL/6J
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2605E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.018
+ |
+
+ 2.43
+ |
+
+ 115
+ |
+
+ 58.60%
+ |
+
+ 40.00%
+ |
+
+ 1.40%
+ |
+
+ 1.31
+ |
+
+ 0.76
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 59
+ |
+
+ R2564E1
+ |
+
+ GDP
+ |
+
+ CAST/Ei
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2564E.CEL
+ |
+
+ 0.124
+ |
+
+ 0.105
+ |
+
+ 1.94
+ |
+
+ 89
+ |
+
+ 58.50%
+ |
+
+ 39.90%
+ |
+
+ 1.60%
+ |
+
+ 1.60
+ |
+
+ 0.77
+ |
+
+ JAX
+ |
+
+
+ |
+ 60
+ |
+
+ R2580E1
+ |
+
+ GDP
+ |
+
+ CAST/Ei
+ |
+
+ 64
+ |
+
+ M
+ |
+
+ R2580E.CEL
+ |
+
+ 0.123
+ |
+
+ 0.109
+ |
+
+ 2.09
+ |
+
+ 95
+ |
+
+ 58.20%
+ |
+
+ 40.10%
+ |
+
+ 1.70%
+ |
+
+ 1.40
+ |
+
+ 0.76
+ |
+
+ JAX
+ |
+
+
+ |
+ 61
+ |
+
+ R2600E1
+ |
+
+ GDP BXD
+ |
+
+ D2B6F1
+ |
+
+ 72
+ |
+
+ F
+ |
+
+ R2600E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.02
+ |
+
+ 2.47
+ |
+
+ 95
+ |
+
+ 58.10%
+ |
+
+ 40.20%
+ |
+
+ 1.70%
+ |
+
+ 1.41
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 62
+ |
+
+ R2604E1
+ |
+
+ GDP BXD
+ |
+
+ D2B6F1
+ |
+
+ 69
+ |
+
+ M
+ |
+
+ R2604E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.014
+ |
+
+ 2.66
+ |
+
+ 90
+ |
+
+ 59.40%
+ |
+
+ 39.20%
+ |
+
+ 1.50%
+ |
+
+ 1.28
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 63
+ |
+
+ R2572E1
+ |
+
+ GDP BXD
+ |
+
+ DBA/2J
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R2572E.CEL
+ |
+
+ 0.091
+ |
+
+ 0.106
+ |
+
+ 2.41
+ |
+
+ 79
+ |
+
+ 55.50%
+ |
+
+ 42.90%
+ |
+
+ 1.60%
+ |
+
+ 1.37
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 64
+ |
+
+ R2636E1
+ |
+
+ GDP
+ |
+
+ KK/HIJ
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2636E.CEL
+ |
+
+ 0.044
+ |
+
+ 0.043
+ |
+
+ 2.61
+ |
+
+ 93
+ |
+
+ 58.90%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.39
+ |
+
+ 0.76
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 65
+ |
+
+ R2637E1
+ |
+
+ GDP
+ |
+
+ KK/HIJ
+ |
+
+ 64
+ |
+
+ M
+ |
+
+ R2637E.CEL
+ |
+
+ 0.056
+ |
+
+ 0.036
+ |
+
+ 2.19
+ |
+
+ 103
+ |
+
+ 59.40%
+ |
+
+ 39.00%
+ |
+
+ 1.50%
+ |
+
+ 1.30
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 66
+ |
+
+ R0999E1
+ |
+
+ GDP
+ |
+
+ LG/J
+ |
+
+ 57
+ |
+
+ F
+ |
+
+ R0999E.CEL
+ |
+
+ 0.021
+ |
+
+ 0.023
+ |
+
+ 2.45
+ |
+
+ 82
+ |
+
+ 59.40%
+ |
+
+ 39.10%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 67
+ |
+
+ R1004E1
+ |
+
+ GDP
+ |
+
+ LG/J
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R1004E.CEL
+ |
+
+ 0.025
+ |
+
+ 0.028
+ |
+
+ 2.44
+ |
+
+ 92
+ |
+
+ 58.70%
+ |
+
+ 39.80%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 68
+ |
+
+ R1688E1
+ |
+
+ GDP
+ |
+
+ NOD/LtJ
+ |
+
+ 66
+ |
+
+ F
+ |
+
+ R1688E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.033
+ |
+
+ 2.66
+ |
+
+ 98
+ |
+
+ 58.60%
+ |
+
+ 39.90%
+ |
+
+ 1.50%
+ |
+
+ 1.26
+ |
+
+ 0.80
+ |
+
+ JAX
+ |
+
+
+ |
+ 69
+ |
+
+ R2566E1
+ |
+
+ GDP
+ |
+
+ NOD/LtJ
+ |
+
+ 76
+ |
+
+ M
+ |
+
+ R2566E-2.CEL
+ |
+
+ 0.036
+ |
+
+ 0.04
+ |
+
+ 3.03
+ |
+
+ 69
+ |
+
+ 59.80%
+ |
+
+ 38.80%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.75
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 70
+ |
+
+ R2535E1
+ |
+
+ GDP
+ |
+
+ NZO/H1LtJ
+ |
+
+ 62
+ |
+
+ F
+ |
+
+ R2535E.CEL
+ |
+
+ 0.037
+ |
+
+ 0.062
+ |
+
+ 1.89
+ |
+
+ 86
+ |
+
+ 60.40%
+ |
+
+ 38.20%
+ |
+
+ 1.40%
+ |
+
+ 1.41
+ |
+
+ 0.85
+ |
+
+ JAX
+ |
+
+
+ |
+ 71
+ |
+
+ R2550E1
+ |
+
+ GDP
+ |
+
+ NZO/HILtJ
+ |
+
+ 96
+ |
+
+ M
+ |
+
+ R2550E.CEL
+ |
+
+ 0.025
+ |
+
+ 0.029
+ |
+
+ 1.79
+ |
+
+ 87
+ |
+
+ 60.70%
+ |
+
+ 37.80%
+ |
+
+ 1.50%
+ |
+
+ 1.52
+ |
+
+ 0.82
+ |
+
+ JAX
+ |
+
+
+ |
+ 72
+ |
+
+ R2634E1
+ |
+
+ GDP
+ |
+
+ PWD/PhJ
+ |
+
+ 62
+ |
+
+ F
+ |
+
+ R2635E.CEL
+ |
+
+ 0.126
+ |
+
+ 0.114
+ |
+
+ 3.29
+ |
+
+ 90
+ |
+
+ 55.90%
+ |
+
+ 42.50%
+ |
+
+ 1.60%
+ |
+
+ 1.57
+ |
+
+ 0.81
+ |
+
+ JAX
+ |
+
+
+ |
+ 73
+ |
+
+ R2635E1
+ |
+
+ GDP
+ |
+
+ PWD/PhJ
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2634E.CEL
+ |
+
+ 0.15
+ |
+
+ 0.137
+ |
+
+ 3.72
+ |
+
+ 80
+ |
+
+ 54.20%
+ |
+
+ 44.10%
+ |
+
+ 1.70%
+ |
+
+ 1.53
+ |
+
+ 0.85
+ |
+
+ JAX
+ |
+
+
+ |
+ 74
+ |
+
+ R2544E1
+ |
+
+ GDP
+ |
+
+ PWK/PhJ
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2544E.CEL
+ |
+
+ 0.174
+ |
+
+ 0.175
+ |
+
+ 2.20
+ |
+
+ 108
+ |
+
+ 54.90%
+ |
+
+ 43.50%
+ |
+
+ 1.70%
+ |
+
+ 1.36
+ |
+
+ 0.82
+ |
+
+ JAX
+ |
+
+
+ |
+ 75
+ |
+
+ R2549E1
+ |
+
+ GDP
+ |
+
+ PWK/PhJ
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R2549E.CEL
+ |
+
+ 0.103
+ |
+
+ 0.087
+ |
+
+ 2.28
+ |
+
+ 84
+ |
+
+ 57.30%
+ |
+
+ 41.20%
+ |
+
+ 1.50%
+ |
+
+ 1.57
+ |
+
+ 0.83
+ |
+
+ JAX
+ |
+
+
+ |
+ 76
+ |
+
+ R2368E1
+ |
+
+ GDP
+ |
+
+ WSB/EI
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2368E.CEL
+ |
+
+ 0.041
+ |
+
+ 0.047
+ |
+
+ 2.57
+ |
+
+ 86
+ |
+
+ 59.50%
+ |
+
+ 39.10%
+ |
+
+ 1.40%
+ |
+
+ 1.29
+ |
+
+ 0.74
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 77
+ |
+
+ R2704E
+ |
+
+ BXD
+ |
+
+ BXD1
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2704E.CEL
+ |
+
+ 0.029
+ |
+
+ 0.03
+ |
+
+ 2.066
+ |
+
+ 139.61
+ |
+
+ 56.60%
+ |
+
+ 41.90%
+ |
+
+ 1.50%
+ |
+
+ 1.31
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 78
+ |
+
+ R2612E
+ |
+
+ BXD
+ |
+
+ BXD11
+ |
+
+ 70
+ |
+
+ M
+ |
+
+ R2612E.CEL
+ |
+
+ 0.101
+ |
+
+ 0.112
+ |
+
+ 1.83
+ |
+
+ 142.03
+ |
+
+ 58.20%
+ |
+
+ 40.50%
+ |
+
+ 1.40%
+ |
+
+ 1.78
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 79
+ |
+
+ R2742E
+ |
+
+ BXD
+ |
+
+ BXD12
+ |
+
+ 71
+ |
+
+ F
+ |
+
+ R2742E.CEL
+ |
+
+ 0.073
+ |
+
+ 0.077
+ |
+
+ 2.127
+ |
+
+ 134.14
+ |
+
+ 57.00%
+ |
+
+ 41.60%
+ |
+
+ 1.40%
+ |
+
+ 1.64
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 80
+ |
+
+ R1086E
+ |
+
+ BXD
+ |
+
+ BXD23
+ |
+
+ 55
+ |
+
+ M
+ |
+
+ R1086E.CEL
+ |
+
+ 0.043
+ |
+
+ 0.034
+ |
+
+ 2.233
+ |
+
+ 125.05
+ |
+
+ 58.60%
+ |
+
+ 39.90%
+ |
+
+ 1.50%
+ |
+
+ 1.43
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 81
+ |
+
+ R2716E
+ |
+
+ BXD
+ |
+
+ BXD15
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2716E.CEL
+ |
+
+ 0.035
+ |
+
+ 0.037
+ |
+
+ 2.015
+ |
+
+ 150.83
+ |
+
+ 56.40%
+ |
+
+ 42.10%
+ |
+
+ 1.60%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 82
+ |
+
+ R2711E
+ |
+
+ BXD
+ |
+
+ BXD16
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R2711E.CEL
+ |
+
+ 0.032
+ |
+
+ 0.021
+ |
+
+ 1.953
+ |
+
+ 118.53
+ |
+
+ 59.00%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.45
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 83
+ |
+
+ R2720E
+ |
+
+ BXD
+ |
+
+ BXD18
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2720E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.019
+ |
+
+ 2.32
+ |
+
+ 99.93
+ |
+
+ 59.50%
+ |
+
+ 39.00%
+ |
+
+ 1.50%
+ |
+
+ 1.33
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 84
+ |
+
+ R2713E
+ |
+
+ BXD
+ |
+
+ BXD19
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2713E.CEL
+ |
+
+ 0.055
+ |
+
+ 0.021
+ |
+
+ 1.67
+ |
+
+ 120.82
+ |
+
+ 60.20%
+ |
+
+ 38.30%
+ |
+
+ 1.50%
+ |
+
+ 1.45
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 85
+ |
+
+ R1231E
+ |
+
+ BXD
+ |
+
+ BXD2
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R1231E.CEL
+ |
+
+ 0.044
+ |
+
+ 0.037
+ |
+
+ 2.197
+ |
+
+ 138.73
+ |
+
+ 57.30%
+ |
+
+ 41.30%
+ |
+
+ 1.40%
+ |
+
+ 1.41
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 86
+ |
+
+ R2731E
+ |
+
+ BXD
+ |
+
+ BXD20
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2731E.CEL
+ |
+
+ 0.017
+ |
+
+ 0.019
+ |
+
+ 1.825
+ |
+
+ 147
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.4
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 87
+ |
+
+ R2702E
+ |
+
+ BXD
+ |
+
+ BXD21
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2702E.CEL
+ |
+
+ 0.009
+ |
+
+ 0.008
+ |
+
+ 1.811
+ |
+
+ 128.65
+ |
+
+ 59.40%
+ |
+
+ 39.10%
+ |
+
+ 1.40%
+ |
+
+ 1.26
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 88
+ |
+
+ R2700E
+ |
+
+ BXD
+ |
+
+ BXD22
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2700E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.015
+ |
+
+ 1.858
+ |
+
+ 102.96
+ |
+
+ 61.50%
+ |
+
+ 37.10%
+ |
+
+ 1.30%
+ |
+
+ 1.48
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 89
+ |
+
+ R1128E
+ |
+
+ BXD
+ |
+
+ BXD14
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R1128E.CEL
+ |
+
+ 0.037
+ |
+
+ 0.038
+ |
+
+ 2.366
+ |
+
+ 118.39
+ |
+
+ 57.30%
+ |
+
+ 41.30%
+ |
+
+ 1.40%
+ |
+
+ 1.45
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 90
+ |
+
+ R2719E
+ |
+
+ BXD
+ |
+
+ BXD24
+ |
+
+ 123
+ |
+
+ F
+ |
+
+ R2719E.CEL
+ |
+
+ 0.112
+ |
+
+ 0.111
+ |
+
+ 1.47
+ |
+
+ 140.38
+ |
+
+ 61.50%
+ |
+
+ 37.20%
+ |
+
+ 1.30%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 91
+ |
+
+ R2683E
+ |
+
+ BXD
+ |
+
+ BXD25
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R2683E.CEL
+ |
+
+ 0.068
+ |
+
+ 0.068
+ |
+
+ 1.777
+ |
+
+ 115.64
+ |
+
+ 58.30%
+ |
+
+ 40.30%
+ |
+
+ 1.40%
+ |
+
+ 2.01
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 92
+ |
+
+ R2703E
+ |
+
+ BXD
+ |
+
+ BXD27
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2703E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.012
+ |
+
+ 1.263
+ |
+
+ 134.78
+ |
+
+ 62.60%
+ |
+
+ 36.10%
+ |
+
+ 1.40%
+ |
+
+ 1.44
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 93
+ |
+
+ R2721E
+ |
+
+ BXD
+ |
+
+ BXD28
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2721E.CEL
+ |
+
+ 0.04
+ |
+
+ 0.048
+ |
+
+ 2.065
+ |
+
+ 157.39
+ |
+
+ 56.10%
+ |
+
+ 42.40%
+ |
+
+ 1.50%
+ |
+
+ 1.31
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 94
+ |
+
+ R1258E
+ |
+
+ BXD
+ |
+
+ BXD31
+ |
+
+ 57
+ |
+
+ F
+ |
+
+ R1258E.CEL
+ |
+
+ 0.037
+ |
+
+ 0.036
+ |
+
+ 2.063
+ |
+
+ 117.09
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.54
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 95
+ |
+
+ R1216E
+ |
+
+ BXD
+ |
+
+ BXD32
+ |
+
+ 76
+ |
+
+ M
+ |
+
+ R1216E.CEL
+ |
+
+ 0.05
+ |
+
+ 0.049
+ |
+
+ 2.23
+ |
+
+ 111.99
+ |
+
+ 58.80%
+ |
+
+ 39.80%
+ |
+
+ 1.40%
+ |
+
+ 1.35
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 96
+ |
+
+ R857E
+ |
+
+ BXD
+ |
+
+ BXD33
+ |
+
+ 77
+ |
+
+ M
+ |
+
+ R857E.CEL
+ |
+
+ 0.078
+ |
+
+ 0.108
+ |
+
+ 1.737
+ |
+
+ 113.98
+ |
+
+ 61.90%
+ |
+
+ 36.70%
+ |
+
+ 1.30%
+ |
+
+ 1.6
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 97
+ |
+
+ R859E
+ |
+
+ BXD
+ |
+
+ BXD90
+ |
+
+ 72
+ |
+
+ M
+ |
+
+ R859E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.02
+ |
+
+ 1.847
+ |
+
+ 152.22
+ |
+
+ 57.90%
+ |
+
+ 40.70%
+ |
+
+ 1.40%
+ |
+
+ 1.36
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 98
+ |
+
+ R1207E
+ |
+
+ BXD
+ |
+
+ BXD66
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R1207E.CEL
+ |
+
+ 0.017
+ |
+
+ 0.012
+ |
+
+ 1.681
+ |
+
+ 136.86
+ |
+
+ 60.40%
+ |
+
+ 38.10%
+ |
+
+ 1.50%
+ |
+
+ 1.45
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 99
+ |
+
+ R2710E
+ |
+
+ BXD
+ |
+
+ BXD38
+ |
+
+ 55
+ |
+
+ F
+ |
+
+ R2710E.CEL
+ |
+
+ 0.033
+ |
+
+ 0.031
+ |
+
+ 2.112
+ |
+
+ 122.1
+ |
+
+ 58.80%
+ |
+
+ 39.80%
+ |
+
+ 1.40%
+ |
+
+ 1.37
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 100
+ |
+
+ R2695E
+ |
+
+ BXD
+ |
+
+ BXD39
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2695E.CEL
+ |
+
+ 0.018
+ |
+
+ 0.016
+ |
+
+ 1.638
+ |
+
+ 122.7
+ |
+
+ 60.80%
+ |
+
+ 37.80%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 101
+ |
+
+ R2699E
+ |
+
+ BXD
+ |
+
+ BXD40
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2699E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.015
+ |
+
+ 1.827
+ |
+
+ 105.23
+ |
+
+ 61.70%
+ |
+
+ 36.90%
+ |
+
+ 1.40%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 102
+ |
+
+ R2696E
+ |
+
+ BXD
+ |
+
+ BXD42
+ |
+
+ 58
+ |
+
+ F
+ |
+
+ R2696E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.017
+ |
+
+ 1.622
+ |
+
+ 118.95
+ |
+
+ 62.00%
+ |
+
+ 36.60%
+ |
+
+ 1.50%
+ |
+
+ 1.53
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 103
+ |
+
+ R943E-2
+ |
+
+ BXD
+ |
+
+ BXD64
+ |
+
+ 56
+ |
+
+ F
+ |
+
+ R943E-2.CEL
+ |
+
+ 0.024
+ |
+
+ 0.021
+ |
+
+ 1.591
+ |
+
+ 141.34
+ |
+
+ 60.10%
+ |
+
+ 38.40%
+ |
+
+ 1.50%
+ |
+
+ 1.32
+ |
+
+ 0.76
+ |
+
+ GU
+ |
+
+
+ |
+ 104
+ |
+
+ R967E
+ |
+
+ BXD
+ |
+
+ BXD48
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R967E.CEL
+ |
+
+ 0.101
+ |
+
+ 0.052
+ |
+
+ 1.948
+ |
+
+ 130.95
+ |
+
+ 57.30%
+ |
+
+ 41.20%
+ |
+
+ 1.50%
+ |
+
+ 1.63
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 105
+ |
+
+ R2714E
+ |
+
+ BXD
+ |
+
+ BXD5
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R2714E.CEL
+ |
+
+ 0.047
+ |
+
+ 0.014
+ |
+
+ 1.404
+ |
+
+ 144.35
+ |
+
+ 60.60%
+ |
+
+ 37.90%
+ |
+
+ 1.50%
+ |
+
+ 1.43
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 106
+ |
+
+ R1042E
+ |
+
+ BXD
+ |
+
+ BXD51
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R1042E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.027
+ |
+
+ 2.352
+ |
+
+ 104.12
+ |
+
+ 58.70%
+ |
+
+ 39.90%
+ |
+
+ 1.40%
+ |
+
+ 1.53
+ |
+
+ 0.82
+ |
+
+ GU
+ |
+
+
+ |
+ 107
+ |
+
+ R2690E
+ |
+
+ BXD
+ |
+
+ BXD55
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R2690E.CEL
+ |
+
+ 0.081
+ |
+
+ 0.067
+ |
+
+ 1.887
+ |
+
+ 164.01
+ |
+
+ 56.10%
+ |
+
+ 42.30%
+ |
+
+ 1.60%
+ |
+
+ 1.43
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 108
+ |
+
+ R2694E
+ |
+
+ BXD
+ |
+
+ BXD6
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R2694E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.018
+ |
+
+ 1.983
+ |
+
+ 97.23
+ |
+
+ 61.60%
+ |
+
+ 37.10%
+ |
+
+ 1.30%
+ |
+
+ 1.39
+ |
+
+ 0.82
+ |
+
+ GU
+ |
+
+
+ |
+ 109
+ |
+
+ R975E
+ |
+
+ BXD
+ |
+
+ BXD70
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R975E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.024
+ |
+
+ 1.841
+ |
+
+ 137.97
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.40%
+ |
+
+ 1.36
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 110
+ |
+
+ R2684E
+ |
+
+ BXD
+ |
+
+ BXD61
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2684E.CEL
+ |
+
+ 0.031
+ |
+
+ 0.032
+ |
+
+ 2.01
+ |
+
+ 131.03
+ |
+
+ 57.00%
+ |
+
+ 41.50%
+ |
+
+ 1.50%
+ |
+
+ 1.34
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 111
+ |
+
+ R994E
+ |
+
+ BXD
+ |
+
+ BXD43
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R994E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.014
+ |
+
+ 1.966
+ |
+
+ 113.12
+ |
+
+ 60.80%
+ |
+
+ 37.80%
+ |
+
+ 1.40%
+ |
+
+ 1.66
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 112
+ |
+
+ R2610E
+ |
+
+ BXD
+ |
+
+ BXD44
+ |
+
+ 68
+ |
+
+ M
+ |
+
+ R2610E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.009
+ |
+
+ 1.814
+ |
+
+ 142.91
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.35
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 113
+ |
+
+ R2689E
+ |
+
+ BXD
+ |
+
+ BXD65
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2689E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.008
+ |
+
+ 1.721
+ |
+
+ 142.44
+ |
+
+ 59.90%
+ |
+
+ 38.60%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.76
+ |
+
+ GU
+ |
+
+
+ |
+ 114
+ |
+
+ R2727E
+ |
+
+ BXD
+ |
+
+ BXD69
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R2727E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.008
+ |
+
+ 1.578
+ |
+
+ 143.86
+ |
+
+ 60.30%
+ |
+
+ 38.30%
+ |
+
+ 1.40%
+ |
+
+ 1.34
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 115
+ |
+
+ R2726E
+ |
+
+ BXD
+ |
+
+ BXD68
+ |
+
+ 64
+ |
+
+ M
+ |
+
+ R2726E.CEL
+ |
+
+ 0.125
+ |
+
+ 0.025
+ |
+
+ 1.811
+ |
+
+ 153.09
+ |
+
+ 58.70%
+ |
+
+ 39.80%
+ |
+
+ 1.50%
+ |
+
+ 1.39
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 116
+ |
+
+ R2732E
+ |
+
+ BXD
+ |
+
+ BXD45
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2732E.CEL
+ |
+
+ 0.039
+ |
+
+ 0.036
+ |
+
+ 2.154
+ |
+
+ 122.45
+ |
+
+ 56.50%
+ |
+
+ 42.10%
+ |
+
+ 1.40%
+ |
+
+ 1.8
+ |
+
+ 0.83
+ |
+
+ GU
+ |
+
+
+ |
+ 117
+ |
+
+ R2709E
+ |
+
+ BXD
+ |
+
+ BXD8
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2709E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.011
+ |
+
+ 1.99
+ |
+
+ 99.79
+ |
+
+ 60.90%
+ |
+
+ 37.60%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.76
+ |
+
+ GU
+ |
+
+
+ |
+ 118
+ |
+
+ R2686E
+ |
+
+ BXD
+ |
+
+ BXD80
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2686E.CEL
+ |
+
+ 0.046
+ |
+
+ 0.05
+ |
+
+ 2.342
+ |
+
+ 119.63
+ |
+
+ 56.00%
+ |
+
+ 42.60%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 119
+ |
+
+ R2692E
+ |
+
+ BXD
+ |
+
+ BXD85
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2692E.CEL
+ |
+
+ 0.006
+ |
+
+ 0.007
+ |
+
+ 1.423
+ |
+
+ 160.87
+ |
+
+ 60.20%
+ |
+
+ 38.30%
+ |
+
+ 1.40%
+ |
+
+ 1.46
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 120
+ |
+
+ R2715E
+ |
+
+ BXD
+ |
+
+ BXD85
+ |
+
+ 91
+ |
+
+ M
+ |
+
+ R2715E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.008
+ |
+
+ 1.488
+ |
+
+ 142.6
+ |
+
+ 61.20%
+ |
+
+ 37.30%
+ |
+
+ 1.40%
+ |
+
+ 1.5
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 121
+ |
+
+ R1405E
+ |
+
+ BXD
+ |
+
+ BXD86
+ |
+
+ 58
+ |
+
+ F
+ |
+
+ R1405E.CEL
+ |
+
+ 0.053
+ |
+
+ 0.052
+ |
+
+ 2.351
+ |
+
+ 119.34
+ |
+
+ 56.40%
+ |
+
+ 42.20%
+ |
+
+ 1.40%
+ |
+
+ 1.64
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 122
+ |
+
+ R2724E
+ |
+
+ BXD
+ |
+
+ BXD87
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2724E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.019
+ |
+
+ 1.906
+ |
+
+ 113.71
+ |
+
+ 60.70%
+ |
+
+ 37.90%
+ |
+
+ 1.40%
+ |
+
+ 1.45
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 123
+ |
+
+ R1451E
+ |
+
+ BXD
+ |
+
+ BXD34
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R1451E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.009
+ |
+
+ 1.843
+ |
+
+ 140.05
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 124
+ |
+
+ R1433E
+ |
+
+ BXD
+ |
+
+ BXD89
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R1433E.CEL
+ |
+
+ 0.029
+ |
+
+ 0.026
+ |
+
+ 2.241
+ |
+
+ 115.86
+ |
+
+ 57.70%
+ |
+
+ 40.80%
+ |
+
+ 1.50%
+ |
+
+ 1.41
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 125
+ |
+
+ R2733E
+ |
+
+ BXD
+ |
+
+ BXD96
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2733E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.054
+ |
+
+ 1.7
+ |
+
+ 113.99
+ |
+
+ 62.10%
+ |
+
+ 36.60%
+ |
+
+ 1.30%
+ |
+
+ 1.4
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 126
+ |
+
+ R2649E
+ |
+
+ BXD
+ |
+
+ BXD97
+ |
+
+ 74
+ |
+
+ F
+ |
+
+ R2649E.CEL
+ |
+
+ 0.029
+ |
+
+ 0.032
+ |
+
+ 2.343
+ |
+
+ 119.04
+ |
+
+ 57.50%
+ |
+
+ 41.20%
+ |
+
+ 1.40%
+ |
+
+ 1.53
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 127
+ |
+
+ R2688E
+ |
+
+ BXD
+ |
+
+ BXD98
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2688E.CEL
+ |
+
+ 0.032
+ |
+
+ 0.03
+ |
+
+ 1.772
+ |
+
+ 145.24
+ |
+
+ 58.50%
+ |
+
+ 40.00%
+ |
+
+ 1.50%
+ |
+
+ 1.48
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 128
+ |
+
+ R877E
+ |
+
+ BXD
+ |
+
+ BXD13
+ |
+
+ 76
+ |
+
+ M
+ |
+
+ R877E.CEL
+ |
+
+ 0.026
+ |
+
+ 0.067
+ |
+
+ 1.558
+ |
+
+ 125.63
+ |
+
+ 61.20%
+ |
+
+ 37.50%
+ |
+
+ 1.20%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 129
+ |
+
+ R1397E-re
+ |
+
+ BXD
+ |
+
+ BXD75
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R1397E-re.CEL
+ |
+
+ 0.032
+ |
+
+ 0.01
+ |
+
+ 1.449
+ |
+
+ 189.71
+ |
+
+ 59.60%
+ |
+
+ 39.00%
+ |
+
+ 1.40%
+ |
+
+ 1.39
+ |
+
+ 0.82
+ |
+
+ GU
+ |
+
+
+ |
+ 130
+ |
+
+ R2779E
+ |
+
+ BXD
+ |
+
+ BXD73
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2779E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.038
+ |
+
+ 1.746
+ |
+
+ 121.11
+ |
+
+ 59.60%
+ |
+
+ 39.00%
+ |
+
+ 1.40%
+ |
+
+ 1.5
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 131
+ |
+
+ R2708E
+ |
+
+ BXD
+ |
+
+ BXD9
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2708E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.045
+ |
+
+ 1.966
+ |
+
+ 126.46
+ |
+
+ 57.70%
+ |
+
+ 40.70%
+ |
+
+ 1.50%
+ |
+
+ 1.4
+ |
+
+ 0.84
+ |
+
+ GU
+ |
+
+
+ |
+ 132
+ |
+
+ R2547E1
+ |
+
+ GDP
+ |
+
+ WSB/Ei
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2547E.CEL
+ |
+
+ 0.041
+ |
+
+ 0.039
+ |
+
+ 2.14
+ |
+
+ 90
+ |
+
+ 58.20%
+ |
+
+ 40.10%
+ |
+
+ 1.60%
+ |
+
+ 1.32
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0608_r/summary.rtf b/general/datasets/Eye_m2_0608_r/summary.rtf
new file mode 100644
index 0000000..58d1226
--- /dev/null
+++ b/general/datasets/Eye_m2_0608_r/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 61, Name: Eye M430v2 (Sep08) RMA
\ No newline at end of file
diff --git a/general/datasets/Eye_m2_0906_r/acknowledgment.rtf b/general/datasets/Eye_m2_0906_r/acknowledgment.rtf
new file mode 100644
index 0000000..3f040d2
--- /dev/null
+++ b/general/datasets/Eye_m2_0906_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant. All arrays were processed at the VA Medical Center, Memphis by Weikuan Gu.
diff --git a/general/datasets/Eye_m2_0906_r/cases.rtf b/general/datasets/Eye_m2_0906_r/cases.rtf
new file mode 100644
index 0000000..5cb5539
--- /dev/null
+++ b/general/datasets/Eye_m2_0906_r/cases.rtf
@@ -0,0 +1,50 @@
+We used a set of 55 BXD recombinant inbred strains, 14 conventional inbred strains including C57BL/6J (B6) and DBA/2J (D2), and their reciprocal F1s. BXD strains were generated by crossing C57BL/6J with DBA/2J. The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage of D2). Physical maps in WebQTL incorporate approximately 2 million B6 vs D2 SNPs from Celera Genomics and from the Perlegen-NIEHS sequencing effort. BXD1 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+Please note that BXD24/TyJ (JAX stock number 000031) used in this study is also known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 stock that has now been rederived, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control.
+
+BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues.
+
+Mouse Diversity Panel (MDP). In addition to the BXD strains, we have profiled a MDP consisting 14 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/LtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ) have been included in the MDP. Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) also carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene.
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase-negative albino (c) mutant
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list. A tyrosinase-negative albino (c) mutant
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list. Important to note for this Eye dataset, C3H/HeJ is a Pdeb6 mutant with near total photoreceptor loss at maturity.
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1, aka F1 in some graphs and tables
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J. These reciprocal F1 can be used to detect some imprinted genes.
+
diff --git a/general/datasets/Eye_m2_0906_r/notes.rtf b/general/datasets/Eye_m2_0906_r/notes.rtf
new file mode 100644
index 0000000..39475ab
--- /dev/null
+++ b/general/datasets/Eye_m2_0906_r/notes.rtf
@@ -0,0 +1,18 @@
+This study includes the following datasets:
+
+
+ -
+
Eye M430v2 (Apr06) RMA
+
+ -
+
Eye M430v2 (Apr06) PDNN
+
+ -
+
Eye M430v2 (Apr06) MAS5
+
+ -
+
Eye M430v2 (Sep06) RMA
+
+
+
+This text file originally generated by RWW, May 26, 2006. Updated by RWW, May 27, 2006.
diff --git a/general/datasets/Eye_m2_0906_r/platform.rtf b/general/datasets/Eye_m2_0906_r/platform.rtf
new file mode 100644
index 0000000..ac743ee
--- /dev/null
+++ b/general/datasets/Eye_m2_0906_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are near duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequences as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
diff --git a/general/datasets/Eye_m2_0906_r/processing.rtf b/general/datasets/Eye_m2_0906_r/processing.rtf
new file mode 100644
index 0000000..d23bc47
--- /dev/null
+++ b/general/datasets/Eye_m2_0906_r/processing.rtf
@@ -0,0 +1,20 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. The CEL files were processed using the RMA protocol. We processed the two batches together in RMA.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 7: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
+After RMA processing all arrays were rank-order normalized. This second round of quantile normalization removes much residual non-linearity across arrays and forces every array to have the same distribution of values as the mean of all arrays. Comparative array data quality was then evaluated in DataDesk. Outlier arrays were flagged by visual inspection in DataDesk, usually by means of an analysis of scatter plots and more quantitatively by generating a correlation matrix of all arrays. Those arrays with mean correlation <0.96 versus all other arrays indicates trouble or a biological outlier). In some cases, outliers were expected, such as samples from strains with retinal degeneration (C3H/HeJ and BXD24) and samples from wild subspecies such as CAST/Ei, PWD/Ph, and PWK/Ph. However, when arrays were anomolous both within strain and across strains, they were often simply discarded. We tended to keep arrays that "conformed" to the expectation. The assumption in these cases is that anomolous data are much more likely due to experimental problem and errors than to informative biological variation. Approximately 8 arrays total were discarded in batches 1 and 2 combined.
+
+After this process, the acceptable set of arrays was renormalized using all step as above, starting with the original RMA procedure, etc.
+
+We then categorized arrays into XXX major "technical groups" depending on expression patterns as noted in scatterplots. This process of defining technical groups was done in DataDesk by manually "typing" arrays. These technical groups are apparently due to subtle within-batch effect that we do not yet understand and that cannot be corrected by quantile normalization. These XXX major technical groups are not obviously related to strain, sex, age, or any other known biological effect or variable. They are also not obviously related to any of the Affymetrix QC data types (3'/5' ratios, gain, etc.). Once the technical groups were defined, we forced the means of each probe set in the XX technical groups to the same value. This simple process partially removes a technical error of unknown origin in large expression array data sets.
+
+We reviewed the final data set using a new method developed by RW Williams, Jeremy Peirce, and Hongqiang Li. For the full set of 140 arrays that passed standard QC protocols described above, we computed the strain means for the BXD strains, B6, D2, and F1s. Using this set of strain means we then computed LRS scores for all 45101 probe sets and counted the number of transcripts that generated QTLs with LRS values greater than 50. This value (e.g. 1000) represented the QTL harvest for the full data set. We then dropped a single array from the data set (n = 139 arrays), recomputed strain means, and recomputed the number of transcripts with LRS scores great than 50. This value is expected to typically reduce the number of QTLs that reach the criterion level (e.g., 950 QTLs > 50). This process was repeated for every array to obtain an array-specific difference value--the effect of removing that array on the total QTL count. For example, the loss of a single array might cause a decrease in 50 QTLs (1000-950). Values ranged from -90 (good0 to +38 (bad). This procedure is similar in some ways to a jackknife protocol, although we are not using this procedure to esimate an error term, but rather as a final method to polish a data set. By applying this procedure we discovered that a set of XX (7?) arrays could be excluded while simultaneously improving the total number of QTLs with values above 50.
+
+During this final process we discovered that nearly XX arrays in the second batch had been mislabeled at some point in processing. We computed the correct strain membership of each array using a large number of Mendelian probe sets (more than 50) and comparing their match to standard SNP and microsatellite markers and the original array data set of November 2005. This allowed us to rescue a large number of arrays that were of very high quality.
+
diff --git a/general/datasets/Eye_m2_0906_r/summary.rtf b/general/datasets/Eye_m2_0906_r/summary.rtf
new file mode 100644
index 0000000..68a4484
--- /dev/null
+++ b/general/datasets/Eye_m2_0906_r/summary.rtf
@@ -0,0 +1,3 @@
+
+SUPERCEDED EYE DATA SET. The HEIMED April 2006 data set provides estimates of mRNA expression in whole eyes of 71 lines of young adult mice generated using 132 Affymetrix M430 2.0 arrays. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). We used pooled RNA samples, usually two independent pools; one male, one female, for each straion. This data set was processed using the RMA protocol. To simplify comparison among different transforms, RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Eye_m2_0906_r/tissue.rtf b/general/datasets/Eye_m2_0906_r/tissue.rtf
new file mode 100644
index 0000000..d8d345f
--- /dev/null
+++ b/general/datasets/Eye_m2_0906_r/tissue.rtf
@@ -0,0 +1,7112 @@
+
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of RNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. Samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center lead by Drs. John Stuart and Weikuan Gu. All processing steps were performed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. centrigrade until use (one third roughly) or were immediately used for hybridization.
+
+Dealing with Ocular Pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations taken from brown and beige colored mice tend to have faint residual pigmentation that affects hybridization signal. The key determinant of this interesting effect is the Tyrp1 (brown) locus on Chr 4 at about 80 Mb. Loci on Chr 4 that map at this location should be considered with skepticism and reviewed carefully. To address this problem Yan Jiao purified total RNA a second time using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204). This was done for 8 colored samples (R2534E2, R2578E2, R1441E2, R2537E2, R2536E2, R2589E2, R2539E2) in the first batch of arrays (the November 05 data set) of which 5 were finally included in this data set (cases in which the strain ID is labeled with asterisks in the table). This same protocol was used for all samples in the second batch added in April 2006.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. The first and second batches of array data, collectively represents a reasonably well balanced sample of males and females belonging to 62 strains, but without within-strain-by-sex replication. Six strains are represented only by male sample pools (BXD15, 28, 29, 55, 98, and DBA/2J. Four strains are represented only by a female pool sample (BXD1, 27, 73 and 86). Please use the probe sets 1427262_at (Xist, high in females) and probe set 1426438_at (Ddx3y, high in males) as quantitative surrogates for the sex balance in this data set.
+
+Batch Structure: This data set consists of a two batches: the original batch that makes up the November 2005 data set and a new batch of 63 arrays (R0857E through R2649E, and R2682E through R2742E, non-consecutive identifiers) run in January 2006 by Dr. Yan Jiao. The arrays in the two batches are from two different lots. All arrays in the second batch were from Lot 4016879 (expiration date 12.28.06). We started working with a total of 140 arrays that passed initial crude quality control based on RNA quality and initial Affymetrix report file information such as 3'/5' ratio, scale factor, and percent present calls. A total of 130 arrays were finally approved for inclusion in this April 2006 data set. The complex normalization procedure is described below.
+
+The table below summarizes information on strain, age, sex, original CEL filename, Affymetrix quality control values, and source of mice. Columns labeled "PDNN 2Z outlier" and "RMA 2Z outlier" list the fraction of probe sets with values that deviated more than 2 z units from the mean. Scale factor, background average, present, absent, marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+IN PROGRESS: PLEASE NOTE THAT THIS TABLE IS NOW BEING UPDATED TO INCLUDE BATCH 2 OF EARLY 2006.
+
+
+
+
+
+ | ID |
+
+ tube ID
+ |
+
+ group_type
+ |
+
+ Strain
+ |
+
+ age
+ |
+
+ Sex
+ |
+
+ original
+
+ CEL
+
+ filename
+ |
+
+ PDNN
+
+ 2Z
+
+ outlier
+ |
+
+ RMA
+
+ 2Z
+
+ outlier
+ |
+
+ scale
+
+ factor
+ |
+
+ background
+
+ average
+ |
+
+ present
+ |
+
+ absent
+ |
+
+ marginal
+ |
+
+ AFFX-b-
+
+ ActinMur(3'/5')
+ |
+
+ AFFX-
+
+ GapdhMur(3'/5')
+ |
+
+ Source
+ |
+
+
+ |
+ 1
+ |
+
+ R2533E1
+ |
+
+ GDP
+ |
+
+ 129S1/SvImJ
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2533E.CEL
+ |
+
+ 0.025
+ |
+
+ 0.028
+ |
+
+ 2.11
+ |
+
+ 94
+ |
+
+ 57.90%
+ |
+
+ 40.50%
+ |
+
+ 1.60%
+ |
+
+ 1.37
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 2
+ |
+
+ R2595E1
+ |
+
+ GDP
+ |
+
+ 129S1/SvImJ
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2595E.CEL
+ |
+
+ 0.033
+ |
+
+ 0.036
+ |
+
+ 1.79
+ |
+
+ 115
+ |
+
+ 61.00%
+ |
+
+ 37.50%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 3
+ |
+
+ R0754E2
+ |
+
+ GDP
+ |
+
+ A/J
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R0754E.CEL
+ |
+
+ 0.027
+ |
+
+ 0.03
+ |
+
+ 2.72
+ |
+
+ 86
+ |
+
+ 59.80%
+ |
+
+ 38.70%
+ |
+
+ 1.50%
+ |
+
+ 1.36
+ |
+
+ 0.76
+ |
+
+ JAX
+ |
+
+
+ |
+ 4
+ |
+
+ R2546E1
+ |
+
+ GDP
+ |
+
+ A/J
+ |
+
+ 66
+ |
+
+ F
+ |
+
+ R2545E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.029
+ |
+
+ 1.99
+ |
+
+ 96
+ |
+
+ 58.60%
+ |
+
+ 39.70%
+ |
+
+ 1.70%
+ |
+
+ 1.47
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 5
+ |
+
+ R2601E1
+ |
+
+ GDP BXD
+ |
+
+ B6D2F1
+ |
+
+ 73
+ |
+
+ F
+ |
+
+ R2601E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.008
+ |
+
+ 2.55
+ |
+
+ 92
+ |
+
+ 58.90%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.44
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 6
+ |
+
+ R2602E1
+ |
+
+ GDP BXD
+ |
+
+ B6D2F1
+ |
+
+ 73
+ |
+
+ M
+ |
+
+ R2602E.CEL
+ |
+
+ 0.003
+ |
+
+ 0.008
+ |
+
+ 2.60
+ |
+
+ 84
+ |
+
+ 59.70%
+ |
+
+ 38.80%
+ |
+
+ 1.50%
+ |
+
+ 1.37
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 7
+ |
+
+ R1672E1
+ |
+
+ GDP
+ |
+
+ BALB/cByJ
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R1672E.CEL
+ |
+
+ 0.043
+ |
+
+ 0.039
+ |
+
+ 2.22
+ |
+
+ 111
+ |
+
+ 59.90%
+ |
+
+ 38.60%
+ |
+
+ 1.50%
+ |
+
+ 1.26
+ |
+
+ 0.80
+ |
+
+ JAX
+ |
+
+
+ |
+ 8
+ |
+
+ R1676E1
+ |
+
+ GDP
+ |
+
+ BALB/cByJ
+ |
+
+ 83
+ |
+
+ F
+ |
+
+ R1676E.CEL
+ |
+
+ 0.083
+ |
+
+ 0.085
+ |
+
+ 2.69
+ |
+
+ 98
+ |
+
+ 58.90%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.74
+ |
+
+ JAX
+ |
+
+
+ |
+ 9
+ |
+
+ R2581E1
+ |
+
+ BXD
+ |
+
+ BXD11
+ |
+
+ 65
+ |
+
+ F
+ |
+
+ R2581E.CEL
+ |
+
+ 0.009
+ |
+
+ 0.021
+ |
+
+ 1.94
+ |
+
+ 89
+ |
+
+ 62.10%
+ |
+
+ 36.40%
+ |
+
+ 1.60%
+ |
+
+ 1.55
+ |
+
+ 0.81
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 10
+ |
+
+ R2543E1
+ |
+
+ BXD
+ |
+
+ BXD12
+ |
+
+ 63
+ |
+
+ M
+ |
+
+ R2543E.CEL
+ |
+
+ 0.018
+ |
+
+ 0.017
+ |
+
+ 1.61
+ |
+
+ 118
+ |
+
+ 58.60%
+ |
+
+ 39.90%
+ |
+
+ 1.60%
+ |
+
+ 1.43
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 11
+ |
+
+ R2586E1
+ |
+
+ BXD
+ |
+
+ BXD13
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2586E.CEL
+ |
+
+ 0.259
+ |
+
+ 0.258
+ |
+
+ 2.01
+ |
+
+ 74
+ |
+
+ 56.40%
+ |
+
+ 42.00%
+ |
+
+ 1.60%
+ |
+
+ 2.85
+ |
+
+ 3.81
+ |
+
+ Glenn
+ |
+
+
+ |
+ 12
+ |
+
+ R2557E1
+ |
+
+ BXD
+ |
+
+ BXD14
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2557E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.027
+ |
+
+ 1.83
+ |
+
+ 99
+ |
+
+ 62.50%
+ |
+
+ 36.10%
+ |
+
+ 1.40%
+ |
+
+ 1.31
+ |
+
+ 0.78
+ |
+
+ Glenn
+ |
+
+
+ |
+ 13
+ |
+
+ R2567E1
+ |
+
+ BXD
+ |
+
+ BXD16
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2567E.CEL
+ |
+
+ 0.048
+ |
+
+ 0.058
+ |
+
+ 2.24
+ |
+
+ 82
+ |
+
+ 56.70%
+ |
+
+ 41.60%
+ |
+
+ 1.70%
+ |
+
+ 1.37
+ |
+
+ 0.75
+ |
+
+ Glenn
+ |
+
+
+ |
+ 14
+ |
+
+ R2559E1
+ |
+
+ BXD
+ |
+
+ BXD18
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2559E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.012
+ |
+
+ 1.65
+ |
+
+ 104
+ |
+
+ 60.80%
+ |
+
+ 37.70%
+ |
+
+ 1.50%
+ |
+
+ 1.27
+ |
+
+ 0.78
+ |
+
+ Glenn
+ |
+
+
+ |
+ 15
+ |
+
+ R2560E1
+ |
+
+ BXD
+ |
+
+ BXD19
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2560E.CEL
+ |
+
+ 0.009
+ |
+
+ 0.012
+ |
+
+ 1.79
+ |
+
+ 98
+ |
+
+ 60.90%
+ |
+
+ 37.50%
+ |
+
+ 1.60%
+ |
+
+ 1.35
+ |
+
+ 0.80
+ |
+
+ Glenn
+ |
+
+
+ |
+ 16
+ |
+
+ R2597E1
+ |
+
+ BXD
+ |
+
+ BXD2
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2597E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.012
+ |
+
+ 2.37
+ |
+
+ 94
+ |
+
+ 60.30%
+ |
+
+ 38.30%
+ |
+
+ 1.50%
+ |
+
+ 1.34
+ |
+
+ 0.77
+ |
+
+ Glenn
+ |
+
+
+ |
+ 17
+ |
+
+ R2584E1
+ |
+
+ BXD
+ |
+
+ BXD20
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2584E.CEL
+ |
+
+ 0.011
+ |
+
+ 0.017
+ |
+
+ 2.07
+ |
+
+ 84
+ |
+
+ 59.30%
+ |
+
+ 39.10%
+ |
+
+ 1.60%
+ |
+
+ 1.40
+ |
+
+ 0.76
+ |
+
+ Glenn
+ |
+
+
+ |
+ 18
+ |
+
+ R2541E2
+ |
+
+ BXD
+ |
+
+ BXD21
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2541E2.CEL
+ |
+
+ 0.049
+ |
+
+ 0.084
+ |
+
+ 2.63
+ |
+
+ 125
+ |
+
+ 56.00%
+ |
+
+ 42.40%
+ |
+
+ 1.50%
+ |
+
+ 1.29
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 19
+ |
+
+ R2553E1
+ |
+
+ BXD
+ |
+
+ BXD22
+ |
+
+ 58
+ |
+
+ F
+ |
+
+ R2553E.CEL
+ |
+
+ 0.004
+ |
+
+ 0.01
+ |
+
+ 1.95
+ |
+
+ 111
+ |
+
+ 59.90%
+ |
+
+ 38.50%
+ |
+
+ 1.50%
+ |
+
+ 1.28
+ |
+
+ 0.76
+ |
+
+ Glenn
+ |
+
+
+ |
+ 20
+ |
+
+ R2558E1
+ |
+
+ BXD
+ |
+
+ BXD23
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2558E-2.CEL
+ |
+
+ 0.018
+ |
+
+ 0.027
+ |
+
+ 1.91
+ |
+
+ 115
+ |
+
+ 59.90%
+ |
+
+ 38.80%
+ |
+
+ 1.40%
+ |
+
+ 1.20
+ |
+
+ 0.82
+ |
+
+ Glenn
+ |
+
+
+ |
+ 21
+ |
+
+ R2589E2
+ |
+
+ BXD
+ |
+
+ BXD24
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2589E2.CEL
+ |
+
+ 0.132
+ |
+
+ 0.176
+ |
+
+ 2.61
+ |
+
+ 112
+ |
+
+ 57.50%
+ |
+
+ 40.90%
+ |
+
+ 1.60%
+ |
+
+ 1.24
+ |
+
+ 0.80
+ |
+
+ Glenn
+ |
+
+
+ |
+ 22
+ |
+
+ R2573E1
+ |
+
+ BXD
+ |
+
+ BXD25
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2573E-2.CEL
+ |
+
+ 0.055
+ |
+
+ 0.063
+ |
+
+ 3.15
+ |
+
+ 72
+ |
+
+ 57.90%
+ |
+
+ 40.70%
+ |
+
+ 1.40%
+ |
+
+ 1.77
+ |
+
+ 0.97
+ |
+
+ UAB
+ |
+
+
+ |
+ 23
+ |
+
+ R2562E1
+ |
+
+ BXD
+ |
+
+ BXD29
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2562E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.01
+ |
+
+ 1.65
+ |
+
+ 116
+ |
+
+ 59.90%
+ |
+
+ 38.40%
+ |
+
+ 1.70%
+ |
+
+ 1.37
+ |
+
+ 0.79
+ |
+
+ Glenn
+ |
+
+
+ |
+ 24
+ |
+
+ R2598E1
+ |
+
+ BXD
+ |
+
+ BXD31
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2598E.CEL
+ |
+
+ 0.006
+ |
+
+ 0.013
+ |
+
+ 1.99
+ |
+
+ 106
+ |
+
+ 60.90%
+ |
+
+ 37.60%
+ |
+
+ 1.50%
+ |
+
+ 1.27
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 25
+ |
+
+ R2563E1
+ |
+
+ BXD
+ |
+
+ BXD32
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2563E.CEL
+ |
+
+ 0.023
+ |
+
+ 0.025
+ |
+
+ 1.55
+ |
+
+ 102
+ |
+
+ 61.90%
+ |
+
+ 36.70%
+ |
+
+ 1.40%
+ |
+
+ 1.50
+ |
+
+ 0.80
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 26
+ |
+
+ R2542E1
+ |
+
+ BXD
+ |
+
+ BXD33
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2542E.CEL
+ |
+
+ 0.058
+ |
+
+ 0.062
+ |
+
+ 2.13
+ |
+
+ 97
+ |
+
+ 56.50%
+ |
+
+ 41.80%
+ |
+
+ 1.60%
+ |
+
+ 1.91
+ |
+
+ 0.93
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 27
+ |
+
+ R2585E1
+ |
+
+ BXD
+ |
+
+ BXD34
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2585E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.032
+ |
+
+ 2.64
+ |
+
+ 75
+ |
+
+ 58.30%
+ |
+
+ 40.00%
+ |
+
+ 1.70%
+ |
+
+ 1.25
+ |
+
+ 0.77
+ |
+
+ Glenn
+ |
+
+
+ |
+ 28
+ |
+
+ R2532E1
+ |
+
+ BXD
+ |
+
+ BXD38
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2532E.CEL
+ |
+
+ 0.002
+ |
+
+ 0.006
+ |
+
+ 2.04
+ |
+
+ 94
+ |
+
+ 59.80%
+ |
+
+ 38.70%
+ |
+
+ 1.50%
+ |
+
+ 1.37
+ |
+
+ 0.80
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 29
+ |
+
+ R2574E1
+ |
+
+ BXD
+ |
+
+ BXD39
+ |
+
+ 70
+ |
+
+ F
+ |
+
+ R2574E.CEL
+ |
+
+ 0.003
+ |
+
+ 0.008
+ |
+
+ 1.98
+ |
+
+ 91
+ |
+
+ 61.20%
+ |
+
+ 37.30%
+ |
+
+ 1.50%
+ |
+
+ 1.39
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 30
+ |
+
+ R2590E1
+ |
+
+ BXD
+ |
+
+ BXD40
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2590E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.012
+ |
+
+ 2.71
+ |
+
+ 77
+ |
+
+ 59.10%
+ |
+
+ 39.30%
+ |
+
+ 1.50%
+ |
+
+ 1.40
+ |
+
+ 0.77
+ |
+
+ Glenn
+ |
+
+
+ |
+ 31
+ |
+
+ R2596E1
+ |
+
+ BXD
+ |
+
+ BXD42
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2596E.CEL
+ |
+
+ 0.016
+ |
+
+ 0.03
+ |
+
+ 2.63
+ |
+
+ 108
+ |
+
+ 59.00%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.24
+ |
+
+ 0.80
+ |
+
+ Glenn
+ |
+
+
+ |
+ 32
+ |
+
+ R2605E1
+ |
+
+ BXD
+ |
+
+ BXD43
+ |
+
+ 79
+ |
+
+ M
+ |
+
+ R2607E.CEL
+ |
+
+ 0.006
+ |
+
+ 0.01
+ |
+
+ 1.82
+ |
+
+ 131
+ |
+
+ 60.50%
+ |
+
+ 38.20%
+ |
+
+ 1.30%
+ |
+
+ 1.32
+ |
+
+ 0.80
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 33
+ |
+
+ R2594E1
+ |
+
+ BXD
+ |
+
+ BXD44
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2594E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.024
+ |
+
+ 1.77
+ |
+
+ 117
+ |
+
+ 59.80%
+ |
+
+ 38.80%
+ |
+
+ 1.40%
+ |
+
+ 1.35
+ |
+
+ 0.85
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 34
+ |
+
+ R2592E1
+ |
+
+ BXD
+ |
+
+ BXD45
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2592E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.011
+ |
+
+ 1.85
+ |
+
+ 106
+ |
+
+ 60.10%
+ |
+
+ 38.60%
+ |
+
+ 1.30%
+ |
+
+ 1.43
+ |
+
+ 0.85
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 35
+ |
+
+ R2606E1
+ |
+
+ BXD
+ |
+
+ BXD48
+ |
+
+ 78
+ |
+
+ M
+ |
+
+ R2606E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.015
+ |
+
+ 2.56
+ |
+
+ 106
+ |
+
+ 58.90%
+ |
+
+ 39.70%
+ |
+
+ 1.40%
+ |
+
+ 1.35
+ |
+
+ 0.83
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 36
+ |
+
+ R2591E1
+ |
+
+ BXD
+ |
+
+ BXD5
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2591E.CEL
+ |
+
+ 0.052
+ |
+
+ 0.014
+ |
+
+ 1.70
+ |
+
+ 136
+ |
+
+ 58.50%
+ |
+
+ 40.00%
+ |
+
+ 1.50%
+ |
+
+ 1.33
+ |
+
+ 0.78
+ |
+
+ Glenn
+ |
+
+
+ |
+ 37
+ |
+
+ R2603E1
+ |
+
+ BXD
+ |
+
+ BXD51
+ |
+
+ 66
+ |
+
+ F
+ |
+
+ R2603E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.02
+ |
+
+ 2.49
+ |
+
+ 115
+ |
+
+ 57.70%
+ |
+
+ 40.80%
+ |
+
+ 1.50%
+ |
+
+ 1.24
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 38
+ |
+
+ R2570E1
+ |
+
+ BXD
+ |
+
+ BXD6
+ |
+
+ 65
+ |
+
+ F
+ |
+
+ R2570E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.017
+ |
+
+ 1.99
+ |
+
+ 87
+ |
+
+ 58.50%
+ |
+
+ 40.00%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.76
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 39
+ |
+
+ R2534E2
+ |
+
+ BXD
+ |
+
+ BXD61
+ |
+
+ 70
+ |
+
+ F
+ |
+
+ R2534E2.CEL
+ |
+
+ 0.03
+ |
+
+ 0.058
+ |
+
+ 2.47
+ |
+
+ 118
+ |
+
+ 57.90%
+ |
+
+ 40.60%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 40
+ |
+
+ R2611E1
+ |
+
+ BXD
+ |
+
+ BXD64
+ |
+
+ 68
+ |
+
+ M
+ |
+
+ R2611E.CEL
+ |
+
+ 0.067
+ |
+
+ 0.068
+ |
+
+ 2.29
+ |
+
+ 92
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.50%
+ |
+
+ 1.57
+ |
+
+ 1.06
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 41
+ |
+
+ R2583E1
+ |
+
+ BXD
+ |
+
+ BXD65
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2583E.CEL
+ |
+
+ 0.027
+ |
+
+ 0.03
+ |
+
+ 2.49
+ |
+
+ 70
+ |
+
+ 56.90%
+ |
+
+ 41.50%
+ |
+
+ 1.60%
+ |
+
+ 1.67
+ |
+
+ 1.01
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 42
+ |
+
+ R2536E2
+ |
+
+ BXD
+ |
+
+ BXD66
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2536E2.CEL
+ |
+
+ 0.067
+ |
+
+ 0.139
+ |
+
+ 2.74
+ |
+
+ 109
+ |
+
+ 56.10%
+ |
+
+ 42.30%
+ |
+
+ 1.70%
+ |
+
+ 1.28
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 43
+ |
+
+ R2551E1
+ |
+
+ BXD
+ |
+
+ BXD68
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2551E.CEL
+ |
+
+ 0.294
+ |
+
+ 0.291
+ |
+
+ 2.49
+ |
+
+ 92
+ |
+
+ 54.30%
+ |
+
+ 44.10%
+ |
+
+ 1.60%
+ |
+
+ 2.91
+ |
+
+ 1.55
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 44
+ |
+
+ R2593E1
+ |
+
+ BXD
+ |
+
+ BXD69
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2593E.CEL
+ |
+
+ 0.027
+ |
+
+ 0.038
+ |
+
+ 1.67
+ |
+
+ 128
+ |
+
+ 59.20%
+ |
+
+ 39.50%
+ |
+
+ 1.30%
+ |
+
+ 1.47
+ |
+
+ 0.92
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 45
+ |
+
+ R2537E2
+ |
+
+ BXD
+ |
+
+ BXD70
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2537E2.CEL
+ |
+
+ 0.049
+ |
+
+ 0.092
+ |
+
+ 2.93
+ |
+
+ 99
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.60%
+ |
+
+ 1.29
+ |
+
+ 0.75
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 46
+ |
+
+ R2565E1
+ |
+
+ BXD
+ |
+
+ BXD75
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R2565E.CEL
+ |
+
+ 0.118
+ |
+
+ 0.124
+ |
+
+ 1.79
+ |
+
+ 102
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.50%
+ |
+
+ 2.31
+ |
+
+ 3.47
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 47
+ |
+
+ R2538E1
+ |
+
+ BXD
+ |
+
+ BXD8
+ |
+
+ 77
+ |
+
+ F
+ |
+
+ R2538E.CEL
+ |
+
+ 0.033
+ |
+
+ 0.056
+ |
+
+ 1.91
+ |
+
+ 102
+ |
+
+ 61.20%
+ |
+
+ 37.30%
+ |
+
+ 1.50%
+ |
+
+ 1.52
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 48
+ |
+
+ R2579E1
+ |
+
+ BXD
+ |
+
+ BXD80
+ |
+
+ 65
+ |
+
+ F
+ |
+
+ R2579E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.026
+ |
+
+ 2.42
+ |
+
+ 72
+ |
+
+ 59.20%
+ |
+
+ 39.40%
+ |
+
+ 1.50%
+ |
+
+ 1.73
+ |
+
+ 0.82
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 49
+ |
+
+ R2540E1
+ |
+
+ BXD
+ |
+
+ BXD87
+ |
+
+ 63
+ |
+
+ M
+ |
+
+ R2540E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.034
+ |
+
+ 2.33
+ |
+
+ 93
+ |
+
+ 61.10%
+ |
+
+ 37.40%
+ |
+
+ 1.40%
+ |
+
+ 1.22
+ |
+
+ 0.81
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 50
+ |
+
+ R2545E1
+ |
+
+ BXD
+ |
+
+ BXD89
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2546E.CEL
+ |
+
+ 0.266
+ |
+
+ 0.257
+ |
+
+ 1.67
+ |
+
+ 105
+ |
+
+ 56.20%
+ |
+
+ 42.30%
+ |
+
+ 1.50%
+ |
+
+ 3.60
+ |
+
+ 9.84
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 51
+ |
+
+ R2569E1
+ |
+
+ BXD
+ |
+
+ BXD9
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2569E.CEL
+ |
+
+ 0.256
+ |
+
+ 0.239
+ |
+
+ 1.75
+ |
+
+ 87
+ |
+
+ 55.10%
+ |
+
+ 43.40%
+ |
+
+ 1.50%
+ |
+
+ 2.82
+ |
+
+ 3.14
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 52
+ |
+
+ R2578E2
+ |
+
+ BXD
+ |
+
+ BXD90
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R2578E2.CEL
+ |
+
+ 0.041
+ |
+
+ 0.062
+ |
+
+ 2.79
+ |
+
+ 92
+ |
+
+ 58.60%
+ |
+
+ 39.80%
+ |
+
+ 1.60%
+ |
+
+ 1.52
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 53
+ |
+
+ R2554E1
+ |
+
+ BXD
+ |
+
+ BXD96
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2554E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.008
+ |
+
+ 2.18
+ |
+
+ 93
+ |
+
+ 60.20%
+ |
+
+ 38.30%
+ |
+
+ 1.50%
+ |
+
+ 1.46
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 54
+ |
+
+ R2577E1
+ |
+
+ BXD
+ |
+
+ BXD97
+ |
+
+ 55
+ |
+
+ M
+ |
+
+ R2577E.CEL
+ |
+
+ 0.065
+ |
+
+ 0.069
+ |
+
+ 2.07
+ |
+
+ 77
+ |
+
+ 59.50%
+ |
+
+ 39.10%
+ |
+
+ 1.40%
+ |
+
+ 1.87
+ |
+
+ 1.29
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 55
+ |
+
+ R1700E1
+ |
+
+ GDP
+ |
+
+ C3H/HeJ
+ |
+
+ 83
+ |
+
+ F
+ |
+
+ R1700E.CEL
+ |
+
+ 0.152
+ |
+
+ 0.168
+ |
+
+ 2.98
+ |
+
+ 69
+ |
+
+ 60.80%
+ |
+
+ 37.90%
+ |
+
+ 1.40%
+ |
+
+ 1.48
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 56
+ |
+
+ R1704E1
+ |
+
+ GDP
+ |
+
+ C3H/HeJ
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R1704E.CEL
+ |
+
+ 0.154
+ |
+
+ 0.165
+ |
+
+ 2.58
+ |
+
+ 88
+ |
+
+ 60.10%
+ |
+
+ 38.60%
+ |
+
+ 1.30%
+ |
+
+ 1.38
+ |
+
+ 0.84
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 57
+ |
+
+ R0872E2
+ |
+
+ GDP BXD
+ |
+
+ C57BL/6J
+ |
+
+ 66
+ |
+
+ M
+ |
+
+ R0872E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.023
+ |
+
+ 3.13
+ |
+
+ 89
+ |
+
+ 58.90%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.30
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 58
+ |
+
+ R2607E1
+ |
+
+ GDP BXD
+ |
+
+ C57BL/6J
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2605E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.018
+ |
+
+ 2.43
+ |
+
+ 115
+ |
+
+ 58.60%
+ |
+
+ 40.00%
+ |
+
+ 1.40%
+ |
+
+ 1.31
+ |
+
+ 0.76
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 59
+ |
+
+ R2564E1
+ |
+
+ GDP
+ |
+
+ CAST/Ei
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2564E.CEL
+ |
+
+ 0.124
+ |
+
+ 0.105
+ |
+
+ 1.94
+ |
+
+ 89
+ |
+
+ 58.50%
+ |
+
+ 39.90%
+ |
+
+ 1.60%
+ |
+
+ 1.60
+ |
+
+ 0.77
+ |
+
+ JAX
+ |
+
+
+ |
+ 60
+ |
+
+ R2580E1
+ |
+
+ GDP
+ |
+
+ CAST/Ei
+ |
+
+ 64
+ |
+
+ M
+ |
+
+ R2580E.CEL
+ |
+
+ 0.123
+ |
+
+ 0.109
+ |
+
+ 2.09
+ |
+
+ 95
+ |
+
+ 58.20%
+ |
+
+ 40.10%
+ |
+
+ 1.70%
+ |
+
+ 1.40
+ |
+
+ 0.76
+ |
+
+ JAX
+ |
+
+
+ |
+ 61
+ |
+
+ R2600E1
+ |
+
+ GDP BXD
+ |
+
+ D2B6F1
+ |
+
+ 72
+ |
+
+ F
+ |
+
+ R2600E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.02
+ |
+
+ 2.47
+ |
+
+ 95
+ |
+
+ 58.10%
+ |
+
+ 40.20%
+ |
+
+ 1.70%
+ |
+
+ 1.41
+ |
+
+ 0.78
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 62
+ |
+
+ R2604E1
+ |
+
+ GDP BXD
+ |
+
+ D2B6F1
+ |
+
+ 69
+ |
+
+ M
+ |
+
+ R2604E.CEL
+ |
+
+ 0.005
+ |
+
+ 0.014
+ |
+
+ 2.66
+ |
+
+ 90
+ |
+
+ 59.40%
+ |
+
+ 39.20%
+ |
+
+ 1.50%
+ |
+
+ 1.28
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 63
+ |
+
+ R2572E1
+ |
+
+ GDP BXD
+ |
+
+ DBA/2J
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R2572E.CEL
+ |
+
+ 0.091
+ |
+
+ 0.106
+ |
+
+ 2.41
+ |
+
+ 79
+ |
+
+ 55.50%
+ |
+
+ 42.90%
+ |
+
+ 1.60%
+ |
+
+ 1.37
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 64
+ |
+
+ R2636E1
+ |
+
+ GDP
+ |
+
+ KK/HIJ
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2636E.CEL
+ |
+
+ 0.044
+ |
+
+ 0.043
+ |
+
+ 2.61
+ |
+
+ 93
+ |
+
+ 58.90%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.39
+ |
+
+ 0.76
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 65
+ |
+
+ R2637E1
+ |
+
+ GDP
+ |
+
+ KK/HIJ
+ |
+
+ 64
+ |
+
+ M
+ |
+
+ R2637E.CEL
+ |
+
+ 0.056
+ |
+
+ 0.036
+ |
+
+ 2.19
+ |
+
+ 103
+ |
+
+ 59.40%
+ |
+
+ 39.00%
+ |
+
+ 1.50%
+ |
+
+ 1.30
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 66
+ |
+
+ R0999E1
+ |
+
+ GDP
+ |
+
+ LG/J
+ |
+
+ 57
+ |
+
+ F
+ |
+
+ R0999E.CEL
+ |
+
+ 0.021
+ |
+
+ 0.023
+ |
+
+ 2.45
+ |
+
+ 82
+ |
+
+ 59.40%
+ |
+
+ 39.10%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 67
+ |
+
+ R1004E1
+ |
+
+ GDP
+ |
+
+ LG/J
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R1004E.CEL
+ |
+
+ 0.025
+ |
+
+ 0.028
+ |
+
+ 2.44
+ |
+
+ 92
+ |
+
+ 58.70%
+ |
+
+ 39.80%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 68
+ |
+
+ R1688E1
+ |
+
+ GDP
+ |
+
+ NOD/LtJ
+ |
+
+ 66
+ |
+
+ F
+ |
+
+ R1688E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.033
+ |
+
+ 2.66
+ |
+
+ 98
+ |
+
+ 58.60%
+ |
+
+ 39.90%
+ |
+
+ 1.50%
+ |
+
+ 1.26
+ |
+
+ 0.80
+ |
+
+ JAX
+ |
+
+
+ |
+ 69
+ |
+
+ R2566E1
+ |
+
+ GDP
+ |
+
+ NOD/LtJ
+ |
+
+ 76
+ |
+
+ M
+ |
+
+ R2566E-2.CEL
+ |
+
+ 0.036
+ |
+
+ 0.04
+ |
+
+ 3.03
+ |
+
+ 69
+ |
+
+ 59.80%
+ |
+
+ 38.80%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.75
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 70
+ |
+
+ R2535E1
+ |
+
+ GDP
+ |
+
+ NZO/H1LtJ
+ |
+
+ 62
+ |
+
+ F
+ |
+
+ R2535E.CEL
+ |
+
+ 0.037
+ |
+
+ 0.062
+ |
+
+ 1.89
+ |
+
+ 86
+ |
+
+ 60.40%
+ |
+
+ 38.20%
+ |
+
+ 1.40%
+ |
+
+ 1.41
+ |
+
+ 0.85
+ |
+
+ JAX
+ |
+
+
+ |
+ 71
+ |
+
+ R2550E1
+ |
+
+ GDP
+ |
+
+ NZO/HILtJ
+ |
+
+ 96
+ |
+
+ M
+ |
+
+ R2550E.CEL
+ |
+
+ 0.025
+ |
+
+ 0.029
+ |
+
+ 1.79
+ |
+
+ 87
+ |
+
+ 60.70%
+ |
+
+ 37.80%
+ |
+
+ 1.50%
+ |
+
+ 1.52
+ |
+
+ 0.82
+ |
+
+ JAX
+ |
+
+
+ |
+ 72
+ |
+
+ R2634E1
+ |
+
+ GDP
+ |
+
+ PWD/PhJ
+ |
+
+ 62
+ |
+
+ F
+ |
+
+ R2635E.CEL
+ |
+
+ 0.126
+ |
+
+ 0.114
+ |
+
+ 3.29
+ |
+
+ 90
+ |
+
+ 55.90%
+ |
+
+ 42.50%
+ |
+
+ 1.60%
+ |
+
+ 1.57
+ |
+
+ 0.81
+ |
+
+ JAX
+ |
+
+
+ |
+ 73
+ |
+
+ R2635E1
+ |
+
+ GDP
+ |
+
+ PWD/PhJ
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2634E.CEL
+ |
+
+ 0.15
+ |
+
+ 0.137
+ |
+
+ 3.72
+ |
+
+ 80
+ |
+
+ 54.20%
+ |
+
+ 44.10%
+ |
+
+ 1.70%
+ |
+
+ 1.53
+ |
+
+ 0.85
+ |
+
+ JAX
+ |
+
+
+ |
+ 74
+ |
+
+ R2544E1
+ |
+
+ GDP
+ |
+
+ PWK/PhJ
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2544E.CEL
+ |
+
+ 0.174
+ |
+
+ 0.175
+ |
+
+ 2.20
+ |
+
+ 108
+ |
+
+ 54.90%
+ |
+
+ 43.50%
+ |
+
+ 1.70%
+ |
+
+ 1.36
+ |
+
+ 0.82
+ |
+
+ JAX
+ |
+
+
+ |
+ 75
+ |
+
+ R2549E1
+ |
+
+ GDP
+ |
+
+ PWK/PhJ
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R2549E.CEL
+ |
+
+ 0.103
+ |
+
+ 0.087
+ |
+
+ 2.28
+ |
+
+ 84
+ |
+
+ 57.30%
+ |
+
+ 41.20%
+ |
+
+ 1.50%
+ |
+
+ 1.57
+ |
+
+ 0.83
+ |
+
+ JAX
+ |
+
+
+ |
+ 76
+ |
+
+ R2368E1
+ |
+
+ GDP
+ |
+
+ WSB/EI
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2368E.CEL
+ |
+
+ 0.041
+ |
+
+ 0.047
+ |
+
+ 2.57
+ |
+
+ 86
+ |
+
+ 59.50%
+ |
+
+ 39.10%
+ |
+
+ 1.40%
+ |
+
+ 1.29
+ |
+
+ 0.74
+ |
+
+ UTM RW
+ |
+
+
+ |
+ 77
+ |
+
+ R2704E
+ |
+
+ BXD
+ |
+
+ BXD1
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2704E.CEL
+ |
+
+ 0.029
+ |
+
+ 0.03
+ |
+
+ 2.066
+ |
+
+ 139.61
+ |
+
+ 56.60%
+ |
+
+ 41.90%
+ |
+
+ 1.50%
+ |
+
+ 1.31
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 78
+ |
+
+ R2612E
+ |
+
+ BXD
+ |
+
+ BXD11
+ |
+
+ 70
+ |
+
+ M
+ |
+
+ R2612E.CEL
+ |
+
+ 0.101
+ |
+
+ 0.112
+ |
+
+ 1.83
+ |
+
+ 142.03
+ |
+
+ 58.20%
+ |
+
+ 40.50%
+ |
+
+ 1.40%
+ |
+
+ 1.78
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 79
+ |
+
+ R2742E
+ |
+
+ BXD
+ |
+
+ BXD12
+ |
+
+ 71
+ |
+
+ F
+ |
+
+ R2742E.CEL
+ |
+
+ 0.073
+ |
+
+ 0.077
+ |
+
+ 2.127
+ |
+
+ 134.14
+ |
+
+ 57.00%
+ |
+
+ 41.60%
+ |
+
+ 1.40%
+ |
+
+ 1.64
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 80
+ |
+
+ R1086E
+ |
+
+ BXD
+ |
+
+ BXD23
+ |
+
+ 55
+ |
+
+ M
+ |
+
+ R1086E.CEL
+ |
+
+ 0.043
+ |
+
+ 0.034
+ |
+
+ 2.233
+ |
+
+ 125.05
+ |
+
+ 58.60%
+ |
+
+ 39.90%
+ |
+
+ 1.50%
+ |
+
+ 1.43
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 81
+ |
+
+ R2716E
+ |
+
+ BXD
+ |
+
+ BXD15
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2716E.CEL
+ |
+
+ 0.035
+ |
+
+ 0.037
+ |
+
+ 2.015
+ |
+
+ 150.83
+ |
+
+ 56.40%
+ |
+
+ 42.10%
+ |
+
+ 1.60%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 82
+ |
+
+ R2711E
+ |
+
+ BXD
+ |
+
+ BXD16
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R2711E.CEL
+ |
+
+ 0.032
+ |
+
+ 0.021
+ |
+
+ 1.953
+ |
+
+ 118.53
+ |
+
+ 59.00%
+ |
+
+ 39.60%
+ |
+
+ 1.50%
+ |
+
+ 1.45
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 83
+ |
+
+ R2720E
+ |
+
+ BXD
+ |
+
+ BXD18
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2720E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.019
+ |
+
+ 2.32
+ |
+
+ 99.93
+ |
+
+ 59.50%
+ |
+
+ 39.00%
+ |
+
+ 1.50%
+ |
+
+ 1.33
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 84
+ |
+
+ R2713E
+ |
+
+ BXD
+ |
+
+ BXD19
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2713E.CEL
+ |
+
+ 0.055
+ |
+
+ 0.021
+ |
+
+ 1.67
+ |
+
+ 120.82
+ |
+
+ 60.20%
+ |
+
+ 38.30%
+ |
+
+ 1.50%
+ |
+
+ 1.45
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 85
+ |
+
+ R1231E
+ |
+
+ BXD
+ |
+
+ BXD2
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R1231E.CEL
+ |
+
+ 0.044
+ |
+
+ 0.037
+ |
+
+ 2.197
+ |
+
+ 138.73
+ |
+
+ 57.30%
+ |
+
+ 41.30%
+ |
+
+ 1.40%
+ |
+
+ 1.41
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 86
+ |
+
+ R2731E
+ |
+
+ BXD
+ |
+
+ BXD20
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2731E.CEL
+ |
+
+ 0.017
+ |
+
+ 0.019
+ |
+
+ 1.825
+ |
+
+ 147
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.4
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 87
+ |
+
+ R2702E
+ |
+
+ BXD
+ |
+
+ BXD21
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2702E.CEL
+ |
+
+ 0.009
+ |
+
+ 0.008
+ |
+
+ 1.811
+ |
+
+ 128.65
+ |
+
+ 59.40%
+ |
+
+ 39.10%
+ |
+
+ 1.40%
+ |
+
+ 1.26
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 88
+ |
+
+ R2700E
+ |
+
+ BXD
+ |
+
+ BXD22
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2700E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.015
+ |
+
+ 1.858
+ |
+
+ 102.96
+ |
+
+ 61.50%
+ |
+
+ 37.10%
+ |
+
+ 1.30%
+ |
+
+ 1.48
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 89
+ |
+
+ R1128E
+ |
+
+ BXD
+ |
+
+ BXD14
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R1128E.CEL
+ |
+
+ 0.037
+ |
+
+ 0.038
+ |
+
+ 2.366
+ |
+
+ 118.39
+ |
+
+ 57.30%
+ |
+
+ 41.30%
+ |
+
+ 1.40%
+ |
+
+ 1.45
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 90
+ |
+
+ R2719E
+ |
+
+ BXD
+ |
+
+ BXD24
+ |
+
+ 123
+ |
+
+ F
+ |
+
+ R2719E.CEL
+ |
+
+ 0.112
+ |
+
+ 0.111
+ |
+
+ 1.47
+ |
+
+ 140.38
+ |
+
+ 61.50%
+ |
+
+ 37.20%
+ |
+
+ 1.30%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 91
+ |
+
+ R2683E
+ |
+
+ BXD
+ |
+
+ BXD25
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R2683E.CEL
+ |
+
+ 0.068
+ |
+
+ 0.068
+ |
+
+ 1.777
+ |
+
+ 115.64
+ |
+
+ 58.30%
+ |
+
+ 40.30%
+ |
+
+ 1.40%
+ |
+
+ 2.01
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 92
+ |
+
+ R2703E
+ |
+
+ BXD
+ |
+
+ BXD27
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2703E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.012
+ |
+
+ 1.263
+ |
+
+ 134.78
+ |
+
+ 62.60%
+ |
+
+ 36.10%
+ |
+
+ 1.40%
+ |
+
+ 1.44
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 93
+ |
+
+ R2721E
+ |
+
+ BXD
+ |
+
+ BXD28
+ |
+
+ 60
+ |
+
+ M
+ |
+
+ R2721E.CEL
+ |
+
+ 0.04
+ |
+
+ 0.048
+ |
+
+ 2.065
+ |
+
+ 157.39
+ |
+
+ 56.10%
+ |
+
+ 42.40%
+ |
+
+ 1.50%
+ |
+
+ 1.31
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 94
+ |
+
+ R1258E
+ |
+
+ BXD
+ |
+
+ BXD31
+ |
+
+ 57
+ |
+
+ F
+ |
+
+ R1258E.CEL
+ |
+
+ 0.037
+ |
+
+ 0.036
+ |
+
+ 2.063
+ |
+
+ 117.09
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.54
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 95
+ |
+
+ R1216E
+ |
+
+ BXD
+ |
+
+ BXD32
+ |
+
+ 76
+ |
+
+ M
+ |
+
+ R1216E.CEL
+ |
+
+ 0.05
+ |
+
+ 0.049
+ |
+
+ 2.23
+ |
+
+ 111.99
+ |
+
+ 58.80%
+ |
+
+ 39.80%
+ |
+
+ 1.40%
+ |
+
+ 1.35
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 96
+ |
+
+ R857E
+ |
+
+ BXD
+ |
+
+ BXD33
+ |
+
+ 77
+ |
+
+ M
+ |
+
+ R857E.CEL
+ |
+
+ 0.078
+ |
+
+ 0.108
+ |
+
+ 1.737
+ |
+
+ 113.98
+ |
+
+ 61.90%
+ |
+
+ 36.70%
+ |
+
+ 1.30%
+ |
+
+ 1.6
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 97
+ |
+
+ R859E
+ |
+
+ BXD
+ |
+
+ BXD90
+ |
+
+ 72
+ |
+
+ M
+ |
+
+ R859E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.02
+ |
+
+ 1.847
+ |
+
+ 152.22
+ |
+
+ 57.90%
+ |
+
+ 40.70%
+ |
+
+ 1.40%
+ |
+
+ 1.36
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 98
+ |
+
+ R1207E
+ |
+
+ BXD
+ |
+
+ BXD66
+ |
+
+ 83
+ |
+
+ M
+ |
+
+ R1207E.CEL
+ |
+
+ 0.017
+ |
+
+ 0.012
+ |
+
+ 1.681
+ |
+
+ 136.86
+ |
+
+ 60.40%
+ |
+
+ 38.10%
+ |
+
+ 1.50%
+ |
+
+ 1.45
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 99
+ |
+
+ R2710E
+ |
+
+ BXD
+ |
+
+ BXD38
+ |
+
+ 55
+ |
+
+ F
+ |
+
+ R2710E.CEL
+ |
+
+ 0.033
+ |
+
+ 0.031
+ |
+
+ 2.112
+ |
+
+ 122.1
+ |
+
+ 58.80%
+ |
+
+ 39.80%
+ |
+
+ 1.40%
+ |
+
+ 1.37
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 100
+ |
+
+ R2695E
+ |
+
+ BXD
+ |
+
+ BXD39
+ |
+
+ 59
+ |
+
+ M
+ |
+
+ R2695E.CEL
+ |
+
+ 0.018
+ |
+
+ 0.016
+ |
+
+ 1.638
+ |
+
+ 122.7
+ |
+
+ 60.80%
+ |
+
+ 37.80%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 101
+ |
+
+ R2699E
+ |
+
+ BXD
+ |
+
+ BXD40
+ |
+
+ 59
+ |
+
+ F
+ |
+
+ R2699E.CEL
+ |
+
+ 0.014
+ |
+
+ 0.015
+ |
+
+ 1.827
+ |
+
+ 105.23
+ |
+
+ 61.70%
+ |
+
+ 36.90%
+ |
+
+ 1.40%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 102
+ |
+
+ R2696E
+ |
+
+ BXD
+ |
+
+ BXD42
+ |
+
+ 58
+ |
+
+ F
+ |
+
+ R2696E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.017
+ |
+
+ 1.622
+ |
+
+ 118.95
+ |
+
+ 62.00%
+ |
+
+ 36.60%
+ |
+
+ 1.50%
+ |
+
+ 1.53
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 103
+ |
+
+ R943E-2
+ |
+
+ BXD
+ |
+
+ BXD64
+ |
+
+ 56
+ |
+
+ F
+ |
+
+ R943E-2.CEL
+ |
+
+ 0.024
+ |
+
+ 0.021
+ |
+
+ 1.591
+ |
+
+ 141.34
+ |
+
+ 60.10%
+ |
+
+ 38.40%
+ |
+
+ 1.50%
+ |
+
+ 1.32
+ |
+
+ 0.76
+ |
+
+ GU
+ |
+
+
+ |
+ 104
+ |
+
+ R967E
+ |
+
+ BXD
+ |
+
+ BXD48
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R967E.CEL
+ |
+
+ 0.101
+ |
+
+ 0.052
+ |
+
+ 1.948
+ |
+
+ 130.95
+ |
+
+ 57.30%
+ |
+
+ 41.20%
+ |
+
+ 1.50%
+ |
+
+ 1.63
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 105
+ |
+
+ R2714E
+ |
+
+ BXD
+ |
+
+ BXD5
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R2714E.CEL
+ |
+
+ 0.047
+ |
+
+ 0.014
+ |
+
+ 1.404
+ |
+
+ 144.35
+ |
+
+ 60.60%
+ |
+
+ 37.90%
+ |
+
+ 1.50%
+ |
+
+ 1.43
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 106
+ |
+
+ R1042E
+ |
+
+ BXD
+ |
+
+ BXD51
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R1042E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.027
+ |
+
+ 2.352
+ |
+
+ 104.12
+ |
+
+ 58.70%
+ |
+
+ 39.90%
+ |
+
+ 1.40%
+ |
+
+ 1.53
+ |
+
+ 0.82
+ |
+
+ GU
+ |
+
+
+ |
+ 107
+ |
+
+ R2690E
+ |
+
+ BXD
+ |
+
+ BXD55
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R2690E.CEL
+ |
+
+ 0.081
+ |
+
+ 0.067
+ |
+
+ 1.887
+ |
+
+ 164.01
+ |
+
+ 56.10%
+ |
+
+ 42.30%
+ |
+
+ 1.60%
+ |
+
+ 1.43
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 108
+ |
+
+ R2694E
+ |
+
+ BXD
+ |
+
+ BXD6
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R2694E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.018
+ |
+
+ 1.983
+ |
+
+ 97.23
+ |
+
+ 61.60%
+ |
+
+ 37.10%
+ |
+
+ 1.30%
+ |
+
+ 1.39
+ |
+
+ 0.82
+ |
+
+ GU
+ |
+
+
+ |
+ 109
+ |
+
+ R975E
+ |
+
+ BXD
+ |
+
+ BXD70
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R975E.CEL
+ |
+
+ 0.028
+ |
+
+ 0.024
+ |
+
+ 1.841
+ |
+
+ 137.97
+ |
+
+ 58.00%
+ |
+
+ 40.50%
+ |
+
+ 1.40%
+ |
+
+ 1.36
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 110
+ |
+
+ R2684E
+ |
+
+ BXD
+ |
+
+ BXD61
+ |
+
+ 62
+ |
+
+ M
+ |
+
+ R2684E.CEL
+ |
+
+ 0.031
+ |
+
+ 0.032
+ |
+
+ 2.01
+ |
+
+ 131.03
+ |
+
+ 57.00%
+ |
+
+ 41.50%
+ |
+
+ 1.50%
+ |
+
+ 1.34
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 111
+ |
+
+ R994E
+ |
+
+ BXD
+ |
+
+ BXD43
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R994E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.014
+ |
+
+ 1.966
+ |
+
+ 113.12
+ |
+
+ 60.80%
+ |
+
+ 37.80%
+ |
+
+ 1.40%
+ |
+
+ 1.66
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 112
+ |
+
+ R2610E
+ |
+
+ BXD
+ |
+
+ BXD44
+ |
+
+ 68
+ |
+
+ M
+ |
+
+ R2610E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.009
+ |
+
+ 1.814
+ |
+
+ 142.91
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.35
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 113
+ |
+
+ R2689E
+ |
+
+ BXD
+ |
+
+ BXD65
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2689E.CEL
+ |
+
+ 0.008
+ |
+
+ 0.008
+ |
+
+ 1.721
+ |
+
+ 142.44
+ |
+
+ 59.90%
+ |
+
+ 38.60%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.76
+ |
+
+ GU
+ |
+
+
+ |
+ 114
+ |
+
+ R2727E
+ |
+
+ BXD
+ |
+
+ BXD69
+ |
+
+ 65
+ |
+
+ M
+ |
+
+ R2727E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.008
+ |
+
+ 1.578
+ |
+
+ 143.86
+ |
+
+ 60.30%
+ |
+
+ 38.30%
+ |
+
+ 1.40%
+ |
+
+ 1.34
+ |
+
+ 0.77
+ |
+
+ GU
+ |
+
+
+ |
+ 115
+ |
+
+ R2726E
+ |
+
+ BXD
+ |
+
+ BXD68
+ |
+
+ 64
+ |
+
+ M
+ |
+
+ R2726E.CEL
+ |
+
+ 0.125
+ |
+
+ 0.025
+ |
+
+ 1.811
+ |
+
+ 153.09
+ |
+
+ 58.70%
+ |
+
+ 39.80%
+ |
+
+ 1.50%
+ |
+
+ 1.39
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 116
+ |
+
+ R2732E
+ |
+
+ BXD
+ |
+
+ BXD45
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2732E.CEL
+ |
+
+ 0.039
+ |
+
+ 0.036
+ |
+
+ 2.154
+ |
+
+ 122.45
+ |
+
+ 56.50%
+ |
+
+ 42.10%
+ |
+
+ 1.40%
+ |
+
+ 1.8
+ |
+
+ 0.83
+ |
+
+ GU
+ |
+
+
+ |
+ 117
+ |
+
+ R2709E
+ |
+
+ BXD
+ |
+
+ BXD8
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2709E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.011
+ |
+
+ 1.99
+ |
+
+ 99.79
+ |
+
+ 60.90%
+ |
+
+ 37.60%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.76
+ |
+
+ GU
+ |
+
+
+ |
+ 118
+ |
+
+ R2686E
+ |
+
+ BXD
+ |
+
+ BXD80
+ |
+
+ 61
+ |
+
+ M
+ |
+
+ R2686E.CEL
+ |
+
+ 0.046
+ |
+
+ 0.05
+ |
+
+ 2.342
+ |
+
+ 119.63
+ |
+
+ 56.00%
+ |
+
+ 42.60%
+ |
+
+ 1.50%
+ |
+
+ 1.38
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 119
+ |
+
+ R2692E
+ |
+
+ BXD
+ |
+
+ BXD85
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2692E.CEL
+ |
+
+ 0.006
+ |
+
+ 0.007
+ |
+
+ 1.423
+ |
+
+ 160.87
+ |
+
+ 60.20%
+ |
+
+ 38.30%
+ |
+
+ 1.40%
+ |
+
+ 1.46
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 120
+ |
+
+ R2715E
+ |
+
+ BXD
+ |
+
+ BXD85
+ |
+
+ 91
+ |
+
+ M
+ |
+
+ R2715E.CEL
+ |
+
+ 0.007
+ |
+
+ 0.008
+ |
+
+ 1.488
+ |
+
+ 142.6
+ |
+
+ 61.20%
+ |
+
+ 37.30%
+ |
+
+ 1.40%
+ |
+
+ 1.5
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 121
+ |
+
+ R1405E
+ |
+
+ BXD
+ |
+
+ BXD86
+ |
+
+ 58
+ |
+
+ F
+ |
+
+ R1405E.CEL
+ |
+
+ 0.053
+ |
+
+ 0.052
+ |
+
+ 2.351
+ |
+
+ 119.34
+ |
+
+ 56.40%
+ |
+
+ 42.20%
+ |
+
+ 1.40%
+ |
+
+ 1.64
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 122
+ |
+
+ R2724E
+ |
+
+ BXD
+ |
+
+ BXD87
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R2724E.CEL
+ |
+
+ 0.013
+ |
+
+ 0.019
+ |
+
+ 1.906
+ |
+
+ 113.71
+ |
+
+ 60.70%
+ |
+
+ 37.90%
+ |
+
+ 1.40%
+ |
+
+ 1.45
+ |
+
+ 0.79
+ |
+
+ GU
+ |
+
+
+ |
+ 123
+ |
+
+ R1451E
+ |
+
+ BXD
+ |
+
+ BXD34
+ |
+
+ 61
+ |
+
+ F
+ |
+
+ R1451E.CEL
+ |
+
+ 0.01
+ |
+
+ 0.009
+ |
+
+ 1.843
+ |
+
+ 140.05
+ |
+
+ 59.00%
+ |
+
+ 39.50%
+ |
+
+ 1.50%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 124
+ |
+
+ R1433E
+ |
+
+ BXD
+ |
+
+ BXD89
+ |
+
+ 63
+ |
+
+ F
+ |
+
+ R1433E.CEL
+ |
+
+ 0.029
+ |
+
+ 0.026
+ |
+
+ 2.241
+ |
+
+ 115.86
+ |
+
+ 57.70%
+ |
+
+ 40.80%
+ |
+
+ 1.50%
+ |
+
+ 1.41
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 125
+ |
+
+ R2733E
+ |
+
+ BXD
+ |
+
+ BXD96
+ |
+
+ 67
+ |
+
+ F
+ |
+
+ R2733E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.054
+ |
+
+ 1.7
+ |
+
+ 113.99
+ |
+
+ 62.10%
+ |
+
+ 36.60%
+ |
+
+ 1.30%
+ |
+
+ 1.4
+ |
+
+ 0.78
+ |
+
+ GU
+ |
+
+
+ |
+ 126
+ |
+
+ R2649E
+ |
+
+ BXD
+ |
+
+ BXD97
+ |
+
+ 74
+ |
+
+ F
+ |
+
+ R2649E.CEL
+ |
+
+ 0.029
+ |
+
+ 0.032
+ |
+
+ 2.343
+ |
+
+ 119.04
+ |
+
+ 57.50%
+ |
+
+ 41.20%
+ |
+
+ 1.40%
+ |
+
+ 1.53
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 127
+ |
+
+ R2688E
+ |
+
+ BXD
+ |
+
+ BXD98
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2688E.CEL
+ |
+
+ 0.032
+ |
+
+ 0.03
+ |
+
+ 1.772
+ |
+
+ 145.24
+ |
+
+ 58.50%
+ |
+
+ 40.00%
+ |
+
+ 1.50%
+ |
+
+ 1.48
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 128
+ |
+
+ R877E
+ |
+
+ BXD
+ |
+
+ BXD13
+ |
+
+ 76
+ |
+
+ M
+ |
+
+ R877E.CEL
+ |
+
+ 0.026
+ |
+
+ 0.067
+ |
+
+ 1.558
+ |
+
+ 125.63
+ |
+
+ 61.20%
+ |
+
+ 37.50%
+ |
+
+ 1.20%
+ |
+
+ 1.42
+ |
+
+ 0.81
+ |
+
+ GU
+ |
+
+
+ |
+ 129
+ |
+
+ R1397E-re
+ |
+
+ BXD
+ |
+
+ BXD75
+ |
+
+ 58
+ |
+
+ M
+ |
+
+ R1397E-re.CEL
+ |
+
+ 0.032
+ |
+
+ 0.01
+ |
+
+ 1.449
+ |
+
+ 189.71
+ |
+
+ 59.60%
+ |
+
+ 39.00%
+ |
+
+ 1.40%
+ |
+
+ 1.39
+ |
+
+ 0.82
+ |
+
+ GU
+ |
+
+
+ |
+ 130
+ |
+
+ R2779E
+ |
+
+ BXD
+ |
+
+ BXD73
+ |
+
+ 64
+ |
+
+ F
+ |
+
+ R2779E.CEL
+ |
+
+ 0.012
+ |
+
+ 0.038
+ |
+
+ 1.746
+ |
+
+ 121.11
+ |
+
+ 59.60%
+ |
+
+ 39.00%
+ |
+
+ 1.40%
+ |
+
+ 1.5
+ |
+
+ 0.8
+ |
+
+ GU
+ |
+
+
+ |
+ 131
+ |
+
+ R2708E
+ |
+
+ BXD
+ |
+
+ BXD9
+ |
+
+ 60
+ |
+
+ F
+ |
+
+ R2708E.CEL
+ |
+
+ 0.024
+ |
+
+ 0.045
+ |
+
+ 1.966
+ |
+
+ 126.46
+ |
+
+ 57.70%
+ |
+
+ 40.70%
+ |
+
+ 1.50%
+ |
+
+ 1.4
+ |
+
+ 0.84
+ |
+
+ GU
+ |
+
+
+ |
+ 132
+ |
+
+ R2547E1
+ |
+
+ GDP
+ |
+
+ WSB/Ei
+ |
+
+ 67
+ |
+
+ M
+ |
+
+ R2547E.CEL
+ |
+
+ 0.041
+ |
+
+ 0.039
+ |
+
+ 2.14
+ |
+
+ 90
+ |
+
+ 58.20%
+ |
+
+ 40.10%
+ |
+
+ 1.60%
+ |
+
+ 1.32
+ |
+
+ 0.77
+ |
+
+ UTM RW
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0908_r/acknowledgment.rtf b/general/datasets/Eye_m2_0908_r/acknowledgment.rtf
new file mode 100644
index 0000000..5098d32
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant and from funds from NEI grant to Dr. Eldon Geisert (R01EY017841), an NEI Vision Core grant (EY14080) and an Unrestricted Grant from Research To Prevent Blindness.
+
+We thank Dr. Ted Choi, Chief Scientific Director of Predictive Biology, Inc. (past director of molecular genetics at Deltagen Inc.) for providing us with eye samples from several interesting DeltaGen knockouts.
diff --git a/general/datasets/Eye_m2_0908_r/cases.rtf b/general/datasets/Eye_m2_0908_r/cases.rtf
new file mode 100644
index 0000000..552d4a5
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r/cases.rtf
@@ -0,0 +1,57 @@
+This is the complete and final HEIMED data set. HEIMED consists of expression data for 103 genetically defined lines of mice with standard errors of the mean. Almost all animals are young adults between 50 and 80 days of age (Table 1, maximum age is 123 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, reciprocal F1s between C57BL/6J and DBA/2J, and several mutant and knockout lines. We have combined all common strains, F1 hybrids, and mutants into a group called the Mouse Diversity Panel (MDP). Four lines, namely, C57BL/6J (B6), DBA/2J (D2), and the pair of B6D2F1 and D2B6F1 hybrids are common to both the MDP and the BXD set. This is a breakdown of cases that are part of HEIMED:
+
+
+ - 68 BXD strains. The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. Only one of these strains, BXD24 (know also known as BXD24b), has retinal degeneration (a spontaneous mutation). The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA.
+ - 35 MDP lines, including 26 inbred strains representing closely related substrains (e.g, BALB/cJ and BALB/cByJ), many of the most widely used common Mus musculus domesticus inbred strains (e.g., C57BL/6J and 129S1/SvImJ), inbred but wild-derived representatives of common subspecies (Mus musculus domesticus, e.g, WSB/EiJ; M. musculus musculus, e.g., CZECHII/EiJ; M. musculus molossinus, e.g., MOLF/EiJ; M. musculus castaneus, e.g., CAST/EiJ); and even one different species of mouse (Mus spicilegus, PANCEVO/EiJ). The MDP also includes the reciprocal F1 hybrids (B6D2F1 and D2B6F1) and the following 6 KO lines and the Nyx-nob mutant:
+ - 6 knockouts (KO), including a KO of Rpe65, and 5 DeltaGen Inc. knockout lines provided by Dr. Ted Choi. These KO lines have had a bacterial lacZ construct inserted into the gene. The endogenous promoter drives expression of beta-galactosidase. RT-PCR analysis detects a gene transcript in most tissues. The following KOs from DeltaGen were studied: Gabra1, Gabbr1, Gnb1, Gpr19, and Clcn3. We also included one spontaneous mutant of the nyctalopin (Nyx no b wave "nob") gene (Pardue et al., 1998) that is on a BALB/cByJ background.
+
+
+Rod photoreceptor degeneration in inbred mice: Six strains of mice included in HEIMED suffer from severe loss of photoreceptors (mainly rods) and have the equivalent of night blindness in human patients. The death of photoreceptors in these strains occurs by one to two months of age and is often caused by the retinal degeneration 1 (rd1) mutant allele in the rod cyclic-GMP phosphodiesterase 6 beta subunit gene (Pde6b). The following strains are known to have photoreceptor degeneration: C3H/HeJ, FVB/NJ, MOLF/EiJ, SJL/J and BXD24/TyJ. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEIMED data set.
+
+As expected (Dickerson LW et al., 2002) and as judged from the absence of rhodopsin expression, one of the DeltaGen KO lines (chloride ion channel 3, Clcn3) also has retinal degeneration: B6129P2F2N1-Clcn3. Degeneration in this strain is likely to include all rods and all cones. The cone defect is obvious from the decrease in expression of Gnat2, a gene associated with cones and achromatopsia in mice and humans.
+
+Lines of mice were selected using the following criteria:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - representation of a fairly wide variety of different subspecies of Mus
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Tel Aviv/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - interesting mutations or knockouts affecting genes with high expression in the eye
+ - general availability from The Jackson Laboratory. The only exception are the DeltaGen KO mice.
+
+
+We have included all eight parents of the Collaborative Cross (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/LtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ) in the MDP. Fourteen MDP strains have been partially sequenced by Perlegen for the NIEHS, including including 129S1/SvImJ, A/J, AKR/J, BALB/cByJ, C3H/HeJ, CAST/EiJ, DBA/2J, FVB/NJ, KK/HlJ, MOLF/EiJ, NOD/LtJ, NZW/LacJ, PWD/PhJ, and WSB/EiJ (see the GeneNetwork SNP Browser for data, details, and see Perlegen's excellent data resources and browser).
+
+
+ - 129S1/SvImJ : Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene. It is also a cone photoreceptor function loss 3 mutant (Cpfl3 allele) of the Gnat2 gene that is a model for achromatopsia (JAX Stock Number: 002448)
+ - A/J: Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase (Tyr c allele) albino mutant. This strain is particularly sensitive to light-induced photoreceptor loss (Danciger et al., 2007). (JAX Stock Number: 000646)
+ - BALB/cByJ: Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project old group A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Small brain, not aggressive (JAX Stock Number: 001026)
+ - BALB/cJ: Phenome Project A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Large brain and aggressive (JAX Stock Number: 000651)
+ - BXSB/MpJ: A white-bellied agouti strains with interesting autoimmune disease restricted to males that is associated with a mutation in the Yaa gene that causes glomerulonephritis, a dramatic increase in number of peripheral monocytes, and pre-B-cell deficiency (JAX Stock Number: 000740)
+ - C3H/HeJ: The Heston (He) substrain with a wildtype agouti (A allele) coat color. Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project old group A list. Important to note for this eye expression dataset, C3H/HeJ is a Pdeb6 rd1 mutant with near total photoreceptor loss at as early as postnatal day 30. Also a Tlr4 mutant that is endotoxin resistant. (JAX Stock Number: 000659)
+ - C57BL/6J: Sequenced by NIH/NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list. Single most widely used inbred strain of mouse. (JAX Stock Number: 000664)
+ - C57BLKS/J: Black Kaliss strain (non-agouti a allele) derived from C57BL/6J, but genetically contaminated at some point mainly with DBA/2J and then reinbred. Now at the Jackson Laboratory. (JAX Stock Number: 000662)
+ - CAST/EiJ: A wild-derived inbred Mus musculus castaneus strain. Samples of this subspecies were captured in Southeast Asia. One of three wild-derived strains in the Collaborative Cross sequenced by NIEHS; Phenome Project A list. CAST/Ei and CAST/EiJ are the same strain. The addition of the "J" is trivial and was added when stock were transferred from Dr. Eicher's lab to the Jackson Laboratory production facility in about 2004. (JAX Stock Number: 000928)
+ - CBA/CaJ: Agouti strain from the Jackson Laboratory. Wildtype pigment genes. (JAX Stock Number: 000654)
+ - CZECHII/EiJ: Czech 2 is a wild-derived inbred strain M. musculus musculus strain. Samples of this subspecies were caught in the Czech Republic and inbred at the Jackson Laboratory by Eva Eicher. White-bellied agouti. (JAX Stock Number: 001144).
+ - DBA/2J: The dilute, brown, agouti (dba) strain is the oldest inbred strain of mouse. Inbreeding was started in 1909 by Little. A tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. A myosin 5a (Myo5a d) dilute allele mutant. Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project old A group list. (JAX Stock Number: 000671)
+ - FVB/NJ: Friend's leukemia virus B (FVB) strain. Sequenced by Perlegen/NIEHS and Celera. Tyr c locus albino and a Pdeb6 rd1 mutant derived from Swiss mice at NIH. This has been the most common strain used to make transgenic mice due to large and easily injected oocytes; Phenome Project A list (JAX Stock Number: 001800).
+ - KK/HlJ: K Kondo's (KK) Kasukabe strain is a homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. Males have a form of type 2 diabetes. Sequenced by Perlegen/NIEHS. (JAX Stock Number: 002106)
+ - LG/J: Large (LG) strain. Paternal parent of the Large-by-Small set of RI strains made by James Cheverud and colleagues (the LGXSM panel, not to be confused with the LongXShort or LXS panel). A Tyr c locus albino strain. (JAX Stock Number: 000675)
+ - LP/J: White-bellied agouit strain with a piebald mutation in the endothelin receptor type B Ednrb gene from at the Jackson Laboratory. Some reduction in melanocytes in choroid of eye due to neural creast migration abnormalities. (JAX Stock Number: 000676)
+ - MOLF/EiJ: A wild-derived inbred strain derived from M. musculus molossinus samples camputered in Fukuoka, Japan. This strain has the retinal degeneration rd1 allele in Pde6b. There appears to have been some genetic contamination of this strain with conventional inbred strains in the past several decades (F. Pardo, personal communication to RWW, August 2006). However, the strain is currently fully inbred. (JAX Stock Number: 000550)
+ - NOD/LtJ: Non-obese diabetic strain, originally from M. Hattori in Kyoto, Japan. This is the Edward Leiter (Lt) substrain from the Jackson Laboratory. Collaborative Cross strain sequenced by NIEHS; Phenome Project B list. Homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. (JAX Stock Number: 001976)
+ - NZO/HlLtJ: New Zealand Obese strain. This is a severely obese and hypertensive strain. Males often develop a type 2 diabetes. Collaborative Cross strain. Agouti coat color. (JAX Stock Number: 002105)
+ - NZB/BlNJ: New Zealand Black inbred strain from Bielschowsky (BL, substrain is "B lowercase L N", not "BiN") now maintained at the Jackson Laboratory. (JAX Stock Number: 000648)
+ - NZW/LacJ: New Zealand White strain from the Laboratory Animal Center (Carshalton, UK), now maintained at the Jackson Laboratory. Carries the Tyr c locus albino mutation, the pink-eye dilution mutation in the Oca2 or p locus, and the brown allele at Tyrp1. (JAX Stock Number: 001058)
+ - PANCEVO/EiJ: PANCEVO/EiJ is a wild-derived inbred strain from the Mus spicilegus samples caught in the Pancevo, Serbia. This species of mouse is also known as the Steppe mouse (taxon identifier 10103). M. spicilegus is a colonial mound-building species. No known ocular or retina mutations, but the expression level of Gnat2 is low in this strain, either due to a 3' UTR length variant or possible achromatosia (cone degeneration) (JAX Stock Number: 001384)
+ - PWD/PhJ: A wild-derived Mus musculus musculus agouti strain inbred from samples caught near Prague, Czech Republic. Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues. (JAX Stock Number: 004660)
+ - PWK/PhJ: A wild-derived Mus musculus musculus inbred strain from samples caught near Lhotka, Czech Republic. Collaborative Cross strain; Phenome Project D list. (JAX Stock Number: 003715)
+ - SJL/J: Swiss Webster inbred strain from Jim Lambert's lab at the Jackson Laboratory. This strain has the retinal degeneration rd1 allele in Pde6b. It also carries both the Tyr c albino mutation and the pink-eye dilution mutation in the Oca2 or p locus. Highly aggressive males. (JAX Stock Number: 000686)
+ - WSB/EiJ: Watkin Star line B (or "wild son-of-a-bitch") is a wild-derived Mus musculus domesticus inbred strain from samples caught in Maryland, USA. A Collaborative Cross strain sequenced by NIEHS; Phenome Project C list (JAX Stock Number: 001145)
+ - B6D2F1 and D2B6F1 (also listed as BDF1 and DBF1 in some graphs and tables): F1 hybrids generated by crossing C57BL/6J with DBA/2J. These black reciprocal F1 can be used to detect dominance effects. Comparison of the two reciprocal F1s can be used to detect parental origin (imprinting) effects. The D2B6F1 animals are currently available from the Jackson Laboratory as a special order.) (JAX Stock Number for B6D2F1 hybrids obtained from the Jackson Laboratory, aka B6D2F1/J 100006)
+
+
+Most of the common inbred strains harbor mutations in genes the control pigmentation (Silvers, 2008 and material above in this INFO file). These gene include the albino and chinchilla alleles of the tyrosinase gene (Tyr, or human OCA1), the brown allele of the tyrosinase related protein 1 (Tyrp1), the pink-eye dilution allele of Oca2 (probe set 1418211), the non-agouti (black) and white-bellied alleles of the agouti signaling protein Asip, the steel allele of Kitlg, the dilute allele of Myo5a (probe set 1419754), and the piebald allele of Ednrb. In some of these cases, effects of the mutation are easily detected at the transcript level (Tyrp1, Oca2, and Myo5a), but in the other cases (Tyr, Asip, Ednrb, and Kitlg), mutations do not leave a strong imprint on expression.
diff --git a/general/datasets/Eye_m2_0908_r/citation.rtf b/general/datasets/Eye_m2_0908_r/citation.rtf
new file mode 100644
index 0000000..ddd98e4
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r/citation.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams. Gene expression landscape of the mammalian eye: A global survey and database of mRNAs of 103 varieties of mice. Molecular Vision 2009; in press.
diff --git a/general/datasets/Eye_m2_0908_r/contributors.rtf b/general/datasets/Eye_m2_0908_r/contributors.rtf
new file mode 100644
index 0000000..d155833
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams
diff --git a/general/datasets/Eye_m2_0908_r/experiment-design.rtf b/general/datasets/Eye_m2_0908_r/experiment-design.rtf
new file mode 100644
index 0000000..1ebe0ad
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r/experiment-design.rtf
@@ -0,0 +1 @@
+Expression profiling by array
diff --git a/general/datasets/Eye_m2_0908_r/experiment-type.rtf b/general/datasets/Eye_m2_0908_r/experiment-type.rtf
new file mode 100644
index 0000000..0546e04
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array
\ No newline at end of file
diff --git a/general/datasets/Eye_m2_0908_r/notes.rtf b/general/datasets/Eye_m2_0908_r/notes.rtf
new file mode 100644
index 0000000..7a26eb5
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r/notes.rtf
@@ -0,0 +1 @@
+This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/Eye_m2_0908_r/platform.rtf b/general/datasets/Eye_m2_0908_r/platform.rtf
new file mode 100644
index 0000000..9024a99
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r/platform.rtf
@@ -0,0 +1,11 @@
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many probes overlap and target the same transcript). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequences as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
+As part of the development of HEIMED, we have manually annotated individual probe sets by sequence alignment to the mouse genome and transcriptome. Approximately 13,000 probe sets that have comparatively high expression in eye and CNS were curated by one of the authors (RWW) and now have specific information on the part of the transcript targeted by each probe set. The other 33,000 transcripts have corresponding data that was generated by Xusheng Wang using computational methods (BLAT analysis combined with annotated genome sequence).
+
+One example may help explain how to exploit this annotation. The four probe sets for rhodopsin include information on the target location. Only the first probe set targets the last two coding exons. The other three probe sets target different parts of the 3’ UTR (mid, distal, and far distal regions). The probe sets can be reordered by from high to low expression using the Sort By function in Search Results pages. In the case of rhodopsin, the probe set that targets that last two coding exons and proximal parts of the 3’ UTR also has the highest expression . Finally, the HEIMED gene descriptions have been customized to help vision researchers. In the case of rhodopsin, the description appended after the gene name reads “rod photoreceptor pigment, retinitis pigmentosa-associated”. For less well known genes this kind of annotation can be extremely useful. For example, the more verbose annotation for Cerkl reads “neuronal survival and apoptosis-related, retinal ganglion cell expressed, retinitis pigmentosa 26); alternative 3' UTR of short form message, intron 2”.
+
+
+
+
+
+Legend: Distribution of expression values for all probe sets in HEIMED.
diff --git a/general/datasets/Eye_m2_0908_r/processing.rtf b/general/datasets/Eye_m2_0908_r/processing.rtf
new file mode 100644
index 0000000..4349e60
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r/processing.rtf
@@ -0,0 +1,3381 @@
+Range of Gene Expression in the Eye. Expression of transcripts in the HEIMED and most other GN data sets is measured on a log2 scale. Each unit corresponding approximately to a 2-fold difference in hybridization signal intensity. To simplify comparisons among different data sets and cases, log2 RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units (variance stabilized). Values of all 45,101 probe sets in this data set range from a low of 4.8 (Tcf15, probe set 1420281_at) to a high of 15.5 (crystallin gamma C, Crygc, probe set 1422674_s_at). This corresponds to 10.7 units or a 1 to 1700 dynamic range of expression (2^10.73).
+
+We used pooled RNA samples of whole eyes, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+We calibrated this log intensity scale using Affymetrix spike-in control probe sets. These 18 control probe sets target exogenous bacterial mRNAs that are added to each sample (a graded dose spike cocktail) during preparation at concentrations of 1.5, 5, 25, and 100 pM. (To find these probe sets, search GN’s ALL search field using the string “AFFX pM”.) A value of 6 or less is equivalent to an mRNA concentration of under 0.4 pM, a value of 8 is equivalent to ~1.5 pM, 9.5 is equivalent to ~5 pM, 11.5 is equivalent to ~25 pM, 13.5 is equivalent to ~100 pM, and a value of 15.5 is equivalent to an mRNA concentration of 400 pM or greater.
+
+This range can be converted to the mRNA molecules per cell in the eye assuming that a value of 8 is equivalent to about 1 mRNA copy per cell (Kanno et al. 2006, see http://www.biomedcentral.com/1471-2164/7/64). Since the expression of rhodopsin mRNA is normally 15 units, we predict that there are 27 or ~128 Rho mRNAs per cell in the whole eye and ~256 in rods themselves (assuming that rods make up about half of all cells in the eye). For this purpose it may be useful to know that a normal mouse eye contains between 6 and 8 million rod photoreceptors (Guo, Lu, and Williams; GN BXD Phenotype ID 11024).
+
+Note that some probe sets with very low expression still provide reliable data. For example, probe set 1440397_at (Cacna2d1) has expression of only 5.5 units (a value that would be declared as "absent" using conventional Affymetrix procedures), but the values for this calcium channel transcript are associated with a very strong cis QTL with an LRS of 79 (LOD = 17). This strong linkage is definitely not due to chance since the probability of the expression data mapping precisely to the location of the parent gene itself is about 10e-16. This indicates a high signal to noise ratio and the detection of significant strain variation of the correct transcript.
+
+The standard error of the mean for the HEIMED data set is computed for 2 to 6 biological replicates. The standard error of such small samples tends to systematically underestimate the population standard error. With n = 2 the underestimate is about 25%, whereas for n = 6 the underestimate is 5%. Gurland and Tripathi (1971) provide a correction and equation for this effect (see Sokal and Rohlf, Biometry, 2nd ed., 1981, p 53 for an equation of the correction factor for small samples of n < 20.) Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. The CEL files were processed using the RMA protocol. We processed the first three batches together. The last batch was processed separately and merged as described below.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
+After RMA processing using Biobase affy10 build running under R version 2.7.1, all array data sets were rank-order normalized. This second round of quantile normalization removes much residual non-linearity across arrays and forces every array to have the same distribution of values as the mean of all arrays. Comparative array data quality was then evaluated in DataDesk. Outlier arrays were flagged by visual inspection in DataDesk, usually by means of an analysis of scatter plots and more quantitatively by generating a correlation matrix of all arrays. Those arrays with mean correlation <0.96 versus all other arrays indicates trouble or a biological outlier). In some cases, outliers were expected, such as samples from strains with retinal degeneration (FVB/NJ, NOD/LtJ, MOLF/EiJ, C3H/HeJ and BXD24), samples from wild subspecies such as WSB/EiJ, CAST/EiJ, PWD/PhJ, and PWK/PhJ, and knockouts. However, when arrays were anomolous both within strain and across strains, they were often simply discarded. The assumption is that anomolous data are much more likely due to experimental and technical errors than to informative biological variation. Approximately 10% of arrays were discarded.
+
+After this process, the acceptable set of arrays was renormalized using all step as above, starting with the original RMA procedure, etc.
+
+We reviewed the data set using a new method developed by RW Williams, Jeremy Peirce, and Hongqiang Li. For the full set of arrays that passed standard QC protocols described above, we computed the strain means for the BXD strains, B6, D2, and F1s. Using this set of strain means we then computed LRS scores for all 45101 probe sets and counted the number of transcripts that generated QTLs with LRS values greater than 50. This value (e.g., 1800) represented the QTL harvest for the full data set. We then dropped a single array from the data set, recomputed strain means, and recomputed the number of transcripts with LRS scores great than 50. This value is expected to typically reduce the number of QTLs that reach the criterion level (e.g., 1750 QTLs > 50). This process was repeated for every array to obtain an array-specific difference value--the effect of removing that array on the total QTL count. For example, the loss of a single array might cause a decrease in 50 QTLs. Values ranged from approximately -90 (good arrays) to +40 (bad arrays). This procedure is similar in some ways to a jackknife protocol, although we are not using this procedure to esimate an error term, but rather as a method to polish a data set.
+
+During this process we discovered that nearly 20 arrays in the batch 2 had been mislabeled at some point in processing. We computed the correct strain membership of each array using a large number of Mendelian probe sets (more than 50) and comparing their match to standard SNP and microsatellite markers and the original array data set of November 2005. This allowed us to rescue a large number of arrays that were of high quality.
+
+A third batch of approximately 40 arrays were processed by Yan Jiao and Weikuan Gu in August 2006. These complete data set assembled by Hongqiang Li. This process again included a correction for a batch effect.
+
+For the June 2006 data set Hongqiang Li used a new batch correction method that stabilizes the range of expression in each batch. For each of the three large batches, we extracted the minumum and maximum raw probe expression (CEL file level) value. We then adjusted raw probe values in each batch to have the same range as the first and largest batch (batch 1) using a simple linear interpolation. These procedures generated new correct CEL files which were then used with RMA to generate final probe set estimates.
+
+For the final fourth batch of arrays (Sept 2008) Arthur Centeno and Rob Williams corrected for a systematic difference in probe set expression values between original arrays run in 2005 and 2006 and the new arrays added in 2008 (n = 45 acceptable arrays). This difference is due to unknown technical batch effects that are probably associated with labeling, hybridization, and scanning. We performed a simple correction to normalize values of the new set of arrays to those of the old set (batches 1 through 3). No changes were made to any values of the previous three batches. We corrected only the probe set level (RMA) values and not the CEL files. For this final batch, we corrected for the difference (offset) in probe set expression between the first three batches arrays run in 2005 and 2006 (a total of 174 acceptable arrays) and the new batch (n = 47 acceptable arrays). This difference is due to unknown technical effects that are probably related to various steps in labeling, hybridization, and scanning. The correction was applied as follows: (1) RWW selected 51 high quality arrays with similar expression characteristics (r = 0.97 or better between pairs of arrays) in the old data set (from batches 1, 2, and 3) and 34 high quality arrays in the final batch. RWW used scatterplots of full RMA transcriptome data sets to review many pairs of arrays within these new and old array batches. Strains with retinal degeneration or unusual eye gene expression characteristics were excluded from these selected subsets. The average expression values for each probe set were then computed for both the old and new array subsets. The offset value (old minus new) was added to each probe set across all 47 new arrays. This processes forces the average probe set in the new arrays to be very close to that of the previous arrays.
+
+Table 2: Sample tube ID, strain, original CEL filename, and Affymetrix quality control values. Columns labeled Scale factor, Background Average, Present, Absent, Marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Strain |
+ Original CEL |
+ Scale factor |
+ Background Average |
+ Present |
+ Absent |
+ Marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ Batch Id |
+ Used for batch control |
+
+
+ | 1 |
+ R2595E.1 |
+ 129S1/SvImJ |
+ R2595E.1.CEL |
+ 1.79 |
+ 115 |
+ 61.00% |
+ 37.50% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 2 |
+ R2533E.1 |
+ 129S1/SvImJ |
+ R2533E.1.CEL |
+ 2.11 |
+ 94 |
+ 57.90% |
+ 40.50% |
+ 1.60% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 3 |
+ R0754E.1 |
+ A/J |
+ R0754E.1.CEL |
+ 2.72 |
+ 86 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.36 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 4 |
+ R4521E |
+ B6129P2F2N1-Clcn3 |
+ R4521E.CEL |
+ 4.83 |
+ 38.7 |
+ 63.30% |
+ 35.30% |
+ 1.40% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 5 |
+ R4522E |
+ B6129P2F2N1-Clcn3 |
+ R4522E.CEL |
+ 5.76 |
+ 37.36 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.37 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 6 |
+ R4523E |
+ B6129P2F2N1-Clcn3 |
+ R4523E.CEL |
+ 4.88 |
+ 40.42 |
+ 63.90% |
+ 34.70% |
+ 1.40% |
+ 1.27 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 7 |
+ R4526E |
+ B6129P2F2N1-Gabbr1 |
+ R4526E.CEL |
+ 3.84 |
+ 44.18 |
+ 65.00% |
+ 33.70% |
+ 1.30% |
+ 1.34 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 8 |
+ R4509E |
+ B6129P2F2N1-Gabbr1 |
+ R4509E.CEL |
+ 7.45 |
+ 34.76 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.45 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 9 |
+ R4510E |
+ B6129P2F2N1-Gabbr1 |
+ R4510E.CEL |
+ 8.44 |
+ 37.44 |
+ 57.40% |
+ 41.10% |
+ 1.50% |
+ 1.35 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 10 |
+ R4511E |
+ B6129P2F2N1-Gabbr1 |
+ R4511E.CEL |
+ 5.91 |
+ 42.02 |
+ 61.40% |
+ 37.20% |
+ 1.40% |
+ 1.41 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 11 |
+ R4524E |
+ B6129P2F2N1-Gabbr1 |
+ R4524E.CEL |
+ 5.49 |
+ 42.34 |
+ 62.40% |
+ 36.20% |
+ 1.40% |
+ 1.29 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 12 |
+ R4525E |
+ B6129P2F2N1-Gabbr1 |
+ R4525E.CEL |
+ 4.69 |
+ 41.3 |
+ 63.10% |
+ 35.50% |
+ 1.40% |
+ 1.27 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 13 |
+ R4515E |
+ B6129P2F2N1-Gabra1 |
+ R4515E.CEL |
+ 5.75 |
+ 41.76 |
+ 62.80% |
+ 35.80% |
+ 1.40% |
+ 1.41 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 14 |
+ R4516E |
+ B6129P2F2N1-Gabra1 |
+ R4516E.CEL |
+ 7.07 |
+ 40.73 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.32 |
+ 0.87 |
+ 4 |
+ Y |
+
+
+ | 15 |
+ R4517E |
+ B6129P2F2N1-Gabra1 |
+ R4517E.CEL |
+ 5.45 |
+ 38.09 |
+ 62.70% |
+ 35.80% |
+ 1.40% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 16 |
+ R4512E |
+ B6129P2F2N1-Gnb5 |
+ R4512E.CEL |
+ 6.56 |
+ 38.02 |
+ 59.90% |
+ 38.70% |
+ 1.50% |
+ 1.33 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 17 |
+ R4513E |
+ B6129P2F2N1-Gnb5 |
+ R4513E.CEL |
+ 4.15 |
+ 41.6 |
+ 63.40% |
+ 35.10% |
+ 1.50% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ |
+
+
+ | 18 |
+ R4514E |
+ B6129P2F2N1-Gnb5 |
+ R4514E.CEL |
+ 5.86 |
+ 39.2 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.34 |
+ 0.81 |
+ 4 |
+ |
+
+
+ | 19 |
+ R4518E |
+ B6129P2F2N1-Gpr19 |
+ R4518E.CEL |
+ 5.58 |
+ 38.9 |
+ 62.60% |
+ 36.00% |
+ 1.30% |
+ 1.39 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 20 |
+ R4519E |
+ B6129P2F2N1-Gpr19 |
+ R4519E.CEL |
+ 5.95 |
+ 41.91 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.35 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 21 |
+ R2601E.1 |
+ B6D2F1 |
+ R2601E.1.CEL |
+ 2.55 |
+ 92 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.44 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 22 |
+ R2602E.1 |
+ B6D2F1 |
+ R2602E.1.CEL |
+ 2.6 |
+ 84 |
+ 59.70% |
+ 38.80% |
+ 1.50% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 23 |
+ R1676E.1 |
+ BALB/cByJ |
+ R1676E.1.CEL |
+ 2.69 |
+ 98 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.46 |
+ 0.74 |
+ 1 |
+ |
+
+
+ | 24 |
+ R1672E.1 |
+ BALB/cByJ |
+ R1672E.1.CEL |
+ 2.22 |
+ 111 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 25 |
+ R4530E |
+ BALB/cJ |
+ R4530E.CEL |
+ 6.37 |
+ 37.53 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.3 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 26 |
+ R4529E |
+ BALB/cJ |
+ R4529E.CEL |
+ 5.71 |
+ 41.33 |
+ 60.50% |
+ 38.00% |
+ 1.50% |
+ 1.48 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD1 |
+ R2704E.2.CEL |
+ 2.066 |
+ 139.61 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD1 |
+ R2707E.3.CEL |
+ 1 |
+ 80 |
+ 56.40% |
+ 42.10% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 3 |
+ |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD2 |
+ R1231E.2.CEL |
+ 2.197 |
+ 138.73 |
+ 57.30% |
+ 41.30% |
+ 1.40% |
+ 1.41 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD2 |
+ R2598E.1.CEL |
+ 1.99 |
+ 106 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD5 |
+ R2591E.1.CEL |
+ 1.7 |
+ 136 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.33 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD5 |
+ R2714E.2.CEL |
+ 1.404 |
+ 144.35 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD6 |
+ R2570E.1.CEL |
+ 1.99 |
+ 87 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.46 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD6 |
+ R2694E.2.CEL |
+ 1.983 |
+ 97.23 |
+ 61.60% |
+ 37.10% |
+ 1.30% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD8 |
+ R2538E.1.CEL |
+ 1.91 |
+ 102 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.52 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD8 |
+ R2709E.2.CEL |
+ 1.99 |
+ 99.79 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.42 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD9 |
+ R2708E.2.CEL |
+ 1.966 |
+ 126.46 |
+ 57.70% |
+ 40.70% |
+ 1.50% |
+ 1.4 |
+ 0.84 |
+ 2 |
+ |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD9 |
+ R2569E.1.CEL |
+ 1.75 |
+ 87 |
+ 55.10% |
+ 43.40% |
+ 1.50% |
+ 2.82 |
+ 3.14 |
+ 1 |
+ |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD11 |
+ R2581E.1.CEL |
+ 1.94 |
+ 89 |
+ 62.10% |
+ 36.40% |
+ 1.60% |
+ 1.55 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD11 |
+ R2612E.2.CEL |
+ 1.83 |
+ 142.03 |
+ 58.20% |
+ 40.50% |
+ 1.40% |
+ 1.78 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD12 |
+ R2742E.2.CEL |
+ 2.127 |
+ 134.14 |
+ 57.00% |
+ 41.60% |
+ 1.40% |
+ 1.64 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD12 |
+ R2543E.1.CEL |
+ 1.61 |
+ 118 |
+ 58.60% |
+ 39.90% |
+ 1.60% |
+ 1.43 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD13 |
+ R2586E.1.CEL |
+ 2.01 |
+ 74 |
+ 56.40% |
+ 42.00% |
+ 1.60% |
+ 2.85 |
+ 3.81 |
+ 1 |
+ |
+
+
+ | 44 |
+ R877E.2 |
+ BXD13 |
+ R877E.2.CEL |
+ 1.558 |
+ 125.63 |
+ 61.20% |
+ 37.50% |
+ 1.20% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD14 |
+ R2557E.1.CEL |
+ 1.83 |
+ 99 |
+ 62.50% |
+ 36.10% |
+ 1.40% |
+ 1.31 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD14 |
+ R1128E.2.CEL |
+ 1.91 |
+ 115 |
+ 59.90% |
+ 38.80% |
+ 1.40% |
+ 1.2 |
+ 0.82 |
+ 1 |
+ Y |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD15 |
+ R2701E.3.CEL |
+ 1 |
+ 88 |
+ 60.60% |
+ 37.90% |
+ 1.40% |
+ 1.5 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD15 |
+ R2716E.2.CEL |
+ 2.015 |
+ 150.83 |
+ 56.40% |
+ 42.10% |
+ 1.60% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD16 |
+ R2711E.2.CEL |
+ 1.953 |
+ 118.53 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD16 |
+ R2567E.1.CEL |
+ 2.24 |
+ 82 |
+ 56.70% |
+ 41.60% |
+ 1.70% |
+ 1.37 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD18 |
+ R2720E.2.CEL |
+ 2.32 |
+ 99.93 |
+ 59.50% |
+ 39.00% |
+ 1.50% |
+ 1.33 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD18 |
+ R2559E.1.CEL |
+ 1.65 |
+ 104 |
+ 60.80% |
+ 37.70% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD19 |
+ R2560E.1.CEL |
+ 1.79 |
+ 98 |
+ 60.90% |
+ 37.50% |
+ 1.60% |
+ 1.35 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD19 |
+ R2713E.2.CEL |
+ 1.67 |
+ 120.82 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD20 |
+ R2584E.1.CEL |
+ 2.07 |
+ 84 |
+ 59.30% |
+ 39.10% |
+ 1.60% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD20 |
+ R2731E.2.CEL |
+ 1.825 |
+ 147 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.4 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD21 |
+ R2702E.2.CEL |
+ 1.811 |
+ 128.65 |
+ 59.40% |
+ 39.10% |
+ 1.40% |
+ 1.26 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD21 |
+ R2541E2.1.CEL |
+ 2.63 |
+ 125 |
+ 56.00% |
+ 42.40% |
+ 1.50% |
+ 1.29 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD22 |
+ R2553E.1.CEL |
+ 1.95 |
+ 111 |
+ 59.90% |
+ 38.50% |
+ 1.50% |
+ 1.28 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD22 |
+ R2700E.2.CEL |
+ 1.858 |
+ 102.96 |
+ 61.50% |
+ 37.10% |
+ 1.30% |
+ 1.48 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD23 |
+ R2558E-2.1.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD23 |
+ R1086E.2.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD24 |
+ R2719E.2.CEL |
+ 1.47 |
+ 140.38 |
+ 61.50% |
+ 37.20% |
+ 1.30% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD24 |
+ R2589E2.1.CEL |
+ 2.61 |
+ 112 |
+ 57.50% |
+ 40.90% |
+ 1.60% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD25 |
+ R2573E-2.1.CEL |
+ 3.15 |
+ 72 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.77 |
+ 0.97 |
+ 1 |
+ |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD25 |
+ R2683E.2.CEL |
+ 1.777 |
+ 115.64 |
+ 58.30% |
+ 40.30% |
+ 1.40% |
+ 2.01 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD27 |
+ R2703E.2.CEL |
+ 1.263 |
+ 134.78 |
+ 62.60% |
+ 36.10% |
+ 1.40% |
+ 1.44 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD27 |
+ R2729E.3.CEL |
+ 1 |
+ 87 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.56 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD28 |
+ R2562E.3.CEL |
+ 1.65 |
+ 116 |
+ 59.90% |
+ 38.40% |
+ 1.70% |
+ 1.37 |
+ 0.79 |
+ 3 |
+ Y |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD28 |
+ R2721E.2.CEL |
+ 2.065 |
+ 157.39 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD29 |
+ R2561E.3.CEL |
+ 1 |
+ 77 |
+ 53.30% |
+ 45.40% |
+ 1.40% |
+ 3.36 |
+ 19.66 |
+ 3 |
+ |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD31 |
+ R1258E.2.CEL |
+ 2.063 |
+ 117.09 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.54 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD31 |
+ R2597E.1.CEL |
+ 2.37 |
+ 94 |
+ 60.30% |
+ 38.30% |
+ 1.50% |
+ 1.34 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD32 |
+ R2563E.1.CEL |
+ 1.55 |
+ 102 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD32 |
+ R1216E.2.CEL |
+ 2.23 |
+ 111.99 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.35 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD33 |
+ R2542E.1.CEL |
+ 2.13 |
+ 97 |
+ 56.50% |
+ 41.80% |
+ 1.60% |
+ 1.91 |
+ 0.93 |
+ 1 |
+ |
+
+
+ | 77 |
+ R857E.2 |
+ BXD33 |
+ R857E.2.CEL |
+ 1.737 |
+ 113.98 |
+ 61.90% |
+ 36.70% |
+ 1.30% |
+ 1.6 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD34 |
+ R1451E.2.CEL |
+ 1.843 |
+ 140.05 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ Y |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD34 |
+ R2585E.1.CEL |
+ 2.64 |
+ 75 |
+ 58.30% |
+ 40.00% |
+ 1.70% |
+ 1.25 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD36 |
+ R2698E.3.CEL |
+ 1 |
+ 86 |
+ 59.70% |
+ 39.00% |
+ 1.30% |
+ 1.46 |
+ 0.78 |
+ 3 |
+ |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD36 |
+ R2705E.3.CEL |
+ 1 |
+ 86 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.46 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD38 |
+ R2710E.2.CEL |
+ 2.112 |
+ 122.1 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.37 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD38 |
+ R2532E.1.CEL |
+ 2.04 |
+ 94 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.37 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD39 |
+ R2574E.1.CEL |
+ 1.98 |
+ 91 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD39 |
+ R2695E.2.CEL |
+ 1.638 |
+ 122.7 |
+ 60.80% |
+ 37.80% |
+ 1.50% |
+ 1.42 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD40 |
+ R2699E.2.CEL |
+ 1.827 |
+ 105.23 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD40 |
+ R2590E.1.CEL |
+ 2.71 |
+ 77 |
+ 59.10% |
+ 39.30% |
+ 1.50% |
+ 1.4 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD42 |
+ R2696E.2.CEL |
+ 1.622 |
+ 118.95 |
+ 62.00% |
+ 36.60% |
+ 1.50% |
+ 1.53 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD42 |
+ R2596E.1.CEL |
+ 2.63 |
+ 108 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 90 |
+ R994E.2 |
+ BXD43 |
+ R994E.2.CEL |
+ 1.966 |
+ 113.12 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.66 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD43 |
+ R2607E.1.CEL |
+ 2.43 |
+ 115 |
+ 58.60% |
+ 40.00% |
+ 1.40% |
+ 1.31 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD44 |
+ R2594E.1.CEL |
+ 1.77 |
+ 117 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.35 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD44 |
+ R2610E.2.CEL |
+ 1.814 |
+ 142.91 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.35 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD45 |
+ R2732E.2.CEL |
+ 2.154 |
+ 122.45 |
+ 56.50% |
+ 42.10% |
+ 1.40% |
+ 1.8 |
+ 0.83 |
+ 2 |
+ |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD45 |
+ R2592E.1.CEL |
+ 1.85 |
+ 106 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.43 |
+ 0.85 |
+ 1 |
+ Y |
+
+
+ | 96 |
+ R967E.2 |
+ BXD48 |
+ R967E.2.CEL |
+ 1.948 |
+ 130.95 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.63 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD48 |
+ R2606E.1.CEL |
+ 2.56 |
+ 106 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.35 |
+ 0.83 |
+ 1 |
+ Y |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD50 |
+ R2933E.3.CEL |
+ 1 |
+ 72 |
+ 52.90% |
+ 45.60% |
+ 1.50% |
+ 2.45 |
+ 0.98 |
+ 3 |
+ |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD50 |
+ R2937E.3.CEL |
+ 1 |
+ 89 |
+ 56.90% |
+ 41.60% |
+ 1.40% |
+ 1.81 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD51 |
+ R2603E.1.CEL |
+ 2.49 |
+ 115 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD51 |
+ R1042E.2.CEL |
+ 2.352 |
+ 104.12 |
+ 58.70% |
+ 39.90% |
+ 1.40% |
+ 1.53 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD55 |
+ R2980E.3.CEL |
+ 1 |
+ 82 |
+ 56.90% |
+ 41.70% |
+ 1.50% |
+ 1.77 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD55 |
+ R2690E.2.CEL |
+ 1.887 |
+ 164.01 |
+ 56.10% |
+ 42.30% |
+ 1.60% |
+ 1.43 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 104 |
+ R4176E |
+ BXD56 |
+ R4176E.CEL |
+ 4.75 |
+ 43.08 |
+ 63.00% |
+ 35.60% |
+ 1.30% |
+ 1.39 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 105 |
+ R4175E |
+ BXD56 |
+ R4175E.CEL |
+ 6 |
+ 38.49 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.47 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD60 |
+ R1006E.3.CEL |
+ 1 |
+ 98 |
+ 54.90% |
+ 43.70% |
+ 1.50% |
+ 2.7 |
+ 0.86 |
+ 3 |
+ |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD60 |
+ R2725E.2.CEL |
+ 1.551 |
+ 148.01 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD60 |
+ R1074E.3.CEL |
+ 1 |
+ 118 |
+ 55.50% |
+ 43.10% |
+ 1.40% |
+ 1.96 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD61 |
+ R2534E2.1.CEL |
+ 2.47 |
+ 118 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.42 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD61 |
+ R2684E.2.CEL |
+ 2.01 |
+ 131.03 |
+ 57.00% |
+ 41.50% |
+ 1.50% |
+ 1.34 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD62 |
+ R1107E.3.CEL |
+ 1 |
+ 83 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.43 |
+ 0.93 |
+ 3 |
+ |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD62 |
+ R2681E.2.CEL |
+ 2.086 |
+ 148.24 |
+ 57.20% |
+ 41.30% |
+ 1.50% |
+ 1.29 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 113 |
+ R965E.3 |
+ BXD62 |
+ R965E.3.CEL |
+ 1 |
+ 93.55 |
+ 53.30% |
+ 45.20% |
+ 1.50% |
+ 3.11 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD63 |
+ R1425E.2.CEL |
+ 1.7 |
+ 136 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.43 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD63 |
+ R2576E.3.CEL |
+ 1 |
+ 84 |
+ 61.30% |
+ 37.40% |
+ 1.40% |
+ 1.48 |
+ 0.76 |
+ 3 |
+ |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD64 |
+ R943E-2.2.CEL |
+ 1.591 |
+ 141.34 |
+ 60.10% |
+ 38.40% |
+ 1.50% |
+ 1.32 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD64 |
+ R2611E.1.CEL |
+ 2.29 |
+ 92 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 1.57 |
+ 1.06 |
+ 1 |
+ |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD65 |
+ R2689E.2.CEL |
+ 1.721 |
+ 142.44 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.38 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD65 |
+ R2583E.1.CEL |
+ 2.49 |
+ 70 |
+ 56.90% |
+ 41.50% |
+ 1.60% |
+ 1.67 |
+ 1.01 |
+ 1 |
+ |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD66 |
+ R2728E.2.CEL |
+ 1.714 |
+ 137.45 |
+ 59.40% |
+ 39.00% |
+ 1.60% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD66 |
+ R2536E2.1.CEL |
+ 2.74 |
+ 109 |
+ 56.10% |
+ 42.30% |
+ 1.70% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD66 |
+ R1207E.2.CEL |
+ 1.681 |
+ 136.86 |
+ 60.40% |
+ 38.10% |
+ 1.50% |
+ 1.45 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD67 |
+ R1192E.2.CEL |
+ 2.126 |
+ 123.37 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD67 |
+ R2727E.3.CEL |
+ 1 |
+ 82.55 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.97 |
+ 0.87 |
+ 2 |
+ |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD67 |
+ R2691E.3.CEL |
+ 1 |
+ 90 |
+ 54.80% |
+ 43.80% |
+ 1.50% |
+ 2.61 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD68 |
+ R2551E.1.CEL |
+ 2.49 |
+ 92 |
+ 54.30% |
+ 44.10% |
+ 1.60% |
+ 2.91 |
+ 1.55 |
+ 1 |
+ |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD68 |
+ R2726E.2.CEL |
+ 1.811 |
+ 153.09 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD69 |
+ R2593E.1.CEL |
+ 1.67 |
+ 128 |
+ 59.20% |
+ 39.50% |
+ 1.30% |
+ 1.47 |
+ 0.92 |
+ 1 |
+ Y |
+
+
+ | 129 |
+ R975E.2 |
+ BXD70 |
+ R975E.2.CEL |
+ 1.841 |
+ 137.97 |
+ 58.00% |
+ 40.50% |
+ 1.40% |
+ 1.36 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD70 |
+ R2537E2.1.CEL |
+ 2.93 |
+ 99 |
+ 58.00% |
+ 40.50% |
+ 1.60% |
+ 1.29 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 131 |
+ R4531E |
+ BXD71 |
+ R4531E.CEL |
+ 4.77 |
+ 43.48 |
+ 62.40% |
+ 36.30% |
+ 1.40% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 132 |
+ R4532E |
+ BXD71 |
+ R4532E.CEL |
+ 5.89 |
+ 40.68 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD73 |
+ R2779E.2.CEL |
+ 1.746 |
+ 121.11 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD73 |
+ R3024E.3.CEL |
+ 1 |
+ 78.05 |
+ 51.70% |
+ 46.60% |
+ 1.70% |
+ 2.3 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD75 |
+ R2565E.1.CEL |
+ 1.79 |
+ 102 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 2.31 |
+ 3.47 |
+ 1 |
+ |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD75 |
+ R1397E-re.2.CEL |
+ 1.449 |
+ 189.71 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD77 |
+ R2687E.3.CEL |
+ 1 |
+ 80 |
+ 58.00% |
+ 40.60% |
+ 1.40% |
+ 1.57 |
+ 0.8 |
+ 3 |
+ Y |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD77 |
+ R2717E.2.CEL |
+ 1.797 |
+ 84.43 |
+ 61.60% |
+ 36.90% |
+ 1.40% |
+ 1.49 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD77 |
+ R1421E.3.CEL |
+ 1 |
+ 94 |
+ 52.40% |
+ 46.20% |
+ 1.40% |
+ 2.29 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD80 |
+ R2579E.1.CEL |
+ 2.42 |
+ 72 |
+ 59.20% |
+ 39.40% |
+ 1.50% |
+ 1.73 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD80 |
+ R2686E.2.CEL |
+ 2.342 |
+ 119.63 |
+ 56.00% |
+ 42.60% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD83 |
+ R2956E.3.CEL |
+ 1 |
+ 84 |
+ 55.40% |
+ 43.20% |
+ 1.40% |
+ 1.39 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD83 |
+ R2960E.3.CEL |
+ 1 |
+ 80 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.5 |
+ 0.82 |
+ 3 |
+ Y |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD84 |
+ R2922E.3.CEL |
+ 1 |
+ 91 |
+ 57.80% |
+ 40.80% |
+ 1.50% |
+ 1.47 |
+ 0.83 |
+ 3 |
+ Y |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD84 |
+ R2895E.3.CEL |
+ 1 |
+ 75 |
+ 58.30% |
+ 40.20% |
+ 1.50% |
+ 1.56 |
+ 0.77 |
+ 3 |
+ Y |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD85 |
+ R2692E.2.CEL |
+ 1.423 |
+ 160.87 |
+ 60.20% |
+ 38.30% |
+ 1.40% |
+ 1.46 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD85 |
+ R2715E.2.CEL |
+ 1.488 |
+ 142.6 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.5 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD86 |
+ R1405E.2.CEL |
+ 2.351 |
+ 119.34 |
+ 56.40% |
+ 42.20% |
+ 1.40% |
+ 1.64 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD86 |
+ R1225E.3.CEL |
+ 1 |
+ 71 |
+ 53.90% |
+ 44.60% |
+ 1.40% |
+ 3.2 |
+ 1.61 |
+ 3 |
+ |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD87 |
+ R2724E.2.CEL |
+ 1.906 |
+ 113.71 |
+ 60.70% |
+ 37.90% |
+ 1.40% |
+ 1.45 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD87 |
+ R2540E.1.CEL |
+ 2.33 |
+ 93 |
+ 61.10% |
+ 37.40% |
+ 1.40% |
+ 1.22 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD89 |
+ R1433E.2.CEL |
+ 1 |
+ 2.241 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.41 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD89 |
+ R2546E.1.CEL |
+ 1.99 |
+ 96 |
+ 58.60% |
+ 39.70% |
+ 1.70% |
+ 1.47 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD90 |
+ R2578E2.1.CEL |
+ 2.79 |
+ 92 |
+ 58.60% |
+ 39.80% |
+ 1.60% |
+ 1.52 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 155 |
+ R859E.2 |
+ BXD90 |
+ R859E.2.CEL |
+ 1.847 |
+ 152.22 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.36 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD92 |
+ R2682E.2.CEL |
+ 1.547 |
+ 156.31 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.37 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD92 |
+ R1388E.3.CEL |
+ 1 |
+ 63 |
+ 60.00% |
+ 38.60% |
+ 1.40% |
+ 1.85 |
+ 1.03 |
+ 3 |
+ |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD92 |
+ R1322E.3.CEL |
+ 1 |
+ 80 |
+ 55.90% |
+ 42.60% |
+ 1.50% |
+ 1.75 |
+ 0.74 |
+ 3 |
+ |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD96 |
+ R2733E.2.CEL |
+ 1.7 |
+ 113.99 |
+ 62.10% |
+ 36.60% |
+ 1.30% |
+ 1.4 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD96 |
+ R2554E.1.CEL |
+ 2.18 |
+ 93 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD97 |
+ R2649E.2.CEL |
+ 2.343 |
+ 119.04 |
+ 57.50% |
+ 41.20% |
+ 1.40% |
+ 1.53 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD97 |
+ R2577E.1.CEL |
+ 2.07 |
+ 77 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.87 |
+ 1.29 |
+ 1 |
+ |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD98 |
+ R2645E.3.CEL |
+ 1 |
+ 88 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.59 |
+ 0.81 |
+ 3 |
+ Y |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD98 |
+ R2688E.2.CEL |
+ 1.772 |
+ 145.24 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.48 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 165 |
+ R4533E |
+ BXD99 |
+ R4533E.CEL |
+ 1 |
+ 37.69 |
+ 60.30% |
+ 38.20% |
+ 1.40% |
+ 1.33 |
+ 0.89 |
+ 4 |
+ Y |
+
+
+ | 166 |
+ R4534E |
+ BXD99 |
+ R4534E.CEL |
+ 5.69 |
+ 36.62 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.16 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 167 |
+ R2885E.3 |
+ BXSB/MpJ |
+ R2885E.3.CEL |
+ 1 |
+ 76 |
+ 58.10% |
+ 40.60% |
+ 1.30% |
+ 1.88 |
+ 1.06 |
+ 3 |
+ |
+
+
+ | 168 |
+ R2883E.3 |
+ BXSB/MpJ |
+ R2883E.3.CEL |
+ 1 |
+ 71 |
+ 56.40% |
+ 42.00% |
+ 1.50% |
+ 1.59 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 169 |
+ R1700E.1 |
+ C3H/HeJ |
+ R1700E.1.CEL |
+ 2.98 |
+ 69 |
+ 60.80% |
+ 37.90% |
+ 1.40% |
+ 1.48 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 170 |
+ R1704E.1 |
+ C3H/HeJ |
+ R1704E.1.CEL |
+ 2.58 |
+ 88 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.38 |
+ 0.84 |
+ 1 |
+ |
+
+
+ | 171 |
+ R2605E.1 |
+ C57BL/6J |
+ R2605E.1.CEL |
+ 1.82 |
+ 131 |
+ 60.50% |
+ 38.20% |
+ 1.30% |
+ 1.32 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 172 |
+ R0871E |
+ C57BL/6J |
+ R0871E.CEL |
+ 6.24 |
+ 37.38 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.41 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 173 |
+ R0872E.1 |
+ C57BL/6J |
+ R0872E.1.CEL |
+ 3.13 |
+ 89 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 174 |
+ R0872E |
+ C57BL/6J |
+ R0872E.CEL |
+ 3.128 |
+ 88.58 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 175 |
+ R4507E |
+ C57BL/6J-Nyx |
+ R4507E.CEL |
+ 8.13 |
+ 37.5 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.32 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 176 |
+ R4508E |
+ C57BL/6J-Nyx |
+ R4508E.CEL |
+ 6.33 |
+ 37.26 |
+ 60.90% |
+ 37.80% |
+ 1.30% |
+ 1.24 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 177 |
+ R4505E |
+ C57BL/6J-Rpe65 |
+ R4505E.CEL |
+ 5.98 |
+ 37.48 |
+ 61.80% |
+ 36.80% |
+ 1.40% |
+ 1.45 |
+ 0.85 |
+ 4 |
+ Y |
+
+
+ | 178 |
+ R4506E |
+ C57BL/6J-Rpe65 |
+ R4506E.CEL |
+ 6.94 |
+ 37.9 |
+ 61.10% |
+ 37.50% |
+ 1.30% |
+ 1.5 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 179 |
+ R4535E |
+ C57BLKS/J |
+ R4535E.CEL |
+ 6.59 |
+ 37.28 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.26 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 180 |
+ R4536E |
+ C57BLKS/J |
+ R4536E.CEL |
+ 1 |
+ 40.71 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 181 |
+ R2564E.1 |
+ CAST/EiJ |
+ R2564E.1.CEL |
+ 1.94 |
+ 89 |
+ 58.50% |
+ 39.90% |
+ 1.60% |
+ 1.6 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 182 |
+ R2580E.1 |
+ CAST/EiJ |
+ R2580E.1.CEL |
+ 2.09 |
+ 95 |
+ 58.20% |
+ 40.10% |
+ 1.70% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ |
+
+
+ | 183 |
+ R4537E |
+ CBA/CaJ |
+ R4537E.CEL |
+ 1 |
+ 38.45 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.63 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 184 |
+ R4538E |
+ CBA/CaJ |
+ R4538E.CEL |
+ 5.89 |
+ 39.18 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.45 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 185 |
+ R4539E |
+ CZECHII/EiJ |
+ R4539E.CEL |
+ 7.73 |
+ 37.1 |
+ 58.30% |
+ 40.10% |
+ 1.50% |
+ 1.7 |
+ 0.95 |
+ 4 |
+ Y |
+
+
+ | 186 |
+ R4540E |
+ CZECHII/EiJ |
+ R4540E.CEL |
+ 11.04 |
+ 36.69 |
+ 53.00% |
+ 45.30% |
+ 1.70% |
+ 1.83 |
+ 1.32 |
+ 4 |
+ |
+
+
+ | 187 |
+ R2600E.1 |
+ D2B6F1 |
+ R2600E.1.CEL |
+ 2.47 |
+ 95 |
+ 58.10% |
+ 40.20% |
+ 1.70% |
+ 1.41 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 188 |
+ R2604E.1 |
+ D2B6F1 |
+ R2604E.1.CEL |
+ 2.66 |
+ 90 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 189 |
+ R1002E.3 |
+ DBA/2J |
+ R1002E.3.CEL |
+ 1 |
+ 102 |
+ 54.80% |
+ 43.70% |
+ 1.50% |
+ 2.84 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 190 |
+ R4541E |
+ DBA/2J |
+ R4541E.CEL |
+ 1 |
+ 43.4 |
+ 61.40% |
+ 37.00% |
+ 1.50% |
+ 1.37 |
+ 0.73 |
+ 4 |
+ Y |
+
+
+ | 191 |
+ R959E.3 |
+ DBA/2J |
+ R959E.3.CEL |
+ 1 |
+ 89.97 |
+ 53.20% |
+ 45.30% |
+ 1.50% |
+ 3.66 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 192 |
+ R2572E.1 |
+ DBA/2J |
+ R2572E.1.CEL |
+ 2.41 |
+ 79 |
+ 55.50% |
+ 42.90% |
+ 1.60% |
+ 1.37 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 193 |
+ R4542E |
+ DBA/2J |
+ R4542E.CEL |
+ 5.7 |
+ 39.95 |
+ 61.00% |
+ 37.40% |
+ 1.50% |
+ 1.23 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 194 |
+ R2771E.3 |
+ FVB/NJ |
+ R2771E.3.CEL |
+ 1 |
+ 70 |
+ 55.30% |
+ 43.20% |
+ 1.50% |
+ 1.69 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 195 |
+ R2772E.3 |
+ FVB/NJ |
+ R2772E.3.CEL |
+ 1 |
+ 76 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.13 |
+ 1.02 |
+ 3 |
+ |
+
+
+ | 196 |
+ R2636E.1 |
+ KK/HlJ |
+ R2636E.1.CEL |
+ 2.61 |
+ 93 |
+ 58.90% |
+ 39.50% |
+ 1.50% |
+ 1.39 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 197 |
+ R2637E.1 |
+ KK/HlJ |
+ R2637E.1.CEL |
+ 2.19 |
+ 103 |
+ 59.40% |
+ 39.00% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 198 |
+ R0999E.1 |
+ LG/J |
+ R0999E.1.CEL |
+ 2.45 |
+ 82 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 199 |
+ R1004E.1 |
+ LG/J |
+ R1004E.1.CEL |
+ 2.44 |
+ 92 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 200 |
+ R4543E |
+ LP/J |
+ R4543E.CEL |
+ 6.57 |
+ 41.99 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.28 |
+ 0.75 |
+ 4 |
+ Y |
+
+
+ | 201 |
+ R4544E |
+ LP/J |
+ R4544E.CEL |
+ 4.56 |
+ 39.9 |
+ 62.40% |
+ 36.10% |
+ 1.50% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 202 |
+ R2858E.3 |
+ MOLF/EiJ |
+ R2858E.3.CEL |
+ 1 |
+ 64 |
+ 53.80% |
+ 44.70% |
+ 1.50% |
+ 1.59 |
+ 0.95 |
+ 3 |
+ |
+
+
+ | 203 |
+ R2919.3 |
+ MOLF/EiJ |
+ R2919.3.CEL |
+ 1 |
+ 64 |
+ 52.40% |
+ 46.00% |
+ 1.60% |
+ 2.15 |
+ 1.07 |
+ 3 |
+ |
+
+
+ | 204 |
+ R1688E.1 |
+ NOD/LtJ |
+ R1688E.1.CEL |
+ 2.66 |
+ 98 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 205 |
+ R2566E-2.1 |
+ NOD/LtJ |
+ R2566E-2.1.CEL |
+ 3.03 |
+ 69 |
+ 59.80% |
+ 38.80% |
+ 1.50% |
+ 1.38 |
+ 0.75 |
+ 1 |
+ Y |
+
+
+ | 206 |
+ R4545E |
+ NZB/BlNJ |
+ R4545E.CEL |
+ 4.23 |
+ 43.48 |
+ 62.10% |
+ 36.40% |
+ 1.50% |
+ 1.33 |
+ 0.76 |
+ 4 |
+ Y |
+
+
+ | 207 |
+ R4546E |
+ NZB/BlNJ |
+ R4546E.CEL |
+ 6.27 |
+ 44.22 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.17 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 208 |
+ R2535E.1 |
+ NZO/HlLtJ |
+ R2535E.1.CEL |
+ 1.89 |
+ 86 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.41 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 209 |
+ R2550E.1 |
+ NZO/HlLtJ |
+ R2550E.1.CEL |
+ 1.79 |
+ 87 |
+ 60.70% |
+ 37.80% |
+ 1.50% |
+ 1.52 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 210 |
+ R2817E.3 |
+ NZW/LacJ |
+ R2817E.3.CEL |
+ 1 |
+ 59 |
+ 50.90% |
+ 47.60% |
+ 1.50% |
+ 3.59 |
+ 1.48 |
+ 3 |
+ |
+
+
+ | 211 |
+ R2810E |
+ NZW/LacJ |
+ R2810E.CEL |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ 3 |
+ |
+
+
+ | 212 |
+ R2810E.3 |
+ NZW/LacJ |
+ R2810E.3.CEL |
+ 1 |
+ 74 |
+ 57.00% |
+ 41.70% |
+ 1.40% |
+ 2.15 |
+ 1.03 |
+ 4 |
+ Y |
+
+
+ | 213 |
+ R4547E |
+ PANCEVO/EiJ |
+ R4547E.CEL |
+ 5.27 |
+ 51.34 |
+ 57.20% |
+ 41.10% |
+ 1.70% |
+ 1.7 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 214 |
+ R4548E |
+ PANCEVO/EiJ |
+ R4548E.CEL |
+ 10.54 |
+ 37.39 |
+ 50.30% |
+ 48.00% |
+ 1.70% |
+ 1.68 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 215 |
+ R2635E.1 |
+ PWD/PhJ |
+ R2635E.1.CEL |
+ 3.72 |
+ 80 |
+ 54.20% |
+ 44.10% |
+ 1.70% |
+ 1.53 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 216 |
+ R2634E.1 |
+ PWD/PhJ |
+ R2634E.1.CEL |
+ 3.29 |
+ 90 |
+ 55.90% |
+ 42.50% |
+ 1.60% |
+ 1.57 |
+ 0.81 |
+ 1 |
+ |
+
+
+ | 217 |
+ R2544E.1 |
+ PWK/PhJ |
+ R2544E.1.CEL |
+ 2.2 |
+ 108 |
+ 54.90% |
+ 43.50% |
+ 1.70% |
+ 1.36 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 218 |
+ R2549E.1 |
+ PWK/PhJ |
+ R2549E.1.CEL |
+ 2.28 |
+ 84 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.57 |
+ 0.83 |
+ 1 |
+ |
+
+
+ | 219 |
+ R4550E |
+ SJL/J |
+ R4550E.CEL |
+ 5.35 |
+ 40.44 |
+ 62.30% |
+ 36.20% |
+ 1.40% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ |
+
+
+ | 220 |
+ R2368E.1 |
+ WSB/EiJ |
+ R2368E.1.CEL |
+ 2.57 |
+ 86 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.29 |
+ 0.74 |
+ 1 |
+ Y |
+
+
+ | 221 |
+ R2547E.1 |
+ WSB/EiJ |
+ R2547E.1.CEL |
+ 2.14 |
+ 90 |
+ 58.20% |
+ 40.10% |
+ 1.60% |
+ 1.32 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0908_r/summary.rtf b/general/datasets/Eye_m2_0908_r/summary.rtf
new file mode 100644
index 0000000..44b7e23
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r/summary.rtf
@@ -0,0 +1,12 @@
+FINAL RECOMMENDED EYE DATA SET. The HEIMED September 2008 RMA data release provides estimates of gene expression in whole eyes of 103 lines of young adult mice generated using 221 Affymetrix M430 2.0 arrays. This data set is intended for exploration of the genetics and genomics of the mouse eye, retina, lens, retinal pigment epithelium, cornea, iris and choroid. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). We used pooled RNA samples, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+Users of these mouse eye data may also find the following complementary resources extremely useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
diff --git a/general/datasets/Eye_m2_0908_r/tissue.rtf b/general/datasets/Eye_m2_0908_r/tissue.rtf
new file mode 100644
index 0000000..9b6ee0f
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r/tissue.rtf
@@ -0,0 +1,2058 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of cRNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. All samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center led by Dr. Weikuan Gu. All arrays were processed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. C until use (roughly one third) or were used immediately for hybridization.
+
+Dealing with ocular pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations taken from brown and beige colored mice tend to have faint residual pigmentation that affects hybridization signal. To address this problem, Dr. Yan Jiao purified total RNA using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204) all four batches.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well balanced sample of males and females, in general without within-strain-by-sex replication. Two strains are represented by a single male sample pool (BXD29 and A/J). Four lines are represented by two or three male sample pools (all of the five DeltaGen KO line). The SJL/J may be a single mixed sex sample. Users can study possible sex effects by comparing any results of expression data to that of a surrogate measurement that summarizes the overall sex balance of HEIMED. To do this just compare your data to those of probe sets 1427262_at (Xist, high in females) and probe set 1426438_at (Ddx3y, high in males). These two sex-specific probes are quantitative surrogates for the sex balance in this data set.
+
+Technical duplicates: One sample, highlighted in the tables below, is a technical duplicate. The pair of technical duplicates were both of high quality. For statistical analysis, they should be combined and treated as single biological sample.
+
+Batch structure: This data set consists of four batches (Table 2, far right column). The final September 2008 data set consists of a total of 221 arrays and 220 independent samples.
+
+
+ - Batch 1: November 2005, n = 78 arrays original arrays of which 76 were accepted into this final data set.
+ - Batch 2: January 2006, n = 62 arrays of which 62 were accepted.
+ - Batch 3: August 2006, n = 39 arrays of which 36 were accepted. (These three batches, including some arrays that were eventually dropped from the final 2008 data set, were combined to form the September 2006 data set.)
+ - Batch 4: Summer 2008, n = 53 arrays of which 47 were accepted.
+
+
+Table 1: HEIMED case IDs, including sample tube ID, strain, age, sex, and source of mice (see Table 2 for information on array quality control)
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Group |
+ Strain |
+ Age |
+ Sex |
+ Source |
+
+
+ | 1 |
+ R2595E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 2 |
+ R2533E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 3 |
+ R0754E.1 |
+ GDP |
+ A/J |
+ 60 |
+ M |
+ JAX |
+
+
+ | 4 |
+ R4521E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 5 |
+ R4522E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 6 |
+ R4523E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 7 |
+ R4526E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 8 |
+ R4509E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 9 |
+ R4510E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 10 |
+ R4511E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 20 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 11 |
+ R4524E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 12 |
+ R4525E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 13 |
+ R4515E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 14 |
+ R4516E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 15 |
+ R4517E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 16 |
+ R4512E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 17 |
+ R4513E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 25 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 18 |
+ R4514E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 19 |
+ R4518E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 70 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 20 |
+ R4519E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 68 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 21 |
+ R2601E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 22 |
+ R2602E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 23 |
+ R1676E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ F |
+ JAX |
+
+
+ | 24 |
+ R1672E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 25 |
+ R4530E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 26 |
+ R4529E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD |
+ BXD1 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD |
+ BXD1 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD |
+ BXD2 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD |
+ BXD2 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD |
+ BXD5 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD |
+ BXD5 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD |
+ BXD6 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD |
+ BXD6 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD |
+ BXD8 |
+ 77 |
+ F |
+ UTHSC RW |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD |
+ BXD8 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD |
+ BXD9 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD |
+ BXD9 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD |
+ BXD11 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD |
+ BXD11 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD |
+ BXD12 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD |
+ BXD12 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD |
+ BXD13 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 44 |
+ R877E.2 |
+ BXD |
+ BXD13 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD |
+ BXD14 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD |
+ BXD14 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD |
+ BXD15 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD |
+ BXD15 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD |
+ BXD16 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD |
+ BXD16 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD |
+ BXD18 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD |
+ BXD18 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD |
+ BXD19 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD |
+ BXD19 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD |
+ BXD20 |
+ 59 |
+ F |
+ BIDMC GR |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD |
+ BXD20 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD |
+ BXD21 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD |
+ BXD21 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD |
+ BXD22 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD |
+ BXD22 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD |
+ BXD23 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD |
+ BXD23 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD |
+ BXD24 |
+ 123 |
+ F |
+ UTHSC RW |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD |
+ BXD24 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD |
+ BXD25 |
+ 67 |
+ F |
+ UAB |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD |
+ BXD25 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD |
+ BXD27 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD |
+ BXD27 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD |
+ BXD28 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD |
+ BXD28 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD |
+ BXD29 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD |
+ BXD31 |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD |
+ BXD31 |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD |
+ BXD32 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD |
+ BXD32 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD |
+ BXD33 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 77 |
+ R857E.2 |
+ BXD |
+ BXD33 |
+ 77 |
+ M |
+ UTHSC RW |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD |
+ BXD34 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD |
+ BXD34 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD |
+ BXD36 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD |
+ BXD36 |
+ 57 |
+ M |
+ BIDMC GR |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD |
+ BXD38 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD |
+ BXD38 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD |
+ BXD39 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD |
+ BXD39 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD |
+ BXD40 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD |
+ BXD40 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD |
+ BXD42 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD |
+ BXD42 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 90 |
+ R994E.2 |
+ BXD |
+ BXD43 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD |
+ BXD43 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD |
+ BXD44 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD |
+ BXD44 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD |
+ BXD45 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD |
+ BXD45 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 96 |
+ R967E.2 |
+ BXD |
+ BXD48 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD |
+ BXD48 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD |
+ BXD51 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD |
+ BXD51 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD |
+ BXD55 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD |
+ BXD55 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 104 |
+ R4176E |
+ BXD |
+ BXD56 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 105 |
+ R4175E |
+ BXD |
+ BXD56 |
+ 53 |
+ M |
+ UTHSC RW |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD |
+ BXD60 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD |
+ BXD60 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD |
+ BXD60 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD |
+ BXD61 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD |
+ BXD61 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ F |
+ UTHSC RW |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD |
+ BXD62 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 113 |
+ R965E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD |
+ BXD63 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD |
+ BXD63 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD |
+ BXD64 |
+ 56 |
+ F |
+ UTHSC RW |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD |
+ BXD64 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD |
+ BXD65 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD |
+ BXD65 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD |
+ BXD66 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD |
+ BXD66 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD |
+ BXD66 |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD |
+ BXD67 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD |
+ BXD68 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD |
+ BXD69 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 129 |
+ R975E.2 |
+ BXD |
+ BXD70 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD |
+ BXD70 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 131 |
+ R4531E |
+ BXD |
+ BXD71 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 132 |
+ R4532E |
+ BXD |
+ BXD71 |
+ 86 |
+ M |
+ UTHSC RW |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD |
+ BXD73 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD |
+ BXD73 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD |
+ BXD75 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD |
+ BXD75 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD |
+ BXD77 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD |
+ BXD77 |
+ 107 |
+ M |
+ UTHSC RW |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD |
+ BXD77 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD |
+ BXD80 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD |
+ BXD80 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD |
+ BXD84 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD |
+ BXD84 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD |
+ BXD85 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD |
+ BXD85 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD |
+ BXD86 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD |
+ BXD86 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD |
+ BXD87 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD |
+ BXD87 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD |
+ BXD89 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD |
+ BXD89 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD |
+ BXD90 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 155 |
+ R859E.2 |
+ BXD |
+ BXD90 |
+ 72 |
+ M |
+ UTHSC RW |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD |
+ BXD92 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD |
+ BXD92 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD |
+ BXD92 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD |
+ BXD96 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD |
+ BXD96 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD |
+ BXD97 |
+ 74 |
+ F |
+ UTHSC RW |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD |
+ BXD97 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD |
+ BXD98 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD |
+ BXD98 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 165 |
+ R4533E |
+ BXD |
+ BXD99 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 166 |
+ R4534E |
+ BXD |
+ BXD99 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 167 |
+ R2885E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 168 |
+ R2883E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 169 |
+ R1700E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 170 |
+ R1704E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 171 |
+ R2605E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 79 |
+ F |
+ UTHSC RW |
+
+
+ | 172 |
+ R0871E |
+ GDP BXD |
+ C57BL/6J |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 173 |
+ R0872E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 174 |
+ R0872E |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 175 |
+ R4507E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 176 |
+ R4508E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 177 |
+ R4505E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 178 |
+ R4506E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 179 |
+ R4535E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ F |
+ JAX |
+
+
+ | 180 |
+ R4536E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ M |
+ JAX |
+
+
+ | 181 |
+ R2564E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ F |
+ JAX |
+
+
+ | 182 |
+ R2580E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ M |
+ JAX |
+
+
+ | 183 |
+ R4537E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 184 |
+ R4538E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 185 |
+ R4539E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 186 |
+ R4540E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 187 |
+ R2600E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 188 |
+ R2604E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 69 |
+ M |
+ UTHSC RW |
+
+
+ | 189 |
+ R1002E.3 |
+ GDP BXD |
+ DBA/2J |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 190 |
+ R4541E |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 191 |
+ R959E.3 |
+ GDP BXD |
+ DBA/2J |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 192 |
+ R2572E.1 |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 193 |
+ R4542E |
+ GDP BXD |
+ DBA/2J |
+ 59 |
+ M |
+ JAX |
+
+
+ | 194 |
+ R2771E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 195 |
+ R2772E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 196 |
+ R2636E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 197 |
+ R2637E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 198 |
+ R0999E.1 |
+ GDP |
+ LG/J |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 199 |
+ R1004E.1 |
+ GDP |
+ LG/J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 200 |
+ R4543E |
+ GDP |
+ LP/J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 201 |
+ R4544E |
+ GDP |
+ LP/J |
+ 65 |
+ M |
+ JAX |
+
+
+ | 202 |
+ R2858E.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 203 |
+ R2919.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 204 |
+ R1688E.1 |
+ GDP |
+ NOD/LtJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 205 |
+ R2566E-2.1 |
+ GDP |
+ NOD/LtJ |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 206 |
+ R4545E |
+ GDP |
+ NZB/BlNJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 207 |
+ R4546E |
+ GDP |
+ NZB/BlNJ |
+ 58 |
+ M |
+ BIDMC GR |
+
+
+ | 208 |
+ R2535E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 209 |
+ R2550E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ JAX |
+
+
+ | 210 |
+ R2817E.3 |
+ GDP |
+ NZW/LacJ |
+ 65 |
+ F |
+ BIDMC GR |
+
+
+ | 211 |
+ R2810E |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 212 |
+ R2810E.3 |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 213 |
+ R4547E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ F |
+ JAX |
+
+
+ | 214 |
+ R4548E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ M |
+ JAX |
+
+
+ | 215 |
+ R2635E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 216 |
+ R2634E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ M |
+ JAX |
+
+
+ | 217 |
+ R2544E.1 |
+ GDP |
+ PWK/PhJ |
+ 63 |
+ F |
+ JAX |
+
+
+ | 218 |
+ R2549E.1 |
+ GDP |
+ PWK/PhJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 219 |
+ R4550E |
+ GDP |
+ SJL/J |
+ 65 |
+ M+F |
+ JAX |
+
+
+ | 220 |
+ R2368E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 221 |
+ R2547E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0908_r_mt/acknowledgment.rtf b/general/datasets/Eye_m2_0908_r_mt/acknowledgment.rtf
new file mode 100644
index 0000000..5098d32
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_mt/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant and from funds from NEI grant to Dr. Eldon Geisert (R01EY017841), an NEI Vision Core grant (EY14080) and an Unrestricted Grant from Research To Prevent Blindness.
+
+We thank Dr. Ted Choi, Chief Scientific Director of Predictive Biology, Inc. (past director of molecular genetics at Deltagen Inc.) for providing us with eye samples from several interesting DeltaGen knockouts.
diff --git a/general/datasets/Eye_m2_0908_r_mt/cases.rtf b/general/datasets/Eye_m2_0908_r_mt/cases.rtf
new file mode 100644
index 0000000..552d4a5
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_mt/cases.rtf
@@ -0,0 +1,57 @@
+This is the complete and final HEIMED data set. HEIMED consists of expression data for 103 genetically defined lines of mice with standard errors of the mean. Almost all animals are young adults between 50 and 80 days of age (Table 1, maximum age is 123 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, reciprocal F1s between C57BL/6J and DBA/2J, and several mutant and knockout lines. We have combined all common strains, F1 hybrids, and mutants into a group called the Mouse Diversity Panel (MDP). Four lines, namely, C57BL/6J (B6), DBA/2J (D2), and the pair of B6D2F1 and D2B6F1 hybrids are common to both the MDP and the BXD set. This is a breakdown of cases that are part of HEIMED:
+
+
+ - 68 BXD strains. The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. Only one of these strains, BXD24 (know also known as BXD24b), has retinal degeneration (a spontaneous mutation). The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA.
+ - 35 MDP lines, including 26 inbred strains representing closely related substrains (e.g, BALB/cJ and BALB/cByJ), many of the most widely used common Mus musculus domesticus inbred strains (e.g., C57BL/6J and 129S1/SvImJ), inbred but wild-derived representatives of common subspecies (Mus musculus domesticus, e.g, WSB/EiJ; M. musculus musculus, e.g., CZECHII/EiJ; M. musculus molossinus, e.g., MOLF/EiJ; M. musculus castaneus, e.g., CAST/EiJ); and even one different species of mouse (Mus spicilegus, PANCEVO/EiJ). The MDP also includes the reciprocal F1 hybrids (B6D2F1 and D2B6F1) and the following 6 KO lines and the Nyx-nob mutant:
+ - 6 knockouts (KO), including a KO of Rpe65, and 5 DeltaGen Inc. knockout lines provided by Dr. Ted Choi. These KO lines have had a bacterial lacZ construct inserted into the gene. The endogenous promoter drives expression of beta-galactosidase. RT-PCR analysis detects a gene transcript in most tissues. The following KOs from DeltaGen were studied: Gabra1, Gabbr1, Gnb1, Gpr19, and Clcn3. We also included one spontaneous mutant of the nyctalopin (Nyx no b wave "nob") gene (Pardue et al., 1998) that is on a BALB/cByJ background.
+
+
+Rod photoreceptor degeneration in inbred mice: Six strains of mice included in HEIMED suffer from severe loss of photoreceptors (mainly rods) and have the equivalent of night blindness in human patients. The death of photoreceptors in these strains occurs by one to two months of age and is often caused by the retinal degeneration 1 (rd1) mutant allele in the rod cyclic-GMP phosphodiesterase 6 beta subunit gene (Pde6b). The following strains are known to have photoreceptor degeneration: C3H/HeJ, FVB/NJ, MOLF/EiJ, SJL/J and BXD24/TyJ. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEIMED data set.
+
+As expected (Dickerson LW et al., 2002) and as judged from the absence of rhodopsin expression, one of the DeltaGen KO lines (chloride ion channel 3, Clcn3) also has retinal degeneration: B6129P2F2N1-Clcn3. Degeneration in this strain is likely to include all rods and all cones. The cone defect is obvious from the decrease in expression of Gnat2, a gene associated with cones and achromatopsia in mice and humans.
+
+Lines of mice were selected using the following criteria:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - representation of a fairly wide variety of different subspecies of Mus
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Tel Aviv/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - interesting mutations or knockouts affecting genes with high expression in the eye
+ - general availability from The Jackson Laboratory. The only exception are the DeltaGen KO mice.
+
+
+We have included all eight parents of the Collaborative Cross (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/LtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ) in the MDP. Fourteen MDP strains have been partially sequenced by Perlegen for the NIEHS, including including 129S1/SvImJ, A/J, AKR/J, BALB/cByJ, C3H/HeJ, CAST/EiJ, DBA/2J, FVB/NJ, KK/HlJ, MOLF/EiJ, NOD/LtJ, NZW/LacJ, PWD/PhJ, and WSB/EiJ (see the GeneNetwork SNP Browser for data, details, and see Perlegen's excellent data resources and browser).
+
+
+ - 129S1/SvImJ : Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene. It is also a cone photoreceptor function loss 3 mutant (Cpfl3 allele) of the Gnat2 gene that is a model for achromatopsia (JAX Stock Number: 002448)
+ - A/J: Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase (Tyr c allele) albino mutant. This strain is particularly sensitive to light-induced photoreceptor loss (Danciger et al., 2007). (JAX Stock Number: 000646)
+ - BALB/cByJ: Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project old group A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Small brain, not aggressive (JAX Stock Number: 001026)
+ - BALB/cJ: Phenome Project A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Large brain and aggressive (JAX Stock Number: 000651)
+ - BXSB/MpJ: A white-bellied agouti strains with interesting autoimmune disease restricted to males that is associated with a mutation in the Yaa gene that causes glomerulonephritis, a dramatic increase in number of peripheral monocytes, and pre-B-cell deficiency (JAX Stock Number: 000740)
+ - C3H/HeJ: The Heston (He) substrain with a wildtype agouti (A allele) coat color. Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project old group A list. Important to note for this eye expression dataset, C3H/HeJ is a Pdeb6 rd1 mutant with near total photoreceptor loss at as early as postnatal day 30. Also a Tlr4 mutant that is endotoxin resistant. (JAX Stock Number: 000659)
+ - C57BL/6J: Sequenced by NIH/NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list. Single most widely used inbred strain of mouse. (JAX Stock Number: 000664)
+ - C57BLKS/J: Black Kaliss strain (non-agouti a allele) derived from C57BL/6J, but genetically contaminated at some point mainly with DBA/2J and then reinbred. Now at the Jackson Laboratory. (JAX Stock Number: 000662)
+ - CAST/EiJ: A wild-derived inbred Mus musculus castaneus strain. Samples of this subspecies were captured in Southeast Asia. One of three wild-derived strains in the Collaborative Cross sequenced by NIEHS; Phenome Project A list. CAST/Ei and CAST/EiJ are the same strain. The addition of the "J" is trivial and was added when stock were transferred from Dr. Eicher's lab to the Jackson Laboratory production facility in about 2004. (JAX Stock Number: 000928)
+ - CBA/CaJ: Agouti strain from the Jackson Laboratory. Wildtype pigment genes. (JAX Stock Number: 000654)
+ - CZECHII/EiJ: Czech 2 is a wild-derived inbred strain M. musculus musculus strain. Samples of this subspecies were caught in the Czech Republic and inbred at the Jackson Laboratory by Eva Eicher. White-bellied agouti. (JAX Stock Number: 001144).
+ - DBA/2J: The dilute, brown, agouti (dba) strain is the oldest inbred strain of mouse. Inbreeding was started in 1909 by Little. A tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. A myosin 5a (Myo5a d) dilute allele mutant. Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project old A group list. (JAX Stock Number: 000671)
+ - FVB/NJ: Friend's leukemia virus B (FVB) strain. Sequenced by Perlegen/NIEHS and Celera. Tyr c locus albino and a Pdeb6 rd1 mutant derived from Swiss mice at NIH. This has been the most common strain used to make transgenic mice due to large and easily injected oocytes; Phenome Project A list (JAX Stock Number: 001800).
+ - KK/HlJ: K Kondo's (KK) Kasukabe strain is a homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. Males have a form of type 2 diabetes. Sequenced by Perlegen/NIEHS. (JAX Stock Number: 002106)
+ - LG/J: Large (LG) strain. Paternal parent of the Large-by-Small set of RI strains made by James Cheverud and colleagues (the LGXSM panel, not to be confused with the LongXShort or LXS panel). A Tyr c locus albino strain. (JAX Stock Number: 000675)
+ - LP/J: White-bellied agouit strain with a piebald mutation in the endothelin receptor type B Ednrb gene from at the Jackson Laboratory. Some reduction in melanocytes in choroid of eye due to neural creast migration abnormalities. (JAX Stock Number: 000676)
+ - MOLF/EiJ: A wild-derived inbred strain derived from M. musculus molossinus samples camputered in Fukuoka, Japan. This strain has the retinal degeneration rd1 allele in Pde6b. There appears to have been some genetic contamination of this strain with conventional inbred strains in the past several decades (F. Pardo, personal communication to RWW, August 2006). However, the strain is currently fully inbred. (JAX Stock Number: 000550)
+ - NOD/LtJ: Non-obese diabetic strain, originally from M. Hattori in Kyoto, Japan. This is the Edward Leiter (Lt) substrain from the Jackson Laboratory. Collaborative Cross strain sequenced by NIEHS; Phenome Project B list. Homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. (JAX Stock Number: 001976)
+ - NZO/HlLtJ: New Zealand Obese strain. This is a severely obese and hypertensive strain. Males often develop a type 2 diabetes. Collaborative Cross strain. Agouti coat color. (JAX Stock Number: 002105)
+ - NZB/BlNJ: New Zealand Black inbred strain from Bielschowsky (BL, substrain is "B lowercase L N", not "BiN") now maintained at the Jackson Laboratory. (JAX Stock Number: 000648)
+ - NZW/LacJ: New Zealand White strain from the Laboratory Animal Center (Carshalton, UK), now maintained at the Jackson Laboratory. Carries the Tyr c locus albino mutation, the pink-eye dilution mutation in the Oca2 or p locus, and the brown allele at Tyrp1. (JAX Stock Number: 001058)
+ - PANCEVO/EiJ: PANCEVO/EiJ is a wild-derived inbred strain from the Mus spicilegus samples caught in the Pancevo, Serbia. This species of mouse is also known as the Steppe mouse (taxon identifier 10103). M. spicilegus is a colonial mound-building species. No known ocular or retina mutations, but the expression level of Gnat2 is low in this strain, either due to a 3' UTR length variant or possible achromatosia (cone degeneration) (JAX Stock Number: 001384)
+ - PWD/PhJ: A wild-derived Mus musculus musculus agouti strain inbred from samples caught near Prague, Czech Republic. Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues. (JAX Stock Number: 004660)
+ - PWK/PhJ: A wild-derived Mus musculus musculus inbred strain from samples caught near Lhotka, Czech Republic. Collaborative Cross strain; Phenome Project D list. (JAX Stock Number: 003715)
+ - SJL/J: Swiss Webster inbred strain from Jim Lambert's lab at the Jackson Laboratory. This strain has the retinal degeneration rd1 allele in Pde6b. It also carries both the Tyr c albino mutation and the pink-eye dilution mutation in the Oca2 or p locus. Highly aggressive males. (JAX Stock Number: 000686)
+ - WSB/EiJ: Watkin Star line B (or "wild son-of-a-bitch") is a wild-derived Mus musculus domesticus inbred strain from samples caught in Maryland, USA. A Collaborative Cross strain sequenced by NIEHS; Phenome Project C list (JAX Stock Number: 001145)
+ - B6D2F1 and D2B6F1 (also listed as BDF1 and DBF1 in some graphs and tables): F1 hybrids generated by crossing C57BL/6J with DBA/2J. These black reciprocal F1 can be used to detect dominance effects. Comparison of the two reciprocal F1s can be used to detect parental origin (imprinting) effects. The D2B6F1 animals are currently available from the Jackson Laboratory as a special order.) (JAX Stock Number for B6D2F1 hybrids obtained from the Jackson Laboratory, aka B6D2F1/J 100006)
+
+
+Most of the common inbred strains harbor mutations in genes the control pigmentation (Silvers, 2008 and material above in this INFO file). These gene include the albino and chinchilla alleles of the tyrosinase gene (Tyr, or human OCA1), the brown allele of the tyrosinase related protein 1 (Tyrp1), the pink-eye dilution allele of Oca2 (probe set 1418211), the non-agouti (black) and white-bellied alleles of the agouti signaling protein Asip, the steel allele of Kitlg, the dilute allele of Myo5a (probe set 1419754), and the piebald allele of Ednrb. In some of these cases, effects of the mutation are easily detected at the transcript level (Tyrp1, Oca2, and Myo5a), but in the other cases (Tyr, Asip, Ednrb, and Kitlg), mutations do not leave a strong imprint on expression.
diff --git a/general/datasets/Eye_m2_0908_r_mt/citation.rtf b/general/datasets/Eye_m2_0908_r_mt/citation.rtf
new file mode 100644
index 0000000..ddd98e4
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_mt/citation.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams. Gene expression landscape of the mammalian eye: A global survey and database of mRNAs of 103 varieties of mice. Molecular Vision 2009; in press.
diff --git a/general/datasets/Eye_m2_0908_r_mt/contributors.rtf b/general/datasets/Eye_m2_0908_r_mt/contributors.rtf
new file mode 100644
index 0000000..d155833
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_mt/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams
diff --git a/general/datasets/Eye_m2_0908_r_mt/experiment-design.rtf b/general/datasets/Eye_m2_0908_r_mt/experiment-design.rtf
new file mode 100644
index 0000000..1ebe0ad
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_mt/experiment-design.rtf
@@ -0,0 +1 @@
+Expression profiling by array
diff --git a/general/datasets/Eye_m2_0908_r_mt/notes.rtf b/general/datasets/Eye_m2_0908_r_mt/notes.rtf
new file mode 100644
index 0000000..7a26eb5
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_mt/notes.rtf
@@ -0,0 +1 @@
+This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/Eye_m2_0908_r_mt/platform.rtf b/general/datasets/Eye_m2_0908_r_mt/platform.rtf
new file mode 100644
index 0000000..9024a99
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_mt/platform.rtf
@@ -0,0 +1,11 @@
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many probes overlap and target the same transcript). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequences as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
+As part of the development of HEIMED, we have manually annotated individual probe sets by sequence alignment to the mouse genome and transcriptome. Approximately 13,000 probe sets that have comparatively high expression in eye and CNS were curated by one of the authors (RWW) and now have specific information on the part of the transcript targeted by each probe set. The other 33,000 transcripts have corresponding data that was generated by Xusheng Wang using computational methods (BLAT analysis combined with annotated genome sequence).
+
+One example may help explain how to exploit this annotation. The four probe sets for rhodopsin include information on the target location. Only the first probe set targets the last two coding exons. The other three probe sets target different parts of the 3’ UTR (mid, distal, and far distal regions). The probe sets can be reordered by from high to low expression using the Sort By function in Search Results pages. In the case of rhodopsin, the probe set that targets that last two coding exons and proximal parts of the 3’ UTR also has the highest expression . Finally, the HEIMED gene descriptions have been customized to help vision researchers. In the case of rhodopsin, the description appended after the gene name reads “rod photoreceptor pigment, retinitis pigmentosa-associated”. For less well known genes this kind of annotation can be extremely useful. For example, the more verbose annotation for Cerkl reads “neuronal survival and apoptosis-related, retinal ganglion cell expressed, retinitis pigmentosa 26); alternative 3' UTR of short form message, intron 2”.
+
+
+
+
+
+Legend: Distribution of expression values for all probe sets in HEIMED.
diff --git a/general/datasets/Eye_m2_0908_r_mt/processing.rtf b/general/datasets/Eye_m2_0908_r_mt/processing.rtf
new file mode 100644
index 0000000..4349e60
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_mt/processing.rtf
@@ -0,0 +1,3381 @@
+Range of Gene Expression in the Eye. Expression of transcripts in the HEIMED and most other GN data sets is measured on a log2 scale. Each unit corresponding approximately to a 2-fold difference in hybridization signal intensity. To simplify comparisons among different data sets and cases, log2 RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units (variance stabilized). Values of all 45,101 probe sets in this data set range from a low of 4.8 (Tcf15, probe set 1420281_at) to a high of 15.5 (crystallin gamma C, Crygc, probe set 1422674_s_at). This corresponds to 10.7 units or a 1 to 1700 dynamic range of expression (2^10.73).
+
+We used pooled RNA samples of whole eyes, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+We calibrated this log intensity scale using Affymetrix spike-in control probe sets. These 18 control probe sets target exogenous bacterial mRNAs that are added to each sample (a graded dose spike cocktail) during preparation at concentrations of 1.5, 5, 25, and 100 pM. (To find these probe sets, search GN’s ALL search field using the string “AFFX pM”.) A value of 6 or less is equivalent to an mRNA concentration of under 0.4 pM, a value of 8 is equivalent to ~1.5 pM, 9.5 is equivalent to ~5 pM, 11.5 is equivalent to ~25 pM, 13.5 is equivalent to ~100 pM, and a value of 15.5 is equivalent to an mRNA concentration of 400 pM or greater.
+
+This range can be converted to the mRNA molecules per cell in the eye assuming that a value of 8 is equivalent to about 1 mRNA copy per cell (Kanno et al. 2006, see http://www.biomedcentral.com/1471-2164/7/64). Since the expression of rhodopsin mRNA is normally 15 units, we predict that there are 27 or ~128 Rho mRNAs per cell in the whole eye and ~256 in rods themselves (assuming that rods make up about half of all cells in the eye). For this purpose it may be useful to know that a normal mouse eye contains between 6 and 8 million rod photoreceptors (Guo, Lu, and Williams; GN BXD Phenotype ID 11024).
+
+Note that some probe sets with very low expression still provide reliable data. For example, probe set 1440397_at (Cacna2d1) has expression of only 5.5 units (a value that would be declared as "absent" using conventional Affymetrix procedures), but the values for this calcium channel transcript are associated with a very strong cis QTL with an LRS of 79 (LOD = 17). This strong linkage is definitely not due to chance since the probability of the expression data mapping precisely to the location of the parent gene itself is about 10e-16. This indicates a high signal to noise ratio and the detection of significant strain variation of the correct transcript.
+
+The standard error of the mean for the HEIMED data set is computed for 2 to 6 biological replicates. The standard error of such small samples tends to systematically underestimate the population standard error. With n = 2 the underestimate is about 25%, whereas for n = 6 the underestimate is 5%. Gurland and Tripathi (1971) provide a correction and equation for this effect (see Sokal and Rohlf, Biometry, 2nd ed., 1981, p 53 for an equation of the correction factor for small samples of n < 20.) Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. The CEL files were processed using the RMA protocol. We processed the first three batches together. The last batch was processed separately and merged as described below.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
+After RMA processing using Biobase affy10 build running under R version 2.7.1, all array data sets were rank-order normalized. This second round of quantile normalization removes much residual non-linearity across arrays and forces every array to have the same distribution of values as the mean of all arrays. Comparative array data quality was then evaluated in DataDesk. Outlier arrays were flagged by visual inspection in DataDesk, usually by means of an analysis of scatter plots and more quantitatively by generating a correlation matrix of all arrays. Those arrays with mean correlation <0.96 versus all other arrays indicates trouble or a biological outlier). In some cases, outliers were expected, such as samples from strains with retinal degeneration (FVB/NJ, NOD/LtJ, MOLF/EiJ, C3H/HeJ and BXD24), samples from wild subspecies such as WSB/EiJ, CAST/EiJ, PWD/PhJ, and PWK/PhJ, and knockouts. However, when arrays were anomolous both within strain and across strains, they were often simply discarded. The assumption is that anomolous data are much more likely due to experimental and technical errors than to informative biological variation. Approximately 10% of arrays were discarded.
+
+After this process, the acceptable set of arrays was renormalized using all step as above, starting with the original RMA procedure, etc.
+
+We reviewed the data set using a new method developed by RW Williams, Jeremy Peirce, and Hongqiang Li. For the full set of arrays that passed standard QC protocols described above, we computed the strain means for the BXD strains, B6, D2, and F1s. Using this set of strain means we then computed LRS scores for all 45101 probe sets and counted the number of transcripts that generated QTLs with LRS values greater than 50. This value (e.g., 1800) represented the QTL harvest for the full data set. We then dropped a single array from the data set, recomputed strain means, and recomputed the number of transcripts with LRS scores great than 50. This value is expected to typically reduce the number of QTLs that reach the criterion level (e.g., 1750 QTLs > 50). This process was repeated for every array to obtain an array-specific difference value--the effect of removing that array on the total QTL count. For example, the loss of a single array might cause a decrease in 50 QTLs. Values ranged from approximately -90 (good arrays) to +40 (bad arrays). This procedure is similar in some ways to a jackknife protocol, although we are not using this procedure to esimate an error term, but rather as a method to polish a data set.
+
+During this process we discovered that nearly 20 arrays in the batch 2 had been mislabeled at some point in processing. We computed the correct strain membership of each array using a large number of Mendelian probe sets (more than 50) and comparing their match to standard SNP and microsatellite markers and the original array data set of November 2005. This allowed us to rescue a large number of arrays that were of high quality.
+
+A third batch of approximately 40 arrays were processed by Yan Jiao and Weikuan Gu in August 2006. These complete data set assembled by Hongqiang Li. This process again included a correction for a batch effect.
+
+For the June 2006 data set Hongqiang Li used a new batch correction method that stabilizes the range of expression in each batch. For each of the three large batches, we extracted the minumum and maximum raw probe expression (CEL file level) value. We then adjusted raw probe values in each batch to have the same range as the first and largest batch (batch 1) using a simple linear interpolation. These procedures generated new correct CEL files which were then used with RMA to generate final probe set estimates.
+
+For the final fourth batch of arrays (Sept 2008) Arthur Centeno and Rob Williams corrected for a systematic difference in probe set expression values between original arrays run in 2005 and 2006 and the new arrays added in 2008 (n = 45 acceptable arrays). This difference is due to unknown technical batch effects that are probably associated with labeling, hybridization, and scanning. We performed a simple correction to normalize values of the new set of arrays to those of the old set (batches 1 through 3). No changes were made to any values of the previous three batches. We corrected only the probe set level (RMA) values and not the CEL files. For this final batch, we corrected for the difference (offset) in probe set expression between the first three batches arrays run in 2005 and 2006 (a total of 174 acceptable arrays) and the new batch (n = 47 acceptable arrays). This difference is due to unknown technical effects that are probably related to various steps in labeling, hybridization, and scanning. The correction was applied as follows: (1) RWW selected 51 high quality arrays with similar expression characteristics (r = 0.97 or better between pairs of arrays) in the old data set (from batches 1, 2, and 3) and 34 high quality arrays in the final batch. RWW used scatterplots of full RMA transcriptome data sets to review many pairs of arrays within these new and old array batches. Strains with retinal degeneration or unusual eye gene expression characteristics were excluded from these selected subsets. The average expression values for each probe set were then computed for both the old and new array subsets. The offset value (old minus new) was added to each probe set across all 47 new arrays. This processes forces the average probe set in the new arrays to be very close to that of the previous arrays.
+
+Table 2: Sample tube ID, strain, original CEL filename, and Affymetrix quality control values. Columns labeled Scale factor, Background Average, Present, Absent, Marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Strain |
+ Original CEL |
+ Scale factor |
+ Background Average |
+ Present |
+ Absent |
+ Marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ Batch Id |
+ Used for batch control |
+
+
+ | 1 |
+ R2595E.1 |
+ 129S1/SvImJ |
+ R2595E.1.CEL |
+ 1.79 |
+ 115 |
+ 61.00% |
+ 37.50% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 2 |
+ R2533E.1 |
+ 129S1/SvImJ |
+ R2533E.1.CEL |
+ 2.11 |
+ 94 |
+ 57.90% |
+ 40.50% |
+ 1.60% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 3 |
+ R0754E.1 |
+ A/J |
+ R0754E.1.CEL |
+ 2.72 |
+ 86 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.36 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 4 |
+ R4521E |
+ B6129P2F2N1-Clcn3 |
+ R4521E.CEL |
+ 4.83 |
+ 38.7 |
+ 63.30% |
+ 35.30% |
+ 1.40% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 5 |
+ R4522E |
+ B6129P2F2N1-Clcn3 |
+ R4522E.CEL |
+ 5.76 |
+ 37.36 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.37 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 6 |
+ R4523E |
+ B6129P2F2N1-Clcn3 |
+ R4523E.CEL |
+ 4.88 |
+ 40.42 |
+ 63.90% |
+ 34.70% |
+ 1.40% |
+ 1.27 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 7 |
+ R4526E |
+ B6129P2F2N1-Gabbr1 |
+ R4526E.CEL |
+ 3.84 |
+ 44.18 |
+ 65.00% |
+ 33.70% |
+ 1.30% |
+ 1.34 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 8 |
+ R4509E |
+ B6129P2F2N1-Gabbr1 |
+ R4509E.CEL |
+ 7.45 |
+ 34.76 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.45 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 9 |
+ R4510E |
+ B6129P2F2N1-Gabbr1 |
+ R4510E.CEL |
+ 8.44 |
+ 37.44 |
+ 57.40% |
+ 41.10% |
+ 1.50% |
+ 1.35 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 10 |
+ R4511E |
+ B6129P2F2N1-Gabbr1 |
+ R4511E.CEL |
+ 5.91 |
+ 42.02 |
+ 61.40% |
+ 37.20% |
+ 1.40% |
+ 1.41 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 11 |
+ R4524E |
+ B6129P2F2N1-Gabbr1 |
+ R4524E.CEL |
+ 5.49 |
+ 42.34 |
+ 62.40% |
+ 36.20% |
+ 1.40% |
+ 1.29 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 12 |
+ R4525E |
+ B6129P2F2N1-Gabbr1 |
+ R4525E.CEL |
+ 4.69 |
+ 41.3 |
+ 63.10% |
+ 35.50% |
+ 1.40% |
+ 1.27 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 13 |
+ R4515E |
+ B6129P2F2N1-Gabra1 |
+ R4515E.CEL |
+ 5.75 |
+ 41.76 |
+ 62.80% |
+ 35.80% |
+ 1.40% |
+ 1.41 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 14 |
+ R4516E |
+ B6129P2F2N1-Gabra1 |
+ R4516E.CEL |
+ 7.07 |
+ 40.73 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.32 |
+ 0.87 |
+ 4 |
+ Y |
+
+
+ | 15 |
+ R4517E |
+ B6129P2F2N1-Gabra1 |
+ R4517E.CEL |
+ 5.45 |
+ 38.09 |
+ 62.70% |
+ 35.80% |
+ 1.40% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 16 |
+ R4512E |
+ B6129P2F2N1-Gnb5 |
+ R4512E.CEL |
+ 6.56 |
+ 38.02 |
+ 59.90% |
+ 38.70% |
+ 1.50% |
+ 1.33 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 17 |
+ R4513E |
+ B6129P2F2N1-Gnb5 |
+ R4513E.CEL |
+ 4.15 |
+ 41.6 |
+ 63.40% |
+ 35.10% |
+ 1.50% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ |
+
+
+ | 18 |
+ R4514E |
+ B6129P2F2N1-Gnb5 |
+ R4514E.CEL |
+ 5.86 |
+ 39.2 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.34 |
+ 0.81 |
+ 4 |
+ |
+
+
+ | 19 |
+ R4518E |
+ B6129P2F2N1-Gpr19 |
+ R4518E.CEL |
+ 5.58 |
+ 38.9 |
+ 62.60% |
+ 36.00% |
+ 1.30% |
+ 1.39 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 20 |
+ R4519E |
+ B6129P2F2N1-Gpr19 |
+ R4519E.CEL |
+ 5.95 |
+ 41.91 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.35 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 21 |
+ R2601E.1 |
+ B6D2F1 |
+ R2601E.1.CEL |
+ 2.55 |
+ 92 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.44 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 22 |
+ R2602E.1 |
+ B6D2F1 |
+ R2602E.1.CEL |
+ 2.6 |
+ 84 |
+ 59.70% |
+ 38.80% |
+ 1.50% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 23 |
+ R1676E.1 |
+ BALB/cByJ |
+ R1676E.1.CEL |
+ 2.69 |
+ 98 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.46 |
+ 0.74 |
+ 1 |
+ |
+
+
+ | 24 |
+ R1672E.1 |
+ BALB/cByJ |
+ R1672E.1.CEL |
+ 2.22 |
+ 111 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 25 |
+ R4530E |
+ BALB/cJ |
+ R4530E.CEL |
+ 6.37 |
+ 37.53 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.3 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 26 |
+ R4529E |
+ BALB/cJ |
+ R4529E.CEL |
+ 5.71 |
+ 41.33 |
+ 60.50% |
+ 38.00% |
+ 1.50% |
+ 1.48 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD1 |
+ R2704E.2.CEL |
+ 2.066 |
+ 139.61 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD1 |
+ R2707E.3.CEL |
+ 1 |
+ 80 |
+ 56.40% |
+ 42.10% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 3 |
+ |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD2 |
+ R1231E.2.CEL |
+ 2.197 |
+ 138.73 |
+ 57.30% |
+ 41.30% |
+ 1.40% |
+ 1.41 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD2 |
+ R2598E.1.CEL |
+ 1.99 |
+ 106 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD5 |
+ R2591E.1.CEL |
+ 1.7 |
+ 136 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.33 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD5 |
+ R2714E.2.CEL |
+ 1.404 |
+ 144.35 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD6 |
+ R2570E.1.CEL |
+ 1.99 |
+ 87 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.46 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD6 |
+ R2694E.2.CEL |
+ 1.983 |
+ 97.23 |
+ 61.60% |
+ 37.10% |
+ 1.30% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD8 |
+ R2538E.1.CEL |
+ 1.91 |
+ 102 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.52 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD8 |
+ R2709E.2.CEL |
+ 1.99 |
+ 99.79 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.42 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD9 |
+ R2708E.2.CEL |
+ 1.966 |
+ 126.46 |
+ 57.70% |
+ 40.70% |
+ 1.50% |
+ 1.4 |
+ 0.84 |
+ 2 |
+ |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD9 |
+ R2569E.1.CEL |
+ 1.75 |
+ 87 |
+ 55.10% |
+ 43.40% |
+ 1.50% |
+ 2.82 |
+ 3.14 |
+ 1 |
+ |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD11 |
+ R2581E.1.CEL |
+ 1.94 |
+ 89 |
+ 62.10% |
+ 36.40% |
+ 1.60% |
+ 1.55 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD11 |
+ R2612E.2.CEL |
+ 1.83 |
+ 142.03 |
+ 58.20% |
+ 40.50% |
+ 1.40% |
+ 1.78 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD12 |
+ R2742E.2.CEL |
+ 2.127 |
+ 134.14 |
+ 57.00% |
+ 41.60% |
+ 1.40% |
+ 1.64 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD12 |
+ R2543E.1.CEL |
+ 1.61 |
+ 118 |
+ 58.60% |
+ 39.90% |
+ 1.60% |
+ 1.43 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD13 |
+ R2586E.1.CEL |
+ 2.01 |
+ 74 |
+ 56.40% |
+ 42.00% |
+ 1.60% |
+ 2.85 |
+ 3.81 |
+ 1 |
+ |
+
+
+ | 44 |
+ R877E.2 |
+ BXD13 |
+ R877E.2.CEL |
+ 1.558 |
+ 125.63 |
+ 61.20% |
+ 37.50% |
+ 1.20% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD14 |
+ R2557E.1.CEL |
+ 1.83 |
+ 99 |
+ 62.50% |
+ 36.10% |
+ 1.40% |
+ 1.31 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD14 |
+ R1128E.2.CEL |
+ 1.91 |
+ 115 |
+ 59.90% |
+ 38.80% |
+ 1.40% |
+ 1.2 |
+ 0.82 |
+ 1 |
+ Y |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD15 |
+ R2701E.3.CEL |
+ 1 |
+ 88 |
+ 60.60% |
+ 37.90% |
+ 1.40% |
+ 1.5 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD15 |
+ R2716E.2.CEL |
+ 2.015 |
+ 150.83 |
+ 56.40% |
+ 42.10% |
+ 1.60% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD16 |
+ R2711E.2.CEL |
+ 1.953 |
+ 118.53 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD16 |
+ R2567E.1.CEL |
+ 2.24 |
+ 82 |
+ 56.70% |
+ 41.60% |
+ 1.70% |
+ 1.37 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD18 |
+ R2720E.2.CEL |
+ 2.32 |
+ 99.93 |
+ 59.50% |
+ 39.00% |
+ 1.50% |
+ 1.33 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD18 |
+ R2559E.1.CEL |
+ 1.65 |
+ 104 |
+ 60.80% |
+ 37.70% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD19 |
+ R2560E.1.CEL |
+ 1.79 |
+ 98 |
+ 60.90% |
+ 37.50% |
+ 1.60% |
+ 1.35 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD19 |
+ R2713E.2.CEL |
+ 1.67 |
+ 120.82 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD20 |
+ R2584E.1.CEL |
+ 2.07 |
+ 84 |
+ 59.30% |
+ 39.10% |
+ 1.60% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD20 |
+ R2731E.2.CEL |
+ 1.825 |
+ 147 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.4 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD21 |
+ R2702E.2.CEL |
+ 1.811 |
+ 128.65 |
+ 59.40% |
+ 39.10% |
+ 1.40% |
+ 1.26 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD21 |
+ R2541E2.1.CEL |
+ 2.63 |
+ 125 |
+ 56.00% |
+ 42.40% |
+ 1.50% |
+ 1.29 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD22 |
+ R2553E.1.CEL |
+ 1.95 |
+ 111 |
+ 59.90% |
+ 38.50% |
+ 1.50% |
+ 1.28 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD22 |
+ R2700E.2.CEL |
+ 1.858 |
+ 102.96 |
+ 61.50% |
+ 37.10% |
+ 1.30% |
+ 1.48 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD23 |
+ R2558E-2.1.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD23 |
+ R1086E.2.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD24 |
+ R2719E.2.CEL |
+ 1.47 |
+ 140.38 |
+ 61.50% |
+ 37.20% |
+ 1.30% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD24 |
+ R2589E2.1.CEL |
+ 2.61 |
+ 112 |
+ 57.50% |
+ 40.90% |
+ 1.60% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD25 |
+ R2573E-2.1.CEL |
+ 3.15 |
+ 72 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.77 |
+ 0.97 |
+ 1 |
+ |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD25 |
+ R2683E.2.CEL |
+ 1.777 |
+ 115.64 |
+ 58.30% |
+ 40.30% |
+ 1.40% |
+ 2.01 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD27 |
+ R2703E.2.CEL |
+ 1.263 |
+ 134.78 |
+ 62.60% |
+ 36.10% |
+ 1.40% |
+ 1.44 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD27 |
+ R2729E.3.CEL |
+ 1 |
+ 87 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.56 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD28 |
+ R2562E.3.CEL |
+ 1.65 |
+ 116 |
+ 59.90% |
+ 38.40% |
+ 1.70% |
+ 1.37 |
+ 0.79 |
+ 3 |
+ Y |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD28 |
+ R2721E.2.CEL |
+ 2.065 |
+ 157.39 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD29 |
+ R2561E.3.CEL |
+ 1 |
+ 77 |
+ 53.30% |
+ 45.40% |
+ 1.40% |
+ 3.36 |
+ 19.66 |
+ 3 |
+ |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD31 |
+ R1258E.2.CEL |
+ 2.063 |
+ 117.09 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.54 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD31 |
+ R2597E.1.CEL |
+ 2.37 |
+ 94 |
+ 60.30% |
+ 38.30% |
+ 1.50% |
+ 1.34 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD32 |
+ R2563E.1.CEL |
+ 1.55 |
+ 102 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD32 |
+ R1216E.2.CEL |
+ 2.23 |
+ 111.99 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.35 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD33 |
+ R2542E.1.CEL |
+ 2.13 |
+ 97 |
+ 56.50% |
+ 41.80% |
+ 1.60% |
+ 1.91 |
+ 0.93 |
+ 1 |
+ |
+
+
+ | 77 |
+ R857E.2 |
+ BXD33 |
+ R857E.2.CEL |
+ 1.737 |
+ 113.98 |
+ 61.90% |
+ 36.70% |
+ 1.30% |
+ 1.6 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD34 |
+ R1451E.2.CEL |
+ 1.843 |
+ 140.05 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ Y |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD34 |
+ R2585E.1.CEL |
+ 2.64 |
+ 75 |
+ 58.30% |
+ 40.00% |
+ 1.70% |
+ 1.25 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD36 |
+ R2698E.3.CEL |
+ 1 |
+ 86 |
+ 59.70% |
+ 39.00% |
+ 1.30% |
+ 1.46 |
+ 0.78 |
+ 3 |
+ |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD36 |
+ R2705E.3.CEL |
+ 1 |
+ 86 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.46 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD38 |
+ R2710E.2.CEL |
+ 2.112 |
+ 122.1 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.37 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD38 |
+ R2532E.1.CEL |
+ 2.04 |
+ 94 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.37 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD39 |
+ R2574E.1.CEL |
+ 1.98 |
+ 91 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD39 |
+ R2695E.2.CEL |
+ 1.638 |
+ 122.7 |
+ 60.80% |
+ 37.80% |
+ 1.50% |
+ 1.42 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD40 |
+ R2699E.2.CEL |
+ 1.827 |
+ 105.23 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD40 |
+ R2590E.1.CEL |
+ 2.71 |
+ 77 |
+ 59.10% |
+ 39.30% |
+ 1.50% |
+ 1.4 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD42 |
+ R2696E.2.CEL |
+ 1.622 |
+ 118.95 |
+ 62.00% |
+ 36.60% |
+ 1.50% |
+ 1.53 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD42 |
+ R2596E.1.CEL |
+ 2.63 |
+ 108 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 90 |
+ R994E.2 |
+ BXD43 |
+ R994E.2.CEL |
+ 1.966 |
+ 113.12 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.66 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD43 |
+ R2607E.1.CEL |
+ 2.43 |
+ 115 |
+ 58.60% |
+ 40.00% |
+ 1.40% |
+ 1.31 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD44 |
+ R2594E.1.CEL |
+ 1.77 |
+ 117 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.35 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD44 |
+ R2610E.2.CEL |
+ 1.814 |
+ 142.91 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.35 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD45 |
+ R2732E.2.CEL |
+ 2.154 |
+ 122.45 |
+ 56.50% |
+ 42.10% |
+ 1.40% |
+ 1.8 |
+ 0.83 |
+ 2 |
+ |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD45 |
+ R2592E.1.CEL |
+ 1.85 |
+ 106 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.43 |
+ 0.85 |
+ 1 |
+ Y |
+
+
+ | 96 |
+ R967E.2 |
+ BXD48 |
+ R967E.2.CEL |
+ 1.948 |
+ 130.95 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.63 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD48 |
+ R2606E.1.CEL |
+ 2.56 |
+ 106 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.35 |
+ 0.83 |
+ 1 |
+ Y |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD50 |
+ R2933E.3.CEL |
+ 1 |
+ 72 |
+ 52.90% |
+ 45.60% |
+ 1.50% |
+ 2.45 |
+ 0.98 |
+ 3 |
+ |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD50 |
+ R2937E.3.CEL |
+ 1 |
+ 89 |
+ 56.90% |
+ 41.60% |
+ 1.40% |
+ 1.81 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD51 |
+ R2603E.1.CEL |
+ 2.49 |
+ 115 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD51 |
+ R1042E.2.CEL |
+ 2.352 |
+ 104.12 |
+ 58.70% |
+ 39.90% |
+ 1.40% |
+ 1.53 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD55 |
+ R2980E.3.CEL |
+ 1 |
+ 82 |
+ 56.90% |
+ 41.70% |
+ 1.50% |
+ 1.77 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD55 |
+ R2690E.2.CEL |
+ 1.887 |
+ 164.01 |
+ 56.10% |
+ 42.30% |
+ 1.60% |
+ 1.43 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 104 |
+ R4176E |
+ BXD56 |
+ R4176E.CEL |
+ 4.75 |
+ 43.08 |
+ 63.00% |
+ 35.60% |
+ 1.30% |
+ 1.39 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 105 |
+ R4175E |
+ BXD56 |
+ R4175E.CEL |
+ 6 |
+ 38.49 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.47 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD60 |
+ R1006E.3.CEL |
+ 1 |
+ 98 |
+ 54.90% |
+ 43.70% |
+ 1.50% |
+ 2.7 |
+ 0.86 |
+ 3 |
+ |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD60 |
+ R2725E.2.CEL |
+ 1.551 |
+ 148.01 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD60 |
+ R1074E.3.CEL |
+ 1 |
+ 118 |
+ 55.50% |
+ 43.10% |
+ 1.40% |
+ 1.96 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD61 |
+ R2534E2.1.CEL |
+ 2.47 |
+ 118 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.42 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD61 |
+ R2684E.2.CEL |
+ 2.01 |
+ 131.03 |
+ 57.00% |
+ 41.50% |
+ 1.50% |
+ 1.34 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD62 |
+ R1107E.3.CEL |
+ 1 |
+ 83 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.43 |
+ 0.93 |
+ 3 |
+ |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD62 |
+ R2681E.2.CEL |
+ 2.086 |
+ 148.24 |
+ 57.20% |
+ 41.30% |
+ 1.50% |
+ 1.29 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 113 |
+ R965E.3 |
+ BXD62 |
+ R965E.3.CEL |
+ 1 |
+ 93.55 |
+ 53.30% |
+ 45.20% |
+ 1.50% |
+ 3.11 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD63 |
+ R1425E.2.CEL |
+ 1.7 |
+ 136 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.43 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD63 |
+ R2576E.3.CEL |
+ 1 |
+ 84 |
+ 61.30% |
+ 37.40% |
+ 1.40% |
+ 1.48 |
+ 0.76 |
+ 3 |
+ |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD64 |
+ R943E-2.2.CEL |
+ 1.591 |
+ 141.34 |
+ 60.10% |
+ 38.40% |
+ 1.50% |
+ 1.32 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD64 |
+ R2611E.1.CEL |
+ 2.29 |
+ 92 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 1.57 |
+ 1.06 |
+ 1 |
+ |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD65 |
+ R2689E.2.CEL |
+ 1.721 |
+ 142.44 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.38 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD65 |
+ R2583E.1.CEL |
+ 2.49 |
+ 70 |
+ 56.90% |
+ 41.50% |
+ 1.60% |
+ 1.67 |
+ 1.01 |
+ 1 |
+ |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD66 |
+ R2728E.2.CEL |
+ 1.714 |
+ 137.45 |
+ 59.40% |
+ 39.00% |
+ 1.60% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD66 |
+ R2536E2.1.CEL |
+ 2.74 |
+ 109 |
+ 56.10% |
+ 42.30% |
+ 1.70% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD66 |
+ R1207E.2.CEL |
+ 1.681 |
+ 136.86 |
+ 60.40% |
+ 38.10% |
+ 1.50% |
+ 1.45 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD67 |
+ R1192E.2.CEL |
+ 2.126 |
+ 123.37 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD67 |
+ R2727E.3.CEL |
+ 1 |
+ 82.55 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.97 |
+ 0.87 |
+ 2 |
+ |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD67 |
+ R2691E.3.CEL |
+ 1 |
+ 90 |
+ 54.80% |
+ 43.80% |
+ 1.50% |
+ 2.61 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD68 |
+ R2551E.1.CEL |
+ 2.49 |
+ 92 |
+ 54.30% |
+ 44.10% |
+ 1.60% |
+ 2.91 |
+ 1.55 |
+ 1 |
+ |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD68 |
+ R2726E.2.CEL |
+ 1.811 |
+ 153.09 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD69 |
+ R2593E.1.CEL |
+ 1.67 |
+ 128 |
+ 59.20% |
+ 39.50% |
+ 1.30% |
+ 1.47 |
+ 0.92 |
+ 1 |
+ Y |
+
+
+ | 129 |
+ R975E.2 |
+ BXD70 |
+ R975E.2.CEL |
+ 1.841 |
+ 137.97 |
+ 58.00% |
+ 40.50% |
+ 1.40% |
+ 1.36 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD70 |
+ R2537E2.1.CEL |
+ 2.93 |
+ 99 |
+ 58.00% |
+ 40.50% |
+ 1.60% |
+ 1.29 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 131 |
+ R4531E |
+ BXD71 |
+ R4531E.CEL |
+ 4.77 |
+ 43.48 |
+ 62.40% |
+ 36.30% |
+ 1.40% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 132 |
+ R4532E |
+ BXD71 |
+ R4532E.CEL |
+ 5.89 |
+ 40.68 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD73 |
+ R2779E.2.CEL |
+ 1.746 |
+ 121.11 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD73 |
+ R3024E.3.CEL |
+ 1 |
+ 78.05 |
+ 51.70% |
+ 46.60% |
+ 1.70% |
+ 2.3 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD75 |
+ R2565E.1.CEL |
+ 1.79 |
+ 102 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 2.31 |
+ 3.47 |
+ 1 |
+ |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD75 |
+ R1397E-re.2.CEL |
+ 1.449 |
+ 189.71 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD77 |
+ R2687E.3.CEL |
+ 1 |
+ 80 |
+ 58.00% |
+ 40.60% |
+ 1.40% |
+ 1.57 |
+ 0.8 |
+ 3 |
+ Y |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD77 |
+ R2717E.2.CEL |
+ 1.797 |
+ 84.43 |
+ 61.60% |
+ 36.90% |
+ 1.40% |
+ 1.49 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD77 |
+ R1421E.3.CEL |
+ 1 |
+ 94 |
+ 52.40% |
+ 46.20% |
+ 1.40% |
+ 2.29 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD80 |
+ R2579E.1.CEL |
+ 2.42 |
+ 72 |
+ 59.20% |
+ 39.40% |
+ 1.50% |
+ 1.73 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD80 |
+ R2686E.2.CEL |
+ 2.342 |
+ 119.63 |
+ 56.00% |
+ 42.60% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD83 |
+ R2956E.3.CEL |
+ 1 |
+ 84 |
+ 55.40% |
+ 43.20% |
+ 1.40% |
+ 1.39 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD83 |
+ R2960E.3.CEL |
+ 1 |
+ 80 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.5 |
+ 0.82 |
+ 3 |
+ Y |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD84 |
+ R2922E.3.CEL |
+ 1 |
+ 91 |
+ 57.80% |
+ 40.80% |
+ 1.50% |
+ 1.47 |
+ 0.83 |
+ 3 |
+ Y |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD84 |
+ R2895E.3.CEL |
+ 1 |
+ 75 |
+ 58.30% |
+ 40.20% |
+ 1.50% |
+ 1.56 |
+ 0.77 |
+ 3 |
+ Y |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD85 |
+ R2692E.2.CEL |
+ 1.423 |
+ 160.87 |
+ 60.20% |
+ 38.30% |
+ 1.40% |
+ 1.46 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD85 |
+ R2715E.2.CEL |
+ 1.488 |
+ 142.6 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.5 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD86 |
+ R1405E.2.CEL |
+ 2.351 |
+ 119.34 |
+ 56.40% |
+ 42.20% |
+ 1.40% |
+ 1.64 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD86 |
+ R1225E.3.CEL |
+ 1 |
+ 71 |
+ 53.90% |
+ 44.60% |
+ 1.40% |
+ 3.2 |
+ 1.61 |
+ 3 |
+ |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD87 |
+ R2724E.2.CEL |
+ 1.906 |
+ 113.71 |
+ 60.70% |
+ 37.90% |
+ 1.40% |
+ 1.45 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD87 |
+ R2540E.1.CEL |
+ 2.33 |
+ 93 |
+ 61.10% |
+ 37.40% |
+ 1.40% |
+ 1.22 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD89 |
+ R1433E.2.CEL |
+ 1 |
+ 2.241 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.41 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD89 |
+ R2546E.1.CEL |
+ 1.99 |
+ 96 |
+ 58.60% |
+ 39.70% |
+ 1.70% |
+ 1.47 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD90 |
+ R2578E2.1.CEL |
+ 2.79 |
+ 92 |
+ 58.60% |
+ 39.80% |
+ 1.60% |
+ 1.52 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 155 |
+ R859E.2 |
+ BXD90 |
+ R859E.2.CEL |
+ 1.847 |
+ 152.22 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.36 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD92 |
+ R2682E.2.CEL |
+ 1.547 |
+ 156.31 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.37 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD92 |
+ R1388E.3.CEL |
+ 1 |
+ 63 |
+ 60.00% |
+ 38.60% |
+ 1.40% |
+ 1.85 |
+ 1.03 |
+ 3 |
+ |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD92 |
+ R1322E.3.CEL |
+ 1 |
+ 80 |
+ 55.90% |
+ 42.60% |
+ 1.50% |
+ 1.75 |
+ 0.74 |
+ 3 |
+ |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD96 |
+ R2733E.2.CEL |
+ 1.7 |
+ 113.99 |
+ 62.10% |
+ 36.60% |
+ 1.30% |
+ 1.4 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD96 |
+ R2554E.1.CEL |
+ 2.18 |
+ 93 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD97 |
+ R2649E.2.CEL |
+ 2.343 |
+ 119.04 |
+ 57.50% |
+ 41.20% |
+ 1.40% |
+ 1.53 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD97 |
+ R2577E.1.CEL |
+ 2.07 |
+ 77 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.87 |
+ 1.29 |
+ 1 |
+ |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD98 |
+ R2645E.3.CEL |
+ 1 |
+ 88 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.59 |
+ 0.81 |
+ 3 |
+ Y |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD98 |
+ R2688E.2.CEL |
+ 1.772 |
+ 145.24 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.48 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 165 |
+ R4533E |
+ BXD99 |
+ R4533E.CEL |
+ 1 |
+ 37.69 |
+ 60.30% |
+ 38.20% |
+ 1.40% |
+ 1.33 |
+ 0.89 |
+ 4 |
+ Y |
+
+
+ | 166 |
+ R4534E |
+ BXD99 |
+ R4534E.CEL |
+ 5.69 |
+ 36.62 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.16 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 167 |
+ R2885E.3 |
+ BXSB/MpJ |
+ R2885E.3.CEL |
+ 1 |
+ 76 |
+ 58.10% |
+ 40.60% |
+ 1.30% |
+ 1.88 |
+ 1.06 |
+ 3 |
+ |
+
+
+ | 168 |
+ R2883E.3 |
+ BXSB/MpJ |
+ R2883E.3.CEL |
+ 1 |
+ 71 |
+ 56.40% |
+ 42.00% |
+ 1.50% |
+ 1.59 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 169 |
+ R1700E.1 |
+ C3H/HeJ |
+ R1700E.1.CEL |
+ 2.98 |
+ 69 |
+ 60.80% |
+ 37.90% |
+ 1.40% |
+ 1.48 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 170 |
+ R1704E.1 |
+ C3H/HeJ |
+ R1704E.1.CEL |
+ 2.58 |
+ 88 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.38 |
+ 0.84 |
+ 1 |
+ |
+
+
+ | 171 |
+ R2605E.1 |
+ C57BL/6J |
+ R2605E.1.CEL |
+ 1.82 |
+ 131 |
+ 60.50% |
+ 38.20% |
+ 1.30% |
+ 1.32 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 172 |
+ R0871E |
+ C57BL/6J |
+ R0871E.CEL |
+ 6.24 |
+ 37.38 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.41 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 173 |
+ R0872E.1 |
+ C57BL/6J |
+ R0872E.1.CEL |
+ 3.13 |
+ 89 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 174 |
+ R0872E |
+ C57BL/6J |
+ R0872E.CEL |
+ 3.128 |
+ 88.58 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 175 |
+ R4507E |
+ C57BL/6J-Nyx |
+ R4507E.CEL |
+ 8.13 |
+ 37.5 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.32 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 176 |
+ R4508E |
+ C57BL/6J-Nyx |
+ R4508E.CEL |
+ 6.33 |
+ 37.26 |
+ 60.90% |
+ 37.80% |
+ 1.30% |
+ 1.24 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 177 |
+ R4505E |
+ C57BL/6J-Rpe65 |
+ R4505E.CEL |
+ 5.98 |
+ 37.48 |
+ 61.80% |
+ 36.80% |
+ 1.40% |
+ 1.45 |
+ 0.85 |
+ 4 |
+ Y |
+
+
+ | 178 |
+ R4506E |
+ C57BL/6J-Rpe65 |
+ R4506E.CEL |
+ 6.94 |
+ 37.9 |
+ 61.10% |
+ 37.50% |
+ 1.30% |
+ 1.5 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 179 |
+ R4535E |
+ C57BLKS/J |
+ R4535E.CEL |
+ 6.59 |
+ 37.28 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.26 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 180 |
+ R4536E |
+ C57BLKS/J |
+ R4536E.CEL |
+ 1 |
+ 40.71 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 181 |
+ R2564E.1 |
+ CAST/EiJ |
+ R2564E.1.CEL |
+ 1.94 |
+ 89 |
+ 58.50% |
+ 39.90% |
+ 1.60% |
+ 1.6 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 182 |
+ R2580E.1 |
+ CAST/EiJ |
+ R2580E.1.CEL |
+ 2.09 |
+ 95 |
+ 58.20% |
+ 40.10% |
+ 1.70% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ |
+
+
+ | 183 |
+ R4537E |
+ CBA/CaJ |
+ R4537E.CEL |
+ 1 |
+ 38.45 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.63 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 184 |
+ R4538E |
+ CBA/CaJ |
+ R4538E.CEL |
+ 5.89 |
+ 39.18 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.45 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 185 |
+ R4539E |
+ CZECHII/EiJ |
+ R4539E.CEL |
+ 7.73 |
+ 37.1 |
+ 58.30% |
+ 40.10% |
+ 1.50% |
+ 1.7 |
+ 0.95 |
+ 4 |
+ Y |
+
+
+ | 186 |
+ R4540E |
+ CZECHII/EiJ |
+ R4540E.CEL |
+ 11.04 |
+ 36.69 |
+ 53.00% |
+ 45.30% |
+ 1.70% |
+ 1.83 |
+ 1.32 |
+ 4 |
+ |
+
+
+ | 187 |
+ R2600E.1 |
+ D2B6F1 |
+ R2600E.1.CEL |
+ 2.47 |
+ 95 |
+ 58.10% |
+ 40.20% |
+ 1.70% |
+ 1.41 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 188 |
+ R2604E.1 |
+ D2B6F1 |
+ R2604E.1.CEL |
+ 2.66 |
+ 90 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 189 |
+ R1002E.3 |
+ DBA/2J |
+ R1002E.3.CEL |
+ 1 |
+ 102 |
+ 54.80% |
+ 43.70% |
+ 1.50% |
+ 2.84 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 190 |
+ R4541E |
+ DBA/2J |
+ R4541E.CEL |
+ 1 |
+ 43.4 |
+ 61.40% |
+ 37.00% |
+ 1.50% |
+ 1.37 |
+ 0.73 |
+ 4 |
+ Y |
+
+
+ | 191 |
+ R959E.3 |
+ DBA/2J |
+ R959E.3.CEL |
+ 1 |
+ 89.97 |
+ 53.20% |
+ 45.30% |
+ 1.50% |
+ 3.66 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 192 |
+ R2572E.1 |
+ DBA/2J |
+ R2572E.1.CEL |
+ 2.41 |
+ 79 |
+ 55.50% |
+ 42.90% |
+ 1.60% |
+ 1.37 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 193 |
+ R4542E |
+ DBA/2J |
+ R4542E.CEL |
+ 5.7 |
+ 39.95 |
+ 61.00% |
+ 37.40% |
+ 1.50% |
+ 1.23 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 194 |
+ R2771E.3 |
+ FVB/NJ |
+ R2771E.3.CEL |
+ 1 |
+ 70 |
+ 55.30% |
+ 43.20% |
+ 1.50% |
+ 1.69 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 195 |
+ R2772E.3 |
+ FVB/NJ |
+ R2772E.3.CEL |
+ 1 |
+ 76 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.13 |
+ 1.02 |
+ 3 |
+ |
+
+
+ | 196 |
+ R2636E.1 |
+ KK/HlJ |
+ R2636E.1.CEL |
+ 2.61 |
+ 93 |
+ 58.90% |
+ 39.50% |
+ 1.50% |
+ 1.39 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 197 |
+ R2637E.1 |
+ KK/HlJ |
+ R2637E.1.CEL |
+ 2.19 |
+ 103 |
+ 59.40% |
+ 39.00% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 198 |
+ R0999E.1 |
+ LG/J |
+ R0999E.1.CEL |
+ 2.45 |
+ 82 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 199 |
+ R1004E.1 |
+ LG/J |
+ R1004E.1.CEL |
+ 2.44 |
+ 92 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 200 |
+ R4543E |
+ LP/J |
+ R4543E.CEL |
+ 6.57 |
+ 41.99 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.28 |
+ 0.75 |
+ 4 |
+ Y |
+
+
+ | 201 |
+ R4544E |
+ LP/J |
+ R4544E.CEL |
+ 4.56 |
+ 39.9 |
+ 62.40% |
+ 36.10% |
+ 1.50% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 202 |
+ R2858E.3 |
+ MOLF/EiJ |
+ R2858E.3.CEL |
+ 1 |
+ 64 |
+ 53.80% |
+ 44.70% |
+ 1.50% |
+ 1.59 |
+ 0.95 |
+ 3 |
+ |
+
+
+ | 203 |
+ R2919.3 |
+ MOLF/EiJ |
+ R2919.3.CEL |
+ 1 |
+ 64 |
+ 52.40% |
+ 46.00% |
+ 1.60% |
+ 2.15 |
+ 1.07 |
+ 3 |
+ |
+
+
+ | 204 |
+ R1688E.1 |
+ NOD/LtJ |
+ R1688E.1.CEL |
+ 2.66 |
+ 98 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 205 |
+ R2566E-2.1 |
+ NOD/LtJ |
+ R2566E-2.1.CEL |
+ 3.03 |
+ 69 |
+ 59.80% |
+ 38.80% |
+ 1.50% |
+ 1.38 |
+ 0.75 |
+ 1 |
+ Y |
+
+
+ | 206 |
+ R4545E |
+ NZB/BlNJ |
+ R4545E.CEL |
+ 4.23 |
+ 43.48 |
+ 62.10% |
+ 36.40% |
+ 1.50% |
+ 1.33 |
+ 0.76 |
+ 4 |
+ Y |
+
+
+ | 207 |
+ R4546E |
+ NZB/BlNJ |
+ R4546E.CEL |
+ 6.27 |
+ 44.22 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.17 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 208 |
+ R2535E.1 |
+ NZO/HlLtJ |
+ R2535E.1.CEL |
+ 1.89 |
+ 86 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.41 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 209 |
+ R2550E.1 |
+ NZO/HlLtJ |
+ R2550E.1.CEL |
+ 1.79 |
+ 87 |
+ 60.70% |
+ 37.80% |
+ 1.50% |
+ 1.52 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 210 |
+ R2817E.3 |
+ NZW/LacJ |
+ R2817E.3.CEL |
+ 1 |
+ 59 |
+ 50.90% |
+ 47.60% |
+ 1.50% |
+ 3.59 |
+ 1.48 |
+ 3 |
+ |
+
+
+ | 211 |
+ R2810E |
+ NZW/LacJ |
+ R2810E.CEL |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ 3 |
+ |
+
+
+ | 212 |
+ R2810E.3 |
+ NZW/LacJ |
+ R2810E.3.CEL |
+ 1 |
+ 74 |
+ 57.00% |
+ 41.70% |
+ 1.40% |
+ 2.15 |
+ 1.03 |
+ 4 |
+ Y |
+
+
+ | 213 |
+ R4547E |
+ PANCEVO/EiJ |
+ R4547E.CEL |
+ 5.27 |
+ 51.34 |
+ 57.20% |
+ 41.10% |
+ 1.70% |
+ 1.7 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 214 |
+ R4548E |
+ PANCEVO/EiJ |
+ R4548E.CEL |
+ 10.54 |
+ 37.39 |
+ 50.30% |
+ 48.00% |
+ 1.70% |
+ 1.68 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 215 |
+ R2635E.1 |
+ PWD/PhJ |
+ R2635E.1.CEL |
+ 3.72 |
+ 80 |
+ 54.20% |
+ 44.10% |
+ 1.70% |
+ 1.53 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 216 |
+ R2634E.1 |
+ PWD/PhJ |
+ R2634E.1.CEL |
+ 3.29 |
+ 90 |
+ 55.90% |
+ 42.50% |
+ 1.60% |
+ 1.57 |
+ 0.81 |
+ 1 |
+ |
+
+
+ | 217 |
+ R2544E.1 |
+ PWK/PhJ |
+ R2544E.1.CEL |
+ 2.2 |
+ 108 |
+ 54.90% |
+ 43.50% |
+ 1.70% |
+ 1.36 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 218 |
+ R2549E.1 |
+ PWK/PhJ |
+ R2549E.1.CEL |
+ 2.28 |
+ 84 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.57 |
+ 0.83 |
+ 1 |
+ |
+
+
+ | 219 |
+ R4550E |
+ SJL/J |
+ R4550E.CEL |
+ 5.35 |
+ 40.44 |
+ 62.30% |
+ 36.20% |
+ 1.40% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ |
+
+
+ | 220 |
+ R2368E.1 |
+ WSB/EiJ |
+ R2368E.1.CEL |
+ 2.57 |
+ 86 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.29 |
+ 0.74 |
+ 1 |
+ Y |
+
+
+ | 221 |
+ R2547E.1 |
+ WSB/EiJ |
+ R2547E.1.CEL |
+ 2.14 |
+ 90 |
+ 58.20% |
+ 40.10% |
+ 1.60% |
+ 1.32 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0908_r_mt/summary.rtf b/general/datasets/Eye_m2_0908_r_mt/summary.rtf
new file mode 100644
index 0000000..44b7e23
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_mt/summary.rtf
@@ -0,0 +1,12 @@
+FINAL RECOMMENDED EYE DATA SET. The HEIMED September 2008 RMA data release provides estimates of gene expression in whole eyes of 103 lines of young adult mice generated using 221 Affymetrix M430 2.0 arrays. This data set is intended for exploration of the genetics and genomics of the mouse eye, retina, lens, retinal pigment epithelium, cornea, iris and choroid. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). We used pooled RNA samples, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+Users of these mouse eye data may also find the following complementary resources extremely useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
diff --git a/general/datasets/Eye_m2_0908_r_mt/tissue.rtf b/general/datasets/Eye_m2_0908_r_mt/tissue.rtf
new file mode 100644
index 0000000..9b6ee0f
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_mt/tissue.rtf
@@ -0,0 +1,2058 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of cRNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. All samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center led by Dr. Weikuan Gu. All arrays were processed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. C until use (roughly one third) or were used immediately for hybridization.
+
+Dealing with ocular pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations taken from brown and beige colored mice tend to have faint residual pigmentation that affects hybridization signal. To address this problem, Dr. Yan Jiao purified total RNA using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204) all four batches.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well balanced sample of males and females, in general without within-strain-by-sex replication. Two strains are represented by a single male sample pool (BXD29 and A/J). Four lines are represented by two or three male sample pools (all of the five DeltaGen KO line). The SJL/J may be a single mixed sex sample. Users can study possible sex effects by comparing any results of expression data to that of a surrogate measurement that summarizes the overall sex balance of HEIMED. To do this just compare your data to those of probe sets 1427262_at (Xist, high in females) and probe set 1426438_at (Ddx3y, high in males). These two sex-specific probes are quantitative surrogates for the sex balance in this data set.
+
+Technical duplicates: One sample, highlighted in the tables below, is a technical duplicate. The pair of technical duplicates were both of high quality. For statistical analysis, they should be combined and treated as single biological sample.
+
+Batch structure: This data set consists of four batches (Table 2, far right column). The final September 2008 data set consists of a total of 221 arrays and 220 independent samples.
+
+
+ - Batch 1: November 2005, n = 78 arrays original arrays of which 76 were accepted into this final data set.
+ - Batch 2: January 2006, n = 62 arrays of which 62 were accepted.
+ - Batch 3: August 2006, n = 39 arrays of which 36 were accepted. (These three batches, including some arrays that were eventually dropped from the final 2008 data set, were combined to form the September 2006 data set.)
+ - Batch 4: Summer 2008, n = 53 arrays of which 47 were accepted.
+
+
+Table 1: HEIMED case IDs, including sample tube ID, strain, age, sex, and source of mice (see Table 2 for information on array quality control)
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Group |
+ Strain |
+ Age |
+ Sex |
+ Source |
+
+
+ | 1 |
+ R2595E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 2 |
+ R2533E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 3 |
+ R0754E.1 |
+ GDP |
+ A/J |
+ 60 |
+ M |
+ JAX |
+
+
+ | 4 |
+ R4521E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 5 |
+ R4522E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 6 |
+ R4523E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 7 |
+ R4526E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 8 |
+ R4509E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 9 |
+ R4510E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 10 |
+ R4511E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 20 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 11 |
+ R4524E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 12 |
+ R4525E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 13 |
+ R4515E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 14 |
+ R4516E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 15 |
+ R4517E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 16 |
+ R4512E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 17 |
+ R4513E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 25 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 18 |
+ R4514E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 19 |
+ R4518E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 70 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 20 |
+ R4519E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 68 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 21 |
+ R2601E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 22 |
+ R2602E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 23 |
+ R1676E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ F |
+ JAX |
+
+
+ | 24 |
+ R1672E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 25 |
+ R4530E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 26 |
+ R4529E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD |
+ BXD1 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD |
+ BXD1 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD |
+ BXD2 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD |
+ BXD2 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD |
+ BXD5 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD |
+ BXD5 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD |
+ BXD6 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD |
+ BXD6 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD |
+ BXD8 |
+ 77 |
+ F |
+ UTHSC RW |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD |
+ BXD8 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD |
+ BXD9 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD |
+ BXD9 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD |
+ BXD11 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD |
+ BXD11 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD |
+ BXD12 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD |
+ BXD12 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD |
+ BXD13 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 44 |
+ R877E.2 |
+ BXD |
+ BXD13 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD |
+ BXD14 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD |
+ BXD14 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD |
+ BXD15 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD |
+ BXD15 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD |
+ BXD16 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD |
+ BXD16 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD |
+ BXD18 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD |
+ BXD18 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD |
+ BXD19 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD |
+ BXD19 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD |
+ BXD20 |
+ 59 |
+ F |
+ BIDMC GR |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD |
+ BXD20 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD |
+ BXD21 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD |
+ BXD21 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD |
+ BXD22 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD |
+ BXD22 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD |
+ BXD23 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD |
+ BXD23 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD |
+ BXD24 |
+ 123 |
+ F |
+ UTHSC RW |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD |
+ BXD24 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD |
+ BXD25 |
+ 67 |
+ F |
+ UAB |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD |
+ BXD25 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD |
+ BXD27 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD |
+ BXD27 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD |
+ BXD28 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD |
+ BXD28 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD |
+ BXD29 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD |
+ BXD31 |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD |
+ BXD31 |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD |
+ BXD32 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD |
+ BXD32 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD |
+ BXD33 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 77 |
+ R857E.2 |
+ BXD |
+ BXD33 |
+ 77 |
+ M |
+ UTHSC RW |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD |
+ BXD34 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD |
+ BXD34 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD |
+ BXD36 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD |
+ BXD36 |
+ 57 |
+ M |
+ BIDMC GR |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD |
+ BXD38 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD |
+ BXD38 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD |
+ BXD39 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD |
+ BXD39 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD |
+ BXD40 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD |
+ BXD40 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD |
+ BXD42 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD |
+ BXD42 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 90 |
+ R994E.2 |
+ BXD |
+ BXD43 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD |
+ BXD43 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD |
+ BXD44 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD |
+ BXD44 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD |
+ BXD45 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD |
+ BXD45 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 96 |
+ R967E.2 |
+ BXD |
+ BXD48 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD |
+ BXD48 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD |
+ BXD51 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD |
+ BXD51 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD |
+ BXD55 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD |
+ BXD55 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 104 |
+ R4176E |
+ BXD |
+ BXD56 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 105 |
+ R4175E |
+ BXD |
+ BXD56 |
+ 53 |
+ M |
+ UTHSC RW |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD |
+ BXD60 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD |
+ BXD60 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD |
+ BXD60 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD |
+ BXD61 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD |
+ BXD61 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ F |
+ UTHSC RW |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD |
+ BXD62 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 113 |
+ R965E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD |
+ BXD63 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD |
+ BXD63 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD |
+ BXD64 |
+ 56 |
+ F |
+ UTHSC RW |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD |
+ BXD64 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD |
+ BXD65 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD |
+ BXD65 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD |
+ BXD66 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD |
+ BXD66 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD |
+ BXD66 |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD |
+ BXD67 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD |
+ BXD68 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD |
+ BXD69 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 129 |
+ R975E.2 |
+ BXD |
+ BXD70 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD |
+ BXD70 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 131 |
+ R4531E |
+ BXD |
+ BXD71 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 132 |
+ R4532E |
+ BXD |
+ BXD71 |
+ 86 |
+ M |
+ UTHSC RW |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD |
+ BXD73 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD |
+ BXD73 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD |
+ BXD75 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD |
+ BXD75 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD |
+ BXD77 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD |
+ BXD77 |
+ 107 |
+ M |
+ UTHSC RW |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD |
+ BXD77 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD |
+ BXD80 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD |
+ BXD80 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD |
+ BXD84 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD |
+ BXD84 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD |
+ BXD85 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD |
+ BXD85 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD |
+ BXD86 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD |
+ BXD86 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD |
+ BXD87 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD |
+ BXD87 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD |
+ BXD89 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD |
+ BXD89 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD |
+ BXD90 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 155 |
+ R859E.2 |
+ BXD |
+ BXD90 |
+ 72 |
+ M |
+ UTHSC RW |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD |
+ BXD92 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD |
+ BXD92 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD |
+ BXD92 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD |
+ BXD96 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD |
+ BXD96 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD |
+ BXD97 |
+ 74 |
+ F |
+ UTHSC RW |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD |
+ BXD97 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD |
+ BXD98 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD |
+ BXD98 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 165 |
+ R4533E |
+ BXD |
+ BXD99 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 166 |
+ R4534E |
+ BXD |
+ BXD99 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 167 |
+ R2885E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 168 |
+ R2883E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 169 |
+ R1700E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 170 |
+ R1704E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 171 |
+ R2605E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 79 |
+ F |
+ UTHSC RW |
+
+
+ | 172 |
+ R0871E |
+ GDP BXD |
+ C57BL/6J |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 173 |
+ R0872E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 174 |
+ R0872E |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 175 |
+ R4507E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 176 |
+ R4508E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 177 |
+ R4505E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 178 |
+ R4506E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 179 |
+ R4535E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ F |
+ JAX |
+
+
+ | 180 |
+ R4536E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ M |
+ JAX |
+
+
+ | 181 |
+ R2564E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ F |
+ JAX |
+
+
+ | 182 |
+ R2580E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ M |
+ JAX |
+
+
+ | 183 |
+ R4537E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 184 |
+ R4538E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 185 |
+ R4539E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 186 |
+ R4540E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 187 |
+ R2600E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 188 |
+ R2604E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 69 |
+ M |
+ UTHSC RW |
+
+
+ | 189 |
+ R1002E.3 |
+ GDP BXD |
+ DBA/2J |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 190 |
+ R4541E |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 191 |
+ R959E.3 |
+ GDP BXD |
+ DBA/2J |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 192 |
+ R2572E.1 |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 193 |
+ R4542E |
+ GDP BXD |
+ DBA/2J |
+ 59 |
+ M |
+ JAX |
+
+
+ | 194 |
+ R2771E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 195 |
+ R2772E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 196 |
+ R2636E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 197 |
+ R2637E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 198 |
+ R0999E.1 |
+ GDP |
+ LG/J |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 199 |
+ R1004E.1 |
+ GDP |
+ LG/J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 200 |
+ R4543E |
+ GDP |
+ LP/J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 201 |
+ R4544E |
+ GDP |
+ LP/J |
+ 65 |
+ M |
+ JAX |
+
+
+ | 202 |
+ R2858E.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 203 |
+ R2919.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 204 |
+ R1688E.1 |
+ GDP |
+ NOD/LtJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 205 |
+ R2566E-2.1 |
+ GDP |
+ NOD/LtJ |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 206 |
+ R4545E |
+ GDP |
+ NZB/BlNJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 207 |
+ R4546E |
+ GDP |
+ NZB/BlNJ |
+ 58 |
+ M |
+ BIDMC GR |
+
+
+ | 208 |
+ R2535E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 209 |
+ R2550E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ JAX |
+
+
+ | 210 |
+ R2817E.3 |
+ GDP |
+ NZW/LacJ |
+ 65 |
+ F |
+ BIDMC GR |
+
+
+ | 211 |
+ R2810E |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 212 |
+ R2810E.3 |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 213 |
+ R4547E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ F |
+ JAX |
+
+
+ | 214 |
+ R4548E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ M |
+ JAX |
+
+
+ | 215 |
+ R2635E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 216 |
+ R2634E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ M |
+ JAX |
+
+
+ | 217 |
+ R2544E.1 |
+ GDP |
+ PWK/PhJ |
+ 63 |
+ F |
+ JAX |
+
+
+ | 218 |
+ R2549E.1 |
+ GDP |
+ PWK/PhJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 219 |
+ R4550E |
+ GDP |
+ SJL/J |
+ 65 |
+ M+F |
+ JAX |
+
+
+ | 220 |
+ R2368E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 221 |
+ R2547E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0908_r_nb/acknowledgment.rtf b/general/datasets/Eye_m2_0908_r_nb/acknowledgment.rtf
new file mode 100644
index 0000000..5098d32
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nb/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant and from funds from NEI grant to Dr. Eldon Geisert (R01EY017841), an NEI Vision Core grant (EY14080) and an Unrestricted Grant from Research To Prevent Blindness.
+
+We thank Dr. Ted Choi, Chief Scientific Director of Predictive Biology, Inc. (past director of molecular genetics at Deltagen Inc.) for providing us with eye samples from several interesting DeltaGen knockouts.
diff --git a/general/datasets/Eye_m2_0908_r_nb/cases.rtf b/general/datasets/Eye_m2_0908_r_nb/cases.rtf
new file mode 100644
index 0000000..552d4a5
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nb/cases.rtf
@@ -0,0 +1,57 @@
+This is the complete and final HEIMED data set. HEIMED consists of expression data for 103 genetically defined lines of mice with standard errors of the mean. Almost all animals are young adults between 50 and 80 days of age (Table 1, maximum age is 123 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, reciprocal F1s between C57BL/6J and DBA/2J, and several mutant and knockout lines. We have combined all common strains, F1 hybrids, and mutants into a group called the Mouse Diversity Panel (MDP). Four lines, namely, C57BL/6J (B6), DBA/2J (D2), and the pair of B6D2F1 and D2B6F1 hybrids are common to both the MDP and the BXD set. This is a breakdown of cases that are part of HEIMED:
+
+
+ - 68 BXD strains. The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. Only one of these strains, BXD24 (know also known as BXD24b), has retinal degeneration (a spontaneous mutation). The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA.
+ - 35 MDP lines, including 26 inbred strains representing closely related substrains (e.g, BALB/cJ and BALB/cByJ), many of the most widely used common Mus musculus domesticus inbred strains (e.g., C57BL/6J and 129S1/SvImJ), inbred but wild-derived representatives of common subspecies (Mus musculus domesticus, e.g, WSB/EiJ; M. musculus musculus, e.g., CZECHII/EiJ; M. musculus molossinus, e.g., MOLF/EiJ; M. musculus castaneus, e.g., CAST/EiJ); and even one different species of mouse (Mus spicilegus, PANCEVO/EiJ). The MDP also includes the reciprocal F1 hybrids (B6D2F1 and D2B6F1) and the following 6 KO lines and the Nyx-nob mutant:
+ - 6 knockouts (KO), including a KO of Rpe65, and 5 DeltaGen Inc. knockout lines provided by Dr. Ted Choi. These KO lines have had a bacterial lacZ construct inserted into the gene. The endogenous promoter drives expression of beta-galactosidase. RT-PCR analysis detects a gene transcript in most tissues. The following KOs from DeltaGen were studied: Gabra1, Gabbr1, Gnb1, Gpr19, and Clcn3. We also included one spontaneous mutant of the nyctalopin (Nyx no b wave "nob") gene (Pardue et al., 1998) that is on a BALB/cByJ background.
+
+
+Rod photoreceptor degeneration in inbred mice: Six strains of mice included in HEIMED suffer from severe loss of photoreceptors (mainly rods) and have the equivalent of night blindness in human patients. The death of photoreceptors in these strains occurs by one to two months of age and is often caused by the retinal degeneration 1 (rd1) mutant allele in the rod cyclic-GMP phosphodiesterase 6 beta subunit gene (Pde6b). The following strains are known to have photoreceptor degeneration: C3H/HeJ, FVB/NJ, MOLF/EiJ, SJL/J and BXD24/TyJ. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEIMED data set.
+
+As expected (Dickerson LW et al., 2002) and as judged from the absence of rhodopsin expression, one of the DeltaGen KO lines (chloride ion channel 3, Clcn3) also has retinal degeneration: B6129P2F2N1-Clcn3. Degeneration in this strain is likely to include all rods and all cones. The cone defect is obvious from the decrease in expression of Gnat2, a gene associated with cones and achromatopsia in mice and humans.
+
+Lines of mice were selected using the following criteria:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - representation of a fairly wide variety of different subspecies of Mus
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Tel Aviv/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - interesting mutations or knockouts affecting genes with high expression in the eye
+ - general availability from The Jackson Laboratory. The only exception are the DeltaGen KO mice.
+
+
+We have included all eight parents of the Collaborative Cross (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/LtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ) in the MDP. Fourteen MDP strains have been partially sequenced by Perlegen for the NIEHS, including including 129S1/SvImJ, A/J, AKR/J, BALB/cByJ, C3H/HeJ, CAST/EiJ, DBA/2J, FVB/NJ, KK/HlJ, MOLF/EiJ, NOD/LtJ, NZW/LacJ, PWD/PhJ, and WSB/EiJ (see the GeneNetwork SNP Browser for data, details, and see Perlegen's excellent data resources and browser).
+
+
+ - 129S1/SvImJ : Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene. It is also a cone photoreceptor function loss 3 mutant (Cpfl3 allele) of the Gnat2 gene that is a model for achromatopsia (JAX Stock Number: 002448)
+ - A/J: Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase (Tyr c allele) albino mutant. This strain is particularly sensitive to light-induced photoreceptor loss (Danciger et al., 2007). (JAX Stock Number: 000646)
+ - BALB/cByJ: Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project old group A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Small brain, not aggressive (JAX Stock Number: 001026)
+ - BALB/cJ: Phenome Project A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Large brain and aggressive (JAX Stock Number: 000651)
+ - BXSB/MpJ: A white-bellied agouti strains with interesting autoimmune disease restricted to males that is associated with a mutation in the Yaa gene that causes glomerulonephritis, a dramatic increase in number of peripheral monocytes, and pre-B-cell deficiency (JAX Stock Number: 000740)
+ - C3H/HeJ: The Heston (He) substrain with a wildtype agouti (A allele) coat color. Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project old group A list. Important to note for this eye expression dataset, C3H/HeJ is a Pdeb6 rd1 mutant with near total photoreceptor loss at as early as postnatal day 30. Also a Tlr4 mutant that is endotoxin resistant. (JAX Stock Number: 000659)
+ - C57BL/6J: Sequenced by NIH/NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list. Single most widely used inbred strain of mouse. (JAX Stock Number: 000664)
+ - C57BLKS/J: Black Kaliss strain (non-agouti a allele) derived from C57BL/6J, but genetically contaminated at some point mainly with DBA/2J and then reinbred. Now at the Jackson Laboratory. (JAX Stock Number: 000662)
+ - CAST/EiJ: A wild-derived inbred Mus musculus castaneus strain. Samples of this subspecies were captured in Southeast Asia. One of three wild-derived strains in the Collaborative Cross sequenced by NIEHS; Phenome Project A list. CAST/Ei and CAST/EiJ are the same strain. The addition of the "J" is trivial and was added when stock were transferred from Dr. Eicher's lab to the Jackson Laboratory production facility in about 2004. (JAX Stock Number: 000928)
+ - CBA/CaJ: Agouti strain from the Jackson Laboratory. Wildtype pigment genes. (JAX Stock Number: 000654)
+ - CZECHII/EiJ: Czech 2 is a wild-derived inbred strain M. musculus musculus strain. Samples of this subspecies were caught in the Czech Republic and inbred at the Jackson Laboratory by Eva Eicher. White-bellied agouti. (JAX Stock Number: 001144).
+ - DBA/2J: The dilute, brown, agouti (dba) strain is the oldest inbred strain of mouse. Inbreeding was started in 1909 by Little. A tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. A myosin 5a (Myo5a d) dilute allele mutant. Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project old A group list. (JAX Stock Number: 000671)
+ - FVB/NJ: Friend's leukemia virus B (FVB) strain. Sequenced by Perlegen/NIEHS and Celera. Tyr c locus albino and a Pdeb6 rd1 mutant derived from Swiss mice at NIH. This has been the most common strain used to make transgenic mice due to large and easily injected oocytes; Phenome Project A list (JAX Stock Number: 001800).
+ - KK/HlJ: K Kondo's (KK) Kasukabe strain is a homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. Males have a form of type 2 diabetes. Sequenced by Perlegen/NIEHS. (JAX Stock Number: 002106)
+ - LG/J: Large (LG) strain. Paternal parent of the Large-by-Small set of RI strains made by James Cheverud and colleagues (the LGXSM panel, not to be confused with the LongXShort or LXS panel). A Tyr c locus albino strain. (JAX Stock Number: 000675)
+ - LP/J: White-bellied agouit strain with a piebald mutation in the endothelin receptor type B Ednrb gene from at the Jackson Laboratory. Some reduction in melanocytes in choroid of eye due to neural creast migration abnormalities. (JAX Stock Number: 000676)
+ - MOLF/EiJ: A wild-derived inbred strain derived from M. musculus molossinus samples camputered in Fukuoka, Japan. This strain has the retinal degeneration rd1 allele in Pde6b. There appears to have been some genetic contamination of this strain with conventional inbred strains in the past several decades (F. Pardo, personal communication to RWW, August 2006). However, the strain is currently fully inbred. (JAX Stock Number: 000550)
+ - NOD/LtJ: Non-obese diabetic strain, originally from M. Hattori in Kyoto, Japan. This is the Edward Leiter (Lt) substrain from the Jackson Laboratory. Collaborative Cross strain sequenced by NIEHS; Phenome Project B list. Homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. (JAX Stock Number: 001976)
+ - NZO/HlLtJ: New Zealand Obese strain. This is a severely obese and hypertensive strain. Males often develop a type 2 diabetes. Collaborative Cross strain. Agouti coat color. (JAX Stock Number: 002105)
+ - NZB/BlNJ: New Zealand Black inbred strain from Bielschowsky (BL, substrain is "B lowercase L N", not "BiN") now maintained at the Jackson Laboratory. (JAX Stock Number: 000648)
+ - NZW/LacJ: New Zealand White strain from the Laboratory Animal Center (Carshalton, UK), now maintained at the Jackson Laboratory. Carries the Tyr c locus albino mutation, the pink-eye dilution mutation in the Oca2 or p locus, and the brown allele at Tyrp1. (JAX Stock Number: 001058)
+ - PANCEVO/EiJ: PANCEVO/EiJ is a wild-derived inbred strain from the Mus spicilegus samples caught in the Pancevo, Serbia. This species of mouse is also known as the Steppe mouse (taxon identifier 10103). M. spicilegus is a colonial mound-building species. No known ocular or retina mutations, but the expression level of Gnat2 is low in this strain, either due to a 3' UTR length variant or possible achromatosia (cone degeneration) (JAX Stock Number: 001384)
+ - PWD/PhJ: A wild-derived Mus musculus musculus agouti strain inbred from samples caught near Prague, Czech Republic. Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues. (JAX Stock Number: 004660)
+ - PWK/PhJ: A wild-derived Mus musculus musculus inbred strain from samples caught near Lhotka, Czech Republic. Collaborative Cross strain; Phenome Project D list. (JAX Stock Number: 003715)
+ - SJL/J: Swiss Webster inbred strain from Jim Lambert's lab at the Jackson Laboratory. This strain has the retinal degeneration rd1 allele in Pde6b. It also carries both the Tyr c albino mutation and the pink-eye dilution mutation in the Oca2 or p locus. Highly aggressive males. (JAX Stock Number: 000686)
+ - WSB/EiJ: Watkin Star line B (or "wild son-of-a-bitch") is a wild-derived Mus musculus domesticus inbred strain from samples caught in Maryland, USA. A Collaborative Cross strain sequenced by NIEHS; Phenome Project C list (JAX Stock Number: 001145)
+ - B6D2F1 and D2B6F1 (also listed as BDF1 and DBF1 in some graphs and tables): F1 hybrids generated by crossing C57BL/6J with DBA/2J. These black reciprocal F1 can be used to detect dominance effects. Comparison of the two reciprocal F1s can be used to detect parental origin (imprinting) effects. The D2B6F1 animals are currently available from the Jackson Laboratory as a special order.) (JAX Stock Number for B6D2F1 hybrids obtained from the Jackson Laboratory, aka B6D2F1/J 100006)
+
+
+Most of the common inbred strains harbor mutations in genes the control pigmentation (Silvers, 2008 and material above in this INFO file). These gene include the albino and chinchilla alleles of the tyrosinase gene (Tyr, or human OCA1), the brown allele of the tyrosinase related protein 1 (Tyrp1), the pink-eye dilution allele of Oca2 (probe set 1418211), the non-agouti (black) and white-bellied alleles of the agouti signaling protein Asip, the steel allele of Kitlg, the dilute allele of Myo5a (probe set 1419754), and the piebald allele of Ednrb. In some of these cases, effects of the mutation are easily detected at the transcript level (Tyrp1, Oca2, and Myo5a), but in the other cases (Tyr, Asip, Ednrb, and Kitlg), mutations do not leave a strong imprint on expression.
diff --git a/general/datasets/Eye_m2_0908_r_nb/citation.rtf b/general/datasets/Eye_m2_0908_r_nb/citation.rtf
new file mode 100644
index 0000000..ddd98e4
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nb/citation.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams. Gene expression landscape of the mammalian eye: A global survey and database of mRNAs of 103 varieties of mice. Molecular Vision 2009; in press.
diff --git a/general/datasets/Eye_m2_0908_r_nb/contributors.rtf b/general/datasets/Eye_m2_0908_r_nb/contributors.rtf
new file mode 100644
index 0000000..d155833
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nb/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams
diff --git a/general/datasets/Eye_m2_0908_r_nb/experiment-design.rtf b/general/datasets/Eye_m2_0908_r_nb/experiment-design.rtf
new file mode 100644
index 0000000..1ebe0ad
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nb/experiment-design.rtf
@@ -0,0 +1 @@
+Expression profiling by array
diff --git a/general/datasets/Eye_m2_0908_r_nb/notes.rtf b/general/datasets/Eye_m2_0908_r_nb/notes.rtf
new file mode 100644
index 0000000..7a26eb5
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nb/notes.rtf
@@ -0,0 +1 @@
+This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/Eye_m2_0908_r_nb/platform.rtf b/general/datasets/Eye_m2_0908_r_nb/platform.rtf
new file mode 100644
index 0000000..9024a99
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nb/platform.rtf
@@ -0,0 +1,11 @@
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many probes overlap and target the same transcript). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequences as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
+As part of the development of HEIMED, we have manually annotated individual probe sets by sequence alignment to the mouse genome and transcriptome. Approximately 13,000 probe sets that have comparatively high expression in eye and CNS were curated by one of the authors (RWW) and now have specific information on the part of the transcript targeted by each probe set. The other 33,000 transcripts have corresponding data that was generated by Xusheng Wang using computational methods (BLAT analysis combined with annotated genome sequence).
+
+One example may help explain how to exploit this annotation. The four probe sets for rhodopsin include information on the target location. Only the first probe set targets the last two coding exons. The other three probe sets target different parts of the 3’ UTR (mid, distal, and far distal regions). The probe sets can be reordered by from high to low expression using the Sort By function in Search Results pages. In the case of rhodopsin, the probe set that targets that last two coding exons and proximal parts of the 3’ UTR also has the highest expression . Finally, the HEIMED gene descriptions have been customized to help vision researchers. In the case of rhodopsin, the description appended after the gene name reads “rod photoreceptor pigment, retinitis pigmentosa-associated”. For less well known genes this kind of annotation can be extremely useful. For example, the more verbose annotation for Cerkl reads “neuronal survival and apoptosis-related, retinal ganglion cell expressed, retinitis pigmentosa 26); alternative 3' UTR of short form message, intron 2”.
+
+
+
+
+
+Legend: Distribution of expression values for all probe sets in HEIMED.
diff --git a/general/datasets/Eye_m2_0908_r_nb/processing.rtf b/general/datasets/Eye_m2_0908_r_nb/processing.rtf
new file mode 100644
index 0000000..4349e60
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nb/processing.rtf
@@ -0,0 +1,3381 @@
+Range of Gene Expression in the Eye. Expression of transcripts in the HEIMED and most other GN data sets is measured on a log2 scale. Each unit corresponding approximately to a 2-fold difference in hybridization signal intensity. To simplify comparisons among different data sets and cases, log2 RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units (variance stabilized). Values of all 45,101 probe sets in this data set range from a low of 4.8 (Tcf15, probe set 1420281_at) to a high of 15.5 (crystallin gamma C, Crygc, probe set 1422674_s_at). This corresponds to 10.7 units or a 1 to 1700 dynamic range of expression (2^10.73).
+
+We used pooled RNA samples of whole eyes, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+We calibrated this log intensity scale using Affymetrix spike-in control probe sets. These 18 control probe sets target exogenous bacterial mRNAs that are added to each sample (a graded dose spike cocktail) during preparation at concentrations of 1.5, 5, 25, and 100 pM. (To find these probe sets, search GN’s ALL search field using the string “AFFX pM”.) A value of 6 or less is equivalent to an mRNA concentration of under 0.4 pM, a value of 8 is equivalent to ~1.5 pM, 9.5 is equivalent to ~5 pM, 11.5 is equivalent to ~25 pM, 13.5 is equivalent to ~100 pM, and a value of 15.5 is equivalent to an mRNA concentration of 400 pM or greater.
+
+This range can be converted to the mRNA molecules per cell in the eye assuming that a value of 8 is equivalent to about 1 mRNA copy per cell (Kanno et al. 2006, see http://www.biomedcentral.com/1471-2164/7/64). Since the expression of rhodopsin mRNA is normally 15 units, we predict that there are 27 or ~128 Rho mRNAs per cell in the whole eye and ~256 in rods themselves (assuming that rods make up about half of all cells in the eye). For this purpose it may be useful to know that a normal mouse eye contains between 6 and 8 million rod photoreceptors (Guo, Lu, and Williams; GN BXD Phenotype ID 11024).
+
+Note that some probe sets with very low expression still provide reliable data. For example, probe set 1440397_at (Cacna2d1) has expression of only 5.5 units (a value that would be declared as "absent" using conventional Affymetrix procedures), but the values for this calcium channel transcript are associated with a very strong cis QTL with an LRS of 79 (LOD = 17). This strong linkage is definitely not due to chance since the probability of the expression data mapping precisely to the location of the parent gene itself is about 10e-16. This indicates a high signal to noise ratio and the detection of significant strain variation of the correct transcript.
+
+The standard error of the mean for the HEIMED data set is computed for 2 to 6 biological replicates. The standard error of such small samples tends to systematically underestimate the population standard error. With n = 2 the underestimate is about 25%, whereas for n = 6 the underestimate is 5%. Gurland and Tripathi (1971) provide a correction and equation for this effect (see Sokal and Rohlf, Biometry, 2nd ed., 1981, p 53 for an equation of the correction factor for small samples of n < 20.) Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. The CEL files were processed using the RMA protocol. We processed the first three batches together. The last batch was processed separately and merged as described below.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
+After RMA processing using Biobase affy10 build running under R version 2.7.1, all array data sets were rank-order normalized. This second round of quantile normalization removes much residual non-linearity across arrays and forces every array to have the same distribution of values as the mean of all arrays. Comparative array data quality was then evaluated in DataDesk. Outlier arrays were flagged by visual inspection in DataDesk, usually by means of an analysis of scatter plots and more quantitatively by generating a correlation matrix of all arrays. Those arrays with mean correlation <0.96 versus all other arrays indicates trouble or a biological outlier). In some cases, outliers were expected, such as samples from strains with retinal degeneration (FVB/NJ, NOD/LtJ, MOLF/EiJ, C3H/HeJ and BXD24), samples from wild subspecies such as WSB/EiJ, CAST/EiJ, PWD/PhJ, and PWK/PhJ, and knockouts. However, when arrays were anomolous both within strain and across strains, they were often simply discarded. The assumption is that anomolous data are much more likely due to experimental and technical errors than to informative biological variation. Approximately 10% of arrays were discarded.
+
+After this process, the acceptable set of arrays was renormalized using all step as above, starting with the original RMA procedure, etc.
+
+We reviewed the data set using a new method developed by RW Williams, Jeremy Peirce, and Hongqiang Li. For the full set of arrays that passed standard QC protocols described above, we computed the strain means for the BXD strains, B6, D2, and F1s. Using this set of strain means we then computed LRS scores for all 45101 probe sets and counted the number of transcripts that generated QTLs with LRS values greater than 50. This value (e.g., 1800) represented the QTL harvest for the full data set. We then dropped a single array from the data set, recomputed strain means, and recomputed the number of transcripts with LRS scores great than 50. This value is expected to typically reduce the number of QTLs that reach the criterion level (e.g., 1750 QTLs > 50). This process was repeated for every array to obtain an array-specific difference value--the effect of removing that array on the total QTL count. For example, the loss of a single array might cause a decrease in 50 QTLs. Values ranged from approximately -90 (good arrays) to +40 (bad arrays). This procedure is similar in some ways to a jackknife protocol, although we are not using this procedure to esimate an error term, but rather as a method to polish a data set.
+
+During this process we discovered that nearly 20 arrays in the batch 2 had been mislabeled at some point in processing. We computed the correct strain membership of each array using a large number of Mendelian probe sets (more than 50) and comparing their match to standard SNP and microsatellite markers and the original array data set of November 2005. This allowed us to rescue a large number of arrays that were of high quality.
+
+A third batch of approximately 40 arrays were processed by Yan Jiao and Weikuan Gu in August 2006. These complete data set assembled by Hongqiang Li. This process again included a correction for a batch effect.
+
+For the June 2006 data set Hongqiang Li used a new batch correction method that stabilizes the range of expression in each batch. For each of the three large batches, we extracted the minumum and maximum raw probe expression (CEL file level) value. We then adjusted raw probe values in each batch to have the same range as the first and largest batch (batch 1) using a simple linear interpolation. These procedures generated new correct CEL files which were then used with RMA to generate final probe set estimates.
+
+For the final fourth batch of arrays (Sept 2008) Arthur Centeno and Rob Williams corrected for a systematic difference in probe set expression values between original arrays run in 2005 and 2006 and the new arrays added in 2008 (n = 45 acceptable arrays). This difference is due to unknown technical batch effects that are probably associated with labeling, hybridization, and scanning. We performed a simple correction to normalize values of the new set of arrays to those of the old set (batches 1 through 3). No changes were made to any values of the previous three batches. We corrected only the probe set level (RMA) values and not the CEL files. For this final batch, we corrected for the difference (offset) in probe set expression between the first three batches arrays run in 2005 and 2006 (a total of 174 acceptable arrays) and the new batch (n = 47 acceptable arrays). This difference is due to unknown technical effects that are probably related to various steps in labeling, hybridization, and scanning. The correction was applied as follows: (1) RWW selected 51 high quality arrays with similar expression characteristics (r = 0.97 or better between pairs of arrays) in the old data set (from batches 1, 2, and 3) and 34 high quality arrays in the final batch. RWW used scatterplots of full RMA transcriptome data sets to review many pairs of arrays within these new and old array batches. Strains with retinal degeneration or unusual eye gene expression characteristics were excluded from these selected subsets. The average expression values for each probe set were then computed for both the old and new array subsets. The offset value (old minus new) was added to each probe set across all 47 new arrays. This processes forces the average probe set in the new arrays to be very close to that of the previous arrays.
+
+Table 2: Sample tube ID, strain, original CEL filename, and Affymetrix quality control values. Columns labeled Scale factor, Background Average, Present, Absent, Marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Strain |
+ Original CEL |
+ Scale factor |
+ Background Average |
+ Present |
+ Absent |
+ Marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ Batch Id |
+ Used for batch control |
+
+
+ | 1 |
+ R2595E.1 |
+ 129S1/SvImJ |
+ R2595E.1.CEL |
+ 1.79 |
+ 115 |
+ 61.00% |
+ 37.50% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 2 |
+ R2533E.1 |
+ 129S1/SvImJ |
+ R2533E.1.CEL |
+ 2.11 |
+ 94 |
+ 57.90% |
+ 40.50% |
+ 1.60% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 3 |
+ R0754E.1 |
+ A/J |
+ R0754E.1.CEL |
+ 2.72 |
+ 86 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.36 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 4 |
+ R4521E |
+ B6129P2F2N1-Clcn3 |
+ R4521E.CEL |
+ 4.83 |
+ 38.7 |
+ 63.30% |
+ 35.30% |
+ 1.40% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 5 |
+ R4522E |
+ B6129P2F2N1-Clcn3 |
+ R4522E.CEL |
+ 5.76 |
+ 37.36 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.37 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 6 |
+ R4523E |
+ B6129P2F2N1-Clcn3 |
+ R4523E.CEL |
+ 4.88 |
+ 40.42 |
+ 63.90% |
+ 34.70% |
+ 1.40% |
+ 1.27 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 7 |
+ R4526E |
+ B6129P2F2N1-Gabbr1 |
+ R4526E.CEL |
+ 3.84 |
+ 44.18 |
+ 65.00% |
+ 33.70% |
+ 1.30% |
+ 1.34 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 8 |
+ R4509E |
+ B6129P2F2N1-Gabbr1 |
+ R4509E.CEL |
+ 7.45 |
+ 34.76 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.45 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 9 |
+ R4510E |
+ B6129P2F2N1-Gabbr1 |
+ R4510E.CEL |
+ 8.44 |
+ 37.44 |
+ 57.40% |
+ 41.10% |
+ 1.50% |
+ 1.35 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 10 |
+ R4511E |
+ B6129P2F2N1-Gabbr1 |
+ R4511E.CEL |
+ 5.91 |
+ 42.02 |
+ 61.40% |
+ 37.20% |
+ 1.40% |
+ 1.41 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 11 |
+ R4524E |
+ B6129P2F2N1-Gabbr1 |
+ R4524E.CEL |
+ 5.49 |
+ 42.34 |
+ 62.40% |
+ 36.20% |
+ 1.40% |
+ 1.29 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 12 |
+ R4525E |
+ B6129P2F2N1-Gabbr1 |
+ R4525E.CEL |
+ 4.69 |
+ 41.3 |
+ 63.10% |
+ 35.50% |
+ 1.40% |
+ 1.27 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 13 |
+ R4515E |
+ B6129P2F2N1-Gabra1 |
+ R4515E.CEL |
+ 5.75 |
+ 41.76 |
+ 62.80% |
+ 35.80% |
+ 1.40% |
+ 1.41 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 14 |
+ R4516E |
+ B6129P2F2N1-Gabra1 |
+ R4516E.CEL |
+ 7.07 |
+ 40.73 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.32 |
+ 0.87 |
+ 4 |
+ Y |
+
+
+ | 15 |
+ R4517E |
+ B6129P2F2N1-Gabra1 |
+ R4517E.CEL |
+ 5.45 |
+ 38.09 |
+ 62.70% |
+ 35.80% |
+ 1.40% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 16 |
+ R4512E |
+ B6129P2F2N1-Gnb5 |
+ R4512E.CEL |
+ 6.56 |
+ 38.02 |
+ 59.90% |
+ 38.70% |
+ 1.50% |
+ 1.33 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 17 |
+ R4513E |
+ B6129P2F2N1-Gnb5 |
+ R4513E.CEL |
+ 4.15 |
+ 41.6 |
+ 63.40% |
+ 35.10% |
+ 1.50% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ |
+
+
+ | 18 |
+ R4514E |
+ B6129P2F2N1-Gnb5 |
+ R4514E.CEL |
+ 5.86 |
+ 39.2 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.34 |
+ 0.81 |
+ 4 |
+ |
+
+
+ | 19 |
+ R4518E |
+ B6129P2F2N1-Gpr19 |
+ R4518E.CEL |
+ 5.58 |
+ 38.9 |
+ 62.60% |
+ 36.00% |
+ 1.30% |
+ 1.39 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 20 |
+ R4519E |
+ B6129P2F2N1-Gpr19 |
+ R4519E.CEL |
+ 5.95 |
+ 41.91 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.35 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 21 |
+ R2601E.1 |
+ B6D2F1 |
+ R2601E.1.CEL |
+ 2.55 |
+ 92 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.44 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 22 |
+ R2602E.1 |
+ B6D2F1 |
+ R2602E.1.CEL |
+ 2.6 |
+ 84 |
+ 59.70% |
+ 38.80% |
+ 1.50% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 23 |
+ R1676E.1 |
+ BALB/cByJ |
+ R1676E.1.CEL |
+ 2.69 |
+ 98 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.46 |
+ 0.74 |
+ 1 |
+ |
+
+
+ | 24 |
+ R1672E.1 |
+ BALB/cByJ |
+ R1672E.1.CEL |
+ 2.22 |
+ 111 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 25 |
+ R4530E |
+ BALB/cJ |
+ R4530E.CEL |
+ 6.37 |
+ 37.53 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.3 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 26 |
+ R4529E |
+ BALB/cJ |
+ R4529E.CEL |
+ 5.71 |
+ 41.33 |
+ 60.50% |
+ 38.00% |
+ 1.50% |
+ 1.48 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD1 |
+ R2704E.2.CEL |
+ 2.066 |
+ 139.61 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD1 |
+ R2707E.3.CEL |
+ 1 |
+ 80 |
+ 56.40% |
+ 42.10% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 3 |
+ |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD2 |
+ R1231E.2.CEL |
+ 2.197 |
+ 138.73 |
+ 57.30% |
+ 41.30% |
+ 1.40% |
+ 1.41 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD2 |
+ R2598E.1.CEL |
+ 1.99 |
+ 106 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD5 |
+ R2591E.1.CEL |
+ 1.7 |
+ 136 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.33 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD5 |
+ R2714E.2.CEL |
+ 1.404 |
+ 144.35 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD6 |
+ R2570E.1.CEL |
+ 1.99 |
+ 87 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.46 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD6 |
+ R2694E.2.CEL |
+ 1.983 |
+ 97.23 |
+ 61.60% |
+ 37.10% |
+ 1.30% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD8 |
+ R2538E.1.CEL |
+ 1.91 |
+ 102 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.52 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD8 |
+ R2709E.2.CEL |
+ 1.99 |
+ 99.79 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.42 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD9 |
+ R2708E.2.CEL |
+ 1.966 |
+ 126.46 |
+ 57.70% |
+ 40.70% |
+ 1.50% |
+ 1.4 |
+ 0.84 |
+ 2 |
+ |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD9 |
+ R2569E.1.CEL |
+ 1.75 |
+ 87 |
+ 55.10% |
+ 43.40% |
+ 1.50% |
+ 2.82 |
+ 3.14 |
+ 1 |
+ |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD11 |
+ R2581E.1.CEL |
+ 1.94 |
+ 89 |
+ 62.10% |
+ 36.40% |
+ 1.60% |
+ 1.55 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD11 |
+ R2612E.2.CEL |
+ 1.83 |
+ 142.03 |
+ 58.20% |
+ 40.50% |
+ 1.40% |
+ 1.78 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD12 |
+ R2742E.2.CEL |
+ 2.127 |
+ 134.14 |
+ 57.00% |
+ 41.60% |
+ 1.40% |
+ 1.64 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD12 |
+ R2543E.1.CEL |
+ 1.61 |
+ 118 |
+ 58.60% |
+ 39.90% |
+ 1.60% |
+ 1.43 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD13 |
+ R2586E.1.CEL |
+ 2.01 |
+ 74 |
+ 56.40% |
+ 42.00% |
+ 1.60% |
+ 2.85 |
+ 3.81 |
+ 1 |
+ |
+
+
+ | 44 |
+ R877E.2 |
+ BXD13 |
+ R877E.2.CEL |
+ 1.558 |
+ 125.63 |
+ 61.20% |
+ 37.50% |
+ 1.20% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD14 |
+ R2557E.1.CEL |
+ 1.83 |
+ 99 |
+ 62.50% |
+ 36.10% |
+ 1.40% |
+ 1.31 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD14 |
+ R1128E.2.CEL |
+ 1.91 |
+ 115 |
+ 59.90% |
+ 38.80% |
+ 1.40% |
+ 1.2 |
+ 0.82 |
+ 1 |
+ Y |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD15 |
+ R2701E.3.CEL |
+ 1 |
+ 88 |
+ 60.60% |
+ 37.90% |
+ 1.40% |
+ 1.5 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD15 |
+ R2716E.2.CEL |
+ 2.015 |
+ 150.83 |
+ 56.40% |
+ 42.10% |
+ 1.60% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD16 |
+ R2711E.2.CEL |
+ 1.953 |
+ 118.53 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD16 |
+ R2567E.1.CEL |
+ 2.24 |
+ 82 |
+ 56.70% |
+ 41.60% |
+ 1.70% |
+ 1.37 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD18 |
+ R2720E.2.CEL |
+ 2.32 |
+ 99.93 |
+ 59.50% |
+ 39.00% |
+ 1.50% |
+ 1.33 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD18 |
+ R2559E.1.CEL |
+ 1.65 |
+ 104 |
+ 60.80% |
+ 37.70% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD19 |
+ R2560E.1.CEL |
+ 1.79 |
+ 98 |
+ 60.90% |
+ 37.50% |
+ 1.60% |
+ 1.35 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD19 |
+ R2713E.2.CEL |
+ 1.67 |
+ 120.82 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD20 |
+ R2584E.1.CEL |
+ 2.07 |
+ 84 |
+ 59.30% |
+ 39.10% |
+ 1.60% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD20 |
+ R2731E.2.CEL |
+ 1.825 |
+ 147 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.4 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD21 |
+ R2702E.2.CEL |
+ 1.811 |
+ 128.65 |
+ 59.40% |
+ 39.10% |
+ 1.40% |
+ 1.26 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD21 |
+ R2541E2.1.CEL |
+ 2.63 |
+ 125 |
+ 56.00% |
+ 42.40% |
+ 1.50% |
+ 1.29 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD22 |
+ R2553E.1.CEL |
+ 1.95 |
+ 111 |
+ 59.90% |
+ 38.50% |
+ 1.50% |
+ 1.28 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD22 |
+ R2700E.2.CEL |
+ 1.858 |
+ 102.96 |
+ 61.50% |
+ 37.10% |
+ 1.30% |
+ 1.48 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD23 |
+ R2558E-2.1.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD23 |
+ R1086E.2.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD24 |
+ R2719E.2.CEL |
+ 1.47 |
+ 140.38 |
+ 61.50% |
+ 37.20% |
+ 1.30% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD24 |
+ R2589E2.1.CEL |
+ 2.61 |
+ 112 |
+ 57.50% |
+ 40.90% |
+ 1.60% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD25 |
+ R2573E-2.1.CEL |
+ 3.15 |
+ 72 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.77 |
+ 0.97 |
+ 1 |
+ |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD25 |
+ R2683E.2.CEL |
+ 1.777 |
+ 115.64 |
+ 58.30% |
+ 40.30% |
+ 1.40% |
+ 2.01 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD27 |
+ R2703E.2.CEL |
+ 1.263 |
+ 134.78 |
+ 62.60% |
+ 36.10% |
+ 1.40% |
+ 1.44 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD27 |
+ R2729E.3.CEL |
+ 1 |
+ 87 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.56 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD28 |
+ R2562E.3.CEL |
+ 1.65 |
+ 116 |
+ 59.90% |
+ 38.40% |
+ 1.70% |
+ 1.37 |
+ 0.79 |
+ 3 |
+ Y |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD28 |
+ R2721E.2.CEL |
+ 2.065 |
+ 157.39 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD29 |
+ R2561E.3.CEL |
+ 1 |
+ 77 |
+ 53.30% |
+ 45.40% |
+ 1.40% |
+ 3.36 |
+ 19.66 |
+ 3 |
+ |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD31 |
+ R1258E.2.CEL |
+ 2.063 |
+ 117.09 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.54 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD31 |
+ R2597E.1.CEL |
+ 2.37 |
+ 94 |
+ 60.30% |
+ 38.30% |
+ 1.50% |
+ 1.34 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD32 |
+ R2563E.1.CEL |
+ 1.55 |
+ 102 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD32 |
+ R1216E.2.CEL |
+ 2.23 |
+ 111.99 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.35 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD33 |
+ R2542E.1.CEL |
+ 2.13 |
+ 97 |
+ 56.50% |
+ 41.80% |
+ 1.60% |
+ 1.91 |
+ 0.93 |
+ 1 |
+ |
+
+
+ | 77 |
+ R857E.2 |
+ BXD33 |
+ R857E.2.CEL |
+ 1.737 |
+ 113.98 |
+ 61.90% |
+ 36.70% |
+ 1.30% |
+ 1.6 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD34 |
+ R1451E.2.CEL |
+ 1.843 |
+ 140.05 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ Y |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD34 |
+ R2585E.1.CEL |
+ 2.64 |
+ 75 |
+ 58.30% |
+ 40.00% |
+ 1.70% |
+ 1.25 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD36 |
+ R2698E.3.CEL |
+ 1 |
+ 86 |
+ 59.70% |
+ 39.00% |
+ 1.30% |
+ 1.46 |
+ 0.78 |
+ 3 |
+ |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD36 |
+ R2705E.3.CEL |
+ 1 |
+ 86 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.46 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD38 |
+ R2710E.2.CEL |
+ 2.112 |
+ 122.1 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.37 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD38 |
+ R2532E.1.CEL |
+ 2.04 |
+ 94 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.37 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD39 |
+ R2574E.1.CEL |
+ 1.98 |
+ 91 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD39 |
+ R2695E.2.CEL |
+ 1.638 |
+ 122.7 |
+ 60.80% |
+ 37.80% |
+ 1.50% |
+ 1.42 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD40 |
+ R2699E.2.CEL |
+ 1.827 |
+ 105.23 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD40 |
+ R2590E.1.CEL |
+ 2.71 |
+ 77 |
+ 59.10% |
+ 39.30% |
+ 1.50% |
+ 1.4 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD42 |
+ R2696E.2.CEL |
+ 1.622 |
+ 118.95 |
+ 62.00% |
+ 36.60% |
+ 1.50% |
+ 1.53 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD42 |
+ R2596E.1.CEL |
+ 2.63 |
+ 108 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 90 |
+ R994E.2 |
+ BXD43 |
+ R994E.2.CEL |
+ 1.966 |
+ 113.12 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.66 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD43 |
+ R2607E.1.CEL |
+ 2.43 |
+ 115 |
+ 58.60% |
+ 40.00% |
+ 1.40% |
+ 1.31 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD44 |
+ R2594E.1.CEL |
+ 1.77 |
+ 117 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.35 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD44 |
+ R2610E.2.CEL |
+ 1.814 |
+ 142.91 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.35 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD45 |
+ R2732E.2.CEL |
+ 2.154 |
+ 122.45 |
+ 56.50% |
+ 42.10% |
+ 1.40% |
+ 1.8 |
+ 0.83 |
+ 2 |
+ |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD45 |
+ R2592E.1.CEL |
+ 1.85 |
+ 106 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.43 |
+ 0.85 |
+ 1 |
+ Y |
+
+
+ | 96 |
+ R967E.2 |
+ BXD48 |
+ R967E.2.CEL |
+ 1.948 |
+ 130.95 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.63 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD48 |
+ R2606E.1.CEL |
+ 2.56 |
+ 106 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.35 |
+ 0.83 |
+ 1 |
+ Y |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD50 |
+ R2933E.3.CEL |
+ 1 |
+ 72 |
+ 52.90% |
+ 45.60% |
+ 1.50% |
+ 2.45 |
+ 0.98 |
+ 3 |
+ |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD50 |
+ R2937E.3.CEL |
+ 1 |
+ 89 |
+ 56.90% |
+ 41.60% |
+ 1.40% |
+ 1.81 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD51 |
+ R2603E.1.CEL |
+ 2.49 |
+ 115 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD51 |
+ R1042E.2.CEL |
+ 2.352 |
+ 104.12 |
+ 58.70% |
+ 39.90% |
+ 1.40% |
+ 1.53 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD55 |
+ R2980E.3.CEL |
+ 1 |
+ 82 |
+ 56.90% |
+ 41.70% |
+ 1.50% |
+ 1.77 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD55 |
+ R2690E.2.CEL |
+ 1.887 |
+ 164.01 |
+ 56.10% |
+ 42.30% |
+ 1.60% |
+ 1.43 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 104 |
+ R4176E |
+ BXD56 |
+ R4176E.CEL |
+ 4.75 |
+ 43.08 |
+ 63.00% |
+ 35.60% |
+ 1.30% |
+ 1.39 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 105 |
+ R4175E |
+ BXD56 |
+ R4175E.CEL |
+ 6 |
+ 38.49 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.47 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD60 |
+ R1006E.3.CEL |
+ 1 |
+ 98 |
+ 54.90% |
+ 43.70% |
+ 1.50% |
+ 2.7 |
+ 0.86 |
+ 3 |
+ |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD60 |
+ R2725E.2.CEL |
+ 1.551 |
+ 148.01 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD60 |
+ R1074E.3.CEL |
+ 1 |
+ 118 |
+ 55.50% |
+ 43.10% |
+ 1.40% |
+ 1.96 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD61 |
+ R2534E2.1.CEL |
+ 2.47 |
+ 118 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.42 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD61 |
+ R2684E.2.CEL |
+ 2.01 |
+ 131.03 |
+ 57.00% |
+ 41.50% |
+ 1.50% |
+ 1.34 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD62 |
+ R1107E.3.CEL |
+ 1 |
+ 83 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.43 |
+ 0.93 |
+ 3 |
+ |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD62 |
+ R2681E.2.CEL |
+ 2.086 |
+ 148.24 |
+ 57.20% |
+ 41.30% |
+ 1.50% |
+ 1.29 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 113 |
+ R965E.3 |
+ BXD62 |
+ R965E.3.CEL |
+ 1 |
+ 93.55 |
+ 53.30% |
+ 45.20% |
+ 1.50% |
+ 3.11 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD63 |
+ R1425E.2.CEL |
+ 1.7 |
+ 136 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.43 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD63 |
+ R2576E.3.CEL |
+ 1 |
+ 84 |
+ 61.30% |
+ 37.40% |
+ 1.40% |
+ 1.48 |
+ 0.76 |
+ 3 |
+ |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD64 |
+ R943E-2.2.CEL |
+ 1.591 |
+ 141.34 |
+ 60.10% |
+ 38.40% |
+ 1.50% |
+ 1.32 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD64 |
+ R2611E.1.CEL |
+ 2.29 |
+ 92 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 1.57 |
+ 1.06 |
+ 1 |
+ |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD65 |
+ R2689E.2.CEL |
+ 1.721 |
+ 142.44 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.38 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD65 |
+ R2583E.1.CEL |
+ 2.49 |
+ 70 |
+ 56.90% |
+ 41.50% |
+ 1.60% |
+ 1.67 |
+ 1.01 |
+ 1 |
+ |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD66 |
+ R2728E.2.CEL |
+ 1.714 |
+ 137.45 |
+ 59.40% |
+ 39.00% |
+ 1.60% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD66 |
+ R2536E2.1.CEL |
+ 2.74 |
+ 109 |
+ 56.10% |
+ 42.30% |
+ 1.70% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD66 |
+ R1207E.2.CEL |
+ 1.681 |
+ 136.86 |
+ 60.40% |
+ 38.10% |
+ 1.50% |
+ 1.45 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD67 |
+ R1192E.2.CEL |
+ 2.126 |
+ 123.37 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD67 |
+ R2727E.3.CEL |
+ 1 |
+ 82.55 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.97 |
+ 0.87 |
+ 2 |
+ |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD67 |
+ R2691E.3.CEL |
+ 1 |
+ 90 |
+ 54.80% |
+ 43.80% |
+ 1.50% |
+ 2.61 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD68 |
+ R2551E.1.CEL |
+ 2.49 |
+ 92 |
+ 54.30% |
+ 44.10% |
+ 1.60% |
+ 2.91 |
+ 1.55 |
+ 1 |
+ |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD68 |
+ R2726E.2.CEL |
+ 1.811 |
+ 153.09 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD69 |
+ R2593E.1.CEL |
+ 1.67 |
+ 128 |
+ 59.20% |
+ 39.50% |
+ 1.30% |
+ 1.47 |
+ 0.92 |
+ 1 |
+ Y |
+
+
+ | 129 |
+ R975E.2 |
+ BXD70 |
+ R975E.2.CEL |
+ 1.841 |
+ 137.97 |
+ 58.00% |
+ 40.50% |
+ 1.40% |
+ 1.36 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD70 |
+ R2537E2.1.CEL |
+ 2.93 |
+ 99 |
+ 58.00% |
+ 40.50% |
+ 1.60% |
+ 1.29 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 131 |
+ R4531E |
+ BXD71 |
+ R4531E.CEL |
+ 4.77 |
+ 43.48 |
+ 62.40% |
+ 36.30% |
+ 1.40% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 132 |
+ R4532E |
+ BXD71 |
+ R4532E.CEL |
+ 5.89 |
+ 40.68 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD73 |
+ R2779E.2.CEL |
+ 1.746 |
+ 121.11 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD73 |
+ R3024E.3.CEL |
+ 1 |
+ 78.05 |
+ 51.70% |
+ 46.60% |
+ 1.70% |
+ 2.3 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD75 |
+ R2565E.1.CEL |
+ 1.79 |
+ 102 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 2.31 |
+ 3.47 |
+ 1 |
+ |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD75 |
+ R1397E-re.2.CEL |
+ 1.449 |
+ 189.71 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD77 |
+ R2687E.3.CEL |
+ 1 |
+ 80 |
+ 58.00% |
+ 40.60% |
+ 1.40% |
+ 1.57 |
+ 0.8 |
+ 3 |
+ Y |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD77 |
+ R2717E.2.CEL |
+ 1.797 |
+ 84.43 |
+ 61.60% |
+ 36.90% |
+ 1.40% |
+ 1.49 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD77 |
+ R1421E.3.CEL |
+ 1 |
+ 94 |
+ 52.40% |
+ 46.20% |
+ 1.40% |
+ 2.29 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD80 |
+ R2579E.1.CEL |
+ 2.42 |
+ 72 |
+ 59.20% |
+ 39.40% |
+ 1.50% |
+ 1.73 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD80 |
+ R2686E.2.CEL |
+ 2.342 |
+ 119.63 |
+ 56.00% |
+ 42.60% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD83 |
+ R2956E.3.CEL |
+ 1 |
+ 84 |
+ 55.40% |
+ 43.20% |
+ 1.40% |
+ 1.39 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD83 |
+ R2960E.3.CEL |
+ 1 |
+ 80 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.5 |
+ 0.82 |
+ 3 |
+ Y |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD84 |
+ R2922E.3.CEL |
+ 1 |
+ 91 |
+ 57.80% |
+ 40.80% |
+ 1.50% |
+ 1.47 |
+ 0.83 |
+ 3 |
+ Y |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD84 |
+ R2895E.3.CEL |
+ 1 |
+ 75 |
+ 58.30% |
+ 40.20% |
+ 1.50% |
+ 1.56 |
+ 0.77 |
+ 3 |
+ Y |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD85 |
+ R2692E.2.CEL |
+ 1.423 |
+ 160.87 |
+ 60.20% |
+ 38.30% |
+ 1.40% |
+ 1.46 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD85 |
+ R2715E.2.CEL |
+ 1.488 |
+ 142.6 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.5 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD86 |
+ R1405E.2.CEL |
+ 2.351 |
+ 119.34 |
+ 56.40% |
+ 42.20% |
+ 1.40% |
+ 1.64 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD86 |
+ R1225E.3.CEL |
+ 1 |
+ 71 |
+ 53.90% |
+ 44.60% |
+ 1.40% |
+ 3.2 |
+ 1.61 |
+ 3 |
+ |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD87 |
+ R2724E.2.CEL |
+ 1.906 |
+ 113.71 |
+ 60.70% |
+ 37.90% |
+ 1.40% |
+ 1.45 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD87 |
+ R2540E.1.CEL |
+ 2.33 |
+ 93 |
+ 61.10% |
+ 37.40% |
+ 1.40% |
+ 1.22 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD89 |
+ R1433E.2.CEL |
+ 1 |
+ 2.241 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.41 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD89 |
+ R2546E.1.CEL |
+ 1.99 |
+ 96 |
+ 58.60% |
+ 39.70% |
+ 1.70% |
+ 1.47 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD90 |
+ R2578E2.1.CEL |
+ 2.79 |
+ 92 |
+ 58.60% |
+ 39.80% |
+ 1.60% |
+ 1.52 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 155 |
+ R859E.2 |
+ BXD90 |
+ R859E.2.CEL |
+ 1.847 |
+ 152.22 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.36 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD92 |
+ R2682E.2.CEL |
+ 1.547 |
+ 156.31 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.37 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD92 |
+ R1388E.3.CEL |
+ 1 |
+ 63 |
+ 60.00% |
+ 38.60% |
+ 1.40% |
+ 1.85 |
+ 1.03 |
+ 3 |
+ |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD92 |
+ R1322E.3.CEL |
+ 1 |
+ 80 |
+ 55.90% |
+ 42.60% |
+ 1.50% |
+ 1.75 |
+ 0.74 |
+ 3 |
+ |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD96 |
+ R2733E.2.CEL |
+ 1.7 |
+ 113.99 |
+ 62.10% |
+ 36.60% |
+ 1.30% |
+ 1.4 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD96 |
+ R2554E.1.CEL |
+ 2.18 |
+ 93 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD97 |
+ R2649E.2.CEL |
+ 2.343 |
+ 119.04 |
+ 57.50% |
+ 41.20% |
+ 1.40% |
+ 1.53 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD97 |
+ R2577E.1.CEL |
+ 2.07 |
+ 77 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.87 |
+ 1.29 |
+ 1 |
+ |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD98 |
+ R2645E.3.CEL |
+ 1 |
+ 88 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.59 |
+ 0.81 |
+ 3 |
+ Y |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD98 |
+ R2688E.2.CEL |
+ 1.772 |
+ 145.24 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.48 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 165 |
+ R4533E |
+ BXD99 |
+ R4533E.CEL |
+ 1 |
+ 37.69 |
+ 60.30% |
+ 38.20% |
+ 1.40% |
+ 1.33 |
+ 0.89 |
+ 4 |
+ Y |
+
+
+ | 166 |
+ R4534E |
+ BXD99 |
+ R4534E.CEL |
+ 5.69 |
+ 36.62 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.16 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 167 |
+ R2885E.3 |
+ BXSB/MpJ |
+ R2885E.3.CEL |
+ 1 |
+ 76 |
+ 58.10% |
+ 40.60% |
+ 1.30% |
+ 1.88 |
+ 1.06 |
+ 3 |
+ |
+
+
+ | 168 |
+ R2883E.3 |
+ BXSB/MpJ |
+ R2883E.3.CEL |
+ 1 |
+ 71 |
+ 56.40% |
+ 42.00% |
+ 1.50% |
+ 1.59 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 169 |
+ R1700E.1 |
+ C3H/HeJ |
+ R1700E.1.CEL |
+ 2.98 |
+ 69 |
+ 60.80% |
+ 37.90% |
+ 1.40% |
+ 1.48 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 170 |
+ R1704E.1 |
+ C3H/HeJ |
+ R1704E.1.CEL |
+ 2.58 |
+ 88 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.38 |
+ 0.84 |
+ 1 |
+ |
+
+
+ | 171 |
+ R2605E.1 |
+ C57BL/6J |
+ R2605E.1.CEL |
+ 1.82 |
+ 131 |
+ 60.50% |
+ 38.20% |
+ 1.30% |
+ 1.32 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 172 |
+ R0871E |
+ C57BL/6J |
+ R0871E.CEL |
+ 6.24 |
+ 37.38 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.41 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 173 |
+ R0872E.1 |
+ C57BL/6J |
+ R0872E.1.CEL |
+ 3.13 |
+ 89 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 174 |
+ R0872E |
+ C57BL/6J |
+ R0872E.CEL |
+ 3.128 |
+ 88.58 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 175 |
+ R4507E |
+ C57BL/6J-Nyx |
+ R4507E.CEL |
+ 8.13 |
+ 37.5 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.32 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 176 |
+ R4508E |
+ C57BL/6J-Nyx |
+ R4508E.CEL |
+ 6.33 |
+ 37.26 |
+ 60.90% |
+ 37.80% |
+ 1.30% |
+ 1.24 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 177 |
+ R4505E |
+ C57BL/6J-Rpe65 |
+ R4505E.CEL |
+ 5.98 |
+ 37.48 |
+ 61.80% |
+ 36.80% |
+ 1.40% |
+ 1.45 |
+ 0.85 |
+ 4 |
+ Y |
+
+
+ | 178 |
+ R4506E |
+ C57BL/6J-Rpe65 |
+ R4506E.CEL |
+ 6.94 |
+ 37.9 |
+ 61.10% |
+ 37.50% |
+ 1.30% |
+ 1.5 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 179 |
+ R4535E |
+ C57BLKS/J |
+ R4535E.CEL |
+ 6.59 |
+ 37.28 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.26 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 180 |
+ R4536E |
+ C57BLKS/J |
+ R4536E.CEL |
+ 1 |
+ 40.71 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 181 |
+ R2564E.1 |
+ CAST/EiJ |
+ R2564E.1.CEL |
+ 1.94 |
+ 89 |
+ 58.50% |
+ 39.90% |
+ 1.60% |
+ 1.6 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 182 |
+ R2580E.1 |
+ CAST/EiJ |
+ R2580E.1.CEL |
+ 2.09 |
+ 95 |
+ 58.20% |
+ 40.10% |
+ 1.70% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ |
+
+
+ | 183 |
+ R4537E |
+ CBA/CaJ |
+ R4537E.CEL |
+ 1 |
+ 38.45 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.63 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 184 |
+ R4538E |
+ CBA/CaJ |
+ R4538E.CEL |
+ 5.89 |
+ 39.18 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.45 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 185 |
+ R4539E |
+ CZECHII/EiJ |
+ R4539E.CEL |
+ 7.73 |
+ 37.1 |
+ 58.30% |
+ 40.10% |
+ 1.50% |
+ 1.7 |
+ 0.95 |
+ 4 |
+ Y |
+
+
+ | 186 |
+ R4540E |
+ CZECHII/EiJ |
+ R4540E.CEL |
+ 11.04 |
+ 36.69 |
+ 53.00% |
+ 45.30% |
+ 1.70% |
+ 1.83 |
+ 1.32 |
+ 4 |
+ |
+
+
+ | 187 |
+ R2600E.1 |
+ D2B6F1 |
+ R2600E.1.CEL |
+ 2.47 |
+ 95 |
+ 58.10% |
+ 40.20% |
+ 1.70% |
+ 1.41 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 188 |
+ R2604E.1 |
+ D2B6F1 |
+ R2604E.1.CEL |
+ 2.66 |
+ 90 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 189 |
+ R1002E.3 |
+ DBA/2J |
+ R1002E.3.CEL |
+ 1 |
+ 102 |
+ 54.80% |
+ 43.70% |
+ 1.50% |
+ 2.84 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 190 |
+ R4541E |
+ DBA/2J |
+ R4541E.CEL |
+ 1 |
+ 43.4 |
+ 61.40% |
+ 37.00% |
+ 1.50% |
+ 1.37 |
+ 0.73 |
+ 4 |
+ Y |
+
+
+ | 191 |
+ R959E.3 |
+ DBA/2J |
+ R959E.3.CEL |
+ 1 |
+ 89.97 |
+ 53.20% |
+ 45.30% |
+ 1.50% |
+ 3.66 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 192 |
+ R2572E.1 |
+ DBA/2J |
+ R2572E.1.CEL |
+ 2.41 |
+ 79 |
+ 55.50% |
+ 42.90% |
+ 1.60% |
+ 1.37 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 193 |
+ R4542E |
+ DBA/2J |
+ R4542E.CEL |
+ 5.7 |
+ 39.95 |
+ 61.00% |
+ 37.40% |
+ 1.50% |
+ 1.23 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 194 |
+ R2771E.3 |
+ FVB/NJ |
+ R2771E.3.CEL |
+ 1 |
+ 70 |
+ 55.30% |
+ 43.20% |
+ 1.50% |
+ 1.69 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 195 |
+ R2772E.3 |
+ FVB/NJ |
+ R2772E.3.CEL |
+ 1 |
+ 76 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.13 |
+ 1.02 |
+ 3 |
+ |
+
+
+ | 196 |
+ R2636E.1 |
+ KK/HlJ |
+ R2636E.1.CEL |
+ 2.61 |
+ 93 |
+ 58.90% |
+ 39.50% |
+ 1.50% |
+ 1.39 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 197 |
+ R2637E.1 |
+ KK/HlJ |
+ R2637E.1.CEL |
+ 2.19 |
+ 103 |
+ 59.40% |
+ 39.00% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 198 |
+ R0999E.1 |
+ LG/J |
+ R0999E.1.CEL |
+ 2.45 |
+ 82 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 199 |
+ R1004E.1 |
+ LG/J |
+ R1004E.1.CEL |
+ 2.44 |
+ 92 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 200 |
+ R4543E |
+ LP/J |
+ R4543E.CEL |
+ 6.57 |
+ 41.99 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.28 |
+ 0.75 |
+ 4 |
+ Y |
+
+
+ | 201 |
+ R4544E |
+ LP/J |
+ R4544E.CEL |
+ 4.56 |
+ 39.9 |
+ 62.40% |
+ 36.10% |
+ 1.50% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 202 |
+ R2858E.3 |
+ MOLF/EiJ |
+ R2858E.3.CEL |
+ 1 |
+ 64 |
+ 53.80% |
+ 44.70% |
+ 1.50% |
+ 1.59 |
+ 0.95 |
+ 3 |
+ |
+
+
+ | 203 |
+ R2919.3 |
+ MOLF/EiJ |
+ R2919.3.CEL |
+ 1 |
+ 64 |
+ 52.40% |
+ 46.00% |
+ 1.60% |
+ 2.15 |
+ 1.07 |
+ 3 |
+ |
+
+
+ | 204 |
+ R1688E.1 |
+ NOD/LtJ |
+ R1688E.1.CEL |
+ 2.66 |
+ 98 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 205 |
+ R2566E-2.1 |
+ NOD/LtJ |
+ R2566E-2.1.CEL |
+ 3.03 |
+ 69 |
+ 59.80% |
+ 38.80% |
+ 1.50% |
+ 1.38 |
+ 0.75 |
+ 1 |
+ Y |
+
+
+ | 206 |
+ R4545E |
+ NZB/BlNJ |
+ R4545E.CEL |
+ 4.23 |
+ 43.48 |
+ 62.10% |
+ 36.40% |
+ 1.50% |
+ 1.33 |
+ 0.76 |
+ 4 |
+ Y |
+
+
+ | 207 |
+ R4546E |
+ NZB/BlNJ |
+ R4546E.CEL |
+ 6.27 |
+ 44.22 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.17 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 208 |
+ R2535E.1 |
+ NZO/HlLtJ |
+ R2535E.1.CEL |
+ 1.89 |
+ 86 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.41 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 209 |
+ R2550E.1 |
+ NZO/HlLtJ |
+ R2550E.1.CEL |
+ 1.79 |
+ 87 |
+ 60.70% |
+ 37.80% |
+ 1.50% |
+ 1.52 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 210 |
+ R2817E.3 |
+ NZW/LacJ |
+ R2817E.3.CEL |
+ 1 |
+ 59 |
+ 50.90% |
+ 47.60% |
+ 1.50% |
+ 3.59 |
+ 1.48 |
+ 3 |
+ |
+
+
+ | 211 |
+ R2810E |
+ NZW/LacJ |
+ R2810E.CEL |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ 3 |
+ |
+
+
+ | 212 |
+ R2810E.3 |
+ NZW/LacJ |
+ R2810E.3.CEL |
+ 1 |
+ 74 |
+ 57.00% |
+ 41.70% |
+ 1.40% |
+ 2.15 |
+ 1.03 |
+ 4 |
+ Y |
+
+
+ | 213 |
+ R4547E |
+ PANCEVO/EiJ |
+ R4547E.CEL |
+ 5.27 |
+ 51.34 |
+ 57.20% |
+ 41.10% |
+ 1.70% |
+ 1.7 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 214 |
+ R4548E |
+ PANCEVO/EiJ |
+ R4548E.CEL |
+ 10.54 |
+ 37.39 |
+ 50.30% |
+ 48.00% |
+ 1.70% |
+ 1.68 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 215 |
+ R2635E.1 |
+ PWD/PhJ |
+ R2635E.1.CEL |
+ 3.72 |
+ 80 |
+ 54.20% |
+ 44.10% |
+ 1.70% |
+ 1.53 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 216 |
+ R2634E.1 |
+ PWD/PhJ |
+ R2634E.1.CEL |
+ 3.29 |
+ 90 |
+ 55.90% |
+ 42.50% |
+ 1.60% |
+ 1.57 |
+ 0.81 |
+ 1 |
+ |
+
+
+ | 217 |
+ R2544E.1 |
+ PWK/PhJ |
+ R2544E.1.CEL |
+ 2.2 |
+ 108 |
+ 54.90% |
+ 43.50% |
+ 1.70% |
+ 1.36 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 218 |
+ R2549E.1 |
+ PWK/PhJ |
+ R2549E.1.CEL |
+ 2.28 |
+ 84 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.57 |
+ 0.83 |
+ 1 |
+ |
+
+
+ | 219 |
+ R4550E |
+ SJL/J |
+ R4550E.CEL |
+ 5.35 |
+ 40.44 |
+ 62.30% |
+ 36.20% |
+ 1.40% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ |
+
+
+ | 220 |
+ R2368E.1 |
+ WSB/EiJ |
+ R2368E.1.CEL |
+ 2.57 |
+ 86 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.29 |
+ 0.74 |
+ 1 |
+ Y |
+
+
+ | 221 |
+ R2547E.1 |
+ WSB/EiJ |
+ R2547E.1.CEL |
+ 2.14 |
+ 90 |
+ 58.20% |
+ 40.10% |
+ 1.60% |
+ 1.32 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0908_r_nb/summary.rtf b/general/datasets/Eye_m2_0908_r_nb/summary.rtf
new file mode 100644
index 0000000..44b7e23
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nb/summary.rtf
@@ -0,0 +1,12 @@
+FINAL RECOMMENDED EYE DATA SET. The HEIMED September 2008 RMA data release provides estimates of gene expression in whole eyes of 103 lines of young adult mice generated using 221 Affymetrix M430 2.0 arrays. This data set is intended for exploration of the genetics and genomics of the mouse eye, retina, lens, retinal pigment epithelium, cornea, iris and choroid. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). We used pooled RNA samples, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+Users of these mouse eye data may also find the following complementary resources extremely useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
diff --git a/general/datasets/Eye_m2_0908_r_nb/tissue.rtf b/general/datasets/Eye_m2_0908_r_nb/tissue.rtf
new file mode 100644
index 0000000..9b6ee0f
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nb/tissue.rtf
@@ -0,0 +1,2058 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of cRNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. All samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center led by Dr. Weikuan Gu. All arrays were processed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. C until use (roughly one third) or were used immediately for hybridization.
+
+Dealing with ocular pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations taken from brown and beige colored mice tend to have faint residual pigmentation that affects hybridization signal. To address this problem, Dr. Yan Jiao purified total RNA using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204) all four batches.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well balanced sample of males and females, in general without within-strain-by-sex replication. Two strains are represented by a single male sample pool (BXD29 and A/J). Four lines are represented by two or three male sample pools (all of the five DeltaGen KO line). The SJL/J may be a single mixed sex sample. Users can study possible sex effects by comparing any results of expression data to that of a surrogate measurement that summarizes the overall sex balance of HEIMED. To do this just compare your data to those of probe sets 1427262_at (Xist, high in females) and probe set 1426438_at (Ddx3y, high in males). These two sex-specific probes are quantitative surrogates for the sex balance in this data set.
+
+Technical duplicates: One sample, highlighted in the tables below, is a technical duplicate. The pair of technical duplicates were both of high quality. For statistical analysis, they should be combined and treated as single biological sample.
+
+Batch structure: This data set consists of four batches (Table 2, far right column). The final September 2008 data set consists of a total of 221 arrays and 220 independent samples.
+
+
+ - Batch 1: November 2005, n = 78 arrays original arrays of which 76 were accepted into this final data set.
+ - Batch 2: January 2006, n = 62 arrays of which 62 were accepted.
+ - Batch 3: August 2006, n = 39 arrays of which 36 were accepted. (These three batches, including some arrays that were eventually dropped from the final 2008 data set, were combined to form the September 2006 data set.)
+ - Batch 4: Summer 2008, n = 53 arrays of which 47 were accepted.
+
+
+Table 1: HEIMED case IDs, including sample tube ID, strain, age, sex, and source of mice (see Table 2 for information on array quality control)
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Group |
+ Strain |
+ Age |
+ Sex |
+ Source |
+
+
+ | 1 |
+ R2595E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 2 |
+ R2533E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 3 |
+ R0754E.1 |
+ GDP |
+ A/J |
+ 60 |
+ M |
+ JAX |
+
+
+ | 4 |
+ R4521E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 5 |
+ R4522E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 6 |
+ R4523E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 7 |
+ R4526E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 8 |
+ R4509E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 9 |
+ R4510E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 10 |
+ R4511E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 20 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 11 |
+ R4524E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 12 |
+ R4525E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 13 |
+ R4515E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 14 |
+ R4516E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 15 |
+ R4517E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 16 |
+ R4512E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 17 |
+ R4513E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 25 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 18 |
+ R4514E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 19 |
+ R4518E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 70 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 20 |
+ R4519E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 68 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 21 |
+ R2601E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 22 |
+ R2602E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 23 |
+ R1676E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ F |
+ JAX |
+
+
+ | 24 |
+ R1672E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 25 |
+ R4530E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 26 |
+ R4529E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD |
+ BXD1 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD |
+ BXD1 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD |
+ BXD2 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD |
+ BXD2 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD |
+ BXD5 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD |
+ BXD5 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD |
+ BXD6 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD |
+ BXD6 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD |
+ BXD8 |
+ 77 |
+ F |
+ UTHSC RW |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD |
+ BXD8 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD |
+ BXD9 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD |
+ BXD9 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD |
+ BXD11 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD |
+ BXD11 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD |
+ BXD12 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD |
+ BXD12 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD |
+ BXD13 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 44 |
+ R877E.2 |
+ BXD |
+ BXD13 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD |
+ BXD14 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD |
+ BXD14 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD |
+ BXD15 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD |
+ BXD15 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD |
+ BXD16 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD |
+ BXD16 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD |
+ BXD18 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD |
+ BXD18 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD |
+ BXD19 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD |
+ BXD19 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD |
+ BXD20 |
+ 59 |
+ F |
+ BIDMC GR |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD |
+ BXD20 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD |
+ BXD21 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD |
+ BXD21 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD |
+ BXD22 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD |
+ BXD22 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD |
+ BXD23 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD |
+ BXD23 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD |
+ BXD24 |
+ 123 |
+ F |
+ UTHSC RW |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD |
+ BXD24 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD |
+ BXD25 |
+ 67 |
+ F |
+ UAB |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD |
+ BXD25 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD |
+ BXD27 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD |
+ BXD27 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD |
+ BXD28 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD |
+ BXD28 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD |
+ BXD29 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD |
+ BXD31 |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD |
+ BXD31 |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD |
+ BXD32 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD |
+ BXD32 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD |
+ BXD33 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 77 |
+ R857E.2 |
+ BXD |
+ BXD33 |
+ 77 |
+ M |
+ UTHSC RW |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD |
+ BXD34 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD |
+ BXD34 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD |
+ BXD36 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD |
+ BXD36 |
+ 57 |
+ M |
+ BIDMC GR |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD |
+ BXD38 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD |
+ BXD38 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD |
+ BXD39 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD |
+ BXD39 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD |
+ BXD40 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD |
+ BXD40 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD |
+ BXD42 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD |
+ BXD42 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 90 |
+ R994E.2 |
+ BXD |
+ BXD43 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD |
+ BXD43 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD |
+ BXD44 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD |
+ BXD44 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD |
+ BXD45 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD |
+ BXD45 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 96 |
+ R967E.2 |
+ BXD |
+ BXD48 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD |
+ BXD48 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD |
+ BXD51 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD |
+ BXD51 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD |
+ BXD55 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD |
+ BXD55 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 104 |
+ R4176E |
+ BXD |
+ BXD56 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 105 |
+ R4175E |
+ BXD |
+ BXD56 |
+ 53 |
+ M |
+ UTHSC RW |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD |
+ BXD60 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD |
+ BXD60 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD |
+ BXD60 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD |
+ BXD61 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD |
+ BXD61 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ F |
+ UTHSC RW |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD |
+ BXD62 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 113 |
+ R965E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD |
+ BXD63 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD |
+ BXD63 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD |
+ BXD64 |
+ 56 |
+ F |
+ UTHSC RW |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD |
+ BXD64 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD |
+ BXD65 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD |
+ BXD65 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD |
+ BXD66 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD |
+ BXD66 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD |
+ BXD66 |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD |
+ BXD67 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD |
+ BXD68 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD |
+ BXD69 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 129 |
+ R975E.2 |
+ BXD |
+ BXD70 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD |
+ BXD70 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 131 |
+ R4531E |
+ BXD |
+ BXD71 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 132 |
+ R4532E |
+ BXD |
+ BXD71 |
+ 86 |
+ M |
+ UTHSC RW |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD |
+ BXD73 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD |
+ BXD73 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD |
+ BXD75 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD |
+ BXD75 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD |
+ BXD77 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD |
+ BXD77 |
+ 107 |
+ M |
+ UTHSC RW |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD |
+ BXD77 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD |
+ BXD80 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD |
+ BXD80 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD |
+ BXD84 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD |
+ BXD84 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD |
+ BXD85 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD |
+ BXD85 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD |
+ BXD86 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD |
+ BXD86 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD |
+ BXD87 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD |
+ BXD87 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD |
+ BXD89 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD |
+ BXD89 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD |
+ BXD90 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 155 |
+ R859E.2 |
+ BXD |
+ BXD90 |
+ 72 |
+ M |
+ UTHSC RW |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD |
+ BXD92 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD |
+ BXD92 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD |
+ BXD92 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD |
+ BXD96 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD |
+ BXD96 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD |
+ BXD97 |
+ 74 |
+ F |
+ UTHSC RW |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD |
+ BXD97 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD |
+ BXD98 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD |
+ BXD98 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 165 |
+ R4533E |
+ BXD |
+ BXD99 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 166 |
+ R4534E |
+ BXD |
+ BXD99 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 167 |
+ R2885E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 168 |
+ R2883E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 169 |
+ R1700E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 170 |
+ R1704E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 171 |
+ R2605E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 79 |
+ F |
+ UTHSC RW |
+
+
+ | 172 |
+ R0871E |
+ GDP BXD |
+ C57BL/6J |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 173 |
+ R0872E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 174 |
+ R0872E |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 175 |
+ R4507E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 176 |
+ R4508E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 177 |
+ R4505E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 178 |
+ R4506E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 179 |
+ R4535E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ F |
+ JAX |
+
+
+ | 180 |
+ R4536E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ M |
+ JAX |
+
+
+ | 181 |
+ R2564E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ F |
+ JAX |
+
+
+ | 182 |
+ R2580E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ M |
+ JAX |
+
+
+ | 183 |
+ R4537E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 184 |
+ R4538E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 185 |
+ R4539E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 186 |
+ R4540E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 187 |
+ R2600E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 188 |
+ R2604E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 69 |
+ M |
+ UTHSC RW |
+
+
+ | 189 |
+ R1002E.3 |
+ GDP BXD |
+ DBA/2J |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 190 |
+ R4541E |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 191 |
+ R959E.3 |
+ GDP BXD |
+ DBA/2J |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 192 |
+ R2572E.1 |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 193 |
+ R4542E |
+ GDP BXD |
+ DBA/2J |
+ 59 |
+ M |
+ JAX |
+
+
+ | 194 |
+ R2771E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 195 |
+ R2772E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 196 |
+ R2636E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 197 |
+ R2637E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 198 |
+ R0999E.1 |
+ GDP |
+ LG/J |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 199 |
+ R1004E.1 |
+ GDP |
+ LG/J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 200 |
+ R4543E |
+ GDP |
+ LP/J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 201 |
+ R4544E |
+ GDP |
+ LP/J |
+ 65 |
+ M |
+ JAX |
+
+
+ | 202 |
+ R2858E.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 203 |
+ R2919.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 204 |
+ R1688E.1 |
+ GDP |
+ NOD/LtJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 205 |
+ R2566E-2.1 |
+ GDP |
+ NOD/LtJ |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 206 |
+ R4545E |
+ GDP |
+ NZB/BlNJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 207 |
+ R4546E |
+ GDP |
+ NZB/BlNJ |
+ 58 |
+ M |
+ BIDMC GR |
+
+
+ | 208 |
+ R2535E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 209 |
+ R2550E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ JAX |
+
+
+ | 210 |
+ R2817E.3 |
+ GDP |
+ NZW/LacJ |
+ 65 |
+ F |
+ BIDMC GR |
+
+
+ | 211 |
+ R2810E |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 212 |
+ R2810E.3 |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 213 |
+ R4547E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ F |
+ JAX |
+
+
+ | 214 |
+ R4548E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ M |
+ JAX |
+
+
+ | 215 |
+ R2635E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 216 |
+ R2634E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ M |
+ JAX |
+
+
+ | 217 |
+ R2544E.1 |
+ GDP |
+ PWK/PhJ |
+ 63 |
+ F |
+ JAX |
+
+
+ | 218 |
+ R2549E.1 |
+ GDP |
+ PWK/PhJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 219 |
+ R4550E |
+ GDP |
+ SJL/J |
+ 65 |
+ M+F |
+ JAX |
+
+
+ | 220 |
+ R2368E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 221 |
+ R2547E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0908_r_nd/acknowledgment.rtf b/general/datasets/Eye_m2_0908_r_nd/acknowledgment.rtf
new file mode 100644
index 0000000..5098d32
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nd/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant and from funds from NEI grant to Dr. Eldon Geisert (R01EY017841), an NEI Vision Core grant (EY14080) and an Unrestricted Grant from Research To Prevent Blindness.
+
+We thank Dr. Ted Choi, Chief Scientific Director of Predictive Biology, Inc. (past director of molecular genetics at Deltagen Inc.) for providing us with eye samples from several interesting DeltaGen knockouts.
diff --git a/general/datasets/Eye_m2_0908_r_nd/cases.rtf b/general/datasets/Eye_m2_0908_r_nd/cases.rtf
new file mode 100644
index 0000000..552d4a5
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nd/cases.rtf
@@ -0,0 +1,57 @@
+This is the complete and final HEIMED data set. HEIMED consists of expression data for 103 genetically defined lines of mice with standard errors of the mean. Almost all animals are young adults between 50 and 80 days of age (Table 1, maximum age is 123 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, reciprocal F1s between C57BL/6J and DBA/2J, and several mutant and knockout lines. We have combined all common strains, F1 hybrids, and mutants into a group called the Mouse Diversity Panel (MDP). Four lines, namely, C57BL/6J (B6), DBA/2J (D2), and the pair of B6D2F1 and D2B6F1 hybrids are common to both the MDP and the BXD set. This is a breakdown of cases that are part of HEIMED:
+
+
+ - 68 BXD strains. The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. Only one of these strains, BXD24 (know also known as BXD24b), has retinal degeneration (a spontaneous mutation). The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA.
+ - 35 MDP lines, including 26 inbred strains representing closely related substrains (e.g, BALB/cJ and BALB/cByJ), many of the most widely used common Mus musculus domesticus inbred strains (e.g., C57BL/6J and 129S1/SvImJ), inbred but wild-derived representatives of common subspecies (Mus musculus domesticus, e.g, WSB/EiJ; M. musculus musculus, e.g., CZECHII/EiJ; M. musculus molossinus, e.g., MOLF/EiJ; M. musculus castaneus, e.g., CAST/EiJ); and even one different species of mouse (Mus spicilegus, PANCEVO/EiJ). The MDP also includes the reciprocal F1 hybrids (B6D2F1 and D2B6F1) and the following 6 KO lines and the Nyx-nob mutant:
+ - 6 knockouts (KO), including a KO of Rpe65, and 5 DeltaGen Inc. knockout lines provided by Dr. Ted Choi. These KO lines have had a bacterial lacZ construct inserted into the gene. The endogenous promoter drives expression of beta-galactosidase. RT-PCR analysis detects a gene transcript in most tissues. The following KOs from DeltaGen were studied: Gabra1, Gabbr1, Gnb1, Gpr19, and Clcn3. We also included one spontaneous mutant of the nyctalopin (Nyx no b wave "nob") gene (Pardue et al., 1998) that is on a BALB/cByJ background.
+
+
+Rod photoreceptor degeneration in inbred mice: Six strains of mice included in HEIMED suffer from severe loss of photoreceptors (mainly rods) and have the equivalent of night blindness in human patients. The death of photoreceptors in these strains occurs by one to two months of age and is often caused by the retinal degeneration 1 (rd1) mutant allele in the rod cyclic-GMP phosphodiesterase 6 beta subunit gene (Pde6b). The following strains are known to have photoreceptor degeneration: C3H/HeJ, FVB/NJ, MOLF/EiJ, SJL/J and BXD24/TyJ. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEIMED data set.
+
+As expected (Dickerson LW et al., 2002) and as judged from the absence of rhodopsin expression, one of the DeltaGen KO lines (chloride ion channel 3, Clcn3) also has retinal degeneration: B6129P2F2N1-Clcn3. Degeneration in this strain is likely to include all rods and all cones. The cone defect is obvious from the decrease in expression of Gnat2, a gene associated with cones and achromatopsia in mice and humans.
+
+Lines of mice were selected using the following criteria:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - representation of a fairly wide variety of different subspecies of Mus
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Tel Aviv/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - interesting mutations or knockouts affecting genes with high expression in the eye
+ - general availability from The Jackson Laboratory. The only exception are the DeltaGen KO mice.
+
+
+We have included all eight parents of the Collaborative Cross (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/LtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ) in the MDP. Fourteen MDP strains have been partially sequenced by Perlegen for the NIEHS, including including 129S1/SvImJ, A/J, AKR/J, BALB/cByJ, C3H/HeJ, CAST/EiJ, DBA/2J, FVB/NJ, KK/HlJ, MOLF/EiJ, NOD/LtJ, NZW/LacJ, PWD/PhJ, and WSB/EiJ (see the GeneNetwork SNP Browser for data, details, and see Perlegen's excellent data resources and browser).
+
+
+ - 129S1/SvImJ : Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene. It is also a cone photoreceptor function loss 3 mutant (Cpfl3 allele) of the Gnat2 gene that is a model for achromatopsia (JAX Stock Number: 002448)
+ - A/J: Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase (Tyr c allele) albino mutant. This strain is particularly sensitive to light-induced photoreceptor loss (Danciger et al., 2007). (JAX Stock Number: 000646)
+ - BALB/cByJ: Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project old group A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Small brain, not aggressive (JAX Stock Number: 001026)
+ - BALB/cJ: Phenome Project A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Large brain and aggressive (JAX Stock Number: 000651)
+ - BXSB/MpJ: A white-bellied agouti strains with interesting autoimmune disease restricted to males that is associated with a mutation in the Yaa gene that causes glomerulonephritis, a dramatic increase in number of peripheral monocytes, and pre-B-cell deficiency (JAX Stock Number: 000740)
+ - C3H/HeJ: The Heston (He) substrain with a wildtype agouti (A allele) coat color. Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project old group A list. Important to note for this eye expression dataset, C3H/HeJ is a Pdeb6 rd1 mutant with near total photoreceptor loss at as early as postnatal day 30. Also a Tlr4 mutant that is endotoxin resistant. (JAX Stock Number: 000659)
+ - C57BL/6J: Sequenced by NIH/NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list. Single most widely used inbred strain of mouse. (JAX Stock Number: 000664)
+ - C57BLKS/J: Black Kaliss strain (non-agouti a allele) derived from C57BL/6J, but genetically contaminated at some point mainly with DBA/2J and then reinbred. Now at the Jackson Laboratory. (JAX Stock Number: 000662)
+ - CAST/EiJ: A wild-derived inbred Mus musculus castaneus strain. Samples of this subspecies were captured in Southeast Asia. One of three wild-derived strains in the Collaborative Cross sequenced by NIEHS; Phenome Project A list. CAST/Ei and CAST/EiJ are the same strain. The addition of the "J" is trivial and was added when stock were transferred from Dr. Eicher's lab to the Jackson Laboratory production facility in about 2004. (JAX Stock Number: 000928)
+ - CBA/CaJ: Agouti strain from the Jackson Laboratory. Wildtype pigment genes. (JAX Stock Number: 000654)
+ - CZECHII/EiJ: Czech 2 is a wild-derived inbred strain M. musculus musculus strain. Samples of this subspecies were caught in the Czech Republic and inbred at the Jackson Laboratory by Eva Eicher. White-bellied agouti. (JAX Stock Number: 001144).
+ - DBA/2J: The dilute, brown, agouti (dba) strain is the oldest inbred strain of mouse. Inbreeding was started in 1909 by Little. A tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. A myosin 5a (Myo5a d) dilute allele mutant. Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project old A group list. (JAX Stock Number: 000671)
+ - FVB/NJ: Friend's leukemia virus B (FVB) strain. Sequenced by Perlegen/NIEHS and Celera. Tyr c locus albino and a Pdeb6 rd1 mutant derived from Swiss mice at NIH. This has been the most common strain used to make transgenic mice due to large and easily injected oocytes; Phenome Project A list (JAX Stock Number: 001800).
+ - KK/HlJ: K Kondo's (KK) Kasukabe strain is a homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. Males have a form of type 2 diabetes. Sequenced by Perlegen/NIEHS. (JAX Stock Number: 002106)
+ - LG/J: Large (LG) strain. Paternal parent of the Large-by-Small set of RI strains made by James Cheverud and colleagues (the LGXSM panel, not to be confused with the LongXShort or LXS panel). A Tyr c locus albino strain. (JAX Stock Number: 000675)
+ - LP/J: White-bellied agouit strain with a piebald mutation in the endothelin receptor type B Ednrb gene from at the Jackson Laboratory. Some reduction in melanocytes in choroid of eye due to neural creast migration abnormalities. (JAX Stock Number: 000676)
+ - MOLF/EiJ: A wild-derived inbred strain derived from M. musculus molossinus samples camputered in Fukuoka, Japan. This strain has the retinal degeneration rd1 allele in Pde6b. There appears to have been some genetic contamination of this strain with conventional inbred strains in the past several decades (F. Pardo, personal communication to RWW, August 2006). However, the strain is currently fully inbred. (JAX Stock Number: 000550)
+ - NOD/LtJ: Non-obese diabetic strain, originally from M. Hattori in Kyoto, Japan. This is the Edward Leiter (Lt) substrain from the Jackson Laboratory. Collaborative Cross strain sequenced by NIEHS; Phenome Project B list. Homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. (JAX Stock Number: 001976)
+ - NZO/HlLtJ: New Zealand Obese strain. This is a severely obese and hypertensive strain. Males often develop a type 2 diabetes. Collaborative Cross strain. Agouti coat color. (JAX Stock Number: 002105)
+ - NZB/BlNJ: New Zealand Black inbred strain from Bielschowsky (BL, substrain is "B lowercase L N", not "BiN") now maintained at the Jackson Laboratory. (JAX Stock Number: 000648)
+ - NZW/LacJ: New Zealand White strain from the Laboratory Animal Center (Carshalton, UK), now maintained at the Jackson Laboratory. Carries the Tyr c locus albino mutation, the pink-eye dilution mutation in the Oca2 or p locus, and the brown allele at Tyrp1. (JAX Stock Number: 001058)
+ - PANCEVO/EiJ: PANCEVO/EiJ is a wild-derived inbred strain from the Mus spicilegus samples caught in the Pancevo, Serbia. This species of mouse is also known as the Steppe mouse (taxon identifier 10103). M. spicilegus is a colonial mound-building species. No known ocular or retina mutations, but the expression level of Gnat2 is low in this strain, either due to a 3' UTR length variant or possible achromatosia (cone degeneration) (JAX Stock Number: 001384)
+ - PWD/PhJ: A wild-derived Mus musculus musculus agouti strain inbred from samples caught near Prague, Czech Republic. Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues. (JAX Stock Number: 004660)
+ - PWK/PhJ: A wild-derived Mus musculus musculus inbred strain from samples caught near Lhotka, Czech Republic. Collaborative Cross strain; Phenome Project D list. (JAX Stock Number: 003715)
+ - SJL/J: Swiss Webster inbred strain from Jim Lambert's lab at the Jackson Laboratory. This strain has the retinal degeneration rd1 allele in Pde6b. It also carries both the Tyr c albino mutation and the pink-eye dilution mutation in the Oca2 or p locus. Highly aggressive males. (JAX Stock Number: 000686)
+ - WSB/EiJ: Watkin Star line B (or "wild son-of-a-bitch") is a wild-derived Mus musculus domesticus inbred strain from samples caught in Maryland, USA. A Collaborative Cross strain sequenced by NIEHS; Phenome Project C list (JAX Stock Number: 001145)
+ - B6D2F1 and D2B6F1 (also listed as BDF1 and DBF1 in some graphs and tables): F1 hybrids generated by crossing C57BL/6J with DBA/2J. These black reciprocal F1 can be used to detect dominance effects. Comparison of the two reciprocal F1s can be used to detect parental origin (imprinting) effects. The D2B6F1 animals are currently available from the Jackson Laboratory as a special order.) (JAX Stock Number for B6D2F1 hybrids obtained from the Jackson Laboratory, aka B6D2F1/J 100006)
+
+
+Most of the common inbred strains harbor mutations in genes the control pigmentation (Silvers, 2008 and material above in this INFO file). These gene include the albino and chinchilla alleles of the tyrosinase gene (Tyr, or human OCA1), the brown allele of the tyrosinase related protein 1 (Tyrp1), the pink-eye dilution allele of Oca2 (probe set 1418211), the non-agouti (black) and white-bellied alleles of the agouti signaling protein Asip, the steel allele of Kitlg, the dilute allele of Myo5a (probe set 1419754), and the piebald allele of Ednrb. In some of these cases, effects of the mutation are easily detected at the transcript level (Tyrp1, Oca2, and Myo5a), but in the other cases (Tyr, Asip, Ednrb, and Kitlg), mutations do not leave a strong imprint on expression.
diff --git a/general/datasets/Eye_m2_0908_r_nd/citation.rtf b/general/datasets/Eye_m2_0908_r_nd/citation.rtf
new file mode 100644
index 0000000..ddd98e4
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nd/citation.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams. Gene expression landscape of the mammalian eye: A global survey and database of mRNAs of 103 varieties of mice. Molecular Vision 2009; in press.
diff --git a/general/datasets/Eye_m2_0908_r_nd/contributors.rtf b/general/datasets/Eye_m2_0908_r_nd/contributors.rtf
new file mode 100644
index 0000000..d155833
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nd/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams
diff --git a/general/datasets/Eye_m2_0908_r_nd/experiment-design.rtf b/general/datasets/Eye_m2_0908_r_nd/experiment-design.rtf
new file mode 100644
index 0000000..1ebe0ad
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nd/experiment-design.rtf
@@ -0,0 +1 @@
+Expression profiling by array
diff --git a/general/datasets/Eye_m2_0908_r_nd/notes.rtf b/general/datasets/Eye_m2_0908_r_nd/notes.rtf
new file mode 100644
index 0000000..7a26eb5
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nd/notes.rtf
@@ -0,0 +1 @@
+This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/Eye_m2_0908_r_nd/platform.rtf b/general/datasets/Eye_m2_0908_r_nd/platform.rtf
new file mode 100644
index 0000000..9024a99
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nd/platform.rtf
@@ -0,0 +1,11 @@
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many probes overlap and target the same transcript). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequences as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
+As part of the development of HEIMED, we have manually annotated individual probe sets by sequence alignment to the mouse genome and transcriptome. Approximately 13,000 probe sets that have comparatively high expression in eye and CNS were curated by one of the authors (RWW) and now have specific information on the part of the transcript targeted by each probe set. The other 33,000 transcripts have corresponding data that was generated by Xusheng Wang using computational methods (BLAT analysis combined with annotated genome sequence).
+
+One example may help explain how to exploit this annotation. The four probe sets for rhodopsin include information on the target location. Only the first probe set targets the last two coding exons. The other three probe sets target different parts of the 3’ UTR (mid, distal, and far distal regions). The probe sets can be reordered by from high to low expression using the Sort By function in Search Results pages. In the case of rhodopsin, the probe set that targets that last two coding exons and proximal parts of the 3’ UTR also has the highest expression . Finally, the HEIMED gene descriptions have been customized to help vision researchers. In the case of rhodopsin, the description appended after the gene name reads “rod photoreceptor pigment, retinitis pigmentosa-associated”. For less well known genes this kind of annotation can be extremely useful. For example, the more verbose annotation for Cerkl reads “neuronal survival and apoptosis-related, retinal ganglion cell expressed, retinitis pigmentosa 26); alternative 3' UTR of short form message, intron 2”.
+
+
+
+
+
+Legend: Distribution of expression values for all probe sets in HEIMED.
diff --git a/general/datasets/Eye_m2_0908_r_nd/processing.rtf b/general/datasets/Eye_m2_0908_r_nd/processing.rtf
new file mode 100644
index 0000000..4349e60
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nd/processing.rtf
@@ -0,0 +1,3381 @@
+Range of Gene Expression in the Eye. Expression of transcripts in the HEIMED and most other GN data sets is measured on a log2 scale. Each unit corresponding approximately to a 2-fold difference in hybridization signal intensity. To simplify comparisons among different data sets and cases, log2 RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units (variance stabilized). Values of all 45,101 probe sets in this data set range from a low of 4.8 (Tcf15, probe set 1420281_at) to a high of 15.5 (crystallin gamma C, Crygc, probe set 1422674_s_at). This corresponds to 10.7 units or a 1 to 1700 dynamic range of expression (2^10.73).
+
+We used pooled RNA samples of whole eyes, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+We calibrated this log intensity scale using Affymetrix spike-in control probe sets. These 18 control probe sets target exogenous bacterial mRNAs that are added to each sample (a graded dose spike cocktail) during preparation at concentrations of 1.5, 5, 25, and 100 pM. (To find these probe sets, search GN’s ALL search field using the string “AFFX pM”.) A value of 6 or less is equivalent to an mRNA concentration of under 0.4 pM, a value of 8 is equivalent to ~1.5 pM, 9.5 is equivalent to ~5 pM, 11.5 is equivalent to ~25 pM, 13.5 is equivalent to ~100 pM, and a value of 15.5 is equivalent to an mRNA concentration of 400 pM or greater.
+
+This range can be converted to the mRNA molecules per cell in the eye assuming that a value of 8 is equivalent to about 1 mRNA copy per cell (Kanno et al. 2006, see http://www.biomedcentral.com/1471-2164/7/64). Since the expression of rhodopsin mRNA is normally 15 units, we predict that there are 27 or ~128 Rho mRNAs per cell in the whole eye and ~256 in rods themselves (assuming that rods make up about half of all cells in the eye). For this purpose it may be useful to know that a normal mouse eye contains between 6 and 8 million rod photoreceptors (Guo, Lu, and Williams; GN BXD Phenotype ID 11024).
+
+Note that some probe sets with very low expression still provide reliable data. For example, probe set 1440397_at (Cacna2d1) has expression of only 5.5 units (a value that would be declared as "absent" using conventional Affymetrix procedures), but the values for this calcium channel transcript are associated with a very strong cis QTL with an LRS of 79 (LOD = 17). This strong linkage is definitely not due to chance since the probability of the expression data mapping precisely to the location of the parent gene itself is about 10e-16. This indicates a high signal to noise ratio and the detection of significant strain variation of the correct transcript.
+
+The standard error of the mean for the HEIMED data set is computed for 2 to 6 biological replicates. The standard error of such small samples tends to systematically underestimate the population standard error. With n = 2 the underestimate is about 25%, whereas for n = 6 the underestimate is 5%. Gurland and Tripathi (1971) provide a correction and equation for this effect (see Sokal and Rohlf, Biometry, 2nd ed., 1981, p 53 for an equation of the correction factor for small samples of n < 20.) Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. The CEL files were processed using the RMA protocol. We processed the first three batches together. The last batch was processed separately and merged as described below.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
+After RMA processing using Biobase affy10 build running under R version 2.7.1, all array data sets were rank-order normalized. This second round of quantile normalization removes much residual non-linearity across arrays and forces every array to have the same distribution of values as the mean of all arrays. Comparative array data quality was then evaluated in DataDesk. Outlier arrays were flagged by visual inspection in DataDesk, usually by means of an analysis of scatter plots and more quantitatively by generating a correlation matrix of all arrays. Those arrays with mean correlation <0.96 versus all other arrays indicates trouble or a biological outlier). In some cases, outliers were expected, such as samples from strains with retinal degeneration (FVB/NJ, NOD/LtJ, MOLF/EiJ, C3H/HeJ and BXD24), samples from wild subspecies such as WSB/EiJ, CAST/EiJ, PWD/PhJ, and PWK/PhJ, and knockouts. However, when arrays were anomolous both within strain and across strains, they were often simply discarded. The assumption is that anomolous data are much more likely due to experimental and technical errors than to informative biological variation. Approximately 10% of arrays were discarded.
+
+After this process, the acceptable set of arrays was renormalized using all step as above, starting with the original RMA procedure, etc.
+
+We reviewed the data set using a new method developed by RW Williams, Jeremy Peirce, and Hongqiang Li. For the full set of arrays that passed standard QC protocols described above, we computed the strain means for the BXD strains, B6, D2, and F1s. Using this set of strain means we then computed LRS scores for all 45101 probe sets and counted the number of transcripts that generated QTLs with LRS values greater than 50. This value (e.g., 1800) represented the QTL harvest for the full data set. We then dropped a single array from the data set, recomputed strain means, and recomputed the number of transcripts with LRS scores great than 50. This value is expected to typically reduce the number of QTLs that reach the criterion level (e.g., 1750 QTLs > 50). This process was repeated for every array to obtain an array-specific difference value--the effect of removing that array on the total QTL count. For example, the loss of a single array might cause a decrease in 50 QTLs. Values ranged from approximately -90 (good arrays) to +40 (bad arrays). This procedure is similar in some ways to a jackknife protocol, although we are not using this procedure to esimate an error term, but rather as a method to polish a data set.
+
+During this process we discovered that nearly 20 arrays in the batch 2 had been mislabeled at some point in processing. We computed the correct strain membership of each array using a large number of Mendelian probe sets (more than 50) and comparing their match to standard SNP and microsatellite markers and the original array data set of November 2005. This allowed us to rescue a large number of arrays that were of high quality.
+
+A third batch of approximately 40 arrays were processed by Yan Jiao and Weikuan Gu in August 2006. These complete data set assembled by Hongqiang Li. This process again included a correction for a batch effect.
+
+For the June 2006 data set Hongqiang Li used a new batch correction method that stabilizes the range of expression in each batch. For each of the three large batches, we extracted the minumum and maximum raw probe expression (CEL file level) value. We then adjusted raw probe values in each batch to have the same range as the first and largest batch (batch 1) using a simple linear interpolation. These procedures generated new correct CEL files which were then used with RMA to generate final probe set estimates.
+
+For the final fourth batch of arrays (Sept 2008) Arthur Centeno and Rob Williams corrected for a systematic difference in probe set expression values between original arrays run in 2005 and 2006 and the new arrays added in 2008 (n = 45 acceptable arrays). This difference is due to unknown technical batch effects that are probably associated with labeling, hybridization, and scanning. We performed a simple correction to normalize values of the new set of arrays to those of the old set (batches 1 through 3). No changes were made to any values of the previous three batches. We corrected only the probe set level (RMA) values and not the CEL files. For this final batch, we corrected for the difference (offset) in probe set expression between the first three batches arrays run in 2005 and 2006 (a total of 174 acceptable arrays) and the new batch (n = 47 acceptable arrays). This difference is due to unknown technical effects that are probably related to various steps in labeling, hybridization, and scanning. The correction was applied as follows: (1) RWW selected 51 high quality arrays with similar expression characteristics (r = 0.97 or better between pairs of arrays) in the old data set (from batches 1, 2, and 3) and 34 high quality arrays in the final batch. RWW used scatterplots of full RMA transcriptome data sets to review many pairs of arrays within these new and old array batches. Strains with retinal degeneration or unusual eye gene expression characteristics were excluded from these selected subsets. The average expression values for each probe set were then computed for both the old and new array subsets. The offset value (old minus new) was added to each probe set across all 47 new arrays. This processes forces the average probe set in the new arrays to be very close to that of the previous arrays.
+
+Table 2: Sample tube ID, strain, original CEL filename, and Affymetrix quality control values. Columns labeled Scale factor, Background Average, Present, Absent, Marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Strain |
+ Original CEL |
+ Scale factor |
+ Background Average |
+ Present |
+ Absent |
+ Marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ Batch Id |
+ Used for batch control |
+
+
+ | 1 |
+ R2595E.1 |
+ 129S1/SvImJ |
+ R2595E.1.CEL |
+ 1.79 |
+ 115 |
+ 61.00% |
+ 37.50% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 2 |
+ R2533E.1 |
+ 129S1/SvImJ |
+ R2533E.1.CEL |
+ 2.11 |
+ 94 |
+ 57.90% |
+ 40.50% |
+ 1.60% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 3 |
+ R0754E.1 |
+ A/J |
+ R0754E.1.CEL |
+ 2.72 |
+ 86 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.36 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 4 |
+ R4521E |
+ B6129P2F2N1-Clcn3 |
+ R4521E.CEL |
+ 4.83 |
+ 38.7 |
+ 63.30% |
+ 35.30% |
+ 1.40% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 5 |
+ R4522E |
+ B6129P2F2N1-Clcn3 |
+ R4522E.CEL |
+ 5.76 |
+ 37.36 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.37 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 6 |
+ R4523E |
+ B6129P2F2N1-Clcn3 |
+ R4523E.CEL |
+ 4.88 |
+ 40.42 |
+ 63.90% |
+ 34.70% |
+ 1.40% |
+ 1.27 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 7 |
+ R4526E |
+ B6129P2F2N1-Gabbr1 |
+ R4526E.CEL |
+ 3.84 |
+ 44.18 |
+ 65.00% |
+ 33.70% |
+ 1.30% |
+ 1.34 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 8 |
+ R4509E |
+ B6129P2F2N1-Gabbr1 |
+ R4509E.CEL |
+ 7.45 |
+ 34.76 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.45 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 9 |
+ R4510E |
+ B6129P2F2N1-Gabbr1 |
+ R4510E.CEL |
+ 8.44 |
+ 37.44 |
+ 57.40% |
+ 41.10% |
+ 1.50% |
+ 1.35 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 10 |
+ R4511E |
+ B6129P2F2N1-Gabbr1 |
+ R4511E.CEL |
+ 5.91 |
+ 42.02 |
+ 61.40% |
+ 37.20% |
+ 1.40% |
+ 1.41 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 11 |
+ R4524E |
+ B6129P2F2N1-Gabbr1 |
+ R4524E.CEL |
+ 5.49 |
+ 42.34 |
+ 62.40% |
+ 36.20% |
+ 1.40% |
+ 1.29 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 12 |
+ R4525E |
+ B6129P2F2N1-Gabbr1 |
+ R4525E.CEL |
+ 4.69 |
+ 41.3 |
+ 63.10% |
+ 35.50% |
+ 1.40% |
+ 1.27 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 13 |
+ R4515E |
+ B6129P2F2N1-Gabra1 |
+ R4515E.CEL |
+ 5.75 |
+ 41.76 |
+ 62.80% |
+ 35.80% |
+ 1.40% |
+ 1.41 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 14 |
+ R4516E |
+ B6129P2F2N1-Gabra1 |
+ R4516E.CEL |
+ 7.07 |
+ 40.73 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.32 |
+ 0.87 |
+ 4 |
+ Y |
+
+
+ | 15 |
+ R4517E |
+ B6129P2F2N1-Gabra1 |
+ R4517E.CEL |
+ 5.45 |
+ 38.09 |
+ 62.70% |
+ 35.80% |
+ 1.40% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 16 |
+ R4512E |
+ B6129P2F2N1-Gnb5 |
+ R4512E.CEL |
+ 6.56 |
+ 38.02 |
+ 59.90% |
+ 38.70% |
+ 1.50% |
+ 1.33 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 17 |
+ R4513E |
+ B6129P2F2N1-Gnb5 |
+ R4513E.CEL |
+ 4.15 |
+ 41.6 |
+ 63.40% |
+ 35.10% |
+ 1.50% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ |
+
+
+ | 18 |
+ R4514E |
+ B6129P2F2N1-Gnb5 |
+ R4514E.CEL |
+ 5.86 |
+ 39.2 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.34 |
+ 0.81 |
+ 4 |
+ |
+
+
+ | 19 |
+ R4518E |
+ B6129P2F2N1-Gpr19 |
+ R4518E.CEL |
+ 5.58 |
+ 38.9 |
+ 62.60% |
+ 36.00% |
+ 1.30% |
+ 1.39 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 20 |
+ R4519E |
+ B6129P2F2N1-Gpr19 |
+ R4519E.CEL |
+ 5.95 |
+ 41.91 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.35 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 21 |
+ R2601E.1 |
+ B6D2F1 |
+ R2601E.1.CEL |
+ 2.55 |
+ 92 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.44 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 22 |
+ R2602E.1 |
+ B6D2F1 |
+ R2602E.1.CEL |
+ 2.6 |
+ 84 |
+ 59.70% |
+ 38.80% |
+ 1.50% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 23 |
+ R1676E.1 |
+ BALB/cByJ |
+ R1676E.1.CEL |
+ 2.69 |
+ 98 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.46 |
+ 0.74 |
+ 1 |
+ |
+
+
+ | 24 |
+ R1672E.1 |
+ BALB/cByJ |
+ R1672E.1.CEL |
+ 2.22 |
+ 111 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 25 |
+ R4530E |
+ BALB/cJ |
+ R4530E.CEL |
+ 6.37 |
+ 37.53 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.3 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 26 |
+ R4529E |
+ BALB/cJ |
+ R4529E.CEL |
+ 5.71 |
+ 41.33 |
+ 60.50% |
+ 38.00% |
+ 1.50% |
+ 1.48 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD1 |
+ R2704E.2.CEL |
+ 2.066 |
+ 139.61 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD1 |
+ R2707E.3.CEL |
+ 1 |
+ 80 |
+ 56.40% |
+ 42.10% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 3 |
+ |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD2 |
+ R1231E.2.CEL |
+ 2.197 |
+ 138.73 |
+ 57.30% |
+ 41.30% |
+ 1.40% |
+ 1.41 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD2 |
+ R2598E.1.CEL |
+ 1.99 |
+ 106 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD5 |
+ R2591E.1.CEL |
+ 1.7 |
+ 136 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.33 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD5 |
+ R2714E.2.CEL |
+ 1.404 |
+ 144.35 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD6 |
+ R2570E.1.CEL |
+ 1.99 |
+ 87 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.46 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD6 |
+ R2694E.2.CEL |
+ 1.983 |
+ 97.23 |
+ 61.60% |
+ 37.10% |
+ 1.30% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD8 |
+ R2538E.1.CEL |
+ 1.91 |
+ 102 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.52 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD8 |
+ R2709E.2.CEL |
+ 1.99 |
+ 99.79 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.42 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD9 |
+ R2708E.2.CEL |
+ 1.966 |
+ 126.46 |
+ 57.70% |
+ 40.70% |
+ 1.50% |
+ 1.4 |
+ 0.84 |
+ 2 |
+ |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD9 |
+ R2569E.1.CEL |
+ 1.75 |
+ 87 |
+ 55.10% |
+ 43.40% |
+ 1.50% |
+ 2.82 |
+ 3.14 |
+ 1 |
+ |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD11 |
+ R2581E.1.CEL |
+ 1.94 |
+ 89 |
+ 62.10% |
+ 36.40% |
+ 1.60% |
+ 1.55 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD11 |
+ R2612E.2.CEL |
+ 1.83 |
+ 142.03 |
+ 58.20% |
+ 40.50% |
+ 1.40% |
+ 1.78 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD12 |
+ R2742E.2.CEL |
+ 2.127 |
+ 134.14 |
+ 57.00% |
+ 41.60% |
+ 1.40% |
+ 1.64 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD12 |
+ R2543E.1.CEL |
+ 1.61 |
+ 118 |
+ 58.60% |
+ 39.90% |
+ 1.60% |
+ 1.43 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD13 |
+ R2586E.1.CEL |
+ 2.01 |
+ 74 |
+ 56.40% |
+ 42.00% |
+ 1.60% |
+ 2.85 |
+ 3.81 |
+ 1 |
+ |
+
+
+ | 44 |
+ R877E.2 |
+ BXD13 |
+ R877E.2.CEL |
+ 1.558 |
+ 125.63 |
+ 61.20% |
+ 37.50% |
+ 1.20% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD14 |
+ R2557E.1.CEL |
+ 1.83 |
+ 99 |
+ 62.50% |
+ 36.10% |
+ 1.40% |
+ 1.31 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD14 |
+ R1128E.2.CEL |
+ 1.91 |
+ 115 |
+ 59.90% |
+ 38.80% |
+ 1.40% |
+ 1.2 |
+ 0.82 |
+ 1 |
+ Y |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD15 |
+ R2701E.3.CEL |
+ 1 |
+ 88 |
+ 60.60% |
+ 37.90% |
+ 1.40% |
+ 1.5 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD15 |
+ R2716E.2.CEL |
+ 2.015 |
+ 150.83 |
+ 56.40% |
+ 42.10% |
+ 1.60% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD16 |
+ R2711E.2.CEL |
+ 1.953 |
+ 118.53 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD16 |
+ R2567E.1.CEL |
+ 2.24 |
+ 82 |
+ 56.70% |
+ 41.60% |
+ 1.70% |
+ 1.37 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD18 |
+ R2720E.2.CEL |
+ 2.32 |
+ 99.93 |
+ 59.50% |
+ 39.00% |
+ 1.50% |
+ 1.33 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD18 |
+ R2559E.1.CEL |
+ 1.65 |
+ 104 |
+ 60.80% |
+ 37.70% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD19 |
+ R2560E.1.CEL |
+ 1.79 |
+ 98 |
+ 60.90% |
+ 37.50% |
+ 1.60% |
+ 1.35 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD19 |
+ R2713E.2.CEL |
+ 1.67 |
+ 120.82 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD20 |
+ R2584E.1.CEL |
+ 2.07 |
+ 84 |
+ 59.30% |
+ 39.10% |
+ 1.60% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD20 |
+ R2731E.2.CEL |
+ 1.825 |
+ 147 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.4 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD21 |
+ R2702E.2.CEL |
+ 1.811 |
+ 128.65 |
+ 59.40% |
+ 39.10% |
+ 1.40% |
+ 1.26 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD21 |
+ R2541E2.1.CEL |
+ 2.63 |
+ 125 |
+ 56.00% |
+ 42.40% |
+ 1.50% |
+ 1.29 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD22 |
+ R2553E.1.CEL |
+ 1.95 |
+ 111 |
+ 59.90% |
+ 38.50% |
+ 1.50% |
+ 1.28 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD22 |
+ R2700E.2.CEL |
+ 1.858 |
+ 102.96 |
+ 61.50% |
+ 37.10% |
+ 1.30% |
+ 1.48 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD23 |
+ R2558E-2.1.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD23 |
+ R1086E.2.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD24 |
+ R2719E.2.CEL |
+ 1.47 |
+ 140.38 |
+ 61.50% |
+ 37.20% |
+ 1.30% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD24 |
+ R2589E2.1.CEL |
+ 2.61 |
+ 112 |
+ 57.50% |
+ 40.90% |
+ 1.60% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD25 |
+ R2573E-2.1.CEL |
+ 3.15 |
+ 72 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.77 |
+ 0.97 |
+ 1 |
+ |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD25 |
+ R2683E.2.CEL |
+ 1.777 |
+ 115.64 |
+ 58.30% |
+ 40.30% |
+ 1.40% |
+ 2.01 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD27 |
+ R2703E.2.CEL |
+ 1.263 |
+ 134.78 |
+ 62.60% |
+ 36.10% |
+ 1.40% |
+ 1.44 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD27 |
+ R2729E.3.CEL |
+ 1 |
+ 87 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.56 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD28 |
+ R2562E.3.CEL |
+ 1.65 |
+ 116 |
+ 59.90% |
+ 38.40% |
+ 1.70% |
+ 1.37 |
+ 0.79 |
+ 3 |
+ Y |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD28 |
+ R2721E.2.CEL |
+ 2.065 |
+ 157.39 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD29 |
+ R2561E.3.CEL |
+ 1 |
+ 77 |
+ 53.30% |
+ 45.40% |
+ 1.40% |
+ 3.36 |
+ 19.66 |
+ 3 |
+ |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD31 |
+ R1258E.2.CEL |
+ 2.063 |
+ 117.09 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.54 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD31 |
+ R2597E.1.CEL |
+ 2.37 |
+ 94 |
+ 60.30% |
+ 38.30% |
+ 1.50% |
+ 1.34 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD32 |
+ R2563E.1.CEL |
+ 1.55 |
+ 102 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD32 |
+ R1216E.2.CEL |
+ 2.23 |
+ 111.99 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.35 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD33 |
+ R2542E.1.CEL |
+ 2.13 |
+ 97 |
+ 56.50% |
+ 41.80% |
+ 1.60% |
+ 1.91 |
+ 0.93 |
+ 1 |
+ |
+
+
+ | 77 |
+ R857E.2 |
+ BXD33 |
+ R857E.2.CEL |
+ 1.737 |
+ 113.98 |
+ 61.90% |
+ 36.70% |
+ 1.30% |
+ 1.6 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD34 |
+ R1451E.2.CEL |
+ 1.843 |
+ 140.05 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ Y |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD34 |
+ R2585E.1.CEL |
+ 2.64 |
+ 75 |
+ 58.30% |
+ 40.00% |
+ 1.70% |
+ 1.25 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD36 |
+ R2698E.3.CEL |
+ 1 |
+ 86 |
+ 59.70% |
+ 39.00% |
+ 1.30% |
+ 1.46 |
+ 0.78 |
+ 3 |
+ |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD36 |
+ R2705E.3.CEL |
+ 1 |
+ 86 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.46 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD38 |
+ R2710E.2.CEL |
+ 2.112 |
+ 122.1 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.37 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD38 |
+ R2532E.1.CEL |
+ 2.04 |
+ 94 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.37 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD39 |
+ R2574E.1.CEL |
+ 1.98 |
+ 91 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD39 |
+ R2695E.2.CEL |
+ 1.638 |
+ 122.7 |
+ 60.80% |
+ 37.80% |
+ 1.50% |
+ 1.42 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD40 |
+ R2699E.2.CEL |
+ 1.827 |
+ 105.23 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD40 |
+ R2590E.1.CEL |
+ 2.71 |
+ 77 |
+ 59.10% |
+ 39.30% |
+ 1.50% |
+ 1.4 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD42 |
+ R2696E.2.CEL |
+ 1.622 |
+ 118.95 |
+ 62.00% |
+ 36.60% |
+ 1.50% |
+ 1.53 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD42 |
+ R2596E.1.CEL |
+ 2.63 |
+ 108 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 90 |
+ R994E.2 |
+ BXD43 |
+ R994E.2.CEL |
+ 1.966 |
+ 113.12 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.66 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD43 |
+ R2607E.1.CEL |
+ 2.43 |
+ 115 |
+ 58.60% |
+ 40.00% |
+ 1.40% |
+ 1.31 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD44 |
+ R2594E.1.CEL |
+ 1.77 |
+ 117 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.35 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD44 |
+ R2610E.2.CEL |
+ 1.814 |
+ 142.91 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.35 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD45 |
+ R2732E.2.CEL |
+ 2.154 |
+ 122.45 |
+ 56.50% |
+ 42.10% |
+ 1.40% |
+ 1.8 |
+ 0.83 |
+ 2 |
+ |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD45 |
+ R2592E.1.CEL |
+ 1.85 |
+ 106 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.43 |
+ 0.85 |
+ 1 |
+ Y |
+
+
+ | 96 |
+ R967E.2 |
+ BXD48 |
+ R967E.2.CEL |
+ 1.948 |
+ 130.95 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.63 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD48 |
+ R2606E.1.CEL |
+ 2.56 |
+ 106 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.35 |
+ 0.83 |
+ 1 |
+ Y |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD50 |
+ R2933E.3.CEL |
+ 1 |
+ 72 |
+ 52.90% |
+ 45.60% |
+ 1.50% |
+ 2.45 |
+ 0.98 |
+ 3 |
+ |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD50 |
+ R2937E.3.CEL |
+ 1 |
+ 89 |
+ 56.90% |
+ 41.60% |
+ 1.40% |
+ 1.81 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD51 |
+ R2603E.1.CEL |
+ 2.49 |
+ 115 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD51 |
+ R1042E.2.CEL |
+ 2.352 |
+ 104.12 |
+ 58.70% |
+ 39.90% |
+ 1.40% |
+ 1.53 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD55 |
+ R2980E.3.CEL |
+ 1 |
+ 82 |
+ 56.90% |
+ 41.70% |
+ 1.50% |
+ 1.77 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD55 |
+ R2690E.2.CEL |
+ 1.887 |
+ 164.01 |
+ 56.10% |
+ 42.30% |
+ 1.60% |
+ 1.43 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 104 |
+ R4176E |
+ BXD56 |
+ R4176E.CEL |
+ 4.75 |
+ 43.08 |
+ 63.00% |
+ 35.60% |
+ 1.30% |
+ 1.39 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 105 |
+ R4175E |
+ BXD56 |
+ R4175E.CEL |
+ 6 |
+ 38.49 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.47 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD60 |
+ R1006E.3.CEL |
+ 1 |
+ 98 |
+ 54.90% |
+ 43.70% |
+ 1.50% |
+ 2.7 |
+ 0.86 |
+ 3 |
+ |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD60 |
+ R2725E.2.CEL |
+ 1.551 |
+ 148.01 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD60 |
+ R1074E.3.CEL |
+ 1 |
+ 118 |
+ 55.50% |
+ 43.10% |
+ 1.40% |
+ 1.96 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD61 |
+ R2534E2.1.CEL |
+ 2.47 |
+ 118 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.42 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD61 |
+ R2684E.2.CEL |
+ 2.01 |
+ 131.03 |
+ 57.00% |
+ 41.50% |
+ 1.50% |
+ 1.34 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD62 |
+ R1107E.3.CEL |
+ 1 |
+ 83 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.43 |
+ 0.93 |
+ 3 |
+ |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD62 |
+ R2681E.2.CEL |
+ 2.086 |
+ 148.24 |
+ 57.20% |
+ 41.30% |
+ 1.50% |
+ 1.29 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 113 |
+ R965E.3 |
+ BXD62 |
+ R965E.3.CEL |
+ 1 |
+ 93.55 |
+ 53.30% |
+ 45.20% |
+ 1.50% |
+ 3.11 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD63 |
+ R1425E.2.CEL |
+ 1.7 |
+ 136 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.43 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD63 |
+ R2576E.3.CEL |
+ 1 |
+ 84 |
+ 61.30% |
+ 37.40% |
+ 1.40% |
+ 1.48 |
+ 0.76 |
+ 3 |
+ |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD64 |
+ R943E-2.2.CEL |
+ 1.591 |
+ 141.34 |
+ 60.10% |
+ 38.40% |
+ 1.50% |
+ 1.32 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD64 |
+ R2611E.1.CEL |
+ 2.29 |
+ 92 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 1.57 |
+ 1.06 |
+ 1 |
+ |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD65 |
+ R2689E.2.CEL |
+ 1.721 |
+ 142.44 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.38 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD65 |
+ R2583E.1.CEL |
+ 2.49 |
+ 70 |
+ 56.90% |
+ 41.50% |
+ 1.60% |
+ 1.67 |
+ 1.01 |
+ 1 |
+ |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD66 |
+ R2728E.2.CEL |
+ 1.714 |
+ 137.45 |
+ 59.40% |
+ 39.00% |
+ 1.60% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD66 |
+ R2536E2.1.CEL |
+ 2.74 |
+ 109 |
+ 56.10% |
+ 42.30% |
+ 1.70% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD66 |
+ R1207E.2.CEL |
+ 1.681 |
+ 136.86 |
+ 60.40% |
+ 38.10% |
+ 1.50% |
+ 1.45 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD67 |
+ R1192E.2.CEL |
+ 2.126 |
+ 123.37 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD67 |
+ R2727E.3.CEL |
+ 1 |
+ 82.55 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.97 |
+ 0.87 |
+ 2 |
+ |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD67 |
+ R2691E.3.CEL |
+ 1 |
+ 90 |
+ 54.80% |
+ 43.80% |
+ 1.50% |
+ 2.61 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD68 |
+ R2551E.1.CEL |
+ 2.49 |
+ 92 |
+ 54.30% |
+ 44.10% |
+ 1.60% |
+ 2.91 |
+ 1.55 |
+ 1 |
+ |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD68 |
+ R2726E.2.CEL |
+ 1.811 |
+ 153.09 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD69 |
+ R2593E.1.CEL |
+ 1.67 |
+ 128 |
+ 59.20% |
+ 39.50% |
+ 1.30% |
+ 1.47 |
+ 0.92 |
+ 1 |
+ Y |
+
+
+ | 129 |
+ R975E.2 |
+ BXD70 |
+ R975E.2.CEL |
+ 1.841 |
+ 137.97 |
+ 58.00% |
+ 40.50% |
+ 1.40% |
+ 1.36 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD70 |
+ R2537E2.1.CEL |
+ 2.93 |
+ 99 |
+ 58.00% |
+ 40.50% |
+ 1.60% |
+ 1.29 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 131 |
+ R4531E |
+ BXD71 |
+ R4531E.CEL |
+ 4.77 |
+ 43.48 |
+ 62.40% |
+ 36.30% |
+ 1.40% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 132 |
+ R4532E |
+ BXD71 |
+ R4532E.CEL |
+ 5.89 |
+ 40.68 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD73 |
+ R2779E.2.CEL |
+ 1.746 |
+ 121.11 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD73 |
+ R3024E.3.CEL |
+ 1 |
+ 78.05 |
+ 51.70% |
+ 46.60% |
+ 1.70% |
+ 2.3 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD75 |
+ R2565E.1.CEL |
+ 1.79 |
+ 102 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 2.31 |
+ 3.47 |
+ 1 |
+ |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD75 |
+ R1397E-re.2.CEL |
+ 1.449 |
+ 189.71 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD77 |
+ R2687E.3.CEL |
+ 1 |
+ 80 |
+ 58.00% |
+ 40.60% |
+ 1.40% |
+ 1.57 |
+ 0.8 |
+ 3 |
+ Y |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD77 |
+ R2717E.2.CEL |
+ 1.797 |
+ 84.43 |
+ 61.60% |
+ 36.90% |
+ 1.40% |
+ 1.49 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD77 |
+ R1421E.3.CEL |
+ 1 |
+ 94 |
+ 52.40% |
+ 46.20% |
+ 1.40% |
+ 2.29 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD80 |
+ R2579E.1.CEL |
+ 2.42 |
+ 72 |
+ 59.20% |
+ 39.40% |
+ 1.50% |
+ 1.73 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD80 |
+ R2686E.2.CEL |
+ 2.342 |
+ 119.63 |
+ 56.00% |
+ 42.60% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD83 |
+ R2956E.3.CEL |
+ 1 |
+ 84 |
+ 55.40% |
+ 43.20% |
+ 1.40% |
+ 1.39 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD83 |
+ R2960E.3.CEL |
+ 1 |
+ 80 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.5 |
+ 0.82 |
+ 3 |
+ Y |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD84 |
+ R2922E.3.CEL |
+ 1 |
+ 91 |
+ 57.80% |
+ 40.80% |
+ 1.50% |
+ 1.47 |
+ 0.83 |
+ 3 |
+ Y |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD84 |
+ R2895E.3.CEL |
+ 1 |
+ 75 |
+ 58.30% |
+ 40.20% |
+ 1.50% |
+ 1.56 |
+ 0.77 |
+ 3 |
+ Y |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD85 |
+ R2692E.2.CEL |
+ 1.423 |
+ 160.87 |
+ 60.20% |
+ 38.30% |
+ 1.40% |
+ 1.46 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD85 |
+ R2715E.2.CEL |
+ 1.488 |
+ 142.6 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.5 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD86 |
+ R1405E.2.CEL |
+ 2.351 |
+ 119.34 |
+ 56.40% |
+ 42.20% |
+ 1.40% |
+ 1.64 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD86 |
+ R1225E.3.CEL |
+ 1 |
+ 71 |
+ 53.90% |
+ 44.60% |
+ 1.40% |
+ 3.2 |
+ 1.61 |
+ 3 |
+ |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD87 |
+ R2724E.2.CEL |
+ 1.906 |
+ 113.71 |
+ 60.70% |
+ 37.90% |
+ 1.40% |
+ 1.45 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD87 |
+ R2540E.1.CEL |
+ 2.33 |
+ 93 |
+ 61.10% |
+ 37.40% |
+ 1.40% |
+ 1.22 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD89 |
+ R1433E.2.CEL |
+ 1 |
+ 2.241 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.41 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD89 |
+ R2546E.1.CEL |
+ 1.99 |
+ 96 |
+ 58.60% |
+ 39.70% |
+ 1.70% |
+ 1.47 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD90 |
+ R2578E2.1.CEL |
+ 2.79 |
+ 92 |
+ 58.60% |
+ 39.80% |
+ 1.60% |
+ 1.52 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 155 |
+ R859E.2 |
+ BXD90 |
+ R859E.2.CEL |
+ 1.847 |
+ 152.22 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.36 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD92 |
+ R2682E.2.CEL |
+ 1.547 |
+ 156.31 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.37 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD92 |
+ R1388E.3.CEL |
+ 1 |
+ 63 |
+ 60.00% |
+ 38.60% |
+ 1.40% |
+ 1.85 |
+ 1.03 |
+ 3 |
+ |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD92 |
+ R1322E.3.CEL |
+ 1 |
+ 80 |
+ 55.90% |
+ 42.60% |
+ 1.50% |
+ 1.75 |
+ 0.74 |
+ 3 |
+ |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD96 |
+ R2733E.2.CEL |
+ 1.7 |
+ 113.99 |
+ 62.10% |
+ 36.60% |
+ 1.30% |
+ 1.4 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD96 |
+ R2554E.1.CEL |
+ 2.18 |
+ 93 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD97 |
+ R2649E.2.CEL |
+ 2.343 |
+ 119.04 |
+ 57.50% |
+ 41.20% |
+ 1.40% |
+ 1.53 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD97 |
+ R2577E.1.CEL |
+ 2.07 |
+ 77 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.87 |
+ 1.29 |
+ 1 |
+ |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD98 |
+ R2645E.3.CEL |
+ 1 |
+ 88 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.59 |
+ 0.81 |
+ 3 |
+ Y |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD98 |
+ R2688E.2.CEL |
+ 1.772 |
+ 145.24 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.48 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 165 |
+ R4533E |
+ BXD99 |
+ R4533E.CEL |
+ 1 |
+ 37.69 |
+ 60.30% |
+ 38.20% |
+ 1.40% |
+ 1.33 |
+ 0.89 |
+ 4 |
+ Y |
+
+
+ | 166 |
+ R4534E |
+ BXD99 |
+ R4534E.CEL |
+ 5.69 |
+ 36.62 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.16 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 167 |
+ R2885E.3 |
+ BXSB/MpJ |
+ R2885E.3.CEL |
+ 1 |
+ 76 |
+ 58.10% |
+ 40.60% |
+ 1.30% |
+ 1.88 |
+ 1.06 |
+ 3 |
+ |
+
+
+ | 168 |
+ R2883E.3 |
+ BXSB/MpJ |
+ R2883E.3.CEL |
+ 1 |
+ 71 |
+ 56.40% |
+ 42.00% |
+ 1.50% |
+ 1.59 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 169 |
+ R1700E.1 |
+ C3H/HeJ |
+ R1700E.1.CEL |
+ 2.98 |
+ 69 |
+ 60.80% |
+ 37.90% |
+ 1.40% |
+ 1.48 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 170 |
+ R1704E.1 |
+ C3H/HeJ |
+ R1704E.1.CEL |
+ 2.58 |
+ 88 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.38 |
+ 0.84 |
+ 1 |
+ |
+
+
+ | 171 |
+ R2605E.1 |
+ C57BL/6J |
+ R2605E.1.CEL |
+ 1.82 |
+ 131 |
+ 60.50% |
+ 38.20% |
+ 1.30% |
+ 1.32 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 172 |
+ R0871E |
+ C57BL/6J |
+ R0871E.CEL |
+ 6.24 |
+ 37.38 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.41 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 173 |
+ R0872E.1 |
+ C57BL/6J |
+ R0872E.1.CEL |
+ 3.13 |
+ 89 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 174 |
+ R0872E |
+ C57BL/6J |
+ R0872E.CEL |
+ 3.128 |
+ 88.58 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 175 |
+ R4507E |
+ C57BL/6J-Nyx |
+ R4507E.CEL |
+ 8.13 |
+ 37.5 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.32 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 176 |
+ R4508E |
+ C57BL/6J-Nyx |
+ R4508E.CEL |
+ 6.33 |
+ 37.26 |
+ 60.90% |
+ 37.80% |
+ 1.30% |
+ 1.24 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 177 |
+ R4505E |
+ C57BL/6J-Rpe65 |
+ R4505E.CEL |
+ 5.98 |
+ 37.48 |
+ 61.80% |
+ 36.80% |
+ 1.40% |
+ 1.45 |
+ 0.85 |
+ 4 |
+ Y |
+
+
+ | 178 |
+ R4506E |
+ C57BL/6J-Rpe65 |
+ R4506E.CEL |
+ 6.94 |
+ 37.9 |
+ 61.10% |
+ 37.50% |
+ 1.30% |
+ 1.5 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 179 |
+ R4535E |
+ C57BLKS/J |
+ R4535E.CEL |
+ 6.59 |
+ 37.28 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.26 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 180 |
+ R4536E |
+ C57BLKS/J |
+ R4536E.CEL |
+ 1 |
+ 40.71 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 181 |
+ R2564E.1 |
+ CAST/EiJ |
+ R2564E.1.CEL |
+ 1.94 |
+ 89 |
+ 58.50% |
+ 39.90% |
+ 1.60% |
+ 1.6 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 182 |
+ R2580E.1 |
+ CAST/EiJ |
+ R2580E.1.CEL |
+ 2.09 |
+ 95 |
+ 58.20% |
+ 40.10% |
+ 1.70% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ |
+
+
+ | 183 |
+ R4537E |
+ CBA/CaJ |
+ R4537E.CEL |
+ 1 |
+ 38.45 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.63 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 184 |
+ R4538E |
+ CBA/CaJ |
+ R4538E.CEL |
+ 5.89 |
+ 39.18 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.45 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 185 |
+ R4539E |
+ CZECHII/EiJ |
+ R4539E.CEL |
+ 7.73 |
+ 37.1 |
+ 58.30% |
+ 40.10% |
+ 1.50% |
+ 1.7 |
+ 0.95 |
+ 4 |
+ Y |
+
+
+ | 186 |
+ R4540E |
+ CZECHII/EiJ |
+ R4540E.CEL |
+ 11.04 |
+ 36.69 |
+ 53.00% |
+ 45.30% |
+ 1.70% |
+ 1.83 |
+ 1.32 |
+ 4 |
+ |
+
+
+ | 187 |
+ R2600E.1 |
+ D2B6F1 |
+ R2600E.1.CEL |
+ 2.47 |
+ 95 |
+ 58.10% |
+ 40.20% |
+ 1.70% |
+ 1.41 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 188 |
+ R2604E.1 |
+ D2B6F1 |
+ R2604E.1.CEL |
+ 2.66 |
+ 90 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 189 |
+ R1002E.3 |
+ DBA/2J |
+ R1002E.3.CEL |
+ 1 |
+ 102 |
+ 54.80% |
+ 43.70% |
+ 1.50% |
+ 2.84 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 190 |
+ R4541E |
+ DBA/2J |
+ R4541E.CEL |
+ 1 |
+ 43.4 |
+ 61.40% |
+ 37.00% |
+ 1.50% |
+ 1.37 |
+ 0.73 |
+ 4 |
+ Y |
+
+
+ | 191 |
+ R959E.3 |
+ DBA/2J |
+ R959E.3.CEL |
+ 1 |
+ 89.97 |
+ 53.20% |
+ 45.30% |
+ 1.50% |
+ 3.66 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 192 |
+ R2572E.1 |
+ DBA/2J |
+ R2572E.1.CEL |
+ 2.41 |
+ 79 |
+ 55.50% |
+ 42.90% |
+ 1.60% |
+ 1.37 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 193 |
+ R4542E |
+ DBA/2J |
+ R4542E.CEL |
+ 5.7 |
+ 39.95 |
+ 61.00% |
+ 37.40% |
+ 1.50% |
+ 1.23 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 194 |
+ R2771E.3 |
+ FVB/NJ |
+ R2771E.3.CEL |
+ 1 |
+ 70 |
+ 55.30% |
+ 43.20% |
+ 1.50% |
+ 1.69 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 195 |
+ R2772E.3 |
+ FVB/NJ |
+ R2772E.3.CEL |
+ 1 |
+ 76 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.13 |
+ 1.02 |
+ 3 |
+ |
+
+
+ | 196 |
+ R2636E.1 |
+ KK/HlJ |
+ R2636E.1.CEL |
+ 2.61 |
+ 93 |
+ 58.90% |
+ 39.50% |
+ 1.50% |
+ 1.39 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 197 |
+ R2637E.1 |
+ KK/HlJ |
+ R2637E.1.CEL |
+ 2.19 |
+ 103 |
+ 59.40% |
+ 39.00% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 198 |
+ R0999E.1 |
+ LG/J |
+ R0999E.1.CEL |
+ 2.45 |
+ 82 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 199 |
+ R1004E.1 |
+ LG/J |
+ R1004E.1.CEL |
+ 2.44 |
+ 92 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 200 |
+ R4543E |
+ LP/J |
+ R4543E.CEL |
+ 6.57 |
+ 41.99 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.28 |
+ 0.75 |
+ 4 |
+ Y |
+
+
+ | 201 |
+ R4544E |
+ LP/J |
+ R4544E.CEL |
+ 4.56 |
+ 39.9 |
+ 62.40% |
+ 36.10% |
+ 1.50% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 202 |
+ R2858E.3 |
+ MOLF/EiJ |
+ R2858E.3.CEL |
+ 1 |
+ 64 |
+ 53.80% |
+ 44.70% |
+ 1.50% |
+ 1.59 |
+ 0.95 |
+ 3 |
+ |
+
+
+ | 203 |
+ R2919.3 |
+ MOLF/EiJ |
+ R2919.3.CEL |
+ 1 |
+ 64 |
+ 52.40% |
+ 46.00% |
+ 1.60% |
+ 2.15 |
+ 1.07 |
+ 3 |
+ |
+
+
+ | 204 |
+ R1688E.1 |
+ NOD/LtJ |
+ R1688E.1.CEL |
+ 2.66 |
+ 98 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 205 |
+ R2566E-2.1 |
+ NOD/LtJ |
+ R2566E-2.1.CEL |
+ 3.03 |
+ 69 |
+ 59.80% |
+ 38.80% |
+ 1.50% |
+ 1.38 |
+ 0.75 |
+ 1 |
+ Y |
+
+
+ | 206 |
+ R4545E |
+ NZB/BlNJ |
+ R4545E.CEL |
+ 4.23 |
+ 43.48 |
+ 62.10% |
+ 36.40% |
+ 1.50% |
+ 1.33 |
+ 0.76 |
+ 4 |
+ Y |
+
+
+ | 207 |
+ R4546E |
+ NZB/BlNJ |
+ R4546E.CEL |
+ 6.27 |
+ 44.22 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.17 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 208 |
+ R2535E.1 |
+ NZO/HlLtJ |
+ R2535E.1.CEL |
+ 1.89 |
+ 86 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.41 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 209 |
+ R2550E.1 |
+ NZO/HlLtJ |
+ R2550E.1.CEL |
+ 1.79 |
+ 87 |
+ 60.70% |
+ 37.80% |
+ 1.50% |
+ 1.52 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 210 |
+ R2817E.3 |
+ NZW/LacJ |
+ R2817E.3.CEL |
+ 1 |
+ 59 |
+ 50.90% |
+ 47.60% |
+ 1.50% |
+ 3.59 |
+ 1.48 |
+ 3 |
+ |
+
+
+ | 211 |
+ R2810E |
+ NZW/LacJ |
+ R2810E.CEL |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ 3 |
+ |
+
+
+ | 212 |
+ R2810E.3 |
+ NZW/LacJ |
+ R2810E.3.CEL |
+ 1 |
+ 74 |
+ 57.00% |
+ 41.70% |
+ 1.40% |
+ 2.15 |
+ 1.03 |
+ 4 |
+ Y |
+
+
+ | 213 |
+ R4547E |
+ PANCEVO/EiJ |
+ R4547E.CEL |
+ 5.27 |
+ 51.34 |
+ 57.20% |
+ 41.10% |
+ 1.70% |
+ 1.7 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 214 |
+ R4548E |
+ PANCEVO/EiJ |
+ R4548E.CEL |
+ 10.54 |
+ 37.39 |
+ 50.30% |
+ 48.00% |
+ 1.70% |
+ 1.68 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 215 |
+ R2635E.1 |
+ PWD/PhJ |
+ R2635E.1.CEL |
+ 3.72 |
+ 80 |
+ 54.20% |
+ 44.10% |
+ 1.70% |
+ 1.53 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 216 |
+ R2634E.1 |
+ PWD/PhJ |
+ R2634E.1.CEL |
+ 3.29 |
+ 90 |
+ 55.90% |
+ 42.50% |
+ 1.60% |
+ 1.57 |
+ 0.81 |
+ 1 |
+ |
+
+
+ | 217 |
+ R2544E.1 |
+ PWK/PhJ |
+ R2544E.1.CEL |
+ 2.2 |
+ 108 |
+ 54.90% |
+ 43.50% |
+ 1.70% |
+ 1.36 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 218 |
+ R2549E.1 |
+ PWK/PhJ |
+ R2549E.1.CEL |
+ 2.28 |
+ 84 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.57 |
+ 0.83 |
+ 1 |
+ |
+
+
+ | 219 |
+ R4550E |
+ SJL/J |
+ R4550E.CEL |
+ 5.35 |
+ 40.44 |
+ 62.30% |
+ 36.20% |
+ 1.40% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ |
+
+
+ | 220 |
+ R2368E.1 |
+ WSB/EiJ |
+ R2368E.1.CEL |
+ 2.57 |
+ 86 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.29 |
+ 0.74 |
+ 1 |
+ Y |
+
+
+ | 221 |
+ R2547E.1 |
+ WSB/EiJ |
+ R2547E.1.CEL |
+ 2.14 |
+ 90 |
+ 58.20% |
+ 40.10% |
+ 1.60% |
+ 1.32 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0908_r_nd/summary.rtf b/general/datasets/Eye_m2_0908_r_nd/summary.rtf
new file mode 100644
index 0000000..44b7e23
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nd/summary.rtf
@@ -0,0 +1,12 @@
+FINAL RECOMMENDED EYE DATA SET. The HEIMED September 2008 RMA data release provides estimates of gene expression in whole eyes of 103 lines of young adult mice generated using 221 Affymetrix M430 2.0 arrays. This data set is intended for exploration of the genetics and genomics of the mouse eye, retina, lens, retinal pigment epithelium, cornea, iris and choroid. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). We used pooled RNA samples, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+Users of these mouse eye data may also find the following complementary resources extremely useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
diff --git a/general/datasets/Eye_m2_0908_r_nd/tissue.rtf b/general/datasets/Eye_m2_0908_r_nd/tissue.rtf
new file mode 100644
index 0000000..9b6ee0f
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_nd/tissue.rtf
@@ -0,0 +1,2058 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of cRNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. All samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center led by Dr. Weikuan Gu. All arrays were processed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. C until use (roughly one third) or were used immediately for hybridization.
+
+Dealing with ocular pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations taken from brown and beige colored mice tend to have faint residual pigmentation that affects hybridization signal. To address this problem, Dr. Yan Jiao purified total RNA using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204) all four batches.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well balanced sample of males and females, in general without within-strain-by-sex replication. Two strains are represented by a single male sample pool (BXD29 and A/J). Four lines are represented by two or three male sample pools (all of the five DeltaGen KO line). The SJL/J may be a single mixed sex sample. Users can study possible sex effects by comparing any results of expression data to that of a surrogate measurement that summarizes the overall sex balance of HEIMED. To do this just compare your data to those of probe sets 1427262_at (Xist, high in females) and probe set 1426438_at (Ddx3y, high in males). These two sex-specific probes are quantitative surrogates for the sex balance in this data set.
+
+Technical duplicates: One sample, highlighted in the tables below, is a technical duplicate. The pair of technical duplicates were both of high quality. For statistical analysis, they should be combined and treated as single biological sample.
+
+Batch structure: This data set consists of four batches (Table 2, far right column). The final September 2008 data set consists of a total of 221 arrays and 220 independent samples.
+
+
+ - Batch 1: November 2005, n = 78 arrays original arrays of which 76 were accepted into this final data set.
+ - Batch 2: January 2006, n = 62 arrays of which 62 were accepted.
+ - Batch 3: August 2006, n = 39 arrays of which 36 were accepted. (These three batches, including some arrays that were eventually dropped from the final 2008 data set, were combined to form the September 2006 data set.)
+ - Batch 4: Summer 2008, n = 53 arrays of which 47 were accepted.
+
+
+Table 1: HEIMED case IDs, including sample tube ID, strain, age, sex, and source of mice (see Table 2 for information on array quality control)
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Group |
+ Strain |
+ Age |
+ Sex |
+ Source |
+
+
+ | 1 |
+ R2595E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 2 |
+ R2533E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 3 |
+ R0754E.1 |
+ GDP |
+ A/J |
+ 60 |
+ M |
+ JAX |
+
+
+ | 4 |
+ R4521E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 5 |
+ R4522E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 6 |
+ R4523E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 7 |
+ R4526E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 8 |
+ R4509E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 9 |
+ R4510E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 10 |
+ R4511E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 20 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 11 |
+ R4524E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 12 |
+ R4525E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 13 |
+ R4515E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 14 |
+ R4516E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 15 |
+ R4517E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 16 |
+ R4512E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 17 |
+ R4513E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 25 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 18 |
+ R4514E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 19 |
+ R4518E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 70 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 20 |
+ R4519E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 68 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 21 |
+ R2601E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 22 |
+ R2602E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 23 |
+ R1676E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ F |
+ JAX |
+
+
+ | 24 |
+ R1672E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 25 |
+ R4530E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 26 |
+ R4529E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD |
+ BXD1 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD |
+ BXD1 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD |
+ BXD2 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD |
+ BXD2 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD |
+ BXD5 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD |
+ BXD5 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD |
+ BXD6 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD |
+ BXD6 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD |
+ BXD8 |
+ 77 |
+ F |
+ UTHSC RW |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD |
+ BXD8 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD |
+ BXD9 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD |
+ BXD9 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD |
+ BXD11 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD |
+ BXD11 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD |
+ BXD12 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD |
+ BXD12 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD |
+ BXD13 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 44 |
+ R877E.2 |
+ BXD |
+ BXD13 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD |
+ BXD14 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD |
+ BXD14 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD |
+ BXD15 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD |
+ BXD15 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD |
+ BXD16 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD |
+ BXD16 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD |
+ BXD18 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD |
+ BXD18 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD |
+ BXD19 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD |
+ BXD19 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD |
+ BXD20 |
+ 59 |
+ F |
+ BIDMC GR |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD |
+ BXD20 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD |
+ BXD21 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD |
+ BXD21 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD |
+ BXD22 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD |
+ BXD22 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD |
+ BXD23 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD |
+ BXD23 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD |
+ BXD24 |
+ 123 |
+ F |
+ UTHSC RW |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD |
+ BXD24 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD |
+ BXD25 |
+ 67 |
+ F |
+ UAB |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD |
+ BXD25 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD |
+ BXD27 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD |
+ BXD27 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD |
+ BXD28 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD |
+ BXD28 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD |
+ BXD29 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD |
+ BXD31 |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD |
+ BXD31 |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD |
+ BXD32 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD |
+ BXD32 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD |
+ BXD33 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 77 |
+ R857E.2 |
+ BXD |
+ BXD33 |
+ 77 |
+ M |
+ UTHSC RW |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD |
+ BXD34 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD |
+ BXD34 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD |
+ BXD36 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD |
+ BXD36 |
+ 57 |
+ M |
+ BIDMC GR |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD |
+ BXD38 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD |
+ BXD38 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD |
+ BXD39 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD |
+ BXD39 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD |
+ BXD40 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD |
+ BXD40 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD |
+ BXD42 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD |
+ BXD42 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 90 |
+ R994E.2 |
+ BXD |
+ BXD43 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD |
+ BXD43 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD |
+ BXD44 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD |
+ BXD44 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD |
+ BXD45 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD |
+ BXD45 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 96 |
+ R967E.2 |
+ BXD |
+ BXD48 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD |
+ BXD48 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD |
+ BXD51 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD |
+ BXD51 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD |
+ BXD55 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD |
+ BXD55 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 104 |
+ R4176E |
+ BXD |
+ BXD56 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 105 |
+ R4175E |
+ BXD |
+ BXD56 |
+ 53 |
+ M |
+ UTHSC RW |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD |
+ BXD60 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD |
+ BXD60 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD |
+ BXD60 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD |
+ BXD61 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD |
+ BXD61 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ F |
+ UTHSC RW |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD |
+ BXD62 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 113 |
+ R965E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD |
+ BXD63 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD |
+ BXD63 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD |
+ BXD64 |
+ 56 |
+ F |
+ UTHSC RW |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD |
+ BXD64 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD |
+ BXD65 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD |
+ BXD65 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD |
+ BXD66 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD |
+ BXD66 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD |
+ BXD66 |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD |
+ BXD67 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD |
+ BXD68 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD |
+ BXD69 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 129 |
+ R975E.2 |
+ BXD |
+ BXD70 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD |
+ BXD70 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 131 |
+ R4531E |
+ BXD |
+ BXD71 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 132 |
+ R4532E |
+ BXD |
+ BXD71 |
+ 86 |
+ M |
+ UTHSC RW |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD |
+ BXD73 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD |
+ BXD73 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD |
+ BXD75 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD |
+ BXD75 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD |
+ BXD77 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD |
+ BXD77 |
+ 107 |
+ M |
+ UTHSC RW |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD |
+ BXD77 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD |
+ BXD80 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD |
+ BXD80 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD |
+ BXD84 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD |
+ BXD84 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD |
+ BXD85 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD |
+ BXD85 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD |
+ BXD86 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD |
+ BXD86 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD |
+ BXD87 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD |
+ BXD87 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD |
+ BXD89 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD |
+ BXD89 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD |
+ BXD90 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 155 |
+ R859E.2 |
+ BXD |
+ BXD90 |
+ 72 |
+ M |
+ UTHSC RW |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD |
+ BXD92 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD |
+ BXD92 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD |
+ BXD92 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD |
+ BXD96 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD |
+ BXD96 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD |
+ BXD97 |
+ 74 |
+ F |
+ UTHSC RW |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD |
+ BXD97 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD |
+ BXD98 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD |
+ BXD98 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 165 |
+ R4533E |
+ BXD |
+ BXD99 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 166 |
+ R4534E |
+ BXD |
+ BXD99 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 167 |
+ R2885E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 168 |
+ R2883E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 169 |
+ R1700E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 170 |
+ R1704E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 171 |
+ R2605E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 79 |
+ F |
+ UTHSC RW |
+
+
+ | 172 |
+ R0871E |
+ GDP BXD |
+ C57BL/6J |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 173 |
+ R0872E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 174 |
+ R0872E |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 175 |
+ R4507E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 176 |
+ R4508E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 177 |
+ R4505E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 178 |
+ R4506E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 179 |
+ R4535E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ F |
+ JAX |
+
+
+ | 180 |
+ R4536E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ M |
+ JAX |
+
+
+ | 181 |
+ R2564E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ F |
+ JAX |
+
+
+ | 182 |
+ R2580E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ M |
+ JAX |
+
+
+ | 183 |
+ R4537E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 184 |
+ R4538E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 185 |
+ R4539E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 186 |
+ R4540E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 187 |
+ R2600E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 188 |
+ R2604E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 69 |
+ M |
+ UTHSC RW |
+
+
+ | 189 |
+ R1002E.3 |
+ GDP BXD |
+ DBA/2J |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 190 |
+ R4541E |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 191 |
+ R959E.3 |
+ GDP BXD |
+ DBA/2J |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 192 |
+ R2572E.1 |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 193 |
+ R4542E |
+ GDP BXD |
+ DBA/2J |
+ 59 |
+ M |
+ JAX |
+
+
+ | 194 |
+ R2771E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 195 |
+ R2772E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 196 |
+ R2636E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 197 |
+ R2637E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 198 |
+ R0999E.1 |
+ GDP |
+ LG/J |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 199 |
+ R1004E.1 |
+ GDP |
+ LG/J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 200 |
+ R4543E |
+ GDP |
+ LP/J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 201 |
+ R4544E |
+ GDP |
+ LP/J |
+ 65 |
+ M |
+ JAX |
+
+
+ | 202 |
+ R2858E.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 203 |
+ R2919.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 204 |
+ R1688E.1 |
+ GDP |
+ NOD/LtJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 205 |
+ R2566E-2.1 |
+ GDP |
+ NOD/LtJ |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 206 |
+ R4545E |
+ GDP |
+ NZB/BlNJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 207 |
+ R4546E |
+ GDP |
+ NZB/BlNJ |
+ 58 |
+ M |
+ BIDMC GR |
+
+
+ | 208 |
+ R2535E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 209 |
+ R2550E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ JAX |
+
+
+ | 210 |
+ R2817E.3 |
+ GDP |
+ NZW/LacJ |
+ 65 |
+ F |
+ BIDMC GR |
+
+
+ | 211 |
+ R2810E |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 212 |
+ R2810E.3 |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 213 |
+ R4547E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ F |
+ JAX |
+
+
+ | 214 |
+ R4548E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ M |
+ JAX |
+
+
+ | 215 |
+ R2635E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 216 |
+ R2634E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ M |
+ JAX |
+
+
+ | 217 |
+ R2544E.1 |
+ GDP |
+ PWK/PhJ |
+ 63 |
+ F |
+ JAX |
+
+
+ | 218 |
+ R2549E.1 |
+ GDP |
+ PWK/PhJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 219 |
+ R4550E |
+ GDP |
+ SJL/J |
+ 65 |
+ M+F |
+ JAX |
+
+
+ | 220 |
+ R2368E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 221 |
+ R2547E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0908_r_wt/acknowledgment.rtf b/general/datasets/Eye_m2_0908_r_wt/acknowledgment.rtf
new file mode 100644
index 0000000..5098d32
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_wt/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant and from funds from NEI grant to Dr. Eldon Geisert (R01EY017841), an NEI Vision Core grant (EY14080) and an Unrestricted Grant from Research To Prevent Blindness.
+
+We thank Dr. Ted Choi, Chief Scientific Director of Predictive Biology, Inc. (past director of molecular genetics at Deltagen Inc.) for providing us with eye samples from several interesting DeltaGen knockouts.
diff --git a/general/datasets/Eye_m2_0908_r_wt/cases.rtf b/general/datasets/Eye_m2_0908_r_wt/cases.rtf
new file mode 100644
index 0000000..552d4a5
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_wt/cases.rtf
@@ -0,0 +1,57 @@
+This is the complete and final HEIMED data set. HEIMED consists of expression data for 103 genetically defined lines of mice with standard errors of the mean. Almost all animals are young adults between 50 and 80 days of age (Table 1, maximum age is 123 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, reciprocal F1s between C57BL/6J and DBA/2J, and several mutant and knockout lines. We have combined all common strains, F1 hybrids, and mutants into a group called the Mouse Diversity Panel (MDP). Four lines, namely, C57BL/6J (B6), DBA/2J (D2), and the pair of B6D2F1 and D2B6F1 hybrids are common to both the MDP and the BXD set. This is a breakdown of cases that are part of HEIMED:
+
+
+ - 68 BXD strains. The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. Only one of these strains, BXD24 (know also known as BXD24b), has retinal degeneration (a spontaneous mutation). The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA.
+ - 35 MDP lines, including 26 inbred strains representing closely related substrains (e.g, BALB/cJ and BALB/cByJ), many of the most widely used common Mus musculus domesticus inbred strains (e.g., C57BL/6J and 129S1/SvImJ), inbred but wild-derived representatives of common subspecies (Mus musculus domesticus, e.g, WSB/EiJ; M. musculus musculus, e.g., CZECHII/EiJ; M. musculus molossinus, e.g., MOLF/EiJ; M. musculus castaneus, e.g., CAST/EiJ); and even one different species of mouse (Mus spicilegus, PANCEVO/EiJ). The MDP also includes the reciprocal F1 hybrids (B6D2F1 and D2B6F1) and the following 6 KO lines and the Nyx-nob mutant:
+ - 6 knockouts (KO), including a KO of Rpe65, and 5 DeltaGen Inc. knockout lines provided by Dr. Ted Choi. These KO lines have had a bacterial lacZ construct inserted into the gene. The endogenous promoter drives expression of beta-galactosidase. RT-PCR analysis detects a gene transcript in most tissues. The following KOs from DeltaGen were studied: Gabra1, Gabbr1, Gnb1, Gpr19, and Clcn3. We also included one spontaneous mutant of the nyctalopin (Nyx no b wave "nob") gene (Pardue et al., 1998) that is on a BALB/cByJ background.
+
+
+Rod photoreceptor degeneration in inbred mice: Six strains of mice included in HEIMED suffer from severe loss of photoreceptors (mainly rods) and have the equivalent of night blindness in human patients. The death of photoreceptors in these strains occurs by one to two months of age and is often caused by the retinal degeneration 1 (rd1) mutant allele in the rod cyclic-GMP phosphodiesterase 6 beta subunit gene (Pde6b). The following strains are known to have photoreceptor degeneration: C3H/HeJ, FVB/NJ, MOLF/EiJ, SJL/J and BXD24/TyJ. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEIMED data set.
+
+As expected (Dickerson LW et al., 2002) and as judged from the absence of rhodopsin expression, one of the DeltaGen KO lines (chloride ion channel 3, Clcn3) also has retinal degeneration: B6129P2F2N1-Clcn3. Degeneration in this strain is likely to include all rods and all cones. The cone defect is obvious from the decrease in expression of Gnat2, a gene associated with cones and achromatopsia in mice and humans.
+
+Lines of mice were selected using the following criteria:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - representation of a fairly wide variety of different subspecies of Mus
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Tel Aviv/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - interesting mutations or knockouts affecting genes with high expression in the eye
+ - general availability from The Jackson Laboratory. The only exception are the DeltaGen KO mice.
+
+
+We have included all eight parents of the Collaborative Cross (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/LtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ) in the MDP. Fourteen MDP strains have been partially sequenced by Perlegen for the NIEHS, including including 129S1/SvImJ, A/J, AKR/J, BALB/cByJ, C3H/HeJ, CAST/EiJ, DBA/2J, FVB/NJ, KK/HlJ, MOLF/EiJ, NOD/LtJ, NZW/LacJ, PWD/PhJ, and WSB/EiJ (see the GeneNetwork SNP Browser for data, details, and see Perlegen's excellent data resources and browser).
+
+
+ - 129S1/SvImJ : Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene. It is also a cone photoreceptor function loss 3 mutant (Cpfl3 allele) of the Gnat2 gene that is a model for achromatopsia (JAX Stock Number: 002448)
+ - A/J: Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase (Tyr c allele) albino mutant. This strain is particularly sensitive to light-induced photoreceptor loss (Danciger et al., 2007). (JAX Stock Number: 000646)
+ - BALB/cByJ: Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project old group A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Small brain, not aggressive (JAX Stock Number: 001026)
+ - BALB/cJ: Phenome Project A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Large brain and aggressive (JAX Stock Number: 000651)
+ - BXSB/MpJ: A white-bellied agouti strains with interesting autoimmune disease restricted to males that is associated with a mutation in the Yaa gene that causes glomerulonephritis, a dramatic increase in number of peripheral monocytes, and pre-B-cell deficiency (JAX Stock Number: 000740)
+ - C3H/HeJ: The Heston (He) substrain with a wildtype agouti (A allele) coat color. Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project old group A list. Important to note for this eye expression dataset, C3H/HeJ is a Pdeb6 rd1 mutant with near total photoreceptor loss at as early as postnatal day 30. Also a Tlr4 mutant that is endotoxin resistant. (JAX Stock Number: 000659)
+ - C57BL/6J: Sequenced by NIH/NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list. Single most widely used inbred strain of mouse. (JAX Stock Number: 000664)
+ - C57BLKS/J: Black Kaliss strain (non-agouti a allele) derived from C57BL/6J, but genetically contaminated at some point mainly with DBA/2J and then reinbred. Now at the Jackson Laboratory. (JAX Stock Number: 000662)
+ - CAST/EiJ: A wild-derived inbred Mus musculus castaneus strain. Samples of this subspecies were captured in Southeast Asia. One of three wild-derived strains in the Collaborative Cross sequenced by NIEHS; Phenome Project A list. CAST/Ei and CAST/EiJ are the same strain. The addition of the "J" is trivial and was added when stock were transferred from Dr. Eicher's lab to the Jackson Laboratory production facility in about 2004. (JAX Stock Number: 000928)
+ - CBA/CaJ: Agouti strain from the Jackson Laboratory. Wildtype pigment genes. (JAX Stock Number: 000654)
+ - CZECHII/EiJ: Czech 2 is a wild-derived inbred strain M. musculus musculus strain. Samples of this subspecies were caught in the Czech Republic and inbred at the Jackson Laboratory by Eva Eicher. White-bellied agouti. (JAX Stock Number: 001144).
+ - DBA/2J: The dilute, brown, agouti (dba) strain is the oldest inbred strain of mouse. Inbreeding was started in 1909 by Little. A tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. A myosin 5a (Myo5a d) dilute allele mutant. Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project old A group list. (JAX Stock Number: 000671)
+ - FVB/NJ: Friend's leukemia virus B (FVB) strain. Sequenced by Perlegen/NIEHS and Celera. Tyr c locus albino and a Pdeb6 rd1 mutant derived from Swiss mice at NIH. This has been the most common strain used to make transgenic mice due to large and easily injected oocytes; Phenome Project A list (JAX Stock Number: 001800).
+ - KK/HlJ: K Kondo's (KK) Kasukabe strain is a homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. Males have a form of type 2 diabetes. Sequenced by Perlegen/NIEHS. (JAX Stock Number: 002106)
+ - LG/J: Large (LG) strain. Paternal parent of the Large-by-Small set of RI strains made by James Cheverud and colleagues (the LGXSM panel, not to be confused with the LongXShort or LXS panel). A Tyr c locus albino strain. (JAX Stock Number: 000675)
+ - LP/J: White-bellied agouit strain with a piebald mutation in the endothelin receptor type B Ednrb gene from at the Jackson Laboratory. Some reduction in melanocytes in choroid of eye due to neural creast migration abnormalities. (JAX Stock Number: 000676)
+ - MOLF/EiJ: A wild-derived inbred strain derived from M. musculus molossinus samples camputered in Fukuoka, Japan. This strain has the retinal degeneration rd1 allele in Pde6b. There appears to have been some genetic contamination of this strain with conventional inbred strains in the past several decades (F. Pardo, personal communication to RWW, August 2006). However, the strain is currently fully inbred. (JAX Stock Number: 000550)
+ - NOD/LtJ: Non-obese diabetic strain, originally from M. Hattori in Kyoto, Japan. This is the Edward Leiter (Lt) substrain from the Jackson Laboratory. Collaborative Cross strain sequenced by NIEHS; Phenome Project B list. Homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. (JAX Stock Number: 001976)
+ - NZO/HlLtJ: New Zealand Obese strain. This is a severely obese and hypertensive strain. Males often develop a type 2 diabetes. Collaborative Cross strain. Agouti coat color. (JAX Stock Number: 002105)
+ - NZB/BlNJ: New Zealand Black inbred strain from Bielschowsky (BL, substrain is "B lowercase L N", not "BiN") now maintained at the Jackson Laboratory. (JAX Stock Number: 000648)
+ - NZW/LacJ: New Zealand White strain from the Laboratory Animal Center (Carshalton, UK), now maintained at the Jackson Laboratory. Carries the Tyr c locus albino mutation, the pink-eye dilution mutation in the Oca2 or p locus, and the brown allele at Tyrp1. (JAX Stock Number: 001058)
+ - PANCEVO/EiJ: PANCEVO/EiJ is a wild-derived inbred strain from the Mus spicilegus samples caught in the Pancevo, Serbia. This species of mouse is also known as the Steppe mouse (taxon identifier 10103). M. spicilegus is a colonial mound-building species. No known ocular or retina mutations, but the expression level of Gnat2 is low in this strain, either due to a 3' UTR length variant or possible achromatosia (cone degeneration) (JAX Stock Number: 001384)
+ - PWD/PhJ: A wild-derived Mus musculus musculus agouti strain inbred from samples caught near Prague, Czech Republic. Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues. (JAX Stock Number: 004660)
+ - PWK/PhJ: A wild-derived Mus musculus musculus inbred strain from samples caught near Lhotka, Czech Republic. Collaborative Cross strain; Phenome Project D list. (JAX Stock Number: 003715)
+ - SJL/J: Swiss Webster inbred strain from Jim Lambert's lab at the Jackson Laboratory. This strain has the retinal degeneration rd1 allele in Pde6b. It also carries both the Tyr c albino mutation and the pink-eye dilution mutation in the Oca2 or p locus. Highly aggressive males. (JAX Stock Number: 000686)
+ - WSB/EiJ: Watkin Star line B (or "wild son-of-a-bitch") is a wild-derived Mus musculus domesticus inbred strain from samples caught in Maryland, USA. A Collaborative Cross strain sequenced by NIEHS; Phenome Project C list (JAX Stock Number: 001145)
+ - B6D2F1 and D2B6F1 (also listed as BDF1 and DBF1 in some graphs and tables): F1 hybrids generated by crossing C57BL/6J with DBA/2J. These black reciprocal F1 can be used to detect dominance effects. Comparison of the two reciprocal F1s can be used to detect parental origin (imprinting) effects. The D2B6F1 animals are currently available from the Jackson Laboratory as a special order.) (JAX Stock Number for B6D2F1 hybrids obtained from the Jackson Laboratory, aka B6D2F1/J 100006)
+
+
+Most of the common inbred strains harbor mutations in genes the control pigmentation (Silvers, 2008 and material above in this INFO file). These gene include the albino and chinchilla alleles of the tyrosinase gene (Tyr, or human OCA1), the brown allele of the tyrosinase related protein 1 (Tyrp1), the pink-eye dilution allele of Oca2 (probe set 1418211), the non-agouti (black) and white-bellied alleles of the agouti signaling protein Asip, the steel allele of Kitlg, the dilute allele of Myo5a (probe set 1419754), and the piebald allele of Ednrb. In some of these cases, effects of the mutation are easily detected at the transcript level (Tyrp1, Oca2, and Myo5a), but in the other cases (Tyr, Asip, Ednrb, and Kitlg), mutations do not leave a strong imprint on expression.
diff --git a/general/datasets/Eye_m2_0908_r_wt/citation.rtf b/general/datasets/Eye_m2_0908_r_wt/citation.rtf
new file mode 100644
index 0000000..ddd98e4
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_wt/citation.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams. Gene expression landscape of the mammalian eye: A global survey and database of mRNAs of 103 varieties of mice. Molecular Vision 2009; in press.
diff --git a/general/datasets/Eye_m2_0908_r_wt/contributors.rtf b/general/datasets/Eye_m2_0908_r_wt/contributors.rtf
new file mode 100644
index 0000000..d155833
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_wt/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams
diff --git a/general/datasets/Eye_m2_0908_r_wt/experiment-design.rtf b/general/datasets/Eye_m2_0908_r_wt/experiment-design.rtf
new file mode 100644
index 0000000..1ebe0ad
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_wt/experiment-design.rtf
@@ -0,0 +1 @@
+Expression profiling by array
diff --git a/general/datasets/Eye_m2_0908_r_wt/notes.rtf b/general/datasets/Eye_m2_0908_r_wt/notes.rtf
new file mode 100644
index 0000000..7a26eb5
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_wt/notes.rtf
@@ -0,0 +1 @@
+This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/Eye_m2_0908_r_wt/platform.rtf b/general/datasets/Eye_m2_0908_r_wt/platform.rtf
new file mode 100644
index 0000000..9024a99
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_wt/platform.rtf
@@ -0,0 +1,11 @@
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many probes overlap and target the same transcript). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequences as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
+As part of the development of HEIMED, we have manually annotated individual probe sets by sequence alignment to the mouse genome and transcriptome. Approximately 13,000 probe sets that have comparatively high expression in eye and CNS were curated by one of the authors (RWW) and now have specific information on the part of the transcript targeted by each probe set. The other 33,000 transcripts have corresponding data that was generated by Xusheng Wang using computational methods (BLAT analysis combined with annotated genome sequence).
+
+One example may help explain how to exploit this annotation. The four probe sets for rhodopsin include information on the target location. Only the first probe set targets the last two coding exons. The other three probe sets target different parts of the 3’ UTR (mid, distal, and far distal regions). The probe sets can be reordered by from high to low expression using the Sort By function in Search Results pages. In the case of rhodopsin, the probe set that targets that last two coding exons and proximal parts of the 3’ UTR also has the highest expression . Finally, the HEIMED gene descriptions have been customized to help vision researchers. In the case of rhodopsin, the description appended after the gene name reads “rod photoreceptor pigment, retinitis pigmentosa-associated”. For less well known genes this kind of annotation can be extremely useful. For example, the more verbose annotation for Cerkl reads “neuronal survival and apoptosis-related, retinal ganglion cell expressed, retinitis pigmentosa 26); alternative 3' UTR of short form message, intron 2”.
+
+
+
+
+
+Legend: Distribution of expression values for all probe sets in HEIMED.
diff --git a/general/datasets/Eye_m2_0908_r_wt/processing.rtf b/general/datasets/Eye_m2_0908_r_wt/processing.rtf
new file mode 100644
index 0000000..4349e60
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_wt/processing.rtf
@@ -0,0 +1,3381 @@
+Range of Gene Expression in the Eye. Expression of transcripts in the HEIMED and most other GN data sets is measured on a log2 scale. Each unit corresponding approximately to a 2-fold difference in hybridization signal intensity. To simplify comparisons among different data sets and cases, log2 RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units (variance stabilized). Values of all 45,101 probe sets in this data set range from a low of 4.8 (Tcf15, probe set 1420281_at) to a high of 15.5 (crystallin gamma C, Crygc, probe set 1422674_s_at). This corresponds to 10.7 units or a 1 to 1700 dynamic range of expression (2^10.73).
+
+We used pooled RNA samples of whole eyes, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+We calibrated this log intensity scale using Affymetrix spike-in control probe sets. These 18 control probe sets target exogenous bacterial mRNAs that are added to each sample (a graded dose spike cocktail) during preparation at concentrations of 1.5, 5, 25, and 100 pM. (To find these probe sets, search GN’s ALL search field using the string “AFFX pM”.) A value of 6 or less is equivalent to an mRNA concentration of under 0.4 pM, a value of 8 is equivalent to ~1.5 pM, 9.5 is equivalent to ~5 pM, 11.5 is equivalent to ~25 pM, 13.5 is equivalent to ~100 pM, and a value of 15.5 is equivalent to an mRNA concentration of 400 pM or greater.
+
+This range can be converted to the mRNA molecules per cell in the eye assuming that a value of 8 is equivalent to about 1 mRNA copy per cell (Kanno et al. 2006, see http://www.biomedcentral.com/1471-2164/7/64). Since the expression of rhodopsin mRNA is normally 15 units, we predict that there are 27 or ~128 Rho mRNAs per cell in the whole eye and ~256 in rods themselves (assuming that rods make up about half of all cells in the eye). For this purpose it may be useful to know that a normal mouse eye contains between 6 and 8 million rod photoreceptors (Guo, Lu, and Williams; GN BXD Phenotype ID 11024).
+
+Note that some probe sets with very low expression still provide reliable data. For example, probe set 1440397_at (Cacna2d1) has expression of only 5.5 units (a value that would be declared as "absent" using conventional Affymetrix procedures), but the values for this calcium channel transcript are associated with a very strong cis QTL with an LRS of 79 (LOD = 17). This strong linkage is definitely not due to chance since the probability of the expression data mapping precisely to the location of the parent gene itself is about 10e-16. This indicates a high signal to noise ratio and the detection of significant strain variation of the correct transcript.
+
+The standard error of the mean for the HEIMED data set is computed for 2 to 6 biological replicates. The standard error of such small samples tends to systematically underestimate the population standard error. With n = 2 the underestimate is about 25%, whereas for n = 6 the underestimate is 5%. Gurland and Tripathi (1971) provide a correction and equation for this effect (see Sokal and Rohlf, Biometry, 2nd ed., 1981, p 53 for an equation of the correction factor for small samples of n < 20.) Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. The CEL files were processed using the RMA protocol. We processed the first three batches together. The last batch was processed separately and merged as described below.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
+After RMA processing using Biobase affy10 build running under R version 2.7.1, all array data sets were rank-order normalized. This second round of quantile normalization removes much residual non-linearity across arrays and forces every array to have the same distribution of values as the mean of all arrays. Comparative array data quality was then evaluated in DataDesk. Outlier arrays were flagged by visual inspection in DataDesk, usually by means of an analysis of scatter plots and more quantitatively by generating a correlation matrix of all arrays. Those arrays with mean correlation <0.96 versus all other arrays indicates trouble or a biological outlier). In some cases, outliers were expected, such as samples from strains with retinal degeneration (FVB/NJ, NOD/LtJ, MOLF/EiJ, C3H/HeJ and BXD24), samples from wild subspecies such as WSB/EiJ, CAST/EiJ, PWD/PhJ, and PWK/PhJ, and knockouts. However, when arrays were anomolous both within strain and across strains, they were often simply discarded. The assumption is that anomolous data are much more likely due to experimental and technical errors than to informative biological variation. Approximately 10% of arrays were discarded.
+
+After this process, the acceptable set of arrays was renormalized using all step as above, starting with the original RMA procedure, etc.
+
+We reviewed the data set using a new method developed by RW Williams, Jeremy Peirce, and Hongqiang Li. For the full set of arrays that passed standard QC protocols described above, we computed the strain means for the BXD strains, B6, D2, and F1s. Using this set of strain means we then computed LRS scores for all 45101 probe sets and counted the number of transcripts that generated QTLs with LRS values greater than 50. This value (e.g., 1800) represented the QTL harvest for the full data set. We then dropped a single array from the data set, recomputed strain means, and recomputed the number of transcripts with LRS scores great than 50. This value is expected to typically reduce the number of QTLs that reach the criterion level (e.g., 1750 QTLs > 50). This process was repeated for every array to obtain an array-specific difference value--the effect of removing that array on the total QTL count. For example, the loss of a single array might cause a decrease in 50 QTLs. Values ranged from approximately -90 (good arrays) to +40 (bad arrays). This procedure is similar in some ways to a jackknife protocol, although we are not using this procedure to esimate an error term, but rather as a method to polish a data set.
+
+During this process we discovered that nearly 20 arrays in the batch 2 had been mislabeled at some point in processing. We computed the correct strain membership of each array using a large number of Mendelian probe sets (more than 50) and comparing their match to standard SNP and microsatellite markers and the original array data set of November 2005. This allowed us to rescue a large number of arrays that were of high quality.
+
+A third batch of approximately 40 arrays were processed by Yan Jiao and Weikuan Gu in August 2006. These complete data set assembled by Hongqiang Li. This process again included a correction for a batch effect.
+
+For the June 2006 data set Hongqiang Li used a new batch correction method that stabilizes the range of expression in each batch. For each of the three large batches, we extracted the minumum and maximum raw probe expression (CEL file level) value. We then adjusted raw probe values in each batch to have the same range as the first and largest batch (batch 1) using a simple linear interpolation. These procedures generated new correct CEL files which were then used with RMA to generate final probe set estimates.
+
+For the final fourth batch of arrays (Sept 2008) Arthur Centeno and Rob Williams corrected for a systematic difference in probe set expression values between original arrays run in 2005 and 2006 and the new arrays added in 2008 (n = 45 acceptable arrays). This difference is due to unknown technical batch effects that are probably associated with labeling, hybridization, and scanning. We performed a simple correction to normalize values of the new set of arrays to those of the old set (batches 1 through 3). No changes were made to any values of the previous three batches. We corrected only the probe set level (RMA) values and not the CEL files. For this final batch, we corrected for the difference (offset) in probe set expression between the first three batches arrays run in 2005 and 2006 (a total of 174 acceptable arrays) and the new batch (n = 47 acceptable arrays). This difference is due to unknown technical effects that are probably related to various steps in labeling, hybridization, and scanning. The correction was applied as follows: (1) RWW selected 51 high quality arrays with similar expression characteristics (r = 0.97 or better between pairs of arrays) in the old data set (from batches 1, 2, and 3) and 34 high quality arrays in the final batch. RWW used scatterplots of full RMA transcriptome data sets to review many pairs of arrays within these new and old array batches. Strains with retinal degeneration or unusual eye gene expression characteristics were excluded from these selected subsets. The average expression values for each probe set were then computed for both the old and new array subsets. The offset value (old minus new) was added to each probe set across all 47 new arrays. This processes forces the average probe set in the new arrays to be very close to that of the previous arrays.
+
+Table 2: Sample tube ID, strain, original CEL filename, and Affymetrix quality control values. Columns labeled Scale factor, Background Average, Present, Absent, Marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Strain |
+ Original CEL |
+ Scale factor |
+ Background Average |
+ Present |
+ Absent |
+ Marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ Batch Id |
+ Used for batch control |
+
+
+ | 1 |
+ R2595E.1 |
+ 129S1/SvImJ |
+ R2595E.1.CEL |
+ 1.79 |
+ 115 |
+ 61.00% |
+ 37.50% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 2 |
+ R2533E.1 |
+ 129S1/SvImJ |
+ R2533E.1.CEL |
+ 2.11 |
+ 94 |
+ 57.90% |
+ 40.50% |
+ 1.60% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 3 |
+ R0754E.1 |
+ A/J |
+ R0754E.1.CEL |
+ 2.72 |
+ 86 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.36 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 4 |
+ R4521E |
+ B6129P2F2N1-Clcn3 |
+ R4521E.CEL |
+ 4.83 |
+ 38.7 |
+ 63.30% |
+ 35.30% |
+ 1.40% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 5 |
+ R4522E |
+ B6129P2F2N1-Clcn3 |
+ R4522E.CEL |
+ 5.76 |
+ 37.36 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.37 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 6 |
+ R4523E |
+ B6129P2F2N1-Clcn3 |
+ R4523E.CEL |
+ 4.88 |
+ 40.42 |
+ 63.90% |
+ 34.70% |
+ 1.40% |
+ 1.27 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 7 |
+ R4526E |
+ B6129P2F2N1-Gabbr1 |
+ R4526E.CEL |
+ 3.84 |
+ 44.18 |
+ 65.00% |
+ 33.70% |
+ 1.30% |
+ 1.34 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 8 |
+ R4509E |
+ B6129P2F2N1-Gabbr1 |
+ R4509E.CEL |
+ 7.45 |
+ 34.76 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.45 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 9 |
+ R4510E |
+ B6129P2F2N1-Gabbr1 |
+ R4510E.CEL |
+ 8.44 |
+ 37.44 |
+ 57.40% |
+ 41.10% |
+ 1.50% |
+ 1.35 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 10 |
+ R4511E |
+ B6129P2F2N1-Gabbr1 |
+ R4511E.CEL |
+ 5.91 |
+ 42.02 |
+ 61.40% |
+ 37.20% |
+ 1.40% |
+ 1.41 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 11 |
+ R4524E |
+ B6129P2F2N1-Gabbr1 |
+ R4524E.CEL |
+ 5.49 |
+ 42.34 |
+ 62.40% |
+ 36.20% |
+ 1.40% |
+ 1.29 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 12 |
+ R4525E |
+ B6129P2F2N1-Gabbr1 |
+ R4525E.CEL |
+ 4.69 |
+ 41.3 |
+ 63.10% |
+ 35.50% |
+ 1.40% |
+ 1.27 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 13 |
+ R4515E |
+ B6129P2F2N1-Gabra1 |
+ R4515E.CEL |
+ 5.75 |
+ 41.76 |
+ 62.80% |
+ 35.80% |
+ 1.40% |
+ 1.41 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 14 |
+ R4516E |
+ B6129P2F2N1-Gabra1 |
+ R4516E.CEL |
+ 7.07 |
+ 40.73 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.32 |
+ 0.87 |
+ 4 |
+ Y |
+
+
+ | 15 |
+ R4517E |
+ B6129P2F2N1-Gabra1 |
+ R4517E.CEL |
+ 5.45 |
+ 38.09 |
+ 62.70% |
+ 35.80% |
+ 1.40% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 16 |
+ R4512E |
+ B6129P2F2N1-Gnb5 |
+ R4512E.CEL |
+ 6.56 |
+ 38.02 |
+ 59.90% |
+ 38.70% |
+ 1.50% |
+ 1.33 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 17 |
+ R4513E |
+ B6129P2F2N1-Gnb5 |
+ R4513E.CEL |
+ 4.15 |
+ 41.6 |
+ 63.40% |
+ 35.10% |
+ 1.50% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ |
+
+
+ | 18 |
+ R4514E |
+ B6129P2F2N1-Gnb5 |
+ R4514E.CEL |
+ 5.86 |
+ 39.2 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.34 |
+ 0.81 |
+ 4 |
+ |
+
+
+ | 19 |
+ R4518E |
+ B6129P2F2N1-Gpr19 |
+ R4518E.CEL |
+ 5.58 |
+ 38.9 |
+ 62.60% |
+ 36.00% |
+ 1.30% |
+ 1.39 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 20 |
+ R4519E |
+ B6129P2F2N1-Gpr19 |
+ R4519E.CEL |
+ 5.95 |
+ 41.91 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.35 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 21 |
+ R2601E.1 |
+ B6D2F1 |
+ R2601E.1.CEL |
+ 2.55 |
+ 92 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.44 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 22 |
+ R2602E.1 |
+ B6D2F1 |
+ R2602E.1.CEL |
+ 2.6 |
+ 84 |
+ 59.70% |
+ 38.80% |
+ 1.50% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 23 |
+ R1676E.1 |
+ BALB/cByJ |
+ R1676E.1.CEL |
+ 2.69 |
+ 98 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.46 |
+ 0.74 |
+ 1 |
+ |
+
+
+ | 24 |
+ R1672E.1 |
+ BALB/cByJ |
+ R1672E.1.CEL |
+ 2.22 |
+ 111 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 25 |
+ R4530E |
+ BALB/cJ |
+ R4530E.CEL |
+ 6.37 |
+ 37.53 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.3 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 26 |
+ R4529E |
+ BALB/cJ |
+ R4529E.CEL |
+ 5.71 |
+ 41.33 |
+ 60.50% |
+ 38.00% |
+ 1.50% |
+ 1.48 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD1 |
+ R2704E.2.CEL |
+ 2.066 |
+ 139.61 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD1 |
+ R2707E.3.CEL |
+ 1 |
+ 80 |
+ 56.40% |
+ 42.10% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 3 |
+ |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD2 |
+ R1231E.2.CEL |
+ 2.197 |
+ 138.73 |
+ 57.30% |
+ 41.30% |
+ 1.40% |
+ 1.41 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD2 |
+ R2598E.1.CEL |
+ 1.99 |
+ 106 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD5 |
+ R2591E.1.CEL |
+ 1.7 |
+ 136 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.33 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD5 |
+ R2714E.2.CEL |
+ 1.404 |
+ 144.35 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD6 |
+ R2570E.1.CEL |
+ 1.99 |
+ 87 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.46 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD6 |
+ R2694E.2.CEL |
+ 1.983 |
+ 97.23 |
+ 61.60% |
+ 37.10% |
+ 1.30% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD8 |
+ R2538E.1.CEL |
+ 1.91 |
+ 102 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.52 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD8 |
+ R2709E.2.CEL |
+ 1.99 |
+ 99.79 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.42 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD9 |
+ R2708E.2.CEL |
+ 1.966 |
+ 126.46 |
+ 57.70% |
+ 40.70% |
+ 1.50% |
+ 1.4 |
+ 0.84 |
+ 2 |
+ |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD9 |
+ R2569E.1.CEL |
+ 1.75 |
+ 87 |
+ 55.10% |
+ 43.40% |
+ 1.50% |
+ 2.82 |
+ 3.14 |
+ 1 |
+ |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD11 |
+ R2581E.1.CEL |
+ 1.94 |
+ 89 |
+ 62.10% |
+ 36.40% |
+ 1.60% |
+ 1.55 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD11 |
+ R2612E.2.CEL |
+ 1.83 |
+ 142.03 |
+ 58.20% |
+ 40.50% |
+ 1.40% |
+ 1.78 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD12 |
+ R2742E.2.CEL |
+ 2.127 |
+ 134.14 |
+ 57.00% |
+ 41.60% |
+ 1.40% |
+ 1.64 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD12 |
+ R2543E.1.CEL |
+ 1.61 |
+ 118 |
+ 58.60% |
+ 39.90% |
+ 1.60% |
+ 1.43 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD13 |
+ R2586E.1.CEL |
+ 2.01 |
+ 74 |
+ 56.40% |
+ 42.00% |
+ 1.60% |
+ 2.85 |
+ 3.81 |
+ 1 |
+ |
+
+
+ | 44 |
+ R877E.2 |
+ BXD13 |
+ R877E.2.CEL |
+ 1.558 |
+ 125.63 |
+ 61.20% |
+ 37.50% |
+ 1.20% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD14 |
+ R2557E.1.CEL |
+ 1.83 |
+ 99 |
+ 62.50% |
+ 36.10% |
+ 1.40% |
+ 1.31 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD14 |
+ R1128E.2.CEL |
+ 1.91 |
+ 115 |
+ 59.90% |
+ 38.80% |
+ 1.40% |
+ 1.2 |
+ 0.82 |
+ 1 |
+ Y |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD15 |
+ R2701E.3.CEL |
+ 1 |
+ 88 |
+ 60.60% |
+ 37.90% |
+ 1.40% |
+ 1.5 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD15 |
+ R2716E.2.CEL |
+ 2.015 |
+ 150.83 |
+ 56.40% |
+ 42.10% |
+ 1.60% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD16 |
+ R2711E.2.CEL |
+ 1.953 |
+ 118.53 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD16 |
+ R2567E.1.CEL |
+ 2.24 |
+ 82 |
+ 56.70% |
+ 41.60% |
+ 1.70% |
+ 1.37 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD18 |
+ R2720E.2.CEL |
+ 2.32 |
+ 99.93 |
+ 59.50% |
+ 39.00% |
+ 1.50% |
+ 1.33 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD18 |
+ R2559E.1.CEL |
+ 1.65 |
+ 104 |
+ 60.80% |
+ 37.70% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD19 |
+ R2560E.1.CEL |
+ 1.79 |
+ 98 |
+ 60.90% |
+ 37.50% |
+ 1.60% |
+ 1.35 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD19 |
+ R2713E.2.CEL |
+ 1.67 |
+ 120.82 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD20 |
+ R2584E.1.CEL |
+ 2.07 |
+ 84 |
+ 59.30% |
+ 39.10% |
+ 1.60% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD20 |
+ R2731E.2.CEL |
+ 1.825 |
+ 147 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.4 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD21 |
+ R2702E.2.CEL |
+ 1.811 |
+ 128.65 |
+ 59.40% |
+ 39.10% |
+ 1.40% |
+ 1.26 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD21 |
+ R2541E2.1.CEL |
+ 2.63 |
+ 125 |
+ 56.00% |
+ 42.40% |
+ 1.50% |
+ 1.29 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD22 |
+ R2553E.1.CEL |
+ 1.95 |
+ 111 |
+ 59.90% |
+ 38.50% |
+ 1.50% |
+ 1.28 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD22 |
+ R2700E.2.CEL |
+ 1.858 |
+ 102.96 |
+ 61.50% |
+ 37.10% |
+ 1.30% |
+ 1.48 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD23 |
+ R2558E-2.1.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD23 |
+ R1086E.2.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD24 |
+ R2719E.2.CEL |
+ 1.47 |
+ 140.38 |
+ 61.50% |
+ 37.20% |
+ 1.30% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD24 |
+ R2589E2.1.CEL |
+ 2.61 |
+ 112 |
+ 57.50% |
+ 40.90% |
+ 1.60% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD25 |
+ R2573E-2.1.CEL |
+ 3.15 |
+ 72 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.77 |
+ 0.97 |
+ 1 |
+ |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD25 |
+ R2683E.2.CEL |
+ 1.777 |
+ 115.64 |
+ 58.30% |
+ 40.30% |
+ 1.40% |
+ 2.01 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD27 |
+ R2703E.2.CEL |
+ 1.263 |
+ 134.78 |
+ 62.60% |
+ 36.10% |
+ 1.40% |
+ 1.44 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD27 |
+ R2729E.3.CEL |
+ 1 |
+ 87 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.56 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD28 |
+ R2562E.3.CEL |
+ 1.65 |
+ 116 |
+ 59.90% |
+ 38.40% |
+ 1.70% |
+ 1.37 |
+ 0.79 |
+ 3 |
+ Y |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD28 |
+ R2721E.2.CEL |
+ 2.065 |
+ 157.39 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD29 |
+ R2561E.3.CEL |
+ 1 |
+ 77 |
+ 53.30% |
+ 45.40% |
+ 1.40% |
+ 3.36 |
+ 19.66 |
+ 3 |
+ |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD31 |
+ R1258E.2.CEL |
+ 2.063 |
+ 117.09 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.54 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD31 |
+ R2597E.1.CEL |
+ 2.37 |
+ 94 |
+ 60.30% |
+ 38.30% |
+ 1.50% |
+ 1.34 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD32 |
+ R2563E.1.CEL |
+ 1.55 |
+ 102 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD32 |
+ R1216E.2.CEL |
+ 2.23 |
+ 111.99 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.35 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD33 |
+ R2542E.1.CEL |
+ 2.13 |
+ 97 |
+ 56.50% |
+ 41.80% |
+ 1.60% |
+ 1.91 |
+ 0.93 |
+ 1 |
+ |
+
+
+ | 77 |
+ R857E.2 |
+ BXD33 |
+ R857E.2.CEL |
+ 1.737 |
+ 113.98 |
+ 61.90% |
+ 36.70% |
+ 1.30% |
+ 1.6 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD34 |
+ R1451E.2.CEL |
+ 1.843 |
+ 140.05 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ Y |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD34 |
+ R2585E.1.CEL |
+ 2.64 |
+ 75 |
+ 58.30% |
+ 40.00% |
+ 1.70% |
+ 1.25 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD36 |
+ R2698E.3.CEL |
+ 1 |
+ 86 |
+ 59.70% |
+ 39.00% |
+ 1.30% |
+ 1.46 |
+ 0.78 |
+ 3 |
+ |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD36 |
+ R2705E.3.CEL |
+ 1 |
+ 86 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.46 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD38 |
+ R2710E.2.CEL |
+ 2.112 |
+ 122.1 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.37 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD38 |
+ R2532E.1.CEL |
+ 2.04 |
+ 94 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.37 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD39 |
+ R2574E.1.CEL |
+ 1.98 |
+ 91 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD39 |
+ R2695E.2.CEL |
+ 1.638 |
+ 122.7 |
+ 60.80% |
+ 37.80% |
+ 1.50% |
+ 1.42 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD40 |
+ R2699E.2.CEL |
+ 1.827 |
+ 105.23 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD40 |
+ R2590E.1.CEL |
+ 2.71 |
+ 77 |
+ 59.10% |
+ 39.30% |
+ 1.50% |
+ 1.4 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD42 |
+ R2696E.2.CEL |
+ 1.622 |
+ 118.95 |
+ 62.00% |
+ 36.60% |
+ 1.50% |
+ 1.53 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD42 |
+ R2596E.1.CEL |
+ 2.63 |
+ 108 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 90 |
+ R994E.2 |
+ BXD43 |
+ R994E.2.CEL |
+ 1.966 |
+ 113.12 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.66 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD43 |
+ R2607E.1.CEL |
+ 2.43 |
+ 115 |
+ 58.60% |
+ 40.00% |
+ 1.40% |
+ 1.31 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD44 |
+ R2594E.1.CEL |
+ 1.77 |
+ 117 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.35 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD44 |
+ R2610E.2.CEL |
+ 1.814 |
+ 142.91 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.35 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD45 |
+ R2732E.2.CEL |
+ 2.154 |
+ 122.45 |
+ 56.50% |
+ 42.10% |
+ 1.40% |
+ 1.8 |
+ 0.83 |
+ 2 |
+ |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD45 |
+ R2592E.1.CEL |
+ 1.85 |
+ 106 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.43 |
+ 0.85 |
+ 1 |
+ Y |
+
+
+ | 96 |
+ R967E.2 |
+ BXD48 |
+ R967E.2.CEL |
+ 1.948 |
+ 130.95 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.63 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD48 |
+ R2606E.1.CEL |
+ 2.56 |
+ 106 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.35 |
+ 0.83 |
+ 1 |
+ Y |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD50 |
+ R2933E.3.CEL |
+ 1 |
+ 72 |
+ 52.90% |
+ 45.60% |
+ 1.50% |
+ 2.45 |
+ 0.98 |
+ 3 |
+ |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD50 |
+ R2937E.3.CEL |
+ 1 |
+ 89 |
+ 56.90% |
+ 41.60% |
+ 1.40% |
+ 1.81 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD51 |
+ R2603E.1.CEL |
+ 2.49 |
+ 115 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD51 |
+ R1042E.2.CEL |
+ 2.352 |
+ 104.12 |
+ 58.70% |
+ 39.90% |
+ 1.40% |
+ 1.53 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD55 |
+ R2980E.3.CEL |
+ 1 |
+ 82 |
+ 56.90% |
+ 41.70% |
+ 1.50% |
+ 1.77 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD55 |
+ R2690E.2.CEL |
+ 1.887 |
+ 164.01 |
+ 56.10% |
+ 42.30% |
+ 1.60% |
+ 1.43 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 104 |
+ R4176E |
+ BXD56 |
+ R4176E.CEL |
+ 4.75 |
+ 43.08 |
+ 63.00% |
+ 35.60% |
+ 1.30% |
+ 1.39 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 105 |
+ R4175E |
+ BXD56 |
+ R4175E.CEL |
+ 6 |
+ 38.49 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.47 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD60 |
+ R1006E.3.CEL |
+ 1 |
+ 98 |
+ 54.90% |
+ 43.70% |
+ 1.50% |
+ 2.7 |
+ 0.86 |
+ 3 |
+ |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD60 |
+ R2725E.2.CEL |
+ 1.551 |
+ 148.01 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD60 |
+ R1074E.3.CEL |
+ 1 |
+ 118 |
+ 55.50% |
+ 43.10% |
+ 1.40% |
+ 1.96 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD61 |
+ R2534E2.1.CEL |
+ 2.47 |
+ 118 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.42 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD61 |
+ R2684E.2.CEL |
+ 2.01 |
+ 131.03 |
+ 57.00% |
+ 41.50% |
+ 1.50% |
+ 1.34 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD62 |
+ R1107E.3.CEL |
+ 1 |
+ 83 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.43 |
+ 0.93 |
+ 3 |
+ |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD62 |
+ R2681E.2.CEL |
+ 2.086 |
+ 148.24 |
+ 57.20% |
+ 41.30% |
+ 1.50% |
+ 1.29 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 113 |
+ R965E.3 |
+ BXD62 |
+ R965E.3.CEL |
+ 1 |
+ 93.55 |
+ 53.30% |
+ 45.20% |
+ 1.50% |
+ 3.11 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD63 |
+ R1425E.2.CEL |
+ 1.7 |
+ 136 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.43 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD63 |
+ R2576E.3.CEL |
+ 1 |
+ 84 |
+ 61.30% |
+ 37.40% |
+ 1.40% |
+ 1.48 |
+ 0.76 |
+ 3 |
+ |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD64 |
+ R943E-2.2.CEL |
+ 1.591 |
+ 141.34 |
+ 60.10% |
+ 38.40% |
+ 1.50% |
+ 1.32 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD64 |
+ R2611E.1.CEL |
+ 2.29 |
+ 92 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 1.57 |
+ 1.06 |
+ 1 |
+ |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD65 |
+ R2689E.2.CEL |
+ 1.721 |
+ 142.44 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.38 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD65 |
+ R2583E.1.CEL |
+ 2.49 |
+ 70 |
+ 56.90% |
+ 41.50% |
+ 1.60% |
+ 1.67 |
+ 1.01 |
+ 1 |
+ |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD66 |
+ R2728E.2.CEL |
+ 1.714 |
+ 137.45 |
+ 59.40% |
+ 39.00% |
+ 1.60% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD66 |
+ R2536E2.1.CEL |
+ 2.74 |
+ 109 |
+ 56.10% |
+ 42.30% |
+ 1.70% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD66 |
+ R1207E.2.CEL |
+ 1.681 |
+ 136.86 |
+ 60.40% |
+ 38.10% |
+ 1.50% |
+ 1.45 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD67 |
+ R1192E.2.CEL |
+ 2.126 |
+ 123.37 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD67 |
+ R2727E.3.CEL |
+ 1 |
+ 82.55 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.97 |
+ 0.87 |
+ 2 |
+ |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD67 |
+ R2691E.3.CEL |
+ 1 |
+ 90 |
+ 54.80% |
+ 43.80% |
+ 1.50% |
+ 2.61 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD68 |
+ R2551E.1.CEL |
+ 2.49 |
+ 92 |
+ 54.30% |
+ 44.10% |
+ 1.60% |
+ 2.91 |
+ 1.55 |
+ 1 |
+ |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD68 |
+ R2726E.2.CEL |
+ 1.811 |
+ 153.09 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD69 |
+ R2593E.1.CEL |
+ 1.67 |
+ 128 |
+ 59.20% |
+ 39.50% |
+ 1.30% |
+ 1.47 |
+ 0.92 |
+ 1 |
+ Y |
+
+
+ | 129 |
+ R975E.2 |
+ BXD70 |
+ R975E.2.CEL |
+ 1.841 |
+ 137.97 |
+ 58.00% |
+ 40.50% |
+ 1.40% |
+ 1.36 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD70 |
+ R2537E2.1.CEL |
+ 2.93 |
+ 99 |
+ 58.00% |
+ 40.50% |
+ 1.60% |
+ 1.29 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 131 |
+ R4531E |
+ BXD71 |
+ R4531E.CEL |
+ 4.77 |
+ 43.48 |
+ 62.40% |
+ 36.30% |
+ 1.40% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 132 |
+ R4532E |
+ BXD71 |
+ R4532E.CEL |
+ 5.89 |
+ 40.68 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD73 |
+ R2779E.2.CEL |
+ 1.746 |
+ 121.11 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD73 |
+ R3024E.3.CEL |
+ 1 |
+ 78.05 |
+ 51.70% |
+ 46.60% |
+ 1.70% |
+ 2.3 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD75 |
+ R2565E.1.CEL |
+ 1.79 |
+ 102 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 2.31 |
+ 3.47 |
+ 1 |
+ |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD75 |
+ R1397E-re.2.CEL |
+ 1.449 |
+ 189.71 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD77 |
+ R2687E.3.CEL |
+ 1 |
+ 80 |
+ 58.00% |
+ 40.60% |
+ 1.40% |
+ 1.57 |
+ 0.8 |
+ 3 |
+ Y |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD77 |
+ R2717E.2.CEL |
+ 1.797 |
+ 84.43 |
+ 61.60% |
+ 36.90% |
+ 1.40% |
+ 1.49 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD77 |
+ R1421E.3.CEL |
+ 1 |
+ 94 |
+ 52.40% |
+ 46.20% |
+ 1.40% |
+ 2.29 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD80 |
+ R2579E.1.CEL |
+ 2.42 |
+ 72 |
+ 59.20% |
+ 39.40% |
+ 1.50% |
+ 1.73 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD80 |
+ R2686E.2.CEL |
+ 2.342 |
+ 119.63 |
+ 56.00% |
+ 42.60% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD83 |
+ R2956E.3.CEL |
+ 1 |
+ 84 |
+ 55.40% |
+ 43.20% |
+ 1.40% |
+ 1.39 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD83 |
+ R2960E.3.CEL |
+ 1 |
+ 80 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.5 |
+ 0.82 |
+ 3 |
+ Y |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD84 |
+ R2922E.3.CEL |
+ 1 |
+ 91 |
+ 57.80% |
+ 40.80% |
+ 1.50% |
+ 1.47 |
+ 0.83 |
+ 3 |
+ Y |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD84 |
+ R2895E.3.CEL |
+ 1 |
+ 75 |
+ 58.30% |
+ 40.20% |
+ 1.50% |
+ 1.56 |
+ 0.77 |
+ 3 |
+ Y |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD85 |
+ R2692E.2.CEL |
+ 1.423 |
+ 160.87 |
+ 60.20% |
+ 38.30% |
+ 1.40% |
+ 1.46 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD85 |
+ R2715E.2.CEL |
+ 1.488 |
+ 142.6 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.5 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD86 |
+ R1405E.2.CEL |
+ 2.351 |
+ 119.34 |
+ 56.40% |
+ 42.20% |
+ 1.40% |
+ 1.64 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD86 |
+ R1225E.3.CEL |
+ 1 |
+ 71 |
+ 53.90% |
+ 44.60% |
+ 1.40% |
+ 3.2 |
+ 1.61 |
+ 3 |
+ |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD87 |
+ R2724E.2.CEL |
+ 1.906 |
+ 113.71 |
+ 60.70% |
+ 37.90% |
+ 1.40% |
+ 1.45 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD87 |
+ R2540E.1.CEL |
+ 2.33 |
+ 93 |
+ 61.10% |
+ 37.40% |
+ 1.40% |
+ 1.22 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD89 |
+ R1433E.2.CEL |
+ 1 |
+ 2.241 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.41 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD89 |
+ R2546E.1.CEL |
+ 1.99 |
+ 96 |
+ 58.60% |
+ 39.70% |
+ 1.70% |
+ 1.47 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD90 |
+ R2578E2.1.CEL |
+ 2.79 |
+ 92 |
+ 58.60% |
+ 39.80% |
+ 1.60% |
+ 1.52 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 155 |
+ R859E.2 |
+ BXD90 |
+ R859E.2.CEL |
+ 1.847 |
+ 152.22 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.36 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD92 |
+ R2682E.2.CEL |
+ 1.547 |
+ 156.31 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.37 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD92 |
+ R1388E.3.CEL |
+ 1 |
+ 63 |
+ 60.00% |
+ 38.60% |
+ 1.40% |
+ 1.85 |
+ 1.03 |
+ 3 |
+ |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD92 |
+ R1322E.3.CEL |
+ 1 |
+ 80 |
+ 55.90% |
+ 42.60% |
+ 1.50% |
+ 1.75 |
+ 0.74 |
+ 3 |
+ |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD96 |
+ R2733E.2.CEL |
+ 1.7 |
+ 113.99 |
+ 62.10% |
+ 36.60% |
+ 1.30% |
+ 1.4 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD96 |
+ R2554E.1.CEL |
+ 2.18 |
+ 93 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD97 |
+ R2649E.2.CEL |
+ 2.343 |
+ 119.04 |
+ 57.50% |
+ 41.20% |
+ 1.40% |
+ 1.53 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD97 |
+ R2577E.1.CEL |
+ 2.07 |
+ 77 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.87 |
+ 1.29 |
+ 1 |
+ |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD98 |
+ R2645E.3.CEL |
+ 1 |
+ 88 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.59 |
+ 0.81 |
+ 3 |
+ Y |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD98 |
+ R2688E.2.CEL |
+ 1.772 |
+ 145.24 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.48 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 165 |
+ R4533E |
+ BXD99 |
+ R4533E.CEL |
+ 1 |
+ 37.69 |
+ 60.30% |
+ 38.20% |
+ 1.40% |
+ 1.33 |
+ 0.89 |
+ 4 |
+ Y |
+
+
+ | 166 |
+ R4534E |
+ BXD99 |
+ R4534E.CEL |
+ 5.69 |
+ 36.62 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.16 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 167 |
+ R2885E.3 |
+ BXSB/MpJ |
+ R2885E.3.CEL |
+ 1 |
+ 76 |
+ 58.10% |
+ 40.60% |
+ 1.30% |
+ 1.88 |
+ 1.06 |
+ 3 |
+ |
+
+
+ | 168 |
+ R2883E.3 |
+ BXSB/MpJ |
+ R2883E.3.CEL |
+ 1 |
+ 71 |
+ 56.40% |
+ 42.00% |
+ 1.50% |
+ 1.59 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 169 |
+ R1700E.1 |
+ C3H/HeJ |
+ R1700E.1.CEL |
+ 2.98 |
+ 69 |
+ 60.80% |
+ 37.90% |
+ 1.40% |
+ 1.48 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 170 |
+ R1704E.1 |
+ C3H/HeJ |
+ R1704E.1.CEL |
+ 2.58 |
+ 88 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.38 |
+ 0.84 |
+ 1 |
+ |
+
+
+ | 171 |
+ R2605E.1 |
+ C57BL/6J |
+ R2605E.1.CEL |
+ 1.82 |
+ 131 |
+ 60.50% |
+ 38.20% |
+ 1.30% |
+ 1.32 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 172 |
+ R0871E |
+ C57BL/6J |
+ R0871E.CEL |
+ 6.24 |
+ 37.38 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.41 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 173 |
+ R0872E.1 |
+ C57BL/6J |
+ R0872E.1.CEL |
+ 3.13 |
+ 89 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 174 |
+ R0872E |
+ C57BL/6J |
+ R0872E.CEL |
+ 3.128 |
+ 88.58 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 175 |
+ R4507E |
+ C57BL/6J-Nyx |
+ R4507E.CEL |
+ 8.13 |
+ 37.5 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.32 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 176 |
+ R4508E |
+ C57BL/6J-Nyx |
+ R4508E.CEL |
+ 6.33 |
+ 37.26 |
+ 60.90% |
+ 37.80% |
+ 1.30% |
+ 1.24 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 177 |
+ R4505E |
+ C57BL/6J-Rpe65 |
+ R4505E.CEL |
+ 5.98 |
+ 37.48 |
+ 61.80% |
+ 36.80% |
+ 1.40% |
+ 1.45 |
+ 0.85 |
+ 4 |
+ Y |
+
+
+ | 178 |
+ R4506E |
+ C57BL/6J-Rpe65 |
+ R4506E.CEL |
+ 6.94 |
+ 37.9 |
+ 61.10% |
+ 37.50% |
+ 1.30% |
+ 1.5 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 179 |
+ R4535E |
+ C57BLKS/J |
+ R4535E.CEL |
+ 6.59 |
+ 37.28 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.26 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 180 |
+ R4536E |
+ C57BLKS/J |
+ R4536E.CEL |
+ 1 |
+ 40.71 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 181 |
+ R2564E.1 |
+ CAST/EiJ |
+ R2564E.1.CEL |
+ 1.94 |
+ 89 |
+ 58.50% |
+ 39.90% |
+ 1.60% |
+ 1.6 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 182 |
+ R2580E.1 |
+ CAST/EiJ |
+ R2580E.1.CEL |
+ 2.09 |
+ 95 |
+ 58.20% |
+ 40.10% |
+ 1.70% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ |
+
+
+ | 183 |
+ R4537E |
+ CBA/CaJ |
+ R4537E.CEL |
+ 1 |
+ 38.45 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.63 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 184 |
+ R4538E |
+ CBA/CaJ |
+ R4538E.CEL |
+ 5.89 |
+ 39.18 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.45 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 185 |
+ R4539E |
+ CZECHII/EiJ |
+ R4539E.CEL |
+ 7.73 |
+ 37.1 |
+ 58.30% |
+ 40.10% |
+ 1.50% |
+ 1.7 |
+ 0.95 |
+ 4 |
+ Y |
+
+
+ | 186 |
+ R4540E |
+ CZECHII/EiJ |
+ R4540E.CEL |
+ 11.04 |
+ 36.69 |
+ 53.00% |
+ 45.30% |
+ 1.70% |
+ 1.83 |
+ 1.32 |
+ 4 |
+ |
+
+
+ | 187 |
+ R2600E.1 |
+ D2B6F1 |
+ R2600E.1.CEL |
+ 2.47 |
+ 95 |
+ 58.10% |
+ 40.20% |
+ 1.70% |
+ 1.41 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 188 |
+ R2604E.1 |
+ D2B6F1 |
+ R2604E.1.CEL |
+ 2.66 |
+ 90 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 189 |
+ R1002E.3 |
+ DBA/2J |
+ R1002E.3.CEL |
+ 1 |
+ 102 |
+ 54.80% |
+ 43.70% |
+ 1.50% |
+ 2.84 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 190 |
+ R4541E |
+ DBA/2J |
+ R4541E.CEL |
+ 1 |
+ 43.4 |
+ 61.40% |
+ 37.00% |
+ 1.50% |
+ 1.37 |
+ 0.73 |
+ 4 |
+ Y |
+
+
+ | 191 |
+ R959E.3 |
+ DBA/2J |
+ R959E.3.CEL |
+ 1 |
+ 89.97 |
+ 53.20% |
+ 45.30% |
+ 1.50% |
+ 3.66 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 192 |
+ R2572E.1 |
+ DBA/2J |
+ R2572E.1.CEL |
+ 2.41 |
+ 79 |
+ 55.50% |
+ 42.90% |
+ 1.60% |
+ 1.37 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 193 |
+ R4542E |
+ DBA/2J |
+ R4542E.CEL |
+ 5.7 |
+ 39.95 |
+ 61.00% |
+ 37.40% |
+ 1.50% |
+ 1.23 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 194 |
+ R2771E.3 |
+ FVB/NJ |
+ R2771E.3.CEL |
+ 1 |
+ 70 |
+ 55.30% |
+ 43.20% |
+ 1.50% |
+ 1.69 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 195 |
+ R2772E.3 |
+ FVB/NJ |
+ R2772E.3.CEL |
+ 1 |
+ 76 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.13 |
+ 1.02 |
+ 3 |
+ |
+
+
+ | 196 |
+ R2636E.1 |
+ KK/HlJ |
+ R2636E.1.CEL |
+ 2.61 |
+ 93 |
+ 58.90% |
+ 39.50% |
+ 1.50% |
+ 1.39 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 197 |
+ R2637E.1 |
+ KK/HlJ |
+ R2637E.1.CEL |
+ 2.19 |
+ 103 |
+ 59.40% |
+ 39.00% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 198 |
+ R0999E.1 |
+ LG/J |
+ R0999E.1.CEL |
+ 2.45 |
+ 82 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 199 |
+ R1004E.1 |
+ LG/J |
+ R1004E.1.CEL |
+ 2.44 |
+ 92 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 200 |
+ R4543E |
+ LP/J |
+ R4543E.CEL |
+ 6.57 |
+ 41.99 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.28 |
+ 0.75 |
+ 4 |
+ Y |
+
+
+ | 201 |
+ R4544E |
+ LP/J |
+ R4544E.CEL |
+ 4.56 |
+ 39.9 |
+ 62.40% |
+ 36.10% |
+ 1.50% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 202 |
+ R2858E.3 |
+ MOLF/EiJ |
+ R2858E.3.CEL |
+ 1 |
+ 64 |
+ 53.80% |
+ 44.70% |
+ 1.50% |
+ 1.59 |
+ 0.95 |
+ 3 |
+ |
+
+
+ | 203 |
+ R2919.3 |
+ MOLF/EiJ |
+ R2919.3.CEL |
+ 1 |
+ 64 |
+ 52.40% |
+ 46.00% |
+ 1.60% |
+ 2.15 |
+ 1.07 |
+ 3 |
+ |
+
+
+ | 204 |
+ R1688E.1 |
+ NOD/LtJ |
+ R1688E.1.CEL |
+ 2.66 |
+ 98 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 205 |
+ R2566E-2.1 |
+ NOD/LtJ |
+ R2566E-2.1.CEL |
+ 3.03 |
+ 69 |
+ 59.80% |
+ 38.80% |
+ 1.50% |
+ 1.38 |
+ 0.75 |
+ 1 |
+ Y |
+
+
+ | 206 |
+ R4545E |
+ NZB/BlNJ |
+ R4545E.CEL |
+ 4.23 |
+ 43.48 |
+ 62.10% |
+ 36.40% |
+ 1.50% |
+ 1.33 |
+ 0.76 |
+ 4 |
+ Y |
+
+
+ | 207 |
+ R4546E |
+ NZB/BlNJ |
+ R4546E.CEL |
+ 6.27 |
+ 44.22 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.17 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 208 |
+ R2535E.1 |
+ NZO/HlLtJ |
+ R2535E.1.CEL |
+ 1.89 |
+ 86 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.41 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 209 |
+ R2550E.1 |
+ NZO/HlLtJ |
+ R2550E.1.CEL |
+ 1.79 |
+ 87 |
+ 60.70% |
+ 37.80% |
+ 1.50% |
+ 1.52 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 210 |
+ R2817E.3 |
+ NZW/LacJ |
+ R2817E.3.CEL |
+ 1 |
+ 59 |
+ 50.90% |
+ 47.60% |
+ 1.50% |
+ 3.59 |
+ 1.48 |
+ 3 |
+ |
+
+
+ | 211 |
+ R2810E |
+ NZW/LacJ |
+ R2810E.CEL |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ 3 |
+ |
+
+
+ | 212 |
+ R2810E.3 |
+ NZW/LacJ |
+ R2810E.3.CEL |
+ 1 |
+ 74 |
+ 57.00% |
+ 41.70% |
+ 1.40% |
+ 2.15 |
+ 1.03 |
+ 4 |
+ Y |
+
+
+ | 213 |
+ R4547E |
+ PANCEVO/EiJ |
+ R4547E.CEL |
+ 5.27 |
+ 51.34 |
+ 57.20% |
+ 41.10% |
+ 1.70% |
+ 1.7 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 214 |
+ R4548E |
+ PANCEVO/EiJ |
+ R4548E.CEL |
+ 10.54 |
+ 37.39 |
+ 50.30% |
+ 48.00% |
+ 1.70% |
+ 1.68 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 215 |
+ R2635E.1 |
+ PWD/PhJ |
+ R2635E.1.CEL |
+ 3.72 |
+ 80 |
+ 54.20% |
+ 44.10% |
+ 1.70% |
+ 1.53 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 216 |
+ R2634E.1 |
+ PWD/PhJ |
+ R2634E.1.CEL |
+ 3.29 |
+ 90 |
+ 55.90% |
+ 42.50% |
+ 1.60% |
+ 1.57 |
+ 0.81 |
+ 1 |
+ |
+
+
+ | 217 |
+ R2544E.1 |
+ PWK/PhJ |
+ R2544E.1.CEL |
+ 2.2 |
+ 108 |
+ 54.90% |
+ 43.50% |
+ 1.70% |
+ 1.36 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 218 |
+ R2549E.1 |
+ PWK/PhJ |
+ R2549E.1.CEL |
+ 2.28 |
+ 84 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.57 |
+ 0.83 |
+ 1 |
+ |
+
+
+ | 219 |
+ R4550E |
+ SJL/J |
+ R4550E.CEL |
+ 5.35 |
+ 40.44 |
+ 62.30% |
+ 36.20% |
+ 1.40% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ |
+
+
+ | 220 |
+ R2368E.1 |
+ WSB/EiJ |
+ R2368E.1.CEL |
+ 2.57 |
+ 86 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.29 |
+ 0.74 |
+ 1 |
+ Y |
+
+
+ | 221 |
+ R2547E.1 |
+ WSB/EiJ |
+ R2547E.1.CEL |
+ 2.14 |
+ 90 |
+ 58.20% |
+ 40.10% |
+ 1.60% |
+ 1.32 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0908_r_wt/summary.rtf b/general/datasets/Eye_m2_0908_r_wt/summary.rtf
new file mode 100644
index 0000000..44b7e23
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_wt/summary.rtf
@@ -0,0 +1,12 @@
+FINAL RECOMMENDED EYE DATA SET. The HEIMED September 2008 RMA data release provides estimates of gene expression in whole eyes of 103 lines of young adult mice generated using 221 Affymetrix M430 2.0 arrays. This data set is intended for exploration of the genetics and genomics of the mouse eye, retina, lens, retinal pigment epithelium, cornea, iris and choroid. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). We used pooled RNA samples, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+Users of these mouse eye data may also find the following complementary resources extremely useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
diff --git a/general/datasets/Eye_m2_0908_r_wt/tissue.rtf b/general/datasets/Eye_m2_0908_r_wt/tissue.rtf
new file mode 100644
index 0000000..9b6ee0f
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_r_wt/tissue.rtf
@@ -0,0 +1,2058 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of cRNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. All samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center led by Dr. Weikuan Gu. All arrays were processed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. C until use (roughly one third) or were used immediately for hybridization.
+
+Dealing with ocular pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations taken from brown and beige colored mice tend to have faint residual pigmentation that affects hybridization signal. To address this problem, Dr. Yan Jiao purified total RNA using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204) all four batches.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well balanced sample of males and females, in general without within-strain-by-sex replication. Two strains are represented by a single male sample pool (BXD29 and A/J). Four lines are represented by two or three male sample pools (all of the five DeltaGen KO line). The SJL/J may be a single mixed sex sample. Users can study possible sex effects by comparing any results of expression data to that of a surrogate measurement that summarizes the overall sex balance of HEIMED. To do this just compare your data to those of probe sets 1427262_at (Xist, high in females) and probe set 1426438_at (Ddx3y, high in males). These two sex-specific probes are quantitative surrogates for the sex balance in this data set.
+
+Technical duplicates: One sample, highlighted in the tables below, is a technical duplicate. The pair of technical duplicates were both of high quality. For statistical analysis, they should be combined and treated as single biological sample.
+
+Batch structure: This data set consists of four batches (Table 2, far right column). The final September 2008 data set consists of a total of 221 arrays and 220 independent samples.
+
+
+ - Batch 1: November 2005, n = 78 arrays original arrays of which 76 were accepted into this final data set.
+ - Batch 2: January 2006, n = 62 arrays of which 62 were accepted.
+ - Batch 3: August 2006, n = 39 arrays of which 36 were accepted. (These three batches, including some arrays that were eventually dropped from the final 2008 data set, were combined to form the September 2006 data set.)
+ - Batch 4: Summer 2008, n = 53 arrays of which 47 were accepted.
+
+
+Table 1: HEIMED case IDs, including sample tube ID, strain, age, sex, and source of mice (see Table 2 for information on array quality control)
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Group |
+ Strain |
+ Age |
+ Sex |
+ Source |
+
+
+ | 1 |
+ R2595E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 2 |
+ R2533E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 3 |
+ R0754E.1 |
+ GDP |
+ A/J |
+ 60 |
+ M |
+ JAX |
+
+
+ | 4 |
+ R4521E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 5 |
+ R4522E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 6 |
+ R4523E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 7 |
+ R4526E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 8 |
+ R4509E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 9 |
+ R4510E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 10 |
+ R4511E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 20 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 11 |
+ R4524E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 12 |
+ R4525E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 13 |
+ R4515E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 14 |
+ R4516E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 15 |
+ R4517E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 16 |
+ R4512E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 17 |
+ R4513E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 25 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 18 |
+ R4514E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 19 |
+ R4518E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 70 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 20 |
+ R4519E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 68 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 21 |
+ R2601E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 22 |
+ R2602E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 23 |
+ R1676E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ F |
+ JAX |
+
+
+ | 24 |
+ R1672E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 25 |
+ R4530E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 26 |
+ R4529E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD |
+ BXD1 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD |
+ BXD1 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD |
+ BXD2 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD |
+ BXD2 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD |
+ BXD5 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD |
+ BXD5 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD |
+ BXD6 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD |
+ BXD6 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD |
+ BXD8 |
+ 77 |
+ F |
+ UTHSC RW |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD |
+ BXD8 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD |
+ BXD9 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD |
+ BXD9 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD |
+ BXD11 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD |
+ BXD11 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD |
+ BXD12 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD |
+ BXD12 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD |
+ BXD13 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 44 |
+ R877E.2 |
+ BXD |
+ BXD13 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD |
+ BXD14 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD |
+ BXD14 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD |
+ BXD15 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD |
+ BXD15 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD |
+ BXD16 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD |
+ BXD16 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD |
+ BXD18 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD |
+ BXD18 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD |
+ BXD19 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD |
+ BXD19 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD |
+ BXD20 |
+ 59 |
+ F |
+ BIDMC GR |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD |
+ BXD20 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD |
+ BXD21 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD |
+ BXD21 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD |
+ BXD22 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD |
+ BXD22 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD |
+ BXD23 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD |
+ BXD23 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD |
+ BXD24 |
+ 123 |
+ F |
+ UTHSC RW |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD |
+ BXD24 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD |
+ BXD25 |
+ 67 |
+ F |
+ UAB |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD |
+ BXD25 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD |
+ BXD27 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD |
+ BXD27 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD |
+ BXD28 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD |
+ BXD28 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD |
+ BXD29 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD |
+ BXD31 |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD |
+ BXD31 |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD |
+ BXD32 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD |
+ BXD32 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD |
+ BXD33 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 77 |
+ R857E.2 |
+ BXD |
+ BXD33 |
+ 77 |
+ M |
+ UTHSC RW |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD |
+ BXD34 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD |
+ BXD34 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD |
+ BXD36 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD |
+ BXD36 |
+ 57 |
+ M |
+ BIDMC GR |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD |
+ BXD38 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD |
+ BXD38 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD |
+ BXD39 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD |
+ BXD39 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD |
+ BXD40 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD |
+ BXD40 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD |
+ BXD42 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD |
+ BXD42 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 90 |
+ R994E.2 |
+ BXD |
+ BXD43 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD |
+ BXD43 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD |
+ BXD44 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD |
+ BXD44 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD |
+ BXD45 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD |
+ BXD45 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 96 |
+ R967E.2 |
+ BXD |
+ BXD48 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD |
+ BXD48 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD |
+ BXD51 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD |
+ BXD51 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD |
+ BXD55 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD |
+ BXD55 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 104 |
+ R4176E |
+ BXD |
+ BXD56 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 105 |
+ R4175E |
+ BXD |
+ BXD56 |
+ 53 |
+ M |
+ UTHSC RW |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD |
+ BXD60 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD |
+ BXD60 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD |
+ BXD60 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD |
+ BXD61 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD |
+ BXD61 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ F |
+ UTHSC RW |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD |
+ BXD62 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 113 |
+ R965E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD |
+ BXD63 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD |
+ BXD63 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD |
+ BXD64 |
+ 56 |
+ F |
+ UTHSC RW |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD |
+ BXD64 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD |
+ BXD65 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD |
+ BXD65 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD |
+ BXD66 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD |
+ BXD66 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD |
+ BXD66 |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD |
+ BXD67 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD |
+ BXD68 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD |
+ BXD69 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 129 |
+ R975E.2 |
+ BXD |
+ BXD70 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD |
+ BXD70 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 131 |
+ R4531E |
+ BXD |
+ BXD71 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 132 |
+ R4532E |
+ BXD |
+ BXD71 |
+ 86 |
+ M |
+ UTHSC RW |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD |
+ BXD73 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD |
+ BXD73 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD |
+ BXD75 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD |
+ BXD75 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD |
+ BXD77 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD |
+ BXD77 |
+ 107 |
+ M |
+ UTHSC RW |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD |
+ BXD77 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD |
+ BXD80 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD |
+ BXD80 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD |
+ BXD84 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD |
+ BXD84 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD |
+ BXD85 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD |
+ BXD85 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD |
+ BXD86 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD |
+ BXD86 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD |
+ BXD87 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD |
+ BXD87 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD |
+ BXD89 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD |
+ BXD89 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD |
+ BXD90 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 155 |
+ R859E.2 |
+ BXD |
+ BXD90 |
+ 72 |
+ M |
+ UTHSC RW |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD |
+ BXD92 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD |
+ BXD92 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD |
+ BXD92 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD |
+ BXD96 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD |
+ BXD96 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD |
+ BXD97 |
+ 74 |
+ F |
+ UTHSC RW |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD |
+ BXD97 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD |
+ BXD98 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD |
+ BXD98 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 165 |
+ R4533E |
+ BXD |
+ BXD99 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 166 |
+ R4534E |
+ BXD |
+ BXD99 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 167 |
+ R2885E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 168 |
+ R2883E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 169 |
+ R1700E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 170 |
+ R1704E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 171 |
+ R2605E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 79 |
+ F |
+ UTHSC RW |
+
+
+ | 172 |
+ R0871E |
+ GDP BXD |
+ C57BL/6J |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 173 |
+ R0872E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 174 |
+ R0872E |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 175 |
+ R4507E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 176 |
+ R4508E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 177 |
+ R4505E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 178 |
+ R4506E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 179 |
+ R4535E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ F |
+ JAX |
+
+
+ | 180 |
+ R4536E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ M |
+ JAX |
+
+
+ | 181 |
+ R2564E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ F |
+ JAX |
+
+
+ | 182 |
+ R2580E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ M |
+ JAX |
+
+
+ | 183 |
+ R4537E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 184 |
+ R4538E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 185 |
+ R4539E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 186 |
+ R4540E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 187 |
+ R2600E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 188 |
+ R2604E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 69 |
+ M |
+ UTHSC RW |
+
+
+ | 189 |
+ R1002E.3 |
+ GDP BXD |
+ DBA/2J |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 190 |
+ R4541E |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 191 |
+ R959E.3 |
+ GDP BXD |
+ DBA/2J |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 192 |
+ R2572E.1 |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 193 |
+ R4542E |
+ GDP BXD |
+ DBA/2J |
+ 59 |
+ M |
+ JAX |
+
+
+ | 194 |
+ R2771E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 195 |
+ R2772E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 196 |
+ R2636E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 197 |
+ R2637E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 198 |
+ R0999E.1 |
+ GDP |
+ LG/J |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 199 |
+ R1004E.1 |
+ GDP |
+ LG/J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 200 |
+ R4543E |
+ GDP |
+ LP/J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 201 |
+ R4544E |
+ GDP |
+ LP/J |
+ 65 |
+ M |
+ JAX |
+
+
+ | 202 |
+ R2858E.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 203 |
+ R2919.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 204 |
+ R1688E.1 |
+ GDP |
+ NOD/LtJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 205 |
+ R2566E-2.1 |
+ GDP |
+ NOD/LtJ |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 206 |
+ R4545E |
+ GDP |
+ NZB/BlNJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 207 |
+ R4546E |
+ GDP |
+ NZB/BlNJ |
+ 58 |
+ M |
+ BIDMC GR |
+
+
+ | 208 |
+ R2535E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 209 |
+ R2550E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ JAX |
+
+
+ | 210 |
+ R2817E.3 |
+ GDP |
+ NZW/LacJ |
+ 65 |
+ F |
+ BIDMC GR |
+
+
+ | 211 |
+ R2810E |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 212 |
+ R2810E.3 |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 213 |
+ R4547E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ F |
+ JAX |
+
+
+ | 214 |
+ R4548E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ M |
+ JAX |
+
+
+ | 215 |
+ R2635E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 216 |
+ R2634E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ M |
+ JAX |
+
+
+ | 217 |
+ R2544E.1 |
+ GDP |
+ PWK/PhJ |
+ 63 |
+ F |
+ JAX |
+
+
+ | 218 |
+ R2549E.1 |
+ GDP |
+ PWK/PhJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 219 |
+ R4550E |
+ GDP |
+ SJL/J |
+ 65 |
+ M+F |
+ JAX |
+
+
+ | 220 |
+ R2368E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 221 |
+ R2547E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0908_wtwt/acknowledgment.rtf b/general/datasets/Eye_m2_0908_wtwt/acknowledgment.rtf
new file mode 100644
index 0000000..5098d32
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_wtwt/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant and from funds from NEI grant to Dr. Eldon Geisert (R01EY017841), an NEI Vision Core grant (EY14080) and an Unrestricted Grant from Research To Prevent Blindness.
+
+We thank Dr. Ted Choi, Chief Scientific Director of Predictive Biology, Inc. (past director of molecular genetics at Deltagen Inc.) for providing us with eye samples from several interesting DeltaGen knockouts.
diff --git a/general/datasets/Eye_m2_0908_wtwt/cases.rtf b/general/datasets/Eye_m2_0908_wtwt/cases.rtf
new file mode 100644
index 0000000..552d4a5
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_wtwt/cases.rtf
@@ -0,0 +1,57 @@
+This is the complete and final HEIMED data set. HEIMED consists of expression data for 103 genetically defined lines of mice with standard errors of the mean. Almost all animals are young adults between 50 and 80 days of age (Table 1, maximum age is 123 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, reciprocal F1s between C57BL/6J and DBA/2J, and several mutant and knockout lines. We have combined all common strains, F1 hybrids, and mutants into a group called the Mouse Diversity Panel (MDP). Four lines, namely, C57BL/6J (B6), DBA/2J (D2), and the pair of B6D2F1 and D2B6F1 hybrids are common to both the MDP and the BXD set. This is a breakdown of cases that are part of HEIMED:
+
+
+ - 68 BXD strains. The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. Only one of these strains, BXD24 (know also known as BXD24b), has retinal degeneration (a spontaneous mutation). The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA.
+ - 35 MDP lines, including 26 inbred strains representing closely related substrains (e.g, BALB/cJ and BALB/cByJ), many of the most widely used common Mus musculus domesticus inbred strains (e.g., C57BL/6J and 129S1/SvImJ), inbred but wild-derived representatives of common subspecies (Mus musculus domesticus, e.g, WSB/EiJ; M. musculus musculus, e.g., CZECHII/EiJ; M. musculus molossinus, e.g., MOLF/EiJ; M. musculus castaneus, e.g., CAST/EiJ); and even one different species of mouse (Mus spicilegus, PANCEVO/EiJ). The MDP also includes the reciprocal F1 hybrids (B6D2F1 and D2B6F1) and the following 6 KO lines and the Nyx-nob mutant:
+ - 6 knockouts (KO), including a KO of Rpe65, and 5 DeltaGen Inc. knockout lines provided by Dr. Ted Choi. These KO lines have had a bacterial lacZ construct inserted into the gene. The endogenous promoter drives expression of beta-galactosidase. RT-PCR analysis detects a gene transcript in most tissues. The following KOs from DeltaGen were studied: Gabra1, Gabbr1, Gnb1, Gpr19, and Clcn3. We also included one spontaneous mutant of the nyctalopin (Nyx no b wave "nob") gene (Pardue et al., 1998) that is on a BALB/cByJ background.
+
+
+Rod photoreceptor degeneration in inbred mice: Six strains of mice included in HEIMED suffer from severe loss of photoreceptors (mainly rods) and have the equivalent of night blindness in human patients. The death of photoreceptors in these strains occurs by one to two months of age and is often caused by the retinal degeneration 1 (rd1) mutant allele in the rod cyclic-GMP phosphodiesterase 6 beta subunit gene (Pde6b). The following strains are known to have photoreceptor degeneration: C3H/HeJ, FVB/NJ, MOLF/EiJ, SJL/J and BXD24/TyJ. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEIMED data set.
+
+As expected (Dickerson LW et al., 2002) and as judged from the absence of rhodopsin expression, one of the DeltaGen KO lines (chloride ion channel 3, Clcn3) also has retinal degeneration: B6129P2F2N1-Clcn3. Degeneration in this strain is likely to include all rods and all cones. The cone defect is obvious from the decrease in expression of Gnat2, a gene associated with cones and achromatopsia in mice and humans.
+
+Lines of mice were selected using the following criteria:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - representation of a fairly wide variety of different subspecies of Mus
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Tel Aviv/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - interesting mutations or knockouts affecting genes with high expression in the eye
+ - general availability from The Jackson Laboratory. The only exception are the DeltaGen KO mice.
+
+
+We have included all eight parents of the Collaborative Cross (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/LtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ) in the MDP. Fourteen MDP strains have been partially sequenced by Perlegen for the NIEHS, including including 129S1/SvImJ, A/J, AKR/J, BALB/cByJ, C3H/HeJ, CAST/EiJ, DBA/2J, FVB/NJ, KK/HlJ, MOLF/EiJ, NOD/LtJ, NZW/LacJ, PWD/PhJ, and WSB/EiJ (see the GeneNetwork SNP Browser for data, details, and see Perlegen's excellent data resources and browser).
+
+
+ - 129S1/SvImJ : Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene. It is also a cone photoreceptor function loss 3 mutant (Cpfl3 allele) of the Gnat2 gene that is a model for achromatopsia (JAX Stock Number: 002448)
+ - A/J: Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase (Tyr c allele) albino mutant. This strain is particularly sensitive to light-induced photoreceptor loss (Danciger et al., 2007). (JAX Stock Number: 000646)
+ - BALB/cByJ: Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project old group A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Small brain, not aggressive (JAX Stock Number: 001026)
+ - BALB/cJ: Phenome Project A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Large brain and aggressive (JAX Stock Number: 000651)
+ - BXSB/MpJ: A white-bellied agouti strains with interesting autoimmune disease restricted to males that is associated with a mutation in the Yaa gene that causes glomerulonephritis, a dramatic increase in number of peripheral monocytes, and pre-B-cell deficiency (JAX Stock Number: 000740)
+ - C3H/HeJ: The Heston (He) substrain with a wildtype agouti (A allele) coat color. Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project old group A list. Important to note for this eye expression dataset, C3H/HeJ is a Pdeb6 rd1 mutant with near total photoreceptor loss at as early as postnatal day 30. Also a Tlr4 mutant that is endotoxin resistant. (JAX Stock Number: 000659)
+ - C57BL/6J: Sequenced by NIH/NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list. Single most widely used inbred strain of mouse. (JAX Stock Number: 000664)
+ - C57BLKS/J: Black Kaliss strain (non-agouti a allele) derived from C57BL/6J, but genetically contaminated at some point mainly with DBA/2J and then reinbred. Now at the Jackson Laboratory. (JAX Stock Number: 000662)
+ - CAST/EiJ: A wild-derived inbred Mus musculus castaneus strain. Samples of this subspecies were captured in Southeast Asia. One of three wild-derived strains in the Collaborative Cross sequenced by NIEHS; Phenome Project A list. CAST/Ei and CAST/EiJ are the same strain. The addition of the "J" is trivial and was added when stock were transferred from Dr. Eicher's lab to the Jackson Laboratory production facility in about 2004. (JAX Stock Number: 000928)
+ - CBA/CaJ: Agouti strain from the Jackson Laboratory. Wildtype pigment genes. (JAX Stock Number: 000654)
+ - CZECHII/EiJ: Czech 2 is a wild-derived inbred strain M. musculus musculus strain. Samples of this subspecies were caught in the Czech Republic and inbred at the Jackson Laboratory by Eva Eicher. White-bellied agouti. (JAX Stock Number: 001144).
+ - DBA/2J: The dilute, brown, agouti (dba) strain is the oldest inbred strain of mouse. Inbreeding was started in 1909 by Little. A tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. A myosin 5a (Myo5a d) dilute allele mutant. Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project old A group list. (JAX Stock Number: 000671)
+ - FVB/NJ: Friend's leukemia virus B (FVB) strain. Sequenced by Perlegen/NIEHS and Celera. Tyr c locus albino and a Pdeb6 rd1 mutant derived from Swiss mice at NIH. This has been the most common strain used to make transgenic mice due to large and easily injected oocytes; Phenome Project A list (JAX Stock Number: 001800).
+ - KK/HlJ: K Kondo's (KK) Kasukabe strain is a homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. Males have a form of type 2 diabetes. Sequenced by Perlegen/NIEHS. (JAX Stock Number: 002106)
+ - LG/J: Large (LG) strain. Paternal parent of the Large-by-Small set of RI strains made by James Cheverud and colleagues (the LGXSM panel, not to be confused with the LongXShort or LXS panel). A Tyr c locus albino strain. (JAX Stock Number: 000675)
+ - LP/J: White-bellied agouit strain with a piebald mutation in the endothelin receptor type B Ednrb gene from at the Jackson Laboratory. Some reduction in melanocytes in choroid of eye due to neural creast migration abnormalities. (JAX Stock Number: 000676)
+ - MOLF/EiJ: A wild-derived inbred strain derived from M. musculus molossinus samples camputered in Fukuoka, Japan. This strain has the retinal degeneration rd1 allele in Pde6b. There appears to have been some genetic contamination of this strain with conventional inbred strains in the past several decades (F. Pardo, personal communication to RWW, August 2006). However, the strain is currently fully inbred. (JAX Stock Number: 000550)
+ - NOD/LtJ: Non-obese diabetic strain, originally from M. Hattori in Kyoto, Japan. This is the Edward Leiter (Lt) substrain from the Jackson Laboratory. Collaborative Cross strain sequenced by NIEHS; Phenome Project B list. Homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. (JAX Stock Number: 001976)
+ - NZO/HlLtJ: New Zealand Obese strain. This is a severely obese and hypertensive strain. Males often develop a type 2 diabetes. Collaborative Cross strain. Agouti coat color. (JAX Stock Number: 002105)
+ - NZB/BlNJ: New Zealand Black inbred strain from Bielschowsky (BL, substrain is "B lowercase L N", not "BiN") now maintained at the Jackson Laboratory. (JAX Stock Number: 000648)
+ - NZW/LacJ: New Zealand White strain from the Laboratory Animal Center (Carshalton, UK), now maintained at the Jackson Laboratory. Carries the Tyr c locus albino mutation, the pink-eye dilution mutation in the Oca2 or p locus, and the brown allele at Tyrp1. (JAX Stock Number: 001058)
+ - PANCEVO/EiJ: PANCEVO/EiJ is a wild-derived inbred strain from the Mus spicilegus samples caught in the Pancevo, Serbia. This species of mouse is also known as the Steppe mouse (taxon identifier 10103). M. spicilegus is a colonial mound-building species. No known ocular or retina mutations, but the expression level of Gnat2 is low in this strain, either due to a 3' UTR length variant or possible achromatosia (cone degeneration) (JAX Stock Number: 001384)
+ - PWD/PhJ: A wild-derived Mus musculus musculus agouti strain inbred from samples caught near Prague, Czech Republic. Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues. (JAX Stock Number: 004660)
+ - PWK/PhJ: A wild-derived Mus musculus musculus inbred strain from samples caught near Lhotka, Czech Republic. Collaborative Cross strain; Phenome Project D list. (JAX Stock Number: 003715)
+ - SJL/J: Swiss Webster inbred strain from Jim Lambert's lab at the Jackson Laboratory. This strain has the retinal degeneration rd1 allele in Pde6b. It also carries both the Tyr c albino mutation and the pink-eye dilution mutation in the Oca2 or p locus. Highly aggressive males. (JAX Stock Number: 000686)
+ - WSB/EiJ: Watkin Star line B (or "wild son-of-a-bitch") is a wild-derived Mus musculus domesticus inbred strain from samples caught in Maryland, USA. A Collaborative Cross strain sequenced by NIEHS; Phenome Project C list (JAX Stock Number: 001145)
+ - B6D2F1 and D2B6F1 (also listed as BDF1 and DBF1 in some graphs and tables): F1 hybrids generated by crossing C57BL/6J with DBA/2J. These black reciprocal F1 can be used to detect dominance effects. Comparison of the two reciprocal F1s can be used to detect parental origin (imprinting) effects. The D2B6F1 animals are currently available from the Jackson Laboratory as a special order.) (JAX Stock Number for B6D2F1 hybrids obtained from the Jackson Laboratory, aka B6D2F1/J 100006)
+
+
+Most of the common inbred strains harbor mutations in genes the control pigmentation (Silvers, 2008 and material above in this INFO file). These gene include the albino and chinchilla alleles of the tyrosinase gene (Tyr, or human OCA1), the brown allele of the tyrosinase related protein 1 (Tyrp1), the pink-eye dilution allele of Oca2 (probe set 1418211), the non-agouti (black) and white-bellied alleles of the agouti signaling protein Asip, the steel allele of Kitlg, the dilute allele of Myo5a (probe set 1419754), and the piebald allele of Ednrb. In some of these cases, effects of the mutation are easily detected at the transcript level (Tyrp1, Oca2, and Myo5a), but in the other cases (Tyr, Asip, Ednrb, and Kitlg), mutations do not leave a strong imprint on expression.
diff --git a/general/datasets/Eye_m2_0908_wtwt/citation.rtf b/general/datasets/Eye_m2_0908_wtwt/citation.rtf
new file mode 100644
index 0000000..ddd98e4
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_wtwt/citation.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams. Gene expression landscape of the mammalian eye: A global survey and database of mRNAs of 103 varieties of mice. Molecular Vision 2009; in press.
diff --git a/general/datasets/Eye_m2_0908_wtwt/contributors.rtf b/general/datasets/Eye_m2_0908_wtwt/contributors.rtf
new file mode 100644
index 0000000..d155833
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_wtwt/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams
diff --git a/general/datasets/Eye_m2_0908_wtwt/experiment-design.rtf b/general/datasets/Eye_m2_0908_wtwt/experiment-design.rtf
new file mode 100644
index 0000000..1ebe0ad
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_wtwt/experiment-design.rtf
@@ -0,0 +1 @@
+Expression profiling by array
diff --git a/general/datasets/Eye_m2_0908_wtwt/notes.rtf b/general/datasets/Eye_m2_0908_wtwt/notes.rtf
new file mode 100644
index 0000000..7a26eb5
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_wtwt/notes.rtf
@@ -0,0 +1 @@
+This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/Eye_m2_0908_wtwt/platform.rtf b/general/datasets/Eye_m2_0908_wtwt/platform.rtf
new file mode 100644
index 0000000..9024a99
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_wtwt/platform.rtf
@@ -0,0 +1,11 @@
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many probes overlap and target the same transcript). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequences as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
+As part of the development of HEIMED, we have manually annotated individual probe sets by sequence alignment to the mouse genome and transcriptome. Approximately 13,000 probe sets that have comparatively high expression in eye and CNS were curated by one of the authors (RWW) and now have specific information on the part of the transcript targeted by each probe set. The other 33,000 transcripts have corresponding data that was generated by Xusheng Wang using computational methods (BLAT analysis combined with annotated genome sequence).
+
+One example may help explain how to exploit this annotation. The four probe sets for rhodopsin include information on the target location. Only the first probe set targets the last two coding exons. The other three probe sets target different parts of the 3’ UTR (mid, distal, and far distal regions). The probe sets can be reordered by from high to low expression using the Sort By function in Search Results pages. In the case of rhodopsin, the probe set that targets that last two coding exons and proximal parts of the 3’ UTR also has the highest expression . Finally, the HEIMED gene descriptions have been customized to help vision researchers. In the case of rhodopsin, the description appended after the gene name reads “rod photoreceptor pigment, retinitis pigmentosa-associated”. For less well known genes this kind of annotation can be extremely useful. For example, the more verbose annotation for Cerkl reads “neuronal survival and apoptosis-related, retinal ganglion cell expressed, retinitis pigmentosa 26); alternative 3' UTR of short form message, intron 2”.
+
+
+
+
+
+Legend: Distribution of expression values for all probe sets in HEIMED.
diff --git a/general/datasets/Eye_m2_0908_wtwt/processing.rtf b/general/datasets/Eye_m2_0908_wtwt/processing.rtf
new file mode 100644
index 0000000..4349e60
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_wtwt/processing.rtf
@@ -0,0 +1,3381 @@
+Range of Gene Expression in the Eye. Expression of transcripts in the HEIMED and most other GN data sets is measured on a log2 scale. Each unit corresponding approximately to a 2-fold difference in hybridization signal intensity. To simplify comparisons among different data sets and cases, log2 RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units (variance stabilized). Values of all 45,101 probe sets in this data set range from a low of 4.8 (Tcf15, probe set 1420281_at) to a high of 15.5 (crystallin gamma C, Crygc, probe set 1422674_s_at). This corresponds to 10.7 units or a 1 to 1700 dynamic range of expression (2^10.73).
+
+We used pooled RNA samples of whole eyes, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+We calibrated this log intensity scale using Affymetrix spike-in control probe sets. These 18 control probe sets target exogenous bacterial mRNAs that are added to each sample (a graded dose spike cocktail) during preparation at concentrations of 1.5, 5, 25, and 100 pM. (To find these probe sets, search GN’s ALL search field using the string “AFFX pM”.) A value of 6 or less is equivalent to an mRNA concentration of under 0.4 pM, a value of 8 is equivalent to ~1.5 pM, 9.5 is equivalent to ~5 pM, 11.5 is equivalent to ~25 pM, 13.5 is equivalent to ~100 pM, and a value of 15.5 is equivalent to an mRNA concentration of 400 pM or greater.
+
+This range can be converted to the mRNA molecules per cell in the eye assuming that a value of 8 is equivalent to about 1 mRNA copy per cell (Kanno et al. 2006, see http://www.biomedcentral.com/1471-2164/7/64). Since the expression of rhodopsin mRNA is normally 15 units, we predict that there are 27 or ~128 Rho mRNAs per cell in the whole eye and ~256 in rods themselves (assuming that rods make up about half of all cells in the eye). For this purpose it may be useful to know that a normal mouse eye contains between 6 and 8 million rod photoreceptors (Guo, Lu, and Williams; GN BXD Phenotype ID 11024).
+
+Note that some probe sets with very low expression still provide reliable data. For example, probe set 1440397_at (Cacna2d1) has expression of only 5.5 units (a value that would be declared as "absent" using conventional Affymetrix procedures), but the values for this calcium channel transcript are associated with a very strong cis QTL with an LRS of 79 (LOD = 17). This strong linkage is definitely not due to chance since the probability of the expression data mapping precisely to the location of the parent gene itself is about 10e-16. This indicates a high signal to noise ratio and the detection of significant strain variation of the correct transcript.
+
+The standard error of the mean for the HEIMED data set is computed for 2 to 6 biological replicates. The standard error of such small samples tends to systematically underestimate the population standard error. With n = 2 the underestimate is about 25%, whereas for n = 6 the underestimate is 5%. Gurland and Tripathi (1971) provide a correction and equation for this effect (see Sokal and Rohlf, Biometry, 2nd ed., 1981, p 53 for an equation of the correction factor for small samples of n < 20.) Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. The CEL files were processed using the RMA protocol. We processed the first three batches together. The last batch was processed separately and merged as described below.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
+After RMA processing using Biobase affy10 build running under R version 2.7.1, all array data sets were rank-order normalized. This second round of quantile normalization removes much residual non-linearity across arrays and forces every array to have the same distribution of values as the mean of all arrays. Comparative array data quality was then evaluated in DataDesk. Outlier arrays were flagged by visual inspection in DataDesk, usually by means of an analysis of scatter plots and more quantitatively by generating a correlation matrix of all arrays. Those arrays with mean correlation <0.96 versus all other arrays indicates trouble or a biological outlier). In some cases, outliers were expected, such as samples from strains with retinal degeneration (FVB/NJ, NOD/LtJ, MOLF/EiJ, C3H/HeJ and BXD24), samples from wild subspecies such as WSB/EiJ, CAST/EiJ, PWD/PhJ, and PWK/PhJ, and knockouts. However, when arrays were anomolous both within strain and across strains, they were often simply discarded. The assumption is that anomolous data are much more likely due to experimental and technical errors than to informative biological variation. Approximately 10% of arrays were discarded.
+
+After this process, the acceptable set of arrays was renormalized using all step as above, starting with the original RMA procedure, etc.
+
+We reviewed the data set using a new method developed by RW Williams, Jeremy Peirce, and Hongqiang Li. For the full set of arrays that passed standard QC protocols described above, we computed the strain means for the BXD strains, B6, D2, and F1s. Using this set of strain means we then computed LRS scores for all 45101 probe sets and counted the number of transcripts that generated QTLs with LRS values greater than 50. This value (e.g., 1800) represented the QTL harvest for the full data set. We then dropped a single array from the data set, recomputed strain means, and recomputed the number of transcripts with LRS scores great than 50. This value is expected to typically reduce the number of QTLs that reach the criterion level (e.g., 1750 QTLs > 50). This process was repeated for every array to obtain an array-specific difference value--the effect of removing that array on the total QTL count. For example, the loss of a single array might cause a decrease in 50 QTLs. Values ranged from approximately -90 (good arrays) to +40 (bad arrays). This procedure is similar in some ways to a jackknife protocol, although we are not using this procedure to esimate an error term, but rather as a method to polish a data set.
+
+During this process we discovered that nearly 20 arrays in the batch 2 had been mislabeled at some point in processing. We computed the correct strain membership of each array using a large number of Mendelian probe sets (more than 50) and comparing their match to standard SNP and microsatellite markers and the original array data set of November 2005. This allowed us to rescue a large number of arrays that were of high quality.
+
+A third batch of approximately 40 arrays were processed by Yan Jiao and Weikuan Gu in August 2006. These complete data set assembled by Hongqiang Li. This process again included a correction for a batch effect.
+
+For the June 2006 data set Hongqiang Li used a new batch correction method that stabilizes the range of expression in each batch. For each of the three large batches, we extracted the minumum and maximum raw probe expression (CEL file level) value. We then adjusted raw probe values in each batch to have the same range as the first and largest batch (batch 1) using a simple linear interpolation. These procedures generated new correct CEL files which were then used with RMA to generate final probe set estimates.
+
+For the final fourth batch of arrays (Sept 2008) Arthur Centeno and Rob Williams corrected for a systematic difference in probe set expression values between original arrays run in 2005 and 2006 and the new arrays added in 2008 (n = 45 acceptable arrays). This difference is due to unknown technical batch effects that are probably associated with labeling, hybridization, and scanning. We performed a simple correction to normalize values of the new set of arrays to those of the old set (batches 1 through 3). No changes were made to any values of the previous three batches. We corrected only the probe set level (RMA) values and not the CEL files. For this final batch, we corrected for the difference (offset) in probe set expression between the first three batches arrays run in 2005 and 2006 (a total of 174 acceptable arrays) and the new batch (n = 47 acceptable arrays). This difference is due to unknown technical effects that are probably related to various steps in labeling, hybridization, and scanning. The correction was applied as follows: (1) RWW selected 51 high quality arrays with similar expression characteristics (r = 0.97 or better between pairs of arrays) in the old data set (from batches 1, 2, and 3) and 34 high quality arrays in the final batch. RWW used scatterplots of full RMA transcriptome data sets to review many pairs of arrays within these new and old array batches. Strains with retinal degeneration or unusual eye gene expression characteristics were excluded from these selected subsets. The average expression values for each probe set were then computed for both the old and new array subsets. The offset value (old minus new) was added to each probe set across all 47 new arrays. This processes forces the average probe set in the new arrays to be very close to that of the previous arrays.
+
+Table 2: Sample tube ID, strain, original CEL filename, and Affymetrix quality control values. Columns labeled Scale factor, Background Average, Present, Absent, Marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Strain |
+ Original CEL |
+ Scale factor |
+ Background Average |
+ Present |
+ Absent |
+ Marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ Batch Id |
+ Used for batch control |
+
+
+ | 1 |
+ R2595E.1 |
+ 129S1/SvImJ |
+ R2595E.1.CEL |
+ 1.79 |
+ 115 |
+ 61.00% |
+ 37.50% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 2 |
+ R2533E.1 |
+ 129S1/SvImJ |
+ R2533E.1.CEL |
+ 2.11 |
+ 94 |
+ 57.90% |
+ 40.50% |
+ 1.60% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 3 |
+ R0754E.1 |
+ A/J |
+ R0754E.1.CEL |
+ 2.72 |
+ 86 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.36 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 4 |
+ R4521E |
+ B6129P2F2N1-Clcn3 |
+ R4521E.CEL |
+ 4.83 |
+ 38.7 |
+ 63.30% |
+ 35.30% |
+ 1.40% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 5 |
+ R4522E |
+ B6129P2F2N1-Clcn3 |
+ R4522E.CEL |
+ 5.76 |
+ 37.36 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.37 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 6 |
+ R4523E |
+ B6129P2F2N1-Clcn3 |
+ R4523E.CEL |
+ 4.88 |
+ 40.42 |
+ 63.90% |
+ 34.70% |
+ 1.40% |
+ 1.27 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 7 |
+ R4526E |
+ B6129P2F2N1-Gabbr1 |
+ R4526E.CEL |
+ 3.84 |
+ 44.18 |
+ 65.00% |
+ 33.70% |
+ 1.30% |
+ 1.34 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 8 |
+ R4509E |
+ B6129P2F2N1-Gabbr1 |
+ R4509E.CEL |
+ 7.45 |
+ 34.76 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.45 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 9 |
+ R4510E |
+ B6129P2F2N1-Gabbr1 |
+ R4510E.CEL |
+ 8.44 |
+ 37.44 |
+ 57.40% |
+ 41.10% |
+ 1.50% |
+ 1.35 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 10 |
+ R4511E |
+ B6129P2F2N1-Gabbr1 |
+ R4511E.CEL |
+ 5.91 |
+ 42.02 |
+ 61.40% |
+ 37.20% |
+ 1.40% |
+ 1.41 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 11 |
+ R4524E |
+ B6129P2F2N1-Gabbr1 |
+ R4524E.CEL |
+ 5.49 |
+ 42.34 |
+ 62.40% |
+ 36.20% |
+ 1.40% |
+ 1.29 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 12 |
+ R4525E |
+ B6129P2F2N1-Gabbr1 |
+ R4525E.CEL |
+ 4.69 |
+ 41.3 |
+ 63.10% |
+ 35.50% |
+ 1.40% |
+ 1.27 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 13 |
+ R4515E |
+ B6129P2F2N1-Gabra1 |
+ R4515E.CEL |
+ 5.75 |
+ 41.76 |
+ 62.80% |
+ 35.80% |
+ 1.40% |
+ 1.41 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 14 |
+ R4516E |
+ B6129P2F2N1-Gabra1 |
+ R4516E.CEL |
+ 7.07 |
+ 40.73 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.32 |
+ 0.87 |
+ 4 |
+ Y |
+
+
+ | 15 |
+ R4517E |
+ B6129P2F2N1-Gabra1 |
+ R4517E.CEL |
+ 5.45 |
+ 38.09 |
+ 62.70% |
+ 35.80% |
+ 1.40% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 16 |
+ R4512E |
+ B6129P2F2N1-Gnb5 |
+ R4512E.CEL |
+ 6.56 |
+ 38.02 |
+ 59.90% |
+ 38.70% |
+ 1.50% |
+ 1.33 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 17 |
+ R4513E |
+ B6129P2F2N1-Gnb5 |
+ R4513E.CEL |
+ 4.15 |
+ 41.6 |
+ 63.40% |
+ 35.10% |
+ 1.50% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ |
+
+
+ | 18 |
+ R4514E |
+ B6129P2F2N1-Gnb5 |
+ R4514E.CEL |
+ 5.86 |
+ 39.2 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.34 |
+ 0.81 |
+ 4 |
+ |
+
+
+ | 19 |
+ R4518E |
+ B6129P2F2N1-Gpr19 |
+ R4518E.CEL |
+ 5.58 |
+ 38.9 |
+ 62.60% |
+ 36.00% |
+ 1.30% |
+ 1.39 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 20 |
+ R4519E |
+ B6129P2F2N1-Gpr19 |
+ R4519E.CEL |
+ 5.95 |
+ 41.91 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.35 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 21 |
+ R2601E.1 |
+ B6D2F1 |
+ R2601E.1.CEL |
+ 2.55 |
+ 92 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.44 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 22 |
+ R2602E.1 |
+ B6D2F1 |
+ R2602E.1.CEL |
+ 2.6 |
+ 84 |
+ 59.70% |
+ 38.80% |
+ 1.50% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 23 |
+ R1676E.1 |
+ BALB/cByJ |
+ R1676E.1.CEL |
+ 2.69 |
+ 98 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.46 |
+ 0.74 |
+ 1 |
+ |
+
+
+ | 24 |
+ R1672E.1 |
+ BALB/cByJ |
+ R1672E.1.CEL |
+ 2.22 |
+ 111 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 25 |
+ R4530E |
+ BALB/cJ |
+ R4530E.CEL |
+ 6.37 |
+ 37.53 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.3 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 26 |
+ R4529E |
+ BALB/cJ |
+ R4529E.CEL |
+ 5.71 |
+ 41.33 |
+ 60.50% |
+ 38.00% |
+ 1.50% |
+ 1.48 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD1 |
+ R2704E.2.CEL |
+ 2.066 |
+ 139.61 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD1 |
+ R2707E.3.CEL |
+ 1 |
+ 80 |
+ 56.40% |
+ 42.10% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 3 |
+ |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD2 |
+ R1231E.2.CEL |
+ 2.197 |
+ 138.73 |
+ 57.30% |
+ 41.30% |
+ 1.40% |
+ 1.41 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD2 |
+ R2598E.1.CEL |
+ 1.99 |
+ 106 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD5 |
+ R2591E.1.CEL |
+ 1.7 |
+ 136 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.33 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD5 |
+ R2714E.2.CEL |
+ 1.404 |
+ 144.35 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD6 |
+ R2570E.1.CEL |
+ 1.99 |
+ 87 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.46 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD6 |
+ R2694E.2.CEL |
+ 1.983 |
+ 97.23 |
+ 61.60% |
+ 37.10% |
+ 1.30% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD8 |
+ R2538E.1.CEL |
+ 1.91 |
+ 102 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.52 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD8 |
+ R2709E.2.CEL |
+ 1.99 |
+ 99.79 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.42 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD9 |
+ R2708E.2.CEL |
+ 1.966 |
+ 126.46 |
+ 57.70% |
+ 40.70% |
+ 1.50% |
+ 1.4 |
+ 0.84 |
+ 2 |
+ |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD9 |
+ R2569E.1.CEL |
+ 1.75 |
+ 87 |
+ 55.10% |
+ 43.40% |
+ 1.50% |
+ 2.82 |
+ 3.14 |
+ 1 |
+ |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD11 |
+ R2581E.1.CEL |
+ 1.94 |
+ 89 |
+ 62.10% |
+ 36.40% |
+ 1.60% |
+ 1.55 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD11 |
+ R2612E.2.CEL |
+ 1.83 |
+ 142.03 |
+ 58.20% |
+ 40.50% |
+ 1.40% |
+ 1.78 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD12 |
+ R2742E.2.CEL |
+ 2.127 |
+ 134.14 |
+ 57.00% |
+ 41.60% |
+ 1.40% |
+ 1.64 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD12 |
+ R2543E.1.CEL |
+ 1.61 |
+ 118 |
+ 58.60% |
+ 39.90% |
+ 1.60% |
+ 1.43 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD13 |
+ R2586E.1.CEL |
+ 2.01 |
+ 74 |
+ 56.40% |
+ 42.00% |
+ 1.60% |
+ 2.85 |
+ 3.81 |
+ 1 |
+ |
+
+
+ | 44 |
+ R877E.2 |
+ BXD13 |
+ R877E.2.CEL |
+ 1.558 |
+ 125.63 |
+ 61.20% |
+ 37.50% |
+ 1.20% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD14 |
+ R2557E.1.CEL |
+ 1.83 |
+ 99 |
+ 62.50% |
+ 36.10% |
+ 1.40% |
+ 1.31 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD14 |
+ R1128E.2.CEL |
+ 1.91 |
+ 115 |
+ 59.90% |
+ 38.80% |
+ 1.40% |
+ 1.2 |
+ 0.82 |
+ 1 |
+ Y |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD15 |
+ R2701E.3.CEL |
+ 1 |
+ 88 |
+ 60.60% |
+ 37.90% |
+ 1.40% |
+ 1.5 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD15 |
+ R2716E.2.CEL |
+ 2.015 |
+ 150.83 |
+ 56.40% |
+ 42.10% |
+ 1.60% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD16 |
+ R2711E.2.CEL |
+ 1.953 |
+ 118.53 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD16 |
+ R2567E.1.CEL |
+ 2.24 |
+ 82 |
+ 56.70% |
+ 41.60% |
+ 1.70% |
+ 1.37 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD18 |
+ R2720E.2.CEL |
+ 2.32 |
+ 99.93 |
+ 59.50% |
+ 39.00% |
+ 1.50% |
+ 1.33 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD18 |
+ R2559E.1.CEL |
+ 1.65 |
+ 104 |
+ 60.80% |
+ 37.70% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD19 |
+ R2560E.1.CEL |
+ 1.79 |
+ 98 |
+ 60.90% |
+ 37.50% |
+ 1.60% |
+ 1.35 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD19 |
+ R2713E.2.CEL |
+ 1.67 |
+ 120.82 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD20 |
+ R2584E.1.CEL |
+ 2.07 |
+ 84 |
+ 59.30% |
+ 39.10% |
+ 1.60% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD20 |
+ R2731E.2.CEL |
+ 1.825 |
+ 147 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.4 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD21 |
+ R2702E.2.CEL |
+ 1.811 |
+ 128.65 |
+ 59.40% |
+ 39.10% |
+ 1.40% |
+ 1.26 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD21 |
+ R2541E2.1.CEL |
+ 2.63 |
+ 125 |
+ 56.00% |
+ 42.40% |
+ 1.50% |
+ 1.29 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD22 |
+ R2553E.1.CEL |
+ 1.95 |
+ 111 |
+ 59.90% |
+ 38.50% |
+ 1.50% |
+ 1.28 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD22 |
+ R2700E.2.CEL |
+ 1.858 |
+ 102.96 |
+ 61.50% |
+ 37.10% |
+ 1.30% |
+ 1.48 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD23 |
+ R2558E-2.1.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD23 |
+ R1086E.2.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD24 |
+ R2719E.2.CEL |
+ 1.47 |
+ 140.38 |
+ 61.50% |
+ 37.20% |
+ 1.30% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD24 |
+ R2589E2.1.CEL |
+ 2.61 |
+ 112 |
+ 57.50% |
+ 40.90% |
+ 1.60% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD25 |
+ R2573E-2.1.CEL |
+ 3.15 |
+ 72 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.77 |
+ 0.97 |
+ 1 |
+ |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD25 |
+ R2683E.2.CEL |
+ 1.777 |
+ 115.64 |
+ 58.30% |
+ 40.30% |
+ 1.40% |
+ 2.01 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD27 |
+ R2703E.2.CEL |
+ 1.263 |
+ 134.78 |
+ 62.60% |
+ 36.10% |
+ 1.40% |
+ 1.44 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD27 |
+ R2729E.3.CEL |
+ 1 |
+ 87 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.56 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD28 |
+ R2562E.3.CEL |
+ 1.65 |
+ 116 |
+ 59.90% |
+ 38.40% |
+ 1.70% |
+ 1.37 |
+ 0.79 |
+ 3 |
+ Y |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD28 |
+ R2721E.2.CEL |
+ 2.065 |
+ 157.39 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD29 |
+ R2561E.3.CEL |
+ 1 |
+ 77 |
+ 53.30% |
+ 45.40% |
+ 1.40% |
+ 3.36 |
+ 19.66 |
+ 3 |
+ |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD31 |
+ R1258E.2.CEL |
+ 2.063 |
+ 117.09 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.54 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD31 |
+ R2597E.1.CEL |
+ 2.37 |
+ 94 |
+ 60.30% |
+ 38.30% |
+ 1.50% |
+ 1.34 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD32 |
+ R2563E.1.CEL |
+ 1.55 |
+ 102 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD32 |
+ R1216E.2.CEL |
+ 2.23 |
+ 111.99 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.35 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD33 |
+ R2542E.1.CEL |
+ 2.13 |
+ 97 |
+ 56.50% |
+ 41.80% |
+ 1.60% |
+ 1.91 |
+ 0.93 |
+ 1 |
+ |
+
+
+ | 77 |
+ R857E.2 |
+ BXD33 |
+ R857E.2.CEL |
+ 1.737 |
+ 113.98 |
+ 61.90% |
+ 36.70% |
+ 1.30% |
+ 1.6 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD34 |
+ R1451E.2.CEL |
+ 1.843 |
+ 140.05 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ Y |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD34 |
+ R2585E.1.CEL |
+ 2.64 |
+ 75 |
+ 58.30% |
+ 40.00% |
+ 1.70% |
+ 1.25 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD36 |
+ R2698E.3.CEL |
+ 1 |
+ 86 |
+ 59.70% |
+ 39.00% |
+ 1.30% |
+ 1.46 |
+ 0.78 |
+ 3 |
+ |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD36 |
+ R2705E.3.CEL |
+ 1 |
+ 86 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.46 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD38 |
+ R2710E.2.CEL |
+ 2.112 |
+ 122.1 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.37 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD38 |
+ R2532E.1.CEL |
+ 2.04 |
+ 94 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.37 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD39 |
+ R2574E.1.CEL |
+ 1.98 |
+ 91 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD39 |
+ R2695E.2.CEL |
+ 1.638 |
+ 122.7 |
+ 60.80% |
+ 37.80% |
+ 1.50% |
+ 1.42 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD40 |
+ R2699E.2.CEL |
+ 1.827 |
+ 105.23 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD40 |
+ R2590E.1.CEL |
+ 2.71 |
+ 77 |
+ 59.10% |
+ 39.30% |
+ 1.50% |
+ 1.4 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD42 |
+ R2696E.2.CEL |
+ 1.622 |
+ 118.95 |
+ 62.00% |
+ 36.60% |
+ 1.50% |
+ 1.53 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD42 |
+ R2596E.1.CEL |
+ 2.63 |
+ 108 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 90 |
+ R994E.2 |
+ BXD43 |
+ R994E.2.CEL |
+ 1.966 |
+ 113.12 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.66 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD43 |
+ R2607E.1.CEL |
+ 2.43 |
+ 115 |
+ 58.60% |
+ 40.00% |
+ 1.40% |
+ 1.31 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD44 |
+ R2594E.1.CEL |
+ 1.77 |
+ 117 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.35 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD44 |
+ R2610E.2.CEL |
+ 1.814 |
+ 142.91 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.35 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD45 |
+ R2732E.2.CEL |
+ 2.154 |
+ 122.45 |
+ 56.50% |
+ 42.10% |
+ 1.40% |
+ 1.8 |
+ 0.83 |
+ 2 |
+ |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD45 |
+ R2592E.1.CEL |
+ 1.85 |
+ 106 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.43 |
+ 0.85 |
+ 1 |
+ Y |
+
+
+ | 96 |
+ R967E.2 |
+ BXD48 |
+ R967E.2.CEL |
+ 1.948 |
+ 130.95 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.63 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD48 |
+ R2606E.1.CEL |
+ 2.56 |
+ 106 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.35 |
+ 0.83 |
+ 1 |
+ Y |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD50 |
+ R2933E.3.CEL |
+ 1 |
+ 72 |
+ 52.90% |
+ 45.60% |
+ 1.50% |
+ 2.45 |
+ 0.98 |
+ 3 |
+ |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD50 |
+ R2937E.3.CEL |
+ 1 |
+ 89 |
+ 56.90% |
+ 41.60% |
+ 1.40% |
+ 1.81 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD51 |
+ R2603E.1.CEL |
+ 2.49 |
+ 115 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD51 |
+ R1042E.2.CEL |
+ 2.352 |
+ 104.12 |
+ 58.70% |
+ 39.90% |
+ 1.40% |
+ 1.53 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD55 |
+ R2980E.3.CEL |
+ 1 |
+ 82 |
+ 56.90% |
+ 41.70% |
+ 1.50% |
+ 1.77 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD55 |
+ R2690E.2.CEL |
+ 1.887 |
+ 164.01 |
+ 56.10% |
+ 42.30% |
+ 1.60% |
+ 1.43 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 104 |
+ R4176E |
+ BXD56 |
+ R4176E.CEL |
+ 4.75 |
+ 43.08 |
+ 63.00% |
+ 35.60% |
+ 1.30% |
+ 1.39 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 105 |
+ R4175E |
+ BXD56 |
+ R4175E.CEL |
+ 6 |
+ 38.49 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.47 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD60 |
+ R1006E.3.CEL |
+ 1 |
+ 98 |
+ 54.90% |
+ 43.70% |
+ 1.50% |
+ 2.7 |
+ 0.86 |
+ 3 |
+ |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD60 |
+ R2725E.2.CEL |
+ 1.551 |
+ 148.01 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD60 |
+ R1074E.3.CEL |
+ 1 |
+ 118 |
+ 55.50% |
+ 43.10% |
+ 1.40% |
+ 1.96 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD61 |
+ R2534E2.1.CEL |
+ 2.47 |
+ 118 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.42 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD61 |
+ R2684E.2.CEL |
+ 2.01 |
+ 131.03 |
+ 57.00% |
+ 41.50% |
+ 1.50% |
+ 1.34 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD62 |
+ R1107E.3.CEL |
+ 1 |
+ 83 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.43 |
+ 0.93 |
+ 3 |
+ |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD62 |
+ R2681E.2.CEL |
+ 2.086 |
+ 148.24 |
+ 57.20% |
+ 41.30% |
+ 1.50% |
+ 1.29 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 113 |
+ R965E.3 |
+ BXD62 |
+ R965E.3.CEL |
+ 1 |
+ 93.55 |
+ 53.30% |
+ 45.20% |
+ 1.50% |
+ 3.11 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD63 |
+ R1425E.2.CEL |
+ 1.7 |
+ 136 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.43 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD63 |
+ R2576E.3.CEL |
+ 1 |
+ 84 |
+ 61.30% |
+ 37.40% |
+ 1.40% |
+ 1.48 |
+ 0.76 |
+ 3 |
+ |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD64 |
+ R943E-2.2.CEL |
+ 1.591 |
+ 141.34 |
+ 60.10% |
+ 38.40% |
+ 1.50% |
+ 1.32 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD64 |
+ R2611E.1.CEL |
+ 2.29 |
+ 92 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 1.57 |
+ 1.06 |
+ 1 |
+ |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD65 |
+ R2689E.2.CEL |
+ 1.721 |
+ 142.44 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.38 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD65 |
+ R2583E.1.CEL |
+ 2.49 |
+ 70 |
+ 56.90% |
+ 41.50% |
+ 1.60% |
+ 1.67 |
+ 1.01 |
+ 1 |
+ |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD66 |
+ R2728E.2.CEL |
+ 1.714 |
+ 137.45 |
+ 59.40% |
+ 39.00% |
+ 1.60% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD66 |
+ R2536E2.1.CEL |
+ 2.74 |
+ 109 |
+ 56.10% |
+ 42.30% |
+ 1.70% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD66 |
+ R1207E.2.CEL |
+ 1.681 |
+ 136.86 |
+ 60.40% |
+ 38.10% |
+ 1.50% |
+ 1.45 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD67 |
+ R1192E.2.CEL |
+ 2.126 |
+ 123.37 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD67 |
+ R2727E.3.CEL |
+ 1 |
+ 82.55 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.97 |
+ 0.87 |
+ 2 |
+ |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD67 |
+ R2691E.3.CEL |
+ 1 |
+ 90 |
+ 54.80% |
+ 43.80% |
+ 1.50% |
+ 2.61 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD68 |
+ R2551E.1.CEL |
+ 2.49 |
+ 92 |
+ 54.30% |
+ 44.10% |
+ 1.60% |
+ 2.91 |
+ 1.55 |
+ 1 |
+ |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD68 |
+ R2726E.2.CEL |
+ 1.811 |
+ 153.09 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD69 |
+ R2593E.1.CEL |
+ 1.67 |
+ 128 |
+ 59.20% |
+ 39.50% |
+ 1.30% |
+ 1.47 |
+ 0.92 |
+ 1 |
+ Y |
+
+
+ | 129 |
+ R975E.2 |
+ BXD70 |
+ R975E.2.CEL |
+ 1.841 |
+ 137.97 |
+ 58.00% |
+ 40.50% |
+ 1.40% |
+ 1.36 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD70 |
+ R2537E2.1.CEL |
+ 2.93 |
+ 99 |
+ 58.00% |
+ 40.50% |
+ 1.60% |
+ 1.29 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 131 |
+ R4531E |
+ BXD71 |
+ R4531E.CEL |
+ 4.77 |
+ 43.48 |
+ 62.40% |
+ 36.30% |
+ 1.40% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 132 |
+ R4532E |
+ BXD71 |
+ R4532E.CEL |
+ 5.89 |
+ 40.68 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD73 |
+ R2779E.2.CEL |
+ 1.746 |
+ 121.11 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD73 |
+ R3024E.3.CEL |
+ 1 |
+ 78.05 |
+ 51.70% |
+ 46.60% |
+ 1.70% |
+ 2.3 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD75 |
+ R2565E.1.CEL |
+ 1.79 |
+ 102 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 2.31 |
+ 3.47 |
+ 1 |
+ |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD75 |
+ R1397E-re.2.CEL |
+ 1.449 |
+ 189.71 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD77 |
+ R2687E.3.CEL |
+ 1 |
+ 80 |
+ 58.00% |
+ 40.60% |
+ 1.40% |
+ 1.57 |
+ 0.8 |
+ 3 |
+ Y |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD77 |
+ R2717E.2.CEL |
+ 1.797 |
+ 84.43 |
+ 61.60% |
+ 36.90% |
+ 1.40% |
+ 1.49 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD77 |
+ R1421E.3.CEL |
+ 1 |
+ 94 |
+ 52.40% |
+ 46.20% |
+ 1.40% |
+ 2.29 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD80 |
+ R2579E.1.CEL |
+ 2.42 |
+ 72 |
+ 59.20% |
+ 39.40% |
+ 1.50% |
+ 1.73 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD80 |
+ R2686E.2.CEL |
+ 2.342 |
+ 119.63 |
+ 56.00% |
+ 42.60% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD83 |
+ R2956E.3.CEL |
+ 1 |
+ 84 |
+ 55.40% |
+ 43.20% |
+ 1.40% |
+ 1.39 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD83 |
+ R2960E.3.CEL |
+ 1 |
+ 80 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.5 |
+ 0.82 |
+ 3 |
+ Y |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD84 |
+ R2922E.3.CEL |
+ 1 |
+ 91 |
+ 57.80% |
+ 40.80% |
+ 1.50% |
+ 1.47 |
+ 0.83 |
+ 3 |
+ Y |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD84 |
+ R2895E.3.CEL |
+ 1 |
+ 75 |
+ 58.30% |
+ 40.20% |
+ 1.50% |
+ 1.56 |
+ 0.77 |
+ 3 |
+ Y |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD85 |
+ R2692E.2.CEL |
+ 1.423 |
+ 160.87 |
+ 60.20% |
+ 38.30% |
+ 1.40% |
+ 1.46 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD85 |
+ R2715E.2.CEL |
+ 1.488 |
+ 142.6 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.5 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD86 |
+ R1405E.2.CEL |
+ 2.351 |
+ 119.34 |
+ 56.40% |
+ 42.20% |
+ 1.40% |
+ 1.64 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD86 |
+ R1225E.3.CEL |
+ 1 |
+ 71 |
+ 53.90% |
+ 44.60% |
+ 1.40% |
+ 3.2 |
+ 1.61 |
+ 3 |
+ |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD87 |
+ R2724E.2.CEL |
+ 1.906 |
+ 113.71 |
+ 60.70% |
+ 37.90% |
+ 1.40% |
+ 1.45 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD87 |
+ R2540E.1.CEL |
+ 2.33 |
+ 93 |
+ 61.10% |
+ 37.40% |
+ 1.40% |
+ 1.22 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD89 |
+ R1433E.2.CEL |
+ 1 |
+ 2.241 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.41 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD89 |
+ R2546E.1.CEL |
+ 1.99 |
+ 96 |
+ 58.60% |
+ 39.70% |
+ 1.70% |
+ 1.47 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD90 |
+ R2578E2.1.CEL |
+ 2.79 |
+ 92 |
+ 58.60% |
+ 39.80% |
+ 1.60% |
+ 1.52 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 155 |
+ R859E.2 |
+ BXD90 |
+ R859E.2.CEL |
+ 1.847 |
+ 152.22 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.36 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD92 |
+ R2682E.2.CEL |
+ 1.547 |
+ 156.31 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.37 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD92 |
+ R1388E.3.CEL |
+ 1 |
+ 63 |
+ 60.00% |
+ 38.60% |
+ 1.40% |
+ 1.85 |
+ 1.03 |
+ 3 |
+ |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD92 |
+ R1322E.3.CEL |
+ 1 |
+ 80 |
+ 55.90% |
+ 42.60% |
+ 1.50% |
+ 1.75 |
+ 0.74 |
+ 3 |
+ |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD96 |
+ R2733E.2.CEL |
+ 1.7 |
+ 113.99 |
+ 62.10% |
+ 36.60% |
+ 1.30% |
+ 1.4 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD96 |
+ R2554E.1.CEL |
+ 2.18 |
+ 93 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD97 |
+ R2649E.2.CEL |
+ 2.343 |
+ 119.04 |
+ 57.50% |
+ 41.20% |
+ 1.40% |
+ 1.53 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD97 |
+ R2577E.1.CEL |
+ 2.07 |
+ 77 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.87 |
+ 1.29 |
+ 1 |
+ |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD98 |
+ R2645E.3.CEL |
+ 1 |
+ 88 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.59 |
+ 0.81 |
+ 3 |
+ Y |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD98 |
+ R2688E.2.CEL |
+ 1.772 |
+ 145.24 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.48 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 165 |
+ R4533E |
+ BXD99 |
+ R4533E.CEL |
+ 1 |
+ 37.69 |
+ 60.30% |
+ 38.20% |
+ 1.40% |
+ 1.33 |
+ 0.89 |
+ 4 |
+ Y |
+
+
+ | 166 |
+ R4534E |
+ BXD99 |
+ R4534E.CEL |
+ 5.69 |
+ 36.62 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.16 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 167 |
+ R2885E.3 |
+ BXSB/MpJ |
+ R2885E.3.CEL |
+ 1 |
+ 76 |
+ 58.10% |
+ 40.60% |
+ 1.30% |
+ 1.88 |
+ 1.06 |
+ 3 |
+ |
+
+
+ | 168 |
+ R2883E.3 |
+ BXSB/MpJ |
+ R2883E.3.CEL |
+ 1 |
+ 71 |
+ 56.40% |
+ 42.00% |
+ 1.50% |
+ 1.59 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 169 |
+ R1700E.1 |
+ C3H/HeJ |
+ R1700E.1.CEL |
+ 2.98 |
+ 69 |
+ 60.80% |
+ 37.90% |
+ 1.40% |
+ 1.48 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 170 |
+ R1704E.1 |
+ C3H/HeJ |
+ R1704E.1.CEL |
+ 2.58 |
+ 88 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.38 |
+ 0.84 |
+ 1 |
+ |
+
+
+ | 171 |
+ R2605E.1 |
+ C57BL/6J |
+ R2605E.1.CEL |
+ 1.82 |
+ 131 |
+ 60.50% |
+ 38.20% |
+ 1.30% |
+ 1.32 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 172 |
+ R0871E |
+ C57BL/6J |
+ R0871E.CEL |
+ 6.24 |
+ 37.38 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.41 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 173 |
+ R0872E.1 |
+ C57BL/6J |
+ R0872E.1.CEL |
+ 3.13 |
+ 89 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 174 |
+ R0872E |
+ C57BL/6J |
+ R0872E.CEL |
+ 3.128 |
+ 88.58 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 175 |
+ R4507E |
+ C57BL/6J-Nyx |
+ R4507E.CEL |
+ 8.13 |
+ 37.5 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.32 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 176 |
+ R4508E |
+ C57BL/6J-Nyx |
+ R4508E.CEL |
+ 6.33 |
+ 37.26 |
+ 60.90% |
+ 37.80% |
+ 1.30% |
+ 1.24 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 177 |
+ R4505E |
+ C57BL/6J-Rpe65 |
+ R4505E.CEL |
+ 5.98 |
+ 37.48 |
+ 61.80% |
+ 36.80% |
+ 1.40% |
+ 1.45 |
+ 0.85 |
+ 4 |
+ Y |
+
+
+ | 178 |
+ R4506E |
+ C57BL/6J-Rpe65 |
+ R4506E.CEL |
+ 6.94 |
+ 37.9 |
+ 61.10% |
+ 37.50% |
+ 1.30% |
+ 1.5 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 179 |
+ R4535E |
+ C57BLKS/J |
+ R4535E.CEL |
+ 6.59 |
+ 37.28 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.26 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 180 |
+ R4536E |
+ C57BLKS/J |
+ R4536E.CEL |
+ 1 |
+ 40.71 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 181 |
+ R2564E.1 |
+ CAST/EiJ |
+ R2564E.1.CEL |
+ 1.94 |
+ 89 |
+ 58.50% |
+ 39.90% |
+ 1.60% |
+ 1.6 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 182 |
+ R2580E.1 |
+ CAST/EiJ |
+ R2580E.1.CEL |
+ 2.09 |
+ 95 |
+ 58.20% |
+ 40.10% |
+ 1.70% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ |
+
+
+ | 183 |
+ R4537E |
+ CBA/CaJ |
+ R4537E.CEL |
+ 1 |
+ 38.45 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.63 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 184 |
+ R4538E |
+ CBA/CaJ |
+ R4538E.CEL |
+ 5.89 |
+ 39.18 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.45 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 185 |
+ R4539E |
+ CZECHII/EiJ |
+ R4539E.CEL |
+ 7.73 |
+ 37.1 |
+ 58.30% |
+ 40.10% |
+ 1.50% |
+ 1.7 |
+ 0.95 |
+ 4 |
+ Y |
+
+
+ | 186 |
+ R4540E |
+ CZECHII/EiJ |
+ R4540E.CEL |
+ 11.04 |
+ 36.69 |
+ 53.00% |
+ 45.30% |
+ 1.70% |
+ 1.83 |
+ 1.32 |
+ 4 |
+ |
+
+
+ | 187 |
+ R2600E.1 |
+ D2B6F1 |
+ R2600E.1.CEL |
+ 2.47 |
+ 95 |
+ 58.10% |
+ 40.20% |
+ 1.70% |
+ 1.41 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 188 |
+ R2604E.1 |
+ D2B6F1 |
+ R2604E.1.CEL |
+ 2.66 |
+ 90 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 189 |
+ R1002E.3 |
+ DBA/2J |
+ R1002E.3.CEL |
+ 1 |
+ 102 |
+ 54.80% |
+ 43.70% |
+ 1.50% |
+ 2.84 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 190 |
+ R4541E |
+ DBA/2J |
+ R4541E.CEL |
+ 1 |
+ 43.4 |
+ 61.40% |
+ 37.00% |
+ 1.50% |
+ 1.37 |
+ 0.73 |
+ 4 |
+ Y |
+
+
+ | 191 |
+ R959E.3 |
+ DBA/2J |
+ R959E.3.CEL |
+ 1 |
+ 89.97 |
+ 53.20% |
+ 45.30% |
+ 1.50% |
+ 3.66 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 192 |
+ R2572E.1 |
+ DBA/2J |
+ R2572E.1.CEL |
+ 2.41 |
+ 79 |
+ 55.50% |
+ 42.90% |
+ 1.60% |
+ 1.37 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 193 |
+ R4542E |
+ DBA/2J |
+ R4542E.CEL |
+ 5.7 |
+ 39.95 |
+ 61.00% |
+ 37.40% |
+ 1.50% |
+ 1.23 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 194 |
+ R2771E.3 |
+ FVB/NJ |
+ R2771E.3.CEL |
+ 1 |
+ 70 |
+ 55.30% |
+ 43.20% |
+ 1.50% |
+ 1.69 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 195 |
+ R2772E.3 |
+ FVB/NJ |
+ R2772E.3.CEL |
+ 1 |
+ 76 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.13 |
+ 1.02 |
+ 3 |
+ |
+
+
+ | 196 |
+ R2636E.1 |
+ KK/HlJ |
+ R2636E.1.CEL |
+ 2.61 |
+ 93 |
+ 58.90% |
+ 39.50% |
+ 1.50% |
+ 1.39 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 197 |
+ R2637E.1 |
+ KK/HlJ |
+ R2637E.1.CEL |
+ 2.19 |
+ 103 |
+ 59.40% |
+ 39.00% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 198 |
+ R0999E.1 |
+ LG/J |
+ R0999E.1.CEL |
+ 2.45 |
+ 82 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 199 |
+ R1004E.1 |
+ LG/J |
+ R1004E.1.CEL |
+ 2.44 |
+ 92 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 200 |
+ R4543E |
+ LP/J |
+ R4543E.CEL |
+ 6.57 |
+ 41.99 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.28 |
+ 0.75 |
+ 4 |
+ Y |
+
+
+ | 201 |
+ R4544E |
+ LP/J |
+ R4544E.CEL |
+ 4.56 |
+ 39.9 |
+ 62.40% |
+ 36.10% |
+ 1.50% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 202 |
+ R2858E.3 |
+ MOLF/EiJ |
+ R2858E.3.CEL |
+ 1 |
+ 64 |
+ 53.80% |
+ 44.70% |
+ 1.50% |
+ 1.59 |
+ 0.95 |
+ 3 |
+ |
+
+
+ | 203 |
+ R2919.3 |
+ MOLF/EiJ |
+ R2919.3.CEL |
+ 1 |
+ 64 |
+ 52.40% |
+ 46.00% |
+ 1.60% |
+ 2.15 |
+ 1.07 |
+ 3 |
+ |
+
+
+ | 204 |
+ R1688E.1 |
+ NOD/LtJ |
+ R1688E.1.CEL |
+ 2.66 |
+ 98 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 205 |
+ R2566E-2.1 |
+ NOD/LtJ |
+ R2566E-2.1.CEL |
+ 3.03 |
+ 69 |
+ 59.80% |
+ 38.80% |
+ 1.50% |
+ 1.38 |
+ 0.75 |
+ 1 |
+ Y |
+
+
+ | 206 |
+ R4545E |
+ NZB/BlNJ |
+ R4545E.CEL |
+ 4.23 |
+ 43.48 |
+ 62.10% |
+ 36.40% |
+ 1.50% |
+ 1.33 |
+ 0.76 |
+ 4 |
+ Y |
+
+
+ | 207 |
+ R4546E |
+ NZB/BlNJ |
+ R4546E.CEL |
+ 6.27 |
+ 44.22 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.17 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 208 |
+ R2535E.1 |
+ NZO/HlLtJ |
+ R2535E.1.CEL |
+ 1.89 |
+ 86 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.41 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 209 |
+ R2550E.1 |
+ NZO/HlLtJ |
+ R2550E.1.CEL |
+ 1.79 |
+ 87 |
+ 60.70% |
+ 37.80% |
+ 1.50% |
+ 1.52 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 210 |
+ R2817E.3 |
+ NZW/LacJ |
+ R2817E.3.CEL |
+ 1 |
+ 59 |
+ 50.90% |
+ 47.60% |
+ 1.50% |
+ 3.59 |
+ 1.48 |
+ 3 |
+ |
+
+
+ | 211 |
+ R2810E |
+ NZW/LacJ |
+ R2810E.CEL |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ 3 |
+ |
+
+
+ | 212 |
+ R2810E.3 |
+ NZW/LacJ |
+ R2810E.3.CEL |
+ 1 |
+ 74 |
+ 57.00% |
+ 41.70% |
+ 1.40% |
+ 2.15 |
+ 1.03 |
+ 4 |
+ Y |
+
+
+ | 213 |
+ R4547E |
+ PANCEVO/EiJ |
+ R4547E.CEL |
+ 5.27 |
+ 51.34 |
+ 57.20% |
+ 41.10% |
+ 1.70% |
+ 1.7 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 214 |
+ R4548E |
+ PANCEVO/EiJ |
+ R4548E.CEL |
+ 10.54 |
+ 37.39 |
+ 50.30% |
+ 48.00% |
+ 1.70% |
+ 1.68 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 215 |
+ R2635E.1 |
+ PWD/PhJ |
+ R2635E.1.CEL |
+ 3.72 |
+ 80 |
+ 54.20% |
+ 44.10% |
+ 1.70% |
+ 1.53 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 216 |
+ R2634E.1 |
+ PWD/PhJ |
+ R2634E.1.CEL |
+ 3.29 |
+ 90 |
+ 55.90% |
+ 42.50% |
+ 1.60% |
+ 1.57 |
+ 0.81 |
+ 1 |
+ |
+
+
+ | 217 |
+ R2544E.1 |
+ PWK/PhJ |
+ R2544E.1.CEL |
+ 2.2 |
+ 108 |
+ 54.90% |
+ 43.50% |
+ 1.70% |
+ 1.36 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 218 |
+ R2549E.1 |
+ PWK/PhJ |
+ R2549E.1.CEL |
+ 2.28 |
+ 84 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.57 |
+ 0.83 |
+ 1 |
+ |
+
+
+ | 219 |
+ R4550E |
+ SJL/J |
+ R4550E.CEL |
+ 5.35 |
+ 40.44 |
+ 62.30% |
+ 36.20% |
+ 1.40% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ |
+
+
+ | 220 |
+ R2368E.1 |
+ WSB/EiJ |
+ R2368E.1.CEL |
+ 2.57 |
+ 86 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.29 |
+ 0.74 |
+ 1 |
+ Y |
+
+
+ | 221 |
+ R2547E.1 |
+ WSB/EiJ |
+ R2547E.1.CEL |
+ 2.14 |
+ 90 |
+ 58.20% |
+ 40.10% |
+ 1.60% |
+ 1.32 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_0908_wtwt/summary.rtf b/general/datasets/Eye_m2_0908_wtwt/summary.rtf
new file mode 100644
index 0000000..44b7e23
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_wtwt/summary.rtf
@@ -0,0 +1,12 @@
+FINAL RECOMMENDED EYE DATA SET. The HEIMED September 2008 RMA data release provides estimates of gene expression in whole eyes of 103 lines of young adult mice generated using 221 Affymetrix M430 2.0 arrays. This data set is intended for exploration of the genetics and genomics of the mouse eye, retina, lens, retinal pigment epithelium, cornea, iris and choroid. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). We used pooled RNA samples, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+Users of these mouse eye data may also find the following complementary resources extremely useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
diff --git a/general/datasets/Eye_m2_0908_wtwt/tissue.rtf b/general/datasets/Eye_m2_0908_wtwt/tissue.rtf
new file mode 100644
index 0000000..9b6ee0f
--- /dev/null
+++ b/general/datasets/Eye_m2_0908_wtwt/tissue.rtf
@@ -0,0 +1,2058 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of cRNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. All samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center led by Dr. Weikuan Gu. All arrays were processed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. C until use (roughly one third) or were used immediately for hybridization.
+
+Dealing with ocular pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations taken from brown and beige colored mice tend to have faint residual pigmentation that affects hybridization signal. To address this problem, Dr. Yan Jiao purified total RNA using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204) all four batches.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well balanced sample of males and females, in general without within-strain-by-sex replication. Two strains are represented by a single male sample pool (BXD29 and A/J). Four lines are represented by two or three male sample pools (all of the five DeltaGen KO line). The SJL/J may be a single mixed sex sample. Users can study possible sex effects by comparing any results of expression data to that of a surrogate measurement that summarizes the overall sex balance of HEIMED. To do this just compare your data to those of probe sets 1427262_at (Xist, high in females) and probe set 1426438_at (Ddx3y, high in males). These two sex-specific probes are quantitative surrogates for the sex balance in this data set.
+
+Technical duplicates: One sample, highlighted in the tables below, is a technical duplicate. The pair of technical duplicates were both of high quality. For statistical analysis, they should be combined and treated as single biological sample.
+
+Batch structure: This data set consists of four batches (Table 2, far right column). The final September 2008 data set consists of a total of 221 arrays and 220 independent samples.
+
+
+ - Batch 1: November 2005, n = 78 arrays original arrays of which 76 were accepted into this final data set.
+ - Batch 2: January 2006, n = 62 arrays of which 62 were accepted.
+ - Batch 3: August 2006, n = 39 arrays of which 36 were accepted. (These three batches, including some arrays that were eventually dropped from the final 2008 data set, were combined to form the September 2006 data set.)
+ - Batch 4: Summer 2008, n = 53 arrays of which 47 were accepted.
+
+
+Table 1: HEIMED case IDs, including sample tube ID, strain, age, sex, and source of mice (see Table 2 for information on array quality control)
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Group |
+ Strain |
+ Age |
+ Sex |
+ Source |
+
+
+ | 1 |
+ R2595E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 2 |
+ R2533E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 3 |
+ R0754E.1 |
+ GDP |
+ A/J |
+ 60 |
+ M |
+ JAX |
+
+
+ | 4 |
+ R4521E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 5 |
+ R4522E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 6 |
+ R4523E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 7 |
+ R4526E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 8 |
+ R4509E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 9 |
+ R4510E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 10 |
+ R4511E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 20 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 11 |
+ R4524E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 12 |
+ R4525E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 13 |
+ R4515E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 14 |
+ R4516E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 15 |
+ R4517E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 16 |
+ R4512E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 17 |
+ R4513E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 25 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 18 |
+ R4514E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 19 |
+ R4518E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 70 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 20 |
+ R4519E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 68 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 21 |
+ R2601E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 22 |
+ R2602E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 23 |
+ R1676E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ F |
+ JAX |
+
+
+ | 24 |
+ R1672E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 25 |
+ R4530E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 26 |
+ R4529E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD |
+ BXD1 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD |
+ BXD1 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD |
+ BXD2 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD |
+ BXD2 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD |
+ BXD5 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD |
+ BXD5 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD |
+ BXD6 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD |
+ BXD6 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD |
+ BXD8 |
+ 77 |
+ F |
+ UTHSC RW |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD |
+ BXD8 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD |
+ BXD9 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD |
+ BXD9 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD |
+ BXD11 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD |
+ BXD11 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD |
+ BXD12 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD |
+ BXD12 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD |
+ BXD13 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 44 |
+ R877E.2 |
+ BXD |
+ BXD13 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD |
+ BXD14 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD |
+ BXD14 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD |
+ BXD15 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD |
+ BXD15 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD |
+ BXD16 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD |
+ BXD16 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD |
+ BXD18 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD |
+ BXD18 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD |
+ BXD19 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD |
+ BXD19 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD |
+ BXD20 |
+ 59 |
+ F |
+ BIDMC GR |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD |
+ BXD20 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD |
+ BXD21 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD |
+ BXD21 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD |
+ BXD22 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD |
+ BXD22 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD |
+ BXD23 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD |
+ BXD23 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD |
+ BXD24 |
+ 123 |
+ F |
+ UTHSC RW |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD |
+ BXD24 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD |
+ BXD25 |
+ 67 |
+ F |
+ UAB |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD |
+ BXD25 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD |
+ BXD27 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD |
+ BXD27 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD |
+ BXD28 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD |
+ BXD28 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD |
+ BXD29 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD |
+ BXD31 |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD |
+ BXD31 |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD |
+ BXD32 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD |
+ BXD32 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD |
+ BXD33 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 77 |
+ R857E.2 |
+ BXD |
+ BXD33 |
+ 77 |
+ M |
+ UTHSC RW |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD |
+ BXD34 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD |
+ BXD34 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD |
+ BXD36 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD |
+ BXD36 |
+ 57 |
+ M |
+ BIDMC GR |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD |
+ BXD38 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD |
+ BXD38 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD |
+ BXD39 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD |
+ BXD39 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD |
+ BXD40 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD |
+ BXD40 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD |
+ BXD42 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD |
+ BXD42 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 90 |
+ R994E.2 |
+ BXD |
+ BXD43 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD |
+ BXD43 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD |
+ BXD44 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD |
+ BXD44 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD |
+ BXD45 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD |
+ BXD45 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 96 |
+ R967E.2 |
+ BXD |
+ BXD48 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD |
+ BXD48 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD |
+ BXD51 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD |
+ BXD51 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD |
+ BXD55 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD |
+ BXD55 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 104 |
+ R4176E |
+ BXD |
+ BXD56 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 105 |
+ R4175E |
+ BXD |
+ BXD56 |
+ 53 |
+ M |
+ UTHSC RW |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD |
+ BXD60 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD |
+ BXD60 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD |
+ BXD60 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD |
+ BXD61 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD |
+ BXD61 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ F |
+ UTHSC RW |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD |
+ BXD62 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 113 |
+ R965E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD |
+ BXD63 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD |
+ BXD63 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD |
+ BXD64 |
+ 56 |
+ F |
+ UTHSC RW |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD |
+ BXD64 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD |
+ BXD65 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD |
+ BXD65 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD |
+ BXD66 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD |
+ BXD66 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD |
+ BXD66 |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD |
+ BXD67 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD |
+ BXD68 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD |
+ BXD69 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 129 |
+ R975E.2 |
+ BXD |
+ BXD70 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD |
+ BXD70 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 131 |
+ R4531E |
+ BXD |
+ BXD71 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 132 |
+ R4532E |
+ BXD |
+ BXD71 |
+ 86 |
+ M |
+ UTHSC RW |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD |
+ BXD73 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD |
+ BXD73 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD |
+ BXD75 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD |
+ BXD75 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD |
+ BXD77 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD |
+ BXD77 |
+ 107 |
+ M |
+ UTHSC RW |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD |
+ BXD77 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD |
+ BXD80 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD |
+ BXD80 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD |
+ BXD84 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD |
+ BXD84 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD |
+ BXD85 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD |
+ BXD85 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD |
+ BXD86 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD |
+ BXD86 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD |
+ BXD87 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD |
+ BXD87 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD |
+ BXD89 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD |
+ BXD89 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD |
+ BXD90 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 155 |
+ R859E.2 |
+ BXD |
+ BXD90 |
+ 72 |
+ M |
+ UTHSC RW |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD |
+ BXD92 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD |
+ BXD92 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD |
+ BXD92 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD |
+ BXD96 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD |
+ BXD96 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD |
+ BXD97 |
+ 74 |
+ F |
+ UTHSC RW |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD |
+ BXD97 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD |
+ BXD98 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD |
+ BXD98 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 165 |
+ R4533E |
+ BXD |
+ BXD99 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 166 |
+ R4534E |
+ BXD |
+ BXD99 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 167 |
+ R2885E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 168 |
+ R2883E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 169 |
+ R1700E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 170 |
+ R1704E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 171 |
+ R2605E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 79 |
+ F |
+ UTHSC RW |
+
+
+ | 172 |
+ R0871E |
+ GDP BXD |
+ C57BL/6J |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 173 |
+ R0872E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 174 |
+ R0872E |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 175 |
+ R4507E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 176 |
+ R4508E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 177 |
+ R4505E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 178 |
+ R4506E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 179 |
+ R4535E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ F |
+ JAX |
+
+
+ | 180 |
+ R4536E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ M |
+ JAX |
+
+
+ | 181 |
+ R2564E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ F |
+ JAX |
+
+
+ | 182 |
+ R2580E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ M |
+ JAX |
+
+
+ | 183 |
+ R4537E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 184 |
+ R4538E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 185 |
+ R4539E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 186 |
+ R4540E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 187 |
+ R2600E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 188 |
+ R2604E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 69 |
+ M |
+ UTHSC RW |
+
+
+ | 189 |
+ R1002E.3 |
+ GDP BXD |
+ DBA/2J |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 190 |
+ R4541E |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 191 |
+ R959E.3 |
+ GDP BXD |
+ DBA/2J |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 192 |
+ R2572E.1 |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 193 |
+ R4542E |
+ GDP BXD |
+ DBA/2J |
+ 59 |
+ M |
+ JAX |
+
+
+ | 194 |
+ R2771E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 195 |
+ R2772E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 196 |
+ R2636E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 197 |
+ R2637E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 198 |
+ R0999E.1 |
+ GDP |
+ LG/J |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 199 |
+ R1004E.1 |
+ GDP |
+ LG/J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 200 |
+ R4543E |
+ GDP |
+ LP/J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 201 |
+ R4544E |
+ GDP |
+ LP/J |
+ 65 |
+ M |
+ JAX |
+
+
+ | 202 |
+ R2858E.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 203 |
+ R2919.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 204 |
+ R1688E.1 |
+ GDP |
+ NOD/LtJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 205 |
+ R2566E-2.1 |
+ GDP |
+ NOD/LtJ |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 206 |
+ R4545E |
+ GDP |
+ NZB/BlNJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 207 |
+ R4546E |
+ GDP |
+ NZB/BlNJ |
+ 58 |
+ M |
+ BIDMC GR |
+
+
+ | 208 |
+ R2535E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 209 |
+ R2550E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ JAX |
+
+
+ | 210 |
+ R2817E.3 |
+ GDP |
+ NZW/LacJ |
+ 65 |
+ F |
+ BIDMC GR |
+
+
+ | 211 |
+ R2810E |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 212 |
+ R2810E.3 |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 213 |
+ R4547E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ F |
+ JAX |
+
+
+ | 214 |
+ R4548E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ M |
+ JAX |
+
+
+ | 215 |
+ R2635E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 216 |
+ R2634E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ M |
+ JAX |
+
+
+ | 217 |
+ R2544E.1 |
+ GDP |
+ PWK/PhJ |
+ 63 |
+ F |
+ JAX |
+
+
+ | 218 |
+ R2549E.1 |
+ GDP |
+ PWK/PhJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 219 |
+ R4550E |
+ GDP |
+ SJL/J |
+ 65 |
+ M+F |
+ JAX |
+
+
+ | 220 |
+ R2368E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 221 |
+ R2547E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Eye_m2_1105_m/acknowledgment.rtf b/general/datasets/Eye_m2_1105_m/acknowledgment.rtf
new file mode 100644
index 0000000..3f040d2
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_m/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant. All arrays were processed at the VA Medical Center, Memphis by Weikuan Gu.
diff --git a/general/datasets/Eye_m2_1105_m/cases.rtf b/general/datasets/Eye_m2_1105_m/cases.rtf
new file mode 100644
index 0000000..687970b
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_m/cases.rtf
@@ -0,0 +1,51 @@
+We have used a set of 14 conventional inbred strains, reciprocal F1s between C57BL/6J (B6 or B) and DBA/2J D2 (or D), and 47 BXD recombinant inbred strains. The BXD strains were generated by crossing C57BL/6J with DBA/2J. The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage of D). Physical maps in WebQTL incorporate approximately 2 million B vs D SNPs from Celera Genomics and from the Perlegen-NIEHS sequencing effort. BXD1 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+Please note that BXD24/TyJ (JAX stock number 000031) used in this study is also known as BXD24b/TyJ and has complete retinal degeneration. BXD24a/TyJ, a 1988 F80 stock that has now been rederived, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control.
+
+BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues.
+
+Mouse Diversity Panel (MDP). In addition to the BXD strains, we have profiled a MDP consisting 14 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) also carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene.
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase-negative albino (c) mutant
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list. A tyrosinase-negative albino (c) mutant
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list. Important to note for this Eye dataset, C3H/HeJ is a Pdeb6 mutant with near total photoreceptor loss at maturity.
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HILtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1, aka F1 in some graphs and tables
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
diff --git a/general/datasets/Eye_m2_1105_m/notes.rtf b/general/datasets/Eye_m2_1105_m/notes.rtf
new file mode 100644
index 0000000..48a01ef
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_m/notes.rtf
@@ -0,0 +1,7 @@
+
+CAUTION: DO NOT USE THE PDNN TRANSFORM of the HEIMED EYE Database. USE RMA INSTEAD. This April 2005 data freeze provides estimates of mRNA expression in adult eye from 50 lines of mice including C57BL/6J, DBA/2J, their F1 hybrids, and 47 BXD recombinant inbred strains. Data were generated at UTHSC. Samples were hybridized in small pools (n = 3) to Affymetrix M430 2.0 arrays. This particular data set was processed using the PDNN method of Zhang. To simplify comparison among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
+
+
+
+This text file originally generated by RWW, Nov 4, 2005. Updated by RWW, Nov 5, 2005. Modified Nov 7 with help of Y. Jiao.
+
diff --git a/general/datasets/Eye_m2_1105_m/platform.rtf b/general/datasets/Eye_m2_1105_m/platform.rtf
new file mode 100644
index 0000000..fa332f1
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_m/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are essentially duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contain the same probe sequence as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
diff --git a/general/datasets/Eye_m2_1105_m/processing.rtf b/general/datasets/Eye_m2_1105_m/processing.rtf
new file mode 100644
index 0000000..ff25e0d
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_m/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 7: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
diff --git a/general/datasets/Eye_m2_1105_m/summary.rtf b/general/datasets/Eye_m2_1105_m/summary.rtf
new file mode 100644
index 0000000..6c0fcbd
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_m/summary.rtf
@@ -0,0 +1,3 @@
+
+SUPERCEDED EYE DATASET. The HEIMED November 2005 data set provides estimates of mRNA expression in whole eyes of 63 lines of mice without significant biological replication. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). Pooled RNA samples were hybridized to Affymetrix M430 2.0 arrays. This particular data set was processed using the RMA protocol. To simplify comparison among different transforms, RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Eye_m2_1105_m/tissue.rtf b/general/datasets/Eye_m2_1105_m/tissue.rtf
new file mode 100644
index 0000000..ec39390
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_m/tissue.rtf
@@ -0,0 +1,1554 @@
+
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of RNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. Samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center lead by Drs. John Stuart and Weikuan Gu. All processing steps were performed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. centrigrade until use (one third roughly) or were immediately used for hybridization.
+
+Dealing with Ocular Pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations of brown and beige colored mice tend to have faint residual pigmentation that does affect hybridization signal. The key determinant of this interesting effect is the Tyrp1 (brown) locus on Chr 5 at about 80 Mb. Loci on Chr 4 that map at this location should be considered with skepticism and reviewed carefully. To address this problem Yan Jiao purified total RNA a second time using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204). This was done for 8 colored samples (R2534E2, R2578E2, R1441E2, R2537E2, R2536E2, R2589E2, R2539E2), of which 5 were finally included in this data set (cases in which the strain ID is labeled with asterisks in the table).
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. The current first batch of array data, represents a balanced sample of males and females, but without within-strain replication. We expect to add roughly 100 additional samples inthe next few months.
+
+Batch Structure: This data set consists of a single batch. The great majority of arrays are from a single lot.
+
+The table below summarizes information on strain, age, sex, original CEL filename, several quality control values, and source of mice. Columns labeled "PDNN 2Z outlier" and "RMA 2Z outlier" list the fraction of probe sets with values that deviated more than 2 z units from the mean. Scale factor, background average, present, absent, marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+
+
+
+
+
+
+
+
+
+ | Id |
+ tube ID |
+ group type |
+ Strain |
+ age |
+ sex |
+ original CEL filename |
+ PDNN 2Z outlier |
+ RMA 2Z outlier |
+ scale factor |
+ background average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur(3'/5') |
+ AFFX-GapdhMur(3'/5') |
+ source |
+
+
+ | 1 |
+ R2607E1 |
+ GDP BXD |
+ C57BL/6J |
+ 67 |
+ F |
+ R2605E.CEL |
+ 0.005 |
+ 0.009 |
+ 2.428 |
+ 115.12 |
+ 0.586 |
+ 0.4 |
+ 0.014 |
+ 1.31 |
+ 0.76 |
+ UTM RW |
+
+
+ | 2 |
+ R0872E2 |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ R0872E.CEL |
+ 0.013 |
+ 0.012 |
+ 3.128 |
+ 88.58 |
+ 0.589 |
+ 0.396 |
+ 0.015 |
+ 1.3 |
+ 0.79 |
+ UTM RW |
+
+
+ | 3 |
+ R2572E1 |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ M |
+ R2572E.CEL |
+ 0.041 |
+ 0.051 |
+ 2.406 |
+ 79.07 |
+ 0.555 |
+ 0.429 |
+ 0.016 |
+ 1.37 |
+ 0.79 |
+ UTM RW |
+
+
+ | 4 |
+ R2601E1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ F |
+ R2601E.CEL |
+ 0.003 |
+ 0.004 |
+ 2.545 |
+ 91.96 |
+ 0.589 |
+ 0.396 |
+ 0.015 |
+ 1.44 |
+ 0.78 |
+ UTM RW |
+
+
+ | 5 |
+ R2602E1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ M |
+ R2602E.CEL |
+ 0.001 |
+ 0.004 |
+ 2.599 |
+ 84.44 |
+ 0.597 |
+ 0.388 |
+ 0.015 |
+ 1.37 |
+ 0.78 |
+ UTM RW |
+
+
+ | 6 |
+ R2600E1 |
+ GDP BXD |
+ D2B6F1 |
+ 72 |
+ F |
+ R2600E.CEL |
+ 0.003 |
+ 0.008 |
+ 2.47 |
+ 94.75 |
+ 0.581 |
+ 0.402 |
+ 0.017 |
+ 1.41 |
+ 0.78 |
+ UTM RW |
+
+
+ | 7 |
+ R2604E1 |
+ GDP BXD |
+ D2B6F1 |
+ 69 |
+ M |
+ R2604E.CEL |
+ 0.003 |
+ 0.007 |
+ 2.657 |
+ 89.63 |
+ 0.594 |
+ 0.392 |
+ 0.015 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 8 |
+ R2597E1 |
+ BXD |
+ BXD2 |
+ 61 |
+ M |
+ R2597E.CEL |
+ 0.003 |
+ 0.007 |
+ 2.374 |
+ 93.56 |
+ 0.603 |
+ 0.383 |
+ 0.015 |
+ 1.34 |
+ 0.77 |
+ Glenn |
+
+
+ | 9 |
+ R2591E1 |
+ BXD |
+ BXD5 |
+ 60 |
+ F |
+ R2591E.CEL |
+ 0.051 |
+ 0.009 |
+ 1.7 |
+ 136.48 |
+ 0.585 |
+ 0.4 |
+ 0.015 |
+ 1.33 |
+ 0.78 |
+ Glenn |
+
+
+ | 10 |
+ R2570E1 |
+ BXD |
+ BXD6 |
+ 65 |
+ F |
+ R2570E.CEL |
+ 0.002 |
+ 0.006 |
+ 1.987 |
+ 86.73 |
+ 0.585 |
+ 0.4 |
+ 0.015 |
+ 1.46 |
+ 0.76 |
+ UTM RW |
+
+
+ | 11 |
+ R2538E1 |
+ BXD |
+ BXD8 |
+ 77 |
+ F |
+ R2538E.CEL |
+ 0.037 |
+ 0.028 |
+ 1.905 |
+ 101.98 |
+ 0.612 |
+ 0.373 |
+ 0.015 |
+ 1.52 |
+ 0.79 |
+ UTM RW |
+
+
+ | 12 |
+ R2569E1 |
+ BXD |
+ BXD9 |
+ 67 |
+ M |
+ R2569E.CEL |
+ 0.014 |
+ 0.027 |
+ 1.753 |
+ 87.36 |
+ 0.551 |
+ 0.434 |
+ 0.015 |
+ 2.82 |
+ 3.14 |
+ UTM RW |
+
+
+ | 13 |
+ R2581E1 |
+ BXD |
+ BXD11 |
+ 65 |
+ F |
+ R2581E.CEL |
+ 0.006 |
+ 0.012 |
+ 1.941 |
+ 88.55 |
+ 0.621 |
+ 0.364 |
+ 0.016 |
+ 1.55 |
+ 0.81 |
+ UTM RW |
+
+
+ | 14 |
+ R2543E1 |
+ BXD |
+ BXD12 |
+ 63 |
+ M |
+ R2543E.CEL |
+ 0.036 |
+ 0.007 |
+ 1.605 |
+ 117.69 |
+ 0.586 |
+ 0.399 |
+ 0.016 |
+ 1.43 |
+ 0.77 |
+ UTM RW |
+
+
+ | 15 |
+ R2586E1 |
+ BXD |
+ BXD13 |
+ 60 |
+ F |
+ R2586E.CEL |
+ 0.020 |
+ 0.035 |
+ 2.006 |
+ 73.61 |
+ 0.564 |
+ 0.42 |
+ 0.016 |
+ 2.85 |
+ 3.81 |
+ Glenn |
+
+
+ | 16 |
+ R2557E1 |
+ BXD |
+ BXD14 |
+ 60 |
+ F |
+ R2557E.CEL |
+ 0.014 |
+ 0.017 |
+ 1.83 |
+ 98.76 |
+ 0.625 |
+ 0.361 |
+ 0.014 |
+ 1.31 |
+ 0.78 |
+ Glenn |
+
+
+ | 17 |
+ R2567E1 |
+ BXD |
+ BXD16 |
+ 60 |
+ M |
+ R2567E.CEL |
+ 0.016 |
+ 0.025 |
+ 2.239 |
+ 82.35 |
+ 0.567 |
+ 0.416 |
+ 0.017 |
+ 1.37 |
+ 0.75 |
+ Glenn |
+
+
+ | 18 |
+ R2559E1 |
+ BXD |
+ BXD18 |
+ 59 |
+ M |
+ R2559E.CEL |
+ 0.035 |
+ 0.006 |
+ 1.654 |
+ 103.68 |
+ 0.608 |
+ 0.377 |
+ 0.015 |
+ 1.27 |
+ 0.78 |
+ Glenn |
+
+
+ | 19 |
+ R2560E1 |
+ BXD |
+ BXD19 |
+ 60 |
+ F |
+ R2560E.CEL |
+ 0.026 |
+ 0.007 |
+ 1.792 |
+ 98.33 |
+ 0.609 |
+ 0.375 |
+ 0.016 |
+ 1.35 |
+ 0.8 |
+ Glenn |
+
+
+ | 20 |
+ R2584E1 |
+ BXD |
+ BXD20 |
+ 59 |
+ F |
+ R2584E.CEL |
+ 0.003 |
+ 0.007 |
+ 2.07 |
+ 83.82 |
+ 0.593 |
+ 0.391 |
+ 0.016 |
+ 1.4 |
+ 0.76 |
+ Glenn |
+
+
+ | 21 |
+ R2541E2 |
+ BXD |
+ BXD21 |
+ 61 |
+ M |
+ R2541E2.CEL |
+ 0.049 |
+ 0.036 |
+ 2.625 |
+ 125.08 |
+ 0.56 |
+ 0.424 |
+ 0.015 |
+ 1.29 |
+ 0.78 |
+ UTM RW |
+
+
+ | 22 |
+ R2553E1 |
+ BXD |
+ BXD22 |
+ 58 |
+ F |
+ R2553E.CEL |
+ 0.003 |
+ 0.005 |
+ 1.952 |
+ 111.3 |
+ 0.599 |
+ 0.385 |
+ 0.015 |
+ 1.28 |
+ 0.76 |
+ Glenn |
+
+
+ | 23 |
+ R2558E1 |
+ BXD |
+ BXD23 |
+ 60 |
+ F |
+ R2558E2.CEL |
+ 0.013 |
+ 0.015 |
+ 1.908 |
+ 114.53 |
+ 0.599 |
+ 0.388 |
+ 0.014 |
+ 1.2 |
+ 0.82 |
+ Glenn |
+
+
+ | 24 |
+ R2589E2 |
+ BXD |
+ BXD24-rd* |
+ 59 |
+ M |
+ R2589E2.CEL |
+ 0.098 |
+ 0.098 |
+ 2.606 |
+ 112.19 |
+ 0.575 |
+ 0.409 |
+ 0.016 |
+ 1.24 |
+ 0.8 |
+ Glenn |
+
+
+ | 25 |
+ R2573E1 |
+ BXD |
+ BXD25 |
+ 67 |
+ F |
+ R2573E2.CEL |
+ 0.009 |
+ 0.018 |
+ 3.153 |
+ 71.88 |
+ 0.579 |
+ 0.407 |
+ 0.014 |
+ 1.77 |
+ 0.97 |
+ UAB |
+
+
+ | 26 |
+ R2562E1 |
+ BXD |
+ BXD28 |
+ 60 |
+ F |
+ R2562E.CEL |
+ 0.003 |
+ 0.005 |
+ 1.649 |
+ 116.35 |
+ 0.599 |
+ 0.384 |
+ 0.017 |
+ 1.37 |
+ 0.79 |
+ Glenn |
+
+
+ | 27 |
+ R2561E1 |
+ BXD |
+ BXD29 |
+ 60 |
+ F |
+ R2561E.CEL |
+ 0.019 |
+ 0.029 |
+ 1.952 |
+ 93.32 |
+ 0.583 |
+ 0.402 |
+ 0.015 |
+ 2.19 |
+ 1 |
+ Glenn |
+
+
+ | 28 |
+ R2598E1 |
+ BXD |
+ BXD31 |
+ 61 |
+ M |
+ R2598E.CEL |
+ 0.003 |
+ 0.006 |
+ 1.989 |
+ 106.48 |
+ 0.609 |
+ 0.376 |
+ 0.015 |
+ 1.27 |
+ 0.78 |
+ UTM RW |
+
+
+ | 29 |
+ R2563E1 |
+ BXD |
+ BXD32 |
+ 63 |
+ F |
+ R2563E.CEL |
+ 0.008 |
+ 0.011 |
+ 1.547 |
+ 101.52 |
+ 0.619 |
+ 0.367 |
+ 0.014 |
+ 1.5 |
+ 0.8 |
+ UTM RW |
+
+
+ | 30 |
+ R2542E1 |
+ BXD |
+ BXD33 |
+ 67 |
+ F |
+ R2542E.CEL |
+ 0.010 |
+ 0.016 |
+ 2.128 |
+ 97.08 |
+ 0.565 |
+ 0.418 |
+ 0.016 |
+ 1.91 |
+ 0.93 |
+ UTM RW |
+
+
+ | 31 |
+ R2585E1 |
+ BXD |
+ BXD34 |
+ 60 |
+ M |
+ R2585E.CEL |
+ 0.007 |
+ 0.014 |
+ 2.64 |
+ 75.13 |
+ 0.583 |
+ 0.4 |
+ 0.017 |
+ 1.25 |
+ 0.77 |
+ Glenn |
+
+
+ | 32 |
+ R2532E1 |
+ BXD |
+ BXD38 |
+ 62 |
+ M |
+ R2532E.CEL |
+ 0.002 |
+ 0.003 |
+ 2.038 |
+ 93.65 |
+ 0.598 |
+ 0.387 |
+ 0.015 |
+ 1.37 |
+ 0.8 |
+ UTM RW |
+
+
+ | 33 |
+ R2574E1 |
+ BXD |
+ BXD39 |
+ 70 |
+ F |
+ R2574E.CEL |
+ 0.001 |
+ 0.004 |
+ 1.981 |
+ 90.64 |
+ 0.612 |
+ 0.373 |
+ 0.015 |
+ 1.39 |
+ 0.78 |
+ UTM RW |
+
+
+ | 34 |
+ R2590E1 |
+ BXD |
+ BXD40 |
+ 60 |
+ M |
+ R2590E.CEL |
+ 0.004 |
+ 0.007 |
+ 2.708 |
+ 77.3 |
+ 0.591 |
+ 0.393 |
+ 0.015 |
+ 1.4 |
+ 0.77 |
+ Glenn |
+
+
+ | 35 |
+ R2596E1 |
+ BXD |
+ BXD42 |
+ 59 |
+ M |
+ R2596E.CEL |
+ 0.013 |
+ 0.017 |
+ 2.632 |
+ 108.46 |
+ 0.59 |
+ 0.396 |
+ 0.015 |
+ 1.24 |
+ 0.8 |
+ Glenn |
+
+
+ | 36 |
+ R2605E1 |
+ BXD |
+ BXD43 |
+ 79 |
+ M |
+ R2607E.CEL |
+ 0.003 |
+ 0.006 |
+ 1.817 |
+ 131.22 |
+ 0.605 |
+ 0.382 |
+ 0.013 |
+ 1.32 |
+ 0.8 |
+ UTM RW |
+
+
+ | 37 |
+ R2594E1 |
+ BXD |
+ BXD44 |
+ 63 |
+ F |
+ R2594E.CEL |
+ 0.004 |
+ 0.009 |
+ 1.766 |
+ 117.33 |
+ 0.598 |
+ 0.388 |
+ 0.014 |
+ 1.35 |
+ 0.85 |
+ UTM RW |
+
+
+ | 38 |
+ R2592E1 |
+ BXD |
+ BXD45 |
+ 62 |
+ M |
+ R2592E.CEL |
+ 0.002 |
+ 0.004 |
+ 1.85 |
+ 106.16 |
+ 0.601 |
+ 0.386 |
+ 0.013 |
+ 1.43 |
+ 0.85 |
+ UTM RW |
+
+
+ | 39 |
+ R2606E1 |
+ BXD |
+ BXD48 |
+ 78 |
+ M |
+ R2606E.CEL |
+ 0.003 |
+ 0.010 |
+ 2.556 |
+ 106.16 |
+ 0.589 |
+ 0.397 |
+ 0.014 |
+ 1.35 |
+ 0.83 |
+ UTM RW |
+
+
+ | 40 |
+ R2603E1 |
+ BXD |
+ BXD51 |
+ 66 |
+ F |
+ R2603E.CEL |
+ 0.003 |
+ 0.009 |
+ 2.488 |
+ 115.16 |
+ 0.577 |
+ 0.408 |
+ 0.015 |
+ 1.24 |
+ 0.79 |
+ UTM RW |
+
+
+ | 41 |
+ R2534E2 |
+ BXD |
+ BXD61* |
+ 70 |
+ F |
+ R2534E2.CEL |
+ 0.030 |
+ 0.028 |
+ 2.473 |
+ 117.76 |
+ 0.579 |
+ 0.406 |
+ 0.015 |
+ 1.42 |
+ 0.79 |
+ UTM RW |
+
+
+ | 42 |
+ R2611E1 |
+ BXD |
+ BXD64 |
+ 68 |
+ M |
+ R2611E.CEL |
+ 0.013 |
+ 0.022 |
+ 2.292 |
+ 91.99 |
+ 0.58 |
+ 0.405 |
+ 0.015 |
+ 1.57 |
+ 1.06 |
+ UTM RW |
+
+
+ | 43 |
+ R2583E1 |
+ BXD |
+ BXD65 |
+ 60 |
+ M |
+ R2583E.CEL |
+ 0.005 |
+ 0.010 |
+ 2.492 |
+ 70.43 |
+ 0.569 |
+ 0.415 |
+ 0.016 |
+ 1.67 |
+ 1.01 |
+ UTM RW |
+
+
+ | 44 |
+ R2536E2 |
+ BXD |
+ BXD66* |
+ 64 |
+ F |
+ R2536E2.CEL |
+ 0.039 |
+ 0.065 |
+ 2.74 |
+ 108.62 |
+ 0.561 |
+ 0.423 |
+ 0.017 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 45 |
+ R2551E1 |
+ BXD |
+ BXD68 |
+ 67 |
+ F |
+ R2551E.CEL |
+ 0.037 |
+ 0.039 |
+ 2.493 |
+ 92.38 |
+ 0.543 |
+ 0.441 |
+ 0.016 |
+ 2.91 |
+ 1.55 |
+ UTM RW |
+
+
+ | 46 |
+ R2593E1 |
+ BXD |
+ BXD69 |
+ 59 |
+ F |
+ R2593E.CEL |
+ 0.008 |
+ 0.013 |
+ 1.672 |
+ 127.6 |
+ 0.592 |
+ 0.395 |
+ 0.013 |
+ 1.47 |
+ 0.92 |
+ UTM RW |
+
+
+ | 47 |
+ R2537E2 |
+ BXD |
+ BXD70* |
+ 59 |
+ M |
+ R2537E2.CEL |
+ 0.046 |
+ 0.044 |
+ 2.93 |
+ 98.66 |
+ 0.58 |
+ 0.405 |
+ 0.016 |
+ 1.29 |
+ 0.75 |
+ UTM RW |
+
+
+ | 48 |
+ R2565E1 |
+ BXD |
+ BXD75 |
+ 61 |
+ F |
+ R2565E.CEL |
+ 0.009 |
+ 0.017 |
+ 1.79 |
+ 101.68 |
+ 0.58 |
+ 0.405 |
+ 0.015 |
+ 2.31 |
+ 3.47 |
+ UTM RW |
+
+
+ | 49 |
+ R2579E1 |
+ BXD |
+ BXD80 |
+ 65 |
+ F |
+ R2579E.CEL |
+ 0.005 |
+ 0.010 |
+ 2.419 |
+ 72.13 |
+ 0.592 |
+ 0.394 |
+ 0.015 |
+ 1.73 |
+ 0.82 |
+ UTM RW |
+
+
+ | 50 |
+ R2540E1 |
+ BXD |
+ BXD87 |
+ 63 |
+ M |
+ R2540E.CEL |
+ 0.013 |
+ 0.016 |
+ 2.333 |
+ 93.15 |
+ 0.611 |
+ 0.374 |
+ 0.014 |
+ 1.22 |
+ 0.81 |
+ UTM RW |
+
+
+ | 51 |
+ R2545E1 |
+ BXD |
+ BXD89 |
+ 67 |
+ M |
+ R2546E.CEL |
+ 0.046 |
+ 0.046 |
+ 1.667 |
+ 104.76 |
+ 0.562 |
+ 0.423 |
+ 0.015 |
+ 3.6 |
+ 9.84 |
+ UTM RW |
+
+
+ | 52 |
+ R2578E2 |
+ BXD |
+ BXD90* |
+ 61 |
+ F |
+ R2578E2.CEL |
+ 0.033 |
+ 0.034 |
+ 2.785 |
+ 92.27 |
+ 0.586 |
+ 0.398 |
+ 0.016 |
+ 1.52 |
+ 0.77 |
+ UTM RW |
+
+
+ | 53 |
+ R2554E1 |
+ BXD |
+ BXD96 |
+ 67 |
+ M |
+ R2554E.CEL |
+ 0.004 |
+ 0.004 |
+ 2.177 |
+ 93.02 |
+ 0.602 |
+ 0.383 |
+ 0.015 |
+ 1.46 |
+ 0.77 |
+ UTM RW |
+
+
+ | 54 |
+ R2577E1 |
+ BXD |
+ BXD97 |
+ 55 |
+ M |
+ R2577E.CEL |
+ 0.019 |
+ 0.016 |
+ 2.07 |
+ 76.58 |
+ 0.595 |
+ 0.391 |
+ 0.014 |
+ 1.87 |
+ 1.29 |
+ UTM RW |
+
+
+ | 55 |
+ R2595E1 |
+ GDP |
+ 129S1/SvImJ |
+ 59 |
+ F |
+ R2595E.CEL |
+ 0.017 |
+ 0.021 |
+ 1.792 |
+ 115.39 |
+ 0.61 |
+ 0.375 |
+ 0.015 |
+ 1.46 |
+ 0.77 |
+ UTM RW |
+
+
+ | 56 |
+ R2533E1 |
+ GDP |
+ 129S1/SvImJ |
+ 60 |
+ M |
+ R2533E.CEL |
+ 0.021 |
+ 0.013 |
+ 2.107 |
+ 93.55 |
+ 0.579 |
+ 0.405 |
+ 0.016 |
+ 1.37 |
+ 0.78 |
+ UTM RW |
+
+
+ | 57 |
+ R2546E1 |
+ GDP |
+ A/J |
+ 66 |
+ F |
+ R2545E.CEL |
+ 0.018 |
+ 0.014 |
+ 1.989 |
+ 95.59 |
+ 0.586 |
+ 0.397 |
+ 0.017 |
+ 1.47 |
+ 0.78 |
+ UTM RW |
+
+
+ | 58 |
+ R0754E2 |
+ GDP |
+ A/J |
+ 60 |
+ M |
+ R0754E.CEL |
+ 0.014 |
+ 0.016 |
+ 2.718 |
+ 85.63 |
+ 0.598 |
+ 0.387 |
+ 0.015 |
+ 1.36 |
+ 0.76 |
+ JAX |
+
+
+ | 59 |
+ R1676E1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ F |
+ R1676E.CEL |
+ 0.042 |
+ 0.041 |
+ 2.685 |
+ 98.37 |
+ 0.589 |
+ 0.396 |
+ 0.015 |
+ 1.46 |
+ 0.74 |
+ JAX |
+
+
+ | 60 |
+ R1672E1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ M |
+ R1672E.CEL |
+ 0.022 |
+ 0.022 |
+ 2.216 |
+ 110.52 |
+ 0.599 |
+ 0.386 |
+ 0.015 |
+ 1.26 |
+ 0.8 |
+ JAX |
+
+
+ | 61 |
+ R1700E1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ F |
+ R1700E.CEL |
+ 0.090 |
+ 0.092 |
+ 2.978 |
+ 68.77 |
+ 0.608 |
+ 0.379 |
+ 0.014 |
+ 1.48 |
+ 0.78 |
+ UTM RW |
+
+
+ | 62 |
+ R1704E1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ M |
+ R1704E.CEL |
+ 0.086 |
+ 0.089 |
+ 2.581 |
+ 88.29 |
+ 0.601 |
+ 0.386 |
+ 0.013 |
+ 1.38 |
+ 0.84 |
+ UTM RW |
+
+
+ | 63 |
+ R2564E1 |
+ GDP |
+ CAST/Ei |
+ 64 |
+ F |
+ R2564E.CEL |
+ 0.078 |
+ 0.064 |
+ 1.937 |
+ 88.89 |
+ 0.585 |
+ 0.399 |
+ 0.016 |
+ 1.6 |
+ 0.77 |
+ JAX |
+
+
+ | 64 |
+ R2580E1 |
+ GDP |
+ CAST/Ei |
+ 64 |
+ M |
+ R2580E.CEL |
+ 0.076 |
+ 0.067 |
+ 2.089 |
+ 94.64 |
+ 0.582 |
+ 0.401 |
+ 0.017 |
+ 1.4 |
+ 0.76 |
+ JAX |
+
+
+ | 65 |
+ R2636E1 |
+ GDP |
+ KK/HIJ |
+ 64 |
+ F |
+ R2636E.CEL |
+ 0.023 |
+ 0.026 |
+ 2.61 |
+ 93.1 |
+ 0.589 |
+ 0.395 |
+ 0.015 |
+ 1.39 |
+ 0.76 |
+ UTM RW |
+
+
+ | 66 |
+ R2637E1 |
+ GDP |
+ KK/HIJ |
+ 64 |
+ M |
+ R2637E.CEL |
+ 0.039 |
+ 0.020 |
+ 2.189 |
+ 102.78 |
+ 0.594 |
+ 0.39 |
+ 0.015 |
+ 1.3 |
+ 0.79 |
+ UTM RW |
+
+
+ | 67 |
+ R0999E1 |
+ GDP |
+ LG/J |
+ 57 |
+ F |
+ R0999E.CEL |
+ 0.012 |
+ 0.012 |
+ 2.448 |
+ 82.09 |
+ 0.594 |
+ 0.391 |
+ 0.015 |
+ 1.38 |
+ 0.79 |
+ UTM RW |
+
+
+ | 68 |
+ R1004E1 |
+ GDP |
+ LG/J |
+ 65 |
+ M |
+ R1004E.CEL |
+ 0.013 |
+ 0.015 |
+ 2.438 |
+ 91.71 |
+ 0.587 |
+ 0.398 |
+ 0.015 |
+ 1.38 |
+ 0.79 |
+ UTM RW |
+
+
+ | 69 |
+ R1688E1 |
+ GDP |
+ NOD/LtJ |
+ 66 |
+ F |
+ R1688E.CEL |
+ 0.017 |
+ 0.019 |
+ 2.664 |
+ 97.65 |
+ 0.586 |
+ 0.399 |
+ 0.015 |
+ 1.26 |
+ 0.8 |
+ JAX |
+
+
+ | 70 |
+ R2566E1 |
+ GDP |
+ NOD/LtJ |
+ 76 |
+ M |
+ R2566E2.CEL |
+ 0.019 |
+ 0.025 |
+ 3.031 |
+ 69.44 |
+ 0.598 |
+ 0.388 |
+ 0.015 |
+ 1.38 |
+ 0.75 |
+ UTM RW |
+
+
+ | 71 |
+ R2550E1 |
+ GDP |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ R2550E.CEL |
+ 0.023 |
+ 0.015 |
+ 1.794 |
+ 87.16 |
+ 0.607 |
+ 0.378 |
+ 0.015 |
+ 1.52 |
+ 0.82 |
+ JAX |
+
+
+ | 72 |
+ R2535E1 |
+ GDP |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ R2535E.CEL |
+ 0.046 |
+ 0.025 |
+ 1.893 |
+ 85.67 |
+ 0.604 |
+ 0.382 |
+ 0.014 |
+ 1.41 |
+ 0.85 |
+ JAX |
+
+
+ | 73 |
+ R2634E1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ F |
+ R2635E.CEL |
+ 0.077 |
+ 0.069 |
+ 3.292 |
+ 89.8 |
+ 0.559 |
+ 0.425 |
+ 0.016 |
+ 1.57 |
+ 0.81 |
+ JAX |
+
+
+ | 74 |
+ R2635E1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ M |
+ R2634E.CEL |
+ 0.088 |
+ 0.081 |
+ 3.722 |
+ 80.05 |
+ 0.542 |
+ 0.441 |
+ 0.017 |
+ 1.53 |
+ 0.85 |
+ JAX |
+
+
+ | 75 |
+ R2544E1 |
+ GDP |
+ PWK/PhJ |
+ 63 |
+ F |
+ R2544E.CEL |
+ 0.106 |
+ 0.100 |
+ 2.196 |
+ 107.51 |
+ 0.549 |
+ 0.435 |
+ 0.017 |
+ 1.36 |
+ 0.82 |
+ JAX |
+
+
+ | 76 |
+ R2549E1 |
+ GDP |
+ PWK/PhJ |
+ 83 |
+ M |
+ R2549E.CEL |
+ 0.065 |
+ 0.048 |
+ 2.275 |
+ 83.8 |
+ 0.573 |
+ 0.412 |
+ 0.015 |
+ 1.57 |
+ 0.83 |
+ JAX |
+
+
+ | 77 |
+ R2368E1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ F |
+ R2368E.CEL |
+ 0.025 |
+ 0.028 |
+ 2.567 |
+ 85.7 |
+ 0.595 |
+ 0.391 |
+ 0.014 |
+ 1.29 |
+ 0.74 |
+ UTM RW |
+
+
+ | 78 |
+ R2547E1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ M |
+ R2547E.CEL |
+ 0.032 |
+ 0.021 |
+ 2.135 |
+ 90.04 |
+ 0.582 |
+ 0.401 |
+ 0.016 |
+ 1.32 |
+ 0.77 |
+ UTM RW |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Eye_m2_1105_p/acknowledgment.rtf b/general/datasets/Eye_m2_1105_p/acknowledgment.rtf
new file mode 100644
index 0000000..3f040d2
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_p/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant. All arrays were processed at the VA Medical Center, Memphis by Weikuan Gu.
diff --git a/general/datasets/Eye_m2_1105_p/cases.rtf b/general/datasets/Eye_m2_1105_p/cases.rtf
new file mode 100644
index 0000000..687970b
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_p/cases.rtf
@@ -0,0 +1,51 @@
+We have used a set of 14 conventional inbred strains, reciprocal F1s between C57BL/6J (B6 or B) and DBA/2J D2 (or D), and 47 BXD recombinant inbred strains. The BXD strains were generated by crossing C57BL/6J with DBA/2J. The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage of D). Physical maps in WebQTL incorporate approximately 2 million B vs D SNPs from Celera Genomics and from the Perlegen-NIEHS sequencing effort. BXD1 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+Please note that BXD24/TyJ (JAX stock number 000031) used in this study is also known as BXD24b/TyJ and has complete retinal degeneration. BXD24a/TyJ, a 1988 F80 stock that has now been rederived, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control.
+
+BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues.
+
+Mouse Diversity Panel (MDP). In addition to the BXD strains, we have profiled a MDP consisting 14 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) also carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene.
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase-negative albino (c) mutant
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list. A tyrosinase-negative albino (c) mutant
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list. Important to note for this Eye dataset, C3H/HeJ is a Pdeb6 mutant with near total photoreceptor loss at maturity.
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HILtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1, aka F1 in some graphs and tables
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
diff --git a/general/datasets/Eye_m2_1105_p/notes.rtf b/general/datasets/Eye_m2_1105_p/notes.rtf
new file mode 100644
index 0000000..48a01ef
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_p/notes.rtf
@@ -0,0 +1,7 @@
+
+CAUTION: DO NOT USE THE PDNN TRANSFORM of the HEIMED EYE Database. USE RMA INSTEAD. This April 2005 data freeze provides estimates of mRNA expression in adult eye from 50 lines of mice including C57BL/6J, DBA/2J, their F1 hybrids, and 47 BXD recombinant inbred strains. Data were generated at UTHSC. Samples were hybridized in small pools (n = 3) to Affymetrix M430 2.0 arrays. This particular data set was processed using the PDNN method of Zhang. To simplify comparison among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
+
+
+
+This text file originally generated by RWW, Nov 4, 2005. Updated by RWW, Nov 5, 2005. Modified Nov 7 with help of Y. Jiao.
+
diff --git a/general/datasets/Eye_m2_1105_p/platform.rtf b/general/datasets/Eye_m2_1105_p/platform.rtf
new file mode 100644
index 0000000..fa332f1
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_p/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are essentially duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contain the same probe sequence as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
diff --git a/general/datasets/Eye_m2_1105_p/processing.rtf b/general/datasets/Eye_m2_1105_p/processing.rtf
new file mode 100644
index 0000000..ff25e0d
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_p/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 7: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
diff --git a/general/datasets/Eye_m2_1105_p/summary.rtf b/general/datasets/Eye_m2_1105_p/summary.rtf
new file mode 100644
index 0000000..6c0fcbd
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_p/summary.rtf
@@ -0,0 +1,3 @@
+
+SUPERCEDED EYE DATASET. The HEIMED November 2005 data set provides estimates of mRNA expression in whole eyes of 63 lines of mice without significant biological replication. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). Pooled RNA samples were hybridized to Affymetrix M430 2.0 arrays. This particular data set was processed using the RMA protocol. To simplify comparison among different transforms, RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Eye_m2_1105_p/tissue.rtf b/general/datasets/Eye_m2_1105_p/tissue.rtf
new file mode 100644
index 0000000..ec39390
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_p/tissue.rtf
@@ -0,0 +1,1554 @@
+
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of RNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. Samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center lead by Drs. John Stuart and Weikuan Gu. All processing steps were performed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. centrigrade until use (one third roughly) or were immediately used for hybridization.
+
+Dealing with Ocular Pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations of brown and beige colored mice tend to have faint residual pigmentation that does affect hybridization signal. The key determinant of this interesting effect is the Tyrp1 (brown) locus on Chr 5 at about 80 Mb. Loci on Chr 4 that map at this location should be considered with skepticism and reviewed carefully. To address this problem Yan Jiao purified total RNA a second time using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204). This was done for 8 colored samples (R2534E2, R2578E2, R1441E2, R2537E2, R2536E2, R2589E2, R2539E2), of which 5 were finally included in this data set (cases in which the strain ID is labeled with asterisks in the table).
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. The current first batch of array data, represents a balanced sample of males and females, but without within-strain replication. We expect to add roughly 100 additional samples inthe next few months.
+
+Batch Structure: This data set consists of a single batch. The great majority of arrays are from a single lot.
+
+The table below summarizes information on strain, age, sex, original CEL filename, several quality control values, and source of mice. Columns labeled "PDNN 2Z outlier" and "RMA 2Z outlier" list the fraction of probe sets with values that deviated more than 2 z units from the mean. Scale factor, background average, present, absent, marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+
+
+
+
+
+
+
+
+
+ | Id |
+ tube ID |
+ group type |
+ Strain |
+ age |
+ sex |
+ original CEL filename |
+ PDNN 2Z outlier |
+ RMA 2Z outlier |
+ scale factor |
+ background average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur(3'/5') |
+ AFFX-GapdhMur(3'/5') |
+ source |
+
+
+ | 1 |
+ R2607E1 |
+ GDP BXD |
+ C57BL/6J |
+ 67 |
+ F |
+ R2605E.CEL |
+ 0.005 |
+ 0.009 |
+ 2.428 |
+ 115.12 |
+ 0.586 |
+ 0.4 |
+ 0.014 |
+ 1.31 |
+ 0.76 |
+ UTM RW |
+
+
+ | 2 |
+ R0872E2 |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ R0872E.CEL |
+ 0.013 |
+ 0.012 |
+ 3.128 |
+ 88.58 |
+ 0.589 |
+ 0.396 |
+ 0.015 |
+ 1.3 |
+ 0.79 |
+ UTM RW |
+
+
+ | 3 |
+ R2572E1 |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ M |
+ R2572E.CEL |
+ 0.041 |
+ 0.051 |
+ 2.406 |
+ 79.07 |
+ 0.555 |
+ 0.429 |
+ 0.016 |
+ 1.37 |
+ 0.79 |
+ UTM RW |
+
+
+ | 4 |
+ R2601E1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ F |
+ R2601E.CEL |
+ 0.003 |
+ 0.004 |
+ 2.545 |
+ 91.96 |
+ 0.589 |
+ 0.396 |
+ 0.015 |
+ 1.44 |
+ 0.78 |
+ UTM RW |
+
+
+ | 5 |
+ R2602E1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ M |
+ R2602E.CEL |
+ 0.001 |
+ 0.004 |
+ 2.599 |
+ 84.44 |
+ 0.597 |
+ 0.388 |
+ 0.015 |
+ 1.37 |
+ 0.78 |
+ UTM RW |
+
+
+ | 6 |
+ R2600E1 |
+ GDP BXD |
+ D2B6F1 |
+ 72 |
+ F |
+ R2600E.CEL |
+ 0.003 |
+ 0.008 |
+ 2.47 |
+ 94.75 |
+ 0.581 |
+ 0.402 |
+ 0.017 |
+ 1.41 |
+ 0.78 |
+ UTM RW |
+
+
+ | 7 |
+ R2604E1 |
+ GDP BXD |
+ D2B6F1 |
+ 69 |
+ M |
+ R2604E.CEL |
+ 0.003 |
+ 0.007 |
+ 2.657 |
+ 89.63 |
+ 0.594 |
+ 0.392 |
+ 0.015 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 8 |
+ R2597E1 |
+ BXD |
+ BXD2 |
+ 61 |
+ M |
+ R2597E.CEL |
+ 0.003 |
+ 0.007 |
+ 2.374 |
+ 93.56 |
+ 0.603 |
+ 0.383 |
+ 0.015 |
+ 1.34 |
+ 0.77 |
+ Glenn |
+
+
+ | 9 |
+ R2591E1 |
+ BXD |
+ BXD5 |
+ 60 |
+ F |
+ R2591E.CEL |
+ 0.051 |
+ 0.009 |
+ 1.7 |
+ 136.48 |
+ 0.585 |
+ 0.4 |
+ 0.015 |
+ 1.33 |
+ 0.78 |
+ Glenn |
+
+
+ | 10 |
+ R2570E1 |
+ BXD |
+ BXD6 |
+ 65 |
+ F |
+ R2570E.CEL |
+ 0.002 |
+ 0.006 |
+ 1.987 |
+ 86.73 |
+ 0.585 |
+ 0.4 |
+ 0.015 |
+ 1.46 |
+ 0.76 |
+ UTM RW |
+
+
+ | 11 |
+ R2538E1 |
+ BXD |
+ BXD8 |
+ 77 |
+ F |
+ R2538E.CEL |
+ 0.037 |
+ 0.028 |
+ 1.905 |
+ 101.98 |
+ 0.612 |
+ 0.373 |
+ 0.015 |
+ 1.52 |
+ 0.79 |
+ UTM RW |
+
+
+ | 12 |
+ R2569E1 |
+ BXD |
+ BXD9 |
+ 67 |
+ M |
+ R2569E.CEL |
+ 0.014 |
+ 0.027 |
+ 1.753 |
+ 87.36 |
+ 0.551 |
+ 0.434 |
+ 0.015 |
+ 2.82 |
+ 3.14 |
+ UTM RW |
+
+
+ | 13 |
+ R2581E1 |
+ BXD |
+ BXD11 |
+ 65 |
+ F |
+ R2581E.CEL |
+ 0.006 |
+ 0.012 |
+ 1.941 |
+ 88.55 |
+ 0.621 |
+ 0.364 |
+ 0.016 |
+ 1.55 |
+ 0.81 |
+ UTM RW |
+
+
+ | 14 |
+ R2543E1 |
+ BXD |
+ BXD12 |
+ 63 |
+ M |
+ R2543E.CEL |
+ 0.036 |
+ 0.007 |
+ 1.605 |
+ 117.69 |
+ 0.586 |
+ 0.399 |
+ 0.016 |
+ 1.43 |
+ 0.77 |
+ UTM RW |
+
+
+ | 15 |
+ R2586E1 |
+ BXD |
+ BXD13 |
+ 60 |
+ F |
+ R2586E.CEL |
+ 0.020 |
+ 0.035 |
+ 2.006 |
+ 73.61 |
+ 0.564 |
+ 0.42 |
+ 0.016 |
+ 2.85 |
+ 3.81 |
+ Glenn |
+
+
+ | 16 |
+ R2557E1 |
+ BXD |
+ BXD14 |
+ 60 |
+ F |
+ R2557E.CEL |
+ 0.014 |
+ 0.017 |
+ 1.83 |
+ 98.76 |
+ 0.625 |
+ 0.361 |
+ 0.014 |
+ 1.31 |
+ 0.78 |
+ Glenn |
+
+
+ | 17 |
+ R2567E1 |
+ BXD |
+ BXD16 |
+ 60 |
+ M |
+ R2567E.CEL |
+ 0.016 |
+ 0.025 |
+ 2.239 |
+ 82.35 |
+ 0.567 |
+ 0.416 |
+ 0.017 |
+ 1.37 |
+ 0.75 |
+ Glenn |
+
+
+ | 18 |
+ R2559E1 |
+ BXD |
+ BXD18 |
+ 59 |
+ M |
+ R2559E.CEL |
+ 0.035 |
+ 0.006 |
+ 1.654 |
+ 103.68 |
+ 0.608 |
+ 0.377 |
+ 0.015 |
+ 1.27 |
+ 0.78 |
+ Glenn |
+
+
+ | 19 |
+ R2560E1 |
+ BXD |
+ BXD19 |
+ 60 |
+ F |
+ R2560E.CEL |
+ 0.026 |
+ 0.007 |
+ 1.792 |
+ 98.33 |
+ 0.609 |
+ 0.375 |
+ 0.016 |
+ 1.35 |
+ 0.8 |
+ Glenn |
+
+
+ | 20 |
+ R2584E1 |
+ BXD |
+ BXD20 |
+ 59 |
+ F |
+ R2584E.CEL |
+ 0.003 |
+ 0.007 |
+ 2.07 |
+ 83.82 |
+ 0.593 |
+ 0.391 |
+ 0.016 |
+ 1.4 |
+ 0.76 |
+ Glenn |
+
+
+ | 21 |
+ R2541E2 |
+ BXD |
+ BXD21 |
+ 61 |
+ M |
+ R2541E2.CEL |
+ 0.049 |
+ 0.036 |
+ 2.625 |
+ 125.08 |
+ 0.56 |
+ 0.424 |
+ 0.015 |
+ 1.29 |
+ 0.78 |
+ UTM RW |
+
+
+ | 22 |
+ R2553E1 |
+ BXD |
+ BXD22 |
+ 58 |
+ F |
+ R2553E.CEL |
+ 0.003 |
+ 0.005 |
+ 1.952 |
+ 111.3 |
+ 0.599 |
+ 0.385 |
+ 0.015 |
+ 1.28 |
+ 0.76 |
+ Glenn |
+
+
+ | 23 |
+ R2558E1 |
+ BXD |
+ BXD23 |
+ 60 |
+ F |
+ R2558E2.CEL |
+ 0.013 |
+ 0.015 |
+ 1.908 |
+ 114.53 |
+ 0.599 |
+ 0.388 |
+ 0.014 |
+ 1.2 |
+ 0.82 |
+ Glenn |
+
+
+ | 24 |
+ R2589E2 |
+ BXD |
+ BXD24-rd* |
+ 59 |
+ M |
+ R2589E2.CEL |
+ 0.098 |
+ 0.098 |
+ 2.606 |
+ 112.19 |
+ 0.575 |
+ 0.409 |
+ 0.016 |
+ 1.24 |
+ 0.8 |
+ Glenn |
+
+
+ | 25 |
+ R2573E1 |
+ BXD |
+ BXD25 |
+ 67 |
+ F |
+ R2573E2.CEL |
+ 0.009 |
+ 0.018 |
+ 3.153 |
+ 71.88 |
+ 0.579 |
+ 0.407 |
+ 0.014 |
+ 1.77 |
+ 0.97 |
+ UAB |
+
+
+ | 26 |
+ R2562E1 |
+ BXD |
+ BXD28 |
+ 60 |
+ F |
+ R2562E.CEL |
+ 0.003 |
+ 0.005 |
+ 1.649 |
+ 116.35 |
+ 0.599 |
+ 0.384 |
+ 0.017 |
+ 1.37 |
+ 0.79 |
+ Glenn |
+
+
+ | 27 |
+ R2561E1 |
+ BXD |
+ BXD29 |
+ 60 |
+ F |
+ R2561E.CEL |
+ 0.019 |
+ 0.029 |
+ 1.952 |
+ 93.32 |
+ 0.583 |
+ 0.402 |
+ 0.015 |
+ 2.19 |
+ 1 |
+ Glenn |
+
+
+ | 28 |
+ R2598E1 |
+ BXD |
+ BXD31 |
+ 61 |
+ M |
+ R2598E.CEL |
+ 0.003 |
+ 0.006 |
+ 1.989 |
+ 106.48 |
+ 0.609 |
+ 0.376 |
+ 0.015 |
+ 1.27 |
+ 0.78 |
+ UTM RW |
+
+
+ | 29 |
+ R2563E1 |
+ BXD |
+ BXD32 |
+ 63 |
+ F |
+ R2563E.CEL |
+ 0.008 |
+ 0.011 |
+ 1.547 |
+ 101.52 |
+ 0.619 |
+ 0.367 |
+ 0.014 |
+ 1.5 |
+ 0.8 |
+ UTM RW |
+
+
+ | 30 |
+ R2542E1 |
+ BXD |
+ BXD33 |
+ 67 |
+ F |
+ R2542E.CEL |
+ 0.010 |
+ 0.016 |
+ 2.128 |
+ 97.08 |
+ 0.565 |
+ 0.418 |
+ 0.016 |
+ 1.91 |
+ 0.93 |
+ UTM RW |
+
+
+ | 31 |
+ R2585E1 |
+ BXD |
+ BXD34 |
+ 60 |
+ M |
+ R2585E.CEL |
+ 0.007 |
+ 0.014 |
+ 2.64 |
+ 75.13 |
+ 0.583 |
+ 0.4 |
+ 0.017 |
+ 1.25 |
+ 0.77 |
+ Glenn |
+
+
+ | 32 |
+ R2532E1 |
+ BXD |
+ BXD38 |
+ 62 |
+ M |
+ R2532E.CEL |
+ 0.002 |
+ 0.003 |
+ 2.038 |
+ 93.65 |
+ 0.598 |
+ 0.387 |
+ 0.015 |
+ 1.37 |
+ 0.8 |
+ UTM RW |
+
+
+ | 33 |
+ R2574E1 |
+ BXD |
+ BXD39 |
+ 70 |
+ F |
+ R2574E.CEL |
+ 0.001 |
+ 0.004 |
+ 1.981 |
+ 90.64 |
+ 0.612 |
+ 0.373 |
+ 0.015 |
+ 1.39 |
+ 0.78 |
+ UTM RW |
+
+
+ | 34 |
+ R2590E1 |
+ BXD |
+ BXD40 |
+ 60 |
+ M |
+ R2590E.CEL |
+ 0.004 |
+ 0.007 |
+ 2.708 |
+ 77.3 |
+ 0.591 |
+ 0.393 |
+ 0.015 |
+ 1.4 |
+ 0.77 |
+ Glenn |
+
+
+ | 35 |
+ R2596E1 |
+ BXD |
+ BXD42 |
+ 59 |
+ M |
+ R2596E.CEL |
+ 0.013 |
+ 0.017 |
+ 2.632 |
+ 108.46 |
+ 0.59 |
+ 0.396 |
+ 0.015 |
+ 1.24 |
+ 0.8 |
+ Glenn |
+
+
+ | 36 |
+ R2605E1 |
+ BXD |
+ BXD43 |
+ 79 |
+ M |
+ R2607E.CEL |
+ 0.003 |
+ 0.006 |
+ 1.817 |
+ 131.22 |
+ 0.605 |
+ 0.382 |
+ 0.013 |
+ 1.32 |
+ 0.8 |
+ UTM RW |
+
+
+ | 37 |
+ R2594E1 |
+ BXD |
+ BXD44 |
+ 63 |
+ F |
+ R2594E.CEL |
+ 0.004 |
+ 0.009 |
+ 1.766 |
+ 117.33 |
+ 0.598 |
+ 0.388 |
+ 0.014 |
+ 1.35 |
+ 0.85 |
+ UTM RW |
+
+
+ | 38 |
+ R2592E1 |
+ BXD |
+ BXD45 |
+ 62 |
+ M |
+ R2592E.CEL |
+ 0.002 |
+ 0.004 |
+ 1.85 |
+ 106.16 |
+ 0.601 |
+ 0.386 |
+ 0.013 |
+ 1.43 |
+ 0.85 |
+ UTM RW |
+
+
+ | 39 |
+ R2606E1 |
+ BXD |
+ BXD48 |
+ 78 |
+ M |
+ R2606E.CEL |
+ 0.003 |
+ 0.010 |
+ 2.556 |
+ 106.16 |
+ 0.589 |
+ 0.397 |
+ 0.014 |
+ 1.35 |
+ 0.83 |
+ UTM RW |
+
+
+ | 40 |
+ R2603E1 |
+ BXD |
+ BXD51 |
+ 66 |
+ F |
+ R2603E.CEL |
+ 0.003 |
+ 0.009 |
+ 2.488 |
+ 115.16 |
+ 0.577 |
+ 0.408 |
+ 0.015 |
+ 1.24 |
+ 0.79 |
+ UTM RW |
+
+
+ | 41 |
+ R2534E2 |
+ BXD |
+ BXD61* |
+ 70 |
+ F |
+ R2534E2.CEL |
+ 0.030 |
+ 0.028 |
+ 2.473 |
+ 117.76 |
+ 0.579 |
+ 0.406 |
+ 0.015 |
+ 1.42 |
+ 0.79 |
+ UTM RW |
+
+
+ | 42 |
+ R2611E1 |
+ BXD |
+ BXD64 |
+ 68 |
+ M |
+ R2611E.CEL |
+ 0.013 |
+ 0.022 |
+ 2.292 |
+ 91.99 |
+ 0.58 |
+ 0.405 |
+ 0.015 |
+ 1.57 |
+ 1.06 |
+ UTM RW |
+
+
+ | 43 |
+ R2583E1 |
+ BXD |
+ BXD65 |
+ 60 |
+ M |
+ R2583E.CEL |
+ 0.005 |
+ 0.010 |
+ 2.492 |
+ 70.43 |
+ 0.569 |
+ 0.415 |
+ 0.016 |
+ 1.67 |
+ 1.01 |
+ UTM RW |
+
+
+ | 44 |
+ R2536E2 |
+ BXD |
+ BXD66* |
+ 64 |
+ F |
+ R2536E2.CEL |
+ 0.039 |
+ 0.065 |
+ 2.74 |
+ 108.62 |
+ 0.561 |
+ 0.423 |
+ 0.017 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 45 |
+ R2551E1 |
+ BXD |
+ BXD68 |
+ 67 |
+ F |
+ R2551E.CEL |
+ 0.037 |
+ 0.039 |
+ 2.493 |
+ 92.38 |
+ 0.543 |
+ 0.441 |
+ 0.016 |
+ 2.91 |
+ 1.55 |
+ UTM RW |
+
+
+ | 46 |
+ R2593E1 |
+ BXD |
+ BXD69 |
+ 59 |
+ F |
+ R2593E.CEL |
+ 0.008 |
+ 0.013 |
+ 1.672 |
+ 127.6 |
+ 0.592 |
+ 0.395 |
+ 0.013 |
+ 1.47 |
+ 0.92 |
+ UTM RW |
+
+
+ | 47 |
+ R2537E2 |
+ BXD |
+ BXD70* |
+ 59 |
+ M |
+ R2537E2.CEL |
+ 0.046 |
+ 0.044 |
+ 2.93 |
+ 98.66 |
+ 0.58 |
+ 0.405 |
+ 0.016 |
+ 1.29 |
+ 0.75 |
+ UTM RW |
+
+
+ | 48 |
+ R2565E1 |
+ BXD |
+ BXD75 |
+ 61 |
+ F |
+ R2565E.CEL |
+ 0.009 |
+ 0.017 |
+ 1.79 |
+ 101.68 |
+ 0.58 |
+ 0.405 |
+ 0.015 |
+ 2.31 |
+ 3.47 |
+ UTM RW |
+
+
+ | 49 |
+ R2579E1 |
+ BXD |
+ BXD80 |
+ 65 |
+ F |
+ R2579E.CEL |
+ 0.005 |
+ 0.010 |
+ 2.419 |
+ 72.13 |
+ 0.592 |
+ 0.394 |
+ 0.015 |
+ 1.73 |
+ 0.82 |
+ UTM RW |
+
+
+ | 50 |
+ R2540E1 |
+ BXD |
+ BXD87 |
+ 63 |
+ M |
+ R2540E.CEL |
+ 0.013 |
+ 0.016 |
+ 2.333 |
+ 93.15 |
+ 0.611 |
+ 0.374 |
+ 0.014 |
+ 1.22 |
+ 0.81 |
+ UTM RW |
+
+
+ | 51 |
+ R2545E1 |
+ BXD |
+ BXD89 |
+ 67 |
+ M |
+ R2546E.CEL |
+ 0.046 |
+ 0.046 |
+ 1.667 |
+ 104.76 |
+ 0.562 |
+ 0.423 |
+ 0.015 |
+ 3.6 |
+ 9.84 |
+ UTM RW |
+
+
+ | 52 |
+ R2578E2 |
+ BXD |
+ BXD90* |
+ 61 |
+ F |
+ R2578E2.CEL |
+ 0.033 |
+ 0.034 |
+ 2.785 |
+ 92.27 |
+ 0.586 |
+ 0.398 |
+ 0.016 |
+ 1.52 |
+ 0.77 |
+ UTM RW |
+
+
+ | 53 |
+ R2554E1 |
+ BXD |
+ BXD96 |
+ 67 |
+ M |
+ R2554E.CEL |
+ 0.004 |
+ 0.004 |
+ 2.177 |
+ 93.02 |
+ 0.602 |
+ 0.383 |
+ 0.015 |
+ 1.46 |
+ 0.77 |
+ UTM RW |
+
+
+ | 54 |
+ R2577E1 |
+ BXD |
+ BXD97 |
+ 55 |
+ M |
+ R2577E.CEL |
+ 0.019 |
+ 0.016 |
+ 2.07 |
+ 76.58 |
+ 0.595 |
+ 0.391 |
+ 0.014 |
+ 1.87 |
+ 1.29 |
+ UTM RW |
+
+
+ | 55 |
+ R2595E1 |
+ GDP |
+ 129S1/SvImJ |
+ 59 |
+ F |
+ R2595E.CEL |
+ 0.017 |
+ 0.021 |
+ 1.792 |
+ 115.39 |
+ 0.61 |
+ 0.375 |
+ 0.015 |
+ 1.46 |
+ 0.77 |
+ UTM RW |
+
+
+ | 56 |
+ R2533E1 |
+ GDP |
+ 129S1/SvImJ |
+ 60 |
+ M |
+ R2533E.CEL |
+ 0.021 |
+ 0.013 |
+ 2.107 |
+ 93.55 |
+ 0.579 |
+ 0.405 |
+ 0.016 |
+ 1.37 |
+ 0.78 |
+ UTM RW |
+
+
+ | 57 |
+ R2546E1 |
+ GDP |
+ A/J |
+ 66 |
+ F |
+ R2545E.CEL |
+ 0.018 |
+ 0.014 |
+ 1.989 |
+ 95.59 |
+ 0.586 |
+ 0.397 |
+ 0.017 |
+ 1.47 |
+ 0.78 |
+ UTM RW |
+
+
+ | 58 |
+ R0754E2 |
+ GDP |
+ A/J |
+ 60 |
+ M |
+ R0754E.CEL |
+ 0.014 |
+ 0.016 |
+ 2.718 |
+ 85.63 |
+ 0.598 |
+ 0.387 |
+ 0.015 |
+ 1.36 |
+ 0.76 |
+ JAX |
+
+
+ | 59 |
+ R1676E1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ F |
+ R1676E.CEL |
+ 0.042 |
+ 0.041 |
+ 2.685 |
+ 98.37 |
+ 0.589 |
+ 0.396 |
+ 0.015 |
+ 1.46 |
+ 0.74 |
+ JAX |
+
+
+ | 60 |
+ R1672E1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ M |
+ R1672E.CEL |
+ 0.022 |
+ 0.022 |
+ 2.216 |
+ 110.52 |
+ 0.599 |
+ 0.386 |
+ 0.015 |
+ 1.26 |
+ 0.8 |
+ JAX |
+
+
+ | 61 |
+ R1700E1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ F |
+ R1700E.CEL |
+ 0.090 |
+ 0.092 |
+ 2.978 |
+ 68.77 |
+ 0.608 |
+ 0.379 |
+ 0.014 |
+ 1.48 |
+ 0.78 |
+ UTM RW |
+
+
+ | 62 |
+ R1704E1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ M |
+ R1704E.CEL |
+ 0.086 |
+ 0.089 |
+ 2.581 |
+ 88.29 |
+ 0.601 |
+ 0.386 |
+ 0.013 |
+ 1.38 |
+ 0.84 |
+ UTM RW |
+
+
+ | 63 |
+ R2564E1 |
+ GDP |
+ CAST/Ei |
+ 64 |
+ F |
+ R2564E.CEL |
+ 0.078 |
+ 0.064 |
+ 1.937 |
+ 88.89 |
+ 0.585 |
+ 0.399 |
+ 0.016 |
+ 1.6 |
+ 0.77 |
+ JAX |
+
+
+ | 64 |
+ R2580E1 |
+ GDP |
+ CAST/Ei |
+ 64 |
+ M |
+ R2580E.CEL |
+ 0.076 |
+ 0.067 |
+ 2.089 |
+ 94.64 |
+ 0.582 |
+ 0.401 |
+ 0.017 |
+ 1.4 |
+ 0.76 |
+ JAX |
+
+
+ | 65 |
+ R2636E1 |
+ GDP |
+ KK/HIJ |
+ 64 |
+ F |
+ R2636E.CEL |
+ 0.023 |
+ 0.026 |
+ 2.61 |
+ 93.1 |
+ 0.589 |
+ 0.395 |
+ 0.015 |
+ 1.39 |
+ 0.76 |
+ UTM RW |
+
+
+ | 66 |
+ R2637E1 |
+ GDP |
+ KK/HIJ |
+ 64 |
+ M |
+ R2637E.CEL |
+ 0.039 |
+ 0.020 |
+ 2.189 |
+ 102.78 |
+ 0.594 |
+ 0.39 |
+ 0.015 |
+ 1.3 |
+ 0.79 |
+ UTM RW |
+
+
+ | 67 |
+ R0999E1 |
+ GDP |
+ LG/J |
+ 57 |
+ F |
+ R0999E.CEL |
+ 0.012 |
+ 0.012 |
+ 2.448 |
+ 82.09 |
+ 0.594 |
+ 0.391 |
+ 0.015 |
+ 1.38 |
+ 0.79 |
+ UTM RW |
+
+
+ | 68 |
+ R1004E1 |
+ GDP |
+ LG/J |
+ 65 |
+ M |
+ R1004E.CEL |
+ 0.013 |
+ 0.015 |
+ 2.438 |
+ 91.71 |
+ 0.587 |
+ 0.398 |
+ 0.015 |
+ 1.38 |
+ 0.79 |
+ UTM RW |
+
+
+ | 69 |
+ R1688E1 |
+ GDP |
+ NOD/LtJ |
+ 66 |
+ F |
+ R1688E.CEL |
+ 0.017 |
+ 0.019 |
+ 2.664 |
+ 97.65 |
+ 0.586 |
+ 0.399 |
+ 0.015 |
+ 1.26 |
+ 0.8 |
+ JAX |
+
+
+ | 70 |
+ R2566E1 |
+ GDP |
+ NOD/LtJ |
+ 76 |
+ M |
+ R2566E2.CEL |
+ 0.019 |
+ 0.025 |
+ 3.031 |
+ 69.44 |
+ 0.598 |
+ 0.388 |
+ 0.015 |
+ 1.38 |
+ 0.75 |
+ UTM RW |
+
+
+ | 71 |
+ R2550E1 |
+ GDP |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ R2550E.CEL |
+ 0.023 |
+ 0.015 |
+ 1.794 |
+ 87.16 |
+ 0.607 |
+ 0.378 |
+ 0.015 |
+ 1.52 |
+ 0.82 |
+ JAX |
+
+
+ | 72 |
+ R2535E1 |
+ GDP |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ R2535E.CEL |
+ 0.046 |
+ 0.025 |
+ 1.893 |
+ 85.67 |
+ 0.604 |
+ 0.382 |
+ 0.014 |
+ 1.41 |
+ 0.85 |
+ JAX |
+
+
+ | 73 |
+ R2634E1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ F |
+ R2635E.CEL |
+ 0.077 |
+ 0.069 |
+ 3.292 |
+ 89.8 |
+ 0.559 |
+ 0.425 |
+ 0.016 |
+ 1.57 |
+ 0.81 |
+ JAX |
+
+
+ | 74 |
+ R2635E1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ M |
+ R2634E.CEL |
+ 0.088 |
+ 0.081 |
+ 3.722 |
+ 80.05 |
+ 0.542 |
+ 0.441 |
+ 0.017 |
+ 1.53 |
+ 0.85 |
+ JAX |
+
+
+ | 75 |
+ R2544E1 |
+ GDP |
+ PWK/PhJ |
+ 63 |
+ F |
+ R2544E.CEL |
+ 0.106 |
+ 0.100 |
+ 2.196 |
+ 107.51 |
+ 0.549 |
+ 0.435 |
+ 0.017 |
+ 1.36 |
+ 0.82 |
+ JAX |
+
+
+ | 76 |
+ R2549E1 |
+ GDP |
+ PWK/PhJ |
+ 83 |
+ M |
+ R2549E.CEL |
+ 0.065 |
+ 0.048 |
+ 2.275 |
+ 83.8 |
+ 0.573 |
+ 0.412 |
+ 0.015 |
+ 1.57 |
+ 0.83 |
+ JAX |
+
+
+ | 77 |
+ R2368E1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ F |
+ R2368E.CEL |
+ 0.025 |
+ 0.028 |
+ 2.567 |
+ 85.7 |
+ 0.595 |
+ 0.391 |
+ 0.014 |
+ 1.29 |
+ 0.74 |
+ UTM RW |
+
+
+ | 78 |
+ R2547E1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ M |
+ R2547E.CEL |
+ 0.032 |
+ 0.021 |
+ 2.135 |
+ 90.04 |
+ 0.582 |
+ 0.401 |
+ 0.016 |
+ 1.32 |
+ 0.77 |
+ UTM RW |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Eye_m2_1105_r/acknowledgment.rtf b/general/datasets/Eye_m2_1105_r/acknowledgment.rtf
new file mode 100644
index 0000000..3f040d2
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant. All arrays were processed at the VA Medical Center, Memphis by Weikuan Gu.
diff --git a/general/datasets/Eye_m2_1105_r/cases.rtf b/general/datasets/Eye_m2_1105_r/cases.rtf
new file mode 100644
index 0000000..687970b
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_r/cases.rtf
@@ -0,0 +1,51 @@
+We have used a set of 14 conventional inbred strains, reciprocal F1s between C57BL/6J (B6 or B) and DBA/2J D2 (or D), and 47 BXD recombinant inbred strains. The BXD strains were generated by crossing C57BL/6J with DBA/2J. The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage of D). Physical maps in WebQTL incorporate approximately 2 million B vs D SNPs from Celera Genomics and from the Perlegen-NIEHS sequencing effort. BXD1 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+Please note that BXD24/TyJ (JAX stock number 000031) used in this study is also known as BXD24b/TyJ and has complete retinal degeneration. BXD24a/TyJ, a 1988 F80 stock that has now been rederived, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control.
+
+BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues.
+
+Mouse Diversity Panel (MDP). In addition to the BXD strains, we have profiled a MDP consisting 14 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) also carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene.
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase-negative albino (c) mutant
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list. A tyrosinase-negative albino (c) mutant
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list. Important to note for this Eye dataset, C3H/HeJ is a Pdeb6 mutant with near total photoreceptor loss at maturity.
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HILtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1, aka F1 in some graphs and tables
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
diff --git a/general/datasets/Eye_m2_1105_r/notes.rtf b/general/datasets/Eye_m2_1105_r/notes.rtf
new file mode 100644
index 0000000..48a01ef
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_r/notes.rtf
@@ -0,0 +1,7 @@
+
+CAUTION: DO NOT USE THE PDNN TRANSFORM of the HEIMED EYE Database. USE RMA INSTEAD. This April 2005 data freeze provides estimates of mRNA expression in adult eye from 50 lines of mice including C57BL/6J, DBA/2J, their F1 hybrids, and 47 BXD recombinant inbred strains. Data were generated at UTHSC. Samples were hybridized in small pools (n = 3) to Affymetrix M430 2.0 arrays. This particular data set was processed using the PDNN method of Zhang. To simplify comparison among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
+
+
+
+This text file originally generated by RWW, Nov 4, 2005. Updated by RWW, Nov 5, 2005. Modified Nov 7 with help of Y. Jiao.
+
diff --git a/general/datasets/Eye_m2_1105_r/platform.rtf b/general/datasets/Eye_m2_1105_r/platform.rtf
new file mode 100644
index 0000000..fa332f1
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are essentially duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contain the same probe sequence as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
diff --git a/general/datasets/Eye_m2_1105_r/processing.rtf b/general/datasets/Eye_m2_1105_r/processing.rtf
new file mode 100644
index 0000000..ff25e0d
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_r/processing.rtf
@@ -0,0 +1,11 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 7: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
diff --git a/general/datasets/Eye_m2_1105_r/summary.rtf b/general/datasets/Eye_m2_1105_r/summary.rtf
new file mode 100644
index 0000000..6c0fcbd
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_r/summary.rtf
@@ -0,0 +1,3 @@
+
+SUPERCEDED EYE DATASET. The HEIMED November 2005 data set provides estimates of mRNA expression in whole eyes of 63 lines of mice without significant biological replication. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). Pooled RNA samples were hybridized to Affymetrix M430 2.0 arrays. This particular data set was processed using the RMA protocol. To simplify comparison among different transforms, RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Eye_m2_1105_r/tissue.rtf b/general/datasets/Eye_m2_1105_r/tissue.rtf
new file mode 100644
index 0000000..ec39390
--- /dev/null
+++ b/general/datasets/Eye_m2_1105_r/tissue.rtf
@@ -0,0 +1,1554 @@
+
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of RNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. Samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center lead by Drs. John Stuart and Weikuan Gu. All processing steps were performed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. centrigrade until use (one third roughly) or were immediately used for hybridization.
+
+Dealing with Ocular Pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations of brown and beige colored mice tend to have faint residual pigmentation that does affect hybridization signal. The key determinant of this interesting effect is the Tyrp1 (brown) locus on Chr 5 at about 80 Mb. Loci on Chr 4 that map at this location should be considered with skepticism and reviewed carefully. To address this problem Yan Jiao purified total RNA a second time using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204). This was done for 8 colored samples (R2534E2, R2578E2, R1441E2, R2537E2, R2536E2, R2589E2, R2539E2), of which 5 were finally included in this data set (cases in which the strain ID is labeled with asterisks in the table).
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. The current first batch of array data, represents a balanced sample of males and females, but without within-strain replication. We expect to add roughly 100 additional samples inthe next few months.
+
+Batch Structure: This data set consists of a single batch. The great majority of arrays are from a single lot.
+
+The table below summarizes information on strain, age, sex, original CEL filename, several quality control values, and source of mice. Columns labeled "PDNN 2Z outlier" and "RMA 2Z outlier" list the fraction of probe sets with values that deviated more than 2 z units from the mean. Scale factor, background average, present, absent, marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+
+
+
+
+
+
+
+
+
+ | Id |
+ tube ID |
+ group type |
+ Strain |
+ age |
+ sex |
+ original CEL filename |
+ PDNN 2Z outlier |
+ RMA 2Z outlier |
+ scale factor |
+ background average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur(3'/5') |
+ AFFX-GapdhMur(3'/5') |
+ source |
+
+
+ | 1 |
+ R2607E1 |
+ GDP BXD |
+ C57BL/6J |
+ 67 |
+ F |
+ R2605E.CEL |
+ 0.005 |
+ 0.009 |
+ 2.428 |
+ 115.12 |
+ 0.586 |
+ 0.4 |
+ 0.014 |
+ 1.31 |
+ 0.76 |
+ UTM RW |
+
+
+ | 2 |
+ R0872E2 |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ R0872E.CEL |
+ 0.013 |
+ 0.012 |
+ 3.128 |
+ 88.58 |
+ 0.589 |
+ 0.396 |
+ 0.015 |
+ 1.3 |
+ 0.79 |
+ UTM RW |
+
+
+ | 3 |
+ R2572E1 |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ M |
+ R2572E.CEL |
+ 0.041 |
+ 0.051 |
+ 2.406 |
+ 79.07 |
+ 0.555 |
+ 0.429 |
+ 0.016 |
+ 1.37 |
+ 0.79 |
+ UTM RW |
+
+
+ | 4 |
+ R2601E1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ F |
+ R2601E.CEL |
+ 0.003 |
+ 0.004 |
+ 2.545 |
+ 91.96 |
+ 0.589 |
+ 0.396 |
+ 0.015 |
+ 1.44 |
+ 0.78 |
+ UTM RW |
+
+
+ | 5 |
+ R2602E1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ M |
+ R2602E.CEL |
+ 0.001 |
+ 0.004 |
+ 2.599 |
+ 84.44 |
+ 0.597 |
+ 0.388 |
+ 0.015 |
+ 1.37 |
+ 0.78 |
+ UTM RW |
+
+
+ | 6 |
+ R2600E1 |
+ GDP BXD |
+ D2B6F1 |
+ 72 |
+ F |
+ R2600E.CEL |
+ 0.003 |
+ 0.008 |
+ 2.47 |
+ 94.75 |
+ 0.581 |
+ 0.402 |
+ 0.017 |
+ 1.41 |
+ 0.78 |
+ UTM RW |
+
+
+ | 7 |
+ R2604E1 |
+ GDP BXD |
+ D2B6F1 |
+ 69 |
+ M |
+ R2604E.CEL |
+ 0.003 |
+ 0.007 |
+ 2.657 |
+ 89.63 |
+ 0.594 |
+ 0.392 |
+ 0.015 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 8 |
+ R2597E1 |
+ BXD |
+ BXD2 |
+ 61 |
+ M |
+ R2597E.CEL |
+ 0.003 |
+ 0.007 |
+ 2.374 |
+ 93.56 |
+ 0.603 |
+ 0.383 |
+ 0.015 |
+ 1.34 |
+ 0.77 |
+ Glenn |
+
+
+ | 9 |
+ R2591E1 |
+ BXD |
+ BXD5 |
+ 60 |
+ F |
+ R2591E.CEL |
+ 0.051 |
+ 0.009 |
+ 1.7 |
+ 136.48 |
+ 0.585 |
+ 0.4 |
+ 0.015 |
+ 1.33 |
+ 0.78 |
+ Glenn |
+
+
+ | 10 |
+ R2570E1 |
+ BXD |
+ BXD6 |
+ 65 |
+ F |
+ R2570E.CEL |
+ 0.002 |
+ 0.006 |
+ 1.987 |
+ 86.73 |
+ 0.585 |
+ 0.4 |
+ 0.015 |
+ 1.46 |
+ 0.76 |
+ UTM RW |
+
+
+ | 11 |
+ R2538E1 |
+ BXD |
+ BXD8 |
+ 77 |
+ F |
+ R2538E.CEL |
+ 0.037 |
+ 0.028 |
+ 1.905 |
+ 101.98 |
+ 0.612 |
+ 0.373 |
+ 0.015 |
+ 1.52 |
+ 0.79 |
+ UTM RW |
+
+
+ | 12 |
+ R2569E1 |
+ BXD |
+ BXD9 |
+ 67 |
+ M |
+ R2569E.CEL |
+ 0.014 |
+ 0.027 |
+ 1.753 |
+ 87.36 |
+ 0.551 |
+ 0.434 |
+ 0.015 |
+ 2.82 |
+ 3.14 |
+ UTM RW |
+
+
+ | 13 |
+ R2581E1 |
+ BXD |
+ BXD11 |
+ 65 |
+ F |
+ R2581E.CEL |
+ 0.006 |
+ 0.012 |
+ 1.941 |
+ 88.55 |
+ 0.621 |
+ 0.364 |
+ 0.016 |
+ 1.55 |
+ 0.81 |
+ UTM RW |
+
+
+ | 14 |
+ R2543E1 |
+ BXD |
+ BXD12 |
+ 63 |
+ M |
+ R2543E.CEL |
+ 0.036 |
+ 0.007 |
+ 1.605 |
+ 117.69 |
+ 0.586 |
+ 0.399 |
+ 0.016 |
+ 1.43 |
+ 0.77 |
+ UTM RW |
+
+
+ | 15 |
+ R2586E1 |
+ BXD |
+ BXD13 |
+ 60 |
+ F |
+ R2586E.CEL |
+ 0.020 |
+ 0.035 |
+ 2.006 |
+ 73.61 |
+ 0.564 |
+ 0.42 |
+ 0.016 |
+ 2.85 |
+ 3.81 |
+ Glenn |
+
+
+ | 16 |
+ R2557E1 |
+ BXD |
+ BXD14 |
+ 60 |
+ F |
+ R2557E.CEL |
+ 0.014 |
+ 0.017 |
+ 1.83 |
+ 98.76 |
+ 0.625 |
+ 0.361 |
+ 0.014 |
+ 1.31 |
+ 0.78 |
+ Glenn |
+
+
+ | 17 |
+ R2567E1 |
+ BXD |
+ BXD16 |
+ 60 |
+ M |
+ R2567E.CEL |
+ 0.016 |
+ 0.025 |
+ 2.239 |
+ 82.35 |
+ 0.567 |
+ 0.416 |
+ 0.017 |
+ 1.37 |
+ 0.75 |
+ Glenn |
+
+
+ | 18 |
+ R2559E1 |
+ BXD |
+ BXD18 |
+ 59 |
+ M |
+ R2559E.CEL |
+ 0.035 |
+ 0.006 |
+ 1.654 |
+ 103.68 |
+ 0.608 |
+ 0.377 |
+ 0.015 |
+ 1.27 |
+ 0.78 |
+ Glenn |
+
+
+ | 19 |
+ R2560E1 |
+ BXD |
+ BXD19 |
+ 60 |
+ F |
+ R2560E.CEL |
+ 0.026 |
+ 0.007 |
+ 1.792 |
+ 98.33 |
+ 0.609 |
+ 0.375 |
+ 0.016 |
+ 1.35 |
+ 0.8 |
+ Glenn |
+
+
+ | 20 |
+ R2584E1 |
+ BXD |
+ BXD20 |
+ 59 |
+ F |
+ R2584E.CEL |
+ 0.003 |
+ 0.007 |
+ 2.07 |
+ 83.82 |
+ 0.593 |
+ 0.391 |
+ 0.016 |
+ 1.4 |
+ 0.76 |
+ Glenn |
+
+
+ | 21 |
+ R2541E2 |
+ BXD |
+ BXD21 |
+ 61 |
+ M |
+ R2541E2.CEL |
+ 0.049 |
+ 0.036 |
+ 2.625 |
+ 125.08 |
+ 0.56 |
+ 0.424 |
+ 0.015 |
+ 1.29 |
+ 0.78 |
+ UTM RW |
+
+
+ | 22 |
+ R2553E1 |
+ BXD |
+ BXD22 |
+ 58 |
+ F |
+ R2553E.CEL |
+ 0.003 |
+ 0.005 |
+ 1.952 |
+ 111.3 |
+ 0.599 |
+ 0.385 |
+ 0.015 |
+ 1.28 |
+ 0.76 |
+ Glenn |
+
+
+ | 23 |
+ R2558E1 |
+ BXD |
+ BXD23 |
+ 60 |
+ F |
+ R2558E2.CEL |
+ 0.013 |
+ 0.015 |
+ 1.908 |
+ 114.53 |
+ 0.599 |
+ 0.388 |
+ 0.014 |
+ 1.2 |
+ 0.82 |
+ Glenn |
+
+
+ | 24 |
+ R2589E2 |
+ BXD |
+ BXD24-rd* |
+ 59 |
+ M |
+ R2589E2.CEL |
+ 0.098 |
+ 0.098 |
+ 2.606 |
+ 112.19 |
+ 0.575 |
+ 0.409 |
+ 0.016 |
+ 1.24 |
+ 0.8 |
+ Glenn |
+
+
+ | 25 |
+ R2573E1 |
+ BXD |
+ BXD25 |
+ 67 |
+ F |
+ R2573E2.CEL |
+ 0.009 |
+ 0.018 |
+ 3.153 |
+ 71.88 |
+ 0.579 |
+ 0.407 |
+ 0.014 |
+ 1.77 |
+ 0.97 |
+ UAB |
+
+
+ | 26 |
+ R2562E1 |
+ BXD |
+ BXD28 |
+ 60 |
+ F |
+ R2562E.CEL |
+ 0.003 |
+ 0.005 |
+ 1.649 |
+ 116.35 |
+ 0.599 |
+ 0.384 |
+ 0.017 |
+ 1.37 |
+ 0.79 |
+ Glenn |
+
+
+ | 27 |
+ R2561E1 |
+ BXD |
+ BXD29 |
+ 60 |
+ F |
+ R2561E.CEL |
+ 0.019 |
+ 0.029 |
+ 1.952 |
+ 93.32 |
+ 0.583 |
+ 0.402 |
+ 0.015 |
+ 2.19 |
+ 1 |
+ Glenn |
+
+
+ | 28 |
+ R2598E1 |
+ BXD |
+ BXD31 |
+ 61 |
+ M |
+ R2598E.CEL |
+ 0.003 |
+ 0.006 |
+ 1.989 |
+ 106.48 |
+ 0.609 |
+ 0.376 |
+ 0.015 |
+ 1.27 |
+ 0.78 |
+ UTM RW |
+
+
+ | 29 |
+ R2563E1 |
+ BXD |
+ BXD32 |
+ 63 |
+ F |
+ R2563E.CEL |
+ 0.008 |
+ 0.011 |
+ 1.547 |
+ 101.52 |
+ 0.619 |
+ 0.367 |
+ 0.014 |
+ 1.5 |
+ 0.8 |
+ UTM RW |
+
+
+ | 30 |
+ R2542E1 |
+ BXD |
+ BXD33 |
+ 67 |
+ F |
+ R2542E.CEL |
+ 0.010 |
+ 0.016 |
+ 2.128 |
+ 97.08 |
+ 0.565 |
+ 0.418 |
+ 0.016 |
+ 1.91 |
+ 0.93 |
+ UTM RW |
+
+
+ | 31 |
+ R2585E1 |
+ BXD |
+ BXD34 |
+ 60 |
+ M |
+ R2585E.CEL |
+ 0.007 |
+ 0.014 |
+ 2.64 |
+ 75.13 |
+ 0.583 |
+ 0.4 |
+ 0.017 |
+ 1.25 |
+ 0.77 |
+ Glenn |
+
+
+ | 32 |
+ R2532E1 |
+ BXD |
+ BXD38 |
+ 62 |
+ M |
+ R2532E.CEL |
+ 0.002 |
+ 0.003 |
+ 2.038 |
+ 93.65 |
+ 0.598 |
+ 0.387 |
+ 0.015 |
+ 1.37 |
+ 0.8 |
+ UTM RW |
+
+
+ | 33 |
+ R2574E1 |
+ BXD |
+ BXD39 |
+ 70 |
+ F |
+ R2574E.CEL |
+ 0.001 |
+ 0.004 |
+ 1.981 |
+ 90.64 |
+ 0.612 |
+ 0.373 |
+ 0.015 |
+ 1.39 |
+ 0.78 |
+ UTM RW |
+
+
+ | 34 |
+ R2590E1 |
+ BXD |
+ BXD40 |
+ 60 |
+ M |
+ R2590E.CEL |
+ 0.004 |
+ 0.007 |
+ 2.708 |
+ 77.3 |
+ 0.591 |
+ 0.393 |
+ 0.015 |
+ 1.4 |
+ 0.77 |
+ Glenn |
+
+
+ | 35 |
+ R2596E1 |
+ BXD |
+ BXD42 |
+ 59 |
+ M |
+ R2596E.CEL |
+ 0.013 |
+ 0.017 |
+ 2.632 |
+ 108.46 |
+ 0.59 |
+ 0.396 |
+ 0.015 |
+ 1.24 |
+ 0.8 |
+ Glenn |
+
+
+ | 36 |
+ R2605E1 |
+ BXD |
+ BXD43 |
+ 79 |
+ M |
+ R2607E.CEL |
+ 0.003 |
+ 0.006 |
+ 1.817 |
+ 131.22 |
+ 0.605 |
+ 0.382 |
+ 0.013 |
+ 1.32 |
+ 0.8 |
+ UTM RW |
+
+
+ | 37 |
+ R2594E1 |
+ BXD |
+ BXD44 |
+ 63 |
+ F |
+ R2594E.CEL |
+ 0.004 |
+ 0.009 |
+ 1.766 |
+ 117.33 |
+ 0.598 |
+ 0.388 |
+ 0.014 |
+ 1.35 |
+ 0.85 |
+ UTM RW |
+
+
+ | 38 |
+ R2592E1 |
+ BXD |
+ BXD45 |
+ 62 |
+ M |
+ R2592E.CEL |
+ 0.002 |
+ 0.004 |
+ 1.85 |
+ 106.16 |
+ 0.601 |
+ 0.386 |
+ 0.013 |
+ 1.43 |
+ 0.85 |
+ UTM RW |
+
+
+ | 39 |
+ R2606E1 |
+ BXD |
+ BXD48 |
+ 78 |
+ M |
+ R2606E.CEL |
+ 0.003 |
+ 0.010 |
+ 2.556 |
+ 106.16 |
+ 0.589 |
+ 0.397 |
+ 0.014 |
+ 1.35 |
+ 0.83 |
+ UTM RW |
+
+
+ | 40 |
+ R2603E1 |
+ BXD |
+ BXD51 |
+ 66 |
+ F |
+ R2603E.CEL |
+ 0.003 |
+ 0.009 |
+ 2.488 |
+ 115.16 |
+ 0.577 |
+ 0.408 |
+ 0.015 |
+ 1.24 |
+ 0.79 |
+ UTM RW |
+
+
+ | 41 |
+ R2534E2 |
+ BXD |
+ BXD61* |
+ 70 |
+ F |
+ R2534E2.CEL |
+ 0.030 |
+ 0.028 |
+ 2.473 |
+ 117.76 |
+ 0.579 |
+ 0.406 |
+ 0.015 |
+ 1.42 |
+ 0.79 |
+ UTM RW |
+
+
+ | 42 |
+ R2611E1 |
+ BXD |
+ BXD64 |
+ 68 |
+ M |
+ R2611E.CEL |
+ 0.013 |
+ 0.022 |
+ 2.292 |
+ 91.99 |
+ 0.58 |
+ 0.405 |
+ 0.015 |
+ 1.57 |
+ 1.06 |
+ UTM RW |
+
+
+ | 43 |
+ R2583E1 |
+ BXD |
+ BXD65 |
+ 60 |
+ M |
+ R2583E.CEL |
+ 0.005 |
+ 0.010 |
+ 2.492 |
+ 70.43 |
+ 0.569 |
+ 0.415 |
+ 0.016 |
+ 1.67 |
+ 1.01 |
+ UTM RW |
+
+
+ | 44 |
+ R2536E2 |
+ BXD |
+ BXD66* |
+ 64 |
+ F |
+ R2536E2.CEL |
+ 0.039 |
+ 0.065 |
+ 2.74 |
+ 108.62 |
+ 0.561 |
+ 0.423 |
+ 0.017 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 45 |
+ R2551E1 |
+ BXD |
+ BXD68 |
+ 67 |
+ F |
+ R2551E.CEL |
+ 0.037 |
+ 0.039 |
+ 2.493 |
+ 92.38 |
+ 0.543 |
+ 0.441 |
+ 0.016 |
+ 2.91 |
+ 1.55 |
+ UTM RW |
+
+
+ | 46 |
+ R2593E1 |
+ BXD |
+ BXD69 |
+ 59 |
+ F |
+ R2593E.CEL |
+ 0.008 |
+ 0.013 |
+ 1.672 |
+ 127.6 |
+ 0.592 |
+ 0.395 |
+ 0.013 |
+ 1.47 |
+ 0.92 |
+ UTM RW |
+
+
+ | 47 |
+ R2537E2 |
+ BXD |
+ BXD70* |
+ 59 |
+ M |
+ R2537E2.CEL |
+ 0.046 |
+ 0.044 |
+ 2.93 |
+ 98.66 |
+ 0.58 |
+ 0.405 |
+ 0.016 |
+ 1.29 |
+ 0.75 |
+ UTM RW |
+
+
+ | 48 |
+ R2565E1 |
+ BXD |
+ BXD75 |
+ 61 |
+ F |
+ R2565E.CEL |
+ 0.009 |
+ 0.017 |
+ 1.79 |
+ 101.68 |
+ 0.58 |
+ 0.405 |
+ 0.015 |
+ 2.31 |
+ 3.47 |
+ UTM RW |
+
+
+ | 49 |
+ R2579E1 |
+ BXD |
+ BXD80 |
+ 65 |
+ F |
+ R2579E.CEL |
+ 0.005 |
+ 0.010 |
+ 2.419 |
+ 72.13 |
+ 0.592 |
+ 0.394 |
+ 0.015 |
+ 1.73 |
+ 0.82 |
+ UTM RW |
+
+
+ | 50 |
+ R2540E1 |
+ BXD |
+ BXD87 |
+ 63 |
+ M |
+ R2540E.CEL |
+ 0.013 |
+ 0.016 |
+ 2.333 |
+ 93.15 |
+ 0.611 |
+ 0.374 |
+ 0.014 |
+ 1.22 |
+ 0.81 |
+ UTM RW |
+
+
+ | 51 |
+ R2545E1 |
+ BXD |
+ BXD89 |
+ 67 |
+ M |
+ R2546E.CEL |
+ 0.046 |
+ 0.046 |
+ 1.667 |
+ 104.76 |
+ 0.562 |
+ 0.423 |
+ 0.015 |
+ 3.6 |
+ 9.84 |
+ UTM RW |
+
+
+ | 52 |
+ R2578E2 |
+ BXD |
+ BXD90* |
+ 61 |
+ F |
+ R2578E2.CEL |
+ 0.033 |
+ 0.034 |
+ 2.785 |
+ 92.27 |
+ 0.586 |
+ 0.398 |
+ 0.016 |
+ 1.52 |
+ 0.77 |
+ UTM RW |
+
+
+ | 53 |
+ R2554E1 |
+ BXD |
+ BXD96 |
+ 67 |
+ M |
+ R2554E.CEL |
+ 0.004 |
+ 0.004 |
+ 2.177 |
+ 93.02 |
+ 0.602 |
+ 0.383 |
+ 0.015 |
+ 1.46 |
+ 0.77 |
+ UTM RW |
+
+
+ | 54 |
+ R2577E1 |
+ BXD |
+ BXD97 |
+ 55 |
+ M |
+ R2577E.CEL |
+ 0.019 |
+ 0.016 |
+ 2.07 |
+ 76.58 |
+ 0.595 |
+ 0.391 |
+ 0.014 |
+ 1.87 |
+ 1.29 |
+ UTM RW |
+
+
+ | 55 |
+ R2595E1 |
+ GDP |
+ 129S1/SvImJ |
+ 59 |
+ F |
+ R2595E.CEL |
+ 0.017 |
+ 0.021 |
+ 1.792 |
+ 115.39 |
+ 0.61 |
+ 0.375 |
+ 0.015 |
+ 1.46 |
+ 0.77 |
+ UTM RW |
+
+
+ | 56 |
+ R2533E1 |
+ GDP |
+ 129S1/SvImJ |
+ 60 |
+ M |
+ R2533E.CEL |
+ 0.021 |
+ 0.013 |
+ 2.107 |
+ 93.55 |
+ 0.579 |
+ 0.405 |
+ 0.016 |
+ 1.37 |
+ 0.78 |
+ UTM RW |
+
+
+ | 57 |
+ R2546E1 |
+ GDP |
+ A/J |
+ 66 |
+ F |
+ R2545E.CEL |
+ 0.018 |
+ 0.014 |
+ 1.989 |
+ 95.59 |
+ 0.586 |
+ 0.397 |
+ 0.017 |
+ 1.47 |
+ 0.78 |
+ UTM RW |
+
+
+ | 58 |
+ R0754E2 |
+ GDP |
+ A/J |
+ 60 |
+ M |
+ R0754E.CEL |
+ 0.014 |
+ 0.016 |
+ 2.718 |
+ 85.63 |
+ 0.598 |
+ 0.387 |
+ 0.015 |
+ 1.36 |
+ 0.76 |
+ JAX |
+
+
+ | 59 |
+ R1676E1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ F |
+ R1676E.CEL |
+ 0.042 |
+ 0.041 |
+ 2.685 |
+ 98.37 |
+ 0.589 |
+ 0.396 |
+ 0.015 |
+ 1.46 |
+ 0.74 |
+ JAX |
+
+
+ | 60 |
+ R1672E1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ M |
+ R1672E.CEL |
+ 0.022 |
+ 0.022 |
+ 2.216 |
+ 110.52 |
+ 0.599 |
+ 0.386 |
+ 0.015 |
+ 1.26 |
+ 0.8 |
+ JAX |
+
+
+ | 61 |
+ R1700E1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ F |
+ R1700E.CEL |
+ 0.090 |
+ 0.092 |
+ 2.978 |
+ 68.77 |
+ 0.608 |
+ 0.379 |
+ 0.014 |
+ 1.48 |
+ 0.78 |
+ UTM RW |
+
+
+ | 62 |
+ R1704E1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ M |
+ R1704E.CEL |
+ 0.086 |
+ 0.089 |
+ 2.581 |
+ 88.29 |
+ 0.601 |
+ 0.386 |
+ 0.013 |
+ 1.38 |
+ 0.84 |
+ UTM RW |
+
+
+ | 63 |
+ R2564E1 |
+ GDP |
+ CAST/Ei |
+ 64 |
+ F |
+ R2564E.CEL |
+ 0.078 |
+ 0.064 |
+ 1.937 |
+ 88.89 |
+ 0.585 |
+ 0.399 |
+ 0.016 |
+ 1.6 |
+ 0.77 |
+ JAX |
+
+
+ | 64 |
+ R2580E1 |
+ GDP |
+ CAST/Ei |
+ 64 |
+ M |
+ R2580E.CEL |
+ 0.076 |
+ 0.067 |
+ 2.089 |
+ 94.64 |
+ 0.582 |
+ 0.401 |
+ 0.017 |
+ 1.4 |
+ 0.76 |
+ JAX |
+
+
+ | 65 |
+ R2636E1 |
+ GDP |
+ KK/HIJ |
+ 64 |
+ F |
+ R2636E.CEL |
+ 0.023 |
+ 0.026 |
+ 2.61 |
+ 93.1 |
+ 0.589 |
+ 0.395 |
+ 0.015 |
+ 1.39 |
+ 0.76 |
+ UTM RW |
+
+
+ | 66 |
+ R2637E1 |
+ GDP |
+ KK/HIJ |
+ 64 |
+ M |
+ R2637E.CEL |
+ 0.039 |
+ 0.020 |
+ 2.189 |
+ 102.78 |
+ 0.594 |
+ 0.39 |
+ 0.015 |
+ 1.3 |
+ 0.79 |
+ UTM RW |
+
+
+ | 67 |
+ R0999E1 |
+ GDP |
+ LG/J |
+ 57 |
+ F |
+ R0999E.CEL |
+ 0.012 |
+ 0.012 |
+ 2.448 |
+ 82.09 |
+ 0.594 |
+ 0.391 |
+ 0.015 |
+ 1.38 |
+ 0.79 |
+ UTM RW |
+
+
+ | 68 |
+ R1004E1 |
+ GDP |
+ LG/J |
+ 65 |
+ M |
+ R1004E.CEL |
+ 0.013 |
+ 0.015 |
+ 2.438 |
+ 91.71 |
+ 0.587 |
+ 0.398 |
+ 0.015 |
+ 1.38 |
+ 0.79 |
+ UTM RW |
+
+
+ | 69 |
+ R1688E1 |
+ GDP |
+ NOD/LtJ |
+ 66 |
+ F |
+ R1688E.CEL |
+ 0.017 |
+ 0.019 |
+ 2.664 |
+ 97.65 |
+ 0.586 |
+ 0.399 |
+ 0.015 |
+ 1.26 |
+ 0.8 |
+ JAX |
+
+
+ | 70 |
+ R2566E1 |
+ GDP |
+ NOD/LtJ |
+ 76 |
+ M |
+ R2566E2.CEL |
+ 0.019 |
+ 0.025 |
+ 3.031 |
+ 69.44 |
+ 0.598 |
+ 0.388 |
+ 0.015 |
+ 1.38 |
+ 0.75 |
+ UTM RW |
+
+
+ | 71 |
+ R2550E1 |
+ GDP |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ R2550E.CEL |
+ 0.023 |
+ 0.015 |
+ 1.794 |
+ 87.16 |
+ 0.607 |
+ 0.378 |
+ 0.015 |
+ 1.52 |
+ 0.82 |
+ JAX |
+
+
+ | 72 |
+ R2535E1 |
+ GDP |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ R2535E.CEL |
+ 0.046 |
+ 0.025 |
+ 1.893 |
+ 85.67 |
+ 0.604 |
+ 0.382 |
+ 0.014 |
+ 1.41 |
+ 0.85 |
+ JAX |
+
+
+ | 73 |
+ R2634E1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ F |
+ R2635E.CEL |
+ 0.077 |
+ 0.069 |
+ 3.292 |
+ 89.8 |
+ 0.559 |
+ 0.425 |
+ 0.016 |
+ 1.57 |
+ 0.81 |
+ JAX |
+
+
+ | 74 |
+ R2635E1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ M |
+ R2634E.CEL |
+ 0.088 |
+ 0.081 |
+ 3.722 |
+ 80.05 |
+ 0.542 |
+ 0.441 |
+ 0.017 |
+ 1.53 |
+ 0.85 |
+ JAX |
+
+
+ | 75 |
+ R2544E1 |
+ GDP |
+ PWK/PhJ |
+ 63 |
+ F |
+ R2544E.CEL |
+ 0.106 |
+ 0.100 |
+ 2.196 |
+ 107.51 |
+ 0.549 |
+ 0.435 |
+ 0.017 |
+ 1.36 |
+ 0.82 |
+ JAX |
+
+
+ | 76 |
+ R2549E1 |
+ GDP |
+ PWK/PhJ |
+ 83 |
+ M |
+ R2549E.CEL |
+ 0.065 |
+ 0.048 |
+ 2.275 |
+ 83.8 |
+ 0.573 |
+ 0.412 |
+ 0.015 |
+ 1.57 |
+ 0.83 |
+ JAX |
+
+
+ | 77 |
+ R2368E1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ F |
+ R2368E.CEL |
+ 0.025 |
+ 0.028 |
+ 2.567 |
+ 85.7 |
+ 0.595 |
+ 0.391 |
+ 0.014 |
+ 1.29 |
+ 0.74 |
+ UTM RW |
+
+
+ | 78 |
+ R2547E1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ M |
+ R2547E.CEL |
+ 0.032 |
+ 0.021 |
+ 2.135 |
+ 90.04 |
+ 0.582 |
+ 0.401 |
+ 0.016 |
+ 1.32 |
+ 0.77 |
+ UTM RW |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/FGUCAS_BAdip0516/summary.rtf b/general/datasets/FGUCAS_BAdip0516/summary.rtf
deleted file mode 100644
index 7de9a53..0000000
--- a/general/datasets/FGUCAS_BAdip0516/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is currently unpublished, please refer to the contact information above if you want to use this data.
diff --git a/general/datasets/Fgucas_badip0516/summary.rtf b/general/datasets/Fgucas_badip0516/summary.rtf
new file mode 100644
index 0000000..7de9a53
--- /dev/null
+++ b/general/datasets/Fgucas_badip0516/summary.rtf
@@ -0,0 +1 @@
+This dataset is currently unpublished, please refer to the contact information above if you want to use this data.
diff --git a/general/datasets/Ft_2a_0605_rz/acknowledgment.rtf b/general/datasets/Ft_2a_0605_rz/acknowledgment.rtf
new file mode 100644
index 0000000..f6b54b6
--- /dev/null
+++ b/general/datasets/Ft_2a_0605_rz/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported with funds to TJA by the MRC Clinical Sciences Centre, the British Heart Foundation, and the Wellcome Trust Cardiovascular Functional Genomics Intiative; to NH from the German Ministry for Science and Education (National Genome Research Network, NGFN); to MP and Vladimir Kren from the Grant Agency of the Czech Republic; to MP and TJA from the Wellcome Trust Collaborative Research Initiative grant, to Theodore W Kurtz from the NIH, to TWK and MP from a Fogarty International Research Collaboration Award. Microarrays were a generous donation of Affymetrix Inc. MP is an International Research Scholar of the Howard Hughes Medical Institute.
diff --git a/general/datasets/Ft_2a_0605_rz/cases.rtf b/general/datasets/Ft_2a_0605_rz/cases.rtf
new file mode 100644
index 0000000..f953b8d
--- /dev/null
+++ b/general/datasets/Ft_2a_0605_rz/cases.rtf
@@ -0,0 +1,7 @@
+We have exploited a set of HXB/BXH recombinant inbred strains of rats generated over the past 20 years in Prague. The parental strains from which all HXB lines are derived are SHR (SHR/OlaIpcv or HSR = H) and Brown Norway (BN.Lx/Cub= B). These parental strains have been used extensively to study cardiovascular system physiology and genetics.
+
+
+The HXB strains were generated by Michal Pravenec at the Institute of Physiology, Czech Academy of Sciences. The BXH strains were generated by Vladimir Kren (see Pravenec et al. 1989, 2004) at a similar animal facility at the Institute of Biology and Medical Genetics, 1st Medical Faculty, Charles University. These strains are at approximately the 60th generation of continuous inbreeding (F60).
+
+Animals used in the transcriptome analyses of kidney and fat (Hübner and colleagues, 2005) were weaned at 4 weeks. Those born at the Charles University were transferred to the Institute of Physiology. Animals were reared on a commercial rat chow (ST-1 from VELAZ, Czech Republic). Four males were house per cage. Cages were made of polystyrene and have a floor size of 22 x 38 cm and height of 23 cm. The bedding was changed twice a week. Light cycle was 12:12 on-off. Vivarium rooms were maintained at 23 degrees C. Rats were sexually naive. All males used in the initial transcriptome studies (Hubner et al., 2005) were born between May and August 2002. They were sacrificed unfastged by rapid cervical dislocation between 9 and 10 AM, following an approved animal protocol (Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague; Animal Protection Law of the Czech Republic (311/1997).
+
diff --git a/general/datasets/Ft_2a_0605_rz/notes.rtf b/general/datasets/Ft_2a_0605_rz/notes.rtf
new file mode 100644
index 0000000..815c6d4
--- /dev/null
+++ b/general/datasets/Ft_2a_0605_rz/notes.rtf
@@ -0,0 +1,3 @@
+This approved text file originally generated by Robert Williams, Norbert Hubner, Michal Pravenec, Timothy Aitman, April 19, 2005. Updated by RWW, April 20, 2005; April 28, 2005. June 15, 2005 by RWW and SY; June 20 by RWW and NH.
+
+
diff --git a/general/datasets/Ft_2a_0605_rz/platform.rtf b/general/datasets/Ft_2a_0605_rz/platform.rtf
new file mode 100644
index 0000000..238952f
--- /dev/null
+++ b/general/datasets/Ft_2a_0605_rz/platform.rtf
@@ -0,0 +1 @@
+Affymetrix 230A GeneChip: Expression data were generated using 230A array. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Rat Genome Sequencing Consortium assembly.
diff --git a/general/datasets/Ft_2a_0605_rz/processing.rtf b/general/datasets/Ft_2a_0605_rz/processing.rtf
new file mode 100644
index 0000000..e119fda
--- /dev/null
+++ b/general/datasets/Ft_2a_0605_rz/processing.rtf
@@ -0,0 +1,25 @@
+Probe and Probe set data: The original cell-level files (in text format) were downloaded from Array Express. These files were then converted to a standard Affymetrix CEL file (old MAS5 style) format using a Perl script written by Senhua Yu. These files were then processed as a large batch (either all 130 arrays or the final 124 arrays) using a custom quantile normalization program written by KF Manly. The output of this program automatically performs the log normalization and variance stabilization at the probe level. We then computed the mean and standard error for each strain using these normalized probe data.
+
+Probe set data were generated starting with the raw Affymetrix CEL file described above (prior to any normalization) and were processed using the Robust Multichip Average (RMA) method (Irrizary et al. 2003).
+
+This data set include further normalization to produce final estimates of expression that can be compared directly to the other transforms (average of 8 units and stabilized variance of 2 units within each array). Data were further transformed as follows:
+
+
+ - Step 1: RMA values were generated as described above.
+ - Step 2: We computed the Z scores for each probe set value for each array.
+ - Step 3: We multiplied all Z scores by 2.
+ - Step 4: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 5: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. We have not corrected for background beyond the background correction implemented by Affymetrix.
+
+
+All transformation steps were carried out by Senhua Yu at UTHSC.
+
+About Quality Control Procedures:
+
+RNA processing:RNA was extracted using Trizol reagent (Invitrogen) and purified using an RNeasy Mini kit from Qiagen. Double-stranded cDNA was generated without pooling. Fat samples were processed using the Enzo Diagnostics Bioarray High Yield RNA Transcript labeling kit. See Hubner et al. 2005 for additional detail. One-hundred and twenty eight samples passed RNA quality control assays.
+
+Probe level QC: All 130 CEL files were collected into a single DataDesk 6.2 analysis file. Probe data from pairs of arrays were plotted and compared after quantile normalization. Six arrays were considered potential outliers (despite having passed RNA quality control) and in the interest of minimizing technical variance, a decision was made to withhold them from the calculation of strain means. The remaining 124 arrays were then quantile normalized again and reexamined in DataDesk to ensure reasonable colinearity of all final array data sets.
+
+Strain assignment check: To confirm strain assignment we exploit a set of transcripts with near-Mendelian segregation patterns (search for "test Mendelian"). Strain means with both intermediate expression values AND unusually high error terms often indicate at a misassignment of a case to a particular strain. This error checking has identified 4 strains with possible errors in this data set.
+
+
diff --git a/general/datasets/Ft_2a_0605_rz/summary.rtf b/general/datasets/Ft_2a_0605_rz/summary.rtf
new file mode 100644
index 0000000..f522e76
--- /dev/null
+++ b/general/datasets/Ft_2a_0605_rz/summary.rtf
@@ -0,0 +1,16 @@
+This June 2005 data set provides estimates of mRNA expression in normal peritoneal fat of 32 strains of rats. The set includes the hypertensive SHR strain, the normotensive BN strain, and 30 HXB/BXH recombinant inbred strains. Each strain was sampled in quadruplicate (6-week-old males). Animals and tissues were generated by Michal Pravenec and colleagues at the Czech Academy of Sciences (CAS). RNA samples were processed at the Max-Delbrück-Center for Molecular Medicine (MDC), Berlin-Buch, by Norbert Hubner and colleagues. Transcriptome mapping was carried out by Norbert Hubner, Timothy Aitman and colleagues at the MDC and the MRC Clinicial Sciences Centre, Imperial College London (ICL). Samples were hybridized individually to a total of 130 Affymetrix RAE230A array. This particular data set includes 124 arrays processed using the RMA protocol. RMA values of each array were adjusted to an average of 8 units and a standard deviation of 2 units (2ZPlus8). This data set complements the MAS5 data set exploited by Hubner and colleagues 2005. Download the particular transform in an Excel work book with both strain means and SEMs.
+
+Genome-wide co-expression analysis in multiple tissues.
+
+And see closely associate set of papers:
+
+
+ - Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease.
+ - Heritability and tissue specificity of expression quantitative trait loci.
+ - Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass.
+ - New insights into the genetic control of gene expression using a Bayesian multi-tissue approach.
+ - The genome sequence of the spontaneously hypertensive rat: Analysis and functional significance.
+ - A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.
+ - Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.
+ - Systems-level approaches reveal conservation of trans-regulated genes in the rat and genetic determinants of blood pressure in humans.
+
diff --git a/general/datasets/Ft_2a_0605_rz/tissue.rtf b/general/datasets/Ft_2a_0605_rz/tissue.rtf
new file mode 100644
index 0000000..85eb931
--- /dev/null
+++ b/general/datasets/Ft_2a_0605_rz/tissue.rtf
@@ -0,0 +1,542 @@
+All tissues were collected at the age of 6 weeks. Peritoneal fat pads were rapidly dissected and cleaned extraneous tissue, inserted into a vial, and immersed in liquid nitrogen for storage until RNA extraction.
+
+The table below lists 130 arrays by strain and sample identifier. Each array was hybridized with mRNA from a single young male rat. Six arrays marked with asterisks were eventually excluded.
+
+
+
+
+
+
+
+
+ | Strain |
+ SampleID |
+
+
+ | BN |
+ BN1 |
+
+
+ | BN |
+ BN2 |
+
+
+ | BN |
+ BN3 |
+
+
+ | BN |
+ BN5 |
+
+
+ | BN |
+ BN6 |
+
+
+ | BXH10 |
+ RI 10c-1 |
+
+
+ | BXH10 |
+ RI 10c-2 |
+
+
+ | BXH10 |
+ RI 10c-3 |
+
+
+ | BXH10 |
+ RI 10c-5 |
+
+
+ | BXH11 |
+ RI 11c-1 |
+
+
+ | BXH11 |
+ RI 11c-2 |
+
+
+ | BXH11 |
+ RI 11c-3 |
+
+
+ | BXH11 |
+ RI 11c-4 |
+
+
+ | BXH12 |
+ RI 12c-1 |
+
+
+ | BXH12 |
+ RI 12c-2 |
+
+
+ | BXH12 |
+ RI 12c-3 |
+
+
+ | BXH12 |
+ RI 12c-4 |
+
+
+ | BXH13 |
+ RI 13c-1 |
+
+
+ | BXH13 |
+ RI 13c-2 |
+
+
+ | BXH13 |
+ RI 13c-3 |
+
+
+ | BXH13 |
+ RI 13c-4 |
+
+
+ | BXH2 |
+ RI 02c-1 |
+
+
+ | BXH2 |
+ RI 02c-2 |
+
+
+ | BXH2 |
+ RI 02c-4 |
+
+
+ | BXH2 |
+ RI 02c-5 |
+
+
+ | BXH3 |
+ RI 03c-1 |
+
+
+ | BXH3 |
+ RI 03c-2 |
+
+
+ | BXH3 |
+ RI 03c-3 |
+
+
+ | BXH3 |
+ RI 03c-4 |
+
+
+ | BXH5 |
+ RI 05c-1 |
+
+
+ | BXH5 |
+ RI 05c-2 |
+
+
+ | BXH5 |
+ *RI 05c-3 |
+
+
+ | BXH5 |
+ RI 05c-5 |
+
+
+ | BXH6 |
+ RI 06c-1 |
+
+
+ | BXH6 |
+ RI 06c-4 |
+
+
+ | BXH6 |
+ RI 06c-5 |
+
+
+ | BXH6 |
+ RI 06c-6 |
+
+
+ | BXH8 |
+ RI 08c-2 |
+
+
+ | BXH8 |
+ RI 08c-3 |
+
+
+ | BXH8 |
+ RI 08c-4 |
+
+
+ | BXH8 |
+ RI 08c-5 |
+
+
+ | BXH9 |
+ RI 09c-1 |
+
+
+ | BXH9 |
+ RI 09c-2 |
+
+
+ | BXH9 |
+ RI 09c-4 |
+
+
+ | BXH9 |
+ RI 09c-5 |
+
+
+ | HXB1 |
+ RI 01-1 |
+
+
+ | HXB1 |
+ RI 01-2 |
+
+
+ | HXB1 |
+ RI 01-4 |
+
+
+ | HXB1 |
+ RI 01-5 |
+
+
+ | HXB10 |
+ RI 10-2 |
+
+
+ | HXB10 |
+ RI 10-3 |
+
+
+ | HXB10 |
+ RI 10-4 |
+
+
+ | HXB10 |
+ RI 10-5 |
+
+
+ | HXB15 |
+ RI 15-1 |
+
+
+ | HXB15 |
+ RI 15-2 |
+
+
+ | HXB15 |
+ RI 15-5 |
+
+
+ | HXB15 |
+ RI 15-6 |
+
+
+ | HXB17 |
+ RI 17-1 |
+
+
+ | HXB17 |
+ RI 17-2 |
+
+
+ | HXB17 |
+ *RI 17-3 |
+
+
+ | HXB17 |
+ RI 17-4 |
+
+
+ | HXB18 |
+ RI 18-1 |
+
+
+ | HXB18 |
+ RI 18-2 |
+
+
+ | HXB18 |
+ *RI 18-3 |
+
+
+ | HXB18 |
+ RI 18-4 |
+
+
+ | HXB2 |
+ RI 02-1 |
+
+
+ | HXB2 |
+ RI 02-2 |
+
+
+ | HXB2 |
+ RI 02-3 |
+
+
+ | HXB2 |
+ RI 02-4 |
+
+
+ | HXB20 |
+ RI 20-1 |
+
+
+ | HXB20 |
+ RI 20-2 |
+
+
+ | HXB20 |
+ *RI 20-3 |
+
+
+ | HXB20 |
+ RI 20-4 |
+
+
+ | HXB21 |
+ RI 21-1 |
+
+
+ | HXB21 |
+ RI 21-2 |
+
+
+ | HXB21 |
+ RI 21-3 |
+
+
+ | HXB21 |
+ RI 21-4 |
+
+
+ | HXB22 |
+ RI 22-1 |
+
+
+ | HXB22 |
+ RI 22-2 |
+
+
+ | HXB22 |
+ *RI 22-3 |
+
+
+ | HXB22 |
+ RI 22-4 |
+
+
+ | HXB23 |
+ RI 23-1 |
+
+
+ | HXB23 |
+ RI 23-2 |
+
+
+ | HXB23 |
+ RI 23-3 |
+
+
+ | HXB23 |
+ RI 23-4 |
+
+
+ | HXB24 |
+ RI 24-1 |
+
+
+ | HXB24 |
+ RI 24-2 |
+
+
+ | HXB24 |
+ RI 24-3 |
+
+
+ | HXB24 |
+ RI 24-5 |
+
+
+ | HXB25 |
+ RI 25-1 |
+
+
+ | HXB25 |
+ RI 25-3 |
+
+
+ | HXB25 |
+ RI 25-4 |
+
+
+ | HXB25 |
+ RI 25-5 |
+
+
+ | HXB26 |
+ RI 26-1 |
+
+
+ | HXB26 |
+ RI 26-2 |
+
+
+ | HXB26 |
+ *RI 26-3 |
+
+
+ | HXB26 |
+ RI 26-4 |
+
+
+ | HXB27 |
+ RI 27-1 |
+
+
+ | HXB27 |
+ RI 27-2 |
+
+
+ | HXB27 |
+ RI 27-3 |
+
+
+ | HXB27 |
+ RI 27-4 |
+
+
+ | HXB29 |
+ RI 29-1 |
+
+
+ | HXB29 |
+ RI 29-2 |
+
+
+ | HXB29 |
+ RI 29-4 |
+
+
+ | HXB29 |
+ RI 29-5 |
+
+
+ | HXB3 |
+ RI 03-1 |
+
+
+ | HXB3 |
+ RI 03-2 |
+
+
+ | HXB3 |
+ RI 03-3 |
+
+
+ | HXB3 |
+ RI 03-4 |
+
+
+ | HXB31 |
+ RI 31-1 |
+
+
+ | HXB31 |
+ RI 31-2 |
+
+
+ | HXB31 |
+ RI 31-3 |
+
+
+ | HXB31 |
+ RI 31-4 |
+
+
+ | HXB4 |
+ RI 04-1 |
+
+
+ | HXB4 |
+ RI 04-2 |
+
+
+ | HXB4 |
+ RI 04-3 |
+
+
+ | HXB4 |
+ RI 04-4 |
+
+
+ | HXB5 |
+ RI 05-1 |
+
+
+ | HXB5 |
+ RI 05-2 |
+
+
+ | HXB5 |
+ RI 05-3 |
+
+
+ | HXB5 |
+ RI 05-4 |
+
+
+ | HXB7 |
+ RI 07-1 |
+
+
+ | HXB7 |
+ RI 07-2 |
+
+
+ | HXB7 |
+ RI 07-3 |
+
+
+ | HXB7 |
+ RI 07-4 |
+
+
+ | HSR |
+ HSR1 |
+
+
+ | HSR |
+ HSR2 |
+
+
+ | HSR |
+ HSR6 |
+
+
+ | HSR |
+ HSR7 |
+
+
+ | HSR |
+ HSR8 |
+
+
+
+ |
+
+
+
+
+*: These six arrays were excluded in the final strain summary data. See section of Quality Control for further explanation.
diff --git a/general/datasets/Ft_2a_0805_m/acknowledgment.rtf b/general/datasets/Ft_2a_0805_m/acknowledgment.rtf
new file mode 100644
index 0000000..f6b54b6
--- /dev/null
+++ b/general/datasets/Ft_2a_0805_m/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported with funds to TJA by the MRC Clinical Sciences Centre, the British Heart Foundation, and the Wellcome Trust Cardiovascular Functional Genomics Intiative; to NH from the German Ministry for Science and Education (National Genome Research Network, NGFN); to MP and Vladimir Kren from the Grant Agency of the Czech Republic; to MP and TJA from the Wellcome Trust Collaborative Research Initiative grant, to Theodore W Kurtz from the NIH, to TWK and MP from a Fogarty International Research Collaboration Award. Microarrays were a generous donation of Affymetrix Inc. MP is an International Research Scholar of the Howard Hughes Medical Institute.
diff --git a/general/datasets/Ft_2a_0805_m/cases.rtf b/general/datasets/Ft_2a_0805_m/cases.rtf
new file mode 100644
index 0000000..f953b8d
--- /dev/null
+++ b/general/datasets/Ft_2a_0805_m/cases.rtf
@@ -0,0 +1,7 @@
+We have exploited a set of HXB/BXH recombinant inbred strains of rats generated over the past 20 years in Prague. The parental strains from which all HXB lines are derived are SHR (SHR/OlaIpcv or HSR = H) and Brown Norway (BN.Lx/Cub= B). These parental strains have been used extensively to study cardiovascular system physiology and genetics.
+
+
+The HXB strains were generated by Michal Pravenec at the Institute of Physiology, Czech Academy of Sciences. The BXH strains were generated by Vladimir Kren (see Pravenec et al. 1989, 2004) at a similar animal facility at the Institute of Biology and Medical Genetics, 1st Medical Faculty, Charles University. These strains are at approximately the 60th generation of continuous inbreeding (F60).
+
+Animals used in the transcriptome analyses of kidney and fat (Hübner and colleagues, 2005) were weaned at 4 weeks. Those born at the Charles University were transferred to the Institute of Physiology. Animals were reared on a commercial rat chow (ST-1 from VELAZ, Czech Republic). Four males were house per cage. Cages were made of polystyrene and have a floor size of 22 x 38 cm and height of 23 cm. The bedding was changed twice a week. Light cycle was 12:12 on-off. Vivarium rooms were maintained at 23 degrees C. Rats were sexually naive. All males used in the initial transcriptome studies (Hubner et al., 2005) were born between May and August 2002. They were sacrificed unfastged by rapid cervical dislocation between 9 and 10 AM, following an approved animal protocol (Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague; Animal Protection Law of the Czech Republic (311/1997).
+
diff --git a/general/datasets/Ft_2a_0805_m/notes.rtf b/general/datasets/Ft_2a_0805_m/notes.rtf
new file mode 100644
index 0000000..815c6d4
--- /dev/null
+++ b/general/datasets/Ft_2a_0805_m/notes.rtf
@@ -0,0 +1,3 @@
+This approved text file originally generated by Robert Williams, Norbert Hubner, Michal Pravenec, Timothy Aitman, April 19, 2005. Updated by RWW, April 20, 2005; April 28, 2005. June 15, 2005 by RWW and SY; June 20 by RWW and NH.
+
+
diff --git a/general/datasets/Ft_2a_0805_m/platform.rtf b/general/datasets/Ft_2a_0805_m/platform.rtf
new file mode 100644
index 0000000..238952f
--- /dev/null
+++ b/general/datasets/Ft_2a_0805_m/platform.rtf
@@ -0,0 +1 @@
+Affymetrix 230A GeneChip: Expression data were generated using 230A array. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Rat Genome Sequencing Consortium assembly.
diff --git a/general/datasets/Ft_2a_0805_m/processing.rtf b/general/datasets/Ft_2a_0805_m/processing.rtf
new file mode 100644
index 0000000..e119fda
--- /dev/null
+++ b/general/datasets/Ft_2a_0805_m/processing.rtf
@@ -0,0 +1,25 @@
+Probe and Probe set data: The original cell-level files (in text format) were downloaded from Array Express. These files were then converted to a standard Affymetrix CEL file (old MAS5 style) format using a Perl script written by Senhua Yu. These files were then processed as a large batch (either all 130 arrays or the final 124 arrays) using a custom quantile normalization program written by KF Manly. The output of this program automatically performs the log normalization and variance stabilization at the probe level. We then computed the mean and standard error for each strain using these normalized probe data.
+
+Probe set data were generated starting with the raw Affymetrix CEL file described above (prior to any normalization) and were processed using the Robust Multichip Average (RMA) method (Irrizary et al. 2003).
+
+This data set include further normalization to produce final estimates of expression that can be compared directly to the other transforms (average of 8 units and stabilized variance of 2 units within each array). Data were further transformed as follows:
+
+
+ - Step 1: RMA values were generated as described above.
+ - Step 2: We computed the Z scores for each probe set value for each array.
+ - Step 3: We multiplied all Z scores by 2.
+ - Step 4: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 5: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. We have not corrected for background beyond the background correction implemented by Affymetrix.
+
+
+All transformation steps were carried out by Senhua Yu at UTHSC.
+
+About Quality Control Procedures:
+
+RNA processing:RNA was extracted using Trizol reagent (Invitrogen) and purified using an RNeasy Mini kit from Qiagen. Double-stranded cDNA was generated without pooling. Fat samples were processed using the Enzo Diagnostics Bioarray High Yield RNA Transcript labeling kit. See Hubner et al. 2005 for additional detail. One-hundred and twenty eight samples passed RNA quality control assays.
+
+Probe level QC: All 130 CEL files were collected into a single DataDesk 6.2 analysis file. Probe data from pairs of arrays were plotted and compared after quantile normalization. Six arrays were considered potential outliers (despite having passed RNA quality control) and in the interest of minimizing technical variance, a decision was made to withhold them from the calculation of strain means. The remaining 124 arrays were then quantile normalized again and reexamined in DataDesk to ensure reasonable colinearity of all final array data sets.
+
+Strain assignment check: To confirm strain assignment we exploit a set of transcripts with near-Mendelian segregation patterns (search for "test Mendelian"). Strain means with both intermediate expression values AND unusually high error terms often indicate at a misassignment of a case to a particular strain. This error checking has identified 4 strains with possible errors in this data set.
+
+
diff --git a/general/datasets/Ft_2a_0805_m/summary.rtf b/general/datasets/Ft_2a_0805_m/summary.rtf
new file mode 100644
index 0000000..f522e76
--- /dev/null
+++ b/general/datasets/Ft_2a_0805_m/summary.rtf
@@ -0,0 +1,16 @@
+This June 2005 data set provides estimates of mRNA expression in normal peritoneal fat of 32 strains of rats. The set includes the hypertensive SHR strain, the normotensive BN strain, and 30 HXB/BXH recombinant inbred strains. Each strain was sampled in quadruplicate (6-week-old males). Animals and tissues were generated by Michal Pravenec and colleagues at the Czech Academy of Sciences (CAS). RNA samples were processed at the Max-Delbrück-Center for Molecular Medicine (MDC), Berlin-Buch, by Norbert Hubner and colleagues. Transcriptome mapping was carried out by Norbert Hubner, Timothy Aitman and colleagues at the MDC and the MRC Clinicial Sciences Centre, Imperial College London (ICL). Samples were hybridized individually to a total of 130 Affymetrix RAE230A array. This particular data set includes 124 arrays processed using the RMA protocol. RMA values of each array were adjusted to an average of 8 units and a standard deviation of 2 units (2ZPlus8). This data set complements the MAS5 data set exploited by Hubner and colleagues 2005. Download the particular transform in an Excel work book with both strain means and SEMs.
+
+Genome-wide co-expression analysis in multiple tissues.
+
+And see closely associate set of papers:
+
+
+ - Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease.
+ - Heritability and tissue specificity of expression quantitative trait loci.
+ - Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass.
+ - New insights into the genetic control of gene expression using a Bayesian multi-tissue approach.
+ - The genome sequence of the spontaneously hypertensive rat: Analysis and functional significance.
+ - A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.
+ - Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.
+ - Systems-level approaches reveal conservation of trans-regulated genes in the rat and genetic determinants of blood pressure in humans.
+
diff --git a/general/datasets/Ft_2a_0805_m/tissue.rtf b/general/datasets/Ft_2a_0805_m/tissue.rtf
new file mode 100644
index 0000000..85eb931
--- /dev/null
+++ b/general/datasets/Ft_2a_0805_m/tissue.rtf
@@ -0,0 +1,542 @@
+All tissues were collected at the age of 6 weeks. Peritoneal fat pads were rapidly dissected and cleaned extraneous tissue, inserted into a vial, and immersed in liquid nitrogen for storage until RNA extraction.
+
+The table below lists 130 arrays by strain and sample identifier. Each array was hybridized with mRNA from a single young male rat. Six arrays marked with asterisks were eventually excluded.
+
+
+
+
+
+
+
+
+ | Strain |
+ SampleID |
+
+
+ | BN |
+ BN1 |
+
+
+ | BN |
+ BN2 |
+
+
+ | BN |
+ BN3 |
+
+
+ | BN |
+ BN5 |
+
+
+ | BN |
+ BN6 |
+
+
+ | BXH10 |
+ RI 10c-1 |
+
+
+ | BXH10 |
+ RI 10c-2 |
+
+
+ | BXH10 |
+ RI 10c-3 |
+
+
+ | BXH10 |
+ RI 10c-5 |
+
+
+ | BXH11 |
+ RI 11c-1 |
+
+
+ | BXH11 |
+ RI 11c-2 |
+
+
+ | BXH11 |
+ RI 11c-3 |
+
+
+ | BXH11 |
+ RI 11c-4 |
+
+
+ | BXH12 |
+ RI 12c-1 |
+
+
+ | BXH12 |
+ RI 12c-2 |
+
+
+ | BXH12 |
+ RI 12c-3 |
+
+
+ | BXH12 |
+ RI 12c-4 |
+
+
+ | BXH13 |
+ RI 13c-1 |
+
+
+ | BXH13 |
+ RI 13c-2 |
+
+
+ | BXH13 |
+ RI 13c-3 |
+
+
+ | BXH13 |
+ RI 13c-4 |
+
+
+ | BXH2 |
+ RI 02c-1 |
+
+
+ | BXH2 |
+ RI 02c-2 |
+
+
+ | BXH2 |
+ RI 02c-4 |
+
+
+ | BXH2 |
+ RI 02c-5 |
+
+
+ | BXH3 |
+ RI 03c-1 |
+
+
+ | BXH3 |
+ RI 03c-2 |
+
+
+ | BXH3 |
+ RI 03c-3 |
+
+
+ | BXH3 |
+ RI 03c-4 |
+
+
+ | BXH5 |
+ RI 05c-1 |
+
+
+ | BXH5 |
+ RI 05c-2 |
+
+
+ | BXH5 |
+ *RI 05c-3 |
+
+
+ | BXH5 |
+ RI 05c-5 |
+
+
+ | BXH6 |
+ RI 06c-1 |
+
+
+ | BXH6 |
+ RI 06c-4 |
+
+
+ | BXH6 |
+ RI 06c-5 |
+
+
+ | BXH6 |
+ RI 06c-6 |
+
+
+ | BXH8 |
+ RI 08c-2 |
+
+
+ | BXH8 |
+ RI 08c-3 |
+
+
+ | BXH8 |
+ RI 08c-4 |
+
+
+ | BXH8 |
+ RI 08c-5 |
+
+
+ | BXH9 |
+ RI 09c-1 |
+
+
+ | BXH9 |
+ RI 09c-2 |
+
+
+ | BXH9 |
+ RI 09c-4 |
+
+
+ | BXH9 |
+ RI 09c-5 |
+
+
+ | HXB1 |
+ RI 01-1 |
+
+
+ | HXB1 |
+ RI 01-2 |
+
+
+ | HXB1 |
+ RI 01-4 |
+
+
+ | HXB1 |
+ RI 01-5 |
+
+
+ | HXB10 |
+ RI 10-2 |
+
+
+ | HXB10 |
+ RI 10-3 |
+
+
+ | HXB10 |
+ RI 10-4 |
+
+
+ | HXB10 |
+ RI 10-5 |
+
+
+ | HXB15 |
+ RI 15-1 |
+
+
+ | HXB15 |
+ RI 15-2 |
+
+
+ | HXB15 |
+ RI 15-5 |
+
+
+ | HXB15 |
+ RI 15-6 |
+
+
+ | HXB17 |
+ RI 17-1 |
+
+
+ | HXB17 |
+ RI 17-2 |
+
+
+ | HXB17 |
+ *RI 17-3 |
+
+
+ | HXB17 |
+ RI 17-4 |
+
+
+ | HXB18 |
+ RI 18-1 |
+
+
+ | HXB18 |
+ RI 18-2 |
+
+
+ | HXB18 |
+ *RI 18-3 |
+
+
+ | HXB18 |
+ RI 18-4 |
+
+
+ | HXB2 |
+ RI 02-1 |
+
+
+ | HXB2 |
+ RI 02-2 |
+
+
+ | HXB2 |
+ RI 02-3 |
+
+
+ | HXB2 |
+ RI 02-4 |
+
+
+ | HXB20 |
+ RI 20-1 |
+
+
+ | HXB20 |
+ RI 20-2 |
+
+
+ | HXB20 |
+ *RI 20-3 |
+
+
+ | HXB20 |
+ RI 20-4 |
+
+
+ | HXB21 |
+ RI 21-1 |
+
+
+ | HXB21 |
+ RI 21-2 |
+
+
+ | HXB21 |
+ RI 21-3 |
+
+
+ | HXB21 |
+ RI 21-4 |
+
+
+ | HXB22 |
+ RI 22-1 |
+
+
+ | HXB22 |
+ RI 22-2 |
+
+
+ | HXB22 |
+ *RI 22-3 |
+
+
+ | HXB22 |
+ RI 22-4 |
+
+
+ | HXB23 |
+ RI 23-1 |
+
+
+ | HXB23 |
+ RI 23-2 |
+
+
+ | HXB23 |
+ RI 23-3 |
+
+
+ | HXB23 |
+ RI 23-4 |
+
+
+ | HXB24 |
+ RI 24-1 |
+
+
+ | HXB24 |
+ RI 24-2 |
+
+
+ | HXB24 |
+ RI 24-3 |
+
+
+ | HXB24 |
+ RI 24-5 |
+
+
+ | HXB25 |
+ RI 25-1 |
+
+
+ | HXB25 |
+ RI 25-3 |
+
+
+ | HXB25 |
+ RI 25-4 |
+
+
+ | HXB25 |
+ RI 25-5 |
+
+
+ | HXB26 |
+ RI 26-1 |
+
+
+ | HXB26 |
+ RI 26-2 |
+
+
+ | HXB26 |
+ *RI 26-3 |
+
+
+ | HXB26 |
+ RI 26-4 |
+
+
+ | HXB27 |
+ RI 27-1 |
+
+
+ | HXB27 |
+ RI 27-2 |
+
+
+ | HXB27 |
+ RI 27-3 |
+
+
+ | HXB27 |
+ RI 27-4 |
+
+
+ | HXB29 |
+ RI 29-1 |
+
+
+ | HXB29 |
+ RI 29-2 |
+
+
+ | HXB29 |
+ RI 29-4 |
+
+
+ | HXB29 |
+ RI 29-5 |
+
+
+ | HXB3 |
+ RI 03-1 |
+
+
+ | HXB3 |
+ RI 03-2 |
+
+
+ | HXB3 |
+ RI 03-3 |
+
+
+ | HXB3 |
+ RI 03-4 |
+
+
+ | HXB31 |
+ RI 31-1 |
+
+
+ | HXB31 |
+ RI 31-2 |
+
+
+ | HXB31 |
+ RI 31-3 |
+
+
+ | HXB31 |
+ RI 31-4 |
+
+
+ | HXB4 |
+ RI 04-1 |
+
+
+ | HXB4 |
+ RI 04-2 |
+
+
+ | HXB4 |
+ RI 04-3 |
+
+
+ | HXB4 |
+ RI 04-4 |
+
+
+ | HXB5 |
+ RI 05-1 |
+
+
+ | HXB5 |
+ RI 05-2 |
+
+
+ | HXB5 |
+ RI 05-3 |
+
+
+ | HXB5 |
+ RI 05-4 |
+
+
+ | HXB7 |
+ RI 07-1 |
+
+
+ | HXB7 |
+ RI 07-2 |
+
+
+ | HXB7 |
+ RI 07-3 |
+
+
+ | HXB7 |
+ RI 07-4 |
+
+
+ | HSR |
+ HSR1 |
+
+
+ | HSR |
+ HSR2 |
+
+
+ | HSR |
+ HSR6 |
+
+
+ | HSR |
+ HSR7 |
+
+
+ | HSR |
+ HSR8 |
+
+
+
+ |
+
+
+
+
+*: These six arrays were excluded in the final strain summary data. See section of Quality Control for further explanation.
diff --git a/general/datasets/G2heioncretilm6_0911/acknowledgment.rtf b/general/datasets/G2heioncretilm6_0911/acknowledgment.rtf
new file mode 100644
index 0000000..a41ff76
--- /dev/null
+++ b/general/datasets/G2heioncretilm6_0911/acknowledgment.rtf
@@ -0,0 +1,13 @@
+The HEI Retinal Database is supported by National Eye Institute Grants:
+
+
+
+
+ - R01EY017841 (Dr. Eldon E. Geisert, PI)
+
+
+ - P030EY13080 (NEI Vision Core Grant), and
+
+
+ - A Unrestricted Grand from Research to Prevent Blindness (Dr. Barrett Haik, PI)
+
diff --git a/general/datasets/G2heioncretilm6_0911/cases.rtf b/general/datasets/G2heioncretilm6_0911/cases.rtf
new file mode 100644
index 0000000..b37d700
--- /dev/null
+++ b/general/datasets/G2heioncretilm6_0911/cases.rtf
@@ -0,0 +1,14 @@
+
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 48 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
+
+BXD strains:
+
+
+ - The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s.
+ - In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset.
+ - The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+What Makes the G2 HEI Retina Database different from the HEI Retina Database Examination of Gfap expression across all of the strains in the HEI Retinal Dataset, reveals that some strains express very high levels of Gfap relative to others. For example, BXD24 expresses Gfap at a 9-fold higher level, than BXD22. It has been established that BXD24 acquired a mutation in Cep290 that results in early onset photoreceptor degeneration (Chang et al., 2006). This degeneration results in reactive gliosis throughout the retina. In addition to BXD24, other BXD strains expressed very high levels of Gfap including: BXD32, BXD49, BXD70, BXD83 and BXD89. For the G2 dataset all of these strains with potential reactive gliosis were removed from the dataset.
diff --git a/general/datasets/G2heioncretilm6_0911/contributors.rtf b/general/datasets/G2heioncretilm6_0911/contributors.rtf
new file mode 100644
index 0000000..b1f321b
--- /dev/null
+++ b/general/datasets/G2heioncretilm6_0911/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Justin P. Templeton, Robert W. Williams
diff --git a/general/datasets/G2heioncretilm6_0911/experiment-design.rtf b/general/datasets/G2heioncretilm6_0911/experiment-design.rtf
new file mode 100644
index 0000000..4fff707
--- /dev/null
+++ b/general/datasets/G2heioncretilm6_0911/experiment-design.rtf
@@ -0,0 +1,12 @@
+Expression profiling by array
+
+We used pooled RNA samples of retinas, usually two independent pools--two male, two female pool--for most lines of mice.
+
+All normalization was performed by William E. Orr in the HEI Vision Core Facility
+
+
+ - Computed the log base 2 of each raw signal value
+ - Calculated the mean and standard Deviation of each Mouse WG-6 v2.0 array
+ - Normalized each array using the formula, 2 (z-score of log2 [intensity]) The result is to produce arrays that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - computed the mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
diff --git a/general/datasets/G2heioncretilm6_0911/experiment-type.rtf b/general/datasets/G2heioncretilm6_0911/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/G2heioncretilm6_0911/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/G2heioncretilm6_0911/notes.rtf b/general/datasets/G2heioncretilm6_0911/notes.rtf
new file mode 100644
index 0000000..13ff99a
--- /dev/null
+++ b/general/datasets/G2heioncretilm6_0911/notes.rtf
@@ -0,0 +1 @@
+This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/G2heioncretilm6_0911/platform.rtf b/general/datasets/G2heioncretilm6_0911/platform.rtf
new file mode 100644
index 0000000..2c52707
--- /dev/null
+++ b/general/datasets/G2heioncretilm6_0911/platform.rtf
@@ -0,0 +1 @@
+Illumina MouseWG-6 v2.0 arrays: The Illumina Sentrix Mouse-6 BeadChip uses 50-nucleotide probes to interrogate approximately 46,000 sequences from the mouse transcriptome. For each array, the RNA was pooled from two retinas.
diff --git a/general/datasets/G2heioncretilm6_0911/processing.rtf b/general/datasets/G2heioncretilm6_0911/processing.rtf
new file mode 100644
index 0000000..97cc2be
--- /dev/null
+++ b/general/datasets/G2heioncretilm6_0911/processing.rtf
@@ -0,0 +1,2654 @@
+Values of all 45,281 probe sets in this data set range from a low of 6.25 (Rho GTPase activating protein 11A, Arhgap11a, probe ID ILMN_2747167) to a high of 18.08 (Ubiquitin B, Ubb, probe ID ILMN_2516699). This corresponds to 11.83 units or a 1 to 3641 dynamic range of expression (2^11.83). We normalized raw signal values using Beadstudio’s rank invariant normalization algorithm. BXD62 was the strain used as the control group
+
+
+
+Sample Processing: Drs. Natalie E. Freeman-Anderson and Justin P. Templeton extracted the retinas from the mice and Dr. Natalie Freeman-Anderson processed all samples in the HEI Vision Core Facility. The tissue was homogenized and extracted according to the RNA-Stat-60 protocol as described by the manufacturer (Tel-Test, Friendswood, TX) listed above. The quality and purity of RNA was assessed using an Agilent Bioanalyzer 2100 system. The RNA from each sample was processed with the Illumina TotalPrep RNA Amplification Kit (Ambion, Austin, TX) to produce labeled cRNA. The cRNA for each sample was then hybridized to an Illumina Sentrix® Mouse-6-V2 BeadChip (Illumina, San Diego, CA)
+
+
+
+
+
+Quality control analysis of the raw image data was performed using the Illumina BeadStudio software. MIAME standards were used for all microarray data. Rank invariant normalization with BeadStudio software was used to calculate the data. Once this data was collected, the data was globally normalized across all samples using the formula 2 (z-score of log2 [intensity]) + 8.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
+
+Table 1: HEI Retina case IDs, including sample tube ID, strain, age, sex, and source of mice
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Age |
+ Sex |
+ Source of Animal |
+
+
+ | 1 |
+ 121608_11-C57BL/6JcFA |
+ C57BL/6J |
+ 69 |
+ F |
+ JAX |
+
+
+ | 2 |
+ 121608_12-C57BL/6JcFB |
+ C57BL/6J |
+ 69 |
+ F |
+ JAX |
+
+
+ | 3 |
+ KA7444-C57BL/6JcMC |
+ C57BL/6J |
+ 97 |
+ M |
+ UTHSC RW |
+
+
+ | 4 |
+ KA7444-C57BL/6JcMD |
+ C57BL/6J |
+ 97 |
+ M |
+ UTHSC RW |
+
+
+ | 5 |
+ 31209.05-DBA2JcFA |
+ DBA2J |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 6 |
+ 31209.05-DBA2JcFB |
+ DBA2J |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 7 |
+ 121608_13-DBA/2JcMA |
+ DBA/2J |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 8 |
+ 121608_14-DBA/2JcMB |
+ DBA/2J |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 9 |
+ KA7446-B6D2F1cFA |
+ B6D2F1 |
+ 92 |
+ F |
+ UTHSC RW |
+
+
+ | 10 |
+ KA7446-B6D2F1cFB |
+ B6D2F1 |
+ 92 |
+ F |
+ UTHSC RW |
+
+
+ | 11 |
+ KA7446-B6D2F1cMC |
+ B6D2F1 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 12 |
+ KA7446-B6D2F1cMD |
+ B6D2F1 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 13 |
+ KA7466-D2B6F1cFA |
+ D2B6F1 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 14 |
+ KA7466-D2B6F1cFB |
+ D2B6F1 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 15 |
+ KA7466-D2B6F1cMC |
+ D2B6F1 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 16 |
+ KA7466-D2B6F1cMD |
+ D2B6F1 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 17 |
+ 82609.13-1cFA |
+ BXD01 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 18 |
+ 82609.14-1cFB |
+ BXD01 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 19 |
+ KA7389-1cFA |
+ BXD01 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 20 |
+ KA7389-1cFB |
+ BXD01 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 21 |
+ KA7389-1cMC |
+ BXD01 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 22 |
+ KA7389-1cMD |
+ BXD01 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 23 |
+ KA7300-2cFA |
+ BXD02 |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 24 |
+ KA7300-2cFB |
+ BXD02 |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 25 |
+ 100909.01-2cMA |
+ BXD02 |
+ 65 |
+ M |
+ JAX |
+
+
+ | 26 |
+ 100909.02-2cMB |
+ BXD02 |
+ 65 |
+ M |
+ JAX |
+
+
+ | 27 |
+ KA6699-5cFA |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 28 |
+ KA6699-5cFB |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 29 |
+ KA6699-5cFC |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 30 |
+ KA6699-5cFD |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 31 |
+ 82609.09-5cMA |
+ BXD05 |
+ 60 |
+ M |
+ JAX |
+
+
+ | 32 |
+ 82609.1-5cMB |
+ BXD05 |
+ 60 |
+ M |
+ JAX |
+
+
+ | 33 |
+ KA6763-6cFA |
+ BXD06 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 34 |
+ KA6763-6cFB |
+ BXD06 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 35 |
+ 81209.06-6cMA |
+ BXD06 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 36 |
+ 81209.07-6cMB |
+ BXD06 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 37 |
+ 82609.07-8cFA |
+ BXD08 |
+ 68 |
+ F |
+ JAX |
+
+
+ | 38 |
+ 82609.08-8cFB |
+ BXD08 |
+ 68 |
+ F |
+ JAX |
+
+
+ | 39 |
+ JAX-8cMA |
+ BXD08 |
+ 76 |
+ M |
+ JAX |
+
+
+ | 40 |
+ JAX-8cMB |
+ BXD08 |
+ 76 |
+ M |
+ JAX |
+
+
+ | 41 |
+ KA7289-9cFA |
+ BXD09 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 42 |
+ KA7289-9cFB |
+ BXD09 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 43 |
+ KA7289-9cMC |
+ BXD09 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 44 |
+ KA7289-9cMD |
+ BXD09 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 45 |
+ JAX-11cFA |
+ BXD11 |
+ 84 |
+ F |
+ JAX |
+
+
+ | 46 |
+ JAX-11cFB |
+ BXD11 |
+ 84 |
+ F |
+ JAX |
+
+
+ | 47 |
+ JAX-11cMC |
+ BXD11 |
+ 71 |
+ M |
+ JAX |
+
+
+ | 48 |
+ JAX-11cMD |
+ BXD11 |
+ 71 |
+ M |
+ JAX |
+
+
+ | 49 |
+ 40209.07-12cFA |
+ BXD12 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 50 |
+ 40209.08-12cFB |
+ BXD12 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 51 |
+ 011309.01-12cMA |
+ BXD12 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 52 |
+ 011309.02-12cMB |
+ BXD12 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 53 |
+ KA7286-13cFA |
+ BXD13 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 54 |
+ KA7286-13cFB |
+ BXD13 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 55 |
+ KA7286-13cMC |
+ BXD13 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 56 |
+ KA7286-13cMD |
+ BXD13 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 57 |
+ KA7302-14cFA |
+ BXD14 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 58 |
+ KA7302-14cFB |
+ BXD14 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 59 |
+ 100909.05-14cMA |
+ BXD14 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 60 |
+ 100909.06-14cMB |
+ BXD14 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 61 |
+ KA7288-15cFA |
+ BXD15 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 62 |
+ KA7288-15cFB |
+ BXD15 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 63 |
+ KA7288-15cMC |
+ BXD15 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 64 |
+ KA7288-15cMD |
+ BXD15 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 65 |
+ 062509.01-16cFA |
+ BXD16 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 66 |
+ KA7267-16cMA |
+ BXD16 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 67 |
+ KA7267-16cMB |
+ BXD16 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 68 |
+ KA6686-18cFB |
+ BXD18 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 69 |
+ KA6686-18cFC |
+ BXD18 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 70 |
+ KA6686-18cME |
+ BXD18 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 71 |
+ KA6686-18cMF |
+ BXD18 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 72 |
+ KA6676-19cFB |
+ BXD19 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 73 |
+ KA6676-19cFC |
+ BXD19 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 74 |
+ KA6676-19cME |
+ BXD19 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 75 |
+ KA6676-19cMF |
+ BXD19 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 76 |
+ 060409.05-20cFA |
+ BXD20 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 77 |
+ 060409.06-20cFB |
+ BXD20 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 78 |
+ 021909.03-20cMA |
+ BXD20 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 79 |
+ 021909.04-20cMB |
+ BXD20 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 80 |
+ 82609.02-21cFC |
+ BXD21 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 81 |
+ 82609.03-21cFD |
+ BXD21 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 82 |
+ 121709.01-21cMA |
+ BXD21 |
+ 80 |
+ M |
+ JAX |
+
+
+ | 83 |
+ 121709.02-21cMB |
+ BXD21 |
+ 80 |
+ M |
+ JAX |
+
+
+ | 84 |
+ 121709.03-22cFA |
+ BXD22 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 85 |
+ 121709.04-22cFB |
+ BXD22 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 86 |
+ 092308_03-22cMA |
+ BXD22 |
+ 118 |
+ M |
+ UTHSC RW |
+
+
+ | 87 |
+ 092308_04-22cMB |
+ BXD22 |
+ 118 |
+ M |
+ UTHSC RW |
+
+
+ | 88 |
+ 80409.01-24AcFA |
+ BXD24A |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 89 |
+ 080409_02_24AcFB |
+ BXD24A |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 90 |
+ 82609.26-24AcFC |
+ BXD24A |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 91 |
+ 81209.03-24AcMC |
+ BXD24A |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 92 |
+ KA6678-24cFA |
+ BXD24 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 93 |
+ KA6678-24cFB |
+ BXD24 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 94 |
+ KA6678-24cME |
+ BXD24 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 95 |
+ KA6678-24cMF |
+ BXD24 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 96 |
+ 060409.07-27cFA |
+ BXD27 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 97 |
+ 060409.08-27cFB |
+ BXD27 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 98 |
+ 80409.03-27cMA |
+ BXD27 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 99 |
+ 80409.04-27cMB |
+ BXD27 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 100 |
+ JAX-28cFA |
+ BXD28 |
+ 67 |
+ F |
+ JAX |
+
+
+ | 101 |
+ JAX-28cFB |
+ BXD28 |
+ 67 |
+ F |
+ JAX |
+
+
+ | 102 |
+ JAX-28cMC |
+ BXD28 |
+ 67 |
+ M |
+ JAX |
+
+
+ | 103 |
+ JAX-28cMD |
+ BXD28 |
+ 67 |
+ M |
+ JAX |
+
+
+ | 104 |
+ 82609.11-29cFA |
+ BXD29 |
+ 66 |
+ F |
+ JAX |
+
+
+ | 105 |
+ 82609.12-29cFB |
+ BXD29 |
+ 66 |
+ F |
+ JAX |
+
+
+ | 106 |
+ 82609.04-29cMA |
+ BXD29 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 107 |
+ 82609.05-29cMB |
+ BXD29 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 108 |
+ JAX-31cMB |
+ BXD 31 |
+ 56 |
+ M |
+ JAX |
+
+
+ | 109 |
+ JAX-31cFC |
+ BXD 31 |
+ 69 |
+ F |
+ JAX |
+
+
+ | 110 |
+ JAX-31cFD |
+ BXD 31 |
+ 69 |
+ F |
+ JAX |
+
+
+ | 111 |
+ 011309.03-32cFA |
+ BXD32 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 112 |
+ 011309.04-32cFB |
+ BXD32 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 113 |
+ KA7318-32cFC |
+ BXD32 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 114 |
+ KA7319-32cMA |
+ BXD32 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 115 |
+ KA7319-32cMB |
+ BXD32 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 116 |
+ 100909.07-33cFA |
+ BXD33 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 117 |
+ 100909.08-33cFB |
+ BXD33 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 118 |
+ 022609.01-33cMA |
+ BXD33 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 119 |
+ 022609.02-33cMB |
+ BXD33 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 120 |
+ KA7416-34cFA |
+ BXD34 |
+ 97 |
+ F |
+ UTHSC RW |
+
+
+ | 121 |
+ KA7416-34cFB |
+ BXD34 |
+ 97 |
+ F |
+ UTHSC RW |
+
+
+ | 122 |
+ KA6321-34cMA |
+ BXD34 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 123 |
+ KA6321-34cMB |
+ BXD34 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 124 |
+ 060409.01-36cFA |
+ BXD36 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 125 |
+ 060409.02-36cFB |
+ BXD36 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 126 |
+ 060409.03-36cMC |
+ BXD36 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 127 |
+ KA6702-38cFA |
+ BXD38 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 128 |
+ KA6702-38cFB |
+ BXD38 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 129 |
+ 82609.24-38cFA |
+ BXD38 |
+ 85 |
+ F |
+ UTHSC RW |
+
+
+ | 130 |
+ 82609.25-38cFB |
+ BXD38 |
+ 85 |
+ F |
+ UTHSC RW |
+
+
+ | 131 |
+ 100909.03-38cMA |
+ BXD38 |
+ 61 |
+ M |
+ JAX |
+
+
+ | 132 |
+ 100909.04-38cMB |
+ BXD38 |
+ 61 |
+ M |
+ JAX |
+
+
+ | 133 |
+ 022609.05-39cFA |
+ BXD39 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 134 |
+ 022609.06-39cFB |
+ BXD39 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 135 |
+ 31209.01-39cMC |
+ BXD39 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 136 |
+ 92409.01-40cFA |
+ BXD40 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 137 |
+ 92409.02-40cFB |
+ BXD40 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 138 |
+ KA6173-40cMA |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 139 |
+ KA6173-40cMB |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 140 |
+ KA6173-40cMC |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 141 |
+ 091809.01-42cFA |
+ BXD42 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 142 |
+ 091809.02-42cFB |
+ BXD42 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 143 |
+ 021909.01-42cFA |
+ BXD42 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 144 |
+ 011309.06-42cMA |
+ BXD42 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 145 |
+ 011309.07-42cMB |
+ BXD42 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 146 |
+ 110408_02-43cFA |
+ BXD43 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 147 |
+ 110408_03-43cFB |
+ BXD43 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 148 |
+ KA6158-43cMA |
+ BXD43 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 149 |
+ KA6158-43cMB |
+ BXD43 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 150 |
+ 100308_01-44cFA |
+ BXD44 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 151 |
+ 102208_02-44cMD |
+ BXD44 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 152 |
+ 103009.03-45cFA |
+ BXD45 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 153 |
+ 103009.04-45cFB |
+ BXD45 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 154 |
+ 022609.03-45cFA |
+ BXD45 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 155 |
+ 022609.04-45cFB |
+ BXD45 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 156 |
+ 40309.05-45cMB |
+ BXD45 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 157 |
+ 40209.05-48cFB |
+ BXD48 |
+ 58 |
+ F |
+ VAMC |
+
+
+ | 158 |
+ 40209.06-48cFC |
+ BXD48 |
+ 58 |
+ F |
+ VAMC |
+
+
+ | 159 |
+ 81209.04-48cMA |
+ BXD48 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 160 |
+ 81209.05-48cMB |
+ BXD48 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 161 |
+ 81209.08-49cFA |
+ BXD49 |
+ 70 |
+ F |
+ VAMC |
+
+
+ | 162 |
+ 81209.09-49cFB |
+ BXD49 |
+ 70 |
+ F |
+ VAMC |
+
+
+ | 163 |
+ 40209.01-49cMA |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 164 |
+ 40209.02-49cMB |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 165 |
+ 40209.03-49cMC |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 166 |
+ KA737850cFA |
+ BXD50 |
+ 50 |
+ F |
+ UTHSC RW |
+
+
+ | 167 |
+ KA737850cFB |
+ BXD50 |
+ 50 |
+ F |
+ UTHSC RW |
+
+
+ | 168 |
+ 121908_01-50cMA |
+ BXD50 |
+ 49 |
+ M |
+ UTHSC RW |
+
+
+ | 169 |
+ 121908_02-50cMB |
+ BXD50 |
+ 49 |
+ M |
+ UTHSC RW |
+
+
+ | 170 |
+ 111208_01-51cFA |
+ BXD51 |
+ 99 |
+ F |
+ UTHSC RW |
+
+
+ | 171 |
+ 102208_03-51cMA |
+ BXD51 |
+ 56 |
+ M |
+ UTHSC RW |
+
+
+ | 172 |
+ 102208_04-51cMB |
+ BXD51 |
+ 56 |
+ M |
+ UTHSC RW |
+
+
+ | 173 |
+ 090208_14-53BcFA |
+ BXD53B |
+ 93 |
+ F |
+ UTHSC RW |
+
+
+ | 174 |
+ 090208_15-53BcFB |
+ BXD53B |
+ 93 |
+ F |
+ UTHSC RW |
+
+
+ | 175 |
+ 090208_16-53BcMC |
+ BXD53B |
+ 93 |
+ M |
+ UTHSC RW |
+
+
+ | 176 |
+ 090208_17-53BcMD |
+ BXD53B |
+ 93 |
+ M |
+ UTHSC RW |
+
+
+ | 177 |
+ 111208_05-55cFB |
+ BXD55 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 178 |
+ KA6183-55cMA |
+ BXD55 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 179 |
+ KA6183-55cMB |
+ BXD55 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 180 |
+ KA7362-56cFB |
+ BXD 56 |
+ 54 |
+ F |
+ UTHSC RW |
+
+
+ | 181 |
+ KA6088-56cMA |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 182 |
+ KA6088-56cMB |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 183 |
+ KA6088-56cMC |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 184 |
+ 21810.01-60RFA |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 185 |
+ 21810.02-60RFB |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 186 |
+ 21810.02-60RFC |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 187 |
+ SQ7325-60cMA |
+ BXD60 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 188 |
+ SQ7325-60cMB |
+ BXD60 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 189 |
+ 092308_10-61cFA |
+ BXD61 |
+ 110 |
+ F |
+ UTHSC RW |
+
+
+ | 190 |
+ 092308_11-61cFB |
+ BXD61 |
+ 110 |
+ F |
+ UTHSC RW |
+
+
+ | 191 |
+ 31909.01-61cMA |
+ BXD61 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 192 |
+ 31909.02-61cMB |
+ BXD61 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 193 |
+ KA7462-62cFA |
+ BXD62 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 194 |
+ KA7462-62cFB |
+ BXD62 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 195 |
+ KA5996-62cMA |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 196 |
+ KA5996-62cMB |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 197 |
+ KA5996-62cMC |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 198 |
+ 090309.01-63cFA |
+ BXD63 |
+ 69 |
+ F |
+ UTHSC RW |
+
+
+ | 199 |
+ 090309.02-63cFB |
+ BXD63 |
+ 69 |
+ F |
+ UTHSC RW |
+
+
+ | 200 |
+ 110609.01-63cMA |
+ BXD63 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 201 |
+ 110609.02-63cMB |
+ BXD63 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 202 |
+ 091809.03-65cFA |
+ BXD65 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 203 |
+ 091809.04-65cFB |
+ BXD65 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 204 |
+ 103009.01-65cMA |
+ BXD65 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 205 |
+ 103009.02-65cMB |
+ BXD65 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 206 |
+ 110408_05-66cFB |
+ BXD66 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 207 |
+ KA7165-66cMA |
+ BXD66 |
+ 95 |
+ M |
+ UTHSC RW |
+
+
+ | 208 |
+ KA7165-66cMB |
+ BXD66 |
+ 95 |
+ M |
+ UTHSC RW |
+
+
+ | 209 |
+ 90809.01-67cMA |
+ BXD67 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 210 |
+ 90809.02-67cMB |
+ BXD67 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 211 |
+ 110609.03-67cFA |
+ BXD67 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 212 |
+ 110609.04-67cFB |
+ BXD67 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 213 |
+ 120408_01-68cFA |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 214 |
+ 120408_02-68cFB |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 215 |
+ SQ7205-68cMA |
+ BXD68 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 216 |
+ SQ7205-68cMB |
+ BXD68 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 217 |
+ KA6316-68cMA |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 218 |
+ KA6316-68cMB |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 219 |
+ KA6316-68cMC |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 220 |
+ KA76-69cFA |
+ BXD69 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 221 |
+ KA76-69cFB |
+ BXD69 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 222 |
+ KA6074-69cMA |
+ BXD69 |
+ 90 |
+ M |
+ UTHSC RW |
+
+
+ | 223 |
+ KA6074-69cMB |
+ BXD69 |
+ 90 |
+ M |
+ UTHSC RW |
+
+
+ | 224 |
+ 121608_01-70cFA |
+ BXD70 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 225 |
+ 121608_02-70cFB |
+ BXD70 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 226 |
+ KA7394-70cMA |
+ BXD70 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 227 |
+ 81209.08-70cMA |
+ BXD70 |
+ 71 |
+ M |
+ VAMC |
+
+
+ | 228 |
+ 81209.09-70cMB |
+ BXD70 |
+ 71 |
+ M |
+ VAMC |
+
+
+ | 229 |
+ 052809.01-71cFA |
+ BXD71 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 230 |
+ 060409.09-71cMA |
+ BXD71 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 231 |
+ 060409.10-71cMB |
+ BXD71 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 232 |
+ 40809.01-73cFA |
+ BXD73 |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 233 |
+ 40809.02-73cFB |
+ BXD73 |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 234 |
+ 111708_01-73cFA |
+ BXD73 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 235 |
+ 111708_01-73cFB |
+ BXD73 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 236 |
+ KA6164-73cMB |
+ BXD73 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 237 |
+ KA6164-73cMC |
+ BXD73 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 238 |
+ 82609.22-74cFA |
+ BXD74 |
+ 68 |
+ F |
+ VAMC |
+
+
+ | 239 |
+ 82609.23-74cFB |
+ BXD74 |
+ 68 |
+ F |
+ VAMC |
+
+
+ | 240 |
+ 82609.20-74cMA |
+ BXD74 |
+ 68 |
+ M |
+ VAMC |
+
+
+ | 241 |
+ 82609.21-74cMB |
+ BXD74 |
+ 68 |
+ M |
+ VAMC |
+
+
+ | 242 |
+ KA733675cFA |
+ BXD75 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 243 |
+ KA733675cFB |
+ BXD75 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 244 |
+ KA38-75cMB |
+ BXD75 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 245 |
+ KA38-75cMC |
+ BXD75 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 246 |
+ 41509.01-77cFA |
+ BXD77 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 247 |
+ 41509.02-77cFB |
+ BXD77 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 248 |
+ 41509.03-77cMC |
+ BXD77 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 249 |
+ 41509.04-77cMD |
+ BXD77 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 250 |
+ 121608_03-80cFA |
+ BXD80 |
+ 77 |
+ F |
+ UTHSC RW |
+
+
+ | 251 |
+ 121608_05-80cMC |
+ BXD80 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 252 |
+ KA23-80cMC |
+ BXD80 |
+ 77 |
+ M |
+ UTHSC RW |
+
+
+ | 253 |
+ KA7305-81cFA |
+ BXD81 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 254 |
+ KA7305-81cFB |
+ BXD81 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 255 |
+ KA7305-81cMD |
+ BXD81 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 256 |
+ 060409.11-83cFA |
+ BXD83 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 257 |
+ KA24-83cFA |
+ BXD83 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 258 |
+ 121608_07-83cMA |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 259 |
+ 121608_08-83cMB |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 260 |
+ KA24-83cMD |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 261 |
+ 090409.05-84cFA |
+ BXD84 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 262 |
+ 090409.06-84cFB |
+ BXD84 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 263 |
+ KA6203-84cMA |
+ BXD84 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 264 |
+ KA6203-84cMB |
+ BXD84 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 265 |
+ 40309.02-85cFD |
+ BXD85 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 266 |
+ 40309.03-85cFE |
+ BXD85 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 267 |
+ 32609.01-85cMA |
+ BXD85 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 268 |
+ 32609.02-85cMB |
+ BXD85 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 269 |
+ 41509.05-86cFA |
+ BXD86 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 270 |
+ 41509.06-86cFB |
+ BXD86 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 271 |
+ KA6101-86cMA |
+ BXD86 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 272 |
+ KA6101-86cMC |
+ BXD86 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 273 |
+ 070909.02-87cFA |
+ BXD87 |
+ 86 |
+ F |
+ UTHSC RW |
+
+
+ | 274 |
+ 070909.03-87cFB |
+ BXD87 |
+ 86 |
+ F |
+ UTHSC RW |
+
+
+ | 275 |
+ KA7407-87cMA |
+ BXD87 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 276 |
+ KA7407-87cMB |
+ BXD87 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 277 |
+ 102208_05-89cFA |
+ BXD89 |
+ 82 |
+ F |
+ UTHSC RW |
+
+
+ | 278 |
+ KA5974-89cMA |
+ BXD89 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 279 |
+ KA5974-89cMB |
+ BXD89 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 280 |
+ 102208_06-89cMC |
+ BXD89 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 281 |
+ 72309.01-90cFA |
+ BXD90 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 282 |
+ 72309.02-90cFB |
+ BXD90 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 283 |
+ 090409.03-90cMA |
+ BXD90 |
+ 64 |
+ M |
+ VAMC |
+
+
+ | 284 |
+ 090409.04-90cMB |
+ BXD90 |
+ 64 |
+ M |
+ VAMC |
+
+
+ | 285 |
+ KA6094-92cMA |
+ BXD92 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 286 |
+ 020609.01-95cFA |
+ BXD95 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 287 |
+ 020609.02-95cFB |
+ BXD95 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 288 |
+ KA6181-95cMA |
+ BXD95 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 289 |
+ KA6181-95cMB |
+ BXD95 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 290 |
+ 31209.03-96cFA |
+ BXD96 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 291 |
+ 31209.04-96cFB |
+ BXD96 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 292 |
+ KA7246-96cMA |
+ BXD96 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 293 |
+ KA7246-96cMB |
+ BXD96 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 294 |
+ 81209.10-97cFA |
+ BXD97 |
+ 83 |
+ F |
+ VAMC |
+
+
+ | 295 |
+ 81209.11-97cFB |
+ BXD97 |
+ 83 |
+ F |
+ VAMC |
+
+
+ | 296 |
+ 81209.1-97cMA |
+ BXD97 |
+ 83 |
+ M |
+ VAMC |
+
+
+ | 297 |
+ 81209.11-97cMB |
+ BXD97 |
+ 83 |
+ M |
+ VAMC |
+
+
+ | 298 |
+ SQ7520-98cFA |
+ BXD98 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 299 |
+ SQ7520-98cFB |
+ BXD98 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 300 |
+ SQ7520-98cMC |
+ BXD98 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 301 |
+ SQ7520-98cMD |
+ BXD98 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 302 |
+ 82609.17-99cFA |
+ BXD99 |
+ 64 |
+ F |
+ VAMC |
+
+
+ | 303 |
+ 82609.18-99cFB |
+ BXD99 |
+ 64 |
+ F |
+ VAMC |
+
+
+ | 304 |
+ 81409.01-99cMA |
+ BXD99 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 305 |
+ 81409.02-99cMB |
+ BXD99 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 306 |
+ 121608_09-100cFA |
+ BXD100 |
+ 81 |
+ F |
+ UTHSC RW |
+
+
+ | 307 |
+ 121608_10-100cFB |
+ BXD100 |
+ 81 |
+ F |
+ UTHSC RW |
+
+
+ | 308 |
+ KA6001-100cMA |
+ BXD100 |
+ 111 |
+ M |
+ UTHSC RW |
+
+
+ | 309 |
+ KA6001-100cMB |
+ BXD100 |
+ 111 |
+ M |
+ UTHSC RW |
+
+
+ | 310 |
+ 81209.12-101cFA |
+ BXD101 |
+ 72 |
+ F |
+ VAMC |
+
+
+ | 311 |
+ 81209.13-101cFB |
+ BXD101 |
+ 72 |
+ F |
+ VAMC |
+
+
+ | 312 |
+ KA7296-101cMA |
+ BXD101 |
+ 75 |
+ M |
+ UTHSC RW |
+
+
+ | 313 |
+ KA7296-101cMB |
+ BXD101 |
+ 75 |
+ M |
+ UTHSC RW |
+
+
+ | 314 |
+ 92409.03-102cFA |
+ BXD102 |
+ 71 |
+ F |
+ VAMC |
+
+
+ | 315 |
+ 92409.04-102cFB |
+ BXD102 |
+ 71 |
+ F |
+ VAMC |
+
+
+ | 316 |
+ KA7380-102cMA |
+ BXD102 |
+ 115 |
+ M |
+ UTHSC RW |
+
+
+ | 317 |
+ 43009.01-103cFA |
+ BXD103 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 318 |
+ 43009.02-103cFB |
+ BXD103 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 319 |
+ KA79-103cFA |
+ BXD103 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 320 |
+ KA79-103cFB |
+ BXD103 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 321 |
+ KA79-103cMC |
+ BXD103 |
+ 48 |
+ M |
+ UTHSC RW |
+
+
+ | 322 |
+ 82609.15-103cMA |
+ BXD103 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 323 |
+ 82609.16-103cMB |
+ BXD103 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 324 |
+ 102909.01-BALBCcFA |
+ BALB/cByJ |
+ 78 |
+ F |
+ JAX |
+
+
+ | 325 |
+ 102909.02-BALBCcFB |
+ BALB/cByJ |
+ 78 |
+ F |
+ JAX |
+
+
+ | 326 |
+ 102909.03-BALBCcMA |
+ BALB/cByJ |
+ 78 |
+ M |
+ JAX |
+
+
+ | 327 |
+ 102909.04-BALBCcMB |
+ BALB/cByJ |
+ 78 |
+ M |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/G2heioncretilm6_0911/summary.rtf b/general/datasets/G2heioncretilm6_0911/summary.rtf
new file mode 100644
index 0000000..44e98a7
--- /dev/null
+++ b/general/datasets/G2heioncretilm6_0911/summary.rtf
@@ -0,0 +1,50 @@
+
+This is a subtractive dataset. The Normal retina dataset was subtracted from the ONC data set probe by probe to create a data set of the changes occurring following ONC. This data set can be used to define gene changes following ONC. It is not compatible with most of the bioinformatic tools available on GeneNetwork.
+
+HEI Retina Illumina V6.2 (April 2010) RankInv was normalized and scaled by William E. Orr and uploaded by Arthur Centeno and Xiaodong Zhou on April 7, 2010. This data set consists of either 69 BXD strains (Normal data set) or 75 BXD strains (Full data set), C57BL/6J, DBA/2J, both reciprocal F1s, and BALB/cByJ. A total of either 74 strains (Normal data set) or 80 strains (Full data set) were quantified.
+
+COMMENT on FULL versus NORMAL data sets: For many general uses there is no significant difference between FULL and NORMAL data sets. However, the FULL data set includes strains with high endogenous Gfap mRNA expression, indicative of reactive gliosis. For that reason, and to compare to OPTIC NERVE CRUSH (ONC), we removed data from six strains to make the NORMAL data set.
+
+The NORMAL data set exludes data from BXD24, BXD32, BXD49, BXD70, BXD83, and BXD89. BXD24 has known retinal degeneration and is now known officially as BXD24/TyJ-Cep290/J, JAX Stock number 000031. BXD32 has mild retinal degeneration. The NORMAL data set does include BXD24a, now also known as BXD24/TyJ (JAX Stock number 005243).
+
+The data are now open and available for analysis.
+
+Please cite: Freeman NE, Templeton JP, Orr WE, Lu L, Williams RW, Geisert EE (2011) Genetic networks in the mouse retina: Growth Associated Protein 43 and Phosphate Tensin Homology network. Molecular Vision 17:1355-1372. Full Text PDF or HTML
+
+This is rank invariant expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 6.25 to 18.08 (11.83 units), a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
+
+The lowest level of expression is 6.254 for ILMN_2747167 (Arhgap11a) from HEI Retina Illumina V6.2 (April 2010) RankInv **. Lowest single data about 5.842.
+
+The highest level of expression is 18.077 for ILMN_2516699 (Ubb). Highest single value is about 18.934.
+
+
+
+
+Other Related Publications
+
+
+
+
+
+ - Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link)
+ - Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674
+ - Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link)
+ - Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.(Link)
+
+
+
+
+
+
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
+
diff --git a/general/datasets/G2heioncretilm6_0911/tissue.rtf b/general/datasets/G2heioncretilm6_0911/tissue.rtf
new file mode 100644
index 0000000..766ab59
--- /dev/null
+++ b/general/datasets/G2heioncretilm6_0911/tissue.rtf
@@ -0,0 +1,32 @@
+
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RNAlater at room temperature. Two retinas from one mouse were stored in a single tube.
+
+Each array was hybridized with a pool of cRNA from 2 retinas (1 mouse). Natalie Freeman-Anderson extracted RNA at UTHSC.
+
+
+
+Dissecting and preparing eyes for RNA extraction
+
+
+
+Retinas for RNA extraction were placed in RNA STAT-60 (Tel-Test Inc.) and processed per manufacturer’s instructions (in brief form below). Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+
+
+ - Homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue via syringe)
+ - Allow the homogenate to stand for 5-10 min at room temperature
+ - Add 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - Mix the sample vigorously for 15 sec and let the sample incubate at room temperature for 5-10 min
+ - Centrifuge at 12,000 g for 1 hr at 4°C
+ - Transfer the aqueous phase to a clean centrifuge tube
+ - Add 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - Vortex and incubate the sample at -20°C for 1 hr or overnight
+ - Centrifuge at 12,000 g for 1 hr
+ - Remove the supernatant and wash the RNA pellet with 75% ethanol
+ - Remove ethanol, let air dry (5-10 min)
+ - Dissolve the pellet in 50 μl of nuclease free water.
+
+
+
+
diff --git a/general/datasets/G2nei_ilm_retina_bxd_ri0410/acknowledgment.rtf b/general/datasets/G2nei_ilm_retina_bxd_ri0410/acknowledgment.rtf
new file mode 100644
index 0000000..a41ff76
--- /dev/null
+++ b/general/datasets/G2nei_ilm_retina_bxd_ri0410/acknowledgment.rtf
@@ -0,0 +1,13 @@
+The HEI Retinal Database is supported by National Eye Institute Grants:
+
+
+
+
+ - R01EY017841 (Dr. Eldon E. Geisert, PI)
+
+
+ - P030EY13080 (NEI Vision Core Grant), and
+
+
+ - A Unrestricted Grand from Research to Prevent Blindness (Dr. Barrett Haik, PI)
+
diff --git a/general/datasets/G2nei_ilm_retina_bxd_ri0410/cases.rtf b/general/datasets/G2nei_ilm_retina_bxd_ri0410/cases.rtf
new file mode 100644
index 0000000..b37d700
--- /dev/null
+++ b/general/datasets/G2nei_ilm_retina_bxd_ri0410/cases.rtf
@@ -0,0 +1,14 @@
+
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 48 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
+
+BXD strains:
+
+
+ - The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s.
+ - In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset.
+ - The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+What Makes the G2 HEI Retina Database different from the HEI Retina Database Examination of Gfap expression across all of the strains in the HEI Retinal Dataset, reveals that some strains express very high levels of Gfap relative to others. For example, BXD24 expresses Gfap at a 9-fold higher level, than BXD22. It has been established that BXD24 acquired a mutation in Cep290 that results in early onset photoreceptor degeneration (Chang et al., 2006). This degeneration results in reactive gliosis throughout the retina. In addition to BXD24, other BXD strains expressed very high levels of Gfap including: BXD32, BXD49, BXD70, BXD83 and BXD89. For the G2 dataset all of these strains with potential reactive gliosis were removed from the dataset.
diff --git a/general/datasets/G2nei_ilm_retina_bxd_ri0410/contributors.rtf b/general/datasets/G2nei_ilm_retina_bxd_ri0410/contributors.rtf
new file mode 100644
index 0000000..b1f321b
--- /dev/null
+++ b/general/datasets/G2nei_ilm_retina_bxd_ri0410/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Justin P. Templeton, Robert W. Williams
diff --git a/general/datasets/G2nei_ilm_retina_bxd_ri0410/experiment-design.rtf b/general/datasets/G2nei_ilm_retina_bxd_ri0410/experiment-design.rtf
new file mode 100644
index 0000000..4fff707
--- /dev/null
+++ b/general/datasets/G2nei_ilm_retina_bxd_ri0410/experiment-design.rtf
@@ -0,0 +1,12 @@
+Expression profiling by array
+
+We used pooled RNA samples of retinas, usually two independent pools--two male, two female pool--for most lines of mice.
+
+All normalization was performed by William E. Orr in the HEI Vision Core Facility
+
+
+ - Computed the log base 2 of each raw signal value
+ - Calculated the mean and standard Deviation of each Mouse WG-6 v2.0 array
+ - Normalized each array using the formula, 2 (z-score of log2 [intensity]) The result is to produce arrays that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - computed the mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
diff --git a/general/datasets/G2nei_ilm_retina_bxd_ri0410/experiment-type.rtf b/general/datasets/G2nei_ilm_retina_bxd_ri0410/experiment-type.rtf
new file mode 100644
index 0000000..0546e04
--- /dev/null
+++ b/general/datasets/G2nei_ilm_retina_bxd_ri0410/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array
\ No newline at end of file
diff --git a/general/datasets/G2nei_ilm_retina_bxd_ri0410/notes.rtf b/general/datasets/G2nei_ilm_retina_bxd_ri0410/notes.rtf
new file mode 100644
index 0000000..13ff99a
--- /dev/null
+++ b/general/datasets/G2nei_ilm_retina_bxd_ri0410/notes.rtf
@@ -0,0 +1 @@
+This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/G2nei_ilm_retina_bxd_ri0410/platform.rtf b/general/datasets/G2nei_ilm_retina_bxd_ri0410/platform.rtf
new file mode 100644
index 0000000..2c52707
--- /dev/null
+++ b/general/datasets/G2nei_ilm_retina_bxd_ri0410/platform.rtf
@@ -0,0 +1 @@
+Illumina MouseWG-6 v2.0 arrays: The Illumina Sentrix Mouse-6 BeadChip uses 50-nucleotide probes to interrogate approximately 46,000 sequences from the mouse transcriptome. For each array, the RNA was pooled from two retinas.
diff --git a/general/datasets/G2nei_ilm_retina_bxd_ri0410/processing.rtf b/general/datasets/G2nei_ilm_retina_bxd_ri0410/processing.rtf
new file mode 100644
index 0000000..97cc2be
--- /dev/null
+++ b/general/datasets/G2nei_ilm_retina_bxd_ri0410/processing.rtf
@@ -0,0 +1,2654 @@
+Values of all 45,281 probe sets in this data set range from a low of 6.25 (Rho GTPase activating protein 11A, Arhgap11a, probe ID ILMN_2747167) to a high of 18.08 (Ubiquitin B, Ubb, probe ID ILMN_2516699). This corresponds to 11.83 units or a 1 to 3641 dynamic range of expression (2^11.83). We normalized raw signal values using Beadstudio’s rank invariant normalization algorithm. BXD62 was the strain used as the control group
+
+
+
+Sample Processing: Drs. Natalie E. Freeman-Anderson and Justin P. Templeton extracted the retinas from the mice and Dr. Natalie Freeman-Anderson processed all samples in the HEI Vision Core Facility. The tissue was homogenized and extracted according to the RNA-Stat-60 protocol as described by the manufacturer (Tel-Test, Friendswood, TX) listed above. The quality and purity of RNA was assessed using an Agilent Bioanalyzer 2100 system. The RNA from each sample was processed with the Illumina TotalPrep RNA Amplification Kit (Ambion, Austin, TX) to produce labeled cRNA. The cRNA for each sample was then hybridized to an Illumina Sentrix® Mouse-6-V2 BeadChip (Illumina, San Diego, CA)
+
+
+
+
+
+Quality control analysis of the raw image data was performed using the Illumina BeadStudio software. MIAME standards were used for all microarray data. Rank invariant normalization with BeadStudio software was used to calculate the data. Once this data was collected, the data was globally normalized across all samples using the formula 2 (z-score of log2 [intensity]) + 8.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
+
+Table 1: HEI Retina case IDs, including sample tube ID, strain, age, sex, and source of mice
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Age |
+ Sex |
+ Source of Animal |
+
+
+ | 1 |
+ 121608_11-C57BL/6JcFA |
+ C57BL/6J |
+ 69 |
+ F |
+ JAX |
+
+
+ | 2 |
+ 121608_12-C57BL/6JcFB |
+ C57BL/6J |
+ 69 |
+ F |
+ JAX |
+
+
+ | 3 |
+ KA7444-C57BL/6JcMC |
+ C57BL/6J |
+ 97 |
+ M |
+ UTHSC RW |
+
+
+ | 4 |
+ KA7444-C57BL/6JcMD |
+ C57BL/6J |
+ 97 |
+ M |
+ UTHSC RW |
+
+
+ | 5 |
+ 31209.05-DBA2JcFA |
+ DBA2J |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 6 |
+ 31209.05-DBA2JcFB |
+ DBA2J |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 7 |
+ 121608_13-DBA/2JcMA |
+ DBA/2J |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 8 |
+ 121608_14-DBA/2JcMB |
+ DBA/2J |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 9 |
+ KA7446-B6D2F1cFA |
+ B6D2F1 |
+ 92 |
+ F |
+ UTHSC RW |
+
+
+ | 10 |
+ KA7446-B6D2F1cFB |
+ B6D2F1 |
+ 92 |
+ F |
+ UTHSC RW |
+
+
+ | 11 |
+ KA7446-B6D2F1cMC |
+ B6D2F1 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 12 |
+ KA7446-B6D2F1cMD |
+ B6D2F1 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 13 |
+ KA7466-D2B6F1cFA |
+ D2B6F1 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 14 |
+ KA7466-D2B6F1cFB |
+ D2B6F1 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 15 |
+ KA7466-D2B6F1cMC |
+ D2B6F1 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 16 |
+ KA7466-D2B6F1cMD |
+ D2B6F1 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 17 |
+ 82609.13-1cFA |
+ BXD01 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 18 |
+ 82609.14-1cFB |
+ BXD01 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 19 |
+ KA7389-1cFA |
+ BXD01 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 20 |
+ KA7389-1cFB |
+ BXD01 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 21 |
+ KA7389-1cMC |
+ BXD01 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 22 |
+ KA7389-1cMD |
+ BXD01 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 23 |
+ KA7300-2cFA |
+ BXD02 |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 24 |
+ KA7300-2cFB |
+ BXD02 |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 25 |
+ 100909.01-2cMA |
+ BXD02 |
+ 65 |
+ M |
+ JAX |
+
+
+ | 26 |
+ 100909.02-2cMB |
+ BXD02 |
+ 65 |
+ M |
+ JAX |
+
+
+ | 27 |
+ KA6699-5cFA |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 28 |
+ KA6699-5cFB |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 29 |
+ KA6699-5cFC |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 30 |
+ KA6699-5cFD |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 31 |
+ 82609.09-5cMA |
+ BXD05 |
+ 60 |
+ M |
+ JAX |
+
+
+ | 32 |
+ 82609.1-5cMB |
+ BXD05 |
+ 60 |
+ M |
+ JAX |
+
+
+ | 33 |
+ KA6763-6cFA |
+ BXD06 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 34 |
+ KA6763-6cFB |
+ BXD06 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 35 |
+ 81209.06-6cMA |
+ BXD06 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 36 |
+ 81209.07-6cMB |
+ BXD06 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 37 |
+ 82609.07-8cFA |
+ BXD08 |
+ 68 |
+ F |
+ JAX |
+
+
+ | 38 |
+ 82609.08-8cFB |
+ BXD08 |
+ 68 |
+ F |
+ JAX |
+
+
+ | 39 |
+ JAX-8cMA |
+ BXD08 |
+ 76 |
+ M |
+ JAX |
+
+
+ | 40 |
+ JAX-8cMB |
+ BXD08 |
+ 76 |
+ M |
+ JAX |
+
+
+ | 41 |
+ KA7289-9cFA |
+ BXD09 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 42 |
+ KA7289-9cFB |
+ BXD09 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 43 |
+ KA7289-9cMC |
+ BXD09 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 44 |
+ KA7289-9cMD |
+ BXD09 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 45 |
+ JAX-11cFA |
+ BXD11 |
+ 84 |
+ F |
+ JAX |
+
+
+ | 46 |
+ JAX-11cFB |
+ BXD11 |
+ 84 |
+ F |
+ JAX |
+
+
+ | 47 |
+ JAX-11cMC |
+ BXD11 |
+ 71 |
+ M |
+ JAX |
+
+
+ | 48 |
+ JAX-11cMD |
+ BXD11 |
+ 71 |
+ M |
+ JAX |
+
+
+ | 49 |
+ 40209.07-12cFA |
+ BXD12 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 50 |
+ 40209.08-12cFB |
+ BXD12 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 51 |
+ 011309.01-12cMA |
+ BXD12 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 52 |
+ 011309.02-12cMB |
+ BXD12 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 53 |
+ KA7286-13cFA |
+ BXD13 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 54 |
+ KA7286-13cFB |
+ BXD13 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 55 |
+ KA7286-13cMC |
+ BXD13 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 56 |
+ KA7286-13cMD |
+ BXD13 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 57 |
+ KA7302-14cFA |
+ BXD14 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 58 |
+ KA7302-14cFB |
+ BXD14 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 59 |
+ 100909.05-14cMA |
+ BXD14 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 60 |
+ 100909.06-14cMB |
+ BXD14 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 61 |
+ KA7288-15cFA |
+ BXD15 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 62 |
+ KA7288-15cFB |
+ BXD15 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 63 |
+ KA7288-15cMC |
+ BXD15 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 64 |
+ KA7288-15cMD |
+ BXD15 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 65 |
+ 062509.01-16cFA |
+ BXD16 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 66 |
+ KA7267-16cMA |
+ BXD16 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 67 |
+ KA7267-16cMB |
+ BXD16 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 68 |
+ KA6686-18cFB |
+ BXD18 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 69 |
+ KA6686-18cFC |
+ BXD18 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 70 |
+ KA6686-18cME |
+ BXD18 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 71 |
+ KA6686-18cMF |
+ BXD18 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 72 |
+ KA6676-19cFB |
+ BXD19 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 73 |
+ KA6676-19cFC |
+ BXD19 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 74 |
+ KA6676-19cME |
+ BXD19 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 75 |
+ KA6676-19cMF |
+ BXD19 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 76 |
+ 060409.05-20cFA |
+ BXD20 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 77 |
+ 060409.06-20cFB |
+ BXD20 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 78 |
+ 021909.03-20cMA |
+ BXD20 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 79 |
+ 021909.04-20cMB |
+ BXD20 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 80 |
+ 82609.02-21cFC |
+ BXD21 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 81 |
+ 82609.03-21cFD |
+ BXD21 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 82 |
+ 121709.01-21cMA |
+ BXD21 |
+ 80 |
+ M |
+ JAX |
+
+
+ | 83 |
+ 121709.02-21cMB |
+ BXD21 |
+ 80 |
+ M |
+ JAX |
+
+
+ | 84 |
+ 121709.03-22cFA |
+ BXD22 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 85 |
+ 121709.04-22cFB |
+ BXD22 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 86 |
+ 092308_03-22cMA |
+ BXD22 |
+ 118 |
+ M |
+ UTHSC RW |
+
+
+ | 87 |
+ 092308_04-22cMB |
+ BXD22 |
+ 118 |
+ M |
+ UTHSC RW |
+
+
+ | 88 |
+ 80409.01-24AcFA |
+ BXD24A |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 89 |
+ 080409_02_24AcFB |
+ BXD24A |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 90 |
+ 82609.26-24AcFC |
+ BXD24A |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 91 |
+ 81209.03-24AcMC |
+ BXD24A |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 92 |
+ KA6678-24cFA |
+ BXD24 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 93 |
+ KA6678-24cFB |
+ BXD24 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 94 |
+ KA6678-24cME |
+ BXD24 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 95 |
+ KA6678-24cMF |
+ BXD24 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 96 |
+ 060409.07-27cFA |
+ BXD27 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 97 |
+ 060409.08-27cFB |
+ BXD27 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 98 |
+ 80409.03-27cMA |
+ BXD27 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 99 |
+ 80409.04-27cMB |
+ BXD27 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 100 |
+ JAX-28cFA |
+ BXD28 |
+ 67 |
+ F |
+ JAX |
+
+
+ | 101 |
+ JAX-28cFB |
+ BXD28 |
+ 67 |
+ F |
+ JAX |
+
+
+ | 102 |
+ JAX-28cMC |
+ BXD28 |
+ 67 |
+ M |
+ JAX |
+
+
+ | 103 |
+ JAX-28cMD |
+ BXD28 |
+ 67 |
+ M |
+ JAX |
+
+
+ | 104 |
+ 82609.11-29cFA |
+ BXD29 |
+ 66 |
+ F |
+ JAX |
+
+
+ | 105 |
+ 82609.12-29cFB |
+ BXD29 |
+ 66 |
+ F |
+ JAX |
+
+
+ | 106 |
+ 82609.04-29cMA |
+ BXD29 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 107 |
+ 82609.05-29cMB |
+ BXD29 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 108 |
+ JAX-31cMB |
+ BXD 31 |
+ 56 |
+ M |
+ JAX |
+
+
+ | 109 |
+ JAX-31cFC |
+ BXD 31 |
+ 69 |
+ F |
+ JAX |
+
+
+ | 110 |
+ JAX-31cFD |
+ BXD 31 |
+ 69 |
+ F |
+ JAX |
+
+
+ | 111 |
+ 011309.03-32cFA |
+ BXD32 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 112 |
+ 011309.04-32cFB |
+ BXD32 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 113 |
+ KA7318-32cFC |
+ BXD32 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 114 |
+ KA7319-32cMA |
+ BXD32 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 115 |
+ KA7319-32cMB |
+ BXD32 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 116 |
+ 100909.07-33cFA |
+ BXD33 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 117 |
+ 100909.08-33cFB |
+ BXD33 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 118 |
+ 022609.01-33cMA |
+ BXD33 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 119 |
+ 022609.02-33cMB |
+ BXD33 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 120 |
+ KA7416-34cFA |
+ BXD34 |
+ 97 |
+ F |
+ UTHSC RW |
+
+
+ | 121 |
+ KA7416-34cFB |
+ BXD34 |
+ 97 |
+ F |
+ UTHSC RW |
+
+
+ | 122 |
+ KA6321-34cMA |
+ BXD34 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 123 |
+ KA6321-34cMB |
+ BXD34 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 124 |
+ 060409.01-36cFA |
+ BXD36 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 125 |
+ 060409.02-36cFB |
+ BXD36 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 126 |
+ 060409.03-36cMC |
+ BXD36 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 127 |
+ KA6702-38cFA |
+ BXD38 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 128 |
+ KA6702-38cFB |
+ BXD38 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 129 |
+ 82609.24-38cFA |
+ BXD38 |
+ 85 |
+ F |
+ UTHSC RW |
+
+
+ | 130 |
+ 82609.25-38cFB |
+ BXD38 |
+ 85 |
+ F |
+ UTHSC RW |
+
+
+ | 131 |
+ 100909.03-38cMA |
+ BXD38 |
+ 61 |
+ M |
+ JAX |
+
+
+ | 132 |
+ 100909.04-38cMB |
+ BXD38 |
+ 61 |
+ M |
+ JAX |
+
+
+ | 133 |
+ 022609.05-39cFA |
+ BXD39 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 134 |
+ 022609.06-39cFB |
+ BXD39 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 135 |
+ 31209.01-39cMC |
+ BXD39 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 136 |
+ 92409.01-40cFA |
+ BXD40 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 137 |
+ 92409.02-40cFB |
+ BXD40 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 138 |
+ KA6173-40cMA |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 139 |
+ KA6173-40cMB |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 140 |
+ KA6173-40cMC |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 141 |
+ 091809.01-42cFA |
+ BXD42 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 142 |
+ 091809.02-42cFB |
+ BXD42 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 143 |
+ 021909.01-42cFA |
+ BXD42 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 144 |
+ 011309.06-42cMA |
+ BXD42 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 145 |
+ 011309.07-42cMB |
+ BXD42 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 146 |
+ 110408_02-43cFA |
+ BXD43 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 147 |
+ 110408_03-43cFB |
+ BXD43 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 148 |
+ KA6158-43cMA |
+ BXD43 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 149 |
+ KA6158-43cMB |
+ BXD43 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 150 |
+ 100308_01-44cFA |
+ BXD44 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 151 |
+ 102208_02-44cMD |
+ BXD44 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 152 |
+ 103009.03-45cFA |
+ BXD45 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 153 |
+ 103009.04-45cFB |
+ BXD45 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 154 |
+ 022609.03-45cFA |
+ BXD45 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 155 |
+ 022609.04-45cFB |
+ BXD45 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 156 |
+ 40309.05-45cMB |
+ BXD45 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 157 |
+ 40209.05-48cFB |
+ BXD48 |
+ 58 |
+ F |
+ VAMC |
+
+
+ | 158 |
+ 40209.06-48cFC |
+ BXD48 |
+ 58 |
+ F |
+ VAMC |
+
+
+ | 159 |
+ 81209.04-48cMA |
+ BXD48 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 160 |
+ 81209.05-48cMB |
+ BXD48 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 161 |
+ 81209.08-49cFA |
+ BXD49 |
+ 70 |
+ F |
+ VAMC |
+
+
+ | 162 |
+ 81209.09-49cFB |
+ BXD49 |
+ 70 |
+ F |
+ VAMC |
+
+
+ | 163 |
+ 40209.01-49cMA |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 164 |
+ 40209.02-49cMB |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 165 |
+ 40209.03-49cMC |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 166 |
+ KA737850cFA |
+ BXD50 |
+ 50 |
+ F |
+ UTHSC RW |
+
+
+ | 167 |
+ KA737850cFB |
+ BXD50 |
+ 50 |
+ F |
+ UTHSC RW |
+
+
+ | 168 |
+ 121908_01-50cMA |
+ BXD50 |
+ 49 |
+ M |
+ UTHSC RW |
+
+
+ | 169 |
+ 121908_02-50cMB |
+ BXD50 |
+ 49 |
+ M |
+ UTHSC RW |
+
+
+ | 170 |
+ 111208_01-51cFA |
+ BXD51 |
+ 99 |
+ F |
+ UTHSC RW |
+
+
+ | 171 |
+ 102208_03-51cMA |
+ BXD51 |
+ 56 |
+ M |
+ UTHSC RW |
+
+
+ | 172 |
+ 102208_04-51cMB |
+ BXD51 |
+ 56 |
+ M |
+ UTHSC RW |
+
+
+ | 173 |
+ 090208_14-53BcFA |
+ BXD53B |
+ 93 |
+ F |
+ UTHSC RW |
+
+
+ | 174 |
+ 090208_15-53BcFB |
+ BXD53B |
+ 93 |
+ F |
+ UTHSC RW |
+
+
+ | 175 |
+ 090208_16-53BcMC |
+ BXD53B |
+ 93 |
+ M |
+ UTHSC RW |
+
+
+ | 176 |
+ 090208_17-53BcMD |
+ BXD53B |
+ 93 |
+ M |
+ UTHSC RW |
+
+
+ | 177 |
+ 111208_05-55cFB |
+ BXD55 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 178 |
+ KA6183-55cMA |
+ BXD55 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 179 |
+ KA6183-55cMB |
+ BXD55 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 180 |
+ KA7362-56cFB |
+ BXD 56 |
+ 54 |
+ F |
+ UTHSC RW |
+
+
+ | 181 |
+ KA6088-56cMA |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 182 |
+ KA6088-56cMB |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 183 |
+ KA6088-56cMC |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 184 |
+ 21810.01-60RFA |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 185 |
+ 21810.02-60RFB |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 186 |
+ 21810.02-60RFC |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 187 |
+ SQ7325-60cMA |
+ BXD60 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 188 |
+ SQ7325-60cMB |
+ BXD60 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 189 |
+ 092308_10-61cFA |
+ BXD61 |
+ 110 |
+ F |
+ UTHSC RW |
+
+
+ | 190 |
+ 092308_11-61cFB |
+ BXD61 |
+ 110 |
+ F |
+ UTHSC RW |
+
+
+ | 191 |
+ 31909.01-61cMA |
+ BXD61 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 192 |
+ 31909.02-61cMB |
+ BXD61 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 193 |
+ KA7462-62cFA |
+ BXD62 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 194 |
+ KA7462-62cFB |
+ BXD62 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 195 |
+ KA5996-62cMA |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 196 |
+ KA5996-62cMB |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 197 |
+ KA5996-62cMC |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 198 |
+ 090309.01-63cFA |
+ BXD63 |
+ 69 |
+ F |
+ UTHSC RW |
+
+
+ | 199 |
+ 090309.02-63cFB |
+ BXD63 |
+ 69 |
+ F |
+ UTHSC RW |
+
+
+ | 200 |
+ 110609.01-63cMA |
+ BXD63 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 201 |
+ 110609.02-63cMB |
+ BXD63 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 202 |
+ 091809.03-65cFA |
+ BXD65 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 203 |
+ 091809.04-65cFB |
+ BXD65 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 204 |
+ 103009.01-65cMA |
+ BXD65 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 205 |
+ 103009.02-65cMB |
+ BXD65 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 206 |
+ 110408_05-66cFB |
+ BXD66 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 207 |
+ KA7165-66cMA |
+ BXD66 |
+ 95 |
+ M |
+ UTHSC RW |
+
+
+ | 208 |
+ KA7165-66cMB |
+ BXD66 |
+ 95 |
+ M |
+ UTHSC RW |
+
+
+ | 209 |
+ 90809.01-67cMA |
+ BXD67 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 210 |
+ 90809.02-67cMB |
+ BXD67 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 211 |
+ 110609.03-67cFA |
+ BXD67 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 212 |
+ 110609.04-67cFB |
+ BXD67 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 213 |
+ 120408_01-68cFA |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 214 |
+ 120408_02-68cFB |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 215 |
+ SQ7205-68cMA |
+ BXD68 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 216 |
+ SQ7205-68cMB |
+ BXD68 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 217 |
+ KA6316-68cMA |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 218 |
+ KA6316-68cMB |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 219 |
+ KA6316-68cMC |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 220 |
+ KA76-69cFA |
+ BXD69 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 221 |
+ KA76-69cFB |
+ BXD69 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 222 |
+ KA6074-69cMA |
+ BXD69 |
+ 90 |
+ M |
+ UTHSC RW |
+
+
+ | 223 |
+ KA6074-69cMB |
+ BXD69 |
+ 90 |
+ M |
+ UTHSC RW |
+
+
+ | 224 |
+ 121608_01-70cFA |
+ BXD70 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 225 |
+ 121608_02-70cFB |
+ BXD70 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 226 |
+ KA7394-70cMA |
+ BXD70 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 227 |
+ 81209.08-70cMA |
+ BXD70 |
+ 71 |
+ M |
+ VAMC |
+
+
+ | 228 |
+ 81209.09-70cMB |
+ BXD70 |
+ 71 |
+ M |
+ VAMC |
+
+
+ | 229 |
+ 052809.01-71cFA |
+ BXD71 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 230 |
+ 060409.09-71cMA |
+ BXD71 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 231 |
+ 060409.10-71cMB |
+ BXD71 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 232 |
+ 40809.01-73cFA |
+ BXD73 |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 233 |
+ 40809.02-73cFB |
+ BXD73 |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 234 |
+ 111708_01-73cFA |
+ BXD73 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 235 |
+ 111708_01-73cFB |
+ BXD73 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 236 |
+ KA6164-73cMB |
+ BXD73 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 237 |
+ KA6164-73cMC |
+ BXD73 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 238 |
+ 82609.22-74cFA |
+ BXD74 |
+ 68 |
+ F |
+ VAMC |
+
+
+ | 239 |
+ 82609.23-74cFB |
+ BXD74 |
+ 68 |
+ F |
+ VAMC |
+
+
+ | 240 |
+ 82609.20-74cMA |
+ BXD74 |
+ 68 |
+ M |
+ VAMC |
+
+
+ | 241 |
+ 82609.21-74cMB |
+ BXD74 |
+ 68 |
+ M |
+ VAMC |
+
+
+ | 242 |
+ KA733675cFA |
+ BXD75 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 243 |
+ KA733675cFB |
+ BXD75 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 244 |
+ KA38-75cMB |
+ BXD75 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 245 |
+ KA38-75cMC |
+ BXD75 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 246 |
+ 41509.01-77cFA |
+ BXD77 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 247 |
+ 41509.02-77cFB |
+ BXD77 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 248 |
+ 41509.03-77cMC |
+ BXD77 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 249 |
+ 41509.04-77cMD |
+ BXD77 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 250 |
+ 121608_03-80cFA |
+ BXD80 |
+ 77 |
+ F |
+ UTHSC RW |
+
+
+ | 251 |
+ 121608_05-80cMC |
+ BXD80 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 252 |
+ KA23-80cMC |
+ BXD80 |
+ 77 |
+ M |
+ UTHSC RW |
+
+
+ | 253 |
+ KA7305-81cFA |
+ BXD81 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 254 |
+ KA7305-81cFB |
+ BXD81 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 255 |
+ KA7305-81cMD |
+ BXD81 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 256 |
+ 060409.11-83cFA |
+ BXD83 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 257 |
+ KA24-83cFA |
+ BXD83 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 258 |
+ 121608_07-83cMA |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 259 |
+ 121608_08-83cMB |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 260 |
+ KA24-83cMD |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 261 |
+ 090409.05-84cFA |
+ BXD84 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 262 |
+ 090409.06-84cFB |
+ BXD84 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 263 |
+ KA6203-84cMA |
+ BXD84 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 264 |
+ KA6203-84cMB |
+ BXD84 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 265 |
+ 40309.02-85cFD |
+ BXD85 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 266 |
+ 40309.03-85cFE |
+ BXD85 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 267 |
+ 32609.01-85cMA |
+ BXD85 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 268 |
+ 32609.02-85cMB |
+ BXD85 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 269 |
+ 41509.05-86cFA |
+ BXD86 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 270 |
+ 41509.06-86cFB |
+ BXD86 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 271 |
+ KA6101-86cMA |
+ BXD86 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 272 |
+ KA6101-86cMC |
+ BXD86 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 273 |
+ 070909.02-87cFA |
+ BXD87 |
+ 86 |
+ F |
+ UTHSC RW |
+
+
+ | 274 |
+ 070909.03-87cFB |
+ BXD87 |
+ 86 |
+ F |
+ UTHSC RW |
+
+
+ | 275 |
+ KA7407-87cMA |
+ BXD87 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 276 |
+ KA7407-87cMB |
+ BXD87 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 277 |
+ 102208_05-89cFA |
+ BXD89 |
+ 82 |
+ F |
+ UTHSC RW |
+
+
+ | 278 |
+ KA5974-89cMA |
+ BXD89 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 279 |
+ KA5974-89cMB |
+ BXD89 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 280 |
+ 102208_06-89cMC |
+ BXD89 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 281 |
+ 72309.01-90cFA |
+ BXD90 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 282 |
+ 72309.02-90cFB |
+ BXD90 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 283 |
+ 090409.03-90cMA |
+ BXD90 |
+ 64 |
+ M |
+ VAMC |
+
+
+ | 284 |
+ 090409.04-90cMB |
+ BXD90 |
+ 64 |
+ M |
+ VAMC |
+
+
+ | 285 |
+ KA6094-92cMA |
+ BXD92 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 286 |
+ 020609.01-95cFA |
+ BXD95 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 287 |
+ 020609.02-95cFB |
+ BXD95 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 288 |
+ KA6181-95cMA |
+ BXD95 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 289 |
+ KA6181-95cMB |
+ BXD95 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 290 |
+ 31209.03-96cFA |
+ BXD96 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 291 |
+ 31209.04-96cFB |
+ BXD96 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 292 |
+ KA7246-96cMA |
+ BXD96 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 293 |
+ KA7246-96cMB |
+ BXD96 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 294 |
+ 81209.10-97cFA |
+ BXD97 |
+ 83 |
+ F |
+ VAMC |
+
+
+ | 295 |
+ 81209.11-97cFB |
+ BXD97 |
+ 83 |
+ F |
+ VAMC |
+
+
+ | 296 |
+ 81209.1-97cMA |
+ BXD97 |
+ 83 |
+ M |
+ VAMC |
+
+
+ | 297 |
+ 81209.11-97cMB |
+ BXD97 |
+ 83 |
+ M |
+ VAMC |
+
+
+ | 298 |
+ SQ7520-98cFA |
+ BXD98 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 299 |
+ SQ7520-98cFB |
+ BXD98 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 300 |
+ SQ7520-98cMC |
+ BXD98 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 301 |
+ SQ7520-98cMD |
+ BXD98 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 302 |
+ 82609.17-99cFA |
+ BXD99 |
+ 64 |
+ F |
+ VAMC |
+
+
+ | 303 |
+ 82609.18-99cFB |
+ BXD99 |
+ 64 |
+ F |
+ VAMC |
+
+
+ | 304 |
+ 81409.01-99cMA |
+ BXD99 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 305 |
+ 81409.02-99cMB |
+ BXD99 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 306 |
+ 121608_09-100cFA |
+ BXD100 |
+ 81 |
+ F |
+ UTHSC RW |
+
+
+ | 307 |
+ 121608_10-100cFB |
+ BXD100 |
+ 81 |
+ F |
+ UTHSC RW |
+
+
+ | 308 |
+ KA6001-100cMA |
+ BXD100 |
+ 111 |
+ M |
+ UTHSC RW |
+
+
+ | 309 |
+ KA6001-100cMB |
+ BXD100 |
+ 111 |
+ M |
+ UTHSC RW |
+
+
+ | 310 |
+ 81209.12-101cFA |
+ BXD101 |
+ 72 |
+ F |
+ VAMC |
+
+
+ | 311 |
+ 81209.13-101cFB |
+ BXD101 |
+ 72 |
+ F |
+ VAMC |
+
+
+ | 312 |
+ KA7296-101cMA |
+ BXD101 |
+ 75 |
+ M |
+ UTHSC RW |
+
+
+ | 313 |
+ KA7296-101cMB |
+ BXD101 |
+ 75 |
+ M |
+ UTHSC RW |
+
+
+ | 314 |
+ 92409.03-102cFA |
+ BXD102 |
+ 71 |
+ F |
+ VAMC |
+
+
+ | 315 |
+ 92409.04-102cFB |
+ BXD102 |
+ 71 |
+ F |
+ VAMC |
+
+
+ | 316 |
+ KA7380-102cMA |
+ BXD102 |
+ 115 |
+ M |
+ UTHSC RW |
+
+
+ | 317 |
+ 43009.01-103cFA |
+ BXD103 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 318 |
+ 43009.02-103cFB |
+ BXD103 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 319 |
+ KA79-103cFA |
+ BXD103 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 320 |
+ KA79-103cFB |
+ BXD103 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 321 |
+ KA79-103cMC |
+ BXD103 |
+ 48 |
+ M |
+ UTHSC RW |
+
+
+ | 322 |
+ 82609.15-103cMA |
+ BXD103 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 323 |
+ 82609.16-103cMB |
+ BXD103 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 324 |
+ 102909.01-BALBCcFA |
+ BALB/cByJ |
+ 78 |
+ F |
+ JAX |
+
+
+ | 325 |
+ 102909.02-BALBCcFB |
+ BALB/cByJ |
+ 78 |
+ F |
+ JAX |
+
+
+ | 326 |
+ 102909.03-BALBCcMA |
+ BALB/cByJ |
+ 78 |
+ M |
+ JAX |
+
+
+ | 327 |
+ 102909.04-BALBCcMB |
+ BALB/cByJ |
+ 78 |
+ M |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/G2nei_ilm_retina_bxd_ri0410/summary.rtf b/general/datasets/G2nei_ilm_retina_bxd_ri0410/summary.rtf
new file mode 100644
index 0000000..44e98a7
--- /dev/null
+++ b/general/datasets/G2nei_ilm_retina_bxd_ri0410/summary.rtf
@@ -0,0 +1,50 @@
+
+This is a subtractive dataset. The Normal retina dataset was subtracted from the ONC data set probe by probe to create a data set of the changes occurring following ONC. This data set can be used to define gene changes following ONC. It is not compatible with most of the bioinformatic tools available on GeneNetwork.
+
+HEI Retina Illumina V6.2 (April 2010) RankInv was normalized and scaled by William E. Orr and uploaded by Arthur Centeno and Xiaodong Zhou on April 7, 2010. This data set consists of either 69 BXD strains (Normal data set) or 75 BXD strains (Full data set), C57BL/6J, DBA/2J, both reciprocal F1s, and BALB/cByJ. A total of either 74 strains (Normal data set) or 80 strains (Full data set) were quantified.
+
+COMMENT on FULL versus NORMAL data sets: For many general uses there is no significant difference between FULL and NORMAL data sets. However, the FULL data set includes strains with high endogenous Gfap mRNA expression, indicative of reactive gliosis. For that reason, and to compare to OPTIC NERVE CRUSH (ONC), we removed data from six strains to make the NORMAL data set.
+
+The NORMAL data set exludes data from BXD24, BXD32, BXD49, BXD70, BXD83, and BXD89. BXD24 has known retinal degeneration and is now known officially as BXD24/TyJ-Cep290/J, JAX Stock number 000031. BXD32 has mild retinal degeneration. The NORMAL data set does include BXD24a, now also known as BXD24/TyJ (JAX Stock number 005243).
+
+The data are now open and available for analysis.
+
+Please cite: Freeman NE, Templeton JP, Orr WE, Lu L, Williams RW, Geisert EE (2011) Genetic networks in the mouse retina: Growth Associated Protein 43 and Phosphate Tensin Homology network. Molecular Vision 17:1355-1372. Full Text PDF or HTML
+
+This is rank invariant expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 6.25 to 18.08 (11.83 units), a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
+
+The lowest level of expression is 6.254 for ILMN_2747167 (Arhgap11a) from HEI Retina Illumina V6.2 (April 2010) RankInv **. Lowest single data about 5.842.
+
+The highest level of expression is 18.077 for ILMN_2516699 (Ubb). Highest single value is about 18.934.
+
+
+
+
+Other Related Publications
+
+
+
+
+
+ - Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link)
+ - Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674
+ - Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link)
+ - Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.(Link)
+
+
+
+
+
+
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
+
diff --git a/general/datasets/G2nei_ilm_retina_bxd_ri0410/tissue.rtf b/general/datasets/G2nei_ilm_retina_bxd_ri0410/tissue.rtf
new file mode 100644
index 0000000..766ab59
--- /dev/null
+++ b/general/datasets/G2nei_ilm_retina_bxd_ri0410/tissue.rtf
@@ -0,0 +1,32 @@
+
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RNAlater at room temperature. Two retinas from one mouse were stored in a single tube.
+
+Each array was hybridized with a pool of cRNA from 2 retinas (1 mouse). Natalie Freeman-Anderson extracted RNA at UTHSC.
+
+
+
+Dissecting and preparing eyes for RNA extraction
+
+
+
+Retinas for RNA extraction were placed in RNA STAT-60 (Tel-Test Inc.) and processed per manufacturer’s instructions (in brief form below). Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+
+
+ - Homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue via syringe)
+ - Allow the homogenate to stand for 5-10 min at room temperature
+ - Add 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - Mix the sample vigorously for 15 sec and let the sample incubate at room temperature for 5-10 min
+ - Centrifuge at 12,000 g for 1 hr at 4°C
+ - Transfer the aqueous phase to a clean centrifuge tube
+ - Add 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - Vortex and incubate the sample at -20°C for 1 hr or overnight
+ - Centrifuge at 12,000 g for 1 hr
+ - Remove the supernatant and wash the RNA pellet with 75% ethanol
+ - Remove ethanol, let air dry (5-10 min)
+ - Dissolve the pellet in 50 μl of nuclease free water.
+
+
+
+
diff --git a/general/datasets/GITrMetPublish/summary.rtf b/general/datasets/GITrMetPublish/summary.rtf
deleted file mode 100644
index 3847a3b..0000000
--- a/general/datasets/GITrMetPublish/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GI Tract Metagenome Phenotypes
diff --git a/general/datasets/GRNG_GSE23545HLT0613/summary.rtf b/general/datasets/GRNG_GSE23545HLT0613/summary.rtf
deleted file mode 100644
index 9cb9538..0000000
--- a/general/datasets/GRNG_GSE23545HLT0613/summary.rtf
+++ /dev/null
@@ -1,15 +0,0 @@
-This SuperSeries is composed of the following SubSeries:
-
-
-
-
- | GSE23352 Whole-genome gene expression profiles of non-tumorous human lung tissues: Laval set |
-
-
- | GSE23529 Whole-genome gene expression profiles of non-tumorous human lung tissues: UBC set |
-
-
- | GSE23545 Whole-genome gene expression profiles of non-tumorous human lung tissues: GRNG set |
-
-
-
diff --git a/general/datasets/GSE15745_GPL6104_Cer0510/experiment-design.rtf b/general/datasets/GSE15745_GPL6104_Cer0510/experiment-design.rtf
deleted file mode 100644
index e93df25..0000000
--- a/general/datasets/GSE15745_GPL6104_Cer0510/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-North American Brain Expression Consortium and UK Human Brain Expression Database: Gene Expression. Genome-wide association studies have nominated many genetic variants for common human traits, including diseases, but in many cases the underlying biological reason for a trait association is unknown. Subsets of genetic polymorphisms show a statistical association with transcript expression levels, and have therefore been nominated as expression quantitative trait loci (eQTL). However, many tissue and cell types have specific gene expression patterns and so it is not clear how frequently eQTLs found in one tissue type will be replicated in others. In the present study we used two appropriately powered sample series to examine the genetic control of gene expression in blood and brain. We find that while many eQTLs associated with human traits are shared between these two tissues, there are also examples where blood and brain differ, either by restricted gene expression patterns in one tissue or because of differences in how genetic variants are associated with transcript levels. These observations suggest that design of eQTL mapping experiments should consider tissue of interest for the disease or other traits studied. Published by Elsevier Inc.
diff --git a/general/datasets/GSE15745_GPL6104_Cer0510/summary.rtf b/general/datasets/GSE15745_GPL6104_Cer0510/summary.rtf
deleted file mode 100644
index 4bc5546..0000000
--- a/general/datasets/GSE15745_GPL6104_Cer0510/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary from GEO Series GSE36192 and GSE: GSE36194 "A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on mRNA expression distinct human brain regions. We show that brain tissues may be readily distinguished based on expression profile. We find an abundance of genetic cis regulation mRNA expression. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation."
diff --git a/general/datasets/GSE15745_GPL6104_PFC0510/experiment-design.rtf b/general/datasets/GSE15745_GPL6104_PFC0510/experiment-design.rtf
deleted file mode 100644
index e93df25..0000000
--- a/general/datasets/GSE15745_GPL6104_PFC0510/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-North American Brain Expression Consortium and UK Human Brain Expression Database: Gene Expression. Genome-wide association studies have nominated many genetic variants for common human traits, including diseases, but in many cases the underlying biological reason for a trait association is unknown. Subsets of genetic polymorphisms show a statistical association with transcript expression levels, and have therefore been nominated as expression quantitative trait loci (eQTL). However, many tissue and cell types have specific gene expression patterns and so it is not clear how frequently eQTLs found in one tissue type will be replicated in others. In the present study we used two appropriately powered sample series to examine the genetic control of gene expression in blood and brain. We find that while many eQTLs associated with human traits are shared between these two tissues, there are also examples where blood and brain differ, either by restricted gene expression patterns in one tissue or because of differences in how genetic variants are associated with transcript levels. These observations suggest that design of eQTL mapping experiments should consider tissue of interest for the disease or other traits studied. Published by Elsevier Inc.
diff --git a/general/datasets/GSE15745_GPL6104_PFC0510/summary.rtf b/general/datasets/GSE15745_GPL6104_PFC0510/summary.rtf
deleted file mode 100644
index 4bc5546..0000000
--- a/general/datasets/GSE15745_GPL6104_PFC0510/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary from GEO Series GSE36192 and GSE: GSE36194 "A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on mRNA expression distinct human brain regions. We show that brain tissues may be readily distinguished based on expression profile. We find an abundance of genetic cis regulation mRNA expression. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation."
diff --git a/general/datasets/GSE15745_GPL6104_Po0510/experiment-design.rtf b/general/datasets/GSE15745_GPL6104_Po0510/experiment-design.rtf
deleted file mode 100644
index e93df25..0000000
--- a/general/datasets/GSE15745_GPL6104_Po0510/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-North American Brain Expression Consortium and UK Human Brain Expression Database: Gene Expression. Genome-wide association studies have nominated many genetic variants for common human traits, including diseases, but in many cases the underlying biological reason for a trait association is unknown. Subsets of genetic polymorphisms show a statistical association with transcript expression levels, and have therefore been nominated as expression quantitative trait loci (eQTL). However, many tissue and cell types have specific gene expression patterns and so it is not clear how frequently eQTLs found in one tissue type will be replicated in others. In the present study we used two appropriately powered sample series to examine the genetic control of gene expression in blood and brain. We find that while many eQTLs associated with human traits are shared between these two tissues, there are also examples where blood and brain differ, either by restricted gene expression patterns in one tissue or because of differences in how genetic variants are associated with transcript levels. These observations suggest that design of eQTL mapping experiments should consider tissue of interest for the disease or other traits studied. Published by Elsevier Inc.
diff --git a/general/datasets/GSE15745_GPL6104_Po0510/summary.rtf b/general/datasets/GSE15745_GPL6104_Po0510/summary.rtf
deleted file mode 100644
index 4bc5546..0000000
--- a/general/datasets/GSE15745_GPL6104_Po0510/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary from GEO Series GSE36192 and GSE: GSE36194 "A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on mRNA expression distinct human brain regions. We show that brain tissues may be readily distinguished based on expression profile. We find an abundance of genetic cis regulation mRNA expression. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation."
diff --git a/general/datasets/GSE23546HLT0613/summary.rtf b/general/datasets/GSE23546HLT0613/summary.rtf
deleted file mode 100644
index 9cb9538..0000000
--- a/general/datasets/GSE23546HLT0613/summary.rtf
+++ /dev/null
@@ -1,15 +0,0 @@
-This SuperSeries is composed of the following SubSeries:
-
-
-
-
- | GSE23352 Whole-genome gene expression profiles of non-tumorous human lung tissues: Laval set |
-
-
- | GSE23529 Whole-genome gene expression profiles of non-tumorous human lung tissues: UBC set |
-
-
- | GSE23545 Whole-genome gene expression profiles of non-tumorous human lung tissues: GRNG set |
-
-
-
diff --git a/general/datasets/GTEXv5_AdiVis_0915/cases.rtf b/general/datasets/GTEXv5_AdiVis_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_AdiVis_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_AdiVis_0915/experiment-design.rtf b/general/datasets/GTEXv5_AdiVis_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_AdiVis_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_AdiVis_0915/platform.rtf b/general/datasets/GTEXv5_AdiVis_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_AdiVis_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_AdiVis_0915/processing.rtf b/general/datasets/GTEXv5_AdiVis_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_AdiVis_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_AdiVis_0915/specifics.rtf b/general/datasets/GTEXv5_AdiVis_0915/specifics.rtf
deleted file mode 100644
index 055221e..0000000
--- a/general/datasets/GTEXv5_AdiVis_0915/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Human Adipose Visceral Omentum
\ No newline at end of file
diff --git a/general/datasets/GTEXv5_AdiVis_0915/summary.rtf b/general/datasets/GTEXv5_AdiVis_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_AdiVis_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_AdiVis_0915/tissue.rtf b/general/datasets/GTEXv5_AdiVis_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_AdiVis_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_AdipSub_0915/cases.rtf b/general/datasets/GTEXv5_AdipSub_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_AdipSub_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_AdipSub_0915/experiment-design.rtf b/general/datasets/GTEXv5_AdipSub_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_AdipSub_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_AdipSub_0915/platform.rtf b/general/datasets/GTEXv5_AdipSub_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_AdipSub_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_AdipSub_0915/processing.rtf b/general/datasets/GTEXv5_AdipSub_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_AdipSub_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_AdipSub_0915/specifics.rtf b/general/datasets/GTEXv5_AdipSub_0915/specifics.rtf
deleted file mode 100644
index 60a3e92..0000000
--- a/general/datasets/GTEXv5_AdipSub_0915/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Human Adipose Subcutaneous
\ No newline at end of file
diff --git a/general/datasets/GTEXv5_AdipSub_0915/summary.rtf b/general/datasets/GTEXv5_AdipSub_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_AdipSub_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_AdipSub_0915/tissue.rtf b/general/datasets/GTEXv5_AdipSub_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_AdipSub_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_AdrGla_0915/cases.rtf b/general/datasets/GTEXv5_AdrGla_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_AdrGla_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_AdrGla_0915/experiment-design.rtf b/general/datasets/GTEXv5_AdrGla_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_AdrGla_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_AdrGla_0915/platform.rtf b/general/datasets/GTEXv5_AdrGla_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_AdrGla_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_AdrGla_0915/processing.rtf b/general/datasets/GTEXv5_AdrGla_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_AdrGla_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_AdrGla_0915/specifics.rtf b/general/datasets/GTEXv5_AdrGla_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_AdrGla_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_AdrGla_0915/summary.rtf b/general/datasets/GTEXv5_AdrGla_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_AdrGla_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_AdrGla_0915/tissue.rtf b/general/datasets/GTEXv5_AdrGla_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_AdrGla_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Amy_0915/cases.rtf b/general/datasets/GTEXv5_Amy_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Amy_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Amy_0915/experiment-design.rtf b/general/datasets/GTEXv5_Amy_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Amy_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Amy_0915/platform.rtf b/general/datasets/GTEXv5_Amy_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Amy_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Amy_0915/processing.rtf b/general/datasets/GTEXv5_Amy_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Amy_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Amy_0915/specifics.rtf b/general/datasets/GTEXv5_Amy_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Amy_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Amy_0915/summary.rtf b/general/datasets/GTEXv5_Amy_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Amy_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Amy_0915/tissue.rtf b/general/datasets/GTEXv5_Amy_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Amy_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_AntCtx_0915/cases.rtf b/general/datasets/GTEXv5_AntCtx_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_AntCtx_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_AntCtx_0915/experiment-design.rtf b/general/datasets/GTEXv5_AntCtx_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_AntCtx_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_AntCtx_0915/platform.rtf b/general/datasets/GTEXv5_AntCtx_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_AntCtx_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_AntCtx_0915/processing.rtf b/general/datasets/GTEXv5_AntCtx_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_AntCtx_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_AntCtx_0915/specifics.rtf b/general/datasets/GTEXv5_AntCtx_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_AntCtx_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_AntCtx_0915/summary.rtf b/general/datasets/GTEXv5_AntCtx_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_AntCtx_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_AntCtx_0915/tissue.rtf b/general/datasets/GTEXv5_AntCtx_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_AntCtx_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_ArtAor_0915/cases.rtf b/general/datasets/GTEXv5_ArtAor_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_ArtAor_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_ArtAor_0915/experiment-design.rtf b/general/datasets/GTEXv5_ArtAor_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_ArtAor_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_ArtAor_0915/platform.rtf b/general/datasets/GTEXv5_ArtAor_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_ArtAor_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_ArtAor_0915/processing.rtf b/general/datasets/GTEXv5_ArtAor_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_ArtAor_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_ArtAor_0915/specifics.rtf b/general/datasets/GTEXv5_ArtAor_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_ArtAor_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_ArtAor_0915/summary.rtf b/general/datasets/GTEXv5_ArtAor_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_ArtAor_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_ArtAor_0915/tissue.rtf b/general/datasets/GTEXv5_ArtAor_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_ArtAor_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_ArtCor_0915/cases.rtf b/general/datasets/GTEXv5_ArtCor_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_ArtCor_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_ArtCor_0915/experiment-design.rtf b/general/datasets/GTEXv5_ArtCor_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_ArtCor_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_ArtCor_0915/platform.rtf b/general/datasets/GTEXv5_ArtCor_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_ArtCor_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_ArtCor_0915/processing.rtf b/general/datasets/GTEXv5_ArtCor_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_ArtCor_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_ArtCor_0915/specifics.rtf b/general/datasets/GTEXv5_ArtCor_0915/specifics.rtf
deleted file mode 100644
index 9288089..0000000
--- a/general/datasets/GTEXv5_ArtCor_0915/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Human Artery Coronary
\ No newline at end of file
diff --git a/general/datasets/GTEXv5_ArtCor_0915/summary.rtf b/general/datasets/GTEXv5_ArtCor_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_ArtCor_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_ArtCor_0915/tissue.rtf b/general/datasets/GTEXv5_ArtCor_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_ArtCor_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_BM_0915/cases.rtf b/general/datasets/GTEXv5_BM_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_BM_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_BM_0915/experiment-design.rtf b/general/datasets/GTEXv5_BM_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_BM_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_BM_0915/platform.rtf b/general/datasets/GTEXv5_BM_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_BM_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_BM_0915/processing.rtf b/general/datasets/GTEXv5_BM_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_BM_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_BM_0915/specifics.rtf b/general/datasets/GTEXv5_BM_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_BM_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_BM_0915/summary.rtf b/general/datasets/GTEXv5_BM_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_BM_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_BM_0915/tissue.rtf b/general/datasets/GTEXv5_BM_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_BM_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_BrCe_0915/cases.rtf b/general/datasets/GTEXv5_BrCe_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_BrCe_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_BrCe_0915/experiment-design.rtf b/general/datasets/GTEXv5_BrCe_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_BrCe_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_BrCe_0915/platform.rtf b/general/datasets/GTEXv5_BrCe_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_BrCe_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_BrCe_0915/processing.rtf b/general/datasets/GTEXv5_BrCe_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_BrCe_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_BrCe_0915/specifics.rtf b/general/datasets/GTEXv5_BrCe_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_BrCe_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_BrCe_0915/summary.rtf b/general/datasets/GTEXv5_BrCe_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_BrCe_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_BrCe_0915/tissue.rtf b/general/datasets/GTEXv5_BrCe_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_BrCe_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_BrMa_0915/cases.rtf b/general/datasets/GTEXv5_BrMa_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_BrMa_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_BrMa_0915/experiment-design.rtf b/general/datasets/GTEXv5_BrMa_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_BrMa_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_BrMa_0915/platform.rtf b/general/datasets/GTEXv5_BrMa_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_BrMa_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_BrMa_0915/processing.rtf b/general/datasets/GTEXv5_BrMa_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_BrMa_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_BrMa_0915/specifics.rtf b/general/datasets/GTEXv5_BrMa_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_BrMa_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_BrMa_0915/summary.rtf b/general/datasets/GTEXv5_BrMa_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_BrMa_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_BrMa_0915/tissue.rtf b/general/datasets/GTEXv5_BrMa_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_BrMa_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_CTF_0915/cases.rtf b/general/datasets/GTEXv5_CTF_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_CTF_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_CTF_0915/experiment-design.rtf b/general/datasets/GTEXv5_CTF_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_CTF_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_CTF_0915/platform.rtf b/general/datasets/GTEXv5_CTF_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_CTF_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_CTF_0915/processing.rtf b/general/datasets/GTEXv5_CTF_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_CTF_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_CTF_0915/specifics.rtf b/general/datasets/GTEXv5_CTF_0915/specifics.rtf
deleted file mode 100644
index 8515741..0000000
--- a/general/datasets/GTEXv5_CTF_0915/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Cell Transformed Fibroblasts
\ No newline at end of file
diff --git a/general/datasets/GTEXv5_CTF_0915/summary.rtf b/general/datasets/GTEXv5_CTF_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_CTF_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_CTF_0915/tissue.rtf b/general/datasets/GTEXv5_CTF_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_CTF_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_ColSig_0915/cases.rtf b/general/datasets/GTEXv5_ColSig_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_ColSig_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_ColSig_0915/experiment-design.rtf b/general/datasets/GTEXv5_ColSig_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_ColSig_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_ColSig_0915/platform.rtf b/general/datasets/GTEXv5_ColSig_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_ColSig_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_ColSig_0915/processing.rtf b/general/datasets/GTEXv5_ColSig_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_ColSig_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_ColSig_0915/specifics.rtf b/general/datasets/GTEXv5_ColSig_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_ColSig_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_ColSig_0915/summary.rtf b/general/datasets/GTEXv5_ColSig_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_ColSig_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_ColSig_0915/tissue.rtf b/general/datasets/GTEXv5_ColSig_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_ColSig_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_GastJun_0915/cases.rtf b/general/datasets/GTEXv5_GastJun_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_GastJun_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_GastJun_0915/experiment-design.rtf b/general/datasets/GTEXv5_GastJun_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_GastJun_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_GastJun_0915/platform.rtf b/general/datasets/GTEXv5_GastJun_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_GastJun_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_GastJun_0915/processing.rtf b/general/datasets/GTEXv5_GastJun_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_GastJun_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_GastJun_0915/specifics.rtf b/general/datasets/GTEXv5_GastJun_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_GastJun_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_GastJun_0915/summary.rtf b/general/datasets/GTEXv5_GastJun_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_GastJun_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_GastJun_0915/tissue.rtf b/general/datasets/GTEXv5_GastJun_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_GastJun_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_HAA_0915/cases.rtf b/general/datasets/GTEXv5_HAA_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_HAA_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_HAA_0915/experiment-design.rtf b/general/datasets/GTEXv5_HAA_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_HAA_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_HAA_0915/platform.rtf b/general/datasets/GTEXv5_HAA_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_HAA_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_HAA_0915/processing.rtf b/general/datasets/GTEXv5_HAA_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_HAA_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_HAA_0915/specifics.rtf b/general/datasets/GTEXv5_HAA_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_HAA_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_HAA_0915/summary.rtf b/general/datasets/GTEXv5_HAA_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_HAA_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_HAA_0915/tissue.rtf b/general/datasets/GTEXv5_HAA_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_HAA_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Hip_0915/cases.rtf b/general/datasets/GTEXv5_Hip_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Hip_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Hip_0915/experiment-design.rtf b/general/datasets/GTEXv5_Hip_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Hip_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Hip_0915/platform.rtf b/general/datasets/GTEXv5_Hip_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Hip_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Hip_0915/processing.rtf b/general/datasets/GTEXv5_Hip_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Hip_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Hip_0915/specifics.rtf b/general/datasets/GTEXv5_Hip_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Hip_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Hip_0915/summary.rtf b/general/datasets/GTEXv5_Hip_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Hip_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Hip_0915/tissue.rtf b/general/datasets/GTEXv5_Hip_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Hip_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Hiptha_0915/cases.rtf b/general/datasets/GTEXv5_Hiptha_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Hiptha_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Hiptha_0915/experiment-design.rtf b/general/datasets/GTEXv5_Hiptha_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Hiptha_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Hiptha_0915/platform.rtf b/general/datasets/GTEXv5_Hiptha_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Hiptha_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Hiptha_0915/processing.rtf b/general/datasets/GTEXv5_Hiptha_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Hiptha_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Hiptha_0915/specifics.rtf b/general/datasets/GTEXv5_Hiptha_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Hiptha_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Hiptha_0915/summary.rtf b/general/datasets/GTEXv5_Hiptha_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Hiptha_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Hiptha_0915/tissue.rtf b/general/datasets/GTEXv5_Hiptha_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Hiptha_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Kidn_0915/cases.rtf b/general/datasets/GTEXv5_Kidn_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Kidn_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Kidn_0915/experiment-design.rtf b/general/datasets/GTEXv5_Kidn_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Kidn_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Kidn_0915/platform.rtf b/general/datasets/GTEXv5_Kidn_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Kidn_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Kidn_0915/processing.rtf b/general/datasets/GTEXv5_Kidn_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Kidn_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Kidn_0915/specifics.rtf b/general/datasets/GTEXv5_Kidn_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Kidn_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Kidn_0915/summary.rtf b/general/datasets/GTEXv5_Kidn_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Kidn_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Kidn_0915/tissue.rtf b/general/datasets/GTEXv5_Kidn_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Kidn_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Liv_0915/cases.rtf b/general/datasets/GTEXv5_Liv_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Liv_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Liv_0915/experiment-design.rtf b/general/datasets/GTEXv5_Liv_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Liv_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Liv_0915/platform.rtf b/general/datasets/GTEXv5_Liv_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Liv_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Liv_0915/processing.rtf b/general/datasets/GTEXv5_Liv_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Liv_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Liv_0915/specifics.rtf b/general/datasets/GTEXv5_Liv_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Liv_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Liv_0915/summary.rtf b/general/datasets/GTEXv5_Liv_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Liv_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Liv_0915/tissue.rtf b/general/datasets/GTEXv5_Liv_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Liv_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_MuSk_0915/cases.rtf b/general/datasets/GTEXv5_MuSk_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_MuSk_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_MuSk_0915/experiment-design.rtf b/general/datasets/GTEXv5_MuSk_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_MuSk_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_MuSk_0915/platform.rtf b/general/datasets/GTEXv5_MuSk_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_MuSk_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_MuSk_0915/processing.rtf b/general/datasets/GTEXv5_MuSk_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_MuSk_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_MuSk_0915/specifics.rtf b/general/datasets/GTEXv5_MuSk_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_MuSk_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_MuSk_0915/summary.rtf b/general/datasets/GTEXv5_MuSk_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_MuSk_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_MuSk_0915/tissue.rtf b/general/datasets/GTEXv5_MuSk_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_MuSk_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Ov_0915/cases.rtf b/general/datasets/GTEXv5_Ov_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Ov_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Ov_0915/experiment-design.rtf b/general/datasets/GTEXv5_Ov_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Ov_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Ov_0915/platform.rtf b/general/datasets/GTEXv5_Ov_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Ov_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Ov_0915/processing.rtf b/general/datasets/GTEXv5_Ov_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Ov_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Ov_0915/specifics.rtf b/general/datasets/GTEXv5_Ov_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Ov_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Ov_0915/summary.rtf b/general/datasets/GTEXv5_Ov_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Ov_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Ov_0915/tissue.rtf b/general/datasets/GTEXv5_Ov_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Ov_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Pit_0915/cases.rtf b/general/datasets/GTEXv5_Pit_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Pit_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Pit_0915/experiment-design.rtf b/general/datasets/GTEXv5_Pit_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Pit_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Pit_0915/platform.rtf b/general/datasets/GTEXv5_Pit_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Pit_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Pit_0915/processing.rtf b/general/datasets/GTEXv5_Pit_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Pit_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Pit_0915/specifics.rtf b/general/datasets/GTEXv5_Pit_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Pit_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Pit_0915/summary.rtf b/general/datasets/GTEXv5_Pit_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Pit_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Pit_0915/tissue.rtf b/general/datasets/GTEXv5_Pit_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Pit_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Prost_0915/cases.rtf b/general/datasets/GTEXv5_Prost_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Prost_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Prost_0915/experiment-design.rtf b/general/datasets/GTEXv5_Prost_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Prost_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Prost_0915/platform.rtf b/general/datasets/GTEXv5_Prost_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Prost_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Prost_0915/processing.rtf b/general/datasets/GTEXv5_Prost_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Prost_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Prost_0915/specifics.rtf b/general/datasets/GTEXv5_Prost_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Prost_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Prost_0915/summary.rtf b/general/datasets/GTEXv5_Prost_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Prost_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Prost_0915/tissue.rtf b/general/datasets/GTEXv5_Prost_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Prost_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_SalGl_0915/cases.rtf b/general/datasets/GTEXv5_SalGl_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_SalGl_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_SalGl_0915/experiment-design.rtf b/general/datasets/GTEXv5_SalGl_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_SalGl_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_SalGl_0915/platform.rtf b/general/datasets/GTEXv5_SalGl_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_SalGl_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_SalGl_0915/processing.rtf b/general/datasets/GTEXv5_SalGl_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_SalGl_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_SalGl_0915/specifics.rtf b/general/datasets/GTEXv5_SalGl_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_SalGl_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_SalGl_0915/summary.rtf b/general/datasets/GTEXv5_SalGl_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_SalGl_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_SalGl_0915/tissue.rtf b/general/datasets/GTEXv5_SalGl_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_SalGl_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_SkS_0915/cases.rtf b/general/datasets/GTEXv5_SkS_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_SkS_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_SkS_0915/experiment-design.rtf b/general/datasets/GTEXv5_SkS_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_SkS_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_SkS_0915/platform.rtf b/general/datasets/GTEXv5_SkS_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_SkS_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_SkS_0915/processing.rtf b/general/datasets/GTEXv5_SkS_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_SkS_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_SkS_0915/specifics.rtf b/general/datasets/GTEXv5_SkS_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_SkS_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_SkS_0915/summary.rtf b/general/datasets/GTEXv5_SkS_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_SkS_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_SkS_0915/tissue.rtf b/general/datasets/GTEXv5_SkS_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_SkS_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Sto_0915/cases.rtf b/general/datasets/GTEXv5_Sto_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Sto_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Sto_0915/experiment-design.rtf b/general/datasets/GTEXv5_Sto_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Sto_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Sto_0915/platform.rtf b/general/datasets/GTEXv5_Sto_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Sto_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Sto_0915/processing.rtf b/general/datasets/GTEXv5_Sto_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Sto_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Sto_0915/specifics.rtf b/general/datasets/GTEXv5_Sto_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Sto_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Sto_0915/summary.rtf b/general/datasets/GTEXv5_Sto_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Sto_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Sto_0915/tissue.rtf b/general/datasets/GTEXv5_Sto_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Sto_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Test_0915/cases.rtf b/general/datasets/GTEXv5_Test_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Test_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Test_0915/experiment-design.rtf b/general/datasets/GTEXv5_Test_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Test_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Test_0915/platform.rtf b/general/datasets/GTEXv5_Test_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Test_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Test_0915/processing.rtf b/general/datasets/GTEXv5_Test_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Test_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Test_0915/specifics.rtf b/general/datasets/GTEXv5_Test_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Test_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Test_0915/summary.rtf b/general/datasets/GTEXv5_Test_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Test_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Test_0915/tissue.rtf b/general/datasets/GTEXv5_Test_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Test_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Thy_0915/cases.rtf b/general/datasets/GTEXv5_Thy_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Thy_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Thy_0915/experiment-design.rtf b/general/datasets/GTEXv5_Thy_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Thy_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Thy_0915/platform.rtf b/general/datasets/GTEXv5_Thy_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Thy_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Thy_0915/processing.rtf b/general/datasets/GTEXv5_Thy_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Thy_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Thy_0915/specifics.rtf b/general/datasets/GTEXv5_Thy_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Thy_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Thy_0915/summary.rtf b/general/datasets/GTEXv5_Thy_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Thy_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Thy_0915/tissue.rtf b/general/datasets/GTEXv5_Thy_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Thy_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Ut_0915/cases.rtf b/general/datasets/GTEXv5_Ut_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Ut_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Ut_0915/experiment-design.rtf b/general/datasets/GTEXv5_Ut_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Ut_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Ut_0915/platform.rtf b/general/datasets/GTEXv5_Ut_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Ut_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Ut_0915/processing.rtf b/general/datasets/GTEXv5_Ut_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Ut_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Ut_0915/specifics.rtf b/general/datasets/GTEXv5_Ut_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Ut_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Ut_0915/summary.rtf b/general/datasets/GTEXv5_Ut_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Ut_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Ut_0915/tissue.rtf b/general/datasets/GTEXv5_Ut_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Ut_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEXv5_Wbl_0915/cases.rtf b/general/datasets/GTEXv5_Wbl_0915/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEXv5_Wbl_0915/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEXv5_Wbl_0915/experiment-design.rtf b/general/datasets/GTEXv5_Wbl_0915/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEXv5_Wbl_0915/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEXv5_Wbl_0915/platform.rtf b/general/datasets/GTEXv5_Wbl_0915/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEXv5_Wbl_0915/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEXv5_Wbl_0915/processing.rtf b/general/datasets/GTEXv5_Wbl_0915/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEXv5_Wbl_0915/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEXv5_Wbl_0915/specifics.rtf b/general/datasets/GTEXv5_Wbl_0915/specifics.rtf
deleted file mode 100644
index 80bf41d..0000000
--- a/general/datasets/GTEXv5_Wbl_0915/specifics.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
-
-
-
-Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
-
-More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
-
diff --git a/general/datasets/GTEXv5_Wbl_0915/summary.rtf b/general/datasets/GTEXv5_Wbl_0915/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEXv5_Wbl_0915/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEXv5_Wbl_0915/tissue.rtf b/general/datasets/GTEXv5_Wbl_0915/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEXv5_Wbl_0915/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_AMY_0314/cases.rtf b/general/datasets/GTEx_AMY_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_AMY_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_AMY_0314/experiment-design.rtf b/general/datasets/GTEx_AMY_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_AMY_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_AMY_0314/platform.rtf b/general/datasets/GTEx_AMY_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_AMY_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_AMY_0314/processing.rtf b/general/datasets/GTEx_AMY_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_AMY_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_AMY_0314/summary.rtf b/general/datasets/GTEx_AMY_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_AMY_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_AMY_0314/tissue.rtf b/general/datasets/GTEx_AMY_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_AMY_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Adren_0414/cases.rtf b/general/datasets/GTEx_Adren_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Adren_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Adren_0414/experiment-design.rtf b/general/datasets/GTEx_Adren_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Adren_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Adren_0414/platform.rtf b/general/datasets/GTEx_Adren_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Adren_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Adren_0414/processing.rtf b/general/datasets/GTEx_Adren_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Adren_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Adren_0414/summary.rtf b/general/datasets/GTEx_Adren_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Adren_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Adren_0414/tissue.rtf b/general/datasets/GTEx_Adren_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Adren_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Anter_0414/cases.rtf b/general/datasets/GTEx_Anter_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Anter_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Anter_0414/experiment-design.rtf b/general/datasets/GTEx_Anter_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Anter_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Anter_0414/platform.rtf b/general/datasets/GTEx_Anter_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Anter_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Anter_0414/processing.rtf b/general/datasets/GTEx_Anter_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Anter_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Anter_0414/summary.rtf b/general/datasets/GTEx_Anter_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Anter_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Anter_0414/tissue.rtf b/general/datasets/GTEx_Anter_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Anter_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Aorta_0414/cases.rtf b/general/datasets/GTEx_Aorta_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Aorta_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Aorta_0414/experiment-design.rtf b/general/datasets/GTEx_Aorta_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Aorta_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Aorta_0414/platform.rtf b/general/datasets/GTEx_Aorta_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Aorta_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Aorta_0414/processing.rtf b/general/datasets/GTEx_Aorta_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Aorta_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Aorta_0414/summary.rtf b/general/datasets/GTEx_Aorta_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Aorta_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Aorta_0414/tissue.rtf b/general/datasets/GTEx_Aorta_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Aorta_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Blood_0414/cases.rtf b/general/datasets/GTEx_Blood_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Blood_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Blood_0414/experiment-design.rtf b/general/datasets/GTEx_Blood_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Blood_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Blood_0414/platform.rtf b/general/datasets/GTEx_Blood_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Blood_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Blood_0414/processing.rtf b/general/datasets/GTEx_Blood_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Blood_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Blood_0414/summary.rtf b/general/datasets/GTEx_Blood_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Blood_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Blood_0414/tissue.rtf b/general/datasets/GTEx_Blood_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Blood_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Breas_0414/cases.rtf b/general/datasets/GTEx_Breas_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Breas_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Breas_0414/experiment-design.rtf b/general/datasets/GTEx_Breas_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Breas_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Breas_0414/platform.rtf b/general/datasets/GTEx_Breas_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Breas_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Breas_0414/processing.rtf b/general/datasets/GTEx_Breas_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Breas_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Breas_0414/summary.rtf b/general/datasets/GTEx_Breas_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Breas_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Breas_0414/tissue.rtf b/general/datasets/GTEx_Breas_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Breas_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_CER_0314/cases.rtf b/general/datasets/GTEx_CER_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_CER_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_CER_0314/experiment-design.rtf b/general/datasets/GTEx_CER_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_CER_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_CER_0314/platform.rtf b/general/datasets/GTEx_CER_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_CER_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_CER_0314/processing.rtf b/general/datasets/GTEx_CER_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_CER_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_CER_0314/summary.rtf b/general/datasets/GTEx_CER_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_CER_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_CER_0314/tissue.rtf b/general/datasets/GTEx_CER_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_CER_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Cauda_0414/cases.rtf b/general/datasets/GTEx_Cauda_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Cauda_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Cauda_0414/experiment-design.rtf b/general/datasets/GTEx_Cauda_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Cauda_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Cauda_0414/platform.rtf b/general/datasets/GTEx_Cauda_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Cauda_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Cauda_0414/processing.rtf b/general/datasets/GTEx_Cauda_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Cauda_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Cauda_0414/summary.rtf b/general/datasets/GTEx_Cauda_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Cauda_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Cauda_0414/tissue.rtf b/general/datasets/GTEx_Cauda_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Cauda_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_CellsEBV_0414/cases.rtf b/general/datasets/GTEx_CellsEBV_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_CellsEBV_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_CellsEBV_0414/experiment-design.rtf b/general/datasets/GTEx_CellsEBV_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_CellsEBV_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_CellsEBV_0414/platform.rtf b/general/datasets/GTEx_CellsEBV_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_CellsEBV_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_CellsEBV_0414/processing.rtf b/general/datasets/GTEx_CellsEBV_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_CellsEBV_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_CellsEBV_0414/summary.rtf b/general/datasets/GTEx_CellsEBV_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_CellsEBV_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_CellsEBV_0414/tissue.rtf b/general/datasets/GTEx_CellsEBV_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_CellsEBV_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_CellsLe_0414/experiment-design.rtf b/general/datasets/GTEx_CellsLe_0414/experiment-design.rtf
deleted file mode 100644
index f6a3038..0000000
--- a/general/datasets/GTEx_CellsLe_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Postmortem brain tissue was collected from ADRC brain banks. Cases were preferentially selected where 3 or more brain regions were available.
diff --git a/general/datasets/GTEx_CellsLe_0414/summary.rtf b/general/datasets/GTEx_CellsLe_0414/summary.rtf
deleted file mode 100644
index fea08e6..0000000
--- a/general/datasets/GTEx_CellsLe_0414/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Gene expression profiles were assessed in the hippocampus (HC), entorhinal cortex (EC), superior frontal gyrus (SG), and postcentral gyrus (PCG) across the lifespan of 63 cognitively intact individuals from 20-99 years old. New perspectives on the global gene changes that are associated with brain aging emerged, revealing two overarching concepts. First, different regions of the forebrain exhibited substantially different gene profile changes with age. For example, comparing equally powered groups, 5,029 probe sets were significantly altered with age (20-59 vs. 60-99) in the superior frontal gyrus, compared with 1,110 in the entorhinal cortex. Prominent change occurred in the 6th-7th decades across cortical regions, suggesting that this period is a critical transition point in brain aging, particularly in males. Second, clear gender differences in brain aging were evident across the lifespan, suggesting that the brain undergoes sexually dimorphic changes in gene expression not only in development but also in later life. Globally across all brain regions, males showed more gene change than females. Further, Gene Ontology analysis revealed that different categories of genes were predominantly affected in males vs. females. Notably, the male brain was characterized by global decreased catabolic and anabolic capacity with aging, with downregulated genes heavily enriched in energy production and protein synthesis/transport categories. Increased immune activation was a prominent feature of aging in both sexes, with more widespread activation in the female brain. These data open new opportunities to explore age-dependent changes in gene expression that set the balance between neurodegeneration and compensatory mechanisms in the brain, and suggest that this balance is set differently in males and females, an intriguing and novel idea. HgU133plus2.0 microarray chips were used to profile gene expression in 4 brain regions of cognitively intact humans, across the adult lifespan (ages 20-99).
diff --git a/general/datasets/GTEx_CellsTr_0414/cases.rtf b/general/datasets/GTEx_CellsTr_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_CellsTr_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_CellsTr_0414/experiment-design.rtf b/general/datasets/GTEx_CellsTr_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_CellsTr_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_CellsTr_0414/platform.rtf b/general/datasets/GTEx_CellsTr_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_CellsTr_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_CellsTr_0414/processing.rtf b/general/datasets/GTEx_CellsTr_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_CellsTr_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_CellsTr_0414/summary.rtf b/general/datasets/GTEx_CellsTr_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_CellsTr_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_CellsTr_0414/tissue.rtf b/general/datasets/GTEx_CellsTr_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_CellsTr_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_CerebC_0414/cases.rtf b/general/datasets/GTEx_CerebC_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_CerebC_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_CerebC_0414/experiment-design.rtf b/general/datasets/GTEx_CerebC_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_CerebC_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_CerebC_0414/platform.rtf b/general/datasets/GTEx_CerebC_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_CerebC_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_CerebC_0414/processing.rtf b/general/datasets/GTEx_CerebC_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_CerebC_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_CerebC_0414/summary.rtf b/general/datasets/GTEx_CerebC_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_CerebC_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_CerebC_0414/tissue.rtf b/general/datasets/GTEx_CerebC_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_CerebC_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_CerebH_0414/cases.rtf b/general/datasets/GTEx_CerebH_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_CerebH_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_CerebH_0414/experiment-design.rtf b/general/datasets/GTEx_CerebH_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_CerebH_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_CerebH_0414/platform.rtf b/general/datasets/GTEx_CerebH_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_CerebH_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_CerebH_0414/processing.rtf b/general/datasets/GTEx_CerebH_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_CerebH_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_CerebH_0414/summary.rtf b/general/datasets/GTEx_CerebH_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_CerebH_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_CerebH_0414/tissue.rtf b/general/datasets/GTEx_CerebH_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_CerebH_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Colon_0414/cases.rtf b/general/datasets/GTEx_Colon_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Colon_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Colon_0414/experiment-design.rtf b/general/datasets/GTEx_Colon_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Colon_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Colon_0414/platform.rtf b/general/datasets/GTEx_Colon_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Colon_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Colon_0414/processing.rtf b/general/datasets/GTEx_Colon_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Colon_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Colon_0414/summary.rtf b/general/datasets/GTEx_Colon_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Colon_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Colon_0414/tissue.rtf b/general/datasets/GTEx_Colon_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Colon_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Coron_0414/cases.rtf b/general/datasets/GTEx_Coron_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Coron_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Coron_0414/experiment-design.rtf b/general/datasets/GTEx_Coron_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Coron_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Coron_0414/platform.rtf b/general/datasets/GTEx_Coron_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Coron_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Coron_0414/processing.rtf b/general/datasets/GTEx_Coron_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Coron_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Coron_0414/summary.rtf b/general/datasets/GTEx_Coron_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Coron_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Coron_0414/tissue.rtf b/general/datasets/GTEx_Coron_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Coron_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_EsophMuc_0414/cases.rtf b/general/datasets/GTEx_EsophMuc_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_EsophMuc_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_EsophMuc_0414/experiment-design.rtf b/general/datasets/GTEx_EsophMuc_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_EsophMuc_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_EsophMuc_0414/platform.rtf b/general/datasets/GTEx_EsophMuc_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_EsophMuc_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_EsophMuc_0414/processing.rtf b/general/datasets/GTEx_EsophMuc_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_EsophMuc_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_EsophMuc_0414/summary.rtf b/general/datasets/GTEx_EsophMuc_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_EsophMuc_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_EsophMuc_0414/tissue.rtf b/general/datasets/GTEx_EsophMuc_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_EsophMuc_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_EsophMus_0414/cases.rtf b/general/datasets/GTEx_EsophMus_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_EsophMus_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_EsophMus_0414/experiment-design.rtf b/general/datasets/GTEx_EsophMus_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_EsophMus_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_EsophMus_0414/platform.rtf b/general/datasets/GTEx_EsophMus_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_EsophMus_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_EsophMus_0414/processing.rtf b/general/datasets/GTEx_EsophMus_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_EsophMus_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_EsophMus_0414/summary.rtf b/general/datasets/GTEx_EsophMus_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_EsophMus_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_EsophMus_0414/tissue.rtf b/general/datasets/GTEx_EsophMus_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_EsophMus_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Fallo_0414/cases.rtf b/general/datasets/GTEx_Fallo_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Fallo_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Fallo_0414/experiment-design.rtf b/general/datasets/GTEx_Fallo_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Fallo_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Fallo_0414/platform.rtf b/general/datasets/GTEx_Fallo_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Fallo_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Fallo_0414/processing.rtf b/general/datasets/GTEx_Fallo_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Fallo_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Fallo_0414/summary.rtf b/general/datasets/GTEx_Fallo_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Fallo_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Fallo_0414/tissue.rtf b/general/datasets/GTEx_Fallo_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Fallo_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Front_0414/cases.rtf b/general/datasets/GTEx_Front_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Front_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Front_0414/experiment-design.rtf b/general/datasets/GTEx_Front_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Front_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Front_0414/platform.rtf b/general/datasets/GTEx_Front_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Front_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Front_0414/processing.rtf b/general/datasets/GTEx_Front_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Front_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Front_0414/summary.rtf b/general/datasets/GTEx_Front_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Front_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Front_0414/tissue.rtf b/general/datasets/GTEx_Front_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Front_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_HIP_0314/cases.rtf b/general/datasets/GTEx_HIP_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_HIP_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_HIP_0314/experiment-design.rtf b/general/datasets/GTEx_HIP_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_HIP_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_HIP_0314/platform.rtf b/general/datasets/GTEx_HIP_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_HIP_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_HIP_0314/processing.rtf b/general/datasets/GTEx_HIP_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_HIP_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_HIP_0314/summary.rtf b/general/datasets/GTEx_HIP_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_HIP_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_HIP_0314/tissue.rtf b/general/datasets/GTEx_HIP_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_HIP_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_HeartAt_0414/cases.rtf b/general/datasets/GTEx_HeartAt_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_HeartAt_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_HeartAt_0414/experiment-design.rtf b/general/datasets/GTEx_HeartAt_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_HeartAt_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_HeartAt_0414/platform.rtf b/general/datasets/GTEx_HeartAt_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_HeartAt_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_HeartAt_0414/processing.rtf b/general/datasets/GTEx_HeartAt_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_HeartAt_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_HeartAt_0414/summary.rtf b/general/datasets/GTEx_HeartAt_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_HeartAt_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_HeartAt_0414/tissue.rtf b/general/datasets/GTEx_HeartAt_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_HeartAt_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_HeartLV_0414/cases.rtf b/general/datasets/GTEx_HeartLV_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_HeartLV_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_HeartLV_0414/experiment-design.rtf b/general/datasets/GTEx_HeartLV_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_HeartLV_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_HeartLV_0414/platform.rtf b/general/datasets/GTEx_HeartLV_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_HeartLV_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_HeartLV_0414/processing.rtf b/general/datasets/GTEx_HeartLV_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_HeartLV_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_HeartLV_0414/summary.rtf b/general/datasets/GTEx_HeartLV_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_HeartLV_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_HeartLV_0414/tissue.rtf b/general/datasets/GTEx_HeartLV_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_HeartLV_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Hypot_0414/cases.rtf b/general/datasets/GTEx_Hypot_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Hypot_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Hypot_0414/experiment-design.rtf b/general/datasets/GTEx_Hypot_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Hypot_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Hypot_0414/platform.rtf b/general/datasets/GTEx_Hypot_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Hypot_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Hypot_0414/processing.rtf b/general/datasets/GTEx_Hypot_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Hypot_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Hypot_0414/summary.rtf b/general/datasets/GTEx_Hypot_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Hypot_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Hypot_0414/tissue.rtf b/general/datasets/GTEx_Hypot_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Hypot_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Kidne_0414/cases.rtf b/general/datasets/GTEx_Kidne_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Kidne_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Kidne_0414/experiment-design.rtf b/general/datasets/GTEx_Kidne_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Kidne_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Kidne_0414/platform.rtf b/general/datasets/GTEx_Kidne_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Kidne_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Kidne_0414/processing.rtf b/general/datasets/GTEx_Kidne_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Kidne_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Kidne_0414/summary.rtf b/general/datasets/GTEx_Kidne_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Kidne_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Kidne_0414/tissue.rtf b/general/datasets/GTEx_Kidne_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Kidne_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Liver_0414/cases.rtf b/general/datasets/GTEx_Liver_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Liver_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Liver_0414/experiment-design.rtf b/general/datasets/GTEx_Liver_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Liver_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Liver_0414/platform.rtf b/general/datasets/GTEx_Liver_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Liver_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Liver_0414/processing.rtf b/general/datasets/GTEx_Liver_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Liver_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Liver_0414/summary.rtf b/general/datasets/GTEx_Liver_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Liver_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Liver_0414/tissue.rtf b/general/datasets/GTEx_Liver_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Liver_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Lung__0414/cases.rtf b/general/datasets/GTEx_Lung__0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Lung__0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Lung__0414/experiment-design.rtf b/general/datasets/GTEx_Lung__0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Lung__0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Lung__0414/platform.rtf b/general/datasets/GTEx_Lung__0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Lung__0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Lung__0414/processing.rtf b/general/datasets/GTEx_Lung__0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Lung__0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Lung__0414/summary.rtf b/general/datasets/GTEx_Lung__0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Lung__0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Lung__0414/tissue.rtf b/general/datasets/GTEx_Lung__0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Lung__0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Muscl_0414/cases.rtf b/general/datasets/GTEx_Muscl_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Muscl_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Muscl_0414/experiment-design.rtf b/general/datasets/GTEx_Muscl_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Muscl_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Muscl_0414/platform.rtf b/general/datasets/GTEx_Muscl_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Muscl_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Muscl_0414/processing.rtf b/general/datasets/GTEx_Muscl_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Muscl_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Muscl_0414/summary.rtf b/general/datasets/GTEx_Muscl_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Muscl_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Muscl_0414/tissue.rtf b/general/datasets/GTEx_Muscl_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Muscl_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Nerve_0414/cases.rtf b/general/datasets/GTEx_Nerve_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Nerve_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Nerve_0414/experiment-design.rtf b/general/datasets/GTEx_Nerve_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Nerve_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Nerve_0414/platform.rtf b/general/datasets/GTEx_Nerve_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Nerve_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Nerve_0414/processing.rtf b/general/datasets/GTEx_Nerve_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Nerve_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Nerve_0414/summary.rtf b/general/datasets/GTEx_Nerve_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Nerve_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Nerve_0414/tissue.rtf b/general/datasets/GTEx_Nerve_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Nerve_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Nucle_0414/cases.rtf b/general/datasets/GTEx_Nucle_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Nucle_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Nucle_0414/experiment-design.rtf b/general/datasets/GTEx_Nucle_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Nucle_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Nucle_0414/platform.rtf b/general/datasets/GTEx_Nucle_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Nucle_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Nucle_0414/processing.rtf b/general/datasets/GTEx_Nucle_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Nucle_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Nucle_0414/summary.rtf b/general/datasets/GTEx_Nucle_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Nucle_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Nucle_0414/tissue.rtf b/general/datasets/GTEx_Nucle_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Nucle_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Ovary_0414/cases.rtf b/general/datasets/GTEx_Ovary_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Ovary_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Ovary_0414/experiment-design.rtf b/general/datasets/GTEx_Ovary_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Ovary_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Ovary_0414/platform.rtf b/general/datasets/GTEx_Ovary_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Ovary_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Ovary_0414/processing.rtf b/general/datasets/GTEx_Ovary_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Ovary_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Ovary_0414/summary.rtf b/general/datasets/GTEx_Ovary_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Ovary_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Ovary_0414/tissue.rtf b/general/datasets/GTEx_Ovary_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Ovary_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Pancr_0414/cases.rtf b/general/datasets/GTEx_Pancr_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Pancr_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Pancr_0414/experiment-design.rtf b/general/datasets/GTEx_Pancr_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Pancr_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Pancr_0414/platform.rtf b/general/datasets/GTEx_Pancr_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Pancr_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Pancr_0414/processing.rtf b/general/datasets/GTEx_Pancr_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Pancr_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Pancr_0414/summary.rtf b/general/datasets/GTEx_Pancr_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Pancr_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Pancr_0414/tissue.rtf b/general/datasets/GTEx_Pancr_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Pancr_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Pitui_0414/cases.rtf b/general/datasets/GTEx_Pitui_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Pitui_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Pitui_0414/experiment-design.rtf b/general/datasets/GTEx_Pitui_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Pitui_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Pitui_0414/platform.rtf b/general/datasets/GTEx_Pitui_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Pitui_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Pitui_0414/processing.rtf b/general/datasets/GTEx_Pitui_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Pitui_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Pitui_0414/summary.rtf b/general/datasets/GTEx_Pitui_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Pitui_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Pitui_0414/tissue.rtf b/general/datasets/GTEx_Pitui_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Pitui_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Prost_0414/cases.rtf b/general/datasets/GTEx_Prost_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Prost_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Prost_0414/experiment-design.rtf b/general/datasets/GTEx_Prost_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Prost_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Prost_0414/platform.rtf b/general/datasets/GTEx_Prost_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Prost_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Prost_0414/processing.rtf b/general/datasets/GTEx_Prost_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Prost_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Prost_0414/summary.rtf b/general/datasets/GTEx_Prost_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Prost_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Prost_0414/tissue.rtf b/general/datasets/GTEx_Prost_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Prost_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Putam_0414/cases.rtf b/general/datasets/GTEx_Putam_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Putam_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Putam_0414/experiment-design.rtf b/general/datasets/GTEx_Putam_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Putam_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Putam_0414/platform.rtf b/general/datasets/GTEx_Putam_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Putam_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Putam_0414/processing.rtf b/general/datasets/GTEx_Putam_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Putam_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Putam_0414/summary.rtf b/general/datasets/GTEx_Putam_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Putam_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Putam_0414/tissue.rtf b/general/datasets/GTEx_Putam_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Putam_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_SkinE_0414/cases.rtf b/general/datasets/GTEx_SkinE_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_SkinE_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_SkinE_0414/experiment-design.rtf b/general/datasets/GTEx_SkinE_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_SkinE_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_SkinE_0414/platform.rtf b/general/datasets/GTEx_SkinE_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_SkinE_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_SkinE_0414/processing.rtf b/general/datasets/GTEx_SkinE_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_SkinE_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_SkinE_0414/summary.rtf b/general/datasets/GTEx_SkinE_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_SkinE_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_SkinE_0414/tissue.rtf b/general/datasets/GTEx_SkinE_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_SkinE_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_SkinN_0414/cases.rtf b/general/datasets/GTEx_SkinN_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_SkinN_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_SkinN_0414/experiment-design.rtf b/general/datasets/GTEx_SkinN_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_SkinN_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_SkinN_0414/platform.rtf b/general/datasets/GTEx_SkinN_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_SkinN_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_SkinN_0414/processing.rtf b/general/datasets/GTEx_SkinN_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_SkinN_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_SkinN_0414/summary.rtf b/general/datasets/GTEx_SkinN_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_SkinN_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_SkinN_0414/tissue.rtf b/general/datasets/GTEx_SkinN_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_SkinN_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Spina_0414/cases.rtf b/general/datasets/GTEx_Spina_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Spina_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Spina_0414/experiment-design.rtf b/general/datasets/GTEx_Spina_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Spina_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Spina_0414/platform.rtf b/general/datasets/GTEx_Spina_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Spina_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Spina_0414/processing.rtf b/general/datasets/GTEx_Spina_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Spina_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Spina_0414/summary.rtf b/general/datasets/GTEx_Spina_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Spina_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Spina_0414/tissue.rtf b/general/datasets/GTEx_Spina_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Spina_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Stoma_0414/cases.rtf b/general/datasets/GTEx_Stoma_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Stoma_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Stoma_0414/experiment-design.rtf b/general/datasets/GTEx_Stoma_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Stoma_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Stoma_0414/platform.rtf b/general/datasets/GTEx_Stoma_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Stoma_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Stoma_0414/processing.rtf b/general/datasets/GTEx_Stoma_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Stoma_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Stoma_0414/summary.rtf b/general/datasets/GTEx_Stoma_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Stoma_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Stoma_0414/tissue.rtf b/general/datasets/GTEx_Stoma_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Stoma_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Subcu_0414/cases.rtf b/general/datasets/GTEx_Subcu_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Subcu_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Subcu_0414/experiment-design.rtf b/general/datasets/GTEx_Subcu_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Subcu_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Subcu_0414/platform.rtf b/general/datasets/GTEx_Subcu_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Subcu_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Subcu_0414/processing.rtf b/general/datasets/GTEx_Subcu_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Subcu_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Subcu_0414/summary.rtf b/general/datasets/GTEx_Subcu_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Subcu_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Subcu_0414/tissue.rtf b/general/datasets/GTEx_Subcu_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Subcu_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Subst_0414/cases.rtf b/general/datasets/GTEx_Subst_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Subst_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Subst_0414/experiment-design.rtf b/general/datasets/GTEx_Subst_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Subst_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Subst_0414/platform.rtf b/general/datasets/GTEx_Subst_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Subst_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Subst_0414/processing.rtf b/general/datasets/GTEx_Subst_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Subst_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Subst_0414/summary.rtf b/general/datasets/GTEx_Subst_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Subst_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Subst_0414/tissue.rtf b/general/datasets/GTEx_Subst_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Subst_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Testi_0414/cases.rtf b/general/datasets/GTEx_Testi_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Testi_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Testi_0414/experiment-design.rtf b/general/datasets/GTEx_Testi_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Testi_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Testi_0414/platform.rtf b/general/datasets/GTEx_Testi_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Testi_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Testi_0414/processing.rtf b/general/datasets/GTEx_Testi_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Testi_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Testi_0414/summary.rtf b/general/datasets/GTEx_Testi_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Testi_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Testi_0414/tissue.rtf b/general/datasets/GTEx_Testi_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Testi_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Thyro_0414/cases.rtf b/general/datasets/GTEx_Thyro_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Thyro_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Thyro_0414/experiment-design.rtf b/general/datasets/GTEx_Thyro_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Thyro_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Thyro_0414/platform.rtf b/general/datasets/GTEx_Thyro_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Thyro_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Thyro_0414/processing.rtf b/general/datasets/GTEx_Thyro_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Thyro_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Thyro_0414/summary.rtf b/general/datasets/GTEx_Thyro_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Thyro_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Thyro_0414/tissue.rtf b/general/datasets/GTEx_Thyro_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Thyro_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Tibia_0414/cases.rtf b/general/datasets/GTEx_Tibia_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Tibia_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Tibia_0414/experiment-design.rtf b/general/datasets/GTEx_Tibia_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Tibia_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Tibia_0414/platform.rtf b/general/datasets/GTEx_Tibia_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Tibia_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Tibia_0414/processing.rtf b/general/datasets/GTEx_Tibia_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Tibia_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Tibia_0414/summary.rtf b/general/datasets/GTEx_Tibia_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Tibia_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Tibia_0414/tissue.rtf b/general/datasets/GTEx_Tibia_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Tibia_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Uteru_0414/cases.rtf b/general/datasets/GTEx_Uteru_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Uteru_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Uteru_0414/experiment-design.rtf b/general/datasets/GTEx_Uteru_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Uteru_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Uteru_0414/platform.rtf b/general/datasets/GTEx_Uteru_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Uteru_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Uteru_0414/processing.rtf b/general/datasets/GTEx_Uteru_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Uteru_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Uteru_0414/summary.rtf b/general/datasets/GTEx_Uteru_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Uteru_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Uteru_0414/tissue.rtf b/general/datasets/GTEx_Uteru_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Uteru_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Vagin_0414/cases.rtf b/general/datasets/GTEx_Vagin_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Vagin_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Vagin_0414/experiment-design.rtf b/general/datasets/GTEx_Vagin_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Vagin_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Vagin_0414/platform.rtf b/general/datasets/GTEx_Vagin_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Vagin_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Vagin_0414/processing.rtf b/general/datasets/GTEx_Vagin_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Vagin_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Vagin_0414/summary.rtf b/general/datasets/GTEx_Vagin_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Vagin_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Vagin_0414/tissue.rtf b/general/datasets/GTEx_Vagin_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Vagin_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Visce_0414/cases.rtf b/general/datasets/GTEx_Visce_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Visce_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Visce_0414/experiment-design.rtf b/general/datasets/GTEx_Visce_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Visce_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Visce_0414/platform.rtf b/general/datasets/GTEx_Visce_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Visce_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Visce_0414/processing.rtf b/general/datasets/GTEx_Visce_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Visce_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Visce_0414/summary.rtf b/general/datasets/GTEx_Visce_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Visce_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Visce_0414/tissue.rtf b/general/datasets/GTEx_Visce_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Visce_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_Whole_0414/cases.rtf b/general/datasets/GTEx_Whole_0414/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_Whole_0414/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_Whole_0414/experiment-design.rtf b/general/datasets/GTEx_Whole_0414/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_Whole_0414/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_Whole_0414/platform.rtf b/general/datasets/GTEx_Whole_0414/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_Whole_0414/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_Whole_0414/processing.rtf b/general/datasets/GTEx_Whole_0414/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_Whole_0414/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_Whole_0414/summary.rtf b/general/datasets/GTEx_Whole_0414/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_Whole_0414/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_Whole_0414/tissue.rtf b/general/datasets/GTEx_Whole_0414/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_Whole_0414/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_AMY_0314/cases.rtf b/general/datasets/GTEx_log2_AMY_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_AMY_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_AMY_0314/experiment-design.rtf b/general/datasets/GTEx_log2_AMY_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_AMY_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_AMY_0314/platform.rtf b/general/datasets/GTEx_log2_AMY_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_AMY_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_AMY_0314/processing.rtf b/general/datasets/GTEx_log2_AMY_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_AMY_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_AMY_0314/summary.rtf b/general/datasets/GTEx_log2_AMY_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_AMY_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_AMY_0314/tissue.rtf b/general/datasets/GTEx_log2_AMY_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_AMY_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Adren_0314/cases.rtf b/general/datasets/GTEx_log2_Adren_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Adren_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Adren_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Adren_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Adren_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Adren_0314/platform.rtf b/general/datasets/GTEx_log2_Adren_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Adren_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Adren_0314/processing.rtf b/general/datasets/GTEx_log2_Adren_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Adren_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Adren_0314/summary.rtf b/general/datasets/GTEx_log2_Adren_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Adren_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Adren_0314/tissue.rtf b/general/datasets/GTEx_log2_Adren_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Adren_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Anter_0314/cases.rtf b/general/datasets/GTEx_log2_Anter_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Anter_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Anter_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Anter_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Anter_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Anter_0314/platform.rtf b/general/datasets/GTEx_log2_Anter_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Anter_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Anter_0314/processing.rtf b/general/datasets/GTEx_log2_Anter_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Anter_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Anter_0314/summary.rtf b/general/datasets/GTEx_log2_Anter_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Anter_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Anter_0314/tissue.rtf b/general/datasets/GTEx_log2_Anter_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Anter_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Aorta_0314/cases.rtf b/general/datasets/GTEx_log2_Aorta_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Aorta_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Aorta_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Aorta_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Aorta_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Aorta_0314/platform.rtf b/general/datasets/GTEx_log2_Aorta_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Aorta_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Aorta_0314/processing.rtf b/general/datasets/GTEx_log2_Aorta_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Aorta_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Aorta_0314/summary.rtf b/general/datasets/GTEx_log2_Aorta_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Aorta_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Aorta_0314/tissue.rtf b/general/datasets/GTEx_log2_Aorta_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Aorta_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Blood_0314/cases.rtf b/general/datasets/GTEx_log2_Blood_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Blood_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Blood_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Blood_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Blood_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Blood_0314/platform.rtf b/general/datasets/GTEx_log2_Blood_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Blood_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Blood_0314/processing.rtf b/general/datasets/GTEx_log2_Blood_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Blood_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Blood_0314/summary.rtf b/general/datasets/GTEx_log2_Blood_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Blood_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Blood_0314/tissue.rtf b/general/datasets/GTEx_log2_Blood_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Blood_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Breas_0314/cases.rtf b/general/datasets/GTEx_log2_Breas_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Breas_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Breas_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Breas_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Breas_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Breas_0314/platform.rtf b/general/datasets/GTEx_log2_Breas_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Breas_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Breas_0314/processing.rtf b/general/datasets/GTEx_log2_Breas_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Breas_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Breas_0314/summary.rtf b/general/datasets/GTEx_log2_Breas_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Breas_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Breas_0314/tissue.rtf b/general/datasets/GTEx_log2_Breas_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Breas_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_CER_0314/cases.rtf b/general/datasets/GTEx_log2_CER_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_CER_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_CER_0314/experiment-design.rtf b/general/datasets/GTEx_log2_CER_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_CER_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_CER_0314/platform.rtf b/general/datasets/GTEx_log2_CER_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_CER_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_CER_0314/processing.rtf b/general/datasets/GTEx_log2_CER_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_CER_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_CER_0314/summary.rtf b/general/datasets/GTEx_log2_CER_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_CER_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_CER_0314/tissue.rtf b/general/datasets/GTEx_log2_CER_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_CER_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Cauda_0314/cases.rtf b/general/datasets/GTEx_log2_Cauda_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Cauda_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Cauda_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Cauda_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Cauda_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Cauda_0314/platform.rtf b/general/datasets/GTEx_log2_Cauda_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Cauda_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Cauda_0314/processing.rtf b/general/datasets/GTEx_log2_Cauda_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Cauda_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Cauda_0314/summary.rtf b/general/datasets/GTEx_log2_Cauda_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Cauda_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Cauda_0314/tissue.rtf b/general/datasets/GTEx_log2_Cauda_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Cauda_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_CellsEBV_0314/cases.rtf b/general/datasets/GTEx_log2_CellsEBV_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_CellsEBV_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_CellsEBV_0314/experiment-design.rtf b/general/datasets/GTEx_log2_CellsEBV_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_CellsEBV_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_CellsEBV_0314/platform.rtf b/general/datasets/GTEx_log2_CellsEBV_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_CellsEBV_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_CellsEBV_0314/processing.rtf b/general/datasets/GTEx_log2_CellsEBV_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_CellsEBV_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_CellsEBV_0314/summary.rtf b/general/datasets/GTEx_log2_CellsEBV_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_CellsEBV_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_CellsEBV_0314/tissue.rtf b/general/datasets/GTEx_log2_CellsEBV_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_CellsEBV_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_CellsLe_0314/cases.rtf b/general/datasets/GTEx_log2_CellsLe_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_CellsLe_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_CellsLe_0314/experiment-design.rtf b/general/datasets/GTEx_log2_CellsLe_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_CellsLe_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_CellsLe_0314/platform.rtf b/general/datasets/GTEx_log2_CellsLe_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_CellsLe_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_CellsLe_0314/processing.rtf b/general/datasets/GTEx_log2_CellsLe_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_CellsLe_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_CellsLe_0314/summary.rtf b/general/datasets/GTEx_log2_CellsLe_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_CellsLe_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_CellsLe_0314/tissue.rtf b/general/datasets/GTEx_log2_CellsLe_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_CellsLe_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_CellsTr_0314/cases.rtf b/general/datasets/GTEx_log2_CellsTr_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_CellsTr_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_CellsTr_0314/experiment-design.rtf b/general/datasets/GTEx_log2_CellsTr_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_CellsTr_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_CellsTr_0314/platform.rtf b/general/datasets/GTEx_log2_CellsTr_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_CellsTr_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_CellsTr_0314/processing.rtf b/general/datasets/GTEx_log2_CellsTr_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_CellsTr_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_CellsTr_0314/summary.rtf b/general/datasets/GTEx_log2_CellsTr_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_CellsTr_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_CellsTr_0314/tissue.rtf b/general/datasets/GTEx_log2_CellsTr_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_CellsTr_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_CerebC_0314/cases.rtf b/general/datasets/GTEx_log2_CerebC_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_CerebC_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_CerebC_0314/experiment-design.rtf b/general/datasets/GTEx_log2_CerebC_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_CerebC_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_CerebC_0314/platform.rtf b/general/datasets/GTEx_log2_CerebC_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_CerebC_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_CerebC_0314/processing.rtf b/general/datasets/GTEx_log2_CerebC_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_CerebC_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_CerebC_0314/summary.rtf b/general/datasets/GTEx_log2_CerebC_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_CerebC_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_CerebC_0314/tissue.rtf b/general/datasets/GTEx_log2_CerebC_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_CerebC_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_CerebH_0314/cases.rtf b/general/datasets/GTEx_log2_CerebH_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_CerebH_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_CerebH_0314/experiment-design.rtf b/general/datasets/GTEx_log2_CerebH_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_CerebH_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_CerebH_0314/platform.rtf b/general/datasets/GTEx_log2_CerebH_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_CerebH_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_CerebH_0314/processing.rtf b/general/datasets/GTEx_log2_CerebH_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_CerebH_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_CerebH_0314/summary.rtf b/general/datasets/GTEx_log2_CerebH_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_CerebH_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_CerebH_0314/tissue.rtf b/general/datasets/GTEx_log2_CerebH_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_CerebH_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Colon_0314/cases.rtf b/general/datasets/GTEx_log2_Colon_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Colon_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Colon_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Colon_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Colon_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Colon_0314/platform.rtf b/general/datasets/GTEx_log2_Colon_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Colon_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Colon_0314/processing.rtf b/general/datasets/GTEx_log2_Colon_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Colon_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Colon_0314/summary.rtf b/general/datasets/GTEx_log2_Colon_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Colon_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Colon_0314/tissue.rtf b/general/datasets/GTEx_log2_Colon_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Colon_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Coron_0314/cases.rtf b/general/datasets/GTEx_log2_Coron_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Coron_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Coron_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Coron_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Coron_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Coron_0314/platform.rtf b/general/datasets/GTEx_log2_Coron_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Coron_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Coron_0314/processing.rtf b/general/datasets/GTEx_log2_Coron_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Coron_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Coron_0314/summary.rtf b/general/datasets/GTEx_log2_Coron_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Coron_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Coron_0314/tissue.rtf b/general/datasets/GTEx_log2_Coron_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Coron_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_EsophMuc_0314/cases.rtf b/general/datasets/GTEx_log2_EsophMuc_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_EsophMuc_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_EsophMuc_0314/experiment-design.rtf b/general/datasets/GTEx_log2_EsophMuc_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_EsophMuc_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_EsophMuc_0314/platform.rtf b/general/datasets/GTEx_log2_EsophMuc_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_EsophMuc_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_EsophMuc_0314/processing.rtf b/general/datasets/GTEx_log2_EsophMuc_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_EsophMuc_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_EsophMuc_0314/summary.rtf b/general/datasets/GTEx_log2_EsophMuc_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_EsophMuc_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_EsophMuc_0314/tissue.rtf b/general/datasets/GTEx_log2_EsophMuc_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_EsophMuc_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_EsophMus_0314/cases.rtf b/general/datasets/GTEx_log2_EsophMus_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_EsophMus_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_EsophMus_0314/experiment-design.rtf b/general/datasets/GTEx_log2_EsophMus_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_EsophMus_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_EsophMus_0314/platform.rtf b/general/datasets/GTEx_log2_EsophMus_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_EsophMus_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_EsophMus_0314/processing.rtf b/general/datasets/GTEx_log2_EsophMus_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_EsophMus_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_EsophMus_0314/summary.rtf b/general/datasets/GTEx_log2_EsophMus_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_EsophMus_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_EsophMus_0314/tissue.rtf b/general/datasets/GTEx_log2_EsophMus_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_EsophMus_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Fallo_0314/cases.rtf b/general/datasets/GTEx_log2_Fallo_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Fallo_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Fallo_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Fallo_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Fallo_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Fallo_0314/platform.rtf b/general/datasets/GTEx_log2_Fallo_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Fallo_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Fallo_0314/processing.rtf b/general/datasets/GTEx_log2_Fallo_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Fallo_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Fallo_0314/summary.rtf b/general/datasets/GTEx_log2_Fallo_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Fallo_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Fallo_0314/tissue.rtf b/general/datasets/GTEx_log2_Fallo_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Fallo_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Front_0314/cases.rtf b/general/datasets/GTEx_log2_Front_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Front_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Front_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Front_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Front_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Front_0314/platform.rtf b/general/datasets/GTEx_log2_Front_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Front_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Front_0314/processing.rtf b/general/datasets/GTEx_log2_Front_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Front_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Front_0314/summary.rtf b/general/datasets/GTEx_log2_Front_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Front_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Front_0314/tissue.rtf b/general/datasets/GTEx_log2_Front_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Front_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_HIP_0314/cases.rtf b/general/datasets/GTEx_log2_HIP_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_HIP_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_HIP_0314/experiment-design.rtf b/general/datasets/GTEx_log2_HIP_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_HIP_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_HIP_0314/platform.rtf b/general/datasets/GTEx_log2_HIP_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_HIP_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_HIP_0314/processing.rtf b/general/datasets/GTEx_log2_HIP_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_HIP_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_HIP_0314/summary.rtf b/general/datasets/GTEx_log2_HIP_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_HIP_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_HIP_0314/tissue.rtf b/general/datasets/GTEx_log2_HIP_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_HIP_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_HeartAt_0314/cases.rtf b/general/datasets/GTEx_log2_HeartAt_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_HeartAt_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_HeartAt_0314/experiment-design.rtf b/general/datasets/GTEx_log2_HeartAt_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_HeartAt_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_HeartAt_0314/platform.rtf b/general/datasets/GTEx_log2_HeartAt_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_HeartAt_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_HeartAt_0314/processing.rtf b/general/datasets/GTEx_log2_HeartAt_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_HeartAt_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_HeartAt_0314/summary.rtf b/general/datasets/GTEx_log2_HeartAt_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_HeartAt_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_HeartAt_0314/tissue.rtf b/general/datasets/GTEx_log2_HeartAt_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_HeartAt_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_HeartLV_0314/cases.rtf b/general/datasets/GTEx_log2_HeartLV_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_HeartLV_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_HeartLV_0314/experiment-design.rtf b/general/datasets/GTEx_log2_HeartLV_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_HeartLV_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_HeartLV_0314/platform.rtf b/general/datasets/GTEx_log2_HeartLV_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_HeartLV_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_HeartLV_0314/processing.rtf b/general/datasets/GTEx_log2_HeartLV_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_HeartLV_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_HeartLV_0314/summary.rtf b/general/datasets/GTEx_log2_HeartLV_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_HeartLV_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_HeartLV_0314/tissue.rtf b/general/datasets/GTEx_log2_HeartLV_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_HeartLV_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Hypot_0314/cases.rtf b/general/datasets/GTEx_log2_Hypot_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Hypot_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Hypot_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Hypot_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Hypot_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Hypot_0314/platform.rtf b/general/datasets/GTEx_log2_Hypot_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Hypot_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Hypot_0314/processing.rtf b/general/datasets/GTEx_log2_Hypot_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Hypot_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Hypot_0314/summary.rtf b/general/datasets/GTEx_log2_Hypot_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Hypot_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Hypot_0314/tissue.rtf b/general/datasets/GTEx_log2_Hypot_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Hypot_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Kidne_0314/cases.rtf b/general/datasets/GTEx_log2_Kidne_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Kidne_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Kidne_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Kidne_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Kidne_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Kidne_0314/platform.rtf b/general/datasets/GTEx_log2_Kidne_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Kidne_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Kidne_0314/processing.rtf b/general/datasets/GTEx_log2_Kidne_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Kidne_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Kidne_0314/summary.rtf b/general/datasets/GTEx_log2_Kidne_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Kidne_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Kidne_0314/tissue.rtf b/general/datasets/GTEx_log2_Kidne_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Kidne_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Liver_0314/cases.rtf b/general/datasets/GTEx_log2_Liver_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Liver_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Liver_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Liver_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Liver_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Liver_0314/platform.rtf b/general/datasets/GTEx_log2_Liver_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Liver_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Liver_0314/processing.rtf b/general/datasets/GTEx_log2_Liver_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Liver_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Liver_0314/summary.rtf b/general/datasets/GTEx_log2_Liver_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Liver_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Liver_0314/tissue.rtf b/general/datasets/GTEx_log2_Liver_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Liver_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Lung_0314/cases.rtf b/general/datasets/GTEx_log2_Lung_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Lung_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Lung_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Lung_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Lung_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Lung_0314/platform.rtf b/general/datasets/GTEx_log2_Lung_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Lung_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Lung_0314/processing.rtf b/general/datasets/GTEx_log2_Lung_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Lung_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Lung_0314/summary.rtf b/general/datasets/GTEx_log2_Lung_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Lung_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Lung_0314/tissue.rtf b/general/datasets/GTEx_log2_Lung_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Lung_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Muscle_0314/cases.rtf b/general/datasets/GTEx_log2_Muscle_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Muscle_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Muscle_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Muscle_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Muscle_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Muscle_0314/platform.rtf b/general/datasets/GTEx_log2_Muscle_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Muscle_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Muscle_0314/processing.rtf b/general/datasets/GTEx_log2_Muscle_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Muscle_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Muscle_0314/summary.rtf b/general/datasets/GTEx_log2_Muscle_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Muscle_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Muscle_0314/tissue.rtf b/general/datasets/GTEx_log2_Muscle_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Muscle_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Nerve_0314/cases.rtf b/general/datasets/GTEx_log2_Nerve_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Nerve_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Nerve_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Nerve_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Nerve_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Nerve_0314/platform.rtf b/general/datasets/GTEx_log2_Nerve_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Nerve_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Nerve_0314/processing.rtf b/general/datasets/GTEx_log2_Nerve_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Nerve_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Nerve_0314/summary.rtf b/general/datasets/GTEx_log2_Nerve_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Nerve_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Nerve_0314/tissue.rtf b/general/datasets/GTEx_log2_Nerve_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Nerve_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Nucle_0314/cases.rtf b/general/datasets/GTEx_log2_Nucle_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Nucle_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Nucle_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Nucle_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Nucle_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Nucle_0314/platform.rtf b/general/datasets/GTEx_log2_Nucle_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Nucle_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Nucle_0314/processing.rtf b/general/datasets/GTEx_log2_Nucle_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Nucle_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Nucle_0314/summary.rtf b/general/datasets/GTEx_log2_Nucle_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Nucle_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Nucle_0314/tissue.rtf b/general/datasets/GTEx_log2_Nucle_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Nucle_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Ovary_0314/cases.rtf b/general/datasets/GTEx_log2_Ovary_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Ovary_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Ovary_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Ovary_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Ovary_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Ovary_0314/platform.rtf b/general/datasets/GTEx_log2_Ovary_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Ovary_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Ovary_0314/processing.rtf b/general/datasets/GTEx_log2_Ovary_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Ovary_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Ovary_0314/summary.rtf b/general/datasets/GTEx_log2_Ovary_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Ovary_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Ovary_0314/tissue.rtf b/general/datasets/GTEx_log2_Ovary_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Ovary_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Pancr_0314/cases.rtf b/general/datasets/GTEx_log2_Pancr_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Pancr_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Pancr_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Pancr_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Pancr_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Pancr_0314/platform.rtf b/general/datasets/GTEx_log2_Pancr_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Pancr_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Pancr_0314/processing.rtf b/general/datasets/GTEx_log2_Pancr_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Pancr_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Pancr_0314/summary.rtf b/general/datasets/GTEx_log2_Pancr_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Pancr_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Pancr_0314/tissue.rtf b/general/datasets/GTEx_log2_Pancr_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Pancr_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Pitui_0314/cases.rtf b/general/datasets/GTEx_log2_Pitui_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Pitui_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Pitui_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Pitui_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Pitui_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Pitui_0314/platform.rtf b/general/datasets/GTEx_log2_Pitui_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Pitui_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Pitui_0314/processing.rtf b/general/datasets/GTEx_log2_Pitui_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Pitui_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Pitui_0314/summary.rtf b/general/datasets/GTEx_log2_Pitui_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Pitui_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Pitui_0314/tissue.rtf b/general/datasets/GTEx_log2_Pitui_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Pitui_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Prost_0314/cases.rtf b/general/datasets/GTEx_log2_Prost_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Prost_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Prost_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Prost_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Prost_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Prost_0314/platform.rtf b/general/datasets/GTEx_log2_Prost_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Prost_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Prost_0314/processing.rtf b/general/datasets/GTEx_log2_Prost_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Prost_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Prost_0314/summary.rtf b/general/datasets/GTEx_log2_Prost_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Prost_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Prost_0314/tissue.rtf b/general/datasets/GTEx_log2_Prost_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Prost_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Putam_0314/cases.rtf b/general/datasets/GTEx_log2_Putam_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Putam_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Putam_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Putam_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Putam_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Putam_0314/platform.rtf b/general/datasets/GTEx_log2_Putam_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Putam_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Putam_0314/processing.rtf b/general/datasets/GTEx_log2_Putam_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Putam_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Putam_0314/summary.rtf b/general/datasets/GTEx_log2_Putam_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Putam_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Putam_0314/tissue.rtf b/general/datasets/GTEx_log2_Putam_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Putam_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_SkinE_0314/cases.rtf b/general/datasets/GTEx_log2_SkinE_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_SkinE_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_SkinE_0314/experiment-design.rtf b/general/datasets/GTEx_log2_SkinE_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_SkinE_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_SkinE_0314/platform.rtf b/general/datasets/GTEx_log2_SkinE_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_SkinE_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_SkinE_0314/processing.rtf b/general/datasets/GTEx_log2_SkinE_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_SkinE_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_SkinE_0314/summary.rtf b/general/datasets/GTEx_log2_SkinE_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_SkinE_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_SkinE_0314/tissue.rtf b/general/datasets/GTEx_log2_SkinE_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_SkinE_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_SkinN_0314/cases.rtf b/general/datasets/GTEx_log2_SkinN_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_SkinN_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_SkinN_0314/experiment-design.rtf b/general/datasets/GTEx_log2_SkinN_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_SkinN_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_SkinN_0314/platform.rtf b/general/datasets/GTEx_log2_SkinN_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_SkinN_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_SkinN_0314/processing.rtf b/general/datasets/GTEx_log2_SkinN_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_SkinN_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_SkinN_0314/summary.rtf b/general/datasets/GTEx_log2_SkinN_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_SkinN_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_SkinN_0314/tissue.rtf b/general/datasets/GTEx_log2_SkinN_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_SkinN_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Spina_0314/cases.rtf b/general/datasets/GTEx_log2_Spina_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Spina_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Spina_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Spina_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Spina_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Spina_0314/platform.rtf b/general/datasets/GTEx_log2_Spina_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Spina_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Spina_0314/processing.rtf b/general/datasets/GTEx_log2_Spina_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Spina_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Spina_0314/summary.rtf b/general/datasets/GTEx_log2_Spina_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Spina_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Spina_0314/tissue.rtf b/general/datasets/GTEx_log2_Spina_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Spina_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Stoma_0314/cases.rtf b/general/datasets/GTEx_log2_Stoma_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Stoma_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Stoma_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Stoma_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Stoma_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Stoma_0314/platform.rtf b/general/datasets/GTEx_log2_Stoma_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Stoma_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Stoma_0314/processing.rtf b/general/datasets/GTEx_log2_Stoma_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Stoma_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Stoma_0314/summary.rtf b/general/datasets/GTEx_log2_Stoma_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Stoma_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Stoma_0314/tissue.rtf b/general/datasets/GTEx_log2_Stoma_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Stoma_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Subcu_0314/cases.rtf b/general/datasets/GTEx_log2_Subcu_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Subcu_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Subcu_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Subcu_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Subcu_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Subcu_0314/platform.rtf b/general/datasets/GTEx_log2_Subcu_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Subcu_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Subcu_0314/processing.rtf b/general/datasets/GTEx_log2_Subcu_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Subcu_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Subcu_0314/summary.rtf b/general/datasets/GTEx_log2_Subcu_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Subcu_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Subcu_0314/tissue.rtf b/general/datasets/GTEx_log2_Subcu_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Subcu_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Subst_0314/cases.rtf b/general/datasets/GTEx_log2_Subst_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Subst_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Subst_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Subst_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Subst_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Subst_0314/platform.rtf b/general/datasets/GTEx_log2_Subst_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Subst_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Subst_0314/processing.rtf b/general/datasets/GTEx_log2_Subst_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Subst_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Subst_0314/summary.rtf b/general/datasets/GTEx_log2_Subst_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Subst_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Subst_0314/tissue.rtf b/general/datasets/GTEx_log2_Subst_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Subst_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Testi_0314/cases.rtf b/general/datasets/GTEx_log2_Testi_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Testi_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Testi_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Testi_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Testi_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Testi_0314/platform.rtf b/general/datasets/GTEx_log2_Testi_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Testi_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Testi_0314/processing.rtf b/general/datasets/GTEx_log2_Testi_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Testi_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Testi_0314/summary.rtf b/general/datasets/GTEx_log2_Testi_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Testi_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Testi_0314/tissue.rtf b/general/datasets/GTEx_log2_Testi_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Testi_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Thyro_0314/cases.rtf b/general/datasets/GTEx_log2_Thyro_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Thyro_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Thyro_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Thyro_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Thyro_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Thyro_0314/platform.rtf b/general/datasets/GTEx_log2_Thyro_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Thyro_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Thyro_0314/processing.rtf b/general/datasets/GTEx_log2_Thyro_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Thyro_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Thyro_0314/summary.rtf b/general/datasets/GTEx_log2_Thyro_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Thyro_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Thyro_0314/tissue.rtf b/general/datasets/GTEx_log2_Thyro_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Thyro_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Tibial_0314/cases.rtf b/general/datasets/GTEx_log2_Tibial_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Tibial_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Tibial_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Tibial_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Tibial_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Tibial_0314/platform.rtf b/general/datasets/GTEx_log2_Tibial_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Tibial_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Tibial_0314/processing.rtf b/general/datasets/GTEx_log2_Tibial_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Tibial_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Tibial_0314/summary.rtf b/general/datasets/GTEx_log2_Tibial_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Tibial_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Tibial_0314/tissue.rtf b/general/datasets/GTEx_log2_Tibial_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Tibial_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Uterus_0314/cases.rtf b/general/datasets/GTEx_log2_Uterus_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Uterus_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Uterus_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Uterus_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Uterus_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Uterus_0314/platform.rtf b/general/datasets/GTEx_log2_Uterus_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Uterus_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Uterus_0314/processing.rtf b/general/datasets/GTEx_log2_Uterus_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Uterus_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Uterus_0314/summary.rtf b/general/datasets/GTEx_log2_Uterus_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Uterus_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Uterus_0314/tissue.rtf b/general/datasets/GTEx_log2_Uterus_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Uterus_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Vagin_0314/cases.rtf b/general/datasets/GTEx_log2_Vagin_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Vagin_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Vagin_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Vagin_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Vagin_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Vagin_0314/platform.rtf b/general/datasets/GTEx_log2_Vagin_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Vagin_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Vagin_0314/processing.rtf b/general/datasets/GTEx_log2_Vagin_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Vagin_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Vagin_0314/summary.rtf b/general/datasets/GTEx_log2_Vagin_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Vagin_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Vagin_0314/tissue.rtf b/general/datasets/GTEx_log2_Vagin_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Vagin_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_Visce_0314/cases.rtf b/general/datasets/GTEx_log2_Visce_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_Visce_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_Visce_0314/experiment-design.rtf b/general/datasets/GTEx_log2_Visce_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_Visce_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_Visce_0314/platform.rtf b/general/datasets/GTEx_log2_Visce_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_Visce_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_Visce_0314/processing.rtf b/general/datasets/GTEx_log2_Visce_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_Visce_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_Visce_0314/summary.rtf b/general/datasets/GTEx_log2_Visce_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_Visce_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_Visce_0314/tissue.rtf b/general/datasets/GTEx_log2_Visce_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_Visce_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GTEx_log2_WholeB_0314/cases.rtf b/general/datasets/GTEx_log2_WholeB_0314/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GTEx_log2_WholeB_0314/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GTEx_log2_WholeB_0314/experiment-design.rtf b/general/datasets/GTEx_log2_WholeB_0314/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GTEx_log2_WholeB_0314/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GTEx_log2_WholeB_0314/platform.rtf b/general/datasets/GTEx_log2_WholeB_0314/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GTEx_log2_WholeB_0314/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GTEx_log2_WholeB_0314/processing.rtf b/general/datasets/GTEx_log2_WholeB_0314/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GTEx_log2_WholeB_0314/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GTEx_log2_WholeB_0314/summary.rtf b/general/datasets/GTEx_log2_WholeB_0314/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GTEx_log2_WholeB_0314/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GTEx_log2_WholeB_0314/tissue.rtf b/general/datasets/GTEx_log2_WholeB_0314/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GTEx_log2_WholeB_0314/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/Gcb_m2_0505_m/acknowledgment.rtf b/general/datasets/Gcb_m2_0505_m/acknowledgment.rtf
new file mode 100644
index 0000000..9ff420d
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_m/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Genome Explorations, Inc., for the NIAAA as part of an SBIR grant to Dr. Divyen Patel. Mouse colony resources and integration of data into GeneNetwork was carried out by Drs. RW Williams and Lu Lu at UTHSC.
diff --git a/general/datasets/Gcb_m2_0505_m/cases.rtf b/general/datasets/Gcb_m2_0505_m/cases.rtf
new file mode 100644
index 0000000..a843e87
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_m/cases.rtf
@@ -0,0 +1,3 @@
+We use a set of BXD recombinant inbred strains and standard inbred strains. The BXD lines are derived crossed between C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D parental strains have been almost fully sequenced (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems) and data for 1.75 millioin B vs D SNPs are incorporated into WebQTL's genetic maps for the BXDs. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004).
+
+Most BXD animals were generated in-house at the University of Tennessee Health Science Center by Lu Lu and Robert Williams using stock obtained from The Jackson Laboratory between 1999 and 2004. All BXD strains with numbers above 42 are new advanced intecross type BXDs (Peirce et al. 2004) that are current available from UTHSC. Additional cases were provided by Glenn Rosen, John Mountz, and Hui-Chen Hsu. These cases were bred either at The Jackson Laboratory (GR) or at the University of Alabama (JM and HCH).
diff --git a/general/datasets/Gcb_m2_0505_m/notes.rtf b/general/datasets/Gcb_m2_0505_m/notes.rtf
new file mode 100644
index 0000000..67339ea
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_m/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW and YHQ, March 21, 2005. Updated by RWW, March 23, 2005; RWW April 8.
diff --git a/general/datasets/Gcb_m2_0505_m/platform.rtf b/general/datasets/Gcb_m2_0505_m/platform.rtf
new file mode 100644
index 0000000..fdbfe32
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_m/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0: The 430 2.0 array consist of approximately 992936 25-nucleotide probes that collectively estimate the expression of approximately 39,000 transcripts. The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequences as the 430A and 430B series. However, we have found that roughy 75000 probes differ from those on A and B arrays and those on the 430 2.0
diff --git a/general/datasets/Gcb_m2_0505_m/processing.rtf b/general/datasets/Gcb_m2_0505_m/processing.rtf
new file mode 100644
index 0000000..6c56850
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_m/processing.rtf
@@ -0,0 +1,15 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 104 arrays (all three batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: No correction for potential batch effect was attempted.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets included on the microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium March 2005 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Gcb_m2_0505_m/summary.rtf b/general/datasets/Gcb_m2_0505_m/summary.rtf
new file mode 100644
index 0000000..ac3d506
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_m/summary.rtf
@@ -0,0 +1,3 @@
+
+NOT RECOMMENDED: This May 2005 data freeze provides estimates of mRNA expression in adult cerebellum of 40 lines of mice including 28 BXD recombinant inbred strains, C57BL/6J, DBA/2J, and 10 other common inbred strains of mice. Data were generated by Genome Explorations Inc. (Divyen Patel and colleagues). Cerebellar samples were hybridized in small pools (n = 3) to Affymetrix M430 2.0 arrays. This particular data set was processed using the Microarray Suite 5
+
diff --git a/general/datasets/Gcb_m2_0505_m/tissue.rtf b/general/datasets/Gcb_m2_0505_m/tissue.rtf
new file mode 100644
index 0000000..af10195
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_m/tissue.rtf
@@ -0,0 +1,13 @@
+The May 2005 data set consists of a total of 61 array (Affymetrix 430 2.0 arrays) from 40 different genotypes. Each sample consists of whole cerebellum taken from three adult animals of the same age and sex. The M430 2.0 arrays were processed in several batches.
+
+Replication and Sample Balance: We obtained data independent biological sample pools from both sexes for half of the strain, including most of the standard inbred strains (129S1/SvImJ is the exception and is represented by two female-only arrays). Most BXD strains are represented by single pooled samples. You can determine the sex of a sample from the table below or by reviewing the expression of the Ddx3y and Xist RNA signal.
+
+
+
+
+
+Legend: Sex balance of the GE-NIAAA data set can be easily evaluated by analysis of this scatterplot of Ddx3y and Xist. Ddx3y (also called Dby) is a transcript with high expression in males whereas Xist is a transcript with high expression in females. Strains that fall in the upper left quadrant are represented only by a single female sample (except in the case of the 129S1/SvImJ data) whereas strains that fall in the lower right quadrant are represented only a a single male sample.
+
+RNA was extracted at Genome Explorations.
+
+All samples were subsequently processed at the Genome Explorations Inc. by Divyen Patel and colleagues.
diff --git a/general/datasets/Gcb_m2_0505_p/acknowledgment.rtf b/general/datasets/Gcb_m2_0505_p/acknowledgment.rtf
new file mode 100644
index 0000000..9ff420d
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_p/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Genome Explorations, Inc., for the NIAAA as part of an SBIR grant to Dr. Divyen Patel. Mouse colony resources and integration of data into GeneNetwork was carried out by Drs. RW Williams and Lu Lu at UTHSC.
diff --git a/general/datasets/Gcb_m2_0505_p/cases.rtf b/general/datasets/Gcb_m2_0505_p/cases.rtf
new file mode 100644
index 0000000..a843e87
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_p/cases.rtf
@@ -0,0 +1,3 @@
+We use a set of BXD recombinant inbred strains and standard inbred strains. The BXD lines are derived crossed between C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D parental strains have been almost fully sequenced (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems) and data for 1.75 millioin B vs D SNPs are incorporated into WebQTL's genetic maps for the BXDs. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004).
+
+Most BXD animals were generated in-house at the University of Tennessee Health Science Center by Lu Lu and Robert Williams using stock obtained from The Jackson Laboratory between 1999 and 2004. All BXD strains with numbers above 42 are new advanced intecross type BXDs (Peirce et al. 2004) that are current available from UTHSC. Additional cases were provided by Glenn Rosen, John Mountz, and Hui-Chen Hsu. These cases were bred either at The Jackson Laboratory (GR) or at the University of Alabama (JM and HCH).
diff --git a/general/datasets/Gcb_m2_0505_p/notes.rtf b/general/datasets/Gcb_m2_0505_p/notes.rtf
new file mode 100644
index 0000000..67339ea
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_p/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW and YHQ, March 21, 2005. Updated by RWW, March 23, 2005; RWW April 8.
diff --git a/general/datasets/Gcb_m2_0505_p/platform.rtf b/general/datasets/Gcb_m2_0505_p/platform.rtf
new file mode 100644
index 0000000..fdbfe32
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_p/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0: The 430 2.0 array consist of approximately 992936 25-nucleotide probes that collectively estimate the expression of approximately 39,000 transcripts. The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequences as the 430A and 430B series. However, we have found that roughy 75000 probes differ from those on A and B arrays and those on the 430 2.0
diff --git a/general/datasets/Gcb_m2_0505_p/processing.rtf b/general/datasets/Gcb_m2_0505_p/processing.rtf
new file mode 100644
index 0000000..6c56850
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_p/processing.rtf
@@ -0,0 +1,15 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 104 arrays (all three batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: No correction for potential batch effect was attempted.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets included on the microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium March 2005 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Gcb_m2_0505_p/summary.rtf b/general/datasets/Gcb_m2_0505_p/summary.rtf
new file mode 100644
index 0000000..ac3d506
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_p/summary.rtf
@@ -0,0 +1,3 @@
+
+NOT RECOMMENDED: This May 2005 data freeze provides estimates of mRNA expression in adult cerebellum of 40 lines of mice including 28 BXD recombinant inbred strains, C57BL/6J, DBA/2J, and 10 other common inbred strains of mice. Data were generated by Genome Explorations Inc. (Divyen Patel and colleagues). Cerebellar samples were hybridized in small pools (n = 3) to Affymetrix M430 2.0 arrays. This particular data set was processed using the Microarray Suite 5
+
diff --git a/general/datasets/Gcb_m2_0505_p/tissue.rtf b/general/datasets/Gcb_m2_0505_p/tissue.rtf
new file mode 100644
index 0000000..af10195
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_p/tissue.rtf
@@ -0,0 +1,13 @@
+The May 2005 data set consists of a total of 61 array (Affymetrix 430 2.0 arrays) from 40 different genotypes. Each sample consists of whole cerebellum taken from three adult animals of the same age and sex. The M430 2.0 arrays were processed in several batches.
+
+Replication and Sample Balance: We obtained data independent biological sample pools from both sexes for half of the strain, including most of the standard inbred strains (129S1/SvImJ is the exception and is represented by two female-only arrays). Most BXD strains are represented by single pooled samples. You can determine the sex of a sample from the table below or by reviewing the expression of the Ddx3y and Xist RNA signal.
+
+
+
+
+
+Legend: Sex balance of the GE-NIAAA data set can be easily evaluated by analysis of this scatterplot of Ddx3y and Xist. Ddx3y (also called Dby) is a transcript with high expression in males whereas Xist is a transcript with high expression in females. Strains that fall in the upper left quadrant are represented only by a single female sample (except in the case of the 129S1/SvImJ data) whereas strains that fall in the lower right quadrant are represented only a a single male sample.
+
+RNA was extracted at Genome Explorations.
+
+All samples were subsequently processed at the Genome Explorations Inc. by Divyen Patel and colleagues.
diff --git a/general/datasets/Gcb_m2_0505_r/acknowledgment.rtf b/general/datasets/Gcb_m2_0505_r/acknowledgment.rtf
new file mode 100644
index 0000000..9ff420d
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Genome Explorations, Inc., for the NIAAA as part of an SBIR grant to Dr. Divyen Patel. Mouse colony resources and integration of data into GeneNetwork was carried out by Drs. RW Williams and Lu Lu at UTHSC.
diff --git a/general/datasets/Gcb_m2_0505_r/cases.rtf b/general/datasets/Gcb_m2_0505_r/cases.rtf
new file mode 100644
index 0000000..a843e87
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_r/cases.rtf
@@ -0,0 +1,3 @@
+We use a set of BXD recombinant inbred strains and standard inbred strains. The BXD lines are derived crossed between C57BL/6J (B6 or B) and DBA/2J (D2 or D). Both B and D parental strains have been almost fully sequenced (8x coverage for B6 by a public consortium and approximately 1.5x coverage for D by Celera Discovery Systems) and data for 1.75 millioin B vs D SNPs are incorporated into WebQTL's genetic maps for the BXDs. BXD2 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were also produced by Taylor, but they were generated in the 1990s. These strains are all available from The Jackson Laboratory, Bar Harbor, Maine. BXD43 through BXD99 were produced by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004).
+
+Most BXD animals were generated in-house at the University of Tennessee Health Science Center by Lu Lu and Robert Williams using stock obtained from The Jackson Laboratory between 1999 and 2004. All BXD strains with numbers above 42 are new advanced intecross type BXDs (Peirce et al. 2004) that are current available from UTHSC. Additional cases were provided by Glenn Rosen, John Mountz, and Hui-Chen Hsu. These cases were bred either at The Jackson Laboratory (GR) or at the University of Alabama (JM and HCH).
diff --git a/general/datasets/Gcb_m2_0505_r/notes.rtf b/general/datasets/Gcb_m2_0505_r/notes.rtf
new file mode 100644
index 0000000..67339ea
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_r/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW and YHQ, March 21, 2005. Updated by RWW, March 23, 2005; RWW April 8.
diff --git a/general/datasets/Gcb_m2_0505_r/platform.rtf b/general/datasets/Gcb_m2_0505_r/platform.rtf
new file mode 100644
index 0000000..fdbfe32
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_r/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0: The 430 2.0 array consist of approximately 992936 25-nucleotide probes that collectively estimate the expression of approximately 39,000 transcripts. The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequences as the 430A and 430B series. However, we have found that roughy 75000 probes differ from those on A and B arrays and those on the 430 2.0
diff --git a/general/datasets/Gcb_m2_0505_r/processing.rtf b/general/datasets/Gcb_m2_0505_r/processing.rtf
new file mode 100644
index 0000000..6c56850
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_r/processing.rtf
@@ -0,0 +1,15 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization for the log base 2 values for the total set of 104 arrays (all three batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: No correction for potential batch effect was attempted.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replciates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for these variables.
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets included on the microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium March 2005 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Gcb_m2_0505_r/summary.rtf b/general/datasets/Gcb_m2_0505_r/summary.rtf
new file mode 100644
index 0000000..ac3d506
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_r/summary.rtf
@@ -0,0 +1,3 @@
+
+NOT RECOMMENDED: This May 2005 data freeze provides estimates of mRNA expression in adult cerebellum of 40 lines of mice including 28 BXD recombinant inbred strains, C57BL/6J, DBA/2J, and 10 other common inbred strains of mice. Data were generated by Genome Explorations Inc. (Divyen Patel and colleagues). Cerebellar samples were hybridized in small pools (n = 3) to Affymetrix M430 2.0 arrays. This particular data set was processed using the Microarray Suite 5
+
diff --git a/general/datasets/Gcb_m2_0505_r/tissue.rtf b/general/datasets/Gcb_m2_0505_r/tissue.rtf
new file mode 100644
index 0000000..af10195
--- /dev/null
+++ b/general/datasets/Gcb_m2_0505_r/tissue.rtf
@@ -0,0 +1,13 @@
+The May 2005 data set consists of a total of 61 array (Affymetrix 430 2.0 arrays) from 40 different genotypes. Each sample consists of whole cerebellum taken from three adult animals of the same age and sex. The M430 2.0 arrays were processed in several batches.
+
+Replication and Sample Balance: We obtained data independent biological sample pools from both sexes for half of the strain, including most of the standard inbred strains (129S1/SvImJ is the exception and is represented by two female-only arrays). Most BXD strains are represented by single pooled samples. You can determine the sex of a sample from the table below or by reviewing the expression of the Ddx3y and Xist RNA signal.
+
+
+
+
+
+Legend: Sex balance of the GE-NIAAA data set can be easily evaluated by analysis of this scatterplot of Ddx3y and Xist. Ddx3y (also called Dby) is a transcript with high expression in males whereas Xist is a transcript with high expression in females. Strains that fall in the upper left quadrant are represented only by a single female sample (except in the case of the 129S1/SvImJ data) whereas strains that fall in the lower right quadrant are represented only a a single male sample.
+
+RNA was extracted at Genome Explorations.
+
+All samples were subsequently processed at the Genome Explorations Inc. by Divyen Patel and colleagues.
diff --git a/general/datasets/GenEx_BXD_CerebEt_RMA_0213/summary.rtf b/general/datasets/GenEx_BXD_CerebEt_RMA_0213/summary.rtf
deleted file mode 100644
index 335e540..0000000
--- a/general/datasets/GenEx_BXD_CerebEt_RMA_0213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 166, Name: GenEx BXD Sal Cerebellum Affy M430 2.0 (Feb13)
\ No newline at end of file
diff --git a/general/datasets/GenEx_BXD_CerebEt_RMA_M_0213/summary.rtf b/general/datasets/GenEx_BXD_CerebEt_RMA_M_0213/summary.rtf
deleted file mode 100644
index 335e540..0000000
--- a/general/datasets/GenEx_BXD_CerebEt_RMA_M_0213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 166, Name: GenEx BXD Sal Cerebellum Affy M430 2.0 (Feb13)
\ No newline at end of file
diff --git a/general/datasets/GenEx_BXD_CerebSal_RMA_0213/summary.rtf b/general/datasets/GenEx_BXD_CerebSal_RMA_0213/summary.rtf
deleted file mode 100644
index 335e540..0000000
--- a/general/datasets/GenEx_BXD_CerebSal_RMA_0213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 166, Name: GenEx BXD Sal Cerebellum Affy M430 2.0 (Feb13)
\ No newline at end of file
diff --git a/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/cases.rtf b/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/cases.rtf
deleted file mode 100644
index 3453126..0000000
--- a/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
-
-The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
-
-For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/experiment-design.rtf b/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/experiment-design.rtf
deleted file mode 100644
index 5e876e0..0000000
--- a/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/platform.rtf b/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/platform.rtf
deleted file mode 100644
index f276bf8..0000000
--- a/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/platform.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Expression
-
-RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/processing.rtf b/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/processing.rtf
deleted file mode 100644
index 6635893..0000000
--- a/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/processing.rtf
+++ /dev/null
@@ -1,102 +0,0 @@
-Analysis Methods
-
-Preprocessing
-
-RNA-seq
-
-RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
-
-See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
-
-Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
-
-Genotyping
-
-DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
-
-Expression Quantification
-
-Gene/Transcript Model
-
-Gencode Version 12
-Contig names modified to match the reference genome used for alignment
-Procedure for collapsing transcript model into gene model
-
-Primary source: gencode.v12
-List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
-Create a separate bin for other types of transcripts and process them independently.
-Merge overlapping intervals.
-Discard intervals associated with multiple genes.
-Map intervals back to gene identifiers and output in GTF format.
-Quantification
-
-For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
-
-Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
-Reads must have proper pairs.
-Alignment distance must be <=6.
-Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
-Exon
-
-For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
-
-Transcript
-
-Transcript-level quantification is provided by Flux Capacitor.
-
-eQTL Analysis
-
-QC and Sample Exclusion Process
-
-D statistic outliers are removed.
-Gender-specific expression outliers are removed.
-Samples with less than 10 million mapped reads are removed.
-In the case of replicates, the samples with the greater number of reads are chosen.
-Covariates
-
-3 Genotyping PCs.
-15 Peer factors:
-
-
-The input to PEER are the post-normalization expression values described below.
-Gender.
-Expression
-
-RPKM data are used as produced by RNA-SeQC.
-Filter on >=10 individuals having >0.1RPKM.
-Log and quantile normalize the expression values across all samples.
-Outlier correction: for each gene, rank values across samples then map to a standard normal.
-Genotypes
-
-Imputation-based genotypes:
-Call Rate Threshold 95%.
-Info score Threshold 0.4.
-Minor Allele Frequency >= 5%.
-Sex chromosomes have been excluded excluded.
-Matrix eQTL Parameters
-
-Produced for radius +-1mb from TSS.
-P value threshold set to 1 to emit all p-values.
-Storey FDR
-
-The Storey q-value method was applied using the public R package with default values.
-eQTLs were filtered for an FDR <=5%.
-Tissues
-
-There are 9 Tissues that have sufficient sample numbers (n > 80).
-
-Adipose_Subcutaneous
-Artery_Tibial
-Heart_Left_Ventricle
-Lung
-Muscle_Skeletal
-Nerve_Tibial
-Skin_Sun_Exposed_Lower_leg
-Thyroid
-Whole_Blood
-
-Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
-
-Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
-
-See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/summary.rtf b/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/summary.rtf
deleted file mode 100644
index dff008b..0000000
--- a/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
-
-WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/tissue.rtf b/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/tissue.rtf
deleted file mode 100644
index 7e60b80..0000000
--- a/general/datasets/GenEx_BXD_CerebSal_RMA_F_0213/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-GTEx explore all tissues:
-
-
diff --git a/general/datasets/GenEx_BXD_CerebSal_RMA_M_0213/summary.rtf b/general/datasets/GenEx_BXD_CerebSal_RMA_M_0213/summary.rtf
deleted file mode 100644
index 335e540..0000000
--- a/general/datasets/GenEx_BXD_CerebSal_RMA_M_0213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 166, Name: GenEx BXD Sal Cerebellum Affy M430 2.0 (Feb13)
\ No newline at end of file
diff --git a/general/datasets/Genex_bxd_cerebet_rma_0213/summary.rtf b/general/datasets/Genex_bxd_cerebet_rma_0213/summary.rtf
new file mode 100644
index 0000000..335e540
--- /dev/null
+++ b/general/datasets/Genex_bxd_cerebet_rma_0213/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 166, Name: GenEx BXD Sal Cerebellum Affy M430 2.0 (Feb13)
\ No newline at end of file
diff --git a/general/datasets/Genex_bxd_cerebet_rma_m_0213/summary.rtf b/general/datasets/Genex_bxd_cerebet_rma_m_0213/summary.rtf
new file mode 100644
index 0000000..335e540
--- /dev/null
+++ b/general/datasets/Genex_bxd_cerebet_rma_m_0213/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 166, Name: GenEx BXD Sal Cerebellum Affy M430 2.0 (Feb13)
\ No newline at end of file
diff --git a/general/datasets/Genex_bxd_cerebsal_rma_0213/summary.rtf b/general/datasets/Genex_bxd_cerebsal_rma_0213/summary.rtf
new file mode 100644
index 0000000..335e540
--- /dev/null
+++ b/general/datasets/Genex_bxd_cerebsal_rma_0213/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 166, Name: GenEx BXD Sal Cerebellum Affy M430 2.0 (Feb13)
\ No newline at end of file
diff --git a/general/datasets/Genex_bxd_cerebsal_rma_f_0213/cases.rtf b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Genex_bxd_cerebsal_rma_f_0213/contributors.rtf b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Genex_bxd_cerebsal_rma_f_0213/experiment-design.rtf b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Genex_bxd_cerebsal_rma_f_0213/platform.rtf b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Genex_bxd_cerebsal_rma_f_0213/processing.rtf b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Genex_bxd_cerebsal_rma_f_0213/summary.rtf b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Genex_bxd_cerebsal_rma_f_0213/tissue.rtf b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Genex_bxd_cerebsal_rma_f_0213/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Genex_bxd_cerebsal_rma_m_0213/summary.rtf b/general/datasets/Genex_bxd_cerebsal_rma_m_0213/summary.rtf
new file mode 100644
index 0000000..335e540
--- /dev/null
+++ b/general/datasets/Genex_bxd_cerebsal_rma_m_0213/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 166, Name: GenEx BXD Sal Cerebellum Affy M430 2.0 (Feb13)
\ No newline at end of file
diff --git a/general/datasets/Genex_bxd_liveret_m5_0912/notes.rtf b/general/datasets/Genex_bxd_liveret_m5_0912/notes.rtf
new file mode 100644
index 0000000..3c8d261
--- /dev/null
+++ b/general/datasets/Genex_bxd_liveret_m5_0912/notes.rtf
@@ -0,0 +1,3 @@
+A total of 239 probe sets have LRS >46. Maximum LRS of 124.5. Perfect concordance between phenotype of probe set and genotype for St3gal4 on Chr 9 at 34.9 Mb.
+
+Xist expression is uniformly high in BXD55 and BXD70 using probe set 1427262_at, but this is probably due to ethanol effect. Note that Eif2s3y indicates all strains have balanced male and female data.
diff --git a/general/datasets/Genex_bxd_liveret_m5_0912/summary.rtf b/general/datasets/Genex_bxd_liveret_m5_0912/summary.rtf
new file mode 100644
index 0000000..60d23d4
--- /dev/null
+++ b/general/datasets/Genex_bxd_liveret_m5_0912/summary.rtf
@@ -0,0 +1,29 @@
+These data generated by Dr. Robert Rooney, Kristin Hamre, Divyen Patel, and colleagues at Genome Explorations as part of an SBIR from NIAAA (2010-2011).
+
+Data entered by Arthur Centeno, Jan and Feb 2011.
+
+Data error checked by Robert W. Williams, Jan-May 2011.
+
+eQTLs with LOD > 10
+
+
+
+
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Females: 303
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Males: 279
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Both Sexes: 493
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Females: 320
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Males: 207
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 513
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Females: 189
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Males: 97
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 327
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Females: 274
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Males: 175
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 444
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Females: 139
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Males: 73
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 230
+
+
+
diff --git a/general/datasets/Genex_bxd_liveret_m5f_0912/notes.rtf b/general/datasets/Genex_bxd_liveret_m5f_0912/notes.rtf
new file mode 100644
index 0000000..3c8d261
--- /dev/null
+++ b/general/datasets/Genex_bxd_liveret_m5f_0912/notes.rtf
@@ -0,0 +1,3 @@
+A total of 239 probe sets have LRS >46. Maximum LRS of 124.5. Perfect concordance between phenotype of probe set and genotype for St3gal4 on Chr 9 at 34.9 Mb.
+
+Xist expression is uniformly high in BXD55 and BXD70 using probe set 1427262_at, but this is probably due to ethanol effect. Note that Eif2s3y indicates all strains have balanced male and female data.
diff --git a/general/datasets/Genex_bxd_liveret_m5f_0912/summary.rtf b/general/datasets/Genex_bxd_liveret_m5f_0912/summary.rtf
new file mode 100644
index 0000000..60d23d4
--- /dev/null
+++ b/general/datasets/Genex_bxd_liveret_m5f_0912/summary.rtf
@@ -0,0 +1,29 @@
+These data generated by Dr. Robert Rooney, Kristin Hamre, Divyen Patel, and colleagues at Genome Explorations as part of an SBIR from NIAAA (2010-2011).
+
+Data entered by Arthur Centeno, Jan and Feb 2011.
+
+Data error checked by Robert W. Williams, Jan-May 2011.
+
+eQTLs with LOD > 10
+
+
+
+
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Females: 303
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Males: 279
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Both Sexes: 493
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Females: 320
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Males: 207
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 513
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Females: 189
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Males: 97
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 327
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Females: 274
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Males: 175
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 444
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Females: 139
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Males: 73
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 230
+
+
+
diff --git a/general/datasets/Genex_bxd_liveret_m5m_0912/notes.rtf b/general/datasets/Genex_bxd_liveret_m5m_0912/notes.rtf
new file mode 100644
index 0000000..3c8d261
--- /dev/null
+++ b/general/datasets/Genex_bxd_liveret_m5m_0912/notes.rtf
@@ -0,0 +1,3 @@
+A total of 239 probe sets have LRS >46. Maximum LRS of 124.5. Perfect concordance between phenotype of probe set and genotype for St3gal4 on Chr 9 at 34.9 Mb.
+
+Xist expression is uniformly high in BXD55 and BXD70 using probe set 1427262_at, but this is probably due to ethanol effect. Note that Eif2s3y indicates all strains have balanced male and female data.
diff --git a/general/datasets/Genex_bxd_liveret_m5m_0912/summary.rtf b/general/datasets/Genex_bxd_liveret_m5m_0912/summary.rtf
new file mode 100644
index 0000000..60d23d4
--- /dev/null
+++ b/general/datasets/Genex_bxd_liveret_m5m_0912/summary.rtf
@@ -0,0 +1,29 @@
+These data generated by Dr. Robert Rooney, Kristin Hamre, Divyen Patel, and colleagues at Genome Explorations as part of an SBIR from NIAAA (2010-2011).
+
+Data entered by Arthur Centeno, Jan and Feb 2011.
+
+Data error checked by Robert W. Williams, Jan-May 2011.
+
+eQTLs with LOD > 10
+
+
+
+
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Females: 303
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Males: 279
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Both Sexes: 493
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Females: 320
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Males: 207
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 513
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Females: 189
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Males: 97
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 327
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Females: 274
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Males: 175
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 444
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Females: 139
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Males: 73
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 230
+
+
+
diff --git a/general/datasets/Genex_bxd_liveret_rma_0211/notes.rtf b/general/datasets/Genex_bxd_liveret_rma_0211/notes.rtf
new file mode 100644
index 0000000..3c8d261
--- /dev/null
+++ b/general/datasets/Genex_bxd_liveret_rma_0211/notes.rtf
@@ -0,0 +1,3 @@
+A total of 239 probe sets have LRS >46. Maximum LRS of 124.5. Perfect concordance between phenotype of probe set and genotype for St3gal4 on Chr 9 at 34.9 Mb.
+
+Xist expression is uniformly high in BXD55 and BXD70 using probe set 1427262_at, but this is probably due to ethanol effect. Note that Eif2s3y indicates all strains have balanced male and female data.
diff --git a/general/datasets/Genex_bxd_liveret_rma_0211/summary.rtf b/general/datasets/Genex_bxd_liveret_rma_0211/summary.rtf
new file mode 100644
index 0000000..60d23d4
--- /dev/null
+++ b/general/datasets/Genex_bxd_liveret_rma_0211/summary.rtf
@@ -0,0 +1,29 @@
+These data generated by Dr. Robert Rooney, Kristin Hamre, Divyen Patel, and colleagues at Genome Explorations as part of an SBIR from NIAAA (2010-2011).
+
+Data entered by Arthur Centeno, Jan and Feb 2011.
+
+Data error checked by Robert W. Williams, Jan-May 2011.
+
+eQTLs with LOD > 10
+
+
+
+
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Females: 303
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Males: 279
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Both Sexes: 493
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Females: 320
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Males: 207
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 513
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Females: 189
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Males: 97
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 327
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Females: 274
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Males: 175
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 444
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Females: 139
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Males: 73
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 230
+
+
+
diff --git a/general/datasets/Genex_bxd_liveret_rma_f_0211/notes.rtf b/general/datasets/Genex_bxd_liveret_rma_f_0211/notes.rtf
new file mode 100644
index 0000000..3c8d261
--- /dev/null
+++ b/general/datasets/Genex_bxd_liveret_rma_f_0211/notes.rtf
@@ -0,0 +1,3 @@
+A total of 239 probe sets have LRS >46. Maximum LRS of 124.5. Perfect concordance between phenotype of probe set and genotype for St3gal4 on Chr 9 at 34.9 Mb.
+
+Xist expression is uniformly high in BXD55 and BXD70 using probe set 1427262_at, but this is probably due to ethanol effect. Note that Eif2s3y indicates all strains have balanced male and female data.
diff --git a/general/datasets/Genex_bxd_liveret_rma_f_0211/summary.rtf b/general/datasets/Genex_bxd_liveret_rma_f_0211/summary.rtf
new file mode 100644
index 0000000..60d23d4
--- /dev/null
+++ b/general/datasets/Genex_bxd_liveret_rma_f_0211/summary.rtf
@@ -0,0 +1,29 @@
+These data generated by Dr. Robert Rooney, Kristin Hamre, Divyen Patel, and colleagues at Genome Explorations as part of an SBIR from NIAAA (2010-2011).
+
+Data entered by Arthur Centeno, Jan and Feb 2011.
+
+Data error checked by Robert W. Williams, Jan-May 2011.
+
+eQTLs with LOD > 10
+
+
+
+
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Females: 303
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Males: 279
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Both Sexes: 493
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Females: 320
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Males: 207
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 513
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Females: 189
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Males: 97
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 327
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Females: 274
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Males: 175
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 444
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Females: 139
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Males: 73
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 230
+
+
+
diff --git a/general/datasets/Genex_bxd_liveret_rma_m_0211/notes.rtf b/general/datasets/Genex_bxd_liveret_rma_m_0211/notes.rtf
new file mode 100644
index 0000000..3c8d261
--- /dev/null
+++ b/general/datasets/Genex_bxd_liveret_rma_m_0211/notes.rtf
@@ -0,0 +1,3 @@
+A total of 239 probe sets have LRS >46. Maximum LRS of 124.5. Perfect concordance between phenotype of probe set and genotype for St3gal4 on Chr 9 at 34.9 Mb.
+
+Xist expression is uniformly high in BXD55 and BXD70 using probe set 1427262_at, but this is probably due to ethanol effect. Note that Eif2s3y indicates all strains have balanced male and female data.
diff --git a/general/datasets/Genex_bxd_liveret_rma_m_0211/summary.rtf b/general/datasets/Genex_bxd_liveret_rma_m_0211/summary.rtf
new file mode 100644
index 0000000..60d23d4
--- /dev/null
+++ b/general/datasets/Genex_bxd_liveret_rma_m_0211/summary.rtf
@@ -0,0 +1,29 @@
+These data generated by Dr. Robert Rooney, Kristin Hamre, Divyen Patel, and colleagues at Genome Explorations as part of an SBIR from NIAAA (2010-2011).
+
+Data entered by Arthur Centeno, Jan and Feb 2011.
+
+Data error checked by Robert W. Williams, Jan-May 2011.
+
+eQTLs with LOD > 10
+
+
+
+
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Females: 303
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Males: 279
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Both Sexes: 493
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Females: 320
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Males: 207
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 513
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Females: 189
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Males: 97
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 327
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Females: 274
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Males: 175
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 444
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Females: 139
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Males: 73
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 230
+
+
+
diff --git a/general/datasets/Genex_bxd_liversal_rma_0211/notes.rtf b/general/datasets/Genex_bxd_liversal_rma_0211/notes.rtf
new file mode 100644
index 0000000..3c8d261
--- /dev/null
+++ b/general/datasets/Genex_bxd_liversal_rma_0211/notes.rtf
@@ -0,0 +1,3 @@
+A total of 239 probe sets have LRS >46. Maximum LRS of 124.5. Perfect concordance between phenotype of probe set and genotype for St3gal4 on Chr 9 at 34.9 Mb.
+
+Xist expression is uniformly high in BXD55 and BXD70 using probe set 1427262_at, but this is probably due to ethanol effect. Note that Eif2s3y indicates all strains have balanced male and female data.
diff --git a/general/datasets/Genex_bxd_liversal_rma_0211/summary.rtf b/general/datasets/Genex_bxd_liversal_rma_0211/summary.rtf
new file mode 100644
index 0000000..60d23d4
--- /dev/null
+++ b/general/datasets/Genex_bxd_liversal_rma_0211/summary.rtf
@@ -0,0 +1,29 @@
+These data generated by Dr. Robert Rooney, Kristin Hamre, Divyen Patel, and colleagues at Genome Explorations as part of an SBIR from NIAAA (2010-2011).
+
+Data entered by Arthur Centeno, Jan and Feb 2011.
+
+Data error checked by Robert W. Williams, Jan-May 2011.
+
+eQTLs with LOD > 10
+
+
+
+
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Females: 303
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Males: 279
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Both Sexes: 493
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Females: 320
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Males: 207
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 513
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Females: 189
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Males: 97
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 327
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Females: 274
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Males: 175
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 444
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Females: 139
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Males: 73
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 230
+
+
+
diff --git a/general/datasets/Genex_bxd_liversal_rma_f_0211/notes.rtf b/general/datasets/Genex_bxd_liversal_rma_f_0211/notes.rtf
new file mode 100644
index 0000000..3c8d261
--- /dev/null
+++ b/general/datasets/Genex_bxd_liversal_rma_f_0211/notes.rtf
@@ -0,0 +1,3 @@
+A total of 239 probe sets have LRS >46. Maximum LRS of 124.5. Perfect concordance between phenotype of probe set and genotype for St3gal4 on Chr 9 at 34.9 Mb.
+
+Xist expression is uniformly high in BXD55 and BXD70 using probe set 1427262_at, but this is probably due to ethanol effect. Note that Eif2s3y indicates all strains have balanced male and female data.
diff --git a/general/datasets/Genex_bxd_liversal_rma_f_0211/summary.rtf b/general/datasets/Genex_bxd_liversal_rma_f_0211/summary.rtf
new file mode 100644
index 0000000..60d23d4
--- /dev/null
+++ b/general/datasets/Genex_bxd_liversal_rma_f_0211/summary.rtf
@@ -0,0 +1,29 @@
+These data generated by Dr. Robert Rooney, Kristin Hamre, Divyen Patel, and colleagues at Genome Explorations as part of an SBIR from NIAAA (2010-2011).
+
+Data entered by Arthur Centeno, Jan and Feb 2011.
+
+Data error checked by Robert W. Williams, Jan-May 2011.
+
+eQTLs with LOD > 10
+
+
+
+
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Females: 303
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Males: 279
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Both Sexes: 493
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Females: 320
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Males: 207
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 513
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Females: 189
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Males: 97
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 327
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Females: 274
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Males: 175
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 444
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Females: 139
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Males: 73
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 230
+
+
+
diff --git a/general/datasets/Genex_bxd_liversal_rma_m_0211/notes.rtf b/general/datasets/Genex_bxd_liversal_rma_m_0211/notes.rtf
new file mode 100644
index 0000000..3c8d261
--- /dev/null
+++ b/general/datasets/Genex_bxd_liversal_rma_m_0211/notes.rtf
@@ -0,0 +1,3 @@
+A total of 239 probe sets have LRS >46. Maximum LRS of 124.5. Perfect concordance between phenotype of probe set and genotype for St3gal4 on Chr 9 at 34.9 Mb.
+
+Xist expression is uniformly high in BXD55 and BXD70 using probe set 1427262_at, but this is probably due to ethanol effect. Note that Eif2s3y indicates all strains have balanced male and female data.
diff --git a/general/datasets/Genex_bxd_liversal_rma_m_0211/summary.rtf b/general/datasets/Genex_bxd_liversal_rma_m_0211/summary.rtf
new file mode 100644
index 0000000..60d23d4
--- /dev/null
+++ b/general/datasets/Genex_bxd_liversal_rma_m_0211/summary.rtf
@@ -0,0 +1,29 @@
+These data generated by Dr. Robert Rooney, Kristin Hamre, Divyen Patel, and colleagues at Genome Explorations as part of an SBIR from NIAAA (2010-2011).
+
+Data entered by Arthur Centeno, Jan and Feb 2011.
+
+Data error checked by Robert W. Williams, Jan-May 2011.
+
+eQTLs with LOD > 10
+
+
+
+
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Females: 303
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Males: 279
+ - UNC Agilent G4121A Liver LOWESS Stanford (Jan06) Both Sexes: 493
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Females: 320
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Males: 207
+ - GenEx BXD Sal Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 513
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Females: 189
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Males: 97
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Feb11) RMA Both Sexes: 327
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Females: 274
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Males: 175
+ - GenEx BXD Sal Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 444
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Females: 139
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Males: 73
+ - GenEx BXD EtOH Liver Affy M430 2.0 (Jan11) RMA Both Sexes: 230
+
+
+
diff --git a/general/datasets/Gitrmetpublish/summary.rtf b/general/datasets/Gitrmetpublish/summary.rtf
new file mode 100644
index 0000000..3847a3b
--- /dev/null
+++ b/general/datasets/Gitrmetpublish/summary.rtf
@@ -0,0 +1 @@
+GI Tract Metagenome Phenotypes
diff --git a/general/datasets/Gn10/acknowledgment.rtf b/general/datasets/Gn10/acknowledgment.rtf
new file mode 100644
index 0000000..5098d32
--- /dev/null
+++ b/general/datasets/Gn10/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant and from funds from NEI grant to Dr. Eldon Geisert (R01EY017841), an NEI Vision Core grant (EY14080) and an Unrestricted Grant from Research To Prevent Blindness.
+
+We thank Dr. Ted Choi, Chief Scientific Director of Predictive Biology, Inc. (past director of molecular genetics at Deltagen Inc.) for providing us with eye samples from several interesting DeltaGen knockouts.
diff --git a/general/datasets/Gn10/cases.rtf b/general/datasets/Gn10/cases.rtf
new file mode 100644
index 0000000..552d4a5
--- /dev/null
+++ b/general/datasets/Gn10/cases.rtf
@@ -0,0 +1,57 @@
+This is the complete and final HEIMED data set. HEIMED consists of expression data for 103 genetically defined lines of mice with standard errors of the mean. Almost all animals are young adults between 50 and 80 days of age (Table 1, maximum age is 123 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, reciprocal F1s between C57BL/6J and DBA/2J, and several mutant and knockout lines. We have combined all common strains, F1 hybrids, and mutants into a group called the Mouse Diversity Panel (MDP). Four lines, namely, C57BL/6J (B6), DBA/2J (D2), and the pair of B6D2F1 and D2B6F1 hybrids are common to both the MDP and the BXD set. This is a breakdown of cases that are part of HEIMED:
+
+
+ - 68 BXD strains. The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. Only one of these strains, BXD24 (know also known as BXD24b), has retinal degeneration (a spontaneous mutation). The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA.
+ - 35 MDP lines, including 26 inbred strains representing closely related substrains (e.g, BALB/cJ and BALB/cByJ), many of the most widely used common Mus musculus domesticus inbred strains (e.g., C57BL/6J and 129S1/SvImJ), inbred but wild-derived representatives of common subspecies (Mus musculus domesticus, e.g, WSB/EiJ; M. musculus musculus, e.g., CZECHII/EiJ; M. musculus molossinus, e.g., MOLF/EiJ; M. musculus castaneus, e.g., CAST/EiJ); and even one different species of mouse (Mus spicilegus, PANCEVO/EiJ). The MDP also includes the reciprocal F1 hybrids (B6D2F1 and D2B6F1) and the following 6 KO lines and the Nyx-nob mutant:
+ - 6 knockouts (KO), including a KO of Rpe65, and 5 DeltaGen Inc. knockout lines provided by Dr. Ted Choi. These KO lines have had a bacterial lacZ construct inserted into the gene. The endogenous promoter drives expression of beta-galactosidase. RT-PCR analysis detects a gene transcript in most tissues. The following KOs from DeltaGen were studied: Gabra1, Gabbr1, Gnb1, Gpr19, and Clcn3. We also included one spontaneous mutant of the nyctalopin (Nyx no b wave "nob") gene (Pardue et al., 1998) that is on a BALB/cByJ background.
+
+
+Rod photoreceptor degeneration in inbred mice: Six strains of mice included in HEIMED suffer from severe loss of photoreceptors (mainly rods) and have the equivalent of night blindness in human patients. The death of photoreceptors in these strains occurs by one to two months of age and is often caused by the retinal degeneration 1 (rd1) mutant allele in the rod cyclic-GMP phosphodiesterase 6 beta subunit gene (Pde6b). The following strains are known to have photoreceptor degeneration: C3H/HeJ, FVB/NJ, MOLF/EiJ, SJL/J and BXD24/TyJ. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEIMED data set.
+
+As expected (Dickerson LW et al., 2002) and as judged from the absence of rhodopsin expression, one of the DeltaGen KO lines (chloride ion channel 3, Clcn3) also has retinal degeneration: B6129P2F2N1-Clcn3. Degeneration in this strain is likely to include all rods and all cones. The cone defect is obvious from the decrease in expression of Gnat2, a gene associated with cones and achromatopsia in mice and humans.
+
+Lines of mice were selected using the following criteria:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - representation of a fairly wide variety of different subspecies of Mus
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Tel Aviv/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - interesting mutations or knockouts affecting genes with high expression in the eye
+ - general availability from The Jackson Laboratory. The only exception are the DeltaGen KO mice.
+
+
+We have included all eight parents of the Collaborative Cross (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/LtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ) in the MDP. Fourteen MDP strains have been partially sequenced by Perlegen for the NIEHS, including including 129S1/SvImJ, A/J, AKR/J, BALB/cByJ, C3H/HeJ, CAST/EiJ, DBA/2J, FVB/NJ, KK/HlJ, MOLF/EiJ, NOD/LtJ, NZW/LacJ, PWD/PhJ, and WSB/EiJ (see the GeneNetwork SNP Browser for data, details, and see Perlegen's excellent data resources and browser).
+
+
+ - 129S1/SvImJ : Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene. It is also a cone photoreceptor function loss 3 mutant (Cpfl3 allele) of the Gnat2 gene that is a model for achromatopsia (JAX Stock Number: 002448)
+ - A/J: Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase (Tyr c allele) albino mutant. This strain is particularly sensitive to light-induced photoreceptor loss (Danciger et al., 2007). (JAX Stock Number: 000646)
+ - BALB/cByJ: Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project old group A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Small brain, not aggressive (JAX Stock Number: 001026)
+ - BALB/cJ: Phenome Project A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Large brain and aggressive (JAX Stock Number: 000651)
+ - BXSB/MpJ: A white-bellied agouti strains with interesting autoimmune disease restricted to males that is associated with a mutation in the Yaa gene that causes glomerulonephritis, a dramatic increase in number of peripheral monocytes, and pre-B-cell deficiency (JAX Stock Number: 000740)
+ - C3H/HeJ: The Heston (He) substrain with a wildtype agouti (A allele) coat color. Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project old group A list. Important to note for this eye expression dataset, C3H/HeJ is a Pdeb6 rd1 mutant with near total photoreceptor loss at as early as postnatal day 30. Also a Tlr4 mutant that is endotoxin resistant. (JAX Stock Number: 000659)
+ - C57BL/6J: Sequenced by NIH/NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list. Single most widely used inbred strain of mouse. (JAX Stock Number: 000664)
+ - C57BLKS/J: Black Kaliss strain (non-agouti a allele) derived from C57BL/6J, but genetically contaminated at some point mainly with DBA/2J and then reinbred. Now at the Jackson Laboratory. (JAX Stock Number: 000662)
+ - CAST/EiJ: A wild-derived inbred Mus musculus castaneus strain. Samples of this subspecies were captured in Southeast Asia. One of three wild-derived strains in the Collaborative Cross sequenced by NIEHS; Phenome Project A list. CAST/Ei and CAST/EiJ are the same strain. The addition of the "J" is trivial and was added when stock were transferred from Dr. Eicher's lab to the Jackson Laboratory production facility in about 2004. (JAX Stock Number: 000928)
+ - CBA/CaJ: Agouti strain from the Jackson Laboratory. Wildtype pigment genes. (JAX Stock Number: 000654)
+ - CZECHII/EiJ: Czech 2 is a wild-derived inbred strain M. musculus musculus strain. Samples of this subspecies were caught in the Czech Republic and inbred at the Jackson Laboratory by Eva Eicher. White-bellied agouti. (JAX Stock Number: 001144).
+ - DBA/2J: The dilute, brown, agouti (dba) strain is the oldest inbred strain of mouse. Inbreeding was started in 1909 by Little. A tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. A myosin 5a (Myo5a d) dilute allele mutant. Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project old A group list. (JAX Stock Number: 000671)
+ - FVB/NJ: Friend's leukemia virus B (FVB) strain. Sequenced by Perlegen/NIEHS and Celera. Tyr c locus albino and a Pdeb6 rd1 mutant derived from Swiss mice at NIH. This has been the most common strain used to make transgenic mice due to large and easily injected oocytes; Phenome Project A list (JAX Stock Number: 001800).
+ - KK/HlJ: K Kondo's (KK) Kasukabe strain is a homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. Males have a form of type 2 diabetes. Sequenced by Perlegen/NIEHS. (JAX Stock Number: 002106)
+ - LG/J: Large (LG) strain. Paternal parent of the Large-by-Small set of RI strains made by James Cheverud and colleagues (the LGXSM panel, not to be confused with the LongXShort or LXS panel). A Tyr c locus albino strain. (JAX Stock Number: 000675)
+ - LP/J: White-bellied agouit strain with a piebald mutation in the endothelin receptor type B Ednrb gene from at the Jackson Laboratory. Some reduction in melanocytes in choroid of eye due to neural creast migration abnormalities. (JAX Stock Number: 000676)
+ - MOLF/EiJ: A wild-derived inbred strain derived from M. musculus molossinus samples camputered in Fukuoka, Japan. This strain has the retinal degeneration rd1 allele in Pde6b. There appears to have been some genetic contamination of this strain with conventional inbred strains in the past several decades (F. Pardo, personal communication to RWW, August 2006). However, the strain is currently fully inbred. (JAX Stock Number: 000550)
+ - NOD/LtJ: Non-obese diabetic strain, originally from M. Hattori in Kyoto, Japan. This is the Edward Leiter (Lt) substrain from the Jackson Laboratory. Collaborative Cross strain sequenced by NIEHS; Phenome Project B list. Homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. (JAX Stock Number: 001976)
+ - NZO/HlLtJ: New Zealand Obese strain. This is a severely obese and hypertensive strain. Males often develop a type 2 diabetes. Collaborative Cross strain. Agouti coat color. (JAX Stock Number: 002105)
+ - NZB/BlNJ: New Zealand Black inbred strain from Bielschowsky (BL, substrain is "B lowercase L N", not "BiN") now maintained at the Jackson Laboratory. (JAX Stock Number: 000648)
+ - NZW/LacJ: New Zealand White strain from the Laboratory Animal Center (Carshalton, UK), now maintained at the Jackson Laboratory. Carries the Tyr c locus albino mutation, the pink-eye dilution mutation in the Oca2 or p locus, and the brown allele at Tyrp1. (JAX Stock Number: 001058)
+ - PANCEVO/EiJ: PANCEVO/EiJ is a wild-derived inbred strain from the Mus spicilegus samples caught in the Pancevo, Serbia. This species of mouse is also known as the Steppe mouse (taxon identifier 10103). M. spicilegus is a colonial mound-building species. No known ocular or retina mutations, but the expression level of Gnat2 is low in this strain, either due to a 3' UTR length variant or possible achromatosia (cone degeneration) (JAX Stock Number: 001384)
+ - PWD/PhJ: A wild-derived Mus musculus musculus agouti strain inbred from samples caught near Prague, Czech Republic. Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues. (JAX Stock Number: 004660)
+ - PWK/PhJ: A wild-derived Mus musculus musculus inbred strain from samples caught near Lhotka, Czech Republic. Collaborative Cross strain; Phenome Project D list. (JAX Stock Number: 003715)
+ - SJL/J: Swiss Webster inbred strain from Jim Lambert's lab at the Jackson Laboratory. This strain has the retinal degeneration rd1 allele in Pde6b. It also carries both the Tyr c albino mutation and the pink-eye dilution mutation in the Oca2 or p locus. Highly aggressive males. (JAX Stock Number: 000686)
+ - WSB/EiJ: Watkin Star line B (or "wild son-of-a-bitch") is a wild-derived Mus musculus domesticus inbred strain from samples caught in Maryland, USA. A Collaborative Cross strain sequenced by NIEHS; Phenome Project C list (JAX Stock Number: 001145)
+ - B6D2F1 and D2B6F1 (also listed as BDF1 and DBF1 in some graphs and tables): F1 hybrids generated by crossing C57BL/6J with DBA/2J. These black reciprocal F1 can be used to detect dominance effects. Comparison of the two reciprocal F1s can be used to detect parental origin (imprinting) effects. The D2B6F1 animals are currently available from the Jackson Laboratory as a special order.) (JAX Stock Number for B6D2F1 hybrids obtained from the Jackson Laboratory, aka B6D2F1/J 100006)
+
+
+Most of the common inbred strains harbor mutations in genes the control pigmentation (Silvers, 2008 and material above in this INFO file). These gene include the albino and chinchilla alleles of the tyrosinase gene (Tyr, or human OCA1), the brown allele of the tyrosinase related protein 1 (Tyrp1), the pink-eye dilution allele of Oca2 (probe set 1418211), the non-agouti (black) and white-bellied alleles of the agouti signaling protein Asip, the steel allele of Kitlg, the dilute allele of Myo5a (probe set 1419754), and the piebald allele of Ednrb. In some of these cases, effects of the mutation are easily detected at the transcript level (Tyrp1, Oca2, and Myo5a), but in the other cases (Tyr, Asip, Ednrb, and Kitlg), mutations do not leave a strong imprint on expression.
diff --git a/general/datasets/Gn10/citation.rtf b/general/datasets/Gn10/citation.rtf
new file mode 100644
index 0000000..ddd98e4
--- /dev/null
+++ b/general/datasets/Gn10/citation.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams. Gene expression landscape of the mammalian eye: A global survey and database of mRNAs of 103 varieties of mice. Molecular Vision 2009; in press.
diff --git a/general/datasets/Gn10/contributors.rtf b/general/datasets/Gn10/contributors.rtf
new file mode 100644
index 0000000..d155833
--- /dev/null
+++ b/general/datasets/Gn10/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Xusheng Wang, Weikuan Gu, Yan Jiao, Robert W. Williams
diff --git a/general/datasets/Gn10/experiment-design.rtf b/general/datasets/Gn10/experiment-design.rtf
new file mode 100644
index 0000000..1ebe0ad
--- /dev/null
+++ b/general/datasets/Gn10/experiment-design.rtf
@@ -0,0 +1 @@
+Expression profiling by array
diff --git a/general/datasets/Gn10/experiment-type.rtf b/general/datasets/Gn10/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Gn10/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Gn10/notes.rtf b/general/datasets/Gn10/notes.rtf
new file mode 100644
index 0000000..7a26eb5
--- /dev/null
+++ b/general/datasets/Gn10/notes.rtf
@@ -0,0 +1 @@
+This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/Gn10/platform.rtf b/general/datasets/Gn10/platform.rtf
new file mode 100644
index 0000000..9024a99
--- /dev/null
+++ b/general/datasets/Gn10/platform.rtf
@@ -0,0 +1,11 @@
+Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many probes overlap and target the same transcript). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequences as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
+
+As part of the development of HEIMED, we have manually annotated individual probe sets by sequence alignment to the mouse genome and transcriptome. Approximately 13,000 probe sets that have comparatively high expression in eye and CNS were curated by one of the authors (RWW) and now have specific information on the part of the transcript targeted by each probe set. The other 33,000 transcripts have corresponding data that was generated by Xusheng Wang using computational methods (BLAT analysis combined with annotated genome sequence).
+
+One example may help explain how to exploit this annotation. The four probe sets for rhodopsin include information on the target location. Only the first probe set targets the last two coding exons. The other three probe sets target different parts of the 3’ UTR (mid, distal, and far distal regions). The probe sets can be reordered by from high to low expression using the Sort By function in Search Results pages. In the case of rhodopsin, the probe set that targets that last two coding exons and proximal parts of the 3’ UTR also has the highest expression . Finally, the HEIMED gene descriptions have been customized to help vision researchers. In the case of rhodopsin, the description appended after the gene name reads “rod photoreceptor pigment, retinitis pigmentosa-associated”. For less well known genes this kind of annotation can be extremely useful. For example, the more verbose annotation for Cerkl reads “neuronal survival and apoptosis-related, retinal ganglion cell expressed, retinitis pigmentosa 26); alternative 3' UTR of short form message, intron 2”.
+
+
+
+
+
+Legend: Distribution of expression values for all probe sets in HEIMED.
diff --git a/general/datasets/Gn10/processing.rtf b/general/datasets/Gn10/processing.rtf
new file mode 100644
index 0000000..4349e60
--- /dev/null
+++ b/general/datasets/Gn10/processing.rtf
@@ -0,0 +1,3381 @@
+Range of Gene Expression in the Eye. Expression of transcripts in the HEIMED and most other GN data sets is measured on a log2 scale. Each unit corresponding approximately to a 2-fold difference in hybridization signal intensity. To simplify comparisons among different data sets and cases, log2 RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units (variance stabilized). Values of all 45,101 probe sets in this data set range from a low of 4.8 (Tcf15, probe set 1420281_at) to a high of 15.5 (crystallin gamma C, Crygc, probe set 1422674_s_at). This corresponds to 10.7 units or a 1 to 1700 dynamic range of expression (2^10.73).
+
+We used pooled RNA samples of whole eyes, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+We calibrated this log intensity scale using Affymetrix spike-in control probe sets. These 18 control probe sets target exogenous bacterial mRNAs that are added to each sample (a graded dose spike cocktail) during preparation at concentrations of 1.5, 5, 25, and 100 pM. (To find these probe sets, search GN’s ALL search field using the string “AFFX pM”.) A value of 6 or less is equivalent to an mRNA concentration of under 0.4 pM, a value of 8 is equivalent to ~1.5 pM, 9.5 is equivalent to ~5 pM, 11.5 is equivalent to ~25 pM, 13.5 is equivalent to ~100 pM, and a value of 15.5 is equivalent to an mRNA concentration of 400 pM or greater.
+
+This range can be converted to the mRNA molecules per cell in the eye assuming that a value of 8 is equivalent to about 1 mRNA copy per cell (Kanno et al. 2006, see http://www.biomedcentral.com/1471-2164/7/64). Since the expression of rhodopsin mRNA is normally 15 units, we predict that there are 27 or ~128 Rho mRNAs per cell in the whole eye and ~256 in rods themselves (assuming that rods make up about half of all cells in the eye). For this purpose it may be useful to know that a normal mouse eye contains between 6 and 8 million rod photoreceptors (Guo, Lu, and Williams; GN BXD Phenotype ID 11024).
+
+Note that some probe sets with very low expression still provide reliable data. For example, probe set 1440397_at (Cacna2d1) has expression of only 5.5 units (a value that would be declared as "absent" using conventional Affymetrix procedures), but the values for this calcium channel transcript are associated with a very strong cis QTL with an LRS of 79 (LOD = 17). This strong linkage is definitely not due to chance since the probability of the expression data mapping precisely to the location of the parent gene itself is about 10e-16. This indicates a high signal to noise ratio and the detection of significant strain variation of the correct transcript.
+
+The standard error of the mean for the HEIMED data set is computed for 2 to 6 biological replicates. The standard error of such small samples tends to systematically underestimate the population standard error. With n = 2 the underestimate is about 25%, whereas for n = 6 the underestimate is 5%. Gurland and Tripathi (1971) provide a correction and equation for this effect (see Sokal and Rohlf, Biometry, 2nd ed., 1981, p 53 for an equation of the correction factor for small samples of n < 20.) Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. The CEL files were processed using the RMA protocol. We processed the first three batches together. The last batch was processed separately and merged as described below.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
+
+After RMA processing using Biobase affy10 build running under R version 2.7.1, all array data sets were rank-order normalized. This second round of quantile normalization removes much residual non-linearity across arrays and forces every array to have the same distribution of values as the mean of all arrays. Comparative array data quality was then evaluated in DataDesk. Outlier arrays were flagged by visual inspection in DataDesk, usually by means of an analysis of scatter plots and more quantitatively by generating a correlation matrix of all arrays. Those arrays with mean correlation <0.96 versus all other arrays indicates trouble or a biological outlier). In some cases, outliers were expected, such as samples from strains with retinal degeneration (FVB/NJ, NOD/LtJ, MOLF/EiJ, C3H/HeJ and BXD24), samples from wild subspecies such as WSB/EiJ, CAST/EiJ, PWD/PhJ, and PWK/PhJ, and knockouts. However, when arrays were anomolous both within strain and across strains, they were often simply discarded. The assumption is that anomolous data are much more likely due to experimental and technical errors than to informative biological variation. Approximately 10% of arrays were discarded.
+
+After this process, the acceptable set of arrays was renormalized using all step as above, starting with the original RMA procedure, etc.
+
+We reviewed the data set using a new method developed by RW Williams, Jeremy Peirce, and Hongqiang Li. For the full set of arrays that passed standard QC protocols described above, we computed the strain means for the BXD strains, B6, D2, and F1s. Using this set of strain means we then computed LRS scores for all 45101 probe sets and counted the number of transcripts that generated QTLs with LRS values greater than 50. This value (e.g., 1800) represented the QTL harvest for the full data set. We then dropped a single array from the data set, recomputed strain means, and recomputed the number of transcripts with LRS scores great than 50. This value is expected to typically reduce the number of QTLs that reach the criterion level (e.g., 1750 QTLs > 50). This process was repeated for every array to obtain an array-specific difference value--the effect of removing that array on the total QTL count. For example, the loss of a single array might cause a decrease in 50 QTLs. Values ranged from approximately -90 (good arrays) to +40 (bad arrays). This procedure is similar in some ways to a jackknife protocol, although we are not using this procedure to esimate an error term, but rather as a method to polish a data set.
+
+During this process we discovered that nearly 20 arrays in the batch 2 had been mislabeled at some point in processing. We computed the correct strain membership of each array using a large number of Mendelian probe sets (more than 50) and comparing their match to standard SNP and microsatellite markers and the original array data set of November 2005. This allowed us to rescue a large number of arrays that were of high quality.
+
+A third batch of approximately 40 arrays were processed by Yan Jiao and Weikuan Gu in August 2006. These complete data set assembled by Hongqiang Li. This process again included a correction for a batch effect.
+
+For the June 2006 data set Hongqiang Li used a new batch correction method that stabilizes the range of expression in each batch. For each of the three large batches, we extracted the minumum and maximum raw probe expression (CEL file level) value. We then adjusted raw probe values in each batch to have the same range as the first and largest batch (batch 1) using a simple linear interpolation. These procedures generated new correct CEL files which were then used with RMA to generate final probe set estimates.
+
+For the final fourth batch of arrays (Sept 2008) Arthur Centeno and Rob Williams corrected for a systematic difference in probe set expression values between original arrays run in 2005 and 2006 and the new arrays added in 2008 (n = 45 acceptable arrays). This difference is due to unknown technical batch effects that are probably associated with labeling, hybridization, and scanning. We performed a simple correction to normalize values of the new set of arrays to those of the old set (batches 1 through 3). No changes were made to any values of the previous three batches. We corrected only the probe set level (RMA) values and not the CEL files. For this final batch, we corrected for the difference (offset) in probe set expression between the first three batches arrays run in 2005 and 2006 (a total of 174 acceptable arrays) and the new batch (n = 47 acceptable arrays). This difference is due to unknown technical effects that are probably related to various steps in labeling, hybridization, and scanning. The correction was applied as follows: (1) RWW selected 51 high quality arrays with similar expression characteristics (r = 0.97 or better between pairs of arrays) in the old data set (from batches 1, 2, and 3) and 34 high quality arrays in the final batch. RWW used scatterplots of full RMA transcriptome data sets to review many pairs of arrays within these new and old array batches. Strains with retinal degeneration or unusual eye gene expression characteristics were excluded from these selected subsets. The average expression values for each probe set were then computed for both the old and new array subsets. The offset value (old minus new) was added to each probe set across all 47 new arrays. This processes forces the average probe set in the new arrays to be very close to that of the previous arrays.
+
+Table 2: Sample tube ID, strain, original CEL filename, and Affymetrix quality control values. Columns labeled Scale factor, Background Average, Present, Absent, Marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Strain |
+ Original CEL |
+ Scale factor |
+ Background Average |
+ Present |
+ Absent |
+ Marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ Batch Id |
+ Used for batch control |
+
+
+ | 1 |
+ R2595E.1 |
+ 129S1/SvImJ |
+ R2595E.1.CEL |
+ 1.79 |
+ 115 |
+ 61.00% |
+ 37.50% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 2 |
+ R2533E.1 |
+ 129S1/SvImJ |
+ R2533E.1.CEL |
+ 2.11 |
+ 94 |
+ 57.90% |
+ 40.50% |
+ 1.60% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 3 |
+ R0754E.1 |
+ A/J |
+ R0754E.1.CEL |
+ 2.72 |
+ 86 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.36 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 4 |
+ R4521E |
+ B6129P2F2N1-Clcn3 |
+ R4521E.CEL |
+ 4.83 |
+ 38.7 |
+ 63.30% |
+ 35.30% |
+ 1.40% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 5 |
+ R4522E |
+ B6129P2F2N1-Clcn3 |
+ R4522E.CEL |
+ 5.76 |
+ 37.36 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.37 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 6 |
+ R4523E |
+ B6129P2F2N1-Clcn3 |
+ R4523E.CEL |
+ 4.88 |
+ 40.42 |
+ 63.90% |
+ 34.70% |
+ 1.40% |
+ 1.27 |
+ 0.77 |
+ 4 |
+ |
+
+
+ | 7 |
+ R4526E |
+ B6129P2F2N1-Gabbr1 |
+ R4526E.CEL |
+ 3.84 |
+ 44.18 |
+ 65.00% |
+ 33.70% |
+ 1.30% |
+ 1.34 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 8 |
+ R4509E |
+ B6129P2F2N1-Gabbr1 |
+ R4509E.CEL |
+ 7.45 |
+ 34.76 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.45 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 9 |
+ R4510E |
+ B6129P2F2N1-Gabbr1 |
+ R4510E.CEL |
+ 8.44 |
+ 37.44 |
+ 57.40% |
+ 41.10% |
+ 1.50% |
+ 1.35 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 10 |
+ R4511E |
+ B6129P2F2N1-Gabbr1 |
+ R4511E.CEL |
+ 5.91 |
+ 42.02 |
+ 61.40% |
+ 37.20% |
+ 1.40% |
+ 1.41 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 11 |
+ R4524E |
+ B6129P2F2N1-Gabbr1 |
+ R4524E.CEL |
+ 5.49 |
+ 42.34 |
+ 62.40% |
+ 36.20% |
+ 1.40% |
+ 1.29 |
+ 0.78 |
+ 4 |
+ Y |
+
+
+ | 12 |
+ R4525E |
+ B6129P2F2N1-Gabbr1 |
+ R4525E.CEL |
+ 4.69 |
+ 41.3 |
+ 63.10% |
+ 35.50% |
+ 1.40% |
+ 1.27 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 13 |
+ R4515E |
+ B6129P2F2N1-Gabra1 |
+ R4515E.CEL |
+ 5.75 |
+ 41.76 |
+ 62.80% |
+ 35.80% |
+ 1.40% |
+ 1.41 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 14 |
+ R4516E |
+ B6129P2F2N1-Gabra1 |
+ R4516E.CEL |
+ 7.07 |
+ 40.73 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.32 |
+ 0.87 |
+ 4 |
+ Y |
+
+
+ | 15 |
+ R4517E |
+ B6129P2F2N1-Gabra1 |
+ R4517E.CEL |
+ 5.45 |
+ 38.09 |
+ 62.70% |
+ 35.80% |
+ 1.40% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 16 |
+ R4512E |
+ B6129P2F2N1-Gnb5 |
+ R4512E.CEL |
+ 6.56 |
+ 38.02 |
+ 59.90% |
+ 38.70% |
+ 1.50% |
+ 1.33 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 17 |
+ R4513E |
+ B6129P2F2N1-Gnb5 |
+ R4513E.CEL |
+ 4.15 |
+ 41.6 |
+ 63.40% |
+ 35.10% |
+ 1.50% |
+ 1.34 |
+ 0.82 |
+ 4 |
+ |
+
+
+ | 18 |
+ R4514E |
+ B6129P2F2N1-Gnb5 |
+ R4514E.CEL |
+ 5.86 |
+ 39.2 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.34 |
+ 0.81 |
+ 4 |
+ |
+
+
+ | 19 |
+ R4518E |
+ B6129P2F2N1-Gpr19 |
+ R4518E.CEL |
+ 5.58 |
+ 38.9 |
+ 62.60% |
+ 36.00% |
+ 1.30% |
+ 1.39 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 20 |
+ R4519E |
+ B6129P2F2N1-Gpr19 |
+ R4519E.CEL |
+ 5.95 |
+ 41.91 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.35 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 21 |
+ R2601E.1 |
+ B6D2F1 |
+ R2601E.1.CEL |
+ 2.55 |
+ 92 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.44 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 22 |
+ R2602E.1 |
+ B6D2F1 |
+ R2602E.1.CEL |
+ 2.6 |
+ 84 |
+ 59.70% |
+ 38.80% |
+ 1.50% |
+ 1.37 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 23 |
+ R1676E.1 |
+ BALB/cByJ |
+ R1676E.1.CEL |
+ 2.69 |
+ 98 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.46 |
+ 0.74 |
+ 1 |
+ |
+
+
+ | 24 |
+ R1672E.1 |
+ BALB/cByJ |
+ R1672E.1.CEL |
+ 2.22 |
+ 111 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 25 |
+ R4530E |
+ BALB/cJ |
+ R4530E.CEL |
+ 6.37 |
+ 37.53 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.3 |
+ 0.84 |
+ 4 |
+ Y |
+
+
+ | 26 |
+ R4529E |
+ BALB/cJ |
+ R4529E.CEL |
+ 5.71 |
+ 41.33 |
+ 60.50% |
+ 38.00% |
+ 1.50% |
+ 1.48 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD1 |
+ R2704E.2.CEL |
+ 2.066 |
+ 139.61 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD1 |
+ R2707E.3.CEL |
+ 1 |
+ 80 |
+ 56.40% |
+ 42.10% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 3 |
+ |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD2 |
+ R1231E.2.CEL |
+ 2.197 |
+ 138.73 |
+ 57.30% |
+ 41.30% |
+ 1.40% |
+ 1.41 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD2 |
+ R2598E.1.CEL |
+ 1.99 |
+ 106 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD5 |
+ R2591E.1.CEL |
+ 1.7 |
+ 136 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.33 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD5 |
+ R2714E.2.CEL |
+ 1.404 |
+ 144.35 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD6 |
+ R2570E.1.CEL |
+ 1.99 |
+ 87 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.46 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD6 |
+ R2694E.2.CEL |
+ 1.983 |
+ 97.23 |
+ 61.60% |
+ 37.10% |
+ 1.30% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD8 |
+ R2538E.1.CEL |
+ 1.91 |
+ 102 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.52 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD8 |
+ R2709E.2.CEL |
+ 1.99 |
+ 99.79 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.42 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD9 |
+ R2708E.2.CEL |
+ 1.966 |
+ 126.46 |
+ 57.70% |
+ 40.70% |
+ 1.50% |
+ 1.4 |
+ 0.84 |
+ 2 |
+ |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD9 |
+ R2569E.1.CEL |
+ 1.75 |
+ 87 |
+ 55.10% |
+ 43.40% |
+ 1.50% |
+ 2.82 |
+ 3.14 |
+ 1 |
+ |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD11 |
+ R2581E.1.CEL |
+ 1.94 |
+ 89 |
+ 62.10% |
+ 36.40% |
+ 1.60% |
+ 1.55 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD11 |
+ R2612E.2.CEL |
+ 1.83 |
+ 142.03 |
+ 58.20% |
+ 40.50% |
+ 1.40% |
+ 1.78 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD12 |
+ R2742E.2.CEL |
+ 2.127 |
+ 134.14 |
+ 57.00% |
+ 41.60% |
+ 1.40% |
+ 1.64 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD12 |
+ R2543E.1.CEL |
+ 1.61 |
+ 118 |
+ 58.60% |
+ 39.90% |
+ 1.60% |
+ 1.43 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD13 |
+ R2586E.1.CEL |
+ 2.01 |
+ 74 |
+ 56.40% |
+ 42.00% |
+ 1.60% |
+ 2.85 |
+ 3.81 |
+ 1 |
+ |
+
+
+ | 44 |
+ R877E.2 |
+ BXD13 |
+ R877E.2.CEL |
+ 1.558 |
+ 125.63 |
+ 61.20% |
+ 37.50% |
+ 1.20% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD14 |
+ R2557E.1.CEL |
+ 1.83 |
+ 99 |
+ 62.50% |
+ 36.10% |
+ 1.40% |
+ 1.31 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD14 |
+ R1128E.2.CEL |
+ 1.91 |
+ 115 |
+ 59.90% |
+ 38.80% |
+ 1.40% |
+ 1.2 |
+ 0.82 |
+ 1 |
+ Y |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD15 |
+ R2701E.3.CEL |
+ 1 |
+ 88 |
+ 60.60% |
+ 37.90% |
+ 1.40% |
+ 1.5 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD15 |
+ R2716E.2.CEL |
+ 2.015 |
+ 150.83 |
+ 56.40% |
+ 42.10% |
+ 1.60% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD16 |
+ R2711E.2.CEL |
+ 1.953 |
+ 118.53 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD16 |
+ R2567E.1.CEL |
+ 2.24 |
+ 82 |
+ 56.70% |
+ 41.60% |
+ 1.70% |
+ 1.37 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD18 |
+ R2720E.2.CEL |
+ 2.32 |
+ 99.93 |
+ 59.50% |
+ 39.00% |
+ 1.50% |
+ 1.33 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD18 |
+ R2559E.1.CEL |
+ 1.65 |
+ 104 |
+ 60.80% |
+ 37.70% |
+ 1.50% |
+ 1.27 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD19 |
+ R2560E.1.CEL |
+ 1.79 |
+ 98 |
+ 60.90% |
+ 37.50% |
+ 1.60% |
+ 1.35 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD19 |
+ R2713E.2.CEL |
+ 1.67 |
+ 120.82 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.45 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD20 |
+ R2584E.1.CEL |
+ 2.07 |
+ 84 |
+ 59.30% |
+ 39.10% |
+ 1.60% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD20 |
+ R2731E.2.CEL |
+ 1.825 |
+ 147 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.4 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD21 |
+ R2702E.2.CEL |
+ 1.811 |
+ 128.65 |
+ 59.40% |
+ 39.10% |
+ 1.40% |
+ 1.26 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD21 |
+ R2541E2.1.CEL |
+ 2.63 |
+ 125 |
+ 56.00% |
+ 42.40% |
+ 1.50% |
+ 1.29 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD22 |
+ R2553E.1.CEL |
+ 1.95 |
+ 111 |
+ 59.90% |
+ 38.50% |
+ 1.50% |
+ 1.28 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD22 |
+ R2700E.2.CEL |
+ 1.858 |
+ 102.96 |
+ 61.50% |
+ 37.10% |
+ 1.30% |
+ 1.48 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD23 |
+ R2558E-2.1.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD23 |
+ R1086E.2.CEL |
+ 2.233 |
+ 125.05 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.43 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD24 |
+ R2719E.2.CEL |
+ 1.47 |
+ 140.38 |
+ 61.50% |
+ 37.20% |
+ 1.30% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD24 |
+ R2589E2.1.CEL |
+ 2.61 |
+ 112 |
+ 57.50% |
+ 40.90% |
+ 1.60% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD25 |
+ R2573E-2.1.CEL |
+ 3.15 |
+ 72 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.77 |
+ 0.97 |
+ 1 |
+ |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD25 |
+ R2683E.2.CEL |
+ 1.777 |
+ 115.64 |
+ 58.30% |
+ 40.30% |
+ 1.40% |
+ 2.01 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD27 |
+ R2703E.2.CEL |
+ 1.263 |
+ 134.78 |
+ 62.60% |
+ 36.10% |
+ 1.40% |
+ 1.44 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD27 |
+ R2729E.3.CEL |
+ 1 |
+ 87 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.56 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD28 |
+ R2562E.3.CEL |
+ 1.65 |
+ 116 |
+ 59.90% |
+ 38.40% |
+ 1.70% |
+ 1.37 |
+ 0.79 |
+ 3 |
+ Y |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD28 |
+ R2721E.2.CEL |
+ 2.065 |
+ 157.39 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.31 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD29 |
+ R2561E.3.CEL |
+ 1 |
+ 77 |
+ 53.30% |
+ 45.40% |
+ 1.40% |
+ 3.36 |
+ 19.66 |
+ 3 |
+ |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD31 |
+ R1258E.2.CEL |
+ 2.063 |
+ 117.09 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.54 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD31 |
+ R2597E.1.CEL |
+ 2.37 |
+ 94 |
+ 60.30% |
+ 38.30% |
+ 1.50% |
+ 1.34 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD32 |
+ R2563E.1.CEL |
+ 1.55 |
+ 102 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD32 |
+ R1216E.2.CEL |
+ 2.23 |
+ 111.99 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.35 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD33 |
+ R2542E.1.CEL |
+ 2.13 |
+ 97 |
+ 56.50% |
+ 41.80% |
+ 1.60% |
+ 1.91 |
+ 0.93 |
+ 1 |
+ |
+
+
+ | 77 |
+ R857E.2 |
+ BXD33 |
+ R857E.2.CEL |
+ 1.737 |
+ 113.98 |
+ 61.90% |
+ 36.70% |
+ 1.30% |
+ 1.6 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD34 |
+ R1451E.2.CEL |
+ 1.843 |
+ 140.05 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ Y |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD34 |
+ R2585E.1.CEL |
+ 2.64 |
+ 75 |
+ 58.30% |
+ 40.00% |
+ 1.70% |
+ 1.25 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD36 |
+ R2698E.3.CEL |
+ 1 |
+ 86 |
+ 59.70% |
+ 39.00% |
+ 1.30% |
+ 1.46 |
+ 0.78 |
+ 3 |
+ |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD36 |
+ R2705E.3.CEL |
+ 1 |
+ 86 |
+ 60.20% |
+ 38.40% |
+ 1.40% |
+ 1.46 |
+ 0.77 |
+ 3 |
+ |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD38 |
+ R2710E.2.CEL |
+ 2.112 |
+ 122.1 |
+ 58.80% |
+ 39.80% |
+ 1.40% |
+ 1.37 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD38 |
+ R2532E.1.CEL |
+ 2.04 |
+ 94 |
+ 59.80% |
+ 38.70% |
+ 1.50% |
+ 1.37 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD39 |
+ R2574E.1.CEL |
+ 1.98 |
+ 91 |
+ 61.20% |
+ 37.30% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD39 |
+ R2695E.2.CEL |
+ 1.638 |
+ 122.7 |
+ 60.80% |
+ 37.80% |
+ 1.50% |
+ 1.42 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD40 |
+ R2699E.2.CEL |
+ 1.827 |
+ 105.23 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.42 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD40 |
+ R2590E.1.CEL |
+ 2.71 |
+ 77 |
+ 59.10% |
+ 39.30% |
+ 1.50% |
+ 1.4 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD42 |
+ R2696E.2.CEL |
+ 1.622 |
+ 118.95 |
+ 62.00% |
+ 36.60% |
+ 1.50% |
+ 1.53 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD42 |
+ R2596E.1.CEL |
+ 2.63 |
+ 108 |
+ 59.00% |
+ 39.60% |
+ 1.50% |
+ 1.24 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 90 |
+ R994E.2 |
+ BXD43 |
+ R994E.2.CEL |
+ 1.966 |
+ 113.12 |
+ 60.80% |
+ 37.80% |
+ 1.40% |
+ 1.66 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD43 |
+ R2607E.1.CEL |
+ 2.43 |
+ 115 |
+ 58.60% |
+ 40.00% |
+ 1.40% |
+ 1.31 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD44 |
+ R2594E.1.CEL |
+ 1.77 |
+ 117 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.35 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD44 |
+ R2610E.2.CEL |
+ 1.814 |
+ 142.91 |
+ 59.00% |
+ 39.50% |
+ 1.50% |
+ 1.35 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD45 |
+ R2732E.2.CEL |
+ 2.154 |
+ 122.45 |
+ 56.50% |
+ 42.10% |
+ 1.40% |
+ 1.8 |
+ 0.83 |
+ 2 |
+ |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD45 |
+ R2592E.1.CEL |
+ 1.85 |
+ 106 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.43 |
+ 0.85 |
+ 1 |
+ Y |
+
+
+ | 96 |
+ R967E.2 |
+ BXD48 |
+ R967E.2.CEL |
+ 1.948 |
+ 130.95 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.63 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD48 |
+ R2606E.1.CEL |
+ 2.56 |
+ 106 |
+ 58.90% |
+ 39.70% |
+ 1.40% |
+ 1.35 |
+ 0.83 |
+ 1 |
+ Y |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD50 |
+ R2933E.3.CEL |
+ 1 |
+ 72 |
+ 52.90% |
+ 45.60% |
+ 1.50% |
+ 2.45 |
+ 0.98 |
+ 3 |
+ |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD50 |
+ R2937E.3.CEL |
+ 1 |
+ 89 |
+ 56.90% |
+ 41.60% |
+ 1.40% |
+ 1.81 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD51 |
+ R2603E.1.CEL |
+ 2.49 |
+ 115 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD51 |
+ R1042E.2.CEL |
+ 2.352 |
+ 104.12 |
+ 58.70% |
+ 39.90% |
+ 1.40% |
+ 1.53 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD55 |
+ R2980E.3.CEL |
+ 1 |
+ 82 |
+ 56.90% |
+ 41.70% |
+ 1.50% |
+ 1.77 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD55 |
+ R2690E.2.CEL |
+ 1.887 |
+ 164.01 |
+ 56.10% |
+ 42.30% |
+ 1.60% |
+ 1.43 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 104 |
+ R4176E |
+ BXD56 |
+ R4176E.CEL |
+ 4.75 |
+ 43.08 |
+ 63.00% |
+ 35.60% |
+ 1.30% |
+ 1.39 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 105 |
+ R4175E |
+ BXD56 |
+ R4175E.CEL |
+ 6 |
+ 38.49 |
+ 61.30% |
+ 37.30% |
+ 1.40% |
+ 1.47 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD60 |
+ R1006E.3.CEL |
+ 1 |
+ 98 |
+ 54.90% |
+ 43.70% |
+ 1.50% |
+ 2.7 |
+ 0.86 |
+ 3 |
+ |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD60 |
+ R2725E.2.CEL |
+ 1.551 |
+ 148.01 |
+ 59.80% |
+ 38.80% |
+ 1.40% |
+ 1.43 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD60 |
+ R1074E.3.CEL |
+ 1 |
+ 118 |
+ 55.50% |
+ 43.10% |
+ 1.40% |
+ 1.96 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD61 |
+ R2534E2.1.CEL |
+ 2.47 |
+ 118 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.42 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD61 |
+ R2684E.2.CEL |
+ 2.01 |
+ 131.03 |
+ 57.00% |
+ 41.50% |
+ 1.50% |
+ 1.34 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD62 |
+ R1107E.3.CEL |
+ 1 |
+ 83 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.43 |
+ 0.93 |
+ 3 |
+ |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD62 |
+ R2681E.2.CEL |
+ 2.086 |
+ 148.24 |
+ 57.20% |
+ 41.30% |
+ 1.50% |
+ 1.29 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 113 |
+ R965E.3 |
+ BXD62 |
+ R965E.3.CEL |
+ 1 |
+ 93.55 |
+ 53.30% |
+ 45.20% |
+ 1.50% |
+ 3.11 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD63 |
+ R1425E.2.CEL |
+ 1.7 |
+ 136 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.43 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD63 |
+ R2576E.3.CEL |
+ 1 |
+ 84 |
+ 61.30% |
+ 37.40% |
+ 1.40% |
+ 1.48 |
+ 0.76 |
+ 3 |
+ |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD64 |
+ R943E-2.2.CEL |
+ 1.591 |
+ 141.34 |
+ 60.10% |
+ 38.40% |
+ 1.50% |
+ 1.32 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD64 |
+ R2611E.1.CEL |
+ 2.29 |
+ 92 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 1.57 |
+ 1.06 |
+ 1 |
+ |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD65 |
+ R2689E.2.CEL |
+ 1.721 |
+ 142.44 |
+ 59.90% |
+ 38.60% |
+ 1.50% |
+ 1.38 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD65 |
+ R2583E.1.CEL |
+ 2.49 |
+ 70 |
+ 56.90% |
+ 41.50% |
+ 1.60% |
+ 1.67 |
+ 1.01 |
+ 1 |
+ |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD66 |
+ R2728E.2.CEL |
+ 1.714 |
+ 137.45 |
+ 59.40% |
+ 39.00% |
+ 1.60% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD66 |
+ R2536E2.1.CEL |
+ 2.74 |
+ 109 |
+ 56.10% |
+ 42.30% |
+ 1.70% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD66 |
+ R1207E.2.CEL |
+ 1.681 |
+ 136.86 |
+ 60.40% |
+ 38.10% |
+ 1.50% |
+ 1.45 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD67 |
+ R1192E.2.CEL |
+ 2.126 |
+ 123.37 |
+ 57.90% |
+ 40.60% |
+ 1.50% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD67 |
+ R2727E.3.CEL |
+ 1 |
+ 82.55 |
+ 56.10% |
+ 42.40% |
+ 1.50% |
+ 1.97 |
+ 0.87 |
+ 2 |
+ |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD67 |
+ R2691E.3.CEL |
+ 1 |
+ 90 |
+ 54.80% |
+ 43.80% |
+ 1.50% |
+ 2.61 |
+ 0.81 |
+ 3 |
+ |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD68 |
+ R2551E.1.CEL |
+ 2.49 |
+ 92 |
+ 54.30% |
+ 44.10% |
+ 1.60% |
+ 2.91 |
+ 1.55 |
+ 1 |
+ |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD68 |
+ R2726E.2.CEL |
+ 1.811 |
+ 153.09 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.39 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD69 |
+ R2593E.1.CEL |
+ 1.67 |
+ 128 |
+ 59.20% |
+ 39.50% |
+ 1.30% |
+ 1.47 |
+ 0.92 |
+ 1 |
+ Y |
+
+
+ | 129 |
+ R975E.2 |
+ BXD70 |
+ R975E.2.CEL |
+ 1.841 |
+ 137.97 |
+ 58.00% |
+ 40.50% |
+ 1.40% |
+ 1.36 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD70 |
+ R2537E2.1.CEL |
+ 2.93 |
+ 99 |
+ 58.00% |
+ 40.50% |
+ 1.60% |
+ 1.29 |
+ 0.75 |
+ 1 |
+ |
+
+
+ | 131 |
+ R4531E |
+ BXD71 |
+ R4531E.CEL |
+ 4.77 |
+ 43.48 |
+ 62.40% |
+ 36.30% |
+ 1.40% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 132 |
+ R4532E |
+ BXD71 |
+ R4532E.CEL |
+ 5.89 |
+ 40.68 |
+ 60.90% |
+ 37.60% |
+ 1.50% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ Y |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD73 |
+ R2779E.2.CEL |
+ 1.746 |
+ 121.11 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.5 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD73 |
+ R3024E.3.CEL |
+ 1 |
+ 78.05 |
+ 51.70% |
+ 46.60% |
+ 1.70% |
+ 2.3 |
+ 0.94 |
+ 3 |
+ |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD75 |
+ R2565E.1.CEL |
+ 1.79 |
+ 102 |
+ 58.00% |
+ 40.50% |
+ 1.50% |
+ 2.31 |
+ 3.47 |
+ 1 |
+ |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD75 |
+ R1397E-re.2.CEL |
+ 1.449 |
+ 189.71 |
+ 59.60% |
+ 39.00% |
+ 1.40% |
+ 1.39 |
+ 0.82 |
+ 2 |
+ |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD77 |
+ R2687E.3.CEL |
+ 1 |
+ 80 |
+ 58.00% |
+ 40.60% |
+ 1.40% |
+ 1.57 |
+ 0.8 |
+ 3 |
+ Y |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD77 |
+ R2717E.2.CEL |
+ 1.797 |
+ 84.43 |
+ 61.60% |
+ 36.90% |
+ 1.40% |
+ 1.49 |
+ 0.76 |
+ 2 |
+ |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD77 |
+ R1421E.3.CEL |
+ 1 |
+ 94 |
+ 52.40% |
+ 46.20% |
+ 1.40% |
+ 2.29 |
+ 0.82 |
+ 3 |
+ |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD80 |
+ R2579E.1.CEL |
+ 2.42 |
+ 72 |
+ 59.20% |
+ 39.40% |
+ 1.50% |
+ 1.73 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD80 |
+ R2686E.2.CEL |
+ 2.342 |
+ 119.63 |
+ 56.00% |
+ 42.60% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD83 |
+ R2956E.3.CEL |
+ 1 |
+ 84 |
+ 55.40% |
+ 43.20% |
+ 1.40% |
+ 1.39 |
+ 0.84 |
+ 3 |
+ |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD83 |
+ R2960E.3.CEL |
+ 1 |
+ 80 |
+ 56.60% |
+ 41.90% |
+ 1.50% |
+ 1.5 |
+ 0.82 |
+ 3 |
+ Y |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD84 |
+ R2922E.3.CEL |
+ 1 |
+ 91 |
+ 57.80% |
+ 40.80% |
+ 1.50% |
+ 1.47 |
+ 0.83 |
+ 3 |
+ Y |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD84 |
+ R2895E.3.CEL |
+ 1 |
+ 75 |
+ 58.30% |
+ 40.20% |
+ 1.50% |
+ 1.56 |
+ 0.77 |
+ 3 |
+ Y |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD85 |
+ R2692E.2.CEL |
+ 1.423 |
+ 160.87 |
+ 60.20% |
+ 38.30% |
+ 1.40% |
+ 1.46 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD85 |
+ R2715E.2.CEL |
+ 1.488 |
+ 142.6 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.5 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD86 |
+ R1405E.2.CEL |
+ 2.351 |
+ 119.34 |
+ 56.40% |
+ 42.20% |
+ 1.40% |
+ 1.64 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD86 |
+ R1225E.3.CEL |
+ 1 |
+ 71 |
+ 53.90% |
+ 44.60% |
+ 1.40% |
+ 3.2 |
+ 1.61 |
+ 3 |
+ |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD87 |
+ R2724E.2.CEL |
+ 1.906 |
+ 113.71 |
+ 60.70% |
+ 37.90% |
+ 1.40% |
+ 1.45 |
+ 0.79 |
+ 2 |
+ |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD87 |
+ R2540E.1.CEL |
+ 2.33 |
+ 93 |
+ 61.10% |
+ 37.40% |
+ 1.40% |
+ 1.22 |
+ 0.81 |
+ 1 |
+ Y |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD89 |
+ R1433E.2.CEL |
+ 1 |
+ 2.241 |
+ 57.70% |
+ 40.80% |
+ 1.50% |
+ 1.41 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD89 |
+ R2546E.1.CEL |
+ 1.99 |
+ 96 |
+ 58.60% |
+ 39.70% |
+ 1.70% |
+ 1.47 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD90 |
+ R2578E2.1.CEL |
+ 2.79 |
+ 92 |
+ 58.60% |
+ 39.80% |
+ 1.60% |
+ 1.52 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 155 |
+ R859E.2 |
+ BXD90 |
+ R859E.2.CEL |
+ 1.847 |
+ 152.22 |
+ 57.90% |
+ 40.70% |
+ 1.40% |
+ 1.36 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD92 |
+ R2682E.2.CEL |
+ 1.547 |
+ 156.31 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.37 |
+ 0.77 |
+ 2 |
+ |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD92 |
+ R1388E.3.CEL |
+ 1 |
+ 63 |
+ 60.00% |
+ 38.60% |
+ 1.40% |
+ 1.85 |
+ 1.03 |
+ 3 |
+ |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD92 |
+ R1322E.3.CEL |
+ 1 |
+ 80 |
+ 55.90% |
+ 42.60% |
+ 1.50% |
+ 1.75 |
+ 0.74 |
+ 3 |
+ |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD96 |
+ R2733E.2.CEL |
+ 1.7 |
+ 113.99 |
+ 62.10% |
+ 36.60% |
+ 1.30% |
+ 1.4 |
+ 0.78 |
+ 2 |
+ |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD96 |
+ R2554E.1.CEL |
+ 2.18 |
+ 93 |
+ 60.20% |
+ 38.30% |
+ 1.50% |
+ 1.46 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD97 |
+ R2649E.2.CEL |
+ 2.343 |
+ 119.04 |
+ 57.50% |
+ 41.20% |
+ 1.40% |
+ 1.53 |
+ 0.8 |
+ 2 |
+ |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD97 |
+ R2577E.1.CEL |
+ 2.07 |
+ 77 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.87 |
+ 1.29 |
+ 1 |
+ |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD98 |
+ R2645E.3.CEL |
+ 1 |
+ 88 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.59 |
+ 0.81 |
+ 3 |
+ Y |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD98 |
+ R2688E.2.CEL |
+ 1.772 |
+ 145.24 |
+ 58.50% |
+ 40.00% |
+ 1.50% |
+ 1.48 |
+ 0.81 |
+ 2 |
+ |
+
+
+ | 165 |
+ R4533E |
+ BXD99 |
+ R4533E.CEL |
+ 1 |
+ 37.69 |
+ 60.30% |
+ 38.20% |
+ 1.40% |
+ 1.33 |
+ 0.89 |
+ 4 |
+ Y |
+
+
+ | 166 |
+ R4534E |
+ BXD99 |
+ R4534E.CEL |
+ 5.69 |
+ 36.62 |
+ 62.90% |
+ 35.70% |
+ 1.40% |
+ 1.16 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 167 |
+ R2885E.3 |
+ BXSB/MpJ |
+ R2885E.3.CEL |
+ 1 |
+ 76 |
+ 58.10% |
+ 40.60% |
+ 1.30% |
+ 1.88 |
+ 1.06 |
+ 3 |
+ |
+
+
+ | 168 |
+ R2883E.3 |
+ BXSB/MpJ |
+ R2883E.3.CEL |
+ 1 |
+ 71 |
+ 56.40% |
+ 42.00% |
+ 1.50% |
+ 1.59 |
+ 0.84 |
+ 3 |
+ Y |
+
+
+ | 169 |
+ R1700E.1 |
+ C3H/HeJ |
+ R1700E.1.CEL |
+ 2.98 |
+ 69 |
+ 60.80% |
+ 37.90% |
+ 1.40% |
+ 1.48 |
+ 0.78 |
+ 1 |
+ |
+
+
+ | 170 |
+ R1704E.1 |
+ C3H/HeJ |
+ R1704E.1.CEL |
+ 2.58 |
+ 88 |
+ 60.10% |
+ 38.60% |
+ 1.30% |
+ 1.38 |
+ 0.84 |
+ 1 |
+ |
+
+
+ | 171 |
+ R2605E.1 |
+ C57BL/6J |
+ R2605E.1.CEL |
+ 1.82 |
+ 131 |
+ 60.50% |
+ 38.20% |
+ 1.30% |
+ 1.32 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 172 |
+ R0871E |
+ C57BL/6J |
+ R0871E.CEL |
+ 6.24 |
+ 37.38 |
+ 61.90% |
+ 36.70% |
+ 1.40% |
+ 1.41 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 173 |
+ R0872E.1 |
+ C57BL/6J |
+ R0872E.1.CEL |
+ 3.13 |
+ 89 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 174 |
+ R0872E |
+ C57BL/6J |
+ R0872E.CEL |
+ 3.128 |
+ 88.58 |
+ 58.90% |
+ 39.60% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 175 |
+ R4507E |
+ C57BL/6J-Nyx |
+ R4507E.CEL |
+ 8.13 |
+ 37.5 |
+ 59.30% |
+ 39.30% |
+ 1.40% |
+ 1.32 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 176 |
+ R4508E |
+ C57BL/6J-Nyx |
+ R4508E.CEL |
+ 6.33 |
+ 37.26 |
+ 60.90% |
+ 37.80% |
+ 1.30% |
+ 1.24 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 177 |
+ R4505E |
+ C57BL/6J-Rpe65 |
+ R4505E.CEL |
+ 5.98 |
+ 37.48 |
+ 61.80% |
+ 36.80% |
+ 1.40% |
+ 1.45 |
+ 0.85 |
+ 4 |
+ Y |
+
+
+ | 178 |
+ R4506E |
+ C57BL/6J-Rpe65 |
+ R4506E.CEL |
+ 6.94 |
+ 37.9 |
+ 61.10% |
+ 37.50% |
+ 1.30% |
+ 1.5 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 179 |
+ R4535E |
+ C57BLKS/J |
+ R4535E.CEL |
+ 6.59 |
+ 37.28 |
+ 61.20% |
+ 37.30% |
+ 1.40% |
+ 1.26 |
+ 0.83 |
+ 4 |
+ Y |
+
+
+ | 180 |
+ R4536E |
+ C57BLKS/J |
+ R4536E.CEL |
+ 1 |
+ 40.71 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.25 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 181 |
+ R2564E.1 |
+ CAST/EiJ |
+ R2564E.1.CEL |
+ 1.94 |
+ 89 |
+ 58.50% |
+ 39.90% |
+ 1.60% |
+ 1.6 |
+ 0.77 |
+ 1 |
+ |
+
+
+ | 182 |
+ R2580E.1 |
+ CAST/EiJ |
+ R2580E.1.CEL |
+ 2.09 |
+ 95 |
+ 58.20% |
+ 40.10% |
+ 1.70% |
+ 1.4 |
+ 0.76 |
+ 1 |
+ |
+
+
+ | 183 |
+ R4537E |
+ CBA/CaJ |
+ R4537E.CEL |
+ 1 |
+ 38.45 |
+ 60.60% |
+ 37.90% |
+ 1.50% |
+ 1.63 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 184 |
+ R4538E |
+ CBA/CaJ |
+ R4538E.CEL |
+ 5.89 |
+ 39.18 |
+ 61.70% |
+ 36.90% |
+ 1.40% |
+ 1.45 |
+ 0.8 |
+ 4 |
+ Y |
+
+
+ | 185 |
+ R4539E |
+ CZECHII/EiJ |
+ R4539E.CEL |
+ 7.73 |
+ 37.1 |
+ 58.30% |
+ 40.10% |
+ 1.50% |
+ 1.7 |
+ 0.95 |
+ 4 |
+ Y |
+
+
+ | 186 |
+ R4540E |
+ CZECHII/EiJ |
+ R4540E.CEL |
+ 11.04 |
+ 36.69 |
+ 53.00% |
+ 45.30% |
+ 1.70% |
+ 1.83 |
+ 1.32 |
+ 4 |
+ |
+
+
+ | 187 |
+ R2600E.1 |
+ D2B6F1 |
+ R2600E.1.CEL |
+ 2.47 |
+ 95 |
+ 58.10% |
+ 40.20% |
+ 1.70% |
+ 1.41 |
+ 0.78 |
+ 1 |
+ Y |
+
+
+ | 188 |
+ R2604E.1 |
+ D2B6F1 |
+ R2604E.1.CEL |
+ 2.66 |
+ 90 |
+ 59.40% |
+ 39.20% |
+ 1.50% |
+ 1.28 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 189 |
+ R1002E.3 |
+ DBA/2J |
+ R1002E.3.CEL |
+ 1 |
+ 102 |
+ 54.80% |
+ 43.70% |
+ 1.50% |
+ 2.84 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 190 |
+ R4541E |
+ DBA/2J |
+ R4541E.CEL |
+ 1 |
+ 43.4 |
+ 61.40% |
+ 37.00% |
+ 1.50% |
+ 1.37 |
+ 0.73 |
+ 4 |
+ Y |
+
+
+ | 191 |
+ R959E.3 |
+ DBA/2J |
+ R959E.3.CEL |
+ 1 |
+ 89.97 |
+ 53.20% |
+ 45.30% |
+ 1.50% |
+ 3.66 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 192 |
+ R2572E.1 |
+ DBA/2J |
+ R2572E.1.CEL |
+ 2.41 |
+ 79 |
+ 55.50% |
+ 42.90% |
+ 1.60% |
+ 1.37 |
+ 0.79 |
+ 1 |
+ |
+
+
+ | 193 |
+ R4542E |
+ DBA/2J |
+ R4542E.CEL |
+ 5.7 |
+ 39.95 |
+ 61.00% |
+ 37.40% |
+ 1.50% |
+ 1.23 |
+ 0.81 |
+ 4 |
+ Y |
+
+
+ | 194 |
+ R2771E.3 |
+ FVB/NJ |
+ R2771E.3.CEL |
+ 1 |
+ 70 |
+ 55.30% |
+ 43.20% |
+ 1.50% |
+ 1.69 |
+ 0.83 |
+ 3 |
+ |
+
+
+ | 195 |
+ R2772E.3 |
+ FVB/NJ |
+ R2772E.3.CEL |
+ 1 |
+ 76 |
+ 55.20% |
+ 43.40% |
+ 1.40% |
+ 2.13 |
+ 1.02 |
+ 3 |
+ |
+
+
+ | 196 |
+ R2636E.1 |
+ KK/HlJ |
+ R2636E.1.CEL |
+ 2.61 |
+ 93 |
+ 58.90% |
+ 39.50% |
+ 1.50% |
+ 1.39 |
+ 0.76 |
+ 1 |
+ Y |
+
+
+ | 197 |
+ R2637E.1 |
+ KK/HlJ |
+ R2637E.1.CEL |
+ 2.19 |
+ 103 |
+ 59.40% |
+ 39.00% |
+ 1.50% |
+ 1.3 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 198 |
+ R0999E.1 |
+ LG/J |
+ R0999E.1.CEL |
+ 2.45 |
+ 82 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 199 |
+ R1004E.1 |
+ LG/J |
+ R1004E.1.CEL |
+ 2.44 |
+ 92 |
+ 58.70% |
+ 39.80% |
+ 1.50% |
+ 1.38 |
+ 0.79 |
+ 1 |
+ Y |
+
+
+ | 200 |
+ R4543E |
+ LP/J |
+ R4543E.CEL |
+ 6.57 |
+ 41.99 |
+ 60.30% |
+ 38.20% |
+ 1.50% |
+ 1.28 |
+ 0.75 |
+ 4 |
+ Y |
+
+
+ | 201 |
+ R4544E |
+ LP/J |
+ R4544E.CEL |
+ 4.56 |
+ 39.9 |
+ 62.40% |
+ 36.10% |
+ 1.50% |
+ 1.23 |
+ 0.77 |
+ 4 |
+ Y |
+
+
+ | 202 |
+ R2858E.3 |
+ MOLF/EiJ |
+ R2858E.3.CEL |
+ 1 |
+ 64 |
+ 53.80% |
+ 44.70% |
+ 1.50% |
+ 1.59 |
+ 0.95 |
+ 3 |
+ |
+
+
+ | 203 |
+ R2919.3 |
+ MOLF/EiJ |
+ R2919.3.CEL |
+ 1 |
+ 64 |
+ 52.40% |
+ 46.00% |
+ 1.60% |
+ 2.15 |
+ 1.07 |
+ 3 |
+ |
+
+
+ | 204 |
+ R1688E.1 |
+ NOD/LtJ |
+ R1688E.1.CEL |
+ 2.66 |
+ 98 |
+ 58.60% |
+ 39.90% |
+ 1.50% |
+ 1.26 |
+ 0.8 |
+ 1 |
+ Y |
+
+
+ | 205 |
+ R2566E-2.1 |
+ NOD/LtJ |
+ R2566E-2.1.CEL |
+ 3.03 |
+ 69 |
+ 59.80% |
+ 38.80% |
+ 1.50% |
+ 1.38 |
+ 0.75 |
+ 1 |
+ Y |
+
+
+ | 206 |
+ R4545E |
+ NZB/BlNJ |
+ R4545E.CEL |
+ 4.23 |
+ 43.48 |
+ 62.10% |
+ 36.40% |
+ 1.50% |
+ 1.33 |
+ 0.76 |
+ 4 |
+ Y |
+
+
+ | 207 |
+ R4546E |
+ NZB/BlNJ |
+ R4546E.CEL |
+ 6.27 |
+ 44.22 |
+ 59.40% |
+ 39.10% |
+ 1.50% |
+ 1.17 |
+ 0.82 |
+ 4 |
+ Y |
+
+
+ | 208 |
+ R2535E.1 |
+ NZO/HlLtJ |
+ R2535E.1.CEL |
+ 1.89 |
+ 86 |
+ 60.40% |
+ 38.20% |
+ 1.40% |
+ 1.41 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 209 |
+ R2550E.1 |
+ NZO/HlLtJ |
+ R2550E.1.CEL |
+ 1.79 |
+ 87 |
+ 60.70% |
+ 37.80% |
+ 1.50% |
+ 1.52 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 210 |
+ R2817E.3 |
+ NZW/LacJ |
+ R2817E.3.CEL |
+ 1 |
+ 59 |
+ 50.90% |
+ 47.60% |
+ 1.50% |
+ 3.59 |
+ 1.48 |
+ 3 |
+ |
+
+
+ | 211 |
+ R2810E |
+ NZW/LacJ |
+ R2810E.CEL |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ 3 |
+ |
+
+
+ | 212 |
+ R2810E.3 |
+ NZW/LacJ |
+ R2810E.3.CEL |
+ 1 |
+ 74 |
+ 57.00% |
+ 41.70% |
+ 1.40% |
+ 2.15 |
+ 1.03 |
+ 4 |
+ Y |
+
+
+ | 213 |
+ R4547E |
+ PANCEVO/EiJ |
+ R4547E.CEL |
+ 5.27 |
+ 51.34 |
+ 57.20% |
+ 41.10% |
+ 1.70% |
+ 1.7 |
+ 0.83 |
+ 4 |
+ |
+
+
+ | 214 |
+ R4548E |
+ PANCEVO/EiJ |
+ R4548E.CEL |
+ 10.54 |
+ 37.39 |
+ 50.30% |
+ 48.00% |
+ 1.70% |
+ 1.68 |
+ 1.09 |
+ 4 |
+ |
+
+
+ | 215 |
+ R2635E.1 |
+ PWD/PhJ |
+ R2635E.1.CEL |
+ 3.72 |
+ 80 |
+ 54.20% |
+ 44.10% |
+ 1.70% |
+ 1.53 |
+ 0.85 |
+ 1 |
+ |
+
+
+ | 216 |
+ R2634E.1 |
+ PWD/PhJ |
+ R2634E.1.CEL |
+ 3.29 |
+ 90 |
+ 55.90% |
+ 42.50% |
+ 1.60% |
+ 1.57 |
+ 0.81 |
+ 1 |
+ |
+
+
+ | 217 |
+ R2544E.1 |
+ PWK/PhJ |
+ R2544E.1.CEL |
+ 2.2 |
+ 108 |
+ 54.90% |
+ 43.50% |
+ 1.70% |
+ 1.36 |
+ 0.82 |
+ 1 |
+ |
+
+
+ | 218 |
+ R2549E.1 |
+ PWK/PhJ |
+ R2549E.1.CEL |
+ 2.28 |
+ 84 |
+ 57.30% |
+ 41.20% |
+ 1.50% |
+ 1.57 |
+ 0.83 |
+ 1 |
+ |
+
+
+ | 219 |
+ R4550E |
+ SJL/J |
+ R4550E.CEL |
+ 5.35 |
+ 40.44 |
+ 62.30% |
+ 36.20% |
+ 1.40% |
+ 1.24 |
+ 0.79 |
+ 4 |
+ |
+
+
+ | 220 |
+ R2368E.1 |
+ WSB/EiJ |
+ R2368E.1.CEL |
+ 2.57 |
+ 86 |
+ 59.50% |
+ 39.10% |
+ 1.40% |
+ 1.29 |
+ 0.74 |
+ 1 |
+ Y |
+
+
+ | 221 |
+ R2547E.1 |
+ WSB/EiJ |
+ R2547E.1.CEL |
+ 2.14 |
+ 90 |
+ 58.20% |
+ 40.10% |
+ 1.60% |
+ 1.32 |
+ 0.77 |
+ 1 |
+ Y |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Gn10/summary.rtf b/general/datasets/Gn10/summary.rtf
new file mode 100644
index 0000000..44b7e23
--- /dev/null
+++ b/general/datasets/Gn10/summary.rtf
@@ -0,0 +1,12 @@
+FINAL RECOMMENDED EYE DATA SET. The HEIMED September 2008 RMA data release provides estimates of gene expression in whole eyes of 103 lines of young adult mice generated using 221 Affymetrix M430 2.0 arrays. This data set is intended for exploration of the genetics and genomics of the mouse eye, retina, lens, retinal pigment epithelium, cornea, iris and choroid. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). We used pooled RNA samples, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
+
+Users of these mouse eye data may also find the following complementary resources extremely useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
diff --git a/general/datasets/Gn10/tissue.rtf b/general/datasets/Gn10/tissue.rtf
new file mode 100644
index 0000000..9b6ee0f
--- /dev/null
+++ b/general/datasets/Gn10/tissue.rtf
@@ -0,0 +1,2058 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
+
+Each array was hybridized with a pool of cRNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
+
+Dissecting and preparing eyes for RNA extraction
+
+
+ - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
+ - Store RNA in 75% ethanol at –80 deg. C until use.
+
+
+Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+ - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
+ - allowed the homogenate to stand for 5 min at room temperature
+ - added 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
+ - centrifuged at 12,000 G for 15 min
+ - transfered the aqueous phase to a fresh tube
+ - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - vortexed and allowed sample to stand at room temperature for 5-10 min
+ - centrifuged at 12,000 G for 10-15 min
+ - removed the supernatant and washed the RNA pellet with 75% ethanol
+ - stored the pellet in 75% ethanol at -80 deg C until use
+
+
+Sample Processing. All samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center led by Dr. Weikuan Gu. All arrays were processed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. C until use (roughly one third) or were used immediately for hybridization.
+
+Dealing with ocular pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations taken from brown and beige colored mice tend to have faint residual pigmentation that affects hybridization signal. To address this problem, Dr. Yan Jiao purified total RNA using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204) all four batches.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well balanced sample of males and females, in general without within-strain-by-sex replication. Two strains are represented by a single male sample pool (BXD29 and A/J). Four lines are represented by two or three male sample pools (all of the five DeltaGen KO line). The SJL/J may be a single mixed sex sample. Users can study possible sex effects by comparing any results of expression data to that of a surrogate measurement that summarizes the overall sex balance of HEIMED. To do this just compare your data to those of probe sets 1427262_at (Xist, high in females) and probe set 1426438_at (Ddx3y, high in males). These two sex-specific probes are quantitative surrogates for the sex balance in this data set.
+
+Technical duplicates: One sample, highlighted in the tables below, is a technical duplicate. The pair of technical duplicates were both of high quality. For statistical analysis, they should be combined and treated as single biological sample.
+
+Batch structure: This data set consists of four batches (Table 2, far right column). The final September 2008 data set consists of a total of 221 arrays and 220 independent samples.
+
+
+ - Batch 1: November 2005, n = 78 arrays original arrays of which 76 were accepted into this final data set.
+ - Batch 2: January 2006, n = 62 arrays of which 62 were accepted.
+ - Batch 3: August 2006, n = 39 arrays of which 36 were accepted. (These three batches, including some arrays that were eventually dropped from the final 2008 data set, were combined to form the September 2006 data set.)
+ - Batch 4: Summer 2008, n = 53 arrays of which 47 were accepted.
+
+
+Table 1: HEIMED case IDs, including sample tube ID, strain, age, sex, and source of mice (see Table 2 for information on array quality control)
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ TubeID |
+ Group |
+ Strain |
+ Age |
+ Sex |
+ Source |
+
+
+ | 1 |
+ R2595E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 2 |
+ R2533E.1 |
+ GDP |
+ 129S1/SvImJ |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 3 |
+ R0754E.1 |
+ GDP |
+ A/J |
+ 60 |
+ M |
+ JAX |
+
+
+ | 4 |
+ R4521E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 5 |
+ R4522E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 6 |
+ R4523E |
+ KO |
+ B6129P2F2N1-Clcn3 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 7 |
+ R4526E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 8 |
+ R4509E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 16 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 9 |
+ R4510E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 10 |
+ R4511E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 20 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 11 |
+ R4524E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 19 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 12 |
+ R4525E |
+ KO |
+ B6129P2F2N1-Gabbr1 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 13 |
+ R4515E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 14 |
+ R4516E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 69 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 15 |
+ R4517E |
+ KO |
+ B6129P2F2N1-Gabra1 |
+ 67 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 16 |
+ R4512E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ F |
+ TChoi_Deltagen |
+
+
+ | 17 |
+ R4513E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 25 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 18 |
+ R4514E |
+ KO |
+ B6129P2F2N1-Gnb5 |
+ 22 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 19 |
+ R4518E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 70 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 20 |
+ R4519E |
+ KO |
+ B6129P2F2N1-Gpr19 |
+ 68 |
+ M |
+ TChoi_Deltagen |
+
+
+ | 21 |
+ R2601E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 22 |
+ R2602E.1 |
+ GDP BXD |
+ B6D2F1 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 23 |
+ R1676E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ F |
+ JAX |
+
+
+ | 24 |
+ R1672E.1 |
+ GDP |
+ BALB/cByJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 25 |
+ R4530E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 26 |
+ R4529E |
+ GDP |
+ BALB/cJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 27 |
+ R2704E.2 |
+ BXD |
+ BXD1 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 28 |
+ R2707E.3 |
+ BXD |
+ BXD1 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 29 |
+ R1231E.2 |
+ BXD |
+ BXD2 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 30 |
+ R2598E.1 |
+ BXD |
+ BXD2 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 31 |
+ R2591E.1 |
+ BXD |
+ BXD5 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 32 |
+ R2714E.2 |
+ BXD |
+ BXD5 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 33 |
+ R2570E.1 |
+ BXD |
+ BXD6 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 34 |
+ R2694E.2 |
+ BXD |
+ BXD6 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 35 |
+ R2538E.1 |
+ BXD |
+ BXD8 |
+ 77 |
+ F |
+ UTHSC RW |
+
+
+ | 36 |
+ R2709E.2 |
+ BXD |
+ BXD8 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 37 |
+ R2708E.2 |
+ BXD |
+ BXD9 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 38 |
+ R2569E.1 |
+ BXD |
+ BXD9 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 39 |
+ R2581E.1 |
+ BXD |
+ BXD11 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 40 |
+ R2612E.2 |
+ BXD |
+ BXD11 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 41 |
+ R2742E.2 |
+ BXD |
+ BXD12 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 42 |
+ R2543E.1 |
+ BXD |
+ BXD12 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 43 |
+ R2586E.1 |
+ BXD |
+ BXD13 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 44 |
+ R877E.2 |
+ BXD |
+ BXD13 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 45 |
+ R2557E.1 |
+ BXD |
+ BXD14 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 46 |
+ R1128E.2 |
+ BXD |
+ BXD14 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 47 |
+ R2701E.3 |
+ BXD |
+ BXD15 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 48 |
+ R2716E.2 |
+ BXD |
+ BXD15 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 49 |
+ R2711E.2 |
+ BXD |
+ BXD16 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 50 |
+ R2567E.1 |
+ BXD |
+ BXD16 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 51 |
+ R2720E.2 |
+ BXD |
+ BXD18 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 52 |
+ R2559E.1 |
+ BXD |
+ BXD18 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 53 |
+ R2560E.1 |
+ BXD |
+ BXD19 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 54 |
+ R2713E.2 |
+ BXD |
+ BXD19 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 55 |
+ R2584E.1 |
+ BXD |
+ BXD20 |
+ 59 |
+ F |
+ BIDMC GR |
+
+
+ | 56 |
+ R2731E.2 |
+ BXD |
+ BXD20 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 57 |
+ R2702E.2 |
+ BXD |
+ BXD21 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 58 |
+ R2541E2.1 |
+ BXD |
+ BXD21 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 59 |
+ R2553E.1 |
+ BXD |
+ BXD22 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 60 |
+ R2700E.2 |
+ BXD |
+ BXD22 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 61 |
+ R2558E-2.1 |
+ BXD |
+ BXD23 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 62 |
+ R1086E.2 |
+ BXD |
+ BXD23 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 63 |
+ R2719E.2 |
+ BXD |
+ BXD24 |
+ 123 |
+ F |
+ UTHSC RW |
+
+
+ | 64 |
+ R2589E2.1 |
+ BXD |
+ BXD24 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 65 |
+ R2573E-2.1 |
+ BXD |
+ BXD25 |
+ 67 |
+ F |
+ UAB |
+
+
+ | 66 |
+ R2683E.2 |
+ BXD |
+ BXD25 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 67 |
+ R2703E.2 |
+ BXD |
+ BXD27 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 68 |
+ R2729E.3 |
+ BXD |
+ BXD27 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 69 |
+ R2562E.3 |
+ BXD |
+ BXD28 |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 70 |
+ R2721E.2 |
+ BXD |
+ BXD28 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 71 |
+ R2561E.3 |
+ BXD |
+ BXD29 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 72 |
+ R1258E.2 |
+ BXD |
+ BXD31 |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 73 |
+ R2597E.1 |
+ BXD |
+ BXD31 |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 74 |
+ R2563E.1 |
+ BXD |
+ BXD32 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 75 |
+ R1216E.2 |
+ BXD |
+ BXD32 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 76 |
+ R2542E.1 |
+ BXD |
+ BXD33 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 77 |
+ R857E.2 |
+ BXD |
+ BXD33 |
+ 77 |
+ M |
+ UTHSC RW |
+
+
+ | 78 |
+ R1451E.2 |
+ BXD |
+ BXD34 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 79 |
+ R2585E.1 |
+ BXD |
+ BXD34 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 80 |
+ R2698E.3 |
+ BXD |
+ BXD36 |
+ 58 |
+ F |
+ BIDMC GR |
+
+
+ | 81 |
+ R2705E.3 |
+ BXD |
+ BXD36 |
+ 57 |
+ M |
+ BIDMC GR |
+
+
+ | 82 |
+ R2710E.2 |
+ BXD |
+ BXD38 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 83 |
+ R2532E.1 |
+ BXD |
+ BXD38 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 84 |
+ R2574E.1 |
+ BXD |
+ BXD39 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 85 |
+ R2695E.2 |
+ BXD |
+ BXD39 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 86 |
+ R2699E.2 |
+ BXD |
+ BXD40 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 87 |
+ R2590E.1 |
+ BXD |
+ BXD40 |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 88 |
+ R2696E.2 |
+ BXD |
+ BXD42 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 89 |
+ R2596E.1 |
+ BXD |
+ BXD42 |
+ 59 |
+ M |
+ BIDMC GR |
+
+
+ | 90 |
+ R994E.2 |
+ BXD |
+ BXD43 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 91 |
+ R2607E.1 |
+ BXD |
+ BXD43 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 92 |
+ R2594E.1 |
+ BXD |
+ BXD44 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 93 |
+ R2610E.2 |
+ BXD |
+ BXD44 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 94 |
+ R2732E.2 |
+ BXD |
+ BXD45 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 95 |
+ R2592E.1 |
+ BXD |
+ BXD45 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 96 |
+ R967E.2 |
+ BXD |
+ BXD48 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 97 |
+ R2606E.1 |
+ BXD |
+ BXD48 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 98 |
+ R2933E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 99 |
+ R2937E.3 |
+ BXD |
+ BXD50 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 100 |
+ R2603E.1 |
+ BXD |
+ BXD51 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 101 |
+ R1042E.2 |
+ BXD |
+ BXD51 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 102 |
+ R2980E.3 |
+ BXD |
+ BXD55 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 103 |
+ R2690E.2 |
+ BXD |
+ BXD55 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 104 |
+ R4176E |
+ BXD |
+ BXD56 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 105 |
+ R4175E |
+ BXD |
+ BXD56 |
+ 53 |
+ M |
+ UTHSC RW |
+
+
+ | 106 |
+ R1006E.3 |
+ BXD |
+ BXD60 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 107 |
+ R2725E.2 |
+ BXD |
+ BXD60 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 108 |
+ R1074E.3 |
+ BXD |
+ BXD60 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 109 |
+ R2534E2.1 |
+ BXD |
+ BXD61 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 110 |
+ R2684E.2 |
+ BXD |
+ BXD61 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 111 |
+ R1107E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ F |
+ UTHSC RW |
+
+
+ | 112 |
+ R2681E.2 |
+ BXD |
+ BXD62 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 113 |
+ R965E.3 |
+ BXD |
+ BXD62 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 114 |
+ R1425E.2 |
+ BXD |
+ BXD63 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 115 |
+ R2576E.3 |
+ BXD |
+ BXD63 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 116 |
+ R943E-2.2 |
+ BXD |
+ BXD64 |
+ 56 |
+ F |
+ UTHSC RW |
+
+
+ | 117 |
+ R2611E.1 |
+ BXD |
+ BXD64 |
+ 68 |
+ M |
+ UTHSC RW |
+
+
+ | 118 |
+ R2689E.2 |
+ BXD |
+ BXD65 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 119 |
+ R2583E.1 |
+ BXD |
+ BXD65 |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 120 |
+ R2728E.2 |
+ BXD |
+ BXD66 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 121 |
+ R2536E2.1 |
+ BXD |
+ BXD66 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 122 |
+ R1207E.2 |
+ BXD |
+ BXD66 |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 123 |
+ R1192E.2 |
+ BXD |
+ BXD67 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 124 |
+ R2727E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 125 |
+ R2691E.3 |
+ BXD |
+ BXD67 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 126 |
+ R2551E.1 |
+ BXD |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 127 |
+ R2726E.2 |
+ BXD |
+ BXD68 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 128 |
+ R2593E.1 |
+ BXD |
+ BXD69 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 129 |
+ R975E.2 |
+ BXD |
+ BXD70 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 130 |
+ R2537E2.1 |
+ BXD |
+ BXD70 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 131 |
+ R4531E |
+ BXD |
+ BXD71 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 132 |
+ R4532E |
+ BXD |
+ BXD71 |
+ 86 |
+ M |
+ UTHSC RW |
+
+
+ | 133 |
+ R2779E.2 |
+ BXD |
+ BXD73 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 134 |
+ R3024E.3 |
+ BXD |
+ BXD73 |
+ 54 |
+ M |
+ UTHSC RW |
+
+
+ | 135 |
+ R2565E.1 |
+ BXD |
+ BXD75 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 136 |
+ R1397E-re.2 |
+ BXD |
+ BXD75 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 137 |
+ R2687E.3 |
+ BXD |
+ BXD77 |
+ 60 |
+ F |
+ UTHSC RW |
+
+
+ | 138 |
+ R2717E.2 |
+ BXD |
+ BXD77 |
+ 107 |
+ M |
+ UTHSC RW |
+
+
+ | 139 |
+ R1421E.3 |
+ BXD |
+ BXD77 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 140 |
+ R2579E.1 |
+ BXD |
+ BXD80 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 141 |
+ R2686E.2 |
+ BXD |
+ BXD80 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 142 |
+ R2956E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 143 |
+ R2960E.3 |
+ BXD |
+ BXD83 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 144 |
+ R2922E.3 |
+ BXD |
+ BXD84 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 145 |
+ R2895E.3 |
+ BXD |
+ BXD84 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 146 |
+ R2692E.2 |
+ BXD |
+ BXD85 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 147 |
+ R2715E.2 |
+ BXD |
+ BXD85 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 148 |
+ R1405E.2 |
+ BXD |
+ BXD86 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 149 |
+ R1225E.3 |
+ BXD |
+ BXD86 |
+ 58 |
+ M |
+ UTHSC RW |
+
+
+ | 150 |
+ R2724E.2 |
+ BXD |
+ BXD87 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 151 |
+ R2540E.1 |
+ BXD |
+ BXD87 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 152 |
+ R1433E.2 |
+ BXD |
+ BXD89 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 153 |
+ R2546E.1 |
+ BXD |
+ BXD89 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 154 |
+ R2578E2.1 |
+ BXD |
+ BXD90 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 155 |
+ R859E.2 |
+ BXD |
+ BXD90 |
+ 72 |
+ M |
+ UTHSC RW |
+
+
+ | 156 |
+ R2682E.2 |
+ BXD |
+ BXD92 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 157 |
+ R1388E.3 |
+ BXD |
+ BXD92 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 158 |
+ R1322E.3 |
+ BXD |
+ BXD92 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 159 |
+ R2733E.2 |
+ BXD |
+ BXD96 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 160 |
+ R2554E.1 |
+ BXD |
+ BXD96 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 161 |
+ R2649E.2 |
+ BXD |
+ BXD97 |
+ 74 |
+ F |
+ UTHSC RW |
+
+
+ | 162 |
+ R2577E.1 |
+ BXD |
+ BXD97 |
+ 55 |
+ M |
+ UTHSC RW |
+
+
+ | 163 |
+ R2645E.3 |
+ BXD |
+ BXD98 |
+ 66 |
+ F |
+ UTHSC RW |
+
+
+ | 164 |
+ R2688E.2 |
+ BXD |
+ BXD98 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 165 |
+ R4533E |
+ BXD |
+ BXD99 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 166 |
+ R4534E |
+ BXD |
+ BXD99 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 167 |
+ R2885E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 168 |
+ R2883E.3 |
+ GDP |
+ BXSB/MpJ |
+ 61 |
+ M |
+ BIDMC GR |
+
+
+ | 169 |
+ R1700E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 170 |
+ R1704E.1 |
+ GDP |
+ C3H/HeJ |
+ 83 |
+ M |
+ UTHSC RW |
+
+
+ | 171 |
+ R2605E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 79 |
+ F |
+ UTHSC RW |
+
+
+ | 172 |
+ R0871E |
+ GDP BXD |
+ C57BL/6J |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 173 |
+ R0872E.1 |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 174 |
+ R0872E |
+ GDP BXD |
+ C57BL/6J |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 175 |
+ R4507E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 176 |
+ R4508E |
+ KO |
+ C57BL/6J-Nyx |
+ 57 |
+ M |
+ Geisert |
+
+
+ | 177 |
+ R4505E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 178 |
+ R4506E |
+ KO |
+ C57BL/6J-Rpe65 |
+ 57 |
+ F |
+ Geisert |
+
+
+ | 179 |
+ R4535E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ F |
+ JAX |
+
+
+ | 180 |
+ R4536E |
+ GDP |
+ C57BLKS/J |
+ 66 |
+ M |
+ JAX |
+
+
+ | 181 |
+ R2564E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ F |
+ JAX |
+
+
+ | 182 |
+ R2580E.1 |
+ GDP |
+ CAST/EiJ |
+ 64 |
+ M |
+ JAX |
+
+
+ | 183 |
+ R4537E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 184 |
+ R4538E |
+ GDP |
+ CBA/CaJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 185 |
+ R4539E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 186 |
+ R4540E |
+ GDP |
+ CZECHII/EiJ |
+ 66 |
+ M |
+ JAX |
+
+
+ | 187 |
+ R2600E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 188 |
+ R2604E.1 |
+ GDP BXD |
+ D2B6F1 |
+ 69 |
+ M |
+ UTHSC RW |
+
+
+ | 189 |
+ R1002E.3 |
+ GDP BXD |
+ DBA/2J |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 190 |
+ R4541E |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 191 |
+ R959E.3 |
+ GDP BXD |
+ DBA/2J |
+ 60 |
+ M |
+ UTHSC RW |
+
+
+ | 192 |
+ R2572E.1 |
+ GDP BXD |
+ DBA/2J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 193 |
+ R4542E |
+ GDP BXD |
+ DBA/2J |
+ 59 |
+ M |
+ JAX |
+
+
+ | 194 |
+ R2771E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 195 |
+ R2772E.3 |
+ GDP |
+ FVB/NJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 196 |
+ R2636E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 197 |
+ R2637E.1 |
+ GDP |
+ KK/HlJ |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 198 |
+ R0999E.1 |
+ GDP |
+ LG/J |
+ 57 |
+ F |
+ UTHSC RW |
+
+
+ | 199 |
+ R1004E.1 |
+ GDP |
+ LG/J |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 200 |
+ R4543E |
+ GDP |
+ LP/J |
+ 65 |
+ F |
+ JAX |
+
+
+ | 201 |
+ R4544E |
+ GDP |
+ LP/J |
+ 65 |
+ M |
+ JAX |
+
+
+ | 202 |
+ R2858E.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ F |
+ BIDMC GR |
+
+
+ | 203 |
+ R2919.3 |
+ GDP |
+ MOLF/EiJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 204 |
+ R1688E.1 |
+ GDP |
+ NOD/LtJ |
+ 66 |
+ F |
+ JAX |
+
+
+ | 205 |
+ R2566E-2.1 |
+ GDP |
+ NOD/LtJ |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 206 |
+ R4545E |
+ GDP |
+ NZB/BlNJ |
+ 61 |
+ F |
+ BIDMC GR |
+
+
+ | 207 |
+ R4546E |
+ GDP |
+ NZB/BlNJ |
+ 58 |
+ M |
+ BIDMC GR |
+
+
+ | 208 |
+ R2535E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 209 |
+ R2550E.1 |
+ GDP |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ JAX |
+
+
+ | 210 |
+ R2817E.3 |
+ GDP |
+ NZW/LacJ |
+ 65 |
+ F |
+ BIDMC GR |
+
+
+ | 211 |
+ R2810E |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 212 |
+ R2810E.3 |
+ GDP |
+ NZW/LacJ |
+ 60 |
+ M |
+ BIDMC GR |
+
+
+ | 213 |
+ R4547E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ F |
+ JAX |
+
+
+ | 214 |
+ R4548E |
+ GDP |
+ PANCEVO/EiJ |
+ 68 |
+ M |
+ JAX |
+
+
+ | 215 |
+ R2635E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ F |
+ JAX |
+
+
+ | 216 |
+ R2634E.1 |
+ GDP |
+ PWD/PhJ |
+ 62 |
+ M |
+ JAX |
+
+
+ | 217 |
+ R2544E.1 |
+ GDP |
+ PWK/PhJ |
+ 63 |
+ F |
+ JAX |
+
+
+ | 218 |
+ R2549E.1 |
+ GDP |
+ PWK/PhJ |
+ 83 |
+ M |
+ JAX |
+
+
+ | 219 |
+ R4550E |
+ GDP |
+ SJL/J |
+ 65 |
+ M+F |
+ JAX |
+
+
+ | 220 |
+ R2368E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 221 |
+ R2547E.1 |
+ GDP |
+ WSB/EiJ |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Grng_gse23545hlt0613/citation.rtf b/general/datasets/Grng_gse23545hlt0613/citation.rtf
new file mode 100644
index 0000000..2aafa46
--- /dev/null
+++ b/general/datasets/Grng_gse23545hlt0613/citation.rtf
@@ -0,0 +1 @@
+Bossé Y, Postma DS, Sin DD, Lamontagne M et al. Molecular signature of smoking in human lung tissues. Cancer Res 2012 Aug 1;72(15):3753-63. PMID: 22659451
diff --git a/general/datasets/Grng_gse23545hlt0613/contributors.rtf b/general/datasets/Grng_gse23545hlt0613/contributors.rtf
new file mode 100644
index 0000000..a22a4a5
--- /dev/null
+++ b/general/datasets/Grng_gse23545hlt0613/contributors.rtf
@@ -0,0 +1 @@
+Bossé Y, Laviolette M
diff --git a/general/datasets/Grng_gse23545hlt0613/summary.rtf b/general/datasets/Grng_gse23545hlt0613/summary.rtf
new file mode 100644
index 0000000..9cb9538
--- /dev/null
+++ b/general/datasets/Grng_gse23545hlt0613/summary.rtf
@@ -0,0 +1,15 @@
+This SuperSeries is composed of the following SubSeries:
+
+
+
+
+ | GSE23352 Whole-genome gene expression profiles of non-tumorous human lung tissues: Laval set |
+
+
+ | GSE23529 Whole-genome gene expression profiles of non-tumorous human lung tissues: UBC set |
+
+
+ | GSE23545 Whole-genome gene expression profiles of non-tumorous human lung tissues: GRNG set |
+
+
+
diff --git a/general/datasets/Gse15222_f_a_ri_0409/acknowledgment.rtf b/general/datasets/Gse15222_f_a_ri_0409/acknowledgment.rtf
new file mode 100644
index 0000000..c203ed9
--- /dev/null
+++ b/general/datasets/Gse15222_f_a_ri_0409/acknowledgment.rtf
@@ -0,0 +1 @@
+http://labs.med.miami.edu/myers
diff --git a/general/datasets/Gse15222_f_a_ri_0409/cases.rtf b/general/datasets/Gse15222_f_a_ri_0409/cases.rtf
new file mode 100644
index 0000000..6933d14
--- /dev/null
+++ b/general/datasets/Gse15222_f_a_ri_0409/cases.rtf
@@ -0,0 +1,3290 @@
+
+
+
+
+
+
+
+
+
+ | Index |
+ GEO Series |
+ Organ Region |
+ Tissue |
+ Case ID |
+ Age |
+ Sex |
+
+
+ | 1 |
+ GSM225652 |
+ Temporal Cortex |
+ Normal |
+ C225652M85N |
+ 85 |
+ M |
+
+
+ | 2 |
+ GSM225662 |
+ Temporal Cortex |
+ Normal |
+ C225662M85N |
+ 85 |
+ M |
+
+
+ | 3 |
+ GSM225664 |
+ Temporal Cortex |
+ Normal |
+ C225664F79N |
+ 79 |
+ F |
+
+
+ | 4 |
+ GSM225665 |
+ Temporal Cortex |
+ Normal |
+ C225665F85N |
+ 85 |
+ F |
+
+
+ | 5 |
+ GSM225666 |
+ Temporal Cortex |
+ Normal |
+ C225666F73N |
+ 73 |
+ F |
+
+
+ | 6 |
+ GSM225667 |
+ Temporal Cortex |
+ Normal |
+ C225667M81N |
+ 81 |
+ M |
+
+
+ | 7 |
+ GSM225668 |
+ Temporal Cortex |
+ Normal |
+ C225668M79N |
+ 79 |
+ M |
+
+
+ | 8 |
+ GSM225669 |
+ Temporal Cortex |
+ Normal |
+ C225669M77N |
+ 77 |
+ M |
+
+
+ | 9 |
+ GSM225670 |
+ Temporal Cortex |
+ Normal |
+ C225670M69N |
+ 69 |
+ M |
+
+
+ | 10 |
+ GSM225671 |
+ Temporal Cortex |
+ Normal |
+ C225671M86N |
+ 86 |
+ M |
+
+
+ | 11 |
+ GSM225672 |
+ Temporal Cortex |
+ Normal |
+ C225672F83N |
+ 83 |
+ F |
+
+
+ | 12 |
+ GSM225673 |
+ Temporal Cortex |
+ Normal |
+ C225673M78N |
+ 78 |
+ M |
+
+
+ | 13 |
+ GSM225674 |
+ Temporal Cortex |
+ Normal |
+ C225674M94N |
+ 94 |
+ M |
+
+
+ | 14 |
+ GSM225675 |
+ Temporal Cortex |
+ Normal |
+ C225675F81N |
+ 81 |
+ F |
+
+
+ | 15 |
+ GSM225676 |
+ Temporal Cortex |
+ Normal |
+ C225676M76N |
+ 76 |
+ M |
+
+
+ | 16 |
+ GSM225677 |
+ Temporal Cortex |
+ Normal |
+ C225677M83N |
+ 83 |
+ M |
+
+
+ | 17 |
+ GSM225678 |
+ Temporal Cortex |
+ Normal |
+ C225678M68N |
+ 68 |
+ M |
+
+
+ | 18 |
+ GSM225679 |
+ Temporal Cortex |
+ Normal |
+ C225679F82N |
+ 82 |
+ F |
+
+
+ | 19 |
+ GSM225680 |
+ Temporal Cortex |
+ Normal |
+ C225680F70N |
+ 70 |
+ F |
+
+
+ | 20 |
+ GSM225681 |
+ Temporal Cortex |
+ Normal |
+ C225681M86N |
+ 86 |
+ M |
+
+
+ | 21 |
+ GSM225682 |
+ Temporal Cortex |
+ Normal |
+ C225682M78N |
+ 78 |
+ M |
+
+
+ | 22 |
+ GSM225683 |
+ Temporal Cortex |
+ Normal |
+ C225683M82N |
+ 82 |
+ M |
+
+
+ | 23 |
+ GSM225684 |
+ Temporal Cortex |
+ Normal |
+ C225684F94N |
+ 94 |
+ F |
+
+
+ | 24 |
+ GSM225685 |
+ Temporal Cortex |
+ Normal |
+ C225685F87N |
+ 87 |
+ F |
+
+
+ | 25 |
+ GSM225686 |
+ Temporal Cortex |
+ Normal |
+ C225686M74N |
+ 74 |
+ M |
+
+
+ | 26 |
+ GSM225687 |
+ Temporal Cortex |
+ Normal |
+ C225687M85N |
+ 85 |
+ M |
+
+
+ | 27 |
+ GSM225688 |
+ Temporal Cortex |
+ Normal |
+ C225688M75N |
+ 75 |
+ M |
+
+
+ | 28 |
+ GSM225689 |
+ Temporal Cortex |
+ Normal |
+ C225689F86N |
+ 86 |
+ F |
+
+
+ | 29 |
+ GSM225690 |
+ Temporal Cortex |
+ Normal |
+ C225690M75N |
+ 75 |
+ M |
+
+
+ | 30 |
+ GSM225691 |
+ Temporal Cortex |
+ Normal |
+ C225691M81N |
+ 81 |
+ M |
+
+
+ | 31 |
+ GSM225692 |
+ Temporal Cortex |
+ Normal |
+ C225692F72N |
+ 72 |
+ F |
+
+
+ | 32 |
+ GSM225693 |
+ Temporal Cortex |
+ Normal |
+ C225693F81N |
+ 81 |
+ F |
+
+
+ | 33 |
+ GSM225695 |
+ Temporal Cortex |
+ Normal |
+ C225695M81N |
+ 81 |
+ M |
+
+
+ | 34 |
+ GSM225696 |
+ Temporal Cortex |
+ Normal |
+ C225696M81N |
+ 81 |
+ M |
+
+
+ | 35 |
+ GSM225697 |
+ Temporal Cortex |
+ Normal |
+ C225697M91N |
+ 91 |
+ M |
+
+
+ | 36 |
+ GSM225698 |
+ Temporal Cortex |
+ Normal |
+ C225698M84N |
+ 84 |
+ M |
+
+
+ | 37 |
+ GSM225699 |
+ Temporal Cortex |
+ Normal |
+ C225699M96N |
+ 96 |
+ M |
+
+
+ | 38 |
+ GSM225700 |
+ Temporal Cortex |
+ Normal |
+ C225700F97N |
+ 97 |
+ F |
+
+
+ | 39 |
+ GSM225701 |
+ Temporal Cortex |
+ Normal |
+ C225701M90N |
+ 90 |
+ M |
+
+
+ | 40 |
+ GSM225702 |
+ Temporal Cortex |
+ Normal |
+ C225702F67N |
+ 67 |
+ F |
+
+
+ | 41 |
+ GSM225703 |
+ Temporal Cortex |
+ Normal |
+ C225703F83N |
+ 83 |
+ F |
+
+
+ | 42 |
+ GSM225704 |
+ Temporal Cortex |
+ Normal |
+ C225704F82N |
+ 82 |
+ F |
+
+
+ | 43 |
+ GSM225705 |
+ Temporal Cortex |
+ Normal |
+ C225705F66N |
+ 66 |
+ F |
+
+
+ | 44 |
+ GSM225706 |
+ Temporal Cortex |
+ Normal |
+ C225706F72N |
+ 72 |
+ F |
+
+
+ | 45 |
+ GSM225707 |
+ Temporal Cortex |
+ Normal |
+ C225707F65N |
+ 65 |
+ F |
+
+
+ | 46 |
+ GSM225708 |
+ Temporal Cortex |
+ Normal |
+ C225708F75N |
+ 75 |
+ F |
+
+
+ | 47 |
+ GSM225709 |
+ Temporal Cortex |
+ Normal |
+ C225709F74N |
+ 74 |
+ F |
+
+
+ | 48 |
+ GSM225711 |
+ Temporal Cortex |
+ Normal |
+ C225711M68N |
+ 68 |
+ M |
+
+
+ | 49 |
+ GSM225713 |
+ Temporal Cortex |
+ Normal |
+ C225713F80N |
+ 80 |
+ F |
+
+
+ | 50 |
+ GSM225714 |
+ Temporal Cortex |
+ Normal |
+ C225714M80N |
+ 80 |
+ M |
+
+
+ | 51 |
+ GSM225715 |
+ Temporal Cortex |
+ Normal |
+ C225715M66N |
+ 66 |
+ M |
+
+
+ | 52 |
+ GSM225717 |
+ Temporal Cortex |
+ Normal |
+ C225717M88N |
+ 88 |
+ M |
+
+
+ | 53 |
+ GSM225718 |
+ Temporal Cortex |
+ Normal |
+ C225718F91N |
+ 91 |
+ F |
+
+
+ | 54 |
+ GSM225719 |
+ Temporal Cortex |
+ Normal |
+ C225719M73N |
+ 73 |
+ M |
+
+
+ | 55 |
+ GSM225720 |
+ Temporal Cortex |
+ Normal |
+ C225720M76N |
+ 76 |
+ M |
+
+
+ | 56 |
+ GSM225721 |
+ Temporal Cortex |
+ Normal |
+ C225721M75N |
+ 75 |
+ M |
+
+
+ | 57 |
+ GSM225722 |
+ Temporal Cortex |
+ Normal |
+ C225722F86N |
+ 86 |
+ F |
+
+
+ | 58 |
+ GSM225723 |
+ Temporal Cortex |
+ Normal |
+ C225723F72N |
+ 72 |
+ F |
+
+
+ | 59 |
+ GSM225724 |
+ Temporal Cortex |
+ Normal |
+ C225724M97N |
+ 97 |
+ M |
+
+
+ | 60 |
+ GSM225725 |
+ Temporal Cortex |
+ Normal |
+ C225725M86N |
+ 86 |
+ M |
+
+
+ | 61 |
+ GSM225726 |
+ Temporal Cortex |
+ Normal |
+ C225726M82N |
+ 82 |
+ M |
+
+
+ | 62 |
+ GSM225727 |
+ Temporal Cortex |
+ Normal |
+ C225727F95N |
+ 95 |
+ F |
+
+
+ | 63 |
+ GSM225728 |
+ Temporal Cortex |
+ Normal |
+ C225728F76N |
+ 76 |
+ F |
+
+
+ | 64 |
+ GSM225729 |
+ Temporal Cortex |
+ Normal |
+ C225729M76N |
+ 76 |
+ M |
+
+
+ | 65 |
+ GSM225730 |
+ Temporal Cortex |
+ Normal |
+ C225730M69N |
+ 69 |
+ M |
+
+
+ | 66 |
+ GSM225731 |
+ Temporal Cortex |
+ Normal |
+ C225731F80N |
+ 80 |
+ F |
+
+
+ | 67 |
+ GSM225732 |
+ Temporal Cortex |
+ Normal |
+ C225732F99N |
+ 99 |
+ F |
+
+
+ | 68 |
+ GSM225733 |
+ Temporal Cortex |
+ Normal |
+ C225733M68N |
+ 68 |
+ M |
+
+
+ | 69 |
+ GSM225734 |
+ Temporal Cortex |
+ Normal |
+ C225734M70N |
+ 70 |
+ M |
+
+
+ | 70 |
+ GSM225735 |
+ Temporal Cortex |
+ Normal |
+ C225735F87N |
+ 87 |
+ F |
+
+
+ | 71 |
+ GSM225736 |
+ Temporal Cortex |
+ Normal |
+ C225736F99N |
+ 99 |
+ F |
+
+
+ | 72 |
+ GSM225737 |
+ Temporal Cortex |
+ Normal |
+ C225737F88N |
+ 88 |
+ F |
+
+
+ | 73 |
+ GSM225739 |
+ Temporal Cortex |
+ Normal |
+ C225739M65N |
+ 65 |
+ M |
+
+
+ | 74 |
+ GSM225741 |
+ Temporal Cortex |
+ Normal |
+ C225741M82N |
+ 82 |
+ M |
+
+
+ | 75 |
+ GSM225742 |
+ Temporal Cortex |
+ Normal |
+ C225742F78N |
+ 78 |
+ F |
+
+
+ | 76 |
+ GSM225743 |
+ Temporal Cortex |
+ Normal |
+ C225743F85N |
+ 85 |
+ F |
+
+
+ | 77 |
+ GSM225744 |
+ Temporal Cortex |
+ Normal |
+ C225744F100N |
+ 100 |
+ F |
+
+
+ | 78 |
+ GSM225745 |
+ Temporal Cortex |
+ Normal |
+ C225745F87N |
+ 87 |
+ F |
+
+
+ | 79 |
+ GSM225746 |
+ Temporal Cortex |
+ Normal |
+ C225746F85N |
+ 85 |
+ F |
+
+
+ | 80 |
+ GSM225747 |
+ Temporal Cortex |
+ Normal |
+ C225747F97N |
+ 97 |
+ F |
+
+
+ | 81 |
+ GSM225748 |
+ Temporal Cortex |
+ Normal |
+ C225748M65N |
+ 65 |
+ M |
+
+
+ | 82 |
+ GSM225749 |
+ Temporal Cortex |
+ Normal |
+ C225749M65N |
+ 65 |
+ M |
+
+
+ | 83 |
+ GSM225751 |
+ Temporal Cortex |
+ Normal |
+ C225751F87N |
+ 87 |
+ F |
+
+
+ | 84 |
+ GSM225752 |
+ Temporal Cortex |
+ Normal |
+ C225752F85N |
+ 85 |
+ F |
+
+
+ | 85 |
+ GSM225753 |
+ Temporal Cortex |
+ Normal |
+ C225753M68N |
+ 68 |
+ M |
+
+
+ | 86 |
+ GSM225754 |
+ Temporal Cortex |
+ Normal |
+ C225754M71N |
+ 71 |
+ M |
+
+
+ | 87 |
+ GSM225755 |
+ Temporal Cortex |
+ Normal |
+ C225755F83N |
+ 83 |
+ F |
+
+
+ | 88 |
+ GSM225756 |
+ Temporal Cortex |
+ Normal |
+ C225756M76N |
+ 76 |
+ M |
+
+
+ | 89 |
+ GSM225757 |
+ Temporal Cortex |
+ Normal |
+ C225757M67N |
+ 67 |
+ M |
+
+
+ | 90 |
+ GSM225758 |
+ Temporal Cortex |
+ Normal |
+ C225758F100N |
+ 100 |
+ F |
+
+
+ | 91 |
+ GSM225759 |
+ Temporal Cortex |
+ Normal |
+ C225759M79N |
+ 79 |
+ M |
+
+
+ | 92 |
+ GSM225760 |
+ Temporal Cortex |
+ Normal |
+ C225760M74N |
+ 74 |
+ M |
+
+
+ | 93 |
+ GSM225761 |
+ Temporal Cortex |
+ Normal |
+ C225761F88N |
+ 88 |
+ F |
+
+
+ | 94 |
+ GSM225762 |
+ Temporal Cortex |
+ Normal |
+ C225762M70N |
+ 70 |
+ M |
+
+
+ | 95 |
+ GSM225763 |
+ Temporal Cortex |
+ Normal |
+ C225763F97N |
+ 97 |
+ F |
+
+
+ | 96 |
+ GSM225764 |
+ Temporal Cortex |
+ Normal |
+ C225764M69N |
+ 69 |
+ M |
+
+
+ | 97 |
+ GSM225915 |
+ Temporal Cortex |
+ Normal |
+ C225915F99N |
+ 99 |
+ F |
+
+
+ | 98 |
+ GSM225916 |
+ Temporal Cortex |
+ Normal |
+ C225916M81N |
+ 81 |
+ M |
+
+
+ | 99 |
+ GSM225917 |
+ Temporal Cortex |
+ Normal |
+ C225917F85N |
+ 85 |
+ F |
+
+
+ | 100 |
+ GSM225918 |
+ Temporal Cortex |
+ Normal |
+ C225918F82N |
+ 82 |
+ F |
+
+
+ | 101 |
+ GSM225919 |
+ Temporal Cortex |
+ Normal |
+ C225919M70N |
+ 70 |
+ M |
+
+
+ | 102 |
+ GSM225920 |
+ Temporal Cortex |
+ Normal |
+ C225920M73N |
+ 73 |
+ M |
+
+
+ | 103 |
+ GSM225921 |
+ Temporal Cortex |
+ Normal |
+ C225921M83N |
+ 83 |
+ M |
+
+
+ | 104 |
+ GSM225922 |
+ Temporal Cortex |
+ Normal |
+ C225922M74N |
+ 74 |
+ M |
+
+
+ | 105 |
+ GSM225923 |
+ Temporal Cortex |
+ Normal |
+ C225923M77N |
+ 77 |
+ M |
+
+
+ | 106 |
+ GSM225924 |
+ Temporal Cortex |
+ Normal |
+ C225924M81N |
+ 81 |
+ M |
+
+
+ | 107 |
+ GSM225925 |
+ Temporal Cortex |
+ Normal |
+ C225925M65N |
+ 65 |
+ M |
+
+
+ | 108 |
+ GSM225926 |
+ Temporal Cortex |
+ Normal |
+ C225926F73N |
+ 73 |
+ F |
+
+
+ | 109 |
+ GSM225927 |
+ Temporal Cortex |
+ Normal |
+ C225927F85N |
+ 85 |
+ F |
+
+
+ | 110 |
+ GSM225928 |
+ Temporal Cortex |
+ Normal |
+ C225928M69N |
+ 69 |
+ M |
+
+
+ | 111 |
+ GSM225929 |
+ Temporal Cortex |
+ Normal |
+ C225929M72N |
+ 72 |
+ M |
+
+
+ | 112 |
+ GSM225930 |
+ Temporal Cortex |
+ Normal |
+ C225930F76N |
+ 76 |
+ F |
+
+
+ | 113 |
+ GSM225931 |
+ Temporal Cortex |
+ Normal |
+ C225931M73N |
+ 73 |
+ M |
+
+
+ | 114 |
+ GSM225932 |
+ Temporal Cortex |
+ Normal |
+ C225932M66N |
+ 66 |
+ M |
+
+
+ | 115 |
+ GSM225933 |
+ Temporal Cortex |
+ Normal |
+ C225933F85N |
+ 85 |
+ F |
+
+
+ | 116 |
+ GSM225934 |
+ Temporal Cortex |
+ Normal |
+ C225934M87N |
+ 87 |
+ M |
+
+
+ | 117 |
+ GSM225935 |
+ Temporal Cortex |
+ Normal |
+ C225935F86N |
+ 86 |
+ F |
+
+
+ | 118 |
+ GSM225936 |
+ Temporal Cortex |
+ Normal |
+ C225936F73N |
+ 73 |
+ F |
+
+
+ | 119 |
+ GSM225937 |
+ Temporal Cortex |
+ Normal |
+ C225937M86N |
+ 86 |
+ M |
+
+
+ | 120 |
+ GSM225938 |
+ Temporal Cortex |
+ Normal |
+ C225938M72N |
+ 72 |
+ M |
+
+
+ | 121 |
+ GSM225939 |
+ Temporal Cortex |
+ Normal |
+ C225939F69N |
+ 69 |
+ F |
+
+
+ | 122 |
+ GSM225940 |
+ Temporal Cortex |
+ Normal |
+ C225940F88N |
+ 88 |
+ F |
+
+
+ | 123 |
+ GSM225941 |
+ Temporal Cortex |
+ Normal |
+ C225941M77N |
+ 77 |
+ M |
+
+
+ | 124 |
+ GSM225942 |
+ Temporal Cortex |
+ Normal |
+ C225942M96N |
+ 96 |
+ M |
+
+
+ | 125 |
+ GSM225943 |
+ Temporal Cortex |
+ Normal |
+ C225943F78N |
+ 78 |
+ F |
+
+
+ | 126 |
+ GSM225944 |
+ Temporal Cortex |
+ Normal |
+ C225944M77N |
+ 77 |
+ M |
+
+
+ | 127 |
+ GSM225945 |
+ Temporal Cortex |
+ Normal |
+ C225945F99N |
+ 99 |
+ F |
+
+
+ | 128 |
+ GSM225946 |
+ Temporal Cortex |
+ Normal |
+ C225946M78N |
+ 78 |
+ M |
+
+
+ | 129 |
+ GSM225947 |
+ Temporal Cortex |
+ Normal |
+ C225947F76N |
+ 76 |
+ F |
+
+
+ | 130 |
+ GSM225948 |
+ Temporal Cortex |
+ Normal |
+ C225948M78N |
+ 78 |
+ M |
+
+
+ | 131 |
+ GSM225949 |
+ Temporal Cortex |
+ Normal |
+ C225949F97N |
+ 97 |
+ F |
+
+
+ | 132 |
+ GSM225950 |
+ Temporal Cortex |
+ Normal |
+ C225950F86N |
+ 86 |
+ F |
+
+
+ | 133 |
+ GSM225951 |
+ Temporal Cortex |
+ Normal |
+ C225951M77N |
+ 77 |
+ M |
+
+
+ | 134 |
+ GSM225952 |
+ Temporal Cortex |
+ Normal |
+ C225952M87N |
+ 87 |
+ M |
+
+
+ | 135 |
+ GSM225953 |
+ Temporal Cortex |
+ Normal |
+ C225953F72N |
+ 72 |
+ F |
+
+
+ | 136 |
+ GSM225954 |
+ Temporal Cortex |
+ Normal |
+ C225954F91N |
+ 91 |
+ F |
+
+
+ | 137 |
+ GSM225955 |
+ Temporal Cortex |
+ Normal |
+ C225955F85N |
+ 85 |
+ F |
+
+
+ | 138 |
+ GSM225956 |
+ Temporal Cortex |
+ Normal |
+ C225956M88N |
+ 88 |
+ M |
+
+
+ | 139 |
+ GSM225957 |
+ Temporal Cortex |
+ Normal |
+ C225957F86N |
+ 86 |
+ F |
+
+
+ | 140 |
+ GSM225958 |
+ Temporal Cortex |
+ Normal |
+ C225958F93N |
+ 93 |
+ F |
+
+
+ | 141 |
+ GSM225959 |
+ Temporal Cortex |
+ Normal |
+ C225959M82N |
+ 82 |
+ M |
+
+
+ | 142 |
+ GSM225961 |
+ Temporal Cortex |
+ Normal |
+ C225961F72N |
+ 72 |
+ F |
+
+
+ | 143 |
+ GSM225962 |
+ Temporal Cortex |
+ Normal |
+ C225962F85N |
+ 85 |
+ F |
+
+
+ | 144 |
+ GSM225963 |
+ Temporal Cortex |
+ Normal |
+ C225963M70N |
+ 70 |
+ M |
+
+
+ | 145 |
+ GSM225964 |
+ Temporal Cortex |
+ Normal |
+ C225964F67N |
+ 67 |
+ F |
+
+
+ | 146 |
+ GSM225965 |
+ Temporal Cortex |
+ Normal |
+ C225965F74N |
+ 74 |
+ F |
+
+
+ | 147 |
+ GSM226034 |
+ Temporal Cortex |
+ Normal |
+ C226034M69N |
+ 69 |
+ M |
+
+
+ | 148 |
+ GSM226035 |
+ Temporal Cortex |
+ Normal |
+ C226035M85N |
+ 85 |
+ M |
+
+
+ | 149 |
+ GSM226037 |
+ Temporal Cortex |
+ Normal |
+ C226037M89N |
+ 89 |
+ M |
+
+
+ | 150 |
+ GSM226038 |
+ Temporal Cortex |
+ Normal |
+ C226038M86N |
+ 86 |
+ M |
+
+
+ | 151 |
+ GSM226039 |
+ Temporal Cortex |
+ Normal |
+ C226039M90N |
+ 90 |
+ M |
+
+
+ | 152 |
+ GSM226040 |
+ Temporal Cortex |
+ Normal |
+ C226040F94N |
+ 94 |
+ F |
+
+
+ | 153 |
+ GSM226041 |
+ Temporal Cortex |
+ Normal |
+ C226041F91N |
+ 91 |
+ F |
+
+
+ | 154 |
+ GSM226042 |
+ Temporal Cortex |
+ Normal |
+ C226042F91N |
+ 91 |
+ F |
+
+
+ | 155 |
+ GSM226044 |
+ Temporal Cortex |
+ Normal |
+ C226044F95N |
+ 95 |
+ F |
+
+
+ | 156 |
+ GSM226045 |
+ Temporal Cortex |
+ Normal |
+ C226045F95N |
+ 95 |
+ F |
+
+
+ | 157 |
+ GSM226046 |
+ Temporal Cortex |
+ Normal |
+ C226046F91N |
+ 91 |
+ F |
+
+
+ | 158 |
+ GSM226047 |
+ Temporal Cortex |
+ Normal |
+ C226047M80N |
+ 80 |
+ M |
+
+
+ | 159 |
+ GSM226048 |
+ Temporal Cortex |
+ Normal |
+ C226048M83N |
+ 83 |
+ M |
+
+
+ | 160 |
+ GSM226049 |
+ Temporal Cortex |
+ Normal |
+ C226049M67N |
+ 67 |
+ M |
+
+
+ | 161 |
+ GSM226050 |
+ Temporal Cortex |
+ Normal |
+ C226050M76N |
+ 76 |
+ M |
+
+
+ | 162 |
+ GSM226051 |
+ Temporal Cortex |
+ Normal |
+ C226051F86N |
+ 86 |
+ F |
+
+
+ | 163 |
+ GSM226052 |
+ Temporal Cortex |
+ Normal |
+ C226052F86N |
+ 86 |
+ F |
+
+
+ | 164 |
+ GSM226053 |
+ Temporal Cortex |
+ Normal |
+ C226053M83N |
+ 83 |
+ M |
+
+
+ | 165 |
+ GSM226055 |
+ Temporal Cortex |
+ Normal |
+ C226055M84N |
+ 84 |
+ M |
+
+
+ | 166 |
+ GSM226056 |
+ Temporal Cortex |
+ Normal |
+ C226056M80N |
+ 80 |
+ M |
+
+
+ | 167 |
+ GSM226082 |
+ Temporal Cortex |
+ Normal |
+ C226082M72N |
+ 72 |
+ M |
+
+
+ | 168 |
+ GSM226145 |
+ Temporal Cortex |
+ Normal |
+ C226145M67N |
+ 67 |
+ M |
+
+
+ | 169 |
+ GSM226146 |
+ Temporal Cortex |
+ Normal |
+ C226146F96N |
+ 96 |
+ F |
+
+
+ | 170 |
+ GSM226147 |
+ Temporal Cortex |
+ Normal |
+ C226147F75N |
+ 75 |
+ F |
+
+
+ | 171 |
+ GSM226148 |
+ Temporal Cortex |
+ Normal |
+ C226148F89N |
+ 89 |
+ F |
+
+
+ | 172 |
+ GSM226149 |
+ Temporal Cortex |
+ Normal |
+ C226149F86N |
+ 86 |
+ F |
+
+
+ | 173 |
+ GSM226150 |
+ Temporal Cortex |
+ Normal |
+ C226150M67N |
+ 67 |
+ M |
+
+
+ | 174 |
+ GSM226151 |
+ Temporal Cortex |
+ Normal |
+ C226151M77N |
+ 77 |
+ M |
+
+
+ | 175 |
+ GSM226154 |
+ Temporal Cortex |
+ Normal |
+ C226154M65N |
+ 65 |
+ M |
+
+
+ | 176 |
+ GSM226155 |
+ Temporal Cortex |
+ Normal |
+ C226155M69N |
+ 69 |
+ M |
+
+
+ | 177 |
+ GSM226156 |
+ Temporal Cortex |
+ Normal |
+ C226156M84N |
+ 84 |
+ M |
+
+
+ | 178 |
+ GSM226157 |
+ Temporal Cortex |
+ Normal |
+ C226157F85N |
+ 85 |
+ F |
+
+
+ | 179 |
+ GSM226158 |
+ Temporal Cortex |
+ Normal |
+ C226158M94N |
+ 94 |
+ M |
+
+
+ | 180 |
+ GSM226159 |
+ Temporal Cortex |
+ Normal |
+ C226159F89N |
+ 89 |
+ F |
+
+
+ | 181 |
+ GSM226160 |
+ Temporal Cortex |
+ Normal |
+ C226160M87N |
+ 87 |
+ M |
+
+
+ | 182 |
+ GSM226162 |
+ Temporal Cortex |
+ Normal |
+ C226162M90N |
+ 90 |
+ M |
+
+
+ | 183 |
+ GSM226163 |
+ Temporal Cortex |
+ Normal |
+ C226163F88N |
+ 88 |
+ F |
+
+
+ | 184 |
+ GSM226164 |
+ Temporal Cortex |
+ Normal |
+ C226164M94N |
+ 94 |
+ M |
+
+
+ | 185 |
+ GSM226165 |
+ Temporal Cortex |
+ Normal |
+ C226165F86N |
+ 86 |
+ F |
+
+
+ | 186 |
+ GSM226167 |
+ Temporal Cortex |
+ Normal |
+ C226167F93N |
+ 93 |
+ F |
+
+
+ | 187 |
+ GSM226168 |
+ Temporal Cortex |
+ Normal |
+ C226168M91N |
+ 91 |
+ M |
+
+
+ | 188 |
+ GSM388217 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388217F97A |
+ 97 |
+ F |
+
+
+ | 189 |
+ GSM388218 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388218F101A |
+ 101 |
+ F |
+
+
+ | 190 |
+ GSM388219 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388219M84A |
+ 84 |
+ M |
+
+
+ | 191 |
+ GSM388220 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388220F95A |
+ 95 |
+ F |
+
+
+ | 192 |
+ GSM388221 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388221F97A |
+ 97 |
+ F |
+
+
+ | 193 |
+ GSM388222 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388222F102A |
+ 102 |
+ F |
+
+
+ | 194 |
+ GSM388223 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388223M87A |
+ 87 |
+ M |
+
+
+ | 195 |
+ GSM388224 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388224F77A |
+ 77 |
+ F |
+
+
+ | 196 |
+ GSM388225 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388225M87A |
+ 87 |
+ M |
+
+
+ | 197 |
+ GSM388226 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388226M84A |
+ 84 |
+ M |
+
+
+ | 198 |
+ GSM388228 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388228F92A |
+ 92 |
+ F |
+
+
+ | 199 |
+ GSM388229 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388229M93A |
+ 93 |
+ M |
+
+
+ | 200 |
+ GSM388230 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388230F93A |
+ 93 |
+ F |
+
+
+ | 201 |
+ GSM388231 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388231F87A |
+ 87 |
+ F |
+
+
+ | 202 |
+ GSM388232 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388232F90A |
+ 90 |
+ F |
+
+
+ | 203 |
+ GSM388233 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388233M75A |
+ 75 |
+ M |
+
+
+ | 204 |
+ GSM388234 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388234M92A |
+ 92 |
+ M |
+
+
+ | 205 |
+ GSM388235 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388235M83A |
+ 83 |
+ M |
+
+
+ | 206 |
+ GSM388236 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388236M88A |
+ 88 |
+ M |
+
+
+ | 207 |
+ GSM388237 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388237M89A |
+ 89 |
+ M |
+
+
+ | 208 |
+ GSM388238 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388238F74A |
+ 74 |
+ F |
+
+
+ | 209 |
+ GSM388239 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388239F79A |
+ 79 |
+ F |
+
+
+ | 210 |
+ GSM388240 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388240M80A |
+ 80 |
+ M |
+
+
+ | 211 |
+ GSM388241 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388241F97A |
+ 97 |
+ F |
+
+
+ | 212 |
+ GSM388242 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388242M87A |
+ 87 |
+ M |
+
+
+ | 213 |
+ GSM388243 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388243F89A |
+ 89 |
+ F |
+
+
+ | 214 |
+ GSM388244 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388244F90A |
+ 90 |
+ F |
+
+
+ | 215 |
+ GSM388245 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388245M90A |
+ 90 |
+ M |
+
+
+ | 216 |
+ GSM388246 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388246M78A |
+ 78 |
+ M |
+
+
+ | 217 |
+ GSM388247 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388247F80A |
+ 80 |
+ F |
+
+
+ | 218 |
+ GSM388248 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388248F79A |
+ 79 |
+ F |
+
+
+ | 219 |
+ GSM388249 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388249F87A |
+ 87 |
+ F |
+
+
+ | 220 |
+ GSM388250 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388250F88A |
+ 88 |
+ F |
+
+
+ | 221 |
+ GSM388251 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388251M86A |
+ 86 |
+ M |
+
+
+ | 222 |
+ GSM388252 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388252F74A |
+ 74 |
+ F |
+
+
+ | 223 |
+ GSM388253 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388253F72A |
+ 72 |
+ F |
+
+
+ | 224 |
+ GSM388254 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388254M81A |
+ 81 |
+ M |
+
+
+ | 225 |
+ GSM388255 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388255F68A |
+ 68 |
+ F |
+
+
+ | 226 |
+ GSM388256 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388256F81A |
+ 81 |
+ F |
+
+
+ | 227 |
+ GSM388257 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388257F82A |
+ 82 |
+ F |
+
+
+ | 228 |
+ GSM388258 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388258M78A |
+ 78 |
+ M |
+
+
+ | 229 |
+ GSM388259 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388259M74A |
+ 74 |
+ M |
+
+
+ | 230 |
+ GSM388260 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388260M88A |
+ 88 |
+ M |
+
+
+ | 231 |
+ GSM388261 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388261F78A |
+ 78 |
+ F |
+
+
+ | 232 |
+ GSM388262 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388262M83A |
+ 83 |
+ M |
+
+
+ | 233 |
+ GSM388263 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388263M83A |
+ 83 |
+ M |
+
+
+ | 234 |
+ GSM388264 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388264M80A |
+ 80 |
+ M |
+
+
+ | 235 |
+ GSM388265 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388265M84A |
+ 84 |
+ M |
+
+
+ | 236 |
+ GSM388266 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388266F79A |
+ 79 |
+ F |
+
+
+ | 237 |
+ GSM388267 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388267F86A |
+ 86 |
+ F |
+
+
+ | 238 |
+ GSM388268 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388268M92A |
+ 92 |
+ M |
+
+
+ | 239 |
+ GSM388269 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388269F81A |
+ 81 |
+ F |
+
+
+ | 240 |
+ GSM388270 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388270F79A |
+ 79 |
+ F |
+
+
+ | 241 |
+ GSM388271 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388271M74A |
+ 74 |
+ M |
+
+
+ | 242 |
+ GSM388272 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388272F73A |
+ 73 |
+ F |
+
+
+ | 243 |
+ GSM388273 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388273M87A |
+ 87 |
+ M |
+
+
+ | 244 |
+ GSM388274 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388274F86A |
+ 86 |
+ F |
+
+
+ | 245 |
+ GSM388275 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388275F86A |
+ 86 |
+ F |
+
+
+ | 246 |
+ GSM388276 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388276F87A |
+ 87 |
+ F |
+
+
+ | 247 |
+ GSM388277 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388277F92A |
+ 92 |
+ F |
+
+
+ | 248 |
+ GSM388278 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388278F78A |
+ 78 |
+ F |
+
+
+ | 249 |
+ GSM388279 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388279F94A |
+ 94 |
+ F |
+
+
+ | 250 |
+ GSM388281 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388281F94A |
+ 94 |
+ F |
+
+
+ | 251 |
+ GSM388282 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388282M76A |
+ 76 |
+ M |
+
+
+ | 252 |
+ GSM388284 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388284M91A |
+ 91 |
+ M |
+
+
+ | 253 |
+ GSM388285 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388285M86A |
+ 86 |
+ M |
+
+
+ | 254 |
+ GSM388286 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388286M77A |
+ 77 |
+ M |
+
+
+ | 255 |
+ GSM388287 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388287M82A |
+ 82 |
+ M |
+
+
+ | 256 |
+ GSM388288 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388288M78A |
+ 78 |
+ M |
+
+
+ | 257 |
+ GSM388289 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388289M79A |
+ 79 |
+ M |
+
+
+ | 258 |
+ GSM388290 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388290F84A |
+ 84 |
+ F |
+
+
+ | 259 |
+ GSM388291 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388291F87A |
+ 87 |
+ F |
+
+
+ | 260 |
+ GSM388292 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388292F86A |
+ 86 |
+ F |
+
+
+ | 261 |
+ GSM388294 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388294M83A |
+ 83 |
+ M |
+
+
+ | 262 |
+ GSM388295 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388295M83A |
+ 83 |
+ M |
+
+
+ | 263 |
+ GSM388296 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388296M81A |
+ 81 |
+ M |
+
+
+ | 264 |
+ GSM388297 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388297F93A |
+ 93 |
+ F |
+
+
+ | 265 |
+ GSM388298 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388298M71A |
+ 71 |
+ M |
+
+
+ | 266 |
+ GSM388299 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388299M78A |
+ 78 |
+ M |
+
+
+ | 267 |
+ GSM388300 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388300F75A |
+ 75 |
+ F |
+
+
+ | 268 |
+ GSM388301 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388301F84A |
+ 84 |
+ F |
+
+
+ | 269 |
+ GSM388302 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388302M73A |
+ 73 |
+ M |
+
+
+ | 270 |
+ GSM388303 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388303F89A |
+ 89 |
+ F |
+
+
+ | 271 |
+ GSM388304 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388304FNAA |
+ NA |
+ F |
+
+
+ | 272 |
+ GSM388305 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388305M69A |
+ 69 |
+ M |
+
+
+ | 273 |
+ GSM388306 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388306M83A |
+ 83 |
+ M |
+
+
+ | 274 |
+ GSM388307 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388307M71A |
+ 71 |
+ M |
+
+
+ | 275 |
+ GSM388308 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388308F86A |
+ 86 |
+ F |
+
+
+ | 276 |
+ GSM388309 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388309M82A |
+ 82 |
+ M |
+
+
+ | 277 |
+ GSM388310 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388310FNAA |
+ NA |
+ F |
+
+
+ | 278 |
+ GSM388311 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388311M88A |
+ 88 |
+ M |
+
+
+ | 279 |
+ GSM388312 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388312M77A |
+ 77 |
+ M |
+
+
+ | 280 |
+ GSM388313 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388313M85A |
+ 85 |
+ M |
+
+
+ | 281 |
+ GSM388314 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388314F81A |
+ 81 |
+ F |
+
+
+ | 282 |
+ GSM388315 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388315F86A |
+ 86 |
+ F |
+
+
+ | 283 |
+ GSM388316 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388316M89A |
+ 89 |
+ M |
+
+
+ | 284 |
+ GSM388317 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388317F73A |
+ 73 |
+ F |
+
+
+ | 285 |
+ GSM388318 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388318F96A |
+ 96 |
+ F |
+
+
+ | 286 |
+ GSM388319 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388319M73A |
+ 73 |
+ M |
+
+
+ | 287 |
+ GSM388320 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388320M81A |
+ 81 |
+ M |
+
+
+ | 288 |
+ GSM388321 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388321F84A |
+ 84 |
+ F |
+
+
+ | 289 |
+ GSM388322 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388322F93A |
+ 93 |
+ F |
+
+
+ | 290 |
+ GSM388323 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388323F82A |
+ 82 |
+ F |
+
+
+ | 291 |
+ GSM388324 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388324M76A |
+ 76 |
+ M |
+
+
+ | 292 |
+ GSM388325 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388325M77A |
+ 77 |
+ M |
+
+
+ | 293 |
+ GSM388326 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388326F86A |
+ 86 |
+ F |
+
+
+ | 294 |
+ GSM388327 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388327F85A |
+ 85 |
+ F |
+
+
+ | 295 |
+ GSM388328 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388328M83A |
+ 83 |
+ M |
+
+
+ | 296 |
+ GSM388329 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388329M76A |
+ 76 |
+ M |
+
+
+ | 297 |
+ GSM388330 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388330M81A |
+ 81 |
+ M |
+
+
+ | 298 |
+ GSM388331 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388331M79A |
+ 79 |
+ M |
+
+
+ | 299 |
+ GSM388332 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388332M81A |
+ 81 |
+ M |
+
+
+ | 300 |
+ GSM388333 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388333F78A |
+ 78 |
+ F |
+
+
+ | 301 |
+ GSM388334 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388334M80A |
+ 80 |
+ M |
+
+
+ | 302 |
+ GSM388335 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388335M84A |
+ 84 |
+ M |
+
+
+ | 303 |
+ GSM388336 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388336F85A |
+ 85 |
+ F |
+
+
+ | 304 |
+ GSM388337 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388337M75A |
+ 75 |
+ M |
+
+
+ | 305 |
+ GSM388338 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388338F80A |
+ 80 |
+ F |
+
+
+ | 306 |
+ GSM388339 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388339F97A |
+ 97 |
+ F |
+
+
+ | 307 |
+ GSM388340 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388340F82A |
+ 82 |
+ F |
+
+
+ | 308 |
+ GSM388341 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388341M82A |
+ 82 |
+ M |
+
+
+ | 309 |
+ GSM388342 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388342M77A |
+ 77 |
+ M |
+
+
+ | 310 |
+ GSM388343 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388343M81A |
+ 81 |
+ M |
+
+
+ | 311 |
+ GSM388345 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388345F96A |
+ 96 |
+ F |
+
+
+ | 312 |
+ GSM388346 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388346F90A |
+ 90 |
+ F |
+
+
+ | 313 |
+ GSM388347 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388347M86A |
+ 86 |
+ M |
+
+
+ | 314 |
+ GSM388348 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388348M88A |
+ 88 |
+ M |
+
+
+ | 315 |
+ GSM388349 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388349F90A |
+ 90 |
+ F |
+
+
+ | 316 |
+ GSM388350 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388350F90A |
+ 90 |
+ F |
+
+
+ | 317 |
+ GSM388351 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388351F84A |
+ 84 |
+ F |
+
+
+ | 318 |
+ GSM388352 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388352M84A |
+ 84 |
+ M |
+
+
+ | 319 |
+ GSM388353 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388353F91A |
+ 91 |
+ F |
+
+
+ | 320 |
+ GSM388354 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388354F81A |
+ 81 |
+ F |
+
+
+ | 321 |
+ GSM388355 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388355F84A |
+ 84 |
+ F |
+
+
+ | 322 |
+ GSM388356 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388356M80A |
+ 80 |
+ M |
+
+
+ | 323 |
+ GSM388357 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388357M81A |
+ 81 |
+ M |
+
+
+ | 324 |
+ GSM388358 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388358F87A |
+ 87 |
+ F |
+
+
+ | 325 |
+ GSM388359 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388359M85A |
+ 85 |
+ M |
+
+
+ | 326 |
+ GSM388360 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388360F90A |
+ 90 |
+ F |
+
+
+ | 327 |
+ GSM388361 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388361M79A |
+ 79 |
+ M |
+
+
+ | 328 |
+ GSM388362 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388362F87A |
+ 87 |
+ F |
+
+
+ | 329 |
+ GSM388363 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388363M75A |
+ 75 |
+ M |
+
+
+ | 330 |
+ GSM388364 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388364F92A |
+ 92 |
+ F |
+
+
+ | 331 |
+ GSM388365 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388365F84A |
+ 84 |
+ F |
+
+
+ | 332 |
+ GSM388366 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388366M75A |
+ 75 |
+ M |
+
+
+ | 333 |
+ GSM388367 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388367F76A |
+ 76 |
+ F |
+
+
+ | 334 |
+ GSM388368 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388368F86A |
+ 86 |
+ F |
+
+
+ | 335 |
+ GSM388369 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388369M82A |
+ 82 |
+ M |
+
+
+ | 336 |
+ GSM388370 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388370M76A |
+ 76 |
+ M |
+
+
+ | 337 |
+ GSM388371 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388371F81A |
+ 81 |
+ F |
+
+
+ | 338 |
+ GSM388372 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388372F80A |
+ 80 |
+ F |
+
+
+ | 339 |
+ GSM388373 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388373M83A |
+ 83 |
+ M |
+
+
+ | 340 |
+ GSM388374 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388374F83A |
+ 83 |
+ F |
+
+
+ | 341 |
+ GSM388375 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388375F84A |
+ 84 |
+ F |
+
+
+ | 342 |
+ GSM388376 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388376M93A |
+ 93 |
+ M |
+
+
+ | 343 |
+ GSM388377 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388377F92A |
+ 92 |
+ F |
+
+
+ | 344 |
+ GSM388378 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388378M78A |
+ 78 |
+ M |
+
+
+ | 345 |
+ GSM388379 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388379M90A |
+ 90 |
+ M |
+
+
+ | 346 |
+ GSM388380 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388380M83A |
+ 83 |
+ M |
+
+
+ | 347 |
+ GSM388381 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388381M79A |
+ 79 |
+ M |
+
+
+ | 348 |
+ GSM388382 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388382M84A |
+ 84 |
+ M |
+
+
+ | 349 |
+ GSM388383 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388383F90A |
+ 90 |
+ F |
+
+
+ | 350 |
+ GSM388384 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388384F88A |
+ 88 |
+ F |
+
+
+ | 351 |
+ GSM388385 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388385M77A |
+ 77 |
+ M |
+
+
+ | 352 |
+ GSM388386 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388386F80A |
+ 80 |
+ F |
+
+
+ | 353 |
+ GSM388387 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388387M87A |
+ 87 |
+ M |
+
+
+ | 354 |
+ GSM388388 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388388M86A |
+ 86 |
+ M |
+
+
+ | 355 |
+ GSM388389 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388389M74A |
+ 74 |
+ M |
+
+
+ | 356 |
+ GSM388390 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388390F86A |
+ 86 |
+ F |
+
+
+ | 357 |
+ GSM388391 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388391F81A |
+ 81 |
+ F |
+
+
+ | 358 |
+ GSM388392 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388392F73A |
+ 73 |
+ F |
+
+
+ | 359 |
+ GSM388393 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388393M83A |
+ 83 |
+ M |
+
+
+ | 360 |
+ GSM388394 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388394M86A |
+ 86 |
+ M |
+
+
+ | 361 |
+ GSM388395 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388395F86A |
+ 86 |
+ F |
+
+
+ | 362 |
+ GSM388396 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388396M78A |
+ 78 |
+ M |
+
+
+ | 363 |
+ GSM388397 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388397M83A |
+ 83 |
+ M |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Gse15222_f_a_ri_0409/contributors.rtf b/general/datasets/Gse15222_f_a_ri_0409/contributors.rtf
new file mode 100644
index 0000000..72c2296
--- /dev/null
+++ b/general/datasets/Gse15222_f_a_ri_0409/contributors.rtf
@@ -0,0 +1 @@
+Webster J, Gibbs R, Myers A
diff --git a/general/datasets/Gse15222_f_a_ri_0409/experiment-design.rtf b/general/datasets/Gse15222_f_a_ri_0409/experiment-design.rtf
new file mode 100644
index 0000000..07d1b52
--- /dev/null
+++ b/general/datasets/Gse15222_f_a_ri_0409/experiment-design.rtf
@@ -0,0 +1,5 @@
+Expression profiling by array
+
+We recently surveyed the relationship between the human brain transcriptome and genome in a series of neuropathologically normal postmortem samples. We now have analyzed additional samples with a confirmed pathologic diagnosis of late onset Alzheimer's disease (LOAD, final n=187 controls, 176 cases). Nine percent of the cortical transcripts we analyzed had expression profiles correlated with their genotypes in the combined cohort and approximately 5% of transcripts had SNP-transcript relationships that could distinguish LOAD samples. Two of these transcripts have been previously implicated in LOAD candidate gene SNP-expression screens. This study shows how the relationship between common inherited genetic variants and brain transcript expression can be used in the study of human brain disorders. We suggest that studying the transcriptome as a quantitative endo-phenotype has greater power to find risk SNPs influencing expression than the use of discrete diagnostic categories such as presence or absence of disease. see DOI:10.1016/j.ajhg.2009.03.011 for further details and complete author list.
+
+Expression quantitative trait loci study using human brain from 363 cortical samples. Affymetrix 500K chip for genotyping, Illumina Sentrix Human-ref 8 bead array chip for expression. Genotyping data will be available at dbGAP.
diff --git a/general/datasets/Gse15222_f_a_ri_0409/experiment-type.rtf b/general/datasets/Gse15222_f_a_ri_0409/experiment-type.rtf
new file mode 100644
index 0000000..0546e04
--- /dev/null
+++ b/general/datasets/Gse15222_f_a_ri_0409/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array
\ No newline at end of file
diff --git a/general/datasets/Gse15222_f_a_ri_0409/notes.rtf b/general/datasets/Gse15222_f_a_ri_0409/notes.rtf
new file mode 100644
index 0000000..e7bd85c
--- /dev/null
+++ b/general/datasets/Gse15222_f_a_ri_0409/notes.rtf
@@ -0,0 +1,6 @@
+Access to the original data from Dr. Myers' laboratory
+or GEO GSE15222
+PMI = Post Mortem Interval
+Cannot find this record in the GEO website: WGACON-120
+
+This data is based on May 2004 (NCBI35/hg17).
diff --git a/general/datasets/Gse15222_f_a_ri_0409/platform.rtf b/general/datasets/Gse15222_f_a_ri_0409/platform.rtf
new file mode 100644
index 0000000..5bcda8b
--- /dev/null
+++ b/general/datasets/Gse15222_f_a_ri_0409/platform.rtf
@@ -0,0 +1,5 @@
+Illumina Human 50 mer probes. Total of 24357 probes according to Myers et al. A total of 24354 probes included in this GeneNetwork file.
+
+From the Methods section of the paper:
+
+Genotyping and Expression Proï¬ling DNA was hybridized to the Affymetrix GeneChip Human Mapping 500K Array Set (502,627 SNPs) as previously described.11,12 Genotypes were extracted with the use of both SNiPer-HD13 and BRLMM (Affymetrix, Santa Clara, CA) algorithms. Genotypes that exhibited less than 98% concordance between calls were excluded. SNPs with call rates less than 90% were excluded from the analysis. HardyWeinberg equilibrium (HWE) was assessed with exact tests and the PLINK analysis toolset.14 SNPs with HWE exact-test p values less than 0.05, as well as SNPs with minor-allele frequencies less than 1%, were excluded. Allele calls had a mean of 97% and a range of 90%–99%. cRNA was hybridized to Illumina Human Refseq-8 Expression BeadChip (24,357 transcripts) via standard protocols. Expression proï¬les were extracted and rank invariant normalized15–17 with the use of the BeadStudio software available from Illumina, with the Illumina custom error model used. Rankinvariant-normalized expression data were log10 transformed, and missing data were encoded as missing, rather than as a zero level of expression.
diff --git a/general/datasets/Gse15222_f_a_ri_0409/summary.rtf b/general/datasets/Gse15222_f_a_ri_0409/summary.rtf
new file mode 100644
index 0000000..e99fa9e
--- /dev/null
+++ b/general/datasets/Gse15222_f_a_ri_0409/summary.rtf
@@ -0,0 +1,9 @@
+Myers and colleagues generated massive neocortical transcriptome data sets for a set of unrelated elderly neurologically and neuropathologically normal humans and from confirmed late onset Alzheimer's disease patients (LOAD, n = 187 normal and 176 LOAD cases, see DOI:10.1016/j.ajhg.2009.03.011 for detail). They used an Illumina Sentrix Bead array (HumanRef-8) that measures expression of approximately 19,730 curated RefSeq sequences (Human Build 34).
+
+Case identifiers: All case identifiers (IDs) in GeneNetwork begin with a capital C followed by a six digit GEO identifier, followed by the sex and age in years. Non-Alzheimer cases are labeled with the suffix letter N: C225652M85N. Alzheimer cases are labeled with the suffix letter A: C388217F97A.
+
+Data were initially downloaded from the NCBI GEO archive under the experiment ID GSE15222. All data were generated using the Illumina HumanRef-8 expression BeadChip (GPL2700) v2 Rev0. This data set in GeneNetwork includes data for 24,354 probes. We have realigned the 50-mer sequences by BLAT to the latest version of the human genome (Feb 2009, hg19) and reannotated the array (August 2009). The annotation in GN will differ from that provided in GEO for this platform. We were unable to obtain 50-mer sequences for several thousand probes (e.g., HTT), and these probes have therefore not been realigned to the human genome.
+
+The GEO data set was processed by Myers and colleagues using Illumina's Rank Invariant transform. We performed a series of QC and renormalization steps to the data to allow more facile comparison to other data sets in GeneNetwork. In brief, data is log2 transformed. We recentered each array to a mean expression of 8 units and a standard deviation of 2 units (2z + 8 transform). The values are therefore modified z scores and each unit represents roughly a two-fold difference in expression. Average expression across all 363 cases range from a low of 6 units (e.g., SYT15) to a high of 19 units for ARSK. APOE has an average expression of 15 units and APP has an average expression of 11.5 units.. The distribution is far from normal with a great excess of measurements of genes with low to moderate expression clustered between 6.5 and 8.5 units.
+
+A small number of arrays (n = 6, GSM226040, GSM226041, GSM226042, GSM226044, GSM226045, GSM226046) had a different distribution from the great majority of other arrays. This was probably due to a batch processing effect. Members of this minority group belonged to both normal and LOAD cases. This putative batch effect has been eliminated in the GeneNetwork rendition of the Myers data. To eliminate the putative batch effect, we simply computed a mean offset for each probe in the "minority set" relative to the remaining "majority set" and added or subtracted this offset to force the mean of each probe in the minority set to conform to mean of the same probe in the majority set.
diff --git a/general/datasets/Gse15222_f_n_ri_0409/acknowledgment.rtf b/general/datasets/Gse15222_f_n_ri_0409/acknowledgment.rtf
new file mode 100644
index 0000000..c203ed9
--- /dev/null
+++ b/general/datasets/Gse15222_f_n_ri_0409/acknowledgment.rtf
@@ -0,0 +1 @@
+http://labs.med.miami.edu/myers
diff --git a/general/datasets/Gse15222_f_n_ri_0409/cases.rtf b/general/datasets/Gse15222_f_n_ri_0409/cases.rtf
new file mode 100644
index 0000000..6933d14
--- /dev/null
+++ b/general/datasets/Gse15222_f_n_ri_0409/cases.rtf
@@ -0,0 +1,3290 @@
+
+
+
+
+
+
+
+
+
+ | Index |
+ GEO Series |
+ Organ Region |
+ Tissue |
+ Case ID |
+ Age |
+ Sex |
+
+
+ | 1 |
+ GSM225652 |
+ Temporal Cortex |
+ Normal |
+ C225652M85N |
+ 85 |
+ M |
+
+
+ | 2 |
+ GSM225662 |
+ Temporal Cortex |
+ Normal |
+ C225662M85N |
+ 85 |
+ M |
+
+
+ | 3 |
+ GSM225664 |
+ Temporal Cortex |
+ Normal |
+ C225664F79N |
+ 79 |
+ F |
+
+
+ | 4 |
+ GSM225665 |
+ Temporal Cortex |
+ Normal |
+ C225665F85N |
+ 85 |
+ F |
+
+
+ | 5 |
+ GSM225666 |
+ Temporal Cortex |
+ Normal |
+ C225666F73N |
+ 73 |
+ F |
+
+
+ | 6 |
+ GSM225667 |
+ Temporal Cortex |
+ Normal |
+ C225667M81N |
+ 81 |
+ M |
+
+
+ | 7 |
+ GSM225668 |
+ Temporal Cortex |
+ Normal |
+ C225668M79N |
+ 79 |
+ M |
+
+
+ | 8 |
+ GSM225669 |
+ Temporal Cortex |
+ Normal |
+ C225669M77N |
+ 77 |
+ M |
+
+
+ | 9 |
+ GSM225670 |
+ Temporal Cortex |
+ Normal |
+ C225670M69N |
+ 69 |
+ M |
+
+
+ | 10 |
+ GSM225671 |
+ Temporal Cortex |
+ Normal |
+ C225671M86N |
+ 86 |
+ M |
+
+
+ | 11 |
+ GSM225672 |
+ Temporal Cortex |
+ Normal |
+ C225672F83N |
+ 83 |
+ F |
+
+
+ | 12 |
+ GSM225673 |
+ Temporal Cortex |
+ Normal |
+ C225673M78N |
+ 78 |
+ M |
+
+
+ | 13 |
+ GSM225674 |
+ Temporal Cortex |
+ Normal |
+ C225674M94N |
+ 94 |
+ M |
+
+
+ | 14 |
+ GSM225675 |
+ Temporal Cortex |
+ Normal |
+ C225675F81N |
+ 81 |
+ F |
+
+
+ | 15 |
+ GSM225676 |
+ Temporal Cortex |
+ Normal |
+ C225676M76N |
+ 76 |
+ M |
+
+
+ | 16 |
+ GSM225677 |
+ Temporal Cortex |
+ Normal |
+ C225677M83N |
+ 83 |
+ M |
+
+
+ | 17 |
+ GSM225678 |
+ Temporal Cortex |
+ Normal |
+ C225678M68N |
+ 68 |
+ M |
+
+
+ | 18 |
+ GSM225679 |
+ Temporal Cortex |
+ Normal |
+ C225679F82N |
+ 82 |
+ F |
+
+
+ | 19 |
+ GSM225680 |
+ Temporal Cortex |
+ Normal |
+ C225680F70N |
+ 70 |
+ F |
+
+
+ | 20 |
+ GSM225681 |
+ Temporal Cortex |
+ Normal |
+ C225681M86N |
+ 86 |
+ M |
+
+
+ | 21 |
+ GSM225682 |
+ Temporal Cortex |
+ Normal |
+ C225682M78N |
+ 78 |
+ M |
+
+
+ | 22 |
+ GSM225683 |
+ Temporal Cortex |
+ Normal |
+ C225683M82N |
+ 82 |
+ M |
+
+
+ | 23 |
+ GSM225684 |
+ Temporal Cortex |
+ Normal |
+ C225684F94N |
+ 94 |
+ F |
+
+
+ | 24 |
+ GSM225685 |
+ Temporal Cortex |
+ Normal |
+ C225685F87N |
+ 87 |
+ F |
+
+
+ | 25 |
+ GSM225686 |
+ Temporal Cortex |
+ Normal |
+ C225686M74N |
+ 74 |
+ M |
+
+
+ | 26 |
+ GSM225687 |
+ Temporal Cortex |
+ Normal |
+ C225687M85N |
+ 85 |
+ M |
+
+
+ | 27 |
+ GSM225688 |
+ Temporal Cortex |
+ Normal |
+ C225688M75N |
+ 75 |
+ M |
+
+
+ | 28 |
+ GSM225689 |
+ Temporal Cortex |
+ Normal |
+ C225689F86N |
+ 86 |
+ F |
+
+
+ | 29 |
+ GSM225690 |
+ Temporal Cortex |
+ Normal |
+ C225690M75N |
+ 75 |
+ M |
+
+
+ | 30 |
+ GSM225691 |
+ Temporal Cortex |
+ Normal |
+ C225691M81N |
+ 81 |
+ M |
+
+
+ | 31 |
+ GSM225692 |
+ Temporal Cortex |
+ Normal |
+ C225692F72N |
+ 72 |
+ F |
+
+
+ | 32 |
+ GSM225693 |
+ Temporal Cortex |
+ Normal |
+ C225693F81N |
+ 81 |
+ F |
+
+
+ | 33 |
+ GSM225695 |
+ Temporal Cortex |
+ Normal |
+ C225695M81N |
+ 81 |
+ M |
+
+
+ | 34 |
+ GSM225696 |
+ Temporal Cortex |
+ Normal |
+ C225696M81N |
+ 81 |
+ M |
+
+
+ | 35 |
+ GSM225697 |
+ Temporal Cortex |
+ Normal |
+ C225697M91N |
+ 91 |
+ M |
+
+
+ | 36 |
+ GSM225698 |
+ Temporal Cortex |
+ Normal |
+ C225698M84N |
+ 84 |
+ M |
+
+
+ | 37 |
+ GSM225699 |
+ Temporal Cortex |
+ Normal |
+ C225699M96N |
+ 96 |
+ M |
+
+
+ | 38 |
+ GSM225700 |
+ Temporal Cortex |
+ Normal |
+ C225700F97N |
+ 97 |
+ F |
+
+
+ | 39 |
+ GSM225701 |
+ Temporal Cortex |
+ Normal |
+ C225701M90N |
+ 90 |
+ M |
+
+
+ | 40 |
+ GSM225702 |
+ Temporal Cortex |
+ Normal |
+ C225702F67N |
+ 67 |
+ F |
+
+
+ | 41 |
+ GSM225703 |
+ Temporal Cortex |
+ Normal |
+ C225703F83N |
+ 83 |
+ F |
+
+
+ | 42 |
+ GSM225704 |
+ Temporal Cortex |
+ Normal |
+ C225704F82N |
+ 82 |
+ F |
+
+
+ | 43 |
+ GSM225705 |
+ Temporal Cortex |
+ Normal |
+ C225705F66N |
+ 66 |
+ F |
+
+
+ | 44 |
+ GSM225706 |
+ Temporal Cortex |
+ Normal |
+ C225706F72N |
+ 72 |
+ F |
+
+
+ | 45 |
+ GSM225707 |
+ Temporal Cortex |
+ Normal |
+ C225707F65N |
+ 65 |
+ F |
+
+
+ | 46 |
+ GSM225708 |
+ Temporal Cortex |
+ Normal |
+ C225708F75N |
+ 75 |
+ F |
+
+
+ | 47 |
+ GSM225709 |
+ Temporal Cortex |
+ Normal |
+ C225709F74N |
+ 74 |
+ F |
+
+
+ | 48 |
+ GSM225711 |
+ Temporal Cortex |
+ Normal |
+ C225711M68N |
+ 68 |
+ M |
+
+
+ | 49 |
+ GSM225713 |
+ Temporal Cortex |
+ Normal |
+ C225713F80N |
+ 80 |
+ F |
+
+
+ | 50 |
+ GSM225714 |
+ Temporal Cortex |
+ Normal |
+ C225714M80N |
+ 80 |
+ M |
+
+
+ | 51 |
+ GSM225715 |
+ Temporal Cortex |
+ Normal |
+ C225715M66N |
+ 66 |
+ M |
+
+
+ | 52 |
+ GSM225717 |
+ Temporal Cortex |
+ Normal |
+ C225717M88N |
+ 88 |
+ M |
+
+
+ | 53 |
+ GSM225718 |
+ Temporal Cortex |
+ Normal |
+ C225718F91N |
+ 91 |
+ F |
+
+
+ | 54 |
+ GSM225719 |
+ Temporal Cortex |
+ Normal |
+ C225719M73N |
+ 73 |
+ M |
+
+
+ | 55 |
+ GSM225720 |
+ Temporal Cortex |
+ Normal |
+ C225720M76N |
+ 76 |
+ M |
+
+
+ | 56 |
+ GSM225721 |
+ Temporal Cortex |
+ Normal |
+ C225721M75N |
+ 75 |
+ M |
+
+
+ | 57 |
+ GSM225722 |
+ Temporal Cortex |
+ Normal |
+ C225722F86N |
+ 86 |
+ F |
+
+
+ | 58 |
+ GSM225723 |
+ Temporal Cortex |
+ Normal |
+ C225723F72N |
+ 72 |
+ F |
+
+
+ | 59 |
+ GSM225724 |
+ Temporal Cortex |
+ Normal |
+ C225724M97N |
+ 97 |
+ M |
+
+
+ | 60 |
+ GSM225725 |
+ Temporal Cortex |
+ Normal |
+ C225725M86N |
+ 86 |
+ M |
+
+
+ | 61 |
+ GSM225726 |
+ Temporal Cortex |
+ Normal |
+ C225726M82N |
+ 82 |
+ M |
+
+
+ | 62 |
+ GSM225727 |
+ Temporal Cortex |
+ Normal |
+ C225727F95N |
+ 95 |
+ F |
+
+
+ | 63 |
+ GSM225728 |
+ Temporal Cortex |
+ Normal |
+ C225728F76N |
+ 76 |
+ F |
+
+
+ | 64 |
+ GSM225729 |
+ Temporal Cortex |
+ Normal |
+ C225729M76N |
+ 76 |
+ M |
+
+
+ | 65 |
+ GSM225730 |
+ Temporal Cortex |
+ Normal |
+ C225730M69N |
+ 69 |
+ M |
+
+
+ | 66 |
+ GSM225731 |
+ Temporal Cortex |
+ Normal |
+ C225731F80N |
+ 80 |
+ F |
+
+
+ | 67 |
+ GSM225732 |
+ Temporal Cortex |
+ Normal |
+ C225732F99N |
+ 99 |
+ F |
+
+
+ | 68 |
+ GSM225733 |
+ Temporal Cortex |
+ Normal |
+ C225733M68N |
+ 68 |
+ M |
+
+
+ | 69 |
+ GSM225734 |
+ Temporal Cortex |
+ Normal |
+ C225734M70N |
+ 70 |
+ M |
+
+
+ | 70 |
+ GSM225735 |
+ Temporal Cortex |
+ Normal |
+ C225735F87N |
+ 87 |
+ F |
+
+
+ | 71 |
+ GSM225736 |
+ Temporal Cortex |
+ Normal |
+ C225736F99N |
+ 99 |
+ F |
+
+
+ | 72 |
+ GSM225737 |
+ Temporal Cortex |
+ Normal |
+ C225737F88N |
+ 88 |
+ F |
+
+
+ | 73 |
+ GSM225739 |
+ Temporal Cortex |
+ Normal |
+ C225739M65N |
+ 65 |
+ M |
+
+
+ | 74 |
+ GSM225741 |
+ Temporal Cortex |
+ Normal |
+ C225741M82N |
+ 82 |
+ M |
+
+
+ | 75 |
+ GSM225742 |
+ Temporal Cortex |
+ Normal |
+ C225742F78N |
+ 78 |
+ F |
+
+
+ | 76 |
+ GSM225743 |
+ Temporal Cortex |
+ Normal |
+ C225743F85N |
+ 85 |
+ F |
+
+
+ | 77 |
+ GSM225744 |
+ Temporal Cortex |
+ Normal |
+ C225744F100N |
+ 100 |
+ F |
+
+
+ | 78 |
+ GSM225745 |
+ Temporal Cortex |
+ Normal |
+ C225745F87N |
+ 87 |
+ F |
+
+
+ | 79 |
+ GSM225746 |
+ Temporal Cortex |
+ Normal |
+ C225746F85N |
+ 85 |
+ F |
+
+
+ | 80 |
+ GSM225747 |
+ Temporal Cortex |
+ Normal |
+ C225747F97N |
+ 97 |
+ F |
+
+
+ | 81 |
+ GSM225748 |
+ Temporal Cortex |
+ Normal |
+ C225748M65N |
+ 65 |
+ M |
+
+
+ | 82 |
+ GSM225749 |
+ Temporal Cortex |
+ Normal |
+ C225749M65N |
+ 65 |
+ M |
+
+
+ | 83 |
+ GSM225751 |
+ Temporal Cortex |
+ Normal |
+ C225751F87N |
+ 87 |
+ F |
+
+
+ | 84 |
+ GSM225752 |
+ Temporal Cortex |
+ Normal |
+ C225752F85N |
+ 85 |
+ F |
+
+
+ | 85 |
+ GSM225753 |
+ Temporal Cortex |
+ Normal |
+ C225753M68N |
+ 68 |
+ M |
+
+
+ | 86 |
+ GSM225754 |
+ Temporal Cortex |
+ Normal |
+ C225754M71N |
+ 71 |
+ M |
+
+
+ | 87 |
+ GSM225755 |
+ Temporal Cortex |
+ Normal |
+ C225755F83N |
+ 83 |
+ F |
+
+
+ | 88 |
+ GSM225756 |
+ Temporal Cortex |
+ Normal |
+ C225756M76N |
+ 76 |
+ M |
+
+
+ | 89 |
+ GSM225757 |
+ Temporal Cortex |
+ Normal |
+ C225757M67N |
+ 67 |
+ M |
+
+
+ | 90 |
+ GSM225758 |
+ Temporal Cortex |
+ Normal |
+ C225758F100N |
+ 100 |
+ F |
+
+
+ | 91 |
+ GSM225759 |
+ Temporal Cortex |
+ Normal |
+ C225759M79N |
+ 79 |
+ M |
+
+
+ | 92 |
+ GSM225760 |
+ Temporal Cortex |
+ Normal |
+ C225760M74N |
+ 74 |
+ M |
+
+
+ | 93 |
+ GSM225761 |
+ Temporal Cortex |
+ Normal |
+ C225761F88N |
+ 88 |
+ F |
+
+
+ | 94 |
+ GSM225762 |
+ Temporal Cortex |
+ Normal |
+ C225762M70N |
+ 70 |
+ M |
+
+
+ | 95 |
+ GSM225763 |
+ Temporal Cortex |
+ Normal |
+ C225763F97N |
+ 97 |
+ F |
+
+
+ | 96 |
+ GSM225764 |
+ Temporal Cortex |
+ Normal |
+ C225764M69N |
+ 69 |
+ M |
+
+
+ | 97 |
+ GSM225915 |
+ Temporal Cortex |
+ Normal |
+ C225915F99N |
+ 99 |
+ F |
+
+
+ | 98 |
+ GSM225916 |
+ Temporal Cortex |
+ Normal |
+ C225916M81N |
+ 81 |
+ M |
+
+
+ | 99 |
+ GSM225917 |
+ Temporal Cortex |
+ Normal |
+ C225917F85N |
+ 85 |
+ F |
+
+
+ | 100 |
+ GSM225918 |
+ Temporal Cortex |
+ Normal |
+ C225918F82N |
+ 82 |
+ F |
+
+
+ | 101 |
+ GSM225919 |
+ Temporal Cortex |
+ Normal |
+ C225919M70N |
+ 70 |
+ M |
+
+
+ | 102 |
+ GSM225920 |
+ Temporal Cortex |
+ Normal |
+ C225920M73N |
+ 73 |
+ M |
+
+
+ | 103 |
+ GSM225921 |
+ Temporal Cortex |
+ Normal |
+ C225921M83N |
+ 83 |
+ M |
+
+
+ | 104 |
+ GSM225922 |
+ Temporal Cortex |
+ Normal |
+ C225922M74N |
+ 74 |
+ M |
+
+
+ | 105 |
+ GSM225923 |
+ Temporal Cortex |
+ Normal |
+ C225923M77N |
+ 77 |
+ M |
+
+
+ | 106 |
+ GSM225924 |
+ Temporal Cortex |
+ Normal |
+ C225924M81N |
+ 81 |
+ M |
+
+
+ | 107 |
+ GSM225925 |
+ Temporal Cortex |
+ Normal |
+ C225925M65N |
+ 65 |
+ M |
+
+
+ | 108 |
+ GSM225926 |
+ Temporal Cortex |
+ Normal |
+ C225926F73N |
+ 73 |
+ F |
+
+
+ | 109 |
+ GSM225927 |
+ Temporal Cortex |
+ Normal |
+ C225927F85N |
+ 85 |
+ F |
+
+
+ | 110 |
+ GSM225928 |
+ Temporal Cortex |
+ Normal |
+ C225928M69N |
+ 69 |
+ M |
+
+
+ | 111 |
+ GSM225929 |
+ Temporal Cortex |
+ Normal |
+ C225929M72N |
+ 72 |
+ M |
+
+
+ | 112 |
+ GSM225930 |
+ Temporal Cortex |
+ Normal |
+ C225930F76N |
+ 76 |
+ F |
+
+
+ | 113 |
+ GSM225931 |
+ Temporal Cortex |
+ Normal |
+ C225931M73N |
+ 73 |
+ M |
+
+
+ | 114 |
+ GSM225932 |
+ Temporal Cortex |
+ Normal |
+ C225932M66N |
+ 66 |
+ M |
+
+
+ | 115 |
+ GSM225933 |
+ Temporal Cortex |
+ Normal |
+ C225933F85N |
+ 85 |
+ F |
+
+
+ | 116 |
+ GSM225934 |
+ Temporal Cortex |
+ Normal |
+ C225934M87N |
+ 87 |
+ M |
+
+
+ | 117 |
+ GSM225935 |
+ Temporal Cortex |
+ Normal |
+ C225935F86N |
+ 86 |
+ F |
+
+
+ | 118 |
+ GSM225936 |
+ Temporal Cortex |
+ Normal |
+ C225936F73N |
+ 73 |
+ F |
+
+
+ | 119 |
+ GSM225937 |
+ Temporal Cortex |
+ Normal |
+ C225937M86N |
+ 86 |
+ M |
+
+
+ | 120 |
+ GSM225938 |
+ Temporal Cortex |
+ Normal |
+ C225938M72N |
+ 72 |
+ M |
+
+
+ | 121 |
+ GSM225939 |
+ Temporal Cortex |
+ Normal |
+ C225939F69N |
+ 69 |
+ F |
+
+
+ | 122 |
+ GSM225940 |
+ Temporal Cortex |
+ Normal |
+ C225940F88N |
+ 88 |
+ F |
+
+
+ | 123 |
+ GSM225941 |
+ Temporal Cortex |
+ Normal |
+ C225941M77N |
+ 77 |
+ M |
+
+
+ | 124 |
+ GSM225942 |
+ Temporal Cortex |
+ Normal |
+ C225942M96N |
+ 96 |
+ M |
+
+
+ | 125 |
+ GSM225943 |
+ Temporal Cortex |
+ Normal |
+ C225943F78N |
+ 78 |
+ F |
+
+
+ | 126 |
+ GSM225944 |
+ Temporal Cortex |
+ Normal |
+ C225944M77N |
+ 77 |
+ M |
+
+
+ | 127 |
+ GSM225945 |
+ Temporal Cortex |
+ Normal |
+ C225945F99N |
+ 99 |
+ F |
+
+
+ | 128 |
+ GSM225946 |
+ Temporal Cortex |
+ Normal |
+ C225946M78N |
+ 78 |
+ M |
+
+
+ | 129 |
+ GSM225947 |
+ Temporal Cortex |
+ Normal |
+ C225947F76N |
+ 76 |
+ F |
+
+
+ | 130 |
+ GSM225948 |
+ Temporal Cortex |
+ Normal |
+ C225948M78N |
+ 78 |
+ M |
+
+
+ | 131 |
+ GSM225949 |
+ Temporal Cortex |
+ Normal |
+ C225949F97N |
+ 97 |
+ F |
+
+
+ | 132 |
+ GSM225950 |
+ Temporal Cortex |
+ Normal |
+ C225950F86N |
+ 86 |
+ F |
+
+
+ | 133 |
+ GSM225951 |
+ Temporal Cortex |
+ Normal |
+ C225951M77N |
+ 77 |
+ M |
+
+
+ | 134 |
+ GSM225952 |
+ Temporal Cortex |
+ Normal |
+ C225952M87N |
+ 87 |
+ M |
+
+
+ | 135 |
+ GSM225953 |
+ Temporal Cortex |
+ Normal |
+ C225953F72N |
+ 72 |
+ F |
+
+
+ | 136 |
+ GSM225954 |
+ Temporal Cortex |
+ Normal |
+ C225954F91N |
+ 91 |
+ F |
+
+
+ | 137 |
+ GSM225955 |
+ Temporal Cortex |
+ Normal |
+ C225955F85N |
+ 85 |
+ F |
+
+
+ | 138 |
+ GSM225956 |
+ Temporal Cortex |
+ Normal |
+ C225956M88N |
+ 88 |
+ M |
+
+
+ | 139 |
+ GSM225957 |
+ Temporal Cortex |
+ Normal |
+ C225957F86N |
+ 86 |
+ F |
+
+
+ | 140 |
+ GSM225958 |
+ Temporal Cortex |
+ Normal |
+ C225958F93N |
+ 93 |
+ F |
+
+
+ | 141 |
+ GSM225959 |
+ Temporal Cortex |
+ Normal |
+ C225959M82N |
+ 82 |
+ M |
+
+
+ | 142 |
+ GSM225961 |
+ Temporal Cortex |
+ Normal |
+ C225961F72N |
+ 72 |
+ F |
+
+
+ | 143 |
+ GSM225962 |
+ Temporal Cortex |
+ Normal |
+ C225962F85N |
+ 85 |
+ F |
+
+
+ | 144 |
+ GSM225963 |
+ Temporal Cortex |
+ Normal |
+ C225963M70N |
+ 70 |
+ M |
+
+
+ | 145 |
+ GSM225964 |
+ Temporal Cortex |
+ Normal |
+ C225964F67N |
+ 67 |
+ F |
+
+
+ | 146 |
+ GSM225965 |
+ Temporal Cortex |
+ Normal |
+ C225965F74N |
+ 74 |
+ F |
+
+
+ | 147 |
+ GSM226034 |
+ Temporal Cortex |
+ Normal |
+ C226034M69N |
+ 69 |
+ M |
+
+
+ | 148 |
+ GSM226035 |
+ Temporal Cortex |
+ Normal |
+ C226035M85N |
+ 85 |
+ M |
+
+
+ | 149 |
+ GSM226037 |
+ Temporal Cortex |
+ Normal |
+ C226037M89N |
+ 89 |
+ M |
+
+
+ | 150 |
+ GSM226038 |
+ Temporal Cortex |
+ Normal |
+ C226038M86N |
+ 86 |
+ M |
+
+
+ | 151 |
+ GSM226039 |
+ Temporal Cortex |
+ Normal |
+ C226039M90N |
+ 90 |
+ M |
+
+
+ | 152 |
+ GSM226040 |
+ Temporal Cortex |
+ Normal |
+ C226040F94N |
+ 94 |
+ F |
+
+
+ | 153 |
+ GSM226041 |
+ Temporal Cortex |
+ Normal |
+ C226041F91N |
+ 91 |
+ F |
+
+
+ | 154 |
+ GSM226042 |
+ Temporal Cortex |
+ Normal |
+ C226042F91N |
+ 91 |
+ F |
+
+
+ | 155 |
+ GSM226044 |
+ Temporal Cortex |
+ Normal |
+ C226044F95N |
+ 95 |
+ F |
+
+
+ | 156 |
+ GSM226045 |
+ Temporal Cortex |
+ Normal |
+ C226045F95N |
+ 95 |
+ F |
+
+
+ | 157 |
+ GSM226046 |
+ Temporal Cortex |
+ Normal |
+ C226046F91N |
+ 91 |
+ F |
+
+
+ | 158 |
+ GSM226047 |
+ Temporal Cortex |
+ Normal |
+ C226047M80N |
+ 80 |
+ M |
+
+
+ | 159 |
+ GSM226048 |
+ Temporal Cortex |
+ Normal |
+ C226048M83N |
+ 83 |
+ M |
+
+
+ | 160 |
+ GSM226049 |
+ Temporal Cortex |
+ Normal |
+ C226049M67N |
+ 67 |
+ M |
+
+
+ | 161 |
+ GSM226050 |
+ Temporal Cortex |
+ Normal |
+ C226050M76N |
+ 76 |
+ M |
+
+
+ | 162 |
+ GSM226051 |
+ Temporal Cortex |
+ Normal |
+ C226051F86N |
+ 86 |
+ F |
+
+
+ | 163 |
+ GSM226052 |
+ Temporal Cortex |
+ Normal |
+ C226052F86N |
+ 86 |
+ F |
+
+
+ | 164 |
+ GSM226053 |
+ Temporal Cortex |
+ Normal |
+ C226053M83N |
+ 83 |
+ M |
+
+
+ | 165 |
+ GSM226055 |
+ Temporal Cortex |
+ Normal |
+ C226055M84N |
+ 84 |
+ M |
+
+
+ | 166 |
+ GSM226056 |
+ Temporal Cortex |
+ Normal |
+ C226056M80N |
+ 80 |
+ M |
+
+
+ | 167 |
+ GSM226082 |
+ Temporal Cortex |
+ Normal |
+ C226082M72N |
+ 72 |
+ M |
+
+
+ | 168 |
+ GSM226145 |
+ Temporal Cortex |
+ Normal |
+ C226145M67N |
+ 67 |
+ M |
+
+
+ | 169 |
+ GSM226146 |
+ Temporal Cortex |
+ Normal |
+ C226146F96N |
+ 96 |
+ F |
+
+
+ | 170 |
+ GSM226147 |
+ Temporal Cortex |
+ Normal |
+ C226147F75N |
+ 75 |
+ F |
+
+
+ | 171 |
+ GSM226148 |
+ Temporal Cortex |
+ Normal |
+ C226148F89N |
+ 89 |
+ F |
+
+
+ | 172 |
+ GSM226149 |
+ Temporal Cortex |
+ Normal |
+ C226149F86N |
+ 86 |
+ F |
+
+
+ | 173 |
+ GSM226150 |
+ Temporal Cortex |
+ Normal |
+ C226150M67N |
+ 67 |
+ M |
+
+
+ | 174 |
+ GSM226151 |
+ Temporal Cortex |
+ Normal |
+ C226151M77N |
+ 77 |
+ M |
+
+
+ | 175 |
+ GSM226154 |
+ Temporal Cortex |
+ Normal |
+ C226154M65N |
+ 65 |
+ M |
+
+
+ | 176 |
+ GSM226155 |
+ Temporal Cortex |
+ Normal |
+ C226155M69N |
+ 69 |
+ M |
+
+
+ | 177 |
+ GSM226156 |
+ Temporal Cortex |
+ Normal |
+ C226156M84N |
+ 84 |
+ M |
+
+
+ | 178 |
+ GSM226157 |
+ Temporal Cortex |
+ Normal |
+ C226157F85N |
+ 85 |
+ F |
+
+
+ | 179 |
+ GSM226158 |
+ Temporal Cortex |
+ Normal |
+ C226158M94N |
+ 94 |
+ M |
+
+
+ | 180 |
+ GSM226159 |
+ Temporal Cortex |
+ Normal |
+ C226159F89N |
+ 89 |
+ F |
+
+
+ | 181 |
+ GSM226160 |
+ Temporal Cortex |
+ Normal |
+ C226160M87N |
+ 87 |
+ M |
+
+
+ | 182 |
+ GSM226162 |
+ Temporal Cortex |
+ Normal |
+ C226162M90N |
+ 90 |
+ M |
+
+
+ | 183 |
+ GSM226163 |
+ Temporal Cortex |
+ Normal |
+ C226163F88N |
+ 88 |
+ F |
+
+
+ | 184 |
+ GSM226164 |
+ Temporal Cortex |
+ Normal |
+ C226164M94N |
+ 94 |
+ M |
+
+
+ | 185 |
+ GSM226165 |
+ Temporal Cortex |
+ Normal |
+ C226165F86N |
+ 86 |
+ F |
+
+
+ | 186 |
+ GSM226167 |
+ Temporal Cortex |
+ Normal |
+ C226167F93N |
+ 93 |
+ F |
+
+
+ | 187 |
+ GSM226168 |
+ Temporal Cortex |
+ Normal |
+ C226168M91N |
+ 91 |
+ M |
+
+
+ | 188 |
+ GSM388217 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388217F97A |
+ 97 |
+ F |
+
+
+ | 189 |
+ GSM388218 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388218F101A |
+ 101 |
+ F |
+
+
+ | 190 |
+ GSM388219 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388219M84A |
+ 84 |
+ M |
+
+
+ | 191 |
+ GSM388220 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388220F95A |
+ 95 |
+ F |
+
+
+ | 192 |
+ GSM388221 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388221F97A |
+ 97 |
+ F |
+
+
+ | 193 |
+ GSM388222 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388222F102A |
+ 102 |
+ F |
+
+
+ | 194 |
+ GSM388223 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388223M87A |
+ 87 |
+ M |
+
+
+ | 195 |
+ GSM388224 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388224F77A |
+ 77 |
+ F |
+
+
+ | 196 |
+ GSM388225 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388225M87A |
+ 87 |
+ M |
+
+
+ | 197 |
+ GSM388226 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388226M84A |
+ 84 |
+ M |
+
+
+ | 198 |
+ GSM388228 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388228F92A |
+ 92 |
+ F |
+
+
+ | 199 |
+ GSM388229 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388229M93A |
+ 93 |
+ M |
+
+
+ | 200 |
+ GSM388230 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388230F93A |
+ 93 |
+ F |
+
+
+ | 201 |
+ GSM388231 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388231F87A |
+ 87 |
+ F |
+
+
+ | 202 |
+ GSM388232 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388232F90A |
+ 90 |
+ F |
+
+
+ | 203 |
+ GSM388233 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388233M75A |
+ 75 |
+ M |
+
+
+ | 204 |
+ GSM388234 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388234M92A |
+ 92 |
+ M |
+
+
+ | 205 |
+ GSM388235 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388235M83A |
+ 83 |
+ M |
+
+
+ | 206 |
+ GSM388236 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388236M88A |
+ 88 |
+ M |
+
+
+ | 207 |
+ GSM388237 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388237M89A |
+ 89 |
+ M |
+
+
+ | 208 |
+ GSM388238 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388238F74A |
+ 74 |
+ F |
+
+
+ | 209 |
+ GSM388239 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388239F79A |
+ 79 |
+ F |
+
+
+ | 210 |
+ GSM388240 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388240M80A |
+ 80 |
+ M |
+
+
+ | 211 |
+ GSM388241 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388241F97A |
+ 97 |
+ F |
+
+
+ | 212 |
+ GSM388242 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388242M87A |
+ 87 |
+ M |
+
+
+ | 213 |
+ GSM388243 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388243F89A |
+ 89 |
+ F |
+
+
+ | 214 |
+ GSM388244 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388244F90A |
+ 90 |
+ F |
+
+
+ | 215 |
+ GSM388245 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388245M90A |
+ 90 |
+ M |
+
+
+ | 216 |
+ GSM388246 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388246M78A |
+ 78 |
+ M |
+
+
+ | 217 |
+ GSM388247 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388247F80A |
+ 80 |
+ F |
+
+
+ | 218 |
+ GSM388248 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388248F79A |
+ 79 |
+ F |
+
+
+ | 219 |
+ GSM388249 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388249F87A |
+ 87 |
+ F |
+
+
+ | 220 |
+ GSM388250 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388250F88A |
+ 88 |
+ F |
+
+
+ | 221 |
+ GSM388251 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388251M86A |
+ 86 |
+ M |
+
+
+ | 222 |
+ GSM388252 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388252F74A |
+ 74 |
+ F |
+
+
+ | 223 |
+ GSM388253 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388253F72A |
+ 72 |
+ F |
+
+
+ | 224 |
+ GSM388254 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388254M81A |
+ 81 |
+ M |
+
+
+ | 225 |
+ GSM388255 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388255F68A |
+ 68 |
+ F |
+
+
+ | 226 |
+ GSM388256 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388256F81A |
+ 81 |
+ F |
+
+
+ | 227 |
+ GSM388257 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388257F82A |
+ 82 |
+ F |
+
+
+ | 228 |
+ GSM388258 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388258M78A |
+ 78 |
+ M |
+
+
+ | 229 |
+ GSM388259 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388259M74A |
+ 74 |
+ M |
+
+
+ | 230 |
+ GSM388260 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388260M88A |
+ 88 |
+ M |
+
+
+ | 231 |
+ GSM388261 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388261F78A |
+ 78 |
+ F |
+
+
+ | 232 |
+ GSM388262 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388262M83A |
+ 83 |
+ M |
+
+
+ | 233 |
+ GSM388263 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388263M83A |
+ 83 |
+ M |
+
+
+ | 234 |
+ GSM388264 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388264M80A |
+ 80 |
+ M |
+
+
+ | 235 |
+ GSM388265 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388265M84A |
+ 84 |
+ M |
+
+
+ | 236 |
+ GSM388266 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388266F79A |
+ 79 |
+ F |
+
+
+ | 237 |
+ GSM388267 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388267F86A |
+ 86 |
+ F |
+
+
+ | 238 |
+ GSM388268 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388268M92A |
+ 92 |
+ M |
+
+
+ | 239 |
+ GSM388269 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388269F81A |
+ 81 |
+ F |
+
+
+ | 240 |
+ GSM388270 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388270F79A |
+ 79 |
+ F |
+
+
+ | 241 |
+ GSM388271 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388271M74A |
+ 74 |
+ M |
+
+
+ | 242 |
+ GSM388272 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388272F73A |
+ 73 |
+ F |
+
+
+ | 243 |
+ GSM388273 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388273M87A |
+ 87 |
+ M |
+
+
+ | 244 |
+ GSM388274 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388274F86A |
+ 86 |
+ F |
+
+
+ | 245 |
+ GSM388275 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388275F86A |
+ 86 |
+ F |
+
+
+ | 246 |
+ GSM388276 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388276F87A |
+ 87 |
+ F |
+
+
+ | 247 |
+ GSM388277 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388277F92A |
+ 92 |
+ F |
+
+
+ | 248 |
+ GSM388278 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388278F78A |
+ 78 |
+ F |
+
+
+ | 249 |
+ GSM388279 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388279F94A |
+ 94 |
+ F |
+
+
+ | 250 |
+ GSM388281 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388281F94A |
+ 94 |
+ F |
+
+
+ | 251 |
+ GSM388282 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388282M76A |
+ 76 |
+ M |
+
+
+ | 252 |
+ GSM388284 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388284M91A |
+ 91 |
+ M |
+
+
+ | 253 |
+ GSM388285 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388285M86A |
+ 86 |
+ M |
+
+
+ | 254 |
+ GSM388286 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388286M77A |
+ 77 |
+ M |
+
+
+ | 255 |
+ GSM388287 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388287M82A |
+ 82 |
+ M |
+
+
+ | 256 |
+ GSM388288 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388288M78A |
+ 78 |
+ M |
+
+
+ | 257 |
+ GSM388289 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388289M79A |
+ 79 |
+ M |
+
+
+ | 258 |
+ GSM388290 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388290F84A |
+ 84 |
+ F |
+
+
+ | 259 |
+ GSM388291 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388291F87A |
+ 87 |
+ F |
+
+
+ | 260 |
+ GSM388292 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388292F86A |
+ 86 |
+ F |
+
+
+ | 261 |
+ GSM388294 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388294M83A |
+ 83 |
+ M |
+
+
+ | 262 |
+ GSM388295 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388295M83A |
+ 83 |
+ M |
+
+
+ | 263 |
+ GSM388296 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388296M81A |
+ 81 |
+ M |
+
+
+ | 264 |
+ GSM388297 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388297F93A |
+ 93 |
+ F |
+
+
+ | 265 |
+ GSM388298 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388298M71A |
+ 71 |
+ M |
+
+
+ | 266 |
+ GSM388299 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388299M78A |
+ 78 |
+ M |
+
+
+ | 267 |
+ GSM388300 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388300F75A |
+ 75 |
+ F |
+
+
+ | 268 |
+ GSM388301 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388301F84A |
+ 84 |
+ F |
+
+
+ | 269 |
+ GSM388302 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388302M73A |
+ 73 |
+ M |
+
+
+ | 270 |
+ GSM388303 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388303F89A |
+ 89 |
+ F |
+
+
+ | 271 |
+ GSM388304 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388304FNAA |
+ NA |
+ F |
+
+
+ | 272 |
+ GSM388305 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388305M69A |
+ 69 |
+ M |
+
+
+ | 273 |
+ GSM388306 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388306M83A |
+ 83 |
+ M |
+
+
+ | 274 |
+ GSM388307 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388307M71A |
+ 71 |
+ M |
+
+
+ | 275 |
+ GSM388308 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388308F86A |
+ 86 |
+ F |
+
+
+ | 276 |
+ GSM388309 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388309M82A |
+ 82 |
+ M |
+
+
+ | 277 |
+ GSM388310 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388310FNAA |
+ NA |
+ F |
+
+
+ | 278 |
+ GSM388311 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388311M88A |
+ 88 |
+ M |
+
+
+ | 279 |
+ GSM388312 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388312M77A |
+ 77 |
+ M |
+
+
+ | 280 |
+ GSM388313 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388313M85A |
+ 85 |
+ M |
+
+
+ | 281 |
+ GSM388314 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388314F81A |
+ 81 |
+ F |
+
+
+ | 282 |
+ GSM388315 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388315F86A |
+ 86 |
+ F |
+
+
+ | 283 |
+ GSM388316 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388316M89A |
+ 89 |
+ M |
+
+
+ | 284 |
+ GSM388317 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388317F73A |
+ 73 |
+ F |
+
+
+ | 285 |
+ GSM388318 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388318F96A |
+ 96 |
+ F |
+
+
+ | 286 |
+ GSM388319 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388319M73A |
+ 73 |
+ M |
+
+
+ | 287 |
+ GSM388320 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388320M81A |
+ 81 |
+ M |
+
+
+ | 288 |
+ GSM388321 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388321F84A |
+ 84 |
+ F |
+
+
+ | 289 |
+ GSM388322 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388322F93A |
+ 93 |
+ F |
+
+
+ | 290 |
+ GSM388323 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388323F82A |
+ 82 |
+ F |
+
+
+ | 291 |
+ GSM388324 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388324M76A |
+ 76 |
+ M |
+
+
+ | 292 |
+ GSM388325 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388325M77A |
+ 77 |
+ M |
+
+
+ | 293 |
+ GSM388326 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388326F86A |
+ 86 |
+ F |
+
+
+ | 294 |
+ GSM388327 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388327F85A |
+ 85 |
+ F |
+
+
+ | 295 |
+ GSM388328 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388328M83A |
+ 83 |
+ M |
+
+
+ | 296 |
+ GSM388329 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388329M76A |
+ 76 |
+ M |
+
+
+ | 297 |
+ GSM388330 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388330M81A |
+ 81 |
+ M |
+
+
+ | 298 |
+ GSM388331 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388331M79A |
+ 79 |
+ M |
+
+
+ | 299 |
+ GSM388332 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388332M81A |
+ 81 |
+ M |
+
+
+ | 300 |
+ GSM388333 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388333F78A |
+ 78 |
+ F |
+
+
+ | 301 |
+ GSM388334 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388334M80A |
+ 80 |
+ M |
+
+
+ | 302 |
+ GSM388335 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388335M84A |
+ 84 |
+ M |
+
+
+ | 303 |
+ GSM388336 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388336F85A |
+ 85 |
+ F |
+
+
+ | 304 |
+ GSM388337 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388337M75A |
+ 75 |
+ M |
+
+
+ | 305 |
+ GSM388338 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388338F80A |
+ 80 |
+ F |
+
+
+ | 306 |
+ GSM388339 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388339F97A |
+ 97 |
+ F |
+
+
+ | 307 |
+ GSM388340 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388340F82A |
+ 82 |
+ F |
+
+
+ | 308 |
+ GSM388341 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388341M82A |
+ 82 |
+ M |
+
+
+ | 309 |
+ GSM388342 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388342M77A |
+ 77 |
+ M |
+
+
+ | 310 |
+ GSM388343 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388343M81A |
+ 81 |
+ M |
+
+
+ | 311 |
+ GSM388345 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388345F96A |
+ 96 |
+ F |
+
+
+ | 312 |
+ GSM388346 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388346F90A |
+ 90 |
+ F |
+
+
+ | 313 |
+ GSM388347 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388347M86A |
+ 86 |
+ M |
+
+
+ | 314 |
+ GSM388348 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388348M88A |
+ 88 |
+ M |
+
+
+ | 315 |
+ GSM388349 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388349F90A |
+ 90 |
+ F |
+
+
+ | 316 |
+ GSM388350 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388350F90A |
+ 90 |
+ F |
+
+
+ | 317 |
+ GSM388351 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388351F84A |
+ 84 |
+ F |
+
+
+ | 318 |
+ GSM388352 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388352M84A |
+ 84 |
+ M |
+
+
+ | 319 |
+ GSM388353 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388353F91A |
+ 91 |
+ F |
+
+
+ | 320 |
+ GSM388354 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388354F81A |
+ 81 |
+ F |
+
+
+ | 321 |
+ GSM388355 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388355F84A |
+ 84 |
+ F |
+
+
+ | 322 |
+ GSM388356 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388356M80A |
+ 80 |
+ M |
+
+
+ | 323 |
+ GSM388357 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388357M81A |
+ 81 |
+ M |
+
+
+ | 324 |
+ GSM388358 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388358F87A |
+ 87 |
+ F |
+
+
+ | 325 |
+ GSM388359 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388359M85A |
+ 85 |
+ M |
+
+
+ | 326 |
+ GSM388360 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388360F90A |
+ 90 |
+ F |
+
+
+ | 327 |
+ GSM388361 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388361M79A |
+ 79 |
+ M |
+
+
+ | 328 |
+ GSM388362 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388362F87A |
+ 87 |
+ F |
+
+
+ | 329 |
+ GSM388363 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388363M75A |
+ 75 |
+ M |
+
+
+ | 330 |
+ GSM388364 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388364F92A |
+ 92 |
+ F |
+
+
+ | 331 |
+ GSM388365 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388365F84A |
+ 84 |
+ F |
+
+
+ | 332 |
+ GSM388366 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388366M75A |
+ 75 |
+ M |
+
+
+ | 333 |
+ GSM388367 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388367F76A |
+ 76 |
+ F |
+
+
+ | 334 |
+ GSM388368 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388368F86A |
+ 86 |
+ F |
+
+
+ | 335 |
+ GSM388369 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388369M82A |
+ 82 |
+ M |
+
+
+ | 336 |
+ GSM388370 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388370M76A |
+ 76 |
+ M |
+
+
+ | 337 |
+ GSM388371 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388371F81A |
+ 81 |
+ F |
+
+
+ | 338 |
+ GSM388372 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388372F80A |
+ 80 |
+ F |
+
+
+ | 339 |
+ GSM388373 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388373M83A |
+ 83 |
+ M |
+
+
+ | 340 |
+ GSM388374 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388374F83A |
+ 83 |
+ F |
+
+
+ | 341 |
+ GSM388375 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388375F84A |
+ 84 |
+ F |
+
+
+ | 342 |
+ GSM388376 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388376M93A |
+ 93 |
+ M |
+
+
+ | 343 |
+ GSM388377 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388377F92A |
+ 92 |
+ F |
+
+
+ | 344 |
+ GSM388378 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388378M78A |
+ 78 |
+ M |
+
+
+ | 345 |
+ GSM388379 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388379M90A |
+ 90 |
+ M |
+
+
+ | 346 |
+ GSM388380 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388380M83A |
+ 83 |
+ M |
+
+
+ | 347 |
+ GSM388381 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388381M79A |
+ 79 |
+ M |
+
+
+ | 348 |
+ GSM388382 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388382M84A |
+ 84 |
+ M |
+
+
+ | 349 |
+ GSM388383 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388383F90A |
+ 90 |
+ F |
+
+
+ | 350 |
+ GSM388384 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388384F88A |
+ 88 |
+ F |
+
+
+ | 351 |
+ GSM388385 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388385M77A |
+ 77 |
+ M |
+
+
+ | 352 |
+ GSM388386 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388386F80A |
+ 80 |
+ F |
+
+
+ | 353 |
+ GSM388387 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388387M87A |
+ 87 |
+ M |
+
+
+ | 354 |
+ GSM388388 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388388M86A |
+ 86 |
+ M |
+
+
+ | 355 |
+ GSM388389 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388389M74A |
+ 74 |
+ M |
+
+
+ | 356 |
+ GSM388390 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388390F86A |
+ 86 |
+ F |
+
+
+ | 357 |
+ GSM388391 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388391F81A |
+ 81 |
+ F |
+
+
+ | 358 |
+ GSM388392 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388392F73A |
+ 73 |
+ F |
+
+
+ | 359 |
+ GSM388393 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388393M83A |
+ 83 |
+ M |
+
+
+ | 360 |
+ GSM388394 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388394M86A |
+ 86 |
+ M |
+
+
+ | 361 |
+ GSM388395 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388395F86A |
+ 86 |
+ F |
+
+
+ | 362 |
+ GSM388396 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388396M78A |
+ 78 |
+ M |
+
+
+ | 363 |
+ GSM388397 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388397M83A |
+ 83 |
+ M |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Gse15222_f_n_ri_0409/contributors.rtf b/general/datasets/Gse15222_f_n_ri_0409/contributors.rtf
new file mode 100644
index 0000000..72c2296
--- /dev/null
+++ b/general/datasets/Gse15222_f_n_ri_0409/contributors.rtf
@@ -0,0 +1 @@
+Webster J, Gibbs R, Myers A
diff --git a/general/datasets/Gse15222_f_n_ri_0409/experiment-design.rtf b/general/datasets/Gse15222_f_n_ri_0409/experiment-design.rtf
new file mode 100644
index 0000000..07d1b52
--- /dev/null
+++ b/general/datasets/Gse15222_f_n_ri_0409/experiment-design.rtf
@@ -0,0 +1,5 @@
+Expression profiling by array
+
+We recently surveyed the relationship between the human brain transcriptome and genome in a series of neuropathologically normal postmortem samples. We now have analyzed additional samples with a confirmed pathologic diagnosis of late onset Alzheimer's disease (LOAD, final n=187 controls, 176 cases). Nine percent of the cortical transcripts we analyzed had expression profiles correlated with their genotypes in the combined cohort and approximately 5% of transcripts had SNP-transcript relationships that could distinguish LOAD samples. Two of these transcripts have been previously implicated in LOAD candidate gene SNP-expression screens. This study shows how the relationship between common inherited genetic variants and brain transcript expression can be used in the study of human brain disorders. We suggest that studying the transcriptome as a quantitative endo-phenotype has greater power to find risk SNPs influencing expression than the use of discrete diagnostic categories such as presence or absence of disease. see DOI:10.1016/j.ajhg.2009.03.011 for further details and complete author list.
+
+Expression quantitative trait loci study using human brain from 363 cortical samples. Affymetrix 500K chip for genotyping, Illumina Sentrix Human-ref 8 bead array chip for expression. Genotyping data will be available at dbGAP.
diff --git a/general/datasets/Gse15222_f_n_ri_0409/experiment-type.rtf b/general/datasets/Gse15222_f_n_ri_0409/experiment-type.rtf
new file mode 100644
index 0000000..0546e04
--- /dev/null
+++ b/general/datasets/Gse15222_f_n_ri_0409/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array
\ No newline at end of file
diff --git a/general/datasets/Gse15222_f_n_ri_0409/notes.rtf b/general/datasets/Gse15222_f_n_ri_0409/notes.rtf
new file mode 100644
index 0000000..e7bd85c
--- /dev/null
+++ b/general/datasets/Gse15222_f_n_ri_0409/notes.rtf
@@ -0,0 +1,6 @@
+Access to the original data from Dr. Myers' laboratory
+or GEO GSE15222
+PMI = Post Mortem Interval
+Cannot find this record in the GEO website: WGACON-120
+
+This data is based on May 2004 (NCBI35/hg17).
diff --git a/general/datasets/Gse15222_f_n_ri_0409/platform.rtf b/general/datasets/Gse15222_f_n_ri_0409/platform.rtf
new file mode 100644
index 0000000..5bcda8b
--- /dev/null
+++ b/general/datasets/Gse15222_f_n_ri_0409/platform.rtf
@@ -0,0 +1,5 @@
+Illumina Human 50 mer probes. Total of 24357 probes according to Myers et al. A total of 24354 probes included in this GeneNetwork file.
+
+From the Methods section of the paper:
+
+Genotyping and Expression Proï¬ling DNA was hybridized to the Affymetrix GeneChip Human Mapping 500K Array Set (502,627 SNPs) as previously described.11,12 Genotypes were extracted with the use of both SNiPer-HD13 and BRLMM (Affymetrix, Santa Clara, CA) algorithms. Genotypes that exhibited less than 98% concordance between calls were excluded. SNPs with call rates less than 90% were excluded from the analysis. HardyWeinberg equilibrium (HWE) was assessed with exact tests and the PLINK analysis toolset.14 SNPs with HWE exact-test p values less than 0.05, as well as SNPs with minor-allele frequencies less than 1%, were excluded. Allele calls had a mean of 97% and a range of 90%–99%. cRNA was hybridized to Illumina Human Refseq-8 Expression BeadChip (24,357 transcripts) via standard protocols. Expression proï¬les were extracted and rank invariant normalized15–17 with the use of the BeadStudio software available from Illumina, with the Illumina custom error model used. Rankinvariant-normalized expression data were log10 transformed, and missing data were encoded as missing, rather than as a zero level of expression.
diff --git a/general/datasets/Gse15222_f_n_ri_0409/summary.rtf b/general/datasets/Gse15222_f_n_ri_0409/summary.rtf
new file mode 100644
index 0000000..e99fa9e
--- /dev/null
+++ b/general/datasets/Gse15222_f_n_ri_0409/summary.rtf
@@ -0,0 +1,9 @@
+Myers and colleagues generated massive neocortical transcriptome data sets for a set of unrelated elderly neurologically and neuropathologically normal humans and from confirmed late onset Alzheimer's disease patients (LOAD, n = 187 normal and 176 LOAD cases, see DOI:10.1016/j.ajhg.2009.03.011 for detail). They used an Illumina Sentrix Bead array (HumanRef-8) that measures expression of approximately 19,730 curated RefSeq sequences (Human Build 34).
+
+Case identifiers: All case identifiers (IDs) in GeneNetwork begin with a capital C followed by a six digit GEO identifier, followed by the sex and age in years. Non-Alzheimer cases are labeled with the suffix letter N: C225652M85N. Alzheimer cases are labeled with the suffix letter A: C388217F97A.
+
+Data were initially downloaded from the NCBI GEO archive under the experiment ID GSE15222. All data were generated using the Illumina HumanRef-8 expression BeadChip (GPL2700) v2 Rev0. This data set in GeneNetwork includes data for 24,354 probes. We have realigned the 50-mer sequences by BLAT to the latest version of the human genome (Feb 2009, hg19) and reannotated the array (August 2009). The annotation in GN will differ from that provided in GEO for this platform. We were unable to obtain 50-mer sequences for several thousand probes (e.g., HTT), and these probes have therefore not been realigned to the human genome.
+
+The GEO data set was processed by Myers and colleagues using Illumina's Rank Invariant transform. We performed a series of QC and renormalization steps to the data to allow more facile comparison to other data sets in GeneNetwork. In brief, data is log2 transformed. We recentered each array to a mean expression of 8 units and a standard deviation of 2 units (2z + 8 transform). The values are therefore modified z scores and each unit represents roughly a two-fold difference in expression. Average expression across all 363 cases range from a low of 6 units (e.g., SYT15) to a high of 19 units for ARSK. APOE has an average expression of 15 units and APP has an average expression of 11.5 units.. The distribution is far from normal with a great excess of measurements of genes with low to moderate expression clustered between 6.5 and 8.5 units.
+
+A small number of arrays (n = 6, GSM226040, GSM226041, GSM226042, GSM226044, GSM226045, GSM226046) had a different distribution from the great majority of other arrays. This was probably due to a batch processing effect. Members of this minority group belonged to both normal and LOAD cases. This putative batch effect has been eliminated in the GeneNetwork rendition of the Myers data. To eliminate the putative batch effect, we simply computed a mean offset for each probe in the "minority set" relative to the remaining "majority set" and added or subtracted this offset to force the mean of each probe in the minority set to conform to mean of the same probe in the majority set.
diff --git a/general/datasets/Gse15222_f_ri_0409/acknowledgment.rtf b/general/datasets/Gse15222_f_ri_0409/acknowledgment.rtf
new file mode 100644
index 0000000..c203ed9
--- /dev/null
+++ b/general/datasets/Gse15222_f_ri_0409/acknowledgment.rtf
@@ -0,0 +1 @@
+http://labs.med.miami.edu/myers
diff --git a/general/datasets/Gse15222_f_ri_0409/cases.rtf b/general/datasets/Gse15222_f_ri_0409/cases.rtf
new file mode 100644
index 0000000..6933d14
--- /dev/null
+++ b/general/datasets/Gse15222_f_ri_0409/cases.rtf
@@ -0,0 +1,3290 @@
+
+
+
+
+
+
+
+
+
+ | Index |
+ GEO Series |
+ Organ Region |
+ Tissue |
+ Case ID |
+ Age |
+ Sex |
+
+
+ | 1 |
+ GSM225652 |
+ Temporal Cortex |
+ Normal |
+ C225652M85N |
+ 85 |
+ M |
+
+
+ | 2 |
+ GSM225662 |
+ Temporal Cortex |
+ Normal |
+ C225662M85N |
+ 85 |
+ M |
+
+
+ | 3 |
+ GSM225664 |
+ Temporal Cortex |
+ Normal |
+ C225664F79N |
+ 79 |
+ F |
+
+
+ | 4 |
+ GSM225665 |
+ Temporal Cortex |
+ Normal |
+ C225665F85N |
+ 85 |
+ F |
+
+
+ | 5 |
+ GSM225666 |
+ Temporal Cortex |
+ Normal |
+ C225666F73N |
+ 73 |
+ F |
+
+
+ | 6 |
+ GSM225667 |
+ Temporal Cortex |
+ Normal |
+ C225667M81N |
+ 81 |
+ M |
+
+
+ | 7 |
+ GSM225668 |
+ Temporal Cortex |
+ Normal |
+ C225668M79N |
+ 79 |
+ M |
+
+
+ | 8 |
+ GSM225669 |
+ Temporal Cortex |
+ Normal |
+ C225669M77N |
+ 77 |
+ M |
+
+
+ | 9 |
+ GSM225670 |
+ Temporal Cortex |
+ Normal |
+ C225670M69N |
+ 69 |
+ M |
+
+
+ | 10 |
+ GSM225671 |
+ Temporal Cortex |
+ Normal |
+ C225671M86N |
+ 86 |
+ M |
+
+
+ | 11 |
+ GSM225672 |
+ Temporal Cortex |
+ Normal |
+ C225672F83N |
+ 83 |
+ F |
+
+
+ | 12 |
+ GSM225673 |
+ Temporal Cortex |
+ Normal |
+ C225673M78N |
+ 78 |
+ M |
+
+
+ | 13 |
+ GSM225674 |
+ Temporal Cortex |
+ Normal |
+ C225674M94N |
+ 94 |
+ M |
+
+
+ | 14 |
+ GSM225675 |
+ Temporal Cortex |
+ Normal |
+ C225675F81N |
+ 81 |
+ F |
+
+
+ | 15 |
+ GSM225676 |
+ Temporal Cortex |
+ Normal |
+ C225676M76N |
+ 76 |
+ M |
+
+
+ | 16 |
+ GSM225677 |
+ Temporal Cortex |
+ Normal |
+ C225677M83N |
+ 83 |
+ M |
+
+
+ | 17 |
+ GSM225678 |
+ Temporal Cortex |
+ Normal |
+ C225678M68N |
+ 68 |
+ M |
+
+
+ | 18 |
+ GSM225679 |
+ Temporal Cortex |
+ Normal |
+ C225679F82N |
+ 82 |
+ F |
+
+
+ | 19 |
+ GSM225680 |
+ Temporal Cortex |
+ Normal |
+ C225680F70N |
+ 70 |
+ F |
+
+
+ | 20 |
+ GSM225681 |
+ Temporal Cortex |
+ Normal |
+ C225681M86N |
+ 86 |
+ M |
+
+
+ | 21 |
+ GSM225682 |
+ Temporal Cortex |
+ Normal |
+ C225682M78N |
+ 78 |
+ M |
+
+
+ | 22 |
+ GSM225683 |
+ Temporal Cortex |
+ Normal |
+ C225683M82N |
+ 82 |
+ M |
+
+
+ | 23 |
+ GSM225684 |
+ Temporal Cortex |
+ Normal |
+ C225684F94N |
+ 94 |
+ F |
+
+
+ | 24 |
+ GSM225685 |
+ Temporal Cortex |
+ Normal |
+ C225685F87N |
+ 87 |
+ F |
+
+
+ | 25 |
+ GSM225686 |
+ Temporal Cortex |
+ Normal |
+ C225686M74N |
+ 74 |
+ M |
+
+
+ | 26 |
+ GSM225687 |
+ Temporal Cortex |
+ Normal |
+ C225687M85N |
+ 85 |
+ M |
+
+
+ | 27 |
+ GSM225688 |
+ Temporal Cortex |
+ Normal |
+ C225688M75N |
+ 75 |
+ M |
+
+
+ | 28 |
+ GSM225689 |
+ Temporal Cortex |
+ Normal |
+ C225689F86N |
+ 86 |
+ F |
+
+
+ | 29 |
+ GSM225690 |
+ Temporal Cortex |
+ Normal |
+ C225690M75N |
+ 75 |
+ M |
+
+
+ | 30 |
+ GSM225691 |
+ Temporal Cortex |
+ Normal |
+ C225691M81N |
+ 81 |
+ M |
+
+
+ | 31 |
+ GSM225692 |
+ Temporal Cortex |
+ Normal |
+ C225692F72N |
+ 72 |
+ F |
+
+
+ | 32 |
+ GSM225693 |
+ Temporal Cortex |
+ Normal |
+ C225693F81N |
+ 81 |
+ F |
+
+
+ | 33 |
+ GSM225695 |
+ Temporal Cortex |
+ Normal |
+ C225695M81N |
+ 81 |
+ M |
+
+
+ | 34 |
+ GSM225696 |
+ Temporal Cortex |
+ Normal |
+ C225696M81N |
+ 81 |
+ M |
+
+
+ | 35 |
+ GSM225697 |
+ Temporal Cortex |
+ Normal |
+ C225697M91N |
+ 91 |
+ M |
+
+
+ | 36 |
+ GSM225698 |
+ Temporal Cortex |
+ Normal |
+ C225698M84N |
+ 84 |
+ M |
+
+
+ | 37 |
+ GSM225699 |
+ Temporal Cortex |
+ Normal |
+ C225699M96N |
+ 96 |
+ M |
+
+
+ | 38 |
+ GSM225700 |
+ Temporal Cortex |
+ Normal |
+ C225700F97N |
+ 97 |
+ F |
+
+
+ | 39 |
+ GSM225701 |
+ Temporal Cortex |
+ Normal |
+ C225701M90N |
+ 90 |
+ M |
+
+
+ | 40 |
+ GSM225702 |
+ Temporal Cortex |
+ Normal |
+ C225702F67N |
+ 67 |
+ F |
+
+
+ | 41 |
+ GSM225703 |
+ Temporal Cortex |
+ Normal |
+ C225703F83N |
+ 83 |
+ F |
+
+
+ | 42 |
+ GSM225704 |
+ Temporal Cortex |
+ Normal |
+ C225704F82N |
+ 82 |
+ F |
+
+
+ | 43 |
+ GSM225705 |
+ Temporal Cortex |
+ Normal |
+ C225705F66N |
+ 66 |
+ F |
+
+
+ | 44 |
+ GSM225706 |
+ Temporal Cortex |
+ Normal |
+ C225706F72N |
+ 72 |
+ F |
+
+
+ | 45 |
+ GSM225707 |
+ Temporal Cortex |
+ Normal |
+ C225707F65N |
+ 65 |
+ F |
+
+
+ | 46 |
+ GSM225708 |
+ Temporal Cortex |
+ Normal |
+ C225708F75N |
+ 75 |
+ F |
+
+
+ | 47 |
+ GSM225709 |
+ Temporal Cortex |
+ Normal |
+ C225709F74N |
+ 74 |
+ F |
+
+
+ | 48 |
+ GSM225711 |
+ Temporal Cortex |
+ Normal |
+ C225711M68N |
+ 68 |
+ M |
+
+
+ | 49 |
+ GSM225713 |
+ Temporal Cortex |
+ Normal |
+ C225713F80N |
+ 80 |
+ F |
+
+
+ | 50 |
+ GSM225714 |
+ Temporal Cortex |
+ Normal |
+ C225714M80N |
+ 80 |
+ M |
+
+
+ | 51 |
+ GSM225715 |
+ Temporal Cortex |
+ Normal |
+ C225715M66N |
+ 66 |
+ M |
+
+
+ | 52 |
+ GSM225717 |
+ Temporal Cortex |
+ Normal |
+ C225717M88N |
+ 88 |
+ M |
+
+
+ | 53 |
+ GSM225718 |
+ Temporal Cortex |
+ Normal |
+ C225718F91N |
+ 91 |
+ F |
+
+
+ | 54 |
+ GSM225719 |
+ Temporal Cortex |
+ Normal |
+ C225719M73N |
+ 73 |
+ M |
+
+
+ | 55 |
+ GSM225720 |
+ Temporal Cortex |
+ Normal |
+ C225720M76N |
+ 76 |
+ M |
+
+
+ | 56 |
+ GSM225721 |
+ Temporal Cortex |
+ Normal |
+ C225721M75N |
+ 75 |
+ M |
+
+
+ | 57 |
+ GSM225722 |
+ Temporal Cortex |
+ Normal |
+ C225722F86N |
+ 86 |
+ F |
+
+
+ | 58 |
+ GSM225723 |
+ Temporal Cortex |
+ Normal |
+ C225723F72N |
+ 72 |
+ F |
+
+
+ | 59 |
+ GSM225724 |
+ Temporal Cortex |
+ Normal |
+ C225724M97N |
+ 97 |
+ M |
+
+
+ | 60 |
+ GSM225725 |
+ Temporal Cortex |
+ Normal |
+ C225725M86N |
+ 86 |
+ M |
+
+
+ | 61 |
+ GSM225726 |
+ Temporal Cortex |
+ Normal |
+ C225726M82N |
+ 82 |
+ M |
+
+
+ | 62 |
+ GSM225727 |
+ Temporal Cortex |
+ Normal |
+ C225727F95N |
+ 95 |
+ F |
+
+
+ | 63 |
+ GSM225728 |
+ Temporal Cortex |
+ Normal |
+ C225728F76N |
+ 76 |
+ F |
+
+
+ | 64 |
+ GSM225729 |
+ Temporal Cortex |
+ Normal |
+ C225729M76N |
+ 76 |
+ M |
+
+
+ | 65 |
+ GSM225730 |
+ Temporal Cortex |
+ Normal |
+ C225730M69N |
+ 69 |
+ M |
+
+
+ | 66 |
+ GSM225731 |
+ Temporal Cortex |
+ Normal |
+ C225731F80N |
+ 80 |
+ F |
+
+
+ | 67 |
+ GSM225732 |
+ Temporal Cortex |
+ Normal |
+ C225732F99N |
+ 99 |
+ F |
+
+
+ | 68 |
+ GSM225733 |
+ Temporal Cortex |
+ Normal |
+ C225733M68N |
+ 68 |
+ M |
+
+
+ | 69 |
+ GSM225734 |
+ Temporal Cortex |
+ Normal |
+ C225734M70N |
+ 70 |
+ M |
+
+
+ | 70 |
+ GSM225735 |
+ Temporal Cortex |
+ Normal |
+ C225735F87N |
+ 87 |
+ F |
+
+
+ | 71 |
+ GSM225736 |
+ Temporal Cortex |
+ Normal |
+ C225736F99N |
+ 99 |
+ F |
+
+
+ | 72 |
+ GSM225737 |
+ Temporal Cortex |
+ Normal |
+ C225737F88N |
+ 88 |
+ F |
+
+
+ | 73 |
+ GSM225739 |
+ Temporal Cortex |
+ Normal |
+ C225739M65N |
+ 65 |
+ M |
+
+
+ | 74 |
+ GSM225741 |
+ Temporal Cortex |
+ Normal |
+ C225741M82N |
+ 82 |
+ M |
+
+
+ | 75 |
+ GSM225742 |
+ Temporal Cortex |
+ Normal |
+ C225742F78N |
+ 78 |
+ F |
+
+
+ | 76 |
+ GSM225743 |
+ Temporal Cortex |
+ Normal |
+ C225743F85N |
+ 85 |
+ F |
+
+
+ | 77 |
+ GSM225744 |
+ Temporal Cortex |
+ Normal |
+ C225744F100N |
+ 100 |
+ F |
+
+
+ | 78 |
+ GSM225745 |
+ Temporal Cortex |
+ Normal |
+ C225745F87N |
+ 87 |
+ F |
+
+
+ | 79 |
+ GSM225746 |
+ Temporal Cortex |
+ Normal |
+ C225746F85N |
+ 85 |
+ F |
+
+
+ | 80 |
+ GSM225747 |
+ Temporal Cortex |
+ Normal |
+ C225747F97N |
+ 97 |
+ F |
+
+
+ | 81 |
+ GSM225748 |
+ Temporal Cortex |
+ Normal |
+ C225748M65N |
+ 65 |
+ M |
+
+
+ | 82 |
+ GSM225749 |
+ Temporal Cortex |
+ Normal |
+ C225749M65N |
+ 65 |
+ M |
+
+
+ | 83 |
+ GSM225751 |
+ Temporal Cortex |
+ Normal |
+ C225751F87N |
+ 87 |
+ F |
+
+
+ | 84 |
+ GSM225752 |
+ Temporal Cortex |
+ Normal |
+ C225752F85N |
+ 85 |
+ F |
+
+
+ | 85 |
+ GSM225753 |
+ Temporal Cortex |
+ Normal |
+ C225753M68N |
+ 68 |
+ M |
+
+
+ | 86 |
+ GSM225754 |
+ Temporal Cortex |
+ Normal |
+ C225754M71N |
+ 71 |
+ M |
+
+
+ | 87 |
+ GSM225755 |
+ Temporal Cortex |
+ Normal |
+ C225755F83N |
+ 83 |
+ F |
+
+
+ | 88 |
+ GSM225756 |
+ Temporal Cortex |
+ Normal |
+ C225756M76N |
+ 76 |
+ M |
+
+
+ | 89 |
+ GSM225757 |
+ Temporal Cortex |
+ Normal |
+ C225757M67N |
+ 67 |
+ M |
+
+
+ | 90 |
+ GSM225758 |
+ Temporal Cortex |
+ Normal |
+ C225758F100N |
+ 100 |
+ F |
+
+
+ | 91 |
+ GSM225759 |
+ Temporal Cortex |
+ Normal |
+ C225759M79N |
+ 79 |
+ M |
+
+
+ | 92 |
+ GSM225760 |
+ Temporal Cortex |
+ Normal |
+ C225760M74N |
+ 74 |
+ M |
+
+
+ | 93 |
+ GSM225761 |
+ Temporal Cortex |
+ Normal |
+ C225761F88N |
+ 88 |
+ F |
+
+
+ | 94 |
+ GSM225762 |
+ Temporal Cortex |
+ Normal |
+ C225762M70N |
+ 70 |
+ M |
+
+
+ | 95 |
+ GSM225763 |
+ Temporal Cortex |
+ Normal |
+ C225763F97N |
+ 97 |
+ F |
+
+
+ | 96 |
+ GSM225764 |
+ Temporal Cortex |
+ Normal |
+ C225764M69N |
+ 69 |
+ M |
+
+
+ | 97 |
+ GSM225915 |
+ Temporal Cortex |
+ Normal |
+ C225915F99N |
+ 99 |
+ F |
+
+
+ | 98 |
+ GSM225916 |
+ Temporal Cortex |
+ Normal |
+ C225916M81N |
+ 81 |
+ M |
+
+
+ | 99 |
+ GSM225917 |
+ Temporal Cortex |
+ Normal |
+ C225917F85N |
+ 85 |
+ F |
+
+
+ | 100 |
+ GSM225918 |
+ Temporal Cortex |
+ Normal |
+ C225918F82N |
+ 82 |
+ F |
+
+
+ | 101 |
+ GSM225919 |
+ Temporal Cortex |
+ Normal |
+ C225919M70N |
+ 70 |
+ M |
+
+
+ | 102 |
+ GSM225920 |
+ Temporal Cortex |
+ Normal |
+ C225920M73N |
+ 73 |
+ M |
+
+
+ | 103 |
+ GSM225921 |
+ Temporal Cortex |
+ Normal |
+ C225921M83N |
+ 83 |
+ M |
+
+
+ | 104 |
+ GSM225922 |
+ Temporal Cortex |
+ Normal |
+ C225922M74N |
+ 74 |
+ M |
+
+
+ | 105 |
+ GSM225923 |
+ Temporal Cortex |
+ Normal |
+ C225923M77N |
+ 77 |
+ M |
+
+
+ | 106 |
+ GSM225924 |
+ Temporal Cortex |
+ Normal |
+ C225924M81N |
+ 81 |
+ M |
+
+
+ | 107 |
+ GSM225925 |
+ Temporal Cortex |
+ Normal |
+ C225925M65N |
+ 65 |
+ M |
+
+
+ | 108 |
+ GSM225926 |
+ Temporal Cortex |
+ Normal |
+ C225926F73N |
+ 73 |
+ F |
+
+
+ | 109 |
+ GSM225927 |
+ Temporal Cortex |
+ Normal |
+ C225927F85N |
+ 85 |
+ F |
+
+
+ | 110 |
+ GSM225928 |
+ Temporal Cortex |
+ Normal |
+ C225928M69N |
+ 69 |
+ M |
+
+
+ | 111 |
+ GSM225929 |
+ Temporal Cortex |
+ Normal |
+ C225929M72N |
+ 72 |
+ M |
+
+
+ | 112 |
+ GSM225930 |
+ Temporal Cortex |
+ Normal |
+ C225930F76N |
+ 76 |
+ F |
+
+
+ | 113 |
+ GSM225931 |
+ Temporal Cortex |
+ Normal |
+ C225931M73N |
+ 73 |
+ M |
+
+
+ | 114 |
+ GSM225932 |
+ Temporal Cortex |
+ Normal |
+ C225932M66N |
+ 66 |
+ M |
+
+
+ | 115 |
+ GSM225933 |
+ Temporal Cortex |
+ Normal |
+ C225933F85N |
+ 85 |
+ F |
+
+
+ | 116 |
+ GSM225934 |
+ Temporal Cortex |
+ Normal |
+ C225934M87N |
+ 87 |
+ M |
+
+
+ | 117 |
+ GSM225935 |
+ Temporal Cortex |
+ Normal |
+ C225935F86N |
+ 86 |
+ F |
+
+
+ | 118 |
+ GSM225936 |
+ Temporal Cortex |
+ Normal |
+ C225936F73N |
+ 73 |
+ F |
+
+
+ | 119 |
+ GSM225937 |
+ Temporal Cortex |
+ Normal |
+ C225937M86N |
+ 86 |
+ M |
+
+
+ | 120 |
+ GSM225938 |
+ Temporal Cortex |
+ Normal |
+ C225938M72N |
+ 72 |
+ M |
+
+
+ | 121 |
+ GSM225939 |
+ Temporal Cortex |
+ Normal |
+ C225939F69N |
+ 69 |
+ F |
+
+
+ | 122 |
+ GSM225940 |
+ Temporal Cortex |
+ Normal |
+ C225940F88N |
+ 88 |
+ F |
+
+
+ | 123 |
+ GSM225941 |
+ Temporal Cortex |
+ Normal |
+ C225941M77N |
+ 77 |
+ M |
+
+
+ | 124 |
+ GSM225942 |
+ Temporal Cortex |
+ Normal |
+ C225942M96N |
+ 96 |
+ M |
+
+
+ | 125 |
+ GSM225943 |
+ Temporal Cortex |
+ Normal |
+ C225943F78N |
+ 78 |
+ F |
+
+
+ | 126 |
+ GSM225944 |
+ Temporal Cortex |
+ Normal |
+ C225944M77N |
+ 77 |
+ M |
+
+
+ | 127 |
+ GSM225945 |
+ Temporal Cortex |
+ Normal |
+ C225945F99N |
+ 99 |
+ F |
+
+
+ | 128 |
+ GSM225946 |
+ Temporal Cortex |
+ Normal |
+ C225946M78N |
+ 78 |
+ M |
+
+
+ | 129 |
+ GSM225947 |
+ Temporal Cortex |
+ Normal |
+ C225947F76N |
+ 76 |
+ F |
+
+
+ | 130 |
+ GSM225948 |
+ Temporal Cortex |
+ Normal |
+ C225948M78N |
+ 78 |
+ M |
+
+
+ | 131 |
+ GSM225949 |
+ Temporal Cortex |
+ Normal |
+ C225949F97N |
+ 97 |
+ F |
+
+
+ | 132 |
+ GSM225950 |
+ Temporal Cortex |
+ Normal |
+ C225950F86N |
+ 86 |
+ F |
+
+
+ | 133 |
+ GSM225951 |
+ Temporal Cortex |
+ Normal |
+ C225951M77N |
+ 77 |
+ M |
+
+
+ | 134 |
+ GSM225952 |
+ Temporal Cortex |
+ Normal |
+ C225952M87N |
+ 87 |
+ M |
+
+
+ | 135 |
+ GSM225953 |
+ Temporal Cortex |
+ Normal |
+ C225953F72N |
+ 72 |
+ F |
+
+
+ | 136 |
+ GSM225954 |
+ Temporal Cortex |
+ Normal |
+ C225954F91N |
+ 91 |
+ F |
+
+
+ | 137 |
+ GSM225955 |
+ Temporal Cortex |
+ Normal |
+ C225955F85N |
+ 85 |
+ F |
+
+
+ | 138 |
+ GSM225956 |
+ Temporal Cortex |
+ Normal |
+ C225956M88N |
+ 88 |
+ M |
+
+
+ | 139 |
+ GSM225957 |
+ Temporal Cortex |
+ Normal |
+ C225957F86N |
+ 86 |
+ F |
+
+
+ | 140 |
+ GSM225958 |
+ Temporal Cortex |
+ Normal |
+ C225958F93N |
+ 93 |
+ F |
+
+
+ | 141 |
+ GSM225959 |
+ Temporal Cortex |
+ Normal |
+ C225959M82N |
+ 82 |
+ M |
+
+
+ | 142 |
+ GSM225961 |
+ Temporal Cortex |
+ Normal |
+ C225961F72N |
+ 72 |
+ F |
+
+
+ | 143 |
+ GSM225962 |
+ Temporal Cortex |
+ Normal |
+ C225962F85N |
+ 85 |
+ F |
+
+
+ | 144 |
+ GSM225963 |
+ Temporal Cortex |
+ Normal |
+ C225963M70N |
+ 70 |
+ M |
+
+
+ | 145 |
+ GSM225964 |
+ Temporal Cortex |
+ Normal |
+ C225964F67N |
+ 67 |
+ F |
+
+
+ | 146 |
+ GSM225965 |
+ Temporal Cortex |
+ Normal |
+ C225965F74N |
+ 74 |
+ F |
+
+
+ | 147 |
+ GSM226034 |
+ Temporal Cortex |
+ Normal |
+ C226034M69N |
+ 69 |
+ M |
+
+
+ | 148 |
+ GSM226035 |
+ Temporal Cortex |
+ Normal |
+ C226035M85N |
+ 85 |
+ M |
+
+
+ | 149 |
+ GSM226037 |
+ Temporal Cortex |
+ Normal |
+ C226037M89N |
+ 89 |
+ M |
+
+
+ | 150 |
+ GSM226038 |
+ Temporal Cortex |
+ Normal |
+ C226038M86N |
+ 86 |
+ M |
+
+
+ | 151 |
+ GSM226039 |
+ Temporal Cortex |
+ Normal |
+ C226039M90N |
+ 90 |
+ M |
+
+
+ | 152 |
+ GSM226040 |
+ Temporal Cortex |
+ Normal |
+ C226040F94N |
+ 94 |
+ F |
+
+
+ | 153 |
+ GSM226041 |
+ Temporal Cortex |
+ Normal |
+ C226041F91N |
+ 91 |
+ F |
+
+
+ | 154 |
+ GSM226042 |
+ Temporal Cortex |
+ Normal |
+ C226042F91N |
+ 91 |
+ F |
+
+
+ | 155 |
+ GSM226044 |
+ Temporal Cortex |
+ Normal |
+ C226044F95N |
+ 95 |
+ F |
+
+
+ | 156 |
+ GSM226045 |
+ Temporal Cortex |
+ Normal |
+ C226045F95N |
+ 95 |
+ F |
+
+
+ | 157 |
+ GSM226046 |
+ Temporal Cortex |
+ Normal |
+ C226046F91N |
+ 91 |
+ F |
+
+
+ | 158 |
+ GSM226047 |
+ Temporal Cortex |
+ Normal |
+ C226047M80N |
+ 80 |
+ M |
+
+
+ | 159 |
+ GSM226048 |
+ Temporal Cortex |
+ Normal |
+ C226048M83N |
+ 83 |
+ M |
+
+
+ | 160 |
+ GSM226049 |
+ Temporal Cortex |
+ Normal |
+ C226049M67N |
+ 67 |
+ M |
+
+
+ | 161 |
+ GSM226050 |
+ Temporal Cortex |
+ Normal |
+ C226050M76N |
+ 76 |
+ M |
+
+
+ | 162 |
+ GSM226051 |
+ Temporal Cortex |
+ Normal |
+ C226051F86N |
+ 86 |
+ F |
+
+
+ | 163 |
+ GSM226052 |
+ Temporal Cortex |
+ Normal |
+ C226052F86N |
+ 86 |
+ F |
+
+
+ | 164 |
+ GSM226053 |
+ Temporal Cortex |
+ Normal |
+ C226053M83N |
+ 83 |
+ M |
+
+
+ | 165 |
+ GSM226055 |
+ Temporal Cortex |
+ Normal |
+ C226055M84N |
+ 84 |
+ M |
+
+
+ | 166 |
+ GSM226056 |
+ Temporal Cortex |
+ Normal |
+ C226056M80N |
+ 80 |
+ M |
+
+
+ | 167 |
+ GSM226082 |
+ Temporal Cortex |
+ Normal |
+ C226082M72N |
+ 72 |
+ M |
+
+
+ | 168 |
+ GSM226145 |
+ Temporal Cortex |
+ Normal |
+ C226145M67N |
+ 67 |
+ M |
+
+
+ | 169 |
+ GSM226146 |
+ Temporal Cortex |
+ Normal |
+ C226146F96N |
+ 96 |
+ F |
+
+
+ | 170 |
+ GSM226147 |
+ Temporal Cortex |
+ Normal |
+ C226147F75N |
+ 75 |
+ F |
+
+
+ | 171 |
+ GSM226148 |
+ Temporal Cortex |
+ Normal |
+ C226148F89N |
+ 89 |
+ F |
+
+
+ | 172 |
+ GSM226149 |
+ Temporal Cortex |
+ Normal |
+ C226149F86N |
+ 86 |
+ F |
+
+
+ | 173 |
+ GSM226150 |
+ Temporal Cortex |
+ Normal |
+ C226150M67N |
+ 67 |
+ M |
+
+
+ | 174 |
+ GSM226151 |
+ Temporal Cortex |
+ Normal |
+ C226151M77N |
+ 77 |
+ M |
+
+
+ | 175 |
+ GSM226154 |
+ Temporal Cortex |
+ Normal |
+ C226154M65N |
+ 65 |
+ M |
+
+
+ | 176 |
+ GSM226155 |
+ Temporal Cortex |
+ Normal |
+ C226155M69N |
+ 69 |
+ M |
+
+
+ | 177 |
+ GSM226156 |
+ Temporal Cortex |
+ Normal |
+ C226156M84N |
+ 84 |
+ M |
+
+
+ | 178 |
+ GSM226157 |
+ Temporal Cortex |
+ Normal |
+ C226157F85N |
+ 85 |
+ F |
+
+
+ | 179 |
+ GSM226158 |
+ Temporal Cortex |
+ Normal |
+ C226158M94N |
+ 94 |
+ M |
+
+
+ | 180 |
+ GSM226159 |
+ Temporal Cortex |
+ Normal |
+ C226159F89N |
+ 89 |
+ F |
+
+
+ | 181 |
+ GSM226160 |
+ Temporal Cortex |
+ Normal |
+ C226160M87N |
+ 87 |
+ M |
+
+
+ | 182 |
+ GSM226162 |
+ Temporal Cortex |
+ Normal |
+ C226162M90N |
+ 90 |
+ M |
+
+
+ | 183 |
+ GSM226163 |
+ Temporal Cortex |
+ Normal |
+ C226163F88N |
+ 88 |
+ F |
+
+
+ | 184 |
+ GSM226164 |
+ Temporal Cortex |
+ Normal |
+ C226164M94N |
+ 94 |
+ M |
+
+
+ | 185 |
+ GSM226165 |
+ Temporal Cortex |
+ Normal |
+ C226165F86N |
+ 86 |
+ F |
+
+
+ | 186 |
+ GSM226167 |
+ Temporal Cortex |
+ Normal |
+ C226167F93N |
+ 93 |
+ F |
+
+
+ | 187 |
+ GSM226168 |
+ Temporal Cortex |
+ Normal |
+ C226168M91N |
+ 91 |
+ M |
+
+
+ | 188 |
+ GSM388217 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388217F97A |
+ 97 |
+ F |
+
+
+ | 189 |
+ GSM388218 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388218F101A |
+ 101 |
+ F |
+
+
+ | 190 |
+ GSM388219 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388219M84A |
+ 84 |
+ M |
+
+
+ | 191 |
+ GSM388220 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388220F95A |
+ 95 |
+ F |
+
+
+ | 192 |
+ GSM388221 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388221F97A |
+ 97 |
+ F |
+
+
+ | 193 |
+ GSM388222 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388222F102A |
+ 102 |
+ F |
+
+
+ | 194 |
+ GSM388223 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388223M87A |
+ 87 |
+ M |
+
+
+ | 195 |
+ GSM388224 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388224F77A |
+ 77 |
+ F |
+
+
+ | 196 |
+ GSM388225 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388225M87A |
+ 87 |
+ M |
+
+
+ | 197 |
+ GSM388226 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388226M84A |
+ 84 |
+ M |
+
+
+ | 198 |
+ GSM388228 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 92 |
+ F |
+
+
+ | 199 |
+ GSM388229 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 93 |
+ M |
+
+
+ | 200 |
+ GSM388230 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388230F93A |
+ 93 |
+ F |
+
+
+ | 201 |
+ GSM388231 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 87 |
+ F |
+
+
+ | 202 |
+ GSM388232 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 90 |
+ F |
+
+
+ | 203 |
+ GSM388233 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 75 |
+ M |
+
+
+ | 204 |
+ GSM388234 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 92 |
+ M |
+
+
+ | 205 |
+ GSM388235 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 83 |
+ M |
+
+
+ | 206 |
+ GSM388236 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 88 |
+ M |
+
+
+ | 207 |
+ GSM388237 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 89 |
+ M |
+
+
+ | 208 |
+ GSM388238 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 74 |
+ F |
+
+
+ | 209 |
+ GSM388239 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 79 |
+ F |
+
+
+ | 210 |
+ GSM388240 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 80 |
+ M |
+
+
+ | 211 |
+ GSM388241 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 97 |
+ F |
+
+
+ | 212 |
+ GSM388242 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 87 |
+ M |
+
+
+ | 213 |
+ GSM388243 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 89 |
+ F |
+
+
+ | 214 |
+ GSM388244 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 90 |
+ F |
+
+
+ | 215 |
+ GSM388245 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 90 |
+ M |
+
+
+ | 216 |
+ GSM388246 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 78 |
+ M |
+
+
+ | 217 |
+ GSM388247 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 80 |
+ F |
+
+
+ | 218 |
+ GSM388248 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 79 |
+ F |
+
+
+ | 219 |
+ GSM388249 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 87 |
+ F |
+
+
+ | 220 |
+ GSM388250 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 88 |
+ F |
+
+
+ | 221 |
+ GSM388251 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 86 |
+ M |
+
+
+ | 222 |
+ GSM388252 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 74 |
+ F |
+
+
+ | 223 |
+ GSM388253 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 72 |
+ F |
+
+
+ | 224 |
+ GSM388254 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388254M81A |
+ 81 |
+ M |
+
+
+ | 225 |
+ GSM388255 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 68 |
+ F |
+
+
+ | 226 |
+ GSM388256 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 81 |
+ F |
+
+
+ | 227 |
+ GSM388257 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 82 |
+ F |
+
+
+ | 228 |
+ GSM388258 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388258M78A |
+ 78 |
+ M |
+
+
+ | 229 |
+ GSM388259 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388259M74A |
+ 74 |
+ M |
+
+
+ | 230 |
+ GSM388260 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388260M88A |
+ 88 |
+ M |
+
+
+ | 231 |
+ GSM388261 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388261F78A |
+ 78 |
+ F |
+
+
+ | 232 |
+ GSM388262 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 83 |
+ M |
+
+
+ | 233 |
+ GSM388263 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388263M83A |
+ 83 |
+ M |
+
+
+ | 234 |
+ GSM388264 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388264M80A |
+ 80 |
+ M |
+
+
+ | 235 |
+ GSM388265 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388265M84A |
+ 84 |
+ M |
+
+
+ | 236 |
+ GSM388266 |
+ Cortical Tissue |
+ Alzheimer's |
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+ 79 |
+ F |
+
+
+ | 237 |
+ GSM388267 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388267F86A |
+ 86 |
+ F |
+
+
+ | 238 |
+ GSM388268 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388268M92A |
+ 92 |
+ M |
+
+
+ | 239 |
+ GSM388269 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388269F81A |
+ 81 |
+ F |
+
+
+ | 240 |
+ GSM388270 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388270F79A |
+ 79 |
+ F |
+
+
+ | 241 |
+ GSM388271 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388271M74A |
+ 74 |
+ M |
+
+
+ | 242 |
+ GSM388272 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388272F73A |
+ 73 |
+ F |
+
+
+ | 243 |
+ GSM388273 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388273M87A |
+ 87 |
+ M |
+
+
+ | 244 |
+ GSM388274 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388274F86A |
+ 86 |
+ F |
+
+
+ | 245 |
+ GSM388275 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388275F86A |
+ 86 |
+ F |
+
+
+ | 246 |
+ GSM388276 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388276F87A |
+ 87 |
+ F |
+
+
+ | 247 |
+ GSM388277 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388277F92A |
+ 92 |
+ F |
+
+
+ | 248 |
+ GSM388278 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388278F78A |
+ 78 |
+ F |
+
+
+ | 249 |
+ GSM388279 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388279F94A |
+ 94 |
+ F |
+
+
+ | 250 |
+ GSM388281 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388281F94A |
+ 94 |
+ F |
+
+
+ | 251 |
+ GSM388282 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388282M76A |
+ 76 |
+ M |
+
+
+ | 252 |
+ GSM388284 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388284M91A |
+ 91 |
+ M |
+
+
+ | 253 |
+ GSM388285 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388285M86A |
+ 86 |
+ M |
+
+
+ | 254 |
+ GSM388286 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388286M77A |
+ 77 |
+ M |
+
+
+ | 255 |
+ GSM388287 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388287M82A |
+ 82 |
+ M |
+
+
+ | 256 |
+ GSM388288 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388288M78A |
+ 78 |
+ M |
+
+
+ | 257 |
+ GSM388289 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388289M79A |
+ 79 |
+ M |
+
+
+ | 258 |
+ GSM388290 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388290F84A |
+ 84 |
+ F |
+
+
+ | 259 |
+ GSM388291 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388291F87A |
+ 87 |
+ F |
+
+
+ | 260 |
+ GSM388292 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388292F86A |
+ 86 |
+ F |
+
+
+ | 261 |
+ GSM388294 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388294M83A |
+ 83 |
+ M |
+
+
+ | 262 |
+ GSM388295 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388295M83A |
+ 83 |
+ M |
+
+
+ | 263 |
+ GSM388296 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388296M81A |
+ 81 |
+ M |
+
+
+ | 264 |
+ GSM388297 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388297F93A |
+ 93 |
+ F |
+
+
+ | 265 |
+ GSM388298 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388298M71A |
+ 71 |
+ M |
+
+
+ | 266 |
+ GSM388299 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388299M78A |
+ 78 |
+ M |
+
+
+ | 267 |
+ GSM388300 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388300F75A |
+ 75 |
+ F |
+
+
+ | 268 |
+ GSM388301 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388301F84A |
+ 84 |
+ F |
+
+
+ | 269 |
+ GSM388302 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388302M73A |
+ 73 |
+ M |
+
+
+ | 270 |
+ GSM388303 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388303F89A |
+ 89 |
+ F |
+
+
+ | 271 |
+ GSM388304 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388304FNAA |
+ NA |
+ F |
+
+
+ | 272 |
+ GSM388305 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388305M69A |
+ 69 |
+ M |
+
+
+ | 273 |
+ GSM388306 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388306M83A |
+ 83 |
+ M |
+
+
+ | 274 |
+ GSM388307 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388307M71A |
+ 71 |
+ M |
+
+
+ | 275 |
+ GSM388308 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388308F86A |
+ 86 |
+ F |
+
+
+ | 276 |
+ GSM388309 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388309M82A |
+ 82 |
+ M |
+
+
+ | 277 |
+ GSM388310 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388310FNAA |
+ NA |
+ F |
+
+
+ | 278 |
+ GSM388311 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388311M88A |
+ 88 |
+ M |
+
+
+ | 279 |
+ GSM388312 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388312M77A |
+ 77 |
+ M |
+
+
+ | 280 |
+ GSM388313 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388313M85A |
+ 85 |
+ M |
+
+
+ | 281 |
+ GSM388314 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388314F81A |
+ 81 |
+ F |
+
+
+ | 282 |
+ GSM388315 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388315F86A |
+ 86 |
+ F |
+
+
+ | 283 |
+ GSM388316 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388316M89A |
+ 89 |
+ M |
+
+
+ | 284 |
+ GSM388317 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388317F73A |
+ 73 |
+ F |
+
+
+ | 285 |
+ GSM388318 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388318F96A |
+ 96 |
+ F |
+
+
+ | 286 |
+ GSM388319 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388319M73A |
+ 73 |
+ M |
+
+
+ | 287 |
+ GSM388320 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388320M81A |
+ 81 |
+ M |
+
+
+ | 288 |
+ GSM388321 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388321F84A |
+ 84 |
+ F |
+
+
+ | 289 |
+ GSM388322 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388322F93A |
+ 93 |
+ F |
+
+
+ | 290 |
+ GSM388323 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388323F82A |
+ 82 |
+ F |
+
+
+ | 291 |
+ GSM388324 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388324M76A |
+ 76 |
+ M |
+
+
+ | 292 |
+ GSM388325 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388325M77A |
+ 77 |
+ M |
+
+
+ | 293 |
+ GSM388326 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388326F86A |
+ 86 |
+ F |
+
+
+ | 294 |
+ GSM388327 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388327F85A |
+ 85 |
+ F |
+
+
+ | 295 |
+ GSM388328 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388328M83A |
+ 83 |
+ M |
+
+
+ | 296 |
+ GSM388329 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388329M76A |
+ 76 |
+ M |
+
+
+ | 297 |
+ GSM388330 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388330M81A |
+ 81 |
+ M |
+
+
+ | 298 |
+ GSM388331 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388331M79A |
+ 79 |
+ M |
+
+
+ | 299 |
+ GSM388332 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388332M81A |
+ 81 |
+ M |
+
+
+ | 300 |
+ GSM388333 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388333F78A |
+ 78 |
+ F |
+
+
+ | 301 |
+ GSM388334 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388334M80A |
+ 80 |
+ M |
+
+
+ | 302 |
+ GSM388335 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388335M84A |
+ 84 |
+ M |
+
+
+ | 303 |
+ GSM388336 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388336F85A |
+ 85 |
+ F |
+
+
+ | 304 |
+ GSM388337 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388337M75A |
+ 75 |
+ M |
+
+
+ | 305 |
+ GSM388338 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388338F80A |
+ 80 |
+ F |
+
+
+ | 306 |
+ GSM388339 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388339F97A |
+ 97 |
+ F |
+
+
+ | 307 |
+ GSM388340 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388340F82A |
+ 82 |
+ F |
+
+
+ | 308 |
+ GSM388341 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388341M82A |
+ 82 |
+ M |
+
+
+ | 309 |
+ GSM388342 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388342M77A |
+ 77 |
+ M |
+
+
+ | 310 |
+ GSM388343 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388343M81A |
+ 81 |
+ M |
+
+
+ | 311 |
+ GSM388345 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388345F96A |
+ 96 |
+ F |
+
+
+ | 312 |
+ GSM388346 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388346F90A |
+ 90 |
+ F |
+
+
+ | 313 |
+ GSM388347 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388347M86A |
+ 86 |
+ M |
+
+
+ | 314 |
+ GSM388348 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388348M88A |
+ 88 |
+ M |
+
+
+ | 315 |
+ GSM388349 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388349F90A |
+ 90 |
+ F |
+
+
+ | 316 |
+ GSM388350 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388350F90A |
+ 90 |
+ F |
+
+
+ | 317 |
+ GSM388351 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388351F84A |
+ 84 |
+ F |
+
+
+ | 318 |
+ GSM388352 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388352M84A |
+ 84 |
+ M |
+
+
+ | 319 |
+ GSM388353 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388353F91A |
+ 91 |
+ F |
+
+
+ | 320 |
+ GSM388354 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388354F81A |
+ 81 |
+ F |
+
+
+ | 321 |
+ GSM388355 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388355F84A |
+ 84 |
+ F |
+
+
+ | 322 |
+ GSM388356 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388356M80A |
+ 80 |
+ M |
+
+
+ | 323 |
+ GSM388357 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388357M81A |
+ 81 |
+ M |
+
+
+ | 324 |
+ GSM388358 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388358F87A |
+ 87 |
+ F |
+
+
+ | 325 |
+ GSM388359 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388359M85A |
+ 85 |
+ M |
+
+
+ | 326 |
+ GSM388360 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388360F90A |
+ 90 |
+ F |
+
+
+ | 327 |
+ GSM388361 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388361M79A |
+ 79 |
+ M |
+
+
+ | 328 |
+ GSM388362 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388362F87A |
+ 87 |
+ F |
+
+
+ | 329 |
+ GSM388363 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388363M75A |
+ 75 |
+ M |
+
+
+ | 330 |
+ GSM388364 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388364F92A |
+ 92 |
+ F |
+
+
+ | 331 |
+ GSM388365 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388365F84A |
+ 84 |
+ F |
+
+
+ | 332 |
+ GSM388366 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388366M75A |
+ 75 |
+ M |
+
+
+ | 333 |
+ GSM388367 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388367F76A |
+ 76 |
+ F |
+
+
+ | 334 |
+ GSM388368 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388368F86A |
+ 86 |
+ F |
+
+
+ | 335 |
+ GSM388369 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388369M82A |
+ 82 |
+ M |
+
+
+ | 336 |
+ GSM388370 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388370M76A |
+ 76 |
+ M |
+
+
+ | 337 |
+ GSM388371 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388371F81A |
+ 81 |
+ F |
+
+
+ | 338 |
+ GSM388372 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388372F80A |
+ 80 |
+ F |
+
+
+ | 339 |
+ GSM388373 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388373M83A |
+ 83 |
+ M |
+
+
+ | 340 |
+ GSM388374 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388374F83A |
+ 83 |
+ F |
+
+
+ | 341 |
+ GSM388375 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388375F84A |
+ 84 |
+ F |
+
+
+ | 342 |
+ GSM388376 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388376M93A |
+ 93 |
+ M |
+
+
+ | 343 |
+ GSM388377 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388377F92A |
+ 92 |
+ F |
+
+
+ | 344 |
+ GSM388378 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388378M78A |
+ 78 |
+ M |
+
+
+ | 345 |
+ GSM388379 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388379M90A |
+ 90 |
+ M |
+
+
+ | 346 |
+ GSM388380 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388380M83A |
+ 83 |
+ M |
+
+
+ | 347 |
+ GSM388381 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388381M79A |
+ 79 |
+ M |
+
+
+ | 348 |
+ GSM388382 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388382M84A |
+ 84 |
+ M |
+
+
+ | 349 |
+ GSM388383 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388383F90A |
+ 90 |
+ F |
+
+
+ | 350 |
+ GSM388384 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388384F88A |
+ 88 |
+ F |
+
+
+ | 351 |
+ GSM388385 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388385M77A |
+ 77 |
+ M |
+
+
+ | 352 |
+ GSM388386 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388386F80A |
+ 80 |
+ F |
+
+
+ | 353 |
+ GSM388387 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388387M87A |
+ 87 |
+ M |
+
+
+ | 354 |
+ GSM388388 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388388M86A |
+ 86 |
+ M |
+
+
+ | 355 |
+ GSM388389 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388389M74A |
+ 74 |
+ M |
+
+
+ | 356 |
+ GSM388390 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388390F86A |
+ 86 |
+ F |
+
+
+ | 357 |
+ GSM388391 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388391F81A |
+ 81 |
+ F |
+
+
+ | 358 |
+ GSM388392 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388392F73A |
+ 73 |
+ F |
+
+
+ | 359 |
+ GSM388393 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388393M83A |
+ 83 |
+ M |
+
+
+ | 360 |
+ GSM388394 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388394M86A |
+ 86 |
+ M |
+
+
+ | 361 |
+ GSM388395 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388395F86A |
+ 86 |
+ F |
+
+
+ | 362 |
+ GSM388396 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388396M78A |
+ 78 |
+ M |
+
+
+ | 363 |
+ GSM388397 |
+ Cortical Tissue |
+ Alzheimer's |
+ C388397M83A |
+ 83 |
+ M |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Gse15222_f_ri_0409/contributors.rtf b/general/datasets/Gse15222_f_ri_0409/contributors.rtf
new file mode 100644
index 0000000..72c2296
--- /dev/null
+++ b/general/datasets/Gse15222_f_ri_0409/contributors.rtf
@@ -0,0 +1 @@
+Webster J, Gibbs R, Myers A
diff --git a/general/datasets/Gse15222_f_ri_0409/experiment-design.rtf b/general/datasets/Gse15222_f_ri_0409/experiment-design.rtf
new file mode 100644
index 0000000..07d1b52
--- /dev/null
+++ b/general/datasets/Gse15222_f_ri_0409/experiment-design.rtf
@@ -0,0 +1,5 @@
+Expression profiling by array
+
+We recently surveyed the relationship between the human brain transcriptome and genome in a series of neuropathologically normal postmortem samples. We now have analyzed additional samples with a confirmed pathologic diagnosis of late onset Alzheimer's disease (LOAD, final n=187 controls, 176 cases). Nine percent of the cortical transcripts we analyzed had expression profiles correlated with their genotypes in the combined cohort and approximately 5% of transcripts had SNP-transcript relationships that could distinguish LOAD samples. Two of these transcripts have been previously implicated in LOAD candidate gene SNP-expression screens. This study shows how the relationship between common inherited genetic variants and brain transcript expression can be used in the study of human brain disorders. We suggest that studying the transcriptome as a quantitative endo-phenotype has greater power to find risk SNPs influencing expression than the use of discrete diagnostic categories such as presence or absence of disease. see DOI:10.1016/j.ajhg.2009.03.011 for further details and complete author list.
+
+Expression quantitative trait loci study using human brain from 363 cortical samples. Affymetrix 500K chip for genotyping, Illumina Sentrix Human-ref 8 bead array chip for expression. Genotyping data will be available at dbGAP.
diff --git a/general/datasets/Gse15222_f_ri_0409/experiment-type.rtf b/general/datasets/Gse15222_f_ri_0409/experiment-type.rtf
new file mode 100644
index 0000000..0546e04
--- /dev/null
+++ b/general/datasets/Gse15222_f_ri_0409/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array
\ No newline at end of file
diff --git a/general/datasets/Gse15222_f_ri_0409/notes.rtf b/general/datasets/Gse15222_f_ri_0409/notes.rtf
new file mode 100644
index 0000000..e7bd85c
--- /dev/null
+++ b/general/datasets/Gse15222_f_ri_0409/notes.rtf
@@ -0,0 +1,6 @@
+Access to the original data from Dr. Myers' laboratory
+or GEO GSE15222
+PMI = Post Mortem Interval
+Cannot find this record in the GEO website: WGACON-120
+
+This data is based on May 2004 (NCBI35/hg17).
diff --git a/general/datasets/Gse15222_f_ri_0409/platform.rtf b/general/datasets/Gse15222_f_ri_0409/platform.rtf
new file mode 100644
index 0000000..5bcda8b
--- /dev/null
+++ b/general/datasets/Gse15222_f_ri_0409/platform.rtf
@@ -0,0 +1,5 @@
+Illumina Human 50 mer probes. Total of 24357 probes according to Myers et al. A total of 24354 probes included in this GeneNetwork file.
+
+From the Methods section of the paper:
+
+Genotyping and Expression Proï¬ling DNA was hybridized to the Affymetrix GeneChip Human Mapping 500K Array Set (502,627 SNPs) as previously described.11,12 Genotypes were extracted with the use of both SNiPer-HD13 and BRLMM (Affymetrix, Santa Clara, CA) algorithms. Genotypes that exhibited less than 98% concordance between calls were excluded. SNPs with call rates less than 90% were excluded from the analysis. HardyWeinberg equilibrium (HWE) was assessed with exact tests and the PLINK analysis toolset.14 SNPs with HWE exact-test p values less than 0.05, as well as SNPs with minor-allele frequencies less than 1%, were excluded. Allele calls had a mean of 97% and a range of 90%–99%. cRNA was hybridized to Illumina Human Refseq-8 Expression BeadChip (24,357 transcripts) via standard protocols. Expression proï¬les were extracted and rank invariant normalized15–17 with the use of the BeadStudio software available from Illumina, with the Illumina custom error model used. Rankinvariant-normalized expression data were log10 transformed, and missing data were encoded as missing, rather than as a zero level of expression.
diff --git a/general/datasets/Gse15222_f_ri_0409/summary.rtf b/general/datasets/Gse15222_f_ri_0409/summary.rtf
new file mode 100644
index 0000000..e99fa9e
--- /dev/null
+++ b/general/datasets/Gse15222_f_ri_0409/summary.rtf
@@ -0,0 +1,9 @@
+Myers and colleagues generated massive neocortical transcriptome data sets for a set of unrelated elderly neurologically and neuropathologically normal humans and from confirmed late onset Alzheimer's disease patients (LOAD, n = 187 normal and 176 LOAD cases, see DOI:10.1016/j.ajhg.2009.03.011 for detail). They used an Illumina Sentrix Bead array (HumanRef-8) that measures expression of approximately 19,730 curated RefSeq sequences (Human Build 34).
+
+Case identifiers: All case identifiers (IDs) in GeneNetwork begin with a capital C followed by a six digit GEO identifier, followed by the sex and age in years. Non-Alzheimer cases are labeled with the suffix letter N: C225652M85N. Alzheimer cases are labeled with the suffix letter A: C388217F97A.
+
+Data were initially downloaded from the NCBI GEO archive under the experiment ID GSE15222. All data were generated using the Illumina HumanRef-8 expression BeadChip (GPL2700) v2 Rev0. This data set in GeneNetwork includes data for 24,354 probes. We have realigned the 50-mer sequences by BLAT to the latest version of the human genome (Feb 2009, hg19) and reannotated the array (August 2009). The annotation in GN will differ from that provided in GEO for this platform. We were unable to obtain 50-mer sequences for several thousand probes (e.g., HTT), and these probes have therefore not been realigned to the human genome.
+
+The GEO data set was processed by Myers and colleagues using Illumina's Rank Invariant transform. We performed a series of QC and renormalization steps to the data to allow more facile comparison to other data sets in GeneNetwork. In brief, data is log2 transformed. We recentered each array to a mean expression of 8 units and a standard deviation of 2 units (2z + 8 transform). The values are therefore modified z scores and each unit represents roughly a two-fold difference in expression. Average expression across all 363 cases range from a low of 6 units (e.g., SYT15) to a high of 19 units for ARSK. APOE has an average expression of 15 units and APP has an average expression of 11.5 units.. The distribution is far from normal with a great excess of measurements of genes with low to moderate expression clustered between 6.5 and 8.5 units.
+
+A small number of arrays (n = 6, GSM226040, GSM226041, GSM226042, GSM226044, GSM226045, GSM226046) had a different distribution from the great majority of other arrays. This was probably due to a batch processing effect. Members of this minority group belonged to both normal and LOAD cases. This putative batch effect has been eliminated in the GeneNetwork rendition of the Myers data. To eliminate the putative batch effect, we simply computed a mean offset for each probe in the "minority set" relative to the remaining "majority set" and added or subtracted this offset to force the mean of each probe in the minority set to conform to mean of the same probe in the majority set.
diff --git a/general/datasets/Gse15745_gpl6104_cer0510/citation.rtf b/general/datasets/Gse15745_gpl6104_cer0510/citation.rtf
new file mode 100644
index 0000000..fac14d3
--- /dev/null
+++ b/general/datasets/Gse15745_gpl6104_cer0510/citation.rtf
@@ -0,0 +1 @@
+Please review and cite: Gibbs JR, Hernandez DG, Dillman A, Ryten M, Trabzuni D, Traynor BJ, Nalls MA, Arepalli S, Ramasamy A, van der Brug MP, Troncoso J, Johnson R, O'Brien R, Zielke HR, Zonderman A, Ferrucci L, Longo DL, Smith C, Walker R, Weale M, Hardy JA, Cookson MR, Singleton AB. PMID: 22433082.
diff --git a/general/datasets/Gse15745_gpl6104_cer0510/experiment-design.rtf b/general/datasets/Gse15745_gpl6104_cer0510/experiment-design.rtf
new file mode 100644
index 0000000..e93df25
--- /dev/null
+++ b/general/datasets/Gse15745_gpl6104_cer0510/experiment-design.rtf
@@ -0,0 +1 @@
+North American Brain Expression Consortium and UK Human Brain Expression Database: Gene Expression. Genome-wide association studies have nominated many genetic variants for common human traits, including diseases, but in many cases the underlying biological reason for a trait association is unknown. Subsets of genetic polymorphisms show a statistical association with transcript expression levels, and have therefore been nominated as expression quantitative trait loci (eQTL). However, many tissue and cell types have specific gene expression patterns and so it is not clear how frequently eQTLs found in one tissue type will be replicated in others. In the present study we used two appropriately powered sample series to examine the genetic control of gene expression in blood and brain. We find that while many eQTLs associated with human traits are shared between these two tissues, there are also examples where blood and brain differ, either by restricted gene expression patterns in one tissue or because of differences in how genetic variants are associated with transcript levels. These observations suggest that design of eQTL mapping experiments should consider tissue of interest for the disease or other traits studied. Published by Elsevier Inc.
diff --git a/general/datasets/Gse15745_gpl6104_cer0510/summary.rtf b/general/datasets/Gse15745_gpl6104_cer0510/summary.rtf
new file mode 100644
index 0000000..4bc5546
--- /dev/null
+++ b/general/datasets/Gse15745_gpl6104_cer0510/summary.rtf
@@ -0,0 +1 @@
+Summary from GEO Series GSE36192 and GSE: GSE36194 "A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on mRNA expression distinct human brain regions. We show that brain tissues may be readily distinguished based on expression profile. We find an abundance of genetic cis regulation mRNA expression. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation."
diff --git a/general/datasets/Gse15745_gpl6104_pfc0510/citation.rtf b/general/datasets/Gse15745_gpl6104_pfc0510/citation.rtf
new file mode 100644
index 0000000..fac14d3
--- /dev/null
+++ b/general/datasets/Gse15745_gpl6104_pfc0510/citation.rtf
@@ -0,0 +1 @@
+Please review and cite: Gibbs JR, Hernandez DG, Dillman A, Ryten M, Trabzuni D, Traynor BJ, Nalls MA, Arepalli S, Ramasamy A, van der Brug MP, Troncoso J, Johnson R, O'Brien R, Zielke HR, Zonderman A, Ferrucci L, Longo DL, Smith C, Walker R, Weale M, Hardy JA, Cookson MR, Singleton AB. PMID: 22433082.
diff --git a/general/datasets/Gse15745_gpl6104_pfc0510/experiment-design.rtf b/general/datasets/Gse15745_gpl6104_pfc0510/experiment-design.rtf
new file mode 100644
index 0000000..e93df25
--- /dev/null
+++ b/general/datasets/Gse15745_gpl6104_pfc0510/experiment-design.rtf
@@ -0,0 +1 @@
+North American Brain Expression Consortium and UK Human Brain Expression Database: Gene Expression. Genome-wide association studies have nominated many genetic variants for common human traits, including diseases, but in many cases the underlying biological reason for a trait association is unknown. Subsets of genetic polymorphisms show a statistical association with transcript expression levels, and have therefore been nominated as expression quantitative trait loci (eQTL). However, many tissue and cell types have specific gene expression patterns and so it is not clear how frequently eQTLs found in one tissue type will be replicated in others. In the present study we used two appropriately powered sample series to examine the genetic control of gene expression in blood and brain. We find that while many eQTLs associated with human traits are shared between these two tissues, there are also examples where blood and brain differ, either by restricted gene expression patterns in one tissue or because of differences in how genetic variants are associated with transcript levels. These observations suggest that design of eQTL mapping experiments should consider tissue of interest for the disease or other traits studied. Published by Elsevier Inc.
diff --git a/general/datasets/Gse15745_gpl6104_pfc0510/summary.rtf b/general/datasets/Gse15745_gpl6104_pfc0510/summary.rtf
new file mode 100644
index 0000000..4bc5546
--- /dev/null
+++ b/general/datasets/Gse15745_gpl6104_pfc0510/summary.rtf
@@ -0,0 +1 @@
+Summary from GEO Series GSE36192 and GSE: GSE36194 "A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on mRNA expression distinct human brain regions. We show that brain tissues may be readily distinguished based on expression profile. We find an abundance of genetic cis regulation mRNA expression. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation."
diff --git a/general/datasets/Gse15745_gpl6104_po0510/citation.rtf b/general/datasets/Gse15745_gpl6104_po0510/citation.rtf
new file mode 100644
index 0000000..fac14d3
--- /dev/null
+++ b/general/datasets/Gse15745_gpl6104_po0510/citation.rtf
@@ -0,0 +1 @@
+Please review and cite: Gibbs JR, Hernandez DG, Dillman A, Ryten M, Trabzuni D, Traynor BJ, Nalls MA, Arepalli S, Ramasamy A, van der Brug MP, Troncoso J, Johnson R, O'Brien R, Zielke HR, Zonderman A, Ferrucci L, Longo DL, Smith C, Walker R, Weale M, Hardy JA, Cookson MR, Singleton AB. PMID: 22433082.
diff --git a/general/datasets/Gse15745_gpl6104_po0510/experiment-design.rtf b/general/datasets/Gse15745_gpl6104_po0510/experiment-design.rtf
new file mode 100644
index 0000000..e93df25
--- /dev/null
+++ b/general/datasets/Gse15745_gpl6104_po0510/experiment-design.rtf
@@ -0,0 +1 @@
+North American Brain Expression Consortium and UK Human Brain Expression Database: Gene Expression. Genome-wide association studies have nominated many genetic variants for common human traits, including diseases, but in many cases the underlying biological reason for a trait association is unknown. Subsets of genetic polymorphisms show a statistical association with transcript expression levels, and have therefore been nominated as expression quantitative trait loci (eQTL). However, many tissue and cell types have specific gene expression patterns and so it is not clear how frequently eQTLs found in one tissue type will be replicated in others. In the present study we used two appropriately powered sample series to examine the genetic control of gene expression in blood and brain. We find that while many eQTLs associated with human traits are shared between these two tissues, there are also examples where blood and brain differ, either by restricted gene expression patterns in one tissue or because of differences in how genetic variants are associated with transcript levels. These observations suggest that design of eQTL mapping experiments should consider tissue of interest for the disease or other traits studied. Published by Elsevier Inc.
diff --git a/general/datasets/Gse15745_gpl6104_po0510/summary.rtf b/general/datasets/Gse15745_gpl6104_po0510/summary.rtf
new file mode 100644
index 0000000..4bc5546
--- /dev/null
+++ b/general/datasets/Gse15745_gpl6104_po0510/summary.rtf
@@ -0,0 +1 @@
+Summary from GEO Series GSE36192 and GSE: GSE36194 "A fundamental challenge in the post-genome era is to understand and annotate the consequences of genetic variation, particularly within the context of human tissues. We describe a set of integrated experiments designed to investigate the effects of common genetic variability on mRNA expression distinct human brain regions. We show that brain tissues may be readily distinguished based on expression profile. We find an abundance of genetic cis regulation mRNA expression. We observe that the largest magnitude effects occur across distinct brain regions. We believe these data, which we have made publicly available, will be useful in understanding the biological effects of genetic variation."
diff --git a/general/datasets/Gse16780_ucla_ml0911/acknowledgment.rtf b/general/datasets/Gse16780_ucla_ml0911/acknowledgment.rtf
new file mode 100644
index 0000000..83eca40
--- /dev/null
+++ b/general/datasets/Gse16780_ucla_ml0911/acknowledgment.rtf
@@ -0,0 +1 @@
+Bennett BJ, Ghazalpour A
diff --git a/general/datasets/Gse16780_ucla_ml0911/cases.rtf b/general/datasets/Gse16780_ucla_ml0911/cases.rtf
new file mode 100644
index 0000000..6eefb7b
--- /dev/null
+++ b/general/datasets/Gse16780_ucla_ml0911/cases.rtf
@@ -0,0 +1 @@
+For complete information please refer to Bennett BJ, Farber CR, Orozco L, Kang HM, Ghazalpour A, Siemers N, Neubauer M, Neuhaus I, Yordanova R, Guan B, Truong A, Yang WP, He A, Kayne P, Gargalovic P, Kirchgessner T, Pan C, Castellani LW, Kostem E, Furlotte N, Drake TA, Eskin E, Lusis AJ (2010) A high-resolution association mapping panel for the dissection of complex traits in mice. Genome Research 20:281-90 PMID: 20054062
diff --git a/general/datasets/Gse16780_ucla_ml0911/citation.rtf b/general/datasets/Gse16780_ucla_ml0911/citation.rtf
new file mode 100644
index 0000000..20e19dd
--- /dev/null
+++ b/general/datasets/Gse16780_ucla_ml0911/citation.rtf
@@ -0,0 +1 @@
+Bennett BJ, Farber CR, Orozco L, Kang HM et al. A high-resolution association mapping panel for the dissection of complex traits in mice. Genome Res 2010 Feb;20(2):281-90. PMID: 20054062
diff --git a/general/datasets/Gse16780_ucla_ml0911/contributors.rtf b/general/datasets/Gse16780_ucla_ml0911/contributors.rtf
new file mode 100644
index 0000000..6e4d970
--- /dev/null
+++ b/general/datasets/Gse16780_ucla_ml0911/contributors.rtf
@@ -0,0 +1 @@
+Bennett BJ, Ghazalpour A
diff --git a/general/datasets/Gse16780_ucla_ml0911/experiment-design.rtf b/general/datasets/Gse16780_ucla_ml0911/experiment-design.rtf
new file mode 100644
index 0000000..40c5b94
--- /dev/null
+++ b/general/datasets/Gse16780_ucla_ml0911/experiment-design.rtf
@@ -0,0 +1,3 @@
+Expression profiling by array.
+
+Expression Profiles from 99 strains of inbred and recombinant inbred mice. Most assayed in triplicate. Two of 288 chips were excluded from the final analysis due to low QC scores.
diff --git a/general/datasets/Gse16780_ucla_ml0911/experiment-type.rtf b/general/datasets/Gse16780_ucla_ml0911/experiment-type.rtf
new file mode 100644
index 0000000..b8429a3
--- /dev/null
+++ b/general/datasets/Gse16780_ucla_ml0911/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array.
\ No newline at end of file
diff --git a/general/datasets/Gse16780_ucla_ml0911/notes.rtf b/general/datasets/Gse16780_ucla_ml0911/notes.rtf
new file mode 100644
index 0000000..51b03e3
--- /dev/null
+++ b/general/datasets/Gse16780_ucla_ml0911/notes.rtf
@@ -0,0 +1 @@
+Raw data provided as supplementary file at GEO Series GSE16780
diff --git a/general/datasets/Gse16780_ucla_ml0911/platform.rtf b/general/datasets/Gse16780_ucla_ml0911/platform.rtf
new file mode 100644
index 0000000..17c2cc4
--- /dev/null
+++ b/general/datasets/Gse16780_ucla_ml0911/platform.rtf
@@ -0,0 +1,5 @@
+Platform GPL8759 [HT_MG-430A] Affymetrix HT Mouse Genome 430A Array
+
+The probe sets were selected from sequences derived from GenBank®, dbEST and RefSeq. The sequence clusters were created from the UniGene database (Build 107, June 2002) and then refined by analysis and comparison with the publicly available draft assembly of the mouse genome from the Whitehead Institute Center for Genome Research (MSCG, April 2002).
+
+Oligonucleotide probes complementary to each corresponding sequence are synthesized in situ on the array. Eleven pairs of oligonucleotide probes, including a perfect match and mismatch probe, are used to measure the level of transcription of each sequence represented on the GeneChip® HT Mouse Genome 430 Array Plate Set.
diff --git a/general/datasets/Gse16780_ucla_ml0911/processing.rtf b/general/datasets/Gse16780_ucla_ml0911/processing.rtf
new file mode 100644
index 0000000..7617e4f
--- /dev/null
+++ b/general/datasets/Gse16780_ucla_ml0911/processing.rtf
@@ -0,0 +1 @@
+For complete information please refer to A high-resolution association mapping panel for the dissection of complex traits in mice. Genome Res 2010 Feb;20(2):281-90. PMID: 20054062
diff --git a/general/datasets/Gse16780_ucla_ml0911/summary.rtf b/general/datasets/Gse16780_ucla_ml0911/summary.rtf
new file mode 100644
index 0000000..2d0ff54
--- /dev/null
+++ b/general/datasets/Gse16780_ucla_ml0911/summary.rtf
@@ -0,0 +1 @@
+Novel, systems-based approach to mouse genetics.
diff --git a/general/datasets/Gse16780_ucla_ml0911/tissue.rtf b/general/datasets/Gse16780_ucla_ml0911/tissue.rtf
new file mode 100644
index 0000000..4628b5b
--- /dev/null
+++ b/general/datasets/Gse16780_ucla_ml0911/tissue.rtf
@@ -0,0 +1 @@
+Hybrid Mouse diversity Panel Liver Expression Profile
diff --git a/general/datasets/Gse16780ab_ucla_ml0911/summary.rtf b/general/datasets/Gse16780ab_ucla_ml0911/summary.rtf
new file mode 100644
index 0000000..6ecd595
--- /dev/null
+++ b/general/datasets/Gse16780ab_ucla_ml0911/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 150, Name: GSE16780 UCLA Mouse AXB/BXA Liver Affy HT M430A (Sep11)
\ No newline at end of file
diff --git a/general/datasets/Gse16780bxh_ucla_ml0911/summary.rtf b/general/datasets/Gse16780bxh_ucla_ml0911/summary.rtf
new file mode 100644
index 0000000..9abf757
--- /dev/null
+++ b/general/datasets/Gse16780bxh_ucla_ml0911/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 151, Name: GSE16780 UCLA Mouse BXH Liver Affy HT M430A (Sep11)
\ No newline at end of file
diff --git a/general/datasets/Gse16780mdp_ucla_ml0911/summary.rtf b/general/datasets/Gse16780mdp_ucla_ml0911/summary.rtf
new file mode 100644
index 0000000..24e1d40
--- /dev/null
+++ b/general/datasets/Gse16780mdp_ucla_ml0911/summary.rtf
@@ -0,0 +1,11 @@
+The following is an excerpt from The Hybrid Mouse Diversity Panel: a resource for systems genetics analyses of metabolic and cardiovascular traits
+
+
+
+The Hybrid Mouse Diversity Panel (HMDP) is a collection of approximately 100 well-characterized inbred strains of mice that can be used to analyze the genetic and environmental factors underlying complex traits. While not nearly as powerful for mapping genetic loci contributing to the traits as human genome-wide association studies, it has some important advantages. First, environmental factors can be controlled. Second, relevant tissues are accessible for global molecular phenotyping. Finally, because inbred strains are renewable, results from separate studies can be integrated. Thus far, the HMDP has been studied for traits relevant to obesity, diabetes, atherosclerosis, osteoporosis, heart failure, immune regulation, fatty liver disease, and host-gut microbiota interactions. High-throughput technologies have been used to examine the genomes, epigenomes, transcriptomes, proteomes, metabolomes, and microbiomes of the mice under various environmental conditions. All of the published data are available and can be readily used to formulate hypotheses about genes, pathways and interactions.
+
+The HMDP was developed as a systems genetics resource similar to recombinant inbred (RI) strain sets (2, 3) or chromosome substitution strains (4), but with the added advantage of high-resolution association mapping (1). It consists of a set of 30 classic inbred strains chosen for diversity plus 70 or more RI strains derived primarily from strains C57BL/6J and DBA/2J (the BxD RI set) and A/J and C57BL/6J (the AxB and BxA RI sets). The classic strains provide mapping resolution, while the RI strains provide power. All of the chosen strains are commercially available from the Jackson Laboratory (https://www.jax.org) and all have been either sequenced (www.sanger.ac.uk/science/data/mouse-genomes-project) or densely genotyped (5).
diff --git a/general/datasets/Gse23546hlt0613/citation.rtf b/general/datasets/Gse23546hlt0613/citation.rtf
new file mode 100644
index 0000000..2aafa46
--- /dev/null
+++ b/general/datasets/Gse23546hlt0613/citation.rtf
@@ -0,0 +1 @@
+Bossé Y, Postma DS, Sin DD, Lamontagne M et al. Molecular signature of smoking in human lung tissues. Cancer Res 2012 Aug 1;72(15):3753-63. PMID: 22659451
diff --git a/general/datasets/Gse23546hlt0613/contributors.rtf b/general/datasets/Gse23546hlt0613/contributors.rtf
new file mode 100644
index 0000000..a22a4a5
--- /dev/null
+++ b/general/datasets/Gse23546hlt0613/contributors.rtf
@@ -0,0 +1 @@
+Bossé Y, Laviolette M
diff --git a/general/datasets/Gse23546hlt0613/summary.rtf b/general/datasets/Gse23546hlt0613/summary.rtf
new file mode 100644
index 0000000..9cb9538
--- /dev/null
+++ b/general/datasets/Gse23546hlt0613/summary.rtf
@@ -0,0 +1,15 @@
+This SuperSeries is composed of the following SubSeries:
+
+
+
+
+ | GSE23352 Whole-genome gene expression profiles of non-tumorous human lung tissues: Laval set |
+
+
+ | GSE23529 Whole-genome gene expression profiles of non-tumorous human lung tissues: UBC set |
+
+
+ | GSE23545 Whole-genome gene expression profiles of non-tumorous human lung tissues: GRNG set |
+
+
+
diff --git a/general/datasets/Gse5281_f_rma0709/acknowledgment.rtf b/general/datasets/Gse5281_f_rma0709/acknowledgment.rtf
new file mode 100644
index 0000000..8ce4f5c
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma0709/acknowledgment.rtf
@@ -0,0 +1 @@
+Please cite: Liang WS, Reiman EM, Valla J, Dunckley T, Beach TG, Grover A, Niedzielko TL, Schneider LE, Mastroeni D, Caselli R, Kukull W, Morris JC, Hulette CM, Schmechel D, Rogers J, Stephan DA (2008) Alzheimer's disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons. Proc Natl Acad Sci USA 105:4441-4446.
diff --git a/general/datasets/Gse5281_f_rma0709/citation.rtf b/general/datasets/Gse5281_f_rma0709/citation.rtf
new file mode 100644
index 0000000..6c255a4
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma0709/citation.rtf
@@ -0,0 +1,2 @@
+Liang WS, Dunckley T, Beach TG, Grover A et al. Gene expression profiles in anatomically and functionally distinct regions of the normal aged human brain. Physiol Genomics 2007 Feb 12;28(3):311-22. PMID: 17077275
+Liang WS, Reiman EM, Valla J, Dunckley T et al. Alzheimer's disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons. Proc Natl Acad Sci U S A 2008 Mar 18;105(11):4441-6. PMID: 18332434
diff --git a/general/datasets/Gse5281_f_rma0709/contributors.rtf b/general/datasets/Gse5281_f_rma0709/contributors.rtf
new file mode 100644
index 0000000..754b3a7
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma0709/contributors.rtf
@@ -0,0 +1 @@
+Stephan DA, Liang WS
diff --git a/general/datasets/Gse5281_f_rma0709/experiment-design.rtf b/general/datasets/Gse5281_f_rma0709/experiment-design.rtf
new file mode 100644
index 0000000..bc54b5c
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma0709/experiment-design.rtf
@@ -0,0 +1,13 @@
+Human brain expression data in patients with Alzheimer's disease and age-matched elderly control subjects. This cortical expression data set is taken from GEO GSE5281 (Liang et al. 2006, Liang et al. 2008). Samples were laser-captured from cortical regions of 16 normal elderly humans (10 males and 4 females) and from 33 AD cases (15 males and 18 females). Mean age of cases and controls was 80 years. All samples were run on the Affymetrix U133 Plus 2.0 array. We renormalized the RMA data to an average expression of 8 units on a log2 scale. Two versions of the data have been entered in GeneNetwork: one consisting of 157 of 161 arrays (full set minus 4 arrays we consider of poor quality); the second consisting of what we regard as the best 102 arrays (those with mean correlations of better than 0.88 with all other arrays). Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex area 17 layer III. GeneNetwork does not yet allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example, expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
+
+NOTE: We detected a minimum of 7.6% case assignment error rate (12 of 158 arrays) in this data set. Twelve cases are assigned to the wrong sex (see XIST probe set 224588_at, the figure below, and table 1). This raises the possibility that some cases are also misassigned by cortical brain region and disease status.
+
+
+
+
+
+Legend: Expression of the sex-specific gene XIST reveals about 10 sex assignment errors in this data set.
+
+Samples were laser-captured from cortical layer 3 (except the hippocampus) and run on the Affymetrix U133 Plus 2.0 array. We renormalized the data to an average expression of 8 units on a log2 scale. Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex layer III. A total of 16 normal subjects were used (10 M and 4 female). The AD samples. GeneNetwork does not allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
+
+Information about the genes that are preferentially expressed during the course of Alzheimer's disease (AD) could improve our understanding of the molecular mechanisms involved in the pathogenesis of this common cause of cognitive impairment in older persons, provide new opportunities in the diagnosis, early detection, and tracking of this disorder, and provide novel targets for the discovery of interventions to treat and prevent this disorder. Information about the genes that are preferentially expressed in relationship to normal neurological aging could provide new information about the molecular mechanisms that are involved in normal age-related cognitive decline and a host of age-related neurological disorders, and they could provide novel targets for the discovery of interventions to mitigate some of these deleterious effects.
diff --git a/general/datasets/Gse5281_f_rma0709/experiment-type.rtf b/general/datasets/Gse5281_f_rma0709/experiment-type.rtf
new file mode 100644
index 0000000..5797da1
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma0709/experiment-type.rtf
@@ -0,0 +1,9 @@
+
+Human brain expression data in patients with Alzheimer's disease and age-matched elderly control subjects. This cortical expression data set is taken from GEO GSE5281 (Liang et al. 2006, Liang et al. 2008). Samples were laser-captured from cortical regions of 16 normal elderly humans (10 males and 4 females) and from 33 AD cases (15 males and 18 females). Mean age of cases and controls was 80 years. All samples were run on the Affymetrix U133 Plus 2.0 array. We renormalized the RMA data to an average expression of 8 units on a log2 scale. Two versions of the data have been entered in GeneNetwork: one consisting of 157 of 161 arrays (full set minus 4 arrays we consider of poor quality); the second consisting of what we regard as the best 102 arrays (those with mean correlations of better than 0.88 with all other arrays). Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex area 17 layer III. GeneNetwork does not yet allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example, expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
+
+
NOTE: We detected a minimum of 7.6% case assignment error rate (12 of 158 arrays) in this data set. Twelve cases are assigned to the wrong sex (see XIST probe set 224588_at, the figure below, and table 1). This raises the possibility that some cases are also misassigned by cortical brain region and disease status.
+
+
+Legend: Expression of the sex-specific gene XIST reveals about 10 sex assignment errors in this data set.
+
+Samples were laser-captured from cortical layer 3 (except the hippocampus) and run on the Affymetrix U133 Plus 2.0 array. We renormalized the data to an average expression of 8 units on a log2 scale. Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex layer III. A total of 16 normal subjects were used (10 M and 4 female). The AD samples. GeneNetwork does not allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
\ No newline at end of file
diff --git a/general/datasets/Gse5281_f_rma0709/platform.rtf b/general/datasets/Gse5281_f_rma0709/platform.rtf
new file mode 100644
index 0000000..6c2af02
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma0709/platform.rtf
@@ -0,0 +1,3 @@
+Affymetrix submissions are typically submitted to GEO using the GEOarchive method described at http://www.ncbi.nlm.nih.gov/projects/geo/info/geo_affy.html Complete coverage of the Human Genome U133 Set plus 6,500 additional genes for analysis of over 47,000 transcripts All probe sets represented on the GeneChip Human Genome U133 Set are identically replicated on the GeneChip Human Genome U133 Plus 2.0 Array. The sequences from which these probe sets were derived were selected from GenBank®, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 133, April 20, 2001) and then refined by analysis and comparison with a number of other publicly available databases, including the Washington University EST trace repository and the University of California, Santa Cruz Golden-Path human genome database (April 2001 release).
+
+In addition, there are 9,921 new probe sets representing approximately 6,500 new genes. These gene sequences were selected from GenBank, dbEST, and RefSeq. Sequence clusters were created from the UniGene database (Build 159, January 25, 2003) and refined by analysis and comparison with a number of other publicly available databases, including the Washington University EST trace repository and the NCBI human genome assembly (Build 31).
diff --git a/general/datasets/Gse5281_f_rma0709/summary.rtf b/general/datasets/Gse5281_f_rma0709/summary.rtf
new file mode 100644
index 0000000..5db3978
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma0709/summary.rtf
@@ -0,0 +1,1484 @@
+(Taken verbatim from the GEO record)
+
+Information about the genes that are preferentially expressed during the course of Alzheimer’s disease (AD) could improve our understanding of the molecular mechanisms involved in the pathogenesis of this common cause of cognitive impairment in older persons, provide new opportunities in the diagnosis, early detection, and tracking of this disorder, and provide novel targets for the discovery of interventions to treat and prevent this disorder. Information about the genes that are preferentially expressed in relationship to normal neurological aging could provide new information about the molecular mechanisms that are involved in normal age-related cognitive decline and a host of age-related neurological disorders, and they could provide novel targets for the discovery of interventions to mitigate some of these deleterious effects.
+
+Aim 1. Collect brain samples from three Alzheimer’s Disease Centers (ADCs) for subsequent gene expression profiling. Individuals will be stratified with respect to diagnostic groups (using both clinical and neuropathological criteria), age groups, and APOE genotype. 150 individual brains will be sampled from the Arizona ADC, the Duke University ADC, and the Washington University ADC. Miniscule sample sizes (200 um of sectioned tissue) from six brain regions that are histopathologically or metabolically relevant to AD and aging will be collected, ensuring that this proposal does not deplete the national resource. Frozen and fixed samples will be sent to Phoenix, sectioned in a standardized fashion, and then returned. Aim 2. Tissue heterogeneity will be eliminated prior to expression profiling by performing laser capture microscopy on all brain regions. Aim 3. Expression profile LCM-captured cells on the Affymetrix U133 Plus 2.0 array (~55,000 transcripts), and quickly provide these data to the community at large. Aim 4. Identify pathogenic cascades related to each of the clinico-pathologic correlates using unsupervised and supervised analyses coupled with a hypothesis-driven approach. Aim 5. Validation of the expression correlates at the protein and functional levels.
+
+Scientific progress in the last few years has improved our understanding of AD and raised the hope of identifying treatments to halt the progression and prevent the onset of this disorder. For instance, researchers have begun to characterize the cascade of molecular events which lead to the major histopathological features of the disorder: neuritic plaques, which contain extra-cellular deposits of amyloid beta-peptides (Abeta); neurofibrillary tangles, which contain the hyperphosphorylated form of the intracellular, microtubule-associated protein, tau; and a loss of neurons and synapses. These molecular events provide targets for the development of promising new treatments. For example, A-beta has been postulated to trigger a cascade of events that are involved in the pathogenesis of AD. This proposal hopes to provide new information about the genes that are preferentially expressed in the development of AD histopathology, including the over-expression of APP, amyloid-induced neurotoxicity, and hyperphosphorylation of tau, as well as bring clarity to the metabolic abnormalities that seem to play a role in dementia and AD development and pathology.
+
+We will perform LCM on 6 brain regions with about 14 biological replicates per brain region. The brain regions are as follows: 1) entorhinal cortex 2) hippocampus 3) medial temporal gyrus 4) posterior cingulate 5) superior frontal gyrus and 6) primary visual cortex. We will collect layer III pyramidal cells from the white matter in each region, isolate total RNA from LCMed cell lysates, and perform double round amplification of each sample for array analysis.
+
+
+
+Bad arrays excluded: Four samples, highlighted in the table below, are bad arrays. For quality control, they should be excluded.
+
+
+
+
+
+
+
+
+ | Index |
+ GEO Series |
+ Organ Region |
+ Tissue |
+ Case ID |
+ Age |
+ Sex |
+
+
+ | 1 |
+ GSM119615 |
+ Entorhinal Cortex |
+ Normal |
+ E119615M63N |
+ 63 |
+ M |
+
+
+ | 2 |
+ GSM119616 |
+ Entorhinal Cortex |
+ Normal |
+ E119616M85N |
+ 85 |
+ M |
+
+
+ | 3 |
+ GSM119617 |
+ Entorhinal Cortex |
+ Normal |
+ E119617M80N |
+ 80 |
+ M |
+
+
+ | 4 |
+ GSM119618 |
+ Entorhinal Cortex |
+ Normal |
+ E119618M->F80N |
+ 80 |
+ M |
+
+
+ | 5 |
+ GSM119619 |
+ Entorhinal Cortex |
+ Normal |
+ E119619F->M102N |
+ 102 |
+ F |
+
+
+ | 6 |
+ GSM119620 |
+ Entorhinal Cortex |
+ Normal |
+ E119620M79N |
+ 79 |
+ M |
+
+
+ | 7 |
+ GSM119621 |
+ Entorhinal Cortex |
+ Normal |
+ E119621M76N |
+ 76 |
+ M |
+
+
+ | 8 |
+ GSM119622 |
+ Entorhinal Cortex |
+ Normal |
+ E119622M83N |
+ 83 |
+ M |
+
+
+ | 9 |
+ GSM119623 |
+ Entorhinal Cortex |
+ Normal |
+ E119623M79N |
+ 79 |
+ M |
+
+
+ | 10 |
+ GSM119624 |
+ Entorhinal Cortex |
+ Normal |
+ E119624F88N |
+ 88 |
+ F |
+
+
+ | 11 |
+ GSM119625 |
+ Entorhinal Cortex |
+ Normal |
+ E119625F82N |
+ 82 |
+ F |
+
+
+ | 12 |
+ GSM119626 |
+ Entorhinal Cortex |
+ Normal |
+ E119626M69N |
+ 69 |
+ M |
+
+
+ | 13 |
+ GSM119627 |
+ Entorhinal Cortex |
+ Normal |
+ E119627M78N |
+ 78 |
+ M |
+
+
+ | 14 |
+ GSM238763 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238763F82A |
+ 82 |
+ F |
+
+
+ | 15 |
+ GSM238790 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238790F86A |
+ 86 |
+ F |
+
+
+ | 16 |
+ GSM238791 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238791F93A |
+ 93 |
+ F |
+
+
+ | 17 |
+ GSM238792 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238792M84A |
+ 84 |
+ M |
+
+
+ | 18 |
+ GSM238793 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238793F79A |
+ 79 |
+ F |
+
+
+ | 19 |
+ GSM238794 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238794F78A |
+ 78 |
+ F |
+
+
+ | 20 |
+ GSM238795 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238795F91A |
+ 91 |
+ F |
+
+
+ | 21 |
+ GSM238796 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238796M86A |
+ 86 |
+ M |
+
+
+ | 22 |
+ GSM238797 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238797NA0A |
+ N/A |
+ N/A |
+
+
+ | 23 |
+ GSM238798 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238798M80A |
+ 80 |
+ M |
+
+
+ | 24 |
+ GSM119628 |
+ Hippocampus |
+ Normal |
+ H119628M85N |
+ 85 |
+ M |
+
+
+ | 25 |
+ GSM119629 |
+ Hippocampus |
+ Normal |
+ H119629M80N |
+ 80 |
+ M |
+
+
+ | 26 |
+ GSM119630 |
+ Hippocampus |
+ Normal |
+ H119630M80N |
+ 80 |
+ M |
+
+
+ | 27 |
+ GSM119631 |
+ Hippocampus |
+ Normal |
+ H119631F102N |
+ 102 |
+ F |
+
+
+ | 28 |
+ GSM119632 |
+ Hippocampus |
+ Normal |
+ H119632M63N |
+ 63 |
+ M |
+
+
+ | 29 |
+ GSM119633 |
+ Hippocampus |
+ Normal |
+ H119633M79N |
+ 79 |
+ M |
+
+
+ | 30 |
+ GSM119634 |
+ Hippocampus |
+ Normal |
+ H119634M76N |
+ 76 |
+ M |
+
+
+ | 31 |
+ GSM119635 |
+ Hippocampus |
+ Normal |
+ H119635M83N |
+ 83 |
+ M |
+
+
+ | 32 |
+ GSM119636 |
+ Hippocampus |
+ Normal |
+ H119636M79N |
+ 79 |
+ M |
+
+
+ | 33 |
+ GSM119637 |
+ Hippocampus |
+ Normal |
+ H119637F88N |
+ 88 |
+ F |
+
+
+ | 34 |
+ GSM119638 |
+ Hippocampus |
+ Normal |
+ H119638F73N |
+ 73 |
+ F |
+
+
+ | 35 |
+ GSM119639 |
+ Hippocampus |
+ Normal |
+ H119639M69N |
+ 69 |
+ M |
+
+
+ | 36 |
+ GSM119640 |
+ Hippocampus |
+ Normal |
+ H119640M78N |
+ 78 |
+ M |
+
+
+ | 37 |
+ GSM238799 |
+ Hippocampus |
+ Alzheimer's |
+ H238799F73A |
+ 73 |
+ F |
+
+
+ | 38 |
+ GSM238800 |
+ Hippocampus |
+ Alzheimer's |
+ H238800M81A |
+ 81 |
+ M |
+
+
+ | 39 |
+ GSM238801 |
+ Hippocampus |
+ Alzheimer's |
+ H238801M78A |
+ 78 |
+ M |
+
+
+ | 40 |
+ GSM238802 |
+ Hippocampus |
+ Alzheimer's |
+ H238802M75A |
+ 75 |
+ M |
+
+
+ | 41 |
+ GSM238803 |
+ Hippocampus |
+ Alzheimer's |
+ H238803F70A |
+ 70 |
+ F |
+
+
+ | 42 |
+ GSM238804 |
+ Hippocampus |
+ Alzheimer's |
+ H238804F85A |
+ 85 |
+ F |
+
+
+ | 43 |
+ GSM238805 |
+ Hippocampus |
+ Alzheimer's |
+ H238805F77A |
+ 77 |
+ F |
+
+
+ | 44 |
+ GSM238806 |
+ Hippocampus |
+ Alzheimer's |
+ H238806M79A |
+ 79 |
+ M |
+
+
+ | 45 |
+ GSM238807 |
+ Hippocampus |
+ Alzheimer's |
+ H238807M88A |
+ 88 |
+ M |
+
+
+ | 46 |
+ GSM238808 |
+ Hippocampus |
+ Alzheimer's |
+ H238808M72A |
+ 72 |
+ M |
+
+
+ | 47 |
+ GSM119641 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119641M85N |
+ 85 |
+ M |
+
+
+ | 48 |
+ GSM119642 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119642M80N |
+ 80 |
+ M |
+
+
+ | 49 |
+ GSM119643 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119643F102N |
+ 102 |
+ F |
+
+
+ | 50 |
+ GSM119644 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119644M63N |
+ 63 |
+ M |
+
+
+ | 51 |
+ GSM119645 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119645M79N |
+ 79 |
+ M |
+
+
+ | 52 |
+ GSM119646 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119646M83N |
+ 83 |
+ M |
+
+
+ | 53 |
+ GSM119647 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119647M79N |
+ 79 |
+ M |
+
+
+ | 54 |
+ GSM119648 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119648F88N |
+ 88 |
+ F |
+
+
+ | 55 |
+ GSM119649 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119649F82N |
+ 82 |
+ F |
+
+
+ | 56 |
+ GSM119650 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119650F73N |
+ 73 |
+ F |
+
+
+ | 57 |
+ GSM119651 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119651M69N |
+ 69 |
+ M |
+
+
+ | 58 |
+ GSM119652 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119652M->F78N |
+ 78 |
+ M |
+
+
+ | 59 |
+ GSM238809 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238809M81A |
+ 81 |
+ M |
+
+
+ | 60 |
+ GSM238810 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238810M72A |
+ 72 |
+ M |
+
+
+ | 61 |
+ GSM238811 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238811M75A |
+ 75 |
+ M |
+
+
+ | 62 |
+ GSM238812 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238812M78A |
+ 78 |
+ M |
+
+
+ | 63 |
+ GSM238813 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238813M75A |
+ 75 |
+ M |
+
+
+ | 64 |
+ GSM238815 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238815F95A |
+ 95 |
+ F |
+
+
+ | 65 |
+ GSM238816 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238816F81A |
+ 81 |
+ F |
+
+
+ | 66 |
+ GSM238817 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238817F85A |
+ 85 |
+ F |
+
+
+ | 67 |
+ GSM238818 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238818M79A |
+ 79 |
+ M |
+
+
+ | 68 |
+ GSM238819 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238819F82A |
+ 82 |
+ F |
+
+
+ | 69 |
+ GSM238820 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238820M88A |
+ 88 |
+ M |
+
+
+ | 70 |
+ GSM238821 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238821M72A |
+ 72 |
+ M |
+
+
+ | 71 |
+ GSM238822 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238822F73A |
+ 73 |
+ F |
+
+
+ | 72 |
+ GSM238823 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238823M87A |
+ 87 |
+ M |
+
+
+ | 73 |
+ GSM238824 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238824M68A |
+ 68 |
+ M |
+
+
+ | 74 |
+ GSM238825 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238825F80A |
+ 80 |
+ F |
+
+
+ | 75 |
+ GSM119653 |
+ Posterior Cingulate |
+ Normal |
+ PC119653M85N |
+ 85 |
+ M |
+
+
+ | 76 |
+ GSM119654 |
+ Posterior Cingulate |
+ Normal |
+ PC119654M80N |
+ 80 |
+ M |
+
+
+ | 77 |
+ GSM119655 |
+ Posterior Cingulate |
+ Normal |
+ PC119655F102N |
+ 102 |
+ F |
+
+
+ | 78 |
+ GSM119656 |
+ Posterior Cingulate |
+ Normal |
+ PC119656M63N |
+ 63 |
+ M |
+
+
+ | 79 |
+ GSM119657 |
+ Posterior Cingulate |
+ Normal |
+ PC119657M79N |
+ 79 |
+ M |
+
+
+ | 80 |
+ GSM119658 |
+ Posterior Cingulate |
+ Normal |
+ PC119658M->F76N |
+ 76 |
+ M |
+
+
+ | 81 |
+ GSM119659 |
+ Posterior Cingulate |
+ Normal |
+ PC119659M83N |
+ 83 |
+ M |
+
+
+ | 82 |
+ GSM119660 |
+ Posterior Cingulate |
+ Normal |
+ PC119660M79N |
+ 79 |
+ M |
+
+
+ | 83 |
+ GSM119661 |
+ Posterior Cingulate |
+ Normal |
+ PC119661F88N |
+ 88 |
+ F |
+
+
+ | 84 |
+ GSM119662 |
+ Posterior Cingulate |
+ Normal |
+ PC119662F82N |
+ 82 |
+ F |
+
+
+ | 85 |
+ GSM119663 |
+ Posterior Cingulate |
+ Normal |
+ PC119663F73N |
+ 73 |
+ F |
+
+
+ | 86 |
+ GSM119664 |
+ Posterior Cingulate |
+ Normal |
+ PC119664M69N |
+ 69 |
+ M |
+
+
+ | 87 |
+ GSM119665 |
+ Posterior Cingulate |
+ Normal |
+ PC119665M78N |
+ 78 |
+ M |
+
+
+ | 88 |
+ GSM238826 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238826F73A |
+ 73 |
+ F |
+
+
+ | 89 |
+ GSM238827 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238827M81A |
+ 81 |
+ M |
+
+
+ | 90 |
+ GSM238834 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238834M78A |
+ 78 |
+ M |
+
+
+ | 91 |
+ GSM238835 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238835M75A |
+ 75 |
+ M |
+
+
+ | 92 |
+ GSM238837 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238837M68A |
+ 68 |
+ M |
+
+
+ | 93 |
+ GSM238838 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238838F70A |
+ 70 |
+ F |
+
+
+ | 94 |
+ GSM238839 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238839F85A |
+ 85 |
+ F |
+
+
+ | 95 |
+ GSM238840 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238840M79A |
+ 79 |
+ M |
+
+
+ | 96 |
+ GSM238841 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238841M88A |
+ 88 |
+ M |
+
+
+ | 97 |
+ GSM119666 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119666M79N |
+ 79 |
+ M |
+
+
+ | 98 |
+ GSM119667 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119667F->M88N |
+ 88 |
+ F |
+
+
+ | 99 |
+ GSM119668 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119668F->M82N |
+ 82 |
+ F |
+
+
+ | 100 |
+ GSM119669 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119669F->M73N |
+ 73 |
+ F |
+
+
+ | 101 |
+ GSM119670 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119670F->M102N |
+ 102 |
+ F |
+
+
+ | 102 |
+ GSM119671 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119671M63N |
+ 63 |
+ M |
+
+
+ | 103 |
+ GSM119672 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119672M->F79N |
+ 79 |
+ M |
+
+
+ | 104 |
+ GSM119673 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119673M->F76N |
+ 76 |
+ M |
+
+
+ | 105 |
+ GSM119674 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119674M->F83N |
+ 83 |
+ M |
+
+
+ | 106 |
+ GSM119675 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119675M69N |
+ 69 |
+ M |
+
+
+ | 107 |
+ GSM119676 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119676M78N |
+ 78 |
+ M |
+
+
+ | 108 |
+ GSM238842 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238842F73A |
+ 73 |
+ F |
+
+
+ | 109 |
+ GSM238843 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238843M81A |
+ 81 |
+ M |
+
+
+ | 110 |
+ GSM238844 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238844M72A |
+ 72 |
+ M |
+
+
+ | 111 |
+ GSM238845 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238845M75A |
+ 75 |
+ M |
+
+
+ | 112 |
+ GSM238846 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238846M78A |
+ 78 |
+ M |
+
+
+ | 113 |
+ GSM238847 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238847M75A |
+ 75 |
+ M |
+
+
+ | 114 |
+ GSM238848 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238848M87A |
+ 87 |
+ M |
+
+
+ | 115 |
+ GSM238851 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238851F95A |
+ 95 |
+ F |
+
+
+ | 116 |
+ GSM238854 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238854M68A |
+ 68 |
+ M |
+
+
+ | 117 |
+ GSM238855 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238855F95A |
+ 95 |
+ F |
+
+
+ | 118 |
+ GSM238856 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238856F70A |
+ 70 |
+ F |
+
+
+ | 119 |
+ GSM238857 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238857F85A |
+ 85 |
+ F |
+
+
+ | 120 |
+ GSM238858 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238858F83A |
+ 83 |
+ F |
+
+
+ | 121 |
+ GSM238860 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238860F77A |
+ 77 |
+ F |
+
+
+ | 122 |
+ GSM238861 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238861F83A |
+ 83 |
+ F |
+
+
+ | 123 |
+ GSM238862 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238862M68A |
+ 68 |
+ M |
+
+
+ | 124 |
+ GSM238863 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238863M79A |
+ 79 |
+ M |
+
+
+ | 125 |
+ GSM238864 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238864F82A |
+ 82 |
+ F |
+
+
+ | 126 |
+ GSM238865 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238865M88A |
+ 88 |
+ M |
+
+
+ | 127 |
+ GSM238867 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238867F80A |
+ 80 |
+ F |
+
+
+ | 128 |
+ GSM238868 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238868M74A |
+ 74 |
+ M |
+
+
+ | 129 |
+ GSM238870 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238870M72A |
+ 72 |
+ M |
+
+
+ | 130 |
+ GSM238871 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238871M80A |
+ 80 |
+ M |
+
+
+ | 131 |
+ GSM119677 |
+ Primary Visual Cortex |
+ Normal |
+ V119677M85N |
+ 85 |
+ M |
+
+
+ | 132 |
+ GSM119678 |
+ Primary Visual Cortex |
+ Normal |
+ V119678M80N |
+ 80 |
+ M |
+
+
+ | 133 |
+ GSM119679 |
+ Primary Visual Cortex |
+ Normal |
+ V119679M63N |
+ 63 |
+ M |
+
+
+ | 134 |
+ GSM119680 |
+ Primary Visual Cortex |
+ Normal |
+ V119680M79N |
+ 79 |
+ M |
+
+
+ | 135 |
+ GSM119681 |
+ Primary Visual Cortex |
+ Normal |
+ V119681M76N |
+ 76 |
+ M |
+
+
+ | 136 |
+ GSM119682 |
+ Primary Visual Cortex |
+ Normal |
+ V119682M83N |
+ 83 |
+ M |
+
+
+ | 137 |
+ GSM119683 |
+ Primary Visual Cortex |
+ Normal |
+ V119683M79N |
+ 79 |
+ M |
+
+
+ | 138 |
+ GSM119684 |
+ Primary Visual Cortex |
+ Normal |
+ V119684F88N |
+ 88 |
+ F |
+
+
+ | 139 |
+ GSM119685 |
+ Primary Visual Cortex |
+ Normal |
+ V119685F82N |
+ 82 |
+ F |
+
+
+ | 140 |
+ GSM119686 |
+ Primary Visual Cortex |
+ Normal |
+ V119686F73N |
+ 73 |
+ F |
+
+
+ | 141 |
+ GSM119687 |
+ Primary Visual Cortex |
+ Normal |
+ V119687M69N |
+ 69 |
+ M |
+
+
+ | 142 |
+ GSM119688 |
+ Primary Visual Cortex |
+ Normal |
+ V119688M78N |
+ 78 |
+ M |
+
+
+ | 143 |
+ GSM238872 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238872F73A |
+ 73 |
+ F |
+
+
+ | 144 |
+ GSM238873 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238873M81A |
+ 81 |
+ M |
+
+
+ | 145 |
+ GSM238874 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238874M75A |
+ 75 |
+ M |
+
+
+ | 146 |
+ GSM238875 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238875M78A |
+ 78 |
+ M |
+
+
+ | 147 |
+ GSM238877 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238877M75A |
+ 75 |
+ M |
+
+
+ | 148 |
+ GSM238941 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238941M87A |
+ 87 |
+ M |
+
+
+ | 149 |
+ GSM238942 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238942F95A |
+ 95 |
+ F |
+
+
+ | 150 |
+ GSM238943 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238943M68A |
+ 68 |
+ M |
+
+
+ | 151 |
+ GSM238944 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238944F70A |
+ 70 |
+ F |
+
+
+ | 152 |
+ GSM238945 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238945F81A |
+ 81 |
+ F |
+
+
+ | 153 |
+ GSM238946 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238946F85A |
+ 85 |
+ F |
+
+
+ | 154 |
+ GSM238947 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238947M68A |
+ 68 |
+ M |
+
+
+ | 155 |
+ GSM238948 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238948M79A |
+ 79 |
+ M |
+
+
+ | 156 |
+ GSM238949 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238949F82A |
+ 82 |
+ F |
+
+
+ | 157 |
+ GSM238951 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238951M88A |
+ 88 |
+ M |
+
+
+ | 158 |
+ GSM238952 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238952M74A |
+ 74 |
+ M |
+
+
+ | 159 |
+ GSM238953 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238953M72A |
+ 72 |
+ M |
+
+
+ | 160 |
+ GSM238955 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238955M->F68A |
+ 68 |
+ M |
+
+
+ | 161 |
+ GSM238963 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238963F80A |
+ 80 |
+ F |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Gse5281_f_rma_alzh_0709/acknowledgment.rtf b/general/datasets/Gse5281_f_rma_alzh_0709/acknowledgment.rtf
new file mode 100644
index 0000000..8ce4f5c
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_alzh_0709/acknowledgment.rtf
@@ -0,0 +1 @@
+Please cite: Liang WS, Reiman EM, Valla J, Dunckley T, Beach TG, Grover A, Niedzielko TL, Schneider LE, Mastroeni D, Caselli R, Kukull W, Morris JC, Hulette CM, Schmechel D, Rogers J, Stephan DA (2008) Alzheimer's disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons. Proc Natl Acad Sci USA 105:4441-4446.
diff --git a/general/datasets/Gse5281_f_rma_alzh_0709/citation.rtf b/general/datasets/Gse5281_f_rma_alzh_0709/citation.rtf
new file mode 100644
index 0000000..6c255a4
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_alzh_0709/citation.rtf
@@ -0,0 +1,2 @@
+Liang WS, Dunckley T, Beach TG, Grover A et al. Gene expression profiles in anatomically and functionally distinct regions of the normal aged human brain. Physiol Genomics 2007 Feb 12;28(3):311-22. PMID: 17077275
+Liang WS, Reiman EM, Valla J, Dunckley T et al. Alzheimer's disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons. Proc Natl Acad Sci U S A 2008 Mar 18;105(11):4441-6. PMID: 18332434
diff --git a/general/datasets/Gse5281_f_rma_alzh_0709/contributors.rtf b/general/datasets/Gse5281_f_rma_alzh_0709/contributors.rtf
new file mode 100644
index 0000000..754b3a7
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_alzh_0709/contributors.rtf
@@ -0,0 +1 @@
+Stephan DA, Liang WS
diff --git a/general/datasets/Gse5281_f_rma_alzh_0709/experiment-design.rtf b/general/datasets/Gse5281_f_rma_alzh_0709/experiment-design.rtf
new file mode 100644
index 0000000..bc54b5c
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_alzh_0709/experiment-design.rtf
@@ -0,0 +1,13 @@
+Human brain expression data in patients with Alzheimer's disease and age-matched elderly control subjects. This cortical expression data set is taken from GEO GSE5281 (Liang et al. 2006, Liang et al. 2008). Samples were laser-captured from cortical regions of 16 normal elderly humans (10 males and 4 females) and from 33 AD cases (15 males and 18 females). Mean age of cases and controls was 80 years. All samples were run on the Affymetrix U133 Plus 2.0 array. We renormalized the RMA data to an average expression of 8 units on a log2 scale. Two versions of the data have been entered in GeneNetwork: one consisting of 157 of 161 arrays (full set minus 4 arrays we consider of poor quality); the second consisting of what we regard as the best 102 arrays (those with mean correlations of better than 0.88 with all other arrays). Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex area 17 layer III. GeneNetwork does not yet allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example, expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
+
+NOTE: We detected a minimum of 7.6% case assignment error rate (12 of 158 arrays) in this data set. Twelve cases are assigned to the wrong sex (see XIST probe set 224588_at, the figure below, and table 1). This raises the possibility that some cases are also misassigned by cortical brain region and disease status.
+
+
+
+
+
+Legend: Expression of the sex-specific gene XIST reveals about 10 sex assignment errors in this data set.
+
+Samples were laser-captured from cortical layer 3 (except the hippocampus) and run on the Affymetrix U133 Plus 2.0 array. We renormalized the data to an average expression of 8 units on a log2 scale. Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex layer III. A total of 16 normal subjects were used (10 M and 4 female). The AD samples. GeneNetwork does not allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
+
+Information about the genes that are preferentially expressed during the course of Alzheimer's disease (AD) could improve our understanding of the molecular mechanisms involved in the pathogenesis of this common cause of cognitive impairment in older persons, provide new opportunities in the diagnosis, early detection, and tracking of this disorder, and provide novel targets for the discovery of interventions to treat and prevent this disorder. Information about the genes that are preferentially expressed in relationship to normal neurological aging could provide new information about the molecular mechanisms that are involved in normal age-related cognitive decline and a host of age-related neurological disorders, and they could provide novel targets for the discovery of interventions to mitigate some of these deleterious effects.
diff --git a/general/datasets/Gse5281_f_rma_alzh_0709/experiment-type.rtf b/general/datasets/Gse5281_f_rma_alzh_0709/experiment-type.rtf
new file mode 100644
index 0000000..5797da1
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_alzh_0709/experiment-type.rtf
@@ -0,0 +1,9 @@
+
+Human brain expression data in patients with Alzheimer's disease and age-matched elderly control subjects. This cortical expression data set is taken from GEO GSE5281 (Liang et al. 2006, Liang et al. 2008). Samples were laser-captured from cortical regions of 16 normal elderly humans (10 males and 4 females) and from 33 AD cases (15 males and 18 females). Mean age of cases and controls was 80 years. All samples were run on the Affymetrix U133 Plus 2.0 array. We renormalized the RMA data to an average expression of 8 units on a log2 scale. Two versions of the data have been entered in GeneNetwork: one consisting of 157 of 161 arrays (full set minus 4 arrays we consider of poor quality); the second consisting of what we regard as the best 102 arrays (those with mean correlations of better than 0.88 with all other arrays). Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex area 17 layer III. GeneNetwork does not yet allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example, expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
+
+
NOTE: We detected a minimum of 7.6% case assignment error rate (12 of 158 arrays) in this data set. Twelve cases are assigned to the wrong sex (see XIST probe set 224588_at, the figure below, and table 1). This raises the possibility that some cases are also misassigned by cortical brain region and disease status.
+
+
+Legend: Expression of the sex-specific gene XIST reveals about 10 sex assignment errors in this data set.
+
+Samples were laser-captured from cortical layer 3 (except the hippocampus) and run on the Affymetrix U133 Plus 2.0 array. We renormalized the data to an average expression of 8 units on a log2 scale. Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex layer III. A total of 16 normal subjects were used (10 M and 4 female). The AD samples. GeneNetwork does not allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
\ No newline at end of file
diff --git a/general/datasets/Gse5281_f_rma_alzh_0709/platform.rtf b/general/datasets/Gse5281_f_rma_alzh_0709/platform.rtf
new file mode 100644
index 0000000..6c2af02
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_alzh_0709/platform.rtf
@@ -0,0 +1,3 @@
+Affymetrix submissions are typically submitted to GEO using the GEOarchive method described at http://www.ncbi.nlm.nih.gov/projects/geo/info/geo_affy.html Complete coverage of the Human Genome U133 Set plus 6,500 additional genes for analysis of over 47,000 transcripts All probe sets represented on the GeneChip Human Genome U133 Set are identically replicated on the GeneChip Human Genome U133 Plus 2.0 Array. The sequences from which these probe sets were derived were selected from GenBank®, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 133, April 20, 2001) and then refined by analysis and comparison with a number of other publicly available databases, including the Washington University EST trace repository and the University of California, Santa Cruz Golden-Path human genome database (April 2001 release).
+
+In addition, there are 9,921 new probe sets representing approximately 6,500 new genes. These gene sequences were selected from GenBank, dbEST, and RefSeq. Sequence clusters were created from the UniGene database (Build 159, January 25, 2003) and refined by analysis and comparison with a number of other publicly available databases, including the Washington University EST trace repository and the NCBI human genome assembly (Build 31).
diff --git a/general/datasets/Gse5281_f_rma_alzh_0709/summary.rtf b/general/datasets/Gse5281_f_rma_alzh_0709/summary.rtf
new file mode 100644
index 0000000..5db3978
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_alzh_0709/summary.rtf
@@ -0,0 +1,1484 @@
+(Taken verbatim from the GEO record)
+
+Information about the genes that are preferentially expressed during the course of Alzheimer’s disease (AD) could improve our understanding of the molecular mechanisms involved in the pathogenesis of this common cause of cognitive impairment in older persons, provide new opportunities in the diagnosis, early detection, and tracking of this disorder, and provide novel targets for the discovery of interventions to treat and prevent this disorder. Information about the genes that are preferentially expressed in relationship to normal neurological aging could provide new information about the molecular mechanisms that are involved in normal age-related cognitive decline and a host of age-related neurological disorders, and they could provide novel targets for the discovery of interventions to mitigate some of these deleterious effects.
+
+Aim 1. Collect brain samples from three Alzheimer’s Disease Centers (ADCs) for subsequent gene expression profiling. Individuals will be stratified with respect to diagnostic groups (using both clinical and neuropathological criteria), age groups, and APOE genotype. 150 individual brains will be sampled from the Arizona ADC, the Duke University ADC, and the Washington University ADC. Miniscule sample sizes (200 um of sectioned tissue) from six brain regions that are histopathologically or metabolically relevant to AD and aging will be collected, ensuring that this proposal does not deplete the national resource. Frozen and fixed samples will be sent to Phoenix, sectioned in a standardized fashion, and then returned. Aim 2. Tissue heterogeneity will be eliminated prior to expression profiling by performing laser capture microscopy on all brain regions. Aim 3. Expression profile LCM-captured cells on the Affymetrix U133 Plus 2.0 array (~55,000 transcripts), and quickly provide these data to the community at large. Aim 4. Identify pathogenic cascades related to each of the clinico-pathologic correlates using unsupervised and supervised analyses coupled with a hypothesis-driven approach. Aim 5. Validation of the expression correlates at the protein and functional levels.
+
+Scientific progress in the last few years has improved our understanding of AD and raised the hope of identifying treatments to halt the progression and prevent the onset of this disorder. For instance, researchers have begun to characterize the cascade of molecular events which lead to the major histopathological features of the disorder: neuritic plaques, which contain extra-cellular deposits of amyloid beta-peptides (Abeta); neurofibrillary tangles, which contain the hyperphosphorylated form of the intracellular, microtubule-associated protein, tau; and a loss of neurons and synapses. These molecular events provide targets for the development of promising new treatments. For example, A-beta has been postulated to trigger a cascade of events that are involved in the pathogenesis of AD. This proposal hopes to provide new information about the genes that are preferentially expressed in the development of AD histopathology, including the over-expression of APP, amyloid-induced neurotoxicity, and hyperphosphorylation of tau, as well as bring clarity to the metabolic abnormalities that seem to play a role in dementia and AD development and pathology.
+
+We will perform LCM on 6 brain regions with about 14 biological replicates per brain region. The brain regions are as follows: 1) entorhinal cortex 2) hippocampus 3) medial temporal gyrus 4) posterior cingulate 5) superior frontal gyrus and 6) primary visual cortex. We will collect layer III pyramidal cells from the white matter in each region, isolate total RNA from LCMed cell lysates, and perform double round amplification of each sample for array analysis.
+
+
+
+Bad arrays excluded: Four samples, highlighted in the table below, are bad arrays. For quality control, they should be excluded.
+
+
+
+
+
+
+
+
+ | Index |
+ GEO Series |
+ Organ Region |
+ Tissue |
+ Case ID |
+ Age |
+ Sex |
+
+
+ | 1 |
+ GSM119615 |
+ Entorhinal Cortex |
+ Normal |
+ E119615M63N |
+ 63 |
+ M |
+
+
+ | 2 |
+ GSM119616 |
+ Entorhinal Cortex |
+ Normal |
+ E119616M85N |
+ 85 |
+ M |
+
+
+ | 3 |
+ GSM119617 |
+ Entorhinal Cortex |
+ Normal |
+ E119617M80N |
+ 80 |
+ M |
+
+
+ | 4 |
+ GSM119618 |
+ Entorhinal Cortex |
+ Normal |
+ E119618M->F80N |
+ 80 |
+ M |
+
+
+ | 5 |
+ GSM119619 |
+ Entorhinal Cortex |
+ Normal |
+ E119619F->M102N |
+ 102 |
+ F |
+
+
+ | 6 |
+ GSM119620 |
+ Entorhinal Cortex |
+ Normal |
+ E119620M79N |
+ 79 |
+ M |
+
+
+ | 7 |
+ GSM119621 |
+ Entorhinal Cortex |
+ Normal |
+ E119621M76N |
+ 76 |
+ M |
+
+
+ | 8 |
+ GSM119622 |
+ Entorhinal Cortex |
+ Normal |
+ E119622M83N |
+ 83 |
+ M |
+
+
+ | 9 |
+ GSM119623 |
+ Entorhinal Cortex |
+ Normal |
+ E119623M79N |
+ 79 |
+ M |
+
+
+ | 10 |
+ GSM119624 |
+ Entorhinal Cortex |
+ Normal |
+ E119624F88N |
+ 88 |
+ F |
+
+
+ | 11 |
+ GSM119625 |
+ Entorhinal Cortex |
+ Normal |
+ E119625F82N |
+ 82 |
+ F |
+
+
+ | 12 |
+ GSM119626 |
+ Entorhinal Cortex |
+ Normal |
+ E119626M69N |
+ 69 |
+ M |
+
+
+ | 13 |
+ GSM119627 |
+ Entorhinal Cortex |
+ Normal |
+ E119627M78N |
+ 78 |
+ M |
+
+
+ | 14 |
+ GSM238763 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238763F82A |
+ 82 |
+ F |
+
+
+ | 15 |
+ GSM238790 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238790F86A |
+ 86 |
+ F |
+
+
+ | 16 |
+ GSM238791 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238791F93A |
+ 93 |
+ F |
+
+
+ | 17 |
+ GSM238792 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238792M84A |
+ 84 |
+ M |
+
+
+ | 18 |
+ GSM238793 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238793F79A |
+ 79 |
+ F |
+
+
+ | 19 |
+ GSM238794 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238794F78A |
+ 78 |
+ F |
+
+
+ | 20 |
+ GSM238795 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238795F91A |
+ 91 |
+ F |
+
+
+ | 21 |
+ GSM238796 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238796M86A |
+ 86 |
+ M |
+
+
+ | 22 |
+ GSM238797 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238797NA0A |
+ N/A |
+ N/A |
+
+
+ | 23 |
+ GSM238798 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238798M80A |
+ 80 |
+ M |
+
+
+ | 24 |
+ GSM119628 |
+ Hippocampus |
+ Normal |
+ H119628M85N |
+ 85 |
+ M |
+
+
+ | 25 |
+ GSM119629 |
+ Hippocampus |
+ Normal |
+ H119629M80N |
+ 80 |
+ M |
+
+
+ | 26 |
+ GSM119630 |
+ Hippocampus |
+ Normal |
+ H119630M80N |
+ 80 |
+ M |
+
+
+ | 27 |
+ GSM119631 |
+ Hippocampus |
+ Normal |
+ H119631F102N |
+ 102 |
+ F |
+
+
+ | 28 |
+ GSM119632 |
+ Hippocampus |
+ Normal |
+ H119632M63N |
+ 63 |
+ M |
+
+
+ | 29 |
+ GSM119633 |
+ Hippocampus |
+ Normal |
+ H119633M79N |
+ 79 |
+ M |
+
+
+ | 30 |
+ GSM119634 |
+ Hippocampus |
+ Normal |
+ H119634M76N |
+ 76 |
+ M |
+
+
+ | 31 |
+ GSM119635 |
+ Hippocampus |
+ Normal |
+ H119635M83N |
+ 83 |
+ M |
+
+
+ | 32 |
+ GSM119636 |
+ Hippocampus |
+ Normal |
+ H119636M79N |
+ 79 |
+ M |
+
+
+ | 33 |
+ GSM119637 |
+ Hippocampus |
+ Normal |
+ H119637F88N |
+ 88 |
+ F |
+
+
+ | 34 |
+ GSM119638 |
+ Hippocampus |
+ Normal |
+ H119638F73N |
+ 73 |
+ F |
+
+
+ | 35 |
+ GSM119639 |
+ Hippocampus |
+ Normal |
+ H119639M69N |
+ 69 |
+ M |
+
+
+ | 36 |
+ GSM119640 |
+ Hippocampus |
+ Normal |
+ H119640M78N |
+ 78 |
+ M |
+
+
+ | 37 |
+ GSM238799 |
+ Hippocampus |
+ Alzheimer's |
+ H238799F73A |
+ 73 |
+ F |
+
+
+ | 38 |
+ GSM238800 |
+ Hippocampus |
+ Alzheimer's |
+ H238800M81A |
+ 81 |
+ M |
+
+
+ | 39 |
+ GSM238801 |
+ Hippocampus |
+ Alzheimer's |
+ H238801M78A |
+ 78 |
+ M |
+
+
+ | 40 |
+ GSM238802 |
+ Hippocampus |
+ Alzheimer's |
+ H238802M75A |
+ 75 |
+ M |
+
+
+ | 41 |
+ GSM238803 |
+ Hippocampus |
+ Alzheimer's |
+ H238803F70A |
+ 70 |
+ F |
+
+
+ | 42 |
+ GSM238804 |
+ Hippocampus |
+ Alzheimer's |
+ H238804F85A |
+ 85 |
+ F |
+
+
+ | 43 |
+ GSM238805 |
+ Hippocampus |
+ Alzheimer's |
+ H238805F77A |
+ 77 |
+ F |
+
+
+ | 44 |
+ GSM238806 |
+ Hippocampus |
+ Alzheimer's |
+ H238806M79A |
+ 79 |
+ M |
+
+
+ | 45 |
+ GSM238807 |
+ Hippocampus |
+ Alzheimer's |
+ H238807M88A |
+ 88 |
+ M |
+
+
+ | 46 |
+ GSM238808 |
+ Hippocampus |
+ Alzheimer's |
+ H238808M72A |
+ 72 |
+ M |
+
+
+ | 47 |
+ GSM119641 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119641M85N |
+ 85 |
+ M |
+
+
+ | 48 |
+ GSM119642 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119642M80N |
+ 80 |
+ M |
+
+
+ | 49 |
+ GSM119643 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119643F102N |
+ 102 |
+ F |
+
+
+ | 50 |
+ GSM119644 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119644M63N |
+ 63 |
+ M |
+
+
+ | 51 |
+ GSM119645 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119645M79N |
+ 79 |
+ M |
+
+
+ | 52 |
+ GSM119646 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119646M83N |
+ 83 |
+ M |
+
+
+ | 53 |
+ GSM119647 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119647M79N |
+ 79 |
+ M |
+
+
+ | 54 |
+ GSM119648 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119648F88N |
+ 88 |
+ F |
+
+
+ | 55 |
+ GSM119649 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119649F82N |
+ 82 |
+ F |
+
+
+ | 56 |
+ GSM119650 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119650F73N |
+ 73 |
+ F |
+
+
+ | 57 |
+ GSM119651 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119651M69N |
+ 69 |
+ M |
+
+
+ | 58 |
+ GSM119652 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119652M->F78N |
+ 78 |
+ M |
+
+
+ | 59 |
+ GSM238809 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238809M81A |
+ 81 |
+ M |
+
+
+ | 60 |
+ GSM238810 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238810M72A |
+ 72 |
+ M |
+
+
+ | 61 |
+ GSM238811 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238811M75A |
+ 75 |
+ M |
+
+
+ | 62 |
+ GSM238812 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238812M78A |
+ 78 |
+ M |
+
+
+ | 63 |
+ GSM238813 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238813M75A |
+ 75 |
+ M |
+
+
+ | 64 |
+ GSM238815 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238815F95A |
+ 95 |
+ F |
+
+
+ | 65 |
+ GSM238816 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238816F81A |
+ 81 |
+ F |
+
+
+ | 66 |
+ GSM238817 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238817F85A |
+ 85 |
+ F |
+
+
+ | 67 |
+ GSM238818 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238818M79A |
+ 79 |
+ M |
+
+
+ | 68 |
+ GSM238819 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238819F82A |
+ 82 |
+ F |
+
+
+ | 69 |
+ GSM238820 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238820M88A |
+ 88 |
+ M |
+
+
+ | 70 |
+ GSM238821 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238821M72A |
+ 72 |
+ M |
+
+
+ | 71 |
+ GSM238822 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238822F73A |
+ 73 |
+ F |
+
+
+ | 72 |
+ GSM238823 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238823M87A |
+ 87 |
+ M |
+
+
+ | 73 |
+ GSM238824 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238824M68A |
+ 68 |
+ M |
+
+
+ | 74 |
+ GSM238825 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238825F80A |
+ 80 |
+ F |
+
+
+ | 75 |
+ GSM119653 |
+ Posterior Cingulate |
+ Normal |
+ PC119653M85N |
+ 85 |
+ M |
+
+
+ | 76 |
+ GSM119654 |
+ Posterior Cingulate |
+ Normal |
+ PC119654M80N |
+ 80 |
+ M |
+
+
+ | 77 |
+ GSM119655 |
+ Posterior Cingulate |
+ Normal |
+ PC119655F102N |
+ 102 |
+ F |
+
+
+ | 78 |
+ GSM119656 |
+ Posterior Cingulate |
+ Normal |
+ PC119656M63N |
+ 63 |
+ M |
+
+
+ | 79 |
+ GSM119657 |
+ Posterior Cingulate |
+ Normal |
+ PC119657M79N |
+ 79 |
+ M |
+
+
+ | 80 |
+ GSM119658 |
+ Posterior Cingulate |
+ Normal |
+ PC119658M->F76N |
+ 76 |
+ M |
+
+
+ | 81 |
+ GSM119659 |
+ Posterior Cingulate |
+ Normal |
+ PC119659M83N |
+ 83 |
+ M |
+
+
+ | 82 |
+ GSM119660 |
+ Posterior Cingulate |
+ Normal |
+ PC119660M79N |
+ 79 |
+ M |
+
+
+ | 83 |
+ GSM119661 |
+ Posterior Cingulate |
+ Normal |
+ PC119661F88N |
+ 88 |
+ F |
+
+
+ | 84 |
+ GSM119662 |
+ Posterior Cingulate |
+ Normal |
+ PC119662F82N |
+ 82 |
+ F |
+
+
+ | 85 |
+ GSM119663 |
+ Posterior Cingulate |
+ Normal |
+ PC119663F73N |
+ 73 |
+ F |
+
+
+ | 86 |
+ GSM119664 |
+ Posterior Cingulate |
+ Normal |
+ PC119664M69N |
+ 69 |
+ M |
+
+
+ | 87 |
+ GSM119665 |
+ Posterior Cingulate |
+ Normal |
+ PC119665M78N |
+ 78 |
+ M |
+
+
+ | 88 |
+ GSM238826 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238826F73A |
+ 73 |
+ F |
+
+
+ | 89 |
+ GSM238827 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238827M81A |
+ 81 |
+ M |
+
+
+ | 90 |
+ GSM238834 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238834M78A |
+ 78 |
+ M |
+
+
+ | 91 |
+ GSM238835 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238835M75A |
+ 75 |
+ M |
+
+
+ | 92 |
+ GSM238837 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238837M68A |
+ 68 |
+ M |
+
+
+ | 93 |
+ GSM238838 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238838F70A |
+ 70 |
+ F |
+
+
+ | 94 |
+ GSM238839 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238839F85A |
+ 85 |
+ F |
+
+
+ | 95 |
+ GSM238840 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238840M79A |
+ 79 |
+ M |
+
+
+ | 96 |
+ GSM238841 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238841M88A |
+ 88 |
+ M |
+
+
+ | 97 |
+ GSM119666 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119666M79N |
+ 79 |
+ M |
+
+
+ | 98 |
+ GSM119667 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119667F->M88N |
+ 88 |
+ F |
+
+
+ | 99 |
+ GSM119668 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119668F->M82N |
+ 82 |
+ F |
+
+
+ | 100 |
+ GSM119669 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119669F->M73N |
+ 73 |
+ F |
+
+
+ | 101 |
+ GSM119670 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119670F->M102N |
+ 102 |
+ F |
+
+
+ | 102 |
+ GSM119671 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119671M63N |
+ 63 |
+ M |
+
+
+ | 103 |
+ GSM119672 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119672M->F79N |
+ 79 |
+ M |
+
+
+ | 104 |
+ GSM119673 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119673M->F76N |
+ 76 |
+ M |
+
+
+ | 105 |
+ GSM119674 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119674M->F83N |
+ 83 |
+ M |
+
+
+ | 106 |
+ GSM119675 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119675M69N |
+ 69 |
+ M |
+
+
+ | 107 |
+ GSM119676 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119676M78N |
+ 78 |
+ M |
+
+
+ | 108 |
+ GSM238842 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238842F73A |
+ 73 |
+ F |
+
+
+ | 109 |
+ GSM238843 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238843M81A |
+ 81 |
+ M |
+
+
+ | 110 |
+ GSM238844 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238844M72A |
+ 72 |
+ M |
+
+
+ | 111 |
+ GSM238845 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238845M75A |
+ 75 |
+ M |
+
+
+ | 112 |
+ GSM238846 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238846M78A |
+ 78 |
+ M |
+
+
+ | 113 |
+ GSM238847 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238847M75A |
+ 75 |
+ M |
+
+
+ | 114 |
+ GSM238848 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238848M87A |
+ 87 |
+ M |
+
+
+ | 115 |
+ GSM238851 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238851F95A |
+ 95 |
+ F |
+
+
+ | 116 |
+ GSM238854 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238854M68A |
+ 68 |
+ M |
+
+
+ | 117 |
+ GSM238855 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238855F95A |
+ 95 |
+ F |
+
+
+ | 118 |
+ GSM238856 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238856F70A |
+ 70 |
+ F |
+
+
+ | 119 |
+ GSM238857 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238857F85A |
+ 85 |
+ F |
+
+
+ | 120 |
+ GSM238858 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238858F83A |
+ 83 |
+ F |
+
+
+ | 121 |
+ GSM238860 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238860F77A |
+ 77 |
+ F |
+
+
+ | 122 |
+ GSM238861 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238861F83A |
+ 83 |
+ F |
+
+
+ | 123 |
+ GSM238862 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238862M68A |
+ 68 |
+ M |
+
+
+ | 124 |
+ GSM238863 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238863M79A |
+ 79 |
+ M |
+
+
+ | 125 |
+ GSM238864 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238864F82A |
+ 82 |
+ F |
+
+
+ | 126 |
+ GSM238865 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238865M88A |
+ 88 |
+ M |
+
+
+ | 127 |
+ GSM238867 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238867F80A |
+ 80 |
+ F |
+
+
+ | 128 |
+ GSM238868 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238868M74A |
+ 74 |
+ M |
+
+
+ | 129 |
+ GSM238870 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238870M72A |
+ 72 |
+ M |
+
+
+ | 130 |
+ GSM238871 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238871M80A |
+ 80 |
+ M |
+
+
+ | 131 |
+ GSM119677 |
+ Primary Visual Cortex |
+ Normal |
+ V119677M85N |
+ 85 |
+ M |
+
+
+ | 132 |
+ GSM119678 |
+ Primary Visual Cortex |
+ Normal |
+ V119678M80N |
+ 80 |
+ M |
+
+
+ | 133 |
+ GSM119679 |
+ Primary Visual Cortex |
+ Normal |
+ V119679M63N |
+ 63 |
+ M |
+
+
+ | 134 |
+ GSM119680 |
+ Primary Visual Cortex |
+ Normal |
+ V119680M79N |
+ 79 |
+ M |
+
+
+ | 135 |
+ GSM119681 |
+ Primary Visual Cortex |
+ Normal |
+ V119681M76N |
+ 76 |
+ M |
+
+
+ | 136 |
+ GSM119682 |
+ Primary Visual Cortex |
+ Normal |
+ V119682M83N |
+ 83 |
+ M |
+
+
+ | 137 |
+ GSM119683 |
+ Primary Visual Cortex |
+ Normal |
+ V119683M79N |
+ 79 |
+ M |
+
+
+ | 138 |
+ GSM119684 |
+ Primary Visual Cortex |
+ Normal |
+ V119684F88N |
+ 88 |
+ F |
+
+
+ | 139 |
+ GSM119685 |
+ Primary Visual Cortex |
+ Normal |
+ V119685F82N |
+ 82 |
+ F |
+
+
+ | 140 |
+ GSM119686 |
+ Primary Visual Cortex |
+ Normal |
+ V119686F73N |
+ 73 |
+ F |
+
+
+ | 141 |
+ GSM119687 |
+ Primary Visual Cortex |
+ Normal |
+ V119687M69N |
+ 69 |
+ M |
+
+
+ | 142 |
+ GSM119688 |
+ Primary Visual Cortex |
+ Normal |
+ V119688M78N |
+ 78 |
+ M |
+
+
+ | 143 |
+ GSM238872 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238872F73A |
+ 73 |
+ F |
+
+
+ | 144 |
+ GSM238873 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238873M81A |
+ 81 |
+ M |
+
+
+ | 145 |
+ GSM238874 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238874M75A |
+ 75 |
+ M |
+
+
+ | 146 |
+ GSM238875 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238875M78A |
+ 78 |
+ M |
+
+
+ | 147 |
+ GSM238877 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238877M75A |
+ 75 |
+ M |
+
+
+ | 148 |
+ GSM238941 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238941M87A |
+ 87 |
+ M |
+
+
+ | 149 |
+ GSM238942 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238942F95A |
+ 95 |
+ F |
+
+
+ | 150 |
+ GSM238943 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238943M68A |
+ 68 |
+ M |
+
+
+ | 151 |
+ GSM238944 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238944F70A |
+ 70 |
+ F |
+
+
+ | 152 |
+ GSM238945 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238945F81A |
+ 81 |
+ F |
+
+
+ | 153 |
+ GSM238946 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238946F85A |
+ 85 |
+ F |
+
+
+ | 154 |
+ GSM238947 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238947M68A |
+ 68 |
+ M |
+
+
+ | 155 |
+ GSM238948 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238948M79A |
+ 79 |
+ M |
+
+
+ | 156 |
+ GSM238949 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238949F82A |
+ 82 |
+ F |
+
+
+ | 157 |
+ GSM238951 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238951M88A |
+ 88 |
+ M |
+
+
+ | 158 |
+ GSM238952 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238952M74A |
+ 74 |
+ M |
+
+
+ | 159 |
+ GSM238953 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238953M72A |
+ 72 |
+ M |
+
+
+ | 160 |
+ GSM238955 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238955M->F68A |
+ 68 |
+ M |
+
+
+ | 161 |
+ GSM238963 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238963F80A |
+ 80 |
+ F |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Gse5281_f_rma_n_0709/acknowledgment.rtf b/general/datasets/Gse5281_f_rma_n_0709/acknowledgment.rtf
new file mode 100644
index 0000000..8ce4f5c
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_n_0709/acknowledgment.rtf
@@ -0,0 +1 @@
+Please cite: Liang WS, Reiman EM, Valla J, Dunckley T, Beach TG, Grover A, Niedzielko TL, Schneider LE, Mastroeni D, Caselli R, Kukull W, Morris JC, Hulette CM, Schmechel D, Rogers J, Stephan DA (2008) Alzheimer's disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons. Proc Natl Acad Sci USA 105:4441-4446.
diff --git a/general/datasets/Gse5281_f_rma_n_0709/citation.rtf b/general/datasets/Gse5281_f_rma_n_0709/citation.rtf
new file mode 100644
index 0000000..6c255a4
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_n_0709/citation.rtf
@@ -0,0 +1,2 @@
+Liang WS, Dunckley T, Beach TG, Grover A et al. Gene expression profiles in anatomically and functionally distinct regions of the normal aged human brain. Physiol Genomics 2007 Feb 12;28(3):311-22. PMID: 17077275
+Liang WS, Reiman EM, Valla J, Dunckley T et al. Alzheimer's disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons. Proc Natl Acad Sci U S A 2008 Mar 18;105(11):4441-6. PMID: 18332434
diff --git a/general/datasets/Gse5281_f_rma_n_0709/contributors.rtf b/general/datasets/Gse5281_f_rma_n_0709/contributors.rtf
new file mode 100644
index 0000000..754b3a7
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_n_0709/contributors.rtf
@@ -0,0 +1 @@
+Stephan DA, Liang WS
diff --git a/general/datasets/Gse5281_f_rma_n_0709/experiment-design.rtf b/general/datasets/Gse5281_f_rma_n_0709/experiment-design.rtf
new file mode 100644
index 0000000..bc54b5c
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_n_0709/experiment-design.rtf
@@ -0,0 +1,13 @@
+Human brain expression data in patients with Alzheimer's disease and age-matched elderly control subjects. This cortical expression data set is taken from GEO GSE5281 (Liang et al. 2006, Liang et al. 2008). Samples were laser-captured from cortical regions of 16 normal elderly humans (10 males and 4 females) and from 33 AD cases (15 males and 18 females). Mean age of cases and controls was 80 years. All samples were run on the Affymetrix U133 Plus 2.0 array. We renormalized the RMA data to an average expression of 8 units on a log2 scale. Two versions of the data have been entered in GeneNetwork: one consisting of 157 of 161 arrays (full set minus 4 arrays we consider of poor quality); the second consisting of what we regard as the best 102 arrays (those with mean correlations of better than 0.88 with all other arrays). Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex area 17 layer III. GeneNetwork does not yet allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example, expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
+
+NOTE: We detected a minimum of 7.6% case assignment error rate (12 of 158 arrays) in this data set. Twelve cases are assigned to the wrong sex (see XIST probe set 224588_at, the figure below, and table 1). This raises the possibility that some cases are also misassigned by cortical brain region and disease status.
+
+
+
+
+
+Legend: Expression of the sex-specific gene XIST reveals about 10 sex assignment errors in this data set.
+
+Samples were laser-captured from cortical layer 3 (except the hippocampus) and run on the Affymetrix U133 Plus 2.0 array. We renormalized the data to an average expression of 8 units on a log2 scale. Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex layer III. A total of 16 normal subjects were used (10 M and 4 female). The AD samples. GeneNetwork does not allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
+
+Information about the genes that are preferentially expressed during the course of Alzheimer's disease (AD) could improve our understanding of the molecular mechanisms involved in the pathogenesis of this common cause of cognitive impairment in older persons, provide new opportunities in the diagnosis, early detection, and tracking of this disorder, and provide novel targets for the discovery of interventions to treat and prevent this disorder. Information about the genes that are preferentially expressed in relationship to normal neurological aging could provide new information about the molecular mechanisms that are involved in normal age-related cognitive decline and a host of age-related neurological disorders, and they could provide novel targets for the discovery of interventions to mitigate some of these deleterious effects.
diff --git a/general/datasets/Gse5281_f_rma_n_0709/experiment-type.rtf b/general/datasets/Gse5281_f_rma_n_0709/experiment-type.rtf
new file mode 100644
index 0000000..5797da1
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_n_0709/experiment-type.rtf
@@ -0,0 +1,9 @@
+
+Human brain expression data in patients with Alzheimer's disease and age-matched elderly control subjects. This cortical expression data set is taken from GEO GSE5281 (Liang et al. 2006, Liang et al. 2008). Samples were laser-captured from cortical regions of 16 normal elderly humans (10 males and 4 females) and from 33 AD cases (15 males and 18 females). Mean age of cases and controls was 80 years. All samples were run on the Affymetrix U133 Plus 2.0 array. We renormalized the RMA data to an average expression of 8 units on a log2 scale. Two versions of the data have been entered in GeneNetwork: one consisting of 157 of 161 arrays (full set minus 4 arrays we consider of poor quality); the second consisting of what we regard as the best 102 arrays (those with mean correlations of better than 0.88 with all other arrays). Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex area 17 layer III. GeneNetwork does not yet allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example, expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
+
+
NOTE: We detected a minimum of 7.6% case assignment error rate (12 of 158 arrays) in this data set. Twelve cases are assigned to the wrong sex (see XIST probe set 224588_at, the figure below, and table 1). This raises the possibility that some cases are also misassigned by cortical brain region and disease status.
+
+
+Legend: Expression of the sex-specific gene XIST reveals about 10 sex assignment errors in this data set.
+
+Samples were laser-captured from cortical layer 3 (except the hippocampus) and run on the Affymetrix U133 Plus 2.0 array. We renormalized the data to an average expression of 8 units on a log2 scale. Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex layer III. A total of 16 normal subjects were used (10 M and 4 female). The AD samples. GeneNetwork does not allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
\ No newline at end of file
diff --git a/general/datasets/Gse5281_f_rma_n_0709/platform.rtf b/general/datasets/Gse5281_f_rma_n_0709/platform.rtf
new file mode 100644
index 0000000..6c2af02
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_n_0709/platform.rtf
@@ -0,0 +1,3 @@
+Affymetrix submissions are typically submitted to GEO using the GEOarchive method described at http://www.ncbi.nlm.nih.gov/projects/geo/info/geo_affy.html Complete coverage of the Human Genome U133 Set plus 6,500 additional genes for analysis of over 47,000 transcripts All probe sets represented on the GeneChip Human Genome U133 Set are identically replicated on the GeneChip Human Genome U133 Plus 2.0 Array. The sequences from which these probe sets were derived were selected from GenBank®, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 133, April 20, 2001) and then refined by analysis and comparison with a number of other publicly available databases, including the Washington University EST trace repository and the University of California, Santa Cruz Golden-Path human genome database (April 2001 release).
+
+In addition, there are 9,921 new probe sets representing approximately 6,500 new genes. These gene sequences were selected from GenBank, dbEST, and RefSeq. Sequence clusters were created from the UniGene database (Build 159, January 25, 2003) and refined by analysis and comparison with a number of other publicly available databases, including the Washington University EST trace repository and the NCBI human genome assembly (Build 31).
diff --git a/general/datasets/Gse5281_f_rma_n_0709/summary.rtf b/general/datasets/Gse5281_f_rma_n_0709/summary.rtf
new file mode 100644
index 0000000..5db3978
--- /dev/null
+++ b/general/datasets/Gse5281_f_rma_n_0709/summary.rtf
@@ -0,0 +1,1484 @@
+(Taken verbatim from the GEO record)
+
+Information about the genes that are preferentially expressed during the course of Alzheimer’s disease (AD) could improve our understanding of the molecular mechanisms involved in the pathogenesis of this common cause of cognitive impairment in older persons, provide new opportunities in the diagnosis, early detection, and tracking of this disorder, and provide novel targets for the discovery of interventions to treat and prevent this disorder. Information about the genes that are preferentially expressed in relationship to normal neurological aging could provide new information about the molecular mechanisms that are involved in normal age-related cognitive decline and a host of age-related neurological disorders, and they could provide novel targets for the discovery of interventions to mitigate some of these deleterious effects.
+
+Aim 1. Collect brain samples from three Alzheimer’s Disease Centers (ADCs) for subsequent gene expression profiling. Individuals will be stratified with respect to diagnostic groups (using both clinical and neuropathological criteria), age groups, and APOE genotype. 150 individual brains will be sampled from the Arizona ADC, the Duke University ADC, and the Washington University ADC. Miniscule sample sizes (200 um of sectioned tissue) from six brain regions that are histopathologically or metabolically relevant to AD and aging will be collected, ensuring that this proposal does not deplete the national resource. Frozen and fixed samples will be sent to Phoenix, sectioned in a standardized fashion, and then returned. Aim 2. Tissue heterogeneity will be eliminated prior to expression profiling by performing laser capture microscopy on all brain regions. Aim 3. Expression profile LCM-captured cells on the Affymetrix U133 Plus 2.0 array (~55,000 transcripts), and quickly provide these data to the community at large. Aim 4. Identify pathogenic cascades related to each of the clinico-pathologic correlates using unsupervised and supervised analyses coupled with a hypothesis-driven approach. Aim 5. Validation of the expression correlates at the protein and functional levels.
+
+Scientific progress in the last few years has improved our understanding of AD and raised the hope of identifying treatments to halt the progression and prevent the onset of this disorder. For instance, researchers have begun to characterize the cascade of molecular events which lead to the major histopathological features of the disorder: neuritic plaques, which contain extra-cellular deposits of amyloid beta-peptides (Abeta); neurofibrillary tangles, which contain the hyperphosphorylated form of the intracellular, microtubule-associated protein, tau; and a loss of neurons and synapses. These molecular events provide targets for the development of promising new treatments. For example, A-beta has been postulated to trigger a cascade of events that are involved in the pathogenesis of AD. This proposal hopes to provide new information about the genes that are preferentially expressed in the development of AD histopathology, including the over-expression of APP, amyloid-induced neurotoxicity, and hyperphosphorylation of tau, as well as bring clarity to the metabolic abnormalities that seem to play a role in dementia and AD development and pathology.
+
+We will perform LCM on 6 brain regions with about 14 biological replicates per brain region. The brain regions are as follows: 1) entorhinal cortex 2) hippocampus 3) medial temporal gyrus 4) posterior cingulate 5) superior frontal gyrus and 6) primary visual cortex. We will collect layer III pyramidal cells from the white matter in each region, isolate total RNA from LCMed cell lysates, and perform double round amplification of each sample for array analysis.
+
+
+
+Bad arrays excluded: Four samples, highlighted in the table below, are bad arrays. For quality control, they should be excluded.
+
+
+
+
+
+
+
+
+ | Index |
+ GEO Series |
+ Organ Region |
+ Tissue |
+ Case ID |
+ Age |
+ Sex |
+
+
+ | 1 |
+ GSM119615 |
+ Entorhinal Cortex |
+ Normal |
+ E119615M63N |
+ 63 |
+ M |
+
+
+ | 2 |
+ GSM119616 |
+ Entorhinal Cortex |
+ Normal |
+ E119616M85N |
+ 85 |
+ M |
+
+
+ | 3 |
+ GSM119617 |
+ Entorhinal Cortex |
+ Normal |
+ E119617M80N |
+ 80 |
+ M |
+
+
+ | 4 |
+ GSM119618 |
+ Entorhinal Cortex |
+ Normal |
+ E119618M->F80N |
+ 80 |
+ M |
+
+
+ | 5 |
+ GSM119619 |
+ Entorhinal Cortex |
+ Normal |
+ E119619F->M102N |
+ 102 |
+ F |
+
+
+ | 6 |
+ GSM119620 |
+ Entorhinal Cortex |
+ Normal |
+ E119620M79N |
+ 79 |
+ M |
+
+
+ | 7 |
+ GSM119621 |
+ Entorhinal Cortex |
+ Normal |
+ E119621M76N |
+ 76 |
+ M |
+
+
+ | 8 |
+ GSM119622 |
+ Entorhinal Cortex |
+ Normal |
+ E119622M83N |
+ 83 |
+ M |
+
+
+ | 9 |
+ GSM119623 |
+ Entorhinal Cortex |
+ Normal |
+ E119623M79N |
+ 79 |
+ M |
+
+
+ | 10 |
+ GSM119624 |
+ Entorhinal Cortex |
+ Normal |
+ E119624F88N |
+ 88 |
+ F |
+
+
+ | 11 |
+ GSM119625 |
+ Entorhinal Cortex |
+ Normal |
+ E119625F82N |
+ 82 |
+ F |
+
+
+ | 12 |
+ GSM119626 |
+ Entorhinal Cortex |
+ Normal |
+ E119626M69N |
+ 69 |
+ M |
+
+
+ | 13 |
+ GSM119627 |
+ Entorhinal Cortex |
+ Normal |
+ E119627M78N |
+ 78 |
+ M |
+
+
+ | 14 |
+ GSM238763 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238763F82A |
+ 82 |
+ F |
+
+
+ | 15 |
+ GSM238790 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238790F86A |
+ 86 |
+ F |
+
+
+ | 16 |
+ GSM238791 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238791F93A |
+ 93 |
+ F |
+
+
+ | 17 |
+ GSM238792 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238792M84A |
+ 84 |
+ M |
+
+
+ | 18 |
+ GSM238793 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238793F79A |
+ 79 |
+ F |
+
+
+ | 19 |
+ GSM238794 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238794F78A |
+ 78 |
+ F |
+
+
+ | 20 |
+ GSM238795 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238795F91A |
+ 91 |
+ F |
+
+
+ | 21 |
+ GSM238796 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238796M86A |
+ 86 |
+ M |
+
+
+ | 22 |
+ GSM238797 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238797NA0A |
+ N/A |
+ N/A |
+
+
+ | 23 |
+ GSM238798 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238798M80A |
+ 80 |
+ M |
+
+
+ | 24 |
+ GSM119628 |
+ Hippocampus |
+ Normal |
+ H119628M85N |
+ 85 |
+ M |
+
+
+ | 25 |
+ GSM119629 |
+ Hippocampus |
+ Normal |
+ H119629M80N |
+ 80 |
+ M |
+
+
+ | 26 |
+ GSM119630 |
+ Hippocampus |
+ Normal |
+ H119630M80N |
+ 80 |
+ M |
+
+
+ | 27 |
+ GSM119631 |
+ Hippocampus |
+ Normal |
+ H119631F102N |
+ 102 |
+ F |
+
+
+ | 28 |
+ GSM119632 |
+ Hippocampus |
+ Normal |
+ H119632M63N |
+ 63 |
+ M |
+
+
+ | 29 |
+ GSM119633 |
+ Hippocampus |
+ Normal |
+ H119633M79N |
+ 79 |
+ M |
+
+
+ | 30 |
+ GSM119634 |
+ Hippocampus |
+ Normal |
+ H119634M76N |
+ 76 |
+ M |
+
+
+ | 31 |
+ GSM119635 |
+ Hippocampus |
+ Normal |
+ H119635M83N |
+ 83 |
+ M |
+
+
+ | 32 |
+ GSM119636 |
+ Hippocampus |
+ Normal |
+ H119636M79N |
+ 79 |
+ M |
+
+
+ | 33 |
+ GSM119637 |
+ Hippocampus |
+ Normal |
+ H119637F88N |
+ 88 |
+ F |
+
+
+ | 34 |
+ GSM119638 |
+ Hippocampus |
+ Normal |
+ H119638F73N |
+ 73 |
+ F |
+
+
+ | 35 |
+ GSM119639 |
+ Hippocampus |
+ Normal |
+ H119639M69N |
+ 69 |
+ M |
+
+
+ | 36 |
+ GSM119640 |
+ Hippocampus |
+ Normal |
+ H119640M78N |
+ 78 |
+ M |
+
+
+ | 37 |
+ GSM238799 |
+ Hippocampus |
+ Alzheimer's |
+ H238799F73A |
+ 73 |
+ F |
+
+
+ | 38 |
+ GSM238800 |
+ Hippocampus |
+ Alzheimer's |
+ H238800M81A |
+ 81 |
+ M |
+
+
+ | 39 |
+ GSM238801 |
+ Hippocampus |
+ Alzheimer's |
+ H238801M78A |
+ 78 |
+ M |
+
+
+ | 40 |
+ GSM238802 |
+ Hippocampus |
+ Alzheimer's |
+ H238802M75A |
+ 75 |
+ M |
+
+
+ | 41 |
+ GSM238803 |
+ Hippocampus |
+ Alzheimer's |
+ H238803F70A |
+ 70 |
+ F |
+
+
+ | 42 |
+ GSM238804 |
+ Hippocampus |
+ Alzheimer's |
+ H238804F85A |
+ 85 |
+ F |
+
+
+ | 43 |
+ GSM238805 |
+ Hippocampus |
+ Alzheimer's |
+ H238805F77A |
+ 77 |
+ F |
+
+
+ | 44 |
+ GSM238806 |
+ Hippocampus |
+ Alzheimer's |
+ H238806M79A |
+ 79 |
+ M |
+
+
+ | 45 |
+ GSM238807 |
+ Hippocampus |
+ Alzheimer's |
+ H238807M88A |
+ 88 |
+ M |
+
+
+ | 46 |
+ GSM238808 |
+ Hippocampus |
+ Alzheimer's |
+ H238808M72A |
+ 72 |
+ M |
+
+
+ | 47 |
+ GSM119641 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119641M85N |
+ 85 |
+ M |
+
+
+ | 48 |
+ GSM119642 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119642M80N |
+ 80 |
+ M |
+
+
+ | 49 |
+ GSM119643 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119643F102N |
+ 102 |
+ F |
+
+
+ | 50 |
+ GSM119644 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119644M63N |
+ 63 |
+ M |
+
+
+ | 51 |
+ GSM119645 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119645M79N |
+ 79 |
+ M |
+
+
+ | 52 |
+ GSM119646 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119646M83N |
+ 83 |
+ M |
+
+
+ | 53 |
+ GSM119647 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119647M79N |
+ 79 |
+ M |
+
+
+ | 54 |
+ GSM119648 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119648F88N |
+ 88 |
+ F |
+
+
+ | 55 |
+ GSM119649 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119649F82N |
+ 82 |
+ F |
+
+
+ | 56 |
+ GSM119650 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119650F73N |
+ 73 |
+ F |
+
+
+ | 57 |
+ GSM119651 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119651M69N |
+ 69 |
+ M |
+
+
+ | 58 |
+ GSM119652 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119652M->F78N |
+ 78 |
+ M |
+
+
+ | 59 |
+ GSM238809 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238809M81A |
+ 81 |
+ M |
+
+
+ | 60 |
+ GSM238810 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238810M72A |
+ 72 |
+ M |
+
+
+ | 61 |
+ GSM238811 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238811M75A |
+ 75 |
+ M |
+
+
+ | 62 |
+ GSM238812 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238812M78A |
+ 78 |
+ M |
+
+
+ | 63 |
+ GSM238813 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238813M75A |
+ 75 |
+ M |
+
+
+ | 64 |
+ GSM238815 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238815F95A |
+ 95 |
+ F |
+
+
+ | 65 |
+ GSM238816 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238816F81A |
+ 81 |
+ F |
+
+
+ | 66 |
+ GSM238817 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238817F85A |
+ 85 |
+ F |
+
+
+ | 67 |
+ GSM238818 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238818M79A |
+ 79 |
+ M |
+
+
+ | 68 |
+ GSM238819 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238819F82A |
+ 82 |
+ F |
+
+
+ | 69 |
+ GSM238820 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238820M88A |
+ 88 |
+ M |
+
+
+ | 70 |
+ GSM238821 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238821M72A |
+ 72 |
+ M |
+
+
+ | 71 |
+ GSM238822 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238822F73A |
+ 73 |
+ F |
+
+
+ | 72 |
+ GSM238823 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238823M87A |
+ 87 |
+ M |
+
+
+ | 73 |
+ GSM238824 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238824M68A |
+ 68 |
+ M |
+
+
+ | 74 |
+ GSM238825 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238825F80A |
+ 80 |
+ F |
+
+
+ | 75 |
+ GSM119653 |
+ Posterior Cingulate |
+ Normal |
+ PC119653M85N |
+ 85 |
+ M |
+
+
+ | 76 |
+ GSM119654 |
+ Posterior Cingulate |
+ Normal |
+ PC119654M80N |
+ 80 |
+ M |
+
+
+ | 77 |
+ GSM119655 |
+ Posterior Cingulate |
+ Normal |
+ PC119655F102N |
+ 102 |
+ F |
+
+
+ | 78 |
+ GSM119656 |
+ Posterior Cingulate |
+ Normal |
+ PC119656M63N |
+ 63 |
+ M |
+
+
+ | 79 |
+ GSM119657 |
+ Posterior Cingulate |
+ Normal |
+ PC119657M79N |
+ 79 |
+ M |
+
+
+ | 80 |
+ GSM119658 |
+ Posterior Cingulate |
+ Normal |
+ PC119658M->F76N |
+ 76 |
+ M |
+
+
+ | 81 |
+ GSM119659 |
+ Posterior Cingulate |
+ Normal |
+ PC119659M83N |
+ 83 |
+ M |
+
+
+ | 82 |
+ GSM119660 |
+ Posterior Cingulate |
+ Normal |
+ PC119660M79N |
+ 79 |
+ M |
+
+
+ | 83 |
+ GSM119661 |
+ Posterior Cingulate |
+ Normal |
+ PC119661F88N |
+ 88 |
+ F |
+
+
+ | 84 |
+ GSM119662 |
+ Posterior Cingulate |
+ Normal |
+ PC119662F82N |
+ 82 |
+ F |
+
+
+ | 85 |
+ GSM119663 |
+ Posterior Cingulate |
+ Normal |
+ PC119663F73N |
+ 73 |
+ F |
+
+
+ | 86 |
+ GSM119664 |
+ Posterior Cingulate |
+ Normal |
+ PC119664M69N |
+ 69 |
+ M |
+
+
+ | 87 |
+ GSM119665 |
+ Posterior Cingulate |
+ Normal |
+ PC119665M78N |
+ 78 |
+ M |
+
+
+ | 88 |
+ GSM238826 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238826F73A |
+ 73 |
+ F |
+
+
+ | 89 |
+ GSM238827 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238827M81A |
+ 81 |
+ M |
+
+
+ | 90 |
+ GSM238834 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238834M78A |
+ 78 |
+ M |
+
+
+ | 91 |
+ GSM238835 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238835M75A |
+ 75 |
+ M |
+
+
+ | 92 |
+ GSM238837 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238837M68A |
+ 68 |
+ M |
+
+
+ | 93 |
+ GSM238838 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238838F70A |
+ 70 |
+ F |
+
+
+ | 94 |
+ GSM238839 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238839F85A |
+ 85 |
+ F |
+
+
+ | 95 |
+ GSM238840 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238840M79A |
+ 79 |
+ M |
+
+
+ | 96 |
+ GSM238841 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238841M88A |
+ 88 |
+ M |
+
+
+ | 97 |
+ GSM119666 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119666M79N |
+ 79 |
+ M |
+
+
+ | 98 |
+ GSM119667 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119667F->M88N |
+ 88 |
+ F |
+
+
+ | 99 |
+ GSM119668 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119668F->M82N |
+ 82 |
+ F |
+
+
+ | 100 |
+ GSM119669 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119669F->M73N |
+ 73 |
+ F |
+
+
+ | 101 |
+ GSM119670 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119670F->M102N |
+ 102 |
+ F |
+
+
+ | 102 |
+ GSM119671 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119671M63N |
+ 63 |
+ M |
+
+
+ | 103 |
+ GSM119672 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119672M->F79N |
+ 79 |
+ M |
+
+
+ | 104 |
+ GSM119673 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119673M->F76N |
+ 76 |
+ M |
+
+
+ | 105 |
+ GSM119674 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119674M->F83N |
+ 83 |
+ M |
+
+
+ | 106 |
+ GSM119675 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119675M69N |
+ 69 |
+ M |
+
+
+ | 107 |
+ GSM119676 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119676M78N |
+ 78 |
+ M |
+
+
+ | 108 |
+ GSM238842 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238842F73A |
+ 73 |
+ F |
+
+
+ | 109 |
+ GSM238843 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238843M81A |
+ 81 |
+ M |
+
+
+ | 110 |
+ GSM238844 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238844M72A |
+ 72 |
+ M |
+
+
+ | 111 |
+ GSM238845 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238845M75A |
+ 75 |
+ M |
+
+
+ | 112 |
+ GSM238846 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238846M78A |
+ 78 |
+ M |
+
+
+ | 113 |
+ GSM238847 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238847M75A |
+ 75 |
+ M |
+
+
+ | 114 |
+ GSM238848 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238848M87A |
+ 87 |
+ M |
+
+
+ | 115 |
+ GSM238851 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238851F95A |
+ 95 |
+ F |
+
+
+ | 116 |
+ GSM238854 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238854M68A |
+ 68 |
+ M |
+
+
+ | 117 |
+ GSM238855 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238855F95A |
+ 95 |
+ F |
+
+
+ | 118 |
+ GSM238856 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238856F70A |
+ 70 |
+ F |
+
+
+ | 119 |
+ GSM238857 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238857F85A |
+ 85 |
+ F |
+
+
+ | 120 |
+ GSM238858 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238858F83A |
+ 83 |
+ F |
+
+
+ | 121 |
+ GSM238860 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238860F77A |
+ 77 |
+ F |
+
+
+ | 122 |
+ GSM238861 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238861F83A |
+ 83 |
+ F |
+
+
+ | 123 |
+ GSM238862 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238862M68A |
+ 68 |
+ M |
+
+
+ | 124 |
+ GSM238863 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238863M79A |
+ 79 |
+ M |
+
+
+ | 125 |
+ GSM238864 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238864F82A |
+ 82 |
+ F |
+
+
+ | 126 |
+ GSM238865 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238865M88A |
+ 88 |
+ M |
+
+
+ | 127 |
+ GSM238867 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238867F80A |
+ 80 |
+ F |
+
+
+ | 128 |
+ GSM238868 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238868M74A |
+ 74 |
+ M |
+
+
+ | 129 |
+ GSM238870 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238870M72A |
+ 72 |
+ M |
+
+
+ | 130 |
+ GSM238871 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238871M80A |
+ 80 |
+ M |
+
+
+ | 131 |
+ GSM119677 |
+ Primary Visual Cortex |
+ Normal |
+ V119677M85N |
+ 85 |
+ M |
+
+
+ | 132 |
+ GSM119678 |
+ Primary Visual Cortex |
+ Normal |
+ V119678M80N |
+ 80 |
+ M |
+
+
+ | 133 |
+ GSM119679 |
+ Primary Visual Cortex |
+ Normal |
+ V119679M63N |
+ 63 |
+ M |
+
+
+ | 134 |
+ GSM119680 |
+ Primary Visual Cortex |
+ Normal |
+ V119680M79N |
+ 79 |
+ M |
+
+
+ | 135 |
+ GSM119681 |
+ Primary Visual Cortex |
+ Normal |
+ V119681M76N |
+ 76 |
+ M |
+
+
+ | 136 |
+ GSM119682 |
+ Primary Visual Cortex |
+ Normal |
+ V119682M83N |
+ 83 |
+ M |
+
+
+ | 137 |
+ GSM119683 |
+ Primary Visual Cortex |
+ Normal |
+ V119683M79N |
+ 79 |
+ M |
+
+
+ | 138 |
+ GSM119684 |
+ Primary Visual Cortex |
+ Normal |
+ V119684F88N |
+ 88 |
+ F |
+
+
+ | 139 |
+ GSM119685 |
+ Primary Visual Cortex |
+ Normal |
+ V119685F82N |
+ 82 |
+ F |
+
+
+ | 140 |
+ GSM119686 |
+ Primary Visual Cortex |
+ Normal |
+ V119686F73N |
+ 73 |
+ F |
+
+
+ | 141 |
+ GSM119687 |
+ Primary Visual Cortex |
+ Normal |
+ V119687M69N |
+ 69 |
+ M |
+
+
+ | 142 |
+ GSM119688 |
+ Primary Visual Cortex |
+ Normal |
+ V119688M78N |
+ 78 |
+ M |
+
+
+ | 143 |
+ GSM238872 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238872F73A |
+ 73 |
+ F |
+
+
+ | 144 |
+ GSM238873 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238873M81A |
+ 81 |
+ M |
+
+
+ | 145 |
+ GSM238874 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238874M75A |
+ 75 |
+ M |
+
+
+ | 146 |
+ GSM238875 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238875M78A |
+ 78 |
+ M |
+
+
+ | 147 |
+ GSM238877 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238877M75A |
+ 75 |
+ M |
+
+
+ | 148 |
+ GSM238941 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238941M87A |
+ 87 |
+ M |
+
+
+ | 149 |
+ GSM238942 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238942F95A |
+ 95 |
+ F |
+
+
+ | 150 |
+ GSM238943 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238943M68A |
+ 68 |
+ M |
+
+
+ | 151 |
+ GSM238944 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238944F70A |
+ 70 |
+ F |
+
+
+ | 152 |
+ GSM238945 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238945F81A |
+ 81 |
+ F |
+
+
+ | 153 |
+ GSM238946 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238946F85A |
+ 85 |
+ F |
+
+
+ | 154 |
+ GSM238947 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238947M68A |
+ 68 |
+ M |
+
+
+ | 155 |
+ GSM238948 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238948M79A |
+ 79 |
+ M |
+
+
+ | 156 |
+ GSM238949 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238949F82A |
+ 82 |
+ F |
+
+
+ | 157 |
+ GSM238951 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238951M88A |
+ 88 |
+ M |
+
+
+ | 158 |
+ GSM238952 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238952M74A |
+ 74 |
+ M |
+
+
+ | 159 |
+ GSM238953 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238953M72A |
+ 72 |
+ M |
+
+
+ | 160 |
+ GSM238955 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238955M->F68A |
+ 68 |
+ M |
+
+
+ | 161 |
+ GSM238963 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238963F80A |
+ 80 |
+ F |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Gse5281_rma0709/acknowledgment.rtf b/general/datasets/Gse5281_rma0709/acknowledgment.rtf
new file mode 100644
index 0000000..8ce4f5c
--- /dev/null
+++ b/general/datasets/Gse5281_rma0709/acknowledgment.rtf
@@ -0,0 +1 @@
+Please cite: Liang WS, Reiman EM, Valla J, Dunckley T, Beach TG, Grover A, Niedzielko TL, Schneider LE, Mastroeni D, Caselli R, Kukull W, Morris JC, Hulette CM, Schmechel D, Rogers J, Stephan DA (2008) Alzheimer's disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons. Proc Natl Acad Sci USA 105:4441-4446.
diff --git a/general/datasets/Gse5281_rma0709/citation.rtf b/general/datasets/Gse5281_rma0709/citation.rtf
new file mode 100644
index 0000000..6c255a4
--- /dev/null
+++ b/general/datasets/Gse5281_rma0709/citation.rtf
@@ -0,0 +1,2 @@
+Liang WS, Dunckley T, Beach TG, Grover A et al. Gene expression profiles in anatomically and functionally distinct regions of the normal aged human brain. Physiol Genomics 2007 Feb 12;28(3):311-22. PMID: 17077275
+Liang WS, Reiman EM, Valla J, Dunckley T et al. Alzheimer's disease is associated with reduced expression of energy metabolism genes in posterior cingulate neurons. Proc Natl Acad Sci U S A 2008 Mar 18;105(11):4441-6. PMID: 18332434
diff --git a/general/datasets/Gse5281_rma0709/contributors.rtf b/general/datasets/Gse5281_rma0709/contributors.rtf
new file mode 100644
index 0000000..754b3a7
--- /dev/null
+++ b/general/datasets/Gse5281_rma0709/contributors.rtf
@@ -0,0 +1 @@
+Stephan DA, Liang WS
diff --git a/general/datasets/Gse5281_rma0709/experiment-design.rtf b/general/datasets/Gse5281_rma0709/experiment-design.rtf
new file mode 100644
index 0000000..bc54b5c
--- /dev/null
+++ b/general/datasets/Gse5281_rma0709/experiment-design.rtf
@@ -0,0 +1,13 @@
+Human brain expression data in patients with Alzheimer's disease and age-matched elderly control subjects. This cortical expression data set is taken from GEO GSE5281 (Liang et al. 2006, Liang et al. 2008). Samples were laser-captured from cortical regions of 16 normal elderly humans (10 males and 4 females) and from 33 AD cases (15 males and 18 females). Mean age of cases and controls was 80 years. All samples were run on the Affymetrix U133 Plus 2.0 array. We renormalized the RMA data to an average expression of 8 units on a log2 scale. Two versions of the data have been entered in GeneNetwork: one consisting of 157 of 161 arrays (full set minus 4 arrays we consider of poor quality); the second consisting of what we regard as the best 102 arrays (those with mean correlations of better than 0.88 with all other arrays). Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex area 17 layer III. GeneNetwork does not yet allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example, expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
+
+NOTE: We detected a minimum of 7.6% case assignment error rate (12 of 158 arrays) in this data set. Twelve cases are assigned to the wrong sex (see XIST probe set 224588_at, the figure below, and table 1). This raises the possibility that some cases are also misassigned by cortical brain region and disease status.
+
+
+
+
+
+Legend: Expression of the sex-specific gene XIST reveals about 10 sex assignment errors in this data set.
+
+Samples were laser-captured from cortical layer 3 (except the hippocampus) and run on the Affymetrix U133 Plus 2.0 array. We renormalized the data to an average expression of 8 units on a log2 scale. Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex layer III. A total of 16 normal subjects were used (10 M and 4 female). The AD samples. GeneNetwork does not allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
+
+Information about the genes that are preferentially expressed during the course of Alzheimer's disease (AD) could improve our understanding of the molecular mechanisms involved in the pathogenesis of this common cause of cognitive impairment in older persons, provide new opportunities in the diagnosis, early detection, and tracking of this disorder, and provide novel targets for the discovery of interventions to treat and prevent this disorder. Information about the genes that are preferentially expressed in relationship to normal neurological aging could provide new information about the molecular mechanisms that are involved in normal age-related cognitive decline and a host of age-related neurological disorders, and they could provide novel targets for the discovery of interventions to mitigate some of these deleterious effects.
diff --git a/general/datasets/Gse5281_rma0709/experiment-type.rtf b/general/datasets/Gse5281_rma0709/experiment-type.rtf
new file mode 100644
index 0000000..5797da1
--- /dev/null
+++ b/general/datasets/Gse5281_rma0709/experiment-type.rtf
@@ -0,0 +1,9 @@
+
+Human brain expression data in patients with Alzheimer's disease and age-matched elderly control subjects. This cortical expression data set is taken from GEO GSE5281 (Liang et al. 2006, Liang et al. 2008). Samples were laser-captured from cortical regions of 16 normal elderly humans (10 males and 4 females) and from 33 AD cases (15 males and 18 females). Mean age of cases and controls was 80 years. All samples were run on the Affymetrix U133 Plus 2.0 array. We renormalized the RMA data to an average expression of 8 units on a log2 scale. Two versions of the data have been entered in GeneNetwork: one consisting of 157 of 161 arrays (full set minus 4 arrays we consider of poor quality); the second consisting of what we regard as the best 102 arrays (those with mean correlations of better than 0.88 with all other arrays). Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex area 17 layer III. GeneNetwork does not yet allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example, expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
+
+
NOTE: We detected a minimum of 7.6% case assignment error rate (12 of 158 arrays) in this data set. Twelve cases are assigned to the wrong sex (see XIST probe set 224588_at, the figure below, and table 1). This raises the possibility that some cases are also misassigned by cortical brain region and disease status.
+
+
+Legend: Expression of the sex-specific gene XIST reveals about 10 sex assignment errors in this data set.
+
+Samples were laser-captured from cortical layer 3 (except the hippocampus) and run on the Affymetrix U133 Plus 2.0 array. We renormalized the data to an average expression of 8 units on a log2 scale. Case IDs have the following code structure: Brain Region, GEO ID, Sex, Age, Disease Status. E119615M63N is a sample of the entorhinal cortex of case GSM119615, a male 63 year old normal case. The tissue codes are E = enorhinal cortex layer II, H = hippocampus CA1 pyramidal layer, MT = medial temporal cortex layer III, PC = porterior cingulate cortex layer III, SP = supeior frontal cortex layer III, V = primary visual cortex layer III. A total of 16 normal subjects were used (10 M and 4 female). The AD samples. GeneNetwork does not allow sophisticated display of the data, but you can perform correlation analyses of any of the 56,000 probe sets. For example expression of the APP transcript is higher in the AD cases and correlates well with many other AD related genes.
\ No newline at end of file
diff --git a/general/datasets/Gse5281_rma0709/platform.rtf b/general/datasets/Gse5281_rma0709/platform.rtf
new file mode 100644
index 0000000..6c2af02
--- /dev/null
+++ b/general/datasets/Gse5281_rma0709/platform.rtf
@@ -0,0 +1,3 @@
+Affymetrix submissions are typically submitted to GEO using the GEOarchive method described at http://www.ncbi.nlm.nih.gov/projects/geo/info/geo_affy.html Complete coverage of the Human Genome U133 Set plus 6,500 additional genes for analysis of over 47,000 transcripts All probe sets represented on the GeneChip Human Genome U133 Set are identically replicated on the GeneChip Human Genome U133 Plus 2.0 Array. The sequences from which these probe sets were derived were selected from GenBank®, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 133, April 20, 2001) and then refined by analysis and comparison with a number of other publicly available databases, including the Washington University EST trace repository and the University of California, Santa Cruz Golden-Path human genome database (April 2001 release).
+
+In addition, there are 9,921 new probe sets representing approximately 6,500 new genes. These gene sequences were selected from GenBank, dbEST, and RefSeq. Sequence clusters were created from the UniGene database (Build 159, January 25, 2003) and refined by analysis and comparison with a number of other publicly available databases, including the Washington University EST trace repository and the NCBI human genome assembly (Build 31).
diff --git a/general/datasets/Gse5281_rma0709/summary.rtf b/general/datasets/Gse5281_rma0709/summary.rtf
new file mode 100644
index 0000000..5db3978
--- /dev/null
+++ b/general/datasets/Gse5281_rma0709/summary.rtf
@@ -0,0 +1,1484 @@
+(Taken verbatim from the GEO record)
+
+Information about the genes that are preferentially expressed during the course of Alzheimer’s disease (AD) could improve our understanding of the molecular mechanisms involved in the pathogenesis of this common cause of cognitive impairment in older persons, provide new opportunities in the diagnosis, early detection, and tracking of this disorder, and provide novel targets for the discovery of interventions to treat and prevent this disorder. Information about the genes that are preferentially expressed in relationship to normal neurological aging could provide new information about the molecular mechanisms that are involved in normal age-related cognitive decline and a host of age-related neurological disorders, and they could provide novel targets for the discovery of interventions to mitigate some of these deleterious effects.
+
+Aim 1. Collect brain samples from three Alzheimer’s Disease Centers (ADCs) for subsequent gene expression profiling. Individuals will be stratified with respect to diagnostic groups (using both clinical and neuropathological criteria), age groups, and APOE genotype. 150 individual brains will be sampled from the Arizona ADC, the Duke University ADC, and the Washington University ADC. Miniscule sample sizes (200 um of sectioned tissue) from six brain regions that are histopathologically or metabolically relevant to AD and aging will be collected, ensuring that this proposal does not deplete the national resource. Frozen and fixed samples will be sent to Phoenix, sectioned in a standardized fashion, and then returned. Aim 2. Tissue heterogeneity will be eliminated prior to expression profiling by performing laser capture microscopy on all brain regions. Aim 3. Expression profile LCM-captured cells on the Affymetrix U133 Plus 2.0 array (~55,000 transcripts), and quickly provide these data to the community at large. Aim 4. Identify pathogenic cascades related to each of the clinico-pathologic correlates using unsupervised and supervised analyses coupled with a hypothesis-driven approach. Aim 5. Validation of the expression correlates at the protein and functional levels.
+
+Scientific progress in the last few years has improved our understanding of AD and raised the hope of identifying treatments to halt the progression and prevent the onset of this disorder. For instance, researchers have begun to characterize the cascade of molecular events which lead to the major histopathological features of the disorder: neuritic plaques, which contain extra-cellular deposits of amyloid beta-peptides (Abeta); neurofibrillary tangles, which contain the hyperphosphorylated form of the intracellular, microtubule-associated protein, tau; and a loss of neurons and synapses. These molecular events provide targets for the development of promising new treatments. For example, A-beta has been postulated to trigger a cascade of events that are involved in the pathogenesis of AD. This proposal hopes to provide new information about the genes that are preferentially expressed in the development of AD histopathology, including the over-expression of APP, amyloid-induced neurotoxicity, and hyperphosphorylation of tau, as well as bring clarity to the metabolic abnormalities that seem to play a role in dementia and AD development and pathology.
+
+We will perform LCM on 6 brain regions with about 14 biological replicates per brain region. The brain regions are as follows: 1) entorhinal cortex 2) hippocampus 3) medial temporal gyrus 4) posterior cingulate 5) superior frontal gyrus and 6) primary visual cortex. We will collect layer III pyramidal cells from the white matter in each region, isolate total RNA from LCMed cell lysates, and perform double round amplification of each sample for array analysis.
+
+
+
+Bad arrays excluded: Four samples, highlighted in the table below, are bad arrays. For quality control, they should be excluded.
+
+
+
+
+
+
+
+
+ | Index |
+ GEO Series |
+ Organ Region |
+ Tissue |
+ Case ID |
+ Age |
+ Sex |
+
+
+ | 1 |
+ GSM119615 |
+ Entorhinal Cortex |
+ Normal |
+ E119615M63N |
+ 63 |
+ M |
+
+
+ | 2 |
+ GSM119616 |
+ Entorhinal Cortex |
+ Normal |
+ E119616M85N |
+ 85 |
+ M |
+
+
+ | 3 |
+ GSM119617 |
+ Entorhinal Cortex |
+ Normal |
+ E119617M80N |
+ 80 |
+ M |
+
+
+ | 4 |
+ GSM119618 |
+ Entorhinal Cortex |
+ Normal |
+ E119618M->F80N |
+ 80 |
+ M |
+
+
+ | 5 |
+ GSM119619 |
+ Entorhinal Cortex |
+ Normal |
+ E119619F->M102N |
+ 102 |
+ F |
+
+
+ | 6 |
+ GSM119620 |
+ Entorhinal Cortex |
+ Normal |
+ E119620M79N |
+ 79 |
+ M |
+
+
+ | 7 |
+ GSM119621 |
+ Entorhinal Cortex |
+ Normal |
+ E119621M76N |
+ 76 |
+ M |
+
+
+ | 8 |
+ GSM119622 |
+ Entorhinal Cortex |
+ Normal |
+ E119622M83N |
+ 83 |
+ M |
+
+
+ | 9 |
+ GSM119623 |
+ Entorhinal Cortex |
+ Normal |
+ E119623M79N |
+ 79 |
+ M |
+
+
+ | 10 |
+ GSM119624 |
+ Entorhinal Cortex |
+ Normal |
+ E119624F88N |
+ 88 |
+ F |
+
+
+ | 11 |
+ GSM119625 |
+ Entorhinal Cortex |
+ Normal |
+ E119625F82N |
+ 82 |
+ F |
+
+
+ | 12 |
+ GSM119626 |
+ Entorhinal Cortex |
+ Normal |
+ E119626M69N |
+ 69 |
+ M |
+
+
+ | 13 |
+ GSM119627 |
+ Entorhinal Cortex |
+ Normal |
+ E119627M78N |
+ 78 |
+ M |
+
+
+ | 14 |
+ GSM238763 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238763F82A |
+ 82 |
+ F |
+
+
+ | 15 |
+ GSM238790 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238790F86A |
+ 86 |
+ F |
+
+
+ | 16 |
+ GSM238791 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238791F93A |
+ 93 |
+ F |
+
+
+ | 17 |
+ GSM238792 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238792M84A |
+ 84 |
+ M |
+
+
+ | 18 |
+ GSM238793 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238793F79A |
+ 79 |
+ F |
+
+
+ | 19 |
+ GSM238794 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238794F78A |
+ 78 |
+ F |
+
+
+ | 20 |
+ GSM238795 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238795F91A |
+ 91 |
+ F |
+
+
+ | 21 |
+ GSM238796 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238796M86A |
+ 86 |
+ M |
+
+
+ | 22 |
+ GSM238797 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238797NA0A |
+ N/A |
+ N/A |
+
+
+ | 23 |
+ GSM238798 |
+ Entorhinal Cortex |
+ Alzheimer's |
+ E238798M80A |
+ 80 |
+ M |
+
+
+ | 24 |
+ GSM119628 |
+ Hippocampus |
+ Normal |
+ H119628M85N |
+ 85 |
+ M |
+
+
+ | 25 |
+ GSM119629 |
+ Hippocampus |
+ Normal |
+ H119629M80N |
+ 80 |
+ M |
+
+
+ | 26 |
+ GSM119630 |
+ Hippocampus |
+ Normal |
+ H119630M80N |
+ 80 |
+ M |
+
+
+ | 27 |
+ GSM119631 |
+ Hippocampus |
+ Normal |
+ H119631F102N |
+ 102 |
+ F |
+
+
+ | 28 |
+ GSM119632 |
+ Hippocampus |
+ Normal |
+ H119632M63N |
+ 63 |
+ M |
+
+
+ | 29 |
+ GSM119633 |
+ Hippocampus |
+ Normal |
+ H119633M79N |
+ 79 |
+ M |
+
+
+ | 30 |
+ GSM119634 |
+ Hippocampus |
+ Normal |
+ H119634M76N |
+ 76 |
+ M |
+
+
+ | 31 |
+ GSM119635 |
+ Hippocampus |
+ Normal |
+ H119635M83N |
+ 83 |
+ M |
+
+
+ | 32 |
+ GSM119636 |
+ Hippocampus |
+ Normal |
+ H119636M79N |
+ 79 |
+ M |
+
+
+ | 33 |
+ GSM119637 |
+ Hippocampus |
+ Normal |
+ H119637F88N |
+ 88 |
+ F |
+
+
+ | 34 |
+ GSM119638 |
+ Hippocampus |
+ Normal |
+ H119638F73N |
+ 73 |
+ F |
+
+
+ | 35 |
+ GSM119639 |
+ Hippocampus |
+ Normal |
+ H119639M69N |
+ 69 |
+ M |
+
+
+ | 36 |
+ GSM119640 |
+ Hippocampus |
+ Normal |
+ H119640M78N |
+ 78 |
+ M |
+
+
+ | 37 |
+ GSM238799 |
+ Hippocampus |
+ Alzheimer's |
+ H238799F73A |
+ 73 |
+ F |
+
+
+ | 38 |
+ GSM238800 |
+ Hippocampus |
+ Alzheimer's |
+ H238800M81A |
+ 81 |
+ M |
+
+
+ | 39 |
+ GSM238801 |
+ Hippocampus |
+ Alzheimer's |
+ H238801M78A |
+ 78 |
+ M |
+
+
+ | 40 |
+ GSM238802 |
+ Hippocampus |
+ Alzheimer's |
+ H238802M75A |
+ 75 |
+ M |
+
+
+ | 41 |
+ GSM238803 |
+ Hippocampus |
+ Alzheimer's |
+ H238803F70A |
+ 70 |
+ F |
+
+
+ | 42 |
+ GSM238804 |
+ Hippocampus |
+ Alzheimer's |
+ H238804F85A |
+ 85 |
+ F |
+
+
+ | 43 |
+ GSM238805 |
+ Hippocampus |
+ Alzheimer's |
+ H238805F77A |
+ 77 |
+ F |
+
+
+ | 44 |
+ GSM238806 |
+ Hippocampus |
+ Alzheimer's |
+ H238806M79A |
+ 79 |
+ M |
+
+
+ | 45 |
+ GSM238807 |
+ Hippocampus |
+ Alzheimer's |
+ H238807M88A |
+ 88 |
+ M |
+
+
+ | 46 |
+ GSM238808 |
+ Hippocampus |
+ Alzheimer's |
+ H238808M72A |
+ 72 |
+ M |
+
+
+ | 47 |
+ GSM119641 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119641M85N |
+ 85 |
+ M |
+
+
+ | 48 |
+ GSM119642 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119642M80N |
+ 80 |
+ M |
+
+
+ | 49 |
+ GSM119643 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119643F102N |
+ 102 |
+ F |
+
+
+ | 50 |
+ GSM119644 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119644M63N |
+ 63 |
+ M |
+
+
+ | 51 |
+ GSM119645 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119645M79N |
+ 79 |
+ M |
+
+
+ | 52 |
+ GSM119646 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119646M83N |
+ 83 |
+ M |
+
+
+ | 53 |
+ GSM119647 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119647M79N |
+ 79 |
+ M |
+
+
+ | 54 |
+ GSM119648 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119648F88N |
+ 88 |
+ F |
+
+
+ | 55 |
+ GSM119649 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119649F82N |
+ 82 |
+ F |
+
+
+ | 56 |
+ GSM119650 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119650F73N |
+ 73 |
+ F |
+
+
+ | 57 |
+ GSM119651 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119651M69N |
+ 69 |
+ M |
+
+
+ | 58 |
+ GSM119652 |
+ Medial Temporal Gyrus |
+ Normal |
+ MT119652M->F78N |
+ 78 |
+ M |
+
+
+ | 59 |
+ GSM238809 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238809M81A |
+ 81 |
+ M |
+
+
+ | 60 |
+ GSM238810 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238810M72A |
+ 72 |
+ M |
+
+
+ | 61 |
+ GSM238811 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238811M75A |
+ 75 |
+ M |
+
+
+ | 62 |
+ GSM238812 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238812M78A |
+ 78 |
+ M |
+
+
+ | 63 |
+ GSM238813 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238813M75A |
+ 75 |
+ M |
+
+
+ | 64 |
+ GSM238815 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238815F95A |
+ 95 |
+ F |
+
+
+ | 65 |
+ GSM238816 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238816F81A |
+ 81 |
+ F |
+
+
+ | 66 |
+ GSM238817 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238817F85A |
+ 85 |
+ F |
+
+
+ | 67 |
+ GSM238818 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238818M79A |
+ 79 |
+ M |
+
+
+ | 68 |
+ GSM238819 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238819F82A |
+ 82 |
+ F |
+
+
+ | 69 |
+ GSM238820 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238820M88A |
+ 88 |
+ M |
+
+
+ | 70 |
+ GSM238821 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238821M72A |
+ 72 |
+ M |
+
+
+ | 71 |
+ GSM238822 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238822F73A |
+ 73 |
+ F |
+
+
+ | 72 |
+ GSM238823 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238823M87A |
+ 87 |
+ M |
+
+
+ | 73 |
+ GSM238824 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238824M68A |
+ 68 |
+ M |
+
+
+ | 74 |
+ GSM238825 |
+ Medial Temporal Gyrus |
+ Alzheimer's |
+ MT238825F80A |
+ 80 |
+ F |
+
+
+ | 75 |
+ GSM119653 |
+ Posterior Cingulate |
+ Normal |
+ PC119653M85N |
+ 85 |
+ M |
+
+
+ | 76 |
+ GSM119654 |
+ Posterior Cingulate |
+ Normal |
+ PC119654M80N |
+ 80 |
+ M |
+
+
+ | 77 |
+ GSM119655 |
+ Posterior Cingulate |
+ Normal |
+ PC119655F102N |
+ 102 |
+ F |
+
+
+ | 78 |
+ GSM119656 |
+ Posterior Cingulate |
+ Normal |
+ PC119656M63N |
+ 63 |
+ M |
+
+
+ | 79 |
+ GSM119657 |
+ Posterior Cingulate |
+ Normal |
+ PC119657M79N |
+ 79 |
+ M |
+
+
+ | 80 |
+ GSM119658 |
+ Posterior Cingulate |
+ Normal |
+ PC119658M->F76N |
+ 76 |
+ M |
+
+
+ | 81 |
+ GSM119659 |
+ Posterior Cingulate |
+ Normal |
+ PC119659M83N |
+ 83 |
+ M |
+
+
+ | 82 |
+ GSM119660 |
+ Posterior Cingulate |
+ Normal |
+ PC119660M79N |
+ 79 |
+ M |
+
+
+ | 83 |
+ GSM119661 |
+ Posterior Cingulate |
+ Normal |
+ PC119661F88N |
+ 88 |
+ F |
+
+
+ | 84 |
+ GSM119662 |
+ Posterior Cingulate |
+ Normal |
+ PC119662F82N |
+ 82 |
+ F |
+
+
+ | 85 |
+ GSM119663 |
+ Posterior Cingulate |
+ Normal |
+ PC119663F73N |
+ 73 |
+ F |
+
+
+ | 86 |
+ GSM119664 |
+ Posterior Cingulate |
+ Normal |
+ PC119664M69N |
+ 69 |
+ M |
+
+
+ | 87 |
+ GSM119665 |
+ Posterior Cingulate |
+ Normal |
+ PC119665M78N |
+ 78 |
+ M |
+
+
+ | 88 |
+ GSM238826 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238826F73A |
+ 73 |
+ F |
+
+
+ | 89 |
+ GSM238827 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238827M81A |
+ 81 |
+ M |
+
+
+ | 90 |
+ GSM238834 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238834M78A |
+ 78 |
+ M |
+
+
+ | 91 |
+ GSM238835 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238835M75A |
+ 75 |
+ M |
+
+
+ | 92 |
+ GSM238837 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238837M68A |
+ 68 |
+ M |
+
+
+ | 93 |
+ GSM238838 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238838F70A |
+ 70 |
+ F |
+
+
+ | 94 |
+ GSM238839 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238839F85A |
+ 85 |
+ F |
+
+
+ | 95 |
+ GSM238840 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238840M79A |
+ 79 |
+ M |
+
+
+ | 96 |
+ GSM238841 |
+ Posterior Cingulate |
+ Alzheimer's |
+ PC238841M88A |
+ 88 |
+ M |
+
+
+ | 97 |
+ GSM119666 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119666M79N |
+ 79 |
+ M |
+
+
+ | 98 |
+ GSM119667 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119667F->M88N |
+ 88 |
+ F |
+
+
+ | 99 |
+ GSM119668 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119668F->M82N |
+ 82 |
+ F |
+
+
+ | 100 |
+ GSM119669 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119669F->M73N |
+ 73 |
+ F |
+
+
+ | 101 |
+ GSM119670 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119670F->M102N |
+ 102 |
+ F |
+
+
+ | 102 |
+ GSM119671 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119671M63N |
+ 63 |
+ M |
+
+
+ | 103 |
+ GSM119672 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119672M->F79N |
+ 79 |
+ M |
+
+
+ | 104 |
+ GSM119673 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119673M->F76N |
+ 76 |
+ M |
+
+
+ | 105 |
+ GSM119674 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119674M->F83N |
+ 83 |
+ M |
+
+
+ | 106 |
+ GSM119675 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119675M69N |
+ 69 |
+ M |
+
+
+ | 107 |
+ GSM119676 |
+ Superior Frontal Gyrus |
+ Normal |
+ SF119676M78N |
+ 78 |
+ M |
+
+
+ | 108 |
+ GSM238842 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238842F73A |
+ 73 |
+ F |
+
+
+ | 109 |
+ GSM238843 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238843M81A |
+ 81 |
+ M |
+
+
+ | 110 |
+ GSM238844 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238844M72A |
+ 72 |
+ M |
+
+
+ | 111 |
+ GSM238845 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238845M75A |
+ 75 |
+ M |
+
+
+ | 112 |
+ GSM238846 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238846M78A |
+ 78 |
+ M |
+
+
+ | 113 |
+ GSM238847 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238847M75A |
+ 75 |
+ M |
+
+
+ | 114 |
+ GSM238848 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238848M87A |
+ 87 |
+ M |
+
+
+ | 115 |
+ GSM238851 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238851F95A |
+ 95 |
+ F |
+
+
+ | 116 |
+ GSM238854 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238854M68A |
+ 68 |
+ M |
+
+
+ | 117 |
+ GSM238855 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238855F95A |
+ 95 |
+ F |
+
+
+ | 118 |
+ GSM238856 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238856F70A |
+ 70 |
+ F |
+
+
+ | 119 |
+ GSM238857 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238857F85A |
+ 85 |
+ F |
+
+
+ | 120 |
+ GSM238858 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238858F83A |
+ 83 |
+ F |
+
+
+ | 121 |
+ GSM238860 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238860F77A |
+ 77 |
+ F |
+
+
+ | 122 |
+ GSM238861 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238861F83A |
+ 83 |
+ F |
+
+
+ | 123 |
+ GSM238862 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238862M68A |
+ 68 |
+ M |
+
+
+ | 124 |
+ GSM238863 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238863M79A |
+ 79 |
+ M |
+
+
+ | 125 |
+ GSM238864 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238864F82A |
+ 82 |
+ F |
+
+
+ | 126 |
+ GSM238865 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238865M88A |
+ 88 |
+ M |
+
+
+ | 127 |
+ GSM238867 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238867F80A |
+ 80 |
+ F |
+
+
+ | 128 |
+ GSM238868 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238868M74A |
+ 74 |
+ M |
+
+
+ | 129 |
+ GSM238870 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238870M72A |
+ 72 |
+ M |
+
+
+ | 130 |
+ GSM238871 |
+ Superior Frontal Gyrus |
+ Alzheimer's |
+ SF238871M80A |
+ 80 |
+ M |
+
+
+ | 131 |
+ GSM119677 |
+ Primary Visual Cortex |
+ Normal |
+ V119677M85N |
+ 85 |
+ M |
+
+
+ | 132 |
+ GSM119678 |
+ Primary Visual Cortex |
+ Normal |
+ V119678M80N |
+ 80 |
+ M |
+
+
+ | 133 |
+ GSM119679 |
+ Primary Visual Cortex |
+ Normal |
+ V119679M63N |
+ 63 |
+ M |
+
+
+ | 134 |
+ GSM119680 |
+ Primary Visual Cortex |
+ Normal |
+ V119680M79N |
+ 79 |
+ M |
+
+
+ | 135 |
+ GSM119681 |
+ Primary Visual Cortex |
+ Normal |
+ V119681M76N |
+ 76 |
+ M |
+
+
+ | 136 |
+ GSM119682 |
+ Primary Visual Cortex |
+ Normal |
+ V119682M83N |
+ 83 |
+ M |
+
+
+ | 137 |
+ GSM119683 |
+ Primary Visual Cortex |
+ Normal |
+ V119683M79N |
+ 79 |
+ M |
+
+
+ | 138 |
+ GSM119684 |
+ Primary Visual Cortex |
+ Normal |
+ V119684F88N |
+ 88 |
+ F |
+
+
+ | 139 |
+ GSM119685 |
+ Primary Visual Cortex |
+ Normal |
+ V119685F82N |
+ 82 |
+ F |
+
+
+ | 140 |
+ GSM119686 |
+ Primary Visual Cortex |
+ Normal |
+ V119686F73N |
+ 73 |
+ F |
+
+
+ | 141 |
+ GSM119687 |
+ Primary Visual Cortex |
+ Normal |
+ V119687M69N |
+ 69 |
+ M |
+
+
+ | 142 |
+ GSM119688 |
+ Primary Visual Cortex |
+ Normal |
+ V119688M78N |
+ 78 |
+ M |
+
+
+ | 143 |
+ GSM238872 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238872F73A |
+ 73 |
+ F |
+
+
+ | 144 |
+ GSM238873 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238873M81A |
+ 81 |
+ M |
+
+
+ | 145 |
+ GSM238874 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238874M75A |
+ 75 |
+ M |
+
+
+ | 146 |
+ GSM238875 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238875M78A |
+ 78 |
+ M |
+
+
+ | 147 |
+ GSM238877 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238877M75A |
+ 75 |
+ M |
+
+
+ | 148 |
+ GSM238941 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238941M87A |
+ 87 |
+ M |
+
+
+ | 149 |
+ GSM238942 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238942F95A |
+ 95 |
+ F |
+
+
+ | 150 |
+ GSM238943 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238943M68A |
+ 68 |
+ M |
+
+
+ | 151 |
+ GSM238944 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238944F70A |
+ 70 |
+ F |
+
+
+ | 152 |
+ GSM238945 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238945F81A |
+ 81 |
+ F |
+
+
+ | 153 |
+ GSM238946 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238946F85A |
+ 85 |
+ F |
+
+
+ | 154 |
+ GSM238947 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238947M68A |
+ 68 |
+ M |
+
+
+ | 155 |
+ GSM238948 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238948M79A |
+ 79 |
+ M |
+
+
+ | 156 |
+ GSM238949 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238949F82A |
+ 82 |
+ F |
+
+
+ | 157 |
+ GSM238951 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238951M88A |
+ 88 |
+ M |
+
+
+ | 158 |
+ GSM238952 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238952M74A |
+ 74 |
+ M |
+
+
+ | 159 |
+ GSM238953 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238953M72A |
+ 72 |
+ M |
+
+
+ | 160 |
+ GSM238955 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238955M->F68A |
+ 68 |
+ M |
+
+
+ | 161 |
+ GSM238963 |
+ Primary Visual Cortex |
+ Alzheimer's |
+ V238963F80A |
+ 80 |
+ F |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Gtex_adren_0414/cases.rtf b/general/datasets/Gtex_adren_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_adren_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_adren_0414/contributors.rtf b/general/datasets/Gtex_adren_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_adren_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_adren_0414/experiment-design.rtf b/general/datasets/Gtex_adren_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_adren_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_adren_0414/platform.rtf b/general/datasets/Gtex_adren_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_adren_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_adren_0414/processing.rtf b/general/datasets/Gtex_adren_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_adren_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_adren_0414/summary.rtf b/general/datasets/Gtex_adren_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_adren_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_adren_0414/tissue.rtf b/general/datasets/Gtex_adren_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_adren_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_amy_0314/cases.rtf b/general/datasets/Gtex_amy_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_amy_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_amy_0314/contributors.rtf b/general/datasets/Gtex_amy_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_amy_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_amy_0314/experiment-design.rtf b/general/datasets/Gtex_amy_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_amy_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_amy_0314/platform.rtf b/general/datasets/Gtex_amy_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_amy_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_amy_0314/processing.rtf b/general/datasets/Gtex_amy_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_amy_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_amy_0314/summary.rtf b/general/datasets/Gtex_amy_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_amy_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_amy_0314/tissue.rtf b/general/datasets/Gtex_amy_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_amy_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_anter_0414/cases.rtf b/general/datasets/Gtex_anter_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_anter_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_anter_0414/contributors.rtf b/general/datasets/Gtex_anter_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_anter_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_anter_0414/experiment-design.rtf b/general/datasets/Gtex_anter_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_anter_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_anter_0414/platform.rtf b/general/datasets/Gtex_anter_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_anter_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_anter_0414/processing.rtf b/general/datasets/Gtex_anter_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_anter_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_anter_0414/summary.rtf b/general/datasets/Gtex_anter_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_anter_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_anter_0414/tissue.rtf b/general/datasets/Gtex_anter_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_anter_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_aorta_0414/cases.rtf b/general/datasets/Gtex_aorta_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_aorta_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_aorta_0414/contributors.rtf b/general/datasets/Gtex_aorta_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_aorta_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_aorta_0414/experiment-design.rtf b/general/datasets/Gtex_aorta_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_aorta_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_aorta_0414/platform.rtf b/general/datasets/Gtex_aorta_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_aorta_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_aorta_0414/processing.rtf b/general/datasets/Gtex_aorta_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_aorta_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_aorta_0414/summary.rtf b/general/datasets/Gtex_aorta_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_aorta_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_aorta_0414/tissue.rtf b/general/datasets/Gtex_aorta_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_aorta_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_blood_0414/cases.rtf b/general/datasets/Gtex_blood_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_blood_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_blood_0414/contributors.rtf b/general/datasets/Gtex_blood_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_blood_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_blood_0414/experiment-design.rtf b/general/datasets/Gtex_blood_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_blood_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_blood_0414/platform.rtf b/general/datasets/Gtex_blood_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_blood_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_blood_0414/processing.rtf b/general/datasets/Gtex_blood_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_blood_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_blood_0414/summary.rtf b/general/datasets/Gtex_blood_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_blood_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_blood_0414/tissue.rtf b/general/datasets/Gtex_blood_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_blood_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_breas_0414/cases.rtf b/general/datasets/Gtex_breas_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_breas_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_breas_0414/contributors.rtf b/general/datasets/Gtex_breas_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_breas_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_breas_0414/experiment-design.rtf b/general/datasets/Gtex_breas_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_breas_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_breas_0414/platform.rtf b/general/datasets/Gtex_breas_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_breas_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_breas_0414/processing.rtf b/general/datasets/Gtex_breas_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_breas_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_breas_0414/summary.rtf b/general/datasets/Gtex_breas_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_breas_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_breas_0414/tissue.rtf b/general/datasets/Gtex_breas_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_breas_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_cauda_0414/cases.rtf b/general/datasets/Gtex_cauda_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_cauda_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_cauda_0414/contributors.rtf b/general/datasets/Gtex_cauda_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_cauda_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_cauda_0414/experiment-design.rtf b/general/datasets/Gtex_cauda_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_cauda_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_cauda_0414/platform.rtf b/general/datasets/Gtex_cauda_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_cauda_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_cauda_0414/processing.rtf b/general/datasets/Gtex_cauda_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_cauda_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_cauda_0414/summary.rtf b/general/datasets/Gtex_cauda_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_cauda_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_cauda_0414/tissue.rtf b/general/datasets/Gtex_cauda_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_cauda_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_cellsebv_0414/cases.rtf b/general/datasets/Gtex_cellsebv_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_cellsebv_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_cellsebv_0414/contributors.rtf b/general/datasets/Gtex_cellsebv_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_cellsebv_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_cellsebv_0414/experiment-design.rtf b/general/datasets/Gtex_cellsebv_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_cellsebv_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_cellsebv_0414/platform.rtf b/general/datasets/Gtex_cellsebv_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_cellsebv_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_cellsebv_0414/processing.rtf b/general/datasets/Gtex_cellsebv_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_cellsebv_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_cellsebv_0414/summary.rtf b/general/datasets/Gtex_cellsebv_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_cellsebv_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_cellsebv_0414/tissue.rtf b/general/datasets/Gtex_cellsebv_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_cellsebv_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_cellsle_0414/citation.rtf b/general/datasets/Gtex_cellsle_0414/citation.rtf
new file mode 100644
index 0000000..f3ba04a
--- /dev/null
+++ b/general/datasets/Gtex_cellsle_0414/citation.rtf
@@ -0,0 +1 @@
+Berchtold NC, Cribbs DH, Coleman PD, Rogers J et al. Gene expression changes in the course of normal brain aging are sexually dimorphic. Proc Natl Acad Sci U S A 2008 Oct 7;105(40):15605-10. PMID: 18832152
diff --git a/general/datasets/Gtex_cellsle_0414/contributors.rtf b/general/datasets/Gtex_cellsle_0414/contributors.rtf
new file mode 100644
index 0000000..fd462e2
--- /dev/null
+++ b/general/datasets/Gtex_cellsle_0414/contributors.rtf
@@ -0,0 +1 @@
+Berchtold NC, Cribbs DH, Coleman PD, Rogers J, Head E, Kim R, Beach T, Miller C, Troncoso J, Trojanowski JQ, Zielke HR, Cotman CW
diff --git a/general/datasets/Gtex_cellsle_0414/experiment-design.rtf b/general/datasets/Gtex_cellsle_0414/experiment-design.rtf
new file mode 100644
index 0000000..f6a3038
--- /dev/null
+++ b/general/datasets/Gtex_cellsle_0414/experiment-design.rtf
@@ -0,0 +1 @@
+Postmortem brain tissue was collected from ADRC brain banks. Cases were preferentially selected where 3 or more brain regions were available.
diff --git a/general/datasets/Gtex_cellsle_0414/summary.rtf b/general/datasets/Gtex_cellsle_0414/summary.rtf
new file mode 100644
index 0000000..fea08e6
--- /dev/null
+++ b/general/datasets/Gtex_cellsle_0414/summary.rtf
@@ -0,0 +1 @@
+Gene expression profiles were assessed in the hippocampus (HC), entorhinal cortex (EC), superior frontal gyrus (SG), and postcentral gyrus (PCG) across the lifespan of 63 cognitively intact individuals from 20-99 years old. New perspectives on the global gene changes that are associated with brain aging emerged, revealing two overarching concepts. First, different regions of the forebrain exhibited substantially different gene profile changes with age. For example, comparing equally powered groups, 5,029 probe sets were significantly altered with age (20-59 vs. 60-99) in the superior frontal gyrus, compared with 1,110 in the entorhinal cortex. Prominent change occurred in the 6th-7th decades across cortical regions, suggesting that this period is a critical transition point in brain aging, particularly in males. Second, clear gender differences in brain aging were evident across the lifespan, suggesting that the brain undergoes sexually dimorphic changes in gene expression not only in development but also in later life. Globally across all brain regions, males showed more gene change than females. Further, Gene Ontology analysis revealed that different categories of genes were predominantly affected in males vs. females. Notably, the male brain was characterized by global decreased catabolic and anabolic capacity with aging, with downregulated genes heavily enriched in energy production and protein synthesis/transport categories. Increased immune activation was a prominent feature of aging in both sexes, with more widespread activation in the female brain. These data open new opportunities to explore age-dependent changes in gene expression that set the balance between neurodegeneration and compensatory mechanisms in the brain, and suggest that this balance is set differently in males and females, an intriguing and novel idea. HgU133plus2.0 microarray chips were used to profile gene expression in 4 brain regions of cognitively intact humans, across the adult lifespan (ages 20-99).
diff --git a/general/datasets/Gtex_cellstr_0414/cases.rtf b/general/datasets/Gtex_cellstr_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_cellstr_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_cellstr_0414/contributors.rtf b/general/datasets/Gtex_cellstr_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_cellstr_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_cellstr_0414/experiment-design.rtf b/general/datasets/Gtex_cellstr_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_cellstr_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_cellstr_0414/platform.rtf b/general/datasets/Gtex_cellstr_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_cellstr_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_cellstr_0414/processing.rtf b/general/datasets/Gtex_cellstr_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_cellstr_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_cellstr_0414/summary.rtf b/general/datasets/Gtex_cellstr_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_cellstr_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_cellstr_0414/tissue.rtf b/general/datasets/Gtex_cellstr_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_cellstr_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_cer_0314/cases.rtf b/general/datasets/Gtex_cer_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_cer_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_cer_0314/contributors.rtf b/general/datasets/Gtex_cer_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_cer_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_cer_0314/experiment-design.rtf b/general/datasets/Gtex_cer_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_cer_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_cer_0314/platform.rtf b/general/datasets/Gtex_cer_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_cer_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_cer_0314/processing.rtf b/general/datasets/Gtex_cer_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_cer_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_cer_0314/summary.rtf b/general/datasets/Gtex_cer_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_cer_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_cer_0314/tissue.rtf b/general/datasets/Gtex_cer_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_cer_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_cerebc_0414/cases.rtf b/general/datasets/Gtex_cerebc_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_cerebc_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_cerebc_0414/contributors.rtf b/general/datasets/Gtex_cerebc_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_cerebc_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_cerebc_0414/experiment-design.rtf b/general/datasets/Gtex_cerebc_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_cerebc_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_cerebc_0414/platform.rtf b/general/datasets/Gtex_cerebc_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_cerebc_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_cerebc_0414/processing.rtf b/general/datasets/Gtex_cerebc_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_cerebc_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_cerebc_0414/summary.rtf b/general/datasets/Gtex_cerebc_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_cerebc_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_cerebc_0414/tissue.rtf b/general/datasets/Gtex_cerebc_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_cerebc_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_cerebh_0414/cases.rtf b/general/datasets/Gtex_cerebh_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_cerebh_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_cerebh_0414/contributors.rtf b/general/datasets/Gtex_cerebh_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_cerebh_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_cerebh_0414/experiment-design.rtf b/general/datasets/Gtex_cerebh_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_cerebh_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_cerebh_0414/platform.rtf b/general/datasets/Gtex_cerebh_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_cerebh_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_cerebh_0414/processing.rtf b/general/datasets/Gtex_cerebh_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_cerebh_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_cerebh_0414/summary.rtf b/general/datasets/Gtex_cerebh_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_cerebh_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_cerebh_0414/tissue.rtf b/general/datasets/Gtex_cerebh_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_cerebh_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_colon_0414/cases.rtf b/general/datasets/Gtex_colon_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_colon_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_colon_0414/contributors.rtf b/general/datasets/Gtex_colon_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_colon_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_colon_0414/experiment-design.rtf b/general/datasets/Gtex_colon_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_colon_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_colon_0414/platform.rtf b/general/datasets/Gtex_colon_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_colon_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_colon_0414/processing.rtf b/general/datasets/Gtex_colon_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_colon_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_colon_0414/summary.rtf b/general/datasets/Gtex_colon_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_colon_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_colon_0414/tissue.rtf b/general/datasets/Gtex_colon_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_colon_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_coron_0414/cases.rtf b/general/datasets/Gtex_coron_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_coron_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_coron_0414/contributors.rtf b/general/datasets/Gtex_coron_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_coron_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_coron_0414/experiment-design.rtf b/general/datasets/Gtex_coron_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_coron_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_coron_0414/platform.rtf b/general/datasets/Gtex_coron_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_coron_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_coron_0414/processing.rtf b/general/datasets/Gtex_coron_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_coron_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_coron_0414/summary.rtf b/general/datasets/Gtex_coron_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_coron_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_coron_0414/tissue.rtf b/general/datasets/Gtex_coron_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_coron_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_esophmuc_0414/cases.rtf b/general/datasets/Gtex_esophmuc_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_esophmuc_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_esophmuc_0414/contributors.rtf b/general/datasets/Gtex_esophmuc_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_esophmuc_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_esophmuc_0414/experiment-design.rtf b/general/datasets/Gtex_esophmuc_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_esophmuc_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_esophmuc_0414/platform.rtf b/general/datasets/Gtex_esophmuc_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_esophmuc_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_esophmuc_0414/processing.rtf b/general/datasets/Gtex_esophmuc_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_esophmuc_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_esophmuc_0414/summary.rtf b/general/datasets/Gtex_esophmuc_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_esophmuc_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_esophmuc_0414/tissue.rtf b/general/datasets/Gtex_esophmuc_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_esophmuc_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_esophmus_0414/cases.rtf b/general/datasets/Gtex_esophmus_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_esophmus_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_esophmus_0414/contributors.rtf b/general/datasets/Gtex_esophmus_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_esophmus_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_esophmus_0414/experiment-design.rtf b/general/datasets/Gtex_esophmus_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_esophmus_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_esophmus_0414/platform.rtf b/general/datasets/Gtex_esophmus_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_esophmus_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_esophmus_0414/processing.rtf b/general/datasets/Gtex_esophmus_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_esophmus_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_esophmus_0414/summary.rtf b/general/datasets/Gtex_esophmus_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_esophmus_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_esophmus_0414/tissue.rtf b/general/datasets/Gtex_esophmus_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_esophmus_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_fallo_0414/cases.rtf b/general/datasets/Gtex_fallo_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_fallo_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_fallo_0414/contributors.rtf b/general/datasets/Gtex_fallo_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_fallo_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_fallo_0414/experiment-design.rtf b/general/datasets/Gtex_fallo_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_fallo_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_fallo_0414/platform.rtf b/general/datasets/Gtex_fallo_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_fallo_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_fallo_0414/processing.rtf b/general/datasets/Gtex_fallo_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_fallo_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_fallo_0414/summary.rtf b/general/datasets/Gtex_fallo_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_fallo_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_fallo_0414/tissue.rtf b/general/datasets/Gtex_fallo_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_fallo_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_front_0414/cases.rtf b/general/datasets/Gtex_front_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_front_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_front_0414/contributors.rtf b/general/datasets/Gtex_front_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_front_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_front_0414/experiment-design.rtf b/general/datasets/Gtex_front_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_front_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_front_0414/platform.rtf b/general/datasets/Gtex_front_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_front_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_front_0414/processing.rtf b/general/datasets/Gtex_front_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_front_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_front_0414/summary.rtf b/general/datasets/Gtex_front_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_front_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_front_0414/tissue.rtf b/general/datasets/Gtex_front_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_front_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_heartat_0414/cases.rtf b/general/datasets/Gtex_heartat_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_heartat_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_heartat_0414/contributors.rtf b/general/datasets/Gtex_heartat_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_heartat_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_heartat_0414/experiment-design.rtf b/general/datasets/Gtex_heartat_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_heartat_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_heartat_0414/platform.rtf b/general/datasets/Gtex_heartat_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_heartat_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_heartat_0414/processing.rtf b/general/datasets/Gtex_heartat_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_heartat_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_heartat_0414/summary.rtf b/general/datasets/Gtex_heartat_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_heartat_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_heartat_0414/tissue.rtf b/general/datasets/Gtex_heartat_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_heartat_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_heartlv_0414/cases.rtf b/general/datasets/Gtex_heartlv_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_heartlv_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_heartlv_0414/contributors.rtf b/general/datasets/Gtex_heartlv_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_heartlv_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_heartlv_0414/experiment-design.rtf b/general/datasets/Gtex_heartlv_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_heartlv_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_heartlv_0414/platform.rtf b/general/datasets/Gtex_heartlv_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_heartlv_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_heartlv_0414/processing.rtf b/general/datasets/Gtex_heartlv_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_heartlv_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_heartlv_0414/summary.rtf b/general/datasets/Gtex_heartlv_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_heartlv_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_heartlv_0414/tissue.rtf b/general/datasets/Gtex_heartlv_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_heartlv_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_hip_0314/cases.rtf b/general/datasets/Gtex_hip_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_hip_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_hip_0314/contributors.rtf b/general/datasets/Gtex_hip_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_hip_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_hip_0314/experiment-design.rtf b/general/datasets/Gtex_hip_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_hip_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_hip_0314/platform.rtf b/general/datasets/Gtex_hip_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_hip_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_hip_0314/processing.rtf b/general/datasets/Gtex_hip_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_hip_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_hip_0314/summary.rtf b/general/datasets/Gtex_hip_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_hip_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_hip_0314/tissue.rtf b/general/datasets/Gtex_hip_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_hip_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_hypot_0414/cases.rtf b/general/datasets/Gtex_hypot_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_hypot_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_hypot_0414/contributors.rtf b/general/datasets/Gtex_hypot_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_hypot_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_hypot_0414/experiment-design.rtf b/general/datasets/Gtex_hypot_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_hypot_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_hypot_0414/platform.rtf b/general/datasets/Gtex_hypot_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_hypot_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_hypot_0414/processing.rtf b/general/datasets/Gtex_hypot_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_hypot_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_hypot_0414/summary.rtf b/general/datasets/Gtex_hypot_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_hypot_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_hypot_0414/tissue.rtf b/general/datasets/Gtex_hypot_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_hypot_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_kidne_0414/cases.rtf b/general/datasets/Gtex_kidne_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_kidne_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_kidne_0414/contributors.rtf b/general/datasets/Gtex_kidne_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_kidne_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_kidne_0414/experiment-design.rtf b/general/datasets/Gtex_kidne_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_kidne_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_kidne_0414/platform.rtf b/general/datasets/Gtex_kidne_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_kidne_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_kidne_0414/processing.rtf b/general/datasets/Gtex_kidne_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_kidne_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_kidne_0414/summary.rtf b/general/datasets/Gtex_kidne_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_kidne_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_kidne_0414/tissue.rtf b/general/datasets/Gtex_kidne_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_kidne_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_liver_0414/cases.rtf b/general/datasets/Gtex_liver_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_liver_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_liver_0414/contributors.rtf b/general/datasets/Gtex_liver_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_liver_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_liver_0414/experiment-design.rtf b/general/datasets/Gtex_liver_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_liver_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_liver_0414/platform.rtf b/general/datasets/Gtex_liver_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_liver_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_liver_0414/processing.rtf b/general/datasets/Gtex_liver_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_liver_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_liver_0414/summary.rtf b/general/datasets/Gtex_liver_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_liver_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_liver_0414/tissue.rtf b/general/datasets/Gtex_liver_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_liver_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_adren_0314/cases.rtf b/general/datasets/Gtex_log2_adren_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_adren_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_adren_0314/contributors.rtf b/general/datasets/Gtex_log2_adren_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_adren_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_adren_0314/experiment-design.rtf b/general/datasets/Gtex_log2_adren_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_adren_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_adren_0314/platform.rtf b/general/datasets/Gtex_log2_adren_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_adren_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_adren_0314/processing.rtf b/general/datasets/Gtex_log2_adren_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_adren_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_adren_0314/summary.rtf b/general/datasets/Gtex_log2_adren_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_adren_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_adren_0314/tissue.rtf b/general/datasets/Gtex_log2_adren_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_adren_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_amy_0314/cases.rtf b/general/datasets/Gtex_log2_amy_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_amy_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_amy_0314/contributors.rtf b/general/datasets/Gtex_log2_amy_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_amy_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_amy_0314/experiment-design.rtf b/general/datasets/Gtex_log2_amy_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_amy_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_amy_0314/platform.rtf b/general/datasets/Gtex_log2_amy_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_amy_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_amy_0314/processing.rtf b/general/datasets/Gtex_log2_amy_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_amy_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_amy_0314/summary.rtf b/general/datasets/Gtex_log2_amy_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_amy_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_amy_0314/tissue.rtf b/general/datasets/Gtex_log2_amy_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_amy_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_anter_0314/cases.rtf b/general/datasets/Gtex_log2_anter_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_anter_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_anter_0314/contributors.rtf b/general/datasets/Gtex_log2_anter_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_anter_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_anter_0314/experiment-design.rtf b/general/datasets/Gtex_log2_anter_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_anter_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_anter_0314/platform.rtf b/general/datasets/Gtex_log2_anter_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_anter_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_anter_0314/processing.rtf b/general/datasets/Gtex_log2_anter_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_anter_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_anter_0314/summary.rtf b/general/datasets/Gtex_log2_anter_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_anter_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_anter_0314/tissue.rtf b/general/datasets/Gtex_log2_anter_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_anter_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_aorta_0314/cases.rtf b/general/datasets/Gtex_log2_aorta_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_aorta_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_aorta_0314/contributors.rtf b/general/datasets/Gtex_log2_aorta_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_aorta_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_aorta_0314/experiment-design.rtf b/general/datasets/Gtex_log2_aorta_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_aorta_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_aorta_0314/platform.rtf b/general/datasets/Gtex_log2_aorta_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_aorta_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_aorta_0314/processing.rtf b/general/datasets/Gtex_log2_aorta_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_aorta_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_aorta_0314/summary.rtf b/general/datasets/Gtex_log2_aorta_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_aorta_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_aorta_0314/tissue.rtf b/general/datasets/Gtex_log2_aorta_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_aorta_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_blood_0314/cases.rtf b/general/datasets/Gtex_log2_blood_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_blood_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_blood_0314/contributors.rtf b/general/datasets/Gtex_log2_blood_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_blood_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_blood_0314/experiment-design.rtf b/general/datasets/Gtex_log2_blood_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_blood_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_blood_0314/platform.rtf b/general/datasets/Gtex_log2_blood_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_blood_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_blood_0314/processing.rtf b/general/datasets/Gtex_log2_blood_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_blood_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_blood_0314/summary.rtf b/general/datasets/Gtex_log2_blood_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_blood_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_blood_0314/tissue.rtf b/general/datasets/Gtex_log2_blood_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_blood_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_breas_0314/cases.rtf b/general/datasets/Gtex_log2_breas_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_breas_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_breas_0314/contributors.rtf b/general/datasets/Gtex_log2_breas_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_breas_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_breas_0314/experiment-design.rtf b/general/datasets/Gtex_log2_breas_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_breas_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_breas_0314/platform.rtf b/general/datasets/Gtex_log2_breas_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_breas_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_breas_0314/processing.rtf b/general/datasets/Gtex_log2_breas_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_breas_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_breas_0314/summary.rtf b/general/datasets/Gtex_log2_breas_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_breas_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_breas_0314/tissue.rtf b/general/datasets/Gtex_log2_breas_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_breas_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_cauda_0314/cases.rtf b/general/datasets/Gtex_log2_cauda_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_cauda_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_cauda_0314/contributors.rtf b/general/datasets/Gtex_log2_cauda_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cauda_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_cauda_0314/experiment-design.rtf b/general/datasets/Gtex_log2_cauda_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cauda_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_cauda_0314/platform.rtf b/general/datasets/Gtex_log2_cauda_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_cauda_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_cauda_0314/processing.rtf b/general/datasets/Gtex_log2_cauda_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_cauda_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_cauda_0314/summary.rtf b/general/datasets/Gtex_log2_cauda_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_cauda_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_cauda_0314/tissue.rtf b/general/datasets/Gtex_log2_cauda_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_cauda_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_cellsebv_0314/cases.rtf b/general/datasets/Gtex_log2_cellsebv_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsebv_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_cellsebv_0314/contributors.rtf b/general/datasets/Gtex_log2_cellsebv_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsebv_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_cellsebv_0314/experiment-design.rtf b/general/datasets/Gtex_log2_cellsebv_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsebv_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_cellsebv_0314/platform.rtf b/general/datasets/Gtex_log2_cellsebv_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsebv_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_cellsebv_0314/processing.rtf b/general/datasets/Gtex_log2_cellsebv_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsebv_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_cellsebv_0314/summary.rtf b/general/datasets/Gtex_log2_cellsebv_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsebv_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_cellsebv_0314/tissue.rtf b/general/datasets/Gtex_log2_cellsebv_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsebv_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_cellsle_0314/cases.rtf b/general/datasets/Gtex_log2_cellsle_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsle_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_cellsle_0314/contributors.rtf b/general/datasets/Gtex_log2_cellsle_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsle_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_cellsle_0314/experiment-design.rtf b/general/datasets/Gtex_log2_cellsle_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsle_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_cellsle_0314/platform.rtf b/general/datasets/Gtex_log2_cellsle_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsle_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_cellsle_0314/processing.rtf b/general/datasets/Gtex_log2_cellsle_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsle_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_cellsle_0314/summary.rtf b/general/datasets/Gtex_log2_cellsle_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsle_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_cellsle_0314/tissue.rtf b/general/datasets/Gtex_log2_cellsle_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellsle_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_cellstr_0314/cases.rtf b/general/datasets/Gtex_log2_cellstr_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellstr_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_cellstr_0314/contributors.rtf b/general/datasets/Gtex_log2_cellstr_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellstr_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_cellstr_0314/experiment-design.rtf b/general/datasets/Gtex_log2_cellstr_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellstr_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_cellstr_0314/platform.rtf b/general/datasets/Gtex_log2_cellstr_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellstr_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_cellstr_0314/processing.rtf b/general/datasets/Gtex_log2_cellstr_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellstr_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_cellstr_0314/summary.rtf b/general/datasets/Gtex_log2_cellstr_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellstr_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_cellstr_0314/tissue.rtf b/general/datasets/Gtex_log2_cellstr_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_cellstr_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_cer_0314/cases.rtf b/general/datasets/Gtex_log2_cer_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_cer_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_cer_0314/contributors.rtf b/general/datasets/Gtex_log2_cer_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cer_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_cer_0314/experiment-design.rtf b/general/datasets/Gtex_log2_cer_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cer_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_cer_0314/platform.rtf b/general/datasets/Gtex_log2_cer_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_cer_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_cer_0314/processing.rtf b/general/datasets/Gtex_log2_cer_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_cer_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_cer_0314/summary.rtf b/general/datasets/Gtex_log2_cer_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_cer_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_cer_0314/tissue.rtf b/general/datasets/Gtex_log2_cer_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_cer_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_cerebc_0314/cases.rtf b/general/datasets/Gtex_log2_cerebc_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebc_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_cerebc_0314/contributors.rtf b/general/datasets/Gtex_log2_cerebc_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebc_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_cerebc_0314/experiment-design.rtf b/general/datasets/Gtex_log2_cerebc_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebc_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_cerebc_0314/platform.rtf b/general/datasets/Gtex_log2_cerebc_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebc_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_cerebc_0314/processing.rtf b/general/datasets/Gtex_log2_cerebc_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebc_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_cerebc_0314/summary.rtf b/general/datasets/Gtex_log2_cerebc_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebc_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_cerebc_0314/tissue.rtf b/general/datasets/Gtex_log2_cerebc_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebc_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_cerebh_0314/cases.rtf b/general/datasets/Gtex_log2_cerebh_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebh_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_cerebh_0314/contributors.rtf b/general/datasets/Gtex_log2_cerebh_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebh_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_cerebh_0314/experiment-design.rtf b/general/datasets/Gtex_log2_cerebh_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebh_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_cerebh_0314/platform.rtf b/general/datasets/Gtex_log2_cerebh_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebh_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_cerebh_0314/processing.rtf b/general/datasets/Gtex_log2_cerebh_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebh_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_cerebh_0314/summary.rtf b/general/datasets/Gtex_log2_cerebh_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebh_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_cerebh_0314/tissue.rtf b/general/datasets/Gtex_log2_cerebh_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_cerebh_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_colon_0314/cases.rtf b/general/datasets/Gtex_log2_colon_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_colon_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_colon_0314/contributors.rtf b/general/datasets/Gtex_log2_colon_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_colon_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_colon_0314/experiment-design.rtf b/general/datasets/Gtex_log2_colon_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_colon_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_colon_0314/platform.rtf b/general/datasets/Gtex_log2_colon_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_colon_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_colon_0314/processing.rtf b/general/datasets/Gtex_log2_colon_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_colon_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_colon_0314/summary.rtf b/general/datasets/Gtex_log2_colon_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_colon_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_colon_0314/tissue.rtf b/general/datasets/Gtex_log2_colon_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_colon_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_coron_0314/cases.rtf b/general/datasets/Gtex_log2_coron_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_coron_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_coron_0314/contributors.rtf b/general/datasets/Gtex_log2_coron_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_coron_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_coron_0314/experiment-design.rtf b/general/datasets/Gtex_log2_coron_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_coron_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_coron_0314/platform.rtf b/general/datasets/Gtex_log2_coron_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_coron_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_coron_0314/processing.rtf b/general/datasets/Gtex_log2_coron_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_coron_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_coron_0314/summary.rtf b/general/datasets/Gtex_log2_coron_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_coron_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_coron_0314/tissue.rtf b/general/datasets/Gtex_log2_coron_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_coron_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_esophmuc_0314/cases.rtf b/general/datasets/Gtex_log2_esophmuc_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmuc_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_esophmuc_0314/contributors.rtf b/general/datasets/Gtex_log2_esophmuc_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmuc_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_esophmuc_0314/experiment-design.rtf b/general/datasets/Gtex_log2_esophmuc_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmuc_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_esophmuc_0314/platform.rtf b/general/datasets/Gtex_log2_esophmuc_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmuc_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_esophmuc_0314/processing.rtf b/general/datasets/Gtex_log2_esophmuc_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmuc_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_esophmuc_0314/summary.rtf b/general/datasets/Gtex_log2_esophmuc_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmuc_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_esophmuc_0314/tissue.rtf b/general/datasets/Gtex_log2_esophmuc_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmuc_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_esophmus_0314/cases.rtf b/general/datasets/Gtex_log2_esophmus_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmus_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_esophmus_0314/contributors.rtf b/general/datasets/Gtex_log2_esophmus_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmus_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_esophmus_0314/experiment-design.rtf b/general/datasets/Gtex_log2_esophmus_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmus_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_esophmus_0314/platform.rtf b/general/datasets/Gtex_log2_esophmus_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmus_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_esophmus_0314/processing.rtf b/general/datasets/Gtex_log2_esophmus_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmus_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_esophmus_0314/summary.rtf b/general/datasets/Gtex_log2_esophmus_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmus_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_esophmus_0314/tissue.rtf b/general/datasets/Gtex_log2_esophmus_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_esophmus_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_fallo_0314/cases.rtf b/general/datasets/Gtex_log2_fallo_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_fallo_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_fallo_0314/contributors.rtf b/general/datasets/Gtex_log2_fallo_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_fallo_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_fallo_0314/experiment-design.rtf b/general/datasets/Gtex_log2_fallo_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_fallo_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_fallo_0314/platform.rtf b/general/datasets/Gtex_log2_fallo_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_fallo_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_fallo_0314/processing.rtf b/general/datasets/Gtex_log2_fallo_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_fallo_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_fallo_0314/summary.rtf b/general/datasets/Gtex_log2_fallo_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_fallo_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_fallo_0314/tissue.rtf b/general/datasets/Gtex_log2_fallo_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_fallo_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_front_0314/cases.rtf b/general/datasets/Gtex_log2_front_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_front_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_front_0314/contributors.rtf b/general/datasets/Gtex_log2_front_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_front_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_front_0314/experiment-design.rtf b/general/datasets/Gtex_log2_front_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_front_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_front_0314/platform.rtf b/general/datasets/Gtex_log2_front_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_front_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_front_0314/processing.rtf b/general/datasets/Gtex_log2_front_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_front_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_front_0314/summary.rtf b/general/datasets/Gtex_log2_front_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_front_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_front_0314/tissue.rtf b/general/datasets/Gtex_log2_front_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_front_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_heartat_0314/cases.rtf b/general/datasets/Gtex_log2_heartat_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartat_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_heartat_0314/contributors.rtf b/general/datasets/Gtex_log2_heartat_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartat_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_heartat_0314/experiment-design.rtf b/general/datasets/Gtex_log2_heartat_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartat_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_heartat_0314/platform.rtf b/general/datasets/Gtex_log2_heartat_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartat_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_heartat_0314/processing.rtf b/general/datasets/Gtex_log2_heartat_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartat_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_heartat_0314/summary.rtf b/general/datasets/Gtex_log2_heartat_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartat_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_heartat_0314/tissue.rtf b/general/datasets/Gtex_log2_heartat_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartat_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_heartlv_0314/cases.rtf b/general/datasets/Gtex_log2_heartlv_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartlv_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_heartlv_0314/contributors.rtf b/general/datasets/Gtex_log2_heartlv_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartlv_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_heartlv_0314/experiment-design.rtf b/general/datasets/Gtex_log2_heartlv_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartlv_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_heartlv_0314/platform.rtf b/general/datasets/Gtex_log2_heartlv_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartlv_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_heartlv_0314/processing.rtf b/general/datasets/Gtex_log2_heartlv_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartlv_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_heartlv_0314/summary.rtf b/general/datasets/Gtex_log2_heartlv_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartlv_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_heartlv_0314/tissue.rtf b/general/datasets/Gtex_log2_heartlv_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_heartlv_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_hip_0314/cases.rtf b/general/datasets/Gtex_log2_hip_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_hip_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_hip_0314/contributors.rtf b/general/datasets/Gtex_log2_hip_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_hip_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_hip_0314/experiment-design.rtf b/general/datasets/Gtex_log2_hip_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_hip_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_hip_0314/platform.rtf b/general/datasets/Gtex_log2_hip_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_hip_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_hip_0314/processing.rtf b/general/datasets/Gtex_log2_hip_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_hip_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_hip_0314/summary.rtf b/general/datasets/Gtex_log2_hip_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_hip_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_hip_0314/tissue.rtf b/general/datasets/Gtex_log2_hip_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_hip_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_hypot_0314/cases.rtf b/general/datasets/Gtex_log2_hypot_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_hypot_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_hypot_0314/contributors.rtf b/general/datasets/Gtex_log2_hypot_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_hypot_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_hypot_0314/experiment-design.rtf b/general/datasets/Gtex_log2_hypot_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_hypot_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_hypot_0314/platform.rtf b/general/datasets/Gtex_log2_hypot_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_hypot_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_hypot_0314/processing.rtf b/general/datasets/Gtex_log2_hypot_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_hypot_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_hypot_0314/summary.rtf b/general/datasets/Gtex_log2_hypot_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_hypot_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_hypot_0314/tissue.rtf b/general/datasets/Gtex_log2_hypot_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_hypot_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_kidne_0314/cases.rtf b/general/datasets/Gtex_log2_kidne_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_kidne_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_kidne_0314/contributors.rtf b/general/datasets/Gtex_log2_kidne_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_kidne_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_kidne_0314/experiment-design.rtf b/general/datasets/Gtex_log2_kidne_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_kidne_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_kidne_0314/platform.rtf b/general/datasets/Gtex_log2_kidne_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_kidne_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_kidne_0314/processing.rtf b/general/datasets/Gtex_log2_kidne_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_kidne_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_kidne_0314/summary.rtf b/general/datasets/Gtex_log2_kidne_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_kidne_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_kidne_0314/tissue.rtf b/general/datasets/Gtex_log2_kidne_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_kidne_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_liver_0314/cases.rtf b/general/datasets/Gtex_log2_liver_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_liver_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_liver_0314/contributors.rtf b/general/datasets/Gtex_log2_liver_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_liver_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_liver_0314/experiment-design.rtf b/general/datasets/Gtex_log2_liver_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_liver_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_liver_0314/platform.rtf b/general/datasets/Gtex_log2_liver_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_liver_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_liver_0314/processing.rtf b/general/datasets/Gtex_log2_liver_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_liver_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_liver_0314/summary.rtf b/general/datasets/Gtex_log2_liver_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_liver_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_liver_0314/tissue.rtf b/general/datasets/Gtex_log2_liver_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_liver_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_lung_0314/cases.rtf b/general/datasets/Gtex_log2_lung_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_lung_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_lung_0314/contributors.rtf b/general/datasets/Gtex_log2_lung_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_lung_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_lung_0314/experiment-design.rtf b/general/datasets/Gtex_log2_lung_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_lung_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_lung_0314/platform.rtf b/general/datasets/Gtex_log2_lung_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_lung_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_lung_0314/processing.rtf b/general/datasets/Gtex_log2_lung_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_lung_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_lung_0314/summary.rtf b/general/datasets/Gtex_log2_lung_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_lung_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_lung_0314/tissue.rtf b/general/datasets/Gtex_log2_lung_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_lung_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_muscle_0314/cases.rtf b/general/datasets/Gtex_log2_muscle_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_muscle_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_muscle_0314/contributors.rtf b/general/datasets/Gtex_log2_muscle_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_muscle_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_muscle_0314/experiment-design.rtf b/general/datasets/Gtex_log2_muscle_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_muscle_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_muscle_0314/platform.rtf b/general/datasets/Gtex_log2_muscle_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_muscle_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_muscle_0314/processing.rtf b/general/datasets/Gtex_log2_muscle_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_muscle_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_muscle_0314/summary.rtf b/general/datasets/Gtex_log2_muscle_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_muscle_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_muscle_0314/tissue.rtf b/general/datasets/Gtex_log2_muscle_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_muscle_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_nerve_0314/cases.rtf b/general/datasets/Gtex_log2_nerve_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_nerve_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_nerve_0314/contributors.rtf b/general/datasets/Gtex_log2_nerve_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_nerve_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_nerve_0314/experiment-design.rtf b/general/datasets/Gtex_log2_nerve_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_nerve_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_nerve_0314/platform.rtf b/general/datasets/Gtex_log2_nerve_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_nerve_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_nerve_0314/processing.rtf b/general/datasets/Gtex_log2_nerve_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_nerve_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_nerve_0314/summary.rtf b/general/datasets/Gtex_log2_nerve_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_nerve_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_nerve_0314/tissue.rtf b/general/datasets/Gtex_log2_nerve_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_nerve_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_nucle_0314/cases.rtf b/general/datasets/Gtex_log2_nucle_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_nucle_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_nucle_0314/contributors.rtf b/general/datasets/Gtex_log2_nucle_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_nucle_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_nucle_0314/experiment-design.rtf b/general/datasets/Gtex_log2_nucle_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_nucle_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_nucle_0314/platform.rtf b/general/datasets/Gtex_log2_nucle_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_nucle_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_nucle_0314/processing.rtf b/general/datasets/Gtex_log2_nucle_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_nucle_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_nucle_0314/summary.rtf b/general/datasets/Gtex_log2_nucle_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_nucle_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_nucle_0314/tissue.rtf b/general/datasets/Gtex_log2_nucle_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_nucle_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_ovary_0314/cases.rtf b/general/datasets/Gtex_log2_ovary_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_ovary_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_ovary_0314/contributors.rtf b/general/datasets/Gtex_log2_ovary_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_ovary_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_ovary_0314/experiment-design.rtf b/general/datasets/Gtex_log2_ovary_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_ovary_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_ovary_0314/platform.rtf b/general/datasets/Gtex_log2_ovary_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_ovary_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_ovary_0314/processing.rtf b/general/datasets/Gtex_log2_ovary_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_ovary_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_ovary_0314/summary.rtf b/general/datasets/Gtex_log2_ovary_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_ovary_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_ovary_0314/tissue.rtf b/general/datasets/Gtex_log2_ovary_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_ovary_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_pancr_0314/cases.rtf b/general/datasets/Gtex_log2_pancr_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_pancr_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_pancr_0314/contributors.rtf b/general/datasets/Gtex_log2_pancr_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_pancr_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_pancr_0314/experiment-design.rtf b/general/datasets/Gtex_log2_pancr_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_pancr_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_pancr_0314/platform.rtf b/general/datasets/Gtex_log2_pancr_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_pancr_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_pancr_0314/processing.rtf b/general/datasets/Gtex_log2_pancr_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_pancr_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_pancr_0314/summary.rtf b/general/datasets/Gtex_log2_pancr_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_pancr_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_pancr_0314/tissue.rtf b/general/datasets/Gtex_log2_pancr_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_pancr_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_pitui_0314/cases.rtf b/general/datasets/Gtex_log2_pitui_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_pitui_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_pitui_0314/contributors.rtf b/general/datasets/Gtex_log2_pitui_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_pitui_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_pitui_0314/experiment-design.rtf b/general/datasets/Gtex_log2_pitui_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_pitui_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_pitui_0314/platform.rtf b/general/datasets/Gtex_log2_pitui_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_pitui_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_pitui_0314/processing.rtf b/general/datasets/Gtex_log2_pitui_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_pitui_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_pitui_0314/summary.rtf b/general/datasets/Gtex_log2_pitui_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_pitui_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_pitui_0314/tissue.rtf b/general/datasets/Gtex_log2_pitui_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_pitui_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_prost_0314/cases.rtf b/general/datasets/Gtex_log2_prost_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_prost_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_prost_0314/contributors.rtf b/general/datasets/Gtex_log2_prost_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_prost_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_prost_0314/experiment-design.rtf b/general/datasets/Gtex_log2_prost_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_prost_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_prost_0314/platform.rtf b/general/datasets/Gtex_log2_prost_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_prost_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_prost_0314/processing.rtf b/general/datasets/Gtex_log2_prost_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_prost_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_prost_0314/summary.rtf b/general/datasets/Gtex_log2_prost_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_prost_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_prost_0314/tissue.rtf b/general/datasets/Gtex_log2_prost_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_prost_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_putam_0314/cases.rtf b/general/datasets/Gtex_log2_putam_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_putam_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_putam_0314/contributors.rtf b/general/datasets/Gtex_log2_putam_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_putam_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_putam_0314/experiment-design.rtf b/general/datasets/Gtex_log2_putam_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_putam_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_putam_0314/platform.rtf b/general/datasets/Gtex_log2_putam_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_putam_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_putam_0314/processing.rtf b/general/datasets/Gtex_log2_putam_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_putam_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_putam_0314/summary.rtf b/general/datasets/Gtex_log2_putam_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_putam_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_putam_0314/tissue.rtf b/general/datasets/Gtex_log2_putam_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_putam_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_skine_0314/cases.rtf b/general/datasets/Gtex_log2_skine_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_skine_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_skine_0314/contributors.rtf b/general/datasets/Gtex_log2_skine_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_skine_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_skine_0314/experiment-design.rtf b/general/datasets/Gtex_log2_skine_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_skine_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_skine_0314/platform.rtf b/general/datasets/Gtex_log2_skine_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_skine_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_skine_0314/processing.rtf b/general/datasets/Gtex_log2_skine_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_skine_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_skine_0314/summary.rtf b/general/datasets/Gtex_log2_skine_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_skine_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_skine_0314/tissue.rtf b/general/datasets/Gtex_log2_skine_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_skine_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_skinn_0314/cases.rtf b/general/datasets/Gtex_log2_skinn_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_skinn_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_skinn_0314/contributors.rtf b/general/datasets/Gtex_log2_skinn_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_skinn_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_skinn_0314/experiment-design.rtf b/general/datasets/Gtex_log2_skinn_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_skinn_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_skinn_0314/platform.rtf b/general/datasets/Gtex_log2_skinn_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_skinn_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_skinn_0314/processing.rtf b/general/datasets/Gtex_log2_skinn_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_skinn_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_skinn_0314/summary.rtf b/general/datasets/Gtex_log2_skinn_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_skinn_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_skinn_0314/tissue.rtf b/general/datasets/Gtex_log2_skinn_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_skinn_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_spina_0314/cases.rtf b/general/datasets/Gtex_log2_spina_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_spina_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_spina_0314/contributors.rtf b/general/datasets/Gtex_log2_spina_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_spina_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_spina_0314/experiment-design.rtf b/general/datasets/Gtex_log2_spina_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_spina_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_spina_0314/platform.rtf b/general/datasets/Gtex_log2_spina_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_spina_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_spina_0314/processing.rtf b/general/datasets/Gtex_log2_spina_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_spina_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_spina_0314/summary.rtf b/general/datasets/Gtex_log2_spina_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_spina_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_spina_0314/tissue.rtf b/general/datasets/Gtex_log2_spina_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_spina_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_stoma_0314/cases.rtf b/general/datasets/Gtex_log2_stoma_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_stoma_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_stoma_0314/contributors.rtf b/general/datasets/Gtex_log2_stoma_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_stoma_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_stoma_0314/experiment-design.rtf b/general/datasets/Gtex_log2_stoma_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_stoma_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_stoma_0314/platform.rtf b/general/datasets/Gtex_log2_stoma_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_stoma_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_stoma_0314/processing.rtf b/general/datasets/Gtex_log2_stoma_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_stoma_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_stoma_0314/summary.rtf b/general/datasets/Gtex_log2_stoma_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_stoma_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_stoma_0314/tissue.rtf b/general/datasets/Gtex_log2_stoma_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_stoma_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_subcu_0314/cases.rtf b/general/datasets/Gtex_log2_subcu_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_subcu_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_subcu_0314/contributors.rtf b/general/datasets/Gtex_log2_subcu_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_subcu_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_subcu_0314/experiment-design.rtf b/general/datasets/Gtex_log2_subcu_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_subcu_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_subcu_0314/platform.rtf b/general/datasets/Gtex_log2_subcu_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_subcu_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_subcu_0314/processing.rtf b/general/datasets/Gtex_log2_subcu_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_subcu_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_subcu_0314/summary.rtf b/general/datasets/Gtex_log2_subcu_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_subcu_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_subcu_0314/tissue.rtf b/general/datasets/Gtex_log2_subcu_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_subcu_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_subst_0314/cases.rtf b/general/datasets/Gtex_log2_subst_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_subst_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_subst_0314/contributors.rtf b/general/datasets/Gtex_log2_subst_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_subst_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_subst_0314/experiment-design.rtf b/general/datasets/Gtex_log2_subst_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_subst_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_subst_0314/platform.rtf b/general/datasets/Gtex_log2_subst_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_subst_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_subst_0314/processing.rtf b/general/datasets/Gtex_log2_subst_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_subst_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_subst_0314/summary.rtf b/general/datasets/Gtex_log2_subst_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_subst_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_subst_0314/tissue.rtf b/general/datasets/Gtex_log2_subst_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_subst_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_testi_0314/cases.rtf b/general/datasets/Gtex_log2_testi_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_testi_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_testi_0314/contributors.rtf b/general/datasets/Gtex_log2_testi_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_testi_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_testi_0314/experiment-design.rtf b/general/datasets/Gtex_log2_testi_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_testi_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_testi_0314/platform.rtf b/general/datasets/Gtex_log2_testi_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_testi_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_testi_0314/processing.rtf b/general/datasets/Gtex_log2_testi_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_testi_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_testi_0314/summary.rtf b/general/datasets/Gtex_log2_testi_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_testi_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_testi_0314/tissue.rtf b/general/datasets/Gtex_log2_testi_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_testi_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_thyro_0314/cases.rtf b/general/datasets/Gtex_log2_thyro_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_thyro_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_thyro_0314/contributors.rtf b/general/datasets/Gtex_log2_thyro_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_thyro_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_thyro_0314/experiment-design.rtf b/general/datasets/Gtex_log2_thyro_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_thyro_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_thyro_0314/platform.rtf b/general/datasets/Gtex_log2_thyro_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_thyro_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_thyro_0314/processing.rtf b/general/datasets/Gtex_log2_thyro_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_thyro_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_thyro_0314/summary.rtf b/general/datasets/Gtex_log2_thyro_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_thyro_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_thyro_0314/tissue.rtf b/general/datasets/Gtex_log2_thyro_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_thyro_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_tibial_0314/cases.rtf b/general/datasets/Gtex_log2_tibial_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_tibial_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_tibial_0314/contributors.rtf b/general/datasets/Gtex_log2_tibial_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_tibial_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_tibial_0314/experiment-design.rtf b/general/datasets/Gtex_log2_tibial_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_tibial_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_tibial_0314/platform.rtf b/general/datasets/Gtex_log2_tibial_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_tibial_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_tibial_0314/processing.rtf b/general/datasets/Gtex_log2_tibial_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_tibial_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_tibial_0314/summary.rtf b/general/datasets/Gtex_log2_tibial_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_tibial_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_tibial_0314/tissue.rtf b/general/datasets/Gtex_log2_tibial_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_tibial_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_uterus_0314/cases.rtf b/general/datasets/Gtex_log2_uterus_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_uterus_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_uterus_0314/contributors.rtf b/general/datasets/Gtex_log2_uterus_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_uterus_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_uterus_0314/experiment-design.rtf b/general/datasets/Gtex_log2_uterus_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_uterus_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_uterus_0314/platform.rtf b/general/datasets/Gtex_log2_uterus_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_uterus_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_uterus_0314/processing.rtf b/general/datasets/Gtex_log2_uterus_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_uterus_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_uterus_0314/summary.rtf b/general/datasets/Gtex_log2_uterus_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_uterus_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_uterus_0314/tissue.rtf b/general/datasets/Gtex_log2_uterus_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_uterus_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_vagin_0314/cases.rtf b/general/datasets/Gtex_log2_vagin_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_vagin_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_vagin_0314/contributors.rtf b/general/datasets/Gtex_log2_vagin_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_vagin_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_vagin_0314/experiment-design.rtf b/general/datasets/Gtex_log2_vagin_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_vagin_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_vagin_0314/platform.rtf b/general/datasets/Gtex_log2_vagin_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_vagin_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_vagin_0314/processing.rtf b/general/datasets/Gtex_log2_vagin_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_vagin_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_vagin_0314/summary.rtf b/general/datasets/Gtex_log2_vagin_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_vagin_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_vagin_0314/tissue.rtf b/general/datasets/Gtex_log2_vagin_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_vagin_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_visce_0314/cases.rtf b/general/datasets/Gtex_log2_visce_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_visce_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_visce_0314/contributors.rtf b/general/datasets/Gtex_log2_visce_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_visce_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_visce_0314/experiment-design.rtf b/general/datasets/Gtex_log2_visce_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_visce_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_visce_0314/platform.rtf b/general/datasets/Gtex_log2_visce_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_visce_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_visce_0314/processing.rtf b/general/datasets/Gtex_log2_visce_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_visce_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_visce_0314/summary.rtf b/general/datasets/Gtex_log2_visce_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_visce_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_visce_0314/tissue.rtf b/general/datasets/Gtex_log2_visce_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_visce_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_log2_wholeb_0314/cases.rtf b/general/datasets/Gtex_log2_wholeb_0314/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_log2_wholeb_0314/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_log2_wholeb_0314/contributors.rtf b/general/datasets/Gtex_log2_wholeb_0314/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_log2_wholeb_0314/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_log2_wholeb_0314/experiment-design.rtf b/general/datasets/Gtex_log2_wholeb_0314/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_log2_wholeb_0314/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_log2_wholeb_0314/platform.rtf b/general/datasets/Gtex_log2_wholeb_0314/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_log2_wholeb_0314/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_log2_wholeb_0314/processing.rtf b/general/datasets/Gtex_log2_wholeb_0314/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_log2_wholeb_0314/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_log2_wholeb_0314/summary.rtf b/general/datasets/Gtex_log2_wholeb_0314/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_log2_wholeb_0314/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_log2_wholeb_0314/tissue.rtf b/general/datasets/Gtex_log2_wholeb_0314/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_log2_wholeb_0314/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_lung__0414/cases.rtf b/general/datasets/Gtex_lung__0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_lung__0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_lung__0414/contributors.rtf b/general/datasets/Gtex_lung__0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_lung__0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_lung__0414/experiment-design.rtf b/general/datasets/Gtex_lung__0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_lung__0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_lung__0414/platform.rtf b/general/datasets/Gtex_lung__0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_lung__0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_lung__0414/processing.rtf b/general/datasets/Gtex_lung__0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_lung__0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_lung__0414/summary.rtf b/general/datasets/Gtex_lung__0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_lung__0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_lung__0414/tissue.rtf b/general/datasets/Gtex_lung__0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_lung__0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_muscl_0414/cases.rtf b/general/datasets/Gtex_muscl_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_muscl_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_muscl_0414/contributors.rtf b/general/datasets/Gtex_muscl_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_muscl_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_muscl_0414/experiment-design.rtf b/general/datasets/Gtex_muscl_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_muscl_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_muscl_0414/platform.rtf b/general/datasets/Gtex_muscl_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_muscl_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_muscl_0414/processing.rtf b/general/datasets/Gtex_muscl_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_muscl_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_muscl_0414/summary.rtf b/general/datasets/Gtex_muscl_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_muscl_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_muscl_0414/tissue.rtf b/general/datasets/Gtex_muscl_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_muscl_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_nerve_0414/cases.rtf b/general/datasets/Gtex_nerve_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_nerve_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_nerve_0414/contributors.rtf b/general/datasets/Gtex_nerve_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_nerve_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_nerve_0414/experiment-design.rtf b/general/datasets/Gtex_nerve_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_nerve_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_nerve_0414/platform.rtf b/general/datasets/Gtex_nerve_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_nerve_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_nerve_0414/processing.rtf b/general/datasets/Gtex_nerve_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_nerve_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_nerve_0414/summary.rtf b/general/datasets/Gtex_nerve_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_nerve_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_nerve_0414/tissue.rtf b/general/datasets/Gtex_nerve_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_nerve_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_nucle_0414/cases.rtf b/general/datasets/Gtex_nucle_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_nucle_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_nucle_0414/contributors.rtf b/general/datasets/Gtex_nucle_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_nucle_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_nucle_0414/experiment-design.rtf b/general/datasets/Gtex_nucle_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_nucle_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_nucle_0414/platform.rtf b/general/datasets/Gtex_nucle_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_nucle_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_nucle_0414/processing.rtf b/general/datasets/Gtex_nucle_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_nucle_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_nucle_0414/summary.rtf b/general/datasets/Gtex_nucle_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_nucle_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_nucle_0414/tissue.rtf b/general/datasets/Gtex_nucle_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_nucle_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_ovary_0414/cases.rtf b/general/datasets/Gtex_ovary_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_ovary_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_ovary_0414/contributors.rtf b/general/datasets/Gtex_ovary_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_ovary_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_ovary_0414/experiment-design.rtf b/general/datasets/Gtex_ovary_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_ovary_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_ovary_0414/platform.rtf b/general/datasets/Gtex_ovary_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_ovary_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_ovary_0414/processing.rtf b/general/datasets/Gtex_ovary_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_ovary_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_ovary_0414/summary.rtf b/general/datasets/Gtex_ovary_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_ovary_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_ovary_0414/tissue.rtf b/general/datasets/Gtex_ovary_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_ovary_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_pancr_0414/cases.rtf b/general/datasets/Gtex_pancr_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_pancr_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_pancr_0414/contributors.rtf b/general/datasets/Gtex_pancr_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_pancr_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_pancr_0414/experiment-design.rtf b/general/datasets/Gtex_pancr_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_pancr_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_pancr_0414/platform.rtf b/general/datasets/Gtex_pancr_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_pancr_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_pancr_0414/processing.rtf b/general/datasets/Gtex_pancr_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_pancr_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_pancr_0414/summary.rtf b/general/datasets/Gtex_pancr_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_pancr_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_pancr_0414/tissue.rtf b/general/datasets/Gtex_pancr_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_pancr_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_pitui_0414/cases.rtf b/general/datasets/Gtex_pitui_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_pitui_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_pitui_0414/contributors.rtf b/general/datasets/Gtex_pitui_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_pitui_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_pitui_0414/experiment-design.rtf b/general/datasets/Gtex_pitui_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_pitui_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_pitui_0414/platform.rtf b/general/datasets/Gtex_pitui_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_pitui_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_pitui_0414/processing.rtf b/general/datasets/Gtex_pitui_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_pitui_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_pitui_0414/summary.rtf b/general/datasets/Gtex_pitui_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_pitui_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_pitui_0414/tissue.rtf b/general/datasets/Gtex_pitui_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_pitui_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_prost_0414/cases.rtf b/general/datasets/Gtex_prost_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_prost_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_prost_0414/contributors.rtf b/general/datasets/Gtex_prost_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_prost_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_prost_0414/experiment-design.rtf b/general/datasets/Gtex_prost_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_prost_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_prost_0414/platform.rtf b/general/datasets/Gtex_prost_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_prost_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_prost_0414/processing.rtf b/general/datasets/Gtex_prost_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_prost_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_prost_0414/summary.rtf b/general/datasets/Gtex_prost_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_prost_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_prost_0414/tissue.rtf b/general/datasets/Gtex_prost_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_prost_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_putam_0414/cases.rtf b/general/datasets/Gtex_putam_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_putam_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_putam_0414/contributors.rtf b/general/datasets/Gtex_putam_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_putam_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_putam_0414/experiment-design.rtf b/general/datasets/Gtex_putam_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_putam_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_putam_0414/platform.rtf b/general/datasets/Gtex_putam_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_putam_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_putam_0414/processing.rtf b/general/datasets/Gtex_putam_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_putam_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_putam_0414/summary.rtf b/general/datasets/Gtex_putam_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_putam_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_putam_0414/tissue.rtf b/general/datasets/Gtex_putam_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_putam_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_skine_0414/cases.rtf b/general/datasets/Gtex_skine_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_skine_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_skine_0414/contributors.rtf b/general/datasets/Gtex_skine_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_skine_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_skine_0414/experiment-design.rtf b/general/datasets/Gtex_skine_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_skine_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_skine_0414/platform.rtf b/general/datasets/Gtex_skine_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_skine_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_skine_0414/processing.rtf b/general/datasets/Gtex_skine_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_skine_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_skine_0414/summary.rtf b/general/datasets/Gtex_skine_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_skine_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_skine_0414/tissue.rtf b/general/datasets/Gtex_skine_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_skine_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_skinn_0414/cases.rtf b/general/datasets/Gtex_skinn_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_skinn_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_skinn_0414/contributors.rtf b/general/datasets/Gtex_skinn_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_skinn_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_skinn_0414/experiment-design.rtf b/general/datasets/Gtex_skinn_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_skinn_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_skinn_0414/platform.rtf b/general/datasets/Gtex_skinn_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_skinn_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_skinn_0414/processing.rtf b/general/datasets/Gtex_skinn_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_skinn_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_skinn_0414/summary.rtf b/general/datasets/Gtex_skinn_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_skinn_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_skinn_0414/tissue.rtf b/general/datasets/Gtex_skinn_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_skinn_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_spina_0414/cases.rtf b/general/datasets/Gtex_spina_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_spina_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_spina_0414/contributors.rtf b/general/datasets/Gtex_spina_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_spina_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_spina_0414/experiment-design.rtf b/general/datasets/Gtex_spina_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_spina_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_spina_0414/platform.rtf b/general/datasets/Gtex_spina_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_spina_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_spina_0414/processing.rtf b/general/datasets/Gtex_spina_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_spina_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_spina_0414/summary.rtf b/general/datasets/Gtex_spina_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_spina_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_spina_0414/tissue.rtf b/general/datasets/Gtex_spina_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_spina_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_stoma_0414/cases.rtf b/general/datasets/Gtex_stoma_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_stoma_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_stoma_0414/contributors.rtf b/general/datasets/Gtex_stoma_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_stoma_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_stoma_0414/experiment-design.rtf b/general/datasets/Gtex_stoma_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_stoma_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_stoma_0414/platform.rtf b/general/datasets/Gtex_stoma_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_stoma_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_stoma_0414/processing.rtf b/general/datasets/Gtex_stoma_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_stoma_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_stoma_0414/summary.rtf b/general/datasets/Gtex_stoma_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_stoma_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_stoma_0414/tissue.rtf b/general/datasets/Gtex_stoma_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_stoma_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_subcu_0414/cases.rtf b/general/datasets/Gtex_subcu_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_subcu_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_subcu_0414/contributors.rtf b/general/datasets/Gtex_subcu_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_subcu_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_subcu_0414/experiment-design.rtf b/general/datasets/Gtex_subcu_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_subcu_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_subcu_0414/platform.rtf b/general/datasets/Gtex_subcu_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_subcu_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_subcu_0414/processing.rtf b/general/datasets/Gtex_subcu_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_subcu_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_subcu_0414/summary.rtf b/general/datasets/Gtex_subcu_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_subcu_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_subcu_0414/tissue.rtf b/general/datasets/Gtex_subcu_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_subcu_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_subst_0414/cases.rtf b/general/datasets/Gtex_subst_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_subst_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_subst_0414/contributors.rtf b/general/datasets/Gtex_subst_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_subst_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_subst_0414/experiment-design.rtf b/general/datasets/Gtex_subst_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_subst_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_subst_0414/platform.rtf b/general/datasets/Gtex_subst_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_subst_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_subst_0414/processing.rtf b/general/datasets/Gtex_subst_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_subst_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_subst_0414/summary.rtf b/general/datasets/Gtex_subst_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_subst_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_subst_0414/tissue.rtf b/general/datasets/Gtex_subst_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_subst_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_testi_0414/cases.rtf b/general/datasets/Gtex_testi_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_testi_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_testi_0414/contributors.rtf b/general/datasets/Gtex_testi_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_testi_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_testi_0414/experiment-design.rtf b/general/datasets/Gtex_testi_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_testi_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_testi_0414/platform.rtf b/general/datasets/Gtex_testi_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_testi_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_testi_0414/processing.rtf b/general/datasets/Gtex_testi_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_testi_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_testi_0414/summary.rtf b/general/datasets/Gtex_testi_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_testi_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_testi_0414/tissue.rtf b/general/datasets/Gtex_testi_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_testi_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_thyro_0414/cases.rtf b/general/datasets/Gtex_thyro_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_thyro_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_thyro_0414/contributors.rtf b/general/datasets/Gtex_thyro_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_thyro_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_thyro_0414/experiment-design.rtf b/general/datasets/Gtex_thyro_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_thyro_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_thyro_0414/platform.rtf b/general/datasets/Gtex_thyro_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_thyro_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_thyro_0414/processing.rtf b/general/datasets/Gtex_thyro_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_thyro_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_thyro_0414/summary.rtf b/general/datasets/Gtex_thyro_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_thyro_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_thyro_0414/tissue.rtf b/general/datasets/Gtex_thyro_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_thyro_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_tibia_0414/cases.rtf b/general/datasets/Gtex_tibia_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_tibia_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_tibia_0414/contributors.rtf b/general/datasets/Gtex_tibia_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_tibia_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_tibia_0414/experiment-design.rtf b/general/datasets/Gtex_tibia_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_tibia_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_tibia_0414/platform.rtf b/general/datasets/Gtex_tibia_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_tibia_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_tibia_0414/processing.rtf b/general/datasets/Gtex_tibia_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_tibia_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_tibia_0414/summary.rtf b/general/datasets/Gtex_tibia_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_tibia_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_tibia_0414/tissue.rtf b/general/datasets/Gtex_tibia_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_tibia_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_uteru_0414/cases.rtf b/general/datasets/Gtex_uteru_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_uteru_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_uteru_0414/contributors.rtf b/general/datasets/Gtex_uteru_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_uteru_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_uteru_0414/experiment-design.rtf b/general/datasets/Gtex_uteru_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_uteru_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_uteru_0414/platform.rtf b/general/datasets/Gtex_uteru_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_uteru_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_uteru_0414/processing.rtf b/general/datasets/Gtex_uteru_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_uteru_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_uteru_0414/summary.rtf b/general/datasets/Gtex_uteru_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_uteru_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_uteru_0414/tissue.rtf b/general/datasets/Gtex_uteru_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_uteru_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_vagin_0414/cases.rtf b/general/datasets/Gtex_vagin_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_vagin_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_vagin_0414/contributors.rtf b/general/datasets/Gtex_vagin_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_vagin_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_vagin_0414/experiment-design.rtf b/general/datasets/Gtex_vagin_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_vagin_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_vagin_0414/platform.rtf b/general/datasets/Gtex_vagin_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_vagin_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_vagin_0414/processing.rtf b/general/datasets/Gtex_vagin_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_vagin_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_vagin_0414/summary.rtf b/general/datasets/Gtex_vagin_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_vagin_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_vagin_0414/tissue.rtf b/general/datasets/Gtex_vagin_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_vagin_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_visce_0414/cases.rtf b/general/datasets/Gtex_visce_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_visce_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_visce_0414/contributors.rtf b/general/datasets/Gtex_visce_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_visce_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_visce_0414/experiment-design.rtf b/general/datasets/Gtex_visce_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_visce_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_visce_0414/platform.rtf b/general/datasets/Gtex_visce_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_visce_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_visce_0414/processing.rtf b/general/datasets/Gtex_visce_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_visce_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_visce_0414/summary.rtf b/general/datasets/Gtex_visce_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_visce_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_visce_0414/tissue.rtf b/general/datasets/Gtex_visce_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_visce_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtex_whole_0414/cases.rtf b/general/datasets/Gtex_whole_0414/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtex_whole_0414/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtex_whole_0414/contributors.rtf b/general/datasets/Gtex_whole_0414/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtex_whole_0414/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtex_whole_0414/experiment-design.rtf b/general/datasets/Gtex_whole_0414/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtex_whole_0414/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtex_whole_0414/platform.rtf b/general/datasets/Gtex_whole_0414/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtex_whole_0414/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtex_whole_0414/processing.rtf b/general/datasets/Gtex_whole_0414/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtex_whole_0414/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtex_whole_0414/summary.rtf b/general/datasets/Gtex_whole_0414/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtex_whole_0414/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtex_whole_0414/tissue.rtf b/general/datasets/Gtex_whole_0414/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtex_whole_0414/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_adipsub_0915/cases.rtf b/general/datasets/Gtexv5_adipsub_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_adipsub_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_adipsub_0915/contributors.rtf b/general/datasets/Gtexv5_adipsub_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_adipsub_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_adipsub_0915/experiment-design.rtf b/general/datasets/Gtexv5_adipsub_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_adipsub_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_adipsub_0915/platform.rtf b/general/datasets/Gtexv5_adipsub_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_adipsub_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_adipsub_0915/processing.rtf b/general/datasets/Gtexv5_adipsub_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_adipsub_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_adipsub_0915/specifics.rtf b/general/datasets/Gtexv5_adipsub_0915/specifics.rtf
new file mode 100644
index 0000000..60a3e92
--- /dev/null
+++ b/general/datasets/Gtexv5_adipsub_0915/specifics.rtf
@@ -0,0 +1 @@
+Human Adipose Subcutaneous
\ No newline at end of file
diff --git a/general/datasets/Gtexv5_adipsub_0915/summary.rtf b/general/datasets/Gtexv5_adipsub_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_adipsub_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_adipsub_0915/tissue.rtf b/general/datasets/Gtexv5_adipsub_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_adipsub_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_adivis_0915/cases.rtf b/general/datasets/Gtexv5_adivis_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_adivis_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_adivis_0915/contributors.rtf b/general/datasets/Gtexv5_adivis_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_adivis_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_adivis_0915/experiment-design.rtf b/general/datasets/Gtexv5_adivis_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_adivis_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_adivis_0915/platform.rtf b/general/datasets/Gtexv5_adivis_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_adivis_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_adivis_0915/processing.rtf b/general/datasets/Gtexv5_adivis_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_adivis_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_adivis_0915/specifics.rtf b/general/datasets/Gtexv5_adivis_0915/specifics.rtf
new file mode 100644
index 0000000..055221e
--- /dev/null
+++ b/general/datasets/Gtexv5_adivis_0915/specifics.rtf
@@ -0,0 +1 @@
+Human Adipose Visceral Omentum
\ No newline at end of file
diff --git a/general/datasets/Gtexv5_adivis_0915/summary.rtf b/general/datasets/Gtexv5_adivis_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_adivis_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_adivis_0915/tissue.rtf b/general/datasets/Gtexv5_adivis_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_adivis_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_adrgla_0915/cases.rtf b/general/datasets/Gtexv5_adrgla_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_adrgla_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_adrgla_0915/contributors.rtf b/general/datasets/Gtexv5_adrgla_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_adrgla_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_adrgla_0915/experiment-design.rtf b/general/datasets/Gtexv5_adrgla_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_adrgla_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_adrgla_0915/platform.rtf b/general/datasets/Gtexv5_adrgla_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_adrgla_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_adrgla_0915/processing.rtf b/general/datasets/Gtexv5_adrgla_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_adrgla_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_adrgla_0915/specifics.rtf b/general/datasets/Gtexv5_adrgla_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_adrgla_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_adrgla_0915/summary.rtf b/general/datasets/Gtexv5_adrgla_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_adrgla_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_adrgla_0915/tissue.rtf b/general/datasets/Gtexv5_adrgla_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_adrgla_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_amy_0915/cases.rtf b/general/datasets/Gtexv5_amy_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_amy_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_amy_0915/contributors.rtf b/general/datasets/Gtexv5_amy_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_amy_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_amy_0915/experiment-design.rtf b/general/datasets/Gtexv5_amy_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_amy_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_amy_0915/platform.rtf b/general/datasets/Gtexv5_amy_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_amy_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_amy_0915/processing.rtf b/general/datasets/Gtexv5_amy_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_amy_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_amy_0915/specifics.rtf b/general/datasets/Gtexv5_amy_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_amy_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_amy_0915/summary.rtf b/general/datasets/Gtexv5_amy_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_amy_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_amy_0915/tissue.rtf b/general/datasets/Gtexv5_amy_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_amy_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_antctx_0915/cases.rtf b/general/datasets/Gtexv5_antctx_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_antctx_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_antctx_0915/contributors.rtf b/general/datasets/Gtexv5_antctx_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_antctx_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_antctx_0915/experiment-design.rtf b/general/datasets/Gtexv5_antctx_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_antctx_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_antctx_0915/platform.rtf b/general/datasets/Gtexv5_antctx_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_antctx_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_antctx_0915/processing.rtf b/general/datasets/Gtexv5_antctx_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_antctx_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_antctx_0915/specifics.rtf b/general/datasets/Gtexv5_antctx_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_antctx_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_antctx_0915/summary.rtf b/general/datasets/Gtexv5_antctx_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_antctx_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_antctx_0915/tissue.rtf b/general/datasets/Gtexv5_antctx_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_antctx_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_artaor_0915/cases.rtf b/general/datasets/Gtexv5_artaor_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_artaor_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_artaor_0915/contributors.rtf b/general/datasets/Gtexv5_artaor_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_artaor_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_artaor_0915/experiment-design.rtf b/general/datasets/Gtexv5_artaor_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_artaor_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_artaor_0915/platform.rtf b/general/datasets/Gtexv5_artaor_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_artaor_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_artaor_0915/processing.rtf b/general/datasets/Gtexv5_artaor_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_artaor_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_artaor_0915/specifics.rtf b/general/datasets/Gtexv5_artaor_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_artaor_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_artaor_0915/summary.rtf b/general/datasets/Gtexv5_artaor_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_artaor_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_artaor_0915/tissue.rtf b/general/datasets/Gtexv5_artaor_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_artaor_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_artcor_0915/cases.rtf b/general/datasets/Gtexv5_artcor_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_artcor_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_artcor_0915/contributors.rtf b/general/datasets/Gtexv5_artcor_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_artcor_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_artcor_0915/experiment-design.rtf b/general/datasets/Gtexv5_artcor_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_artcor_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_artcor_0915/platform.rtf b/general/datasets/Gtexv5_artcor_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_artcor_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_artcor_0915/processing.rtf b/general/datasets/Gtexv5_artcor_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_artcor_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_artcor_0915/specifics.rtf b/general/datasets/Gtexv5_artcor_0915/specifics.rtf
new file mode 100644
index 0000000..9288089
--- /dev/null
+++ b/general/datasets/Gtexv5_artcor_0915/specifics.rtf
@@ -0,0 +1 @@
+Human Artery Coronary
\ No newline at end of file
diff --git a/general/datasets/Gtexv5_artcor_0915/summary.rtf b/general/datasets/Gtexv5_artcor_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_artcor_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_artcor_0915/tissue.rtf b/general/datasets/Gtexv5_artcor_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_artcor_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_bm_0915/cases.rtf b/general/datasets/Gtexv5_bm_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_bm_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_bm_0915/contributors.rtf b/general/datasets/Gtexv5_bm_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_bm_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_bm_0915/experiment-design.rtf b/general/datasets/Gtexv5_bm_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_bm_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_bm_0915/platform.rtf b/general/datasets/Gtexv5_bm_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_bm_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_bm_0915/processing.rtf b/general/datasets/Gtexv5_bm_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_bm_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_bm_0915/specifics.rtf b/general/datasets/Gtexv5_bm_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_bm_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_bm_0915/summary.rtf b/general/datasets/Gtexv5_bm_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_bm_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_bm_0915/tissue.rtf b/general/datasets/Gtexv5_bm_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_bm_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_brce_0915/cases.rtf b/general/datasets/Gtexv5_brce_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_brce_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_brce_0915/contributors.rtf b/general/datasets/Gtexv5_brce_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_brce_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_brce_0915/experiment-design.rtf b/general/datasets/Gtexv5_brce_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_brce_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_brce_0915/platform.rtf b/general/datasets/Gtexv5_brce_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_brce_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_brce_0915/processing.rtf b/general/datasets/Gtexv5_brce_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_brce_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_brce_0915/specifics.rtf b/general/datasets/Gtexv5_brce_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_brce_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_brce_0915/summary.rtf b/general/datasets/Gtexv5_brce_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_brce_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_brce_0915/tissue.rtf b/general/datasets/Gtexv5_brce_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_brce_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_brma_0915/cases.rtf b/general/datasets/Gtexv5_brma_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_brma_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_brma_0915/contributors.rtf b/general/datasets/Gtexv5_brma_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_brma_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_brma_0915/experiment-design.rtf b/general/datasets/Gtexv5_brma_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_brma_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_brma_0915/platform.rtf b/general/datasets/Gtexv5_brma_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_brma_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_brma_0915/processing.rtf b/general/datasets/Gtexv5_brma_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_brma_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_brma_0915/specifics.rtf b/general/datasets/Gtexv5_brma_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_brma_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_brma_0915/summary.rtf b/general/datasets/Gtexv5_brma_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_brma_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_brma_0915/tissue.rtf b/general/datasets/Gtexv5_brma_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_brma_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_colsig_0915/cases.rtf b/general/datasets/Gtexv5_colsig_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_colsig_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_colsig_0915/contributors.rtf b/general/datasets/Gtexv5_colsig_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_colsig_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_colsig_0915/experiment-design.rtf b/general/datasets/Gtexv5_colsig_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_colsig_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_colsig_0915/platform.rtf b/general/datasets/Gtexv5_colsig_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_colsig_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_colsig_0915/processing.rtf b/general/datasets/Gtexv5_colsig_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_colsig_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_colsig_0915/specifics.rtf b/general/datasets/Gtexv5_colsig_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_colsig_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_colsig_0915/summary.rtf b/general/datasets/Gtexv5_colsig_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_colsig_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_colsig_0915/tissue.rtf b/general/datasets/Gtexv5_colsig_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_colsig_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_ctf_0915/cases.rtf b/general/datasets/Gtexv5_ctf_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_ctf_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_ctf_0915/contributors.rtf b/general/datasets/Gtexv5_ctf_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_ctf_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_ctf_0915/experiment-design.rtf b/general/datasets/Gtexv5_ctf_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_ctf_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_ctf_0915/platform.rtf b/general/datasets/Gtexv5_ctf_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_ctf_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_ctf_0915/processing.rtf b/general/datasets/Gtexv5_ctf_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_ctf_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_ctf_0915/specifics.rtf b/general/datasets/Gtexv5_ctf_0915/specifics.rtf
new file mode 100644
index 0000000..8515741
--- /dev/null
+++ b/general/datasets/Gtexv5_ctf_0915/specifics.rtf
@@ -0,0 +1 @@
+Cell Transformed Fibroblasts
\ No newline at end of file
diff --git a/general/datasets/Gtexv5_ctf_0915/summary.rtf b/general/datasets/Gtexv5_ctf_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_ctf_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_ctf_0915/tissue.rtf b/general/datasets/Gtexv5_ctf_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_ctf_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_gastjun_0915/cases.rtf b/general/datasets/Gtexv5_gastjun_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_gastjun_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_gastjun_0915/contributors.rtf b/general/datasets/Gtexv5_gastjun_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_gastjun_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_gastjun_0915/experiment-design.rtf b/general/datasets/Gtexv5_gastjun_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_gastjun_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_gastjun_0915/platform.rtf b/general/datasets/Gtexv5_gastjun_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_gastjun_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_gastjun_0915/processing.rtf b/general/datasets/Gtexv5_gastjun_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_gastjun_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_gastjun_0915/specifics.rtf b/general/datasets/Gtexv5_gastjun_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_gastjun_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_gastjun_0915/summary.rtf b/general/datasets/Gtexv5_gastjun_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_gastjun_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_gastjun_0915/tissue.rtf b/general/datasets/Gtexv5_gastjun_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_gastjun_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_haa_0915/cases.rtf b/general/datasets/Gtexv5_haa_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_haa_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_haa_0915/contributors.rtf b/general/datasets/Gtexv5_haa_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_haa_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_haa_0915/experiment-design.rtf b/general/datasets/Gtexv5_haa_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_haa_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_haa_0915/platform.rtf b/general/datasets/Gtexv5_haa_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_haa_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_haa_0915/processing.rtf b/general/datasets/Gtexv5_haa_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_haa_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_haa_0915/specifics.rtf b/general/datasets/Gtexv5_haa_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_haa_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_haa_0915/summary.rtf b/general/datasets/Gtexv5_haa_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_haa_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_haa_0915/tissue.rtf b/general/datasets/Gtexv5_haa_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_haa_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_hip_0915/cases.rtf b/general/datasets/Gtexv5_hip_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_hip_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_hip_0915/contributors.rtf b/general/datasets/Gtexv5_hip_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_hip_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_hip_0915/experiment-design.rtf b/general/datasets/Gtexv5_hip_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_hip_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_hip_0915/platform.rtf b/general/datasets/Gtexv5_hip_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_hip_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_hip_0915/processing.rtf b/general/datasets/Gtexv5_hip_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_hip_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_hip_0915/specifics.rtf b/general/datasets/Gtexv5_hip_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_hip_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_hip_0915/summary.rtf b/general/datasets/Gtexv5_hip_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_hip_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_hip_0915/tissue.rtf b/general/datasets/Gtexv5_hip_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_hip_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_hiptha_0915/cases.rtf b/general/datasets/Gtexv5_hiptha_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_hiptha_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_hiptha_0915/contributors.rtf b/general/datasets/Gtexv5_hiptha_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_hiptha_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_hiptha_0915/experiment-design.rtf b/general/datasets/Gtexv5_hiptha_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_hiptha_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_hiptha_0915/platform.rtf b/general/datasets/Gtexv5_hiptha_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_hiptha_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_hiptha_0915/processing.rtf b/general/datasets/Gtexv5_hiptha_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_hiptha_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_hiptha_0915/specifics.rtf b/general/datasets/Gtexv5_hiptha_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_hiptha_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_hiptha_0915/summary.rtf b/general/datasets/Gtexv5_hiptha_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_hiptha_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_hiptha_0915/tissue.rtf b/general/datasets/Gtexv5_hiptha_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_hiptha_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_kidn_0915/cases.rtf b/general/datasets/Gtexv5_kidn_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_kidn_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_kidn_0915/contributors.rtf b/general/datasets/Gtexv5_kidn_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_kidn_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_kidn_0915/experiment-design.rtf b/general/datasets/Gtexv5_kidn_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_kidn_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_kidn_0915/platform.rtf b/general/datasets/Gtexv5_kidn_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_kidn_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_kidn_0915/processing.rtf b/general/datasets/Gtexv5_kidn_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_kidn_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_kidn_0915/specifics.rtf b/general/datasets/Gtexv5_kidn_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_kidn_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_kidn_0915/summary.rtf b/general/datasets/Gtexv5_kidn_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_kidn_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_kidn_0915/tissue.rtf b/general/datasets/Gtexv5_kidn_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_kidn_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_liv_0915/cases.rtf b/general/datasets/Gtexv5_liv_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_liv_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_liv_0915/contributors.rtf b/general/datasets/Gtexv5_liv_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_liv_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_liv_0915/experiment-design.rtf b/general/datasets/Gtexv5_liv_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_liv_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_liv_0915/platform.rtf b/general/datasets/Gtexv5_liv_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_liv_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_liv_0915/processing.rtf b/general/datasets/Gtexv5_liv_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_liv_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_liv_0915/specifics.rtf b/general/datasets/Gtexv5_liv_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_liv_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_liv_0915/summary.rtf b/general/datasets/Gtexv5_liv_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_liv_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_liv_0915/tissue.rtf b/general/datasets/Gtexv5_liv_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_liv_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_musk_0915/cases.rtf b/general/datasets/Gtexv5_musk_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_musk_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_musk_0915/contributors.rtf b/general/datasets/Gtexv5_musk_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_musk_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_musk_0915/experiment-design.rtf b/general/datasets/Gtexv5_musk_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_musk_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_musk_0915/platform.rtf b/general/datasets/Gtexv5_musk_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_musk_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_musk_0915/processing.rtf b/general/datasets/Gtexv5_musk_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_musk_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_musk_0915/specifics.rtf b/general/datasets/Gtexv5_musk_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_musk_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_musk_0915/summary.rtf b/general/datasets/Gtexv5_musk_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_musk_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_musk_0915/tissue.rtf b/general/datasets/Gtexv5_musk_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_musk_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_ov_0915/cases.rtf b/general/datasets/Gtexv5_ov_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_ov_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_ov_0915/contributors.rtf b/general/datasets/Gtexv5_ov_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_ov_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_ov_0915/experiment-design.rtf b/general/datasets/Gtexv5_ov_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_ov_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_ov_0915/platform.rtf b/general/datasets/Gtexv5_ov_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_ov_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_ov_0915/processing.rtf b/general/datasets/Gtexv5_ov_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_ov_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_ov_0915/specifics.rtf b/general/datasets/Gtexv5_ov_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_ov_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_ov_0915/summary.rtf b/general/datasets/Gtexv5_ov_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_ov_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_ov_0915/tissue.rtf b/general/datasets/Gtexv5_ov_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_ov_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_pit_0915/cases.rtf b/general/datasets/Gtexv5_pit_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_pit_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_pit_0915/contributors.rtf b/general/datasets/Gtexv5_pit_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_pit_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_pit_0915/experiment-design.rtf b/general/datasets/Gtexv5_pit_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_pit_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_pit_0915/platform.rtf b/general/datasets/Gtexv5_pit_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_pit_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_pit_0915/processing.rtf b/general/datasets/Gtexv5_pit_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_pit_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_pit_0915/specifics.rtf b/general/datasets/Gtexv5_pit_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_pit_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_pit_0915/summary.rtf b/general/datasets/Gtexv5_pit_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_pit_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_pit_0915/tissue.rtf b/general/datasets/Gtexv5_pit_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_pit_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_prost_0915/cases.rtf b/general/datasets/Gtexv5_prost_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_prost_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_prost_0915/contributors.rtf b/general/datasets/Gtexv5_prost_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_prost_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_prost_0915/experiment-design.rtf b/general/datasets/Gtexv5_prost_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_prost_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_prost_0915/platform.rtf b/general/datasets/Gtexv5_prost_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_prost_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_prost_0915/processing.rtf b/general/datasets/Gtexv5_prost_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_prost_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_prost_0915/specifics.rtf b/general/datasets/Gtexv5_prost_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_prost_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_prost_0915/summary.rtf b/general/datasets/Gtexv5_prost_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_prost_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_prost_0915/tissue.rtf b/general/datasets/Gtexv5_prost_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_prost_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_salgl_0915/cases.rtf b/general/datasets/Gtexv5_salgl_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_salgl_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_salgl_0915/contributors.rtf b/general/datasets/Gtexv5_salgl_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_salgl_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_salgl_0915/experiment-design.rtf b/general/datasets/Gtexv5_salgl_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_salgl_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_salgl_0915/platform.rtf b/general/datasets/Gtexv5_salgl_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_salgl_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_salgl_0915/processing.rtf b/general/datasets/Gtexv5_salgl_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_salgl_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_salgl_0915/specifics.rtf b/general/datasets/Gtexv5_salgl_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_salgl_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_salgl_0915/summary.rtf b/general/datasets/Gtexv5_salgl_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_salgl_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_salgl_0915/tissue.rtf b/general/datasets/Gtexv5_salgl_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_salgl_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_sks_0915/cases.rtf b/general/datasets/Gtexv5_sks_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_sks_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_sks_0915/contributors.rtf b/general/datasets/Gtexv5_sks_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_sks_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_sks_0915/experiment-design.rtf b/general/datasets/Gtexv5_sks_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_sks_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_sks_0915/platform.rtf b/general/datasets/Gtexv5_sks_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_sks_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_sks_0915/processing.rtf b/general/datasets/Gtexv5_sks_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_sks_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_sks_0915/specifics.rtf b/general/datasets/Gtexv5_sks_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_sks_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_sks_0915/summary.rtf b/general/datasets/Gtexv5_sks_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_sks_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_sks_0915/tissue.rtf b/general/datasets/Gtexv5_sks_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_sks_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_sto_0915/cases.rtf b/general/datasets/Gtexv5_sto_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_sto_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_sto_0915/contributors.rtf b/general/datasets/Gtexv5_sto_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_sto_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_sto_0915/experiment-design.rtf b/general/datasets/Gtexv5_sto_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_sto_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_sto_0915/platform.rtf b/general/datasets/Gtexv5_sto_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_sto_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_sto_0915/processing.rtf b/general/datasets/Gtexv5_sto_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_sto_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_sto_0915/specifics.rtf b/general/datasets/Gtexv5_sto_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_sto_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_sto_0915/summary.rtf b/general/datasets/Gtexv5_sto_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_sto_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_sto_0915/tissue.rtf b/general/datasets/Gtexv5_sto_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_sto_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_test_0915/cases.rtf b/general/datasets/Gtexv5_test_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_test_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_test_0915/contributors.rtf b/general/datasets/Gtexv5_test_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_test_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_test_0915/experiment-design.rtf b/general/datasets/Gtexv5_test_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_test_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_test_0915/platform.rtf b/general/datasets/Gtexv5_test_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_test_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_test_0915/processing.rtf b/general/datasets/Gtexv5_test_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_test_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_test_0915/specifics.rtf b/general/datasets/Gtexv5_test_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_test_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_test_0915/summary.rtf b/general/datasets/Gtexv5_test_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_test_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_test_0915/tissue.rtf b/general/datasets/Gtexv5_test_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_test_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_thy_0915/cases.rtf b/general/datasets/Gtexv5_thy_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_thy_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_thy_0915/contributors.rtf b/general/datasets/Gtexv5_thy_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_thy_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_thy_0915/experiment-design.rtf b/general/datasets/Gtexv5_thy_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_thy_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_thy_0915/platform.rtf b/general/datasets/Gtexv5_thy_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_thy_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_thy_0915/processing.rtf b/general/datasets/Gtexv5_thy_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_thy_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_thy_0915/specifics.rtf b/general/datasets/Gtexv5_thy_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_thy_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_thy_0915/summary.rtf b/general/datasets/Gtexv5_thy_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_thy_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_thy_0915/tissue.rtf b/general/datasets/Gtexv5_thy_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_thy_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_ut_0915/cases.rtf b/general/datasets/Gtexv5_ut_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_ut_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_ut_0915/contributors.rtf b/general/datasets/Gtexv5_ut_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_ut_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_ut_0915/experiment-design.rtf b/general/datasets/Gtexv5_ut_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_ut_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_ut_0915/platform.rtf b/general/datasets/Gtexv5_ut_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_ut_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_ut_0915/processing.rtf b/general/datasets/Gtexv5_ut_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_ut_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_ut_0915/specifics.rtf b/general/datasets/Gtexv5_ut_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_ut_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_ut_0915/summary.rtf b/general/datasets/Gtexv5_ut_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_ut_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_ut_0915/tissue.rtf b/general/datasets/Gtexv5_ut_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_ut_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/Gtexv5_wbl_0915/cases.rtf b/general/datasets/Gtexv5_wbl_0915/cases.rtf
new file mode 100644
index 0000000..3453126
--- /dev/null
+++ b/general/datasets/Gtexv5_wbl_0915/cases.rtf
@@ -0,0 +1,5 @@
+The Genotype-Tissue Expression project (GTEx) aims to create a comprehensive public atlas of gene expression and regulation across multiple human tissues. The resource will provide valuable insights in to the mechanisms of gene regulation, aid in the interpretation of genome wide association studies, and enable studies of expression quantitative trait loci (eQTLs), alternative splicing, and the tissue speciï¬city of gene regulatory mechanisms.
+
+The GTEx project recently completed an initial pilot phase during which >185 donor DNAs were genotyped using high density SNP and exome arrays. RNA expression was proï¬led on multiple tissues from these donors (from 9 to 30) by both array-based methods and RNA sequencing, to an average depth of 50 million reads. These pilot phase data have been made available to the public through davailable through the database of Genotype and Phenotype (dbGaP).
+
+For more information about the GTEx project, please visit the About GTEx page, view the Consortium Members, or read the Publication Policy. Additional GTEx resources such as funding opportunities and information for donors are also available on the NIH Common Fund and NHGRI websites respectively.
diff --git a/general/datasets/Gtexv5_wbl_0915/contributors.rtf b/general/datasets/Gtexv5_wbl_0915/contributors.rtf
new file mode 100644
index 0000000..aae39a0
--- /dev/null
+++ b/general/datasets/Gtexv5_wbl_0915/contributors.rtf
@@ -0,0 +1 @@
+Please review and cite: John Lonsdale, Jeffrey Thomas, Mike Salvatore, Rebecca Phillips, Edmund Lo, Saboor Shad, Richard Hasz, Gary Walters, Fernando Garcia, Nancy Young, Barbara Foster, Mike Moser, Ellen Karasik, Bryan Gillard, Kimberley Ramsey, Susan Sullivan, Jason Bridge, Harold Magazine, John Syron, Johnelle Fleming, Laura Siminoff, Heather Traino, Maghboeba Mosavel, Laura Barker, Scott Jewell, Dan Rohrer, Dan Maxim, Dana Filkins, Philip Harbach, Eddie Cortadillo, Bree Berghuis, Lisa Turner, Eric Hudson, Kristin Feenstra, Leslie Sobin, James Robb, Phillip Branton, Greg Korzeniewski, Charles Shive, David Tabor, Liqun Qi, Kevin Groch, Sreenath Nampally, Steve Buia, Angela Zimmerman, Anna Smith, Robin Burges, Karna Robinson, Kim Valentino, Deborah Bradbury, Mark Cosentino, Norma Diaz-Mayoral, Mary Kennedy, Theresa Engel, Penelope Williams, Kenyon Erickson, Kristin Ardlie, Wendy Winckler, Gad Getz, David DeLuca, Daniel MacArthur, Manolis Kellis, Alexander Thomson, Taylor Young, Ellen Gelfand, Molly Donovan, Yan Meng, George Grant, Deborah Mash, Yvonne Marcus, Margaret Basile, Jun Liu, Jun Zhu, Zhidong Tu, Nancy J Cox, Dan L Nicolae, Eric R Gamazon, Hae Kyung Im, Anuar Konkashbaev, Jonathan Pritchard, Matthew Stevens, Timothèe Flutre, Xiaoquan Wen, Emmanouil T Dermitzakis, Tuuli Lappalainen, Roderic Guigo, Jean Monlong, Michael Sammeth, Daphne Koller, Alexis Battle, Sara Mostafavi, Mark McCarthy, Manual Rivas, Julian Maller, Ivan Rusyn, Andrew Nobel, Fred Wright, Andrey Shabalin, Mike Feolo, Nataliya Sharopova, Anne Sturcke, Justin Paschal, James M Anderson, Elizabeth L Wilder, Leslie K Derr, Eric D Green, Jeffery P Struewing, Gary Temple, Simona Volpi, Joy T Boyer, Elizabeth J Thomson, Mark S Guyer, Cathy Ng, Assya Abdallah, Deborah Colantuoni, Thomas R Insel, Susan E Koester, A Roger Little, Patrick K Bender, Thomas Lehner, Yin Yao, Carolyn C Compton, Jimmie B Vaught, Sherilyn Sawyer, Nicole C Lockhart, Joanne Demchok & Helen F Moore. Nature Genetics 45, 580–585 (2013).
diff --git a/general/datasets/Gtexv5_wbl_0915/experiment-design.rtf b/general/datasets/Gtexv5_wbl_0915/experiment-design.rtf
new file mode 100644
index 0000000..5e876e0
--- /dev/null
+++ b/general/datasets/Gtexv5_wbl_0915/experiment-design.rtf
@@ -0,0 +1 @@
+GTEx samples are collected from deceased donors at low post-mortem intervals and preserved in PAXgene fixative prior to DNA and RNA extraction.
diff --git a/general/datasets/Gtexv5_wbl_0915/platform.rtf b/general/datasets/Gtexv5_wbl_0915/platform.rtf
new file mode 100644
index 0000000..f276bf8
--- /dev/null
+++ b/general/datasets/Gtexv5_wbl_0915/platform.rtf
@@ -0,0 +1,3 @@
+Expression
+
+RPKM data are used as produced by RNA-SeQC. Filter on >=10 individuals having >0.1RPKM. Log and quantile normalize the expression values across all samples. Outlier correction: for each gene, rank values across samples then map to a standard normal.
diff --git a/general/datasets/Gtexv5_wbl_0915/processing.rtf b/general/datasets/Gtexv5_wbl_0915/processing.rtf
new file mode 100644
index 0000000..6635893
--- /dev/null
+++ b/general/datasets/Gtexv5_wbl_0915/processing.rtf
@@ -0,0 +1,102 @@
+Analysis Methods
+
+Preprocessing
+
+RNA-seq
+
+RNA-seq was performed using the Illumina TruSeq library construction protocol. This is a non-strand specific polyA+ selected library. The sequencing produced 76-bp paired end reads.
+
+See also:How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
+
+Alignment to the HG19 human genome was performed using Tophat v1.1.4 assisted by the GENCODE v12 transcriptome definition. In a post processing step, unaligned reads are reintroduced into the bam. The final bam contains aligned and unaligned reads, marked duplicates, quality score recalibration. It should be noted that Tophat produces multiple mappings for some reads, but in post processing one read is flagged as the primary alignment.
+
+Genotyping
+
+DNA samples that are sent to the Broad Institute Genetic Analysis Platform for genotyping, are placed on 96-well plates using the Illumina HumanOmni5-4v1_B SNP array. Omni genotypes are called using GenomeStudio v2010.3 with the calling algorithm/genotyping module version 1.8.4 using the default cluster file HumanOmni5-4v1-Multi_B.egt. Called genotypes are run through a standard QC pipeline and only samples passing a call rate threshold of 97%, and passing genetic fingerprint and gender concordance are passed. For the final eQTL analysis, the following filters were applied: call rate (< 90%), low HWE (pValue < 1E-6) or are monormorphic.
+
+Expression Quantification
+
+Gene/Transcript Model
+
+Gencode Version 12
+Contig names modified to match the reference genome used for alignment
+Procedure for collapsing transcript model into gene model
+
+Primary source: gencode.v12
+List exons as a set of intervals, discarding any labeled as 'retained_intron' and retaining only coding and linc rna.
+Create a separate bin for other types of transcripts and process them independently.
+Merge overlapping intervals.
+Discard intervals associated with multiple genes.
+Map intervals back to gene identifiers and output in GTF format.
+Quantification
+
+For gene/exon level read count and gene level RPKM values, we filter reads based on the requirements:
+
+Reads must have be uniquely mapped (for tophat this is mapping quality > 3; == 255).
+Reads must have proper pairs.
+Alignment distance must be <=6.
+Reads must be contained 100% within exon boundaries. Reads overlapping introns are not counted.
+Exon
+
+For exon read counts, if a read overlaps multiple exons, then then a fractional value equal to the portion of the read contained within that exon is allotted.
+
+Transcript
+
+Transcript-level quantification is provided by Flux Capacitor.
+
+eQTL Analysis
+
+QC and Sample Exclusion Process
+
+D statistic outliers are removed.
+Gender-specific expression outliers are removed.
+Samples with less than 10 million mapped reads are removed.
+In the case of replicates, the samples with the greater number of reads are chosen.
+Covariates
+
+3 Genotyping PCs.
+15 Peer factors:
+
+
+The input to PEER are the post-normalization expression values described below.
+Gender.
+Expression
+
+RPKM data are used as produced by RNA-SeQC.
+Filter on >=10 individuals having >0.1RPKM.
+Log and quantile normalize the expression values across all samples.
+Outlier correction: for each gene, rank values across samples then map to a standard normal.
+Genotypes
+
+Imputation-based genotypes:
+Call Rate Threshold 95%.
+Info score Threshold 0.4.
+Minor Allele Frequency >= 5%.
+Sex chromosomes have been excluded excluded.
+Matrix eQTL Parameters
+
+Produced for radius +-1mb from TSS.
+P value threshold set to 1 to emit all p-values.
+Storey FDR
+
+The Storey q-value method was applied using the public R package with default values.
+eQTLs were filtered for an FDR <=5%.
+Tissues
+
+There are 9 Tissues that have sufficient sample numbers (n > 80).
+
+Adipose_Subcutaneous
+Artery_Tibial
+Heart_Left_Ventricle
+Lung
+Muscle_Skeletal
+Nerve_Tibial
+Skin_Sun_Exposed_Lower_leg
+Thyroid
+Whole_Blood
+
+Note: RPKM original values that we enter in GeneNetwork have been log2 transformed after added 1, then values lower than 2.0 were transformed to 0 (zero).
+
+Read Bits of DNA blog: GTEx is throwing away 90% of their data and response to: "GTEx is throwing away 90% of their data. by Manolis Dermitzakis, Gad Getz, Krisitn Ardlie, Roderic Guigo for the GTEx consortium.
+
+See also: How to Evaluate and Use Human and Mouse mRNA Data Sets (e.g. GTEx)
diff --git a/general/datasets/Gtexv5_wbl_0915/specifics.rtf b/general/datasets/Gtexv5_wbl_0915/specifics.rtf
new file mode 100644
index 0000000..80bf41d
--- /dev/null
+++ b/general/datasets/Gtexv5_wbl_0915/specifics.rtf
@@ -0,0 +1,10 @@
+2015-09-14: The Genotype-Tissue Expression (GTEx) is providing a comprehensive atlas of gene expression and regulation across 53 human tissues. The latest GTEx data release (dbGaP release phs000424.v5.p1) is now available on GeneNetwork.
+
+
+
+Note: Please disregard confusing legend provided in Study tab of the study page which claims that study contains 552 subjects with genotypes - those totals are counts of subjects with all molecular data types, not just molecular genotypes.
+
+More detailed representation of subject counts in molecular datasets (including genotypes) may be found in 'Molecular Data' tab at Common Fund (CF) Genotype-Tissue Expression Project (GTEx) dbGaP Study Accession: phs000424.v5.p1.
+
diff --git a/general/datasets/Gtexv5_wbl_0915/summary.rtf b/general/datasets/Gtexv5_wbl_0915/summary.rtf
new file mode 100644
index 0000000..dff008b
--- /dev/null
+++ b/general/datasets/Gtexv5_wbl_0915/summary.rtf
@@ -0,0 +1,3 @@
+The Genotype-Tissue Expression (GTEx) project is a collaborative effort that aims to identify correlations between genotype and tissue-specific gene expression levels that will help identify regions of the genome that influence whether and how much a gene is expressed. GTEx is funded through the Common Fund, and managed by the NIH Office of the Director in partnership with the National Human Genome Research Institute, National Institute of Mental Health, the National Cancer Institute, the National Center for Biotechnology Information at the National Library of Medicine, the National Heart, Lung and Blood Institute, the National Institute on Drug Abuse, and the National Institute of Neurological Diseases and Stroke, all part of NIH. This series of 837 samples represents multiple tissues collected from 102 GTEX donors and 1 control cell line. In total, 30 tissue sites are represented including Adipose, Artery, Heart, Lung, Whole Blood, Muscle, Skin, and 11 brain subregions. RNA-seq expression data, robust clinical data, pathological annotations, and genotypes are also available for these samples from dbGaP (http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000424.v2.p1) and the GTEx portal (www.broadinstitute.org/gtex). While GTEx is no longer generating Affymetrix expression data, donor enrollment continues and is expected to reach 1,000 by the end of 2015. Updates to the GTEx data in dbGaP and the GTEx Portal will be made periodically. contributor: GTEx Laboratory, Data Analysis, and Coordinating Center (LDACC) contributor: The Broad Institute of MIT and Harvard (LDACC PIs: Kristin Ardlie and Gaddy Getz).
+
+WU-Minn HCP Consortium Open Access Data Use Terms
diff --git a/general/datasets/Gtexv5_wbl_0915/tissue.rtf b/general/datasets/Gtexv5_wbl_0915/tissue.rtf
new file mode 100644
index 0000000..7e60b80
--- /dev/null
+++ b/general/datasets/Gtexv5_wbl_0915/tissue.rtf
@@ -0,0 +1,3 @@
+GTEx explore all tissues:
+
+
diff --git a/general/datasets/HBTRC-MLC_0611/acknowledgment.rtf b/general/datasets/HBTRC-MLC_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC-MLC_0611/cases.rtf b/general/datasets/HBTRC-MLC_0611/cases.rtf
new file mode 100644
index 0000000..e64114d
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_0611/cases.rtf
@@ -0,0 +1,4156 @@
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
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+
+ | 510 |
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+ AD |
+ NA |
+ 6227_VC_A_0080 |
+
+
+ | 511 |
+ HB_598_AD |
+ AD |
+ NA |
+ 6231_VC_A_1479 |
+
+
+ | 512 |
+ HB_605_AD |
+ AD |
+ NA |
+ 6261_VC_A_0084 |
+
+
+ | 513 |
+ HB_608_AD |
+ AD |
+ NA |
+ 6268_CR_A_0525 |
+
+
+ | 514 |
+ HB_611_AD |
+ AD |
+ NA |
+ 6279_VC_A_0089 |
+
+
+ | 515 |
+ HB_612_AD |
+ AD |
+ NA |
+ 6280_VC_A_0091 |
+
+
+ | 516 |
+ HB_613_AD |
+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/HBTRC-MLC_0611/experiment-design.rtf b/general/datasets/HBTRC-MLC_0611/experiment-design.rtf
new file mode 100644
index 0000000..3b0c224
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_0611/experiment-design.rtf
@@ -0,0 +1 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
diff --git a/general/datasets/HBTRC-MLC_0611/notes.rtf b/general/datasets/HBTRC-MLC_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC-MLC_0611/summary.rtf b/general/datasets/HBTRC-MLC_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC-MLC_AD_0611/acknowledgment.rtf b/general/datasets/HBTRC-MLC_AD_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_AD_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC-MLC_AD_0611/cases.rtf b/general/datasets/HBTRC-MLC_AD_0611/cases.rtf
new file mode 100644
index 0000000..e64114d
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_AD_0611/cases.rtf
@@ -0,0 +1,4156 @@
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
+ NA |
+ 5370_PF_A_1400 |
+
+
+ | 364 |
+ HB_259_AD |
+ AD |
+ NA |
+ 5371_PF_A_2636 |
+
+
+ | 365 |
+ HB_260_AD |
+ AD |
+ NA |
+ 5375_VC_A_0188 |
+
+
+ | 366 |
+ HB_263_AD |
+ AD |
+ NA |
+ 5381_VC_A_0022 |
+
+
+ | 367 |
+ HB_265_AD |
+ AD |
+ NA |
+ 5385_VC_A_1402 |
+
+
+ | 368 |
+ HB_267_AD |
+ AD |
+ NA |
+ 5389_VC_A_0928 |
+
+
+ | 369 |
+ HB_268_AD |
+ AD |
+ NA |
+ 5390_CR_A_0151 |
+
+
+ | 370 |
+ HB_273_AD |
+ AD |
+ NA |
+ 5400_PF_A_2645 |
+
+
+ | 371 |
+ HB_274_AD |
+ AD |
+ NA |
+ 5401_VC_A_0931 |
+
+
+ | 372 |
+ HB_275_AD |
+ AD |
+ NA |
+ 5404_PF_A_2648 |
+
+
+ | 373 |
+ HB_276_AD |
+ AD |
+ NA |
+ 5406_VC_A_0933 |
+
+
+ | 374 |
+ HB_277_AD |
+ AD |
+ NA |
+ 5407_PF_A_2651 |
+
+
+ | 375 |
+ HB_280_AD |
+ AD |
+ NA |
+ 5412_VC_A_0935 |
+
+
+ | 376 |
+ HB_281_AD |
+ AD |
+ NA |
+ 5413_PF_A_2657 |
+
+
+ | 377 |
+ HB_283_AD |
+ AD |
+ NA |
+ 5419_VC_A_0937 |
+
+
+ | 378 |
+ HB_284_AD |
+ AD |
+ NA |
+ 5420_VC_A_0939 |
+
+
+ | 379 |
+ HB_285_AD |
+ AD |
+ NA |
+ 5421_CR_A_0432 |
+
+
+ | 380 |
+ HB_286_AD |
+ AD |
+ NA |
+ 5423_PF_A_2660 |
+
+
+ | 381 |
+ HB_288_AD |
+ AD |
+ NA |
+ 5425_PF_A_2666 |
+
+
+ | 382 |
+ HB_289_AD |
+ AD |
+ NA |
+ 5426_VC_A_1405 |
+
+
+ | 383 |
+ HB_290_AD |
+ AD |
+ NA |
+ 5433_VC_A_0434 |
+
+
+ | 384 |
+ HB_296_AD |
+ AD |
+ NA |
+ 5456_PF_A_2675 |
+
+
+ | 385 |
+ HB_299_AD |
+ AD |
+ NA |
+ 5461_VC_A_0192 |
+
+
+ | 386 |
+ HB_302_AD |
+ AD |
+ NA |
+ 5465_PF_A_2678 |
+
+
+ | 387 |
+ HB_303_AD |
+ AD |
+ NA |
+ 5469_VC_A_1417 |
+
+
+ | 388 |
+ HB_305_AD |
+ AD |
+ NA |
+ 5479_PF_A_1421 |
+
+
+ | 389 |
+ HB_306_AD |
+ AD |
+ NA |
+ 5480_VC_A_0437 |
+
+
+ | 390 |
+ HB_307_AD |
+ AD |
+ NA |
+ 5482_VC_A_0028 |
+
+
+ | 391 |
+ HB_308_AD |
+ AD |
+ NA |
+ 5483_VC_A_0941 |
+
+
+ | 392 |
+ HB_309_AD |
+ AD |
+ NA |
+ 5487_CR_A_0441 |
+
+
+ | 393 |
+ HB_310_AD |
+ AD |
+ NA |
+ 5488_CR_A_0194 |
+
+
+ | 394 |
+ HB_312_AD |
+ AD |
+ NA |
+ 5500_VC_A_0198 |
+
+
+ | 395 |
+ HB_313_AD |
+ AD |
+ NA |
+ 5502_PF_A_2684 |
+
+
+ | 396 |
+ HB_315_AD |
+ AD |
+ NA |
+ 5513_PF_A_2687 |
+
+
+ | 397 |
+ HB_316_AD |
+ AD |
+ NA |
+ 5516_PF_A_2690 |
+
+
+ | 398 |
+ HB_317_AD |
+ AD |
+ NA |
+ 5517_PF_A_2693 |
+
+
+ | 399 |
+ HB_318_AD |
+ AD |
+ NA |
+ 5518_CR_A_0030 |
+
+
+ | 400 |
+ HB_319_AD |
+ AD |
+ NA |
+ 5519_CR_A_2695 |
+
+
+ | 401 |
+ HB_320_AD |
+ AD |
+ NA |
+ 5520_PF_A_2699 |
+
+
+ | 402 |
+ HB_322_AD |
+ AD |
+ NA |
+ 5527_VC_A_0945 |
+
+
+ | 403 |
+ HB_325_AD |
+ AD |
+ NA |
+ 5532_PF_A_2702 |
+
+
+ | 404 |
+ HB_328_AD |
+ AD |
+ NA |
+ 5541_PF_A_2705 |
+
+
+ | 405 |
+ HB_330_AD |
+ AD |
+ NA |
+ 5544_VC_A_0201 |
+
+
+ | 406 |
+ HB_334_AD |
+ AD |
+ NA |
+ 5554_VC_A_0452 |
+
+
+ | 407 |
+ HB_335_AD |
+ AD |
+ NA |
+ 5557_VC_A_0950 |
+
+
+ | 408 |
+ HB_337_AD |
+ AD |
+ NA |
+ 5560_VC_A_0204 |
+
+
+ | 409 |
+ HB_342_AD |
+ AD |
+ NA |
+ 5571_PF_A_1430 |
+
+
+ | 410 |
+ HB_345_AD |
+ AD |
+ NA |
+ 5583_PF_A_2708 |
+
+
+ | 411 |
+ HB_347_AD |
+ AD |
+ NA |
+ 5589_PF_A_2714 |
+
+
+ | 412 |
+ HB_349_AD |
+ AD |
+ NA |
+ 5592_PF_A_2717 |
+
+
+ | 413 |
+ HB_352_AD |
+ AD |
+ NA |
+ 5604_VC_A_0037 |
+
+
+ | 414 |
+ HB_353_AD |
+ AD |
+ NA |
+ 5607_PF_A_2723 |
+
+
+ | 415 |
+ HB_356_AD |
+ AD |
+ NA |
+ 5615_VC_A_0041 |
+
+
+ | 416 |
+ HB_357_AD |
+ AD |
+ NA |
+ 5616_CR_A_0127 |
+
+
+ | 417 |
+ HB_358_AD |
+ AD |
+ NA |
+ 5617_CR_A_0456 |
+
+
+ | 418 |
+ HB_359_AD |
+ AD |
+ NA |
+ 5618_CR_A_0044 |
+
+
+ | 419 |
+ HB_362_AD |
+ AD |
+ NA |
+ 5625_CR_A_2495 |
+
+
+ | 420 |
+ HB_363_AD |
+ AD |
+ NA |
+ 5626_CR_A_2498 |
+
+
+ | 421 |
+ HB_364_AD |
+ AD |
+ NA |
+ 5629_CR_A_0390 |
+
+
+ | 422 |
+ HB_369_AD |
+ AD |
+ NA |
+ 5643_VC_A_1143 |
+
+
+ | 423 |
+ HB_373_AD |
+ AD |
+ NA |
+ 5654_VC_A_0047 |
+
+
+ | 424 |
+ HB_375_AD |
+ AD |
+ NA |
+ 5660_CR_A_0462 |
+
+
+ | 425 |
+ HB_376_AD |
+ AD |
+ NA |
+ 5661_VC_A_0464 |
+
+
+ | 426 |
+ HB_377_AD |
+ AD |
+ NA |
+ 5667_VC_A_2509 |
+
+
+ | 427 |
+ HB_378_AD |
+ AD |
+ NA |
+ 5668_VC_A_1438 |
+
+
+ | 428 |
+ HB_383_AD |
+ AD |
+ NA |
+ 5686_CR_A_2728 |
+
+
+ | 429 |
+ HB_386_AD |
+ AD |
+ NA |
+ 5695_VC_A_0953 |
+
+
+ | 430 |
+ HB_389_AD |
+ AD |
+ NA |
+ 5700_VC_A_2514 |
+
+
+ | 431 |
+ HB_391_AD |
+ AD |
+ NA |
+ 5705_CR_A_0474 |
+
+
+ | 432 |
+ HB_392_AD |
+ AD |
+ NA |
+ 5706_VC_A_0476 |
+
+
+ | 433 |
+ HB_394_AD |
+ AD |
+ NA |
+ 5713_VC_A_0479 |
+
+
+ | 434 |
+ HB_397_AD |
+ AD |
+ NA |
+ 5721_CR_A_0210 |
+
+
+ | 435 |
+ HB_404_AD |
+ AD |
+ NA |
+ 5735_CR_A_0489 |
+
+
+ | 436 |
+ HB_406_AD |
+ AD |
+ NA |
+ 5744_CR_A_0960 |
+
+
+ | 437 |
+ HB_409_AD |
+ AD |
+ NA |
+ 5749_CR_A_0159 |
+
+
+ | 438 |
+ HB_410_AD |
+ AD |
+ NA |
+ 5751_CR_A_2518 |
+
+
+ | 439 |
+ HB_411_AD |
+ AD |
+ NA |
+ 5755_CR_A_2731 |
+
+
+ | 440 |
+ HB_413_AD |
+ AD |
+ NA |
+ 5766_VC_A_0214 |
+
+
+ | 441 |
+ HB_419_AD |
+ AD |
+ NA |
+ 5790_VC_A_0217 |
+
+
+ | 442 |
+ HB_420_AD |
+ AD |
+ NA |
+ 5796_CR_A_0964 |
+
+
+ | 443 |
+ HB_428_AD |
+ AD |
+ NA |
+ 5811_CR_A_2524 |
+
+
+ | 444 |
+ HB_429_AD |
+ AD |
+ NA |
+ 5819_CR_A_2527 |
+
+
+ | 445 |
+ HB_430_AD |
+ AD |
+ NA |
+ 5822_CR_A_2530 |
+
+
+ | 446 |
+ HB_434_AD |
+ AD |
+ NA |
+ 5828_CR_A_2533 |
+
+
+ | 447 |
+ HB_435_AD |
+ AD |
+ NA |
+ 5831_CR_A_0222 |
+
+
+ | 448 |
+ HB_437_AD |
+ AD |
+ NA |
+ 5839_CR_A_2539 |
+
+
+ | 449 |
+ HB_438_AD |
+ AD |
+ NA |
+ 5843_CR_A_0227 |
+
+
+ | 450 |
+ HB_439_AD |
+ AD |
+ NA |
+ 5845_CR_A_0230 |
+
+
+ | 451 |
+ HB_441_AD |
+ AD |
+ NA |
+ 5849_CR_A_0233 |
+
+
+ | 452 |
+ HB_442_AD |
+ AD |
+ NA |
+ 5850_CR_A_0495 |
+
+
+ | 453 |
+ HB_445_AD |
+ AD |
+ NA |
+ 5858_CR_A_0969 |
+
+
+ | 454 |
+ HB_448_AD |
+ AD |
+ NA |
+ 5864_CR_A_0974 |
+
+
+ | 455 |
+ HB_451_AD |
+ AD |
+ NA |
+ 5871_CR_A_2542 |
+
+
+ | 456 |
+ HB_454_AD |
+ AD |
+ NA |
+ 5879_CR_A_2545 |
+
+
+ | 457 |
+ HB_455_AD |
+ AD |
+ NA |
+ 5887_CR_A_0976_Bis |
+
+
+ | 458 |
+ HB_459_AD |
+ AD |
+ NA |
+ 5898_CR_A_2548 |
+
+
+ | 459 |
+ HB_460_AD |
+ AD |
+ NA |
+ 5900_VC_A_0237 |
+
+
+ | 460 |
+ HB_461_AD |
+ AD |
+ NA |
+ 5901_CR_A_0239 |
+
+
+ | 461 |
+ HB_469_AD |
+ AD |
+ NA |
+ 5914_CR_A_2554 |
+
+
+ | 462 |
+ HB_471_AD |
+ AD |
+ NA |
+ 5922_VC_A_0246 |
+
+
+ | 463 |
+ HB_473_AD |
+ AD |
+ NA |
+ 5927_CR_A_2560 |
+
+
+ | 464 |
+ HB_474_AD |
+ AD |
+ NA |
+ 5933_VC_A_1071 |
+
+
+ | 465 |
+ HB_477_AD |
+ AD |
+ NA |
+ 5939_CR_A_1151 |
+
+
+ | 466 |
+ HB_479_AD |
+ AD |
+ NA |
+ 5945_VC_A_0983 |
+
+
+ | 467 |
+ HB_484_AD |
+ AD |
+ NA |
+ 5956_CR_A_0123 |
+
+
+ | 468 |
+ HB_489_AD |
+ AD |
+ NA |
+ 5968_VC_A_1075 |
+
+
+ | 469 |
+ HB_491_AD |
+ AD |
+ NA |
+ 5971_CR_A_0119 |
+
+
+ | 470 |
+ HB_492_AD |
+ AD |
+ NA |
+ 5972_VC_A_0251 |
+
+
+ | 471 |
+ HB_494_AD |
+ AD |
+ NA |
+ 5979_CR_A_0115 |
+
+
+ | 472 |
+ HB_498_AD |
+ AD |
+ NA |
+ 5988_VC_A_0503 |
+
+
+ | 473 |
+ HB_502_AD |
+ AD |
+ NA |
+ 5994_PF_A_1605 |
+
+
+ | 474 |
+ HB_503_AD |
+ AD |
+ NA |
+ 5995_CR_A_2563 |
+
+
+ | 475 |
+ HB_510_AD |
+ AD |
+ NA |
+ 6017_CR_A_0048 |
+
+
+ | 476 |
+ HB_514_AD |
+ AD |
+ NA |
+ 6025_VC_A_0506 |
+
+
+ | 477 |
+ HB_517_AD |
+ AD |
+ NA |
+ 6031_VC_A_0258 |
+
+
+ | 478 |
+ HB_520_AD |
+ AD |
+ NA |
+ 6035_VC_A_1621 |
+
+
+ | 479 |
+ HB_523_AD |
+ AD |
+ NA |
+ 6038_VC_A_0261 |
+
+
+ | 480 |
+ HB_524_AD |
+ AD |
+ NA |
+ 6042_VC_A_1156 |
+
+
+ | 481 |
+ HB_525_AD |
+ AD |
+ NA |
+ 6044_VC_A_0264 |
+
+
+ | 482 |
+ HB_531_AD |
+ AD |
+ NA |
+ 6056_CR_A_0999 |
+
+
+ | 483 |
+ HB_533_AD |
+ AD |
+ NA |
+ 6061_PF_A_1650 |
+
+
+ | 484 |
+ HB_534_AD |
+ AD |
+ NA |
+ 6066_VC_A_0270 |
+
+
+ | 485 |
+ HB_535_AD |
+ AD |
+ NA |
+ 6067_PF_A_1452 |
+
+
+ | 486 |
+ HB_536_AD |
+ AD |
+ NA |
+ 6068_VC_A_0273 |
+
+
+ | 487 |
+ HB_545_AD |
+ AD |
+ NA |
+ 6102_CR_A_1661 |
+
+
+ | 488 |
+ HB_546_AD |
+ AD |
+ NA |
+ 6107_CR_A_0055 |
+
+
+ | 489 |
+ HB_550_AD |
+ AD |
+ NA |
+ 6120_VC_A_0058 |
+
+
+ | 490 |
+ HB_552_AD |
+ AD |
+ NA |
+ 6126_VC_A_1675 |
+
+
+ | 491 |
+ HB_553_AD |
+ AD |
+ NA |
+ 6129_PF_A_0274 |
+
+
+ | 492 |
+ HB_554_AD |
+ AD |
+ NA |
+ 6130_VC_A_1678 |
+
+
+ | 493 |
+ HB_555_AD |
+ AD |
+ NA |
+ 6131_CR_A_0510 |
+
+
+ | 494 |
+ HB_556_AD |
+ AD |
+ NA |
+ 6132_CR_A_0513 |
+
+
+ | 495 |
+ HB_558_AD |
+ AD |
+ NA |
+ 6137_VC_A_1681 |
+
+
+ | 496 |
+ HB_564_AD |
+ AD |
+ NA |
+ 6153_VC_A_1465 |
+
+
+ | 497 |
+ HB_565_AD |
+ AD |
+ NA |
+ 6154_VC_A_1468 |
+
+
+ | 498 |
+ HB_566_AD |
+ AD |
+ NA |
+ 6157_VC_A_0062 |
+
+
+ | 499 |
+ HB_568_AD |
+ AD |
+ NA |
+ 6164_CR_A_1005 |
+
+
+ | 500 |
+ HB_571_AD |
+ AD |
+ NA |
+ 6171_CR_A_0065 |
+
+
+ | 501 |
+ HB_573_AD |
+ AD |
+ NA |
+ 6174_VC_A_0068 |
+
+
+ | 502 |
+ HB_576_AD |
+ AD |
+ NA |
+ 6180_CR_A_0281 |
+
+
+ | 503 |
+ HB_583_AD |
+ AD |
+ NA |
+ 6194_VC_A_0071 |
+
+
+ | 504 |
+ HB_585_AD |
+ AD |
+ NA |
+ 6198_VC_A_0073 |
+
+
+ | 505 |
+ HB_590_AD |
+ AD |
+ NA |
+ 6215_VC_A_0518 |
+
+
+ | 506 |
+ HB_591_AD |
+ AD |
+ NA |
+ 6216_VC_A_1476 |
+
+
+ | 507 |
+ HB_592_AD |
+ AD |
+ NA |
+ 6218_CR_A_0522 |
+
+
+ | 508 |
+ HB_594_AD |
+ AD |
+ NA |
+ 6223_VC_A_0288 |
+
+
+ | 509 |
+ HB_596_AD |
+ AD |
+ NA |
+ 6226_CR_A_0076 |
+
+
+ | 510 |
+ HB_597_AD |
+ AD |
+ NA |
+ 6227_VC_A_0080 |
+
+
+ | 511 |
+ HB_598_AD |
+ AD |
+ NA |
+ 6231_VC_A_1479 |
+
+
+ | 512 |
+ HB_605_AD |
+ AD |
+ NA |
+ 6261_VC_A_0084 |
+
+
+ | 513 |
+ HB_608_AD |
+ AD |
+ NA |
+ 6268_CR_A_0525 |
+
+
+ | 514 |
+ HB_611_AD |
+ AD |
+ NA |
+ 6279_VC_A_0089 |
+
+
+ | 515 |
+ HB_612_AD |
+ AD |
+ NA |
+ 6280_VC_A_0091 |
+
+
+ | 516 |
+ HB_613_AD |
+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/HBTRC-MLC_AD_0611/experiment-design.rtf b/general/datasets/HBTRC-MLC_AD_0611/experiment-design.rtf
new file mode 100644
index 0000000..3b0c224
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_AD_0611/experiment-design.rtf
@@ -0,0 +1 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
diff --git a/general/datasets/HBTRC-MLC_AD_0611/notes.rtf b/general/datasets/HBTRC-MLC_AD_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_AD_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC-MLC_AD_0611/summary.rtf b/general/datasets/HBTRC-MLC_AD_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_AD_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC-MLC_HD_0611/acknowledgment.rtf b/general/datasets/HBTRC-MLC_HD_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_HD_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC-MLC_HD_0611/cases.rtf b/general/datasets/HBTRC-MLC_HD_0611/cases.rtf
new file mode 100644
index 0000000..e64114d
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_HD_0611/cases.rtf
@@ -0,0 +1,4156 @@
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
+ NA |
+ 5370_PF_A_1400 |
+
+
+ | 364 |
+ HB_259_AD |
+ AD |
+ NA |
+ 5371_PF_A_2636 |
+
+
+ | 365 |
+ HB_260_AD |
+ AD |
+ NA |
+ 5375_VC_A_0188 |
+
+
+ | 366 |
+ HB_263_AD |
+ AD |
+ NA |
+ 5381_VC_A_0022 |
+
+
+ | 367 |
+ HB_265_AD |
+ AD |
+ NA |
+ 5385_VC_A_1402 |
+
+
+ | 368 |
+ HB_267_AD |
+ AD |
+ NA |
+ 5389_VC_A_0928 |
+
+
+ | 369 |
+ HB_268_AD |
+ AD |
+ NA |
+ 5390_CR_A_0151 |
+
+
+ | 370 |
+ HB_273_AD |
+ AD |
+ NA |
+ 5400_PF_A_2645 |
+
+
+ | 371 |
+ HB_274_AD |
+ AD |
+ NA |
+ 5401_VC_A_0931 |
+
+
+ | 372 |
+ HB_275_AD |
+ AD |
+ NA |
+ 5404_PF_A_2648 |
+
+
+ | 373 |
+ HB_276_AD |
+ AD |
+ NA |
+ 5406_VC_A_0933 |
+
+
+ | 374 |
+ HB_277_AD |
+ AD |
+ NA |
+ 5407_PF_A_2651 |
+
+
+ | 375 |
+ HB_280_AD |
+ AD |
+ NA |
+ 5412_VC_A_0935 |
+
+
+ | 376 |
+ HB_281_AD |
+ AD |
+ NA |
+ 5413_PF_A_2657 |
+
+
+ | 377 |
+ HB_283_AD |
+ AD |
+ NA |
+ 5419_VC_A_0937 |
+
+
+ | 378 |
+ HB_284_AD |
+ AD |
+ NA |
+ 5420_VC_A_0939 |
+
+
+ | 379 |
+ HB_285_AD |
+ AD |
+ NA |
+ 5421_CR_A_0432 |
+
+
+ | 380 |
+ HB_286_AD |
+ AD |
+ NA |
+ 5423_PF_A_2660 |
+
+
+ | 381 |
+ HB_288_AD |
+ AD |
+ NA |
+ 5425_PF_A_2666 |
+
+
+ | 382 |
+ HB_289_AD |
+ AD |
+ NA |
+ 5426_VC_A_1405 |
+
+
+ | 383 |
+ HB_290_AD |
+ AD |
+ NA |
+ 5433_VC_A_0434 |
+
+
+ | 384 |
+ HB_296_AD |
+ AD |
+ NA |
+ 5456_PF_A_2675 |
+
+
+ | 385 |
+ HB_299_AD |
+ AD |
+ NA |
+ 5461_VC_A_0192 |
+
+
+ | 386 |
+ HB_302_AD |
+ AD |
+ NA |
+ 5465_PF_A_2678 |
+
+
+ | 387 |
+ HB_303_AD |
+ AD |
+ NA |
+ 5469_VC_A_1417 |
+
+
+ | 388 |
+ HB_305_AD |
+ AD |
+ NA |
+ 5479_PF_A_1421 |
+
+
+ | 389 |
+ HB_306_AD |
+ AD |
+ NA |
+ 5480_VC_A_0437 |
+
+
+ | 390 |
+ HB_307_AD |
+ AD |
+ NA |
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+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/HBTRC-MLC_HD_0611/experiment-design.rtf b/general/datasets/HBTRC-MLC_HD_0611/experiment-design.rtf
new file mode 100644
index 0000000..3b0c224
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_HD_0611/experiment-design.rtf
@@ -0,0 +1 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
diff --git a/general/datasets/HBTRC-MLC_HD_0611/notes.rtf b/general/datasets/HBTRC-MLC_HD_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_HD_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC-MLC_HD_0611/summary.rtf b/general/datasets/HBTRC-MLC_HD_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_HD_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC-MLC_N_0611/acknowledgment.rtf b/general/datasets/HBTRC-MLC_N_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_N_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC-MLC_N_0611/cases.rtf b/general/datasets/HBTRC-MLC_N_0611/cases.rtf
new file mode 100644
index 0000000..e64114d
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_N_0611/cases.rtf
@@ -0,0 +1,4156 @@
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
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+
+ | 516 |
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+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/HBTRC-MLC_N_0611/experiment-design.rtf b/general/datasets/HBTRC-MLC_N_0611/experiment-design.rtf
new file mode 100644
index 0000000..3b0c224
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_N_0611/experiment-design.rtf
@@ -0,0 +1 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
diff --git a/general/datasets/HBTRC-MLC_N_0611/notes.rtf b/general/datasets/HBTRC-MLC_N_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_N_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC-MLC_N_0611/summary.rtf b/general/datasets/HBTRC-MLC_N_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/HBTRC-MLC_N_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC-MLPFC_0611/acknowledgment.rtf b/general/datasets/HBTRC-MLPFC_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC-MLPFC_0611/cases.rtf b/general/datasets/HBTRC-MLPFC_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
+ NA |
+ 5370_PF_A_1400 |
+
+
+ | 364 |
+ HB_259_AD |
+ AD |
+ NA |
+ 5371_PF_A_2636 |
+
+
+ | 365 |
+ HB_260_AD |
+ AD |
+ NA |
+ 5375_VC_A_0188 |
+
+
+ | 366 |
+ HB_263_AD |
+ AD |
+ NA |
+ 5381_VC_A_0022 |
+
+
+ | 367 |
+ HB_265_AD |
+ AD |
+ NA |
+ 5385_VC_A_1402 |
+
+
+ | 368 |
+ HB_267_AD |
+ AD |
+ NA |
+ 5389_VC_A_0928 |
+
+
+ | 369 |
+ HB_268_AD |
+ AD |
+ NA |
+ 5390_CR_A_0151 |
+
+
+ | 370 |
+ HB_273_AD |
+ AD |
+ NA |
+ 5400_PF_A_2645 |
+
+
+ | 371 |
+ HB_274_AD |
+ AD |
+ NA |
+ 5401_VC_A_0931 |
+
+
+ | 372 |
+ HB_275_AD |
+ AD |
+ NA |
+ 5404_PF_A_2648 |
+
+
+ | 373 |
+ HB_276_AD |
+ AD |
+ NA |
+ 5406_VC_A_0933 |
+
+
+ | 374 |
+ HB_277_AD |
+ AD |
+ NA |
+ 5407_PF_A_2651 |
+
+
+ | 375 |
+ HB_280_AD |
+ AD |
+ NA |
+ 5412_VC_A_0935 |
+
+
+ | 376 |
+ HB_281_AD |
+ AD |
+ NA |
+ 5413_PF_A_2657 |
+
+
+ | 377 |
+ HB_283_AD |
+ AD |
+ NA |
+ 5419_VC_A_0937 |
+
+
+ | 378 |
+ HB_284_AD |
+ AD |
+ NA |
+ 5420_VC_A_0939 |
+
+
+ | 379 |
+ HB_285_AD |
+ AD |
+ NA |
+ 5421_CR_A_0432 |
+
+
+ | 380 |
+ HB_286_AD |
+ AD |
+ NA |
+ 5423_PF_A_2660 |
+
+
+ | 381 |
+ HB_288_AD |
+ AD |
+ NA |
+ 5425_PF_A_2666 |
+
+
+ | 382 |
+ HB_289_AD |
+ AD |
+ NA |
+ 5426_VC_A_1405 |
+
+
+ | 383 |
+ HB_290_AD |
+ AD |
+ NA |
+ 5433_VC_A_0434 |
+
+
+ | 384 |
+ HB_296_AD |
+ AD |
+ NA |
+ 5456_PF_A_2675 |
+
+
+ | 385 |
+ HB_299_AD |
+ AD |
+ NA |
+ 5461_VC_A_0192 |
+
+
+ | 386 |
+ HB_302_AD |
+ AD |
+ NA |
+ 5465_PF_A_2678 |
+
+
+ | 387 |
+ HB_303_AD |
+ AD |
+ NA |
+ 5469_VC_A_1417 |
+
+
+ | 388 |
+ HB_305_AD |
+ AD |
+ NA |
+ 5479_PF_A_1421 |
+
+
+ | 389 |
+ HB_306_AD |
+ AD |
+ NA |
+ 5480_VC_A_0437 |
+
+
+ | 390 |
+ HB_307_AD |
+ AD |
+ NA |
+ 5482_VC_A_0028 |
+
+
+ | 391 |
+ HB_308_AD |
+ AD |
+ NA |
+ 5483_VC_A_0941 |
+
+
+ | 392 |
+ HB_309_AD |
+ AD |
+ NA |
+ 5487_CR_A_0441 |
+
+
+ | 393 |
+ HB_310_AD |
+ AD |
+ NA |
+ 5488_CR_A_0194 |
+
+
+ | 394 |
+ HB_312_AD |
+ AD |
+ NA |
+ 5500_VC_A_0198 |
+
+
+ | 395 |
+ HB_313_AD |
+ AD |
+ NA |
+ 5502_PF_A_2684 |
+
+
+ | 396 |
+ HB_315_AD |
+ AD |
+ NA |
+ 5513_PF_A_2687 |
+
+
+ | 397 |
+ HB_316_AD |
+ AD |
+ NA |
+ 5516_PF_A_2690 |
+
+
+ | 398 |
+ HB_317_AD |
+ AD |
+ NA |
+ 5517_PF_A_2693 |
+
+
+ | 399 |
+ HB_318_AD |
+ AD |
+ NA |
+ 5518_CR_A_0030 |
+
+
+ | 400 |
+ HB_319_AD |
+ AD |
+ NA |
+ 5519_CR_A_2695 |
+
+
+ | 401 |
+ HB_320_AD |
+ AD |
+ NA |
+ 5520_PF_A_2699 |
+
+
+ | 402 |
+ HB_322_AD |
+ AD |
+ NA |
+ 5527_VC_A_0945 |
+
+
+ | 403 |
+ HB_325_AD |
+ AD |
+ NA |
+ 5532_PF_A_2702 |
+
+
+ | 404 |
+ HB_328_AD |
+ AD |
+ NA |
+ 5541_PF_A_2705 |
+
+
+ | 405 |
+ HB_330_AD |
+ AD |
+ NA |
+ 5544_VC_A_0201 |
+
+
+ | 406 |
+ HB_334_AD |
+ AD |
+ NA |
+ 5554_VC_A_0452 |
+
+
+ | 407 |
+ HB_335_AD |
+ AD |
+ NA |
+ 5557_VC_A_0950 |
+
+
+ | 408 |
+ HB_337_AD |
+ AD |
+ NA |
+ 5560_VC_A_0204 |
+
+
+ | 409 |
+ HB_342_AD |
+ AD |
+ NA |
+ 5571_PF_A_1430 |
+
+
+ | 410 |
+ HB_345_AD |
+ AD |
+ NA |
+ 5583_PF_A_2708 |
+
+
+ | 411 |
+ HB_347_AD |
+ AD |
+ NA |
+ 5589_PF_A_2714 |
+
+
+ | 412 |
+ HB_349_AD |
+ AD |
+ NA |
+ 5592_PF_A_2717 |
+
+
+ | 413 |
+ HB_352_AD |
+ AD |
+ NA |
+ 5604_VC_A_0037 |
+
+
+ | 414 |
+ HB_353_AD |
+ AD |
+ NA |
+ 5607_PF_A_2723 |
+
+
+ | 415 |
+ HB_356_AD |
+ AD |
+ NA |
+ 5615_VC_A_0041 |
+
+
+ | 416 |
+ HB_357_AD |
+ AD |
+ NA |
+ 5616_CR_A_0127 |
+
+
+ | 417 |
+ HB_358_AD |
+ AD |
+ NA |
+ 5617_CR_A_0456 |
+
+
+ | 418 |
+ HB_359_AD |
+ AD |
+ NA |
+ 5618_CR_A_0044 |
+
+
+ | 419 |
+ HB_362_AD |
+ AD |
+ NA |
+ 5625_CR_A_2495 |
+
+
+ | 420 |
+ HB_363_AD |
+ AD |
+ NA |
+ 5626_CR_A_2498 |
+
+
+ | 421 |
+ HB_364_AD |
+ AD |
+ NA |
+ 5629_CR_A_0390 |
+
+
+ | 422 |
+ HB_369_AD |
+ AD |
+ NA |
+ 5643_VC_A_1143 |
+
+
+ | 423 |
+ HB_373_AD |
+ AD |
+ NA |
+ 5654_VC_A_0047 |
+
+
+ | 424 |
+ HB_375_AD |
+ AD |
+ NA |
+ 5660_CR_A_0462 |
+
+
+ | 425 |
+ HB_376_AD |
+ AD |
+ NA |
+ 5661_VC_A_0464 |
+
+
+ | 426 |
+ HB_377_AD |
+ AD |
+ NA |
+ 5667_VC_A_2509 |
+
+
+ | 427 |
+ HB_378_AD |
+ AD |
+ NA |
+ 5668_VC_A_1438 |
+
+
+ | 428 |
+ HB_383_AD |
+ AD |
+ NA |
+ 5686_CR_A_2728 |
+
+
+ | 429 |
+ HB_386_AD |
+ AD |
+ NA |
+ 5695_VC_A_0953 |
+
+
+ | 430 |
+ HB_389_AD |
+ AD |
+ NA |
+ 5700_VC_A_2514 |
+
+
+ | 431 |
+ HB_391_AD |
+ AD |
+ NA |
+ 5705_CR_A_0474 |
+
+
+ | 432 |
+ HB_392_AD |
+ AD |
+ NA |
+ 5706_VC_A_0476 |
+
+
+ | 433 |
+ HB_394_AD |
+ AD |
+ NA |
+ 5713_VC_A_0479 |
+
+
+ | 434 |
+ HB_397_AD |
+ AD |
+ NA |
+ 5721_CR_A_0210 |
+
+
+ | 435 |
+ HB_404_AD |
+ AD |
+ NA |
+ 5735_CR_A_0489 |
+
+
+ | 436 |
+ HB_406_AD |
+ AD |
+ NA |
+ 5744_CR_A_0960 |
+
+
+ | 437 |
+ HB_409_AD |
+ AD |
+ NA |
+ 5749_CR_A_0159 |
+
+
+ | 438 |
+ HB_410_AD |
+ AD |
+ NA |
+ 5751_CR_A_2518 |
+
+
+ | 439 |
+ HB_411_AD |
+ AD |
+ NA |
+ 5755_CR_A_2731 |
+
+
+ | 440 |
+ HB_413_AD |
+ AD |
+ NA |
+ 5766_VC_A_0214 |
+
+
+ | 441 |
+ HB_419_AD |
+ AD |
+ NA |
+ 5790_VC_A_0217 |
+
+
+ | 442 |
+ HB_420_AD |
+ AD |
+ NA |
+ 5796_CR_A_0964 |
+
+
+ | 443 |
+ HB_428_AD |
+ AD |
+ NA |
+ 5811_CR_A_2524 |
+
+
+ | 444 |
+ HB_429_AD |
+ AD |
+ NA |
+ 5819_CR_A_2527 |
+
+
+ | 445 |
+ HB_430_AD |
+ AD |
+ NA |
+ 5822_CR_A_2530 |
+
+
+ | 446 |
+ HB_434_AD |
+ AD |
+ NA |
+ 5828_CR_A_2533 |
+
+
+ | 447 |
+ HB_435_AD |
+ AD |
+ NA |
+ 5831_CR_A_0222 |
+
+
+ | 448 |
+ HB_437_AD |
+ AD |
+ NA |
+ 5839_CR_A_2539 |
+
+
+ | 449 |
+ HB_438_AD |
+ AD |
+ NA |
+ 5843_CR_A_0227 |
+
+
+ | 450 |
+ HB_439_AD |
+ AD |
+ NA |
+ 5845_CR_A_0230 |
+
+
+ | 451 |
+ HB_441_AD |
+ AD |
+ NA |
+ 5849_CR_A_0233 |
+
+
+ | 452 |
+ HB_442_AD |
+ AD |
+ NA |
+ 5850_CR_A_0495 |
+
+
+ | 453 |
+ HB_445_AD |
+ AD |
+ NA |
+ 5858_CR_A_0969 |
+
+
+ | 454 |
+ HB_448_AD |
+ AD |
+ NA |
+ 5864_CR_A_0974 |
+
+
+ | 455 |
+ HB_451_AD |
+ AD |
+ NA |
+ 5871_CR_A_2542 |
+
+
+ | 456 |
+ HB_454_AD |
+ AD |
+ NA |
+ 5879_CR_A_2545 |
+
+
+ | 457 |
+ HB_455_AD |
+ AD |
+ NA |
+ 5887_CR_A_0976_Bis |
+
+
+ | 458 |
+ HB_459_AD |
+ AD |
+ NA |
+ 5898_CR_A_2548 |
+
+
+ | 459 |
+ HB_460_AD |
+ AD |
+ NA |
+ 5900_VC_A_0237 |
+
+
+ | 460 |
+ HB_461_AD |
+ AD |
+ NA |
+ 5901_CR_A_0239 |
+
+
+ | 461 |
+ HB_469_AD |
+ AD |
+ NA |
+ 5914_CR_A_2554 |
+
+
+ | 462 |
+ HB_471_AD |
+ AD |
+ NA |
+ 5922_VC_A_0246 |
+
+
+ | 463 |
+ HB_473_AD |
+ AD |
+ NA |
+ 5927_CR_A_2560 |
+
+
+ | 464 |
+ HB_474_AD |
+ AD |
+ NA |
+ 5933_VC_A_1071 |
+
+
+ | 465 |
+ HB_477_AD |
+ AD |
+ NA |
+ 5939_CR_A_1151 |
+
+
+ | 466 |
+ HB_479_AD |
+ AD |
+ NA |
+ 5945_VC_A_0983 |
+
+
+ | 467 |
+ HB_484_AD |
+ AD |
+ NA |
+ 5956_CR_A_0123 |
+
+
+ | 468 |
+ HB_489_AD |
+ AD |
+ NA |
+ 5968_VC_A_1075 |
+
+
+ | 469 |
+ HB_491_AD |
+ AD |
+ NA |
+ 5971_CR_A_0119 |
+
+
+ | 470 |
+ HB_492_AD |
+ AD |
+ NA |
+ 5972_VC_A_0251 |
+
+
+ | 471 |
+ HB_494_AD |
+ AD |
+ NA |
+ 5979_CR_A_0115 |
+
+
+ | 472 |
+ HB_498_AD |
+ AD |
+ NA |
+ 5988_VC_A_0503 |
+
+
+ | 473 |
+ HB_502_AD |
+ AD |
+ NA |
+ 5994_PF_A_1605 |
+
+
+ | 474 |
+ HB_503_AD |
+ AD |
+ NA |
+ 5995_CR_A_2563 |
+
+
+ | 475 |
+ HB_510_AD |
+ AD |
+ NA |
+ 6017_CR_A_0048 |
+
+
+ | 476 |
+ HB_514_AD |
+ AD |
+ NA |
+ 6025_VC_A_0506 |
+
+
+ | 477 |
+ HB_517_AD |
+ AD |
+ NA |
+ 6031_VC_A_0258 |
+
+
+ | 478 |
+ HB_520_AD |
+ AD |
+ NA |
+ 6035_VC_A_1621 |
+
+
+ | 479 |
+ HB_523_AD |
+ AD |
+ NA |
+ 6038_VC_A_0261 |
+
+
+ | 480 |
+ HB_524_AD |
+ AD |
+ NA |
+ 6042_VC_A_1156 |
+
+
+ | 481 |
+ HB_525_AD |
+ AD |
+ NA |
+ 6044_VC_A_0264 |
+
+
+ | 482 |
+ HB_531_AD |
+ AD |
+ NA |
+ 6056_CR_A_0999 |
+
+
+ | 483 |
+ HB_533_AD |
+ AD |
+ NA |
+ 6061_PF_A_1650 |
+
+
+ | 484 |
+ HB_534_AD |
+ AD |
+ NA |
+ 6066_VC_A_0270 |
+
+
+ | 485 |
+ HB_535_AD |
+ AD |
+ NA |
+ 6067_PF_A_1452 |
+
+
+ | 486 |
+ HB_536_AD |
+ AD |
+ NA |
+ 6068_VC_A_0273 |
+
+
+ | 487 |
+ HB_545_AD |
+ AD |
+ NA |
+ 6102_CR_A_1661 |
+
+
+ | 488 |
+ HB_546_AD |
+ AD |
+ NA |
+ 6107_CR_A_0055 |
+
+
+ | 489 |
+ HB_550_AD |
+ AD |
+ NA |
+ 6120_VC_A_0058 |
+
+
+ | 490 |
+ HB_552_AD |
+ AD |
+ NA |
+ 6126_VC_A_1675 |
+
+
+ | 491 |
+ HB_553_AD |
+ AD |
+ NA |
+ 6129_PF_A_0274 |
+
+
+ | 492 |
+ HB_554_AD |
+ AD |
+ NA |
+ 6130_VC_A_1678 |
+
+
+ | 493 |
+ HB_555_AD |
+ AD |
+ NA |
+ 6131_CR_A_0510 |
+
+
+ | 494 |
+ HB_556_AD |
+ AD |
+ NA |
+ 6132_CR_A_0513 |
+
+
+ | 495 |
+ HB_558_AD |
+ AD |
+ NA |
+ 6137_VC_A_1681 |
+
+
+ | 496 |
+ HB_564_AD |
+ AD |
+ NA |
+ 6153_VC_A_1465 |
+
+
+ | 497 |
+ HB_565_AD |
+ AD |
+ NA |
+ 6154_VC_A_1468 |
+
+
+ | 498 |
+ HB_566_AD |
+ AD |
+ NA |
+ 6157_VC_A_0062 |
+
+
+ | 499 |
+ HB_568_AD |
+ AD |
+ NA |
+ 6164_CR_A_1005 |
+
+
+ | 500 |
+ HB_571_AD |
+ AD |
+ NA |
+ 6171_CR_A_0065 |
+
+
+ | 501 |
+ HB_573_AD |
+ AD |
+ NA |
+ 6174_VC_A_0068 |
+
+
+ | 502 |
+ HB_576_AD |
+ AD |
+ NA |
+ 6180_CR_A_0281 |
+
+
+ | 503 |
+ HB_583_AD |
+ AD |
+ NA |
+ 6194_VC_A_0071 |
+
+
+ | 504 |
+ HB_585_AD |
+ AD |
+ NA |
+ 6198_VC_A_0073 |
+
+
+ | 505 |
+ HB_590_AD |
+ AD |
+ NA |
+ 6215_VC_A_0518 |
+
+
+ | 506 |
+ HB_591_AD |
+ AD |
+ NA |
+ 6216_VC_A_1476 |
+
+
+ | 507 |
+ HB_592_AD |
+ AD |
+ NA |
+ 6218_CR_A_0522 |
+
+
+ | 508 |
+ HB_594_AD |
+ AD |
+ NA |
+ 6223_VC_A_0288 |
+
+
+ | 509 |
+ HB_596_AD |
+ AD |
+ NA |
+ 6226_CR_A_0076 |
+
+
+ | 510 |
+ HB_597_AD |
+ AD |
+ NA |
+ 6227_VC_A_0080 |
+
+
+ | 511 |
+ HB_598_AD |
+ AD |
+ NA |
+ 6231_VC_A_1479 |
+
+
+ | 512 |
+ HB_605_AD |
+ AD |
+ NA |
+ 6261_VC_A_0084 |
+
+
+ | 513 |
+ HB_608_AD |
+ AD |
+ NA |
+ 6268_CR_A_0525 |
+
+
+ | 514 |
+ HB_611_AD |
+ AD |
+ NA |
+ 6279_VC_A_0089 |
+
+
+ | 515 |
+ HB_612_AD |
+ AD |
+ NA |
+ 6280_VC_A_0091 |
+
+
+ | 516 |
+ HB_613_AD |
+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/HBTRC-MLPFC_0611/experiment-design.rtf b/general/datasets/HBTRC-MLPFC_0611/experiment-design.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_0611/experiment-design.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_0611/notes.rtf b/general/datasets/HBTRC-MLPFC_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC-MLPFC_0611/platform.rtf b/general/datasets/HBTRC-MLPFC_0611/platform.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_0611/platform.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_0611/processing.rtf b/general/datasets/HBTRC-MLPFC_0611/processing.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_0611/processing.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_0611/summary.rtf b/general/datasets/HBTRC-MLPFC_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC-MLPFC_0611/tissue.rtf b/general/datasets/HBTRC-MLPFC_0611/tissue.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_0611/tissue.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_AD_0611/acknowledgment.rtf b/general/datasets/HBTRC-MLPFC_AD_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_AD_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC-MLPFC_AD_0611/cases.rtf b/general/datasets/HBTRC-MLPFC_AD_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_AD_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
+ NA |
+ 5370_PF_A_1400 |
+
+
+ | 364 |
+ HB_259_AD |
+ AD |
+ NA |
+ 5371_PF_A_2636 |
+
+
+ | 365 |
+ HB_260_AD |
+ AD |
+ NA |
+ 5375_VC_A_0188 |
+
+
+ | 366 |
+ HB_263_AD |
+ AD |
+ NA |
+ 5381_VC_A_0022 |
+
+
+ | 367 |
+ HB_265_AD |
+ AD |
+ NA |
+ 5385_VC_A_1402 |
+
+
+ | 368 |
+ HB_267_AD |
+ AD |
+ NA |
+ 5389_VC_A_0928 |
+
+
+ | 369 |
+ HB_268_AD |
+ AD |
+ NA |
+ 5390_CR_A_0151 |
+
+
+ | 370 |
+ HB_273_AD |
+ AD |
+ NA |
+ 5400_PF_A_2645 |
+
+
+ | 371 |
+ HB_274_AD |
+ AD |
+ NA |
+ 5401_VC_A_0931 |
+
+
+ | 372 |
+ HB_275_AD |
+ AD |
+ NA |
+ 5404_PF_A_2648 |
+
+
+ | 373 |
+ HB_276_AD |
+ AD |
+ NA |
+ 5406_VC_A_0933 |
+
+
+ | 374 |
+ HB_277_AD |
+ AD |
+ NA |
+ 5407_PF_A_2651 |
+
+
+ | 375 |
+ HB_280_AD |
+ AD |
+ NA |
+ 5412_VC_A_0935 |
+
+
+ | 376 |
+ HB_281_AD |
+ AD |
+ NA |
+ 5413_PF_A_2657 |
+
+
+ | 377 |
+ HB_283_AD |
+ AD |
+ NA |
+ 5419_VC_A_0937 |
+
+
+ | 378 |
+ HB_284_AD |
+ AD |
+ NA |
+ 5420_VC_A_0939 |
+
+
+ | 379 |
+ HB_285_AD |
+ AD |
+ NA |
+ 5421_CR_A_0432 |
+
+
+ | 380 |
+ HB_286_AD |
+ AD |
+ NA |
+ 5423_PF_A_2660 |
+
+
+ | 381 |
+ HB_288_AD |
+ AD |
+ NA |
+ 5425_PF_A_2666 |
+
+
+ | 382 |
+ HB_289_AD |
+ AD |
+ NA |
+ 5426_VC_A_1405 |
+
+
+ | 383 |
+ HB_290_AD |
+ AD |
+ NA |
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+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/HBTRC-MLPFC_AD_0611/experiment-design.rtf b/general/datasets/HBTRC-MLPFC_AD_0611/experiment-design.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_AD_0611/experiment-design.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_AD_0611/notes.rtf b/general/datasets/HBTRC-MLPFC_AD_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_AD_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC-MLPFC_AD_0611/platform.rtf b/general/datasets/HBTRC-MLPFC_AD_0611/platform.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_AD_0611/platform.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_AD_0611/processing.rtf b/general/datasets/HBTRC-MLPFC_AD_0611/processing.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_AD_0611/processing.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_AD_0611/summary.rtf b/general/datasets/HBTRC-MLPFC_AD_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_AD_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC-MLPFC_AD_0611/tissue.rtf b/general/datasets/HBTRC-MLPFC_AD_0611/tissue.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_AD_0611/tissue.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_HD_0611/acknowledgment.rtf b/general/datasets/HBTRC-MLPFC_HD_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_HD_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC-MLPFC_HD_0611/cases.rtf b/general/datasets/HBTRC-MLPFC_HD_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_HD_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
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+
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+ HB_568_AD |
+ AD |
+ NA |
+ 6164_CR_A_1005 |
+
+
+ | 500 |
+ HB_571_AD |
+ AD |
+ NA |
+ 6171_CR_A_0065 |
+
+
+ | 501 |
+ HB_573_AD |
+ AD |
+ NA |
+ 6174_VC_A_0068 |
+
+
+ | 502 |
+ HB_576_AD |
+ AD |
+ NA |
+ 6180_CR_A_0281 |
+
+
+ | 503 |
+ HB_583_AD |
+ AD |
+ NA |
+ 6194_VC_A_0071 |
+
+
+ | 504 |
+ HB_585_AD |
+ AD |
+ NA |
+ 6198_VC_A_0073 |
+
+
+ | 505 |
+ HB_590_AD |
+ AD |
+ NA |
+ 6215_VC_A_0518 |
+
+
+ | 506 |
+ HB_591_AD |
+ AD |
+ NA |
+ 6216_VC_A_1476 |
+
+
+ | 507 |
+ HB_592_AD |
+ AD |
+ NA |
+ 6218_CR_A_0522 |
+
+
+ | 508 |
+ HB_594_AD |
+ AD |
+ NA |
+ 6223_VC_A_0288 |
+
+
+ | 509 |
+ HB_596_AD |
+ AD |
+ NA |
+ 6226_CR_A_0076 |
+
+
+ | 510 |
+ HB_597_AD |
+ AD |
+ NA |
+ 6227_VC_A_0080 |
+
+
+ | 511 |
+ HB_598_AD |
+ AD |
+ NA |
+ 6231_VC_A_1479 |
+
+
+ | 512 |
+ HB_605_AD |
+ AD |
+ NA |
+ 6261_VC_A_0084 |
+
+
+ | 513 |
+ HB_608_AD |
+ AD |
+ NA |
+ 6268_CR_A_0525 |
+
+
+ | 514 |
+ HB_611_AD |
+ AD |
+ NA |
+ 6279_VC_A_0089 |
+
+
+ | 515 |
+ HB_612_AD |
+ AD |
+ NA |
+ 6280_VC_A_0091 |
+
+
+ | 516 |
+ HB_613_AD |
+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/HBTRC-MLPFC_HD_0611/experiment-design.rtf b/general/datasets/HBTRC-MLPFC_HD_0611/experiment-design.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_HD_0611/experiment-design.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_HD_0611/notes.rtf b/general/datasets/HBTRC-MLPFC_HD_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_HD_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC-MLPFC_HD_0611/platform.rtf b/general/datasets/HBTRC-MLPFC_HD_0611/platform.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_HD_0611/platform.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_HD_0611/processing.rtf b/general/datasets/HBTRC-MLPFC_HD_0611/processing.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_HD_0611/processing.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_HD_0611/summary.rtf b/general/datasets/HBTRC-MLPFC_HD_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_HD_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC-MLPFC_HD_0611/tissue.rtf b/general/datasets/HBTRC-MLPFC_HD_0611/tissue.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_HD_0611/tissue.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_N_0611/acknowledgment.rtf b/general/datasets/HBTRC-MLPFC_N_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_N_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC-MLPFC_N_0611/cases.rtf b/general/datasets/HBTRC-MLPFC_N_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_N_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
+ NA |
+ 5370_PF_A_1400 |
+
+
+ | 364 |
+ HB_259_AD |
+ AD |
+ NA |
+ 5371_PF_A_2636 |
+
+
+ | 365 |
+ HB_260_AD |
+ AD |
+ NA |
+ 5375_VC_A_0188 |
+
+
+ | 366 |
+ HB_263_AD |
+ AD |
+ NA |
+ 5381_VC_A_0022 |
+
+
+ | 367 |
+ HB_265_AD |
+ AD |
+ NA |
+ 5385_VC_A_1402 |
+
+
+ | 368 |
+ HB_267_AD |
+ AD |
+ NA |
+ 5389_VC_A_0928 |
+
+
+ | 369 |
+ HB_268_AD |
+ AD |
+ NA |
+ 5390_CR_A_0151 |
+
+
+ | 370 |
+ HB_273_AD |
+ AD |
+ NA |
+ 5400_PF_A_2645 |
+
+
+ | 371 |
+ HB_274_AD |
+ AD |
+ NA |
+ 5401_VC_A_0931 |
+
+
+ | 372 |
+ HB_275_AD |
+ AD |
+ NA |
+ 5404_PF_A_2648 |
+
+
+ | 373 |
+ HB_276_AD |
+ AD |
+ NA |
+ 5406_VC_A_0933 |
+
+
+ | 374 |
+ HB_277_AD |
+ AD |
+ NA |
+ 5407_PF_A_2651 |
+
+
+ | 375 |
+ HB_280_AD |
+ AD |
+ NA |
+ 5412_VC_A_0935 |
+
+
+ | 376 |
+ HB_281_AD |
+ AD |
+ NA |
+ 5413_PF_A_2657 |
+
+
+ | 377 |
+ HB_283_AD |
+ AD |
+ NA |
+ 5419_VC_A_0937 |
+
+
+ | 378 |
+ HB_284_AD |
+ AD |
+ NA |
+ 5420_VC_A_0939 |
+
+
+ | 379 |
+ HB_285_AD |
+ AD |
+ NA |
+ 5421_CR_A_0432 |
+
+
+ | 380 |
+ HB_286_AD |
+ AD |
+ NA |
+ 5423_PF_A_2660 |
+
+
+ | 381 |
+ HB_288_AD |
+ AD |
+ NA |
+ 5425_PF_A_2666 |
+
+
+ | 382 |
+ HB_289_AD |
+ AD |
+ NA |
+ 5426_VC_A_1405 |
+
+
+ | 383 |
+ HB_290_AD |
+ AD |
+ NA |
+ 5433_VC_A_0434 |
+
+
+ | 384 |
+ HB_296_AD |
+ AD |
+ NA |
+ 5456_PF_A_2675 |
+
+
+ | 385 |
+ HB_299_AD |
+ AD |
+ NA |
+ 5461_VC_A_0192 |
+
+
+ | 386 |
+ HB_302_AD |
+ AD |
+ NA |
+ 5465_PF_A_2678 |
+
+
+ | 387 |
+ HB_303_AD |
+ AD |
+ NA |
+ 5469_VC_A_1417 |
+
+
+ | 388 |
+ HB_305_AD |
+ AD |
+ NA |
+ 5479_PF_A_1421 |
+
+
+ | 389 |
+ HB_306_AD |
+ AD |
+ NA |
+ 5480_VC_A_0437 |
+
+
+ | 390 |
+ HB_307_AD |
+ AD |
+ NA |
+ 5482_VC_A_0028 |
+
+
+ | 391 |
+ HB_308_AD |
+ AD |
+ NA |
+ 5483_VC_A_0941 |
+
+
+ | 392 |
+ HB_309_AD |
+ AD |
+ NA |
+ 5487_CR_A_0441 |
+
+
+ | 393 |
+ HB_310_AD |
+ AD |
+ NA |
+ 5488_CR_A_0194 |
+
+
+ | 394 |
+ HB_312_AD |
+ AD |
+ NA |
+ 5500_VC_A_0198 |
+
+
+ | 395 |
+ HB_313_AD |
+ AD |
+ NA |
+ 5502_PF_A_2684 |
+
+
+ | 396 |
+ HB_315_AD |
+ AD |
+ NA |
+ 5513_PF_A_2687 |
+
+
+ | 397 |
+ HB_316_AD |
+ AD |
+ NA |
+ 5516_PF_A_2690 |
+
+
+ | 398 |
+ HB_317_AD |
+ AD |
+ NA |
+ 5517_PF_A_2693 |
+
+
+ | 399 |
+ HB_318_AD |
+ AD |
+ NA |
+ 5518_CR_A_0030 |
+
+
+ | 400 |
+ HB_319_AD |
+ AD |
+ NA |
+ 5519_CR_A_2695 |
+
+
+ | 401 |
+ HB_320_AD |
+ AD |
+ NA |
+ 5520_PF_A_2699 |
+
+
+ | 402 |
+ HB_322_AD |
+ AD |
+ NA |
+ 5527_VC_A_0945 |
+
+
+ | 403 |
+ HB_325_AD |
+ AD |
+ NA |
+ 5532_PF_A_2702 |
+
+
+ | 404 |
+ HB_328_AD |
+ AD |
+ NA |
+ 5541_PF_A_2705 |
+
+
+ | 405 |
+ HB_330_AD |
+ AD |
+ NA |
+ 5544_VC_A_0201 |
+
+
+ | 406 |
+ HB_334_AD |
+ AD |
+ NA |
+ 5554_VC_A_0452 |
+
+
+ | 407 |
+ HB_335_AD |
+ AD |
+ NA |
+ 5557_VC_A_0950 |
+
+
+ | 408 |
+ HB_337_AD |
+ AD |
+ NA |
+ 5560_VC_A_0204 |
+
+
+ | 409 |
+ HB_342_AD |
+ AD |
+ NA |
+ 5571_PF_A_1430 |
+
+
+ | 410 |
+ HB_345_AD |
+ AD |
+ NA |
+ 5583_PF_A_2708 |
+
+
+ | 411 |
+ HB_347_AD |
+ AD |
+ NA |
+ 5589_PF_A_2714 |
+
+
+ | 412 |
+ HB_349_AD |
+ AD |
+ NA |
+ 5592_PF_A_2717 |
+
+
+ | 413 |
+ HB_352_AD |
+ AD |
+ NA |
+ 5604_VC_A_0037 |
+
+
+ | 414 |
+ HB_353_AD |
+ AD |
+ NA |
+ 5607_PF_A_2723 |
+
+
+ | 415 |
+ HB_356_AD |
+ AD |
+ NA |
+ 5615_VC_A_0041 |
+
+
+ | 416 |
+ HB_357_AD |
+ AD |
+ NA |
+ 5616_CR_A_0127 |
+
+
+ | 417 |
+ HB_358_AD |
+ AD |
+ NA |
+ 5617_CR_A_0456 |
+
+
+ | 418 |
+ HB_359_AD |
+ AD |
+ NA |
+ 5618_CR_A_0044 |
+
+
+ | 419 |
+ HB_362_AD |
+ AD |
+ NA |
+ 5625_CR_A_2495 |
+
+
+ | 420 |
+ HB_363_AD |
+ AD |
+ NA |
+ 5626_CR_A_2498 |
+
+
+ | 421 |
+ HB_364_AD |
+ AD |
+ NA |
+ 5629_CR_A_0390 |
+
+
+ | 422 |
+ HB_369_AD |
+ AD |
+ NA |
+ 5643_VC_A_1143 |
+
+
+ | 423 |
+ HB_373_AD |
+ AD |
+ NA |
+ 5654_VC_A_0047 |
+
+
+ | 424 |
+ HB_375_AD |
+ AD |
+ NA |
+ 5660_CR_A_0462 |
+
+
+ | 425 |
+ HB_376_AD |
+ AD |
+ NA |
+ 5661_VC_A_0464 |
+
+
+ | 426 |
+ HB_377_AD |
+ AD |
+ NA |
+ 5667_VC_A_2509 |
+
+
+ | 427 |
+ HB_378_AD |
+ AD |
+ NA |
+ 5668_VC_A_1438 |
+
+
+ | 428 |
+ HB_383_AD |
+ AD |
+ NA |
+ 5686_CR_A_2728 |
+
+
+ | 429 |
+ HB_386_AD |
+ AD |
+ NA |
+ 5695_VC_A_0953 |
+
+
+ | 430 |
+ HB_389_AD |
+ AD |
+ NA |
+ 5700_VC_A_2514 |
+
+
+ | 431 |
+ HB_391_AD |
+ AD |
+ NA |
+ 5705_CR_A_0474 |
+
+
+ | 432 |
+ HB_392_AD |
+ AD |
+ NA |
+ 5706_VC_A_0476 |
+
+
+ | 433 |
+ HB_394_AD |
+ AD |
+ NA |
+ 5713_VC_A_0479 |
+
+
+ | 434 |
+ HB_397_AD |
+ AD |
+ NA |
+ 5721_CR_A_0210 |
+
+
+ | 435 |
+ HB_404_AD |
+ AD |
+ NA |
+ 5735_CR_A_0489 |
+
+
+ | 436 |
+ HB_406_AD |
+ AD |
+ NA |
+ 5744_CR_A_0960 |
+
+
+ | 437 |
+ HB_409_AD |
+ AD |
+ NA |
+ 5749_CR_A_0159 |
+
+
+ | 438 |
+ HB_410_AD |
+ AD |
+ NA |
+ 5751_CR_A_2518 |
+
+
+ | 439 |
+ HB_411_AD |
+ AD |
+ NA |
+ 5755_CR_A_2731 |
+
+
+ | 440 |
+ HB_413_AD |
+ AD |
+ NA |
+ 5766_VC_A_0214 |
+
+
+ | 441 |
+ HB_419_AD |
+ AD |
+ NA |
+ 5790_VC_A_0217 |
+
+
+ | 442 |
+ HB_420_AD |
+ AD |
+ NA |
+ 5796_CR_A_0964 |
+
+
+ | 443 |
+ HB_428_AD |
+ AD |
+ NA |
+ 5811_CR_A_2524 |
+
+
+ | 444 |
+ HB_429_AD |
+ AD |
+ NA |
+ 5819_CR_A_2527 |
+
+
+ | 445 |
+ HB_430_AD |
+ AD |
+ NA |
+ 5822_CR_A_2530 |
+
+
+ | 446 |
+ HB_434_AD |
+ AD |
+ NA |
+ 5828_CR_A_2533 |
+
+
+ | 447 |
+ HB_435_AD |
+ AD |
+ NA |
+ 5831_CR_A_0222 |
+
+
+ | 448 |
+ HB_437_AD |
+ AD |
+ NA |
+ 5839_CR_A_2539 |
+
+
+ | 449 |
+ HB_438_AD |
+ AD |
+ NA |
+ 5843_CR_A_0227 |
+
+
+ | 450 |
+ HB_439_AD |
+ AD |
+ NA |
+ 5845_CR_A_0230 |
+
+
+ | 451 |
+ HB_441_AD |
+ AD |
+ NA |
+ 5849_CR_A_0233 |
+
+
+ | 452 |
+ HB_442_AD |
+ AD |
+ NA |
+ 5850_CR_A_0495 |
+
+
+ | 453 |
+ HB_445_AD |
+ AD |
+ NA |
+ 5858_CR_A_0969 |
+
+
+ | 454 |
+ HB_448_AD |
+ AD |
+ NA |
+ 5864_CR_A_0974 |
+
+
+ | 455 |
+ HB_451_AD |
+ AD |
+ NA |
+ 5871_CR_A_2542 |
+
+
+ | 456 |
+ HB_454_AD |
+ AD |
+ NA |
+ 5879_CR_A_2545 |
+
+
+ | 457 |
+ HB_455_AD |
+ AD |
+ NA |
+ 5887_CR_A_0976_Bis |
+
+
+ | 458 |
+ HB_459_AD |
+ AD |
+ NA |
+ 5898_CR_A_2548 |
+
+
+ | 459 |
+ HB_460_AD |
+ AD |
+ NA |
+ 5900_VC_A_0237 |
+
+
+ | 460 |
+ HB_461_AD |
+ AD |
+ NA |
+ 5901_CR_A_0239 |
+
+
+ | 461 |
+ HB_469_AD |
+ AD |
+ NA |
+ 5914_CR_A_2554 |
+
+
+ | 462 |
+ HB_471_AD |
+ AD |
+ NA |
+ 5922_VC_A_0246 |
+
+
+ | 463 |
+ HB_473_AD |
+ AD |
+ NA |
+ 5927_CR_A_2560 |
+
+
+ | 464 |
+ HB_474_AD |
+ AD |
+ NA |
+ 5933_VC_A_1071 |
+
+
+ | 465 |
+ HB_477_AD |
+ AD |
+ NA |
+ 5939_CR_A_1151 |
+
+
+ | 466 |
+ HB_479_AD |
+ AD |
+ NA |
+ 5945_VC_A_0983 |
+
+
+ | 467 |
+ HB_484_AD |
+ AD |
+ NA |
+ 5956_CR_A_0123 |
+
+
+ | 468 |
+ HB_489_AD |
+ AD |
+ NA |
+ 5968_VC_A_1075 |
+
+
+ | 469 |
+ HB_491_AD |
+ AD |
+ NA |
+ 5971_CR_A_0119 |
+
+
+ | 470 |
+ HB_492_AD |
+ AD |
+ NA |
+ 5972_VC_A_0251 |
+
+
+ | 471 |
+ HB_494_AD |
+ AD |
+ NA |
+ 5979_CR_A_0115 |
+
+
+ | 472 |
+ HB_498_AD |
+ AD |
+ NA |
+ 5988_VC_A_0503 |
+
+
+ | 473 |
+ HB_502_AD |
+ AD |
+ NA |
+ 5994_PF_A_1605 |
+
+
+ | 474 |
+ HB_503_AD |
+ AD |
+ NA |
+ 5995_CR_A_2563 |
+
+
+ | 475 |
+ HB_510_AD |
+ AD |
+ NA |
+ 6017_CR_A_0048 |
+
+
+ | 476 |
+ HB_514_AD |
+ AD |
+ NA |
+ 6025_VC_A_0506 |
+
+
+ | 477 |
+ HB_517_AD |
+ AD |
+ NA |
+ 6031_VC_A_0258 |
+
+
+ | 478 |
+ HB_520_AD |
+ AD |
+ NA |
+ 6035_VC_A_1621 |
+
+
+ | 479 |
+ HB_523_AD |
+ AD |
+ NA |
+ 6038_VC_A_0261 |
+
+
+ | 480 |
+ HB_524_AD |
+ AD |
+ NA |
+ 6042_VC_A_1156 |
+
+
+ | 481 |
+ HB_525_AD |
+ AD |
+ NA |
+ 6044_VC_A_0264 |
+
+
+ | 482 |
+ HB_531_AD |
+ AD |
+ NA |
+ 6056_CR_A_0999 |
+
+
+ | 483 |
+ HB_533_AD |
+ AD |
+ NA |
+ 6061_PF_A_1650 |
+
+
+ | 484 |
+ HB_534_AD |
+ AD |
+ NA |
+ 6066_VC_A_0270 |
+
+
+ | 485 |
+ HB_535_AD |
+ AD |
+ NA |
+ 6067_PF_A_1452 |
+
+
+ | 486 |
+ HB_536_AD |
+ AD |
+ NA |
+ 6068_VC_A_0273 |
+
+
+ | 487 |
+ HB_545_AD |
+ AD |
+ NA |
+ 6102_CR_A_1661 |
+
+
+ | 488 |
+ HB_546_AD |
+ AD |
+ NA |
+ 6107_CR_A_0055 |
+
+
+ | 489 |
+ HB_550_AD |
+ AD |
+ NA |
+ 6120_VC_A_0058 |
+
+
+ | 490 |
+ HB_552_AD |
+ AD |
+ NA |
+ 6126_VC_A_1675 |
+
+
+ | 491 |
+ HB_553_AD |
+ AD |
+ NA |
+ 6129_PF_A_0274 |
+
+
+ | 492 |
+ HB_554_AD |
+ AD |
+ NA |
+ 6130_VC_A_1678 |
+
+
+ | 493 |
+ HB_555_AD |
+ AD |
+ NA |
+ 6131_CR_A_0510 |
+
+
+ | 494 |
+ HB_556_AD |
+ AD |
+ NA |
+ 6132_CR_A_0513 |
+
+
+ | 495 |
+ HB_558_AD |
+ AD |
+ NA |
+ 6137_VC_A_1681 |
+
+
+ | 496 |
+ HB_564_AD |
+ AD |
+ NA |
+ 6153_VC_A_1465 |
+
+
+ | 497 |
+ HB_565_AD |
+ AD |
+ NA |
+ 6154_VC_A_1468 |
+
+
+ | 498 |
+ HB_566_AD |
+ AD |
+ NA |
+ 6157_VC_A_0062 |
+
+
+ | 499 |
+ HB_568_AD |
+ AD |
+ NA |
+ 6164_CR_A_1005 |
+
+
+ | 500 |
+ HB_571_AD |
+ AD |
+ NA |
+ 6171_CR_A_0065 |
+
+
+ | 501 |
+ HB_573_AD |
+ AD |
+ NA |
+ 6174_VC_A_0068 |
+
+
+ | 502 |
+ HB_576_AD |
+ AD |
+ NA |
+ 6180_CR_A_0281 |
+
+
+ | 503 |
+ HB_583_AD |
+ AD |
+ NA |
+ 6194_VC_A_0071 |
+
+
+ | 504 |
+ HB_585_AD |
+ AD |
+ NA |
+ 6198_VC_A_0073 |
+
+
+ | 505 |
+ HB_590_AD |
+ AD |
+ NA |
+ 6215_VC_A_0518 |
+
+
+ | 506 |
+ HB_591_AD |
+ AD |
+ NA |
+ 6216_VC_A_1476 |
+
+
+ | 507 |
+ HB_592_AD |
+ AD |
+ NA |
+ 6218_CR_A_0522 |
+
+
+ | 508 |
+ HB_594_AD |
+ AD |
+ NA |
+ 6223_VC_A_0288 |
+
+
+ | 509 |
+ HB_596_AD |
+ AD |
+ NA |
+ 6226_CR_A_0076 |
+
+
+ | 510 |
+ HB_597_AD |
+ AD |
+ NA |
+ 6227_VC_A_0080 |
+
+
+ | 511 |
+ HB_598_AD |
+ AD |
+ NA |
+ 6231_VC_A_1479 |
+
+
+ | 512 |
+ HB_605_AD |
+ AD |
+ NA |
+ 6261_VC_A_0084 |
+
+
+ | 513 |
+ HB_608_AD |
+ AD |
+ NA |
+ 6268_CR_A_0525 |
+
+
+ | 514 |
+ HB_611_AD |
+ AD |
+ NA |
+ 6279_VC_A_0089 |
+
+
+ | 515 |
+ HB_612_AD |
+ AD |
+ NA |
+ 6280_VC_A_0091 |
+
+
+ | 516 |
+ HB_613_AD |
+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/HBTRC-MLPFC_N_0611/experiment-design.rtf b/general/datasets/HBTRC-MLPFC_N_0611/experiment-design.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_N_0611/experiment-design.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_N_0611/notes.rtf b/general/datasets/HBTRC-MLPFC_N_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_N_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC-MLPFC_N_0611/platform.rtf b/general/datasets/HBTRC-MLPFC_N_0611/platform.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_N_0611/platform.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_N_0611/processing.rtf b/general/datasets/HBTRC-MLPFC_N_0611/processing.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_N_0611/processing.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLPFC_N_0611/summary.rtf b/general/datasets/HBTRC-MLPFC_N_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_N_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC-MLPFC_N_0611/tissue.rtf b/general/datasets/HBTRC-MLPFC_N_0611/tissue.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/HBTRC-MLPFC_N_0611/tissue.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/HBTRC-MLVC_0611/acknowledgment.rtf b/general/datasets/HBTRC-MLVC_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC-MLVC_0611/cases.rtf b/general/datasets/HBTRC-MLVC_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
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+
+ | 538 |
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+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/HBTRC-MLVC_0611/notes.rtf b/general/datasets/HBTRC-MLVC_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC-MLVC_0611/summary.rtf b/general/datasets/HBTRC-MLVC_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC-MLVC_AD_0611/acknowledgment.rtf b/general/datasets/HBTRC-MLVC_AD_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_AD_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC-MLVC_AD_0611/cases.rtf b/general/datasets/HBTRC-MLVC_AD_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_AD_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
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+ AD |
+ NA |
+ 6044_VC_A_0264 |
+
+
+ | 482 |
+ HB_531_AD |
+ AD |
+ NA |
+ 6056_CR_A_0999 |
+
+
+ | 483 |
+ HB_533_AD |
+ AD |
+ NA |
+ 6061_PF_A_1650 |
+
+
+ | 484 |
+ HB_534_AD |
+ AD |
+ NA |
+ 6066_VC_A_0270 |
+
+
+ | 485 |
+ HB_535_AD |
+ AD |
+ NA |
+ 6067_PF_A_1452 |
+
+
+ | 486 |
+ HB_536_AD |
+ AD |
+ NA |
+ 6068_VC_A_0273 |
+
+
+ | 487 |
+ HB_545_AD |
+ AD |
+ NA |
+ 6102_CR_A_1661 |
+
+
+ | 488 |
+ HB_546_AD |
+ AD |
+ NA |
+ 6107_CR_A_0055 |
+
+
+ | 489 |
+ HB_550_AD |
+ AD |
+ NA |
+ 6120_VC_A_0058 |
+
+
+ | 490 |
+ HB_552_AD |
+ AD |
+ NA |
+ 6126_VC_A_1675 |
+
+
+ | 491 |
+ HB_553_AD |
+ AD |
+ NA |
+ 6129_PF_A_0274 |
+
+
+ | 492 |
+ HB_554_AD |
+ AD |
+ NA |
+ 6130_VC_A_1678 |
+
+
+ | 493 |
+ HB_555_AD |
+ AD |
+ NA |
+ 6131_CR_A_0510 |
+
+
+ | 494 |
+ HB_556_AD |
+ AD |
+ NA |
+ 6132_CR_A_0513 |
+
+
+ | 495 |
+ HB_558_AD |
+ AD |
+ NA |
+ 6137_VC_A_1681 |
+
+
+ | 496 |
+ HB_564_AD |
+ AD |
+ NA |
+ 6153_VC_A_1465 |
+
+
+ | 497 |
+ HB_565_AD |
+ AD |
+ NA |
+ 6154_VC_A_1468 |
+
+
+ | 498 |
+ HB_566_AD |
+ AD |
+ NA |
+ 6157_VC_A_0062 |
+
+
+ | 499 |
+ HB_568_AD |
+ AD |
+ NA |
+ 6164_CR_A_1005 |
+
+
+ | 500 |
+ HB_571_AD |
+ AD |
+ NA |
+ 6171_CR_A_0065 |
+
+
+ | 501 |
+ HB_573_AD |
+ AD |
+ NA |
+ 6174_VC_A_0068 |
+
+
+ | 502 |
+ HB_576_AD |
+ AD |
+ NA |
+ 6180_CR_A_0281 |
+
+
+ | 503 |
+ HB_583_AD |
+ AD |
+ NA |
+ 6194_VC_A_0071 |
+
+
+ | 504 |
+ HB_585_AD |
+ AD |
+ NA |
+ 6198_VC_A_0073 |
+
+
+ | 505 |
+ HB_590_AD |
+ AD |
+ NA |
+ 6215_VC_A_0518 |
+
+
+ | 506 |
+ HB_591_AD |
+ AD |
+ NA |
+ 6216_VC_A_1476 |
+
+
+ | 507 |
+ HB_592_AD |
+ AD |
+ NA |
+ 6218_CR_A_0522 |
+
+
+ | 508 |
+ HB_594_AD |
+ AD |
+ NA |
+ 6223_VC_A_0288 |
+
+
+ | 509 |
+ HB_596_AD |
+ AD |
+ NA |
+ 6226_CR_A_0076 |
+
+
+ | 510 |
+ HB_597_AD |
+ AD |
+ NA |
+ 6227_VC_A_0080 |
+
+
+ | 511 |
+ HB_598_AD |
+ AD |
+ NA |
+ 6231_VC_A_1479 |
+
+
+ | 512 |
+ HB_605_AD |
+ AD |
+ NA |
+ 6261_VC_A_0084 |
+
+
+ | 513 |
+ HB_608_AD |
+ AD |
+ NA |
+ 6268_CR_A_0525 |
+
+
+ | 514 |
+ HB_611_AD |
+ AD |
+ NA |
+ 6279_VC_A_0089 |
+
+
+ | 515 |
+ HB_612_AD |
+ AD |
+ NA |
+ 6280_VC_A_0091 |
+
+
+ | 516 |
+ HB_613_AD |
+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/HBTRC-MLVC_AD_0611/notes.rtf b/general/datasets/HBTRC-MLVC_AD_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_AD_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC-MLVC_AD_0611/summary.rtf b/general/datasets/HBTRC-MLVC_AD_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_AD_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC-MLVC_HD_0611/acknowledgment.rtf b/general/datasets/HBTRC-MLVC_HD_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_HD_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC-MLVC_HD_0611/cases.rtf b/general/datasets/HBTRC-MLVC_HD_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_HD_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
+ NA |
+ 5370_PF_A_1400 |
+
+
+ | 364 |
+ HB_259_AD |
+ AD |
+ NA |
+ 5371_PF_A_2636 |
+
+
+ | 365 |
+ HB_260_AD |
+ AD |
+ NA |
+ 5375_VC_A_0188 |
+
+
+ | 366 |
+ HB_263_AD |
+ AD |
+ NA |
+ 5381_VC_A_0022 |
+
+
+ | 367 |
+ HB_265_AD |
+ AD |
+ NA |
+ 5385_VC_A_1402 |
+
+
+ | 368 |
+ HB_267_AD |
+ AD |
+ NA |
+ 5389_VC_A_0928 |
+
+
+ | 369 |
+ HB_268_AD |
+ AD |
+ NA |
+ 5390_CR_A_0151 |
+
+
+ | 370 |
+ HB_273_AD |
+ AD |
+ NA |
+ 5400_PF_A_2645 |
+
+
+ | 371 |
+ HB_274_AD |
+ AD |
+ NA |
+ 5401_VC_A_0931 |
+
+
+ | 372 |
+ HB_275_AD |
+ AD |
+ NA |
+ 5404_PF_A_2648 |
+
+
+ | 373 |
+ HB_276_AD |
+ AD |
+ NA |
+ 5406_VC_A_0933 |
+
+
+ | 374 |
+ HB_277_AD |
+ AD |
+ NA |
+ 5407_PF_A_2651 |
+
+
+ | 375 |
+ HB_280_AD |
+ AD |
+ NA |
+ 5412_VC_A_0935 |
+
+
+ | 376 |
+ HB_281_AD |
+ AD |
+ NA |
+ 5413_PF_A_2657 |
+
+
+ | 377 |
+ HB_283_AD |
+ AD |
+ NA |
+ 5419_VC_A_0937 |
+
+
+ | 378 |
+ HB_284_AD |
+ AD |
+ NA |
+ 5420_VC_A_0939 |
+
+
+ | 379 |
+ HB_285_AD |
+ AD |
+ NA |
+ 5421_CR_A_0432 |
+
+
+ | 380 |
+ HB_286_AD |
+ AD |
+ NA |
+ 5423_PF_A_2660 |
+
+
+ | 381 |
+ HB_288_AD |
+ AD |
+ NA |
+ 5425_PF_A_2666 |
+
+
+ | 382 |
+ HB_289_AD |
+ AD |
+ NA |
+ 5426_VC_A_1405 |
+
+
+ | 383 |
+ HB_290_AD |
+ AD |
+ NA |
+ 5433_VC_A_0434 |
+
+
+ | 384 |
+ HB_296_AD |
+ AD |
+ NA |
+ 5456_PF_A_2675 |
+
+
+ | 385 |
+ HB_299_AD |
+ AD |
+ NA |
+ 5461_VC_A_0192 |
+
+
+ | 386 |
+ HB_302_AD |
+ AD |
+ NA |
+ 5465_PF_A_2678 |
+
+
+ | 387 |
+ HB_303_AD |
+ AD |
+ NA |
+ 5469_VC_A_1417 |
+
+
+ | 388 |
+ HB_305_AD |
+ AD |
+ NA |
+ 5479_PF_A_1421 |
+
+
+ | 389 |
+ HB_306_AD |
+ AD |
+ NA |
+ 5480_VC_A_0437 |
+
+
+ | 390 |
+ HB_307_AD |
+ AD |
+ NA |
+ 5482_VC_A_0028 |
+
+
+ | 391 |
+ HB_308_AD |
+ AD |
+ NA |
+ 5483_VC_A_0941 |
+
+
+ | 392 |
+ HB_309_AD |
+ AD |
+ NA |
+ 5487_CR_A_0441 |
+
+
+ | 393 |
+ HB_310_AD |
+ AD |
+ NA |
+ 5488_CR_A_0194 |
+
+
+ | 394 |
+ HB_312_AD |
+ AD |
+ NA |
+ 5500_VC_A_0198 |
+
+
+ | 395 |
+ HB_313_AD |
+ AD |
+ NA |
+ 5502_PF_A_2684 |
+
+
+ | 396 |
+ HB_315_AD |
+ AD |
+ NA |
+ 5513_PF_A_2687 |
+
+
+ | 397 |
+ HB_316_AD |
+ AD |
+ NA |
+ 5516_PF_A_2690 |
+
+
+ | 398 |
+ HB_317_AD |
+ AD |
+ NA |
+ 5517_PF_A_2693 |
+
+
+ | 399 |
+ HB_318_AD |
+ AD |
+ NA |
+ 5518_CR_A_0030 |
+
+
+ | 400 |
+ HB_319_AD |
+ AD |
+ NA |
+ 5519_CR_A_2695 |
+
+
+ | 401 |
+ HB_320_AD |
+ AD |
+ NA |
+ 5520_PF_A_2699 |
+
+
+ | 402 |
+ HB_322_AD |
+ AD |
+ NA |
+ 5527_VC_A_0945 |
+
+
+ | 403 |
+ HB_325_AD |
+ AD |
+ NA |
+ 5532_PF_A_2702 |
+
+
+ | 404 |
+ HB_328_AD |
+ AD |
+ NA |
+ 5541_PF_A_2705 |
+
+
+ | 405 |
+ HB_330_AD |
+ AD |
+ NA |
+ 5544_VC_A_0201 |
+
+
+ | 406 |
+ HB_334_AD |
+ AD |
+ NA |
+ 5554_VC_A_0452 |
+
+
+ | 407 |
+ HB_335_AD |
+ AD |
+ NA |
+ 5557_VC_A_0950 |
+
+
+ | 408 |
+ HB_337_AD |
+ AD |
+ NA |
+ 5560_VC_A_0204 |
+
+
+ | 409 |
+ HB_342_AD |
+ AD |
+ NA |
+ 5571_PF_A_1430 |
+
+
+ | 410 |
+ HB_345_AD |
+ AD |
+ NA |
+ 5583_PF_A_2708 |
+
+
+ | 411 |
+ HB_347_AD |
+ AD |
+ NA |
+ 5589_PF_A_2714 |
+
+
+ | 412 |
+ HB_349_AD |
+ AD |
+ NA |
+ 5592_PF_A_2717 |
+
+
+ | 413 |
+ HB_352_AD |
+ AD |
+ NA |
+ 5604_VC_A_0037 |
+
+
+ | 414 |
+ HB_353_AD |
+ AD |
+ NA |
+ 5607_PF_A_2723 |
+
+
+ | 415 |
+ HB_356_AD |
+ AD |
+ NA |
+ 5615_VC_A_0041 |
+
+
+ | 416 |
+ HB_357_AD |
+ AD |
+ NA |
+ 5616_CR_A_0127 |
+
+
+ | 417 |
+ HB_358_AD |
+ AD |
+ NA |
+ 5617_CR_A_0456 |
+
+
+ | 418 |
+ HB_359_AD |
+ AD |
+ NA |
+ 5618_CR_A_0044 |
+
+
+ | 419 |
+ HB_362_AD |
+ AD |
+ NA |
+ 5625_CR_A_2495 |
+
+
+ | 420 |
+ HB_363_AD |
+ AD |
+ NA |
+ 5626_CR_A_2498 |
+
+
+ | 421 |
+ HB_364_AD |
+ AD |
+ NA |
+ 5629_CR_A_0390 |
+
+
+ | 422 |
+ HB_369_AD |
+ AD |
+ NA |
+ 5643_VC_A_1143 |
+
+
+ | 423 |
+ HB_373_AD |
+ AD |
+ NA |
+ 5654_VC_A_0047 |
+
+
+ | 424 |
+ HB_375_AD |
+ AD |
+ NA |
+ 5660_CR_A_0462 |
+
+
+ | 425 |
+ HB_376_AD |
+ AD |
+ NA |
+ 5661_VC_A_0464 |
+
+
+ | 426 |
+ HB_377_AD |
+ AD |
+ NA |
+ 5667_VC_A_2509 |
+
+
+ | 427 |
+ HB_378_AD |
+ AD |
+ NA |
+ 5668_VC_A_1438 |
+
+
+ | 428 |
+ HB_383_AD |
+ AD |
+ NA |
+ 5686_CR_A_2728 |
+
+
+ | 429 |
+ HB_386_AD |
+ AD |
+ NA |
+ 5695_VC_A_0953 |
+
+
+ | 430 |
+ HB_389_AD |
+ AD |
+ NA |
+ 5700_VC_A_2514 |
+
+
+ | 431 |
+ HB_391_AD |
+ AD |
+ NA |
+ 5705_CR_A_0474 |
+
+
+ | 432 |
+ HB_392_AD |
+ AD |
+ NA |
+ 5706_VC_A_0476 |
+
+
+ | 433 |
+ HB_394_AD |
+ AD |
+ NA |
+ 5713_VC_A_0479 |
+
+
+ | 434 |
+ HB_397_AD |
+ AD |
+ NA |
+ 5721_CR_A_0210 |
+
+
+ | 435 |
+ HB_404_AD |
+ AD |
+ NA |
+ 5735_CR_A_0489 |
+
+
+ | 436 |
+ HB_406_AD |
+ AD |
+ NA |
+ 5744_CR_A_0960 |
+
+
+ | 437 |
+ HB_409_AD |
+ AD |
+ NA |
+ 5749_CR_A_0159 |
+
+
+ | 438 |
+ HB_410_AD |
+ AD |
+ NA |
+ 5751_CR_A_2518 |
+
+
+ | 439 |
+ HB_411_AD |
+ AD |
+ NA |
+ 5755_CR_A_2731 |
+
+
+ | 440 |
+ HB_413_AD |
+ AD |
+ NA |
+ 5766_VC_A_0214 |
+
+
+ | 441 |
+ HB_419_AD |
+ AD |
+ NA |
+ 5790_VC_A_0217 |
+
+
+ | 442 |
+ HB_420_AD |
+ AD |
+ NA |
+ 5796_CR_A_0964 |
+
+
+ | 443 |
+ HB_428_AD |
+ AD |
+ NA |
+ 5811_CR_A_2524 |
+
+
+ | 444 |
+ HB_429_AD |
+ AD |
+ NA |
+ 5819_CR_A_2527 |
+
+
+ | 445 |
+ HB_430_AD |
+ AD |
+ NA |
+ 5822_CR_A_2530 |
+
+
+ | 446 |
+ HB_434_AD |
+ AD |
+ NA |
+ 5828_CR_A_2533 |
+
+
+ | 447 |
+ HB_435_AD |
+ AD |
+ NA |
+ 5831_CR_A_0222 |
+
+
+ | 448 |
+ HB_437_AD |
+ AD |
+ NA |
+ 5839_CR_A_2539 |
+
+
+ | 449 |
+ HB_438_AD |
+ AD |
+ NA |
+ 5843_CR_A_0227 |
+
+
+ | 450 |
+ HB_439_AD |
+ AD |
+ NA |
+ 5845_CR_A_0230 |
+
+
+ | 451 |
+ HB_441_AD |
+ AD |
+ NA |
+ 5849_CR_A_0233 |
+
+
+ | 452 |
+ HB_442_AD |
+ AD |
+ NA |
+ 5850_CR_A_0495 |
+
+
+ | 453 |
+ HB_445_AD |
+ AD |
+ NA |
+ 5858_CR_A_0969 |
+
+
+ | 454 |
+ HB_448_AD |
+ AD |
+ NA |
+ 5864_CR_A_0974 |
+
+
+ | 455 |
+ HB_451_AD |
+ AD |
+ NA |
+ 5871_CR_A_2542 |
+
+
+ | 456 |
+ HB_454_AD |
+ AD |
+ NA |
+ 5879_CR_A_2545 |
+
+
+ | 457 |
+ HB_455_AD |
+ AD |
+ NA |
+ 5887_CR_A_0976_Bis |
+
+
+ | 458 |
+ HB_459_AD |
+ AD |
+ NA |
+ 5898_CR_A_2548 |
+
+
+ | 459 |
+ HB_460_AD |
+ AD |
+ NA |
+ 5900_VC_A_0237 |
+
+
+ | 460 |
+ HB_461_AD |
+ AD |
+ NA |
+ 5901_CR_A_0239 |
+
+
+ | 461 |
+ HB_469_AD |
+ AD |
+ NA |
+ 5914_CR_A_2554 |
+
+
+ | 462 |
+ HB_471_AD |
+ AD |
+ NA |
+ 5922_VC_A_0246 |
+
+
+ | 463 |
+ HB_473_AD |
+ AD |
+ NA |
+ 5927_CR_A_2560 |
+
+
+ | 464 |
+ HB_474_AD |
+ AD |
+ NA |
+ 5933_VC_A_1071 |
+
+
+ | 465 |
+ HB_477_AD |
+ AD |
+ NA |
+ 5939_CR_A_1151 |
+
+
+ | 466 |
+ HB_479_AD |
+ AD |
+ NA |
+ 5945_VC_A_0983 |
+
+
+ | 467 |
+ HB_484_AD |
+ AD |
+ NA |
+ 5956_CR_A_0123 |
+
+
+ | 468 |
+ HB_489_AD |
+ AD |
+ NA |
+ 5968_VC_A_1075 |
+
+
+ | 469 |
+ HB_491_AD |
+ AD |
+ NA |
+ 5971_CR_A_0119 |
+
+
+ | 470 |
+ HB_492_AD |
+ AD |
+ NA |
+ 5972_VC_A_0251 |
+
+
+ | 471 |
+ HB_494_AD |
+ AD |
+ NA |
+ 5979_CR_A_0115 |
+
+
+ | 472 |
+ HB_498_AD |
+ AD |
+ NA |
+ 5988_VC_A_0503 |
+
+
+ | 473 |
+ HB_502_AD |
+ AD |
+ NA |
+ 5994_PF_A_1605 |
+
+
+ | 474 |
+ HB_503_AD |
+ AD |
+ NA |
+ 5995_CR_A_2563 |
+
+
+ | 475 |
+ HB_510_AD |
+ AD |
+ NA |
+ 6017_CR_A_0048 |
+
+
+ | 476 |
+ HB_514_AD |
+ AD |
+ NA |
+ 6025_VC_A_0506 |
+
+
+ | 477 |
+ HB_517_AD |
+ AD |
+ NA |
+ 6031_VC_A_0258 |
+
+
+ | 478 |
+ HB_520_AD |
+ AD |
+ NA |
+ 6035_VC_A_1621 |
+
+
+ | 479 |
+ HB_523_AD |
+ AD |
+ NA |
+ 6038_VC_A_0261 |
+
+
+ | 480 |
+ HB_524_AD |
+ AD |
+ NA |
+ 6042_VC_A_1156 |
+
+
+ | 481 |
+ HB_525_AD |
+ AD |
+ NA |
+ 6044_VC_A_0264 |
+
+
+ | 482 |
+ HB_531_AD |
+ AD |
+ NA |
+ 6056_CR_A_0999 |
+
+
+ | 483 |
+ HB_533_AD |
+ AD |
+ NA |
+ 6061_PF_A_1650 |
+
+
+ | 484 |
+ HB_534_AD |
+ AD |
+ NA |
+ 6066_VC_A_0270 |
+
+
+ | 485 |
+ HB_535_AD |
+ AD |
+ NA |
+ 6067_PF_A_1452 |
+
+
+ | 486 |
+ HB_536_AD |
+ AD |
+ NA |
+ 6068_VC_A_0273 |
+
+
+ | 487 |
+ HB_545_AD |
+ AD |
+ NA |
+ 6102_CR_A_1661 |
+
+
+ | 488 |
+ HB_546_AD |
+ AD |
+ NA |
+ 6107_CR_A_0055 |
+
+
+ | 489 |
+ HB_550_AD |
+ AD |
+ NA |
+ 6120_VC_A_0058 |
+
+
+ | 490 |
+ HB_552_AD |
+ AD |
+ NA |
+ 6126_VC_A_1675 |
+
+
+ | 491 |
+ HB_553_AD |
+ AD |
+ NA |
+ 6129_PF_A_0274 |
+
+
+ | 492 |
+ HB_554_AD |
+ AD |
+ NA |
+ 6130_VC_A_1678 |
+
+
+ | 493 |
+ HB_555_AD |
+ AD |
+ NA |
+ 6131_CR_A_0510 |
+
+
+ | 494 |
+ HB_556_AD |
+ AD |
+ NA |
+ 6132_CR_A_0513 |
+
+
+ | 495 |
+ HB_558_AD |
+ AD |
+ NA |
+ 6137_VC_A_1681 |
+
+
+ | 496 |
+ HB_564_AD |
+ AD |
+ NA |
+ 6153_VC_A_1465 |
+
+
+ | 497 |
+ HB_565_AD |
+ AD |
+ NA |
+ 6154_VC_A_1468 |
+
+
+ | 498 |
+ HB_566_AD |
+ AD |
+ NA |
+ 6157_VC_A_0062 |
+
+
+ | 499 |
+ HB_568_AD |
+ AD |
+ NA |
+ 6164_CR_A_1005 |
+
+
+ | 500 |
+ HB_571_AD |
+ AD |
+ NA |
+ 6171_CR_A_0065 |
+
+
+ | 501 |
+ HB_573_AD |
+ AD |
+ NA |
+ 6174_VC_A_0068 |
+
+
+ | 502 |
+ HB_576_AD |
+ AD |
+ NA |
+ 6180_CR_A_0281 |
+
+
+ | 503 |
+ HB_583_AD |
+ AD |
+ NA |
+ 6194_VC_A_0071 |
+
+
+ | 504 |
+ HB_585_AD |
+ AD |
+ NA |
+ 6198_VC_A_0073 |
+
+
+ | 505 |
+ HB_590_AD |
+ AD |
+ NA |
+ 6215_VC_A_0518 |
+
+
+ | 506 |
+ HB_591_AD |
+ AD |
+ NA |
+ 6216_VC_A_1476 |
+
+
+ | 507 |
+ HB_592_AD |
+ AD |
+ NA |
+ 6218_CR_A_0522 |
+
+
+ | 508 |
+ HB_594_AD |
+ AD |
+ NA |
+ 6223_VC_A_0288 |
+
+
+ | 509 |
+ HB_596_AD |
+ AD |
+ NA |
+ 6226_CR_A_0076 |
+
+
+ | 510 |
+ HB_597_AD |
+ AD |
+ NA |
+ 6227_VC_A_0080 |
+
+
+ | 511 |
+ HB_598_AD |
+ AD |
+ NA |
+ 6231_VC_A_1479 |
+
+
+ | 512 |
+ HB_605_AD |
+ AD |
+ NA |
+ 6261_VC_A_0084 |
+
+
+ | 513 |
+ HB_608_AD |
+ AD |
+ NA |
+ 6268_CR_A_0525 |
+
+
+ | 514 |
+ HB_611_AD |
+ AD |
+ NA |
+ 6279_VC_A_0089 |
+
+
+ | 515 |
+ HB_612_AD |
+ AD |
+ NA |
+ 6280_VC_A_0091 |
+
+
+ | 516 |
+ HB_613_AD |
+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/HBTRC-MLVC_HD_0611/notes.rtf b/general/datasets/HBTRC-MLVC_HD_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_HD_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC-MLVC_HD_0611/summary.rtf b/general/datasets/HBTRC-MLVC_HD_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_HD_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC-MLVC_N_0611/acknowledgment.rtf b/general/datasets/HBTRC-MLVC_N_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_N_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC-MLVC_N_0611/cases.rtf b/general/datasets/HBTRC-MLVC_N_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_N_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
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+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/HBTRC-MLVC_N_0611/notes.rtf b/general/datasets/HBTRC-MLVC_N_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_N_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC-MLVC_N_0611/summary.rtf b/general/datasets/HBTRC-MLVC_N_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/HBTRC-MLVC_N_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC_MLC_0611/acknowledgment.rtf b/general/datasets/HBTRC_MLC_0611/acknowledgment.rtf
deleted file mode 100644
index 208cb6e..0000000
--- a/general/datasets/HBTRC_MLC_0611/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC_MLC_0611/cases.rtf b/general/datasets/HBTRC_MLC_0611/cases.rtf
deleted file mode 100644
index e64114d..0000000
--- a/general/datasets/HBTRC_MLC_0611/cases.rtf
+++ /dev/null
@@ -1,4156 +0,0 @@
-
-
-
-
-
-
-
- | Series |
- Cerebellum in GN |
- Condition |
- Gender |
- BioSample Name |
-
-
- | 1 |
- HB_029_N |
- N |
- NA |
- 3405_VC_N_0859 |
-
-
- | 2 |
- HB_058_N |
- N |
- NA |
- 4021_VC_N_0854 |
-
-
- | 3 |
- HB_064_N |
- N |
- NA |
- 4338_VC_N_0861 |
-
-
- | 4 |
- HB_086_N |
- N |
- NA |
- 4729_PF_N_0756 |
-
-
- | 5 |
- HB_091_N |
- N |
- NA |
- 4741_VC_N_0864 |
-
-
- | 6 |
- HB_092_N |
- N |
- NA |
- 4744_VC_N_0865 |
-
-
- | 7 |
- HB_102_N |
- N |
- NA |
- 4810_VC_N_0869 |
-
-
- | 8 |
- HB_119_N |
- N |
- NA |
- 4872_VC_N_0878 |
-
-
- | 9 |
- HB_147_N |
- N |
- NA |
- 5021_VC_N_0852 |
-
-
- | 10 |
- HB_161_N |
- N |
- NA |
- 5077_VC_N_0851 |
-
-
- | 11 |
- HB_162_N |
- N |
- NA |
- 5081_VC_N_1021 |
-
-
- | 12 |
- HB_166_N |
- N |
- NA |
- 5095_VC_N_1024 |
-
-
- | 13 |
- HB_183_N |
- N |
- NA |
- 5162_VC_N_0850 |
-
-
- | 14 |
- HB_206_N |
- N |
- NA |
- 5245_VC_N_0849 |
-
-
- | 15 |
- HB_215_N |
- N |
- NA |
- 5270_VC_N_0848 |
-
-
- | 16 |
- HB_218_N |
- N |
- NA |
- 5276_CR_N_0912 |
-
-
- | 17 |
- HB_223_N |
- N |
- NA |
- 5287_VC_N_0916 |
-
-
- | 18 |
- HB_226_N |
- N |
- NA |
- 5294_VC_N_0919 |
-
-
- | 19 |
- HB_241_N |
- N |
- NA |
- 5326_CR_N_0652 |
-
-
- | 20 |
- HB_243_N |
- N |
- NA |
- 5333_VC_N_1262 |
-
-
- | 21 |
- HB_247_N |
- N |
- NA |
- 5341_VC_N_0923 |
-
-
- | 22 |
- HB_257_N |
- N |
- NA |
- 5368_PF_N_1032 |
-
-
- | 23 |
- HB_264_N |
- N |
- NA |
- 5384_VC_N_0924 |
-
-
- | 24 |
- HB_295_N |
- N |
- NA |
- 5452_VC_N_1268 |
-
-
- | 25 |
- HB_300_N |
- N |
- NA |
- 5463_VC_N_0845 |
-
-
- | 26 |
- HB_311_N |
- N |
- NA |
- 5489_CR_N_0942 |
-
-
- | 27 |
- HB_324_N |
- N |
- NA |
- 5531_VC_N_0844 |
-
-
- | 28 |
- HB_332_N |
- N |
- NA |
- 5547_VC_N_0843 |
-
-
- | 29 |
- HB_340_N |
- N |
- NA |
- 5568_VC_N_0842 |
-
-
- | 30 |
- HB_360_N |
- N |
- NA |
- 5619_CR_N_0645 |
-
-
- | 31 |
- HB_365_N |
- N |
- NA |
- 5632_VC_N_0838 |
-
-
- | 32 |
- HB_367_N |
- N |
- NA |
- 5637_VC_N_0837 |
-
-
- | 33 |
- HB_382_N |
- N |
- NA |
- 5684_PF_N_1270 |
-
-
- | 34 |
- HB_396_N |
- N |
- NA |
- 5718_VC_N_0956 |
-
-
- | 35 |
- HB_398_N |
- N |
- NA |
- 5722_VC_N_1044 |
-
-
- | 36 |
- HB_400_N |
- N |
- NA |
- 5726_VC_N_0834_Bis |
-
-
- | 37 |
- HB_403_N |
- N |
- NA |
- 5734_VC_N_0833 |
-
-
- | 38 |
- HB_414_N |
- N |
- NA |
- 5772_VC_N_0832_Bis |
-
-
- | 39 |
- HB_416_N |
- N |
- NA |
- 5778_CR_N_0962 |
-
-
- | 40 |
- HB_418_N |
- N |
- NA |
- 5789_PF_N_1273 |
-
-
- | 41 |
- HB_421_N |
- N |
- NA |
- 5799_VC_N_1058 |
-
-
- | 42 |
- HB_423_N |
- N |
- NA |
- 5803_VC_N_0966 |
-
-
- | 43 |
- HB_426_N |
- N |
- NA |
- 5806_PF_N_1064 |
-
-
- | 44 |
- HB_427_N |
- N |
- NA |
- 5810_CR_N_0636 |
-
-
- | 45 |
- HB_431_N |
- N |
- NA |
- 5823_VC_N_0829 |
-
-
- | 46 |
- HB_432_N |
- N |
- NA |
- 5826_VC_N_0828 |
-
-
- | 47 |
- HB_433_N |
- N |
- NA |
- 5827_VC_N_0827 |
-
-
- | 48 |
- HB_436_N |
- N |
- NA |
- 5832_PF_N_1145 |
-
-
- | 49 |
- HB_443_N |
- N |
- NA |
- 5852_VC_N_0826 |
-
-
- | 50 |
- HB_446_N |
- N |
- NA |
- 5859_VC_N_0825 |
-
-
- | 51 |
- HB_449_N |
- N |
- NA |
- 5866_VC_N_0824 |
-
-
- | 52 |
- HB_450_N |
- N |
- NA |
- 5867_VC_N_1277 |
-
-
- | 53 |
- HB_453_N |
- N |
- NA |
- 5876_VC_N_0823 |
-
-
- | 54 |
- HB_462_N |
- N |
- NA |
- 5903_VC_N_0822 |
-
-
- | 55 |
- HB_464_N |
- N |
- NA |
- 5905_VC_N_0820 |
-
-
- | 56 |
- HB_468_N |
- N |
- NA |
- 5912_VC_N_1286 |
-
-
- | 57 |
- HB_472_N |
- N |
- NA |
- 5925_VC_N_1289 |
-
-
- | 58 |
- HB_475_N |
- N |
- NA |
- 5936_VC_N_0979 |
-
-
- | 59 |
- HB_476_N |
- N |
- NA |
- 5938_VC_N_0819 |
-
-
- | 60 |
- HB_480_N |
- N |
- NA |
- 5946_VC_N_0985 |
-
-
- | 61 |
- HB_485_N |
- N |
- NA |
- 5959_VC_N_0818 |
-
-
- | 62 |
- HB_486_N |
- N |
- NA |
- 5963_VC_N_0987 |
-
-
- | 63 |
- HB_495_N |
- N |
- NA |
- 5980_VC_N_0989 |
-
-
- | 64 |
- HB_497_N |
- N |
- NA |
- 5985_VC_N_0990 |
-
-
- | 65 |
- HB_500_N |
- N |
- NA |
- 5990_VC_N_0817 |
-
-
- | 66 |
- HB_501_N |
- N |
- NA |
- 5991_VC_N_0816 |
-
-
- | 67 |
- HB_504_N |
- N |
- NA |
- 5996_VC_N_0815 |
-
-
- | 68 |
- HB_505_N |
- N |
- NA |
- 5998_VC_N_0814 |
-
-
- | 69 |
- HB_507_N |
- N |
- NA |
- 6006_VC_N_0813 |
-
-
- | 70 |
- HB_508_N |
- N |
- NA |
- 6007_CR_N_0618 |
-
-
- | 71 |
- HB_509_N |
- N |
- NA |
- 6008_PF_N_1081 |
-
-
- | 72 |
- HB_512_N |
- N |
- NA |
- 6023_PF_N_1155 |
-
-
- | 73 |
- HB_516_N |
- N |
- NA |
- 6030_VC_N_0810 |
-
-
- | 74 |
- HB_519_N |
- N |
- NA |
- 6034_VC_N_0809 |
-
-
- | 75 |
- HB_532_N |
- N |
- NA |
- 6060_VC_N_1292 |
-
-
- | 76 |
- HB_541_N |
- N |
- NA |
- 6092_VC_N_1001 |
-
-
- | 77 |
- HB_542_N |
- N |
- NA |
- 6096_VC_N_0807 |
-
-
- | 78 |
- HB_544_N |
- N |
- NA |
- 6101_CR_N_1161 |
-
-
- | 79 |
- HB_547_N |
- N |
- NA |
- 6110_VC_N_1295 |
-
-
- | 80 |
- HB_551_N |
- N |
- NA |
- 6124_VC_N_0806 |
-
-
- | 81 |
- HB_557_N |
- N |
- NA |
- 6134_PF_N_1297 |
-
-
- | 82 |
- HB_560_N |
- N |
- NA |
- 6142_VC_N_0805 |
-
-
- | 83 |
- HB_569_N |
- N |
- NA |
- 6166_VC_N_0804 |
-
-
- | 84 |
- HB_570_N |
- N |
- NA |
- 6170_VC_N_0803 |
-
-
- | 85 |
- HB_572_N |
- N |
- NA |
- 6172_VC_N_1008 |
-
-
- | 86 |
- HB_577_N |
- N |
- NA |
- 6182_VC_N_1166 |
-
-
- | 87 |
- HB_579_N |
- N |
- NA |
- 6187_CR_N_0607 |
-
-
- | 88 |
- HB_581_N |
- N |
- NA |
- 6191_VC_N_1010 |
-
-
- | 89 |
- HB_584_N |
- N |
- NA |
- 6196_CR_N_0605 |
-
-
- | 90 |
- HB_586_N |
- N |
- NA |
- 6200_VC_N_0799 |
-
-
- | 91 |
- HB_587_N |
- N |
- NA |
- 6206_PF_N_1176 |
-
-
- | 92 |
- HB_589_N |
- N |
- NA |
- 6213_VC_N_0798 |
-
-
- | 93 |
- HB_601_N |
- N |
- NA |
- 6241_VC_N_0796 |
-
-
- | 94 |
- HB_604_N |
- N |
- NA |
- 6260_VC_N_0794 |
-
-
- | 95 |
- HB_609_N |
- N |
- NA |
- 6270_VC_N_0793 |
-
-
- | 96 |
- HB_618_N |
- N |
- NA |
- 6289_VC_N_0791 |
-
-
- | 97 |
- HB_622_N |
- N |
- NA |
- 6310_VC_N_0790 |
-
-
- | 98 |
- HB_625_N |
- N |
- NA |
- 6314_VC_N_0789 |
-
-
- | 99 |
- HB_637_N |
- N |
- NA |
- 6340_VC_N_0786 |
-
-
- | 100 |
- HB_638_N |
- N |
- NA |
- 6341_VC_N_0785 |
-
-
- | 101 |
- HB_640_N |
- N |
- NA |
- 6347_VC_N_0784 |
-
-
- | 102 |
- HB_641_N |
- N |
- NA |
- 6356_VC_N_0783 |
-
-
- | 103 |
- HB_643_N |
- N |
- NA |
- 6363_VC_N_0781 |
-
-
- | 104 |
- HB_644_N |
- N |
- NA |
- 6366_VC_N_0780 |
-
-
- | 105 |
- HB_645_N |
- N |
- NA |
- 6374_VC_N_0779 |
-
-
- | 106 |
- HB_650_N |
- N |
- NA |
- 6384_VC_N_0777 |
-
-
- | 107 |
- HB_651_N |
- N |
- NA |
- 6386_VC_N_0776 |
-
-
- | 108 |
- HB_653_N |
- N |
- NA |
- 6388_VC_N_0775 |
-
-
- | 109 |
- HB_659_N |
- N |
- NA |
- 6406_VC_N_1180 |
-
-
- | 110 |
- HB_662_N |
- N |
- NA |
- 6411_VC_N_0771 |
-
-
- | 111 |
- HB_663_N |
- N |
- NA |
- 6415_VC_N_0770 |
-
-
- | 112 |
- HB_670_N |
- N |
- NA |
- 6436_VC_N_0769 |
-
-
- | 113 |
- HB_687_N |
- N |
- NA |
- 6484_VC_N_0765 |
-
-
- | 114 |
- HB_689_N |
- N |
- NA |
- 6486_VC_N_0764 |
-
-
- | 115 |
- HB_694_N |
- N |
- NA |
- 6500_VC_N_0763 |
-
-
- | 116 |
- HB_697_N |
- N |
- NA |
- 6512_VC_N_0762 |
-
-
- | 117 |
- HB_700_N |
- N |
- NA |
- 6520_VC_N_0761 |
-
-
- | 118 |
- HB_711_N |
- N |
- NA |
- 6543_PF_N_1191 |
-
-
- | 119 |
- HB_714_N |
- N |
- NA |
- 6549_VC_N_1198 |
-
-
- | 120 |
- HB_717_N |
- N |
- NA |
- 6553_PF_N_2284 |
-
-
- | 121 |
- HB_721_N |
- N |
- NA |
- 6560_VC_N_2578 |
-
-
- | 122 |
- HB_726_N |
- N |
- NA |
- 6573_PF_N_2293 |
-
-
- | 123 |
- HB_730_N |
- N |
- NA |
- 6580_VC_N_2306 |
-
-
- | 124 |
- HB_735_N |
- N |
- NA |
- 6588_VC_N_1213 |
-
-
- | 125 |
- HB_737_N |
- N |
- NA |
- 6593_VC_N_1219 |
-
-
- | 126 |
- HB_738_N |
- N |
- NA |
- 6594_VC_N_1222 |
-
-
- | 127 |
- HB_759_N |
- N |
- NA |
- 6645_VC_N_1231 |
-
-
- | 128 |
- HB_764_N |
- N |
- NA |
- 6655_VC_N_1240 |
-
-
- | 129 |
- HB_765_N |
- N |
- NA |
- 6656_VC_N_1243 |
-
-
- | 130 |
- HB_767_N |
- N |
- NA |
- 6661_PF_N_2341 |
-
-
- | 131 |
- HB_770_N |
- N |
- NA |
- 6669_VC_N_1246 |
-
-
- | 132 |
- HB_772_N |
- N |
- NA |
- 6676_PF_N_1248 |
-
-
- | 133 |
- HB_001_HD |
- HD |
- F |
- 2028_CR_H_2282 |
-
-
- | 134 |
- HB_003_HD |
- HD |
- F |
- 2685_PF_H_2212 |
-
-
- | 135 |
- HB_004_HD |
- HD |
- M |
- 2706_CR_H_2432 |
-
-
- | 136 |
- HB_006_HD |
- HD |
- M |
- 2737_VC_H_2194 |
-
-
- | 137 |
- HB_007_HD |
- HD |
- NA |
- 2769_VC_H_2193 |
-
-
- | 138 |
- HB_008_HD |
- HD |
- F |
- 2790_CR_H_1890 |
-
-
- | 139 |
- HB_009_HD |
- HD |
- NA |
- 2879_VC_H_2192 |
-
-
- | 140 |
- HB_010_HD |
- HD |
- M |
- 2960_VC_H_2002 |
-
-
- | 141 |
- HB_011_HD |
- HD |
- F |
- 3053_VC_H_2001 |
-
-
- | 142 |
- HB_012_HD |
- HD |
- F |
- 3128_VC_H_1999 |
-
-
- | 143 |
- HB_014_HD |
- HD |
- F |
- 3149_PF_H_2110 |
-
-
- | 144 |
- HB_015_HD |
- HD |
- F |
- 3150_VC_H_1996 |
-
-
- | 145 |
- HB_016_HD |
- HD |
- F |
- 3177_VC_H_2191 |
-
-
- | 146 |
- HB_017_HD |
- HD |
- NA |
- 3195_VC_H_2190 |
-
-
- | 147 |
- HB_018_HD |
- HD |
- M |
- 3200_VC_H_2189 |
-
-
- | 148 |
- HB_019_HD |
- HD |
- M |
- 3209_VC_H_2188 |
-
-
- | 149 |
- HB_020_HD |
- HD |
- M |
- 3224_VC_H_1994 |
-
-
- | 150 |
- HB_022_HD |
- HD |
- F |
- 3242_PF_H_2105 |
-
-
- | 151 |
- HB_024_HD |
- HD |
- NA |
- 3272_VC_H_2186 |
-
-
- | 152 |
- HB_027_HD |
- HD |
- M |
- 3356_VC_H_2439 |
-
-
- | 153 |
- HB_028_HD |
- HD |
- F |
- 3394_PF_H_2104 |
-
-
- | 154 |
- HB_031_HD |
- HD |
- M |
- 3430_VC_H_1990 |
-
-
- | 155 |
- HB_032_HD |
- HD |
- NA |
- 3444_PF_H_2208 |
-
-
- | 156 |
- HB_034_HD |
- HD |
- F |
- 3482_VC_H_1987 |
-
-
- | 157 |
- HB_036_HD |
- HD |
- M |
- 3576_VC_H_1984 |
-
-
- | 158 |
- HB_037_HD |
- HD |
- F |
- 3579_VC_H_1983 |
-
-
- | 159 |
- HB_038_HD |
- HD |
- F |
- 3584_VC_H_2183 |
-
-
- | 160 |
- HB_039_HD |
- HD |
- NA |
- 3635_VC_H_2182 |
-
-
- | 161 |
- HB_041_HD |
- HD |
- F |
- 3695_CR_H_2267 |
-
-
- | 162 |
- HB_042_HD |
- HD |
- M |
- 3697_VC_H_1982 |
-
-
- | 163 |
- HB_043_HD |
- HD |
- NA |
- 3703_VC_H_2180 |
-
-
- | 164 |
- HB_044_HD |
- HD |
- NA |
- 3723_VC_H_2179 |
-
-
- | 165 |
- HB_046_HD |
- HD |
- F |
- 3735_VC_H_1981 |
-
-
- | 166 |
- HB_050_HD |
- HD |
- M |
- 3820_PF_H_2207 |
-
-
- | 167 |
- HB_051_HD |
- HD |
- F |
- 3849_CR_H_2262 |
-
-
- | 168 |
- HB_054_HD |
- HD |
- M |
- 3884_VC_H_2175 |
-
-
- | 169 |
- HB_056_HD |
- HD |
- NA |
- 4012_VC_H_2174 |
-
-
- | 170 |
- HB_057_HD |
- HD |
- NA |
- 4013_VC_H_2173 |
-
-
- | 171 |
- HB_059_HD |
- HD |
- NA |
- 4066_VC_H_2172 |
-
-
- | 172 |
- HB_060_HD |
- HD |
- NA |
- 4094_VC_H_2171 |
-
-
- | 173 |
- HB_061_HD |
- HD |
- F |
- 4116_VC_H_2170 |
-
-
- | 174 |
- HB_062_HD |
- HD |
- NA |
- 4121_VC_H_2169 |
-
-
- | 175 |
- HB_063_HD |
- HD |
- NA |
- 4215_VC_H_2167 |
-
-
- | 176 |
- HB_065_HD |
- HD |
- M |
- 4340_PF_H_2091 |
-
-
- | 177 |
- HB_066_HD |
- HD |
- F |
- 4344_VC_H_1977 |
-
-
- | 178 |
- HB_067_HD |
- HD |
- M |
- 4346_VC_H_2165 |
-
-
- | 179 |
- HB_069_HD |
- HD |
- F |
- 4356_VC_H_2164 |
-
-
- | 180 |
- HB_070_HD |
- HD |
- NA |
- 4386_CR_H_2249 |
-
-
- | 181 |
- HB_072_HD |
- HD |
- NA |
- 4404_VC_H_2161 |
-
-
- | 182 |
- HB_073_HD |
- HD |
- F |
- 4411_VC_H_1975 |
-
-
- | 183 |
- HB_074_HD |
- HD |
- NA |
- 4430_VC_H_2465 |
-
-
- | 184 |
- HB_075_HD |
- HD |
- M |
- 4470_VC_H_1974 |
-
-
- | 185 |
- HB_076_HD |
- HD |
- F |
- 4497_CR_H_1860 |
-
-
- | 186 |
- HB_077_HD |
- HD |
- M |
- 4509_CR_H_2244 |
-
-
- | 187 |
- HB_079_HD |
- HD |
- M |
- 4631_VC_H_1971 |
-
-
- | 188 |
- HB_080_HD |
- HD |
- F |
- 4653_PF_H_2083 |
-
-
- | 189 |
- HB_081_HD |
- HD |
- NA |
- 4678_CR_H_2242 |
-
-
- | 190 |
- HB_084_HD |
- HD |
- M |
- 4718_VC_H_2125 |
-
-
- | 191 |
- HB_090_HD |
- HD |
- NA |
- 4740_CR_H_2474 |
-
-
- | 192 |
- HB_094_HD |
- HD |
- NA |
- 4754_CR_H_2476 |
-
-
- | 193 |
- HB_098_HD |
- HD |
- NA |
- 4780_VC_H_2151 |
-
-
- | 194 |
- HB_101_HD |
- HD |
- F |
- 4809_VC_H_2148 |
-
-
- | 195 |
- HB_105_HD |
- HD |
- NA |
- 4819_CR_H_2238 |
-
-
- | 196 |
- HB_106_HD |
- HD |
- F |
- 4822_VC_H_1969 |
-
-
- | 197 |
- HB_108_HD |
- HD |
- M |
- 4826_VC_H_1968 |
-
-
- | 198 |
- HB_109_HD |
- HD |
- M |
- 4828_VC_H_2124 |
-
-
- | 199 |
- HB_115_HD |
- HD |
- NA |
- 4855_CR_H_2235 |
-
-
- | 200 |
- HB_121_HD |
- HD |
- F |
- 4902_VC_H_1967 |
-
-
- | 201 |
- HB_129_HD |
- HD |
- NA |
- 4938_VC_H_1966 |
-
-
- | 202 |
- HB_141_HD |
- HD |
- F |
- 4996_PF_H_2076 |
-
-
- | 203 |
- HB_152_HD |
- HD |
- NA |
- 5034_CR_H_2233 |
-
-
- | 204 |
- HB_153_HD |
- HD |
- M |
- 5043_VC_H_1960 |
-
-
- | 205 |
- HB_159_HD |
- HD |
- M |
- 5062_VC_H_1959 |
-
-
- | 206 |
- HB_172_HD |
- HD |
- F |
- 5114_PF_H_2070 |
-
-
- | 207 |
- HB_175_HD |
- HD |
- M |
- 5127_PF_H_2068 |
-
-
- | 208 |
- HB_180_HD |
- HD |
- M |
- 5148_VC_H_1944 |
-
-
- | 209 |
- HB_185_HD |
- HD |
- F |
- 5167_CR_H_2231 |
-
-
- | 210 |
- HB_188_HD |
- HD |
- F |
- 5172_VC_H_1951 |
-
-
- | 211 |
- HB_191_HD |
- HD |
- M |
- 5180_VC_H_1949 |
-
-
- | 212 |
- HB_196_HD |
- HD |
- NA |
- 5199_PF_H_2202 |
-
-
- | 213 |
- HB_203_HD |
- HD |
- F |
- 5228_PF_H_2059 |
-
-
- | 214 |
- HB_207_HD |
- HD |
- NA |
- 5248_PF_H_2201 |
-
-
- | 215 |
- HB_228_HD |
- HD |
- F |
- 5299_CR_H_2228 |
-
-
- | 216 |
- HB_233_HD |
- HD |
- M |
- 5312_VC_H_1938 |
-
-
- | 217 |
- HB_235_HD |
- HD |
- F |
- 5316_VC_H_1937 |
-
-
- | 218 |
- HB_242_HD |
- HD |
- F |
- 5328_PF_H_2048 |
-
-
- | 219 |
- HB_266_HD |
- HD |
- M |
- 5387_VC_H_1928 |
-
-
- | 220 |
- HB_271_HD |
- HD |
- M |
- 5394_PF_H_2039 |
-
-
- | 221 |
- HB_272_HD |
- HD |
- F |
- 5396_VC_H_1925 |
-
-
- | 222 |
- HB_279_HD |
- HD |
- F |
- 5409_VC_H_1924 |
-
-
- | 223 |
- HB_294_HD |
- HD |
- M |
- 5448_VC_H_1921 |
-
-
- | 224 |
- HB_301_HD |
- HD |
- NA |
- 5464_VC_H_1919 |
-
-
- | 225 |
- HB_304_HD |
- HD |
- F |
- 5471_VC_H_1918 |
-
-
- | 226 |
- HB_321_HD |
- HD |
- NA |
- 5522_PF_H_2199 |
-
-
- | 227 |
- HB_361_HD |
- HD |
- F |
- 5622_VC_H_2121 |
-
-
- | 228 |
- HB_370_HD |
- HD |
- M |
- 5645_VC_H_1904 |
-
-
- | 229 |
- HB_371_HD |
- HD |
- F |
- 5648_PF_H_2016 |
-
-
- | 230 |
- HB_384_HD |
- HD |
- F |
- 5688_PF_H_2012 |
-
-
- | 231 |
- HB_390_HD |
- HD |
- M |
- 5704_PF_H_2009 |
-
-
- | 232 |
- HB_393_HD |
- HD |
- F |
- 5709_VC_H_1895 |
-
-
- | 233 |
- HB_402_HD |
- HD |
- F |
- 5732_PF_H_2007 |
-
-
- | 234 |
- HB_405_HD |
- HD |
- NA |
- 5742_PF_H_2006 |
-
-
- | 235 |
- HB_407_HD |
- HD |
- M |
- 5745_PF_H_2005 |
-
-
- | 236 |
- HB_408_HD |
- HD |
- M |
- 5747_VC_H_1891 |
-
-
- | 237 |
- HB_415_HD |
- HD |
- NA |
- 5777_PF_H_1551 |
-
-
- | 238 |
- HB_417_HD |
- HD |
- M |
- 5784_PF_H_1554 |
-
-
- | 239 |
- HB_424_HD |
- HD |
- M |
- 5804_VC_H_1558 |
-
-
- | 240 |
- HB_444_HD |
- HD |
- M |
- 5856_VC_H_1567 |
-
-
- | 241 |
- HB_457_HD |
- HD |
- M |
- 5896_VC_H_1570 |
-
-
- | 242 |
- HB_466_HD |
- HD |
- M |
- 5910_PF_H_1572 |
-
-
- | 243 |
- HB_478_HD |
- HD |
- M |
- 5941_CR_H_1583 |
-
-
- | 244 |
- HB_487_HD |
- HD |
- F |
- 5964_VC_H_1597 |
-
-
- | 245 |
- HB_511_HD |
- HD |
- M |
- 6019_PF_H_2198 |
-
-
- | 246 |
- HB_513_HD |
- HD |
- F |
- 6024_VC_H_1612 |
-
-
- | 247 |
- HB_515_HD |
- HD |
- F |
- 6028_CR_H_1613 |
-
-
- | 248 |
- HB_518_HD |
- HD |
- M |
- 6033_VC_H_1618 |
-
-
- | 249 |
- HB_522_HD |
- HD |
- M |
- 6037_PF_H_1626 |
-
-
- | 250 |
- HB_527_HD |
- HD |
- F |
- 6047_VC_H_1639 |
-
-
- | 251 |
- HB_528_HD |
- HD |
- M |
- 6051_PF_H_1641 |
-
-
- | 252 |
- HB_530_HD |
- HD |
- M |
- 6054_VC_H_1648 |
-
-
- | 253 |
- HB_537_HD |
- HD |
- F |
- 6071_PF_H_1653 |
-
-
- | 254 |
- HB_549_HD |
- HD |
- M |
- 6119_CR_H_1670 |
-
-
- | 255 |
- HB_593_HD |
- HD |
- NA |
- 6219_CR_H_2567 |
-
-
- | 256 |
- HB_610_HD |
- HD |
- NA |
- 6275_PF_H_1692 |
-
-
- | 257 |
- HB_616_HD |
- HD |
- F |
- 6284_CR_H_1694 |
-
-
- | 258 |
- HB_626_HD |
- HD |
- M |
- 6315_VC_H_1702 |
-
-
- | 259 |
- HB_639_HD |
- HD |
- F |
- 6344_CR_H_1703 |
-
-
- | 260 |
- HB_649_HD |
- HD |
- F |
- 6382_CR_H_1709 |
-
-
- | 261 |
- HB_661_HD |
- HD |
- M |
- 6408_VC_H_1714 |
-
-
- | 262 |
- HB_682_HD |
- HD |
- M |
- 6467_PF_H_1725 |
-
-
- | 263 |
- HB_683_HD |
- HD |
- M |
- 6472_VC_H_1729 |
-
-
- | 264 |
- HB_691_HD |
- HD |
- F |
- 6493_VC_H_1732 |
-
-
- | 265 |
- HB_692_HD |
- HD |
- M |
- 6495_CR_H_1733 |
-
-
- | 266 |
- HB_707_HD |
- HD |
- M |
- 6535_PF_H_1737 |
-
-
- | 267 |
- HB_709_HD |
- HD |
- F |
- 6539_CR_H_1739 |
-
-
- | 268 |
- HB_725_HD |
- HD |
- M |
- 6572_PF_H_1746 |
-
-
- | 269 |
- HB_732_HD |
- HD |
- F |
- 6584_VC_H_1750 |
-
-
- | 270 |
- HB_734_HD |
- HD |
- F |
- 6587_CR_H_1751 |
-
-
- | 271 |
- HB_748_HD |
- HD |
- NA |
- 6615_VC_H_2315 |
-
-
- | 272 |
- HB_750_HD |
- HD |
- NA |
- 6628_PF_H_2326 |
-
-
- | 273 |
- HB_758_HD |
- HD |
- NA |
- 6643_VC_H_2602 |
-
-
- | 274 |
- HB_760_HD |
- HD |
- M |
- 6646_PF_H_1761 |
-
-
- | 275 |
- HB_762_HD |
- HD |
- M |
- 6650_VC_H_1765 |
-
-
- | 276 |
- HB_766_HD |
- HD |
- M |
- 6658_VC_H_1768 |
-
-
- | 277 |
- HB_768_HD |
- HD |
- NA |
- 6663_VC_H_1771 |
-
-
- | 278 |
- HB_769_HD |
- HD |
- M |
- 6666_VC_H_1774 |
-
-
- | 279 |
- HB_774_HD |
- HD |
- NA |
- 6689_PF_H_2344 |
-
-
- | 280 |
- HB_778_HD |
- HD |
- NA |
- 6696_PF_H_2356 |
-
-
- | 281 |
- HB_780_HD |
- HD |
- NA |
- 6704_PF_H_2362 |
-
-
- | 282 |
- HB_790_HD |
- HD |
- NA |
- 6788_PF_H_2389 |
-
-
- | 283 |
- HB_800_HD |
- HD |
- NA |
- 6807_PF_H_2419 |
-
-
- | 284 |
- HB_802_HD |
- HD |
- NA |
- 6811_PF_H_2425 |
-
-
- | 285 |
- HB_045_AD |
- AD |
- NA |
- 3734_CR_A_0122 |
-
-
- | 286 |
- HB_048_AD |
- AD |
- NA |
- 3791_CR_A_0128 |
-
-
- | 287 |
- HB_053_AD |
- AD |
- NA |
- 3877_CR_A_0134 |
-
-
- | 288 |
- HB_055_AD |
- AD |
- NA |
- 3893_VC_A_0142 |
-
-
- | 289 |
- HB_068_AD |
- AD |
- NA |
- 4349_VC_A_0148 |
-
-
- | 290 |
- HB_082_AD |
- AD |
- NA |
- 4712_CR_A_0309 |
-
-
- | 291 |
- HB_085_AD |
- AD |
- NA |
- 4726_VC_A_0311 |
-
-
- | 292 |
- HB_087_AD |
- AD |
- NA |
- 4730_CR_A_0315 |
-
-
- | 293 |
- HB_089_AD |
- AD |
- NA |
- 4733_VC_A_0320 |
-
-
- | 294 |
- HB_093_AD |
- AD |
- NA |
- 4749_VC_A_0323 |
-
-
- | 295 |
- HB_095_AD |
- AD |
- NA |
- 4759_CR_A_0327 |
-
-
- | 296 |
- HB_097_AD |
- AD |
- NA |
- 4773_CR_A_0866 |
-
-
- | 297 |
- HB_099_AD |
- AD |
- NA |
- 4785_VC_A_0332 |
-
-
- | 298 |
- HB_100_AD |
- AD |
- NA |
- 4795_VC_A_0335 |
-
-
- | 299 |
- HB_103_AD |
- AD |
- NA |
- 4811_VC_A_0341 |
-
-
- | 300 |
- HB_104_AD |
- AD |
- NA |
- 4813_CR_A_0345 |
-
-
- | 301 |
- HB_112_AD |
- AD |
- NA |
- 4842_VC_A_0870 |
-
-
- | 302 |
- HB_113_AD |
- AD |
- NA |
- 4850_CR_A_0351 |
-
-
- | 303 |
- HB_114_AD |
- AD |
- NA |
- 4852_CR_A_0354 |
-
-
- | 304 |
- HB_117_AD |
- AD |
- NA |
- 4868_VC_A_0874 |
-
-
- | 305 |
- HB_122_AD |
- AD |
- NA |
- 4904_CR_A_1132 |
-
-
- | 306 |
- HB_123_AD |
- AD |
- NA |
- 4905_VC_A_0884 |
-
-
- | 307 |
- HB_124_AD |
- AD |
- NA |
- 4916_VC_A_0886 |
-
-
- | 308 |
- HB_125_AD |
- AD |
- NA |
- 4917_CR_A_0360 |
-
-
- | 309 |
- HB_126_AD |
- AD |
- NA |
- 4921_VC_A_0362 |
-
-
- | 310 |
- HB_128_AD |
- AD |
- NA |
- 4936_CR_A_0369 |
-
-
- | 311 |
- HB_130_AD |
- AD |
- NA |
- 4939_VC_A_0888 |
-
-
- | 312 |
- HB_131_AD |
- AD |
- NA |
- 4944_CR_A_0889 |
-
-
- | 313 |
- HB_132_AD |
- AD |
- NA |
- 4946_CR_A_0372 |
-
-
- | 314 |
- HB_134_AD |
- AD |
- NA |
- 4951_CR_A_0891 |
-
-
- | 315 |
- HB_135_AD |
- AD |
- NA |
- 4953_VC_A_0893 |
-
-
- | 316 |
- HB_136_AD |
- AD |
- NA |
- 4965_VC_A_0160 |
-
-
- | 317 |
- HB_137_AD |
- AD |
- NA |
- 4966_VC_A_0374 |
-
-
- | 318 |
- HB_138_AD |
- AD |
- NA |
- 4969_VC_A_0895 |
-
-
- | 319 |
- HB_140_AD |
- AD |
- NA |
- 4993_CR_A_0896 |
-
-
- | 320 |
- HB_146_AD |
- AD |
- NA |
- 5018_CR_A_0384 |
-
-
- | 321 |
- HB_148_AD |
- AD |
- NA |
- 5022_VC_A_0386 |
-
-
- | 322 |
- HB_150_AD |
- AD |
- NA |
- 5031_VC_A_0392 |
-
-
- | 323 |
- HB_151_AD |
- AD |
- NA |
- 5033_CR_A_0396 |
-
-
- | 324 |
- HB_154_AD |
- AD |
- NA |
- 5048_VC_A_1321 |
-
-
- | 325 |
- HB_155_AD |
- AD |
- NA |
- 5056_VC_A_0398 |
-
-
- | 326 |
- HB_156_AD |
- AD |
- NA |
- 5057_VC_A_0163 |
-
-
- | 327 |
- HB_157_AD |
- AD |
- NA |
- 5059_VC_A_0401 |
-
-
- | 328 |
- HB_158_AD |
- AD |
- NA |
- 5061_PF_A_2612 |
-
-
- | 329 |
- HB_160_AD |
- AD |
- NA |
- 5064_PF_A_2615 |
-
-
- | 330 |
- HB_165_AD |
- AD |
- NA |
- 5092_CR_A_0899 |
-
-
- | 331 |
- HB_168_AD |
- AD |
- NA |
- 5097_VC_A_0407 |
-
-
- | 332 |
- HB_170_AD |
- AD |
- NA |
- 5101_VC_A_0410 |
-
-
- | 333 |
- HB_174_AD |
- AD |
- NA |
- 5124_PF_A_1343 |
-
-
- | 334 |
- HB_179_AD |
- AD |
- NA |
- 5145_VC_A_1351 |
-
-
- | 335 |
- HB_181_AD |
- AD |
- NA |
- 5152_CR_A_0414 |
-
-
- | 336 |
- HB_184_AD |
- AD |
- NA |
- 5166_VC_A_1354 |
-
-
- | 337 |
- HB_194_AD |
- AD |
- NA |
- 5193_VC_A_1360 |
-
-
- | 338 |
- HB_197_AD |
- AD |
- NA |
- 5202_CR_A_1368 |
-
-
- | 339 |
- HB_199_AD |
- AD |
- NA |
- 5205_VC_A_0166 |
-
-
- | 340 |
- HB_200_AD |
- AD |
- NA |
- 5210_VC_A_0905 |
-
-
- | 341 |
- HB_205_AD |
- AD |
- NA |
- 5235_VC_A_0419 |
-
-
- | 342 |
- HB_208_AD |
- AD |
- NA |
- 5249_VC_A_0422 |
-
-
- | 343 |
- HB_209_AD |
- AD |
- NA |
- 5252_VC_A_0907 |
-
-
- | 344 |
- HB_211_AD |
- AD |
- NA |
- 5257_VC_A_0169 |
-
-
- | 345 |
- HB_216_AD |
- AD |
- NA |
- 5272_VC_A_0425 |
-
-
- | 346 |
- HB_219_AD |
- AD |
- NA |
- 5279_CR_A_0147 |
-
-
- | 347 |
- HB_221_AD |
- AD |
- NA |
- 5283_VC_A_0145 |
-
-
- | 348 |
- HB_222_AD |
- AD |
- NA |
- 5285_VC_A_0141 |
-
-
- | 349 |
- HB_224_AD |
- AD |
- NA |
- 5288_VC_A_0428 |
-
-
- | 350 |
- HB_230_AD |
- AD |
- NA |
- 5301_VC_A_0174 |
-
-
- | 351 |
- HB_231_AD |
- AD |
- NA |
- 5305_VC_A_1384 |
-
-
- | 352 |
- HB_232_AD |
- AD |
- NA |
- 5310_CR_A_0176 |
-
-
- | 353 |
- HB_234_AD |
- AD |
- NA |
- 5313_PF_A_2618 |
-
-
- | 354 |
- HB_236_AD |
- AD |
- NA |
- 5317_PF_A_2624 |
-
-
- | 355 |
- HB_238_AD |
- AD |
- NA |
- 5322_CR_A_2632 |
-
-
- | 356 |
- HB_240_AD |
- AD |
- NA |
- 5325_VC_A_0137 |
-
-
- | 357 |
- HB_244_AD |
- AD |
- NA |
- 5337_VC_A_1387 |
-
-
- | 358 |
- HB_245_AD |
- AD |
- NA |
- 5339_VC_A_0181 |
-
-
- | 359 |
- HB_250_AD |
- AD |
- NA |
- 5346_VC_A_1393 |
-
-
- | 360 |
- HB_251_AD |
- AD |
- NA |
- 5350_VC_A_0184 |
-
-
- | 361 |
- HB_252_AD |
- AD |
- NA |
- 5355_VC_A_0133 |
-
-
- | 362 |
- HB_253_AD |
- AD |
- NA |
- 5359_CR_A_1395 |
-
-
- | 363 |
- HB_258_AD |
- AD |
- NA |
- 5370_PF_A_1400 |
-
-
- | 364 |
- HB_259_AD |
- AD |
- NA |
- 5371_PF_A_2636 |
-
-
- | 365 |
- HB_260_AD |
- AD |
- NA |
- 5375_VC_A_0188 |
-
-
- | 366 |
- HB_263_AD |
- AD |
- NA |
- 5381_VC_A_0022 |
-
-
- | 367 |
- HB_265_AD |
- AD |
- NA |
- 5385_VC_A_1402 |
-
-
- | 368 |
- HB_267_AD |
- AD |
- NA |
- 5389_VC_A_0928 |
-
-
- | 369 |
- HB_268_AD |
- AD |
- NA |
- 5390_CR_A_0151 |
-
-
- | 370 |
- HB_273_AD |
- AD |
- NA |
- 5400_PF_A_2645 |
-
-
- | 371 |
- HB_274_AD |
- AD |
- NA |
- 5401_VC_A_0931 |
-
-
- | 372 |
- HB_275_AD |
- AD |
- NA |
- 5404_PF_A_2648 |
-
-
- | 373 |
- HB_276_AD |
- AD |
- NA |
- 5406_VC_A_0933 |
-
-
- | 374 |
- HB_277_AD |
- AD |
- NA |
- 5407_PF_A_2651 |
-
-
- | 375 |
- HB_280_AD |
- AD |
- NA |
- 5412_VC_A_0935 |
-
-
- | 376 |
- HB_281_AD |
- AD |
- NA |
- 5413_PF_A_2657 |
-
-
- | 377 |
- HB_283_AD |
- AD |
- NA |
- 5419_VC_A_0937 |
-
-
- | 378 |
- HB_284_AD |
- AD |
- NA |
- 5420_VC_A_0939 |
-
-
- | 379 |
- HB_285_AD |
- AD |
- NA |
- 5421_CR_A_0432 |
-
-
- | 380 |
- HB_286_AD |
- AD |
- NA |
- 5423_PF_A_2660 |
-
-
- | 381 |
- HB_288_AD |
- AD |
- NA |
- 5425_PF_A_2666 |
-
-
- | 382 |
- HB_289_AD |
- AD |
- NA |
- 5426_VC_A_1405 |
-
-
- | 383 |
- HB_290_AD |
- AD |
- NA |
- 5433_VC_A_0434 |
-
-
- | 384 |
- HB_296_AD |
- AD |
- NA |
- 5456_PF_A_2675 |
-
-
- | 385 |
- HB_299_AD |
- AD |
- NA |
- 5461_VC_A_0192 |
-
-
- | 386 |
- HB_302_AD |
- AD |
- NA |
- 5465_PF_A_2678 |
-
-
- | 387 |
- HB_303_AD |
- AD |
- NA |
- 5469_VC_A_1417 |
-
-
- | 388 |
- HB_305_AD |
- AD |
- NA |
- 5479_PF_A_1421 |
-
-
- | 389 |
- HB_306_AD |
- AD |
- NA |
- 5480_VC_A_0437 |
-
-
- | 390 |
- HB_307_AD |
- AD |
- NA |
- 5482_VC_A_0028 |
-
-
- | 391 |
- HB_308_AD |
- AD |
- NA |
- 5483_VC_A_0941 |
-
-
- | 392 |
- HB_309_AD |
- AD |
- NA |
- 5487_CR_A_0441 |
-
-
- | 393 |
- HB_310_AD |
- AD |
- NA |
- 5488_CR_A_0194 |
-
-
- | 394 |
- HB_312_AD |
- AD |
- NA |
- 5500_VC_A_0198 |
-
-
- | 395 |
- HB_313_AD |
- AD |
- NA |
- 5502_PF_A_2684 |
-
-
- | 396 |
- HB_315_AD |
- AD |
- NA |
- 5513_PF_A_2687 |
-
-
- | 397 |
- HB_316_AD |
- AD |
- NA |
- 5516_PF_A_2690 |
-
-
- | 398 |
- HB_317_AD |
- AD |
- NA |
- 5517_PF_A_2693 |
-
-
- | 399 |
- HB_318_AD |
- AD |
- NA |
- 5518_CR_A_0030 |
-
-
- | 400 |
- HB_319_AD |
- AD |
- NA |
- 5519_CR_A_2695 |
-
-
- | 401 |
- HB_320_AD |
- AD |
- NA |
- 5520_PF_A_2699 |
-
-
- | 402 |
- HB_322_AD |
- AD |
- NA |
- 5527_VC_A_0945 |
-
-
- | 403 |
- HB_325_AD |
- AD |
- NA |
- 5532_PF_A_2702 |
-
-
- | 404 |
- HB_328_AD |
- AD |
- NA |
- 5541_PF_A_2705 |
-
-
- | 405 |
- HB_330_AD |
- AD |
- NA |
- 5544_VC_A_0201 |
-
-
- | 406 |
- HB_334_AD |
- AD |
- NA |
- 5554_VC_A_0452 |
-
-
- | 407 |
- HB_335_AD |
- AD |
- NA |
- 5557_VC_A_0950 |
-
-
- | 408 |
- HB_337_AD |
- AD |
- NA |
- 5560_VC_A_0204 |
-
-
- | 409 |
- HB_342_AD |
- AD |
- NA |
- 5571_PF_A_1430 |
-
-
- | 410 |
- HB_345_AD |
- AD |
- NA |
- 5583_PF_A_2708 |
-
-
- | 411 |
- HB_347_AD |
- AD |
- NA |
- 5589_PF_A_2714 |
-
-
- | 412 |
- HB_349_AD |
- AD |
- NA |
- 5592_PF_A_2717 |
-
-
- | 413 |
- HB_352_AD |
- AD |
- NA |
- 5604_VC_A_0037 |
-
-
- | 414 |
- HB_353_AD |
- AD |
- NA |
- 5607_PF_A_2723 |
-
-
- | 415 |
- HB_356_AD |
- AD |
- NA |
- 5615_VC_A_0041 |
-
-
- | 416 |
- HB_357_AD |
- AD |
- NA |
- 5616_CR_A_0127 |
-
-
- | 417 |
- HB_358_AD |
- AD |
- NA |
- 5617_CR_A_0456 |
-
-
- | 418 |
- HB_359_AD |
- AD |
- NA |
- 5618_CR_A_0044 |
-
-
- | 419 |
- HB_362_AD |
- AD |
- NA |
- 5625_CR_A_2495 |
-
-
- | 420 |
- HB_363_AD |
- AD |
- NA |
- 5626_CR_A_2498 |
-
-
- | 421 |
- HB_364_AD |
- AD |
- NA |
- 5629_CR_A_0390 |
-
-
- | 422 |
- HB_369_AD |
- AD |
- NA |
- 5643_VC_A_1143 |
-
-
- | 423 |
- HB_373_AD |
- AD |
- NA |
- 5654_VC_A_0047 |
-
-
- | 424 |
- HB_375_AD |
- AD |
- NA |
- 5660_CR_A_0462 |
-
-
- | 425 |
- HB_376_AD |
- AD |
- NA |
- 5661_VC_A_0464 |
-
-
- | 426 |
- HB_377_AD |
- AD |
- NA |
- 5667_VC_A_2509 |
-
-
- | 427 |
- HB_378_AD |
- AD |
- NA |
- 5668_VC_A_1438 |
-
-
- | 428 |
- HB_383_AD |
- AD |
- NA |
- 5686_CR_A_2728 |
-
-
- | 429 |
- HB_386_AD |
- AD |
- NA |
- 5695_VC_A_0953 |
-
-
- | 430 |
- HB_389_AD |
- AD |
- NA |
- 5700_VC_A_2514 |
-
-
- | 431 |
- HB_391_AD |
- AD |
- NA |
- 5705_CR_A_0474 |
-
-
- | 432 |
- HB_392_AD |
- AD |
- NA |
- 5706_VC_A_0476 |
-
-
- | 433 |
- HB_394_AD |
- AD |
- NA |
- 5713_VC_A_0479 |
-
-
- | 434 |
- HB_397_AD |
- AD |
- NA |
- 5721_CR_A_0210 |
-
-
- | 435 |
- HB_404_AD |
- AD |
- NA |
- 5735_CR_A_0489 |
-
-
- | 436 |
- HB_406_AD |
- AD |
- NA |
- 5744_CR_A_0960 |
-
-
- | 437 |
- HB_409_AD |
- AD |
- NA |
- 5749_CR_A_0159 |
-
-
- | 438 |
- HB_410_AD |
- AD |
- NA |
- 5751_CR_A_2518 |
-
-
- | 439 |
- HB_411_AD |
- AD |
- NA |
- 5755_CR_A_2731 |
-
-
- | 440 |
- HB_413_AD |
- AD |
- NA |
- 5766_VC_A_0214 |
-
-
- | 441 |
- HB_419_AD |
- AD |
- NA |
- 5790_VC_A_0217 |
-
-
- | 442 |
- HB_420_AD |
- AD |
- NA |
- 5796_CR_A_0964 |
-
-
- | 443 |
- HB_428_AD |
- AD |
- NA |
- 5811_CR_A_2524 |
-
-
- | 444 |
- HB_429_AD |
- AD |
- NA |
- 5819_CR_A_2527 |
-
-
- | 445 |
- HB_430_AD |
- AD |
- NA |
- 5822_CR_A_2530 |
-
-
- | 446 |
- HB_434_AD |
- AD |
- NA |
- 5828_CR_A_2533 |
-
-
- | 447 |
- HB_435_AD |
- AD |
- NA |
- 5831_CR_A_0222 |
-
-
- | 448 |
- HB_437_AD |
- AD |
- NA |
- 5839_CR_A_2539 |
-
-
- | 449 |
- HB_438_AD |
- AD |
- NA |
- 5843_CR_A_0227 |
-
-
- | 450 |
- HB_439_AD |
- AD |
- NA |
- 5845_CR_A_0230 |
-
-
- | 451 |
- HB_441_AD |
- AD |
- NA |
- 5849_CR_A_0233 |
-
-
- | 452 |
- HB_442_AD |
- AD |
- NA |
- 5850_CR_A_0495 |
-
-
- | 453 |
- HB_445_AD |
- AD |
- NA |
- 5858_CR_A_0969 |
-
-
- | 454 |
- HB_448_AD |
- AD |
- NA |
- 5864_CR_A_0974 |
-
-
- | 455 |
- HB_451_AD |
- AD |
- NA |
- 5871_CR_A_2542 |
-
-
- | 456 |
- HB_454_AD |
- AD |
- NA |
- 5879_CR_A_2545 |
-
-
- | 457 |
- HB_455_AD |
- AD |
- NA |
- 5887_CR_A_0976_Bis |
-
-
- | 458 |
- HB_459_AD |
- AD |
- NA |
- 5898_CR_A_2548 |
-
-
- | 459 |
- HB_460_AD |
- AD |
- NA |
- 5900_VC_A_0237 |
-
-
- | 460 |
- HB_461_AD |
- AD |
- NA |
- 5901_CR_A_0239 |
-
-
- | 461 |
- HB_469_AD |
- AD |
- NA |
- 5914_CR_A_2554 |
-
-
- | 462 |
- HB_471_AD |
- AD |
- NA |
- 5922_VC_A_0246 |
-
-
- | 463 |
- HB_473_AD |
- AD |
- NA |
- 5927_CR_A_2560 |
-
-
- | 464 |
- HB_474_AD |
- AD |
- NA |
- 5933_VC_A_1071 |
-
-
- | 465 |
- HB_477_AD |
- AD |
- NA |
- 5939_CR_A_1151 |
-
-
- | 466 |
- HB_479_AD |
- AD |
- NA |
- 5945_VC_A_0983 |
-
-
- | 467 |
- HB_484_AD |
- AD |
- NA |
- 5956_CR_A_0123 |
-
-
- | 468 |
- HB_489_AD |
- AD |
- NA |
- 5968_VC_A_1075 |
-
-
- | 469 |
- HB_491_AD |
- AD |
- NA |
- 5971_CR_A_0119 |
-
-
- | 470 |
- HB_492_AD |
- AD |
- NA |
- 5972_VC_A_0251 |
-
-
- | 471 |
- HB_494_AD |
- AD |
- NA |
- 5979_CR_A_0115 |
-
-
- | 472 |
- HB_498_AD |
- AD |
- NA |
- 5988_VC_A_0503 |
-
-
- | 473 |
- HB_502_AD |
- AD |
- NA |
- 5994_PF_A_1605 |
-
-
- | 474 |
- HB_503_AD |
- AD |
- NA |
- 5995_CR_A_2563 |
-
-
- | 475 |
- HB_510_AD |
- AD |
- NA |
- 6017_CR_A_0048 |
-
-
- | 476 |
- HB_514_AD |
- AD |
- NA |
- 6025_VC_A_0506 |
-
-
- | 477 |
- HB_517_AD |
- AD |
- NA |
- 6031_VC_A_0258 |
-
-
- | 478 |
- HB_520_AD |
- AD |
- NA |
- 6035_VC_A_1621 |
-
-
- | 479 |
- HB_523_AD |
- AD |
- NA |
- 6038_VC_A_0261 |
-
-
- | 480 |
- HB_524_AD |
- AD |
- NA |
- 6042_VC_A_1156 |
-
-
- | 481 |
- HB_525_AD |
- AD |
- NA |
- 6044_VC_A_0264 |
-
-
- | 482 |
- HB_531_AD |
- AD |
- NA |
- 6056_CR_A_0999 |
-
-
- | 483 |
- HB_533_AD |
- AD |
- NA |
- 6061_PF_A_1650 |
-
-
- | 484 |
- HB_534_AD |
- AD |
- NA |
- 6066_VC_A_0270 |
-
-
- | 485 |
- HB_535_AD |
- AD |
- NA |
- 6067_PF_A_1452 |
-
-
- | 486 |
- HB_536_AD |
- AD |
- NA |
- 6068_VC_A_0273 |
-
-
- | 487 |
- HB_545_AD |
- AD |
- NA |
- 6102_CR_A_1661 |
-
-
- | 488 |
- HB_546_AD |
- AD |
- NA |
- 6107_CR_A_0055 |
-
-
- | 489 |
- HB_550_AD |
- AD |
- NA |
- 6120_VC_A_0058 |
-
-
- | 490 |
- HB_552_AD |
- AD |
- NA |
- 6126_VC_A_1675 |
-
-
- | 491 |
- HB_553_AD |
- AD |
- NA |
- 6129_PF_A_0274 |
-
-
- | 492 |
- HB_554_AD |
- AD |
- NA |
- 6130_VC_A_1678 |
-
-
- | 493 |
- HB_555_AD |
- AD |
- NA |
- 6131_CR_A_0510 |
-
-
- | 494 |
- HB_556_AD |
- AD |
- NA |
- 6132_CR_A_0513 |
-
-
- | 495 |
- HB_558_AD |
- AD |
- NA |
- 6137_VC_A_1681 |
-
-
- | 496 |
- HB_564_AD |
- AD |
- NA |
- 6153_VC_A_1465 |
-
-
- | 497 |
- HB_565_AD |
- AD |
- NA |
- 6154_VC_A_1468 |
-
-
- | 498 |
- HB_566_AD |
- AD |
- NA |
- 6157_VC_A_0062 |
-
-
- | 499 |
- HB_568_AD |
- AD |
- NA |
- 6164_CR_A_1005 |
-
-
- | 500 |
- HB_571_AD |
- AD |
- NA |
- 6171_CR_A_0065 |
-
-
- | 501 |
- HB_573_AD |
- AD |
- NA |
- 6174_VC_A_0068 |
-
-
- | 502 |
- HB_576_AD |
- AD |
- NA |
- 6180_CR_A_0281 |
-
-
- | 503 |
- HB_583_AD |
- AD |
- NA |
- 6194_VC_A_0071 |
-
-
- | 504 |
- HB_585_AD |
- AD |
- NA |
- 6198_VC_A_0073 |
-
-
- | 505 |
- HB_590_AD |
- AD |
- NA |
- 6215_VC_A_0518 |
-
-
- | 506 |
- HB_591_AD |
- AD |
- NA |
- 6216_VC_A_1476 |
-
-
- | 507 |
- HB_592_AD |
- AD |
- NA |
- 6218_CR_A_0522 |
-
-
- | 508 |
- HB_594_AD |
- AD |
- NA |
- 6223_VC_A_0288 |
-
-
- | 509 |
- HB_596_AD |
- AD |
- NA |
- 6226_CR_A_0076 |
-
-
- | 510 |
- HB_597_AD |
- AD |
- NA |
- 6227_VC_A_0080 |
-
-
- | 511 |
- HB_598_AD |
- AD |
- NA |
- 6231_VC_A_1479 |
-
-
- | 512 |
- HB_605_AD |
- AD |
- NA |
- 6261_VC_A_0084 |
-
-
- | 513 |
- HB_608_AD |
- AD |
- NA |
- 6268_CR_A_0525 |
-
-
- | 514 |
- HB_611_AD |
- AD |
- NA |
- 6279_VC_A_0089 |
-
-
- | 515 |
- HB_612_AD |
- AD |
- NA |
- 6280_VC_A_0091 |
-
-
- | 516 |
- HB_613_AD |
- AD |
- NA |
- 6281_CR_A_0528 |
-
-
- | 517 |
- HB_621_AD |
- AD |
- NA |
- 6308_VC_A_1503 |
-
-
- | 518 |
- HB_623_AD |
- AD |
- NA |
- 6311_CR_A_0531 |
-
-
- | 519 |
- HB_624_AD |
- AD |
- NA |
- 6312_CR_A_0534 |
-
-
- | 520 |
- HB_630_AD |
- AD |
- NA |
- 6324_PF_A_1514 |
-
-
- | 521 |
- HB_633_AD |
- AD |
- NA |
- 6332_VC_A_1518 |
-
-
- | 522 |
- HB_634_AD |
- AD |
- NA |
- 6335_VC_A_0536 |
-
-
- | 523 |
- HB_635_AD |
- AD |
- NA |
- 6336_CR_A_0290 |
-
-
- | 524 |
- HB_636_AD |
- AD |
- NA |
- 6338_VC_A_0539 |
-
-
- | 525 |
- HB_642_AD |
- AD |
- NA |
- 6358_VC_A_0545 |
-
-
- | 526 |
- HB_652_AD |
- AD |
- NA |
- 6387_VC_A_0093 |
-
-
- | 527 |
- HB_657_AD |
- AD |
- NA |
- 6394_VC_A_0551 |
-
-
- | 528 |
- HB_664_AD |
- AD |
- NA |
- 6416_VC_A_1095 |
-
-
- | 529 |
- HB_666_AD |
- AD |
- NA |
- 6422_CR_A_0555 |
-
-
- | 530 |
- HB_669_AD |
- AD |
- NA |
- 6431_VC_A_0294 |
-
-
- | 531 |
- HB_674_AD |
- AD |
- NA |
- 6449_VC_A_1183 |
-
-
- | 532 |
- HB_680_AD |
- AD |
- NA |
- 6458_CR_A_2570 |
-
-
- | 533 |
- HB_685_AD |
- AD |
- NA |
- 6481_VC_A_0560 |
-
-
- | 534 |
- HB_690_AD |
- AD |
- NA |
- 6489_CR_A_0100 |
-
-
- | 535 |
- HB_696_AD |
- AD |
- NA |
- 6511_VC_A_1119 |
-
-
- | 536 |
- HB_698_AD |
- AD |
- NA |
- 6515_CR_A_0564 |
-
-
- | 537 |
- HB_699_AD |
- AD |
- NA |
- 6518_VC_A_0103 |
-
-
- | 538 |
- HB_703_AD |
- AD |
- NA |
- 6523_VC_A_0107 |
-
-
- | 539 |
- HB_704_AD |
- AD |
- NA |
- 6530_VC_A_0112 |
-
-
- | 540 |
- HB_706_AD |
- AD |
- NA |
- 6534_VC_A_0306 |
-
-
- | 541 |
- HB_712_AD |
- AD |
- NA |
- 6546_PF_A_1194 |
-
-
- | 542 |
- HB_713_AD |
- AD |
- NA |
- 6548_PF_A_1541 |
-
-
- | 543 |
- HB_715_AD |
- AD |
- NA |
- 6550_VC_A_1201 |
-
-
- | 544 |
- HB_718_AD |
- AD |
- NA |
- 6554_PF_A_1203 |
-
-
- | 545 |
- HB_720_AD |
- AD |
- NA |
- 6559_PF_A_2287 |
-
-
- | 546 |
- HB_722_AD |
- AD |
- NA |
- 6561_CR_A_2582 |
-
-
- | 547 |
- HB_723_AD |
- AD |
- NA |
- 6562_PF_A_2290 |
-
-
- | 548 |
- HB_724_AD |
- AD |
- NA |
- 6564_CR_A_2585 |
-
-
- | 549 |
- HB_727_AD |
- AD |
- NA |
- 6575_CR_A_2298 |
-
-
- | 550 |
- HB_728_AD |
- AD |
- NA |
- 6577_PF_A_2299 |
-
-
- | 551 |
- HB_729_AD |
- AD |
- NA |
- 6578_PF_A_2302 |
-
-
- | 552 |
- HB_731_AD |
- AD |
- NA |
- 6582_VC_A_1207 |
-
-
- | 553 |
- HB_733_AD |
- AD |
- NA |
- 6585_VC_A_1210 |
-
-
- | 554 |
- HB_736_AD |
- AD |
- NA |
- 6590_PF_A_1215 |
-
-
- | 555 |
- HB_743_AD |
- AD |
- NA |
- 6603_PF_A_1448 |
-
-
- | 556 |
- HB_745_AD |
- AD |
- NA |
- 6610_PF_A_1227 |
-
-
- | 557 |
- HB_746_AD |
- AD |
- NA |
- 6612_PF_A_2308 |
-
-
- | 558 |
- HB_749_AD |
- AD |
- NA |
- 6617_VC_A_2587 |
-
-
- | 559 |
- HB_751_AD |
- AD |
- NA |
- 6629_VC_A_2330 |
-
-
- | 560 |
- HB_752_AD |
- AD |
- NA |
- 6630_VC_A_2590 |
-
-
- | 561 |
- HB_753_AD |
- AD |
- NA |
- 6632_PF_A_2332 |
-
-
- | 562 |
- HB_754_AD |
- AD |
- NA |
- 6637_VC_A_2596 |
-
-
- | 563 |
- HB_755_AD |
- AD |
- NA |
- 6638_VC_A_2599 |
-
-
- | 564 |
- HB_756_AD |
- AD |
- NA |
- 6639_VC_A_2336 |
-
-
- | 565 |
- HB_757_AD |
- AD |
- NA |
- 6641_PF_A_2338 |
-
-
- | 566 |
- HB_763_AD |
- AD |
- NA |
- 6654_VC_A_1237 |
-
-
- | 567 |
- HB_773_AD |
- AD |
- NA |
- 6681_VC_A_1252 |
-
-
- | 568 |
- HB_775_AD |
- AD |
- NA |
- 6693_VC_A_2348 |
-
-
- | 569 |
- HB_776_AD |
- AD |
- NA |
- 6694_VC_A_2351 |
-
-
- | 570 |
- HB_777_AD |
- AD |
- NA |
- 6695_PF_A_2353 |
-
-
- | 571 |
- HB_779_AD |
- AD |
- NA |
- 6699_PF_A_2359 |
-
-
- | 572 |
- HB_781_AD |
- AD |
- NA |
- 6708_VC_A_2366 |
-
-
- | 573 |
- HB_782_AD |
- AD |
- NA |
- 6776_PF_A_2607 |
-
-
- | 574 |
- HB_783_AD |
- AD |
- NA |
- 6778_PF_A_2368 |
-
-
- | 575 |
- HB_784_AD |
- AD |
- NA |
- 6779_PF_A_2371 |
-
-
- | 576 |
- HB_785_AD |
- AD |
- NA |
- 6780_PF_A_2374 |
-
-
- | 577 |
- HB_786_AD |
- AD |
- NA |
- 6782_PF_A_2377 |
-
-
- | 578 |
- HB_787_AD |
- AD |
- NA |
- 6784_PF_A_2380 |
-
-
- | 579 |
- HB_788_AD |
- AD |
- NA |
- 6785_CR_A_2385 |
-
-
- | 580 |
- HB_789_AD |
- AD |
- NA |
- 6787_CR_A_2388 |
-
-
- | 581 |
- HB_791_AD |
- AD |
- NA |
- 6790_PF_A_2392 |
-
-
- | 582 |
- HB_792_AD |
- AD |
- NA |
- 6791_PF_A_2395 |
-
-
- | 583 |
- HB_793_AD |
- AD |
- NA |
- 6793_PF_A_2398 |
-
-
- | 584 |
- HB_794_AD |
- AD |
- NA |
- 6794_PF_A_2401 |
-
-
- | 585 |
- HB_795_AD |
- AD |
- NA |
- 6797_PF_A_2404 |
-
-
- | 586 |
- HB_796_AD |
- AD |
- NA |
- 6798_PF_A_2407 |
-
-
- | 587 |
- HB_797_AD |
- AD |
- NA |
- 6799_VC_A_2411 |
-
-
- | 588 |
- HB_798_AD |
- AD |
- NA |
- 6801_VC_A_2414 |
-
-
- | 589 |
- HB_799_AD |
- AD |
- NA |
- 6803_VC_A_2417 |
-
-
- | 590 |
- HB_801_AD |
- AD |
- NA |
- 6809_PF_A_2422 |
-
-
- | 591 |
- HB_803_AD |
- AD |
- NA |
- 6818_CR_A_2430 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/HBTRC_MLC_0611/experiment-design.rtf b/general/datasets/HBTRC_MLC_0611/experiment-design.rtf
deleted file mode 100644
index 3b0c224..0000000
--- a/general/datasets/HBTRC_MLC_0611/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
diff --git a/general/datasets/HBTRC_MLC_0611/notes.rtf b/general/datasets/HBTRC_MLC_0611/notes.rtf
deleted file mode 100644
index ff90e34..0000000
--- a/general/datasets/HBTRC_MLC_0611/notes.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Species: Human
-Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
-Disease: Neurological Disease
-Investigator: Francine Benes/ Eric Schadt
-Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
-Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC_MLC_0611/summary.rtf b/general/datasets/HBTRC_MLC_0611/summary.rtf
deleted file mode 100644
index 5cde3bf..0000000
--- a/general/datasets/HBTRC_MLC_0611/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC_MLC_AD_0611/acknowledgment.rtf b/general/datasets/HBTRC_MLC_AD_0611/acknowledgment.rtf
deleted file mode 100644
index 208cb6e..0000000
--- a/general/datasets/HBTRC_MLC_AD_0611/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC_MLC_AD_0611/cases.rtf b/general/datasets/HBTRC_MLC_AD_0611/cases.rtf
deleted file mode 100644
index e64114d..0000000
--- a/general/datasets/HBTRC_MLC_AD_0611/cases.rtf
+++ /dev/null
@@ -1,4156 +0,0 @@
-
-
-
-
-
-
-
- | Series |
- Cerebellum in GN |
- Condition |
- Gender |
- BioSample Name |
-
-
- | 1 |
- HB_029_N |
- N |
- NA |
- 3405_VC_N_0859 |
-
-
- | 2 |
- HB_058_N |
- N |
- NA |
- 4021_VC_N_0854 |
-
-
- | 3 |
- HB_064_N |
- N |
- NA |
- 4338_VC_N_0861 |
-
-
- | 4 |
- HB_086_N |
- N |
- NA |
- 4729_PF_N_0756 |
-
-
- | 5 |
- HB_091_N |
- N |
- NA |
- 4741_VC_N_0864 |
-
-
- | 6 |
- HB_092_N |
- N |
- NA |
- 4744_VC_N_0865 |
-
-
- | 7 |
- HB_102_N |
- N |
- NA |
- 4810_VC_N_0869 |
-
-
- | 8 |
- HB_119_N |
- N |
- NA |
- 4872_VC_N_0878 |
-
-
- | 9 |
- HB_147_N |
- N |
- NA |
- 5021_VC_N_0852 |
-
-
- | 10 |
- HB_161_N |
- N |
- NA |
- 5077_VC_N_0851 |
-
-
- | 11 |
- HB_162_N |
- N |
- NA |
- 5081_VC_N_1021 |
-
-
- | 12 |
- HB_166_N |
- N |
- NA |
- 5095_VC_N_1024 |
-
-
- | 13 |
- HB_183_N |
- N |
- NA |
- 5162_VC_N_0850 |
-
-
- | 14 |
- HB_206_N |
- N |
- NA |
- 5245_VC_N_0849 |
-
-
- | 15 |
- HB_215_N |
- N |
- NA |
- 5270_VC_N_0848 |
-
-
- | 16 |
- HB_218_N |
- N |
- NA |
- 5276_CR_N_0912 |
-
-
- | 17 |
- HB_223_N |
- N |
- NA |
- 5287_VC_N_0916 |
-
-
- | 18 |
- HB_226_N |
- N |
- NA |
- 5294_VC_N_0919 |
-
-
- | 19 |
- HB_241_N |
- N |
- NA |
- 5326_CR_N_0652 |
-
-
- | 20 |
- HB_243_N |
- N |
- NA |
- 5333_VC_N_1262 |
-
-
- | 21 |
- HB_247_N |
- N |
- NA |
- 5341_VC_N_0923 |
-
-
- | 22 |
- HB_257_N |
- N |
- NA |
- 5368_PF_N_1032 |
-
-
- | 23 |
- HB_264_N |
- N |
- NA |
- 5384_VC_N_0924 |
-
-
- | 24 |
- HB_295_N |
- N |
- NA |
- 5452_VC_N_1268 |
-
-
- | 25 |
- HB_300_N |
- N |
- NA |
- 5463_VC_N_0845 |
-
-
- | 26 |
- HB_311_N |
- N |
- NA |
- 5489_CR_N_0942 |
-
-
- | 27 |
- HB_324_N |
- N |
- NA |
- 5531_VC_N_0844 |
-
-
- | 28 |
- HB_332_N |
- N |
- NA |
- 5547_VC_N_0843 |
-
-
- | 29 |
- HB_340_N |
- N |
- NA |
- 5568_VC_N_0842 |
-
-
- | 30 |
- HB_360_N |
- N |
- NA |
- 5619_CR_N_0645 |
-
-
- | 31 |
- HB_365_N |
- N |
- NA |
- 5632_VC_N_0838 |
-
-
- | 32 |
- HB_367_N |
- N |
- NA |
- 5637_VC_N_0837 |
-
-
- | 33 |
- HB_382_N |
- N |
- NA |
- 5684_PF_N_1270 |
-
-
- | 34 |
- HB_396_N |
- N |
- NA |
- 5718_VC_N_0956 |
-
-
- | 35 |
- HB_398_N |
- N |
- NA |
- 5722_VC_N_1044 |
-
-
- | 36 |
- HB_400_N |
- N |
- NA |
- 5726_VC_N_0834_Bis |
-
-
- | 37 |
- HB_403_N |
- N |
- NA |
- 5734_VC_N_0833 |
-
-
- | 38 |
- HB_414_N |
- N |
- NA |
- 5772_VC_N_0832_Bis |
-
-
- | 39 |
- HB_416_N |
- N |
- NA |
- 5778_CR_N_0962 |
-
-
- | 40 |
- HB_418_N |
- N |
- NA |
- 5789_PF_N_1273 |
-
-
- | 41 |
- HB_421_N |
- N |
- NA |
- 5799_VC_N_1058 |
-
-
- | 42 |
- HB_423_N |
- N |
- NA |
- 5803_VC_N_0966 |
-
-
- | 43 |
- HB_426_N |
- N |
- NA |
- 5806_PF_N_1064 |
-
-
- | 44 |
- HB_427_N |
- N |
- NA |
- 5810_CR_N_0636 |
-
-
- | 45 |
- HB_431_N |
- N |
- NA |
- 5823_VC_N_0829 |
-
-
- | 46 |
- HB_432_N |
- N |
- NA |
- 5826_VC_N_0828 |
-
-
- | 47 |
- HB_433_N |
- N |
- NA |
- 5827_VC_N_0827 |
-
-
- | 48 |
- HB_436_N |
- N |
- NA |
- 5832_PF_N_1145 |
-
-
- | 49 |
- HB_443_N |
- N |
- NA |
- 5852_VC_N_0826 |
-
-
- | 50 |
- HB_446_N |
- N |
- NA |
- 5859_VC_N_0825 |
-
-
- | 51 |
- HB_449_N |
- N |
- NA |
- 5866_VC_N_0824 |
-
-
- | 52 |
- HB_450_N |
- N |
- NA |
- 5867_VC_N_1277 |
-
-
- | 53 |
- HB_453_N |
- N |
- NA |
- 5876_VC_N_0823 |
-
-
- | 54 |
- HB_462_N |
- N |
- NA |
- 5903_VC_N_0822 |
-
-
- | 55 |
- HB_464_N |
- N |
- NA |
- 5905_VC_N_0820 |
-
-
- | 56 |
- HB_468_N |
- N |
- NA |
- 5912_VC_N_1286 |
-
-
- | 57 |
- HB_472_N |
- N |
- NA |
- 5925_VC_N_1289 |
-
-
- | 58 |
- HB_475_N |
- N |
- NA |
- 5936_VC_N_0979 |
-
-
- | 59 |
- HB_476_N |
- N |
- NA |
- 5938_VC_N_0819 |
-
-
- | 60 |
- HB_480_N |
- N |
- NA |
- 5946_VC_N_0985 |
-
-
- | 61 |
- HB_485_N |
- N |
- NA |
- 5959_VC_N_0818 |
-
-
- | 62 |
- HB_486_N |
- N |
- NA |
- 5963_VC_N_0987 |
-
-
- | 63 |
- HB_495_N |
- N |
- NA |
- 5980_VC_N_0989 |
-
-
- | 64 |
- HB_497_N |
- N |
- NA |
- 5985_VC_N_0990 |
-
-
- | 65 |
- HB_500_N |
- N |
- NA |
- 5990_VC_N_0817 |
-
-
- | 66 |
- HB_501_N |
- N |
- NA |
- 5991_VC_N_0816 |
-
-
- | 67 |
- HB_504_N |
- N |
- NA |
- 5996_VC_N_0815 |
-
-
- | 68 |
- HB_505_N |
- N |
- NA |
- 5998_VC_N_0814 |
-
-
- | 69 |
- HB_507_N |
- N |
- NA |
- 6006_VC_N_0813 |
-
-
- | 70 |
- HB_508_N |
- N |
- NA |
- 6007_CR_N_0618 |
-
-
- | 71 |
- HB_509_N |
- N |
- NA |
- 6008_PF_N_1081 |
-
-
- | 72 |
- HB_512_N |
- N |
- NA |
- 6023_PF_N_1155 |
-
-
- | 73 |
- HB_516_N |
- N |
- NA |
- 6030_VC_N_0810 |
-
-
- | 74 |
- HB_519_N |
- N |
- NA |
- 6034_VC_N_0809 |
-
-
- | 75 |
- HB_532_N |
- N |
- NA |
- 6060_VC_N_1292 |
-
-
- | 76 |
- HB_541_N |
- N |
- NA |
- 6092_VC_N_1001 |
-
-
- | 77 |
- HB_542_N |
- N |
- NA |
- 6096_VC_N_0807 |
-
-
- | 78 |
- HB_544_N |
- N |
- NA |
- 6101_CR_N_1161 |
-
-
- | 79 |
- HB_547_N |
- N |
- NA |
- 6110_VC_N_1295 |
-
-
- | 80 |
- HB_551_N |
- N |
- NA |
- 6124_VC_N_0806 |
-
-
- | 81 |
- HB_557_N |
- N |
- NA |
- 6134_PF_N_1297 |
-
-
- | 82 |
- HB_560_N |
- N |
- NA |
- 6142_VC_N_0805 |
-
-
- | 83 |
- HB_569_N |
- N |
- NA |
- 6166_VC_N_0804 |
-
-
- | 84 |
- HB_570_N |
- N |
- NA |
- 6170_VC_N_0803 |
-
-
- | 85 |
- HB_572_N |
- N |
- NA |
- 6172_VC_N_1008 |
-
-
- | 86 |
- HB_577_N |
- N |
- NA |
- 6182_VC_N_1166 |
-
-
- | 87 |
- HB_579_N |
- N |
- NA |
- 6187_CR_N_0607 |
-
-
- | 88 |
- HB_581_N |
- N |
- NA |
- 6191_VC_N_1010 |
-
-
- | 89 |
- HB_584_N |
- N |
- NA |
- 6196_CR_N_0605 |
-
-
- | 90 |
- HB_586_N |
- N |
- NA |
- 6200_VC_N_0799 |
-
-
- | 91 |
- HB_587_N |
- N |
- NA |
- 6206_PF_N_1176 |
-
-
- | 92 |
- HB_589_N |
- N |
- NA |
- 6213_VC_N_0798 |
-
-
- | 93 |
- HB_601_N |
- N |
- NA |
- 6241_VC_N_0796 |
-
-
- | 94 |
- HB_604_N |
- N |
- NA |
- 6260_VC_N_0794 |
-
-
- | 95 |
- HB_609_N |
- N |
- NA |
- 6270_VC_N_0793 |
-
-
- | 96 |
- HB_618_N |
- N |
- NA |
- 6289_VC_N_0791 |
-
-
- | 97 |
- HB_622_N |
- N |
- NA |
- 6310_VC_N_0790 |
-
-
- | 98 |
- HB_625_N |
- N |
- NA |
- 6314_VC_N_0789 |
-
-
- | 99 |
- HB_637_N |
- N |
- NA |
- 6340_VC_N_0786 |
-
-
- | 100 |
- HB_638_N |
- N |
- NA |
- 6341_VC_N_0785 |
-
-
- | 101 |
- HB_640_N |
- N |
- NA |
- 6347_VC_N_0784 |
-
-
- | 102 |
- HB_641_N |
- N |
- NA |
- 6356_VC_N_0783 |
-
-
- | 103 |
- HB_643_N |
- N |
- NA |
- 6363_VC_N_0781 |
-
-
- | 104 |
- HB_644_N |
- N |
- NA |
- 6366_VC_N_0780 |
-
-
- | 105 |
- HB_645_N |
- N |
- NA |
- 6374_VC_N_0779 |
-
-
- | 106 |
- HB_650_N |
- N |
- NA |
- 6384_VC_N_0777 |
-
-
- | 107 |
- HB_651_N |
- N |
- NA |
- 6386_VC_N_0776 |
-
-
- | 108 |
- HB_653_N |
- N |
- NA |
- 6388_VC_N_0775 |
-
-
- | 109 |
- HB_659_N |
- N |
- NA |
- 6406_VC_N_1180 |
-
-
- | 110 |
- HB_662_N |
- N |
- NA |
- 6411_VC_N_0771 |
-
-
- | 111 |
- HB_663_N |
- N |
- NA |
- 6415_VC_N_0770 |
-
-
- | 112 |
- HB_670_N |
- N |
- NA |
- 6436_VC_N_0769 |
-
-
- | 113 |
- HB_687_N |
- N |
- NA |
- 6484_VC_N_0765 |
-
-
- | 114 |
- HB_689_N |
- N |
- NA |
- 6486_VC_N_0764 |
-
-
- | 115 |
- HB_694_N |
- N |
- NA |
- 6500_VC_N_0763 |
-
-
- | 116 |
- HB_697_N |
- N |
- NA |
- 6512_VC_N_0762 |
-
-
- | 117 |
- HB_700_N |
- N |
- NA |
- 6520_VC_N_0761 |
-
-
- | 118 |
- HB_711_N |
- N |
- NA |
- 6543_PF_N_1191 |
-
-
- | 119 |
- HB_714_N |
- N |
- NA |
- 6549_VC_N_1198 |
-
-
- | 120 |
- HB_717_N |
- N |
- NA |
- 6553_PF_N_2284 |
-
-
- | 121 |
- HB_721_N |
- N |
- NA |
- 6560_VC_N_2578 |
-
-
- | 122 |
- HB_726_N |
- N |
- NA |
- 6573_PF_N_2293 |
-
-
- | 123 |
- HB_730_N |
- N |
- NA |
- 6580_VC_N_2306 |
-
-
- | 124 |
- HB_735_N |
- N |
- NA |
- 6588_VC_N_1213 |
-
-
- | 125 |
- HB_737_N |
- N |
- NA |
- 6593_VC_N_1219 |
-
-
- | 126 |
- HB_738_N |
- N |
- NA |
- 6594_VC_N_1222 |
-
-
- | 127 |
- HB_759_N |
- N |
- NA |
- 6645_VC_N_1231 |
-
-
- | 128 |
- HB_764_N |
- N |
- NA |
- 6655_VC_N_1240 |
-
-
- | 129 |
- HB_765_N |
- N |
- NA |
- 6656_VC_N_1243 |
-
-
- | 130 |
- HB_767_N |
- N |
- NA |
- 6661_PF_N_2341 |
-
-
- | 131 |
- HB_770_N |
- N |
- NA |
- 6669_VC_N_1246 |
-
-
- | 132 |
- HB_772_N |
- N |
- NA |
- 6676_PF_N_1248 |
-
-
- | 133 |
- HB_001_HD |
- HD |
- F |
- 2028_CR_H_2282 |
-
-
- | 134 |
- HB_003_HD |
- HD |
- F |
- 2685_PF_H_2212 |
-
-
- | 135 |
- HB_004_HD |
- HD |
- M |
- 2706_CR_H_2432 |
-
-
- | 136 |
- HB_006_HD |
- HD |
- M |
- 2737_VC_H_2194 |
-
-
- | 137 |
- HB_007_HD |
- HD |
- NA |
- 2769_VC_H_2193 |
-
-
- | 138 |
- HB_008_HD |
- HD |
- F |
- 2790_CR_H_1890 |
-
-
- | 139 |
- HB_009_HD |
- HD |
- NA |
- 2879_VC_H_2192 |
-
-
- | 140 |
- HB_010_HD |
- HD |
- M |
- 2960_VC_H_2002 |
-
-
- | 141 |
- HB_011_HD |
- HD |
- F |
- 3053_VC_H_2001 |
-
-
- | 142 |
- HB_012_HD |
- HD |
- F |
- 3128_VC_H_1999 |
-
-
- | 143 |
- HB_014_HD |
- HD |
- F |
- 3149_PF_H_2110 |
-
-
- | 144 |
- HB_015_HD |
- HD |
- F |
- 3150_VC_H_1996 |
-
-
- | 145 |
- HB_016_HD |
- HD |
- F |
- 3177_VC_H_2191 |
-
-
- | 146 |
- HB_017_HD |
- HD |
- NA |
- 3195_VC_H_2190 |
-
-
- | 147 |
- HB_018_HD |
- HD |
- M |
- 3200_VC_H_2189 |
-
-
- | 148 |
- HB_019_HD |
- HD |
- M |
- 3209_VC_H_2188 |
-
-
- | 149 |
- HB_020_HD |
- HD |
- M |
- 3224_VC_H_1994 |
-
-
- | 150 |
- HB_022_HD |
- HD |
- F |
- 3242_PF_H_2105 |
-
-
- | 151 |
- HB_024_HD |
- HD |
- NA |
- 3272_VC_H_2186 |
-
-
- | 152 |
- HB_027_HD |
- HD |
- M |
- 3356_VC_H_2439 |
-
-
- | 153 |
- HB_028_HD |
- HD |
- F |
- 3394_PF_H_2104 |
-
-
- | 154 |
- HB_031_HD |
- HD |
- M |
- 3430_VC_H_1990 |
-
-
- | 155 |
- HB_032_HD |
- HD |
- NA |
- 3444_PF_H_2208 |
-
-
- | 156 |
- HB_034_HD |
- HD |
- F |
- 3482_VC_H_1987 |
-
-
- | 157 |
- HB_036_HD |
- HD |
- M |
- 3576_VC_H_1984 |
-
-
- | 158 |
- HB_037_HD |
- HD |
- F |
- 3579_VC_H_1983 |
-
-
- | 159 |
- HB_038_HD |
- HD |
- F |
- 3584_VC_H_2183 |
-
-
- | 160 |
- HB_039_HD |
- HD |
- NA |
- 3635_VC_H_2182 |
-
-
- | 161 |
- HB_041_HD |
- HD |
- F |
- 3695_CR_H_2267 |
-
-
- | 162 |
- HB_042_HD |
- HD |
- M |
- 3697_VC_H_1982 |
-
-
- | 163 |
- HB_043_HD |
- HD |
- NA |
- 3703_VC_H_2180 |
-
-
- | 164 |
- HB_044_HD |
- HD |
- NA |
- 3723_VC_H_2179 |
-
-
- | 165 |
- HB_046_HD |
- HD |
- F |
- 3735_VC_H_1981 |
-
-
- | 166 |
- HB_050_HD |
- HD |
- M |
- 3820_PF_H_2207 |
-
-
- | 167 |
- HB_051_HD |
- HD |
- F |
- 3849_CR_H_2262 |
-
-
- | 168 |
- HB_054_HD |
- HD |
- M |
- 3884_VC_H_2175 |
-
-
- | 169 |
- HB_056_HD |
- HD |
- NA |
- 4012_VC_H_2174 |
-
-
- | 170 |
- HB_057_HD |
- HD |
- NA |
- 4013_VC_H_2173 |
-
-
- | 171 |
- HB_059_HD |
- HD |
- NA |
- 4066_VC_H_2172 |
-
-
- | 172 |
- HB_060_HD |
- HD |
- NA |
- 4094_VC_H_2171 |
-
-
- | 173 |
- HB_061_HD |
- HD |
- F |
- 4116_VC_H_2170 |
-
-
- | 174 |
- HB_062_HD |
- HD |
- NA |
- 4121_VC_H_2169 |
-
-
- | 175 |
- HB_063_HD |
- HD |
- NA |
- 4215_VC_H_2167 |
-
-
- | 176 |
- HB_065_HD |
- HD |
- M |
- 4340_PF_H_2091 |
-
-
- | 177 |
- HB_066_HD |
- HD |
- F |
- 4344_VC_H_1977 |
-
-
- | 178 |
- HB_067_HD |
- HD |
- M |
- 4346_VC_H_2165 |
-
-
- | 179 |
- HB_069_HD |
- HD |
- F |
- 4356_VC_H_2164 |
-
-
- | 180 |
- HB_070_HD |
- HD |
- NA |
- 4386_CR_H_2249 |
-
-
- | 181 |
- HB_072_HD |
- HD |
- NA |
- 4404_VC_H_2161 |
-
-
- | 182 |
- HB_073_HD |
- HD |
- F |
- 4411_VC_H_1975 |
-
-
- | 183 |
- HB_074_HD |
- HD |
- NA |
- 4430_VC_H_2465 |
-
-
- | 184 |
- HB_075_HD |
- HD |
- M |
- 4470_VC_H_1974 |
-
-
- | 185 |
- HB_076_HD |
- HD |
- F |
- 4497_CR_H_1860 |
-
-
- | 186 |
- HB_077_HD |
- HD |
- M |
- 4509_CR_H_2244 |
-
-
- | 187 |
- HB_079_HD |
- HD |
- M |
- 4631_VC_H_1971 |
-
-
- | 188 |
- HB_080_HD |
- HD |
- F |
- 4653_PF_H_2083 |
-
-
- | 189 |
- HB_081_HD |
- HD |
- NA |
- 4678_CR_H_2242 |
-
-
- | 190 |
- HB_084_HD |
- HD |
- M |
- 4718_VC_H_2125 |
-
-
- | 191 |
- HB_090_HD |
- HD |
- NA |
- 4740_CR_H_2474 |
-
-
- | 192 |
- HB_094_HD |
- HD |
- NA |
- 4754_CR_H_2476 |
-
-
- | 193 |
- HB_098_HD |
- HD |
- NA |
- 4780_VC_H_2151 |
-
-
- | 194 |
- HB_101_HD |
- HD |
- F |
- 4809_VC_H_2148 |
-
-
- | 195 |
- HB_105_HD |
- HD |
- NA |
- 4819_CR_H_2238 |
-
-
- | 196 |
- HB_106_HD |
- HD |
- F |
- 4822_VC_H_1969 |
-
-
- | 197 |
- HB_108_HD |
- HD |
- M |
- 4826_VC_H_1968 |
-
-
- | 198 |
- HB_109_HD |
- HD |
- M |
- 4828_VC_H_2124 |
-
-
- | 199 |
- HB_115_HD |
- HD |
- NA |
- 4855_CR_H_2235 |
-
-
- | 200 |
- HB_121_HD |
- HD |
- F |
- 4902_VC_H_1967 |
-
-
- | 201 |
- HB_129_HD |
- HD |
- NA |
- 4938_VC_H_1966 |
-
-
- | 202 |
- HB_141_HD |
- HD |
- F |
- 4996_PF_H_2076 |
-
-
- | 203 |
- HB_152_HD |
- HD |
- NA |
- 5034_CR_H_2233 |
-
-
- | 204 |
- HB_153_HD |
- HD |
- M |
- 5043_VC_H_1960 |
-
-
- | 205 |
- HB_159_HD |
- HD |
- M |
- 5062_VC_H_1959 |
-
-
- | 206 |
- HB_172_HD |
- HD |
- F |
- 5114_PF_H_2070 |
-
-
- | 207 |
- HB_175_HD |
- HD |
- M |
- 5127_PF_H_2068 |
-
-
- | 208 |
- HB_180_HD |
- HD |
- M |
- 5148_VC_H_1944 |
-
-
- | 209 |
- HB_185_HD |
- HD |
- F |
- 5167_CR_H_2231 |
-
-
- | 210 |
- HB_188_HD |
- HD |
- F |
- 5172_VC_H_1951 |
-
-
- | 211 |
- HB_191_HD |
- HD |
- M |
- 5180_VC_H_1949 |
-
-
- | 212 |
- HB_196_HD |
- HD |
- NA |
- 5199_PF_H_2202 |
-
-
- | 213 |
- HB_203_HD |
- HD |
- F |
- 5228_PF_H_2059 |
-
-
- | 214 |
- HB_207_HD |
- HD |
- NA |
- 5248_PF_H_2201 |
-
-
- | 215 |
- HB_228_HD |
- HD |
- F |
- 5299_CR_H_2228 |
-
-
- | 216 |
- HB_233_HD |
- HD |
- M |
- 5312_VC_H_1938 |
-
-
- | 217 |
- HB_235_HD |
- HD |
- F |
- 5316_VC_H_1937 |
-
-
- | 218 |
- HB_242_HD |
- HD |
- F |
- 5328_PF_H_2048 |
-
-
- | 219 |
- HB_266_HD |
- HD |
- M |
- 5387_VC_H_1928 |
-
-
- | 220 |
- HB_271_HD |
- HD |
- M |
- 5394_PF_H_2039 |
-
-
- | 221 |
- HB_272_HD |
- HD |
- F |
- 5396_VC_H_1925 |
-
-
- | 222 |
- HB_279_HD |
- HD |
- F |
- 5409_VC_H_1924 |
-
-
- | 223 |
- HB_294_HD |
- HD |
- M |
- 5448_VC_H_1921 |
-
-
- | 224 |
- HB_301_HD |
- HD |
- NA |
- 5464_VC_H_1919 |
-
-
- | 225 |
- HB_304_HD |
- HD |
- F |
- 5471_VC_H_1918 |
-
-
- | 226 |
- HB_321_HD |
- HD |
- NA |
- 5522_PF_H_2199 |
-
-
- | 227 |
- HB_361_HD |
- HD |
- F |
- 5622_VC_H_2121 |
-
-
- | 228 |
- HB_370_HD |
- HD |
- M |
- 5645_VC_H_1904 |
-
-
- | 229 |
- HB_371_HD |
- HD |
- F |
- 5648_PF_H_2016 |
-
-
- | 230 |
- HB_384_HD |
- HD |
- F |
- 5688_PF_H_2012 |
-
-
- | 231 |
- HB_390_HD |
- HD |
- M |
- 5704_PF_H_2009 |
-
-
- | 232 |
- HB_393_HD |
- HD |
- F |
- 5709_VC_H_1895 |
-
-
- | 233 |
- HB_402_HD |
- HD |
- F |
- 5732_PF_H_2007 |
-
-
- | 234 |
- HB_405_HD |
- HD |
- NA |
- 5742_PF_H_2006 |
-
-
- | 235 |
- HB_407_HD |
- HD |
- M |
- 5745_PF_H_2005 |
-
-
- | 236 |
- HB_408_HD |
- HD |
- M |
- 5747_VC_H_1891 |
-
-
- | 237 |
- HB_415_HD |
- HD |
- NA |
- 5777_PF_H_1551 |
-
-
- | 238 |
- HB_417_HD |
- HD |
- M |
- 5784_PF_H_1554 |
-
-
- | 239 |
- HB_424_HD |
- HD |
- M |
- 5804_VC_H_1558 |
-
-
- | 240 |
- HB_444_HD |
- HD |
- M |
- 5856_VC_H_1567 |
-
-
- | 241 |
- HB_457_HD |
- HD |
- M |
- 5896_VC_H_1570 |
-
-
- | 242 |
- HB_466_HD |
- HD |
- M |
- 5910_PF_H_1572 |
-
-
- | 243 |
- HB_478_HD |
- HD |
- M |
- 5941_CR_H_1583 |
-
-
- | 244 |
- HB_487_HD |
- HD |
- F |
- 5964_VC_H_1597 |
-
-
- | 245 |
- HB_511_HD |
- HD |
- M |
- 6019_PF_H_2198 |
-
-
- | 246 |
- HB_513_HD |
- HD |
- F |
- 6024_VC_H_1612 |
-
-
- | 247 |
- HB_515_HD |
- HD |
- F |
- 6028_CR_H_1613 |
-
-
- | 248 |
- HB_518_HD |
- HD |
- M |
- 6033_VC_H_1618 |
-
-
- | 249 |
- HB_522_HD |
- HD |
- M |
- 6037_PF_H_1626 |
-
-
- | 250 |
- HB_527_HD |
- HD |
- F |
- 6047_VC_H_1639 |
-
-
- | 251 |
- HB_528_HD |
- HD |
- M |
- 6051_PF_H_1641 |
-
-
- | 252 |
- HB_530_HD |
- HD |
- M |
- 6054_VC_H_1648 |
-
-
- | 253 |
- HB_537_HD |
- HD |
- F |
- 6071_PF_H_1653 |
-
-
- | 254 |
- HB_549_HD |
- HD |
- M |
- 6119_CR_H_1670 |
-
-
- | 255 |
- HB_593_HD |
- HD |
- NA |
- 6219_CR_H_2567 |
-
-
- | 256 |
- HB_610_HD |
- HD |
- NA |
- 6275_PF_H_1692 |
-
-
- | 257 |
- HB_616_HD |
- HD |
- F |
- 6284_CR_H_1694 |
-
-
- | 258 |
- HB_626_HD |
- HD |
- M |
- 6315_VC_H_1702 |
-
-
- | 259 |
- HB_639_HD |
- HD |
- F |
- 6344_CR_H_1703 |
-
-
- | 260 |
- HB_649_HD |
- HD |
- F |
- 6382_CR_H_1709 |
-
-
- | 261 |
- HB_661_HD |
- HD |
- M |
- 6408_VC_H_1714 |
-
-
- | 262 |
- HB_682_HD |
- HD |
- M |
- 6467_PF_H_1725 |
-
-
- | 263 |
- HB_683_HD |
- HD |
- M |
- 6472_VC_H_1729 |
-
-
- | 264 |
- HB_691_HD |
- HD |
- F |
- 6493_VC_H_1732 |
-
-
- | 265 |
- HB_692_HD |
- HD |
- M |
- 6495_CR_H_1733 |
-
-
- | 266 |
- HB_707_HD |
- HD |
- M |
- 6535_PF_H_1737 |
-
-
- | 267 |
- HB_709_HD |
- HD |
- F |
- 6539_CR_H_1739 |
-
-
- | 268 |
- HB_725_HD |
- HD |
- M |
- 6572_PF_H_1746 |
-
-
- | 269 |
- HB_732_HD |
- HD |
- F |
- 6584_VC_H_1750 |
-
-
- | 270 |
- HB_734_HD |
- HD |
- F |
- 6587_CR_H_1751 |
-
-
- | 271 |
- HB_748_HD |
- HD |
- NA |
- 6615_VC_H_2315 |
-
-
- | 272 |
- HB_750_HD |
- HD |
- NA |
- 6628_PF_H_2326 |
-
-
- | 273 |
- HB_758_HD |
- HD |
- NA |
- 6643_VC_H_2602 |
-
-
- | 274 |
- HB_760_HD |
- HD |
- M |
- 6646_PF_H_1761 |
-
-
- | 275 |
- HB_762_HD |
- HD |
- M |
- 6650_VC_H_1765 |
-
-
- | 276 |
- HB_766_HD |
- HD |
- M |
- 6658_VC_H_1768 |
-
-
- | 277 |
- HB_768_HD |
- HD |
- NA |
- 6663_VC_H_1771 |
-
-
- | 278 |
- HB_769_HD |
- HD |
- M |
- 6666_VC_H_1774 |
-
-
- | 279 |
- HB_774_HD |
- HD |
- NA |
- 6689_PF_H_2344 |
-
-
- | 280 |
- HB_778_HD |
- HD |
- NA |
- 6696_PF_H_2356 |
-
-
- | 281 |
- HB_780_HD |
- HD |
- NA |
- 6704_PF_H_2362 |
-
-
- | 282 |
- HB_790_HD |
- HD |
- NA |
- 6788_PF_H_2389 |
-
-
- | 283 |
- HB_800_HD |
- HD |
- NA |
- 6807_PF_H_2419 |
-
-
- | 284 |
- HB_802_HD |
- HD |
- NA |
- 6811_PF_H_2425 |
-
-
- | 285 |
- HB_045_AD |
- AD |
- NA |
- 3734_CR_A_0122 |
-
-
- | 286 |
- HB_048_AD |
- AD |
- NA |
- 3791_CR_A_0128 |
-
-
- | 287 |
- HB_053_AD |
- AD |
- NA |
- 3877_CR_A_0134 |
-
-
- | 288 |
- HB_055_AD |
- AD |
- NA |
- 3893_VC_A_0142 |
-
-
- | 289 |
- HB_068_AD |
- AD |
- NA |
- 4349_VC_A_0148 |
-
-
- | 290 |
- HB_082_AD |
- AD |
- NA |
- 4712_CR_A_0309 |
-
-
- | 291 |
- HB_085_AD |
- AD |
- NA |
- 4726_VC_A_0311 |
-
-
- | 292 |
- HB_087_AD |
- AD |
- NA |
- 4730_CR_A_0315 |
-
-
- | 293 |
- HB_089_AD |
- AD |
- NA |
- 4733_VC_A_0320 |
-
-
- | 294 |
- HB_093_AD |
- AD |
- NA |
- 4749_VC_A_0323 |
-
-
- | 295 |
- HB_095_AD |
- AD |
- NA |
- 4759_CR_A_0327 |
-
-
- | 296 |
- HB_097_AD |
- AD |
- NA |
- 4773_CR_A_0866 |
-
-
- | 297 |
- HB_099_AD |
- AD |
- NA |
- 4785_VC_A_0332 |
-
-
- | 298 |
- HB_100_AD |
- AD |
- NA |
- 4795_VC_A_0335 |
-
-
- | 299 |
- HB_103_AD |
- AD |
- NA |
- 4811_VC_A_0341 |
-
-
- | 300 |
- HB_104_AD |
- AD |
- NA |
- 4813_CR_A_0345 |
-
-
- | 301 |
- HB_112_AD |
- AD |
- NA |
- 4842_VC_A_0870 |
-
-
- | 302 |
- HB_113_AD |
- AD |
- NA |
- 4850_CR_A_0351 |
-
-
- | 303 |
- HB_114_AD |
- AD |
- NA |
- 4852_CR_A_0354 |
-
-
- | 304 |
- HB_117_AD |
- AD |
- NA |
- 4868_VC_A_0874 |
-
-
- | 305 |
- HB_122_AD |
- AD |
- NA |
- 4904_CR_A_1132 |
-
-
- | 306 |
- HB_123_AD |
- AD |
- NA |
- 4905_VC_A_0884 |
-
-
- | 307 |
- HB_124_AD |
- AD |
- NA |
- 4916_VC_A_0886 |
-
-
- | 308 |
- HB_125_AD |
- AD |
- NA |
- 4917_CR_A_0360 |
-
-
- | 309 |
- HB_126_AD |
- AD |
- NA |
- 4921_VC_A_0362 |
-
-
- | 310 |
- HB_128_AD |
- AD |
- NA |
- 4936_CR_A_0369 |
-
-
- | 311 |
- HB_130_AD |
- AD |
- NA |
- 4939_VC_A_0888 |
-
-
- | 312 |
- HB_131_AD |
- AD |
- NA |
- 4944_CR_A_0889 |
-
-
- | 313 |
- HB_132_AD |
- AD |
- NA |
- 4946_CR_A_0372 |
-
-
- | 314 |
- HB_134_AD |
- AD |
- NA |
- 4951_CR_A_0891 |
-
-
- | 315 |
- HB_135_AD |
- AD |
- NA |
- 4953_VC_A_0893 |
-
-
- | 316 |
- HB_136_AD |
- AD |
- NA |
- 4965_VC_A_0160 |
-
-
- | 317 |
- HB_137_AD |
- AD |
- NA |
- 4966_VC_A_0374 |
-
-
- | 318 |
- HB_138_AD |
- AD |
- NA |
- 4969_VC_A_0895 |
-
-
- | 319 |
- HB_140_AD |
- AD |
- NA |
- 4993_CR_A_0896 |
-
-
- | 320 |
- HB_146_AD |
- AD |
- NA |
- 5018_CR_A_0384 |
-
-
- | 321 |
- HB_148_AD |
- AD |
- NA |
- 5022_VC_A_0386 |
-
-
- | 322 |
- HB_150_AD |
- AD |
- NA |
- 5031_VC_A_0392 |
-
-
- | 323 |
- HB_151_AD |
- AD |
- NA |
- 5033_CR_A_0396 |
-
-
- | 324 |
- HB_154_AD |
- AD |
- NA |
- 5048_VC_A_1321 |
-
-
- | 325 |
- HB_155_AD |
- AD |
- NA |
- 5056_VC_A_0398 |
-
-
- | 326 |
- HB_156_AD |
- AD |
- NA |
- 5057_VC_A_0163 |
-
-
- | 327 |
- HB_157_AD |
- AD |
- NA |
- 5059_VC_A_0401 |
-
-
- | 328 |
- HB_158_AD |
- AD |
- NA |
- 5061_PF_A_2612 |
-
-
- | 329 |
- HB_160_AD |
- AD |
- NA |
- 5064_PF_A_2615 |
-
-
- | 330 |
- HB_165_AD |
- AD |
- NA |
- 5092_CR_A_0899 |
-
-
- | 331 |
- HB_168_AD |
- AD |
- NA |
- 5097_VC_A_0407 |
-
-
- | 332 |
- HB_170_AD |
- AD |
- NA |
- 5101_VC_A_0410 |
-
-
- | 333 |
- HB_174_AD |
- AD |
- NA |
- 5124_PF_A_1343 |
-
-
- | 334 |
- HB_179_AD |
- AD |
- NA |
- 5145_VC_A_1351 |
-
-
- | 335 |
- HB_181_AD |
- AD |
- NA |
- 5152_CR_A_0414 |
-
-
- | 336 |
- HB_184_AD |
- AD |
- NA |
- 5166_VC_A_1354 |
-
-
- | 337 |
- HB_194_AD |
- AD |
- NA |
- 5193_VC_A_1360 |
-
-
- | 338 |
- HB_197_AD |
- AD |
- NA |
- 5202_CR_A_1368 |
-
-
- | 339 |
- HB_199_AD |
- AD |
- NA |
- 5205_VC_A_0166 |
-
-
- | 340 |
- HB_200_AD |
- AD |
- NA |
- 5210_VC_A_0905 |
-
-
- | 341 |
- HB_205_AD |
- AD |
- NA |
- 5235_VC_A_0419 |
-
-
- | 342 |
- HB_208_AD |
- AD |
- NA |
- 5249_VC_A_0422 |
-
-
- | 343 |
- HB_209_AD |
- AD |
- NA |
- 5252_VC_A_0907 |
-
-
- | 344 |
- HB_211_AD |
- AD |
- NA |
- 5257_VC_A_0169 |
-
-
- | 345 |
- HB_216_AD |
- AD |
- NA |
- 5272_VC_A_0425 |
-
-
- | 346 |
- HB_219_AD |
- AD |
- NA |
- 5279_CR_A_0147 |
-
-
- | 347 |
- HB_221_AD |
- AD |
- NA |
- 5283_VC_A_0145 |
-
-
- | 348 |
- HB_222_AD |
- AD |
- NA |
- 5285_VC_A_0141 |
-
-
- | 349 |
- HB_224_AD |
- AD |
- NA |
- 5288_VC_A_0428 |
-
-
- | 350 |
- HB_230_AD |
- AD |
- NA |
- 5301_VC_A_0174 |
-
-
- | 351 |
- HB_231_AD |
- AD |
- NA |
- 5305_VC_A_1384 |
-
-
- | 352 |
- HB_232_AD |
- AD |
- NA |
- 5310_CR_A_0176 |
-
-
- | 353 |
- HB_234_AD |
- AD |
- NA |
- 5313_PF_A_2618 |
-
-
- | 354 |
- HB_236_AD |
- AD |
- NA |
- 5317_PF_A_2624 |
-
-
- | 355 |
- HB_238_AD |
- AD |
- NA |
- 5322_CR_A_2632 |
-
-
- | 356 |
- HB_240_AD |
- AD |
- NA |
- 5325_VC_A_0137 |
-
-
- | 357 |
- HB_244_AD |
- AD |
- NA |
- 5337_VC_A_1387 |
-
-
- | 358 |
- HB_245_AD |
- AD |
- NA |
- 5339_VC_A_0181 |
-
-
- | 359 |
- HB_250_AD |
- AD |
- NA |
- 5346_VC_A_1393 |
-
-
- | 360 |
- HB_251_AD |
- AD |
- NA |
- 5350_VC_A_0184 |
-
-
- | 361 |
- HB_252_AD |
- AD |
- NA |
- 5355_VC_A_0133 |
-
-
- | 362 |
- HB_253_AD |
- AD |
- NA |
- 5359_CR_A_1395 |
-
-
- | 363 |
- HB_258_AD |
- AD |
- NA |
- 5370_PF_A_1400 |
-
-
- | 364 |
- HB_259_AD |
- AD |
- NA |
- 5371_PF_A_2636 |
-
-
- | 365 |
- HB_260_AD |
- AD |
- NA |
- 5375_VC_A_0188 |
-
-
- | 366 |
- HB_263_AD |
- AD |
- NA |
- 5381_VC_A_0022 |
-
-
- | 367 |
- HB_265_AD |
- AD |
- NA |
- 5385_VC_A_1402 |
-
-
- | 368 |
- HB_267_AD |
- AD |
- NA |
- 5389_VC_A_0928 |
-
-
- | 369 |
- HB_268_AD |
- AD |
- NA |
- 5390_CR_A_0151 |
-
-
- | 370 |
- HB_273_AD |
- AD |
- NA |
- 5400_PF_A_2645 |
-
-
- | 371 |
- HB_274_AD |
- AD |
- NA |
- 5401_VC_A_0931 |
-
-
- | 372 |
- HB_275_AD |
- AD |
- NA |
- 5404_PF_A_2648 |
-
-
- | 373 |
- HB_276_AD |
- AD |
- NA |
- 5406_VC_A_0933 |
-
-
- | 374 |
- HB_277_AD |
- AD |
- NA |
- 5407_PF_A_2651 |
-
-
- | 375 |
- HB_280_AD |
- AD |
- NA |
- 5412_VC_A_0935 |
-
-
- | 376 |
- HB_281_AD |
- AD |
- NA |
- 5413_PF_A_2657 |
-
-
- | 377 |
- HB_283_AD |
- AD |
- NA |
- 5419_VC_A_0937 |
-
-
- | 378 |
- HB_284_AD |
- AD |
- NA |
- 5420_VC_A_0939 |
-
-
- | 379 |
- HB_285_AD |
- AD |
- NA |
- 5421_CR_A_0432 |
-
-
- | 380 |
- HB_286_AD |
- AD |
- NA |
- 5423_PF_A_2660 |
-
-
- | 381 |
- HB_288_AD |
- AD |
- NA |
- 5425_PF_A_2666 |
-
-
- | 382 |
- HB_289_AD |
- AD |
- NA |
- 5426_VC_A_1405 |
-
-
- | 383 |
- HB_290_AD |
- AD |
- NA |
- 5433_VC_A_0434 |
-
-
- | 384 |
- HB_296_AD |
- AD |
- NA |
- 5456_PF_A_2675 |
-
-
- | 385 |
- HB_299_AD |
- AD |
- NA |
- 5461_VC_A_0192 |
-
-
- | 386 |
- HB_302_AD |
- AD |
- NA |
- 5465_PF_A_2678 |
-
-
- | 387 |
- HB_303_AD |
- AD |
- NA |
- 5469_VC_A_1417 |
-
-
- | 388 |
- HB_305_AD |
- AD |
- NA |
- 5479_PF_A_1421 |
-
-
- | 389 |
- HB_306_AD |
- AD |
- NA |
- 5480_VC_A_0437 |
-
-
- | 390 |
- HB_307_AD |
- AD |
- NA |
- 5482_VC_A_0028 |
-
-
- | 391 |
- HB_308_AD |
- AD |
- NA |
- 5483_VC_A_0941 |
-
-
- | 392 |
- HB_309_AD |
- AD |
- NA |
- 5487_CR_A_0441 |
-
-
- | 393 |
- HB_310_AD |
- AD |
- NA |
- 5488_CR_A_0194 |
-
-
- | 394 |
- HB_312_AD |
- AD |
- NA |
- 5500_VC_A_0198 |
-
-
- | 395 |
- HB_313_AD |
- AD |
- NA |
- 5502_PF_A_2684 |
-
-
- | 396 |
- HB_315_AD |
- AD |
- NA |
- 5513_PF_A_2687 |
-
-
- | 397 |
- HB_316_AD |
- AD |
- NA |
- 5516_PF_A_2690 |
-
-
- | 398 |
- HB_317_AD |
- AD |
- NA |
- 5517_PF_A_2693 |
-
-
- | 399 |
- HB_318_AD |
- AD |
- NA |
- 5518_CR_A_0030 |
-
-
- | 400 |
- HB_319_AD |
- AD |
- NA |
- 5519_CR_A_2695 |
-
-
- | 401 |
- HB_320_AD |
- AD |
- NA |
- 5520_PF_A_2699 |
-
-
- | 402 |
- HB_322_AD |
- AD |
- NA |
- 5527_VC_A_0945 |
-
-
- | 403 |
- HB_325_AD |
- AD |
- NA |
- 5532_PF_A_2702 |
-
-
- | 404 |
- HB_328_AD |
- AD |
- NA |
- 5541_PF_A_2705 |
-
-
- | 405 |
- HB_330_AD |
- AD |
- NA |
- 5544_VC_A_0201 |
-
-
- | 406 |
- HB_334_AD |
- AD |
- NA |
- 5554_VC_A_0452 |
-
-
- | 407 |
- HB_335_AD |
- AD |
- NA |
- 5557_VC_A_0950 |
-
-
- | 408 |
- HB_337_AD |
- AD |
- NA |
- 5560_VC_A_0204 |
-
-
- | 409 |
- HB_342_AD |
- AD |
- NA |
- 5571_PF_A_1430 |
-
-
- | 410 |
- HB_345_AD |
- AD |
- NA |
- 5583_PF_A_2708 |
-
-
- | 411 |
- HB_347_AD |
- AD |
- NA |
- 5589_PF_A_2714 |
-
-
- | 412 |
- HB_349_AD |
- AD |
- NA |
- 5592_PF_A_2717 |
-
-
- | 413 |
- HB_352_AD |
- AD |
- NA |
- 5604_VC_A_0037 |
-
-
- | 414 |
- HB_353_AD |
- AD |
- NA |
- 5607_PF_A_2723 |
-
-
- | 415 |
- HB_356_AD |
- AD |
- NA |
- 5615_VC_A_0041 |
-
-
- | 416 |
- HB_357_AD |
- AD |
- NA |
- 5616_CR_A_0127 |
-
-
- | 417 |
- HB_358_AD |
- AD |
- NA |
- 5617_CR_A_0456 |
-
-
- | 418 |
- HB_359_AD |
- AD |
- NA |
- 5618_CR_A_0044 |
-
-
- | 419 |
- HB_362_AD |
- AD |
- NA |
- 5625_CR_A_2495 |
-
-
- | 420 |
- HB_363_AD |
- AD |
- NA |
- 5626_CR_A_2498 |
-
-
- | 421 |
- HB_364_AD |
- AD |
- NA |
- 5629_CR_A_0390 |
-
-
- | 422 |
- HB_369_AD |
- AD |
- NA |
- 5643_VC_A_1143 |
-
-
- | 423 |
- HB_373_AD |
- AD |
- NA |
- 5654_VC_A_0047 |
-
-
- | 424 |
- HB_375_AD |
- AD |
- NA |
- 5660_CR_A_0462 |
-
-
- | 425 |
- HB_376_AD |
- AD |
- NA |
- 5661_VC_A_0464 |
-
-
- | 426 |
- HB_377_AD |
- AD |
- NA |
- 5667_VC_A_2509 |
-
-
- | 427 |
- HB_378_AD |
- AD |
- NA |
- 5668_VC_A_1438 |
-
-
- | 428 |
- HB_383_AD |
- AD |
- NA |
- 5686_CR_A_2728 |
-
-
- | 429 |
- HB_386_AD |
- AD |
- NA |
- 5695_VC_A_0953 |
-
-
- | 430 |
- HB_389_AD |
- AD |
- NA |
- 5700_VC_A_2514 |
-
-
- | 431 |
- HB_391_AD |
- AD |
- NA |
- 5705_CR_A_0474 |
-
-
- | 432 |
- HB_392_AD |
- AD |
- NA |
- 5706_VC_A_0476 |
-
-
- | 433 |
- HB_394_AD |
- AD |
- NA |
- 5713_VC_A_0479 |
-
-
- | 434 |
- HB_397_AD |
- AD |
- NA |
- 5721_CR_A_0210 |
-
-
- | 435 |
- HB_404_AD |
- AD |
- NA |
- 5735_CR_A_0489 |
-
-
- | 436 |
- HB_406_AD |
- AD |
- NA |
- 5744_CR_A_0960 |
-
-
- | 437 |
- HB_409_AD |
- AD |
- NA |
- 5749_CR_A_0159 |
-
-
- | 438 |
- HB_410_AD |
- AD |
- NA |
- 5751_CR_A_2518 |
-
-
- | 439 |
- HB_411_AD |
- AD |
- NA |
- 5755_CR_A_2731 |
-
-
- | 440 |
- HB_413_AD |
- AD |
- NA |
- 5766_VC_A_0214 |
-
-
- | 441 |
- HB_419_AD |
- AD |
- NA |
- 5790_VC_A_0217 |
-
-
- | 442 |
- HB_420_AD |
- AD |
- NA |
- 5796_CR_A_0964 |
-
-
- | 443 |
- HB_428_AD |
- AD |
- NA |
- 5811_CR_A_2524 |
-
-
- | 444 |
- HB_429_AD |
- AD |
- NA |
- 5819_CR_A_2527 |
-
-
- | 445 |
- HB_430_AD |
- AD |
- NA |
- 5822_CR_A_2530 |
-
-
- | 446 |
- HB_434_AD |
- AD |
- NA |
- 5828_CR_A_2533 |
-
-
- | 447 |
- HB_435_AD |
- AD |
- NA |
- 5831_CR_A_0222 |
-
-
- | 448 |
- HB_437_AD |
- AD |
- NA |
- 5839_CR_A_2539 |
-
-
- | 449 |
- HB_438_AD |
- AD |
- NA |
- 5843_CR_A_0227 |
-
-
- | 450 |
- HB_439_AD |
- AD |
- NA |
- 5845_CR_A_0230 |
-
-
- | 451 |
- HB_441_AD |
- AD |
- NA |
- 5849_CR_A_0233 |
-
-
- | 452 |
- HB_442_AD |
- AD |
- NA |
- 5850_CR_A_0495 |
-
-
- | 453 |
- HB_445_AD |
- AD |
- NA |
- 5858_CR_A_0969 |
-
-
- | 454 |
- HB_448_AD |
- AD |
- NA |
- 5864_CR_A_0974 |
-
-
- | 455 |
- HB_451_AD |
- AD |
- NA |
- 5871_CR_A_2542 |
-
-
- | 456 |
- HB_454_AD |
- AD |
- NA |
- 5879_CR_A_2545 |
-
-
- | 457 |
- HB_455_AD |
- AD |
- NA |
- 5887_CR_A_0976_Bis |
-
-
- | 458 |
- HB_459_AD |
- AD |
- NA |
- 5898_CR_A_2548 |
-
-
- | 459 |
- HB_460_AD |
- AD |
- NA |
- 5900_VC_A_0237 |
-
-
- | 460 |
- HB_461_AD |
- AD |
- NA |
- 5901_CR_A_0239 |
-
-
- | 461 |
- HB_469_AD |
- AD |
- NA |
- 5914_CR_A_2554 |
-
-
- | 462 |
- HB_471_AD |
- AD |
- NA |
- 5922_VC_A_0246 |
-
-
- | 463 |
- HB_473_AD |
- AD |
- NA |
- 5927_CR_A_2560 |
-
-
- | 464 |
- HB_474_AD |
- AD |
- NA |
- 5933_VC_A_1071 |
-
-
- | 465 |
- HB_477_AD |
- AD |
- NA |
- 5939_CR_A_1151 |
-
-
- | 466 |
- HB_479_AD |
- AD |
- NA |
- 5945_VC_A_0983 |
-
-
- | 467 |
- HB_484_AD |
- AD |
- NA |
- 5956_CR_A_0123 |
-
-
- | 468 |
- HB_489_AD |
- AD |
- NA |
- 5968_VC_A_1075 |
-
-
- | 469 |
- HB_491_AD |
- AD |
- NA |
- 5971_CR_A_0119 |
-
-
- | 470 |
- HB_492_AD |
- AD |
- NA |
- 5972_VC_A_0251 |
-
-
- | 471 |
- HB_494_AD |
- AD |
- NA |
- 5979_CR_A_0115 |
-
-
- | 472 |
- HB_498_AD |
- AD |
- NA |
- 5988_VC_A_0503 |
-
-
- | 473 |
- HB_502_AD |
- AD |
- NA |
- 5994_PF_A_1605 |
-
-
- | 474 |
- HB_503_AD |
- AD |
- NA |
- 5995_CR_A_2563 |
-
-
- | 475 |
- HB_510_AD |
- AD |
- NA |
- 6017_CR_A_0048 |
-
-
- | 476 |
- HB_514_AD |
- AD |
- NA |
- 6025_VC_A_0506 |
-
-
- | 477 |
- HB_517_AD |
- AD |
- NA |
- 6031_VC_A_0258 |
-
-
- | 478 |
- HB_520_AD |
- AD |
- NA |
- 6035_VC_A_1621 |
-
-
- | 479 |
- HB_523_AD |
- AD |
- NA |
- 6038_VC_A_0261 |
-
-
- | 480 |
- HB_524_AD |
- AD |
- NA |
- 6042_VC_A_1156 |
-
-
- | 481 |
- HB_525_AD |
- AD |
- NA |
- 6044_VC_A_0264 |
-
-
- | 482 |
- HB_531_AD |
- AD |
- NA |
- 6056_CR_A_0999 |
-
-
- | 483 |
- HB_533_AD |
- AD |
- NA |
- 6061_PF_A_1650 |
-
-
- | 484 |
- HB_534_AD |
- AD |
- NA |
- 6066_VC_A_0270 |
-
-
- | 485 |
- HB_535_AD |
- AD |
- NA |
- 6067_PF_A_1452 |
-
-
- | 486 |
- HB_536_AD |
- AD |
- NA |
- 6068_VC_A_0273 |
-
-
- | 487 |
- HB_545_AD |
- AD |
- NA |
- 6102_CR_A_1661 |
-
-
- | 488 |
- HB_546_AD |
- AD |
- NA |
- 6107_CR_A_0055 |
-
-
- | 489 |
- HB_550_AD |
- AD |
- NA |
- 6120_VC_A_0058 |
-
-
- | 490 |
- HB_552_AD |
- AD |
- NA |
- 6126_VC_A_1675 |
-
-
- | 491 |
- HB_553_AD |
- AD |
- NA |
- 6129_PF_A_0274 |
-
-
- | 492 |
- HB_554_AD |
- AD |
- NA |
- 6130_VC_A_1678 |
-
-
- | 493 |
- HB_555_AD |
- AD |
- NA |
- 6131_CR_A_0510 |
-
-
- | 494 |
- HB_556_AD |
- AD |
- NA |
- 6132_CR_A_0513 |
-
-
- | 495 |
- HB_558_AD |
- AD |
- NA |
- 6137_VC_A_1681 |
-
-
- | 496 |
- HB_564_AD |
- AD |
- NA |
- 6153_VC_A_1465 |
-
-
- | 497 |
- HB_565_AD |
- AD |
- NA |
- 6154_VC_A_1468 |
-
-
- | 498 |
- HB_566_AD |
- AD |
- NA |
- 6157_VC_A_0062 |
-
-
- | 499 |
- HB_568_AD |
- AD |
- NA |
- 6164_CR_A_1005 |
-
-
- | 500 |
- HB_571_AD |
- AD |
- NA |
- 6171_CR_A_0065 |
-
-
- | 501 |
- HB_573_AD |
- AD |
- NA |
- 6174_VC_A_0068 |
-
-
- | 502 |
- HB_576_AD |
- AD |
- NA |
- 6180_CR_A_0281 |
-
-
- | 503 |
- HB_583_AD |
- AD |
- NA |
- 6194_VC_A_0071 |
-
-
- | 504 |
- HB_585_AD |
- AD |
- NA |
- 6198_VC_A_0073 |
-
-
- | 505 |
- HB_590_AD |
- AD |
- NA |
- 6215_VC_A_0518 |
-
-
- | 506 |
- HB_591_AD |
- AD |
- NA |
- 6216_VC_A_1476 |
-
-
- | 507 |
- HB_592_AD |
- AD |
- NA |
- 6218_CR_A_0522 |
-
-
- | 508 |
- HB_594_AD |
- AD |
- NA |
- 6223_VC_A_0288 |
-
-
- | 509 |
- HB_596_AD |
- AD |
- NA |
- 6226_CR_A_0076 |
-
-
- | 510 |
- HB_597_AD |
- AD |
- NA |
- 6227_VC_A_0080 |
-
-
- | 511 |
- HB_598_AD |
- AD |
- NA |
- 6231_VC_A_1479 |
-
-
- | 512 |
- HB_605_AD |
- AD |
- NA |
- 6261_VC_A_0084 |
-
-
- | 513 |
- HB_608_AD |
- AD |
- NA |
- 6268_CR_A_0525 |
-
-
- | 514 |
- HB_611_AD |
- AD |
- NA |
- 6279_VC_A_0089 |
-
-
- | 515 |
- HB_612_AD |
- AD |
- NA |
- 6280_VC_A_0091 |
-
-
- | 516 |
- HB_613_AD |
- AD |
- NA |
- 6281_CR_A_0528 |
-
-
- | 517 |
- HB_621_AD |
- AD |
- NA |
- 6308_VC_A_1503 |
-
-
- | 518 |
- HB_623_AD |
- AD |
- NA |
- 6311_CR_A_0531 |
-
-
- | 519 |
- HB_624_AD |
- AD |
- NA |
- 6312_CR_A_0534 |
-
-
- | 520 |
- HB_630_AD |
- AD |
- NA |
- 6324_PF_A_1514 |
-
-
- | 521 |
- HB_633_AD |
- AD |
- NA |
- 6332_VC_A_1518 |
-
-
- | 522 |
- HB_634_AD |
- AD |
- NA |
- 6335_VC_A_0536 |
-
-
- | 523 |
- HB_635_AD |
- AD |
- NA |
- 6336_CR_A_0290 |
-
-
- | 524 |
- HB_636_AD |
- AD |
- NA |
- 6338_VC_A_0539 |
-
-
- | 525 |
- HB_642_AD |
- AD |
- NA |
- 6358_VC_A_0545 |
-
-
- | 526 |
- HB_652_AD |
- AD |
- NA |
- 6387_VC_A_0093 |
-
-
- | 527 |
- HB_657_AD |
- AD |
- NA |
- 6394_VC_A_0551 |
-
-
- | 528 |
- HB_664_AD |
- AD |
- NA |
- 6416_VC_A_1095 |
-
-
- | 529 |
- HB_666_AD |
- AD |
- NA |
- 6422_CR_A_0555 |
-
-
- | 530 |
- HB_669_AD |
- AD |
- NA |
- 6431_VC_A_0294 |
-
-
- | 531 |
- HB_674_AD |
- AD |
- NA |
- 6449_VC_A_1183 |
-
-
- | 532 |
- HB_680_AD |
- AD |
- NA |
- 6458_CR_A_2570 |
-
-
- | 533 |
- HB_685_AD |
- AD |
- NA |
- 6481_VC_A_0560 |
-
-
- | 534 |
- HB_690_AD |
- AD |
- NA |
- 6489_CR_A_0100 |
-
-
- | 535 |
- HB_696_AD |
- AD |
- NA |
- 6511_VC_A_1119 |
-
-
- | 536 |
- HB_698_AD |
- AD |
- NA |
- 6515_CR_A_0564 |
-
-
- | 537 |
- HB_699_AD |
- AD |
- NA |
- 6518_VC_A_0103 |
-
-
- | 538 |
- HB_703_AD |
- AD |
- NA |
- 6523_VC_A_0107 |
-
-
- | 539 |
- HB_704_AD |
- AD |
- NA |
- 6530_VC_A_0112 |
-
-
- | 540 |
- HB_706_AD |
- AD |
- NA |
- 6534_VC_A_0306 |
-
-
- | 541 |
- HB_712_AD |
- AD |
- NA |
- 6546_PF_A_1194 |
-
-
- | 542 |
- HB_713_AD |
- AD |
- NA |
- 6548_PF_A_1541 |
-
-
- | 543 |
- HB_715_AD |
- AD |
- NA |
- 6550_VC_A_1201 |
-
-
- | 544 |
- HB_718_AD |
- AD |
- NA |
- 6554_PF_A_1203 |
-
-
- | 545 |
- HB_720_AD |
- AD |
- NA |
- 6559_PF_A_2287 |
-
-
- | 546 |
- HB_722_AD |
- AD |
- NA |
- 6561_CR_A_2582 |
-
-
- | 547 |
- HB_723_AD |
- AD |
- NA |
- 6562_PF_A_2290 |
-
-
- | 548 |
- HB_724_AD |
- AD |
- NA |
- 6564_CR_A_2585 |
-
-
- | 549 |
- HB_727_AD |
- AD |
- NA |
- 6575_CR_A_2298 |
-
-
- | 550 |
- HB_728_AD |
- AD |
- NA |
- 6577_PF_A_2299 |
-
-
- | 551 |
- HB_729_AD |
- AD |
- NA |
- 6578_PF_A_2302 |
-
-
- | 552 |
- HB_731_AD |
- AD |
- NA |
- 6582_VC_A_1207 |
-
-
- | 553 |
- HB_733_AD |
- AD |
- NA |
- 6585_VC_A_1210 |
-
-
- | 554 |
- HB_736_AD |
- AD |
- NA |
- 6590_PF_A_1215 |
-
-
- | 555 |
- HB_743_AD |
- AD |
- NA |
- 6603_PF_A_1448 |
-
-
- | 556 |
- HB_745_AD |
- AD |
- NA |
- 6610_PF_A_1227 |
-
-
- | 557 |
- HB_746_AD |
- AD |
- NA |
- 6612_PF_A_2308 |
-
-
- | 558 |
- HB_749_AD |
- AD |
- NA |
- 6617_VC_A_2587 |
-
-
- | 559 |
- HB_751_AD |
- AD |
- NA |
- 6629_VC_A_2330 |
-
-
- | 560 |
- HB_752_AD |
- AD |
- NA |
- 6630_VC_A_2590 |
-
-
- | 561 |
- HB_753_AD |
- AD |
- NA |
- 6632_PF_A_2332 |
-
-
- | 562 |
- HB_754_AD |
- AD |
- NA |
- 6637_VC_A_2596 |
-
-
- | 563 |
- HB_755_AD |
- AD |
- NA |
- 6638_VC_A_2599 |
-
-
- | 564 |
- HB_756_AD |
- AD |
- NA |
- 6639_VC_A_2336 |
-
-
- | 565 |
- HB_757_AD |
- AD |
- NA |
- 6641_PF_A_2338 |
-
-
- | 566 |
- HB_763_AD |
- AD |
- NA |
- 6654_VC_A_1237 |
-
-
- | 567 |
- HB_773_AD |
- AD |
- NA |
- 6681_VC_A_1252 |
-
-
- | 568 |
- HB_775_AD |
- AD |
- NA |
- 6693_VC_A_2348 |
-
-
- | 569 |
- HB_776_AD |
- AD |
- NA |
- 6694_VC_A_2351 |
-
-
- | 570 |
- HB_777_AD |
- AD |
- NA |
- 6695_PF_A_2353 |
-
-
- | 571 |
- HB_779_AD |
- AD |
- NA |
- 6699_PF_A_2359 |
-
-
- | 572 |
- HB_781_AD |
- AD |
- NA |
- 6708_VC_A_2366 |
-
-
- | 573 |
- HB_782_AD |
- AD |
- NA |
- 6776_PF_A_2607 |
-
-
- | 574 |
- HB_783_AD |
- AD |
- NA |
- 6778_PF_A_2368 |
-
-
- | 575 |
- HB_784_AD |
- AD |
- NA |
- 6779_PF_A_2371 |
-
-
- | 576 |
- HB_785_AD |
- AD |
- NA |
- 6780_PF_A_2374 |
-
-
- | 577 |
- HB_786_AD |
- AD |
- NA |
- 6782_PF_A_2377 |
-
-
- | 578 |
- HB_787_AD |
- AD |
- NA |
- 6784_PF_A_2380 |
-
-
- | 579 |
- HB_788_AD |
- AD |
- NA |
- 6785_CR_A_2385 |
-
-
- | 580 |
- HB_789_AD |
- AD |
- NA |
- 6787_CR_A_2388 |
-
-
- | 581 |
- HB_791_AD |
- AD |
- NA |
- 6790_PF_A_2392 |
-
-
- | 582 |
- HB_792_AD |
- AD |
- NA |
- 6791_PF_A_2395 |
-
-
- | 583 |
- HB_793_AD |
- AD |
- NA |
- 6793_PF_A_2398 |
-
-
- | 584 |
- HB_794_AD |
- AD |
- NA |
- 6794_PF_A_2401 |
-
-
- | 585 |
- HB_795_AD |
- AD |
- NA |
- 6797_PF_A_2404 |
-
-
- | 586 |
- HB_796_AD |
- AD |
- NA |
- 6798_PF_A_2407 |
-
-
- | 587 |
- HB_797_AD |
- AD |
- NA |
- 6799_VC_A_2411 |
-
-
- | 588 |
- HB_798_AD |
- AD |
- NA |
- 6801_VC_A_2414 |
-
-
- | 589 |
- HB_799_AD |
- AD |
- NA |
- 6803_VC_A_2417 |
-
-
- | 590 |
- HB_801_AD |
- AD |
- NA |
- 6809_PF_A_2422 |
-
-
- | 591 |
- HB_803_AD |
- AD |
- NA |
- 6818_CR_A_2430 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/HBTRC_MLC_AD_0611/experiment-design.rtf b/general/datasets/HBTRC_MLC_AD_0611/experiment-design.rtf
deleted file mode 100644
index 3b0c224..0000000
--- a/general/datasets/HBTRC_MLC_AD_0611/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
diff --git a/general/datasets/HBTRC_MLC_AD_0611/notes.rtf b/general/datasets/HBTRC_MLC_AD_0611/notes.rtf
deleted file mode 100644
index ff90e34..0000000
--- a/general/datasets/HBTRC_MLC_AD_0611/notes.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Species: Human
-Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
-Disease: Neurological Disease
-Investigator: Francine Benes/ Eric Schadt
-Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
-Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC_MLC_AD_0611/summary.rtf b/general/datasets/HBTRC_MLC_AD_0611/summary.rtf
deleted file mode 100644
index 5cde3bf..0000000
--- a/general/datasets/HBTRC_MLC_AD_0611/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC_MLC_HD_0611/acknowledgment.rtf b/general/datasets/HBTRC_MLC_HD_0611/acknowledgment.rtf
deleted file mode 100644
index 208cb6e..0000000
--- a/general/datasets/HBTRC_MLC_HD_0611/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC_MLC_HD_0611/cases.rtf b/general/datasets/HBTRC_MLC_HD_0611/cases.rtf
deleted file mode 100644
index e64114d..0000000
--- a/general/datasets/HBTRC_MLC_HD_0611/cases.rtf
+++ /dev/null
@@ -1,4156 +0,0 @@
-
-
-
-
-
-
-
- | Series |
- Cerebellum in GN |
- Condition |
- Gender |
- BioSample Name |
-
-
- | 1 |
- HB_029_N |
- N |
- NA |
- 3405_VC_N_0859 |
-
-
- | 2 |
- HB_058_N |
- N |
- NA |
- 4021_VC_N_0854 |
-
-
- | 3 |
- HB_064_N |
- N |
- NA |
- 4338_VC_N_0861 |
-
-
- | 4 |
- HB_086_N |
- N |
- NA |
- 4729_PF_N_0756 |
-
-
- | 5 |
- HB_091_N |
- N |
- NA |
- 4741_VC_N_0864 |
-
-
- | 6 |
- HB_092_N |
- N |
- NA |
- 4744_VC_N_0865 |
-
-
- | 7 |
- HB_102_N |
- N |
- NA |
- 4810_VC_N_0869 |
-
-
- | 8 |
- HB_119_N |
- N |
- NA |
- 4872_VC_N_0878 |
-
-
- | 9 |
- HB_147_N |
- N |
- NA |
- 5021_VC_N_0852 |
-
-
- | 10 |
- HB_161_N |
- N |
- NA |
- 5077_VC_N_0851 |
-
-
- | 11 |
- HB_162_N |
- N |
- NA |
- 5081_VC_N_1021 |
-
-
- | 12 |
- HB_166_N |
- N |
- NA |
- 5095_VC_N_1024 |
-
-
- | 13 |
- HB_183_N |
- N |
- NA |
- 5162_VC_N_0850 |
-
-
- | 14 |
- HB_206_N |
- N |
- NA |
- 5245_VC_N_0849 |
-
-
- | 15 |
- HB_215_N |
- N |
- NA |
- 5270_VC_N_0848 |
-
-
- | 16 |
- HB_218_N |
- N |
- NA |
- 5276_CR_N_0912 |
-
-
- | 17 |
- HB_223_N |
- N |
- NA |
- 5287_VC_N_0916 |
-
-
- | 18 |
- HB_226_N |
- N |
- NA |
- 5294_VC_N_0919 |
-
-
- | 19 |
- HB_241_N |
- N |
- NA |
- 5326_CR_N_0652 |
-
-
- | 20 |
- HB_243_N |
- N |
- NA |
- 5333_VC_N_1262 |
-
-
- | 21 |
- HB_247_N |
- N |
- NA |
- 5341_VC_N_0923 |
-
-
- | 22 |
- HB_257_N |
- N |
- NA |
- 5368_PF_N_1032 |
-
-
- | 23 |
- HB_264_N |
- N |
- NA |
- 5384_VC_N_0924 |
-
-
- | 24 |
- HB_295_N |
- N |
- NA |
- 5452_VC_N_1268 |
-
-
- | 25 |
- HB_300_N |
- N |
- NA |
- 5463_VC_N_0845 |
-
-
- | 26 |
- HB_311_N |
- N |
- NA |
- 5489_CR_N_0942 |
-
-
- | 27 |
- HB_324_N |
- N |
- NA |
- 5531_VC_N_0844 |
-
-
- | 28 |
- HB_332_N |
- N |
- NA |
- 5547_VC_N_0843 |
-
-
- | 29 |
- HB_340_N |
- N |
- NA |
- 5568_VC_N_0842 |
-
-
- | 30 |
- HB_360_N |
- N |
- NA |
- 5619_CR_N_0645 |
-
-
- | 31 |
- HB_365_N |
- N |
- NA |
- 5632_VC_N_0838 |
-
-
- | 32 |
- HB_367_N |
- N |
- NA |
- 5637_VC_N_0837 |
-
-
- | 33 |
- HB_382_N |
- N |
- NA |
- 5684_PF_N_1270 |
-
-
- | 34 |
- HB_396_N |
- N |
- NA |
- 5718_VC_N_0956 |
-
-
- | 35 |
- HB_398_N |
- N |
- NA |
- 5722_VC_N_1044 |
-
-
- | 36 |
- HB_400_N |
- N |
- NA |
- 5726_VC_N_0834_Bis |
-
-
- | 37 |
- HB_403_N |
- N |
- NA |
- 5734_VC_N_0833 |
-
-
- | 38 |
- HB_414_N |
- N |
- NA |
- 5772_VC_N_0832_Bis |
-
-
- | 39 |
- HB_416_N |
- N |
- NA |
- 5778_CR_N_0962 |
-
-
- | 40 |
- HB_418_N |
- N |
- NA |
- 5789_PF_N_1273 |
-
-
- | 41 |
- HB_421_N |
- N |
- NA |
- 5799_VC_N_1058 |
-
-
- | 42 |
- HB_423_N |
- N |
- NA |
- 5803_VC_N_0966 |
-
-
- | 43 |
- HB_426_N |
- N |
- NA |
- 5806_PF_N_1064 |
-
-
- | 44 |
- HB_427_N |
- N |
- NA |
- 5810_CR_N_0636 |
-
-
- | 45 |
- HB_431_N |
- N |
- NA |
- 5823_VC_N_0829 |
-
-
- | 46 |
- HB_432_N |
- N |
- NA |
- 5826_VC_N_0828 |
-
-
- | 47 |
- HB_433_N |
- N |
- NA |
- 5827_VC_N_0827 |
-
-
- | 48 |
- HB_436_N |
- N |
- NA |
- 5832_PF_N_1145 |
-
-
- | 49 |
- HB_443_N |
- N |
- NA |
- 5852_VC_N_0826 |
-
-
- | 50 |
- HB_446_N |
- N |
- NA |
- 5859_VC_N_0825 |
-
-
- | 51 |
- HB_449_N |
- N |
- NA |
- 5866_VC_N_0824 |
-
-
- | 52 |
- HB_450_N |
- N |
- NA |
- 5867_VC_N_1277 |
-
-
- | 53 |
- HB_453_N |
- N |
- NA |
- 5876_VC_N_0823 |
-
-
- | 54 |
- HB_462_N |
- N |
- NA |
- 5903_VC_N_0822 |
-
-
- | 55 |
- HB_464_N |
- N |
- NA |
- 5905_VC_N_0820 |
-
-
- | 56 |
- HB_468_N |
- N |
- NA |
- 5912_VC_N_1286 |
-
-
- | 57 |
- HB_472_N |
- N |
- NA |
- 5925_VC_N_1289 |
-
-
- | 58 |
- HB_475_N |
- N |
- NA |
- 5936_VC_N_0979 |
-
-
- | 59 |
- HB_476_N |
- N |
- NA |
- 5938_VC_N_0819 |
-
-
- | 60 |
- HB_480_N |
- N |
- NA |
- 5946_VC_N_0985 |
-
-
- | 61 |
- HB_485_N |
- N |
- NA |
- 5959_VC_N_0818 |
-
-
- | 62 |
- HB_486_N |
- N |
- NA |
- 5963_VC_N_0987 |
-
-
- | 63 |
- HB_495_N |
- N |
- NA |
- 5980_VC_N_0989 |
-
-
- | 64 |
- HB_497_N |
- N |
- NA |
- 5985_VC_N_0990 |
-
-
- | 65 |
- HB_500_N |
- N |
- NA |
- 5990_VC_N_0817 |
-
-
- | 66 |
- HB_501_N |
- N |
- NA |
- 5991_VC_N_0816 |
-
-
- | 67 |
- HB_504_N |
- N |
- NA |
- 5996_VC_N_0815 |
-
-
- | 68 |
- HB_505_N |
- N |
- NA |
- 5998_VC_N_0814 |
-
-
- | 69 |
- HB_507_N |
- N |
- NA |
- 6006_VC_N_0813 |
-
-
- | 70 |
- HB_508_N |
- N |
- NA |
- 6007_CR_N_0618 |
-
-
- | 71 |
- HB_509_N |
- N |
- NA |
- 6008_PF_N_1081 |
-
-
- | 72 |
- HB_512_N |
- N |
- NA |
- 6023_PF_N_1155 |
-
-
- | 73 |
- HB_516_N |
- N |
- NA |
- 6030_VC_N_0810 |
-
-
- | 74 |
- HB_519_N |
- N |
- NA |
- 6034_VC_N_0809 |
-
-
- | 75 |
- HB_532_N |
- N |
- NA |
- 6060_VC_N_1292 |
-
-
- | 76 |
- HB_541_N |
- N |
- NA |
- 6092_VC_N_1001 |
-
-
- | 77 |
- HB_542_N |
- N |
- NA |
- 6096_VC_N_0807 |
-
-
- | 78 |
- HB_544_N |
- N |
- NA |
- 6101_CR_N_1161 |
-
-
- | 79 |
- HB_547_N |
- N |
- NA |
- 6110_VC_N_1295 |
-
-
- | 80 |
- HB_551_N |
- N |
- NA |
- 6124_VC_N_0806 |
-
-
- | 81 |
- HB_557_N |
- N |
- NA |
- 6134_PF_N_1297 |
-
-
- | 82 |
- HB_560_N |
- N |
- NA |
- 6142_VC_N_0805 |
-
-
- | 83 |
- HB_569_N |
- N |
- NA |
- 6166_VC_N_0804 |
-
-
- | 84 |
- HB_570_N |
- N |
- NA |
- 6170_VC_N_0803 |
-
-
- | 85 |
- HB_572_N |
- N |
- NA |
- 6172_VC_N_1008 |
-
-
- | 86 |
- HB_577_N |
- N |
- NA |
- 6182_VC_N_1166 |
-
-
- | 87 |
- HB_579_N |
- N |
- NA |
- 6187_CR_N_0607 |
-
-
- | 88 |
- HB_581_N |
- N |
- NA |
- 6191_VC_N_1010 |
-
-
- | 89 |
- HB_584_N |
- N |
- NA |
- 6196_CR_N_0605 |
-
-
- | 90 |
- HB_586_N |
- N |
- NA |
- 6200_VC_N_0799 |
-
-
- | 91 |
- HB_587_N |
- N |
- NA |
- 6206_PF_N_1176 |
-
-
- | 92 |
- HB_589_N |
- N |
- NA |
- 6213_VC_N_0798 |
-
-
- | 93 |
- HB_601_N |
- N |
- NA |
- 6241_VC_N_0796 |
-
-
- | 94 |
- HB_604_N |
- N |
- NA |
- 6260_VC_N_0794 |
-
-
- | 95 |
- HB_609_N |
- N |
- NA |
- 6270_VC_N_0793 |
-
-
- | 96 |
- HB_618_N |
- N |
- NA |
- 6289_VC_N_0791 |
-
-
- | 97 |
- HB_622_N |
- N |
- NA |
- 6310_VC_N_0790 |
-
-
- | 98 |
- HB_625_N |
- N |
- NA |
- 6314_VC_N_0789 |
-
-
- | 99 |
- HB_637_N |
- N |
- NA |
- 6340_VC_N_0786 |
-
-
- | 100 |
- HB_638_N |
- N |
- NA |
- 6341_VC_N_0785 |
-
-
- | 101 |
- HB_640_N |
- N |
- NA |
- 6347_VC_N_0784 |
-
-
- | 102 |
- HB_641_N |
- N |
- NA |
- 6356_VC_N_0783 |
-
-
- | 103 |
- HB_643_N |
- N |
- NA |
- 6363_VC_N_0781 |
-
-
- | 104 |
- HB_644_N |
- N |
- NA |
- 6366_VC_N_0780 |
-
-
- | 105 |
- HB_645_N |
- N |
- NA |
- 6374_VC_N_0779 |
-
-
- | 106 |
- HB_650_N |
- N |
- NA |
- 6384_VC_N_0777 |
-
-
- | 107 |
- HB_651_N |
- N |
- NA |
- 6386_VC_N_0776 |
-
-
- | 108 |
- HB_653_N |
- N |
- NA |
- 6388_VC_N_0775 |
-
-
- | 109 |
- HB_659_N |
- N |
- NA |
- 6406_VC_N_1180 |
-
-
- | 110 |
- HB_662_N |
- N |
- NA |
- 6411_VC_N_0771 |
-
-
- | 111 |
- HB_663_N |
- N |
- NA |
- 6415_VC_N_0770 |
-
-
- | 112 |
- HB_670_N |
- N |
- NA |
- 6436_VC_N_0769 |
-
-
- | 113 |
- HB_687_N |
- N |
- NA |
- 6484_VC_N_0765 |
-
-
- | 114 |
- HB_689_N |
- N |
- NA |
- 6486_VC_N_0764 |
-
-
- | 115 |
- HB_694_N |
- N |
- NA |
- 6500_VC_N_0763 |
-
-
- | 116 |
- HB_697_N |
- N |
- NA |
- 6512_VC_N_0762 |
-
-
- | 117 |
- HB_700_N |
- N |
- NA |
- 6520_VC_N_0761 |
-
-
- | 118 |
- HB_711_N |
- N |
- NA |
- 6543_PF_N_1191 |
-
-
- | 119 |
- HB_714_N |
- N |
- NA |
- 6549_VC_N_1198 |
-
-
- | 120 |
- HB_717_N |
- N |
- NA |
- 6553_PF_N_2284 |
-
-
- | 121 |
- HB_721_N |
- N |
- NA |
- 6560_VC_N_2578 |
-
-
- | 122 |
- HB_726_N |
- N |
- NA |
- 6573_PF_N_2293 |
-
-
- | 123 |
- HB_730_N |
- N |
- NA |
- 6580_VC_N_2306 |
-
-
- | 124 |
- HB_735_N |
- N |
- NA |
- 6588_VC_N_1213 |
-
-
- | 125 |
- HB_737_N |
- N |
- NA |
- 6593_VC_N_1219 |
-
-
- | 126 |
- HB_738_N |
- N |
- NA |
- 6594_VC_N_1222 |
-
-
- | 127 |
- HB_759_N |
- N |
- NA |
- 6645_VC_N_1231 |
-
-
- | 128 |
- HB_764_N |
- N |
- NA |
- 6655_VC_N_1240 |
-
-
- | 129 |
- HB_765_N |
- N |
- NA |
- 6656_VC_N_1243 |
-
-
- | 130 |
- HB_767_N |
- N |
- NA |
- 6661_PF_N_2341 |
-
-
- | 131 |
- HB_770_N |
- N |
- NA |
- 6669_VC_N_1246 |
-
-
- | 132 |
- HB_772_N |
- N |
- NA |
- 6676_PF_N_1248 |
-
-
- | 133 |
- HB_001_HD |
- HD |
- F |
- 2028_CR_H_2282 |
-
-
- | 134 |
- HB_003_HD |
- HD |
- F |
- 2685_PF_H_2212 |
-
-
- | 135 |
- HB_004_HD |
- HD |
- M |
- 2706_CR_H_2432 |
-
-
- | 136 |
- HB_006_HD |
- HD |
- M |
- 2737_VC_H_2194 |
-
-
- | 137 |
- HB_007_HD |
- HD |
- NA |
- 2769_VC_H_2193 |
-
-
- | 138 |
- HB_008_HD |
- HD |
- F |
- 2790_CR_H_1890 |
-
-
- | 139 |
- HB_009_HD |
- HD |
- NA |
- 2879_VC_H_2192 |
-
-
- | 140 |
- HB_010_HD |
- HD |
- M |
- 2960_VC_H_2002 |
-
-
- | 141 |
- HB_011_HD |
- HD |
- F |
- 3053_VC_H_2001 |
-
-
- | 142 |
- HB_012_HD |
- HD |
- F |
- 3128_VC_H_1999 |
-
-
- | 143 |
- HB_014_HD |
- HD |
- F |
- 3149_PF_H_2110 |
-
-
- | 144 |
- HB_015_HD |
- HD |
- F |
- 3150_VC_H_1996 |
-
-
- | 145 |
- HB_016_HD |
- HD |
- F |
- 3177_VC_H_2191 |
-
-
- | 146 |
- HB_017_HD |
- HD |
- NA |
- 3195_VC_H_2190 |
-
-
- | 147 |
- HB_018_HD |
- HD |
- M |
- 3200_VC_H_2189 |
-
-
- | 148 |
- HB_019_HD |
- HD |
- M |
- 3209_VC_H_2188 |
-
-
- | 149 |
- HB_020_HD |
- HD |
- M |
- 3224_VC_H_1994 |
-
-
- | 150 |
- HB_022_HD |
- HD |
- F |
- 3242_PF_H_2105 |
-
-
- | 151 |
- HB_024_HD |
- HD |
- NA |
- 3272_VC_H_2186 |
-
-
- | 152 |
- HB_027_HD |
- HD |
- M |
- 3356_VC_H_2439 |
-
-
- | 153 |
- HB_028_HD |
- HD |
- F |
- 3394_PF_H_2104 |
-
-
- | 154 |
- HB_031_HD |
- HD |
- M |
- 3430_VC_H_1990 |
-
-
- | 155 |
- HB_032_HD |
- HD |
- NA |
- 3444_PF_H_2208 |
-
-
- | 156 |
- HB_034_HD |
- HD |
- F |
- 3482_VC_H_1987 |
-
-
- | 157 |
- HB_036_HD |
- HD |
- M |
- 3576_VC_H_1984 |
-
-
- | 158 |
- HB_037_HD |
- HD |
- F |
- 3579_VC_H_1983 |
-
-
- | 159 |
- HB_038_HD |
- HD |
- F |
- 3584_VC_H_2183 |
-
-
- | 160 |
- HB_039_HD |
- HD |
- NA |
- 3635_VC_H_2182 |
-
-
- | 161 |
- HB_041_HD |
- HD |
- F |
- 3695_CR_H_2267 |
-
-
- | 162 |
- HB_042_HD |
- HD |
- M |
- 3697_VC_H_1982 |
-
-
- | 163 |
- HB_043_HD |
- HD |
- NA |
- 3703_VC_H_2180 |
-
-
- | 164 |
- HB_044_HD |
- HD |
- NA |
- 3723_VC_H_2179 |
-
-
- | 165 |
- HB_046_HD |
- HD |
- F |
- 3735_VC_H_1981 |
-
-
- | 166 |
- HB_050_HD |
- HD |
- M |
- 3820_PF_H_2207 |
-
-
- | 167 |
- HB_051_HD |
- HD |
- F |
- 3849_CR_H_2262 |
-
-
- | 168 |
- HB_054_HD |
- HD |
- M |
- 3884_VC_H_2175 |
-
-
- | 169 |
- HB_056_HD |
- HD |
- NA |
- 4012_VC_H_2174 |
-
-
- | 170 |
- HB_057_HD |
- HD |
- NA |
- 4013_VC_H_2173 |
-
-
- | 171 |
- HB_059_HD |
- HD |
- NA |
- 4066_VC_H_2172 |
-
-
- | 172 |
- HB_060_HD |
- HD |
- NA |
- 4094_VC_H_2171 |
-
-
- | 173 |
- HB_061_HD |
- HD |
- F |
- 4116_VC_H_2170 |
-
-
- | 174 |
- HB_062_HD |
- HD |
- NA |
- 4121_VC_H_2169 |
-
-
- | 175 |
- HB_063_HD |
- HD |
- NA |
- 4215_VC_H_2167 |
-
-
- | 176 |
- HB_065_HD |
- HD |
- M |
- 4340_PF_H_2091 |
-
-
- | 177 |
- HB_066_HD |
- HD |
- F |
- 4344_VC_H_1977 |
-
-
- | 178 |
- HB_067_HD |
- HD |
- M |
- 4346_VC_H_2165 |
-
-
- | 179 |
- HB_069_HD |
- HD |
- F |
- 4356_VC_H_2164 |
-
-
- | 180 |
- HB_070_HD |
- HD |
- NA |
- 4386_CR_H_2249 |
-
-
- | 181 |
- HB_072_HD |
- HD |
- NA |
- 4404_VC_H_2161 |
-
-
- | 182 |
- HB_073_HD |
- HD |
- F |
- 4411_VC_H_1975 |
-
-
- | 183 |
- HB_074_HD |
- HD |
- NA |
- 4430_VC_H_2465 |
-
-
- | 184 |
- HB_075_HD |
- HD |
- M |
- 4470_VC_H_1974 |
-
-
- | 185 |
- HB_076_HD |
- HD |
- F |
- 4497_CR_H_1860 |
-
-
- | 186 |
- HB_077_HD |
- HD |
- M |
- 4509_CR_H_2244 |
-
-
- | 187 |
- HB_079_HD |
- HD |
- M |
- 4631_VC_H_1971 |
-
-
- | 188 |
- HB_080_HD |
- HD |
- F |
- 4653_PF_H_2083 |
-
-
- | 189 |
- HB_081_HD |
- HD |
- NA |
- 4678_CR_H_2242 |
-
-
- | 190 |
- HB_084_HD |
- HD |
- M |
- 4718_VC_H_2125 |
-
-
- | 191 |
- HB_090_HD |
- HD |
- NA |
- 4740_CR_H_2474 |
-
-
- | 192 |
- HB_094_HD |
- HD |
- NA |
- 4754_CR_H_2476 |
-
-
- | 193 |
- HB_098_HD |
- HD |
- NA |
- 4780_VC_H_2151 |
-
-
- | 194 |
- HB_101_HD |
- HD |
- F |
- 4809_VC_H_2148 |
-
-
- | 195 |
- HB_105_HD |
- HD |
- NA |
- 4819_CR_H_2238 |
-
-
- | 196 |
- HB_106_HD |
- HD |
- F |
- 4822_VC_H_1969 |
-
-
- | 197 |
- HB_108_HD |
- HD |
- M |
- 4826_VC_H_1968 |
-
-
- | 198 |
- HB_109_HD |
- HD |
- M |
- 4828_VC_H_2124 |
-
-
- | 199 |
- HB_115_HD |
- HD |
- NA |
- 4855_CR_H_2235 |
-
-
- | 200 |
- HB_121_HD |
- HD |
- F |
- 4902_VC_H_1967 |
-
-
- | 201 |
- HB_129_HD |
- HD |
- NA |
- 4938_VC_H_1966 |
-
-
- | 202 |
- HB_141_HD |
- HD |
- F |
- 4996_PF_H_2076 |
-
-
- | 203 |
- HB_152_HD |
- HD |
- NA |
- 5034_CR_H_2233 |
-
-
- | 204 |
- HB_153_HD |
- HD |
- M |
- 5043_VC_H_1960 |
-
-
- | 205 |
- HB_159_HD |
- HD |
- M |
- 5062_VC_H_1959 |
-
-
- | 206 |
- HB_172_HD |
- HD |
- F |
- 5114_PF_H_2070 |
-
-
- | 207 |
- HB_175_HD |
- HD |
- M |
- 5127_PF_H_2068 |
-
-
- | 208 |
- HB_180_HD |
- HD |
- M |
- 5148_VC_H_1944 |
-
-
- | 209 |
- HB_185_HD |
- HD |
- F |
- 5167_CR_H_2231 |
-
-
- | 210 |
- HB_188_HD |
- HD |
- F |
- 5172_VC_H_1951 |
-
-
- | 211 |
- HB_191_HD |
- HD |
- M |
- 5180_VC_H_1949 |
-
-
- | 212 |
- HB_196_HD |
- HD |
- NA |
- 5199_PF_H_2202 |
-
-
- | 213 |
- HB_203_HD |
- HD |
- F |
- 5228_PF_H_2059 |
-
-
- | 214 |
- HB_207_HD |
- HD |
- NA |
- 5248_PF_H_2201 |
-
-
- | 215 |
- HB_228_HD |
- HD |
- F |
- 5299_CR_H_2228 |
-
-
- | 216 |
- HB_233_HD |
- HD |
- M |
- 5312_VC_H_1938 |
-
-
- | 217 |
- HB_235_HD |
- HD |
- F |
- 5316_VC_H_1937 |
-
-
- | 218 |
- HB_242_HD |
- HD |
- F |
- 5328_PF_H_2048 |
-
-
- | 219 |
- HB_266_HD |
- HD |
- M |
- 5387_VC_H_1928 |
-
-
- | 220 |
- HB_271_HD |
- HD |
- M |
- 5394_PF_H_2039 |
-
-
- | 221 |
- HB_272_HD |
- HD |
- F |
- 5396_VC_H_1925 |
-
-
- | 222 |
- HB_279_HD |
- HD |
- F |
- 5409_VC_H_1924 |
-
-
- | 223 |
- HB_294_HD |
- HD |
- M |
- 5448_VC_H_1921 |
-
-
- | 224 |
- HB_301_HD |
- HD |
- NA |
- 5464_VC_H_1919 |
-
-
- | 225 |
- HB_304_HD |
- HD |
- F |
- 5471_VC_H_1918 |
-
-
- | 226 |
- HB_321_HD |
- HD |
- NA |
- 5522_PF_H_2199 |
-
-
- | 227 |
- HB_361_HD |
- HD |
- F |
- 5622_VC_H_2121 |
-
-
- | 228 |
- HB_370_HD |
- HD |
- M |
- 5645_VC_H_1904 |
-
-
- | 229 |
- HB_371_HD |
- HD |
- F |
- 5648_PF_H_2016 |
-
-
- | 230 |
- HB_384_HD |
- HD |
- F |
- 5688_PF_H_2012 |
-
-
- | 231 |
- HB_390_HD |
- HD |
- M |
- 5704_PF_H_2009 |
-
-
- | 232 |
- HB_393_HD |
- HD |
- F |
- 5709_VC_H_1895 |
-
-
- | 233 |
- HB_402_HD |
- HD |
- F |
- 5732_PF_H_2007 |
-
-
- | 234 |
- HB_405_HD |
- HD |
- NA |
- 5742_PF_H_2006 |
-
-
- | 235 |
- HB_407_HD |
- HD |
- M |
- 5745_PF_H_2005 |
-
-
- | 236 |
- HB_408_HD |
- HD |
- M |
- 5747_VC_H_1891 |
-
-
- | 237 |
- HB_415_HD |
- HD |
- NA |
- 5777_PF_H_1551 |
-
-
- | 238 |
- HB_417_HD |
- HD |
- M |
- 5784_PF_H_1554 |
-
-
- | 239 |
- HB_424_HD |
- HD |
- M |
- 5804_VC_H_1558 |
-
-
- | 240 |
- HB_444_HD |
- HD |
- M |
- 5856_VC_H_1567 |
-
-
- | 241 |
- HB_457_HD |
- HD |
- M |
- 5896_VC_H_1570 |
-
-
- | 242 |
- HB_466_HD |
- HD |
- M |
- 5910_PF_H_1572 |
-
-
- | 243 |
- HB_478_HD |
- HD |
- M |
- 5941_CR_H_1583 |
-
-
- | 244 |
- HB_487_HD |
- HD |
- F |
- 5964_VC_H_1597 |
-
-
- | 245 |
- HB_511_HD |
- HD |
- M |
- 6019_PF_H_2198 |
-
-
- | 246 |
- HB_513_HD |
- HD |
- F |
- 6024_VC_H_1612 |
-
-
- | 247 |
- HB_515_HD |
- HD |
- F |
- 6028_CR_H_1613 |
-
-
- | 248 |
- HB_518_HD |
- HD |
- M |
- 6033_VC_H_1618 |
-
-
- | 249 |
- HB_522_HD |
- HD |
- M |
- 6037_PF_H_1626 |
-
-
- | 250 |
- HB_527_HD |
- HD |
- F |
- 6047_VC_H_1639 |
-
-
- | 251 |
- HB_528_HD |
- HD |
- M |
- 6051_PF_H_1641 |
-
-
- | 252 |
- HB_530_HD |
- HD |
- M |
- 6054_VC_H_1648 |
-
-
- | 253 |
- HB_537_HD |
- HD |
- F |
- 6071_PF_H_1653 |
-
-
- | 254 |
- HB_549_HD |
- HD |
- M |
- 6119_CR_H_1670 |
-
-
- | 255 |
- HB_593_HD |
- HD |
- NA |
- 6219_CR_H_2567 |
-
-
- | 256 |
- HB_610_HD |
- HD |
- NA |
- 6275_PF_H_1692 |
-
-
- | 257 |
- HB_616_HD |
- HD |
- F |
- 6284_CR_H_1694 |
-
-
- | 258 |
- HB_626_HD |
- HD |
- M |
- 6315_VC_H_1702 |
-
-
- | 259 |
- HB_639_HD |
- HD |
- F |
- 6344_CR_H_1703 |
-
-
- | 260 |
- HB_649_HD |
- HD |
- F |
- 6382_CR_H_1709 |
-
-
- | 261 |
- HB_661_HD |
- HD |
- M |
- 6408_VC_H_1714 |
-
-
- | 262 |
- HB_682_HD |
- HD |
- M |
- 6467_PF_H_1725 |
-
-
- | 263 |
- HB_683_HD |
- HD |
- M |
- 6472_VC_H_1729 |
-
-
- | 264 |
- HB_691_HD |
- HD |
- F |
- 6493_VC_H_1732 |
-
-
- | 265 |
- HB_692_HD |
- HD |
- M |
- 6495_CR_H_1733 |
-
-
- | 266 |
- HB_707_HD |
- HD |
- M |
- 6535_PF_H_1737 |
-
-
- | 267 |
- HB_709_HD |
- HD |
- F |
- 6539_CR_H_1739 |
-
-
- | 268 |
- HB_725_HD |
- HD |
- M |
- 6572_PF_H_1746 |
-
-
- | 269 |
- HB_732_HD |
- HD |
- F |
- 6584_VC_H_1750 |
-
-
- | 270 |
- HB_734_HD |
- HD |
- F |
- 6587_CR_H_1751 |
-
-
- | 271 |
- HB_748_HD |
- HD |
- NA |
- 6615_VC_H_2315 |
-
-
- | 272 |
- HB_750_HD |
- HD |
- NA |
- 6628_PF_H_2326 |
-
-
- | 273 |
- HB_758_HD |
- HD |
- NA |
- 6643_VC_H_2602 |
-
-
- | 274 |
- HB_760_HD |
- HD |
- M |
- 6646_PF_H_1761 |
-
-
- | 275 |
- HB_762_HD |
- HD |
- M |
- 6650_VC_H_1765 |
-
-
- | 276 |
- HB_766_HD |
- HD |
- M |
- 6658_VC_H_1768 |
-
-
- | 277 |
- HB_768_HD |
- HD |
- NA |
- 6663_VC_H_1771 |
-
-
- | 278 |
- HB_769_HD |
- HD |
- M |
- 6666_VC_H_1774 |
-
-
- | 279 |
- HB_774_HD |
- HD |
- NA |
- 6689_PF_H_2344 |
-
-
- | 280 |
- HB_778_HD |
- HD |
- NA |
- 6696_PF_H_2356 |
-
-
- | 281 |
- HB_780_HD |
- HD |
- NA |
- 6704_PF_H_2362 |
-
-
- | 282 |
- HB_790_HD |
- HD |
- NA |
- 6788_PF_H_2389 |
-
-
- | 283 |
- HB_800_HD |
- HD |
- NA |
- 6807_PF_H_2419 |
-
-
- | 284 |
- HB_802_HD |
- HD |
- NA |
- 6811_PF_H_2425 |
-
-
- | 285 |
- HB_045_AD |
- AD |
- NA |
- 3734_CR_A_0122 |
-
-
- | 286 |
- HB_048_AD |
- AD |
- NA |
- 3791_CR_A_0128 |
-
-
- | 287 |
- HB_053_AD |
- AD |
- NA |
- 3877_CR_A_0134 |
-
-
- | 288 |
- HB_055_AD |
- AD |
- NA |
- 3893_VC_A_0142 |
-
-
- | 289 |
- HB_068_AD |
- AD |
- NA |
- 4349_VC_A_0148 |
-
-
- | 290 |
- HB_082_AD |
- AD |
- NA |
- 4712_CR_A_0309 |
-
-
- | 291 |
- HB_085_AD |
- AD |
- NA |
- 4726_VC_A_0311 |
-
-
- | 292 |
- HB_087_AD |
- AD |
- NA |
- 4730_CR_A_0315 |
-
-
- | 293 |
- HB_089_AD |
- AD |
- NA |
- 4733_VC_A_0320 |
-
-
- | 294 |
- HB_093_AD |
- AD |
- NA |
- 4749_VC_A_0323 |
-
-
- | 295 |
- HB_095_AD |
- AD |
- NA |
- 4759_CR_A_0327 |
-
-
- | 296 |
- HB_097_AD |
- AD |
- NA |
- 4773_CR_A_0866 |
-
-
- | 297 |
- HB_099_AD |
- AD |
- NA |
- 4785_VC_A_0332 |
-
-
- | 298 |
- HB_100_AD |
- AD |
- NA |
- 4795_VC_A_0335 |
-
-
- | 299 |
- HB_103_AD |
- AD |
- NA |
- 4811_VC_A_0341 |
-
-
- | 300 |
- HB_104_AD |
- AD |
- NA |
- 4813_CR_A_0345 |
-
-
- | 301 |
- HB_112_AD |
- AD |
- NA |
- 4842_VC_A_0870 |
-
-
- | 302 |
- HB_113_AD |
- AD |
- NA |
- 4850_CR_A_0351 |
-
-
- | 303 |
- HB_114_AD |
- AD |
- NA |
- 4852_CR_A_0354 |
-
-
- | 304 |
- HB_117_AD |
- AD |
- NA |
- 4868_VC_A_0874 |
-
-
- | 305 |
- HB_122_AD |
- AD |
- NA |
- 4904_CR_A_1132 |
-
-
- | 306 |
- HB_123_AD |
- AD |
- NA |
- 4905_VC_A_0884 |
-
-
- | 307 |
- HB_124_AD |
- AD |
- NA |
- 4916_VC_A_0886 |
-
-
- | 308 |
- HB_125_AD |
- AD |
- NA |
- 4917_CR_A_0360 |
-
-
- | 309 |
- HB_126_AD |
- AD |
- NA |
- 4921_VC_A_0362 |
-
-
- | 310 |
- HB_128_AD |
- AD |
- NA |
- 4936_CR_A_0369 |
-
-
- | 311 |
- HB_130_AD |
- AD |
- NA |
- 4939_VC_A_0888 |
-
-
- | 312 |
- HB_131_AD |
- AD |
- NA |
- 4944_CR_A_0889 |
-
-
- | 313 |
- HB_132_AD |
- AD |
- NA |
- 4946_CR_A_0372 |
-
-
- | 314 |
- HB_134_AD |
- AD |
- NA |
- 4951_CR_A_0891 |
-
-
- | 315 |
- HB_135_AD |
- AD |
- NA |
- 4953_VC_A_0893 |
-
-
- | 316 |
- HB_136_AD |
- AD |
- NA |
- 4965_VC_A_0160 |
-
-
- | 317 |
- HB_137_AD |
- AD |
- NA |
- 4966_VC_A_0374 |
-
-
- | 318 |
- HB_138_AD |
- AD |
- NA |
- 4969_VC_A_0895 |
-
-
- | 319 |
- HB_140_AD |
- AD |
- NA |
- 4993_CR_A_0896 |
-
-
- | 320 |
- HB_146_AD |
- AD |
- NA |
- 5018_CR_A_0384 |
-
-
- | 321 |
- HB_148_AD |
- AD |
- NA |
- 5022_VC_A_0386 |
-
-
- | 322 |
- HB_150_AD |
- AD |
- NA |
- 5031_VC_A_0392 |
-
-
- | 323 |
- HB_151_AD |
- AD |
- NA |
- 5033_CR_A_0396 |
-
-
- | 324 |
- HB_154_AD |
- AD |
- NA |
- 5048_VC_A_1321 |
-
-
- | 325 |
- HB_155_AD |
- AD |
- NA |
- 5056_VC_A_0398 |
-
-
- | 326 |
- HB_156_AD |
- AD |
- NA |
- 5057_VC_A_0163 |
-
-
- | 327 |
- HB_157_AD |
- AD |
- NA |
- 5059_VC_A_0401 |
-
-
- | 328 |
- HB_158_AD |
- AD |
- NA |
- 5061_PF_A_2612 |
-
-
- | 329 |
- HB_160_AD |
- AD |
- NA |
- 5064_PF_A_2615 |
-
-
- | 330 |
- HB_165_AD |
- AD |
- NA |
- 5092_CR_A_0899 |
-
-
- | 331 |
- HB_168_AD |
- AD |
- NA |
- 5097_VC_A_0407 |
-
-
- | 332 |
- HB_170_AD |
- AD |
- NA |
- 5101_VC_A_0410 |
-
-
- | 333 |
- HB_174_AD |
- AD |
- NA |
- 5124_PF_A_1343 |
-
-
- | 334 |
- HB_179_AD |
- AD |
- NA |
- 5145_VC_A_1351 |
-
-
- | 335 |
- HB_181_AD |
- AD |
- NA |
- 5152_CR_A_0414 |
-
-
- | 336 |
- HB_184_AD |
- AD |
- NA |
- 5166_VC_A_1354 |
-
-
- | 337 |
- HB_194_AD |
- AD |
- NA |
- 5193_VC_A_1360 |
-
-
- | 338 |
- HB_197_AD |
- AD |
- NA |
- 5202_CR_A_1368 |
-
-
- | 339 |
- HB_199_AD |
- AD |
- NA |
- 5205_VC_A_0166 |
-
-
- | 340 |
- HB_200_AD |
- AD |
- NA |
- 5210_VC_A_0905 |
-
-
- | 341 |
- HB_205_AD |
- AD |
- NA |
- 5235_VC_A_0419 |
-
-
- | 342 |
- HB_208_AD |
- AD |
- NA |
- 5249_VC_A_0422 |
-
-
- | 343 |
- HB_209_AD |
- AD |
- NA |
- 5252_VC_A_0907 |
-
-
- | 344 |
- HB_211_AD |
- AD |
- NA |
- 5257_VC_A_0169 |
-
-
- | 345 |
- HB_216_AD |
- AD |
- NA |
- 5272_VC_A_0425 |
-
-
- | 346 |
- HB_219_AD |
- AD |
- NA |
- 5279_CR_A_0147 |
-
-
- | 347 |
- HB_221_AD |
- AD |
- NA |
- 5283_VC_A_0145 |
-
-
- | 348 |
- HB_222_AD |
- AD |
- NA |
- 5285_VC_A_0141 |
-
-
- | 349 |
- HB_224_AD |
- AD |
- NA |
- 5288_VC_A_0428 |
-
-
- | 350 |
- HB_230_AD |
- AD |
- NA |
- 5301_VC_A_0174 |
-
-
- | 351 |
- HB_231_AD |
- AD |
- NA |
- 5305_VC_A_1384 |
-
-
- | 352 |
- HB_232_AD |
- AD |
- NA |
- 5310_CR_A_0176 |
-
-
- | 353 |
- HB_234_AD |
- AD |
- NA |
- 5313_PF_A_2618 |
-
-
- | 354 |
- HB_236_AD |
- AD |
- NA |
- 5317_PF_A_2624 |
-
-
- | 355 |
- HB_238_AD |
- AD |
- NA |
- 5322_CR_A_2632 |
-
-
- | 356 |
- HB_240_AD |
- AD |
- NA |
- 5325_VC_A_0137 |
-
-
- | 357 |
- HB_244_AD |
- AD |
- NA |
- 5337_VC_A_1387 |
-
-
- | 358 |
- HB_245_AD |
- AD |
- NA |
- 5339_VC_A_0181 |
-
-
- | 359 |
- HB_250_AD |
- AD |
- NA |
- 5346_VC_A_1393 |
-
-
- | 360 |
- HB_251_AD |
- AD |
- NA |
- 5350_VC_A_0184 |
-
-
- | 361 |
- HB_252_AD |
- AD |
- NA |
- 5355_VC_A_0133 |
-
-
- | 362 |
- HB_253_AD |
- AD |
- NA |
- 5359_CR_A_1395 |
-
-
- | 363 |
- HB_258_AD |
- AD |
- NA |
- 5370_PF_A_1400 |
-
-
- | 364 |
- HB_259_AD |
- AD |
- NA |
- 5371_PF_A_2636 |
-
-
- | 365 |
- HB_260_AD |
- AD |
- NA |
- 5375_VC_A_0188 |
-
-
- | 366 |
- HB_263_AD |
- AD |
- NA |
- 5381_VC_A_0022 |
-
-
- | 367 |
- HB_265_AD |
- AD |
- NA |
- 5385_VC_A_1402 |
-
-
- | 368 |
- HB_267_AD |
- AD |
- NA |
- 5389_VC_A_0928 |
-
-
- | 369 |
- HB_268_AD |
- AD |
- NA |
- 5390_CR_A_0151 |
-
-
- | 370 |
- HB_273_AD |
- AD |
- NA |
- 5400_PF_A_2645 |
-
-
- | 371 |
- HB_274_AD |
- AD |
- NA |
- 5401_VC_A_0931 |
-
-
- | 372 |
- HB_275_AD |
- AD |
- NA |
- 5404_PF_A_2648 |
-
-
- | 373 |
- HB_276_AD |
- AD |
- NA |
- 5406_VC_A_0933 |
-
-
- | 374 |
- HB_277_AD |
- AD |
- NA |
- 5407_PF_A_2651 |
-
-
- | 375 |
- HB_280_AD |
- AD |
- NA |
- 5412_VC_A_0935 |
-
-
- | 376 |
- HB_281_AD |
- AD |
- NA |
- 5413_PF_A_2657 |
-
-
- | 377 |
- HB_283_AD |
- AD |
- NA |
- 5419_VC_A_0937 |
-
-
- | 378 |
- HB_284_AD |
- AD |
- NA |
- 5420_VC_A_0939 |
-
-
- | 379 |
- HB_285_AD |
- AD |
- NA |
- 5421_CR_A_0432 |
-
-
- | 380 |
- HB_286_AD |
- AD |
- NA |
- 5423_PF_A_2660 |
-
-
- | 381 |
- HB_288_AD |
- AD |
- NA |
- 5425_PF_A_2666 |
-
-
- | 382 |
- HB_289_AD |
- AD |
- NA |
- 5426_VC_A_1405 |
-
-
- | 383 |
- HB_290_AD |
- AD |
- NA |
- 5433_VC_A_0434 |
-
-
- | 384 |
- HB_296_AD |
- AD |
- NA |
- 5456_PF_A_2675 |
-
-
- | 385 |
- HB_299_AD |
- AD |
- NA |
- 5461_VC_A_0192 |
-
-
- | 386 |
- HB_302_AD |
- AD |
- NA |
- 5465_PF_A_2678 |
-
-
- | 387 |
- HB_303_AD |
- AD |
- NA |
- 5469_VC_A_1417 |
-
-
- | 388 |
- HB_305_AD |
- AD |
- NA |
- 5479_PF_A_1421 |
-
-
- | 389 |
- HB_306_AD |
- AD |
- NA |
- 5480_VC_A_0437 |
-
-
- | 390 |
- HB_307_AD |
- AD |
- NA |
- 5482_VC_A_0028 |
-
-
- | 391 |
- HB_308_AD |
- AD |
- NA |
- 5483_VC_A_0941 |
-
-
- | 392 |
- HB_309_AD |
- AD |
- NA |
- 5487_CR_A_0441 |
-
-
- | 393 |
- HB_310_AD |
- AD |
- NA |
- 5488_CR_A_0194 |
-
-
- | 394 |
- HB_312_AD |
- AD |
- NA |
- 5500_VC_A_0198 |
-
-
- | 395 |
- HB_313_AD |
- AD |
- NA |
- 5502_PF_A_2684 |
-
-
- | 396 |
- HB_315_AD |
- AD |
- NA |
- 5513_PF_A_2687 |
-
-
- | 397 |
- HB_316_AD |
- AD |
- NA |
- 5516_PF_A_2690 |
-
-
- | 398 |
- HB_317_AD |
- AD |
- NA |
- 5517_PF_A_2693 |
-
-
- | 399 |
- HB_318_AD |
- AD |
- NA |
- 5518_CR_A_0030 |
-
-
- | 400 |
- HB_319_AD |
- AD |
- NA |
- 5519_CR_A_2695 |
-
-
- | 401 |
- HB_320_AD |
- AD |
- NA |
- 5520_PF_A_2699 |
-
-
- | 402 |
- HB_322_AD |
- AD |
- NA |
- 5527_VC_A_0945 |
-
-
- | 403 |
- HB_325_AD |
- AD |
- NA |
- 5532_PF_A_2702 |
-
-
- | 404 |
- HB_328_AD |
- AD |
- NA |
- 5541_PF_A_2705 |
-
-
- | 405 |
- HB_330_AD |
- AD |
- NA |
- 5544_VC_A_0201 |
-
-
- | 406 |
- HB_334_AD |
- AD |
- NA |
- 5554_VC_A_0452 |
-
-
- | 407 |
- HB_335_AD |
- AD |
- NA |
- 5557_VC_A_0950 |
-
-
- | 408 |
- HB_337_AD |
- AD |
- NA |
- 5560_VC_A_0204 |
-
-
- | 409 |
- HB_342_AD |
- AD |
- NA |
- 5571_PF_A_1430 |
-
-
- | 410 |
- HB_345_AD |
- AD |
- NA |
- 5583_PF_A_2708 |
-
-
- | 411 |
- HB_347_AD |
- AD |
- NA |
- 5589_PF_A_2714 |
-
-
- | 412 |
- HB_349_AD |
- AD |
- NA |
- 5592_PF_A_2717 |
-
-
- | 413 |
- HB_352_AD |
- AD |
- NA |
- 5604_VC_A_0037 |
-
-
- | 414 |
- HB_353_AD |
- AD |
- NA |
- 5607_PF_A_2723 |
-
-
- | 415 |
- HB_356_AD |
- AD |
- NA |
- 5615_VC_A_0041 |
-
-
- | 416 |
- HB_357_AD |
- AD |
- NA |
- 5616_CR_A_0127 |
-
-
- | 417 |
- HB_358_AD |
- AD |
- NA |
- 5617_CR_A_0456 |
-
-
- | 418 |
- HB_359_AD |
- AD |
- NA |
- 5618_CR_A_0044 |
-
-
- | 419 |
- HB_362_AD |
- AD |
- NA |
- 5625_CR_A_2495 |
-
-
- | 420 |
- HB_363_AD |
- AD |
- NA |
- 5626_CR_A_2498 |
-
-
- | 421 |
- HB_364_AD |
- AD |
- NA |
- 5629_CR_A_0390 |
-
-
- | 422 |
- HB_369_AD |
- AD |
- NA |
- 5643_VC_A_1143 |
-
-
- | 423 |
- HB_373_AD |
- AD |
- NA |
- 5654_VC_A_0047 |
-
-
- | 424 |
- HB_375_AD |
- AD |
- NA |
- 5660_CR_A_0462 |
-
-
- | 425 |
- HB_376_AD |
- AD |
- NA |
- 5661_VC_A_0464 |
-
-
- | 426 |
- HB_377_AD |
- AD |
- NA |
- 5667_VC_A_2509 |
-
-
- | 427 |
- HB_378_AD |
- AD |
- NA |
- 5668_VC_A_1438 |
-
-
- | 428 |
- HB_383_AD |
- AD |
- NA |
- 5686_CR_A_2728 |
-
-
- | 429 |
- HB_386_AD |
- AD |
- NA |
- 5695_VC_A_0953 |
-
-
- | 430 |
- HB_389_AD |
- AD |
- NA |
- 5700_VC_A_2514 |
-
-
- | 431 |
- HB_391_AD |
- AD |
- NA |
- 5705_CR_A_0474 |
-
-
- | 432 |
- HB_392_AD |
- AD |
- NA |
- 5706_VC_A_0476 |
-
-
- | 433 |
- HB_394_AD |
- AD |
- NA |
- 5713_VC_A_0479 |
-
-
- | 434 |
- HB_397_AD |
- AD |
- NA |
- 5721_CR_A_0210 |
-
-
- | 435 |
- HB_404_AD |
- AD |
- NA |
- 5735_CR_A_0489 |
-
-
- | 436 |
- HB_406_AD |
- AD |
- NA |
- 5744_CR_A_0960 |
-
-
- | 437 |
- HB_409_AD |
- AD |
- NA |
- 5749_CR_A_0159 |
-
-
- | 438 |
- HB_410_AD |
- AD |
- NA |
- 5751_CR_A_2518 |
-
-
- | 439 |
- HB_411_AD |
- AD |
- NA |
- 5755_CR_A_2731 |
-
-
- | 440 |
- HB_413_AD |
- AD |
- NA |
- 5766_VC_A_0214 |
-
-
- | 441 |
- HB_419_AD |
- AD |
- NA |
- 5790_VC_A_0217 |
-
-
- | 442 |
- HB_420_AD |
- AD |
- NA |
- 5796_CR_A_0964 |
-
-
- | 443 |
- HB_428_AD |
- AD |
- NA |
- 5811_CR_A_2524 |
-
-
- | 444 |
- HB_429_AD |
- AD |
- NA |
- 5819_CR_A_2527 |
-
-
- | 445 |
- HB_430_AD |
- AD |
- NA |
- 5822_CR_A_2530 |
-
-
- | 446 |
- HB_434_AD |
- AD |
- NA |
- 5828_CR_A_2533 |
-
-
- | 447 |
- HB_435_AD |
- AD |
- NA |
- 5831_CR_A_0222 |
-
-
- | 448 |
- HB_437_AD |
- AD |
- NA |
- 5839_CR_A_2539 |
-
-
- | 449 |
- HB_438_AD |
- AD |
- NA |
- 5843_CR_A_0227 |
-
-
- | 450 |
- HB_439_AD |
- AD |
- NA |
- 5845_CR_A_0230 |
-
-
- | 451 |
- HB_441_AD |
- AD |
- NA |
- 5849_CR_A_0233 |
-
-
- | 452 |
- HB_442_AD |
- AD |
- NA |
- 5850_CR_A_0495 |
-
-
- | 453 |
- HB_445_AD |
- AD |
- NA |
- 5858_CR_A_0969 |
-
-
- | 454 |
- HB_448_AD |
- AD |
- NA |
- 5864_CR_A_0974 |
-
-
- | 455 |
- HB_451_AD |
- AD |
- NA |
- 5871_CR_A_2542 |
-
-
- | 456 |
- HB_454_AD |
- AD |
- NA |
- 5879_CR_A_2545 |
-
-
- | 457 |
- HB_455_AD |
- AD |
- NA |
- 5887_CR_A_0976_Bis |
-
-
- | 458 |
- HB_459_AD |
- AD |
- NA |
- 5898_CR_A_2548 |
-
-
- | 459 |
- HB_460_AD |
- AD |
- NA |
- 5900_VC_A_0237 |
-
-
- | 460 |
- HB_461_AD |
- AD |
- NA |
- 5901_CR_A_0239 |
-
-
- | 461 |
- HB_469_AD |
- AD |
- NA |
- 5914_CR_A_2554 |
-
-
- | 462 |
- HB_471_AD |
- AD |
- NA |
- 5922_VC_A_0246 |
-
-
- | 463 |
- HB_473_AD |
- AD |
- NA |
- 5927_CR_A_2560 |
-
-
- | 464 |
- HB_474_AD |
- AD |
- NA |
- 5933_VC_A_1071 |
-
-
- | 465 |
- HB_477_AD |
- AD |
- NA |
- 5939_CR_A_1151 |
-
-
- | 466 |
- HB_479_AD |
- AD |
- NA |
- 5945_VC_A_0983 |
-
-
- | 467 |
- HB_484_AD |
- AD |
- NA |
- 5956_CR_A_0123 |
-
-
- | 468 |
- HB_489_AD |
- AD |
- NA |
- 5968_VC_A_1075 |
-
-
- | 469 |
- HB_491_AD |
- AD |
- NA |
- 5971_CR_A_0119 |
-
-
- | 470 |
- HB_492_AD |
- AD |
- NA |
- 5972_VC_A_0251 |
-
-
- | 471 |
- HB_494_AD |
- AD |
- NA |
- 5979_CR_A_0115 |
-
-
- | 472 |
- HB_498_AD |
- AD |
- NA |
- 5988_VC_A_0503 |
-
-
- | 473 |
- HB_502_AD |
- AD |
- NA |
- 5994_PF_A_1605 |
-
-
- | 474 |
- HB_503_AD |
- AD |
- NA |
- 5995_CR_A_2563 |
-
-
- | 475 |
- HB_510_AD |
- AD |
- NA |
- 6017_CR_A_0048 |
-
-
- | 476 |
- HB_514_AD |
- AD |
- NA |
- 6025_VC_A_0506 |
-
-
- | 477 |
- HB_517_AD |
- AD |
- NA |
- 6031_VC_A_0258 |
-
-
- | 478 |
- HB_520_AD |
- AD |
- NA |
- 6035_VC_A_1621 |
-
-
- | 479 |
- HB_523_AD |
- AD |
- NA |
- 6038_VC_A_0261 |
-
-
- | 480 |
- HB_524_AD |
- AD |
- NA |
- 6042_VC_A_1156 |
-
-
- | 481 |
- HB_525_AD |
- AD |
- NA |
- 6044_VC_A_0264 |
-
-
- | 482 |
- HB_531_AD |
- AD |
- NA |
- 6056_CR_A_0999 |
-
-
- | 483 |
- HB_533_AD |
- AD |
- NA |
- 6061_PF_A_1650 |
-
-
- | 484 |
- HB_534_AD |
- AD |
- NA |
- 6066_VC_A_0270 |
-
-
- | 485 |
- HB_535_AD |
- AD |
- NA |
- 6067_PF_A_1452 |
-
-
- | 486 |
- HB_536_AD |
- AD |
- NA |
- 6068_VC_A_0273 |
-
-
- | 487 |
- HB_545_AD |
- AD |
- NA |
- 6102_CR_A_1661 |
-
-
- | 488 |
- HB_546_AD |
- AD |
- NA |
- 6107_CR_A_0055 |
-
-
- | 489 |
- HB_550_AD |
- AD |
- NA |
- 6120_VC_A_0058 |
-
-
- | 490 |
- HB_552_AD |
- AD |
- NA |
- 6126_VC_A_1675 |
-
-
- | 491 |
- HB_553_AD |
- AD |
- NA |
- 6129_PF_A_0274 |
-
-
- | 492 |
- HB_554_AD |
- AD |
- NA |
- 6130_VC_A_1678 |
-
-
- | 493 |
- HB_555_AD |
- AD |
- NA |
- 6131_CR_A_0510 |
-
-
- | 494 |
- HB_556_AD |
- AD |
- NA |
- 6132_CR_A_0513 |
-
-
- | 495 |
- HB_558_AD |
- AD |
- NA |
- 6137_VC_A_1681 |
-
-
- | 496 |
- HB_564_AD |
- AD |
- NA |
- 6153_VC_A_1465 |
-
-
- | 497 |
- HB_565_AD |
- AD |
- NA |
- 6154_VC_A_1468 |
-
-
- | 498 |
- HB_566_AD |
- AD |
- NA |
- 6157_VC_A_0062 |
-
-
- | 499 |
- HB_568_AD |
- AD |
- NA |
- 6164_CR_A_1005 |
-
-
- | 500 |
- HB_571_AD |
- AD |
- NA |
- 6171_CR_A_0065 |
-
-
- | 501 |
- HB_573_AD |
- AD |
- NA |
- 6174_VC_A_0068 |
-
-
- | 502 |
- HB_576_AD |
- AD |
- NA |
- 6180_CR_A_0281 |
-
-
- | 503 |
- HB_583_AD |
- AD |
- NA |
- 6194_VC_A_0071 |
-
-
- | 504 |
- HB_585_AD |
- AD |
- NA |
- 6198_VC_A_0073 |
-
-
- | 505 |
- HB_590_AD |
- AD |
- NA |
- 6215_VC_A_0518 |
-
-
- | 506 |
- HB_591_AD |
- AD |
- NA |
- 6216_VC_A_1476 |
-
-
- | 507 |
- HB_592_AD |
- AD |
- NA |
- 6218_CR_A_0522 |
-
-
- | 508 |
- HB_594_AD |
- AD |
- NA |
- 6223_VC_A_0288 |
-
-
- | 509 |
- HB_596_AD |
- AD |
- NA |
- 6226_CR_A_0076 |
-
-
- | 510 |
- HB_597_AD |
- AD |
- NA |
- 6227_VC_A_0080 |
-
-
- | 511 |
- HB_598_AD |
- AD |
- NA |
- 6231_VC_A_1479 |
-
-
- | 512 |
- HB_605_AD |
- AD |
- NA |
- 6261_VC_A_0084 |
-
-
- | 513 |
- HB_608_AD |
- AD |
- NA |
- 6268_CR_A_0525 |
-
-
- | 514 |
- HB_611_AD |
- AD |
- NA |
- 6279_VC_A_0089 |
-
-
- | 515 |
- HB_612_AD |
- AD |
- NA |
- 6280_VC_A_0091 |
-
-
- | 516 |
- HB_613_AD |
- AD |
- NA |
- 6281_CR_A_0528 |
-
-
- | 517 |
- HB_621_AD |
- AD |
- NA |
- 6308_VC_A_1503 |
-
-
- | 518 |
- HB_623_AD |
- AD |
- NA |
- 6311_CR_A_0531 |
-
-
- | 519 |
- HB_624_AD |
- AD |
- NA |
- 6312_CR_A_0534 |
-
-
- | 520 |
- HB_630_AD |
- AD |
- NA |
- 6324_PF_A_1514 |
-
-
- | 521 |
- HB_633_AD |
- AD |
- NA |
- 6332_VC_A_1518 |
-
-
- | 522 |
- HB_634_AD |
- AD |
- NA |
- 6335_VC_A_0536 |
-
-
- | 523 |
- HB_635_AD |
- AD |
- NA |
- 6336_CR_A_0290 |
-
-
- | 524 |
- HB_636_AD |
- AD |
- NA |
- 6338_VC_A_0539 |
-
-
- | 525 |
- HB_642_AD |
- AD |
- NA |
- 6358_VC_A_0545 |
-
-
- | 526 |
- HB_652_AD |
- AD |
- NA |
- 6387_VC_A_0093 |
-
-
- | 527 |
- HB_657_AD |
- AD |
- NA |
- 6394_VC_A_0551 |
-
-
- | 528 |
- HB_664_AD |
- AD |
- NA |
- 6416_VC_A_1095 |
-
-
- | 529 |
- HB_666_AD |
- AD |
- NA |
- 6422_CR_A_0555 |
-
-
- | 530 |
- HB_669_AD |
- AD |
- NA |
- 6431_VC_A_0294 |
-
-
- | 531 |
- HB_674_AD |
- AD |
- NA |
- 6449_VC_A_1183 |
-
-
- | 532 |
- HB_680_AD |
- AD |
- NA |
- 6458_CR_A_2570 |
-
-
- | 533 |
- HB_685_AD |
- AD |
- NA |
- 6481_VC_A_0560 |
-
-
- | 534 |
- HB_690_AD |
- AD |
- NA |
- 6489_CR_A_0100 |
-
-
- | 535 |
- HB_696_AD |
- AD |
- NA |
- 6511_VC_A_1119 |
-
-
- | 536 |
- HB_698_AD |
- AD |
- NA |
- 6515_CR_A_0564 |
-
-
- | 537 |
- HB_699_AD |
- AD |
- NA |
- 6518_VC_A_0103 |
-
-
- | 538 |
- HB_703_AD |
- AD |
- NA |
- 6523_VC_A_0107 |
-
-
- | 539 |
- HB_704_AD |
- AD |
- NA |
- 6530_VC_A_0112 |
-
-
- | 540 |
- HB_706_AD |
- AD |
- NA |
- 6534_VC_A_0306 |
-
-
- | 541 |
- HB_712_AD |
- AD |
- NA |
- 6546_PF_A_1194 |
-
-
- | 542 |
- HB_713_AD |
- AD |
- NA |
- 6548_PF_A_1541 |
-
-
- | 543 |
- HB_715_AD |
- AD |
- NA |
- 6550_VC_A_1201 |
-
-
- | 544 |
- HB_718_AD |
- AD |
- NA |
- 6554_PF_A_1203 |
-
-
- | 545 |
- HB_720_AD |
- AD |
- NA |
- 6559_PF_A_2287 |
-
-
- | 546 |
- HB_722_AD |
- AD |
- NA |
- 6561_CR_A_2582 |
-
-
- | 547 |
- HB_723_AD |
- AD |
- NA |
- 6562_PF_A_2290 |
-
-
- | 548 |
- HB_724_AD |
- AD |
- NA |
- 6564_CR_A_2585 |
-
-
- | 549 |
- HB_727_AD |
- AD |
- NA |
- 6575_CR_A_2298 |
-
-
- | 550 |
- HB_728_AD |
- AD |
- NA |
- 6577_PF_A_2299 |
-
-
- | 551 |
- HB_729_AD |
- AD |
- NA |
- 6578_PF_A_2302 |
-
-
- | 552 |
- HB_731_AD |
- AD |
- NA |
- 6582_VC_A_1207 |
-
-
- | 553 |
- HB_733_AD |
- AD |
- NA |
- 6585_VC_A_1210 |
-
-
- | 554 |
- HB_736_AD |
- AD |
- NA |
- 6590_PF_A_1215 |
-
-
- | 555 |
- HB_743_AD |
- AD |
- NA |
- 6603_PF_A_1448 |
-
-
- | 556 |
- HB_745_AD |
- AD |
- NA |
- 6610_PF_A_1227 |
-
-
- | 557 |
- HB_746_AD |
- AD |
- NA |
- 6612_PF_A_2308 |
-
-
- | 558 |
- HB_749_AD |
- AD |
- NA |
- 6617_VC_A_2587 |
-
-
- | 559 |
- HB_751_AD |
- AD |
- NA |
- 6629_VC_A_2330 |
-
-
- | 560 |
- HB_752_AD |
- AD |
- NA |
- 6630_VC_A_2590 |
-
-
- | 561 |
- HB_753_AD |
- AD |
- NA |
- 6632_PF_A_2332 |
-
-
- | 562 |
- HB_754_AD |
- AD |
- NA |
- 6637_VC_A_2596 |
-
-
- | 563 |
- HB_755_AD |
- AD |
- NA |
- 6638_VC_A_2599 |
-
-
- | 564 |
- HB_756_AD |
- AD |
- NA |
- 6639_VC_A_2336 |
-
-
- | 565 |
- HB_757_AD |
- AD |
- NA |
- 6641_PF_A_2338 |
-
-
- | 566 |
- HB_763_AD |
- AD |
- NA |
- 6654_VC_A_1237 |
-
-
- | 567 |
- HB_773_AD |
- AD |
- NA |
- 6681_VC_A_1252 |
-
-
- | 568 |
- HB_775_AD |
- AD |
- NA |
- 6693_VC_A_2348 |
-
-
- | 569 |
- HB_776_AD |
- AD |
- NA |
- 6694_VC_A_2351 |
-
-
- | 570 |
- HB_777_AD |
- AD |
- NA |
- 6695_PF_A_2353 |
-
-
- | 571 |
- HB_779_AD |
- AD |
- NA |
- 6699_PF_A_2359 |
-
-
- | 572 |
- HB_781_AD |
- AD |
- NA |
- 6708_VC_A_2366 |
-
-
- | 573 |
- HB_782_AD |
- AD |
- NA |
- 6776_PF_A_2607 |
-
-
- | 574 |
- HB_783_AD |
- AD |
- NA |
- 6778_PF_A_2368 |
-
-
- | 575 |
- HB_784_AD |
- AD |
- NA |
- 6779_PF_A_2371 |
-
-
- | 576 |
- HB_785_AD |
- AD |
- NA |
- 6780_PF_A_2374 |
-
-
- | 577 |
- HB_786_AD |
- AD |
- NA |
- 6782_PF_A_2377 |
-
-
- | 578 |
- HB_787_AD |
- AD |
- NA |
- 6784_PF_A_2380 |
-
-
- | 579 |
- HB_788_AD |
- AD |
- NA |
- 6785_CR_A_2385 |
-
-
- | 580 |
- HB_789_AD |
- AD |
- NA |
- 6787_CR_A_2388 |
-
-
- | 581 |
- HB_791_AD |
- AD |
- NA |
- 6790_PF_A_2392 |
-
-
- | 582 |
- HB_792_AD |
- AD |
- NA |
- 6791_PF_A_2395 |
-
-
- | 583 |
- HB_793_AD |
- AD |
- NA |
- 6793_PF_A_2398 |
-
-
- | 584 |
- HB_794_AD |
- AD |
- NA |
- 6794_PF_A_2401 |
-
-
- | 585 |
- HB_795_AD |
- AD |
- NA |
- 6797_PF_A_2404 |
-
-
- | 586 |
- HB_796_AD |
- AD |
- NA |
- 6798_PF_A_2407 |
-
-
- | 587 |
- HB_797_AD |
- AD |
- NA |
- 6799_VC_A_2411 |
-
-
- | 588 |
- HB_798_AD |
- AD |
- NA |
- 6801_VC_A_2414 |
-
-
- | 589 |
- HB_799_AD |
- AD |
- NA |
- 6803_VC_A_2417 |
-
-
- | 590 |
- HB_801_AD |
- AD |
- NA |
- 6809_PF_A_2422 |
-
-
- | 591 |
- HB_803_AD |
- AD |
- NA |
- 6818_CR_A_2430 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/HBTRC_MLC_HD_0611/experiment-design.rtf b/general/datasets/HBTRC_MLC_HD_0611/experiment-design.rtf
deleted file mode 100644
index 3b0c224..0000000
--- a/general/datasets/HBTRC_MLC_HD_0611/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
diff --git a/general/datasets/HBTRC_MLC_HD_0611/notes.rtf b/general/datasets/HBTRC_MLC_HD_0611/notes.rtf
deleted file mode 100644
index ff90e34..0000000
--- a/general/datasets/HBTRC_MLC_HD_0611/notes.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Species: Human
-Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
-Disease: Neurological Disease
-Investigator: Francine Benes/ Eric Schadt
-Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
-Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC_MLC_HD_0611/summary.rtf b/general/datasets/HBTRC_MLC_HD_0611/summary.rtf
deleted file mode 100644
index 5cde3bf..0000000
--- a/general/datasets/HBTRC_MLC_HD_0611/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC_MLC_N_0611/acknowledgment.rtf b/general/datasets/HBTRC_MLC_N_0611/acknowledgment.rtf
deleted file mode 100644
index 208cb6e..0000000
--- a/general/datasets/HBTRC_MLC_N_0611/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC_MLC_N_0611/cases.rtf b/general/datasets/HBTRC_MLC_N_0611/cases.rtf
deleted file mode 100644
index e64114d..0000000
--- a/general/datasets/HBTRC_MLC_N_0611/cases.rtf
+++ /dev/null
@@ -1,4156 +0,0 @@
-
-
-
-
-
-
-
- | Series |
- Cerebellum in GN |
- Condition |
- Gender |
- BioSample Name |
-
-
- | 1 |
- HB_029_N |
- N |
- NA |
- 3405_VC_N_0859 |
-
-
- | 2 |
- HB_058_N |
- N |
- NA |
- 4021_VC_N_0854 |
-
-
- | 3 |
- HB_064_N |
- N |
- NA |
- 4338_VC_N_0861 |
-
-
- | 4 |
- HB_086_N |
- N |
- NA |
- 4729_PF_N_0756 |
-
-
- | 5 |
- HB_091_N |
- N |
- NA |
- 4741_VC_N_0864 |
-
-
- | 6 |
- HB_092_N |
- N |
- NA |
- 4744_VC_N_0865 |
-
-
- | 7 |
- HB_102_N |
- N |
- NA |
- 4810_VC_N_0869 |
-
-
- | 8 |
- HB_119_N |
- N |
- NA |
- 4872_VC_N_0878 |
-
-
- | 9 |
- HB_147_N |
- N |
- NA |
- 5021_VC_N_0852 |
-
-
- | 10 |
- HB_161_N |
- N |
- NA |
- 5077_VC_N_0851 |
-
-
- | 11 |
- HB_162_N |
- N |
- NA |
- 5081_VC_N_1021 |
-
-
- | 12 |
- HB_166_N |
- N |
- NA |
- 5095_VC_N_1024 |
-
-
- | 13 |
- HB_183_N |
- N |
- NA |
- 5162_VC_N_0850 |
-
-
- | 14 |
- HB_206_N |
- N |
- NA |
- 5245_VC_N_0849 |
-
-
- | 15 |
- HB_215_N |
- N |
- NA |
- 5270_VC_N_0848 |
-
-
- | 16 |
- HB_218_N |
- N |
- NA |
- 5276_CR_N_0912 |
-
-
- | 17 |
- HB_223_N |
- N |
- NA |
- 5287_VC_N_0916 |
-
-
- | 18 |
- HB_226_N |
- N |
- NA |
- 5294_VC_N_0919 |
-
-
- | 19 |
- HB_241_N |
- N |
- NA |
- 5326_CR_N_0652 |
-
-
- | 20 |
- HB_243_N |
- N |
- NA |
- 5333_VC_N_1262 |
-
-
- | 21 |
- HB_247_N |
- N |
- NA |
- 5341_VC_N_0923 |
-
-
- | 22 |
- HB_257_N |
- N |
- NA |
- 5368_PF_N_1032 |
-
-
- | 23 |
- HB_264_N |
- N |
- NA |
- 5384_VC_N_0924 |
-
-
- | 24 |
- HB_295_N |
- N |
- NA |
- 5452_VC_N_1268 |
-
-
- | 25 |
- HB_300_N |
- N |
- NA |
- 5463_VC_N_0845 |
-
-
- | 26 |
- HB_311_N |
- N |
- NA |
- 5489_CR_N_0942 |
-
-
- | 27 |
- HB_324_N |
- N |
- NA |
- 5531_VC_N_0844 |
-
-
- | 28 |
- HB_332_N |
- N |
- NA |
- 5547_VC_N_0843 |
-
-
- | 29 |
- HB_340_N |
- N |
- NA |
- 5568_VC_N_0842 |
-
-
- | 30 |
- HB_360_N |
- N |
- NA |
- 5619_CR_N_0645 |
-
-
- | 31 |
- HB_365_N |
- N |
- NA |
- 5632_VC_N_0838 |
-
-
- | 32 |
- HB_367_N |
- N |
- NA |
- 5637_VC_N_0837 |
-
-
- | 33 |
- HB_382_N |
- N |
- NA |
- 5684_PF_N_1270 |
-
-
- | 34 |
- HB_396_N |
- N |
- NA |
- 5718_VC_N_0956 |
-
-
- | 35 |
- HB_398_N |
- N |
- NA |
- 5722_VC_N_1044 |
-
-
- | 36 |
- HB_400_N |
- N |
- NA |
- 5726_VC_N_0834_Bis |
-
-
- | 37 |
- HB_403_N |
- N |
- NA |
- 5734_VC_N_0833 |
-
-
- | 38 |
- HB_414_N |
- N |
- NA |
- 5772_VC_N_0832_Bis |
-
-
- | 39 |
- HB_416_N |
- N |
- NA |
- 5778_CR_N_0962 |
-
-
- | 40 |
- HB_418_N |
- N |
- NA |
- 5789_PF_N_1273 |
-
-
- | 41 |
- HB_421_N |
- N |
- NA |
- 5799_VC_N_1058 |
-
-
- | 42 |
- HB_423_N |
- N |
- NA |
- 5803_VC_N_0966 |
-
-
- | 43 |
- HB_426_N |
- N |
- NA |
- 5806_PF_N_1064 |
-
-
- | 44 |
- HB_427_N |
- N |
- NA |
- 5810_CR_N_0636 |
-
-
- | 45 |
- HB_431_N |
- N |
- NA |
- 5823_VC_N_0829 |
-
-
- | 46 |
- HB_432_N |
- N |
- NA |
- 5826_VC_N_0828 |
-
-
- | 47 |
- HB_433_N |
- N |
- NA |
- 5827_VC_N_0827 |
-
-
- | 48 |
- HB_436_N |
- N |
- NA |
- 5832_PF_N_1145 |
-
-
- | 49 |
- HB_443_N |
- N |
- NA |
- 5852_VC_N_0826 |
-
-
- | 50 |
- HB_446_N |
- N |
- NA |
- 5859_VC_N_0825 |
-
-
- | 51 |
- HB_449_N |
- N |
- NA |
- 5866_VC_N_0824 |
-
-
- | 52 |
- HB_450_N |
- N |
- NA |
- 5867_VC_N_1277 |
-
-
- | 53 |
- HB_453_N |
- N |
- NA |
- 5876_VC_N_0823 |
-
-
- | 54 |
- HB_462_N |
- N |
- NA |
- 5903_VC_N_0822 |
-
-
- | 55 |
- HB_464_N |
- N |
- NA |
- 5905_VC_N_0820 |
-
-
- | 56 |
- HB_468_N |
- N |
- NA |
- 5912_VC_N_1286 |
-
-
- | 57 |
- HB_472_N |
- N |
- NA |
- 5925_VC_N_1289 |
-
-
- | 58 |
- HB_475_N |
- N |
- NA |
- 5936_VC_N_0979 |
-
-
- | 59 |
- HB_476_N |
- N |
- NA |
- 5938_VC_N_0819 |
-
-
- | 60 |
- HB_480_N |
- N |
- NA |
- 5946_VC_N_0985 |
-
-
- | 61 |
- HB_485_N |
- N |
- NA |
- 5959_VC_N_0818 |
-
-
- | 62 |
- HB_486_N |
- N |
- NA |
- 5963_VC_N_0987 |
-
-
- | 63 |
- HB_495_N |
- N |
- NA |
- 5980_VC_N_0989 |
-
-
- | 64 |
- HB_497_N |
- N |
- NA |
- 5985_VC_N_0990 |
-
-
- | 65 |
- HB_500_N |
- N |
- NA |
- 5990_VC_N_0817 |
-
-
- | 66 |
- HB_501_N |
- N |
- NA |
- 5991_VC_N_0816 |
-
-
- | 67 |
- HB_504_N |
- N |
- NA |
- 5996_VC_N_0815 |
-
-
- | 68 |
- HB_505_N |
- N |
- NA |
- 5998_VC_N_0814 |
-
-
- | 69 |
- HB_507_N |
- N |
- NA |
- 6006_VC_N_0813 |
-
-
- | 70 |
- HB_508_N |
- N |
- NA |
- 6007_CR_N_0618 |
-
-
- | 71 |
- HB_509_N |
- N |
- NA |
- 6008_PF_N_1081 |
-
-
- | 72 |
- HB_512_N |
- N |
- NA |
- 6023_PF_N_1155 |
-
-
- | 73 |
- HB_516_N |
- N |
- NA |
- 6030_VC_N_0810 |
-
-
- | 74 |
- HB_519_N |
- N |
- NA |
- 6034_VC_N_0809 |
-
-
- | 75 |
- HB_532_N |
- N |
- NA |
- 6060_VC_N_1292 |
-
-
- | 76 |
- HB_541_N |
- N |
- NA |
- 6092_VC_N_1001 |
-
-
- | 77 |
- HB_542_N |
- N |
- NA |
- 6096_VC_N_0807 |
-
-
- | 78 |
- HB_544_N |
- N |
- NA |
- 6101_CR_N_1161 |
-
-
- | 79 |
- HB_547_N |
- N |
- NA |
- 6110_VC_N_1295 |
-
-
- | 80 |
- HB_551_N |
- N |
- NA |
- 6124_VC_N_0806 |
-
-
- | 81 |
- HB_557_N |
- N |
- NA |
- 6134_PF_N_1297 |
-
-
- | 82 |
- HB_560_N |
- N |
- NA |
- 6142_VC_N_0805 |
-
-
- | 83 |
- HB_569_N |
- N |
- NA |
- 6166_VC_N_0804 |
-
-
- | 84 |
- HB_570_N |
- N |
- NA |
- 6170_VC_N_0803 |
-
-
- | 85 |
- HB_572_N |
- N |
- NA |
- 6172_VC_N_1008 |
-
-
- | 86 |
- HB_577_N |
- N |
- NA |
- 6182_VC_N_1166 |
-
-
- | 87 |
- HB_579_N |
- N |
- NA |
- 6187_CR_N_0607 |
-
-
- | 88 |
- HB_581_N |
- N |
- NA |
- 6191_VC_N_1010 |
-
-
- | 89 |
- HB_584_N |
- N |
- NA |
- 6196_CR_N_0605 |
-
-
- | 90 |
- HB_586_N |
- N |
- NA |
- 6200_VC_N_0799 |
-
-
- | 91 |
- HB_587_N |
- N |
- NA |
- 6206_PF_N_1176 |
-
-
- | 92 |
- HB_589_N |
- N |
- NA |
- 6213_VC_N_0798 |
-
-
- | 93 |
- HB_601_N |
- N |
- NA |
- 6241_VC_N_0796 |
-
-
- | 94 |
- HB_604_N |
- N |
- NA |
- 6260_VC_N_0794 |
-
-
- | 95 |
- HB_609_N |
- N |
- NA |
- 6270_VC_N_0793 |
-
-
- | 96 |
- HB_618_N |
- N |
- NA |
- 6289_VC_N_0791 |
-
-
- | 97 |
- HB_622_N |
- N |
- NA |
- 6310_VC_N_0790 |
-
-
- | 98 |
- HB_625_N |
- N |
- NA |
- 6314_VC_N_0789 |
-
-
- | 99 |
- HB_637_N |
- N |
- NA |
- 6340_VC_N_0786 |
-
-
- | 100 |
- HB_638_N |
- N |
- NA |
- 6341_VC_N_0785 |
-
-
- | 101 |
- HB_640_N |
- N |
- NA |
- 6347_VC_N_0784 |
-
-
- | 102 |
- HB_641_N |
- N |
- NA |
- 6356_VC_N_0783 |
-
-
- | 103 |
- HB_643_N |
- N |
- NA |
- 6363_VC_N_0781 |
-
-
- | 104 |
- HB_644_N |
- N |
- NA |
- 6366_VC_N_0780 |
-
-
- | 105 |
- HB_645_N |
- N |
- NA |
- 6374_VC_N_0779 |
-
-
- | 106 |
- HB_650_N |
- N |
- NA |
- 6384_VC_N_0777 |
-
-
- | 107 |
- HB_651_N |
- N |
- NA |
- 6386_VC_N_0776 |
-
-
- | 108 |
- HB_653_N |
- N |
- NA |
- 6388_VC_N_0775 |
-
-
- | 109 |
- HB_659_N |
- N |
- NA |
- 6406_VC_N_1180 |
-
-
- | 110 |
- HB_662_N |
- N |
- NA |
- 6411_VC_N_0771 |
-
-
- | 111 |
- HB_663_N |
- N |
- NA |
- 6415_VC_N_0770 |
-
-
- | 112 |
- HB_670_N |
- N |
- NA |
- 6436_VC_N_0769 |
-
-
- | 113 |
- HB_687_N |
- N |
- NA |
- 6484_VC_N_0765 |
-
-
- | 114 |
- HB_689_N |
- N |
- NA |
- 6486_VC_N_0764 |
-
-
- | 115 |
- HB_694_N |
- N |
- NA |
- 6500_VC_N_0763 |
-
-
- | 116 |
- HB_697_N |
- N |
- NA |
- 6512_VC_N_0762 |
-
-
- | 117 |
- HB_700_N |
- N |
- NA |
- 6520_VC_N_0761 |
-
-
- | 118 |
- HB_711_N |
- N |
- NA |
- 6543_PF_N_1191 |
-
-
- | 119 |
- HB_714_N |
- N |
- NA |
- 6549_VC_N_1198 |
-
-
- | 120 |
- HB_717_N |
- N |
- NA |
- 6553_PF_N_2284 |
-
-
- | 121 |
- HB_721_N |
- N |
- NA |
- 6560_VC_N_2578 |
-
-
- | 122 |
- HB_726_N |
- N |
- NA |
- 6573_PF_N_2293 |
-
-
- | 123 |
- HB_730_N |
- N |
- NA |
- 6580_VC_N_2306 |
-
-
- | 124 |
- HB_735_N |
- N |
- NA |
- 6588_VC_N_1213 |
-
-
- | 125 |
- HB_737_N |
- N |
- NA |
- 6593_VC_N_1219 |
-
-
- | 126 |
- HB_738_N |
- N |
- NA |
- 6594_VC_N_1222 |
-
-
- | 127 |
- HB_759_N |
- N |
- NA |
- 6645_VC_N_1231 |
-
-
- | 128 |
- HB_764_N |
- N |
- NA |
- 6655_VC_N_1240 |
-
-
- | 129 |
- HB_765_N |
- N |
- NA |
- 6656_VC_N_1243 |
-
-
- | 130 |
- HB_767_N |
- N |
- NA |
- 6661_PF_N_2341 |
-
-
- | 131 |
- HB_770_N |
- N |
- NA |
- 6669_VC_N_1246 |
-
-
- | 132 |
- HB_772_N |
- N |
- NA |
- 6676_PF_N_1248 |
-
-
- | 133 |
- HB_001_HD |
- HD |
- F |
- 2028_CR_H_2282 |
-
-
- | 134 |
- HB_003_HD |
- HD |
- F |
- 2685_PF_H_2212 |
-
-
- | 135 |
- HB_004_HD |
- HD |
- M |
- 2706_CR_H_2432 |
-
-
- | 136 |
- HB_006_HD |
- HD |
- M |
- 2737_VC_H_2194 |
-
-
- | 137 |
- HB_007_HD |
- HD |
- NA |
- 2769_VC_H_2193 |
-
-
- | 138 |
- HB_008_HD |
- HD |
- F |
- 2790_CR_H_1890 |
-
-
- | 139 |
- HB_009_HD |
- HD |
- NA |
- 2879_VC_H_2192 |
-
-
- | 140 |
- HB_010_HD |
- HD |
- M |
- 2960_VC_H_2002 |
-
-
- | 141 |
- HB_011_HD |
- HD |
- F |
- 3053_VC_H_2001 |
-
-
- | 142 |
- HB_012_HD |
- HD |
- F |
- 3128_VC_H_1999 |
-
-
- | 143 |
- HB_014_HD |
- HD |
- F |
- 3149_PF_H_2110 |
-
-
- | 144 |
- HB_015_HD |
- HD |
- F |
- 3150_VC_H_1996 |
-
-
- | 145 |
- HB_016_HD |
- HD |
- F |
- 3177_VC_H_2191 |
-
-
- | 146 |
- HB_017_HD |
- HD |
- NA |
- 3195_VC_H_2190 |
-
-
- | 147 |
- HB_018_HD |
- HD |
- M |
- 3200_VC_H_2189 |
-
-
- | 148 |
- HB_019_HD |
- HD |
- M |
- 3209_VC_H_2188 |
-
-
- | 149 |
- HB_020_HD |
- HD |
- M |
- 3224_VC_H_1994 |
-
-
- | 150 |
- HB_022_HD |
- HD |
- F |
- 3242_PF_H_2105 |
-
-
- | 151 |
- HB_024_HD |
- HD |
- NA |
- 3272_VC_H_2186 |
-
-
- | 152 |
- HB_027_HD |
- HD |
- M |
- 3356_VC_H_2439 |
-
-
- | 153 |
- HB_028_HD |
- HD |
- F |
- 3394_PF_H_2104 |
-
-
- | 154 |
- HB_031_HD |
- HD |
- M |
- 3430_VC_H_1990 |
-
-
- | 155 |
- HB_032_HD |
- HD |
- NA |
- 3444_PF_H_2208 |
-
-
- | 156 |
- HB_034_HD |
- HD |
- F |
- 3482_VC_H_1987 |
-
-
- | 157 |
- HB_036_HD |
- HD |
- M |
- 3576_VC_H_1984 |
-
-
- | 158 |
- HB_037_HD |
- HD |
- F |
- 3579_VC_H_1983 |
-
-
- | 159 |
- HB_038_HD |
- HD |
- F |
- 3584_VC_H_2183 |
-
-
- | 160 |
- HB_039_HD |
- HD |
- NA |
- 3635_VC_H_2182 |
-
-
- | 161 |
- HB_041_HD |
- HD |
- F |
- 3695_CR_H_2267 |
-
-
- | 162 |
- HB_042_HD |
- HD |
- M |
- 3697_VC_H_1982 |
-
-
- | 163 |
- HB_043_HD |
- HD |
- NA |
- 3703_VC_H_2180 |
-
-
- | 164 |
- HB_044_HD |
- HD |
- NA |
- 3723_VC_H_2179 |
-
-
- | 165 |
- HB_046_HD |
- HD |
- F |
- 3735_VC_H_1981 |
-
-
- | 166 |
- HB_050_HD |
- HD |
- M |
- 3820_PF_H_2207 |
-
-
- | 167 |
- HB_051_HD |
- HD |
- F |
- 3849_CR_H_2262 |
-
-
- | 168 |
- HB_054_HD |
- HD |
- M |
- 3884_VC_H_2175 |
-
-
- | 169 |
- HB_056_HD |
- HD |
- NA |
- 4012_VC_H_2174 |
-
-
- | 170 |
- HB_057_HD |
- HD |
- NA |
- 4013_VC_H_2173 |
-
-
- | 171 |
- HB_059_HD |
- HD |
- NA |
- 4066_VC_H_2172 |
-
-
- | 172 |
- HB_060_HD |
- HD |
- NA |
- 4094_VC_H_2171 |
-
-
- | 173 |
- HB_061_HD |
- HD |
- F |
- 4116_VC_H_2170 |
-
-
- | 174 |
- HB_062_HD |
- HD |
- NA |
- 4121_VC_H_2169 |
-
-
- | 175 |
- HB_063_HD |
- HD |
- NA |
- 4215_VC_H_2167 |
-
-
- | 176 |
- HB_065_HD |
- HD |
- M |
- 4340_PF_H_2091 |
-
-
- | 177 |
- HB_066_HD |
- HD |
- F |
- 4344_VC_H_1977 |
-
-
- | 178 |
- HB_067_HD |
- HD |
- M |
- 4346_VC_H_2165 |
-
-
- | 179 |
- HB_069_HD |
- HD |
- F |
- 4356_VC_H_2164 |
-
-
- | 180 |
- HB_070_HD |
- HD |
- NA |
- 4386_CR_H_2249 |
-
-
- | 181 |
- HB_072_HD |
- HD |
- NA |
- 4404_VC_H_2161 |
-
-
- | 182 |
- HB_073_HD |
- HD |
- F |
- 4411_VC_H_1975 |
-
-
- | 183 |
- HB_074_HD |
- HD |
- NA |
- 4430_VC_H_2465 |
-
-
- | 184 |
- HB_075_HD |
- HD |
- M |
- 4470_VC_H_1974 |
-
-
- | 185 |
- HB_076_HD |
- HD |
- F |
- 4497_CR_H_1860 |
-
-
- | 186 |
- HB_077_HD |
- HD |
- M |
- 4509_CR_H_2244 |
-
-
- | 187 |
- HB_079_HD |
- HD |
- M |
- 4631_VC_H_1971 |
-
-
- | 188 |
- HB_080_HD |
- HD |
- F |
- 4653_PF_H_2083 |
-
-
- | 189 |
- HB_081_HD |
- HD |
- NA |
- 4678_CR_H_2242 |
-
-
- | 190 |
- HB_084_HD |
- HD |
- M |
- 4718_VC_H_2125 |
-
-
- | 191 |
- HB_090_HD |
- HD |
- NA |
- 4740_CR_H_2474 |
-
-
- | 192 |
- HB_094_HD |
- HD |
- NA |
- 4754_CR_H_2476 |
-
-
- | 193 |
- HB_098_HD |
- HD |
- NA |
- 4780_VC_H_2151 |
-
-
- | 194 |
- HB_101_HD |
- HD |
- F |
- 4809_VC_H_2148 |
-
-
- | 195 |
- HB_105_HD |
- HD |
- NA |
- 4819_CR_H_2238 |
-
-
- | 196 |
- HB_106_HD |
- HD |
- F |
- 4822_VC_H_1969 |
-
-
- | 197 |
- HB_108_HD |
- HD |
- M |
- 4826_VC_H_1968 |
-
-
- | 198 |
- HB_109_HD |
- HD |
- M |
- 4828_VC_H_2124 |
-
-
- | 199 |
- HB_115_HD |
- HD |
- NA |
- 4855_CR_H_2235 |
-
-
- | 200 |
- HB_121_HD |
- HD |
- F |
- 4902_VC_H_1967 |
-
-
- | 201 |
- HB_129_HD |
- HD |
- NA |
- 4938_VC_H_1966 |
-
-
- | 202 |
- HB_141_HD |
- HD |
- F |
- 4996_PF_H_2076 |
-
-
- | 203 |
- HB_152_HD |
- HD |
- NA |
- 5034_CR_H_2233 |
-
-
- | 204 |
- HB_153_HD |
- HD |
- M |
- 5043_VC_H_1960 |
-
-
- | 205 |
- HB_159_HD |
- HD |
- M |
- 5062_VC_H_1959 |
-
-
- | 206 |
- HB_172_HD |
- HD |
- F |
- 5114_PF_H_2070 |
-
-
- | 207 |
- HB_175_HD |
- HD |
- M |
- 5127_PF_H_2068 |
-
-
- | 208 |
- HB_180_HD |
- HD |
- M |
- 5148_VC_H_1944 |
-
-
- | 209 |
- HB_185_HD |
- HD |
- F |
- 5167_CR_H_2231 |
-
-
- | 210 |
- HB_188_HD |
- HD |
- F |
- 5172_VC_H_1951 |
-
-
- | 211 |
- HB_191_HD |
- HD |
- M |
- 5180_VC_H_1949 |
-
-
- | 212 |
- HB_196_HD |
- HD |
- NA |
- 5199_PF_H_2202 |
-
-
- | 213 |
- HB_203_HD |
- HD |
- F |
- 5228_PF_H_2059 |
-
-
- | 214 |
- HB_207_HD |
- HD |
- NA |
- 5248_PF_H_2201 |
-
-
- | 215 |
- HB_228_HD |
- HD |
- F |
- 5299_CR_H_2228 |
-
-
- | 216 |
- HB_233_HD |
- HD |
- M |
- 5312_VC_H_1938 |
-
-
- | 217 |
- HB_235_HD |
- HD |
- F |
- 5316_VC_H_1937 |
-
-
- | 218 |
- HB_242_HD |
- HD |
- F |
- 5328_PF_H_2048 |
-
-
- | 219 |
- HB_266_HD |
- HD |
- M |
- 5387_VC_H_1928 |
-
-
- | 220 |
- HB_271_HD |
- HD |
- M |
- 5394_PF_H_2039 |
-
-
- | 221 |
- HB_272_HD |
- HD |
- F |
- 5396_VC_H_1925 |
-
-
- | 222 |
- HB_279_HD |
- HD |
- F |
- 5409_VC_H_1924 |
-
-
- | 223 |
- HB_294_HD |
- HD |
- M |
- 5448_VC_H_1921 |
-
-
- | 224 |
- HB_301_HD |
- HD |
- NA |
- 5464_VC_H_1919 |
-
-
- | 225 |
- HB_304_HD |
- HD |
- F |
- 5471_VC_H_1918 |
-
-
- | 226 |
- HB_321_HD |
- HD |
- NA |
- 5522_PF_H_2199 |
-
-
- | 227 |
- HB_361_HD |
- HD |
- F |
- 5622_VC_H_2121 |
-
-
- | 228 |
- HB_370_HD |
- HD |
- M |
- 5645_VC_H_1904 |
-
-
- | 229 |
- HB_371_HD |
- HD |
- F |
- 5648_PF_H_2016 |
-
-
- | 230 |
- HB_384_HD |
- HD |
- F |
- 5688_PF_H_2012 |
-
-
- | 231 |
- HB_390_HD |
- HD |
- M |
- 5704_PF_H_2009 |
-
-
- | 232 |
- HB_393_HD |
- HD |
- F |
- 5709_VC_H_1895 |
-
-
- | 233 |
- HB_402_HD |
- HD |
- F |
- 5732_PF_H_2007 |
-
-
- | 234 |
- HB_405_HD |
- HD |
- NA |
- 5742_PF_H_2006 |
-
-
- | 235 |
- HB_407_HD |
- HD |
- M |
- 5745_PF_H_2005 |
-
-
- | 236 |
- HB_408_HD |
- HD |
- M |
- 5747_VC_H_1891 |
-
-
- | 237 |
- HB_415_HD |
- HD |
- NA |
- 5777_PF_H_1551 |
-
-
- | 238 |
- HB_417_HD |
- HD |
- M |
- 5784_PF_H_1554 |
-
-
- | 239 |
- HB_424_HD |
- HD |
- M |
- 5804_VC_H_1558 |
-
-
- | 240 |
- HB_444_HD |
- HD |
- M |
- 5856_VC_H_1567 |
-
-
- | 241 |
- HB_457_HD |
- HD |
- M |
- 5896_VC_H_1570 |
-
-
- | 242 |
- HB_466_HD |
- HD |
- M |
- 5910_PF_H_1572 |
-
-
- | 243 |
- HB_478_HD |
- HD |
- M |
- 5941_CR_H_1583 |
-
-
- | 244 |
- HB_487_HD |
- HD |
- F |
- 5964_VC_H_1597 |
-
-
- | 245 |
- HB_511_HD |
- HD |
- M |
- 6019_PF_H_2198 |
-
-
- | 246 |
- HB_513_HD |
- HD |
- F |
- 6024_VC_H_1612 |
-
-
- | 247 |
- HB_515_HD |
- HD |
- F |
- 6028_CR_H_1613 |
-
-
- | 248 |
- HB_518_HD |
- HD |
- M |
- 6033_VC_H_1618 |
-
-
- | 249 |
- HB_522_HD |
- HD |
- M |
- 6037_PF_H_1626 |
-
-
- | 250 |
- HB_527_HD |
- HD |
- F |
- 6047_VC_H_1639 |
-
-
- | 251 |
- HB_528_HD |
- HD |
- M |
- 6051_PF_H_1641 |
-
-
- | 252 |
- HB_530_HD |
- HD |
- M |
- 6054_VC_H_1648 |
-
-
- | 253 |
- HB_537_HD |
- HD |
- F |
- 6071_PF_H_1653 |
-
-
- | 254 |
- HB_549_HD |
- HD |
- M |
- 6119_CR_H_1670 |
-
-
- | 255 |
- HB_593_HD |
- HD |
- NA |
- 6219_CR_H_2567 |
-
-
- | 256 |
- HB_610_HD |
- HD |
- NA |
- 6275_PF_H_1692 |
-
-
- | 257 |
- HB_616_HD |
- HD |
- F |
- 6284_CR_H_1694 |
-
-
- | 258 |
- HB_626_HD |
- HD |
- M |
- 6315_VC_H_1702 |
-
-
- | 259 |
- HB_639_HD |
- HD |
- F |
- 6344_CR_H_1703 |
-
-
- | 260 |
- HB_649_HD |
- HD |
- F |
- 6382_CR_H_1709 |
-
-
- | 261 |
- HB_661_HD |
- HD |
- M |
- 6408_VC_H_1714 |
-
-
- | 262 |
- HB_682_HD |
- HD |
- M |
- 6467_PF_H_1725 |
-
-
- | 263 |
- HB_683_HD |
- HD |
- M |
- 6472_VC_H_1729 |
-
-
- | 264 |
- HB_691_HD |
- HD |
- F |
- 6493_VC_H_1732 |
-
-
- | 265 |
- HB_692_HD |
- HD |
- M |
- 6495_CR_H_1733 |
-
-
- | 266 |
- HB_707_HD |
- HD |
- M |
- 6535_PF_H_1737 |
-
-
- | 267 |
- HB_709_HD |
- HD |
- F |
- 6539_CR_H_1739 |
-
-
- | 268 |
- HB_725_HD |
- HD |
- M |
- 6572_PF_H_1746 |
-
-
- | 269 |
- HB_732_HD |
- HD |
- F |
- 6584_VC_H_1750 |
-
-
- | 270 |
- HB_734_HD |
- HD |
- F |
- 6587_CR_H_1751 |
-
-
- | 271 |
- HB_748_HD |
- HD |
- NA |
- 6615_VC_H_2315 |
-
-
- | 272 |
- HB_750_HD |
- HD |
- NA |
- 6628_PF_H_2326 |
-
-
- | 273 |
- HB_758_HD |
- HD |
- NA |
- 6643_VC_H_2602 |
-
-
- | 274 |
- HB_760_HD |
- HD |
- M |
- 6646_PF_H_1761 |
-
-
- | 275 |
- HB_762_HD |
- HD |
- M |
- 6650_VC_H_1765 |
-
-
- | 276 |
- HB_766_HD |
- HD |
- M |
- 6658_VC_H_1768 |
-
-
- | 277 |
- HB_768_HD |
- HD |
- NA |
- 6663_VC_H_1771 |
-
-
- | 278 |
- HB_769_HD |
- HD |
- M |
- 6666_VC_H_1774 |
-
-
- | 279 |
- HB_774_HD |
- HD |
- NA |
- 6689_PF_H_2344 |
-
-
- | 280 |
- HB_778_HD |
- HD |
- NA |
- 6696_PF_H_2356 |
-
-
- | 281 |
- HB_780_HD |
- HD |
- NA |
- 6704_PF_H_2362 |
-
-
- | 282 |
- HB_790_HD |
- HD |
- NA |
- 6788_PF_H_2389 |
-
-
- | 283 |
- HB_800_HD |
- HD |
- NA |
- 6807_PF_H_2419 |
-
-
- | 284 |
- HB_802_HD |
- HD |
- NA |
- 6811_PF_H_2425 |
-
-
- | 285 |
- HB_045_AD |
- AD |
- NA |
- 3734_CR_A_0122 |
-
-
- | 286 |
- HB_048_AD |
- AD |
- NA |
- 3791_CR_A_0128 |
-
-
- | 287 |
- HB_053_AD |
- AD |
- NA |
- 3877_CR_A_0134 |
-
-
- | 288 |
- HB_055_AD |
- AD |
- NA |
- 3893_VC_A_0142 |
-
-
- | 289 |
- HB_068_AD |
- AD |
- NA |
- 4349_VC_A_0148 |
-
-
- | 290 |
- HB_082_AD |
- AD |
- NA |
- 4712_CR_A_0309 |
-
-
- | 291 |
- HB_085_AD |
- AD |
- NA |
- 4726_VC_A_0311 |
-
-
- | 292 |
- HB_087_AD |
- AD |
- NA |
- 4730_CR_A_0315 |
-
-
- | 293 |
- HB_089_AD |
- AD |
- NA |
- 4733_VC_A_0320 |
-
-
- | 294 |
- HB_093_AD |
- AD |
- NA |
- 4749_VC_A_0323 |
-
-
- | 295 |
- HB_095_AD |
- AD |
- NA |
- 4759_CR_A_0327 |
-
-
- | 296 |
- HB_097_AD |
- AD |
- NA |
- 4773_CR_A_0866 |
-
-
- | 297 |
- HB_099_AD |
- AD |
- NA |
- 4785_VC_A_0332 |
-
-
- | 298 |
- HB_100_AD |
- AD |
- NA |
- 4795_VC_A_0335 |
-
-
- | 299 |
- HB_103_AD |
- AD |
- NA |
- 4811_VC_A_0341 |
-
-
- | 300 |
- HB_104_AD |
- AD |
- NA |
- 4813_CR_A_0345 |
-
-
- | 301 |
- HB_112_AD |
- AD |
- NA |
- 4842_VC_A_0870 |
-
-
- | 302 |
- HB_113_AD |
- AD |
- NA |
- 4850_CR_A_0351 |
-
-
- | 303 |
- HB_114_AD |
- AD |
- NA |
- 4852_CR_A_0354 |
-
-
- | 304 |
- HB_117_AD |
- AD |
- NA |
- 4868_VC_A_0874 |
-
-
- | 305 |
- HB_122_AD |
- AD |
- NA |
- 4904_CR_A_1132 |
-
-
- | 306 |
- HB_123_AD |
- AD |
- NA |
- 4905_VC_A_0884 |
-
-
- | 307 |
- HB_124_AD |
- AD |
- NA |
- 4916_VC_A_0886 |
-
-
- | 308 |
- HB_125_AD |
- AD |
- NA |
- 4917_CR_A_0360 |
-
-
- | 309 |
- HB_126_AD |
- AD |
- NA |
- 4921_VC_A_0362 |
-
-
- | 310 |
- HB_128_AD |
- AD |
- NA |
- 4936_CR_A_0369 |
-
-
- | 311 |
- HB_130_AD |
- AD |
- NA |
- 4939_VC_A_0888 |
-
-
- | 312 |
- HB_131_AD |
- AD |
- NA |
- 4944_CR_A_0889 |
-
-
- | 313 |
- HB_132_AD |
- AD |
- NA |
- 4946_CR_A_0372 |
-
-
- | 314 |
- HB_134_AD |
- AD |
- NA |
- 4951_CR_A_0891 |
-
-
- | 315 |
- HB_135_AD |
- AD |
- NA |
- 4953_VC_A_0893 |
-
-
- | 316 |
- HB_136_AD |
- AD |
- NA |
- 4965_VC_A_0160 |
-
-
- | 317 |
- HB_137_AD |
- AD |
- NA |
- 4966_VC_A_0374 |
-
-
- | 318 |
- HB_138_AD |
- AD |
- NA |
- 4969_VC_A_0895 |
-
-
- | 319 |
- HB_140_AD |
- AD |
- NA |
- 4993_CR_A_0896 |
-
-
- | 320 |
- HB_146_AD |
- AD |
- NA |
- 5018_CR_A_0384 |
-
-
- | 321 |
- HB_148_AD |
- AD |
- NA |
- 5022_VC_A_0386 |
-
-
- | 322 |
- HB_150_AD |
- AD |
- NA |
- 5031_VC_A_0392 |
-
-
- | 323 |
- HB_151_AD |
- AD |
- NA |
- 5033_CR_A_0396 |
-
-
- | 324 |
- HB_154_AD |
- AD |
- NA |
- 5048_VC_A_1321 |
-
-
- | 325 |
- HB_155_AD |
- AD |
- NA |
- 5056_VC_A_0398 |
-
-
- | 326 |
- HB_156_AD |
- AD |
- NA |
- 5057_VC_A_0163 |
-
-
- | 327 |
- HB_157_AD |
- AD |
- NA |
- 5059_VC_A_0401 |
-
-
- | 328 |
- HB_158_AD |
- AD |
- NA |
- 5061_PF_A_2612 |
-
-
- | 329 |
- HB_160_AD |
- AD |
- NA |
- 5064_PF_A_2615 |
-
-
- | 330 |
- HB_165_AD |
- AD |
- NA |
- 5092_CR_A_0899 |
-
-
- | 331 |
- HB_168_AD |
- AD |
- NA |
- 5097_VC_A_0407 |
-
-
- | 332 |
- HB_170_AD |
- AD |
- NA |
- 5101_VC_A_0410 |
-
-
- | 333 |
- HB_174_AD |
- AD |
- NA |
- 5124_PF_A_1343 |
-
-
- | 334 |
- HB_179_AD |
- AD |
- NA |
- 5145_VC_A_1351 |
-
-
- | 335 |
- HB_181_AD |
- AD |
- NA |
- 5152_CR_A_0414 |
-
-
- | 336 |
- HB_184_AD |
- AD |
- NA |
- 5166_VC_A_1354 |
-
-
- | 337 |
- HB_194_AD |
- AD |
- NA |
- 5193_VC_A_1360 |
-
-
- | 338 |
- HB_197_AD |
- AD |
- NA |
- 5202_CR_A_1368 |
-
-
- | 339 |
- HB_199_AD |
- AD |
- NA |
- 5205_VC_A_0166 |
-
-
- | 340 |
- HB_200_AD |
- AD |
- NA |
- 5210_VC_A_0905 |
-
-
- | 341 |
- HB_205_AD |
- AD |
- NA |
- 5235_VC_A_0419 |
-
-
- | 342 |
- HB_208_AD |
- AD |
- NA |
- 5249_VC_A_0422 |
-
-
- | 343 |
- HB_209_AD |
- AD |
- NA |
- 5252_VC_A_0907 |
-
-
- | 344 |
- HB_211_AD |
- AD |
- NA |
- 5257_VC_A_0169 |
-
-
- | 345 |
- HB_216_AD |
- AD |
- NA |
- 5272_VC_A_0425 |
-
-
- | 346 |
- HB_219_AD |
- AD |
- NA |
- 5279_CR_A_0147 |
-
-
- | 347 |
- HB_221_AD |
- AD |
- NA |
- 5283_VC_A_0145 |
-
-
- | 348 |
- HB_222_AD |
- AD |
- NA |
- 5285_VC_A_0141 |
-
-
- | 349 |
- HB_224_AD |
- AD |
- NA |
- 5288_VC_A_0428 |
-
-
- | 350 |
- HB_230_AD |
- AD |
- NA |
- 5301_VC_A_0174 |
-
-
- | 351 |
- HB_231_AD |
- AD |
- NA |
- 5305_VC_A_1384 |
-
-
- | 352 |
- HB_232_AD |
- AD |
- NA |
- 5310_CR_A_0176 |
-
-
- | 353 |
- HB_234_AD |
- AD |
- NA |
- 5313_PF_A_2618 |
-
-
- | 354 |
- HB_236_AD |
- AD |
- NA |
- 5317_PF_A_2624 |
-
-
- | 355 |
- HB_238_AD |
- AD |
- NA |
- 5322_CR_A_2632 |
-
-
- | 356 |
- HB_240_AD |
- AD |
- NA |
- 5325_VC_A_0137 |
-
-
- | 357 |
- HB_244_AD |
- AD |
- NA |
- 5337_VC_A_1387 |
-
-
- | 358 |
- HB_245_AD |
- AD |
- NA |
- 5339_VC_A_0181 |
-
-
- | 359 |
- HB_250_AD |
- AD |
- NA |
- 5346_VC_A_1393 |
-
-
- | 360 |
- HB_251_AD |
- AD |
- NA |
- 5350_VC_A_0184 |
-
-
- | 361 |
- HB_252_AD |
- AD |
- NA |
- 5355_VC_A_0133 |
-
-
- | 362 |
- HB_253_AD |
- AD |
- NA |
- 5359_CR_A_1395 |
-
-
- | 363 |
- HB_258_AD |
- AD |
- NA |
- 5370_PF_A_1400 |
-
-
- | 364 |
- HB_259_AD |
- AD |
- NA |
- 5371_PF_A_2636 |
-
-
- | 365 |
- HB_260_AD |
- AD |
- NA |
- 5375_VC_A_0188 |
-
-
- | 366 |
- HB_263_AD |
- AD |
- NA |
- 5381_VC_A_0022 |
-
-
- | 367 |
- HB_265_AD |
- AD |
- NA |
- 5385_VC_A_1402 |
-
-
- | 368 |
- HB_267_AD |
- AD |
- NA |
- 5389_VC_A_0928 |
-
-
- | 369 |
- HB_268_AD |
- AD |
- NA |
- 5390_CR_A_0151 |
-
-
- | 370 |
- HB_273_AD |
- AD |
- NA |
- 5400_PF_A_2645 |
-
-
- | 371 |
- HB_274_AD |
- AD |
- NA |
- 5401_VC_A_0931 |
-
-
- | 372 |
- HB_275_AD |
- AD |
- NA |
- 5404_PF_A_2648 |
-
-
- | 373 |
- HB_276_AD |
- AD |
- NA |
- 5406_VC_A_0933 |
-
-
- | 374 |
- HB_277_AD |
- AD |
- NA |
- 5407_PF_A_2651 |
-
-
- | 375 |
- HB_280_AD |
- AD |
- NA |
- 5412_VC_A_0935 |
-
-
- | 376 |
- HB_281_AD |
- AD |
- NA |
- 5413_PF_A_2657 |
-
-
- | 377 |
- HB_283_AD |
- AD |
- NA |
- 5419_VC_A_0937 |
-
-
- | 378 |
- HB_284_AD |
- AD |
- NA |
- 5420_VC_A_0939 |
-
-
- | 379 |
- HB_285_AD |
- AD |
- NA |
- 5421_CR_A_0432 |
-
-
- | 380 |
- HB_286_AD |
- AD |
- NA |
- 5423_PF_A_2660 |
-
-
- | 381 |
- HB_288_AD |
- AD |
- NA |
- 5425_PF_A_2666 |
-
-
- | 382 |
- HB_289_AD |
- AD |
- NA |
- 5426_VC_A_1405 |
-
-
- | 383 |
- HB_290_AD |
- AD |
- NA |
- 5433_VC_A_0434 |
-
-
- | 384 |
- HB_296_AD |
- AD |
- NA |
- 5456_PF_A_2675 |
-
-
- | 385 |
- HB_299_AD |
- AD |
- NA |
- 5461_VC_A_0192 |
-
-
- | 386 |
- HB_302_AD |
- AD |
- NA |
- 5465_PF_A_2678 |
-
-
- | 387 |
- HB_303_AD |
- AD |
- NA |
- 5469_VC_A_1417 |
-
-
- | 388 |
- HB_305_AD |
- AD |
- NA |
- 5479_PF_A_1421 |
-
-
- | 389 |
- HB_306_AD |
- AD |
- NA |
- 5480_VC_A_0437 |
-
-
- | 390 |
- HB_307_AD |
- AD |
- NA |
- 5482_VC_A_0028 |
-
-
- | 391 |
- HB_308_AD |
- AD |
- NA |
- 5483_VC_A_0941 |
-
-
- | 392 |
- HB_309_AD |
- AD |
- NA |
- 5487_CR_A_0441 |
-
-
- | 393 |
- HB_310_AD |
- AD |
- NA |
- 5488_CR_A_0194 |
-
-
- | 394 |
- HB_312_AD |
- AD |
- NA |
- 5500_VC_A_0198 |
-
-
- | 395 |
- HB_313_AD |
- AD |
- NA |
- 5502_PF_A_2684 |
-
-
- | 396 |
- HB_315_AD |
- AD |
- NA |
- 5513_PF_A_2687 |
-
-
- | 397 |
- HB_316_AD |
- AD |
- NA |
- 5516_PF_A_2690 |
-
-
- | 398 |
- HB_317_AD |
- AD |
- NA |
- 5517_PF_A_2693 |
-
-
- | 399 |
- HB_318_AD |
- AD |
- NA |
- 5518_CR_A_0030 |
-
-
- | 400 |
- HB_319_AD |
- AD |
- NA |
- 5519_CR_A_2695 |
-
-
- | 401 |
- HB_320_AD |
- AD |
- NA |
- 5520_PF_A_2699 |
-
-
- | 402 |
- HB_322_AD |
- AD |
- NA |
- 5527_VC_A_0945 |
-
-
- | 403 |
- HB_325_AD |
- AD |
- NA |
- 5532_PF_A_2702 |
-
-
- | 404 |
- HB_328_AD |
- AD |
- NA |
- 5541_PF_A_2705 |
-
-
- | 405 |
- HB_330_AD |
- AD |
- NA |
- 5544_VC_A_0201 |
-
-
- | 406 |
- HB_334_AD |
- AD |
- NA |
- 5554_VC_A_0452 |
-
-
- | 407 |
- HB_335_AD |
- AD |
- NA |
- 5557_VC_A_0950 |
-
-
- | 408 |
- HB_337_AD |
- AD |
- NA |
- 5560_VC_A_0204 |
-
-
- | 409 |
- HB_342_AD |
- AD |
- NA |
- 5571_PF_A_1430 |
-
-
- | 410 |
- HB_345_AD |
- AD |
- NA |
- 5583_PF_A_2708 |
-
-
- | 411 |
- HB_347_AD |
- AD |
- NA |
- 5589_PF_A_2714 |
-
-
- | 412 |
- HB_349_AD |
- AD |
- NA |
- 5592_PF_A_2717 |
-
-
- | 413 |
- HB_352_AD |
- AD |
- NA |
- 5604_VC_A_0037 |
-
-
- | 414 |
- HB_353_AD |
- AD |
- NA |
- 5607_PF_A_2723 |
-
-
- | 415 |
- HB_356_AD |
- AD |
- NA |
- 5615_VC_A_0041 |
-
-
- | 416 |
- HB_357_AD |
- AD |
- NA |
- 5616_CR_A_0127 |
-
-
- | 417 |
- HB_358_AD |
- AD |
- NA |
- 5617_CR_A_0456 |
-
-
- | 418 |
- HB_359_AD |
- AD |
- NA |
- 5618_CR_A_0044 |
-
-
- | 419 |
- HB_362_AD |
- AD |
- NA |
- 5625_CR_A_2495 |
-
-
- | 420 |
- HB_363_AD |
- AD |
- NA |
- 5626_CR_A_2498 |
-
-
- | 421 |
- HB_364_AD |
- AD |
- NA |
- 5629_CR_A_0390 |
-
-
- | 422 |
- HB_369_AD |
- AD |
- NA |
- 5643_VC_A_1143 |
-
-
- | 423 |
- HB_373_AD |
- AD |
- NA |
- 5654_VC_A_0047 |
-
-
- | 424 |
- HB_375_AD |
- AD |
- NA |
- 5660_CR_A_0462 |
-
-
- | 425 |
- HB_376_AD |
- AD |
- NA |
- 5661_VC_A_0464 |
-
-
- | 426 |
- HB_377_AD |
- AD |
- NA |
- 5667_VC_A_2509 |
-
-
- | 427 |
- HB_378_AD |
- AD |
- NA |
- 5668_VC_A_1438 |
-
-
- | 428 |
- HB_383_AD |
- AD |
- NA |
- 5686_CR_A_2728 |
-
-
- | 429 |
- HB_386_AD |
- AD |
- NA |
- 5695_VC_A_0953 |
-
-
- | 430 |
- HB_389_AD |
- AD |
- NA |
- 5700_VC_A_2514 |
-
-
- | 431 |
- HB_391_AD |
- AD |
- NA |
- 5705_CR_A_0474 |
-
-
- | 432 |
- HB_392_AD |
- AD |
- NA |
- 5706_VC_A_0476 |
-
-
- | 433 |
- HB_394_AD |
- AD |
- NA |
- 5713_VC_A_0479 |
-
-
- | 434 |
- HB_397_AD |
- AD |
- NA |
- 5721_CR_A_0210 |
-
-
- | 435 |
- HB_404_AD |
- AD |
- NA |
- 5735_CR_A_0489 |
-
-
- | 436 |
- HB_406_AD |
- AD |
- NA |
- 5744_CR_A_0960 |
-
-
- | 437 |
- HB_409_AD |
- AD |
- NA |
- 5749_CR_A_0159 |
-
-
- | 438 |
- HB_410_AD |
- AD |
- NA |
- 5751_CR_A_2518 |
-
-
- | 439 |
- HB_411_AD |
- AD |
- NA |
- 5755_CR_A_2731 |
-
-
- | 440 |
- HB_413_AD |
- AD |
- NA |
- 5766_VC_A_0214 |
-
-
- | 441 |
- HB_419_AD |
- AD |
- NA |
- 5790_VC_A_0217 |
-
-
- | 442 |
- HB_420_AD |
- AD |
- NA |
- 5796_CR_A_0964 |
-
-
- | 443 |
- HB_428_AD |
- AD |
- NA |
- 5811_CR_A_2524 |
-
-
- | 444 |
- HB_429_AD |
- AD |
- NA |
- 5819_CR_A_2527 |
-
-
- | 445 |
- HB_430_AD |
- AD |
- NA |
- 5822_CR_A_2530 |
-
-
- | 446 |
- HB_434_AD |
- AD |
- NA |
- 5828_CR_A_2533 |
-
-
- | 447 |
- HB_435_AD |
- AD |
- NA |
- 5831_CR_A_0222 |
-
-
- | 448 |
- HB_437_AD |
- AD |
- NA |
- 5839_CR_A_2539 |
-
-
- | 449 |
- HB_438_AD |
- AD |
- NA |
- 5843_CR_A_0227 |
-
-
- | 450 |
- HB_439_AD |
- AD |
- NA |
- 5845_CR_A_0230 |
-
-
- | 451 |
- HB_441_AD |
- AD |
- NA |
- 5849_CR_A_0233 |
-
-
- | 452 |
- HB_442_AD |
- AD |
- NA |
- 5850_CR_A_0495 |
-
-
- | 453 |
- HB_445_AD |
- AD |
- NA |
- 5858_CR_A_0969 |
-
-
- | 454 |
- HB_448_AD |
- AD |
- NA |
- 5864_CR_A_0974 |
-
-
- | 455 |
- HB_451_AD |
- AD |
- NA |
- 5871_CR_A_2542 |
-
-
- | 456 |
- HB_454_AD |
- AD |
- NA |
- 5879_CR_A_2545 |
-
-
- | 457 |
- HB_455_AD |
- AD |
- NA |
- 5887_CR_A_0976_Bis |
-
-
- | 458 |
- HB_459_AD |
- AD |
- NA |
- 5898_CR_A_2548 |
-
-
- | 459 |
- HB_460_AD |
- AD |
- NA |
- 5900_VC_A_0237 |
-
-
- | 460 |
- HB_461_AD |
- AD |
- NA |
- 5901_CR_A_0239 |
-
-
- | 461 |
- HB_469_AD |
- AD |
- NA |
- 5914_CR_A_2554 |
-
-
- | 462 |
- HB_471_AD |
- AD |
- NA |
- 5922_VC_A_0246 |
-
-
- | 463 |
- HB_473_AD |
- AD |
- NA |
- 5927_CR_A_2560 |
-
-
- | 464 |
- HB_474_AD |
- AD |
- NA |
- 5933_VC_A_1071 |
-
-
- | 465 |
- HB_477_AD |
- AD |
- NA |
- 5939_CR_A_1151 |
-
-
- | 466 |
- HB_479_AD |
- AD |
- NA |
- 5945_VC_A_0983 |
-
-
- | 467 |
- HB_484_AD |
- AD |
- NA |
- 5956_CR_A_0123 |
-
-
- | 468 |
- HB_489_AD |
- AD |
- NA |
- 5968_VC_A_1075 |
-
-
- | 469 |
- HB_491_AD |
- AD |
- NA |
- 5971_CR_A_0119 |
-
-
- | 470 |
- HB_492_AD |
- AD |
- NA |
- 5972_VC_A_0251 |
-
-
- | 471 |
- HB_494_AD |
- AD |
- NA |
- 5979_CR_A_0115 |
-
-
- | 472 |
- HB_498_AD |
- AD |
- NA |
- 5988_VC_A_0503 |
-
-
- | 473 |
- HB_502_AD |
- AD |
- NA |
- 5994_PF_A_1605 |
-
-
- | 474 |
- HB_503_AD |
- AD |
- NA |
- 5995_CR_A_2563 |
-
-
- | 475 |
- HB_510_AD |
- AD |
- NA |
- 6017_CR_A_0048 |
-
-
- | 476 |
- HB_514_AD |
- AD |
- NA |
- 6025_VC_A_0506 |
-
-
- | 477 |
- HB_517_AD |
- AD |
- NA |
- 6031_VC_A_0258 |
-
-
- | 478 |
- HB_520_AD |
- AD |
- NA |
- 6035_VC_A_1621 |
-
-
- | 479 |
- HB_523_AD |
- AD |
- NA |
- 6038_VC_A_0261 |
-
-
- | 480 |
- HB_524_AD |
- AD |
- NA |
- 6042_VC_A_1156 |
-
-
- | 481 |
- HB_525_AD |
- AD |
- NA |
- 6044_VC_A_0264 |
-
-
- | 482 |
- HB_531_AD |
- AD |
- NA |
- 6056_CR_A_0999 |
-
-
- | 483 |
- HB_533_AD |
- AD |
- NA |
- 6061_PF_A_1650 |
-
-
- | 484 |
- HB_534_AD |
- AD |
- NA |
- 6066_VC_A_0270 |
-
-
- | 485 |
- HB_535_AD |
- AD |
- NA |
- 6067_PF_A_1452 |
-
-
- | 486 |
- HB_536_AD |
- AD |
- NA |
- 6068_VC_A_0273 |
-
-
- | 487 |
- HB_545_AD |
- AD |
- NA |
- 6102_CR_A_1661 |
-
-
- | 488 |
- HB_546_AD |
- AD |
- NA |
- 6107_CR_A_0055 |
-
-
- | 489 |
- HB_550_AD |
- AD |
- NA |
- 6120_VC_A_0058 |
-
-
- | 490 |
- HB_552_AD |
- AD |
- NA |
- 6126_VC_A_1675 |
-
-
- | 491 |
- HB_553_AD |
- AD |
- NA |
- 6129_PF_A_0274 |
-
-
- | 492 |
- HB_554_AD |
- AD |
- NA |
- 6130_VC_A_1678 |
-
-
- | 493 |
- HB_555_AD |
- AD |
- NA |
- 6131_CR_A_0510 |
-
-
- | 494 |
- HB_556_AD |
- AD |
- NA |
- 6132_CR_A_0513 |
-
-
- | 495 |
- HB_558_AD |
- AD |
- NA |
- 6137_VC_A_1681 |
-
-
- | 496 |
- HB_564_AD |
- AD |
- NA |
- 6153_VC_A_1465 |
-
-
- | 497 |
- HB_565_AD |
- AD |
- NA |
- 6154_VC_A_1468 |
-
-
- | 498 |
- HB_566_AD |
- AD |
- NA |
- 6157_VC_A_0062 |
-
-
- | 499 |
- HB_568_AD |
- AD |
- NA |
- 6164_CR_A_1005 |
-
-
- | 500 |
- HB_571_AD |
- AD |
- NA |
- 6171_CR_A_0065 |
-
-
- | 501 |
- HB_573_AD |
- AD |
- NA |
- 6174_VC_A_0068 |
-
-
- | 502 |
- HB_576_AD |
- AD |
- NA |
- 6180_CR_A_0281 |
-
-
- | 503 |
- HB_583_AD |
- AD |
- NA |
- 6194_VC_A_0071 |
-
-
- | 504 |
- HB_585_AD |
- AD |
- NA |
- 6198_VC_A_0073 |
-
-
- | 505 |
- HB_590_AD |
- AD |
- NA |
- 6215_VC_A_0518 |
-
-
- | 506 |
- HB_591_AD |
- AD |
- NA |
- 6216_VC_A_1476 |
-
-
- | 507 |
- HB_592_AD |
- AD |
- NA |
- 6218_CR_A_0522 |
-
-
- | 508 |
- HB_594_AD |
- AD |
- NA |
- 6223_VC_A_0288 |
-
-
- | 509 |
- HB_596_AD |
- AD |
- NA |
- 6226_CR_A_0076 |
-
-
- | 510 |
- HB_597_AD |
- AD |
- NA |
- 6227_VC_A_0080 |
-
-
- | 511 |
- HB_598_AD |
- AD |
- NA |
- 6231_VC_A_1479 |
-
-
- | 512 |
- HB_605_AD |
- AD |
- NA |
- 6261_VC_A_0084 |
-
-
- | 513 |
- HB_608_AD |
- AD |
- NA |
- 6268_CR_A_0525 |
-
-
- | 514 |
- HB_611_AD |
- AD |
- NA |
- 6279_VC_A_0089 |
-
-
- | 515 |
- HB_612_AD |
- AD |
- NA |
- 6280_VC_A_0091 |
-
-
- | 516 |
- HB_613_AD |
- AD |
- NA |
- 6281_CR_A_0528 |
-
-
- | 517 |
- HB_621_AD |
- AD |
- NA |
- 6308_VC_A_1503 |
-
-
- | 518 |
- HB_623_AD |
- AD |
- NA |
- 6311_CR_A_0531 |
-
-
- | 519 |
- HB_624_AD |
- AD |
- NA |
- 6312_CR_A_0534 |
-
-
- | 520 |
- HB_630_AD |
- AD |
- NA |
- 6324_PF_A_1514 |
-
-
- | 521 |
- HB_633_AD |
- AD |
- NA |
- 6332_VC_A_1518 |
-
-
- | 522 |
- HB_634_AD |
- AD |
- NA |
- 6335_VC_A_0536 |
-
-
- | 523 |
- HB_635_AD |
- AD |
- NA |
- 6336_CR_A_0290 |
-
-
- | 524 |
- HB_636_AD |
- AD |
- NA |
- 6338_VC_A_0539 |
-
-
- | 525 |
- HB_642_AD |
- AD |
- NA |
- 6358_VC_A_0545 |
-
-
- | 526 |
- HB_652_AD |
- AD |
- NA |
- 6387_VC_A_0093 |
-
-
- | 527 |
- HB_657_AD |
- AD |
- NA |
- 6394_VC_A_0551 |
-
-
- | 528 |
- HB_664_AD |
- AD |
- NA |
- 6416_VC_A_1095 |
-
-
- | 529 |
- HB_666_AD |
- AD |
- NA |
- 6422_CR_A_0555 |
-
-
- | 530 |
- HB_669_AD |
- AD |
- NA |
- 6431_VC_A_0294 |
-
-
- | 531 |
- HB_674_AD |
- AD |
- NA |
- 6449_VC_A_1183 |
-
-
- | 532 |
- HB_680_AD |
- AD |
- NA |
- 6458_CR_A_2570 |
-
-
- | 533 |
- HB_685_AD |
- AD |
- NA |
- 6481_VC_A_0560 |
-
-
- | 534 |
- HB_690_AD |
- AD |
- NA |
- 6489_CR_A_0100 |
-
-
- | 535 |
- HB_696_AD |
- AD |
- NA |
- 6511_VC_A_1119 |
-
-
- | 536 |
- HB_698_AD |
- AD |
- NA |
- 6515_CR_A_0564 |
-
-
- | 537 |
- HB_699_AD |
- AD |
- NA |
- 6518_VC_A_0103 |
-
-
- | 538 |
- HB_703_AD |
- AD |
- NA |
- 6523_VC_A_0107 |
-
-
- | 539 |
- HB_704_AD |
- AD |
- NA |
- 6530_VC_A_0112 |
-
-
- | 540 |
- HB_706_AD |
- AD |
- NA |
- 6534_VC_A_0306 |
-
-
- | 541 |
- HB_712_AD |
- AD |
- NA |
- 6546_PF_A_1194 |
-
-
- | 542 |
- HB_713_AD |
- AD |
- NA |
- 6548_PF_A_1541 |
-
-
- | 543 |
- HB_715_AD |
- AD |
- NA |
- 6550_VC_A_1201 |
-
-
- | 544 |
- HB_718_AD |
- AD |
- NA |
- 6554_PF_A_1203 |
-
-
- | 545 |
- HB_720_AD |
- AD |
- NA |
- 6559_PF_A_2287 |
-
-
- | 546 |
- HB_722_AD |
- AD |
- NA |
- 6561_CR_A_2582 |
-
-
- | 547 |
- HB_723_AD |
- AD |
- NA |
- 6562_PF_A_2290 |
-
-
- | 548 |
- HB_724_AD |
- AD |
- NA |
- 6564_CR_A_2585 |
-
-
- | 549 |
- HB_727_AD |
- AD |
- NA |
- 6575_CR_A_2298 |
-
-
- | 550 |
- HB_728_AD |
- AD |
- NA |
- 6577_PF_A_2299 |
-
-
- | 551 |
- HB_729_AD |
- AD |
- NA |
- 6578_PF_A_2302 |
-
-
- | 552 |
- HB_731_AD |
- AD |
- NA |
- 6582_VC_A_1207 |
-
-
- | 553 |
- HB_733_AD |
- AD |
- NA |
- 6585_VC_A_1210 |
-
-
- | 554 |
- HB_736_AD |
- AD |
- NA |
- 6590_PF_A_1215 |
-
-
- | 555 |
- HB_743_AD |
- AD |
- NA |
- 6603_PF_A_1448 |
-
-
- | 556 |
- HB_745_AD |
- AD |
- NA |
- 6610_PF_A_1227 |
-
-
- | 557 |
- HB_746_AD |
- AD |
- NA |
- 6612_PF_A_2308 |
-
-
- | 558 |
- HB_749_AD |
- AD |
- NA |
- 6617_VC_A_2587 |
-
-
- | 559 |
- HB_751_AD |
- AD |
- NA |
- 6629_VC_A_2330 |
-
-
- | 560 |
- HB_752_AD |
- AD |
- NA |
- 6630_VC_A_2590 |
-
-
- | 561 |
- HB_753_AD |
- AD |
- NA |
- 6632_PF_A_2332 |
-
-
- | 562 |
- HB_754_AD |
- AD |
- NA |
- 6637_VC_A_2596 |
-
-
- | 563 |
- HB_755_AD |
- AD |
- NA |
- 6638_VC_A_2599 |
-
-
- | 564 |
- HB_756_AD |
- AD |
- NA |
- 6639_VC_A_2336 |
-
-
- | 565 |
- HB_757_AD |
- AD |
- NA |
- 6641_PF_A_2338 |
-
-
- | 566 |
- HB_763_AD |
- AD |
- NA |
- 6654_VC_A_1237 |
-
-
- | 567 |
- HB_773_AD |
- AD |
- NA |
- 6681_VC_A_1252 |
-
-
- | 568 |
- HB_775_AD |
- AD |
- NA |
- 6693_VC_A_2348 |
-
-
- | 569 |
- HB_776_AD |
- AD |
- NA |
- 6694_VC_A_2351 |
-
-
- | 570 |
- HB_777_AD |
- AD |
- NA |
- 6695_PF_A_2353 |
-
-
- | 571 |
- HB_779_AD |
- AD |
- NA |
- 6699_PF_A_2359 |
-
-
- | 572 |
- HB_781_AD |
- AD |
- NA |
- 6708_VC_A_2366 |
-
-
- | 573 |
- HB_782_AD |
- AD |
- NA |
- 6776_PF_A_2607 |
-
-
- | 574 |
- HB_783_AD |
- AD |
- NA |
- 6778_PF_A_2368 |
-
-
- | 575 |
- HB_784_AD |
- AD |
- NA |
- 6779_PF_A_2371 |
-
-
- | 576 |
- HB_785_AD |
- AD |
- NA |
- 6780_PF_A_2374 |
-
-
- | 577 |
- HB_786_AD |
- AD |
- NA |
- 6782_PF_A_2377 |
-
-
- | 578 |
- HB_787_AD |
- AD |
- NA |
- 6784_PF_A_2380 |
-
-
- | 579 |
- HB_788_AD |
- AD |
- NA |
- 6785_CR_A_2385 |
-
-
- | 580 |
- HB_789_AD |
- AD |
- NA |
- 6787_CR_A_2388 |
-
-
- | 581 |
- HB_791_AD |
- AD |
- NA |
- 6790_PF_A_2392 |
-
-
- | 582 |
- HB_792_AD |
- AD |
- NA |
- 6791_PF_A_2395 |
-
-
- | 583 |
- HB_793_AD |
- AD |
- NA |
- 6793_PF_A_2398 |
-
-
- | 584 |
- HB_794_AD |
- AD |
- NA |
- 6794_PF_A_2401 |
-
-
- | 585 |
- HB_795_AD |
- AD |
- NA |
- 6797_PF_A_2404 |
-
-
- | 586 |
- HB_796_AD |
- AD |
- NA |
- 6798_PF_A_2407 |
-
-
- | 587 |
- HB_797_AD |
- AD |
- NA |
- 6799_VC_A_2411 |
-
-
- | 588 |
- HB_798_AD |
- AD |
- NA |
- 6801_VC_A_2414 |
-
-
- | 589 |
- HB_799_AD |
- AD |
- NA |
- 6803_VC_A_2417 |
-
-
- | 590 |
- HB_801_AD |
- AD |
- NA |
- 6809_PF_A_2422 |
-
-
- | 591 |
- HB_803_AD |
- AD |
- NA |
- 6818_CR_A_2430 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/HBTRC_MLC_N_0611/experiment-design.rtf b/general/datasets/HBTRC_MLC_N_0611/experiment-design.rtf
deleted file mode 100644
index 3b0c224..0000000
--- a/general/datasets/HBTRC_MLC_N_0611/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
diff --git a/general/datasets/HBTRC_MLC_N_0611/notes.rtf b/general/datasets/HBTRC_MLC_N_0611/notes.rtf
deleted file mode 100644
index ff90e34..0000000
--- a/general/datasets/HBTRC_MLC_N_0611/notes.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Species: Human
-Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
-Disease: Neurological Disease
-Investigator: Francine Benes/ Eric Schadt
-Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
-Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC_MLC_N_0611/summary.rtf b/general/datasets/HBTRC_MLC_N_0611/summary.rtf
deleted file mode 100644
index 5cde3bf..0000000
--- a/general/datasets/HBTRC_MLC_N_0611/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC_MLPFC_0611/acknowledgment.rtf b/general/datasets/HBTRC_MLPFC_0611/acknowledgment.rtf
deleted file mode 100644
index 208cb6e..0000000
--- a/general/datasets/HBTRC_MLPFC_0611/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC_MLPFC_0611/cases.rtf b/general/datasets/HBTRC_MLPFC_0611/cases.rtf
deleted file mode 100644
index 86ed08e..0000000
--- a/general/datasets/HBTRC_MLPFC_0611/cases.rtf
+++ /dev/null
@@ -1,4166 +0,0 @@
-This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- | Series |
- Cerebellum in GN |
- Condition |
- Gender |
- BioSample Name |
-
-
- | 1 |
- HB_029_N |
- N |
- NA |
- 3405_VC_N_0859 |
-
-
- | 2 |
- HB_058_N |
- N |
- NA |
- 4021_VC_N_0854 |
-
-
- | 3 |
- HB_064_N |
- N |
- NA |
- 4338_VC_N_0861 |
-
-
- | 4 |
- HB_086_N |
- N |
- NA |
- 4729_PF_N_0756 |
-
-
- | 5 |
- HB_091_N |
- N |
- NA |
- 4741_VC_N_0864 |
-
-
- | 6 |
- HB_092_N |
- N |
- NA |
- 4744_VC_N_0865 |
-
-
- | 7 |
- HB_102_N |
- N |
- NA |
- 4810_VC_N_0869 |
-
-
- | 8 |
- HB_119_N |
- N |
- NA |
- 4872_VC_N_0878 |
-
-
- | 9 |
- HB_147_N |
- N |
- NA |
- 5021_VC_N_0852 |
-
-
- | 10 |
- HB_161_N |
- N |
- NA |
- 5077_VC_N_0851 |
-
-
- | 11 |
- HB_162_N |
- N |
- NA |
- 5081_VC_N_1021 |
-
-
- | 12 |
- HB_166_N |
- N |
- NA |
- 5095_VC_N_1024 |
-
-
- | 13 |
- HB_183_N |
- N |
- NA |
- 5162_VC_N_0850 |
-
-
- | 14 |
- HB_206_N |
- N |
- NA |
- 5245_VC_N_0849 |
-
-
- | 15 |
- HB_215_N |
- N |
- NA |
- 5270_VC_N_0848 |
-
-
- | 16 |
- HB_218_N |
- N |
- NA |
- 5276_CR_N_0912 |
-
-
- | 17 |
- HB_223_N |
- N |
- NA |
- 5287_VC_N_0916 |
-
-
- | 18 |
- HB_226_N |
- N |
- NA |
- 5294_VC_N_0919 |
-
-
- | 19 |
- HB_241_N |
- N |
- NA |
- 5326_CR_N_0652 |
-
-
- | 20 |
- HB_243_N |
- N |
- NA |
- 5333_VC_N_1262 |
-
-
- | 21 |
- HB_247_N |
- N |
- NA |
- 5341_VC_N_0923 |
-
-
- | 22 |
- HB_257_N |
- N |
- NA |
- 5368_PF_N_1032 |
-
-
- | 23 |
- HB_264_N |
- N |
- NA |
- 5384_VC_N_0924 |
-
-
- | 24 |
- HB_295_N |
- N |
- NA |
- 5452_VC_N_1268 |
-
-
- | 25 |
- HB_300_N |
- N |
- NA |
- 5463_VC_N_0845 |
-
-
- | 26 |
- HB_311_N |
- N |
- NA |
- 5489_CR_N_0942 |
-
-
- | 27 |
- HB_324_N |
- N |
- NA |
- 5531_VC_N_0844 |
-
-
- | 28 |
- HB_332_N |
- N |
- NA |
- 5547_VC_N_0843 |
-
-
- | 29 |
- HB_340_N |
- N |
- NA |
- 5568_VC_N_0842 |
-
-
- | 30 |
- HB_360_N |
- N |
- NA |
- 5619_CR_N_0645 |
-
-
- | 31 |
- HB_365_N |
- N |
- NA |
- 5632_VC_N_0838 |
-
-
- | 32 |
- HB_367_N |
- N |
- NA |
- 5637_VC_N_0837 |
-
-
- | 33 |
- HB_382_N |
- N |
- NA |
- 5684_PF_N_1270 |
-
-
- | 34 |
- HB_396_N |
- N |
- NA |
- 5718_VC_N_0956 |
-
-
- | 35 |
- HB_398_N |
- N |
- NA |
- 5722_VC_N_1044 |
-
-
- | 36 |
- HB_400_N |
- N |
- NA |
- 5726_VC_N_0834_Bis |
-
-
- | 37 |
- HB_403_N |
- N |
- NA |
- 5734_VC_N_0833 |
-
-
- | 38 |
- HB_414_N |
- N |
- NA |
- 5772_VC_N_0832_Bis |
-
-
- | 39 |
- HB_416_N |
- N |
- NA |
- 5778_CR_N_0962 |
-
-
- | 40 |
- HB_418_N |
- N |
- NA |
- 5789_PF_N_1273 |
-
-
- | 41 |
- HB_421_N |
- N |
- NA |
- 5799_VC_N_1058 |
-
-
- | 42 |
- HB_423_N |
- N |
- NA |
- 5803_VC_N_0966 |
-
-
- | 43 |
- HB_426_N |
- N |
- NA |
- 5806_PF_N_1064 |
-
-
- | 44 |
- HB_427_N |
- N |
- NA |
- 5810_CR_N_0636 |
-
-
- | 45 |
- HB_431_N |
- N |
- NA |
- 5823_VC_N_0829 |
-
-
- | 46 |
- HB_432_N |
- N |
- NA |
- 5826_VC_N_0828 |
-
-
- | 47 |
- HB_433_N |
- N |
- NA |
- 5827_VC_N_0827 |
-
-
- | 48 |
- HB_436_N |
- N |
- NA |
- 5832_PF_N_1145 |
-
-
- | 49 |
- HB_443_N |
- N |
- NA |
- 5852_VC_N_0826 |
-
-
- | 50 |
- HB_446_N |
- N |
- NA |
- 5859_VC_N_0825 |
-
-
- | 51 |
- HB_449_N |
- N |
- NA |
- 5866_VC_N_0824 |
-
-
- | 52 |
- HB_450_N |
- N |
- NA |
- 5867_VC_N_1277 |
-
-
- | 53 |
- HB_453_N |
- N |
- NA |
- 5876_VC_N_0823 |
-
-
- | 54 |
- HB_462_N |
- N |
- NA |
- 5903_VC_N_0822 |
-
-
- | 55 |
- HB_464_N |
- N |
- NA |
- 5905_VC_N_0820 |
-
-
- | 56 |
- HB_468_N |
- N |
- NA |
- 5912_VC_N_1286 |
-
-
- | 57 |
- HB_472_N |
- N |
- NA |
- 5925_VC_N_1289 |
-
-
- | 58 |
- HB_475_N |
- N |
- NA |
- 5936_VC_N_0979 |
-
-
- | 59 |
- HB_476_N |
- N |
- NA |
- 5938_VC_N_0819 |
-
-
- | 60 |
- HB_480_N |
- N |
- NA |
- 5946_VC_N_0985 |
-
-
- | 61 |
- HB_485_N |
- N |
- NA |
- 5959_VC_N_0818 |
-
-
- | 62 |
- HB_486_N |
- N |
- NA |
- 5963_VC_N_0987 |
-
-
- | 63 |
- HB_495_N |
- N |
- NA |
- 5980_VC_N_0989 |
-
-
- | 64 |
- HB_497_N |
- N |
- NA |
- 5985_VC_N_0990 |
-
-
- | 65 |
- HB_500_N |
- N |
- NA |
- 5990_VC_N_0817 |
-
-
- | 66 |
- HB_501_N |
- N |
- NA |
- 5991_VC_N_0816 |
-
-
- | 67 |
- HB_504_N |
- N |
- NA |
- 5996_VC_N_0815 |
-
-
- | 68 |
- HB_505_N |
- N |
- NA |
- 5998_VC_N_0814 |
-
-
- | 69 |
- HB_507_N |
- N |
- NA |
- 6006_VC_N_0813 |
-
-
- | 70 |
- HB_508_N |
- N |
- NA |
- 6007_CR_N_0618 |
-
-
- | 71 |
- HB_509_N |
- N |
- NA |
- 6008_PF_N_1081 |
-
-
- | 72 |
- HB_512_N |
- N |
- NA |
- 6023_PF_N_1155 |
-
-
- | 73 |
- HB_516_N |
- N |
- NA |
- 6030_VC_N_0810 |
-
-
- | 74 |
- HB_519_N |
- N |
- NA |
- 6034_VC_N_0809 |
-
-
- | 75 |
- HB_532_N |
- N |
- NA |
- 6060_VC_N_1292 |
-
-
- | 76 |
- HB_541_N |
- N |
- NA |
- 6092_VC_N_1001 |
-
-
- | 77 |
- HB_542_N |
- N |
- NA |
- 6096_VC_N_0807 |
-
-
- | 78 |
- HB_544_N |
- N |
- NA |
- 6101_CR_N_1161 |
-
-
- | 79 |
- HB_547_N |
- N |
- NA |
- 6110_VC_N_1295 |
-
-
- | 80 |
- HB_551_N |
- N |
- NA |
- 6124_VC_N_0806 |
-
-
- | 81 |
- HB_557_N |
- N |
- NA |
- 6134_PF_N_1297 |
-
-
- | 82 |
- HB_560_N |
- N |
- NA |
- 6142_VC_N_0805 |
-
-
- | 83 |
- HB_569_N |
- N |
- NA |
- 6166_VC_N_0804 |
-
-
- | 84 |
- HB_570_N |
- N |
- NA |
- 6170_VC_N_0803 |
-
-
- | 85 |
- HB_572_N |
- N |
- NA |
- 6172_VC_N_1008 |
-
-
- | 86 |
- HB_577_N |
- N |
- NA |
- 6182_VC_N_1166 |
-
-
- | 87 |
- HB_579_N |
- N |
- NA |
- 6187_CR_N_0607 |
-
-
- | 88 |
- HB_581_N |
- N |
- NA |
- 6191_VC_N_1010 |
-
-
- | 89 |
- HB_584_N |
- N |
- NA |
- 6196_CR_N_0605 |
-
-
- | 90 |
- HB_586_N |
- N |
- NA |
- 6200_VC_N_0799 |
-
-
- | 91 |
- HB_587_N |
- N |
- NA |
- 6206_PF_N_1176 |
-
-
- | 92 |
- HB_589_N |
- N |
- NA |
- 6213_VC_N_0798 |
-
-
- | 93 |
- HB_601_N |
- N |
- NA |
- 6241_VC_N_0796 |
-
-
- | 94 |
- HB_604_N |
- N |
- NA |
- 6260_VC_N_0794 |
-
-
- | 95 |
- HB_609_N |
- N |
- NA |
- 6270_VC_N_0793 |
-
-
- | 96 |
- HB_618_N |
- N |
- NA |
- 6289_VC_N_0791 |
-
-
- | 97 |
- HB_622_N |
- N |
- NA |
- 6310_VC_N_0790 |
-
-
- | 98 |
- HB_625_N |
- N |
- NA |
- 6314_VC_N_0789 |
-
-
- | 99 |
- HB_637_N |
- N |
- NA |
- 6340_VC_N_0786 |
-
-
- | 100 |
- HB_638_N |
- N |
- NA |
- 6341_VC_N_0785 |
-
-
- | 101 |
- HB_640_N |
- N |
- NA |
- 6347_VC_N_0784 |
-
-
- | 102 |
- HB_641_N |
- N |
- NA |
- 6356_VC_N_0783 |
-
-
- | 103 |
- HB_643_N |
- N |
- NA |
- 6363_VC_N_0781 |
-
-
- | 104 |
- HB_644_N |
- N |
- NA |
- 6366_VC_N_0780 |
-
-
- | 105 |
- HB_645_N |
- N |
- NA |
- 6374_VC_N_0779 |
-
-
- | 106 |
- HB_650_N |
- N |
- NA |
- 6384_VC_N_0777 |
-
-
- | 107 |
- HB_651_N |
- N |
- NA |
- 6386_VC_N_0776 |
-
-
- | 108 |
- HB_653_N |
- N |
- NA |
- 6388_VC_N_0775 |
-
-
- | 109 |
- HB_659_N |
- N |
- NA |
- 6406_VC_N_1180 |
-
-
- | 110 |
- HB_662_N |
- N |
- NA |
- 6411_VC_N_0771 |
-
-
- | 111 |
- HB_663_N |
- N |
- NA |
- 6415_VC_N_0770 |
-
-
- | 112 |
- HB_670_N |
- N |
- NA |
- 6436_VC_N_0769 |
-
-
- | 113 |
- HB_687_N |
- N |
- NA |
- 6484_VC_N_0765 |
-
-
- | 114 |
- HB_689_N |
- N |
- NA |
- 6486_VC_N_0764 |
-
-
- | 115 |
- HB_694_N |
- N |
- NA |
- 6500_VC_N_0763 |
-
-
- | 116 |
- HB_697_N |
- N |
- NA |
- 6512_VC_N_0762 |
-
-
- | 117 |
- HB_700_N |
- N |
- NA |
- 6520_VC_N_0761 |
-
-
- | 118 |
- HB_711_N |
- N |
- NA |
- 6543_PF_N_1191 |
-
-
- | 119 |
- HB_714_N |
- N |
- NA |
- 6549_VC_N_1198 |
-
-
- | 120 |
- HB_717_N |
- N |
- NA |
- 6553_PF_N_2284 |
-
-
- | 121 |
- HB_721_N |
- N |
- NA |
- 6560_VC_N_2578 |
-
-
- | 122 |
- HB_726_N |
- N |
- NA |
- 6573_PF_N_2293 |
-
-
- | 123 |
- HB_730_N |
- N |
- NA |
- 6580_VC_N_2306 |
-
-
- | 124 |
- HB_735_N |
- N |
- NA |
- 6588_VC_N_1213 |
-
-
- | 125 |
- HB_737_N |
- N |
- NA |
- 6593_VC_N_1219 |
-
-
- | 126 |
- HB_738_N |
- N |
- NA |
- 6594_VC_N_1222 |
-
-
- | 127 |
- HB_759_N |
- N |
- NA |
- 6645_VC_N_1231 |
-
-
- | 128 |
- HB_764_N |
- N |
- NA |
- 6655_VC_N_1240 |
-
-
- | 129 |
- HB_765_N |
- N |
- NA |
- 6656_VC_N_1243 |
-
-
- | 130 |
- HB_767_N |
- N |
- NA |
- 6661_PF_N_2341 |
-
-
- | 131 |
- HB_770_N |
- N |
- NA |
- 6669_VC_N_1246 |
-
-
- | 132 |
- HB_772_N |
- N |
- NA |
- 6676_PF_N_1248 |
-
-
- | 133 |
- HB_001_HD |
- HD |
- F |
- 2028_CR_H_2282 |
-
-
- | 134 |
- HB_003_HD |
- HD |
- F |
- 2685_PF_H_2212 |
-
-
- | 135 |
- HB_004_HD |
- HD |
- M |
- 2706_CR_H_2432 |
-
-
- | 136 |
- HB_006_HD |
- HD |
- M |
- 2737_VC_H_2194 |
-
-
- | 137 |
- HB_007_HD |
- HD |
- NA |
- 2769_VC_H_2193 |
-
-
- | 138 |
- HB_008_HD |
- HD |
- F |
- 2790_CR_H_1890 |
-
-
- | 139 |
- HB_009_HD |
- HD |
- NA |
- 2879_VC_H_2192 |
-
-
- | 140 |
- HB_010_HD |
- HD |
- M |
- 2960_VC_H_2002 |
-
-
- | 141 |
- HB_011_HD |
- HD |
- F |
- 3053_VC_H_2001 |
-
-
- | 142 |
- HB_012_HD |
- HD |
- F |
- 3128_VC_H_1999 |
-
-
- | 143 |
- HB_014_HD |
- HD |
- F |
- 3149_PF_H_2110 |
-
-
- | 144 |
- HB_015_HD |
- HD |
- F |
- 3150_VC_H_1996 |
-
-
- | 145 |
- HB_016_HD |
- HD |
- F |
- 3177_VC_H_2191 |
-
-
- | 146 |
- HB_017_HD |
- HD |
- NA |
- 3195_VC_H_2190 |
-
-
- | 147 |
- HB_018_HD |
- HD |
- M |
- 3200_VC_H_2189 |
-
-
- | 148 |
- HB_019_HD |
- HD |
- M |
- 3209_VC_H_2188 |
-
-
- | 149 |
- HB_020_HD |
- HD |
- M |
- 3224_VC_H_1994 |
-
-
- | 150 |
- HB_022_HD |
- HD |
- F |
- 3242_PF_H_2105 |
-
-
- | 151 |
- HB_024_HD |
- HD |
- NA |
- 3272_VC_H_2186 |
-
-
- | 152 |
- HB_027_HD |
- HD |
- M |
- 3356_VC_H_2439 |
-
-
- | 153 |
- HB_028_HD |
- HD |
- F |
- 3394_PF_H_2104 |
-
-
- | 154 |
- HB_031_HD |
- HD |
- M |
- 3430_VC_H_1990 |
-
-
- | 155 |
- HB_032_HD |
- HD |
- NA |
- 3444_PF_H_2208 |
-
-
- | 156 |
- HB_034_HD |
- HD |
- F |
- 3482_VC_H_1987 |
-
-
- | 157 |
- HB_036_HD |
- HD |
- M |
- 3576_VC_H_1984 |
-
-
- | 158 |
- HB_037_HD |
- HD |
- F |
- 3579_VC_H_1983 |
-
-
- | 159 |
- HB_038_HD |
- HD |
- F |
- 3584_VC_H_2183 |
-
-
- | 160 |
- HB_039_HD |
- HD |
- NA |
- 3635_VC_H_2182 |
-
-
- | 161 |
- HB_041_HD |
- HD |
- F |
- 3695_CR_H_2267 |
-
-
- | 162 |
- HB_042_HD |
- HD |
- M |
- 3697_VC_H_1982 |
-
-
- | 163 |
- HB_043_HD |
- HD |
- NA |
- 3703_VC_H_2180 |
-
-
- | 164 |
- HB_044_HD |
- HD |
- NA |
- 3723_VC_H_2179 |
-
-
- | 165 |
- HB_046_HD |
- HD |
- F |
- 3735_VC_H_1981 |
-
-
- | 166 |
- HB_050_HD |
- HD |
- M |
- 3820_PF_H_2207 |
-
-
- | 167 |
- HB_051_HD |
- HD |
- F |
- 3849_CR_H_2262 |
-
-
- | 168 |
- HB_054_HD |
- HD |
- M |
- 3884_VC_H_2175 |
-
-
- | 169 |
- HB_056_HD |
- HD |
- NA |
- 4012_VC_H_2174 |
-
-
- | 170 |
- HB_057_HD |
- HD |
- NA |
- 4013_VC_H_2173 |
-
-
- | 171 |
- HB_059_HD |
- HD |
- NA |
- 4066_VC_H_2172 |
-
-
- | 172 |
- HB_060_HD |
- HD |
- NA |
- 4094_VC_H_2171 |
-
-
- | 173 |
- HB_061_HD |
- HD |
- F |
- 4116_VC_H_2170 |
-
-
- | 174 |
- HB_062_HD |
- HD |
- NA |
- 4121_VC_H_2169 |
-
-
- | 175 |
- HB_063_HD |
- HD |
- NA |
- 4215_VC_H_2167 |
-
-
- | 176 |
- HB_065_HD |
- HD |
- M |
- 4340_PF_H_2091 |
-
-
- | 177 |
- HB_066_HD |
- HD |
- F |
- 4344_VC_H_1977 |
-
-
- | 178 |
- HB_067_HD |
- HD |
- M |
- 4346_VC_H_2165 |
-
-
- | 179 |
- HB_069_HD |
- HD |
- F |
- 4356_VC_H_2164 |
-
-
- | 180 |
- HB_070_HD |
- HD |
- NA |
- 4386_CR_H_2249 |
-
-
- | 181 |
- HB_072_HD |
- HD |
- NA |
- 4404_VC_H_2161 |
-
-
- | 182 |
- HB_073_HD |
- HD |
- F |
- 4411_VC_H_1975 |
-
-
- | 183 |
- HB_074_HD |
- HD |
- NA |
- 4430_VC_H_2465 |
-
-
- | 184 |
- HB_075_HD |
- HD |
- M |
- 4470_VC_H_1974 |
-
-
- | 185 |
- HB_076_HD |
- HD |
- F |
- 4497_CR_H_1860 |
-
-
- | 186 |
- HB_077_HD |
- HD |
- M |
- 4509_CR_H_2244 |
-
-
- | 187 |
- HB_079_HD |
- HD |
- M |
- 4631_VC_H_1971 |
-
-
- | 188 |
- HB_080_HD |
- HD |
- F |
- 4653_PF_H_2083 |
-
-
- | 189 |
- HB_081_HD |
- HD |
- NA |
- 4678_CR_H_2242 |
-
-
- | 190 |
- HB_084_HD |
- HD |
- M |
- 4718_VC_H_2125 |
-
-
- | 191 |
- HB_090_HD |
- HD |
- NA |
- 4740_CR_H_2474 |
-
-
- | 192 |
- HB_094_HD |
- HD |
- NA |
- 4754_CR_H_2476 |
-
-
- | 193 |
- HB_098_HD |
- HD |
- NA |
- 4780_VC_H_2151 |
-
-
- | 194 |
- HB_101_HD |
- HD |
- F |
- 4809_VC_H_2148 |
-
-
- | 195 |
- HB_105_HD |
- HD |
- NA |
- 4819_CR_H_2238 |
-
-
- | 196 |
- HB_106_HD |
- HD |
- F |
- 4822_VC_H_1969 |
-
-
- | 197 |
- HB_108_HD |
- HD |
- M |
- 4826_VC_H_1968 |
-
-
- | 198 |
- HB_109_HD |
- HD |
- M |
- 4828_VC_H_2124 |
-
-
- | 199 |
- HB_115_HD |
- HD |
- NA |
- 4855_CR_H_2235 |
-
-
- | 200 |
- HB_121_HD |
- HD |
- F |
- 4902_VC_H_1967 |
-
-
- | 201 |
- HB_129_HD |
- HD |
- NA |
- 4938_VC_H_1966 |
-
-
- | 202 |
- HB_141_HD |
- HD |
- F |
- 4996_PF_H_2076 |
-
-
- | 203 |
- HB_152_HD |
- HD |
- NA |
- 5034_CR_H_2233 |
-
-
- | 204 |
- HB_153_HD |
- HD |
- M |
- 5043_VC_H_1960 |
-
-
- | 205 |
- HB_159_HD |
- HD |
- M |
- 5062_VC_H_1959 |
-
-
- | 206 |
- HB_172_HD |
- HD |
- F |
- 5114_PF_H_2070 |
-
-
- | 207 |
- HB_175_HD |
- HD |
- M |
- 5127_PF_H_2068 |
-
-
- | 208 |
- HB_180_HD |
- HD |
- M |
- 5148_VC_H_1944 |
-
-
- | 209 |
- HB_185_HD |
- HD |
- F |
- 5167_CR_H_2231 |
-
-
- | 210 |
- HB_188_HD |
- HD |
- F |
- 5172_VC_H_1951 |
-
-
- | 211 |
- HB_191_HD |
- HD |
- M |
- 5180_VC_H_1949 |
-
-
- | 212 |
- HB_196_HD |
- HD |
- NA |
- 5199_PF_H_2202 |
-
-
- | 213 |
- HB_203_HD |
- HD |
- F |
- 5228_PF_H_2059 |
-
-
- | 214 |
- HB_207_HD |
- HD |
- NA |
- 5248_PF_H_2201 |
-
-
- | 215 |
- HB_228_HD |
- HD |
- F |
- 5299_CR_H_2228 |
-
-
- | 216 |
- HB_233_HD |
- HD |
- M |
- 5312_VC_H_1938 |
-
-
- | 217 |
- HB_235_HD |
- HD |
- F |
- 5316_VC_H_1937 |
-
-
- | 218 |
- HB_242_HD |
- HD |
- F |
- 5328_PF_H_2048 |
-
-
- | 219 |
- HB_266_HD |
- HD |
- M |
- 5387_VC_H_1928 |
-
-
- | 220 |
- HB_271_HD |
- HD |
- M |
- 5394_PF_H_2039 |
-
-
- | 221 |
- HB_272_HD |
- HD |
- F |
- 5396_VC_H_1925 |
-
-
- | 222 |
- HB_279_HD |
- HD |
- F |
- 5409_VC_H_1924 |
-
-
- | 223 |
- HB_294_HD |
- HD |
- M |
- 5448_VC_H_1921 |
-
-
- | 224 |
- HB_301_HD |
- HD |
- NA |
- 5464_VC_H_1919 |
-
-
- | 225 |
- HB_304_HD |
- HD |
- F |
- 5471_VC_H_1918 |
-
-
- | 226 |
- HB_321_HD |
- HD |
- NA |
- 5522_PF_H_2199 |
-
-
- | 227 |
- HB_361_HD |
- HD |
- F |
- 5622_VC_H_2121 |
-
-
- | 228 |
- HB_370_HD |
- HD |
- M |
- 5645_VC_H_1904 |
-
-
- | 229 |
- HB_371_HD |
- HD |
- F |
- 5648_PF_H_2016 |
-
-
- | 230 |
- HB_384_HD |
- HD |
- F |
- 5688_PF_H_2012 |
-
-
- | 231 |
- HB_390_HD |
- HD |
- M |
- 5704_PF_H_2009 |
-
-
- | 232 |
- HB_393_HD |
- HD |
- F |
- 5709_VC_H_1895 |
-
-
- | 233 |
- HB_402_HD |
- HD |
- F |
- 5732_PF_H_2007 |
-
-
- | 234 |
- HB_405_HD |
- HD |
- NA |
- 5742_PF_H_2006 |
-
-
- | 235 |
- HB_407_HD |
- HD |
- M |
- 5745_PF_H_2005 |
-
-
- | 236 |
- HB_408_HD |
- HD |
- M |
- 5747_VC_H_1891 |
-
-
- | 237 |
- HB_415_HD |
- HD |
- NA |
- 5777_PF_H_1551 |
-
-
- | 238 |
- HB_417_HD |
- HD |
- M |
- 5784_PF_H_1554 |
-
-
- | 239 |
- HB_424_HD |
- HD |
- M |
- 5804_VC_H_1558 |
-
-
- | 240 |
- HB_444_HD |
- HD |
- M |
- 5856_VC_H_1567 |
-
-
- | 241 |
- HB_457_HD |
- HD |
- M |
- 5896_VC_H_1570 |
-
-
- | 242 |
- HB_466_HD |
- HD |
- M |
- 5910_PF_H_1572 |
-
-
- | 243 |
- HB_478_HD |
- HD |
- M |
- 5941_CR_H_1583 |
-
-
- | 244 |
- HB_487_HD |
- HD |
- F |
- 5964_VC_H_1597 |
-
-
- | 245 |
- HB_511_HD |
- HD |
- M |
- 6019_PF_H_2198 |
-
-
- | 246 |
- HB_513_HD |
- HD |
- F |
- 6024_VC_H_1612 |
-
-
- | 247 |
- HB_515_HD |
- HD |
- F |
- 6028_CR_H_1613 |
-
-
- | 248 |
- HB_518_HD |
- HD |
- M |
- 6033_VC_H_1618 |
-
-
- | 249 |
- HB_522_HD |
- HD |
- M |
- 6037_PF_H_1626 |
-
-
- | 250 |
- HB_527_HD |
- HD |
- F |
- 6047_VC_H_1639 |
-
-
- | 251 |
- HB_528_HD |
- HD |
- M |
- 6051_PF_H_1641 |
-
-
- | 252 |
- HB_530_HD |
- HD |
- M |
- 6054_VC_H_1648 |
-
-
- | 253 |
- HB_537_HD |
- HD |
- F |
- 6071_PF_H_1653 |
-
-
- | 254 |
- HB_549_HD |
- HD |
- M |
- 6119_CR_H_1670 |
-
-
- | 255 |
- HB_593_HD |
- HD |
- NA |
- 6219_CR_H_2567 |
-
-
- | 256 |
- HB_610_HD |
- HD |
- NA |
- 6275_PF_H_1692 |
-
-
- | 257 |
- HB_616_HD |
- HD |
- F |
- 6284_CR_H_1694 |
-
-
- | 258 |
- HB_626_HD |
- HD |
- M |
- 6315_VC_H_1702 |
-
-
- | 259 |
- HB_639_HD |
- HD |
- F |
- 6344_CR_H_1703 |
-
-
- | 260 |
- HB_649_HD |
- HD |
- F |
- 6382_CR_H_1709 |
-
-
- | 261 |
- HB_661_HD |
- HD |
- M |
- 6408_VC_H_1714 |
-
-
- | 262 |
- HB_682_HD |
- HD |
- M |
- 6467_PF_H_1725 |
-
-
- | 263 |
- HB_683_HD |
- HD |
- M |
- 6472_VC_H_1729 |
-
-
- | 264 |
- HB_691_HD |
- HD |
- F |
- 6493_VC_H_1732 |
-
-
- | 265 |
- HB_692_HD |
- HD |
- M |
- 6495_CR_H_1733 |
-
-
- | 266 |
- HB_707_HD |
- HD |
- M |
- 6535_PF_H_1737 |
-
-
- | 267 |
- HB_709_HD |
- HD |
- F |
- 6539_CR_H_1739 |
-
-
- | 268 |
- HB_725_HD |
- HD |
- M |
- 6572_PF_H_1746 |
-
-
- | 269 |
- HB_732_HD |
- HD |
- F |
- 6584_VC_H_1750 |
-
-
- | 270 |
- HB_734_HD |
- HD |
- F |
- 6587_CR_H_1751 |
-
-
- | 271 |
- HB_748_HD |
- HD |
- NA |
- 6615_VC_H_2315 |
-
-
- | 272 |
- HB_750_HD |
- HD |
- NA |
- 6628_PF_H_2326 |
-
-
- | 273 |
- HB_758_HD |
- HD |
- NA |
- 6643_VC_H_2602 |
-
-
- | 274 |
- HB_760_HD |
- HD |
- M |
- 6646_PF_H_1761 |
-
-
- | 275 |
- HB_762_HD |
- HD |
- M |
- 6650_VC_H_1765 |
-
-
- | 276 |
- HB_766_HD |
- HD |
- M |
- 6658_VC_H_1768 |
-
-
- | 277 |
- HB_768_HD |
- HD |
- NA |
- 6663_VC_H_1771 |
-
-
- | 278 |
- HB_769_HD |
- HD |
- M |
- 6666_VC_H_1774 |
-
-
- | 279 |
- HB_774_HD |
- HD |
- NA |
- 6689_PF_H_2344 |
-
-
- | 280 |
- HB_778_HD |
- HD |
- NA |
- 6696_PF_H_2356 |
-
-
- | 281 |
- HB_780_HD |
- HD |
- NA |
- 6704_PF_H_2362 |
-
-
- | 282 |
- HB_790_HD |
- HD |
- NA |
- 6788_PF_H_2389 |
-
-
- | 283 |
- HB_800_HD |
- HD |
- NA |
- 6807_PF_H_2419 |
-
-
- | 284 |
- HB_802_HD |
- HD |
- NA |
- 6811_PF_H_2425 |
-
-
- | 285 |
- HB_045_AD |
- AD |
- NA |
- 3734_CR_A_0122 |
-
-
- | 286 |
- HB_048_AD |
- AD |
- NA |
- 3791_CR_A_0128 |
-
-
- | 287 |
- HB_053_AD |
- AD |
- NA |
- 3877_CR_A_0134 |
-
-
- | 288 |
- HB_055_AD |
- AD |
- NA |
- 3893_VC_A_0142 |
-
-
- | 289 |
- HB_068_AD |
- AD |
- NA |
- 4349_VC_A_0148 |
-
-
- | 290 |
- HB_082_AD |
- AD |
- NA |
- 4712_CR_A_0309 |
-
-
- | 291 |
- HB_085_AD |
- AD |
- NA |
- 4726_VC_A_0311 |
-
-
- | 292 |
- HB_087_AD |
- AD |
- NA |
- 4730_CR_A_0315 |
-
-
- | 293 |
- HB_089_AD |
- AD |
- NA |
- 4733_VC_A_0320 |
-
-
- | 294 |
- HB_093_AD |
- AD |
- NA |
- 4749_VC_A_0323 |
-
-
- | 295 |
- HB_095_AD |
- AD |
- NA |
- 4759_CR_A_0327 |
-
-
- | 296 |
- HB_097_AD |
- AD |
- NA |
- 4773_CR_A_0866 |
-
-
- | 297 |
- HB_099_AD |
- AD |
- NA |
- 4785_VC_A_0332 |
-
-
- | 298 |
- HB_100_AD |
- AD |
- NA |
- 4795_VC_A_0335 |
-
-
- | 299 |
- HB_103_AD |
- AD |
- NA |
- 4811_VC_A_0341 |
-
-
- | 300 |
- HB_104_AD |
- AD |
- NA |
- 4813_CR_A_0345 |
-
-
- | 301 |
- HB_112_AD |
- AD |
- NA |
- 4842_VC_A_0870 |
-
-
- | 302 |
- HB_113_AD |
- AD |
- NA |
- 4850_CR_A_0351 |
-
-
- | 303 |
- HB_114_AD |
- AD |
- NA |
- 4852_CR_A_0354 |
-
-
- | 304 |
- HB_117_AD |
- AD |
- NA |
- 4868_VC_A_0874 |
-
-
- | 305 |
- HB_122_AD |
- AD |
- NA |
- 4904_CR_A_1132 |
-
-
- | 306 |
- HB_123_AD |
- AD |
- NA |
- 4905_VC_A_0884 |
-
-
- | 307 |
- HB_124_AD |
- AD |
- NA |
- 4916_VC_A_0886 |
-
-
- | 308 |
- HB_125_AD |
- AD |
- NA |
- 4917_CR_A_0360 |
-
-
- | 309 |
- HB_126_AD |
- AD |
- NA |
- 4921_VC_A_0362 |
-
-
- | 310 |
- HB_128_AD |
- AD |
- NA |
- 4936_CR_A_0369 |
-
-
- | 311 |
- HB_130_AD |
- AD |
- NA |
- 4939_VC_A_0888 |
-
-
- | 312 |
- HB_131_AD |
- AD |
- NA |
- 4944_CR_A_0889 |
-
-
- | 313 |
- HB_132_AD |
- AD |
- NA |
- 4946_CR_A_0372 |
-
-
- | 314 |
- HB_134_AD |
- AD |
- NA |
- 4951_CR_A_0891 |
-
-
- | 315 |
- HB_135_AD |
- AD |
- NA |
- 4953_VC_A_0893 |
-
-
- | 316 |
- HB_136_AD |
- AD |
- NA |
- 4965_VC_A_0160 |
-
-
- | 317 |
- HB_137_AD |
- AD |
- NA |
- 4966_VC_A_0374 |
-
-
- | 318 |
- HB_138_AD |
- AD |
- NA |
- 4969_VC_A_0895 |
-
-
- | 319 |
- HB_140_AD |
- AD |
- NA |
- 4993_CR_A_0896 |
-
-
- | 320 |
- HB_146_AD |
- AD |
- NA |
- 5018_CR_A_0384 |
-
-
- | 321 |
- HB_148_AD |
- AD |
- NA |
- 5022_VC_A_0386 |
-
-
- | 322 |
- HB_150_AD |
- AD |
- NA |
- 5031_VC_A_0392 |
-
-
- | 323 |
- HB_151_AD |
- AD |
- NA |
- 5033_CR_A_0396 |
-
-
- | 324 |
- HB_154_AD |
- AD |
- NA |
- 5048_VC_A_1321 |
-
-
- | 325 |
- HB_155_AD |
- AD |
- NA |
- 5056_VC_A_0398 |
-
-
- | 326 |
- HB_156_AD |
- AD |
- NA |
- 5057_VC_A_0163 |
-
-
- | 327 |
- HB_157_AD |
- AD |
- NA |
- 5059_VC_A_0401 |
-
-
- | 328 |
- HB_158_AD |
- AD |
- NA |
- 5061_PF_A_2612 |
-
-
- | 329 |
- HB_160_AD |
- AD |
- NA |
- 5064_PF_A_2615 |
-
-
- | 330 |
- HB_165_AD |
- AD |
- NA |
- 5092_CR_A_0899 |
-
-
- | 331 |
- HB_168_AD |
- AD |
- NA |
- 5097_VC_A_0407 |
-
-
- | 332 |
- HB_170_AD |
- AD |
- NA |
- 5101_VC_A_0410 |
-
-
- | 333 |
- HB_174_AD |
- AD |
- NA |
- 5124_PF_A_1343 |
-
-
- | 334 |
- HB_179_AD |
- AD |
- NA |
- 5145_VC_A_1351 |
-
-
- | 335 |
- HB_181_AD |
- AD |
- NA |
- 5152_CR_A_0414 |
-
-
- | 336 |
- HB_184_AD |
- AD |
- NA |
- 5166_VC_A_1354 |
-
-
- | 337 |
- HB_194_AD |
- AD |
- NA |
- 5193_VC_A_1360 |
-
-
- | 338 |
- HB_197_AD |
- AD |
- NA |
- 5202_CR_A_1368 |
-
-
- | 339 |
- HB_199_AD |
- AD |
- NA |
- 5205_VC_A_0166 |
-
-
- | 340 |
- HB_200_AD |
- AD |
- NA |
- 5210_VC_A_0905 |
-
-
- | 341 |
- HB_205_AD |
- AD |
- NA |
- 5235_VC_A_0419 |
-
-
- | 342 |
- HB_208_AD |
- AD |
- NA |
- 5249_VC_A_0422 |
-
-
- | 343 |
- HB_209_AD |
- AD |
- NA |
- 5252_VC_A_0907 |
-
-
- | 344 |
- HB_211_AD |
- AD |
- NA |
- 5257_VC_A_0169 |
-
-
- | 345 |
- HB_216_AD |
- AD |
- NA |
- 5272_VC_A_0425 |
-
-
- | 346 |
- HB_219_AD |
- AD |
- NA |
- 5279_CR_A_0147 |
-
-
- | 347 |
- HB_221_AD |
- AD |
- NA |
- 5283_VC_A_0145 |
-
-
- | 348 |
- HB_222_AD |
- AD |
- NA |
- 5285_VC_A_0141 |
-
-
- | 349 |
- HB_224_AD |
- AD |
- NA |
- 5288_VC_A_0428 |
-
-
- | 350 |
- HB_230_AD |
- AD |
- NA |
- 5301_VC_A_0174 |
-
-
- | 351 |
- HB_231_AD |
- AD |
- NA |
- 5305_VC_A_1384 |
-
-
- | 352 |
- HB_232_AD |
- AD |
- NA |
- 5310_CR_A_0176 |
-
-
- | 353 |
- HB_234_AD |
- AD |
- NA |
- 5313_PF_A_2618 |
-
-
- | 354 |
- HB_236_AD |
- AD |
- NA |
- 5317_PF_A_2624 |
-
-
- | 355 |
- HB_238_AD |
- AD |
- NA |
- 5322_CR_A_2632 |
-
-
- | 356 |
- HB_240_AD |
- AD |
- NA |
- 5325_VC_A_0137 |
-
-
- | 357 |
- HB_244_AD |
- AD |
- NA |
- 5337_VC_A_1387 |
-
-
- | 358 |
- HB_245_AD |
- AD |
- NA |
- 5339_VC_A_0181 |
-
-
- | 359 |
- HB_250_AD |
- AD |
- NA |
- 5346_VC_A_1393 |
-
-
- | 360 |
- HB_251_AD |
- AD |
- NA |
- 5350_VC_A_0184 |
-
-
- | 361 |
- HB_252_AD |
- AD |
- NA |
- 5355_VC_A_0133 |
-
-
- | 362 |
- HB_253_AD |
- AD |
- NA |
- 5359_CR_A_1395 |
-
-
- | 363 |
- HB_258_AD |
- AD |
- NA |
- 5370_PF_A_1400 |
-
-
- | 364 |
- HB_259_AD |
- AD |
- NA |
- 5371_PF_A_2636 |
-
-
- | 365 |
- HB_260_AD |
- AD |
- NA |
- 5375_VC_A_0188 |
-
-
- | 366 |
- HB_263_AD |
- AD |
- NA |
- 5381_VC_A_0022 |
-
-
- | 367 |
- HB_265_AD |
- AD |
- NA |
- 5385_VC_A_1402 |
-
-
- | 368 |
- HB_267_AD |
- AD |
- NA |
- 5389_VC_A_0928 |
-
-
- | 369 |
- HB_268_AD |
- AD |
- NA |
- 5390_CR_A_0151 |
-
-
- | 370 |
- HB_273_AD |
- AD |
- NA |
- 5400_PF_A_2645 |
-
-
- | 371 |
- HB_274_AD |
- AD |
- NA |
- 5401_VC_A_0931 |
-
-
- | 372 |
- HB_275_AD |
- AD |
- NA |
- 5404_PF_A_2648 |
-
-
- | 373 |
- HB_276_AD |
- AD |
- NA |
- 5406_VC_A_0933 |
-
-
- | 374 |
- HB_277_AD |
- AD |
- NA |
- 5407_PF_A_2651 |
-
-
- | 375 |
- HB_280_AD |
- AD |
- NA |
- 5412_VC_A_0935 |
-
-
- | 376 |
- HB_281_AD |
- AD |
- NA |
- 5413_PF_A_2657 |
-
-
- | 377 |
- HB_283_AD |
- AD |
- NA |
- 5419_VC_A_0937 |
-
-
- | 378 |
- HB_284_AD |
- AD |
- NA |
- 5420_VC_A_0939 |
-
-
- | 379 |
- HB_285_AD |
- AD |
- NA |
- 5421_CR_A_0432 |
-
-
- | 380 |
- HB_286_AD |
- AD |
- NA |
- 5423_PF_A_2660 |
-
-
- | 381 |
- HB_288_AD |
- AD |
- NA |
- 5425_PF_A_2666 |
-
-
- | 382 |
- HB_289_AD |
- AD |
- NA |
- 5426_VC_A_1405 |
-
-
- | 383 |
- HB_290_AD |
- AD |
- NA |
- 5433_VC_A_0434 |
-
-
- | 384 |
- HB_296_AD |
- AD |
- NA |
- 5456_PF_A_2675 |
-
-
- | 385 |
- HB_299_AD |
- AD |
- NA |
- 5461_VC_A_0192 |
-
-
- | 386 |
- HB_302_AD |
- AD |
- NA |
- 5465_PF_A_2678 |
-
-
- | 387 |
- HB_303_AD |
- AD |
- NA |
- 5469_VC_A_1417 |
-
-
- | 388 |
- HB_305_AD |
- AD |
- NA |
- 5479_PF_A_1421 |
-
-
- | 389 |
- HB_306_AD |
- AD |
- NA |
- 5480_VC_A_0437 |
-
-
- | 390 |
- HB_307_AD |
- AD |
- NA |
- 5482_VC_A_0028 |
-
-
- | 391 |
- HB_308_AD |
- AD |
- NA |
- 5483_VC_A_0941 |
-
-
- | 392 |
- HB_309_AD |
- AD |
- NA |
- 5487_CR_A_0441 |
-
-
- | 393 |
- HB_310_AD |
- AD |
- NA |
- 5488_CR_A_0194 |
-
-
- | 394 |
- HB_312_AD |
- AD |
- NA |
- 5500_VC_A_0198 |
-
-
- | 395 |
- HB_313_AD |
- AD |
- NA |
- 5502_PF_A_2684 |
-
-
- | 396 |
- HB_315_AD |
- AD |
- NA |
- 5513_PF_A_2687 |
-
-
- | 397 |
- HB_316_AD |
- AD |
- NA |
- 5516_PF_A_2690 |
-
-
- | 398 |
- HB_317_AD |
- AD |
- NA |
- 5517_PF_A_2693 |
-
-
- | 399 |
- HB_318_AD |
- AD |
- NA |
- 5518_CR_A_0030 |
-
-
- | 400 |
- HB_319_AD |
- AD |
- NA |
- 5519_CR_A_2695 |
-
-
- | 401 |
- HB_320_AD |
- AD |
- NA |
- 5520_PF_A_2699 |
-
-
- | 402 |
- HB_322_AD |
- AD |
- NA |
- 5527_VC_A_0945 |
-
-
- | 403 |
- HB_325_AD |
- AD |
- NA |
- 5532_PF_A_2702 |
-
-
- | 404 |
- HB_328_AD |
- AD |
- NA |
- 5541_PF_A_2705 |
-
-
- | 405 |
- HB_330_AD |
- AD |
- NA |
- 5544_VC_A_0201 |
-
-
- | 406 |
- HB_334_AD |
- AD |
- NA |
- 5554_VC_A_0452 |
-
-
- | 407 |
- HB_335_AD |
- AD |
- NA |
- 5557_VC_A_0950 |
-
-
- | 408 |
- HB_337_AD |
- AD |
- NA |
- 5560_VC_A_0204 |
-
-
- | 409 |
- HB_342_AD |
- AD |
- NA |
- 5571_PF_A_1430 |
-
-
- | 410 |
- HB_345_AD |
- AD |
- NA |
- 5583_PF_A_2708 |
-
-
- | 411 |
- HB_347_AD |
- AD |
- NA |
- 5589_PF_A_2714 |
-
-
- | 412 |
- HB_349_AD |
- AD |
- NA |
- 5592_PF_A_2717 |
-
-
- | 413 |
- HB_352_AD |
- AD |
- NA |
- 5604_VC_A_0037 |
-
-
- | 414 |
- HB_353_AD |
- AD |
- NA |
- 5607_PF_A_2723 |
-
-
- | 415 |
- HB_356_AD |
- AD |
- NA |
- 5615_VC_A_0041 |
-
-
- | 416 |
- HB_357_AD |
- AD |
- NA |
- 5616_CR_A_0127 |
-
-
- | 417 |
- HB_358_AD |
- AD |
- NA |
- 5617_CR_A_0456 |
-
-
- | 418 |
- HB_359_AD |
- AD |
- NA |
- 5618_CR_A_0044 |
-
-
- | 419 |
- HB_362_AD |
- AD |
- NA |
- 5625_CR_A_2495 |
-
-
- | 420 |
- HB_363_AD |
- AD |
- NA |
- 5626_CR_A_2498 |
-
-
- | 421 |
- HB_364_AD |
- AD |
- NA |
- 5629_CR_A_0390 |
-
-
- | 422 |
- HB_369_AD |
- AD |
- NA |
- 5643_VC_A_1143 |
-
-
- | 423 |
- HB_373_AD |
- AD |
- NA |
- 5654_VC_A_0047 |
-
-
- | 424 |
- HB_375_AD |
- AD |
- NA |
- 5660_CR_A_0462 |
-
-
- | 425 |
- HB_376_AD |
- AD |
- NA |
- 5661_VC_A_0464 |
-
-
- | 426 |
- HB_377_AD |
- AD |
- NA |
- 5667_VC_A_2509 |
-
-
- | 427 |
- HB_378_AD |
- AD |
- NA |
- 5668_VC_A_1438 |
-
-
- | 428 |
- HB_383_AD |
- AD |
- NA |
- 5686_CR_A_2728 |
-
-
- | 429 |
- HB_386_AD |
- AD |
- NA |
- 5695_VC_A_0953 |
-
-
- | 430 |
- HB_389_AD |
- AD |
- NA |
- 5700_VC_A_2514 |
-
-
- | 431 |
- HB_391_AD |
- AD |
- NA |
- 5705_CR_A_0474 |
-
-
- | 432 |
- HB_392_AD |
- AD |
- NA |
- 5706_VC_A_0476 |
-
-
- | 433 |
- HB_394_AD |
- AD |
- NA |
- 5713_VC_A_0479 |
-
-
- | 434 |
- HB_397_AD |
- AD |
- NA |
- 5721_CR_A_0210 |
-
-
- | 435 |
- HB_404_AD |
- AD |
- NA |
- 5735_CR_A_0489 |
-
-
- | 436 |
- HB_406_AD |
- AD |
- NA |
- 5744_CR_A_0960 |
-
-
- | 437 |
- HB_409_AD |
- AD |
- NA |
- 5749_CR_A_0159 |
-
-
- | 438 |
- HB_410_AD |
- AD |
- NA |
- 5751_CR_A_2518 |
-
-
- | 439 |
- HB_411_AD |
- AD |
- NA |
- 5755_CR_A_2731 |
-
-
- | 440 |
- HB_413_AD |
- AD |
- NA |
- 5766_VC_A_0214 |
-
-
- | 441 |
- HB_419_AD |
- AD |
- NA |
- 5790_VC_A_0217 |
-
-
- | 442 |
- HB_420_AD |
- AD |
- NA |
- 5796_CR_A_0964 |
-
-
- | 443 |
- HB_428_AD |
- AD |
- NA |
- 5811_CR_A_2524 |
-
-
- | 444 |
- HB_429_AD |
- AD |
- NA |
- 5819_CR_A_2527 |
-
-
- | 445 |
- HB_430_AD |
- AD |
- NA |
- 5822_CR_A_2530 |
-
-
- | 446 |
- HB_434_AD |
- AD |
- NA |
- 5828_CR_A_2533 |
-
-
- | 447 |
- HB_435_AD |
- AD |
- NA |
- 5831_CR_A_0222 |
-
-
- | 448 |
- HB_437_AD |
- AD |
- NA |
- 5839_CR_A_2539 |
-
-
- | 449 |
- HB_438_AD |
- AD |
- NA |
- 5843_CR_A_0227 |
-
-
- | 450 |
- HB_439_AD |
- AD |
- NA |
- 5845_CR_A_0230 |
-
-
- | 451 |
- HB_441_AD |
- AD |
- NA |
- 5849_CR_A_0233 |
-
-
- | 452 |
- HB_442_AD |
- AD |
- NA |
- 5850_CR_A_0495 |
-
-
- | 453 |
- HB_445_AD |
- AD |
- NA |
- 5858_CR_A_0969 |
-
-
- | 454 |
- HB_448_AD |
- AD |
- NA |
- 5864_CR_A_0974 |
-
-
- | 455 |
- HB_451_AD |
- AD |
- NA |
- 5871_CR_A_2542 |
-
-
- | 456 |
- HB_454_AD |
- AD |
- NA |
- 5879_CR_A_2545 |
-
-
- | 457 |
- HB_455_AD |
- AD |
- NA |
- 5887_CR_A_0976_Bis |
-
-
- | 458 |
- HB_459_AD |
- AD |
- NA |
- 5898_CR_A_2548 |
-
-
- | 459 |
- HB_460_AD |
- AD |
- NA |
- 5900_VC_A_0237 |
-
-
- | 460 |
- HB_461_AD |
- AD |
- NA |
- 5901_CR_A_0239 |
-
-
- | 461 |
- HB_469_AD |
- AD |
- NA |
- 5914_CR_A_2554 |
-
-
- | 462 |
- HB_471_AD |
- AD |
- NA |
- 5922_VC_A_0246 |
-
-
- | 463 |
- HB_473_AD |
- AD |
- NA |
- 5927_CR_A_2560 |
-
-
- | 464 |
- HB_474_AD |
- AD |
- NA |
- 5933_VC_A_1071 |
-
-
- | 465 |
- HB_477_AD |
- AD |
- NA |
- 5939_CR_A_1151 |
-
-
- | 466 |
- HB_479_AD |
- AD |
- NA |
- 5945_VC_A_0983 |
-
-
- | 467 |
- HB_484_AD |
- AD |
- NA |
- 5956_CR_A_0123 |
-
-
- | 468 |
- HB_489_AD |
- AD |
- NA |
- 5968_VC_A_1075 |
-
-
- | 469 |
- HB_491_AD |
- AD |
- NA |
- 5971_CR_A_0119 |
-
-
- | 470 |
- HB_492_AD |
- AD |
- NA |
- 5972_VC_A_0251 |
-
-
- | 471 |
- HB_494_AD |
- AD |
- NA |
- 5979_CR_A_0115 |
-
-
- | 472 |
- HB_498_AD |
- AD |
- NA |
- 5988_VC_A_0503 |
-
-
- | 473 |
- HB_502_AD |
- AD |
- NA |
- 5994_PF_A_1605 |
-
-
- | 474 |
- HB_503_AD |
- AD |
- NA |
- 5995_CR_A_2563 |
-
-
- | 475 |
- HB_510_AD |
- AD |
- NA |
- 6017_CR_A_0048 |
-
-
- | 476 |
- HB_514_AD |
- AD |
- NA |
- 6025_VC_A_0506 |
-
-
- | 477 |
- HB_517_AD |
- AD |
- NA |
- 6031_VC_A_0258 |
-
-
- | 478 |
- HB_520_AD |
- AD |
- NA |
- 6035_VC_A_1621 |
-
-
- | 479 |
- HB_523_AD |
- AD |
- NA |
- 6038_VC_A_0261 |
-
-
- | 480 |
- HB_524_AD |
- AD |
- NA |
- 6042_VC_A_1156 |
-
-
- | 481 |
- HB_525_AD |
- AD |
- NA |
- 6044_VC_A_0264 |
-
-
- | 482 |
- HB_531_AD |
- AD |
- NA |
- 6056_CR_A_0999 |
-
-
- | 483 |
- HB_533_AD |
- AD |
- NA |
- 6061_PF_A_1650 |
-
-
- | 484 |
- HB_534_AD |
- AD |
- NA |
- 6066_VC_A_0270 |
-
-
- | 485 |
- HB_535_AD |
- AD |
- NA |
- 6067_PF_A_1452 |
-
-
- | 486 |
- HB_536_AD |
- AD |
- NA |
- 6068_VC_A_0273 |
-
-
- | 487 |
- HB_545_AD |
- AD |
- NA |
- 6102_CR_A_1661 |
-
-
- | 488 |
- HB_546_AD |
- AD |
- NA |
- 6107_CR_A_0055 |
-
-
- | 489 |
- HB_550_AD |
- AD |
- NA |
- 6120_VC_A_0058 |
-
-
- | 490 |
- HB_552_AD |
- AD |
- NA |
- 6126_VC_A_1675 |
-
-
- | 491 |
- HB_553_AD |
- AD |
- NA |
- 6129_PF_A_0274 |
-
-
- | 492 |
- HB_554_AD |
- AD |
- NA |
- 6130_VC_A_1678 |
-
-
- | 493 |
- HB_555_AD |
- AD |
- NA |
- 6131_CR_A_0510 |
-
-
- | 494 |
- HB_556_AD |
- AD |
- NA |
- 6132_CR_A_0513 |
-
-
- | 495 |
- HB_558_AD |
- AD |
- NA |
- 6137_VC_A_1681 |
-
-
- | 496 |
- HB_564_AD |
- AD |
- NA |
- 6153_VC_A_1465 |
-
-
- | 497 |
- HB_565_AD |
- AD |
- NA |
- 6154_VC_A_1468 |
-
-
- | 498 |
- HB_566_AD |
- AD |
- NA |
- 6157_VC_A_0062 |
-
-
- | 499 |
- HB_568_AD |
- AD |
- NA |
- 6164_CR_A_1005 |
-
-
- | 500 |
- HB_571_AD |
- AD |
- NA |
- 6171_CR_A_0065 |
-
-
- | 501 |
- HB_573_AD |
- AD |
- NA |
- 6174_VC_A_0068 |
-
-
- | 502 |
- HB_576_AD |
- AD |
- NA |
- 6180_CR_A_0281 |
-
-
- | 503 |
- HB_583_AD |
- AD |
- NA |
- 6194_VC_A_0071 |
-
-
- | 504 |
- HB_585_AD |
- AD |
- NA |
- 6198_VC_A_0073 |
-
-
- | 505 |
- HB_590_AD |
- AD |
- NA |
- 6215_VC_A_0518 |
-
-
- | 506 |
- HB_591_AD |
- AD |
- NA |
- 6216_VC_A_1476 |
-
-
- | 507 |
- HB_592_AD |
- AD |
- NA |
- 6218_CR_A_0522 |
-
-
- | 508 |
- HB_594_AD |
- AD |
- NA |
- 6223_VC_A_0288 |
-
-
- | 509 |
- HB_596_AD |
- AD |
- NA |
- 6226_CR_A_0076 |
-
-
- | 510 |
- HB_597_AD |
- AD |
- NA |
- 6227_VC_A_0080 |
-
-
- | 511 |
- HB_598_AD |
- AD |
- NA |
- 6231_VC_A_1479 |
-
-
- | 512 |
- HB_605_AD |
- AD |
- NA |
- 6261_VC_A_0084 |
-
-
- | 513 |
- HB_608_AD |
- AD |
- NA |
- 6268_CR_A_0525 |
-
-
- | 514 |
- HB_611_AD |
- AD |
- NA |
- 6279_VC_A_0089 |
-
-
- | 515 |
- HB_612_AD |
- AD |
- NA |
- 6280_VC_A_0091 |
-
-
- | 516 |
- HB_613_AD |
- AD |
- NA |
- 6281_CR_A_0528 |
-
-
- | 517 |
- HB_621_AD |
- AD |
- NA |
- 6308_VC_A_1503 |
-
-
- | 518 |
- HB_623_AD |
- AD |
- NA |
- 6311_CR_A_0531 |
-
-
- | 519 |
- HB_624_AD |
- AD |
- NA |
- 6312_CR_A_0534 |
-
-
- | 520 |
- HB_630_AD |
- AD |
- NA |
- 6324_PF_A_1514 |
-
-
- | 521 |
- HB_633_AD |
- AD |
- NA |
- 6332_VC_A_1518 |
-
-
- | 522 |
- HB_634_AD |
- AD |
- NA |
- 6335_VC_A_0536 |
-
-
- | 523 |
- HB_635_AD |
- AD |
- NA |
- 6336_CR_A_0290 |
-
-
- | 524 |
- HB_636_AD |
- AD |
- NA |
- 6338_VC_A_0539 |
-
-
- | 525 |
- HB_642_AD |
- AD |
- NA |
- 6358_VC_A_0545 |
-
-
- | 526 |
- HB_652_AD |
- AD |
- NA |
- 6387_VC_A_0093 |
-
-
- | 527 |
- HB_657_AD |
- AD |
- NA |
- 6394_VC_A_0551 |
-
-
- | 528 |
- HB_664_AD |
- AD |
- NA |
- 6416_VC_A_1095 |
-
-
- | 529 |
- HB_666_AD |
- AD |
- NA |
- 6422_CR_A_0555 |
-
-
- | 530 |
- HB_669_AD |
- AD |
- NA |
- 6431_VC_A_0294 |
-
-
- | 531 |
- HB_674_AD |
- AD |
- NA |
- 6449_VC_A_1183 |
-
-
- | 532 |
- HB_680_AD |
- AD |
- NA |
- 6458_CR_A_2570 |
-
-
- | 533 |
- HB_685_AD |
- AD |
- NA |
- 6481_VC_A_0560 |
-
-
- | 534 |
- HB_690_AD |
- AD |
- NA |
- 6489_CR_A_0100 |
-
-
- | 535 |
- HB_696_AD |
- AD |
- NA |
- 6511_VC_A_1119 |
-
-
- | 536 |
- HB_698_AD |
- AD |
- NA |
- 6515_CR_A_0564 |
-
-
- | 537 |
- HB_699_AD |
- AD |
- NA |
- 6518_VC_A_0103 |
-
-
- | 538 |
- HB_703_AD |
- AD |
- NA |
- 6523_VC_A_0107 |
-
-
- | 539 |
- HB_704_AD |
- AD |
- NA |
- 6530_VC_A_0112 |
-
-
- | 540 |
- HB_706_AD |
- AD |
- NA |
- 6534_VC_A_0306 |
-
-
- | 541 |
- HB_712_AD |
- AD |
- NA |
- 6546_PF_A_1194 |
-
-
- | 542 |
- HB_713_AD |
- AD |
- NA |
- 6548_PF_A_1541 |
-
-
- | 543 |
- HB_715_AD |
- AD |
- NA |
- 6550_VC_A_1201 |
-
-
- | 544 |
- HB_718_AD |
- AD |
- NA |
- 6554_PF_A_1203 |
-
-
- | 545 |
- HB_720_AD |
- AD |
- NA |
- 6559_PF_A_2287 |
-
-
- | 546 |
- HB_722_AD |
- AD |
- NA |
- 6561_CR_A_2582 |
-
-
- | 547 |
- HB_723_AD |
- AD |
- NA |
- 6562_PF_A_2290 |
-
-
- | 548 |
- HB_724_AD |
- AD |
- NA |
- 6564_CR_A_2585 |
-
-
- | 549 |
- HB_727_AD |
- AD |
- NA |
- 6575_CR_A_2298 |
-
-
- | 550 |
- HB_728_AD |
- AD |
- NA |
- 6577_PF_A_2299 |
-
-
- | 551 |
- HB_729_AD |
- AD |
- NA |
- 6578_PF_A_2302 |
-
-
- | 552 |
- HB_731_AD |
- AD |
- NA |
- 6582_VC_A_1207 |
-
-
- | 553 |
- HB_733_AD |
- AD |
- NA |
- 6585_VC_A_1210 |
-
-
- | 554 |
- HB_736_AD |
- AD |
- NA |
- 6590_PF_A_1215 |
-
-
- | 555 |
- HB_743_AD |
- AD |
- NA |
- 6603_PF_A_1448 |
-
-
- | 556 |
- HB_745_AD |
- AD |
- NA |
- 6610_PF_A_1227 |
-
-
- | 557 |
- HB_746_AD |
- AD |
- NA |
- 6612_PF_A_2308 |
-
-
- | 558 |
- HB_749_AD |
- AD |
- NA |
- 6617_VC_A_2587 |
-
-
- | 559 |
- HB_751_AD |
- AD |
- NA |
- 6629_VC_A_2330 |
-
-
- | 560 |
- HB_752_AD |
- AD |
- NA |
- 6630_VC_A_2590 |
-
-
- | 561 |
- HB_753_AD |
- AD |
- NA |
- 6632_PF_A_2332 |
-
-
- | 562 |
- HB_754_AD |
- AD |
- NA |
- 6637_VC_A_2596 |
-
-
- | 563 |
- HB_755_AD |
- AD |
- NA |
- 6638_VC_A_2599 |
-
-
- | 564 |
- HB_756_AD |
- AD |
- NA |
- 6639_VC_A_2336 |
-
-
- | 565 |
- HB_757_AD |
- AD |
- NA |
- 6641_PF_A_2338 |
-
-
- | 566 |
- HB_763_AD |
- AD |
- NA |
- 6654_VC_A_1237 |
-
-
- | 567 |
- HB_773_AD |
- AD |
- NA |
- 6681_VC_A_1252 |
-
-
- | 568 |
- HB_775_AD |
- AD |
- NA |
- 6693_VC_A_2348 |
-
-
- | 569 |
- HB_776_AD |
- AD |
- NA |
- 6694_VC_A_2351 |
-
-
- | 570 |
- HB_777_AD |
- AD |
- NA |
- 6695_PF_A_2353 |
-
-
- | 571 |
- HB_779_AD |
- AD |
- NA |
- 6699_PF_A_2359 |
-
-
- | 572 |
- HB_781_AD |
- AD |
- NA |
- 6708_VC_A_2366 |
-
-
- | 573 |
- HB_782_AD |
- AD |
- NA |
- 6776_PF_A_2607 |
-
-
- | 574 |
- HB_783_AD |
- AD |
- NA |
- 6778_PF_A_2368 |
-
-
- | 575 |
- HB_784_AD |
- AD |
- NA |
- 6779_PF_A_2371 |
-
-
- | 576 |
- HB_785_AD |
- AD |
- NA |
- 6780_PF_A_2374 |
-
-
- | 577 |
- HB_786_AD |
- AD |
- NA |
- 6782_PF_A_2377 |
-
-
- | 578 |
- HB_787_AD |
- AD |
- NA |
- 6784_PF_A_2380 |
-
-
- | 579 |
- HB_788_AD |
- AD |
- NA |
- 6785_CR_A_2385 |
-
-
- | 580 |
- HB_789_AD |
- AD |
- NA |
- 6787_CR_A_2388 |
-
-
- | 581 |
- HB_791_AD |
- AD |
- NA |
- 6790_PF_A_2392 |
-
-
- | 582 |
- HB_792_AD |
- AD |
- NA |
- 6791_PF_A_2395 |
-
-
- | 583 |
- HB_793_AD |
- AD |
- NA |
- 6793_PF_A_2398 |
-
-
- | 584 |
- HB_794_AD |
- AD |
- NA |
- 6794_PF_A_2401 |
-
-
- | 585 |
- HB_795_AD |
- AD |
- NA |
- 6797_PF_A_2404 |
-
-
- | 586 |
- HB_796_AD |
- AD |
- NA |
- 6798_PF_A_2407 |
-
-
- | 587 |
- HB_797_AD |
- AD |
- NA |
- 6799_VC_A_2411 |
-
-
- | 588 |
- HB_798_AD |
- AD |
- NA |
- 6801_VC_A_2414 |
-
-
- | 589 |
- HB_799_AD |
- AD |
- NA |
- 6803_VC_A_2417 |
-
-
- | 590 |
- HB_801_AD |
- AD |
- NA |
- 6809_PF_A_2422 |
-
-
- | 591 |
- HB_803_AD |
- AD |
- NA |
- 6818_CR_A_2430 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/HBTRC_MLPFC_0611/experiment-design.rtf b/general/datasets/HBTRC_MLPFC_0611/experiment-design.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_0611/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_0611/notes.rtf b/general/datasets/HBTRC_MLPFC_0611/notes.rtf
deleted file mode 100644
index ff90e34..0000000
--- a/general/datasets/HBTRC_MLPFC_0611/notes.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Species: Human
-Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
-Disease: Neurological Disease
-Investigator: Francine Benes/ Eric Schadt
-Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
-Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC_MLPFC_0611/platform.rtf b/general/datasets/HBTRC_MLPFC_0611/platform.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_0611/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_0611/processing.rtf b/general/datasets/HBTRC_MLPFC_0611/processing.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_0611/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_0611/summary.rtf b/general/datasets/HBTRC_MLPFC_0611/summary.rtf
deleted file mode 100644
index 5cde3bf..0000000
--- a/general/datasets/HBTRC_MLPFC_0611/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC_MLPFC_0611/tissue.rtf b/general/datasets/HBTRC_MLPFC_0611/tissue.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_0611/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_AD_0611/acknowledgment.rtf b/general/datasets/HBTRC_MLPFC_AD_0611/acknowledgment.rtf
deleted file mode 100644
index 208cb6e..0000000
--- a/general/datasets/HBTRC_MLPFC_AD_0611/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC_MLPFC_AD_0611/cases.rtf b/general/datasets/HBTRC_MLPFC_AD_0611/cases.rtf
deleted file mode 100644
index 86ed08e..0000000
--- a/general/datasets/HBTRC_MLPFC_AD_0611/cases.rtf
+++ /dev/null
@@ -1,4166 +0,0 @@
-This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
-
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-
-
-
- | Series |
- Cerebellum in GN |
- Condition |
- Gender |
- BioSample Name |
-
-
- | 1 |
- HB_029_N |
- N |
- NA |
- 3405_VC_N_0859 |
-
-
- | 2 |
- HB_058_N |
- N |
- NA |
- 4021_VC_N_0854 |
-
-
- | 3 |
- HB_064_N |
- N |
- NA |
- 4338_VC_N_0861 |
-
-
- | 4 |
- HB_086_N |
- N |
- NA |
- 4729_PF_N_0756 |
-
-
- | 5 |
- HB_091_N |
- N |
- NA |
- 4741_VC_N_0864 |
-
-
- | 6 |
- HB_092_N |
- N |
- NA |
- 4744_VC_N_0865 |
-
-
- | 7 |
- HB_102_N |
- N |
- NA |
- 4810_VC_N_0869 |
-
-
- | 8 |
- HB_119_N |
- N |
- NA |
- 4872_VC_N_0878 |
-
-
- | 9 |
- HB_147_N |
- N |
- NA |
- 5021_VC_N_0852 |
-
-
- | 10 |
- HB_161_N |
- N |
- NA |
- 5077_VC_N_0851 |
-
-
- | 11 |
- HB_162_N |
- N |
- NA |
- 5081_VC_N_1021 |
-
-
- | 12 |
- HB_166_N |
- N |
- NA |
- 5095_VC_N_1024 |
-
-
- | 13 |
- HB_183_N |
- N |
- NA |
- 5162_VC_N_0850 |
-
-
- | 14 |
- HB_206_N |
- N |
- NA |
- 5245_VC_N_0849 |
-
-
- | 15 |
- HB_215_N |
- N |
- NA |
- 5270_VC_N_0848 |
-
-
- | 16 |
- HB_218_N |
- N |
- NA |
- 5276_CR_N_0912 |
-
-
- | 17 |
- HB_223_N |
- N |
- NA |
- 5287_VC_N_0916 |
-
-
- | 18 |
- HB_226_N |
- N |
- NA |
- 5294_VC_N_0919 |
-
-
- | 19 |
- HB_241_N |
- N |
- NA |
- 5326_CR_N_0652 |
-
-
- | 20 |
- HB_243_N |
- N |
- NA |
- 5333_VC_N_1262 |
-
-
- | 21 |
- HB_247_N |
- N |
- NA |
- 5341_VC_N_0923 |
-
-
- | 22 |
- HB_257_N |
- N |
- NA |
- 5368_PF_N_1032 |
-
-
- | 23 |
- HB_264_N |
- N |
- NA |
- 5384_VC_N_0924 |
-
-
- | 24 |
- HB_295_N |
- N |
- NA |
- 5452_VC_N_1268 |
-
-
- | 25 |
- HB_300_N |
- N |
- NA |
- 5463_VC_N_0845 |
-
-
- | 26 |
- HB_311_N |
- N |
- NA |
- 5489_CR_N_0942 |
-
-
- | 27 |
- HB_324_N |
- N |
- NA |
- 5531_VC_N_0844 |
-
-
- | 28 |
- HB_332_N |
- N |
- NA |
- 5547_VC_N_0843 |
-
-
- | 29 |
- HB_340_N |
- N |
- NA |
- 5568_VC_N_0842 |
-
-
- | 30 |
- HB_360_N |
- N |
- NA |
- 5619_CR_N_0645 |
-
-
- | 31 |
- HB_365_N |
- N |
- NA |
- 5632_VC_N_0838 |
-
-
- | 32 |
- HB_367_N |
- N |
- NA |
- 5637_VC_N_0837 |
-
-
- | 33 |
- HB_382_N |
- N |
- NA |
- 5684_PF_N_1270 |
-
-
- | 34 |
- HB_396_N |
- N |
- NA |
- 5718_VC_N_0956 |
-
-
- | 35 |
- HB_398_N |
- N |
- NA |
- 5722_VC_N_1044 |
-
-
- | 36 |
- HB_400_N |
- N |
- NA |
- 5726_VC_N_0834_Bis |
-
-
- | 37 |
- HB_403_N |
- N |
- NA |
- 5734_VC_N_0833 |
-
-
- | 38 |
- HB_414_N |
- N |
- NA |
- 5772_VC_N_0832_Bis |
-
-
- | 39 |
- HB_416_N |
- N |
- NA |
- 5778_CR_N_0962 |
-
-
- | 40 |
- HB_418_N |
- N |
- NA |
- 5789_PF_N_1273 |
-
-
- | 41 |
- HB_421_N |
- N |
- NA |
- 5799_VC_N_1058 |
-
-
- | 42 |
- HB_423_N |
- N |
- NA |
- 5803_VC_N_0966 |
-
-
- | 43 |
- HB_426_N |
- N |
- NA |
- 5806_PF_N_1064 |
-
-
- | 44 |
- HB_427_N |
- N |
- NA |
- 5810_CR_N_0636 |
-
-
- | 45 |
- HB_431_N |
- N |
- NA |
- 5823_VC_N_0829 |
-
-
- | 46 |
- HB_432_N |
- N |
- NA |
- 5826_VC_N_0828 |
-
-
- | 47 |
- HB_433_N |
- N |
- NA |
- 5827_VC_N_0827 |
-
-
- | 48 |
- HB_436_N |
- N |
- NA |
- 5832_PF_N_1145 |
-
-
- | 49 |
- HB_443_N |
- N |
- NA |
- 5852_VC_N_0826 |
-
-
- | 50 |
- HB_446_N |
- N |
- NA |
- 5859_VC_N_0825 |
-
-
- | 51 |
- HB_449_N |
- N |
- NA |
- 5866_VC_N_0824 |
-
-
- | 52 |
- HB_450_N |
- N |
- NA |
- 5867_VC_N_1277 |
-
-
- | 53 |
- HB_453_N |
- N |
- NA |
- 5876_VC_N_0823 |
-
-
- | 54 |
- HB_462_N |
- N |
- NA |
- 5903_VC_N_0822 |
-
-
- | 55 |
- HB_464_N |
- N |
- NA |
- 5905_VC_N_0820 |
-
-
- | 56 |
- HB_468_N |
- N |
- NA |
- 5912_VC_N_1286 |
-
-
- | 57 |
- HB_472_N |
- N |
- NA |
- 5925_VC_N_1289 |
-
-
- | 58 |
- HB_475_N |
- N |
- NA |
- 5936_VC_N_0979 |
-
-
- | 59 |
- HB_476_N |
- N |
- NA |
- 5938_VC_N_0819 |
-
-
- | 60 |
- HB_480_N |
- N |
- NA |
- 5946_VC_N_0985 |
-
-
- | 61 |
- HB_485_N |
- N |
- NA |
- 5959_VC_N_0818 |
-
-
- | 62 |
- HB_486_N |
- N |
- NA |
- 5963_VC_N_0987 |
-
-
- | 63 |
- HB_495_N |
- N |
- NA |
- 5980_VC_N_0989 |
-
-
- | 64 |
- HB_497_N |
- N |
- NA |
- 5985_VC_N_0990 |
-
-
- | 65 |
- HB_500_N |
- N |
- NA |
- 5990_VC_N_0817 |
-
-
- | 66 |
- HB_501_N |
- N |
- NA |
- 5991_VC_N_0816 |
-
-
- | 67 |
- HB_504_N |
- N |
- NA |
- 5996_VC_N_0815 |
-
-
- | 68 |
- HB_505_N |
- N |
- NA |
- 5998_VC_N_0814 |
-
-
- | 69 |
- HB_507_N |
- N |
- NA |
- 6006_VC_N_0813 |
-
-
- | 70 |
- HB_508_N |
- N |
- NA |
- 6007_CR_N_0618 |
-
-
- | 71 |
- HB_509_N |
- N |
- NA |
- 6008_PF_N_1081 |
-
-
- | 72 |
- HB_512_N |
- N |
- NA |
- 6023_PF_N_1155 |
-
-
- | 73 |
- HB_516_N |
- N |
- NA |
- 6030_VC_N_0810 |
-
-
- | 74 |
- HB_519_N |
- N |
- NA |
- 6034_VC_N_0809 |
-
-
- | 75 |
- HB_532_N |
- N |
- NA |
- 6060_VC_N_1292 |
-
-
- | 76 |
- HB_541_N |
- N |
- NA |
- 6092_VC_N_1001 |
-
-
- | 77 |
- HB_542_N |
- N |
- NA |
- 6096_VC_N_0807 |
-
-
- | 78 |
- HB_544_N |
- N |
- NA |
- 6101_CR_N_1161 |
-
-
- | 79 |
- HB_547_N |
- N |
- NA |
- 6110_VC_N_1295 |
-
-
- | 80 |
- HB_551_N |
- N |
- NA |
- 6124_VC_N_0806 |
-
-
- | 81 |
- HB_557_N |
- N |
- NA |
- 6134_PF_N_1297 |
-
-
- | 82 |
- HB_560_N |
- N |
- NA |
- 6142_VC_N_0805 |
-
-
- | 83 |
- HB_569_N |
- N |
- NA |
- 6166_VC_N_0804 |
-
-
- | 84 |
- HB_570_N |
- N |
- NA |
- 6170_VC_N_0803 |
-
-
- | 85 |
- HB_572_N |
- N |
- NA |
- 6172_VC_N_1008 |
-
-
- | 86 |
- HB_577_N |
- N |
- NA |
- 6182_VC_N_1166 |
-
-
- | 87 |
- HB_579_N |
- N |
- NA |
- 6187_CR_N_0607 |
-
-
- | 88 |
- HB_581_N |
- N |
- NA |
- 6191_VC_N_1010 |
-
-
- | 89 |
- HB_584_N |
- N |
- NA |
- 6196_CR_N_0605 |
-
-
- | 90 |
- HB_586_N |
- N |
- NA |
- 6200_VC_N_0799 |
-
-
- | 91 |
- HB_587_N |
- N |
- NA |
- 6206_PF_N_1176 |
-
-
- | 92 |
- HB_589_N |
- N |
- NA |
- 6213_VC_N_0798 |
-
-
- | 93 |
- HB_601_N |
- N |
- NA |
- 6241_VC_N_0796 |
-
-
- | 94 |
- HB_604_N |
- N |
- NA |
- 6260_VC_N_0794 |
-
-
- | 95 |
- HB_609_N |
- N |
- NA |
- 6270_VC_N_0793 |
-
-
- | 96 |
- HB_618_N |
- N |
- NA |
- 6289_VC_N_0791 |
-
-
- | 97 |
- HB_622_N |
- N |
- NA |
- 6310_VC_N_0790 |
-
-
- | 98 |
- HB_625_N |
- N |
- NA |
- 6314_VC_N_0789 |
-
-
- | 99 |
- HB_637_N |
- N |
- NA |
- 6340_VC_N_0786 |
-
-
- | 100 |
- HB_638_N |
- N |
- NA |
- 6341_VC_N_0785 |
-
-
- | 101 |
- HB_640_N |
- N |
- NA |
- 6347_VC_N_0784 |
-
-
- | 102 |
- HB_641_N |
- N |
- NA |
- 6356_VC_N_0783 |
-
-
- | 103 |
- HB_643_N |
- N |
- NA |
- 6363_VC_N_0781 |
-
-
- | 104 |
- HB_644_N |
- N |
- NA |
- 6366_VC_N_0780 |
-
-
- | 105 |
- HB_645_N |
- N |
- NA |
- 6374_VC_N_0779 |
-
-
- | 106 |
- HB_650_N |
- N |
- NA |
- 6384_VC_N_0777 |
-
-
- | 107 |
- HB_651_N |
- N |
- NA |
- 6386_VC_N_0776 |
-
-
- | 108 |
- HB_653_N |
- N |
- NA |
- 6388_VC_N_0775 |
-
-
- | 109 |
- HB_659_N |
- N |
- NA |
- 6406_VC_N_1180 |
-
-
- | 110 |
- HB_662_N |
- N |
- NA |
- 6411_VC_N_0771 |
-
-
- | 111 |
- HB_663_N |
- N |
- NA |
- 6415_VC_N_0770 |
-
-
- | 112 |
- HB_670_N |
- N |
- NA |
- 6436_VC_N_0769 |
-
-
- | 113 |
- HB_687_N |
- N |
- NA |
- 6484_VC_N_0765 |
-
-
- | 114 |
- HB_689_N |
- N |
- NA |
- 6486_VC_N_0764 |
-
-
- | 115 |
- HB_694_N |
- N |
- NA |
- 6500_VC_N_0763 |
-
-
- | 116 |
- HB_697_N |
- N |
- NA |
- 6512_VC_N_0762 |
-
-
- | 117 |
- HB_700_N |
- N |
- NA |
- 6520_VC_N_0761 |
-
-
- | 118 |
- HB_711_N |
- N |
- NA |
- 6543_PF_N_1191 |
-
-
- | 119 |
- HB_714_N |
- N |
- NA |
- 6549_VC_N_1198 |
-
-
- | 120 |
- HB_717_N |
- N |
- NA |
- 6553_PF_N_2284 |
-
-
- | 121 |
- HB_721_N |
- N |
- NA |
- 6560_VC_N_2578 |
-
-
- | 122 |
- HB_726_N |
- N |
- NA |
- 6573_PF_N_2293 |
-
-
- | 123 |
- HB_730_N |
- N |
- NA |
- 6580_VC_N_2306 |
-
-
- | 124 |
- HB_735_N |
- N |
- NA |
- 6588_VC_N_1213 |
-
-
- | 125 |
- HB_737_N |
- N |
- NA |
- 6593_VC_N_1219 |
-
-
- | 126 |
- HB_738_N |
- N |
- NA |
- 6594_VC_N_1222 |
-
-
- | 127 |
- HB_759_N |
- N |
- NA |
- 6645_VC_N_1231 |
-
-
- | 128 |
- HB_764_N |
- N |
- NA |
- 6655_VC_N_1240 |
-
-
- | 129 |
- HB_765_N |
- N |
- NA |
- 6656_VC_N_1243 |
-
-
- | 130 |
- HB_767_N |
- N |
- NA |
- 6661_PF_N_2341 |
-
-
- | 131 |
- HB_770_N |
- N |
- NA |
- 6669_VC_N_1246 |
-
-
- | 132 |
- HB_772_N |
- N |
- NA |
- 6676_PF_N_1248 |
-
-
- | 133 |
- HB_001_HD |
- HD |
- F |
- 2028_CR_H_2282 |
-
-
- | 134 |
- HB_003_HD |
- HD |
- F |
- 2685_PF_H_2212 |
-
-
- | 135 |
- HB_004_HD |
- HD |
- M |
- 2706_CR_H_2432 |
-
-
- | 136 |
- HB_006_HD |
- HD |
- M |
- 2737_VC_H_2194 |
-
-
- | 137 |
- HB_007_HD |
- HD |
- NA |
- 2769_VC_H_2193 |
-
-
- | 138 |
- HB_008_HD |
- HD |
- F |
- 2790_CR_H_1890 |
-
-
- | 139 |
- HB_009_HD |
- HD |
- NA |
- 2879_VC_H_2192 |
-
-
- | 140 |
- HB_010_HD |
- HD |
- M |
- 2960_VC_H_2002 |
-
-
- | 141 |
- HB_011_HD |
- HD |
- F |
- 3053_VC_H_2001 |
-
-
- | 142 |
- HB_012_HD |
- HD |
- F |
- 3128_VC_H_1999 |
-
-
- | 143 |
- HB_014_HD |
- HD |
- F |
- 3149_PF_H_2110 |
-
-
- | 144 |
- HB_015_HD |
- HD |
- F |
- 3150_VC_H_1996 |
-
-
- | 145 |
- HB_016_HD |
- HD |
- F |
- 3177_VC_H_2191 |
-
-
- | 146 |
- HB_017_HD |
- HD |
- NA |
- 3195_VC_H_2190 |
-
-
- | 147 |
- HB_018_HD |
- HD |
- M |
- 3200_VC_H_2189 |
-
-
- | 148 |
- HB_019_HD |
- HD |
- M |
- 3209_VC_H_2188 |
-
-
- | 149 |
- HB_020_HD |
- HD |
- M |
- 3224_VC_H_1994 |
-
-
- | 150 |
- HB_022_HD |
- HD |
- F |
- 3242_PF_H_2105 |
-
-
- | 151 |
- HB_024_HD |
- HD |
- NA |
- 3272_VC_H_2186 |
-
-
- | 152 |
- HB_027_HD |
- HD |
- M |
- 3356_VC_H_2439 |
-
-
- | 153 |
- HB_028_HD |
- HD |
- F |
- 3394_PF_H_2104 |
-
-
- | 154 |
- HB_031_HD |
- HD |
- M |
- 3430_VC_H_1990 |
-
-
- | 155 |
- HB_032_HD |
- HD |
- NA |
- 3444_PF_H_2208 |
-
-
- | 156 |
- HB_034_HD |
- HD |
- F |
- 3482_VC_H_1987 |
-
-
- | 157 |
- HB_036_HD |
- HD |
- M |
- 3576_VC_H_1984 |
-
-
- | 158 |
- HB_037_HD |
- HD |
- F |
- 3579_VC_H_1983 |
-
-
- | 159 |
- HB_038_HD |
- HD |
- F |
- 3584_VC_H_2183 |
-
-
- | 160 |
- HB_039_HD |
- HD |
- NA |
- 3635_VC_H_2182 |
-
-
- | 161 |
- HB_041_HD |
- HD |
- F |
- 3695_CR_H_2267 |
-
-
- | 162 |
- HB_042_HD |
- HD |
- M |
- 3697_VC_H_1982 |
-
-
- | 163 |
- HB_043_HD |
- HD |
- NA |
- 3703_VC_H_2180 |
-
-
- | 164 |
- HB_044_HD |
- HD |
- NA |
- 3723_VC_H_2179 |
-
-
- | 165 |
- HB_046_HD |
- HD |
- F |
- 3735_VC_H_1981 |
-
-
- | 166 |
- HB_050_HD |
- HD |
- M |
- 3820_PF_H_2207 |
-
-
- | 167 |
- HB_051_HD |
- HD |
- F |
- 3849_CR_H_2262 |
-
-
- | 168 |
- HB_054_HD |
- HD |
- M |
- 3884_VC_H_2175 |
-
-
- | 169 |
- HB_056_HD |
- HD |
- NA |
- 4012_VC_H_2174 |
-
-
- | 170 |
- HB_057_HD |
- HD |
- NA |
- 4013_VC_H_2173 |
-
-
- | 171 |
- HB_059_HD |
- HD |
- NA |
- 4066_VC_H_2172 |
-
-
- | 172 |
- HB_060_HD |
- HD |
- NA |
- 4094_VC_H_2171 |
-
-
- | 173 |
- HB_061_HD |
- HD |
- F |
- 4116_VC_H_2170 |
-
-
- | 174 |
- HB_062_HD |
- HD |
- NA |
- 4121_VC_H_2169 |
-
-
- | 175 |
- HB_063_HD |
- HD |
- NA |
- 4215_VC_H_2167 |
-
-
- | 176 |
- HB_065_HD |
- HD |
- M |
- 4340_PF_H_2091 |
-
-
- | 177 |
- HB_066_HD |
- HD |
- F |
- 4344_VC_H_1977 |
-
-
- | 178 |
- HB_067_HD |
- HD |
- M |
- 4346_VC_H_2165 |
-
-
- | 179 |
- HB_069_HD |
- HD |
- F |
- 4356_VC_H_2164 |
-
-
- | 180 |
- HB_070_HD |
- HD |
- NA |
- 4386_CR_H_2249 |
-
-
- | 181 |
- HB_072_HD |
- HD |
- NA |
- 4404_VC_H_2161 |
-
-
- | 182 |
- HB_073_HD |
- HD |
- F |
- 4411_VC_H_1975 |
-
-
- | 183 |
- HB_074_HD |
- HD |
- NA |
- 4430_VC_H_2465 |
-
-
- | 184 |
- HB_075_HD |
- HD |
- M |
- 4470_VC_H_1974 |
-
-
- | 185 |
- HB_076_HD |
- HD |
- F |
- 4497_CR_H_1860 |
-
-
- | 186 |
- HB_077_HD |
- HD |
- M |
- 4509_CR_H_2244 |
-
-
- | 187 |
- HB_079_HD |
- HD |
- M |
- 4631_VC_H_1971 |
-
-
- | 188 |
- HB_080_HD |
- HD |
- F |
- 4653_PF_H_2083 |
-
-
- | 189 |
- HB_081_HD |
- HD |
- NA |
- 4678_CR_H_2242 |
-
-
- | 190 |
- HB_084_HD |
- HD |
- M |
- 4718_VC_H_2125 |
-
-
- | 191 |
- HB_090_HD |
- HD |
- NA |
- 4740_CR_H_2474 |
-
-
- | 192 |
- HB_094_HD |
- HD |
- NA |
- 4754_CR_H_2476 |
-
-
- | 193 |
- HB_098_HD |
- HD |
- NA |
- 4780_VC_H_2151 |
-
-
- | 194 |
- HB_101_HD |
- HD |
- F |
- 4809_VC_H_2148 |
-
-
- | 195 |
- HB_105_HD |
- HD |
- NA |
- 4819_CR_H_2238 |
-
-
- | 196 |
- HB_106_HD |
- HD |
- F |
- 4822_VC_H_1969 |
-
-
- | 197 |
- HB_108_HD |
- HD |
- M |
- 4826_VC_H_1968 |
-
-
- | 198 |
- HB_109_HD |
- HD |
- M |
- 4828_VC_H_2124 |
-
-
- | 199 |
- HB_115_HD |
- HD |
- NA |
- 4855_CR_H_2235 |
-
-
- | 200 |
- HB_121_HD |
- HD |
- F |
- 4902_VC_H_1967 |
-
-
- | 201 |
- HB_129_HD |
- HD |
- NA |
- 4938_VC_H_1966 |
-
-
- | 202 |
- HB_141_HD |
- HD |
- F |
- 4996_PF_H_2076 |
-
-
- | 203 |
- HB_152_HD |
- HD |
- NA |
- 5034_CR_H_2233 |
-
-
- | 204 |
- HB_153_HD |
- HD |
- M |
- 5043_VC_H_1960 |
-
-
- | 205 |
- HB_159_HD |
- HD |
- M |
- 5062_VC_H_1959 |
-
-
- | 206 |
- HB_172_HD |
- HD |
- F |
- 5114_PF_H_2070 |
-
-
- | 207 |
- HB_175_HD |
- HD |
- M |
- 5127_PF_H_2068 |
-
-
- | 208 |
- HB_180_HD |
- HD |
- M |
- 5148_VC_H_1944 |
-
-
- | 209 |
- HB_185_HD |
- HD |
- F |
- 5167_CR_H_2231 |
-
-
- | 210 |
- HB_188_HD |
- HD |
- F |
- 5172_VC_H_1951 |
-
-
- | 211 |
- HB_191_HD |
- HD |
- M |
- 5180_VC_H_1949 |
-
-
- | 212 |
- HB_196_HD |
- HD |
- NA |
- 5199_PF_H_2202 |
-
-
- | 213 |
- HB_203_HD |
- HD |
- F |
- 5228_PF_H_2059 |
-
-
- | 214 |
- HB_207_HD |
- HD |
- NA |
- 5248_PF_H_2201 |
-
-
- | 215 |
- HB_228_HD |
- HD |
- F |
- 5299_CR_H_2228 |
-
-
- | 216 |
- HB_233_HD |
- HD |
- M |
- 5312_VC_H_1938 |
-
-
- | 217 |
- HB_235_HD |
- HD |
- F |
- 5316_VC_H_1937 |
-
-
- | 218 |
- HB_242_HD |
- HD |
- F |
- 5328_PF_H_2048 |
-
-
- | 219 |
- HB_266_HD |
- HD |
- M |
- 5387_VC_H_1928 |
-
-
- | 220 |
- HB_271_HD |
- HD |
- M |
- 5394_PF_H_2039 |
-
-
- | 221 |
- HB_272_HD |
- HD |
- F |
- 5396_VC_H_1925 |
-
-
- | 222 |
- HB_279_HD |
- HD |
- F |
- 5409_VC_H_1924 |
-
-
- | 223 |
- HB_294_HD |
- HD |
- M |
- 5448_VC_H_1921 |
-
-
- | 224 |
- HB_301_HD |
- HD |
- NA |
- 5464_VC_H_1919 |
-
-
- | 225 |
- HB_304_HD |
- HD |
- F |
- 5471_VC_H_1918 |
-
-
- | 226 |
- HB_321_HD |
- HD |
- NA |
- 5522_PF_H_2199 |
-
-
- | 227 |
- HB_361_HD |
- HD |
- F |
- 5622_VC_H_2121 |
-
-
- | 228 |
- HB_370_HD |
- HD |
- M |
- 5645_VC_H_1904 |
-
-
- | 229 |
- HB_371_HD |
- HD |
- F |
- 5648_PF_H_2016 |
-
-
- | 230 |
- HB_384_HD |
- HD |
- F |
- 5688_PF_H_2012 |
-
-
- | 231 |
- HB_390_HD |
- HD |
- M |
- 5704_PF_H_2009 |
-
-
- | 232 |
- HB_393_HD |
- HD |
- F |
- 5709_VC_H_1895 |
-
-
- | 233 |
- HB_402_HD |
- HD |
- F |
- 5732_PF_H_2007 |
-
-
- | 234 |
- HB_405_HD |
- HD |
- NA |
- 5742_PF_H_2006 |
-
-
- | 235 |
- HB_407_HD |
- HD |
- M |
- 5745_PF_H_2005 |
-
-
- | 236 |
- HB_408_HD |
- HD |
- M |
- 5747_VC_H_1891 |
-
-
- | 237 |
- HB_415_HD |
- HD |
- NA |
- 5777_PF_H_1551 |
-
-
- | 238 |
- HB_417_HD |
- HD |
- M |
- 5784_PF_H_1554 |
-
-
- | 239 |
- HB_424_HD |
- HD |
- M |
- 5804_VC_H_1558 |
-
-
- | 240 |
- HB_444_HD |
- HD |
- M |
- 5856_VC_H_1567 |
-
-
- | 241 |
- HB_457_HD |
- HD |
- M |
- 5896_VC_H_1570 |
-
-
- | 242 |
- HB_466_HD |
- HD |
- M |
- 5910_PF_H_1572 |
-
-
- | 243 |
- HB_478_HD |
- HD |
- M |
- 5941_CR_H_1583 |
-
-
- | 244 |
- HB_487_HD |
- HD |
- F |
- 5964_VC_H_1597 |
-
-
- | 245 |
- HB_511_HD |
- HD |
- M |
- 6019_PF_H_2198 |
-
-
- | 246 |
- HB_513_HD |
- HD |
- F |
- 6024_VC_H_1612 |
-
-
- | 247 |
- HB_515_HD |
- HD |
- F |
- 6028_CR_H_1613 |
-
-
- | 248 |
- HB_518_HD |
- HD |
- M |
- 6033_VC_H_1618 |
-
-
- | 249 |
- HB_522_HD |
- HD |
- M |
- 6037_PF_H_1626 |
-
-
- | 250 |
- HB_527_HD |
- HD |
- F |
- 6047_VC_H_1639 |
-
-
- | 251 |
- HB_528_HD |
- HD |
- M |
- 6051_PF_H_1641 |
-
-
- | 252 |
- HB_530_HD |
- HD |
- M |
- 6054_VC_H_1648 |
-
-
- | 253 |
- HB_537_HD |
- HD |
- F |
- 6071_PF_H_1653 |
-
-
- | 254 |
- HB_549_HD |
- HD |
- M |
- 6119_CR_H_1670 |
-
-
- | 255 |
- HB_593_HD |
- HD |
- NA |
- 6219_CR_H_2567 |
-
-
- | 256 |
- HB_610_HD |
- HD |
- NA |
- 6275_PF_H_1692 |
-
-
- | 257 |
- HB_616_HD |
- HD |
- F |
- 6284_CR_H_1694 |
-
-
- | 258 |
- HB_626_HD |
- HD |
- M |
- 6315_VC_H_1702 |
-
-
- | 259 |
- HB_639_HD |
- HD |
- F |
- 6344_CR_H_1703 |
-
-
- | 260 |
- HB_649_HD |
- HD |
- F |
- 6382_CR_H_1709 |
-
-
- | 261 |
- HB_661_HD |
- HD |
- M |
- 6408_VC_H_1714 |
-
-
- | 262 |
- HB_682_HD |
- HD |
- M |
- 6467_PF_H_1725 |
-
-
- | 263 |
- HB_683_HD |
- HD |
- M |
- 6472_VC_H_1729 |
-
-
- | 264 |
- HB_691_HD |
- HD |
- F |
- 6493_VC_H_1732 |
-
-
- | 265 |
- HB_692_HD |
- HD |
- M |
- 6495_CR_H_1733 |
-
-
- | 266 |
- HB_707_HD |
- HD |
- M |
- 6535_PF_H_1737 |
-
-
- | 267 |
- HB_709_HD |
- HD |
- F |
- 6539_CR_H_1739 |
-
-
- | 268 |
- HB_725_HD |
- HD |
- M |
- 6572_PF_H_1746 |
-
-
- | 269 |
- HB_732_HD |
- HD |
- F |
- 6584_VC_H_1750 |
-
-
- | 270 |
- HB_734_HD |
- HD |
- F |
- 6587_CR_H_1751 |
-
-
- | 271 |
- HB_748_HD |
- HD |
- NA |
- 6615_VC_H_2315 |
-
-
- | 272 |
- HB_750_HD |
- HD |
- NA |
- 6628_PF_H_2326 |
-
-
- | 273 |
- HB_758_HD |
- HD |
- NA |
- 6643_VC_H_2602 |
-
-
- | 274 |
- HB_760_HD |
- HD |
- M |
- 6646_PF_H_1761 |
-
-
- | 275 |
- HB_762_HD |
- HD |
- M |
- 6650_VC_H_1765 |
-
-
- | 276 |
- HB_766_HD |
- HD |
- M |
- 6658_VC_H_1768 |
-
-
- | 277 |
- HB_768_HD |
- HD |
- NA |
- 6663_VC_H_1771 |
-
-
- | 278 |
- HB_769_HD |
- HD |
- M |
- 6666_VC_H_1774 |
-
-
- | 279 |
- HB_774_HD |
- HD |
- NA |
- 6689_PF_H_2344 |
-
-
- | 280 |
- HB_778_HD |
- HD |
- NA |
- 6696_PF_H_2356 |
-
-
- | 281 |
- HB_780_HD |
- HD |
- NA |
- 6704_PF_H_2362 |
-
-
- | 282 |
- HB_790_HD |
- HD |
- NA |
- 6788_PF_H_2389 |
-
-
- | 283 |
- HB_800_HD |
- HD |
- NA |
- 6807_PF_H_2419 |
-
-
- | 284 |
- HB_802_HD |
- HD |
- NA |
- 6811_PF_H_2425 |
-
-
- | 285 |
- HB_045_AD |
- AD |
- NA |
- 3734_CR_A_0122 |
-
-
- | 286 |
- HB_048_AD |
- AD |
- NA |
- 3791_CR_A_0128 |
-
-
- | 287 |
- HB_053_AD |
- AD |
- NA |
- 3877_CR_A_0134 |
-
-
- | 288 |
- HB_055_AD |
- AD |
- NA |
- 3893_VC_A_0142 |
-
-
- | 289 |
- HB_068_AD |
- AD |
- NA |
- 4349_VC_A_0148 |
-
-
- | 290 |
- HB_082_AD |
- AD |
- NA |
- 4712_CR_A_0309 |
-
-
- | 291 |
- HB_085_AD |
- AD |
- NA |
- 4726_VC_A_0311 |
-
-
- | 292 |
- HB_087_AD |
- AD |
- NA |
- 4730_CR_A_0315 |
-
-
- | 293 |
- HB_089_AD |
- AD |
- NA |
- 4733_VC_A_0320 |
-
-
- | 294 |
- HB_093_AD |
- AD |
- NA |
- 4749_VC_A_0323 |
-
-
- | 295 |
- HB_095_AD |
- AD |
- NA |
- 4759_CR_A_0327 |
-
-
- | 296 |
- HB_097_AD |
- AD |
- NA |
- 4773_CR_A_0866 |
-
-
- | 297 |
- HB_099_AD |
- AD |
- NA |
- 4785_VC_A_0332 |
-
-
- | 298 |
- HB_100_AD |
- AD |
- NA |
- 4795_VC_A_0335 |
-
-
- | 299 |
- HB_103_AD |
- AD |
- NA |
- 4811_VC_A_0341 |
-
-
- | 300 |
- HB_104_AD |
- AD |
- NA |
- 4813_CR_A_0345 |
-
-
- | 301 |
- HB_112_AD |
- AD |
- NA |
- 4842_VC_A_0870 |
-
-
- | 302 |
- HB_113_AD |
- AD |
- NA |
- 4850_CR_A_0351 |
-
-
- | 303 |
- HB_114_AD |
- AD |
- NA |
- 4852_CR_A_0354 |
-
-
- | 304 |
- HB_117_AD |
- AD |
- NA |
- 4868_VC_A_0874 |
-
-
- | 305 |
- HB_122_AD |
- AD |
- NA |
- 4904_CR_A_1132 |
-
-
- | 306 |
- HB_123_AD |
- AD |
- NA |
- 4905_VC_A_0884 |
-
-
- | 307 |
- HB_124_AD |
- AD |
- NA |
- 4916_VC_A_0886 |
-
-
- | 308 |
- HB_125_AD |
- AD |
- NA |
- 4917_CR_A_0360 |
-
-
- | 309 |
- HB_126_AD |
- AD |
- NA |
- 4921_VC_A_0362 |
-
-
- | 310 |
- HB_128_AD |
- AD |
- NA |
- 4936_CR_A_0369 |
-
-
- | 311 |
- HB_130_AD |
- AD |
- NA |
- 4939_VC_A_0888 |
-
-
- | 312 |
- HB_131_AD |
- AD |
- NA |
- 4944_CR_A_0889 |
-
-
- | 313 |
- HB_132_AD |
- AD |
- NA |
- 4946_CR_A_0372 |
-
-
- | 314 |
- HB_134_AD |
- AD |
- NA |
- 4951_CR_A_0891 |
-
-
- | 315 |
- HB_135_AD |
- AD |
- NA |
- 4953_VC_A_0893 |
-
-
- | 316 |
- HB_136_AD |
- AD |
- NA |
- 4965_VC_A_0160 |
-
-
- | 317 |
- HB_137_AD |
- AD |
- NA |
- 4966_VC_A_0374 |
-
-
- | 318 |
- HB_138_AD |
- AD |
- NA |
- 4969_VC_A_0895 |
-
-
- | 319 |
- HB_140_AD |
- AD |
- NA |
- 4993_CR_A_0896 |
-
-
- | 320 |
- HB_146_AD |
- AD |
- NA |
- 5018_CR_A_0384 |
-
-
- | 321 |
- HB_148_AD |
- AD |
- NA |
- 5022_VC_A_0386 |
-
-
- | 322 |
- HB_150_AD |
- AD |
- NA |
- 5031_VC_A_0392 |
-
-
- | 323 |
- HB_151_AD |
- AD |
- NA |
- 5033_CR_A_0396 |
-
-
- | 324 |
- HB_154_AD |
- AD |
- NA |
- 5048_VC_A_1321 |
-
-
- | 325 |
- HB_155_AD |
- AD |
- NA |
- 5056_VC_A_0398 |
-
-
- | 326 |
- HB_156_AD |
- AD |
- NA |
- 5057_VC_A_0163 |
-
-
- | 327 |
- HB_157_AD |
- AD |
- NA |
- 5059_VC_A_0401 |
-
-
- | 328 |
- HB_158_AD |
- AD |
- NA |
- 5061_PF_A_2612 |
-
-
- | 329 |
- HB_160_AD |
- AD |
- NA |
- 5064_PF_A_2615 |
-
-
- | 330 |
- HB_165_AD |
- AD |
- NA |
- 5092_CR_A_0899 |
-
-
- | 331 |
- HB_168_AD |
- AD |
- NA |
- 5097_VC_A_0407 |
-
-
- | 332 |
- HB_170_AD |
- AD |
- NA |
- 5101_VC_A_0410 |
-
-
- | 333 |
- HB_174_AD |
- AD |
- NA |
- 5124_PF_A_1343 |
-
-
- | 334 |
- HB_179_AD |
- AD |
- NA |
- 5145_VC_A_1351 |
-
-
- | 335 |
- HB_181_AD |
- AD |
- NA |
- 5152_CR_A_0414 |
-
-
- | 336 |
- HB_184_AD |
- AD |
- NA |
- 5166_VC_A_1354 |
-
-
- | 337 |
- HB_194_AD |
- AD |
- NA |
- 5193_VC_A_1360 |
-
-
- | 338 |
- HB_197_AD |
- AD |
- NA |
- 5202_CR_A_1368 |
-
-
- | 339 |
- HB_199_AD |
- AD |
- NA |
- 5205_VC_A_0166 |
-
-
- | 340 |
- HB_200_AD |
- AD |
- NA |
- 5210_VC_A_0905 |
-
-
- | 341 |
- HB_205_AD |
- AD |
- NA |
- 5235_VC_A_0419 |
-
-
- | 342 |
- HB_208_AD |
- AD |
- NA |
- 5249_VC_A_0422 |
-
-
- | 343 |
- HB_209_AD |
- AD |
- NA |
- 5252_VC_A_0907 |
-
-
- | 344 |
- HB_211_AD |
- AD |
- NA |
- 5257_VC_A_0169 |
-
-
- | 345 |
- HB_216_AD |
- AD |
- NA |
- 5272_VC_A_0425 |
-
-
- | 346 |
- HB_219_AD |
- AD |
- NA |
- 5279_CR_A_0147 |
-
-
- | 347 |
- HB_221_AD |
- AD |
- NA |
- 5283_VC_A_0145 |
-
-
- | 348 |
- HB_222_AD |
- AD |
- NA |
- 5285_VC_A_0141 |
-
-
- | 349 |
- HB_224_AD |
- AD |
- NA |
- 5288_VC_A_0428 |
-
-
- | 350 |
- HB_230_AD |
- AD |
- NA |
- 5301_VC_A_0174 |
-
-
- | 351 |
- HB_231_AD |
- AD |
- NA |
- 5305_VC_A_1384 |
-
-
- | 352 |
- HB_232_AD |
- AD |
- NA |
- 5310_CR_A_0176 |
-
-
- | 353 |
- HB_234_AD |
- AD |
- NA |
- 5313_PF_A_2618 |
-
-
- | 354 |
- HB_236_AD |
- AD |
- NA |
- 5317_PF_A_2624 |
-
-
- | 355 |
- HB_238_AD |
- AD |
- NA |
- 5322_CR_A_2632 |
-
-
- | 356 |
- HB_240_AD |
- AD |
- NA |
- 5325_VC_A_0137 |
-
-
- | 357 |
- HB_244_AD |
- AD |
- NA |
- 5337_VC_A_1387 |
-
-
- | 358 |
- HB_245_AD |
- AD |
- NA |
- 5339_VC_A_0181 |
-
-
- | 359 |
- HB_250_AD |
- AD |
- NA |
- 5346_VC_A_1393 |
-
-
- | 360 |
- HB_251_AD |
- AD |
- NA |
- 5350_VC_A_0184 |
-
-
- | 361 |
- HB_252_AD |
- AD |
- NA |
- 5355_VC_A_0133 |
-
-
- | 362 |
- HB_253_AD |
- AD |
- NA |
- 5359_CR_A_1395 |
-
-
- | 363 |
- HB_258_AD |
- AD |
- NA |
- 5370_PF_A_1400 |
-
-
- | 364 |
- HB_259_AD |
- AD |
- NA |
- 5371_PF_A_2636 |
-
-
- | 365 |
- HB_260_AD |
- AD |
- NA |
- 5375_VC_A_0188 |
-
-
- | 366 |
- HB_263_AD |
- AD |
- NA |
- 5381_VC_A_0022 |
-
-
- | 367 |
- HB_265_AD |
- AD |
- NA |
- 5385_VC_A_1402 |
-
-
- | 368 |
- HB_267_AD |
- AD |
- NA |
- 5389_VC_A_0928 |
-
-
- | 369 |
- HB_268_AD |
- AD |
- NA |
- 5390_CR_A_0151 |
-
-
- | 370 |
- HB_273_AD |
- AD |
- NA |
- 5400_PF_A_2645 |
-
-
- | 371 |
- HB_274_AD |
- AD |
- NA |
- 5401_VC_A_0931 |
-
-
- | 372 |
- HB_275_AD |
- AD |
- NA |
- 5404_PF_A_2648 |
-
-
- | 373 |
- HB_276_AD |
- AD |
- NA |
- 5406_VC_A_0933 |
-
-
- | 374 |
- HB_277_AD |
- AD |
- NA |
- 5407_PF_A_2651 |
-
-
- | 375 |
- HB_280_AD |
- AD |
- NA |
- 5412_VC_A_0935 |
-
-
- | 376 |
- HB_281_AD |
- AD |
- NA |
- 5413_PF_A_2657 |
-
-
- | 377 |
- HB_283_AD |
- AD |
- NA |
- 5419_VC_A_0937 |
-
-
- | 378 |
- HB_284_AD |
- AD |
- NA |
- 5420_VC_A_0939 |
-
-
- | 379 |
- HB_285_AD |
- AD |
- NA |
- 5421_CR_A_0432 |
-
-
- | 380 |
- HB_286_AD |
- AD |
- NA |
- 5423_PF_A_2660 |
-
-
- | 381 |
- HB_288_AD |
- AD |
- NA |
- 5425_PF_A_2666 |
-
-
- | 382 |
- HB_289_AD |
- AD |
- NA |
- 5426_VC_A_1405 |
-
-
- | 383 |
- HB_290_AD |
- AD |
- NA |
- 5433_VC_A_0434 |
-
-
- | 384 |
- HB_296_AD |
- AD |
- NA |
- 5456_PF_A_2675 |
-
-
- | 385 |
- HB_299_AD |
- AD |
- NA |
- 5461_VC_A_0192 |
-
-
- | 386 |
- HB_302_AD |
- AD |
- NA |
- 5465_PF_A_2678 |
-
-
- | 387 |
- HB_303_AD |
- AD |
- NA |
- 5469_VC_A_1417 |
-
-
- | 388 |
- HB_305_AD |
- AD |
- NA |
- 5479_PF_A_1421 |
-
-
- | 389 |
- HB_306_AD |
- AD |
- NA |
- 5480_VC_A_0437 |
-
-
- | 390 |
- HB_307_AD |
- AD |
- NA |
- 5482_VC_A_0028 |
-
-
- | 391 |
- HB_308_AD |
- AD |
- NA |
- 5483_VC_A_0941 |
-
-
- | 392 |
- HB_309_AD |
- AD |
- NA |
- 5487_CR_A_0441 |
-
-
- | 393 |
- HB_310_AD |
- AD |
- NA |
- 5488_CR_A_0194 |
-
-
- | 394 |
- HB_312_AD |
- AD |
- NA |
- 5500_VC_A_0198 |
-
-
- | 395 |
- HB_313_AD |
- AD |
- NA |
- 5502_PF_A_2684 |
-
-
- | 396 |
- HB_315_AD |
- AD |
- NA |
- 5513_PF_A_2687 |
-
-
- | 397 |
- HB_316_AD |
- AD |
- NA |
- 5516_PF_A_2690 |
-
-
- | 398 |
- HB_317_AD |
- AD |
- NA |
- 5517_PF_A_2693 |
-
-
- | 399 |
- HB_318_AD |
- AD |
- NA |
- 5518_CR_A_0030 |
-
-
- | 400 |
- HB_319_AD |
- AD |
- NA |
- 5519_CR_A_2695 |
-
-
- | 401 |
- HB_320_AD |
- AD |
- NA |
- 5520_PF_A_2699 |
-
-
- | 402 |
- HB_322_AD |
- AD |
- NA |
- 5527_VC_A_0945 |
-
-
- | 403 |
- HB_325_AD |
- AD |
- NA |
- 5532_PF_A_2702 |
-
-
- | 404 |
- HB_328_AD |
- AD |
- NA |
- 5541_PF_A_2705 |
-
-
- | 405 |
- HB_330_AD |
- AD |
- NA |
- 5544_VC_A_0201 |
-
-
- | 406 |
- HB_334_AD |
- AD |
- NA |
- 5554_VC_A_0452 |
-
-
- | 407 |
- HB_335_AD |
- AD |
- NA |
- 5557_VC_A_0950 |
-
-
- | 408 |
- HB_337_AD |
- AD |
- NA |
- 5560_VC_A_0204 |
-
-
- | 409 |
- HB_342_AD |
- AD |
- NA |
- 5571_PF_A_1430 |
-
-
- | 410 |
- HB_345_AD |
- AD |
- NA |
- 5583_PF_A_2708 |
-
-
- | 411 |
- HB_347_AD |
- AD |
- NA |
- 5589_PF_A_2714 |
-
-
- | 412 |
- HB_349_AD |
- AD |
- NA |
- 5592_PF_A_2717 |
-
-
- | 413 |
- HB_352_AD |
- AD |
- NA |
- 5604_VC_A_0037 |
-
-
- | 414 |
- HB_353_AD |
- AD |
- NA |
- 5607_PF_A_2723 |
-
-
- | 415 |
- HB_356_AD |
- AD |
- NA |
- 5615_VC_A_0041 |
-
-
- | 416 |
- HB_357_AD |
- AD |
- NA |
- 5616_CR_A_0127 |
-
-
- | 417 |
- HB_358_AD |
- AD |
- NA |
- 5617_CR_A_0456 |
-
-
- | 418 |
- HB_359_AD |
- AD |
- NA |
- 5618_CR_A_0044 |
-
-
- | 419 |
- HB_362_AD |
- AD |
- NA |
- 5625_CR_A_2495 |
-
-
- | 420 |
- HB_363_AD |
- AD |
- NA |
- 5626_CR_A_2498 |
-
-
- | 421 |
- HB_364_AD |
- AD |
- NA |
- 5629_CR_A_0390 |
-
-
- | 422 |
- HB_369_AD |
- AD |
- NA |
- 5643_VC_A_1143 |
-
-
- | 423 |
- HB_373_AD |
- AD |
- NA |
- 5654_VC_A_0047 |
-
-
- | 424 |
- HB_375_AD |
- AD |
- NA |
- 5660_CR_A_0462 |
-
-
- | 425 |
- HB_376_AD |
- AD |
- NA |
- 5661_VC_A_0464 |
-
-
- | 426 |
- HB_377_AD |
- AD |
- NA |
- 5667_VC_A_2509 |
-
-
- | 427 |
- HB_378_AD |
- AD |
- NA |
- 5668_VC_A_1438 |
-
-
- | 428 |
- HB_383_AD |
- AD |
- NA |
- 5686_CR_A_2728 |
-
-
- | 429 |
- HB_386_AD |
- AD |
- NA |
- 5695_VC_A_0953 |
-
-
- | 430 |
- HB_389_AD |
- AD |
- NA |
- 5700_VC_A_2514 |
-
-
- | 431 |
- HB_391_AD |
- AD |
- NA |
- 5705_CR_A_0474 |
-
-
- | 432 |
- HB_392_AD |
- AD |
- NA |
- 5706_VC_A_0476 |
-
-
- | 433 |
- HB_394_AD |
- AD |
- NA |
- 5713_VC_A_0479 |
-
-
- | 434 |
- HB_397_AD |
- AD |
- NA |
- 5721_CR_A_0210 |
-
-
- | 435 |
- HB_404_AD |
- AD |
- NA |
- 5735_CR_A_0489 |
-
-
- | 436 |
- HB_406_AD |
- AD |
- NA |
- 5744_CR_A_0960 |
-
-
- | 437 |
- HB_409_AD |
- AD |
- NA |
- 5749_CR_A_0159 |
-
-
- | 438 |
- HB_410_AD |
- AD |
- NA |
- 5751_CR_A_2518 |
-
-
- | 439 |
- HB_411_AD |
- AD |
- NA |
- 5755_CR_A_2731 |
-
-
- | 440 |
- HB_413_AD |
- AD |
- NA |
- 5766_VC_A_0214 |
-
-
- | 441 |
- HB_419_AD |
- AD |
- NA |
- 5790_VC_A_0217 |
-
-
- | 442 |
- HB_420_AD |
- AD |
- NA |
- 5796_CR_A_0964 |
-
-
- | 443 |
- HB_428_AD |
- AD |
- NA |
- 5811_CR_A_2524 |
-
-
- | 444 |
- HB_429_AD |
- AD |
- NA |
- 5819_CR_A_2527 |
-
-
- | 445 |
- HB_430_AD |
- AD |
- NA |
- 5822_CR_A_2530 |
-
-
- | 446 |
- HB_434_AD |
- AD |
- NA |
- 5828_CR_A_2533 |
-
-
- | 447 |
- HB_435_AD |
- AD |
- NA |
- 5831_CR_A_0222 |
-
-
- | 448 |
- HB_437_AD |
- AD |
- NA |
- 5839_CR_A_2539 |
-
-
- | 449 |
- HB_438_AD |
- AD |
- NA |
- 5843_CR_A_0227 |
-
-
- | 450 |
- HB_439_AD |
- AD |
- NA |
- 5845_CR_A_0230 |
-
-
- | 451 |
- HB_441_AD |
- AD |
- NA |
- 5849_CR_A_0233 |
-
-
- | 452 |
- HB_442_AD |
- AD |
- NA |
- 5850_CR_A_0495 |
-
-
- | 453 |
- HB_445_AD |
- AD |
- NA |
- 5858_CR_A_0969 |
-
-
- | 454 |
- HB_448_AD |
- AD |
- NA |
- 5864_CR_A_0974 |
-
-
- | 455 |
- HB_451_AD |
- AD |
- NA |
- 5871_CR_A_2542 |
-
-
- | 456 |
- HB_454_AD |
- AD |
- NA |
- 5879_CR_A_2545 |
-
-
- | 457 |
- HB_455_AD |
- AD |
- NA |
- 5887_CR_A_0976_Bis |
-
-
- | 458 |
- HB_459_AD |
- AD |
- NA |
- 5898_CR_A_2548 |
-
-
- | 459 |
- HB_460_AD |
- AD |
- NA |
- 5900_VC_A_0237 |
-
-
- | 460 |
- HB_461_AD |
- AD |
- NA |
- 5901_CR_A_0239 |
-
-
- | 461 |
- HB_469_AD |
- AD |
- NA |
- 5914_CR_A_2554 |
-
-
- | 462 |
- HB_471_AD |
- AD |
- NA |
- 5922_VC_A_0246 |
-
-
- | 463 |
- HB_473_AD |
- AD |
- NA |
- 5927_CR_A_2560 |
-
-
- | 464 |
- HB_474_AD |
- AD |
- NA |
- 5933_VC_A_1071 |
-
-
- | 465 |
- HB_477_AD |
- AD |
- NA |
- 5939_CR_A_1151 |
-
-
- | 466 |
- HB_479_AD |
- AD |
- NA |
- 5945_VC_A_0983 |
-
-
- | 467 |
- HB_484_AD |
- AD |
- NA |
- 5956_CR_A_0123 |
-
-
- | 468 |
- HB_489_AD |
- AD |
- NA |
- 5968_VC_A_1075 |
-
-
- | 469 |
- HB_491_AD |
- AD |
- NA |
- 5971_CR_A_0119 |
-
-
- | 470 |
- HB_492_AD |
- AD |
- NA |
- 5972_VC_A_0251 |
-
-
- | 471 |
- HB_494_AD |
- AD |
- NA |
- 5979_CR_A_0115 |
-
-
- | 472 |
- HB_498_AD |
- AD |
- NA |
- 5988_VC_A_0503 |
-
-
- | 473 |
- HB_502_AD |
- AD |
- NA |
- 5994_PF_A_1605 |
-
-
- | 474 |
- HB_503_AD |
- AD |
- NA |
- 5995_CR_A_2563 |
-
-
- | 475 |
- HB_510_AD |
- AD |
- NA |
- 6017_CR_A_0048 |
-
-
- | 476 |
- HB_514_AD |
- AD |
- NA |
- 6025_VC_A_0506 |
-
-
- | 477 |
- HB_517_AD |
- AD |
- NA |
- 6031_VC_A_0258 |
-
-
- | 478 |
- HB_520_AD |
- AD |
- NA |
- 6035_VC_A_1621 |
-
-
- | 479 |
- HB_523_AD |
- AD |
- NA |
- 6038_VC_A_0261 |
-
-
- | 480 |
- HB_524_AD |
- AD |
- NA |
- 6042_VC_A_1156 |
-
-
- | 481 |
- HB_525_AD |
- AD |
- NA |
- 6044_VC_A_0264 |
-
-
- | 482 |
- HB_531_AD |
- AD |
- NA |
- 6056_CR_A_0999 |
-
-
- | 483 |
- HB_533_AD |
- AD |
- NA |
- 6061_PF_A_1650 |
-
-
- | 484 |
- HB_534_AD |
- AD |
- NA |
- 6066_VC_A_0270 |
-
-
- | 485 |
- HB_535_AD |
- AD |
- NA |
- 6067_PF_A_1452 |
-
-
- | 486 |
- HB_536_AD |
- AD |
- NA |
- 6068_VC_A_0273 |
-
-
- | 487 |
- HB_545_AD |
- AD |
- NA |
- 6102_CR_A_1661 |
-
-
- | 488 |
- HB_546_AD |
- AD |
- NA |
- 6107_CR_A_0055 |
-
-
- | 489 |
- HB_550_AD |
- AD |
- NA |
- 6120_VC_A_0058 |
-
-
- | 490 |
- HB_552_AD |
- AD |
- NA |
- 6126_VC_A_1675 |
-
-
- | 491 |
- HB_553_AD |
- AD |
- NA |
- 6129_PF_A_0274 |
-
-
- | 492 |
- HB_554_AD |
- AD |
- NA |
- 6130_VC_A_1678 |
-
-
- | 493 |
- HB_555_AD |
- AD |
- NA |
- 6131_CR_A_0510 |
-
-
- | 494 |
- HB_556_AD |
- AD |
- NA |
- 6132_CR_A_0513 |
-
-
- | 495 |
- HB_558_AD |
- AD |
- NA |
- 6137_VC_A_1681 |
-
-
- | 496 |
- HB_564_AD |
- AD |
- NA |
- 6153_VC_A_1465 |
-
-
- | 497 |
- HB_565_AD |
- AD |
- NA |
- 6154_VC_A_1468 |
-
-
- | 498 |
- HB_566_AD |
- AD |
- NA |
- 6157_VC_A_0062 |
-
-
- | 499 |
- HB_568_AD |
- AD |
- NA |
- 6164_CR_A_1005 |
-
-
- | 500 |
- HB_571_AD |
- AD |
- NA |
- 6171_CR_A_0065 |
-
-
- | 501 |
- HB_573_AD |
- AD |
- NA |
- 6174_VC_A_0068 |
-
-
- | 502 |
- HB_576_AD |
- AD |
- NA |
- 6180_CR_A_0281 |
-
-
- | 503 |
- HB_583_AD |
- AD |
- NA |
- 6194_VC_A_0071 |
-
-
- | 504 |
- HB_585_AD |
- AD |
- NA |
- 6198_VC_A_0073 |
-
-
- | 505 |
- HB_590_AD |
- AD |
- NA |
- 6215_VC_A_0518 |
-
-
- | 506 |
- HB_591_AD |
- AD |
- NA |
- 6216_VC_A_1476 |
-
-
- | 507 |
- HB_592_AD |
- AD |
- NA |
- 6218_CR_A_0522 |
-
-
- | 508 |
- HB_594_AD |
- AD |
- NA |
- 6223_VC_A_0288 |
-
-
- | 509 |
- HB_596_AD |
- AD |
- NA |
- 6226_CR_A_0076 |
-
-
- | 510 |
- HB_597_AD |
- AD |
- NA |
- 6227_VC_A_0080 |
-
-
- | 511 |
- HB_598_AD |
- AD |
- NA |
- 6231_VC_A_1479 |
-
-
- | 512 |
- HB_605_AD |
- AD |
- NA |
- 6261_VC_A_0084 |
-
-
- | 513 |
- HB_608_AD |
- AD |
- NA |
- 6268_CR_A_0525 |
-
-
- | 514 |
- HB_611_AD |
- AD |
- NA |
- 6279_VC_A_0089 |
-
-
- | 515 |
- HB_612_AD |
- AD |
- NA |
- 6280_VC_A_0091 |
-
-
- | 516 |
- HB_613_AD |
- AD |
- NA |
- 6281_CR_A_0528 |
-
-
- | 517 |
- HB_621_AD |
- AD |
- NA |
- 6308_VC_A_1503 |
-
-
- | 518 |
- HB_623_AD |
- AD |
- NA |
- 6311_CR_A_0531 |
-
-
- | 519 |
- HB_624_AD |
- AD |
- NA |
- 6312_CR_A_0534 |
-
-
- | 520 |
- HB_630_AD |
- AD |
- NA |
- 6324_PF_A_1514 |
-
-
- | 521 |
- HB_633_AD |
- AD |
- NA |
- 6332_VC_A_1518 |
-
-
- | 522 |
- HB_634_AD |
- AD |
- NA |
- 6335_VC_A_0536 |
-
-
- | 523 |
- HB_635_AD |
- AD |
- NA |
- 6336_CR_A_0290 |
-
-
- | 524 |
- HB_636_AD |
- AD |
- NA |
- 6338_VC_A_0539 |
-
-
- | 525 |
- HB_642_AD |
- AD |
- NA |
- 6358_VC_A_0545 |
-
-
- | 526 |
- HB_652_AD |
- AD |
- NA |
- 6387_VC_A_0093 |
-
-
- | 527 |
- HB_657_AD |
- AD |
- NA |
- 6394_VC_A_0551 |
-
-
- | 528 |
- HB_664_AD |
- AD |
- NA |
- 6416_VC_A_1095 |
-
-
- | 529 |
- HB_666_AD |
- AD |
- NA |
- 6422_CR_A_0555 |
-
-
- | 530 |
- HB_669_AD |
- AD |
- NA |
- 6431_VC_A_0294 |
-
-
- | 531 |
- HB_674_AD |
- AD |
- NA |
- 6449_VC_A_1183 |
-
-
- | 532 |
- HB_680_AD |
- AD |
- NA |
- 6458_CR_A_2570 |
-
-
- | 533 |
- HB_685_AD |
- AD |
- NA |
- 6481_VC_A_0560 |
-
-
- | 534 |
- HB_690_AD |
- AD |
- NA |
- 6489_CR_A_0100 |
-
-
- | 535 |
- HB_696_AD |
- AD |
- NA |
- 6511_VC_A_1119 |
-
-
- | 536 |
- HB_698_AD |
- AD |
- NA |
- 6515_CR_A_0564 |
-
-
- | 537 |
- HB_699_AD |
- AD |
- NA |
- 6518_VC_A_0103 |
-
-
- | 538 |
- HB_703_AD |
- AD |
- NA |
- 6523_VC_A_0107 |
-
-
- | 539 |
- HB_704_AD |
- AD |
- NA |
- 6530_VC_A_0112 |
-
-
- | 540 |
- HB_706_AD |
- AD |
- NA |
- 6534_VC_A_0306 |
-
-
- | 541 |
- HB_712_AD |
- AD |
- NA |
- 6546_PF_A_1194 |
-
-
- | 542 |
- HB_713_AD |
- AD |
- NA |
- 6548_PF_A_1541 |
-
-
- | 543 |
- HB_715_AD |
- AD |
- NA |
- 6550_VC_A_1201 |
-
-
- | 544 |
- HB_718_AD |
- AD |
- NA |
- 6554_PF_A_1203 |
-
-
- | 545 |
- HB_720_AD |
- AD |
- NA |
- 6559_PF_A_2287 |
-
-
- | 546 |
- HB_722_AD |
- AD |
- NA |
- 6561_CR_A_2582 |
-
-
- | 547 |
- HB_723_AD |
- AD |
- NA |
- 6562_PF_A_2290 |
-
-
- | 548 |
- HB_724_AD |
- AD |
- NA |
- 6564_CR_A_2585 |
-
-
- | 549 |
- HB_727_AD |
- AD |
- NA |
- 6575_CR_A_2298 |
-
-
- | 550 |
- HB_728_AD |
- AD |
- NA |
- 6577_PF_A_2299 |
-
-
- | 551 |
- HB_729_AD |
- AD |
- NA |
- 6578_PF_A_2302 |
-
-
- | 552 |
- HB_731_AD |
- AD |
- NA |
- 6582_VC_A_1207 |
-
-
- | 553 |
- HB_733_AD |
- AD |
- NA |
- 6585_VC_A_1210 |
-
-
- | 554 |
- HB_736_AD |
- AD |
- NA |
- 6590_PF_A_1215 |
-
-
- | 555 |
- HB_743_AD |
- AD |
- NA |
- 6603_PF_A_1448 |
-
-
- | 556 |
- HB_745_AD |
- AD |
- NA |
- 6610_PF_A_1227 |
-
-
- | 557 |
- HB_746_AD |
- AD |
- NA |
- 6612_PF_A_2308 |
-
-
- | 558 |
- HB_749_AD |
- AD |
- NA |
- 6617_VC_A_2587 |
-
-
- | 559 |
- HB_751_AD |
- AD |
- NA |
- 6629_VC_A_2330 |
-
-
- | 560 |
- HB_752_AD |
- AD |
- NA |
- 6630_VC_A_2590 |
-
-
- | 561 |
- HB_753_AD |
- AD |
- NA |
- 6632_PF_A_2332 |
-
-
- | 562 |
- HB_754_AD |
- AD |
- NA |
- 6637_VC_A_2596 |
-
-
- | 563 |
- HB_755_AD |
- AD |
- NA |
- 6638_VC_A_2599 |
-
-
- | 564 |
- HB_756_AD |
- AD |
- NA |
- 6639_VC_A_2336 |
-
-
- | 565 |
- HB_757_AD |
- AD |
- NA |
- 6641_PF_A_2338 |
-
-
- | 566 |
- HB_763_AD |
- AD |
- NA |
- 6654_VC_A_1237 |
-
-
- | 567 |
- HB_773_AD |
- AD |
- NA |
- 6681_VC_A_1252 |
-
-
- | 568 |
- HB_775_AD |
- AD |
- NA |
- 6693_VC_A_2348 |
-
-
- | 569 |
- HB_776_AD |
- AD |
- NA |
- 6694_VC_A_2351 |
-
-
- | 570 |
- HB_777_AD |
- AD |
- NA |
- 6695_PF_A_2353 |
-
-
- | 571 |
- HB_779_AD |
- AD |
- NA |
- 6699_PF_A_2359 |
-
-
- | 572 |
- HB_781_AD |
- AD |
- NA |
- 6708_VC_A_2366 |
-
-
- | 573 |
- HB_782_AD |
- AD |
- NA |
- 6776_PF_A_2607 |
-
-
- | 574 |
- HB_783_AD |
- AD |
- NA |
- 6778_PF_A_2368 |
-
-
- | 575 |
- HB_784_AD |
- AD |
- NA |
- 6779_PF_A_2371 |
-
-
- | 576 |
- HB_785_AD |
- AD |
- NA |
- 6780_PF_A_2374 |
-
-
- | 577 |
- HB_786_AD |
- AD |
- NA |
- 6782_PF_A_2377 |
-
-
- | 578 |
- HB_787_AD |
- AD |
- NA |
- 6784_PF_A_2380 |
-
-
- | 579 |
- HB_788_AD |
- AD |
- NA |
- 6785_CR_A_2385 |
-
-
- | 580 |
- HB_789_AD |
- AD |
- NA |
- 6787_CR_A_2388 |
-
-
- | 581 |
- HB_791_AD |
- AD |
- NA |
- 6790_PF_A_2392 |
-
-
- | 582 |
- HB_792_AD |
- AD |
- NA |
- 6791_PF_A_2395 |
-
-
- | 583 |
- HB_793_AD |
- AD |
- NA |
- 6793_PF_A_2398 |
-
-
- | 584 |
- HB_794_AD |
- AD |
- NA |
- 6794_PF_A_2401 |
-
-
- | 585 |
- HB_795_AD |
- AD |
- NA |
- 6797_PF_A_2404 |
-
-
- | 586 |
- HB_796_AD |
- AD |
- NA |
- 6798_PF_A_2407 |
-
-
- | 587 |
- HB_797_AD |
- AD |
- NA |
- 6799_VC_A_2411 |
-
-
- | 588 |
- HB_798_AD |
- AD |
- NA |
- 6801_VC_A_2414 |
-
-
- | 589 |
- HB_799_AD |
- AD |
- NA |
- 6803_VC_A_2417 |
-
-
- | 590 |
- HB_801_AD |
- AD |
- NA |
- 6809_PF_A_2422 |
-
-
- | 591 |
- HB_803_AD |
- AD |
- NA |
- 6818_CR_A_2430 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/HBTRC_MLPFC_AD_0611/experiment-design.rtf b/general/datasets/HBTRC_MLPFC_AD_0611/experiment-design.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_AD_0611/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_AD_0611/notes.rtf b/general/datasets/HBTRC_MLPFC_AD_0611/notes.rtf
deleted file mode 100644
index ff90e34..0000000
--- a/general/datasets/HBTRC_MLPFC_AD_0611/notes.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Species: Human
-Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
-Disease: Neurological Disease
-Investigator: Francine Benes/ Eric Schadt
-Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
-Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC_MLPFC_AD_0611/platform.rtf b/general/datasets/HBTRC_MLPFC_AD_0611/platform.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_AD_0611/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_AD_0611/processing.rtf b/general/datasets/HBTRC_MLPFC_AD_0611/processing.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_AD_0611/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_AD_0611/summary.rtf b/general/datasets/HBTRC_MLPFC_AD_0611/summary.rtf
deleted file mode 100644
index 5cde3bf..0000000
--- a/general/datasets/HBTRC_MLPFC_AD_0611/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC_MLPFC_AD_0611/tissue.rtf b/general/datasets/HBTRC_MLPFC_AD_0611/tissue.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_AD_0611/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_HD_0611/acknowledgment.rtf b/general/datasets/HBTRC_MLPFC_HD_0611/acknowledgment.rtf
deleted file mode 100644
index 208cb6e..0000000
--- a/general/datasets/HBTRC_MLPFC_HD_0611/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC_MLPFC_HD_0611/cases.rtf b/general/datasets/HBTRC_MLPFC_HD_0611/cases.rtf
deleted file mode 100644
index 86ed08e..0000000
--- a/general/datasets/HBTRC_MLPFC_HD_0611/cases.rtf
+++ /dev/null
@@ -1,4166 +0,0 @@
-This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- | Series |
- Cerebellum in GN |
- Condition |
- Gender |
- BioSample Name |
-
-
- | 1 |
- HB_029_N |
- N |
- NA |
- 3405_VC_N_0859 |
-
-
- | 2 |
- HB_058_N |
- N |
- NA |
- 4021_VC_N_0854 |
-
-
- | 3 |
- HB_064_N |
- N |
- NA |
- 4338_VC_N_0861 |
-
-
- | 4 |
- HB_086_N |
- N |
- NA |
- 4729_PF_N_0756 |
-
-
- | 5 |
- HB_091_N |
- N |
- NA |
- 4741_VC_N_0864 |
-
-
- | 6 |
- HB_092_N |
- N |
- NA |
- 4744_VC_N_0865 |
-
-
- | 7 |
- HB_102_N |
- N |
- NA |
- 4810_VC_N_0869 |
-
-
- | 8 |
- HB_119_N |
- N |
- NA |
- 4872_VC_N_0878 |
-
-
- | 9 |
- HB_147_N |
- N |
- NA |
- 5021_VC_N_0852 |
-
-
- | 10 |
- HB_161_N |
- N |
- NA |
- 5077_VC_N_0851 |
-
-
- | 11 |
- HB_162_N |
- N |
- NA |
- 5081_VC_N_1021 |
-
-
- | 12 |
- HB_166_N |
- N |
- NA |
- 5095_VC_N_1024 |
-
-
- | 13 |
- HB_183_N |
- N |
- NA |
- 5162_VC_N_0850 |
-
-
- | 14 |
- HB_206_N |
- N |
- NA |
- 5245_VC_N_0849 |
-
-
- | 15 |
- HB_215_N |
- N |
- NA |
- 5270_VC_N_0848 |
-
-
- | 16 |
- HB_218_N |
- N |
- NA |
- 5276_CR_N_0912 |
-
-
- | 17 |
- HB_223_N |
- N |
- NA |
- 5287_VC_N_0916 |
-
-
- | 18 |
- HB_226_N |
- N |
- NA |
- 5294_VC_N_0919 |
-
-
- | 19 |
- HB_241_N |
- N |
- NA |
- 5326_CR_N_0652 |
-
-
- | 20 |
- HB_243_N |
- N |
- NA |
- 5333_VC_N_1262 |
-
-
- | 21 |
- HB_247_N |
- N |
- NA |
- 5341_VC_N_0923 |
-
-
- | 22 |
- HB_257_N |
- N |
- NA |
- 5368_PF_N_1032 |
-
-
- | 23 |
- HB_264_N |
- N |
- NA |
- 5384_VC_N_0924 |
-
-
- | 24 |
- HB_295_N |
- N |
- NA |
- 5452_VC_N_1268 |
-
-
- | 25 |
- HB_300_N |
- N |
- NA |
- 5463_VC_N_0845 |
-
-
- | 26 |
- HB_311_N |
- N |
- NA |
- 5489_CR_N_0942 |
-
-
- | 27 |
- HB_324_N |
- N |
- NA |
- 5531_VC_N_0844 |
-
-
- | 28 |
- HB_332_N |
- N |
- NA |
- 5547_VC_N_0843 |
-
-
- | 29 |
- HB_340_N |
- N |
- NA |
- 5568_VC_N_0842 |
-
-
- | 30 |
- HB_360_N |
- N |
- NA |
- 5619_CR_N_0645 |
-
-
- | 31 |
- HB_365_N |
- N |
- NA |
- 5632_VC_N_0838 |
-
-
- | 32 |
- HB_367_N |
- N |
- NA |
- 5637_VC_N_0837 |
-
-
- | 33 |
- HB_382_N |
- N |
- NA |
- 5684_PF_N_1270 |
-
-
- | 34 |
- HB_396_N |
- N |
- NA |
- 5718_VC_N_0956 |
-
-
- | 35 |
- HB_398_N |
- N |
- NA |
- 5722_VC_N_1044 |
-
-
- | 36 |
- HB_400_N |
- N |
- NA |
- 5726_VC_N_0834_Bis |
-
-
- | 37 |
- HB_403_N |
- N |
- NA |
- 5734_VC_N_0833 |
-
-
- | 38 |
- HB_414_N |
- N |
- NA |
- 5772_VC_N_0832_Bis |
-
-
- | 39 |
- HB_416_N |
- N |
- NA |
- 5778_CR_N_0962 |
-
-
- | 40 |
- HB_418_N |
- N |
- NA |
- 5789_PF_N_1273 |
-
-
- | 41 |
- HB_421_N |
- N |
- NA |
- 5799_VC_N_1058 |
-
-
- | 42 |
- HB_423_N |
- N |
- NA |
- 5803_VC_N_0966 |
-
-
- | 43 |
- HB_426_N |
- N |
- NA |
- 5806_PF_N_1064 |
-
-
- | 44 |
- HB_427_N |
- N |
- NA |
- 5810_CR_N_0636 |
-
-
- | 45 |
- HB_431_N |
- N |
- NA |
- 5823_VC_N_0829 |
-
-
- | 46 |
- HB_432_N |
- N |
- NA |
- 5826_VC_N_0828 |
-
-
- | 47 |
- HB_433_N |
- N |
- NA |
- 5827_VC_N_0827 |
-
-
- | 48 |
- HB_436_N |
- N |
- NA |
- 5832_PF_N_1145 |
-
-
- | 49 |
- HB_443_N |
- N |
- NA |
- 5852_VC_N_0826 |
-
-
- | 50 |
- HB_446_N |
- N |
- NA |
- 5859_VC_N_0825 |
-
-
- | 51 |
- HB_449_N |
- N |
- NA |
- 5866_VC_N_0824 |
-
-
- | 52 |
- HB_450_N |
- N |
- NA |
- 5867_VC_N_1277 |
-
-
- | 53 |
- HB_453_N |
- N |
- NA |
- 5876_VC_N_0823 |
-
-
- | 54 |
- HB_462_N |
- N |
- NA |
- 5903_VC_N_0822 |
-
-
- | 55 |
- HB_464_N |
- N |
- NA |
- 5905_VC_N_0820 |
-
-
- | 56 |
- HB_468_N |
- N |
- NA |
- 5912_VC_N_1286 |
-
-
- | 57 |
- HB_472_N |
- N |
- NA |
- 5925_VC_N_1289 |
-
-
- | 58 |
- HB_475_N |
- N |
- NA |
- 5936_VC_N_0979 |
-
-
- | 59 |
- HB_476_N |
- N |
- NA |
- 5938_VC_N_0819 |
-
-
- | 60 |
- HB_480_N |
- N |
- NA |
- 5946_VC_N_0985 |
-
-
- | 61 |
- HB_485_N |
- N |
- NA |
- 5959_VC_N_0818 |
-
-
- | 62 |
- HB_486_N |
- N |
- NA |
- 5963_VC_N_0987 |
-
-
- | 63 |
- HB_495_N |
- N |
- NA |
- 5980_VC_N_0989 |
-
-
- | 64 |
- HB_497_N |
- N |
- NA |
- 5985_VC_N_0990 |
-
-
- | 65 |
- HB_500_N |
- N |
- NA |
- 5990_VC_N_0817 |
-
-
- | 66 |
- HB_501_N |
- N |
- NA |
- 5991_VC_N_0816 |
-
-
- | 67 |
- HB_504_N |
- N |
- NA |
- 5996_VC_N_0815 |
-
-
- | 68 |
- HB_505_N |
- N |
- NA |
- 5998_VC_N_0814 |
-
-
- | 69 |
- HB_507_N |
- N |
- NA |
- 6006_VC_N_0813 |
-
-
- | 70 |
- HB_508_N |
- N |
- NA |
- 6007_CR_N_0618 |
-
-
- | 71 |
- HB_509_N |
- N |
- NA |
- 6008_PF_N_1081 |
-
-
- | 72 |
- HB_512_N |
- N |
- NA |
- 6023_PF_N_1155 |
-
-
- | 73 |
- HB_516_N |
- N |
- NA |
- 6030_VC_N_0810 |
-
-
- | 74 |
- HB_519_N |
- N |
- NA |
- 6034_VC_N_0809 |
-
-
- | 75 |
- HB_532_N |
- N |
- NA |
- 6060_VC_N_1292 |
-
-
- | 76 |
- HB_541_N |
- N |
- NA |
- 6092_VC_N_1001 |
-
-
- | 77 |
- HB_542_N |
- N |
- NA |
- 6096_VC_N_0807 |
-
-
- | 78 |
- HB_544_N |
- N |
- NA |
- 6101_CR_N_1161 |
-
-
- | 79 |
- HB_547_N |
- N |
- NA |
- 6110_VC_N_1295 |
-
-
- | 80 |
- HB_551_N |
- N |
- NA |
- 6124_VC_N_0806 |
-
-
- | 81 |
- HB_557_N |
- N |
- NA |
- 6134_PF_N_1297 |
-
-
- | 82 |
- HB_560_N |
- N |
- NA |
- 6142_VC_N_0805 |
-
-
- | 83 |
- HB_569_N |
- N |
- NA |
- 6166_VC_N_0804 |
-
-
- | 84 |
- HB_570_N |
- N |
- NA |
- 6170_VC_N_0803 |
-
-
- | 85 |
- HB_572_N |
- N |
- NA |
- 6172_VC_N_1008 |
-
-
- | 86 |
- HB_577_N |
- N |
- NA |
- 6182_VC_N_1166 |
-
-
- | 87 |
- HB_579_N |
- N |
- NA |
- 6187_CR_N_0607 |
-
-
- | 88 |
- HB_581_N |
- N |
- NA |
- 6191_VC_N_1010 |
-
-
- | 89 |
- HB_584_N |
- N |
- NA |
- 6196_CR_N_0605 |
-
-
- | 90 |
- HB_586_N |
- N |
- NA |
- 6200_VC_N_0799 |
-
-
- | 91 |
- HB_587_N |
- N |
- NA |
- 6206_PF_N_1176 |
-
-
- | 92 |
- HB_589_N |
- N |
- NA |
- 6213_VC_N_0798 |
-
-
- | 93 |
- HB_601_N |
- N |
- NA |
- 6241_VC_N_0796 |
-
-
- | 94 |
- HB_604_N |
- N |
- NA |
- 6260_VC_N_0794 |
-
-
- | 95 |
- HB_609_N |
- N |
- NA |
- 6270_VC_N_0793 |
-
-
- | 96 |
- HB_618_N |
- N |
- NA |
- 6289_VC_N_0791 |
-
-
- | 97 |
- HB_622_N |
- N |
- NA |
- 6310_VC_N_0790 |
-
-
- | 98 |
- HB_625_N |
- N |
- NA |
- 6314_VC_N_0789 |
-
-
- | 99 |
- HB_637_N |
- N |
- NA |
- 6340_VC_N_0786 |
-
-
- | 100 |
- HB_638_N |
- N |
- NA |
- 6341_VC_N_0785 |
-
-
- | 101 |
- HB_640_N |
- N |
- NA |
- 6347_VC_N_0784 |
-
-
- | 102 |
- HB_641_N |
- N |
- NA |
- 6356_VC_N_0783 |
-
-
- | 103 |
- HB_643_N |
- N |
- NA |
- 6363_VC_N_0781 |
-
-
- | 104 |
- HB_644_N |
- N |
- NA |
- 6366_VC_N_0780 |
-
-
- | 105 |
- HB_645_N |
- N |
- NA |
- 6374_VC_N_0779 |
-
-
- | 106 |
- HB_650_N |
- N |
- NA |
- 6384_VC_N_0777 |
-
-
- | 107 |
- HB_651_N |
- N |
- NA |
- 6386_VC_N_0776 |
-
-
- | 108 |
- HB_653_N |
- N |
- NA |
- 6388_VC_N_0775 |
-
-
- | 109 |
- HB_659_N |
- N |
- NA |
- 6406_VC_N_1180 |
-
-
- | 110 |
- HB_662_N |
- N |
- NA |
- 6411_VC_N_0771 |
-
-
- | 111 |
- HB_663_N |
- N |
- NA |
- 6415_VC_N_0770 |
-
-
- | 112 |
- HB_670_N |
- N |
- NA |
- 6436_VC_N_0769 |
-
-
- | 113 |
- HB_687_N |
- N |
- NA |
- 6484_VC_N_0765 |
-
-
- | 114 |
- HB_689_N |
- N |
- NA |
- 6486_VC_N_0764 |
-
-
- | 115 |
- HB_694_N |
- N |
- NA |
- 6500_VC_N_0763 |
-
-
- | 116 |
- HB_697_N |
- N |
- NA |
- 6512_VC_N_0762 |
-
-
- | 117 |
- HB_700_N |
- N |
- NA |
- 6520_VC_N_0761 |
-
-
- | 118 |
- HB_711_N |
- N |
- NA |
- 6543_PF_N_1191 |
-
-
- | 119 |
- HB_714_N |
- N |
- NA |
- 6549_VC_N_1198 |
-
-
- | 120 |
- HB_717_N |
- N |
- NA |
- 6553_PF_N_2284 |
-
-
- | 121 |
- HB_721_N |
- N |
- NA |
- 6560_VC_N_2578 |
-
-
- | 122 |
- HB_726_N |
- N |
- NA |
- 6573_PF_N_2293 |
-
-
- | 123 |
- HB_730_N |
- N |
- NA |
- 6580_VC_N_2306 |
-
-
- | 124 |
- HB_735_N |
- N |
- NA |
- 6588_VC_N_1213 |
-
-
- | 125 |
- HB_737_N |
- N |
- NA |
- 6593_VC_N_1219 |
-
-
- | 126 |
- HB_738_N |
- N |
- NA |
- 6594_VC_N_1222 |
-
-
- | 127 |
- HB_759_N |
- N |
- NA |
- 6645_VC_N_1231 |
-
-
- | 128 |
- HB_764_N |
- N |
- NA |
- 6655_VC_N_1240 |
-
-
- | 129 |
- HB_765_N |
- N |
- NA |
- 6656_VC_N_1243 |
-
-
- | 130 |
- HB_767_N |
- N |
- NA |
- 6661_PF_N_2341 |
-
-
- | 131 |
- HB_770_N |
- N |
- NA |
- 6669_VC_N_1246 |
-
-
- | 132 |
- HB_772_N |
- N |
- NA |
- 6676_PF_N_1248 |
-
-
- | 133 |
- HB_001_HD |
- HD |
- F |
- 2028_CR_H_2282 |
-
-
- | 134 |
- HB_003_HD |
- HD |
- F |
- 2685_PF_H_2212 |
-
-
- | 135 |
- HB_004_HD |
- HD |
- M |
- 2706_CR_H_2432 |
-
-
- | 136 |
- HB_006_HD |
- HD |
- M |
- 2737_VC_H_2194 |
-
-
- | 137 |
- HB_007_HD |
- HD |
- NA |
- 2769_VC_H_2193 |
-
-
- | 138 |
- HB_008_HD |
- HD |
- F |
- 2790_CR_H_1890 |
-
-
- | 139 |
- HB_009_HD |
- HD |
- NA |
- 2879_VC_H_2192 |
-
-
- | 140 |
- HB_010_HD |
- HD |
- M |
- 2960_VC_H_2002 |
-
-
- | 141 |
- HB_011_HD |
- HD |
- F |
- 3053_VC_H_2001 |
-
-
- | 142 |
- HB_012_HD |
- HD |
- F |
- 3128_VC_H_1999 |
-
-
- | 143 |
- HB_014_HD |
- HD |
- F |
- 3149_PF_H_2110 |
-
-
- | 144 |
- HB_015_HD |
- HD |
- F |
- 3150_VC_H_1996 |
-
-
- | 145 |
- HB_016_HD |
- HD |
- F |
- 3177_VC_H_2191 |
-
-
- | 146 |
- HB_017_HD |
- HD |
- NA |
- 3195_VC_H_2190 |
-
-
- | 147 |
- HB_018_HD |
- HD |
- M |
- 3200_VC_H_2189 |
-
-
- | 148 |
- HB_019_HD |
- HD |
- M |
- 3209_VC_H_2188 |
-
-
- | 149 |
- HB_020_HD |
- HD |
- M |
- 3224_VC_H_1994 |
-
-
- | 150 |
- HB_022_HD |
- HD |
- F |
- 3242_PF_H_2105 |
-
-
- | 151 |
- HB_024_HD |
- HD |
- NA |
- 3272_VC_H_2186 |
-
-
- | 152 |
- HB_027_HD |
- HD |
- M |
- 3356_VC_H_2439 |
-
-
- | 153 |
- HB_028_HD |
- HD |
- F |
- 3394_PF_H_2104 |
-
-
- | 154 |
- HB_031_HD |
- HD |
- M |
- 3430_VC_H_1990 |
-
-
- | 155 |
- HB_032_HD |
- HD |
- NA |
- 3444_PF_H_2208 |
-
-
- | 156 |
- HB_034_HD |
- HD |
- F |
- 3482_VC_H_1987 |
-
-
- | 157 |
- HB_036_HD |
- HD |
- M |
- 3576_VC_H_1984 |
-
-
- | 158 |
- HB_037_HD |
- HD |
- F |
- 3579_VC_H_1983 |
-
-
- | 159 |
- HB_038_HD |
- HD |
- F |
- 3584_VC_H_2183 |
-
-
- | 160 |
- HB_039_HD |
- HD |
- NA |
- 3635_VC_H_2182 |
-
-
- | 161 |
- HB_041_HD |
- HD |
- F |
- 3695_CR_H_2267 |
-
-
- | 162 |
- HB_042_HD |
- HD |
- M |
- 3697_VC_H_1982 |
-
-
- | 163 |
- HB_043_HD |
- HD |
- NA |
- 3703_VC_H_2180 |
-
-
- | 164 |
- HB_044_HD |
- HD |
- NA |
- 3723_VC_H_2179 |
-
-
- | 165 |
- HB_046_HD |
- HD |
- F |
- 3735_VC_H_1981 |
-
-
- | 166 |
- HB_050_HD |
- HD |
- M |
- 3820_PF_H_2207 |
-
-
- | 167 |
- HB_051_HD |
- HD |
- F |
- 3849_CR_H_2262 |
-
-
- | 168 |
- HB_054_HD |
- HD |
- M |
- 3884_VC_H_2175 |
-
-
- | 169 |
- HB_056_HD |
- HD |
- NA |
- 4012_VC_H_2174 |
-
-
- | 170 |
- HB_057_HD |
- HD |
- NA |
- 4013_VC_H_2173 |
-
-
- | 171 |
- HB_059_HD |
- HD |
- NA |
- 4066_VC_H_2172 |
-
-
- | 172 |
- HB_060_HD |
- HD |
- NA |
- 4094_VC_H_2171 |
-
-
- | 173 |
- HB_061_HD |
- HD |
- F |
- 4116_VC_H_2170 |
-
-
- | 174 |
- HB_062_HD |
- HD |
- NA |
- 4121_VC_H_2169 |
-
-
- | 175 |
- HB_063_HD |
- HD |
- NA |
- 4215_VC_H_2167 |
-
-
- | 176 |
- HB_065_HD |
- HD |
- M |
- 4340_PF_H_2091 |
-
-
- | 177 |
- HB_066_HD |
- HD |
- F |
- 4344_VC_H_1977 |
-
-
- | 178 |
- HB_067_HD |
- HD |
- M |
- 4346_VC_H_2165 |
-
-
- | 179 |
- HB_069_HD |
- HD |
- F |
- 4356_VC_H_2164 |
-
-
- | 180 |
- HB_070_HD |
- HD |
- NA |
- 4386_CR_H_2249 |
-
-
- | 181 |
- HB_072_HD |
- HD |
- NA |
- 4404_VC_H_2161 |
-
-
- | 182 |
- HB_073_HD |
- HD |
- F |
- 4411_VC_H_1975 |
-
-
- | 183 |
- HB_074_HD |
- HD |
- NA |
- 4430_VC_H_2465 |
-
-
- | 184 |
- HB_075_HD |
- HD |
- M |
- 4470_VC_H_1974 |
-
-
- | 185 |
- HB_076_HD |
- HD |
- F |
- 4497_CR_H_1860 |
-
-
- | 186 |
- HB_077_HD |
- HD |
- M |
- 4509_CR_H_2244 |
-
-
- | 187 |
- HB_079_HD |
- HD |
- M |
- 4631_VC_H_1971 |
-
-
- | 188 |
- HB_080_HD |
- HD |
- F |
- 4653_PF_H_2083 |
-
-
- | 189 |
- HB_081_HD |
- HD |
- NA |
- 4678_CR_H_2242 |
-
-
- | 190 |
- HB_084_HD |
- HD |
- M |
- 4718_VC_H_2125 |
-
-
- | 191 |
- HB_090_HD |
- HD |
- NA |
- 4740_CR_H_2474 |
-
-
- | 192 |
- HB_094_HD |
- HD |
- NA |
- 4754_CR_H_2476 |
-
-
- | 193 |
- HB_098_HD |
- HD |
- NA |
- 4780_VC_H_2151 |
-
-
- | 194 |
- HB_101_HD |
- HD |
- F |
- 4809_VC_H_2148 |
-
-
- | 195 |
- HB_105_HD |
- HD |
- NA |
- 4819_CR_H_2238 |
-
-
- | 196 |
- HB_106_HD |
- HD |
- F |
- 4822_VC_H_1969 |
-
-
- | 197 |
- HB_108_HD |
- HD |
- M |
- 4826_VC_H_1968 |
-
-
- | 198 |
- HB_109_HD |
- HD |
- M |
- 4828_VC_H_2124 |
-
-
- | 199 |
- HB_115_HD |
- HD |
- NA |
- 4855_CR_H_2235 |
-
-
- | 200 |
- HB_121_HD |
- HD |
- F |
- 4902_VC_H_1967 |
-
-
- | 201 |
- HB_129_HD |
- HD |
- NA |
- 4938_VC_H_1966 |
-
-
- | 202 |
- HB_141_HD |
- HD |
- F |
- 4996_PF_H_2076 |
-
-
- | 203 |
- HB_152_HD |
- HD |
- NA |
- 5034_CR_H_2233 |
-
-
- | 204 |
- HB_153_HD |
- HD |
- M |
- 5043_VC_H_1960 |
-
-
- | 205 |
- HB_159_HD |
- HD |
- M |
- 5062_VC_H_1959 |
-
-
- | 206 |
- HB_172_HD |
- HD |
- F |
- 5114_PF_H_2070 |
-
-
- | 207 |
- HB_175_HD |
- HD |
- M |
- 5127_PF_H_2068 |
-
-
- | 208 |
- HB_180_HD |
- HD |
- M |
- 5148_VC_H_1944 |
-
-
- | 209 |
- HB_185_HD |
- HD |
- F |
- 5167_CR_H_2231 |
-
-
- | 210 |
- HB_188_HD |
- HD |
- F |
- 5172_VC_H_1951 |
-
-
- | 211 |
- HB_191_HD |
- HD |
- M |
- 5180_VC_H_1949 |
-
-
- | 212 |
- HB_196_HD |
- HD |
- NA |
- 5199_PF_H_2202 |
-
-
- | 213 |
- HB_203_HD |
- HD |
- F |
- 5228_PF_H_2059 |
-
-
- | 214 |
- HB_207_HD |
- HD |
- NA |
- 5248_PF_H_2201 |
-
-
- | 215 |
- HB_228_HD |
- HD |
- F |
- 5299_CR_H_2228 |
-
-
- | 216 |
- HB_233_HD |
- HD |
- M |
- 5312_VC_H_1938 |
-
-
- | 217 |
- HB_235_HD |
- HD |
- F |
- 5316_VC_H_1937 |
-
-
- | 218 |
- HB_242_HD |
- HD |
- F |
- 5328_PF_H_2048 |
-
-
- | 219 |
- HB_266_HD |
- HD |
- M |
- 5387_VC_H_1928 |
-
-
- | 220 |
- HB_271_HD |
- HD |
- M |
- 5394_PF_H_2039 |
-
-
- | 221 |
- HB_272_HD |
- HD |
- F |
- 5396_VC_H_1925 |
-
-
- | 222 |
- HB_279_HD |
- HD |
- F |
- 5409_VC_H_1924 |
-
-
- | 223 |
- HB_294_HD |
- HD |
- M |
- 5448_VC_H_1921 |
-
-
- | 224 |
- HB_301_HD |
- HD |
- NA |
- 5464_VC_H_1919 |
-
-
- | 225 |
- HB_304_HD |
- HD |
- F |
- 5471_VC_H_1918 |
-
-
- | 226 |
- HB_321_HD |
- HD |
- NA |
- 5522_PF_H_2199 |
-
-
- | 227 |
- HB_361_HD |
- HD |
- F |
- 5622_VC_H_2121 |
-
-
- | 228 |
- HB_370_HD |
- HD |
- M |
- 5645_VC_H_1904 |
-
-
- | 229 |
- HB_371_HD |
- HD |
- F |
- 5648_PF_H_2016 |
-
-
- | 230 |
- HB_384_HD |
- HD |
- F |
- 5688_PF_H_2012 |
-
-
- | 231 |
- HB_390_HD |
- HD |
- M |
- 5704_PF_H_2009 |
-
-
- | 232 |
- HB_393_HD |
- HD |
- F |
- 5709_VC_H_1895 |
-
-
- | 233 |
- HB_402_HD |
- HD |
- F |
- 5732_PF_H_2007 |
-
-
- | 234 |
- HB_405_HD |
- HD |
- NA |
- 5742_PF_H_2006 |
-
-
- | 235 |
- HB_407_HD |
- HD |
- M |
- 5745_PF_H_2005 |
-
-
- | 236 |
- HB_408_HD |
- HD |
- M |
- 5747_VC_H_1891 |
-
-
- | 237 |
- HB_415_HD |
- HD |
- NA |
- 5777_PF_H_1551 |
-
-
- | 238 |
- HB_417_HD |
- HD |
- M |
- 5784_PF_H_1554 |
-
-
- | 239 |
- HB_424_HD |
- HD |
- M |
- 5804_VC_H_1558 |
-
-
- | 240 |
- HB_444_HD |
- HD |
- M |
- 5856_VC_H_1567 |
-
-
- | 241 |
- HB_457_HD |
- HD |
- M |
- 5896_VC_H_1570 |
-
-
- | 242 |
- HB_466_HD |
- HD |
- M |
- 5910_PF_H_1572 |
-
-
- | 243 |
- HB_478_HD |
- HD |
- M |
- 5941_CR_H_1583 |
-
-
- | 244 |
- HB_487_HD |
- HD |
- F |
- 5964_VC_H_1597 |
-
-
- | 245 |
- HB_511_HD |
- HD |
- M |
- 6019_PF_H_2198 |
-
-
- | 246 |
- HB_513_HD |
- HD |
- F |
- 6024_VC_H_1612 |
-
-
- | 247 |
- HB_515_HD |
- HD |
- F |
- 6028_CR_H_1613 |
-
-
- | 248 |
- HB_518_HD |
- HD |
- M |
- 6033_VC_H_1618 |
-
-
- | 249 |
- HB_522_HD |
- HD |
- M |
- 6037_PF_H_1626 |
-
-
- | 250 |
- HB_527_HD |
- HD |
- F |
- 6047_VC_H_1639 |
-
-
- | 251 |
- HB_528_HD |
- HD |
- M |
- 6051_PF_H_1641 |
-
-
- | 252 |
- HB_530_HD |
- HD |
- M |
- 6054_VC_H_1648 |
-
-
- | 253 |
- HB_537_HD |
- HD |
- F |
- 6071_PF_H_1653 |
-
-
- | 254 |
- HB_549_HD |
- HD |
- M |
- 6119_CR_H_1670 |
-
-
- | 255 |
- HB_593_HD |
- HD |
- NA |
- 6219_CR_H_2567 |
-
-
- | 256 |
- HB_610_HD |
- HD |
- NA |
- 6275_PF_H_1692 |
-
-
- | 257 |
- HB_616_HD |
- HD |
- F |
- 6284_CR_H_1694 |
-
-
- | 258 |
- HB_626_HD |
- HD |
- M |
- 6315_VC_H_1702 |
-
-
- | 259 |
- HB_639_HD |
- HD |
- F |
- 6344_CR_H_1703 |
-
-
- | 260 |
- HB_649_HD |
- HD |
- F |
- 6382_CR_H_1709 |
-
-
- | 261 |
- HB_661_HD |
- HD |
- M |
- 6408_VC_H_1714 |
-
-
- | 262 |
- HB_682_HD |
- HD |
- M |
- 6467_PF_H_1725 |
-
-
- | 263 |
- HB_683_HD |
- HD |
- M |
- 6472_VC_H_1729 |
-
-
- | 264 |
- HB_691_HD |
- HD |
- F |
- 6493_VC_H_1732 |
-
-
- | 265 |
- HB_692_HD |
- HD |
- M |
- 6495_CR_H_1733 |
-
-
- | 266 |
- HB_707_HD |
- HD |
- M |
- 6535_PF_H_1737 |
-
-
- | 267 |
- HB_709_HD |
- HD |
- F |
- 6539_CR_H_1739 |
-
-
- | 268 |
- HB_725_HD |
- HD |
- M |
- 6572_PF_H_1746 |
-
-
- | 269 |
- HB_732_HD |
- HD |
- F |
- 6584_VC_H_1750 |
-
-
- | 270 |
- HB_734_HD |
- HD |
- F |
- 6587_CR_H_1751 |
-
-
- | 271 |
- HB_748_HD |
- HD |
- NA |
- 6615_VC_H_2315 |
-
-
- | 272 |
- HB_750_HD |
- HD |
- NA |
- 6628_PF_H_2326 |
-
-
- | 273 |
- HB_758_HD |
- HD |
- NA |
- 6643_VC_H_2602 |
-
-
- | 274 |
- HB_760_HD |
- HD |
- M |
- 6646_PF_H_1761 |
-
-
- | 275 |
- HB_762_HD |
- HD |
- M |
- 6650_VC_H_1765 |
-
-
- | 276 |
- HB_766_HD |
- HD |
- M |
- 6658_VC_H_1768 |
-
-
- | 277 |
- HB_768_HD |
- HD |
- NA |
- 6663_VC_H_1771 |
-
-
- | 278 |
- HB_769_HD |
- HD |
- M |
- 6666_VC_H_1774 |
-
-
- | 279 |
- HB_774_HD |
- HD |
- NA |
- 6689_PF_H_2344 |
-
-
- | 280 |
- HB_778_HD |
- HD |
- NA |
- 6696_PF_H_2356 |
-
-
- | 281 |
- HB_780_HD |
- HD |
- NA |
- 6704_PF_H_2362 |
-
-
- | 282 |
- HB_790_HD |
- HD |
- NA |
- 6788_PF_H_2389 |
-
-
- | 283 |
- HB_800_HD |
- HD |
- NA |
- 6807_PF_H_2419 |
-
-
- | 284 |
- HB_802_HD |
- HD |
- NA |
- 6811_PF_H_2425 |
-
-
- | 285 |
- HB_045_AD |
- AD |
- NA |
- 3734_CR_A_0122 |
-
-
- | 286 |
- HB_048_AD |
- AD |
- NA |
- 3791_CR_A_0128 |
-
-
- | 287 |
- HB_053_AD |
- AD |
- NA |
- 3877_CR_A_0134 |
-
-
- | 288 |
- HB_055_AD |
- AD |
- NA |
- 3893_VC_A_0142 |
-
-
- | 289 |
- HB_068_AD |
- AD |
- NA |
- 4349_VC_A_0148 |
-
-
- | 290 |
- HB_082_AD |
- AD |
- NA |
- 4712_CR_A_0309 |
-
-
- | 291 |
- HB_085_AD |
- AD |
- NA |
- 4726_VC_A_0311 |
-
-
- | 292 |
- HB_087_AD |
- AD |
- NA |
- 4730_CR_A_0315 |
-
-
- | 293 |
- HB_089_AD |
- AD |
- NA |
- 4733_VC_A_0320 |
-
-
- | 294 |
- HB_093_AD |
- AD |
- NA |
- 4749_VC_A_0323 |
-
-
- | 295 |
- HB_095_AD |
- AD |
- NA |
- 4759_CR_A_0327 |
-
-
- | 296 |
- HB_097_AD |
- AD |
- NA |
- 4773_CR_A_0866 |
-
-
- | 297 |
- HB_099_AD |
- AD |
- NA |
- 4785_VC_A_0332 |
-
-
- | 298 |
- HB_100_AD |
- AD |
- NA |
- 4795_VC_A_0335 |
-
-
- | 299 |
- HB_103_AD |
- AD |
- NA |
- 4811_VC_A_0341 |
-
-
- | 300 |
- HB_104_AD |
- AD |
- NA |
- 4813_CR_A_0345 |
-
-
- | 301 |
- HB_112_AD |
- AD |
- NA |
- 4842_VC_A_0870 |
-
-
- | 302 |
- HB_113_AD |
- AD |
- NA |
- 4850_CR_A_0351 |
-
-
- | 303 |
- HB_114_AD |
- AD |
- NA |
- 4852_CR_A_0354 |
-
-
- | 304 |
- HB_117_AD |
- AD |
- NA |
- 4868_VC_A_0874 |
-
-
- | 305 |
- HB_122_AD |
- AD |
- NA |
- 4904_CR_A_1132 |
-
-
- | 306 |
- HB_123_AD |
- AD |
- NA |
- 4905_VC_A_0884 |
-
-
- | 307 |
- HB_124_AD |
- AD |
- NA |
- 4916_VC_A_0886 |
-
-
- | 308 |
- HB_125_AD |
- AD |
- NA |
- 4917_CR_A_0360 |
-
-
- | 309 |
- HB_126_AD |
- AD |
- NA |
- 4921_VC_A_0362 |
-
-
- | 310 |
- HB_128_AD |
- AD |
- NA |
- 4936_CR_A_0369 |
-
-
- | 311 |
- HB_130_AD |
- AD |
- NA |
- 4939_VC_A_0888 |
-
-
- | 312 |
- HB_131_AD |
- AD |
- NA |
- 4944_CR_A_0889 |
-
-
- | 313 |
- HB_132_AD |
- AD |
- NA |
- 4946_CR_A_0372 |
-
-
- | 314 |
- HB_134_AD |
- AD |
- NA |
- 4951_CR_A_0891 |
-
-
- | 315 |
- HB_135_AD |
- AD |
- NA |
- 4953_VC_A_0893 |
-
-
- | 316 |
- HB_136_AD |
- AD |
- NA |
- 4965_VC_A_0160 |
-
-
- | 317 |
- HB_137_AD |
- AD |
- NA |
- 4966_VC_A_0374 |
-
-
- | 318 |
- HB_138_AD |
- AD |
- NA |
- 4969_VC_A_0895 |
-
-
- | 319 |
- HB_140_AD |
- AD |
- NA |
- 4993_CR_A_0896 |
-
-
- | 320 |
- HB_146_AD |
- AD |
- NA |
- 5018_CR_A_0384 |
-
-
- | 321 |
- HB_148_AD |
- AD |
- NA |
- 5022_VC_A_0386 |
-
-
- | 322 |
- HB_150_AD |
- AD |
- NA |
- 5031_VC_A_0392 |
-
-
- | 323 |
- HB_151_AD |
- AD |
- NA |
- 5033_CR_A_0396 |
-
-
- | 324 |
- HB_154_AD |
- AD |
- NA |
- 5048_VC_A_1321 |
-
-
- | 325 |
- HB_155_AD |
- AD |
- NA |
- 5056_VC_A_0398 |
-
-
- | 326 |
- HB_156_AD |
- AD |
- NA |
- 5057_VC_A_0163 |
-
-
- | 327 |
- HB_157_AD |
- AD |
- NA |
- 5059_VC_A_0401 |
-
-
- | 328 |
- HB_158_AD |
- AD |
- NA |
- 5061_PF_A_2612 |
-
-
- | 329 |
- HB_160_AD |
- AD |
- NA |
- 5064_PF_A_2615 |
-
-
- | 330 |
- HB_165_AD |
- AD |
- NA |
- 5092_CR_A_0899 |
-
-
- | 331 |
- HB_168_AD |
- AD |
- NA |
- 5097_VC_A_0407 |
-
-
- | 332 |
- HB_170_AD |
- AD |
- NA |
- 5101_VC_A_0410 |
-
-
- | 333 |
- HB_174_AD |
- AD |
- NA |
- 5124_PF_A_1343 |
-
-
- | 334 |
- HB_179_AD |
- AD |
- NA |
- 5145_VC_A_1351 |
-
-
- | 335 |
- HB_181_AD |
- AD |
- NA |
- 5152_CR_A_0414 |
-
-
- | 336 |
- HB_184_AD |
- AD |
- NA |
- 5166_VC_A_1354 |
-
-
- | 337 |
- HB_194_AD |
- AD |
- NA |
- 5193_VC_A_1360 |
-
-
- | 338 |
- HB_197_AD |
- AD |
- NA |
- 5202_CR_A_1368 |
-
-
- | 339 |
- HB_199_AD |
- AD |
- NA |
- 5205_VC_A_0166 |
-
-
- | 340 |
- HB_200_AD |
- AD |
- NA |
- 5210_VC_A_0905 |
-
-
- | 341 |
- HB_205_AD |
- AD |
- NA |
- 5235_VC_A_0419 |
-
-
- | 342 |
- HB_208_AD |
- AD |
- NA |
- 5249_VC_A_0422 |
-
-
- | 343 |
- HB_209_AD |
- AD |
- NA |
- 5252_VC_A_0907 |
-
-
- | 344 |
- HB_211_AD |
- AD |
- NA |
- 5257_VC_A_0169 |
-
-
- | 345 |
- HB_216_AD |
- AD |
- NA |
- 5272_VC_A_0425 |
-
-
- | 346 |
- HB_219_AD |
- AD |
- NA |
- 5279_CR_A_0147 |
-
-
- | 347 |
- HB_221_AD |
- AD |
- NA |
- 5283_VC_A_0145 |
-
-
- | 348 |
- HB_222_AD |
- AD |
- NA |
- 5285_VC_A_0141 |
-
-
- | 349 |
- HB_224_AD |
- AD |
- NA |
- 5288_VC_A_0428 |
-
-
- | 350 |
- HB_230_AD |
- AD |
- NA |
- 5301_VC_A_0174 |
-
-
- | 351 |
- HB_231_AD |
- AD |
- NA |
- 5305_VC_A_1384 |
-
-
- | 352 |
- HB_232_AD |
- AD |
- NA |
- 5310_CR_A_0176 |
-
-
- | 353 |
- HB_234_AD |
- AD |
- NA |
- 5313_PF_A_2618 |
-
-
- | 354 |
- HB_236_AD |
- AD |
- NA |
- 5317_PF_A_2624 |
-
-
- | 355 |
- HB_238_AD |
- AD |
- NA |
- 5322_CR_A_2632 |
-
-
- | 356 |
- HB_240_AD |
- AD |
- NA |
- 5325_VC_A_0137 |
-
-
- | 357 |
- HB_244_AD |
- AD |
- NA |
- 5337_VC_A_1387 |
-
-
- | 358 |
- HB_245_AD |
- AD |
- NA |
- 5339_VC_A_0181 |
-
-
- | 359 |
- HB_250_AD |
- AD |
- NA |
- 5346_VC_A_1393 |
-
-
- | 360 |
- HB_251_AD |
- AD |
- NA |
- 5350_VC_A_0184 |
-
-
- | 361 |
- HB_252_AD |
- AD |
- NA |
- 5355_VC_A_0133 |
-
-
- | 362 |
- HB_253_AD |
- AD |
- NA |
- 5359_CR_A_1395 |
-
-
- | 363 |
- HB_258_AD |
- AD |
- NA |
- 5370_PF_A_1400 |
-
-
- | 364 |
- HB_259_AD |
- AD |
- NA |
- 5371_PF_A_2636 |
-
-
- | 365 |
- HB_260_AD |
- AD |
- NA |
- 5375_VC_A_0188 |
-
-
- | 366 |
- HB_263_AD |
- AD |
- NA |
- 5381_VC_A_0022 |
-
-
- | 367 |
- HB_265_AD |
- AD |
- NA |
- 5385_VC_A_1402 |
-
-
- | 368 |
- HB_267_AD |
- AD |
- NA |
- 5389_VC_A_0928 |
-
-
- | 369 |
- HB_268_AD |
- AD |
- NA |
- 5390_CR_A_0151 |
-
-
- | 370 |
- HB_273_AD |
- AD |
- NA |
- 5400_PF_A_2645 |
-
-
- | 371 |
- HB_274_AD |
- AD |
- NA |
- 5401_VC_A_0931 |
-
-
- | 372 |
- HB_275_AD |
- AD |
- NA |
- 5404_PF_A_2648 |
-
-
- | 373 |
- HB_276_AD |
- AD |
- NA |
- 5406_VC_A_0933 |
-
-
- | 374 |
- HB_277_AD |
- AD |
- NA |
- 5407_PF_A_2651 |
-
-
- | 375 |
- HB_280_AD |
- AD |
- NA |
- 5412_VC_A_0935 |
-
-
- | 376 |
- HB_281_AD |
- AD |
- NA |
- 5413_PF_A_2657 |
-
-
- | 377 |
- HB_283_AD |
- AD |
- NA |
- 5419_VC_A_0937 |
-
-
- | 378 |
- HB_284_AD |
- AD |
- NA |
- 5420_VC_A_0939 |
-
-
- | 379 |
- HB_285_AD |
- AD |
- NA |
- 5421_CR_A_0432 |
-
-
- | 380 |
- HB_286_AD |
- AD |
- NA |
- 5423_PF_A_2660 |
-
-
- | 381 |
- HB_288_AD |
- AD |
- NA |
- 5425_PF_A_2666 |
-
-
- | 382 |
- HB_289_AD |
- AD |
- NA |
- 5426_VC_A_1405 |
-
-
- | 383 |
- HB_290_AD |
- AD |
- NA |
- 5433_VC_A_0434 |
-
-
- | 384 |
- HB_296_AD |
- AD |
- NA |
- 5456_PF_A_2675 |
-
-
- | 385 |
- HB_299_AD |
- AD |
- NA |
- 5461_VC_A_0192 |
-
-
- | 386 |
- HB_302_AD |
- AD |
- NA |
- 5465_PF_A_2678 |
-
-
- | 387 |
- HB_303_AD |
- AD |
- NA |
- 5469_VC_A_1417 |
-
-
- | 388 |
- HB_305_AD |
- AD |
- NA |
- 5479_PF_A_1421 |
-
-
- | 389 |
- HB_306_AD |
- AD |
- NA |
- 5480_VC_A_0437 |
-
-
- | 390 |
- HB_307_AD |
- AD |
- NA |
- 5482_VC_A_0028 |
-
-
- | 391 |
- HB_308_AD |
- AD |
- NA |
- 5483_VC_A_0941 |
-
-
- | 392 |
- HB_309_AD |
- AD |
- NA |
- 5487_CR_A_0441 |
-
-
- | 393 |
- HB_310_AD |
- AD |
- NA |
- 5488_CR_A_0194 |
-
-
- | 394 |
- HB_312_AD |
- AD |
- NA |
- 5500_VC_A_0198 |
-
-
- | 395 |
- HB_313_AD |
- AD |
- NA |
- 5502_PF_A_2684 |
-
-
- | 396 |
- HB_315_AD |
- AD |
- NA |
- 5513_PF_A_2687 |
-
-
- | 397 |
- HB_316_AD |
- AD |
- NA |
- 5516_PF_A_2690 |
-
-
- | 398 |
- HB_317_AD |
- AD |
- NA |
- 5517_PF_A_2693 |
-
-
- | 399 |
- HB_318_AD |
- AD |
- NA |
- 5518_CR_A_0030 |
-
-
- | 400 |
- HB_319_AD |
- AD |
- NA |
- 5519_CR_A_2695 |
-
-
- | 401 |
- HB_320_AD |
- AD |
- NA |
- 5520_PF_A_2699 |
-
-
- | 402 |
- HB_322_AD |
- AD |
- NA |
- 5527_VC_A_0945 |
-
-
- | 403 |
- HB_325_AD |
- AD |
- NA |
- 5532_PF_A_2702 |
-
-
- | 404 |
- HB_328_AD |
- AD |
- NA |
- 5541_PF_A_2705 |
-
-
- | 405 |
- HB_330_AD |
- AD |
- NA |
- 5544_VC_A_0201 |
-
-
- | 406 |
- HB_334_AD |
- AD |
- NA |
- 5554_VC_A_0452 |
-
-
- | 407 |
- HB_335_AD |
- AD |
- NA |
- 5557_VC_A_0950 |
-
-
- | 408 |
- HB_337_AD |
- AD |
- NA |
- 5560_VC_A_0204 |
-
-
- | 409 |
- HB_342_AD |
- AD |
- NA |
- 5571_PF_A_1430 |
-
-
- | 410 |
- HB_345_AD |
- AD |
- NA |
- 5583_PF_A_2708 |
-
-
- | 411 |
- HB_347_AD |
- AD |
- NA |
- 5589_PF_A_2714 |
-
-
- | 412 |
- HB_349_AD |
- AD |
- NA |
- 5592_PF_A_2717 |
-
-
- | 413 |
- HB_352_AD |
- AD |
- NA |
- 5604_VC_A_0037 |
-
-
- | 414 |
- HB_353_AD |
- AD |
- NA |
- 5607_PF_A_2723 |
-
-
- | 415 |
- HB_356_AD |
- AD |
- NA |
- 5615_VC_A_0041 |
-
-
- | 416 |
- HB_357_AD |
- AD |
- NA |
- 5616_CR_A_0127 |
-
-
- | 417 |
- HB_358_AD |
- AD |
- NA |
- 5617_CR_A_0456 |
-
-
- | 418 |
- HB_359_AD |
- AD |
- NA |
- 5618_CR_A_0044 |
-
-
- | 419 |
- HB_362_AD |
- AD |
- NA |
- 5625_CR_A_2495 |
-
-
- | 420 |
- HB_363_AD |
- AD |
- NA |
- 5626_CR_A_2498 |
-
-
- | 421 |
- HB_364_AD |
- AD |
- NA |
- 5629_CR_A_0390 |
-
-
- | 422 |
- HB_369_AD |
- AD |
- NA |
- 5643_VC_A_1143 |
-
-
- | 423 |
- HB_373_AD |
- AD |
- NA |
- 5654_VC_A_0047 |
-
-
- | 424 |
- HB_375_AD |
- AD |
- NA |
- 5660_CR_A_0462 |
-
-
- | 425 |
- HB_376_AD |
- AD |
- NA |
- 5661_VC_A_0464 |
-
-
- | 426 |
- HB_377_AD |
- AD |
- NA |
- 5667_VC_A_2509 |
-
-
- | 427 |
- HB_378_AD |
- AD |
- NA |
- 5668_VC_A_1438 |
-
-
- | 428 |
- HB_383_AD |
- AD |
- NA |
- 5686_CR_A_2728 |
-
-
- | 429 |
- HB_386_AD |
- AD |
- NA |
- 5695_VC_A_0953 |
-
-
- | 430 |
- HB_389_AD |
- AD |
- NA |
- 5700_VC_A_2514 |
-
-
- | 431 |
- HB_391_AD |
- AD |
- NA |
- 5705_CR_A_0474 |
-
-
- | 432 |
- HB_392_AD |
- AD |
- NA |
- 5706_VC_A_0476 |
-
-
- | 433 |
- HB_394_AD |
- AD |
- NA |
- 5713_VC_A_0479 |
-
-
- | 434 |
- HB_397_AD |
- AD |
- NA |
- 5721_CR_A_0210 |
-
-
- | 435 |
- HB_404_AD |
- AD |
- NA |
- 5735_CR_A_0489 |
-
-
- | 436 |
- HB_406_AD |
- AD |
- NA |
- 5744_CR_A_0960 |
-
-
- | 437 |
- HB_409_AD |
- AD |
- NA |
- 5749_CR_A_0159 |
-
-
- | 438 |
- HB_410_AD |
- AD |
- NA |
- 5751_CR_A_2518 |
-
-
- | 439 |
- HB_411_AD |
- AD |
- NA |
- 5755_CR_A_2731 |
-
-
- | 440 |
- HB_413_AD |
- AD |
- NA |
- 5766_VC_A_0214 |
-
-
- | 441 |
- HB_419_AD |
- AD |
- NA |
- 5790_VC_A_0217 |
-
-
- | 442 |
- HB_420_AD |
- AD |
- NA |
- 5796_CR_A_0964 |
-
-
- | 443 |
- HB_428_AD |
- AD |
- NA |
- 5811_CR_A_2524 |
-
-
- | 444 |
- HB_429_AD |
- AD |
- NA |
- 5819_CR_A_2527 |
-
-
- | 445 |
- HB_430_AD |
- AD |
- NA |
- 5822_CR_A_2530 |
-
-
- | 446 |
- HB_434_AD |
- AD |
- NA |
- 5828_CR_A_2533 |
-
-
- | 447 |
- HB_435_AD |
- AD |
- NA |
- 5831_CR_A_0222 |
-
-
- | 448 |
- HB_437_AD |
- AD |
- NA |
- 5839_CR_A_2539 |
-
-
- | 449 |
- HB_438_AD |
- AD |
- NA |
- 5843_CR_A_0227 |
-
-
- | 450 |
- HB_439_AD |
- AD |
- NA |
- 5845_CR_A_0230 |
-
-
- | 451 |
- HB_441_AD |
- AD |
- NA |
- 5849_CR_A_0233 |
-
-
- | 452 |
- HB_442_AD |
- AD |
- NA |
- 5850_CR_A_0495 |
-
-
- | 453 |
- HB_445_AD |
- AD |
- NA |
- 5858_CR_A_0969 |
-
-
- | 454 |
- HB_448_AD |
- AD |
- NA |
- 5864_CR_A_0974 |
-
-
- | 455 |
- HB_451_AD |
- AD |
- NA |
- 5871_CR_A_2542 |
-
-
- | 456 |
- HB_454_AD |
- AD |
- NA |
- 5879_CR_A_2545 |
-
-
- | 457 |
- HB_455_AD |
- AD |
- NA |
- 5887_CR_A_0976_Bis |
-
-
- | 458 |
- HB_459_AD |
- AD |
- NA |
- 5898_CR_A_2548 |
-
-
- | 459 |
- HB_460_AD |
- AD |
- NA |
- 5900_VC_A_0237 |
-
-
- | 460 |
- HB_461_AD |
- AD |
- NA |
- 5901_CR_A_0239 |
-
-
- | 461 |
- HB_469_AD |
- AD |
- NA |
- 5914_CR_A_2554 |
-
-
- | 462 |
- HB_471_AD |
- AD |
- NA |
- 5922_VC_A_0246 |
-
-
- | 463 |
- HB_473_AD |
- AD |
- NA |
- 5927_CR_A_2560 |
-
-
- | 464 |
- HB_474_AD |
- AD |
- NA |
- 5933_VC_A_1071 |
-
-
- | 465 |
- HB_477_AD |
- AD |
- NA |
- 5939_CR_A_1151 |
-
-
- | 466 |
- HB_479_AD |
- AD |
- NA |
- 5945_VC_A_0983 |
-
-
- | 467 |
- HB_484_AD |
- AD |
- NA |
- 5956_CR_A_0123 |
-
-
- | 468 |
- HB_489_AD |
- AD |
- NA |
- 5968_VC_A_1075 |
-
-
- | 469 |
- HB_491_AD |
- AD |
- NA |
- 5971_CR_A_0119 |
-
-
- | 470 |
- HB_492_AD |
- AD |
- NA |
- 5972_VC_A_0251 |
-
-
- | 471 |
- HB_494_AD |
- AD |
- NA |
- 5979_CR_A_0115 |
-
-
- | 472 |
- HB_498_AD |
- AD |
- NA |
- 5988_VC_A_0503 |
-
-
- | 473 |
- HB_502_AD |
- AD |
- NA |
- 5994_PF_A_1605 |
-
-
- | 474 |
- HB_503_AD |
- AD |
- NA |
- 5995_CR_A_2563 |
-
-
- | 475 |
- HB_510_AD |
- AD |
- NA |
- 6017_CR_A_0048 |
-
-
- | 476 |
- HB_514_AD |
- AD |
- NA |
- 6025_VC_A_0506 |
-
-
- | 477 |
- HB_517_AD |
- AD |
- NA |
- 6031_VC_A_0258 |
-
-
- | 478 |
- HB_520_AD |
- AD |
- NA |
- 6035_VC_A_1621 |
-
-
- | 479 |
- HB_523_AD |
- AD |
- NA |
- 6038_VC_A_0261 |
-
-
- | 480 |
- HB_524_AD |
- AD |
- NA |
- 6042_VC_A_1156 |
-
-
- | 481 |
- HB_525_AD |
- AD |
- NA |
- 6044_VC_A_0264 |
-
-
- | 482 |
- HB_531_AD |
- AD |
- NA |
- 6056_CR_A_0999 |
-
-
- | 483 |
- HB_533_AD |
- AD |
- NA |
- 6061_PF_A_1650 |
-
-
- | 484 |
- HB_534_AD |
- AD |
- NA |
- 6066_VC_A_0270 |
-
-
- | 485 |
- HB_535_AD |
- AD |
- NA |
- 6067_PF_A_1452 |
-
-
- | 486 |
- HB_536_AD |
- AD |
- NA |
- 6068_VC_A_0273 |
-
-
- | 487 |
- HB_545_AD |
- AD |
- NA |
- 6102_CR_A_1661 |
-
-
- | 488 |
- HB_546_AD |
- AD |
- NA |
- 6107_CR_A_0055 |
-
-
- | 489 |
- HB_550_AD |
- AD |
- NA |
- 6120_VC_A_0058 |
-
-
- | 490 |
- HB_552_AD |
- AD |
- NA |
- 6126_VC_A_1675 |
-
-
- | 491 |
- HB_553_AD |
- AD |
- NA |
- 6129_PF_A_0274 |
-
-
- | 492 |
- HB_554_AD |
- AD |
- NA |
- 6130_VC_A_1678 |
-
-
- | 493 |
- HB_555_AD |
- AD |
- NA |
- 6131_CR_A_0510 |
-
-
- | 494 |
- HB_556_AD |
- AD |
- NA |
- 6132_CR_A_0513 |
-
-
- | 495 |
- HB_558_AD |
- AD |
- NA |
- 6137_VC_A_1681 |
-
-
- | 496 |
- HB_564_AD |
- AD |
- NA |
- 6153_VC_A_1465 |
-
-
- | 497 |
- HB_565_AD |
- AD |
- NA |
- 6154_VC_A_1468 |
-
-
- | 498 |
- HB_566_AD |
- AD |
- NA |
- 6157_VC_A_0062 |
-
-
- | 499 |
- HB_568_AD |
- AD |
- NA |
- 6164_CR_A_1005 |
-
-
- | 500 |
- HB_571_AD |
- AD |
- NA |
- 6171_CR_A_0065 |
-
-
- | 501 |
- HB_573_AD |
- AD |
- NA |
- 6174_VC_A_0068 |
-
-
- | 502 |
- HB_576_AD |
- AD |
- NA |
- 6180_CR_A_0281 |
-
-
- | 503 |
- HB_583_AD |
- AD |
- NA |
- 6194_VC_A_0071 |
-
-
- | 504 |
- HB_585_AD |
- AD |
- NA |
- 6198_VC_A_0073 |
-
-
- | 505 |
- HB_590_AD |
- AD |
- NA |
- 6215_VC_A_0518 |
-
-
- | 506 |
- HB_591_AD |
- AD |
- NA |
- 6216_VC_A_1476 |
-
-
- | 507 |
- HB_592_AD |
- AD |
- NA |
- 6218_CR_A_0522 |
-
-
- | 508 |
- HB_594_AD |
- AD |
- NA |
- 6223_VC_A_0288 |
-
-
- | 509 |
- HB_596_AD |
- AD |
- NA |
- 6226_CR_A_0076 |
-
-
- | 510 |
- HB_597_AD |
- AD |
- NA |
- 6227_VC_A_0080 |
-
-
- | 511 |
- HB_598_AD |
- AD |
- NA |
- 6231_VC_A_1479 |
-
-
- | 512 |
- HB_605_AD |
- AD |
- NA |
- 6261_VC_A_0084 |
-
-
- | 513 |
- HB_608_AD |
- AD |
- NA |
- 6268_CR_A_0525 |
-
-
- | 514 |
- HB_611_AD |
- AD |
- NA |
- 6279_VC_A_0089 |
-
-
- | 515 |
- HB_612_AD |
- AD |
- NA |
- 6280_VC_A_0091 |
-
-
- | 516 |
- HB_613_AD |
- AD |
- NA |
- 6281_CR_A_0528 |
-
-
- | 517 |
- HB_621_AD |
- AD |
- NA |
- 6308_VC_A_1503 |
-
-
- | 518 |
- HB_623_AD |
- AD |
- NA |
- 6311_CR_A_0531 |
-
-
- | 519 |
- HB_624_AD |
- AD |
- NA |
- 6312_CR_A_0534 |
-
-
- | 520 |
- HB_630_AD |
- AD |
- NA |
- 6324_PF_A_1514 |
-
-
- | 521 |
- HB_633_AD |
- AD |
- NA |
- 6332_VC_A_1518 |
-
-
- | 522 |
- HB_634_AD |
- AD |
- NA |
- 6335_VC_A_0536 |
-
-
- | 523 |
- HB_635_AD |
- AD |
- NA |
- 6336_CR_A_0290 |
-
-
- | 524 |
- HB_636_AD |
- AD |
- NA |
- 6338_VC_A_0539 |
-
-
- | 525 |
- HB_642_AD |
- AD |
- NA |
- 6358_VC_A_0545 |
-
-
- | 526 |
- HB_652_AD |
- AD |
- NA |
- 6387_VC_A_0093 |
-
-
- | 527 |
- HB_657_AD |
- AD |
- NA |
- 6394_VC_A_0551 |
-
-
- | 528 |
- HB_664_AD |
- AD |
- NA |
- 6416_VC_A_1095 |
-
-
- | 529 |
- HB_666_AD |
- AD |
- NA |
- 6422_CR_A_0555 |
-
-
- | 530 |
- HB_669_AD |
- AD |
- NA |
- 6431_VC_A_0294 |
-
-
- | 531 |
- HB_674_AD |
- AD |
- NA |
- 6449_VC_A_1183 |
-
-
- | 532 |
- HB_680_AD |
- AD |
- NA |
- 6458_CR_A_2570 |
-
-
- | 533 |
- HB_685_AD |
- AD |
- NA |
- 6481_VC_A_0560 |
-
-
- | 534 |
- HB_690_AD |
- AD |
- NA |
- 6489_CR_A_0100 |
-
-
- | 535 |
- HB_696_AD |
- AD |
- NA |
- 6511_VC_A_1119 |
-
-
- | 536 |
- HB_698_AD |
- AD |
- NA |
- 6515_CR_A_0564 |
-
-
- | 537 |
- HB_699_AD |
- AD |
- NA |
- 6518_VC_A_0103 |
-
-
- | 538 |
- HB_703_AD |
- AD |
- NA |
- 6523_VC_A_0107 |
-
-
- | 539 |
- HB_704_AD |
- AD |
- NA |
- 6530_VC_A_0112 |
-
-
- | 540 |
- HB_706_AD |
- AD |
- NA |
- 6534_VC_A_0306 |
-
-
- | 541 |
- HB_712_AD |
- AD |
- NA |
- 6546_PF_A_1194 |
-
-
- | 542 |
- HB_713_AD |
- AD |
- NA |
- 6548_PF_A_1541 |
-
-
- | 543 |
- HB_715_AD |
- AD |
- NA |
- 6550_VC_A_1201 |
-
-
- | 544 |
- HB_718_AD |
- AD |
- NA |
- 6554_PF_A_1203 |
-
-
- | 545 |
- HB_720_AD |
- AD |
- NA |
- 6559_PF_A_2287 |
-
-
- | 546 |
- HB_722_AD |
- AD |
- NA |
- 6561_CR_A_2582 |
-
-
- | 547 |
- HB_723_AD |
- AD |
- NA |
- 6562_PF_A_2290 |
-
-
- | 548 |
- HB_724_AD |
- AD |
- NA |
- 6564_CR_A_2585 |
-
-
- | 549 |
- HB_727_AD |
- AD |
- NA |
- 6575_CR_A_2298 |
-
-
- | 550 |
- HB_728_AD |
- AD |
- NA |
- 6577_PF_A_2299 |
-
-
- | 551 |
- HB_729_AD |
- AD |
- NA |
- 6578_PF_A_2302 |
-
-
- | 552 |
- HB_731_AD |
- AD |
- NA |
- 6582_VC_A_1207 |
-
-
- | 553 |
- HB_733_AD |
- AD |
- NA |
- 6585_VC_A_1210 |
-
-
- | 554 |
- HB_736_AD |
- AD |
- NA |
- 6590_PF_A_1215 |
-
-
- | 555 |
- HB_743_AD |
- AD |
- NA |
- 6603_PF_A_1448 |
-
-
- | 556 |
- HB_745_AD |
- AD |
- NA |
- 6610_PF_A_1227 |
-
-
- | 557 |
- HB_746_AD |
- AD |
- NA |
- 6612_PF_A_2308 |
-
-
- | 558 |
- HB_749_AD |
- AD |
- NA |
- 6617_VC_A_2587 |
-
-
- | 559 |
- HB_751_AD |
- AD |
- NA |
- 6629_VC_A_2330 |
-
-
- | 560 |
- HB_752_AD |
- AD |
- NA |
- 6630_VC_A_2590 |
-
-
- | 561 |
- HB_753_AD |
- AD |
- NA |
- 6632_PF_A_2332 |
-
-
- | 562 |
- HB_754_AD |
- AD |
- NA |
- 6637_VC_A_2596 |
-
-
- | 563 |
- HB_755_AD |
- AD |
- NA |
- 6638_VC_A_2599 |
-
-
- | 564 |
- HB_756_AD |
- AD |
- NA |
- 6639_VC_A_2336 |
-
-
- | 565 |
- HB_757_AD |
- AD |
- NA |
- 6641_PF_A_2338 |
-
-
- | 566 |
- HB_763_AD |
- AD |
- NA |
- 6654_VC_A_1237 |
-
-
- | 567 |
- HB_773_AD |
- AD |
- NA |
- 6681_VC_A_1252 |
-
-
- | 568 |
- HB_775_AD |
- AD |
- NA |
- 6693_VC_A_2348 |
-
-
- | 569 |
- HB_776_AD |
- AD |
- NA |
- 6694_VC_A_2351 |
-
-
- | 570 |
- HB_777_AD |
- AD |
- NA |
- 6695_PF_A_2353 |
-
-
- | 571 |
- HB_779_AD |
- AD |
- NA |
- 6699_PF_A_2359 |
-
-
- | 572 |
- HB_781_AD |
- AD |
- NA |
- 6708_VC_A_2366 |
-
-
- | 573 |
- HB_782_AD |
- AD |
- NA |
- 6776_PF_A_2607 |
-
-
- | 574 |
- HB_783_AD |
- AD |
- NA |
- 6778_PF_A_2368 |
-
-
- | 575 |
- HB_784_AD |
- AD |
- NA |
- 6779_PF_A_2371 |
-
-
- | 576 |
- HB_785_AD |
- AD |
- NA |
- 6780_PF_A_2374 |
-
-
- | 577 |
- HB_786_AD |
- AD |
- NA |
- 6782_PF_A_2377 |
-
-
- | 578 |
- HB_787_AD |
- AD |
- NA |
- 6784_PF_A_2380 |
-
-
- | 579 |
- HB_788_AD |
- AD |
- NA |
- 6785_CR_A_2385 |
-
-
- | 580 |
- HB_789_AD |
- AD |
- NA |
- 6787_CR_A_2388 |
-
-
- | 581 |
- HB_791_AD |
- AD |
- NA |
- 6790_PF_A_2392 |
-
-
- | 582 |
- HB_792_AD |
- AD |
- NA |
- 6791_PF_A_2395 |
-
-
- | 583 |
- HB_793_AD |
- AD |
- NA |
- 6793_PF_A_2398 |
-
-
- | 584 |
- HB_794_AD |
- AD |
- NA |
- 6794_PF_A_2401 |
-
-
- | 585 |
- HB_795_AD |
- AD |
- NA |
- 6797_PF_A_2404 |
-
-
- | 586 |
- HB_796_AD |
- AD |
- NA |
- 6798_PF_A_2407 |
-
-
- | 587 |
- HB_797_AD |
- AD |
- NA |
- 6799_VC_A_2411 |
-
-
- | 588 |
- HB_798_AD |
- AD |
- NA |
- 6801_VC_A_2414 |
-
-
- | 589 |
- HB_799_AD |
- AD |
- NA |
- 6803_VC_A_2417 |
-
-
- | 590 |
- HB_801_AD |
- AD |
- NA |
- 6809_PF_A_2422 |
-
-
- | 591 |
- HB_803_AD |
- AD |
- NA |
- 6818_CR_A_2430 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/HBTRC_MLPFC_HD_0611/experiment-design.rtf b/general/datasets/HBTRC_MLPFC_HD_0611/experiment-design.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_HD_0611/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_HD_0611/notes.rtf b/general/datasets/HBTRC_MLPFC_HD_0611/notes.rtf
deleted file mode 100644
index ff90e34..0000000
--- a/general/datasets/HBTRC_MLPFC_HD_0611/notes.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Species: Human
-Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
-Disease: Neurological Disease
-Investigator: Francine Benes/ Eric Schadt
-Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
-Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC_MLPFC_HD_0611/platform.rtf b/general/datasets/HBTRC_MLPFC_HD_0611/platform.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_HD_0611/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_HD_0611/processing.rtf b/general/datasets/HBTRC_MLPFC_HD_0611/processing.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_HD_0611/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_HD_0611/summary.rtf b/general/datasets/HBTRC_MLPFC_HD_0611/summary.rtf
deleted file mode 100644
index 5cde3bf..0000000
--- a/general/datasets/HBTRC_MLPFC_HD_0611/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC_MLPFC_HD_0611/tissue.rtf b/general/datasets/HBTRC_MLPFC_HD_0611/tissue.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_HD_0611/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_N_0611/acknowledgment.rtf b/general/datasets/HBTRC_MLPFC_N_0611/acknowledgment.rtf
deleted file mode 100644
index 208cb6e..0000000
--- a/general/datasets/HBTRC_MLPFC_N_0611/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC_MLPFC_N_0611/cases.rtf b/general/datasets/HBTRC_MLPFC_N_0611/cases.rtf
deleted file mode 100644
index 86ed08e..0000000
--- a/general/datasets/HBTRC_MLPFC_N_0611/cases.rtf
+++ /dev/null
@@ -1,4166 +0,0 @@
-This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- | Series |
- Cerebellum in GN |
- Condition |
- Gender |
- BioSample Name |
-
-
- | 1 |
- HB_029_N |
- N |
- NA |
- 3405_VC_N_0859 |
-
-
- | 2 |
- HB_058_N |
- N |
- NA |
- 4021_VC_N_0854 |
-
-
- | 3 |
- HB_064_N |
- N |
- NA |
- 4338_VC_N_0861 |
-
-
- | 4 |
- HB_086_N |
- N |
- NA |
- 4729_PF_N_0756 |
-
-
- | 5 |
- HB_091_N |
- N |
- NA |
- 4741_VC_N_0864 |
-
-
- | 6 |
- HB_092_N |
- N |
- NA |
- 4744_VC_N_0865 |
-
-
- | 7 |
- HB_102_N |
- N |
- NA |
- 4810_VC_N_0869 |
-
-
- | 8 |
- HB_119_N |
- N |
- NA |
- 4872_VC_N_0878 |
-
-
- | 9 |
- HB_147_N |
- N |
- NA |
- 5021_VC_N_0852 |
-
-
- | 10 |
- HB_161_N |
- N |
- NA |
- 5077_VC_N_0851 |
-
-
- | 11 |
- HB_162_N |
- N |
- NA |
- 5081_VC_N_1021 |
-
-
- | 12 |
- HB_166_N |
- N |
- NA |
- 5095_VC_N_1024 |
-
-
- | 13 |
- HB_183_N |
- N |
- NA |
- 5162_VC_N_0850 |
-
-
- | 14 |
- HB_206_N |
- N |
- NA |
- 5245_VC_N_0849 |
-
-
- | 15 |
- HB_215_N |
- N |
- NA |
- 5270_VC_N_0848 |
-
-
- | 16 |
- HB_218_N |
- N |
- NA |
- 5276_CR_N_0912 |
-
-
- | 17 |
- HB_223_N |
- N |
- NA |
- 5287_VC_N_0916 |
-
-
- | 18 |
- HB_226_N |
- N |
- NA |
- 5294_VC_N_0919 |
-
-
- | 19 |
- HB_241_N |
- N |
- NA |
- 5326_CR_N_0652 |
-
-
- | 20 |
- HB_243_N |
- N |
- NA |
- 5333_VC_N_1262 |
-
-
- | 21 |
- HB_247_N |
- N |
- NA |
- 5341_VC_N_0923 |
-
-
- | 22 |
- HB_257_N |
- N |
- NA |
- 5368_PF_N_1032 |
-
-
- | 23 |
- HB_264_N |
- N |
- NA |
- 5384_VC_N_0924 |
-
-
- | 24 |
- HB_295_N |
- N |
- NA |
- 5452_VC_N_1268 |
-
-
- | 25 |
- HB_300_N |
- N |
- NA |
- 5463_VC_N_0845 |
-
-
- | 26 |
- HB_311_N |
- N |
- NA |
- 5489_CR_N_0942 |
-
-
- | 27 |
- HB_324_N |
- N |
- NA |
- 5531_VC_N_0844 |
-
-
- | 28 |
- HB_332_N |
- N |
- NA |
- 5547_VC_N_0843 |
-
-
- | 29 |
- HB_340_N |
- N |
- NA |
- 5568_VC_N_0842 |
-
-
- | 30 |
- HB_360_N |
- N |
- NA |
- 5619_CR_N_0645 |
-
-
- | 31 |
- HB_365_N |
- N |
- NA |
- 5632_VC_N_0838 |
-
-
- | 32 |
- HB_367_N |
- N |
- NA |
- 5637_VC_N_0837 |
-
-
- | 33 |
- HB_382_N |
- N |
- NA |
- 5684_PF_N_1270 |
-
-
- | 34 |
- HB_396_N |
- N |
- NA |
- 5718_VC_N_0956 |
-
-
- | 35 |
- HB_398_N |
- N |
- NA |
- 5722_VC_N_1044 |
-
-
- | 36 |
- HB_400_N |
- N |
- NA |
- 5726_VC_N_0834_Bis |
-
-
- | 37 |
- HB_403_N |
- N |
- NA |
- 5734_VC_N_0833 |
-
-
- | 38 |
- HB_414_N |
- N |
- NA |
- 5772_VC_N_0832_Bis |
-
-
- | 39 |
- HB_416_N |
- N |
- NA |
- 5778_CR_N_0962 |
-
-
- | 40 |
- HB_418_N |
- N |
- NA |
- 5789_PF_N_1273 |
-
-
- | 41 |
- HB_421_N |
- N |
- NA |
- 5799_VC_N_1058 |
-
-
- | 42 |
- HB_423_N |
- N |
- NA |
- 5803_VC_N_0966 |
-
-
- | 43 |
- HB_426_N |
- N |
- NA |
- 5806_PF_N_1064 |
-
-
- | 44 |
- HB_427_N |
- N |
- NA |
- 5810_CR_N_0636 |
-
-
- | 45 |
- HB_431_N |
- N |
- NA |
- 5823_VC_N_0829 |
-
-
- | 46 |
- HB_432_N |
- N |
- NA |
- 5826_VC_N_0828 |
-
-
- | 47 |
- HB_433_N |
- N |
- NA |
- 5827_VC_N_0827 |
-
-
- | 48 |
- HB_436_N |
- N |
- NA |
- 5832_PF_N_1145 |
-
-
- | 49 |
- HB_443_N |
- N |
- NA |
- 5852_VC_N_0826 |
-
-
- | 50 |
- HB_446_N |
- N |
- NA |
- 5859_VC_N_0825 |
-
-
- | 51 |
- HB_449_N |
- N |
- NA |
- 5866_VC_N_0824 |
-
-
- | 52 |
- HB_450_N |
- N |
- NA |
- 5867_VC_N_1277 |
-
-
- | 53 |
- HB_453_N |
- N |
- NA |
- 5876_VC_N_0823 |
-
-
- | 54 |
- HB_462_N |
- N |
- NA |
- 5903_VC_N_0822 |
-
-
- | 55 |
- HB_464_N |
- N |
- NA |
- 5905_VC_N_0820 |
-
-
- | 56 |
- HB_468_N |
- N |
- NA |
- 5912_VC_N_1286 |
-
-
- | 57 |
- HB_472_N |
- N |
- NA |
- 5925_VC_N_1289 |
-
-
- | 58 |
- HB_475_N |
- N |
- NA |
- 5936_VC_N_0979 |
-
-
- | 59 |
- HB_476_N |
- N |
- NA |
- 5938_VC_N_0819 |
-
-
- | 60 |
- HB_480_N |
- N |
- NA |
- 5946_VC_N_0985 |
-
-
- | 61 |
- HB_485_N |
- N |
- NA |
- 5959_VC_N_0818 |
-
-
- | 62 |
- HB_486_N |
- N |
- NA |
- 5963_VC_N_0987 |
-
-
- | 63 |
- HB_495_N |
- N |
- NA |
- 5980_VC_N_0989 |
-
-
- | 64 |
- HB_497_N |
- N |
- NA |
- 5985_VC_N_0990 |
-
-
- | 65 |
- HB_500_N |
- N |
- NA |
- 5990_VC_N_0817 |
-
-
- | 66 |
- HB_501_N |
- N |
- NA |
- 5991_VC_N_0816 |
-
-
- | 67 |
- HB_504_N |
- N |
- NA |
- 5996_VC_N_0815 |
-
-
- | 68 |
- HB_505_N |
- N |
- NA |
- 5998_VC_N_0814 |
-
-
- | 69 |
- HB_507_N |
- N |
- NA |
- 6006_VC_N_0813 |
-
-
- | 70 |
- HB_508_N |
- N |
- NA |
- 6007_CR_N_0618 |
-
-
- | 71 |
- HB_509_N |
- N |
- NA |
- 6008_PF_N_1081 |
-
-
- | 72 |
- HB_512_N |
- N |
- NA |
- 6023_PF_N_1155 |
-
-
- | 73 |
- HB_516_N |
- N |
- NA |
- 6030_VC_N_0810 |
-
-
- | 74 |
- HB_519_N |
- N |
- NA |
- 6034_VC_N_0809 |
-
-
- | 75 |
- HB_532_N |
- N |
- NA |
- 6060_VC_N_1292 |
-
-
- | 76 |
- HB_541_N |
- N |
- NA |
- 6092_VC_N_1001 |
-
-
- | 77 |
- HB_542_N |
- N |
- NA |
- 6096_VC_N_0807 |
-
-
- | 78 |
- HB_544_N |
- N |
- NA |
- 6101_CR_N_1161 |
-
-
- | 79 |
- HB_547_N |
- N |
- NA |
- 6110_VC_N_1295 |
-
-
- | 80 |
- HB_551_N |
- N |
- NA |
- 6124_VC_N_0806 |
-
-
- | 81 |
- HB_557_N |
- N |
- NA |
- 6134_PF_N_1297 |
-
-
- | 82 |
- HB_560_N |
- N |
- NA |
- 6142_VC_N_0805 |
-
-
- | 83 |
- HB_569_N |
- N |
- NA |
- 6166_VC_N_0804 |
-
-
- | 84 |
- HB_570_N |
- N |
- NA |
- 6170_VC_N_0803 |
-
-
- | 85 |
- HB_572_N |
- N |
- NA |
- 6172_VC_N_1008 |
-
-
- | 86 |
- HB_577_N |
- N |
- NA |
- 6182_VC_N_1166 |
-
-
- | 87 |
- HB_579_N |
- N |
- NA |
- 6187_CR_N_0607 |
-
-
- | 88 |
- HB_581_N |
- N |
- NA |
- 6191_VC_N_1010 |
-
-
- | 89 |
- HB_584_N |
- N |
- NA |
- 6196_CR_N_0605 |
-
-
- | 90 |
- HB_586_N |
- N |
- NA |
- 6200_VC_N_0799 |
-
-
- | 91 |
- HB_587_N |
- N |
- NA |
- 6206_PF_N_1176 |
-
-
- | 92 |
- HB_589_N |
- N |
- NA |
- 6213_VC_N_0798 |
-
-
- | 93 |
- HB_601_N |
- N |
- NA |
- 6241_VC_N_0796 |
-
-
- | 94 |
- HB_604_N |
- N |
- NA |
- 6260_VC_N_0794 |
-
-
- | 95 |
- HB_609_N |
- N |
- NA |
- 6270_VC_N_0793 |
-
-
- | 96 |
- HB_618_N |
- N |
- NA |
- 6289_VC_N_0791 |
-
-
- | 97 |
- HB_622_N |
- N |
- NA |
- 6310_VC_N_0790 |
-
-
- | 98 |
- HB_625_N |
- N |
- NA |
- 6314_VC_N_0789 |
-
-
- | 99 |
- HB_637_N |
- N |
- NA |
- 6340_VC_N_0786 |
-
-
- | 100 |
- HB_638_N |
- N |
- NA |
- 6341_VC_N_0785 |
-
-
- | 101 |
- HB_640_N |
- N |
- NA |
- 6347_VC_N_0784 |
-
-
- | 102 |
- HB_641_N |
- N |
- NA |
- 6356_VC_N_0783 |
-
-
- | 103 |
- HB_643_N |
- N |
- NA |
- 6363_VC_N_0781 |
-
-
- | 104 |
- HB_644_N |
- N |
- NA |
- 6366_VC_N_0780 |
-
-
- | 105 |
- HB_645_N |
- N |
- NA |
- 6374_VC_N_0779 |
-
-
- | 106 |
- HB_650_N |
- N |
- NA |
- 6384_VC_N_0777 |
-
-
- | 107 |
- HB_651_N |
- N |
- NA |
- 6386_VC_N_0776 |
-
-
- | 108 |
- HB_653_N |
- N |
- NA |
- 6388_VC_N_0775 |
-
-
- | 109 |
- HB_659_N |
- N |
- NA |
- 6406_VC_N_1180 |
-
-
- | 110 |
- HB_662_N |
- N |
- NA |
- 6411_VC_N_0771 |
-
-
- | 111 |
- HB_663_N |
- N |
- NA |
- 6415_VC_N_0770 |
-
-
- | 112 |
- HB_670_N |
- N |
- NA |
- 6436_VC_N_0769 |
-
-
- | 113 |
- HB_687_N |
- N |
- NA |
- 6484_VC_N_0765 |
-
-
- | 114 |
- HB_689_N |
- N |
- NA |
- 6486_VC_N_0764 |
-
-
- | 115 |
- HB_694_N |
- N |
- NA |
- 6500_VC_N_0763 |
-
-
- | 116 |
- HB_697_N |
- N |
- NA |
- 6512_VC_N_0762 |
-
-
- | 117 |
- HB_700_N |
- N |
- NA |
- 6520_VC_N_0761 |
-
-
- | 118 |
- HB_711_N |
- N |
- NA |
- 6543_PF_N_1191 |
-
-
- | 119 |
- HB_714_N |
- N |
- NA |
- 6549_VC_N_1198 |
-
-
- | 120 |
- HB_717_N |
- N |
- NA |
- 6553_PF_N_2284 |
-
-
- | 121 |
- HB_721_N |
- N |
- NA |
- 6560_VC_N_2578 |
-
-
- | 122 |
- HB_726_N |
- N |
- NA |
- 6573_PF_N_2293 |
-
-
- | 123 |
- HB_730_N |
- N |
- NA |
- 6580_VC_N_2306 |
-
-
- | 124 |
- HB_735_N |
- N |
- NA |
- 6588_VC_N_1213 |
-
-
- | 125 |
- HB_737_N |
- N |
- NA |
- 6593_VC_N_1219 |
-
-
- | 126 |
- HB_738_N |
- N |
- NA |
- 6594_VC_N_1222 |
-
-
- | 127 |
- HB_759_N |
- N |
- NA |
- 6645_VC_N_1231 |
-
-
- | 128 |
- HB_764_N |
- N |
- NA |
- 6655_VC_N_1240 |
-
-
- | 129 |
- HB_765_N |
- N |
- NA |
- 6656_VC_N_1243 |
-
-
- | 130 |
- HB_767_N |
- N |
- NA |
- 6661_PF_N_2341 |
-
-
- | 131 |
- HB_770_N |
- N |
- NA |
- 6669_VC_N_1246 |
-
-
- | 132 |
- HB_772_N |
- N |
- NA |
- 6676_PF_N_1248 |
-
-
- | 133 |
- HB_001_HD |
- HD |
- F |
- 2028_CR_H_2282 |
-
-
- | 134 |
- HB_003_HD |
- HD |
- F |
- 2685_PF_H_2212 |
-
-
- | 135 |
- HB_004_HD |
- HD |
- M |
- 2706_CR_H_2432 |
-
-
- | 136 |
- HB_006_HD |
- HD |
- M |
- 2737_VC_H_2194 |
-
-
- | 137 |
- HB_007_HD |
- HD |
- NA |
- 2769_VC_H_2193 |
-
-
- | 138 |
- HB_008_HD |
- HD |
- F |
- 2790_CR_H_1890 |
-
-
- | 139 |
- HB_009_HD |
- HD |
- NA |
- 2879_VC_H_2192 |
-
-
- | 140 |
- HB_010_HD |
- HD |
- M |
- 2960_VC_H_2002 |
-
-
- | 141 |
- HB_011_HD |
- HD |
- F |
- 3053_VC_H_2001 |
-
-
- | 142 |
- HB_012_HD |
- HD |
- F |
- 3128_VC_H_1999 |
-
-
- | 143 |
- HB_014_HD |
- HD |
- F |
- 3149_PF_H_2110 |
-
-
- | 144 |
- HB_015_HD |
- HD |
- F |
- 3150_VC_H_1996 |
-
-
- | 145 |
- HB_016_HD |
- HD |
- F |
- 3177_VC_H_2191 |
-
-
- | 146 |
- HB_017_HD |
- HD |
- NA |
- 3195_VC_H_2190 |
-
-
- | 147 |
- HB_018_HD |
- HD |
- M |
- 3200_VC_H_2189 |
-
-
- | 148 |
- HB_019_HD |
- HD |
- M |
- 3209_VC_H_2188 |
-
-
- | 149 |
- HB_020_HD |
- HD |
- M |
- 3224_VC_H_1994 |
-
-
- | 150 |
- HB_022_HD |
- HD |
- F |
- 3242_PF_H_2105 |
-
-
- | 151 |
- HB_024_HD |
- HD |
- NA |
- 3272_VC_H_2186 |
-
-
- | 152 |
- HB_027_HD |
- HD |
- M |
- 3356_VC_H_2439 |
-
-
- | 153 |
- HB_028_HD |
- HD |
- F |
- 3394_PF_H_2104 |
-
-
- | 154 |
- HB_031_HD |
- HD |
- M |
- 3430_VC_H_1990 |
-
-
- | 155 |
- HB_032_HD |
- HD |
- NA |
- 3444_PF_H_2208 |
-
-
- | 156 |
- HB_034_HD |
- HD |
- F |
- 3482_VC_H_1987 |
-
-
- | 157 |
- HB_036_HD |
- HD |
- M |
- 3576_VC_H_1984 |
-
-
- | 158 |
- HB_037_HD |
- HD |
- F |
- 3579_VC_H_1983 |
-
-
- | 159 |
- HB_038_HD |
- HD |
- F |
- 3584_VC_H_2183 |
-
-
- | 160 |
- HB_039_HD |
- HD |
- NA |
- 3635_VC_H_2182 |
-
-
- | 161 |
- HB_041_HD |
- HD |
- F |
- 3695_CR_H_2267 |
-
-
- | 162 |
- HB_042_HD |
- HD |
- M |
- 3697_VC_H_1982 |
-
-
- | 163 |
- HB_043_HD |
- HD |
- NA |
- 3703_VC_H_2180 |
-
-
- | 164 |
- HB_044_HD |
- HD |
- NA |
- 3723_VC_H_2179 |
-
-
- | 165 |
- HB_046_HD |
- HD |
- F |
- 3735_VC_H_1981 |
-
-
- | 166 |
- HB_050_HD |
- HD |
- M |
- 3820_PF_H_2207 |
-
-
- | 167 |
- HB_051_HD |
- HD |
- F |
- 3849_CR_H_2262 |
-
-
- | 168 |
- HB_054_HD |
- HD |
- M |
- 3884_VC_H_2175 |
-
-
- | 169 |
- HB_056_HD |
- HD |
- NA |
- 4012_VC_H_2174 |
-
-
- | 170 |
- HB_057_HD |
- HD |
- NA |
- 4013_VC_H_2173 |
-
-
- | 171 |
- HB_059_HD |
- HD |
- NA |
- 4066_VC_H_2172 |
-
-
- | 172 |
- HB_060_HD |
- HD |
- NA |
- 4094_VC_H_2171 |
-
-
- | 173 |
- HB_061_HD |
- HD |
- F |
- 4116_VC_H_2170 |
-
-
- | 174 |
- HB_062_HD |
- HD |
- NA |
- 4121_VC_H_2169 |
-
-
- | 175 |
- HB_063_HD |
- HD |
- NA |
- 4215_VC_H_2167 |
-
-
- | 176 |
- HB_065_HD |
- HD |
- M |
- 4340_PF_H_2091 |
-
-
- | 177 |
- HB_066_HD |
- HD |
- F |
- 4344_VC_H_1977 |
-
-
- | 178 |
- HB_067_HD |
- HD |
- M |
- 4346_VC_H_2165 |
-
-
- | 179 |
- HB_069_HD |
- HD |
- F |
- 4356_VC_H_2164 |
-
-
- | 180 |
- HB_070_HD |
- HD |
- NA |
- 4386_CR_H_2249 |
-
-
- | 181 |
- HB_072_HD |
- HD |
- NA |
- 4404_VC_H_2161 |
-
-
- | 182 |
- HB_073_HD |
- HD |
- F |
- 4411_VC_H_1975 |
-
-
- | 183 |
- HB_074_HD |
- HD |
- NA |
- 4430_VC_H_2465 |
-
-
- | 184 |
- HB_075_HD |
- HD |
- M |
- 4470_VC_H_1974 |
-
-
- | 185 |
- HB_076_HD |
- HD |
- F |
- 4497_CR_H_1860 |
-
-
- | 186 |
- HB_077_HD |
- HD |
- M |
- 4509_CR_H_2244 |
-
-
- | 187 |
- HB_079_HD |
- HD |
- M |
- 4631_VC_H_1971 |
-
-
- | 188 |
- HB_080_HD |
- HD |
- F |
- 4653_PF_H_2083 |
-
-
- | 189 |
- HB_081_HD |
- HD |
- NA |
- 4678_CR_H_2242 |
-
-
- | 190 |
- HB_084_HD |
- HD |
- M |
- 4718_VC_H_2125 |
-
-
- | 191 |
- HB_090_HD |
- HD |
- NA |
- 4740_CR_H_2474 |
-
-
- | 192 |
- HB_094_HD |
- HD |
- NA |
- 4754_CR_H_2476 |
-
-
- | 193 |
- HB_098_HD |
- HD |
- NA |
- 4780_VC_H_2151 |
-
-
- | 194 |
- HB_101_HD |
- HD |
- F |
- 4809_VC_H_2148 |
-
-
- | 195 |
- HB_105_HD |
- HD |
- NA |
- 4819_CR_H_2238 |
-
-
- | 196 |
- HB_106_HD |
- HD |
- F |
- 4822_VC_H_1969 |
-
-
- | 197 |
- HB_108_HD |
- HD |
- M |
- 4826_VC_H_1968 |
-
-
- | 198 |
- HB_109_HD |
- HD |
- M |
- 4828_VC_H_2124 |
-
-
- | 199 |
- HB_115_HD |
- HD |
- NA |
- 4855_CR_H_2235 |
-
-
- | 200 |
- HB_121_HD |
- HD |
- F |
- 4902_VC_H_1967 |
-
-
- | 201 |
- HB_129_HD |
- HD |
- NA |
- 4938_VC_H_1966 |
-
-
- | 202 |
- HB_141_HD |
- HD |
- F |
- 4996_PF_H_2076 |
-
-
- | 203 |
- HB_152_HD |
- HD |
- NA |
- 5034_CR_H_2233 |
-
-
- | 204 |
- HB_153_HD |
- HD |
- M |
- 5043_VC_H_1960 |
-
-
- | 205 |
- HB_159_HD |
- HD |
- M |
- 5062_VC_H_1959 |
-
-
- | 206 |
- HB_172_HD |
- HD |
- F |
- 5114_PF_H_2070 |
-
-
- | 207 |
- HB_175_HD |
- HD |
- M |
- 5127_PF_H_2068 |
-
-
- | 208 |
- HB_180_HD |
- HD |
- M |
- 5148_VC_H_1944 |
-
-
- | 209 |
- HB_185_HD |
- HD |
- F |
- 5167_CR_H_2231 |
-
-
- | 210 |
- HB_188_HD |
- HD |
- F |
- 5172_VC_H_1951 |
-
-
- | 211 |
- HB_191_HD |
- HD |
- M |
- 5180_VC_H_1949 |
-
-
- | 212 |
- HB_196_HD |
- HD |
- NA |
- 5199_PF_H_2202 |
-
-
- | 213 |
- HB_203_HD |
- HD |
- F |
- 5228_PF_H_2059 |
-
-
- | 214 |
- HB_207_HD |
- HD |
- NA |
- 5248_PF_H_2201 |
-
-
- | 215 |
- HB_228_HD |
- HD |
- F |
- 5299_CR_H_2228 |
-
-
- | 216 |
- HB_233_HD |
- HD |
- M |
- 5312_VC_H_1938 |
-
-
- | 217 |
- HB_235_HD |
- HD |
- F |
- 5316_VC_H_1937 |
-
-
- | 218 |
- HB_242_HD |
- HD |
- F |
- 5328_PF_H_2048 |
-
-
- | 219 |
- HB_266_HD |
- HD |
- M |
- 5387_VC_H_1928 |
-
-
- | 220 |
- HB_271_HD |
- HD |
- M |
- 5394_PF_H_2039 |
-
-
- | 221 |
- HB_272_HD |
- HD |
- F |
- 5396_VC_H_1925 |
-
-
- | 222 |
- HB_279_HD |
- HD |
- F |
- 5409_VC_H_1924 |
-
-
- | 223 |
- HB_294_HD |
- HD |
- M |
- 5448_VC_H_1921 |
-
-
- | 224 |
- HB_301_HD |
- HD |
- NA |
- 5464_VC_H_1919 |
-
-
- | 225 |
- HB_304_HD |
- HD |
- F |
- 5471_VC_H_1918 |
-
-
- | 226 |
- HB_321_HD |
- HD |
- NA |
- 5522_PF_H_2199 |
-
-
- | 227 |
- HB_361_HD |
- HD |
- F |
- 5622_VC_H_2121 |
-
-
- | 228 |
- HB_370_HD |
- HD |
- M |
- 5645_VC_H_1904 |
-
-
- | 229 |
- HB_371_HD |
- HD |
- F |
- 5648_PF_H_2016 |
-
-
- | 230 |
- HB_384_HD |
- HD |
- F |
- 5688_PF_H_2012 |
-
-
- | 231 |
- HB_390_HD |
- HD |
- M |
- 5704_PF_H_2009 |
-
-
- | 232 |
- HB_393_HD |
- HD |
- F |
- 5709_VC_H_1895 |
-
-
- | 233 |
- HB_402_HD |
- HD |
- F |
- 5732_PF_H_2007 |
-
-
- | 234 |
- HB_405_HD |
- HD |
- NA |
- 5742_PF_H_2006 |
-
-
- | 235 |
- HB_407_HD |
- HD |
- M |
- 5745_PF_H_2005 |
-
-
- | 236 |
- HB_408_HD |
- HD |
- M |
- 5747_VC_H_1891 |
-
-
- | 237 |
- HB_415_HD |
- HD |
- NA |
- 5777_PF_H_1551 |
-
-
- | 238 |
- HB_417_HD |
- HD |
- M |
- 5784_PF_H_1554 |
-
-
- | 239 |
- HB_424_HD |
- HD |
- M |
- 5804_VC_H_1558 |
-
-
- | 240 |
- HB_444_HD |
- HD |
- M |
- 5856_VC_H_1567 |
-
-
- | 241 |
- HB_457_HD |
- HD |
- M |
- 5896_VC_H_1570 |
-
-
- | 242 |
- HB_466_HD |
- HD |
- M |
- 5910_PF_H_1572 |
-
-
- | 243 |
- HB_478_HD |
- HD |
- M |
- 5941_CR_H_1583 |
-
-
- | 244 |
- HB_487_HD |
- HD |
- F |
- 5964_VC_H_1597 |
-
-
- | 245 |
- HB_511_HD |
- HD |
- M |
- 6019_PF_H_2198 |
-
-
- | 246 |
- HB_513_HD |
- HD |
- F |
- 6024_VC_H_1612 |
-
-
- | 247 |
- HB_515_HD |
- HD |
- F |
- 6028_CR_H_1613 |
-
-
- | 248 |
- HB_518_HD |
- HD |
- M |
- 6033_VC_H_1618 |
-
-
- | 249 |
- HB_522_HD |
- HD |
- M |
- 6037_PF_H_1626 |
-
-
- | 250 |
- HB_527_HD |
- HD |
- F |
- 6047_VC_H_1639 |
-
-
- | 251 |
- HB_528_HD |
- HD |
- M |
- 6051_PF_H_1641 |
-
-
- | 252 |
- HB_530_HD |
- HD |
- M |
- 6054_VC_H_1648 |
-
-
- | 253 |
- HB_537_HD |
- HD |
- F |
- 6071_PF_H_1653 |
-
-
- | 254 |
- HB_549_HD |
- HD |
- M |
- 6119_CR_H_1670 |
-
-
- | 255 |
- HB_593_HD |
- HD |
- NA |
- 6219_CR_H_2567 |
-
-
- | 256 |
- HB_610_HD |
- HD |
- NA |
- 6275_PF_H_1692 |
-
-
- | 257 |
- HB_616_HD |
- HD |
- F |
- 6284_CR_H_1694 |
-
-
- | 258 |
- HB_626_HD |
- HD |
- M |
- 6315_VC_H_1702 |
-
-
- | 259 |
- HB_639_HD |
- HD |
- F |
- 6344_CR_H_1703 |
-
-
- | 260 |
- HB_649_HD |
- HD |
- F |
- 6382_CR_H_1709 |
-
-
- | 261 |
- HB_661_HD |
- HD |
- M |
- 6408_VC_H_1714 |
-
-
- | 262 |
- HB_682_HD |
- HD |
- M |
- 6467_PF_H_1725 |
-
-
- | 263 |
- HB_683_HD |
- HD |
- M |
- 6472_VC_H_1729 |
-
-
- | 264 |
- HB_691_HD |
- HD |
- F |
- 6493_VC_H_1732 |
-
-
- | 265 |
- HB_692_HD |
- HD |
- M |
- 6495_CR_H_1733 |
-
-
- | 266 |
- HB_707_HD |
- HD |
- M |
- 6535_PF_H_1737 |
-
-
- | 267 |
- HB_709_HD |
- HD |
- F |
- 6539_CR_H_1739 |
-
-
- | 268 |
- HB_725_HD |
- HD |
- M |
- 6572_PF_H_1746 |
-
-
- | 269 |
- HB_732_HD |
- HD |
- F |
- 6584_VC_H_1750 |
-
-
- | 270 |
- HB_734_HD |
- HD |
- F |
- 6587_CR_H_1751 |
-
-
- | 271 |
- HB_748_HD |
- HD |
- NA |
- 6615_VC_H_2315 |
-
-
- | 272 |
- HB_750_HD |
- HD |
- NA |
- 6628_PF_H_2326 |
-
-
- | 273 |
- HB_758_HD |
- HD |
- NA |
- 6643_VC_H_2602 |
-
-
- | 274 |
- HB_760_HD |
- HD |
- M |
- 6646_PF_H_1761 |
-
-
- | 275 |
- HB_762_HD |
- HD |
- M |
- 6650_VC_H_1765 |
-
-
- | 276 |
- HB_766_HD |
- HD |
- M |
- 6658_VC_H_1768 |
-
-
- | 277 |
- HB_768_HD |
- HD |
- NA |
- 6663_VC_H_1771 |
-
-
- | 278 |
- HB_769_HD |
- HD |
- M |
- 6666_VC_H_1774 |
-
-
- | 279 |
- HB_774_HD |
- HD |
- NA |
- 6689_PF_H_2344 |
-
-
- | 280 |
- HB_778_HD |
- HD |
- NA |
- 6696_PF_H_2356 |
-
-
- | 281 |
- HB_780_HD |
- HD |
- NA |
- 6704_PF_H_2362 |
-
-
- | 282 |
- HB_790_HD |
- HD |
- NA |
- 6788_PF_H_2389 |
-
-
- | 283 |
- HB_800_HD |
- HD |
- NA |
- 6807_PF_H_2419 |
-
-
- | 284 |
- HB_802_HD |
- HD |
- NA |
- 6811_PF_H_2425 |
-
-
- | 285 |
- HB_045_AD |
- AD |
- NA |
- 3734_CR_A_0122 |
-
-
- | 286 |
- HB_048_AD |
- AD |
- NA |
- 3791_CR_A_0128 |
-
-
- | 287 |
- HB_053_AD |
- AD |
- NA |
- 3877_CR_A_0134 |
-
-
- | 288 |
- HB_055_AD |
- AD |
- NA |
- 3893_VC_A_0142 |
-
-
- | 289 |
- HB_068_AD |
- AD |
- NA |
- 4349_VC_A_0148 |
-
-
- | 290 |
- HB_082_AD |
- AD |
- NA |
- 4712_CR_A_0309 |
-
-
- | 291 |
- HB_085_AD |
- AD |
- NA |
- 4726_VC_A_0311 |
-
-
- | 292 |
- HB_087_AD |
- AD |
- NA |
- 4730_CR_A_0315 |
-
-
- | 293 |
- HB_089_AD |
- AD |
- NA |
- 4733_VC_A_0320 |
-
-
- | 294 |
- HB_093_AD |
- AD |
- NA |
- 4749_VC_A_0323 |
-
-
- | 295 |
- HB_095_AD |
- AD |
- NA |
- 4759_CR_A_0327 |
-
-
- | 296 |
- HB_097_AD |
- AD |
- NA |
- 4773_CR_A_0866 |
-
-
- | 297 |
- HB_099_AD |
- AD |
- NA |
- 4785_VC_A_0332 |
-
-
- | 298 |
- HB_100_AD |
- AD |
- NA |
- 4795_VC_A_0335 |
-
-
- | 299 |
- HB_103_AD |
- AD |
- NA |
- 4811_VC_A_0341 |
-
-
- | 300 |
- HB_104_AD |
- AD |
- NA |
- 4813_CR_A_0345 |
-
-
- | 301 |
- HB_112_AD |
- AD |
- NA |
- 4842_VC_A_0870 |
-
-
- | 302 |
- HB_113_AD |
- AD |
- NA |
- 4850_CR_A_0351 |
-
-
- | 303 |
- HB_114_AD |
- AD |
- NA |
- 4852_CR_A_0354 |
-
-
- | 304 |
- HB_117_AD |
- AD |
- NA |
- 4868_VC_A_0874 |
-
-
- | 305 |
- HB_122_AD |
- AD |
- NA |
- 4904_CR_A_1132 |
-
-
- | 306 |
- HB_123_AD |
- AD |
- NA |
- 4905_VC_A_0884 |
-
-
- | 307 |
- HB_124_AD |
- AD |
- NA |
- 4916_VC_A_0886 |
-
-
- | 308 |
- HB_125_AD |
- AD |
- NA |
- 4917_CR_A_0360 |
-
-
- | 309 |
- HB_126_AD |
- AD |
- NA |
- 4921_VC_A_0362 |
-
-
- | 310 |
- HB_128_AD |
- AD |
- NA |
- 4936_CR_A_0369 |
-
-
- | 311 |
- HB_130_AD |
- AD |
- NA |
- 4939_VC_A_0888 |
-
-
- | 312 |
- HB_131_AD |
- AD |
- NA |
- 4944_CR_A_0889 |
-
-
- | 313 |
- HB_132_AD |
- AD |
- NA |
- 4946_CR_A_0372 |
-
-
- | 314 |
- HB_134_AD |
- AD |
- NA |
- 4951_CR_A_0891 |
-
-
- | 315 |
- HB_135_AD |
- AD |
- NA |
- 4953_VC_A_0893 |
-
-
- | 316 |
- HB_136_AD |
- AD |
- NA |
- 4965_VC_A_0160 |
-
-
- | 317 |
- HB_137_AD |
- AD |
- NA |
- 4966_VC_A_0374 |
-
-
- | 318 |
- HB_138_AD |
- AD |
- NA |
- 4969_VC_A_0895 |
-
-
- | 319 |
- HB_140_AD |
- AD |
- NA |
- 4993_CR_A_0896 |
-
-
- | 320 |
- HB_146_AD |
- AD |
- NA |
- 5018_CR_A_0384 |
-
-
- | 321 |
- HB_148_AD |
- AD |
- NA |
- 5022_VC_A_0386 |
-
-
- | 322 |
- HB_150_AD |
- AD |
- NA |
- 5031_VC_A_0392 |
-
-
- | 323 |
- HB_151_AD |
- AD |
- NA |
- 5033_CR_A_0396 |
-
-
- | 324 |
- HB_154_AD |
- AD |
- NA |
- 5048_VC_A_1321 |
-
-
- | 325 |
- HB_155_AD |
- AD |
- NA |
- 5056_VC_A_0398 |
-
-
- | 326 |
- HB_156_AD |
- AD |
- NA |
- 5057_VC_A_0163 |
-
-
- | 327 |
- HB_157_AD |
- AD |
- NA |
- 5059_VC_A_0401 |
-
-
- | 328 |
- HB_158_AD |
- AD |
- NA |
- 5061_PF_A_2612 |
-
-
- | 329 |
- HB_160_AD |
- AD |
- NA |
- 5064_PF_A_2615 |
-
-
- | 330 |
- HB_165_AD |
- AD |
- NA |
- 5092_CR_A_0899 |
-
-
- | 331 |
- HB_168_AD |
- AD |
- NA |
- 5097_VC_A_0407 |
-
-
- | 332 |
- HB_170_AD |
- AD |
- NA |
- 5101_VC_A_0410 |
-
-
- | 333 |
- HB_174_AD |
- AD |
- NA |
- 5124_PF_A_1343 |
-
-
- | 334 |
- HB_179_AD |
- AD |
- NA |
- 5145_VC_A_1351 |
-
-
- | 335 |
- HB_181_AD |
- AD |
- NA |
- 5152_CR_A_0414 |
-
-
- | 336 |
- HB_184_AD |
- AD |
- NA |
- 5166_VC_A_1354 |
-
-
- | 337 |
- HB_194_AD |
- AD |
- NA |
- 5193_VC_A_1360 |
-
-
- | 338 |
- HB_197_AD |
- AD |
- NA |
- 5202_CR_A_1368 |
-
-
- | 339 |
- HB_199_AD |
- AD |
- NA |
- 5205_VC_A_0166 |
-
-
- | 340 |
- HB_200_AD |
- AD |
- NA |
- 5210_VC_A_0905 |
-
-
- | 341 |
- HB_205_AD |
- AD |
- NA |
- 5235_VC_A_0419 |
-
-
- | 342 |
- HB_208_AD |
- AD |
- NA |
- 5249_VC_A_0422 |
-
-
- | 343 |
- HB_209_AD |
- AD |
- NA |
- 5252_VC_A_0907 |
-
-
- | 344 |
- HB_211_AD |
- AD |
- NA |
- 5257_VC_A_0169 |
-
-
- | 345 |
- HB_216_AD |
- AD |
- NA |
- 5272_VC_A_0425 |
-
-
- | 346 |
- HB_219_AD |
- AD |
- NA |
- 5279_CR_A_0147 |
-
-
- | 347 |
- HB_221_AD |
- AD |
- NA |
- 5283_VC_A_0145 |
-
-
- | 348 |
- HB_222_AD |
- AD |
- NA |
- 5285_VC_A_0141 |
-
-
- | 349 |
- HB_224_AD |
- AD |
- NA |
- 5288_VC_A_0428 |
-
-
- | 350 |
- HB_230_AD |
- AD |
- NA |
- 5301_VC_A_0174 |
-
-
- | 351 |
- HB_231_AD |
- AD |
- NA |
- 5305_VC_A_1384 |
-
-
- | 352 |
- HB_232_AD |
- AD |
- NA |
- 5310_CR_A_0176 |
-
-
- | 353 |
- HB_234_AD |
- AD |
- NA |
- 5313_PF_A_2618 |
-
-
- | 354 |
- HB_236_AD |
- AD |
- NA |
- 5317_PF_A_2624 |
-
-
- | 355 |
- HB_238_AD |
- AD |
- NA |
- 5322_CR_A_2632 |
-
-
- | 356 |
- HB_240_AD |
- AD |
- NA |
- 5325_VC_A_0137 |
-
-
- | 357 |
- HB_244_AD |
- AD |
- NA |
- 5337_VC_A_1387 |
-
-
- | 358 |
- HB_245_AD |
- AD |
- NA |
- 5339_VC_A_0181 |
-
-
- | 359 |
- HB_250_AD |
- AD |
- NA |
- 5346_VC_A_1393 |
-
-
- | 360 |
- HB_251_AD |
- AD |
- NA |
- 5350_VC_A_0184 |
-
-
- | 361 |
- HB_252_AD |
- AD |
- NA |
- 5355_VC_A_0133 |
-
-
- | 362 |
- HB_253_AD |
- AD |
- NA |
- 5359_CR_A_1395 |
-
-
- | 363 |
- HB_258_AD |
- AD |
- NA |
- 5370_PF_A_1400 |
-
-
- | 364 |
- HB_259_AD |
- AD |
- NA |
- 5371_PF_A_2636 |
-
-
- | 365 |
- HB_260_AD |
- AD |
- NA |
- 5375_VC_A_0188 |
-
-
- | 366 |
- HB_263_AD |
- AD |
- NA |
- 5381_VC_A_0022 |
-
-
- | 367 |
- HB_265_AD |
- AD |
- NA |
- 5385_VC_A_1402 |
-
-
- | 368 |
- HB_267_AD |
- AD |
- NA |
- 5389_VC_A_0928 |
-
-
- | 369 |
- HB_268_AD |
- AD |
- NA |
- 5390_CR_A_0151 |
-
-
- | 370 |
- HB_273_AD |
- AD |
- NA |
- 5400_PF_A_2645 |
-
-
- | 371 |
- HB_274_AD |
- AD |
- NA |
- 5401_VC_A_0931 |
-
-
- | 372 |
- HB_275_AD |
- AD |
- NA |
- 5404_PF_A_2648 |
-
-
- | 373 |
- HB_276_AD |
- AD |
- NA |
- 5406_VC_A_0933 |
-
-
- | 374 |
- HB_277_AD |
- AD |
- NA |
- 5407_PF_A_2651 |
-
-
- | 375 |
- HB_280_AD |
- AD |
- NA |
- 5412_VC_A_0935 |
-
-
- | 376 |
- HB_281_AD |
- AD |
- NA |
- 5413_PF_A_2657 |
-
-
- | 377 |
- HB_283_AD |
- AD |
- NA |
- 5419_VC_A_0937 |
-
-
- | 378 |
- HB_284_AD |
- AD |
- NA |
- 5420_VC_A_0939 |
-
-
- | 379 |
- HB_285_AD |
- AD |
- NA |
- 5421_CR_A_0432 |
-
-
- | 380 |
- HB_286_AD |
- AD |
- NA |
- 5423_PF_A_2660 |
-
-
- | 381 |
- HB_288_AD |
- AD |
- NA |
- 5425_PF_A_2666 |
-
-
- | 382 |
- HB_289_AD |
- AD |
- NA |
- 5426_VC_A_1405 |
-
-
- | 383 |
- HB_290_AD |
- AD |
- NA |
- 5433_VC_A_0434 |
-
-
- | 384 |
- HB_296_AD |
- AD |
- NA |
- 5456_PF_A_2675 |
-
-
- | 385 |
- HB_299_AD |
- AD |
- NA |
- 5461_VC_A_0192 |
-
-
- | 386 |
- HB_302_AD |
- AD |
- NA |
- 5465_PF_A_2678 |
-
-
- | 387 |
- HB_303_AD |
- AD |
- NA |
- 5469_VC_A_1417 |
-
-
- | 388 |
- HB_305_AD |
- AD |
- NA |
- 5479_PF_A_1421 |
-
-
- | 389 |
- HB_306_AD |
- AD |
- NA |
- 5480_VC_A_0437 |
-
-
- | 390 |
- HB_307_AD |
- AD |
- NA |
- 5482_VC_A_0028 |
-
-
- | 391 |
- HB_308_AD |
- AD |
- NA |
- 5483_VC_A_0941 |
-
-
- | 392 |
- HB_309_AD |
- AD |
- NA |
- 5487_CR_A_0441 |
-
-
- | 393 |
- HB_310_AD |
- AD |
- NA |
- 5488_CR_A_0194 |
-
-
- | 394 |
- HB_312_AD |
- AD |
- NA |
- 5500_VC_A_0198 |
-
-
- | 395 |
- HB_313_AD |
- AD |
- NA |
- 5502_PF_A_2684 |
-
-
- | 396 |
- HB_315_AD |
- AD |
- NA |
- 5513_PF_A_2687 |
-
-
- | 397 |
- HB_316_AD |
- AD |
- NA |
- 5516_PF_A_2690 |
-
-
- | 398 |
- HB_317_AD |
- AD |
- NA |
- 5517_PF_A_2693 |
-
-
- | 399 |
- HB_318_AD |
- AD |
- NA |
- 5518_CR_A_0030 |
-
-
- | 400 |
- HB_319_AD |
- AD |
- NA |
- 5519_CR_A_2695 |
-
-
- | 401 |
- HB_320_AD |
- AD |
- NA |
- 5520_PF_A_2699 |
-
-
- | 402 |
- HB_322_AD |
- AD |
- NA |
- 5527_VC_A_0945 |
-
-
- | 403 |
- HB_325_AD |
- AD |
- NA |
- 5532_PF_A_2702 |
-
-
- | 404 |
- HB_328_AD |
- AD |
- NA |
- 5541_PF_A_2705 |
-
-
- | 405 |
- HB_330_AD |
- AD |
- NA |
- 5544_VC_A_0201 |
-
-
- | 406 |
- HB_334_AD |
- AD |
- NA |
- 5554_VC_A_0452 |
-
-
- | 407 |
- HB_335_AD |
- AD |
- NA |
- 5557_VC_A_0950 |
-
-
- | 408 |
- HB_337_AD |
- AD |
- NA |
- 5560_VC_A_0204 |
-
-
- | 409 |
- HB_342_AD |
- AD |
- NA |
- 5571_PF_A_1430 |
-
-
- | 410 |
- HB_345_AD |
- AD |
- NA |
- 5583_PF_A_2708 |
-
-
- | 411 |
- HB_347_AD |
- AD |
- NA |
- 5589_PF_A_2714 |
-
-
- | 412 |
- HB_349_AD |
- AD |
- NA |
- 5592_PF_A_2717 |
-
-
- | 413 |
- HB_352_AD |
- AD |
- NA |
- 5604_VC_A_0037 |
-
-
- | 414 |
- HB_353_AD |
- AD |
- NA |
- 5607_PF_A_2723 |
-
-
- | 415 |
- HB_356_AD |
- AD |
- NA |
- 5615_VC_A_0041 |
-
-
- | 416 |
- HB_357_AD |
- AD |
- NA |
- 5616_CR_A_0127 |
-
-
- | 417 |
- HB_358_AD |
- AD |
- NA |
- 5617_CR_A_0456 |
-
-
- | 418 |
- HB_359_AD |
- AD |
- NA |
- 5618_CR_A_0044 |
-
-
- | 419 |
- HB_362_AD |
- AD |
- NA |
- 5625_CR_A_2495 |
-
-
- | 420 |
- HB_363_AD |
- AD |
- NA |
- 5626_CR_A_2498 |
-
-
- | 421 |
- HB_364_AD |
- AD |
- NA |
- 5629_CR_A_0390 |
-
-
- | 422 |
- HB_369_AD |
- AD |
- NA |
- 5643_VC_A_1143 |
-
-
- | 423 |
- HB_373_AD |
- AD |
- NA |
- 5654_VC_A_0047 |
-
-
- | 424 |
- HB_375_AD |
- AD |
- NA |
- 5660_CR_A_0462 |
-
-
- | 425 |
- HB_376_AD |
- AD |
- NA |
- 5661_VC_A_0464 |
-
-
- | 426 |
- HB_377_AD |
- AD |
- NA |
- 5667_VC_A_2509 |
-
-
- | 427 |
- HB_378_AD |
- AD |
- NA |
- 5668_VC_A_1438 |
-
-
- | 428 |
- HB_383_AD |
- AD |
- NA |
- 5686_CR_A_2728 |
-
-
- | 429 |
- HB_386_AD |
- AD |
- NA |
- 5695_VC_A_0953 |
-
-
- | 430 |
- HB_389_AD |
- AD |
- NA |
- 5700_VC_A_2514 |
-
-
- | 431 |
- HB_391_AD |
- AD |
- NA |
- 5705_CR_A_0474 |
-
-
- | 432 |
- HB_392_AD |
- AD |
- NA |
- 5706_VC_A_0476 |
-
-
- | 433 |
- HB_394_AD |
- AD |
- NA |
- 5713_VC_A_0479 |
-
-
- | 434 |
- HB_397_AD |
- AD |
- NA |
- 5721_CR_A_0210 |
-
-
- | 435 |
- HB_404_AD |
- AD |
- NA |
- 5735_CR_A_0489 |
-
-
- | 436 |
- HB_406_AD |
- AD |
- NA |
- 5744_CR_A_0960 |
-
-
- | 437 |
- HB_409_AD |
- AD |
- NA |
- 5749_CR_A_0159 |
-
-
- | 438 |
- HB_410_AD |
- AD |
- NA |
- 5751_CR_A_2518 |
-
-
- | 439 |
- HB_411_AD |
- AD |
- NA |
- 5755_CR_A_2731 |
-
-
- | 440 |
- HB_413_AD |
- AD |
- NA |
- 5766_VC_A_0214 |
-
-
- | 441 |
- HB_419_AD |
- AD |
- NA |
- 5790_VC_A_0217 |
-
-
- | 442 |
- HB_420_AD |
- AD |
- NA |
- 5796_CR_A_0964 |
-
-
- | 443 |
- HB_428_AD |
- AD |
- NA |
- 5811_CR_A_2524 |
-
-
- | 444 |
- HB_429_AD |
- AD |
- NA |
- 5819_CR_A_2527 |
-
-
- | 445 |
- HB_430_AD |
- AD |
- NA |
- 5822_CR_A_2530 |
-
-
- | 446 |
- HB_434_AD |
- AD |
- NA |
- 5828_CR_A_2533 |
-
-
- | 447 |
- HB_435_AD |
- AD |
- NA |
- 5831_CR_A_0222 |
-
-
- | 448 |
- HB_437_AD |
- AD |
- NA |
- 5839_CR_A_2539 |
-
-
- | 449 |
- HB_438_AD |
- AD |
- NA |
- 5843_CR_A_0227 |
-
-
- | 450 |
- HB_439_AD |
- AD |
- NA |
- 5845_CR_A_0230 |
-
-
- | 451 |
- HB_441_AD |
- AD |
- NA |
- 5849_CR_A_0233 |
-
-
- | 452 |
- HB_442_AD |
- AD |
- NA |
- 5850_CR_A_0495 |
-
-
- | 453 |
- HB_445_AD |
- AD |
- NA |
- 5858_CR_A_0969 |
-
-
- | 454 |
- HB_448_AD |
- AD |
- NA |
- 5864_CR_A_0974 |
-
-
- | 455 |
- HB_451_AD |
- AD |
- NA |
- 5871_CR_A_2542 |
-
-
- | 456 |
- HB_454_AD |
- AD |
- NA |
- 5879_CR_A_2545 |
-
-
- | 457 |
- HB_455_AD |
- AD |
- NA |
- 5887_CR_A_0976_Bis |
-
-
- | 458 |
- HB_459_AD |
- AD |
- NA |
- 5898_CR_A_2548 |
-
-
- | 459 |
- HB_460_AD |
- AD |
- NA |
- 5900_VC_A_0237 |
-
-
- | 460 |
- HB_461_AD |
- AD |
- NA |
- 5901_CR_A_0239 |
-
-
- | 461 |
- HB_469_AD |
- AD |
- NA |
- 5914_CR_A_2554 |
-
-
- | 462 |
- HB_471_AD |
- AD |
- NA |
- 5922_VC_A_0246 |
-
-
- | 463 |
- HB_473_AD |
- AD |
- NA |
- 5927_CR_A_2560 |
-
-
- | 464 |
- HB_474_AD |
- AD |
- NA |
- 5933_VC_A_1071 |
-
-
- | 465 |
- HB_477_AD |
- AD |
- NA |
- 5939_CR_A_1151 |
-
-
- | 466 |
- HB_479_AD |
- AD |
- NA |
- 5945_VC_A_0983 |
-
-
- | 467 |
- HB_484_AD |
- AD |
- NA |
- 5956_CR_A_0123 |
-
-
- | 468 |
- HB_489_AD |
- AD |
- NA |
- 5968_VC_A_1075 |
-
-
- | 469 |
- HB_491_AD |
- AD |
- NA |
- 5971_CR_A_0119 |
-
-
- | 470 |
- HB_492_AD |
- AD |
- NA |
- 5972_VC_A_0251 |
-
-
- | 471 |
- HB_494_AD |
- AD |
- NA |
- 5979_CR_A_0115 |
-
-
- | 472 |
- HB_498_AD |
- AD |
- NA |
- 5988_VC_A_0503 |
-
-
- | 473 |
- HB_502_AD |
- AD |
- NA |
- 5994_PF_A_1605 |
-
-
- | 474 |
- HB_503_AD |
- AD |
- NA |
- 5995_CR_A_2563 |
-
-
- | 475 |
- HB_510_AD |
- AD |
- NA |
- 6017_CR_A_0048 |
-
-
- | 476 |
- HB_514_AD |
- AD |
- NA |
- 6025_VC_A_0506 |
-
-
- | 477 |
- HB_517_AD |
- AD |
- NA |
- 6031_VC_A_0258 |
-
-
- | 478 |
- HB_520_AD |
- AD |
- NA |
- 6035_VC_A_1621 |
-
-
- | 479 |
- HB_523_AD |
- AD |
- NA |
- 6038_VC_A_0261 |
-
-
- | 480 |
- HB_524_AD |
- AD |
- NA |
- 6042_VC_A_1156 |
-
-
- | 481 |
- HB_525_AD |
- AD |
- NA |
- 6044_VC_A_0264 |
-
-
- | 482 |
- HB_531_AD |
- AD |
- NA |
- 6056_CR_A_0999 |
-
-
- | 483 |
- HB_533_AD |
- AD |
- NA |
- 6061_PF_A_1650 |
-
-
- | 484 |
- HB_534_AD |
- AD |
- NA |
- 6066_VC_A_0270 |
-
-
- | 485 |
- HB_535_AD |
- AD |
- NA |
- 6067_PF_A_1452 |
-
-
- | 486 |
- HB_536_AD |
- AD |
- NA |
- 6068_VC_A_0273 |
-
-
- | 487 |
- HB_545_AD |
- AD |
- NA |
- 6102_CR_A_1661 |
-
-
- | 488 |
- HB_546_AD |
- AD |
- NA |
- 6107_CR_A_0055 |
-
-
- | 489 |
- HB_550_AD |
- AD |
- NA |
- 6120_VC_A_0058 |
-
-
- | 490 |
- HB_552_AD |
- AD |
- NA |
- 6126_VC_A_1675 |
-
-
- | 491 |
- HB_553_AD |
- AD |
- NA |
- 6129_PF_A_0274 |
-
-
- | 492 |
- HB_554_AD |
- AD |
- NA |
- 6130_VC_A_1678 |
-
-
- | 493 |
- HB_555_AD |
- AD |
- NA |
- 6131_CR_A_0510 |
-
-
- | 494 |
- HB_556_AD |
- AD |
- NA |
- 6132_CR_A_0513 |
-
-
- | 495 |
- HB_558_AD |
- AD |
- NA |
- 6137_VC_A_1681 |
-
-
- | 496 |
- HB_564_AD |
- AD |
- NA |
- 6153_VC_A_1465 |
-
-
- | 497 |
- HB_565_AD |
- AD |
- NA |
- 6154_VC_A_1468 |
-
-
- | 498 |
- HB_566_AD |
- AD |
- NA |
- 6157_VC_A_0062 |
-
-
- | 499 |
- HB_568_AD |
- AD |
- NA |
- 6164_CR_A_1005 |
-
-
- | 500 |
- HB_571_AD |
- AD |
- NA |
- 6171_CR_A_0065 |
-
-
- | 501 |
- HB_573_AD |
- AD |
- NA |
- 6174_VC_A_0068 |
-
-
- | 502 |
- HB_576_AD |
- AD |
- NA |
- 6180_CR_A_0281 |
-
-
- | 503 |
- HB_583_AD |
- AD |
- NA |
- 6194_VC_A_0071 |
-
-
- | 504 |
- HB_585_AD |
- AD |
- NA |
- 6198_VC_A_0073 |
-
-
- | 505 |
- HB_590_AD |
- AD |
- NA |
- 6215_VC_A_0518 |
-
-
- | 506 |
- HB_591_AD |
- AD |
- NA |
- 6216_VC_A_1476 |
-
-
- | 507 |
- HB_592_AD |
- AD |
- NA |
- 6218_CR_A_0522 |
-
-
- | 508 |
- HB_594_AD |
- AD |
- NA |
- 6223_VC_A_0288 |
-
-
- | 509 |
- HB_596_AD |
- AD |
- NA |
- 6226_CR_A_0076 |
-
-
- | 510 |
- HB_597_AD |
- AD |
- NA |
- 6227_VC_A_0080 |
-
-
- | 511 |
- HB_598_AD |
- AD |
- NA |
- 6231_VC_A_1479 |
-
-
- | 512 |
- HB_605_AD |
- AD |
- NA |
- 6261_VC_A_0084 |
-
-
- | 513 |
- HB_608_AD |
- AD |
- NA |
- 6268_CR_A_0525 |
-
-
- | 514 |
- HB_611_AD |
- AD |
- NA |
- 6279_VC_A_0089 |
-
-
- | 515 |
- HB_612_AD |
- AD |
- NA |
- 6280_VC_A_0091 |
-
-
- | 516 |
- HB_613_AD |
- AD |
- NA |
- 6281_CR_A_0528 |
-
-
- | 517 |
- HB_621_AD |
- AD |
- NA |
- 6308_VC_A_1503 |
-
-
- | 518 |
- HB_623_AD |
- AD |
- NA |
- 6311_CR_A_0531 |
-
-
- | 519 |
- HB_624_AD |
- AD |
- NA |
- 6312_CR_A_0534 |
-
-
- | 520 |
- HB_630_AD |
- AD |
- NA |
- 6324_PF_A_1514 |
-
-
- | 521 |
- HB_633_AD |
- AD |
- NA |
- 6332_VC_A_1518 |
-
-
- | 522 |
- HB_634_AD |
- AD |
- NA |
- 6335_VC_A_0536 |
-
-
- | 523 |
- HB_635_AD |
- AD |
- NA |
- 6336_CR_A_0290 |
-
-
- | 524 |
- HB_636_AD |
- AD |
- NA |
- 6338_VC_A_0539 |
-
-
- | 525 |
- HB_642_AD |
- AD |
- NA |
- 6358_VC_A_0545 |
-
-
- | 526 |
- HB_652_AD |
- AD |
- NA |
- 6387_VC_A_0093 |
-
-
- | 527 |
- HB_657_AD |
- AD |
- NA |
- 6394_VC_A_0551 |
-
-
- | 528 |
- HB_664_AD |
- AD |
- NA |
- 6416_VC_A_1095 |
-
-
- | 529 |
- HB_666_AD |
- AD |
- NA |
- 6422_CR_A_0555 |
-
-
- | 530 |
- HB_669_AD |
- AD |
- NA |
- 6431_VC_A_0294 |
-
-
- | 531 |
- HB_674_AD |
- AD |
- NA |
- 6449_VC_A_1183 |
-
-
- | 532 |
- HB_680_AD |
- AD |
- NA |
- 6458_CR_A_2570 |
-
-
- | 533 |
- HB_685_AD |
- AD |
- NA |
- 6481_VC_A_0560 |
-
-
- | 534 |
- HB_690_AD |
- AD |
- NA |
- 6489_CR_A_0100 |
-
-
- | 535 |
- HB_696_AD |
- AD |
- NA |
- 6511_VC_A_1119 |
-
-
- | 536 |
- HB_698_AD |
- AD |
- NA |
- 6515_CR_A_0564 |
-
-
- | 537 |
- HB_699_AD |
- AD |
- NA |
- 6518_VC_A_0103 |
-
-
- | 538 |
- HB_703_AD |
- AD |
- NA |
- 6523_VC_A_0107 |
-
-
- | 539 |
- HB_704_AD |
- AD |
- NA |
- 6530_VC_A_0112 |
-
-
- | 540 |
- HB_706_AD |
- AD |
- NA |
- 6534_VC_A_0306 |
-
-
- | 541 |
- HB_712_AD |
- AD |
- NA |
- 6546_PF_A_1194 |
-
-
- | 542 |
- HB_713_AD |
- AD |
- NA |
- 6548_PF_A_1541 |
-
-
- | 543 |
- HB_715_AD |
- AD |
- NA |
- 6550_VC_A_1201 |
-
-
- | 544 |
- HB_718_AD |
- AD |
- NA |
- 6554_PF_A_1203 |
-
-
- | 545 |
- HB_720_AD |
- AD |
- NA |
- 6559_PF_A_2287 |
-
-
- | 546 |
- HB_722_AD |
- AD |
- NA |
- 6561_CR_A_2582 |
-
-
- | 547 |
- HB_723_AD |
- AD |
- NA |
- 6562_PF_A_2290 |
-
-
- | 548 |
- HB_724_AD |
- AD |
- NA |
- 6564_CR_A_2585 |
-
-
- | 549 |
- HB_727_AD |
- AD |
- NA |
- 6575_CR_A_2298 |
-
-
- | 550 |
- HB_728_AD |
- AD |
- NA |
- 6577_PF_A_2299 |
-
-
- | 551 |
- HB_729_AD |
- AD |
- NA |
- 6578_PF_A_2302 |
-
-
- | 552 |
- HB_731_AD |
- AD |
- NA |
- 6582_VC_A_1207 |
-
-
- | 553 |
- HB_733_AD |
- AD |
- NA |
- 6585_VC_A_1210 |
-
-
- | 554 |
- HB_736_AD |
- AD |
- NA |
- 6590_PF_A_1215 |
-
-
- | 555 |
- HB_743_AD |
- AD |
- NA |
- 6603_PF_A_1448 |
-
-
- | 556 |
- HB_745_AD |
- AD |
- NA |
- 6610_PF_A_1227 |
-
-
- | 557 |
- HB_746_AD |
- AD |
- NA |
- 6612_PF_A_2308 |
-
-
- | 558 |
- HB_749_AD |
- AD |
- NA |
- 6617_VC_A_2587 |
-
-
- | 559 |
- HB_751_AD |
- AD |
- NA |
- 6629_VC_A_2330 |
-
-
- | 560 |
- HB_752_AD |
- AD |
- NA |
- 6630_VC_A_2590 |
-
-
- | 561 |
- HB_753_AD |
- AD |
- NA |
- 6632_PF_A_2332 |
-
-
- | 562 |
- HB_754_AD |
- AD |
- NA |
- 6637_VC_A_2596 |
-
-
- | 563 |
- HB_755_AD |
- AD |
- NA |
- 6638_VC_A_2599 |
-
-
- | 564 |
- HB_756_AD |
- AD |
- NA |
- 6639_VC_A_2336 |
-
-
- | 565 |
- HB_757_AD |
- AD |
- NA |
- 6641_PF_A_2338 |
-
-
- | 566 |
- HB_763_AD |
- AD |
- NA |
- 6654_VC_A_1237 |
-
-
- | 567 |
- HB_773_AD |
- AD |
- NA |
- 6681_VC_A_1252 |
-
-
- | 568 |
- HB_775_AD |
- AD |
- NA |
- 6693_VC_A_2348 |
-
-
- | 569 |
- HB_776_AD |
- AD |
- NA |
- 6694_VC_A_2351 |
-
-
- | 570 |
- HB_777_AD |
- AD |
- NA |
- 6695_PF_A_2353 |
-
-
- | 571 |
- HB_779_AD |
- AD |
- NA |
- 6699_PF_A_2359 |
-
-
- | 572 |
- HB_781_AD |
- AD |
- NA |
- 6708_VC_A_2366 |
-
-
- | 573 |
- HB_782_AD |
- AD |
- NA |
- 6776_PF_A_2607 |
-
-
- | 574 |
- HB_783_AD |
- AD |
- NA |
- 6778_PF_A_2368 |
-
-
- | 575 |
- HB_784_AD |
- AD |
- NA |
- 6779_PF_A_2371 |
-
-
- | 576 |
- HB_785_AD |
- AD |
- NA |
- 6780_PF_A_2374 |
-
-
- | 577 |
- HB_786_AD |
- AD |
- NA |
- 6782_PF_A_2377 |
-
-
- | 578 |
- HB_787_AD |
- AD |
- NA |
- 6784_PF_A_2380 |
-
-
- | 579 |
- HB_788_AD |
- AD |
- NA |
- 6785_CR_A_2385 |
-
-
- | 580 |
- HB_789_AD |
- AD |
- NA |
- 6787_CR_A_2388 |
-
-
- | 581 |
- HB_791_AD |
- AD |
- NA |
- 6790_PF_A_2392 |
-
-
- | 582 |
- HB_792_AD |
- AD |
- NA |
- 6791_PF_A_2395 |
-
-
- | 583 |
- HB_793_AD |
- AD |
- NA |
- 6793_PF_A_2398 |
-
-
- | 584 |
- HB_794_AD |
- AD |
- NA |
- 6794_PF_A_2401 |
-
-
- | 585 |
- HB_795_AD |
- AD |
- NA |
- 6797_PF_A_2404 |
-
-
- | 586 |
- HB_796_AD |
- AD |
- NA |
- 6798_PF_A_2407 |
-
-
- | 587 |
- HB_797_AD |
- AD |
- NA |
- 6799_VC_A_2411 |
-
-
- | 588 |
- HB_798_AD |
- AD |
- NA |
- 6801_VC_A_2414 |
-
-
- | 589 |
- HB_799_AD |
- AD |
- NA |
- 6803_VC_A_2417 |
-
-
- | 590 |
- HB_801_AD |
- AD |
- NA |
- 6809_PF_A_2422 |
-
-
- | 591 |
- HB_803_AD |
- AD |
- NA |
- 6818_CR_A_2430 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/HBTRC_MLPFC_N_0611/experiment-design.rtf b/general/datasets/HBTRC_MLPFC_N_0611/experiment-design.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_N_0611/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_N_0611/notes.rtf b/general/datasets/HBTRC_MLPFC_N_0611/notes.rtf
deleted file mode 100644
index ff90e34..0000000
--- a/general/datasets/HBTRC_MLPFC_N_0611/notes.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Species: Human
-Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
-Disease: Neurological Disease
-Investigator: Francine Benes/ Eric Schadt
-Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
-Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC_MLPFC_N_0611/platform.rtf b/general/datasets/HBTRC_MLPFC_N_0611/platform.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_N_0611/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_N_0611/processing.rtf b/general/datasets/HBTRC_MLPFC_N_0611/processing.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_N_0611/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLPFC_N_0611/summary.rtf b/general/datasets/HBTRC_MLPFC_N_0611/summary.rtf
deleted file mode 100644
index 5cde3bf..0000000
--- a/general/datasets/HBTRC_MLPFC_N_0611/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC_MLPFC_N_0611/tissue.rtf b/general/datasets/HBTRC_MLPFC_N_0611/tissue.rtf
deleted file mode 100644
index 4ee3070..0000000
--- a/general/datasets/HBTRC_MLPFC_N_0611/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-See PMID: 25080494
diff --git a/general/datasets/HBTRC_MLVC_0611/acknowledgment.rtf b/general/datasets/HBTRC_MLVC_0611/acknowledgment.rtf
deleted file mode 100644
index 208cb6e..0000000
--- a/general/datasets/HBTRC_MLVC_0611/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC_MLVC_0611/cases.rtf b/general/datasets/HBTRC_MLVC_0611/cases.rtf
deleted file mode 100644
index 86ed08e..0000000
--- a/general/datasets/HBTRC_MLVC_0611/cases.rtf
+++ /dev/null
@@ -1,4166 +0,0 @@
-This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- | Series |
- Cerebellum in GN |
- Condition |
- Gender |
- BioSample Name |
-
-
- | 1 |
- HB_029_N |
- N |
- NA |
- 3405_VC_N_0859 |
-
-
- | 2 |
- HB_058_N |
- N |
- NA |
- 4021_VC_N_0854 |
-
-
- | 3 |
- HB_064_N |
- N |
- NA |
- 4338_VC_N_0861 |
-
-
- | 4 |
- HB_086_N |
- N |
- NA |
- 4729_PF_N_0756 |
-
-
- | 5 |
- HB_091_N |
- N |
- NA |
- 4741_VC_N_0864 |
-
-
- | 6 |
- HB_092_N |
- N |
- NA |
- 4744_VC_N_0865 |
-
-
- | 7 |
- HB_102_N |
- N |
- NA |
- 4810_VC_N_0869 |
-
-
- | 8 |
- HB_119_N |
- N |
- NA |
- 4872_VC_N_0878 |
-
-
- | 9 |
- HB_147_N |
- N |
- NA |
- 5021_VC_N_0852 |
-
-
- | 10 |
- HB_161_N |
- N |
- NA |
- 5077_VC_N_0851 |
-
-
- | 11 |
- HB_162_N |
- N |
- NA |
- 5081_VC_N_1021 |
-
-
- | 12 |
- HB_166_N |
- N |
- NA |
- 5095_VC_N_1024 |
-
-
- | 13 |
- HB_183_N |
- N |
- NA |
- 5162_VC_N_0850 |
-
-
- | 14 |
- HB_206_N |
- N |
- NA |
- 5245_VC_N_0849 |
-
-
- | 15 |
- HB_215_N |
- N |
- NA |
- 5270_VC_N_0848 |
-
-
- | 16 |
- HB_218_N |
- N |
- NA |
- 5276_CR_N_0912 |
-
-
- | 17 |
- HB_223_N |
- N |
- NA |
- 5287_VC_N_0916 |
-
-
- | 18 |
- HB_226_N |
- N |
- NA |
- 5294_VC_N_0919 |
-
-
- | 19 |
- HB_241_N |
- N |
- NA |
- 5326_CR_N_0652 |
-
-
- | 20 |
- HB_243_N |
- N |
- NA |
- 5333_VC_N_1262 |
-
-
- | 21 |
- HB_247_N |
- N |
- NA |
- 5341_VC_N_0923 |
-
-
- | 22 |
- HB_257_N |
- N |
- NA |
- 5368_PF_N_1032 |
-
-
- | 23 |
- HB_264_N |
- N |
- NA |
- 5384_VC_N_0924 |
-
-
- | 24 |
- HB_295_N |
- N |
- NA |
- 5452_VC_N_1268 |
-
-
- | 25 |
- HB_300_N |
- N |
- NA |
- 5463_VC_N_0845 |
-
-
- | 26 |
- HB_311_N |
- N |
- NA |
- 5489_CR_N_0942 |
-
-
- | 27 |
- HB_324_N |
- N |
- NA |
- 5531_VC_N_0844 |
-
-
- | 28 |
- HB_332_N |
- N |
- NA |
- 5547_VC_N_0843 |
-
-
- | 29 |
- HB_340_N |
- N |
- NA |
- 5568_VC_N_0842 |
-
-
- | 30 |
- HB_360_N |
- N |
- NA |
- 5619_CR_N_0645 |
-
-
- | 31 |
- HB_365_N |
- N |
- NA |
- 5632_VC_N_0838 |
-
-
- | 32 |
- HB_367_N |
- N |
- NA |
- 5637_VC_N_0837 |
-
-
- | 33 |
- HB_382_N |
- N |
- NA |
- 5684_PF_N_1270 |
-
-
- | 34 |
- HB_396_N |
- N |
- NA |
- 5718_VC_N_0956 |
-
-
- | 35 |
- HB_398_N |
- N |
- NA |
- 5722_VC_N_1044 |
-
-
- | 36 |
- HB_400_N |
- N |
- NA |
- 5726_VC_N_0834_Bis |
-
-
- | 37 |
- HB_403_N |
- N |
- NA |
- 5734_VC_N_0833 |
-
-
- | 38 |
- HB_414_N |
- N |
- NA |
- 5772_VC_N_0832_Bis |
-
-
- | 39 |
- HB_416_N |
- N |
- NA |
- 5778_CR_N_0962 |
-
-
- | 40 |
- HB_418_N |
- N |
- NA |
- 5789_PF_N_1273 |
-
-
- | 41 |
- HB_421_N |
- N |
- NA |
- 5799_VC_N_1058 |
-
-
- | 42 |
- HB_423_N |
- N |
- NA |
- 5803_VC_N_0966 |
-
-
- | 43 |
- HB_426_N |
- N |
- NA |
- 5806_PF_N_1064 |
-
-
- | 44 |
- HB_427_N |
- N |
- NA |
- 5810_CR_N_0636 |
-
-
- | 45 |
- HB_431_N |
- N |
- NA |
- 5823_VC_N_0829 |
-
-
- | 46 |
- HB_432_N |
- N |
- NA |
- 5826_VC_N_0828 |
-
-
- | 47 |
- HB_433_N |
- N |
- NA |
- 5827_VC_N_0827 |
-
-
- | 48 |
- HB_436_N |
- N |
- NA |
- 5832_PF_N_1145 |
-
-
- | 49 |
- HB_443_N |
- N |
- NA |
- 5852_VC_N_0826 |
-
-
- | 50 |
- HB_446_N |
- N |
- NA |
- 5859_VC_N_0825 |
-
-
- | 51 |
- HB_449_N |
- N |
- NA |
- 5866_VC_N_0824 |
-
-
- | 52 |
- HB_450_N |
- N |
- NA |
- 5867_VC_N_1277 |
-
-
- | 53 |
- HB_453_N |
- N |
- NA |
- 5876_VC_N_0823 |
-
-
- | 54 |
- HB_462_N |
- N |
- NA |
- 5903_VC_N_0822 |
-
-
- | 55 |
- HB_464_N |
- N |
- NA |
- 5905_VC_N_0820 |
-
-
- | 56 |
- HB_468_N |
- N |
- NA |
- 5912_VC_N_1286 |
-
-
- | 57 |
- HB_472_N |
- N |
- NA |
- 5925_VC_N_1289 |
-
-
- | 58 |
- HB_475_N |
- N |
- NA |
- 5936_VC_N_0979 |
-
-
- | 59 |
- HB_476_N |
- N |
- NA |
- 5938_VC_N_0819 |
-
-
- | 60 |
- HB_480_N |
- N |
- NA |
- 5946_VC_N_0985 |
-
-
- | 61 |
- HB_485_N |
- N |
- NA |
- 5959_VC_N_0818 |
-
-
- | 62 |
- HB_486_N |
- N |
- NA |
- 5963_VC_N_0987 |
-
-
- | 63 |
- HB_495_N |
- N |
- NA |
- 5980_VC_N_0989 |
-
-
- | 64 |
- HB_497_N |
- N |
- NA |
- 5985_VC_N_0990 |
-
-
- | 65 |
- HB_500_N |
- N |
- NA |
- 5990_VC_N_0817 |
-
-
- | 66 |
- HB_501_N |
- N |
- NA |
- 5991_VC_N_0816 |
-
-
- | 67 |
- HB_504_N |
- N |
- NA |
- 5996_VC_N_0815 |
-
-
- | 68 |
- HB_505_N |
- N |
- NA |
- 5998_VC_N_0814 |
-
-
- | 69 |
- HB_507_N |
- N |
- NA |
- 6006_VC_N_0813 |
-
-
- | 70 |
- HB_508_N |
- N |
- NA |
- 6007_CR_N_0618 |
-
-
- | 71 |
- HB_509_N |
- N |
- NA |
- 6008_PF_N_1081 |
-
-
- | 72 |
- HB_512_N |
- N |
- NA |
- 6023_PF_N_1155 |
-
-
- | 73 |
- HB_516_N |
- N |
- NA |
- 6030_VC_N_0810 |
-
-
- | 74 |
- HB_519_N |
- N |
- NA |
- 6034_VC_N_0809 |
-
-
- | 75 |
- HB_532_N |
- N |
- NA |
- 6060_VC_N_1292 |
-
-
- | 76 |
- HB_541_N |
- N |
- NA |
- 6092_VC_N_1001 |
-
-
- | 77 |
- HB_542_N |
- N |
- NA |
- 6096_VC_N_0807 |
-
-
- | 78 |
- HB_544_N |
- N |
- NA |
- 6101_CR_N_1161 |
-
-
- | 79 |
- HB_547_N |
- N |
- NA |
- 6110_VC_N_1295 |
-
-
- | 80 |
- HB_551_N |
- N |
- NA |
- 6124_VC_N_0806 |
-
-
- | 81 |
- HB_557_N |
- N |
- NA |
- 6134_PF_N_1297 |
-
-
- | 82 |
- HB_560_N |
- N |
- NA |
- 6142_VC_N_0805 |
-
-
- | 83 |
- HB_569_N |
- N |
- NA |
- 6166_VC_N_0804 |
-
-
- | 84 |
- HB_570_N |
- N |
- NA |
- 6170_VC_N_0803 |
-
-
- | 85 |
- HB_572_N |
- N |
- NA |
- 6172_VC_N_1008 |
-
-
- | 86 |
- HB_577_N |
- N |
- NA |
- 6182_VC_N_1166 |
-
-
- | 87 |
- HB_579_N |
- N |
- NA |
- 6187_CR_N_0607 |
-
-
- | 88 |
- HB_581_N |
- N |
- NA |
- 6191_VC_N_1010 |
-
-
- | 89 |
- HB_584_N |
- N |
- NA |
- 6196_CR_N_0605 |
-
-
- | 90 |
- HB_586_N |
- N |
- NA |
- 6200_VC_N_0799 |
-
-
- | 91 |
- HB_587_N |
- N |
- NA |
- 6206_PF_N_1176 |
-
-
- | 92 |
- HB_589_N |
- N |
- NA |
- 6213_VC_N_0798 |
-
-
- | 93 |
- HB_601_N |
- N |
- NA |
- 6241_VC_N_0796 |
-
-
- | 94 |
- HB_604_N |
- N |
- NA |
- 6260_VC_N_0794 |
-
-
- | 95 |
- HB_609_N |
- N |
- NA |
- 6270_VC_N_0793 |
-
-
- | 96 |
- HB_618_N |
- N |
- NA |
- 6289_VC_N_0791 |
-
-
- | 97 |
- HB_622_N |
- N |
- NA |
- 6310_VC_N_0790 |
-
-
- | 98 |
- HB_625_N |
- N |
- NA |
- 6314_VC_N_0789 |
-
-
- | 99 |
- HB_637_N |
- N |
- NA |
- 6340_VC_N_0786 |
-
-
- | 100 |
- HB_638_N |
- N |
- NA |
- 6341_VC_N_0785 |
-
-
- | 101 |
- HB_640_N |
- N |
- NA |
- 6347_VC_N_0784 |
-
-
- | 102 |
- HB_641_N |
- N |
- NA |
- 6356_VC_N_0783 |
-
-
- | 103 |
- HB_643_N |
- N |
- NA |
- 6363_VC_N_0781 |
-
-
- | 104 |
- HB_644_N |
- N |
- NA |
- 6366_VC_N_0780 |
-
-
- | 105 |
- HB_645_N |
- N |
- NA |
- 6374_VC_N_0779 |
-
-
- | 106 |
- HB_650_N |
- N |
- NA |
- 6384_VC_N_0777 |
-
-
- | 107 |
- HB_651_N |
- N |
- NA |
- 6386_VC_N_0776 |
-
-
- | 108 |
- HB_653_N |
- N |
- NA |
- 6388_VC_N_0775 |
-
-
- | 109 |
- HB_659_N |
- N |
- NA |
- 6406_VC_N_1180 |
-
-
- | 110 |
- HB_662_N |
- N |
- NA |
- 6411_VC_N_0771 |
-
-
- | 111 |
- HB_663_N |
- N |
- NA |
- 6415_VC_N_0770 |
-
-
- | 112 |
- HB_670_N |
- N |
- NA |
- 6436_VC_N_0769 |
-
-
- | 113 |
- HB_687_N |
- N |
- NA |
- 6484_VC_N_0765 |
-
-
- | 114 |
- HB_689_N |
- N |
- NA |
- 6486_VC_N_0764 |
-
-
- | 115 |
- HB_694_N |
- N |
- NA |
- 6500_VC_N_0763 |
-
-
- | 116 |
- HB_697_N |
- N |
- NA |
- 6512_VC_N_0762 |
-
-
- | 117 |
- HB_700_N |
- N |
- NA |
- 6520_VC_N_0761 |
-
-
- | 118 |
- HB_711_N |
- N |
- NA |
- 6543_PF_N_1191 |
-
-
- | 119 |
- HB_714_N |
- N |
- NA |
- 6549_VC_N_1198 |
-
-
- | 120 |
- HB_717_N |
- N |
- NA |
- 6553_PF_N_2284 |
-
-
- | 121 |
- HB_721_N |
- N |
- NA |
- 6560_VC_N_2578 |
-
-
- | 122 |
- HB_726_N |
- N |
- NA |
- 6573_PF_N_2293 |
-
-
- | 123 |
- HB_730_N |
- N |
- NA |
- 6580_VC_N_2306 |
-
-
- | 124 |
- HB_735_N |
- N |
- NA |
- 6588_VC_N_1213 |
-
-
- | 125 |
- HB_737_N |
- N |
- NA |
- 6593_VC_N_1219 |
-
-
- | 126 |
- HB_738_N |
- N |
- NA |
- 6594_VC_N_1222 |
-
-
- | 127 |
- HB_759_N |
- N |
- NA |
- 6645_VC_N_1231 |
-
-
- | 128 |
- HB_764_N |
- N |
- NA |
- 6655_VC_N_1240 |
-
-
- | 129 |
- HB_765_N |
- N |
- NA |
- 6656_VC_N_1243 |
-
-
- | 130 |
- HB_767_N |
- N |
- NA |
- 6661_PF_N_2341 |
-
-
- | 131 |
- HB_770_N |
- N |
- NA |
- 6669_VC_N_1246 |
-
-
- | 132 |
- HB_772_N |
- N |
- NA |
- 6676_PF_N_1248 |
-
-
- | 133 |
- HB_001_HD |
- HD |
- F |
- 2028_CR_H_2282 |
-
-
- | 134 |
- HB_003_HD |
- HD |
- F |
- 2685_PF_H_2212 |
-
-
- | 135 |
- HB_004_HD |
- HD |
- M |
- 2706_CR_H_2432 |
-
-
- | 136 |
- HB_006_HD |
- HD |
- M |
- 2737_VC_H_2194 |
-
-
- | 137 |
- HB_007_HD |
- HD |
- NA |
- 2769_VC_H_2193 |
-
-
- | 138 |
- HB_008_HD |
- HD |
- F |
- 2790_CR_H_1890 |
-
-
- | 139 |
- HB_009_HD |
- HD |
- NA |
- 2879_VC_H_2192 |
-
-
- | 140 |
- HB_010_HD |
- HD |
- M |
- 2960_VC_H_2002 |
-
-
- | 141 |
- HB_011_HD |
- HD |
- F |
- 3053_VC_H_2001 |
-
-
- | 142 |
- HB_012_HD |
- HD |
- F |
- 3128_VC_H_1999 |
-
-
- | 143 |
- HB_014_HD |
- HD |
- F |
- 3149_PF_H_2110 |
-
-
- | 144 |
- HB_015_HD |
- HD |
- F |
- 3150_VC_H_1996 |
-
-
- | 145 |
- HB_016_HD |
- HD |
- F |
- 3177_VC_H_2191 |
-
-
- | 146 |
- HB_017_HD |
- HD |
- NA |
- 3195_VC_H_2190 |
-
-
- | 147 |
- HB_018_HD |
- HD |
- M |
- 3200_VC_H_2189 |
-
-
- | 148 |
- HB_019_HD |
- HD |
- M |
- 3209_VC_H_2188 |
-
-
- | 149 |
- HB_020_HD |
- HD |
- M |
- 3224_VC_H_1994 |
-
-
- | 150 |
- HB_022_HD |
- HD |
- F |
- 3242_PF_H_2105 |
-
-
- | 151 |
- HB_024_HD |
- HD |
- NA |
- 3272_VC_H_2186 |
-
-
- | 152 |
- HB_027_HD |
- HD |
- M |
- 3356_VC_H_2439 |
-
-
- | 153 |
- HB_028_HD |
- HD |
- F |
- 3394_PF_H_2104 |
-
-
- | 154 |
- HB_031_HD |
- HD |
- M |
- 3430_VC_H_1990 |
-
-
- | 155 |
- HB_032_HD |
- HD |
- NA |
- 3444_PF_H_2208 |
-
-
- | 156 |
- HB_034_HD |
- HD |
- F |
- 3482_VC_H_1987 |
-
-
- | 157 |
- HB_036_HD |
- HD |
- M |
- 3576_VC_H_1984 |
-
-
- | 158 |
- HB_037_HD |
- HD |
- F |
- 3579_VC_H_1983 |
-
-
- | 159 |
- HB_038_HD |
- HD |
- F |
- 3584_VC_H_2183 |
-
-
- | 160 |
- HB_039_HD |
- HD |
- NA |
- 3635_VC_H_2182 |
-
-
- | 161 |
- HB_041_HD |
- HD |
- F |
- 3695_CR_H_2267 |
-
-
- | 162 |
- HB_042_HD |
- HD |
- M |
- 3697_VC_H_1982 |
-
-
- | 163 |
- HB_043_HD |
- HD |
- NA |
- 3703_VC_H_2180 |
-
-
- | 164 |
- HB_044_HD |
- HD |
- NA |
- 3723_VC_H_2179 |
-
-
- | 165 |
- HB_046_HD |
- HD |
- F |
- 3735_VC_H_1981 |
-
-
- | 166 |
- HB_050_HD |
- HD |
- M |
- 3820_PF_H_2207 |
-
-
- | 167 |
- HB_051_HD |
- HD |
- F |
- 3849_CR_H_2262 |
-
-
- | 168 |
- HB_054_HD |
- HD |
- M |
- 3884_VC_H_2175 |
-
-
- | 169 |
- HB_056_HD |
- HD |
- NA |
- 4012_VC_H_2174 |
-
-
- | 170 |
- HB_057_HD |
- HD |
- NA |
- 4013_VC_H_2173 |
-
-
- | 171 |
- HB_059_HD |
- HD |
- NA |
- 4066_VC_H_2172 |
-
-
- | 172 |
- HB_060_HD |
- HD |
- NA |
- 4094_VC_H_2171 |
-
-
- | 173 |
- HB_061_HD |
- HD |
- F |
- 4116_VC_H_2170 |
-
-
- | 174 |
- HB_062_HD |
- HD |
- NA |
- 4121_VC_H_2169 |
-
-
- | 175 |
- HB_063_HD |
- HD |
- NA |
- 4215_VC_H_2167 |
-
-
- | 176 |
- HB_065_HD |
- HD |
- M |
- 4340_PF_H_2091 |
-
-
- | 177 |
- HB_066_HD |
- HD |
- F |
- 4344_VC_H_1977 |
-
-
- | 178 |
- HB_067_HD |
- HD |
- M |
- 4346_VC_H_2165 |
-
-
- | 179 |
- HB_069_HD |
- HD |
- F |
- 4356_VC_H_2164 |
-
-
- | 180 |
- HB_070_HD |
- HD |
- NA |
- 4386_CR_H_2249 |
-
-
- | 181 |
- HB_072_HD |
- HD |
- NA |
- 4404_VC_H_2161 |
-
-
- | 182 |
- HB_073_HD |
- HD |
- F |
- 4411_VC_H_1975 |
-
-
- | 183 |
- HB_074_HD |
- HD |
- NA |
- 4430_VC_H_2465 |
-
-
- | 184 |
- HB_075_HD |
- HD |
- M |
- 4470_VC_H_1974 |
-
-
- | 185 |
- HB_076_HD |
- HD |
- F |
- 4497_CR_H_1860 |
-
-
- | 186 |
- HB_077_HD |
- HD |
- M |
- 4509_CR_H_2244 |
-
-
- | 187 |
- HB_079_HD |
- HD |
- M |
- 4631_VC_H_1971 |
-
-
- | 188 |
- HB_080_HD |
- HD |
- F |
- 4653_PF_H_2083 |
-
-
- | 189 |
- HB_081_HD |
- HD |
- NA |
- 4678_CR_H_2242 |
-
-
- | 190 |
- HB_084_HD |
- HD |
- M |
- 4718_VC_H_2125 |
-
-
- | 191 |
- HB_090_HD |
- HD |
- NA |
- 4740_CR_H_2474 |
-
-
- | 192 |
- HB_094_HD |
- HD |
- NA |
- 4754_CR_H_2476 |
-
-
- | 193 |
- HB_098_HD |
- HD |
- NA |
- 4780_VC_H_2151 |
-
-
- | 194 |
- HB_101_HD |
- HD |
- F |
- 4809_VC_H_2148 |
-
-
- | 195 |
- HB_105_HD |
- HD |
- NA |
- 4819_CR_H_2238 |
-
-
- | 196 |
- HB_106_HD |
- HD |
- F |
- 4822_VC_H_1969 |
-
-
- | 197 |
- HB_108_HD |
- HD |
- M |
- 4826_VC_H_1968 |
-
-
- | 198 |
- HB_109_HD |
- HD |
- M |
- 4828_VC_H_2124 |
-
-
- | 199 |
- HB_115_HD |
- HD |
- NA |
- 4855_CR_H_2235 |
-
-
- | 200 |
- HB_121_HD |
- HD |
- F |
- 4902_VC_H_1967 |
-
-
- | 201 |
- HB_129_HD |
- HD |
- NA |
- 4938_VC_H_1966 |
-
-
- | 202 |
- HB_141_HD |
- HD |
- F |
- 4996_PF_H_2076 |
-
-
- | 203 |
- HB_152_HD |
- HD |
- NA |
- 5034_CR_H_2233 |
-
-
- | 204 |
- HB_153_HD |
- HD |
- M |
- 5043_VC_H_1960 |
-
-
- | 205 |
- HB_159_HD |
- HD |
- M |
- 5062_VC_H_1959 |
-
-
- | 206 |
- HB_172_HD |
- HD |
- F |
- 5114_PF_H_2070 |
-
-
- | 207 |
- HB_175_HD |
- HD |
- M |
- 5127_PF_H_2068 |
-
-
- | 208 |
- HB_180_HD |
- HD |
- M |
- 5148_VC_H_1944 |
-
-
- | 209 |
- HB_185_HD |
- HD |
- F |
- 5167_CR_H_2231 |
-
-
- | 210 |
- HB_188_HD |
- HD |
- F |
- 5172_VC_H_1951 |
-
-
- | 211 |
- HB_191_HD |
- HD |
- M |
- 5180_VC_H_1949 |
-
-
- | 212 |
- HB_196_HD |
- HD |
- NA |
- 5199_PF_H_2202 |
-
-
- | 213 |
- HB_203_HD |
- HD |
- F |
- 5228_PF_H_2059 |
-
-
- | 214 |
- HB_207_HD |
- HD |
- NA |
- 5248_PF_H_2201 |
-
-
- | 215 |
- HB_228_HD |
- HD |
- F |
- 5299_CR_H_2228 |
-
-
- | 216 |
- HB_233_HD |
- HD |
- M |
- 5312_VC_H_1938 |
-
-
- | 217 |
- HB_235_HD |
- HD |
- F |
- 5316_VC_H_1937 |
-
-
- | 218 |
- HB_242_HD |
- HD |
- F |
- 5328_PF_H_2048 |
-
-
- | 219 |
- HB_266_HD |
- HD |
- M |
- 5387_VC_H_1928 |
-
-
- | 220 |
- HB_271_HD |
- HD |
- M |
- 5394_PF_H_2039 |
-
-
- | 221 |
- HB_272_HD |
- HD |
- F |
- 5396_VC_H_1925 |
-
-
- | 222 |
- HB_279_HD |
- HD |
- F |
- 5409_VC_H_1924 |
-
-
- | 223 |
- HB_294_HD |
- HD |
- M |
- 5448_VC_H_1921 |
-
-
- | 224 |
- HB_301_HD |
- HD |
- NA |
- 5464_VC_H_1919 |
-
-
- | 225 |
- HB_304_HD |
- HD |
- F |
- 5471_VC_H_1918 |
-
-
- | 226 |
- HB_321_HD |
- HD |
- NA |
- 5522_PF_H_2199 |
-
-
- | 227 |
- HB_361_HD |
- HD |
- F |
- 5622_VC_H_2121 |
-
-
- | 228 |
- HB_370_HD |
- HD |
- M |
- 5645_VC_H_1904 |
-
-
- | 229 |
- HB_371_HD |
- HD |
- F |
- 5648_PF_H_2016 |
-
-
- | 230 |
- HB_384_HD |
- HD |
- F |
- 5688_PF_H_2012 |
-
-
- | 231 |
- HB_390_HD |
- HD |
- M |
- 5704_PF_H_2009 |
-
-
- | 232 |
- HB_393_HD |
- HD |
- F |
- 5709_VC_H_1895 |
-
-
- | 233 |
- HB_402_HD |
- HD |
- F |
- 5732_PF_H_2007 |
-
-
- | 234 |
- HB_405_HD |
- HD |
- NA |
- 5742_PF_H_2006 |
-
-
- | 235 |
- HB_407_HD |
- HD |
- M |
- 5745_PF_H_2005 |
-
-
- | 236 |
- HB_408_HD |
- HD |
- M |
- 5747_VC_H_1891 |
-
-
- | 237 |
- HB_415_HD |
- HD |
- NA |
- 5777_PF_H_1551 |
-
-
- | 238 |
- HB_417_HD |
- HD |
- M |
- 5784_PF_H_1554 |
-
-
- | 239 |
- HB_424_HD |
- HD |
- M |
- 5804_VC_H_1558 |
-
-
- | 240 |
- HB_444_HD |
- HD |
- M |
- 5856_VC_H_1567 |
-
-
- | 241 |
- HB_457_HD |
- HD |
- M |
- 5896_VC_H_1570 |
-
-
- | 242 |
- HB_466_HD |
- HD |
- M |
- 5910_PF_H_1572 |
-
-
- | 243 |
- HB_478_HD |
- HD |
- M |
- 5941_CR_H_1583 |
-
-
- | 244 |
- HB_487_HD |
- HD |
- F |
- 5964_VC_H_1597 |
-
-
- | 245 |
- HB_511_HD |
- HD |
- M |
- 6019_PF_H_2198 |
-
-
- | 246 |
- HB_513_HD |
- HD |
- F |
- 6024_VC_H_1612 |
-
-
- | 247 |
- HB_515_HD |
- HD |
- F |
- 6028_CR_H_1613 |
-
-
- | 248 |
- HB_518_HD |
- HD |
- M |
- 6033_VC_H_1618 |
-
-
- | 249 |
- HB_522_HD |
- HD |
- M |
- 6037_PF_H_1626 |
-
-
- | 250 |
- HB_527_HD |
- HD |
- F |
- 6047_VC_H_1639 |
-
-
- | 251 |
- HB_528_HD |
- HD |
- M |
- 6051_PF_H_1641 |
-
-
- | 252 |
- HB_530_HD |
- HD |
- M |
- 6054_VC_H_1648 |
-
-
- | 253 |
- HB_537_HD |
- HD |
- F |
- 6071_PF_H_1653 |
-
-
- | 254 |
- HB_549_HD |
- HD |
- M |
- 6119_CR_H_1670 |
-
-
- | 255 |
- HB_593_HD |
- HD |
- NA |
- 6219_CR_H_2567 |
-
-
- | 256 |
- HB_610_HD |
- HD |
- NA |
- 6275_PF_H_1692 |
-
-
- | 257 |
- HB_616_HD |
- HD |
- F |
- 6284_CR_H_1694 |
-
-
- | 258 |
- HB_626_HD |
- HD |
- M |
- 6315_VC_H_1702 |
-
-
- | 259 |
- HB_639_HD |
- HD |
- F |
- 6344_CR_H_1703 |
-
-
- | 260 |
- HB_649_HD |
- HD |
- F |
- 6382_CR_H_1709 |
-
-
- | 261 |
- HB_661_HD |
- HD |
- M |
- 6408_VC_H_1714 |
-
-
- | 262 |
- HB_682_HD |
- HD |
- M |
- 6467_PF_H_1725 |
-
-
- | 263 |
- HB_683_HD |
- HD |
- M |
- 6472_VC_H_1729 |
-
-
- | 264 |
- HB_691_HD |
- HD |
- F |
- 6493_VC_H_1732 |
-
-
- | 265 |
- HB_692_HD |
- HD |
- M |
- 6495_CR_H_1733 |
-
-
- | 266 |
- HB_707_HD |
- HD |
- M |
- 6535_PF_H_1737 |
-
-
- | 267 |
- HB_709_HD |
- HD |
- F |
- 6539_CR_H_1739 |
-
-
- | 268 |
- HB_725_HD |
- HD |
- M |
- 6572_PF_H_1746 |
-
-
- | 269 |
- HB_732_HD |
- HD |
- F |
- 6584_VC_H_1750 |
-
-
- | 270 |
- HB_734_HD |
- HD |
- F |
- 6587_CR_H_1751 |
-
-
- | 271 |
- HB_748_HD |
- HD |
- NA |
- 6615_VC_H_2315 |
-
-
- | 272 |
- HB_750_HD |
- HD |
- NA |
- 6628_PF_H_2326 |
-
-
- | 273 |
- HB_758_HD |
- HD |
- NA |
- 6643_VC_H_2602 |
-
-
- | 274 |
- HB_760_HD |
- HD |
- M |
- 6646_PF_H_1761 |
-
-
- | 275 |
- HB_762_HD |
- HD |
- M |
- 6650_VC_H_1765 |
-
-
- | 276 |
- HB_766_HD |
- HD |
- M |
- 6658_VC_H_1768 |
-
-
- | 277 |
- HB_768_HD |
- HD |
- NA |
- 6663_VC_H_1771 |
-
-
- | 278 |
- HB_769_HD |
- HD |
- M |
- 6666_VC_H_1774 |
-
-
- | 279 |
- HB_774_HD |
- HD |
- NA |
- 6689_PF_H_2344 |
-
-
- | 280 |
- HB_778_HD |
- HD |
- NA |
- 6696_PF_H_2356 |
-
-
- | 281 |
- HB_780_HD |
- HD |
- NA |
- 6704_PF_H_2362 |
-
-
- | 282 |
- HB_790_HD |
- HD |
- NA |
- 6788_PF_H_2389 |
-
-
- | 283 |
- HB_800_HD |
- HD |
- NA |
- 6807_PF_H_2419 |
-
-
- | 284 |
- HB_802_HD |
- HD |
- NA |
- 6811_PF_H_2425 |
-
-
- | 285 |
- HB_045_AD |
- AD |
- NA |
- 3734_CR_A_0122 |
-
-
- | 286 |
- HB_048_AD |
- AD |
- NA |
- 3791_CR_A_0128 |
-
-
- | 287 |
- HB_053_AD |
- AD |
- NA |
- 3877_CR_A_0134 |
-
-
- | 288 |
- HB_055_AD |
- AD |
- NA |
- 3893_VC_A_0142 |
-
-
- | 289 |
- HB_068_AD |
- AD |
- NA |
- 4349_VC_A_0148 |
-
-
- | 290 |
- HB_082_AD |
- AD |
- NA |
- 4712_CR_A_0309 |
-
-
- | 291 |
- HB_085_AD |
- AD |
- NA |
- 4726_VC_A_0311 |
-
-
- | 292 |
- HB_087_AD |
- AD |
- NA |
- 4730_CR_A_0315 |
-
-
- | 293 |
- HB_089_AD |
- AD |
- NA |
- 4733_VC_A_0320 |
-
-
- | 294 |
- HB_093_AD |
- AD |
- NA |
- 4749_VC_A_0323 |
-
-
- | 295 |
- HB_095_AD |
- AD |
- NA |
- 4759_CR_A_0327 |
-
-
- | 296 |
- HB_097_AD |
- AD |
- NA |
- 4773_CR_A_0866 |
-
-
- | 297 |
- HB_099_AD |
- AD |
- NA |
- 4785_VC_A_0332 |
-
-
- | 298 |
- HB_100_AD |
- AD |
- NA |
- 4795_VC_A_0335 |
-
-
- | 299 |
- HB_103_AD |
- AD |
- NA |
- 4811_VC_A_0341 |
-
-
- | 300 |
- HB_104_AD |
- AD |
- NA |
- 4813_CR_A_0345 |
-
-
- | 301 |
- HB_112_AD |
- AD |
- NA |
- 4842_VC_A_0870 |
-
-
- | 302 |
- HB_113_AD |
- AD |
- NA |
- 4850_CR_A_0351 |
-
-
- | 303 |
- HB_114_AD |
- AD |
- NA |
- 4852_CR_A_0354 |
-
-
- | 304 |
- HB_117_AD |
- AD |
- NA |
- 4868_VC_A_0874 |
-
-
- | 305 |
- HB_122_AD |
- AD |
- NA |
- 4904_CR_A_1132 |
-
-
- | 306 |
- HB_123_AD |
- AD |
- NA |
- 4905_VC_A_0884 |
-
-
- | 307 |
- HB_124_AD |
- AD |
- NA |
- 4916_VC_A_0886 |
-
-
- | 308 |
- HB_125_AD |
- AD |
- NA |
- 4917_CR_A_0360 |
-
-
- | 309 |
- HB_126_AD |
- AD |
- NA |
- 4921_VC_A_0362 |
-
-
- | 310 |
- HB_128_AD |
- AD |
- NA |
- 4936_CR_A_0369 |
-
-
- | 311 |
- HB_130_AD |
- AD |
- NA |
- 4939_VC_A_0888 |
-
-
- | 312 |
- HB_131_AD |
- AD |
- NA |
- 4944_CR_A_0889 |
-
-
- | 313 |
- HB_132_AD |
- AD |
- NA |
- 4946_CR_A_0372 |
-
-
- | 314 |
- HB_134_AD |
- AD |
- NA |
- 4951_CR_A_0891 |
-
-
- | 315 |
- HB_135_AD |
- AD |
- NA |
- 4953_VC_A_0893 |
-
-
- | 316 |
- HB_136_AD |
- AD |
- NA |
- 4965_VC_A_0160 |
-
-
- | 317 |
- HB_137_AD |
- AD |
- NA |
- 4966_VC_A_0374 |
-
-
- | 318 |
- HB_138_AD |
- AD |
- NA |
- 4969_VC_A_0895 |
-
-
- | 319 |
- HB_140_AD |
- AD |
- NA |
- 4993_CR_A_0896 |
-
-
- | 320 |
- HB_146_AD |
- AD |
- NA |
- 5018_CR_A_0384 |
-
-
- | 321 |
- HB_148_AD |
- AD |
- NA |
- 5022_VC_A_0386 |
-
-
- | 322 |
- HB_150_AD |
- AD |
- NA |
- 5031_VC_A_0392 |
-
-
- | 323 |
- HB_151_AD |
- AD |
- NA |
- 5033_CR_A_0396 |
-
-
- | 324 |
- HB_154_AD |
- AD |
- NA |
- 5048_VC_A_1321 |
-
-
- | 325 |
- HB_155_AD |
- AD |
- NA |
- 5056_VC_A_0398 |
-
-
- | 326 |
- HB_156_AD |
- AD |
- NA |
- 5057_VC_A_0163 |
-
-
- | 327 |
- HB_157_AD |
- AD |
- NA |
- 5059_VC_A_0401 |
-
-
- | 328 |
- HB_158_AD |
- AD |
- NA |
- 5061_PF_A_2612 |
-
-
- | 329 |
- HB_160_AD |
- AD |
- NA |
- 5064_PF_A_2615 |
-
-
- | 330 |
- HB_165_AD |
- AD |
- NA |
- 5092_CR_A_0899 |
-
-
- | 331 |
- HB_168_AD |
- AD |
- NA |
- 5097_VC_A_0407 |
-
-
- | 332 |
- HB_170_AD |
- AD |
- NA |
- 5101_VC_A_0410 |
-
-
- | 333 |
- HB_174_AD |
- AD |
- NA |
- 5124_PF_A_1343 |
-
-
- | 334 |
- HB_179_AD |
- AD |
- NA |
- 5145_VC_A_1351 |
-
-
- | 335 |
- HB_181_AD |
- AD |
- NA |
- 5152_CR_A_0414 |
-
-
- | 336 |
- HB_184_AD |
- AD |
- NA |
- 5166_VC_A_1354 |
-
-
- | 337 |
- HB_194_AD |
- AD |
- NA |
- 5193_VC_A_1360 |
-
-
- | 338 |
- HB_197_AD |
- AD |
- NA |
- 5202_CR_A_1368 |
-
-
- | 339 |
- HB_199_AD |
- AD |
- NA |
- 5205_VC_A_0166 |
-
-
- | 340 |
- HB_200_AD |
- AD |
- NA |
- 5210_VC_A_0905 |
-
-
- | 341 |
- HB_205_AD |
- AD |
- NA |
- 5235_VC_A_0419 |
-
-
- | 342 |
- HB_208_AD |
- AD |
- NA |
- 5249_VC_A_0422 |
-
-
- | 343 |
- HB_209_AD |
- AD |
- NA |
- 5252_VC_A_0907 |
-
-
- | 344 |
- HB_211_AD |
- AD |
- NA |
- 5257_VC_A_0169 |
-
-
- | 345 |
- HB_216_AD |
- AD |
- NA |
- 5272_VC_A_0425 |
-
-
- | 346 |
- HB_219_AD |
- AD |
- NA |
- 5279_CR_A_0147 |
-
-
- | 347 |
- HB_221_AD |
- AD |
- NA |
- 5283_VC_A_0145 |
-
-
- | 348 |
- HB_222_AD |
- AD |
- NA |
- 5285_VC_A_0141 |
-
-
- | 349 |
- HB_224_AD |
- AD |
- NA |
- 5288_VC_A_0428 |
-
-
- | 350 |
- HB_230_AD |
- AD |
- NA |
- 5301_VC_A_0174 |
-
-
- | 351 |
- HB_231_AD |
- AD |
- NA |
- 5305_VC_A_1384 |
-
-
- | 352 |
- HB_232_AD |
- AD |
- NA |
- 5310_CR_A_0176 |
-
-
- | 353 |
- HB_234_AD |
- AD |
- NA |
- 5313_PF_A_2618 |
-
-
- | 354 |
- HB_236_AD |
- AD |
- NA |
- 5317_PF_A_2624 |
-
-
- | 355 |
- HB_238_AD |
- AD |
- NA |
- 5322_CR_A_2632 |
-
-
- | 356 |
- HB_240_AD |
- AD |
- NA |
- 5325_VC_A_0137 |
-
-
- | 357 |
- HB_244_AD |
- AD |
- NA |
- 5337_VC_A_1387 |
-
-
- | 358 |
- HB_245_AD |
- AD |
- NA |
- 5339_VC_A_0181 |
-
-
- | 359 |
- HB_250_AD |
- AD |
- NA |
- 5346_VC_A_1393 |
-
-
- | 360 |
- HB_251_AD |
- AD |
- NA |
- 5350_VC_A_0184 |
-
-
- | 361 |
- HB_252_AD |
- AD |
- NA |
- 5355_VC_A_0133 |
-
-
- | 362 |
- HB_253_AD |
- AD |
- NA |
- 5359_CR_A_1395 |
-
-
- | 363 |
- HB_258_AD |
- AD |
- NA |
- 5370_PF_A_1400 |
-
-
- | 364 |
- HB_259_AD |
- AD |
- NA |
- 5371_PF_A_2636 |
-
-
- | 365 |
- HB_260_AD |
- AD |
- NA |
- 5375_VC_A_0188 |
-
-
- | 366 |
- HB_263_AD |
- AD |
- NA |
- 5381_VC_A_0022 |
-
-
- | 367 |
- HB_265_AD |
- AD |
- NA |
- 5385_VC_A_1402 |
-
-
- | 368 |
- HB_267_AD |
- AD |
- NA |
- 5389_VC_A_0928 |
-
-
- | 369 |
- HB_268_AD |
- AD |
- NA |
- 5390_CR_A_0151 |
-
-
- | 370 |
- HB_273_AD |
- AD |
- NA |
- 5400_PF_A_2645 |
-
-
- | 371 |
- HB_274_AD |
- AD |
- NA |
- 5401_VC_A_0931 |
-
-
- | 372 |
- HB_275_AD |
- AD |
- NA |
- 5404_PF_A_2648 |
-
-
- | 373 |
- HB_276_AD |
- AD |
- NA |
- 5406_VC_A_0933 |
-
-
- | 374 |
- HB_277_AD |
- AD |
- NA |
- 5407_PF_A_2651 |
-
-
- | 375 |
- HB_280_AD |
- AD |
- NA |
- 5412_VC_A_0935 |
-
-
- | 376 |
- HB_281_AD |
- AD |
- NA |
- 5413_PF_A_2657 |
-
-
- | 377 |
- HB_283_AD |
- AD |
- NA |
- 5419_VC_A_0937 |
-
-
- | 378 |
- HB_284_AD |
- AD |
- NA |
- 5420_VC_A_0939 |
-
-
- | 379 |
- HB_285_AD |
- AD |
- NA |
- 5421_CR_A_0432 |
-
-
- | 380 |
- HB_286_AD |
- AD |
- NA |
- 5423_PF_A_2660 |
-
-
- | 381 |
- HB_288_AD |
- AD |
- NA |
- 5425_PF_A_2666 |
-
-
- | 382 |
- HB_289_AD |
- AD |
- NA |
- 5426_VC_A_1405 |
-
-
- | 383 |
- HB_290_AD |
- AD |
- NA |
- 5433_VC_A_0434 |
-
-
- | 384 |
- HB_296_AD |
- AD |
- NA |
- 5456_PF_A_2675 |
-
-
- | 385 |
- HB_299_AD |
- AD |
- NA |
- 5461_VC_A_0192 |
-
-
- | 386 |
- HB_302_AD |
- AD |
- NA |
- 5465_PF_A_2678 |
-
-
- | 387 |
- HB_303_AD |
- AD |
- NA |
- 5469_VC_A_1417 |
-
-
- | 388 |
- HB_305_AD |
- AD |
- NA |
- 5479_PF_A_1421 |
-
-
- | 389 |
- HB_306_AD |
- AD |
- NA |
- 5480_VC_A_0437 |
-
-
- | 390 |
- HB_307_AD |
- AD |
- NA |
- 5482_VC_A_0028 |
-
-
- | 391 |
- HB_308_AD |
- AD |
- NA |
- 5483_VC_A_0941 |
-
-
- | 392 |
- HB_309_AD |
- AD |
- NA |
- 5487_CR_A_0441 |
-
-
- | 393 |
- HB_310_AD |
- AD |
- NA |
- 5488_CR_A_0194 |
-
-
- | 394 |
- HB_312_AD |
- AD |
- NA |
- 5500_VC_A_0198 |
-
-
- | 395 |
- HB_313_AD |
- AD |
- NA |
- 5502_PF_A_2684 |
-
-
- | 396 |
- HB_315_AD |
- AD |
- NA |
- 5513_PF_A_2687 |
-
-
- | 397 |
- HB_316_AD |
- AD |
- NA |
- 5516_PF_A_2690 |
-
-
- | 398 |
- HB_317_AD |
- AD |
- NA |
- 5517_PF_A_2693 |
-
-
- | 399 |
- HB_318_AD |
- AD |
- NA |
- 5518_CR_A_0030 |
-
-
- | 400 |
- HB_319_AD |
- AD |
- NA |
- 5519_CR_A_2695 |
-
-
- | 401 |
- HB_320_AD |
- AD |
- NA |
- 5520_PF_A_2699 |
-
-
- | 402 |
- HB_322_AD |
- AD |
- NA |
- 5527_VC_A_0945 |
-
-
- | 403 |
- HB_325_AD |
- AD |
- NA |
- 5532_PF_A_2702 |
-
-
- | 404 |
- HB_328_AD |
- AD |
- NA |
- 5541_PF_A_2705 |
-
-
- | 405 |
- HB_330_AD |
- AD |
- NA |
- 5544_VC_A_0201 |
-
-
- | 406 |
- HB_334_AD |
- AD |
- NA |
- 5554_VC_A_0452 |
-
-
- | 407 |
- HB_335_AD |
- AD |
- NA |
- 5557_VC_A_0950 |
-
-
- | 408 |
- HB_337_AD |
- AD |
- NA |
- 5560_VC_A_0204 |
-
-
- | 409 |
- HB_342_AD |
- AD |
- NA |
- 5571_PF_A_1430 |
-
-
- | 410 |
- HB_345_AD |
- AD |
- NA |
- 5583_PF_A_2708 |
-
-
- | 411 |
- HB_347_AD |
- AD |
- NA |
- 5589_PF_A_2714 |
-
-
- | 412 |
- HB_349_AD |
- AD |
- NA |
- 5592_PF_A_2717 |
-
-
- | 413 |
- HB_352_AD |
- AD |
- NA |
- 5604_VC_A_0037 |
-
-
- | 414 |
- HB_353_AD |
- AD |
- NA |
- 5607_PF_A_2723 |
-
-
- | 415 |
- HB_356_AD |
- AD |
- NA |
- 5615_VC_A_0041 |
-
-
- | 416 |
- HB_357_AD |
- AD |
- NA |
- 5616_CR_A_0127 |
-
-
- | 417 |
- HB_358_AD |
- AD |
- NA |
- 5617_CR_A_0456 |
-
-
- | 418 |
- HB_359_AD |
- AD |
- NA |
- 5618_CR_A_0044 |
-
-
- | 419 |
- HB_362_AD |
- AD |
- NA |
- 5625_CR_A_2495 |
-
-
- | 420 |
- HB_363_AD |
- AD |
- NA |
- 5626_CR_A_2498 |
-
-
- | 421 |
- HB_364_AD |
- AD |
- NA |
- 5629_CR_A_0390 |
-
-
- | 422 |
- HB_369_AD |
- AD |
- NA |
- 5643_VC_A_1143 |
-
-
- | 423 |
- HB_373_AD |
- AD |
- NA |
- 5654_VC_A_0047 |
-
-
- | 424 |
- HB_375_AD |
- AD |
- NA |
- 5660_CR_A_0462 |
-
-
- | 425 |
- HB_376_AD |
- AD |
- NA |
- 5661_VC_A_0464 |
-
-
- | 426 |
- HB_377_AD |
- AD |
- NA |
- 5667_VC_A_2509 |
-
-
- | 427 |
- HB_378_AD |
- AD |
- NA |
- 5668_VC_A_1438 |
-
-
- | 428 |
- HB_383_AD |
- AD |
- NA |
- 5686_CR_A_2728 |
-
-
- | 429 |
- HB_386_AD |
- AD |
- NA |
- 5695_VC_A_0953 |
-
-
- | 430 |
- HB_389_AD |
- AD |
- NA |
- 5700_VC_A_2514 |
-
-
- | 431 |
- HB_391_AD |
- AD |
- NA |
- 5705_CR_A_0474 |
-
-
- | 432 |
- HB_392_AD |
- AD |
- NA |
- 5706_VC_A_0476 |
-
-
- | 433 |
- HB_394_AD |
- AD |
- NA |
- 5713_VC_A_0479 |
-
-
- | 434 |
- HB_397_AD |
- AD |
- NA |
- 5721_CR_A_0210 |
-
-
- | 435 |
- HB_404_AD |
- AD |
- NA |
- 5735_CR_A_0489 |
-
-
- | 436 |
- HB_406_AD |
- AD |
- NA |
- 5744_CR_A_0960 |
-
-
- | 437 |
- HB_409_AD |
- AD |
- NA |
- 5749_CR_A_0159 |
-
-
- | 438 |
- HB_410_AD |
- AD |
- NA |
- 5751_CR_A_2518 |
-
-
- | 439 |
- HB_411_AD |
- AD |
- NA |
- 5755_CR_A_2731 |
-
-
- | 440 |
- HB_413_AD |
- AD |
- NA |
- 5766_VC_A_0214 |
-
-
- | 441 |
- HB_419_AD |
- AD |
- NA |
- 5790_VC_A_0217 |
-
-
- | 442 |
- HB_420_AD |
- AD |
- NA |
- 5796_CR_A_0964 |
-
-
- | 443 |
- HB_428_AD |
- AD |
- NA |
- 5811_CR_A_2524 |
-
-
- | 444 |
- HB_429_AD |
- AD |
- NA |
- 5819_CR_A_2527 |
-
-
- | 445 |
- HB_430_AD |
- AD |
- NA |
- 5822_CR_A_2530 |
-
-
- | 446 |
- HB_434_AD |
- AD |
- NA |
- 5828_CR_A_2533 |
-
-
- | 447 |
- HB_435_AD |
- AD |
- NA |
- 5831_CR_A_0222 |
-
-
- | 448 |
- HB_437_AD |
- AD |
- NA |
- 5839_CR_A_2539 |
-
-
- | 449 |
- HB_438_AD |
- AD |
- NA |
- 5843_CR_A_0227 |
-
-
- | 450 |
- HB_439_AD |
- AD |
- NA |
- 5845_CR_A_0230 |
-
-
- | 451 |
- HB_441_AD |
- AD |
- NA |
- 5849_CR_A_0233 |
-
-
- | 452 |
- HB_442_AD |
- AD |
- NA |
- 5850_CR_A_0495 |
-
-
- | 453 |
- HB_445_AD |
- AD |
- NA |
- 5858_CR_A_0969 |
-
-
- | 454 |
- HB_448_AD |
- AD |
- NA |
- 5864_CR_A_0974 |
-
-
- | 455 |
- HB_451_AD |
- AD |
- NA |
- 5871_CR_A_2542 |
-
-
- | 456 |
- HB_454_AD |
- AD |
- NA |
- 5879_CR_A_2545 |
-
-
- | 457 |
- HB_455_AD |
- AD |
- NA |
- 5887_CR_A_0976_Bis |
-
-
- | 458 |
- HB_459_AD |
- AD |
- NA |
- 5898_CR_A_2548 |
-
-
- | 459 |
- HB_460_AD |
- AD |
- NA |
- 5900_VC_A_0237 |
-
-
- | 460 |
- HB_461_AD |
- AD |
- NA |
- 5901_CR_A_0239 |
-
-
- | 461 |
- HB_469_AD |
- AD |
- NA |
- 5914_CR_A_2554 |
-
-
- | 462 |
- HB_471_AD |
- AD |
- NA |
- 5922_VC_A_0246 |
-
-
- | 463 |
- HB_473_AD |
- AD |
- NA |
- 5927_CR_A_2560 |
-
-
- | 464 |
- HB_474_AD |
- AD |
- NA |
- 5933_VC_A_1071 |
-
-
- | 465 |
- HB_477_AD |
- AD |
- NA |
- 5939_CR_A_1151 |
-
-
- | 466 |
- HB_479_AD |
- AD |
- NA |
- 5945_VC_A_0983 |
-
-
- | 467 |
- HB_484_AD |
- AD |
- NA |
- 5956_CR_A_0123 |
-
-
- | 468 |
- HB_489_AD |
- AD |
- NA |
- 5968_VC_A_1075 |
-
-
- | 469 |
- HB_491_AD |
- AD |
- NA |
- 5971_CR_A_0119 |
-
-
- | 470 |
- HB_492_AD |
- AD |
- NA |
- 5972_VC_A_0251 |
-
-
- | 471 |
- HB_494_AD |
- AD |
- NA |
- 5979_CR_A_0115 |
-
-
- | 472 |
- HB_498_AD |
- AD |
- NA |
- 5988_VC_A_0503 |
-
-
- | 473 |
- HB_502_AD |
- AD |
- NA |
- 5994_PF_A_1605 |
-
-
- | 474 |
- HB_503_AD |
- AD |
- NA |
- 5995_CR_A_2563 |
-
-
- | 475 |
- HB_510_AD |
- AD |
- NA |
- 6017_CR_A_0048 |
-
-
- | 476 |
- HB_514_AD |
- AD |
- NA |
- 6025_VC_A_0506 |
-
-
- | 477 |
- HB_517_AD |
- AD |
- NA |
- 6031_VC_A_0258 |
-
-
- | 478 |
- HB_520_AD |
- AD |
- NA |
- 6035_VC_A_1621 |
-
-
- | 479 |
- HB_523_AD |
- AD |
- NA |
- 6038_VC_A_0261 |
-
-
- | 480 |
- HB_524_AD |
- AD |
- NA |
- 6042_VC_A_1156 |
-
-
- | 481 |
- HB_525_AD |
- AD |
- NA |
- 6044_VC_A_0264 |
-
-
- | 482 |
- HB_531_AD |
- AD |
- NA |
- 6056_CR_A_0999 |
-
-
- | 483 |
- HB_533_AD |
- AD |
- NA |
- 6061_PF_A_1650 |
-
-
- | 484 |
- HB_534_AD |
- AD |
- NA |
- 6066_VC_A_0270 |
-
-
- | 485 |
- HB_535_AD |
- AD |
- NA |
- 6067_PF_A_1452 |
-
-
- | 486 |
- HB_536_AD |
- AD |
- NA |
- 6068_VC_A_0273 |
-
-
- | 487 |
- HB_545_AD |
- AD |
- NA |
- 6102_CR_A_1661 |
-
-
- | 488 |
- HB_546_AD |
- AD |
- NA |
- 6107_CR_A_0055 |
-
-
- | 489 |
- HB_550_AD |
- AD |
- NA |
- 6120_VC_A_0058 |
-
-
- | 490 |
- HB_552_AD |
- AD |
- NA |
- 6126_VC_A_1675 |
-
-
- | 491 |
- HB_553_AD |
- AD |
- NA |
- 6129_PF_A_0274 |
-
-
- | 492 |
- HB_554_AD |
- AD |
- NA |
- 6130_VC_A_1678 |
-
-
- | 493 |
- HB_555_AD |
- AD |
- NA |
- 6131_CR_A_0510 |
-
-
- | 494 |
- HB_556_AD |
- AD |
- NA |
- 6132_CR_A_0513 |
-
-
- | 495 |
- HB_558_AD |
- AD |
- NA |
- 6137_VC_A_1681 |
-
-
- | 496 |
- HB_564_AD |
- AD |
- NA |
- 6153_VC_A_1465 |
-
-
- | 497 |
- HB_565_AD |
- AD |
- NA |
- 6154_VC_A_1468 |
-
-
- | 498 |
- HB_566_AD |
- AD |
- NA |
- 6157_VC_A_0062 |
-
-
- | 499 |
- HB_568_AD |
- AD |
- NA |
- 6164_CR_A_1005 |
-
-
- | 500 |
- HB_571_AD |
- AD |
- NA |
- 6171_CR_A_0065 |
-
-
- | 501 |
- HB_573_AD |
- AD |
- NA |
- 6174_VC_A_0068 |
-
-
- | 502 |
- HB_576_AD |
- AD |
- NA |
- 6180_CR_A_0281 |
-
-
- | 503 |
- HB_583_AD |
- AD |
- NA |
- 6194_VC_A_0071 |
-
-
- | 504 |
- HB_585_AD |
- AD |
- NA |
- 6198_VC_A_0073 |
-
-
- | 505 |
- HB_590_AD |
- AD |
- NA |
- 6215_VC_A_0518 |
-
-
- | 506 |
- HB_591_AD |
- AD |
- NA |
- 6216_VC_A_1476 |
-
-
- | 507 |
- HB_592_AD |
- AD |
- NA |
- 6218_CR_A_0522 |
-
-
- | 508 |
- HB_594_AD |
- AD |
- NA |
- 6223_VC_A_0288 |
-
-
- | 509 |
- HB_596_AD |
- AD |
- NA |
- 6226_CR_A_0076 |
-
-
- | 510 |
- HB_597_AD |
- AD |
- NA |
- 6227_VC_A_0080 |
-
-
- | 511 |
- HB_598_AD |
- AD |
- NA |
- 6231_VC_A_1479 |
-
-
- | 512 |
- HB_605_AD |
- AD |
- NA |
- 6261_VC_A_0084 |
-
-
- | 513 |
- HB_608_AD |
- AD |
- NA |
- 6268_CR_A_0525 |
-
-
- | 514 |
- HB_611_AD |
- AD |
- NA |
- 6279_VC_A_0089 |
-
-
- | 515 |
- HB_612_AD |
- AD |
- NA |
- 6280_VC_A_0091 |
-
-
- | 516 |
- HB_613_AD |
- AD |
- NA |
- 6281_CR_A_0528 |
-
-
- | 517 |
- HB_621_AD |
- AD |
- NA |
- 6308_VC_A_1503 |
-
-
- | 518 |
- HB_623_AD |
- AD |
- NA |
- 6311_CR_A_0531 |
-
-
- | 519 |
- HB_624_AD |
- AD |
- NA |
- 6312_CR_A_0534 |
-
-
- | 520 |
- HB_630_AD |
- AD |
- NA |
- 6324_PF_A_1514 |
-
-
- | 521 |
- HB_633_AD |
- AD |
- NA |
- 6332_VC_A_1518 |
-
-
- | 522 |
- HB_634_AD |
- AD |
- NA |
- 6335_VC_A_0536 |
-
-
- | 523 |
- HB_635_AD |
- AD |
- NA |
- 6336_CR_A_0290 |
-
-
- | 524 |
- HB_636_AD |
- AD |
- NA |
- 6338_VC_A_0539 |
-
-
- | 525 |
- HB_642_AD |
- AD |
- NA |
- 6358_VC_A_0545 |
-
-
- | 526 |
- HB_652_AD |
- AD |
- NA |
- 6387_VC_A_0093 |
-
-
- | 527 |
- HB_657_AD |
- AD |
- NA |
- 6394_VC_A_0551 |
-
-
- | 528 |
- HB_664_AD |
- AD |
- NA |
- 6416_VC_A_1095 |
-
-
- | 529 |
- HB_666_AD |
- AD |
- NA |
- 6422_CR_A_0555 |
-
-
- | 530 |
- HB_669_AD |
- AD |
- NA |
- 6431_VC_A_0294 |
-
-
- | 531 |
- HB_674_AD |
- AD |
- NA |
- 6449_VC_A_1183 |
-
-
- | 532 |
- HB_680_AD |
- AD |
- NA |
- 6458_CR_A_2570 |
-
-
- | 533 |
- HB_685_AD |
- AD |
- NA |
- 6481_VC_A_0560 |
-
-
- | 534 |
- HB_690_AD |
- AD |
- NA |
- 6489_CR_A_0100 |
-
-
- | 535 |
- HB_696_AD |
- AD |
- NA |
- 6511_VC_A_1119 |
-
-
- | 536 |
- HB_698_AD |
- AD |
- NA |
- 6515_CR_A_0564 |
-
-
- | 537 |
- HB_699_AD |
- AD |
- NA |
- 6518_VC_A_0103 |
-
-
- | 538 |
- HB_703_AD |
- AD |
- NA |
- 6523_VC_A_0107 |
-
-
- | 539 |
- HB_704_AD |
- AD |
- NA |
- 6530_VC_A_0112 |
-
-
- | 540 |
- HB_706_AD |
- AD |
- NA |
- 6534_VC_A_0306 |
-
-
- | 541 |
- HB_712_AD |
- AD |
- NA |
- 6546_PF_A_1194 |
-
-
- | 542 |
- HB_713_AD |
- AD |
- NA |
- 6548_PF_A_1541 |
-
-
- | 543 |
- HB_715_AD |
- AD |
- NA |
- 6550_VC_A_1201 |
-
-
- | 544 |
- HB_718_AD |
- AD |
- NA |
- 6554_PF_A_1203 |
-
-
- | 545 |
- HB_720_AD |
- AD |
- NA |
- 6559_PF_A_2287 |
-
-
- | 546 |
- HB_722_AD |
- AD |
- NA |
- 6561_CR_A_2582 |
-
-
- | 547 |
- HB_723_AD |
- AD |
- NA |
- 6562_PF_A_2290 |
-
-
- | 548 |
- HB_724_AD |
- AD |
- NA |
- 6564_CR_A_2585 |
-
-
- | 549 |
- HB_727_AD |
- AD |
- NA |
- 6575_CR_A_2298 |
-
-
- | 550 |
- HB_728_AD |
- AD |
- NA |
- 6577_PF_A_2299 |
-
-
- | 551 |
- HB_729_AD |
- AD |
- NA |
- 6578_PF_A_2302 |
-
-
- | 552 |
- HB_731_AD |
- AD |
- NA |
- 6582_VC_A_1207 |
-
-
- | 553 |
- HB_733_AD |
- AD |
- NA |
- 6585_VC_A_1210 |
-
-
- | 554 |
- HB_736_AD |
- AD |
- NA |
- 6590_PF_A_1215 |
-
-
- | 555 |
- HB_743_AD |
- AD |
- NA |
- 6603_PF_A_1448 |
-
-
- | 556 |
- HB_745_AD |
- AD |
- NA |
- 6610_PF_A_1227 |
-
-
- | 557 |
- HB_746_AD |
- AD |
- NA |
- 6612_PF_A_2308 |
-
-
- | 558 |
- HB_749_AD |
- AD |
- NA |
- 6617_VC_A_2587 |
-
-
- | 559 |
- HB_751_AD |
- AD |
- NA |
- 6629_VC_A_2330 |
-
-
- | 560 |
- HB_752_AD |
- AD |
- NA |
- 6630_VC_A_2590 |
-
-
- | 561 |
- HB_753_AD |
- AD |
- NA |
- 6632_PF_A_2332 |
-
-
- | 562 |
- HB_754_AD |
- AD |
- NA |
- 6637_VC_A_2596 |
-
-
- | 563 |
- HB_755_AD |
- AD |
- NA |
- 6638_VC_A_2599 |
-
-
- | 564 |
- HB_756_AD |
- AD |
- NA |
- 6639_VC_A_2336 |
-
-
- | 565 |
- HB_757_AD |
- AD |
- NA |
- 6641_PF_A_2338 |
-
-
- | 566 |
- HB_763_AD |
- AD |
- NA |
- 6654_VC_A_1237 |
-
-
- | 567 |
- HB_773_AD |
- AD |
- NA |
- 6681_VC_A_1252 |
-
-
- | 568 |
- HB_775_AD |
- AD |
- NA |
- 6693_VC_A_2348 |
-
-
- | 569 |
- HB_776_AD |
- AD |
- NA |
- 6694_VC_A_2351 |
-
-
- | 570 |
- HB_777_AD |
- AD |
- NA |
- 6695_PF_A_2353 |
-
-
- | 571 |
- HB_779_AD |
- AD |
- NA |
- 6699_PF_A_2359 |
-
-
- | 572 |
- HB_781_AD |
- AD |
- NA |
- 6708_VC_A_2366 |
-
-
- | 573 |
- HB_782_AD |
- AD |
- NA |
- 6776_PF_A_2607 |
-
-
- | 574 |
- HB_783_AD |
- AD |
- NA |
- 6778_PF_A_2368 |
-
-
- | 575 |
- HB_784_AD |
- AD |
- NA |
- 6779_PF_A_2371 |
-
-
- | 576 |
- HB_785_AD |
- AD |
- NA |
- 6780_PF_A_2374 |
-
-
- | 577 |
- HB_786_AD |
- AD |
- NA |
- 6782_PF_A_2377 |
-
-
- | 578 |
- HB_787_AD |
- AD |
- NA |
- 6784_PF_A_2380 |
-
-
- | 579 |
- HB_788_AD |
- AD |
- NA |
- 6785_CR_A_2385 |
-
-
- | 580 |
- HB_789_AD |
- AD |
- NA |
- 6787_CR_A_2388 |
-
-
- | 581 |
- HB_791_AD |
- AD |
- NA |
- 6790_PF_A_2392 |
-
-
- | 582 |
- HB_792_AD |
- AD |
- NA |
- 6791_PF_A_2395 |
-
-
- | 583 |
- HB_793_AD |
- AD |
- NA |
- 6793_PF_A_2398 |
-
-
- | 584 |
- HB_794_AD |
- AD |
- NA |
- 6794_PF_A_2401 |
-
-
- | 585 |
- HB_795_AD |
- AD |
- NA |
- 6797_PF_A_2404 |
-
-
- | 586 |
- HB_796_AD |
- AD |
- NA |
- 6798_PF_A_2407 |
-
-
- | 587 |
- HB_797_AD |
- AD |
- NA |
- 6799_VC_A_2411 |
-
-
- | 588 |
- HB_798_AD |
- AD |
- NA |
- 6801_VC_A_2414 |
-
-
- | 589 |
- HB_799_AD |
- AD |
- NA |
- 6803_VC_A_2417 |
-
-
- | 590 |
- HB_801_AD |
- AD |
- NA |
- 6809_PF_A_2422 |
-
-
- | 591 |
- HB_803_AD |
- AD |
- NA |
- 6818_CR_A_2430 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/HBTRC_MLVC_0611/notes.rtf b/general/datasets/HBTRC_MLVC_0611/notes.rtf
deleted file mode 100644
index ff90e34..0000000
--- a/general/datasets/HBTRC_MLVC_0611/notes.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Species: Human
-Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
-Disease: Neurological Disease
-Investigator: Francine Benes/ Eric Schadt
-Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
-Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC_MLVC_0611/summary.rtf b/general/datasets/HBTRC_MLVC_0611/summary.rtf
deleted file mode 100644
index 5cde3bf..0000000
--- a/general/datasets/HBTRC_MLVC_0611/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC_MLVC_AD_0611/acknowledgment.rtf b/general/datasets/HBTRC_MLVC_AD_0611/acknowledgment.rtf
deleted file mode 100644
index 208cb6e..0000000
--- a/general/datasets/HBTRC_MLVC_AD_0611/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC_MLVC_AD_0611/cases.rtf b/general/datasets/HBTRC_MLVC_AD_0611/cases.rtf
deleted file mode 100644
index 86ed08e..0000000
--- a/general/datasets/HBTRC_MLVC_AD_0611/cases.rtf
+++ /dev/null
@@ -1,4166 +0,0 @@
-This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- | Series |
- Cerebellum in GN |
- Condition |
- Gender |
- BioSample Name |
-
-
- | 1 |
- HB_029_N |
- N |
- NA |
- 3405_VC_N_0859 |
-
-
- | 2 |
- HB_058_N |
- N |
- NA |
- 4021_VC_N_0854 |
-
-
- | 3 |
- HB_064_N |
- N |
- NA |
- 4338_VC_N_0861 |
-
-
- | 4 |
- HB_086_N |
- N |
- NA |
- 4729_PF_N_0756 |
-
-
- | 5 |
- HB_091_N |
- N |
- NA |
- 4741_VC_N_0864 |
-
-
- | 6 |
- HB_092_N |
- N |
- NA |
- 4744_VC_N_0865 |
-
-
- | 7 |
- HB_102_N |
- N |
- NA |
- 4810_VC_N_0869 |
-
-
- | 8 |
- HB_119_N |
- N |
- NA |
- 4872_VC_N_0878 |
-
-
- | 9 |
- HB_147_N |
- N |
- NA |
- 5021_VC_N_0852 |
-
-
- | 10 |
- HB_161_N |
- N |
- NA |
- 5077_VC_N_0851 |
-
-
- | 11 |
- HB_162_N |
- N |
- NA |
- 5081_VC_N_1021 |
-
-
- | 12 |
- HB_166_N |
- N |
- NA |
- 5095_VC_N_1024 |
-
-
- | 13 |
- HB_183_N |
- N |
- NA |
- 5162_VC_N_0850 |
-
-
- | 14 |
- HB_206_N |
- N |
- NA |
- 5245_VC_N_0849 |
-
-
- | 15 |
- HB_215_N |
- N |
- NA |
- 5270_VC_N_0848 |
-
-
- | 16 |
- HB_218_N |
- N |
- NA |
- 5276_CR_N_0912 |
-
-
- | 17 |
- HB_223_N |
- N |
- NA |
- 5287_VC_N_0916 |
-
-
- | 18 |
- HB_226_N |
- N |
- NA |
- 5294_VC_N_0919 |
-
-
- | 19 |
- HB_241_N |
- N |
- NA |
- 5326_CR_N_0652 |
-
-
- | 20 |
- HB_243_N |
- N |
- NA |
- 5333_VC_N_1262 |
-
-
- | 21 |
- HB_247_N |
- N |
- NA |
- 5341_VC_N_0923 |
-
-
- | 22 |
- HB_257_N |
- N |
- NA |
- 5368_PF_N_1032 |
-
-
- | 23 |
- HB_264_N |
- N |
- NA |
- 5384_VC_N_0924 |
-
-
- | 24 |
- HB_295_N |
- N |
- NA |
- 5452_VC_N_1268 |
-
-
- | 25 |
- HB_300_N |
- N |
- NA |
- 5463_VC_N_0845 |
-
-
- | 26 |
- HB_311_N |
- N |
- NA |
- 5489_CR_N_0942 |
-
-
- | 27 |
- HB_324_N |
- N |
- NA |
- 5531_VC_N_0844 |
-
-
- | 28 |
- HB_332_N |
- N |
- NA |
- 5547_VC_N_0843 |
-
-
- | 29 |
- HB_340_N |
- N |
- NA |
- 5568_VC_N_0842 |
-
-
- | 30 |
- HB_360_N |
- N |
- NA |
- 5619_CR_N_0645 |
-
-
- | 31 |
- HB_365_N |
- N |
- NA |
- 5632_VC_N_0838 |
-
-
- | 32 |
- HB_367_N |
- N |
- NA |
- 5637_VC_N_0837 |
-
-
- | 33 |
- HB_382_N |
- N |
- NA |
- 5684_PF_N_1270 |
-
-
- | 34 |
- HB_396_N |
- N |
- NA |
- 5718_VC_N_0956 |
-
-
- | 35 |
- HB_398_N |
- N |
- NA |
- 5722_VC_N_1044 |
-
-
- | 36 |
- HB_400_N |
- N |
- NA |
- 5726_VC_N_0834_Bis |
-
-
- | 37 |
- HB_403_N |
- N |
- NA |
- 5734_VC_N_0833 |
-
-
- | 38 |
- HB_414_N |
- N |
- NA |
- 5772_VC_N_0832_Bis |
-
-
- | 39 |
- HB_416_N |
- N |
- NA |
- 5778_CR_N_0962 |
-
-
- | 40 |
- HB_418_N |
- N |
- NA |
- 5789_PF_N_1273 |
-
-
- | 41 |
- HB_421_N |
- N |
- NA |
- 5799_VC_N_1058 |
-
-
- | 42 |
- HB_423_N |
- N |
- NA |
- 5803_VC_N_0966 |
-
-
- | 43 |
- HB_426_N |
- N |
- NA |
- 5806_PF_N_1064 |
-
-
- | 44 |
- HB_427_N |
- N |
- NA |
- 5810_CR_N_0636 |
-
-
- | 45 |
- HB_431_N |
- N |
- NA |
- 5823_VC_N_0829 |
-
-
- | 46 |
- HB_432_N |
- N |
- NA |
- 5826_VC_N_0828 |
-
-
- | 47 |
- HB_433_N |
- N |
- NA |
- 5827_VC_N_0827 |
-
-
- | 48 |
- HB_436_N |
- N |
- NA |
- 5832_PF_N_1145 |
-
-
- | 49 |
- HB_443_N |
- N |
- NA |
- 5852_VC_N_0826 |
-
-
- | 50 |
- HB_446_N |
- N |
- NA |
- 5859_VC_N_0825 |
-
-
- | 51 |
- HB_449_N |
- N |
- NA |
- 5866_VC_N_0824 |
-
-
- | 52 |
- HB_450_N |
- N |
- NA |
- 5867_VC_N_1277 |
-
-
- | 53 |
- HB_453_N |
- N |
- NA |
- 5876_VC_N_0823 |
-
-
- | 54 |
- HB_462_N |
- N |
- NA |
- 5903_VC_N_0822 |
-
-
- | 55 |
- HB_464_N |
- N |
- NA |
- 5905_VC_N_0820 |
-
-
- | 56 |
- HB_468_N |
- N |
- NA |
- 5912_VC_N_1286 |
-
-
- | 57 |
- HB_472_N |
- N |
- NA |
- 5925_VC_N_1289 |
-
-
- | 58 |
- HB_475_N |
- N |
- NA |
- 5936_VC_N_0979 |
-
-
- | 59 |
- HB_476_N |
- N |
- NA |
- 5938_VC_N_0819 |
-
-
- | 60 |
- HB_480_N |
- N |
- NA |
- 5946_VC_N_0985 |
-
-
- | 61 |
- HB_485_N |
- N |
- NA |
- 5959_VC_N_0818 |
-
-
- | 62 |
- HB_486_N |
- N |
- NA |
- 5963_VC_N_0987 |
-
-
- | 63 |
- HB_495_N |
- N |
- NA |
- 5980_VC_N_0989 |
-
-
- | 64 |
- HB_497_N |
- N |
- NA |
- 5985_VC_N_0990 |
-
-
- | 65 |
- HB_500_N |
- N |
- NA |
- 5990_VC_N_0817 |
-
-
- | 66 |
- HB_501_N |
- N |
- NA |
- 5991_VC_N_0816 |
-
-
- | 67 |
- HB_504_N |
- N |
- NA |
- 5996_VC_N_0815 |
-
-
- | 68 |
- HB_505_N |
- N |
- NA |
- 5998_VC_N_0814 |
-
-
- | 69 |
- HB_507_N |
- N |
- NA |
- 6006_VC_N_0813 |
-
-
- | 70 |
- HB_508_N |
- N |
- NA |
- 6007_CR_N_0618 |
-
-
- | 71 |
- HB_509_N |
- N |
- NA |
- 6008_PF_N_1081 |
-
-
- | 72 |
- HB_512_N |
- N |
- NA |
- 6023_PF_N_1155 |
-
-
- | 73 |
- HB_516_N |
- N |
- NA |
- 6030_VC_N_0810 |
-
-
- | 74 |
- HB_519_N |
- N |
- NA |
- 6034_VC_N_0809 |
-
-
- | 75 |
- HB_532_N |
- N |
- NA |
- 6060_VC_N_1292 |
-
-
- | 76 |
- HB_541_N |
- N |
- NA |
- 6092_VC_N_1001 |
-
-
- | 77 |
- HB_542_N |
- N |
- NA |
- 6096_VC_N_0807 |
-
-
- | 78 |
- HB_544_N |
- N |
- NA |
- 6101_CR_N_1161 |
-
-
- | 79 |
- HB_547_N |
- N |
- NA |
- 6110_VC_N_1295 |
-
-
- | 80 |
- HB_551_N |
- N |
- NA |
- 6124_VC_N_0806 |
-
-
- | 81 |
- HB_557_N |
- N |
- NA |
- 6134_PF_N_1297 |
-
-
- | 82 |
- HB_560_N |
- N |
- NA |
- 6142_VC_N_0805 |
-
-
- | 83 |
- HB_569_N |
- N |
- NA |
- 6166_VC_N_0804 |
-
-
- | 84 |
- HB_570_N |
- N |
- NA |
- 6170_VC_N_0803 |
-
-
- | 85 |
- HB_572_N |
- N |
- NA |
- 6172_VC_N_1008 |
-
-
- | 86 |
- HB_577_N |
- N |
- NA |
- 6182_VC_N_1166 |
-
-
- | 87 |
- HB_579_N |
- N |
- NA |
- 6187_CR_N_0607 |
-
-
- | 88 |
- HB_581_N |
- N |
- NA |
- 6191_VC_N_1010 |
-
-
- | 89 |
- HB_584_N |
- N |
- NA |
- 6196_CR_N_0605 |
-
-
- | 90 |
- HB_586_N |
- N |
- NA |
- 6200_VC_N_0799 |
-
-
- | 91 |
- HB_587_N |
- N |
- NA |
- 6206_PF_N_1176 |
-
-
- | 92 |
- HB_589_N |
- N |
- NA |
- 6213_VC_N_0798 |
-
-
- | 93 |
- HB_601_N |
- N |
- NA |
- 6241_VC_N_0796 |
-
-
- | 94 |
- HB_604_N |
- N |
- NA |
- 6260_VC_N_0794 |
-
-
- | 95 |
- HB_609_N |
- N |
- NA |
- 6270_VC_N_0793 |
-
-
- | 96 |
- HB_618_N |
- N |
- NA |
- 6289_VC_N_0791 |
-
-
- | 97 |
- HB_622_N |
- N |
- NA |
- 6310_VC_N_0790 |
-
-
- | 98 |
- HB_625_N |
- N |
- NA |
- 6314_VC_N_0789 |
-
-
- | 99 |
- HB_637_N |
- N |
- NA |
- 6340_VC_N_0786 |
-
-
- | 100 |
- HB_638_N |
- N |
- NA |
- 6341_VC_N_0785 |
-
-
- | 101 |
- HB_640_N |
- N |
- NA |
- 6347_VC_N_0784 |
-
-
- | 102 |
- HB_641_N |
- N |
- NA |
- 6356_VC_N_0783 |
-
-
- | 103 |
- HB_643_N |
- N |
- NA |
- 6363_VC_N_0781 |
-
-
- | 104 |
- HB_644_N |
- N |
- NA |
- 6366_VC_N_0780 |
-
-
- | 105 |
- HB_645_N |
- N |
- NA |
- 6374_VC_N_0779 |
-
-
- | 106 |
- HB_650_N |
- N |
- NA |
- 6384_VC_N_0777 |
-
-
- | 107 |
- HB_651_N |
- N |
- NA |
- 6386_VC_N_0776 |
-
-
- | 108 |
- HB_653_N |
- N |
- NA |
- 6388_VC_N_0775 |
-
-
- | 109 |
- HB_659_N |
- N |
- NA |
- 6406_VC_N_1180 |
-
-
- | 110 |
- HB_662_N |
- N |
- NA |
- 6411_VC_N_0771 |
-
-
- | 111 |
- HB_663_N |
- N |
- NA |
- 6415_VC_N_0770 |
-
-
- | 112 |
- HB_670_N |
- N |
- NA |
- 6436_VC_N_0769 |
-
-
- | 113 |
- HB_687_N |
- N |
- NA |
- 6484_VC_N_0765 |
-
-
- | 114 |
- HB_689_N |
- N |
- NA |
- 6486_VC_N_0764 |
-
-
- | 115 |
- HB_694_N |
- N |
- NA |
- 6500_VC_N_0763 |
-
-
- | 116 |
- HB_697_N |
- N |
- NA |
- 6512_VC_N_0762 |
-
-
- | 117 |
- HB_700_N |
- N |
- NA |
- 6520_VC_N_0761 |
-
-
- | 118 |
- HB_711_N |
- N |
- NA |
- 6543_PF_N_1191 |
-
-
- | 119 |
- HB_714_N |
- N |
- NA |
- 6549_VC_N_1198 |
-
-
- | 120 |
- HB_717_N |
- N |
- NA |
- 6553_PF_N_2284 |
-
-
- | 121 |
- HB_721_N |
- N |
- NA |
- 6560_VC_N_2578 |
-
-
- | 122 |
- HB_726_N |
- N |
- NA |
- 6573_PF_N_2293 |
-
-
- | 123 |
- HB_730_N |
- N |
- NA |
- 6580_VC_N_2306 |
-
-
- | 124 |
- HB_735_N |
- N |
- NA |
- 6588_VC_N_1213 |
-
-
- | 125 |
- HB_737_N |
- N |
- NA |
- 6593_VC_N_1219 |
-
-
- | 126 |
- HB_738_N |
- N |
- NA |
- 6594_VC_N_1222 |
-
-
- | 127 |
- HB_759_N |
- N |
- NA |
- 6645_VC_N_1231 |
-
-
- | 128 |
- HB_764_N |
- N |
- NA |
- 6655_VC_N_1240 |
-
-
- | 129 |
- HB_765_N |
- N |
- NA |
- 6656_VC_N_1243 |
-
-
- | 130 |
- HB_767_N |
- N |
- NA |
- 6661_PF_N_2341 |
-
-
- | 131 |
- HB_770_N |
- N |
- NA |
- 6669_VC_N_1246 |
-
-
- | 132 |
- HB_772_N |
- N |
- NA |
- 6676_PF_N_1248 |
-
-
- | 133 |
- HB_001_HD |
- HD |
- F |
- 2028_CR_H_2282 |
-
-
- | 134 |
- HB_003_HD |
- HD |
- F |
- 2685_PF_H_2212 |
-
-
- | 135 |
- HB_004_HD |
- HD |
- M |
- 2706_CR_H_2432 |
-
-
- | 136 |
- HB_006_HD |
- HD |
- M |
- 2737_VC_H_2194 |
-
-
- | 137 |
- HB_007_HD |
- HD |
- NA |
- 2769_VC_H_2193 |
-
-
- | 138 |
- HB_008_HD |
- HD |
- F |
- 2790_CR_H_1890 |
-
-
- | 139 |
- HB_009_HD |
- HD |
- NA |
- 2879_VC_H_2192 |
-
-
- | 140 |
- HB_010_HD |
- HD |
- M |
- 2960_VC_H_2002 |
-
-
- | 141 |
- HB_011_HD |
- HD |
- F |
- 3053_VC_H_2001 |
-
-
- | 142 |
- HB_012_HD |
- HD |
- F |
- 3128_VC_H_1999 |
-
-
- | 143 |
- HB_014_HD |
- HD |
- F |
- 3149_PF_H_2110 |
-
-
- | 144 |
- HB_015_HD |
- HD |
- F |
- 3150_VC_H_1996 |
-
-
- | 145 |
- HB_016_HD |
- HD |
- F |
- 3177_VC_H_2191 |
-
-
- | 146 |
- HB_017_HD |
- HD |
- NA |
- 3195_VC_H_2190 |
-
-
- | 147 |
- HB_018_HD |
- HD |
- M |
- 3200_VC_H_2189 |
-
-
- | 148 |
- HB_019_HD |
- HD |
- M |
- 3209_VC_H_2188 |
-
-
- | 149 |
- HB_020_HD |
- HD |
- M |
- 3224_VC_H_1994 |
-
-
- | 150 |
- HB_022_HD |
- HD |
- F |
- 3242_PF_H_2105 |
-
-
- | 151 |
- HB_024_HD |
- HD |
- NA |
- 3272_VC_H_2186 |
-
-
- | 152 |
- HB_027_HD |
- HD |
- M |
- 3356_VC_H_2439 |
-
-
- | 153 |
- HB_028_HD |
- HD |
- F |
- 3394_PF_H_2104 |
-
-
- | 154 |
- HB_031_HD |
- HD |
- M |
- 3430_VC_H_1990 |
-
-
- | 155 |
- HB_032_HD |
- HD |
- NA |
- 3444_PF_H_2208 |
-
-
- | 156 |
- HB_034_HD |
- HD |
- F |
- 3482_VC_H_1987 |
-
-
- | 157 |
- HB_036_HD |
- HD |
- M |
- 3576_VC_H_1984 |
-
-
- | 158 |
- HB_037_HD |
- HD |
- F |
- 3579_VC_H_1983 |
-
-
- | 159 |
- HB_038_HD |
- HD |
- F |
- 3584_VC_H_2183 |
-
-
- | 160 |
- HB_039_HD |
- HD |
- NA |
- 3635_VC_H_2182 |
-
-
- | 161 |
- HB_041_HD |
- HD |
- F |
- 3695_CR_H_2267 |
-
-
- | 162 |
- HB_042_HD |
- HD |
- M |
- 3697_VC_H_1982 |
-
-
- | 163 |
- HB_043_HD |
- HD |
- NA |
- 3703_VC_H_2180 |
-
-
- | 164 |
- HB_044_HD |
- HD |
- NA |
- 3723_VC_H_2179 |
-
-
- | 165 |
- HB_046_HD |
- HD |
- F |
- 3735_VC_H_1981 |
-
-
- | 166 |
- HB_050_HD |
- HD |
- M |
- 3820_PF_H_2207 |
-
-
- | 167 |
- HB_051_HD |
- HD |
- F |
- 3849_CR_H_2262 |
-
-
- | 168 |
- HB_054_HD |
- HD |
- M |
- 3884_VC_H_2175 |
-
-
- | 169 |
- HB_056_HD |
- HD |
- NA |
- 4012_VC_H_2174 |
-
-
- | 170 |
- HB_057_HD |
- HD |
- NA |
- 4013_VC_H_2173 |
-
-
- | 171 |
- HB_059_HD |
- HD |
- NA |
- 4066_VC_H_2172 |
-
-
- | 172 |
- HB_060_HD |
- HD |
- NA |
- 4094_VC_H_2171 |
-
-
- | 173 |
- HB_061_HD |
- HD |
- F |
- 4116_VC_H_2170 |
-
-
- | 174 |
- HB_062_HD |
- HD |
- NA |
- 4121_VC_H_2169 |
-
-
- | 175 |
- HB_063_HD |
- HD |
- NA |
- 4215_VC_H_2167 |
-
-
- | 176 |
- HB_065_HD |
- HD |
- M |
- 4340_PF_H_2091 |
-
-
- | 177 |
- HB_066_HD |
- HD |
- F |
- 4344_VC_H_1977 |
-
-
- | 178 |
- HB_067_HD |
- HD |
- M |
- 4346_VC_H_2165 |
-
-
- | 179 |
- HB_069_HD |
- HD |
- F |
- 4356_VC_H_2164 |
-
-
- | 180 |
- HB_070_HD |
- HD |
- NA |
- 4386_CR_H_2249 |
-
-
- | 181 |
- HB_072_HD |
- HD |
- NA |
- 4404_VC_H_2161 |
-
-
- | 182 |
- HB_073_HD |
- HD |
- F |
- 4411_VC_H_1975 |
-
-
- | 183 |
- HB_074_HD |
- HD |
- NA |
- 4430_VC_H_2465 |
-
-
- | 184 |
- HB_075_HD |
- HD |
- M |
- 4470_VC_H_1974 |
-
-
- | 185 |
- HB_076_HD |
- HD |
- F |
- 4497_CR_H_1860 |
-
-
- | 186 |
- HB_077_HD |
- HD |
- M |
- 4509_CR_H_2244 |
-
-
- | 187 |
- HB_079_HD |
- HD |
- M |
- 4631_VC_H_1971 |
-
-
- | 188 |
- HB_080_HD |
- HD |
- F |
- 4653_PF_H_2083 |
-
-
- | 189 |
- HB_081_HD |
- HD |
- NA |
- 4678_CR_H_2242 |
-
-
- | 190 |
- HB_084_HD |
- HD |
- M |
- 4718_VC_H_2125 |
-
-
- | 191 |
- HB_090_HD |
- HD |
- NA |
- 4740_CR_H_2474 |
-
-
- | 192 |
- HB_094_HD |
- HD |
- NA |
- 4754_CR_H_2476 |
-
-
- | 193 |
- HB_098_HD |
- HD |
- NA |
- 4780_VC_H_2151 |
-
-
- | 194 |
- HB_101_HD |
- HD |
- F |
- 4809_VC_H_2148 |
-
-
- | 195 |
- HB_105_HD |
- HD |
- NA |
- 4819_CR_H_2238 |
-
-
- | 196 |
- HB_106_HD |
- HD |
- F |
- 4822_VC_H_1969 |
-
-
- | 197 |
- HB_108_HD |
- HD |
- M |
- 4826_VC_H_1968 |
-
-
- | 198 |
- HB_109_HD |
- HD |
- M |
- 4828_VC_H_2124 |
-
-
- | 199 |
- HB_115_HD |
- HD |
- NA |
- 4855_CR_H_2235 |
-
-
- | 200 |
- HB_121_HD |
- HD |
- F |
- 4902_VC_H_1967 |
-
-
- | 201 |
- HB_129_HD |
- HD |
- NA |
- 4938_VC_H_1966 |
-
-
- | 202 |
- HB_141_HD |
- HD |
- F |
- 4996_PF_H_2076 |
-
-
- | 203 |
- HB_152_HD |
- HD |
- NA |
- 5034_CR_H_2233 |
-
-
- | 204 |
- HB_153_HD |
- HD |
- M |
- 5043_VC_H_1960 |
-
-
- | 205 |
- HB_159_HD |
- HD |
- M |
- 5062_VC_H_1959 |
-
-
- | 206 |
- HB_172_HD |
- HD |
- F |
- 5114_PF_H_2070 |
-
-
- | 207 |
- HB_175_HD |
- HD |
- M |
- 5127_PF_H_2068 |
-
-
- | 208 |
- HB_180_HD |
- HD |
- M |
- 5148_VC_H_1944 |
-
-
- | 209 |
- HB_185_HD |
- HD |
- F |
- 5167_CR_H_2231 |
-
-
- | 210 |
- HB_188_HD |
- HD |
- F |
- 5172_VC_H_1951 |
-
-
- | 211 |
- HB_191_HD |
- HD |
- M |
- 5180_VC_H_1949 |
-
-
- | 212 |
- HB_196_HD |
- HD |
- NA |
- 5199_PF_H_2202 |
-
-
- | 213 |
- HB_203_HD |
- HD |
- F |
- 5228_PF_H_2059 |
-
-
- | 214 |
- HB_207_HD |
- HD |
- NA |
- 5248_PF_H_2201 |
-
-
- | 215 |
- HB_228_HD |
- HD |
- F |
- 5299_CR_H_2228 |
-
-
- | 216 |
- HB_233_HD |
- HD |
- M |
- 5312_VC_H_1938 |
-
-
- | 217 |
- HB_235_HD |
- HD |
- F |
- 5316_VC_H_1937 |
-
-
- | 218 |
- HB_242_HD |
- HD |
- F |
- 5328_PF_H_2048 |
-
-
- | 219 |
- HB_266_HD |
- HD |
- M |
- 5387_VC_H_1928 |
-
-
- | 220 |
- HB_271_HD |
- HD |
- M |
- 5394_PF_H_2039 |
-
-
- | 221 |
- HB_272_HD |
- HD |
- F |
- 5396_VC_H_1925 |
-
-
- | 222 |
- HB_279_HD |
- HD |
- F |
- 5409_VC_H_1924 |
-
-
- | 223 |
- HB_294_HD |
- HD |
- M |
- 5448_VC_H_1921 |
-
-
- | 224 |
- HB_301_HD |
- HD |
- NA |
- 5464_VC_H_1919 |
-
-
- | 225 |
- HB_304_HD |
- HD |
- F |
- 5471_VC_H_1918 |
-
-
- | 226 |
- HB_321_HD |
- HD |
- NA |
- 5522_PF_H_2199 |
-
-
- | 227 |
- HB_361_HD |
- HD |
- F |
- 5622_VC_H_2121 |
-
-
- | 228 |
- HB_370_HD |
- HD |
- M |
- 5645_VC_H_1904 |
-
-
- | 229 |
- HB_371_HD |
- HD |
- F |
- 5648_PF_H_2016 |
-
-
- | 230 |
- HB_384_HD |
- HD |
- F |
- 5688_PF_H_2012 |
-
-
- | 231 |
- HB_390_HD |
- HD |
- M |
- 5704_PF_H_2009 |
-
-
- | 232 |
- HB_393_HD |
- HD |
- F |
- 5709_VC_H_1895 |
-
-
- | 233 |
- HB_402_HD |
- HD |
- F |
- 5732_PF_H_2007 |
-
-
- | 234 |
- HB_405_HD |
- HD |
- NA |
- 5742_PF_H_2006 |
-
-
- | 235 |
- HB_407_HD |
- HD |
- M |
- 5745_PF_H_2005 |
-
-
- | 236 |
- HB_408_HD |
- HD |
- M |
- 5747_VC_H_1891 |
-
-
- | 237 |
- HB_415_HD |
- HD |
- NA |
- 5777_PF_H_1551 |
-
-
- | 238 |
- HB_417_HD |
- HD |
- M |
- 5784_PF_H_1554 |
-
-
- | 239 |
- HB_424_HD |
- HD |
- M |
- 5804_VC_H_1558 |
-
-
- | 240 |
- HB_444_HD |
- HD |
- M |
- 5856_VC_H_1567 |
-
-
- | 241 |
- HB_457_HD |
- HD |
- M |
- 5896_VC_H_1570 |
-
-
- | 242 |
- HB_466_HD |
- HD |
- M |
- 5910_PF_H_1572 |
-
-
- | 243 |
- HB_478_HD |
- HD |
- M |
- 5941_CR_H_1583 |
-
-
- | 244 |
- HB_487_HD |
- HD |
- F |
- 5964_VC_H_1597 |
-
-
- | 245 |
- HB_511_HD |
- HD |
- M |
- 6019_PF_H_2198 |
-
-
- | 246 |
- HB_513_HD |
- HD |
- F |
- 6024_VC_H_1612 |
-
-
- | 247 |
- HB_515_HD |
- HD |
- F |
- 6028_CR_H_1613 |
-
-
- | 248 |
- HB_518_HD |
- HD |
- M |
- 6033_VC_H_1618 |
-
-
- | 249 |
- HB_522_HD |
- HD |
- M |
- 6037_PF_H_1626 |
-
-
- | 250 |
- HB_527_HD |
- HD |
- F |
- 6047_VC_H_1639 |
-
-
- | 251 |
- HB_528_HD |
- HD |
- M |
- 6051_PF_H_1641 |
-
-
- | 252 |
- HB_530_HD |
- HD |
- M |
- 6054_VC_H_1648 |
-
-
- | 253 |
- HB_537_HD |
- HD |
- F |
- 6071_PF_H_1653 |
-
-
- | 254 |
- HB_549_HD |
- HD |
- M |
- 6119_CR_H_1670 |
-
-
- | 255 |
- HB_593_HD |
- HD |
- NA |
- 6219_CR_H_2567 |
-
-
- | 256 |
- HB_610_HD |
- HD |
- NA |
- 6275_PF_H_1692 |
-
-
- | 257 |
- HB_616_HD |
- HD |
- F |
- 6284_CR_H_1694 |
-
-
- | 258 |
- HB_626_HD |
- HD |
- M |
- 6315_VC_H_1702 |
-
-
- | 259 |
- HB_639_HD |
- HD |
- F |
- 6344_CR_H_1703 |
-
-
- | 260 |
- HB_649_HD |
- HD |
- F |
- 6382_CR_H_1709 |
-
-
- | 261 |
- HB_661_HD |
- HD |
- M |
- 6408_VC_H_1714 |
-
-
- | 262 |
- HB_682_HD |
- HD |
- M |
- 6467_PF_H_1725 |
-
-
- | 263 |
- HB_683_HD |
- HD |
- M |
- 6472_VC_H_1729 |
-
-
- | 264 |
- HB_691_HD |
- HD |
- F |
- 6493_VC_H_1732 |
-
-
- | 265 |
- HB_692_HD |
- HD |
- M |
- 6495_CR_H_1733 |
-
-
- | 266 |
- HB_707_HD |
- HD |
- M |
- 6535_PF_H_1737 |
-
-
- | 267 |
- HB_709_HD |
- HD |
- F |
- 6539_CR_H_1739 |
-
-
- | 268 |
- HB_725_HD |
- HD |
- M |
- 6572_PF_H_1746 |
-
-
- | 269 |
- HB_732_HD |
- HD |
- F |
- 6584_VC_H_1750 |
-
-
- | 270 |
- HB_734_HD |
- HD |
- F |
- 6587_CR_H_1751 |
-
-
- | 271 |
- HB_748_HD |
- HD |
- NA |
- 6615_VC_H_2315 |
-
-
- | 272 |
- HB_750_HD |
- HD |
- NA |
- 6628_PF_H_2326 |
-
-
- | 273 |
- HB_758_HD |
- HD |
- NA |
- 6643_VC_H_2602 |
-
-
- | 274 |
- HB_760_HD |
- HD |
- M |
- 6646_PF_H_1761 |
-
-
- | 275 |
- HB_762_HD |
- HD |
- M |
- 6650_VC_H_1765 |
-
-
- | 276 |
- HB_766_HD |
- HD |
- M |
- 6658_VC_H_1768 |
-
-
- | 277 |
- HB_768_HD |
- HD |
- NA |
- 6663_VC_H_1771 |
-
-
- | 278 |
- HB_769_HD |
- HD |
- M |
- 6666_VC_H_1774 |
-
-
- | 279 |
- HB_774_HD |
- HD |
- NA |
- 6689_PF_H_2344 |
-
-
- | 280 |
- HB_778_HD |
- HD |
- NA |
- 6696_PF_H_2356 |
-
-
- | 281 |
- HB_780_HD |
- HD |
- NA |
- 6704_PF_H_2362 |
-
-
- | 282 |
- HB_790_HD |
- HD |
- NA |
- 6788_PF_H_2389 |
-
-
- | 283 |
- HB_800_HD |
- HD |
- NA |
- 6807_PF_H_2419 |
-
-
- | 284 |
- HB_802_HD |
- HD |
- NA |
- 6811_PF_H_2425 |
-
-
- | 285 |
- HB_045_AD |
- AD |
- NA |
- 3734_CR_A_0122 |
-
-
- | 286 |
- HB_048_AD |
- AD |
- NA |
- 3791_CR_A_0128 |
-
-
- | 287 |
- HB_053_AD |
- AD |
- NA |
- 3877_CR_A_0134 |
-
-
- | 288 |
- HB_055_AD |
- AD |
- NA |
- 3893_VC_A_0142 |
-
-
- | 289 |
- HB_068_AD |
- AD |
- NA |
- 4349_VC_A_0148 |
-
-
- | 290 |
- HB_082_AD |
- AD |
- NA |
- 4712_CR_A_0309 |
-
-
- | 291 |
- HB_085_AD |
- AD |
- NA |
- 4726_VC_A_0311 |
-
-
- | 292 |
- HB_087_AD |
- AD |
- NA |
- 4730_CR_A_0315 |
-
-
- | 293 |
- HB_089_AD |
- AD |
- NA |
- 4733_VC_A_0320 |
-
-
- | 294 |
- HB_093_AD |
- AD |
- NA |
- 4749_VC_A_0323 |
-
-
- | 295 |
- HB_095_AD |
- AD |
- NA |
- 4759_CR_A_0327 |
-
-
- | 296 |
- HB_097_AD |
- AD |
- NA |
- 4773_CR_A_0866 |
-
-
- | 297 |
- HB_099_AD |
- AD |
- NA |
- 4785_VC_A_0332 |
-
-
- | 298 |
- HB_100_AD |
- AD |
- NA |
- 4795_VC_A_0335 |
-
-
- | 299 |
- HB_103_AD |
- AD |
- NA |
- 4811_VC_A_0341 |
-
-
- | 300 |
- HB_104_AD |
- AD |
- NA |
- 4813_CR_A_0345 |
-
-
- | 301 |
- HB_112_AD |
- AD |
- NA |
- 4842_VC_A_0870 |
-
-
- | 302 |
- HB_113_AD |
- AD |
- NA |
- 4850_CR_A_0351 |
-
-
- | 303 |
- HB_114_AD |
- AD |
- NA |
- 4852_CR_A_0354 |
-
-
- | 304 |
- HB_117_AD |
- AD |
- NA |
- 4868_VC_A_0874 |
-
-
- | 305 |
- HB_122_AD |
- AD |
- NA |
- 4904_CR_A_1132 |
-
-
- | 306 |
- HB_123_AD |
- AD |
- NA |
- 4905_VC_A_0884 |
-
-
- | 307 |
- HB_124_AD |
- AD |
- NA |
- 4916_VC_A_0886 |
-
-
- | 308 |
- HB_125_AD |
- AD |
- NA |
- 4917_CR_A_0360 |
-
-
- | 309 |
- HB_126_AD |
- AD |
- NA |
- 4921_VC_A_0362 |
-
-
- | 310 |
- HB_128_AD |
- AD |
- NA |
- 4936_CR_A_0369 |
-
-
- | 311 |
- HB_130_AD |
- AD |
- NA |
- 4939_VC_A_0888 |
-
-
- | 312 |
- HB_131_AD |
- AD |
- NA |
- 4944_CR_A_0889 |
-
-
- | 313 |
- HB_132_AD |
- AD |
- NA |
- 4946_CR_A_0372 |
-
-
- | 314 |
- HB_134_AD |
- AD |
- NA |
- 4951_CR_A_0891 |
-
-
- | 315 |
- HB_135_AD |
- AD |
- NA |
- 4953_VC_A_0893 |
-
-
- | 316 |
- HB_136_AD |
- AD |
- NA |
- 4965_VC_A_0160 |
-
-
- | 317 |
- HB_137_AD |
- AD |
- NA |
- 4966_VC_A_0374 |
-
-
- | 318 |
- HB_138_AD |
- AD |
- NA |
- 4969_VC_A_0895 |
-
-
- | 319 |
- HB_140_AD |
- AD |
- NA |
- 4993_CR_A_0896 |
-
-
- | 320 |
- HB_146_AD |
- AD |
- NA |
- 5018_CR_A_0384 |
-
-
- | 321 |
- HB_148_AD |
- AD |
- NA |
- 5022_VC_A_0386 |
-
-
- | 322 |
- HB_150_AD |
- AD |
- NA |
- 5031_VC_A_0392 |
-
-
- | 323 |
- HB_151_AD |
- AD |
- NA |
- 5033_CR_A_0396 |
-
-
- | 324 |
- HB_154_AD |
- AD |
- NA |
- 5048_VC_A_1321 |
-
-
- | 325 |
- HB_155_AD |
- AD |
- NA |
- 5056_VC_A_0398 |
-
-
- | 326 |
- HB_156_AD |
- AD |
- NA |
- 5057_VC_A_0163 |
-
-
- | 327 |
- HB_157_AD |
- AD |
- NA |
- 5059_VC_A_0401 |
-
-
- | 328 |
- HB_158_AD |
- AD |
- NA |
- 5061_PF_A_2612 |
-
-
- | 329 |
- HB_160_AD |
- AD |
- NA |
- 5064_PF_A_2615 |
-
-
- | 330 |
- HB_165_AD |
- AD |
- NA |
- 5092_CR_A_0899 |
-
-
- | 331 |
- HB_168_AD |
- AD |
- NA |
- 5097_VC_A_0407 |
-
-
- | 332 |
- HB_170_AD |
- AD |
- NA |
- 5101_VC_A_0410 |
-
-
- | 333 |
- HB_174_AD |
- AD |
- NA |
- 5124_PF_A_1343 |
-
-
- | 334 |
- HB_179_AD |
- AD |
- NA |
- 5145_VC_A_1351 |
-
-
- | 335 |
- HB_181_AD |
- AD |
- NA |
- 5152_CR_A_0414 |
-
-
- | 336 |
- HB_184_AD |
- AD |
- NA |
- 5166_VC_A_1354 |
-
-
- | 337 |
- HB_194_AD |
- AD |
- NA |
- 5193_VC_A_1360 |
-
-
- | 338 |
- HB_197_AD |
- AD |
- NA |
- 5202_CR_A_1368 |
-
-
- | 339 |
- HB_199_AD |
- AD |
- NA |
- 5205_VC_A_0166 |
-
-
- | 340 |
- HB_200_AD |
- AD |
- NA |
- 5210_VC_A_0905 |
-
-
- | 341 |
- HB_205_AD |
- AD |
- NA |
- 5235_VC_A_0419 |
-
-
- | 342 |
- HB_208_AD |
- AD |
- NA |
- 5249_VC_A_0422 |
-
-
- | 343 |
- HB_209_AD |
- AD |
- NA |
- 5252_VC_A_0907 |
-
-
- | 344 |
- HB_211_AD |
- AD |
- NA |
- 5257_VC_A_0169 |
-
-
- | 345 |
- HB_216_AD |
- AD |
- NA |
- 5272_VC_A_0425 |
-
-
- | 346 |
- HB_219_AD |
- AD |
- NA |
- 5279_CR_A_0147 |
-
-
- | 347 |
- HB_221_AD |
- AD |
- NA |
- 5283_VC_A_0145 |
-
-
- | 348 |
- HB_222_AD |
- AD |
- NA |
- 5285_VC_A_0141 |
-
-
- | 349 |
- HB_224_AD |
- AD |
- NA |
- 5288_VC_A_0428 |
-
-
- | 350 |
- HB_230_AD |
- AD |
- NA |
- 5301_VC_A_0174 |
-
-
- | 351 |
- HB_231_AD |
- AD |
- NA |
- 5305_VC_A_1384 |
-
-
- | 352 |
- HB_232_AD |
- AD |
- NA |
- 5310_CR_A_0176 |
-
-
- | 353 |
- HB_234_AD |
- AD |
- NA |
- 5313_PF_A_2618 |
-
-
- | 354 |
- HB_236_AD |
- AD |
- NA |
- 5317_PF_A_2624 |
-
-
- | 355 |
- HB_238_AD |
- AD |
- NA |
- 5322_CR_A_2632 |
-
-
- | 356 |
- HB_240_AD |
- AD |
- NA |
- 5325_VC_A_0137 |
-
-
- | 357 |
- HB_244_AD |
- AD |
- NA |
- 5337_VC_A_1387 |
-
-
- | 358 |
- HB_245_AD |
- AD |
- NA |
- 5339_VC_A_0181 |
-
-
- | 359 |
- HB_250_AD |
- AD |
- NA |
- 5346_VC_A_1393 |
-
-
- | 360 |
- HB_251_AD |
- AD |
- NA |
- 5350_VC_A_0184 |
-
-
- | 361 |
- HB_252_AD |
- AD |
- NA |
- 5355_VC_A_0133 |
-
-
- | 362 |
- HB_253_AD |
- AD |
- NA |
- 5359_CR_A_1395 |
-
-
- | 363 |
- HB_258_AD |
- AD |
- NA |
- 5370_PF_A_1400 |
-
-
- | 364 |
- HB_259_AD |
- AD |
- NA |
- 5371_PF_A_2636 |
-
-
- | 365 |
- HB_260_AD |
- AD |
- NA |
- 5375_VC_A_0188 |
-
-
- | 366 |
- HB_263_AD |
- AD |
- NA |
- 5381_VC_A_0022 |
-
-
- | 367 |
- HB_265_AD |
- AD |
- NA |
- 5385_VC_A_1402 |
-
-
- | 368 |
- HB_267_AD |
- AD |
- NA |
- 5389_VC_A_0928 |
-
-
- | 369 |
- HB_268_AD |
- AD |
- NA |
- 5390_CR_A_0151 |
-
-
- | 370 |
- HB_273_AD |
- AD |
- NA |
- 5400_PF_A_2645 |
-
-
- | 371 |
- HB_274_AD |
- AD |
- NA |
- 5401_VC_A_0931 |
-
-
- | 372 |
- HB_275_AD |
- AD |
- NA |
- 5404_PF_A_2648 |
-
-
- | 373 |
- HB_276_AD |
- AD |
- NA |
- 5406_VC_A_0933 |
-
-
- | 374 |
- HB_277_AD |
- AD |
- NA |
- 5407_PF_A_2651 |
-
-
- | 375 |
- HB_280_AD |
- AD |
- NA |
- 5412_VC_A_0935 |
-
-
- | 376 |
- HB_281_AD |
- AD |
- NA |
- 5413_PF_A_2657 |
-
-
- | 377 |
- HB_283_AD |
- AD |
- NA |
- 5419_VC_A_0937 |
-
-
- | 378 |
- HB_284_AD |
- AD |
- NA |
- 5420_VC_A_0939 |
-
-
- | 379 |
- HB_285_AD |
- AD |
- NA |
- 5421_CR_A_0432 |
-
-
- | 380 |
- HB_286_AD |
- AD |
- NA |
- 5423_PF_A_2660 |
-
-
- | 381 |
- HB_288_AD |
- AD |
- NA |
- 5425_PF_A_2666 |
-
-
- | 382 |
- HB_289_AD |
- AD |
- NA |
- 5426_VC_A_1405 |
-
-
- | 383 |
- HB_290_AD |
- AD |
- NA |
- 5433_VC_A_0434 |
-
-
- | 384 |
- HB_296_AD |
- AD |
- NA |
- 5456_PF_A_2675 |
-
-
- | 385 |
- HB_299_AD |
- AD |
- NA |
- 5461_VC_A_0192 |
-
-
- | 386 |
- HB_302_AD |
- AD |
- NA |
- 5465_PF_A_2678 |
-
-
- | 387 |
- HB_303_AD |
- AD |
- NA |
- 5469_VC_A_1417 |
-
-
- | 388 |
- HB_305_AD |
- AD |
- NA |
- 5479_PF_A_1421 |
-
-
- | 389 |
- HB_306_AD |
- AD |
- NA |
- 5480_VC_A_0437 |
-
-
- | 390 |
- HB_307_AD |
- AD |
- NA |
- 5482_VC_A_0028 |
-
-
- | 391 |
- HB_308_AD |
- AD |
- NA |
- 5483_VC_A_0941 |
-
-
- | 392 |
- HB_309_AD |
- AD |
- NA |
- 5487_CR_A_0441 |
-
-
- | 393 |
- HB_310_AD |
- AD |
- NA |
- 5488_CR_A_0194 |
-
-
- | 394 |
- HB_312_AD |
- AD |
- NA |
- 5500_VC_A_0198 |
-
-
- | 395 |
- HB_313_AD |
- AD |
- NA |
- 5502_PF_A_2684 |
-
-
- | 396 |
- HB_315_AD |
- AD |
- NA |
- 5513_PF_A_2687 |
-
-
- | 397 |
- HB_316_AD |
- AD |
- NA |
- 5516_PF_A_2690 |
-
-
- | 398 |
- HB_317_AD |
- AD |
- NA |
- 5517_PF_A_2693 |
-
-
- | 399 |
- HB_318_AD |
- AD |
- NA |
- 5518_CR_A_0030 |
-
-
- | 400 |
- HB_319_AD |
- AD |
- NA |
- 5519_CR_A_2695 |
-
-
- | 401 |
- HB_320_AD |
- AD |
- NA |
- 5520_PF_A_2699 |
-
-
- | 402 |
- HB_322_AD |
- AD |
- NA |
- 5527_VC_A_0945 |
-
-
- | 403 |
- HB_325_AD |
- AD |
- NA |
- 5532_PF_A_2702 |
-
-
- | 404 |
- HB_328_AD |
- AD |
- NA |
- 5541_PF_A_2705 |
-
-
- | 405 |
- HB_330_AD |
- AD |
- NA |
- 5544_VC_A_0201 |
-
-
- | 406 |
- HB_334_AD |
- AD |
- NA |
- 5554_VC_A_0452 |
-
-
- | 407 |
- HB_335_AD |
- AD |
- NA |
- 5557_VC_A_0950 |
-
-
- | 408 |
- HB_337_AD |
- AD |
- NA |
- 5560_VC_A_0204 |
-
-
- | 409 |
- HB_342_AD |
- AD |
- NA |
- 5571_PF_A_1430 |
-
-
- | 410 |
- HB_345_AD |
- AD |
- NA |
- 5583_PF_A_2708 |
-
-
- | 411 |
- HB_347_AD |
- AD |
- NA |
- 5589_PF_A_2714 |
-
-
- | 412 |
- HB_349_AD |
- AD |
- NA |
- 5592_PF_A_2717 |
-
-
- | 413 |
- HB_352_AD |
- AD |
- NA |
- 5604_VC_A_0037 |
-
-
- | 414 |
- HB_353_AD |
- AD |
- NA |
- 5607_PF_A_2723 |
-
-
- | 415 |
- HB_356_AD |
- AD |
- NA |
- 5615_VC_A_0041 |
-
-
- | 416 |
- HB_357_AD |
- AD |
- NA |
- 5616_CR_A_0127 |
-
-
- | 417 |
- HB_358_AD |
- AD |
- NA |
- 5617_CR_A_0456 |
-
-
- | 418 |
- HB_359_AD |
- AD |
- NA |
- 5618_CR_A_0044 |
-
-
- | 419 |
- HB_362_AD |
- AD |
- NA |
- 5625_CR_A_2495 |
-
-
- | 420 |
- HB_363_AD |
- AD |
- NA |
- 5626_CR_A_2498 |
-
-
- | 421 |
- HB_364_AD |
- AD |
- NA |
- 5629_CR_A_0390 |
-
-
- | 422 |
- HB_369_AD |
- AD |
- NA |
- 5643_VC_A_1143 |
-
-
- | 423 |
- HB_373_AD |
- AD |
- NA |
- 5654_VC_A_0047 |
-
-
- | 424 |
- HB_375_AD |
- AD |
- NA |
- 5660_CR_A_0462 |
-
-
- | 425 |
- HB_376_AD |
- AD |
- NA |
- 5661_VC_A_0464 |
-
-
- | 426 |
- HB_377_AD |
- AD |
- NA |
- 5667_VC_A_2509 |
-
-
- | 427 |
- HB_378_AD |
- AD |
- NA |
- 5668_VC_A_1438 |
-
-
- | 428 |
- HB_383_AD |
- AD |
- NA |
- 5686_CR_A_2728 |
-
-
- | 429 |
- HB_386_AD |
- AD |
- NA |
- 5695_VC_A_0953 |
-
-
- | 430 |
- HB_389_AD |
- AD |
- NA |
- 5700_VC_A_2514 |
-
-
- | 431 |
- HB_391_AD |
- AD |
- NA |
- 5705_CR_A_0474 |
-
-
- | 432 |
- HB_392_AD |
- AD |
- NA |
- 5706_VC_A_0476 |
-
-
- | 433 |
- HB_394_AD |
- AD |
- NA |
- 5713_VC_A_0479 |
-
-
- | 434 |
- HB_397_AD |
- AD |
- NA |
- 5721_CR_A_0210 |
-
-
- | 435 |
- HB_404_AD |
- AD |
- NA |
- 5735_CR_A_0489 |
-
-
- | 436 |
- HB_406_AD |
- AD |
- NA |
- 5744_CR_A_0960 |
-
-
- | 437 |
- HB_409_AD |
- AD |
- NA |
- 5749_CR_A_0159 |
-
-
- | 438 |
- HB_410_AD |
- AD |
- NA |
- 5751_CR_A_2518 |
-
-
- | 439 |
- HB_411_AD |
- AD |
- NA |
- 5755_CR_A_2731 |
-
-
- | 440 |
- HB_413_AD |
- AD |
- NA |
- 5766_VC_A_0214 |
-
-
- | 441 |
- HB_419_AD |
- AD |
- NA |
- 5790_VC_A_0217 |
-
-
- | 442 |
- HB_420_AD |
- AD |
- NA |
- 5796_CR_A_0964 |
-
-
- | 443 |
- HB_428_AD |
- AD |
- NA |
- 5811_CR_A_2524 |
-
-
- | 444 |
- HB_429_AD |
- AD |
- NA |
- 5819_CR_A_2527 |
-
-
- | 445 |
- HB_430_AD |
- AD |
- NA |
- 5822_CR_A_2530 |
-
-
- | 446 |
- HB_434_AD |
- AD |
- NA |
- 5828_CR_A_2533 |
-
-
- | 447 |
- HB_435_AD |
- AD |
- NA |
- 5831_CR_A_0222 |
-
-
- | 448 |
- HB_437_AD |
- AD |
- NA |
- 5839_CR_A_2539 |
-
-
- | 449 |
- HB_438_AD |
- AD |
- NA |
- 5843_CR_A_0227 |
-
-
- | 450 |
- HB_439_AD |
- AD |
- NA |
- 5845_CR_A_0230 |
-
-
- | 451 |
- HB_441_AD |
- AD |
- NA |
- 5849_CR_A_0233 |
-
-
- | 452 |
- HB_442_AD |
- AD |
- NA |
- 5850_CR_A_0495 |
-
-
- | 453 |
- HB_445_AD |
- AD |
- NA |
- 5858_CR_A_0969 |
-
-
- | 454 |
- HB_448_AD |
- AD |
- NA |
- 5864_CR_A_0974 |
-
-
- | 455 |
- HB_451_AD |
- AD |
- NA |
- 5871_CR_A_2542 |
-
-
- | 456 |
- HB_454_AD |
- AD |
- NA |
- 5879_CR_A_2545 |
-
-
- | 457 |
- HB_455_AD |
- AD |
- NA |
- 5887_CR_A_0976_Bis |
-
-
- | 458 |
- HB_459_AD |
- AD |
- NA |
- 5898_CR_A_2548 |
-
-
- | 459 |
- HB_460_AD |
- AD |
- NA |
- 5900_VC_A_0237 |
-
-
- | 460 |
- HB_461_AD |
- AD |
- NA |
- 5901_CR_A_0239 |
-
-
- | 461 |
- HB_469_AD |
- AD |
- NA |
- 5914_CR_A_2554 |
-
-
- | 462 |
- HB_471_AD |
- AD |
- NA |
- 5922_VC_A_0246 |
-
-
- | 463 |
- HB_473_AD |
- AD |
- NA |
- 5927_CR_A_2560 |
-
-
- | 464 |
- HB_474_AD |
- AD |
- NA |
- 5933_VC_A_1071 |
-
-
- | 465 |
- HB_477_AD |
- AD |
- NA |
- 5939_CR_A_1151 |
-
-
- | 466 |
- HB_479_AD |
- AD |
- NA |
- 5945_VC_A_0983 |
-
-
- | 467 |
- HB_484_AD |
- AD |
- NA |
- 5956_CR_A_0123 |
-
-
- | 468 |
- HB_489_AD |
- AD |
- NA |
- 5968_VC_A_1075 |
-
-
- | 469 |
- HB_491_AD |
- AD |
- NA |
- 5971_CR_A_0119 |
-
-
- | 470 |
- HB_492_AD |
- AD |
- NA |
- 5972_VC_A_0251 |
-
-
- | 471 |
- HB_494_AD |
- AD |
- NA |
- 5979_CR_A_0115 |
-
-
- | 472 |
- HB_498_AD |
- AD |
- NA |
- 5988_VC_A_0503 |
-
-
- | 473 |
- HB_502_AD |
- AD |
- NA |
- 5994_PF_A_1605 |
-
-
- | 474 |
- HB_503_AD |
- AD |
- NA |
- 5995_CR_A_2563 |
-
-
- | 475 |
- HB_510_AD |
- AD |
- NA |
- 6017_CR_A_0048 |
-
-
- | 476 |
- HB_514_AD |
- AD |
- NA |
- 6025_VC_A_0506 |
-
-
- | 477 |
- HB_517_AD |
- AD |
- NA |
- 6031_VC_A_0258 |
-
-
- | 478 |
- HB_520_AD |
- AD |
- NA |
- 6035_VC_A_1621 |
-
-
- | 479 |
- HB_523_AD |
- AD |
- NA |
- 6038_VC_A_0261 |
-
-
- | 480 |
- HB_524_AD |
- AD |
- NA |
- 6042_VC_A_1156 |
-
-
- | 481 |
- HB_525_AD |
- AD |
- NA |
- 6044_VC_A_0264 |
-
-
- | 482 |
- HB_531_AD |
- AD |
- NA |
- 6056_CR_A_0999 |
-
-
- | 483 |
- HB_533_AD |
- AD |
- NA |
- 6061_PF_A_1650 |
-
-
- | 484 |
- HB_534_AD |
- AD |
- NA |
- 6066_VC_A_0270 |
-
-
- | 485 |
- HB_535_AD |
- AD |
- NA |
- 6067_PF_A_1452 |
-
-
- | 486 |
- HB_536_AD |
- AD |
- NA |
- 6068_VC_A_0273 |
-
-
- | 487 |
- HB_545_AD |
- AD |
- NA |
- 6102_CR_A_1661 |
-
-
- | 488 |
- HB_546_AD |
- AD |
- NA |
- 6107_CR_A_0055 |
-
-
- | 489 |
- HB_550_AD |
- AD |
- NA |
- 6120_VC_A_0058 |
-
-
- | 490 |
- HB_552_AD |
- AD |
- NA |
- 6126_VC_A_1675 |
-
-
- | 491 |
- HB_553_AD |
- AD |
- NA |
- 6129_PF_A_0274 |
-
-
- | 492 |
- HB_554_AD |
- AD |
- NA |
- 6130_VC_A_1678 |
-
-
- | 493 |
- HB_555_AD |
- AD |
- NA |
- 6131_CR_A_0510 |
-
-
- | 494 |
- HB_556_AD |
- AD |
- NA |
- 6132_CR_A_0513 |
-
-
- | 495 |
- HB_558_AD |
- AD |
- NA |
- 6137_VC_A_1681 |
-
-
- | 496 |
- HB_564_AD |
- AD |
- NA |
- 6153_VC_A_1465 |
-
-
- | 497 |
- HB_565_AD |
- AD |
- NA |
- 6154_VC_A_1468 |
-
-
- | 498 |
- HB_566_AD |
- AD |
- NA |
- 6157_VC_A_0062 |
-
-
- | 499 |
- HB_568_AD |
- AD |
- NA |
- 6164_CR_A_1005 |
-
-
- | 500 |
- HB_571_AD |
- AD |
- NA |
- 6171_CR_A_0065 |
-
-
- | 501 |
- HB_573_AD |
- AD |
- NA |
- 6174_VC_A_0068 |
-
-
- | 502 |
- HB_576_AD |
- AD |
- NA |
- 6180_CR_A_0281 |
-
-
- | 503 |
- HB_583_AD |
- AD |
- NA |
- 6194_VC_A_0071 |
-
-
- | 504 |
- HB_585_AD |
- AD |
- NA |
- 6198_VC_A_0073 |
-
-
- | 505 |
- HB_590_AD |
- AD |
- NA |
- 6215_VC_A_0518 |
-
-
- | 506 |
- HB_591_AD |
- AD |
- NA |
- 6216_VC_A_1476 |
-
-
- | 507 |
- HB_592_AD |
- AD |
- NA |
- 6218_CR_A_0522 |
-
-
- | 508 |
- HB_594_AD |
- AD |
- NA |
- 6223_VC_A_0288 |
-
-
- | 509 |
- HB_596_AD |
- AD |
- NA |
- 6226_CR_A_0076 |
-
-
- | 510 |
- HB_597_AD |
- AD |
- NA |
- 6227_VC_A_0080 |
-
-
- | 511 |
- HB_598_AD |
- AD |
- NA |
- 6231_VC_A_1479 |
-
-
- | 512 |
- HB_605_AD |
- AD |
- NA |
- 6261_VC_A_0084 |
-
-
- | 513 |
- HB_608_AD |
- AD |
- NA |
- 6268_CR_A_0525 |
-
-
- | 514 |
- HB_611_AD |
- AD |
- NA |
- 6279_VC_A_0089 |
-
-
- | 515 |
- HB_612_AD |
- AD |
- NA |
- 6280_VC_A_0091 |
-
-
- | 516 |
- HB_613_AD |
- AD |
- NA |
- 6281_CR_A_0528 |
-
-
- | 517 |
- HB_621_AD |
- AD |
- NA |
- 6308_VC_A_1503 |
-
-
- | 518 |
- HB_623_AD |
- AD |
- NA |
- 6311_CR_A_0531 |
-
-
- | 519 |
- HB_624_AD |
- AD |
- NA |
- 6312_CR_A_0534 |
-
-
- | 520 |
- HB_630_AD |
- AD |
- NA |
- 6324_PF_A_1514 |
-
-
- | 521 |
- HB_633_AD |
- AD |
- NA |
- 6332_VC_A_1518 |
-
-
- | 522 |
- HB_634_AD |
- AD |
- NA |
- 6335_VC_A_0536 |
-
-
- | 523 |
- HB_635_AD |
- AD |
- NA |
- 6336_CR_A_0290 |
-
-
- | 524 |
- HB_636_AD |
- AD |
- NA |
- 6338_VC_A_0539 |
-
-
- | 525 |
- HB_642_AD |
- AD |
- NA |
- 6358_VC_A_0545 |
-
-
- | 526 |
- HB_652_AD |
- AD |
- NA |
- 6387_VC_A_0093 |
-
-
- | 527 |
- HB_657_AD |
- AD |
- NA |
- 6394_VC_A_0551 |
-
-
- | 528 |
- HB_664_AD |
- AD |
- NA |
- 6416_VC_A_1095 |
-
-
- | 529 |
- HB_666_AD |
- AD |
- NA |
- 6422_CR_A_0555 |
-
-
- | 530 |
- HB_669_AD |
- AD |
- NA |
- 6431_VC_A_0294 |
-
-
- | 531 |
- HB_674_AD |
- AD |
- NA |
- 6449_VC_A_1183 |
-
-
- | 532 |
- HB_680_AD |
- AD |
- NA |
- 6458_CR_A_2570 |
-
-
- | 533 |
- HB_685_AD |
- AD |
- NA |
- 6481_VC_A_0560 |
-
-
- | 534 |
- HB_690_AD |
- AD |
- NA |
- 6489_CR_A_0100 |
-
-
- | 535 |
- HB_696_AD |
- AD |
- NA |
- 6511_VC_A_1119 |
-
-
- | 536 |
- HB_698_AD |
- AD |
- NA |
- 6515_CR_A_0564 |
-
-
- | 537 |
- HB_699_AD |
- AD |
- NA |
- 6518_VC_A_0103 |
-
-
- | 538 |
- HB_703_AD |
- AD |
- NA |
- 6523_VC_A_0107 |
-
-
- | 539 |
- HB_704_AD |
- AD |
- NA |
- 6530_VC_A_0112 |
-
-
- | 540 |
- HB_706_AD |
- AD |
- NA |
- 6534_VC_A_0306 |
-
-
- | 541 |
- HB_712_AD |
- AD |
- NA |
- 6546_PF_A_1194 |
-
-
- | 542 |
- HB_713_AD |
- AD |
- NA |
- 6548_PF_A_1541 |
-
-
- | 543 |
- HB_715_AD |
- AD |
- NA |
- 6550_VC_A_1201 |
-
-
- | 544 |
- HB_718_AD |
- AD |
- NA |
- 6554_PF_A_1203 |
-
-
- | 545 |
- HB_720_AD |
- AD |
- NA |
- 6559_PF_A_2287 |
-
-
- | 546 |
- HB_722_AD |
- AD |
- NA |
- 6561_CR_A_2582 |
-
-
- | 547 |
- HB_723_AD |
- AD |
- NA |
- 6562_PF_A_2290 |
-
-
- | 548 |
- HB_724_AD |
- AD |
- NA |
- 6564_CR_A_2585 |
-
-
- | 549 |
- HB_727_AD |
- AD |
- NA |
- 6575_CR_A_2298 |
-
-
- | 550 |
- HB_728_AD |
- AD |
- NA |
- 6577_PF_A_2299 |
-
-
- | 551 |
- HB_729_AD |
- AD |
- NA |
- 6578_PF_A_2302 |
-
-
- | 552 |
- HB_731_AD |
- AD |
- NA |
- 6582_VC_A_1207 |
-
-
- | 553 |
- HB_733_AD |
- AD |
- NA |
- 6585_VC_A_1210 |
-
-
- | 554 |
- HB_736_AD |
- AD |
- NA |
- 6590_PF_A_1215 |
-
-
- | 555 |
- HB_743_AD |
- AD |
- NA |
- 6603_PF_A_1448 |
-
-
- | 556 |
- HB_745_AD |
- AD |
- NA |
- 6610_PF_A_1227 |
-
-
- | 557 |
- HB_746_AD |
- AD |
- NA |
- 6612_PF_A_2308 |
-
-
- | 558 |
- HB_749_AD |
- AD |
- NA |
- 6617_VC_A_2587 |
-
-
- | 559 |
- HB_751_AD |
- AD |
- NA |
- 6629_VC_A_2330 |
-
-
- | 560 |
- HB_752_AD |
- AD |
- NA |
- 6630_VC_A_2590 |
-
-
- | 561 |
- HB_753_AD |
- AD |
- NA |
- 6632_PF_A_2332 |
-
-
- | 562 |
- HB_754_AD |
- AD |
- NA |
- 6637_VC_A_2596 |
-
-
- | 563 |
- HB_755_AD |
- AD |
- NA |
- 6638_VC_A_2599 |
-
-
- | 564 |
- HB_756_AD |
- AD |
- NA |
- 6639_VC_A_2336 |
-
-
- | 565 |
- HB_757_AD |
- AD |
- NA |
- 6641_PF_A_2338 |
-
-
- | 566 |
- HB_763_AD |
- AD |
- NA |
- 6654_VC_A_1237 |
-
-
- | 567 |
- HB_773_AD |
- AD |
- NA |
- 6681_VC_A_1252 |
-
-
- | 568 |
- HB_775_AD |
- AD |
- NA |
- 6693_VC_A_2348 |
-
-
- | 569 |
- HB_776_AD |
- AD |
- NA |
- 6694_VC_A_2351 |
-
-
- | 570 |
- HB_777_AD |
- AD |
- NA |
- 6695_PF_A_2353 |
-
-
- | 571 |
- HB_779_AD |
- AD |
- NA |
- 6699_PF_A_2359 |
-
-
- | 572 |
- HB_781_AD |
- AD |
- NA |
- 6708_VC_A_2366 |
-
-
- | 573 |
- HB_782_AD |
- AD |
- NA |
- 6776_PF_A_2607 |
-
-
- | 574 |
- HB_783_AD |
- AD |
- NA |
- 6778_PF_A_2368 |
-
-
- | 575 |
- HB_784_AD |
- AD |
- NA |
- 6779_PF_A_2371 |
-
-
- | 576 |
- HB_785_AD |
- AD |
- NA |
- 6780_PF_A_2374 |
-
-
- | 577 |
- HB_786_AD |
- AD |
- NA |
- 6782_PF_A_2377 |
-
-
- | 578 |
- HB_787_AD |
- AD |
- NA |
- 6784_PF_A_2380 |
-
-
- | 579 |
- HB_788_AD |
- AD |
- NA |
- 6785_CR_A_2385 |
-
-
- | 580 |
- HB_789_AD |
- AD |
- NA |
- 6787_CR_A_2388 |
-
-
- | 581 |
- HB_791_AD |
- AD |
- NA |
- 6790_PF_A_2392 |
-
-
- | 582 |
- HB_792_AD |
- AD |
- NA |
- 6791_PF_A_2395 |
-
-
- | 583 |
- HB_793_AD |
- AD |
- NA |
- 6793_PF_A_2398 |
-
-
- | 584 |
- HB_794_AD |
- AD |
- NA |
- 6794_PF_A_2401 |
-
-
- | 585 |
- HB_795_AD |
- AD |
- NA |
- 6797_PF_A_2404 |
-
-
- | 586 |
- HB_796_AD |
- AD |
- NA |
- 6798_PF_A_2407 |
-
-
- | 587 |
- HB_797_AD |
- AD |
- NA |
- 6799_VC_A_2411 |
-
-
- | 588 |
- HB_798_AD |
- AD |
- NA |
- 6801_VC_A_2414 |
-
-
- | 589 |
- HB_799_AD |
- AD |
- NA |
- 6803_VC_A_2417 |
-
-
- | 590 |
- HB_801_AD |
- AD |
- NA |
- 6809_PF_A_2422 |
-
-
- | 591 |
- HB_803_AD |
- AD |
- NA |
- 6818_CR_A_2430 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/HBTRC_MLVC_AD_0611/notes.rtf b/general/datasets/HBTRC_MLVC_AD_0611/notes.rtf
deleted file mode 100644
index ff90e34..0000000
--- a/general/datasets/HBTRC_MLVC_AD_0611/notes.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Species: Human
-Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
-Disease: Neurological Disease
-Investigator: Francine Benes/ Eric Schadt
-Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
-Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC_MLVC_AD_0611/summary.rtf b/general/datasets/HBTRC_MLVC_AD_0611/summary.rtf
deleted file mode 100644
index 5cde3bf..0000000
--- a/general/datasets/HBTRC_MLVC_AD_0611/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC_MLVC_HD_0611/acknowledgment.rtf b/general/datasets/HBTRC_MLVC_HD_0611/acknowledgment.rtf
deleted file mode 100644
index 208cb6e..0000000
--- a/general/datasets/HBTRC_MLVC_HD_0611/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC_MLVC_HD_0611/cases.rtf b/general/datasets/HBTRC_MLVC_HD_0611/cases.rtf
deleted file mode 100644
index 86ed08e..0000000
--- a/general/datasets/HBTRC_MLVC_HD_0611/cases.rtf
+++ /dev/null
@@ -1,4166 +0,0 @@
-This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- | Series |
- Cerebellum in GN |
- Condition |
- Gender |
- BioSample Name |
-
-
- | 1 |
- HB_029_N |
- N |
- NA |
- 3405_VC_N_0859 |
-
-
- | 2 |
- HB_058_N |
- N |
- NA |
- 4021_VC_N_0854 |
-
-
- | 3 |
- HB_064_N |
- N |
- NA |
- 4338_VC_N_0861 |
-
-
- | 4 |
- HB_086_N |
- N |
- NA |
- 4729_PF_N_0756 |
-
-
- | 5 |
- HB_091_N |
- N |
- NA |
- 4741_VC_N_0864 |
-
-
- | 6 |
- HB_092_N |
- N |
- NA |
- 4744_VC_N_0865 |
-
-
- | 7 |
- HB_102_N |
- N |
- NA |
- 4810_VC_N_0869 |
-
-
- | 8 |
- HB_119_N |
- N |
- NA |
- 4872_VC_N_0878 |
-
-
- | 9 |
- HB_147_N |
- N |
- NA |
- 5021_VC_N_0852 |
-
-
- | 10 |
- HB_161_N |
- N |
- NA |
- 5077_VC_N_0851 |
-
-
- | 11 |
- HB_162_N |
- N |
- NA |
- 5081_VC_N_1021 |
-
-
- | 12 |
- HB_166_N |
- N |
- NA |
- 5095_VC_N_1024 |
-
-
- | 13 |
- HB_183_N |
- N |
- NA |
- 5162_VC_N_0850 |
-
-
- | 14 |
- HB_206_N |
- N |
- NA |
- 5245_VC_N_0849 |
-
-
- | 15 |
- HB_215_N |
- N |
- NA |
- 5270_VC_N_0848 |
-
-
- | 16 |
- HB_218_N |
- N |
- NA |
- 5276_CR_N_0912 |
-
-
- | 17 |
- HB_223_N |
- N |
- NA |
- 5287_VC_N_0916 |
-
-
- | 18 |
- HB_226_N |
- N |
- NA |
- 5294_VC_N_0919 |
-
-
- | 19 |
- HB_241_N |
- N |
- NA |
- 5326_CR_N_0652 |
-
-
- | 20 |
- HB_243_N |
- N |
- NA |
- 5333_VC_N_1262 |
-
-
- | 21 |
- HB_247_N |
- N |
- NA |
- 5341_VC_N_0923 |
-
-
- | 22 |
- HB_257_N |
- N |
- NA |
- 5368_PF_N_1032 |
-
-
- | 23 |
- HB_264_N |
- N |
- NA |
- 5384_VC_N_0924 |
-
-
- | 24 |
- HB_295_N |
- N |
- NA |
- 5452_VC_N_1268 |
-
-
- | 25 |
- HB_300_N |
- N |
- NA |
- 5463_VC_N_0845 |
-
-
- | 26 |
- HB_311_N |
- N |
- NA |
- 5489_CR_N_0942 |
-
-
- | 27 |
- HB_324_N |
- N |
- NA |
- 5531_VC_N_0844 |
-
-
- | 28 |
- HB_332_N |
- N |
- NA |
- 5547_VC_N_0843 |
-
-
- | 29 |
- HB_340_N |
- N |
- NA |
- 5568_VC_N_0842 |
-
-
- | 30 |
- HB_360_N |
- N |
- NA |
- 5619_CR_N_0645 |
-
-
- | 31 |
- HB_365_N |
- N |
- NA |
- 5632_VC_N_0838 |
-
-
- | 32 |
- HB_367_N |
- N |
- NA |
- 5637_VC_N_0837 |
-
-
- | 33 |
- HB_382_N |
- N |
- NA |
- 5684_PF_N_1270 |
-
-
- | 34 |
- HB_396_N |
- N |
- NA |
- 5718_VC_N_0956 |
-
-
- | 35 |
- HB_398_N |
- N |
- NA |
- 5722_VC_N_1044 |
-
-
- | 36 |
- HB_400_N |
- N |
- NA |
- 5726_VC_N_0834_Bis |
-
-
- | 37 |
- HB_403_N |
- N |
- NA |
- 5734_VC_N_0833 |
-
-
- | 38 |
- HB_414_N |
- N |
- NA |
- 5772_VC_N_0832_Bis |
-
-
- | 39 |
- HB_416_N |
- N |
- NA |
- 5778_CR_N_0962 |
-
-
- | 40 |
- HB_418_N |
- N |
- NA |
- 5789_PF_N_1273 |
-
-
- | 41 |
- HB_421_N |
- N |
- NA |
- 5799_VC_N_1058 |
-
-
- | 42 |
- HB_423_N |
- N |
- NA |
- 5803_VC_N_0966 |
-
-
- | 43 |
- HB_426_N |
- N |
- NA |
- 5806_PF_N_1064 |
-
-
- | 44 |
- HB_427_N |
- N |
- NA |
- 5810_CR_N_0636 |
-
-
- | 45 |
- HB_431_N |
- N |
- NA |
- 5823_VC_N_0829 |
-
-
- | 46 |
- HB_432_N |
- N |
- NA |
- 5826_VC_N_0828 |
-
-
- | 47 |
- HB_433_N |
- N |
- NA |
- 5827_VC_N_0827 |
-
-
- | 48 |
- HB_436_N |
- N |
- NA |
- 5832_PF_N_1145 |
-
-
- | 49 |
- HB_443_N |
- N |
- NA |
- 5852_VC_N_0826 |
-
-
- | 50 |
- HB_446_N |
- N |
- NA |
- 5859_VC_N_0825 |
-
-
- | 51 |
- HB_449_N |
- N |
- NA |
- 5866_VC_N_0824 |
-
-
- | 52 |
- HB_450_N |
- N |
- NA |
- 5867_VC_N_1277 |
-
-
- | 53 |
- HB_453_N |
- N |
- NA |
- 5876_VC_N_0823 |
-
-
- | 54 |
- HB_462_N |
- N |
- NA |
- 5903_VC_N_0822 |
-
-
- | 55 |
- HB_464_N |
- N |
- NA |
- 5905_VC_N_0820 |
-
-
- | 56 |
- HB_468_N |
- N |
- NA |
- 5912_VC_N_1286 |
-
-
- | 57 |
- HB_472_N |
- N |
- NA |
- 5925_VC_N_1289 |
-
-
- | 58 |
- HB_475_N |
- N |
- NA |
- 5936_VC_N_0979 |
-
-
- | 59 |
- HB_476_N |
- N |
- NA |
- 5938_VC_N_0819 |
-
-
- | 60 |
- HB_480_N |
- N |
- NA |
- 5946_VC_N_0985 |
-
-
- | 61 |
- HB_485_N |
- N |
- NA |
- 5959_VC_N_0818 |
-
-
- | 62 |
- HB_486_N |
- N |
- NA |
- 5963_VC_N_0987 |
-
-
- | 63 |
- HB_495_N |
- N |
- NA |
- 5980_VC_N_0989 |
-
-
- | 64 |
- HB_497_N |
- N |
- NA |
- 5985_VC_N_0990 |
-
-
- | 65 |
- HB_500_N |
- N |
- NA |
- 5990_VC_N_0817 |
-
-
- | 66 |
- HB_501_N |
- N |
- NA |
- 5991_VC_N_0816 |
-
-
- | 67 |
- HB_504_N |
- N |
- NA |
- 5996_VC_N_0815 |
-
-
- | 68 |
- HB_505_N |
- N |
- NA |
- 5998_VC_N_0814 |
-
-
- | 69 |
- HB_507_N |
- N |
- NA |
- 6006_VC_N_0813 |
-
-
- | 70 |
- HB_508_N |
- N |
- NA |
- 6007_CR_N_0618 |
-
-
- | 71 |
- HB_509_N |
- N |
- NA |
- 6008_PF_N_1081 |
-
-
- | 72 |
- HB_512_N |
- N |
- NA |
- 6023_PF_N_1155 |
-
-
- | 73 |
- HB_516_N |
- N |
- NA |
- 6030_VC_N_0810 |
-
-
- | 74 |
- HB_519_N |
- N |
- NA |
- 6034_VC_N_0809 |
-
-
- | 75 |
- HB_532_N |
- N |
- NA |
- 6060_VC_N_1292 |
-
-
- | 76 |
- HB_541_N |
- N |
- NA |
- 6092_VC_N_1001 |
-
-
- | 77 |
- HB_542_N |
- N |
- NA |
- 6096_VC_N_0807 |
-
-
- | 78 |
- HB_544_N |
- N |
- NA |
- 6101_CR_N_1161 |
-
-
- | 79 |
- HB_547_N |
- N |
- NA |
- 6110_VC_N_1295 |
-
-
- | 80 |
- HB_551_N |
- N |
- NA |
- 6124_VC_N_0806 |
-
-
- | 81 |
- HB_557_N |
- N |
- NA |
- 6134_PF_N_1297 |
-
-
- | 82 |
- HB_560_N |
- N |
- NA |
- 6142_VC_N_0805 |
-
-
- | 83 |
- HB_569_N |
- N |
- NA |
- 6166_VC_N_0804 |
-
-
- | 84 |
- HB_570_N |
- N |
- NA |
- 6170_VC_N_0803 |
-
-
- | 85 |
- HB_572_N |
- N |
- NA |
- 6172_VC_N_1008 |
-
-
- | 86 |
- HB_577_N |
- N |
- NA |
- 6182_VC_N_1166 |
-
-
- | 87 |
- HB_579_N |
- N |
- NA |
- 6187_CR_N_0607 |
-
-
- | 88 |
- HB_581_N |
- N |
- NA |
- 6191_VC_N_1010 |
-
-
- | 89 |
- HB_584_N |
- N |
- NA |
- 6196_CR_N_0605 |
-
-
- | 90 |
- HB_586_N |
- N |
- NA |
- 6200_VC_N_0799 |
-
-
- | 91 |
- HB_587_N |
- N |
- NA |
- 6206_PF_N_1176 |
-
-
- | 92 |
- HB_589_N |
- N |
- NA |
- 6213_VC_N_0798 |
-
-
- | 93 |
- HB_601_N |
- N |
- NA |
- 6241_VC_N_0796 |
-
-
- | 94 |
- HB_604_N |
- N |
- NA |
- 6260_VC_N_0794 |
-
-
- | 95 |
- HB_609_N |
- N |
- NA |
- 6270_VC_N_0793 |
-
-
- | 96 |
- HB_618_N |
- N |
- NA |
- 6289_VC_N_0791 |
-
-
- | 97 |
- HB_622_N |
- N |
- NA |
- 6310_VC_N_0790 |
-
-
- | 98 |
- HB_625_N |
- N |
- NA |
- 6314_VC_N_0789 |
-
-
- | 99 |
- HB_637_N |
- N |
- NA |
- 6340_VC_N_0786 |
-
-
- | 100 |
- HB_638_N |
- N |
- NA |
- 6341_VC_N_0785 |
-
-
- | 101 |
- HB_640_N |
- N |
- NA |
- 6347_VC_N_0784 |
-
-
- | 102 |
- HB_641_N |
- N |
- NA |
- 6356_VC_N_0783 |
-
-
- | 103 |
- HB_643_N |
- N |
- NA |
- 6363_VC_N_0781 |
-
-
- | 104 |
- HB_644_N |
- N |
- NA |
- 6366_VC_N_0780 |
-
-
- | 105 |
- HB_645_N |
- N |
- NA |
- 6374_VC_N_0779 |
-
-
- | 106 |
- HB_650_N |
- N |
- NA |
- 6384_VC_N_0777 |
-
-
- | 107 |
- HB_651_N |
- N |
- NA |
- 6386_VC_N_0776 |
-
-
- | 108 |
- HB_653_N |
- N |
- NA |
- 6388_VC_N_0775 |
-
-
- | 109 |
- HB_659_N |
- N |
- NA |
- 6406_VC_N_1180 |
-
-
- | 110 |
- HB_662_N |
- N |
- NA |
- 6411_VC_N_0771 |
-
-
- | 111 |
- HB_663_N |
- N |
- NA |
- 6415_VC_N_0770 |
-
-
- | 112 |
- HB_670_N |
- N |
- NA |
- 6436_VC_N_0769 |
-
-
- | 113 |
- HB_687_N |
- N |
- NA |
- 6484_VC_N_0765 |
-
-
- | 114 |
- HB_689_N |
- N |
- NA |
- 6486_VC_N_0764 |
-
-
- | 115 |
- HB_694_N |
- N |
- NA |
- 6500_VC_N_0763 |
-
-
- | 116 |
- HB_697_N |
- N |
- NA |
- 6512_VC_N_0762 |
-
-
- | 117 |
- HB_700_N |
- N |
- NA |
- 6520_VC_N_0761 |
-
-
- | 118 |
- HB_711_N |
- N |
- NA |
- 6543_PF_N_1191 |
-
-
- | 119 |
- HB_714_N |
- N |
- NA |
- 6549_VC_N_1198 |
-
-
- | 120 |
- HB_717_N |
- N |
- NA |
- 6553_PF_N_2284 |
-
-
- | 121 |
- HB_721_N |
- N |
- NA |
- 6560_VC_N_2578 |
-
-
- | 122 |
- HB_726_N |
- N |
- NA |
- 6573_PF_N_2293 |
-
-
- | 123 |
- HB_730_N |
- N |
- NA |
- 6580_VC_N_2306 |
-
-
- | 124 |
- HB_735_N |
- N |
- NA |
- 6588_VC_N_1213 |
-
-
- | 125 |
- HB_737_N |
- N |
- NA |
- 6593_VC_N_1219 |
-
-
- | 126 |
- HB_738_N |
- N |
- NA |
- 6594_VC_N_1222 |
-
-
- | 127 |
- HB_759_N |
- N |
- NA |
- 6645_VC_N_1231 |
-
-
- | 128 |
- HB_764_N |
- N |
- NA |
- 6655_VC_N_1240 |
-
-
- | 129 |
- HB_765_N |
- N |
- NA |
- 6656_VC_N_1243 |
-
-
- | 130 |
- HB_767_N |
- N |
- NA |
- 6661_PF_N_2341 |
-
-
- | 131 |
- HB_770_N |
- N |
- NA |
- 6669_VC_N_1246 |
-
-
- | 132 |
- HB_772_N |
- N |
- NA |
- 6676_PF_N_1248 |
-
-
- | 133 |
- HB_001_HD |
- HD |
- F |
- 2028_CR_H_2282 |
-
-
- | 134 |
- HB_003_HD |
- HD |
- F |
- 2685_PF_H_2212 |
-
-
- | 135 |
- HB_004_HD |
- HD |
- M |
- 2706_CR_H_2432 |
-
-
- | 136 |
- HB_006_HD |
- HD |
- M |
- 2737_VC_H_2194 |
-
-
- | 137 |
- HB_007_HD |
- HD |
- NA |
- 2769_VC_H_2193 |
-
-
- | 138 |
- HB_008_HD |
- HD |
- F |
- 2790_CR_H_1890 |
-
-
- | 139 |
- HB_009_HD |
- HD |
- NA |
- 2879_VC_H_2192 |
-
-
- | 140 |
- HB_010_HD |
- HD |
- M |
- 2960_VC_H_2002 |
-
-
- | 141 |
- HB_011_HD |
- HD |
- F |
- 3053_VC_H_2001 |
-
-
- | 142 |
- HB_012_HD |
- HD |
- F |
- 3128_VC_H_1999 |
-
-
- | 143 |
- HB_014_HD |
- HD |
- F |
- 3149_PF_H_2110 |
-
-
- | 144 |
- HB_015_HD |
- HD |
- F |
- 3150_VC_H_1996 |
-
-
- | 145 |
- HB_016_HD |
- HD |
- F |
- 3177_VC_H_2191 |
-
-
- | 146 |
- HB_017_HD |
- HD |
- NA |
- 3195_VC_H_2190 |
-
-
- | 147 |
- HB_018_HD |
- HD |
- M |
- 3200_VC_H_2189 |
-
-
- | 148 |
- HB_019_HD |
- HD |
- M |
- 3209_VC_H_2188 |
-
-
- | 149 |
- HB_020_HD |
- HD |
- M |
- 3224_VC_H_1994 |
-
-
- | 150 |
- HB_022_HD |
- HD |
- F |
- 3242_PF_H_2105 |
-
-
- | 151 |
- HB_024_HD |
- HD |
- NA |
- 3272_VC_H_2186 |
-
-
- | 152 |
- HB_027_HD |
- HD |
- M |
- 3356_VC_H_2439 |
-
-
- | 153 |
- HB_028_HD |
- HD |
- F |
- 3394_PF_H_2104 |
-
-
- | 154 |
- HB_031_HD |
- HD |
- M |
- 3430_VC_H_1990 |
-
-
- | 155 |
- HB_032_HD |
- HD |
- NA |
- 3444_PF_H_2208 |
-
-
- | 156 |
- HB_034_HD |
- HD |
- F |
- 3482_VC_H_1987 |
-
-
- | 157 |
- HB_036_HD |
- HD |
- M |
- 3576_VC_H_1984 |
-
-
- | 158 |
- HB_037_HD |
- HD |
- F |
- 3579_VC_H_1983 |
-
-
- | 159 |
- HB_038_HD |
- HD |
- F |
- 3584_VC_H_2183 |
-
-
- | 160 |
- HB_039_HD |
- HD |
- NA |
- 3635_VC_H_2182 |
-
-
- | 161 |
- HB_041_HD |
- HD |
- F |
- 3695_CR_H_2267 |
-
-
- | 162 |
- HB_042_HD |
- HD |
- M |
- 3697_VC_H_1982 |
-
-
- | 163 |
- HB_043_HD |
- HD |
- NA |
- 3703_VC_H_2180 |
-
-
- | 164 |
- HB_044_HD |
- HD |
- NA |
- 3723_VC_H_2179 |
-
-
- | 165 |
- HB_046_HD |
- HD |
- F |
- 3735_VC_H_1981 |
-
-
- | 166 |
- HB_050_HD |
- HD |
- M |
- 3820_PF_H_2207 |
-
-
- | 167 |
- HB_051_HD |
- HD |
- F |
- 3849_CR_H_2262 |
-
-
- | 168 |
- HB_054_HD |
- HD |
- M |
- 3884_VC_H_2175 |
-
-
- | 169 |
- HB_056_HD |
- HD |
- NA |
- 4012_VC_H_2174 |
-
-
- | 170 |
- HB_057_HD |
- HD |
- NA |
- 4013_VC_H_2173 |
-
-
- | 171 |
- HB_059_HD |
- HD |
- NA |
- 4066_VC_H_2172 |
-
-
- | 172 |
- HB_060_HD |
- HD |
- NA |
- 4094_VC_H_2171 |
-
-
- | 173 |
- HB_061_HD |
- HD |
- F |
- 4116_VC_H_2170 |
-
-
- | 174 |
- HB_062_HD |
- HD |
- NA |
- 4121_VC_H_2169 |
-
-
- | 175 |
- HB_063_HD |
- HD |
- NA |
- 4215_VC_H_2167 |
-
-
- | 176 |
- HB_065_HD |
- HD |
- M |
- 4340_PF_H_2091 |
-
-
- | 177 |
- HB_066_HD |
- HD |
- F |
- 4344_VC_H_1977 |
-
-
- | 178 |
- HB_067_HD |
- HD |
- M |
- 4346_VC_H_2165 |
-
-
- | 179 |
- HB_069_HD |
- HD |
- F |
- 4356_VC_H_2164 |
-
-
- | 180 |
- HB_070_HD |
- HD |
- NA |
- 4386_CR_H_2249 |
-
-
- | 181 |
- HB_072_HD |
- HD |
- NA |
- 4404_VC_H_2161 |
-
-
- | 182 |
- HB_073_HD |
- HD |
- F |
- 4411_VC_H_1975 |
-
-
- | 183 |
- HB_074_HD |
- HD |
- NA |
- 4430_VC_H_2465 |
-
-
- | 184 |
- HB_075_HD |
- HD |
- M |
- 4470_VC_H_1974 |
-
-
- | 185 |
- HB_076_HD |
- HD |
- F |
- 4497_CR_H_1860 |
-
-
- | 186 |
- HB_077_HD |
- HD |
- M |
- 4509_CR_H_2244 |
-
-
- | 187 |
- HB_079_HD |
- HD |
- M |
- 4631_VC_H_1971 |
-
-
- | 188 |
- HB_080_HD |
- HD |
- F |
- 4653_PF_H_2083 |
-
-
- | 189 |
- HB_081_HD |
- HD |
- NA |
- 4678_CR_H_2242 |
-
-
- | 190 |
- HB_084_HD |
- HD |
- M |
- 4718_VC_H_2125 |
-
-
- | 191 |
- HB_090_HD |
- HD |
- NA |
- 4740_CR_H_2474 |
-
-
- | 192 |
- HB_094_HD |
- HD |
- NA |
- 4754_CR_H_2476 |
-
-
- | 193 |
- HB_098_HD |
- HD |
- NA |
- 4780_VC_H_2151 |
-
-
- | 194 |
- HB_101_HD |
- HD |
- F |
- 4809_VC_H_2148 |
-
-
- | 195 |
- HB_105_HD |
- HD |
- NA |
- 4819_CR_H_2238 |
-
-
- | 196 |
- HB_106_HD |
- HD |
- F |
- 4822_VC_H_1969 |
-
-
- | 197 |
- HB_108_HD |
- HD |
- M |
- 4826_VC_H_1968 |
-
-
- | 198 |
- HB_109_HD |
- HD |
- M |
- 4828_VC_H_2124 |
-
-
- | 199 |
- HB_115_HD |
- HD |
- NA |
- 4855_CR_H_2235 |
-
-
- | 200 |
- HB_121_HD |
- HD |
- F |
- 4902_VC_H_1967 |
-
-
- | 201 |
- HB_129_HD |
- HD |
- NA |
- 4938_VC_H_1966 |
-
-
- | 202 |
- HB_141_HD |
- HD |
- F |
- 4996_PF_H_2076 |
-
-
- | 203 |
- HB_152_HD |
- HD |
- NA |
- 5034_CR_H_2233 |
-
-
- | 204 |
- HB_153_HD |
- HD |
- M |
- 5043_VC_H_1960 |
-
-
- | 205 |
- HB_159_HD |
- HD |
- M |
- 5062_VC_H_1959 |
-
-
- | 206 |
- HB_172_HD |
- HD |
- F |
- 5114_PF_H_2070 |
-
-
- | 207 |
- HB_175_HD |
- HD |
- M |
- 5127_PF_H_2068 |
-
-
- | 208 |
- HB_180_HD |
- HD |
- M |
- 5148_VC_H_1944 |
-
-
- | 209 |
- HB_185_HD |
- HD |
- F |
- 5167_CR_H_2231 |
-
-
- | 210 |
- HB_188_HD |
- HD |
- F |
- 5172_VC_H_1951 |
-
-
- | 211 |
- HB_191_HD |
- HD |
- M |
- 5180_VC_H_1949 |
-
-
- | 212 |
- HB_196_HD |
- HD |
- NA |
- 5199_PF_H_2202 |
-
-
- | 213 |
- HB_203_HD |
- HD |
- F |
- 5228_PF_H_2059 |
-
-
- | 214 |
- HB_207_HD |
- HD |
- NA |
- 5248_PF_H_2201 |
-
-
- | 215 |
- HB_228_HD |
- HD |
- F |
- 5299_CR_H_2228 |
-
-
- | 216 |
- HB_233_HD |
- HD |
- M |
- 5312_VC_H_1938 |
-
-
- | 217 |
- HB_235_HD |
- HD |
- F |
- 5316_VC_H_1937 |
-
-
- | 218 |
- HB_242_HD |
- HD |
- F |
- 5328_PF_H_2048 |
-
-
- | 219 |
- HB_266_HD |
- HD |
- M |
- 5387_VC_H_1928 |
-
-
- | 220 |
- HB_271_HD |
- HD |
- M |
- 5394_PF_H_2039 |
-
-
- | 221 |
- HB_272_HD |
- HD |
- F |
- 5396_VC_H_1925 |
-
-
- | 222 |
- HB_279_HD |
- HD |
- F |
- 5409_VC_H_1924 |
-
-
- | 223 |
- HB_294_HD |
- HD |
- M |
- 5448_VC_H_1921 |
-
-
- | 224 |
- HB_301_HD |
- HD |
- NA |
- 5464_VC_H_1919 |
-
-
- | 225 |
- HB_304_HD |
- HD |
- F |
- 5471_VC_H_1918 |
-
-
- | 226 |
- HB_321_HD |
- HD |
- NA |
- 5522_PF_H_2199 |
-
-
- | 227 |
- HB_361_HD |
- HD |
- F |
- 5622_VC_H_2121 |
-
-
- | 228 |
- HB_370_HD |
- HD |
- M |
- 5645_VC_H_1904 |
-
-
- | 229 |
- HB_371_HD |
- HD |
- F |
- 5648_PF_H_2016 |
-
-
- | 230 |
- HB_384_HD |
- HD |
- F |
- 5688_PF_H_2012 |
-
-
- | 231 |
- HB_390_HD |
- HD |
- M |
- 5704_PF_H_2009 |
-
-
- | 232 |
- HB_393_HD |
- HD |
- F |
- 5709_VC_H_1895 |
-
-
- | 233 |
- HB_402_HD |
- HD |
- F |
- 5732_PF_H_2007 |
-
-
- | 234 |
- HB_405_HD |
- HD |
- NA |
- 5742_PF_H_2006 |
-
-
- | 235 |
- HB_407_HD |
- HD |
- M |
- 5745_PF_H_2005 |
-
-
- | 236 |
- HB_408_HD |
- HD |
- M |
- 5747_VC_H_1891 |
-
-
- | 237 |
- HB_415_HD |
- HD |
- NA |
- 5777_PF_H_1551 |
-
-
- | 238 |
- HB_417_HD |
- HD |
- M |
- 5784_PF_H_1554 |
-
-
- | 239 |
- HB_424_HD |
- HD |
- M |
- 5804_VC_H_1558 |
-
-
- | 240 |
- HB_444_HD |
- HD |
- M |
- 5856_VC_H_1567 |
-
-
- | 241 |
- HB_457_HD |
- HD |
- M |
- 5896_VC_H_1570 |
-
-
- | 242 |
- HB_466_HD |
- HD |
- M |
- 5910_PF_H_1572 |
-
-
- | 243 |
- HB_478_HD |
- HD |
- M |
- 5941_CR_H_1583 |
-
-
- | 244 |
- HB_487_HD |
- HD |
- F |
- 5964_VC_H_1597 |
-
-
- | 245 |
- HB_511_HD |
- HD |
- M |
- 6019_PF_H_2198 |
-
-
- | 246 |
- HB_513_HD |
- HD |
- F |
- 6024_VC_H_1612 |
-
-
- | 247 |
- HB_515_HD |
- HD |
- F |
- 6028_CR_H_1613 |
-
-
- | 248 |
- HB_518_HD |
- HD |
- M |
- 6033_VC_H_1618 |
-
-
- | 249 |
- HB_522_HD |
- HD |
- M |
- 6037_PF_H_1626 |
-
-
- | 250 |
- HB_527_HD |
- HD |
- F |
- 6047_VC_H_1639 |
-
-
- | 251 |
- HB_528_HD |
- HD |
- M |
- 6051_PF_H_1641 |
-
-
- | 252 |
- HB_530_HD |
- HD |
- M |
- 6054_VC_H_1648 |
-
-
- | 253 |
- HB_537_HD |
- HD |
- F |
- 6071_PF_H_1653 |
-
-
- | 254 |
- HB_549_HD |
- HD |
- M |
- 6119_CR_H_1670 |
-
-
- | 255 |
- HB_593_HD |
- HD |
- NA |
- 6219_CR_H_2567 |
-
-
- | 256 |
- HB_610_HD |
- HD |
- NA |
- 6275_PF_H_1692 |
-
-
- | 257 |
- HB_616_HD |
- HD |
- F |
- 6284_CR_H_1694 |
-
-
- | 258 |
- HB_626_HD |
- HD |
- M |
- 6315_VC_H_1702 |
-
-
- | 259 |
- HB_639_HD |
- HD |
- F |
- 6344_CR_H_1703 |
-
-
- | 260 |
- HB_649_HD |
- HD |
- F |
- 6382_CR_H_1709 |
-
-
- | 261 |
- HB_661_HD |
- HD |
- M |
- 6408_VC_H_1714 |
-
-
- | 262 |
- HB_682_HD |
- HD |
- M |
- 6467_PF_H_1725 |
-
-
- | 263 |
- HB_683_HD |
- HD |
- M |
- 6472_VC_H_1729 |
-
-
- | 264 |
- HB_691_HD |
- HD |
- F |
- 6493_VC_H_1732 |
-
-
- | 265 |
- HB_692_HD |
- HD |
- M |
- 6495_CR_H_1733 |
-
-
- | 266 |
- HB_707_HD |
- HD |
- M |
- 6535_PF_H_1737 |
-
-
- | 267 |
- HB_709_HD |
- HD |
- F |
- 6539_CR_H_1739 |
-
-
- | 268 |
- HB_725_HD |
- HD |
- M |
- 6572_PF_H_1746 |
-
-
- | 269 |
- HB_732_HD |
- HD |
- F |
- 6584_VC_H_1750 |
-
-
- | 270 |
- HB_734_HD |
- HD |
- F |
- 6587_CR_H_1751 |
-
-
- | 271 |
- HB_748_HD |
- HD |
- NA |
- 6615_VC_H_2315 |
-
-
- | 272 |
- HB_750_HD |
- HD |
- NA |
- 6628_PF_H_2326 |
-
-
- | 273 |
- HB_758_HD |
- HD |
- NA |
- 6643_VC_H_2602 |
-
-
- | 274 |
- HB_760_HD |
- HD |
- M |
- 6646_PF_H_1761 |
-
-
- | 275 |
- HB_762_HD |
- HD |
- M |
- 6650_VC_H_1765 |
-
-
- | 276 |
- HB_766_HD |
- HD |
- M |
- 6658_VC_H_1768 |
-
-
- | 277 |
- HB_768_HD |
- HD |
- NA |
- 6663_VC_H_1771 |
-
-
- | 278 |
- HB_769_HD |
- HD |
- M |
- 6666_VC_H_1774 |
-
-
- | 279 |
- HB_774_HD |
- HD |
- NA |
- 6689_PF_H_2344 |
-
-
- | 280 |
- HB_778_HD |
- HD |
- NA |
- 6696_PF_H_2356 |
-
-
- | 281 |
- HB_780_HD |
- HD |
- NA |
- 6704_PF_H_2362 |
-
-
- | 282 |
- HB_790_HD |
- HD |
- NA |
- 6788_PF_H_2389 |
-
-
- | 283 |
- HB_800_HD |
- HD |
- NA |
- 6807_PF_H_2419 |
-
-
- | 284 |
- HB_802_HD |
- HD |
- NA |
- 6811_PF_H_2425 |
-
-
- | 285 |
- HB_045_AD |
- AD |
- NA |
- 3734_CR_A_0122 |
-
-
- | 286 |
- HB_048_AD |
- AD |
- NA |
- 3791_CR_A_0128 |
-
-
- | 287 |
- HB_053_AD |
- AD |
- NA |
- 3877_CR_A_0134 |
-
-
- | 288 |
- HB_055_AD |
- AD |
- NA |
- 3893_VC_A_0142 |
-
-
- | 289 |
- HB_068_AD |
- AD |
- NA |
- 4349_VC_A_0148 |
-
-
- | 290 |
- HB_082_AD |
- AD |
- NA |
- 4712_CR_A_0309 |
-
-
- | 291 |
- HB_085_AD |
- AD |
- NA |
- 4726_VC_A_0311 |
-
-
- | 292 |
- HB_087_AD |
- AD |
- NA |
- 4730_CR_A_0315 |
-
-
- | 293 |
- HB_089_AD |
- AD |
- NA |
- 4733_VC_A_0320 |
-
-
- | 294 |
- HB_093_AD |
- AD |
- NA |
- 4749_VC_A_0323 |
-
-
- | 295 |
- HB_095_AD |
- AD |
- NA |
- 4759_CR_A_0327 |
-
-
- | 296 |
- HB_097_AD |
- AD |
- NA |
- 4773_CR_A_0866 |
-
-
- | 297 |
- HB_099_AD |
- AD |
- NA |
- 4785_VC_A_0332 |
-
-
- | 298 |
- HB_100_AD |
- AD |
- NA |
- 4795_VC_A_0335 |
-
-
- | 299 |
- HB_103_AD |
- AD |
- NA |
- 4811_VC_A_0341 |
-
-
- | 300 |
- HB_104_AD |
- AD |
- NA |
- 4813_CR_A_0345 |
-
-
- | 301 |
- HB_112_AD |
- AD |
- NA |
- 4842_VC_A_0870 |
-
-
- | 302 |
- HB_113_AD |
- AD |
- NA |
- 4850_CR_A_0351 |
-
-
- | 303 |
- HB_114_AD |
- AD |
- NA |
- 4852_CR_A_0354 |
-
-
- | 304 |
- HB_117_AD |
- AD |
- NA |
- 4868_VC_A_0874 |
-
-
- | 305 |
- HB_122_AD |
- AD |
- NA |
- 4904_CR_A_1132 |
-
-
- | 306 |
- HB_123_AD |
- AD |
- NA |
- 4905_VC_A_0884 |
-
-
- | 307 |
- HB_124_AD |
- AD |
- NA |
- 4916_VC_A_0886 |
-
-
- | 308 |
- HB_125_AD |
- AD |
- NA |
- 4917_CR_A_0360 |
-
-
- | 309 |
- HB_126_AD |
- AD |
- NA |
- 4921_VC_A_0362 |
-
-
- | 310 |
- HB_128_AD |
- AD |
- NA |
- 4936_CR_A_0369 |
-
-
- | 311 |
- HB_130_AD |
- AD |
- NA |
- 4939_VC_A_0888 |
-
-
- | 312 |
- HB_131_AD |
- AD |
- NA |
- 4944_CR_A_0889 |
-
-
- | 313 |
- HB_132_AD |
- AD |
- NA |
- 4946_CR_A_0372 |
-
-
- | 314 |
- HB_134_AD |
- AD |
- NA |
- 4951_CR_A_0891 |
-
-
- | 315 |
- HB_135_AD |
- AD |
- NA |
- 4953_VC_A_0893 |
-
-
- | 316 |
- HB_136_AD |
- AD |
- NA |
- 4965_VC_A_0160 |
-
-
- | 317 |
- HB_137_AD |
- AD |
- NA |
- 4966_VC_A_0374 |
-
-
- | 318 |
- HB_138_AD |
- AD |
- NA |
- 4969_VC_A_0895 |
-
-
- | 319 |
- HB_140_AD |
- AD |
- NA |
- 4993_CR_A_0896 |
-
-
- | 320 |
- HB_146_AD |
- AD |
- NA |
- 5018_CR_A_0384 |
-
-
- | 321 |
- HB_148_AD |
- AD |
- NA |
- 5022_VC_A_0386 |
-
-
- | 322 |
- HB_150_AD |
- AD |
- NA |
- 5031_VC_A_0392 |
-
-
- | 323 |
- HB_151_AD |
- AD |
- NA |
- 5033_CR_A_0396 |
-
-
- | 324 |
- HB_154_AD |
- AD |
- NA |
- 5048_VC_A_1321 |
-
-
- | 325 |
- HB_155_AD |
- AD |
- NA |
- 5056_VC_A_0398 |
-
-
- | 326 |
- HB_156_AD |
- AD |
- NA |
- 5057_VC_A_0163 |
-
-
- | 327 |
- HB_157_AD |
- AD |
- NA |
- 5059_VC_A_0401 |
-
-
- | 328 |
- HB_158_AD |
- AD |
- NA |
- 5061_PF_A_2612 |
-
-
- | 329 |
- HB_160_AD |
- AD |
- NA |
- 5064_PF_A_2615 |
-
-
- | 330 |
- HB_165_AD |
- AD |
- NA |
- 5092_CR_A_0899 |
-
-
- | 331 |
- HB_168_AD |
- AD |
- NA |
- 5097_VC_A_0407 |
-
-
- | 332 |
- HB_170_AD |
- AD |
- NA |
- 5101_VC_A_0410 |
-
-
- | 333 |
- HB_174_AD |
- AD |
- NA |
- 5124_PF_A_1343 |
-
-
- | 334 |
- HB_179_AD |
- AD |
- NA |
- 5145_VC_A_1351 |
-
-
- | 335 |
- HB_181_AD |
- AD |
- NA |
- 5152_CR_A_0414 |
-
-
- | 336 |
- HB_184_AD |
- AD |
- NA |
- 5166_VC_A_1354 |
-
-
- | 337 |
- HB_194_AD |
- AD |
- NA |
- 5193_VC_A_1360 |
-
-
- | 338 |
- HB_197_AD |
- AD |
- NA |
- 5202_CR_A_1368 |
-
-
- | 339 |
- HB_199_AD |
- AD |
- NA |
- 5205_VC_A_0166 |
-
-
- | 340 |
- HB_200_AD |
- AD |
- NA |
- 5210_VC_A_0905 |
-
-
- | 341 |
- HB_205_AD |
- AD |
- NA |
- 5235_VC_A_0419 |
-
-
- | 342 |
- HB_208_AD |
- AD |
- NA |
- 5249_VC_A_0422 |
-
-
- | 343 |
- HB_209_AD |
- AD |
- NA |
- 5252_VC_A_0907 |
-
-
- | 344 |
- HB_211_AD |
- AD |
- NA |
- 5257_VC_A_0169 |
-
-
- | 345 |
- HB_216_AD |
- AD |
- NA |
- 5272_VC_A_0425 |
-
-
- | 346 |
- HB_219_AD |
- AD |
- NA |
- 5279_CR_A_0147 |
-
-
- | 347 |
- HB_221_AD |
- AD |
- NA |
- 5283_VC_A_0145 |
-
-
- | 348 |
- HB_222_AD |
- AD |
- NA |
- 5285_VC_A_0141 |
-
-
- | 349 |
- HB_224_AD |
- AD |
- NA |
- 5288_VC_A_0428 |
-
-
- | 350 |
- HB_230_AD |
- AD |
- NA |
- 5301_VC_A_0174 |
-
-
- | 351 |
- HB_231_AD |
- AD |
- NA |
- 5305_VC_A_1384 |
-
-
- | 352 |
- HB_232_AD |
- AD |
- NA |
- 5310_CR_A_0176 |
-
-
- | 353 |
- HB_234_AD |
- AD |
- NA |
- 5313_PF_A_2618 |
-
-
- | 354 |
- HB_236_AD |
- AD |
- NA |
- 5317_PF_A_2624 |
-
-
- | 355 |
- HB_238_AD |
- AD |
- NA |
- 5322_CR_A_2632 |
-
-
- | 356 |
- HB_240_AD |
- AD |
- NA |
- 5325_VC_A_0137 |
-
-
- | 357 |
- HB_244_AD |
- AD |
- NA |
- 5337_VC_A_1387 |
-
-
- | 358 |
- HB_245_AD |
- AD |
- NA |
- 5339_VC_A_0181 |
-
-
- | 359 |
- HB_250_AD |
- AD |
- NA |
- 5346_VC_A_1393 |
-
-
- | 360 |
- HB_251_AD |
- AD |
- NA |
- 5350_VC_A_0184 |
-
-
- | 361 |
- HB_252_AD |
- AD |
- NA |
- 5355_VC_A_0133 |
-
-
- | 362 |
- HB_253_AD |
- AD |
- NA |
- 5359_CR_A_1395 |
-
-
- | 363 |
- HB_258_AD |
- AD |
- NA |
- 5370_PF_A_1400 |
-
-
- | 364 |
- HB_259_AD |
- AD |
- NA |
- 5371_PF_A_2636 |
-
-
- | 365 |
- HB_260_AD |
- AD |
- NA |
- 5375_VC_A_0188 |
-
-
- | 366 |
- HB_263_AD |
- AD |
- NA |
- 5381_VC_A_0022 |
-
-
- | 367 |
- HB_265_AD |
- AD |
- NA |
- 5385_VC_A_1402 |
-
-
- | 368 |
- HB_267_AD |
- AD |
- NA |
- 5389_VC_A_0928 |
-
-
- | 369 |
- HB_268_AD |
- AD |
- NA |
- 5390_CR_A_0151 |
-
-
- | 370 |
- HB_273_AD |
- AD |
- NA |
- 5400_PF_A_2645 |
-
-
- | 371 |
- HB_274_AD |
- AD |
- NA |
- 5401_VC_A_0931 |
-
-
- | 372 |
- HB_275_AD |
- AD |
- NA |
- 5404_PF_A_2648 |
-
-
- | 373 |
- HB_276_AD |
- AD |
- NA |
- 5406_VC_A_0933 |
-
-
- | 374 |
- HB_277_AD |
- AD |
- NA |
- 5407_PF_A_2651 |
-
-
- | 375 |
- HB_280_AD |
- AD |
- NA |
- 5412_VC_A_0935 |
-
-
- | 376 |
- HB_281_AD |
- AD |
- NA |
- 5413_PF_A_2657 |
-
-
- | 377 |
- HB_283_AD |
- AD |
- NA |
- 5419_VC_A_0937 |
-
-
- | 378 |
- HB_284_AD |
- AD |
- NA |
- 5420_VC_A_0939 |
-
-
- | 379 |
- HB_285_AD |
- AD |
- NA |
- 5421_CR_A_0432 |
-
-
- | 380 |
- HB_286_AD |
- AD |
- NA |
- 5423_PF_A_2660 |
-
-
- | 381 |
- HB_288_AD |
- AD |
- NA |
- 5425_PF_A_2666 |
-
-
- | 382 |
- HB_289_AD |
- AD |
- NA |
- 5426_VC_A_1405 |
-
-
- | 383 |
- HB_290_AD |
- AD |
- NA |
- 5433_VC_A_0434 |
-
-
- | 384 |
- HB_296_AD |
- AD |
- NA |
- 5456_PF_A_2675 |
-
-
- | 385 |
- HB_299_AD |
- AD |
- NA |
- 5461_VC_A_0192 |
-
-
- | 386 |
- HB_302_AD |
- AD |
- NA |
- 5465_PF_A_2678 |
-
-
- | 387 |
- HB_303_AD |
- AD |
- NA |
- 5469_VC_A_1417 |
-
-
- | 388 |
- HB_305_AD |
- AD |
- NA |
- 5479_PF_A_1421 |
-
-
- | 389 |
- HB_306_AD |
- AD |
- NA |
- 5480_VC_A_0437 |
-
-
- | 390 |
- HB_307_AD |
- AD |
- NA |
- 5482_VC_A_0028 |
-
-
- | 391 |
- HB_308_AD |
- AD |
- NA |
- 5483_VC_A_0941 |
-
-
- | 392 |
- HB_309_AD |
- AD |
- NA |
- 5487_CR_A_0441 |
-
-
- | 393 |
- HB_310_AD |
- AD |
- NA |
- 5488_CR_A_0194 |
-
-
- | 394 |
- HB_312_AD |
- AD |
- NA |
- 5500_VC_A_0198 |
-
-
- | 395 |
- HB_313_AD |
- AD |
- NA |
- 5502_PF_A_2684 |
-
-
- | 396 |
- HB_315_AD |
- AD |
- NA |
- 5513_PF_A_2687 |
-
-
- | 397 |
- HB_316_AD |
- AD |
- NA |
- 5516_PF_A_2690 |
-
-
- | 398 |
- HB_317_AD |
- AD |
- NA |
- 5517_PF_A_2693 |
-
-
- | 399 |
- HB_318_AD |
- AD |
- NA |
- 5518_CR_A_0030 |
-
-
- | 400 |
- HB_319_AD |
- AD |
- NA |
- 5519_CR_A_2695 |
-
-
- | 401 |
- HB_320_AD |
- AD |
- NA |
- 5520_PF_A_2699 |
-
-
- | 402 |
- HB_322_AD |
- AD |
- NA |
- 5527_VC_A_0945 |
-
-
- | 403 |
- HB_325_AD |
- AD |
- NA |
- 5532_PF_A_2702 |
-
-
- | 404 |
- HB_328_AD |
- AD |
- NA |
- 5541_PF_A_2705 |
-
-
- | 405 |
- HB_330_AD |
- AD |
- NA |
- 5544_VC_A_0201 |
-
-
- | 406 |
- HB_334_AD |
- AD |
- NA |
- 5554_VC_A_0452 |
-
-
- | 407 |
- HB_335_AD |
- AD |
- NA |
- 5557_VC_A_0950 |
-
-
- | 408 |
- HB_337_AD |
- AD |
- NA |
- 5560_VC_A_0204 |
-
-
- | 409 |
- HB_342_AD |
- AD |
- NA |
- 5571_PF_A_1430 |
-
-
- | 410 |
- HB_345_AD |
- AD |
- NA |
- 5583_PF_A_2708 |
-
-
- | 411 |
- HB_347_AD |
- AD |
- NA |
- 5589_PF_A_2714 |
-
-
- | 412 |
- HB_349_AD |
- AD |
- NA |
- 5592_PF_A_2717 |
-
-
- | 413 |
- HB_352_AD |
- AD |
- NA |
- 5604_VC_A_0037 |
-
-
- | 414 |
- HB_353_AD |
- AD |
- NA |
- 5607_PF_A_2723 |
-
-
- | 415 |
- HB_356_AD |
- AD |
- NA |
- 5615_VC_A_0041 |
-
-
- | 416 |
- HB_357_AD |
- AD |
- NA |
- 5616_CR_A_0127 |
-
-
- | 417 |
- HB_358_AD |
- AD |
- NA |
- 5617_CR_A_0456 |
-
-
- | 418 |
- HB_359_AD |
- AD |
- NA |
- 5618_CR_A_0044 |
-
-
- | 419 |
- HB_362_AD |
- AD |
- NA |
- 5625_CR_A_2495 |
-
-
- | 420 |
- HB_363_AD |
- AD |
- NA |
- 5626_CR_A_2498 |
-
-
- | 421 |
- HB_364_AD |
- AD |
- NA |
- 5629_CR_A_0390 |
-
-
- | 422 |
- HB_369_AD |
- AD |
- NA |
- 5643_VC_A_1143 |
-
-
- | 423 |
- HB_373_AD |
- AD |
- NA |
- 5654_VC_A_0047 |
-
-
- | 424 |
- HB_375_AD |
- AD |
- NA |
- 5660_CR_A_0462 |
-
-
- | 425 |
- HB_376_AD |
- AD |
- NA |
- 5661_VC_A_0464 |
-
-
- | 426 |
- HB_377_AD |
- AD |
- NA |
- 5667_VC_A_2509 |
-
-
- | 427 |
- HB_378_AD |
- AD |
- NA |
- 5668_VC_A_1438 |
-
-
- | 428 |
- HB_383_AD |
- AD |
- NA |
- 5686_CR_A_2728 |
-
-
- | 429 |
- HB_386_AD |
- AD |
- NA |
- 5695_VC_A_0953 |
-
-
- | 430 |
- HB_389_AD |
- AD |
- NA |
- 5700_VC_A_2514 |
-
-
- | 431 |
- HB_391_AD |
- AD |
- NA |
- 5705_CR_A_0474 |
-
-
- | 432 |
- HB_392_AD |
- AD |
- NA |
- 5706_VC_A_0476 |
-
-
- | 433 |
- HB_394_AD |
- AD |
- NA |
- 5713_VC_A_0479 |
-
-
- | 434 |
- HB_397_AD |
- AD |
- NA |
- 5721_CR_A_0210 |
-
-
- | 435 |
- HB_404_AD |
- AD |
- NA |
- 5735_CR_A_0489 |
-
-
- | 436 |
- HB_406_AD |
- AD |
- NA |
- 5744_CR_A_0960 |
-
-
- | 437 |
- HB_409_AD |
- AD |
- NA |
- 5749_CR_A_0159 |
-
-
- | 438 |
- HB_410_AD |
- AD |
- NA |
- 5751_CR_A_2518 |
-
-
- | 439 |
- HB_411_AD |
- AD |
- NA |
- 5755_CR_A_2731 |
-
-
- | 440 |
- HB_413_AD |
- AD |
- NA |
- 5766_VC_A_0214 |
-
-
- | 441 |
- HB_419_AD |
- AD |
- NA |
- 5790_VC_A_0217 |
-
-
- | 442 |
- HB_420_AD |
- AD |
- NA |
- 5796_CR_A_0964 |
-
-
- | 443 |
- HB_428_AD |
- AD |
- NA |
- 5811_CR_A_2524 |
-
-
- | 444 |
- HB_429_AD |
- AD |
- NA |
- 5819_CR_A_2527 |
-
-
- | 445 |
- HB_430_AD |
- AD |
- NA |
- 5822_CR_A_2530 |
-
-
- | 446 |
- HB_434_AD |
- AD |
- NA |
- 5828_CR_A_2533 |
-
-
- | 447 |
- HB_435_AD |
- AD |
- NA |
- 5831_CR_A_0222 |
-
-
- | 448 |
- HB_437_AD |
- AD |
- NA |
- 5839_CR_A_2539 |
-
-
- | 449 |
- HB_438_AD |
- AD |
- NA |
- 5843_CR_A_0227 |
-
-
- | 450 |
- HB_439_AD |
- AD |
- NA |
- 5845_CR_A_0230 |
-
-
- | 451 |
- HB_441_AD |
- AD |
- NA |
- 5849_CR_A_0233 |
-
-
- | 452 |
- HB_442_AD |
- AD |
- NA |
- 5850_CR_A_0495 |
-
-
- | 453 |
- HB_445_AD |
- AD |
- NA |
- 5858_CR_A_0969 |
-
-
- | 454 |
- HB_448_AD |
- AD |
- NA |
- 5864_CR_A_0974 |
-
-
- | 455 |
- HB_451_AD |
- AD |
- NA |
- 5871_CR_A_2542 |
-
-
- | 456 |
- HB_454_AD |
- AD |
- NA |
- 5879_CR_A_2545 |
-
-
- | 457 |
- HB_455_AD |
- AD |
- NA |
- 5887_CR_A_0976_Bis |
-
-
- | 458 |
- HB_459_AD |
- AD |
- NA |
- 5898_CR_A_2548 |
-
-
- | 459 |
- HB_460_AD |
- AD |
- NA |
- 5900_VC_A_0237 |
-
-
- | 460 |
- HB_461_AD |
- AD |
- NA |
- 5901_CR_A_0239 |
-
-
- | 461 |
- HB_469_AD |
- AD |
- NA |
- 5914_CR_A_2554 |
-
-
- | 462 |
- HB_471_AD |
- AD |
- NA |
- 5922_VC_A_0246 |
-
-
- | 463 |
- HB_473_AD |
- AD |
- NA |
- 5927_CR_A_2560 |
-
-
- | 464 |
- HB_474_AD |
- AD |
- NA |
- 5933_VC_A_1071 |
-
-
- | 465 |
- HB_477_AD |
- AD |
- NA |
- 5939_CR_A_1151 |
-
-
- | 466 |
- HB_479_AD |
- AD |
- NA |
- 5945_VC_A_0983 |
-
-
- | 467 |
- HB_484_AD |
- AD |
- NA |
- 5956_CR_A_0123 |
-
-
- | 468 |
- HB_489_AD |
- AD |
- NA |
- 5968_VC_A_1075 |
-
-
- | 469 |
- HB_491_AD |
- AD |
- NA |
- 5971_CR_A_0119 |
-
-
- | 470 |
- HB_492_AD |
- AD |
- NA |
- 5972_VC_A_0251 |
-
-
- | 471 |
- HB_494_AD |
- AD |
- NA |
- 5979_CR_A_0115 |
-
-
- | 472 |
- HB_498_AD |
- AD |
- NA |
- 5988_VC_A_0503 |
-
-
- | 473 |
- HB_502_AD |
- AD |
- NA |
- 5994_PF_A_1605 |
-
-
- | 474 |
- HB_503_AD |
- AD |
- NA |
- 5995_CR_A_2563 |
-
-
- | 475 |
- HB_510_AD |
- AD |
- NA |
- 6017_CR_A_0048 |
-
-
- | 476 |
- HB_514_AD |
- AD |
- NA |
- 6025_VC_A_0506 |
-
-
- | 477 |
- HB_517_AD |
- AD |
- NA |
- 6031_VC_A_0258 |
-
-
- | 478 |
- HB_520_AD |
- AD |
- NA |
- 6035_VC_A_1621 |
-
-
- | 479 |
- HB_523_AD |
- AD |
- NA |
- 6038_VC_A_0261 |
-
-
- | 480 |
- HB_524_AD |
- AD |
- NA |
- 6042_VC_A_1156 |
-
-
- | 481 |
- HB_525_AD |
- AD |
- NA |
- 6044_VC_A_0264 |
-
-
- | 482 |
- HB_531_AD |
- AD |
- NA |
- 6056_CR_A_0999 |
-
-
- | 483 |
- HB_533_AD |
- AD |
- NA |
- 6061_PF_A_1650 |
-
-
- | 484 |
- HB_534_AD |
- AD |
- NA |
- 6066_VC_A_0270 |
-
-
- | 485 |
- HB_535_AD |
- AD |
- NA |
- 6067_PF_A_1452 |
-
-
- | 486 |
- HB_536_AD |
- AD |
- NA |
- 6068_VC_A_0273 |
-
-
- | 487 |
- HB_545_AD |
- AD |
- NA |
- 6102_CR_A_1661 |
-
-
- | 488 |
- HB_546_AD |
- AD |
- NA |
- 6107_CR_A_0055 |
-
-
- | 489 |
- HB_550_AD |
- AD |
- NA |
- 6120_VC_A_0058 |
-
-
- | 490 |
- HB_552_AD |
- AD |
- NA |
- 6126_VC_A_1675 |
-
-
- | 491 |
- HB_553_AD |
- AD |
- NA |
- 6129_PF_A_0274 |
-
-
- | 492 |
- HB_554_AD |
- AD |
- NA |
- 6130_VC_A_1678 |
-
-
- | 493 |
- HB_555_AD |
- AD |
- NA |
- 6131_CR_A_0510 |
-
-
- | 494 |
- HB_556_AD |
- AD |
- NA |
- 6132_CR_A_0513 |
-
-
- | 495 |
- HB_558_AD |
- AD |
- NA |
- 6137_VC_A_1681 |
-
-
- | 496 |
- HB_564_AD |
- AD |
- NA |
- 6153_VC_A_1465 |
-
-
- | 497 |
- HB_565_AD |
- AD |
- NA |
- 6154_VC_A_1468 |
-
-
- | 498 |
- HB_566_AD |
- AD |
- NA |
- 6157_VC_A_0062 |
-
-
- | 499 |
- HB_568_AD |
- AD |
- NA |
- 6164_CR_A_1005 |
-
-
- | 500 |
- HB_571_AD |
- AD |
- NA |
- 6171_CR_A_0065 |
-
-
- | 501 |
- HB_573_AD |
- AD |
- NA |
- 6174_VC_A_0068 |
-
-
- | 502 |
- HB_576_AD |
- AD |
- NA |
- 6180_CR_A_0281 |
-
-
- | 503 |
- HB_583_AD |
- AD |
- NA |
- 6194_VC_A_0071 |
-
-
- | 504 |
- HB_585_AD |
- AD |
- NA |
- 6198_VC_A_0073 |
-
-
- | 505 |
- HB_590_AD |
- AD |
- NA |
- 6215_VC_A_0518 |
-
-
- | 506 |
- HB_591_AD |
- AD |
- NA |
- 6216_VC_A_1476 |
-
-
- | 507 |
- HB_592_AD |
- AD |
- NA |
- 6218_CR_A_0522 |
-
-
- | 508 |
- HB_594_AD |
- AD |
- NA |
- 6223_VC_A_0288 |
-
-
- | 509 |
- HB_596_AD |
- AD |
- NA |
- 6226_CR_A_0076 |
-
-
- | 510 |
- HB_597_AD |
- AD |
- NA |
- 6227_VC_A_0080 |
-
-
- | 511 |
- HB_598_AD |
- AD |
- NA |
- 6231_VC_A_1479 |
-
-
- | 512 |
- HB_605_AD |
- AD |
- NA |
- 6261_VC_A_0084 |
-
-
- | 513 |
- HB_608_AD |
- AD |
- NA |
- 6268_CR_A_0525 |
-
-
- | 514 |
- HB_611_AD |
- AD |
- NA |
- 6279_VC_A_0089 |
-
-
- | 515 |
- HB_612_AD |
- AD |
- NA |
- 6280_VC_A_0091 |
-
-
- | 516 |
- HB_613_AD |
- AD |
- NA |
- 6281_CR_A_0528 |
-
-
- | 517 |
- HB_621_AD |
- AD |
- NA |
- 6308_VC_A_1503 |
-
-
- | 518 |
- HB_623_AD |
- AD |
- NA |
- 6311_CR_A_0531 |
-
-
- | 519 |
- HB_624_AD |
- AD |
- NA |
- 6312_CR_A_0534 |
-
-
- | 520 |
- HB_630_AD |
- AD |
- NA |
- 6324_PF_A_1514 |
-
-
- | 521 |
- HB_633_AD |
- AD |
- NA |
- 6332_VC_A_1518 |
-
-
- | 522 |
- HB_634_AD |
- AD |
- NA |
- 6335_VC_A_0536 |
-
-
- | 523 |
- HB_635_AD |
- AD |
- NA |
- 6336_CR_A_0290 |
-
-
- | 524 |
- HB_636_AD |
- AD |
- NA |
- 6338_VC_A_0539 |
-
-
- | 525 |
- HB_642_AD |
- AD |
- NA |
- 6358_VC_A_0545 |
-
-
- | 526 |
- HB_652_AD |
- AD |
- NA |
- 6387_VC_A_0093 |
-
-
- | 527 |
- HB_657_AD |
- AD |
- NA |
- 6394_VC_A_0551 |
-
-
- | 528 |
- HB_664_AD |
- AD |
- NA |
- 6416_VC_A_1095 |
-
-
- | 529 |
- HB_666_AD |
- AD |
- NA |
- 6422_CR_A_0555 |
-
-
- | 530 |
- HB_669_AD |
- AD |
- NA |
- 6431_VC_A_0294 |
-
-
- | 531 |
- HB_674_AD |
- AD |
- NA |
- 6449_VC_A_1183 |
-
-
- | 532 |
- HB_680_AD |
- AD |
- NA |
- 6458_CR_A_2570 |
-
-
- | 533 |
- HB_685_AD |
- AD |
- NA |
- 6481_VC_A_0560 |
-
-
- | 534 |
- HB_690_AD |
- AD |
- NA |
- 6489_CR_A_0100 |
-
-
- | 535 |
- HB_696_AD |
- AD |
- NA |
- 6511_VC_A_1119 |
-
-
- | 536 |
- HB_698_AD |
- AD |
- NA |
- 6515_CR_A_0564 |
-
-
- | 537 |
- HB_699_AD |
- AD |
- NA |
- 6518_VC_A_0103 |
-
-
- | 538 |
- HB_703_AD |
- AD |
- NA |
- 6523_VC_A_0107 |
-
-
- | 539 |
- HB_704_AD |
- AD |
- NA |
- 6530_VC_A_0112 |
-
-
- | 540 |
- HB_706_AD |
- AD |
- NA |
- 6534_VC_A_0306 |
-
-
- | 541 |
- HB_712_AD |
- AD |
- NA |
- 6546_PF_A_1194 |
-
-
- | 542 |
- HB_713_AD |
- AD |
- NA |
- 6548_PF_A_1541 |
-
-
- | 543 |
- HB_715_AD |
- AD |
- NA |
- 6550_VC_A_1201 |
-
-
- | 544 |
- HB_718_AD |
- AD |
- NA |
- 6554_PF_A_1203 |
-
-
- | 545 |
- HB_720_AD |
- AD |
- NA |
- 6559_PF_A_2287 |
-
-
- | 546 |
- HB_722_AD |
- AD |
- NA |
- 6561_CR_A_2582 |
-
-
- | 547 |
- HB_723_AD |
- AD |
- NA |
- 6562_PF_A_2290 |
-
-
- | 548 |
- HB_724_AD |
- AD |
- NA |
- 6564_CR_A_2585 |
-
-
- | 549 |
- HB_727_AD |
- AD |
- NA |
- 6575_CR_A_2298 |
-
-
- | 550 |
- HB_728_AD |
- AD |
- NA |
- 6577_PF_A_2299 |
-
-
- | 551 |
- HB_729_AD |
- AD |
- NA |
- 6578_PF_A_2302 |
-
-
- | 552 |
- HB_731_AD |
- AD |
- NA |
- 6582_VC_A_1207 |
-
-
- | 553 |
- HB_733_AD |
- AD |
- NA |
- 6585_VC_A_1210 |
-
-
- | 554 |
- HB_736_AD |
- AD |
- NA |
- 6590_PF_A_1215 |
-
-
- | 555 |
- HB_743_AD |
- AD |
- NA |
- 6603_PF_A_1448 |
-
-
- | 556 |
- HB_745_AD |
- AD |
- NA |
- 6610_PF_A_1227 |
-
-
- | 557 |
- HB_746_AD |
- AD |
- NA |
- 6612_PF_A_2308 |
-
-
- | 558 |
- HB_749_AD |
- AD |
- NA |
- 6617_VC_A_2587 |
-
-
- | 559 |
- HB_751_AD |
- AD |
- NA |
- 6629_VC_A_2330 |
-
-
- | 560 |
- HB_752_AD |
- AD |
- NA |
- 6630_VC_A_2590 |
-
-
- | 561 |
- HB_753_AD |
- AD |
- NA |
- 6632_PF_A_2332 |
-
-
- | 562 |
- HB_754_AD |
- AD |
- NA |
- 6637_VC_A_2596 |
-
-
- | 563 |
- HB_755_AD |
- AD |
- NA |
- 6638_VC_A_2599 |
-
-
- | 564 |
- HB_756_AD |
- AD |
- NA |
- 6639_VC_A_2336 |
-
-
- | 565 |
- HB_757_AD |
- AD |
- NA |
- 6641_PF_A_2338 |
-
-
- | 566 |
- HB_763_AD |
- AD |
- NA |
- 6654_VC_A_1237 |
-
-
- | 567 |
- HB_773_AD |
- AD |
- NA |
- 6681_VC_A_1252 |
-
-
- | 568 |
- HB_775_AD |
- AD |
- NA |
- 6693_VC_A_2348 |
-
-
- | 569 |
- HB_776_AD |
- AD |
- NA |
- 6694_VC_A_2351 |
-
-
- | 570 |
- HB_777_AD |
- AD |
- NA |
- 6695_PF_A_2353 |
-
-
- | 571 |
- HB_779_AD |
- AD |
- NA |
- 6699_PF_A_2359 |
-
-
- | 572 |
- HB_781_AD |
- AD |
- NA |
- 6708_VC_A_2366 |
-
-
- | 573 |
- HB_782_AD |
- AD |
- NA |
- 6776_PF_A_2607 |
-
-
- | 574 |
- HB_783_AD |
- AD |
- NA |
- 6778_PF_A_2368 |
-
-
- | 575 |
- HB_784_AD |
- AD |
- NA |
- 6779_PF_A_2371 |
-
-
- | 576 |
- HB_785_AD |
- AD |
- NA |
- 6780_PF_A_2374 |
-
-
- | 577 |
- HB_786_AD |
- AD |
- NA |
- 6782_PF_A_2377 |
-
-
- | 578 |
- HB_787_AD |
- AD |
- NA |
- 6784_PF_A_2380 |
-
-
- | 579 |
- HB_788_AD |
- AD |
- NA |
- 6785_CR_A_2385 |
-
-
- | 580 |
- HB_789_AD |
- AD |
- NA |
- 6787_CR_A_2388 |
-
-
- | 581 |
- HB_791_AD |
- AD |
- NA |
- 6790_PF_A_2392 |
-
-
- | 582 |
- HB_792_AD |
- AD |
- NA |
- 6791_PF_A_2395 |
-
-
- | 583 |
- HB_793_AD |
- AD |
- NA |
- 6793_PF_A_2398 |
-
-
- | 584 |
- HB_794_AD |
- AD |
- NA |
- 6794_PF_A_2401 |
-
-
- | 585 |
- HB_795_AD |
- AD |
- NA |
- 6797_PF_A_2404 |
-
-
- | 586 |
- HB_796_AD |
- AD |
- NA |
- 6798_PF_A_2407 |
-
-
- | 587 |
- HB_797_AD |
- AD |
- NA |
- 6799_VC_A_2411 |
-
-
- | 588 |
- HB_798_AD |
- AD |
- NA |
- 6801_VC_A_2414 |
-
-
- | 589 |
- HB_799_AD |
- AD |
- NA |
- 6803_VC_A_2417 |
-
-
- | 590 |
- HB_801_AD |
- AD |
- NA |
- 6809_PF_A_2422 |
-
-
- | 591 |
- HB_803_AD |
- AD |
- NA |
- 6818_CR_A_2430 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/HBTRC_MLVC_HD_0611/notes.rtf b/general/datasets/HBTRC_MLVC_HD_0611/notes.rtf
deleted file mode 100644
index ff90e34..0000000
--- a/general/datasets/HBTRC_MLVC_HD_0611/notes.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Species: Human
-Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
-Disease: Neurological Disease
-Investigator: Francine Benes/ Eric Schadt
-Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
-Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC_MLVC_HD_0611/summary.rtf b/general/datasets/HBTRC_MLVC_HD_0611/summary.rtf
deleted file mode 100644
index 5cde3bf..0000000
--- a/general/datasets/HBTRC_MLVC_HD_0611/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HBTRC_MLVC_N_0611/acknowledgment.rtf b/general/datasets/HBTRC_MLVC_N_0611/acknowledgment.rtf
deleted file mode 100644
index 208cb6e..0000000
--- a/general/datasets/HBTRC_MLVC_N_0611/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/HBTRC_MLVC_N_0611/cases.rtf b/general/datasets/HBTRC_MLVC_N_0611/cases.rtf
deleted file mode 100644
index 86ed08e..0000000
--- a/general/datasets/HBTRC_MLVC_N_0611/cases.rtf
+++ /dev/null
@@ -1,4166 +0,0 @@
-This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- | Series |
- Cerebellum in GN |
- Condition |
- Gender |
- BioSample Name |
-
-
- | 1 |
- HB_029_N |
- N |
- NA |
- 3405_VC_N_0859 |
-
-
- | 2 |
- HB_058_N |
- N |
- NA |
- 4021_VC_N_0854 |
-
-
- | 3 |
- HB_064_N |
- N |
- NA |
- 4338_VC_N_0861 |
-
-
- | 4 |
- HB_086_N |
- N |
- NA |
- 4729_PF_N_0756 |
-
-
- | 5 |
- HB_091_N |
- N |
- NA |
- 4741_VC_N_0864 |
-
-
- | 6 |
- HB_092_N |
- N |
- NA |
- 4744_VC_N_0865 |
-
-
- | 7 |
- HB_102_N |
- N |
- NA |
- 4810_VC_N_0869 |
-
-
- | 8 |
- HB_119_N |
- N |
- NA |
- 4872_VC_N_0878 |
-
-
- | 9 |
- HB_147_N |
- N |
- NA |
- 5021_VC_N_0852 |
-
-
- | 10 |
- HB_161_N |
- N |
- NA |
- 5077_VC_N_0851 |
-
-
- | 11 |
- HB_162_N |
- N |
- NA |
- 5081_VC_N_1021 |
-
-
- | 12 |
- HB_166_N |
- N |
- NA |
- 5095_VC_N_1024 |
-
-
- | 13 |
- HB_183_N |
- N |
- NA |
- 5162_VC_N_0850 |
-
-
- | 14 |
- HB_206_N |
- N |
- NA |
- 5245_VC_N_0849 |
-
-
- | 15 |
- HB_215_N |
- N |
- NA |
- 5270_VC_N_0848 |
-
-
- | 16 |
- HB_218_N |
- N |
- NA |
- 5276_CR_N_0912 |
-
-
- | 17 |
- HB_223_N |
- N |
- NA |
- 5287_VC_N_0916 |
-
-
- | 18 |
- HB_226_N |
- N |
- NA |
- 5294_VC_N_0919 |
-
-
- | 19 |
- HB_241_N |
- N |
- NA |
- 5326_CR_N_0652 |
-
-
- | 20 |
- HB_243_N |
- N |
- NA |
- 5333_VC_N_1262 |
-
-
- | 21 |
- HB_247_N |
- N |
- NA |
- 5341_VC_N_0923 |
-
-
- | 22 |
- HB_257_N |
- N |
- NA |
- 5368_PF_N_1032 |
-
-
- | 23 |
- HB_264_N |
- N |
- NA |
- 5384_VC_N_0924 |
-
-
- | 24 |
- HB_295_N |
- N |
- NA |
- 5452_VC_N_1268 |
-
-
- | 25 |
- HB_300_N |
- N |
- NA |
- 5463_VC_N_0845 |
-
-
- | 26 |
- HB_311_N |
- N |
- NA |
- 5489_CR_N_0942 |
-
-
- | 27 |
- HB_324_N |
- N |
- NA |
- 5531_VC_N_0844 |
-
-
- | 28 |
- HB_332_N |
- N |
- NA |
- 5547_VC_N_0843 |
-
-
- | 29 |
- HB_340_N |
- N |
- NA |
- 5568_VC_N_0842 |
-
-
- | 30 |
- HB_360_N |
- N |
- NA |
- 5619_CR_N_0645 |
-
-
- | 31 |
- HB_365_N |
- N |
- NA |
- 5632_VC_N_0838 |
-
-
- | 32 |
- HB_367_N |
- N |
- NA |
- 5637_VC_N_0837 |
-
-
- | 33 |
- HB_382_N |
- N |
- NA |
- 5684_PF_N_1270 |
-
-
- | 34 |
- HB_396_N |
- N |
- NA |
- 5718_VC_N_0956 |
-
-
- | 35 |
- HB_398_N |
- N |
- NA |
- 5722_VC_N_1044 |
-
-
- | 36 |
- HB_400_N |
- N |
- NA |
- 5726_VC_N_0834_Bis |
-
-
- | 37 |
- HB_403_N |
- N |
- NA |
- 5734_VC_N_0833 |
-
-
- | 38 |
- HB_414_N |
- N |
- NA |
- 5772_VC_N_0832_Bis |
-
-
- | 39 |
- HB_416_N |
- N |
- NA |
- 5778_CR_N_0962 |
-
-
- | 40 |
- HB_418_N |
- N |
- NA |
- 5789_PF_N_1273 |
-
-
- | 41 |
- HB_421_N |
- N |
- NA |
- 5799_VC_N_1058 |
-
-
- | 42 |
- HB_423_N |
- N |
- NA |
- 5803_VC_N_0966 |
-
-
- | 43 |
- HB_426_N |
- N |
- NA |
- 5806_PF_N_1064 |
-
-
- | 44 |
- HB_427_N |
- N |
- NA |
- 5810_CR_N_0636 |
-
-
- | 45 |
- HB_431_N |
- N |
- NA |
- 5823_VC_N_0829 |
-
-
- | 46 |
- HB_432_N |
- N |
- NA |
- 5826_VC_N_0828 |
-
-
- | 47 |
- HB_433_N |
- N |
- NA |
- 5827_VC_N_0827 |
-
-
- | 48 |
- HB_436_N |
- N |
- NA |
- 5832_PF_N_1145 |
-
-
- | 49 |
- HB_443_N |
- N |
- NA |
- 5852_VC_N_0826 |
-
-
- | 50 |
- HB_446_N |
- N |
- NA |
- 5859_VC_N_0825 |
-
-
- | 51 |
- HB_449_N |
- N |
- NA |
- 5866_VC_N_0824 |
-
-
- | 52 |
- HB_450_N |
- N |
- NA |
- 5867_VC_N_1277 |
-
-
- | 53 |
- HB_453_N |
- N |
- NA |
- 5876_VC_N_0823 |
-
-
- | 54 |
- HB_462_N |
- N |
- NA |
- 5903_VC_N_0822 |
-
-
- | 55 |
- HB_464_N |
- N |
- NA |
- 5905_VC_N_0820 |
-
-
- | 56 |
- HB_468_N |
- N |
- NA |
- 5912_VC_N_1286 |
-
-
- | 57 |
- HB_472_N |
- N |
- NA |
- 5925_VC_N_1289 |
-
-
- | 58 |
- HB_475_N |
- N |
- NA |
- 5936_VC_N_0979 |
-
-
- | 59 |
- HB_476_N |
- N |
- NA |
- 5938_VC_N_0819 |
-
-
- | 60 |
- HB_480_N |
- N |
- NA |
- 5946_VC_N_0985 |
-
-
- | 61 |
- HB_485_N |
- N |
- NA |
- 5959_VC_N_0818 |
-
-
- | 62 |
- HB_486_N |
- N |
- NA |
- 5963_VC_N_0987 |
-
-
- | 63 |
- HB_495_N |
- N |
- NA |
- 5980_VC_N_0989 |
-
-
- | 64 |
- HB_497_N |
- N |
- NA |
- 5985_VC_N_0990 |
-
-
- | 65 |
- HB_500_N |
- N |
- NA |
- 5990_VC_N_0817 |
-
-
- | 66 |
- HB_501_N |
- N |
- NA |
- 5991_VC_N_0816 |
-
-
- | 67 |
- HB_504_N |
- N |
- NA |
- 5996_VC_N_0815 |
-
-
- | 68 |
- HB_505_N |
- N |
- NA |
- 5998_VC_N_0814 |
-
-
- | 69 |
- HB_507_N |
- N |
- NA |
- 6006_VC_N_0813 |
-
-
- | 70 |
- HB_508_N |
- N |
- NA |
- 6007_CR_N_0618 |
-
-
- | 71 |
- HB_509_N |
- N |
- NA |
- 6008_PF_N_1081 |
-
-
- | 72 |
- HB_512_N |
- N |
- NA |
- 6023_PF_N_1155 |
-
-
- | 73 |
- HB_516_N |
- N |
- NA |
- 6030_VC_N_0810 |
-
-
- | 74 |
- HB_519_N |
- N |
- NA |
- 6034_VC_N_0809 |
-
-
- | 75 |
- HB_532_N |
- N |
- NA |
- 6060_VC_N_1292 |
-
-
- | 76 |
- HB_541_N |
- N |
- NA |
- 6092_VC_N_1001 |
-
-
- | 77 |
- HB_542_N |
- N |
- NA |
- 6096_VC_N_0807 |
-
-
- | 78 |
- HB_544_N |
- N |
- NA |
- 6101_CR_N_1161 |
-
-
- | 79 |
- HB_547_N |
- N |
- NA |
- 6110_VC_N_1295 |
-
-
- | 80 |
- HB_551_N |
- N |
- NA |
- 6124_VC_N_0806 |
-
-
- | 81 |
- HB_557_N |
- N |
- NA |
- 6134_PF_N_1297 |
-
-
- | 82 |
- HB_560_N |
- N |
- NA |
- 6142_VC_N_0805 |
-
-
- | 83 |
- HB_569_N |
- N |
- NA |
- 6166_VC_N_0804 |
-
-
- | 84 |
- HB_570_N |
- N |
- NA |
- 6170_VC_N_0803 |
-
-
- | 85 |
- HB_572_N |
- N |
- NA |
- 6172_VC_N_1008 |
-
-
- | 86 |
- HB_577_N |
- N |
- NA |
- 6182_VC_N_1166 |
-
-
- | 87 |
- HB_579_N |
- N |
- NA |
- 6187_CR_N_0607 |
-
-
- | 88 |
- HB_581_N |
- N |
- NA |
- 6191_VC_N_1010 |
-
-
- | 89 |
- HB_584_N |
- N |
- NA |
- 6196_CR_N_0605 |
-
-
- | 90 |
- HB_586_N |
- N |
- NA |
- 6200_VC_N_0799 |
-
-
- | 91 |
- HB_587_N |
- N |
- NA |
- 6206_PF_N_1176 |
-
-
- | 92 |
- HB_589_N |
- N |
- NA |
- 6213_VC_N_0798 |
-
-
- | 93 |
- HB_601_N |
- N |
- NA |
- 6241_VC_N_0796 |
-
-
- | 94 |
- HB_604_N |
- N |
- NA |
- 6260_VC_N_0794 |
-
-
- | 95 |
- HB_609_N |
- N |
- NA |
- 6270_VC_N_0793 |
-
-
- | 96 |
- HB_618_N |
- N |
- NA |
- 6289_VC_N_0791 |
-
-
- | 97 |
- HB_622_N |
- N |
- NA |
- 6310_VC_N_0790 |
-
-
- | 98 |
- HB_625_N |
- N |
- NA |
- 6314_VC_N_0789 |
-
-
- | 99 |
- HB_637_N |
- N |
- NA |
- 6340_VC_N_0786 |
-
-
- | 100 |
- HB_638_N |
- N |
- NA |
- 6341_VC_N_0785 |
-
-
- | 101 |
- HB_640_N |
- N |
- NA |
- 6347_VC_N_0784 |
-
-
- | 102 |
- HB_641_N |
- N |
- NA |
- 6356_VC_N_0783 |
-
-
- | 103 |
- HB_643_N |
- N |
- NA |
- 6363_VC_N_0781 |
-
-
- | 104 |
- HB_644_N |
- N |
- NA |
- 6366_VC_N_0780 |
-
-
- | 105 |
- HB_645_N |
- N |
- NA |
- 6374_VC_N_0779 |
-
-
- | 106 |
- HB_650_N |
- N |
- NA |
- 6384_VC_N_0777 |
-
-
- | 107 |
- HB_651_N |
- N |
- NA |
- 6386_VC_N_0776 |
-
-
- | 108 |
- HB_653_N |
- N |
- NA |
- 6388_VC_N_0775 |
-
-
- | 109 |
- HB_659_N |
- N |
- NA |
- 6406_VC_N_1180 |
-
-
- | 110 |
- HB_662_N |
- N |
- NA |
- 6411_VC_N_0771 |
-
-
- | 111 |
- HB_663_N |
- N |
- NA |
- 6415_VC_N_0770 |
-
-
- | 112 |
- HB_670_N |
- N |
- NA |
- 6436_VC_N_0769 |
-
-
- | 113 |
- HB_687_N |
- N |
- NA |
- 6484_VC_N_0765 |
-
-
- | 114 |
- HB_689_N |
- N |
- NA |
- 6486_VC_N_0764 |
-
-
- | 115 |
- HB_694_N |
- N |
- NA |
- 6500_VC_N_0763 |
-
-
- | 116 |
- HB_697_N |
- N |
- NA |
- 6512_VC_N_0762 |
-
-
- | 117 |
- HB_700_N |
- N |
- NA |
- 6520_VC_N_0761 |
-
-
- | 118 |
- HB_711_N |
- N |
- NA |
- 6543_PF_N_1191 |
-
-
- | 119 |
- HB_714_N |
- N |
- NA |
- 6549_VC_N_1198 |
-
-
- | 120 |
- HB_717_N |
- N |
- NA |
- 6553_PF_N_2284 |
-
-
- | 121 |
- HB_721_N |
- N |
- NA |
- 6560_VC_N_2578 |
-
-
- | 122 |
- HB_726_N |
- N |
- NA |
- 6573_PF_N_2293 |
-
-
- | 123 |
- HB_730_N |
- N |
- NA |
- 6580_VC_N_2306 |
-
-
- | 124 |
- HB_735_N |
- N |
- NA |
- 6588_VC_N_1213 |
-
-
- | 125 |
- HB_737_N |
- N |
- NA |
- 6593_VC_N_1219 |
-
-
- | 126 |
- HB_738_N |
- N |
- NA |
- 6594_VC_N_1222 |
-
-
- | 127 |
- HB_759_N |
- N |
- NA |
- 6645_VC_N_1231 |
-
-
- | 128 |
- HB_764_N |
- N |
- NA |
- 6655_VC_N_1240 |
-
-
- | 129 |
- HB_765_N |
- N |
- NA |
- 6656_VC_N_1243 |
-
-
- | 130 |
- HB_767_N |
- N |
- NA |
- 6661_PF_N_2341 |
-
-
- | 131 |
- HB_770_N |
- N |
- NA |
- 6669_VC_N_1246 |
-
-
- | 132 |
- HB_772_N |
- N |
- NA |
- 6676_PF_N_1248 |
-
-
- | 133 |
- HB_001_HD |
- HD |
- F |
- 2028_CR_H_2282 |
-
-
- | 134 |
- HB_003_HD |
- HD |
- F |
- 2685_PF_H_2212 |
-
-
- | 135 |
- HB_004_HD |
- HD |
- M |
- 2706_CR_H_2432 |
-
-
- | 136 |
- HB_006_HD |
- HD |
- M |
- 2737_VC_H_2194 |
-
-
- | 137 |
- HB_007_HD |
- HD |
- NA |
- 2769_VC_H_2193 |
-
-
- | 138 |
- HB_008_HD |
- HD |
- F |
- 2790_CR_H_1890 |
-
-
- | 139 |
- HB_009_HD |
- HD |
- NA |
- 2879_VC_H_2192 |
-
-
- | 140 |
- HB_010_HD |
- HD |
- M |
- 2960_VC_H_2002 |
-
-
- | 141 |
- HB_011_HD |
- HD |
- F |
- 3053_VC_H_2001 |
-
-
- | 142 |
- HB_012_HD |
- HD |
- F |
- 3128_VC_H_1999 |
-
-
- | 143 |
- HB_014_HD |
- HD |
- F |
- 3149_PF_H_2110 |
-
-
- | 144 |
- HB_015_HD |
- HD |
- F |
- 3150_VC_H_1996 |
-
-
- | 145 |
- HB_016_HD |
- HD |
- F |
- 3177_VC_H_2191 |
-
-
- | 146 |
- HB_017_HD |
- HD |
- NA |
- 3195_VC_H_2190 |
-
-
- | 147 |
- HB_018_HD |
- HD |
- M |
- 3200_VC_H_2189 |
-
-
- | 148 |
- HB_019_HD |
- HD |
- M |
- 3209_VC_H_2188 |
-
-
- | 149 |
- HB_020_HD |
- HD |
- M |
- 3224_VC_H_1994 |
-
-
- | 150 |
- HB_022_HD |
- HD |
- F |
- 3242_PF_H_2105 |
-
-
- | 151 |
- HB_024_HD |
- HD |
- NA |
- 3272_VC_H_2186 |
-
-
- | 152 |
- HB_027_HD |
- HD |
- M |
- 3356_VC_H_2439 |
-
-
- | 153 |
- HB_028_HD |
- HD |
- F |
- 3394_PF_H_2104 |
-
-
- | 154 |
- HB_031_HD |
- HD |
- M |
- 3430_VC_H_1990 |
-
-
- | 155 |
- HB_032_HD |
- HD |
- NA |
- 3444_PF_H_2208 |
-
-
- | 156 |
- HB_034_HD |
- HD |
- F |
- 3482_VC_H_1987 |
-
-
- | 157 |
- HB_036_HD |
- HD |
- M |
- 3576_VC_H_1984 |
-
-
- | 158 |
- HB_037_HD |
- HD |
- F |
- 3579_VC_H_1983 |
-
-
- | 159 |
- HB_038_HD |
- HD |
- F |
- 3584_VC_H_2183 |
-
-
- | 160 |
- HB_039_HD |
- HD |
- NA |
- 3635_VC_H_2182 |
-
-
- | 161 |
- HB_041_HD |
- HD |
- F |
- 3695_CR_H_2267 |
-
-
- | 162 |
- HB_042_HD |
- HD |
- M |
- 3697_VC_H_1982 |
-
-
- | 163 |
- HB_043_HD |
- HD |
- NA |
- 3703_VC_H_2180 |
-
-
- | 164 |
- HB_044_HD |
- HD |
- NA |
- 3723_VC_H_2179 |
-
-
- | 165 |
- HB_046_HD |
- HD |
- F |
- 3735_VC_H_1981 |
-
-
- | 166 |
- HB_050_HD |
- HD |
- M |
- 3820_PF_H_2207 |
-
-
- | 167 |
- HB_051_HD |
- HD |
- F |
- 3849_CR_H_2262 |
-
-
- | 168 |
- HB_054_HD |
- HD |
- M |
- 3884_VC_H_2175 |
-
-
- | 169 |
- HB_056_HD |
- HD |
- NA |
- 4012_VC_H_2174 |
-
-
- | 170 |
- HB_057_HD |
- HD |
- NA |
- 4013_VC_H_2173 |
-
-
- | 171 |
- HB_059_HD |
- HD |
- NA |
- 4066_VC_H_2172 |
-
-
- | 172 |
- HB_060_HD |
- HD |
- NA |
- 4094_VC_H_2171 |
-
-
- | 173 |
- HB_061_HD |
- HD |
- F |
- 4116_VC_H_2170 |
-
-
- | 174 |
- HB_062_HD |
- HD |
- NA |
- 4121_VC_H_2169 |
-
-
- | 175 |
- HB_063_HD |
- HD |
- NA |
- 4215_VC_H_2167 |
-
-
- | 176 |
- HB_065_HD |
- HD |
- M |
- 4340_PF_H_2091 |
-
-
- | 177 |
- HB_066_HD |
- HD |
- F |
- 4344_VC_H_1977 |
-
-
- | 178 |
- HB_067_HD |
- HD |
- M |
- 4346_VC_H_2165 |
-
-
- | 179 |
- HB_069_HD |
- HD |
- F |
- 4356_VC_H_2164 |
-
-
- | 180 |
- HB_070_HD |
- HD |
- NA |
- 4386_CR_H_2249 |
-
-
- | 181 |
- HB_072_HD |
- HD |
- NA |
- 4404_VC_H_2161 |
-
-
- | 182 |
- HB_073_HD |
- HD |
- F |
- 4411_VC_H_1975 |
-
-
- | 183 |
- HB_074_HD |
- HD |
- NA |
- 4430_VC_H_2465 |
-
-
- | 184 |
- HB_075_HD |
- HD |
- M |
- 4470_VC_H_1974 |
-
-
- | 185 |
- HB_076_HD |
- HD |
- F |
- 4497_CR_H_1860 |
-
-
- | 186 |
- HB_077_HD |
- HD |
- M |
- 4509_CR_H_2244 |
-
-
- | 187 |
- HB_079_HD |
- HD |
- M |
- 4631_VC_H_1971 |
-
-
- | 188 |
- HB_080_HD |
- HD |
- F |
- 4653_PF_H_2083 |
-
-
- | 189 |
- HB_081_HD |
- HD |
- NA |
- 4678_CR_H_2242 |
-
-
- | 190 |
- HB_084_HD |
- HD |
- M |
- 4718_VC_H_2125 |
-
-
- | 191 |
- HB_090_HD |
- HD |
- NA |
- 4740_CR_H_2474 |
-
-
- | 192 |
- HB_094_HD |
- HD |
- NA |
- 4754_CR_H_2476 |
-
-
- | 193 |
- HB_098_HD |
- HD |
- NA |
- 4780_VC_H_2151 |
-
-
- | 194 |
- HB_101_HD |
- HD |
- F |
- 4809_VC_H_2148 |
-
-
- | 195 |
- HB_105_HD |
- HD |
- NA |
- 4819_CR_H_2238 |
-
-
- | 196 |
- HB_106_HD |
- HD |
- F |
- 4822_VC_H_1969 |
-
-
- | 197 |
- HB_108_HD |
- HD |
- M |
- 4826_VC_H_1968 |
-
-
- | 198 |
- HB_109_HD |
- HD |
- M |
- 4828_VC_H_2124 |
-
-
- | 199 |
- HB_115_HD |
- HD |
- NA |
- 4855_CR_H_2235 |
-
-
- | 200 |
- HB_121_HD |
- HD |
- F |
- 4902_VC_H_1967 |
-
-
- | 201 |
- HB_129_HD |
- HD |
- NA |
- 4938_VC_H_1966 |
-
-
- | 202 |
- HB_141_HD |
- HD |
- F |
- 4996_PF_H_2076 |
-
-
- | 203 |
- HB_152_HD |
- HD |
- NA |
- 5034_CR_H_2233 |
-
-
- | 204 |
- HB_153_HD |
- HD |
- M |
- 5043_VC_H_1960 |
-
-
- | 205 |
- HB_159_HD |
- HD |
- M |
- 5062_VC_H_1959 |
-
-
- | 206 |
- HB_172_HD |
- HD |
- F |
- 5114_PF_H_2070 |
-
-
- | 207 |
- HB_175_HD |
- HD |
- M |
- 5127_PF_H_2068 |
-
-
- | 208 |
- HB_180_HD |
- HD |
- M |
- 5148_VC_H_1944 |
-
-
- | 209 |
- HB_185_HD |
- HD |
- F |
- 5167_CR_H_2231 |
-
-
- | 210 |
- HB_188_HD |
- HD |
- F |
- 5172_VC_H_1951 |
-
-
- | 211 |
- HB_191_HD |
- HD |
- M |
- 5180_VC_H_1949 |
-
-
- | 212 |
- HB_196_HD |
- HD |
- NA |
- 5199_PF_H_2202 |
-
-
- | 213 |
- HB_203_HD |
- HD |
- F |
- 5228_PF_H_2059 |
-
-
- | 214 |
- HB_207_HD |
- HD |
- NA |
- 5248_PF_H_2201 |
-
-
- | 215 |
- HB_228_HD |
- HD |
- F |
- 5299_CR_H_2228 |
-
-
- | 216 |
- HB_233_HD |
- HD |
- M |
- 5312_VC_H_1938 |
-
-
- | 217 |
- HB_235_HD |
- HD |
- F |
- 5316_VC_H_1937 |
-
-
- | 218 |
- HB_242_HD |
- HD |
- F |
- 5328_PF_H_2048 |
-
-
- | 219 |
- HB_266_HD |
- HD |
- M |
- 5387_VC_H_1928 |
-
-
- | 220 |
- HB_271_HD |
- HD |
- M |
- 5394_PF_H_2039 |
-
-
- | 221 |
- HB_272_HD |
- HD |
- F |
- 5396_VC_H_1925 |
-
-
- | 222 |
- HB_279_HD |
- HD |
- F |
- 5409_VC_H_1924 |
-
-
- | 223 |
- HB_294_HD |
- HD |
- M |
- 5448_VC_H_1921 |
-
-
- | 224 |
- HB_301_HD |
- HD |
- NA |
- 5464_VC_H_1919 |
-
-
- | 225 |
- HB_304_HD |
- HD |
- F |
- 5471_VC_H_1918 |
-
-
- | 226 |
- HB_321_HD |
- HD |
- NA |
- 5522_PF_H_2199 |
-
-
- | 227 |
- HB_361_HD |
- HD |
- F |
- 5622_VC_H_2121 |
-
-
- | 228 |
- HB_370_HD |
- HD |
- M |
- 5645_VC_H_1904 |
-
-
- | 229 |
- HB_371_HD |
- HD |
- F |
- 5648_PF_H_2016 |
-
-
- | 230 |
- HB_384_HD |
- HD |
- F |
- 5688_PF_H_2012 |
-
-
- | 231 |
- HB_390_HD |
- HD |
- M |
- 5704_PF_H_2009 |
-
-
- | 232 |
- HB_393_HD |
- HD |
- F |
- 5709_VC_H_1895 |
-
-
- | 233 |
- HB_402_HD |
- HD |
- F |
- 5732_PF_H_2007 |
-
-
- | 234 |
- HB_405_HD |
- HD |
- NA |
- 5742_PF_H_2006 |
-
-
- | 235 |
- HB_407_HD |
- HD |
- M |
- 5745_PF_H_2005 |
-
-
- | 236 |
- HB_408_HD |
- HD |
- M |
- 5747_VC_H_1891 |
-
-
- | 237 |
- HB_415_HD |
- HD |
- NA |
- 5777_PF_H_1551 |
-
-
- | 238 |
- HB_417_HD |
- HD |
- M |
- 5784_PF_H_1554 |
-
-
- | 239 |
- HB_424_HD |
- HD |
- M |
- 5804_VC_H_1558 |
-
-
- | 240 |
- HB_444_HD |
- HD |
- M |
- 5856_VC_H_1567 |
-
-
- | 241 |
- HB_457_HD |
- HD |
- M |
- 5896_VC_H_1570 |
-
-
- | 242 |
- HB_466_HD |
- HD |
- M |
- 5910_PF_H_1572 |
-
-
- | 243 |
- HB_478_HD |
- HD |
- M |
- 5941_CR_H_1583 |
-
-
- | 244 |
- HB_487_HD |
- HD |
- F |
- 5964_VC_H_1597 |
-
-
- | 245 |
- HB_511_HD |
- HD |
- M |
- 6019_PF_H_2198 |
-
-
- | 246 |
- HB_513_HD |
- HD |
- F |
- 6024_VC_H_1612 |
-
-
- | 247 |
- HB_515_HD |
- HD |
- F |
- 6028_CR_H_1613 |
-
-
- | 248 |
- HB_518_HD |
- HD |
- M |
- 6033_VC_H_1618 |
-
-
- | 249 |
- HB_522_HD |
- HD |
- M |
- 6037_PF_H_1626 |
-
-
- | 250 |
- HB_527_HD |
- HD |
- F |
- 6047_VC_H_1639 |
-
-
- | 251 |
- HB_528_HD |
- HD |
- M |
- 6051_PF_H_1641 |
-
-
- | 252 |
- HB_530_HD |
- HD |
- M |
- 6054_VC_H_1648 |
-
-
- | 253 |
- HB_537_HD |
- HD |
- F |
- 6071_PF_H_1653 |
-
-
- | 254 |
- HB_549_HD |
- HD |
- M |
- 6119_CR_H_1670 |
-
-
- | 255 |
- HB_593_HD |
- HD |
- NA |
- 6219_CR_H_2567 |
-
-
- | 256 |
- HB_610_HD |
- HD |
- NA |
- 6275_PF_H_1692 |
-
-
- | 257 |
- HB_616_HD |
- HD |
- F |
- 6284_CR_H_1694 |
-
-
- | 258 |
- HB_626_HD |
- HD |
- M |
- 6315_VC_H_1702 |
-
-
- | 259 |
- HB_639_HD |
- HD |
- F |
- 6344_CR_H_1703 |
-
-
- | 260 |
- HB_649_HD |
- HD |
- F |
- 6382_CR_H_1709 |
-
-
- | 261 |
- HB_661_HD |
- HD |
- M |
- 6408_VC_H_1714 |
-
-
- | 262 |
- HB_682_HD |
- HD |
- M |
- 6467_PF_H_1725 |
-
-
- | 263 |
- HB_683_HD |
- HD |
- M |
- 6472_VC_H_1729 |
-
-
- | 264 |
- HB_691_HD |
- HD |
- F |
- 6493_VC_H_1732 |
-
-
- | 265 |
- HB_692_HD |
- HD |
- M |
- 6495_CR_H_1733 |
-
-
- | 266 |
- HB_707_HD |
- HD |
- M |
- 6535_PF_H_1737 |
-
-
- | 267 |
- HB_709_HD |
- HD |
- F |
- 6539_CR_H_1739 |
-
-
- | 268 |
- HB_725_HD |
- HD |
- M |
- 6572_PF_H_1746 |
-
-
- | 269 |
- HB_732_HD |
- HD |
- F |
- 6584_VC_H_1750 |
-
-
- | 270 |
- HB_734_HD |
- HD |
- F |
- 6587_CR_H_1751 |
-
-
- | 271 |
- HB_748_HD |
- HD |
- NA |
- 6615_VC_H_2315 |
-
-
- | 272 |
- HB_750_HD |
- HD |
- NA |
- 6628_PF_H_2326 |
-
-
- | 273 |
- HB_758_HD |
- HD |
- NA |
- 6643_VC_H_2602 |
-
-
- | 274 |
- HB_760_HD |
- HD |
- M |
- 6646_PF_H_1761 |
-
-
- | 275 |
- HB_762_HD |
- HD |
- M |
- 6650_VC_H_1765 |
-
-
- | 276 |
- HB_766_HD |
- HD |
- M |
- 6658_VC_H_1768 |
-
-
- | 277 |
- HB_768_HD |
- HD |
- NA |
- 6663_VC_H_1771 |
-
-
- | 278 |
- HB_769_HD |
- HD |
- M |
- 6666_VC_H_1774 |
-
-
- | 279 |
- HB_774_HD |
- HD |
- NA |
- 6689_PF_H_2344 |
-
-
- | 280 |
- HB_778_HD |
- HD |
- NA |
- 6696_PF_H_2356 |
-
-
- | 281 |
- HB_780_HD |
- HD |
- NA |
- 6704_PF_H_2362 |
-
-
- | 282 |
- HB_790_HD |
- HD |
- NA |
- 6788_PF_H_2389 |
-
-
- | 283 |
- HB_800_HD |
- HD |
- NA |
- 6807_PF_H_2419 |
-
-
- | 284 |
- HB_802_HD |
- HD |
- NA |
- 6811_PF_H_2425 |
-
-
- | 285 |
- HB_045_AD |
- AD |
- NA |
- 3734_CR_A_0122 |
-
-
- | 286 |
- HB_048_AD |
- AD |
- NA |
- 3791_CR_A_0128 |
-
-
- | 287 |
- HB_053_AD |
- AD |
- NA |
- 3877_CR_A_0134 |
-
-
- | 288 |
- HB_055_AD |
- AD |
- NA |
- 3893_VC_A_0142 |
-
-
- | 289 |
- HB_068_AD |
- AD |
- NA |
- 4349_VC_A_0148 |
-
-
- | 290 |
- HB_082_AD |
- AD |
- NA |
- 4712_CR_A_0309 |
-
-
- | 291 |
- HB_085_AD |
- AD |
- NA |
- 4726_VC_A_0311 |
-
-
- | 292 |
- HB_087_AD |
- AD |
- NA |
- 4730_CR_A_0315 |
-
-
- | 293 |
- HB_089_AD |
- AD |
- NA |
- 4733_VC_A_0320 |
-
-
- | 294 |
- HB_093_AD |
- AD |
- NA |
- 4749_VC_A_0323 |
-
-
- | 295 |
- HB_095_AD |
- AD |
- NA |
- 4759_CR_A_0327 |
-
-
- | 296 |
- HB_097_AD |
- AD |
- NA |
- 4773_CR_A_0866 |
-
-
- | 297 |
- HB_099_AD |
- AD |
- NA |
- 4785_VC_A_0332 |
-
-
- | 298 |
- HB_100_AD |
- AD |
- NA |
- 4795_VC_A_0335 |
-
-
- | 299 |
- HB_103_AD |
- AD |
- NA |
- 4811_VC_A_0341 |
-
-
- | 300 |
- HB_104_AD |
- AD |
- NA |
- 4813_CR_A_0345 |
-
-
- | 301 |
- HB_112_AD |
- AD |
- NA |
- 4842_VC_A_0870 |
-
-
- | 302 |
- HB_113_AD |
- AD |
- NA |
- 4850_CR_A_0351 |
-
-
- | 303 |
- HB_114_AD |
- AD |
- NA |
- 4852_CR_A_0354 |
-
-
- | 304 |
- HB_117_AD |
- AD |
- NA |
- 4868_VC_A_0874 |
-
-
- | 305 |
- HB_122_AD |
- AD |
- NA |
- 4904_CR_A_1132 |
-
-
- | 306 |
- HB_123_AD |
- AD |
- NA |
- 4905_VC_A_0884 |
-
-
- | 307 |
- HB_124_AD |
- AD |
- NA |
- 4916_VC_A_0886 |
-
-
- | 308 |
- HB_125_AD |
- AD |
- NA |
- 4917_CR_A_0360 |
-
-
- | 309 |
- HB_126_AD |
- AD |
- NA |
- 4921_VC_A_0362 |
-
-
- | 310 |
- HB_128_AD |
- AD |
- NA |
- 4936_CR_A_0369 |
-
-
- | 311 |
- HB_130_AD |
- AD |
- NA |
- 4939_VC_A_0888 |
-
-
- | 312 |
- HB_131_AD |
- AD |
- NA |
- 4944_CR_A_0889 |
-
-
- | 313 |
- HB_132_AD |
- AD |
- NA |
- 4946_CR_A_0372 |
-
-
- | 314 |
- HB_134_AD |
- AD |
- NA |
- 4951_CR_A_0891 |
-
-
- | 315 |
- HB_135_AD |
- AD |
- NA |
- 4953_VC_A_0893 |
-
-
- | 316 |
- HB_136_AD |
- AD |
- NA |
- 4965_VC_A_0160 |
-
-
- | 317 |
- HB_137_AD |
- AD |
- NA |
- 4966_VC_A_0374 |
-
-
- | 318 |
- HB_138_AD |
- AD |
- NA |
- 4969_VC_A_0895 |
-
-
- | 319 |
- HB_140_AD |
- AD |
- NA |
- 4993_CR_A_0896 |
-
-
- | 320 |
- HB_146_AD |
- AD |
- NA |
- 5018_CR_A_0384 |
-
-
- | 321 |
- HB_148_AD |
- AD |
- NA |
- 5022_VC_A_0386 |
-
-
- | 322 |
- HB_150_AD |
- AD |
- NA |
- 5031_VC_A_0392 |
-
-
- | 323 |
- HB_151_AD |
- AD |
- NA |
- 5033_CR_A_0396 |
-
-
- | 324 |
- HB_154_AD |
- AD |
- NA |
- 5048_VC_A_1321 |
-
-
- | 325 |
- HB_155_AD |
- AD |
- NA |
- 5056_VC_A_0398 |
-
-
- | 326 |
- HB_156_AD |
- AD |
- NA |
- 5057_VC_A_0163 |
-
-
- | 327 |
- HB_157_AD |
- AD |
- NA |
- 5059_VC_A_0401 |
-
-
- | 328 |
- HB_158_AD |
- AD |
- NA |
- 5061_PF_A_2612 |
-
-
- | 329 |
- HB_160_AD |
- AD |
- NA |
- 5064_PF_A_2615 |
-
-
- | 330 |
- HB_165_AD |
- AD |
- NA |
- 5092_CR_A_0899 |
-
-
- | 331 |
- HB_168_AD |
- AD |
- NA |
- 5097_VC_A_0407 |
-
-
- | 332 |
- HB_170_AD |
- AD |
- NA |
- 5101_VC_A_0410 |
-
-
- | 333 |
- HB_174_AD |
- AD |
- NA |
- 5124_PF_A_1343 |
-
-
- | 334 |
- HB_179_AD |
- AD |
- NA |
- 5145_VC_A_1351 |
-
-
- | 335 |
- HB_181_AD |
- AD |
- NA |
- 5152_CR_A_0414 |
-
-
- | 336 |
- HB_184_AD |
- AD |
- NA |
- 5166_VC_A_1354 |
-
-
- | 337 |
- HB_194_AD |
- AD |
- NA |
- 5193_VC_A_1360 |
-
-
- | 338 |
- HB_197_AD |
- AD |
- NA |
- 5202_CR_A_1368 |
-
-
- | 339 |
- HB_199_AD |
- AD |
- NA |
- 5205_VC_A_0166 |
-
-
- | 340 |
- HB_200_AD |
- AD |
- NA |
- 5210_VC_A_0905 |
-
-
- | 341 |
- HB_205_AD |
- AD |
- NA |
- 5235_VC_A_0419 |
-
-
- | 342 |
- HB_208_AD |
- AD |
- NA |
- 5249_VC_A_0422 |
-
-
- | 343 |
- HB_209_AD |
- AD |
- NA |
- 5252_VC_A_0907 |
-
-
- | 344 |
- HB_211_AD |
- AD |
- NA |
- 5257_VC_A_0169 |
-
-
- | 345 |
- HB_216_AD |
- AD |
- NA |
- 5272_VC_A_0425 |
-
-
- | 346 |
- HB_219_AD |
- AD |
- NA |
- 5279_CR_A_0147 |
-
-
- | 347 |
- HB_221_AD |
- AD |
- NA |
- 5283_VC_A_0145 |
-
-
- | 348 |
- HB_222_AD |
- AD |
- NA |
- 5285_VC_A_0141 |
-
-
- | 349 |
- HB_224_AD |
- AD |
- NA |
- 5288_VC_A_0428 |
-
-
- | 350 |
- HB_230_AD |
- AD |
- NA |
- 5301_VC_A_0174 |
-
-
- | 351 |
- HB_231_AD |
- AD |
- NA |
- 5305_VC_A_1384 |
-
-
- | 352 |
- HB_232_AD |
- AD |
- NA |
- 5310_CR_A_0176 |
-
-
- | 353 |
- HB_234_AD |
- AD |
- NA |
- 5313_PF_A_2618 |
-
-
- | 354 |
- HB_236_AD |
- AD |
- NA |
- 5317_PF_A_2624 |
-
-
- | 355 |
- HB_238_AD |
- AD |
- NA |
- 5322_CR_A_2632 |
-
-
- | 356 |
- HB_240_AD |
- AD |
- NA |
- 5325_VC_A_0137 |
-
-
- | 357 |
- HB_244_AD |
- AD |
- NA |
- 5337_VC_A_1387 |
-
-
- | 358 |
- HB_245_AD |
- AD |
- NA |
- 5339_VC_A_0181 |
-
-
- | 359 |
- HB_250_AD |
- AD |
- NA |
- 5346_VC_A_1393 |
-
-
- | 360 |
- HB_251_AD |
- AD |
- NA |
- 5350_VC_A_0184 |
-
-
- | 361 |
- HB_252_AD |
- AD |
- NA |
- 5355_VC_A_0133 |
-
-
- | 362 |
- HB_253_AD |
- AD |
- NA |
- 5359_CR_A_1395 |
-
-
- | 363 |
- HB_258_AD |
- AD |
- NA |
- 5370_PF_A_1400 |
-
-
- | 364 |
- HB_259_AD |
- AD |
- NA |
- 5371_PF_A_2636 |
-
-
- | 365 |
- HB_260_AD |
- AD |
- NA |
- 5375_VC_A_0188 |
-
-
- | 366 |
- HB_263_AD |
- AD |
- NA |
- 5381_VC_A_0022 |
-
-
- | 367 |
- HB_265_AD |
- AD |
- NA |
- 5385_VC_A_1402 |
-
-
- | 368 |
- HB_267_AD |
- AD |
- NA |
- 5389_VC_A_0928 |
-
-
- | 369 |
- HB_268_AD |
- AD |
- NA |
- 5390_CR_A_0151 |
-
-
- | 370 |
- HB_273_AD |
- AD |
- NA |
- 5400_PF_A_2645 |
-
-
- | 371 |
- HB_274_AD |
- AD |
- NA |
- 5401_VC_A_0931 |
-
-
- | 372 |
- HB_275_AD |
- AD |
- NA |
- 5404_PF_A_2648 |
-
-
- | 373 |
- HB_276_AD |
- AD |
- NA |
- 5406_VC_A_0933 |
-
-
- | 374 |
- HB_277_AD |
- AD |
- NA |
- 5407_PF_A_2651 |
-
-
- | 375 |
- HB_280_AD |
- AD |
- NA |
- 5412_VC_A_0935 |
-
-
- | 376 |
- HB_281_AD |
- AD |
- NA |
- 5413_PF_A_2657 |
-
-
- | 377 |
- HB_283_AD |
- AD |
- NA |
- 5419_VC_A_0937 |
-
-
- | 378 |
- HB_284_AD |
- AD |
- NA |
- 5420_VC_A_0939 |
-
-
- | 379 |
- HB_285_AD |
- AD |
- NA |
- 5421_CR_A_0432 |
-
-
- | 380 |
- HB_286_AD |
- AD |
- NA |
- 5423_PF_A_2660 |
-
-
- | 381 |
- HB_288_AD |
- AD |
- NA |
- 5425_PF_A_2666 |
-
-
- | 382 |
- HB_289_AD |
- AD |
- NA |
- 5426_VC_A_1405 |
-
-
- | 383 |
- HB_290_AD |
- AD |
- NA |
- 5433_VC_A_0434 |
-
-
- | 384 |
- HB_296_AD |
- AD |
- NA |
- 5456_PF_A_2675 |
-
-
- | 385 |
- HB_299_AD |
- AD |
- NA |
- 5461_VC_A_0192 |
-
-
- | 386 |
- HB_302_AD |
- AD |
- NA |
- 5465_PF_A_2678 |
-
-
- | 387 |
- HB_303_AD |
- AD |
- NA |
- 5469_VC_A_1417 |
-
-
- | 388 |
- HB_305_AD |
- AD |
- NA |
- 5479_PF_A_1421 |
-
-
- | 389 |
- HB_306_AD |
- AD |
- NA |
- 5480_VC_A_0437 |
-
-
- | 390 |
- HB_307_AD |
- AD |
- NA |
- 5482_VC_A_0028 |
-
-
- | 391 |
- HB_308_AD |
- AD |
- NA |
- 5483_VC_A_0941 |
-
-
- | 392 |
- HB_309_AD |
- AD |
- NA |
- 5487_CR_A_0441 |
-
-
- | 393 |
- HB_310_AD |
- AD |
- NA |
- 5488_CR_A_0194 |
-
-
- | 394 |
- HB_312_AD |
- AD |
- NA |
- 5500_VC_A_0198 |
-
-
- | 395 |
- HB_313_AD |
- AD |
- NA |
- 5502_PF_A_2684 |
-
-
- | 396 |
- HB_315_AD |
- AD |
- NA |
- 5513_PF_A_2687 |
-
-
- | 397 |
- HB_316_AD |
- AD |
- NA |
- 5516_PF_A_2690 |
-
-
- | 398 |
- HB_317_AD |
- AD |
- NA |
- 5517_PF_A_2693 |
-
-
- | 399 |
- HB_318_AD |
- AD |
- NA |
- 5518_CR_A_0030 |
-
-
- | 400 |
- HB_319_AD |
- AD |
- NA |
- 5519_CR_A_2695 |
-
-
- | 401 |
- HB_320_AD |
- AD |
- NA |
- 5520_PF_A_2699 |
-
-
- | 402 |
- HB_322_AD |
- AD |
- NA |
- 5527_VC_A_0945 |
-
-
- | 403 |
- HB_325_AD |
- AD |
- NA |
- 5532_PF_A_2702 |
-
-
- | 404 |
- HB_328_AD |
- AD |
- NA |
- 5541_PF_A_2705 |
-
-
- | 405 |
- HB_330_AD |
- AD |
- NA |
- 5544_VC_A_0201 |
-
-
- | 406 |
- HB_334_AD |
- AD |
- NA |
- 5554_VC_A_0452 |
-
-
- | 407 |
- HB_335_AD |
- AD |
- NA |
- 5557_VC_A_0950 |
-
-
- | 408 |
- HB_337_AD |
- AD |
- NA |
- 5560_VC_A_0204 |
-
-
- | 409 |
- HB_342_AD |
- AD |
- NA |
- 5571_PF_A_1430 |
-
-
- | 410 |
- HB_345_AD |
- AD |
- NA |
- 5583_PF_A_2708 |
-
-
- | 411 |
- HB_347_AD |
- AD |
- NA |
- 5589_PF_A_2714 |
-
-
- | 412 |
- HB_349_AD |
- AD |
- NA |
- 5592_PF_A_2717 |
-
-
- | 413 |
- HB_352_AD |
- AD |
- NA |
- 5604_VC_A_0037 |
-
-
- | 414 |
- HB_353_AD |
- AD |
- NA |
- 5607_PF_A_2723 |
-
-
- | 415 |
- HB_356_AD |
- AD |
- NA |
- 5615_VC_A_0041 |
-
-
- | 416 |
- HB_357_AD |
- AD |
- NA |
- 5616_CR_A_0127 |
-
-
- | 417 |
- HB_358_AD |
- AD |
- NA |
- 5617_CR_A_0456 |
-
-
- | 418 |
- HB_359_AD |
- AD |
- NA |
- 5618_CR_A_0044 |
-
-
- | 419 |
- HB_362_AD |
- AD |
- NA |
- 5625_CR_A_2495 |
-
-
- | 420 |
- HB_363_AD |
- AD |
- NA |
- 5626_CR_A_2498 |
-
-
- | 421 |
- HB_364_AD |
- AD |
- NA |
- 5629_CR_A_0390 |
-
-
- | 422 |
- HB_369_AD |
- AD |
- NA |
- 5643_VC_A_1143 |
-
-
- | 423 |
- HB_373_AD |
- AD |
- NA |
- 5654_VC_A_0047 |
-
-
- | 424 |
- HB_375_AD |
- AD |
- NA |
- 5660_CR_A_0462 |
-
-
- | 425 |
- HB_376_AD |
- AD |
- NA |
- 5661_VC_A_0464 |
-
-
- | 426 |
- HB_377_AD |
- AD |
- NA |
- 5667_VC_A_2509 |
-
-
- | 427 |
- HB_378_AD |
- AD |
- NA |
- 5668_VC_A_1438 |
-
-
- | 428 |
- HB_383_AD |
- AD |
- NA |
- 5686_CR_A_2728 |
-
-
- | 429 |
- HB_386_AD |
- AD |
- NA |
- 5695_VC_A_0953 |
-
-
- | 430 |
- HB_389_AD |
- AD |
- NA |
- 5700_VC_A_2514 |
-
-
- | 431 |
- HB_391_AD |
- AD |
- NA |
- 5705_CR_A_0474 |
-
-
- | 432 |
- HB_392_AD |
- AD |
- NA |
- 5706_VC_A_0476 |
-
-
- | 433 |
- HB_394_AD |
- AD |
- NA |
- 5713_VC_A_0479 |
-
-
- | 434 |
- HB_397_AD |
- AD |
- NA |
- 5721_CR_A_0210 |
-
-
- | 435 |
- HB_404_AD |
- AD |
- NA |
- 5735_CR_A_0489 |
-
-
- | 436 |
- HB_406_AD |
- AD |
- NA |
- 5744_CR_A_0960 |
-
-
- | 437 |
- HB_409_AD |
- AD |
- NA |
- 5749_CR_A_0159 |
-
-
- | 438 |
- HB_410_AD |
- AD |
- NA |
- 5751_CR_A_2518 |
-
-
- | 439 |
- HB_411_AD |
- AD |
- NA |
- 5755_CR_A_2731 |
-
-
- | 440 |
- HB_413_AD |
- AD |
- NA |
- 5766_VC_A_0214 |
-
-
- | 441 |
- HB_419_AD |
- AD |
- NA |
- 5790_VC_A_0217 |
-
-
- | 442 |
- HB_420_AD |
- AD |
- NA |
- 5796_CR_A_0964 |
-
-
- | 443 |
- HB_428_AD |
- AD |
- NA |
- 5811_CR_A_2524 |
-
-
- | 444 |
- HB_429_AD |
- AD |
- NA |
- 5819_CR_A_2527 |
-
-
- | 445 |
- HB_430_AD |
- AD |
- NA |
- 5822_CR_A_2530 |
-
-
- | 446 |
- HB_434_AD |
- AD |
- NA |
- 5828_CR_A_2533 |
-
-
- | 447 |
- HB_435_AD |
- AD |
- NA |
- 5831_CR_A_0222 |
-
-
- | 448 |
- HB_437_AD |
- AD |
- NA |
- 5839_CR_A_2539 |
-
-
- | 449 |
- HB_438_AD |
- AD |
- NA |
- 5843_CR_A_0227 |
-
-
- | 450 |
- HB_439_AD |
- AD |
- NA |
- 5845_CR_A_0230 |
-
-
- | 451 |
- HB_441_AD |
- AD |
- NA |
- 5849_CR_A_0233 |
-
-
- | 452 |
- HB_442_AD |
- AD |
- NA |
- 5850_CR_A_0495 |
-
-
- | 453 |
- HB_445_AD |
- AD |
- NA |
- 5858_CR_A_0969 |
-
-
- | 454 |
- HB_448_AD |
- AD |
- NA |
- 5864_CR_A_0974 |
-
-
- | 455 |
- HB_451_AD |
- AD |
- NA |
- 5871_CR_A_2542 |
-
-
- | 456 |
- HB_454_AD |
- AD |
- NA |
- 5879_CR_A_2545 |
-
-
- | 457 |
- HB_455_AD |
- AD |
- NA |
- 5887_CR_A_0976_Bis |
-
-
- | 458 |
- HB_459_AD |
- AD |
- NA |
- 5898_CR_A_2548 |
-
-
- | 459 |
- HB_460_AD |
- AD |
- NA |
- 5900_VC_A_0237 |
-
-
- | 460 |
- HB_461_AD |
- AD |
- NA |
- 5901_CR_A_0239 |
-
-
- | 461 |
- HB_469_AD |
- AD |
- NA |
- 5914_CR_A_2554 |
-
-
- | 462 |
- HB_471_AD |
- AD |
- NA |
- 5922_VC_A_0246 |
-
-
- | 463 |
- HB_473_AD |
- AD |
- NA |
- 5927_CR_A_2560 |
-
-
- | 464 |
- HB_474_AD |
- AD |
- NA |
- 5933_VC_A_1071 |
-
-
- | 465 |
- HB_477_AD |
- AD |
- NA |
- 5939_CR_A_1151 |
-
-
- | 466 |
- HB_479_AD |
- AD |
- NA |
- 5945_VC_A_0983 |
-
-
- | 467 |
- HB_484_AD |
- AD |
- NA |
- 5956_CR_A_0123 |
-
-
- | 468 |
- HB_489_AD |
- AD |
- NA |
- 5968_VC_A_1075 |
-
-
- | 469 |
- HB_491_AD |
- AD |
- NA |
- 5971_CR_A_0119 |
-
-
- | 470 |
- HB_492_AD |
- AD |
- NA |
- 5972_VC_A_0251 |
-
-
- | 471 |
- HB_494_AD |
- AD |
- NA |
- 5979_CR_A_0115 |
-
-
- | 472 |
- HB_498_AD |
- AD |
- NA |
- 5988_VC_A_0503 |
-
-
- | 473 |
- HB_502_AD |
- AD |
- NA |
- 5994_PF_A_1605 |
-
-
- | 474 |
- HB_503_AD |
- AD |
- NA |
- 5995_CR_A_2563 |
-
-
- | 475 |
- HB_510_AD |
- AD |
- NA |
- 6017_CR_A_0048 |
-
-
- | 476 |
- HB_514_AD |
- AD |
- NA |
- 6025_VC_A_0506 |
-
-
- | 477 |
- HB_517_AD |
- AD |
- NA |
- 6031_VC_A_0258 |
-
-
- | 478 |
- HB_520_AD |
- AD |
- NA |
- 6035_VC_A_1621 |
-
-
- | 479 |
- HB_523_AD |
- AD |
- NA |
- 6038_VC_A_0261 |
-
-
- | 480 |
- HB_524_AD |
- AD |
- NA |
- 6042_VC_A_1156 |
-
-
- | 481 |
- HB_525_AD |
- AD |
- NA |
- 6044_VC_A_0264 |
-
-
- | 482 |
- HB_531_AD |
- AD |
- NA |
- 6056_CR_A_0999 |
-
-
- | 483 |
- HB_533_AD |
- AD |
- NA |
- 6061_PF_A_1650 |
-
-
- | 484 |
- HB_534_AD |
- AD |
- NA |
- 6066_VC_A_0270 |
-
-
- | 485 |
- HB_535_AD |
- AD |
- NA |
- 6067_PF_A_1452 |
-
-
- | 486 |
- HB_536_AD |
- AD |
- NA |
- 6068_VC_A_0273 |
-
-
- | 487 |
- HB_545_AD |
- AD |
- NA |
- 6102_CR_A_1661 |
-
-
- | 488 |
- HB_546_AD |
- AD |
- NA |
- 6107_CR_A_0055 |
-
-
- | 489 |
- HB_550_AD |
- AD |
- NA |
- 6120_VC_A_0058 |
-
-
- | 490 |
- HB_552_AD |
- AD |
- NA |
- 6126_VC_A_1675 |
-
-
- | 491 |
- HB_553_AD |
- AD |
- NA |
- 6129_PF_A_0274 |
-
-
- | 492 |
- HB_554_AD |
- AD |
- NA |
- 6130_VC_A_1678 |
-
-
- | 493 |
- HB_555_AD |
- AD |
- NA |
- 6131_CR_A_0510 |
-
-
- | 494 |
- HB_556_AD |
- AD |
- NA |
- 6132_CR_A_0513 |
-
-
- | 495 |
- HB_558_AD |
- AD |
- NA |
- 6137_VC_A_1681 |
-
-
- | 496 |
- HB_564_AD |
- AD |
- NA |
- 6153_VC_A_1465 |
-
-
- | 497 |
- HB_565_AD |
- AD |
- NA |
- 6154_VC_A_1468 |
-
-
- | 498 |
- HB_566_AD |
- AD |
- NA |
- 6157_VC_A_0062 |
-
-
- | 499 |
- HB_568_AD |
- AD |
- NA |
- 6164_CR_A_1005 |
-
-
- | 500 |
- HB_571_AD |
- AD |
- NA |
- 6171_CR_A_0065 |
-
-
- | 501 |
- HB_573_AD |
- AD |
- NA |
- 6174_VC_A_0068 |
-
-
- | 502 |
- HB_576_AD |
- AD |
- NA |
- 6180_CR_A_0281 |
-
-
- | 503 |
- HB_583_AD |
- AD |
- NA |
- 6194_VC_A_0071 |
-
-
- | 504 |
- HB_585_AD |
- AD |
- NA |
- 6198_VC_A_0073 |
-
-
- | 505 |
- HB_590_AD |
- AD |
- NA |
- 6215_VC_A_0518 |
-
-
- | 506 |
- HB_591_AD |
- AD |
- NA |
- 6216_VC_A_1476 |
-
-
- | 507 |
- HB_592_AD |
- AD |
- NA |
- 6218_CR_A_0522 |
-
-
- | 508 |
- HB_594_AD |
- AD |
- NA |
- 6223_VC_A_0288 |
-
-
- | 509 |
- HB_596_AD |
- AD |
- NA |
- 6226_CR_A_0076 |
-
-
- | 510 |
- HB_597_AD |
- AD |
- NA |
- 6227_VC_A_0080 |
-
-
- | 511 |
- HB_598_AD |
- AD |
- NA |
- 6231_VC_A_1479 |
-
-
- | 512 |
- HB_605_AD |
- AD |
- NA |
- 6261_VC_A_0084 |
-
-
- | 513 |
- HB_608_AD |
- AD |
- NA |
- 6268_CR_A_0525 |
-
-
- | 514 |
- HB_611_AD |
- AD |
- NA |
- 6279_VC_A_0089 |
-
-
- | 515 |
- HB_612_AD |
- AD |
- NA |
- 6280_VC_A_0091 |
-
-
- | 516 |
- HB_613_AD |
- AD |
- NA |
- 6281_CR_A_0528 |
-
-
- | 517 |
- HB_621_AD |
- AD |
- NA |
- 6308_VC_A_1503 |
-
-
- | 518 |
- HB_623_AD |
- AD |
- NA |
- 6311_CR_A_0531 |
-
-
- | 519 |
- HB_624_AD |
- AD |
- NA |
- 6312_CR_A_0534 |
-
-
- | 520 |
- HB_630_AD |
- AD |
- NA |
- 6324_PF_A_1514 |
-
-
- | 521 |
- HB_633_AD |
- AD |
- NA |
- 6332_VC_A_1518 |
-
-
- | 522 |
- HB_634_AD |
- AD |
- NA |
- 6335_VC_A_0536 |
-
-
- | 523 |
- HB_635_AD |
- AD |
- NA |
- 6336_CR_A_0290 |
-
-
- | 524 |
- HB_636_AD |
- AD |
- NA |
- 6338_VC_A_0539 |
-
-
- | 525 |
- HB_642_AD |
- AD |
- NA |
- 6358_VC_A_0545 |
-
-
- | 526 |
- HB_652_AD |
- AD |
- NA |
- 6387_VC_A_0093 |
-
-
- | 527 |
- HB_657_AD |
- AD |
- NA |
- 6394_VC_A_0551 |
-
-
- | 528 |
- HB_664_AD |
- AD |
- NA |
- 6416_VC_A_1095 |
-
-
- | 529 |
- HB_666_AD |
- AD |
- NA |
- 6422_CR_A_0555 |
-
-
- | 530 |
- HB_669_AD |
- AD |
- NA |
- 6431_VC_A_0294 |
-
-
- | 531 |
- HB_674_AD |
- AD |
- NA |
- 6449_VC_A_1183 |
-
-
- | 532 |
- HB_680_AD |
- AD |
- NA |
- 6458_CR_A_2570 |
-
-
- | 533 |
- HB_685_AD |
- AD |
- NA |
- 6481_VC_A_0560 |
-
-
- | 534 |
- HB_690_AD |
- AD |
- NA |
- 6489_CR_A_0100 |
-
-
- | 535 |
- HB_696_AD |
- AD |
- NA |
- 6511_VC_A_1119 |
-
-
- | 536 |
- HB_698_AD |
- AD |
- NA |
- 6515_CR_A_0564 |
-
-
- | 537 |
- HB_699_AD |
- AD |
- NA |
- 6518_VC_A_0103 |
-
-
- | 538 |
- HB_703_AD |
- AD |
- NA |
- 6523_VC_A_0107 |
-
-
- | 539 |
- HB_704_AD |
- AD |
- NA |
- 6530_VC_A_0112 |
-
-
- | 540 |
- HB_706_AD |
- AD |
- NA |
- 6534_VC_A_0306 |
-
-
- | 541 |
- HB_712_AD |
- AD |
- NA |
- 6546_PF_A_1194 |
-
-
- | 542 |
- HB_713_AD |
- AD |
- NA |
- 6548_PF_A_1541 |
-
-
- | 543 |
- HB_715_AD |
- AD |
- NA |
- 6550_VC_A_1201 |
-
-
- | 544 |
- HB_718_AD |
- AD |
- NA |
- 6554_PF_A_1203 |
-
-
- | 545 |
- HB_720_AD |
- AD |
- NA |
- 6559_PF_A_2287 |
-
-
- | 546 |
- HB_722_AD |
- AD |
- NA |
- 6561_CR_A_2582 |
-
-
- | 547 |
- HB_723_AD |
- AD |
- NA |
- 6562_PF_A_2290 |
-
-
- | 548 |
- HB_724_AD |
- AD |
- NA |
- 6564_CR_A_2585 |
-
-
- | 549 |
- HB_727_AD |
- AD |
- NA |
- 6575_CR_A_2298 |
-
-
- | 550 |
- HB_728_AD |
- AD |
- NA |
- 6577_PF_A_2299 |
-
-
- | 551 |
- HB_729_AD |
- AD |
- NA |
- 6578_PF_A_2302 |
-
-
- | 552 |
- HB_731_AD |
- AD |
- NA |
- 6582_VC_A_1207 |
-
-
- | 553 |
- HB_733_AD |
- AD |
- NA |
- 6585_VC_A_1210 |
-
-
- | 554 |
- HB_736_AD |
- AD |
- NA |
- 6590_PF_A_1215 |
-
-
- | 555 |
- HB_743_AD |
- AD |
- NA |
- 6603_PF_A_1448 |
-
-
- | 556 |
- HB_745_AD |
- AD |
- NA |
- 6610_PF_A_1227 |
-
-
- | 557 |
- HB_746_AD |
- AD |
- NA |
- 6612_PF_A_2308 |
-
-
- | 558 |
- HB_749_AD |
- AD |
- NA |
- 6617_VC_A_2587 |
-
-
- | 559 |
- HB_751_AD |
- AD |
- NA |
- 6629_VC_A_2330 |
-
-
- | 560 |
- HB_752_AD |
- AD |
- NA |
- 6630_VC_A_2590 |
-
-
- | 561 |
- HB_753_AD |
- AD |
- NA |
- 6632_PF_A_2332 |
-
-
- | 562 |
- HB_754_AD |
- AD |
- NA |
- 6637_VC_A_2596 |
-
-
- | 563 |
- HB_755_AD |
- AD |
- NA |
- 6638_VC_A_2599 |
-
-
- | 564 |
- HB_756_AD |
- AD |
- NA |
- 6639_VC_A_2336 |
-
-
- | 565 |
- HB_757_AD |
- AD |
- NA |
- 6641_PF_A_2338 |
-
-
- | 566 |
- HB_763_AD |
- AD |
- NA |
- 6654_VC_A_1237 |
-
-
- | 567 |
- HB_773_AD |
- AD |
- NA |
- 6681_VC_A_1252 |
-
-
- | 568 |
- HB_775_AD |
- AD |
- NA |
- 6693_VC_A_2348 |
-
-
- | 569 |
- HB_776_AD |
- AD |
- NA |
- 6694_VC_A_2351 |
-
-
- | 570 |
- HB_777_AD |
- AD |
- NA |
- 6695_PF_A_2353 |
-
-
- | 571 |
- HB_779_AD |
- AD |
- NA |
- 6699_PF_A_2359 |
-
-
- | 572 |
- HB_781_AD |
- AD |
- NA |
- 6708_VC_A_2366 |
-
-
- | 573 |
- HB_782_AD |
- AD |
- NA |
- 6776_PF_A_2607 |
-
-
- | 574 |
- HB_783_AD |
- AD |
- NA |
- 6778_PF_A_2368 |
-
-
- | 575 |
- HB_784_AD |
- AD |
- NA |
- 6779_PF_A_2371 |
-
-
- | 576 |
- HB_785_AD |
- AD |
- NA |
- 6780_PF_A_2374 |
-
-
- | 577 |
- HB_786_AD |
- AD |
- NA |
- 6782_PF_A_2377 |
-
-
- | 578 |
- HB_787_AD |
- AD |
- NA |
- 6784_PF_A_2380 |
-
-
- | 579 |
- HB_788_AD |
- AD |
- NA |
- 6785_CR_A_2385 |
-
-
- | 580 |
- HB_789_AD |
- AD |
- NA |
- 6787_CR_A_2388 |
-
-
- | 581 |
- HB_791_AD |
- AD |
- NA |
- 6790_PF_A_2392 |
-
-
- | 582 |
- HB_792_AD |
- AD |
- NA |
- 6791_PF_A_2395 |
-
-
- | 583 |
- HB_793_AD |
- AD |
- NA |
- 6793_PF_A_2398 |
-
-
- | 584 |
- HB_794_AD |
- AD |
- NA |
- 6794_PF_A_2401 |
-
-
- | 585 |
- HB_795_AD |
- AD |
- NA |
- 6797_PF_A_2404 |
-
-
- | 586 |
- HB_796_AD |
- AD |
- NA |
- 6798_PF_A_2407 |
-
-
- | 587 |
- HB_797_AD |
- AD |
- NA |
- 6799_VC_A_2411 |
-
-
- | 588 |
- HB_798_AD |
- AD |
- NA |
- 6801_VC_A_2414 |
-
-
- | 589 |
- HB_799_AD |
- AD |
- NA |
- 6803_VC_A_2417 |
-
-
- | 590 |
- HB_801_AD |
- AD |
- NA |
- 6809_PF_A_2422 |
-
-
- | 591 |
- HB_803_AD |
- AD |
- NA |
- 6818_CR_A_2430 |
-
-
-
- |
-
-
-
diff --git a/general/datasets/HBTRC_MLVC_N_0611/notes.rtf b/general/datasets/HBTRC_MLVC_N_0611/notes.rtf
deleted file mode 100644
index ff90e34..0000000
--- a/general/datasets/HBTRC_MLVC_N_0611/notes.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Species: Human
-Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
-Disease: Neurological Disease
-Investigator: Francine Benes/ Eric Schadt
-Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
-Approximate Number Subjects: 803
diff --git a/general/datasets/HBTRC_MLVC_N_0611/summary.rtf b/general/datasets/HBTRC_MLVC_N_0611/summary.rtf
deleted file mode 100644
index 5cde3bf..0000000
--- a/general/datasets/HBTRC_MLVC_N_0611/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/HET3_ITPPublish/specifics.rtf b/general/datasets/HET3_ITPPublish/specifics.rtf
deleted file mode 100644
index 4c7f4e9..0000000
--- a/general/datasets/HET3_ITPPublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Aging Mouse Lifespan Studies (NIA UM-HET3)
\ No newline at end of file
diff --git a/general/datasets/HET3_ITPPublish/summary.rtf b/general/datasets/HET3_ITPPublish/summary.rtf
deleted file mode 100644
index 4a3de8b..0000000
--- a/general/datasets/HET3_ITPPublish/summary.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-http://www-personal.umich.edu/~millerr/ITP.htm
-
-https://www.nia.nih.gov/research/dab/interventions-testing-program-itp/frequently-asked-questions-about-itp
-
-https://www.nia.nih.gov/research/dab/interventions-testing-program-itp/compounds-testing
diff --git a/general/datasets/HMS_mm8_MDP_Spl_CD4_1116/experiment-design.rtf b/general/datasets/HMS_mm8_MDP_Spl_CD4_1116/experiment-design.rtf
deleted file mode 100644
index 29bf7fb..0000000
--- a/general/datasets/HMS_mm8_MDP_Spl_CD4_1116/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201955/
diff --git a/general/datasets/HMS_mm8_MDP_Spl_CD4_1116/specifics.rtf b/general/datasets/HMS_mm8_MDP_Spl_CD4_1116/specifics.rtf
deleted file mode 100644
index 0b70afe..0000000
--- a/general/datasets/HMS_mm8_MDP_Spl_CD4_1116/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Gene Level
\ No newline at end of file
diff --git a/general/datasets/HMS_mm8_MDP_Spl_CD4_1116/summary.rtf b/general/datasets/HMS_mm8_MDP_Spl_CD4_1116/summary.rtf
deleted file mode 100644
index c81e1bb..0000000
--- a/general/datasets/HMS_mm8_MDP_Spl_CD4_1116/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-To determine the breadth and underpinning of changes in immunocyte gene expression due to genetic variation in mice, we performed, as part of the Immunological Genome Project, gene expression profiling for CD4(+) T cells and neutrophils purified from 39 inbred strains of the Mouse Phenome Database. Considering both cell types, a large number of transcripts showed significant variation across the inbred strains, with 22% of the transcriptome varying by 2-fold or more. These included 119 loci with apparent complete loss of function, where the corresponding transcript was not expressed in some of the strains, representing a useful resource of "natural knockouts." We identified 1222 cis-expression quantitative trait loci (cis-eQTL) that control some of this variation. Most (60%) cis-eQTLs were shared between T cells and neutrophils, but a significant portion uniquely impacted one of the cell types, suggesting cell type-specific regulatory mechanisms. Using a conditional regression algorithm, we predicted regulatory interactions between transcription factors and potential targets, and we demonstrated that these predictions overlap with regulatory interactions inferred from transcriptional changes during immunocyte differentiation. Finally, comparison of these and parallel data from CD4(+) T cells of healthy humans demonstrated intriguing similarities in variability of a gene's expression: the most variable genes tended to be the same in both species, and there was an overlap in genes subject to strong cis-acting genetic variants. We speculate that this "conservation of variation" reflects a differential constraint on intraspecies variation in expression levels of different genes, either through lower pressure for some genes, or by favoring variability for others.
diff --git a/general/datasets/HRDPPublish/specifics.rtf b/general/datasets/HRDPPublish/specifics.rtf
deleted file mode 100644
index 6ea3cd9..0000000
--- a/general/datasets/HRDPPublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HRDP Published Phenotypes
\ No newline at end of file
diff --git a/general/datasets/HRDPPublish/summary.rtf b/general/datasets/HRDPPublish/summary.rtf
deleted file mode 100644
index bce5ebd..0000000
--- a/general/datasets/HRDPPublish/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HRDP Published Phenotypes
diff --git a/general/datasets/HSNIH_PalmerPublish/specifics.rtf b/general/datasets/HSNIH_PalmerPublish/specifics.rtf
deleted file mode 100644
index 6bb3581..0000000
--- a/general/datasets/HSNIH_PalmerPublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HSNIH Published Phenotypes
\ No newline at end of file
diff --git a/general/datasets/HSNIH_PalmerPublish/summary.rtf b/general/datasets/HSNIH_PalmerPublish/summary.rtf
deleted file mode 100644
index 2503d26..0000000
--- a/general/datasets/HSNIH_PalmerPublish/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/HSNIH_Rat_Acbc_RSeq_0818/specifics.rtf b/general/datasets/HSNIH_Rat_Acbc_RSeq_0818/specifics.rtf
deleted file mode 100644
index db20c9a..0000000
--- a/general/datasets/HSNIH_Rat_Acbc_RSeq_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Nucleus Accumbens Core
\ No newline at end of file
diff --git a/general/datasets/HSNIH_Rat_Acbc_RSeq_0818/summary.rtf b/general/datasets/HSNIH_Rat_Acbc_RSeq_0818/summary.rtf
deleted file mode 100644
index 2503d26..0000000
--- a/general/datasets/HSNIH_Rat_Acbc_RSeq_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/HSNIH_Rat_Acbc_RSeqlog2_0818/specifics.rtf b/general/datasets/HSNIH_Rat_Acbc_RSeqlog2_0818/specifics.rtf
deleted file mode 100644
index 843d470..0000000
--- a/general/datasets/HSNIH_Rat_Acbc_RSeqlog2_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Log2
\ No newline at end of file
diff --git a/general/datasets/HSNIH_Rat_Acbc_RSeqlog2_0818/summary.rtf b/general/datasets/HSNIH_Rat_Acbc_RSeqlog2_0818/summary.rtf
deleted file mode 100644
index 2503d26..0000000
--- a/general/datasets/HSNIH_Rat_Acbc_RSeqlog2_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/HSNIH_Rat_IL_RSeq_0818/specifics.rtf b/general/datasets/HSNIH_Rat_IL_RSeq_0818/specifics.rtf
deleted file mode 100644
index 67ff940..0000000
--- a/general/datasets/HSNIH_Rat_IL_RSeq_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Infralimbic Cortex
\ No newline at end of file
diff --git a/general/datasets/HSNIH_Rat_IL_RSeq_0818/summary.rtf b/general/datasets/HSNIH_Rat_IL_RSeq_0818/summary.rtf
deleted file mode 100644
index 2503d26..0000000
--- a/general/datasets/HSNIH_Rat_IL_RSeq_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/HSNIH_Rat_IL_RSeqlog2_0818/specifics.rtf b/general/datasets/HSNIH_Rat_IL_RSeqlog2_0818/specifics.rtf
deleted file mode 100644
index 843d470..0000000
--- a/general/datasets/HSNIH_Rat_IL_RSeqlog2_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Log2
\ No newline at end of file
diff --git a/general/datasets/HSNIH_Rat_IL_RSeqlog2_0818/summary.rtf b/general/datasets/HSNIH_Rat_IL_RSeqlog2_0818/summary.rtf
deleted file mode 100644
index 2503d26..0000000
--- a/general/datasets/HSNIH_Rat_IL_RSeqlog2_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/HSNIH_Rat_LHB_RSeq_0818/specifics.rtf b/general/datasets/HSNIH_Rat_LHB_RSeq_0818/specifics.rtf
deleted file mode 100644
index e3b7857..0000000
--- a/general/datasets/HSNIH_Rat_LHB_RSeq_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Lateral Habenula
\ No newline at end of file
diff --git a/general/datasets/HSNIH_Rat_LHB_RSeq_0818/summary.rtf b/general/datasets/HSNIH_Rat_LHB_RSeq_0818/summary.rtf
deleted file mode 100644
index 2503d26..0000000
--- a/general/datasets/HSNIH_Rat_LHB_RSeq_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/HSNIH_Rat_LHB_RSeqlog2_0818/specifics.rtf b/general/datasets/HSNIH_Rat_LHB_RSeqlog2_0818/specifics.rtf
deleted file mode 100644
index 843d470..0000000
--- a/general/datasets/HSNIH_Rat_LHB_RSeqlog2_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Log2
\ No newline at end of file
diff --git a/general/datasets/HSNIH_Rat_LHB_RSeqlog2_0818/summary.rtf b/general/datasets/HSNIH_Rat_LHB_RSeqlog2_0818/summary.rtf
deleted file mode 100644
index 2503d26..0000000
--- a/general/datasets/HSNIH_Rat_LHB_RSeqlog2_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/HSNIH_Rat_PL_RSeq_0818/specifics.rtf b/general/datasets/HSNIH_Rat_PL_RSeq_0818/specifics.rtf
deleted file mode 100644
index 282c9b5..0000000
--- a/general/datasets/HSNIH_Rat_PL_RSeq_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Prelimbic Cortex
\ No newline at end of file
diff --git a/general/datasets/HSNIH_Rat_PL_RSeq_0818/summary.rtf b/general/datasets/HSNIH_Rat_PL_RSeq_0818/summary.rtf
deleted file mode 100644
index 2503d26..0000000
--- a/general/datasets/HSNIH_Rat_PL_RSeq_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/HSNIH_Rat_PL_RSeqlog2_0818/specifics.rtf b/general/datasets/HSNIH_Rat_PL_RSeqlog2_0818/specifics.rtf
deleted file mode 100644
index 843d470..0000000
--- a/general/datasets/HSNIH_Rat_PL_RSeqlog2_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Log2
\ No newline at end of file
diff --git a/general/datasets/HSNIH_Rat_PL_RSeqlog2_0818/summary.rtf b/general/datasets/HSNIH_Rat_PL_RSeqlog2_0818/summary.rtf
deleted file mode 100644
index 2503d26..0000000
--- a/general/datasets/HSNIH_Rat_PL_RSeqlog2_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/HSNIH_Rat_VoLo_RSeq_0818/specifics.rtf b/general/datasets/HSNIH_Rat_VoLo_RSeq_0818/specifics.rtf
deleted file mode 100644
index 01b8829..0000000
--- a/general/datasets/HSNIH_Rat_VoLo_RSeq_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Orbitofrontal Cortex
\ No newline at end of file
diff --git a/general/datasets/HSNIH_Rat_VoLo_RSeq_0818/summary.rtf b/general/datasets/HSNIH_Rat_VoLo_RSeq_0818/summary.rtf
deleted file mode 100644
index 2503d26..0000000
--- a/general/datasets/HSNIH_Rat_VoLo_RSeq_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/HSNIH_Rat_VoLo_RSeqlog2_0818/specifics.rtf b/general/datasets/HSNIH_Rat_VoLo_RSeqlog2_0818/specifics.rtf
deleted file mode 100644
index 843d470..0000000
--- a/general/datasets/HSNIH_Rat_VoLo_RSeqlog2_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Log2
\ No newline at end of file
diff --git a/general/datasets/HSNIH_Rat_VoLo_RSeqlog2_0818/summary.rtf b/general/datasets/HSNIH_Rat_VoLo_RSeqlog2_0818/summary.rtf
deleted file mode 100644
index 2503d26..0000000
--- a/general/datasets/HSNIH_Rat_VoLo_RSeqlog2_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/HZI_LTCF_0313/acknowledgment.rtf b/general/datasets/HZI_LTCF_0313/acknowledgment.rtf
deleted file mode 100644
index 5350054..0000000
--- a/general/datasets/HZI_LTCF_0313/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Primary human bronchial epithelial cells were provided by Scott H. Randell (Marsico Lung Institute, Tissue Procurement and Cell Culture Core, The University of North Carolina at Chapel Hill, USA). The cells were obtained under protocol 03-1396 approved by the University of North Carolina at Chapel Hill Biomedical Institutional Review Board. The RNA-seq was carried out by the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/HZI_LTCF_0313/cases.rtf b/general/datasets/HZI_LTCF_0313/cases.rtf
deleted file mode 100644
index 50868a3..0000000
--- a/general/datasets/HZI_LTCF_0313/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Mice We used females from 41 BXD RI strains and both parental strains—B6 and D2. Mice were between 8 and 12 weeks of age when infected. They were housed and maintained on a 12:12 light/dark cycle, with ad libitum access to food and water. Virus Original stocks of mouse-adapted A/Puerto Rico/8/34 (H1N1, PR8M) virus were obtained from Stefan Ludwig, University of Münster (28). Virus stocks were propagated in the chorioallantoic cavity of 10-day-old pathogen-free embryonated chicken eggs for 48 h at 37°C as described previously (29). Viral titer was determined using a focus-forming unit (FFU) assay as described previously (29). Infection of Mice Animals were anesthetized by intraperitoneal injection of ketamine/xylazine (10 % (v/v) of 100 mg/ml ketamine and 5 % (v/v) of 20 mg/ml xylazine in 0.9 % (w/v) NaCl with a dose adjusted to body weight (200 μl/20 g body weight). Infection was performed by intranasal application of virus solution in 20 μl sterile phosphate-buffered saline (PBS), with a PR8M dosage of 2×103 FFU. Mice were bred and infected at the animal facilities at UTHSC
diff --git a/general/datasets/HZI_LTCF_0313/notes.rtf b/general/datasets/HZI_LTCF_0313/notes.rtf
deleted file mode 100644
index e6040a2..0000000
--- a/general/datasets/HZI_LTCF_0313/notes.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2020.07314/full#supplementary-material
diff --git a/general/datasets/HZI_LTCF_0313/processing.rtf b/general/datasets/HZI_LTCF_0313/processing.rtf
deleted file mode 100644
index 5502082..0000000
--- a/general/datasets/HZI_LTCF_0313/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Read Mapping and Gene Expression Quantification RNA-seq reads were quality-trimmed using Trim Galore (31) and mapped to the mm10 reference genome or to the IAV PR8M genome using STAR (32). Counts were summarized at the gene level using the R-package Rsubread (33), normalized and log transformed using the R-package DESeq2 (34), and batchcorrected using the ComBat function of the R-package sva (35, 36). For annotations of genes, ENTREZID from Rsubread were matched to RefSeq annotations using R-package biomart (37).
diff --git a/general/datasets/HZI_LTCF_0313/summary.rtf b/general/datasets/HZI_LTCF_0313/summary.rtf
deleted file mode 100644
index 1ad3d9f..0000000
--- a/general/datasets/HZI_LTCF_0313/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Full article available at https://www.frontiersin.org/articles/10.3389/fimmu.2020.607314/full
-
-Acute lung injury (ALI) is an important cause of morbidity and mortality after viral infections, including influenza A virus H1N1, SARS-CoV,MERS-CoV, and SARS-CoV-2. The angiotensin I converting enzyme 2 (ACE2) is a key host membrane-bound protein that modulates ALI induced by viral infection, pulmonary acid aspiration, and sepsis. However, the contributions of ACE2 sequence variants to individual differences in disease risk and severity after viral infection are not understood. In this study, we quantified H1N1 influenza-infected lung transcriptomes across a family of 41 BXD recombinant inbred strains of mice and both parents—C57BL/6J and DBA/2J. In response to infection Ace2 mRNA levels decreased significantly for both parental strains and the expression levels was associated with disease severity (body weight loss) and viral load (expression levels of viral NA segment) across the BXD family members. Pulmonary RNA-seq for 43 lines was analyzed using weighted gene co-expression network analysis (WGCNA) and Bayesian network approaches. Ace2 not only participated in virusinduced ALI by interacting with TNF, MAPK, and NOTCH signaling pathways, but was also linked with high confidence to gene products that have important functions in the pulmonary epithelium, including Rnf128, Muc5b, and Tmprss2. Comparable sets of transcripts were also highlighted in parallel studies of human SARS-CoV-infected primary human airway epithelial cells. Using conventional mapping methods, we determined that weight loss at two and three days after viral infection maps to chromosome X—the location of Ace2. This finding motivated the hierarchical Bayesian network analysis, which defined molecular endophenotypes of lung infection linked to Ace2 expression and to a key disease outcome. Core members of this Bayesian network include Ace2, Atf4, Csf2, Cxcl2, Lif, Maml3, Muc5b, Reg3g, Ripk3, and Traf3. Collectively, these findings define a causally-rooted Ace2 modulatory network relevant to host response to viral infection and identify potential therapeutic targets for virus-induced respiratory diseases, including those caused by influenza and coronaviruses.
diff --git a/general/datasets/HZI_LTCF_0313/tissue.rtf b/general/datasets/HZI_LTCF_0313/tissue.rtf
deleted file mode 100644
index 2258f28..0000000
--- a/general/datasets/HZI_LTCF_0313/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-RNA Isolation and Sequencing Mice were sacrificed 3 days post-infection (dpi) and both lungs were extracted and transferred immediately to RNAlater (Qiagen), stored at 4°C for one day, and then stored at −20°C. RNA was isolated using Qiagen Midi kit (30). RNA quality was evaluated on a 2100 Bioanalyzer (Agilent). Five-hundred nanograms of total RNA was used to prepare libraries for sequencing using the Lexogen SENSE RNA-seq library kit for Ion Torrent. Libraries were amplified for 11 cycles as the final step of library preparation. Before sequencing, 1-μl aliquots were pooled and sequenced on an Ion Torrent PGM 314 chip. Barcoded data from the PGM was used to balance the final pool before sequencing. Library pools were sized to ~260 bp on a Pippin Prep instrument using 2% Pippin agarose gel. The sized libraries were evaluated on an Agilent High Sensitivity chip, quantified using real-time PCR, and used to prepare beads using a One-Touch 2 device. Beads were sequenced on an Ion Torrent Proton P1 chip. On average, 67 million reads were obtained per strain.
diff --git a/general/datasets/HZI_LungBXD_RNA_Seq_1116/acknowledgment.rtf b/general/datasets/HZI_LungBXD_RNA_Seq_1116/acknowledgment.rtf
deleted file mode 100644
index 5350054..0000000
--- a/general/datasets/HZI_LungBXD_RNA_Seq_1116/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Primary human bronchial epithelial cells were provided by Scott H. Randell (Marsico Lung Institute, Tissue Procurement and Cell Culture Core, The University of North Carolina at Chapel Hill, USA). The cells were obtained under protocol 03-1396 approved by the University of North Carolina at Chapel Hill Biomedical Institutional Review Board. The RNA-seq was carried out by the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/HZI_LungBXD_RNA_Seq_1116/cases.rtf b/general/datasets/HZI_LungBXD_RNA_Seq_1116/cases.rtf
deleted file mode 100644
index 50868a3..0000000
--- a/general/datasets/HZI_LungBXD_RNA_Seq_1116/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Mice We used females from 41 BXD RI strains and both parental strains—B6 and D2. Mice were between 8 and 12 weeks of age when infected. They were housed and maintained on a 12:12 light/dark cycle, with ad libitum access to food and water. Virus Original stocks of mouse-adapted A/Puerto Rico/8/34 (H1N1, PR8M) virus were obtained from Stefan Ludwig, University of Münster (28). Virus stocks were propagated in the chorioallantoic cavity of 10-day-old pathogen-free embryonated chicken eggs for 48 h at 37°C as described previously (29). Viral titer was determined using a focus-forming unit (FFU) assay as described previously (29). Infection of Mice Animals were anesthetized by intraperitoneal injection of ketamine/xylazine (10 % (v/v) of 100 mg/ml ketamine and 5 % (v/v) of 20 mg/ml xylazine in 0.9 % (w/v) NaCl with a dose adjusted to body weight (200 μl/20 g body weight). Infection was performed by intranasal application of virus solution in 20 μl sterile phosphate-buffered saline (PBS), with a PR8M dosage of 2×103 FFU. Mice were bred and infected at the animal facilities at UTHSC
diff --git a/general/datasets/HZI_LungBXD_RNA_Seq_1116/notes.rtf b/general/datasets/HZI_LungBXD_RNA_Seq_1116/notes.rtf
deleted file mode 100644
index e6040a2..0000000
--- a/general/datasets/HZI_LungBXD_RNA_Seq_1116/notes.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2020.07314/full#supplementary-material
diff --git a/general/datasets/HZI_LungBXD_RNA_Seq_1116/platform.rtf b/general/datasets/HZI_LungBXD_RNA_Seq_1116/platform.rtf
deleted file mode 100644
index f9bc2e3..0000000
--- a/general/datasets/HZI_LungBXD_RNA_Seq_1116/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-IonTorrent (see above)
diff --git a/general/datasets/HZI_LungBXD_RNA_Seq_1116/processing.rtf b/general/datasets/HZI_LungBXD_RNA_Seq_1116/processing.rtf
deleted file mode 100644
index 5502082..0000000
--- a/general/datasets/HZI_LungBXD_RNA_Seq_1116/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Read Mapping and Gene Expression Quantification RNA-seq reads were quality-trimmed using Trim Galore (31) and mapped to the mm10 reference genome or to the IAV PR8M genome using STAR (32). Counts were summarized at the gene level using the R-package Rsubread (33), normalized and log transformed using the R-package DESeq2 (34), and batchcorrected using the ComBat function of the R-package sva (35, 36). For annotations of genes, ENTREZID from Rsubread were matched to RefSeq annotations using R-package biomart (37).
diff --git a/general/datasets/HZI_LungBXD_RNA_Seq_1116/specifics.rtf b/general/datasets/HZI_LungBXD_RNA_Seq_1116/specifics.rtf
deleted file mode 100644
index d75a4b7..0000000
--- a/general/datasets/HZI_LungBXD_RNA_Seq_1116/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HZI Lung Flu Infected BXD (Nov16) RNA-Seq
diff --git a/general/datasets/HZI_LungBXD_RNA_Seq_1116/summary.rtf b/general/datasets/HZI_LungBXD_RNA_Seq_1116/summary.rtf
deleted file mode 100644
index 1ad3d9f..0000000
--- a/general/datasets/HZI_LungBXD_RNA_Seq_1116/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Full article available at https://www.frontiersin.org/articles/10.3389/fimmu.2020.607314/full
-
-Acute lung injury (ALI) is an important cause of morbidity and mortality after viral infections, including influenza A virus H1N1, SARS-CoV,MERS-CoV, and SARS-CoV-2. The angiotensin I converting enzyme 2 (ACE2) is a key host membrane-bound protein that modulates ALI induced by viral infection, pulmonary acid aspiration, and sepsis. However, the contributions of ACE2 sequence variants to individual differences in disease risk and severity after viral infection are not understood. In this study, we quantified H1N1 influenza-infected lung transcriptomes across a family of 41 BXD recombinant inbred strains of mice and both parents—C57BL/6J and DBA/2J. In response to infection Ace2 mRNA levels decreased significantly for both parental strains and the expression levels was associated with disease severity (body weight loss) and viral load (expression levels of viral NA segment) across the BXD family members. Pulmonary RNA-seq for 43 lines was analyzed using weighted gene co-expression network analysis (WGCNA) and Bayesian network approaches. Ace2 not only participated in virusinduced ALI by interacting with TNF, MAPK, and NOTCH signaling pathways, but was also linked with high confidence to gene products that have important functions in the pulmonary epithelium, including Rnf128, Muc5b, and Tmprss2. Comparable sets of transcripts were also highlighted in parallel studies of human SARS-CoV-infected primary human airway epithelial cells. Using conventional mapping methods, we determined that weight loss at two and three days after viral infection maps to chromosome X—the location of Ace2. This finding motivated the hierarchical Bayesian network analysis, which defined molecular endophenotypes of lung infection linked to Ace2 expression and to a key disease outcome. Core members of this Bayesian network include Ace2, Atf4, Csf2, Cxcl2, Lif, Maml3, Muc5b, Reg3g, Ripk3, and Traf3. Collectively, these findings define a causally-rooted Ace2 modulatory network relevant to host response to viral infection and identify potential therapeutic targets for virus-induced respiratory diseases, including those caused by influenza and coronaviruses.
diff --git a/general/datasets/HZI_LungBXD_RNA_Seq_1116/tissue.rtf b/general/datasets/HZI_LungBXD_RNA_Seq_1116/tissue.rtf
deleted file mode 100644
index 2258f28..0000000
--- a/general/datasets/HZI_LungBXD_RNA_Seq_1116/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-RNA Isolation and Sequencing Mice were sacrificed 3 days post-infection (dpi) and both lungs were extracted and transferred immediately to RNAlater (Qiagen), stored at 4°C for one day, and then stored at −20°C. RNA was isolated using Qiagen Midi kit (30). RNA quality was evaluated on a 2100 Bioanalyzer (Agilent). Five-hundred nanograms of total RNA was used to prepare libraries for sequencing using the Lexogen SENSE RNA-seq library kit for Ion Torrent. Libraries were amplified for 11 cycles as the final step of library preparation. Before sequencing, 1-μl aliquots were pooled and sequenced on an Ion Torrent PGM 314 chip. Barcoded data from the PGM was used to balance the final pool before sequencing. Library pools were sized to ~260 bp on a Pippin Prep instrument using 2% Pippin agarose gel. The sized libraries were evaluated on an Agilent High Sensitivity chip, quantified using real-time PCR, and used to prepare beads using a One-Touch 2 device. Beads were sequenced on an Ion Torrent Proton P1 chip. On average, 67 million reads were obtained per strain.
diff --git a/general/datasets/HZI_PR8M_F_1014/processing.rtf b/general/datasets/HZI_PR8M_F_1014/processing.rtf
deleted file mode 100644
index 3aca25d..0000000
--- a/general/datasets/HZI_PR8M_F_1014/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-For dataset HZI PR8M-Infected Lungs Females RNAseq (Oct14) RPKM Log2 we took the RPKM values, added 1 and then log2.
-
-For dataset HZI PR8M-Infected Lungs Females RNAseq (Oct14) RPKM Log2 Treatment we took the RPKM values, added 1 and then log2 and threshold values at average of less than 1 = 0
diff --git a/general/datasets/HZI_PR8M_F_1014/summary.rtf b/general/datasets/HZI_PR8M_F_1014/summary.rtf
deleted file mode 100644
index 07a4fb8..0000000
--- a/general/datasets/HZI_PR8M_F_1014/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This group of datasets is currently confidential.
diff --git a/general/datasets/HZI_PR8M_F_1113/processing.rtf b/general/datasets/HZI_PR8M_F_1113/processing.rtf
deleted file mode 100644
index 3aca25d..0000000
--- a/general/datasets/HZI_PR8M_F_1113/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-For dataset HZI PR8M-Infected Lungs Females RNAseq (Oct14) RPKM Log2 we took the RPKM values, added 1 and then log2.
-
-For dataset HZI PR8M-Infected Lungs Females RNAseq (Oct14) RPKM Log2 Treatment we took the RPKM values, added 1 and then log2 and threshold values at average of less than 1 = 0
diff --git a/general/datasets/HZI_PR8M_F_1113/summary.rtf b/general/datasets/HZI_PR8M_F_1113/summary.rtf
deleted file mode 100644
index 07a4fb8..0000000
--- a/general/datasets/HZI_PR8M_F_1113/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This group of datasets is currently confidential.
diff --git a/general/datasets/HZI_PR8M_F_freq1_1014/processing.rtf b/general/datasets/HZI_PR8M_F_freq1_1014/processing.rtf
deleted file mode 100644
index 3aca25d..0000000
--- a/general/datasets/HZI_PR8M_F_freq1_1014/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-For dataset HZI PR8M-Infected Lungs Females RNAseq (Oct14) RPKM Log2 we took the RPKM values, added 1 and then log2.
-
-For dataset HZI PR8M-Infected Lungs Females RNAseq (Oct14) RPKM Log2 Treatment we took the RPKM values, added 1 and then log2 and threshold values at average of less than 1 = 0
diff --git a/general/datasets/HZI_PR8M_F_freq1_1014/summary.rtf b/general/datasets/HZI_PR8M_F_freq1_1014/summary.rtf
deleted file mode 100644
index 07a4fb8..0000000
--- a/general/datasets/HZI_PR8M_F_freq1_1014/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This group of datasets is currently confidential.
diff --git a/general/datasets/HZI_PR8M_Q_0612/acknowledgment.rtf b/general/datasets/HZI_PR8M_Q_0612/acknowledgment.rtf
deleted file mode 100644
index 5350054..0000000
--- a/general/datasets/HZI_PR8M_Q_0612/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Primary human bronchial epithelial cells were provided by Scott H. Randell (Marsico Lung Institute, Tissue Procurement and Cell Culture Core, The University of North Carolina at Chapel Hill, USA). The cells were obtained under protocol 03-1396 approved by the University of North Carolina at Chapel Hill Biomedical Institutional Review Board. The RNA-seq was carried out by the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/HZI_PR8M_Q_0612/cases.rtf b/general/datasets/HZI_PR8M_Q_0612/cases.rtf
deleted file mode 100644
index 50868a3..0000000
--- a/general/datasets/HZI_PR8M_Q_0612/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Mice We used females from 41 BXD RI strains and both parental strains—B6 and D2. Mice were between 8 and 12 weeks of age when infected. They were housed and maintained on a 12:12 light/dark cycle, with ad libitum access to food and water. Virus Original stocks of mouse-adapted A/Puerto Rico/8/34 (H1N1, PR8M) virus were obtained from Stefan Ludwig, University of Münster (28). Virus stocks were propagated in the chorioallantoic cavity of 10-day-old pathogen-free embryonated chicken eggs for 48 h at 37°C as described previously (29). Viral titer was determined using a focus-forming unit (FFU) assay as described previously (29). Infection of Mice Animals were anesthetized by intraperitoneal injection of ketamine/xylazine (10 % (v/v) of 100 mg/ml ketamine and 5 % (v/v) of 20 mg/ml xylazine in 0.9 % (w/v) NaCl with a dose adjusted to body weight (200 μl/20 g body weight). Infection was performed by intranasal application of virus solution in 20 μl sterile phosphate-buffered saline (PBS), with a PR8M dosage of 2×103 FFU. Mice were bred and infected at the animal facilities at UTHSC
diff --git a/general/datasets/HZI_PR8M_Q_0612/notes.rtf b/general/datasets/HZI_PR8M_Q_0612/notes.rtf
deleted file mode 100644
index e6040a2..0000000
--- a/general/datasets/HZI_PR8M_Q_0612/notes.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2020.07314/full#supplementary-material
diff --git a/general/datasets/HZI_PR8M_Q_0612/processing.rtf b/general/datasets/HZI_PR8M_Q_0612/processing.rtf
deleted file mode 100644
index 5502082..0000000
--- a/general/datasets/HZI_PR8M_Q_0612/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Read Mapping and Gene Expression Quantification RNA-seq reads were quality-trimmed using Trim Galore (31) and mapped to the mm10 reference genome or to the IAV PR8M genome using STAR (32). Counts were summarized at the gene level using the R-package Rsubread (33), normalized and log transformed using the R-package DESeq2 (34), and batchcorrected using the ComBat function of the R-package sva (35, 36). For annotations of genes, ENTREZID from Rsubread were matched to RefSeq annotations using R-package biomart (37).
diff --git a/general/datasets/HZI_PR8M_Q_0612/summary.rtf b/general/datasets/HZI_PR8M_Q_0612/summary.rtf
deleted file mode 100644
index 1ad3d9f..0000000
--- a/general/datasets/HZI_PR8M_Q_0612/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Full article available at https://www.frontiersin.org/articles/10.3389/fimmu.2020.607314/full
-
-Acute lung injury (ALI) is an important cause of morbidity and mortality after viral infections, including influenza A virus H1N1, SARS-CoV,MERS-CoV, and SARS-CoV-2. The angiotensin I converting enzyme 2 (ACE2) is a key host membrane-bound protein that modulates ALI induced by viral infection, pulmonary acid aspiration, and sepsis. However, the contributions of ACE2 sequence variants to individual differences in disease risk and severity after viral infection are not understood. In this study, we quantified H1N1 influenza-infected lung transcriptomes across a family of 41 BXD recombinant inbred strains of mice and both parents—C57BL/6J and DBA/2J. In response to infection Ace2 mRNA levels decreased significantly for both parental strains and the expression levels was associated with disease severity (body weight loss) and viral load (expression levels of viral NA segment) across the BXD family members. Pulmonary RNA-seq for 43 lines was analyzed using weighted gene co-expression network analysis (WGCNA) and Bayesian network approaches. Ace2 not only participated in virusinduced ALI by interacting with TNF, MAPK, and NOTCH signaling pathways, but was also linked with high confidence to gene products that have important functions in the pulmonary epithelium, including Rnf128, Muc5b, and Tmprss2. Comparable sets of transcripts were also highlighted in parallel studies of human SARS-CoV-infected primary human airway epithelial cells. Using conventional mapping methods, we determined that weight loss at two and three days after viral infection maps to chromosome X—the location of Ace2. This finding motivated the hierarchical Bayesian network analysis, which defined molecular endophenotypes of lung infection linked to Ace2 expression and to a key disease outcome. Core members of this Bayesian network include Ace2, Atf4, Csf2, Cxcl2, Lif, Maml3, Muc5b, Reg3g, Ripk3, and Traf3. Collectively, these findings define a causally-rooted Ace2 modulatory network relevant to host response to viral infection and identify potential therapeutic targets for virus-induced respiratory diseases, including those caused by influenza and coronaviruses.
diff --git a/general/datasets/HZI_PR8M_Q_0612/tissue.rtf b/general/datasets/HZI_PR8M_Q_0612/tissue.rtf
deleted file mode 100644
index 2258f28..0000000
--- a/general/datasets/HZI_PR8M_Q_0612/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-RNA Isolation and Sequencing Mice were sacrificed 3 days post-infection (dpi) and both lungs were extracted and transferred immediately to RNAlater (Qiagen), stored at 4°C for one day, and then stored at −20°C. RNA was isolated using Qiagen Midi kit (30). RNA quality was evaluated on a 2100 Bioanalyzer (Agilent). Five-hundred nanograms of total RNA was used to prepare libraries for sequencing using the Lexogen SENSE RNA-seq library kit for Ion Torrent. Libraries were amplified for 11 cycles as the final step of library preparation. Before sequencing, 1-μl aliquots were pooled and sequenced on an Ion Torrent PGM 314 chip. Barcoded data from the PGM was used to balance the final pool before sequencing. Library pools were sized to ~260 bp on a Pippin Prep instrument using 2% Pippin agarose gel. The sized libraries were evaluated on an Agilent High Sensitivity chip, quantified using real-time PCR, and used to prepare beads using a One-Touch 2 device. Beads were sequenced on an Ion Torrent Proton P1 chip. On average, 67 million reads were obtained per strain.
diff --git a/general/datasets/Hbtrc_mlc_0611/acknowledgment.rtf b/general/datasets/Hbtrc_mlc_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/Hbtrc_mlc_0611/cases.rtf b/general/datasets/Hbtrc_mlc_0611/cases.rtf
new file mode 100644
index 0000000..e64114d
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_0611/cases.rtf
@@ -0,0 +1,4156 @@
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
+ NA |
+ 5370_PF_A_1400 |
+
+
+ | 364 |
+ HB_259_AD |
+ AD |
+ NA |
+ 5371_PF_A_2636 |
+
+
+ | 365 |
+ HB_260_AD |
+ AD |
+ NA |
+ 5375_VC_A_0188 |
+
+
+ | 366 |
+ HB_263_AD |
+ AD |
+ NA |
+ 5381_VC_A_0022 |
+
+
+ | 367 |
+ HB_265_AD |
+ AD |
+ NA |
+ 5385_VC_A_1402 |
+
+
+ | 368 |
+ HB_267_AD |
+ AD |
+ NA |
+ 5389_VC_A_0928 |
+
+
+ | 369 |
+ HB_268_AD |
+ AD |
+ NA |
+ 5390_CR_A_0151 |
+
+
+ | 370 |
+ HB_273_AD |
+ AD |
+ NA |
+ 5400_PF_A_2645 |
+
+
+ | 371 |
+ HB_274_AD |
+ AD |
+ NA |
+ 5401_VC_A_0931 |
+
+
+ | 372 |
+ HB_275_AD |
+ AD |
+ NA |
+ 5404_PF_A_2648 |
+
+
+ | 373 |
+ HB_276_AD |
+ AD |
+ NA |
+ 5406_VC_A_0933 |
+
+
+ | 374 |
+ HB_277_AD |
+ AD |
+ NA |
+ 5407_PF_A_2651 |
+
+
+ | 375 |
+ HB_280_AD |
+ AD |
+ NA |
+ 5412_VC_A_0935 |
+
+
+ | 376 |
+ HB_281_AD |
+ AD |
+ NA |
+ 5413_PF_A_2657 |
+
+
+ | 377 |
+ HB_283_AD |
+ AD |
+ NA |
+ 5419_VC_A_0937 |
+
+
+ | 378 |
+ HB_284_AD |
+ AD |
+ NA |
+ 5420_VC_A_0939 |
+
+
+ | 379 |
+ HB_285_AD |
+ AD |
+ NA |
+ 5421_CR_A_0432 |
+
+
+ | 380 |
+ HB_286_AD |
+ AD |
+ NA |
+ 5423_PF_A_2660 |
+
+
+ | 381 |
+ HB_288_AD |
+ AD |
+ NA |
+ 5425_PF_A_2666 |
+
+
+ | 382 |
+ HB_289_AD |
+ AD |
+ NA |
+ 5426_VC_A_1405 |
+
+
+ | 383 |
+ HB_290_AD |
+ AD |
+ NA |
+ 5433_VC_A_0434 |
+
+
+ | 384 |
+ HB_296_AD |
+ AD |
+ NA |
+ 5456_PF_A_2675 |
+
+
+ | 385 |
+ HB_299_AD |
+ AD |
+ NA |
+ 5461_VC_A_0192 |
+
+
+ | 386 |
+ HB_302_AD |
+ AD |
+ NA |
+ 5465_PF_A_2678 |
+
+
+ | 387 |
+ HB_303_AD |
+ AD |
+ NA |
+ 5469_VC_A_1417 |
+
+
+ | 388 |
+ HB_305_AD |
+ AD |
+ NA |
+ 5479_PF_A_1421 |
+
+
+ | 389 |
+ HB_306_AD |
+ AD |
+ NA |
+ 5480_VC_A_0437 |
+
+
+ | 390 |
+ HB_307_AD |
+ AD |
+ NA |
+ 5482_VC_A_0028 |
+
+
+ | 391 |
+ HB_308_AD |
+ AD |
+ NA |
+ 5483_VC_A_0941 |
+
+
+ | 392 |
+ HB_309_AD |
+ AD |
+ NA |
+ 5487_CR_A_0441 |
+
+
+ | 393 |
+ HB_310_AD |
+ AD |
+ NA |
+ 5488_CR_A_0194 |
+
+
+ | 394 |
+ HB_312_AD |
+ AD |
+ NA |
+ 5500_VC_A_0198 |
+
+
+ | 395 |
+ HB_313_AD |
+ AD |
+ NA |
+ 5502_PF_A_2684 |
+
+
+ | 396 |
+ HB_315_AD |
+ AD |
+ NA |
+ 5513_PF_A_2687 |
+
+
+ | 397 |
+ HB_316_AD |
+ AD |
+ NA |
+ 5516_PF_A_2690 |
+
+
+ | 398 |
+ HB_317_AD |
+ AD |
+ NA |
+ 5517_PF_A_2693 |
+
+
+ | 399 |
+ HB_318_AD |
+ AD |
+ NA |
+ 5518_CR_A_0030 |
+
+
+ | 400 |
+ HB_319_AD |
+ AD |
+ NA |
+ 5519_CR_A_2695 |
+
+
+ | 401 |
+ HB_320_AD |
+ AD |
+ NA |
+ 5520_PF_A_2699 |
+
+
+ | 402 |
+ HB_322_AD |
+ AD |
+ NA |
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+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hbtrc_mlc_0611/experiment-design.rtf b/general/datasets/Hbtrc_mlc_0611/experiment-design.rtf
new file mode 100644
index 0000000..3b0c224
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_0611/experiment-design.rtf
@@ -0,0 +1 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
diff --git a/general/datasets/Hbtrc_mlc_0611/notes.rtf b/general/datasets/Hbtrc_mlc_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/Hbtrc_mlc_0611/summary.rtf b/general/datasets/Hbtrc_mlc_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/Hbtrc_mlc_ad_0611/acknowledgment.rtf b/general/datasets/Hbtrc_mlc_ad_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_ad_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/Hbtrc_mlc_ad_0611/cases.rtf b/general/datasets/Hbtrc_mlc_ad_0611/cases.rtf
new file mode 100644
index 0000000..e64114d
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_ad_0611/cases.rtf
@@ -0,0 +1,4156 @@
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
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+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hbtrc_mlc_ad_0611/experiment-design.rtf b/general/datasets/Hbtrc_mlc_ad_0611/experiment-design.rtf
new file mode 100644
index 0000000..3b0c224
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_ad_0611/experiment-design.rtf
@@ -0,0 +1 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
diff --git a/general/datasets/Hbtrc_mlc_ad_0611/notes.rtf b/general/datasets/Hbtrc_mlc_ad_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_ad_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/Hbtrc_mlc_ad_0611/summary.rtf b/general/datasets/Hbtrc_mlc_ad_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_ad_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/Hbtrc_mlc_hd_0611/acknowledgment.rtf b/general/datasets/Hbtrc_mlc_hd_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_hd_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/Hbtrc_mlc_hd_0611/cases.rtf b/general/datasets/Hbtrc_mlc_hd_0611/cases.rtf
new file mode 100644
index 0000000..e64114d
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_hd_0611/cases.rtf
@@ -0,0 +1,4156 @@
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
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+ HD |
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+
+
+ | 283 |
+ HB_800_HD |
+ HD |
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+
+
+ | 284 |
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+ HD |
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+
+
+ | 285 |
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+ AD |
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+
+
+ | 286 |
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+
+
+ | 287 |
+ HB_053_AD |
+ AD |
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+
+
+ | 288 |
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+ AD |
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+
+
+ | 289 |
+ HB_068_AD |
+ AD |
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+
+
+ | 290 |
+ HB_082_AD |
+ AD |
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+
+
+ | 291 |
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+ AD |
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+
+
+ | 292 |
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+ AD |
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+
+
+ | 293 |
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+ AD |
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+
+
+ | 294 |
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+ AD |
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+
+
+ | 295 |
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+ AD |
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+
+
+ | 296 |
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+ AD |
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+
+
+ | 297 |
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+ AD |
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+
+
+ | 298 |
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+
+
+ | 299 |
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+
+
+ | 300 |
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+ AD |
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+
+
+ | 301 |
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+ AD |
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+
+
+ | 302 |
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+
+
+ | 303 |
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+ AD |
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+
+
+ | 304 |
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+
+
+ | 305 |
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+
+
+ | 306 |
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+
+
+ | 307 |
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+
+
+ | 308 |
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+
+
+ | 309 |
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+
+
+ | 310 |
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+ AD |
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+
+
+ | 311 |
+ HB_130_AD |
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+
+
+ | 312 |
+ HB_131_AD |
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+
+
+ | 313 |
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+
+
+ | 314 |
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+
+
+ | 315 |
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+
+
+ | 316 |
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+
+
+ | 317 |
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+
+
+ | 318 |
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+
+
+ | 319 |
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+
+
+ | 320 |
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+
+
+ | 321 |
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+
+
+ | 322 |
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+
+
+ | 323 |
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+
+
+ | 324 |
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+
+
+ | 325 |
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+
+
+ | 326 |
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+
+
+ | 327 |
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+
+
+ | 328 |
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+
+
+ | 329 |
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+
+
+ | 330 |
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+
+
+ | 331 |
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+
+
+ | 332 |
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+
+
+ | 333 |
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+
+
+ | 334 |
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+
+
+ | 335 |
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+
+
+ | 336 |
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+
+
+ | 337 |
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+
+
+ | 338 |
+ HB_197_AD |
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+
+
+ | 339 |
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+
+
+ | 340 |
+ HB_200_AD |
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+
+
+ | 341 |
+ HB_205_AD |
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+
+
+ | 342 |
+ HB_208_AD |
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+
+
+ | 343 |
+ HB_209_AD |
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+
+
+ | 344 |
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+
+
+ | 345 |
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+
+
+ | 346 |
+ HB_219_AD |
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+
+
+ | 347 |
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+
+
+ | 348 |
+ HB_222_AD |
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+
+
+ | 349 |
+ HB_224_AD |
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+
+
+ | 350 |
+ HB_230_AD |
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+
+
+ | 351 |
+ HB_231_AD |
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+
+
+ | 352 |
+ HB_232_AD |
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+
+
+ | 353 |
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+
+
+ | 354 |
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+
+
+ | 355 |
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+
+
+ | 356 |
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+
+
+ | 357 |
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+
+
+ | 358 |
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+
+
+ | 359 |
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+
+
+ | 360 |
+ HB_251_AD |
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+
+
+ | 361 |
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+
+
+ | 362 |
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+
+
+ | 363 |
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+
+
+ | 364 |
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+
+
+ | 365 |
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+
+
+ | 366 |
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+
+
+ | 367 |
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+
+
+ | 368 |
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+
+
+ | 369 |
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+
+
+ | 370 |
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+
+
+ | 371 |
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+
+
+ | 372 |
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+
+
+ | 373 |
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+
+
+ | 374 |
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+
+
+ | 375 |
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+
+
+ | 376 |
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+
+
+ | 377 |
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+
+
+ | 378 |
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+
+
+ | 379 |
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+
+
+ | 380 |
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+
+
+ | 381 |
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+
+
+ | 382 |
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+
+
+ | 383 |
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+
+
+ | 384 |
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+
+
+ | 385 |
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+
+
+ | 386 |
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+
+
+ | 387 |
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+
+
+ | 388 |
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+
+
+ | 389 |
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+
+
+ | 390 |
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+
+
+ | 391 |
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+
+
+ | 392 |
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+
+
+ | 393 |
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+
+
+ | 394 |
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+
+
+ | 395 |
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+
+
+ | 396 |
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+
+
+ | 397 |
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+
+
+ | 398 |
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+
+
+ | 399 |
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+
+
+ | 400 |
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+
+
+ | 401 |
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+
+
+ | 402 |
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+
+
+ | 403 |
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+
+
+ | 404 |
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+
+
+ | 405 |
+ HB_330_AD |
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+
+
+ | 406 |
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+
+
+ | 407 |
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+
+
+ | 408 |
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+
+
+ | 409 |
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+
+
+ | 410 |
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+
+
+ | 411 |
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+
+
+ | 412 |
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+
+
+ | 413 |
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+
+
+ | 414 |
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+
+
+ | 415 |
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+
+
+ | 416 |
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+
+
+ | 417 |
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+
+
+ | 418 |
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+
+
+ | 419 |
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+
+
+ | 420 |
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+
+
+ | 421 |
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+
+
+ | 422 |
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+
+
+ | 423 |
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+
+
+ | 424 |
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+
+
+ | 425 |
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+
+
+ | 426 |
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+
+
+ | 427 |
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+
+
+ | 428 |
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+
+
+ | 429 |
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+
+
+ | 430 |
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+
+
+ | 431 |
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+
+
+ | 432 |
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+
+
+ | 433 |
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+
+
+ | 434 |
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+
+
+ | 435 |
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+
+
+ | 436 |
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+
+
+ | 437 |
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+
+
+ | 438 |
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+
+
+ | 439 |
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+
+
+ | 440 |
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+
+
+ | 441 |
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+
+
+ | 442 |
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+
+
+ | 443 |
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+
+
+ | 444 |
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+
+
+ | 445 |
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+
+
+ | 446 |
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+
+
+ | 447 |
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+
+
+ | 448 |
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+
+
+ | 449 |
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+
+
+ | 450 |
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+
+
+ | 451 |
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+
+
+ | 452 |
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+
+
+ | 453 |
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+
+
+ | 454 |
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+
+
+ | 455 |
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+
+
+ | 456 |
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+
+
+ | 457 |
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+
+
+ | 458 |
+ HB_459_AD |
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+
+
+ | 459 |
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+
+
+ | 460 |
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+
+
+ | 461 |
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+
+
+ | 462 |
+ HB_471_AD |
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+
+
+ | 463 |
+ HB_473_AD |
+ AD |
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+
+
+ | 464 |
+ HB_474_AD |
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+ NA |
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+
+
+ | 465 |
+ HB_477_AD |
+ AD |
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+
+
+ | 466 |
+ HB_479_AD |
+ AD |
+ NA |
+ 5945_VC_A_0983 |
+
+
+ | 467 |
+ HB_484_AD |
+ AD |
+ NA |
+ 5956_CR_A_0123 |
+
+
+ | 468 |
+ HB_489_AD |
+ AD |
+ NA |
+ 5968_VC_A_1075 |
+
+
+ | 469 |
+ HB_491_AD |
+ AD |
+ NA |
+ 5971_CR_A_0119 |
+
+
+ | 470 |
+ HB_492_AD |
+ AD |
+ NA |
+ 5972_VC_A_0251 |
+
+
+ | 471 |
+ HB_494_AD |
+ AD |
+ NA |
+ 5979_CR_A_0115 |
+
+
+ | 472 |
+ HB_498_AD |
+ AD |
+ NA |
+ 5988_VC_A_0503 |
+
+
+ | 473 |
+ HB_502_AD |
+ AD |
+ NA |
+ 5994_PF_A_1605 |
+
+
+ | 474 |
+ HB_503_AD |
+ AD |
+ NA |
+ 5995_CR_A_2563 |
+
+
+ | 475 |
+ HB_510_AD |
+ AD |
+ NA |
+ 6017_CR_A_0048 |
+
+
+ | 476 |
+ HB_514_AD |
+ AD |
+ NA |
+ 6025_VC_A_0506 |
+
+
+ | 477 |
+ HB_517_AD |
+ AD |
+ NA |
+ 6031_VC_A_0258 |
+
+
+ | 478 |
+ HB_520_AD |
+ AD |
+ NA |
+ 6035_VC_A_1621 |
+
+
+ | 479 |
+ HB_523_AD |
+ AD |
+ NA |
+ 6038_VC_A_0261 |
+
+
+ | 480 |
+ HB_524_AD |
+ AD |
+ NA |
+ 6042_VC_A_1156 |
+
+
+ | 481 |
+ HB_525_AD |
+ AD |
+ NA |
+ 6044_VC_A_0264 |
+
+
+ | 482 |
+ HB_531_AD |
+ AD |
+ NA |
+ 6056_CR_A_0999 |
+
+
+ | 483 |
+ HB_533_AD |
+ AD |
+ NA |
+ 6061_PF_A_1650 |
+
+
+ | 484 |
+ HB_534_AD |
+ AD |
+ NA |
+ 6066_VC_A_0270 |
+
+
+ | 485 |
+ HB_535_AD |
+ AD |
+ NA |
+ 6067_PF_A_1452 |
+
+
+ | 486 |
+ HB_536_AD |
+ AD |
+ NA |
+ 6068_VC_A_0273 |
+
+
+ | 487 |
+ HB_545_AD |
+ AD |
+ NA |
+ 6102_CR_A_1661 |
+
+
+ | 488 |
+ HB_546_AD |
+ AD |
+ NA |
+ 6107_CR_A_0055 |
+
+
+ | 489 |
+ HB_550_AD |
+ AD |
+ NA |
+ 6120_VC_A_0058 |
+
+
+ | 490 |
+ HB_552_AD |
+ AD |
+ NA |
+ 6126_VC_A_1675 |
+
+
+ | 491 |
+ HB_553_AD |
+ AD |
+ NA |
+ 6129_PF_A_0274 |
+
+
+ | 492 |
+ HB_554_AD |
+ AD |
+ NA |
+ 6130_VC_A_1678 |
+
+
+ | 493 |
+ HB_555_AD |
+ AD |
+ NA |
+ 6131_CR_A_0510 |
+
+
+ | 494 |
+ HB_556_AD |
+ AD |
+ NA |
+ 6132_CR_A_0513 |
+
+
+ | 495 |
+ HB_558_AD |
+ AD |
+ NA |
+ 6137_VC_A_1681 |
+
+
+ | 496 |
+ HB_564_AD |
+ AD |
+ NA |
+ 6153_VC_A_1465 |
+
+
+ | 497 |
+ HB_565_AD |
+ AD |
+ NA |
+ 6154_VC_A_1468 |
+
+
+ | 498 |
+ HB_566_AD |
+ AD |
+ NA |
+ 6157_VC_A_0062 |
+
+
+ | 499 |
+ HB_568_AD |
+ AD |
+ NA |
+ 6164_CR_A_1005 |
+
+
+ | 500 |
+ HB_571_AD |
+ AD |
+ NA |
+ 6171_CR_A_0065 |
+
+
+ | 501 |
+ HB_573_AD |
+ AD |
+ NA |
+ 6174_VC_A_0068 |
+
+
+ | 502 |
+ HB_576_AD |
+ AD |
+ NA |
+ 6180_CR_A_0281 |
+
+
+ | 503 |
+ HB_583_AD |
+ AD |
+ NA |
+ 6194_VC_A_0071 |
+
+
+ | 504 |
+ HB_585_AD |
+ AD |
+ NA |
+ 6198_VC_A_0073 |
+
+
+ | 505 |
+ HB_590_AD |
+ AD |
+ NA |
+ 6215_VC_A_0518 |
+
+
+ | 506 |
+ HB_591_AD |
+ AD |
+ NA |
+ 6216_VC_A_1476 |
+
+
+ | 507 |
+ HB_592_AD |
+ AD |
+ NA |
+ 6218_CR_A_0522 |
+
+
+ | 508 |
+ HB_594_AD |
+ AD |
+ NA |
+ 6223_VC_A_0288 |
+
+
+ | 509 |
+ HB_596_AD |
+ AD |
+ NA |
+ 6226_CR_A_0076 |
+
+
+ | 510 |
+ HB_597_AD |
+ AD |
+ NA |
+ 6227_VC_A_0080 |
+
+
+ | 511 |
+ HB_598_AD |
+ AD |
+ NA |
+ 6231_VC_A_1479 |
+
+
+ | 512 |
+ HB_605_AD |
+ AD |
+ NA |
+ 6261_VC_A_0084 |
+
+
+ | 513 |
+ HB_608_AD |
+ AD |
+ NA |
+ 6268_CR_A_0525 |
+
+
+ | 514 |
+ HB_611_AD |
+ AD |
+ NA |
+ 6279_VC_A_0089 |
+
+
+ | 515 |
+ HB_612_AD |
+ AD |
+ NA |
+ 6280_VC_A_0091 |
+
+
+ | 516 |
+ HB_613_AD |
+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hbtrc_mlc_hd_0611/experiment-design.rtf b/general/datasets/Hbtrc_mlc_hd_0611/experiment-design.rtf
new file mode 100644
index 0000000..3b0c224
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_hd_0611/experiment-design.rtf
@@ -0,0 +1 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
diff --git a/general/datasets/Hbtrc_mlc_hd_0611/notes.rtf b/general/datasets/Hbtrc_mlc_hd_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_hd_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/Hbtrc_mlc_hd_0611/summary.rtf b/general/datasets/Hbtrc_mlc_hd_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_hd_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/Hbtrc_mlc_n_0611/acknowledgment.rtf b/general/datasets/Hbtrc_mlc_n_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_n_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/Hbtrc_mlc_n_0611/cases.rtf b/general/datasets/Hbtrc_mlc_n_0611/cases.rtf
new file mode 100644
index 0000000..e64114d
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_n_0611/cases.rtf
@@ -0,0 +1,4156 @@
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
+ NA |
+ 5370_PF_A_1400 |
+
+
+ | 364 |
+ HB_259_AD |
+ AD |
+ NA |
+ 5371_PF_A_2636 |
+
+
+ | 365 |
+ HB_260_AD |
+ AD |
+ NA |
+ 5375_VC_A_0188 |
+
+
+ | 366 |
+ HB_263_AD |
+ AD |
+ NA |
+ 5381_VC_A_0022 |
+
+
+ | 367 |
+ HB_265_AD |
+ AD |
+ NA |
+ 5385_VC_A_1402 |
+
+
+ | 368 |
+ HB_267_AD |
+ AD |
+ NA |
+ 5389_VC_A_0928 |
+
+
+ | 369 |
+ HB_268_AD |
+ AD |
+ NA |
+ 5390_CR_A_0151 |
+
+
+ | 370 |
+ HB_273_AD |
+ AD |
+ NA |
+ 5400_PF_A_2645 |
+
+
+ | 371 |
+ HB_274_AD |
+ AD |
+ NA |
+ 5401_VC_A_0931 |
+
+
+ | 372 |
+ HB_275_AD |
+ AD |
+ NA |
+ 5404_PF_A_2648 |
+
+
+ | 373 |
+ HB_276_AD |
+ AD |
+ NA |
+ 5406_VC_A_0933 |
+
+
+ | 374 |
+ HB_277_AD |
+ AD |
+ NA |
+ 5407_PF_A_2651 |
+
+
+ | 375 |
+ HB_280_AD |
+ AD |
+ NA |
+ 5412_VC_A_0935 |
+
+
+ | 376 |
+ HB_281_AD |
+ AD |
+ NA |
+ 5413_PF_A_2657 |
+
+
+ | 377 |
+ HB_283_AD |
+ AD |
+ NA |
+ 5419_VC_A_0937 |
+
+
+ | 378 |
+ HB_284_AD |
+ AD |
+ NA |
+ 5420_VC_A_0939 |
+
+
+ | 379 |
+ HB_285_AD |
+ AD |
+ NA |
+ 5421_CR_A_0432 |
+
+
+ | 380 |
+ HB_286_AD |
+ AD |
+ NA |
+ 5423_PF_A_2660 |
+
+
+ | 381 |
+ HB_288_AD |
+ AD |
+ NA |
+ 5425_PF_A_2666 |
+
+
+ | 382 |
+ HB_289_AD |
+ AD |
+ NA |
+ 5426_VC_A_1405 |
+
+
+ | 383 |
+ HB_290_AD |
+ AD |
+ NA |
+ 5433_VC_A_0434 |
+
+
+ | 384 |
+ HB_296_AD |
+ AD |
+ NA |
+ 5456_PF_A_2675 |
+
+
+ | 385 |
+ HB_299_AD |
+ AD |
+ NA |
+ 5461_VC_A_0192 |
+
+
+ | 386 |
+ HB_302_AD |
+ AD |
+ NA |
+ 5465_PF_A_2678 |
+
+
+ | 387 |
+ HB_303_AD |
+ AD |
+ NA |
+ 5469_VC_A_1417 |
+
+
+ | 388 |
+ HB_305_AD |
+ AD |
+ NA |
+ 5479_PF_A_1421 |
+
+
+ | 389 |
+ HB_306_AD |
+ AD |
+ NA |
+ 5480_VC_A_0437 |
+
+
+ | 390 |
+ HB_307_AD |
+ AD |
+ NA |
+ 5482_VC_A_0028 |
+
+
+ | 391 |
+ HB_308_AD |
+ AD |
+ NA |
+ 5483_VC_A_0941 |
+
+
+ | 392 |
+ HB_309_AD |
+ AD |
+ NA |
+ 5487_CR_A_0441 |
+
+
+ | 393 |
+ HB_310_AD |
+ AD |
+ NA |
+ 5488_CR_A_0194 |
+
+
+ | 394 |
+ HB_312_AD |
+ AD |
+ NA |
+ 5500_VC_A_0198 |
+
+
+ | 395 |
+ HB_313_AD |
+ AD |
+ NA |
+ 5502_PF_A_2684 |
+
+
+ | 396 |
+ HB_315_AD |
+ AD |
+ NA |
+ 5513_PF_A_2687 |
+
+
+ | 397 |
+ HB_316_AD |
+ AD |
+ NA |
+ 5516_PF_A_2690 |
+
+
+ | 398 |
+ HB_317_AD |
+ AD |
+ NA |
+ 5517_PF_A_2693 |
+
+
+ | 399 |
+ HB_318_AD |
+ AD |
+ NA |
+ 5518_CR_A_0030 |
+
+
+ | 400 |
+ HB_319_AD |
+ AD |
+ NA |
+ 5519_CR_A_2695 |
+
+
+ | 401 |
+ HB_320_AD |
+ AD |
+ NA |
+ 5520_PF_A_2699 |
+
+
+ | 402 |
+ HB_322_AD |
+ AD |
+ NA |
+ 5527_VC_A_0945 |
+
+
+ | 403 |
+ HB_325_AD |
+ AD |
+ NA |
+ 5532_PF_A_2702 |
+
+
+ | 404 |
+ HB_328_AD |
+ AD |
+ NA |
+ 5541_PF_A_2705 |
+
+
+ | 405 |
+ HB_330_AD |
+ AD |
+ NA |
+ 5544_VC_A_0201 |
+
+
+ | 406 |
+ HB_334_AD |
+ AD |
+ NA |
+ 5554_VC_A_0452 |
+
+
+ | 407 |
+ HB_335_AD |
+ AD |
+ NA |
+ 5557_VC_A_0950 |
+
+
+ | 408 |
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+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hbtrc_mlc_n_0611/experiment-design.rtf b/general/datasets/Hbtrc_mlc_n_0611/experiment-design.rtf
new file mode 100644
index 0000000..3b0c224
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_n_0611/experiment-design.rtf
@@ -0,0 +1 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
diff --git a/general/datasets/Hbtrc_mlc_n_0611/notes.rtf b/general/datasets/Hbtrc_mlc_n_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_n_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/Hbtrc_mlc_n_0611/summary.rtf b/general/datasets/Hbtrc_mlc_n_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/Hbtrc_mlc_n_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/Hbtrc_mlpfc_0611/acknowledgment.rtf b/general/datasets/Hbtrc_mlpfc_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/Hbtrc_mlpfc_0611/cases.rtf b/general/datasets/Hbtrc_mlpfc_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
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+ | 528 |
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+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hbtrc_mlpfc_0611/citation.rtf b/general/datasets/Hbtrc_mlpfc_0611/citation.rtf
new file mode 100644
index 0000000..fa9245d
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_0611/citation.rtf
@@ -0,0 +1,7 @@
+Narayanan M, Huynh JL, Wang K, Yang X, Yoo S, McElwee J, Zhang B, Zhang C, Lamb JR, Xie T, Suver C, Molony C, Melquist S, Johnson AD, Fan G, Stone DJ, Schadt EE, Casaccia P, Emilsson V, Zhu J
+
+Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases.
+
+Mol Syst Biol. 2014 Jul 30;10:743. doi: 10.15252/msb.20145304.
+
+PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_0611/contributors.rtf b/general/datasets/Hbtrc_mlpfc_0611/contributors.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_0611/contributors.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_0611/experiment-design.rtf b/general/datasets/Hbtrc_mlpfc_0611/experiment-design.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_0611/experiment-design.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_0611/notes.rtf b/general/datasets/Hbtrc_mlpfc_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/Hbtrc_mlpfc_0611/platform.rtf b/general/datasets/Hbtrc_mlpfc_0611/platform.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_0611/platform.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_0611/processing.rtf b/general/datasets/Hbtrc_mlpfc_0611/processing.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_0611/processing.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_0611/summary.rtf b/general/datasets/Hbtrc_mlpfc_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/Hbtrc_mlpfc_0611/tissue.rtf b/general/datasets/Hbtrc_mlpfc_0611/tissue.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_0611/tissue.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_ad_0611/acknowledgment.rtf b/general/datasets/Hbtrc_mlpfc_ad_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_ad_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/Hbtrc_mlpfc_ad_0611/cases.rtf b/general/datasets/Hbtrc_mlpfc_ad_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_ad_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
+ NA |
+ 5370_PF_A_1400 |
+
+
+ | 364 |
+ HB_259_AD |
+ AD |
+ NA |
+ 5371_PF_A_2636 |
+
+
+ | 365 |
+ HB_260_AD |
+ AD |
+ NA |
+ 5375_VC_A_0188 |
+
+
+ | 366 |
+ HB_263_AD |
+ AD |
+ NA |
+ 5381_VC_A_0022 |
+
+
+ | 367 |
+ HB_265_AD |
+ AD |
+ NA |
+ 5385_VC_A_1402 |
+
+
+ | 368 |
+ HB_267_AD |
+ AD |
+ NA |
+ 5389_VC_A_0928 |
+
+
+ | 369 |
+ HB_268_AD |
+ AD |
+ NA |
+ 5390_CR_A_0151 |
+
+
+ | 370 |
+ HB_273_AD |
+ AD |
+ NA |
+ 5400_PF_A_2645 |
+
+
+ | 371 |
+ HB_274_AD |
+ AD |
+ NA |
+ 5401_VC_A_0931 |
+
+
+ | 372 |
+ HB_275_AD |
+ AD |
+ NA |
+ 5404_PF_A_2648 |
+
+
+ | 373 |
+ HB_276_AD |
+ AD |
+ NA |
+ 5406_VC_A_0933 |
+
+
+ | 374 |
+ HB_277_AD |
+ AD |
+ NA |
+ 5407_PF_A_2651 |
+
+
+ | 375 |
+ HB_280_AD |
+ AD |
+ NA |
+ 5412_VC_A_0935 |
+
+
+ | 376 |
+ HB_281_AD |
+ AD |
+ NA |
+ 5413_PF_A_2657 |
+
+
+ | 377 |
+ HB_283_AD |
+ AD |
+ NA |
+ 5419_VC_A_0937 |
+
+
+ | 378 |
+ HB_284_AD |
+ AD |
+ NA |
+ 5420_VC_A_0939 |
+
+
+ | 379 |
+ HB_285_AD |
+ AD |
+ NA |
+ 5421_CR_A_0432 |
+
+
+ | 380 |
+ HB_286_AD |
+ AD |
+ NA |
+ 5423_PF_A_2660 |
+
+
+ | 381 |
+ HB_288_AD |
+ AD |
+ NA |
+ 5425_PF_A_2666 |
+
+
+ | 382 |
+ HB_289_AD |
+ AD |
+ NA |
+ 5426_VC_A_1405 |
+
+
+ | 383 |
+ HB_290_AD |
+ AD |
+ NA |
+ 5433_VC_A_0434 |
+
+
+ | 384 |
+ HB_296_AD |
+ AD |
+ NA |
+ 5456_PF_A_2675 |
+
+
+ | 385 |
+ HB_299_AD |
+ AD |
+ NA |
+ 5461_VC_A_0192 |
+
+
+ | 386 |
+ HB_302_AD |
+ AD |
+ NA |
+ 5465_PF_A_2678 |
+
+
+ | 387 |
+ HB_303_AD |
+ AD |
+ NA |
+ 5469_VC_A_1417 |
+
+
+ | 388 |
+ HB_305_AD |
+ AD |
+ NA |
+ 5479_PF_A_1421 |
+
+
+ | 389 |
+ HB_306_AD |
+ AD |
+ NA |
+ 5480_VC_A_0437 |
+
+
+ | 390 |
+ HB_307_AD |
+ AD |
+ NA |
+ 5482_VC_A_0028 |
+
+
+ | 391 |
+ HB_308_AD |
+ AD |
+ NA |
+ 5483_VC_A_0941 |
+
+
+ | 392 |
+ HB_309_AD |
+ AD |
+ NA |
+ 5487_CR_A_0441 |
+
+
+ | 393 |
+ HB_310_AD |
+ AD |
+ NA |
+ 5488_CR_A_0194 |
+
+
+ | 394 |
+ HB_312_AD |
+ AD |
+ NA |
+ 5500_VC_A_0198 |
+
+
+ | 395 |
+ HB_313_AD |
+ AD |
+ NA |
+ 5502_PF_A_2684 |
+
+
+ | 396 |
+ HB_315_AD |
+ AD |
+ NA |
+ 5513_PF_A_2687 |
+
+
+ | 397 |
+ HB_316_AD |
+ AD |
+ NA |
+ 5516_PF_A_2690 |
+
+
+ | 398 |
+ HB_317_AD |
+ AD |
+ NA |
+ 5517_PF_A_2693 |
+
+
+ | 399 |
+ HB_318_AD |
+ AD |
+ NA |
+ 5518_CR_A_0030 |
+
+
+ | 400 |
+ HB_319_AD |
+ AD |
+ NA |
+ 5519_CR_A_2695 |
+
+
+ | 401 |
+ HB_320_AD |
+ AD |
+ NA |
+ 5520_PF_A_2699 |
+
+
+ | 402 |
+ HB_322_AD |
+ AD |
+ NA |
+ 5527_VC_A_0945 |
+
+
+ | 403 |
+ HB_325_AD |
+ AD |
+ NA |
+ 5532_PF_A_2702 |
+
+
+ | 404 |
+ HB_328_AD |
+ AD |
+ NA |
+ 5541_PF_A_2705 |
+
+
+ | 405 |
+ HB_330_AD |
+ AD |
+ NA |
+ 5544_VC_A_0201 |
+
+
+ | 406 |
+ HB_334_AD |
+ AD |
+ NA |
+ 5554_VC_A_0452 |
+
+
+ | 407 |
+ HB_335_AD |
+ AD |
+ NA |
+ 5557_VC_A_0950 |
+
+
+ | 408 |
+ HB_337_AD |
+ AD |
+ NA |
+ 5560_VC_A_0204 |
+
+
+ | 409 |
+ HB_342_AD |
+ AD |
+ NA |
+ 5571_PF_A_1430 |
+
+
+ | 410 |
+ HB_345_AD |
+ AD |
+ NA |
+ 5583_PF_A_2708 |
+
+
+ | 411 |
+ HB_347_AD |
+ AD |
+ NA |
+ 5589_PF_A_2714 |
+
+
+ | 412 |
+ HB_349_AD |
+ AD |
+ NA |
+ 5592_PF_A_2717 |
+
+
+ | 413 |
+ HB_352_AD |
+ AD |
+ NA |
+ 5604_VC_A_0037 |
+
+
+ | 414 |
+ HB_353_AD |
+ AD |
+ NA |
+ 5607_PF_A_2723 |
+
+
+ | 415 |
+ HB_356_AD |
+ AD |
+ NA |
+ 5615_VC_A_0041 |
+
+
+ | 416 |
+ HB_357_AD |
+ AD |
+ NA |
+ 5616_CR_A_0127 |
+
+
+ | 417 |
+ HB_358_AD |
+ AD |
+ NA |
+ 5617_CR_A_0456 |
+
+
+ | 418 |
+ HB_359_AD |
+ AD |
+ NA |
+ 5618_CR_A_0044 |
+
+
+ | 419 |
+ HB_362_AD |
+ AD |
+ NA |
+ 5625_CR_A_2495 |
+
+
+ | 420 |
+ HB_363_AD |
+ AD |
+ NA |
+ 5626_CR_A_2498 |
+
+
+ | 421 |
+ HB_364_AD |
+ AD |
+ NA |
+ 5629_CR_A_0390 |
+
+
+ | 422 |
+ HB_369_AD |
+ AD |
+ NA |
+ 5643_VC_A_1143 |
+
+
+ | 423 |
+ HB_373_AD |
+ AD |
+ NA |
+ 5654_VC_A_0047 |
+
+
+ | 424 |
+ HB_375_AD |
+ AD |
+ NA |
+ 5660_CR_A_0462 |
+
+
+ | 425 |
+ HB_376_AD |
+ AD |
+ NA |
+ 5661_VC_A_0464 |
+
+
+ | 426 |
+ HB_377_AD |
+ AD |
+ NA |
+ 5667_VC_A_2509 |
+
+
+ | 427 |
+ HB_378_AD |
+ AD |
+ NA |
+ 5668_VC_A_1438 |
+
+
+ | 428 |
+ HB_383_AD |
+ AD |
+ NA |
+ 5686_CR_A_2728 |
+
+
+ | 429 |
+ HB_386_AD |
+ AD |
+ NA |
+ 5695_VC_A_0953 |
+
+
+ | 430 |
+ HB_389_AD |
+ AD |
+ NA |
+ 5700_VC_A_2514 |
+
+
+ | 431 |
+ HB_391_AD |
+ AD |
+ NA |
+ 5705_CR_A_0474 |
+
+
+ | 432 |
+ HB_392_AD |
+ AD |
+ NA |
+ 5706_VC_A_0476 |
+
+
+ | 433 |
+ HB_394_AD |
+ AD |
+ NA |
+ 5713_VC_A_0479 |
+
+
+ | 434 |
+ HB_397_AD |
+ AD |
+ NA |
+ 5721_CR_A_0210 |
+
+
+ | 435 |
+ HB_404_AD |
+ AD |
+ NA |
+ 5735_CR_A_0489 |
+
+
+ | 436 |
+ HB_406_AD |
+ AD |
+ NA |
+ 5744_CR_A_0960 |
+
+
+ | 437 |
+ HB_409_AD |
+ AD |
+ NA |
+ 5749_CR_A_0159 |
+
+
+ | 438 |
+ HB_410_AD |
+ AD |
+ NA |
+ 5751_CR_A_2518 |
+
+
+ | 439 |
+ HB_411_AD |
+ AD |
+ NA |
+ 5755_CR_A_2731 |
+
+
+ | 440 |
+ HB_413_AD |
+ AD |
+ NA |
+ 5766_VC_A_0214 |
+
+
+ | 441 |
+ HB_419_AD |
+ AD |
+ NA |
+ 5790_VC_A_0217 |
+
+
+ | 442 |
+ HB_420_AD |
+ AD |
+ NA |
+ 5796_CR_A_0964 |
+
+
+ | 443 |
+ HB_428_AD |
+ AD |
+ NA |
+ 5811_CR_A_2524 |
+
+
+ | 444 |
+ HB_429_AD |
+ AD |
+ NA |
+ 5819_CR_A_2527 |
+
+
+ | 445 |
+ HB_430_AD |
+ AD |
+ NA |
+ 5822_CR_A_2530 |
+
+
+ | 446 |
+ HB_434_AD |
+ AD |
+ NA |
+ 5828_CR_A_2533 |
+
+
+ | 447 |
+ HB_435_AD |
+ AD |
+ NA |
+ 5831_CR_A_0222 |
+
+
+ | 448 |
+ HB_437_AD |
+ AD |
+ NA |
+ 5839_CR_A_2539 |
+
+
+ | 449 |
+ HB_438_AD |
+ AD |
+ NA |
+ 5843_CR_A_0227 |
+
+
+ | 450 |
+ HB_439_AD |
+ AD |
+ NA |
+ 5845_CR_A_0230 |
+
+
+ | 451 |
+ HB_441_AD |
+ AD |
+ NA |
+ 5849_CR_A_0233 |
+
+
+ | 452 |
+ HB_442_AD |
+ AD |
+ NA |
+ 5850_CR_A_0495 |
+
+
+ | 453 |
+ HB_445_AD |
+ AD |
+ NA |
+ 5858_CR_A_0969 |
+
+
+ | 454 |
+ HB_448_AD |
+ AD |
+ NA |
+ 5864_CR_A_0974 |
+
+
+ | 455 |
+ HB_451_AD |
+ AD |
+ NA |
+ 5871_CR_A_2542 |
+
+
+ | 456 |
+ HB_454_AD |
+ AD |
+ NA |
+ 5879_CR_A_2545 |
+
+
+ | 457 |
+ HB_455_AD |
+ AD |
+ NA |
+ 5887_CR_A_0976_Bis |
+
+
+ | 458 |
+ HB_459_AD |
+ AD |
+ NA |
+ 5898_CR_A_2548 |
+
+
+ | 459 |
+ HB_460_AD |
+ AD |
+ NA |
+ 5900_VC_A_0237 |
+
+
+ | 460 |
+ HB_461_AD |
+ AD |
+ NA |
+ 5901_CR_A_0239 |
+
+
+ | 461 |
+ HB_469_AD |
+ AD |
+ NA |
+ 5914_CR_A_2554 |
+
+
+ | 462 |
+ HB_471_AD |
+ AD |
+ NA |
+ 5922_VC_A_0246 |
+
+
+ | 463 |
+ HB_473_AD |
+ AD |
+ NA |
+ 5927_CR_A_2560 |
+
+
+ | 464 |
+ HB_474_AD |
+ AD |
+ NA |
+ 5933_VC_A_1071 |
+
+
+ | 465 |
+ HB_477_AD |
+ AD |
+ NA |
+ 5939_CR_A_1151 |
+
+
+ | 466 |
+ HB_479_AD |
+ AD |
+ NA |
+ 5945_VC_A_0983 |
+
+
+ | 467 |
+ HB_484_AD |
+ AD |
+ NA |
+ 5956_CR_A_0123 |
+
+
+ | 468 |
+ HB_489_AD |
+ AD |
+ NA |
+ 5968_VC_A_1075 |
+
+
+ | 469 |
+ HB_491_AD |
+ AD |
+ NA |
+ 5971_CR_A_0119 |
+
+
+ | 470 |
+ HB_492_AD |
+ AD |
+ NA |
+ 5972_VC_A_0251 |
+
+
+ | 471 |
+ HB_494_AD |
+ AD |
+ NA |
+ 5979_CR_A_0115 |
+
+
+ | 472 |
+ HB_498_AD |
+ AD |
+ NA |
+ 5988_VC_A_0503 |
+
+
+ | 473 |
+ HB_502_AD |
+ AD |
+ NA |
+ 5994_PF_A_1605 |
+
+
+ | 474 |
+ HB_503_AD |
+ AD |
+ NA |
+ 5995_CR_A_2563 |
+
+
+ | 475 |
+ HB_510_AD |
+ AD |
+ NA |
+ 6017_CR_A_0048 |
+
+
+ | 476 |
+ HB_514_AD |
+ AD |
+ NA |
+ 6025_VC_A_0506 |
+
+
+ | 477 |
+ HB_517_AD |
+ AD |
+ NA |
+ 6031_VC_A_0258 |
+
+
+ | 478 |
+ HB_520_AD |
+ AD |
+ NA |
+ 6035_VC_A_1621 |
+
+
+ | 479 |
+ HB_523_AD |
+ AD |
+ NA |
+ 6038_VC_A_0261 |
+
+
+ | 480 |
+ HB_524_AD |
+ AD |
+ NA |
+ 6042_VC_A_1156 |
+
+
+ | 481 |
+ HB_525_AD |
+ AD |
+ NA |
+ 6044_VC_A_0264 |
+
+
+ | 482 |
+ HB_531_AD |
+ AD |
+ NA |
+ 6056_CR_A_0999 |
+
+
+ | 483 |
+ HB_533_AD |
+ AD |
+ NA |
+ 6061_PF_A_1650 |
+
+
+ | 484 |
+ HB_534_AD |
+ AD |
+ NA |
+ 6066_VC_A_0270 |
+
+
+ | 485 |
+ HB_535_AD |
+ AD |
+ NA |
+ 6067_PF_A_1452 |
+
+
+ | 486 |
+ HB_536_AD |
+ AD |
+ NA |
+ 6068_VC_A_0273 |
+
+
+ | 487 |
+ HB_545_AD |
+ AD |
+ NA |
+ 6102_CR_A_1661 |
+
+
+ | 488 |
+ HB_546_AD |
+ AD |
+ NA |
+ 6107_CR_A_0055 |
+
+
+ | 489 |
+ HB_550_AD |
+ AD |
+ NA |
+ 6120_VC_A_0058 |
+
+
+ | 490 |
+ HB_552_AD |
+ AD |
+ NA |
+ 6126_VC_A_1675 |
+
+
+ | 491 |
+ HB_553_AD |
+ AD |
+ NA |
+ 6129_PF_A_0274 |
+
+
+ | 492 |
+ HB_554_AD |
+ AD |
+ NA |
+ 6130_VC_A_1678 |
+
+
+ | 493 |
+ HB_555_AD |
+ AD |
+ NA |
+ 6131_CR_A_0510 |
+
+
+ | 494 |
+ HB_556_AD |
+ AD |
+ NA |
+ 6132_CR_A_0513 |
+
+
+ | 495 |
+ HB_558_AD |
+ AD |
+ NA |
+ 6137_VC_A_1681 |
+
+
+ | 496 |
+ HB_564_AD |
+ AD |
+ NA |
+ 6153_VC_A_1465 |
+
+
+ | 497 |
+ HB_565_AD |
+ AD |
+ NA |
+ 6154_VC_A_1468 |
+
+
+ | 498 |
+ HB_566_AD |
+ AD |
+ NA |
+ 6157_VC_A_0062 |
+
+
+ | 499 |
+ HB_568_AD |
+ AD |
+ NA |
+ 6164_CR_A_1005 |
+
+
+ | 500 |
+ HB_571_AD |
+ AD |
+ NA |
+ 6171_CR_A_0065 |
+
+
+ | 501 |
+ HB_573_AD |
+ AD |
+ NA |
+ 6174_VC_A_0068 |
+
+
+ | 502 |
+ HB_576_AD |
+ AD |
+ NA |
+ 6180_CR_A_0281 |
+
+
+ | 503 |
+ HB_583_AD |
+ AD |
+ NA |
+ 6194_VC_A_0071 |
+
+
+ | 504 |
+ HB_585_AD |
+ AD |
+ NA |
+ 6198_VC_A_0073 |
+
+
+ | 505 |
+ HB_590_AD |
+ AD |
+ NA |
+ 6215_VC_A_0518 |
+
+
+ | 506 |
+ HB_591_AD |
+ AD |
+ NA |
+ 6216_VC_A_1476 |
+
+
+ | 507 |
+ HB_592_AD |
+ AD |
+ NA |
+ 6218_CR_A_0522 |
+
+
+ | 508 |
+ HB_594_AD |
+ AD |
+ NA |
+ 6223_VC_A_0288 |
+
+
+ | 509 |
+ HB_596_AD |
+ AD |
+ NA |
+ 6226_CR_A_0076 |
+
+
+ | 510 |
+ HB_597_AD |
+ AD |
+ NA |
+ 6227_VC_A_0080 |
+
+
+ | 511 |
+ HB_598_AD |
+ AD |
+ NA |
+ 6231_VC_A_1479 |
+
+
+ | 512 |
+ HB_605_AD |
+ AD |
+ NA |
+ 6261_VC_A_0084 |
+
+
+ | 513 |
+ HB_608_AD |
+ AD |
+ NA |
+ 6268_CR_A_0525 |
+
+
+ | 514 |
+ HB_611_AD |
+ AD |
+ NA |
+ 6279_VC_A_0089 |
+
+
+ | 515 |
+ HB_612_AD |
+ AD |
+ NA |
+ 6280_VC_A_0091 |
+
+
+ | 516 |
+ HB_613_AD |
+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hbtrc_mlpfc_ad_0611/citation.rtf b/general/datasets/Hbtrc_mlpfc_ad_0611/citation.rtf
new file mode 100644
index 0000000..fa9245d
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_ad_0611/citation.rtf
@@ -0,0 +1,7 @@
+Narayanan M, Huynh JL, Wang K, Yang X, Yoo S, McElwee J, Zhang B, Zhang C, Lamb JR, Xie T, Suver C, Molony C, Melquist S, Johnson AD, Fan G, Stone DJ, Schadt EE, Casaccia P, Emilsson V, Zhu J
+
+Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases.
+
+Mol Syst Biol. 2014 Jul 30;10:743. doi: 10.15252/msb.20145304.
+
+PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_ad_0611/contributors.rtf b/general/datasets/Hbtrc_mlpfc_ad_0611/contributors.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_ad_0611/contributors.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_ad_0611/experiment-design.rtf b/general/datasets/Hbtrc_mlpfc_ad_0611/experiment-design.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_ad_0611/experiment-design.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_ad_0611/notes.rtf b/general/datasets/Hbtrc_mlpfc_ad_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_ad_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/Hbtrc_mlpfc_ad_0611/platform.rtf b/general/datasets/Hbtrc_mlpfc_ad_0611/platform.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_ad_0611/platform.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_ad_0611/processing.rtf b/general/datasets/Hbtrc_mlpfc_ad_0611/processing.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_ad_0611/processing.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_ad_0611/summary.rtf b/general/datasets/Hbtrc_mlpfc_ad_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_ad_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/Hbtrc_mlpfc_ad_0611/tissue.rtf b/general/datasets/Hbtrc_mlpfc_ad_0611/tissue.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_ad_0611/tissue.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_hd_0611/acknowledgment.rtf b/general/datasets/Hbtrc_mlpfc_hd_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_hd_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/Hbtrc_mlpfc_hd_0611/cases.rtf b/general/datasets/Hbtrc_mlpfc_hd_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_hd_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
+ NA |
+ 5370_PF_A_1400 |
+
+
+ | 364 |
+ HB_259_AD |
+ AD |
+ NA |
+ 5371_PF_A_2636 |
+
+
+ | 365 |
+ HB_260_AD |
+ AD |
+ NA |
+ 5375_VC_A_0188 |
+
+
+ | 366 |
+ HB_263_AD |
+ AD |
+ NA |
+ 5381_VC_A_0022 |
+
+
+ | 367 |
+ HB_265_AD |
+ AD |
+ NA |
+ 5385_VC_A_1402 |
+
+
+ | 368 |
+ HB_267_AD |
+ AD |
+ NA |
+ 5389_VC_A_0928 |
+
+
+ | 369 |
+ HB_268_AD |
+ AD |
+ NA |
+ 5390_CR_A_0151 |
+
+
+ | 370 |
+ HB_273_AD |
+ AD |
+ NA |
+ 5400_PF_A_2645 |
+
+
+ | 371 |
+ HB_274_AD |
+ AD |
+ NA |
+ 5401_VC_A_0931 |
+
+
+ | 372 |
+ HB_275_AD |
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+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hbtrc_mlpfc_hd_0611/citation.rtf b/general/datasets/Hbtrc_mlpfc_hd_0611/citation.rtf
new file mode 100644
index 0000000..fa9245d
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_hd_0611/citation.rtf
@@ -0,0 +1,7 @@
+Narayanan M, Huynh JL, Wang K, Yang X, Yoo S, McElwee J, Zhang B, Zhang C, Lamb JR, Xie T, Suver C, Molony C, Melquist S, Johnson AD, Fan G, Stone DJ, Schadt EE, Casaccia P, Emilsson V, Zhu J
+
+Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases.
+
+Mol Syst Biol. 2014 Jul 30;10:743. doi: 10.15252/msb.20145304.
+
+PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_hd_0611/contributors.rtf b/general/datasets/Hbtrc_mlpfc_hd_0611/contributors.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_hd_0611/contributors.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_hd_0611/experiment-design.rtf b/general/datasets/Hbtrc_mlpfc_hd_0611/experiment-design.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_hd_0611/experiment-design.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_hd_0611/notes.rtf b/general/datasets/Hbtrc_mlpfc_hd_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_hd_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/Hbtrc_mlpfc_hd_0611/platform.rtf b/general/datasets/Hbtrc_mlpfc_hd_0611/platform.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_hd_0611/platform.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_hd_0611/processing.rtf b/general/datasets/Hbtrc_mlpfc_hd_0611/processing.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_hd_0611/processing.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_hd_0611/summary.rtf b/general/datasets/Hbtrc_mlpfc_hd_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_hd_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/Hbtrc_mlpfc_hd_0611/tissue.rtf b/general/datasets/Hbtrc_mlpfc_hd_0611/tissue.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_hd_0611/tissue.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_n_0611/acknowledgment.rtf b/general/datasets/Hbtrc_mlpfc_n_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_n_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/Hbtrc_mlpfc_n_0611/cases.rtf b/general/datasets/Hbtrc_mlpfc_n_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_n_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
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+
+
+ | 479 |
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+ AD |
+ NA |
+ 6038_VC_A_0261 |
+
+
+ | 480 |
+ HB_524_AD |
+ AD |
+ NA |
+ 6042_VC_A_1156 |
+
+
+ | 481 |
+ HB_525_AD |
+ AD |
+ NA |
+ 6044_VC_A_0264 |
+
+
+ | 482 |
+ HB_531_AD |
+ AD |
+ NA |
+ 6056_CR_A_0999 |
+
+
+ | 483 |
+ HB_533_AD |
+ AD |
+ NA |
+ 6061_PF_A_1650 |
+
+
+ | 484 |
+ HB_534_AD |
+ AD |
+ NA |
+ 6066_VC_A_0270 |
+
+
+ | 485 |
+ HB_535_AD |
+ AD |
+ NA |
+ 6067_PF_A_1452 |
+
+
+ | 486 |
+ HB_536_AD |
+ AD |
+ NA |
+ 6068_VC_A_0273 |
+
+
+ | 487 |
+ HB_545_AD |
+ AD |
+ NA |
+ 6102_CR_A_1661 |
+
+
+ | 488 |
+ HB_546_AD |
+ AD |
+ NA |
+ 6107_CR_A_0055 |
+
+
+ | 489 |
+ HB_550_AD |
+ AD |
+ NA |
+ 6120_VC_A_0058 |
+
+
+ | 490 |
+ HB_552_AD |
+ AD |
+ NA |
+ 6126_VC_A_1675 |
+
+
+ | 491 |
+ HB_553_AD |
+ AD |
+ NA |
+ 6129_PF_A_0274 |
+
+
+ | 492 |
+ HB_554_AD |
+ AD |
+ NA |
+ 6130_VC_A_1678 |
+
+
+ | 493 |
+ HB_555_AD |
+ AD |
+ NA |
+ 6131_CR_A_0510 |
+
+
+ | 494 |
+ HB_556_AD |
+ AD |
+ NA |
+ 6132_CR_A_0513 |
+
+
+ | 495 |
+ HB_558_AD |
+ AD |
+ NA |
+ 6137_VC_A_1681 |
+
+
+ | 496 |
+ HB_564_AD |
+ AD |
+ NA |
+ 6153_VC_A_1465 |
+
+
+ | 497 |
+ HB_565_AD |
+ AD |
+ NA |
+ 6154_VC_A_1468 |
+
+
+ | 498 |
+ HB_566_AD |
+ AD |
+ NA |
+ 6157_VC_A_0062 |
+
+
+ | 499 |
+ HB_568_AD |
+ AD |
+ NA |
+ 6164_CR_A_1005 |
+
+
+ | 500 |
+ HB_571_AD |
+ AD |
+ NA |
+ 6171_CR_A_0065 |
+
+
+ | 501 |
+ HB_573_AD |
+ AD |
+ NA |
+ 6174_VC_A_0068 |
+
+
+ | 502 |
+ HB_576_AD |
+ AD |
+ NA |
+ 6180_CR_A_0281 |
+
+
+ | 503 |
+ HB_583_AD |
+ AD |
+ NA |
+ 6194_VC_A_0071 |
+
+
+ | 504 |
+ HB_585_AD |
+ AD |
+ NA |
+ 6198_VC_A_0073 |
+
+
+ | 505 |
+ HB_590_AD |
+ AD |
+ NA |
+ 6215_VC_A_0518 |
+
+
+ | 506 |
+ HB_591_AD |
+ AD |
+ NA |
+ 6216_VC_A_1476 |
+
+
+ | 507 |
+ HB_592_AD |
+ AD |
+ NA |
+ 6218_CR_A_0522 |
+
+
+ | 508 |
+ HB_594_AD |
+ AD |
+ NA |
+ 6223_VC_A_0288 |
+
+
+ | 509 |
+ HB_596_AD |
+ AD |
+ NA |
+ 6226_CR_A_0076 |
+
+
+ | 510 |
+ HB_597_AD |
+ AD |
+ NA |
+ 6227_VC_A_0080 |
+
+
+ | 511 |
+ HB_598_AD |
+ AD |
+ NA |
+ 6231_VC_A_1479 |
+
+
+ | 512 |
+ HB_605_AD |
+ AD |
+ NA |
+ 6261_VC_A_0084 |
+
+
+ | 513 |
+ HB_608_AD |
+ AD |
+ NA |
+ 6268_CR_A_0525 |
+
+
+ | 514 |
+ HB_611_AD |
+ AD |
+ NA |
+ 6279_VC_A_0089 |
+
+
+ | 515 |
+ HB_612_AD |
+ AD |
+ NA |
+ 6280_VC_A_0091 |
+
+
+ | 516 |
+ HB_613_AD |
+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hbtrc_mlpfc_n_0611/citation.rtf b/general/datasets/Hbtrc_mlpfc_n_0611/citation.rtf
new file mode 100644
index 0000000..fa9245d
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_n_0611/citation.rtf
@@ -0,0 +1,7 @@
+Narayanan M, Huynh JL, Wang K, Yang X, Yoo S, McElwee J, Zhang B, Zhang C, Lamb JR, Xie T, Suver C, Molony C, Melquist S, Johnson AD, Fan G, Stone DJ, Schadt EE, Casaccia P, Emilsson V, Zhu J
+
+Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases.
+
+Mol Syst Biol. 2014 Jul 30;10:743. doi: 10.15252/msb.20145304.
+
+PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_n_0611/contributors.rtf b/general/datasets/Hbtrc_mlpfc_n_0611/contributors.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_n_0611/contributors.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_n_0611/experiment-design.rtf b/general/datasets/Hbtrc_mlpfc_n_0611/experiment-design.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_n_0611/experiment-design.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_n_0611/notes.rtf b/general/datasets/Hbtrc_mlpfc_n_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_n_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/Hbtrc_mlpfc_n_0611/platform.rtf b/general/datasets/Hbtrc_mlpfc_n_0611/platform.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_n_0611/platform.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_n_0611/processing.rtf b/general/datasets/Hbtrc_mlpfc_n_0611/processing.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_n_0611/processing.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlpfc_n_0611/summary.rtf b/general/datasets/Hbtrc_mlpfc_n_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_n_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/Hbtrc_mlpfc_n_0611/tissue.rtf b/general/datasets/Hbtrc_mlpfc_n_0611/tissue.rtf
new file mode 100644
index 0000000..4ee3070
--- /dev/null
+++ b/general/datasets/Hbtrc_mlpfc_n_0611/tissue.rtf
@@ -0,0 +1 @@
+See PMID: 25080494
diff --git a/general/datasets/Hbtrc_mlvc_0611/acknowledgment.rtf b/general/datasets/Hbtrc_mlvc_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/Hbtrc_mlvc_0611/cases.rtf b/general/datasets/Hbtrc_mlvc_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
+ NA |
+ 5370_PF_A_1400 |
+
+
+ | 364 |
+ HB_259_AD |
+ AD |
+ NA |
+ 5371_PF_A_2636 |
+
+
+ | 365 |
+ HB_260_AD |
+ AD |
+ NA |
+ 5375_VC_A_0188 |
+
+
+ | 366 |
+ HB_263_AD |
+ AD |
+ NA |
+ 5381_VC_A_0022 |
+
+
+ | 367 |
+ HB_265_AD |
+ AD |
+ NA |
+ 5385_VC_A_1402 |
+
+
+ | 368 |
+ HB_267_AD |
+ AD |
+ NA |
+ 5389_VC_A_0928 |
+
+
+ | 369 |
+ HB_268_AD |
+ AD |
+ NA |
+ 5390_CR_A_0151 |
+
+
+ | 370 |
+ HB_273_AD |
+ AD |
+ NA |
+ 5400_PF_A_2645 |
+
+
+ | 371 |
+ HB_274_AD |
+ AD |
+ NA |
+ 5401_VC_A_0931 |
+
+
+ | 372 |
+ HB_275_AD |
+ AD |
+ NA |
+ 5404_PF_A_2648 |
+
+
+ | 373 |
+ HB_276_AD |
+ AD |
+ NA |
+ 5406_VC_A_0933 |
+
+
+ | 374 |
+ HB_277_AD |
+ AD |
+ NA |
+ 5407_PF_A_2651 |
+
+
+ | 375 |
+ HB_280_AD |
+ AD |
+ NA |
+ 5412_VC_A_0935 |
+
+
+ | 376 |
+ HB_281_AD |
+ AD |
+ NA |
+ 5413_PF_A_2657 |
+
+
+ | 377 |
+ HB_283_AD |
+ AD |
+ NA |
+ 5419_VC_A_0937 |
+
+
+ | 378 |
+ HB_284_AD |
+ AD |
+ NA |
+ 5420_VC_A_0939 |
+
+
+ | 379 |
+ HB_285_AD |
+ AD |
+ NA |
+ 5421_CR_A_0432 |
+
+
+ | 380 |
+ HB_286_AD |
+ AD |
+ NA |
+ 5423_PF_A_2660 |
+
+
+ | 381 |
+ HB_288_AD |
+ AD |
+ NA |
+ 5425_PF_A_2666 |
+
+
+ | 382 |
+ HB_289_AD |
+ AD |
+ NA |
+ 5426_VC_A_1405 |
+
+
+ | 383 |
+ HB_290_AD |
+ AD |
+ NA |
+ 5433_VC_A_0434 |
+
+
+ | 384 |
+ HB_296_AD |
+ AD |
+ NA |
+ 5456_PF_A_2675 |
+
+
+ | 385 |
+ HB_299_AD |
+ AD |
+ NA |
+ 5461_VC_A_0192 |
+
+
+ | 386 |
+ HB_302_AD |
+ AD |
+ NA |
+ 5465_PF_A_2678 |
+
+
+ | 387 |
+ HB_303_AD |
+ AD |
+ NA |
+ 5469_VC_A_1417 |
+
+
+ | 388 |
+ HB_305_AD |
+ AD |
+ NA |
+ 5479_PF_A_1421 |
+
+
+ | 389 |
+ HB_306_AD |
+ AD |
+ NA |
+ 5480_VC_A_0437 |
+
+
+ | 390 |
+ HB_307_AD |
+ AD |
+ NA |
+ 5482_VC_A_0028 |
+
+
+ | 391 |
+ HB_308_AD |
+ AD |
+ NA |
+ 5483_VC_A_0941 |
+
+
+ | 392 |
+ HB_309_AD |
+ AD |
+ NA |
+ 5487_CR_A_0441 |
+
+
+ | 393 |
+ HB_310_AD |
+ AD |
+ NA |
+ 5488_CR_A_0194 |
+
+
+ | 394 |
+ HB_312_AD |
+ AD |
+ NA |
+ 5500_VC_A_0198 |
+
+
+ | 395 |
+ HB_313_AD |
+ AD |
+ NA |
+ 5502_PF_A_2684 |
+
+
+ | 396 |
+ HB_315_AD |
+ AD |
+ NA |
+ 5513_PF_A_2687 |
+
+
+ | 397 |
+ HB_316_AD |
+ AD |
+ NA |
+ 5516_PF_A_2690 |
+
+
+ | 398 |
+ HB_317_AD |
+ AD |
+ NA |
+ 5517_PF_A_2693 |
+
+
+ | 399 |
+ HB_318_AD |
+ AD |
+ NA |
+ 5518_CR_A_0030 |
+
+
+ | 400 |
+ HB_319_AD |
+ AD |
+ NA |
+ 5519_CR_A_2695 |
+
+
+ | 401 |
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+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hbtrc_mlvc_0611/notes.rtf b/general/datasets/Hbtrc_mlvc_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/Hbtrc_mlvc_0611/summary.rtf b/general/datasets/Hbtrc_mlvc_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/Hbtrc_mlvc_ad_0611/acknowledgment.rtf b/general/datasets/Hbtrc_mlvc_ad_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_ad_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/Hbtrc_mlvc_ad_0611/cases.rtf b/general/datasets/Hbtrc_mlvc_ad_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_ad_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
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+
+ | 344 |
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+
+ | 345 |
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+
+ | 346 |
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+ | 347 |
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+ | 348 |
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+ | 349 |
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+ | 351 |
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+ | 352 |
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+ | 355 |
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+ | 360 |
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+
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+
+ | 518 |
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+ | 519 |
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+
+ | 520 |
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+
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+
+
+ | 523 |
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+
+
+ | 527 |
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+
+
+ | 528 |
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+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hbtrc_mlvc_ad_0611/notes.rtf b/general/datasets/Hbtrc_mlvc_ad_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_ad_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/Hbtrc_mlvc_ad_0611/summary.rtf b/general/datasets/Hbtrc_mlvc_ad_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_ad_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/Hbtrc_mlvc_hd_0611/acknowledgment.rtf b/general/datasets/Hbtrc_mlvc_hd_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_hd_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/Hbtrc_mlvc_hd_0611/cases.rtf b/general/datasets/Hbtrc_mlvc_hd_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_hd_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
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+
+
+ | 471 |
+ HB_494_AD |
+ AD |
+ NA |
+ 5979_CR_A_0115 |
+
+
+ | 472 |
+ HB_498_AD |
+ AD |
+ NA |
+ 5988_VC_A_0503 |
+
+
+ | 473 |
+ HB_502_AD |
+ AD |
+ NA |
+ 5994_PF_A_1605 |
+
+
+ | 474 |
+ HB_503_AD |
+ AD |
+ NA |
+ 5995_CR_A_2563 |
+
+
+ | 475 |
+ HB_510_AD |
+ AD |
+ NA |
+ 6017_CR_A_0048 |
+
+
+ | 476 |
+ HB_514_AD |
+ AD |
+ NA |
+ 6025_VC_A_0506 |
+
+
+ | 477 |
+ HB_517_AD |
+ AD |
+ NA |
+ 6031_VC_A_0258 |
+
+
+ | 478 |
+ HB_520_AD |
+ AD |
+ NA |
+ 6035_VC_A_1621 |
+
+
+ | 479 |
+ HB_523_AD |
+ AD |
+ NA |
+ 6038_VC_A_0261 |
+
+
+ | 480 |
+ HB_524_AD |
+ AD |
+ NA |
+ 6042_VC_A_1156 |
+
+
+ | 481 |
+ HB_525_AD |
+ AD |
+ NA |
+ 6044_VC_A_0264 |
+
+
+ | 482 |
+ HB_531_AD |
+ AD |
+ NA |
+ 6056_CR_A_0999 |
+
+
+ | 483 |
+ HB_533_AD |
+ AD |
+ NA |
+ 6061_PF_A_1650 |
+
+
+ | 484 |
+ HB_534_AD |
+ AD |
+ NA |
+ 6066_VC_A_0270 |
+
+
+ | 485 |
+ HB_535_AD |
+ AD |
+ NA |
+ 6067_PF_A_1452 |
+
+
+ | 486 |
+ HB_536_AD |
+ AD |
+ NA |
+ 6068_VC_A_0273 |
+
+
+ | 487 |
+ HB_545_AD |
+ AD |
+ NA |
+ 6102_CR_A_1661 |
+
+
+ | 488 |
+ HB_546_AD |
+ AD |
+ NA |
+ 6107_CR_A_0055 |
+
+
+ | 489 |
+ HB_550_AD |
+ AD |
+ NA |
+ 6120_VC_A_0058 |
+
+
+ | 490 |
+ HB_552_AD |
+ AD |
+ NA |
+ 6126_VC_A_1675 |
+
+
+ | 491 |
+ HB_553_AD |
+ AD |
+ NA |
+ 6129_PF_A_0274 |
+
+
+ | 492 |
+ HB_554_AD |
+ AD |
+ NA |
+ 6130_VC_A_1678 |
+
+
+ | 493 |
+ HB_555_AD |
+ AD |
+ NA |
+ 6131_CR_A_0510 |
+
+
+ | 494 |
+ HB_556_AD |
+ AD |
+ NA |
+ 6132_CR_A_0513 |
+
+
+ | 495 |
+ HB_558_AD |
+ AD |
+ NA |
+ 6137_VC_A_1681 |
+
+
+ | 496 |
+ HB_564_AD |
+ AD |
+ NA |
+ 6153_VC_A_1465 |
+
+
+ | 497 |
+ HB_565_AD |
+ AD |
+ NA |
+ 6154_VC_A_1468 |
+
+
+ | 498 |
+ HB_566_AD |
+ AD |
+ NA |
+ 6157_VC_A_0062 |
+
+
+ | 499 |
+ HB_568_AD |
+ AD |
+ NA |
+ 6164_CR_A_1005 |
+
+
+ | 500 |
+ HB_571_AD |
+ AD |
+ NA |
+ 6171_CR_A_0065 |
+
+
+ | 501 |
+ HB_573_AD |
+ AD |
+ NA |
+ 6174_VC_A_0068 |
+
+
+ | 502 |
+ HB_576_AD |
+ AD |
+ NA |
+ 6180_CR_A_0281 |
+
+
+ | 503 |
+ HB_583_AD |
+ AD |
+ NA |
+ 6194_VC_A_0071 |
+
+
+ | 504 |
+ HB_585_AD |
+ AD |
+ NA |
+ 6198_VC_A_0073 |
+
+
+ | 505 |
+ HB_590_AD |
+ AD |
+ NA |
+ 6215_VC_A_0518 |
+
+
+ | 506 |
+ HB_591_AD |
+ AD |
+ NA |
+ 6216_VC_A_1476 |
+
+
+ | 507 |
+ HB_592_AD |
+ AD |
+ NA |
+ 6218_CR_A_0522 |
+
+
+ | 508 |
+ HB_594_AD |
+ AD |
+ NA |
+ 6223_VC_A_0288 |
+
+
+ | 509 |
+ HB_596_AD |
+ AD |
+ NA |
+ 6226_CR_A_0076 |
+
+
+ | 510 |
+ HB_597_AD |
+ AD |
+ NA |
+ 6227_VC_A_0080 |
+
+
+ | 511 |
+ HB_598_AD |
+ AD |
+ NA |
+ 6231_VC_A_1479 |
+
+
+ | 512 |
+ HB_605_AD |
+ AD |
+ NA |
+ 6261_VC_A_0084 |
+
+
+ | 513 |
+ HB_608_AD |
+ AD |
+ NA |
+ 6268_CR_A_0525 |
+
+
+ | 514 |
+ HB_611_AD |
+ AD |
+ NA |
+ 6279_VC_A_0089 |
+
+
+ | 515 |
+ HB_612_AD |
+ AD |
+ NA |
+ 6280_VC_A_0091 |
+
+
+ | 516 |
+ HB_613_AD |
+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hbtrc_mlvc_hd_0611/notes.rtf b/general/datasets/Hbtrc_mlvc_hd_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_hd_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/Hbtrc_mlvc_hd_0611/summary.rtf b/general/datasets/Hbtrc_mlvc_hd_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_hd_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/Hbtrc_mlvc_n_0611/acknowledgment.rtf b/general/datasets/Hbtrc_mlvc_n_0611/acknowledgment.rtf
new file mode 100644
index 0000000..208cb6e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_n_0611/acknowledgment.rtf
@@ -0,0 +1 @@
+The Harvard Brain dataset was contributed by Merck Pharmaceutical through the Sage Bionetworks Repository. The tissues were provided by Harvard Brain Tissue Resource Center which is supported in part by PHS grant R24 MH068855 (http://www.brainbank.mclean.org/).
diff --git a/general/datasets/Hbtrc_mlvc_n_0611/cases.rtf b/general/datasets/Hbtrc_mlvc_n_0611/cases.rtf
new file mode 100644
index 0000000..86ed08e
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_n_0611/cases.rtf
@@ -0,0 +1,4166 @@
+This data packet contains genotypes, clinical traits, as well as expression traits measured in three regions of the brain: visual cortex, cerebellum, prefrontal cortex. Samples were collected from 803 participants including 388 diagnosed with Alzheimer's disease and 220 diagnosed with Huntington's disease. Genotypes were run using two platforms (Illumina and Perlagen). Expression traits were profiled using a custom Agilent platform. Western-IRB has confirmed that this dataset residing in Sage Bionetworks Repository is 'exempt' under federal regulation 45 CFR 46.101(b)4 and does not involve human subject research as defined by OHRP guidelines.
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | Series |
+ Cerebellum in GN |
+ Condition |
+ Gender |
+ BioSample Name |
+
+
+ | 1 |
+ HB_029_N |
+ N |
+ NA |
+ 3405_VC_N_0859 |
+
+
+ | 2 |
+ HB_058_N |
+ N |
+ NA |
+ 4021_VC_N_0854 |
+
+
+ | 3 |
+ HB_064_N |
+ N |
+ NA |
+ 4338_VC_N_0861 |
+
+
+ | 4 |
+ HB_086_N |
+ N |
+ NA |
+ 4729_PF_N_0756 |
+
+
+ | 5 |
+ HB_091_N |
+ N |
+ NA |
+ 4741_VC_N_0864 |
+
+
+ | 6 |
+ HB_092_N |
+ N |
+ NA |
+ 4744_VC_N_0865 |
+
+
+ | 7 |
+ HB_102_N |
+ N |
+ NA |
+ 4810_VC_N_0869 |
+
+
+ | 8 |
+ HB_119_N |
+ N |
+ NA |
+ 4872_VC_N_0878 |
+
+
+ | 9 |
+ HB_147_N |
+ N |
+ NA |
+ 5021_VC_N_0852 |
+
+
+ | 10 |
+ HB_161_N |
+ N |
+ NA |
+ 5077_VC_N_0851 |
+
+
+ | 11 |
+ HB_162_N |
+ N |
+ NA |
+ 5081_VC_N_1021 |
+
+
+ | 12 |
+ HB_166_N |
+ N |
+ NA |
+ 5095_VC_N_1024 |
+
+
+ | 13 |
+ HB_183_N |
+ N |
+ NA |
+ 5162_VC_N_0850 |
+
+
+ | 14 |
+ HB_206_N |
+ N |
+ NA |
+ 5245_VC_N_0849 |
+
+
+ | 15 |
+ HB_215_N |
+ N |
+ NA |
+ 5270_VC_N_0848 |
+
+
+ | 16 |
+ HB_218_N |
+ N |
+ NA |
+ 5276_CR_N_0912 |
+
+
+ | 17 |
+ HB_223_N |
+ N |
+ NA |
+ 5287_VC_N_0916 |
+
+
+ | 18 |
+ HB_226_N |
+ N |
+ NA |
+ 5294_VC_N_0919 |
+
+
+ | 19 |
+ HB_241_N |
+ N |
+ NA |
+ 5326_CR_N_0652 |
+
+
+ | 20 |
+ HB_243_N |
+ N |
+ NA |
+ 5333_VC_N_1262 |
+
+
+ | 21 |
+ HB_247_N |
+ N |
+ NA |
+ 5341_VC_N_0923 |
+
+
+ | 22 |
+ HB_257_N |
+ N |
+ NA |
+ 5368_PF_N_1032 |
+
+
+ | 23 |
+ HB_264_N |
+ N |
+ NA |
+ 5384_VC_N_0924 |
+
+
+ | 24 |
+ HB_295_N |
+ N |
+ NA |
+ 5452_VC_N_1268 |
+
+
+ | 25 |
+ HB_300_N |
+ N |
+ NA |
+ 5463_VC_N_0845 |
+
+
+ | 26 |
+ HB_311_N |
+ N |
+ NA |
+ 5489_CR_N_0942 |
+
+
+ | 27 |
+ HB_324_N |
+ N |
+ NA |
+ 5531_VC_N_0844 |
+
+
+ | 28 |
+ HB_332_N |
+ N |
+ NA |
+ 5547_VC_N_0843 |
+
+
+ | 29 |
+ HB_340_N |
+ N |
+ NA |
+ 5568_VC_N_0842 |
+
+
+ | 30 |
+ HB_360_N |
+ N |
+ NA |
+ 5619_CR_N_0645 |
+
+
+ | 31 |
+ HB_365_N |
+ N |
+ NA |
+ 5632_VC_N_0838 |
+
+
+ | 32 |
+ HB_367_N |
+ N |
+ NA |
+ 5637_VC_N_0837 |
+
+
+ | 33 |
+ HB_382_N |
+ N |
+ NA |
+ 5684_PF_N_1270 |
+
+
+ | 34 |
+ HB_396_N |
+ N |
+ NA |
+ 5718_VC_N_0956 |
+
+
+ | 35 |
+ HB_398_N |
+ N |
+ NA |
+ 5722_VC_N_1044 |
+
+
+ | 36 |
+ HB_400_N |
+ N |
+ NA |
+ 5726_VC_N_0834_Bis |
+
+
+ | 37 |
+ HB_403_N |
+ N |
+ NA |
+ 5734_VC_N_0833 |
+
+
+ | 38 |
+ HB_414_N |
+ N |
+ NA |
+ 5772_VC_N_0832_Bis |
+
+
+ | 39 |
+ HB_416_N |
+ N |
+ NA |
+ 5778_CR_N_0962 |
+
+
+ | 40 |
+ HB_418_N |
+ N |
+ NA |
+ 5789_PF_N_1273 |
+
+
+ | 41 |
+ HB_421_N |
+ N |
+ NA |
+ 5799_VC_N_1058 |
+
+
+ | 42 |
+ HB_423_N |
+ N |
+ NA |
+ 5803_VC_N_0966 |
+
+
+ | 43 |
+ HB_426_N |
+ N |
+ NA |
+ 5806_PF_N_1064 |
+
+
+ | 44 |
+ HB_427_N |
+ N |
+ NA |
+ 5810_CR_N_0636 |
+
+
+ | 45 |
+ HB_431_N |
+ N |
+ NA |
+ 5823_VC_N_0829 |
+
+
+ | 46 |
+ HB_432_N |
+ N |
+ NA |
+ 5826_VC_N_0828 |
+
+
+ | 47 |
+ HB_433_N |
+ N |
+ NA |
+ 5827_VC_N_0827 |
+
+
+ | 48 |
+ HB_436_N |
+ N |
+ NA |
+ 5832_PF_N_1145 |
+
+
+ | 49 |
+ HB_443_N |
+ N |
+ NA |
+ 5852_VC_N_0826 |
+
+
+ | 50 |
+ HB_446_N |
+ N |
+ NA |
+ 5859_VC_N_0825 |
+
+
+ | 51 |
+ HB_449_N |
+ N |
+ NA |
+ 5866_VC_N_0824 |
+
+
+ | 52 |
+ HB_450_N |
+ N |
+ NA |
+ 5867_VC_N_1277 |
+
+
+ | 53 |
+ HB_453_N |
+ N |
+ NA |
+ 5876_VC_N_0823 |
+
+
+ | 54 |
+ HB_462_N |
+ N |
+ NA |
+ 5903_VC_N_0822 |
+
+
+ | 55 |
+ HB_464_N |
+ N |
+ NA |
+ 5905_VC_N_0820 |
+
+
+ | 56 |
+ HB_468_N |
+ N |
+ NA |
+ 5912_VC_N_1286 |
+
+
+ | 57 |
+ HB_472_N |
+ N |
+ NA |
+ 5925_VC_N_1289 |
+
+
+ | 58 |
+ HB_475_N |
+ N |
+ NA |
+ 5936_VC_N_0979 |
+
+
+ | 59 |
+ HB_476_N |
+ N |
+ NA |
+ 5938_VC_N_0819 |
+
+
+ | 60 |
+ HB_480_N |
+ N |
+ NA |
+ 5946_VC_N_0985 |
+
+
+ | 61 |
+ HB_485_N |
+ N |
+ NA |
+ 5959_VC_N_0818 |
+
+
+ | 62 |
+ HB_486_N |
+ N |
+ NA |
+ 5963_VC_N_0987 |
+
+
+ | 63 |
+ HB_495_N |
+ N |
+ NA |
+ 5980_VC_N_0989 |
+
+
+ | 64 |
+ HB_497_N |
+ N |
+ NA |
+ 5985_VC_N_0990 |
+
+
+ | 65 |
+ HB_500_N |
+ N |
+ NA |
+ 5990_VC_N_0817 |
+
+
+ | 66 |
+ HB_501_N |
+ N |
+ NA |
+ 5991_VC_N_0816 |
+
+
+ | 67 |
+ HB_504_N |
+ N |
+ NA |
+ 5996_VC_N_0815 |
+
+
+ | 68 |
+ HB_505_N |
+ N |
+ NA |
+ 5998_VC_N_0814 |
+
+
+ | 69 |
+ HB_507_N |
+ N |
+ NA |
+ 6006_VC_N_0813 |
+
+
+ | 70 |
+ HB_508_N |
+ N |
+ NA |
+ 6007_CR_N_0618 |
+
+
+ | 71 |
+ HB_509_N |
+ N |
+ NA |
+ 6008_PF_N_1081 |
+
+
+ | 72 |
+ HB_512_N |
+ N |
+ NA |
+ 6023_PF_N_1155 |
+
+
+ | 73 |
+ HB_516_N |
+ N |
+ NA |
+ 6030_VC_N_0810 |
+
+
+ | 74 |
+ HB_519_N |
+ N |
+ NA |
+ 6034_VC_N_0809 |
+
+
+ | 75 |
+ HB_532_N |
+ N |
+ NA |
+ 6060_VC_N_1292 |
+
+
+ | 76 |
+ HB_541_N |
+ N |
+ NA |
+ 6092_VC_N_1001 |
+
+
+ | 77 |
+ HB_542_N |
+ N |
+ NA |
+ 6096_VC_N_0807 |
+
+
+ | 78 |
+ HB_544_N |
+ N |
+ NA |
+ 6101_CR_N_1161 |
+
+
+ | 79 |
+ HB_547_N |
+ N |
+ NA |
+ 6110_VC_N_1295 |
+
+
+ | 80 |
+ HB_551_N |
+ N |
+ NA |
+ 6124_VC_N_0806 |
+
+
+ | 81 |
+ HB_557_N |
+ N |
+ NA |
+ 6134_PF_N_1297 |
+
+
+ | 82 |
+ HB_560_N |
+ N |
+ NA |
+ 6142_VC_N_0805 |
+
+
+ | 83 |
+ HB_569_N |
+ N |
+ NA |
+ 6166_VC_N_0804 |
+
+
+ | 84 |
+ HB_570_N |
+ N |
+ NA |
+ 6170_VC_N_0803 |
+
+
+ | 85 |
+ HB_572_N |
+ N |
+ NA |
+ 6172_VC_N_1008 |
+
+
+ | 86 |
+ HB_577_N |
+ N |
+ NA |
+ 6182_VC_N_1166 |
+
+
+ | 87 |
+ HB_579_N |
+ N |
+ NA |
+ 6187_CR_N_0607 |
+
+
+ | 88 |
+ HB_581_N |
+ N |
+ NA |
+ 6191_VC_N_1010 |
+
+
+ | 89 |
+ HB_584_N |
+ N |
+ NA |
+ 6196_CR_N_0605 |
+
+
+ | 90 |
+ HB_586_N |
+ N |
+ NA |
+ 6200_VC_N_0799 |
+
+
+ | 91 |
+ HB_587_N |
+ N |
+ NA |
+ 6206_PF_N_1176 |
+
+
+ | 92 |
+ HB_589_N |
+ N |
+ NA |
+ 6213_VC_N_0798 |
+
+
+ | 93 |
+ HB_601_N |
+ N |
+ NA |
+ 6241_VC_N_0796 |
+
+
+ | 94 |
+ HB_604_N |
+ N |
+ NA |
+ 6260_VC_N_0794 |
+
+
+ | 95 |
+ HB_609_N |
+ N |
+ NA |
+ 6270_VC_N_0793 |
+
+
+ | 96 |
+ HB_618_N |
+ N |
+ NA |
+ 6289_VC_N_0791 |
+
+
+ | 97 |
+ HB_622_N |
+ N |
+ NA |
+ 6310_VC_N_0790 |
+
+
+ | 98 |
+ HB_625_N |
+ N |
+ NA |
+ 6314_VC_N_0789 |
+
+
+ | 99 |
+ HB_637_N |
+ N |
+ NA |
+ 6340_VC_N_0786 |
+
+
+ | 100 |
+ HB_638_N |
+ N |
+ NA |
+ 6341_VC_N_0785 |
+
+
+ | 101 |
+ HB_640_N |
+ N |
+ NA |
+ 6347_VC_N_0784 |
+
+
+ | 102 |
+ HB_641_N |
+ N |
+ NA |
+ 6356_VC_N_0783 |
+
+
+ | 103 |
+ HB_643_N |
+ N |
+ NA |
+ 6363_VC_N_0781 |
+
+
+ | 104 |
+ HB_644_N |
+ N |
+ NA |
+ 6366_VC_N_0780 |
+
+
+ | 105 |
+ HB_645_N |
+ N |
+ NA |
+ 6374_VC_N_0779 |
+
+
+ | 106 |
+ HB_650_N |
+ N |
+ NA |
+ 6384_VC_N_0777 |
+
+
+ | 107 |
+ HB_651_N |
+ N |
+ NA |
+ 6386_VC_N_0776 |
+
+
+ | 108 |
+ HB_653_N |
+ N |
+ NA |
+ 6388_VC_N_0775 |
+
+
+ | 109 |
+ HB_659_N |
+ N |
+ NA |
+ 6406_VC_N_1180 |
+
+
+ | 110 |
+ HB_662_N |
+ N |
+ NA |
+ 6411_VC_N_0771 |
+
+
+ | 111 |
+ HB_663_N |
+ N |
+ NA |
+ 6415_VC_N_0770 |
+
+
+ | 112 |
+ HB_670_N |
+ N |
+ NA |
+ 6436_VC_N_0769 |
+
+
+ | 113 |
+ HB_687_N |
+ N |
+ NA |
+ 6484_VC_N_0765 |
+
+
+ | 114 |
+ HB_689_N |
+ N |
+ NA |
+ 6486_VC_N_0764 |
+
+
+ | 115 |
+ HB_694_N |
+ N |
+ NA |
+ 6500_VC_N_0763 |
+
+
+ | 116 |
+ HB_697_N |
+ N |
+ NA |
+ 6512_VC_N_0762 |
+
+
+ | 117 |
+ HB_700_N |
+ N |
+ NA |
+ 6520_VC_N_0761 |
+
+
+ | 118 |
+ HB_711_N |
+ N |
+ NA |
+ 6543_PF_N_1191 |
+
+
+ | 119 |
+ HB_714_N |
+ N |
+ NA |
+ 6549_VC_N_1198 |
+
+
+ | 120 |
+ HB_717_N |
+ N |
+ NA |
+ 6553_PF_N_2284 |
+
+
+ | 121 |
+ HB_721_N |
+ N |
+ NA |
+ 6560_VC_N_2578 |
+
+
+ | 122 |
+ HB_726_N |
+ N |
+ NA |
+ 6573_PF_N_2293 |
+
+
+ | 123 |
+ HB_730_N |
+ N |
+ NA |
+ 6580_VC_N_2306 |
+
+
+ | 124 |
+ HB_735_N |
+ N |
+ NA |
+ 6588_VC_N_1213 |
+
+
+ | 125 |
+ HB_737_N |
+ N |
+ NA |
+ 6593_VC_N_1219 |
+
+
+ | 126 |
+ HB_738_N |
+ N |
+ NA |
+ 6594_VC_N_1222 |
+
+
+ | 127 |
+ HB_759_N |
+ N |
+ NA |
+ 6645_VC_N_1231 |
+
+
+ | 128 |
+ HB_764_N |
+ N |
+ NA |
+ 6655_VC_N_1240 |
+
+
+ | 129 |
+ HB_765_N |
+ N |
+ NA |
+ 6656_VC_N_1243 |
+
+
+ | 130 |
+ HB_767_N |
+ N |
+ NA |
+ 6661_PF_N_2341 |
+
+
+ | 131 |
+ HB_770_N |
+ N |
+ NA |
+ 6669_VC_N_1246 |
+
+
+ | 132 |
+ HB_772_N |
+ N |
+ NA |
+ 6676_PF_N_1248 |
+
+
+ | 133 |
+ HB_001_HD |
+ HD |
+ F |
+ 2028_CR_H_2282 |
+
+
+ | 134 |
+ HB_003_HD |
+ HD |
+ F |
+ 2685_PF_H_2212 |
+
+
+ | 135 |
+ HB_004_HD |
+ HD |
+ M |
+ 2706_CR_H_2432 |
+
+
+ | 136 |
+ HB_006_HD |
+ HD |
+ M |
+ 2737_VC_H_2194 |
+
+
+ | 137 |
+ HB_007_HD |
+ HD |
+ NA |
+ 2769_VC_H_2193 |
+
+
+ | 138 |
+ HB_008_HD |
+ HD |
+ F |
+ 2790_CR_H_1890 |
+
+
+ | 139 |
+ HB_009_HD |
+ HD |
+ NA |
+ 2879_VC_H_2192 |
+
+
+ | 140 |
+ HB_010_HD |
+ HD |
+ M |
+ 2960_VC_H_2002 |
+
+
+ | 141 |
+ HB_011_HD |
+ HD |
+ F |
+ 3053_VC_H_2001 |
+
+
+ | 142 |
+ HB_012_HD |
+ HD |
+ F |
+ 3128_VC_H_1999 |
+
+
+ | 143 |
+ HB_014_HD |
+ HD |
+ F |
+ 3149_PF_H_2110 |
+
+
+ | 144 |
+ HB_015_HD |
+ HD |
+ F |
+ 3150_VC_H_1996 |
+
+
+ | 145 |
+ HB_016_HD |
+ HD |
+ F |
+ 3177_VC_H_2191 |
+
+
+ | 146 |
+ HB_017_HD |
+ HD |
+ NA |
+ 3195_VC_H_2190 |
+
+
+ | 147 |
+ HB_018_HD |
+ HD |
+ M |
+ 3200_VC_H_2189 |
+
+
+ | 148 |
+ HB_019_HD |
+ HD |
+ M |
+ 3209_VC_H_2188 |
+
+
+ | 149 |
+ HB_020_HD |
+ HD |
+ M |
+ 3224_VC_H_1994 |
+
+
+ | 150 |
+ HB_022_HD |
+ HD |
+ F |
+ 3242_PF_H_2105 |
+
+
+ | 151 |
+ HB_024_HD |
+ HD |
+ NA |
+ 3272_VC_H_2186 |
+
+
+ | 152 |
+ HB_027_HD |
+ HD |
+ M |
+ 3356_VC_H_2439 |
+
+
+ | 153 |
+ HB_028_HD |
+ HD |
+ F |
+ 3394_PF_H_2104 |
+
+
+ | 154 |
+ HB_031_HD |
+ HD |
+ M |
+ 3430_VC_H_1990 |
+
+
+ | 155 |
+ HB_032_HD |
+ HD |
+ NA |
+ 3444_PF_H_2208 |
+
+
+ | 156 |
+ HB_034_HD |
+ HD |
+ F |
+ 3482_VC_H_1987 |
+
+
+ | 157 |
+ HB_036_HD |
+ HD |
+ M |
+ 3576_VC_H_1984 |
+
+
+ | 158 |
+ HB_037_HD |
+ HD |
+ F |
+ 3579_VC_H_1983 |
+
+
+ | 159 |
+ HB_038_HD |
+ HD |
+ F |
+ 3584_VC_H_2183 |
+
+
+ | 160 |
+ HB_039_HD |
+ HD |
+ NA |
+ 3635_VC_H_2182 |
+
+
+ | 161 |
+ HB_041_HD |
+ HD |
+ F |
+ 3695_CR_H_2267 |
+
+
+ | 162 |
+ HB_042_HD |
+ HD |
+ M |
+ 3697_VC_H_1982 |
+
+
+ | 163 |
+ HB_043_HD |
+ HD |
+ NA |
+ 3703_VC_H_2180 |
+
+
+ | 164 |
+ HB_044_HD |
+ HD |
+ NA |
+ 3723_VC_H_2179 |
+
+
+ | 165 |
+ HB_046_HD |
+ HD |
+ F |
+ 3735_VC_H_1981 |
+
+
+ | 166 |
+ HB_050_HD |
+ HD |
+ M |
+ 3820_PF_H_2207 |
+
+
+ | 167 |
+ HB_051_HD |
+ HD |
+ F |
+ 3849_CR_H_2262 |
+
+
+ | 168 |
+ HB_054_HD |
+ HD |
+ M |
+ 3884_VC_H_2175 |
+
+
+ | 169 |
+ HB_056_HD |
+ HD |
+ NA |
+ 4012_VC_H_2174 |
+
+
+ | 170 |
+ HB_057_HD |
+ HD |
+ NA |
+ 4013_VC_H_2173 |
+
+
+ | 171 |
+ HB_059_HD |
+ HD |
+ NA |
+ 4066_VC_H_2172 |
+
+
+ | 172 |
+ HB_060_HD |
+ HD |
+ NA |
+ 4094_VC_H_2171 |
+
+
+ | 173 |
+ HB_061_HD |
+ HD |
+ F |
+ 4116_VC_H_2170 |
+
+
+ | 174 |
+ HB_062_HD |
+ HD |
+ NA |
+ 4121_VC_H_2169 |
+
+
+ | 175 |
+ HB_063_HD |
+ HD |
+ NA |
+ 4215_VC_H_2167 |
+
+
+ | 176 |
+ HB_065_HD |
+ HD |
+ M |
+ 4340_PF_H_2091 |
+
+
+ | 177 |
+ HB_066_HD |
+ HD |
+ F |
+ 4344_VC_H_1977 |
+
+
+ | 178 |
+ HB_067_HD |
+ HD |
+ M |
+ 4346_VC_H_2165 |
+
+
+ | 179 |
+ HB_069_HD |
+ HD |
+ F |
+ 4356_VC_H_2164 |
+
+
+ | 180 |
+ HB_070_HD |
+ HD |
+ NA |
+ 4386_CR_H_2249 |
+
+
+ | 181 |
+ HB_072_HD |
+ HD |
+ NA |
+ 4404_VC_H_2161 |
+
+
+ | 182 |
+ HB_073_HD |
+ HD |
+ F |
+ 4411_VC_H_1975 |
+
+
+ | 183 |
+ HB_074_HD |
+ HD |
+ NA |
+ 4430_VC_H_2465 |
+
+
+ | 184 |
+ HB_075_HD |
+ HD |
+ M |
+ 4470_VC_H_1974 |
+
+
+ | 185 |
+ HB_076_HD |
+ HD |
+ F |
+ 4497_CR_H_1860 |
+
+
+ | 186 |
+ HB_077_HD |
+ HD |
+ M |
+ 4509_CR_H_2244 |
+
+
+ | 187 |
+ HB_079_HD |
+ HD |
+ M |
+ 4631_VC_H_1971 |
+
+
+ | 188 |
+ HB_080_HD |
+ HD |
+ F |
+ 4653_PF_H_2083 |
+
+
+ | 189 |
+ HB_081_HD |
+ HD |
+ NA |
+ 4678_CR_H_2242 |
+
+
+ | 190 |
+ HB_084_HD |
+ HD |
+ M |
+ 4718_VC_H_2125 |
+
+
+ | 191 |
+ HB_090_HD |
+ HD |
+ NA |
+ 4740_CR_H_2474 |
+
+
+ | 192 |
+ HB_094_HD |
+ HD |
+ NA |
+ 4754_CR_H_2476 |
+
+
+ | 193 |
+ HB_098_HD |
+ HD |
+ NA |
+ 4780_VC_H_2151 |
+
+
+ | 194 |
+ HB_101_HD |
+ HD |
+ F |
+ 4809_VC_H_2148 |
+
+
+ | 195 |
+ HB_105_HD |
+ HD |
+ NA |
+ 4819_CR_H_2238 |
+
+
+ | 196 |
+ HB_106_HD |
+ HD |
+ F |
+ 4822_VC_H_1969 |
+
+
+ | 197 |
+ HB_108_HD |
+ HD |
+ M |
+ 4826_VC_H_1968 |
+
+
+ | 198 |
+ HB_109_HD |
+ HD |
+ M |
+ 4828_VC_H_2124 |
+
+
+ | 199 |
+ HB_115_HD |
+ HD |
+ NA |
+ 4855_CR_H_2235 |
+
+
+ | 200 |
+ HB_121_HD |
+ HD |
+ F |
+ 4902_VC_H_1967 |
+
+
+ | 201 |
+ HB_129_HD |
+ HD |
+ NA |
+ 4938_VC_H_1966 |
+
+
+ | 202 |
+ HB_141_HD |
+ HD |
+ F |
+ 4996_PF_H_2076 |
+
+
+ | 203 |
+ HB_152_HD |
+ HD |
+ NA |
+ 5034_CR_H_2233 |
+
+
+ | 204 |
+ HB_153_HD |
+ HD |
+ M |
+ 5043_VC_H_1960 |
+
+
+ | 205 |
+ HB_159_HD |
+ HD |
+ M |
+ 5062_VC_H_1959 |
+
+
+ | 206 |
+ HB_172_HD |
+ HD |
+ F |
+ 5114_PF_H_2070 |
+
+
+ | 207 |
+ HB_175_HD |
+ HD |
+ M |
+ 5127_PF_H_2068 |
+
+
+ | 208 |
+ HB_180_HD |
+ HD |
+ M |
+ 5148_VC_H_1944 |
+
+
+ | 209 |
+ HB_185_HD |
+ HD |
+ F |
+ 5167_CR_H_2231 |
+
+
+ | 210 |
+ HB_188_HD |
+ HD |
+ F |
+ 5172_VC_H_1951 |
+
+
+ | 211 |
+ HB_191_HD |
+ HD |
+ M |
+ 5180_VC_H_1949 |
+
+
+ | 212 |
+ HB_196_HD |
+ HD |
+ NA |
+ 5199_PF_H_2202 |
+
+
+ | 213 |
+ HB_203_HD |
+ HD |
+ F |
+ 5228_PF_H_2059 |
+
+
+ | 214 |
+ HB_207_HD |
+ HD |
+ NA |
+ 5248_PF_H_2201 |
+
+
+ | 215 |
+ HB_228_HD |
+ HD |
+ F |
+ 5299_CR_H_2228 |
+
+
+ | 216 |
+ HB_233_HD |
+ HD |
+ M |
+ 5312_VC_H_1938 |
+
+
+ | 217 |
+ HB_235_HD |
+ HD |
+ F |
+ 5316_VC_H_1937 |
+
+
+ | 218 |
+ HB_242_HD |
+ HD |
+ F |
+ 5328_PF_H_2048 |
+
+
+ | 219 |
+ HB_266_HD |
+ HD |
+ M |
+ 5387_VC_H_1928 |
+
+
+ | 220 |
+ HB_271_HD |
+ HD |
+ M |
+ 5394_PF_H_2039 |
+
+
+ | 221 |
+ HB_272_HD |
+ HD |
+ F |
+ 5396_VC_H_1925 |
+
+
+ | 222 |
+ HB_279_HD |
+ HD |
+ F |
+ 5409_VC_H_1924 |
+
+
+ | 223 |
+ HB_294_HD |
+ HD |
+ M |
+ 5448_VC_H_1921 |
+
+
+ | 224 |
+ HB_301_HD |
+ HD |
+ NA |
+ 5464_VC_H_1919 |
+
+
+ | 225 |
+ HB_304_HD |
+ HD |
+ F |
+ 5471_VC_H_1918 |
+
+
+ | 226 |
+ HB_321_HD |
+ HD |
+ NA |
+ 5522_PF_H_2199 |
+
+
+ | 227 |
+ HB_361_HD |
+ HD |
+ F |
+ 5622_VC_H_2121 |
+
+
+ | 228 |
+ HB_370_HD |
+ HD |
+ M |
+ 5645_VC_H_1904 |
+
+
+ | 229 |
+ HB_371_HD |
+ HD |
+ F |
+ 5648_PF_H_2016 |
+
+
+ | 230 |
+ HB_384_HD |
+ HD |
+ F |
+ 5688_PF_H_2012 |
+
+
+ | 231 |
+ HB_390_HD |
+ HD |
+ M |
+ 5704_PF_H_2009 |
+
+
+ | 232 |
+ HB_393_HD |
+ HD |
+ F |
+ 5709_VC_H_1895 |
+
+
+ | 233 |
+ HB_402_HD |
+ HD |
+ F |
+ 5732_PF_H_2007 |
+
+
+ | 234 |
+ HB_405_HD |
+ HD |
+ NA |
+ 5742_PF_H_2006 |
+
+
+ | 235 |
+ HB_407_HD |
+ HD |
+ M |
+ 5745_PF_H_2005 |
+
+
+ | 236 |
+ HB_408_HD |
+ HD |
+ M |
+ 5747_VC_H_1891 |
+
+
+ | 237 |
+ HB_415_HD |
+ HD |
+ NA |
+ 5777_PF_H_1551 |
+
+
+ | 238 |
+ HB_417_HD |
+ HD |
+ M |
+ 5784_PF_H_1554 |
+
+
+ | 239 |
+ HB_424_HD |
+ HD |
+ M |
+ 5804_VC_H_1558 |
+
+
+ | 240 |
+ HB_444_HD |
+ HD |
+ M |
+ 5856_VC_H_1567 |
+
+
+ | 241 |
+ HB_457_HD |
+ HD |
+ M |
+ 5896_VC_H_1570 |
+
+
+ | 242 |
+ HB_466_HD |
+ HD |
+ M |
+ 5910_PF_H_1572 |
+
+
+ | 243 |
+ HB_478_HD |
+ HD |
+ M |
+ 5941_CR_H_1583 |
+
+
+ | 244 |
+ HB_487_HD |
+ HD |
+ F |
+ 5964_VC_H_1597 |
+
+
+ | 245 |
+ HB_511_HD |
+ HD |
+ M |
+ 6019_PF_H_2198 |
+
+
+ | 246 |
+ HB_513_HD |
+ HD |
+ F |
+ 6024_VC_H_1612 |
+
+
+ | 247 |
+ HB_515_HD |
+ HD |
+ F |
+ 6028_CR_H_1613 |
+
+
+ | 248 |
+ HB_518_HD |
+ HD |
+ M |
+ 6033_VC_H_1618 |
+
+
+ | 249 |
+ HB_522_HD |
+ HD |
+ M |
+ 6037_PF_H_1626 |
+
+
+ | 250 |
+ HB_527_HD |
+ HD |
+ F |
+ 6047_VC_H_1639 |
+
+
+ | 251 |
+ HB_528_HD |
+ HD |
+ M |
+ 6051_PF_H_1641 |
+
+
+ | 252 |
+ HB_530_HD |
+ HD |
+ M |
+ 6054_VC_H_1648 |
+
+
+ | 253 |
+ HB_537_HD |
+ HD |
+ F |
+ 6071_PF_H_1653 |
+
+
+ | 254 |
+ HB_549_HD |
+ HD |
+ M |
+ 6119_CR_H_1670 |
+
+
+ | 255 |
+ HB_593_HD |
+ HD |
+ NA |
+ 6219_CR_H_2567 |
+
+
+ | 256 |
+ HB_610_HD |
+ HD |
+ NA |
+ 6275_PF_H_1692 |
+
+
+ | 257 |
+ HB_616_HD |
+ HD |
+ F |
+ 6284_CR_H_1694 |
+
+
+ | 258 |
+ HB_626_HD |
+ HD |
+ M |
+ 6315_VC_H_1702 |
+
+
+ | 259 |
+ HB_639_HD |
+ HD |
+ F |
+ 6344_CR_H_1703 |
+
+
+ | 260 |
+ HB_649_HD |
+ HD |
+ F |
+ 6382_CR_H_1709 |
+
+
+ | 261 |
+ HB_661_HD |
+ HD |
+ M |
+ 6408_VC_H_1714 |
+
+
+ | 262 |
+ HB_682_HD |
+ HD |
+ M |
+ 6467_PF_H_1725 |
+
+
+ | 263 |
+ HB_683_HD |
+ HD |
+ M |
+ 6472_VC_H_1729 |
+
+
+ | 264 |
+ HB_691_HD |
+ HD |
+ F |
+ 6493_VC_H_1732 |
+
+
+ | 265 |
+ HB_692_HD |
+ HD |
+ M |
+ 6495_CR_H_1733 |
+
+
+ | 266 |
+ HB_707_HD |
+ HD |
+ M |
+ 6535_PF_H_1737 |
+
+
+ | 267 |
+ HB_709_HD |
+ HD |
+ F |
+ 6539_CR_H_1739 |
+
+
+ | 268 |
+ HB_725_HD |
+ HD |
+ M |
+ 6572_PF_H_1746 |
+
+
+ | 269 |
+ HB_732_HD |
+ HD |
+ F |
+ 6584_VC_H_1750 |
+
+
+ | 270 |
+ HB_734_HD |
+ HD |
+ F |
+ 6587_CR_H_1751 |
+
+
+ | 271 |
+ HB_748_HD |
+ HD |
+ NA |
+ 6615_VC_H_2315 |
+
+
+ | 272 |
+ HB_750_HD |
+ HD |
+ NA |
+ 6628_PF_H_2326 |
+
+
+ | 273 |
+ HB_758_HD |
+ HD |
+ NA |
+ 6643_VC_H_2602 |
+
+
+ | 274 |
+ HB_760_HD |
+ HD |
+ M |
+ 6646_PF_H_1761 |
+
+
+ | 275 |
+ HB_762_HD |
+ HD |
+ M |
+ 6650_VC_H_1765 |
+
+
+ | 276 |
+ HB_766_HD |
+ HD |
+ M |
+ 6658_VC_H_1768 |
+
+
+ | 277 |
+ HB_768_HD |
+ HD |
+ NA |
+ 6663_VC_H_1771 |
+
+
+ | 278 |
+ HB_769_HD |
+ HD |
+ M |
+ 6666_VC_H_1774 |
+
+
+ | 279 |
+ HB_774_HD |
+ HD |
+ NA |
+ 6689_PF_H_2344 |
+
+
+ | 280 |
+ HB_778_HD |
+ HD |
+ NA |
+ 6696_PF_H_2356 |
+
+
+ | 281 |
+ HB_780_HD |
+ HD |
+ NA |
+ 6704_PF_H_2362 |
+
+
+ | 282 |
+ HB_790_HD |
+ HD |
+ NA |
+ 6788_PF_H_2389 |
+
+
+ | 283 |
+ HB_800_HD |
+ HD |
+ NA |
+ 6807_PF_H_2419 |
+
+
+ | 284 |
+ HB_802_HD |
+ HD |
+ NA |
+ 6811_PF_H_2425 |
+
+
+ | 285 |
+ HB_045_AD |
+ AD |
+ NA |
+ 3734_CR_A_0122 |
+
+
+ | 286 |
+ HB_048_AD |
+ AD |
+ NA |
+ 3791_CR_A_0128 |
+
+
+ | 287 |
+ HB_053_AD |
+ AD |
+ NA |
+ 3877_CR_A_0134 |
+
+
+ | 288 |
+ HB_055_AD |
+ AD |
+ NA |
+ 3893_VC_A_0142 |
+
+
+ | 289 |
+ HB_068_AD |
+ AD |
+ NA |
+ 4349_VC_A_0148 |
+
+
+ | 290 |
+ HB_082_AD |
+ AD |
+ NA |
+ 4712_CR_A_0309 |
+
+
+ | 291 |
+ HB_085_AD |
+ AD |
+ NA |
+ 4726_VC_A_0311 |
+
+
+ | 292 |
+ HB_087_AD |
+ AD |
+ NA |
+ 4730_CR_A_0315 |
+
+
+ | 293 |
+ HB_089_AD |
+ AD |
+ NA |
+ 4733_VC_A_0320 |
+
+
+ | 294 |
+ HB_093_AD |
+ AD |
+ NA |
+ 4749_VC_A_0323 |
+
+
+ | 295 |
+ HB_095_AD |
+ AD |
+ NA |
+ 4759_CR_A_0327 |
+
+
+ | 296 |
+ HB_097_AD |
+ AD |
+ NA |
+ 4773_CR_A_0866 |
+
+
+ | 297 |
+ HB_099_AD |
+ AD |
+ NA |
+ 4785_VC_A_0332 |
+
+
+ | 298 |
+ HB_100_AD |
+ AD |
+ NA |
+ 4795_VC_A_0335 |
+
+
+ | 299 |
+ HB_103_AD |
+ AD |
+ NA |
+ 4811_VC_A_0341 |
+
+
+ | 300 |
+ HB_104_AD |
+ AD |
+ NA |
+ 4813_CR_A_0345 |
+
+
+ | 301 |
+ HB_112_AD |
+ AD |
+ NA |
+ 4842_VC_A_0870 |
+
+
+ | 302 |
+ HB_113_AD |
+ AD |
+ NA |
+ 4850_CR_A_0351 |
+
+
+ | 303 |
+ HB_114_AD |
+ AD |
+ NA |
+ 4852_CR_A_0354 |
+
+
+ | 304 |
+ HB_117_AD |
+ AD |
+ NA |
+ 4868_VC_A_0874 |
+
+
+ | 305 |
+ HB_122_AD |
+ AD |
+ NA |
+ 4904_CR_A_1132 |
+
+
+ | 306 |
+ HB_123_AD |
+ AD |
+ NA |
+ 4905_VC_A_0884 |
+
+
+ | 307 |
+ HB_124_AD |
+ AD |
+ NA |
+ 4916_VC_A_0886 |
+
+
+ | 308 |
+ HB_125_AD |
+ AD |
+ NA |
+ 4917_CR_A_0360 |
+
+
+ | 309 |
+ HB_126_AD |
+ AD |
+ NA |
+ 4921_VC_A_0362 |
+
+
+ | 310 |
+ HB_128_AD |
+ AD |
+ NA |
+ 4936_CR_A_0369 |
+
+
+ | 311 |
+ HB_130_AD |
+ AD |
+ NA |
+ 4939_VC_A_0888 |
+
+
+ | 312 |
+ HB_131_AD |
+ AD |
+ NA |
+ 4944_CR_A_0889 |
+
+
+ | 313 |
+ HB_132_AD |
+ AD |
+ NA |
+ 4946_CR_A_0372 |
+
+
+ | 314 |
+ HB_134_AD |
+ AD |
+ NA |
+ 4951_CR_A_0891 |
+
+
+ | 315 |
+ HB_135_AD |
+ AD |
+ NA |
+ 4953_VC_A_0893 |
+
+
+ | 316 |
+ HB_136_AD |
+ AD |
+ NA |
+ 4965_VC_A_0160 |
+
+
+ | 317 |
+ HB_137_AD |
+ AD |
+ NA |
+ 4966_VC_A_0374 |
+
+
+ | 318 |
+ HB_138_AD |
+ AD |
+ NA |
+ 4969_VC_A_0895 |
+
+
+ | 319 |
+ HB_140_AD |
+ AD |
+ NA |
+ 4993_CR_A_0896 |
+
+
+ | 320 |
+ HB_146_AD |
+ AD |
+ NA |
+ 5018_CR_A_0384 |
+
+
+ | 321 |
+ HB_148_AD |
+ AD |
+ NA |
+ 5022_VC_A_0386 |
+
+
+ | 322 |
+ HB_150_AD |
+ AD |
+ NA |
+ 5031_VC_A_0392 |
+
+
+ | 323 |
+ HB_151_AD |
+ AD |
+ NA |
+ 5033_CR_A_0396 |
+
+
+ | 324 |
+ HB_154_AD |
+ AD |
+ NA |
+ 5048_VC_A_1321 |
+
+
+ | 325 |
+ HB_155_AD |
+ AD |
+ NA |
+ 5056_VC_A_0398 |
+
+
+ | 326 |
+ HB_156_AD |
+ AD |
+ NA |
+ 5057_VC_A_0163 |
+
+
+ | 327 |
+ HB_157_AD |
+ AD |
+ NA |
+ 5059_VC_A_0401 |
+
+
+ | 328 |
+ HB_158_AD |
+ AD |
+ NA |
+ 5061_PF_A_2612 |
+
+
+ | 329 |
+ HB_160_AD |
+ AD |
+ NA |
+ 5064_PF_A_2615 |
+
+
+ | 330 |
+ HB_165_AD |
+ AD |
+ NA |
+ 5092_CR_A_0899 |
+
+
+ | 331 |
+ HB_168_AD |
+ AD |
+ NA |
+ 5097_VC_A_0407 |
+
+
+ | 332 |
+ HB_170_AD |
+ AD |
+ NA |
+ 5101_VC_A_0410 |
+
+
+ | 333 |
+ HB_174_AD |
+ AD |
+ NA |
+ 5124_PF_A_1343 |
+
+
+ | 334 |
+ HB_179_AD |
+ AD |
+ NA |
+ 5145_VC_A_1351 |
+
+
+ | 335 |
+ HB_181_AD |
+ AD |
+ NA |
+ 5152_CR_A_0414 |
+
+
+ | 336 |
+ HB_184_AD |
+ AD |
+ NA |
+ 5166_VC_A_1354 |
+
+
+ | 337 |
+ HB_194_AD |
+ AD |
+ NA |
+ 5193_VC_A_1360 |
+
+
+ | 338 |
+ HB_197_AD |
+ AD |
+ NA |
+ 5202_CR_A_1368 |
+
+
+ | 339 |
+ HB_199_AD |
+ AD |
+ NA |
+ 5205_VC_A_0166 |
+
+
+ | 340 |
+ HB_200_AD |
+ AD |
+ NA |
+ 5210_VC_A_0905 |
+
+
+ | 341 |
+ HB_205_AD |
+ AD |
+ NA |
+ 5235_VC_A_0419 |
+
+
+ | 342 |
+ HB_208_AD |
+ AD |
+ NA |
+ 5249_VC_A_0422 |
+
+
+ | 343 |
+ HB_209_AD |
+ AD |
+ NA |
+ 5252_VC_A_0907 |
+
+
+ | 344 |
+ HB_211_AD |
+ AD |
+ NA |
+ 5257_VC_A_0169 |
+
+
+ | 345 |
+ HB_216_AD |
+ AD |
+ NA |
+ 5272_VC_A_0425 |
+
+
+ | 346 |
+ HB_219_AD |
+ AD |
+ NA |
+ 5279_CR_A_0147 |
+
+
+ | 347 |
+ HB_221_AD |
+ AD |
+ NA |
+ 5283_VC_A_0145 |
+
+
+ | 348 |
+ HB_222_AD |
+ AD |
+ NA |
+ 5285_VC_A_0141 |
+
+
+ | 349 |
+ HB_224_AD |
+ AD |
+ NA |
+ 5288_VC_A_0428 |
+
+
+ | 350 |
+ HB_230_AD |
+ AD |
+ NA |
+ 5301_VC_A_0174 |
+
+
+ | 351 |
+ HB_231_AD |
+ AD |
+ NA |
+ 5305_VC_A_1384 |
+
+
+ | 352 |
+ HB_232_AD |
+ AD |
+ NA |
+ 5310_CR_A_0176 |
+
+
+ | 353 |
+ HB_234_AD |
+ AD |
+ NA |
+ 5313_PF_A_2618 |
+
+
+ | 354 |
+ HB_236_AD |
+ AD |
+ NA |
+ 5317_PF_A_2624 |
+
+
+ | 355 |
+ HB_238_AD |
+ AD |
+ NA |
+ 5322_CR_A_2632 |
+
+
+ | 356 |
+ HB_240_AD |
+ AD |
+ NA |
+ 5325_VC_A_0137 |
+
+
+ | 357 |
+ HB_244_AD |
+ AD |
+ NA |
+ 5337_VC_A_1387 |
+
+
+ | 358 |
+ HB_245_AD |
+ AD |
+ NA |
+ 5339_VC_A_0181 |
+
+
+ | 359 |
+ HB_250_AD |
+ AD |
+ NA |
+ 5346_VC_A_1393 |
+
+
+ | 360 |
+ HB_251_AD |
+ AD |
+ NA |
+ 5350_VC_A_0184 |
+
+
+ | 361 |
+ HB_252_AD |
+ AD |
+ NA |
+ 5355_VC_A_0133 |
+
+
+ | 362 |
+ HB_253_AD |
+ AD |
+ NA |
+ 5359_CR_A_1395 |
+
+
+ | 363 |
+ HB_258_AD |
+ AD |
+ NA |
+ 5370_PF_A_1400 |
+
+
+ | 364 |
+ HB_259_AD |
+ AD |
+ NA |
+ 5371_PF_A_2636 |
+
+
+ | 365 |
+ HB_260_AD |
+ AD |
+ NA |
+ 5375_VC_A_0188 |
+
+
+ | 366 |
+ HB_263_AD |
+ AD |
+ NA |
+ 5381_VC_A_0022 |
+
+
+ | 367 |
+ HB_265_AD |
+ AD |
+ NA |
+ 5385_VC_A_1402 |
+
+
+ | 368 |
+ HB_267_AD |
+ AD |
+ NA |
+ 5389_VC_A_0928 |
+
+
+ | 369 |
+ HB_268_AD |
+ AD |
+ NA |
+ 5390_CR_A_0151 |
+
+
+ | 370 |
+ HB_273_AD |
+ AD |
+ NA |
+ 5400_PF_A_2645 |
+
+
+ | 371 |
+ HB_274_AD |
+ AD |
+ NA |
+ 5401_VC_A_0931 |
+
+
+ | 372 |
+ HB_275_AD |
+ AD |
+ NA |
+ 5404_PF_A_2648 |
+
+
+ | 373 |
+ HB_276_AD |
+ AD |
+ NA |
+ 5406_VC_A_0933 |
+
+
+ | 374 |
+ HB_277_AD |
+ AD |
+ NA |
+ 5407_PF_A_2651 |
+
+
+ | 375 |
+ HB_280_AD |
+ AD |
+ NA |
+ 5412_VC_A_0935 |
+
+
+ | 376 |
+ HB_281_AD |
+ AD |
+ NA |
+ 5413_PF_A_2657 |
+
+
+ | 377 |
+ HB_283_AD |
+ AD |
+ NA |
+ 5419_VC_A_0937 |
+
+
+ | 378 |
+ HB_284_AD |
+ AD |
+ NA |
+ 5420_VC_A_0939 |
+
+
+ | 379 |
+ HB_285_AD |
+ AD |
+ NA |
+ 5421_CR_A_0432 |
+
+
+ | 380 |
+ HB_286_AD |
+ AD |
+ NA |
+ 5423_PF_A_2660 |
+
+
+ | 381 |
+ HB_288_AD |
+ AD |
+ NA |
+ 5425_PF_A_2666 |
+
+
+ | 382 |
+ HB_289_AD |
+ AD |
+ NA |
+ 5426_VC_A_1405 |
+
+
+ | 383 |
+ HB_290_AD |
+ AD |
+ NA |
+ 5433_VC_A_0434 |
+
+
+ | 384 |
+ HB_296_AD |
+ AD |
+ NA |
+ 5456_PF_A_2675 |
+
+
+ | 385 |
+ HB_299_AD |
+ AD |
+ NA |
+ 5461_VC_A_0192 |
+
+
+ | 386 |
+ HB_302_AD |
+ AD |
+ NA |
+ 5465_PF_A_2678 |
+
+
+ | 387 |
+ HB_303_AD |
+ AD |
+ NA |
+ 5469_VC_A_1417 |
+
+
+ | 388 |
+ HB_305_AD |
+ AD |
+ NA |
+ 5479_PF_A_1421 |
+
+
+ | 389 |
+ HB_306_AD |
+ AD |
+ NA |
+ 5480_VC_A_0437 |
+
+
+ | 390 |
+ HB_307_AD |
+ AD |
+ NA |
+ 5482_VC_A_0028 |
+
+
+ | 391 |
+ HB_308_AD |
+ AD |
+ NA |
+ 5483_VC_A_0941 |
+
+
+ | 392 |
+ HB_309_AD |
+ AD |
+ NA |
+ 5487_CR_A_0441 |
+
+
+ | 393 |
+ HB_310_AD |
+ AD |
+ NA |
+ 5488_CR_A_0194 |
+
+
+ | 394 |
+ HB_312_AD |
+ AD |
+ NA |
+ 5500_VC_A_0198 |
+
+
+ | 395 |
+ HB_313_AD |
+ AD |
+ NA |
+ 5502_PF_A_2684 |
+
+
+ | 396 |
+ HB_315_AD |
+ AD |
+ NA |
+ 5513_PF_A_2687 |
+
+
+ | 397 |
+ HB_316_AD |
+ AD |
+ NA |
+ 5516_PF_A_2690 |
+
+
+ | 398 |
+ HB_317_AD |
+ AD |
+ NA |
+ 5517_PF_A_2693 |
+
+
+ | 399 |
+ HB_318_AD |
+ AD |
+ NA |
+ 5518_CR_A_0030 |
+
+
+ | 400 |
+ HB_319_AD |
+ AD |
+ NA |
+ 5519_CR_A_2695 |
+
+
+ | 401 |
+ HB_320_AD |
+ AD |
+ NA |
+ 5520_PF_A_2699 |
+
+
+ | 402 |
+ HB_322_AD |
+ AD |
+ NA |
+ 5527_VC_A_0945 |
+
+
+ | 403 |
+ HB_325_AD |
+ AD |
+ NA |
+ 5532_PF_A_2702 |
+
+
+ | 404 |
+ HB_328_AD |
+ AD |
+ NA |
+ 5541_PF_A_2705 |
+
+
+ | 405 |
+ HB_330_AD |
+ AD |
+ NA |
+ 5544_VC_A_0201 |
+
+
+ | 406 |
+ HB_334_AD |
+ AD |
+ NA |
+ 5554_VC_A_0452 |
+
+
+ | 407 |
+ HB_335_AD |
+ AD |
+ NA |
+ 5557_VC_A_0950 |
+
+
+ | 408 |
+ HB_337_AD |
+ AD |
+ NA |
+ 5560_VC_A_0204 |
+
+
+ | 409 |
+ HB_342_AD |
+ AD |
+ NA |
+ 5571_PF_A_1430 |
+
+
+ | 410 |
+ HB_345_AD |
+ AD |
+ NA |
+ 5583_PF_A_2708 |
+
+
+ | 411 |
+ HB_347_AD |
+ AD |
+ NA |
+ 5589_PF_A_2714 |
+
+
+ | 412 |
+ HB_349_AD |
+ AD |
+ NA |
+ 5592_PF_A_2717 |
+
+
+ | 413 |
+ HB_352_AD |
+ AD |
+ NA |
+ 5604_VC_A_0037 |
+
+
+ | 414 |
+ HB_353_AD |
+ AD |
+ NA |
+ 5607_PF_A_2723 |
+
+
+ | 415 |
+ HB_356_AD |
+ AD |
+ NA |
+ 5615_VC_A_0041 |
+
+
+ | 416 |
+ HB_357_AD |
+ AD |
+ NA |
+ 5616_CR_A_0127 |
+
+
+ | 417 |
+ HB_358_AD |
+ AD |
+ NA |
+ 5617_CR_A_0456 |
+
+
+ | 418 |
+ HB_359_AD |
+ AD |
+ NA |
+ 5618_CR_A_0044 |
+
+
+ | 419 |
+ HB_362_AD |
+ AD |
+ NA |
+ 5625_CR_A_2495 |
+
+
+ | 420 |
+ HB_363_AD |
+ AD |
+ NA |
+ 5626_CR_A_2498 |
+
+
+ | 421 |
+ HB_364_AD |
+ AD |
+ NA |
+ 5629_CR_A_0390 |
+
+
+ | 422 |
+ HB_369_AD |
+ AD |
+ NA |
+ 5643_VC_A_1143 |
+
+
+ | 423 |
+ HB_373_AD |
+ AD |
+ NA |
+ 5654_VC_A_0047 |
+
+
+ | 424 |
+ HB_375_AD |
+ AD |
+ NA |
+ 5660_CR_A_0462 |
+
+
+ | 425 |
+ HB_376_AD |
+ AD |
+ NA |
+ 5661_VC_A_0464 |
+
+
+ | 426 |
+ HB_377_AD |
+ AD |
+ NA |
+ 5667_VC_A_2509 |
+
+
+ | 427 |
+ HB_378_AD |
+ AD |
+ NA |
+ 5668_VC_A_1438 |
+
+
+ | 428 |
+ HB_383_AD |
+ AD |
+ NA |
+ 5686_CR_A_2728 |
+
+
+ | 429 |
+ HB_386_AD |
+ AD |
+ NA |
+ 5695_VC_A_0953 |
+
+
+ | 430 |
+ HB_389_AD |
+ AD |
+ NA |
+ 5700_VC_A_2514 |
+
+
+ | 431 |
+ HB_391_AD |
+ AD |
+ NA |
+ 5705_CR_A_0474 |
+
+
+ | 432 |
+ HB_392_AD |
+ AD |
+ NA |
+ 5706_VC_A_0476 |
+
+
+ | 433 |
+ HB_394_AD |
+ AD |
+ NA |
+ 5713_VC_A_0479 |
+
+
+ | 434 |
+ HB_397_AD |
+ AD |
+ NA |
+ 5721_CR_A_0210 |
+
+
+ | 435 |
+ HB_404_AD |
+ AD |
+ NA |
+ 5735_CR_A_0489 |
+
+
+ | 436 |
+ HB_406_AD |
+ AD |
+ NA |
+ 5744_CR_A_0960 |
+
+
+ | 437 |
+ HB_409_AD |
+ AD |
+ NA |
+ 5749_CR_A_0159 |
+
+
+ | 438 |
+ HB_410_AD |
+ AD |
+ NA |
+ 5751_CR_A_2518 |
+
+
+ | 439 |
+ HB_411_AD |
+ AD |
+ NA |
+ 5755_CR_A_2731 |
+
+
+ | 440 |
+ HB_413_AD |
+ AD |
+ NA |
+ 5766_VC_A_0214 |
+
+
+ | 441 |
+ HB_419_AD |
+ AD |
+ NA |
+ 5790_VC_A_0217 |
+
+
+ | 442 |
+ HB_420_AD |
+ AD |
+ NA |
+ 5796_CR_A_0964 |
+
+
+ | 443 |
+ HB_428_AD |
+ AD |
+ NA |
+ 5811_CR_A_2524 |
+
+
+ | 444 |
+ HB_429_AD |
+ AD |
+ NA |
+ 5819_CR_A_2527 |
+
+
+ | 445 |
+ HB_430_AD |
+ AD |
+ NA |
+ 5822_CR_A_2530 |
+
+
+ | 446 |
+ HB_434_AD |
+ AD |
+ NA |
+ 5828_CR_A_2533 |
+
+
+ | 447 |
+ HB_435_AD |
+ AD |
+ NA |
+ 5831_CR_A_0222 |
+
+
+ | 448 |
+ HB_437_AD |
+ AD |
+ NA |
+ 5839_CR_A_2539 |
+
+
+ | 449 |
+ HB_438_AD |
+ AD |
+ NA |
+ 5843_CR_A_0227 |
+
+
+ | 450 |
+ HB_439_AD |
+ AD |
+ NA |
+ 5845_CR_A_0230 |
+
+
+ | 451 |
+ HB_441_AD |
+ AD |
+ NA |
+ 5849_CR_A_0233 |
+
+
+ | 452 |
+ HB_442_AD |
+ AD |
+ NA |
+ 5850_CR_A_0495 |
+
+
+ | 453 |
+ HB_445_AD |
+ AD |
+ NA |
+ 5858_CR_A_0969 |
+
+
+ | 454 |
+ HB_448_AD |
+ AD |
+ NA |
+ 5864_CR_A_0974 |
+
+
+ | 455 |
+ HB_451_AD |
+ AD |
+ NA |
+ 5871_CR_A_2542 |
+
+
+ | 456 |
+ HB_454_AD |
+ AD |
+ NA |
+ 5879_CR_A_2545 |
+
+
+ | 457 |
+ HB_455_AD |
+ AD |
+ NA |
+ 5887_CR_A_0976_Bis |
+
+
+ | 458 |
+ HB_459_AD |
+ AD |
+ NA |
+ 5898_CR_A_2548 |
+
+
+ | 459 |
+ HB_460_AD |
+ AD |
+ NA |
+ 5900_VC_A_0237 |
+
+
+ | 460 |
+ HB_461_AD |
+ AD |
+ NA |
+ 5901_CR_A_0239 |
+
+
+ | 461 |
+ HB_469_AD |
+ AD |
+ NA |
+ 5914_CR_A_2554 |
+
+
+ | 462 |
+ HB_471_AD |
+ AD |
+ NA |
+ 5922_VC_A_0246 |
+
+
+ | 463 |
+ HB_473_AD |
+ AD |
+ NA |
+ 5927_CR_A_2560 |
+
+
+ | 464 |
+ HB_474_AD |
+ AD |
+ NA |
+ 5933_VC_A_1071 |
+
+
+ | 465 |
+ HB_477_AD |
+ AD |
+ NA |
+ 5939_CR_A_1151 |
+
+
+ | 466 |
+ HB_479_AD |
+ AD |
+ NA |
+ 5945_VC_A_0983 |
+
+
+ | 467 |
+ HB_484_AD |
+ AD |
+ NA |
+ 5956_CR_A_0123 |
+
+
+ | 468 |
+ HB_489_AD |
+ AD |
+ NA |
+ 5968_VC_A_1075 |
+
+
+ | 469 |
+ HB_491_AD |
+ AD |
+ NA |
+ 5971_CR_A_0119 |
+
+
+ | 470 |
+ HB_492_AD |
+ AD |
+ NA |
+ 5972_VC_A_0251 |
+
+
+ | 471 |
+ HB_494_AD |
+ AD |
+ NA |
+ 5979_CR_A_0115 |
+
+
+ | 472 |
+ HB_498_AD |
+ AD |
+ NA |
+ 5988_VC_A_0503 |
+
+
+ | 473 |
+ HB_502_AD |
+ AD |
+ NA |
+ 5994_PF_A_1605 |
+
+
+ | 474 |
+ HB_503_AD |
+ AD |
+ NA |
+ 5995_CR_A_2563 |
+
+
+ | 475 |
+ HB_510_AD |
+ AD |
+ NA |
+ 6017_CR_A_0048 |
+
+
+ | 476 |
+ HB_514_AD |
+ AD |
+ NA |
+ 6025_VC_A_0506 |
+
+
+ | 477 |
+ HB_517_AD |
+ AD |
+ NA |
+ 6031_VC_A_0258 |
+
+
+ | 478 |
+ HB_520_AD |
+ AD |
+ NA |
+ 6035_VC_A_1621 |
+
+
+ | 479 |
+ HB_523_AD |
+ AD |
+ NA |
+ 6038_VC_A_0261 |
+
+
+ | 480 |
+ HB_524_AD |
+ AD |
+ NA |
+ 6042_VC_A_1156 |
+
+
+ | 481 |
+ HB_525_AD |
+ AD |
+ NA |
+ 6044_VC_A_0264 |
+
+
+ | 482 |
+ HB_531_AD |
+ AD |
+ NA |
+ 6056_CR_A_0999 |
+
+
+ | 483 |
+ HB_533_AD |
+ AD |
+ NA |
+ 6061_PF_A_1650 |
+
+
+ | 484 |
+ HB_534_AD |
+ AD |
+ NA |
+ 6066_VC_A_0270 |
+
+
+ | 485 |
+ HB_535_AD |
+ AD |
+ NA |
+ 6067_PF_A_1452 |
+
+
+ | 486 |
+ HB_536_AD |
+ AD |
+ NA |
+ 6068_VC_A_0273 |
+
+
+ | 487 |
+ HB_545_AD |
+ AD |
+ NA |
+ 6102_CR_A_1661 |
+
+
+ | 488 |
+ HB_546_AD |
+ AD |
+ NA |
+ 6107_CR_A_0055 |
+
+
+ | 489 |
+ HB_550_AD |
+ AD |
+ NA |
+ 6120_VC_A_0058 |
+
+
+ | 490 |
+ HB_552_AD |
+ AD |
+ NA |
+ 6126_VC_A_1675 |
+
+
+ | 491 |
+ HB_553_AD |
+ AD |
+ NA |
+ 6129_PF_A_0274 |
+
+
+ | 492 |
+ HB_554_AD |
+ AD |
+ NA |
+ 6130_VC_A_1678 |
+
+
+ | 493 |
+ HB_555_AD |
+ AD |
+ NA |
+ 6131_CR_A_0510 |
+
+
+ | 494 |
+ HB_556_AD |
+ AD |
+ NA |
+ 6132_CR_A_0513 |
+
+
+ | 495 |
+ HB_558_AD |
+ AD |
+ NA |
+ 6137_VC_A_1681 |
+
+
+ | 496 |
+ HB_564_AD |
+ AD |
+ NA |
+ 6153_VC_A_1465 |
+
+
+ | 497 |
+ HB_565_AD |
+ AD |
+ NA |
+ 6154_VC_A_1468 |
+
+
+ | 498 |
+ HB_566_AD |
+ AD |
+ NA |
+ 6157_VC_A_0062 |
+
+
+ | 499 |
+ HB_568_AD |
+ AD |
+ NA |
+ 6164_CR_A_1005 |
+
+
+ | 500 |
+ HB_571_AD |
+ AD |
+ NA |
+ 6171_CR_A_0065 |
+
+
+ | 501 |
+ HB_573_AD |
+ AD |
+ NA |
+ 6174_VC_A_0068 |
+
+
+ | 502 |
+ HB_576_AD |
+ AD |
+ NA |
+ 6180_CR_A_0281 |
+
+
+ | 503 |
+ HB_583_AD |
+ AD |
+ NA |
+ 6194_VC_A_0071 |
+
+
+ | 504 |
+ HB_585_AD |
+ AD |
+ NA |
+ 6198_VC_A_0073 |
+
+
+ | 505 |
+ HB_590_AD |
+ AD |
+ NA |
+ 6215_VC_A_0518 |
+
+
+ | 506 |
+ HB_591_AD |
+ AD |
+ NA |
+ 6216_VC_A_1476 |
+
+
+ | 507 |
+ HB_592_AD |
+ AD |
+ NA |
+ 6218_CR_A_0522 |
+
+
+ | 508 |
+ HB_594_AD |
+ AD |
+ NA |
+ 6223_VC_A_0288 |
+
+
+ | 509 |
+ HB_596_AD |
+ AD |
+ NA |
+ 6226_CR_A_0076 |
+
+
+ | 510 |
+ HB_597_AD |
+ AD |
+ NA |
+ 6227_VC_A_0080 |
+
+
+ | 511 |
+ HB_598_AD |
+ AD |
+ NA |
+ 6231_VC_A_1479 |
+
+
+ | 512 |
+ HB_605_AD |
+ AD |
+ NA |
+ 6261_VC_A_0084 |
+
+
+ | 513 |
+ HB_608_AD |
+ AD |
+ NA |
+ 6268_CR_A_0525 |
+
+
+ | 514 |
+ HB_611_AD |
+ AD |
+ NA |
+ 6279_VC_A_0089 |
+
+
+ | 515 |
+ HB_612_AD |
+ AD |
+ NA |
+ 6280_VC_A_0091 |
+
+
+ | 516 |
+ HB_613_AD |
+ AD |
+ NA |
+ 6281_CR_A_0528 |
+
+
+ | 517 |
+ HB_621_AD |
+ AD |
+ NA |
+ 6308_VC_A_1503 |
+
+
+ | 518 |
+ HB_623_AD |
+ AD |
+ NA |
+ 6311_CR_A_0531 |
+
+
+ | 519 |
+ HB_624_AD |
+ AD |
+ NA |
+ 6312_CR_A_0534 |
+
+
+ | 520 |
+ HB_630_AD |
+ AD |
+ NA |
+ 6324_PF_A_1514 |
+
+
+ | 521 |
+ HB_633_AD |
+ AD |
+ NA |
+ 6332_VC_A_1518 |
+
+
+ | 522 |
+ HB_634_AD |
+ AD |
+ NA |
+ 6335_VC_A_0536 |
+
+
+ | 523 |
+ HB_635_AD |
+ AD |
+ NA |
+ 6336_CR_A_0290 |
+
+
+ | 524 |
+ HB_636_AD |
+ AD |
+ NA |
+ 6338_VC_A_0539 |
+
+
+ | 525 |
+ HB_642_AD |
+ AD |
+ NA |
+ 6358_VC_A_0545 |
+
+
+ | 526 |
+ HB_652_AD |
+ AD |
+ NA |
+ 6387_VC_A_0093 |
+
+
+ | 527 |
+ HB_657_AD |
+ AD |
+ NA |
+ 6394_VC_A_0551 |
+
+
+ | 528 |
+ HB_664_AD |
+ AD |
+ NA |
+ 6416_VC_A_1095 |
+
+
+ | 529 |
+ HB_666_AD |
+ AD |
+ NA |
+ 6422_CR_A_0555 |
+
+
+ | 530 |
+ HB_669_AD |
+ AD |
+ NA |
+ 6431_VC_A_0294 |
+
+
+ | 531 |
+ HB_674_AD |
+ AD |
+ NA |
+ 6449_VC_A_1183 |
+
+
+ | 532 |
+ HB_680_AD |
+ AD |
+ NA |
+ 6458_CR_A_2570 |
+
+
+ | 533 |
+ HB_685_AD |
+ AD |
+ NA |
+ 6481_VC_A_0560 |
+
+
+ | 534 |
+ HB_690_AD |
+ AD |
+ NA |
+ 6489_CR_A_0100 |
+
+
+ | 535 |
+ HB_696_AD |
+ AD |
+ NA |
+ 6511_VC_A_1119 |
+
+
+ | 536 |
+ HB_698_AD |
+ AD |
+ NA |
+ 6515_CR_A_0564 |
+
+
+ | 537 |
+ HB_699_AD |
+ AD |
+ NA |
+ 6518_VC_A_0103 |
+
+
+ | 538 |
+ HB_703_AD |
+ AD |
+ NA |
+ 6523_VC_A_0107 |
+
+
+ | 539 |
+ HB_704_AD |
+ AD |
+ NA |
+ 6530_VC_A_0112 |
+
+
+ | 540 |
+ HB_706_AD |
+ AD |
+ NA |
+ 6534_VC_A_0306 |
+
+
+ | 541 |
+ HB_712_AD |
+ AD |
+ NA |
+ 6546_PF_A_1194 |
+
+
+ | 542 |
+ HB_713_AD |
+ AD |
+ NA |
+ 6548_PF_A_1541 |
+
+
+ | 543 |
+ HB_715_AD |
+ AD |
+ NA |
+ 6550_VC_A_1201 |
+
+
+ | 544 |
+ HB_718_AD |
+ AD |
+ NA |
+ 6554_PF_A_1203 |
+
+
+ | 545 |
+ HB_720_AD |
+ AD |
+ NA |
+ 6559_PF_A_2287 |
+
+
+ | 546 |
+ HB_722_AD |
+ AD |
+ NA |
+ 6561_CR_A_2582 |
+
+
+ | 547 |
+ HB_723_AD |
+ AD |
+ NA |
+ 6562_PF_A_2290 |
+
+
+ | 548 |
+ HB_724_AD |
+ AD |
+ NA |
+ 6564_CR_A_2585 |
+
+
+ | 549 |
+ HB_727_AD |
+ AD |
+ NA |
+ 6575_CR_A_2298 |
+
+
+ | 550 |
+ HB_728_AD |
+ AD |
+ NA |
+ 6577_PF_A_2299 |
+
+
+ | 551 |
+ HB_729_AD |
+ AD |
+ NA |
+ 6578_PF_A_2302 |
+
+
+ | 552 |
+ HB_731_AD |
+ AD |
+ NA |
+ 6582_VC_A_1207 |
+
+
+ | 553 |
+ HB_733_AD |
+ AD |
+ NA |
+ 6585_VC_A_1210 |
+
+
+ | 554 |
+ HB_736_AD |
+ AD |
+ NA |
+ 6590_PF_A_1215 |
+
+
+ | 555 |
+ HB_743_AD |
+ AD |
+ NA |
+ 6603_PF_A_1448 |
+
+
+ | 556 |
+ HB_745_AD |
+ AD |
+ NA |
+ 6610_PF_A_1227 |
+
+
+ | 557 |
+ HB_746_AD |
+ AD |
+ NA |
+ 6612_PF_A_2308 |
+
+
+ | 558 |
+ HB_749_AD |
+ AD |
+ NA |
+ 6617_VC_A_2587 |
+
+
+ | 559 |
+ HB_751_AD |
+ AD |
+ NA |
+ 6629_VC_A_2330 |
+
+
+ | 560 |
+ HB_752_AD |
+ AD |
+ NA |
+ 6630_VC_A_2590 |
+
+
+ | 561 |
+ HB_753_AD |
+ AD |
+ NA |
+ 6632_PF_A_2332 |
+
+
+ | 562 |
+ HB_754_AD |
+ AD |
+ NA |
+ 6637_VC_A_2596 |
+
+
+ | 563 |
+ HB_755_AD |
+ AD |
+ NA |
+ 6638_VC_A_2599 |
+
+
+ | 564 |
+ HB_756_AD |
+ AD |
+ NA |
+ 6639_VC_A_2336 |
+
+
+ | 565 |
+ HB_757_AD |
+ AD |
+ NA |
+ 6641_PF_A_2338 |
+
+
+ | 566 |
+ HB_763_AD |
+ AD |
+ NA |
+ 6654_VC_A_1237 |
+
+
+ | 567 |
+ HB_773_AD |
+ AD |
+ NA |
+ 6681_VC_A_1252 |
+
+
+ | 568 |
+ HB_775_AD |
+ AD |
+ NA |
+ 6693_VC_A_2348 |
+
+
+ | 569 |
+ HB_776_AD |
+ AD |
+ NA |
+ 6694_VC_A_2351 |
+
+
+ | 570 |
+ HB_777_AD |
+ AD |
+ NA |
+ 6695_PF_A_2353 |
+
+
+ | 571 |
+ HB_779_AD |
+ AD |
+ NA |
+ 6699_PF_A_2359 |
+
+
+ | 572 |
+ HB_781_AD |
+ AD |
+ NA |
+ 6708_VC_A_2366 |
+
+
+ | 573 |
+ HB_782_AD |
+ AD |
+ NA |
+ 6776_PF_A_2607 |
+
+
+ | 574 |
+ HB_783_AD |
+ AD |
+ NA |
+ 6778_PF_A_2368 |
+
+
+ | 575 |
+ HB_784_AD |
+ AD |
+ NA |
+ 6779_PF_A_2371 |
+
+
+ | 576 |
+ HB_785_AD |
+ AD |
+ NA |
+ 6780_PF_A_2374 |
+
+
+ | 577 |
+ HB_786_AD |
+ AD |
+ NA |
+ 6782_PF_A_2377 |
+
+
+ | 578 |
+ HB_787_AD |
+ AD |
+ NA |
+ 6784_PF_A_2380 |
+
+
+ | 579 |
+ HB_788_AD |
+ AD |
+ NA |
+ 6785_CR_A_2385 |
+
+
+ | 580 |
+ HB_789_AD |
+ AD |
+ NA |
+ 6787_CR_A_2388 |
+
+
+ | 581 |
+ HB_791_AD |
+ AD |
+ NA |
+ 6790_PF_A_2392 |
+
+
+ | 582 |
+ HB_792_AD |
+ AD |
+ NA |
+ 6791_PF_A_2395 |
+
+
+ | 583 |
+ HB_793_AD |
+ AD |
+ NA |
+ 6793_PF_A_2398 |
+
+
+ | 584 |
+ HB_794_AD |
+ AD |
+ NA |
+ 6794_PF_A_2401 |
+
+
+ | 585 |
+ HB_795_AD |
+ AD |
+ NA |
+ 6797_PF_A_2404 |
+
+
+ | 586 |
+ HB_796_AD |
+ AD |
+ NA |
+ 6798_PF_A_2407 |
+
+
+ | 587 |
+ HB_797_AD |
+ AD |
+ NA |
+ 6799_VC_A_2411 |
+
+
+ | 588 |
+ HB_798_AD |
+ AD |
+ NA |
+ 6801_VC_A_2414 |
+
+
+ | 589 |
+ HB_799_AD |
+ AD |
+ NA |
+ 6803_VC_A_2417 |
+
+
+ | 590 |
+ HB_801_AD |
+ AD |
+ NA |
+ 6809_PF_A_2422 |
+
+
+ | 591 |
+ HB_803_AD |
+ AD |
+ NA |
+ 6818_CR_A_2430 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hbtrc_mlvc_n_0611/notes.rtf b/general/datasets/Hbtrc_mlvc_n_0611/notes.rtf
new file mode 100644
index 0000000..ff90e34
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_n_0611/notes.rtf
@@ -0,0 +1,6 @@
+Species: Human
+Tissue: Brain visual cortex,Brain cerebellum,Brain prefrontal cortex
+Disease: Neurological Disease
+Investigator: Francine Benes/ Eric Schadt
+Institution: Harvard Brain Tissue Resource Center/ Merck Research Laboratories
+Approximate Number Subjects: 803
diff --git a/general/datasets/Hbtrc_mlvc_n_0611/summary.rtf b/general/datasets/Hbtrc_mlvc_n_0611/summary.rtf
new file mode 100644
index 0000000..5cde3bf
--- /dev/null
+++ b/general/datasets/Hbtrc_mlvc_n_0611/summary.rtf
@@ -0,0 +1 @@
+This study aims at identifying functional variation in the human genome (especially as it pertains to brain expressed RNAs) and elucidate its relationship to disease and drug response. The ~800 individuals in this dataset are composed of approximately 400 Alzheimers disease (AD) cases, 230 Huntington's Disease (HD) and 170 controls (N) matched for age, gender, and post mortem interval (PMI). The tissue specimens for this study were provided by Harvard Brain Tissue Resource Center (HBTRC). Three brain regions (cerebellum, visual cortex, and dorsolateral prefrontal cortex) from the same individuals were profiled on a custom-made Agilent 44K microarray of 39,280 DNA probes uniquely targeting 37,585 known and predicted genes, including splice variants, miRNAs and high-confidence non-coding RNA sequences. The individuals were genotyped on two different platforms, the Illumina HumanHap650Y array and a custom Perlegen 300K array (a focused panel for detection of singleton SNPs). Clinical outcomes available include age at onset, age at death, Braak scores (AD), Vonsattel scores (HD), Regional brain enlargement/atrophy.
diff --git a/general/datasets/Hc_m2_0606_m/acknowledgment.rtf b/general/datasets/Hc_m2_0606_m/acknowledgment.rtf
new file mode 100644
index 0000000..1481cd1
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_m/acknowledgment.rtf
@@ -0,0 +1,50 @@
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
diff --git a/general/datasets/Hc_m2_0606_m/cases.rtf b/general/datasets/Hc_m2_0606_m/cases.rtf
new file mode 100644
index 0000000..15e6cda
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_m/cases.rtf
@@ -0,0 +1,56 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 27 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondrial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 strains are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2_0606_m/citation.rtf b/general/datasets/Hc_m2_0606_m/citation.rtf
new file mode 100644
index 0000000..61a0788
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_m/citation.rtf
@@ -0,0 +1 @@
+Please cite: Overall RW, Kempermann G, Peirce J, Lu L, Goldowitz D, Gage FH, Goodwin S, Smit AB, Airey DC, Rosen GD, Schalkwyk LC, Sutter TR, Nowakowski RS, Whatley S, Williams RW (2009) Genetics of the hippocampal transcriptome in mice: a systematic survey and online neurogenomic resource. Front. Neurogen. 1:3 Full Text HTML doi:10.3389/neuro.15.003.2009
diff --git a/general/datasets/Hc_m2_0606_m/contributors.rtf b/general/datasets/Hc_m2_0606_m/contributors.rtf
new file mode 100644
index 0000000..4108279
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_m/contributors.rtf
@@ -0,0 +1,46 @@
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
diff --git a/general/datasets/Hc_m2_0606_m/experiment-design.rtf b/general/datasets/Hc_m2_0606_m/experiment-design.rtf
new file mode 100644
index 0000000..356f1d2
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_m/experiment-design.rtf
@@ -0,0 +1 @@
+Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2_0606_m/notes.rtf b/general/datasets/Hc_m2_0606_m/notes.rtf
new file mode 100644
index 0000000..9c11719
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_m/notes.rtf
@@ -0,0 +1,12 @@
+This study includes the following datasets:
+
+
+ - Hippocampus Consortium M430v2 CXB (Oct05) MAS5
+ - Hippocampus Consortium M430v2 CXB (Oct05) RMA
+ - Hippocampus Consortium M430v2 CXB (Oct05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) RMA
+ - Hippocampus Consortium M430v2 (Jun06) RMA
+ - Hippocampus Consortium M430v2 (Jun06) MAS5
+ - Hippocampus Consortium M430v2 (Jun06) PDNN
+
diff --git a/general/datasets/Hc_m2_0606_m/platform.rtf b/general/datasets/Hc_m2_0606_m/platform.rtf
new file mode 100644
index 0000000..6c99bee
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_m/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2_0606_m/processing.rtf b/general/datasets/Hc_m2_0606_m/processing.rtf
new file mode 100644
index 0000000..3698a7b
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_m/processing.rtf
@@ -0,0 +1,37 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very sensitive to the transformation method that is used. Using the PDNN transform, the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For example, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one would include the sample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the probe level (CEL) data after step 5 below. DataDesk allows the rapid detection of subsets of probes that are particularly sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - We performed a quantile normalization of the log base 2 values for all arrays using the same initial steps used by the RMA transform.
+ - We computed the Z scores for each cell value.
+ - We multiplied all Z scores by 2.
+ - We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level (probe brightness level) corresponds approximately to a 1 unit difference.
+ - Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data from the CHP file: The expression values were generated using PDNN. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1 unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2_0606_m/summary.rtf b/general/datasets/Hc_m2_0606_m/summary.rtf
new file mode 100644
index 0000000..1e86e54
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_m/summary.rtf
@@ -0,0 +1,3 @@
+MOST HIGHLY RECOMMENDED DATA SET (Overall et al., 2009): The Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of 99 genetically diverse strains of mice including 67 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a diverse set of common inbred strains, and two reciprocal F1 hybrids.
+
+The hippocampus is an important and intriguing part of the forebrain that is crucial in memory formation and retrieval, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section.
diff --git a/general/datasets/Hc_m2_0606_m/tissue.rtf b/general/datasets/Hc_m2_0606_m/tissue.rtf
new file mode 100644
index 0000000..bcea7b0
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_m/tissue.rtf
@@ -0,0 +1,3721 @@
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thank Muriel Davisson for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below). All animals were sacrifice between 9 AM and 5 PM during the light phase.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+RNA Extraction: In brief, we used the RNA STAT-60 protocol (TEL-TEST "B" Bulletin No. 1), steps 5.1A (homogenization of tissue), 5.2 (RNA extraction), 5.3 (RNA precipitation), and 5.4 (RNA wash). In Step 5.4 we stopped after adding 75% ethanol (1 ml per 1 ml RNA STAT-60) and stored the mix at -80°C until further use. Before RNA labeling we thawed samples and proceeded with the remainder of Step 5.4; pelleting, drying, and redissolving the pellet in RNase-free water.
+
+We finally purify RNA by using Na4OAc before running arrays. Here is the detailed method:
+
+Final RNA purification protocol
+
+
+ - Add 1/10th volume of 3M Na4OAc , pH 5.2. If the sample was eluted with 100 µl nuclease-free water as suggested, this will be 10 µl of 3M Na4OAc.
+ - Add 2.5 volumes of 100% ethanol (250 µl if the RNA was eluted in100 µl). Mix well and incubate at –20°C for 2 hrs.
+ - Centrifuge at speed of 13,000 rpm for 20 min at 4°C. Carefully remove and discard the supernatant.
+ - Wash the pellet with 800 µl 75% cold ethanol, centrifuge at speed of 8,600 rpm for 5 min, and remove the 75% ethanol. Wash again.
+ - To remove the last traces of ethanol, quickly respin the tube, and aspirate any residual fluid.
+ - Air dry the pellet.
+ - Resuspend pellet in nuclease-free water.
+
+
+
+
+5. PROTOCOL: RNA/mRNA isolation by the RNA STAT-60 method includes the following steps:
+1. Homogenization RNA STAT-60TM (1 ml per 50-100 mg tissue, or 5-10 x 10-6 cells)
+2. RNA Extraction 1 vol. of homogenate +0.2 vol. of chloroform
+3. RNA Precipitation 0.5 vol. of isopropanol
+4. RNA Wash 75% ethanol
+
+Unless stated otherwise the procedure is carried out at room temperature.
+
+5.1 HOMOGENIZATION
+
+A. TISSUES: Homogenize tissues samples in the RNA STAT-60(1 ml/50-100mg tissue) in a glass-Teflon or Polytron homogenizer. Sample volume should not exceed 10% of the volume of the RNA STAT-60 used for homogenization.
+
+B. CELLS: Cells grown in mono layer are lysed directly in a culture dish by adding the RNA STAT-60TM (1 ml/3.5 cm petri dish) and passing the cell lysate several times through a pipette. Cells grown in suspension are sediment then lysed in the RNA STAT-60TM (1 ml per 5-10 x 106 cells) by repetitive pipetting. Washing calls before addition of the RNA STAT-60TM should be avoided as this increases the possibility of mRNA degradation.
+
+5.2 RNA EXTRACTION: Following homogenization, store the homogenate for 5 min at room temp to permit the complete dissociation of nucleoprotein complexes. Next, add 0.2 ml of chloroform per 1 ml of the RNA STAT-60, cover the sample tightly, shake vigorously for 15 seconds and let it stay at room temperature for 2-3minutes. Centrifuge the homogenate at 12,000g (max) for 15 minutes at 4°C. Following centrifugation, the homogenate separates into two phases: a lower red phenol chloroform phase and the colorless upper aqueous phase. RNA remains exclusively in the aqueous phase whereas DNA and proteins are in the interferes and organic phase. The volume of the aqueous phase is about 60% of the volume of RNA STAT-60 used for homogenization.
+
+5.3 RNA PRECIPITATION: Transfer the aqueous phase to a fresh tube and mix with isopropanol. Add 0.5 ml of isopropanol per 1 ml of the RNA STAT-60 used for homogenization. Store samples at room temp for 5-10 minutes and centrifuge at 12,000g (max.) for 10 min at 4°C. RNA precipitate (often visible before centrifugation) forms a white pellet at the bottom of the tube.
+
+5.4 RNA WASH: Remove supernatant and wash the RNA pellet once with 75% ethanol by vortexing and subsequent centrifugation at 7,500g (max.) for 5 min at 4°C. Add at least 1 ml of 75% ethanol per 1 ml of the RNA STAT-60 used for the initial homogenization.
+
+At the end of the procedure, dry the RNA pellet briefly by air-drying or in a vacuum (5-10 min.). It is important not to let the RNA pellet dry completely as it will greatly decrease its solubility. Do not use the Speed-Vac for drying. Dissolve the RNA pellet in water or in 1 mm EDTA, pH 7, or 0.5% SDS solution. Vortex or pass the pellet a few times through a pipette tip. An incubation for 10-15 minutes at 55-60oC may be required to dissolve RNA samples. Diethylpyrocarbonate (DEPC) treated RNase-free solutions1 should be used for solubilization of RNA.
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80°C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: Our goal was to obtain a male sample pool and female sample pool from each isogenic group. While almost all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. All but 5 of 99 strains (BXD55, BXD86, BXD94, BALB/cByJ, and CAST/EiJ) are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquots R1291H3 and R1291H4).
+
+
+
+Sex Balance: Based on the expression of Xist, probe set 1427262_at, DBA/2J and KK/HlJ are represented only by female samples, BXD55, and BALB/cByJ are only represented by a single male sample, BXD74 is represented by two male samples, and BXD86, BXD94, and CAST/EiJ are possibly mixed sex samples. One of the BXD9 samples, array R1523, may be a mixed sex sample pool because the expression of Xist is intermediate.
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays. Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4°C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+COMPARISON with December 2005 Data Set: Both BXD14 arrays in the Dec05 data set were found to actually be from BXD23 cases. This error of strain identification has been corrected in the present data set. Four arrays in the Dec05 data set have been deleted because we judged them to be of poor quality (strain_sex_sample_firstreaction_group):
+
+
+ - BXD21_F_1_1_G1
+ - BXD23_M_1_1_G7
+ - BXD36_M_1_1_G2
+ - BXD36_F_1_1_G3
+
+
+In the Dec05 data set there are a total of 1986 transcripts with QTLs that have LRS scores above 50, whereas in the corrected June06 data sets there are a total of 2074 transcripts with QTLs above 50.
+
+Data Table 1:
+
+This table lists all arrays by file order (Index), tube/sample ID, age, sex, batch, and numbers of animals in each sample pool (pool size). The next columns (RMA outlier, scale factor, background average, present, absent, marginal, AFFY-b-ActinMur(3'/5'), AFFY-GapdhMur(3'/5')) are all Affymetrix QC data. Finally, source lists the source colony of the animals. (Final version, fully corrected, by Arthur Centeno, October 2008)
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool size |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 2 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 3 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M technical duplicate of above |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 4 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 5 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 2.579 |
+ 58.49 |
+ 0.506 |
+ 0.475 |
+ 0.019 |
+ 2.49 |
+ 1.21 |
+ UTM RW |
+
+
+ | 6 |
+ R1551H1 |
+ D2B6F1 |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.62 |
+ 53.76 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 1.37 |
+ 0.76 |
+ UTM RW |
+
+
+ | 7 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
+ 3.058 |
+ 51.87 |
+ 0.477 |
+ 0.503 |
+ 0.02 |
+ 1.67 |
+ 0.76 |
+ UTM RW |
+
+
+ | 8 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
+ 3.341 |
+ 49.26 |
+ 0.527 |
+ 0.456 |
+ 0.018 |
+ 1.14 |
+ 1.45 |
+ UTM RW |
+
+
+ | 9 |
+ R1449H2 |
+ C57BL/6J |
+ 71 |
+ M |
+ 5 |
+ 3 |
+ 0.09 |
+ 3.592 |
+ 44.32 |
+ 0.47 |
+ 0.51 |
+ 0.02 |
+ 1.68 |
+ 0.77 |
+ UTM DG |
+
+
+ | 10 |
+ R1290H2 |
+ DBA/2J |
+ 63 |
+ F |
+ 7 |
+ 2 |
+ 0.04 |
+ 2.576 |
+ 59.6 |
+ 0.513 |
+ 0.468 |
+ 0.018 |
+ 1.3 |
+ 0.78 |
+ JAX |
+
+
+ | 11 |
+ R1468H1 |
+ DBA/2J |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.03 |
+ 2.929 |
+ 53.8 |
+ 0.515 |
+ 0.465 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 12 |
+ R1507H1 |
+ BXD1 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.056 |
+ 60.17 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.15 |
+ 0.76 |
+ Glenn |
+
+
+ | 13 |
+ R1542H1 |
+ BXD1 |
+ 59 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.792 |
+ 80.56 |
+ 0.492 |
+ 0.489 |
+ 0.018 |
+ 1.57 |
+ 0.79 |
+ Glenn |
+
+
+ | 14 |
+ R1520H1 |
+ BXD2 |
+ 56 |
+ F |
+ 4 |
+ 4 |
+ 0.09 |
+ 1.715 |
+ 71.62 |
+ 0.515 |
+ 0.467 |
+ 0.018 |
+ 2.36 |
+ 1.6 |
+ Glenn |
+
+
+ | 15 |
+ R1516H1 |
+ BXD2 |
+ 61 |
+ M |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.231 |
+ 64.86 |
+ 0.508 |
+ 0.474 |
+ 0.019 |
+ 1.3 |
+ 1.53 |
+ Glenn |
+
+
+ | 16 |
+ R1593H2 |
+ BXD5 |
+ 60 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 1.913 |
+ 59.96 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.98 |
+ 1.44 |
+ Glenn |
+
+
+ | 17 |
+ R1692H1 |
+ BXD5 |
+ 60 |
+ M |
+ 3 |
+ 2 |
+ 0.07 |
+ 3.764 |
+ 72.74 |
+ 0.465 |
+ 0.516 |
+ 0.02 |
+ 1.15 |
+ 0.74 |
+ Glenn |
+
+
+ | 18 |
+ R1539H2 |
+ BXD6 |
+ 59 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 2.488 |
+ 54.97 |
+ 0.518 |
+ 0.463 |
+ 0.018 |
+ 1.08 |
+ 1.33 |
+ Glenn |
+
+
+ | 19 |
+ R1538H1 |
+ BXD6 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.01 |
+ 2.585 |
+ 50.27 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 1.46 |
+ 0.79 |
+ Glenn |
+
+
+ | 20 |
+ R1518H1 |
+ BXD8 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 2.92 |
+ 54.84 |
+ 0.515 |
+ 0.465 |
+ 0.02 |
+ 1.32 |
+ 1.24 |
+ Glenn |
+
+
+ | 21 |
+ R1548H1 |
+ BXD8 |
+ 59 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.132 |
+ 59.37 |
+ 0.504 |
+ 0.477 |
+ 0.019 |
+ 2.16 |
+ 1.54 |
+ Glenn |
+
+
+ | 22 |
+ R1350H2 |
+ BXD9 |
+ 86 |
+ F |
+ 1 |
+ 3 |
+ 0.05 |
+ 2.771 |
+ 60.62 |
+ 0.5 |
+ 0.482 |
+ 0.018 |
+ 1.01 |
+ 1.28 |
+ UMemphis |
+
+
+ | 23 |
+ R1523H3 |
+ BXD9 |
+ 57 |
+ MF (mixed) |
+ 7 |
+ 3 |
+ 0.14 |
+ 3.9 |
+ 78.36 |
+ 0.435 |
+ 0.547 |
+ 0.018 |
+ 1.36 |
+ 0.77 |
+ UTM RW |
+
+
+ | 24 |
+ R1531H1 |
+ BXD11 |
+ 56 |
+ F |
+ 6 |
+ 3 |
+ 0.06 |
+ 2.229 |
+ 56.36 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 2.23 |
+ 1.02 |
+ Glenn |
+
+
+ | 25 |
+ R1367H1 |
+ BXD11 |
+ 56 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.11 |
+ 78.78 |
+ 0.503 |
+ 0.477 |
+ 0.02 |
+ 1.07 |
+ 1.27 |
+ Glenn |
+
+
+ | 26 |
+ R1530H1 |
+ BXD12 |
+ 58 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 3.227 |
+ 53.77 |
+ 0.505 |
+ 0.477 |
+ 0.018 |
+ 0.95 |
+ 1.4 |
+ Glenn |
+
+
+ | 27 |
+ R2674H1 |
+ BXD12 |
+ 59 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.924 |
+ 83.44 |
+ 0.519 |
+ 0.464 |
+ 0.018 |
+ 1.21 |
+ 0.78 |
+ Glenn |
+
+
+ | 28 |
+ R1529H1 |
+ BXD13 |
+ 58 |
+ F |
+ 6 |
+ 3 |
+ 0.05 |
+ 2.55 |
+ 59.05 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 2 |
+ 1.54 |
+ Glenn |
+
+
+ | 29 |
+ R1662H2 |
+ BXD13 |
+ 60 |
+ M |
+ 1 |
+ 3 |
+ 0.03 |
+ 4.603 |
+ 45.81 |
+ 0.509 |
+ 0.472 |
+ 0.019 |
+ 1.3 |
+ 0.82 |
+ Glenn |
+
+
+ | 30 |
+ R1304H2 |
+ BXD14 |
+ 72 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.946 |
+ 61.87 |
+ 0.484 |
+ 0.498 |
+ 0.018 |
+ 1.22 |
+ 0.77 |
+ UTM RW |
+
+
+ | 31 |
+ R1278H2 |
+ BXD14 |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.06 |
+ 4.75 |
+ 67.52 |
+ 0.449 |
+ 0.532 |
+ 0.019 |
+ 1.1 |
+ 0.73 |
+ UTM RW |
+
+
+ | 32 |
+ R1524H1 |
+ BXD15 |
+ 60 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.961 |
+ 50.93 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 1.74 |
+ 0.91 |
+ Glenn |
+
+
+ | 33 |
+ R1515H1 |
+ BXD15 |
+ 61 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.316 |
+ 57.05 |
+ 0.503 |
+ 0.478 |
+ 0.019 |
+ 1.32 |
+ 1.21 |
+ Glenn |
+
+
+ | 34 |
+ R1661H1 |
+ BXD16 |
+ 61 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.778 |
+ 59.81 |
+ 0.516 |
+ 0.466 |
+ 0.019 |
+ 1.39 |
+ 1.2 |
+ Glenn |
+
+
+ | 35 |
+ R1594H1 |
+ BXD16 |
+ 61 |
+ M |
+ 4 |
+ 3 |
+ 0.03 |
+ 2.634 |
+ 53.66 |
+ 0.504 |
+ 0.478 |
+ 0.018 |
+ 1.96 |
+ 1.51 |
+ Glenn |
+
+
+ | 36 |
+ R2666H1 |
+ BXD19 |
+ 60 |
+ F |
+ 7 |
+ 3 |
+ 0.02 |
+ 2.498 |
+ 76.2 |
+ 0.495 |
+ 0.486 |
+ 0.019 |
+ 1.41 |
+ 0.77 |
+ Glenn |
+
+
+ | 37 |
+ R1471H1 |
+ BXD19 |
+ 157 |
+ M |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.165 |
+ 43.34 |
+ 0.519 |
+ 0.462 |
+ 0.018 |
+ 1.01 |
+ 1.29 |
+ UTM JB |
+
+
+ | 38 |
+ R1573H1 |
+ BXD20 |
+ 59 |
+ F |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.749 |
+ 52.7 |
+ 0.513 |
+ 0.469 |
+ 0.018 |
+ 1.01 |
+ 1.27 |
+ Glenn |
+
+
+ | 39 |
+ R2507H1 |
+ BXD20 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.06 |
+ 3.568 |
+ 57 |
+ 0.472 |
+ 0.508 |
+ 0.02 |
+ 1.29 |
+ 0.76 |
+ Glenn |
+
+
+ | 40 |
+ R2668H1 |
+ BXD21 |
+ 60 |
+ M |
+ 7 |
+ 4 |
+ 0.07 |
+ 2.605 |
+ 44.9 |
+ 0.535 |
+ 0.449 |
+ 0.017 |
+ 1.54 |
+ 0.76 |
+ Glenn |
+
+
+ | 41 |
+ R1337H2 |
+ BXD21 |
+ 102 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.673 |
+ 58.05 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.4 |
+ 0.76 |
+ UAB |
+
+
+ | 42 |
+ R1848H3 |
+ BXD22 |
+ 196 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.943 |
+ 51.7 |
+ 0.494 |
+ 0.485 |
+ 0.021 |
+ 2.2 |
+ 0.78 |
+ UAB |
+
+
+ | 43 |
+ R1525H1 |
+ BXD22 |
+ 59 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.248 |
+ 55.76 |
+ 0.548 |
+ 0.433 |
+ 0.018 |
+ 1.26 |
+ 0.74 |
+ Glenn |
+
+
+ | 44 |
+ R1280H2 |
+ BXD23 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.187 |
+ 54.63 |
+ 0.458 |
+ 0.523 |
+ 0.019 |
+ 0.96 |
+ 1.2 |
+ UTM RW |
+
+
+ | 45 |
+ R1537H1 |
+ BXD23 |
+ 58 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.719 |
+ 67.54 |
+ 0.468 |
+ 0.513 |
+ 0.019 |
+ 1.51 |
+ 0.96 |
+ Glenn |
+
+
+ | 46 |
+ R1343H2 |
+ BXD24 |
+ 71 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.083 |
+ 65.07 |
+ 0.506 |
+ 0.474 |
+ 0.019 |
+ 1.46 |
+ 0.75 |
+ UMemphis |
+
+
+ | 47 |
+ R1517H1 |
+ BXD24 |
+ 57 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.471 |
+ 53.66 |
+ 0.504 |
+ 0.476 |
+ 0.019 |
+ 1.28 |
+ 0.78 |
+ Glenn |
+
+
+ | 48 |
+ R1366H1 |
+ BXD27 |
+ 60 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.26 |
+ 48.46 |
+ 0.518 |
+ 0.463 |
+ 0.019 |
+ 1.29 |
+ 0.77 |
+ Glenn |
+
+
+ | 49 |
+ R1849H1 |
+ BXD27 |
+ 70 |
+ M |
+ 5 |
+ 3 |
+ 0.06 |
+ 8.801 |
+ 38.34 |
+ 0.468 |
+ 0.512 |
+ 0.019 |
+ 2.42 |
+ 1.08 |
+ UAB |
+
+
+ | 50 |
+ R1353H1 |
+ BXD28 |
+ 79 |
+ F |
+ 3 |
+ 4 |
+ 0.01 |
+ 3.22 |
+ 76.22 |
+ 0.48 |
+ 0.5 |
+ 0.02 |
+ 1.33 |
+ 0.78 |
+ UMemphis |
+
+
+ | 51 |
+ R2332H1 |
+ BXD28 |
+ 60 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 3.217 |
+ 63.68 |
+ 0.491 |
+ 0.49 |
+ 0.019 |
+ 1.37 |
+ 0.79 |
+ Glenn |
+
+
+ | 52 |
+ R1532H1 |
+ BXD29 |
+ 57 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.122 |
+ 59.18 |
+ 0.524 |
+ 0.456 |
+ 0.019 |
+ 1.17 |
+ 0.76 |
+ Glenn |
+
+
+ | 53 |
+ R1356H1 |
+ BXD29 |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.01 |
+ 4.033 |
+ 47.67 |
+ 0.52 |
+ 0.463 |
+ 0.017 |
+ 1.17 |
+ 0.78 |
+ UMemphis |
+
+
+ | 54 |
+ R1240H2 |
+ BXD31 |
+ 61 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.335 |
+ 65.17 |
+ 0.507 |
+ 0.474 |
+ 0.019 |
+ 1.31 |
+ 0.78 |
+ UTM RW |
+
+
+ | 55 |
+ R1526H2 |
+ BXD31 |
+ 57 |
+ F |
+ 7 |
+ 4 |
+ 0.1 |
+ 7.267 |
+ 89.54 |
+ 0.435 |
+ 0.547 |
+ 0.017 |
+ 1.35 |
+ 0.78 |
+ UTM RW |
+
+
+ | 56 |
+ R2675H1 |
+ BXD32 |
+ 57 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 2.268 |
+ 78.01 |
+ 0.502 |
+ 0.478 |
+ 0.02 |
+ 1.22 |
+ 0.78 |
+ Glenn |
+
+
+ | 57 |
+ R1508H2 |
+ BXD32 |
+ 58 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 1.917 |
+ 67.78 |
+ 0.539 |
+ 0.442 |
+ 0.019 |
+ 1.28 |
+ 0.73 |
+ Glenn |
+
+
+ | 58 |
+ R1345H3 |
+ BXD33 |
+ 65 |
+ F |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.098 |
+ 63.14 |
+ 0.522 |
+ 0.459 |
+ 0.019 |
+ 1.27 |
+ 0.73 |
+ UMemphis |
+
+
+ | 59 |
+ R1581H1 |
+ BXD33 |
+ 59 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.229 |
+ 53.16 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.19 |
+ 0.78 |
+ Glenn |
+
+
+ | 60 |
+ R1527H1 |
+ BXD34 |
+ 59 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.3 |
+ 58.92 |
+ 0.51 |
+ 0.471 |
+ 0.019 |
+ 1.24 |
+ 0.76 |
+ Glenn |
+
+
+ | 61 |
+ R1339H3 |
+ BXD34 |
+ 74 |
+ M |
+ 5 |
+ 3 |
+ 0.12 |
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+
+
+ | 62 |
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+ 55 |
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+ 3 |
+ 4 |
+ 0.01 |
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+
+
+ | 63 |
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+ 59 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 64 |
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+ 2 |
+ 3 |
+ 0.03 |
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+
+
+ | 65 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+
+ | 66 |
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+ 59 |
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+ 4 |
+ 4 |
+ 0 |
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+
+
+ | 67 |
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+ 2 |
+ 3 |
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+
+
+ | 68 |
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+ 7 |
+ 3 |
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+
+
+ | 69 |
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+ 7 |
+ 4 |
+ 0.03 |
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+
+
+ | 70 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 71 |
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+ 63 |
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+ 3 |
+ 4 |
+ 0.02 |
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+
+
+ | 72 |
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+ 65 |
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+ 3 |
+ 4 |
+ 0 |
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+
+
+ | 73 |
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+ 56 |
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+ 1 |
+ 3 |
+ 0.02 |
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+
+
+ | 74 |
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+ 7 |
+ 2 |
+ 0.03 |
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+
+
+ | 75 |
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+ 7 |
+ 4 |
+ 0.04 |
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+
+
+ | 76 |
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+ 58 |
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+ 4 |
+ 3 |
+ 0 |
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+
+
+ | 77 |
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+ 65 |
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+ 3 |
+ 4 |
+ 0.05 |
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+
+
+ | 78 |
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+ 6 |
+ 4 |
+ 0.01 |
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+
+
+ | 79 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 80 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+
+ | 81 |
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+ 6 |
+ 4 |
+ 0.03 |
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+
+
+ | 82 |
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+ 7 |
+ 3 |
+ 0.07 |
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+
+
+ | 83 |
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+ 4 |
+ 3 |
+ 0.01 |
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+
+
+ | 84 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 85 |
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+ 7 |
+ 4 |
+ 0.03 |
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+
+
+ | 86 |
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+ 1 |
+ 2 |
+ 0 |
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+
+
+ | 87 |
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+ 1 |
+ 4 |
+ 0.02 |
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+
+
+ | 88 |
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+ 6 |
+ 4 |
+ 0.01 |
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+
+
+ | 89 |
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+ 1 |
+ 3 |
+ 0.02 |
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+
+
+ | 90 |
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+ 6 |
+ 3 |
+ 0.02 |
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+
+
+ | 91 |
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+ 1 |
+ 3 |
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+
+
+ | 92 |
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+ 3 |
+ 4 |
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+
+
+ | 93 |
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+ 1 |
+ 2 |
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+
+
+ | 94 |
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+ 6 |
+ 2 |
+ 0 |
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+
+
+ | 95 |
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+ 1 |
+ 4 |
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+
+
+ | 96 |
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+ 2 |
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+
+
+ | 97 |
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+ 3 |
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+
+
+ | 98 |
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+ 1 |
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+
+
+ | 99 |
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+
+
+ | 100 |
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+ 2 |
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+
+
+ | 101 |
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+
+
+ | 102 |
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+ 3 |
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+
+
+ | 103 |
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+
+
+ | 104 |
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+
+
+ | 105 |
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+
+
+ | 106 |
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+ 3 |
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+
+
+ | 107 |
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+
+
+ | 108 |
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+
+
+ | 109 |
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+
+
+ | 110 |
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+
+
+ | 111 |
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+
+
+ | 112 |
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+
+
+ | 113 |
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+
+
+ | 114 |
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+ 3 |
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+
+
+ | 115 |
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+ 2 |
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+
+
+ | 116 |
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+
+
+ | 117 |
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+ 3 |
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+
+
+ | 118 |
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+ 3 |
+ 0.02 |
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+
+
+ | 119 |
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+ 3 |
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+
+
+ | 120 |
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+ 3 |
+ 0.03 |
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+
+
+ | 121 |
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+ 2 |
+ 0 |
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+
+
+ | 122 |
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+ 2 |
+ 0.01 |
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+
+
+ | 123 |
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+ 3 |
+ 0.02 |
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+
+
+ | 124 |
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+ 3 |
+ 0.01 |
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+
+
+ | 125 |
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+ 4 |
+ 0.09 |
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+
+
+ | 126 |
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+ 3 |
+ 0.02 |
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+
+
+ | 127 |
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+ 3 |
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+
+
+ | 128 |
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+ 4 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 129 |
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+ 2 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 130 |
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+ 4 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 131 |
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+ 3 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 132 |
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+ 7 |
+ 4 |
+ 0.03 |
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+
+
+ | 133 |
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+ 3 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 134 |
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+ M |
+ 4 |
+ 3 |
+ 0.05 |
+ 1.655 |
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+ 0.498 |
+ 0.481 |
+ 0.021 |
+ 1.52 |
+ 0.82 |
+ UTM RW |
+
+
+ | 135 |
+ R2057H1 |
+ BXD93 |
+ 92 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.033 |
+ 44.41 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 1.22 |
+ 0.78 |
+ UTM RW |
+
+
+ | 136 |
+ R2059H1 |
+ BXD93 |
+ 58 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.058 |
+ 60.29 |
+ 0.493 |
+ 0.488 |
+ 0.019 |
+ 1.18 |
+ 1.37 |
+ UTM RW |
+
+
+ | 137 |
+ R2313H1 |
+ BXD94 |
+ 59 |
+ F |
+ 3 |
+ 3 |
+ 0 |
+ 3.091 |
+ 59.45 |
+ 0.487 |
+ 0.495 |
+ 0.018 |
+ 1.34 |
+ 0.73 |
+ UTM RW |
+
+
+ | 138 |
+ R1915H1 |
+ BXD96 |
+ 65 |
+ F |
+ 5 |
+ 2 |
+ 0.04 |
+ 5.145 |
+ 46.19 |
+ 0.502 |
+ 0.481 |
+ 0.017 |
+ 1.37 |
+ 0.74 |
+ UTM RW |
+
+
+ | 139 |
+ R1846H2 |
+ BXD96 |
+ 63 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.159 |
+ 55.85 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.92 |
+ 1.26 |
+ UTM RW |
+
+
+ | 140 |
+ R2648H1 |
+ BXD97 |
+ 74 |
+ F |
+ 7 |
+ 4 |
+ 0.02 |
+ 1.664 |
+ 82.08 |
+ 0.518 |
+ 0.464 |
+ 0.019 |
+ 1.4 |
+ 0.78 |
+ UTM RW |
+
+
+ | 141 |
+ R1927H2 |
+ BXD97 |
+ 67 |
+ M |
+ 1 |
+ 3 |
+ 0.04 |
+ 2.622 |
+ 57.81 |
+ 0.539 |
+ 0.444 |
+ 0.017 |
+ 1.45 |
+ 1.32 |
+ UTM RW |
+
+
+ | 142 |
+ R1942H1 |
+ BXD98 |
+ 62 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.104 |
+ 48.42 |
+ 0.528 |
+ 0.454 |
+ 0.019 |
+ 2.22 |
+ 1.08 |
+ UTM RW |
+
+
+ | 143 |
+ R1943H2 |
+ BXD98 |
+ 62 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.04 |
+ 56.85 |
+ 0.484 |
+ 0.497 |
+ 0.019 |
+ 1.18 |
+ 0.76 |
+ UTM RW |
+
+
+ | 144 |
+ R2197H1 |
+ BXD99 |
+ 70 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.288 |
+ 51.75 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.35 |
+ 0.81 |
+ UTM RW |
+
+
+ | 145 |
+ R2315H1 |
+ BXD99 |
+ 84 |
+ M |
+ 5 |
+ 2 |
+ 0.03 |
+ 6.036 |
+ 43.05 |
+ 0.484 |
+ 0.497 |
+ 0.018 |
+ 1.7 |
+ 0.96 |
+ UTM RW |
+
+
+ | 146 |
+ R2028H2 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 4.362 |
+ 64.49 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 2.78 |
+ 1.13 |
+ JAX |
+
+
+ | 147 |
+ R2029H2 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.04 |
+ 5.208 |
+ 41.21 |
+ 0.49 |
+ 0.49 |
+ 0.02 |
+ 1.62 |
+ 0.95 |
+ JAX |
+
+
+ | 148 |
+ R2670H1 |
+ A/J |
+ 65 |
+ F |
+ 7 |
+ 3 |
+ 0.04 |
+ 3.951 |
+ 46.8 |
+ 0.498 |
+ 0.485 |
+ 0.017 |
+ 1.32 |
+ 0.75 |
+ UTM RW |
+
+
+ | 149 |
+ R2030H1 |
+ A/J |
+ 57 |
+ M |
+ 5 |
+ 2 |
+ 0.06 |
+ 3.307 |
+ 45.16 |
+ 0.527 |
+ 0.454 |
+ 0.018 |
+ 1.63 |
+ 0.99 |
+ UTM RW |
+
+
+ | 150 |
+ R2032H3 |
+ AKR/J |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.054 |
+ 61.03 |
+ 0.51 |
+ 0.471 |
+ 0.018 |
+ 1.46 |
+ 0.79 |
+ JAX |
+
+
+ | 151 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 152 |
+ R1675H1 |
+ BALB/cByJ |
+ 83 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.405 |
+ 48.13 |
+ 0.509 |
+ 0.474 |
+ 0.018 |
+ 1.13 |
+ 0.78 |
+ JAX |
+
+
+ | 153 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 154 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 155 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 156 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 157 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 158 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 159 |
+ R2673H1 |
+ C57BL/6ByJ |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.08 |
+ 1.842 |
+ 67.69 |
+ 0.514 |
+ 0.469 |
+ 0.017 |
+ 1.75 |
+ 0.78 |
+ JAX |
+
+
+ | 160 |
+ R2619H1 |
+ CAST/EiJ |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 161 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 162 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 163 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 164 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 165 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 166 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 167 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 168 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 169 |
+ R2677H1 |
+ PWD/PhJ |
+ 65 |
+ M |
+ 7 |
+ 2 |
+ 0.12 |
+ 2.764 |
+ 65.49 |
+ 0.462 |
+ 0.52 |
+ 0.018 |
+ 1.89 |
+ 1.16 |
+ UTM RW |
+
+
+ | 170 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 171 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 172 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 173 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 174 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+ | 175 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 176 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 177 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 178 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 179 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 180 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 181 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 182 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 183 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 184 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 185 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 186 |
+ R2676H1 |
+ CXB6 |
+ 47 |
+ F |
+ 7 |
+ 2 |
+ 0.05 |
+ 2.146 |
+ 62.51 |
+ 0.507 |
+ 0.475 |
+ 0.018 |
+ 1.52 |
+ 0.78 |
+ JAX |
+
+
+ | 187 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 188 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 189 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 190 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 191 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 192 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 193 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 194 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 195 |
+ R2671H1 |
+ CXB10 |
+ 53 |
+ M |
+ 7 |
+ 3 |
+ 0.09 |
+ 2.348 |
+ 71.45 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 2.2 |
+ 1.14 |
+ JAX |
+
+
+ | 196 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 197 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 198 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 199 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 200 |
+ R2672H1 |
+ CXB13 |
+ 49 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.722 |
+ 79.52 |
+ 0.516 |
+ 0.465 |
+ 0.019 |
+ 1.64 |
+ 0.75 |
+ JAX |
+
+
+ | 201 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hc_m2_0606_mdp/summary.rtf b/general/datasets/Hc_m2_0606_mdp/summary.rtf
new file mode 100644
index 0000000..c8593c7
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_mdp/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 97, Name: Hippocampus Consortium M430v2 (Jun06)
\ No newline at end of file
diff --git a/general/datasets/Hc_m2_0606_p/acknowledgment.rtf b/general/datasets/Hc_m2_0606_p/acknowledgment.rtf
new file mode 100644
index 0000000..1481cd1
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_p/acknowledgment.rtf
@@ -0,0 +1,50 @@
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
diff --git a/general/datasets/Hc_m2_0606_p/cases.rtf b/general/datasets/Hc_m2_0606_p/cases.rtf
new file mode 100644
index 0000000..15e6cda
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_p/cases.rtf
@@ -0,0 +1,56 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 27 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondrial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 strains are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2_0606_p/citation.rtf b/general/datasets/Hc_m2_0606_p/citation.rtf
new file mode 100644
index 0000000..61a0788
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_p/citation.rtf
@@ -0,0 +1 @@
+Please cite: Overall RW, Kempermann G, Peirce J, Lu L, Goldowitz D, Gage FH, Goodwin S, Smit AB, Airey DC, Rosen GD, Schalkwyk LC, Sutter TR, Nowakowski RS, Whatley S, Williams RW (2009) Genetics of the hippocampal transcriptome in mice: a systematic survey and online neurogenomic resource. Front. Neurogen. 1:3 Full Text HTML doi:10.3389/neuro.15.003.2009
diff --git a/general/datasets/Hc_m2_0606_p/contributors.rtf b/general/datasets/Hc_m2_0606_p/contributors.rtf
new file mode 100644
index 0000000..4108279
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_p/contributors.rtf
@@ -0,0 +1,46 @@
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
diff --git a/general/datasets/Hc_m2_0606_p/experiment-design.rtf b/general/datasets/Hc_m2_0606_p/experiment-design.rtf
new file mode 100644
index 0000000..356f1d2
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_p/experiment-design.rtf
@@ -0,0 +1 @@
+Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2_0606_p/experiment-type.rtf b/general/datasets/Hc_m2_0606_p/experiment-type.rtf
new file mode 100644
index 0000000..f1b8174
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_p/experiment-type.rtf
@@ -0,0 +1 @@
+Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2_0606_p/notes.rtf b/general/datasets/Hc_m2_0606_p/notes.rtf
new file mode 100644
index 0000000..9c11719
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_p/notes.rtf
@@ -0,0 +1,12 @@
+
This study includes the following datasets:
+
+
+ - Hippocampus Consortium M430v2 CXB (Oct05) MAS5
+ - Hippocampus Consortium M430v2 CXB (Oct05) RMA
+ - Hippocampus Consortium M430v2 CXB (Oct05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) RMA
+ - Hippocampus Consortium M430v2 (Jun06) RMA
+ - Hippocampus Consortium M430v2 (Jun06) MAS5
+ - Hippocampus Consortium M430v2 (Jun06) PDNN
+
diff --git a/general/datasets/Hc_m2_0606_p/platform.rtf b/general/datasets/Hc_m2_0606_p/platform.rtf
new file mode 100644
index 0000000..6c99bee
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_p/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2_0606_p/processing.rtf b/general/datasets/Hc_m2_0606_p/processing.rtf
new file mode 100644
index 0000000..3698a7b
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_p/processing.rtf
@@ -0,0 +1,37 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very sensitive to the transformation method that is used. Using the PDNN transform, the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For example, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one would include the sample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the probe level (CEL) data after step 5 below. DataDesk allows the rapid detection of subsets of probes that are particularly sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - We performed a quantile normalization of the log base 2 values for all arrays using the same initial steps used by the RMA transform.
+ - We computed the Z scores for each cell value.
+ - We multiplied all Z scores by 2.
+ - We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level (probe brightness level) corresponds approximately to a 1 unit difference.
+ - Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data from the CHP file: The expression values were generated using PDNN. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1 unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2_0606_p/summary.rtf b/general/datasets/Hc_m2_0606_p/summary.rtf
new file mode 100644
index 0000000..1e86e54
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_p/summary.rtf
@@ -0,0 +1,3 @@
+MOST HIGHLY RECOMMENDED DATA SET (Overall et al., 2009): The Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of 99 genetically diverse strains of mice including 67 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a diverse set of common inbred strains, and two reciprocal F1 hybrids.
+
+The hippocampus is an important and intriguing part of the forebrain that is crucial in memory formation and retrieval, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section.
diff --git a/general/datasets/Hc_m2_0606_p/tissue.rtf b/general/datasets/Hc_m2_0606_p/tissue.rtf
new file mode 100644
index 0000000..bcea7b0
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_p/tissue.rtf
@@ -0,0 +1,3721 @@
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thank Muriel Davisson for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below). All animals were sacrifice between 9 AM and 5 PM during the light phase.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+RNA Extraction: In brief, we used the RNA STAT-60 protocol (TEL-TEST "B" Bulletin No. 1), steps 5.1A (homogenization of tissue), 5.2 (RNA extraction), 5.3 (RNA precipitation), and 5.4 (RNA wash). In Step 5.4 we stopped after adding 75% ethanol (1 ml per 1 ml RNA STAT-60) and stored the mix at -80°C until further use. Before RNA labeling we thawed samples and proceeded with the remainder of Step 5.4; pelleting, drying, and redissolving the pellet in RNase-free water.
+
+We finally purify RNA by using Na4OAc before running arrays. Here is the detailed method:
+
+Final RNA purification protocol
+
+
+ - Add 1/10th volume of 3M Na4OAc , pH 5.2. If the sample was eluted with 100 µl nuclease-free water as suggested, this will be 10 µl of 3M Na4OAc.
+ - Add 2.5 volumes of 100% ethanol (250 µl if the RNA was eluted in100 µl). Mix well and incubate at –20°C for 2 hrs.
+ - Centrifuge at speed of 13,000 rpm for 20 min at 4°C. Carefully remove and discard the supernatant.
+ - Wash the pellet with 800 µl 75% cold ethanol, centrifuge at speed of 8,600 rpm for 5 min, and remove the 75% ethanol. Wash again.
+ - To remove the last traces of ethanol, quickly respin the tube, and aspirate any residual fluid.
+ - Air dry the pellet.
+ - Resuspend pellet in nuclease-free water.
+
+
+
+
+5. PROTOCOL: RNA/mRNA isolation by the RNA STAT-60 method includes the following steps:
+1. Homogenization RNA STAT-60TM (1 ml per 50-100 mg tissue, or 5-10 x 10-6 cells)
+2. RNA Extraction 1 vol. of homogenate +0.2 vol. of chloroform
+3. RNA Precipitation 0.5 vol. of isopropanol
+4. RNA Wash 75% ethanol
+
+Unless stated otherwise the procedure is carried out at room temperature.
+
+5.1 HOMOGENIZATION
+
+A. TISSUES: Homogenize tissues samples in the RNA STAT-60(1 ml/50-100mg tissue) in a glass-Teflon or Polytron homogenizer. Sample volume should not exceed 10% of the volume of the RNA STAT-60 used for homogenization.
+
+B. CELLS: Cells grown in mono layer are lysed directly in a culture dish by adding the RNA STAT-60TM (1 ml/3.5 cm petri dish) and passing the cell lysate several times through a pipette. Cells grown in suspension are sediment then lysed in the RNA STAT-60TM (1 ml per 5-10 x 106 cells) by repetitive pipetting. Washing calls before addition of the RNA STAT-60TM should be avoided as this increases the possibility of mRNA degradation.
+
+5.2 RNA EXTRACTION: Following homogenization, store the homogenate for 5 min at room temp to permit the complete dissociation of nucleoprotein complexes. Next, add 0.2 ml of chloroform per 1 ml of the RNA STAT-60, cover the sample tightly, shake vigorously for 15 seconds and let it stay at room temperature for 2-3minutes. Centrifuge the homogenate at 12,000g (max) for 15 minutes at 4°C. Following centrifugation, the homogenate separates into two phases: a lower red phenol chloroform phase and the colorless upper aqueous phase. RNA remains exclusively in the aqueous phase whereas DNA and proteins are in the interferes and organic phase. The volume of the aqueous phase is about 60% of the volume of RNA STAT-60 used for homogenization.
+
+5.3 RNA PRECIPITATION: Transfer the aqueous phase to a fresh tube and mix with isopropanol. Add 0.5 ml of isopropanol per 1 ml of the RNA STAT-60 used for homogenization. Store samples at room temp for 5-10 minutes and centrifuge at 12,000g (max.) for 10 min at 4°C. RNA precipitate (often visible before centrifugation) forms a white pellet at the bottom of the tube.
+
+5.4 RNA WASH: Remove supernatant and wash the RNA pellet once with 75% ethanol by vortexing and subsequent centrifugation at 7,500g (max.) for 5 min at 4°C. Add at least 1 ml of 75% ethanol per 1 ml of the RNA STAT-60 used for the initial homogenization.
+
+At the end of the procedure, dry the RNA pellet briefly by air-drying or in a vacuum (5-10 min.). It is important not to let the RNA pellet dry completely as it will greatly decrease its solubility. Do not use the Speed-Vac for drying. Dissolve the RNA pellet in water or in 1 mm EDTA, pH 7, or 0.5% SDS solution. Vortex or pass the pellet a few times through a pipette tip. An incubation for 10-15 minutes at 55-60oC may be required to dissolve RNA samples. Diethylpyrocarbonate (DEPC) treated RNase-free solutions1 should be used for solubilization of RNA.
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80°C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: Our goal was to obtain a male sample pool and female sample pool from each isogenic group. While almost all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. All but 5 of 99 strains (BXD55, BXD86, BXD94, BALB/cByJ, and CAST/EiJ) are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquots R1291H3 and R1291H4).
+
+
+
+Sex Balance: Based on the expression of Xist, probe set 1427262_at, DBA/2J and KK/HlJ are represented only by female samples, BXD55, and BALB/cByJ are only represented by a single male sample, BXD74 is represented by two male samples, and BXD86, BXD94, and CAST/EiJ are possibly mixed sex samples. One of the BXD9 samples, array R1523, may be a mixed sex sample pool because the expression of Xist is intermediate.
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays. Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4°C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+COMPARISON with December 2005 Data Set: Both BXD14 arrays in the Dec05 data set were found to actually be from BXD23 cases. This error of strain identification has been corrected in the present data set. Four arrays in the Dec05 data set have been deleted because we judged them to be of poor quality (strain_sex_sample_firstreaction_group):
+
+
+ - BXD21_F_1_1_G1
+ - BXD23_M_1_1_G7
+ - BXD36_M_1_1_G2
+ - BXD36_F_1_1_G3
+
+
+In the Dec05 data set there are a total of 1986 transcripts with QTLs that have LRS scores above 50, whereas in the corrected June06 data sets there are a total of 2074 transcripts with QTLs above 50.
+
+Data Table 1:
+
+This table lists all arrays by file order (Index), tube/sample ID, age, sex, batch, and numbers of animals in each sample pool (pool size). The next columns (RMA outlier, scale factor, background average, present, absent, marginal, AFFY-b-ActinMur(3'/5'), AFFY-GapdhMur(3'/5')) are all Affymetrix QC data. Finally, source lists the source colony of the animals. (Final version, fully corrected, by Arthur Centeno, October 2008)
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool size |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 2 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 3 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M technical duplicate of above |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 4 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 5 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 2.579 |
+ 58.49 |
+ 0.506 |
+ 0.475 |
+ 0.019 |
+ 2.49 |
+ 1.21 |
+ UTM RW |
+
+
+ | 6 |
+ R1551H1 |
+ D2B6F1 |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.62 |
+ 53.76 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 1.37 |
+ 0.76 |
+ UTM RW |
+
+
+ | 7 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
+ 3.058 |
+ 51.87 |
+ 0.477 |
+ 0.503 |
+ 0.02 |
+ 1.67 |
+ 0.76 |
+ UTM RW |
+
+
+ | 8 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
+ 3.341 |
+ 49.26 |
+ 0.527 |
+ 0.456 |
+ 0.018 |
+ 1.14 |
+ 1.45 |
+ UTM RW |
+
+
+ | 9 |
+ R1449H2 |
+ C57BL/6J |
+ 71 |
+ M |
+ 5 |
+ 3 |
+ 0.09 |
+ 3.592 |
+ 44.32 |
+ 0.47 |
+ 0.51 |
+ 0.02 |
+ 1.68 |
+ 0.77 |
+ UTM DG |
+
+
+ | 10 |
+ R1290H2 |
+ DBA/2J |
+ 63 |
+ F |
+ 7 |
+ 2 |
+ 0.04 |
+ 2.576 |
+ 59.6 |
+ 0.513 |
+ 0.468 |
+ 0.018 |
+ 1.3 |
+ 0.78 |
+ JAX |
+
+
+ | 11 |
+ R1468H1 |
+ DBA/2J |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.03 |
+ 2.929 |
+ 53.8 |
+ 0.515 |
+ 0.465 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 12 |
+ R1507H1 |
+ BXD1 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.056 |
+ 60.17 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.15 |
+ 0.76 |
+ Glenn |
+
+
+ | 13 |
+ R1542H1 |
+ BXD1 |
+ 59 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.792 |
+ 80.56 |
+ 0.492 |
+ 0.489 |
+ 0.018 |
+ 1.57 |
+ 0.79 |
+ Glenn |
+
+
+ | 14 |
+ R1520H1 |
+ BXD2 |
+ 56 |
+ F |
+ 4 |
+ 4 |
+ 0.09 |
+ 1.715 |
+ 71.62 |
+ 0.515 |
+ 0.467 |
+ 0.018 |
+ 2.36 |
+ 1.6 |
+ Glenn |
+
+
+ | 15 |
+ R1516H1 |
+ BXD2 |
+ 61 |
+ M |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.231 |
+ 64.86 |
+ 0.508 |
+ 0.474 |
+ 0.019 |
+ 1.3 |
+ 1.53 |
+ Glenn |
+
+
+ | 16 |
+ R1593H2 |
+ BXD5 |
+ 60 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 1.913 |
+ 59.96 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.98 |
+ 1.44 |
+ Glenn |
+
+
+ | 17 |
+ R1692H1 |
+ BXD5 |
+ 60 |
+ M |
+ 3 |
+ 2 |
+ 0.07 |
+ 3.764 |
+ 72.74 |
+ 0.465 |
+ 0.516 |
+ 0.02 |
+ 1.15 |
+ 0.74 |
+ Glenn |
+
+
+ | 18 |
+ R1539H2 |
+ BXD6 |
+ 59 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 2.488 |
+ 54.97 |
+ 0.518 |
+ 0.463 |
+ 0.018 |
+ 1.08 |
+ 1.33 |
+ Glenn |
+
+
+ | 19 |
+ R1538H1 |
+ BXD6 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.01 |
+ 2.585 |
+ 50.27 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 1.46 |
+ 0.79 |
+ Glenn |
+
+
+ | 20 |
+ R1518H1 |
+ BXD8 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 2.92 |
+ 54.84 |
+ 0.515 |
+ 0.465 |
+ 0.02 |
+ 1.32 |
+ 1.24 |
+ Glenn |
+
+
+ | 21 |
+ R1548H1 |
+ BXD8 |
+ 59 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.132 |
+ 59.37 |
+ 0.504 |
+ 0.477 |
+ 0.019 |
+ 2.16 |
+ 1.54 |
+ Glenn |
+
+
+ | 22 |
+ R1350H2 |
+ BXD9 |
+ 86 |
+ F |
+ 1 |
+ 3 |
+ 0.05 |
+ 2.771 |
+ 60.62 |
+ 0.5 |
+ 0.482 |
+ 0.018 |
+ 1.01 |
+ 1.28 |
+ UMemphis |
+
+
+ | 23 |
+ R1523H3 |
+ BXD9 |
+ 57 |
+ MF (mixed) |
+ 7 |
+ 3 |
+ 0.14 |
+ 3.9 |
+ 78.36 |
+ 0.435 |
+ 0.547 |
+ 0.018 |
+ 1.36 |
+ 0.77 |
+ UTM RW |
+
+
+ | 24 |
+ R1531H1 |
+ BXD11 |
+ 56 |
+ F |
+ 6 |
+ 3 |
+ 0.06 |
+ 2.229 |
+ 56.36 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 2.23 |
+ 1.02 |
+ Glenn |
+
+
+ | 25 |
+ R1367H1 |
+ BXD11 |
+ 56 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.11 |
+ 78.78 |
+ 0.503 |
+ 0.477 |
+ 0.02 |
+ 1.07 |
+ 1.27 |
+ Glenn |
+
+
+ | 26 |
+ R1530H1 |
+ BXD12 |
+ 58 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 3.227 |
+ 53.77 |
+ 0.505 |
+ 0.477 |
+ 0.018 |
+ 0.95 |
+ 1.4 |
+ Glenn |
+
+
+ | 27 |
+ R2674H1 |
+ BXD12 |
+ 59 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.924 |
+ 83.44 |
+ 0.519 |
+ 0.464 |
+ 0.018 |
+ 1.21 |
+ 0.78 |
+ Glenn |
+
+
+ | 28 |
+ R1529H1 |
+ BXD13 |
+ 58 |
+ F |
+ 6 |
+ 3 |
+ 0.05 |
+ 2.55 |
+ 59.05 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 2 |
+ 1.54 |
+ Glenn |
+
+
+ | 29 |
+ R1662H2 |
+ BXD13 |
+ 60 |
+ M |
+ 1 |
+ 3 |
+ 0.03 |
+ 4.603 |
+ 45.81 |
+ 0.509 |
+ 0.472 |
+ 0.019 |
+ 1.3 |
+ 0.82 |
+ Glenn |
+
+
+ | 30 |
+ R1304H2 |
+ BXD14 |
+ 72 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.946 |
+ 61.87 |
+ 0.484 |
+ 0.498 |
+ 0.018 |
+ 1.22 |
+ 0.77 |
+ UTM RW |
+
+
+ | 31 |
+ R1278H2 |
+ BXD14 |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.06 |
+ 4.75 |
+ 67.52 |
+ 0.449 |
+ 0.532 |
+ 0.019 |
+ 1.1 |
+ 0.73 |
+ UTM RW |
+
+
+ | 32 |
+ R1524H1 |
+ BXD15 |
+ 60 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.961 |
+ 50.93 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 1.74 |
+ 0.91 |
+ Glenn |
+
+
+ | 33 |
+ R1515H1 |
+ BXD15 |
+ 61 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.316 |
+ 57.05 |
+ 0.503 |
+ 0.478 |
+ 0.019 |
+ 1.32 |
+ 1.21 |
+ Glenn |
+
+
+ | 34 |
+ R1661H1 |
+ BXD16 |
+ 61 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.778 |
+ 59.81 |
+ 0.516 |
+ 0.466 |
+ 0.019 |
+ 1.39 |
+ 1.2 |
+ Glenn |
+
+
+ | 35 |
+ R1594H1 |
+ BXD16 |
+ 61 |
+ M |
+ 4 |
+ 3 |
+ 0.03 |
+ 2.634 |
+ 53.66 |
+ 0.504 |
+ 0.478 |
+ 0.018 |
+ 1.96 |
+ 1.51 |
+ Glenn |
+
+
+ | 36 |
+ R2666H1 |
+ BXD19 |
+ 60 |
+ F |
+ 7 |
+ 3 |
+ 0.02 |
+ 2.498 |
+ 76.2 |
+ 0.495 |
+ 0.486 |
+ 0.019 |
+ 1.41 |
+ 0.77 |
+ Glenn |
+
+
+ | 37 |
+ R1471H1 |
+ BXD19 |
+ 157 |
+ M |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.165 |
+ 43.34 |
+ 0.519 |
+ 0.462 |
+ 0.018 |
+ 1.01 |
+ 1.29 |
+ UTM JB |
+
+
+ | 38 |
+ R1573H1 |
+ BXD20 |
+ 59 |
+ F |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.749 |
+ 52.7 |
+ 0.513 |
+ 0.469 |
+ 0.018 |
+ 1.01 |
+ 1.27 |
+ Glenn |
+
+
+ | 39 |
+ R2507H1 |
+ BXD20 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.06 |
+ 3.568 |
+ 57 |
+ 0.472 |
+ 0.508 |
+ 0.02 |
+ 1.29 |
+ 0.76 |
+ Glenn |
+
+
+ | 40 |
+ R2668H1 |
+ BXD21 |
+ 60 |
+ M |
+ 7 |
+ 4 |
+ 0.07 |
+ 2.605 |
+ 44.9 |
+ 0.535 |
+ 0.449 |
+ 0.017 |
+ 1.54 |
+ 0.76 |
+ Glenn |
+
+
+ | 41 |
+ R1337H2 |
+ BXD21 |
+ 102 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.673 |
+ 58.05 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.4 |
+ 0.76 |
+ UAB |
+
+
+ | 42 |
+ R1848H3 |
+ BXD22 |
+ 196 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.943 |
+ 51.7 |
+ 0.494 |
+ 0.485 |
+ 0.021 |
+ 2.2 |
+ 0.78 |
+ UAB |
+
+
+ | 43 |
+ R1525H1 |
+ BXD22 |
+ 59 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.248 |
+ 55.76 |
+ 0.548 |
+ 0.433 |
+ 0.018 |
+ 1.26 |
+ 0.74 |
+ Glenn |
+
+
+ | 44 |
+ R1280H2 |
+ BXD23 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.187 |
+ 54.63 |
+ 0.458 |
+ 0.523 |
+ 0.019 |
+ 0.96 |
+ 1.2 |
+ UTM RW |
+
+
+ | 45 |
+ R1537H1 |
+ BXD23 |
+ 58 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.719 |
+ 67.54 |
+ 0.468 |
+ 0.513 |
+ 0.019 |
+ 1.51 |
+ 0.96 |
+ Glenn |
+
+
+ | 46 |
+ R1343H2 |
+ BXD24 |
+ 71 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.083 |
+ 65.07 |
+ 0.506 |
+ 0.474 |
+ 0.019 |
+ 1.46 |
+ 0.75 |
+ UMemphis |
+
+
+ | 47 |
+ R1517H1 |
+ BXD24 |
+ 57 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.471 |
+ 53.66 |
+ 0.504 |
+ 0.476 |
+ 0.019 |
+ 1.28 |
+ 0.78 |
+ Glenn |
+
+
+ | 48 |
+ R1366H1 |
+ BXD27 |
+ 60 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.26 |
+ 48.46 |
+ 0.518 |
+ 0.463 |
+ 0.019 |
+ 1.29 |
+ 0.77 |
+ Glenn |
+
+
+ | 49 |
+ R1849H1 |
+ BXD27 |
+ 70 |
+ M |
+ 5 |
+ 3 |
+ 0.06 |
+ 8.801 |
+ 38.34 |
+ 0.468 |
+ 0.512 |
+ 0.019 |
+ 2.42 |
+ 1.08 |
+ UAB |
+
+
+ | 50 |
+ R1353H1 |
+ BXD28 |
+ 79 |
+ F |
+ 3 |
+ 4 |
+ 0.01 |
+ 3.22 |
+ 76.22 |
+ 0.48 |
+ 0.5 |
+ 0.02 |
+ 1.33 |
+ 0.78 |
+ UMemphis |
+
+
+ | 51 |
+ R2332H1 |
+ BXD28 |
+ 60 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 3.217 |
+ 63.68 |
+ 0.491 |
+ 0.49 |
+ 0.019 |
+ 1.37 |
+ 0.79 |
+ Glenn |
+
+
+ | 52 |
+ R1532H1 |
+ BXD29 |
+ 57 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.122 |
+ 59.18 |
+ 0.524 |
+ 0.456 |
+ 0.019 |
+ 1.17 |
+ 0.76 |
+ Glenn |
+
+
+ | 53 |
+ R1356H1 |
+ BXD29 |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.01 |
+ 4.033 |
+ 47.67 |
+ 0.52 |
+ 0.463 |
+ 0.017 |
+ 1.17 |
+ 0.78 |
+ UMemphis |
+
+
+ | 54 |
+ R1240H2 |
+ BXD31 |
+ 61 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.335 |
+ 65.17 |
+ 0.507 |
+ 0.474 |
+ 0.019 |
+ 1.31 |
+ 0.78 |
+ UTM RW |
+
+
+ | 55 |
+ R1526H2 |
+ BXD31 |
+ 57 |
+ F |
+ 7 |
+ 4 |
+ 0.1 |
+ 7.267 |
+ 89.54 |
+ 0.435 |
+ 0.547 |
+ 0.017 |
+ 1.35 |
+ 0.78 |
+ UTM RW |
+
+
+ | 56 |
+ R2675H1 |
+ BXD32 |
+ 57 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 2.268 |
+ 78.01 |
+ 0.502 |
+ 0.478 |
+ 0.02 |
+ 1.22 |
+ 0.78 |
+ Glenn |
+
+
+ | 57 |
+ R1508H2 |
+ BXD32 |
+ 58 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 1.917 |
+ 67.78 |
+ 0.539 |
+ 0.442 |
+ 0.019 |
+ 1.28 |
+ 0.73 |
+ Glenn |
+
+
+ | 58 |
+ R1345H3 |
+ BXD33 |
+ 65 |
+ F |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.098 |
+ 63.14 |
+ 0.522 |
+ 0.459 |
+ 0.019 |
+ 1.27 |
+ 0.73 |
+ UMemphis |
+
+
+ | 59 |
+ R1581H1 |
+ BXD33 |
+ 59 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.229 |
+ 53.16 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.19 |
+ 0.78 |
+ Glenn |
+
+
+ | 60 |
+ R1527H1 |
+ BXD34 |
+ 59 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.3 |
+ 58.92 |
+ 0.51 |
+ 0.471 |
+ 0.019 |
+ 1.24 |
+ 0.76 |
+ Glenn |
+
+
+ | 61 |
+ R1339H3 |
+ BXD34 |
+ 74 |
+ M |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.888 |
+ 53.49 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 2.39 |
+ 1.35 |
+ UMemphis |
+
+
+ | 62 |
+ R1855H1 |
+ BXD38 |
+ 55 |
+ F |
+ 3 |
+ 4 |
+ 0.01 |
+ 3.536 |
+ 54.54 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.39 |
+ 0.75 |
+ Glenn |
+
+
+ | 63 |
+ R1510H1 |
+ BXD38 |
+ 59 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.186 |
+ 68.06 |
+ 0.521 |
+ 0.46 |
+ 0.019 |
+ 1.26 |
+ 0.79 |
+ Glenn |
+
+
+ | 64 |
+ R1528H2 |
+ BXD39 |
+ 59 |
+ F |
+ 2 |
+ 3 |
+ 0.03 |
+ 4.717 |
+ 38.3 |
+ 0.511 |
+ 0.47 |
+ 0.02 |
+ 1.12 |
+ 0.75 |
+ Glenn |
+
+
+ | 65 |
+ R1514H1 |
+ BXD39 |
+ 59 |
+ M |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.992 |
+ 56.06 |
+ 0.477 |
+ 0.504 |
+ 0.019 |
+ 1.43 |
+ 0.81 |
+ Glenn |
+
+
+ | 66 |
+ R1522H1 |
+ BXD40 |
+ 59 |
+ F |
+ 4 |
+ 4 |
+ 0 |
+ 2.631 |
+ 67.16 |
+ 0.49 |
+ 0.491 |
+ 0.018 |
+ 1.56 |
+ 0.77 |
+ Glenn |
+
+
+ | 67 |
+ R1359H1 |
+ BXD40 |
+ 73 |
+ M |
+ 2 |
+ 3 |
+ 0.09 |
+ 7.458 |
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+
+
+ | 68 |
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+ 7 |
+ 3 |
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+
+
+ | 69 |
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+ 7 |
+ 4 |
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+
+
+ | 70 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 71 |
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+ 63 |
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+ 3 |
+ 4 |
+ 0.02 |
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+
+
+ | 72 |
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+ 65 |
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+ 3 |
+ 4 |
+ 0 |
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+
+
+ | 73 |
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+ 1 |
+ 3 |
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+
+
+ | 74 |
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+ 2 |
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+
+
+ | 75 |
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+ 7 |
+ 4 |
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+
+
+ | 76 |
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+ 4 |
+ 3 |
+ 0 |
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+
+
+ | 77 |
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+ 3 |
+ 4 |
+ 0.05 |
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+
+
+ | 78 |
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+ 6 |
+ 4 |
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+
+
+ | 79 |
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+ 1 |
+ 3 |
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+
+
+ | 80 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+
+ | 81 |
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+ 6 |
+ 4 |
+ 0.03 |
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+
+
+ | 82 |
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+ 7 |
+ 3 |
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+
+
+ | 83 |
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+ 4 |
+ 3 |
+ 0.01 |
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+
+
+ | 84 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 85 |
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+ 7 |
+ 4 |
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+
+
+ | 86 |
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+ 1 |
+ 2 |
+ 0 |
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+
+
+ | 87 |
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+ 1 |
+ 4 |
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+
+
+ | 88 |
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+ 6 |
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+
+
+ | 89 |
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+ 1 |
+ 3 |
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+
+
+ | 90 |
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+ 6 |
+ 3 |
+ 0.02 |
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+
+
+ | 91 |
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+ 1 |
+ 3 |
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+
+
+ | 92 |
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+ 3 |
+ 4 |
+ 0.01 |
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+
+
+ | 93 |
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+ 1 |
+ 2 |
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+
+
+ | 94 |
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+ 6 |
+ 2 |
+ 0 |
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+
+
+ | 95 |
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+ 1 |
+ 4 |
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+
+
+ | 96 |
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+ 2 |
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+
+
+ | 97 |
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+ 3 |
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+
+
+ | 98 |
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+ 1 |
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+
+
+ | 99 |
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+ 3 |
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+
+
+ | 100 |
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+ 2 |
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+
+
+ | 101 |
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+
+
+ | 102 |
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+ 3 |
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+
+
+ | 103 |
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+
+
+ | 104 |
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+
+
+ | 105 |
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+
+
+ | 106 |
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+
+
+ | 107 |
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+
+
+ | 108 |
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+
+
+ | 109 |
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+
+
+ | 110 |
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+
+
+ | 111 |
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+
+
+ | 112 |
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+
+
+ | 113 |
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+
+
+ | 114 |
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+
+
+ | 115 |
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+
+
+ | 116 |
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+
+
+ | 117 |
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+
+
+ | 118 |
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+
+
+ | 119 |
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+
+
+ | 120 |
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+
+
+ | 121 |
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+ 0 |
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+
+
+ | 122 |
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+ 2 |
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+
+
+ | 123 |
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+ 3 |
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+
+
+ | 124 |
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+ 3 |
+ 0.01 |
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+
+
+ | 125 |
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+ 4 |
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+
+
+ | 126 |
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+
+
+ | 127 |
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+
+
+ | 128 |
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+
+
+ | 129 |
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+ 2 |
+ 0.02 |
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+
+
+ | 130 |
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+ 4 |
+ 0.03 |
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+
+
+ | 131 |
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+ 3 |
+ 0.01 |
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+
+
+ | 132 |
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+ 4 |
+ 0.03 |
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+
+
+ | 133 |
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+ 3 |
+ 0.02 |
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+
+
+ | 134 |
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+ 3 |
+ 0.05 |
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+
+
+ | 135 |
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+ 3 |
+ 0.02 |
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+
+
+ | 136 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 137 |
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+ 3 |
+ 0 |
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+
+
+ | 138 |
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+ 2 |
+ 0.04 |
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+ UTM RW |
+
+
+ | 139 |
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+ 1 |
+ 3 |
+ 0 |
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+ UTM RW |
+
+
+ | 140 |
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+ 7 |
+ 4 |
+ 0.02 |
+ 1.664 |
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+ 0.464 |
+ 0.019 |
+ 1.4 |
+ 0.78 |
+ UTM RW |
+
+
+ | 141 |
+ R1927H2 |
+ BXD97 |
+ 67 |
+ M |
+ 1 |
+ 3 |
+ 0.04 |
+ 2.622 |
+ 57.81 |
+ 0.539 |
+ 0.444 |
+ 0.017 |
+ 1.45 |
+ 1.32 |
+ UTM RW |
+
+
+ | 142 |
+ R1942H1 |
+ BXD98 |
+ 62 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.104 |
+ 48.42 |
+ 0.528 |
+ 0.454 |
+ 0.019 |
+ 2.22 |
+ 1.08 |
+ UTM RW |
+
+
+ | 143 |
+ R1943H2 |
+ BXD98 |
+ 62 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.04 |
+ 56.85 |
+ 0.484 |
+ 0.497 |
+ 0.019 |
+ 1.18 |
+ 0.76 |
+ UTM RW |
+
+
+ | 144 |
+ R2197H1 |
+ BXD99 |
+ 70 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.288 |
+ 51.75 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.35 |
+ 0.81 |
+ UTM RW |
+
+
+ | 145 |
+ R2315H1 |
+ BXD99 |
+ 84 |
+ M |
+ 5 |
+ 2 |
+ 0.03 |
+ 6.036 |
+ 43.05 |
+ 0.484 |
+ 0.497 |
+ 0.018 |
+ 1.7 |
+ 0.96 |
+ UTM RW |
+
+
+ | 146 |
+ R2028H2 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 4.362 |
+ 64.49 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 2.78 |
+ 1.13 |
+ JAX |
+
+
+ | 147 |
+ R2029H2 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.04 |
+ 5.208 |
+ 41.21 |
+ 0.49 |
+ 0.49 |
+ 0.02 |
+ 1.62 |
+ 0.95 |
+ JAX |
+
+
+ | 148 |
+ R2670H1 |
+ A/J |
+ 65 |
+ F |
+ 7 |
+ 3 |
+ 0.04 |
+ 3.951 |
+ 46.8 |
+ 0.498 |
+ 0.485 |
+ 0.017 |
+ 1.32 |
+ 0.75 |
+ UTM RW |
+
+
+ | 149 |
+ R2030H1 |
+ A/J |
+ 57 |
+ M |
+ 5 |
+ 2 |
+ 0.06 |
+ 3.307 |
+ 45.16 |
+ 0.527 |
+ 0.454 |
+ 0.018 |
+ 1.63 |
+ 0.99 |
+ UTM RW |
+
+
+ | 150 |
+ R2032H3 |
+ AKR/J |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.054 |
+ 61.03 |
+ 0.51 |
+ 0.471 |
+ 0.018 |
+ 1.46 |
+ 0.79 |
+ JAX |
+
+
+ | 151 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 152 |
+ R1675H1 |
+ BALB/cByJ |
+ 83 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.405 |
+ 48.13 |
+ 0.509 |
+ 0.474 |
+ 0.018 |
+ 1.13 |
+ 0.78 |
+ JAX |
+
+
+ | 153 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 154 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 155 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 156 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 157 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 158 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 159 |
+ R2673H1 |
+ C57BL/6ByJ |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.08 |
+ 1.842 |
+ 67.69 |
+ 0.514 |
+ 0.469 |
+ 0.017 |
+ 1.75 |
+ 0.78 |
+ JAX |
+
+
+ | 160 |
+ R2619H1 |
+ CAST/EiJ |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 161 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 162 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 163 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 164 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 165 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 166 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 167 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 168 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 169 |
+ R2677H1 |
+ PWD/PhJ |
+ 65 |
+ M |
+ 7 |
+ 2 |
+ 0.12 |
+ 2.764 |
+ 65.49 |
+ 0.462 |
+ 0.52 |
+ 0.018 |
+ 1.89 |
+ 1.16 |
+ UTM RW |
+
+
+ | 170 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 171 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 172 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 173 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 174 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+ | 175 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 176 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 177 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 178 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 179 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 180 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 181 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 182 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 183 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 184 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 185 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 186 |
+ R2676H1 |
+ CXB6 |
+ 47 |
+ F |
+ 7 |
+ 2 |
+ 0.05 |
+ 2.146 |
+ 62.51 |
+ 0.507 |
+ 0.475 |
+ 0.018 |
+ 1.52 |
+ 0.78 |
+ JAX |
+
+
+ | 187 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 188 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 189 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 190 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 191 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 192 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 193 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 194 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 195 |
+ R2671H1 |
+ CXB10 |
+ 53 |
+ M |
+ 7 |
+ 3 |
+ 0.09 |
+ 2.348 |
+ 71.45 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 2.2 |
+ 1.14 |
+ JAX |
+
+
+ | 196 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 197 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 198 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 199 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 200 |
+ R2672H1 |
+ CXB13 |
+ 49 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.722 |
+ 79.52 |
+ 0.516 |
+ 0.465 |
+ 0.019 |
+ 1.64 |
+ 0.75 |
+ JAX |
+
+
+ | 201 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hc_m2_0606_r/acknowledgment.rtf b/general/datasets/Hc_m2_0606_r/acknowledgment.rtf
new file mode 100644
index 0000000..1481cd1
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_r/acknowledgment.rtf
@@ -0,0 +1,50 @@
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
diff --git a/general/datasets/Hc_m2_0606_r/cases.rtf b/general/datasets/Hc_m2_0606_r/cases.rtf
new file mode 100644
index 0000000..15e6cda
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_r/cases.rtf
@@ -0,0 +1,56 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 27 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondrial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 strains are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2_0606_r/citation.rtf b/general/datasets/Hc_m2_0606_r/citation.rtf
new file mode 100644
index 0000000..61a0788
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_r/citation.rtf
@@ -0,0 +1 @@
+Please cite: Overall RW, Kempermann G, Peirce J, Lu L, Goldowitz D, Gage FH, Goodwin S, Smit AB, Airey DC, Rosen GD, Schalkwyk LC, Sutter TR, Nowakowski RS, Whatley S, Williams RW (2009) Genetics of the hippocampal transcriptome in mice: a systematic survey and online neurogenomic resource. Front. Neurogen. 1:3 Full Text HTML doi:10.3389/neuro.15.003.2009
diff --git a/general/datasets/Hc_m2_0606_r/contributors.rtf b/general/datasets/Hc_m2_0606_r/contributors.rtf
new file mode 100644
index 0000000..4108279
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_r/contributors.rtf
@@ -0,0 +1,46 @@
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
diff --git a/general/datasets/Hc_m2_0606_r/experiment-design.rtf b/general/datasets/Hc_m2_0606_r/experiment-design.rtf
new file mode 100644
index 0000000..356f1d2
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_r/experiment-design.rtf
@@ -0,0 +1 @@
+Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2_0606_r/notes.rtf b/general/datasets/Hc_m2_0606_r/notes.rtf
new file mode 100644
index 0000000..9c11719
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_r/notes.rtf
@@ -0,0 +1,12 @@
+This study includes the following datasets:
+
+
+ - Hippocampus Consortium M430v2 CXB (Oct05) MAS5
+ - Hippocampus Consortium M430v2 CXB (Oct05) RMA
+ - Hippocampus Consortium M430v2 CXB (Oct05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) RMA
+ - Hippocampus Consortium M430v2 (Jun06) RMA
+ - Hippocampus Consortium M430v2 (Jun06) MAS5
+ - Hippocampus Consortium M430v2 (Jun06) PDNN
+
diff --git a/general/datasets/Hc_m2_0606_r/platform.rtf b/general/datasets/Hc_m2_0606_r/platform.rtf
new file mode 100644
index 0000000..6c99bee
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_r/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2_0606_r/processing.rtf b/general/datasets/Hc_m2_0606_r/processing.rtf
new file mode 100644
index 0000000..3698a7b
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_r/processing.rtf
@@ -0,0 +1,37 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very sensitive to the transformation method that is used. Using the PDNN transform, the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For example, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one would include the sample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the probe level (CEL) data after step 5 below. DataDesk allows the rapid detection of subsets of probes that are particularly sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - We performed a quantile normalization of the log base 2 values for all arrays using the same initial steps used by the RMA transform.
+ - We computed the Z scores for each cell value.
+ - We multiplied all Z scores by 2.
+ - We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level (probe brightness level) corresponds approximately to a 1 unit difference.
+ - Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data from the CHP file: The expression values were generated using PDNN. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1 unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2_0606_r/summary.rtf b/general/datasets/Hc_m2_0606_r/summary.rtf
new file mode 100644
index 0000000..1e86e54
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_r/summary.rtf
@@ -0,0 +1,3 @@
+MOST HIGHLY RECOMMENDED DATA SET (Overall et al., 2009): The Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of 99 genetically diverse strains of mice including 67 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a diverse set of common inbred strains, and two reciprocal F1 hybrids.
+
+The hippocampus is an important and intriguing part of the forebrain that is crucial in memory formation and retrieval, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section.
diff --git a/general/datasets/Hc_m2_0606_r/tissue.rtf b/general/datasets/Hc_m2_0606_r/tissue.rtf
new file mode 100644
index 0000000..bcea7b0
--- /dev/null
+++ b/general/datasets/Hc_m2_0606_r/tissue.rtf
@@ -0,0 +1,3721 @@
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thank Muriel Davisson for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below). All animals were sacrifice between 9 AM and 5 PM during the light phase.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+RNA Extraction: In brief, we used the RNA STAT-60 protocol (TEL-TEST "B" Bulletin No. 1), steps 5.1A (homogenization of tissue), 5.2 (RNA extraction), 5.3 (RNA precipitation), and 5.4 (RNA wash). In Step 5.4 we stopped after adding 75% ethanol (1 ml per 1 ml RNA STAT-60) and stored the mix at -80°C until further use. Before RNA labeling we thawed samples and proceeded with the remainder of Step 5.4; pelleting, drying, and redissolving the pellet in RNase-free water.
+
+We finally purify RNA by using Na4OAc before running arrays. Here is the detailed method:
+
+Final RNA purification protocol
+
+
+ - Add 1/10th volume of 3M Na4OAc , pH 5.2. If the sample was eluted with 100 µl nuclease-free water as suggested, this will be 10 µl of 3M Na4OAc.
+ - Add 2.5 volumes of 100% ethanol (250 µl if the RNA was eluted in100 µl). Mix well and incubate at –20°C for 2 hrs.
+ - Centrifuge at speed of 13,000 rpm for 20 min at 4°C. Carefully remove and discard the supernatant.
+ - Wash the pellet with 800 µl 75% cold ethanol, centrifuge at speed of 8,600 rpm for 5 min, and remove the 75% ethanol. Wash again.
+ - To remove the last traces of ethanol, quickly respin the tube, and aspirate any residual fluid.
+ - Air dry the pellet.
+ - Resuspend pellet in nuclease-free water.
+
+
+
+
+5. PROTOCOL: RNA/mRNA isolation by the RNA STAT-60 method includes the following steps:
+1. Homogenization RNA STAT-60TM (1 ml per 50-100 mg tissue, or 5-10 x 10-6 cells)
+2. RNA Extraction 1 vol. of homogenate +0.2 vol. of chloroform
+3. RNA Precipitation 0.5 vol. of isopropanol
+4. RNA Wash 75% ethanol
+
+Unless stated otherwise the procedure is carried out at room temperature.
+
+5.1 HOMOGENIZATION
+
+A. TISSUES: Homogenize tissues samples in the RNA STAT-60(1 ml/50-100mg tissue) in a glass-Teflon or Polytron homogenizer. Sample volume should not exceed 10% of the volume of the RNA STAT-60 used for homogenization.
+
+B. CELLS: Cells grown in mono layer are lysed directly in a culture dish by adding the RNA STAT-60TM (1 ml/3.5 cm petri dish) and passing the cell lysate several times through a pipette. Cells grown in suspension are sediment then lysed in the RNA STAT-60TM (1 ml per 5-10 x 106 cells) by repetitive pipetting. Washing calls before addition of the RNA STAT-60TM should be avoided as this increases the possibility of mRNA degradation.
+
+5.2 RNA EXTRACTION: Following homogenization, store the homogenate for 5 min at room temp to permit the complete dissociation of nucleoprotein complexes. Next, add 0.2 ml of chloroform per 1 ml of the RNA STAT-60, cover the sample tightly, shake vigorously for 15 seconds and let it stay at room temperature for 2-3minutes. Centrifuge the homogenate at 12,000g (max) for 15 minutes at 4°C. Following centrifugation, the homogenate separates into two phases: a lower red phenol chloroform phase and the colorless upper aqueous phase. RNA remains exclusively in the aqueous phase whereas DNA and proteins are in the interferes and organic phase. The volume of the aqueous phase is about 60% of the volume of RNA STAT-60 used for homogenization.
+
+5.3 RNA PRECIPITATION: Transfer the aqueous phase to a fresh tube and mix with isopropanol. Add 0.5 ml of isopropanol per 1 ml of the RNA STAT-60 used for homogenization. Store samples at room temp for 5-10 minutes and centrifuge at 12,000g (max.) for 10 min at 4°C. RNA precipitate (often visible before centrifugation) forms a white pellet at the bottom of the tube.
+
+5.4 RNA WASH: Remove supernatant and wash the RNA pellet once with 75% ethanol by vortexing and subsequent centrifugation at 7,500g (max.) for 5 min at 4°C. Add at least 1 ml of 75% ethanol per 1 ml of the RNA STAT-60 used for the initial homogenization.
+
+At the end of the procedure, dry the RNA pellet briefly by air-drying or in a vacuum (5-10 min.). It is important not to let the RNA pellet dry completely as it will greatly decrease its solubility. Do not use the Speed-Vac for drying. Dissolve the RNA pellet in water or in 1 mm EDTA, pH 7, or 0.5% SDS solution. Vortex or pass the pellet a few times through a pipette tip. An incubation for 10-15 minutes at 55-60oC may be required to dissolve RNA samples. Diethylpyrocarbonate (DEPC) treated RNase-free solutions1 should be used for solubilization of RNA.
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80°C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: Our goal was to obtain a male sample pool and female sample pool from each isogenic group. While almost all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. All but 5 of 99 strains (BXD55, BXD86, BXD94, BALB/cByJ, and CAST/EiJ) are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquots R1291H3 and R1291H4).
+
+
+
+Sex Balance: Based on the expression of Xist, probe set 1427262_at, DBA/2J and KK/HlJ are represented only by female samples, BXD55, and BALB/cByJ are only represented by a single male sample, BXD74 is represented by two male samples, and BXD86, BXD94, and CAST/EiJ are possibly mixed sex samples. One of the BXD9 samples, array R1523, may be a mixed sex sample pool because the expression of Xist is intermediate.
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays. Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4°C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+COMPARISON with December 2005 Data Set: Both BXD14 arrays in the Dec05 data set were found to actually be from BXD23 cases. This error of strain identification has been corrected in the present data set. Four arrays in the Dec05 data set have been deleted because we judged them to be of poor quality (strain_sex_sample_firstreaction_group):
+
+
+ - BXD21_F_1_1_G1
+ - BXD23_M_1_1_G7
+ - BXD36_M_1_1_G2
+ - BXD36_F_1_1_G3
+
+
+In the Dec05 data set there are a total of 1986 transcripts with QTLs that have LRS scores above 50, whereas in the corrected June06 data sets there are a total of 2074 transcripts with QTLs above 50.
+
+Data Table 1:
+
+This table lists all arrays by file order (Index), tube/sample ID, age, sex, batch, and numbers of animals in each sample pool (pool size). The next columns (RMA outlier, scale factor, background average, present, absent, marginal, AFFY-b-ActinMur(3'/5'), AFFY-GapdhMur(3'/5')) are all Affymetrix QC data. Finally, source lists the source colony of the animals. (Final version, fully corrected, by Arthur Centeno, October 2008)
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool size |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 2 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 3 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M technical duplicate of above |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 4 |
+ R2045H2 |
+ D2B6F1 |
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+ 1 |
+ 2 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 5 |
+ R1595H2 |
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+ 5 |
+ 3 |
+ 0.06 |
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+ UTM RW |
+
+
+ | 6 |
+ R1551H1 |
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+ 72 |
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+ 6 |
+ 3 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 7 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 8 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
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+ UTM RW |
+
+
+ | 9 |
+ R1449H2 |
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+ 71 |
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+ 5 |
+ 3 |
+ 0.09 |
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+
+
+ | 10 |
+ R1290H2 |
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+ 63 |
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+ 7 |
+ 2 |
+ 0.04 |
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+
+
+ | 11 |
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+ 5 |
+ 3 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 12 |
+ R1507H1 |
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+ 3 |
+ 3 |
+ 0.02 |
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+
+
+ | 13 |
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+ 7 |
+ 3 |
+ 0.03 |
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+
+
+ | 14 |
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+ 4 |
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+
+
+ | 15 |
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+ 1 |
+ 4 |
+ 0.01 |
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+
+
+ | 16 |
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+ 1 |
+ 4 |
+ 0 |
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+
+
+ | 17 |
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+ 3 |
+ 2 |
+ 0.07 |
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+
+
+ | 18 |
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+ 1 |
+ 4 |
+ 0 |
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+
+ | 19 |
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+ 4 |
+ 3 |
+ 0.01 |
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+
+
+ | 20 |
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+ 56 |
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+ 1 |
+ 3 |
+ 0 |
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+
+ | 21 |
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+ 6 |
+ 3 |
+ 0.07 |
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+
+
+ | 22 |
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+ 86 |
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+ 1 |
+ 3 |
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+
+
+ | 23 |
+ R1523H3 |
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+ 3 |
+ 0.14 |
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+ UTM RW |
+
+
+ | 24 |
+ R1531H1 |
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+ 6 |
+ 3 |
+ 0.06 |
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+
+ | 25 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+ | 26 |
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+ 1 |
+ 3 |
+ 0 |
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+
+ | 27 |
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+ 7 |
+ 3 |
+ 0.03 |
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+
+ | 28 |
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+ 3 |
+ 0.05 |
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+ 2 |
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+
+
+ | 29 |
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+ 1 |
+ 3 |
+ 0.03 |
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+
+ | 30 |
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+ 7 |
+ 3 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 31 |
+ R1278H2 |
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+ 7 |
+ 3 |
+ 0.06 |
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+ UTM RW |
+
+
+ | 32 |
+ R1524H1 |
+ BXD15 |
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+ 6 |
+ 4 |
+ 0.02 |
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+
+
+ | 33 |
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+ 1 |
+ 3 |
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+
+ | 34 |
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+ 1 |
+ 3 |
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+
+ | 35 |
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+ 0.03 |
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+
+ | 36 |
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+ 3 |
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+
+
+ | 37 |
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+ 1 |
+ 3 |
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+
+
+ | 38 |
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+ 3 |
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+
+ | 39 |
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+ 3 |
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+
+ | 40 |
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+
+
+ | 41 |
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+ 0 |
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+
+
+ | 42 |
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+ 4 |
+ 0.02 |
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+
+ | 43 |
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+
+
+ | 44 |
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+ 3 |
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+
+
+ | 45 |
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+ 0.1 |
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+
+
+ | 46 |
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+
+
+ | 47 |
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+
+ | 48 |
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+
+ | 49 |
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+ 3 |
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+
+ | 50 |
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+
+
+ | 51 |
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+
+
+ | 52 |
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+
+
+ | 53 |
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+
+
+ | 54 |
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+
+
+ | 55 |
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+ 4 |
+ 0.1 |
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+
+
+ | 56 |
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+
+
+ | 57 |
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+
+
+ | 58 |
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+
+
+ | 59 |
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+
+
+ | 60 |
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+
+
+ | 61 |
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+
+
+ | 62 |
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+
+
+ | 63 |
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+ 2 |
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+
+
+ | 64 |
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+ 3 |
+ 0.03 |
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+
+
+ | 65 |
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+ 3 |
+ 0.03 |
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+
+
+ | 66 |
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+ 0 |
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+
+
+ | 67 |
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+ 3 |
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+ UMemphis |
+
+
+ | 68 |
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+ 3 |
+ 0.07 |
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+ Glenn |
+
+
+ | 69 |
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+ 4 |
+ 0.03 |
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+
+
+ | 70 |
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+ 1 |
+ 3 |
+ 0 |
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+ 0.017 |
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+ 2.06 |
+ UTM RW |
+
+
+ | 71 |
+ R1303H1 |
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+ 63 |
+ M |
+ 3 |
+ 4 |
+ 0.02 |
+ 3.497 |
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+ 0.8 |
+ UTM RW |
+
+
+ | 72 |
+ R1326H1 |
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+ F |
+ 3 |
+ 4 |
+ 0 |
+ 3.412 |
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+ UTM RW |
+
+
+ | 73 |
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+ M |
+ 1 |
+ 3 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 74 |
+ R1403H2 |
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+ F |
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+ 2 |
+ 0.03 |
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+ Glenn |
+
+
+ | 75 |
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+ M |
+ 7 |
+ 4 |
+ 0.04 |
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+ 0.543 |
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+ UTM RW |
+
+
+ | 76 |
+ R1316H1 |
+ BXD48 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0 |
+ 2.445 |
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+ 0.73 |
+ UTM RW |
+
+
+ | 77 |
+ R1575H3 |
+ BXD48 |
+ 65 |
+ M |
+ 3 |
+ 4 |
+ 0.05 |
+ 4.577 |
+ 55.78 |
+ 0.466 |
+ 0.514 |
+ 0.019 |
+ 1.59 |
+ 0.9 |
+ UTM RW |
+
+
+ | 78 |
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+ 6 |
+ 4 |
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+ UTM RW |
+
+
+ | 79 |
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+ 81 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 80 |
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+ 66 |
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+ 3 |
+ 3 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 81 |
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+ 71 |
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+ 6 |
+ 4 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 82 |
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+ 65 |
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+ 7 |
+ 3 |
+ 0.07 |
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+
+
+ | 83 |
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+ 60 |
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+ 4 |
+ 3 |
+ 0.01 |
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+
+
+ | 84 |
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+ 59 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 85 |
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+ 70 |
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+ 7 |
+ 4 |
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+
+
+ | 86 |
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+ 94 |
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+ 1 |
+ 2 |
+ 0 |
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+
+
+ | 87 |
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+ 54 |
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+ 1 |
+ 4 |
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+
+
+ | 88 |
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+ 6 |
+ 4 |
+ 0.01 |
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+
+
+ | 89 |
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+ 1 |
+ 3 |
+ 0.02 |
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+
+
+ | 90 |
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+ 6 |
+ 3 |
+ 0.02 |
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+
+
+ | 91 |
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+ 1 |
+ 3 |
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+
+
+ | 92 |
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+ 3 |
+ 4 |
+ 0.01 |
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+
+
+ | 93 |
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+ 1 |
+ 2 |
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+
+
+ | 94 |
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+ 6 |
+ 2 |
+ 0 |
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+
+
+ | 95 |
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+ 1 |
+ 4 |
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+
+
+ | 96 |
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+ 4 |
+ 2 |
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+
+
+ | 97 |
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+ 6 |
+ 3 |
+ 0.01 |
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+
+
+ | 98 |
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+ 1 |
+ 4 |
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+
+
+ | 99 |
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+ 5 |
+ 3 |
+ 0.02 |
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+
+
+ | 100 |
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+ 2 |
+ 2 |
+ 0.01 |
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+
+
+ | 101 |
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+ 2 |
+ 3 |
+ 0.02 |
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+
+
+ | 102 |
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+ 3 |
+ 3 |
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+
+
+ | 103 |
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+ 5 |
+ 2 |
+ 0.02 |
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+
+
+ | 104 |
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+ 2 |
+ 3 |
+ 0.02 |
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+
+
+ | 105 |
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+ 4 |
+ 2 |
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+
+
+ | 106 |
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+ 2 |
+ 3 |
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+
+
+ | 107 |
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+ 2 |
+ 3 |
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+
+
+ | 108 |
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+ 2 |
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+
+
+ | 109 |
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+ 3 |
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+
+
+ | 110 |
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+ 3 |
+ 4 |
+ 0.01 |
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+
+
+ | 111 |
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+ 3 |
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+
+
+ | 112 |
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+
+
+ | 113 |
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+
+
+ | 114 |
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+
+
+ | 115 |
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+ 2 |
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+
+
+ | 116 |
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+
+
+ | 117 |
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+
+
+ | 118 |
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+
+
+ | 119 |
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+
+
+ | 120 |
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+
+
+ | 121 |
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+ 0 |
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+
+
+ | 122 |
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+ 2 |
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+
+
+ | 123 |
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+
+
+ | 124 |
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+ 3 |
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+
+
+ | 125 |
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+
+
+ | 126 |
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+
+
+ | 127 |
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+
+
+ | 128 |
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+
+
+ | 129 |
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+ 2 |
+ 0.02 |
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+
+
+ | 130 |
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+ 4 |
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+
+
+ | 131 |
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+ 3 |
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+
+
+ | 132 |
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+ 4 |
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+
+
+ | 133 |
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+
+
+ | 134 |
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+ 3 |
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+
+
+ | 135 |
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+ 3 |
+ 0.02 |
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+
+
+ | 136 |
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+ 3 |
+ 0 |
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+
+
+ | 137 |
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+ 0 |
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+
+
+ | 138 |
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+ 2 |
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+
+
+ | 139 |
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+ 3 |
+ 0 |
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+
+
+ | 140 |
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+
+
+ | 141 |
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+ 3 |
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+
+
+ | 142 |
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+ 3 |
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+
+
+ | 143 |
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+ 3 |
+ 0.02 |
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+
+
+ | 144 |
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+ 3 |
+ 0.02 |
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+
+
+ | 145 |
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+ 2 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 146 |
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+ 3 |
+ 0.1 |
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+
+
+ | 147 |
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+ 3 |
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+
+
+ | 148 |
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+ 3 |
+ 0.04 |
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+ UTM RW |
+
+
+ | 149 |
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+ 5 |
+ 2 |
+ 0.06 |
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+ UTM RW |
+
+
+ | 150 |
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+ 5 |
+ 3 |
+ 0.04 |
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+ JAX |
+
+
+ | 151 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 152 |
+ R1675H1 |
+ BALB/cByJ |
+ 83 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.405 |
+ 48.13 |
+ 0.509 |
+ 0.474 |
+ 0.018 |
+ 1.13 |
+ 0.78 |
+ JAX |
+
+
+ | 153 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 154 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 155 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 156 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 157 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 158 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 159 |
+ R2673H1 |
+ C57BL/6ByJ |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.08 |
+ 1.842 |
+ 67.69 |
+ 0.514 |
+ 0.469 |
+ 0.017 |
+ 1.75 |
+ 0.78 |
+ JAX |
+
+
+ | 160 |
+ R2619H1 |
+ CAST/EiJ |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 161 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 162 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 163 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 164 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 165 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 166 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 167 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 168 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 169 |
+ R2677H1 |
+ PWD/PhJ |
+ 65 |
+ M |
+ 7 |
+ 2 |
+ 0.12 |
+ 2.764 |
+ 65.49 |
+ 0.462 |
+ 0.52 |
+ 0.018 |
+ 1.89 |
+ 1.16 |
+ UTM RW |
+
+
+ | 170 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 171 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 172 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 173 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 174 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+ | 175 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 176 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 177 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 178 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 179 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 180 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 181 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 182 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 183 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 184 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 185 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 186 |
+ R2676H1 |
+ CXB6 |
+ 47 |
+ F |
+ 7 |
+ 2 |
+ 0.05 |
+ 2.146 |
+ 62.51 |
+ 0.507 |
+ 0.475 |
+ 0.018 |
+ 1.52 |
+ 0.78 |
+ JAX |
+
+
+ | 187 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 188 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 189 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 190 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 191 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 192 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 193 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 194 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 195 |
+ R2671H1 |
+ CXB10 |
+ 53 |
+ M |
+ 7 |
+ 3 |
+ 0.09 |
+ 2.348 |
+ 71.45 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 2.2 |
+ 1.14 |
+ JAX |
+
+
+ | 196 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 197 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 198 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 199 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 200 |
+ R2672H1 |
+ CXB13 |
+ 49 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.722 |
+ 79.52 |
+ 0.516 |
+ 0.465 |
+ 0.019 |
+ 1.64 |
+ 0.75 |
+ JAX |
+
+
+ | 201 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hc_m2_1005_m/acknowledgment.rtf b/general/datasets/Hc_m2_1005_m/acknowledgment.rtf
new file mode 100644
index 0000000..08c9160
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_m/acknowledgment.rtf
@@ -0,0 +1,54 @@
+
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: NIH XXXX
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Yanhua Qu, Ph.D.
+ Grant Support: NIH U01CA105417
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
+
diff --git a/general/datasets/Hc_m2_1005_m/cases.rtf b/general/datasets/Hc_m2_1005_m/cases.rtf
new file mode 100644
index 0000000..3e78bb4
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_m/cases.rtf
@@ -0,0 +1,60 @@
+This analysis has used 68 of BXD strains, the complete set of 13 CXB recombinant inbred strain sets, and a mouse diversity panel consisting of 16 inbred strains and a pair of reciprocal F1 hybrids (B6D2F1 and D2B6F1).
+
+The BXD genetic reference population of recombinant inbred strains consists of approximately 80 strains. Approximately 800 classical phenotypes from sets of 10 to 70 of these strains been integrated in the GeneNetwork. The BXD strains in this data set include 29 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD40). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+The CXB is the first and oldest set of recombinant inbred strains. Over 500 classical phenotypes from these strains been integrated in the GeneNetwork. It is noteworthy that the CXB strains segregate for the hippocampal lamination defect (Hld),characterized by Nowakowski and colleagues (1984). All of the CXBs have been recently genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ STILL IN PROGRESS (samples did not pass quality control); Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HIJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HILtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2_1005_m/experiment-design.rtf b/general/datasets/Hc_m2_1005_m/experiment-design.rtf
new file mode 100644
index 0000000..68713a4
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_m/experiment-design.rtf
@@ -0,0 +1,3252 @@
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80 deg. C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each isogenic group. While all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. Seventy-seven of 99 strains are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquotes R1291H3 and R1291H4).
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays.Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4 deg C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+
+ Data Table 1:
+
+
+This table lists all arrays by order of processing (Run), Sample ID, Strain, Sex, Age, number of animals in each sample pool (Pool), F generation number when less than 30 (GenN, and the Source of animals. SampleID is the ID number of the pooled RNA sample with a H1 through H3 suffix to indicate the actual hippocampal RNA aliquot used to prepare cRNA. Grp is the sequential group processing number (1 - 6).
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool sizel |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R2028H2 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 4.362 |
+ 64.49 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 2.78 |
+ 1.13 |
+ JAX |
+
+
+ | 2 |
+ R2029H2 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.04 |
+ 5.208 |
+ 41.21 |
+ 0.49 |
+ 0.49 |
+ 0.02 |
+ 1.62 |
+ 0.95 |
+ JAX |
+
+
+ | 3 |
+ R2030H1 |
+ A/J |
+ 57 |
+ M |
+ 5 |
+ 2 |
+ 0.06 |
+ 3.307 |
+ 45.16 |
+ 0.527 |
+ 0.454 |
+ 0.018 |
+ 1.63 |
+ 0.99 |
+ UTM RW |
+
+
+ | 4 |
+ R2032H3 |
+ AKR/J |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.054 |
+ 61.03 |
+ 0.51 |
+ 0.471 |
+ 0.018 |
+ 1.46 |
+ 0.79 |
+ JAX |
+
+
+ | 5 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 6 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 7 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 8 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 9 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 10 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 11 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 12 |
+ R1507H1 |
+ BXD1 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.056 |
+ 60.17 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.15 |
+ 0.76 |
+ Glenn |
+
+
+ | 13 |
+ R1520H1 |
+ BXD2 |
+ 56 |
+ F |
+ 4 |
+ 4 |
+ 0.09 |
+ 1.715 |
+ 71.62 |
+ 0.515 |
+ 0.467 |
+ 0.018 |
+ 2.36 |
+ 1.6 |
+ Glenn |
+
+
+ | 14 |
+ R1516H1 |
+ BXD2 |
+ 61 |
+ M |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.231 |
+ 64.86 |
+ 0.508 |
+ 0.474 |
+ 0.019 |
+ 1.3 |
+ 1.53 |
+ Glenn |
+
+
+ | 15 |
+ R1593H2 |
+ BXD5 |
+ 60 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 1.913 |
+ 59.96 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.98 |
+ 1.44 |
+ Glenn |
+
+
+ | 16 |
+ R1692H1 |
+ BXD5 |
+ 60 |
+ M |
+ 3 |
+ 2 |
+ 0.07 |
+ 3.764 |
+ 72.74 |
+ 0.465 |
+ 0.516 |
+ 0.02 |
+ 1.15 |
+ 0.74 |
+ Glenn |
+
+
+ | 17 |
+ R1539H2 |
+ BXD6 |
+ 59 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 2.488 |
+ 54.97 |
+ 0.518 |
+ 0.463 |
+ 0.018 |
+ 1.08 |
+ 1.33 |
+ Glenn |
+
+
+ | 18 |
+ R1538H1 |
+ BXD6 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.01 |
+ 2.585 |
+ 50.27 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 1.46 |
+ 0.79 |
+ Glenn |
+
+
+ | 19 |
+ R1518H1 |
+ BXD8 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 2.92 |
+ 54.84 |
+ 0.515 |
+ 0.465 |
+ 0.02 |
+ 1.32 |
+ 1.24 |
+ Glenn |
+
+
+ | 20 |
+ R1548H1 |
+ BXD8 |
+ 59 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.132 |
+ 59.37 |
+ 0.504 |
+ 0.477 |
+ 0.019 |
+ 2.16 |
+ 1.54 |
+ Glenn |
+
+
+ | 21 |
+ R1350H2 |
+ BXD9 |
+ 86 |
+ F |
+ 1 |
+ 3 |
+ 0.05 |
+ 2.771 |
+ 60.62 |
+ 0.5 |
+ 0.482 |
+ 0.018 |
+ 1.01 |
+ 1.28 |
+ UMemphis |
+
+
+ | 22 |
+ R1531H1 |
+ BXD11 |
+ 56 |
+ F |
+ 6 |
+ 3 |
+ 0.06 |
+ 2.229 |
+ 56.36 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 2.23 |
+ 1.02 |
+ Glenn |
+
+
+ | 23 |
+ R1367H1 |
+ BXD11 |
+ 56 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.11 |
+ 78.78 |
+ 0.503 |
+ 0.477 |
+ 0.02 |
+ 1.07 |
+ 1.27 |
+ Glenn |
+
+
+ | 24 |
+ R1530H1 |
+ BXD12 |
+ 58 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 3.227 |
+ 53.77 |
+ 0.505 |
+ 0.477 |
+ 0.018 |
+ 0.95 |
+ 1.4 |
+ Glenn |
+
+
+ | 25 |
+ R1529H1 |
+ BXD13 |
+ 58 |
+ F |
+ 6 |
+ 3 |
+ 0.05 |
+ 2.55 |
+ 59.05 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 2 |
+ 1.54 |
+ Glenn |
+
+
+ | 26 |
+ R1662H2 |
+ BXD13 |
+ 60 |
+ M |
+ 1 |
+ 3 |
+ 0.03 |
+ 4.603 |
+ 45.81 |
+ 0.509 |
+ 0.472 |
+ 0.019 |
+ 1.3 |
+ 0.82 |
+ Glenn |
+
+
+ | 27 |
+ R1524H1 |
+ BXD15 |
+ 60 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.961 |
+ 50.93 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 1.74 |
+ 0.91 |
+ Glenn |
+
+
+ | 28 |
+ R1515H1 |
+ BXD15 |
+ 61 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.316 |
+ 57.05 |
+ 0.503 |
+ 0.478 |
+ 0.019 |
+ 1.32 |
+ 1.21 |
+ Glenn |
+
+
+ | 29 |
+ R1661H1 |
+ BXD16 |
+ 61 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.778 |
+ 59.81 |
+ 0.516 |
+ 0.466 |
+ 0.019 |
+ 1.39 |
+ 1.2 |
+ Glenn |
+
+
+ | 30 |
+ R1594H1 |
+ BXD16 |
+ 61 |
+ M |
+ 4 |
+ 3 |
+ 0.03 |
+ 2.634 |
+ 53.66 |
+ 0.504 |
+ 0.478 |
+ 0.018 |
+ 1.96 |
+ 1.51 |
+ Glenn |
+
+
+ | 31 |
+ R1471H1 |
+ BXD19 |
+ 157 |
+ M |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.165 |
+ 43.34 |
+ 0.519 |
+ 0.462 |
+ 0.018 |
+ 1.01 |
+ 1.29 |
+ UTM JB |
+
+
+ | 32 |
+ R1573H1 |
+ BXD20 |
+ 59 |
+ F |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.749 |
+ 52.7 |
+ 0.513 |
+ 0.469 |
+ 0.018 |
+ 1.01 |
+ 1.27 |
+ Glenn |
+
+
+ | 33 |
+ R2507H1 |
+ BXD20 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.06 |
+ 3.568 |
+ 57 |
+ 0.472 |
+ 0.508 |
+ 0.02 |
+ 1.29 |
+ 0.76 |
+ Glenn |
+
+
+ | 34 |
+ R1347H2 |
+ BXD21 |
+ 64 |
+ F |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.881 |
+ 61.49 |
+ 0.494 |
+ 0.486 |
+ 0.019 |
+ 0.92 |
+ 1.22 |
+ UMemphis |
+
+
+ | 35 |
+ R1337H2 |
+ BXD21 |
+ 102 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.673 |
+ 58.05 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.4 |
+ 0.76 |
+ UAB |
+
+
+ | 36 |
+ R1848H3 |
+ BXD22 |
+ 196 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.943 |
+ 51.7 |
+ 0.494 |
+ 0.485 |
+ 0.021 |
+ 2.2 |
+ 0.78 |
+ UAB |
+
+
+ | 37 |
+ R1525H1 |
+ BXD22 |
+ 59 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.248 |
+ 55.76 |
+ 0.548 |
+ 0.433 |
+ 0.018 |
+ 1.26 |
+ 0.74 |
+ Glenn |
+
+
+ | 38 |
+ R1280H2 |
+ BXD23 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.187 |
+ 54.63 |
+ 0.458 |
+ 0.523 |
+ 0.019 |
+ 0.96 |
+ 1.2 |
+ UTM RW |
+
+
+ | 39 |
+ R1537H1 |
+ BXD23 |
+ 58 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.719 |
+ 67.54 |
+ 0.468 |
+ 0.513 |
+ 0.019 |
+ 1.51 |
+ 0.96 |
+ Glenn |
+
+
+ | 40 |
+ R1343H2 |
+ BXD24 |
+ 71 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.083 |
+ 65.07 |
+ 0.506 |
+ 0.474 |
+ 0.019 |
+ 1.46 |
+ 0.75 |
+ UMemphis |
+
+
+ | 41 |
+ R1517H1 |
+ BXD24 |
+ 57 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.471 |
+ 53.66 |
+ 0.504 |
+ 0.476 |
+ 0.019 |
+ 1.28 |
+ 0.78 |
+ Glenn |
+
+
+ | 42 |
+ R1366H1 |
+ BXD27 |
+ 60 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.26 |
+ 48.46 |
+ 0.518 |
+ 0.463 |
+ 0.019 |
+ 1.29 |
+ 0.77 |
+ Glenn |
+
+
+ | 43 |
+ R1849H1 |
+ BXD27 |
+ 70 |
+ M |
+ 5 |
+ 3 |
+ 0.06 |
+ 8.801 |
+ 38.34 |
+ 0.468 |
+ 0.512 |
+ 0.019 |
+ 2.42 |
+ 1.08 |
+ UAB |
+
+
+ | 44 |
+ R1353H1 |
+ BXD28 |
+ 79 |
+ F |
+ 3 |
+ 4 |
+ 0.01 |
+ 3.22 |
+ 76.22 |
+ 0.48 |
+ 0.5 |
+ 0.02 |
+ 1.33 |
+ 0.78 |
+ UMemphis |
+
+
+ | 45 |
+ R2332H1 |
+ BXD28 |
+ 60 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 3.217 |
+ 63.68 |
+ 0.491 |
+ 0.49 |
+ 0.019 |
+ 1.37 |
+ 0.79 |
+ Glenn |
+
+
+ | 46 |
+ R1532H1 |
+ BXD29 |
+ 57 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.122 |
+ 59.18 |
+ 0.524 |
+ 0.456 |
+ 0.019 |
+ 1.17 |
+ 0.76 |
+ Glenn |
+
+
+ | 47 |
+ R1356H1 |
+ BXD29 |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.01 |
+ 4.033 |
+ 47.67 |
+ 0.52 |
+ 0.463 |
+ 0.017 |
+ 1.17 |
+ 0.78 |
+ UMemphis |
+
+
+ | 48 |
+ R1240H2 |
+ BXD31 |
+ 61 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.335 |
+ 65.17 |
+ 0.507 |
+ 0.474 |
+ 0.019 |
+ 1.31 |
+ 0.78 |
+ UTM RW |
+
+
+ | 49 |
+ R1508H2 |
+ BXD32 |
+ 58 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 1.917 |
+ 67.78 |
+ 0.539 |
+ 0.442 |
+ 0.019 |
+ 1.28 |
+ 0.73 |
+ Glenn |
+
+
+ | 50 |
+ R1345H3 |
+ BXD33 |
+ 65 |
+ F |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.098 |
+ 63.14 |
+ 0.522 |
+ 0.459 |
+ 0.019 |
+ 1.27 |
+ 0.73 |
+ UMemphis |
+
+
+ | 51 |
+ R1581H1 |
+ BXD33 |
+ 59 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.229 |
+ 53.16 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.19 |
+ 0.78 |
+ Glenn |
+
+
+ | 52 |
+ R1527H1 |
+ BXD34 |
+ 59 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.3 |
+ 58.92 |
+ 0.51 |
+ 0.471 |
+ 0.019 |
+ 1.24 |
+ 0.76 |
+ Glenn |
+
+
+ | 53 |
+ R1339H3 |
+ BXD34 |
+ 74 |
+ M |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.888 |
+ 53.49 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 2.39 |
+ 1.35 |
+ UMemphis |
+
+
+ | 54 |
+ R1469H1 |
+ BXD36 |
+ 83 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 3.473 |
+ 49.9 |
+ 0.494 |
+ 0.486 |
+ 0.02 |
+ 1.11 |
+ 0.76 |
+ UMemphis |
+
+
+ | 55 |
+ R1363H1 |
+ BXD36 |
+ 77 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 2.184 |
+ 48.19 |
+ 0.538 |
+ 0.443 |
+ 0.02 |
+ 1.28 |
+ 0.77 |
+ UMemphis |
+
+
+ | 56 |
+ R1855H1 |
+ BXD38 |
+ 55 |
+ F |
+ 3 |
+ 4 |
+ 0.01 |
+ 3.536 |
+ 54.54 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.39 |
+ 0.75 |
+ Glenn |
+
+
+ | 57 |
+ R1510H1 |
+ BXD38 |
+ 59 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.186 |
+ 68.06 |
+ 0.521 |
+ 0.46 |
+ 0.019 |
+ 1.26 |
+ 0.79 |
+ Glenn |
+
+
+ | 58 |
+ R1528H2 |
+ BXD39 |
+ 59 |
+ F |
+ 2 |
+ 3 |
+ 0.03 |
+ 4.717 |
+ 38.3 |
+ 0.511 |
+ 0.47 |
+ 0.02 |
+ 1.12 |
+ 0.75 |
+ Glenn |
+
+
+ | 59 |
+ R1514H1 |
+ BXD39 |
+ 59 |
+ M |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.992 |
+ 56.06 |
+ 0.477 |
+ 0.504 |
+ 0.019 |
+ 1.43 |
+ 0.81 |
+ Glenn |
+
+
+ | 60 |
+ R1522H1 |
+ BXD40 |
+ 59 |
+ F |
+ 4 |
+ 4 |
+ 0 |
+ 2.631 |
+ 67.16 |
+ 0.49 |
+ 0.491 |
+ 0.018 |
+ 1.56 |
+ 0.77 |
+ Glenn |
+
+
+ | 61 |
+ R1359H1 |
+ BXD40 |
+ 73 |
+ M |
+ 2 |
+ 3 |
+ 0.09 |
+ 7.458 |
+ 39.86 |
+ 0.451 |
+ 0.527 |
+ 0.021 |
+ 1.28 |
+ 0.74 |
+ UMemphis |
+
+
+ | 62 |
+ R1334H2 |
+ BXD43 |
+ 59 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 2.672 |
+ 54.36 |
+ 0.492 |
+ 0.491 |
+ 0.017 |
+ 1.2 |
+ 2.06 |
+ UTM RW |
+
+
+ | 63 |
+ R1303H1 |
+ BXD43 |
+ 63 |
+ M |
+ 3 |
+ 4 |
+ 0.02 |
+ 3.497 |
+ 51.9 |
+ 0.486 |
+ 0.495 |
+ 0.019 |
+ 1.15 |
+ 0.8 |
+ UTM RW |
+
+
+ | 64 |
+ R1326H1 |
+ BXD44 |
+ 65 |
+ F |
+ 3 |
+ 4 |
+ 0 |
+ 3.412 |
+ 53.96 |
+ 0.496 |
+ 0.485 |
+ 0.018 |
+ 1.35 |
+ 0.78 |
+ UTM RW |
+
+
+ | 65 |
+ R1577H2 |
+ BXD44 |
+ 56 |
+ M |
+ 1 |
+ 3 |
+ 0.02 |
+ 2.159 |
+ 67.52 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.18 |
+ 1.71 |
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+
+
+ | 66 |
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+ 58 |
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+ 4 |
+ 3 |
+ 0 |
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+
+
+ | 67 |
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+ 65 |
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+ 3 |
+ 4 |
+ 0.05 |
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+ UTM RW |
+
+
+ | 68 |
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+ 63 |
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+ 6 |
+ 4 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 69 |
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+ 81 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 70 |
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+ 66 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+
+ | 71 |
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+ 6 |
+ 4 |
+ 0.03 |
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+
+
+ | 72 |
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+ 4 |
+ 3 |
+ 0.01 |
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+
+
+ | 73 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 74 |
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+ 1 |
+ 2 |
+ 0 |
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+
+
+ | 75 |
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+ 1 |
+ 4 |
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+
+
+ | 76 |
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+ 6 |
+ 4 |
+ 0.01 |
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+
+
+ | 77 |
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+ 1 |
+ 3 |
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+
+
+ | 78 |
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+ 6 |
+ 3 |
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+
+
+ | 79 |
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+ 1 |
+ 3 |
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+
+
+ | 80 |
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+ 3 |
+ 4 |
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+
+
+ | 81 |
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+ 1 |
+ 2 |
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+
+
+ | 82 |
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+ 6 |
+ 2 |
+ 0 |
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+
+
+ | 83 |
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+ 1 |
+ 4 |
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+
+
+ | 84 |
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+ 4 |
+ 2 |
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+
+
+ | 85 |
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+ 6 |
+ 3 |
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+
+
+ | 86 |
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+ 1 |
+ 4 |
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+
+
+ | 87 |
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+ 5 |
+ 3 |
+ 0.02 |
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+
+
+ | 88 |
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+ 2 |
+ 2 |
+ 0.01 |
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+
+
+ | 89 |
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+ 3 |
+ 0.02 |
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+
+
+ | 90 |
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+ 3 |
+ 3 |
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+
+
+ | 91 |
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+ 2 |
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+
+
+ | 92 |
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+ 2 |
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+
+
+ | 93 |
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+ 2 |
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+
+
+ | 94 |
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+
+
+ | 95 |
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+
+
+ | 96 |
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+
+
+ | 97 |
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+
+
+ | 98 |
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+
+
+ | 99 |
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+
+
+ | 100 |
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+
+
+ | 101 |
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+
+
+ | 102 |
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+
+
+ | 103 |
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+
+
+ | 104 |
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+
+ | 105 |
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+
+
+ | 106 |
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+
+
+ | 107 |
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+
+
+ | 108 |
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+
+
+ | 109 |
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+ 0 |
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+
+
+ | 110 |
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+
+
+ | 111 |
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+
+
+ | 112 |
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+
+
+ | 113 |
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+
+
+ | 114 |
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+
+
+ | 115 |
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+
+
+ | 116 |
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+ 2 |
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+
+
+ | 117 |
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+
+
+ | 118 |
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+
+
+ | 119 |
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+
+
+ | 120 |
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+ 3 |
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+
+
+ | 121 |
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+ 3 |
+ 0.02 |
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+
+
+ | 122 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 123 |
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+ 3 |
+ 0 |
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+
+
+ | 124 |
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+ 2 |
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+
+
+ | 125 |
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+ 3 |
+ 0 |
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+
+
+ | 126 |
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+ 3 |
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+
+
+ | 127 |
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+ 3 |
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+
+
+ | 128 |
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+ 3 |
+ 0.02 |
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+
+
+ | 129 |
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+ 3 |
+ 0.02 |
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+
+
+ | 130 |
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+ 2 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 131 |
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+ 3 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 132 |
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+ 3 |
+ 0.1 |
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+ UTM RW |
+
+
+ | 133 |
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+ 5 |
+ 3 |
+ 0.02 |
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+
+
+ | 134 |
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+ 6 |
+ 4 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 135 |
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+ 65 |
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+ 1 |
+ 4 |
+ 0.04 |
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+ UTM RW |
+
+
+ | 136 |
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+ 5 |
+ 3 |
+ 0.09 |
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+ UTM DG |
+
+
+ | 137 |
+ R2619H1 |
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+ 64 |
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+ 5 |
+ 3 |
+ 0.14 |
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+ JAX |
+
+
+ | 138 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 139 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 140 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 141 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 142 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 143 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 144 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 145 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+ | 146 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 147 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 148 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 149 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 150 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 151 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 152 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 153 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 154 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 155 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 156 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 157 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 158 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 159 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 160 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 161 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 162 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 163 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 2.579 |
+ 58.49 |
+ 0.506 |
+ 0.475 |
+ 0.019 |
+ 2.49 |
+ 1.21 |
+ UTM RW |
+
+
+ | 164 |
+ R1551H1 |
+ D2B6F1 |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.62 |
+ 53.76 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 1.37 |
+ 0.76 |
+ UTM RW |
+
+
+ | 165 |
+ R1468H1 |
+ DBA/2J |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.03 |
+ 2.929 |
+ 53.8 |
+ 0.515 |
+ 0.465 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 166 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 167 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 168 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 169 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 170 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 171 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 172 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 173 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 174 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 175 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 176 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 177 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 178 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Hc_m2_1005_m/notes.rtf b/general/datasets/Hc_m2_1005_m/notes.rtf
new file mode 100644
index 0000000..4490ee3
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_m/notes.rtf
@@ -0,0 +1,15 @@
+This study includes the following datasets:
+
+
+Hippocampus Consortium M430v2 (Oct05) MAS5
+
+Hippocampus Consortium M430v2 (Oct05) RMA
+
+Hippocampus Consortium M430v2 (Oct05) PDNN
+
+Hippocampus Consortium M430v2 (Dec05) RMA
+
+Hippocampus Consortium M430v2 (Dec05) PDNN
+
+
+This text file originally generated prospectively by RWW on July 30 2005. Updated by RWW July 31, 2005.
diff --git a/general/datasets/Hc_m2_1005_m/platform.rtf b/general/datasets/Hc_m2_1005_m/platform.rtf
new file mode 100644
index 0000000..af0948c
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_m/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2_1005_m/processing.rtf b/general/datasets/Hc_m2_1005_m/processing.rtf
new file mode 100644
index 0000000..df5513b
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_m/processing.rtf
@@ -0,0 +1,40 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very senstive to the transformation method that is used. Using the PDNN transform the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For examploe, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one whould include the ssample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the of the probe level (CEL) data after step 5 below. DataDesk allows a rapid detection of subsets of probes that are particular sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. <0L>
+
+
+
+
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2_1005_m/summary.rtf b/general/datasets/Hc_m2_1005_m/summary.rtf
new file mode 100644
index 0000000..9b7c1d6
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_m/summary.rtf
@@ -0,0 +1 @@
+PRELIMINARY: The October 2005 Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of approximately 99 genetically diverse strains of mice including 68 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a set of 16 diverse inbred strains, and 2 reciprocal F1 hybrids. The hippocampus is an important and intriguing part of the forebrain that is crucial for memory formation, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3, and parts of the subiculum) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section. Samples were processed using a total of 206 Affymetrix Mouse Expression 430 2.0 short oligomer microarrays (MOE430 2.0 or M430v2), of which 179 passed stringent quality control and error checking. This particular data set was processed using the MAS5 protocol. To simplify comparisons among transforms, MAS5 values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2_1005_m/tissue.rtf b/general/datasets/Hc_m2_1005_m/tissue.rtf
new file mode 100644
index 0000000..2bb700d
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_m/tissue.rtf
@@ -0,0 +1,7 @@
+
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thanks Muriel Davission for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below).
+
diff --git a/general/datasets/Hc_m2_1005_p/acknowledgment.rtf b/general/datasets/Hc_m2_1005_p/acknowledgment.rtf
new file mode 100644
index 0000000..08c9160
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_p/acknowledgment.rtf
@@ -0,0 +1,54 @@
+
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: NIH XXXX
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Yanhua Qu, Ph.D.
+ Grant Support: NIH U01CA105417
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
+
diff --git a/general/datasets/Hc_m2_1005_p/cases.rtf b/general/datasets/Hc_m2_1005_p/cases.rtf
new file mode 100644
index 0000000..3e78bb4
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_p/cases.rtf
@@ -0,0 +1,60 @@
+This analysis has used 68 of BXD strains, the complete set of 13 CXB recombinant inbred strain sets, and a mouse diversity panel consisting of 16 inbred strains and a pair of reciprocal F1 hybrids (B6D2F1 and D2B6F1).
+
+The BXD genetic reference population of recombinant inbred strains consists of approximately 80 strains. Approximately 800 classical phenotypes from sets of 10 to 70 of these strains been integrated in the GeneNetwork. The BXD strains in this data set include 29 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD40). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+The CXB is the first and oldest set of recombinant inbred strains. Over 500 classical phenotypes from these strains been integrated in the GeneNetwork. It is noteworthy that the CXB strains segregate for the hippocampal lamination defect (Hld),characterized by Nowakowski and colleagues (1984). All of the CXBs have been recently genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ STILL IN PROGRESS (samples did not pass quality control); Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HIJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HILtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2_1005_p/experiment-design.rtf b/general/datasets/Hc_m2_1005_p/experiment-design.rtf
new file mode 100644
index 0000000..68713a4
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_p/experiment-design.rtf
@@ -0,0 +1,3252 @@
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80 deg. C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each isogenic group. While all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. Seventy-seven of 99 strains are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquotes R1291H3 and R1291H4).
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays.Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4 deg C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+
+ Data Table 1:
+
+
+This table lists all arrays by order of processing (Run), Sample ID, Strain, Sex, Age, number of animals in each sample pool (Pool), F generation number when less than 30 (GenN, and the Source of animals. SampleID is the ID number of the pooled RNA sample with a H1 through H3 suffix to indicate the actual hippocampal RNA aliquot used to prepare cRNA. Grp is the sequential group processing number (1 - 6).
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool sizel |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R2028H2 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 4.362 |
+ 64.49 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 2.78 |
+ 1.13 |
+ JAX |
+
+
+ | 2 |
+ R2029H2 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.04 |
+ 5.208 |
+ 41.21 |
+ 0.49 |
+ 0.49 |
+ 0.02 |
+ 1.62 |
+ 0.95 |
+ JAX |
+
+
+ | 3 |
+ R2030H1 |
+ A/J |
+ 57 |
+ M |
+ 5 |
+ 2 |
+ 0.06 |
+ 3.307 |
+ 45.16 |
+ 0.527 |
+ 0.454 |
+ 0.018 |
+ 1.63 |
+ 0.99 |
+ UTM RW |
+
+
+ | 4 |
+ R2032H3 |
+ AKR/J |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.054 |
+ 61.03 |
+ 0.51 |
+ 0.471 |
+ 0.018 |
+ 1.46 |
+ 0.79 |
+ JAX |
+
+
+ | 5 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 6 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 7 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 8 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 9 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 10 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 11 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 12 |
+ R1507H1 |
+ BXD1 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.056 |
+ 60.17 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.15 |
+ 0.76 |
+ Glenn |
+
+
+ | 13 |
+ R1520H1 |
+ BXD2 |
+ 56 |
+ F |
+ 4 |
+ 4 |
+ 0.09 |
+ 1.715 |
+ 71.62 |
+ 0.515 |
+ 0.467 |
+ 0.018 |
+ 2.36 |
+ 1.6 |
+ Glenn |
+
+
+ | 14 |
+ R1516H1 |
+ BXD2 |
+ 61 |
+ M |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.231 |
+ 64.86 |
+ 0.508 |
+ 0.474 |
+ 0.019 |
+ 1.3 |
+ 1.53 |
+ Glenn |
+
+
+ | 15 |
+ R1593H2 |
+ BXD5 |
+ 60 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 1.913 |
+ 59.96 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.98 |
+ 1.44 |
+ Glenn |
+
+
+ | 16 |
+ R1692H1 |
+ BXD5 |
+ 60 |
+ M |
+ 3 |
+ 2 |
+ 0.07 |
+ 3.764 |
+ 72.74 |
+ 0.465 |
+ 0.516 |
+ 0.02 |
+ 1.15 |
+ 0.74 |
+ Glenn |
+
+
+ | 17 |
+ R1539H2 |
+ BXD6 |
+ 59 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 2.488 |
+ 54.97 |
+ 0.518 |
+ 0.463 |
+ 0.018 |
+ 1.08 |
+ 1.33 |
+ Glenn |
+
+
+ | 18 |
+ R1538H1 |
+ BXD6 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.01 |
+ 2.585 |
+ 50.27 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 1.46 |
+ 0.79 |
+ Glenn |
+
+
+ | 19 |
+ R1518H1 |
+ BXD8 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 2.92 |
+ 54.84 |
+ 0.515 |
+ 0.465 |
+ 0.02 |
+ 1.32 |
+ 1.24 |
+ Glenn |
+
+
+ | 20 |
+ R1548H1 |
+ BXD8 |
+ 59 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.132 |
+ 59.37 |
+ 0.504 |
+ 0.477 |
+ 0.019 |
+ 2.16 |
+ 1.54 |
+ Glenn |
+
+
+ | 21 |
+ R1350H2 |
+ BXD9 |
+ 86 |
+ F |
+ 1 |
+ 3 |
+ 0.05 |
+ 2.771 |
+ 60.62 |
+ 0.5 |
+ 0.482 |
+ 0.018 |
+ 1.01 |
+ 1.28 |
+ UMemphis |
+
+
+ | 22 |
+ R1531H1 |
+ BXD11 |
+ 56 |
+ F |
+ 6 |
+ 3 |
+ 0.06 |
+ 2.229 |
+ 56.36 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 2.23 |
+ 1.02 |
+ Glenn |
+
+
+ | 23 |
+ R1367H1 |
+ BXD11 |
+ 56 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.11 |
+ 78.78 |
+ 0.503 |
+ 0.477 |
+ 0.02 |
+ 1.07 |
+ 1.27 |
+ Glenn |
+
+
+ | 24 |
+ R1530H1 |
+ BXD12 |
+ 58 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 3.227 |
+ 53.77 |
+ 0.505 |
+ 0.477 |
+ 0.018 |
+ 0.95 |
+ 1.4 |
+ Glenn |
+
+
+ | 25 |
+ R1529H1 |
+ BXD13 |
+ 58 |
+ F |
+ 6 |
+ 3 |
+ 0.05 |
+ 2.55 |
+ 59.05 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 2 |
+ 1.54 |
+ Glenn |
+
+
+ | 26 |
+ R1662H2 |
+ BXD13 |
+ 60 |
+ M |
+ 1 |
+ 3 |
+ 0.03 |
+ 4.603 |
+ 45.81 |
+ 0.509 |
+ 0.472 |
+ 0.019 |
+ 1.3 |
+ 0.82 |
+ Glenn |
+
+
+ | 27 |
+ R1524H1 |
+ BXD15 |
+ 60 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.961 |
+ 50.93 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 1.74 |
+ 0.91 |
+ Glenn |
+
+
+ | 28 |
+ R1515H1 |
+ BXD15 |
+ 61 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.316 |
+ 57.05 |
+ 0.503 |
+ 0.478 |
+ 0.019 |
+ 1.32 |
+ 1.21 |
+ Glenn |
+
+
+ | 29 |
+ R1661H1 |
+ BXD16 |
+ 61 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.778 |
+ 59.81 |
+ 0.516 |
+ 0.466 |
+ 0.019 |
+ 1.39 |
+ 1.2 |
+ Glenn |
+
+
+ | 30 |
+ R1594H1 |
+ BXD16 |
+ 61 |
+ M |
+ 4 |
+ 3 |
+ 0.03 |
+ 2.634 |
+ 53.66 |
+ 0.504 |
+ 0.478 |
+ 0.018 |
+ 1.96 |
+ 1.51 |
+ Glenn |
+
+
+ | 31 |
+ R1471H1 |
+ BXD19 |
+ 157 |
+ M |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.165 |
+ 43.34 |
+ 0.519 |
+ 0.462 |
+ 0.018 |
+ 1.01 |
+ 1.29 |
+ UTM JB |
+
+
+ | 32 |
+ R1573H1 |
+ BXD20 |
+ 59 |
+ F |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.749 |
+ 52.7 |
+ 0.513 |
+ 0.469 |
+ 0.018 |
+ 1.01 |
+ 1.27 |
+ Glenn |
+
+
+ | 33 |
+ R2507H1 |
+ BXD20 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.06 |
+ 3.568 |
+ 57 |
+ 0.472 |
+ 0.508 |
+ 0.02 |
+ 1.29 |
+ 0.76 |
+ Glenn |
+
+
+ | 34 |
+ R1347H2 |
+ BXD21 |
+ 64 |
+ F |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.881 |
+ 61.49 |
+ 0.494 |
+ 0.486 |
+ 0.019 |
+ 0.92 |
+ 1.22 |
+ UMemphis |
+
+
+ | 35 |
+ R1337H2 |
+ BXD21 |
+ 102 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.673 |
+ 58.05 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.4 |
+ 0.76 |
+ UAB |
+
+
+ | 36 |
+ R1848H3 |
+ BXD22 |
+ 196 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.943 |
+ 51.7 |
+ 0.494 |
+ 0.485 |
+ 0.021 |
+ 2.2 |
+ 0.78 |
+ UAB |
+
+
+ | 37 |
+ R1525H1 |
+ BXD22 |
+ 59 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.248 |
+ 55.76 |
+ 0.548 |
+ 0.433 |
+ 0.018 |
+ 1.26 |
+ 0.74 |
+ Glenn |
+
+
+ | 38 |
+ R1280H2 |
+ BXD23 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.187 |
+ 54.63 |
+ 0.458 |
+ 0.523 |
+ 0.019 |
+ 0.96 |
+ 1.2 |
+ UTM RW |
+
+
+ | 39 |
+ R1537H1 |
+ BXD23 |
+ 58 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.719 |
+ 67.54 |
+ 0.468 |
+ 0.513 |
+ 0.019 |
+ 1.51 |
+ 0.96 |
+ Glenn |
+
+
+ | 40 |
+ R1343H2 |
+ BXD24 |
+ 71 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.083 |
+ 65.07 |
+ 0.506 |
+ 0.474 |
+ 0.019 |
+ 1.46 |
+ 0.75 |
+ UMemphis |
+
+
+ | 41 |
+ R1517H1 |
+ BXD24 |
+ 57 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.471 |
+ 53.66 |
+ 0.504 |
+ 0.476 |
+ 0.019 |
+ 1.28 |
+ 0.78 |
+ Glenn |
+
+
+ | 42 |
+ R1366H1 |
+ BXD27 |
+ 60 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.26 |
+ 48.46 |
+ 0.518 |
+ 0.463 |
+ 0.019 |
+ 1.29 |
+ 0.77 |
+ Glenn |
+
+
+ | 43 |
+ R1849H1 |
+ BXD27 |
+ 70 |
+ M |
+ 5 |
+ 3 |
+ 0.06 |
+ 8.801 |
+ 38.34 |
+ 0.468 |
+ 0.512 |
+ 0.019 |
+ 2.42 |
+ 1.08 |
+ UAB |
+
+
+ | 44 |
+ R1353H1 |
+ BXD28 |
+ 79 |
+ F |
+ 3 |
+ 4 |
+ 0.01 |
+ 3.22 |
+ 76.22 |
+ 0.48 |
+ 0.5 |
+ 0.02 |
+ 1.33 |
+ 0.78 |
+ UMemphis |
+
+
+ | 45 |
+ R2332H1 |
+ BXD28 |
+ 60 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 3.217 |
+ 63.68 |
+ 0.491 |
+ 0.49 |
+ 0.019 |
+ 1.37 |
+ 0.79 |
+ Glenn |
+
+
+ | 46 |
+ R1532H1 |
+ BXD29 |
+ 57 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.122 |
+ 59.18 |
+ 0.524 |
+ 0.456 |
+ 0.019 |
+ 1.17 |
+ 0.76 |
+ Glenn |
+
+
+ | 47 |
+ R1356H1 |
+ BXD29 |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.01 |
+ 4.033 |
+ 47.67 |
+ 0.52 |
+ 0.463 |
+ 0.017 |
+ 1.17 |
+ 0.78 |
+ UMemphis |
+
+
+ | 48 |
+ R1240H2 |
+ BXD31 |
+ 61 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.335 |
+ 65.17 |
+ 0.507 |
+ 0.474 |
+ 0.019 |
+ 1.31 |
+ 0.78 |
+ UTM RW |
+
+
+ | 49 |
+ R1508H2 |
+ BXD32 |
+ 58 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 1.917 |
+ 67.78 |
+ 0.539 |
+ 0.442 |
+ 0.019 |
+ 1.28 |
+ 0.73 |
+ Glenn |
+
+
+ | 50 |
+ R1345H3 |
+ BXD33 |
+ 65 |
+ F |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.098 |
+ 63.14 |
+ 0.522 |
+ 0.459 |
+ 0.019 |
+ 1.27 |
+ 0.73 |
+ UMemphis |
+
+
+ | 51 |
+ R1581H1 |
+ BXD33 |
+ 59 |
+ M |
+ 3 |
+ 3 |
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+
+
+ | 52 |
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+ 2 |
+ 3 |
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+
+
+ | 53 |
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+ 5 |
+ 3 |
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+
+
+ | 54 |
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+ 3 |
+ 3 |
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+
+
+ | 55 |
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+ 2 |
+ 4 |
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+
+
+ | 56 |
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+ 3 |
+ 4 |
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+
+
+ | 57 |
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+ 2 |
+ 3 |
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+
+
+ | 58 |
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+ 3 |
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+
+
+ | 59 |
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+ 3 |
+ 3 |
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+
+ | 60 |
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+ 4 |
+ 0 |
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+
+
+ | 61 |
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+ 2 |
+ 3 |
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+
+
+ | 62 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 63 |
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+ 3 |
+ 4 |
+ 0.02 |
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+
+
+ | 64 |
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+ 3 |
+ 4 |
+ 0 |
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+
+
+ | 65 |
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+ 1 |
+ 3 |
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+
+
+ | 66 |
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+ 4 |
+ 3 |
+ 0 |
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+
+
+ | 67 |
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+ 3 |
+ 4 |
+ 0.05 |
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+
+
+ | 68 |
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+ 6 |
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+
+
+ | 69 |
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+ 1 |
+ 3 |
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+
+
+ | 70 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+
+ | 71 |
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+ 6 |
+ 4 |
+ 0.03 |
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+
+
+ | 72 |
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+
+
+ | 73 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 74 |
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+ 1 |
+ 2 |
+ 0 |
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+
+
+ | 75 |
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+ 1 |
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+
+
+ | 76 |
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+
+
+ | 77 |
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+ 1 |
+ 3 |
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+
+
+ | 78 |
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+
+
+ | 79 |
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+
+
+ | 80 |
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+
+
+ | 81 |
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+
+
+ | 82 |
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+ 0 |
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+
+
+ | 83 |
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+ 1 |
+ 4 |
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+
+
+ | 84 |
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+
+
+ | 85 |
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+
+
+ | 86 |
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+
+
+ | 87 |
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+
+
+ | 88 |
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+
+
+ | 89 |
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+
+
+ | 90 |
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+
+
+ | 91 |
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+
+
+ | 92 |
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+
+
+ | 93 |
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+
+
+ | 94 |
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+
+
+ | 95 |
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+
+
+ | 96 |
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+
+
+ | 97 |
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+
+
+ | 98 |
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+
+
+ | 99 |
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+
+
+ | 100 |
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+
+
+ | 101 |
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+
+
+ | 102 |
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+
+
+ | 103 |
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+
+
+ | 104 |
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+
+
+ | 105 |
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+
+
+ | 106 |
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+
+
+ | 107 |
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+
+
+ | 108 |
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+
+
+ | 109 |
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+ 0 |
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+
+
+ | 110 |
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+
+
+ | 111 |
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+
+
+ | 112 |
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+ 3 |
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+
+
+ | 113 |
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+
+
+ | 114 |
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+
+
+ | 115 |
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+
+
+ | 116 |
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+ 2 |
+ 0.02 |
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+
+
+ | 117 |
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+ 4 |
+ 0.03 |
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+
+
+ | 118 |
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+ 3 |
+ 0.01 |
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+
+
+ | 119 |
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+ 3 |
+ 0.02 |
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+
+
+ | 120 |
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+ 3 |
+ 0.05 |
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+
+
+ | 121 |
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+ 3 |
+ 0.02 |
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+
+
+ | 122 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 123 |
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+ 3 |
+ 0 |
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+
+
+ | 124 |
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+ 2 |
+ 0.04 |
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+ 0.502 |
+ 0.481 |
+ 0.017 |
+ 1.37 |
+ 0.74 |
+ UTM RW |
+
+
+ | 125 |
+ R1846H2 |
+ BXD96 |
+ 63 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.159 |
+ 55.85 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.92 |
+ 1.26 |
+ UTM RW |
+
+
+ | 126 |
+ R1927H2 |
+ BXD97 |
+ 67 |
+ M |
+ 1 |
+ 3 |
+ 0.04 |
+ 2.622 |
+ 57.81 |
+ 0.539 |
+ 0.444 |
+ 0.017 |
+ 1.45 |
+ 1.32 |
+ UTM RW |
+
+
+ | 127 |
+ R1942H1 |
+ BXD98 |
+ 62 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.104 |
+ 48.42 |
+ 0.528 |
+ 0.454 |
+ 0.019 |
+ 2.22 |
+ 1.08 |
+ UTM RW |
+
+
+ | 128 |
+ R1943H2 |
+ BXD98 |
+ 62 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.04 |
+ 56.85 |
+ 0.484 |
+ 0.497 |
+ 0.019 |
+ 1.18 |
+ 0.76 |
+ UTM RW |
+
+
+ | 129 |
+ R2197H1 |
+ BXD99 |
+ 70 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.288 |
+ 51.75 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.35 |
+ 0.81 |
+ UTM RW |
+
+
+ | 130 |
+ R2315H1 |
+ BXD99 |
+ 84 |
+ M |
+ 5 |
+ 2 |
+ 0.03 |
+ 6.036 |
+ 43.05 |
+ 0.484 |
+ 0.497 |
+ 0.018 |
+ 1.7 |
+ 0.96 |
+ UTM RW |
+
+
+ | 131 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 132 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 133 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 134 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
+ 3.058 |
+ 51.87 |
+ 0.477 |
+ 0.503 |
+ 0.02 |
+ 1.67 |
+ 0.76 |
+ UTM RW |
+
+
+ | 135 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
+ 3.341 |
+ 49.26 |
+ 0.527 |
+ 0.456 |
+ 0.018 |
+ 1.14 |
+ 1.45 |
+ UTM RW |
+
+
+ | 136 |
+ R1449H2 |
+ C57BL/6J |
+ 71 |
+ M |
+ 5 |
+ 3 |
+ 0.09 |
+ 3.592 |
+ 44.32 |
+ 0.47 |
+ 0.51 |
+ 0.02 |
+ 1.68 |
+ 0.77 |
+ UTM DG |
+
+
+ | 137 |
+ R2619H1 |
+ CAST/Ei |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 138 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 139 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 140 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 141 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 142 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 143 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 144 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 145 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+ | 146 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 147 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 148 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 149 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 150 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 151 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 152 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 153 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 154 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 155 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 156 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 157 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 158 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 159 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 160 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 161 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 162 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 163 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 2.579 |
+ 58.49 |
+ 0.506 |
+ 0.475 |
+ 0.019 |
+ 2.49 |
+ 1.21 |
+ UTM RW |
+
+
+ | 164 |
+ R1551H1 |
+ D2B6F1 |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.62 |
+ 53.76 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 1.37 |
+ 0.76 |
+ UTM RW |
+
+
+ | 165 |
+ R1468H1 |
+ DBA/2J |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.03 |
+ 2.929 |
+ 53.8 |
+ 0.515 |
+ 0.465 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 166 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 167 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 168 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 169 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 170 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 171 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 172 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 173 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 174 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 175 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 176 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 177 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 178 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Hc_m2_1005_p/notes.rtf b/general/datasets/Hc_m2_1005_p/notes.rtf
new file mode 100644
index 0000000..4490ee3
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_p/notes.rtf
@@ -0,0 +1,15 @@
+This study includes the following datasets:
+
+
+Hippocampus Consortium M430v2 (Oct05) MAS5
+
+Hippocampus Consortium M430v2 (Oct05) RMA
+
+Hippocampus Consortium M430v2 (Oct05) PDNN
+
+Hippocampus Consortium M430v2 (Dec05) RMA
+
+Hippocampus Consortium M430v2 (Dec05) PDNN
+
+
+This text file originally generated prospectively by RWW on July 30 2005. Updated by RWW July 31, 2005.
diff --git a/general/datasets/Hc_m2_1005_p/platform.rtf b/general/datasets/Hc_m2_1005_p/platform.rtf
new file mode 100644
index 0000000..af0948c
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_p/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2_1005_p/processing.rtf b/general/datasets/Hc_m2_1005_p/processing.rtf
new file mode 100644
index 0000000..df5513b
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_p/processing.rtf
@@ -0,0 +1,40 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very senstive to the transformation method that is used. Using the PDNN transform the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For examploe, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one whould include the ssample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the of the probe level (CEL) data after step 5 below. DataDesk allows a rapid detection of subsets of probes that are particular sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. <0L>
+
+
+
+
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2_1005_p/summary.rtf b/general/datasets/Hc_m2_1005_p/summary.rtf
new file mode 100644
index 0000000..9b7c1d6
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_p/summary.rtf
@@ -0,0 +1 @@
+PRELIMINARY: The October 2005 Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of approximately 99 genetically diverse strains of mice including 68 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a set of 16 diverse inbred strains, and 2 reciprocal F1 hybrids. The hippocampus is an important and intriguing part of the forebrain that is crucial for memory formation, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3, and parts of the subiculum) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section. Samples were processed using a total of 206 Affymetrix Mouse Expression 430 2.0 short oligomer microarrays (MOE430 2.0 or M430v2), of which 179 passed stringent quality control and error checking. This particular data set was processed using the MAS5 protocol. To simplify comparisons among transforms, MAS5 values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2_1005_p/tissue.rtf b/general/datasets/Hc_m2_1005_p/tissue.rtf
new file mode 100644
index 0000000..2bb700d
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_p/tissue.rtf
@@ -0,0 +1,7 @@
+
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thanks Muriel Davission for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below).
+
diff --git a/general/datasets/Hc_m2_1005_r/acknowledgment.rtf b/general/datasets/Hc_m2_1005_r/acknowledgment.rtf
new file mode 100644
index 0000000..08c9160
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_r/acknowledgment.rtf
@@ -0,0 +1,54 @@
+
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: NIH XXXX
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Yanhua Qu, Ph.D.
+ Grant Support: NIH U01CA105417
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
+
diff --git a/general/datasets/Hc_m2_1005_r/cases.rtf b/general/datasets/Hc_m2_1005_r/cases.rtf
new file mode 100644
index 0000000..3e78bb4
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_r/cases.rtf
@@ -0,0 +1,60 @@
+This analysis has used 68 of BXD strains, the complete set of 13 CXB recombinant inbred strain sets, and a mouse diversity panel consisting of 16 inbred strains and a pair of reciprocal F1 hybrids (B6D2F1 and D2B6F1).
+
+The BXD genetic reference population of recombinant inbred strains consists of approximately 80 strains. Approximately 800 classical phenotypes from sets of 10 to 70 of these strains been integrated in the GeneNetwork. The BXD strains in this data set include 29 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD40). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+The CXB is the first and oldest set of recombinant inbred strains. Over 500 classical phenotypes from these strains been integrated in the GeneNetwork. It is noteworthy that the CXB strains segregate for the hippocampal lamination defect (Hld),characterized by Nowakowski and colleagues (1984). All of the CXBs have been recently genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ STILL IN PROGRESS (samples did not pass quality control); Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HIJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HILtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2_1005_r/experiment-design.rtf b/general/datasets/Hc_m2_1005_r/experiment-design.rtf
new file mode 100644
index 0000000..68713a4
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_r/experiment-design.rtf
@@ -0,0 +1,3252 @@
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80 deg. C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each isogenic group. While all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. Seventy-seven of 99 strains are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquotes R1291H3 and R1291H4).
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays.Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4 deg C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+
+ Data Table 1:
+
+
+This table lists all arrays by order of processing (Run), Sample ID, Strain, Sex, Age, number of animals in each sample pool (Pool), F generation number when less than 30 (GenN, and the Source of animals. SampleID is the ID number of the pooled RNA sample with a H1 through H3 suffix to indicate the actual hippocampal RNA aliquot used to prepare cRNA. Grp is the sequential group processing number (1 - 6).
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool sizel |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R2028H2 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 4.362 |
+ 64.49 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 2.78 |
+ 1.13 |
+ JAX |
+
+
+ | 2 |
+ R2029H2 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.04 |
+ 5.208 |
+ 41.21 |
+ 0.49 |
+ 0.49 |
+ 0.02 |
+ 1.62 |
+ 0.95 |
+ JAX |
+
+
+ | 3 |
+ R2030H1 |
+ A/J |
+ 57 |
+ M |
+ 5 |
+ 2 |
+ 0.06 |
+ 3.307 |
+ 45.16 |
+ 0.527 |
+ 0.454 |
+ 0.018 |
+ 1.63 |
+ 0.99 |
+ UTM RW |
+
+
+ | 4 |
+ R2032H3 |
+ AKR/J |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.054 |
+ 61.03 |
+ 0.51 |
+ 0.471 |
+ 0.018 |
+ 1.46 |
+ 0.79 |
+ JAX |
+
+
+ | 5 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 6 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 7 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 8 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 9 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 10 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 11 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 12 |
+ R1507H1 |
+ BXD1 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.056 |
+ 60.17 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.15 |
+ 0.76 |
+ Glenn |
+
+
+ | 13 |
+ R1520H1 |
+ BXD2 |
+ 56 |
+ F |
+ 4 |
+ 4 |
+ 0.09 |
+ 1.715 |
+ 71.62 |
+ 0.515 |
+ 0.467 |
+ 0.018 |
+ 2.36 |
+ 1.6 |
+ Glenn |
+
+
+ | 14 |
+ R1516H1 |
+ BXD2 |
+ 61 |
+ M |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.231 |
+ 64.86 |
+ 0.508 |
+ 0.474 |
+ 0.019 |
+ 1.3 |
+ 1.53 |
+ Glenn |
+
+
+ | 15 |
+ R1593H2 |
+ BXD5 |
+ 60 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 1.913 |
+ 59.96 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.98 |
+ 1.44 |
+ Glenn |
+
+
+ | 16 |
+ R1692H1 |
+ BXD5 |
+ 60 |
+ M |
+ 3 |
+ 2 |
+ 0.07 |
+ 3.764 |
+ 72.74 |
+ 0.465 |
+ 0.516 |
+ 0.02 |
+ 1.15 |
+ 0.74 |
+ Glenn |
+
+
+ | 17 |
+ R1539H2 |
+ BXD6 |
+ 59 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 2.488 |
+ 54.97 |
+ 0.518 |
+ 0.463 |
+ 0.018 |
+ 1.08 |
+ 1.33 |
+ Glenn |
+
+
+ | 18 |
+ R1538H1 |
+ BXD6 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.01 |
+ 2.585 |
+ 50.27 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 1.46 |
+ 0.79 |
+ Glenn |
+
+
+ | 19 |
+ R1518H1 |
+ BXD8 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 2.92 |
+ 54.84 |
+ 0.515 |
+ 0.465 |
+ 0.02 |
+ 1.32 |
+ 1.24 |
+ Glenn |
+
+
+ | 20 |
+ R1548H1 |
+ BXD8 |
+ 59 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.132 |
+ 59.37 |
+ 0.504 |
+ 0.477 |
+ 0.019 |
+ 2.16 |
+ 1.54 |
+ Glenn |
+
+
+ | 21 |
+ R1350H2 |
+ BXD9 |
+ 86 |
+ F |
+ 1 |
+ 3 |
+ 0.05 |
+ 2.771 |
+ 60.62 |
+ 0.5 |
+ 0.482 |
+ 0.018 |
+ 1.01 |
+ 1.28 |
+ UMemphis |
+
+
+ | 22 |
+ R1531H1 |
+ BXD11 |
+ 56 |
+ F |
+ 6 |
+ 3 |
+ 0.06 |
+ 2.229 |
+ 56.36 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 2.23 |
+ 1.02 |
+ Glenn |
+
+
+ | 23 |
+ R1367H1 |
+ BXD11 |
+ 56 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.11 |
+ 78.78 |
+ 0.503 |
+ 0.477 |
+ 0.02 |
+ 1.07 |
+ 1.27 |
+ Glenn |
+
+
+ | 24 |
+ R1530H1 |
+ BXD12 |
+ 58 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 3.227 |
+ 53.77 |
+ 0.505 |
+ 0.477 |
+ 0.018 |
+ 0.95 |
+ 1.4 |
+ Glenn |
+
+
+ | 25 |
+ R1529H1 |
+ BXD13 |
+ 58 |
+ F |
+ 6 |
+ 3 |
+ 0.05 |
+ 2.55 |
+ 59.05 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 2 |
+ 1.54 |
+ Glenn |
+
+
+ | 26 |
+ R1662H2 |
+ BXD13 |
+ 60 |
+ M |
+ 1 |
+ 3 |
+ 0.03 |
+ 4.603 |
+ 45.81 |
+ 0.509 |
+ 0.472 |
+ 0.019 |
+ 1.3 |
+ 0.82 |
+ Glenn |
+
+
+ | 27 |
+ R1524H1 |
+ BXD15 |
+ 60 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.961 |
+ 50.93 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 1.74 |
+ 0.91 |
+ Glenn |
+
+
+ | 28 |
+ R1515H1 |
+ BXD15 |
+ 61 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.316 |
+ 57.05 |
+ 0.503 |
+ 0.478 |
+ 0.019 |
+ 1.32 |
+ 1.21 |
+ Glenn |
+
+
+ | 29 |
+ R1661H1 |
+ BXD16 |
+ 61 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.778 |
+ 59.81 |
+ 0.516 |
+ 0.466 |
+ 0.019 |
+ 1.39 |
+ 1.2 |
+ Glenn |
+
+
+ | 30 |
+ R1594H1 |
+ BXD16 |
+ 61 |
+ M |
+ 4 |
+ 3 |
+ 0.03 |
+ 2.634 |
+ 53.66 |
+ 0.504 |
+ 0.478 |
+ 0.018 |
+ 1.96 |
+ 1.51 |
+ Glenn |
+
+
+ | 31 |
+ R1471H1 |
+ BXD19 |
+ 157 |
+ M |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.165 |
+ 43.34 |
+ 0.519 |
+ 0.462 |
+ 0.018 |
+ 1.01 |
+ 1.29 |
+ UTM JB |
+
+
+ | 32 |
+ R1573H1 |
+ BXD20 |
+ 59 |
+ F |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.749 |
+ 52.7 |
+ 0.513 |
+ 0.469 |
+ 0.018 |
+ 1.01 |
+ 1.27 |
+ Glenn |
+
+
+ | 33 |
+ R2507H1 |
+ BXD20 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.06 |
+ 3.568 |
+ 57 |
+ 0.472 |
+ 0.508 |
+ 0.02 |
+ 1.29 |
+ 0.76 |
+ Glenn |
+
+
+ | 34 |
+ R1347H2 |
+ BXD21 |
+ 64 |
+ F |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.881 |
+ 61.49 |
+ 0.494 |
+ 0.486 |
+ 0.019 |
+ 0.92 |
+ 1.22 |
+ UMemphis |
+
+
+ | 35 |
+ R1337H2 |
+ BXD21 |
+ 102 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.673 |
+ 58.05 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.4 |
+ 0.76 |
+ UAB |
+
+
+ | 36 |
+ R1848H3 |
+ BXD22 |
+ 196 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.943 |
+ 51.7 |
+ 0.494 |
+ 0.485 |
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+
+
+ | 37 |
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+ 2 |
+ 3 |
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+
+
+ | 38 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 39 |
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+ 5 |
+ 3 |
+ 0.1 |
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+
+
+ | 40 |
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+ 2 |
+ 3 |
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+
+
+ | 41 |
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+ 3 |
+ 3 |
+ 0.01 |
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+
+
+ | 42 |
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+ 2 |
+ 4 |
+ 0 |
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+
+
+ | 43 |
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+ 5 |
+ 3 |
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+
+
+ | 44 |
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+ 3 |
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+
+
+ | 45 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+ | 46 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+ | 47 |
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+ 5 |
+ 3 |
+ 0.01 |
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+
+
+ | 48 |
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+ 2 |
+ 3 |
+ 0.02 |
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+
+
+ | 49 |
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+ 2 |
+ 4 |
+ 0.01 |
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+
+
+ | 50 |
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+ 2 |
+ 2 |
+ 0.01 |
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+
+
+ | 51 |
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+ 3 |
+ 3 |
+ 0.01 |
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+
+ | 52 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 53 |
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+ 5 |
+ 3 |
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+
+ | 54 |
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+ 3 |
+ 3 |
+ 0.02 |
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+
+
+ | 55 |
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+ 2 |
+ 4 |
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+
+ | 56 |
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+ 3 |
+ 4 |
+ 0.01 |
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+
+ | 57 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+ | 58 |
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+ 3 |
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+
+ | 59 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+ | 60 |
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+ 4 |
+ 0 |
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+
+ | 61 |
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+ 3 |
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+
+ | 62 |
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+ 3 |
+ 0 |
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+
+
+ | 63 |
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+ 3 |
+ 4 |
+ 0.02 |
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+
+
+ | 64 |
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+ 0 |
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+
+
+ | 65 |
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+
+
+ | 66 |
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+ 0 |
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+
+
+ | 67 |
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+
+
+ | 68 |
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+
+
+ | 69 |
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+ 1 |
+ 3 |
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+
+
+ | 70 |
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+ 0.03 |
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+
+
+ | 71 |
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+
+
+ | 72 |
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+
+
+ | 73 |
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+ 0 |
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+
+
+ | 74 |
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+
+
+ | 75 |
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+
+ | 76 |
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+
+ | 77 |
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+
+ | 78 |
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+
+ | 79 |
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+
+ | 80 |
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+
+ | 81 |
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+
+ | 82 |
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+
+ | 83 |
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+
+ | 84 |
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+
+ | 85 |
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+
+ | 86 |
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+
+ | 87 |
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+
+ | 88 |
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+
+
+ | 89 |
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+
+
+ | 90 |
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+
+
+ | 91 |
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+
+
+ | 92 |
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+
+
+ | 93 |
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+
+
+ | 94 |
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+
+
+ | 95 |
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+
+
+ | 96 |
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+
+
+ | 97 |
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+
+
+ | 98 |
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+
+
+ | 99 |
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+
+
+ | 100 |
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+
+
+ | 101 |
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+
+
+ | 102 |
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+
+
+ | 103 |
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+
+
+ | 104 |
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+
+
+ | 105 |
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+
+
+ | 106 |
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+
+
+ | 107 |
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+
+
+ | 108 |
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+ 3 |
+ 0.03 |
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+
+
+ | 109 |
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+ 2 |
+ 0 |
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+ UTM RW |
+
+
+ | 110 |
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+ 75 |
+ M |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.467 |
+ 64.46 |
+ 0.505 |
+ 0.476 |
+ 0.019 |
+ 1.2 |
+ 0.74 |
+ UTM RW |
+
+
+ | 111 |
+ R1473H1 |
+ BXD85 |
+ 79 |
+ F |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.384 |
+ 55.34 |
+ 0.478 |
+ 0.502 |
+ 0.02 |
+ 1.24 |
+ 0.77 |
+ UTM RW |
+
+
+ | 112 |
+ R1474H1 |
+ BXD85 |
+ 57 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.831 |
+ 55.24 |
+ 0.522 |
+ 0.461 |
+ 0.018 |
+ 1.04 |
+ 1.29 |
+ UTM RW |
+
+
+ | 113 |
+ R1597H1 |
+ BXD85 |
+ 86 |
+ M |
+ 4 |
+ 4 |
+ 0.09 |
+ 2.028 |
+ 53.95 |
+ 0.487 |
+ 0.492 |
+ 0.021 |
+ 1.28 |
+ 0.83 |
+ UTM RW |
+
+
+ | 114 |
+ R1415H1 |
+ BXD86 |
+ 77 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 2.525 |
+ 53.16 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.66 |
+ 0.91 |
+ UTM RW |
+
+
+ | 115 |
+ R1710H1 |
+ BXD87 |
+ 84 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 2.697 |
+ 56.4 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 116 |
+ R1872H2 |
+ BXD89 |
+ 90 |
+ F |
+ 2 |
+ 2 |
+ 0.02 |
+ 3.013 |
+ 63.53 |
+ 0.492 |
+ 0.488 |
+ 0.021 |
+ 1.22 |
+ 0.72 |
+ UTM RW |
+
+
+ | 117 |
+ R1850H3 |
+ BXD89 |
+ 82 |
+ M |
+ 4 |
+ 4 |
+ 0.03 |
+ 2.736 |
+ 44.89 |
+ 0.498 |
+ 0.483 |
+ 0.019 |
+ 1.5 |
+ 0.83 |
+ UTM RW |
+
+
+ | 118 |
+ R2058H1 |
+ BXD90 |
+ 61 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 3.389 |
+ 48.05 |
+ 0.502 |
+ 0.478 |
+ 0.02 |
+ 1.53 |
+ 0.76 |
+ UTM RW |
+
+
+ | 119 |
+ R1301H2 |
+ BXD92 |
+ 58 |
+ F |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.543 |
+ 41.97 |
+ 0.522 |
+ 0.46 |
+ 0.018 |
+ 1.5 |
+ 0.79 |
+ UTM RW |
+
+
+ | 120 |
+ R1309H1 |
+ BXD92 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.05 |
+ 1.655 |
+ 66.34 |
+ 0.498 |
+ 0.481 |
+ 0.021 |
+ 1.52 |
+ 0.82 |
+ UTM RW |
+
+
+ | 121 |
+ R2057H1 |
+ BXD93 |
+ 92 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.033 |
+ 44.41 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 1.22 |
+ 0.78 |
+ UTM RW |
+
+
+ | 122 |
+ R2059H1 |
+ BXD93 |
+ 58 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.058 |
+ 60.29 |
+ 0.493 |
+ 0.488 |
+ 0.019 |
+ 1.18 |
+ 1.37 |
+ UTM RW |
+
+
+ | 123 |
+ R2313H1 |
+ BXD94 |
+ 59 |
+ F |
+ 3 |
+ 3 |
+ 0 |
+ 3.091 |
+ 59.45 |
+ 0.487 |
+ 0.495 |
+ 0.018 |
+ 1.34 |
+ 0.73 |
+ UTM RW |
+
+
+ | 124 |
+ R1915H1 |
+ BXD96 |
+ 65 |
+ F |
+ 5 |
+ 2 |
+ 0.04 |
+ 5.145 |
+ 46.19 |
+ 0.502 |
+ 0.481 |
+ 0.017 |
+ 1.37 |
+ 0.74 |
+ UTM RW |
+
+
+ | 125 |
+ R1846H2 |
+ BXD96 |
+ 63 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.159 |
+ 55.85 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.92 |
+ 1.26 |
+ UTM RW |
+
+
+ | 126 |
+ R1927H2 |
+ BXD97 |
+ 67 |
+ M |
+ 1 |
+ 3 |
+ 0.04 |
+ 2.622 |
+ 57.81 |
+ 0.539 |
+ 0.444 |
+ 0.017 |
+ 1.45 |
+ 1.32 |
+ UTM RW |
+
+
+ | 127 |
+ R1942H1 |
+ BXD98 |
+ 62 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.104 |
+ 48.42 |
+ 0.528 |
+ 0.454 |
+ 0.019 |
+ 2.22 |
+ 1.08 |
+ UTM RW |
+
+
+ | 128 |
+ R1943H2 |
+ BXD98 |
+ 62 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.04 |
+ 56.85 |
+ 0.484 |
+ 0.497 |
+ 0.019 |
+ 1.18 |
+ 0.76 |
+ UTM RW |
+
+
+ | 129 |
+ R2197H1 |
+ BXD99 |
+ 70 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.288 |
+ 51.75 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.35 |
+ 0.81 |
+ UTM RW |
+
+
+ | 130 |
+ R2315H1 |
+ BXD99 |
+ 84 |
+ M |
+ 5 |
+ 2 |
+ 0.03 |
+ 6.036 |
+ 43.05 |
+ 0.484 |
+ 0.497 |
+ 0.018 |
+ 1.7 |
+ 0.96 |
+ UTM RW |
+
+
+ | 131 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 132 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 133 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 134 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
+ 3.058 |
+ 51.87 |
+ 0.477 |
+ 0.503 |
+ 0.02 |
+ 1.67 |
+ 0.76 |
+ UTM RW |
+
+
+ | 135 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
+ 3.341 |
+ 49.26 |
+ 0.527 |
+ 0.456 |
+ 0.018 |
+ 1.14 |
+ 1.45 |
+ UTM RW |
+
+
+ | 136 |
+ R1449H2 |
+ C57BL/6J |
+ 71 |
+ M |
+ 5 |
+ 3 |
+ 0.09 |
+ 3.592 |
+ 44.32 |
+ 0.47 |
+ 0.51 |
+ 0.02 |
+ 1.68 |
+ 0.77 |
+ UTM DG |
+
+
+ | 137 |
+ R2619H1 |
+ CAST/Ei |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 138 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 139 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 140 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 141 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 142 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 143 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 144 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 145 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+ | 146 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 147 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 148 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 149 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 150 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 151 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 152 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 153 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 154 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 155 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 156 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 157 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 158 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 159 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 160 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 161 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 162 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 163 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 2.579 |
+ 58.49 |
+ 0.506 |
+ 0.475 |
+ 0.019 |
+ 2.49 |
+ 1.21 |
+ UTM RW |
+
+
+ | 164 |
+ R1551H1 |
+ D2B6F1 |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.62 |
+ 53.76 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 1.37 |
+ 0.76 |
+ UTM RW |
+
+
+ | 165 |
+ R1468H1 |
+ DBA/2J |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.03 |
+ 2.929 |
+ 53.8 |
+ 0.515 |
+ 0.465 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 166 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 167 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 168 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 169 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 170 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 171 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 172 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 173 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 174 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 175 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 176 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 177 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 178 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Hc_m2_1005_r/notes.rtf b/general/datasets/Hc_m2_1005_r/notes.rtf
new file mode 100644
index 0000000..4490ee3
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_r/notes.rtf
@@ -0,0 +1,15 @@
+This study includes the following datasets:
+
+
+Hippocampus Consortium M430v2 (Oct05) MAS5
+
+Hippocampus Consortium M430v2 (Oct05) RMA
+
+Hippocampus Consortium M430v2 (Oct05) PDNN
+
+Hippocampus Consortium M430v2 (Dec05) RMA
+
+Hippocampus Consortium M430v2 (Dec05) PDNN
+
+
+This text file originally generated prospectively by RWW on July 30 2005. Updated by RWW July 31, 2005.
diff --git a/general/datasets/Hc_m2_1005_r/platform.rtf b/general/datasets/Hc_m2_1005_r/platform.rtf
new file mode 100644
index 0000000..af0948c
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_r/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2_1005_r/processing.rtf b/general/datasets/Hc_m2_1005_r/processing.rtf
new file mode 100644
index 0000000..df5513b
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_r/processing.rtf
@@ -0,0 +1,40 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very senstive to the transformation method that is used. Using the PDNN transform the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For examploe, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one whould include the ssample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the of the probe level (CEL) data after step 5 below. DataDesk allows a rapid detection of subsets of probes that are particular sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. <0L>
+
+
+
+
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2_1005_r/summary.rtf b/general/datasets/Hc_m2_1005_r/summary.rtf
new file mode 100644
index 0000000..9b7c1d6
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_r/summary.rtf
@@ -0,0 +1 @@
+PRELIMINARY: The October 2005 Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of approximately 99 genetically diverse strains of mice including 68 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a set of 16 diverse inbred strains, and 2 reciprocal F1 hybrids. The hippocampus is an important and intriguing part of the forebrain that is crucial for memory formation, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3, and parts of the subiculum) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section. Samples were processed using a total of 206 Affymetrix Mouse Expression 430 2.0 short oligomer microarrays (MOE430 2.0 or M430v2), of which 179 passed stringent quality control and error checking. This particular data set was processed using the MAS5 protocol. To simplify comparisons among transforms, MAS5 values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2_1005_r/tissue.rtf b/general/datasets/Hc_m2_1005_r/tissue.rtf
new file mode 100644
index 0000000..2bb700d
--- /dev/null
+++ b/general/datasets/Hc_m2_1005_r/tissue.rtf
@@ -0,0 +1,7 @@
+
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thanks Muriel Davission for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below).
+
diff --git a/general/datasets/Hc_m2_1205_p/acknowledgment.rtf b/general/datasets/Hc_m2_1205_p/acknowledgment.rtf
new file mode 100644
index 0000000..08c9160
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_p/acknowledgment.rtf
@@ -0,0 +1,54 @@
+
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: NIH XXXX
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Yanhua Qu, Ph.D.
+ Grant Support: NIH U01CA105417
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
+
diff --git a/general/datasets/Hc_m2_1205_p/cases.rtf b/general/datasets/Hc_m2_1205_p/cases.rtf
new file mode 100644
index 0000000..3e78bb4
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_p/cases.rtf
@@ -0,0 +1,60 @@
+This analysis has used 68 of BXD strains, the complete set of 13 CXB recombinant inbred strain sets, and a mouse diversity panel consisting of 16 inbred strains and a pair of reciprocal F1 hybrids (B6D2F1 and D2B6F1).
+
+The BXD genetic reference population of recombinant inbred strains consists of approximately 80 strains. Approximately 800 classical phenotypes from sets of 10 to 70 of these strains been integrated in the GeneNetwork. The BXD strains in this data set include 29 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD40). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+The CXB is the first and oldest set of recombinant inbred strains. Over 500 classical phenotypes from these strains been integrated in the GeneNetwork. It is noteworthy that the CXB strains segregate for the hippocampal lamination defect (Hld),characterized by Nowakowski and colleagues (1984). All of the CXBs have been recently genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ STILL IN PROGRESS (samples did not pass quality control); Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HIJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HILtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2_1205_p/experiment-design.rtf b/general/datasets/Hc_m2_1205_p/experiment-design.rtf
new file mode 100644
index 0000000..68713a4
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_p/experiment-design.rtf
@@ -0,0 +1,3252 @@
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80 deg. C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each isogenic group. While all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. Seventy-seven of 99 strains are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquotes R1291H3 and R1291H4).
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays.Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4 deg C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+
+ Data Table 1:
+
+
+This table lists all arrays by order of processing (Run), Sample ID, Strain, Sex, Age, number of animals in each sample pool (Pool), F generation number when less than 30 (GenN, and the Source of animals. SampleID is the ID number of the pooled RNA sample with a H1 through H3 suffix to indicate the actual hippocampal RNA aliquot used to prepare cRNA. Grp is the sequential group processing number (1 - 6).
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool sizel |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R2028H2 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 4.362 |
+ 64.49 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 2.78 |
+ 1.13 |
+ JAX |
+
+
+ | 2 |
+ R2029H2 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.04 |
+ 5.208 |
+ 41.21 |
+ 0.49 |
+ 0.49 |
+ 0.02 |
+ 1.62 |
+ 0.95 |
+ JAX |
+
+
+ | 3 |
+ R2030H1 |
+ A/J |
+ 57 |
+ M |
+ 5 |
+ 2 |
+ 0.06 |
+ 3.307 |
+ 45.16 |
+ 0.527 |
+ 0.454 |
+ 0.018 |
+ 1.63 |
+ 0.99 |
+ UTM RW |
+
+
+ | 4 |
+ R2032H3 |
+ AKR/J |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.054 |
+ 61.03 |
+ 0.51 |
+ 0.471 |
+ 0.018 |
+ 1.46 |
+ 0.79 |
+ JAX |
+
+
+ | 5 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 6 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 7 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 8 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 9 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 10 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 11 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 12 |
+ R1507H1 |
+ BXD1 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.056 |
+ 60.17 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.15 |
+ 0.76 |
+ Glenn |
+
+
+ | 13 |
+ R1520H1 |
+ BXD2 |
+ 56 |
+ F |
+ 4 |
+ 4 |
+ 0.09 |
+ 1.715 |
+ 71.62 |
+ 0.515 |
+ 0.467 |
+ 0.018 |
+ 2.36 |
+ 1.6 |
+ Glenn |
+
+
+ | 14 |
+ R1516H1 |
+ BXD2 |
+ 61 |
+ M |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.231 |
+ 64.86 |
+ 0.508 |
+ 0.474 |
+ 0.019 |
+ 1.3 |
+ 1.53 |
+ Glenn |
+
+
+ | 15 |
+ R1593H2 |
+ BXD5 |
+ 60 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 1.913 |
+ 59.96 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.98 |
+ 1.44 |
+ Glenn |
+
+
+ | 16 |
+ R1692H1 |
+ BXD5 |
+ 60 |
+ M |
+ 3 |
+ 2 |
+ 0.07 |
+ 3.764 |
+ 72.74 |
+ 0.465 |
+ 0.516 |
+ 0.02 |
+ 1.15 |
+ 0.74 |
+ Glenn |
+
+
+ | 17 |
+ R1539H2 |
+ BXD6 |
+ 59 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 2.488 |
+ 54.97 |
+ 0.518 |
+ 0.463 |
+ 0.018 |
+ 1.08 |
+ 1.33 |
+ Glenn |
+
+
+ | 18 |
+ R1538H1 |
+ BXD6 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.01 |
+ 2.585 |
+ 50.27 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 1.46 |
+ 0.79 |
+ Glenn |
+
+
+ | 19 |
+ R1518H1 |
+ BXD8 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 2.92 |
+ 54.84 |
+ 0.515 |
+ 0.465 |
+ 0.02 |
+ 1.32 |
+ 1.24 |
+ Glenn |
+
+
+ | 20 |
+ R1548H1 |
+ BXD8 |
+ 59 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.132 |
+ 59.37 |
+ 0.504 |
+ 0.477 |
+ 0.019 |
+ 2.16 |
+ 1.54 |
+ Glenn |
+
+
+ | 21 |
+ R1350H2 |
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+ 1 |
+ 3 |
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+
+
+ | 22 |
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+ 6 |
+ 3 |
+ 0.06 |
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+
+
+ | 23 |
+ R1367H1 |
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+ 56 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
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+ 0.503 |
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+
+
+ | 24 |
+ R1530H1 |
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+ 58 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 25 |
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+ 58 |
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+ 6 |
+ 3 |
+ 0.05 |
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+ 2 |
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+ Glenn |
+
+
+ | 26 |
+ R1662H2 |
+ BXD13 |
+ 60 |
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+ 1 |
+ 3 |
+ 0.03 |
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+
+
+ | 27 |
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+ 6 |
+ 4 |
+ 0.02 |
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+
+
+ | 28 |
+ R1515H1 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 29 |
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+ 1 |
+ 3 |
+ 0.01 |
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+ 1.2 |
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+
+
+ | 30 |
+ R1594H1 |
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+ 4 |
+ 3 |
+ 0.03 |
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+
+
+ | 31 |
+ R1471H1 |
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+ 1 |
+ 3 |
+ 0.02 |
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+
+
+ | 32 |
+ R1573H1 |
+ BXD20 |
+ 59 |
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+ 1 |
+ 3 |
+ 0.02 |
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+
+
+ | 33 |
+ R2507H1 |
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+ 6 |
+ 3 |
+ 0.06 |
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+
+
+ | 34 |
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+ 1 |
+ 4 |
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+
+
+ | 35 |
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+ 2 |
+ 4 |
+ 0 |
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+
+
+ | 36 |
+ R1848H3 |
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+ F |
+ 6 |
+ 4 |
+ 0.02 |
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+ UAB |
+
+
+ | 37 |
+ R1525H1 |
+ BXD22 |
+ 59 |
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+ 2 |
+ 3 |
+ 0.02 |
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+
+
+ | 38 |
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+ 56 |
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+ 1 |
+ 3 |
+ 0.01 |
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+ 1.2 |
+ UTM RW |
+
+
+ | 39 |
+ R1537H1 |
+ BXD23 |
+ 58 |
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+ 5 |
+ 3 |
+ 0.1 |
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+
+
+ | 40 |
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+ 71 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 41 |
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+ 3 |
+ 3 |
+ 0.01 |
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+
+
+ | 42 |
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+ 2 |
+ 4 |
+ 0 |
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+
+
+ | 43 |
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+ 5 |
+ 3 |
+ 0.06 |
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+
+
+ | 44 |
+ R1353H1 |
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+ 3 |
+ 4 |
+ 0.01 |
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+
+
+ | 45 |
+ R2332H1 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 46 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 47 |
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+ 5 |
+ 3 |
+ 0.01 |
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+
+
+ | 48 |
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+ 2 |
+ 3 |
+ 0.02 |
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+
+
+ | 49 |
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+ 2 |
+ 4 |
+ 0.01 |
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+
+
+ | 50 |
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+ 2 |
+ 2 |
+ 0.01 |
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+
+
+ | 51 |
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+ 3 |
+ 0.01 |
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+
+
+ | 52 |
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+ 3 |
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+
+
+ | 53 |
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+ 5 |
+ 3 |
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+
+ | 54 |
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+ 3 |
+ 0.02 |
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+
+
+ | 55 |
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+ 4 |
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+
+ | 56 |
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+
+ | 57 |
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+
+ | 58 |
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+
+ | 59 |
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+
+ | 60 |
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+ 0 |
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+
+ | 61 |
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+
+ | 62 |
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+ 0 |
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+
+
+ | 63 |
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+
+
+ | 64 |
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+ 0 |
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+
+
+ | 65 |
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+
+ | 66 |
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+
+
+ | 67 |
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+
+
+ | 68 |
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+
+
+ | 69 |
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+
+
+ | 70 |
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+
+
+ | 71 |
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+
+
+ | 72 |
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+
+
+ | 73 |
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+ 0 |
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+
+
+ | 74 |
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+ 0 |
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+
+
+ | 75 |
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+
+
+ | 76 |
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+
+
+ | 77 |
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+
+
+ | 78 |
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+
+
+ | 79 |
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+
+
+ | 80 |
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+
+
+ | 81 |
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+
+
+ | 82 |
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+ 0 |
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+
+
+ | 83 |
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+
+
+ | 84 |
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+
+
+ | 85 |
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+
+
+ | 86 |
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+
+
+ | 87 |
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+ 0.02 |
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+
+
+ | 88 |
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+ 2 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 89 |
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+ 2 |
+ 3 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 90 |
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+ 3 |
+ 3 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 91 |
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+ 2 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 92 |
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+ 2 |
+ 3 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 93 |
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+ 4 |
+ 2 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 94 |
+ R1443H2 |
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+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.312 |
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+ 0.499 |
+ 0.481 |
+ 0.02 |
+ 1.48 |
+ 0.77 |
+ UTM RW |
+
+
+ | 95 |
+ R2055H2 |
+ BXD74 |
+ 79 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.576 |
+ 56.84 |
+ 0.509 |
+ 0.473 |
+ 0.018 |
+ 1.46 |
+ 0.88 |
+ UTM RW |
+
+
+ | 96 |
+ R2316H1 |
+ BXD74 |
+ 193 |
+ M |
+ 5 |
+ 2 |
+ 0.01 |
+ 3.457 |
+ 55.35 |
+ 0.508 |
+ 0.471 |
+ 0.02 |
+ 1.17 |
+ 0.78 |
+ UTM RW |
+
+
+ | 97 |
+ R1871H1 |
+ BXD75 |
+ 61 |
+ F |
+ 2 |
+ 3 |
+ 0.04 |
+ 1.723 |
+ 56.4 |
+ 0.53 |
+ 0.451 |
+ 0.019 |
+ 1.3 |
+ 0.76 |
+ UTM RW |
+
+
+ | 98 |
+ R1844H2 |
+ BXD75 |
+ 90 |
+ M |
+ 3 |
+ 4 |
+ 0.01 |
+ 1.934 |
+ 56.23 |
+ 0.52 |
+ 0.461 |
+ 0.019 |
+ 1.62 |
+ 0.86 |
+ UTM RW |
+
+
+ | 99 |
+ R1948H2 |
+ BXD76 |
+ 81 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 1.507 |
+ 68.85 |
+ 0.553 |
+ 0.428 |
+ 0.02 |
+ 1.3 |
+ 0.75 |
+ UTM RW |
+
+
+ | 100 |
+ R2094H1 |
+ BXD76 |
+ 61 |
+ M |
+ 5 |
+ 4 |
+ 0.01 |
+ 3.299 |
+ 42.69 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 1.39 |
+ 0.88 |
+ UTM RW |
+
+
+ | 101 |
+ R2262H1 |
+ BXD77 |
+ 62 |
+ F |
+ 3 |
+ 4 |
+ 0.02 |
+ 4.317 |
+ 47.16 |
+ 0.493 |
+ 0.488 |
+ 0.019 |
+ 1.32 |
+ 0.74 |
+ UTM RW |
+
+
+ | 102 |
+ R1423H1 |
+ BXD77 |
+ 62 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.071 |
+ 54.15 |
+ 0.51 |
+ 0.471 |
+ 0.019 |
+ 1.26 |
+ 0.74 |
+ UTM RW |
+
+
+ | 103 |
+ R1947H1 |
+ BXD79 |
+ 108 |
+ F |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.599 |
+ 51.52 |
+ 0.524 |
+ 0.457 |
+ 0.019 |
+ 1.35 |
+ 0.74 |
+ UTM RW |
+
+
+ | 104 |
+ R2092H1 |
+ BXD79 |
+ 86 |
+ M |
+ 5 |
+ 4 |
+ 0.06 |
+ 3.735 |
+ 42.25 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 2.94 |
+ 1.06 |
+ UTM RW |
+
+
+ | 105 |
+ R1880H1 |
+ BXD80 |
+ 68 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 4.855 |
+ 42.22 |
+ 0.501 |
+ 0.481 |
+ 0.018 |
+ 2.17 |
+ 1.36 |
+ UTM RW |
+
+
+ | 106 |
+ R1881H2 |
+ BXD80 |
+ 68 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.073 |
+ 48.93 |
+ 0.524 |
+ 0.458 |
+ 0.019 |
+ 1.34 |
+ 0.83 |
+ UTM RW |
+
+
+ | 107 |
+ R2075H1 |
+ BXD83 |
+ 60 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.454 |
+ 55.1 |
+ 0.502 |
+ 0.48 |
+ 0.018 |
+ 1.27 |
+ 0.77 |
+ UTM RW |
+
+
+ | 108 |
+ R2076H2 |
+ BXD83 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.03 |
+ 2.624 |
+ 55.65 |
+ 0.495 |
+ 0.488 |
+ 0.018 |
+ 2.21 |
+ 0.94 |
+ UTM RW |
+
+
+ | 109 |
+ R2077H2 |
+ BXD84 |
+ 62 |
+ F |
+ 6 |
+ 2 |
+ 0 |
+ 2.1 |
+ 71.87 |
+ 0.522 |
+ 0.459 |
+ 0.018 |
+ 1.68 |
+ 0.81 |
+ UTM RW |
+
+
+ | 110 |
+ R2135H3 |
+ BXD84 |
+ 75 |
+ M |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.467 |
+ 64.46 |
+ 0.505 |
+ 0.476 |
+ 0.019 |
+ 1.2 |
+ 0.74 |
+ UTM RW |
+
+
+ | 111 |
+ R1473H1 |
+ BXD85 |
+ 79 |
+ F |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.384 |
+ 55.34 |
+ 0.478 |
+ 0.502 |
+ 0.02 |
+ 1.24 |
+ 0.77 |
+ UTM RW |
+
+
+ | 112 |
+ R1474H1 |
+ BXD85 |
+ 57 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.831 |
+ 55.24 |
+ 0.522 |
+ 0.461 |
+ 0.018 |
+ 1.04 |
+ 1.29 |
+ UTM RW |
+
+
+ | 113 |
+ R1597H1 |
+ BXD85 |
+ 86 |
+ M |
+ 4 |
+ 4 |
+ 0.09 |
+ 2.028 |
+ 53.95 |
+ 0.487 |
+ 0.492 |
+ 0.021 |
+ 1.28 |
+ 0.83 |
+ UTM RW |
+
+
+ | 114 |
+ R1415H1 |
+ BXD86 |
+ 77 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 2.525 |
+ 53.16 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.66 |
+ 0.91 |
+ UTM RW |
+
+
+ | 115 |
+ R1710H1 |
+ BXD87 |
+ 84 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 2.697 |
+ 56.4 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 116 |
+ R1872H2 |
+ BXD89 |
+ 90 |
+ F |
+ 2 |
+ 2 |
+ 0.02 |
+ 3.013 |
+ 63.53 |
+ 0.492 |
+ 0.488 |
+ 0.021 |
+ 1.22 |
+ 0.72 |
+ UTM RW |
+
+
+ | 117 |
+ R1850H3 |
+ BXD89 |
+ 82 |
+ M |
+ 4 |
+ 4 |
+ 0.03 |
+ 2.736 |
+ 44.89 |
+ 0.498 |
+ 0.483 |
+ 0.019 |
+ 1.5 |
+ 0.83 |
+ UTM RW |
+
+
+ | 118 |
+ R2058H1 |
+ BXD90 |
+ 61 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 3.389 |
+ 48.05 |
+ 0.502 |
+ 0.478 |
+ 0.02 |
+ 1.53 |
+ 0.76 |
+ UTM RW |
+
+
+ | 119 |
+ R1301H2 |
+ BXD92 |
+ 58 |
+ F |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.543 |
+ 41.97 |
+ 0.522 |
+ 0.46 |
+ 0.018 |
+ 1.5 |
+ 0.79 |
+ UTM RW |
+
+
+ | 120 |
+ R1309H1 |
+ BXD92 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.05 |
+ 1.655 |
+ 66.34 |
+ 0.498 |
+ 0.481 |
+ 0.021 |
+ 1.52 |
+ 0.82 |
+ UTM RW |
+
+
+ | 121 |
+ R2057H1 |
+ BXD93 |
+ 92 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.033 |
+ 44.41 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 1.22 |
+ 0.78 |
+ UTM RW |
+
+
+ | 122 |
+ R2059H1 |
+ BXD93 |
+ 58 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.058 |
+ 60.29 |
+ 0.493 |
+ 0.488 |
+ 0.019 |
+ 1.18 |
+ 1.37 |
+ UTM RW |
+
+
+ | 123 |
+ R2313H1 |
+ BXD94 |
+ 59 |
+ F |
+ 3 |
+ 3 |
+ 0 |
+ 3.091 |
+ 59.45 |
+ 0.487 |
+ 0.495 |
+ 0.018 |
+ 1.34 |
+ 0.73 |
+ UTM RW |
+
+
+ | 124 |
+ R1915H1 |
+ BXD96 |
+ 65 |
+ F |
+ 5 |
+ 2 |
+ 0.04 |
+ 5.145 |
+ 46.19 |
+ 0.502 |
+ 0.481 |
+ 0.017 |
+ 1.37 |
+ 0.74 |
+ UTM RW |
+
+
+ | 125 |
+ R1846H2 |
+ BXD96 |
+ 63 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.159 |
+ 55.85 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.92 |
+ 1.26 |
+ UTM RW |
+
+
+ | 126 |
+ R1927H2 |
+ BXD97 |
+ 67 |
+ M |
+ 1 |
+ 3 |
+ 0.04 |
+ 2.622 |
+ 57.81 |
+ 0.539 |
+ 0.444 |
+ 0.017 |
+ 1.45 |
+ 1.32 |
+ UTM RW |
+
+
+ | 127 |
+ R1942H1 |
+ BXD98 |
+ 62 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.104 |
+ 48.42 |
+ 0.528 |
+ 0.454 |
+ 0.019 |
+ 2.22 |
+ 1.08 |
+ UTM RW |
+
+
+ | 128 |
+ R1943H2 |
+ BXD98 |
+ 62 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.04 |
+ 56.85 |
+ 0.484 |
+ 0.497 |
+ 0.019 |
+ 1.18 |
+ 0.76 |
+ UTM RW |
+
+
+ | 129 |
+ R2197H1 |
+ BXD99 |
+ 70 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.288 |
+ 51.75 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.35 |
+ 0.81 |
+ UTM RW |
+
+
+ | 130 |
+ R2315H1 |
+ BXD99 |
+ 84 |
+ M |
+ 5 |
+ 2 |
+ 0.03 |
+ 6.036 |
+ 43.05 |
+ 0.484 |
+ 0.497 |
+ 0.018 |
+ 1.7 |
+ 0.96 |
+ UTM RW |
+
+
+ | 131 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 132 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 133 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 134 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
+ 3.058 |
+ 51.87 |
+ 0.477 |
+ 0.503 |
+ 0.02 |
+ 1.67 |
+ 0.76 |
+ UTM RW |
+
+
+ | 135 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
+ 3.341 |
+ 49.26 |
+ 0.527 |
+ 0.456 |
+ 0.018 |
+ 1.14 |
+ 1.45 |
+ UTM RW |
+
+
+ | 136 |
+ R1449H2 |
+ C57BL/6J |
+ 71 |
+ M |
+ 5 |
+ 3 |
+ 0.09 |
+ 3.592 |
+ 44.32 |
+ 0.47 |
+ 0.51 |
+ 0.02 |
+ 1.68 |
+ 0.77 |
+ UTM DG |
+
+
+ | 137 |
+ R2619H1 |
+ CAST/Ei |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 138 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 139 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 140 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 141 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 142 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 143 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 144 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 145 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+ | 146 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 147 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 148 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 149 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 150 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 151 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 152 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 153 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 154 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 155 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 156 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 157 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 158 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 159 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 160 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 161 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 162 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 163 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 2.579 |
+ 58.49 |
+ 0.506 |
+ 0.475 |
+ 0.019 |
+ 2.49 |
+ 1.21 |
+ UTM RW |
+
+
+ | 164 |
+ R1551H1 |
+ D2B6F1 |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.62 |
+ 53.76 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 1.37 |
+ 0.76 |
+ UTM RW |
+
+
+ | 165 |
+ R1468H1 |
+ DBA/2J |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.03 |
+ 2.929 |
+ 53.8 |
+ 0.515 |
+ 0.465 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 166 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 167 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 168 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 169 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 170 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 171 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 172 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 173 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 174 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 175 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 176 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 177 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 178 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Hc_m2_1205_p/notes.rtf b/general/datasets/Hc_m2_1205_p/notes.rtf
new file mode 100644
index 0000000..4490ee3
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_p/notes.rtf
@@ -0,0 +1,15 @@
+This study includes the following datasets:
+
+
+Hippocampus Consortium M430v2 (Oct05) MAS5
+
+Hippocampus Consortium M430v2 (Oct05) RMA
+
+Hippocampus Consortium M430v2 (Oct05) PDNN
+
+Hippocampus Consortium M430v2 (Dec05) RMA
+
+Hippocampus Consortium M430v2 (Dec05) PDNN
+
+
+This text file originally generated prospectively by RWW on July 30 2005. Updated by RWW July 31, 2005.
diff --git a/general/datasets/Hc_m2_1205_p/platform.rtf b/general/datasets/Hc_m2_1205_p/platform.rtf
new file mode 100644
index 0000000..af0948c
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_p/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2_1205_p/processing.rtf b/general/datasets/Hc_m2_1205_p/processing.rtf
new file mode 100644
index 0000000..df5513b
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_p/processing.rtf
@@ -0,0 +1,40 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very senstive to the transformation method that is used. Using the PDNN transform the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For examploe, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one whould include the ssample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the of the probe level (CEL) data after step 5 below. DataDesk allows a rapid detection of subsets of probes that are particular sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. <0L>
+
+
+
+
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2_1205_p/summary.rtf b/general/datasets/Hc_m2_1205_p/summary.rtf
new file mode 100644
index 0000000..9b7c1d6
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_p/summary.rtf
@@ -0,0 +1 @@
+PRELIMINARY: The October 2005 Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of approximately 99 genetically diverse strains of mice including 68 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a set of 16 diverse inbred strains, and 2 reciprocal F1 hybrids. The hippocampus is an important and intriguing part of the forebrain that is crucial for memory formation, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3, and parts of the subiculum) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section. Samples were processed using a total of 206 Affymetrix Mouse Expression 430 2.0 short oligomer microarrays (MOE430 2.0 or M430v2), of which 179 passed stringent quality control and error checking. This particular data set was processed using the MAS5 protocol. To simplify comparisons among transforms, MAS5 values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2_1205_p/tissue.rtf b/general/datasets/Hc_m2_1205_p/tissue.rtf
new file mode 100644
index 0000000..2bb700d
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_p/tissue.rtf
@@ -0,0 +1,7 @@
+
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thanks Muriel Davission for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below).
+
diff --git a/general/datasets/Hc_m2_1205_r/acknowledgment.rtf b/general/datasets/Hc_m2_1205_r/acknowledgment.rtf
new file mode 100644
index 0000000..08c9160
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_r/acknowledgment.rtf
@@ -0,0 +1,54 @@
+
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: NIH XXXX
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Yanhua Qu, Ph.D.
+ Grant Support: NIH U01CA105417
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
+
diff --git a/general/datasets/Hc_m2_1205_r/cases.rtf b/general/datasets/Hc_m2_1205_r/cases.rtf
new file mode 100644
index 0000000..3e78bb4
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_r/cases.rtf
@@ -0,0 +1,60 @@
+This analysis has used 68 of BXD strains, the complete set of 13 CXB recombinant inbred strain sets, and a mouse diversity panel consisting of 16 inbred strains and a pair of reciprocal F1 hybrids (B6D2F1 and D2B6F1).
+
+The BXD genetic reference population of recombinant inbred strains consists of approximately 80 strains. Approximately 800 classical phenotypes from sets of 10 to 70 of these strains been integrated in the GeneNetwork. The BXD strains in this data set include 29 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD40). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+The CXB is the first and oldest set of recombinant inbred strains. Over 500 classical phenotypes from these strains been integrated in the GeneNetwork. It is noteworthy that the CXB strains segregate for the hippocampal lamination defect (Hld),characterized by Nowakowski and colleagues (1984). All of the CXBs have been recently genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ STILL IN PROGRESS (samples did not pass quality control); Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HIJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HILtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2_1205_r/experiment-design.rtf b/general/datasets/Hc_m2_1205_r/experiment-design.rtf
new file mode 100644
index 0000000..68713a4
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_r/experiment-design.rtf
@@ -0,0 +1,3252 @@
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80 deg. C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each isogenic group. While all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. Seventy-seven of 99 strains are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquotes R1291H3 and R1291H4).
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays.Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4 deg C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+
+ Data Table 1:
+
+
+This table lists all arrays by order of processing (Run), Sample ID, Strain, Sex, Age, number of animals in each sample pool (Pool), F generation number when less than 30 (GenN, and the Source of animals. SampleID is the ID number of the pooled RNA sample with a H1 through H3 suffix to indicate the actual hippocampal RNA aliquot used to prepare cRNA. Grp is the sequential group processing number (1 - 6).
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool sizel |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R2028H2 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 4.362 |
+ 64.49 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 2.78 |
+ 1.13 |
+ JAX |
+
+
+ | 2 |
+ R2029H2 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.04 |
+ 5.208 |
+ 41.21 |
+ 0.49 |
+ 0.49 |
+ 0.02 |
+ 1.62 |
+ 0.95 |
+ JAX |
+
+
+ | 3 |
+ R2030H1 |
+ A/J |
+ 57 |
+ M |
+ 5 |
+ 2 |
+ 0.06 |
+ 3.307 |
+ 45.16 |
+ 0.527 |
+ 0.454 |
+ 0.018 |
+ 1.63 |
+ 0.99 |
+ UTM RW |
+
+
+ | 4 |
+ R2032H3 |
+ AKR/J |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.054 |
+ 61.03 |
+ 0.51 |
+ 0.471 |
+ 0.018 |
+ 1.46 |
+ 0.79 |
+ JAX |
+
+
+ | 5 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 6 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
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+
+
+ | 7 |
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+
+ | 8 |
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+
+ | 9 |
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+
+ | 10 |
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+
+ | 11 |
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+
+ | 12 |
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+
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+
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+
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+
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+
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+
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+
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+
+ | 21 |
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+
+ | 22 |
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+
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+
+ | 24 |
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+
+ | 25 |
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+
+ | 26 |
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+ 1 |
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+
+ | 27 |
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+
+ | 28 |
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+
+ | 29 |
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+
+ | 30 |
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+
+ | 31 |
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+
+ | 32 |
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+
+ | 33 |
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+
+ | 34 |
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+
+ | 35 |
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+
+ | 36 |
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+
+ | 37 |
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+
+ | 38 |
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+
+ | 39 |
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+
+ | 40 |
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+
+ | 41 |
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+
+ | 42 |
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+
+ | 43 |
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+
+ | 44 |
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+
+ | 45 |
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+
+ | 46 |
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+
+ | 47 |
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+
+ | 48 |
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+
+ | 49 |
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+
+ | 50 |
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+
+ | 51 |
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+
+ | 52 |
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+
+ | 53 |
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+
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+
+ | 55 |
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+
+ | 56 |
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+
+ | 57 |
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+
+ | 58 |
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+
+ | 59 |
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+
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+
+ | 61 |
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+
+ | 62 |
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+
+ | 63 |
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+
+ | 64 |
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+
+ | 65 |
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+
+ | 66 |
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+
+ | 67 |
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+
+ | 68 |
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+
+ | 69 |
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+
+ | 70 |
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+
+ | 71 |
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+
+ | 72 |
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+
+ | 73 |
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+
+ | 74 |
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+
+
+ | 75 |
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+
+ | 76 |
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+
+
+ | 77 |
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+
+
+ | 78 |
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+
+
+ | 79 |
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+
+
+ | 80 |
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+ 3 |
+ 4 |
+ 0.01 |
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+ 0.477 |
+ 0.504 |
+ 0.019 |
+ 1.31 |
+ 0.78 |
+ UTM RW |
+
+
+ | 81 |
+ R2054H2 |
+ BXD65 |
+ 55 |
+ F |
+ 1 |
+ 2 |
+ 0.03 |
+ 3.159 |
+ 80.96 |
+ 0.48 |
+ 0.502 |
+ 0.018 |
+ 1.09 |
+ 1.24 |
+ UTM RW |
+
+
+ | 82 |
+ R2056H2 |
+ BXD65 |
+ 89 |
+ M |
+ 6 |
+ 2 |
+ 0 |
+ 2.836 |
+ 59.6 |
+ 0.504 |
+ 0.477 |
+ 0.019 |
+ 1.3 |
+ 0.75 |
+ UTM RW |
+
+
+ | 83 |
+ R1941H2 |
+ BXD66 |
+ 78 |
+ F |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.734 |
+ 50.93 |
+ 0.499 |
+ 0.481 |
+ 0.02 |
+ 1.18 |
+ 1.29 |
+ UTM RW |
+
+
+ | 84 |
+ R1949H2 |
+ BXD66 |
+ 96 |
+ M |
+ 4 |
+ 2 |
+ 0.04 |
+ 2.828 |
+ 51.27 |
+ 0.474 |
+ 0.508 |
+ 0.019 |
+ 2.05 |
+ 1.12 |
+ UTM RW |
+
+
+ | 85 |
+ R2060H1 |
+ BXD67 |
+ 54 |
+ F |
+ 6 |
+ 3 |
+ 0.01 |
+ 2.561 |
+ 43.88 |
+ 0.502 |
+ 0.479 |
+ 0.02 |
+ 1.7 |
+ 0.84 |
+ UTM RW |
+
+
+ | 86 |
+ R2052H1 |
+ BXD67 |
+ 61 |
+ M |
+ 1 |
+ 4 |
+ 0.01 |
+ 3.161 |
+ 43.23 |
+ 0.521 |
+ 0.46 |
+ 0.018 |
+ 1.09 |
+ 1.31 |
+ UTM RW |
+
+
+ | 87 |
+ R2074H1 |
+ BXD68 |
+ 60 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 6.528 |
+ 49.62 |
+ 0.479 |
+ 0.502 |
+ 0.019 |
+ 1.48 |
+ 0.83 |
+ UTM RW |
+
+
+ | 88 |
+ R1928H1 |
+ BXD68 |
+ 72 |
+ M |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.404 |
+ 48.28 |
+ 0.521 |
+ 0.459 |
+ 0.02 |
+ 1.3 |
+ 0.74 |
+ UTM RW |
+
+
+ | 89 |
+ R1439H3 |
+ BXD69 |
+ 60 |
+ F |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.463 |
+ 59.14 |
+ 0.522 |
+ 0.459 |
+ 0.018 |
+ 1.31 |
+ 0.78 |
+ UTM RW |
+
+
+ | 90 |
+ R1559H1 |
+ BXD69 |
+ 64 |
+ M |
+ 3 |
+ 3 |
+ 0.03 |
+ 2.987 |
+ 67.74 |
+ 0.486 |
+ 0.496 |
+ 0.017 |
+ 1.38 |
+ 0.8 |
+ UTM RW |
+
+
+ | 91 |
+ R2134H1 |
+ BXD70 |
+ 64 |
+ F |
+ 5 |
+ 2 |
+ 0.02 |
+ 2.148 |
+ 58.64 |
+ 0.532 |
+ 0.45 |
+ 0.019 |
+ 1.4 |
+ 0.85 |
+ UTM RW |
+
+
+ | 92 |
+ R2063H1 |
+ BXD70 |
+ 55 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.481 |
+ 55.32 |
+ 0.513 |
+ 0.469 |
+ 0.018 |
+ 1.28 |
+ 0.71 |
+ UTM RW |
+
+
+ | 93 |
+ R1277H1 |
+ BXD73 |
+ 60 |
+ F |
+ 4 |
+ 2 |
+ 0.01 |
+ 2.576 |
+ 62.45 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.35 |
+ 0.79 |
+ UTM RW |
+
+
+ | 94 |
+ R1443H2 |
+ BXD73 |
+ 76 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.312 |
+ 64.34 |
+ 0.499 |
+ 0.481 |
+ 0.02 |
+ 1.48 |
+ 0.77 |
+ UTM RW |
+
+
+ | 95 |
+ R2055H2 |
+ BXD74 |
+ 79 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.576 |
+ 56.84 |
+ 0.509 |
+ 0.473 |
+ 0.018 |
+ 1.46 |
+ 0.88 |
+ UTM RW |
+
+
+ | 96 |
+ R2316H1 |
+ BXD74 |
+ 193 |
+ M |
+ 5 |
+ 2 |
+ 0.01 |
+ 3.457 |
+ 55.35 |
+ 0.508 |
+ 0.471 |
+ 0.02 |
+ 1.17 |
+ 0.78 |
+ UTM RW |
+
+
+ | 97 |
+ R1871H1 |
+ BXD75 |
+ 61 |
+ F |
+ 2 |
+ 3 |
+ 0.04 |
+ 1.723 |
+ 56.4 |
+ 0.53 |
+ 0.451 |
+ 0.019 |
+ 1.3 |
+ 0.76 |
+ UTM RW |
+
+
+ | 98 |
+ R1844H2 |
+ BXD75 |
+ 90 |
+ M |
+ 3 |
+ 4 |
+ 0.01 |
+ 1.934 |
+ 56.23 |
+ 0.52 |
+ 0.461 |
+ 0.019 |
+ 1.62 |
+ 0.86 |
+ UTM RW |
+
+
+ | 99 |
+ R1948H2 |
+ BXD76 |
+ 81 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 1.507 |
+ 68.85 |
+ 0.553 |
+ 0.428 |
+ 0.02 |
+ 1.3 |
+ 0.75 |
+ UTM RW |
+
+
+ | 100 |
+ R2094H1 |
+ BXD76 |
+ 61 |
+ M |
+ 5 |
+ 4 |
+ 0.01 |
+ 3.299 |
+ 42.69 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 1.39 |
+ 0.88 |
+ UTM RW |
+
+
+ | 101 |
+ R2262H1 |
+ BXD77 |
+ 62 |
+ F |
+ 3 |
+ 4 |
+ 0.02 |
+ 4.317 |
+ 47.16 |
+ 0.493 |
+ 0.488 |
+ 0.019 |
+ 1.32 |
+ 0.74 |
+ UTM RW |
+
+
+ | 102 |
+ R1423H1 |
+ BXD77 |
+ 62 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.071 |
+ 54.15 |
+ 0.51 |
+ 0.471 |
+ 0.019 |
+ 1.26 |
+ 0.74 |
+ UTM RW |
+
+
+ | 103 |
+ R1947H1 |
+ BXD79 |
+ 108 |
+ F |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.599 |
+ 51.52 |
+ 0.524 |
+ 0.457 |
+ 0.019 |
+ 1.35 |
+ 0.74 |
+ UTM RW |
+
+
+ | 104 |
+ R2092H1 |
+ BXD79 |
+ 86 |
+ M |
+ 5 |
+ 4 |
+ 0.06 |
+ 3.735 |
+ 42.25 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 2.94 |
+ 1.06 |
+ UTM RW |
+
+
+ | 105 |
+ R1880H1 |
+ BXD80 |
+ 68 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 4.855 |
+ 42.22 |
+ 0.501 |
+ 0.481 |
+ 0.018 |
+ 2.17 |
+ 1.36 |
+ UTM RW |
+
+
+ | 106 |
+ R1881H2 |
+ BXD80 |
+ 68 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.073 |
+ 48.93 |
+ 0.524 |
+ 0.458 |
+ 0.019 |
+ 1.34 |
+ 0.83 |
+ UTM RW |
+
+
+ | 107 |
+ R2075H1 |
+ BXD83 |
+ 60 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.454 |
+ 55.1 |
+ 0.502 |
+ 0.48 |
+ 0.018 |
+ 1.27 |
+ 0.77 |
+ UTM RW |
+
+
+ | 108 |
+ R2076H2 |
+ BXD83 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.03 |
+ 2.624 |
+ 55.65 |
+ 0.495 |
+ 0.488 |
+ 0.018 |
+ 2.21 |
+ 0.94 |
+ UTM RW |
+
+
+ | 109 |
+ R2077H2 |
+ BXD84 |
+ 62 |
+ F |
+ 6 |
+ 2 |
+ 0 |
+ 2.1 |
+ 71.87 |
+ 0.522 |
+ 0.459 |
+ 0.018 |
+ 1.68 |
+ 0.81 |
+ UTM RW |
+
+
+ | 110 |
+ R2135H3 |
+ BXD84 |
+ 75 |
+ M |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.467 |
+ 64.46 |
+ 0.505 |
+ 0.476 |
+ 0.019 |
+ 1.2 |
+ 0.74 |
+ UTM RW |
+
+
+ | 111 |
+ R1473H1 |
+ BXD85 |
+ 79 |
+ F |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.384 |
+ 55.34 |
+ 0.478 |
+ 0.502 |
+ 0.02 |
+ 1.24 |
+ 0.77 |
+ UTM RW |
+
+
+ | 112 |
+ R1474H1 |
+ BXD85 |
+ 57 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.831 |
+ 55.24 |
+ 0.522 |
+ 0.461 |
+ 0.018 |
+ 1.04 |
+ 1.29 |
+ UTM RW |
+
+
+ | 113 |
+ R1597H1 |
+ BXD85 |
+ 86 |
+ M |
+ 4 |
+ 4 |
+ 0.09 |
+ 2.028 |
+ 53.95 |
+ 0.487 |
+ 0.492 |
+ 0.021 |
+ 1.28 |
+ 0.83 |
+ UTM RW |
+
+
+ | 114 |
+ R1415H1 |
+ BXD86 |
+ 77 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 2.525 |
+ 53.16 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.66 |
+ 0.91 |
+ UTM RW |
+
+
+ | 115 |
+ R1710H1 |
+ BXD87 |
+ 84 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 2.697 |
+ 56.4 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 116 |
+ R1872H2 |
+ BXD89 |
+ 90 |
+ F |
+ 2 |
+ 2 |
+ 0.02 |
+ 3.013 |
+ 63.53 |
+ 0.492 |
+ 0.488 |
+ 0.021 |
+ 1.22 |
+ 0.72 |
+ UTM RW |
+
+
+ | 117 |
+ R1850H3 |
+ BXD89 |
+ 82 |
+ M |
+ 4 |
+ 4 |
+ 0.03 |
+ 2.736 |
+ 44.89 |
+ 0.498 |
+ 0.483 |
+ 0.019 |
+ 1.5 |
+ 0.83 |
+ UTM RW |
+
+
+ | 118 |
+ R2058H1 |
+ BXD90 |
+ 61 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 3.389 |
+ 48.05 |
+ 0.502 |
+ 0.478 |
+ 0.02 |
+ 1.53 |
+ 0.76 |
+ UTM RW |
+
+
+ | 119 |
+ R1301H2 |
+ BXD92 |
+ 58 |
+ F |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.543 |
+ 41.97 |
+ 0.522 |
+ 0.46 |
+ 0.018 |
+ 1.5 |
+ 0.79 |
+ UTM RW |
+
+
+ | 120 |
+ R1309H1 |
+ BXD92 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.05 |
+ 1.655 |
+ 66.34 |
+ 0.498 |
+ 0.481 |
+ 0.021 |
+ 1.52 |
+ 0.82 |
+ UTM RW |
+
+
+ | 121 |
+ R2057H1 |
+ BXD93 |
+ 92 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.033 |
+ 44.41 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 1.22 |
+ 0.78 |
+ UTM RW |
+
+
+ | 122 |
+ R2059H1 |
+ BXD93 |
+ 58 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.058 |
+ 60.29 |
+ 0.493 |
+ 0.488 |
+ 0.019 |
+ 1.18 |
+ 1.37 |
+ UTM RW |
+
+
+ | 123 |
+ R2313H1 |
+ BXD94 |
+ 59 |
+ F |
+ 3 |
+ 3 |
+ 0 |
+ 3.091 |
+ 59.45 |
+ 0.487 |
+ 0.495 |
+ 0.018 |
+ 1.34 |
+ 0.73 |
+ UTM RW |
+
+
+ | 124 |
+ R1915H1 |
+ BXD96 |
+ 65 |
+ F |
+ 5 |
+ 2 |
+ 0.04 |
+ 5.145 |
+ 46.19 |
+ 0.502 |
+ 0.481 |
+ 0.017 |
+ 1.37 |
+ 0.74 |
+ UTM RW |
+
+
+ | 125 |
+ R1846H2 |
+ BXD96 |
+ 63 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.159 |
+ 55.85 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.92 |
+ 1.26 |
+ UTM RW |
+
+
+ | 126 |
+ R1927H2 |
+ BXD97 |
+ 67 |
+ M |
+ 1 |
+ 3 |
+ 0.04 |
+ 2.622 |
+ 57.81 |
+ 0.539 |
+ 0.444 |
+ 0.017 |
+ 1.45 |
+ 1.32 |
+ UTM RW |
+
+
+ | 127 |
+ R1942H1 |
+ BXD98 |
+ 62 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.104 |
+ 48.42 |
+ 0.528 |
+ 0.454 |
+ 0.019 |
+ 2.22 |
+ 1.08 |
+ UTM RW |
+
+
+ | 128 |
+ R1943H2 |
+ BXD98 |
+ 62 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.04 |
+ 56.85 |
+ 0.484 |
+ 0.497 |
+ 0.019 |
+ 1.18 |
+ 0.76 |
+ UTM RW |
+
+
+ | 129 |
+ R2197H1 |
+ BXD99 |
+ 70 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.288 |
+ 51.75 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.35 |
+ 0.81 |
+ UTM RW |
+
+
+ | 130 |
+ R2315H1 |
+ BXD99 |
+ 84 |
+ M |
+ 5 |
+ 2 |
+ 0.03 |
+ 6.036 |
+ 43.05 |
+ 0.484 |
+ 0.497 |
+ 0.018 |
+ 1.7 |
+ 0.96 |
+ UTM RW |
+
+
+ | 131 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 132 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 133 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 134 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
+ 3.058 |
+ 51.87 |
+ 0.477 |
+ 0.503 |
+ 0.02 |
+ 1.67 |
+ 0.76 |
+ UTM RW |
+
+
+ | 135 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
+ 3.341 |
+ 49.26 |
+ 0.527 |
+ 0.456 |
+ 0.018 |
+ 1.14 |
+ 1.45 |
+ UTM RW |
+
+
+ | 136 |
+ R1449H2 |
+ C57BL/6J |
+ 71 |
+ M |
+ 5 |
+ 3 |
+ 0.09 |
+ 3.592 |
+ 44.32 |
+ 0.47 |
+ 0.51 |
+ 0.02 |
+ 1.68 |
+ 0.77 |
+ UTM DG |
+
+
+ | 137 |
+ R2619H1 |
+ CAST/Ei |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 138 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 139 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 140 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 141 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 142 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 143 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 144 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 145 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+ | 146 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 147 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 148 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 149 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 150 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 151 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 152 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 153 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 154 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 155 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 156 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 157 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 158 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 159 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 160 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 161 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 162 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 163 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 2.579 |
+ 58.49 |
+ 0.506 |
+ 0.475 |
+ 0.019 |
+ 2.49 |
+ 1.21 |
+ UTM RW |
+
+
+ | 164 |
+ R1551H1 |
+ D2B6F1 |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.62 |
+ 53.76 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 1.37 |
+ 0.76 |
+ UTM RW |
+
+
+ | 165 |
+ R1468H1 |
+ DBA/2J |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.03 |
+ 2.929 |
+ 53.8 |
+ 0.515 |
+ 0.465 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 166 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 167 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 168 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 169 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 170 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 171 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 172 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 173 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 174 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 175 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 176 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 177 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 178 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Hc_m2_1205_r/notes.rtf b/general/datasets/Hc_m2_1205_r/notes.rtf
new file mode 100644
index 0000000..4490ee3
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_r/notes.rtf
@@ -0,0 +1,15 @@
+This study includes the following datasets:
+
+
+Hippocampus Consortium M430v2 (Oct05) MAS5
+
+Hippocampus Consortium M430v2 (Oct05) RMA
+
+Hippocampus Consortium M430v2 (Oct05) PDNN
+
+Hippocampus Consortium M430v2 (Dec05) RMA
+
+Hippocampus Consortium M430v2 (Dec05) PDNN
+
+
+This text file originally generated prospectively by RWW on July 30 2005. Updated by RWW July 31, 2005.
diff --git a/general/datasets/Hc_m2_1205_r/platform.rtf b/general/datasets/Hc_m2_1205_r/platform.rtf
new file mode 100644
index 0000000..af0948c
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_r/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2_1205_r/processing.rtf b/general/datasets/Hc_m2_1205_r/processing.rtf
new file mode 100644
index 0000000..df5513b
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_r/processing.rtf
@@ -0,0 +1,40 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very senstive to the transformation method that is used. Using the PDNN transform the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For examploe, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one whould include the ssample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the of the probe level (CEL) data after step 5 below. DataDesk allows a rapid detection of subsets of probes that are particular sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. <0L>
+
+
+
+
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2_1205_r/summary.rtf b/general/datasets/Hc_m2_1205_r/summary.rtf
new file mode 100644
index 0000000..9b7c1d6
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_r/summary.rtf
@@ -0,0 +1 @@
+PRELIMINARY: The October 2005 Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of approximately 99 genetically diverse strains of mice including 68 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a set of 16 diverse inbred strains, and 2 reciprocal F1 hybrids. The hippocampus is an important and intriguing part of the forebrain that is crucial for memory formation, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3, and parts of the subiculum) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section. Samples were processed using a total of 206 Affymetrix Mouse Expression 430 2.0 short oligomer microarrays (MOE430 2.0 or M430v2), of which 179 passed stringent quality control and error checking. This particular data set was processed using the MAS5 protocol. To simplify comparisons among transforms, MAS5 values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2_1205_r/tissue.rtf b/general/datasets/Hc_m2_1205_r/tissue.rtf
new file mode 100644
index 0000000..2bb700d
--- /dev/null
+++ b/general/datasets/Hc_m2_1205_r/tissue.rtf
@@ -0,0 +1,7 @@
+
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thanks Muriel Davission for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below).
+
diff --git a/general/datasets/Hc_m2_1206_r/acknowledgment.rtf b/general/datasets/Hc_m2_1206_r/acknowledgment.rtf
new file mode 100644
index 0000000..aa6285a
--- /dev/null
+++ b/general/datasets/Hc_m2_1206_r/acknowledgment.rtf
@@ -0,0 +1,61 @@
+
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integrative Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Yanhua Qu, Ph.D.
+ Grant Support: NIH U01CA105417
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
diff --git a/general/datasets/Hc_m2_1206_r/cases.rtf b/general/datasets/Hc_m2_1206_r/cases.rtf
new file mode 100644
index 0000000..28305bf
--- /dev/null
+++ b/general/datasets/Hc_m2_1206_r/cases.rtf
@@ -0,0 +1,3791 @@
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 27 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 strains are available from Lu Lu and colleagues at UTHSC.
+
+
+
+This table lists all arrays by order of processing (Run), Sample ID, Strain, Sex, Age, number of animals in each sample pool (Pool), F generation number when less than 30 (GenN, and the Source of animals. SampleID is the ID number of the pooled RNA sample with a H1 through H3 suffix to indicate the actual hippocampal RNA aliquot used to prepare cRNA. Grp is the sequential group processing number (1 - 6).
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool sizel |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R2028H2 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 4.362 |
+ 64.49 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 2.78 |
+ 1.13 |
+ JAX |
+
+
+ | 2 |
+ R2029H2 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.04 |
+ 5.208 |
+ 41.21 |
+ 0.49 |
+ 0.49 |
+ 0.02 |
+ 1.62 |
+ 0.95 |
+ JAX |
+
+
+ | 3 |
+ R2670H1 |
+ A/J |
+ 65 |
+ F |
+ 7 |
+ 3 |
+ 0.04 |
+ 3.951 |
+ 46.8 |
+ 0.498 |
+ 0.485 |
+ 0.017 |
+ 1.32 |
+ 0.75 |
+ UTM RW |
+
+
+ | 4 |
+ R2030H1 |
+ A/J |
+ 57 |
+ M |
+ 5 |
+ 2 |
+ 0.06 |
+ 3.307 |
+ 45.16 |
+ 0.527 |
+ 0.454 |
+ 0.018 |
+ 1.63 |
+ 0.99 |
+ UTM RW |
+
+
+ | 5 |
+ R2032H3 |
+ AKR/J |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.054 |
+ 61.03 |
+ 0.51 |
+ 0.471 |
+ 0.018 |
+ 1.46 |
+ 0.79 |
+ JAX |
+
+
+ | 6 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 7 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 8 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 9 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 10 |
+ R1675H1 |
+ BALB/cByJ |
+ 83 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.405 |
+ 48.13 |
+ 0.509 |
+ 0.474 |
+ 0.018 |
+ 1.13 |
+ 0.78 |
+ JAX |
+
+
+ | 11 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 12 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 13 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 14 |
+ R1507H1 |
+ BXD1 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.056 |
+ 60.17 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.15 |
+ 0.76 |
+ Glenn |
+
+
+ | 15 |
+ R1542H1 |
+ BXD1 |
+ 59 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.792 |
+ 80.56 |
+ 0.492 |
+ 0.489 |
+ 0.018 |
+ 1.57 |
+ 0.79 |
+ Glenn |
+
+
+ | 16 |
+ R1520H1 |
+ BXD2 |
+ 56 |
+ F |
+ 4 |
+ 4 |
+ 0.09 |
+ 1.715 |
+ 71.62 |
+ 0.515 |
+ 0.467 |
+ 0.018 |
+ 2.36 |
+ 1.6 |
+ Glenn |
+
+
+ | 17 |
+ R1516H1 |
+ BXD2 |
+ 61 |
+ M |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.231 |
+ 64.86 |
+ 0.508 |
+ 0.474 |
+ 0.019 |
+ 1.3 |
+ 1.53 |
+ Glenn |
+
+
+ | 18 |
+ R1593H2 |
+ BXD5 |
+ 60 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 1.913 |
+ 59.96 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.98 |
+ 1.44 |
+ Glenn |
+
+
+ | 19 |
+ R1692H1 |
+ BXD5 |
+ 60 |
+ M |
+ 3 |
+ 2 |
+ 0.07 |
+ 3.764 |
+ 72.74 |
+ 0.465 |
+ 0.516 |
+ 0.02 |
+ 1.15 |
+ 0.74 |
+ Glenn |
+
+
+ | 20 |
+ R1539H2 |
+ BXD6 |
+ 59 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 2.488 |
+ 54.97 |
+ 0.518 |
+ 0.463 |
+ 0.018 |
+ 1.08 |
+ 1.33 |
+ Glenn |
+
+
+ | 21 |
+ R1538H1 |
+ BXD6 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.01 |
+ 2.585 |
+ 50.27 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 1.46 |
+ 0.79 |
+ Glenn |
+
+
+ | 22 |
+ R1518H1 |
+ BXD8 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 2.92 |
+ 54.84 |
+ 0.515 |
+ 0.465 |
+ 0.02 |
+ 1.32 |
+ 1.24 |
+ Glenn |
+
+
+ | 23 |
+ R1548H1 |
+ BXD8 |
+ 59 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.132 |
+ 59.37 |
+ 0.504 |
+ 0.477 |
+ 0.019 |
+ 2.16 |
+ 1.54 |
+ Glenn |
+
+
+ | 24 |
+ R1350H2 |
+ BXD9 |
+ 86 |
+ F |
+ 1 |
+ 3 |
+ 0.05 |
+ 2.771 |
+ 60.62 |
+ 0.5 |
+ 0.482 |
+ 0.018 |
+ 1.01 |
+ 1.28 |
+ UMemphis |
+
+
+ | 25 |
+ R1523H3 |
+ BXD9 |
+ 57 |
+ M |
+ 7 |
+ 3 |
+ 0.14 |
+ 3.9 |
+ 78.36 |
+ 0.435 |
+ 0.547 |
+ 0.018 |
+ 1.36 |
+ 0.77 |
+ UTM RW |
+
+
+ | 26 |
+ R1531H1 |
+ BXD11 |
+ 56 |
+ F |
+ 6 |
+ 3 |
+ 0.06 |
+ 2.229 |
+ 56.36 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 2.23 |
+ 1.02 |
+ Glenn |
+
+
+ | 27 |
+ R1367H1 |
+ BXD11 |
+ 56 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.11 |
+ 78.78 |
+ 0.503 |
+ 0.477 |
+ 0.02 |
+ 1.07 |
+ 1.27 |
+ Glenn |
+
+
+ | 28 |
+ R1530H1 |
+ BXD12 |
+ 58 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 3.227 |
+ 53.77 |
+ 0.505 |
+ 0.477 |
+ 0.018 |
+ 0.95 |
+ 1.4 |
+ Glenn |
+
+
+ | 29 |
+ R2674H1 |
+ BXD12 |
+ 59 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.924 |
+ 83.44 |
+ 0.519 |
+ 0.464 |
+ 0.018 |
+ 1.21 |
+ 0.78 |
+ Glenn |
+
+
+ | 30 |
+ R1529H1 |
+ BXD13 |
+ 58 |
+ F |
+ 6 |
+ 3 |
+ 0.05 |
+ 2.55 |
+ 59.05 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 2 |
+ 1.54 |
+ Glenn |
+
+
+ | 31 |
+ R1662H2 |
+ BXD13 |
+ 60 |
+ M |
+ 1 |
+ 3 |
+ 0.03 |
+ 4.603 |
+ 45.81 |
+ 0.509 |
+ 0.472 |
+ 0.019 |
+ 1.3 |
+ 0.82 |
+ Glenn |
+
+
+ | 32 |
+ R1304H2 |
+ BXD14 |
+ 72 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.946 |
+ 61.87 |
+ 0.484 |
+ 0.498 |
+ 0.018 |
+ 1.22 |
+ 0.77 |
+ UTM RW |
+
+
+ | 33 |
+ R1278H2 |
+ BXD14 |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.06 |
+ 4.75 |
+ 67.52 |
+ 0.449 |
+ 0.532 |
+ 0.019 |
+ 1.1 |
+ 0.73 |
+ UTM RW |
+
+
+ | 34 |
+ R1524H1 |
+ BXD15 |
+ 60 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.961 |
+ 50.93 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 1.74 |
+ 0.91 |
+ Glenn |
+
+
+ | 35 |
+ R1515H1 |
+ BXD15 |
+ 61 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.316 |
+ 57.05 |
+ 0.503 |
+ 0.478 |
+ 0.019 |
+ 1.32 |
+ 1.21 |
+ Glenn |
+
+
+ | 36 |
+ R1661H1 |
+ BXD16 |
+ 61 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.778 |
+ 59.81 |
+ 0.516 |
+ 0.466 |
+ 0.019 |
+ 1.39 |
+ 1.2 |
+ Glenn |
+
+
+ | 37 |
+ R1594H1 |
+ BXD16 |
+ 61 |
+ M |
+ 4 |
+ 3 |
+ 0.03 |
+ 2.634 |
+ 53.66 |
+ 0.504 |
+ 0.478 |
+ 0.018 |
+ 1.96 |
+ 1.51 |
+ Glenn |
+
+
+ | 38 |
+ R2666H1 |
+ BXD19 |
+ 60 |
+ F |
+ 7 |
+ 3 |
+ 0.02 |
+ 2.498 |
+ 76.2 |
+ 0.495 |
+ 0.486 |
+ 0.019 |
+ 1.41 |
+ 0.77 |
+ Glenn |
+
+
+ | 39 |
+ R1471H1 |
+ BXD19 |
+ 157 |
+ M |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.165 |
+ 43.34 |
+ 0.519 |
+ 0.462 |
+ 0.018 |
+ 1.01 |
+ 1.29 |
+ UTM JB |
+
+
+ | 40 |
+ R1573H1 |
+ BXD20 |
+ 59 |
+ F |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.749 |
+ 52.7 |
+ 0.513 |
+ 0.469 |
+ 0.018 |
+ 1.01 |
+ 1.27 |
+ Glenn |
+
+
+ | 41 |
+ R2507H1 |
+ BXD20 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.06 |
+ 3.568 |
+ 57 |
+ 0.472 |
+ 0.508 |
+ 0.02 |
+ 1.29 |
+ 0.76 |
+ Glenn |
+
+
+ | 42 |
+ R1347H2 |
+ BXD21 |
+ 64 |
+ F |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.881 |
+ 61.49 |
+ 0.494 |
+ 0.486 |
+ 0.019 |
+ 0.92 |
+ 1.22 |
+ UMemphis |
+
+
+ | 43 |
+ R2668H1 |
+ BXD21 |
+ 60 |
+ M |
+ 7 |
+ 4 |
+ 0.07 |
+ 2.605 |
+ 44.9 |
+ 0.535 |
+ 0.449 |
+ 0.017 |
+ 1.54 |
+ 0.76 |
+ Glenn |
+
+
+ | 44 |
+ R1337H2 |
+ BXD21 |
+ 102 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.673 |
+ 58.05 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.4 |
+ 0.76 |
+ UAB |
+
+
+ | 45 |
+ R1848H3 |
+ BXD22 |
+ 196 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.943 |
+ 51.7 |
+ 0.494 |
+ 0.485 |
+ 0.021 |
+ 2.2 |
+ 0.78 |
+ UAB |
+
+
+ | 46 |
+ R1525H1 |
+ BXD22 |
+ 59 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.248 |
+ 55.76 |
+ 0.548 |
+ 0.433 |
+ 0.018 |
+ 1.26 |
+ 0.74 |
+ Glenn |
+
+
+ | 47 |
+ R1280H2 |
+ BXD23 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.187 |
+ 54.63 |
+ 0.458 |
+ 0.523 |
+ 0.019 |
+ 0.96 |
+ 1.2 |
+ UTM RW |
+
+
+ | 48 |
+ R1537H1 |
+ BXD23 |
+ 58 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.719 |
+ 67.54 |
+ 0.468 |
+ 0.513 |
+ 0.019 |
+ 1.51 |
+ 0.96 |
+ Glenn |
+
+
+ | 49 |
+ R1244H2 |
+ BXD23 |
+ 65 |
+ M |
+ 7 |
+ 3 |
+ 0.05 |
+ 1.257 |
+ 81.93 |
+ 0.565 |
+ 0.417 |
+ 0.018 |
+ 1.24 |
+ 0.74 |
+ Glenn |
+
+
+ | 50 |
+ R1343H2 |
+ BXD24 |
+ 71 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.083 |
+ 65.07 |
+ 0.506 |
+ 0.474 |
+ 0.019 |
+ 1.46 |
+ 0.75 |
+ UMemphis |
+
+
+ | 51 |
+ R1517H1 |
+ BXD24 |
+ 57 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.471 |
+ 53.66 |
+ 0.504 |
+ 0.476 |
+ 0.019 |
+ 1.28 |
+ 0.78 |
+ Glenn |
+
+
+ | 52 |
+ R1366H1 |
+ BXD27 |
+ 60 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.26 |
+ 48.46 |
+ 0.518 |
+ 0.463 |
+ 0.019 |
+ 1.29 |
+ 0.77 |
+ Glenn |
+
+
+ | 53 |
+ R1849H1 |
+ BXD27 |
+ 70 |
+ M |
+ 5 |
+ 3 |
+ 0.06 |
+ 8.801 |
+ 38.34 |
+ 0.468 |
+ 0.512 |
+ 0.019 |
+ 2.42 |
+ 1.08 |
+ UAB |
+
+
+ | 54 |
+ R1353H1 |
+ BXD28 |
+ 79 |
+ F |
+ 3 |
+ 4 |
+ 0.01 |
+ 3.22 |
+ 76.22 |
+ 0.48 |
+ 0.5 |
+ 0.02 |
+ 1.33 |
+ 0.78 |
+ UMemphis |
+
+
+ | 55 |
+ R2332H1 |
+ BXD28 |
+ 60 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 3.217 |
+ 63.68 |
+ 0.491 |
+ 0.49 |
+ 0.019 |
+ 1.37 |
+ 0.79 |
+ Glenn |
+
+
+ | 56 |
+ R1532H1 |
+ BXD29 |
+ 57 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.122 |
+ 59.18 |
+ 0.524 |
+ 0.456 |
+ 0.019 |
+ 1.17 |
+ 0.76 |
+ Glenn |
+
+
+ | 57 |
+ R1356H1 |
+ BXD29 |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.01 |
+ 4.033 |
+ 47.67 |
+ 0.52 |
+ 0.463 |
+ 0.017 |
+ 1.17 |
+ 0.78 |
+ UMemphis |
+
+
+ | 58 |
+ R1240H2 |
+ BXD31 |
+ 61 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.335 |
+ 65.17 |
+ 0.507 |
+ 0.474 |
+ 0.019 |
+ 1.31 |
+ 0.78 |
+ UTM RW |
+
+
+ | 59 |
+ R1526H2 |
+ BXD31 |
+ 57 |
+ F |
+ 7 |
+ 4 |
+ 0.1 |
+ 7.267 |
+ 89.54 |
+ 0.435 |
+ 0.547 |
+ 0.017 |
+ 1.35 |
+ 0.78 |
+ UTM RW |
+
+
+ | 60 |
+ R2675H1 |
+ BXD32 |
+ 57 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 2.268 |
+ 78.01 |
+ 0.502 |
+ 0.478 |
+ 0.02 |
+ 1.22 |
+ 0.78 |
+ Glenn |
+
+
+ | 61 |
+ R1508H2 |
+ BXD32 |
+ 58 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 1.917 |
+ 67.78 |
+ 0.539 |
+ 0.442 |
+ 0.019 |
+ 1.28 |
+ 0.73 |
+ Glenn |
+
+
+ | 62 |
+ R1345H3 |
+ BXD33 |
+ 65 |
+ F |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.098 |
+ 63.14 |
+ 0.522 |
+ 0.459 |
+ 0.019 |
+ 1.27 |
+ 0.73 |
+ UMemphis |
+
+
+ | 63 |
+ R1581H1 |
+ BXD33 |
+ 59 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.229 |
+ 53.16 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.19 |
+ 0.78 |
+ Glenn |
+
+
+ | 64 |
+ R1527H1 |
+ BXD34 |
+ 59 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.3 |
+ 58.92 |
+ 0.51 |
+ 0.471 |
+ 0.019 |
+ 1.24 |
+ 0.76 |
+ Glenn |
+
+
+ | 65 |
+ R1339H3 |
+ BXD34 |
+ 74 |
+ M |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.888 |
+ 53.49 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 2.39 |
+ 1.35 |
+ UMemphis |
+
+
+ | 66 |
+ R1469H1 |
+ BXD36 |
+ 83 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 3.473 |
+ 49.9 |
+ 0.494 |
+ 0.486 |
+ 0.02 |
+ 1.11 |
+ 0.76 |
+ UMemphis |
+
+
+ | 67 |
+ R1363H1 |
+ BXD36 |
+ 77 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 2.184 |
+ 48.19 |
+ 0.538 |
+ 0.443 |
+ 0.02 |
+ 1.28 |
+ 0.77 |
+ UMemphis |
+
+
+ | 68 |
+ R1855H1 |
+ BXD38 |
+ 55 |
+ F |
+ 3 |
+ 4 |
+ 0.01 |
+ 3.536 |
+ 54.54 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.39 |
+ 0.75 |
+ Glenn |
+
+
+ | 69 |
+ R1510H1 |
+ BXD38 |
+ 59 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.186 |
+ 68.06 |
+ 0.521 |
+ 0.46 |
+ 0.019 |
+ 1.26 |
+ 0.79 |
+ Glenn |
+
+
+ | 70 |
+ R1528H2 |
+ BXD39 |
+ 59 |
+ F |
+ 2 |
+ 3 |
+ 0.03 |
+ 4.717 |
+ 38.3 |
+ 0.511 |
+ 0.47 |
+ 0.02 |
+ 1.12 |
+ 0.75 |
+ Glenn |
+
+
+ | 71 |
+ R1514H1 |
+ BXD39 |
+ 59 |
+ M |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.992 |
+ 56.06 |
+ 0.477 |
+ 0.504 |
+ 0.019 |
+ 1.43 |
+ 0.81 |
+ Glenn |
+
+
+ | 72 |
+ R1522H1 |
+ BXD40 |
+ 59 |
+ F |
+ 4 |
+ 4 |
+ 0 |
+ 2.631 |
+ 67.16 |
+ 0.49 |
+ 0.491 |
+ 0.018 |
+ 1.56 |
+ 0.77 |
+ Glenn |
+
+
+ | 73 |
+ R1359H1 |
+ BXD40 |
+ 73 |
+ M |
+ 2 |
+ 3 |
+ 0.09 |
+ 7.458 |
+ 39.86 |
+ 0.451 |
+ 0.527 |
+ 0.021 |
+ 1.28 |
+ 0.74 |
+ UMemphis |
+
+
+ | 74 |
+ R1541H2 |
+ BXD42 |
+ 58 |
+ F |
+ 7 |
+ 3 |
+ 0.07 |
+ 6.784 |
+ 52.12 |
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+
+
+ | 75 |
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+ 58 |
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+ 7 |
+ 4 |
+ 0.03 |
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+
+
+ | 76 |
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+ 59 |
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+ 1 |
+ 3 |
+ 0 |
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+ 2.06 |
+ UTM RW |
+
+
+ | 77 |
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+ BXD43 |
+ 63 |
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+ 3 |
+ 4 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 78 |
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+ 65 |
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+ 3 |
+ 4 |
+ 0 |
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+
+
+ | 79 |
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+ BXD44 |
+ 56 |
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+ 1 |
+ 3 |
+ 0.02 |
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+
+
+ | 80 |
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+ 63 |
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+ 7 |
+ 2 |
+ 0.03 |
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+
+
+ | 81 |
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+ 7 |
+ 4 |
+ 0.04 |
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+
+
+ | 82 |
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+ 58 |
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+ 4 |
+ 3 |
+ 0 |
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+
+
+ | 83 |
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+ 65 |
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+ 3 |
+ 4 |
+ 0.05 |
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+
+
+ | 84 |
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+ 6 |
+ 4 |
+ 0.01 |
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+
+
+ | 85 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 86 |
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+ 66 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+
+ | 87 |
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+ 6 |
+ 4 |
+ 0.03 |
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+
+
+ | 88 |
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+ 7 |
+ 3 |
+ 0.07 |
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+
+
+ | 89 |
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+ 4 |
+ 3 |
+ 0.01 |
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+
+
+ | 90 |
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+ 59 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 91 |
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+ 7 |
+ 4 |
+ 0.03 |
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+
+
+ | 92 |
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+ 1 |
+ 2 |
+ 0 |
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+
+
+ | 93 |
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+ 1 |
+ 4 |
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+
+
+ | 94 |
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+ 6 |
+ 4 |
+ 0.01 |
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+
+
+ | 95 |
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+ 1 |
+ 3 |
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+
+
+ | 96 |
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+ 6 |
+ 3 |
+ 0.02 |
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+
+
+ | 97 |
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+ 1 |
+ 3 |
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+
+
+ | 98 |
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+ 3 |
+ 4 |
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+
+
+ | 99 |
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+ 1 |
+ 2 |
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+
+
+ | 100 |
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+ 6 |
+ 2 |
+ 0 |
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+
+
+ | 101 |
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+ 1 |
+ 4 |
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+
+
+ | 102 |
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+ 4 |
+ 2 |
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+
+
+ | 103 |
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+ 6 |
+ 3 |
+ 0.01 |
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+
+
+ | 104 |
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+ 1 |
+ 4 |
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+
+
+ | 105 |
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+ 3 |
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+
+
+ | 106 |
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+ 2 |
+ 2 |
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+
+
+ | 107 |
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+ 3 |
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+
+
+ | 108 |
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+ 3 |
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+
+
+ | 109 |
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+ 2 |
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+
+
+ | 110 |
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+ 3 |
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+
+
+ | 111 |
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+ 2 |
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+
+
+ | 112 |
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+ 3 |
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+
+
+ | 113 |
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+
+
+ | 114 |
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+
+
+ | 115 |
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+
+
+ | 116 |
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+
+
+ | 117 |
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+
+
+ | 118 |
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+
+
+ | 119 |
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+
+
+ | 120 |
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+
+
+ | 121 |
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+ 2 |
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+
+
+ | 122 |
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+
+
+ | 123 |
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+
+
+ | 124 |
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+ 3 |
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+
+
+ | 125 |
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+
+
+ | 126 |
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+
+
+ | 127 |
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+ 2 |
+ 0 |
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+
+
+ | 128 |
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+ 2 |
+ 0.01 |
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+
+
+ | 129 |
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+ 3 |
+ 0.02 |
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+
+
+ | 130 |
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+ 3 |
+ 0.01 |
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+
+
+ | 131 |
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+ 4 |
+ 0.09 |
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+
+
+ | 132 |
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+ 3 |
+ 0.02 |
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+
+
+ | 133 |
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+ 3 |
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+
+
+ | 134 |
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+ 4 |
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+
+
+ | 135 |
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+ 2 |
+ 0.02 |
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+
+
+ | 136 |
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+ 4 |
+ 0.03 |
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+
+
+ | 137 |
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+ 3 |
+ 0.01 |
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+
+
+ | 138 |
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+ 4 |
+ 0.03 |
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+
+
+ | 139 |
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+ 3 |
+ 0.02 |
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+
+
+ | 140 |
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+ 3 |
+ 0.05 |
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+ UTM RW |
+
+
+ | 141 |
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+ 3 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 142 |
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+ 1 |
+ 3 |
+ 0 |
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+ UTM RW |
+
+
+ | 143 |
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+ 3 |
+ 0 |
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+ UTM RW |
+
+
+ | 144 |
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+ 2 |
+ 0.04 |
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+ UTM RW |
+
+
+ | 145 |
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+ 1 |
+ 3 |
+ 0 |
+ 3.159 |
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+ UTM RW |
+
+
+ | 146 |
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+ 4 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 147 |
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+ M |
+ 1 |
+ 3 |
+ 0.04 |
+ 2.622 |
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+ 0.017 |
+ 1.45 |
+ 1.32 |
+ UTM RW |
+
+
+ | 148 |
+ R1942H1 |
+ BXD98 |
+ 62 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.104 |
+ 48.42 |
+ 0.528 |
+ 0.454 |
+ 0.019 |
+ 2.22 |
+ 1.08 |
+ UTM RW |
+
+
+ | 149 |
+ R1943H2 |
+ BXD98 |
+ 62 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.04 |
+ 56.85 |
+ 0.484 |
+ 0.497 |
+ 0.019 |
+ 1.18 |
+ 0.76 |
+ UTM RW |
+
+
+ | 150 |
+ R2197H1 |
+ BXD99 |
+ 70 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.288 |
+ 51.75 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.35 |
+ 0.81 |
+ UTM RW |
+
+
+ | 151 |
+ R2315H1 |
+ BXD99 |
+ 84 |
+ M |
+ 5 |
+ 2 |
+ 0.03 |
+ 6.036 |
+ 43.05 |
+ 0.484 |
+ 0.497 |
+ 0.018 |
+ 1.7 |
+ 0.96 |
+ UTM RW |
+
+
+ | 152 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 153 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 154 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 155 |
+ R2673H1 |
+ C57BL/6ByJ |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.08 |
+ 1.842 |
+ 67.69 |
+ 0.514 |
+ 0.469 |
+ 0.017 |
+ 1.75 |
+ 0.78 |
+ JAX |
+
+
+ | 156 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
+ 3.058 |
+ 51.87 |
+ 0.477 |
+ 0.503 |
+ 0.02 |
+ 1.67 |
+ 0.76 |
+ UTM RW |
+
+
+ | 157 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
+ 3.341 |
+ 49.26 |
+ 0.527 |
+ 0.456 |
+ 0.018 |
+ 1.14 |
+ 1.45 |
+ UTM RW |
+
+
+ | 158 |
+ R1449H2 |
+ C57BL/6J |
+ 71 |
+ M |
+ 5 |
+ 3 |
+ 0.09 |
+ 3.592 |
+ 44.32 |
+ 0.47 |
+ 0.51 |
+ 0.02 |
+ 1.68 |
+ 0.77 |
+ UTM DG |
+
+
+ | 159 |
+ R2619H1 |
+ CAST/Ei |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 160 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 161 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 162 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 163 |
+ R2671H1 |
+ CXB10 |
+ 53 |
+ M |
+ 7 |
+ 3 |
+ 0.09 |
+ 2.348 |
+ 71.45 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 2.2 |
+ 1.14 |
+ JAX |
+
+
+ | 164 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 165 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 166 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 167 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 168 |
+ R2672H1 |
+ CXB13 |
+ 49 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.722 |
+ 79.52 |
+ 0.516 |
+ 0.465 |
+ 0.019 |
+ 1.64 |
+ 0.75 |
+ JAX |
+
+
+ | 169 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+ | 170 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 171 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 172 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 173 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 174 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 175 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 176 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 177 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 178 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 179 |
+ R2676H1 |
+ CXB6 |
+ 47 |
+ F |
+ 7 |
+ 2 |
+ 0.05 |
+ 2.146 |
+ 62.51 |
+ 0.507 |
+ 0.475 |
+ 0.018 |
+ 1.52 |
+ 0.78 |
+ JAX |
+
+
+ | 180 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 181 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 182 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 183 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 184 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 185 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 186 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 187 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 188 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 2.579 |
+ 58.49 |
+ 0.506 |
+ 0.475 |
+ 0.019 |
+ 2.49 |
+ 1.21 |
+ UTM RW |
+
+
+ | 189 |
+ R1551H1 |
+ D2B6F1 |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.62 |
+ 53.76 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 1.37 |
+ 0.76 |
+ UTM RW |
+
+
+ | 190 |
+ R1290H2 |
+ DBA/2J |
+ 63 |
+ F |
+ 7 |
+ 2 |
+ 0.04 |
+ 2.576 |
+ 59.6 |
+ 0.513 |
+ 0.468 |
+ 0.018 |
+ 1.3 |
+ 0.78 |
+ JAX |
+
+
+ | 191 |
+ R1468H1 |
+ DBA/2J |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.03 |
+ 2.929 |
+ 53.8 |
+ 0.515 |
+ 0.465 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 192 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 193 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 194 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 195 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 196 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 197 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 198 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 199 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 200 |
+ R2677H1 |
+ PWD/PhJ |
+ 65 |
+ F |
+ 7 |
+ 2 |
+ 0.12 |
+ 2.764 |
+ 65.49 |
+ 0.462 |
+ 0.52 |
+ 0.018 |
+ 1.89 |
+ 1.16 |
+ UTM RW |
+
+
+ | 201 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 202 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 203 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 204 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 205 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+
+ |
+
+
+
+
+
+Downloading all data:
+
+
+All data links (right-most column above) will be made active as sooon as the global analysis of these data by the Consoritum has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of the PDNN probe set data. Contact RW Williams regarding data access probelms.
+
diff --git a/general/datasets/Hc_m2_1206_r/contributors.rtf b/general/datasets/Hc_m2_1206_r/contributors.rtf
new file mode 100644
index 0000000..ff0385a
--- /dev/null
+++ b/general/datasets/Hc_m2_1206_r/contributors.rtf
@@ -0,0 +1,3 @@
+
+All data links (right-most column above) will be made active as sooon as the global analysis of these data by the Consoritum has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of the PDNN probe set data. Contact RW Williams regarding data access problems.
+
diff --git a/general/datasets/Hc_m2_1206_r/experiment-design.rtf b/general/datasets/Hc_m2_1206_r/experiment-design.rtf
new file mode 100644
index 0000000..23a857d
--- /dev/null
+++ b/general/datasets/Hc_m2_1206_r/experiment-design.rtf
@@ -0,0 +1,9 @@
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80 deg. C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each isogenic group. While all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. Seventy-seven of 97 strains are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquots R1291H3 and R1291H4).
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays. Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4 deg C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
diff --git a/general/datasets/Hc_m2_1206_r/notes.rtf b/general/datasets/Hc_m2_1206_r/notes.rtf
new file mode 100644
index 0000000..f5f115c
--- /dev/null
+++ b/general/datasets/Hc_m2_1206_r/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW and Rupert Overall on January 30, 2007.
diff --git a/general/datasets/Hc_m2_1206_r/platform.rtf b/general/datasets/Hc_m2_1206_r/platform.rtf
new file mode 100644
index 0000000..4b34d93
--- /dev/null
+++ b/general/datasets/Hc_m2_1206_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 16,578 NCBI Reference Sequences. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The annotation used in this data set assigns probes to probe sets based on their alignment to Entrez GeneID sequences using the latest Mouse Genome assembly (Build 36, mm8).
+
diff --git a/general/datasets/Hc_m2_1206_r/processing.rtf b/general/datasets/Hc_m2_1206_r/processing.rtf
new file mode 100644
index 0000000..bfc45d4
--- /dev/null
+++ b/general/datasets/Hc_m2_1206_r/processing.rtf
@@ -0,0 +1,41 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very senstive to the transformation method that is used. Using the PDNN transform the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For examploe, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one whould include the ssample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the of the probe level (CEL) data after step 5 below. DataDesk allows a rapid detection of subsets of probes that are particular sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe set data with custom CDF mapping: The original Affymetrix annotation often has multiple probe sets mapping to a single gene. Some of these redundancies represent alternative splicing products, while some reflect our changing knowledge of the mouse genome. This transformation uses an annotation generated by the Microarray Group at the University of Michigan where each probe has been checked against the latest mouse genome build (Build 36, mm8) and then collated into a new probe set based on its placement within a gene sequence in the Entrez Gene database. The following quote from their Brainarray website explains in more detail:
+
+Affymetrix GeneChips were based on the best UniGene clustering and genomic sequence information available at the time of chip design. Due to the significant increase in EST/cDNA/Genomic sequence information in the last couple of years, some oligonucleotide probes in these old designs can now be assigned to different genes/transcripts based on the current UniGene clustering and genome annotation. While Affymetrix's current annotation system maps each probe set to the latest UniGene build every couple of months, it does not deal with situations where a subset of oligonucleotide probes in a probe set may be assigned to another gene or more than one gene based on the current UniGene clustering and genome annotation. In addition, a significant portion of UniGene clusters can be represented by more than one oligonucleotide probe set on GeneChips but there is no standard approach to deal with signals from different probe sets representing the same gene. It will be highly desirable to have one probe set-one target relationship for the interpretation of the data.
+
+
+ - CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+ - Probe level data from the CEL files were transformed with the RMA transform using the Mm74Bv2_Mm_ENTREZG_8 (Version 8) CDF mapping. Data transformation was done in Bioconductor using the
affy.justRMA() package and the Mm430_Mm_ENTREZG file as contained in the Bioconductor repository. This yields only one unique probeset for each Entrez GeneID.
+ - We computed the Z scores for each array.
+ - The arithmetic mean of the values for the set of microarrays for each strain was computed.
+
+ - The Z scores were recomputed for each strain.
+ - We multiplied all Z scores by 2.
+ - We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level (probe brightness level) corresponds approximately to a 1 unit difference.
+
+
+
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
+
diff --git a/general/datasets/Hc_m2_1206_r/summary.rtf b/general/datasets/Hc_m2_1206_r/summary.rtf
new file mode 100644
index 0000000..60da981
--- /dev/null
+++ b/general/datasets/Hc_m2_1206_r/summary.rtf
@@ -0,0 +1,5 @@
+PRELIMINARY: The June 2006 Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of 99 genetically diverse strains of mice including 67 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a set of diverse inbred strains, and two reciprocal F1 hybrids.
+
+The hippocampus is an important and intriguing part of the forebrain that is crucial in memory formation and retrieval, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section.
+
+Samples were processed using a total of 205 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 179 passed stringent quality control and error checking . This particular data set was processed using the RMA protocol using a custom CDF. To simplify comparisons among transforms, RMA values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2_1206_r/tissue.rtf b/general/datasets/Hc_m2_1206_r/tissue.rtf
new file mode 100644
index 0000000..2bb700d
--- /dev/null
+++ b/general/datasets/Hc_m2_1206_r/tissue.rtf
@@ -0,0 +1,7 @@
+
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thanks Muriel Davission for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below).
+
diff --git a/general/datasets/Hc_m2cb_1005_m/acknowledgment.rtf b/general/datasets/Hc_m2cb_1005_m/acknowledgment.rtf
new file mode 100644
index 0000000..1481cd1
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_m/acknowledgment.rtf
@@ -0,0 +1,50 @@
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
diff --git a/general/datasets/Hc_m2cb_1005_m/cases.rtf b/general/datasets/Hc_m2cb_1005_m/cases.rtf
new file mode 100644
index 0000000..15e6cda
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_m/cases.rtf
@@ -0,0 +1,56 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 27 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondrial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 strains are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2cb_1005_m/citation.rtf b/general/datasets/Hc_m2cb_1005_m/citation.rtf
new file mode 100644
index 0000000..61a0788
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_m/citation.rtf
@@ -0,0 +1 @@
+Please cite: Overall RW, Kempermann G, Peirce J, Lu L, Goldowitz D, Gage FH, Goodwin S, Smit AB, Airey DC, Rosen GD, Schalkwyk LC, Sutter TR, Nowakowski RS, Whatley S, Williams RW (2009) Genetics of the hippocampal transcriptome in mice: a systematic survey and online neurogenomic resource. Front. Neurogen. 1:3 Full Text HTML doi:10.3389/neuro.15.003.2009
diff --git a/general/datasets/Hc_m2cb_1005_m/contributors.rtf b/general/datasets/Hc_m2cb_1005_m/contributors.rtf
new file mode 100644
index 0000000..4108279
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_m/contributors.rtf
@@ -0,0 +1,46 @@
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
diff --git a/general/datasets/Hc_m2cb_1005_m/experiment-design.rtf b/general/datasets/Hc_m2cb_1005_m/experiment-design.rtf
new file mode 100644
index 0000000..356f1d2
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_m/experiment-design.rtf
@@ -0,0 +1 @@
+Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2cb_1005_m/notes.rtf b/general/datasets/Hc_m2cb_1005_m/notes.rtf
new file mode 100644
index 0000000..9c11719
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_m/notes.rtf
@@ -0,0 +1,12 @@
+This study includes the following datasets:
+
+
+ - Hippocampus Consortium M430v2 CXB (Oct05) MAS5
+ - Hippocampus Consortium M430v2 CXB (Oct05) RMA
+ - Hippocampus Consortium M430v2 CXB (Oct05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) RMA
+ - Hippocampus Consortium M430v2 (Jun06) RMA
+ - Hippocampus Consortium M430v2 (Jun06) MAS5
+ - Hippocampus Consortium M430v2 (Jun06) PDNN
+
diff --git a/general/datasets/Hc_m2cb_1005_m/platform.rtf b/general/datasets/Hc_m2cb_1005_m/platform.rtf
new file mode 100644
index 0000000..6c99bee
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_m/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2cb_1005_m/processing.rtf b/general/datasets/Hc_m2cb_1005_m/processing.rtf
new file mode 100644
index 0000000..3698a7b
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_m/processing.rtf
@@ -0,0 +1,37 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very sensitive to the transformation method that is used. Using the PDNN transform, the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For example, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one would include the sample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the probe level (CEL) data after step 5 below. DataDesk allows the rapid detection of subsets of probes that are particularly sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - We performed a quantile normalization of the log base 2 values for all arrays using the same initial steps used by the RMA transform.
+ - We computed the Z scores for each cell value.
+ - We multiplied all Z scores by 2.
+ - We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level (probe brightness level) corresponds approximately to a 1 unit difference.
+ - Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data from the CHP file: The expression values were generated using PDNN. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1 unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2cb_1005_m/summary.rtf b/general/datasets/Hc_m2cb_1005_m/summary.rtf
new file mode 100644
index 0000000..1e86e54
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_m/summary.rtf
@@ -0,0 +1,3 @@
+MOST HIGHLY RECOMMENDED DATA SET (Overall et al., 2009): The Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of 99 genetically diverse strains of mice including 67 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a diverse set of common inbred strains, and two reciprocal F1 hybrids.
+
+The hippocampus is an important and intriguing part of the forebrain that is crucial in memory formation and retrieval, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section.
diff --git a/general/datasets/Hc_m2cb_1005_m/tissue.rtf b/general/datasets/Hc_m2cb_1005_m/tissue.rtf
new file mode 100644
index 0000000..bcea7b0
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_m/tissue.rtf
@@ -0,0 +1,3721 @@
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thank Muriel Davisson for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below). All animals were sacrifice between 9 AM and 5 PM during the light phase.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+RNA Extraction: In brief, we used the RNA STAT-60 protocol (TEL-TEST "B" Bulletin No. 1), steps 5.1A (homogenization of tissue), 5.2 (RNA extraction), 5.3 (RNA precipitation), and 5.4 (RNA wash). In Step 5.4 we stopped after adding 75% ethanol (1 ml per 1 ml RNA STAT-60) and stored the mix at -80°C until further use. Before RNA labeling we thawed samples and proceeded with the remainder of Step 5.4; pelleting, drying, and redissolving the pellet in RNase-free water.
+
+We finally purify RNA by using Na4OAc before running arrays. Here is the detailed method:
+
+Final RNA purification protocol
+
+
+ - Add 1/10th volume of 3M Na4OAc , pH 5.2. If the sample was eluted with 100 µl nuclease-free water as suggested, this will be 10 µl of 3M Na4OAc.
+ - Add 2.5 volumes of 100% ethanol (250 µl if the RNA was eluted in100 µl). Mix well and incubate at –20°C for 2 hrs.
+ - Centrifuge at speed of 13,000 rpm for 20 min at 4°C. Carefully remove and discard the supernatant.
+ - Wash the pellet with 800 µl 75% cold ethanol, centrifuge at speed of 8,600 rpm for 5 min, and remove the 75% ethanol. Wash again.
+ - To remove the last traces of ethanol, quickly respin the tube, and aspirate any residual fluid.
+ - Air dry the pellet.
+ - Resuspend pellet in nuclease-free water.
+
+
+
+
+5. PROTOCOL: RNA/mRNA isolation by the RNA STAT-60 method includes the following steps:
+1. Homogenization RNA STAT-60TM (1 ml per 50-100 mg tissue, or 5-10 x 10-6 cells)
+2. RNA Extraction 1 vol. of homogenate +0.2 vol. of chloroform
+3. RNA Precipitation 0.5 vol. of isopropanol
+4. RNA Wash 75% ethanol
+
+Unless stated otherwise the procedure is carried out at room temperature.
+
+5.1 HOMOGENIZATION
+
+A. TISSUES: Homogenize tissues samples in the RNA STAT-60(1 ml/50-100mg tissue) in a glass-Teflon or Polytron homogenizer. Sample volume should not exceed 10% of the volume of the RNA STAT-60 used for homogenization.
+
+B. CELLS: Cells grown in mono layer are lysed directly in a culture dish by adding the RNA STAT-60TM (1 ml/3.5 cm petri dish) and passing the cell lysate several times through a pipette. Cells grown in suspension are sediment then lysed in the RNA STAT-60TM (1 ml per 5-10 x 106 cells) by repetitive pipetting. Washing calls before addition of the RNA STAT-60TM should be avoided as this increases the possibility of mRNA degradation.
+
+5.2 RNA EXTRACTION: Following homogenization, store the homogenate for 5 min at room temp to permit the complete dissociation of nucleoprotein complexes. Next, add 0.2 ml of chloroform per 1 ml of the RNA STAT-60, cover the sample tightly, shake vigorously for 15 seconds and let it stay at room temperature for 2-3minutes. Centrifuge the homogenate at 12,000g (max) for 15 minutes at 4°C. Following centrifugation, the homogenate separates into two phases: a lower red phenol chloroform phase and the colorless upper aqueous phase. RNA remains exclusively in the aqueous phase whereas DNA and proteins are in the interferes and organic phase. The volume of the aqueous phase is about 60% of the volume of RNA STAT-60 used for homogenization.
+
+5.3 RNA PRECIPITATION: Transfer the aqueous phase to a fresh tube and mix with isopropanol. Add 0.5 ml of isopropanol per 1 ml of the RNA STAT-60 used for homogenization. Store samples at room temp for 5-10 minutes and centrifuge at 12,000g (max.) for 10 min at 4°C. RNA precipitate (often visible before centrifugation) forms a white pellet at the bottom of the tube.
+
+5.4 RNA WASH: Remove supernatant and wash the RNA pellet once with 75% ethanol by vortexing and subsequent centrifugation at 7,500g (max.) for 5 min at 4°C. Add at least 1 ml of 75% ethanol per 1 ml of the RNA STAT-60 used for the initial homogenization.
+
+At the end of the procedure, dry the RNA pellet briefly by air-drying or in a vacuum (5-10 min.). It is important not to let the RNA pellet dry completely as it will greatly decrease its solubility. Do not use the Speed-Vac for drying. Dissolve the RNA pellet in water or in 1 mm EDTA, pH 7, or 0.5% SDS solution. Vortex or pass the pellet a few times through a pipette tip. An incubation for 10-15 minutes at 55-60oC may be required to dissolve RNA samples. Diethylpyrocarbonate (DEPC) treated RNase-free solutions1 should be used for solubilization of RNA.
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80°C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: Our goal was to obtain a male sample pool and female sample pool from each isogenic group. While almost all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. All but 5 of 99 strains (BXD55, BXD86, BXD94, BALB/cByJ, and CAST/EiJ) are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquots R1291H3 and R1291H4).
+
+
+
+Sex Balance: Based on the expression of Xist, probe set 1427262_at, DBA/2J and KK/HlJ are represented only by female samples, BXD55, and BALB/cByJ are only represented by a single male sample, BXD74 is represented by two male samples, and BXD86, BXD94, and CAST/EiJ are possibly mixed sex samples. One of the BXD9 samples, array R1523, may be a mixed sex sample pool because the expression of Xist is intermediate.
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays. Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4°C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+COMPARISON with December 2005 Data Set: Both BXD14 arrays in the Dec05 data set were found to actually be from BXD23 cases. This error of strain identification has been corrected in the present data set. Four arrays in the Dec05 data set have been deleted because we judged them to be of poor quality (strain_sex_sample_firstreaction_group):
+
+
+ - BXD21_F_1_1_G1
+ - BXD23_M_1_1_G7
+ - BXD36_M_1_1_G2
+ - BXD36_F_1_1_G3
+
+
+In the Dec05 data set there are a total of 1986 transcripts with QTLs that have LRS scores above 50, whereas in the corrected June06 data sets there are a total of 2074 transcripts with QTLs above 50.
+
+Data Table 1:
+
+This table lists all arrays by file order (Index), tube/sample ID, age, sex, batch, and numbers of animals in each sample pool (pool size). The next columns (RMA outlier, scale factor, background average, present, absent, marginal, AFFY-b-ActinMur(3'/5'), AFFY-GapdhMur(3'/5')) are all Affymetrix QC data. Finally, source lists the source colony of the animals. (Final version, fully corrected, by Arthur Centeno, October 2008)
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool size |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 2 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 3 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M technical duplicate of above |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 4 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 5 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 2.579 |
+ 58.49 |
+ 0.506 |
+ 0.475 |
+ 0.019 |
+ 2.49 |
+ 1.21 |
+ UTM RW |
+
+
+ | 6 |
+ R1551H1 |
+ D2B6F1 |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.62 |
+ 53.76 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 1.37 |
+ 0.76 |
+ UTM RW |
+
+
+ | 7 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
+ 3.058 |
+ 51.87 |
+ 0.477 |
+ 0.503 |
+ 0.02 |
+ 1.67 |
+ 0.76 |
+ UTM RW |
+
+
+ | 8 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
+ 3.341 |
+ 49.26 |
+ 0.527 |
+ 0.456 |
+ 0.018 |
+ 1.14 |
+ 1.45 |
+ UTM RW |
+
+
+ | 9 |
+ R1449H2 |
+ C57BL/6J |
+ 71 |
+ M |
+ 5 |
+ 3 |
+ 0.09 |
+ 3.592 |
+ 44.32 |
+ 0.47 |
+ 0.51 |
+ 0.02 |
+ 1.68 |
+ 0.77 |
+ UTM DG |
+
+
+ | 10 |
+ R1290H2 |
+ DBA/2J |
+ 63 |
+ F |
+ 7 |
+ 2 |
+ 0.04 |
+ 2.576 |
+ 59.6 |
+ 0.513 |
+ 0.468 |
+ 0.018 |
+ 1.3 |
+ 0.78 |
+ JAX |
+
+
+ | 11 |
+ R1468H1 |
+ DBA/2J |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.03 |
+ 2.929 |
+ 53.8 |
+ 0.515 |
+ 0.465 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 12 |
+ R1507H1 |
+ BXD1 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.056 |
+ 60.17 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.15 |
+ 0.76 |
+ Glenn |
+
+
+ | 13 |
+ R1542H1 |
+ BXD1 |
+ 59 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.792 |
+ 80.56 |
+ 0.492 |
+ 0.489 |
+ 0.018 |
+ 1.57 |
+ 0.79 |
+ Glenn |
+
+
+ | 14 |
+ R1520H1 |
+ BXD2 |
+ 56 |
+ F |
+ 4 |
+ 4 |
+ 0.09 |
+ 1.715 |
+ 71.62 |
+ 0.515 |
+ 0.467 |
+ 0.018 |
+ 2.36 |
+ 1.6 |
+ Glenn |
+
+
+ | 15 |
+ R1516H1 |
+ BXD2 |
+ 61 |
+ M |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.231 |
+ 64.86 |
+ 0.508 |
+ 0.474 |
+ 0.019 |
+ 1.3 |
+ 1.53 |
+ Glenn |
+
+
+ | 16 |
+ R1593H2 |
+ BXD5 |
+ 60 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 1.913 |
+ 59.96 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.98 |
+ 1.44 |
+ Glenn |
+
+
+ | 17 |
+ R1692H1 |
+ BXD5 |
+ 60 |
+ M |
+ 3 |
+ 2 |
+ 0.07 |
+ 3.764 |
+ 72.74 |
+ 0.465 |
+ 0.516 |
+ 0.02 |
+ 1.15 |
+ 0.74 |
+ Glenn |
+
+
+ | 18 |
+ R1539H2 |
+ BXD6 |
+ 59 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 2.488 |
+ 54.97 |
+ 0.518 |
+ 0.463 |
+ 0.018 |
+ 1.08 |
+ 1.33 |
+ Glenn |
+
+
+ | 19 |
+ R1538H1 |
+ BXD6 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.01 |
+ 2.585 |
+ 50.27 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 1.46 |
+ 0.79 |
+ Glenn |
+
+
+ | 20 |
+ R1518H1 |
+ BXD8 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 2.92 |
+ 54.84 |
+ 0.515 |
+ 0.465 |
+ 0.02 |
+ 1.32 |
+ 1.24 |
+ Glenn |
+
+
+ | 21 |
+ R1548H1 |
+ BXD8 |
+ 59 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.132 |
+ 59.37 |
+ 0.504 |
+ 0.477 |
+ 0.019 |
+ 2.16 |
+ 1.54 |
+ Glenn |
+
+
+ | 22 |
+ R1350H2 |
+ BXD9 |
+ 86 |
+ F |
+ 1 |
+ 3 |
+ 0.05 |
+ 2.771 |
+ 60.62 |
+ 0.5 |
+ 0.482 |
+ 0.018 |
+ 1.01 |
+ 1.28 |
+ UMemphis |
+
+
+ | 23 |
+ R1523H3 |
+ BXD9 |
+ 57 |
+ MF (mixed) |
+ 7 |
+ 3 |
+ 0.14 |
+ 3.9 |
+ 78.36 |
+ 0.435 |
+ 0.547 |
+ 0.018 |
+ 1.36 |
+ 0.77 |
+ UTM RW |
+
+
+ | 24 |
+ R1531H1 |
+ BXD11 |
+ 56 |
+ F |
+ 6 |
+ 3 |
+ 0.06 |
+ 2.229 |
+ 56.36 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 2.23 |
+ 1.02 |
+ Glenn |
+
+
+ | 25 |
+ R1367H1 |
+ BXD11 |
+ 56 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.11 |
+ 78.78 |
+ 0.503 |
+ 0.477 |
+ 0.02 |
+ 1.07 |
+ 1.27 |
+ Glenn |
+
+
+ | 26 |
+ R1530H1 |
+ BXD12 |
+ 58 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 3.227 |
+ 53.77 |
+ 0.505 |
+ 0.477 |
+ 0.018 |
+ 0.95 |
+ 1.4 |
+ Glenn |
+
+
+ | 27 |
+ R2674H1 |
+ BXD12 |
+ 59 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.924 |
+ 83.44 |
+ 0.519 |
+ 0.464 |
+ 0.018 |
+ 1.21 |
+ 0.78 |
+ Glenn |
+
+
+ | 28 |
+ R1529H1 |
+ BXD13 |
+ 58 |
+ F |
+ 6 |
+ 3 |
+ 0.05 |
+ 2.55 |
+ 59.05 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 2 |
+ 1.54 |
+ Glenn |
+
+
+ | 29 |
+ R1662H2 |
+ BXD13 |
+ 60 |
+ M |
+ 1 |
+ 3 |
+ 0.03 |
+ 4.603 |
+ 45.81 |
+ 0.509 |
+ 0.472 |
+ 0.019 |
+ 1.3 |
+ 0.82 |
+ Glenn |
+
+
+ | 30 |
+ R1304H2 |
+ BXD14 |
+ 72 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.946 |
+ 61.87 |
+ 0.484 |
+ 0.498 |
+ 0.018 |
+ 1.22 |
+ 0.77 |
+ UTM RW |
+
+
+ | 31 |
+ R1278H2 |
+ BXD14 |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.06 |
+ 4.75 |
+ 67.52 |
+ 0.449 |
+ 0.532 |
+ 0.019 |
+ 1.1 |
+ 0.73 |
+ UTM RW |
+
+
+ | 32 |
+ R1524H1 |
+ BXD15 |
+ 60 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.961 |
+ 50.93 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 1.74 |
+ 0.91 |
+ Glenn |
+
+
+ | 33 |
+ R1515H1 |
+ BXD15 |
+ 61 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.316 |
+ 57.05 |
+ 0.503 |
+ 0.478 |
+ 0.019 |
+ 1.32 |
+ 1.21 |
+ Glenn |
+
+
+ | 34 |
+ R1661H1 |
+ BXD16 |
+ 61 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.778 |
+ 59.81 |
+ 0.516 |
+ 0.466 |
+ 0.019 |
+ 1.39 |
+ 1.2 |
+ Glenn |
+
+
+ | 35 |
+ R1594H1 |
+ BXD16 |
+ 61 |
+ M |
+ 4 |
+ 3 |
+ 0.03 |
+ 2.634 |
+ 53.66 |
+ 0.504 |
+ 0.478 |
+ 0.018 |
+ 1.96 |
+ 1.51 |
+ Glenn |
+
+
+ | 36 |
+ R2666H1 |
+ BXD19 |
+ 60 |
+ F |
+ 7 |
+ 3 |
+ 0.02 |
+ 2.498 |
+ 76.2 |
+ 0.495 |
+ 0.486 |
+ 0.019 |
+ 1.41 |
+ 0.77 |
+ Glenn |
+
+
+ | 37 |
+ R1471H1 |
+ BXD19 |
+ 157 |
+ M |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.165 |
+ 43.34 |
+ 0.519 |
+ 0.462 |
+ 0.018 |
+ 1.01 |
+ 1.29 |
+ UTM JB |
+
+
+ | 38 |
+ R1573H1 |
+ BXD20 |
+ 59 |
+ F |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.749 |
+ 52.7 |
+ 0.513 |
+ 0.469 |
+ 0.018 |
+ 1.01 |
+ 1.27 |
+ Glenn |
+
+
+ | 39 |
+ R2507H1 |
+ BXD20 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.06 |
+ 3.568 |
+ 57 |
+ 0.472 |
+ 0.508 |
+ 0.02 |
+ 1.29 |
+ 0.76 |
+ Glenn |
+
+
+ | 40 |
+ R2668H1 |
+ BXD21 |
+ 60 |
+ M |
+ 7 |
+ 4 |
+ 0.07 |
+ 2.605 |
+ 44.9 |
+ 0.535 |
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+
+
+ | 41 |
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+ 2 |
+ 4 |
+ 0 |
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+
+
+ | 42 |
+ R1848H3 |
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+ 6 |
+ 4 |
+ 0.02 |
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+
+
+ | 43 |
+ R1525H1 |
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+ 2 |
+ 3 |
+ 0.02 |
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+
+
+ | 44 |
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+ 1 |
+ 3 |
+ 0.01 |
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+ 1.2 |
+ UTM RW |
+
+
+ | 45 |
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+ BXD23 |
+ 58 |
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+ 5 |
+ 3 |
+ 0.1 |
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+
+
+ | 46 |
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+ 2 |
+ 3 |
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+
+
+ | 47 |
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+ 3 |
+ 3 |
+ 0.01 |
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+
+
+ | 48 |
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+ 2 |
+ 4 |
+ 0 |
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+
+
+ | 49 |
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+ 5 |
+ 3 |
+ 0.06 |
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+
+
+ | 50 |
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+ 3 |
+ 4 |
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+
+
+ | 51 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 52 |
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+ 57 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 53 |
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+ 5 |
+ 3 |
+ 0.01 |
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+
+
+ | 54 |
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+ 2 |
+ 3 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 55 |
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+ 57 |
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+ 7 |
+ 4 |
+ 0.1 |
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+ UTM RW |
+
+
+ | 56 |
+ R2675H1 |
+ BXD32 |
+ 57 |
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+ 7 |
+ 3 |
+ 0.03 |
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+
+
+ | 57 |
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+ 2 |
+ 4 |
+ 0.01 |
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+
+
+ | 58 |
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+ 2 |
+ 2 |
+ 0.01 |
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+
+ | 59 |
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+ 3 |
+ 3 |
+ 0.01 |
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+
+ | 60 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 61 |
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+ 5 |
+ 3 |
+ 0.12 |
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+
+ | 62 |
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+ 3 |
+ 4 |
+ 0.01 |
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+
+
+ | 63 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 64 |
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+ 2 |
+ 3 |
+ 0.03 |
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+
+ | 65 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+ | 66 |
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+ 4 |
+ 0 |
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+
+ | 67 |
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+ 2 |
+ 3 |
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+
+ | 68 |
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+ 3 |
+ 0.07 |
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+
+ | 69 |
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+ 7 |
+ 4 |
+ 0.03 |
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+
+ | 70 |
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+ 3 |
+ 0 |
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+
+
+ | 71 |
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+ 0.02 |
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+
+
+ | 72 |
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+ 0 |
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+
+
+ | 73 |
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+ 1 |
+ 3 |
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+
+
+ | 74 |
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+
+ | 75 |
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+
+
+ | 76 |
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+ 0 |
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+
+
+ | 77 |
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+
+
+ | 78 |
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+
+ | 79 |
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+
+
+ | 80 |
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+
+
+ | 81 |
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+
+
+ | 82 |
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+
+
+ | 83 |
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+
+
+ | 84 |
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+ 0 |
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+
+ | 85 |
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+
+
+ | 86 |
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+
+ | 87 |
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+
+ | 88 |
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+
+ | 89 |
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+
+
+ | 90 |
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+
+
+ | 91 |
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+
+
+ | 92 |
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+
+
+ | 93 |
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+
+
+ | 94 |
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+ 0 |
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+
+
+ | 95 |
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+ 4 |
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+
+
+ | 96 |
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+
+
+ | 97 |
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+
+
+ | 98 |
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+
+
+ | 99 |
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+
+
+ | 100 |
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+
+
+ | 101 |
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+
+
+ | 102 |
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+
+
+ | 103 |
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+
+
+ | 104 |
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+
+
+ | 105 |
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+
+
+ | 106 |
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+ 3 |
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+
+
+ | 107 |
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+ 0.01 |
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+
+
+ | 108 |
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+ 2 |
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+
+
+ | 109 |
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+ 3 |
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+
+
+ | 110 |
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+ 4 |
+ 0.01 |
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+
+
+ | 111 |
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+ 3 |
+ 0.01 |
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+
+
+ | 112 |
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+ 4 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 113 |
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+ 4 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 114 |
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+ BXD77 |
+ 62 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.071 |
+ 54.15 |
+ 0.51 |
+ 0.471 |
+ 0.019 |
+ 1.26 |
+ 0.74 |
+ UTM RW |
+
+
+ | 115 |
+ R1947H1 |
+ BXD79 |
+ 108 |
+ F |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.599 |
+ 51.52 |
+ 0.524 |
+ 0.457 |
+ 0.019 |
+ 1.35 |
+ 0.74 |
+ UTM RW |
+
+
+ | 116 |
+ R2092H1 |
+ BXD79 |
+ 86 |
+ M |
+ 5 |
+ 4 |
+ 0.06 |
+ 3.735 |
+ 42.25 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 2.94 |
+ 1.06 |
+ UTM RW |
+
+
+ | 117 |
+ R1880H1 |
+ BXD80 |
+ 68 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 4.855 |
+ 42.22 |
+ 0.501 |
+ 0.481 |
+ 0.018 |
+ 2.17 |
+ 1.36 |
+ UTM RW |
+
+
+ | 118 |
+ R1881H2 |
+ BXD80 |
+ 68 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.073 |
+ 48.93 |
+ 0.524 |
+ 0.458 |
+ 0.019 |
+ 1.34 |
+ 0.83 |
+ UTM RW |
+
+
+ | 119 |
+ R2075H1 |
+ BXD83 |
+ 60 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.454 |
+ 55.1 |
+ 0.502 |
+ 0.48 |
+ 0.018 |
+ 1.27 |
+ 0.77 |
+ UTM RW |
+
+
+ | 120 |
+ R2076H2 |
+ BXD83 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.03 |
+ 2.624 |
+ 55.65 |
+ 0.495 |
+ 0.488 |
+ 0.018 |
+ 2.21 |
+ 0.94 |
+ UTM RW |
+
+
+ | 121 |
+ R2077H2 |
+ BXD84 |
+ 62 |
+ F |
+ 6 |
+ 2 |
+ 0 |
+ 2.1 |
+ 71.87 |
+ 0.522 |
+ 0.459 |
+ 0.018 |
+ 1.68 |
+ 0.81 |
+ UTM RW |
+
+
+ | 122 |
+ R2135H3 |
+ BXD84 |
+ 75 |
+ M |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.467 |
+ 64.46 |
+ 0.505 |
+ 0.476 |
+ 0.019 |
+ 1.2 |
+ 0.74 |
+ UTM RW |
+
+
+ | 123 |
+ R1473H1 |
+ BXD85 |
+ 79 |
+ F |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.384 |
+ 55.34 |
+ 0.478 |
+ 0.502 |
+ 0.02 |
+ 1.24 |
+ 0.77 |
+ UTM RW |
+
+
+ | 124 |
+ R1474H1 |
+ BXD85 |
+ 57 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.831 |
+ 55.24 |
+ 0.522 |
+ 0.461 |
+ 0.018 |
+ 1.04 |
+ 1.29 |
+ UTM RW |
+
+
+ | 125 |
+ R1597H1 |
+ BXD85 |
+ 86 |
+ M |
+ 4 |
+ 4 |
+ 0.09 |
+ 2.028 |
+ 53.95 |
+ 0.487 |
+ 0.492 |
+ 0.021 |
+ 1.28 |
+ 0.83 |
+ UTM RW |
+
+
+ | 126 |
+ R1415H1 |
+ BXD86 |
+ 77 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 2.525 |
+ 53.16 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.66 |
+ 0.91 |
+ UTM RW |
+
+
+ | 127 |
+ R2669H2 |
+ BXD87 |
+ 63 |
+ F |
+ 7 |
+ 3 |
+ 0.07 |
+ 2.61 |
+ 57.59 |
+ 0.513 |
+ 0.47 |
+ 0.018 |
+ 1.6 |
+ 0.91 |
+ UTM RW |
+
+
+ | 128 |
+ R1710H1 |
+ BXD87 |
+ 84 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 2.697 |
+ 56.4 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 129 |
+ R1872H2 |
+ BXD89 |
+ 90 |
+ F |
+ 2 |
+ 2 |
+ 0.02 |
+ 3.013 |
+ 63.53 |
+ 0.492 |
+ 0.488 |
+ 0.021 |
+ 1.22 |
+ 0.72 |
+ UTM RW |
+
+
+ | 130 |
+ R1850H3 |
+ BXD89 |
+ 82 |
+ M |
+ 4 |
+ 4 |
+ 0.03 |
+ 2.736 |
+ 44.89 |
+ 0.498 |
+ 0.483 |
+ 0.019 |
+ 1.5 |
+ 0.83 |
+ UTM RW |
+
+
+ | 131 |
+ R2058H1 |
+ BXD90 |
+ 61 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 3.389 |
+ 48.05 |
+ 0.502 |
+ 0.478 |
+ 0.02 |
+ 1.53 |
+ 0.76 |
+ UTM RW |
+
+
+ | 132 |
+ R1600H2 |
+ BXD90 |
+ 74 |
+ M |
+ 7 |
+ 4 |
+ 0.03 |
+ 3.261 |
+ 51.31 |
+ 0.517 |
+ 0.465 |
+ 0.018 |
+ 1.16 |
+ 0.75 |
+ Glenn |
+
+
+ | 133 |
+ R1301H2 |
+ BXD92 |
+ 58 |
+ F |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.543 |
+ 41.97 |
+ 0.522 |
+ 0.46 |
+ 0.018 |
+ 1.5 |
+ 0.79 |
+ UTM RW |
+
+
+ | 134 |
+ R1309H1 |
+ BXD92 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.05 |
+ 1.655 |
+ 66.34 |
+ 0.498 |
+ 0.481 |
+ 0.021 |
+ 1.52 |
+ 0.82 |
+ UTM RW |
+
+
+ | 135 |
+ R2057H1 |
+ BXD93 |
+ 92 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.033 |
+ 44.41 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 1.22 |
+ 0.78 |
+ UTM RW |
+
+
+ | 136 |
+ R2059H1 |
+ BXD93 |
+ 58 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.058 |
+ 60.29 |
+ 0.493 |
+ 0.488 |
+ 0.019 |
+ 1.18 |
+ 1.37 |
+ UTM RW |
+
+
+ | 137 |
+ R2313H1 |
+ BXD94 |
+ 59 |
+ F |
+ 3 |
+ 3 |
+ 0 |
+ 3.091 |
+ 59.45 |
+ 0.487 |
+ 0.495 |
+ 0.018 |
+ 1.34 |
+ 0.73 |
+ UTM RW |
+
+
+ | 138 |
+ R1915H1 |
+ BXD96 |
+ 65 |
+ F |
+ 5 |
+ 2 |
+ 0.04 |
+ 5.145 |
+ 46.19 |
+ 0.502 |
+ 0.481 |
+ 0.017 |
+ 1.37 |
+ 0.74 |
+ UTM RW |
+
+
+ | 139 |
+ R1846H2 |
+ BXD96 |
+ 63 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.159 |
+ 55.85 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.92 |
+ 1.26 |
+ UTM RW |
+
+
+ | 140 |
+ R2648H1 |
+ BXD97 |
+ 74 |
+ F |
+ 7 |
+ 4 |
+ 0.02 |
+ 1.664 |
+ 82.08 |
+ 0.518 |
+ 0.464 |
+ 0.019 |
+ 1.4 |
+ 0.78 |
+ UTM RW |
+
+
+ | 141 |
+ R1927H2 |
+ BXD97 |
+ 67 |
+ M |
+ 1 |
+ 3 |
+ 0.04 |
+ 2.622 |
+ 57.81 |
+ 0.539 |
+ 0.444 |
+ 0.017 |
+ 1.45 |
+ 1.32 |
+ UTM RW |
+
+
+ | 142 |
+ R1942H1 |
+ BXD98 |
+ 62 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.104 |
+ 48.42 |
+ 0.528 |
+ 0.454 |
+ 0.019 |
+ 2.22 |
+ 1.08 |
+ UTM RW |
+
+
+ | 143 |
+ R1943H2 |
+ BXD98 |
+ 62 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.04 |
+ 56.85 |
+ 0.484 |
+ 0.497 |
+ 0.019 |
+ 1.18 |
+ 0.76 |
+ UTM RW |
+
+
+ | 144 |
+ R2197H1 |
+ BXD99 |
+ 70 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.288 |
+ 51.75 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.35 |
+ 0.81 |
+ UTM RW |
+
+
+ | 145 |
+ R2315H1 |
+ BXD99 |
+ 84 |
+ M |
+ 5 |
+ 2 |
+ 0.03 |
+ 6.036 |
+ 43.05 |
+ 0.484 |
+ 0.497 |
+ 0.018 |
+ 1.7 |
+ 0.96 |
+ UTM RW |
+
+
+ | 146 |
+ R2028H2 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 4.362 |
+ 64.49 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 2.78 |
+ 1.13 |
+ JAX |
+
+
+ | 147 |
+ R2029H2 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.04 |
+ 5.208 |
+ 41.21 |
+ 0.49 |
+ 0.49 |
+ 0.02 |
+ 1.62 |
+ 0.95 |
+ JAX |
+
+
+ | 148 |
+ R2670H1 |
+ A/J |
+ 65 |
+ F |
+ 7 |
+ 3 |
+ 0.04 |
+ 3.951 |
+ 46.8 |
+ 0.498 |
+ 0.485 |
+ 0.017 |
+ 1.32 |
+ 0.75 |
+ UTM RW |
+
+
+ | 149 |
+ R2030H1 |
+ A/J |
+ 57 |
+ M |
+ 5 |
+ 2 |
+ 0.06 |
+ 3.307 |
+ 45.16 |
+ 0.527 |
+ 0.454 |
+ 0.018 |
+ 1.63 |
+ 0.99 |
+ UTM RW |
+
+
+ | 150 |
+ R2032H3 |
+ AKR/J |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.054 |
+ 61.03 |
+ 0.51 |
+ 0.471 |
+ 0.018 |
+ 1.46 |
+ 0.79 |
+ JAX |
+
+
+ | 151 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 152 |
+ R1675H1 |
+ BALB/cByJ |
+ 83 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.405 |
+ 48.13 |
+ 0.509 |
+ 0.474 |
+ 0.018 |
+ 1.13 |
+ 0.78 |
+ JAX |
+
+
+ | 153 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 154 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 155 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 156 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 157 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 158 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 159 |
+ R2673H1 |
+ C57BL/6ByJ |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.08 |
+ 1.842 |
+ 67.69 |
+ 0.514 |
+ 0.469 |
+ 0.017 |
+ 1.75 |
+ 0.78 |
+ JAX |
+
+
+ | 160 |
+ R2619H1 |
+ CAST/EiJ |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 161 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 162 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 163 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 164 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 165 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 166 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 167 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 168 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 169 |
+ R2677H1 |
+ PWD/PhJ |
+ 65 |
+ M |
+ 7 |
+ 2 |
+ 0.12 |
+ 2.764 |
+ 65.49 |
+ 0.462 |
+ 0.52 |
+ 0.018 |
+ 1.89 |
+ 1.16 |
+ UTM RW |
+
+
+ | 170 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 171 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 172 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 173 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 174 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+ | 175 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 176 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 177 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 178 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 179 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 180 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 181 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 182 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 183 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 184 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 185 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 186 |
+ R2676H1 |
+ CXB6 |
+ 47 |
+ F |
+ 7 |
+ 2 |
+ 0.05 |
+ 2.146 |
+ 62.51 |
+ 0.507 |
+ 0.475 |
+ 0.018 |
+ 1.52 |
+ 0.78 |
+ JAX |
+
+
+ | 187 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 188 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 189 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 190 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 191 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 192 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 193 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 194 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 195 |
+ R2671H1 |
+ CXB10 |
+ 53 |
+ M |
+ 7 |
+ 3 |
+ 0.09 |
+ 2.348 |
+ 71.45 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 2.2 |
+ 1.14 |
+ JAX |
+
+
+ | 196 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 197 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 198 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 199 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 200 |
+ R2672H1 |
+ CXB13 |
+ 49 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.722 |
+ 79.52 |
+ 0.516 |
+ 0.465 |
+ 0.019 |
+ 1.64 |
+ 0.75 |
+ JAX |
+
+
+ | 201 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hc_m2cb_1005_p/acknowledgment.rtf b/general/datasets/Hc_m2cb_1005_p/acknowledgment.rtf
new file mode 100644
index 0000000..1481cd1
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_p/acknowledgment.rtf
@@ -0,0 +1,50 @@
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
diff --git a/general/datasets/Hc_m2cb_1005_p/cases.rtf b/general/datasets/Hc_m2cb_1005_p/cases.rtf
new file mode 100644
index 0000000..15e6cda
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_p/cases.rtf
@@ -0,0 +1,56 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 27 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondrial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 strains are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2cb_1005_p/citation.rtf b/general/datasets/Hc_m2cb_1005_p/citation.rtf
new file mode 100644
index 0000000..61a0788
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_p/citation.rtf
@@ -0,0 +1 @@
+Please cite: Overall RW, Kempermann G, Peirce J, Lu L, Goldowitz D, Gage FH, Goodwin S, Smit AB, Airey DC, Rosen GD, Schalkwyk LC, Sutter TR, Nowakowski RS, Whatley S, Williams RW (2009) Genetics of the hippocampal transcriptome in mice: a systematic survey and online neurogenomic resource. Front. Neurogen. 1:3 Full Text HTML doi:10.3389/neuro.15.003.2009
diff --git a/general/datasets/Hc_m2cb_1005_p/contributors.rtf b/general/datasets/Hc_m2cb_1005_p/contributors.rtf
new file mode 100644
index 0000000..4108279
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_p/contributors.rtf
@@ -0,0 +1,46 @@
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
diff --git a/general/datasets/Hc_m2cb_1005_p/experiment-design.rtf b/general/datasets/Hc_m2cb_1005_p/experiment-design.rtf
new file mode 100644
index 0000000..356f1d2
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_p/experiment-design.rtf
@@ -0,0 +1 @@
+Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2cb_1005_p/notes.rtf b/general/datasets/Hc_m2cb_1005_p/notes.rtf
new file mode 100644
index 0000000..9c11719
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_p/notes.rtf
@@ -0,0 +1,12 @@
+This study includes the following datasets:
+
+
+ - Hippocampus Consortium M430v2 CXB (Oct05) MAS5
+ - Hippocampus Consortium M430v2 CXB (Oct05) RMA
+ - Hippocampus Consortium M430v2 CXB (Oct05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) RMA
+ - Hippocampus Consortium M430v2 (Jun06) RMA
+ - Hippocampus Consortium M430v2 (Jun06) MAS5
+ - Hippocampus Consortium M430v2 (Jun06) PDNN
+
diff --git a/general/datasets/Hc_m2cb_1005_p/platform.rtf b/general/datasets/Hc_m2cb_1005_p/platform.rtf
new file mode 100644
index 0000000..6c99bee
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_p/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2cb_1005_p/processing.rtf b/general/datasets/Hc_m2cb_1005_p/processing.rtf
new file mode 100644
index 0000000..3698a7b
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_p/processing.rtf
@@ -0,0 +1,37 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very sensitive to the transformation method that is used. Using the PDNN transform, the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For example, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one would include the sample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the probe level (CEL) data after step 5 below. DataDesk allows the rapid detection of subsets of probes that are particularly sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - We performed a quantile normalization of the log base 2 values for all arrays using the same initial steps used by the RMA transform.
+ - We computed the Z scores for each cell value.
+ - We multiplied all Z scores by 2.
+ - We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level (probe brightness level) corresponds approximately to a 1 unit difference.
+ - Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data from the CHP file: The expression values were generated using PDNN. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1 unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2cb_1005_p/summary.rtf b/general/datasets/Hc_m2cb_1005_p/summary.rtf
new file mode 100644
index 0000000..1e86e54
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_p/summary.rtf
@@ -0,0 +1,3 @@
+MOST HIGHLY RECOMMENDED DATA SET (Overall et al., 2009): The Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of 99 genetically diverse strains of mice including 67 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a diverse set of common inbred strains, and two reciprocal F1 hybrids.
+
+The hippocampus is an important and intriguing part of the forebrain that is crucial in memory formation and retrieval, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section.
diff --git a/general/datasets/Hc_m2cb_1005_p/tissue.rtf b/general/datasets/Hc_m2cb_1005_p/tissue.rtf
new file mode 100644
index 0000000..bcea7b0
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_p/tissue.rtf
@@ -0,0 +1,3721 @@
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thank Muriel Davisson for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below). All animals were sacrifice between 9 AM and 5 PM during the light phase.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+RNA Extraction: In brief, we used the RNA STAT-60 protocol (TEL-TEST "B" Bulletin No. 1), steps 5.1A (homogenization of tissue), 5.2 (RNA extraction), 5.3 (RNA precipitation), and 5.4 (RNA wash). In Step 5.4 we stopped after adding 75% ethanol (1 ml per 1 ml RNA STAT-60) and stored the mix at -80°C until further use. Before RNA labeling we thawed samples and proceeded with the remainder of Step 5.4; pelleting, drying, and redissolving the pellet in RNase-free water.
+
+We finally purify RNA by using Na4OAc before running arrays. Here is the detailed method:
+
+Final RNA purification protocol
+
+
+ - Add 1/10th volume of 3M Na4OAc , pH 5.2. If the sample was eluted with 100 µl nuclease-free water as suggested, this will be 10 µl of 3M Na4OAc.
+ - Add 2.5 volumes of 100% ethanol (250 µl if the RNA was eluted in100 µl). Mix well and incubate at –20°C for 2 hrs.
+ - Centrifuge at speed of 13,000 rpm for 20 min at 4°C. Carefully remove and discard the supernatant.
+ - Wash the pellet with 800 µl 75% cold ethanol, centrifuge at speed of 8,600 rpm for 5 min, and remove the 75% ethanol. Wash again.
+ - To remove the last traces of ethanol, quickly respin the tube, and aspirate any residual fluid.
+ - Air dry the pellet.
+ - Resuspend pellet in nuclease-free water.
+
+
+
+
+5. PROTOCOL: RNA/mRNA isolation by the RNA STAT-60 method includes the following steps:
+1. Homogenization RNA STAT-60TM (1 ml per 50-100 mg tissue, or 5-10 x 10-6 cells)
+2. RNA Extraction 1 vol. of homogenate +0.2 vol. of chloroform
+3. RNA Precipitation 0.5 vol. of isopropanol
+4. RNA Wash 75% ethanol
+
+Unless stated otherwise the procedure is carried out at room temperature.
+
+5.1 HOMOGENIZATION
+
+A. TISSUES: Homogenize tissues samples in the RNA STAT-60(1 ml/50-100mg tissue) in a glass-Teflon or Polytron homogenizer. Sample volume should not exceed 10% of the volume of the RNA STAT-60 used for homogenization.
+
+B. CELLS: Cells grown in mono layer are lysed directly in a culture dish by adding the RNA STAT-60TM (1 ml/3.5 cm petri dish) and passing the cell lysate several times through a pipette. Cells grown in suspension are sediment then lysed in the RNA STAT-60TM (1 ml per 5-10 x 106 cells) by repetitive pipetting. Washing calls before addition of the RNA STAT-60TM should be avoided as this increases the possibility of mRNA degradation.
+
+5.2 RNA EXTRACTION: Following homogenization, store the homogenate for 5 min at room temp to permit the complete dissociation of nucleoprotein complexes. Next, add 0.2 ml of chloroform per 1 ml of the RNA STAT-60, cover the sample tightly, shake vigorously for 15 seconds and let it stay at room temperature for 2-3minutes. Centrifuge the homogenate at 12,000g (max) for 15 minutes at 4°C. Following centrifugation, the homogenate separates into two phases: a lower red phenol chloroform phase and the colorless upper aqueous phase. RNA remains exclusively in the aqueous phase whereas DNA and proteins are in the interferes and organic phase. The volume of the aqueous phase is about 60% of the volume of RNA STAT-60 used for homogenization.
+
+5.3 RNA PRECIPITATION: Transfer the aqueous phase to a fresh tube and mix with isopropanol. Add 0.5 ml of isopropanol per 1 ml of the RNA STAT-60 used for homogenization. Store samples at room temp for 5-10 minutes and centrifuge at 12,000g (max.) for 10 min at 4°C. RNA precipitate (often visible before centrifugation) forms a white pellet at the bottom of the tube.
+
+5.4 RNA WASH: Remove supernatant and wash the RNA pellet once with 75% ethanol by vortexing and subsequent centrifugation at 7,500g (max.) for 5 min at 4°C. Add at least 1 ml of 75% ethanol per 1 ml of the RNA STAT-60 used for the initial homogenization.
+
+At the end of the procedure, dry the RNA pellet briefly by air-drying or in a vacuum (5-10 min.). It is important not to let the RNA pellet dry completely as it will greatly decrease its solubility. Do not use the Speed-Vac for drying. Dissolve the RNA pellet in water or in 1 mm EDTA, pH 7, or 0.5% SDS solution. Vortex or pass the pellet a few times through a pipette tip. An incubation for 10-15 minutes at 55-60oC may be required to dissolve RNA samples. Diethylpyrocarbonate (DEPC) treated RNase-free solutions1 should be used for solubilization of RNA.
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80°C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: Our goal was to obtain a male sample pool and female sample pool from each isogenic group. While almost all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. All but 5 of 99 strains (BXD55, BXD86, BXD94, BALB/cByJ, and CAST/EiJ) are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquots R1291H3 and R1291H4).
+
+
+
+Sex Balance: Based on the expression of Xist, probe set 1427262_at, DBA/2J and KK/HlJ are represented only by female samples, BXD55, and BALB/cByJ are only represented by a single male sample, BXD74 is represented by two male samples, and BXD86, BXD94, and CAST/EiJ are possibly mixed sex samples. One of the BXD9 samples, array R1523, may be a mixed sex sample pool because the expression of Xist is intermediate.
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays. Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4°C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+COMPARISON with December 2005 Data Set: Both BXD14 arrays in the Dec05 data set were found to actually be from BXD23 cases. This error of strain identification has been corrected in the present data set. Four arrays in the Dec05 data set have been deleted because we judged them to be of poor quality (strain_sex_sample_firstreaction_group):
+
+
+ - BXD21_F_1_1_G1
+ - BXD23_M_1_1_G7
+ - BXD36_M_1_1_G2
+ - BXD36_F_1_1_G3
+
+
+In the Dec05 data set there are a total of 1986 transcripts with QTLs that have LRS scores above 50, whereas in the corrected June06 data sets there are a total of 2074 transcripts with QTLs above 50.
+
+Data Table 1:
+
+This table lists all arrays by file order (Index), tube/sample ID, age, sex, batch, and numbers of animals in each sample pool (pool size). The next columns (RMA outlier, scale factor, background average, present, absent, marginal, AFFY-b-ActinMur(3'/5'), AFFY-GapdhMur(3'/5')) are all Affymetrix QC data. Finally, source lists the source colony of the animals. (Final version, fully corrected, by Arthur Centeno, October 2008)
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool size |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 2 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 3 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M technical duplicate of above |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 4 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 5 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 2.579 |
+ 58.49 |
+ 0.506 |
+ 0.475 |
+ 0.019 |
+ 2.49 |
+ 1.21 |
+ UTM RW |
+
+
+ | 6 |
+ R1551H1 |
+ D2B6F1 |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.62 |
+ 53.76 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 1.37 |
+ 0.76 |
+ UTM RW |
+
+
+ | 7 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
+ 3.058 |
+ 51.87 |
+ 0.477 |
+ 0.503 |
+ 0.02 |
+ 1.67 |
+ 0.76 |
+ UTM RW |
+
+
+ | 8 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
+ 3.341 |
+ 49.26 |
+ 0.527 |
+ 0.456 |
+ 0.018 |
+ 1.14 |
+ 1.45 |
+ UTM RW |
+
+
+ | 9 |
+ R1449H2 |
+ C57BL/6J |
+ 71 |
+ M |
+ 5 |
+ 3 |
+ 0.09 |
+ 3.592 |
+ 44.32 |
+ 0.47 |
+ 0.51 |
+ 0.02 |
+ 1.68 |
+ 0.77 |
+ UTM DG |
+
+
+ | 10 |
+ R1290H2 |
+ DBA/2J |
+ 63 |
+ F |
+ 7 |
+ 2 |
+ 0.04 |
+ 2.576 |
+ 59.6 |
+ 0.513 |
+ 0.468 |
+ 0.018 |
+ 1.3 |
+ 0.78 |
+ JAX |
+
+
+ | 11 |
+ R1468H1 |
+ DBA/2J |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.03 |
+ 2.929 |
+ 53.8 |
+ 0.515 |
+ 0.465 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 12 |
+ R1507H1 |
+ BXD1 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.056 |
+ 60.17 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.15 |
+ 0.76 |
+ Glenn |
+
+
+ | 13 |
+ R1542H1 |
+ BXD1 |
+ 59 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.792 |
+ 80.56 |
+ 0.492 |
+ 0.489 |
+ 0.018 |
+ 1.57 |
+ 0.79 |
+ Glenn |
+
+
+ | 14 |
+ R1520H1 |
+ BXD2 |
+ 56 |
+ F |
+ 4 |
+ 4 |
+ 0.09 |
+ 1.715 |
+ 71.62 |
+ 0.515 |
+ 0.467 |
+ 0.018 |
+ 2.36 |
+ 1.6 |
+ Glenn |
+
+
+ | 15 |
+ R1516H1 |
+ BXD2 |
+ 61 |
+ M |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.231 |
+ 64.86 |
+ 0.508 |
+ 0.474 |
+ 0.019 |
+ 1.3 |
+ 1.53 |
+ Glenn |
+
+
+ | 16 |
+ R1593H2 |
+ BXD5 |
+ 60 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 1.913 |
+ 59.96 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.98 |
+ 1.44 |
+ Glenn |
+
+
+ | 17 |
+ R1692H1 |
+ BXD5 |
+ 60 |
+ M |
+ 3 |
+ 2 |
+ 0.07 |
+ 3.764 |
+ 72.74 |
+ 0.465 |
+ 0.516 |
+ 0.02 |
+ 1.15 |
+ 0.74 |
+ Glenn |
+
+
+ | 18 |
+ R1539H2 |
+ BXD6 |
+ 59 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 2.488 |
+ 54.97 |
+ 0.518 |
+ 0.463 |
+ 0.018 |
+ 1.08 |
+ 1.33 |
+ Glenn |
+
+
+ | 19 |
+ R1538H1 |
+ BXD6 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.01 |
+ 2.585 |
+ 50.27 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 1.46 |
+ 0.79 |
+ Glenn |
+
+
+ | 20 |
+ R1518H1 |
+ BXD8 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 2.92 |
+ 54.84 |
+ 0.515 |
+ 0.465 |
+ 0.02 |
+ 1.32 |
+ 1.24 |
+ Glenn |
+
+
+ | 21 |
+ R1548H1 |
+ BXD8 |
+ 59 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.132 |
+ 59.37 |
+ 0.504 |
+ 0.477 |
+ 0.019 |
+ 2.16 |
+ 1.54 |
+ Glenn |
+
+
+ | 22 |
+ R1350H2 |
+ BXD9 |
+ 86 |
+ F |
+ 1 |
+ 3 |
+ 0.05 |
+ 2.771 |
+ 60.62 |
+ 0.5 |
+ 0.482 |
+ 0.018 |
+ 1.01 |
+ 1.28 |
+ UMemphis |
+
+
+ | 23 |
+ R1523H3 |
+ BXD9 |
+ 57 |
+ MF (mixed) |
+ 7 |
+ 3 |
+ 0.14 |
+ 3.9 |
+ 78.36 |
+ 0.435 |
+ 0.547 |
+ 0.018 |
+ 1.36 |
+ 0.77 |
+ UTM RW |
+
+
+ | 24 |
+ R1531H1 |
+ BXD11 |
+ 56 |
+ F |
+ 6 |
+ 3 |
+ 0.06 |
+ 2.229 |
+ 56.36 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 2.23 |
+ 1.02 |
+ Glenn |
+
+
+ | 25 |
+ R1367H1 |
+ BXD11 |
+ 56 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.11 |
+ 78.78 |
+ 0.503 |
+ 0.477 |
+ 0.02 |
+ 1.07 |
+ 1.27 |
+ Glenn |
+
+
+ | 26 |
+ R1530H1 |
+ BXD12 |
+ 58 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 3.227 |
+ 53.77 |
+ 0.505 |
+ 0.477 |
+ 0.018 |
+ 0.95 |
+ 1.4 |
+ Glenn |
+
+
+ | 27 |
+ R2674H1 |
+ BXD12 |
+ 59 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.924 |
+ 83.44 |
+ 0.519 |
+ 0.464 |
+ 0.018 |
+ 1.21 |
+ 0.78 |
+ Glenn |
+
+
+ | 28 |
+ R1529H1 |
+ BXD13 |
+ 58 |
+ F |
+ 6 |
+ 3 |
+ 0.05 |
+ 2.55 |
+ 59.05 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 2 |
+ 1.54 |
+ Glenn |
+
+
+ | 29 |
+ R1662H2 |
+ BXD13 |
+ 60 |
+ M |
+ 1 |
+ 3 |
+ 0.03 |
+ 4.603 |
+ 45.81 |
+ 0.509 |
+ 0.472 |
+ 0.019 |
+ 1.3 |
+ 0.82 |
+ Glenn |
+
+
+ | 30 |
+ R1304H2 |
+ BXD14 |
+ 72 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.946 |
+ 61.87 |
+ 0.484 |
+ 0.498 |
+ 0.018 |
+ 1.22 |
+ 0.77 |
+ UTM RW |
+
+
+ | 31 |
+ R1278H2 |
+ BXD14 |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.06 |
+ 4.75 |
+ 67.52 |
+ 0.449 |
+ 0.532 |
+ 0.019 |
+ 1.1 |
+ 0.73 |
+ UTM RW |
+
+
+ | 32 |
+ R1524H1 |
+ BXD15 |
+ 60 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.961 |
+ 50.93 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 1.74 |
+ 0.91 |
+ Glenn |
+
+
+ | 33 |
+ R1515H1 |
+ BXD15 |
+ 61 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.316 |
+ 57.05 |
+ 0.503 |
+ 0.478 |
+ 0.019 |
+ 1.32 |
+ 1.21 |
+ Glenn |
+
+
+ | 34 |
+ R1661H1 |
+ BXD16 |
+ 61 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.778 |
+ 59.81 |
+ 0.516 |
+ 0.466 |
+ 0.019 |
+ 1.39 |
+ 1.2 |
+ Glenn |
+
+
+ | 35 |
+ R1594H1 |
+ BXD16 |
+ 61 |
+ M |
+ 4 |
+ 3 |
+ 0.03 |
+ 2.634 |
+ 53.66 |
+ 0.504 |
+ 0.478 |
+ 0.018 |
+ 1.96 |
+ 1.51 |
+ Glenn |
+
+
+ | 36 |
+ R2666H1 |
+ BXD19 |
+ 60 |
+ F |
+ 7 |
+ 3 |
+ 0.02 |
+ 2.498 |
+ 76.2 |
+ 0.495 |
+ 0.486 |
+ 0.019 |
+ 1.41 |
+ 0.77 |
+ Glenn |
+
+
+ | 37 |
+ R1471H1 |
+ BXD19 |
+ 157 |
+ M |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.165 |
+ 43.34 |
+ 0.519 |
+ 0.462 |
+ 0.018 |
+ 1.01 |
+ 1.29 |
+ UTM JB |
+
+
+ | 38 |
+ R1573H1 |
+ BXD20 |
+ 59 |
+ F |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.749 |
+ 52.7 |
+ 0.513 |
+ 0.469 |
+ 0.018 |
+ 1.01 |
+ 1.27 |
+ Glenn |
+
+
+ | 39 |
+ R2507H1 |
+ BXD20 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.06 |
+ 3.568 |
+ 57 |
+ 0.472 |
+ 0.508 |
+ 0.02 |
+ 1.29 |
+ 0.76 |
+ Glenn |
+
+
+ | 40 |
+ R2668H1 |
+ BXD21 |
+ 60 |
+ M |
+ 7 |
+ 4 |
+ 0.07 |
+ 2.605 |
+ 44.9 |
+ 0.535 |
+ 0.449 |
+ 0.017 |
+ 1.54 |
+ 0.76 |
+ Glenn |
+
+
+ | 41 |
+ R1337H2 |
+ BXD21 |
+ 102 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.673 |
+ 58.05 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.4 |
+ 0.76 |
+ UAB |
+
+
+ | 42 |
+ R1848H3 |
+ BXD22 |
+ 196 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.943 |
+ 51.7 |
+ 0.494 |
+ 0.485 |
+ 0.021 |
+ 2.2 |
+ 0.78 |
+ UAB |
+
+
+ | 43 |
+ R1525H1 |
+ BXD22 |
+ 59 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.248 |
+ 55.76 |
+ 0.548 |
+ 0.433 |
+ 0.018 |
+ 1.26 |
+ 0.74 |
+ Glenn |
+
+
+ | 44 |
+ R1280H2 |
+ BXD23 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.187 |
+ 54.63 |
+ 0.458 |
+ 0.523 |
+ 0.019 |
+ 0.96 |
+ 1.2 |
+ UTM RW |
+
+
+ | 45 |
+ R1537H1 |
+ BXD23 |
+ 58 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.719 |
+ 67.54 |
+ 0.468 |
+ 0.513 |
+ 0.019 |
+ 1.51 |
+ 0.96 |
+ Glenn |
+
+
+ | 46 |
+ R1343H2 |
+ BXD24 |
+ 71 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.083 |
+ 65.07 |
+ 0.506 |
+ 0.474 |
+ 0.019 |
+ 1.46 |
+ 0.75 |
+ UMemphis |
+
+
+ | 47 |
+ R1517H1 |
+ BXD24 |
+ 57 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.471 |
+ 53.66 |
+ 0.504 |
+ 0.476 |
+ 0.019 |
+ 1.28 |
+ 0.78 |
+ Glenn |
+
+
+ | 48 |
+ R1366H1 |
+ BXD27 |
+ 60 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.26 |
+ 48.46 |
+ 0.518 |
+ 0.463 |
+ 0.019 |
+ 1.29 |
+ 0.77 |
+ Glenn |
+
+
+ | 49 |
+ R1849H1 |
+ BXD27 |
+ 70 |
+ M |
+ 5 |
+ 3 |
+ 0.06 |
+ 8.801 |
+ 38.34 |
+ 0.468 |
+ 0.512 |
+ 0.019 |
+ 2.42 |
+ 1.08 |
+ UAB |
+
+
+ | 50 |
+ R1353H1 |
+ BXD28 |
+ 79 |
+ F |
+ 3 |
+ 4 |
+ 0.01 |
+ 3.22 |
+ 76.22 |
+ 0.48 |
+ 0.5 |
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+
+
+ | 51 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 52 |
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+ 57 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 53 |
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+ 5 |
+ 3 |
+ 0.01 |
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+
+
+ | 54 |
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+ 2 |
+ 3 |
+ 0.02 |
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+
+
+ | 55 |
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+ 7 |
+ 4 |
+ 0.1 |
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+
+
+ | 56 |
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+ 7 |
+ 3 |
+ 0.03 |
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+
+
+ | 57 |
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+ 2 |
+ 4 |
+ 0.01 |
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+
+
+ | 58 |
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+ 2 |
+ 2 |
+ 0.01 |
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+
+
+ | 59 |
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+ 3 |
+ 3 |
+ 0.01 |
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+
+
+ | 60 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 61 |
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+ 5 |
+ 3 |
+ 0.12 |
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+
+ | 62 |
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+ 3 |
+ 4 |
+ 0.01 |
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+
+
+ | 63 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 64 |
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+ 2 |
+ 3 |
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+
+
+ | 65 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+ | 66 |
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+ 4 |
+ 4 |
+ 0 |
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+
+
+ | 67 |
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+ 2 |
+ 3 |
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+
+ | 68 |
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+ 7 |
+ 3 |
+ 0.07 |
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+
+
+ | 69 |
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+ 7 |
+ 4 |
+ 0.03 |
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+
+
+ | 70 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 71 |
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+ 3 |
+ 4 |
+ 0.02 |
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+
+
+ | 72 |
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+ 3 |
+ 4 |
+ 0 |
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+
+
+ | 73 |
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+ 1 |
+ 3 |
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+
+
+ | 74 |
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+ 2 |
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+
+ | 75 |
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+
+
+ | 76 |
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+ 4 |
+ 3 |
+ 0 |
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+
+
+ | 77 |
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+ 3 |
+ 4 |
+ 0.05 |
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+
+
+ | 78 |
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+
+
+ | 79 |
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+ 1 |
+ 3 |
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+
+
+ | 80 |
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+ 3 |
+ 0.03 |
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+
+
+ | 81 |
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+ 6 |
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+ 0.03 |
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+
+
+ | 82 |
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+ 3 |
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+
+
+ | 83 |
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+ 0.01 |
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+
+
+ | 84 |
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+ 3 |
+ 0 |
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+
+
+ | 85 |
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+
+
+ | 86 |
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+ 2 |
+ 0 |
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+
+
+ | 87 |
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+
+
+ | 88 |
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+
+
+ | 89 |
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+
+
+ | 90 |
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+
+
+ | 91 |
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+
+
+ | 92 |
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+
+
+ | 93 |
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+
+
+ | 94 |
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+ 0 |
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+
+
+ | 95 |
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+
+ | 96 |
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+
+ | 97 |
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+
+
+ | 98 |
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+
+ | 99 |
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+
+
+ | 100 |
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+
+
+ | 101 |
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+
+
+ | 102 |
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+
+
+ | 103 |
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+
+
+ | 104 |
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+
+
+ | 105 |
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+
+
+ | 106 |
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+ 3 |
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+
+
+ | 107 |
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+
+
+ | 108 |
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+
+
+ | 109 |
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+
+
+ | 110 |
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+ 0.01 |
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+
+
+ | 111 |
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+
+
+ | 112 |
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+ 0.01 |
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+
+
+ | 113 |
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+
+
+ | 114 |
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+
+
+ | 115 |
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+
+
+ | 116 |
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+
+
+ | 117 |
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+
+
+ | 118 |
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+ 3 |
+ 0.02 |
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+
+
+ | 119 |
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+ 0.01 |
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+
+
+ | 120 |
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+ 3 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 121 |
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+ 2 |
+ 0 |
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+
+
+ | 122 |
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+ 2 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 123 |
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+ 3 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 124 |
+ R1474H1 |
+ BXD85 |
+ 57 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.831 |
+ 55.24 |
+ 0.522 |
+ 0.461 |
+ 0.018 |
+ 1.04 |
+ 1.29 |
+ UTM RW |
+
+
+ | 125 |
+ R1597H1 |
+ BXD85 |
+ 86 |
+ M |
+ 4 |
+ 4 |
+ 0.09 |
+ 2.028 |
+ 53.95 |
+ 0.487 |
+ 0.492 |
+ 0.021 |
+ 1.28 |
+ 0.83 |
+ UTM RW |
+
+
+ | 126 |
+ R1415H1 |
+ BXD86 |
+ 77 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 2.525 |
+ 53.16 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.66 |
+ 0.91 |
+ UTM RW |
+
+
+ | 127 |
+ R2669H2 |
+ BXD87 |
+ 63 |
+ F |
+ 7 |
+ 3 |
+ 0.07 |
+ 2.61 |
+ 57.59 |
+ 0.513 |
+ 0.47 |
+ 0.018 |
+ 1.6 |
+ 0.91 |
+ UTM RW |
+
+
+ | 128 |
+ R1710H1 |
+ BXD87 |
+ 84 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 2.697 |
+ 56.4 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 129 |
+ R1872H2 |
+ BXD89 |
+ 90 |
+ F |
+ 2 |
+ 2 |
+ 0.02 |
+ 3.013 |
+ 63.53 |
+ 0.492 |
+ 0.488 |
+ 0.021 |
+ 1.22 |
+ 0.72 |
+ UTM RW |
+
+
+ | 130 |
+ R1850H3 |
+ BXD89 |
+ 82 |
+ M |
+ 4 |
+ 4 |
+ 0.03 |
+ 2.736 |
+ 44.89 |
+ 0.498 |
+ 0.483 |
+ 0.019 |
+ 1.5 |
+ 0.83 |
+ UTM RW |
+
+
+ | 131 |
+ R2058H1 |
+ BXD90 |
+ 61 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 3.389 |
+ 48.05 |
+ 0.502 |
+ 0.478 |
+ 0.02 |
+ 1.53 |
+ 0.76 |
+ UTM RW |
+
+
+ | 132 |
+ R1600H2 |
+ BXD90 |
+ 74 |
+ M |
+ 7 |
+ 4 |
+ 0.03 |
+ 3.261 |
+ 51.31 |
+ 0.517 |
+ 0.465 |
+ 0.018 |
+ 1.16 |
+ 0.75 |
+ Glenn |
+
+
+ | 133 |
+ R1301H2 |
+ BXD92 |
+ 58 |
+ F |
+ 2 |
+ 3 |
+ 0.02 |
+ 3.543 |
+ 41.97 |
+ 0.522 |
+ 0.46 |
+ 0.018 |
+ 1.5 |
+ 0.79 |
+ UTM RW |
+
+
+ | 134 |
+ R1309H1 |
+ BXD92 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.05 |
+ 1.655 |
+ 66.34 |
+ 0.498 |
+ 0.481 |
+ 0.021 |
+ 1.52 |
+ 0.82 |
+ UTM RW |
+
+
+ | 135 |
+ R2057H1 |
+ BXD93 |
+ 92 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.033 |
+ 44.41 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 1.22 |
+ 0.78 |
+ UTM RW |
+
+
+ | 136 |
+ R2059H1 |
+ BXD93 |
+ 58 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.058 |
+ 60.29 |
+ 0.493 |
+ 0.488 |
+ 0.019 |
+ 1.18 |
+ 1.37 |
+ UTM RW |
+
+
+ | 137 |
+ R2313H1 |
+ BXD94 |
+ 59 |
+ F |
+ 3 |
+ 3 |
+ 0 |
+ 3.091 |
+ 59.45 |
+ 0.487 |
+ 0.495 |
+ 0.018 |
+ 1.34 |
+ 0.73 |
+ UTM RW |
+
+
+ | 138 |
+ R1915H1 |
+ BXD96 |
+ 65 |
+ F |
+ 5 |
+ 2 |
+ 0.04 |
+ 5.145 |
+ 46.19 |
+ 0.502 |
+ 0.481 |
+ 0.017 |
+ 1.37 |
+ 0.74 |
+ UTM RW |
+
+
+ | 139 |
+ R1846H2 |
+ BXD96 |
+ 63 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.159 |
+ 55.85 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.92 |
+ 1.26 |
+ UTM RW |
+
+
+ | 140 |
+ R2648H1 |
+ BXD97 |
+ 74 |
+ F |
+ 7 |
+ 4 |
+ 0.02 |
+ 1.664 |
+ 82.08 |
+ 0.518 |
+ 0.464 |
+ 0.019 |
+ 1.4 |
+ 0.78 |
+ UTM RW |
+
+
+ | 141 |
+ R1927H2 |
+ BXD97 |
+ 67 |
+ M |
+ 1 |
+ 3 |
+ 0.04 |
+ 2.622 |
+ 57.81 |
+ 0.539 |
+ 0.444 |
+ 0.017 |
+ 1.45 |
+ 1.32 |
+ UTM RW |
+
+
+ | 142 |
+ R1942H1 |
+ BXD98 |
+ 62 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.104 |
+ 48.42 |
+ 0.528 |
+ 0.454 |
+ 0.019 |
+ 2.22 |
+ 1.08 |
+ UTM RW |
+
+
+ | 143 |
+ R1943H2 |
+ BXD98 |
+ 62 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.04 |
+ 56.85 |
+ 0.484 |
+ 0.497 |
+ 0.019 |
+ 1.18 |
+ 0.76 |
+ UTM RW |
+
+
+ | 144 |
+ R2197H1 |
+ BXD99 |
+ 70 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.288 |
+ 51.75 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.35 |
+ 0.81 |
+ UTM RW |
+
+
+ | 145 |
+ R2315H1 |
+ BXD99 |
+ 84 |
+ M |
+ 5 |
+ 2 |
+ 0.03 |
+ 6.036 |
+ 43.05 |
+ 0.484 |
+ 0.497 |
+ 0.018 |
+ 1.7 |
+ 0.96 |
+ UTM RW |
+
+
+ | 146 |
+ R2028H2 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 4.362 |
+ 64.49 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 2.78 |
+ 1.13 |
+ JAX |
+
+
+ | 147 |
+ R2029H2 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.04 |
+ 5.208 |
+ 41.21 |
+ 0.49 |
+ 0.49 |
+ 0.02 |
+ 1.62 |
+ 0.95 |
+ JAX |
+
+
+ | 148 |
+ R2670H1 |
+ A/J |
+ 65 |
+ F |
+ 7 |
+ 3 |
+ 0.04 |
+ 3.951 |
+ 46.8 |
+ 0.498 |
+ 0.485 |
+ 0.017 |
+ 1.32 |
+ 0.75 |
+ UTM RW |
+
+
+ | 149 |
+ R2030H1 |
+ A/J |
+ 57 |
+ M |
+ 5 |
+ 2 |
+ 0.06 |
+ 3.307 |
+ 45.16 |
+ 0.527 |
+ 0.454 |
+ 0.018 |
+ 1.63 |
+ 0.99 |
+ UTM RW |
+
+
+ | 150 |
+ R2032H3 |
+ AKR/J |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.054 |
+ 61.03 |
+ 0.51 |
+ 0.471 |
+ 0.018 |
+ 1.46 |
+ 0.79 |
+ JAX |
+
+
+ | 151 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 152 |
+ R1675H1 |
+ BALB/cByJ |
+ 83 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.405 |
+ 48.13 |
+ 0.509 |
+ 0.474 |
+ 0.018 |
+ 1.13 |
+ 0.78 |
+ JAX |
+
+
+ | 153 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 154 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 155 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 156 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 157 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 158 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 159 |
+ R2673H1 |
+ C57BL/6ByJ |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.08 |
+ 1.842 |
+ 67.69 |
+ 0.514 |
+ 0.469 |
+ 0.017 |
+ 1.75 |
+ 0.78 |
+ JAX |
+
+
+ | 160 |
+ R2619H1 |
+ CAST/EiJ |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 161 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 162 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 163 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 164 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 165 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 166 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 167 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 168 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 169 |
+ R2677H1 |
+ PWD/PhJ |
+ 65 |
+ M |
+ 7 |
+ 2 |
+ 0.12 |
+ 2.764 |
+ 65.49 |
+ 0.462 |
+ 0.52 |
+ 0.018 |
+ 1.89 |
+ 1.16 |
+ UTM RW |
+
+
+ | 170 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 171 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 172 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 173 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 174 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+ | 175 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 176 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 177 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 178 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 179 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 180 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 181 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 182 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 183 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 184 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 185 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 186 |
+ R2676H1 |
+ CXB6 |
+ 47 |
+ F |
+ 7 |
+ 2 |
+ 0.05 |
+ 2.146 |
+ 62.51 |
+ 0.507 |
+ 0.475 |
+ 0.018 |
+ 1.52 |
+ 0.78 |
+ JAX |
+
+
+ | 187 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 188 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 189 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 190 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 191 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 192 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 193 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 194 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 195 |
+ R2671H1 |
+ CXB10 |
+ 53 |
+ M |
+ 7 |
+ 3 |
+ 0.09 |
+ 2.348 |
+ 71.45 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 2.2 |
+ 1.14 |
+ JAX |
+
+
+ | 196 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 197 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 198 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 199 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 200 |
+ R2672H1 |
+ CXB13 |
+ 49 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.722 |
+ 79.52 |
+ 0.516 |
+ 0.465 |
+ 0.019 |
+ 1.64 |
+ 0.75 |
+ JAX |
+
+
+ | 201 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hc_m2cb_1005_r/acknowledgment.rtf b/general/datasets/Hc_m2cb_1005_r/acknowledgment.rtf
new file mode 100644
index 0000000..1481cd1
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_r/acknowledgment.rtf
@@ -0,0 +1,50 @@
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
diff --git a/general/datasets/Hc_m2cb_1005_r/cases.rtf b/general/datasets/Hc_m2cb_1005_r/cases.rtf
new file mode 100644
index 0000000..15e6cda
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_r/cases.rtf
@@ -0,0 +1,56 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 27 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondrial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 strains are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2cb_1005_r/citation.rtf b/general/datasets/Hc_m2cb_1005_r/citation.rtf
new file mode 100644
index 0000000..61a0788
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_r/citation.rtf
@@ -0,0 +1 @@
+Please cite: Overall RW, Kempermann G, Peirce J, Lu L, Goldowitz D, Gage FH, Goodwin S, Smit AB, Airey DC, Rosen GD, Schalkwyk LC, Sutter TR, Nowakowski RS, Whatley S, Williams RW (2009) Genetics of the hippocampal transcriptome in mice: a systematic survey and online neurogenomic resource. Front. Neurogen. 1:3 Full Text HTML doi:10.3389/neuro.15.003.2009
diff --git a/general/datasets/Hc_m2cb_1005_r/contributors.rtf b/general/datasets/Hc_m2cb_1005_r/contributors.rtf
new file mode 100644
index 0000000..4108279
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_r/contributors.rtf
@@ -0,0 +1,46 @@
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
diff --git a/general/datasets/Hc_m2cb_1005_r/experiment-design.rtf b/general/datasets/Hc_m2cb_1005_r/experiment-design.rtf
new file mode 100644
index 0000000..356f1d2
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_r/experiment-design.rtf
@@ -0,0 +1 @@
+Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2cb_1005_r/notes.rtf b/general/datasets/Hc_m2cb_1005_r/notes.rtf
new file mode 100644
index 0000000..9c11719
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_r/notes.rtf
@@ -0,0 +1,12 @@
+This study includes the following datasets:
+
+
+ - Hippocampus Consortium M430v2 CXB (Oct05) MAS5
+ - Hippocampus Consortium M430v2 CXB (Oct05) RMA
+ - Hippocampus Consortium M430v2 CXB (Oct05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) RMA
+ - Hippocampus Consortium M430v2 (Jun06) RMA
+ - Hippocampus Consortium M430v2 (Jun06) MAS5
+ - Hippocampus Consortium M430v2 (Jun06) PDNN
+
diff --git a/general/datasets/Hc_m2cb_1005_r/platform.rtf b/general/datasets/Hc_m2cb_1005_r/platform.rtf
new file mode 100644
index 0000000..6c99bee
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_r/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2cb_1005_r/processing.rtf b/general/datasets/Hc_m2cb_1005_r/processing.rtf
new file mode 100644
index 0000000..3698a7b
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_r/processing.rtf
@@ -0,0 +1,37 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very sensitive to the transformation method that is used. Using the PDNN transform, the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For example, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one would include the sample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the probe level (CEL) data after step 5 below. DataDesk allows the rapid detection of subsets of probes that are particularly sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - We performed a quantile normalization of the log base 2 values for all arrays using the same initial steps used by the RMA transform.
+ - We computed the Z scores for each cell value.
+ - We multiplied all Z scores by 2.
+ - We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level (probe brightness level) corresponds approximately to a 1 unit difference.
+ - Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data from the CHP file: The expression values were generated using PDNN. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1 unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2cb_1005_r/summary.rtf b/general/datasets/Hc_m2cb_1005_r/summary.rtf
new file mode 100644
index 0000000..1e86e54
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_r/summary.rtf
@@ -0,0 +1,3 @@
+MOST HIGHLY RECOMMENDED DATA SET (Overall et al., 2009): The Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of 99 genetically diverse strains of mice including 67 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a diverse set of common inbred strains, and two reciprocal F1 hybrids.
+
+The hippocampus is an important and intriguing part of the forebrain that is crucial in memory formation and retrieval, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section.
diff --git a/general/datasets/Hc_m2cb_1005_r/tissue.rtf b/general/datasets/Hc_m2cb_1005_r/tissue.rtf
new file mode 100644
index 0000000..bcea7b0
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1005_r/tissue.rtf
@@ -0,0 +1,3721 @@
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thank Muriel Davisson for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below). All animals were sacrifice between 9 AM and 5 PM during the light phase.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+RNA Extraction: In brief, we used the RNA STAT-60 protocol (TEL-TEST "B" Bulletin No. 1), steps 5.1A (homogenization of tissue), 5.2 (RNA extraction), 5.3 (RNA precipitation), and 5.4 (RNA wash). In Step 5.4 we stopped after adding 75% ethanol (1 ml per 1 ml RNA STAT-60) and stored the mix at -80°C until further use. Before RNA labeling we thawed samples and proceeded with the remainder of Step 5.4; pelleting, drying, and redissolving the pellet in RNase-free water.
+
+We finally purify RNA by using Na4OAc before running arrays. Here is the detailed method:
+
+Final RNA purification protocol
+
+
+ - Add 1/10th volume of 3M Na4OAc , pH 5.2. If the sample was eluted with 100 µl nuclease-free water as suggested, this will be 10 µl of 3M Na4OAc.
+ - Add 2.5 volumes of 100% ethanol (250 µl if the RNA was eluted in100 µl). Mix well and incubate at –20°C for 2 hrs.
+ - Centrifuge at speed of 13,000 rpm for 20 min at 4°C. Carefully remove and discard the supernatant.
+ - Wash the pellet with 800 µl 75% cold ethanol, centrifuge at speed of 8,600 rpm for 5 min, and remove the 75% ethanol. Wash again.
+ - To remove the last traces of ethanol, quickly respin the tube, and aspirate any residual fluid.
+ - Air dry the pellet.
+ - Resuspend pellet in nuclease-free water.
+
+
+
+
+5. PROTOCOL: RNA/mRNA isolation by the RNA STAT-60 method includes the following steps:
+1. Homogenization RNA STAT-60TM (1 ml per 50-100 mg tissue, or 5-10 x 10-6 cells)
+2. RNA Extraction 1 vol. of homogenate +0.2 vol. of chloroform
+3. RNA Precipitation 0.5 vol. of isopropanol
+4. RNA Wash 75% ethanol
+
+Unless stated otherwise the procedure is carried out at room temperature.
+
+5.1 HOMOGENIZATION
+
+A. TISSUES: Homogenize tissues samples in the RNA STAT-60(1 ml/50-100mg tissue) in a glass-Teflon or Polytron homogenizer. Sample volume should not exceed 10% of the volume of the RNA STAT-60 used for homogenization.
+
+B. CELLS: Cells grown in mono layer are lysed directly in a culture dish by adding the RNA STAT-60TM (1 ml/3.5 cm petri dish) and passing the cell lysate several times through a pipette. Cells grown in suspension are sediment then lysed in the RNA STAT-60TM (1 ml per 5-10 x 106 cells) by repetitive pipetting. Washing calls before addition of the RNA STAT-60TM should be avoided as this increases the possibility of mRNA degradation.
+
+5.2 RNA EXTRACTION: Following homogenization, store the homogenate for 5 min at room temp to permit the complete dissociation of nucleoprotein complexes. Next, add 0.2 ml of chloroform per 1 ml of the RNA STAT-60, cover the sample tightly, shake vigorously for 15 seconds and let it stay at room temperature for 2-3minutes. Centrifuge the homogenate at 12,000g (max) for 15 minutes at 4°C. Following centrifugation, the homogenate separates into two phases: a lower red phenol chloroform phase and the colorless upper aqueous phase. RNA remains exclusively in the aqueous phase whereas DNA and proteins are in the interferes and organic phase. The volume of the aqueous phase is about 60% of the volume of RNA STAT-60 used for homogenization.
+
+5.3 RNA PRECIPITATION: Transfer the aqueous phase to a fresh tube and mix with isopropanol. Add 0.5 ml of isopropanol per 1 ml of the RNA STAT-60 used for homogenization. Store samples at room temp for 5-10 minutes and centrifuge at 12,000g (max.) for 10 min at 4°C. RNA precipitate (often visible before centrifugation) forms a white pellet at the bottom of the tube.
+
+5.4 RNA WASH: Remove supernatant and wash the RNA pellet once with 75% ethanol by vortexing and subsequent centrifugation at 7,500g (max.) for 5 min at 4°C. Add at least 1 ml of 75% ethanol per 1 ml of the RNA STAT-60 used for the initial homogenization.
+
+At the end of the procedure, dry the RNA pellet briefly by air-drying or in a vacuum (5-10 min.). It is important not to let the RNA pellet dry completely as it will greatly decrease its solubility. Do not use the Speed-Vac for drying. Dissolve the RNA pellet in water or in 1 mm EDTA, pH 7, or 0.5% SDS solution. Vortex or pass the pellet a few times through a pipette tip. An incubation for 10-15 minutes at 55-60oC may be required to dissolve RNA samples. Diethylpyrocarbonate (DEPC) treated RNase-free solutions1 should be used for solubilization of RNA.
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80°C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: Our goal was to obtain a male sample pool and female sample pool from each isogenic group. While almost all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. All but 5 of 99 strains (BXD55, BXD86, BXD94, BALB/cByJ, and CAST/EiJ) are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquots R1291H3 and R1291H4).
+
+
+
+Sex Balance: Based on the expression of Xist, probe set 1427262_at, DBA/2J and KK/HlJ are represented only by female samples, BXD55, and BALB/cByJ are only represented by a single male sample, BXD74 is represented by two male samples, and BXD86, BXD94, and CAST/EiJ are possibly mixed sex samples. One of the BXD9 samples, array R1523, may be a mixed sex sample pool because the expression of Xist is intermediate.
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays. Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4°C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+COMPARISON with December 2005 Data Set: Both BXD14 arrays in the Dec05 data set were found to actually be from BXD23 cases. This error of strain identification has been corrected in the present data set. Four arrays in the Dec05 data set have been deleted because we judged them to be of poor quality (strain_sex_sample_firstreaction_group):
+
+
+ - BXD21_F_1_1_G1
+ - BXD23_M_1_1_G7
+ - BXD36_M_1_1_G2
+ - BXD36_F_1_1_G3
+
+
+In the Dec05 data set there are a total of 1986 transcripts with QTLs that have LRS scores above 50, whereas in the corrected June06 data sets there are a total of 2074 transcripts with QTLs above 50.
+
+Data Table 1:
+
+This table lists all arrays by file order (Index), tube/sample ID, age, sex, batch, and numbers of animals in each sample pool (pool size). The next columns (RMA outlier, scale factor, background average, present, absent, marginal, AFFY-b-ActinMur(3'/5'), AFFY-GapdhMur(3'/5')) are all Affymetrix QC data. Finally, source lists the source colony of the animals. (Final version, fully corrected, by Arthur Centeno, October 2008)
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool size |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 2 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 3 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M technical duplicate of above |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 4 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 5 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 2.579 |
+ 58.49 |
+ 0.506 |
+ 0.475 |
+ 0.019 |
+ 2.49 |
+ 1.21 |
+ UTM RW |
+
+
+ | 6 |
+ R1551H1 |
+ D2B6F1 |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.62 |
+ 53.76 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 1.37 |
+ 0.76 |
+ UTM RW |
+
+
+ | 7 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
+ 3.058 |
+ 51.87 |
+ 0.477 |
+ 0.503 |
+ 0.02 |
+ 1.67 |
+ 0.76 |
+ UTM RW |
+
+
+ | 8 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
+ 3.341 |
+ 49.26 |
+ 0.527 |
+ 0.456 |
+ 0.018 |
+ 1.14 |
+ 1.45 |
+ UTM RW |
+
+
+ | 9 |
+ R1449H2 |
+ C57BL/6J |
+ 71 |
+ M |
+ 5 |
+ 3 |
+ 0.09 |
+ 3.592 |
+ 44.32 |
+ 0.47 |
+ 0.51 |
+ 0.02 |
+ 1.68 |
+ 0.77 |
+ UTM DG |
+
+
+ | 10 |
+ R1290H2 |
+ DBA/2J |
+ 63 |
+ F |
+ 7 |
+ 2 |
+ 0.04 |
+ 2.576 |
+ 59.6 |
+ 0.513 |
+ 0.468 |
+ 0.018 |
+ 1.3 |
+ 0.78 |
+ JAX |
+
+
+ | 11 |
+ R1468H1 |
+ DBA/2J |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.03 |
+ 2.929 |
+ 53.8 |
+ 0.515 |
+ 0.465 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 12 |
+ R1507H1 |
+ BXD1 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.056 |
+ 60.17 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.15 |
+ 0.76 |
+ Glenn |
+
+
+ | 13 |
+ R1542H1 |
+ BXD1 |
+ 59 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.792 |
+ 80.56 |
+ 0.492 |
+ 0.489 |
+ 0.018 |
+ 1.57 |
+ 0.79 |
+ Glenn |
+
+
+ | 14 |
+ R1520H1 |
+ BXD2 |
+ 56 |
+ F |
+ 4 |
+ 4 |
+ 0.09 |
+ 1.715 |
+ 71.62 |
+ 0.515 |
+ 0.467 |
+ 0.018 |
+ 2.36 |
+ 1.6 |
+ Glenn |
+
+
+ | 15 |
+ R1516H1 |
+ BXD2 |
+ 61 |
+ M |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.231 |
+ 64.86 |
+ 0.508 |
+ 0.474 |
+ 0.019 |
+ 1.3 |
+ 1.53 |
+ Glenn |
+
+
+ | 16 |
+ R1593H2 |
+ BXD5 |
+ 60 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 1.913 |
+ 59.96 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.98 |
+ 1.44 |
+ Glenn |
+
+
+ | 17 |
+ R1692H1 |
+ BXD5 |
+ 60 |
+ M |
+ 3 |
+ 2 |
+ 0.07 |
+ 3.764 |
+ 72.74 |
+ 0.465 |
+ 0.516 |
+ 0.02 |
+ 1.15 |
+ 0.74 |
+ Glenn |
+
+
+ | 18 |
+ R1539H2 |
+ BXD6 |
+ 59 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 2.488 |
+ 54.97 |
+ 0.518 |
+ 0.463 |
+ 0.018 |
+ 1.08 |
+ 1.33 |
+ Glenn |
+
+
+ | 19 |
+ R1538H1 |
+ BXD6 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.01 |
+ 2.585 |
+ 50.27 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 1.46 |
+ 0.79 |
+ Glenn |
+
+
+ | 20 |
+ R1518H1 |
+ BXD8 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 2.92 |
+ 54.84 |
+ 0.515 |
+ 0.465 |
+ 0.02 |
+ 1.32 |
+ 1.24 |
+ Glenn |
+
+
+ | 21 |
+ R1548H1 |
+ BXD8 |
+ 59 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.132 |
+ 59.37 |
+ 0.504 |
+ 0.477 |
+ 0.019 |
+ 2.16 |
+ 1.54 |
+ Glenn |
+
+
+ | 22 |
+ R1350H2 |
+ BXD9 |
+ 86 |
+ F |
+ 1 |
+ 3 |
+ 0.05 |
+ 2.771 |
+ 60.62 |
+ 0.5 |
+ 0.482 |
+ 0.018 |
+ 1.01 |
+ 1.28 |
+ UMemphis |
+
+
+ | 23 |
+ R1523H3 |
+ BXD9 |
+ 57 |
+ MF (mixed) |
+ 7 |
+ 3 |
+ 0.14 |
+ 3.9 |
+ 78.36 |
+ 0.435 |
+ 0.547 |
+ 0.018 |
+ 1.36 |
+ 0.77 |
+ UTM RW |
+
+
+ | 24 |
+ R1531H1 |
+ BXD11 |
+ 56 |
+ F |
+ 6 |
+ 3 |
+ 0.06 |
+ 2.229 |
+ 56.36 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 2.23 |
+ 1.02 |
+ Glenn |
+
+
+ | 25 |
+ R1367H1 |
+ BXD11 |
+ 56 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.11 |
+ 78.78 |
+ 0.503 |
+ 0.477 |
+ 0.02 |
+ 1.07 |
+ 1.27 |
+ Glenn |
+
+
+ | 26 |
+ R1530H1 |
+ BXD12 |
+ 58 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 3.227 |
+ 53.77 |
+ 0.505 |
+ 0.477 |
+ 0.018 |
+ 0.95 |
+ 1.4 |
+ Glenn |
+
+
+ | 27 |
+ R2674H1 |
+ BXD12 |
+ 59 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.924 |
+ 83.44 |
+ 0.519 |
+ 0.464 |
+ 0.018 |
+ 1.21 |
+ 0.78 |
+ Glenn |
+
+
+ | 28 |
+ R1529H1 |
+ BXD13 |
+ 58 |
+ F |
+ 6 |
+ 3 |
+ 0.05 |
+ 2.55 |
+ 59.05 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 2 |
+ 1.54 |
+ Glenn |
+
+
+ | 29 |
+ R1662H2 |
+ BXD13 |
+ 60 |
+ M |
+ 1 |
+ 3 |
+ 0.03 |
+ 4.603 |
+ 45.81 |
+ 0.509 |
+ 0.472 |
+ 0.019 |
+ 1.3 |
+ 0.82 |
+ Glenn |
+
+
+ | 30 |
+ R1304H2 |
+ BXD14 |
+ 72 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.946 |
+ 61.87 |
+ 0.484 |
+ 0.498 |
+ 0.018 |
+ 1.22 |
+ 0.77 |
+ UTM RW |
+
+
+ | 31 |
+ R1278H2 |
+ BXD14 |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.06 |
+ 4.75 |
+ 67.52 |
+ 0.449 |
+ 0.532 |
+ 0.019 |
+ 1.1 |
+ 0.73 |
+ UTM RW |
+
+
+ | 32 |
+ R1524H1 |
+ BXD15 |
+ 60 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.961 |
+ 50.93 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 1.74 |
+ 0.91 |
+ Glenn |
+
+
+ | 33 |
+ R1515H1 |
+ BXD15 |
+ 61 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.316 |
+ 57.05 |
+ 0.503 |
+ 0.478 |
+ 0.019 |
+ 1.32 |
+ 1.21 |
+ Glenn |
+
+
+ | 34 |
+ R1661H1 |
+ BXD16 |
+ 61 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.778 |
+ 59.81 |
+ 0.516 |
+ 0.466 |
+ 0.019 |
+ 1.39 |
+ 1.2 |
+ Glenn |
+
+
+ | 35 |
+ R1594H1 |
+ BXD16 |
+ 61 |
+ M |
+ 4 |
+ 3 |
+ 0.03 |
+ 2.634 |
+ 53.66 |
+ 0.504 |
+ 0.478 |
+ 0.018 |
+ 1.96 |
+ 1.51 |
+ Glenn |
+
+
+ | 36 |
+ R2666H1 |
+ BXD19 |
+ 60 |
+ F |
+ 7 |
+ 3 |
+ 0.02 |
+ 2.498 |
+ 76.2 |
+ 0.495 |
+ 0.486 |
+ 0.019 |
+ 1.41 |
+ 0.77 |
+ Glenn |
+
+
+ | 37 |
+ R1471H1 |
+ BXD19 |
+ 157 |
+ M |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.165 |
+ 43.34 |
+ 0.519 |
+ 0.462 |
+ 0.018 |
+ 1.01 |
+ 1.29 |
+ UTM JB |
+
+
+ | 38 |
+ R1573H1 |
+ BXD20 |
+ 59 |
+ F |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.749 |
+ 52.7 |
+ 0.513 |
+ 0.469 |
+ 0.018 |
+ 1.01 |
+ 1.27 |
+ Glenn |
+
+
+ | 39 |
+ R2507H1 |
+ BXD20 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.06 |
+ 3.568 |
+ 57 |
+ 0.472 |
+ 0.508 |
+ 0.02 |
+ 1.29 |
+ 0.76 |
+ Glenn |
+
+
+ | 40 |
+ R2668H1 |
+ BXD21 |
+ 60 |
+ M |
+ 7 |
+ 4 |
+ 0.07 |
+ 2.605 |
+ 44.9 |
+ 0.535 |
+ 0.449 |
+ 0.017 |
+ 1.54 |
+ 0.76 |
+ Glenn |
+
+
+ | 41 |
+ R1337H2 |
+ BXD21 |
+ 102 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.673 |
+ 58.05 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.4 |
+ 0.76 |
+ UAB |
+
+
+ | 42 |
+ R1848H3 |
+ BXD22 |
+ 196 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.943 |
+ 51.7 |
+ 0.494 |
+ 0.485 |
+ 0.021 |
+ 2.2 |
+ 0.78 |
+ UAB |
+
+
+ | 43 |
+ R1525H1 |
+ BXD22 |
+ 59 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.248 |
+ 55.76 |
+ 0.548 |
+ 0.433 |
+ 0.018 |
+ 1.26 |
+ 0.74 |
+ Glenn |
+
+
+ | 44 |
+ R1280H2 |
+ BXD23 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.187 |
+ 54.63 |
+ 0.458 |
+ 0.523 |
+ 0.019 |
+ 0.96 |
+ 1.2 |
+ UTM RW |
+
+
+ | 45 |
+ R1537H1 |
+ BXD23 |
+ 58 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.719 |
+ 67.54 |
+ 0.468 |
+ 0.513 |
+ 0.019 |
+ 1.51 |
+ 0.96 |
+ Glenn |
+
+
+ | 46 |
+ R1343H2 |
+ BXD24 |
+ 71 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.083 |
+ 65.07 |
+ 0.506 |
+ 0.474 |
+ 0.019 |
+ 1.46 |
+ 0.75 |
+ UMemphis |
+
+
+ | 47 |
+ R1517H1 |
+ BXD24 |
+ 57 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.471 |
+ 53.66 |
+ 0.504 |
+ 0.476 |
+ 0.019 |
+ 1.28 |
+ 0.78 |
+ Glenn |
+
+
+ | 48 |
+ R1366H1 |
+ BXD27 |
+ 60 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.26 |
+ 48.46 |
+ 0.518 |
+ 0.463 |
+ 0.019 |
+ 1.29 |
+ 0.77 |
+ Glenn |
+
+
+ | 49 |
+ R1849H1 |
+ BXD27 |
+ 70 |
+ M |
+ 5 |
+ 3 |
+ 0.06 |
+ 8.801 |
+ 38.34 |
+ 0.468 |
+ 0.512 |
+ 0.019 |
+ 2.42 |
+ 1.08 |
+ UAB |
+
+
+ | 50 |
+ R1353H1 |
+ BXD28 |
+ 79 |
+ F |
+ 3 |
+ 4 |
+ 0.01 |
+ 3.22 |
+ 76.22 |
+ 0.48 |
+ 0.5 |
+ 0.02 |
+ 1.33 |
+ 0.78 |
+ UMemphis |
+
+
+ | 51 |
+ R2332H1 |
+ BXD28 |
+ 60 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 3.217 |
+ 63.68 |
+ 0.491 |
+ 0.49 |
+ 0.019 |
+ 1.37 |
+ 0.79 |
+ Glenn |
+
+
+ | 52 |
+ R1532H1 |
+ BXD29 |
+ 57 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.122 |
+ 59.18 |
+ 0.524 |
+ 0.456 |
+ 0.019 |
+ 1.17 |
+ 0.76 |
+ Glenn |
+
+
+ | 53 |
+ R1356H1 |
+ BXD29 |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.01 |
+ 4.033 |
+ 47.67 |
+ 0.52 |
+ 0.463 |
+ 0.017 |
+ 1.17 |
+ 0.78 |
+ UMemphis |
+
+
+ | 54 |
+ R1240H2 |
+ BXD31 |
+ 61 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.335 |
+ 65.17 |
+ 0.507 |
+ 0.474 |
+ 0.019 |
+ 1.31 |
+ 0.78 |
+ UTM RW |
+
+
+ | 55 |
+ R1526H2 |
+ BXD31 |
+ 57 |
+ F |
+ 7 |
+ 4 |
+ 0.1 |
+ 7.267 |
+ 89.54 |
+ 0.435 |
+ 0.547 |
+ 0.017 |
+ 1.35 |
+ 0.78 |
+ UTM RW |
+
+
+ | 56 |
+ R2675H1 |
+ BXD32 |
+ 57 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 2.268 |
+ 78.01 |
+ 0.502 |
+ 0.478 |
+ 0.02 |
+ 1.22 |
+ 0.78 |
+ Glenn |
+
+
+ | 57 |
+ R1508H2 |
+ BXD32 |
+ 58 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 1.917 |
+ 67.78 |
+ 0.539 |
+ 0.442 |
+ 0.019 |
+ 1.28 |
+ 0.73 |
+ Glenn |
+
+
+ | 58 |
+ R1345H3 |
+ BXD33 |
+ 65 |
+ F |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.098 |
+ 63.14 |
+ 0.522 |
+ 0.459 |
+ 0.019 |
+ 1.27 |
+ 0.73 |
+ UMemphis |
+
+
+ | 59 |
+ R1581H1 |
+ BXD33 |
+ 59 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.229 |
+ 53.16 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.19 |
+ 0.78 |
+ Glenn |
+
+
+ | 60 |
+ R1527H1 |
+ BXD34 |
+ 59 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.3 |
+ 58.92 |
+ 0.51 |
+ 0.471 |
+ 0.019 |
+ 1.24 |
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+
+
+ | 61 |
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+ 5 |
+ 3 |
+ 0.12 |
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+
+
+ | 62 |
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+ 55 |
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+ 3 |
+ 4 |
+ 0.01 |
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+
+
+ | 63 |
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+ 59 |
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+ 2 |
+ 3 |
+ 0.01 |
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+
+
+ | 64 |
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+ 2 |
+ 3 |
+ 0.03 |
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+
+
+ | 65 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+
+ | 66 |
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+ 4 |
+ 4 |
+ 0 |
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+
+
+ | 67 |
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+ 2 |
+ 3 |
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+
+
+ | 68 |
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+ 7 |
+ 3 |
+ 0.07 |
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+
+
+ | 69 |
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+ 7 |
+ 4 |
+ 0.03 |
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+
+
+ | 70 |
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+ 59 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 71 |
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+ 63 |
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+ 3 |
+ 4 |
+ 0.02 |
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+
+
+ | 72 |
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+ 65 |
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+ 3 |
+ 4 |
+ 0 |
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+
+
+ | 73 |
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+ 56 |
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+ 1 |
+ 3 |
+ 0.02 |
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+
+
+ | 74 |
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+ 7 |
+ 2 |
+ 0.03 |
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+
+
+ | 75 |
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+ 7 |
+ 4 |
+ 0.04 |
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+
+
+ | 76 |
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+ 58 |
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+ 4 |
+ 3 |
+ 0 |
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+
+
+ | 77 |
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+ 65 |
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+ 3 |
+ 4 |
+ 0.05 |
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+
+
+ | 78 |
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+ 6 |
+ 4 |
+ 0.01 |
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+
+
+ | 79 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 80 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+
+ | 81 |
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+ 6 |
+ 4 |
+ 0.03 |
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+
+
+ | 82 |
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+ 7 |
+ 3 |
+ 0.07 |
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+
+
+ | 83 |
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+ 4 |
+ 3 |
+ 0.01 |
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+
+
+ | 84 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 85 |
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+ 7 |
+ 4 |
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+
+
+ | 86 |
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+ 1 |
+ 2 |
+ 0 |
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+
+
+ | 87 |
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+ 1 |
+ 4 |
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+
+
+ | 88 |
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+ 6 |
+ 4 |
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+
+
+ | 89 |
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+ 1 |
+ 3 |
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+
+
+ | 90 |
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+ 6 |
+ 3 |
+ 0.02 |
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+
+
+ | 91 |
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+ 1 |
+ 3 |
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+
+
+ | 92 |
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+ 3 |
+ 4 |
+ 0.01 |
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+
+
+ | 93 |
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+ 1 |
+ 2 |
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+
+
+ | 94 |
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+ 6 |
+ 2 |
+ 0 |
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+
+
+ | 95 |
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+ 1 |
+ 4 |
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+
+
+ | 96 |
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+ 2 |
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+
+
+ | 97 |
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+ 3 |
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+
+
+ | 98 |
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+
+
+ | 99 |
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+
+
+ | 100 |
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+ 2 |
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+
+
+ | 101 |
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+
+
+ | 102 |
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+ 3 |
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+
+
+ | 103 |
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+
+
+ | 104 |
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+
+
+ | 105 |
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+
+
+ | 106 |
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+ 3 |
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+
+
+ | 107 |
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+
+
+ | 108 |
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+
+
+ | 109 |
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+
+
+ | 110 |
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+ 0.01 |
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+
+
+ | 111 |
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+
+
+ | 112 |
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+ 0.01 |
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+
+
+ | 113 |
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+
+
+ | 114 |
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+ 3 |
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+
+
+ | 115 |
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+ 2 |
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+
+
+ | 116 |
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+
+
+ | 117 |
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+ 3 |
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+
+
+ | 118 |
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+ 3 |
+ 0.02 |
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+
+
+ | 119 |
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+ 3 |
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+
+
+ | 120 |
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+ 3 |
+ 0.03 |
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+
+
+ | 121 |
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+ 2 |
+ 0 |
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+
+
+ | 122 |
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+ 2 |
+ 0.01 |
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+
+
+ | 123 |
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+ 3 |
+ 0.02 |
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+
+
+ | 124 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 125 |
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+ 4 |
+ 0.09 |
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+
+
+ | 126 |
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+ 3 |
+ 0.02 |
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+
+
+ | 127 |
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+ 3 |
+ 0.07 |
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+
+
+ | 128 |
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+ 2 |
+ 4 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 129 |
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+ 2 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 130 |
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+ 4 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 131 |
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+ 3 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 132 |
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+ 7 |
+ 4 |
+ 0.03 |
+ 3.261 |
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+
+
+ | 133 |
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+ 2 |
+ 3 |
+ 0.02 |
+ 3.543 |
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+ UTM RW |
+
+
+ | 134 |
+ R1309H1 |
+ BXD92 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.05 |
+ 1.655 |
+ 66.34 |
+ 0.498 |
+ 0.481 |
+ 0.021 |
+ 1.52 |
+ 0.82 |
+ UTM RW |
+
+
+ | 135 |
+ R2057H1 |
+ BXD93 |
+ 92 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.033 |
+ 44.41 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 1.22 |
+ 0.78 |
+ UTM RW |
+
+
+ | 136 |
+ R2059H1 |
+ BXD93 |
+ 58 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.058 |
+ 60.29 |
+ 0.493 |
+ 0.488 |
+ 0.019 |
+ 1.18 |
+ 1.37 |
+ UTM RW |
+
+
+ | 137 |
+ R2313H1 |
+ BXD94 |
+ 59 |
+ F |
+ 3 |
+ 3 |
+ 0 |
+ 3.091 |
+ 59.45 |
+ 0.487 |
+ 0.495 |
+ 0.018 |
+ 1.34 |
+ 0.73 |
+ UTM RW |
+
+
+ | 138 |
+ R1915H1 |
+ BXD96 |
+ 65 |
+ F |
+ 5 |
+ 2 |
+ 0.04 |
+ 5.145 |
+ 46.19 |
+ 0.502 |
+ 0.481 |
+ 0.017 |
+ 1.37 |
+ 0.74 |
+ UTM RW |
+
+
+ | 139 |
+ R1846H2 |
+ BXD96 |
+ 63 |
+ M |
+ 1 |
+ 3 |
+ 0 |
+ 3.159 |
+ 55.85 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.92 |
+ 1.26 |
+ UTM RW |
+
+
+ | 140 |
+ R2648H1 |
+ BXD97 |
+ 74 |
+ F |
+ 7 |
+ 4 |
+ 0.02 |
+ 1.664 |
+ 82.08 |
+ 0.518 |
+ 0.464 |
+ 0.019 |
+ 1.4 |
+ 0.78 |
+ UTM RW |
+
+
+ | 141 |
+ R1927H2 |
+ BXD97 |
+ 67 |
+ M |
+ 1 |
+ 3 |
+ 0.04 |
+ 2.622 |
+ 57.81 |
+ 0.539 |
+ 0.444 |
+ 0.017 |
+ 1.45 |
+ 1.32 |
+ UTM RW |
+
+
+ | 142 |
+ R1942H1 |
+ BXD98 |
+ 62 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.104 |
+ 48.42 |
+ 0.528 |
+ 0.454 |
+ 0.019 |
+ 2.22 |
+ 1.08 |
+ UTM RW |
+
+
+ | 143 |
+ R1943H2 |
+ BXD98 |
+ 62 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.04 |
+ 56.85 |
+ 0.484 |
+ 0.497 |
+ 0.019 |
+ 1.18 |
+ 0.76 |
+ UTM RW |
+
+
+ | 144 |
+ R2197H1 |
+ BXD99 |
+ 70 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.288 |
+ 51.75 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.35 |
+ 0.81 |
+ UTM RW |
+
+
+ | 145 |
+ R2315H1 |
+ BXD99 |
+ 84 |
+ M |
+ 5 |
+ 2 |
+ 0.03 |
+ 6.036 |
+ 43.05 |
+ 0.484 |
+ 0.497 |
+ 0.018 |
+ 1.7 |
+ 0.96 |
+ UTM RW |
+
+
+ | 146 |
+ R2028H2 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 4.362 |
+ 64.49 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 2.78 |
+ 1.13 |
+ JAX |
+
+
+ | 147 |
+ R2029H2 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.04 |
+ 5.208 |
+ 41.21 |
+ 0.49 |
+ 0.49 |
+ 0.02 |
+ 1.62 |
+ 0.95 |
+ JAX |
+
+
+ | 148 |
+ R2670H1 |
+ A/J |
+ 65 |
+ F |
+ 7 |
+ 3 |
+ 0.04 |
+ 3.951 |
+ 46.8 |
+ 0.498 |
+ 0.485 |
+ 0.017 |
+ 1.32 |
+ 0.75 |
+ UTM RW |
+
+
+ | 149 |
+ R2030H1 |
+ A/J |
+ 57 |
+ M |
+ 5 |
+ 2 |
+ 0.06 |
+ 3.307 |
+ 45.16 |
+ 0.527 |
+ 0.454 |
+ 0.018 |
+ 1.63 |
+ 0.99 |
+ UTM RW |
+
+
+ | 150 |
+ R2032H3 |
+ AKR/J |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.054 |
+ 61.03 |
+ 0.51 |
+ 0.471 |
+ 0.018 |
+ 1.46 |
+ 0.79 |
+ JAX |
+
+
+ | 151 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 152 |
+ R1675H1 |
+ BALB/cByJ |
+ 83 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.405 |
+ 48.13 |
+ 0.509 |
+ 0.474 |
+ 0.018 |
+ 1.13 |
+ 0.78 |
+ JAX |
+
+
+ | 153 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 154 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 155 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 156 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 157 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 158 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 159 |
+ R2673H1 |
+ C57BL/6ByJ |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.08 |
+ 1.842 |
+ 67.69 |
+ 0.514 |
+ 0.469 |
+ 0.017 |
+ 1.75 |
+ 0.78 |
+ JAX |
+
+
+ | 160 |
+ R2619H1 |
+ CAST/EiJ |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 161 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 162 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 163 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 164 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 165 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 166 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 167 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 168 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 169 |
+ R2677H1 |
+ PWD/PhJ |
+ 65 |
+ M |
+ 7 |
+ 2 |
+ 0.12 |
+ 2.764 |
+ 65.49 |
+ 0.462 |
+ 0.52 |
+ 0.018 |
+ 1.89 |
+ 1.16 |
+ UTM RW |
+
+
+ | 170 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 171 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 172 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 173 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 174 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+ | 175 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 176 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 177 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 178 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 179 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 180 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 181 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 182 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 183 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 184 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 185 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 186 |
+ R2676H1 |
+ CXB6 |
+ 47 |
+ F |
+ 7 |
+ 2 |
+ 0.05 |
+ 2.146 |
+ 62.51 |
+ 0.507 |
+ 0.475 |
+ 0.018 |
+ 1.52 |
+ 0.78 |
+ JAX |
+
+
+ | 187 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 188 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 189 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 190 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 191 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 192 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 193 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 194 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 195 |
+ R2671H1 |
+ CXB10 |
+ 53 |
+ M |
+ 7 |
+ 3 |
+ 0.09 |
+ 2.348 |
+ 71.45 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 2.2 |
+ 1.14 |
+ JAX |
+
+
+ | 196 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 197 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 198 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 199 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 200 |
+ R2672H1 |
+ CXB13 |
+ 49 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.722 |
+ 79.52 |
+ 0.516 |
+ 0.465 |
+ 0.019 |
+ 1.64 |
+ 0.75 |
+ JAX |
+
+
+ | 201 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hc_m2cb_1205_p/acknowledgment.rtf b/general/datasets/Hc_m2cb_1205_p/acknowledgment.rtf
new file mode 100644
index 0000000..1481cd1
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_p/acknowledgment.rtf
@@ -0,0 +1,50 @@
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
diff --git a/general/datasets/Hc_m2cb_1205_p/cases.rtf b/general/datasets/Hc_m2cb_1205_p/cases.rtf
new file mode 100644
index 0000000..15e6cda
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_p/cases.rtf
@@ -0,0 +1,56 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 27 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondrial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 strains are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2cb_1205_p/citation.rtf b/general/datasets/Hc_m2cb_1205_p/citation.rtf
new file mode 100644
index 0000000..61a0788
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_p/citation.rtf
@@ -0,0 +1 @@
+Please cite: Overall RW, Kempermann G, Peirce J, Lu L, Goldowitz D, Gage FH, Goodwin S, Smit AB, Airey DC, Rosen GD, Schalkwyk LC, Sutter TR, Nowakowski RS, Whatley S, Williams RW (2009) Genetics of the hippocampal transcriptome in mice: a systematic survey and online neurogenomic resource. Front. Neurogen. 1:3 Full Text HTML doi:10.3389/neuro.15.003.2009
diff --git a/general/datasets/Hc_m2cb_1205_p/contributors.rtf b/general/datasets/Hc_m2cb_1205_p/contributors.rtf
new file mode 100644
index 0000000..4108279
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_p/contributors.rtf
@@ -0,0 +1,46 @@
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
diff --git a/general/datasets/Hc_m2cb_1205_p/experiment-design.rtf b/general/datasets/Hc_m2cb_1205_p/experiment-design.rtf
new file mode 100644
index 0000000..356f1d2
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_p/experiment-design.rtf
@@ -0,0 +1 @@
+Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2cb_1205_p/notes.rtf b/general/datasets/Hc_m2cb_1205_p/notes.rtf
new file mode 100644
index 0000000..9c11719
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_p/notes.rtf
@@ -0,0 +1,12 @@
+This study includes the following datasets:
+
+
+ - Hippocampus Consortium M430v2 CXB (Oct05) MAS5
+ - Hippocampus Consortium M430v2 CXB (Oct05) RMA
+ - Hippocampus Consortium M430v2 CXB (Oct05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) RMA
+ - Hippocampus Consortium M430v2 (Jun06) RMA
+ - Hippocampus Consortium M430v2 (Jun06) MAS5
+ - Hippocampus Consortium M430v2 (Jun06) PDNN
+
diff --git a/general/datasets/Hc_m2cb_1205_p/platform.rtf b/general/datasets/Hc_m2cb_1205_p/platform.rtf
new file mode 100644
index 0000000..6c99bee
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_p/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2cb_1205_p/processing.rtf b/general/datasets/Hc_m2cb_1205_p/processing.rtf
new file mode 100644
index 0000000..3698a7b
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_p/processing.rtf
@@ -0,0 +1,37 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very sensitive to the transformation method that is used. Using the PDNN transform, the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For example, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one would include the sample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the probe level (CEL) data after step 5 below. DataDesk allows the rapid detection of subsets of probes that are particularly sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - We performed a quantile normalization of the log base 2 values for all arrays using the same initial steps used by the RMA transform.
+ - We computed the Z scores for each cell value.
+ - We multiplied all Z scores by 2.
+ - We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level (probe brightness level) corresponds approximately to a 1 unit difference.
+ - Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data from the CHP file: The expression values were generated using PDNN. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1 unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2cb_1205_p/summary.rtf b/general/datasets/Hc_m2cb_1205_p/summary.rtf
new file mode 100644
index 0000000..1e86e54
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_p/summary.rtf
@@ -0,0 +1,3 @@
+MOST HIGHLY RECOMMENDED DATA SET (Overall et al., 2009): The Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of 99 genetically diverse strains of mice including 67 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a diverse set of common inbred strains, and two reciprocal F1 hybrids.
+
+The hippocampus is an important and intriguing part of the forebrain that is crucial in memory formation and retrieval, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section.
diff --git a/general/datasets/Hc_m2cb_1205_p/tissue.rtf b/general/datasets/Hc_m2cb_1205_p/tissue.rtf
new file mode 100644
index 0000000..bcea7b0
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_p/tissue.rtf
@@ -0,0 +1,3721 @@
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thank Muriel Davisson for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below). All animals were sacrifice between 9 AM and 5 PM during the light phase.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+RNA Extraction: In brief, we used the RNA STAT-60 protocol (TEL-TEST "B" Bulletin No. 1), steps 5.1A (homogenization of tissue), 5.2 (RNA extraction), 5.3 (RNA precipitation), and 5.4 (RNA wash). In Step 5.4 we stopped after adding 75% ethanol (1 ml per 1 ml RNA STAT-60) and stored the mix at -80°C until further use. Before RNA labeling we thawed samples and proceeded with the remainder of Step 5.4; pelleting, drying, and redissolving the pellet in RNase-free water.
+
+We finally purify RNA by using Na4OAc before running arrays. Here is the detailed method:
+
+Final RNA purification protocol
+
+
+ - Add 1/10th volume of 3M Na4OAc , pH 5.2. If the sample was eluted with 100 µl nuclease-free water as suggested, this will be 10 µl of 3M Na4OAc.
+ - Add 2.5 volumes of 100% ethanol (250 µl if the RNA was eluted in100 µl). Mix well and incubate at –20°C for 2 hrs.
+ - Centrifuge at speed of 13,000 rpm for 20 min at 4°C. Carefully remove and discard the supernatant.
+ - Wash the pellet with 800 µl 75% cold ethanol, centrifuge at speed of 8,600 rpm for 5 min, and remove the 75% ethanol. Wash again.
+ - To remove the last traces of ethanol, quickly respin the tube, and aspirate any residual fluid.
+ - Air dry the pellet.
+ - Resuspend pellet in nuclease-free water.
+
+
+
+
+5. PROTOCOL: RNA/mRNA isolation by the RNA STAT-60 method includes the following steps:
+1. Homogenization RNA STAT-60TM (1 ml per 50-100 mg tissue, or 5-10 x 10-6 cells)
+2. RNA Extraction 1 vol. of homogenate +0.2 vol. of chloroform
+3. RNA Precipitation 0.5 vol. of isopropanol
+4. RNA Wash 75% ethanol
+
+Unless stated otherwise the procedure is carried out at room temperature.
+
+5.1 HOMOGENIZATION
+
+A. TISSUES: Homogenize tissues samples in the RNA STAT-60(1 ml/50-100mg tissue) in a glass-Teflon or Polytron homogenizer. Sample volume should not exceed 10% of the volume of the RNA STAT-60 used for homogenization.
+
+B. CELLS: Cells grown in mono layer are lysed directly in a culture dish by adding the RNA STAT-60TM (1 ml/3.5 cm petri dish) and passing the cell lysate several times through a pipette. Cells grown in suspension are sediment then lysed in the RNA STAT-60TM (1 ml per 5-10 x 106 cells) by repetitive pipetting. Washing calls before addition of the RNA STAT-60TM should be avoided as this increases the possibility of mRNA degradation.
+
+5.2 RNA EXTRACTION: Following homogenization, store the homogenate for 5 min at room temp to permit the complete dissociation of nucleoprotein complexes. Next, add 0.2 ml of chloroform per 1 ml of the RNA STAT-60, cover the sample tightly, shake vigorously for 15 seconds and let it stay at room temperature for 2-3minutes. Centrifuge the homogenate at 12,000g (max) for 15 minutes at 4°C. Following centrifugation, the homogenate separates into two phases: a lower red phenol chloroform phase and the colorless upper aqueous phase. RNA remains exclusively in the aqueous phase whereas DNA and proteins are in the interferes and organic phase. The volume of the aqueous phase is about 60% of the volume of RNA STAT-60 used for homogenization.
+
+5.3 RNA PRECIPITATION: Transfer the aqueous phase to a fresh tube and mix with isopropanol. Add 0.5 ml of isopropanol per 1 ml of the RNA STAT-60 used for homogenization. Store samples at room temp for 5-10 minutes and centrifuge at 12,000g (max.) for 10 min at 4°C. RNA precipitate (often visible before centrifugation) forms a white pellet at the bottom of the tube.
+
+5.4 RNA WASH: Remove supernatant and wash the RNA pellet once with 75% ethanol by vortexing and subsequent centrifugation at 7,500g (max.) for 5 min at 4°C. Add at least 1 ml of 75% ethanol per 1 ml of the RNA STAT-60 used for the initial homogenization.
+
+At the end of the procedure, dry the RNA pellet briefly by air-drying or in a vacuum (5-10 min.). It is important not to let the RNA pellet dry completely as it will greatly decrease its solubility. Do not use the Speed-Vac for drying. Dissolve the RNA pellet in water or in 1 mm EDTA, pH 7, or 0.5% SDS solution. Vortex or pass the pellet a few times through a pipette tip. An incubation for 10-15 minutes at 55-60oC may be required to dissolve RNA samples. Diethylpyrocarbonate (DEPC) treated RNase-free solutions1 should be used for solubilization of RNA.
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80°C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: Our goal was to obtain a male sample pool and female sample pool from each isogenic group. While almost all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. All but 5 of 99 strains (BXD55, BXD86, BXD94, BALB/cByJ, and CAST/EiJ) are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquots R1291H3 and R1291H4).
+
+
+
+Sex Balance: Based on the expression of Xist, probe set 1427262_at, DBA/2J and KK/HlJ are represented only by female samples, BXD55, and BALB/cByJ are only represented by a single male sample, BXD74 is represented by two male samples, and BXD86, BXD94, and CAST/EiJ are possibly mixed sex samples. One of the BXD9 samples, array R1523, may be a mixed sex sample pool because the expression of Xist is intermediate.
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays. Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4°C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+COMPARISON with December 2005 Data Set: Both BXD14 arrays in the Dec05 data set were found to actually be from BXD23 cases. This error of strain identification has been corrected in the present data set. Four arrays in the Dec05 data set have been deleted because we judged them to be of poor quality (strain_sex_sample_firstreaction_group):
+
+
+ - BXD21_F_1_1_G1
+ - BXD23_M_1_1_G7
+ - BXD36_M_1_1_G2
+ - BXD36_F_1_1_G3
+
+
+In the Dec05 data set there are a total of 1986 transcripts with QTLs that have LRS scores above 50, whereas in the corrected June06 data sets there are a total of 2074 transcripts with QTLs above 50.
+
+Data Table 1:
+
+This table lists all arrays by file order (Index), tube/sample ID, age, sex, batch, and numbers of animals in each sample pool (pool size). The next columns (RMA outlier, scale factor, background average, present, absent, marginal, AFFY-b-ActinMur(3'/5'), AFFY-GapdhMur(3'/5')) are all Affymetrix QC data. Finally, source lists the source colony of the animals. (Final version, fully corrected, by Arthur Centeno, October 2008)
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool size |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 2 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 3 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M technical duplicate of above |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 4 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 5 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
+ F |
+ 5 |
+ 3 |
+ 0.06 |
+ 2.579 |
+ 58.49 |
+ 0.506 |
+ 0.475 |
+ 0.019 |
+ 2.49 |
+ 1.21 |
+ UTM RW |
+
+
+ | 6 |
+ R1551H1 |
+ D2B6F1 |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.62 |
+ 53.76 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 1.37 |
+ 0.76 |
+ UTM RW |
+
+
+ | 7 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
+ 3.058 |
+ 51.87 |
+ 0.477 |
+ 0.503 |
+ 0.02 |
+ 1.67 |
+ 0.76 |
+ UTM RW |
+
+
+ | 8 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
+ 3.341 |
+ 49.26 |
+ 0.527 |
+ 0.456 |
+ 0.018 |
+ 1.14 |
+ 1.45 |
+ UTM RW |
+
+
+ | 9 |
+ R1449H2 |
+ C57BL/6J |
+ 71 |
+ M |
+ 5 |
+ 3 |
+ 0.09 |
+ 3.592 |
+ 44.32 |
+ 0.47 |
+ 0.51 |
+ 0.02 |
+ 1.68 |
+ 0.77 |
+ UTM DG |
+
+
+ | 10 |
+ R1290H2 |
+ DBA/2J |
+ 63 |
+ F |
+ 7 |
+ 2 |
+ 0.04 |
+ 2.576 |
+ 59.6 |
+ 0.513 |
+ 0.468 |
+ 0.018 |
+ 1.3 |
+ 0.78 |
+ JAX |
+
+
+ | 11 |
+ R1468H1 |
+ DBA/2J |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.03 |
+ 2.929 |
+ 53.8 |
+ 0.515 |
+ 0.465 |
+ 0.019 |
+ 1.28 |
+ 0.79 |
+ UTM RW |
+
+
+ | 12 |
+ R1507H1 |
+ BXD1 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.056 |
+ 60.17 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.15 |
+ 0.76 |
+ Glenn |
+
+
+ | 13 |
+ R1542H1 |
+ BXD1 |
+ 59 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.792 |
+ 80.56 |
+ 0.492 |
+ 0.489 |
+ 0.018 |
+ 1.57 |
+ 0.79 |
+ Glenn |
+
+
+ | 14 |
+ R1520H1 |
+ BXD2 |
+ 56 |
+ F |
+ 4 |
+ 4 |
+ 0.09 |
+ 1.715 |
+ 71.62 |
+ 0.515 |
+ 0.467 |
+ 0.018 |
+ 2.36 |
+ 1.6 |
+ Glenn |
+
+
+ | 15 |
+ R1516H1 |
+ BXD2 |
+ 61 |
+ M |
+ 1 |
+ 4 |
+ 0.01 |
+ 2.231 |
+ 64.86 |
+ 0.508 |
+ 0.474 |
+ 0.019 |
+ 1.3 |
+ 1.53 |
+ Glenn |
+
+
+ | 16 |
+ R1593H2 |
+ BXD5 |
+ 60 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 1.913 |
+ 59.96 |
+ 0.487 |
+ 0.493 |
+ 0.02 |
+ 0.98 |
+ 1.44 |
+ Glenn |
+
+
+ | 17 |
+ R1692H1 |
+ BXD5 |
+ 60 |
+ M |
+ 3 |
+ 2 |
+ 0.07 |
+ 3.764 |
+ 72.74 |
+ 0.465 |
+ 0.516 |
+ 0.02 |
+ 1.15 |
+ 0.74 |
+ Glenn |
+
+
+ | 18 |
+ R1539H2 |
+ BXD6 |
+ 59 |
+ F |
+ 1 |
+ 4 |
+ 0 |
+ 2.488 |
+ 54.97 |
+ 0.518 |
+ 0.463 |
+ 0.018 |
+ 1.08 |
+ 1.33 |
+ Glenn |
+
+
+ | 19 |
+ R1538H1 |
+ BXD6 |
+ 59 |
+ M |
+ 4 |
+ 3 |
+ 0.01 |
+ 2.585 |
+ 50.27 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 1.46 |
+ 0.79 |
+ Glenn |
+
+
+ | 20 |
+ R1518H1 |
+ BXD8 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 2.92 |
+ 54.84 |
+ 0.515 |
+ 0.465 |
+ 0.02 |
+ 1.32 |
+ 1.24 |
+ Glenn |
+
+
+ | 21 |
+ R1548H1 |
+ BXD8 |
+ 59 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.132 |
+ 59.37 |
+ 0.504 |
+ 0.477 |
+ 0.019 |
+ 2.16 |
+ 1.54 |
+ Glenn |
+
+
+ | 22 |
+ R1350H2 |
+ BXD9 |
+ 86 |
+ F |
+ 1 |
+ 3 |
+ 0.05 |
+ 2.771 |
+ 60.62 |
+ 0.5 |
+ 0.482 |
+ 0.018 |
+ 1.01 |
+ 1.28 |
+ UMemphis |
+
+
+ | 23 |
+ R1523H3 |
+ BXD9 |
+ 57 |
+ MF (mixed) |
+ 7 |
+ 3 |
+ 0.14 |
+ 3.9 |
+ 78.36 |
+ 0.435 |
+ 0.547 |
+ 0.018 |
+ 1.36 |
+ 0.77 |
+ UTM RW |
+
+
+ | 24 |
+ R1531H1 |
+ BXD11 |
+ 56 |
+ F |
+ 6 |
+ 3 |
+ 0.06 |
+ 2.229 |
+ 56.36 |
+ 0.505 |
+ 0.475 |
+ 0.02 |
+ 2.23 |
+ 1.02 |
+ Glenn |
+
+
+ | 25 |
+ R1367H1 |
+ BXD11 |
+ 56 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.11 |
+ 78.78 |
+ 0.503 |
+ 0.477 |
+ 0.02 |
+ 1.07 |
+ 1.27 |
+ Glenn |
+
+
+ | 26 |
+ R1530H1 |
+ BXD12 |
+ 58 |
+ F |
+ 1 |
+ 3 |
+ 0 |
+ 3.227 |
+ 53.77 |
+ 0.505 |
+ 0.477 |
+ 0.018 |
+ 0.95 |
+ 1.4 |
+ Glenn |
+
+
+ | 27 |
+ R2674H1 |
+ BXD12 |
+ 59 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.924 |
+ 83.44 |
+ 0.519 |
+ 0.464 |
+ 0.018 |
+ 1.21 |
+ 0.78 |
+ Glenn |
+
+
+ | 28 |
+ R1529H1 |
+ BXD13 |
+ 58 |
+ F |
+ 6 |
+ 3 |
+ 0.05 |
+ 2.55 |
+ 59.05 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 2 |
+ 1.54 |
+ Glenn |
+
+
+ | 29 |
+ R1662H2 |
+ BXD13 |
+ 60 |
+ M |
+ 1 |
+ 3 |
+ 0.03 |
+ 4.603 |
+ 45.81 |
+ 0.509 |
+ 0.472 |
+ 0.019 |
+ 1.3 |
+ 0.82 |
+ Glenn |
+
+
+ | 30 |
+ R1304H2 |
+ BXD14 |
+ 72 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.946 |
+ 61.87 |
+ 0.484 |
+ 0.498 |
+ 0.018 |
+ 1.22 |
+ 0.77 |
+ UTM RW |
+
+
+ | 31 |
+ R1278H2 |
+ BXD14 |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.06 |
+ 4.75 |
+ 67.52 |
+ 0.449 |
+ 0.532 |
+ 0.019 |
+ 1.1 |
+ 0.73 |
+ UTM RW |
+
+
+ | 32 |
+ R1524H1 |
+ BXD15 |
+ 60 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.961 |
+ 50.93 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 1.74 |
+ 0.91 |
+ Glenn |
+
+
+ | 33 |
+ R1515H1 |
+ BXD15 |
+ 61 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.316 |
+ 57.05 |
+ 0.503 |
+ 0.478 |
+ 0.019 |
+ 1.32 |
+ 1.21 |
+ Glenn |
+
+
+ | 34 |
+ R1661H1 |
+ BXD16 |
+ 61 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 2.778 |
+ 59.81 |
+ 0.516 |
+ 0.466 |
+ 0.019 |
+ 1.39 |
+ 1.2 |
+ Glenn |
+
+
+ | 35 |
+ R1594H1 |
+ BXD16 |
+ 61 |
+ M |
+ 4 |
+ 3 |
+ 0.03 |
+ 2.634 |
+ 53.66 |
+ 0.504 |
+ 0.478 |
+ 0.018 |
+ 1.96 |
+ 1.51 |
+ Glenn |
+
+
+ | 36 |
+ R2666H1 |
+ BXD19 |
+ 60 |
+ F |
+ 7 |
+ 3 |
+ 0.02 |
+ 2.498 |
+ 76.2 |
+ 0.495 |
+ 0.486 |
+ 0.019 |
+ 1.41 |
+ 0.77 |
+ Glenn |
+
+
+ | 37 |
+ R1471H1 |
+ BXD19 |
+ 157 |
+ M |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.165 |
+ 43.34 |
+ 0.519 |
+ 0.462 |
+ 0.018 |
+ 1.01 |
+ 1.29 |
+ UTM JB |
+
+
+ | 38 |
+ R1573H1 |
+ BXD20 |
+ 59 |
+ F |
+ 1 |
+ 3 |
+ 0.02 |
+ 3.749 |
+ 52.7 |
+ 0.513 |
+ 0.469 |
+ 0.018 |
+ 1.01 |
+ 1.27 |
+ Glenn |
+
+
+ | 39 |
+ R2507H1 |
+ BXD20 |
+ 60 |
+ M |
+ 6 |
+ 3 |
+ 0.06 |
+ 3.568 |
+ 57 |
+ 0.472 |
+ 0.508 |
+ 0.02 |
+ 1.29 |
+ 0.76 |
+ Glenn |
+
+
+ | 40 |
+ R2668H1 |
+ BXD21 |
+ 60 |
+ M |
+ 7 |
+ 4 |
+ 0.07 |
+ 2.605 |
+ 44.9 |
+ 0.535 |
+ 0.449 |
+ 0.017 |
+ 1.54 |
+ 0.76 |
+ Glenn |
+
+
+ | 41 |
+ R1337H2 |
+ BXD21 |
+ 102 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.673 |
+ 58.05 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.4 |
+ 0.76 |
+ UAB |
+
+
+ | 42 |
+ R1848H3 |
+ BXD22 |
+ 196 |
+ F |
+ 6 |
+ 4 |
+ 0.02 |
+ 2.943 |
+ 51.7 |
+ 0.494 |
+ 0.485 |
+ 0.021 |
+ 2.2 |
+ 0.78 |
+ UAB |
+
+
+ | 43 |
+ R1525H1 |
+ BXD22 |
+ 59 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.248 |
+ 55.76 |
+ 0.548 |
+ 0.433 |
+ 0.018 |
+ 1.26 |
+ 0.74 |
+ Glenn |
+
+
+ | 44 |
+ R1280H2 |
+ BXD23 |
+ 56 |
+ F |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.187 |
+ 54.63 |
+ 0.458 |
+ 0.523 |
+ 0.019 |
+ 0.96 |
+ 1.2 |
+ UTM RW |
+
+
+ | 45 |
+ R1537H1 |
+ BXD23 |
+ 58 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.719 |
+ 67.54 |
+ 0.468 |
+ 0.513 |
+ 0.019 |
+ 1.51 |
+ 0.96 |
+ Glenn |
+
+
+ | 46 |
+ R1343H2 |
+ BXD24 |
+ 71 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.083 |
+ 65.07 |
+ 0.506 |
+ 0.474 |
+ 0.019 |
+ 1.46 |
+ 0.75 |
+ UMemphis |
+
+
+ | 47 |
+ R1517H1 |
+ BXD24 |
+ 57 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.471 |
+ 53.66 |
+ 0.504 |
+ 0.476 |
+ 0.019 |
+ 1.28 |
+ 0.78 |
+ Glenn |
+
+
+ | 48 |
+ R1366H1 |
+ BXD27 |
+ 60 |
+ F |
+ 2 |
+ 4 |
+ 0 |
+ 2.26 |
+ 48.46 |
+ 0.518 |
+ 0.463 |
+ 0.019 |
+ 1.29 |
+ 0.77 |
+ Glenn |
+
+
+ | 49 |
+ R1849H1 |
+ BXD27 |
+ 70 |
+ M |
+ 5 |
+ 3 |
+ 0.06 |
+ 8.801 |
+ 38.34 |
+ 0.468 |
+ 0.512 |
+ 0.019 |
+ 2.42 |
+ 1.08 |
+ UAB |
+
+
+ | 50 |
+ R1353H1 |
+ BXD28 |
+ 79 |
+ F |
+ 3 |
+ 4 |
+ 0.01 |
+ 3.22 |
+ 76.22 |
+ 0.48 |
+ 0.5 |
+ 0.02 |
+ 1.33 |
+ 0.78 |
+ UMemphis |
+
+
+ | 51 |
+ R2332H1 |
+ BXD28 |
+ 60 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 3.217 |
+ 63.68 |
+ 0.491 |
+ 0.49 |
+ 0.019 |
+ 1.37 |
+ 0.79 |
+ Glenn |
+
+
+ | 52 |
+ R1532H1 |
+ BXD29 |
+ 57 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.122 |
+ 59.18 |
+ 0.524 |
+ 0.456 |
+ 0.019 |
+ 1.17 |
+ 0.76 |
+ Glenn |
+
+
+ | 53 |
+ R1356H1 |
+ BXD29 |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.01 |
+ 4.033 |
+ 47.67 |
+ 0.52 |
+ 0.463 |
+ 0.017 |
+ 1.17 |
+ 0.78 |
+ UMemphis |
+
+
+ | 54 |
+ R1240H2 |
+ BXD31 |
+ 61 |
+ M |
+ 2 |
+ 3 |
+ 0.02 |
+ 2.335 |
+ 65.17 |
+ 0.507 |
+ 0.474 |
+ 0.019 |
+ 1.31 |
+ 0.78 |
+ UTM RW |
+
+
+ | 55 |
+ R1526H2 |
+ BXD31 |
+ 57 |
+ F |
+ 7 |
+ 4 |
+ 0.1 |
+ 7.267 |
+ 89.54 |
+ 0.435 |
+ 0.547 |
+ 0.017 |
+ 1.35 |
+ 0.78 |
+ UTM RW |
+
+
+ | 56 |
+ R2675H1 |
+ BXD32 |
+ 57 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 2.268 |
+ 78.01 |
+ 0.502 |
+ 0.478 |
+ 0.02 |
+ 1.22 |
+ 0.78 |
+ Glenn |
+
+
+ | 57 |
+ R1508H2 |
+ BXD32 |
+ 58 |
+ M |
+ 2 |
+ 4 |
+ 0.01 |
+ 1.917 |
+ 67.78 |
+ 0.539 |
+ 0.442 |
+ 0.019 |
+ 1.28 |
+ 0.73 |
+ Glenn |
+
+
+ | 58 |
+ R1345H3 |
+ BXD33 |
+ 65 |
+ F |
+ 2 |
+ 2 |
+ 0.01 |
+ 2.098 |
+ 63.14 |
+ 0.522 |
+ 0.459 |
+ 0.019 |
+ 1.27 |
+ 0.73 |
+ UMemphis |
+
+
+ | 59 |
+ R1581H1 |
+ BXD33 |
+ 59 |
+ M |
+ 3 |
+ 3 |
+ 0.01 |
+ 3.229 |
+ 53.16 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.19 |
+ 0.78 |
+ Glenn |
+
+
+ | 60 |
+ R1527H1 |
+ BXD34 |
+ 59 |
+ F |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.3 |
+ 58.92 |
+ 0.51 |
+ 0.471 |
+ 0.019 |
+ 1.24 |
+ 0.76 |
+ Glenn |
+
+
+ | 61 |
+ R1339H3 |
+ BXD34 |
+ 74 |
+ M |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.888 |
+ 53.49 |
+ 0.506 |
+ 0.476 |
+ 0.018 |
+ 2.39 |
+ 1.35 |
+ UMemphis |
+
+
+ | 62 |
+ R1855H1 |
+ BXD38 |
+ 55 |
+ F |
+ 3 |
+ 4 |
+ 0.01 |
+ 3.536 |
+ 54.54 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.39 |
+ 0.75 |
+ Glenn |
+
+
+ | 63 |
+ R1510H1 |
+ BXD38 |
+ 59 |
+ M |
+ 2 |
+ 3 |
+ 0.01 |
+ 2.186 |
+ 68.06 |
+ 0.521 |
+ 0.46 |
+ 0.019 |
+ 1.26 |
+ 0.79 |
+ Glenn |
+
+
+ | 64 |
+ R1528H2 |
+ BXD39 |
+ 59 |
+ F |
+ 2 |
+ 3 |
+ 0.03 |
+ 4.717 |
+ 38.3 |
+ 0.511 |
+ 0.47 |
+ 0.02 |
+ 1.12 |
+ 0.75 |
+ Glenn |
+
+
+ | 65 |
+ R1514H1 |
+ BXD39 |
+ 59 |
+ M |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.992 |
+ 56.06 |
+ 0.477 |
+ 0.504 |
+ 0.019 |
+ 1.43 |
+ 0.81 |
+ Glenn |
+
+
+ | 66 |
+ R1522H1 |
+ BXD40 |
+ 59 |
+ F |
+ 4 |
+ 4 |
+ 0 |
+ 2.631 |
+ 67.16 |
+ 0.49 |
+ 0.491 |
+ 0.018 |
+ 1.56 |
+ 0.77 |
+ Glenn |
+
+
+ | 67 |
+ R1359H1 |
+ BXD40 |
+ 73 |
+ M |
+ 2 |
+ 3 |
+ 0.09 |
+ 7.458 |
+ 39.86 |
+ 0.451 |
+ 0.527 |
+ 0.021 |
+ 1.28 |
+ 0.74 |
+ UMemphis |
+
+
+ | 68 |
+ R1541H2 |
+ BXD42 |
+ 58 |
+ F |
+ 7 |
+ 3 |
+ 0.07 |
+ 6.784 |
+ 52.12 |
+ 0.483 |
+ 0.499 |
+ 0.017 |
+ 1.13 |
+ 0.66 |
+ Glenn |
+
+
+ | 69 |
+ R1540H1 |
+ BXD42 |
+ 58 |
+ M |
+ 7 |
+ 4 |
+ 0.03 |
+ 2.423 |
+ 75.14 |
+ 0.492 |
+ 0.488 |
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+
+
+ | 70 |
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+ 59 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 71 |
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+ 63 |
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+ 3 |
+ 4 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 72 |
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+ 65 |
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+ 3 |
+ 4 |
+ 0 |
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+ UTM RW |
+
+
+ | 73 |
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+ 56 |
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+ 1 |
+ 3 |
+ 0.02 |
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+
+
+ | 74 |
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+ 7 |
+ 2 |
+ 0.03 |
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+
+
+ | 75 |
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+ 65 |
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+ 7 |
+ 4 |
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+
+
+ | 76 |
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+ 58 |
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+ 4 |
+ 3 |
+ 0 |
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+
+
+ | 77 |
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+ 65 |
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+ 3 |
+ 4 |
+ 0.05 |
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+
+
+ | 78 |
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+ 63 |
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+ 6 |
+ 4 |
+ 0.01 |
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+
+
+ | 79 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 80 |
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+ 66 |
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+ 3 |
+ 3 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 81 |
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+ 71 |
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+ 6 |
+ 4 |
+ 0.03 |
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+
+
+ | 82 |
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+ 7 |
+ 3 |
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+
+
+ | 83 |
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+ 4 |
+ 3 |
+ 0.01 |
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+
+
+ | 84 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 85 |
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+ 7 |
+ 4 |
+ 0.03 |
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+
+
+ | 86 |
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+ 1 |
+ 2 |
+ 0 |
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+
+
+ | 87 |
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+ 1 |
+ 4 |
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+
+
+ | 88 |
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+ 6 |
+ 4 |
+ 0.01 |
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+
+
+ | 89 |
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+ 1 |
+ 3 |
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+
+
+ | 90 |
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+ 6 |
+ 3 |
+ 0.02 |
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+
+
+ | 91 |
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+ 1 |
+ 3 |
+ 0.05 |
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+
+
+ | 92 |
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+ 3 |
+ 4 |
+ 0.01 |
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+
+
+ | 93 |
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+ 1 |
+ 2 |
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+
+
+ | 94 |
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+ 6 |
+ 2 |
+ 0 |
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+
+
+ | 95 |
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+ 1 |
+ 4 |
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+
+
+ | 96 |
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+ 4 |
+ 2 |
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+
+
+ | 97 |
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+ 6 |
+ 3 |
+ 0.01 |
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+
+
+ | 98 |
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+ 1 |
+ 4 |
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+
+
+ | 99 |
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+ 3 |
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+
+
+ | 100 |
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+ 2 |
+ 2 |
+ 0.01 |
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+
+
+ | 101 |
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+ 3 |
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+
+
+ | 102 |
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+ 3 |
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+
+
+ | 103 |
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+ 2 |
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+
+
+ | 104 |
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+
+
+ | 105 |
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+ 2 |
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+
+
+ | 106 |
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+ 3 |
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+
+
+ | 107 |
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+
+
+ | 108 |
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+
+
+ | 109 |
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+
+
+ | 110 |
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+
+
+ | 111 |
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+
+
+ | 112 |
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+
+
+ | 113 |
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+
+
+ | 114 |
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+
+
+ | 115 |
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+ 2 |
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+
+
+ | 116 |
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+
+
+ | 117 |
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+
+
+ | 118 |
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+
+
+ | 119 |
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+
+
+ | 120 |
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+
+
+ | 121 |
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+ 2 |
+ 0 |
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+
+
+ | 122 |
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+ 2 |
+ 0.01 |
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+
+
+ | 123 |
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+ 3 |
+ 0.02 |
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+
+
+ | 124 |
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+ 3 |
+ 0.01 |
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+
+
+ | 125 |
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+ 4 |
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+
+
+ | 126 |
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+ 3 |
+ 0.02 |
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+
+
+ | 127 |
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+ 3 |
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+
+
+ | 128 |
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+ 4 |
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+
+
+ | 129 |
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+ 2 |
+ 0.02 |
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+
+
+ | 130 |
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+ 4 |
+ 0.03 |
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+
+
+ | 131 |
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+ 3 |
+ 0.01 |
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+
+
+ | 132 |
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+ 4 |
+ 0.03 |
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+
+
+ | 133 |
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+ 3 |
+ 0.02 |
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+
+
+ | 134 |
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+ 3 |
+ 0.05 |
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+
+
+ | 135 |
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+ 3 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 136 |
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+ 1 |
+ 3 |
+ 0 |
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+ UTM RW |
+
+
+ | 137 |
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+ 3 |
+ 0 |
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+ UTM RW |
+
+
+ | 138 |
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+ 2 |
+ 0.04 |
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+ UTM RW |
+
+
+ | 139 |
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+ 1 |
+ 3 |
+ 0 |
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+ UTM RW |
+
+
+ | 140 |
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+ 4 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 141 |
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+ 1 |
+ 3 |
+ 0.04 |
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+ UTM RW |
+
+
+ | 142 |
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+ 3 |
+ 0.04 |
+ 3.104 |
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+ 0.528 |
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+ 2.22 |
+ 1.08 |
+ UTM RW |
+
+
+ | 143 |
+ R1943H2 |
+ BXD98 |
+ 62 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.04 |
+ 56.85 |
+ 0.484 |
+ 0.497 |
+ 0.019 |
+ 1.18 |
+ 0.76 |
+ UTM RW |
+
+
+ | 144 |
+ R2197H1 |
+ BXD99 |
+ 70 |
+ F |
+ 3 |
+ 3 |
+ 0.02 |
+ 4.288 |
+ 51.75 |
+ 0.49 |
+ 0.492 |
+ 0.018 |
+ 1.35 |
+ 0.81 |
+ UTM RW |
+
+
+ | 145 |
+ R2315H1 |
+ BXD99 |
+ 84 |
+ M |
+ 5 |
+ 2 |
+ 0.03 |
+ 6.036 |
+ 43.05 |
+ 0.484 |
+ 0.497 |
+ 0.018 |
+ 1.7 |
+ 0.96 |
+ UTM RW |
+
+
+ | 146 |
+ R2028H2 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.1 |
+ 4.362 |
+ 64.49 |
+ 0.497 |
+ 0.484 |
+ 0.019 |
+ 2.78 |
+ 1.13 |
+ JAX |
+
+
+ | 147 |
+ R2029H2 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+ 6 |
+ 3 |
+ 0.04 |
+ 5.208 |
+ 41.21 |
+ 0.49 |
+ 0.49 |
+ 0.02 |
+ 1.62 |
+ 0.95 |
+ JAX |
+
+
+ | 148 |
+ R2670H1 |
+ A/J |
+ 65 |
+ F |
+ 7 |
+ 3 |
+ 0.04 |
+ 3.951 |
+ 46.8 |
+ 0.498 |
+ 0.485 |
+ 0.017 |
+ 1.32 |
+ 0.75 |
+ UTM RW |
+
+
+ | 149 |
+ R2030H1 |
+ A/J |
+ 57 |
+ M |
+ 5 |
+ 2 |
+ 0.06 |
+ 3.307 |
+ 45.16 |
+ 0.527 |
+ 0.454 |
+ 0.018 |
+ 1.63 |
+ 0.99 |
+ UTM RW |
+
+
+ | 150 |
+ R2032H3 |
+ AKR/J |
+ 66 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.054 |
+ 61.03 |
+ 0.51 |
+ 0.471 |
+ 0.018 |
+ 1.46 |
+ 0.79 |
+ JAX |
+
+
+ | 151 |
+ R2454H1 |
+ AKR/J |
+ 66 |
+ M |
+ 6 |
+ 4 |
+ 0.11 |
+ 2.892 |
+ 58.55 |
+ 0.474 |
+ 0.507 |
+ 0.019 |
+ 1.99 |
+ 0.78 |
+ JAX |
+
+
+ | 152 |
+ R1675H1 |
+ BALB/cByJ |
+ 83 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.405 |
+ 48.13 |
+ 0.509 |
+ 0.474 |
+ 0.018 |
+ 1.13 |
+ 0.78 |
+ JAX |
+
+
+ | 153 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 154 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 155 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 156 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 157 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 158 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 159 |
+ R2673H1 |
+ C57BL/6ByJ |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.08 |
+ 1.842 |
+ 67.69 |
+ 0.514 |
+ 0.469 |
+ 0.017 |
+ 1.75 |
+ 0.78 |
+ JAX |
+
+
+ | 160 |
+ R2619H1 |
+ CAST/EiJ |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 161 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 162 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 163 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 164 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 165 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 166 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 167 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 168 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 169 |
+ R2677H1 |
+ PWD/PhJ |
+ 65 |
+ M |
+ 7 |
+ 2 |
+ 0.12 |
+ 2.764 |
+ 65.49 |
+ 0.462 |
+ 0.52 |
+ 0.018 |
+ 1.89 |
+ 1.16 |
+ UTM RW |
+
+
+ | 170 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 171 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 172 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 173 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 174 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+ | 175 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 176 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 177 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 178 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 179 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 180 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 181 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 182 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 183 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 184 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 185 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 186 |
+ R2676H1 |
+ CXB6 |
+ 47 |
+ F |
+ 7 |
+ 2 |
+ 0.05 |
+ 2.146 |
+ 62.51 |
+ 0.507 |
+ 0.475 |
+ 0.018 |
+ 1.52 |
+ 0.78 |
+ JAX |
+
+
+ | 187 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 188 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 189 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 190 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 191 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 192 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 193 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 194 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 195 |
+ R2671H1 |
+ CXB10 |
+ 53 |
+ M |
+ 7 |
+ 3 |
+ 0.09 |
+ 2.348 |
+ 71.45 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 2.2 |
+ 1.14 |
+ JAX |
+
+
+ | 196 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 197 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 198 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 199 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 200 |
+ R2672H1 |
+ CXB13 |
+ 49 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.722 |
+ 79.52 |
+ 0.516 |
+ 0.465 |
+ 0.019 |
+ 1.64 |
+ 0.75 |
+ JAX |
+
+
+ | 201 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hc_m2cb_1205_r/acknowledgment.rtf b/general/datasets/Hc_m2cb_1205_r/acknowledgment.rtf
new file mode 100644
index 0000000..1481cd1
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_r/acknowledgment.rtf
@@ -0,0 +1,50 @@
+Data were generated with funds provided by a variety of public and private source to members of the Consortium. All of us thank Muriel Davisson, Cathy Lutz, and colleagues at the Jackson Laboratory for making it possible for us to add all of the CXB strains, and one or more samples from KK/HIJ, WSB/Ei, NZO/HILtJ, LG/J, CAST/Ei, PWD/PhJ, and PWK/PhJ to this study. We thank Yan Cui at UTHSC for allowing us to use his Linux cluster to align all M430 2.0 probes and probe sets to the mouse genome. We thank Hui-Chen Hsu and John Mountz for providing us BXD tissue samples, as well as many strains of BXD stock. We thanks Douglas Matthews (UMem in Table 1) and John Boughter (JBo in Table 1) for sharing BXD stock with us. Members of the Hippocampus Consortium thank the following sources for financial support of this effort:
+
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
diff --git a/general/datasets/Hc_m2cb_1205_r/cases.rtf b/general/datasets/Hc_m2cb_1205_r/cases.rtf
new file mode 100644
index 0000000..15e6cda
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_r/cases.rtf
@@ -0,0 +1,56 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 27 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 39 inbred (25 strains at F20+) and nearly inbred (14 strains between F14 and F20) BXD lines generated by Lu and Peirce. All of these strains, including those between F14 and F20, have been genotyped at 13,377 SNPs.
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 16 inbred strains and a pair of reciprocal F1 hybrids; B6D2F1 and D2B6F1. These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1 and D2B6F1
+ F1 hybrids generated by crossing C57BL/6J with DBA/2J
+
+
+We have not combined data from reciprocal F1s because they have different Y chromosome and mitochondrial haplotypes. Parent-of-origin effects (imprinting, maternal environment) may also lead to interesting differences in hippocampal transcript levels.
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 strains are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hc_m2cb_1205_r/citation.rtf b/general/datasets/Hc_m2cb_1205_r/citation.rtf
new file mode 100644
index 0000000..61a0788
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_r/citation.rtf
@@ -0,0 +1 @@
+Please cite: Overall RW, Kempermann G, Peirce J, Lu L, Goldowitz D, Gage FH, Goodwin S, Smit AB, Airey DC, Rosen GD, Schalkwyk LC, Sutter TR, Nowakowski RS, Whatley S, Williams RW (2009) Genetics of the hippocampal transcriptome in mice: a systematic survey and online neurogenomic resource. Front. Neurogen. 1:3 Full Text HTML doi:10.3389/neuro.15.003.2009
diff --git a/general/datasets/Hc_m2cb_1205_r/contributors.rtf b/general/datasets/Hc_m2cb_1205_r/contributors.rtf
new file mode 100644
index 0000000..4108279
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_r/contributors.rtf
@@ -0,0 +1,46 @@
+
+ - David C. Airey, Ph.D.
+ Grant Support: Vanderbilt Institute for Integratie Genomics
+ Department of Pharmacology
+ david.airey at vanderbilt.edu
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Fred H. Gage, Ph.D.
+ Grant Support: Lookout Foundation
+ - Dan Goldowitz, Ph.D.
+ Grant Support: NIAAA INIA AA013503
+ University of Tennessee Health Science Center
+ Dept. Anatomy and Neurobiology
+ email: dgold@nb.utmem.edu
+ - Shirlean Goodwin, Ph.D.
+ Grant Support: NIAAA INIA U01AA013515
+ - Gerd Kempermann, M.D.
+ Grant Support: The Volkswagen Foundation Grant on Permissive and Persistent Factors in Neurogenesis in the Adult Central Nervous System
+ Humboldt-Universitat Berlin
+ Universitatsklinikum Charite
+ email: gerd.kempermann at mdc-berlin.de
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Richard S. Nowakowski, Ph.D.
+ Grant Support: R01 NS049445-01
+ - Glenn D. Rosen, Ph.D.
+ Grant Support: NIH P20
+ - Leonard C. Schalkwyk, Ph.D.
+ Grant Support: MRC Career Establishment Grant G0000170
+ Social, Genetic and Developmental Psychiatry
+ Institute of Psychiatry,Kings College London
+ PO82, De Crespigny Park London SE5 8AF
+ L.Schalkwyk@iop.kcl.ac.uk
+ - Guus Smit, Ph.D.
+ Dutch NeuroBsik Mouse Phenomics Consortium
+ Center for Neurogenomics & Cognitive Research
+ Vrije Universiteit Amsterdam, The Netherlands
+ e-mail: guus.smit at falw.vu.nl
+ Grant Support: BSIK 03053
+ - Thomas Sutter, Ph.D.
+ Grant Support: INIA U01 AA13515 and the W. Harry Feinstone Center for Genome Research
+ - Stephen Whatley, Ph.D.
+ Grant Support: XXXX
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
diff --git a/general/datasets/Hc_m2cb_1205_r/experiment-design.rtf b/general/datasets/Hc_m2cb_1205_r/experiment-design.rtf
new file mode 100644
index 0000000..356f1d2
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_r/experiment-design.rtf
@@ -0,0 +1 @@
+Pooled RNA samples (usually one pool of male hippocampii and one pool of female hippocampii) were prepared using standard protocols. Samples were processed using a total of 206 Affymetrix GeneChip Mouse Expression 430 2.0 short oligomer arrays (MOE430 2.0 or M430v2; see GEO platform ID GPL1261), of which 201 passed quality control and error checking. This particular data set was processed using the PDNN protocol. To simplify comparisons among transforms, PDNN values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Hc_m2cb_1205_r/notes.rtf b/general/datasets/Hc_m2cb_1205_r/notes.rtf
new file mode 100644
index 0000000..9c11719
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_r/notes.rtf
@@ -0,0 +1,12 @@
+This study includes the following datasets:
+
+
+ - Hippocampus Consortium M430v2 CXB (Oct05) MAS5
+ - Hippocampus Consortium M430v2 CXB (Oct05) RMA
+ - Hippocampus Consortium M430v2 CXB (Oct05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) PDNN
+ - Hippocampus Consortium M430v2 CXB (Dec05) RMA
+ - Hippocampus Consortium M430v2 (Jun06) RMA
+ - Hippocampus Consortium M430v2 (Jun06) MAS5
+ - Hippocampus Consortium M430v2 (Jun06) PDNN
+
diff --git a/general/datasets/Hc_m2cb_1205_r/platform.rtf b/general/datasets/Hc_m2cb_1205_r/platform.rtf
new file mode 100644
index 0000000..6c99bee
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_r/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
diff --git a/general/datasets/Hc_m2cb_1205_r/processing.rtf b/general/datasets/Hc_m2cb_1205_r/processing.rtf
new file mode 100644
index 0000000..3698a7b
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_r/processing.rtf
@@ -0,0 +1,37 @@
+Harshlight was used to examine the image quality of the array (CEL files). Bad areas (bubbles, scratches, blemishes) of arrays were masked.
+
+First pass data quality control: Affymetrix GCOS provides useful array quality control data including:
+
+
+ - The scale factor used to normalize mean probe intensity. This averaged 3.3 for the 179 arrays that passed and 6.2 for arrays that were excluded. The scale factor is not a particular critical parameter.
+ - The average background level. Values averaged 54.8 units for the data sets that passed and 55.8 for data sets that were excluded. This factor is not important for quality control.
+ - The percentage of probe sets that are associated with good signal ("present" calls). This averaged 50% for the 179 data sets that passed and 42% for those that failed. Values for passing data sets extended from 43% to 55%. This is a particularly important criterion.
+ - The 3':5' signal ratios of actin and Gapdh. Values for passing data sets averaged 1.5 for actin and 1.0 for Gapdh. Values for excluded data sets averaged 12.9 for actin and 9.6 for Gapdh. This is a highly discriminative QC criterion, although one must keep in mind that only two transcripts are being tested. Sequence variation among strains (particularly wild derivative strains such as CAST/Ei) may affect these ratios.
+
+
+The second step in our post-processing QC involves a count of the number of probe sets in each array that are more than 2 standard deviations (z score units) from the mean across the entire 206 array data sets. This was the most important criterion used to eliminate "bad" data sets. All 206 arrays were processed togther using standard RMA and PDNN methods. The count and percentage of probe sets in each array that were beyond the 2 z theshold was computed. Using the RMA transform the average percentage of probe sets beyond the 2 z threshold for the 179 arrays that finally passed of QC procedure was 1.76% (median of 1.18%). In contrast the 2 z percentage was more than 10-fold higher (mean of 22.4% and median 20.2%) for those arrays that were excluded. This method is not very sensitive to the transformation method that is used. Using the PDNN transform, the average percent of probe sets exceeding was 1.31% for good arrays and was 22.6% for those that were excluded. In our opinion, this 2 z criterion is the most useful criterion for the final decision of whether or not to include arrays, although again, allowances need to be made for wild strains that one expects to be different from the majority of conventional inbred strains. For example, if a data set has excellent characteristics on all of the Affymetrix GCOS metrics listed above, but generates a high 2 z percentage, then one would include the sample if one can verify that there are no problems in sample and data set identification.
+
+The entire procedure can be reapplied once the initial outlier data sets have been eliminated to detect any remaining outlier data sets.
+
+DataDesk was used to examine the statistical quality of the probe level (CEL) data after step 5 below. DataDesk allows the rapid detection of subsets of probes that are particularly sensitive to still unknown factors in array processing. Arrays can then be categorized at the probe level into "reaction classes." A reaction class is a group of arrays for which the expression of essentially all probes are colinear over the full range of log2 values. A single but large group of arrays (n = 32) processed in essentially the identical manner by a single operator can produce arrays belonging to as many as four different reaction classes. Reaction classes are NOT related to strain, age, sex, treatment, or any known biological parameter (technical replicates can belong to different reaction classes). We do not yet understand the technical origins of reaction classes. The number of probes that contribute to the definition of reaction classes is quite small (<10% of all probes). We have categorized all arrays in this data set into one of 5 reaction classes. These have then been treated as if they were separate batches. Probes in these data type "batches" have been aligned to a common mean as described below.
+
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - We performed a quantile normalization of the log base 2 values for all arrays using the same initial steps used by the RMA transform.
+ - We computed the Z scores for each cell value.
+ - We multiplied all Z scores by 2.
+ - We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level (probe brightness level) corresponds approximately to a 1 unit difference.
+ - Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data from the CHP file: The expression values were generated using PDNN. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1 unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients. XY plots of probe expression and signal variance were also examined. Probe level array data sets were organized into reaction groups. Arrays with probe data that were not homogeneous when compared to other arrays were flagged.
+
+Probe set level QC: The final normalized individual array data were evaluated for outliers. This involved counting the number of times that the probe set value for a particular array was beyond two standard deviations of the mean. This outlier analysis was carried out using the PDNN, RMA and MAS5 transforms and outliers across different levels of expression. Arrays that were associated with an average of more than 8% outlier probe sets across all transforms and at all expression levels were eliminated. In contrast, most other arrays generated fewer than 5% outliers.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
diff --git a/general/datasets/Hc_m2cb_1205_r/summary.rtf b/general/datasets/Hc_m2cb_1205_r/summary.rtf
new file mode 100644
index 0000000..1e86e54
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_r/summary.rtf
@@ -0,0 +1,3 @@
+MOST HIGHLY RECOMMENDED DATA SET (Overall et al., 2009): The Hippocampus Consortium data set provides estimates of mRNA expression in the adult hippocampus of 99 genetically diverse strains of mice including 67 BXD recombinant inbred strains, 13 CXB recombinant inbred strains, a diverse set of common inbred strains, and two reciprocal F1 hybrids.
+
+The hippocampus is an important and intriguing part of the forebrain that is crucial in memory formation and retrieval, and that is often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3) is a joint effort of 14 investigators that is supported by numerous agencies described in the acknowledgments section.
diff --git a/general/datasets/Hc_m2cb_1205_r/tissue.rtf b/general/datasets/Hc_m2cb_1205_r/tissue.rtf
new file mode 100644
index 0000000..bcea7b0
--- /dev/null
+++ b/general/datasets/Hc_m2cb_1205_r/tissue.rtf
@@ -0,0 +1,3721 @@
+BXD animals were obtained from UTHSC, UAB, or directly from The Jackson Laboratory (see Table 1 below). Animals were housed at UTHSC, Beth Israel Deaconess, or the Jackson Laboratory before sacrifice. Virtually all CXB animals were obtained directly at the Jackson Laboratory by Lu Lu. We thank Muriel Davisson for making it possible to collect these cases on site. Standard inbred strain stock was from The Jackson Laboratory, but most animals were housed or reared at UTHSC. Mice were killed by cervical dislocation and brains were removed and placed in RNAlater prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both hippocampi were dissected whole by Hong Tao Zhang in the Lu lab. Hippocampal samples are very close to complete (see Lu et al., 2001) but probably include variable amounts of subiculum and fimbria.
+
+A great majority of animals used in this study were between 45 and 90 days of age (average of 66 days, maximum range from 41 to 196 days; see Table 1 below). All animals were sacrifice between 9 AM and 5 PM during the light phase.
+
+A pool of dissected tissue typically from six hippocampi and three naive adults of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Two-hundred and one RNA samples were extracted at UTHSC by Zhiping Jia, four samples by Shuhua Qi (R2331H1, R2332H1, P2350H1, R2349H1), and one by Siming Shou (R0129H2).
+
+RNA Extraction: In brief, we used the RNA STAT-60 protocol (TEL-TEST "B" Bulletin No. 1), steps 5.1A (homogenization of tissue), 5.2 (RNA extraction), 5.3 (RNA precipitation), and 5.4 (RNA wash). In Step 5.4 we stopped after adding 75% ethanol (1 ml per 1 ml RNA STAT-60) and stored the mix at -80°C until further use. Before RNA labeling we thawed samples and proceeded with the remainder of Step 5.4; pelleting, drying, and redissolving the pellet in RNase-free water.
+
+We finally purify RNA by using Na4OAc before running arrays. Here is the detailed method:
+
+Final RNA purification protocol
+
+
+ - Add 1/10th volume of 3M Na4OAc , pH 5.2. If the sample was eluted with 100 µl nuclease-free water as suggested, this will be 10 µl of 3M Na4OAc.
+ - Add 2.5 volumes of 100% ethanol (250 µl if the RNA was eluted in100 µl). Mix well and incubate at –20°C for 2 hrs.
+ - Centrifuge at speed of 13,000 rpm for 20 min at 4°C. Carefully remove and discard the supernatant.
+ - Wash the pellet with 800 µl 75% cold ethanol, centrifuge at speed of 8,600 rpm for 5 min, and remove the 75% ethanol. Wash again.
+ - To remove the last traces of ethanol, quickly respin the tube, and aspirate any residual fluid.
+ - Air dry the pellet.
+ - Resuspend pellet in nuclease-free water.
+
+
+
+
+5. PROTOCOL: RNA/mRNA isolation by the RNA STAT-60 method includes the following steps:
+1. Homogenization RNA STAT-60TM (1 ml per 50-100 mg tissue, or 5-10 x 10-6 cells)
+2. RNA Extraction 1 vol. of homogenate +0.2 vol. of chloroform
+3. RNA Precipitation 0.5 vol. of isopropanol
+4. RNA Wash 75% ethanol
+
+Unless stated otherwise the procedure is carried out at room temperature.
+
+5.1 HOMOGENIZATION
+
+A. TISSUES: Homogenize tissues samples in the RNA STAT-60(1 ml/50-100mg tissue) in a glass-Teflon or Polytron homogenizer. Sample volume should not exceed 10% of the volume of the RNA STAT-60 used for homogenization.
+
+B. CELLS: Cells grown in mono layer are lysed directly in a culture dish by adding the RNA STAT-60TM (1 ml/3.5 cm petri dish) and passing the cell lysate several times through a pipette. Cells grown in suspension are sediment then lysed in the RNA STAT-60TM (1 ml per 5-10 x 106 cells) by repetitive pipetting. Washing calls before addition of the RNA STAT-60TM should be avoided as this increases the possibility of mRNA degradation.
+
+5.2 RNA EXTRACTION: Following homogenization, store the homogenate for 5 min at room temp to permit the complete dissociation of nucleoprotein complexes. Next, add 0.2 ml of chloroform per 1 ml of the RNA STAT-60, cover the sample tightly, shake vigorously for 15 seconds and let it stay at room temperature for 2-3minutes. Centrifuge the homogenate at 12,000g (max) for 15 minutes at 4°C. Following centrifugation, the homogenate separates into two phases: a lower red phenol chloroform phase and the colorless upper aqueous phase. RNA remains exclusively in the aqueous phase whereas DNA and proteins are in the interferes and organic phase. The volume of the aqueous phase is about 60% of the volume of RNA STAT-60 used for homogenization.
+
+5.3 RNA PRECIPITATION: Transfer the aqueous phase to a fresh tube and mix with isopropanol. Add 0.5 ml of isopropanol per 1 ml of the RNA STAT-60 used for homogenization. Store samples at room temp for 5-10 minutes and centrifuge at 12,000g (max.) for 10 min at 4°C. RNA precipitate (often visible before centrifugation) forms a white pellet at the bottom of the tube.
+
+5.4 RNA WASH: Remove supernatant and wash the RNA pellet once with 75% ethanol by vortexing and subsequent centrifugation at 7,500g (max.) for 5 min at 4°C. Add at least 1 ml of 75% ethanol per 1 ml of the RNA STAT-60 used for the initial homogenization.
+
+At the end of the procedure, dry the RNA pellet briefly by air-drying or in a vacuum (5-10 min.). It is important not to let the RNA pellet dry completely as it will greatly decrease its solubility. Do not use the Speed-Vac for drying. Dissolve the RNA pellet in water or in 1 mm EDTA, pH 7, or 0.5% SDS solution. Vortex or pass the pellet a few times through a pipette tip. An incubation for 10-15 minutes at 55-60oC may be required to dissolve RNA samples. Diethylpyrocarbonate (DEPC) treated RNase-free solutions1 should be used for solubilization of RNA.
+
+Sample Processing: Samples were processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center for Genomic Research, The University of Memphis, led by Thomas R. Sutter. All processing steps were performed by Shirlean Goodwin. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8. The majority of samples were 1.9 to 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. We required an RNA integrity number (RIN) of greater than 8. This RIN value is based on the intensity ratio and amplitude of 18S and 28S rRNA signals. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using Superscript II reverse transcriptase (Invitrogen Inc.). The Enzo Life Sciences, Inc., BioArray High Yield RNA Transcript Labeling Kit (T7, Part No. 42655) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 2.0 or 2.1 are acceptable) and the Bioanalyzer output (a dark cRNA smear on the 2100 output centered roughly between 600 and 2000 nucleotides is required). Those samples that passed both QC steps (10% usually failed and new RNA samples had to be acquired and processed) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No. 900371). Fragmented cRNA samples were either stored at -80°C until use or were immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: Our goal was to obtain a male sample pool and female sample pool from each isogenic group. While almost all strains were orginally represented by matched male and female samples, not all data sets passed the final quality control steps. All but 5 of 99 strains (BXD55, BXD86, BXD94, BALB/cByJ, and CAST/EiJ) are represented by pairs or (rarely) trios of arrays. The first and last samples are technical replicates of a B6D2F1 hippocampal pool (aliquots R1291H3 and R1291H4).
+
+
+
+Sex Balance: Based on the expression of Xist, probe set 1427262_at, DBA/2J and KK/HlJ are represented only by female samples, BXD55, and BALB/cByJ are only represented by a single male sample, BXD74 is represented by two male samples, and BXD86, BXD94, and CAST/EiJ are possibly mixed sex samples. One of the BXD9 samples, array R1523, may be a mixed sex sample pool because the expression of Xist is intermediate.
+
+Experimental Design and Batch Structure: This data set consists arrays processed in six groups over a three month period (May 2005 to August 2005). Each group consists of 32 to 34 arrays. Sex, strain, and strain type (BXD, CXB, and MDP) were interleaved among groups to ensure reasonable balance and to minimize group-by-strain statistical confounds in group normalization. The two independent samples from a single strain were always run in different groups. All arrays were processed using a single protocol by a single operator, Shirlean Goodwin.
+
+All samples in a group were labeled on one day, except for a few cases that failed QC on their first pass. The hybridization station accommodates up to 20 samples, and for this reason each group was split into a large first set of 20 samples and a second set of 12 to 14 samples. Samples were washed in groups of four and then held in at 4°C until all 20 (or 12-14) arrays were ready to scan. The last four samples out of the wash stations were scanned directly. Samples were scanned in sets of four.
+
+COMPARISON with December 2005 Data Set: Both BXD14 arrays in the Dec05 data set were found to actually be from BXD23 cases. This error of strain identification has been corrected in the present data set. Four arrays in the Dec05 data set have been deleted because we judged them to be of poor quality (strain_sex_sample_firstreaction_group):
+
+
+ - BXD21_F_1_1_G1
+ - BXD23_M_1_1_G7
+ - BXD36_M_1_1_G2
+ - BXD36_F_1_1_G3
+
+
+In the Dec05 data set there are a total of 1986 transcripts with QTLs that have LRS scores above 50, whereas in the corrected June06 data sets there are a total of 2074 transcripts with QTLs above 50.
+
+Data Table 1:
+
+This table lists all arrays by file order (Index), tube/sample ID, age, sex, batch, and numbers of animals in each sample pool (pool size). The next columns (RMA outlier, scale factor, background average, present, absent, marginal, AFFY-b-ActinMur(3'/5'), AFFY-GapdhMur(3'/5')) are all Affymetrix QC data. Finally, source lists the source colony of the animals. (Final version, fully corrected, by Arthur Centeno, October 2008)
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ batch ID |
+ pool size |
+ RMA outlier |
+ scale factor |
+ back ground average |
+ present |
+ absent |
+ marginal |
+ AFFX-b-ActinMur (3'/5') |
+ AFFX-GapdhMur (3'/5') |
+ source |
+
+
+ | 1 |
+ R1289H2 |
+ B6D2F1 |
+ 64 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.406 |
+ 53.84 |
+ 0.492 |
+ 0.489 |
+ 0.019 |
+ 1.61 |
+ 0.96 |
+ UTM RW |
+
+
+ | 2 |
+ R1291H3 |
+ B6D2F1 |
+ 66 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
+ 3.524 |
+ 48.54 |
+ 0.487 |
+ 0.494 |
+ 0.019 |
+ 1.21 |
+ 1.52 |
+ UTM RW |
+
+
+ | 3 |
+ R1291H4 |
+ B6D2F1 |
+ 66 |
+ M technical duplicate of above |
+ 6 |
+ 3 |
+ 0.08 |
+ 3.891 |
+ 46.69 |
+ 0.512 |
+ 0.469 |
+ 0.019 |
+ 1.9 |
+ 0.89 |
+ UTM RW |
+
+
+ | 4 |
+ R2045H2 |
+ D2B6F1 |
+ 65 |
+ F |
+ 1 |
+ 2 |
+ 0.01 |
+ 4.403 |
+ 47.99 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.09 |
+ 1.53 |
+ UTM RW |
+
+
+ | 5 |
+ R1595H2 |
+ D2B6F1 |
+ 63 |
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+ 3 |
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+ UTM RW |
+
+
+ | 6 |
+ R1551H1 |
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+ 6 |
+ 3 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 7 |
+ R1361H1 |
+ C57BL/6J |
+ 69 |
+ F |
+ 6 |
+ 4 |
+ 0.01 |
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+ UTM RW |
+
+
+ | 8 |
+ R2041H2 |
+ C57BL/6J |
+ 65 |
+ M |
+ 1 |
+ 4 |
+ 0.04 |
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+ UTM RW |
+
+
+ | 9 |
+ R1449H2 |
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+ 71 |
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+ 5 |
+ 3 |
+ 0.09 |
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+
+
+ | 10 |
+ R1290H2 |
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+ 63 |
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+ 7 |
+ 2 |
+ 0.04 |
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+
+
+ | 11 |
+ R1468H1 |
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+ 5 |
+ 3 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 12 |
+ R1507H1 |
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+ 3 |
+ 3 |
+ 0.02 |
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+
+
+ | 13 |
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+ 7 |
+ 3 |
+ 0.03 |
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+
+
+ | 14 |
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+ 4 |
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+
+
+ | 15 |
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+ 1 |
+ 4 |
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+
+
+ | 16 |
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+ 1 |
+ 4 |
+ 0 |
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+
+
+ | 17 |
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+ 3 |
+ 2 |
+ 0.07 |
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+
+ | 18 |
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+ 1 |
+ 4 |
+ 0 |
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+
+ | 19 |
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+ 4 |
+ 3 |
+ 0.01 |
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+
+
+ | 20 |
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+ 1 |
+ 3 |
+ 0 |
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+
+ | 21 |
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+ 6 |
+ 3 |
+ 0.07 |
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+
+ | 22 |
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+ 1 |
+ 3 |
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+
+
+ | 23 |
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+ 3 |
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+ UTM RW |
+
+
+ | 24 |
+ R1531H1 |
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+ 6 |
+ 3 |
+ 0.06 |
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+
+ | 25 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+ | 26 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 27 |
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+ 7 |
+ 3 |
+ 0.03 |
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+
+ | 28 |
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+ 6 |
+ 3 |
+ 0.05 |
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+ 2 |
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+ Glenn |
+
+
+ | 29 |
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+ 1 |
+ 3 |
+ 0.03 |
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+
+ | 30 |
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+ 7 |
+ 3 |
+ 0.03 |
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+ UTM RW |
+
+
+ | 31 |
+ R1278H2 |
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+ 7 |
+ 3 |
+ 0.06 |
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+ UTM RW |
+
+
+ | 32 |
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+ BXD15 |
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+ 6 |
+ 4 |
+ 0.02 |
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+
+
+ | 33 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 34 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 35 |
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+ 0.03 |
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+
+ | 36 |
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+ 3 |
+ 0.02 |
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+
+
+ | 37 |
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+ 1 |
+ 3 |
+ 0.02 |
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+
+
+ | 38 |
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+ 1 |
+ 3 |
+ 0.02 |
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+
+
+ | 39 |
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+ 6 |
+ 3 |
+ 0.06 |
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+
+ | 40 |
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+ 0.07 |
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+
+
+ | 41 |
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+ 2 |
+ 4 |
+ 0 |
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+
+
+ | 42 |
+ R1848H3 |
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+ 4 |
+ 0.02 |
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+
+ | 43 |
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+
+
+ | 44 |
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+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 45 |
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+ 0.1 |
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+
+ | 46 |
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+
+
+ | 47 |
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+ 0.01 |
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+
+ | 48 |
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+ 0 |
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+
+ | 49 |
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+
+ | 50 |
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+
+ | 51 |
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+
+ | 52 |
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+
+
+ | 53 |
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+
+
+ | 54 |
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+
+
+ | 55 |
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+
+
+ | 56 |
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+
+
+ | 57 |
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+
+
+ | 58 |
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+
+ | 59 |
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+
+
+ | 60 |
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+
+
+ | 61 |
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+
+
+ | 62 |
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+
+
+ | 63 |
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+ 2 |
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+
+
+ | 64 |
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+
+
+ | 65 |
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+
+
+ | 66 |
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+ 0 |
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+
+
+ | 67 |
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+
+
+ | 68 |
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+
+
+ | 69 |
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+
+
+ | 70 |
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+ 3 |
+ 0 |
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+
+
+ | 71 |
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+ 0.02 |
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+ UTM RW |
+
+
+ | 72 |
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+ 0 |
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+
+
+ | 73 |
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+ 1 |
+ 3 |
+ 0.02 |
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+ UTM RW |
+
+
+ | 74 |
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+ 2 |
+ 0.03 |
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+
+
+ | 75 |
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+ UTM RW |
+
+
+ | 76 |
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+ 4 |
+ 3 |
+ 0 |
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+ UTM RW |
+
+
+ | 77 |
+ R1575H3 |
+ BXD48 |
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+ M |
+ 3 |
+ 4 |
+ 0.05 |
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+ UTM RW |
+
+
+ | 78 |
+ R2521H1 |
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+ F |
+ 6 |
+ 4 |
+ 0.01 |
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+ 0.02 |
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+ 0.78 |
+ UTM RW |
+
+
+ | 79 |
+ R1944H2 |
+ BXD50 |
+ 81 |
+ M |
+ 1 |
+ 3 |
+ 0.01 |
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+
+
+ | 80 |
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+ 66 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+
+ | 81 |
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+ 71 |
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+ 6 |
+ 4 |
+ 0.03 |
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+
+
+ | 82 |
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+ 7 |
+ 3 |
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+
+
+ | 83 |
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+ 4 |
+ 3 |
+ 0.01 |
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+
+
+ | 84 |
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+ 1 |
+ 3 |
+ 0 |
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+
+
+ | 85 |
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+ 7 |
+ 4 |
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+
+
+ | 86 |
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+ 94 |
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+ 1 |
+ 2 |
+ 0 |
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+
+
+ | 87 |
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+ 1 |
+ 4 |
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+
+
+ | 88 |
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+ 6 |
+ 4 |
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+
+
+ | 89 |
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+ 1 |
+ 3 |
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+
+
+ | 90 |
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+ 6 |
+ 3 |
+ 0.02 |
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+
+
+ | 91 |
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+ 1 |
+ 3 |
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+
+
+ | 92 |
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+ 3 |
+ 4 |
+ 0.01 |
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+
+
+ | 93 |
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+ 1 |
+ 2 |
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+
+
+ | 94 |
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+ 6 |
+ 2 |
+ 0 |
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+
+
+ | 95 |
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+ 1 |
+ 4 |
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+
+
+ | 96 |
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+ 4 |
+ 2 |
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+
+
+ | 97 |
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+ 6 |
+ 3 |
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+
+
+ | 98 |
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+ 1 |
+ 4 |
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+
+
+ | 99 |
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+ 5 |
+ 3 |
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+
+
+ | 100 |
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+ 2 |
+ 2 |
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+
+
+ | 101 |
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+ 2 |
+ 3 |
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+
+
+ | 102 |
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+ 3 |
+ 3 |
+ 0.03 |
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+
+
+ | 103 |
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+ 5 |
+ 2 |
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+
+
+ | 104 |
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+ 2 |
+ 3 |
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+
+
+ | 105 |
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+ 4 |
+ 2 |
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+
+
+ | 106 |
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+ 2 |
+ 3 |
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+
+
+ | 107 |
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+ 2 |
+ 3 |
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+
+
+ | 108 |
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+ 2 |
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+
+
+ | 109 |
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+ 3 |
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+
+
+ | 110 |
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+ 3 |
+ 4 |
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+
+
+ | 111 |
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+ 3 |
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+
+
+ | 112 |
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+
+
+ | 113 |
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+
+
+ | 114 |
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+
+
+ | 115 |
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+ 2 |
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+
+
+ | 116 |
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+
+
+ | 117 |
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+
+
+ | 118 |
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+
+
+ | 119 |
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+
+
+ | 120 |
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+
+
+ | 121 |
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+ 0 |
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+
+
+ | 122 |
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+ 2 |
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+
+
+ | 123 |
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+
+
+ | 124 |
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+
+
+ | 125 |
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+
+
+ | 126 |
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+
+
+ | 127 |
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+
+
+ | 128 |
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+
+
+ | 129 |
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+ 2 |
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+
+
+ | 130 |
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+
+
+ | 131 |
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+
+
+ | 132 |
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+
+
+ | 133 |
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+
+
+ | 134 |
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+
+
+ | 135 |
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+ 3 |
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+
+
+ | 136 |
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+ 3 |
+ 0 |
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+
+
+ | 137 |
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+ 0 |
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+
+
+ | 138 |
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+ 2 |
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+
+
+ | 139 |
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+ 3 |
+ 0 |
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+
+
+ | 140 |
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+
+
+ | 141 |
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+ 3 |
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+
+
+ | 142 |
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+ 3 |
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+
+
+ | 143 |
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+ 3 |
+ 0.02 |
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+
+
+ | 144 |
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+ 3 |
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+
+
+ | 145 |
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+ 2 |
+ 0.03 |
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+
+
+ | 146 |
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+ 3 |
+ 0.1 |
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+
+ | 147 |
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+ 3 |
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+
+
+ | 148 |
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+ 3 |
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+
+
+ | 149 |
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+ 2 |
+ 0.06 |
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+ UTM RW |
+
+
+ | 150 |
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+ 3 |
+ 0.04 |
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+
+
+ | 151 |
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+ 4 |
+ 0.11 |
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+ JAX |
+
+
+ | 152 |
+ R1675H1 |
+ BALB/cByJ |
+ 83 |
+ M |
+ 7 |
+ 3 |
+ 0.03 |
+ 3.405 |
+ 48.13 |
+ 0.509 |
+ 0.474 |
+ 0.018 |
+ 1.13 |
+ 0.78 |
+ JAX |
+
+
+ | 153 |
+ R2036H3 |
+ BALB/cJ |
+ 51 |
+ F |
+ 5 |
+ 3 |
+ 0.12 |
+ 2.611 |
+ 56.29 |
+ 0.518 |
+ 0.466 |
+ 0.017 |
+ 3.3 |
+ 1.23 |
+ UTM RW |
+
+
+ | 154 |
+ R2053H1 |
+ BALB/cJ |
+ 55 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.505 |
+ 63.27 |
+ 0.499 |
+ 0.483 |
+ 0.018 |
+ 3.1 |
+ 1.34 |
+ UTM RW |
+
+
+ | 155 |
+ R2037H2 |
+ BALB/cJ |
+ 51 |
+ M |
+ 6 |
+ 4 |
+ 0.01 |
+ 2.546 |
+ 58.13 |
+ 0.497 |
+ 0.485 |
+ 0.018 |
+ 1.26 |
+ 0.77 |
+ UTM RW |
+
+
+ | 156 |
+ R2038H3 |
+ C3H/HeJ |
+ 63 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.671 |
+ 66.74 |
+ 0.476 |
+ 0.504 |
+ 0.02 |
+ 1.41 |
+ 0.77 |
+ UTM RW |
+
+
+ | 157 |
+ R2039H1 |
+ C3H/HeJ |
+ 63 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 3.384 |
+ 44.15 |
+ 0.528 |
+ 0.454 |
+ 0.017 |
+ 2.16 |
+ 0.88 |
+ UTM RW |
+
+
+ | 158 |
+ R2137H1 |
+ C57BL/6ByJ |
+ 55 |
+ F |
+ 5 |
+ 3 |
+ 0.02 |
+ 4.746 |
+ 47.01 |
+ 0.488 |
+ 0.493 |
+ 0.018 |
+ 1.23 |
+ 0.79 |
+ JAX |
+
+
+ | 159 |
+ R2673H1 |
+ C57BL/6ByJ |
+ 55 |
+ M |
+ 7 |
+ 3 |
+ 0.08 |
+ 1.842 |
+ 67.69 |
+ 0.514 |
+ 0.469 |
+ 0.017 |
+ 1.75 |
+ 0.78 |
+ JAX |
+
+
+ | 160 |
+ R2619H1 |
+ CAST/EiJ |
+ 64 |
+ F |
+ 5 |
+ 3 |
+ 0.14 |
+ 4.077 |
+ 51.87 |
+ 0.455 |
+ 0.528 |
+ 0.018 |
+ 2.74 |
+ 1.2 |
+ JAX |
+
+
+ | 161 |
+ R1683H1 |
+ KK/HIJ |
+ 72 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 3.919 |
+ 54.23 |
+ 0.491 |
+ 0.489 |
+ 0.02 |
+ 1.31 |
+ 0.83 |
+ JAX |
+
+
+ | 162 |
+ R1687H3 |
+ KK/HIJ |
+ 72 |
+ F |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.888 |
+ 40.86 |
+ 0.499 |
+ 0.483 |
+ 0.019 |
+ 1.86 |
+ 0.88 |
+ JAX |
+
+
+ | 163 |
+ R2046H1 |
+ LG/J |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.822 |
+ 59.18 |
+ 0.514 |
+ 0.468 |
+ 0.018 |
+ 1.68 |
+ 0.8 |
+ UTM RW |
+
+
+ | 164 |
+ R2047H2 |
+ LG/J |
+ 63 |
+ M |
+ 6 |
+ 3 |
+ 0.07 |
+ 2.038 |
+ 60.34 |
+ 0.509 |
+ 0.471 |
+ 0.02 |
+ 2.16 |
+ 0.95 |
+ UTM RW |
+
+
+ | 165 |
+ R2048H1 |
+ NOD/LtJ |
+ 77 |
+ F |
+ 6 |
+ 2 |
+ 0.14 |
+ 4.045 |
+ 50.21 |
+ 0.489 |
+ 0.49 |
+ 0.021 |
+ 2.89 |
+ 0.95 |
+ UTM RW |
+
+
+ | 166 |
+ R2049H3 |
+ NOD/LtJ |
+ 76 |
+ M |
+ 5 |
+ 3 |
+ 0.1 |
+ 2.328 |
+ 52.78 |
+ 0.519 |
+ 0.462 |
+ 0.019 |
+ 3.09 |
+ 1.35 |
+ UTM RW |
+
+
+ | 167 |
+ R2200H1 |
+ NZO/HlLtJ |
+ 62 |
+ F |
+ 5 |
+ 2 |
+ 0.03 |
+ 2.648 |
+ 54.29 |
+ 0.543 |
+ 0.438 |
+ 0.019 |
+ 1.27 |
+ 0.8 |
+ JAX |
+
+
+ | 168 |
+ R2350H1 |
+ NZO/HlLtJ |
+ 96 |
+ M |
+ 6 |
+ 2 |
+ 0.19 |
+ 2.391 |
+ 50.52 |
+ 0.518 |
+ 0.463 |
+ 0.02 |
+ 3.71 |
+ 2.21 |
+ JAX |
+
+
+ | 169 |
+ R2677H1 |
+ PWD/PhJ |
+ 65 |
+ M |
+ 7 |
+ 2 |
+ 0.12 |
+ 2.764 |
+ 65.49 |
+ 0.462 |
+ 0.52 |
+ 0.018 |
+ 1.89 |
+ 1.16 |
+ UTM RW |
+
+
+ | 170 |
+ R2051H3 |
+ PWD/PhJ |
+ 64 |
+ M |
+ 5 |
+ 3 |
+ 0.07 |
+ 3.266 |
+ 51.5 |
+ 0.475 |
+ 0.506 |
+ 0.019 |
+ 2.8 |
+ 1.01 |
+ UTM RW |
+
+
+ | 171 |
+ R2322H1 |
+ PWK/PhJ |
+ 63 |
+ F |
+ 5 |
+ 2 |
+ 0.09 |
+ 2.94 |
+ 54.91 |
+ 0.511 |
+ 0.47 |
+ 0.019 |
+ 2.32 |
+ 1.02 |
+ JAX |
+
+
+ | 172 |
+ R2349H1 |
+ PWK/PhJ |
+ 83 |
+ M |
+ 6 |
+ 2 |
+ 0.15 |
+ 3.306 |
+ 54.93 |
+ 0.459 |
+ 0.522 |
+ 0.019 |
+ 4.65 |
+ 1.45 |
+ JAX |
+
+
+ | 173 |
+ R2198H2 |
+ WSB/EiJ |
+ 58 |
+ F |
+ 6 |
+ 1 |
+ 0.02 |
+ 2.922 |
+ 57.97 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.44 |
+ 0.76 |
+ JAX |
+
+
+ | 174 |
+ R2199H1 |
+ WSB/EiJ |
+ 58 |
+ M |
+ 5 |
+ 3 |
+ 0.04 |
+ 3.171 |
+ 54.95 |
+ 0.475 |
+ 0.505 |
+ 0.02 |
+ 1.32 |
+ 0.81 |
+ JAX |
+
+
+ | 175 |
+ R2116H1 |
+ CXB1 |
+ 55 |
+ F |
+ 3 |
+ 3 |
+ 0.07 |
+ 5.792 |
+ 51.59 |
+ 0.459 |
+ 0.521 |
+ 0.02 |
+ 1.17 |
+ 0.8 |
+ JAX |
+
+
+ | 176 |
+ R2096H1 |
+ CXB1 |
+ 55 |
+ M |
+ 4 |
+ 2 |
+ 0.01 |
+ 3.435 |
+ 53.78 |
+ 0.495 |
+ 0.485 |
+ 0.02 |
+ 1.22 |
+ 0.79 |
+ JAX |
+
+
+ | 177 |
+ R2117H2 |
+ CXB2 |
+ 62 |
+ F |
+ 4 |
+ 2 |
+ 0.04 |
+ 3.39 |
+ 45.97 |
+ 0.533 |
+ 0.45 |
+ 0.017 |
+ 2.05 |
+ 0.89 |
+ JAX |
+
+
+ | 178 |
+ R2098H1 |
+ CXB2 |
+ 68 |
+ M |
+ 3 |
+ 3 |
+ 0.02 |
+ 2.572 |
+ 54.22 |
+ 0.496 |
+ 0.485 |
+ 0.019 |
+ 1.38 |
+ 0.86 |
+ JAX |
+
+
+ | 179 |
+ R2118H1 |
+ CXB3 |
+ 47 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.646 |
+ 63.16 |
+ 0.478 |
+ 0.503 |
+ 0.019 |
+ 1.22 |
+ 0.77 |
+ JAX |
+
+
+ | 180 |
+ R2100H1 |
+ CXB3 |
+ 47 |
+ M |
+ 4 |
+ 3 |
+ 0.02 |
+ 5.76 |
+ 51.38 |
+ 0.48 |
+ 0.503 |
+ 0.017 |
+ 1.24 |
+ 0.81 |
+ JAX |
+
+
+ | 181 |
+ R2119H1 |
+ CXB4 |
+ 58 |
+ F |
+ 4 |
+ 3 |
+ 0.02 |
+ 3.897 |
+ 49.21 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 1.31 |
+ 0.79 |
+ JAX |
+
+
+ | 182 |
+ R2101H1 |
+ CXB4 |
+ 58 |
+ M |
+ 3 |
+ 3 |
+ 0.13 |
+ 7.372 |
+ 53.77 |
+ 0.433 |
+ 0.548 |
+ 0.019 |
+ 1.2 |
+ 0.97 |
+ JAX |
+
+
+ | 183 |
+ R2505H1 |
+ CXB5 |
+ 80 |
+ F |
+ 6 |
+ 3 |
+ 0.02 |
+ 2.83 |
+ 49.6 |
+ 0.499 |
+ 0.48 |
+ 0.02 |
+ 1.33 |
+ 0.76 |
+ UTM RW |
+
+
+ | 184 |
+ R2131H1 |
+ CXB5 |
+ 42 |
+ M |
+ 4 |
+ 3 |
+ 0.1 |
+ 5.577 |
+ 51.15 |
+ 0.434 |
+ 0.547 |
+ 0.019 |
+ 1.7 |
+ 0.89 |
+ JAX |
+
+
+ | 185 |
+ R0129H2 |
+ CXB5 |
+ 70 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.829 |
+ 45.42 |
+ 0.488 |
+ 0.493 |
+ 0.019 |
+ 1.23 |
+ 0.83 |
+ UTM RW |
+
+
+ | 186 |
+ R2676H1 |
+ CXB6 |
+ 47 |
+ F |
+ 7 |
+ 2 |
+ 0.05 |
+ 2.146 |
+ 62.51 |
+ 0.507 |
+ 0.475 |
+ 0.018 |
+ 1.52 |
+ 0.78 |
+ JAX |
+
+
+ | 187 |
+ R2102H1 |
+ CXB6 |
+ 49 |
+ M |
+ 4 |
+ 3 |
+ 0.07 |
+ 5.148 |
+ 51.63 |
+ 0.453 |
+ 0.529 |
+ 0.018 |
+ 1.43 |
+ 0.87 |
+ JAX |
+
+
+ | 188 |
+ R2121H1 |
+ CXB7 |
+ 63 |
+ F |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.904 |
+ 48.71 |
+ 0.464 |
+ 0.517 |
+ 0.019 |
+ 1.19 |
+ 0.92 |
+ JAX |
+
+
+ | 189 |
+ R2104H2 |
+ CXB7 |
+ 58 |
+ M |
+ 3 |
+ 2 |
+ 0.06 |
+ 3.389 |
+ 48.79 |
+ 0.502 |
+ 0.479 |
+ 0.019 |
+ 1.74 |
+ 1.48 |
+ JAX |
+
+
+ | 190 |
+ R2122H1 |
+ CXB8 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.04 |
+ 4.128 |
+ 59.77 |
+ 0.451 |
+ 0.529 |
+ 0.02 |
+ 1.12 |
+ 0.76 |
+ JAX |
+
+
+ | 191 |
+ R2105H1 |
+ CXB8 |
+ 41 |
+ M |
+ 4 |
+ 3 |
+ 0.16 |
+ 3.146 |
+ 61.04 |
+ 0.451 |
+ 0.53 |
+ 0.019 |
+ 1.34 |
+ 0.84 |
+ JAX |
+
+
+ | 192 |
+ R2123H1 |
+ CXB9 |
+ 54 |
+ F |
+ 3 |
+ 3 |
+ 0.08 |
+ 5.708 |
+ 55.94 |
+ 0.438 |
+ 0.543 |
+ 0.019 |
+ 1.32 |
+ 0.78 |
+ JAX |
+
+
+ | 193 |
+ R2106H1 |
+ CXB9 |
+ 54 |
+ M |
+ 4 |
+ 3 |
+ 0.06 |
+ 5.868 |
+ 46.55 |
+ 0.469 |
+ 0.512 |
+ 0.019 |
+ 1.18 |
+ 0.82 |
+ JAX |
+
+
+ | 194 |
+ R2124H1 |
+ CXB10 |
+ 53 |
+ F |
+ 4 |
+ 2 |
+ 0.11 |
+ 4.867 |
+ 39.88 |
+ 0.451 |
+ 0.528 |
+ 0.02 |
+ 1.55 |
+ 0.8 |
+ JAX |
+
+
+ | 195 |
+ R2671H1 |
+ CXB10 |
+ 53 |
+ M |
+ 7 |
+ 3 |
+ 0.09 |
+ 2.348 |
+ 71.45 |
+ 0.488 |
+ 0.494 |
+ 0.018 |
+ 2.2 |
+ 1.14 |
+ JAX |
+
+
+ | 196 |
+ R2125H1 |
+ CXB11 |
+ 58 |
+ F |
+ 3 |
+ 3 |
+ 0.03 |
+ 3.256 |
+ 54.95 |
+ 0.461 |
+ 0.519 |
+ 0.02 |
+ 1.46 |
+ 0.77 |
+ JAX |
+
+
+ | 197 |
+ R2128H1 |
+ CXB11 |
+ 58 |
+ M |
+ 4 |
+ 2 |
+ 0.06 |
+ 4.986 |
+ 54.13 |
+ 0.465 |
+ 0.515 |
+ 0.02 |
+ 1.11 |
+ 0.83 |
+ JAX |
+
+
+ | 198 |
+ R2126H1 |
+ CXB12 |
+ 47 |
+ F |
+ 4 |
+ 3 |
+ 0.11 |
+ 3.935 |
+ 54.11 |
+ 0.469 |
+ 0.511 |
+ 0.021 |
+ 1.5 |
+ 0.79 |
+ JAX |
+
+
+ | 199 |
+ R2109H1 |
+ CXB12 |
+ 47 |
+ M |
+ 3 |
+ 3 |
+ 0.07 |
+ 4.518 |
+ 49.26 |
+ 0.488 |
+ 0.492 |
+ 0.02 |
+ 1.23 |
+ 0.77 |
+ JAX |
+
+
+ | 200 |
+ R2672H1 |
+ CXB13 |
+ 49 |
+ F |
+ 7 |
+ 3 |
+ 0.03 |
+ 1.722 |
+ 79.52 |
+ 0.516 |
+ 0.465 |
+ 0.019 |
+ 1.64 |
+ 0.75 |
+ JAX |
+
+
+ | 201 |
+ R2110H1 |
+ CXB13 |
+ 56 |
+ M |
+ 4 |
+ 3 |
+ 0.21 |
+ 3.478 |
+ 48.08 |
+ 0.461 |
+ 0.517 |
+ 0.022 |
+ 1.21 |
+ 0.78 |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hc_u_0303_m/acknowledgment.rtf b/general/datasets/Hc_u_0303_m/acknowledgment.rtf
new file mode 100644
index 0000000..e520fa9
--- /dev/null
+++ b/general/datasets/Hc_u_0303_m/acknowledgment.rtf
@@ -0,0 +1,5 @@
+
+Cell and samples were generated by Leonid V. Bystrykh, Ellen Weersing, Bert Dontje, Gerald de Haan, Department of Stem Cell Biology, University of Groningen, the Netherlands. RNA amplification and array processing were carried out by Michael Cooke, John Hogenesch, Andrew Su, and colleagues at GNF.
+
+Data normalization and conversion for WebQTL were handled by Robert Williams, Kenneth Manly, Jintao Wang, and Yanhua Qu at UTHSC and Roswell Park Cancer Institute.
+
diff --git a/general/datasets/Hc_u_0303_m/cases.rtf b/general/datasets/Hc_u_0303_m/cases.rtf
new file mode 100644
index 0000000..03bd3fe
--- /dev/null
+++ b/general/datasets/Hc_u_0303_m/cases.rtf
@@ -0,0 +1,5 @@
+
+BXD recombinant inbred mice were purchased from The Jackson Laboratory and upon arrival were housed under clean conventional conditions in the Central Animal Facility of the University of Groningen, Netherlands. We used female mice between 3 and 6 months old.
+
+Stem cells (described below) were isolated from pooled bone marrow obtained from three BXD animals per strain. Pooled RNA samples were split in two aliquots and each sample was independently amplified and hybridized to the U74Av2 array (3 mice x 2 arrays).
+
diff --git a/general/datasets/Hc_u_0303_m/citation.rtf b/general/datasets/Hc_u_0303_m/citation.rtf
new file mode 100644
index 0000000..9f0651d
--- /dev/null
+++ b/general/datasets/Hc_u_0303_m/citation.rtf
@@ -0,0 +1,17 @@
+References:
+
+
+Scherer A, Krause A, Walker JR, Sutton SE, Seron D, Raulf F, Cooke MP (2003) Optimized protocol for linear RNA amplification and application to gene expression profiling of human renal biopsies. Biotechniques 34:546-550, 552-554, 556.
+
+
+
+de Haan G, Bystrykh LV, Weersing E, Dontje B, Geiger H, Ivanova N, Lemischka IR, Vellenga E, Van Zant G (2002) A genetic and genomic analysis identifies a cluster of genes associated with hematopoietic cell turnover Blood 100:2056-2062.
+
+
+
+Wang J, Williams RW, Manly KF (2003) WebQTL: Web-based complex trait analysis. Neuroinformatics 1: 299-308.
+
+
+
+Williams RW, Manly KF, Shou S, Chesler E, Hsu HC, Mountz J, Wang J, Threadgill DW, Lu L (2002) Massively parallel complex trait analysis of transcriptional activity in mouse brain. International Mouse Genome Conference 16:46.
+
diff --git a/general/datasets/Hc_u_0303_m/experiment-design.rtf b/general/datasets/Hc_u_0303_m/experiment-design.rtf
new file mode 100644
index 0000000..5b0ad70
--- /dev/null
+++ b/general/datasets/Hc_u_0303_m/experiment-design.rtf
@@ -0,0 +1,7 @@
+About amplification and hybridization:
+
+Total RNA was quantified using RiboGreen and split into equal aliquots of approximately 10 ng, representing RNA from approximately 10,000 cells, and labeled using a total of three rounds of RNA amplification, exactly as described previously (Scherer et al. 2003). Labeled cRNA was fractionated and hybridized to the U74Av2 microarray following standard Affymetrix protocols.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers were determined by BLAT analysis using the Mouse Genome Sequencing Consortium Oct 2003 Assembly (see http://genome.ucsc.edu/). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Hc_u_0303_m/experiment-type.rtf b/general/datasets/Hc_u_0303_m/experiment-type.rtf
new file mode 100644
index 0000000..de208e6
--- /dev/null
+++ b/general/datasets/Hc_u_0303_m/experiment-type.rtf
@@ -0,0 +1 @@
+Total RNA was quantified using RiboGreen and split into equal aliquots of approximately 10 ng, representing RNA from approximately 10,000 cells, and labeled using a total of three rounds of RNA amplification, exactly as described previously (Scherer et al. 2003). Labeled cRNA was fractionated and hybridized to the U74Av2 microarray following standard Affymetrix protocols.
\ No newline at end of file
diff --git a/general/datasets/Hc_u_0303_m/notes.rtf b/general/datasets/Hc_u_0303_m/notes.rtf
new file mode 100644
index 0000000..c9da172
--- /dev/null
+++ b/general/datasets/Hc_u_0303_m/notes.rtf
@@ -0,0 +1,5 @@
+Information about this text file:
+
+
+This text file originally generated by GdH and RWW, March 2003. Updated by RWW, October 30, 2004.
+
diff --git a/general/datasets/Hc_u_0303_m/processing.rtf b/general/datasets/Hc_u_0303_m/processing.rtf
new file mode 100644
index 0000000..6de5cfc
--- /dev/null
+++ b/general/datasets/Hc_u_0303_m/processing.rtf
@@ -0,0 +1,30 @@
+About data processing:
+
+Probe (cell) level data from the CEL file: These CEL values produced by MAS 5 are the 75% quantiles from a set of 36 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell.
+ - Step 3: We computed the Z score for each cell.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each of the individual strains.
+
+Probe set data from the TXT file: These TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefore represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+About the array probe set names:
+
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target): Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
diff --git a/general/datasets/Hc_u_0303_m/summary.rtf b/general/datasets/Hc_u_0303_m/summary.rtf
new file mode 100644
index 0000000..f04a43e
--- /dev/null
+++ b/general/datasets/Hc_u_0303_m/summary.rtf
@@ -0,0 +1 @@
+This data set is now superceeded by the March 2004 RMA data set. The original March 2003 data freeze provides estimates of mRNA expression in hematopoietic stem cells (HSC) from adult female BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the Genomics Institute of the Norvartis Research Foundations (GNF) and by de Haan and colleagues at the University of Groningen. Samples from 22 strains were hybridized to 44 arrays in a single batch. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between data sets (HSC and other tissues), the MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units.
diff --git a/general/datasets/Hc_u_0303_m/tissue.rtf b/general/datasets/Hc_u_0303_m/tissue.rtf
new file mode 100644
index 0000000..cde2ac6
--- /dev/null
+++ b/general/datasets/Hc_u_0303_m/tissue.rtf
@@ -0,0 +1,3 @@
+
+Bone marrow cells were flushed from the femurs and tibiae of three mice and pooled. After standard erythrocyte lysis nucleated cells were incubated with normal rat serum for 15 min at 4 degrees Celsius. Subsequently cells were stained with a panel of biotinylated lineage-specific antibodies (murine progenitor enrichment cocktail, containing anti-CD5, anti-CD45R, anti-CD11b, anti-TER119, anti-Gr-1, and anti-7-4, Stem Cell Technologies, Vancouver, Canada), FITC-anti-Sca-1 and APC-anti-c-kit (Pharmingen). Cells were washed twice, and incubated for 30 minutes with streptavidin-PerCP (Pharmingen). After two washes cells were resuspended in PBS with 1% BSA, and purified using a MoFlo flow cytometer. The lineage-depleted bone marrow cell population was defined as the 5% cells showing least PerCP-fluorescence intensity. Stem cell yield across all BXD samples varied from 16,000 to 118,000 Lin-Sca-1+ c-kit+ cells. A small aliquot of each sample of purified cells was functionally tested for stem cell activity by directly depositing single cells in a cobblestone area forming cell assay. The remainder of the cells was immediately collected in RNA lysis buffer. Total RNA was isolated using StrataPrep Total RNA Microprep kit (Stratagene) as described by the manufacturer. RNA pellets were resolved in 500 microliters absolute ethanol, and sent on dry ice by courrier to GNF, La Jolla, CA.
+
diff --git a/general/datasets/Hc_u_0304_r/acknowledgment.rtf b/general/datasets/Hc_u_0304_r/acknowledgment.rtf
new file mode 100644
index 0000000..e520fa9
--- /dev/null
+++ b/general/datasets/Hc_u_0304_r/acknowledgment.rtf
@@ -0,0 +1,5 @@
+
+Cell and samples were generated by Leonid V. Bystrykh, Ellen Weersing, Bert Dontje, Gerald de Haan, Department of Stem Cell Biology, University of Groningen, the Netherlands. RNA amplification and array processing were carried out by Michael Cooke, John Hogenesch, Andrew Su, and colleagues at GNF.
+
+Data normalization and conversion for WebQTL were handled by Robert Williams, Kenneth Manly, Jintao Wang, and Yanhua Qu at UTHSC and Roswell Park Cancer Institute.
+
diff --git a/general/datasets/Hc_u_0304_r/cases.rtf b/general/datasets/Hc_u_0304_r/cases.rtf
new file mode 100644
index 0000000..03bd3fe
--- /dev/null
+++ b/general/datasets/Hc_u_0304_r/cases.rtf
@@ -0,0 +1,5 @@
+
+BXD recombinant inbred mice were purchased from The Jackson Laboratory and upon arrival were housed under clean conventional conditions in the Central Animal Facility of the University of Groningen, Netherlands. We used female mice between 3 and 6 months old.
+
+Stem cells (described below) were isolated from pooled bone marrow obtained from three BXD animals per strain. Pooled RNA samples were split in two aliquots and each sample was independently amplified and hybridized to the U74Av2 array (3 mice x 2 arrays).
+
diff --git a/general/datasets/Hc_u_0304_r/citation.rtf b/general/datasets/Hc_u_0304_r/citation.rtf
new file mode 100644
index 0000000..9f0651d
--- /dev/null
+++ b/general/datasets/Hc_u_0304_r/citation.rtf
@@ -0,0 +1,17 @@
+References:
+
+
+Scherer A, Krause A, Walker JR, Sutton SE, Seron D, Raulf F, Cooke MP (2003) Optimized protocol for linear RNA amplification and application to gene expression profiling of human renal biopsies. Biotechniques 34:546-550, 552-554, 556.
+
+
+
+de Haan G, Bystrykh LV, Weersing E, Dontje B, Geiger H, Ivanova N, Lemischka IR, Vellenga E, Van Zant G (2002) A genetic and genomic analysis identifies a cluster of genes associated with hematopoietic cell turnover Blood 100:2056-2062.
+
+
+
+Wang J, Williams RW, Manly KF (2003) WebQTL: Web-based complex trait analysis. Neuroinformatics 1: 299-308.
+
+
+
+Williams RW, Manly KF, Shou S, Chesler E, Hsu HC, Mountz J, Wang J, Threadgill DW, Lu L (2002) Massively parallel complex trait analysis of transcriptional activity in mouse brain. International Mouse Genome Conference 16:46.
+
diff --git a/general/datasets/Hc_u_0304_r/experiment-design.rtf b/general/datasets/Hc_u_0304_r/experiment-design.rtf
new file mode 100644
index 0000000..5b0ad70
--- /dev/null
+++ b/general/datasets/Hc_u_0304_r/experiment-design.rtf
@@ -0,0 +1,7 @@
+About amplification and hybridization:
+
+Total RNA was quantified using RiboGreen and split into equal aliquots of approximately 10 ng, representing RNA from approximately 10,000 cells, and labeled using a total of three rounds of RNA amplification, exactly as described previously (Scherer et al. 2003). Labeled cRNA was fractionated and hybridized to the U74Av2 microarray following standard Affymetrix protocols.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers were determined by BLAT analysis using the Mouse Genome Sequencing Consortium Oct 2003 Assembly (see http://genome.ucsc.edu/). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Hc_u_0304_r/notes.rtf b/general/datasets/Hc_u_0304_r/notes.rtf
new file mode 100644
index 0000000..c9da172
--- /dev/null
+++ b/general/datasets/Hc_u_0304_r/notes.rtf
@@ -0,0 +1,5 @@
+Information about this text file:
+
+
+This text file originally generated by GdH and RWW, March 2003. Updated by RWW, October 30, 2004.
+
diff --git a/general/datasets/Hc_u_0304_r/processing.rtf b/general/datasets/Hc_u_0304_r/processing.rtf
new file mode 100644
index 0000000..6de5cfc
--- /dev/null
+++ b/general/datasets/Hc_u_0304_r/processing.rtf
@@ -0,0 +1,30 @@
+About data processing:
+
+Probe (cell) level data from the CEL file: These CEL values produced by MAS 5 are the 75% quantiles from a set of 36 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell.
+ - Step 3: We computed the Z score for each cell.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each of the individual strains.
+
+Probe set data from the TXT file: These TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefore represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+About the array probe set names:
+
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target): Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
diff --git a/general/datasets/Hc_u_0304_r/summary.rtf b/general/datasets/Hc_u_0304_r/summary.rtf
new file mode 100644
index 0000000..f04a43e
--- /dev/null
+++ b/general/datasets/Hc_u_0304_r/summary.rtf
@@ -0,0 +1 @@
+This data set is now superceeded by the March 2004 RMA data set. The original March 2003 data freeze provides estimates of mRNA expression in hematopoietic stem cells (HSC) from adult female BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the Genomics Institute of the Norvartis Research Foundations (GNF) and by de Haan and colleagues at the University of Groningen. Samples from 22 strains were hybridized to 44 arrays in a single batch. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between data sets (HSC and other tissues), the MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units.
diff --git a/general/datasets/Hc_u_0304_r/tissue.rtf b/general/datasets/Hc_u_0304_r/tissue.rtf
new file mode 100644
index 0000000..cde2ac6
--- /dev/null
+++ b/general/datasets/Hc_u_0304_r/tissue.rtf
@@ -0,0 +1,3 @@
+
+Bone marrow cells were flushed from the femurs and tibiae of three mice and pooled. After standard erythrocyte lysis nucleated cells were incubated with normal rat serum for 15 min at 4 degrees Celsius. Subsequently cells were stained with a panel of biotinylated lineage-specific antibodies (murine progenitor enrichment cocktail, containing anti-CD5, anti-CD45R, anti-CD11b, anti-TER119, anti-Gr-1, and anti-7-4, Stem Cell Technologies, Vancouver, Canada), FITC-anti-Sca-1 and APC-anti-c-kit (Pharmingen). Cells were washed twice, and incubated for 30 minutes with streptavidin-PerCP (Pharmingen). After two washes cells were resuspended in PBS with 1% BSA, and purified using a MoFlo flow cytometer. The lineage-depleted bone marrow cell population was defined as the 5% cells showing least PerCP-fluorescence intensity. Stem cell yield across all BXD samples varied from 16,000 to 118,000 Lin-Sca-1+ c-kit+ cells. A small aliquot of each sample of purified cells was functionally tested for stem cell activity by directly depositing single cells in a cobblestone area forming cell assay. The remainder of the cells was immediately collected in RNA lysis buffer. Total RNA was isolated using StrataPrep Total RNA Microprep kit (Stratagene) as described by the manufacturer. RNA pellets were resolved in 500 microliters absolute ethanol, and sent on dry ice by courrier to GNF, La Jolla, CA.
+
diff --git a/general/datasets/Hc_u_0903_m/acknowledgment.rtf b/general/datasets/Hc_u_0903_m/acknowledgment.rtf
new file mode 100644
index 0000000..e520fa9
--- /dev/null
+++ b/general/datasets/Hc_u_0903_m/acknowledgment.rtf
@@ -0,0 +1,5 @@
+
+Cell and samples were generated by Leonid V. Bystrykh, Ellen Weersing, Bert Dontje, Gerald de Haan, Department of Stem Cell Biology, University of Groningen, the Netherlands. RNA amplification and array processing were carried out by Michael Cooke, John Hogenesch, Andrew Su, and colleagues at GNF.
+
+Data normalization and conversion for WebQTL were handled by Robert Williams, Kenneth Manly, Jintao Wang, and Yanhua Qu at UTHSC and Roswell Park Cancer Institute.
+
diff --git a/general/datasets/Hc_u_0903_m/cases.rtf b/general/datasets/Hc_u_0903_m/cases.rtf
new file mode 100644
index 0000000..03bd3fe
--- /dev/null
+++ b/general/datasets/Hc_u_0903_m/cases.rtf
@@ -0,0 +1,5 @@
+
+BXD recombinant inbred mice were purchased from The Jackson Laboratory and upon arrival were housed under clean conventional conditions in the Central Animal Facility of the University of Groningen, Netherlands. We used female mice between 3 and 6 months old.
+
+Stem cells (described below) were isolated from pooled bone marrow obtained from three BXD animals per strain. Pooled RNA samples were split in two aliquots and each sample was independently amplified and hybridized to the U74Av2 array (3 mice x 2 arrays).
+
diff --git a/general/datasets/Hc_u_0903_m/citation.rtf b/general/datasets/Hc_u_0903_m/citation.rtf
new file mode 100644
index 0000000..9f0651d
--- /dev/null
+++ b/general/datasets/Hc_u_0903_m/citation.rtf
@@ -0,0 +1,17 @@
+References:
+
+
+Scherer A, Krause A, Walker JR, Sutton SE, Seron D, Raulf F, Cooke MP (2003) Optimized protocol for linear RNA amplification and application to gene expression profiling of human renal biopsies. Biotechniques 34:546-550, 552-554, 556.
+
+
+
+de Haan G, Bystrykh LV, Weersing E, Dontje B, Geiger H, Ivanova N, Lemischka IR, Vellenga E, Van Zant G (2002) A genetic and genomic analysis identifies a cluster of genes associated with hematopoietic cell turnover Blood 100:2056-2062.
+
+
+
+Wang J, Williams RW, Manly KF (2003) WebQTL: Web-based complex trait analysis. Neuroinformatics 1: 299-308.
+
+
+
+Williams RW, Manly KF, Shou S, Chesler E, Hsu HC, Mountz J, Wang J, Threadgill DW, Lu L (2002) Massively parallel complex trait analysis of transcriptional activity in mouse brain. International Mouse Genome Conference 16:46.
+
diff --git a/general/datasets/Hc_u_0903_m/experiment-design.rtf b/general/datasets/Hc_u_0903_m/experiment-design.rtf
new file mode 100644
index 0000000..5b0ad70
--- /dev/null
+++ b/general/datasets/Hc_u_0903_m/experiment-design.rtf
@@ -0,0 +1,7 @@
+About amplification and hybridization:
+
+Total RNA was quantified using RiboGreen and split into equal aliquots of approximately 10 ng, representing RNA from approximately 10,000 cells, and labeled using a total of three rounds of RNA amplification, exactly as described previously (Scherer et al. 2003). Labeled cRNA was fractionated and hybridized to the U74Av2 microarray following standard Affymetrix protocols.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers were determined by BLAT analysis using the Mouse Genome Sequencing Consortium Oct 2003 Assembly (see http://genome.ucsc.edu/). We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Hc_u_0903_m/experiment-type.rtf b/general/datasets/Hc_u_0903_m/experiment-type.rtf
new file mode 100644
index 0000000..15642e7
--- /dev/null
+++ b/general/datasets/Hc_u_0903_m/experiment-type.rtf
@@ -0,0 +1,17 @@
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+ _f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+
+_s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+
+ _g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+
+ _r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+
+ _i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+
+ _st (sense target): Designates a sense target; almost always generated in error.
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
\ No newline at end of file
diff --git a/general/datasets/Hc_u_0903_m/notes.rtf b/general/datasets/Hc_u_0903_m/notes.rtf
new file mode 100644
index 0000000..c9da172
--- /dev/null
+++ b/general/datasets/Hc_u_0903_m/notes.rtf
@@ -0,0 +1,5 @@
+Information about this text file:
+
+
+This text file originally generated by GdH and RWW, March 2003. Updated by RWW, October 30, 2004.
+
diff --git a/general/datasets/Hc_u_0903_m/processing.rtf b/general/datasets/Hc_u_0903_m/processing.rtf
new file mode 100644
index 0000000..6de5cfc
--- /dev/null
+++ b/general/datasets/Hc_u_0903_m/processing.rtf
@@ -0,0 +1,30 @@
+About data processing:
+
+Probe (cell) level data from the CEL file: These CEL values produced by MAS 5 are the 75% quantiles from a set of 36 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log2 of each cell.
+ - Step 3: We computed the Z score for each cell.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We computed the arithmetic mean of the values for the set of microarrays for each of the individual strains.
+
+Probe set data from the TXT file: These TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefore represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+About the array probe set names:
+
+
+Most probe sets on the U74Av2 array consist of a total of 32 probes, divided into 16 perfect match probes and 16 mismatch controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, and several suffix characters that highlight design features. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene. Other codes include:
+
+
+ - f_at (sequence family): Some probes in this probe set will hybridize to identical and/or slightly different sequences of related gene transcripts.
+ - s_at (similarity constraint): All Probes in this probe set target common sequences found in transcripts from several genes.
+ - g_at (common groups): Some probes in this set target identical sequences in multiple genes and some target unique sequences in the intended target gene.
+ - r_at (rules dropped): Probe sets for which it was not possible to pick a full set of unique probes using the Affymetrix probe selection rules. Probes were picked after dropping some of the selection rules.
+ - i_at (incomplete): Designates probe sets for which there are fewer than the standard numbers of unique probes specified in the design (16 perfect match for the U74Av2).
+ - st (sense target): Designates a sense target; almost always generated in error.
+
+
+Descriptions for the probe set extensions were taken from the Affymetrix GeneChip Expression Analysis Fundamentals.
+
diff --git a/general/datasets/Hc_u_0903_m/summary.rtf b/general/datasets/Hc_u_0903_m/summary.rtf
new file mode 100644
index 0000000..f04a43e
--- /dev/null
+++ b/general/datasets/Hc_u_0903_m/summary.rtf
@@ -0,0 +1 @@
+This data set is now superceeded by the March 2004 RMA data set. The original March 2003 data freeze provides estimates of mRNA expression in hematopoietic stem cells (HSC) from adult female BXD recombinant inbred mice measured using Affymetrix U74Av2 microarrays. Data were generated at the Genomics Institute of the Norvartis Research Foundations (GNF) and by de Haan and colleagues at the University of Groningen. Samples from 22 strains were hybridized to 44 arrays in a single batch. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between data sets (HSC and other tissues), the MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units.
diff --git a/general/datasets/Hc_u_0903_m/tissue.rtf b/general/datasets/Hc_u_0903_m/tissue.rtf
new file mode 100644
index 0000000..cde2ac6
--- /dev/null
+++ b/general/datasets/Hc_u_0903_m/tissue.rtf
@@ -0,0 +1,3 @@
+
+Bone marrow cells were flushed from the femurs and tibiae of three mice and pooled. After standard erythrocyte lysis nucleated cells were incubated with normal rat serum for 15 min at 4 degrees Celsius. Subsequently cells were stained with a panel of biotinylated lineage-specific antibodies (murine progenitor enrichment cocktail, containing anti-CD5, anti-CD45R, anti-CD11b, anti-TER119, anti-Gr-1, and anti-7-4, Stem Cell Technologies, Vancouver, Canada), FITC-anti-Sca-1 and APC-anti-c-kit (Pharmingen). Cells were washed twice, and incubated for 30 minutes with streptavidin-PerCP (Pharmingen). After two washes cells were resuspended in PBS with 1% BSA, and purified using a MoFlo flow cytometer. The lineage-depleted bone marrow cell population was defined as the 5% cells showing least PerCP-fluorescence intensity. Stem cell yield across all BXD samples varied from 16,000 to 118,000 Lin-Sca-1+ c-kit+ cells. A small aliquot of each sample of purified cells was functionally tested for stem cell activity by directly depositing single cells in a cobblestone area forming cell assay. The remainder of the cells was immediately collected in RNA lysis buffer. Total RNA was isolated using StrataPrep Total RNA Microprep kit (Stratagene) as described by the manufacturer. RNA pellets were resolved in 500 microliters absolute ethanol, and sent on dry ice by courrier to GNF, La Jolla, CA.
+
diff --git a/general/datasets/Heioncvscretilm6_0911/acknowledgment.rtf b/general/datasets/Heioncvscretilm6_0911/acknowledgment.rtf
new file mode 100644
index 0000000..a41ff76
--- /dev/null
+++ b/general/datasets/Heioncvscretilm6_0911/acknowledgment.rtf
@@ -0,0 +1,13 @@
+The HEI Retinal Database is supported by National Eye Institute Grants:
+
+
+
+
+ - R01EY017841 (Dr. Eldon E. Geisert, PI)
+
+
+ - P030EY13080 (NEI Vision Core Grant), and
+
+
+ - A Unrestricted Grand from Research to Prevent Blindness (Dr. Barrett Haik, PI)
+
diff --git a/general/datasets/Heioncvscretilm6_0911/cases.rtf b/general/datasets/Heioncvscretilm6_0911/cases.rtf
new file mode 100644
index 0000000..b37d700
--- /dev/null
+++ b/general/datasets/Heioncvscretilm6_0911/cases.rtf
@@ -0,0 +1,14 @@
+
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 48 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
+
+BXD strains:
+
+
+ - The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s.
+ - In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset.
+ - The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+What Makes the G2 HEI Retina Database different from the HEI Retina Database Examination of Gfap expression across all of the strains in the HEI Retinal Dataset, reveals that some strains express very high levels of Gfap relative to others. For example, BXD24 expresses Gfap at a 9-fold higher level, than BXD22. It has been established that BXD24 acquired a mutation in Cep290 that results in early onset photoreceptor degeneration (Chang et al., 2006). This degeneration results in reactive gliosis throughout the retina. In addition to BXD24, other BXD strains expressed very high levels of Gfap including: BXD32, BXD49, BXD70, BXD83 and BXD89. For the G2 dataset all of these strains with potential reactive gliosis were removed from the dataset.
diff --git a/general/datasets/Heioncvscretilm6_0911/contributors.rtf b/general/datasets/Heioncvscretilm6_0911/contributors.rtf
new file mode 100644
index 0000000..b1f321b
--- /dev/null
+++ b/general/datasets/Heioncvscretilm6_0911/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Justin P. Templeton, Robert W. Williams
diff --git a/general/datasets/Heioncvscretilm6_0911/experiment-design.rtf b/general/datasets/Heioncvscretilm6_0911/experiment-design.rtf
new file mode 100644
index 0000000..4fff707
--- /dev/null
+++ b/general/datasets/Heioncvscretilm6_0911/experiment-design.rtf
@@ -0,0 +1,12 @@
+Expression profiling by array
+
+We used pooled RNA samples of retinas, usually two independent pools--two male, two female pool--for most lines of mice.
+
+All normalization was performed by William E. Orr in the HEI Vision Core Facility
+
+
+ - Computed the log base 2 of each raw signal value
+ - Calculated the mean and standard Deviation of each Mouse WG-6 v2.0 array
+ - Normalized each array using the formula, 2 (z-score of log2 [intensity]) The result is to produce arrays that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - computed the mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
diff --git a/general/datasets/Heioncvscretilm6_0911/experiment-type.rtf b/general/datasets/Heioncvscretilm6_0911/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Heioncvscretilm6_0911/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Heioncvscretilm6_0911/notes.rtf b/general/datasets/Heioncvscretilm6_0911/notes.rtf
new file mode 100644
index 0000000..13ff99a
--- /dev/null
+++ b/general/datasets/Heioncvscretilm6_0911/notes.rtf
@@ -0,0 +1 @@
+This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/Heioncvscretilm6_0911/platform.rtf b/general/datasets/Heioncvscretilm6_0911/platform.rtf
new file mode 100644
index 0000000..2c52707
--- /dev/null
+++ b/general/datasets/Heioncvscretilm6_0911/platform.rtf
@@ -0,0 +1 @@
+Illumina MouseWG-6 v2.0 arrays: The Illumina Sentrix Mouse-6 BeadChip uses 50-nucleotide probes to interrogate approximately 46,000 sequences from the mouse transcriptome. For each array, the RNA was pooled from two retinas.
diff --git a/general/datasets/Heioncvscretilm6_0911/processing.rtf b/general/datasets/Heioncvscretilm6_0911/processing.rtf
new file mode 100644
index 0000000..97cc2be
--- /dev/null
+++ b/general/datasets/Heioncvscretilm6_0911/processing.rtf
@@ -0,0 +1,2654 @@
+Values of all 45,281 probe sets in this data set range from a low of 6.25 (Rho GTPase activating protein 11A, Arhgap11a, probe ID ILMN_2747167) to a high of 18.08 (Ubiquitin B, Ubb, probe ID ILMN_2516699). This corresponds to 11.83 units or a 1 to 3641 dynamic range of expression (2^11.83). We normalized raw signal values using Beadstudio’s rank invariant normalization algorithm. BXD62 was the strain used as the control group
+
+
+
+Sample Processing: Drs. Natalie E. Freeman-Anderson and Justin P. Templeton extracted the retinas from the mice and Dr. Natalie Freeman-Anderson processed all samples in the HEI Vision Core Facility. The tissue was homogenized and extracted according to the RNA-Stat-60 protocol as described by the manufacturer (Tel-Test, Friendswood, TX) listed above. The quality and purity of RNA was assessed using an Agilent Bioanalyzer 2100 system. The RNA from each sample was processed with the Illumina TotalPrep RNA Amplification Kit (Ambion, Austin, TX) to produce labeled cRNA. The cRNA for each sample was then hybridized to an Illumina Sentrix® Mouse-6-V2 BeadChip (Illumina, San Diego, CA)
+
+
+
+
+
+Quality control analysis of the raw image data was performed using the Illumina BeadStudio software. MIAME standards were used for all microarray data. Rank invariant normalization with BeadStudio software was used to calculate the data. Once this data was collected, the data was globally normalized across all samples using the formula 2 (z-score of log2 [intensity]) + 8.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
+
+Table 1: HEI Retina case IDs, including sample tube ID, strain, age, sex, and source of mice
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Age |
+ Sex |
+ Source of Animal |
+
+
+ | 1 |
+ 121608_11-C57BL/6JcFA |
+ C57BL/6J |
+ 69 |
+ F |
+ JAX |
+
+
+ | 2 |
+ 121608_12-C57BL/6JcFB |
+ C57BL/6J |
+ 69 |
+ F |
+ JAX |
+
+
+ | 3 |
+ KA7444-C57BL/6JcMC |
+ C57BL/6J |
+ 97 |
+ M |
+ UTHSC RW |
+
+
+ | 4 |
+ KA7444-C57BL/6JcMD |
+ C57BL/6J |
+ 97 |
+ M |
+ UTHSC RW |
+
+
+ | 5 |
+ 31209.05-DBA2JcFA |
+ DBA2J |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 6 |
+ 31209.05-DBA2JcFB |
+ DBA2J |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 7 |
+ 121608_13-DBA/2JcMA |
+ DBA/2J |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 8 |
+ 121608_14-DBA/2JcMB |
+ DBA/2J |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 9 |
+ KA7446-B6D2F1cFA |
+ B6D2F1 |
+ 92 |
+ F |
+ UTHSC RW |
+
+
+ | 10 |
+ KA7446-B6D2F1cFB |
+ B6D2F1 |
+ 92 |
+ F |
+ UTHSC RW |
+
+
+ | 11 |
+ KA7446-B6D2F1cMC |
+ B6D2F1 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 12 |
+ KA7446-B6D2F1cMD |
+ B6D2F1 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 13 |
+ KA7466-D2B6F1cFA |
+ D2B6F1 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 14 |
+ KA7466-D2B6F1cFB |
+ D2B6F1 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 15 |
+ KA7466-D2B6F1cMC |
+ D2B6F1 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 16 |
+ KA7466-D2B6F1cMD |
+ D2B6F1 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 17 |
+ 82609.13-1cFA |
+ BXD01 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 18 |
+ 82609.14-1cFB |
+ BXD01 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 19 |
+ KA7389-1cFA |
+ BXD01 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 20 |
+ KA7389-1cFB |
+ BXD01 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 21 |
+ KA7389-1cMC |
+ BXD01 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 22 |
+ KA7389-1cMD |
+ BXD01 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 23 |
+ KA7300-2cFA |
+ BXD02 |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 24 |
+ KA7300-2cFB |
+ BXD02 |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 25 |
+ 100909.01-2cMA |
+ BXD02 |
+ 65 |
+ M |
+ JAX |
+
+
+ | 26 |
+ 100909.02-2cMB |
+ BXD02 |
+ 65 |
+ M |
+ JAX |
+
+
+ | 27 |
+ KA6699-5cFA |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 28 |
+ KA6699-5cFB |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 29 |
+ KA6699-5cFC |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 30 |
+ KA6699-5cFD |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 31 |
+ 82609.09-5cMA |
+ BXD05 |
+ 60 |
+ M |
+ JAX |
+
+
+ | 32 |
+ 82609.1-5cMB |
+ BXD05 |
+ 60 |
+ M |
+ JAX |
+
+
+ | 33 |
+ KA6763-6cFA |
+ BXD06 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 34 |
+ KA6763-6cFB |
+ BXD06 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 35 |
+ 81209.06-6cMA |
+ BXD06 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 36 |
+ 81209.07-6cMB |
+ BXD06 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 37 |
+ 82609.07-8cFA |
+ BXD08 |
+ 68 |
+ F |
+ JAX |
+
+
+ | 38 |
+ 82609.08-8cFB |
+ BXD08 |
+ 68 |
+ F |
+ JAX |
+
+
+ | 39 |
+ JAX-8cMA |
+ BXD08 |
+ 76 |
+ M |
+ JAX |
+
+
+ | 40 |
+ JAX-8cMB |
+ BXD08 |
+ 76 |
+ M |
+ JAX |
+
+
+ | 41 |
+ KA7289-9cFA |
+ BXD09 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 42 |
+ KA7289-9cFB |
+ BXD09 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 43 |
+ KA7289-9cMC |
+ BXD09 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 44 |
+ KA7289-9cMD |
+ BXD09 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 45 |
+ JAX-11cFA |
+ BXD11 |
+ 84 |
+ F |
+ JAX |
+
+
+ | 46 |
+ JAX-11cFB |
+ BXD11 |
+ 84 |
+ F |
+ JAX |
+
+
+ | 47 |
+ JAX-11cMC |
+ BXD11 |
+ 71 |
+ M |
+ JAX |
+
+
+ | 48 |
+ JAX-11cMD |
+ BXD11 |
+ 71 |
+ M |
+ JAX |
+
+
+ | 49 |
+ 40209.07-12cFA |
+ BXD12 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 50 |
+ 40209.08-12cFB |
+ BXD12 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 51 |
+ 011309.01-12cMA |
+ BXD12 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 52 |
+ 011309.02-12cMB |
+ BXD12 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 53 |
+ KA7286-13cFA |
+ BXD13 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 54 |
+ KA7286-13cFB |
+ BXD13 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 55 |
+ KA7286-13cMC |
+ BXD13 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 56 |
+ KA7286-13cMD |
+ BXD13 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 57 |
+ KA7302-14cFA |
+ BXD14 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 58 |
+ KA7302-14cFB |
+ BXD14 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 59 |
+ 100909.05-14cMA |
+ BXD14 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 60 |
+ 100909.06-14cMB |
+ BXD14 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 61 |
+ KA7288-15cFA |
+ BXD15 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 62 |
+ KA7288-15cFB |
+ BXD15 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 63 |
+ KA7288-15cMC |
+ BXD15 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 64 |
+ KA7288-15cMD |
+ BXD15 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 65 |
+ 062509.01-16cFA |
+ BXD16 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 66 |
+ KA7267-16cMA |
+ BXD16 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 67 |
+ KA7267-16cMB |
+ BXD16 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 68 |
+ KA6686-18cFB |
+ BXD18 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 69 |
+ KA6686-18cFC |
+ BXD18 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 70 |
+ KA6686-18cME |
+ BXD18 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 71 |
+ KA6686-18cMF |
+ BXD18 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 72 |
+ KA6676-19cFB |
+ BXD19 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 73 |
+ KA6676-19cFC |
+ BXD19 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 74 |
+ KA6676-19cME |
+ BXD19 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 75 |
+ KA6676-19cMF |
+ BXD19 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 76 |
+ 060409.05-20cFA |
+ BXD20 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 77 |
+ 060409.06-20cFB |
+ BXD20 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 78 |
+ 021909.03-20cMA |
+ BXD20 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 79 |
+ 021909.04-20cMB |
+ BXD20 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 80 |
+ 82609.02-21cFC |
+ BXD21 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 81 |
+ 82609.03-21cFD |
+ BXD21 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 82 |
+ 121709.01-21cMA |
+ BXD21 |
+ 80 |
+ M |
+ JAX |
+
+
+ | 83 |
+ 121709.02-21cMB |
+ BXD21 |
+ 80 |
+ M |
+ JAX |
+
+
+ | 84 |
+ 121709.03-22cFA |
+ BXD22 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 85 |
+ 121709.04-22cFB |
+ BXD22 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 86 |
+ 092308_03-22cMA |
+ BXD22 |
+ 118 |
+ M |
+ UTHSC RW |
+
+
+ | 87 |
+ 092308_04-22cMB |
+ BXD22 |
+ 118 |
+ M |
+ UTHSC RW |
+
+
+ | 88 |
+ 80409.01-24AcFA |
+ BXD24A |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 89 |
+ 080409_02_24AcFB |
+ BXD24A |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 90 |
+ 82609.26-24AcFC |
+ BXD24A |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 91 |
+ 81209.03-24AcMC |
+ BXD24A |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 92 |
+ KA6678-24cFA |
+ BXD24 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 93 |
+ KA6678-24cFB |
+ BXD24 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 94 |
+ KA6678-24cME |
+ BXD24 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 95 |
+ KA6678-24cMF |
+ BXD24 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 96 |
+ 060409.07-27cFA |
+ BXD27 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 97 |
+ 060409.08-27cFB |
+ BXD27 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 98 |
+ 80409.03-27cMA |
+ BXD27 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 99 |
+ 80409.04-27cMB |
+ BXD27 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 100 |
+ JAX-28cFA |
+ BXD28 |
+ 67 |
+ F |
+ JAX |
+
+
+ | 101 |
+ JAX-28cFB |
+ BXD28 |
+ 67 |
+ F |
+ JAX |
+
+
+ | 102 |
+ JAX-28cMC |
+ BXD28 |
+ 67 |
+ M |
+ JAX |
+
+
+ | 103 |
+ JAX-28cMD |
+ BXD28 |
+ 67 |
+ M |
+ JAX |
+
+
+ | 104 |
+ 82609.11-29cFA |
+ BXD29 |
+ 66 |
+ F |
+ JAX |
+
+
+ | 105 |
+ 82609.12-29cFB |
+ BXD29 |
+ 66 |
+ F |
+ JAX |
+
+
+ | 106 |
+ 82609.04-29cMA |
+ BXD29 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 107 |
+ 82609.05-29cMB |
+ BXD29 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 108 |
+ JAX-31cMB |
+ BXD 31 |
+ 56 |
+ M |
+ JAX |
+
+
+ | 109 |
+ JAX-31cFC |
+ BXD 31 |
+ 69 |
+ F |
+ JAX |
+
+
+ | 110 |
+ JAX-31cFD |
+ BXD 31 |
+ 69 |
+ F |
+ JAX |
+
+
+ | 111 |
+ 011309.03-32cFA |
+ BXD32 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 112 |
+ 011309.04-32cFB |
+ BXD32 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 113 |
+ KA7318-32cFC |
+ BXD32 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 114 |
+ KA7319-32cMA |
+ BXD32 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 115 |
+ KA7319-32cMB |
+ BXD32 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 116 |
+ 100909.07-33cFA |
+ BXD33 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 117 |
+ 100909.08-33cFB |
+ BXD33 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 118 |
+ 022609.01-33cMA |
+ BXD33 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 119 |
+ 022609.02-33cMB |
+ BXD33 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 120 |
+ KA7416-34cFA |
+ BXD34 |
+ 97 |
+ F |
+ UTHSC RW |
+
+
+ | 121 |
+ KA7416-34cFB |
+ BXD34 |
+ 97 |
+ F |
+ UTHSC RW |
+
+
+ | 122 |
+ KA6321-34cMA |
+ BXD34 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 123 |
+ KA6321-34cMB |
+ BXD34 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 124 |
+ 060409.01-36cFA |
+ BXD36 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 125 |
+ 060409.02-36cFB |
+ BXD36 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 126 |
+ 060409.03-36cMC |
+ BXD36 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 127 |
+ KA6702-38cFA |
+ BXD38 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 128 |
+ KA6702-38cFB |
+ BXD38 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 129 |
+ 82609.24-38cFA |
+ BXD38 |
+ 85 |
+ F |
+ UTHSC RW |
+
+
+ | 130 |
+ 82609.25-38cFB |
+ BXD38 |
+ 85 |
+ F |
+ UTHSC RW |
+
+
+ | 131 |
+ 100909.03-38cMA |
+ BXD38 |
+ 61 |
+ M |
+ JAX |
+
+
+ | 132 |
+ 100909.04-38cMB |
+ BXD38 |
+ 61 |
+ M |
+ JAX |
+
+
+ | 133 |
+ 022609.05-39cFA |
+ BXD39 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 134 |
+ 022609.06-39cFB |
+ BXD39 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 135 |
+ 31209.01-39cMC |
+ BXD39 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 136 |
+ 92409.01-40cFA |
+ BXD40 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 137 |
+ 92409.02-40cFB |
+ BXD40 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 138 |
+ KA6173-40cMA |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 139 |
+ KA6173-40cMB |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 140 |
+ KA6173-40cMC |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 141 |
+ 091809.01-42cFA |
+ BXD42 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 142 |
+ 091809.02-42cFB |
+ BXD42 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 143 |
+ 021909.01-42cFA |
+ BXD42 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 144 |
+ 011309.06-42cMA |
+ BXD42 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 145 |
+ 011309.07-42cMB |
+ BXD42 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 146 |
+ 110408_02-43cFA |
+ BXD43 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 147 |
+ 110408_03-43cFB |
+ BXD43 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 148 |
+ KA6158-43cMA |
+ BXD43 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 149 |
+ KA6158-43cMB |
+ BXD43 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 150 |
+ 100308_01-44cFA |
+ BXD44 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 151 |
+ 102208_02-44cMD |
+ BXD44 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 152 |
+ 103009.03-45cFA |
+ BXD45 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 153 |
+ 103009.04-45cFB |
+ BXD45 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 154 |
+ 022609.03-45cFA |
+ BXD45 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 155 |
+ 022609.04-45cFB |
+ BXD45 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 156 |
+ 40309.05-45cMB |
+ BXD45 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 157 |
+ 40209.05-48cFB |
+ BXD48 |
+ 58 |
+ F |
+ VAMC |
+
+
+ | 158 |
+ 40209.06-48cFC |
+ BXD48 |
+ 58 |
+ F |
+ VAMC |
+
+
+ | 159 |
+ 81209.04-48cMA |
+ BXD48 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 160 |
+ 81209.05-48cMB |
+ BXD48 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 161 |
+ 81209.08-49cFA |
+ BXD49 |
+ 70 |
+ F |
+ VAMC |
+
+
+ | 162 |
+ 81209.09-49cFB |
+ BXD49 |
+ 70 |
+ F |
+ VAMC |
+
+
+ | 163 |
+ 40209.01-49cMA |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 164 |
+ 40209.02-49cMB |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 165 |
+ 40209.03-49cMC |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 166 |
+ KA737850cFA |
+ BXD50 |
+ 50 |
+ F |
+ UTHSC RW |
+
+
+ | 167 |
+ KA737850cFB |
+ BXD50 |
+ 50 |
+ F |
+ UTHSC RW |
+
+
+ | 168 |
+ 121908_01-50cMA |
+ BXD50 |
+ 49 |
+ M |
+ UTHSC RW |
+
+
+ | 169 |
+ 121908_02-50cMB |
+ BXD50 |
+ 49 |
+ M |
+ UTHSC RW |
+
+
+ | 170 |
+ 111208_01-51cFA |
+ BXD51 |
+ 99 |
+ F |
+ UTHSC RW |
+
+
+ | 171 |
+ 102208_03-51cMA |
+ BXD51 |
+ 56 |
+ M |
+ UTHSC RW |
+
+
+ | 172 |
+ 102208_04-51cMB |
+ BXD51 |
+ 56 |
+ M |
+ UTHSC RW |
+
+
+ | 173 |
+ 090208_14-53BcFA |
+ BXD53B |
+ 93 |
+ F |
+ UTHSC RW |
+
+
+ | 174 |
+ 090208_15-53BcFB |
+ BXD53B |
+ 93 |
+ F |
+ UTHSC RW |
+
+
+ | 175 |
+ 090208_16-53BcMC |
+ BXD53B |
+ 93 |
+ M |
+ UTHSC RW |
+
+
+ | 176 |
+ 090208_17-53BcMD |
+ BXD53B |
+ 93 |
+ M |
+ UTHSC RW |
+
+
+ | 177 |
+ 111208_05-55cFB |
+ BXD55 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 178 |
+ KA6183-55cMA |
+ BXD55 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 179 |
+ KA6183-55cMB |
+ BXD55 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 180 |
+ KA7362-56cFB |
+ BXD 56 |
+ 54 |
+ F |
+ UTHSC RW |
+
+
+ | 181 |
+ KA6088-56cMA |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 182 |
+ KA6088-56cMB |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 183 |
+ KA6088-56cMC |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 184 |
+ 21810.01-60RFA |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 185 |
+ 21810.02-60RFB |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 186 |
+ 21810.02-60RFC |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 187 |
+ SQ7325-60cMA |
+ BXD60 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 188 |
+ SQ7325-60cMB |
+ BXD60 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 189 |
+ 092308_10-61cFA |
+ BXD61 |
+ 110 |
+ F |
+ UTHSC RW |
+
+
+ | 190 |
+ 092308_11-61cFB |
+ BXD61 |
+ 110 |
+ F |
+ UTHSC RW |
+
+
+ | 191 |
+ 31909.01-61cMA |
+ BXD61 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 192 |
+ 31909.02-61cMB |
+ BXD61 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 193 |
+ KA7462-62cFA |
+ BXD62 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 194 |
+ KA7462-62cFB |
+ BXD62 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 195 |
+ KA5996-62cMA |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 196 |
+ KA5996-62cMB |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 197 |
+ KA5996-62cMC |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 198 |
+ 090309.01-63cFA |
+ BXD63 |
+ 69 |
+ F |
+ UTHSC RW |
+
+
+ | 199 |
+ 090309.02-63cFB |
+ BXD63 |
+ 69 |
+ F |
+ UTHSC RW |
+
+
+ | 200 |
+ 110609.01-63cMA |
+ BXD63 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 201 |
+ 110609.02-63cMB |
+ BXD63 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 202 |
+ 091809.03-65cFA |
+ BXD65 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 203 |
+ 091809.04-65cFB |
+ BXD65 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 204 |
+ 103009.01-65cMA |
+ BXD65 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 205 |
+ 103009.02-65cMB |
+ BXD65 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 206 |
+ 110408_05-66cFB |
+ BXD66 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 207 |
+ KA7165-66cMA |
+ BXD66 |
+ 95 |
+ M |
+ UTHSC RW |
+
+
+ | 208 |
+ KA7165-66cMB |
+ BXD66 |
+ 95 |
+ M |
+ UTHSC RW |
+
+
+ | 209 |
+ 90809.01-67cMA |
+ BXD67 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 210 |
+ 90809.02-67cMB |
+ BXD67 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 211 |
+ 110609.03-67cFA |
+ BXD67 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 212 |
+ 110609.04-67cFB |
+ BXD67 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 213 |
+ 120408_01-68cFA |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 214 |
+ 120408_02-68cFB |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 215 |
+ SQ7205-68cMA |
+ BXD68 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 216 |
+ SQ7205-68cMB |
+ BXD68 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 217 |
+ KA6316-68cMA |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 218 |
+ KA6316-68cMB |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 219 |
+ KA6316-68cMC |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 220 |
+ KA76-69cFA |
+ BXD69 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 221 |
+ KA76-69cFB |
+ BXD69 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 222 |
+ KA6074-69cMA |
+ BXD69 |
+ 90 |
+ M |
+ UTHSC RW |
+
+
+ | 223 |
+ KA6074-69cMB |
+ BXD69 |
+ 90 |
+ M |
+ UTHSC RW |
+
+
+ | 224 |
+ 121608_01-70cFA |
+ BXD70 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 225 |
+ 121608_02-70cFB |
+ BXD70 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 226 |
+ KA7394-70cMA |
+ BXD70 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 227 |
+ 81209.08-70cMA |
+ BXD70 |
+ 71 |
+ M |
+ VAMC |
+
+
+ | 228 |
+ 81209.09-70cMB |
+ BXD70 |
+ 71 |
+ M |
+ VAMC |
+
+
+ | 229 |
+ 052809.01-71cFA |
+ BXD71 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 230 |
+ 060409.09-71cMA |
+ BXD71 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 231 |
+ 060409.10-71cMB |
+ BXD71 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 232 |
+ 40809.01-73cFA |
+ BXD73 |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 233 |
+ 40809.02-73cFB |
+ BXD73 |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 234 |
+ 111708_01-73cFA |
+ BXD73 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 235 |
+ 111708_01-73cFB |
+ BXD73 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 236 |
+ KA6164-73cMB |
+ BXD73 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 237 |
+ KA6164-73cMC |
+ BXD73 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 238 |
+ 82609.22-74cFA |
+ BXD74 |
+ 68 |
+ F |
+ VAMC |
+
+
+ | 239 |
+ 82609.23-74cFB |
+ BXD74 |
+ 68 |
+ F |
+ VAMC |
+
+
+ | 240 |
+ 82609.20-74cMA |
+ BXD74 |
+ 68 |
+ M |
+ VAMC |
+
+
+ | 241 |
+ 82609.21-74cMB |
+ BXD74 |
+ 68 |
+ M |
+ VAMC |
+
+
+ | 242 |
+ KA733675cFA |
+ BXD75 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 243 |
+ KA733675cFB |
+ BXD75 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 244 |
+ KA38-75cMB |
+ BXD75 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 245 |
+ KA38-75cMC |
+ BXD75 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 246 |
+ 41509.01-77cFA |
+ BXD77 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 247 |
+ 41509.02-77cFB |
+ BXD77 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 248 |
+ 41509.03-77cMC |
+ BXD77 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 249 |
+ 41509.04-77cMD |
+ BXD77 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 250 |
+ 121608_03-80cFA |
+ BXD80 |
+ 77 |
+ F |
+ UTHSC RW |
+
+
+ | 251 |
+ 121608_05-80cMC |
+ BXD80 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 252 |
+ KA23-80cMC |
+ BXD80 |
+ 77 |
+ M |
+ UTHSC RW |
+
+
+ | 253 |
+ KA7305-81cFA |
+ BXD81 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 254 |
+ KA7305-81cFB |
+ BXD81 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 255 |
+ KA7305-81cMD |
+ BXD81 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 256 |
+ 060409.11-83cFA |
+ BXD83 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 257 |
+ KA24-83cFA |
+ BXD83 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 258 |
+ 121608_07-83cMA |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 259 |
+ 121608_08-83cMB |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 260 |
+ KA24-83cMD |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 261 |
+ 090409.05-84cFA |
+ BXD84 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 262 |
+ 090409.06-84cFB |
+ BXD84 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 263 |
+ KA6203-84cMA |
+ BXD84 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 264 |
+ KA6203-84cMB |
+ BXD84 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 265 |
+ 40309.02-85cFD |
+ BXD85 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 266 |
+ 40309.03-85cFE |
+ BXD85 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 267 |
+ 32609.01-85cMA |
+ BXD85 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 268 |
+ 32609.02-85cMB |
+ BXD85 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 269 |
+ 41509.05-86cFA |
+ BXD86 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 270 |
+ 41509.06-86cFB |
+ BXD86 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 271 |
+ KA6101-86cMA |
+ BXD86 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 272 |
+ KA6101-86cMC |
+ BXD86 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 273 |
+ 070909.02-87cFA |
+ BXD87 |
+ 86 |
+ F |
+ UTHSC RW |
+
+
+ | 274 |
+ 070909.03-87cFB |
+ BXD87 |
+ 86 |
+ F |
+ UTHSC RW |
+
+
+ | 275 |
+ KA7407-87cMA |
+ BXD87 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 276 |
+ KA7407-87cMB |
+ BXD87 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 277 |
+ 102208_05-89cFA |
+ BXD89 |
+ 82 |
+ F |
+ UTHSC RW |
+
+
+ | 278 |
+ KA5974-89cMA |
+ BXD89 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 279 |
+ KA5974-89cMB |
+ BXD89 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 280 |
+ 102208_06-89cMC |
+ BXD89 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 281 |
+ 72309.01-90cFA |
+ BXD90 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 282 |
+ 72309.02-90cFB |
+ BXD90 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 283 |
+ 090409.03-90cMA |
+ BXD90 |
+ 64 |
+ M |
+ VAMC |
+
+
+ | 284 |
+ 090409.04-90cMB |
+ BXD90 |
+ 64 |
+ M |
+ VAMC |
+
+
+ | 285 |
+ KA6094-92cMA |
+ BXD92 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 286 |
+ 020609.01-95cFA |
+ BXD95 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 287 |
+ 020609.02-95cFB |
+ BXD95 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 288 |
+ KA6181-95cMA |
+ BXD95 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 289 |
+ KA6181-95cMB |
+ BXD95 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 290 |
+ 31209.03-96cFA |
+ BXD96 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 291 |
+ 31209.04-96cFB |
+ BXD96 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 292 |
+ KA7246-96cMA |
+ BXD96 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 293 |
+ KA7246-96cMB |
+ BXD96 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 294 |
+ 81209.10-97cFA |
+ BXD97 |
+ 83 |
+ F |
+ VAMC |
+
+
+ | 295 |
+ 81209.11-97cFB |
+ BXD97 |
+ 83 |
+ F |
+ VAMC |
+
+
+ | 296 |
+ 81209.1-97cMA |
+ BXD97 |
+ 83 |
+ M |
+ VAMC |
+
+
+ | 297 |
+ 81209.11-97cMB |
+ BXD97 |
+ 83 |
+ M |
+ VAMC |
+
+
+ | 298 |
+ SQ7520-98cFA |
+ BXD98 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 299 |
+ SQ7520-98cFB |
+ BXD98 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 300 |
+ SQ7520-98cMC |
+ BXD98 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 301 |
+ SQ7520-98cMD |
+ BXD98 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 302 |
+ 82609.17-99cFA |
+ BXD99 |
+ 64 |
+ F |
+ VAMC |
+
+
+ | 303 |
+ 82609.18-99cFB |
+ BXD99 |
+ 64 |
+ F |
+ VAMC |
+
+
+ | 304 |
+ 81409.01-99cMA |
+ BXD99 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 305 |
+ 81409.02-99cMB |
+ BXD99 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 306 |
+ 121608_09-100cFA |
+ BXD100 |
+ 81 |
+ F |
+ UTHSC RW |
+
+
+ | 307 |
+ 121608_10-100cFB |
+ BXD100 |
+ 81 |
+ F |
+ UTHSC RW |
+
+
+ | 308 |
+ KA6001-100cMA |
+ BXD100 |
+ 111 |
+ M |
+ UTHSC RW |
+
+
+ | 309 |
+ KA6001-100cMB |
+ BXD100 |
+ 111 |
+ M |
+ UTHSC RW |
+
+
+ | 310 |
+ 81209.12-101cFA |
+ BXD101 |
+ 72 |
+ F |
+ VAMC |
+
+
+ | 311 |
+ 81209.13-101cFB |
+ BXD101 |
+ 72 |
+ F |
+ VAMC |
+
+
+ | 312 |
+ KA7296-101cMA |
+ BXD101 |
+ 75 |
+ M |
+ UTHSC RW |
+
+
+ | 313 |
+ KA7296-101cMB |
+ BXD101 |
+ 75 |
+ M |
+ UTHSC RW |
+
+
+ | 314 |
+ 92409.03-102cFA |
+ BXD102 |
+ 71 |
+ F |
+ VAMC |
+
+
+ | 315 |
+ 92409.04-102cFB |
+ BXD102 |
+ 71 |
+ F |
+ VAMC |
+
+
+ | 316 |
+ KA7380-102cMA |
+ BXD102 |
+ 115 |
+ M |
+ UTHSC RW |
+
+
+ | 317 |
+ 43009.01-103cFA |
+ BXD103 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 318 |
+ 43009.02-103cFB |
+ BXD103 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 319 |
+ KA79-103cFA |
+ BXD103 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 320 |
+ KA79-103cFB |
+ BXD103 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 321 |
+ KA79-103cMC |
+ BXD103 |
+ 48 |
+ M |
+ UTHSC RW |
+
+
+ | 322 |
+ 82609.15-103cMA |
+ BXD103 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 323 |
+ 82609.16-103cMB |
+ BXD103 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 324 |
+ 102909.01-BALBCcFA |
+ BALB/cByJ |
+ 78 |
+ F |
+ JAX |
+
+
+ | 325 |
+ 102909.02-BALBCcFB |
+ BALB/cByJ |
+ 78 |
+ F |
+ JAX |
+
+
+ | 326 |
+ 102909.03-BALBCcMA |
+ BALB/cByJ |
+ 78 |
+ M |
+ JAX |
+
+
+ | 327 |
+ 102909.04-BALBCcMB |
+ BALB/cByJ |
+ 78 |
+ M |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Heioncvscretilm6_0911/summary.rtf b/general/datasets/Heioncvscretilm6_0911/summary.rtf
new file mode 100644
index 0000000..44e98a7
--- /dev/null
+++ b/general/datasets/Heioncvscretilm6_0911/summary.rtf
@@ -0,0 +1,50 @@
+
+This is a subtractive dataset. The Normal retina dataset was subtracted from the ONC data set probe by probe to create a data set of the changes occurring following ONC. This data set can be used to define gene changes following ONC. It is not compatible with most of the bioinformatic tools available on GeneNetwork.
+
+HEI Retina Illumina V6.2 (April 2010) RankInv was normalized and scaled by William E. Orr and uploaded by Arthur Centeno and Xiaodong Zhou on April 7, 2010. This data set consists of either 69 BXD strains (Normal data set) or 75 BXD strains (Full data set), C57BL/6J, DBA/2J, both reciprocal F1s, and BALB/cByJ. A total of either 74 strains (Normal data set) or 80 strains (Full data set) were quantified.
+
+COMMENT on FULL versus NORMAL data sets: For many general uses there is no significant difference between FULL and NORMAL data sets. However, the FULL data set includes strains with high endogenous Gfap mRNA expression, indicative of reactive gliosis. For that reason, and to compare to OPTIC NERVE CRUSH (ONC), we removed data from six strains to make the NORMAL data set.
+
+The NORMAL data set exludes data from BXD24, BXD32, BXD49, BXD70, BXD83, and BXD89. BXD24 has known retinal degeneration and is now known officially as BXD24/TyJ-Cep290/J, JAX Stock number 000031. BXD32 has mild retinal degeneration. The NORMAL data set does include BXD24a, now also known as BXD24/TyJ (JAX Stock number 005243).
+
+The data are now open and available for analysis.
+
+Please cite: Freeman NE, Templeton JP, Orr WE, Lu L, Williams RW, Geisert EE (2011) Genetic networks in the mouse retina: Growth Associated Protein 43 and Phosphate Tensin Homology network. Molecular Vision 17:1355-1372. Full Text PDF or HTML
+
+This is rank invariant expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 6.25 to 18.08 (11.83 units), a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
+
+The lowest level of expression is 6.254 for ILMN_2747167 (Arhgap11a) from HEI Retina Illumina V6.2 (April 2010) RankInv **. Lowest single data about 5.842.
+
+The highest level of expression is 18.077 for ILMN_2516699 (Ubb). Highest single value is about 18.934.
+
+
+
+
+Other Related Publications
+
+
+
+
+
+ - Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link)
+ - Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674
+ - Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link)
+ - Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.(Link)
+
+
+
+
+
+
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
+
diff --git a/general/datasets/Heioncvscretilm6_0911/tissue.rtf b/general/datasets/Heioncvscretilm6_0911/tissue.rtf
new file mode 100644
index 0000000..766ab59
--- /dev/null
+++ b/general/datasets/Heioncvscretilm6_0911/tissue.rtf
@@ -0,0 +1,32 @@
+
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RNAlater at room temperature. Two retinas from one mouse were stored in a single tube.
+
+Each array was hybridized with a pool of cRNA from 2 retinas (1 mouse). Natalie Freeman-Anderson extracted RNA at UTHSC.
+
+
+
+Dissecting and preparing eyes for RNA extraction
+
+
+
+Retinas for RNA extraction were placed in RNA STAT-60 (Tel-Test Inc.) and processed per manufacturer’s instructions (in brief form below). Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+
+
+ - Homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue via syringe)
+ - Allow the homogenate to stand for 5-10 min at room temperature
+ - Add 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - Mix the sample vigorously for 15 sec and let the sample incubate at room temperature for 5-10 min
+ - Centrifuge at 12,000 g for 1 hr at 4°C
+ - Transfer the aqueous phase to a clean centrifuge tube
+ - Add 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - Vortex and incubate the sample at -20°C for 1 hr or overnight
+ - Centrifuge at 12,000 g for 1 hr
+ - Remove the supernatant and wash the RNA pellet with 75% ethanol
+ - Remove ethanol, let air dry (5-10 min)
+ - Dissolve the pellet in 50 μl of nuclease free water.
+
+
+
+
diff --git a/general/datasets/Het3_itppublish/citation.rtf b/general/datasets/Het3_itppublish/citation.rtf
new file mode 100644
index 0000000..e723d03
--- /dev/null
+++ b/general/datasets/Het3_itppublish/citation.rtf
@@ -0,0 +1,18 @@
+The first use of this strain designation was UM-HET3
+
+
+Miller, R. A., C. Chrisp, and A. Galecki. 1997. CD4 memory T cell levels predict lifespan in genetically heterogeneous mice. FASEB Journal 11:775-783
+
+
+UM-HET3 mice are neither an F1 nor an F2 hybrid. (An F2 hybrid is made by crossing males and females of the same F1 hybrid stock.) The correct designation is a "four-way cross."
+
+Publications from the NIA Interventions Testing Program
+
+The first ITP paper also referred to these mice as UM-HET3, using this strain designation regardless of the site at which the mice were produced.
+See:
+
+
+Miller, R. A., D. E. Harrison, C. M. Astle, R. A. Floyd, K. Flurkey, K. L. Hensley, M. A. Javors, C. Leeuwenburgh, J. F. Nelson, E. Ongini, N. L. Nadon, H. R. Warner, R. Strong. 2007. An aging interventions testing program: study design and interim report. Aging Cell 6: 565 - 575. [PMC: 17578509]
+
+
+ITP1: Interventions Testing Program: Effects of various treatments on lifespan and related phenotypes in genetically heterogeneous mice (UM-HET3) (2004-2022)
diff --git a/general/datasets/Het3_itppublish/specifics.rtf b/general/datasets/Het3_itppublish/specifics.rtf
new file mode 100644
index 0000000..4c7f4e9
--- /dev/null
+++ b/general/datasets/Het3_itppublish/specifics.rtf
@@ -0,0 +1 @@
+Aging Mouse Lifespan Studies (NIA UM-HET3)
\ No newline at end of file
diff --git a/general/datasets/Het3_itppublish/summary.rtf b/general/datasets/Het3_itppublish/summary.rtf
new file mode 100644
index 0000000..4a3de8b
--- /dev/null
+++ b/general/datasets/Het3_itppublish/summary.rtf
@@ -0,0 +1,5 @@
+http://www-personal.umich.edu/~millerr/ITP.htm
+
+https://www.nia.nih.gov/research/dab/interventions-testing-program-itp/frequently-asked-questions-about-itp
+
+https://www.nia.nih.gov/research/dab/interventions-testing-program-itp/compounds-testing
diff --git a/general/datasets/Hipp_illumina_rank_1006/acknowledgment.rtf b/general/datasets/Hipp_illumina_rank_1006/acknowledgment.rtf
new file mode 100644
index 0000000..959532f
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rank_1006/acknowledgment.rtf
@@ -0,0 +1,8 @@
+
+Data were generated with funds to Lu Lu, Beth Bennett, Mike Miles, Melloni Cook from INIA.
+
+
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513 (Lu Lu, PI)
+
+
diff --git a/general/datasets/Hipp_illumina_rank_1006/cases.rtf b/general/datasets/Hipp_illumina_rank_1006/cases.rtf
new file mode 100644
index 0000000..f3302c7
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rank_1006/cases.rtf
@@ -0,0 +1,5 @@
+
+The LXS genetic reference panel of recombinant inbred strains consists of just over 77 strains. All of these strains have been inbred for more than 23 generations (F23). All strains have been genotyped at 13,377 SNPs. Thanks to the efforts of Dr. Timothy Wiltshire at the Genome Institute of the Novartis Research Foundation, the two parental strains have been genotyped at 156,551 SNPs. These genotypes are incorporated in the GeneNetwork SNP Browser.
+
+Strains are currently available from Drs. Beth Bennett and Tom Johnson at the Institute of Behavioral Genetics (IBG) in Boulder Colorado.
+
diff --git a/general/datasets/Hipp_illumina_rank_1006/experiment-design.rtf b/general/datasets/Hipp_illumina_rank_1006/experiment-design.rtf
new file mode 100644
index 0000000..da9d781
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rank_1006/experiment-design.rtf
@@ -0,0 +1,2123 @@
+
+Sample Processing: Samples were processed by Lu Lu and colleagues in the Illumina Core at UTHSC between July 25 and Dec 20, 2006. All processing steps were performed by Feng Jiao. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on the original Mouse-6 v 1.0 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each strain. While all strains were orginally represented by matched male and female samples, one strain LXS34 consists of two female samples. Given the expression of Xist, we suspect that strain LXS114 is represented by two male pools (see figure at bottom of page).
+
+Experimental Design and Batch Structure: This data set consists arrays processed in 13 groups over a five month period (July 2006 to Dec 2006). Most groups consisted of 12 samples. All arrays in this data set were processed using a single protocol by a single operator, Feng Yiao. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between July 28 and Dec 21, 2006. Details on sample assignment to slides and batches is provide in the table below.
+
+
+This table lists all arrays by order of strain (index) and includes data on tube ID, strain, age, sex, F generation number, number of animals in each sample pool (pool size), slide ID, slide position (A through F), scan date, and scan batch.
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ gener-
+ ation |
+ pool
+ size |
+ slide
+ ID |
+ slide
+ position |
+ batch
+ by slide |
+ scan
+ batch |
+
+
+ | 1 |
+ R2851H2 |
+ ILS |
+ 77 |
+ F |
+ >100 |
+ 4 |
+ 1523516003 |
+ B |
+ 1 |
+ 1 |
+
+
+ | 2 |
+ R0595H2 |
+ ILS |
+ 71 |
+ F |
+ >100 |
+ 2 |
+ 1523516030 |
+ B |
+ 4 |
+ 2 |
+
+
+ | 3 |
+ R2874H2 |
+ ILS |
+ 78 |
+ M |
+ >100 |
+ 4 |
+ 1523516011 |
+ B |
+ 2 |
+ 1 |
+
+
+ | 4 |
+ R0585H2 |
+ ILS |
+ 65 |
+ M |
+ >100 |
+ 2 |
+ 1523516028 |
+ A |
+ 3 |
+ 2 |
+
+
+ | 5 |
+ R3281H1 |
+ ILSXISSF1 |
+ 90 |
+ F |
+ NA |
+ 3 |
+ 1562224029 |
+ A |
+ 28 |
+ 13 |
+
+
+ | 6 |
+ R2857H2 |
+ ISS |
+ 75 |
+ F |
+ >100 |
+ 4 |
+ 1523516011 |
+ A |
+ 2 |
+ 1 |
+
+
+ | 7 |
+ R0589H2 |
+ ISS |
+ 73 |
+ F |
+ >100 |
+ 2 |
+ 1523516028 |
+ B |
+ 3 |
+ 2 |
+
+
+ | 8 |
+ R2955H2 |
+ ISS |
+ 53 |
+ M |
+ >100 |
+ 3 |
+ 1523516003 |
+ A |
+ 1 |
+ 1 |
+
+
+ | 9 |
+ R0578H2 |
+ ISS |
+ 67 |
+ M |
+ >100 |
+ 2 |
+ 1523516030 |
+ A |
+ 4 |
+ 2 |
+
+
+ | 10 |
+ R3282H1 |
+ ISSXILSF1 |
+ 97 |
+ M |
+ NA |
+ 3 |
+ 1562224029 |
+ B |
+ 28 |
+ 13 |
+
+
+ | 11 |
+ R2013H2 |
+ LXS10 |
+ 84 |
+ F |
+ 27 |
+ 2 |
+ 1562224049 |
+ E |
+ 18 |
+ 9 |
+
+
+ | 12 |
+ R1993H2 |
+ LXS10 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1562224036 |
+ E |
+ 17 |
+ 9 |
+
+
+ | 13 |
+ R1997H2 |
+ LXS100 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ A |
+ 18 |
+ 9 |
+
+
+ | 14 |
+ R1983H2 |
+ LXS100 |
+ 77 |
+ M |
+ 25 |
+ 2 |
+ 1562224047 |
+ F |
+ 16 |
+ 8 |
+
+
+ | 15 |
+ R2083H2 |
+ LXS101 |
+ 85 |
+ F |
+ 28 |
+ 2 |
+ 1562224050 |
+ B |
+ 19 |
+ 9 |
+
+
+ | 16 |
+ R2084H2 |
+ LXS101 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224050 |
+ C |
+ 19 |
+ 9 |
+
+
+ | 17 |
+ R2186H2 |
+ LXS102 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1523516001 |
+ C |
+ 9 |
+ 5 |
+
+
+ | 18 |
+ R2187H2 |
+ LXS102 |
+ 73 |
+ M |
+ 29 |
+ 2 |
+ 1562224053 |
+ C |
+ 20 |
+ 10 |
+
+
+ | 19 |
+ R2809H2 |
+ LXS103 |
+ 72 |
+ F |
+ 26 |
+ 2 |
+ 1562224034 |
+ C |
+ 23 |
+ 11 |
+
+
+ | 20 |
+ R2854H1 |
+ LXS103 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516006 |
+ D |
+ 6 |
+ 3 |
+
+
+ | 21 |
+ R2735H2 |
+ LXS107 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516028 |
+ D |
+ 3 |
+ 2 |
+
+
+ | 22 |
+ R2738H2 |
+ LXS107 |
+ 78 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ C |
+ 21 |
+ 10 |
+
+
+ | 23 |
+ R2840H2 |
+ LXS110 |
+ 67 |
+ F |
+ 25 |
+ 2 |
+ 1562224037 |
+ D |
+ 24 |
+ 11 |
+
+
+ | 24 |
+ R2157H2 |
+ LXS110 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516033 |
+ E |
+ 8 |
+ 4 |
+
+
+ | 25 |
+ R2172H2 |
+ LXS112 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ B |
+ 9 |
+ 5 |
+
+
+ | 26 |
+ R2841H2 |
+ LXS112 |
+ 84 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ D |
+ 27 |
+ 12 |
+
+
+ | 27 |
+ R2188H2 |
+ LXS114 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224053 |
+ D |
+ 20 |
+ 10 |
+
+
+ | 28 |
+ R2204H2 |
+ LXS114 |
+ 72 |
+ M |
+ 28 |
+ 2 |
+ 1523516001 |
+ D |
+ 9 |
+ 5 |
+
+
+ | 29 |
+ R2168H2 |
+ LXS115 |
+ 80 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ A |
+ 9 |
+ 5 |
+
+
+ | 30 |
+ R2085H2 |
+ LXS115 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ D |
+ 19 |
+ 9 |
+
+
+ | 31 |
+ R2811H2 |
+ LXS117 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224034 |
+ D |
+ 23 |
+ 11 |
+
+
+ | 32 |
+ R2212H2 |
+ LXS117 |
+ 74 |
+ M |
+ 27 |
+ 2 |
+ 1523516001 |
+ E |
+ 9 |
+ 5 |
+
+
+ | 33 |
+ R1992H2 |
+ LXS122 |
+ 86 |
+ F |
+ 26 |
+ 2 |
+ 1562224036 |
+ D |
+ 17 |
+ 9 |
+
+
+ | 34 |
+ R2219H2 |
+ LXS122 |
+ 72 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ A |
+ 21 |
+ 10 |
+
+
+ | 35 |
+ R2876H2 |
+ LXS123 |
+ 87 |
+ F |
+ 28 |
+ 2 |
+ 1562224038 |
+ C |
+ 25 |
+ 11 |
+
+
+ | 36 |
+ R2832H1 |
+ LXS123 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1523516011 |
+ E |
+ 2 |
+ 1 |
+
+
+ | 37 |
+ R2872H1 |
+ LXS124 |
+ 83 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ E |
+ 6 |
+ 3 |
+
+
+ | 38 |
+ R2871H2 |
+ LXS124 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224042 |
+ F |
+ 27 |
+ 12 |
+
+
+ | 39 |
+ R1909H2 |
+ LXS13 |
+ 79 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ D |
+ 13 |
+ 7 |
+
+
+ | 40 |
+ R1901H2 |
+ LXS13 |
+ 81 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ D |
+ 26 |
+ 12 |
+
+
+ | 41 |
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+ 25 |
+ 2 |
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+ A |
+ 19 |
+ 9 |
+
+
+ | 42 |
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+ 85 |
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+ 26 |
+ 2 |
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+ A |
+ 10 |
+ 5 |
+
+
+ | 43 |
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+ 81 |
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+ 25 |
+ 2 |
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+ E |
+ 13 |
+ 7 |
+
+
+ | 44 |
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+ 25 |
+ 2 |
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+ B |
+ 8 |
+ 4 |
+
+
+ | 45 |
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+ 66 |
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+ 26 |
+ 2 |
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+ F |
+ 14 |
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+
+
+ | 46 |
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+ 26 |
+ 2 |
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+ 13 |
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+
+
+ | 47 |
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+ LXS2 |
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+ 27 |
+ 2 |
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+ F |
+ 12 |
+ 6 |
+
+
+ | 48 |
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+ LXS2 |
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+ 28 |
+ 2 |
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+ E |
+ 4 |
+ 2 |
+
+
+ | 49 |
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+ 72 |
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+ 27 |
+ 2 |
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+ E |
+ 7 |
+ 4 |
+
+
+ | 50 |
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+ 27 |
+ 2 |
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+ D |
+ 21 |
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+
+ | 51 |
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+ 26 |
+ 2 |
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+ D |
+ 15 |
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+
+ | 52 |
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+ 26 |
+ 2 |
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+ A |
+ 16 |
+ 8 |
+
+
+ | 53 |
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+ 74 |
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+ 26 |
+ 2 |
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+ C |
+ 1 |
+ 1 |
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+
+ | 54 |
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+ 56 |
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+ 25 |
+ 2 |
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+ A |
+ 11 |
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+
+ | 55 |
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+ 75 |
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+ 27 |
+ 2 |
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+ 17 |
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+
+ | 56 |
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+ 27 |
+ 2 |
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+ C |
+ 18 |
+ 9 |
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+
+ | 57 |
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+ 82 |
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+ 25 |
+ 2 |
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+ 18 |
+ 9 |
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+
+ | 58 |
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+ 82 |
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+ 26 |
+ 2 |
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+ D |
+ 18 |
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+
+
+ | 59 |
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+ 28 |
+ 2 |
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+ 27 |
+ 12 |
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+
+ | 60 |
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+ 27 |
+ 2 |
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+ 26 |
+ 12 |
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+
+ | 61 |
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+ 27 |
+ 2 |
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+ 5 |
+ 3 |
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+
+ | 62 |
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+ 26 |
+ 2 |
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+ 12 |
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+
+ | 63 |
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+ 29 |
+ 2 |
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+ 22 |
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+
+ | 64 |
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+ 28 |
+ 2 |
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+ C |
+ 13 |
+ 7 |
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+
+ | 65 |
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+ 26 |
+ 2 |
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+ 4 |
+ 2 |
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+
+ | 66 |
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+ 25 |
+ 2 |
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+ 12 |
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+
+ | 67 |
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+ 75 |
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+ 27 |
+ 2 |
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+ 11 |
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+
+ | 68 |
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+ 27 |
+ 2 |
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+ C |
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+
+ | 69 |
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+ 22 |
+ 2 |
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+ C |
+ 4 |
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+
+ | 70 |
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+ 22 |
+ 2 |
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+ A |
+ 22 |
+ 10 |
+
+
+ | 71 |
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+ 25 |
+ 2 |
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+ E |
+ 15 |
+ 8 |
+
+
+ | 72 |
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+ 25 |
+ 2 |
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+ C |
+ 7 |
+ 4 |
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+
+ | 73 |
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+ 27 |
+ 2 |
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+ 2 |
+ 1 |
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+
+ | 74 |
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+ 27 |
+ 2 |
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+ 12 |
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+
+ | 75 |
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+ 2 |
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+ E |
+ 20 |
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+
+ | 76 |
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+ 2 |
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+ 3 |
+ 2 |
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+
+ | 77 |
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+ 26 |
+ 2 |
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+ C |
+ 16 |
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+
+
+ | 78 |
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+ 26 |
+ 2 |
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+ D |
+ 11 |
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+
+ | 79 |
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+ 2 |
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+
+ | 80 |
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+ 2 |
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+ 12 |
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+
+ | 81 |
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+ 26 |
+ 2 |
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+ 16 |
+ 8 |
+
+
+ | 82 |
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+ 26 |
+ 2 |
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+ C |
+ 10 |
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+
+
+ | 83 |
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+ 2 |
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+ 6 |
+
+
+ | 84 |
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+ 25 |
+ 2 |
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+ D |
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+ 4 |
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+
+ | 85 |
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+ 2 |
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+ 15 |
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+
+
+ | 86 |
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+ 27 |
+ 2 |
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+ 12 |
+
+
+ | 87 |
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+ 2 |
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+ 14 |
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+
+
+ | 88 |
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+ 25 |
+ 2 |
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+ 3 |
+ 2 |
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+
+ | 89 |
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+ 28 |
+ 2 |
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+ 6 |
+ 3 |
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+
+ | 90 |
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+ 2 |
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+ 20 |
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+
+ | 91 |
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+ 2 |
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+
+ | 92 |
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+ 2 |
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+ 4 |
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+
+ | 93 |
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+ 2 |
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+ 4 |
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+
+ | 94 |
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+ 2 |
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+
+ | 95 |
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+ 2 |
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+
+ | 96 |
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+ 2 |
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+
+ | 97 |
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+ 2 |
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+
+
+ | 98 |
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+ 2 |
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+
+
+ | 99 |
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+ 2 |
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+
+
+ | 100 |
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+ 2 |
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+
+
+ | 101 |
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+ 2 |
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+
+ | 102 |
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+
+ | 103 |
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+ 2 |
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+
+ | 104 |
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+ 2 |
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+
+ | 105 |
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+
+ | 106 |
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+ 2 |
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+
+ | 107 |
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+ 2 |
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+
+ | 108 |
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+ 2 |
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+
+ | 109 |
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+ 2 |
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+
+ | 110 |
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+ 2 |
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+
+ | 111 |
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+ 2 |
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+
+
+ | 112 |
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+ 2 |
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+
+
+ | 113 |
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+ 2 |
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+ 1 |
+ 1 |
+
+
+ | 114 |
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+ 2 |
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+
+
+ | 115 |
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+ 2 |
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+
+
+ | 116 |
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+ 2 |
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+
+
+ | 117 |
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+ 2 |
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+
+
+ | 118 |
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+ 2 |
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+
+
+ | 119 |
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+ 2 |
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+
+
+ | 120 |
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+ 2 |
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+
+
+ | 121 |
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+ 2 |
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+
+ | 122 |
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+ 2 |
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+
+
+ | 123 |
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+ 2 |
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+
+
+ | 124 |
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+ 2 |
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+ 1 |
+ 1 |
+
+
+ | 125 |
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+ 2 |
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+
+
+ | 126 |
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+ 2 |
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+
+
+ | 127 |
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+ 2 |
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+ 14 |
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+
+
+ | 128 |
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+ 2 |
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+ 7 |
+
+
+ | 129 |
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+ 28 |
+ 2 |
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+ C |
+ 6 |
+ 3 |
+
+
+ | 130 |
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+ 2 |
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+
+
+ | 131 |
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+ 25 |
+ 2 |
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+ 14 |
+ 7 |
+
+
+ | 132 |
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+ 25 |
+ 2 |
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+ 14 |
+ 7 |
+
+
+ | 133 |
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+ 26 |
+ 2 |
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+ 2 |
+ 1 |
+
+
+ | 134 |
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+ 2 |
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+
+
+ | 135 |
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+ 2 |
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+
+
+ | 136 |
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+ 27 |
+ 2 |
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+ 6 |
+ 3 |
+
+
+ | 137 |
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+ 2 |
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+ 6 |
+ 3 |
+
+
+ | 138 |
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+ 2 |
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+
+
+ | 139 |
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+ 2 |
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+ 11 |
+
+
+ | 140 |
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+ 27 |
+ 2 |
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+ A |
+ 5 |
+ 3 |
+
+
+ | 141 |
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+ 26 |
+ 2 |
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+ C |
+ 2 |
+ 1 |
+
+
+ | 142 |
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+ 25 |
+ 2 |
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+ A |
+ 15 |
+ 8 |
+
+
+ | 143 |
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+ 26 |
+ 2 |
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+ 10 |
+ 5 |
+
+
+ | 144 |
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+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ D |
+ 1 |
+ 1 |
+
+
+ | 145 |
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+ LXS90 |
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+ 25 |
+ 2 |
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+ 11 |
+
+
+ | 146 |
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+ M |
+ 25 |
+ 2 |
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+ A |
+ 12 |
+ 6 |
+
+
+ | 147 |
+ R1736H2 |
+ LXS92 |
+ 66 |
+ F |
+ 23 |
+ 2 |
+ 1523516015 |
+ E |
+ 10 |
+ 5 |
+
+
+ | 148 |
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+ LXS92 |
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+ M |
+ 23 |
+ 2 |
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+ A |
+ 7 |
+ 4 |
+
+
+ | 149 |
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+ LXS93 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516032 |
+ B |
+ 7 |
+ 4 |
+
+
+ | 150 |
+ R1815H2 |
+ LXS93 |
+ 61 |
+ M |
+ 26 |
+ 2 |
+ 1523516009 |
+ B |
+ 12 |
+ 6 |
+
+
+ | 151 |
+ R1991H2 |
+ LXS94 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224036 |
+ C |
+ 17 |
+ 9 |
+
+
+ | 152 |
+ R2002H2 |
+ LXS94 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1562224049 |
+ B |
+ 18 |
+ 9 |
+
+
+ | 153 |
+ R1996H2 |
+ LXS96 |
+ 75 |
+ F |
+ 23 |
+ 2 |
+ 1562224036 |
+ F |
+ 17 |
+ 9 |
+
+
+ | 154 |
+ R1772H2 |
+ LXS96 |
+ 63 |
+ M |
+ 23 |
+ 2 |
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+ C |
+ 11 |
+ 6 |
+
+
+ | 155 |
+ R2759H2 |
+ LXS97 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224060 |
+ B |
+ 22 |
+ 10 |
+
+
+ | 156 |
+ R2739H2 |
+ LXS97 |
+ 79 |
+ M |
+ 26 |
+ 2 |
+ 1523516028 |
+ F |
+ 3 |
+ 2 |
+
+
+ | 157 |
+ R2149H2 |
+ LXS98 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516033 |
+ C |
+ 8 |
+ 4 |
+
+
+ | 158 |
+ R1888H2 |
+ LXS98 |
+ 76 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ B |
+ 26 |
+ 12 |
+
+
+ | 159 |
+ R1644H2 |
+ LXS99 |
+ 79 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ B |
+ 10 |
+ 5 |
+
+
+ | 160 |
+ R2145H2 |
+ LXS99 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ F |
+ 19 |
+ 9 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Hipp_illumina_rank_1006/notes.rtf b/general/datasets/Hipp_illumina_rank_1006/notes.rtf
new file mode 100644
index 0000000..4ae3a03
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rank_1006/notes.rtf
@@ -0,0 +1 @@
+Data uploaded by Hongqiang Li, Oct 30, 2006. This text file originally generated by LL and RWW on November 29, 2006. Updated by LL, Dec 1, 2006. Updated March 25, April 25 by RWW.
diff --git a/general/datasets/Hipp_illumina_rank_1006/platform.rtf b/general/datasets/Hipp_illumina_rank_1006/platform.rtf
new file mode 100644
index 0000000..cb0e31f
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rank_1006/platform.rtf
@@ -0,0 +1,9 @@
+
+Illumina Sentrix Mouse-6 BeadArray Platform: The Mouse6 array consists of 46,116 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+Dunning M, Smith M, Thorne N, Tavare S (2006) beadarray: An R package to analyse Illumina BeadArrays. R News (the Newsletter of the P Project) 6:17-23. (see pages 17-23 of http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf).
+
+ANNOTATION: In spring of 2007, Robert W. Williams and Hongqiang Li reannotated the Illumina Mouse-6 array content. This new annotation is now incorporated into GeneNetwork. For 46166 probes on the Mouse 6 array platform (including control probes) we have identified 35975 NCBI Entrez Gene IDs; 26481 matched human Gene IDs; 23899 matched rat Gene IDs; 26883 NCBI HomoloGene IDs; and 12791 OMIM IDs.
+
+Position data for the 50-mer Illumina Mouse-6 array were initially downloaded from Sanger at http://www.sanger.ac.uk/Users/avc/Illumina/Mouse-6_V1.gff.gz but we then updated all positions by BLAT analysis from mm6 positions to mm8 positions (Hongqiang Li).
+
diff --git a/general/datasets/Hipp_illumina_rank_1006/processing.rtf b/general/datasets/Hipp_illumina_rank_1006/processing.rtf
new file mode 100644
index 0000000..678856e
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rank_1006/processing.rtf
@@ -0,0 +1,13 @@
+
+All data links (right-most column above) will be made active as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
+
+
+
+This data set uses the standard Rank Invariant method developed by Illumina and described in their BeadStation Studio documentation.
+
+Sex of the samples was validated using sex-specific probe set: Xist (probe ILM106520068, also known as scl00213742.1_141-S).
+
+
+
+Legend: Checking that the sex of samples was labeled correctly in mouse array data sets using Xist expression measured by probe ILM106520068. In this bar chart the expression of Xist is very low in LXS114 and has a low error term. This is because both arrays are male samples rather than 1 male and 1 female sample. In contrast LXS34 has very high expression and no error bar because the sample is from a single female pool.
+
diff --git a/general/datasets/Hipp_illumina_rank_1006/summary.rtf b/general/datasets/Hipp_illumina_rank_1006/summary.rtf
new file mode 100644
index 0000000..357e642
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rank_1006/summary.rtf
@@ -0,0 +1,14 @@
+ILLUMINA Mouse-6 DATA SET: The LXS Hippocampus Illumina Rank Invariant data set provides estimates of mRNA expression in the hippocampus of 75 LXS recombinant inbred strains, the two parental strains and ILS/Ibg and ISS/Ibg (Inbred Long Sleep and Inbred Short Sleep strains from the Institute of Behavioral Genetics).All samples are from normal adult control animals raised in a standard laboratory environment. Subsequent data sets will provide estimates of mRNA expression following restraint stress, ethanol treatment, and stress followed by ethanol using many of the same strains (Lu Lu and colleagues).
+
+A total of 240 pooled hippocampal samples were processed using 40 Illumina Sentrix Mouse-6 v 1.0 oligomer microarray (GEO GPL6099) BeadArray slides. Twenty-seven Mouse-6 slides and a total of 160 samples passed stringent quality control and error checking. We should note that this is our first experience using the Illumina platform and the initial set of 13 slides were are not included. This particular data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from 6.141 average (very low or no expression) to 19.987 (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this initial data set, 1170 probes have LRS values >46. The maximum LRS achieved in this data set is 358.8 for probe ILM103520706 (Disabled 1; Dab1).
+
+
+
+Legend: Bar chart of the expression of Dab1 probe ILM103520706 in the LXS data set. This probe has a Mendelian segregation pattern and is associated with a LOD score of 77.7 (LRS 358.8). The two parental strains are shown to the far left, followed by all of the LXS strains for which we have acquired mRNA expression estimates in the hippocampus.
+
+
+
+ABOUT THE HIPPOCAMPUS. The hippocampus is an important and intriguing part of the forebrain that is crucial in memory formation and retrieval. This region of the brain is particularly vulnerable to the effects of environmental stressors and is a key upstream modulator of the hypothalamic-pituitary-adrenal axis (the HPA). The hippocampus is also often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3) is a joint effort of 14 investigators supported by numerous agencies described in the Acknowledgments section.
+
diff --git a/general/datasets/Hipp_illumina_rank_1006/tissue.rtf b/general/datasets/Hipp_illumina_rank_1006/tissue.rtf
new file mode 100644
index 0000000..04565fc
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rank_1006/tissue.rtf
@@ -0,0 +1,7 @@
+
+All animals were raised at the IBG by Bennett and colleagues in an SPF facility. No cases were MHV positive. Mice were killed by cervical dislocation. Whole brain dissections were performed at the IBG by Bennett and colleagues and shipped in RNAlater to Lu Lu and colleagues at UTHSC. Most hippocampal dissections (all were bilateral) were performed by Zhiping Jia. Cerebella, olfactory bulbs, and brain stems were also dissected and stored at -80 deg C using further use. Hippocampal samples are very close to complete (see Lu et al., 2001 but probably include variable amounts of fimbria and choroid plexus (see expression of transthyretin, Ttr, as a marker of choroid plexus).
+
+A pool of dissected tissue from four hippocampi taken from two naive adults of the same strain, sex, and age was collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at UTHSC by Zhiping Jia.
+
+All animals used in this study were between 53 and 90 days of age (average of 72 days; see Table 1 below).
+
diff --git a/general/datasets/Hipp_illumina_rankinv_0507/acknowledgment.rtf b/general/datasets/Hipp_illumina_rankinv_0507/acknowledgment.rtf
new file mode 100644
index 0000000..959532f
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_0507/acknowledgment.rtf
@@ -0,0 +1,8 @@
+
+Data were generated with funds to Lu Lu, Beth Bennett, Mike Miles, Melloni Cook from INIA.
+
+
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513 (Lu Lu, PI)
+
+
diff --git a/general/datasets/Hipp_illumina_rankinv_0507/cases.rtf b/general/datasets/Hipp_illumina_rankinv_0507/cases.rtf
new file mode 100644
index 0000000..f3302c7
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_0507/cases.rtf
@@ -0,0 +1,5 @@
+
+The LXS genetic reference panel of recombinant inbred strains consists of just over 77 strains. All of these strains have been inbred for more than 23 generations (F23). All strains have been genotyped at 13,377 SNPs. Thanks to the efforts of Dr. Timothy Wiltshire at the Genome Institute of the Novartis Research Foundation, the two parental strains have been genotyped at 156,551 SNPs. These genotypes are incorporated in the GeneNetwork SNP Browser.
+
+Strains are currently available from Drs. Beth Bennett and Tom Johnson at the Institute of Behavioral Genetics (IBG) in Boulder Colorado.
+
diff --git a/general/datasets/Hipp_illumina_rankinv_0507/experiment-design.rtf b/general/datasets/Hipp_illumina_rankinv_0507/experiment-design.rtf
new file mode 100644
index 0000000..da9d781
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_0507/experiment-design.rtf
@@ -0,0 +1,2123 @@
+
+Sample Processing: Samples were processed by Lu Lu and colleagues in the Illumina Core at UTHSC between July 25 and Dec 20, 2006. All processing steps were performed by Feng Jiao. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on the original Mouse-6 v 1.0 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each strain. While all strains were orginally represented by matched male and female samples, one strain LXS34 consists of two female samples. Given the expression of Xist, we suspect that strain LXS114 is represented by two male pools (see figure at bottom of page).
+
+Experimental Design and Batch Structure: This data set consists arrays processed in 13 groups over a five month period (July 2006 to Dec 2006). Most groups consisted of 12 samples. All arrays in this data set were processed using a single protocol by a single operator, Feng Yiao. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between July 28 and Dec 21, 2006. Details on sample assignment to slides and batches is provide in the table below.
+
+
+This table lists all arrays by order of strain (index) and includes data on tube ID, strain, age, sex, F generation number, number of animals in each sample pool (pool size), slide ID, slide position (A through F), scan date, and scan batch.
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ gener-
+ ation |
+ pool
+ size |
+ slide
+ ID |
+ slide
+ position |
+ batch
+ by slide |
+ scan
+ batch |
+
+
+ | 1 |
+ R2851H2 |
+ ILS |
+ 77 |
+ F |
+ >100 |
+ 4 |
+ 1523516003 |
+ B |
+ 1 |
+ 1 |
+
+
+ | 2 |
+ R0595H2 |
+ ILS |
+ 71 |
+ F |
+ >100 |
+ 2 |
+ 1523516030 |
+ B |
+ 4 |
+ 2 |
+
+
+ | 3 |
+ R2874H2 |
+ ILS |
+ 78 |
+ M |
+ >100 |
+ 4 |
+ 1523516011 |
+ B |
+ 2 |
+ 1 |
+
+
+ | 4 |
+ R0585H2 |
+ ILS |
+ 65 |
+ M |
+ >100 |
+ 2 |
+ 1523516028 |
+ A |
+ 3 |
+ 2 |
+
+
+ | 5 |
+ R3281H1 |
+ ILSXISSF1 |
+ 90 |
+ F |
+ NA |
+ 3 |
+ 1562224029 |
+ A |
+ 28 |
+ 13 |
+
+
+ | 6 |
+ R2857H2 |
+ ISS |
+ 75 |
+ F |
+ >100 |
+ 4 |
+ 1523516011 |
+ A |
+ 2 |
+ 1 |
+
+
+ | 7 |
+ R0589H2 |
+ ISS |
+ 73 |
+ F |
+ >100 |
+ 2 |
+ 1523516028 |
+ B |
+ 3 |
+ 2 |
+
+
+ | 8 |
+ R2955H2 |
+ ISS |
+ 53 |
+ M |
+ >100 |
+ 3 |
+ 1523516003 |
+ A |
+ 1 |
+ 1 |
+
+
+ | 9 |
+ R0578H2 |
+ ISS |
+ 67 |
+ M |
+ >100 |
+ 2 |
+ 1523516030 |
+ A |
+ 4 |
+ 2 |
+
+
+ | 10 |
+ R3282H1 |
+ ISSXILSF1 |
+ 97 |
+ M |
+ NA |
+ 3 |
+ 1562224029 |
+ B |
+ 28 |
+ 13 |
+
+
+ | 11 |
+ R2013H2 |
+ LXS10 |
+ 84 |
+ F |
+ 27 |
+ 2 |
+ 1562224049 |
+ E |
+ 18 |
+ 9 |
+
+
+ | 12 |
+ R1993H2 |
+ LXS10 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1562224036 |
+ E |
+ 17 |
+ 9 |
+
+
+ | 13 |
+ R1997H2 |
+ LXS100 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ A |
+ 18 |
+ 9 |
+
+
+ | 14 |
+ R1983H2 |
+ LXS100 |
+ 77 |
+ M |
+ 25 |
+ 2 |
+ 1562224047 |
+ F |
+ 16 |
+ 8 |
+
+
+ | 15 |
+ R2083H2 |
+ LXS101 |
+ 85 |
+ F |
+ 28 |
+ 2 |
+ 1562224050 |
+ B |
+ 19 |
+ 9 |
+
+
+ | 16 |
+ R2084H2 |
+ LXS101 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224050 |
+ C |
+ 19 |
+ 9 |
+
+
+ | 17 |
+ R2186H2 |
+ LXS102 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1523516001 |
+ C |
+ 9 |
+ 5 |
+
+
+ | 18 |
+ R2187H2 |
+ LXS102 |
+ 73 |
+ M |
+ 29 |
+ 2 |
+ 1562224053 |
+ C |
+ 20 |
+ 10 |
+
+
+ | 19 |
+ R2809H2 |
+ LXS103 |
+ 72 |
+ F |
+ 26 |
+ 2 |
+ 1562224034 |
+ C |
+ 23 |
+ 11 |
+
+
+ | 20 |
+ R2854H1 |
+ LXS103 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516006 |
+ D |
+ 6 |
+ 3 |
+
+
+ | 21 |
+ R2735H2 |
+ LXS107 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516028 |
+ D |
+ 3 |
+ 2 |
+
+
+ | 22 |
+ R2738H2 |
+ LXS107 |
+ 78 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ C |
+ 21 |
+ 10 |
+
+
+ | 23 |
+ R2840H2 |
+ LXS110 |
+ 67 |
+ F |
+ 25 |
+ 2 |
+ 1562224037 |
+ D |
+ 24 |
+ 11 |
+
+
+ | 24 |
+ R2157H2 |
+ LXS110 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516033 |
+ E |
+ 8 |
+ 4 |
+
+
+ | 25 |
+ R2172H2 |
+ LXS112 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ B |
+ 9 |
+ 5 |
+
+
+ | 26 |
+ R2841H2 |
+ LXS112 |
+ 84 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ D |
+ 27 |
+ 12 |
+
+
+ | 27 |
+ R2188H2 |
+ LXS114 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224053 |
+ D |
+ 20 |
+ 10 |
+
+
+ | 28 |
+ R2204H2 |
+ LXS114 |
+ 72 |
+ M |
+ 28 |
+ 2 |
+ 1523516001 |
+ D |
+ 9 |
+ 5 |
+
+
+ | 29 |
+ R2168H2 |
+ LXS115 |
+ 80 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ A |
+ 9 |
+ 5 |
+
+
+ | 30 |
+ R2085H2 |
+ LXS115 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ D |
+ 19 |
+ 9 |
+
+
+ | 31 |
+ R2811H2 |
+ LXS117 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224034 |
+ D |
+ 23 |
+ 11 |
+
+
+ | 32 |
+ R2212H2 |
+ LXS117 |
+ 74 |
+ M |
+ 27 |
+ 2 |
+ 1523516001 |
+ E |
+ 9 |
+ 5 |
+
+
+ | 33 |
+ R1992H2 |
+ LXS122 |
+ 86 |
+ F |
+ 26 |
+ 2 |
+ 1562224036 |
+ D |
+ 17 |
+ 9 |
+
+
+ | 34 |
+ R2219H2 |
+ LXS122 |
+ 72 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ A |
+ 21 |
+ 10 |
+
+
+ | 35 |
+ R2876H2 |
+ LXS123 |
+ 87 |
+ F |
+ 28 |
+ 2 |
+ 1562224038 |
+ C |
+ 25 |
+ 11 |
+
+
+ | 36 |
+ R2832H1 |
+ LXS123 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1523516011 |
+ E |
+ 2 |
+ 1 |
+
+
+ | 37 |
+ R2872H1 |
+ LXS124 |
+ 83 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ E |
+ 6 |
+ 3 |
+
+
+ | 38 |
+ R2871H2 |
+ LXS124 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224042 |
+ F |
+ 27 |
+ 12 |
+
+
+ | 39 |
+ R1909H2 |
+ LXS13 |
+ 79 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ D |
+ 13 |
+ 7 |
+
+
+ | 40 |
+ R1901H2 |
+ LXS13 |
+ 81 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ D |
+ 26 |
+ 12 |
+
+
+ | 41 |
+ R2023H2 |
+ LXS14 |
+ 86 |
+ F |
+ 25 |
+ 2 |
+ 1562224050 |
+ A |
+ 19 |
+ 9 |
+
+
+ | 42 |
+ R1612H2 |
+ LXS14 |
+ 85 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ A |
+ 10 |
+ 5 |
+
+
+ | 43 |
+ R1936H2 |
+ LXS16 |
+ 81 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ E |
+ 13 |
+ 7 |
+
+
+ | 44 |
+ R1912H2 |
+ LXS16 |
+ 81 |
+ M |
+ 25 |
+ 2 |
+ 1523516033 |
+ B |
+ 8 |
+ 4 |
+
+
+ | 45 |
+ R1961H2 |
+ LXS19 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516029 |
+ F |
+ 14 |
+ 7 |
+
+
+ | 46 |
+ R1904H2 |
+ LXS19 |
+ 66 |
+ M |
+ 26 |
+ 2 |
+ 1523516024 |
+ B |
+ 13 |
+ 7 |
+
+
+ | 47 |
+ R1883H2 |
+ LXS2 |
+ 71 |
+ F |
+ 27 |
+ 2 |
+ 1523516009 |
+ F |
+ 12 |
+ 6 |
+
+
+ | 48 |
+ R2753H2 |
+ LXS2 |
+ 74 |
+ M |
+ 28 |
+ 2 |
+ 1523516030 |
+ E |
+ 4 |
+ 2 |
+
+
+ | 49 |
+ R1729H2 |
+ LXS22 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516032 |
+ E |
+ 7 |
+ 4 |
+
+
+ | 50 |
+ R2743H2 |
+ LXS22 |
+ 79 |
+ M |
+ 27 |
+ 2 |
+ 1562224054 |
+ D |
+ 21 |
+ 10 |
+
+
+ | 51 |
+ R1966H2 |
+ LXS23 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224032 |
+ D |
+ 15 |
+ 8 |
+
+
+ | 52 |
+ R1971H2 |
+ LXS23 |
+ 73 |
+ M |
+ 26 |
+ 2 |
+ 1562224047 |
+ A |
+ 16 |
+ 8 |
+
+
+ | 53 |
+ R2795H2 |
+ LXS24 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516003 |
+ C |
+ 1 |
+ 1 |
+
+
+ | 54 |
+ R1755H2 |
+ LXS24 |
+ 56 |
+ M |
+ 25 |
+ 2 |
+ 1523516007 |
+ A |
+ 11 |
+ 6 |
+
+
+ | 55 |
+ R1986H2 |
+ LXS25 |
+ 75 |
+ F |
+ 27 |
+ 2 |
+ 1562224036 |
+ A |
+ 17 |
+ 9 |
+
+
+ | 56 |
+ R2006H2 |
+ LXS25 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1562224049 |
+ C |
+ 18 |
+ 9 |
+
+
+ | 57 |
+ R2014H2 |
+ LXS26 |
+ 82 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ F |
+ 18 |
+ 9 |
+
+
+ | 58 |
+ R2009H2 |
+ LXS26 |
+ 82 |
+ M |
+ 26 |
+ 2 |
+ 1562224049 |
+ D |
+ 18 |
+ 9 |
+
+
+ | 59 |
+ R2824H1 |
+ LXS28 |
+ 67 |
+ F |
+ 28 |
+ 2 |
+ 1562224042 |
+ A |
+ 27 |
+ 12 |
+
+
+ | 60 |
+ R1753H1 |
+ LXS28 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1562224041 |
+ F |
+ 26 |
+ 12 |
+
+
+ | 61 |
+ R2765H2 |
+ LXS3 |
+ 63 |
+ F |
+ 27 |
+ 2 |
+ 1523516005 |
+ B |
+ 5 |
+ 3 |
+
+
+ | 62 |
+ R1898H2 |
+ LXS3 |
+ 81 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ C |
+ 26 |
+ 12 |
+
+
+ | 63 |
+ R2764H2 |
+ LXS31 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1562224060 |
+ C |
+ 22 |
+ 10 |
+
+
+ | 64 |
+ R1908H2 |
+ LXS31 |
+ 80 |
+ M |
+ 28 |
+ 2 |
+ 1523516024 |
+ C |
+ 13 |
+ 7 |
+
+
+ | 65 |
+ R2758H2 |
+ LXS32 |
+ 70 |
+ F |
+ 26 |
+ 2 |
+ 1523516030 |
+ F |
+ 4 |
+ 2 |
+
+
+ | 66 |
+ R1743H1 |
+ LXS32 |
+ 67 |
+ M |
+ 25 |
+ 2 |
+ 1562224041 |
+ E |
+ 26 |
+ 12 |
+
+
+ | 67 |
+ R2794H2 |
+ LXS34 |
+ 75 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ B |
+ 23 |
+ 11 |
+
+
+ | 68 |
+ R2870H2 |
+ LXS34 |
+ 78 |
+ F |
+ 27 |
+ 2 |
+ 1562224029 |
+ C |
+ 28 |
+ 13 |
+
+
+ | 69 |
+ R2746H2 |
+ LXS35 |
+ 80 |
+ F |
+ 22 |
+ 2 |
+ 1523516030 |
+ C |
+ 4 |
+ 2 |
+
+
+ | 70 |
+ R2747H2 |
+ LXS35 |
+ 81 |
+ M |
+ 22 |
+ 2 |
+ 1562224060 |
+ A |
+ 22 |
+ 10 |
+
+
+ | 71 |
+ R1968H2 |
+ LXS36 |
+ 76 |
+ F |
+ 25 |
+ 2 |
+ 1562224032 |
+ E |
+ 15 |
+ 8 |
+
+
+ | 72 |
+ R1640H2 |
+ LXS36 |
+ 76 |
+ M |
+ 25 |
+ 2 |
+ 1523516032 |
+ C |
+ 7 |
+ 4 |
+
+
+ | 73 |
+ R2835H1 |
+ LXS38 |
+ 67 |
+ F |
+ 27 |
+ 2 |
+ 1523516011 |
+ F |
+ 2 |
+ 1 |
+
+
+ | 74 |
+ R2842H2 |
+ LXS38 |
+ 67 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ E |
+ 27 |
+ 12 |
+
+
+ | 75 |
+ R2210H2 |
+ LXS39 |
+ 81 |
+ F |
+ 28 |
+ 2 |
+ 1562224053 |
+ E |
+ 20 |
+ 10 |
+
+
+ | 76 |
+ R2736H2 |
+ LXS39 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516028 |
+ E |
+ 3 |
+ 2 |
+
+
+ | 77 |
+ R1978H2 |
+ LXS41 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1562224047 |
+ C |
+ 16 |
+ 8 |
+
+
+ | 78 |
+ R1783H2 |
+ LXS41 |
+ 56 |
+ M |
+ 26 |
+ 2 |
+ 1523516007 |
+ D |
+ 11 |
+ 6 |
+
+
+ | 79 |
+ R2822H2 |
+ LXS42 |
+ 66 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ F |
+ 23 |
+ 11 |
+
+
+ | 80 |
+ R2769H2 |
+ LXS42 |
+ 70 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ B |
+ 27 |
+ 12 |
+
+
+ | 81 |
+ R1974H2 |
+ LXS43 |
+ 84 |
+ F |
+ 26 |
+ 2 |
+ 1562224047 |
+ B |
+ 16 |
+ 8 |
+
+
+ | 82 |
+ R1733H2 |
+ LXS43 |
+ 72 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ C |
+ 10 |
+ 5 |
+
+
+ | 83 |
+ R1756H2 |
+ LXS46 |
+ 56 |
+ F |
+ 25 |
+ 2 |
+ 1523516007 |
+ B |
+ 11 |
+ 6 |
+
+
+ | 84 |
+ R1727H2 |
+ LXS46 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1523516032 |
+ D |
+ 7 |
+ 4 |
+
+
+ | 85 |
+ R1970H2 |
+ LXS48 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1562224032 |
+ F |
+ 15 |
+ 8 |
+
+
+ | 86 |
+ R1981H2 |
+ LXS48 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ C |
+ 27 |
+ 12 |
+
+
+ | 87 |
+ R1957H2 |
+ LXS49 |
+ 72 |
+ F |
+ 25 |
+ 2 |
+ 1523516029 |
+ C |
+ 14 |
+ 7 |
+
+
+ | 88 |
+ R2259H2 |
+ LXS49 |
+ 72 |
+ M |
+ 25 |
+ 2 |
+ 1523516028 |
+ C |
+ 3 |
+ 2 |
+
+
+ | 89 |
+ R2836H1 |
+ LXS5 |
+ 68 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ A |
+ 6 |
+ 3 |
+
+
+ | 90 |
+ R2213H2 |
+ LXS5 |
+ 80 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ F |
+ 20 |
+ 10 |
+
+
+ | 91 |
+ R2791H2 |
+ LXS50 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ A |
+ 23 |
+ 11 |
+
+
+ | 92 |
+ R1789H2 |
+ LXS50 |
+ 57 |
+ M |
+ 26 |
+ 2 |
+ 1523516033 |
+ A |
+ 8 |
+ 4 |
+
+
+ | 93 |
+ R1740H2 |
+ LXS51 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1523516032 |
+ F |
+ 7 |
+ 4 |
+
+
+ | 94 |
+ R1734H2 |
+ LXS51 |
+ 68 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ D |
+ 10 |
+ 5 |
+
+
+ | 95 |
+ R2786H2 |
+ LXS52 |
+ 61 |
+ F |
+ 27 |
+ 2 |
+ 1562224060 |
+ D |
+ 22 |
+ 10 |
+
+
+ | 96 |
+ R2768H2 |
+ LXS52 |
+ 61 |
+ M |
+ 27 |
+ 2 |
+ 1523516005 |
+ C |
+ 5 |
+ 3 |
+
+
+ | 97 |
+ R2154H2 |
+ LXS54 |
+ 70 |
+ F |
+ 27 |
+ 2 |
+ 1523516033 |
+ D |
+ 8 |
+ 4 |
+
+
+ | 98 |
+ R2155H2 |
+ LXS54 |
+ 70 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ A |
+ 20 |
+ 10 |
+
+
+ | 99 |
+ R1821H2 |
+ LXS55 |
+ 77 |
+ F |
+ 25 |
+ 2 |
+ 1523516009 |
+ C |
+ 12 |
+ 6 |
+
+
+ | 100 |
+ R1951H2 |
+ LXS55 |
+ 74 |
+ M |
+ 26 |
+ 2 |
+ 1523516024 |
+ F |
+ 13 |
+ 7 |
+
+
+ | 101 |
+ R2789H2 |
+ LXS56 |
+ 71 |
+ F |
+ 25 |
+ 2 |
+ 1523516005 |
+ F |
+ 5 |
+ 3 |
+
+
+ | 102 |
+ R2788H2 |
+ LXS56 |
+ 71 |
+ M |
+ 25 |
+ 2 |
+ 1562224060 |
+ F |
+ 22 |
+ 10 |
+
+
+ | 103 |
+ R2787H2 |
+ LXS59 |
+ 66 |
+ F |
+ 29 |
+ 2 |
+ 1562224060 |
+ E |
+ 22 |
+ 10 |
+
+
+ | 104 |
+ R2785H2 |
+ LXS59 |
+ 62 |
+ M |
+ 29 |
+ 2 |
+ 1523516005 |
+ E |
+ 5 |
+ 3 |
+
+
+ | 105 |
+ R1791H2 |
+ LXS60 |
+ 58 |
+ F |
+ 27 |
+ 2 |
+ 1562224038 |
+ D |
+ 25 |
+ 11 |
+
+
+ | 106 |
+ R1792H2 |
+ LXS60 |
+ 64 |
+ M |
+ 27 |
+ 2 |
+ 1523516007 |
+ E |
+ 11 |
+ 6 |
+
+
+ | 107 |
+ R1796H2 |
+ LXS62 |
+ 58 |
+ F |
+ 27 |
+ 2 |
+ 1523516007 |
+ F |
+ 11 |
+ 6 |
+
+
+ | 108 |
+ R1797H2 |
+ LXS62 |
+ 58 |
+ M |
+ 27 |
+ 2 |
+ 1562224038 |
+ E |
+ 25 |
+ 11 |
+
+
+ | 109 |
+ R2220H2 |
+ LXS64 |
+ 71 |
+ F |
+ 28 |
+ 2 |
+ 1523516001 |
+ F |
+ 9 |
+ 5 |
+
+
+ | 110 |
+ R2221H2 |
+ LXS64 |
+ 71 |
+ M |
+ 28 |
+ 2 |
+ 1562224054 |
+ B |
+ 21 |
+ 10 |
+
+
+ | 111 |
+ R1989H2 |
+ LXS66 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224036 |
+ B |
+ 17 |
+ 9 |
+
+
+ | 112 |
+ R1843H2 |
+ LXS66 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1523516009 |
+ E |
+ 12 |
+ 6 |
+
+
+ | 113 |
+ R2820H2 |
+ LXS68 |
+ 67 |
+ F |
+ 29 |
+ 2 |
+ 1523516003 |
+ E |
+ 1 |
+ 1 |
+
+
+ | 114 |
+ R2819H2 |
+ LXS68 |
+ 67 |
+ M |
+ 29 |
+ 2 |
+ 1562224034 |
+ E |
+ 23 |
+ 11 |
+
+
+ | 115 |
+ R1963H2 |
+ LXS7 |
+ 78 |
+ F |
+ 28 |
+ 2 |
+ 1562224032 |
+ B |
+ 15 |
+ 8 |
+
+
+ | 116 |
+ R1964H2 |
+ LXS7 |
+ 78 |
+ M |
+ 28 |
+ 2 |
+ 1562224032 |
+ C |
+ 15 |
+ 8 |
+
+
+ | 117 |
+ R2166H2 |
+ LXS70 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516033 |
+ F |
+ 8 |
+ 4 |
+
+
+ | 118 |
+ R2745H2 |
+ LXS70 |
+ 71 |
+ M |
+ 28 |
+ 2 |
+ 1562224054 |
+ F |
+ 21 |
+ 10 |
+
+
+ | 119 |
+ R2848H2 |
+ LXS72 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1562224038 |
+ A |
+ 25 |
+ 11 |
+
+
+ | 120 |
+ R1902H2 |
+ LXS72 |
+ 66 |
+ M |
+ 27 |
+ 2 |
+ 1523516024 |
+ A |
+ 13 |
+ 7 |
+
+
+ | 121 |
+ R2750H2 |
+ LXS73 |
+ 81 |
+ F |
+ 25 |
+ 2 |
+ 1523516030 |
+ D |
+ 4 |
+ 2 |
+
+
+ | 122 |
+ R1835H2 |
+ LXS73 |
+ 90 |
+ M |
+ 24 |
+ 2 |
+ 1523516009 |
+ D |
+ 12 |
+ 6 |
+
+
+ | 123 |
+ R1979H2 |
+ LXS75 |
+ 59 |
+ F |
+ 27 |
+ 2 |
+ 1562224047 |
+ D |
+ 16 |
+ 8 |
+
+
+ | 124 |
+ R2826H2 |
+ LXS75 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ F |
+ 1 |
+ 1 |
+
+
+ | 125 |
+ R2142H2 |
+ LXS76 |
+ 77 |
+ F |
+ 26 |
+ 2 |
+ 1562224050 |
+ E |
+ 19 |
+ 9 |
+
+
+ | 126 |
+ R1884H2 |
+ LXS76 |
+ 85 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ A |
+ 26 |
+ 12 |
+
+
+ | 127 |
+ R1959H2 |
+ LXS78 |
+ 69 |
+ F |
+ 26 |
+ 2 |
+ 1523516029 |
+ E |
+ 14 |
+ 7 |
+
+
+ | 128 |
+ R1958H2 |
+ LXS78 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516029 |
+ D |
+ 14 |
+ 7 |
+
+
+ | 129 |
+ R2845H1 |
+ LXS8 |
+ 70 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ C |
+ 6 |
+ 3 |
+
+
+ | 130 |
+ R2156H2 |
+ LXS8 |
+ 76 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ B |
+ 20 |
+ 10 |
+
+
+ | 131 |
+ R1955H2 |
+ LXS80 |
+ 71 |
+ F |
+ 25 |
+ 2 |
+ 1523516029 |
+ A |
+ 14 |
+ 7 |
+
+
+ | 132 |
+ R1956H2 |
+ LXS80 |
+ 71 |
+ M |
+ 25 |
+ 2 |
+ 1523516029 |
+ B |
+ 14 |
+ 7 |
+
+
+ | 133 |
+ R2830H1 |
+ LXS84 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ D |
+ 2 |
+ 1 |
+
+
+ | 134 |
+ R2829H2 |
+ LXS84 |
+ 66 |
+ M |
+ 26 |
+ 2 |
+ 1562224037 |
+ A |
+ 24 |
+ 11 |
+
+
+ | 135 |
+ R2839H2 |
+ LXS86 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ C |
+ 24 |
+ 11 |
+
+
+ | 136 |
+ R2838H1 |
+ LXS86 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516006 |
+ B |
+ 6 |
+ 3 |
+
+
+ | 137 |
+ R2882H1 |
+ LXS87 |
+ 66 |
+ F |
+ 27 |
+ 2 |
+ 1523516006 |
+ F |
+ 6 |
+ 3 |
+
+
+ | 138 |
+ R2744H2 |
+ LXS87 |
+ 71 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ E |
+ 21 |
+ 10 |
+
+
+ | 139 |
+ R2831H2 |
+ LXS88 |
+ 69 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ B |
+ 24 |
+ 11 |
+
+
+ | 140 |
+ R2762H2 |
+ LXS88 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1523516005 |
+ A |
+ 5 |
+ 3 |
+
+
+ | 141 |
+ R2828H1 |
+ LXS89 |
+ 75 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ C |
+ 2 |
+ 1 |
+
+
+ | 142 |
+ R1962H2 |
+ LXS89 |
+ 73 |
+ M |
+ 25 |
+ 2 |
+ 1562224032 |
+ A |
+ 15 |
+ 8 |
+
+
+ | 143 |
+ R1746H2 |
+ LXS9 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ F |
+ 10 |
+ 5 |
+
+
+ | 144 |
+ R2801H2 |
+ LXS9 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ D |
+ 1 |
+ 1 |
+
+
+ | 145 |
+ R1812H2 |
+ LXS90 |
+ 61 |
+ F |
+ 25 |
+ 2 |
+ 1562224038 |
+ F |
+ 25 |
+ 11 |
+
+
+ | 146 |
+ R1813H2 |
+ LXS90 |
+ 61 |
+ M |
+ 25 |
+ 2 |
+ 1523516009 |
+ A |
+ 12 |
+ 6 |
+
+
+ | 147 |
+ R1736H2 |
+ LXS92 |
+ 66 |
+ F |
+ 23 |
+ 2 |
+ 1523516015 |
+ E |
+ 10 |
+ 5 |
+
+
+ | 148 |
+ R1609H2 |
+ LXS92 |
+ 87 |
+ M |
+ 23 |
+ 2 |
+ 1523516032 |
+ A |
+ 7 |
+ 4 |
+
+
+ | 149 |
+ R1624H2 |
+ LXS93 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516032 |
+ B |
+ 7 |
+ 4 |
+
+
+ | 150 |
+ R1815H2 |
+ LXS93 |
+ 61 |
+ M |
+ 26 |
+ 2 |
+ 1523516009 |
+ B |
+ 12 |
+ 6 |
+
+
+ | 151 |
+ R1991H2 |
+ LXS94 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224036 |
+ C |
+ 17 |
+ 9 |
+
+
+ | 152 |
+ R2002H2 |
+ LXS94 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1562224049 |
+ B |
+ 18 |
+ 9 |
+
+
+ | 153 |
+ R1996H2 |
+ LXS96 |
+ 75 |
+ F |
+ 23 |
+ 2 |
+ 1562224036 |
+ F |
+ 17 |
+ 9 |
+
+
+ | 154 |
+ R1772H2 |
+ LXS96 |
+ 63 |
+ M |
+ 23 |
+ 2 |
+ 1523516007 |
+ C |
+ 11 |
+ 6 |
+
+
+ | 155 |
+ R2759H2 |
+ LXS97 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224060 |
+ B |
+ 22 |
+ 10 |
+
+
+ | 156 |
+ R2739H2 |
+ LXS97 |
+ 79 |
+ M |
+ 26 |
+ 2 |
+ 1523516028 |
+ F |
+ 3 |
+ 2 |
+
+
+ | 157 |
+ R2149H2 |
+ LXS98 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516033 |
+ C |
+ 8 |
+ 4 |
+
+
+ | 158 |
+ R1888H2 |
+ LXS98 |
+ 76 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ B |
+ 26 |
+ 12 |
+
+
+ | 159 |
+ R1644H2 |
+ LXS99 |
+ 79 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ B |
+ 10 |
+ 5 |
+
+
+ | 160 |
+ R2145H2 |
+ LXS99 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ F |
+ 19 |
+ 9 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Hipp_illumina_rankinv_0507/notes.rtf b/general/datasets/Hipp_illumina_rankinv_0507/notes.rtf
new file mode 100644
index 0000000..4ae3a03
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_0507/notes.rtf
@@ -0,0 +1 @@
+Data uploaded by Hongqiang Li, Oct 30, 2006. This text file originally generated by LL and RWW on November 29, 2006. Updated by LL, Dec 1, 2006. Updated March 25, April 25 by RWW.
diff --git a/general/datasets/Hipp_illumina_rankinv_0507/platform.rtf b/general/datasets/Hipp_illumina_rankinv_0507/platform.rtf
new file mode 100644
index 0000000..cb0e31f
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_0507/platform.rtf
@@ -0,0 +1,9 @@
+
+Illumina Sentrix Mouse-6 BeadArray Platform: The Mouse6 array consists of 46,116 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+Dunning M, Smith M, Thorne N, Tavare S (2006) beadarray: An R package to analyse Illumina BeadArrays. R News (the Newsletter of the P Project) 6:17-23. (see pages 17-23 of http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf).
+
+ANNOTATION: In spring of 2007, Robert W. Williams and Hongqiang Li reannotated the Illumina Mouse-6 array content. This new annotation is now incorporated into GeneNetwork. For 46166 probes on the Mouse 6 array platform (including control probes) we have identified 35975 NCBI Entrez Gene IDs; 26481 matched human Gene IDs; 23899 matched rat Gene IDs; 26883 NCBI HomoloGene IDs; and 12791 OMIM IDs.
+
+Position data for the 50-mer Illumina Mouse-6 array were initially downloaded from Sanger at http://www.sanger.ac.uk/Users/avc/Illumina/Mouse-6_V1.gff.gz but we then updated all positions by BLAT analysis from mm6 positions to mm8 positions (Hongqiang Li).
+
diff --git a/general/datasets/Hipp_illumina_rankinv_0507/processing.rtf b/general/datasets/Hipp_illumina_rankinv_0507/processing.rtf
new file mode 100644
index 0000000..678856e
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_0507/processing.rtf
@@ -0,0 +1,13 @@
+
+All data links (right-most column above) will be made active as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
+
+
+
+This data set uses the standard Rank Invariant method developed by Illumina and described in their BeadStation Studio documentation.
+
+Sex of the samples was validated using sex-specific probe set: Xist (probe ILM106520068, also known as scl00213742.1_141-S).
+
+
+
+Legend: Checking that the sex of samples was labeled correctly in mouse array data sets using Xist expression measured by probe ILM106520068. In this bar chart the expression of Xist is very low in LXS114 and has a low error term. This is because both arrays are male samples rather than 1 male and 1 female sample. In contrast LXS34 has very high expression and no error bar because the sample is from a single female pool.
+
diff --git a/general/datasets/Hipp_illumina_rankinv_0507/summary.rtf b/general/datasets/Hipp_illumina_rankinv_0507/summary.rtf
new file mode 100644
index 0000000..357e642
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_0507/summary.rtf
@@ -0,0 +1,14 @@
+ILLUMINA Mouse-6 DATA SET: The LXS Hippocampus Illumina Rank Invariant data set provides estimates of mRNA expression in the hippocampus of 75 LXS recombinant inbred strains, the two parental strains and ILS/Ibg and ISS/Ibg (Inbred Long Sleep and Inbred Short Sleep strains from the Institute of Behavioral Genetics).All samples are from normal adult control animals raised in a standard laboratory environment. Subsequent data sets will provide estimates of mRNA expression following restraint stress, ethanol treatment, and stress followed by ethanol using many of the same strains (Lu Lu and colleagues).
+
+A total of 240 pooled hippocampal samples were processed using 40 Illumina Sentrix Mouse-6 v 1.0 oligomer microarray (GEO GPL6099) BeadArray slides. Twenty-seven Mouse-6 slides and a total of 160 samples passed stringent quality control and error checking. We should note that this is our first experience using the Illumina platform and the initial set of 13 slides were are not included. This particular data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from 6.141 average (very low or no expression) to 19.987 (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this initial data set, 1170 probes have LRS values >46. The maximum LRS achieved in this data set is 358.8 for probe ILM103520706 (Disabled 1; Dab1).
+
+
+
+Legend: Bar chart of the expression of Dab1 probe ILM103520706 in the LXS data set. This probe has a Mendelian segregation pattern and is associated with a LOD score of 77.7 (LRS 358.8). The two parental strains are shown to the far left, followed by all of the LXS strains for which we have acquired mRNA expression estimates in the hippocampus.
+
+
+
+ABOUT THE HIPPOCAMPUS. The hippocampus is an important and intriguing part of the forebrain that is crucial in memory formation and retrieval. This region of the brain is particularly vulnerable to the effects of environmental stressors and is a key upstream modulator of the hypothalamic-pituitary-adrenal axis (the HPA). The hippocampus is also often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3) is a joint effort of 14 investigators supported by numerous agencies described in the Acknowledgments section.
+
diff --git a/general/datasets/Hipp_illumina_rankinv_0507/tissue.rtf b/general/datasets/Hipp_illumina_rankinv_0507/tissue.rtf
new file mode 100644
index 0000000..04565fc
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_0507/tissue.rtf
@@ -0,0 +1,7 @@
+
+All animals were raised at the IBG by Bennett and colleagues in an SPF facility. No cases were MHV positive. Mice were killed by cervical dislocation. Whole brain dissections were performed at the IBG by Bennett and colleagues and shipped in RNAlater to Lu Lu and colleagues at UTHSC. Most hippocampal dissections (all were bilateral) were performed by Zhiping Jia. Cerebella, olfactory bulbs, and brain stems were also dissected and stored at -80 deg C using further use. Hippocampal samples are very close to complete (see Lu et al., 2001 but probably include variable amounts of fimbria and choroid plexus (see expression of transthyretin, Ttr, as a marker of choroid plexus).
+
+A pool of dissected tissue from four hippocampi taken from two naive adults of the same strain, sex, and age was collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at UTHSC by Zhiping Jia.
+
+All animals used in this study were between 53 and 90 days of age (average of 72 days; see Table 1 below).
+
diff --git a/general/datasets/Hipp_illumina_rankinv_1006/acknowledgment.rtf b/general/datasets/Hipp_illumina_rankinv_1006/acknowledgment.rtf
new file mode 100644
index 0000000..959532f
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_1006/acknowledgment.rtf
@@ -0,0 +1,8 @@
+
+Data were generated with funds to Lu Lu, Beth Bennett, Mike Miles, Melloni Cook from INIA.
+
+
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513 (Lu Lu, PI)
+
+
diff --git a/general/datasets/Hipp_illumina_rankinv_1006/cases.rtf b/general/datasets/Hipp_illumina_rankinv_1006/cases.rtf
new file mode 100644
index 0000000..f3302c7
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_1006/cases.rtf
@@ -0,0 +1,5 @@
+
+The LXS genetic reference panel of recombinant inbred strains consists of just over 77 strains. All of these strains have been inbred for more than 23 generations (F23). All strains have been genotyped at 13,377 SNPs. Thanks to the efforts of Dr. Timothy Wiltshire at the Genome Institute of the Novartis Research Foundation, the two parental strains have been genotyped at 156,551 SNPs. These genotypes are incorporated in the GeneNetwork SNP Browser.
+
+Strains are currently available from Drs. Beth Bennett and Tom Johnson at the Institute of Behavioral Genetics (IBG) in Boulder Colorado.
+
diff --git a/general/datasets/Hipp_illumina_rankinv_1006/experiment-design.rtf b/general/datasets/Hipp_illumina_rankinv_1006/experiment-design.rtf
new file mode 100644
index 0000000..da9d781
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_1006/experiment-design.rtf
@@ -0,0 +1,2123 @@
+
+Sample Processing: Samples were processed by Lu Lu and colleagues in the Illumina Core at UTHSC between July 25 and Dec 20, 2006. All processing steps were performed by Feng Jiao. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on the original Mouse-6 v 1.0 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each strain. While all strains were orginally represented by matched male and female samples, one strain LXS34 consists of two female samples. Given the expression of Xist, we suspect that strain LXS114 is represented by two male pools (see figure at bottom of page).
+
+Experimental Design and Batch Structure: This data set consists arrays processed in 13 groups over a five month period (July 2006 to Dec 2006). Most groups consisted of 12 samples. All arrays in this data set were processed using a single protocol by a single operator, Feng Yiao. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between July 28 and Dec 21, 2006. Details on sample assignment to slides and batches is provide in the table below.
+
+
+This table lists all arrays by order of strain (index) and includes data on tube ID, strain, age, sex, F generation number, number of animals in each sample pool (pool size), slide ID, slide position (A through F), scan date, and scan batch.
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ gener-
+ ation |
+ pool
+ size |
+ slide
+ ID |
+ slide
+ position |
+ batch
+ by slide |
+ scan
+ batch |
+
+
+ | 1 |
+ R2851H2 |
+ ILS |
+ 77 |
+ F |
+ >100 |
+ 4 |
+ 1523516003 |
+ B |
+ 1 |
+ 1 |
+
+
+ | 2 |
+ R0595H2 |
+ ILS |
+ 71 |
+ F |
+ >100 |
+ 2 |
+ 1523516030 |
+ B |
+ 4 |
+ 2 |
+
+
+ | 3 |
+ R2874H2 |
+ ILS |
+ 78 |
+ M |
+ >100 |
+ 4 |
+ 1523516011 |
+ B |
+ 2 |
+ 1 |
+
+
+ | 4 |
+ R0585H2 |
+ ILS |
+ 65 |
+ M |
+ >100 |
+ 2 |
+ 1523516028 |
+ A |
+ 3 |
+ 2 |
+
+
+ | 5 |
+ R3281H1 |
+ ILSXISSF1 |
+ 90 |
+ F |
+ NA |
+ 3 |
+ 1562224029 |
+ A |
+ 28 |
+ 13 |
+
+
+ | 6 |
+ R2857H2 |
+ ISS |
+ 75 |
+ F |
+ >100 |
+ 4 |
+ 1523516011 |
+ A |
+ 2 |
+ 1 |
+
+
+ | 7 |
+ R0589H2 |
+ ISS |
+ 73 |
+ F |
+ >100 |
+ 2 |
+ 1523516028 |
+ B |
+ 3 |
+ 2 |
+
+
+ | 8 |
+ R2955H2 |
+ ISS |
+ 53 |
+ M |
+ >100 |
+ 3 |
+ 1523516003 |
+ A |
+ 1 |
+ 1 |
+
+
+ | 9 |
+ R0578H2 |
+ ISS |
+ 67 |
+ M |
+ >100 |
+ 2 |
+ 1523516030 |
+ A |
+ 4 |
+ 2 |
+
+
+ | 10 |
+ R3282H1 |
+ ISSXILSF1 |
+ 97 |
+ M |
+ NA |
+ 3 |
+ 1562224029 |
+ B |
+ 28 |
+ 13 |
+
+
+ | 11 |
+ R2013H2 |
+ LXS10 |
+ 84 |
+ F |
+ 27 |
+ 2 |
+ 1562224049 |
+ E |
+ 18 |
+ 9 |
+
+
+ | 12 |
+ R1993H2 |
+ LXS10 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1562224036 |
+ E |
+ 17 |
+ 9 |
+
+
+ | 13 |
+ R1997H2 |
+ LXS100 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ A |
+ 18 |
+ 9 |
+
+
+ | 14 |
+ R1983H2 |
+ LXS100 |
+ 77 |
+ M |
+ 25 |
+ 2 |
+ 1562224047 |
+ F |
+ 16 |
+ 8 |
+
+
+ | 15 |
+ R2083H2 |
+ LXS101 |
+ 85 |
+ F |
+ 28 |
+ 2 |
+ 1562224050 |
+ B |
+ 19 |
+ 9 |
+
+
+ | 16 |
+ R2084H2 |
+ LXS101 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224050 |
+ C |
+ 19 |
+ 9 |
+
+
+ | 17 |
+ R2186H2 |
+ LXS102 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1523516001 |
+ C |
+ 9 |
+ 5 |
+
+
+ | 18 |
+ R2187H2 |
+ LXS102 |
+ 73 |
+ M |
+ 29 |
+ 2 |
+ 1562224053 |
+ C |
+ 20 |
+ 10 |
+
+
+ | 19 |
+ R2809H2 |
+ LXS103 |
+ 72 |
+ F |
+ 26 |
+ 2 |
+ 1562224034 |
+ C |
+ 23 |
+ 11 |
+
+
+ | 20 |
+ R2854H1 |
+ LXS103 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516006 |
+ D |
+ 6 |
+ 3 |
+
+
+ | 21 |
+ R2735H2 |
+ LXS107 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516028 |
+ D |
+ 3 |
+ 2 |
+
+
+ | 22 |
+ R2738H2 |
+ LXS107 |
+ 78 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ C |
+ 21 |
+ 10 |
+
+
+ | 23 |
+ R2840H2 |
+ LXS110 |
+ 67 |
+ F |
+ 25 |
+ 2 |
+ 1562224037 |
+ D |
+ 24 |
+ 11 |
+
+
+ | 24 |
+ R2157H2 |
+ LXS110 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516033 |
+ E |
+ 8 |
+ 4 |
+
+
+ | 25 |
+ R2172H2 |
+ LXS112 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ B |
+ 9 |
+ 5 |
+
+
+ | 26 |
+ R2841H2 |
+ LXS112 |
+ 84 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ D |
+ 27 |
+ 12 |
+
+
+ | 27 |
+ R2188H2 |
+ LXS114 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224053 |
+ D |
+ 20 |
+ 10 |
+
+
+ | 28 |
+ R2204H2 |
+ LXS114 |
+ 72 |
+ M |
+ 28 |
+ 2 |
+ 1523516001 |
+ D |
+ 9 |
+ 5 |
+
+
+ | 29 |
+ R2168H2 |
+ LXS115 |
+ 80 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ A |
+ 9 |
+ 5 |
+
+
+ | 30 |
+ R2085H2 |
+ LXS115 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ D |
+ 19 |
+ 9 |
+
+
+ | 31 |
+ R2811H2 |
+ LXS117 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224034 |
+ D |
+ 23 |
+ 11 |
+
+
+ | 32 |
+ R2212H2 |
+ LXS117 |
+ 74 |
+ M |
+ 27 |
+ 2 |
+ 1523516001 |
+ E |
+ 9 |
+ 5 |
+
+
+ | 33 |
+ R1992H2 |
+ LXS122 |
+ 86 |
+ F |
+ 26 |
+ 2 |
+ 1562224036 |
+ D |
+ 17 |
+ 9 |
+
+
+ | 34 |
+ R2219H2 |
+ LXS122 |
+ 72 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ A |
+ 21 |
+ 10 |
+
+
+ | 35 |
+ R2876H2 |
+ LXS123 |
+ 87 |
+ F |
+ 28 |
+ 2 |
+ 1562224038 |
+ C |
+ 25 |
+ 11 |
+
+
+ | 36 |
+ R2832H1 |
+ LXS123 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1523516011 |
+ E |
+ 2 |
+ 1 |
+
+
+ | 37 |
+ R2872H1 |
+ LXS124 |
+ 83 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ E |
+ 6 |
+ 3 |
+
+
+ | 38 |
+ R2871H2 |
+ LXS124 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224042 |
+ F |
+ 27 |
+ 12 |
+
+
+ | 39 |
+ R1909H2 |
+ LXS13 |
+ 79 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ D |
+ 13 |
+ 7 |
+
+
+ | 40 |
+ R1901H2 |
+ LXS13 |
+ 81 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ D |
+ 26 |
+ 12 |
+
+
+ | 41 |
+ R2023H2 |
+ LXS14 |
+ 86 |
+ F |
+ 25 |
+ 2 |
+ 1562224050 |
+ A |
+ 19 |
+ 9 |
+
+
+ | 42 |
+ R1612H2 |
+ LXS14 |
+ 85 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ A |
+ 10 |
+ 5 |
+
+
+ | 43 |
+ R1936H2 |
+ LXS16 |
+ 81 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ E |
+ 13 |
+ 7 |
+
+
+ | 44 |
+ R1912H2 |
+ LXS16 |
+ 81 |
+ M |
+ 25 |
+ 2 |
+ 1523516033 |
+ B |
+ 8 |
+ 4 |
+
+
+ | 45 |
+ R1961H2 |
+ LXS19 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516029 |
+ F |
+ 14 |
+ 7 |
+
+
+ | 46 |
+ R1904H2 |
+ LXS19 |
+ 66 |
+ M |
+ 26 |
+ 2 |
+ 1523516024 |
+ B |
+ 13 |
+ 7 |
+
+
+ | 47 |
+ R1883H2 |
+ LXS2 |
+ 71 |
+ F |
+ 27 |
+ 2 |
+ 1523516009 |
+ F |
+ 12 |
+ 6 |
+
+
+ | 48 |
+ R2753H2 |
+ LXS2 |
+ 74 |
+ M |
+ 28 |
+ 2 |
+ 1523516030 |
+ E |
+ 4 |
+ 2 |
+
+
+ | 49 |
+ R1729H2 |
+ LXS22 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516032 |
+ E |
+ 7 |
+ 4 |
+
+
+ | 50 |
+ R2743H2 |
+ LXS22 |
+ 79 |
+ M |
+ 27 |
+ 2 |
+ 1562224054 |
+ D |
+ 21 |
+ 10 |
+
+
+ | 51 |
+ R1966H2 |
+ LXS23 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224032 |
+ D |
+ 15 |
+ 8 |
+
+
+ | 52 |
+ R1971H2 |
+ LXS23 |
+ 73 |
+ M |
+ 26 |
+ 2 |
+ 1562224047 |
+ A |
+ 16 |
+ 8 |
+
+
+ | 53 |
+ R2795H2 |
+ LXS24 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516003 |
+ C |
+ 1 |
+ 1 |
+
+
+ | 54 |
+ R1755H2 |
+ LXS24 |
+ 56 |
+ M |
+ 25 |
+ 2 |
+ 1523516007 |
+ A |
+ 11 |
+ 6 |
+
+
+ | 55 |
+ R1986H2 |
+ LXS25 |
+ 75 |
+ F |
+ 27 |
+ 2 |
+ 1562224036 |
+ A |
+ 17 |
+ 9 |
+
+
+ | 56 |
+ R2006H2 |
+ LXS25 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1562224049 |
+ C |
+ 18 |
+ 9 |
+
+
+ | 57 |
+ R2014H2 |
+ LXS26 |
+ 82 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ F |
+ 18 |
+ 9 |
+
+
+ | 58 |
+ R2009H2 |
+ LXS26 |
+ 82 |
+ M |
+ 26 |
+ 2 |
+ 1562224049 |
+ D |
+ 18 |
+ 9 |
+
+
+ | 59 |
+ R2824H1 |
+ LXS28 |
+ 67 |
+ F |
+ 28 |
+ 2 |
+ 1562224042 |
+ A |
+ 27 |
+ 12 |
+
+
+ | 60 |
+ R1753H1 |
+ LXS28 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1562224041 |
+ F |
+ 26 |
+ 12 |
+
+
+ | 61 |
+ R2765H2 |
+ LXS3 |
+ 63 |
+ F |
+ 27 |
+ 2 |
+ 1523516005 |
+ B |
+ 5 |
+ 3 |
+
+
+ | 62 |
+ R1898H2 |
+ LXS3 |
+ 81 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ C |
+ 26 |
+ 12 |
+
+
+ | 63 |
+ R2764H2 |
+ LXS31 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1562224060 |
+ C |
+ 22 |
+ 10 |
+
+
+ | 64 |
+ R1908H2 |
+ LXS31 |
+ 80 |
+ M |
+ 28 |
+ 2 |
+ 1523516024 |
+ C |
+ 13 |
+ 7 |
+
+
+ | 65 |
+ R2758H2 |
+ LXS32 |
+ 70 |
+ F |
+ 26 |
+ 2 |
+ 1523516030 |
+ F |
+ 4 |
+ 2 |
+
+
+ | 66 |
+ R1743H1 |
+ LXS32 |
+ 67 |
+ M |
+ 25 |
+ 2 |
+ 1562224041 |
+ E |
+ 26 |
+ 12 |
+
+
+ | 67 |
+ R2794H2 |
+ LXS34 |
+ 75 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ B |
+ 23 |
+ 11 |
+
+
+ | 68 |
+ R2870H2 |
+ LXS34 |
+ 78 |
+ F |
+ 27 |
+ 2 |
+ 1562224029 |
+ C |
+ 28 |
+ 13 |
+
+
+ | 69 |
+ R2746H2 |
+ LXS35 |
+ 80 |
+ F |
+ 22 |
+ 2 |
+ 1523516030 |
+ C |
+ 4 |
+ 2 |
+
+
+ | 70 |
+ R2747H2 |
+ LXS35 |
+ 81 |
+ M |
+ 22 |
+ 2 |
+ 1562224060 |
+ A |
+ 22 |
+ 10 |
+
+
+ | 71 |
+ R1968H2 |
+ LXS36 |
+ 76 |
+ F |
+ 25 |
+ 2 |
+ 1562224032 |
+ E |
+ 15 |
+ 8 |
+
+
+ | 72 |
+ R1640H2 |
+ LXS36 |
+ 76 |
+ M |
+ 25 |
+ 2 |
+ 1523516032 |
+ C |
+ 7 |
+ 4 |
+
+
+ | 73 |
+ R2835H1 |
+ LXS38 |
+ 67 |
+ F |
+ 27 |
+ 2 |
+ 1523516011 |
+ F |
+ 2 |
+ 1 |
+
+
+ | 74 |
+ R2842H2 |
+ LXS38 |
+ 67 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ E |
+ 27 |
+ 12 |
+
+
+ | 75 |
+ R2210H2 |
+ LXS39 |
+ 81 |
+ F |
+ 28 |
+ 2 |
+ 1562224053 |
+ E |
+ 20 |
+ 10 |
+
+
+ | 76 |
+ R2736H2 |
+ LXS39 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516028 |
+ E |
+ 3 |
+ 2 |
+
+
+ | 77 |
+ R1978H2 |
+ LXS41 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1562224047 |
+ C |
+ 16 |
+ 8 |
+
+
+ | 78 |
+ R1783H2 |
+ LXS41 |
+ 56 |
+ M |
+ 26 |
+ 2 |
+ 1523516007 |
+ D |
+ 11 |
+ 6 |
+
+
+ | 79 |
+ R2822H2 |
+ LXS42 |
+ 66 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ F |
+ 23 |
+ 11 |
+
+
+ | 80 |
+ R2769H2 |
+ LXS42 |
+ 70 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ B |
+ 27 |
+ 12 |
+
+
+ | 81 |
+ R1974H2 |
+ LXS43 |
+ 84 |
+ F |
+ 26 |
+ 2 |
+ 1562224047 |
+ B |
+ 16 |
+ 8 |
+
+
+ | 82 |
+ R1733H2 |
+ LXS43 |
+ 72 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ C |
+ 10 |
+ 5 |
+
+
+ | 83 |
+ R1756H2 |
+ LXS46 |
+ 56 |
+ F |
+ 25 |
+ 2 |
+ 1523516007 |
+ B |
+ 11 |
+ 6 |
+
+
+ | 84 |
+ R1727H2 |
+ LXS46 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1523516032 |
+ D |
+ 7 |
+ 4 |
+
+
+ | 85 |
+ R1970H2 |
+ LXS48 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1562224032 |
+ F |
+ 15 |
+ 8 |
+
+
+ | 86 |
+ R1981H2 |
+ LXS48 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ C |
+ 27 |
+ 12 |
+
+
+ | 87 |
+ R1957H2 |
+ LXS49 |
+ 72 |
+ F |
+ 25 |
+ 2 |
+ 1523516029 |
+ C |
+ 14 |
+ 7 |
+
+
+ | 88 |
+ R2259H2 |
+ LXS49 |
+ 72 |
+ M |
+ 25 |
+ 2 |
+ 1523516028 |
+ C |
+ 3 |
+ 2 |
+
+
+ | 89 |
+ R2836H1 |
+ LXS5 |
+ 68 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ A |
+ 6 |
+ 3 |
+
+
+ | 90 |
+ R2213H2 |
+ LXS5 |
+ 80 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ F |
+ 20 |
+ 10 |
+
+
+ | 91 |
+ R2791H2 |
+ LXS50 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ A |
+ 23 |
+ 11 |
+
+
+ | 92 |
+ R1789H2 |
+ LXS50 |
+ 57 |
+ M |
+ 26 |
+ 2 |
+ 1523516033 |
+ A |
+ 8 |
+ 4 |
+
+
+ | 93 |
+ R1740H2 |
+ LXS51 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1523516032 |
+ F |
+ 7 |
+ 4 |
+
+
+ | 94 |
+ R1734H2 |
+ LXS51 |
+ 68 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ D |
+ 10 |
+ 5 |
+
+
+ | 95 |
+ R2786H2 |
+ LXS52 |
+ 61 |
+ F |
+ 27 |
+ 2 |
+ 1562224060 |
+ D |
+ 22 |
+ 10 |
+
+
+ | 96 |
+ R2768H2 |
+ LXS52 |
+ 61 |
+ M |
+ 27 |
+ 2 |
+ 1523516005 |
+ C |
+ 5 |
+ 3 |
+
+
+ | 97 |
+ R2154H2 |
+ LXS54 |
+ 70 |
+ F |
+ 27 |
+ 2 |
+ 1523516033 |
+ D |
+ 8 |
+ 4 |
+
+
+ | 98 |
+ R2155H2 |
+ LXS54 |
+ 70 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ A |
+ 20 |
+ 10 |
+
+
+ | 99 |
+ R1821H2 |
+ LXS55 |
+ 77 |
+ F |
+ 25 |
+ 2 |
+ 1523516009 |
+ C |
+ 12 |
+ 6 |
+
+
+ | 100 |
+ R1951H2 |
+ LXS55 |
+ 74 |
+ M |
+ 26 |
+ 2 |
+ 1523516024 |
+ F |
+ 13 |
+ 7 |
+
+
+ | 101 |
+ R2789H2 |
+ LXS56 |
+ 71 |
+ F |
+ 25 |
+ 2 |
+ 1523516005 |
+ F |
+ 5 |
+ 3 |
+
+
+ | 102 |
+ R2788H2 |
+ LXS56 |
+ 71 |
+ M |
+ 25 |
+ 2 |
+ 1562224060 |
+ F |
+ 22 |
+ 10 |
+
+
+ | 103 |
+ R2787H2 |
+ LXS59 |
+ 66 |
+ F |
+ 29 |
+ 2 |
+ 1562224060 |
+ E |
+ 22 |
+ 10 |
+
+
+ | 104 |
+ R2785H2 |
+ LXS59 |
+ 62 |
+ M |
+ 29 |
+ 2 |
+ 1523516005 |
+ E |
+ 5 |
+ 3 |
+
+
+ | 105 |
+ R1791H2 |
+ LXS60 |
+ 58 |
+ F |
+ 27 |
+ 2 |
+ 1562224038 |
+ D |
+ 25 |
+ 11 |
+
+
+ | 106 |
+ R1792H2 |
+ LXS60 |
+ 64 |
+ M |
+ 27 |
+ 2 |
+ 1523516007 |
+ E |
+ 11 |
+ 6 |
+
+
+ | 107 |
+ R1796H2 |
+ LXS62 |
+ 58 |
+ F |
+ 27 |
+ 2 |
+ 1523516007 |
+ F |
+ 11 |
+ 6 |
+
+
+ | 108 |
+ R1797H2 |
+ LXS62 |
+ 58 |
+ M |
+ 27 |
+ 2 |
+ 1562224038 |
+ E |
+ 25 |
+ 11 |
+
+
+ | 109 |
+ R2220H2 |
+ LXS64 |
+ 71 |
+ F |
+ 28 |
+ 2 |
+ 1523516001 |
+ F |
+ 9 |
+ 5 |
+
+
+ | 110 |
+ R2221H2 |
+ LXS64 |
+ 71 |
+ M |
+ 28 |
+ 2 |
+ 1562224054 |
+ B |
+ 21 |
+ 10 |
+
+
+ | 111 |
+ R1989H2 |
+ LXS66 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224036 |
+ B |
+ 17 |
+ 9 |
+
+
+ | 112 |
+ R1843H2 |
+ LXS66 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1523516009 |
+ E |
+ 12 |
+ 6 |
+
+
+ | 113 |
+ R2820H2 |
+ LXS68 |
+ 67 |
+ F |
+ 29 |
+ 2 |
+ 1523516003 |
+ E |
+ 1 |
+ 1 |
+
+
+ | 114 |
+ R2819H2 |
+ LXS68 |
+ 67 |
+ M |
+ 29 |
+ 2 |
+ 1562224034 |
+ E |
+ 23 |
+ 11 |
+
+
+ | 115 |
+ R1963H2 |
+ LXS7 |
+ 78 |
+ F |
+ 28 |
+ 2 |
+ 1562224032 |
+ B |
+ 15 |
+ 8 |
+
+
+ | 116 |
+ R1964H2 |
+ LXS7 |
+ 78 |
+ M |
+ 28 |
+ 2 |
+ 1562224032 |
+ C |
+ 15 |
+ 8 |
+
+
+ | 117 |
+ R2166H2 |
+ LXS70 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516033 |
+ F |
+ 8 |
+ 4 |
+
+
+ | 118 |
+ R2745H2 |
+ LXS70 |
+ 71 |
+ M |
+ 28 |
+ 2 |
+ 1562224054 |
+ F |
+ 21 |
+ 10 |
+
+
+ | 119 |
+ R2848H2 |
+ LXS72 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1562224038 |
+ A |
+ 25 |
+ 11 |
+
+
+ | 120 |
+ R1902H2 |
+ LXS72 |
+ 66 |
+ M |
+ 27 |
+ 2 |
+ 1523516024 |
+ A |
+ 13 |
+ 7 |
+
+
+ | 121 |
+ R2750H2 |
+ LXS73 |
+ 81 |
+ F |
+ 25 |
+ 2 |
+ 1523516030 |
+ D |
+ 4 |
+ 2 |
+
+
+ | 122 |
+ R1835H2 |
+ LXS73 |
+ 90 |
+ M |
+ 24 |
+ 2 |
+ 1523516009 |
+ D |
+ 12 |
+ 6 |
+
+
+ | 123 |
+ R1979H2 |
+ LXS75 |
+ 59 |
+ F |
+ 27 |
+ 2 |
+ 1562224047 |
+ D |
+ 16 |
+ 8 |
+
+
+ | 124 |
+ R2826H2 |
+ LXS75 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ F |
+ 1 |
+ 1 |
+
+
+ | 125 |
+ R2142H2 |
+ LXS76 |
+ 77 |
+ F |
+ 26 |
+ 2 |
+ 1562224050 |
+ E |
+ 19 |
+ 9 |
+
+
+ | 126 |
+ R1884H2 |
+ LXS76 |
+ 85 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ A |
+ 26 |
+ 12 |
+
+
+ | 127 |
+ R1959H2 |
+ LXS78 |
+ 69 |
+ F |
+ 26 |
+ 2 |
+ 1523516029 |
+ E |
+ 14 |
+ 7 |
+
+
+ | 128 |
+ R1958H2 |
+ LXS78 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516029 |
+ D |
+ 14 |
+ 7 |
+
+
+ | 129 |
+ R2845H1 |
+ LXS8 |
+ 70 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ C |
+ 6 |
+ 3 |
+
+
+ | 130 |
+ R2156H2 |
+ LXS8 |
+ 76 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ B |
+ 20 |
+ 10 |
+
+
+ | 131 |
+ R1955H2 |
+ LXS80 |
+ 71 |
+ F |
+ 25 |
+ 2 |
+ 1523516029 |
+ A |
+ 14 |
+ 7 |
+
+
+ | 132 |
+ R1956H2 |
+ LXS80 |
+ 71 |
+ M |
+ 25 |
+ 2 |
+ 1523516029 |
+ B |
+ 14 |
+ 7 |
+
+
+ | 133 |
+ R2830H1 |
+ LXS84 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ D |
+ 2 |
+ 1 |
+
+
+ | 134 |
+ R2829H2 |
+ LXS84 |
+ 66 |
+ M |
+ 26 |
+ 2 |
+ 1562224037 |
+ A |
+ 24 |
+ 11 |
+
+
+ | 135 |
+ R2839H2 |
+ LXS86 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ C |
+ 24 |
+ 11 |
+
+
+ | 136 |
+ R2838H1 |
+ LXS86 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516006 |
+ B |
+ 6 |
+ 3 |
+
+
+ | 137 |
+ R2882H1 |
+ LXS87 |
+ 66 |
+ F |
+ 27 |
+ 2 |
+ 1523516006 |
+ F |
+ 6 |
+ 3 |
+
+
+ | 138 |
+ R2744H2 |
+ LXS87 |
+ 71 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ E |
+ 21 |
+ 10 |
+
+
+ | 139 |
+ R2831H2 |
+ LXS88 |
+ 69 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ B |
+ 24 |
+ 11 |
+
+
+ | 140 |
+ R2762H2 |
+ LXS88 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1523516005 |
+ A |
+ 5 |
+ 3 |
+
+
+ | 141 |
+ R2828H1 |
+ LXS89 |
+ 75 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ C |
+ 2 |
+ 1 |
+
+
+ | 142 |
+ R1962H2 |
+ LXS89 |
+ 73 |
+ M |
+ 25 |
+ 2 |
+ 1562224032 |
+ A |
+ 15 |
+ 8 |
+
+
+ | 143 |
+ R1746H2 |
+ LXS9 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ F |
+ 10 |
+ 5 |
+
+
+ | 144 |
+ R2801H2 |
+ LXS9 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ D |
+ 1 |
+ 1 |
+
+
+ | 145 |
+ R1812H2 |
+ LXS90 |
+ 61 |
+ F |
+ 25 |
+ 2 |
+ 1562224038 |
+ F |
+ 25 |
+ 11 |
+
+
+ | 146 |
+ R1813H2 |
+ LXS90 |
+ 61 |
+ M |
+ 25 |
+ 2 |
+ 1523516009 |
+ A |
+ 12 |
+ 6 |
+
+
+ | 147 |
+ R1736H2 |
+ LXS92 |
+ 66 |
+ F |
+ 23 |
+ 2 |
+ 1523516015 |
+ E |
+ 10 |
+ 5 |
+
+
+ | 148 |
+ R1609H2 |
+ LXS92 |
+ 87 |
+ M |
+ 23 |
+ 2 |
+ 1523516032 |
+ A |
+ 7 |
+ 4 |
+
+
+ | 149 |
+ R1624H2 |
+ LXS93 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516032 |
+ B |
+ 7 |
+ 4 |
+
+
+ | 150 |
+ R1815H2 |
+ LXS93 |
+ 61 |
+ M |
+ 26 |
+ 2 |
+ 1523516009 |
+ B |
+ 12 |
+ 6 |
+
+
+ | 151 |
+ R1991H2 |
+ LXS94 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224036 |
+ C |
+ 17 |
+ 9 |
+
+
+ | 152 |
+ R2002H2 |
+ LXS94 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1562224049 |
+ B |
+ 18 |
+ 9 |
+
+
+ | 153 |
+ R1996H2 |
+ LXS96 |
+ 75 |
+ F |
+ 23 |
+ 2 |
+ 1562224036 |
+ F |
+ 17 |
+ 9 |
+
+
+ | 154 |
+ R1772H2 |
+ LXS96 |
+ 63 |
+ M |
+ 23 |
+ 2 |
+ 1523516007 |
+ C |
+ 11 |
+ 6 |
+
+
+ | 155 |
+ R2759H2 |
+ LXS97 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224060 |
+ B |
+ 22 |
+ 10 |
+
+
+ | 156 |
+ R2739H2 |
+ LXS97 |
+ 79 |
+ M |
+ 26 |
+ 2 |
+ 1523516028 |
+ F |
+ 3 |
+ 2 |
+
+
+ | 157 |
+ R2149H2 |
+ LXS98 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516033 |
+ C |
+ 8 |
+ 4 |
+
+
+ | 158 |
+ R1888H2 |
+ LXS98 |
+ 76 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ B |
+ 26 |
+ 12 |
+
+
+ | 159 |
+ R1644H2 |
+ LXS99 |
+ 79 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ B |
+ 10 |
+ 5 |
+
+
+ | 160 |
+ R2145H2 |
+ LXS99 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ F |
+ 19 |
+ 9 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Hipp_illumina_rankinv_1006/notes.rtf b/general/datasets/Hipp_illumina_rankinv_1006/notes.rtf
new file mode 100644
index 0000000..4ae3a03
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_1006/notes.rtf
@@ -0,0 +1 @@
+Data uploaded by Hongqiang Li, Oct 30, 2006. This text file originally generated by LL and RWW on November 29, 2006. Updated by LL, Dec 1, 2006. Updated March 25, April 25 by RWW.
diff --git a/general/datasets/Hipp_illumina_rankinv_1006/platform.rtf b/general/datasets/Hipp_illumina_rankinv_1006/platform.rtf
new file mode 100644
index 0000000..cb0e31f
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_1006/platform.rtf
@@ -0,0 +1,9 @@
+
+Illumina Sentrix Mouse-6 BeadArray Platform: The Mouse6 array consists of 46,116 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+Dunning M, Smith M, Thorne N, Tavare S (2006) beadarray: An R package to analyse Illumina BeadArrays. R News (the Newsletter of the P Project) 6:17-23. (see pages 17-23 of http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf).
+
+ANNOTATION: In spring of 2007, Robert W. Williams and Hongqiang Li reannotated the Illumina Mouse-6 array content. This new annotation is now incorporated into GeneNetwork. For 46166 probes on the Mouse 6 array platform (including control probes) we have identified 35975 NCBI Entrez Gene IDs; 26481 matched human Gene IDs; 23899 matched rat Gene IDs; 26883 NCBI HomoloGene IDs; and 12791 OMIM IDs.
+
+Position data for the 50-mer Illumina Mouse-6 array were initially downloaded from Sanger at http://www.sanger.ac.uk/Users/avc/Illumina/Mouse-6_V1.gff.gz but we then updated all positions by BLAT analysis from mm6 positions to mm8 positions (Hongqiang Li).
+
diff --git a/general/datasets/Hipp_illumina_rankinv_1006/processing.rtf b/general/datasets/Hipp_illumina_rankinv_1006/processing.rtf
new file mode 100644
index 0000000..678856e
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_1006/processing.rtf
@@ -0,0 +1,13 @@
+
+All data links (right-most column above) will be made active as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
+
+
+
+This data set uses the standard Rank Invariant method developed by Illumina and described in their BeadStation Studio documentation.
+
+Sex of the samples was validated using sex-specific probe set: Xist (probe ILM106520068, also known as scl00213742.1_141-S).
+
+
+
+Legend: Checking that the sex of samples was labeled correctly in mouse array data sets using Xist expression measured by probe ILM106520068. In this bar chart the expression of Xist is very low in LXS114 and has a low error term. This is because both arrays are male samples rather than 1 male and 1 female sample. In contrast LXS34 has very high expression and no error bar because the sample is from a single female pool.
+
diff --git a/general/datasets/Hipp_illumina_rankinv_1006/summary.rtf b/general/datasets/Hipp_illumina_rankinv_1006/summary.rtf
new file mode 100644
index 0000000..357e642
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_1006/summary.rtf
@@ -0,0 +1,14 @@
+ILLUMINA Mouse-6 DATA SET: The LXS Hippocampus Illumina Rank Invariant data set provides estimates of mRNA expression in the hippocampus of 75 LXS recombinant inbred strains, the two parental strains and ILS/Ibg and ISS/Ibg (Inbred Long Sleep and Inbred Short Sleep strains from the Institute of Behavioral Genetics).All samples are from normal adult control animals raised in a standard laboratory environment. Subsequent data sets will provide estimates of mRNA expression following restraint stress, ethanol treatment, and stress followed by ethanol using many of the same strains (Lu Lu and colleagues).
+
+A total of 240 pooled hippocampal samples were processed using 40 Illumina Sentrix Mouse-6 v 1.0 oligomer microarray (GEO GPL6099) BeadArray slides. Twenty-seven Mouse-6 slides and a total of 160 samples passed stringent quality control and error checking. We should note that this is our first experience using the Illumina platform and the initial set of 13 slides were are not included. This particular data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from 6.141 average (very low or no expression) to 19.987 (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this initial data set, 1170 probes have LRS values >46. The maximum LRS achieved in this data set is 358.8 for probe ILM103520706 (Disabled 1; Dab1).
+
+
+
+Legend: Bar chart of the expression of Dab1 probe ILM103520706 in the LXS data set. This probe has a Mendelian segregation pattern and is associated with a LOD score of 77.7 (LRS 358.8). The two parental strains are shown to the far left, followed by all of the LXS strains for which we have acquired mRNA expression estimates in the hippocampus.
+
+
+
+ABOUT THE HIPPOCAMPUS. The hippocampus is an important and intriguing part of the forebrain that is crucial in memory formation and retrieval. This region of the brain is particularly vulnerable to the effects of environmental stressors and is a key upstream modulator of the hypothalamic-pituitary-adrenal axis (the HPA). The hippocampus is also often affected in epilepsy, Alzheimer's disease, and schizophrenia. Unlike most other parts of the brain, the hippocampus contains a remarkable population of stems cells that continue to generate neurons and glial cells even in adult mammals (Kempermann, 2005). This genetic analysis of transcript expression in the hippocampus (dentate gyrus, CA1-CA3) is a joint effort of 14 investigators supported by numerous agencies described in the Acknowledgments section.
+
diff --git a/general/datasets/Hipp_illumina_rankinv_1006/tissue.rtf b/general/datasets/Hipp_illumina_rankinv_1006/tissue.rtf
new file mode 100644
index 0000000..04565fc
--- /dev/null
+++ b/general/datasets/Hipp_illumina_rankinv_1006/tissue.rtf
@@ -0,0 +1,7 @@
+
+All animals were raised at the IBG by Bennett and colleagues in an SPF facility. No cases were MHV positive. Mice were killed by cervical dislocation. Whole brain dissections were performed at the IBG by Bennett and colleagues and shipped in RNAlater to Lu Lu and colleagues at UTHSC. Most hippocampal dissections (all were bilateral) were performed by Zhiping Jia. Cerebella, olfactory bulbs, and brain stems were also dissected and stored at -80 deg C using further use. Hippocampal samples are very close to complete (see Lu et al., 2001 but probably include variable amounts of fimbria and choroid plexus (see expression of transthyretin, Ttr, as a marker of choroid plexus).
+
+A pool of dissected tissue from four hippocampi taken from two naive adults of the same strain, sex, and age was collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at UTHSC by Zhiping Jia.
+
+All animals used in this study were between 53 and 90 days of age (average of 72 days; see Table 1 below).
+
diff --git a/general/datasets/Hlc_0311/acknowledgment.rtf b/general/datasets/Hlc_0311/acknowledgment.rtf
new file mode 100644
index 0000000..119d5f3
--- /dev/null
+++ b/general/datasets/Hlc_0311/acknowledgment.rtf
@@ -0,0 +1,6 @@
+Schadt EE, Molony C, Chudin E, Hao K, Yang X, Lum PY, Kasarskis A, Zhang B, Wang S, Suver C, Zhu J, Millstein J, Sieberts S, Lamb J, GuhaThakurta D, Derry J, Storey JD, Avila-Campillo I, Kruger MJ, Johnson JM, Rohl CA, van Nas A, Mehrabian M, Drake TA, Lusis AJ, Smith RC, Guengerich FP, Strom SC, Schuetz E, Rushmore TH, Ulrich R (2008) Mapping the genetic architecture of gene expression in human liver. PLoS Biol 6:e107. Full text
+
+Yang X, Zhang B, Molony C, Chudin E, Hao K, Zhu J, Gaedigk A, Suver C, Zhong H, Leeder JS, Guengerich FP, Strom SC, Schuetz E, Rushmore TH, Ulrich RG, Slatter JG, Schadt EE, Kasarskis A, Lum PY (2010) Systematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liver. Genome Res. 20:1020-36.
+
+GEO Series GSE9588
+Genotype data for 228 individuals who satisfy privacy policy have been submitted to the NCBI dbGaP (http://www.ncbi.nlm.nih.gov/gap/) under accession no. phs000253.v1.p1.]
diff --git a/general/datasets/Hlc_0311/citation.rtf b/general/datasets/Hlc_0311/citation.rtf
new file mode 100644
index 0000000..2cec619
--- /dev/null
+++ b/general/datasets/Hlc_0311/citation.rtf
@@ -0,0 +1 @@
+Schadt EE, Molony C, Chudin E, Hao K et al. Mapping the genetic architecture of gene expression in human liver. PLoS Biol 2008 May 6;6(5):e107. PMID: 18462017
diff --git a/general/datasets/Hlc_0311/contributors.rtf b/general/datasets/Hlc_0311/contributors.rtf
new file mode 100644
index 0000000..09251aa
--- /dev/null
+++ b/general/datasets/Hlc_0311/contributors.rtf
@@ -0,0 +1 @@
+Schadt EE, Molony C, Chudin E, Hao K, Yang X, Lum P, Kasarskis A, Zhang B, Wang S, Suver C, Zhu J, Millstein J, Sieberts S, Lamb J, Guhathakurta D, Derry J, Storey J, Mehrabian M, Drake TA, Lusis AJ, Smith R, Guengerich P, Strom SC, Schuetz E, Rushmore T, Ulrich R
diff --git a/general/datasets/Hlc_0311/experiment-design.rtf b/general/datasets/Hlc_0311/experiment-design.rtf
new file mode 100644
index 0000000..cae776a
--- /dev/null
+++ b/general/datasets/Hlc_0311/experiment-design.rtf
@@ -0,0 +1 @@
+Liver samples (1-2 g) were acquired from Caucasian individuals from three independent liver collections at tissue resource centers at Vanderbilt University, University of Pittsburg, and Merck Research Laboratories. All individuals were compared to a common pool created from equal portions of RNA from 191 (111 from Vanderbilt University and 80 from University of Pittsburg) samples.
diff --git a/general/datasets/Hlc_0311/experiment-type.rtf b/general/datasets/Hlc_0311/experiment-type.rtf
new file mode 100644
index 0000000..0546e04
--- /dev/null
+++ b/general/datasets/Hlc_0311/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array
\ No newline at end of file
diff --git a/general/datasets/Hlc_0311/platform.rtf b/general/datasets/Hlc_0311/platform.rtf
new file mode 100644
index 0000000..6687600
--- /dev/null
+++ b/general/datasets/Hlc_0311/platform.rtf
@@ -0,0 +1 @@
+Rosetta/Merck Human 44k 1.1 microarray
diff --git a/general/datasets/Hlc_0311/summary.rtf b/general/datasets/Hlc_0311/summary.rtf
new file mode 100644
index 0000000..d0282cd
--- /dev/null
+++ b/general/datasets/Hlc_0311/summary.rtf
@@ -0,0 +1,5 @@
+The Human Liver Cohort (HLC) study aimed to characterize the genetic architecture of gene expression in human liver using genotyping, gene expression profiling, and enzyme activity measurements of Cytochrom P450. The HLC was assembled from a total of 780 liver samples screened. These liver samples were acquired from caucasian individuals from three independant tissue collection centers. DNA samples were genotyped on the Affymetrix 500K SNP and Illumina 650Y SNP genotyping arrays representing a total of 782,476 unique single nucleotide polymorphisms (SNPs). Only the genotype data from those samples which were collected postmortem are accessible in dbGap. These 228 samples represent a subset of the 427 samples included in the Human Liver Cohort Publication (Schadt, Molony et al. 2008). RNA samples were profiled on a custom Agilent 44,000 feature microarray composed of 39,280 oligonucleotide probes targeting transcripts representing 34,266 known and predicted genes, including high-confidence, noncoding RNA sequences. Each of the liver samples was processed into cytosol and microsomes using a standard differential centrifugation method. The activities of nine P450 enzymes (CYP1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, and 3A4) in isolated microsomes from 398 HLC liver samples were measured in the microsome preparations using probe substrate metabolism assays expressed as nmol/min/mg protein. Each was measured with a single substrate except for the CYP3A4 activity that was measured using two substrates, midazolam and testosterone.
+
+To uncover the genetic determinants affecting expression in a metabolically active tissue relevant to the study of obesity, diabetes, atherosclerosis, and other common human diseases, we profiled 427 human liver samples on a comprehensive gene expression microarray targeting greater than 40,000 transcripts and genotyped DNA from each of these samples at greater than 1,000,000 SNPs. The relatively large sample size of this study and the large number of SNPs genotyped provided the means to assess the relationship between genetic variants and gene expression and it provided this look for the first time in a non-blood derived, metabolically active tissue. A comprehensive analysis of the liver gene expression traits revealed that thousands of these traits are under the control of well defined genetic loci, with many of the genes having already been implicated in a number of human diseases.
+
+Clincal data was requested, but not provided by submitter. Keywords: eQTL
diff --git a/general/datasets/Hlcf_0311/acknowledgment.rtf b/general/datasets/Hlcf_0311/acknowledgment.rtf
new file mode 100644
index 0000000..119d5f3
--- /dev/null
+++ b/general/datasets/Hlcf_0311/acknowledgment.rtf
@@ -0,0 +1,6 @@
+Schadt EE, Molony C, Chudin E, Hao K, Yang X, Lum PY, Kasarskis A, Zhang B, Wang S, Suver C, Zhu J, Millstein J, Sieberts S, Lamb J, GuhaThakurta D, Derry J, Storey JD, Avila-Campillo I, Kruger MJ, Johnson JM, Rohl CA, van Nas A, Mehrabian M, Drake TA, Lusis AJ, Smith RC, Guengerich FP, Strom SC, Schuetz E, Rushmore TH, Ulrich R (2008) Mapping the genetic architecture of gene expression in human liver. PLoS Biol 6:e107. Full text
+
+Yang X, Zhang B, Molony C, Chudin E, Hao K, Zhu J, Gaedigk A, Suver C, Zhong H, Leeder JS, Guengerich FP, Strom SC, Schuetz E, Rushmore TH, Ulrich RG, Slatter JG, Schadt EE, Kasarskis A, Lum PY (2010) Systematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liver. Genome Res. 20:1020-36.
+
+GEO Series GSE9588
+Genotype data for 228 individuals who satisfy privacy policy have been submitted to the NCBI dbGaP (http://www.ncbi.nlm.nih.gov/gap/) under accession no. phs000253.v1.p1.]
diff --git a/general/datasets/Hlcf_0311/citation.rtf b/general/datasets/Hlcf_0311/citation.rtf
new file mode 100644
index 0000000..2cec619
--- /dev/null
+++ b/general/datasets/Hlcf_0311/citation.rtf
@@ -0,0 +1 @@
+Schadt EE, Molony C, Chudin E, Hao K et al. Mapping the genetic architecture of gene expression in human liver. PLoS Biol 2008 May 6;6(5):e107. PMID: 18462017
diff --git a/general/datasets/Hlcf_0311/contributors.rtf b/general/datasets/Hlcf_0311/contributors.rtf
new file mode 100644
index 0000000..09251aa
--- /dev/null
+++ b/general/datasets/Hlcf_0311/contributors.rtf
@@ -0,0 +1 @@
+Schadt EE, Molony C, Chudin E, Hao K, Yang X, Lum P, Kasarskis A, Zhang B, Wang S, Suver C, Zhu J, Millstein J, Sieberts S, Lamb J, Guhathakurta D, Derry J, Storey J, Mehrabian M, Drake TA, Lusis AJ, Smith R, Guengerich P, Strom SC, Schuetz E, Rushmore T, Ulrich R
diff --git a/general/datasets/Hlcf_0311/experiment-design.rtf b/general/datasets/Hlcf_0311/experiment-design.rtf
new file mode 100644
index 0000000..cae776a
--- /dev/null
+++ b/general/datasets/Hlcf_0311/experiment-design.rtf
@@ -0,0 +1 @@
+Liver samples (1-2 g) were acquired from Caucasian individuals from three independent liver collections at tissue resource centers at Vanderbilt University, University of Pittsburg, and Merck Research Laboratories. All individuals were compared to a common pool created from equal portions of RNA from 191 (111 from Vanderbilt University and 80 from University of Pittsburg) samples.
diff --git a/general/datasets/Hlcf_0311/experiment-type.rtf b/general/datasets/Hlcf_0311/experiment-type.rtf
new file mode 100644
index 0000000..0546e04
--- /dev/null
+++ b/general/datasets/Hlcf_0311/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array
\ No newline at end of file
diff --git a/general/datasets/Hlcf_0311/platform.rtf b/general/datasets/Hlcf_0311/platform.rtf
new file mode 100644
index 0000000..6687600
--- /dev/null
+++ b/general/datasets/Hlcf_0311/platform.rtf
@@ -0,0 +1 @@
+Rosetta/Merck Human 44k 1.1 microarray
diff --git a/general/datasets/Hlcf_0311/summary.rtf b/general/datasets/Hlcf_0311/summary.rtf
new file mode 100644
index 0000000..d0282cd
--- /dev/null
+++ b/general/datasets/Hlcf_0311/summary.rtf
@@ -0,0 +1,5 @@
+The Human Liver Cohort (HLC) study aimed to characterize the genetic architecture of gene expression in human liver using genotyping, gene expression profiling, and enzyme activity measurements of Cytochrom P450. The HLC was assembled from a total of 780 liver samples screened. These liver samples were acquired from caucasian individuals from three independant tissue collection centers. DNA samples were genotyped on the Affymetrix 500K SNP and Illumina 650Y SNP genotyping arrays representing a total of 782,476 unique single nucleotide polymorphisms (SNPs). Only the genotype data from those samples which were collected postmortem are accessible in dbGap. These 228 samples represent a subset of the 427 samples included in the Human Liver Cohort Publication (Schadt, Molony et al. 2008). RNA samples were profiled on a custom Agilent 44,000 feature microarray composed of 39,280 oligonucleotide probes targeting transcripts representing 34,266 known and predicted genes, including high-confidence, noncoding RNA sequences. Each of the liver samples was processed into cytosol and microsomes using a standard differential centrifugation method. The activities of nine P450 enzymes (CYP1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, and 3A4) in isolated microsomes from 398 HLC liver samples were measured in the microsome preparations using probe substrate metabolism assays expressed as nmol/min/mg protein. Each was measured with a single substrate except for the CYP3A4 activity that was measured using two substrates, midazolam and testosterone.
+
+To uncover the genetic determinants affecting expression in a metabolically active tissue relevant to the study of obesity, diabetes, atherosclerosis, and other common human diseases, we profiled 427 human liver samples on a comprehensive gene expression microarray targeting greater than 40,000 transcripts and genotyped DNA from each of these samples at greater than 1,000,000 SNPs. The relatively large sample size of this study and the large number of SNPs genotyped provided the means to assess the relationship between genetic variants and gene expression and it provided this look for the first time in a non-blood derived, metabolically active tissue. A comprehensive analysis of the liver gene expression traits revealed that thousands of these traits are under the control of well defined genetic loci, with many of the genes having already been implicated in a number of human diseases.
+
+Clincal data was requested, but not provided by submitter. Keywords: eQTL
diff --git a/general/datasets/Hlcm_0311/acknowledgment.rtf b/general/datasets/Hlcm_0311/acknowledgment.rtf
new file mode 100644
index 0000000..119d5f3
--- /dev/null
+++ b/general/datasets/Hlcm_0311/acknowledgment.rtf
@@ -0,0 +1,6 @@
+Schadt EE, Molony C, Chudin E, Hao K, Yang X, Lum PY, Kasarskis A, Zhang B, Wang S, Suver C, Zhu J, Millstein J, Sieberts S, Lamb J, GuhaThakurta D, Derry J, Storey JD, Avila-Campillo I, Kruger MJ, Johnson JM, Rohl CA, van Nas A, Mehrabian M, Drake TA, Lusis AJ, Smith RC, Guengerich FP, Strom SC, Schuetz E, Rushmore TH, Ulrich R (2008) Mapping the genetic architecture of gene expression in human liver. PLoS Biol 6:e107. Full text
+
+Yang X, Zhang B, Molony C, Chudin E, Hao K, Zhu J, Gaedigk A, Suver C, Zhong H, Leeder JS, Guengerich FP, Strom SC, Schuetz E, Rushmore TH, Ulrich RG, Slatter JG, Schadt EE, Kasarskis A, Lum PY (2010) Systematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liver. Genome Res. 20:1020-36.
+
+GEO Series GSE9588
+Genotype data for 228 individuals who satisfy privacy policy have been submitted to the NCBI dbGaP (http://www.ncbi.nlm.nih.gov/gap/) under accession no. phs000253.v1.p1.]
diff --git a/general/datasets/Hlcm_0311/citation.rtf b/general/datasets/Hlcm_0311/citation.rtf
new file mode 100644
index 0000000..2cec619
--- /dev/null
+++ b/general/datasets/Hlcm_0311/citation.rtf
@@ -0,0 +1 @@
+Schadt EE, Molony C, Chudin E, Hao K et al. Mapping the genetic architecture of gene expression in human liver. PLoS Biol 2008 May 6;6(5):e107. PMID: 18462017
diff --git a/general/datasets/Hlcm_0311/contributors.rtf b/general/datasets/Hlcm_0311/contributors.rtf
new file mode 100644
index 0000000..09251aa
--- /dev/null
+++ b/general/datasets/Hlcm_0311/contributors.rtf
@@ -0,0 +1 @@
+Schadt EE, Molony C, Chudin E, Hao K, Yang X, Lum P, Kasarskis A, Zhang B, Wang S, Suver C, Zhu J, Millstein J, Sieberts S, Lamb J, Guhathakurta D, Derry J, Storey J, Mehrabian M, Drake TA, Lusis AJ, Smith R, Guengerich P, Strom SC, Schuetz E, Rushmore T, Ulrich R
diff --git a/general/datasets/Hlcm_0311/experiment-design.rtf b/general/datasets/Hlcm_0311/experiment-design.rtf
new file mode 100644
index 0000000..cae776a
--- /dev/null
+++ b/general/datasets/Hlcm_0311/experiment-design.rtf
@@ -0,0 +1 @@
+Liver samples (1-2 g) were acquired from Caucasian individuals from three independent liver collections at tissue resource centers at Vanderbilt University, University of Pittsburg, and Merck Research Laboratories. All individuals were compared to a common pool created from equal portions of RNA from 191 (111 from Vanderbilt University and 80 from University of Pittsburg) samples.
diff --git a/general/datasets/Hlcm_0311/experiment-type.rtf b/general/datasets/Hlcm_0311/experiment-type.rtf
new file mode 100644
index 0000000..5fe1af1
--- /dev/null
+++ b/general/datasets/Hlcm_0311/experiment-type.rtf
@@ -0,0 +1,6 @@
+
+RNA samples were profiled on a custom Agilent 44,000 feature microarray composed of 39,280 oligonucleotide probes targeting transcripts representing 34,266 known and predicted genes, including high-confidence, noncoding RNA sequences.
+
+
+
+
Each of the liver samples was processed into cytosol and microsomes using a standard differential centrifugation method. The activities of nine P450 enzymes (CYP1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, and 3A4) in isolated microsomes from 398 HLC liver samples were measured in the microsome preparations using probe substrate metabolism assays expressed as nmol/min/mg protein. Each was measured with a single substrate except for the CYP3A4 activity that was measured using two substrates, midazolam and testosterone.
diff --git a/general/datasets/Hlcm_0311/platform.rtf b/general/datasets/Hlcm_0311/platform.rtf
new file mode 100644
index 0000000..6687600
--- /dev/null
+++ b/general/datasets/Hlcm_0311/platform.rtf
@@ -0,0 +1 @@
+Rosetta/Merck Human 44k 1.1 microarray
diff --git a/general/datasets/Hlcm_0311/summary.rtf b/general/datasets/Hlcm_0311/summary.rtf
new file mode 100644
index 0000000..d0282cd
--- /dev/null
+++ b/general/datasets/Hlcm_0311/summary.rtf
@@ -0,0 +1,5 @@
+The Human Liver Cohort (HLC) study aimed to characterize the genetic architecture of gene expression in human liver using genotyping, gene expression profiling, and enzyme activity measurements of Cytochrom P450. The HLC was assembled from a total of 780 liver samples screened. These liver samples were acquired from caucasian individuals from three independant tissue collection centers. DNA samples were genotyped on the Affymetrix 500K SNP and Illumina 650Y SNP genotyping arrays representing a total of 782,476 unique single nucleotide polymorphisms (SNPs). Only the genotype data from those samples which were collected postmortem are accessible in dbGap. These 228 samples represent a subset of the 427 samples included in the Human Liver Cohort Publication (Schadt, Molony et al. 2008). RNA samples were profiled on a custom Agilent 44,000 feature microarray composed of 39,280 oligonucleotide probes targeting transcripts representing 34,266 known and predicted genes, including high-confidence, noncoding RNA sequences. Each of the liver samples was processed into cytosol and microsomes using a standard differential centrifugation method. The activities of nine P450 enzymes (CYP1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, and 3A4) in isolated microsomes from 398 HLC liver samples were measured in the microsome preparations using probe substrate metabolism assays expressed as nmol/min/mg protein. Each was measured with a single substrate except for the CYP3A4 activity that was measured using two substrates, midazolam and testosterone.
+
+To uncover the genetic determinants affecting expression in a metabolically active tissue relevant to the study of obesity, diabetes, atherosclerosis, and other common human diseases, we profiled 427 human liver samples on a comprehensive gene expression microarray targeting greater than 40,000 transcripts and genotyped DNA from each of these samples at greater than 1,000,000 SNPs. The relatively large sample size of this study and the large number of SNPs genotyped provided the means to assess the relationship between genetic variants and gene expression and it provided this look for the first time in a non-blood derived, metabolically active tissue. A comprehensive analysis of the liver gene expression traits revealed that thousands of these traits are under the control of well defined genetic loci, with many of the genes having already been implicated in a number of human diseases.
+
+Clincal data was requested, but not provided by submitter. Keywords: eQTL
diff --git a/general/datasets/Hms_mm8_mdp_spl_cd4_1116/contributors.rtf b/general/datasets/Hms_mm8_mdp_spl_cd4_1116/contributors.rtf
new file mode 100644
index 0000000..3908d41
--- /dev/null
+++ b/general/datasets/Hms_mm8_mdp_spl_cd4_1116/contributors.rtf
@@ -0,0 +1,8 @@
+Blair DA, Dustin ML, Shinton SA, Hardy RR, Shay T, Regev A, Cohen N, Brennan P, Brenner M, Kim F, Rao TN, Wagers A, Heng T, Ericson J, Rothamel K, Ortiz-Lopez A, Mathis D, Benoist C, Kreslavsky T, Fletcher A, Elpek K, Bellemare-Pelletier A, Malhotra D, Turley S, Miller J, Brown B, Merad M, Gautier EL, Jakubzick C, Randolph GJ, Monach P, Best AJ, Knell J, Goldrath A, Jojic V, Koller D, Laidlaw D, Collins J, Gazit R, Rossi DJ, Malhotra N, Sylvia K, Kang J, Bezman NA, Sun JC, Min-Oo G, Kim CC, Lanier LL.
+
+
+ - 1 Department of Computer Science, Stanford University, Stanford, CA 94305;
+ - 2 Division of Immunology, Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA 02115; and.
+ - 3 The Jackson Laboratory, Bar Harbor, ME 04609.
+ - 4 Division of Immunology, Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA 02115; and cbdm@hms.harvard.edu.
+
diff --git a/general/datasets/Hms_mm8_mdp_spl_cd4_1116/experiment-design.rtf b/general/datasets/Hms_mm8_mdp_spl_cd4_1116/experiment-design.rtf
new file mode 100644
index 0000000..29bf7fb
--- /dev/null
+++ b/general/datasets/Hms_mm8_mdp_spl_cd4_1116/experiment-design.rtf
@@ -0,0 +1 @@
+https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4201955/
diff --git a/general/datasets/Hms_mm8_mdp_spl_cd4_1116/specifics.rtf b/general/datasets/Hms_mm8_mdp_spl_cd4_1116/specifics.rtf
new file mode 100644
index 0000000..0b70afe
--- /dev/null
+++ b/general/datasets/Hms_mm8_mdp_spl_cd4_1116/specifics.rtf
@@ -0,0 +1 @@
+Gene Level
\ No newline at end of file
diff --git a/general/datasets/Hms_mm8_mdp_spl_cd4_1116/summary.rtf b/general/datasets/Hms_mm8_mdp_spl_cd4_1116/summary.rtf
new file mode 100644
index 0000000..c81e1bb
--- /dev/null
+++ b/general/datasets/Hms_mm8_mdp_spl_cd4_1116/summary.rtf
@@ -0,0 +1 @@
+To determine the breadth and underpinning of changes in immunocyte gene expression due to genetic variation in mice, we performed, as part of the Immunological Genome Project, gene expression profiling for CD4(+) T cells and neutrophils purified from 39 inbred strains of the Mouse Phenome Database. Considering both cell types, a large number of transcripts showed significant variation across the inbred strains, with 22% of the transcriptome varying by 2-fold or more. These included 119 loci with apparent complete loss of function, where the corresponding transcript was not expressed in some of the strains, representing a useful resource of "natural knockouts." We identified 1222 cis-expression quantitative trait loci (cis-eQTL) that control some of this variation. Most (60%) cis-eQTLs were shared between T cells and neutrophils, but a significant portion uniquely impacted one of the cell types, suggesting cell type-specific regulatory mechanisms. Using a conditional regression algorithm, we predicted regulatory interactions between transcription factors and potential targets, and we demonstrated that these predictions overlap with regulatory interactions inferred from transcriptional changes during immunocyte differentiation. Finally, comparison of these and parallel data from CD4(+) T cells of healthy humans demonstrated intriguing similarities in variability of a gene's expression: the most variable genes tended to be the same in both species, and there was an overlap in genes subject to strong cis-acting genetic variants. We speculate that this "conservation of variation" reflects a differential constraint on intraspecies variation in expression levels of different genes, either through lower pressure for some genes, or by favoring variability for others.
diff --git a/general/datasets/Hqfneoc_0208_rankinv/acknowledgment.rtf b/general/datasets/Hqfneoc_0208_rankinv/acknowledgment.rtf
new file mode 100644
index 0000000..3135d79
--- /dev/null
+++ b/general/datasets/Hqfneoc_0208_rankinv/acknowledgment.rtf
@@ -0,0 +1,6 @@
+Data were generated with funds to RW Williams, Glenn D. Rosen, Weikuan Gu, and Lu Lu from the High Q Foundation. Informatics support also provided by NIH NIAAA INIA grants to RWW and LL.
+
+
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513 (Lu Lu, PI)
+
diff --git a/general/datasets/Hqfneoc_0208_rankinv/cases.rtf b/general/datasets/Hqfneoc_0208_rankinv/cases.rtf
new file mode 100644
index 0000000..a98a7ff
--- /dev/null
+++ b/general/datasets/Hqfneoc_0208_rankinv/cases.rtf
@@ -0,0 +1,54 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 27 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 25 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 20 inbred strains and an F1 hybrid (B6D2F1). These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1
+ This F1 hybrid was generated by crossing C57BL/6J with DBA/2J.
+
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 strains are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hqfneoc_0208_rankinv/experiment-design.rtf b/general/datasets/Hqfneoc_0208_rankinv/experiment-design.rtf
new file mode 100644
index 0000000..322268a
--- /dev/null
+++ b/general/datasets/Hqfneoc_0208_rankinv/experiment-design.rtf
@@ -0,0 +1,937 @@
+This data set consists arrays processed in XX groups over a XX month period (from Month Year to Month Year). Most groups consisted of XX samples. All arrays in this data set were processed using a single protocol by a single operator, NAME HERE. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
+
+Error checking
+
+
+ - Checked for genotypes of BXD strains on all chromosomes using a battery of test Mendelian transcripts (transcripts with a Mendelian segregation pattern in the BXDs). Peak LRS of 260.2 for Prdx2 using Illumina probe ILM5340577. There are no errors in the strain assignment but there are possible genotyping errors, such as:
+ Thumpd1 (ILM7510148) in BXD34 using marker rs6271956
+ H2-D2 (ILM2190725) in BXD69 using marker gnf17.035.152
+ Fcer1g (ILM5550020) in BXD100 using marker rs3722740 (incorrectly scored as a heterozygote).
+
+ These genotype discrepancies are either due to recombination between the marker and the probe or a genotyping errors. (RWW, Feb 27, 2008)
+ - Total count of transcripts/probes with LOD greater than 10 is 1564 with 52 BXD strains (BXD1 through BXD43 from (n = 27) from JAX, and BXD43 through 100 (n = 25) from UTHSC).
+ - Sex assignment checked using Xist probe ILM104280446.
+ All female samples: Strains BXD43, BXD42, BXD68, BXD77, NZW/LacJ, and NZO/HlLtJ
+ All male samples: Strains BXD1, PWK/PhJ, BXD66, BXD97, BXD10, BXD75, BXD44, BXD89, BXD86, BXD80, BXD69
+
+
+Data Table 1:
+
+This table lists all arrays by order of strain (index) and includes data on strain, sex, slide ID and slide position (A through F).
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Sex |
+ Slide ID |
+ Slide
+ Position |
+
+
+ | 1 |
+ B6D2F1 |
+ F |
+ 1848071018 |
+ D |
+
+
+ | 2 |
+ B6D2F1 |
+ M |
+ 1957998076 |
+ B |
+
+
+ | 3 |
+ C57BL/6J |
+ F |
+ 1957998083 |
+ A |
+
+
+ | 4 |
+ C57BL/6J |
+ M |
+ 1833451021 |
+ A |
+
+
+ | 5 |
+ DBA/2J |
+ F |
+ 1957998083 |
+ C |
+
+
+ | 6 |
+ DBA/2J |
+ M |
+ 1833451021 |
+ C |
+
+
+ | 7 |
+ BXD1 |
+ M |
+ 4051964030 |
+ B |
+
+
+ | 8 |
+ BXD5 |
+ F |
+ 1736925307 |
+ A |
+
+
+ | 9 |
+ BXD5 |
+ M |
+ 4051964028 |
+ C |
+
+
+ | 10 |
+ BXD6 |
+ F |
+ 4051964028 |
+ F |
+
+
+ | 11 |
+ BXD6 |
+ M |
+ 1736925307 |
+ D |
+
+
+ | 12 |
+ BXD8 |
+ F |
+ 4060001025 |
+ A |
+
+
+ | 13 |
+ BXD8 |
+ M |
+ 1957998111 |
+ E |
+
+
+ | 14 |
+ BXD9 |
+ F |
+ 4060001025 |
+ D |
+
+
+ | 15 |
+ BXD9 |
+ M |
+ 1736925359 |
+ B |
+
+
+ | 16 |
+ BXD11 |
+ F |
+ 4051964030 |
+ D |
+
+
+ | 17 |
+ BXD11 |
+ M |
+ 1848071017 |
+ B |
+
+
+ | 18 |
+ BXD12 |
+ F |
+ 4051964030 |
+ E |
+
+
+ | 19 |
+ BXD12 |
+ M |
+ 1848071017 |
+ C |
+
+
+ | 20 |
+ BXD13 |
+ F |
+ 4051964030 |
+ F |
+
+
+ | 21 |
+ BXD13 |
+ M |
+ 1848071017 |
+ D |
+
+
+ | 22 |
+ BXD14 |
+ F |
+ 4051964065 |
+ A |
+
+
+ | 23 |
+ BXD14 |
+ M |
+ 1848071017 |
+ E |
+
+
+ | 24 |
+ BXD15 |
+ F |
+ 4051964065 |
+ B |
+
+
+ | 25 |
+ BXD15 |
+ M |
+ 1848071017 |
+ F |
+
+
+ | 26 |
+ BXD16 |
+ F |
+ 1848071024 |
+ A |
+
+
+ | 27 |
+ BXD16 |
+ M |
+ 4051964065 |
+ C |
+
+
+ | 28 |
+ BXD18 |
+ F |
+ 4051964065 |
+ D |
+
+
+ | 29 |
+ BXD18 |
+ M |
+ 1848071024 |
+ B |
+
+
+ | 30 |
+ BXD19 |
+ F |
+ 4051964065 |
+ E |
+
+
+ | 31 |
+ BXD19 |
+ M |
+ 1848071024 |
+ C |
+
+
+ | 32 |
+ BXD21 |
+ F |
+ 1848071024 |
+ D |
+
+
+ | 33 |
+ BXD21 |
+ M |
+ 4051964065 |
+ F |
+
+
+ | 34 |
+ BXD23 |
+ F |
+ 1848071024 |
+ E |
+
+
+ | 35 |
+ BXD23 |
+ M |
+ 4051964022 |
+ A |
+
+
+ | 36 |
+ BXD27 |
+ F |
+ 1848071024 |
+ F |
+
+
+ | 37 |
+ BXD27 |
+ M |
+ 4051964022 |
+ B |
+
+
+ | 38 |
+ BXD28 |
+ F |
+ 1848071025 |
+ A |
+
+
+ | 39 |
+ BXD28 |
+ M |
+ 4051964022 |
+ C |
+
+
+ | 40 |
+ BXD31 |
+ F |
+ 4051964022 |
+ D |
+
+
+ | 41 |
+ BXD31 |
+ M |
+ 1848071025 |
+ B |
+
+
+ | 42 |
+ BXD32 |
+ F |
+ 4051964022 |
+ E |
+
+
+ | 43 |
+ BXD32 |
+ M |
+ 1848071025 |
+ C |
+
+
+ | 44 |
+ BXD33 |
+ F |
+ 4051964022 |
+ F |
+
+
+ | 45 |
+ BXD33 |
+ M |
+ 1848071025 |
+ D |
+
+
+ | 46 |
+ BXD34 |
+ F |
+ 4051964023 |
+ A |
+
+
+ | 47 |
+ BXD34 |
+ M |
+ 1848071025 |
+ E |
+
+
+ | 48 |
+ BXD36 |
+ F |
+ 1848071025 |
+ F |
+
+
+ | 49 |
+ BXD36 |
+ M |
+ 4051964023 |
+ B |
+
+
+ | 50 |
+ BXD38 |
+ F |
+ 4051964023 |
+ C |
+
+
+ | 51 |
+ BXD38 |
+ M |
+ 1957998101 |
+ A |
+
+
+ | 52 |
+ BXD39 |
+ F |
+ 4051964023 |
+ D |
+
+
+ | 53 |
+ BXD39 |
+ M |
+ 1957998101 |
+ B |
+
+
+ | 54 |
+ BXD40 |
+ F |
+ 4051964023 |
+ E |
+
+
+ | 55 |
+ BXD40 |
+ M |
+ 1957998101 |
+ C |
+
+
+ | 56 |
+ BXD42 |
+ F |
+ 4060001026 |
+ B |
+
+
+ | 57 |
+ BXD43 |
+ F |
+ 1957998101 |
+ D |
+
+
+ | 58 |
+ BXD43 |
+ F |
+ 4051964023 |
+ F |
+
+
+ | 59 |
+ BXD44 |
+ F |
+ 1957998101 |
+ E |
+
+
+ | 60 |
+ BXD44 |
+ M |
+ 4051964028 |
+ A |
+
+
+ | 61 |
+ BXD45 |
+ F |
+ 4051964028 |
+ B |
+
+
+ | 62 |
+ BXD45 |
+ M |
+ 1957998101 |
+ F |
+
+
+ | 63 |
+ BXD51 |
+ F |
+ 4051964028 |
+ D |
+
+
+ | 64 |
+ BXD51 |
+ M |
+ 1736925307 |
+ B |
+
+
+ | 65 |
+ BXD55 |
+ F |
+ 1736925307 |
+ C |
+
+
+ | 66 |
+ BXD55 |
+ M |
+ 4051964028 |
+ E |
+
+
+ | 67 |
+ BXD60 |
+ F |
+ 4060001014 |
+ A |
+
+
+ | 68 |
+ BXD60 |
+ M |
+ 1736925307 |
+ E |
+
+
+ | 69 |
+ BXD61 |
+ F |
+ 4060001014 |
+ B |
+
+
+ | 70 |
+ BXD61 |
+ M |
+ 1736925307 |
+ F |
+
+
+ | 71 |
+ BXD62 |
+ F |
+ 4060001014 |
+ C |
+
+
+ | 72 |
+ BXD62 |
+ M |
+ 1957998111 |
+ A |
+
+
+ | 73 |
+ BXD65 |
+ F |
+ 1957998111 |
+ B |
+
+
+ | 74 |
+ BXD65 |
+ M |
+ 4060001014 |
+ D |
+
+
+ | 75 |
+ BXD66 |
+ M |
+ 4060001026 |
+ C |
+
+
+ | 76 |
+ BXD68 |
+ F |
+ 4060001026 |
+ D |
+
+
+ | 77 |
+ BXD69 |
+ M |
+ 1957998111 |
+ C |
+
+
+ | 78 |
+ BXD69 |
+ M |
+ 4060001014 |
+ E |
+
+
+ | 79 |
+ BXD70 |
+ M |
+ 4060001026 |
+ E |
+
+
+ | 80 |
+ BXD73 |
+ F |
+ 1957998111 |
+ D |
+
+
+ | 81 |
+ BXD73 |
+ M |
+ 4060001014 |
+ F |
+
+
+ | 82 |
+ BXD75 |
+ M |
+ 4060001026 |
+ F |
+
+
+ | 83 |
+ BXD77 |
+ F |
+ 4060001027 |
+ A |
+
+
+ | 84 |
+ BXD80 |
+ M |
+ 4060001027 |
+ B |
+
+
+ | 85 |
+ BXD84 |
+ F |
+ 1957998111 |
+ F |
+
+
+ | 86 |
+ BXD84 |
+ M |
+ 4060001025 |
+ B |
+
+
+ | 87 |
+ BXD86 |
+ M |
+ 4060001027 |
+ C |
+
+
+ | 88 |
+ BXD87 |
+ F |
+ 4060001027 |
+ F |
+
+
+ | 89 |
+ BXD87 |
+ M |
+ 4060001025 |
+ C |
+
+
+ | 90 |
+ BXD89 |
+ M |
+ 4060001027 |
+ D |
+
+
+ | 91 |
+ BXD90 |
+ F |
+ 1736925359 |
+ C |
+
+
+ | 92 |
+ BXD90 |
+ M |
+ 4060001025 |
+ E |
+
+
+ | 93 |
+ BXD96 |
+ F |
+ 4060001025 |
+ F |
+
+
+ | 94 |
+ BXD96 |
+ M |
+ 1736925359 |
+ D |
+
+
+ | 95 |
+ BXD97 |
+ M |
+ 4060001027 |
+ E |
+
+
+ | 96 |
+ BXD100 |
+ F |
+ 1848071017 |
+ A |
+
+
+ | 97 |
+ BXD100 |
+ M |
+ 4051964030 |
+ C |
+
+
+ | 98 |
+ 129S1/SvImJ |
+ F |
+ 1736925359 |
+ E |
+
+
+ | 99 |
+ 129S1/SvImJ |
+ M |
+ 1848071018 |
+ A |
+
+
+ | 100 |
+ A/J |
+ F |
+ 1848071018 |
+ B |
+
+
+ | 101 |
+ A/J |
+ M |
+ 1736925359 |
+ F |
+
+
+ | 102 |
+ AKR/J |
+ F |
+ 1848071018 |
+ C |
+
+
+ | 103 |
+ AKR/J |
+ M |
+ 1957998076 |
+ A |
+
+
+ | 104 |
+ BALB/cByJ |
+ F |
+ 1957998076 |
+ C |
+
+
+ | 105 |
+ BALB/cByJ |
+ M |
+ 1953348019 |
+ A |
+
+
+ | 106 |
+ C3H/HeJ |
+ F |
+ 1953348019 |
+ D |
+
+
+ | 107 |
+ C3H/HeJ |
+ M |
+ 1957998076 |
+ F |
+
+
+ | 108 |
+ CAST/EiJ |
+ F |
+ 1833451021 |
+ B |
+
+
+ | 109 |
+ CAST/EiJ |
+ M |
+ 1957998083 |
+ B |
+
+
+ | 110 |
+ KK/HlJ |
+ F |
+ 1957998083 |
+ E |
+
+
+ | 111 |
+ KK/HlJ |
+ M |
+ 1848071023 |
+ F |
+
+
+ | 112 |
+ BXSB/MpJ |
+ F |
+ 1957998076 |
+ E |
+
+
+ | 113 |
+ BXSB/MpJ |
+ M |
+ 1953348019 |
+ C |
+
+
+ | 114 |
+ FVB/NJ |
+ F |
+ 1833451021 |
+ D |
+
+
+ | 115 |
+ FVB/NJ |
+ M |
+ 1957998083 |
+ D |
+
+
+ | 116 |
+ MOLF/EiJ |
+ F |
+ 1957998083 |
+ F |
+
+
+ | 117 |
+ MOLF/EiJ |
+ M |
+ 1848071001 |
+ B |
+
+
+ | 118 |
+ NOD/LtJ |
+ F |
+ 1848071001 |
+ C |
+
+
+ | 119 |
+ NOD/LtJ |
+ M |
+ 4060001004 |
+ A |
+
+
+ | 120 |
+ NZB/BlNJ |
+ F |
+ 4060001004 |
+ B |
+
+
+ | 121 |
+ NZB/BlNJ |
+ M |
+ 1848071001 |
+ D |
+
+
+ | 122 |
+ NZO/HlLtJ |
+ F |
+ 4060001004 |
+ C |
+
+
+ | 123 |
+ NZW/LacJ |
+ F |
+ 4060001004 |
+ D |
+
+
+ | 124 |
+ PWD/PhJ |
+ F |
+ 4060001004 |
+ E |
+
+
+ | 125 |
+ PWK/PhJ |
+ M |
+ 4060001004 |
+ F |
+
+
+ | 126 |
+ WSB/EiJ |
+ F |
+ 4051964030 |
+ A |
+
+
+ | 127 |
+ BTBRT<+>tf/J |
+ F |
+ 1957998076 |
+ D |
+
+
+ | 128 |
+ BTBRT<+>tf/J |
+ M |
+ 1953348019 |
+ B |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hqfneoc_0208_rankinv/experiment-type.rtf b/general/datasets/Hqfneoc_0208_rankinv/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Hqfneoc_0208_rankinv/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Hqfneoc_0208_rankinv/platform.rtf b/general/datasets/Hqfneoc_0208_rankinv/platform.rtf
new file mode 100644
index 0000000..f0c5210
--- /dev/null
+++ b/general/datasets/Hqfneoc_0208_rankinv/platform.rtf
@@ -0,0 +1,7 @@
+Illumina Sentrix Mouse-6.1 BeadArray Platform (ILM6v1.1): The Mouse6.1 array consists of 46,643 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+Dunning M, Smith M, Thorne N, Tavare S (2006) beadarray: An R package to analyse Illumina BeadArrays. R News (the Newsletter of the P Project) 6:17-23. (see pages 17-23 of http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf).
+
+ANNOTATION: In summer of 2008, Xusheng Wang and Robert W. Williams reannotated the Illumina Mouse-6.1 array content. This new annotation is now incorporated into GeneNetwork. For 46643 probes on the Mouse 6.1 array platform (including control probes) we have identified XXXXX NCBI Entrez Gene IDs; XXXXX matched human Gene IDs; XXXXX matched rat Gene IDs; XXXXX NCBI HomoloGene IDs; and XXXXX OMIM IDs.
+
+Position data for the 50-mer Illumina Mouse-6 array were initially downloaded from Sanger at http://www.sanger.ac.uk/Users/avc/Illumina/Mouse-6_V1.gff.gz but we then updated all positions by BLAT analysis from mm6 positions to mm8 positions (Hongqiang Li).
diff --git a/general/datasets/Hqfneoc_0208_rankinv/processing.rtf b/general/datasets/Hqfneoc_0208_rankinv/processing.rtf
new file mode 100644
index 0000000..895fa91
--- /dev/null
+++ b/general/datasets/Hqfneoc_0208_rankinv/processing.rtf
@@ -0,0 +1,3 @@
+This data set uses the standard Rank Invariant method developed by Illumina and described in their BeadStation Studio documentation.
+
+Sex of the samples was validated using sex-specific probe set: Xist probe ILM104280446.
diff --git a/general/datasets/Hqfneoc_0208_rankinv/summary.rtf b/general/datasets/Hqfneoc_0208_rankinv/summary.rtf
new file mode 100644
index 0000000..ca42527
--- /dev/null
+++ b/general/datasets/Hqfneoc_0208_rankinv/summary.rtf
@@ -0,0 +1,16 @@
+The February 2008 High Q Foundation Neocortex data set provides estimates of mRNA expression in the cerebral cortex of 73 lines of mice, including 52 BXD strains, 20 standard inbred strains, and B6D2F1 isogenic hybrids. All samples are from normal adult control animals raised in a standard laboratory environment. All data were generated with funds provided by the High Q Foundation using the Illumina Mouse 6.1 bead array (the second version of the Illumina Mouse-6 platform).
+
+While this February data release is still a provisional, we are not aware of any specific errors.
+
+
+
+A total of 129 pooled neocortex samples were processed using approximately XX Illumina Sentrix Mouse-6.1 oligomer microarray BeadArray slides. XX Mouse-6.1 slides and a total of 128 samples passed stringent quality control and error checking. This data set is a companion to the High Q Foundation Striatum data set and was processed using very closely matched methods and most of the same samples. This is our third large data set generated using the Illumina platform. This particular data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Illumina (Feb 08) RankInv data set, 1564 probes have LRS values >46 (LOD >10).
+
+Users of these mouse neocortex data may also find the following complementary resources and papers useful:
+
+
+ - Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
+ - A movie of the dissection of the brain by Dr. Glenn Rosen.
+
diff --git a/general/datasets/Hqfneoc_0208_rankinv/tissue.rtf b/general/datasets/Hqfneoc_0208_rankinv/tissue.rtf
new file mode 100644
index 0000000..48d0a2c
--- /dev/null
+++ b/general/datasets/Hqfneoc_0208_rankinv/tissue.rtf
@@ -0,0 +1,9 @@
+All animals were raised at the Jackson Laboratory or at UTHSC in SPF facilities. All mice were killed by cervical dislocation. Whole brain dissections were performed at either Beth Israel Deaconess Medical Center by Glenn Rosen or at UTHSC by Lu Lu and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
+
+A pool of dissected neocortical tissue from two to three naive adults of the same strain, sex, and age was collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at UTHSC by Zhiping Jia (CHECK LAST STATEMENT WITH LU).
+
+All animals used in this study were between XX and XX days of age (average of XX days; see Table 1 below). All animals were sacrifice between 9 AM and 5 PM during the light phase.
+
+Sample Processing: Samples were processed by Lu Lu and colleagues in the Illumina Core at UTHSC between December 2007 and January 2008. All processing steps were performed by Feng Jiao. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from as many strains as possible. However, a number of strains are represented by samples from a single sex (see figure at bottom of page).
diff --git a/general/datasets/Hqfneoc_1210_rankinv/acknowledgment.rtf b/general/datasets/Hqfneoc_1210_rankinv/acknowledgment.rtf
new file mode 100644
index 0000000..3135d79
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210_rankinv/acknowledgment.rtf
@@ -0,0 +1,6 @@
+Data were generated with funds to RW Williams, Glenn D. Rosen, Weikuan Gu, and Lu Lu from the High Q Foundation. Informatics support also provided by NIH NIAAA INIA grants to RWW and LL.
+
+
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513 (Lu Lu, PI)
+
diff --git a/general/datasets/Hqfneoc_1210_rankinv/cases.rtf b/general/datasets/Hqfneoc_1210_rankinv/cases.rtf
new file mode 100644
index 0000000..a98a7ff
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210_rankinv/cases.rtf
@@ -0,0 +1,54 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 27 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 25 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 20 inbred strains and an F1 hybrid (B6D2F1). These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1
+ This F1 hybrid was generated by crossing C57BL/6J with DBA/2J.
+
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 strains are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hqfneoc_1210_rankinv/experiment-design.rtf b/general/datasets/Hqfneoc_1210_rankinv/experiment-design.rtf
new file mode 100644
index 0000000..322268a
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210_rankinv/experiment-design.rtf
@@ -0,0 +1,937 @@
+This data set consists arrays processed in XX groups over a XX month period (from Month Year to Month Year). Most groups consisted of XX samples. All arrays in this data set were processed using a single protocol by a single operator, NAME HERE. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
+
+Error checking
+
+
+ - Checked for genotypes of BXD strains on all chromosomes using a battery of test Mendelian transcripts (transcripts with a Mendelian segregation pattern in the BXDs). Peak LRS of 260.2 for Prdx2 using Illumina probe ILM5340577. There are no errors in the strain assignment but there are possible genotyping errors, such as:
+ Thumpd1 (ILM7510148) in BXD34 using marker rs6271956
+ H2-D2 (ILM2190725) in BXD69 using marker gnf17.035.152
+ Fcer1g (ILM5550020) in BXD100 using marker rs3722740 (incorrectly scored as a heterozygote).
+
+ These genotype discrepancies are either due to recombination between the marker and the probe or a genotyping errors. (RWW, Feb 27, 2008)
+ - Total count of transcripts/probes with LOD greater than 10 is 1564 with 52 BXD strains (BXD1 through BXD43 from (n = 27) from JAX, and BXD43 through 100 (n = 25) from UTHSC).
+ - Sex assignment checked using Xist probe ILM104280446.
+ All female samples: Strains BXD43, BXD42, BXD68, BXD77, NZW/LacJ, and NZO/HlLtJ
+ All male samples: Strains BXD1, PWK/PhJ, BXD66, BXD97, BXD10, BXD75, BXD44, BXD89, BXD86, BXD80, BXD69
+
+
+Data Table 1:
+
+This table lists all arrays by order of strain (index) and includes data on strain, sex, slide ID and slide position (A through F).
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Sex |
+ Slide ID |
+ Slide
+ Position |
+
+
+ | 1 |
+ B6D2F1 |
+ F |
+ 1848071018 |
+ D |
+
+
+ | 2 |
+ B6D2F1 |
+ M |
+ 1957998076 |
+ B |
+
+
+ | 3 |
+ C57BL/6J |
+ F |
+ 1957998083 |
+ A |
+
+
+ | 4 |
+ C57BL/6J |
+ M |
+ 1833451021 |
+ A |
+
+
+ | 5 |
+ DBA/2J |
+ F |
+ 1957998083 |
+ C |
+
+
+ | 6 |
+ DBA/2J |
+ M |
+ 1833451021 |
+ C |
+
+
+ | 7 |
+ BXD1 |
+ M |
+ 4051964030 |
+ B |
+
+
+ | 8 |
+ BXD5 |
+ F |
+ 1736925307 |
+ A |
+
+
+ | 9 |
+ BXD5 |
+ M |
+ 4051964028 |
+ C |
+
+
+ | 10 |
+ BXD6 |
+ F |
+ 4051964028 |
+ F |
+
+
+ | 11 |
+ BXD6 |
+ M |
+ 1736925307 |
+ D |
+
+
+ | 12 |
+ BXD8 |
+ F |
+ 4060001025 |
+ A |
+
+
+ | 13 |
+ BXD8 |
+ M |
+ 1957998111 |
+ E |
+
+
+ | 14 |
+ BXD9 |
+ F |
+ 4060001025 |
+ D |
+
+
+ | 15 |
+ BXD9 |
+ M |
+ 1736925359 |
+ B |
+
+
+ | 16 |
+ BXD11 |
+ F |
+ 4051964030 |
+ D |
+
+
+ | 17 |
+ BXD11 |
+ M |
+ 1848071017 |
+ B |
+
+
+ | 18 |
+ BXD12 |
+ F |
+ 4051964030 |
+ E |
+
+
+ | 19 |
+ BXD12 |
+ M |
+ 1848071017 |
+ C |
+
+
+ | 20 |
+ BXD13 |
+ F |
+ 4051964030 |
+ F |
+
+
+ | 21 |
+ BXD13 |
+ M |
+ 1848071017 |
+ D |
+
+
+ | 22 |
+ BXD14 |
+ F |
+ 4051964065 |
+ A |
+
+
+ | 23 |
+ BXD14 |
+ M |
+ 1848071017 |
+ E |
+
+
+ | 24 |
+ BXD15 |
+ F |
+ 4051964065 |
+ B |
+
+
+ | 25 |
+ BXD15 |
+ M |
+ 1848071017 |
+ F |
+
+
+ | 26 |
+ BXD16 |
+ F |
+ 1848071024 |
+ A |
+
+
+ | 27 |
+ BXD16 |
+ M |
+ 4051964065 |
+ C |
+
+
+ | 28 |
+ BXD18 |
+ F |
+ 4051964065 |
+ D |
+
+
+ | 29 |
+ BXD18 |
+ M |
+ 1848071024 |
+ B |
+
+
+ | 30 |
+ BXD19 |
+ F |
+ 4051964065 |
+ E |
+
+
+ | 31 |
+ BXD19 |
+ M |
+ 1848071024 |
+ C |
+
+
+ | 32 |
+ BXD21 |
+ F |
+ 1848071024 |
+ D |
+
+
+ | 33 |
+ BXD21 |
+ M |
+ 4051964065 |
+ F |
+
+
+ | 34 |
+ BXD23 |
+ F |
+ 1848071024 |
+ E |
+
+
+ | 35 |
+ BXD23 |
+ M |
+ 4051964022 |
+ A |
+
+
+ | 36 |
+ BXD27 |
+ F |
+ 1848071024 |
+ F |
+
+
+ | 37 |
+ BXD27 |
+ M |
+ 4051964022 |
+ B |
+
+
+ | 38 |
+ BXD28 |
+ F |
+ 1848071025 |
+ A |
+
+
+ | 39 |
+ BXD28 |
+ M |
+ 4051964022 |
+ C |
+
+
+ | 40 |
+ BXD31 |
+ F |
+ 4051964022 |
+ D |
+
+
+ | 41 |
+ BXD31 |
+ M |
+ 1848071025 |
+ B |
+
+
+ | 42 |
+ BXD32 |
+ F |
+ 4051964022 |
+ E |
+
+
+ | 43 |
+ BXD32 |
+ M |
+ 1848071025 |
+ C |
+
+
+ | 44 |
+ BXD33 |
+ F |
+ 4051964022 |
+ F |
+
+
+ | 45 |
+ BXD33 |
+ M |
+ 1848071025 |
+ D |
+
+
+ | 46 |
+ BXD34 |
+ F |
+ 4051964023 |
+ A |
+
+
+ | 47 |
+ BXD34 |
+ M |
+ 1848071025 |
+ E |
+
+
+ | 48 |
+ BXD36 |
+ F |
+ 1848071025 |
+ F |
+
+
+ | 49 |
+ BXD36 |
+ M |
+ 4051964023 |
+ B |
+
+
+ | 50 |
+ BXD38 |
+ F |
+ 4051964023 |
+ C |
+
+
+ | 51 |
+ BXD38 |
+ M |
+ 1957998101 |
+ A |
+
+
+ | 52 |
+ BXD39 |
+ F |
+ 4051964023 |
+ D |
+
+
+ | 53 |
+ BXD39 |
+ M |
+ 1957998101 |
+ B |
+
+
+ | 54 |
+ BXD40 |
+ F |
+ 4051964023 |
+ E |
+
+
+ | 55 |
+ BXD40 |
+ M |
+ 1957998101 |
+ C |
+
+
+ | 56 |
+ BXD42 |
+ F |
+ 4060001026 |
+ B |
+
+
+ | 57 |
+ BXD43 |
+ F |
+ 1957998101 |
+ D |
+
+
+ | 58 |
+ BXD43 |
+ F |
+ 4051964023 |
+ F |
+
+
+ | 59 |
+ BXD44 |
+ F |
+ 1957998101 |
+ E |
+
+
+ | 60 |
+ BXD44 |
+ M |
+ 4051964028 |
+ A |
+
+
+ | 61 |
+ BXD45 |
+ F |
+ 4051964028 |
+ B |
+
+
+ | 62 |
+ BXD45 |
+ M |
+ 1957998101 |
+ F |
+
+
+ | 63 |
+ BXD51 |
+ F |
+ 4051964028 |
+ D |
+
+
+ | 64 |
+ BXD51 |
+ M |
+ 1736925307 |
+ B |
+
+
+ | 65 |
+ BXD55 |
+ F |
+ 1736925307 |
+ C |
+
+
+ | 66 |
+ BXD55 |
+ M |
+ 4051964028 |
+ E |
+
+
+ | 67 |
+ BXD60 |
+ F |
+ 4060001014 |
+ A |
+
+
+ | 68 |
+ BXD60 |
+ M |
+ 1736925307 |
+ E |
+
+
+ | 69 |
+ BXD61 |
+ F |
+ 4060001014 |
+ B |
+
+
+ | 70 |
+ BXD61 |
+ M |
+ 1736925307 |
+ F |
+
+
+ | 71 |
+ BXD62 |
+ F |
+ 4060001014 |
+ C |
+
+
+ | 72 |
+ BXD62 |
+ M |
+ 1957998111 |
+ A |
+
+
+ | 73 |
+ BXD65 |
+ F |
+ 1957998111 |
+ B |
+
+
+ | 74 |
+ BXD65 |
+ M |
+ 4060001014 |
+ D |
+
+
+ | 75 |
+ BXD66 |
+ M |
+ 4060001026 |
+ C |
+
+
+ | 76 |
+ BXD68 |
+ F |
+ 4060001026 |
+ D |
+
+
+ | 77 |
+ BXD69 |
+ M |
+ 1957998111 |
+ C |
+
+
+ | 78 |
+ BXD69 |
+ M |
+ 4060001014 |
+ E |
+
+
+ | 79 |
+ BXD70 |
+ M |
+ 4060001026 |
+ E |
+
+
+ | 80 |
+ BXD73 |
+ F |
+ 1957998111 |
+ D |
+
+
+ | 81 |
+ BXD73 |
+ M |
+ 4060001014 |
+ F |
+
+
+ | 82 |
+ BXD75 |
+ M |
+ 4060001026 |
+ F |
+
+
+ | 83 |
+ BXD77 |
+ F |
+ 4060001027 |
+ A |
+
+
+ | 84 |
+ BXD80 |
+ M |
+ 4060001027 |
+ B |
+
+
+ | 85 |
+ BXD84 |
+ F |
+ 1957998111 |
+ F |
+
+
+ | 86 |
+ BXD84 |
+ M |
+ 4060001025 |
+ B |
+
+
+ | 87 |
+ BXD86 |
+ M |
+ 4060001027 |
+ C |
+
+
+ | 88 |
+ BXD87 |
+ F |
+ 4060001027 |
+ F |
+
+
+ | 89 |
+ BXD87 |
+ M |
+ 4060001025 |
+ C |
+
+
+ | 90 |
+ BXD89 |
+ M |
+ 4060001027 |
+ D |
+
+
+ | 91 |
+ BXD90 |
+ F |
+ 1736925359 |
+ C |
+
+
+ | 92 |
+ BXD90 |
+ M |
+ 4060001025 |
+ E |
+
+
+ | 93 |
+ BXD96 |
+ F |
+ 4060001025 |
+ F |
+
+
+ | 94 |
+ BXD96 |
+ M |
+ 1736925359 |
+ D |
+
+
+ | 95 |
+ BXD97 |
+ M |
+ 4060001027 |
+ E |
+
+
+ | 96 |
+ BXD100 |
+ F |
+ 1848071017 |
+ A |
+
+
+ | 97 |
+ BXD100 |
+ M |
+ 4051964030 |
+ C |
+
+
+ | 98 |
+ 129S1/SvImJ |
+ F |
+ 1736925359 |
+ E |
+
+
+ | 99 |
+ 129S1/SvImJ |
+ M |
+ 1848071018 |
+ A |
+
+
+ | 100 |
+ A/J |
+ F |
+ 1848071018 |
+ B |
+
+
+ | 101 |
+ A/J |
+ M |
+ 1736925359 |
+ F |
+
+
+ | 102 |
+ AKR/J |
+ F |
+ 1848071018 |
+ C |
+
+
+ | 103 |
+ AKR/J |
+ M |
+ 1957998076 |
+ A |
+
+
+ | 104 |
+ BALB/cByJ |
+ F |
+ 1957998076 |
+ C |
+
+
+ | 105 |
+ BALB/cByJ |
+ M |
+ 1953348019 |
+ A |
+
+
+ | 106 |
+ C3H/HeJ |
+ F |
+ 1953348019 |
+ D |
+
+
+ | 107 |
+ C3H/HeJ |
+ M |
+ 1957998076 |
+ F |
+
+
+ | 108 |
+ CAST/EiJ |
+ F |
+ 1833451021 |
+ B |
+
+
+ | 109 |
+ CAST/EiJ |
+ M |
+ 1957998083 |
+ B |
+
+
+ | 110 |
+ KK/HlJ |
+ F |
+ 1957998083 |
+ E |
+
+
+ | 111 |
+ KK/HlJ |
+ M |
+ 1848071023 |
+ F |
+
+
+ | 112 |
+ BXSB/MpJ |
+ F |
+ 1957998076 |
+ E |
+
+
+ | 113 |
+ BXSB/MpJ |
+ M |
+ 1953348019 |
+ C |
+
+
+ | 114 |
+ FVB/NJ |
+ F |
+ 1833451021 |
+ D |
+
+
+ | 115 |
+ FVB/NJ |
+ M |
+ 1957998083 |
+ D |
+
+
+ | 116 |
+ MOLF/EiJ |
+ F |
+ 1957998083 |
+ F |
+
+
+ | 117 |
+ MOLF/EiJ |
+ M |
+ 1848071001 |
+ B |
+
+
+ | 118 |
+ NOD/LtJ |
+ F |
+ 1848071001 |
+ C |
+
+
+ | 119 |
+ NOD/LtJ |
+ M |
+ 4060001004 |
+ A |
+
+
+ | 120 |
+ NZB/BlNJ |
+ F |
+ 4060001004 |
+ B |
+
+
+ | 121 |
+ NZB/BlNJ |
+ M |
+ 1848071001 |
+ D |
+
+
+ | 122 |
+ NZO/HlLtJ |
+ F |
+ 4060001004 |
+ C |
+
+
+ | 123 |
+ NZW/LacJ |
+ F |
+ 4060001004 |
+ D |
+
+
+ | 124 |
+ PWD/PhJ |
+ F |
+ 4060001004 |
+ E |
+
+
+ | 125 |
+ PWK/PhJ |
+ M |
+ 4060001004 |
+ F |
+
+
+ | 126 |
+ WSB/EiJ |
+ F |
+ 4051964030 |
+ A |
+
+
+ | 127 |
+ BTBRT<+>tf/J |
+ F |
+ 1957998076 |
+ D |
+
+
+ | 128 |
+ BTBRT<+>tf/J |
+ M |
+ 1953348019 |
+ B |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hqfneoc_1210_rankinv/experiment-type.rtf b/general/datasets/Hqfneoc_1210_rankinv/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210_rankinv/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Hqfneoc_1210_rankinv/platform.rtf b/general/datasets/Hqfneoc_1210_rankinv/platform.rtf
new file mode 100644
index 0000000..f0c5210
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210_rankinv/platform.rtf
@@ -0,0 +1,7 @@
+Illumina Sentrix Mouse-6.1 BeadArray Platform (ILM6v1.1): The Mouse6.1 array consists of 46,643 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+Dunning M, Smith M, Thorne N, Tavare S (2006) beadarray: An R package to analyse Illumina BeadArrays. R News (the Newsletter of the P Project) 6:17-23. (see pages 17-23 of http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf).
+
+ANNOTATION: In summer of 2008, Xusheng Wang and Robert W. Williams reannotated the Illumina Mouse-6.1 array content. This new annotation is now incorporated into GeneNetwork. For 46643 probes on the Mouse 6.1 array platform (including control probes) we have identified XXXXX NCBI Entrez Gene IDs; XXXXX matched human Gene IDs; XXXXX matched rat Gene IDs; XXXXX NCBI HomoloGene IDs; and XXXXX OMIM IDs.
+
+Position data for the 50-mer Illumina Mouse-6 array were initially downloaded from Sanger at http://www.sanger.ac.uk/Users/avc/Illumina/Mouse-6_V1.gff.gz but we then updated all positions by BLAT analysis from mm6 positions to mm8 positions (Hongqiang Li).
diff --git a/general/datasets/Hqfneoc_1210_rankinv/processing.rtf b/general/datasets/Hqfneoc_1210_rankinv/processing.rtf
new file mode 100644
index 0000000..895fa91
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210_rankinv/processing.rtf
@@ -0,0 +1,3 @@
+This data set uses the standard Rank Invariant method developed by Illumina and described in their BeadStation Studio documentation.
+
+Sex of the samples was validated using sex-specific probe set: Xist probe ILM104280446.
diff --git a/general/datasets/Hqfneoc_1210_rankinv/summary.rtf b/general/datasets/Hqfneoc_1210_rankinv/summary.rtf
new file mode 100644
index 0000000..ca42527
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210_rankinv/summary.rtf
@@ -0,0 +1,16 @@
+The February 2008 High Q Foundation Neocortex data set provides estimates of mRNA expression in the cerebral cortex of 73 lines of mice, including 52 BXD strains, 20 standard inbred strains, and B6D2F1 isogenic hybrids. All samples are from normal adult control animals raised in a standard laboratory environment. All data were generated with funds provided by the High Q Foundation using the Illumina Mouse 6.1 bead array (the second version of the Illumina Mouse-6 platform).
+
+While this February data release is still a provisional, we are not aware of any specific errors.
+
+
+
+A total of 129 pooled neocortex samples were processed using approximately XX Illumina Sentrix Mouse-6.1 oligomer microarray BeadArray slides. XX Mouse-6.1 slides and a total of 128 samples passed stringent quality control and error checking. This data set is a companion to the High Q Foundation Striatum data set and was processed using very closely matched methods and most of the same samples. This is our third large data set generated using the Illumina platform. This particular data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Illumina (Feb 08) RankInv data set, 1564 probes have LRS values >46 (LOD >10).
+
+Users of these mouse neocortex data may also find the following complementary resources and papers useful:
+
+
+ - Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
+ - A movie of the dissection of the brain by Dr. Glenn Rosen.
+
diff --git a/general/datasets/Hqfneoc_1210_rankinv/tissue.rtf b/general/datasets/Hqfneoc_1210_rankinv/tissue.rtf
new file mode 100644
index 0000000..48d0a2c
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210_rankinv/tissue.rtf
@@ -0,0 +1,9 @@
+All animals were raised at the Jackson Laboratory or at UTHSC in SPF facilities. All mice were killed by cervical dislocation. Whole brain dissections were performed at either Beth Israel Deaconess Medical Center by Glenn Rosen or at UTHSC by Lu Lu and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
+
+A pool of dissected neocortical tissue from two to three naive adults of the same strain, sex, and age was collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at UTHSC by Zhiping Jia (CHECK LAST STATEMENT WITH LU).
+
+All animals used in this study were between XX and XX days of age (average of XX days; see Table 1 below). All animals were sacrifice between 9 AM and 5 PM during the light phase.
+
+Sample Processing: Samples were processed by Lu Lu and colleagues in the Illumina Core at UTHSC between December 2007 and January 2008. All processing steps were performed by Feng Jiao. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from as many strains as possible. However, a number of strains are represented by samples from a single sex (see figure at bottom of page).
diff --git a/general/datasets/Hqfneoc_1210v2_rankinv/acknowledgment.rtf b/general/datasets/Hqfneoc_1210v2_rankinv/acknowledgment.rtf
new file mode 100644
index 0000000..3135d79
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210v2_rankinv/acknowledgment.rtf
@@ -0,0 +1,6 @@
+Data were generated with funds to RW Williams, Glenn D. Rosen, Weikuan Gu, and Lu Lu from the High Q Foundation. Informatics support also provided by NIH NIAAA INIA grants to RWW and LL.
+
+
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513 (Lu Lu, PI)
+
diff --git a/general/datasets/Hqfneoc_1210v2_rankinv/cases.rtf b/general/datasets/Hqfneoc_1210v2_rankinv/cases.rtf
new file mode 100644
index 0000000..a98a7ff
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210v2_rankinv/cases.rtf
@@ -0,0 +1,54 @@
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 27 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding. We have also included 25 new inbred strains BXD (F21+) generated by Lu and Peirce. All of these strains were been genotyped at 13,377 SNPs in 2005 (Shifman et al., 2006).
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 20 inbred strains and an F1 hybrid (B6D2F1). These strains were selected for several reasons:
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+All eight parents of the Collaborative Cross (129, A, C57BL/6J, CAST, NOD, NZO, PWK, and WSB) have been included in the MDP (noted below in the list). Twelve MDP strains have been sequenced, or are currently being resequenced by Perlegen for the NIEHS. This panel will be extremely helpful in systems genetic analysis of a wide variety of traits, and will be a powerful adjunct in fine mapping modulators using what is essentially an association analysis of sequence variants.
+
+
+ - 129S1/SvImJ
+ Collaborative Cross strain sequenced by NIEHS; background for many knockouts; Phenome Project A list
+ - A/J
+ Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel
+ - AKR/J
+ Sequenced by NIEHS; Phenome Project B list
+ - BALB/cByJ
+ Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project A list
+ - BALB/cJ
+ Widely used strain with forebrain abnormalities (callosal defects); Phenome Project A list
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - LG/J
+ Paternal parent of the LGXSM panel
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - NZO/HlLtJ
+ Collaborative Cross strain
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - B6D2F1
+ This F1 hybrid was generated by crossing C57BL/6J with DBA/2J.
+
+
+These strains are available from The Jackson Laboratory. BXD43 through BXD100 strains are available from Lu Lu and colleagues at UTHSC.
diff --git a/general/datasets/Hqfneoc_1210v2_rankinv/experiment-design.rtf b/general/datasets/Hqfneoc_1210v2_rankinv/experiment-design.rtf
new file mode 100644
index 0000000..322268a
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210v2_rankinv/experiment-design.rtf
@@ -0,0 +1,937 @@
+This data set consists arrays processed in XX groups over a XX month period (from Month Year to Month Year). Most groups consisted of XX samples. All arrays in this data set were processed using a single protocol by a single operator, NAME HERE. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between Month Day and Month Day, Year. Details on sample assignment to slides and batches is provide in the table below.
+
+Error checking
+
+
+ - Checked for genotypes of BXD strains on all chromosomes using a battery of test Mendelian transcripts (transcripts with a Mendelian segregation pattern in the BXDs). Peak LRS of 260.2 for Prdx2 using Illumina probe ILM5340577. There are no errors in the strain assignment but there are possible genotyping errors, such as:
+ Thumpd1 (ILM7510148) in BXD34 using marker rs6271956
+ H2-D2 (ILM2190725) in BXD69 using marker gnf17.035.152
+ Fcer1g (ILM5550020) in BXD100 using marker rs3722740 (incorrectly scored as a heterozygote).
+
+ These genotype discrepancies are either due to recombination between the marker and the probe or a genotyping errors. (RWW, Feb 27, 2008)
+ - Total count of transcripts/probes with LOD greater than 10 is 1564 with 52 BXD strains (BXD1 through BXD43 from (n = 27) from JAX, and BXD43 through 100 (n = 25) from UTHSC).
+ - Sex assignment checked using Xist probe ILM104280446.
+ All female samples: Strains BXD43, BXD42, BXD68, BXD77, NZW/LacJ, and NZO/HlLtJ
+ All male samples: Strains BXD1, PWK/PhJ, BXD66, BXD97, BXD10, BXD75, BXD44, BXD89, BXD86, BXD80, BXD69
+
+
+Data Table 1:
+
+This table lists all arrays by order of strain (index) and includes data on strain, sex, slide ID and slide position (A through F).
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Sex |
+ Slide ID |
+ Slide
+ Position |
+
+
+ | 1 |
+ B6D2F1 |
+ F |
+ 1848071018 |
+ D |
+
+
+ | 2 |
+ B6D2F1 |
+ M |
+ 1957998076 |
+ B |
+
+
+ | 3 |
+ C57BL/6J |
+ F |
+ 1957998083 |
+ A |
+
+
+ | 4 |
+ C57BL/6J |
+ M |
+ 1833451021 |
+ A |
+
+
+ | 5 |
+ DBA/2J |
+ F |
+ 1957998083 |
+ C |
+
+
+ | 6 |
+ DBA/2J |
+ M |
+ 1833451021 |
+ C |
+
+
+ | 7 |
+ BXD1 |
+ M |
+ 4051964030 |
+ B |
+
+
+ | 8 |
+ BXD5 |
+ F |
+ 1736925307 |
+ A |
+
+
+ | 9 |
+ BXD5 |
+ M |
+ 4051964028 |
+ C |
+
+
+ | 10 |
+ BXD6 |
+ F |
+ 4051964028 |
+ F |
+
+
+ | 11 |
+ BXD6 |
+ M |
+ 1736925307 |
+ D |
+
+
+ | 12 |
+ BXD8 |
+ F |
+ 4060001025 |
+ A |
+
+
+ | 13 |
+ BXD8 |
+ M |
+ 1957998111 |
+ E |
+
+
+ | 14 |
+ BXD9 |
+ F |
+ 4060001025 |
+ D |
+
+
+ | 15 |
+ BXD9 |
+ M |
+ 1736925359 |
+ B |
+
+
+ | 16 |
+ BXD11 |
+ F |
+ 4051964030 |
+ D |
+
+
+ | 17 |
+ BXD11 |
+ M |
+ 1848071017 |
+ B |
+
+
+ | 18 |
+ BXD12 |
+ F |
+ 4051964030 |
+ E |
+
+
+ | 19 |
+ BXD12 |
+ M |
+ 1848071017 |
+ C |
+
+
+ | 20 |
+ BXD13 |
+ F |
+ 4051964030 |
+ F |
+
+
+ | 21 |
+ BXD13 |
+ M |
+ 1848071017 |
+ D |
+
+
+ | 22 |
+ BXD14 |
+ F |
+ 4051964065 |
+ A |
+
+
+ | 23 |
+ BXD14 |
+ M |
+ 1848071017 |
+ E |
+
+
+ | 24 |
+ BXD15 |
+ F |
+ 4051964065 |
+ B |
+
+
+ | 25 |
+ BXD15 |
+ M |
+ 1848071017 |
+ F |
+
+
+ | 26 |
+ BXD16 |
+ F |
+ 1848071024 |
+ A |
+
+
+ | 27 |
+ BXD16 |
+ M |
+ 4051964065 |
+ C |
+
+
+ | 28 |
+ BXD18 |
+ F |
+ 4051964065 |
+ D |
+
+
+ | 29 |
+ BXD18 |
+ M |
+ 1848071024 |
+ B |
+
+
+ | 30 |
+ BXD19 |
+ F |
+ 4051964065 |
+ E |
+
+
+ | 31 |
+ BXD19 |
+ M |
+ 1848071024 |
+ C |
+
+
+ | 32 |
+ BXD21 |
+ F |
+ 1848071024 |
+ D |
+
+
+ | 33 |
+ BXD21 |
+ M |
+ 4051964065 |
+ F |
+
+
+ | 34 |
+ BXD23 |
+ F |
+ 1848071024 |
+ E |
+
+
+ | 35 |
+ BXD23 |
+ M |
+ 4051964022 |
+ A |
+
+
+ | 36 |
+ BXD27 |
+ F |
+ 1848071024 |
+ F |
+
+
+ | 37 |
+ BXD27 |
+ M |
+ 4051964022 |
+ B |
+
+
+ | 38 |
+ BXD28 |
+ F |
+ 1848071025 |
+ A |
+
+
+ | 39 |
+ BXD28 |
+ M |
+ 4051964022 |
+ C |
+
+
+ | 40 |
+ BXD31 |
+ F |
+ 4051964022 |
+ D |
+
+
+ | 41 |
+ BXD31 |
+ M |
+ 1848071025 |
+ B |
+
+
+ | 42 |
+ BXD32 |
+ F |
+ 4051964022 |
+ E |
+
+
+ | 43 |
+ BXD32 |
+ M |
+ 1848071025 |
+ C |
+
+
+ | 44 |
+ BXD33 |
+ F |
+ 4051964022 |
+ F |
+
+
+ | 45 |
+ BXD33 |
+ M |
+ 1848071025 |
+ D |
+
+
+ | 46 |
+ BXD34 |
+ F |
+ 4051964023 |
+ A |
+
+
+ | 47 |
+ BXD34 |
+ M |
+ 1848071025 |
+ E |
+
+
+ | 48 |
+ BXD36 |
+ F |
+ 1848071025 |
+ F |
+
+
+ | 49 |
+ BXD36 |
+ M |
+ 4051964023 |
+ B |
+
+
+ | 50 |
+ BXD38 |
+ F |
+ 4051964023 |
+ C |
+
+
+ | 51 |
+ BXD38 |
+ M |
+ 1957998101 |
+ A |
+
+
+ | 52 |
+ BXD39 |
+ F |
+ 4051964023 |
+ D |
+
+
+ | 53 |
+ BXD39 |
+ M |
+ 1957998101 |
+ B |
+
+
+ | 54 |
+ BXD40 |
+ F |
+ 4051964023 |
+ E |
+
+
+ | 55 |
+ BXD40 |
+ M |
+ 1957998101 |
+ C |
+
+
+ | 56 |
+ BXD42 |
+ F |
+ 4060001026 |
+ B |
+
+
+ | 57 |
+ BXD43 |
+ F |
+ 1957998101 |
+ D |
+
+
+ | 58 |
+ BXD43 |
+ F |
+ 4051964023 |
+ F |
+
+
+ | 59 |
+ BXD44 |
+ F |
+ 1957998101 |
+ E |
+
+
+ | 60 |
+ BXD44 |
+ M |
+ 4051964028 |
+ A |
+
+
+ | 61 |
+ BXD45 |
+ F |
+ 4051964028 |
+ B |
+
+
+ | 62 |
+ BXD45 |
+ M |
+ 1957998101 |
+ F |
+
+
+ | 63 |
+ BXD51 |
+ F |
+ 4051964028 |
+ D |
+
+
+ | 64 |
+ BXD51 |
+ M |
+ 1736925307 |
+ B |
+
+
+ | 65 |
+ BXD55 |
+ F |
+ 1736925307 |
+ C |
+
+
+ | 66 |
+ BXD55 |
+ M |
+ 4051964028 |
+ E |
+
+
+ | 67 |
+ BXD60 |
+ F |
+ 4060001014 |
+ A |
+
+
+ | 68 |
+ BXD60 |
+ M |
+ 1736925307 |
+ E |
+
+
+ | 69 |
+ BXD61 |
+ F |
+ 4060001014 |
+ B |
+
+
+ | 70 |
+ BXD61 |
+ M |
+ 1736925307 |
+ F |
+
+
+ | 71 |
+ BXD62 |
+ F |
+ 4060001014 |
+ C |
+
+
+ | 72 |
+ BXD62 |
+ M |
+ 1957998111 |
+ A |
+
+
+ | 73 |
+ BXD65 |
+ F |
+ 1957998111 |
+ B |
+
+
+ | 74 |
+ BXD65 |
+ M |
+ 4060001014 |
+ D |
+
+
+ | 75 |
+ BXD66 |
+ M |
+ 4060001026 |
+ C |
+
+
+ | 76 |
+ BXD68 |
+ F |
+ 4060001026 |
+ D |
+
+
+ | 77 |
+ BXD69 |
+ M |
+ 1957998111 |
+ C |
+
+
+ | 78 |
+ BXD69 |
+ M |
+ 4060001014 |
+ E |
+
+
+ | 79 |
+ BXD70 |
+ M |
+ 4060001026 |
+ E |
+
+
+ | 80 |
+ BXD73 |
+ F |
+ 1957998111 |
+ D |
+
+
+ | 81 |
+ BXD73 |
+ M |
+ 4060001014 |
+ F |
+
+
+ | 82 |
+ BXD75 |
+ M |
+ 4060001026 |
+ F |
+
+
+ | 83 |
+ BXD77 |
+ F |
+ 4060001027 |
+ A |
+
+
+ | 84 |
+ BXD80 |
+ M |
+ 4060001027 |
+ B |
+
+
+ | 85 |
+ BXD84 |
+ F |
+ 1957998111 |
+ F |
+
+
+ | 86 |
+ BXD84 |
+ M |
+ 4060001025 |
+ B |
+
+
+ | 87 |
+ BXD86 |
+ M |
+ 4060001027 |
+ C |
+
+
+ | 88 |
+ BXD87 |
+ F |
+ 4060001027 |
+ F |
+
+
+ | 89 |
+ BXD87 |
+ M |
+ 4060001025 |
+ C |
+
+
+ | 90 |
+ BXD89 |
+ M |
+ 4060001027 |
+ D |
+
+
+ | 91 |
+ BXD90 |
+ F |
+ 1736925359 |
+ C |
+
+
+ | 92 |
+ BXD90 |
+ M |
+ 4060001025 |
+ E |
+
+
+ | 93 |
+ BXD96 |
+ F |
+ 4060001025 |
+ F |
+
+
+ | 94 |
+ BXD96 |
+ M |
+ 1736925359 |
+ D |
+
+
+ | 95 |
+ BXD97 |
+ M |
+ 4060001027 |
+ E |
+
+
+ | 96 |
+ BXD100 |
+ F |
+ 1848071017 |
+ A |
+
+
+ | 97 |
+ BXD100 |
+ M |
+ 4051964030 |
+ C |
+
+
+ | 98 |
+ 129S1/SvImJ |
+ F |
+ 1736925359 |
+ E |
+
+
+ | 99 |
+ 129S1/SvImJ |
+ M |
+ 1848071018 |
+ A |
+
+
+ | 100 |
+ A/J |
+ F |
+ 1848071018 |
+ B |
+
+
+ | 101 |
+ A/J |
+ M |
+ 1736925359 |
+ F |
+
+
+ | 102 |
+ AKR/J |
+ F |
+ 1848071018 |
+ C |
+
+
+ | 103 |
+ AKR/J |
+ M |
+ 1957998076 |
+ A |
+
+
+ | 104 |
+ BALB/cByJ |
+ F |
+ 1957998076 |
+ C |
+
+
+ | 105 |
+ BALB/cByJ |
+ M |
+ 1953348019 |
+ A |
+
+
+ | 106 |
+ C3H/HeJ |
+ F |
+ 1953348019 |
+ D |
+
+
+ | 107 |
+ C3H/HeJ |
+ M |
+ 1957998076 |
+ F |
+
+
+ | 108 |
+ CAST/EiJ |
+ F |
+ 1833451021 |
+ B |
+
+
+ | 109 |
+ CAST/EiJ |
+ M |
+ 1957998083 |
+ B |
+
+
+ | 110 |
+ KK/HlJ |
+ F |
+ 1957998083 |
+ E |
+
+
+ | 111 |
+ KK/HlJ |
+ M |
+ 1848071023 |
+ F |
+
+
+ | 112 |
+ BXSB/MpJ |
+ F |
+ 1957998076 |
+ E |
+
+
+ | 113 |
+ BXSB/MpJ |
+ M |
+ 1953348019 |
+ C |
+
+
+ | 114 |
+ FVB/NJ |
+ F |
+ 1833451021 |
+ D |
+
+
+ | 115 |
+ FVB/NJ |
+ M |
+ 1957998083 |
+ D |
+
+
+ | 116 |
+ MOLF/EiJ |
+ F |
+ 1957998083 |
+ F |
+
+
+ | 117 |
+ MOLF/EiJ |
+ M |
+ 1848071001 |
+ B |
+
+
+ | 118 |
+ NOD/LtJ |
+ F |
+ 1848071001 |
+ C |
+
+
+ | 119 |
+ NOD/LtJ |
+ M |
+ 4060001004 |
+ A |
+
+
+ | 120 |
+ NZB/BlNJ |
+ F |
+ 4060001004 |
+ B |
+
+
+ | 121 |
+ NZB/BlNJ |
+ M |
+ 1848071001 |
+ D |
+
+
+ | 122 |
+ NZO/HlLtJ |
+ F |
+ 4060001004 |
+ C |
+
+
+ | 123 |
+ NZW/LacJ |
+ F |
+ 4060001004 |
+ D |
+
+
+ | 124 |
+ PWD/PhJ |
+ F |
+ 4060001004 |
+ E |
+
+
+ | 125 |
+ PWK/PhJ |
+ M |
+ 4060001004 |
+ F |
+
+
+ | 126 |
+ WSB/EiJ |
+ F |
+ 4051964030 |
+ A |
+
+
+ | 127 |
+ BTBRT<+>tf/J |
+ F |
+ 1957998076 |
+ D |
+
+
+ | 128 |
+ BTBRT<+>tf/J |
+ M |
+ 1953348019 |
+ B |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hqfneoc_1210v2_rankinv/experiment-type.rtf b/general/datasets/Hqfneoc_1210v2_rankinv/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210v2_rankinv/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Hqfneoc_1210v2_rankinv/platform.rtf b/general/datasets/Hqfneoc_1210v2_rankinv/platform.rtf
new file mode 100644
index 0000000..f0c5210
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210v2_rankinv/platform.rtf
@@ -0,0 +1,7 @@
+Illumina Sentrix Mouse-6.1 BeadArray Platform (ILM6v1.1): The Mouse6.1 array consists of 46,643 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+Dunning M, Smith M, Thorne N, Tavare S (2006) beadarray: An R package to analyse Illumina BeadArrays. R News (the Newsletter of the P Project) 6:17-23. (see pages 17-23 of http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf).
+
+ANNOTATION: In summer of 2008, Xusheng Wang and Robert W. Williams reannotated the Illumina Mouse-6.1 array content. This new annotation is now incorporated into GeneNetwork. For 46643 probes on the Mouse 6.1 array platform (including control probes) we have identified XXXXX NCBI Entrez Gene IDs; XXXXX matched human Gene IDs; XXXXX matched rat Gene IDs; XXXXX NCBI HomoloGene IDs; and XXXXX OMIM IDs.
+
+Position data for the 50-mer Illumina Mouse-6 array were initially downloaded from Sanger at http://www.sanger.ac.uk/Users/avc/Illumina/Mouse-6_V1.gff.gz but we then updated all positions by BLAT analysis from mm6 positions to mm8 positions (Hongqiang Li).
diff --git a/general/datasets/Hqfneoc_1210v2_rankinv/processing.rtf b/general/datasets/Hqfneoc_1210v2_rankinv/processing.rtf
new file mode 100644
index 0000000..895fa91
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210v2_rankinv/processing.rtf
@@ -0,0 +1,3 @@
+This data set uses the standard Rank Invariant method developed by Illumina and described in their BeadStation Studio documentation.
+
+Sex of the samples was validated using sex-specific probe set: Xist probe ILM104280446.
diff --git a/general/datasets/Hqfneoc_1210v2_rankinv/summary.rtf b/general/datasets/Hqfneoc_1210v2_rankinv/summary.rtf
new file mode 100644
index 0000000..ca42527
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210v2_rankinv/summary.rtf
@@ -0,0 +1,16 @@
+The February 2008 High Q Foundation Neocortex data set provides estimates of mRNA expression in the cerebral cortex of 73 lines of mice, including 52 BXD strains, 20 standard inbred strains, and B6D2F1 isogenic hybrids. All samples are from normal adult control animals raised in a standard laboratory environment. All data were generated with funds provided by the High Q Foundation using the Illumina Mouse 6.1 bead array (the second version of the Illumina Mouse-6 platform).
+
+While this February data release is still a provisional, we are not aware of any specific errors.
+
+
+
+A total of 129 pooled neocortex samples were processed using approximately XX Illumina Sentrix Mouse-6.1 oligomer microarray BeadArray slides. XX Mouse-6.1 slides and a total of 128 samples passed stringent quality control and error checking. This data set is a companion to the High Q Foundation Striatum data set and was processed using very closely matched methods and most of the same samples. This is our third large data set generated using the Illumina platform. This particular data set was processed using the Illumina "Rank Invariant" protocol. Values were log2 transformed and the current data range from XXX (very low or no expression) to XXXX (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Neocortex Illumina (Feb 08) RankInv data set, 1564 probes have LRS values >46 (LOD >10).
+
+Users of these mouse neocortex data may also find the following complementary resources and papers useful:
+
+
+ - Rossner and colleagues, 2006: a paper on the transcriptome of identified subtypes of neurons in the mouse neocortex.
+ - A movie of the dissection of the brain by Dr. Glenn Rosen.
+
diff --git a/general/datasets/Hqfneoc_1210v2_rankinv/tissue.rtf b/general/datasets/Hqfneoc_1210v2_rankinv/tissue.rtf
new file mode 100644
index 0000000..48d0a2c
--- /dev/null
+++ b/general/datasets/Hqfneoc_1210v2_rankinv/tissue.rtf
@@ -0,0 +1,9 @@
+All animals were raised at the Jackson Laboratory or at UTHSC in SPF facilities. All mice were killed by cervical dislocation. Whole brain dissections were performed at either Beth Israel Deaconess Medical Center by Glenn Rosen or at UTHSC by Lu Lu and colleagues. Neocortex samples were close to complete but are likely to include variable amounts of underlying white matter. Samples may also include parts of the pyriform cortex and subiculum.
+
+A pool of dissected neocortical tissue from two to three naive adults of the same strain, sex, and age was collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at UTHSC by Zhiping Jia (CHECK LAST STATEMENT WITH LU).
+
+All animals used in this study were between XX and XX days of age (average of XX days; see Table 1 below). All animals were sacrifice between 9 AM and 5 PM during the light phase.
+
+Sample Processing: Samples were processed by Lu Lu and colleagues in the Illumina Core at UTHSC between December 2007 and January 2008. All processing steps were performed by Feng Jiao. In brief, RNA purity was evaluated using the 260/280 nm absorbance ratio, and values had to be greater than 1.8 to pass our quality control (QC). The majority of samples had values between 1.9 and 2.1. RNA integrity was assessed using the Agilent Bioanalyzer 2100. The standard Eberwine T7 polymerase method was used to catalyze the synthesis of cDNA template from polyA-tailed RNA using the Ambion/Illumina (http://www.ambion.com/catalog/CatNum.php?AMIL1791) TotalPrep RNA amplication kit (Cat#IL1791). The biotin labeled cRNA was then evaluated using both the 260/280 ratio (values of 2.0-2.3 are acceptable) using a NanoDrop ND-1000 (http://www.nanodrop.com/nd-1000-overview.html). Those samples that passed QC steps (1-3% failed and new RNA samples had to be acquired and processed) were immediately used on Mouse-6 v 1.1 slide. The slides were hybridized and washed following standard Illumina protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from as many strains as possible. However, a number of strains are represented by samples from a single sex (see figure at bottom of page).
diff --git a/general/datasets/Hrdppublish/specifics.rtf b/general/datasets/Hrdppublish/specifics.rtf
new file mode 100644
index 0000000..6ea3cd9
--- /dev/null
+++ b/general/datasets/Hrdppublish/specifics.rtf
@@ -0,0 +1 @@
+HRDP Published Phenotypes
\ No newline at end of file
diff --git a/general/datasets/Hrdppublish/summary.rtf b/general/datasets/Hrdppublish/summary.rtf
new file mode 100644
index 0000000..bce5ebd
--- /dev/null
+++ b/general/datasets/Hrdppublish/summary.rtf
@@ -0,0 +1 @@
+HRDP Published Phenotypes
diff --git a/general/datasets/Hsnih_palmerpublish/specifics.rtf b/general/datasets/Hsnih_palmerpublish/specifics.rtf
new file mode 100644
index 0000000..6bb3581
--- /dev/null
+++ b/general/datasets/Hsnih_palmerpublish/specifics.rtf
@@ -0,0 +1 @@
+HSNIH Published Phenotypes
\ No newline at end of file
diff --git a/general/datasets/Hsnih_palmerpublish/summary.rtf b/general/datasets/Hsnih_palmerpublish/summary.rtf
new file mode 100644
index 0000000..2503d26
--- /dev/null
+++ b/general/datasets/Hsnih_palmerpublish/summary.rtf
@@ -0,0 +1 @@
+HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/Hsnih_rat_acbc_rseq_0818/specifics.rtf b/general/datasets/Hsnih_rat_acbc_rseq_0818/specifics.rtf
new file mode 100644
index 0000000..db20c9a
--- /dev/null
+++ b/general/datasets/Hsnih_rat_acbc_rseq_0818/specifics.rtf
@@ -0,0 +1 @@
+Nucleus Accumbens Core
\ No newline at end of file
diff --git a/general/datasets/Hsnih_rat_acbc_rseq_0818/summary.rtf b/general/datasets/Hsnih_rat_acbc_rseq_0818/summary.rtf
new file mode 100644
index 0000000..2503d26
--- /dev/null
+++ b/general/datasets/Hsnih_rat_acbc_rseq_0818/summary.rtf
@@ -0,0 +1 @@
+HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/Hsnih_rat_acbc_rseqlog2_0818/specifics.rtf b/general/datasets/Hsnih_rat_acbc_rseqlog2_0818/specifics.rtf
new file mode 100644
index 0000000..843d470
--- /dev/null
+++ b/general/datasets/Hsnih_rat_acbc_rseqlog2_0818/specifics.rtf
@@ -0,0 +1 @@
+Log2
\ No newline at end of file
diff --git a/general/datasets/Hsnih_rat_acbc_rseqlog2_0818/summary.rtf b/general/datasets/Hsnih_rat_acbc_rseqlog2_0818/summary.rtf
new file mode 100644
index 0000000..2503d26
--- /dev/null
+++ b/general/datasets/Hsnih_rat_acbc_rseqlog2_0818/summary.rtf
@@ -0,0 +1 @@
+HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/Hsnih_rat_il_rseq_0818/specifics.rtf b/general/datasets/Hsnih_rat_il_rseq_0818/specifics.rtf
new file mode 100644
index 0000000..67ff940
--- /dev/null
+++ b/general/datasets/Hsnih_rat_il_rseq_0818/specifics.rtf
@@ -0,0 +1 @@
+Infralimbic Cortex
\ No newline at end of file
diff --git a/general/datasets/Hsnih_rat_il_rseq_0818/summary.rtf b/general/datasets/Hsnih_rat_il_rseq_0818/summary.rtf
new file mode 100644
index 0000000..2503d26
--- /dev/null
+++ b/general/datasets/Hsnih_rat_il_rseq_0818/summary.rtf
@@ -0,0 +1 @@
+HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/Hsnih_rat_il_rseqlog2_0818/specifics.rtf b/general/datasets/Hsnih_rat_il_rseqlog2_0818/specifics.rtf
new file mode 100644
index 0000000..843d470
--- /dev/null
+++ b/general/datasets/Hsnih_rat_il_rseqlog2_0818/specifics.rtf
@@ -0,0 +1 @@
+Log2
\ No newline at end of file
diff --git a/general/datasets/Hsnih_rat_il_rseqlog2_0818/summary.rtf b/general/datasets/Hsnih_rat_il_rseqlog2_0818/summary.rtf
new file mode 100644
index 0000000..2503d26
--- /dev/null
+++ b/general/datasets/Hsnih_rat_il_rseqlog2_0818/summary.rtf
@@ -0,0 +1 @@
+HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/Hsnih_rat_lhb_rseq_0818/specifics.rtf b/general/datasets/Hsnih_rat_lhb_rseq_0818/specifics.rtf
new file mode 100644
index 0000000..e3b7857
--- /dev/null
+++ b/general/datasets/Hsnih_rat_lhb_rseq_0818/specifics.rtf
@@ -0,0 +1 @@
+Lateral Habenula
\ No newline at end of file
diff --git a/general/datasets/Hsnih_rat_lhb_rseq_0818/summary.rtf b/general/datasets/Hsnih_rat_lhb_rseq_0818/summary.rtf
new file mode 100644
index 0000000..2503d26
--- /dev/null
+++ b/general/datasets/Hsnih_rat_lhb_rseq_0818/summary.rtf
@@ -0,0 +1 @@
+HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/Hsnih_rat_lhb_rseqlog2_0818/specifics.rtf b/general/datasets/Hsnih_rat_lhb_rseqlog2_0818/specifics.rtf
new file mode 100644
index 0000000..843d470
--- /dev/null
+++ b/general/datasets/Hsnih_rat_lhb_rseqlog2_0818/specifics.rtf
@@ -0,0 +1 @@
+Log2
\ No newline at end of file
diff --git a/general/datasets/Hsnih_rat_lhb_rseqlog2_0818/summary.rtf b/general/datasets/Hsnih_rat_lhb_rseqlog2_0818/summary.rtf
new file mode 100644
index 0000000..2503d26
--- /dev/null
+++ b/general/datasets/Hsnih_rat_lhb_rseqlog2_0818/summary.rtf
@@ -0,0 +1 @@
+HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/Hsnih_rat_pl_rseq_0818/specifics.rtf b/general/datasets/Hsnih_rat_pl_rseq_0818/specifics.rtf
new file mode 100644
index 0000000..282c9b5
--- /dev/null
+++ b/general/datasets/Hsnih_rat_pl_rseq_0818/specifics.rtf
@@ -0,0 +1 @@
+Prelimbic Cortex
\ No newline at end of file
diff --git a/general/datasets/Hsnih_rat_pl_rseq_0818/summary.rtf b/general/datasets/Hsnih_rat_pl_rseq_0818/summary.rtf
new file mode 100644
index 0000000..2503d26
--- /dev/null
+++ b/general/datasets/Hsnih_rat_pl_rseq_0818/summary.rtf
@@ -0,0 +1 @@
+HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/Hsnih_rat_pl_rseqlog2_0818/specifics.rtf b/general/datasets/Hsnih_rat_pl_rseqlog2_0818/specifics.rtf
new file mode 100644
index 0000000..843d470
--- /dev/null
+++ b/general/datasets/Hsnih_rat_pl_rseqlog2_0818/specifics.rtf
@@ -0,0 +1 @@
+Log2
\ No newline at end of file
diff --git a/general/datasets/Hsnih_rat_pl_rseqlog2_0818/summary.rtf b/general/datasets/Hsnih_rat_pl_rseqlog2_0818/summary.rtf
new file mode 100644
index 0000000..2503d26
--- /dev/null
+++ b/general/datasets/Hsnih_rat_pl_rseqlog2_0818/summary.rtf
@@ -0,0 +1 @@
+HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/Hsnih_rat_volo_rseq_0818/specifics.rtf b/general/datasets/Hsnih_rat_volo_rseq_0818/specifics.rtf
new file mode 100644
index 0000000..01b8829
--- /dev/null
+++ b/general/datasets/Hsnih_rat_volo_rseq_0818/specifics.rtf
@@ -0,0 +1 @@
+Orbitofrontal Cortex
\ No newline at end of file
diff --git a/general/datasets/Hsnih_rat_volo_rseq_0818/summary.rtf b/general/datasets/Hsnih_rat_volo_rseq_0818/summary.rtf
new file mode 100644
index 0000000..2503d26
--- /dev/null
+++ b/general/datasets/Hsnih_rat_volo_rseq_0818/summary.rtf
@@ -0,0 +1 @@
+HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/Hsnih_rat_volo_rseqlog2_0818/specifics.rtf b/general/datasets/Hsnih_rat_volo_rseqlog2_0818/specifics.rtf
new file mode 100644
index 0000000..843d470
--- /dev/null
+++ b/general/datasets/Hsnih_rat_volo_rseqlog2_0818/specifics.rtf
@@ -0,0 +1 @@
+Log2
\ No newline at end of file
diff --git a/general/datasets/Hsnih_rat_volo_rseqlog2_0818/summary.rtf b/general/datasets/Hsnih_rat_volo_rseqlog2_0818/summary.rtf
new file mode 100644
index 0000000..2503d26
--- /dev/null
+++ b/general/datasets/Hsnih_rat_volo_rseqlog2_0818/summary.rtf
@@ -0,0 +1 @@
+HSNIH-Palmer Published Phenotypes
diff --git a/general/datasets/Human_1008/citation.rtf b/general/datasets/Human_1008/citation.rtf
new file mode 100644
index 0000000..62879f7
--- /dev/null
+++ b/general/datasets/Human_1008/citation.rtf
@@ -0,0 +1 @@
+Monks SA, Leonardson A, Zhu H, Cundiff P et al. Genetic inheritance of gene expression in human cell lines. Am J Hum Genet 2004 Dec;75(6):1094-105. PMID: 15514893
diff --git a/general/datasets/Human_1008/contributors.rtf b/general/datasets/Human_1008/contributors.rtf
new file mode 100644
index 0000000..fe578df
--- /dev/null
+++ b/general/datasets/Human_1008/contributors.rtf
@@ -0,0 +1,3 @@
+Monks SA1, Leonardson A, Zhu H, Cundiff P, Pietrusiak P, Edwards S, Phillips JW, Sachs A, Schadt EE.
+
+1Department of Statistics, Oklahoma State University, Stillwater, OK 74078-1056, USA. stephanie.monks@okstate.edu
diff --git a/general/datasets/Hxb_adrenal_1208/acknowledgment.rtf b/general/datasets/Hxb_adrenal_1208/acknowledgment.rtf
new file mode 100644
index 0000000..d0e4106
--- /dev/null
+++ b/general/datasets/Hxb_adrenal_1208/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported with funds to TJA by the MRC Clinical Sciences Centre, the British Heart Foundation, and the Wellcome Trust Cardiovascular Functional Genomics Initiative; to NH from the German Ministry for Science and Education (National Genome Research Network); to MP and Vladimir Kren from the Grant Agency of the Czech Republic; to MP and TJA from the Wellcome Trust Collaborative Research Initiative grant, to Theodore W Kurtz from the NIH, to TWK and MP from a Fogarty International Research Collaboration Award. Microarrays were a generous donation of Affymetrix Inc. Michal Pravenec thanks the Howard Hughes Medical Institute for its support to him as an international research scholar.
diff --git a/general/datasets/Hxb_adrenal_1208/cases.rtf b/general/datasets/Hxb_adrenal_1208/cases.rtf
new file mode 100644
index 0000000..f105019
--- /dev/null
+++ b/general/datasets/Hxb_adrenal_1208/cases.rtf
@@ -0,0 +1,7 @@
+Data were generated using the HXB/BXH recombinant inbred strains of rats generated over the past 20 years in Prague. The parental strains from which all HXB lines are derived are SHR (SHR/OlaIpcv, abbreviated SHR or HSR = H) and Brown Norway (BN-Lx/Cub= B). These strains have been used extensively to study cardiovascular system physiology and genetics.
+
+
+
+The HXB strains were bred by Michal Pravenec at the Institute of Physiology, Czech Academy of Sciences. The BXH strains were bred by Vladimir Kren (see Pravenec et al. 1989, 2004) at a similar animal facility at the Institute of Biology and Medical Genetics, 1st Medical Faculty, Charles University. These strains are at approximately the 6oth generation of continuous inbreeding (F60).
+
+Animals used in the transcriptome analyses of multiple tissues (Hübner and colleagues, 2005) were weaned at 4 weeks. Those born at the Charles University were transferred to the Institute of Physiology. Animals were reared on a commerical rat chow (ST-1 from VELAZ, Czech Republic). Four males were house per cage. Cages were made of polystyrene and have a floor size of 22 x 38 cm and height of 23 cm. The bedding was changed twice a week. Light cycle was 12:12 on-off. Vivarium rooms were maintained at 23 deg. C. Rats were sexually naive. All males used in the initial transcriptome studies (Hübner et al., 2005) were born between May and August 2002. They were sacrificed unfastged by rapid cervical dislocation between 9 and 10 AM, following an approved animal protocol (Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague; Animal Protectiion Law of the Czech Republic (311/1997).
diff --git a/general/datasets/Hxb_adrenal_1208/citation.rtf b/general/datasets/Hxb_adrenal_1208/citation.rtf
new file mode 100644
index 0000000..a8b8cc0
--- /dev/null
+++ b/general/datasets/Hxb_adrenal_1208/citation.rtf
@@ -0,0 +1 @@
+PLoS One. 2008;3(12):e4033. doi: 10.1371/journal.pone.0004033. Epub 2008 Dec 29.
diff --git a/general/datasets/Hxb_adrenal_1208/contributors.rtf b/general/datasets/Hxb_adrenal_1208/contributors.rtf
new file mode 100644
index 0000000..0afa863
--- /dev/null
+++ b/general/datasets/Hxb_adrenal_1208/contributors.rtf
@@ -0,0 +1 @@
+Grieve IC1, Dickens NJ, Pravenec M, Kren V, Hubner N, Cook SA, Aitman TJ, Petretto E, Mangion J. Author information 1MRC Clinical Sciences Centre, Imperial College, Hammersmith Hospital, London, United Kingdom.
diff --git a/general/datasets/Hxb_adrenal_1208/experiment-design.rtf b/general/datasets/Hxb_adrenal_1208/experiment-design.rtf
new file mode 100644
index 0000000..e7386b3
--- /dev/null
+++ b/general/datasets/Hxb_adrenal_1208/experiment-design.rtf
@@ -0,0 +1 @@
+RNA processing:RNA was extracted using Trizol reagent (Invitrogen) and purified using an RNeasy Mini kit from Qiagen. Double-stranded cDNA was generated without pooling. The Ambion MEGAscript T7 kit from Ambion was used to generate biotinylated cRNA for kidney. See Hübner et al. 2005 for additional detail. One-hundred and twenty eight samples passed RNA quality control steps.
diff --git a/general/datasets/Hxb_adrenal_1208/notes.rtf b/general/datasets/Hxb_adrenal_1208/notes.rtf
new file mode 100644
index 0000000..e4b510d
--- /dev/null
+++ b/general/datasets/Hxb_adrenal_1208/notes.rtf
@@ -0,0 +1,9 @@
+Entered by Arthur Centeno, Dec 18, 2008. Data from Herbert Schulz. CEL files processed by AC. Data normalized by AC and RWW (2z+8).
+
+Access to this data set is currently limited to the three teams of researchers who generated the data: Norbert Hübner (MDC, Berlin), Timothy Aitman (UC London), and Michal Pravenec (CAS, Prague). For access to data please contact N. Hübner by email.
+
+The text below was copied from the INFO file for the older (2005) kidney gene expression data set by RWW (Dec 20, 2008). It contains errors and will need to be corrected with the guidance of the data generators and owners.
+
+
+This text file originally copied from the old kidney INFO file that was generated by Robert Williams, Norbert Hübner, Michal Pravnec, Timothy Aitman. This version entered into the adrenal INFO file, December 19, 2008, by RWW, Kathrin Saar Dec 23.
+
diff --git a/general/datasets/Hxb_adrenal_1208/platform.rtf b/general/datasets/Hxb_adrenal_1208/platform.rtf
new file mode 100644
index 0000000..372ab1c
--- /dev/null
+++ b/general/datasets/Hxb_adrenal_1208/platform.rtf
@@ -0,0 +1 @@
+Affymetrix 230A GeneChip: Expression data were generated using the Affymetrix 230A array. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Rat Genome Sequencing Consortium assembly.
diff --git a/general/datasets/Hxb_adrenal_1208/processing.rtf b/general/datasets/Hxb_adrenal_1208/processing.rtf
new file mode 100644
index 0000000..584e49b
--- /dev/null
+++ b/general/datasets/Hxb_adrenal_1208/processing.rtf
@@ -0,0 +1,3 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of pixel measured in each cell.
+Probe set data: The original CEL values were processed using RMA and log2 transformed using our standard 2z +8 transform. This recenters each array to a mean of 8 units and a SD of 2 units. Probe set values are typically the averages of four biological replicates within strain.
+
diff --git a/general/datasets/Hxb_adrenal_1208/summary.rtf b/general/datasets/Hxb_adrenal_1208/summary.rtf
new file mode 100644
index 0000000..6c7a859
--- /dev/null
+++ b/general/datasets/Hxb_adrenal_1208/summary.rtf
@@ -0,0 +1,19 @@
+This December 2008 data set provides estimates of mRNA expression in normal adrenal glands of 31 strains of rats including the hypertensive SHR strain (aka HSR), the normotensive BN strain, and 29 HXB/BXH recombinant inbred strains. Most strains were sampled in quadruplicate (6-week-old males). Animals and tissues were generated by Michal Pravenec and colleagues at the Czech Academy of Sciences (CAS). RNA samples were processed at the Max-Delbrück-Center (MDC), Berlin Buch by Norbert Hübner and colleagues. Transcriptome mapping was carried out by Timothy Aitman and colleagues at the Imperial College, London (ICL). Samples were hybridized individually to a total of approximately 124 Affymetrix RAE230A array processed using the RMA protocol. The expression values of each array have been logged and adjusted to a mean of 8 and a standard deviation of 2 (mean and variance stabilized). This data set complements the kidney and fat data set exploited by Hübner and colleagues 2005.
+
+These data may also be viewed using the eQTL Explorer Java application by John Mangion, Tim Aitman, and colleagues (Mueller et al. 2006).
+
+Genome-wide co-expression analysis in multiple tissues.
+
+And see closely associate set of papers:
+
+
+ - Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease.
+ - Heritability and tissue specificity of expression quantitative trait loci.
+ - Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass.
+ - New insights into the genetic control of gene expression using a Bayesian multi-tissue approach.
+ - The genome sequence of the spontaneously hypertensive rat: Analysis and functional significance.
+ - A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.
+ - Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.
+ - Systems-level approaches reveal conservation of trans-regulated genes in the rat and genetic determinants of blood pressure in humans.
+
diff --git a/general/datasets/Hxb_adrenal_1208/tissue.rtf b/general/datasets/Hxb_adrenal_1208/tissue.rtf
new file mode 100644
index 0000000..d0d0236
--- /dev/null
+++ b/general/datasets/Hxb_adrenal_1208/tissue.rtf
@@ -0,0 +1,530 @@
+All tissues were collected at the age of 6 weeks. Adrenal glands and other organs were rapidly dissected and cleaned of fat, inserted into a vial, and immersed in liquid nitrogen for storage until RNA extraction. THIS IS AN OLD TABLE FOR THE KIDNEY DATA IN THIS INFO FILE ONLY AS A PLACEHOLDER. The table below lists the arrays by strain and sample identifier. Each array was hybridized with mRNA from a single young male rat.
+
+
+
+
+
+
+
+
+ | Strain |
+ SampleID |
+
+
+ | HSR |
+ HSR1 |
+
+
+ | HSR |
+ HSR2 |
+
+
+ | HSR |
+ HSR3 |
+
+
+ | HSR |
+ HSR4 |
+
+
+ | BN |
+ BN1 |
+
+
+ | BN |
+ BN2 |
+
+
+ | BN |
+ BN3 |
+
+
+ | BN |
+ BN4 |
+
+
+ | BN |
+ BN5 |
+
+
+ | HXB1 |
+ RI 01-1 |
+
+
+ | HXB1 |
+ RI 01-2 |
+
+
+ | HXB1 |
+ RI 01-3 |
+
+
+ | HXB1 |
+ RI 01-4 |
+
+
+ | HXB2 |
+ RI 02-1 |
+
+
+ | HXB2 |
+ RI 02-2 |
+
+
+ | HXB2 |
+ RI 02-3 |
+
+
+ | HXB2 |
+ RI 02-4 |
+
+
+ | HXB3 |
+ RI 03-1 |
+
+
+ | HXB3 |
+ RI 03-2 |
+
+
+ | HXB3 |
+ RI 03-3 |
+
+
+ | HXB3 |
+ RI 03-4 |
+
+
+ | HXB4 |
+ RI 04-1 |
+
+
+ | HXB4 |
+ RI 04-2 |
+
+
+ | HXB4 |
+ RI 04-3 |
+
+
+ | HXB4 |
+ RI 04-4 |
+
+
+ | HXB5 |
+ RI 05-1 |
+
+
+ | HXB5 |
+ RI 05-2 |
+
+
+ | HXB5 |
+ RI 05-3 |
+
+
+ | HXB5 |
+ *RI 05-4 |
+
+
+ | HXB7 |
+ RI 07-1 |
+
+
+ | HXB7 |
+ RI 07-2 |
+
+
+ | HXB7 |
+ RI 07-3 |
+
+
+ | HXB7 |
+ RI 07-4 |
+
+
+ | HXB10 |
+ RI 10-1 |
+
+
+ | HXB10 |
+ RI 10-2 |
+
+
+ | HXB10 |
+ RI 10-3 |
+
+
+ | HXB10 |
+ RI 10-4 |
+
+
+ | HXB15 |
+ RI 15-1 |
+
+
+ | HXB15 |
+ RI 15-2 |
+
+
+ | HXB15 |
+ RI 15-3 |
+
+
+ | HXB15 |
+ RI 15-4 |
+
+
+ | HXB17 |
+ RI 17-1 |
+
+
+ | HXB17 |
+ RI 17-2 |
+
+
+ | HXB17 |
+ RI 17-3 |
+
+
+ | HXB17 |
+ RI 17-4 |
+
+
+ | HXB18 |
+ RI 18-1 |
+
+
+ | HXB18 |
+ RI 18-2 |
+
+
+ | HXB18 |
+ RI 18-3 |
+
+
+ | HXB18 |
+ RI 18-4 |
+
+
+ | HXB20 |
+ RI 20-1 |
+
+
+ | HXB20 |
+ RI 20-2 |
+
+
+ | HXB20 |
+ RI 20-3 |
+
+
+ | HXB20 |
+ RI 20-4 |
+
+
+ | HXB21 |
+ RI 21-1 |
+
+
+ | HXB21 |
+ RI 21-2 |
+
+
+ | HXB21 |
+ RI 21-3 |
+
+
+ | HXB21 |
+ RI 21-4 |
+
+
+ | HXB22 |
+ RI 22-1 |
+
+
+ | HXB22 |
+ RI 22-2 |
+
+
+ | HXB22 |
+ RI 22-3 |
+
+
+ | HXB22 |
+ RI 22-4 |
+
+
+ | HXB23 |
+ RI 23-1 |
+
+
+ | HXB23 |
+ RI 23-2 |
+
+
+ | HXB23 |
+ RI 23-3 |
+
+
+ | HXB23 |
+ RI 23-4 |
+
+
+ | HXB24 |
+ RI 24-1 |
+
+
+ | HXB24 |
+ RI 24-2 |
+
+
+ | HXB24 |
+ RI 24-3 |
+
+
+ | HXB24 |
+ RI 24-4 |
+
+
+ | HXB25 |
+ RI 25-1 |
+
+
+ | HXB25 |
+ RI 25-2 |
+
+
+ | HXB25 |
+ RI 25-3 |
+
+
+ | HXB25 |
+ *RI 25-4 |
+
+
+ | HXB26 |
+ RI 26-1 |
+
+
+ | HXB26 |
+ RI 26-2 |
+
+
+ | HXB26 |
+ RI 26-3 |
+
+
+ | HXB26 |
+ RI 26-4 |
+
+
+ | HXB27 |
+ RI 27-1 |
+
+
+ | HXB27 |
+ RI 27-2 |
+
+
+ | HXB27 |
+ RI 27-3 |
+
+
+ | HXB27 |
+ RI 27-4 |
+
+
+ | HXB29 |
+ RI 29-1 |
+
+
+ | HXB29 |
+ RI 29-2 |
+
+
+ | HXB29 |
+ RI 29-3 |
+
+
+ | HXB29 |
+ RI 29-4 |
+
+
+ | HXB31 |
+ RI 31-1 |
+
+
+ | HXB31 |
+ RI 31-2 |
+
+
+ | HXB31 |
+ RI 31-3 |
+
+
+ | HXB31 |
+ RI 31-4 |
+
+
+ | BXH2 |
+ RI 02c-1 |
+
+
+ | BXH2 |
+ RI 02c-2 |
+
+
+ | BXH2 |
+ RI 02c-3 |
+
+
+ | BXH2 |
+ RI 02c-4 |
+
+
+ | BXH3 |
+ RI 03c-1 |
+
+
+ | BXH3 |
+ RI 03c-2 |
+
+
+ | BXH3 |
+ RI 03c-3 |
+
+
+ | BXH3 |
+ RI 03c-4 |
+
+
+ | BXH5 |
+ RI 05c-1 |
+
+
+ | BXH5 |
+ RI 05c-2 |
+
+
+ | BXH5 |
+ RI 05c-3 |
+
+
+ | BXH5 |
+ RI 05c-4 |
+
+
+ | BXH6 |
+ RI 06c-1 |
+
+
+ | BXH6 |
+ RI 06c-2 |
+
+
+ | BXH6 |
+ RI 06c-3 |
+
+
+ | BXH6 |
+ RI 06c-4 |
+
+
+ | BXH8 |
+ RI 08c-1 |
+
+
+ | BXH8 |
+ RI 08c-2 |
+
+
+ | BXH8 |
+ RI 08c-3 |
+
+
+ | BXH8 |
+ RI 08c-4 |
+
+
+ | BXH9 |
+ RI 09c-1 |
+
+
+ | BXH9 |
+ RI 09c-2 |
+
+
+ | BXH9 |
+ RI 09c-3 |
+
+
+ | BXH9 |
+ RI 09c-4 |
+
+
+ | BXH10 |
+ RI 10c-1 |
+
+
+ | BXH10 |
+ RI 10c-2 |
+
+
+ | BXH10 |
+ RI 10c-3 |
+
+
+ | BXH11 |
+ RI 11c-1 |
+
+
+ | BXH11 |
+ RI 11c-2 |
+
+
+ | BXH11 |
+ RI 11c-3 |
+
+
+ | BXH11 |
+ RI 11c-4 |
+
+
+ | BXH12 |
+ RI 12c-1 |
+
+
+ | BXH12 |
+ RI 12c-2 |
+
+
+ | BXH12 |
+ RI 12c-3 |
+
+
+ | BXH12 |
+ RI 12c-4 |
+
+
+ | BXH13 |
+ RI 13c-1 |
+
+
+ | BXH13 |
+ RI 13c-2 |
+
+
+ | BXH13 |
+ RI 13c-3 |
+
+
+ | BXH13 |
+ RI 13c-4 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hxb_heart_1208/acknowledgment.rtf b/general/datasets/Hxb_heart_1208/acknowledgment.rtf
new file mode 100644
index 0000000..ea86842
--- /dev/null
+++ b/general/datasets/Hxb_heart_1208/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported with funds to TJA by the MRC Clinical Sciences Centre, the British Heart Foundation, and the Wellcome Trust Cardiovascular Functional Genomics Initiative; to NH from the German Ministry for Science and Education (National Genome Research Network); to MP and Vladimir Kren from the Grant Agency of the Czech Republic; to MP and TJA from the Wellcome Trust Collaborative Research Initiative grant, to Theodore W Kurtz from the NIH, to TWK and MP from a Fogarty International Research Collaboration Award. Microarrays were a generous donation of Affymetrix Inc. Michal Pravenec thanks the Howard Hughes Medical Institute for its support to him as an international research scholar.
diff --git a/general/datasets/Hxb_heart_1208/cases.rtf b/general/datasets/Hxb_heart_1208/cases.rtf
new file mode 100644
index 0000000..34c7d7a
--- /dev/null
+++ b/general/datasets/Hxb_heart_1208/cases.rtf
@@ -0,0 +1,7 @@
+Data were generated using the HXB/BXH recombinant inbred strains of rats generated over the past 20 years in Prague. The parental strains from which all HXB lines are derived are SHR (SHR/OlaIpcv, abbreviated SHR or HSR = H) and Brown Norway (BN-Lx/Cub= B). These strains have been used extensively to study cardiovascular system physiology and genetics.
+
+
+The HXB strains were bred by Michal Pravenec at the Institute of Physiology, Czech Academy of Sciences. The BXH strains were bred by Vladimir Kren (see Pravenec et al. 1989, 2004) at a similar animal facility at the Institute of Biology and Medical Genetics, 1st Medical Faculty, Charles University. These strains are at approximately the 6oth generation of continuous inbreeding (F60).
+
+Animals used in the transcriptome analyses of multiple tissues (Hübner and colleagues, 2005) were weaned at 4 weeks. Those born at the Charles University were transferred to the Institute of Physiology. Animals were reared on a commerical rat chow (ST-1 from VELAZ, Czech Republic). Four males were house per cage. Cages were made of polystyrene and have a floor size of 22 x 38 cm and height of 23 cm. The bedding was changed twice a week. Light cycle was 12:12 on-off. Vivarium rooms were maintained at 23 deg. C. Rats were sexually naive. All males used in the initial transcriptome studies (Hübner et al., 2005) were born between May and August 2002. They were sacrificed unfastged by rapid cervical dislocation between 9 and 10 AM, following an approved animal protocol (Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague; Animal Protectiion Law of the Czech Republic (311/1997).
+
diff --git a/general/datasets/Hxb_heart_1208/citation.rtf b/general/datasets/Hxb_heart_1208/citation.rtf
new file mode 100644
index 0000000..a8b8cc0
--- /dev/null
+++ b/general/datasets/Hxb_heart_1208/citation.rtf
@@ -0,0 +1 @@
+PLoS One. 2008;3(12):e4033. doi: 10.1371/journal.pone.0004033. Epub 2008 Dec 29.
diff --git a/general/datasets/Hxb_heart_1208/contributors.rtf b/general/datasets/Hxb_heart_1208/contributors.rtf
new file mode 100644
index 0000000..0afa863
--- /dev/null
+++ b/general/datasets/Hxb_heart_1208/contributors.rtf
@@ -0,0 +1 @@
+Grieve IC1, Dickens NJ, Pravenec M, Kren V, Hubner N, Cook SA, Aitman TJ, Petretto E, Mangion J. Author information 1MRC Clinical Sciences Centre, Imperial College, Hammersmith Hospital, London, United Kingdom.
diff --git a/general/datasets/Hxb_heart_1208/experiment-design.rtf b/general/datasets/Hxb_heart_1208/experiment-design.rtf
new file mode 100644
index 0000000..984be42
--- /dev/null
+++ b/general/datasets/Hxb_heart_1208/experiment-design.rtf
@@ -0,0 +1,3 @@
+
+RNA processing:RNA was extracted using Trizol reagent (Invitrogen) and purified using an RNeasy Mini kit from Qiagen. Double-stranded cDNA was generated without pooling. The Ambion MEGAscript T7 kit from Ambion was used to generate biotinylated cRNA for kidney. See Hübner et al. 2005 for additional detail. One-hundred and twenty eight samples passed RNA quality control steps.
+
diff --git a/general/datasets/Hxb_heart_1208/notes.rtf b/general/datasets/Hxb_heart_1208/notes.rtf
new file mode 100644
index 0000000..91c8b67
--- /dev/null
+++ b/general/datasets/Hxb_heart_1208/notes.rtf
@@ -0,0 +1,21 @@
+
+Heart Left Ventricle
+
+http://www.expressionanalysis.com/pdf/Affymetrix/GXRat230v2.pdf
+
+GEO platform id http://www.ncbi.nlm.nih.gov/projects/geo/query/acc.cgi?acc=GPL1355
+
+Data entered by Evan Williams and Rob Williams, Jan 2, 2009.
+
+Mapping of probes http://compbio.dcs.gla.ac.uk/sf/index.html#230map
+
+Entered by Arthur Centeno, Dec 18, 2008. Data from Herbert Schulz. CEL files processed by AC. Data normalized by AC and RWW (2z+8).
+
+Access to this data set is currently limited to the three teams of researchers who generated the data: Norbert Hübner (MDC, Berlin), Timothy Aitman (UC London), and Michal Pravenec (CAS, Prague). For access to data please contact N. Hübner by email.
+
+The text below was copied from the INFO file for the older (2005) kidney gene expression data set by RWW (Dec 20, 2008). It contains errors and will need to be corrected with the guidance of the data generators and owners.
+
+
+
+This text file originally copied from the old kidney INFO file that was generated by Robert Williams, Norbert Hübner, Michal Pravnec, Timothy Aitman. This version entered into the adrenal INFO file, December 19, 2008, by RWW, Kathrin Saar Dec 23.
+
diff --git a/general/datasets/Hxb_heart_1208/platform.rtf b/general/datasets/Hxb_heart_1208/platform.rtf
new file mode 100644
index 0000000..b6eb818
--- /dev/null
+++ b/general/datasets/Hxb_heart_1208/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix 230Av2 GeneChip: Expression data were generated using the Affymetrix 230Av2 array (GEO_GPL341). The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Rat Genome Sequencing Consortium assembly.
+
diff --git a/general/datasets/Hxb_heart_1208/processing.rtf b/general/datasets/Hxb_heart_1208/processing.rtf
new file mode 100644
index 0000000..9bb9584
--- /dev/null
+++ b/general/datasets/Hxb_heart_1208/processing.rtf
@@ -0,0 +1,4 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of pixel measured in each cell.
+
+Probe set data: The original CEL values were processed using RMA and log2 transformed using our standard 2z +8 transform. This recenters each array to a mean of 8 units and a SD of 2 units. Probe set values are typically the averages of four biological replicates within strain.
+
diff --git a/general/datasets/Hxb_heart_1208/summary.rtf b/general/datasets/Hxb_heart_1208/summary.rtf
new file mode 100644
index 0000000..88bf1b8
--- /dev/null
+++ b/general/datasets/Hxb_heart_1208/summary.rtf
@@ -0,0 +1,19 @@
+This December 2008 data set provides estimates of mRNA expression in normal hearts of 31 strains of rats including the hypertensive SHR strain (aka HSR), the normotensive BN strain, and 29 HXB/BXH recombinant inbred strains. Most strains were sampled in quadruplicate (6-week-old males). Animals and tissues were generated by Michal Pravenec and colleagues at the Czech Academy of Sciences (CAS). RNA samples were processed at the Max-Delbrück-Center (MDC), Berlin Buch by Norbert Hübner and colleagues. Transcriptome mapping was carried out by Timothy Aitman and colleagues at the Imperial College, London (ICL). Samples were hybridized individually to a total of approximately XXX Affymetrix RAE230A array processed using the RMA protocol. The expression values of each array have been logged and adjusted to a mean of 8 and a standard deviation of 2 (mean and variance stabilized). This data set complements the kidney and fat data set exploited by Hübner and colleagues 2005.
+
+These data may also be viewed using the eQTL Explorer Java application by John Mangion, Tim Aitman, and colleagues (Mueller et al. 2006).
+
+Genome-wide co-expression analysis in multiple tissues.
+
+And see closely associate set of papers:
+
+
+ - Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease.
+ - Heritability and tissue specificity of expression quantitative trait loci.
+ - Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass.
+ - New insights into the genetic control of gene expression using a Bayesian multi-tissue approach.
+ - The genome sequence of the spontaneously hypertensive rat: Analysis and functional significance.
+ - A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.
+ - Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.
+ - Systems-level approaches reveal conservation of trans-regulated genes in the rat and genetic determinants of blood pressure in humans.
+
diff --git a/general/datasets/Hxb_heart_1208/tissue.rtf b/general/datasets/Hxb_heart_1208/tissue.rtf
new file mode 100644
index 0000000..485694f
--- /dev/null
+++ b/general/datasets/Hxb_heart_1208/tissue.rtf
@@ -0,0 +1,530 @@
+All tissues were collected at the age of 6 weeks. Hearts and other organs were rapidly dissected and cleaned of fat, inserted into a vial, and immersed in liquid nitrogen for storage until RNA extraction. THIS IS AN OLD TABLE FOR THE KIDNEY DATA IN THIS INFO FILE ONLY AS A PLACEHOLDER. The table below lists the arrays by strain and sample identifier. Each array was hybridized with mRNA from a single young male rat.
+
+
+
+
+
+
+
+
+ | Strain |
+ SampleID |
+
+
+ | HSR |
+ HSR1 |
+
+
+ | HSR |
+ HSR2 |
+
+
+ | HSR |
+ HSR3 |
+
+
+ | HSR |
+ HSR4 |
+
+
+ | BN |
+ BN1 |
+
+
+ | BN |
+ BN2 |
+
+
+ | BN |
+ BN3 |
+
+
+ | BN |
+ BN4 |
+
+
+ | BN |
+ BN5 |
+
+
+ | HXB1 |
+ RI 01-1 |
+
+
+ | HXB1 |
+ RI 01-2 |
+
+
+ | HXB1 |
+ RI 01-3 |
+
+
+ | HXB1 |
+ RI 01-4 |
+
+
+ | HXB2 |
+ RI 02-1 |
+
+
+ | HXB2 |
+ RI 02-2 |
+
+
+ | HXB2 |
+ RI 02-3 |
+
+
+ | HXB2 |
+ RI 02-4 |
+
+
+ | HXB3 |
+ RI 03-1 |
+
+
+ | HXB3 |
+ RI 03-2 |
+
+
+ | HXB3 |
+ RI 03-3 |
+
+
+ | HXB3 |
+ RI 03-4 |
+
+
+ | HXB4 |
+ RI 04-1 |
+
+
+ | HXB4 |
+ RI 04-2 |
+
+
+ | HXB4 |
+ RI 04-3 |
+
+
+ | HXB4 |
+ RI 04-4 |
+
+
+ | HXB5 |
+ RI 05-1 |
+
+
+ | HXB5 |
+ RI 05-2 |
+
+
+ | HXB5 |
+ RI 05-3 |
+
+
+ | HXB5 |
+ *RI 05-4 |
+
+
+ | HXB7 |
+ RI 07-1 |
+
+
+ | HXB7 |
+ RI 07-2 |
+
+
+ | HXB7 |
+ RI 07-3 |
+
+
+ | HXB7 |
+ RI 07-4 |
+
+
+ | HXB10 |
+ RI 10-1 |
+
+
+ | HXB10 |
+ RI 10-2 |
+
+
+ | HXB10 |
+ RI 10-3 |
+
+
+ | HXB10 |
+ RI 10-4 |
+
+
+ | HXB15 |
+ RI 15-1 |
+
+
+ | HXB15 |
+ RI 15-2 |
+
+
+ | HXB15 |
+ RI 15-3 |
+
+
+ | HXB15 |
+ RI 15-4 |
+
+
+ | HXB17 |
+ RI 17-1 |
+
+
+ | HXB17 |
+ RI 17-2 |
+
+
+ | HXB17 |
+ RI 17-3 |
+
+
+ | HXB17 |
+ RI 17-4 |
+
+
+ | HXB18 |
+ RI 18-1 |
+
+
+ | HXB18 |
+ RI 18-2 |
+
+
+ | HXB18 |
+ RI 18-3 |
+
+
+ | HXB18 |
+ RI 18-4 |
+
+
+ | HXB20 |
+ RI 20-1 |
+
+
+ | HXB20 |
+ RI 20-2 |
+
+
+ | HXB20 |
+ RI 20-3 |
+
+
+ | HXB20 |
+ RI 20-4 |
+
+
+ | HXB21 |
+ RI 21-1 |
+
+
+ | HXB21 |
+ RI 21-2 |
+
+
+ | HXB21 |
+ RI 21-3 |
+
+
+ | HXB21 |
+ RI 21-4 |
+
+
+ | HXB22 |
+ RI 22-1 |
+
+
+ | HXB22 |
+ RI 22-2 |
+
+
+ | HXB22 |
+ RI 22-3 |
+
+
+ | HXB22 |
+ RI 22-4 |
+
+
+ | HXB23 |
+ RI 23-1 |
+
+
+ | HXB23 |
+ RI 23-2 |
+
+
+ | HXB23 |
+ RI 23-3 |
+
+
+ | HXB23 |
+ RI 23-4 |
+
+
+ | HXB24 |
+ RI 24-1 |
+
+
+ | HXB24 |
+ RI 24-2 |
+
+
+ | HXB24 |
+ RI 24-3 |
+
+
+ | HXB24 |
+ RI 24-4 |
+
+
+ | HXB25 |
+ RI 25-1 |
+
+
+ | HXB25 |
+ RI 25-2 |
+
+
+ | HXB25 |
+ RI 25-3 |
+
+
+ | HXB25 |
+ *RI 25-4 |
+
+
+ | HXB26 |
+ RI 26-1 |
+
+
+ | HXB26 |
+ RI 26-2 |
+
+
+ | HXB26 |
+ RI 26-3 |
+
+
+ | HXB26 |
+ RI 26-4 |
+
+
+ | HXB27 |
+ RI 27-1 |
+
+
+ | HXB27 |
+ RI 27-2 |
+
+
+ | HXB27 |
+ RI 27-3 |
+
+
+ | HXB27 |
+ RI 27-4 |
+
+
+ | HXB29 |
+ RI 29-1 |
+
+
+ | HXB29 |
+ RI 29-2 |
+
+
+ | HXB29 |
+ RI 29-3 |
+
+
+ | HXB29 |
+ RI 29-4 |
+
+
+ | HXB31 |
+ RI 31-1 |
+
+
+ | HXB31 |
+ RI 31-2 |
+
+
+ | HXB31 |
+ RI 31-3 |
+
+
+ | HXB31 |
+ RI 31-4 |
+
+
+ | BXH2 |
+ RI 02c-1 |
+
+
+ | BXH2 |
+ RI 02c-2 |
+
+
+ | BXH2 |
+ RI 02c-3 |
+
+
+ | BXH2 |
+ RI 02c-4 |
+
+
+ | BXH3 |
+ RI 03c-1 |
+
+
+ | BXH3 |
+ RI 03c-2 |
+
+
+ | BXH3 |
+ RI 03c-3 |
+
+
+ | BXH3 |
+ RI 03c-4 |
+
+
+ | BXH5 |
+ RI 05c-1 |
+
+
+ | BXH5 |
+ RI 05c-2 |
+
+
+ | BXH5 |
+ RI 05c-3 |
+
+
+ | BXH5 |
+ RI 05c-4 |
+
+
+ | BXH6 |
+ RI 06c-1 |
+
+
+ | BXH6 |
+ RI 06c-2 |
+
+
+ | BXH6 |
+ RI 06c-3 |
+
+
+ | BXH6 |
+ RI 06c-4 |
+
+
+ | BXH8 |
+ RI 08c-1 |
+
+
+ | BXH8 |
+ RI 08c-2 |
+
+
+ | BXH8 |
+ RI 08c-3 |
+
+
+ | BXH8 |
+ RI 08c-4 |
+
+
+ | BXH9 |
+ RI 09c-1 |
+
+
+ | BXH9 |
+ RI 09c-2 |
+
+
+ | BXH9 |
+ RI 09c-3 |
+
+
+ | BXH9 |
+ RI 09c-4 |
+
+
+ | BXH10 |
+ RI 10c-1 |
+
+
+ | BXH10 |
+ RI 10c-2 |
+
+
+ | BXH10 |
+ RI 10c-3 |
+
+
+ | BXH11 |
+ RI 11c-1 |
+
+
+ | BXH11 |
+ RI 11c-2 |
+
+
+ | BXH11 |
+ RI 11c-3 |
+
+
+ | BXH11 |
+ RI 11c-4 |
+
+
+ | BXH12 |
+ RI 12c-1 |
+
+
+ | BXH12 |
+ RI 12c-2 |
+
+
+ | BXH12 |
+ RI 12c-3 |
+
+
+ | BXH12 |
+ RI 12c-4 |
+
+
+ | BXH13 |
+ RI 13c-1 |
+
+
+ | BXH13 |
+ RI 13c-2 |
+
+
+ | BXH13 |
+ RI 13c-3 |
+
+
+ | BXH13 |
+ RI 13c-4 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Hxb_liver_1208/acknowledgment.rtf b/general/datasets/Hxb_liver_1208/acknowledgment.rtf
new file mode 100644
index 0000000..ea86842
--- /dev/null
+++ b/general/datasets/Hxb_liver_1208/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported with funds to TJA by the MRC Clinical Sciences Centre, the British Heart Foundation, and the Wellcome Trust Cardiovascular Functional Genomics Initiative; to NH from the German Ministry for Science and Education (National Genome Research Network); to MP and Vladimir Kren from the Grant Agency of the Czech Republic; to MP and TJA from the Wellcome Trust Collaborative Research Initiative grant, to Theodore W Kurtz from the NIH, to TWK and MP from a Fogarty International Research Collaboration Award. Microarrays were a generous donation of Affymetrix Inc. Michal Pravenec thanks the Howard Hughes Medical Institute for its support to him as an international research scholar.
diff --git a/general/datasets/Hxb_liver_1208/citation.rtf b/general/datasets/Hxb_liver_1208/citation.rtf
new file mode 100644
index 0000000..a8b8cc0
--- /dev/null
+++ b/general/datasets/Hxb_liver_1208/citation.rtf
@@ -0,0 +1 @@
+PLoS One. 2008;3(12):e4033. doi: 10.1371/journal.pone.0004033. Epub 2008 Dec 29.
diff --git a/general/datasets/Hxb_liver_1208/contributors.rtf b/general/datasets/Hxb_liver_1208/contributors.rtf
new file mode 100644
index 0000000..0afa863
--- /dev/null
+++ b/general/datasets/Hxb_liver_1208/contributors.rtf
@@ -0,0 +1 @@
+Grieve IC1, Dickens NJ, Pravenec M, Kren V, Hubner N, Cook SA, Aitman TJ, Petretto E, Mangion J. Author information 1MRC Clinical Sciences Centre, Imperial College, Hammersmith Hospital, London, United Kingdom.
diff --git a/general/datasets/Hxb_liver_1208/platform.rtf b/general/datasets/Hxb_liver_1208/platform.rtf
new file mode 100644
index 0000000..b6eb818
--- /dev/null
+++ b/general/datasets/Hxb_liver_1208/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix 230Av2 GeneChip: Expression data were generated using the Affymetrix 230Av2 array (GEO_GPL341). The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Rat Genome Sequencing Consortium assembly.
+
diff --git a/general/datasets/Hxb_liver_1208/summary.rtf b/general/datasets/Hxb_liver_1208/summary.rtf
new file mode 100644
index 0000000..d524ef3
--- /dev/null
+++ b/general/datasets/Hxb_liver_1208/summary.rtf
@@ -0,0 +1,14 @@
+Genome-wide co-expression analysis in multiple tissues.
+
+And see closely associate set of papers:
+
+
+ - Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease.
+ - Heritability and tissue specificity of expression quantitative trait loci.
+ - Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass.
+ - New insights into the genetic control of gene expression using a Bayesian multi-tissue approach.
+ - The genome sequence of the spontaneously hypertensive rat: Analysis and functional significance.
+ - A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.
+ - Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.
+ - Systems-level approaches reveal conservation of trans-regulated genes in the rat and genetic determinants of blood pressure in humans.
+
diff --git a/general/datasets/Hxbbxhgeno/citation.rtf b/general/datasets/Hxbbxhgeno/citation.rtf
new file mode 100644
index 0000000..372e9b9
--- /dev/null
+++ b/general/datasets/Hxbbxhgeno/citation.rtf
@@ -0,0 +1 @@
+http://genome.ucsc.edu/cgi-bin/hgGateway?db=rn6
diff --git a/general/datasets/Hxbbxhgeno/summary.rtf b/general/datasets/Hxbbxhgeno/summary.rtf
new file mode 100644
index 0000000..098796a
--- /dev/null
+++ b/general/datasets/Hxbbxhgeno/summary.rtf
@@ -0,0 +1,7 @@
+UCSC Genome Browser assembly ID: rn6
+Sequencing/Assembly provider ID: RGSC Rnor_6.0
+Assembly date: Jul. 2014
+Accession ID: GCA_000001895.4
+NCBI Genome ID: 73 (Rattus norvegicus)
+NCBI Assembly ID: 191871 (Rnor_6.0)
+NCBI BioProject ID: 10629
diff --git a/general/datasets/Hzi_0408_m/cases.rtf b/general/datasets/Hzi_0408_m/cases.rtf
new file mode 100644
index 0000000..83b146d
--- /dev/null
+++ b/general/datasets/Hzi_0408_m/cases.rtf
@@ -0,0 +1,784 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Array |
+ Sample |
+ Strain |
+ Sex |
+ Age |
+ Color |
+ Pool Size |
+ Source |
+
+
+ | 1 |
+ R4435LU.CEL |
+ R4435LU |
+ BXD100 |
+ F |
+ 64 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 2 |
+ R4436LU.CEL |
+ R4436LU |
+ BXD14 |
+ F |
+ 85 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 3 |
+ R4437LU.CEL |
+ R4437LU |
+ BXD34 |
+ F |
+ 58 |
+ black |
+ 5 |
+ UTM RW |
+
+
+ | 4 |
+ R4438LU.CEL |
+ R4438LU |
+ BXD39 |
+ F |
+ 63 |
+ gray |
+ 3 |
+ UTM RW |
+
+
+ | 5 |
+ R4439LU.CEL |
+ R4439LU |
+ BXD40 |
+ F |
+ 54 |
+ gray |
+ 3 |
+ ORNL |
+
+
+ | 6 |
+ R4440LU.CEL |
+ R4440LU |
+ BXD45 |
+ F |
+ 60 |
+ dilute brown DBA |
+ 4 |
+ UTM RW |
+
+
+ | 7 |
+ R4441LU.CEL |
+ R4441LU |
+ BXD50 |
+ F |
+ 64 |
+ dilute brown DBA |
+ 4 |
+ ORNL |
+
+
+ | 8 |
+ R4442LU.CEL |
+ R4442LU |
+ BXD1 |
+ F |
+ 88 |
+ dilute brown DBA |
+ 3 |
+ UTM RW |
+
+
+ | 9 |
+ R4443LU.CEL |
+ R4443LU |
+ BXD16 |
+ F |
+ 79 |
+ gray |
+ 3 |
+ ORNL |
+
+
+ | 10 |
+ R4444LU.CEL |
+ R4444LU |
+ BXD12 |
+ F |
+ 61 |
+ gray |
+ 5 |
+ UTM RW |
+
+
+ | 11 |
+ R4445LU.CEL |
+ R4445LU |
+ BXD21 |
+ F |
+ 50 |
+ dilute brown DBA |
+ 3 |
+ ORNL |
+
+
+ | 12 |
+ R4446LU.CEL |
+ R4446LU |
+ BXD19 |
+ F |
+ 49 |
+ gray |
+ 3 |
+ ORNL |
+
+
+ | 13 |
+ R4447LU.CEL |
+ R4447LU |
+ BXD27 |
+ F |
+ 85 |
+ brown |
+ 3 |
+ UTM RW |
+
+
+ | 14 |
+ R4448LU.CEL |
+ R4448LU |
+ BXD31 |
+ F |
+ 81 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 15 |
+ R4449LU.CEL |
+ R4449LU |
+ BXD32 |
+ F |
+ 68 |
+ black |
+ 5 |
+ ORNL |
+
+
+ | 16 |
+ R4450LU.CEL |
+ R4450LU |
+ BXD33 |
+ F |
+ 61 |
+ gray |
+ 2 |
+ ORNL |
+
+
+ | 17 |
+ R4451LU.CEL |
+ R4451LU |
+ BXD42 |
+ F |
+ 65 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 18 |
+ R4452LU.CEL |
+ R4452LU |
+ BXD43 |
+ F |
+ 79 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 19 |
+ R4453LU.CEL |
+ R4453LU |
+ BXD45 |
+ F |
+ 60 |
+ dilute brown DBA |
+ 4 |
+ UTM RW |
+
+
+ | 20 |
+ R4454LU.CEL |
+ R4454LU |
+ BXD55 |
+ M |
+ 80 |
+ brown |
+ 3 |
+ UTM RW |
+
+
+ | 21 |
+ R4455LU.CEL |
+ R4455LU |
+ BXD56 |
+ M |
+ 91 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 22 |
+ R4456LU.CEL |
+ R4456LU |
+ BXD66 |
+ F |
+ 80 |
+ brown |
+ 3 |
+ UTM RW |
+
+
+ | 23 |
+ R4457LU.CEL |
+ R4457LU |
+ BXD68 |
+ F |
+ 65 |
+ brown |
+ 4 |
+ UTM RW |
+
+
+ | 24 |
+ R4459LU-re.CEL |
+ R4459LU |
+ BXD89 |
+ F |
+ 79 |
+ dilute brown DBA |
+ 2 |
+ UTM RW |
+
+
+ | 25 |
+ R4460LU.CEL |
+ R4460LU |
+ BXD51 |
+ M |
+ 81 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 26 |
+ R4461LU.CEL |
+ R4461LU |
+ BXD97 |
+ F |
+ N/A |
+ N/A |
+ N/A |
+ N/A |
+
+
+ | 27 |
+ R4462LU.CEL |
+ R4462LU |
+ BXD48 |
+ F |
+ 61 |
+ black |
+ 3 |
+ ORNL |
+
+
+ | 28 |
+ R4463LU.CEL |
+ R4463LU |
+ BXD60 |
+ M |
+ 93 |
+ brown |
+ 2 |
+ UTM RW |
+
+
+ | 29 |
+ R4464LU.CEL |
+ R4464LU |
+ BXD62 |
+ M |
+ 80 |
+ brown |
+ 2 |
+ UTM RW |
+
+
+ | 30 |
+ R4465LU.CEL |
+ R4465LU |
+ BXD69 |
+ M |
+ 63 |
+ dilute brown DBA |
+ 5 |
+ UTM RW |
+
+
+ | 31 |
+ R4466LU.CEL |
+ R4466LU |
+ BXD70 |
+ M |
+ 75 |
+ dilute brown DBA |
+ 3 |
+ UTM RW |
+
+
+ | 32 |
+ R4467LU.CEL |
+ R4467LU |
+ BXD71 |
+ M |
+ 64 |
+ dilute brown DBA |
+ 4 |
+ UTM RW |
+
+
+ | 33 |
+ R4468LU.CEL |
+ R4468LU |
+ BXD73 |
+ M |
+ 59 |
+ dilute brown DBA |
+ 3 |
+ UTM RW |
+
+
+ | 34 |
+ R4469L.CEL |
+ R4469LU |
+ BXD75 |
+ M |
+ 51 |
+ dilute brown DBA |
+ 4 |
+ UTM RW |
+
+
+ | 35 |
+ R4470L.CEL |
+ R4470LU |
+ BXD2 |
+ M |
+ 84 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 36 |
+ R4471H-re.CEL |
+ R4471LU |
+ BXD83 |
+ M |
+ 75 |
+ dilute brown DBA |
+ 2 |
+ UTM RW |
+
+
+ | 37 |
+ R4472L.CEL |
+ R4472LU |
+ BXD84 |
+ M |
+ 78 |
+ dilute brown DBA |
+ 2 |
+ UTM RW |
+
+
+ | 38 |
+ R4473LU.CEL |
+ R4473LU |
+ BXD86 |
+ M |
+ 77 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 39 |
+ R4474LU.CEL |
+ R4474LU |
+ BXD87 |
+ M |
+ 67 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 40 |
+ R4475LU.CEL |
+ R4475LU |
+ BXD9 |
+ M |
+ 78 |
+ dilute brown DBA |
+ 3 |
+ UTM RW |
+
+
+ | 41 |
+ R4476LU.CEL |
+ R4476LU |
+ BXD90 |
+ M |
+ 63 |
+ dilute brown DBA |
+ 3 |
+ UTM RW |
+
+
+ | 42 |
+ R4477LU.CEL |
+ R4477LU |
+ BXD65 |
+ M |
+ 59 |
+ brown |
+ 3 |
+ ORNL |
+
+
+ | 43 |
+ R4478LU.CEL |
+ R4478LU |
+ BXD6 |
+ M |
+ 92 |
+ gray |
+ 3 |
+ UTM RW |
+
+
+ | 44 |
+ R4479LU.CEL |
+ R4479LU |
+ BXD96 |
+ M |
+ 71 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 45 |
+ R4480LU.CEL |
+ R4480LU |
+ BXD97 |
+ M |
+ 80 |
+ brown |
+ 3 |
+ UTM RW |
+
+
+ | 46 |
+ R4481LU.CEL |
+ R4481LU |
+ BXD98 |
+ M |
+ 80 |
+ dilute brown DBA |
+ 2 |
+ UTM RW |
+
+
+ | 47 |
+ R4482LU.CEL |
+ R4482LU |
+ BXD99 |
+ M |
+ 72 |
+ dilute brown DBA |
+ 2 |
+ UTM RW |
+
+
+ | 48 |
+ R4483LU.CEL |
+ R4483LU |
+ BXD22 |
+ M |
+ 66 |
+ gray |
+ 2 |
+ UTM RW |
+
+
+ | 49 |
+ R4484LU.CEL |
+ R4484LU |
+ BXD25 |
+ M |
+ 54 |
+ brown |
+ 3 |
+ UTM RW |
+
+
+ | 50 |
+ R4485LU.CEL |
+ R4485LU |
+ B6D2F1 |
+ M |
+ 62 |
+ black |
+ 5 |
+ UTM RW |
+
+
+ | 51 |
+ R4486LU.CEL |
+ R4486LU |
+ B6D2F1 |
+ F |
+ 70 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 52 |
+ R4487LU.CEL |
+ R4487LU |
+ BALB/cByJ |
+ F |
+ 91 |
+ white |
+ 3 |
+ UTM RW |
+
+
+ | 53 |
+ R4488LU.CEL |
+ R4488LU |
+ BALB/cByJ |
+ M |
+ 91 |
+ white |
+ 2 |
+ UTM RW |
+
+
+ | 54 |
+ R4489LU.CEL |
+ R4489LU |
+ D2B6F1 |
+ F |
+ 61 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 55 |
+ R4490LU.CEL |
+ R4490LU |
+ D2B6F1 |
+ M |
+ 61 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 56 |
+ R4491LU.CEL |
+ R4491LU |
+ FVB/NJ |
+ F |
+ 62 |
+ white |
+ 5 |
+ UTM RW |
+
+
+ | 57 |
+ R4492LU.CEL |
+ R4492LU |
+ FVB/NJ |
+ M |
+ 73 |
+ white |
+ 3 |
+ UTM RW |
+
+
+ | 58 |
+ R4493LU.CEL |
+ R4493LU |
+ WSB/EiJ |
+ F |
+ 76 |
+ agouti |
+ 3 |
+ UTM RW |
+
+
+ | 59 |
+ R4494LU.CEL |
+ R4494LU |
+ WSB/EiJ |
+ M |
+ 76 |
+ agouti |
+ 3 |
+ UTM RW |
+
+
+ | 60 |
+ R4495LU.CEL |
+ R4495LU |
+ C57BL/6J |
+ F |
+ 65 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 61 |
+ R4496LU.CEL |
+ R4496LU |
+ C57BL/6J |
+ M |
+ 65 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 62 |
+ R4497LU.CEL |
+ R4497LU |
+ 129X1/SvJ |
+ F |
+ 65 |
+ white |
+ 4 |
+ JAX |
+
+
+ | 63 |
+ R4498LU.CEL |
+ R4498LU |
+ 129X1/SvJ |
+ M |
+ 66 |
+ white |
+ 4 |
+ JAX |
+
+
+ | 64 |
+ R4499LU.CEL |
+ R4499LU |
+ DBA/2J |
+ F |
+ 65 |
+ dilute brown DBA |
+ 3 |
+ ORNL |
+
+
+ | 65 |
+ R4500LU.CEL |
+ R4500LU |
+ DBA/2J |
+ M |
+ 59 |
+ dilute brown DBA |
+ 2 |
+ JAX |
+
+
+ | 66 |
+ R4501LU.CEL |
+ R4501LU |
+ LP/J |
+ F |
+ 65 |
+ agouti |
+ 4 |
+ JAX |
+
+
+ | 67 |
+ R4502LU.CEL |
+ R4502LU |
+ LP/J |
+ M |
+ 65 |
+ agouti |
+ 4 |
+ JAX |
+
+
+ | 68 |
+ R4503LU.CEL |
+ R4503LU |
+ SJL/J |
+ F |
+ 63 |
+ white |
+ 4 |
+ JAX |
+
+
+ | 69 |
+ R4504LU.CEL |
+ R4504LU |
+ SJL/J |
+ M |
+ 65 |
+ white |
+ 4 |
+ JAX |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Hzi_0408_m/summary.rtf b/general/datasets/Hzi_0408_m/summary.rtf
new file mode 100644
index 0000000..5d3c1a7
--- /dev/null
+++ b/general/datasets/Hzi_0408_m/summary.rtf
@@ -0,0 +1,37 @@
+Phase I of BXD lung transcriptome mapping project. Project organized by Drs. Robert Williams, Klaus Schughart, Lu Lu. Started November 29, 2008. There are total 70 samples in phase I including 50 BXD strains and 10 paired inbred strains.
+
+Respir Res. 2011 May 2;12:61. doi: 10.1186/1465-9921-12-61.
+
+Genome-wide analysis of the mouse lung transcriptome reveals novel molecular gene interaction networks and cell-specific expression signatures.
+
+Alberts R1, Lu L, Williams RW, Schughart K.
+
+
+
+Erratum in
+
+
+ - Respir Res. 2012;13(1):5.
+
+
+Abstract
+
+BACKGROUND:
+
+The lung is critical in surveillance and initial defense against pathogens. In humans, as in mice, individual genetic differences strongly modulate pulmonary responses to infectious agents, severity of lung disease, and potential allergic reactions. In a first step towards understanding genetic predisposition and pulmonary molecular networks that underlie individual differences in disease vulnerability, we performed a global analysis of normative lung gene expression levels in inbred mouse strains and a large family of BXD strains that are widely used for systems genetics. Our goal is to provide a key community resource on the genetics of the normative lungtranscriptome that can serve as a foundation for experimental analysis and allow predicting genetic predisposition and response to pathogens, allergens, and xenobiotics.
+
+METHODS:
+
+Steady-state polyA+ mRNA levels were assayed across a diverse and fully genotyped panel of 57 isogenic strains using the Affymetrix M430 2.0 array. Correlations of expression levels between genes were determined. Global expression QTL (eQTL) analysis and network covariance analysis was performed using tools and resources in GeneNetwork http://www.genenetwork.org.
+
+RESULTS:
+
+Expression values were highly variable across strains and in many cases exhibited a high heritability factor. Several genes which showed a restricted expression to lung tissue were identified. Using correlations between gene expression values across all strains, we defined and extended memberships of several important molecular networks in the lung. Furthermore, we were able to extract signatures of immune cell subpopulations and characterize co-variation and shared genetic modulation. Known QTL regions for respiratory infection susceptibility were investigated and several cis-eQTL genes were identified. Numerous cis- and trans-regulated transcripts and chromosomal intervals with strong regulatory activity were mapped. The Cyp1a1 P450 transcript had a strong trans-acting eQTL (LOD 11.8) on Chr 12 at 36 ± 1 Mb. This interval contains the transcription factor Ahr that has a critical mis-sense allele in the DBA/2J haplotype and evidently modulates transcriptional activation by AhR.
+
+CONCLUSIONS:
+
+Large-scale gene expression analyses in genetic reference populations revealed lung-specific and immune-cell gene expression profiles and suggested specific gene regulatory interactions.
+
+
+ - PMID:21535883 PMCID:PMC3105947 DOI:10.1186/1465-9921-12-61
+
diff --git a/general/datasets/Hzi_0408_r/cases.rtf b/general/datasets/Hzi_0408_r/cases.rtf
new file mode 100644
index 0000000..83b146d
--- /dev/null
+++ b/general/datasets/Hzi_0408_r/cases.rtf
@@ -0,0 +1,784 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Array |
+ Sample |
+ Strain |
+ Sex |
+ Age |
+ Color |
+ Pool Size |
+ Source |
+
+
+ | 1 |
+ R4435LU.CEL |
+ R4435LU |
+ BXD100 |
+ F |
+ 64 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 2 |
+ R4436LU.CEL |
+ R4436LU |
+ BXD14 |
+ F |
+ 85 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 3 |
+ R4437LU.CEL |
+ R4437LU |
+ BXD34 |
+ F |
+ 58 |
+ black |
+ 5 |
+ UTM RW |
+
+
+ | 4 |
+ R4438LU.CEL |
+ R4438LU |
+ BXD39 |
+ F |
+ 63 |
+ gray |
+ 3 |
+ UTM RW |
+
+
+ | 5 |
+ R4439LU.CEL |
+ R4439LU |
+ BXD40 |
+ F |
+ 54 |
+ gray |
+ 3 |
+ ORNL |
+
+
+ | 6 |
+ R4440LU.CEL |
+ R4440LU |
+ BXD45 |
+ F |
+ 60 |
+ dilute brown DBA |
+ 4 |
+ UTM RW |
+
+
+ | 7 |
+ R4441LU.CEL |
+ R4441LU |
+ BXD50 |
+ F |
+ 64 |
+ dilute brown DBA |
+ 4 |
+ ORNL |
+
+
+ | 8 |
+ R4442LU.CEL |
+ R4442LU |
+ BXD1 |
+ F |
+ 88 |
+ dilute brown DBA |
+ 3 |
+ UTM RW |
+
+
+ | 9 |
+ R4443LU.CEL |
+ R4443LU |
+ BXD16 |
+ F |
+ 79 |
+ gray |
+ 3 |
+ ORNL |
+
+
+ | 10 |
+ R4444LU.CEL |
+ R4444LU |
+ BXD12 |
+ F |
+ 61 |
+ gray |
+ 5 |
+ UTM RW |
+
+
+ | 11 |
+ R4445LU.CEL |
+ R4445LU |
+ BXD21 |
+ F |
+ 50 |
+ dilute brown DBA |
+ 3 |
+ ORNL |
+
+
+ | 12 |
+ R4446LU.CEL |
+ R4446LU |
+ BXD19 |
+ F |
+ 49 |
+ gray |
+ 3 |
+ ORNL |
+
+
+ | 13 |
+ R4447LU.CEL |
+ R4447LU |
+ BXD27 |
+ F |
+ 85 |
+ brown |
+ 3 |
+ UTM RW |
+
+
+ | 14 |
+ R4448LU.CEL |
+ R4448LU |
+ BXD31 |
+ F |
+ 81 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 15 |
+ R4449LU.CEL |
+ R4449LU |
+ BXD32 |
+ F |
+ 68 |
+ black |
+ 5 |
+ ORNL |
+
+
+ | 16 |
+ R4450LU.CEL |
+ R4450LU |
+ BXD33 |
+ F |
+ 61 |
+ gray |
+ 2 |
+ ORNL |
+
+
+ | 17 |
+ R4451LU.CEL |
+ R4451LU |
+ BXD42 |
+ F |
+ 65 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 18 |
+ R4452LU.CEL |
+ R4452LU |
+ BXD43 |
+ F |
+ 79 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 19 |
+ R4453LU.CEL |
+ R4453LU |
+ BXD45 |
+ F |
+ 60 |
+ dilute brown DBA |
+ 4 |
+ UTM RW |
+
+
+ | 20 |
+ R4454LU.CEL |
+ R4454LU |
+ BXD55 |
+ M |
+ 80 |
+ brown |
+ 3 |
+ UTM RW |
+
+
+ | 21 |
+ R4455LU.CEL |
+ R4455LU |
+ BXD56 |
+ M |
+ 91 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 22 |
+ R4456LU.CEL |
+ R4456LU |
+ BXD66 |
+ F |
+ 80 |
+ brown |
+ 3 |
+ UTM RW |
+
+
+ | 23 |
+ R4457LU.CEL |
+ R4457LU |
+ BXD68 |
+ F |
+ 65 |
+ brown |
+ 4 |
+ UTM RW |
+
+
+ | 24 |
+ R4459LU-re.CEL |
+ R4459LU |
+ BXD89 |
+ F |
+ 79 |
+ dilute brown DBA |
+ 2 |
+ UTM RW |
+
+
+ | 25 |
+ R4460LU.CEL |
+ R4460LU |
+ BXD51 |
+ M |
+ 81 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 26 |
+ R4461LU.CEL |
+ R4461LU |
+ BXD97 |
+ F |
+ N/A |
+ N/A |
+ N/A |
+ N/A |
+
+
+ | 27 |
+ R4462LU.CEL |
+ R4462LU |
+ BXD48 |
+ F |
+ 61 |
+ black |
+ 3 |
+ ORNL |
+
+
+ | 28 |
+ R4463LU.CEL |
+ R4463LU |
+ BXD60 |
+ M |
+ 93 |
+ brown |
+ 2 |
+ UTM RW |
+
+
+ | 29 |
+ R4464LU.CEL |
+ R4464LU |
+ BXD62 |
+ M |
+ 80 |
+ brown |
+ 2 |
+ UTM RW |
+
+
+ | 30 |
+ R4465LU.CEL |
+ R4465LU |
+ BXD69 |
+ M |
+ 63 |
+ dilute brown DBA |
+ 5 |
+ UTM RW |
+
+
+ | 31 |
+ R4466LU.CEL |
+ R4466LU |
+ BXD70 |
+ M |
+ 75 |
+ dilute brown DBA |
+ 3 |
+ UTM RW |
+
+
+ | 32 |
+ R4467LU.CEL |
+ R4467LU |
+ BXD71 |
+ M |
+ 64 |
+ dilute brown DBA |
+ 4 |
+ UTM RW |
+
+
+ | 33 |
+ R4468LU.CEL |
+ R4468LU |
+ BXD73 |
+ M |
+ 59 |
+ dilute brown DBA |
+ 3 |
+ UTM RW |
+
+
+ | 34 |
+ R4469L.CEL |
+ R4469LU |
+ BXD75 |
+ M |
+ 51 |
+ dilute brown DBA |
+ 4 |
+ UTM RW |
+
+
+ | 35 |
+ R4470L.CEL |
+ R4470LU |
+ BXD2 |
+ M |
+ 84 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 36 |
+ R4471H-re.CEL |
+ R4471LU |
+ BXD83 |
+ M |
+ 75 |
+ dilute brown DBA |
+ 2 |
+ UTM RW |
+
+
+ | 37 |
+ R4472L.CEL |
+ R4472LU |
+ BXD84 |
+ M |
+ 78 |
+ dilute brown DBA |
+ 2 |
+ UTM RW |
+
+
+ | 38 |
+ R4473LU.CEL |
+ R4473LU |
+ BXD86 |
+ M |
+ 77 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 39 |
+ R4474LU.CEL |
+ R4474LU |
+ BXD87 |
+ M |
+ 67 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 40 |
+ R4475LU.CEL |
+ R4475LU |
+ BXD9 |
+ M |
+ 78 |
+ dilute brown DBA |
+ 3 |
+ UTM RW |
+
+
+ | 41 |
+ R4476LU.CEL |
+ R4476LU |
+ BXD90 |
+ M |
+ 63 |
+ dilute brown DBA |
+ 3 |
+ UTM RW |
+
+
+ | 42 |
+ R4477LU.CEL |
+ R4477LU |
+ BXD65 |
+ M |
+ 59 |
+ brown |
+ 3 |
+ ORNL |
+
+
+ | 43 |
+ R4478LU.CEL |
+ R4478LU |
+ BXD6 |
+ M |
+ 92 |
+ gray |
+ 3 |
+ UTM RW |
+
+
+ | 44 |
+ R4479LU.CEL |
+ R4479LU |
+ BXD96 |
+ M |
+ 71 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 45 |
+ R4480LU.CEL |
+ R4480LU |
+ BXD97 |
+ M |
+ 80 |
+ brown |
+ 3 |
+ UTM RW |
+
+
+ | 46 |
+ R4481LU.CEL |
+ R4481LU |
+ BXD98 |
+ M |
+ 80 |
+ dilute brown DBA |
+ 2 |
+ UTM RW |
+
+
+ | 47 |
+ R4482LU.CEL |
+ R4482LU |
+ BXD99 |
+ M |
+ 72 |
+ dilute brown DBA |
+ 2 |
+ UTM RW |
+
+
+ | 48 |
+ R4483LU.CEL |
+ R4483LU |
+ BXD22 |
+ M |
+ 66 |
+ gray |
+ 2 |
+ UTM RW |
+
+
+ | 49 |
+ R4484LU.CEL |
+ R4484LU |
+ BXD25 |
+ M |
+ 54 |
+ brown |
+ 3 |
+ UTM RW |
+
+
+ | 50 |
+ R4485LU.CEL |
+ R4485LU |
+ B6D2F1 |
+ M |
+ 62 |
+ black |
+ 5 |
+ UTM RW |
+
+
+ | 51 |
+ R4486LU.CEL |
+ R4486LU |
+ B6D2F1 |
+ F |
+ 70 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 52 |
+ R4487LU.CEL |
+ R4487LU |
+ BALB/cByJ |
+ F |
+ 91 |
+ white |
+ 3 |
+ UTM RW |
+
+
+ | 53 |
+ R4488LU.CEL |
+ R4488LU |
+ BALB/cByJ |
+ M |
+ 91 |
+ white |
+ 2 |
+ UTM RW |
+
+
+ | 54 |
+ R4489LU.CEL |
+ R4489LU |
+ D2B6F1 |
+ F |
+ 61 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 55 |
+ R4490LU.CEL |
+ R4490LU |
+ D2B6F1 |
+ M |
+ 61 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 56 |
+ R4491LU.CEL |
+ R4491LU |
+ FVB/NJ |
+ F |
+ 62 |
+ white |
+ 5 |
+ UTM RW |
+
+
+ | 57 |
+ R4492LU.CEL |
+ R4492LU |
+ FVB/NJ |
+ M |
+ 73 |
+ white |
+ 3 |
+ UTM RW |
+
+
+ | 58 |
+ R4493LU.CEL |
+ R4493LU |
+ WSB/EiJ |
+ F |
+ 76 |
+ agouti |
+ 3 |
+ UTM RW |
+
+
+ | 59 |
+ R4494LU.CEL |
+ R4494LU |
+ WSB/EiJ |
+ M |
+ 76 |
+ agouti |
+ 3 |
+ UTM RW |
+
+
+ | 60 |
+ R4495LU.CEL |
+ R4495LU |
+ C57BL/6J |
+ F |
+ 65 |
+ black |
+ 3 |
+ UTM RW |
+
+
+ | 61 |
+ R4496LU.CEL |
+ R4496LU |
+ C57BL/6J |
+ M |
+ 65 |
+ black |
+ 2 |
+ UTM RW |
+
+
+ | 62 |
+ R4497LU.CEL |
+ R4497LU |
+ 129X1/SvJ |
+ F |
+ 65 |
+ white |
+ 4 |
+ JAX |
+
+
+ | 63 |
+ R4498LU.CEL |
+ R4498LU |
+ 129X1/SvJ |
+ M |
+ 66 |
+ white |
+ 4 |
+ JAX |
+
+
+ | 64 |
+ R4499LU.CEL |
+ R4499LU |
+ DBA/2J |
+ F |
+ 65 |
+ dilute brown DBA |
+ 3 |
+ ORNL |
+
+
+ | 65 |
+ R4500LU.CEL |
+ R4500LU |
+ DBA/2J |
+ M |
+ 59 |
+ dilute brown DBA |
+ 2 |
+ JAX |
+
+
+ | 66 |
+ R4501LU.CEL |
+ R4501LU |
+ LP/J |
+ F |
+ 65 |
+ agouti |
+ 4 |
+ JAX |
+
+
+ | 67 |
+ R4502LU.CEL |
+ R4502LU |
+ LP/J |
+ M |
+ 65 |
+ agouti |
+ 4 |
+ JAX |
+
+
+ | 68 |
+ R4503LU.CEL |
+ R4503LU |
+ SJL/J |
+ F |
+ 63 |
+ white |
+ 4 |
+ JAX |
+
+
+ | 69 |
+ R4504LU.CEL |
+ R4504LU |
+ SJL/J |
+ M |
+ 65 |
+ white |
+ 4 |
+ JAX |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Hzi_0408_r/summary.rtf b/general/datasets/Hzi_0408_r/summary.rtf
new file mode 100644
index 0000000..5d3c1a7
--- /dev/null
+++ b/general/datasets/Hzi_0408_r/summary.rtf
@@ -0,0 +1,37 @@
+Phase I of BXD lung transcriptome mapping project. Project organized by Drs. Robert Williams, Klaus Schughart, Lu Lu. Started November 29, 2008. There are total 70 samples in phase I including 50 BXD strains and 10 paired inbred strains.
+
+Respir Res. 2011 May 2;12:61. doi: 10.1186/1465-9921-12-61.
+
+Genome-wide analysis of the mouse lung transcriptome reveals novel molecular gene interaction networks and cell-specific expression signatures.
+
+Alberts R1, Lu L, Williams RW, Schughart K.
+
+
+
+Erratum in
+
+
+ - Respir Res. 2012;13(1):5.
+
+
+Abstract
+
+BACKGROUND:
+
+The lung is critical in surveillance and initial defense against pathogens. In humans, as in mice, individual genetic differences strongly modulate pulmonary responses to infectious agents, severity of lung disease, and potential allergic reactions. In a first step towards understanding genetic predisposition and pulmonary molecular networks that underlie individual differences in disease vulnerability, we performed a global analysis of normative lung gene expression levels in inbred mouse strains and a large family of BXD strains that are widely used for systems genetics. Our goal is to provide a key community resource on the genetics of the normative lungtranscriptome that can serve as a foundation for experimental analysis and allow predicting genetic predisposition and response to pathogens, allergens, and xenobiotics.
+
+METHODS:
+
+Steady-state polyA+ mRNA levels were assayed across a diverse and fully genotyped panel of 57 isogenic strains using the Affymetrix M430 2.0 array. Correlations of expression levels between genes were determined. Global expression QTL (eQTL) analysis and network covariance analysis was performed using tools and resources in GeneNetwork http://www.genenetwork.org.
+
+RESULTS:
+
+Expression values were highly variable across strains and in many cases exhibited a high heritability factor. Several genes which showed a restricted expression to lung tissue were identified. Using correlations between gene expression values across all strains, we defined and extended memberships of several important molecular networks in the lung. Furthermore, we were able to extract signatures of immune cell subpopulations and characterize co-variation and shared genetic modulation. Known QTL regions for respiratory infection susceptibility were investigated and several cis-eQTL genes were identified. Numerous cis- and trans-regulated transcripts and chromosomal intervals with strong regulatory activity were mapped. The Cyp1a1 P450 transcript had a strong trans-acting eQTL (LOD 11.8) on Chr 12 at 36 ± 1 Mb. This interval contains the transcription factor Ahr that has a critical mis-sense allele in the DBA/2J haplotype and evidently modulates transcriptional activation by AhR.
+
+CONCLUSIONS:
+
+Large-scale gene expression analyses in genetic reference populations revealed lung-specific and immune-cell gene expression profiles and suggested specific gene regulatory interactions.
+
+
+ - PMID:21535883 PMCID:PMC3105947 DOI:10.1186/1465-9921-12-61
+
diff --git a/general/datasets/Hzi_ltcf_0313/acknowledgment.rtf b/general/datasets/Hzi_ltcf_0313/acknowledgment.rtf
new file mode 100644
index 0000000..5350054
--- /dev/null
+++ b/general/datasets/Hzi_ltcf_0313/acknowledgment.rtf
@@ -0,0 +1 @@
+Primary human bronchial epithelial cells were provided by Scott H. Randell (Marsico Lung Institute, Tissue Procurement and Cell Culture Core, The University of North Carolina at Chapel Hill, USA). The cells were obtained under protocol 03-1396 approved by the University of North Carolina at Chapel Hill Biomedical Institutional Review Board. The RNA-seq was carried out by the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/Hzi_ltcf_0313/cases.rtf b/general/datasets/Hzi_ltcf_0313/cases.rtf
new file mode 100644
index 0000000..50868a3
--- /dev/null
+++ b/general/datasets/Hzi_ltcf_0313/cases.rtf
@@ -0,0 +1 @@
+Mice We used females from 41 BXD RI strains and both parental strains—B6 and D2. Mice were between 8 and 12 weeks of age when infected. They were housed and maintained on a 12:12 light/dark cycle, with ad libitum access to food and water. Virus Original stocks of mouse-adapted A/Puerto Rico/8/34 (H1N1, PR8M) virus were obtained from Stefan Ludwig, University of Münster (28). Virus stocks were propagated in the chorioallantoic cavity of 10-day-old pathogen-free embryonated chicken eggs for 48 h at 37°C as described previously (29). Viral titer was determined using a focus-forming unit (FFU) assay as described previously (29). Infection of Mice Animals were anesthetized by intraperitoneal injection of ketamine/xylazine (10 % (v/v) of 100 mg/ml ketamine and 5 % (v/v) of 20 mg/ml xylazine in 0.9 % (w/v) NaCl with a dose adjusted to body weight (200 μl/20 g body weight). Infection was performed by intranasal application of virus solution in 20 μl sterile phosphate-buffered saline (PBS), with a PR8M dosage of 2×103 FFU. Mice were bred and infected at the animal facilities at UTHSC
diff --git a/general/datasets/Hzi_ltcf_0313/citation.rtf b/general/datasets/Hzi_ltcf_0313/citation.rtf
new file mode 100644
index 0000000..bad40b4
--- /dev/null
+++ b/general/datasets/Hzi_ltcf_0313/citation.rtf
@@ -0,0 +1 @@
+Xu F, Gao J, Bergmann S, Sims AC, Ashbrook DG, Baric RS, Cui Y, Jonsson CB, Li K, Williams RW, Schughart K and Lu L (2021) Genetic Dissection of the Regulatory Mechanisms of Ace2 in the Infected Mouse Lung. Front. Immunol. 11:607314. doi: 10.3389/fimmu.2020.607314
diff --git a/general/datasets/Hzi_ltcf_0313/contributors.rtf b/general/datasets/Hzi_ltcf_0313/contributors.rtf
new file mode 100644
index 0000000..0b5cb98
--- /dev/null
+++ b/general/datasets/Hzi_ltcf_0313/contributors.rtf
@@ -0,0 +1 @@
+LL, KS, RW, and RB conceived the study. SB and AS conducted the experiments. FX, KS, YC, and RW performed data analysis. LL, FX, KS, RW, and JG wrote the manuscript. FX, KS, and JG prepared the figures and tables. RW, KL, DA, and CJ edited the manuscript. All authors contributed to the article and approved the submitted version.
diff --git a/general/datasets/Hzi_ltcf_0313/notes.rtf b/general/datasets/Hzi_ltcf_0313/notes.rtf
new file mode 100644
index 0000000..e6040a2
--- /dev/null
+++ b/general/datasets/Hzi_ltcf_0313/notes.rtf
@@ -0,0 +1 @@
+The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2020.07314/full#supplementary-material
diff --git a/general/datasets/Hzi_ltcf_0313/processing.rtf b/general/datasets/Hzi_ltcf_0313/processing.rtf
new file mode 100644
index 0000000..5502082
--- /dev/null
+++ b/general/datasets/Hzi_ltcf_0313/processing.rtf
@@ -0,0 +1 @@
+Read Mapping and Gene Expression Quantification RNA-seq reads were quality-trimmed using Trim Galore (31) and mapped to the mm10 reference genome or to the IAV PR8M genome using STAR (32). Counts were summarized at the gene level using the R-package Rsubread (33), normalized and log transformed using the R-package DESeq2 (34), and batchcorrected using the ComBat function of the R-package sva (35, 36). For annotations of genes, ENTREZID from Rsubread were matched to RefSeq annotations using R-package biomart (37).
diff --git a/general/datasets/Hzi_ltcf_0313/summary.rtf b/general/datasets/Hzi_ltcf_0313/summary.rtf
new file mode 100644
index 0000000..1ad3d9f
--- /dev/null
+++ b/general/datasets/Hzi_ltcf_0313/summary.rtf
@@ -0,0 +1,3 @@
+Full article available at https://www.frontiersin.org/articles/10.3389/fimmu.2020.607314/full
+
+Acute lung injury (ALI) is an important cause of morbidity and mortality after viral infections, including influenza A virus H1N1, SARS-CoV,MERS-CoV, and SARS-CoV-2. The angiotensin I converting enzyme 2 (ACE2) is a key host membrane-bound protein that modulates ALI induced by viral infection, pulmonary acid aspiration, and sepsis. However, the contributions of ACE2 sequence variants to individual differences in disease risk and severity after viral infection are not understood. In this study, we quantified H1N1 influenza-infected lung transcriptomes across a family of 41 BXD recombinant inbred strains of mice and both parents—C57BL/6J and DBA/2J. In response to infection Ace2 mRNA levels decreased significantly for both parental strains and the expression levels was associated with disease severity (body weight loss) and viral load (expression levels of viral NA segment) across the BXD family members. Pulmonary RNA-seq for 43 lines was analyzed using weighted gene co-expression network analysis (WGCNA) and Bayesian network approaches. Ace2 not only participated in virusinduced ALI by interacting with TNF, MAPK, and NOTCH signaling pathways, but was also linked with high confidence to gene products that have important functions in the pulmonary epithelium, including Rnf128, Muc5b, and Tmprss2. Comparable sets of transcripts were also highlighted in parallel studies of human SARS-CoV-infected primary human airway epithelial cells. Using conventional mapping methods, we determined that weight loss at two and three days after viral infection maps to chromosome X—the location of Ace2. This finding motivated the hierarchical Bayesian network analysis, which defined molecular endophenotypes of lung infection linked to Ace2 expression and to a key disease outcome. Core members of this Bayesian network include Ace2, Atf4, Csf2, Cxcl2, Lif, Maml3, Muc5b, Reg3g, Ripk3, and Traf3. Collectively, these findings define a causally-rooted Ace2 modulatory network relevant to host response to viral infection and identify potential therapeutic targets for virus-induced respiratory diseases, including those caused by influenza and coronaviruses.
diff --git a/general/datasets/Hzi_ltcf_0313/tissue.rtf b/general/datasets/Hzi_ltcf_0313/tissue.rtf
new file mode 100644
index 0000000..2258f28
--- /dev/null
+++ b/general/datasets/Hzi_ltcf_0313/tissue.rtf
@@ -0,0 +1 @@
+RNA Isolation and Sequencing Mice were sacrificed 3 days post-infection (dpi) and both lungs were extracted and transferred immediately to RNAlater (Qiagen), stored at 4°C for one day, and then stored at −20°C. RNA was isolated using Qiagen Midi kit (30). RNA quality was evaluated on a 2100 Bioanalyzer (Agilent). Five-hundred nanograms of total RNA was used to prepare libraries for sequencing using the Lexogen SENSE RNA-seq library kit for Ion Torrent. Libraries were amplified for 11 cycles as the final step of library preparation. Before sequencing, 1-μl aliquots were pooled and sequenced on an Ion Torrent PGM 314 chip. Barcoded data from the PGM was used to balance the final pool before sequencing. Library pools were sized to ~260 bp on a Pippin Prep instrument using 2% Pippin agarose gel. The sized libraries were evaluated on an Agilent High Sensitivity chip, quantified using real-time PCR, and used to prepare beads using a One-Touch 2 device. Beads were sequenced on an Ion Torrent Proton P1 chip. On average, 67 million reads were obtained per strain.
diff --git a/general/datasets/Hzi_lungbxd_rna_seq_1116/acknowledgment.rtf b/general/datasets/Hzi_lungbxd_rna_seq_1116/acknowledgment.rtf
new file mode 100644
index 0000000..5350054
--- /dev/null
+++ b/general/datasets/Hzi_lungbxd_rna_seq_1116/acknowledgment.rtf
@@ -0,0 +1 @@
+Primary human bronchial epithelial cells were provided by Scott H. Randell (Marsico Lung Institute, Tissue Procurement and Cell Culture Core, The University of North Carolina at Chapel Hill, USA). The cells were obtained under protocol 03-1396 approved by the University of North Carolina at Chapel Hill Biomedical Institutional Review Board. The RNA-seq was carried out by the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/Hzi_lungbxd_rna_seq_1116/cases.rtf b/general/datasets/Hzi_lungbxd_rna_seq_1116/cases.rtf
new file mode 100644
index 0000000..50868a3
--- /dev/null
+++ b/general/datasets/Hzi_lungbxd_rna_seq_1116/cases.rtf
@@ -0,0 +1 @@
+Mice We used females from 41 BXD RI strains and both parental strains—B6 and D2. Mice were between 8 and 12 weeks of age when infected. They were housed and maintained on a 12:12 light/dark cycle, with ad libitum access to food and water. Virus Original stocks of mouse-adapted A/Puerto Rico/8/34 (H1N1, PR8M) virus were obtained from Stefan Ludwig, University of Münster (28). Virus stocks were propagated in the chorioallantoic cavity of 10-day-old pathogen-free embryonated chicken eggs for 48 h at 37°C as described previously (29). Viral titer was determined using a focus-forming unit (FFU) assay as described previously (29). Infection of Mice Animals were anesthetized by intraperitoneal injection of ketamine/xylazine (10 % (v/v) of 100 mg/ml ketamine and 5 % (v/v) of 20 mg/ml xylazine in 0.9 % (w/v) NaCl with a dose adjusted to body weight (200 μl/20 g body weight). Infection was performed by intranasal application of virus solution in 20 μl sterile phosphate-buffered saline (PBS), with a PR8M dosage of 2×103 FFU. Mice were bred and infected at the animal facilities at UTHSC
diff --git a/general/datasets/Hzi_lungbxd_rna_seq_1116/citation.rtf b/general/datasets/Hzi_lungbxd_rna_seq_1116/citation.rtf
new file mode 100644
index 0000000..3bd25af
--- /dev/null
+++ b/general/datasets/Hzi_lungbxd_rna_seq_1116/citation.rtf
@@ -0,0 +1,3 @@
+1. Xu F, Gao J, Bergman S, Sims AC, Baric RS, Cui Y, Jonsson C, Kui L, Williams RW, Schughart K, Lu L (2020) Genetic dissection of the modulatory mechanisms of Ace2 in the infected mouse lung. In submission.
+
+2. Nedelko T, Kollmus H, Klawonn F, Spijker S, Lu L, Heßman M, Alberts R, Williams RW, Schughart K (2012) Distinct gene loci control the host response to influenza H1N1 virus infection in a time-dependent manner. BMC Genomics. 2012 Aug 20;13:411. doi: 10.1186/1471-2164-13-411.
diff --git a/general/datasets/Hzi_lungbxd_rna_seq_1116/contributors.rtf b/general/datasets/Hzi_lungbxd_rna_seq_1116/contributors.rtf
new file mode 100644
index 0000000..0b5cb98
--- /dev/null
+++ b/general/datasets/Hzi_lungbxd_rna_seq_1116/contributors.rtf
@@ -0,0 +1 @@
+LL, KS, RW, and RB conceived the study. SB and AS conducted the experiments. FX, KS, YC, and RW performed data analysis. LL, FX, KS, RW, and JG wrote the manuscript. FX, KS, and JG prepared the figures and tables. RW, KL, DA, and CJ edited the manuscript. All authors contributed to the article and approved the submitted version.
diff --git a/general/datasets/Hzi_lungbxd_rna_seq_1116/notes.rtf b/general/datasets/Hzi_lungbxd_rna_seq_1116/notes.rtf
new file mode 100644
index 0000000..e6040a2
--- /dev/null
+++ b/general/datasets/Hzi_lungbxd_rna_seq_1116/notes.rtf
@@ -0,0 +1 @@
+The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2020.07314/full#supplementary-material
diff --git a/general/datasets/Hzi_lungbxd_rna_seq_1116/platform.rtf b/general/datasets/Hzi_lungbxd_rna_seq_1116/platform.rtf
new file mode 100644
index 0000000..f9bc2e3
--- /dev/null
+++ b/general/datasets/Hzi_lungbxd_rna_seq_1116/platform.rtf
@@ -0,0 +1 @@
+IonTorrent (see above)
diff --git a/general/datasets/Hzi_lungbxd_rna_seq_1116/processing.rtf b/general/datasets/Hzi_lungbxd_rna_seq_1116/processing.rtf
new file mode 100644
index 0000000..5502082
--- /dev/null
+++ b/general/datasets/Hzi_lungbxd_rna_seq_1116/processing.rtf
@@ -0,0 +1 @@
+Read Mapping and Gene Expression Quantification RNA-seq reads were quality-trimmed using Trim Galore (31) and mapped to the mm10 reference genome or to the IAV PR8M genome using STAR (32). Counts were summarized at the gene level using the R-package Rsubread (33), normalized and log transformed using the R-package DESeq2 (34), and batchcorrected using the ComBat function of the R-package sva (35, 36). For annotations of genes, ENTREZID from Rsubread were matched to RefSeq annotations using R-package biomart (37).
diff --git a/general/datasets/Hzi_lungbxd_rna_seq_1116/specifics.rtf b/general/datasets/Hzi_lungbxd_rna_seq_1116/specifics.rtf
new file mode 100644
index 0000000..d75a4b7
--- /dev/null
+++ b/general/datasets/Hzi_lungbxd_rna_seq_1116/specifics.rtf
@@ -0,0 +1 @@
+HZI Lung Flu Infected BXD (Nov16) RNA-Seq
diff --git a/general/datasets/Hzi_lungbxd_rna_seq_1116/summary.rtf b/general/datasets/Hzi_lungbxd_rna_seq_1116/summary.rtf
new file mode 100644
index 0000000..1ad3d9f
--- /dev/null
+++ b/general/datasets/Hzi_lungbxd_rna_seq_1116/summary.rtf
@@ -0,0 +1,3 @@
+Full article available at https://www.frontiersin.org/articles/10.3389/fimmu.2020.607314/full
+
+Acute lung injury (ALI) is an important cause of morbidity and mortality after viral infections, including influenza A virus H1N1, SARS-CoV,MERS-CoV, and SARS-CoV-2. The angiotensin I converting enzyme 2 (ACE2) is a key host membrane-bound protein that modulates ALI induced by viral infection, pulmonary acid aspiration, and sepsis. However, the contributions of ACE2 sequence variants to individual differences in disease risk and severity after viral infection are not understood. In this study, we quantified H1N1 influenza-infected lung transcriptomes across a family of 41 BXD recombinant inbred strains of mice and both parents—C57BL/6J and DBA/2J. In response to infection Ace2 mRNA levels decreased significantly for both parental strains and the expression levels was associated with disease severity (body weight loss) and viral load (expression levels of viral NA segment) across the BXD family members. Pulmonary RNA-seq for 43 lines was analyzed using weighted gene co-expression network analysis (WGCNA) and Bayesian network approaches. Ace2 not only participated in virusinduced ALI by interacting with TNF, MAPK, and NOTCH signaling pathways, but was also linked with high confidence to gene products that have important functions in the pulmonary epithelium, including Rnf128, Muc5b, and Tmprss2. Comparable sets of transcripts were also highlighted in parallel studies of human SARS-CoV-infected primary human airway epithelial cells. Using conventional mapping methods, we determined that weight loss at two and three days after viral infection maps to chromosome X—the location of Ace2. This finding motivated the hierarchical Bayesian network analysis, which defined molecular endophenotypes of lung infection linked to Ace2 expression and to a key disease outcome. Core members of this Bayesian network include Ace2, Atf4, Csf2, Cxcl2, Lif, Maml3, Muc5b, Reg3g, Ripk3, and Traf3. Collectively, these findings define a causally-rooted Ace2 modulatory network relevant to host response to viral infection and identify potential therapeutic targets for virus-induced respiratory diseases, including those caused by influenza and coronaviruses.
diff --git a/general/datasets/Hzi_lungbxd_rna_seq_1116/tissue.rtf b/general/datasets/Hzi_lungbxd_rna_seq_1116/tissue.rtf
new file mode 100644
index 0000000..2258f28
--- /dev/null
+++ b/general/datasets/Hzi_lungbxd_rna_seq_1116/tissue.rtf
@@ -0,0 +1 @@
+RNA Isolation and Sequencing Mice were sacrificed 3 days post-infection (dpi) and both lungs were extracted and transferred immediately to RNAlater (Qiagen), stored at 4°C for one day, and then stored at −20°C. RNA was isolated using Qiagen Midi kit (30). RNA quality was evaluated on a 2100 Bioanalyzer (Agilent). Five-hundred nanograms of total RNA was used to prepare libraries for sequencing using the Lexogen SENSE RNA-seq library kit for Ion Torrent. Libraries were amplified for 11 cycles as the final step of library preparation. Before sequencing, 1-μl aliquots were pooled and sequenced on an Ion Torrent PGM 314 chip. Barcoded data from the PGM was used to balance the final pool before sequencing. Library pools were sized to ~260 bp on a Pippin Prep instrument using 2% Pippin agarose gel. The sized libraries were evaluated on an Agilent High Sensitivity chip, quantified using real-time PCR, and used to prepare beads using a One-Touch 2 device. Beads were sequenced on an Ion Torrent Proton P1 chip. On average, 67 million reads were obtained per strain.
diff --git a/general/datasets/Hzi_pr8m_f_1014/processing.rtf b/general/datasets/Hzi_pr8m_f_1014/processing.rtf
new file mode 100644
index 0000000..3aca25d
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_f_1014/processing.rtf
@@ -0,0 +1,3 @@
+For dataset HZI PR8M-Infected Lungs Females RNAseq (Oct14) RPKM Log2 we took the RPKM values, added 1 and then log2.
+
+For dataset HZI PR8M-Infected Lungs Females RNAseq (Oct14) RPKM Log2 Treatment we took the RPKM values, added 1 and then log2 and threshold values at average of less than 1 = 0
diff --git a/general/datasets/Hzi_pr8m_f_1014/summary.rtf b/general/datasets/Hzi_pr8m_f_1014/summary.rtf
new file mode 100644
index 0000000..07a4fb8
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_f_1014/summary.rtf
@@ -0,0 +1 @@
+This group of datasets is currently confidential.
diff --git a/general/datasets/Hzi_pr8m_f_1113/processing.rtf b/general/datasets/Hzi_pr8m_f_1113/processing.rtf
new file mode 100644
index 0000000..3aca25d
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_f_1113/processing.rtf
@@ -0,0 +1,3 @@
+For dataset HZI PR8M-Infected Lungs Females RNAseq (Oct14) RPKM Log2 we took the RPKM values, added 1 and then log2.
+
+For dataset HZI PR8M-Infected Lungs Females RNAseq (Oct14) RPKM Log2 Treatment we took the RPKM values, added 1 and then log2 and threshold values at average of less than 1 = 0
diff --git a/general/datasets/Hzi_pr8m_f_1113/summary.rtf b/general/datasets/Hzi_pr8m_f_1113/summary.rtf
new file mode 100644
index 0000000..07a4fb8
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_f_1113/summary.rtf
@@ -0,0 +1 @@
+This group of datasets is currently confidential.
diff --git a/general/datasets/Hzi_pr8m_f_freq1_1014/processing.rtf b/general/datasets/Hzi_pr8m_f_freq1_1014/processing.rtf
new file mode 100644
index 0000000..3aca25d
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_f_freq1_1014/processing.rtf
@@ -0,0 +1,3 @@
+For dataset HZI PR8M-Infected Lungs Females RNAseq (Oct14) RPKM Log2 we took the RPKM values, added 1 and then log2.
+
+For dataset HZI PR8M-Infected Lungs Females RNAseq (Oct14) RPKM Log2 Treatment we took the RPKM values, added 1 and then log2 and threshold values at average of less than 1 = 0
diff --git a/general/datasets/Hzi_pr8m_f_freq1_1014/summary.rtf b/general/datasets/Hzi_pr8m_f_freq1_1014/summary.rtf
new file mode 100644
index 0000000..07a4fb8
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_f_freq1_1014/summary.rtf
@@ -0,0 +1 @@
+This group of datasets is currently confidential.
diff --git a/general/datasets/Hzi_pr8m_q_0612/acknowledgment.rtf b/general/datasets/Hzi_pr8m_q_0612/acknowledgment.rtf
new file mode 100644
index 0000000..5350054
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_q_0612/acknowledgment.rtf
@@ -0,0 +1 @@
+Primary human bronchial epithelial cells were provided by Scott H. Randell (Marsico Lung Institute, Tissue Procurement and Cell Culture Core, The University of North Carolina at Chapel Hill, USA). The cells were obtained under protocol 03-1396 approved by the University of North Carolina at Chapel Hill Biomedical Institutional Review Board. The RNA-seq was carried out by the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/Hzi_pr8m_q_0612/cases.rtf b/general/datasets/Hzi_pr8m_q_0612/cases.rtf
new file mode 100644
index 0000000..50868a3
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_q_0612/cases.rtf
@@ -0,0 +1 @@
+Mice We used females from 41 BXD RI strains and both parental strains—B6 and D2. Mice were between 8 and 12 weeks of age when infected. They were housed and maintained on a 12:12 light/dark cycle, with ad libitum access to food and water. Virus Original stocks of mouse-adapted A/Puerto Rico/8/34 (H1N1, PR8M) virus were obtained from Stefan Ludwig, University of Münster (28). Virus stocks were propagated in the chorioallantoic cavity of 10-day-old pathogen-free embryonated chicken eggs for 48 h at 37°C as described previously (29). Viral titer was determined using a focus-forming unit (FFU) assay as described previously (29). Infection of Mice Animals were anesthetized by intraperitoneal injection of ketamine/xylazine (10 % (v/v) of 100 mg/ml ketamine and 5 % (v/v) of 20 mg/ml xylazine in 0.9 % (w/v) NaCl with a dose adjusted to body weight (200 μl/20 g body weight). Infection was performed by intranasal application of virus solution in 20 μl sterile phosphate-buffered saline (PBS), with a PR8M dosage of 2×103 FFU. Mice were bred and infected at the animal facilities at UTHSC
diff --git a/general/datasets/Hzi_pr8m_q_0612/citation.rtf b/general/datasets/Hzi_pr8m_q_0612/citation.rtf
new file mode 100644
index 0000000..bad40b4
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_q_0612/citation.rtf
@@ -0,0 +1 @@
+Xu F, Gao J, Bergmann S, Sims AC, Ashbrook DG, Baric RS, Cui Y, Jonsson CB, Li K, Williams RW, Schughart K and Lu L (2021) Genetic Dissection of the Regulatory Mechanisms of Ace2 in the Infected Mouse Lung. Front. Immunol. 11:607314. doi: 10.3389/fimmu.2020.607314
diff --git a/general/datasets/Hzi_pr8m_q_0612/contributors.rtf b/general/datasets/Hzi_pr8m_q_0612/contributors.rtf
new file mode 100644
index 0000000..0b5cb98
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_q_0612/contributors.rtf
@@ -0,0 +1 @@
+LL, KS, RW, and RB conceived the study. SB and AS conducted the experiments. FX, KS, YC, and RW performed data analysis. LL, FX, KS, RW, and JG wrote the manuscript. FX, KS, and JG prepared the figures and tables. RW, KL, DA, and CJ edited the manuscript. All authors contributed to the article and approved the submitted version.
diff --git a/general/datasets/Hzi_pr8m_q_0612/experiment-type.rtf b/general/datasets/Hzi_pr8m_q_0612/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_q_0612/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Hzi_pr8m_q_0612/notes.rtf b/general/datasets/Hzi_pr8m_q_0612/notes.rtf
new file mode 100644
index 0000000..e6040a2
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_q_0612/notes.rtf
@@ -0,0 +1 @@
+The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2020.07314/full#supplementary-material
diff --git a/general/datasets/Hzi_pr8m_q_0612/processing.rtf b/general/datasets/Hzi_pr8m_q_0612/processing.rtf
new file mode 100644
index 0000000..5502082
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_q_0612/processing.rtf
@@ -0,0 +1 @@
+Read Mapping and Gene Expression Quantification RNA-seq reads were quality-trimmed using Trim Galore (31) and mapped to the mm10 reference genome or to the IAV PR8M genome using STAR (32). Counts were summarized at the gene level using the R-package Rsubread (33), normalized and log transformed using the R-package DESeq2 (34), and batchcorrected using the ComBat function of the R-package sva (35, 36). For annotations of genes, ENTREZID from Rsubread were matched to RefSeq annotations using R-package biomart (37).
diff --git a/general/datasets/Hzi_pr8m_q_0612/summary.rtf b/general/datasets/Hzi_pr8m_q_0612/summary.rtf
new file mode 100644
index 0000000..1ad3d9f
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_q_0612/summary.rtf
@@ -0,0 +1,3 @@
+Full article available at https://www.frontiersin.org/articles/10.3389/fimmu.2020.607314/full
+
+Acute lung injury (ALI) is an important cause of morbidity and mortality after viral infections, including influenza A virus H1N1, SARS-CoV,MERS-CoV, and SARS-CoV-2. The angiotensin I converting enzyme 2 (ACE2) is a key host membrane-bound protein that modulates ALI induced by viral infection, pulmonary acid aspiration, and sepsis. However, the contributions of ACE2 sequence variants to individual differences in disease risk and severity after viral infection are not understood. In this study, we quantified H1N1 influenza-infected lung transcriptomes across a family of 41 BXD recombinant inbred strains of mice and both parents—C57BL/6J and DBA/2J. In response to infection Ace2 mRNA levels decreased significantly for both parental strains and the expression levels was associated with disease severity (body weight loss) and viral load (expression levels of viral NA segment) across the BXD family members. Pulmonary RNA-seq for 43 lines was analyzed using weighted gene co-expression network analysis (WGCNA) and Bayesian network approaches. Ace2 not only participated in virusinduced ALI by interacting with TNF, MAPK, and NOTCH signaling pathways, but was also linked with high confidence to gene products that have important functions in the pulmonary epithelium, including Rnf128, Muc5b, and Tmprss2. Comparable sets of transcripts were also highlighted in parallel studies of human SARS-CoV-infected primary human airway epithelial cells. Using conventional mapping methods, we determined that weight loss at two and three days after viral infection maps to chromosome X—the location of Ace2. This finding motivated the hierarchical Bayesian network analysis, which defined molecular endophenotypes of lung infection linked to Ace2 expression and to a key disease outcome. Core members of this Bayesian network include Ace2, Atf4, Csf2, Cxcl2, Lif, Maml3, Muc5b, Reg3g, Ripk3, and Traf3. Collectively, these findings define a causally-rooted Ace2 modulatory network relevant to host response to viral infection and identify potential therapeutic targets for virus-induced respiratory diseases, including those caused by influenza and coronaviruses.
diff --git a/general/datasets/Hzi_pr8m_q_0612/tissue.rtf b/general/datasets/Hzi_pr8m_q_0612/tissue.rtf
new file mode 100644
index 0000000..2258f28
--- /dev/null
+++ b/general/datasets/Hzi_pr8m_q_0612/tissue.rtf
@@ -0,0 +1 @@
+RNA Isolation and Sequencing Mice were sacrificed 3 days post-infection (dpi) and both lungs were extracted and transferred immediately to RNAlater (Qiagen), stored at 4°C for one day, and then stored at −20°C. RNA was isolated using Qiagen Midi kit (30). RNA quality was evaluated on a 2100 Bioanalyzer (Agilent). Five-hundred nanograms of total RNA was used to prepare libraries for sequencing using the Lexogen SENSE RNA-seq library kit for Ion Torrent. Libraries were amplified for 11 cycles as the final step of library preparation. Before sequencing, 1-μl aliquots were pooled and sequenced on an Ion Torrent PGM 314 chip. Barcoded data from the PGM was used to balance the final pool before sequencing. Library pools were sized to ~260 bp on a Pippin Prep instrument using 2% Pippin agarose gel. The sized libraries were evaluated on an Agilent High Sensitivity chip, quantified using real-time PCR, and used to prepare beads using a One-Touch 2 device. Beads were sequenced on an Ion Torrent Proton P1 chip. On average, 67 million reads were obtained per strain.
diff --git a/general/datasets/INIA_Adrenal_RMA_0612/cases.rtf b/general/datasets/INIA_Adrenal_RMA_0612/cases.rtf
deleted file mode 100644
index f0b204b..0000000
--- a/general/datasets/INIA_Adrenal_RMA_0612/cases.rtf
+++ /dev/null
@@ -1,771 +0,0 @@
-Young adult mice raised in specific pathogen-free vivarium at UTHSC.
-Table 1. Final strain correction by Khyobeni Mozhui on Mar 28, 2013.
-
-
-
-
-
-
-
-
- | Index |
- Sample ID |
- Strain |
- Tissue |
- Sex |
-
-
- | 1 |
- R6947A |
- BXD48 |
- Adrenal |
- M |
-
-
- | 2 |
- R6948A |
- BXD90 |
- Adrenal |
- M |
-
-
- | 3 |
- R6949A |
- BXD97 |
- Adrenal |
- M |
-
-
- | 4 |
- R6950A |
- BXD87 |
- Adrenal |
- M |
-
-
- | 5 |
- R6952A |
- BXD83 |
- Adrenal |
- F |
-
-
- | 6 |
- R6953A |
- BXD67 |
- Adrenal |
- M |
-
-
- | 7 |
- R6954A |
- BXD56 |
- Adrenal |
- M |
-
-
- | 8 |
- R6955A |
- BXD48 |
- Adrenal |
- F |
-
-
- | 9 |
- R6956A |
- BXD90 |
- Adrenal |
- F |
-
-
- | 10 |
- R6957A |
- BXD89 |
- Adrenal |
- M |
-
-
- | 11 |
- R6958A |
- BXD65 |
- Adrenal |
- M |
-
-
- | 12 |
- R6959A |
- BXD65 |
- Adrenal |
- F |
-
-
- | 13 |
- R6960A |
- BXD63 |
- Adrenal |
- F |
-
-
- | 14 |
- R6961A |
- BXD63 |
- Adrenal |
- M |
-
-
- | 15 |
- R6963A |
- BXD31 |
- Adrenal |
- M |
-
-
- | 16 |
- R6964A |
- BXD31 |
- Adrenal |
- F |
-
-
- | 17 |
- R6965A |
- BXD1 |
- Adrenal |
- F |
-
-
- | 18 |
- R6966A |
- BXD1 |
- Adrenal |
- F |
-
-
- | 19 |
- R6967A |
- BXD24 |
- Adrenal |
- F |
-
-
- | 20 |
- R6968A |
- BXD34 |
- Adrenal |
- M |
-
-
- | 21 |
- R6969A |
- BXD1 |
- Adrenal |
- M |
-
-
- | 22 |
- R6971A |
- BXD27 |
- Adrenal |
- F |
-
-
- | 23 |
- R6972A |
- BXD29 |
- Adrenal |
- M |
-
-
- | 24 |
- R6973A |
- BXD12 |
- Adrenal |
- F |
-
-
- | 25 |
- R6974A |
- BXD14 |
- Adrenal |
- F |
-
-
- | 26 |
- R6975A |
- BXD99 |
- Adrenal |
- F |
-
-
- | 27 |
- R6976A |
- BXD32 |
- Adrenal |
- F |
-
-
- | 28 |
- R6977A |
- BXD97 |
- Adrenal |
- F |
-
-
- | 29 |
- R6978A |
- BXD84 |
- Adrenal |
- M |
-
-
- | 30 |
- R6979A |
- BXD39 |
- Adrenal |
- M |
-
-
- | 31 |
- R6980A |
- BXD24 |
- Adrenal |
- M |
-
-
- | 32 |
- R6981A |
- BXD50 |
- Adrenal |
- F |
-
-
- | 33 |
- R6982A |
- BXD75 |
- Adrenal |
- M |
-
-
- | 34 |
- R6983A |
- BXD42 |
- Adrenal |
- M |
-
-
- | 35 |
- R6984A |
- BXD39 |
- Adrenal |
- F |
-
-
- | 36 |
- R6985A |
- BXD34 |
- Adrenal |
- F |
-
-
- | 37 |
- R6986A |
- BXD87 |
- Adrenal |
- F |
-
-
- | 38 |
- R6987A |
- BXD50 |
- Adrenal |
- M |
-
-
- | 39 |
- R6989A |
- BXD62 |
- Adrenal |
- M |
-
-
- | 40 |
- R6990A |
- BXD70 |
- Adrenal |
- M |
-
-
- | 41 |
- R6991A |
- BXD64 |
- Adrenal |
- F |
-
-
- | 42 |
- R6992A |
- BXD84 |
- Adrenal |
- F |
-
-
- | 43 |
- R6993A |
- BXD100 |
- Adrenal |
- F |
-
-
- | 44 |
- R6994A |
- BXD62 |
- Adrenal |
- F |
-
-
- | 45 |
- R6996A |
- BXD95 |
- Adrenal |
- M |
-
-
- | 46 |
- R6998A |
- BXD32 |
- Adrenal |
- M |
-
-
- | 47 |
- R6999A |
- BXD101 |
- Adrenal |
- F |
-
-
- | 48 |
- R7000A |
- BXD49 |
- Adrenal |
- M |
-
-
- | 49 |
- R7002A |
- BXD11 |
- Adrenal |
- M |
-
-
- | 50 |
- R7003A |
- BXD100 |
- Adrenal |
- M |
-
-
- | 51 |
- R7004A |
- BXD43 |
- Adrenal |
- F |
-
-
- | 52 |
- R7005A |
- BXD103 |
- Adrenal |
- M |
-
-
- | 53 |
- R7006A |
- BXD73 |
- Adrenal |
- F |
-
-
- | 54 |
- R7008A |
- BXD43 |
- Adrenal |
- M |
-
-
- | 55 |
- R7009A |
- BXD102 |
- Adrenal |
- F |
-
-
- | 56 |
- R7010A |
- BXD69 |
- Adrenal |
- F |
-
-
- | 57 |
- R7011A |
- BXD60 |
- Adrenal |
- M |
-
-
- | 58 |
- R7012A |
- BXD45 |
- Adrenal |
- F |
-
-
- | 59 |
- R7013A |
- BXD79 |
- Adrenal |
- M |
-
-
- | 60 |
- R7014A |
- BXD40 |
- Adrenal |
- M |
-
-
- | 61 |
- R7015A |
- BXD79 |
- Adrenal |
- F |
-
-
- | 62 |
- R7016A |
- BXD40 |
- Adrenal |
- F |
-
-
- | 63 |
- R7017A |
- BXD68 |
- Adrenal |
- F |
-
-
- | 64 |
- R7018A |
- BXD85 |
- Adrenal |
- F |
-
-
- | 65 |
- R7019A |
- BXD44 |
- Adrenal |
- F |
-
-
- | 66 |
- R7020A |
- BXD70 |
- Adrenal |
- F |
-
-
- | 67 |
- R7021A |
- BXD68 |
- Adrenal |
- M |
-
-
- | 68 |
- R7023A |
- BXD44 |
- Adrenal |
- M |
-
-
- | 69 |
- R7024A |
- BXD95 |
- Adrenal |
- F |
-
-
- | 70 |
- R7025A |
- BXD56 |
- Adrenal |
- F |
-
-
- | 71 |
- R7032A |
- BXD103 |
- Adrenal |
- F |
-
-
- | 72 |
- R7034A |
- BXD24 |
- Adrenal |
- F |
-
-
- | 73 |
- R7035A |
- BXD101 |
- Adrenal |
- M |
-
-
- | 74 |
- R7036A |
- BXD29 |
- Adrenal |
- F |
-
-
- | 75 |
- R7037A |
- BXD60 |
- Adrenal |
- F |
-
-
- | 76 |
- R7038A |
- BXD69 |
- Adrenal |
- M |
-
-
- | 77 |
- R7039A |
- BXD73 |
- Adrenal |
- M |
-
-
- | 78 |
- R7040A |
- BXD80 |
- Adrenal |
- M |
-
-
- | 79 |
- R7041A |
- BXD11 |
- Adrenal |
- F |
-
-
- | 80 |
- R7042A |
- BXD74 |
- Adrenal |
- F |
-
-
- | 81 |
- R7043A |
- BXD67 |
- Adrenal |
- F |
-
-
- | 82 |
- R7044A |
- BXD67 |
- Adrenal |
- M |
-
-
- | 83 |
- R7046A |
- C57BL/6J |
- Adrenal |
- F |
-
-
- | 84 |
- R7047A |
- D2B6F1 |
- Adrenal |
- F |
-
-
- | 85 |
- R7048A |
- B6D2F1 |
- Adrenal |
- M |
-
-
- | 86 |
- R7051A |
- BXD80 |
- Adrenal |
- F |
-
-
- | 87 |
- R7053A |
- BXD102 |
- Adrenal |
- M |
-
-
- | 88 |
- R7054A |
- BXD49 |
- Adrenal |
- F |
-
-
- | 89 |
- R7055A |
- BXD77 |
- Adrenal |
- F |
-
-
- | 90 |
- R7056A |
- BXD77 |
- Adrenal |
- M |
-
-
- | 91 |
- R7057A |
- BXD66 |
- Adrenal |
- M |
-
-
- | 92 |
- R7058A |
- BXD66 |
- Adrenal |
- F |
-
-
- | 93 |
- R7059A |
- BXD45 |
- Adrenal |
- F |
-
-
- | 94 |
- R7145A |
- BXD67 |
- Adrenal |
- M |
-
-
- | 95 |
- R7147A |
- BXD85 |
- Adrenal |
- M |
-
-
- | 96 |
- R7148A |
- DBA/2J |
- Adrenal |
- F |
-
-
- | 97 |
- R7149A |
- D2B6F1 |
- Adrenal |
- M |
-
-
- | 98 |
- R7150A |
- D2B6F1 |
- Adrenal |
- F |
-
-
- | 99 |
- R7151A |
- BXD27 |
- Adrenal |
- M |
-
-
- | 100 |
- R7152A |
- B6D2F1 |
- Adrenal |
- M |
-
-
- | 101 |
- R7153A |
- DBA/2J |
- Adrenal |
- M |
-
-
- | 102 |
- R7159A |
- C57BL/6J |
- Adrenal |
- F |
-
-
- | 103 |
- R7161A |
- C57BL/6J |
- Adrenal |
- M |
-
-
- | 104 |
- R7164A |
- B6D2F1 |
- Adrenal |
- F |
-
-
- | 105 |
- R7166A |
- B6D2F1 |
- Adrenal |
- M |
-
-
- | 106 |
- R7167A |
- DBA/2J |
- Adrenal |
- F |
-
-
- | 107 |
- R7168A |
- DBA/2J |
- Adrenal |
- M |
-
-
-
- |
-
-
-
diff --git a/general/datasets/INIA_Adrenal_RMA_0612/experiment-design.rtf b/general/datasets/INIA_Adrenal_RMA_0612/experiment-design.rtf
deleted file mode 100644
index b069873..0000000
--- a/general/datasets/INIA_Adrenal_RMA_0612/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Normative expression in the adrenals (whole organ) of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
-
-Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/INIA_Adrenal_RMA_0612/platform.rtf b/general/datasets/INIA_Adrenal_RMA_0612/platform.rtf
deleted file mode 100644
index 7057d48..0000000
--- a/general/datasets/INIA_Adrenal_RMA_0612/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/INIA_Adrenal_RMA_0612/processing.rtf b/general/datasets/INIA_Adrenal_RMA_0612/processing.rtf
deleted file mode 100644
index 55aad2e..0000000
--- a/general/datasets/INIA_Adrenal_RMA_0612/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/INIA_Adrenal_RMA_0612/summary.rtf b/general/datasets/INIA_Adrenal_RMA_0612/summary.rtf
deleted file mode 100644
index 9858a55..0000000
--- a/general/datasets/INIA_Adrenal_RMA_0612/summary.rtf
+++ /dev/null
@@ -1,17 +0,0 @@
-Preliminary data WITH ERRORS of strain assignment as of July 20, 2012.
-
-Original Assignment had 253 probe sets with LRS >46.
-
-Corrections on Adrenal Data on July 25, 2012:
-R6963A(BXD31).....it should be BXD34
-R7018A(BXD85).....it should be BXD95
-R7152A(C57BL/6J)...it should be B6D2F1
-R7020A(BXD70).......it should be BXD65
-
-229 probe sets with LRS >46 after the corrections above from S. Roy of July 25, July 26 AM.
-
-More corrections from S. Roy (5 PM July 26)
-R6965A(BXD42).........should be BXD2
-R6973A(BXD12).........should be BXD8
-R6985A(BXD34).........should be BXD8
-R7151A(BXD99)..........should be BXD42
diff --git a/general/datasets/INIA_Adrenal_RMA_0612/tissue.rtf b/general/datasets/INIA_Adrenal_RMA_0612/tissue.rtf
deleted file mode 100644
index 54000a9..0000000
--- a/general/datasets/INIA_Adrenal_RMA_0612/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Whole adrenal gland. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/INIA_Adrenal_RMA_Ex_0612/cases.rtf b/general/datasets/INIA_Adrenal_RMA_Ex_0612/cases.rtf
deleted file mode 100644
index f0b204b..0000000
--- a/general/datasets/INIA_Adrenal_RMA_Ex_0612/cases.rtf
+++ /dev/null
@@ -1,771 +0,0 @@
-Young adult mice raised in specific pathogen-free vivarium at UTHSC.
-Table 1. Final strain correction by Khyobeni Mozhui on Mar 28, 2013.
-
-
-
-
-
-
-
-
- | Index |
- Sample ID |
- Strain |
- Tissue |
- Sex |
-
-
- | 1 |
- R6947A |
- BXD48 |
- Adrenal |
- M |
-
-
- | 2 |
- R6948A |
- BXD90 |
- Adrenal |
- M |
-
-
- | 3 |
- R6949A |
- BXD97 |
- Adrenal |
- M |
-
-
- | 4 |
- R6950A |
- BXD87 |
- Adrenal |
- M |
-
-
- | 5 |
- R6952A |
- BXD83 |
- Adrenal |
- F |
-
-
- | 6 |
- R6953A |
- BXD67 |
- Adrenal |
- M |
-
-
- | 7 |
- R6954A |
- BXD56 |
- Adrenal |
- M |
-
-
- | 8 |
- R6955A |
- BXD48 |
- Adrenal |
- F |
-
-
- | 9 |
- R6956A |
- BXD90 |
- Adrenal |
- F |
-
-
- | 10 |
- R6957A |
- BXD89 |
- Adrenal |
- M |
-
-
- | 11 |
- R6958A |
- BXD65 |
- Adrenal |
- M |
-
-
- | 12 |
- R6959A |
- BXD65 |
- Adrenal |
- F |
-
-
- | 13 |
- R6960A |
- BXD63 |
- Adrenal |
- F |
-
-
- | 14 |
- R6961A |
- BXD63 |
- Adrenal |
- M |
-
-
- | 15 |
- R6963A |
- BXD31 |
- Adrenal |
- M |
-
-
- | 16 |
- R6964A |
- BXD31 |
- Adrenal |
- F |
-
-
- | 17 |
- R6965A |
- BXD1 |
- Adrenal |
- F |
-
-
- | 18 |
- R6966A |
- BXD1 |
- Adrenal |
- F |
-
-
- | 19 |
- R6967A |
- BXD24 |
- Adrenal |
- F |
-
-
- | 20 |
- R6968A |
- BXD34 |
- Adrenal |
- M |
-
-
- | 21 |
- R6969A |
- BXD1 |
- Adrenal |
- M |
-
-
- | 22 |
- R6971A |
- BXD27 |
- Adrenal |
- F |
-
-
- | 23 |
- R6972A |
- BXD29 |
- Adrenal |
- M |
-
-
- | 24 |
- R6973A |
- BXD12 |
- Adrenal |
- F |
-
-
- | 25 |
- R6974A |
- BXD14 |
- Adrenal |
- F |
-
-
- | 26 |
- R6975A |
- BXD99 |
- Adrenal |
- F |
-
-
- | 27 |
- R6976A |
- BXD32 |
- Adrenal |
- F |
-
-
- | 28 |
- R6977A |
- BXD97 |
- Adrenal |
- F |
-
-
- | 29 |
- R6978A |
- BXD84 |
- Adrenal |
- M |
-
-
- | 30 |
- R6979A |
- BXD39 |
- Adrenal |
- M |
-
-
- | 31 |
- R6980A |
- BXD24 |
- Adrenal |
- M |
-
-
- | 32 |
- R6981A |
- BXD50 |
- Adrenal |
- F |
-
-
- | 33 |
- R6982A |
- BXD75 |
- Adrenal |
- M |
-
-
- | 34 |
- R6983A |
- BXD42 |
- Adrenal |
- M |
-
-
- | 35 |
- R6984A |
- BXD39 |
- Adrenal |
- F |
-
-
- | 36 |
- R6985A |
- BXD34 |
- Adrenal |
- F |
-
-
- | 37 |
- R6986A |
- BXD87 |
- Adrenal |
- F |
-
-
- | 38 |
- R6987A |
- BXD50 |
- Adrenal |
- M |
-
-
- | 39 |
- R6989A |
- BXD62 |
- Adrenal |
- M |
-
-
- | 40 |
- R6990A |
- BXD70 |
- Adrenal |
- M |
-
-
- | 41 |
- R6991A |
- BXD64 |
- Adrenal |
- F |
-
-
- | 42 |
- R6992A |
- BXD84 |
- Adrenal |
- F |
-
-
- | 43 |
- R6993A |
- BXD100 |
- Adrenal |
- F |
-
-
- | 44 |
- R6994A |
- BXD62 |
- Adrenal |
- F |
-
-
- | 45 |
- R6996A |
- BXD95 |
- Adrenal |
- M |
-
-
- | 46 |
- R6998A |
- BXD32 |
- Adrenal |
- M |
-
-
- | 47 |
- R6999A |
- BXD101 |
- Adrenal |
- F |
-
-
- | 48 |
- R7000A |
- BXD49 |
- Adrenal |
- M |
-
-
- | 49 |
- R7002A |
- BXD11 |
- Adrenal |
- M |
-
-
- | 50 |
- R7003A |
- BXD100 |
- Adrenal |
- M |
-
-
- | 51 |
- R7004A |
- BXD43 |
- Adrenal |
- F |
-
-
- | 52 |
- R7005A |
- BXD103 |
- Adrenal |
- M |
-
-
- | 53 |
- R7006A |
- BXD73 |
- Adrenal |
- F |
-
-
- | 54 |
- R7008A |
- BXD43 |
- Adrenal |
- M |
-
-
- | 55 |
- R7009A |
- BXD102 |
- Adrenal |
- F |
-
-
- | 56 |
- R7010A |
- BXD69 |
- Adrenal |
- F |
-
-
- | 57 |
- R7011A |
- BXD60 |
- Adrenal |
- M |
-
-
- | 58 |
- R7012A |
- BXD45 |
- Adrenal |
- F |
-
-
- | 59 |
- R7013A |
- BXD79 |
- Adrenal |
- M |
-
-
- | 60 |
- R7014A |
- BXD40 |
- Adrenal |
- M |
-
-
- | 61 |
- R7015A |
- BXD79 |
- Adrenal |
- F |
-
-
- | 62 |
- R7016A |
- BXD40 |
- Adrenal |
- F |
-
-
- | 63 |
- R7017A |
- BXD68 |
- Adrenal |
- F |
-
-
- | 64 |
- R7018A |
- BXD85 |
- Adrenal |
- F |
-
-
- | 65 |
- R7019A |
- BXD44 |
- Adrenal |
- F |
-
-
- | 66 |
- R7020A |
- BXD70 |
- Adrenal |
- F |
-
-
- | 67 |
- R7021A |
- BXD68 |
- Adrenal |
- M |
-
-
- | 68 |
- R7023A |
- BXD44 |
- Adrenal |
- M |
-
-
- | 69 |
- R7024A |
- BXD95 |
- Adrenal |
- F |
-
-
- | 70 |
- R7025A |
- BXD56 |
- Adrenal |
- F |
-
-
- | 71 |
- R7032A |
- BXD103 |
- Adrenal |
- F |
-
-
- | 72 |
- R7034A |
- BXD24 |
- Adrenal |
- F |
-
-
- | 73 |
- R7035A |
- BXD101 |
- Adrenal |
- M |
-
-
- | 74 |
- R7036A |
- BXD29 |
- Adrenal |
- F |
-
-
- | 75 |
- R7037A |
- BXD60 |
- Adrenal |
- F |
-
-
- | 76 |
- R7038A |
- BXD69 |
- Adrenal |
- M |
-
-
- | 77 |
- R7039A |
- BXD73 |
- Adrenal |
- M |
-
-
- | 78 |
- R7040A |
- BXD80 |
- Adrenal |
- M |
-
-
- | 79 |
- R7041A |
- BXD11 |
- Adrenal |
- F |
-
-
- | 80 |
- R7042A |
- BXD74 |
- Adrenal |
- F |
-
-
- | 81 |
- R7043A |
- BXD67 |
- Adrenal |
- F |
-
-
- | 82 |
- R7044A |
- BXD67 |
- Adrenal |
- M |
-
-
- | 83 |
- R7046A |
- C57BL/6J |
- Adrenal |
- F |
-
-
- | 84 |
- R7047A |
- D2B6F1 |
- Adrenal |
- F |
-
-
- | 85 |
- R7048A |
- B6D2F1 |
- Adrenal |
- M |
-
-
- | 86 |
- R7051A |
- BXD80 |
- Adrenal |
- F |
-
-
- | 87 |
- R7053A |
- BXD102 |
- Adrenal |
- M |
-
-
- | 88 |
- R7054A |
- BXD49 |
- Adrenal |
- F |
-
-
- | 89 |
- R7055A |
- BXD77 |
- Adrenal |
- F |
-
-
- | 90 |
- R7056A |
- BXD77 |
- Adrenal |
- M |
-
-
- | 91 |
- R7057A |
- BXD66 |
- Adrenal |
- M |
-
-
- | 92 |
- R7058A |
- BXD66 |
- Adrenal |
- F |
-
-
- | 93 |
- R7059A |
- BXD45 |
- Adrenal |
- F |
-
-
- | 94 |
- R7145A |
- BXD67 |
- Adrenal |
- M |
-
-
- | 95 |
- R7147A |
- BXD85 |
- Adrenal |
- M |
-
-
- | 96 |
- R7148A |
- DBA/2J |
- Adrenal |
- F |
-
-
- | 97 |
- R7149A |
- D2B6F1 |
- Adrenal |
- M |
-
-
- | 98 |
- R7150A |
- D2B6F1 |
- Adrenal |
- F |
-
-
- | 99 |
- R7151A |
- BXD27 |
- Adrenal |
- M |
-
-
- | 100 |
- R7152A |
- B6D2F1 |
- Adrenal |
- M |
-
-
- | 101 |
- R7153A |
- DBA/2J |
- Adrenal |
- M |
-
-
- | 102 |
- R7159A |
- C57BL/6J |
- Adrenal |
- F |
-
-
- | 103 |
- R7161A |
- C57BL/6J |
- Adrenal |
- M |
-
-
- | 104 |
- R7164A |
- B6D2F1 |
- Adrenal |
- F |
-
-
- | 105 |
- R7166A |
- B6D2F1 |
- Adrenal |
- M |
-
-
- | 106 |
- R7167A |
- DBA/2J |
- Adrenal |
- F |
-
-
- | 107 |
- R7168A |
- DBA/2J |
- Adrenal |
- M |
-
-
-
- |
-
-
-
diff --git a/general/datasets/INIA_Adrenal_RMA_Ex_0612/experiment-design.rtf b/general/datasets/INIA_Adrenal_RMA_Ex_0612/experiment-design.rtf
deleted file mode 100644
index b069873..0000000
--- a/general/datasets/INIA_Adrenal_RMA_Ex_0612/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Normative expression in the adrenals (whole organ) of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
-
-Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/INIA_Adrenal_RMA_Ex_0612/platform.rtf b/general/datasets/INIA_Adrenal_RMA_Ex_0612/platform.rtf
deleted file mode 100644
index 7057d48..0000000
--- a/general/datasets/INIA_Adrenal_RMA_Ex_0612/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/INIA_Adrenal_RMA_Ex_0612/processing.rtf b/general/datasets/INIA_Adrenal_RMA_Ex_0612/processing.rtf
deleted file mode 100644
index 55aad2e..0000000
--- a/general/datasets/INIA_Adrenal_RMA_Ex_0612/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/INIA_Adrenal_RMA_Ex_0612/summary.rtf b/general/datasets/INIA_Adrenal_RMA_Ex_0612/summary.rtf
deleted file mode 100644
index 9858a55..0000000
--- a/general/datasets/INIA_Adrenal_RMA_Ex_0612/summary.rtf
+++ /dev/null
@@ -1,17 +0,0 @@
-Preliminary data WITH ERRORS of strain assignment as of July 20, 2012.
-
-Original Assignment had 253 probe sets with LRS >46.
-
-Corrections on Adrenal Data on July 25, 2012:
-R6963A(BXD31).....it should be BXD34
-R7018A(BXD85).....it should be BXD95
-R7152A(C57BL/6J)...it should be B6D2F1
-R7020A(BXD70).......it should be BXD65
-
-229 probe sets with LRS >46 after the corrections above from S. Roy of July 25, July 26 AM.
-
-More corrections from S. Roy (5 PM July 26)
-R6965A(BXD42).........should be BXD2
-R6973A(BXD12).........should be BXD8
-R6985A(BXD34).........should be BXD8
-R7151A(BXD99)..........should be BXD42
diff --git a/general/datasets/INIA_Adrenal_RMA_Ex_0612/tissue.rtf b/general/datasets/INIA_Adrenal_RMA_Ex_0612/tissue.rtf
deleted file mode 100644
index 54000a9..0000000
--- a/general/datasets/INIA_Adrenal_RMA_Ex_0612/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Whole adrenal gland. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/INIA_Adrenal_RMA_F_0612/cases.rtf b/general/datasets/INIA_Adrenal_RMA_F_0612/cases.rtf
deleted file mode 100644
index f0b204b..0000000
--- a/general/datasets/INIA_Adrenal_RMA_F_0612/cases.rtf
+++ /dev/null
@@ -1,771 +0,0 @@
-Young adult mice raised in specific pathogen-free vivarium at UTHSC.
-Table 1. Final strain correction by Khyobeni Mozhui on Mar 28, 2013.
-
-
-
-
-
-
-
-
- | Index |
- Sample ID |
- Strain |
- Tissue |
- Sex |
-
-
- | 1 |
- R6947A |
- BXD48 |
- Adrenal |
- M |
-
-
- | 2 |
- R6948A |
- BXD90 |
- Adrenal |
- M |
-
-
- | 3 |
- R6949A |
- BXD97 |
- Adrenal |
- M |
-
-
- | 4 |
- R6950A |
- BXD87 |
- Adrenal |
- M |
-
-
- | 5 |
- R6952A |
- BXD83 |
- Adrenal |
- F |
-
-
- | 6 |
- R6953A |
- BXD67 |
- Adrenal |
- M |
-
-
- | 7 |
- R6954A |
- BXD56 |
- Adrenal |
- M |
-
-
- | 8 |
- R6955A |
- BXD48 |
- Adrenal |
- F |
-
-
- | 9 |
- R6956A |
- BXD90 |
- Adrenal |
- F |
-
-
- | 10 |
- R6957A |
- BXD89 |
- Adrenal |
- M |
-
-
- | 11 |
- R6958A |
- BXD65 |
- Adrenal |
- M |
-
-
- | 12 |
- R6959A |
- BXD65 |
- Adrenal |
- F |
-
-
- | 13 |
- R6960A |
- BXD63 |
- Adrenal |
- F |
-
-
- | 14 |
- R6961A |
- BXD63 |
- Adrenal |
- M |
-
-
- | 15 |
- R6963A |
- BXD31 |
- Adrenal |
- M |
-
-
- | 16 |
- R6964A |
- BXD31 |
- Adrenal |
- F |
-
-
- | 17 |
- R6965A |
- BXD1 |
- Adrenal |
- F |
-
-
- | 18 |
- R6966A |
- BXD1 |
- Adrenal |
- F |
-
-
- | 19 |
- R6967A |
- BXD24 |
- Adrenal |
- F |
-
-
- | 20 |
- R6968A |
- BXD34 |
- Adrenal |
- M |
-
-
- | 21 |
- R6969A |
- BXD1 |
- Adrenal |
- M |
-
-
- | 22 |
- R6971A |
- BXD27 |
- Adrenal |
- F |
-
-
- | 23 |
- R6972A |
- BXD29 |
- Adrenal |
- M |
-
-
- | 24 |
- R6973A |
- BXD12 |
- Adrenal |
- F |
-
-
- | 25 |
- R6974A |
- BXD14 |
- Adrenal |
- F |
-
-
- | 26 |
- R6975A |
- BXD99 |
- Adrenal |
- F |
-
-
- | 27 |
- R6976A |
- BXD32 |
- Adrenal |
- F |
-
-
- | 28 |
- R6977A |
- BXD97 |
- Adrenal |
- F |
-
-
- | 29 |
- R6978A |
- BXD84 |
- Adrenal |
- M |
-
-
- | 30 |
- R6979A |
- BXD39 |
- Adrenal |
- M |
-
-
- | 31 |
- R6980A |
- BXD24 |
- Adrenal |
- M |
-
-
- | 32 |
- R6981A |
- BXD50 |
- Adrenal |
- F |
-
-
- | 33 |
- R6982A |
- BXD75 |
- Adrenal |
- M |
-
-
- | 34 |
- R6983A |
- BXD42 |
- Adrenal |
- M |
-
-
- | 35 |
- R6984A |
- BXD39 |
- Adrenal |
- F |
-
-
- | 36 |
- R6985A |
- BXD34 |
- Adrenal |
- F |
-
-
- | 37 |
- R6986A |
- BXD87 |
- Adrenal |
- F |
-
-
- | 38 |
- R6987A |
- BXD50 |
- Adrenal |
- M |
-
-
- | 39 |
- R6989A |
- BXD62 |
- Adrenal |
- M |
-
-
- | 40 |
- R6990A |
- BXD70 |
- Adrenal |
- M |
-
-
- | 41 |
- R6991A |
- BXD64 |
- Adrenal |
- F |
-
-
- | 42 |
- R6992A |
- BXD84 |
- Adrenal |
- F |
-
-
- | 43 |
- R6993A |
- BXD100 |
- Adrenal |
- F |
-
-
- | 44 |
- R6994A |
- BXD62 |
- Adrenal |
- F |
-
-
- | 45 |
- R6996A |
- BXD95 |
- Adrenal |
- M |
-
-
- | 46 |
- R6998A |
- BXD32 |
- Adrenal |
- M |
-
-
- | 47 |
- R6999A |
- BXD101 |
- Adrenal |
- F |
-
-
- | 48 |
- R7000A |
- BXD49 |
- Adrenal |
- M |
-
-
- | 49 |
- R7002A |
- BXD11 |
- Adrenal |
- M |
-
-
- | 50 |
- R7003A |
- BXD100 |
- Adrenal |
- M |
-
-
- | 51 |
- R7004A |
- BXD43 |
- Adrenal |
- F |
-
-
- | 52 |
- R7005A |
- BXD103 |
- Adrenal |
- M |
-
-
- | 53 |
- R7006A |
- BXD73 |
- Adrenal |
- F |
-
-
- | 54 |
- R7008A |
- BXD43 |
- Adrenal |
- M |
-
-
- | 55 |
- R7009A |
- BXD102 |
- Adrenal |
- F |
-
-
- | 56 |
- R7010A |
- BXD69 |
- Adrenal |
- F |
-
-
- | 57 |
- R7011A |
- BXD60 |
- Adrenal |
- M |
-
-
- | 58 |
- R7012A |
- BXD45 |
- Adrenal |
- F |
-
-
- | 59 |
- R7013A |
- BXD79 |
- Adrenal |
- M |
-
-
- | 60 |
- R7014A |
- BXD40 |
- Adrenal |
- M |
-
-
- | 61 |
- R7015A |
- BXD79 |
- Adrenal |
- F |
-
-
- | 62 |
- R7016A |
- BXD40 |
- Adrenal |
- F |
-
-
- | 63 |
- R7017A |
- BXD68 |
- Adrenal |
- F |
-
-
- | 64 |
- R7018A |
- BXD85 |
- Adrenal |
- F |
-
-
- | 65 |
- R7019A |
- BXD44 |
- Adrenal |
- F |
-
-
- | 66 |
- R7020A |
- BXD70 |
- Adrenal |
- F |
-
-
- | 67 |
- R7021A |
- BXD68 |
- Adrenal |
- M |
-
-
- | 68 |
- R7023A |
- BXD44 |
- Adrenal |
- M |
-
-
- | 69 |
- R7024A |
- BXD95 |
- Adrenal |
- F |
-
-
- | 70 |
- R7025A |
- BXD56 |
- Adrenal |
- F |
-
-
- | 71 |
- R7032A |
- BXD103 |
- Adrenal |
- F |
-
-
- | 72 |
- R7034A |
- BXD24 |
- Adrenal |
- F |
-
-
- | 73 |
- R7035A |
- BXD101 |
- Adrenal |
- M |
-
-
- | 74 |
- R7036A |
- BXD29 |
- Adrenal |
- F |
-
-
- | 75 |
- R7037A |
- BXD60 |
- Adrenal |
- F |
-
-
- | 76 |
- R7038A |
- BXD69 |
- Adrenal |
- M |
-
-
- | 77 |
- R7039A |
- BXD73 |
- Adrenal |
- M |
-
-
- | 78 |
- R7040A |
- BXD80 |
- Adrenal |
- M |
-
-
- | 79 |
- R7041A |
- BXD11 |
- Adrenal |
- F |
-
-
- | 80 |
- R7042A |
- BXD74 |
- Adrenal |
- F |
-
-
- | 81 |
- R7043A |
- BXD67 |
- Adrenal |
- F |
-
-
- | 82 |
- R7044A |
- BXD67 |
- Adrenal |
- M |
-
-
- | 83 |
- R7046A |
- C57BL/6J |
- Adrenal |
- F |
-
-
- | 84 |
- R7047A |
- D2B6F1 |
- Adrenal |
- F |
-
-
- | 85 |
- R7048A |
- B6D2F1 |
- Adrenal |
- M |
-
-
- | 86 |
- R7051A |
- BXD80 |
- Adrenal |
- F |
-
-
- | 87 |
- R7053A |
- BXD102 |
- Adrenal |
- M |
-
-
- | 88 |
- R7054A |
- BXD49 |
- Adrenal |
- F |
-
-
- | 89 |
- R7055A |
- BXD77 |
- Adrenal |
- F |
-
-
- | 90 |
- R7056A |
- BXD77 |
- Adrenal |
- M |
-
-
- | 91 |
- R7057A |
- BXD66 |
- Adrenal |
- M |
-
-
- | 92 |
- R7058A |
- BXD66 |
- Adrenal |
- F |
-
-
- | 93 |
- R7059A |
- BXD45 |
- Adrenal |
- F |
-
-
- | 94 |
- R7145A |
- BXD67 |
- Adrenal |
- M |
-
-
- | 95 |
- R7147A |
- BXD85 |
- Adrenal |
- M |
-
-
- | 96 |
- R7148A |
- DBA/2J |
- Adrenal |
- F |
-
-
- | 97 |
- R7149A |
- D2B6F1 |
- Adrenal |
- M |
-
-
- | 98 |
- R7150A |
- D2B6F1 |
- Adrenal |
- F |
-
-
- | 99 |
- R7151A |
- BXD27 |
- Adrenal |
- M |
-
-
- | 100 |
- R7152A |
- B6D2F1 |
- Adrenal |
- M |
-
-
- | 101 |
- R7153A |
- DBA/2J |
- Adrenal |
- M |
-
-
- | 102 |
- R7159A |
- C57BL/6J |
- Adrenal |
- F |
-
-
- | 103 |
- R7161A |
- C57BL/6J |
- Adrenal |
- M |
-
-
- | 104 |
- R7164A |
- B6D2F1 |
- Adrenal |
- F |
-
-
- | 105 |
- R7166A |
- B6D2F1 |
- Adrenal |
- M |
-
-
- | 106 |
- R7167A |
- DBA/2J |
- Adrenal |
- F |
-
-
- | 107 |
- R7168A |
- DBA/2J |
- Adrenal |
- M |
-
-
-
- |
-
-
-
diff --git a/general/datasets/INIA_Adrenal_RMA_F_0612/experiment-design.rtf b/general/datasets/INIA_Adrenal_RMA_F_0612/experiment-design.rtf
deleted file mode 100644
index b069873..0000000
--- a/general/datasets/INIA_Adrenal_RMA_F_0612/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Normative expression in the adrenals (whole organ) of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
-
-Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/INIA_Adrenal_RMA_F_0612/platform.rtf b/general/datasets/INIA_Adrenal_RMA_F_0612/platform.rtf
deleted file mode 100644
index 7057d48..0000000
--- a/general/datasets/INIA_Adrenal_RMA_F_0612/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/INIA_Adrenal_RMA_F_0612/processing.rtf b/general/datasets/INIA_Adrenal_RMA_F_0612/processing.rtf
deleted file mode 100644
index 55aad2e..0000000
--- a/general/datasets/INIA_Adrenal_RMA_F_0612/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/INIA_Adrenal_RMA_F_0612/summary.rtf b/general/datasets/INIA_Adrenal_RMA_F_0612/summary.rtf
deleted file mode 100644
index 9858a55..0000000
--- a/general/datasets/INIA_Adrenal_RMA_F_0612/summary.rtf
+++ /dev/null
@@ -1,17 +0,0 @@
-Preliminary data WITH ERRORS of strain assignment as of July 20, 2012.
-
-Original Assignment had 253 probe sets with LRS >46.
-
-Corrections on Adrenal Data on July 25, 2012:
-R6963A(BXD31).....it should be BXD34
-R7018A(BXD85).....it should be BXD95
-R7152A(C57BL/6J)...it should be B6D2F1
-R7020A(BXD70).......it should be BXD65
-
-229 probe sets with LRS >46 after the corrections above from S. Roy of July 25, July 26 AM.
-
-More corrections from S. Roy (5 PM July 26)
-R6965A(BXD42).........should be BXD2
-R6973A(BXD12).........should be BXD8
-R6985A(BXD34).........should be BXD8
-R7151A(BXD99)..........should be BXD42
diff --git a/general/datasets/INIA_Adrenal_RMA_F_0612/tissue.rtf b/general/datasets/INIA_Adrenal_RMA_F_0612/tissue.rtf
deleted file mode 100644
index 54000a9..0000000
--- a/general/datasets/INIA_Adrenal_RMA_F_0612/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Whole adrenal gland. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/INIA_Adrenal_RMA_M_0612/cases.rtf b/general/datasets/INIA_Adrenal_RMA_M_0612/cases.rtf
deleted file mode 100644
index f0b204b..0000000
--- a/general/datasets/INIA_Adrenal_RMA_M_0612/cases.rtf
+++ /dev/null
@@ -1,771 +0,0 @@
-Young adult mice raised in specific pathogen-free vivarium at UTHSC.
-Table 1. Final strain correction by Khyobeni Mozhui on Mar 28, 2013.
-
-
-
-
-
-
-
-
- | Index |
- Sample ID |
- Strain |
- Tissue |
- Sex |
-
-
- | 1 |
- R6947A |
- BXD48 |
- Adrenal |
- M |
-
-
- | 2 |
- R6948A |
- BXD90 |
- Adrenal |
- M |
-
-
- | 3 |
- R6949A |
- BXD97 |
- Adrenal |
- M |
-
-
- | 4 |
- R6950A |
- BXD87 |
- Adrenal |
- M |
-
-
- | 5 |
- R6952A |
- BXD83 |
- Adrenal |
- F |
-
-
- | 6 |
- R6953A |
- BXD67 |
- Adrenal |
- M |
-
-
- | 7 |
- R6954A |
- BXD56 |
- Adrenal |
- M |
-
-
- | 8 |
- R6955A |
- BXD48 |
- Adrenal |
- F |
-
-
- | 9 |
- R6956A |
- BXD90 |
- Adrenal |
- F |
-
-
- | 10 |
- R6957A |
- BXD89 |
- Adrenal |
- M |
-
-
- | 11 |
- R6958A |
- BXD65 |
- Adrenal |
- M |
-
-
- | 12 |
- R6959A |
- BXD65 |
- Adrenal |
- F |
-
-
- | 13 |
- R6960A |
- BXD63 |
- Adrenal |
- F |
-
-
- | 14 |
- R6961A |
- BXD63 |
- Adrenal |
- M |
-
-
- | 15 |
- R6963A |
- BXD31 |
- Adrenal |
- M |
-
-
- | 16 |
- R6964A |
- BXD31 |
- Adrenal |
- F |
-
-
- | 17 |
- R6965A |
- BXD1 |
- Adrenal |
- F |
-
-
- | 18 |
- R6966A |
- BXD1 |
- Adrenal |
- F |
-
-
- | 19 |
- R6967A |
- BXD24 |
- Adrenal |
- F |
-
-
- | 20 |
- R6968A |
- BXD34 |
- Adrenal |
- M |
-
-
- | 21 |
- R6969A |
- BXD1 |
- Adrenal |
- M |
-
-
- | 22 |
- R6971A |
- BXD27 |
- Adrenal |
- F |
-
-
- | 23 |
- R6972A |
- BXD29 |
- Adrenal |
- M |
-
-
- | 24 |
- R6973A |
- BXD12 |
- Adrenal |
- F |
-
-
- | 25 |
- R6974A |
- BXD14 |
- Adrenal |
- F |
-
-
- | 26 |
- R6975A |
- BXD99 |
- Adrenal |
- F |
-
-
- | 27 |
- R6976A |
- BXD32 |
- Adrenal |
- F |
-
-
- | 28 |
- R6977A |
- BXD97 |
- Adrenal |
- F |
-
-
- | 29 |
- R6978A |
- BXD84 |
- Adrenal |
- M |
-
-
- | 30 |
- R6979A |
- BXD39 |
- Adrenal |
- M |
-
-
- | 31 |
- R6980A |
- BXD24 |
- Adrenal |
- M |
-
-
- | 32 |
- R6981A |
- BXD50 |
- Adrenal |
- F |
-
-
- | 33 |
- R6982A |
- BXD75 |
- Adrenal |
- M |
-
-
- | 34 |
- R6983A |
- BXD42 |
- Adrenal |
- M |
-
-
- | 35 |
- R6984A |
- BXD39 |
- Adrenal |
- F |
-
-
- | 36 |
- R6985A |
- BXD34 |
- Adrenal |
- F |
-
-
- | 37 |
- R6986A |
- BXD87 |
- Adrenal |
- F |
-
-
- | 38 |
- R6987A |
- BXD50 |
- Adrenal |
- M |
-
-
- | 39 |
- R6989A |
- BXD62 |
- Adrenal |
- M |
-
-
- | 40 |
- R6990A |
- BXD70 |
- Adrenal |
- M |
-
-
- | 41 |
- R6991A |
- BXD64 |
- Adrenal |
- F |
-
-
- | 42 |
- R6992A |
- BXD84 |
- Adrenal |
- F |
-
-
- | 43 |
- R6993A |
- BXD100 |
- Adrenal |
- F |
-
-
- | 44 |
- R6994A |
- BXD62 |
- Adrenal |
- F |
-
-
- | 45 |
- R6996A |
- BXD95 |
- Adrenal |
- M |
-
-
- | 46 |
- R6998A |
- BXD32 |
- Adrenal |
- M |
-
-
- | 47 |
- R6999A |
- BXD101 |
- Adrenal |
- F |
-
-
- | 48 |
- R7000A |
- BXD49 |
- Adrenal |
- M |
-
-
- | 49 |
- R7002A |
- BXD11 |
- Adrenal |
- M |
-
-
- | 50 |
- R7003A |
- BXD100 |
- Adrenal |
- M |
-
-
- | 51 |
- R7004A |
- BXD43 |
- Adrenal |
- F |
-
-
- | 52 |
- R7005A |
- BXD103 |
- Adrenal |
- M |
-
-
- | 53 |
- R7006A |
- BXD73 |
- Adrenal |
- F |
-
-
- | 54 |
- R7008A |
- BXD43 |
- Adrenal |
- M |
-
-
- | 55 |
- R7009A |
- BXD102 |
- Adrenal |
- F |
-
-
- | 56 |
- R7010A |
- BXD69 |
- Adrenal |
- F |
-
-
- | 57 |
- R7011A |
- BXD60 |
- Adrenal |
- M |
-
-
- | 58 |
- R7012A |
- BXD45 |
- Adrenal |
- F |
-
-
- | 59 |
- R7013A |
- BXD79 |
- Adrenal |
- M |
-
-
- | 60 |
- R7014A |
- BXD40 |
- Adrenal |
- M |
-
-
- | 61 |
- R7015A |
- BXD79 |
- Adrenal |
- F |
-
-
- | 62 |
- R7016A |
- BXD40 |
- Adrenal |
- F |
-
-
- | 63 |
- R7017A |
- BXD68 |
- Adrenal |
- F |
-
-
- | 64 |
- R7018A |
- BXD85 |
- Adrenal |
- F |
-
-
- | 65 |
- R7019A |
- BXD44 |
- Adrenal |
- F |
-
-
- | 66 |
- R7020A |
- BXD70 |
- Adrenal |
- F |
-
-
- | 67 |
- R7021A |
- BXD68 |
- Adrenal |
- M |
-
-
- | 68 |
- R7023A |
- BXD44 |
- Adrenal |
- M |
-
-
- | 69 |
- R7024A |
- BXD95 |
- Adrenal |
- F |
-
-
- | 70 |
- R7025A |
- BXD56 |
- Adrenal |
- F |
-
-
- | 71 |
- R7032A |
- BXD103 |
- Adrenal |
- F |
-
-
- | 72 |
- R7034A |
- BXD24 |
- Adrenal |
- F |
-
-
- | 73 |
- R7035A |
- BXD101 |
- Adrenal |
- M |
-
-
- | 74 |
- R7036A |
- BXD29 |
- Adrenal |
- F |
-
-
- | 75 |
- R7037A |
- BXD60 |
- Adrenal |
- F |
-
-
- | 76 |
- R7038A |
- BXD69 |
- Adrenal |
- M |
-
-
- | 77 |
- R7039A |
- BXD73 |
- Adrenal |
- M |
-
-
- | 78 |
- R7040A |
- BXD80 |
- Adrenal |
- M |
-
-
- | 79 |
- R7041A |
- BXD11 |
- Adrenal |
- F |
-
-
- | 80 |
- R7042A |
- BXD74 |
- Adrenal |
- F |
-
-
- | 81 |
- R7043A |
- BXD67 |
- Adrenal |
- F |
-
-
- | 82 |
- R7044A |
- BXD67 |
- Adrenal |
- M |
-
-
- | 83 |
- R7046A |
- C57BL/6J |
- Adrenal |
- F |
-
-
- | 84 |
- R7047A |
- D2B6F1 |
- Adrenal |
- F |
-
-
- | 85 |
- R7048A |
- B6D2F1 |
- Adrenal |
- M |
-
-
- | 86 |
- R7051A |
- BXD80 |
- Adrenal |
- F |
-
-
- | 87 |
- R7053A |
- BXD102 |
- Adrenal |
- M |
-
-
- | 88 |
- R7054A |
- BXD49 |
- Adrenal |
- F |
-
-
- | 89 |
- R7055A |
- BXD77 |
- Adrenal |
- F |
-
-
- | 90 |
- R7056A |
- BXD77 |
- Adrenal |
- M |
-
-
- | 91 |
- R7057A |
- BXD66 |
- Adrenal |
- M |
-
-
- | 92 |
- R7058A |
- BXD66 |
- Adrenal |
- F |
-
-
- | 93 |
- R7059A |
- BXD45 |
- Adrenal |
- F |
-
-
- | 94 |
- R7145A |
- BXD67 |
- Adrenal |
- M |
-
-
- | 95 |
- R7147A |
- BXD85 |
- Adrenal |
- M |
-
-
- | 96 |
- R7148A |
- DBA/2J |
- Adrenal |
- F |
-
-
- | 97 |
- R7149A |
- D2B6F1 |
- Adrenal |
- M |
-
-
- | 98 |
- R7150A |
- D2B6F1 |
- Adrenal |
- F |
-
-
- | 99 |
- R7151A |
- BXD27 |
- Adrenal |
- M |
-
-
- | 100 |
- R7152A |
- B6D2F1 |
- Adrenal |
- M |
-
-
- | 101 |
- R7153A |
- DBA/2J |
- Adrenal |
- M |
-
-
- | 102 |
- R7159A |
- C57BL/6J |
- Adrenal |
- F |
-
-
- | 103 |
- R7161A |
- C57BL/6J |
- Adrenal |
- M |
-
-
- | 104 |
- R7164A |
- B6D2F1 |
- Adrenal |
- F |
-
-
- | 105 |
- R7166A |
- B6D2F1 |
- Adrenal |
- M |
-
-
- | 106 |
- R7167A |
- DBA/2J |
- Adrenal |
- F |
-
-
- | 107 |
- R7168A |
- DBA/2J |
- Adrenal |
- M |
-
-
-
- |
-
-
-
diff --git a/general/datasets/INIA_Adrenal_RMA_M_0612/experiment-design.rtf b/general/datasets/INIA_Adrenal_RMA_M_0612/experiment-design.rtf
deleted file mode 100644
index b069873..0000000
--- a/general/datasets/INIA_Adrenal_RMA_M_0612/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Normative expression in the adrenals (whole organ) of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
-
-Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/INIA_Adrenal_RMA_M_0612/platform.rtf b/general/datasets/INIA_Adrenal_RMA_M_0612/platform.rtf
deleted file mode 100644
index 7057d48..0000000
--- a/general/datasets/INIA_Adrenal_RMA_M_0612/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/INIA_Adrenal_RMA_M_0612/processing.rtf b/general/datasets/INIA_Adrenal_RMA_M_0612/processing.rtf
deleted file mode 100644
index 55aad2e..0000000
--- a/general/datasets/INIA_Adrenal_RMA_M_0612/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/INIA_Adrenal_RMA_M_0612/summary.rtf b/general/datasets/INIA_Adrenal_RMA_M_0612/summary.rtf
deleted file mode 100644
index 9858a55..0000000
--- a/general/datasets/INIA_Adrenal_RMA_M_0612/summary.rtf
+++ /dev/null
@@ -1,17 +0,0 @@
-Preliminary data WITH ERRORS of strain assignment as of July 20, 2012.
-
-Original Assignment had 253 probe sets with LRS >46.
-
-Corrections on Adrenal Data on July 25, 2012:
-R6963A(BXD31).....it should be BXD34
-R7018A(BXD85).....it should be BXD95
-R7152A(C57BL/6J)...it should be B6D2F1
-R7020A(BXD70).......it should be BXD65
-
-229 probe sets with LRS >46 after the corrections above from S. Roy of July 25, July 26 AM.
-
-More corrections from S. Roy (5 PM July 26)
-R6965A(BXD42).........should be BXD2
-R6973A(BXD12).........should be BXD8
-R6985A(BXD34).........should be BXD8
-R7151A(BXD99)..........should be BXD42
diff --git a/general/datasets/INIA_Adrenal_RMA_M_0612/tissue.rtf b/general/datasets/INIA_Adrenal_RMA_M_0612/tissue.rtf
deleted file mode 100644
index 54000a9..0000000
--- a/general/datasets/INIA_Adrenal_RMA_M_0612/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Whole adrenal gland. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/cases.rtf b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/cases.rtf
new file mode 100644
index 0000000..b02b19a
--- /dev/null
+++ b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 58 strains, including 54 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1) were analyzed. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by K. Mozhui. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. Fifty strains have matched male and female samples. Five strains have male only samples (BXD5, 13, 16, 100 and 103). Three strains have only female samples (BXD44, 70, and 87.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/experiment-design.rtf b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/experiment-design.rtf
new file mode 100644
index 0000000..126d431
--- /dev/null
+++ b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/experiment-design.rtf
@@ -0,0 +1,1152 @@
+Data Evaluation Summary
+
+
+ - eQLTs with LOD >10 (LRS>46.1): n = 525
+ - eQTL with high LOD and LRS: Trait ID 10513604 (Hdhd3) LOD = 39.8, LRS = 183.5
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6853BL |
+ BLA |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6861BL |
+ BLA |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6851BL |
+ BLA |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6859BL |
+ BLA |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6863BL |
+ BLA |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6865BL |
+ BLA |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6857BL |
+ BLA |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6855BL |
+ BLA |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6799BL |
+ BLA |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6795BL |
+ BLA |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6787BL |
+ BLA |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6785BL |
+ BLA |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6819BL |
+ BLA |
+ BXD12 |
+ 78 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 14 |
+ R6789BL |
+ BLA |
+ BXD12 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 15 |
+ R6805BL |
+ BLA |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6291BL |
+ BLA |
+ BXD13 |
+ N/A |
+ M |
+ 6/11/09 |
+ N/A |
+
+
+ | 17 |
+ R6811BL |
+ BLA |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 18 |
+ R6825BL |
+ BLA |
+ BXD14 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 19 |
+ R6657BL |
+ BLA |
+ BXD16 |
+ N/A |
+ M |
+ 1/8/08 |
+ N/A |
+
+
+ | 20 |
+ R6054BL |
+ BLA |
+ BXD19 |
+ N/A |
+ F |
+ 2/26/08 |
+ N/A |
+
+
+ | 21 |
+ R6052BL |
+ BLA |
+ BXD19 |
+ N/A |
+ M |
+ 2/26/08 |
+ N/A |
+
+
+ | 22 |
+ R6803BL |
+ BLA |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 23 |
+ R6817BL |
+ BLA |
+ BXD24 |
+ 86 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6063BL |
+ BLA |
+ BXD25 |
+ N/A |
+ F |
+ 3/12/08 |
+ N/A |
+
+
+ | 25 |
+ R6062BL |
+ BLA |
+ BXD25 |
+ N/A |
+ M |
+ 3/12/08 |
+ N/A |
+
+
+ | 26 |
+ R6659BL |
+ BLA |
+ BXD27 |
+ N/A |
+ F |
+ 1/8/08 |
+ N/A |
+
+
+ | 27 |
+ R6791BL |
+ BLA |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 28 |
+ R6797BL |
+ BLA |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 29 |
+ R6793BL |
+ BLA |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 30 |
+ R6815BL |
+ BLA |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 31 |
+ R6801BL |
+ BLA |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 32 |
+ R6915BL |
+ BLA |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 33 |
+ R6845BL |
+ BLA |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 34 |
+ R6821BL |
+ BLA |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 35 |
+ R6807BL |
+ BLA |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 36 |
+ R6057BL |
+ BLA |
+ BXD38 |
+ N/A |
+ F |
+ 2/26/08 |
+ N/A |
+
+
+ | 37 |
+ R6056BL |
+ BLA |
+ BXD38 |
+ N/A |
+ M |
+ 2/26/08 |
+ N/A |
+
+
+ | 38 |
+ R6827BL |
+ BLA |
+ BXD39 |
+ 79 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 39 |
+ R6813BL |
+ BLA |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 40 |
+ R6847BL |
+ BLA |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 41 |
+ R6849BL |
+ BLA |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 42 |
+ R6809BL |
+ BLA |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 43 |
+ R6823BL |
+ BLA |
+ BXD42 |
+ 87 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 44 |
+ R6759BL |
+ BLA |
+ BXD43 |
+ 81 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 45 |
+ R6757BL |
+ BLA |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 46 |
+ R6745BL |
+ BLA |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 47 |
+ R6763BL |
+ BLA |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 48 |
+ R6761BL |
+ BLA |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 49 |
+ R6879BL |
+ BLA |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6881BL |
+ BLA |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6751BL |
+ BLA |
+ BXD49 |
+ 84 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 52 |
+ R6747BL |
+ BLA |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 53 |
+ R6104BL |
+ BLA |
+ BXD5 |
+ N/A |
+ f |
+ 10/23/09 |
+ N/A |
+
+
+ | 54 |
+ R6103BL |
+ BLA |
+ BXD5 |
+ N/A |
+ M |
+ 10/23/09 |
+ N/A |
+
+
+ | 55 |
+ R6889BL |
+ BLA |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6891BL |
+ BLA |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6074BL |
+ BLA |
+ BXD51 |
+ N/A |
+ F |
+ 3/12/08 |
+ N/A |
+
+
+ | 58 |
+ R6699BL |
+ BLA |
+ BXD51 |
+ N/A |
+ M |
+ 4/30/09 |
+ N/A |
+
+
+ | 59 |
+ R6917BL |
+ BLA |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 60 |
+ R6893BL |
+ BLA |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 61 |
+ R6769BL |
+ BLA |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 62 |
+ R6771BL |
+ BLA |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6655BL |
+ BLA |
+ BXD61 |
+ N/A |
+ F |
+ 1/29/08 |
+ N/A |
+
+
+ | 64 |
+ R6653BL |
+ BLA |
+ BXD61 |
+ N/A |
+ M |
+ 1/29/08 |
+ N/A |
+
+
+ | 65 |
+ R6835BL |
+ BLA |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 66 |
+ R6843BL |
+ BLA |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6887BL |
+ BLA |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6885BL |
+ BLA |
+ BXD63 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6877BL |
+ BLA |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6873BL |
+ BLA |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6929BL |
+ BLA |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6931BL |
+ BLA |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6775BL |
+ BLA |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 74 |
+ R6773BL |
+ BLA |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 75 |
+ R6925BL |
+ BLA |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6921BL |
+ BLA |
+ BXD70 |
+ 76 |
+ M |
+ 8/17/06 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6869BL |
+ BLA |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6871BL |
+ BLA |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 79 |
+ R6777BL |
+ BLA |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 80 |
+ R6779BL |
+ BLA |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 81 |
+ R6837BL |
+ BLA |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 82 |
+ R6829BL |
+ BLA |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 83 |
+ R6933BL |
+ BLA |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 84 |
+ R6935BL |
+ BLA |
+ BXD79 |
+ 87 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 85 |
+ R6781BL |
+ BLA |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 86 |
+ R6783BL |
+ BLA |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 87 |
+ R6913BL |
+ BLA |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 88 |
+ R6911BL |
+ BLA |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 89 |
+ R6841BL |
+ BLA |
+ BXD84 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 90 |
+ R6833BL |
+ BLA |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 91 |
+ R6937BL |
+ BLA |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 92 |
+ R6939BL |
+ BLA |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 93 |
+ R6909BL |
+ BLA |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 94 |
+ R6895BL |
+ BLA |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 95 |
+ R6897BL |
+ BLA |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 96 |
+ R6903BL |
+ BLA |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 97 |
+ R6905BL |
+ BLA |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 98 |
+ R6923BL |
+ BLA |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 99 |
+ R6927BL |
+ BLA |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 100 |
+ R6919BL |
+ BLA |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 101 |
+ R6867BL |
+ BLA |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 102 |
+ R6899BL |
+ BLA |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 103 |
+ R6901BL |
+ BLA |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 104 |
+ R6875BL |
+ BLA |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 105 |
+ R6883BL |
+ BLA |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 106 |
+ R6831BL |
+ BLA |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 107 |
+ R6943BL |
+ BLA |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 108 |
+ R6941BL |
+ BLA |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 109 |
+ R6753BL |
+ BLA |
+ BXD102 |
+ 88 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 110 |
+ R6755BL |
+ BLA |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 111 |
+ R6765BL |
+ BLA |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/platform.rtf b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/processing.rtf b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/processing.rtf
new file mode 100644
index 0000000..a2a6c30
--- /dev/null
+++ b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/processing.rtf
@@ -0,0 +1,16 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required no initial correction for batch effects and the data in this initial release do not incorporate any additional corrections. However, there are several confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Dissection variation: examine and use probe sets for Ttr as a correction for the inclusion of choroid plexus and non-parenchmymal tissue in samples. Transthyretin is only expressed in the choroid plexus (PMID 16698124
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the 54 probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases (58) in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest 54 probe sets in this amygdala data set accounts of 42% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the amygdala data set can be map as a trait. It is not associated with any QLTs that are even suggestive, and the highest LRS is about 10 on chromosomes 18 and 19. The second principal component trait, which accounts for only 5% of the "noise" variance, has a suggestive QTL (LRS of 12, high B allele) on chromosome 4 at about 90 Mb. We therefore do not think that there is significant risk of major false trans eQTL bands in this data set.
+
+
+Data Release. This data set was first uploaded into GeneNetwork November 25, 2010 and made accessible without a password to all users on December 1, 2010. The data set was orginally entered with two strain identification errors that were fixed Dec 10, 2010 by KM Mozhui and A Centeno (array R6659BL was originally listed as BXD16 but is BXD27; R6789BL was original listed as BXD27 is BXD12). The current data release has no known errors of sex or strain assignment.
+
+Data Status and Use. The data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/specifics.rtf b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/specifics.rtf
new file mode 100644
index 0000000..2400c03
--- /dev/null
+++ b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/specifics.rtf
@@ -0,0 +1 @@
+Exon Level
diff --git a/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/summary.rtf b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/summary.rtf
new file mode 100644
index 0000000..41311b7
--- /dev/null
+++ b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/summary.rtf
@@ -0,0 +1 @@
+This is a final error-checked release of an amygdala gene expression data set generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from the NIH NIAAA. The basolateral complex of the amygdala of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/tissue.rtf b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/tissue.rtf
new file mode 100644
index 0000000..ea556c7
--- /dev/null
+++ b/general/datasets/INIA_Amg_BLA_Ex-RMA_1110/tissue.rtf
@@ -0,0 +1,12 @@
+Dissection Protocol
+
+
+ - Animals were sacrificed by cervical dislocation and brains were immediately dissected from the head and stored in RNAlater (www.ambion.com) for 2 to 3 days at 4 deg C in a refrigerator.
+ - Brains were placed with ventral side up on a cutting surface and a partial coronal cut was made with a surgical blade at a level that corresponds approximately to the -2.5 mm behind the stereotaxic Bregma point (this cut is just a little rostral from the pontine fibres when viewed from the ventral side).
+ - Brains were placed in a coronal matrix (egg-style slicer) and a 2-mm thick coronal slab was taken just rostral to the initial cut.
+ - The 2-mm thick slab was placed on a clean glass slide and the hypothalamus was cut out and placed in a tube on dry ice.
+ - To dissect the BLA, the temporal lobes were detached by placing a scalpel in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then cut out and placed in a tube on dry ice.
+ - Tissue from two mice (right and left sides) and from the same strain and sex (an usually the same litter) were pooled. The only exceptions are BLA samples from strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue was obtained from only one animal per array).
+
+
+
diff --git a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/cases.rtf b/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/cases.rtf
deleted file mode 100644
index b02b19a..0000000
--- a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Cases. A total of 58 strains, including 54 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1) were analyzed. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by K. Mozhui. Samples were pooled by sex and usually include at least two cases per sex and strain.
-
-Sex Balance. Fifty strains have matched male and female samples. Five strains have male only samples (BXD5, 13, 16, 100 and 103). Three strains have only female samples (BXD44, 70, and 87.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/experiment-design.rtf b/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/experiment-design.rtf
deleted file mode 100644
index 126d431..0000000
--- a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/experiment-design.rtf
+++ /dev/null
@@ -1,1152 +0,0 @@
-Data Evaluation Summary
-
-
- - eQLTs with LOD >10 (LRS>46.1): n = 525
- - eQTL with high LOD and LRS: Trait ID 10513604 (Hdhd3) LOD = 39.8, LRS = 183.5
- - Lowest mean value: Trait ID 10344361, mean = 3.998
- - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
- - Greatest sex difference: Trait ID: 10606178 (Xist)
- - Great variation within and among strains: Trait ID 10454192 (Ttr
-
-
-
-
-
-
-
-
-
- | Index |
- Array ID |
- Tissue |
- Strain |
- Age |
- Sex |
- Date sacrifice |
- Time sacrifice |
-
-
- | 1 |
- R6853BL |
- BLA |
- C57BL/6J |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 2 |
- R6861BL |
- BLA |
- C57BL/6J |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 3 |
- R6851BL |
- BLA |
- D2B6F1 |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 4 |
- R6859BL |
- BLA |
- D2B6F1 |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 5 |
- R6863BL |
- BLA |
- DBA/2J |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 6 |
- R6865BL |
- BLA |
- DBA/2J |
- 68 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 7 |
- R6857BL |
- BLA |
- B6D2F1 |
- 69 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 8 |
- R6855BL |
- BLA |
- B6D2F1 |
- 69 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 9 |
- R6799BL |
- BLA |
- BXD1 |
- 71 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 10 |
- R6795BL |
- BLA |
- BXD1 |
- 85 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 11 |
- R6787BL |
- BLA |
- BXD11 |
- 87 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 12 |
- R6785BL |
- BLA |
- BXD11 |
- 76 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 13 |
- R6819BL |
- BLA |
- BXD12 |
- 78 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 14 |
- R6789BL |
- BLA |
- BXD12 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 15 |
- R6805BL |
- BLA |
- BXD12 |
- 77 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 16 |
- R6291BL |
- BLA |
- BXD13 |
- N/A |
- M |
- 6/11/09 |
- N/A |
-
-
- | 17 |
- R6811BL |
- BLA |
- BXD14 |
- 81 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 18 |
- R6825BL |
- BLA |
- BXD14 |
- 81 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 19 |
- R6657BL |
- BLA |
- BXD16 |
- N/A |
- M |
- 1/8/08 |
- N/A |
-
-
- | 20 |
- R6054BL |
- BLA |
- BXD19 |
- N/A |
- F |
- 2/26/08 |
- N/A |
-
-
- | 21 |
- R6052BL |
- BLA |
- BXD19 |
- N/A |
- M |
- 2/26/08 |
- N/A |
-
-
- | 22 |
- R6803BL |
- BLA |
- BXD24 |
- 85 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 23 |
- R6817BL |
- BLA |
- BXD24 |
- 86 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 24 |
- R6063BL |
- BLA |
- BXD25 |
- N/A |
- F |
- 3/12/08 |
- N/A |
-
-
- | 25 |
- R6062BL |
- BLA |
- BXD25 |
- N/A |
- M |
- 3/12/08 |
- N/A |
-
-
- | 26 |
- R6659BL |
- BLA |
- BXD27 |
- N/A |
- F |
- 1/8/08 |
- N/A |
-
-
- | 27 |
- R6791BL |
- BLA |
- BXD27 |
- 75 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 28 |
- R6797BL |
- BLA |
- BXD29 |
- 71 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 29 |
- R6793BL |
- BLA |
- BXD29 |
- 71 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 30 |
- R6815BL |
- BLA |
- BXD31 |
- 74 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 31 |
- R6801BL |
- BLA |
- BXD31 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 32 |
- R6915BL |
- BLA |
- BXD32 |
- 81 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 33 |
- R6845BL |
- BLA |
- BXD32 |
- 81 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 34 |
- R6821BL |
- BLA |
- BXD34 |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 35 |
- R6807BL |
- BLA |
- BXD34 |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 36 |
- R6057BL |
- BLA |
- BXD38 |
- N/A |
- F |
- 2/26/08 |
- N/A |
-
-
- | 37 |
- R6056BL |
- BLA |
- BXD38 |
- N/A |
- M |
- 2/26/08 |
- N/A |
-
-
- | 38 |
- R6827BL |
- BLA |
- BXD39 |
- 79 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 39 |
- R6813BL |
- BLA |
- BXD39 |
- 79 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 40 |
- R6847BL |
- BLA |
- BXD40 |
- 85 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 41 |
- R6849BL |
- BLA |
- BXD40 |
- 85 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 42 |
- R6809BL |
- BLA |
- BXD42 |
- 87 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 43 |
- R6823BL |
- BLA |
- BXD42 |
- 87 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 44 |
- R6759BL |
- BLA |
- BXD43 |
- 81 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 45 |
- R6757BL |
- BLA |
- BXD43 |
- 81 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 46 |
- R6745BL |
- BLA |
- BXD44 |
- 83 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 47 |
- R6763BL |
- BLA |
- BXD45 |
- 77 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 48 |
- R6761BL |
- BLA |
- BXD45 |
- 77 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 49 |
- R6879BL |
- BLA |
- BXD48 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 50 |
- R6881BL |
- BLA |
- BXD48 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 51 |
- R6751BL |
- BLA |
- BXD49 |
- 84 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 52 |
- R6747BL |
- BLA |
- BXD49 |
- 84 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 53 |
- R6104BL |
- BLA |
- BXD5 |
- N/A |
- f |
- 10/23/09 |
- N/A |
-
-
- | 54 |
- R6103BL |
- BLA |
- BXD5 |
- N/A |
- M |
- 10/23/09 |
- N/A |
-
-
- | 55 |
- R6889BL |
- BLA |
- BXD50 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 56 |
- R6891BL |
- BLA |
- BXD50 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 57 |
- R6074BL |
- BLA |
- BXD51 |
- N/A |
- F |
- 3/12/08 |
- N/A |
-
-
- | 58 |
- R6699BL |
- BLA |
- BXD51 |
- N/A |
- M |
- 4/30/09 |
- N/A |
-
-
- | 59 |
- R6917BL |
- BLA |
- BXD56 |
- 84 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 60 |
- R6893BL |
- BLA |
- BXD56 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 61 |
- R6769BL |
- BLA |
- BXD60 |
- 70 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 62 |
- R6771BL |
- BLA |
- BXD60 |
- 70 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 63 |
- R6655BL |
- BLA |
- BXD61 |
- N/A |
- F |
- 1/29/08 |
- N/A |
-
-
- | 64 |
- R6653BL |
- BLA |
- BXD61 |
- N/A |
- M |
- 1/29/08 |
- N/A |
-
-
- | 65 |
- R6835BL |
- BLA |
- BXD62 |
- 83 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 66 |
- R6843BL |
- BLA |
- BXD62 |
- 83 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 67 |
- R6887BL |
- BLA |
- BXD63 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 68 |
- R6885BL |
- BLA |
- BXD63 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 69 |
- R6877BL |
- BLA |
- BXD65 |
- 84 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 70 |
- R6873BL |
- BLA |
- BXD65 |
- 84 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 71 |
- R6929BL |
- BLA |
- BXD68 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 72 |
- R6931BL |
- BLA |
- BXD68 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 73 |
- R6775BL |
- BLA |
- BXD69 |
- 69 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 74 |
- R6773BL |
- BLA |
- BXD69 |
- 80 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 75 |
- R6925BL |
- BLA |
- BXD70 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 76 |
- R6921BL |
- BLA |
- BXD70 |
- 76 |
- M |
- 8/17/06 |
- 1 PM to 6:45 PM |
-
-
- | 77 |
- R6869BL |
- BLA |
- BXD71 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 78 |
- R6871BL |
- BLA |
- BXD71 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 79 |
- R6777BL |
- BLA |
- BXD73 |
- 83 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 80 |
- R6779BL |
- BLA |
- BXD73 |
- 83 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 81 |
- R6837BL |
- BLA |
- BXD75 |
- 76 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 82 |
- R6829BL |
- BLA |
- BXD75 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 83 |
- R6933BL |
- BLA |
- BXD79 |
- 87 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 84 |
- R6935BL |
- BLA |
- BXD79 |
- 87 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 85 |
- R6781BL |
- BLA |
- BXD80 |
- 73 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 86 |
- R6783BL |
- BLA |
- BXD80 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 87 |
- R6913BL |
- BLA |
- BXD83 |
- 81 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 88 |
- R6911BL |
- BLA |
- BXD83 |
- 81 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 89 |
- R6841BL |
- BLA |
- BXD84 |
- 76 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 90 |
- R6833BL |
- BLA |
- BXD84 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 91 |
- R6937BL |
- BLA |
- BXD85 |
- 74 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 92 |
- R6939BL |
- BLA |
- BXD85 |
- 74 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 93 |
- R6909BL |
- BLA |
- BXD87 |
- 83 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 94 |
- R6895BL |
- BLA |
- BXD89 |
- 82 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 95 |
- R6897BL |
- BLA |
- BXD89 |
- 82 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 96 |
- R6903BL |
- BLA |
- BXD90 |
- 82 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 97 |
- R6905BL |
- BLA |
- BXD90 |
- 82 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 98 |
- R6923BL |
- BLA |
- BXD92 |
- 86 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 99 |
- R6927BL |
- BLA |
- BXD92 |
- 89 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 100 |
- R6919BL |
- BLA |
- BXD95 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 101 |
- R6867BL |
- BLA |
- BXD95 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 102 |
- R6899BL |
- BLA |
- BXD97 |
- 71 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 103 |
- R6901BL |
- BLA |
- BXD97 |
- 71 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 104 |
- R6875BL |
- BLA |
- BXD99 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 105 |
- R6883BL |
- BLA |
- BXD99 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 106 |
- R6831BL |
- BLA |
- BXD100 |
- 83 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 107 |
- R6943BL |
- BLA |
- BXD101 |
- 89 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 108 |
- R6941BL |
- BLA |
- BXD101 |
- 89 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 109 |
- R6753BL |
- BLA |
- BXD102 |
- 88 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 110 |
- R6755BL |
- BLA |
- BXD102 |
- 88 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 111 |
- R6765BL |
- BLA |
- BXD103 |
- 78 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
-
- |
-
-
-
-
-
-
-
-
-
-
-
-
diff --git a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/platform.rtf b/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/platform.rtf
deleted file mode 100644
index aba2206..0000000
--- a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/processing.rtf b/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/processing.rtf
deleted file mode 100644
index a2a6c30..0000000
--- a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/processing.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
-
-Batch Effects. This data set required no initial correction for batch effects and the data in this initial release do not incorporate any additional corrections. However, there are several confounder-like factors that should be considered:
-
-
- - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
- - Dissection variation: examine and use probe sets for Ttr as a correction for the inclusion of choroid plexus and non-parenchmymal tissue in samples. Transthyretin is only expressed in the choroid plexus (PMID 16698124
- - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the 54 probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases (58) in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest 54 probe sets in this amygdala data set accounts of 42% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the amygdala data set can be map as a trait. It is not associated with any QLTs that are even suggestive, and the highest LRS is about 10 on chromosomes 18 and 19. The second principal component trait, which accounts for only 5% of the "noise" variance, has a suggestive QTL (LRS of 12, high B allele) on chromosome 4 at about 90 Mb. We therefore do not think that there is significant risk of major false trans eQTL bands in this data set.
-
-
-Data Release. This data set was first uploaded into GeneNetwork November 25, 2010 and made accessible without a password to all users on December 1, 2010. The data set was orginally entered with two strain identification errors that were fixed Dec 10, 2010 by KM Mozhui and A Centeno (array R6659BL was originally listed as BXD16 but is BXD27; R6789BL was original listed as BXD27 is BXD12). The current data release has no known errors of sex or strain assignment.
-
-Data Status and Use. The data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
-This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
-
-Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/specifics.rtf b/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/specifics.rtf
deleted file mode 100644
index 2400c03..0000000
--- a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Exon Level
diff --git a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/summary.rtf b/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/summary.rtf
deleted file mode 100644
index 41311b7..0000000
--- a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This is a final error-checked release of an amygdala gene expression data set generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from the NIH NIAAA. The basolateral complex of the amygdala of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/tissue.rtf b/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/tissue.rtf
deleted file mode 100644
index ea556c7..0000000
--- a/general/datasets/INIA_Amg_BLA_Ex_RMA_1110/tissue.rtf
+++ /dev/null
@@ -1,12 +0,0 @@
-Dissection Protocol
-
-
- - Animals were sacrificed by cervical dislocation and brains were immediately dissected from the head and stored in RNAlater (www.ambion.com) for 2 to 3 days at 4 deg C in a refrigerator.
- - Brains were placed with ventral side up on a cutting surface and a partial coronal cut was made with a surgical blade at a level that corresponds approximately to the -2.5 mm behind the stereotaxic Bregma point (this cut is just a little rostral from the pontine fibres when viewed from the ventral side).
- - Brains were placed in a coronal matrix (egg-style slicer) and a 2-mm thick coronal slab was taken just rostral to the initial cut.
- - The 2-mm thick slab was placed on a clean glass slide and the hypothalamus was cut out and placed in a tube on dry ice.
- - To dissect the BLA, the temporal lobes were detached by placing a scalpel in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then cut out and placed in a tube on dry ice.
- - Tissue from two mice (right and left sides) and from the same strain and sex (an usually the same litter) were pooled. The only exceptions are BLA samples from strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue was obtained from only one animal per array).
-
-
-
diff --git a/general/datasets/INIA_BXD_LivDNAm_1119/experiment-design.rtf b/general/datasets/INIA_BXD_LivDNAm_1119/experiment-design.rtf
deleted file mode 100644
index 5c63e07..0000000
--- a/general/datasets/INIA_BXD_LivDNAm_1119/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Aging
diff --git a/general/datasets/INIA_BXD_LivDNAm_1119/platform.rtf b/general/datasets/INIA_BXD_LivDNAm_1119/platform.rtf
deleted file mode 100644
index 01ea9ea..0000000
--- a/general/datasets/INIA_BXD_LivDNAm_1119/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Pan-Mammalian DNAm Infinium array; this is a custom array
diff --git a/general/datasets/INIA_BXD_LivDNAm_1119/processing.rtf b/general/datasets/INIA_BXD_LivDNAm_1119/processing.rtf
deleted file mode 100644
index 5dc0f7f..0000000
--- a/general/datasets/INIA_BXD_LivDNAm_1119/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Beta-values after normalization
diff --git a/general/datasets/INIA_BXD_LivDNAm_1119/specifics.rtf b/general/datasets/INIA_BXD_LivDNAm_1119/specifics.rtf
deleted file mode 100644
index 925cbbe..0000000
--- a/general/datasets/INIA_BXD_LivDNAm_1119/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Normalization Sesame
\ No newline at end of file
diff --git a/general/datasets/INIA_BXD_LivDNAm_1119/summary.rtf b/general/datasets/INIA_BXD_LivDNAm_1119/summary.rtf
deleted file mode 100644
index 0961144..0000000
--- a/general/datasets/INIA_BXD_LivDNAm_1119/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DNA from liver tissue profiled on the Illumina Pan-Mammalian Infinium microarray. This array was designed and developed by Steve Horvath at UCLA. Array hybridization, initial data QC, and normalization done at UCLA.
diff --git a/general/datasets/INIA_BXD_LivDNAminfi_1020/experiment-design.rtf b/general/datasets/INIA_BXD_LivDNAminfi_1020/experiment-design.rtf
deleted file mode 100644
index 5c63e07..0000000
--- a/general/datasets/INIA_BXD_LivDNAminfi_1020/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Aging
diff --git a/general/datasets/INIA_BXD_LivDNAminfi_1020/platform.rtf b/general/datasets/INIA_BXD_LivDNAminfi_1020/platform.rtf
deleted file mode 100644
index 01ea9ea..0000000
--- a/general/datasets/INIA_BXD_LivDNAminfi_1020/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Pan-Mammalian DNAm Infinium array; this is a custom array
diff --git a/general/datasets/INIA_BXD_LivDNAminfi_1020/processing.rtf b/general/datasets/INIA_BXD_LivDNAminfi_1020/processing.rtf
deleted file mode 100644
index 5dc0f7f..0000000
--- a/general/datasets/INIA_BXD_LivDNAminfi_1020/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Beta-values after normalization
diff --git a/general/datasets/INIA_BXD_LivDNAminfi_1020/specifics.rtf b/general/datasets/INIA_BXD_LivDNAminfi_1020/specifics.rtf
deleted file mode 100644
index 717d006..0000000
--- a/general/datasets/INIA_BXD_LivDNAminfi_1020/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Normalization minfi
\ No newline at end of file
diff --git a/general/datasets/INIA_BXD_LivDNAminfi_1020/summary.rtf b/general/datasets/INIA_BXD_LivDNAminfi_1020/summary.rtf
deleted file mode 100644
index 0961144..0000000
--- a/general/datasets/INIA_BXD_LivDNAminfi_1020/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DNA from liver tissue profiled on the Illumina Pan-Mammalian Infinium microarray. This array was designed and developed by Steve Horvath at UCLA. Array hybridization, initial data QC, and normalization done at UCLA.
diff --git a/general/datasets/INIA_Hyp_PCA_0813/acknowledgment.rtf b/general/datasets/INIA_Hyp_PCA_0813/acknowledgment.rtf
deleted file mode 100644
index 2c3f2bd..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/INIA_Hyp_PCA_0813/cases.rtf b/general/datasets/INIA_Hyp_PCA_0813/cases.rtf
deleted file mode 100644
index f19e9c8..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813/cases.rtf
+++ /dev/null
@@ -1,916 +0,0 @@
-The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
-
-
-
-
-
-
-
-
- | Index |
- Array ID |
- Tissue |
- Strain |
- Age |
- Sex |
- Date sacrifice |
- Time sacrifice |
-
-
- | 1 |
- R6854HYP |
- Hyp |
- C57BL/6J |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 2 |
- R6862HYP |
- Hyp |
- C57BL/6J |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 3 |
- R6852HYP |
- Hyp |
- D2B6F1 |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 4 |
- R6860HYP |
- Hyp |
- D2B6F1 |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 5 |
- R6864HYP |
- Hyp |
- DBA/2J |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 6 |
- R6866HYP |
- Hyp |
- DBA/2J |
- 68 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 7 |
- R6858HYP |
- Hyp |
- B6D2F1 |
- 69 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 8 |
- R6856HYP |
- Hyp |
- B6D2F1 |
- 69 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 9 |
- R6800HYP |
- Hyp |
- BXD1 |
- 71 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 10 |
- R6796HYP |
- Hyp |
- BXD1 |
- 85 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 11 |
- R6788HYP |
- Hyp |
- BXD11 |
- 87 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 12 |
- R6786HYP |
- Hyp |
- BXD11 |
- 76 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 13 |
- R6806HYP |
- Hyp |
- BXD12 |
- 77 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 14 |
- R6812HYP |
- Hyp |
- BXD14 |
- 81 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 15 |
- R6804HYP |
- Hyp |
- BXD24 |
- 85 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 16 |
- R6792HYP |
- Hyp |
- BXD27 |
- 75 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 17 |
- R6790HYP |
- Hyp |
- BXD27 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 18 |
- R6798HYP |
- Hyp |
- BXD29 |
- 71 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 19 |
- R6794HYP |
- Hyp |
- BXD29 |
- 71 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 20 |
- R6816HYP |
- Hyp |
- BXD31 |
- 74 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 21 |
- R6802HYP |
- Hyp |
- BXD31 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 22 |
- R6916HYP |
- Hyp |
- BXD32 |
- 81 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 23 |
- R6846HYP |
- Hyp |
- BXD32 |
- 81 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 24 |
- R6822HYP |
- Hyp |
- BXD34 |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 25 |
- R6808HYP |
- Hyp |
- BXD34 |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 26 |
- R6814HYP |
- Hyp |
- BXD39 |
- 79 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 27 |
- R6848HYP |
- Hyp |
- BXD40 |
- 85 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 28 |
- R6850HYP |
- Hyp |
- BXD40 |
- 85 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 29 |
- R6810HYP |
- Hyp |
- BXD42 |
- 87 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 30 |
- R6758HYP |
- Hyp |
- BXD43 |
- 81 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 31 |
- R6746HYP |
- Hyp |
- BXD44 |
- 83 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 32 |
- R6750HYP |
- Hyp |
- BXD44 |
- 83 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 33 |
- R6764HYP |
- Hyp |
- BXD45 |
- 77 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 34 |
- R6762HYP |
- Hyp |
- BXD45 |
- 77 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 35 |
- R6880HYP |
- Hyp |
- BXD48 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 36 |
- R6882HYP |
- Hyp |
- BXD48 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 37 |
- R6748HYP |
- Hyp |
- BXD49 |
- 84 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 38 |
- R6890HYP |
- Hyp |
- BXD50 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 39 |
- R6892HYP |
- Hyp |
- BXD50 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 40 |
- R6918HYP |
- Hyp |
- BXD56 |
- 84 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 41 |
- R6894HYP |
- Hyp |
- BXD56 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 42 |
- R6770HYP |
- Hyp |
- BXD60 |
- 70 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 43 |
- R6772HYP |
- Hyp |
- BXD60 |
- 70 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 44 |
- R6836HYP |
- Hyp |
- BXD62 |
- 83 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 45 |
- R6844HYP |
- Hyp |
- BXD62 |
- 83 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 46 |
- R6888HYP |
- Hyp |
- BXD63 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 47 |
- R6878HYP |
- Hyp |
- BXD65 |
- 84 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 48 |
- R6874HYP |
- Hyp |
- BXD65 |
- 84 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 49 |
- R6930HYP |
- Hyp |
- BXD68 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 50 |
- R6932HYP |
- Hyp |
- BXD68 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 51 |
- R6776HYP |
- Hyp |
- BXD69 |
- 69 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 52 |
- R6774HYP |
- Hyp |
- BXD69 |
- 80 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 53 |
- R6926HYP |
- Hyp |
- BXD70 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 54 |
- R6922HYP |
- Hyp |
- BXD70 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 55 |
- R6870HYP |
- Hyp |
- BXD71 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 56 |
- R6872HYP |
- Hyp |
- BXD71 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 57 |
- R6778HYP |
- Hyp |
- BXD73 |
- 83 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 58 |
- R6780HYP |
- Hyp |
- BXD73 |
- 83 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 59 |
- R6838HYP |
- Hyp |
- BXD75 |
- 76 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 60 |
- R6830HYP |
- Hyp |
- BXD75 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 61 |
- R6934HYP |
- Hyp |
- BXD79 |
- 87 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 62 |
- R6782HYP |
- Hyp |
- BXD80 |
- 73 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 63 |
- R6784HYP |
- Hyp |
- BXD80 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 64 |
- R6914HYP |
- Hyp |
- BXD83 |
- 81 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 65 |
- R6912HYP |
- Hyp |
- BXD83 |
- 81 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 66 |
- R6834HYP |
- Hyp |
- BXD84 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 67 |
- R6938HYP |
- Hyp |
- BXD85 |
- 74 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 68 |
- R6940HYP |
- Hyp |
- BXD85 |
- 74 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 69 |
- R6910HYP |
- Hyp |
- BXD87 |
- 83 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 70 |
- R6908HYP |
- Hyp |
- BXD87 |
- 83 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 71 |
- R6896HYP |
- Hyp |
- BXD89 |
- 82 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 72 |
- R6898HYP |
- Hyp |
- BXD89 |
- 82 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 73 |
- R6904HYP |
- Hyp |
- BXD90 |
- 82 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 74 |
- R6906HYP |
- Hyp |
- BXD90 |
- 82 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 75 |
- R6924HYP |
- Hyp |
- BXD92 |
- 86 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 76 |
- R6928HYP |
- Hyp |
- BXD92 |
- 89 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 77 |
- R6920HYP |
- Hyp |
- BXD95 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 78 |
- R6868HYP |
- Hyp |
- BXD95 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 79 |
- R6900HYP |
- Hyp |
- BXD97 |
- 71 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 80 |
- R6902HYP |
- Hyp |
- BXD97 |
- 71 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 81 |
- R6876HYP |
- Hyp |
- BXD99 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 82 |
- R6884HYP |
- Hyp |
- BXD99 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 83 |
- R6840HYP |
- Hyp |
- BXD100 |
- 83 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 84 |
- R6832HYP |
- Hyp |
- BXD100 |
- 83 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 85 |
- R6944HYP |
- Hyp |
- BXD101 |
- 89 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 86 |
- R6942HYP |
- Hyp |
- BXD101 |
- 89 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 87 |
- R6756HYP |
- Hyp |
- BXD102 |
- 88 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 88 |
- R6768HYP |
- Hyp |
- BXD103 |
- 78 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 89 |
- R6766HYP |
- Hyp |
- BXD103 |
- 78 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
-
- |
-
-
-
-
-
diff --git a/general/datasets/INIA_Hyp_PCA_0813/experiment-design.rtf b/general/datasets/INIA_Hyp_PCA_0813/experiment-design.rtf
deleted file mode 100644
index 443af4a..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813/experiment-design.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Hypothalamus was dissected from adult male and female mice and process for expression analysis.
-
-RNA isolation
-Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
-
-This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/INIA_Hyp_PCA_0813/platform.rtf b/general/datasets/INIA_Hyp_PCA_0813/platform.rtf
deleted file mode 100644
index aba2206..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/INIA_Hyp_PCA_0813/processing.rtf b/general/datasets/INIA_Hyp_PCA_0813/processing.rtf
deleted file mode 100644
index b3e8689..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/INIA_Hyp_PCA_0813/summary.rtf b/general/datasets/INIA_Hyp_PCA_0813/summary.rtf
deleted file mode 100644
index 02671d5..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813/summary.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
-
-Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
-
-Dissection protocol:
-
-
- - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
- - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
- - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
- - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
- - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
- - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
-
-
-The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/INIA_Hyp_PCA_0813_v2/acknowledgment.rtf b/general/datasets/INIA_Hyp_PCA_0813_v2/acknowledgment.rtf
deleted file mode 100644
index 2c3f2bd..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813_v2/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/INIA_Hyp_PCA_0813_v2/cases.rtf b/general/datasets/INIA_Hyp_PCA_0813_v2/cases.rtf
deleted file mode 100644
index f19e9c8..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813_v2/cases.rtf
+++ /dev/null
@@ -1,916 +0,0 @@
-The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
-
-
-
-
-
-
-
-
- | Index |
- Array ID |
- Tissue |
- Strain |
- Age |
- Sex |
- Date sacrifice |
- Time sacrifice |
-
-
- | 1 |
- R6854HYP |
- Hyp |
- C57BL/6J |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 2 |
- R6862HYP |
- Hyp |
- C57BL/6J |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 3 |
- R6852HYP |
- Hyp |
- D2B6F1 |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 4 |
- R6860HYP |
- Hyp |
- D2B6F1 |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 5 |
- R6864HYP |
- Hyp |
- DBA/2J |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 6 |
- R6866HYP |
- Hyp |
- DBA/2J |
- 68 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 7 |
- R6858HYP |
- Hyp |
- B6D2F1 |
- 69 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 8 |
- R6856HYP |
- Hyp |
- B6D2F1 |
- 69 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 9 |
- R6800HYP |
- Hyp |
- BXD1 |
- 71 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 10 |
- R6796HYP |
- Hyp |
- BXD1 |
- 85 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 11 |
- R6788HYP |
- Hyp |
- BXD11 |
- 87 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 12 |
- R6786HYP |
- Hyp |
- BXD11 |
- 76 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 13 |
- R6806HYP |
- Hyp |
- BXD12 |
- 77 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 14 |
- R6812HYP |
- Hyp |
- BXD14 |
- 81 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 15 |
- R6804HYP |
- Hyp |
- BXD24 |
- 85 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 16 |
- R6792HYP |
- Hyp |
- BXD27 |
- 75 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 17 |
- R6790HYP |
- Hyp |
- BXD27 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 18 |
- R6798HYP |
- Hyp |
- BXD29 |
- 71 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 19 |
- R6794HYP |
- Hyp |
- BXD29 |
- 71 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 20 |
- R6816HYP |
- Hyp |
- BXD31 |
- 74 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 21 |
- R6802HYP |
- Hyp |
- BXD31 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 22 |
- R6916HYP |
- Hyp |
- BXD32 |
- 81 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 23 |
- R6846HYP |
- Hyp |
- BXD32 |
- 81 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 24 |
- R6822HYP |
- Hyp |
- BXD34 |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 25 |
- R6808HYP |
- Hyp |
- BXD34 |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 26 |
- R6814HYP |
- Hyp |
- BXD39 |
- 79 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 27 |
- R6848HYP |
- Hyp |
- BXD40 |
- 85 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 28 |
- R6850HYP |
- Hyp |
- BXD40 |
- 85 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 29 |
- R6810HYP |
- Hyp |
- BXD42 |
- 87 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 30 |
- R6758HYP |
- Hyp |
- BXD43 |
- 81 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 31 |
- R6746HYP |
- Hyp |
- BXD44 |
- 83 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 32 |
- R6750HYP |
- Hyp |
- BXD44 |
- 83 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 33 |
- R6764HYP |
- Hyp |
- BXD45 |
- 77 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 34 |
- R6762HYP |
- Hyp |
- BXD45 |
- 77 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 35 |
- R6880HYP |
- Hyp |
- BXD48 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 36 |
- R6882HYP |
- Hyp |
- BXD48 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 37 |
- R6748HYP |
- Hyp |
- BXD49 |
- 84 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 38 |
- R6890HYP |
- Hyp |
- BXD50 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 39 |
- R6892HYP |
- Hyp |
- BXD50 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 40 |
- R6918HYP |
- Hyp |
- BXD56 |
- 84 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 41 |
- R6894HYP |
- Hyp |
- BXD56 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 42 |
- R6770HYP |
- Hyp |
- BXD60 |
- 70 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 43 |
- R6772HYP |
- Hyp |
- BXD60 |
- 70 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 44 |
- R6836HYP |
- Hyp |
- BXD62 |
- 83 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 45 |
- R6844HYP |
- Hyp |
- BXD62 |
- 83 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 46 |
- R6888HYP |
- Hyp |
- BXD63 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 47 |
- R6878HYP |
- Hyp |
- BXD65 |
- 84 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 48 |
- R6874HYP |
- Hyp |
- BXD65 |
- 84 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 49 |
- R6930HYP |
- Hyp |
- BXD68 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 50 |
- R6932HYP |
- Hyp |
- BXD68 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 51 |
- R6776HYP |
- Hyp |
- BXD69 |
- 69 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 52 |
- R6774HYP |
- Hyp |
- BXD69 |
- 80 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 53 |
- R6926HYP |
- Hyp |
- BXD70 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 54 |
- R6922HYP |
- Hyp |
- BXD70 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 55 |
- R6870HYP |
- Hyp |
- BXD71 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 56 |
- R6872HYP |
- Hyp |
- BXD71 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 57 |
- R6778HYP |
- Hyp |
- BXD73 |
- 83 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 58 |
- R6780HYP |
- Hyp |
- BXD73 |
- 83 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 59 |
- R6838HYP |
- Hyp |
- BXD75 |
- 76 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 60 |
- R6830HYP |
- Hyp |
- BXD75 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 61 |
- R6934HYP |
- Hyp |
- BXD79 |
- 87 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 62 |
- R6782HYP |
- Hyp |
- BXD80 |
- 73 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 63 |
- R6784HYP |
- Hyp |
- BXD80 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 64 |
- R6914HYP |
- Hyp |
- BXD83 |
- 81 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 65 |
- R6912HYP |
- Hyp |
- BXD83 |
- 81 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 66 |
- R6834HYP |
- Hyp |
- BXD84 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 67 |
- R6938HYP |
- Hyp |
- BXD85 |
- 74 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 68 |
- R6940HYP |
- Hyp |
- BXD85 |
- 74 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 69 |
- R6910HYP |
- Hyp |
- BXD87 |
- 83 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 70 |
- R6908HYP |
- Hyp |
- BXD87 |
- 83 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 71 |
- R6896HYP |
- Hyp |
- BXD89 |
- 82 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 72 |
- R6898HYP |
- Hyp |
- BXD89 |
- 82 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 73 |
- R6904HYP |
- Hyp |
- BXD90 |
- 82 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 74 |
- R6906HYP |
- Hyp |
- BXD90 |
- 82 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 75 |
- R6924HYP |
- Hyp |
- BXD92 |
- 86 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 76 |
- R6928HYP |
- Hyp |
- BXD92 |
- 89 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 77 |
- R6920HYP |
- Hyp |
- BXD95 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 78 |
- R6868HYP |
- Hyp |
- BXD95 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 79 |
- R6900HYP |
- Hyp |
- BXD97 |
- 71 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 80 |
- R6902HYP |
- Hyp |
- BXD97 |
- 71 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 81 |
- R6876HYP |
- Hyp |
- BXD99 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 82 |
- R6884HYP |
- Hyp |
- BXD99 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 83 |
- R6840HYP |
- Hyp |
- BXD100 |
- 83 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 84 |
- R6832HYP |
- Hyp |
- BXD100 |
- 83 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 85 |
- R6944HYP |
- Hyp |
- BXD101 |
- 89 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 86 |
- R6942HYP |
- Hyp |
- BXD101 |
- 89 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 87 |
- R6756HYP |
- Hyp |
- BXD102 |
- 88 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 88 |
- R6768HYP |
- Hyp |
- BXD103 |
- 78 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 89 |
- R6766HYP |
- Hyp |
- BXD103 |
- 78 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
-
- |
-
-
-
-
-
diff --git a/general/datasets/INIA_Hyp_PCA_0813_v2/experiment-design.rtf b/general/datasets/INIA_Hyp_PCA_0813_v2/experiment-design.rtf
deleted file mode 100644
index 443af4a..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813_v2/experiment-design.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Hypothalamus was dissected from adult male and female mice and process for expression analysis.
-
-RNA isolation
-Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
-
-This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/INIA_Hyp_PCA_0813_v2/platform.rtf b/general/datasets/INIA_Hyp_PCA_0813_v2/platform.rtf
deleted file mode 100644
index aba2206..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813_v2/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/INIA_Hyp_PCA_0813_v2/processing.rtf b/general/datasets/INIA_Hyp_PCA_0813_v2/processing.rtf
deleted file mode 100644
index b3e8689..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813_v2/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/INIA_Hyp_PCA_0813_v2/summary.rtf b/general/datasets/INIA_Hyp_PCA_0813_v2/summary.rtf
deleted file mode 100644
index 02671d5..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813_v2/summary.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
-
-Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
-
-Dissection protocol:
-
-
- - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
- - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
- - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
- - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
- - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
- - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
-
-
-The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/INIA_Hyp_PCA_0813_v3/acknowledgment.rtf b/general/datasets/INIA_Hyp_PCA_0813_v3/acknowledgment.rtf
deleted file mode 100644
index 2c3f2bd..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813_v3/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/INIA_Hyp_PCA_0813_v3/cases.rtf b/general/datasets/INIA_Hyp_PCA_0813_v3/cases.rtf
deleted file mode 100644
index f19e9c8..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813_v3/cases.rtf
+++ /dev/null
@@ -1,916 +0,0 @@
-The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
-
-
-
-
-
-
-
-
- | Index |
- Array ID |
- Tissue |
- Strain |
- Age |
- Sex |
- Date sacrifice |
- Time sacrifice |
-
-
- | 1 |
- R6854HYP |
- Hyp |
- C57BL/6J |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 2 |
- R6862HYP |
- Hyp |
- C57BL/6J |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 3 |
- R6852HYP |
- Hyp |
- D2B6F1 |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 4 |
- R6860HYP |
- Hyp |
- D2B6F1 |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 5 |
- R6864HYP |
- Hyp |
- DBA/2J |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 6 |
- R6866HYP |
- Hyp |
- DBA/2J |
- 68 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 7 |
- R6858HYP |
- Hyp |
- B6D2F1 |
- 69 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 8 |
- R6856HYP |
- Hyp |
- B6D2F1 |
- 69 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 9 |
- R6800HYP |
- Hyp |
- BXD1 |
- 71 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 10 |
- R6796HYP |
- Hyp |
- BXD1 |
- 85 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 11 |
- R6788HYP |
- Hyp |
- BXD11 |
- 87 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 12 |
- R6786HYP |
- Hyp |
- BXD11 |
- 76 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 13 |
- R6806HYP |
- Hyp |
- BXD12 |
- 77 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 14 |
- R6812HYP |
- Hyp |
- BXD14 |
- 81 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 15 |
- R6804HYP |
- Hyp |
- BXD24 |
- 85 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 16 |
- R6792HYP |
- Hyp |
- BXD27 |
- 75 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 17 |
- R6790HYP |
- Hyp |
- BXD27 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 18 |
- R6798HYP |
- Hyp |
- BXD29 |
- 71 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 19 |
- R6794HYP |
- Hyp |
- BXD29 |
- 71 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 20 |
- R6816HYP |
- Hyp |
- BXD31 |
- 74 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 21 |
- R6802HYP |
- Hyp |
- BXD31 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 22 |
- R6916HYP |
- Hyp |
- BXD32 |
- 81 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 23 |
- R6846HYP |
- Hyp |
- BXD32 |
- 81 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 24 |
- R6822HYP |
- Hyp |
- BXD34 |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 25 |
- R6808HYP |
- Hyp |
- BXD34 |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 26 |
- R6814HYP |
- Hyp |
- BXD39 |
- 79 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 27 |
- R6848HYP |
- Hyp |
- BXD40 |
- 85 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 28 |
- R6850HYP |
- Hyp |
- BXD40 |
- 85 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 29 |
- R6810HYP |
- Hyp |
- BXD42 |
- 87 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 30 |
- R6758HYP |
- Hyp |
- BXD43 |
- 81 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 31 |
- R6746HYP |
- Hyp |
- BXD44 |
- 83 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 32 |
- R6750HYP |
- Hyp |
- BXD44 |
- 83 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 33 |
- R6764HYP |
- Hyp |
- BXD45 |
- 77 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 34 |
- R6762HYP |
- Hyp |
- BXD45 |
- 77 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 35 |
- R6880HYP |
- Hyp |
- BXD48 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 36 |
- R6882HYP |
- Hyp |
- BXD48 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 37 |
- R6748HYP |
- Hyp |
- BXD49 |
- 84 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 38 |
- R6890HYP |
- Hyp |
- BXD50 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 39 |
- R6892HYP |
- Hyp |
- BXD50 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 40 |
- R6918HYP |
- Hyp |
- BXD56 |
- 84 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 41 |
- R6894HYP |
- Hyp |
- BXD56 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 42 |
- R6770HYP |
- Hyp |
- BXD60 |
- 70 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 43 |
- R6772HYP |
- Hyp |
- BXD60 |
- 70 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 44 |
- R6836HYP |
- Hyp |
- BXD62 |
- 83 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 45 |
- R6844HYP |
- Hyp |
- BXD62 |
- 83 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 46 |
- R6888HYP |
- Hyp |
- BXD63 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 47 |
- R6878HYP |
- Hyp |
- BXD65 |
- 84 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 48 |
- R6874HYP |
- Hyp |
- BXD65 |
- 84 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 49 |
- R6930HYP |
- Hyp |
- BXD68 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 50 |
- R6932HYP |
- Hyp |
- BXD68 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 51 |
- R6776HYP |
- Hyp |
- BXD69 |
- 69 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 52 |
- R6774HYP |
- Hyp |
- BXD69 |
- 80 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 53 |
- R6926HYP |
- Hyp |
- BXD70 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 54 |
- R6922HYP |
- Hyp |
- BXD70 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 55 |
- R6870HYP |
- Hyp |
- BXD71 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 56 |
- R6872HYP |
- Hyp |
- BXD71 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 57 |
- R6778HYP |
- Hyp |
- BXD73 |
- 83 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 58 |
- R6780HYP |
- Hyp |
- BXD73 |
- 83 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 59 |
- R6838HYP |
- Hyp |
- BXD75 |
- 76 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 60 |
- R6830HYP |
- Hyp |
- BXD75 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 61 |
- R6934HYP |
- Hyp |
- BXD79 |
- 87 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 62 |
- R6782HYP |
- Hyp |
- BXD80 |
- 73 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 63 |
- R6784HYP |
- Hyp |
- BXD80 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 64 |
- R6914HYP |
- Hyp |
- BXD83 |
- 81 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 65 |
- R6912HYP |
- Hyp |
- BXD83 |
- 81 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 66 |
- R6834HYP |
- Hyp |
- BXD84 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 67 |
- R6938HYP |
- Hyp |
- BXD85 |
- 74 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 68 |
- R6940HYP |
- Hyp |
- BXD85 |
- 74 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 69 |
- R6910HYP |
- Hyp |
- BXD87 |
- 83 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 70 |
- R6908HYP |
- Hyp |
- BXD87 |
- 83 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 71 |
- R6896HYP |
- Hyp |
- BXD89 |
- 82 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 72 |
- R6898HYP |
- Hyp |
- BXD89 |
- 82 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 73 |
- R6904HYP |
- Hyp |
- BXD90 |
- 82 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 74 |
- R6906HYP |
- Hyp |
- BXD90 |
- 82 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 75 |
- R6924HYP |
- Hyp |
- BXD92 |
- 86 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 76 |
- R6928HYP |
- Hyp |
- BXD92 |
- 89 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 77 |
- R6920HYP |
- Hyp |
- BXD95 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 78 |
- R6868HYP |
- Hyp |
- BXD95 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 79 |
- R6900HYP |
- Hyp |
- BXD97 |
- 71 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 80 |
- R6902HYP |
- Hyp |
- BXD97 |
- 71 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 81 |
- R6876HYP |
- Hyp |
- BXD99 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 82 |
- R6884HYP |
- Hyp |
- BXD99 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 83 |
- R6840HYP |
- Hyp |
- BXD100 |
- 83 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 84 |
- R6832HYP |
- Hyp |
- BXD100 |
- 83 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 85 |
- R6944HYP |
- Hyp |
- BXD101 |
- 89 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 86 |
- R6942HYP |
- Hyp |
- BXD101 |
- 89 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 87 |
- R6756HYP |
- Hyp |
- BXD102 |
- 88 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 88 |
- R6768HYP |
- Hyp |
- BXD103 |
- 78 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 89 |
- R6766HYP |
- Hyp |
- BXD103 |
- 78 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
-
- |
-
-
-
-
-
diff --git a/general/datasets/INIA_Hyp_PCA_0813_v3/experiment-design.rtf b/general/datasets/INIA_Hyp_PCA_0813_v3/experiment-design.rtf
deleted file mode 100644
index 443af4a..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813_v3/experiment-design.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Hypothalamus was dissected from adult male and female mice and process for expression analysis.
-
-RNA isolation
-Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
-
-This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/INIA_Hyp_PCA_0813_v3/platform.rtf b/general/datasets/INIA_Hyp_PCA_0813_v3/platform.rtf
deleted file mode 100644
index aba2206..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813_v3/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/INIA_Hyp_PCA_0813_v3/processing.rtf b/general/datasets/INIA_Hyp_PCA_0813_v3/processing.rtf
deleted file mode 100644
index b3e8689..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813_v3/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/INIA_Hyp_PCA_0813_v3/summary.rtf b/general/datasets/INIA_Hyp_PCA_0813_v3/summary.rtf
deleted file mode 100644
index 02671d5..0000000
--- a/general/datasets/INIA_Hyp_PCA_0813_v3/summary.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
-
-Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
-
-Dissection protocol:
-
-
- - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
- - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
- - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
- - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
- - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
- - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
-
-
-The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/INIA_Hyp_RMA_Ex-1110/acknowledgment.rtf b/general/datasets/INIA_Hyp_RMA_Ex-1110/acknowledgment.rtf
new file mode 100644
index 0000000..2c3f2bd
--- /dev/null
+++ b/general/datasets/INIA_Hyp_RMA_Ex-1110/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/INIA_Hyp_RMA_Ex-1110/cases.rtf b/general/datasets/INIA_Hyp_RMA_Ex-1110/cases.rtf
new file mode 100644
index 0000000..f19e9c8
--- /dev/null
+++ b/general/datasets/INIA_Hyp_RMA_Ex-1110/cases.rtf
@@ -0,0 +1,916 @@
+The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6854HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6862HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6852HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6860HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6864HYP |
+ Hyp |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6866HYP |
+ Hyp |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6858HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6856HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6800HYP |
+ Hyp |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6796HYP |
+ Hyp |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6788HYP |
+ Hyp |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6786HYP |
+ Hyp |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6806HYP |
+ Hyp |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 14 |
+ R6812HYP |
+ Hyp |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 15 |
+ R6804HYP |
+ Hyp |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6792HYP |
+ Hyp |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 17 |
+ R6790HYP |
+ Hyp |
+ BXD27 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 18 |
+ R6798HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 19 |
+ R6794HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 20 |
+ R6816HYP |
+ Hyp |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 21 |
+ R6802HYP |
+ Hyp |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 22 |
+ R6916HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 23 |
+ R6846HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6822HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 25 |
+ R6808HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 26 |
+ R6814HYP |
+ Hyp |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 27 |
+ R6848HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 28 |
+ R6850HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 29 |
+ R6810HYP |
+ Hyp |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 30 |
+ R6758HYP |
+ Hyp |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 31 |
+ R6746HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 32 |
+ R6750HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 33 |
+ R6764HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 34 |
+ R6762HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 35 |
+ R6880HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 36 |
+ R6882HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 37 |
+ R6748HYP |
+ Hyp |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 38 |
+ R6890HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 39 |
+ R6892HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 40 |
+ R6918HYP |
+ Hyp |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 41 |
+ R6894HYP |
+ Hyp |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 42 |
+ R6770HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 43 |
+ R6772HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 44 |
+ R6836HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 45 |
+ R6844HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 46 |
+ R6888HYP |
+ Hyp |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 47 |
+ R6878HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 48 |
+ R6874HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 49 |
+ R6930HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6932HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6776HYP |
+ Hyp |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 52 |
+ R6774HYP |
+ Hyp |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 53 |
+ R6926HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 54 |
+ R6922HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 55 |
+ R6870HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6872HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6778HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 58 |
+ R6780HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 59 |
+ R6838HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 60 |
+ R6830HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 61 |
+ R6934HYP |
+ Hyp |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 62 |
+ R6782HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6784HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 64 |
+ R6914HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 65 |
+ R6912HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 66 |
+ R6834HYP |
+ Hyp |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6938HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6940HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6910HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6908HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6896HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6898HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6904HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 74 |
+ R6906HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 75 |
+ R6924HYP |
+ Hyp |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6928HYP |
+ Hyp |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6920HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6868HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 79 |
+ R6900HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 80 |
+ R6902HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 81 |
+ R6876HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 82 |
+ R6884HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 83 |
+ R6840HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 84 |
+ R6832HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 85 |
+ R6944HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 86 |
+ R6942HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 87 |
+ R6756HYP |
+ Hyp |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 88 |
+ R6768HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 89 |
+ R6766HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/INIA_Hyp_RMA_Ex-1110/experiment-design.rtf b/general/datasets/INIA_Hyp_RMA_Ex-1110/experiment-design.rtf
new file mode 100644
index 0000000..443af4a
--- /dev/null
+++ b/general/datasets/INIA_Hyp_RMA_Ex-1110/experiment-design.rtf
@@ -0,0 +1,6 @@
+Hypothalamus was dissected from adult male and female mice and process for expression analysis.
+
+RNA isolation
+Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/INIA_Hyp_RMA_Ex-1110/platform.rtf b/general/datasets/INIA_Hyp_RMA_Ex-1110/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/INIA_Hyp_RMA_Ex-1110/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/INIA_Hyp_RMA_Ex-1110/processing.rtf b/general/datasets/INIA_Hyp_RMA_Ex-1110/processing.rtf
new file mode 100644
index 0000000..b3e8689
--- /dev/null
+++ b/general/datasets/INIA_Hyp_RMA_Ex-1110/processing.rtf
@@ -0,0 +1 @@
+Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/INIA_Hyp_RMA_Ex-1110/summary.rtf b/general/datasets/INIA_Hyp_RMA_Ex-1110/summary.rtf
new file mode 100644
index 0000000..02671d5
--- /dev/null
+++ b/general/datasets/INIA_Hyp_RMA_Ex-1110/summary.rtf
@@ -0,0 +1,16 @@
+These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
+
+Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
+
+Dissection protocol:
+
+
+ - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
+ - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
+ - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
+ - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
+ - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
+ - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
+
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/INIA_Hyp_RMA_Ex_1110/acknowledgment.rtf b/general/datasets/INIA_Hyp_RMA_Ex_1110/acknowledgment.rtf
deleted file mode 100644
index 2c3f2bd..0000000
--- a/general/datasets/INIA_Hyp_RMA_Ex_1110/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/INIA_Hyp_RMA_Ex_1110/cases.rtf b/general/datasets/INIA_Hyp_RMA_Ex_1110/cases.rtf
deleted file mode 100644
index f19e9c8..0000000
--- a/general/datasets/INIA_Hyp_RMA_Ex_1110/cases.rtf
+++ /dev/null
@@ -1,916 +0,0 @@
-The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
-
-
-
-
-
-
-
-
- | Index |
- Array ID |
- Tissue |
- Strain |
- Age |
- Sex |
- Date sacrifice |
- Time sacrifice |
-
-
- | 1 |
- R6854HYP |
- Hyp |
- C57BL/6J |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 2 |
- R6862HYP |
- Hyp |
- C57BL/6J |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 3 |
- R6852HYP |
- Hyp |
- D2B6F1 |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 4 |
- R6860HYP |
- Hyp |
- D2B6F1 |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 5 |
- R6864HYP |
- Hyp |
- DBA/2J |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 6 |
- R6866HYP |
- Hyp |
- DBA/2J |
- 68 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 7 |
- R6858HYP |
- Hyp |
- B6D2F1 |
- 69 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 8 |
- R6856HYP |
- Hyp |
- B6D2F1 |
- 69 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 9 |
- R6800HYP |
- Hyp |
- BXD1 |
- 71 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 10 |
- R6796HYP |
- Hyp |
- BXD1 |
- 85 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 11 |
- R6788HYP |
- Hyp |
- BXD11 |
- 87 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 12 |
- R6786HYP |
- Hyp |
- BXD11 |
- 76 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 13 |
- R6806HYP |
- Hyp |
- BXD12 |
- 77 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 14 |
- R6812HYP |
- Hyp |
- BXD14 |
- 81 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 15 |
- R6804HYP |
- Hyp |
- BXD24 |
- 85 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 16 |
- R6792HYP |
- Hyp |
- BXD27 |
- 75 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 17 |
- R6790HYP |
- Hyp |
- BXD27 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 18 |
- R6798HYP |
- Hyp |
- BXD29 |
- 71 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 19 |
- R6794HYP |
- Hyp |
- BXD29 |
- 71 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 20 |
- R6816HYP |
- Hyp |
- BXD31 |
- 74 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 21 |
- R6802HYP |
- Hyp |
- BXD31 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 22 |
- R6916HYP |
- Hyp |
- BXD32 |
- 81 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 23 |
- R6846HYP |
- Hyp |
- BXD32 |
- 81 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 24 |
- R6822HYP |
- Hyp |
- BXD34 |
- 77 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 25 |
- R6808HYP |
- Hyp |
- BXD34 |
- 77 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 26 |
- R6814HYP |
- Hyp |
- BXD39 |
- 79 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 27 |
- R6848HYP |
- Hyp |
- BXD40 |
- 85 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 28 |
- R6850HYP |
- Hyp |
- BXD40 |
- 85 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 29 |
- R6810HYP |
- Hyp |
- BXD42 |
- 87 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 30 |
- R6758HYP |
- Hyp |
- BXD43 |
- 81 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 31 |
- R6746HYP |
- Hyp |
- BXD44 |
- 83 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 32 |
- R6750HYP |
- Hyp |
- BXD44 |
- 83 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 33 |
- R6764HYP |
- Hyp |
- BXD45 |
- 77 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 34 |
- R6762HYP |
- Hyp |
- BXD45 |
- 77 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 35 |
- R6880HYP |
- Hyp |
- BXD48 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 36 |
- R6882HYP |
- Hyp |
- BXD48 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 37 |
- R6748HYP |
- Hyp |
- BXD49 |
- 84 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 38 |
- R6890HYP |
- Hyp |
- BXD50 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 39 |
- R6892HYP |
- Hyp |
- BXD50 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 40 |
- R6918HYP |
- Hyp |
- BXD56 |
- 84 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 41 |
- R6894HYP |
- Hyp |
- BXD56 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 42 |
- R6770HYP |
- Hyp |
- BXD60 |
- 70 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 43 |
- R6772HYP |
- Hyp |
- BXD60 |
- 70 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 44 |
- R6836HYP |
- Hyp |
- BXD62 |
- 83 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 45 |
- R6844HYP |
- Hyp |
- BXD62 |
- 83 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 46 |
- R6888HYP |
- Hyp |
- BXD63 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 47 |
- R6878HYP |
- Hyp |
- BXD65 |
- 84 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 48 |
- R6874HYP |
- Hyp |
- BXD65 |
- 84 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 49 |
- R6930HYP |
- Hyp |
- BXD68 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 50 |
- R6932HYP |
- Hyp |
- BXD68 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 51 |
- R6776HYP |
- Hyp |
- BXD69 |
- 69 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 52 |
- R6774HYP |
- Hyp |
- BXD69 |
- 80 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 53 |
- R6926HYP |
- Hyp |
- BXD70 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 54 |
- R6922HYP |
- Hyp |
- BXD70 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 55 |
- R6870HYP |
- Hyp |
- BXD71 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 56 |
- R6872HYP |
- Hyp |
- BXD71 |
- 76 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 57 |
- R6778HYP |
- Hyp |
- BXD73 |
- 83 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 58 |
- R6780HYP |
- Hyp |
- BXD73 |
- 83 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 59 |
- R6838HYP |
- Hyp |
- BXD75 |
- 76 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 60 |
- R6830HYP |
- Hyp |
- BXD75 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 61 |
- R6934HYP |
- Hyp |
- BXD79 |
- 87 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 62 |
- R6782HYP |
- Hyp |
- BXD80 |
- 73 |
- F |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 63 |
- R6784HYP |
- Hyp |
- BXD80 |
- 73 |
- M |
- 8/17/10 |
- 1:15 PM to 5 PM |
-
-
- | 64 |
- R6914HYP |
- Hyp |
- BXD83 |
- 81 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 65 |
- R6912HYP |
- Hyp |
- BXD83 |
- 81 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 66 |
- R6834HYP |
- Hyp |
- BXD84 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 67 |
- R6938HYP |
- Hyp |
- BXD85 |
- 74 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 68 |
- R6940HYP |
- Hyp |
- BXD85 |
- 74 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 69 |
- R6910HYP |
- Hyp |
- BXD87 |
- 83 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 70 |
- R6908HYP |
- Hyp |
- BXD87 |
- 83 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 71 |
- R6896HYP |
- Hyp |
- BXD89 |
- 82 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 72 |
- R6898HYP |
- Hyp |
- BXD89 |
- 82 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 73 |
- R6904HYP |
- Hyp |
- BXD90 |
- 82 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 74 |
- R6906HYP |
- Hyp |
- BXD90 |
- 82 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 75 |
- R6924HYP |
- Hyp |
- BXD92 |
- 86 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 76 |
- R6928HYP |
- Hyp |
- BXD92 |
- 89 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 77 |
- R6920HYP |
- Hyp |
- BXD95 |
- 76 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 78 |
- R6868HYP |
- Hyp |
- BXD95 |
- 76 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 79 |
- R6900HYP |
- Hyp |
- BXD97 |
- 71 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 80 |
- R6902HYP |
- Hyp |
- BXD97 |
- 71 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 81 |
- R6876HYP |
- Hyp |
- BXD99 |
- 77 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 82 |
- R6884HYP |
- Hyp |
- BXD99 |
- 77 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 83 |
- R6840HYP |
- Hyp |
- BXD100 |
- 83 |
- F |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 84 |
- R6832HYP |
- Hyp |
- BXD100 |
- 83 |
- M |
- 8/18/10 |
- 8:45AM to 12:30 PM |
-
-
- | 85 |
- R6944HYP |
- Hyp |
- BXD101 |
- 89 |
- F |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 86 |
- R6942HYP |
- Hyp |
- BXD101 |
- 89 |
- M |
- 8/18/10 |
- 1 PM to 6:45 PM |
-
-
- | 87 |
- R6756HYP |
- Hyp |
- BXD102 |
- 88 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 88 |
- R6768HYP |
- Hyp |
- BXD103 |
- 78 |
- F |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
- | 89 |
- R6766HYP |
- Hyp |
- BXD103 |
- 78 |
- M |
- 8/17/10 |
- 9:30 AM to 12:30AM |
-
-
-
- |
-
-
-
-
-
diff --git a/general/datasets/INIA_Hyp_RMA_Ex_1110/experiment-design.rtf b/general/datasets/INIA_Hyp_RMA_Ex_1110/experiment-design.rtf
deleted file mode 100644
index 443af4a..0000000
--- a/general/datasets/INIA_Hyp_RMA_Ex_1110/experiment-design.rtf
+++ /dev/null
@@ -1,6 +0,0 @@
-Hypothalamus was dissected from adult male and female mice and process for expression analysis.
-
-RNA isolation
-Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
-
-This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/INIA_Hyp_RMA_Ex_1110/platform.rtf b/general/datasets/INIA_Hyp_RMA_Ex_1110/platform.rtf
deleted file mode 100644
index aba2206..0000000
--- a/general/datasets/INIA_Hyp_RMA_Ex_1110/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/INIA_Hyp_RMA_Ex_1110/processing.rtf b/general/datasets/INIA_Hyp_RMA_Ex_1110/processing.rtf
deleted file mode 100644
index b3e8689..0000000
--- a/general/datasets/INIA_Hyp_RMA_Ex_1110/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/INIA_Hyp_RMA_Ex_1110/summary.rtf b/general/datasets/INIA_Hyp_RMA_Ex_1110/summary.rtf
deleted file mode 100644
index 02671d5..0000000
--- a/general/datasets/INIA_Hyp_RMA_Ex_1110/summary.rtf
+++ /dev/null
@@ -1,16 +0,0 @@
-These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
-
-Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
-
-Dissection protocol:
-
-
- - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
- - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
- - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
- - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
- - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
- - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
-
-
-The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/INIA_LCMB_1215/acknowledgment.rtf b/general/datasets/INIA_LCMB_1215/acknowledgment.rtf
deleted file mode 100644
index 8b7d4ad..0000000
--- a/general/datasets/INIA_LCMB_1215/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Thanks to NIH NIAAA and funding support was provided by INIA grants U01AA013499 and U01AA06662.
diff --git a/general/datasets/INIA_LCMB_1215/cases.rtf b/general/datasets/INIA_LCMB_1215/cases.rtf
deleted file mode 100644
index 4d95e2a..0000000
--- a/general/datasets/INIA_LCMB_1215/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Male C57BL/6J and DBA/2J mice (10 weeks old upon arrival) were purchased from the Jackson Laboratory and assigned to either baseline untreated control (BAS), the air control (AIR), or CIE group. Mice were individually housed with free access to food (Harland Teklad, Madison, WI) and water throughout all phases of the experiments. Body weights were recorded weekly during ethanol-drinking weeks or daily during chronic intermittent ethanol (CIE) or air exposure (detailed below). Mice were housed in a temperature- and humidity-controlled an- imal facility under a reversed 12-h light/dark cycle (lights on at 0200 h). Mice were not food- or water-deprived at any time during the study. All procedures were approved by the Institutional Ani- mal Care and Use Committee at the Medical University of South Carolina (MUSC). Brain tissue was removed at MUSC and shipped to UTHSC for laser capture microdissection (LCM).
diff --git a/general/datasets/INIA_LCMB_1215/platform.rtf b/general/datasets/INIA_LCMB_1215/platform.rtf
deleted file mode 100644
index 25cb790..0000000
--- a/general/datasets/INIA_LCMB_1215/platform.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
-(Updated Dec 9, 2015 by AC and RW)
-
-Annotation data for transcripts and genes were downloaded from ENSEMBL by Arthur Centeno, December 2015. We downloaded the entire transcript database at http://useast.ensembl.org/Mus_musculus/Info/Index.
-
-The positions of transcripts and genes on the mouse assembly are version GRCm38.p4 (mm10 equivalent). However, we converted all chromosome coordinates to the mm9 assembly to be consistent with all other GN1 data sets. However, for some sequences, mostly on Chr Y and the mitochondrial genome, the values are mm10 equivalent (we had no corresponding mm9 values).
-
-We also extracted sequence data corresponding to the transcripts whenever these data were available. However in some cases we do not have sequence data at all.
diff --git a/general/datasets/INIA_LCMB_1215/processing.rtf b/general/datasets/INIA_LCMB_1215/processing.rtf
deleted file mode 100644
index f04ab87..0000000
--- a/general/datasets/INIA_LCMB_1215/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-RNA from tissue trapped in the CapSure LCM caps was extracted using the PicoPure RNA isolation kit (Life Technologies) according to the manufacturer's instructions (RNA was eluted from provided capture columns in 13.5-mL nuclease-free water). RNA quality was analyzed using a Bioanalyzer (Model 100, Agilent, Foster City, CA). Samples with an associated RNA integrity number (RIN) greater than 6 were subsequently used for RNA sequencing.
-
-
-
-Poly-A enriched mRNA was sequenced on two platforms, ABI SOLID 550XL Wildfire (65 samples) and Ion Proton (39 samples). Read length was 50 nt for the SOLID system and the average read length for the Proton system was ~180 nt. Reads generated on the SOLID system were aligned to the mm10 reference genome using the LifeScope aligner, and BAM files were subsequently generated using custom scripts for third-party downstream analysis. For the Proton system, reads were also aligned to the mm10 (Ensemble GRCm38) reference genome using TopHat2. Settings for TopHat2 are as follows: “-p 15 -N 4 –read-gap-length 6 –read-edit-dist 8 –max-insertion-length 6 –max-deletion-length 6 –max-intron-length 300000 –b2-very-sensitive”. Alignments on both platforms were splice-aware. RSeQC-2.6.1 (RPKM_count.py) was used to generate count data based on mm10 GENECODE Basic transcript annotation (43,320 transcripts detected). We selected this annotation for greater reproducibility with existing microarray data sets and to simplify downstream analysis by limiting the number of transcript models for each gene. On average, 2.5 million and 7.8 million reads uniquely aligned to transcript models on the SOLID and Proton platforms, respectively. Data were further filtered to remove tran- scripts that had less than 1 count in 90% or more samples. After filtering, 24,597 transcripts representing 12,011 unique genes remained (Supplemental Table 1). The variance stabilizing trans- form (R package DESeq2, FitType 1⁄4 local) was applied to the count data, and transformed data were corrected by dividing by transcript length to generate log2 reads per kilobase gene model (RPK) values. The use of two different sequencing platforms was corrected using batch correction (ComBat, Supplemental Fig. 3). All data filtering, transformations, and batch correction were performed using custom R scripts. Batch-corrected and transformed log2 RPK and log2 count values are available in Supplemental Tables 2 and 3, and log2 RPK data are also available at GeneNetwork [http://www. genenetwork.org/webqtl/main.py?FormID1⁄4sharinginfo&GN_ AccessionId1⁄4772; Group 1⁄4 Chronic Intermittent Ethanol, Type 1⁄4 LCM Brain Regions mRNA, Data set 1⁄4 INIA LCM (11 Regions) CIE/AIR RNA-seq Transcript Level (Dec15)].
diff --git a/general/datasets/INIA_LCMB_1215/summary.rtf b/general/datasets/INIA_LCMB_1215/summary.rtf
deleted file mode 100644
index 45d122d..0000000
--- a/general/datasets/INIA_LCMB_1215/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is open. Please contact Dr. Megan K. Mulligan (mmulliga@uthsc.edu) or Dr. Robert W. Williams (rwilliams@uthsc.edu) if you need more information or low-level data access.
diff --git a/general/datasets/INIA_LCMB_1215/tissue.rtf b/general/datasets/INIA_LCMB_1215/tissue.rtf
deleted file mode 100644
index 6a51951..0000000
--- a/general/datasets/INIA_LCMB_1215/tissue.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Whole brain tissue was sectioned at 10 mm using a Leica cryostat and mounted in series with 6e8 sections per slide onto uncharged and uncoated glass slides. Mounted sections were dehydrated in 100% methanol (90 s), 70% ethanol (1 min), 95% ethanol (1 min), 100% ethanol (1 min 2), xylene (5 min). Slides were then allowed to air dry for 10 min under a fume hood.
-
-Series were created from distinct coronal sections (bregma po- sitions based on a C57BL/6J reference brain atlas) and individual regions were matched across section and harvested by LCM (Supplemental Fig. 2). Prelimbic (PrL) and infralimbic (ILC) cortex included a series spanning from bregma 1.98 to 1.54 mm. The accumbens core (NAc) and shell (NAs) series were collected from bregma 1.54 to 0.98 mm, and dorsolateral (DLS) and dorsomedial (DMS) striatum and bed nucleus stria terminalis (BST) were collected from bregma 0.38 to 0.10 mm. Basolateral (BLA) and central nucleus (CeA) of the amygdala series were collected from bregma 0.58 to 1.22 mm and hippocampus (CA1 and CA3) was collected from bregma 1.46 to 2.46 mm. Finally, the ventral tegmental area (VTA) and primary visual cortex (VCX) series were collected from bregma 3.28 to 3.80 mm.
-
-Arcturus XT (Life Technologies) was used to capture 13 brain areas. The infrared laser was then used to capture the tissue onto CapSure LCM caps (Life Technologies, laser spot power set to 70 mV with a duration of 25 msec).
diff --git a/general/datasets/INIA_LCM_1215/acknowledgment.rtf b/general/datasets/INIA_LCM_1215/acknowledgment.rtf
deleted file mode 100644
index 8b7d4ad..0000000
--- a/general/datasets/INIA_LCM_1215/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Thanks to NIH NIAAA and funding support was provided by INIA grants U01AA013499 and U01AA06662.
diff --git a/general/datasets/INIA_LCM_1215/cases.rtf b/general/datasets/INIA_LCM_1215/cases.rtf
deleted file mode 100644
index 4d95e2a..0000000
--- a/general/datasets/INIA_LCM_1215/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Male C57BL/6J and DBA/2J mice (10 weeks old upon arrival) were purchased from the Jackson Laboratory and assigned to either baseline untreated control (BAS), the air control (AIR), or CIE group. Mice were individually housed with free access to food (Harland Teklad, Madison, WI) and water throughout all phases of the experiments. Body weights were recorded weekly during ethanol-drinking weeks or daily during chronic intermittent ethanol (CIE) or air exposure (detailed below). Mice were housed in a temperature- and humidity-controlled an- imal facility under a reversed 12-h light/dark cycle (lights on at 0200 h). Mice were not food- or water-deprived at any time during the study. All procedures were approved by the Institutional Ani- mal Care and Use Committee at the Medical University of South Carolina (MUSC). Brain tissue was removed at MUSC and shipped to UTHSC for laser capture microdissection (LCM).
diff --git a/general/datasets/INIA_LCM_1215/platform.rtf b/general/datasets/INIA_LCM_1215/platform.rtf
deleted file mode 100644
index 25cb790..0000000
--- a/general/datasets/INIA_LCM_1215/platform.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
-(Updated Dec 9, 2015 by AC and RW)
-
-Annotation data for transcripts and genes were downloaded from ENSEMBL by Arthur Centeno, December 2015. We downloaded the entire transcript database at http://useast.ensembl.org/Mus_musculus/Info/Index.
-
-The positions of transcripts and genes on the mouse assembly are version GRCm38.p4 (mm10 equivalent). However, we converted all chromosome coordinates to the mm9 assembly to be consistent with all other GN1 data sets. However, for some sequences, mostly on Chr Y and the mitochondrial genome, the values are mm10 equivalent (we had no corresponding mm9 values).
-
-We also extracted sequence data corresponding to the transcripts whenever these data were available. However in some cases we do not have sequence data at all.
diff --git a/general/datasets/INIA_LCM_1215/processing.rtf b/general/datasets/INIA_LCM_1215/processing.rtf
deleted file mode 100644
index f04ab87..0000000
--- a/general/datasets/INIA_LCM_1215/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-RNA from tissue trapped in the CapSure LCM caps was extracted using the PicoPure RNA isolation kit (Life Technologies) according to the manufacturer's instructions (RNA was eluted from provided capture columns in 13.5-mL nuclease-free water). RNA quality was analyzed using a Bioanalyzer (Model 100, Agilent, Foster City, CA). Samples with an associated RNA integrity number (RIN) greater than 6 were subsequently used for RNA sequencing.
-
-
-
-Poly-A enriched mRNA was sequenced on two platforms, ABI SOLID 550XL Wildfire (65 samples) and Ion Proton (39 samples). Read length was 50 nt for the SOLID system and the average read length for the Proton system was ~180 nt. Reads generated on the SOLID system were aligned to the mm10 reference genome using the LifeScope aligner, and BAM files were subsequently generated using custom scripts for third-party downstream analysis. For the Proton system, reads were also aligned to the mm10 (Ensemble GRCm38) reference genome using TopHat2. Settings for TopHat2 are as follows: “-p 15 -N 4 –read-gap-length 6 –read-edit-dist 8 –max-insertion-length 6 –max-deletion-length 6 –max-intron-length 300000 –b2-very-sensitive”. Alignments on both platforms were splice-aware. RSeQC-2.6.1 (RPKM_count.py) was used to generate count data based on mm10 GENECODE Basic transcript annotation (43,320 transcripts detected). We selected this annotation for greater reproducibility with existing microarray data sets and to simplify downstream analysis by limiting the number of transcript models for each gene. On average, 2.5 million and 7.8 million reads uniquely aligned to transcript models on the SOLID and Proton platforms, respectively. Data were further filtered to remove tran- scripts that had less than 1 count in 90% or more samples. After filtering, 24,597 transcripts representing 12,011 unique genes remained (Supplemental Table 1). The variance stabilizing trans- form (R package DESeq2, FitType 1⁄4 local) was applied to the count data, and transformed data were corrected by dividing by transcript length to generate log2 reads per kilobase gene model (RPK) values. The use of two different sequencing platforms was corrected using batch correction (ComBat, Supplemental Fig. 3). All data filtering, transformations, and batch correction were performed using custom R scripts. Batch-corrected and transformed log2 RPK and log2 count values are available in Supplemental Tables 2 and 3, and log2 RPK data are also available at GeneNetwork [http://www. genenetwork.org/webqtl/main.py?FormID1⁄4sharinginfo&GN_ AccessionId1⁄4772; Group 1⁄4 Chronic Intermittent Ethanol, Type 1⁄4 LCM Brain Regions mRNA, Data set 1⁄4 INIA LCM (11 Regions) CIE/AIR RNA-seq Transcript Level (Dec15)].
diff --git a/general/datasets/INIA_LCM_1215/summary.rtf b/general/datasets/INIA_LCM_1215/summary.rtf
deleted file mode 100644
index 45d122d..0000000
--- a/general/datasets/INIA_LCM_1215/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is open. Please contact Dr. Megan K. Mulligan (mmulliga@uthsc.edu) or Dr. Robert W. Williams (rwilliams@uthsc.edu) if you need more information or low-level data access.
diff --git a/general/datasets/INIA_LCM_1215/tissue.rtf b/general/datasets/INIA_LCM_1215/tissue.rtf
deleted file mode 100644
index 6a51951..0000000
--- a/general/datasets/INIA_LCM_1215/tissue.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Whole brain tissue was sectioned at 10 mm using a Leica cryostat and mounted in series with 6e8 sections per slide onto uncharged and uncoated glass slides. Mounted sections were dehydrated in 100% methanol (90 s), 70% ethanol (1 min), 95% ethanol (1 min), 100% ethanol (1 min 2), xylene (5 min). Slides were then allowed to air dry for 10 min under a fume hood.
-
-Series were created from distinct coronal sections (bregma po- sitions based on a C57BL/6J reference brain atlas) and individual regions were matched across section and harvested by LCM (Supplemental Fig. 2). Prelimbic (PrL) and infralimbic (ILC) cortex included a series spanning from bregma 1.98 to 1.54 mm. The accumbens core (NAc) and shell (NAs) series were collected from bregma 1.54 to 0.98 mm, and dorsolateral (DLS) and dorsomedial (DMS) striatum and bed nucleus stria terminalis (BST) were collected from bregma 0.38 to 0.10 mm. Basolateral (BLA) and central nucleus (CeA) of the amygdala series were collected from bregma 0.58 to 1.22 mm and hippocampus (CA1 and CA3) was collected from bregma 1.46 to 2.46 mm. Finally, the ventral tegmental area (VTA) and primary visual cortex (VCX) series were collected from bregma 3.28 to 3.80 mm.
-
-Arcturus XT (Life Technologies) was used to capture 13 brain areas. The infrared laser was then used to capture the tissue onto CapSure LCM caps (Life Technologies, laser spot power set to 70 mV with a duration of 25 msec).
diff --git a/general/datasets/INIA_LCM_CAB_1215/acknowledgment.rtf b/general/datasets/INIA_LCM_CAB_1215/acknowledgment.rtf
deleted file mode 100644
index 8b7d4ad..0000000
--- a/general/datasets/INIA_LCM_CAB_1215/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Thanks to NIH NIAAA and funding support was provided by INIA grants U01AA013499 and U01AA06662.
diff --git a/general/datasets/INIA_LCM_CAB_1215/cases.rtf b/general/datasets/INIA_LCM_CAB_1215/cases.rtf
deleted file mode 100644
index 4d95e2a..0000000
--- a/general/datasets/INIA_LCM_CAB_1215/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Male C57BL/6J and DBA/2J mice (10 weeks old upon arrival) were purchased from the Jackson Laboratory and assigned to either baseline untreated control (BAS), the air control (AIR), or CIE group. Mice were individually housed with free access to food (Harland Teklad, Madison, WI) and water throughout all phases of the experiments. Body weights were recorded weekly during ethanol-drinking weeks or daily during chronic intermittent ethanol (CIE) or air exposure (detailed below). Mice were housed in a temperature- and humidity-controlled an- imal facility under a reversed 12-h light/dark cycle (lights on at 0200 h). Mice were not food- or water-deprived at any time during the study. All procedures were approved by the Institutional Ani- mal Care and Use Committee at the Medical University of South Carolina (MUSC). Brain tissue was removed at MUSC and shipped to UTHSC for laser capture microdissection (LCM).
diff --git a/general/datasets/INIA_LCM_CAB_1215/platform.rtf b/general/datasets/INIA_LCM_CAB_1215/platform.rtf
deleted file mode 100644
index 25cb790..0000000
--- a/general/datasets/INIA_LCM_CAB_1215/platform.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-
-
-
-
-(Updated Dec 9, 2015 by AC and RW)
-
-Annotation data for transcripts and genes were downloaded from ENSEMBL by Arthur Centeno, December 2015. We downloaded the entire transcript database at http://useast.ensembl.org/Mus_musculus/Info/Index.
-
-The positions of transcripts and genes on the mouse assembly are version GRCm38.p4 (mm10 equivalent). However, we converted all chromosome coordinates to the mm9 assembly to be consistent with all other GN1 data sets. However, for some sequences, mostly on Chr Y and the mitochondrial genome, the values are mm10 equivalent (we had no corresponding mm9 values).
-
-We also extracted sequence data corresponding to the transcripts whenever these data were available. However in some cases we do not have sequence data at all.
diff --git a/general/datasets/INIA_LCM_CAB_1215/processing.rtf b/general/datasets/INIA_LCM_CAB_1215/processing.rtf
deleted file mode 100644
index f04ab87..0000000
--- a/general/datasets/INIA_LCM_CAB_1215/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-RNA from tissue trapped in the CapSure LCM caps was extracted using the PicoPure RNA isolation kit (Life Technologies) according to the manufacturer's instructions (RNA was eluted from provided capture columns in 13.5-mL nuclease-free water). RNA quality was analyzed using a Bioanalyzer (Model 100, Agilent, Foster City, CA). Samples with an associated RNA integrity number (RIN) greater than 6 were subsequently used for RNA sequencing.
-
-
-
-Poly-A enriched mRNA was sequenced on two platforms, ABI SOLID 550XL Wildfire (65 samples) and Ion Proton (39 samples). Read length was 50 nt for the SOLID system and the average read length for the Proton system was ~180 nt. Reads generated on the SOLID system were aligned to the mm10 reference genome using the LifeScope aligner, and BAM files were subsequently generated using custom scripts for third-party downstream analysis. For the Proton system, reads were also aligned to the mm10 (Ensemble GRCm38) reference genome using TopHat2. Settings for TopHat2 are as follows: “-p 15 -N 4 –read-gap-length 6 –read-edit-dist 8 –max-insertion-length 6 –max-deletion-length 6 –max-intron-length 300000 –b2-very-sensitive”. Alignments on both platforms were splice-aware. RSeQC-2.6.1 (RPKM_count.py) was used to generate count data based on mm10 GENECODE Basic transcript annotation (43,320 transcripts detected). We selected this annotation for greater reproducibility with existing microarray data sets and to simplify downstream analysis by limiting the number of transcript models for each gene. On average, 2.5 million and 7.8 million reads uniquely aligned to transcript models on the SOLID and Proton platforms, respectively. Data were further filtered to remove tran- scripts that had less than 1 count in 90% or more samples. After filtering, 24,597 transcripts representing 12,011 unique genes remained (Supplemental Table 1). The variance stabilizing trans- form (R package DESeq2, FitType 1⁄4 local) was applied to the count data, and transformed data were corrected by dividing by transcript length to generate log2 reads per kilobase gene model (RPK) values. The use of two different sequencing platforms was corrected using batch correction (ComBat, Supplemental Fig. 3). All data filtering, transformations, and batch correction were performed using custom R scripts. Batch-corrected and transformed log2 RPK and log2 count values are available in Supplemental Tables 2 and 3, and log2 RPK data are also available at GeneNetwork [http://www. genenetwork.org/webqtl/main.py?FormID1⁄4sharinginfo&GN_ AccessionId1⁄4772; Group 1⁄4 Chronic Intermittent Ethanol, Type 1⁄4 LCM Brain Regions mRNA, Data set 1⁄4 INIA LCM (11 Regions) CIE/AIR RNA-seq Transcript Level (Dec15)].
diff --git a/general/datasets/INIA_LCM_CAB_1215/specifics.rtf b/general/datasets/INIA_LCM_CAB_1215/specifics.rtf
deleted file mode 100644
index 61a050f..0000000
--- a/general/datasets/INIA_LCM_CAB_1215/specifics.rtf
+++ /dev/null
@@ -1,17 +0,0 @@
-Published in Alcohol 2017:
-
-
-
-Alcohol. 2017 Feb;58:61-72. doi: 10.1016/j.alcohol.2016.09.001. Epub 2016 Oct 15.
-
-Genetic divergence in the transcriptional engram of chronic alcohol abuse: A laser-capture RNA-seq study of the mouse mesocorticolimbic system.
-
-Mulligan MK1, Mozhui K2, Pandey AK2, Smith ML3, Gong S2, Ingels J2, Miles MF3, Lopez MF4, Lu L2, Williams RW2.
-
-
-
-Abstract
-
-Genetic factors that influence the transition from initial drinking to dependence remain enigmatic. Recent studies have leveraged chronic intermittent ethanol (CIE) paradigms to measure changes in brain gene expression in a single strain at 0, 8, 72 h, and even 7 days following CIE. We extend these findings using LCM RNA-seq to profile expression in 11 brain regions in two inbred strains - C57BL/6J (B6) and DBA/2J (D2) - 72 h following multiple cycles of ethanol self-administration and CIE. Linear models identified differential expression based on treatment, region, strain, or interactions with treatment. Nearly 40% of genes showed a robust effect (FDR < 0.01) of region, and hippocampus CA1, cortex, bed nucleus stria terminalis, and nucleus accumbens core had the highest number of differentially expressed genes after treatment. Another 8% of differentially expressed genes demonstrated a robust effect of strain. As expected, based on similar studies in B6, treatment had a much smaller impact on expression; only 72 genes (p < 0.01) are modulated by treatment (independent of region or strain). Strikingly, many more genes (415) show a strain-specific and largely opposite response to treatment and are enriched in processes related to RNA metabolism, transcription factor activity, and mitochondrial function. Over 3 times as many changes in gene expression were detected in D2 compared to B6, and weighted gene co-expression network analysis (WGCNA) module comparison identified more modules enriched for treatment effects in D2. Substantial strain differences exist in the temporal pattern of transcriptional neuroadaptation to CIE, and these may drive individual differences in risk of addiction following excessive alcohol consumption.
-
-PMID:27894806; PMCID:PMC5450909; DOI:10.1016/j.alcohol.2016.09.001
diff --git a/general/datasets/INIA_LCM_CAB_1215/summary.rtf b/general/datasets/INIA_LCM_CAB_1215/summary.rtf
deleted file mode 100644
index 45d122d..0000000
--- a/general/datasets/INIA_LCM_CAB_1215/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is open. Please contact Dr. Megan K. Mulligan (mmulliga@uthsc.edu) or Dr. Robert W. Williams (rwilliams@uthsc.edu) if you need more information or low-level data access.
diff --git a/general/datasets/INIA_LCM_CAB_1215/tissue.rtf b/general/datasets/INIA_LCM_CAB_1215/tissue.rtf
deleted file mode 100644
index 6a51951..0000000
--- a/general/datasets/INIA_LCM_CAB_1215/tissue.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Whole brain tissue was sectioned at 10 mm using a Leica cryostat and mounted in series with 6e8 sections per slide onto uncharged and uncoated glass slides. Mounted sections were dehydrated in 100% methanol (90 s), 70% ethanol (1 min), 95% ethanol (1 min), 100% ethanol (1 min 2), xylene (5 min). Slides were then allowed to air dry for 10 min under a fume hood.
-
-Series were created from distinct coronal sections (bregma po- sitions based on a C57BL/6J reference brain atlas) and individual regions were matched across section and harvested by LCM (Supplemental Fig. 2). Prelimbic (PrL) and infralimbic (ILC) cortex included a series spanning from bregma 1.98 to 1.54 mm. The accumbens core (NAc) and shell (NAs) series were collected from bregma 1.54 to 0.98 mm, and dorsolateral (DLS) and dorsomedial (DMS) striatum and bed nucleus stria terminalis (BST) were collected from bregma 0.38 to 0.10 mm. Basolateral (BLA) and central nucleus (CeA) of the amygdala series were collected from bregma 0.58 to 1.22 mm and hippocampus (CA1 and CA3) was collected from bregma 1.46 to 2.46 mm. Finally, the ventral tegmental area (VTA) and primary visual cortex (VCX) series were collected from bregma 3.28 to 3.80 mm.
-
-Arcturus XT (Life Technologies) was used to capture 13 brain areas. The infrared laser was then used to capture the tissue onto CapSure LCM caps (Life Technologies, laser spot power set to 70 mV with a duration of 25 msec).
diff --git a/general/datasets/INIA_PG_RMA_0612/acknowledgment.rtf b/general/datasets/INIA_PG_RMA_0612/acknowledgment.rtf
deleted file mode 100644
index f8bf764..0000000
--- a/general/datasets/INIA_PG_RMA_0612/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NIAAA U01 support to RWW.
diff --git a/general/datasets/INIA_PG_RMA_0612/cases.rtf b/general/datasets/INIA_PG_RMA_0612/cases.rtf
deleted file mode 100644
index faf8ab0..0000000
--- a/general/datasets/INIA_PG_RMA_0612/cases.rtf
+++ /dev/null
@@ -1,840 +0,0 @@
-Young adult mice raised in specific pathogen-free vivarium at UTHSC.
-
-ERROR CHECKING by Mozhui, Centeno and Roy: The changes have been applied in GeneNetwork (GN389 - Pituitary) as follow:
-
-SampleId - New Strain Assignment
-R7087P (was BXD101) = BXD100
-R7138P_RW170 (was BXD85) = BXD95
-R7156P (was C57BL/6J) = B6D2F1
-R7141P = BXD65
-
-
-
-
-
-
-
-
-
-
- | Index |
- Sample ID |
- Strain |
- Tissue |
- Age |
- Sex |
-
-
- | 1 |
- R7128P |
- B6D2F1 |
- Pituitary |
- 69 |
- F |
-
-
- | 2 |
- R7156P |
- B6D2F1 |
- Pituitary |
- 92 |
- M |
-
-
- | 3 |
- R7129P |
- B6D2F1 |
- Pituitary |
- 69 |
- M |
-
-
- | 4 |
- R7134P |
- D2B6F1 |
- Pituitary |
- 77 |
- F |
-
-
- | 5 |
- R7133P |
- D2B6F1 |
- Pituitary |
- 77 |
- M |
-
-
- | 6 |
- R7160P |
- C57BL/6J |
- Pituitary |
- 92 |
- F |
-
-
- | 7 |
- R7127P |
- C57BL/6J |
- Pituitary |
- 77 |
- M |
-
-
- | 8 |
- R7126P |
- DBA/2J |
- Pituitary |
- 77 |
- F |
-
-
- | 9 |
- R7157P |
- DBA/2J |
- Pituitary |
- 75 |
- F |
-
-
- | 10 |
- R7125P |
- DBA/2J |
- Pituitary |
- 68 |
- M |
-
-
- | 11 |
- R7155P |
- DBA/2J |
- Pituitary |
- 75 |
- M |
-
-
- | 12 |
- R7058P |
- BXD1 |
- Pituitary |
- 72 |
- F |
-
-
- | 13 |
- R7063P |
- BXD1 |
- Pituitary |
- 86 |
- M |
-
-
- | 14 |
- R7079P |
- BXD11 |
- Pituitary |
- 87 |
- F |
-
-
- | 15 |
- R7069P |
- BXD11 |
- Pituitary |
- 76 |
- M |
-
-
- | 16 |
- R7051P |
- BXD12 |
- Pituitary |
- 78 |
- F |
-
-
- | 17 |
- R7061P |
- BXD12 |
- Pituitary |
- 78 |
- M |
-
-
- | 18 |
- R7064P |
- BXD14 |
- Pituitary |
- 81 |
- F |
-
-
- | 19 |
- R7066P |
- BXD14 |
- Pituitary |
- 81 |
- M |
-
-
- | 20 |
- R7052P |
- BXD24 |
- Pituitary |
- 86 |
- M |
-
-
- | 21 |
- R7076P |
- BXD27 |
- Pituitary |
- 76 |
- F |
-
-
- | 22 |
- R7071P |
- BXD27 |
- Pituitary |
- 73 |
- M |
-
-
- | 23 |
- R7059P |
- BXD29 |
- Pituitary |
- 72 |
- F |
-
-
- | 24 |
- R7060P |
- BXD29 |
- Pituitary |
- 72 |
- M |
-
-
- | 25 |
- R7055P |
- BXD31 |
- Pituitary |
- 74 |
- F |
-
-
- | 26 |
- R7062P |
- BXD31 |
- Pituitary |
- 74 |
- M |
-
-
- | 27 |
- R7143P |
- BXD32 |
- Pituitary |
- 81 |
- F |
-
-
- | 28 |
- R7135P |
- BXD32 |
- Pituitary |
- 81 |
- M |
-
-
- | 29 |
- R7119P |
- BXD34 |
- Pituitary |
- 77 |
- F |
-
-
- | 30 |
- R7054P |
- BXD34 |
- Pituitary |
- 77 |
- M |
-
-
- | 31 |
- R7049P |
- BXD39 |
- Pituitary |
- 79 |
- F |
-
-
- | 32 |
- R7065P |
- BXD39 |
- Pituitary |
- 79 |
- M |
-
-
- | 33 |
- R7130P |
- BXD40 |
- Pituitary |
- 85 |
- F |
-
-
- | 34 |
- R7132P |
- BXD40 |
- Pituitary |
- 85 |
- M |
-
-
- | 35 |
- R7056P |
- BXD42 |
- Pituitary |
- 87 |
- F |
-
-
- | 36 |
- R7044P |
- BXD42 |
- Pituitary |
- 87 |
- M |
-
-
- | 37 |
- R7043P |
- BXD43 |
- Pituitary |
- 81 |
- F |
-
-
- | 38 |
- R7047P |
- BXD43 |
- Pituitary |
- 81 |
- M |
-
-
- | 39 |
- R7091P |
- BXD44 |
- Pituitary |
- 83 |
- F |
-
-
- | 40 |
- R7050P |
- BXD44 |
- Pituitary |
- 83 |
- M |
-
-
- | 41 |
- R7077P |
- BXD45 |
- Pituitary |
- 77 |
- F |
-
-
- | 42 |
- R7078P |
- BXD45 |
- Pituitary |
- 77 |
- F |
-
-
- | 43 |
- R7042P |
- BXD45 |
- Pituitary |
- 77 |
- F |
-
-
- | 44 |
- R7092P |
- BXD48 |
- Pituitary |
- 76 |
- F |
-
-
- | 45 |
- R7093P |
- BXD48 |
- Pituitary |
- 76 |
- M |
-
-
- | 46 |
- R7045P |
- BXD49 |
- Pituitary |
- 84 |
- F |
-
-
- | 47 |
- R7094P |
- BXD49 |
- Pituitary |
- 84 |
- M |
-
-
- | 48 |
- R7095P |
- BXD50 |
- Pituitary |
- 77 |
- F |
-
-
- | 49 |
- R7096P |
- BXD50 |
- Pituitary |
- 77 |
- M |
-
-
- | 50 |
- R7142P |
- BXD56 |
- Pituitary |
- 84 |
- F |
-
-
- | 51 |
- R7097P |
- BXD56 |
- Pituitary |
- 77 |
- M |
-
-
- | 52 |
- R7080P |
- BXD60 |
- Pituitary |
- 70 |
- F |
-
-
- | 53 |
- R7141P_RW204 |
- BXD60 |
- Pituitary |
- 76 |
- M |
-
-
- | 54 |
- R7075P |
- BXD62 |
- Pituitary |
- 83 |
- F |
-
-
- | 55 |
- R7083P |
- BXD62 |
- Pituitary |
- 83 |
- M |
-
-
- | 56 |
- R7084P |
- BXD62 |
- Pituitary |
- 83 |
- M |
-
-
- | 57 |
- R7098P |
- BXD63 |
- Pituitary |
- 77 |
- F |
-
-
- | 58 |
- R7100P |
- BXD65 |
- Pituitary |
- 84 |
- M |
-
-
- | 59 |
- R7120P |
- BXD66 |
- Pituitary |
- 257 |
- M |
-
-
- | 60 |
- R7140P |
- BXD68 |
- Pituitary |
- 76 |
- F |
-
-
- | 61 |
- R7101P |
- BXD68 |
- Pituitary |
- 76 |
- M |
-
-
- | 62 |
- R7074P |
- BXD69 |
- Pituitary |
- 69 |
- F |
-
-
- | 63 |
- R7139P |
- BXD69 |
- Pituitary |
- 81 |
- M |
-
-
- | 64 |
- R7141P |
- BXD65 |
- Pituitary |
- 76 |
- F |
-
-
- | 65 |
- R7137P_RW112 |
- BXD70 |
- Pituitary |
- 76 |
- M |
-
-
- | 66 |
- R7124P |
- BXD71 |
- Pituitary |
- 76 |
- F |
-
-
- | 67 |
- R7123P |
- BXD71 |
- Pituitary |
- 76 |
- M |
-
-
- | 68 |
- R7068P |
- BXD73 |
- Pituitary |
- 83 |
- M |
-
-
- | 69 |
- R7118P |
- BXD74 |
- Pituitary |
- 69 |
- F |
-
-
- | 70 |
- R7117P |
- BXD74 |
- Pituitary |
- 69 |
- M |
-
-
- | 71 |
- R7082P |
- BXD75 |
- Pituitary |
- 76 |
- F |
-
-
- | 72 |
- R7048P |
- BXD75 |
- Pituitary |
- 76 |
- M |
-
-
- | 73 |
- R7122P |
- BXD77 |
- Pituitary |
- 223 |
- M |
-
-
- | 74 |
- R7103P |
- BXD79 |
- Pituitary |
- 86 |
- F |
-
-
- | 75 |
- R7104P |
- BXD79 |
- Pituitary |
- 86 |
- M |
-
-
- | 76 |
- R7073P |
- BXD80 |
- Pituitary |
- 73 |
- F |
-
-
- | 77 |
- R7070P |
- BXD80 |
- Pituitary |
- 73 |
- M |
-
-
- | 78 |
- R7139P_RW138 |
- BXD83 |
- Pituitary |
- 81 |
- F |
-
-
- | 79 |
- R7137P |
- BXD83 |
- Pituitary |
- 76 |
- M |
-
-
- | 80 |
- R7085P |
- BXD84 |
- Pituitary |
- 76 |
- F |
-
-
- | 81 |
- R7081P |
- BXD84 |
- Pituitary |
- 76 |
- M |
-
-
- | 82 |
- R7105P |
- BXD85 |
- Pituitary |
- 73 |
- M |
-
-
- | 83 |
- R7144P |
- BXD87 |
- Pituitary |
- 83 |
- F |
-
-
- | 84 |
- R7136P_RW196 |
- BXD87 |
- Pituitary |
- 83 |
- M |
-
-
- | 85 |
- R7106P |
- BXD89 |
- Pituitary |
- 82 |
- F |
-
-
- | 86 |
- R7107P |
- BXD89 |
- Pituitary |
- 82 |
- M |
-
-
- | 87 |
- R7108P |
- BXD90 |
- Pituitary |
- 82 |
- F |
-
-
- | 88 |
- R7109P |
- BXD90 |
- Pituitary |
- 82 |
- M |
-
-
- | 89 |
- R7138P_RW170 |
- BXD95 |
- Pituitary |
- 73 |
- F |
-
-
- | 90 |
- R7111P |
- BXD97 |
- Pituitary |
- 71 |
- F |
-
-
- | 91 |
- R7112P |
- BXD97 |
- Pituitary |
- 71 |
- M |
-
-
- | 92 |
- R7113P |
- BXD99 |
- Pituitary |
- 77 |
- F |
-
-
- | 93 |
- R7114P |
- BXD99 |
- Pituitary |
- 77 |
- M |
-
-
- | 94 |
- R7072P |
- BXD100 |
- Pituitary |
- 83 |
- F |
-
-
- | 95 |
- R7087P |
- BXD100 |
- Pituitary |
- 88 |
- F |
-
-
- | 96 |
- R7086P |
- BXD100 |
- Pituitary |
- 83 |
- M |
-
-
- | 97 |
- R7088P |
- BXD101 |
- Pituitary |
- 88 |
- M |
-
-
- | 98 |
- R7053P |
- BXD102 |
- Pituitary |
- 88 |
- F |
-
-
- | 99 |
- R7046P |
- BXD102 |
- Pituitary |
- 88 |
- M |
-
-
- | 100 |
- R7090P |
- BXD103 |
- Pituitary |
- 78 |
- F |
-
-
- | 101 |
- R7067P |
- BXD103 |
- Pituitary |
- 78 |
- M |
-
-
-
- |
-
-
-
diff --git a/general/datasets/INIA_PG_RMA_0612/experiment-design.rtf b/general/datasets/INIA_PG_RMA_0612/experiment-design.rtf
deleted file mode 100644
index 13175b5..0000000
--- a/general/datasets/INIA_PG_RMA_0612/experiment-design.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-Normative expression in the whole pituitary of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
-
-QUALITY CONTROL DATA
-
-
- - 737 probe sets with LRS of 46 or higher (LOD>10)
- - Highest LRS = 165.7
- - Review of top Mendelian transcripts consist with correct strain assignment
- - Final sex assignment is correct
-
diff --git a/general/datasets/INIA_PG_RMA_0612/platform.rtf b/general/datasets/INIA_PG_RMA_0612/platform.rtf
deleted file mode 100644
index 7057d48..0000000
--- a/general/datasets/INIA_PG_RMA_0612/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/INIA_PG_RMA_0612/processing.rtf b/general/datasets/INIA_PG_RMA_0612/processing.rtf
deleted file mode 100644
index 55aad2e..0000000
--- a/general/datasets/INIA_PG_RMA_0612/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/INIA_PG_RMA_0612/summary.rtf b/general/datasets/INIA_PG_RMA_0612/summary.rtf
deleted file mode 100644
index 14a715d..0000000
--- a/general/datasets/INIA_PG_RMA_0612/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Gene expression data for the whole pituitary across 52 strains of mice. Sex Balance: Sex of samples has been double-checked. As of July 2012, for 42 strains we have separate data for both males and females (usually one array each). Three strains (BXD45, 63, and 95) are only represented by female samples and two strains (BXD65 and BXD77) are only represented by male samples. Five other strains (BXD24, 66, 73, 85, 101) are may represent combined male and female samples. These unpublished data are apparently error-free based on a review and analysis of transcripts with Mendelian segregation patterns (as of July 20, 2012). The data set contains 751 eQTLs with LOD scores above 10 (LRS>46). Peak LRS of 165.9 for Record ID 10513604. Data for BXD70 are somewhat problematic (see 10444135 and 10467784), perhaps due to a bad array, strain assignment error, or residual heterozygozity. S Roy double-checked (July 22) and thinks that Sample R7141P is more likely to be BXD65.
-
-Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/INIA_PG_RMA_0612/tissue.rtf b/general/datasets/INIA_PG_RMA_0612/tissue.rtf
deleted file mode 100644
index 3977f1e..0000000
--- a/general/datasets/INIA_PG_RMA_0612/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Whole pituitary gland dissected by hand. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/INIA_PG_RMA_Ex_0612/acknowledgment.rtf b/general/datasets/INIA_PG_RMA_Ex_0612/acknowledgment.rtf
deleted file mode 100644
index f8bf764..0000000
--- a/general/datasets/INIA_PG_RMA_Ex_0612/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NIAAA U01 support to RWW.
diff --git a/general/datasets/INIA_PG_RMA_Ex_0612/cases.rtf b/general/datasets/INIA_PG_RMA_Ex_0612/cases.rtf
deleted file mode 100644
index faf8ab0..0000000
--- a/general/datasets/INIA_PG_RMA_Ex_0612/cases.rtf
+++ /dev/null
@@ -1,840 +0,0 @@
-Young adult mice raised in specific pathogen-free vivarium at UTHSC.
-
-ERROR CHECKING by Mozhui, Centeno and Roy: The changes have been applied in GeneNetwork (GN389 - Pituitary) as follow:
-
-SampleId - New Strain Assignment
-R7087P (was BXD101) = BXD100
-R7138P_RW170 (was BXD85) = BXD95
-R7156P (was C57BL/6J) = B6D2F1
-R7141P = BXD65
-
-
-
-
-
-
-
-
-
-
- | Index |
- Sample ID |
- Strain |
- Tissue |
- Age |
- Sex |
-
-
- | 1 |
- R7128P |
- B6D2F1 |
- Pituitary |
- 69 |
- F |
-
-
- | 2 |
- R7156P |
- B6D2F1 |
- Pituitary |
- 92 |
- M |
-
-
- | 3 |
- R7129P |
- B6D2F1 |
- Pituitary |
- 69 |
- M |
-
-
- | 4 |
- R7134P |
- D2B6F1 |
- Pituitary |
- 77 |
- F |
-
-
- | 5 |
- R7133P |
- D2B6F1 |
- Pituitary |
- 77 |
- M |
-
-
- | 6 |
- R7160P |
- C57BL/6J |
- Pituitary |
- 92 |
- F |
-
-
- | 7 |
- R7127P |
- C57BL/6J |
- Pituitary |
- 77 |
- M |
-
-
- | 8 |
- R7126P |
- DBA/2J |
- Pituitary |
- 77 |
- F |
-
-
- | 9 |
- R7157P |
- DBA/2J |
- Pituitary |
- 75 |
- F |
-
-
- | 10 |
- R7125P |
- DBA/2J |
- Pituitary |
- 68 |
- M |
-
-
- | 11 |
- R7155P |
- DBA/2J |
- Pituitary |
- 75 |
- M |
-
-
- | 12 |
- R7058P |
- BXD1 |
- Pituitary |
- 72 |
- F |
-
-
- | 13 |
- R7063P |
- BXD1 |
- Pituitary |
- 86 |
- M |
-
-
- | 14 |
- R7079P |
- BXD11 |
- Pituitary |
- 87 |
- F |
-
-
- | 15 |
- R7069P |
- BXD11 |
- Pituitary |
- 76 |
- M |
-
-
- | 16 |
- R7051P |
- BXD12 |
- Pituitary |
- 78 |
- F |
-
-
- | 17 |
- R7061P |
- BXD12 |
- Pituitary |
- 78 |
- M |
-
-
- | 18 |
- R7064P |
- BXD14 |
- Pituitary |
- 81 |
- F |
-
-
- | 19 |
- R7066P |
- BXD14 |
- Pituitary |
- 81 |
- M |
-
-
- | 20 |
- R7052P |
- BXD24 |
- Pituitary |
- 86 |
- M |
-
-
- | 21 |
- R7076P |
- BXD27 |
- Pituitary |
- 76 |
- F |
-
-
- | 22 |
- R7071P |
- BXD27 |
- Pituitary |
- 73 |
- M |
-
-
- | 23 |
- R7059P |
- BXD29 |
- Pituitary |
- 72 |
- F |
-
-
- | 24 |
- R7060P |
- BXD29 |
- Pituitary |
- 72 |
- M |
-
-
- | 25 |
- R7055P |
- BXD31 |
- Pituitary |
- 74 |
- F |
-
-
- | 26 |
- R7062P |
- BXD31 |
- Pituitary |
- 74 |
- M |
-
-
- | 27 |
- R7143P |
- BXD32 |
- Pituitary |
- 81 |
- F |
-
-
- | 28 |
- R7135P |
- BXD32 |
- Pituitary |
- 81 |
- M |
-
-
- | 29 |
- R7119P |
- BXD34 |
- Pituitary |
- 77 |
- F |
-
-
- | 30 |
- R7054P |
- BXD34 |
- Pituitary |
- 77 |
- M |
-
-
- | 31 |
- R7049P |
- BXD39 |
- Pituitary |
- 79 |
- F |
-
-
- | 32 |
- R7065P |
- BXD39 |
- Pituitary |
- 79 |
- M |
-
-
- | 33 |
- R7130P |
- BXD40 |
- Pituitary |
- 85 |
- F |
-
-
- | 34 |
- R7132P |
- BXD40 |
- Pituitary |
- 85 |
- M |
-
-
- | 35 |
- R7056P |
- BXD42 |
- Pituitary |
- 87 |
- F |
-
-
- | 36 |
- R7044P |
- BXD42 |
- Pituitary |
- 87 |
- M |
-
-
- | 37 |
- R7043P |
- BXD43 |
- Pituitary |
- 81 |
- F |
-
-
- | 38 |
- R7047P |
- BXD43 |
- Pituitary |
- 81 |
- M |
-
-
- | 39 |
- R7091P |
- BXD44 |
- Pituitary |
- 83 |
- F |
-
-
- | 40 |
- R7050P |
- BXD44 |
- Pituitary |
- 83 |
- M |
-
-
- | 41 |
- R7077P |
- BXD45 |
- Pituitary |
- 77 |
- F |
-
-
- | 42 |
- R7078P |
- BXD45 |
- Pituitary |
- 77 |
- F |
-
-
- | 43 |
- R7042P |
- BXD45 |
- Pituitary |
- 77 |
- F |
-
-
- | 44 |
- R7092P |
- BXD48 |
- Pituitary |
- 76 |
- F |
-
-
- | 45 |
- R7093P |
- BXD48 |
- Pituitary |
- 76 |
- M |
-
-
- | 46 |
- R7045P |
- BXD49 |
- Pituitary |
- 84 |
- F |
-
-
- | 47 |
- R7094P |
- BXD49 |
- Pituitary |
- 84 |
- M |
-
-
- | 48 |
- R7095P |
- BXD50 |
- Pituitary |
- 77 |
- F |
-
-
- | 49 |
- R7096P |
- BXD50 |
- Pituitary |
- 77 |
- M |
-
-
- | 50 |
- R7142P |
- BXD56 |
- Pituitary |
- 84 |
- F |
-
-
- | 51 |
- R7097P |
- BXD56 |
- Pituitary |
- 77 |
- M |
-
-
- | 52 |
- R7080P |
- BXD60 |
- Pituitary |
- 70 |
- F |
-
-
- | 53 |
- R7141P_RW204 |
- BXD60 |
- Pituitary |
- 76 |
- M |
-
-
- | 54 |
- R7075P |
- BXD62 |
- Pituitary |
- 83 |
- F |
-
-
- | 55 |
- R7083P |
- BXD62 |
- Pituitary |
- 83 |
- M |
-
-
- | 56 |
- R7084P |
- BXD62 |
- Pituitary |
- 83 |
- M |
-
-
- | 57 |
- R7098P |
- BXD63 |
- Pituitary |
- 77 |
- F |
-
-
- | 58 |
- R7100P |
- BXD65 |
- Pituitary |
- 84 |
- M |
-
-
- | 59 |
- R7120P |
- BXD66 |
- Pituitary |
- 257 |
- M |
-
-
- | 60 |
- R7140P |
- BXD68 |
- Pituitary |
- 76 |
- F |
-
-
- | 61 |
- R7101P |
- BXD68 |
- Pituitary |
- 76 |
- M |
-
-
- | 62 |
- R7074P |
- BXD69 |
- Pituitary |
- 69 |
- F |
-
-
- | 63 |
- R7139P |
- BXD69 |
- Pituitary |
- 81 |
- M |
-
-
- | 64 |
- R7141P |
- BXD65 |
- Pituitary |
- 76 |
- F |
-
-
- | 65 |
- R7137P_RW112 |
- BXD70 |
- Pituitary |
- 76 |
- M |
-
-
- | 66 |
- R7124P |
- BXD71 |
- Pituitary |
- 76 |
- F |
-
-
- | 67 |
- R7123P |
- BXD71 |
- Pituitary |
- 76 |
- M |
-
-
- | 68 |
- R7068P |
- BXD73 |
- Pituitary |
- 83 |
- M |
-
-
- | 69 |
- R7118P |
- BXD74 |
- Pituitary |
- 69 |
- F |
-
-
- | 70 |
- R7117P |
- BXD74 |
- Pituitary |
- 69 |
- M |
-
-
- | 71 |
- R7082P |
- BXD75 |
- Pituitary |
- 76 |
- F |
-
-
- | 72 |
- R7048P |
- BXD75 |
- Pituitary |
- 76 |
- M |
-
-
- | 73 |
- R7122P |
- BXD77 |
- Pituitary |
- 223 |
- M |
-
-
- | 74 |
- R7103P |
- BXD79 |
- Pituitary |
- 86 |
- F |
-
-
- | 75 |
- R7104P |
- BXD79 |
- Pituitary |
- 86 |
- M |
-
-
- | 76 |
- R7073P |
- BXD80 |
- Pituitary |
- 73 |
- F |
-
-
- | 77 |
- R7070P |
- BXD80 |
- Pituitary |
- 73 |
- M |
-
-
- | 78 |
- R7139P_RW138 |
- BXD83 |
- Pituitary |
- 81 |
- F |
-
-
- | 79 |
- R7137P |
- BXD83 |
- Pituitary |
- 76 |
- M |
-
-
- | 80 |
- R7085P |
- BXD84 |
- Pituitary |
- 76 |
- F |
-
-
- | 81 |
- R7081P |
- BXD84 |
- Pituitary |
- 76 |
- M |
-
-
- | 82 |
- R7105P |
- BXD85 |
- Pituitary |
- 73 |
- M |
-
-
- | 83 |
- R7144P |
- BXD87 |
- Pituitary |
- 83 |
- F |
-
-
- | 84 |
- R7136P_RW196 |
- BXD87 |
- Pituitary |
- 83 |
- M |
-
-
- | 85 |
- R7106P |
- BXD89 |
- Pituitary |
- 82 |
- F |
-
-
- | 86 |
- R7107P |
- BXD89 |
- Pituitary |
- 82 |
- M |
-
-
- | 87 |
- R7108P |
- BXD90 |
- Pituitary |
- 82 |
- F |
-
-
- | 88 |
- R7109P |
- BXD90 |
- Pituitary |
- 82 |
- M |
-
-
- | 89 |
- R7138P_RW170 |
- BXD95 |
- Pituitary |
- 73 |
- F |
-
-
- | 90 |
- R7111P |
- BXD97 |
- Pituitary |
- 71 |
- F |
-
-
- | 91 |
- R7112P |
- BXD97 |
- Pituitary |
- 71 |
- M |
-
-
- | 92 |
- R7113P |
- BXD99 |
- Pituitary |
- 77 |
- F |
-
-
- | 93 |
- R7114P |
- BXD99 |
- Pituitary |
- 77 |
- M |
-
-
- | 94 |
- R7072P |
- BXD100 |
- Pituitary |
- 83 |
- F |
-
-
- | 95 |
- R7087P |
- BXD100 |
- Pituitary |
- 88 |
- F |
-
-
- | 96 |
- R7086P |
- BXD100 |
- Pituitary |
- 83 |
- M |
-
-
- | 97 |
- R7088P |
- BXD101 |
- Pituitary |
- 88 |
- M |
-
-
- | 98 |
- R7053P |
- BXD102 |
- Pituitary |
- 88 |
- F |
-
-
- | 99 |
- R7046P |
- BXD102 |
- Pituitary |
- 88 |
- M |
-
-
- | 100 |
- R7090P |
- BXD103 |
- Pituitary |
- 78 |
- F |
-
-
- | 101 |
- R7067P |
- BXD103 |
- Pituitary |
- 78 |
- M |
-
-
-
- |
-
-
-
diff --git a/general/datasets/INIA_PG_RMA_Ex_0612/experiment-design.rtf b/general/datasets/INIA_PG_RMA_Ex_0612/experiment-design.rtf
deleted file mode 100644
index 13175b5..0000000
--- a/general/datasets/INIA_PG_RMA_Ex_0612/experiment-design.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-Normative expression in the whole pituitary of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
-
-QUALITY CONTROL DATA
-
-
- - 737 probe sets with LRS of 46 or higher (LOD>10)
- - Highest LRS = 165.7
- - Review of top Mendelian transcripts consist with correct strain assignment
- - Final sex assignment is correct
-
diff --git a/general/datasets/INIA_PG_RMA_Ex_0612/platform.rtf b/general/datasets/INIA_PG_RMA_Ex_0612/platform.rtf
deleted file mode 100644
index 7057d48..0000000
--- a/general/datasets/INIA_PG_RMA_Ex_0612/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/INIA_PG_RMA_Ex_0612/processing.rtf b/general/datasets/INIA_PG_RMA_Ex_0612/processing.rtf
deleted file mode 100644
index 55aad2e..0000000
--- a/general/datasets/INIA_PG_RMA_Ex_0612/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/INIA_PG_RMA_Ex_0612/summary.rtf b/general/datasets/INIA_PG_RMA_Ex_0612/summary.rtf
deleted file mode 100644
index 14a715d..0000000
--- a/general/datasets/INIA_PG_RMA_Ex_0612/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Gene expression data for the whole pituitary across 52 strains of mice. Sex Balance: Sex of samples has been double-checked. As of July 2012, for 42 strains we have separate data for both males and females (usually one array each). Three strains (BXD45, 63, and 95) are only represented by female samples and two strains (BXD65 and BXD77) are only represented by male samples. Five other strains (BXD24, 66, 73, 85, 101) are may represent combined male and female samples. These unpublished data are apparently error-free based on a review and analysis of transcripts with Mendelian segregation patterns (as of July 20, 2012). The data set contains 751 eQTLs with LOD scores above 10 (LRS>46). Peak LRS of 165.9 for Record ID 10513604. Data for BXD70 are somewhat problematic (see 10444135 and 10467784), perhaps due to a bad array, strain assignment error, or residual heterozygozity. S Roy double-checked (July 22) and thinks that Sample R7141P is more likely to be BXD65.
-
-Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/INIA_PG_RMA_Ex_0612/tissue.rtf b/general/datasets/INIA_PG_RMA_Ex_0612/tissue.rtf
deleted file mode 100644
index 3977f1e..0000000
--- a/general/datasets/INIA_PG_RMA_Ex_0612/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Whole pituitary gland dissected by hand. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/INIA_Pituitary_RMA_F_0612/acknowledgment.rtf b/general/datasets/INIA_Pituitary_RMA_F_0612/acknowledgment.rtf
deleted file mode 100644
index f8bf764..0000000
--- a/general/datasets/INIA_Pituitary_RMA_F_0612/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NIAAA U01 support to RWW.
diff --git a/general/datasets/INIA_Pituitary_RMA_F_0612/cases.rtf b/general/datasets/INIA_Pituitary_RMA_F_0612/cases.rtf
deleted file mode 100644
index faf8ab0..0000000
--- a/general/datasets/INIA_Pituitary_RMA_F_0612/cases.rtf
+++ /dev/null
@@ -1,840 +0,0 @@
-Young adult mice raised in specific pathogen-free vivarium at UTHSC.
-
-ERROR CHECKING by Mozhui, Centeno and Roy: The changes have been applied in GeneNetwork (GN389 - Pituitary) as follow:
-
-SampleId - New Strain Assignment
-R7087P (was BXD101) = BXD100
-R7138P_RW170 (was BXD85) = BXD95
-R7156P (was C57BL/6J) = B6D2F1
-R7141P = BXD65
-
-
-
-
-
-
-
-
-
-
- | Index |
- Sample ID |
- Strain |
- Tissue |
- Age |
- Sex |
-
-
- | 1 |
- R7128P |
- B6D2F1 |
- Pituitary |
- 69 |
- F |
-
-
- | 2 |
- R7156P |
- B6D2F1 |
- Pituitary |
- 92 |
- M |
-
-
- | 3 |
- R7129P |
- B6D2F1 |
- Pituitary |
- 69 |
- M |
-
-
- | 4 |
- R7134P |
- D2B6F1 |
- Pituitary |
- 77 |
- F |
-
-
- | 5 |
- R7133P |
- D2B6F1 |
- Pituitary |
- 77 |
- M |
-
-
- | 6 |
- R7160P |
- C57BL/6J |
- Pituitary |
- 92 |
- F |
-
-
- | 7 |
- R7127P |
- C57BL/6J |
- Pituitary |
- 77 |
- M |
-
-
- | 8 |
- R7126P |
- DBA/2J |
- Pituitary |
- 77 |
- F |
-
-
- | 9 |
- R7157P |
- DBA/2J |
- Pituitary |
- 75 |
- F |
-
-
- | 10 |
- R7125P |
- DBA/2J |
- Pituitary |
- 68 |
- M |
-
-
- | 11 |
- R7155P |
- DBA/2J |
- Pituitary |
- 75 |
- M |
-
-
- | 12 |
- R7058P |
- BXD1 |
- Pituitary |
- 72 |
- F |
-
-
- | 13 |
- R7063P |
- BXD1 |
- Pituitary |
- 86 |
- M |
-
-
- | 14 |
- R7079P |
- BXD11 |
- Pituitary |
- 87 |
- F |
-
-
- | 15 |
- R7069P |
- BXD11 |
- Pituitary |
- 76 |
- M |
-
-
- | 16 |
- R7051P |
- BXD12 |
- Pituitary |
- 78 |
- F |
-
-
- | 17 |
- R7061P |
- BXD12 |
- Pituitary |
- 78 |
- M |
-
-
- | 18 |
- R7064P |
- BXD14 |
- Pituitary |
- 81 |
- F |
-
-
- | 19 |
- R7066P |
- BXD14 |
- Pituitary |
- 81 |
- M |
-
-
- | 20 |
- R7052P |
- BXD24 |
- Pituitary |
- 86 |
- M |
-
-
- | 21 |
- R7076P |
- BXD27 |
- Pituitary |
- 76 |
- F |
-
-
- | 22 |
- R7071P |
- BXD27 |
- Pituitary |
- 73 |
- M |
-
-
- | 23 |
- R7059P |
- BXD29 |
- Pituitary |
- 72 |
- F |
-
-
- | 24 |
- R7060P |
- BXD29 |
- Pituitary |
- 72 |
- M |
-
-
- | 25 |
- R7055P |
- BXD31 |
- Pituitary |
- 74 |
- F |
-
-
- | 26 |
- R7062P |
- BXD31 |
- Pituitary |
- 74 |
- M |
-
-
- | 27 |
- R7143P |
- BXD32 |
- Pituitary |
- 81 |
- F |
-
-
- | 28 |
- R7135P |
- BXD32 |
- Pituitary |
- 81 |
- M |
-
-
- | 29 |
- R7119P |
- BXD34 |
- Pituitary |
- 77 |
- F |
-
-
- | 30 |
- R7054P |
- BXD34 |
- Pituitary |
- 77 |
- M |
-
-
- | 31 |
- R7049P |
- BXD39 |
- Pituitary |
- 79 |
- F |
-
-
- | 32 |
- R7065P |
- BXD39 |
- Pituitary |
- 79 |
- M |
-
-
- | 33 |
- R7130P |
- BXD40 |
- Pituitary |
- 85 |
- F |
-
-
- | 34 |
- R7132P |
- BXD40 |
- Pituitary |
- 85 |
- M |
-
-
- | 35 |
- R7056P |
- BXD42 |
- Pituitary |
- 87 |
- F |
-
-
- | 36 |
- R7044P |
- BXD42 |
- Pituitary |
- 87 |
- M |
-
-
- | 37 |
- R7043P |
- BXD43 |
- Pituitary |
- 81 |
- F |
-
-
- | 38 |
- R7047P |
- BXD43 |
- Pituitary |
- 81 |
- M |
-
-
- | 39 |
- R7091P |
- BXD44 |
- Pituitary |
- 83 |
- F |
-
-
- | 40 |
- R7050P |
- BXD44 |
- Pituitary |
- 83 |
- M |
-
-
- | 41 |
- R7077P |
- BXD45 |
- Pituitary |
- 77 |
- F |
-
-
- | 42 |
- R7078P |
- BXD45 |
- Pituitary |
- 77 |
- F |
-
-
- | 43 |
- R7042P |
- BXD45 |
- Pituitary |
- 77 |
- F |
-
-
- | 44 |
- R7092P |
- BXD48 |
- Pituitary |
- 76 |
- F |
-
-
- | 45 |
- R7093P |
- BXD48 |
- Pituitary |
- 76 |
- M |
-
-
- | 46 |
- R7045P |
- BXD49 |
- Pituitary |
- 84 |
- F |
-
-
- | 47 |
- R7094P |
- BXD49 |
- Pituitary |
- 84 |
- M |
-
-
- | 48 |
- R7095P |
- BXD50 |
- Pituitary |
- 77 |
- F |
-
-
- | 49 |
- R7096P |
- BXD50 |
- Pituitary |
- 77 |
- M |
-
-
- | 50 |
- R7142P |
- BXD56 |
- Pituitary |
- 84 |
- F |
-
-
- | 51 |
- R7097P |
- BXD56 |
- Pituitary |
- 77 |
- M |
-
-
- | 52 |
- R7080P |
- BXD60 |
- Pituitary |
- 70 |
- F |
-
-
- | 53 |
- R7141P_RW204 |
- BXD60 |
- Pituitary |
- 76 |
- M |
-
-
- | 54 |
- R7075P |
- BXD62 |
- Pituitary |
- 83 |
- F |
-
-
- | 55 |
- R7083P |
- BXD62 |
- Pituitary |
- 83 |
- M |
-
-
- | 56 |
- R7084P |
- BXD62 |
- Pituitary |
- 83 |
- M |
-
-
- | 57 |
- R7098P |
- BXD63 |
- Pituitary |
- 77 |
- F |
-
-
- | 58 |
- R7100P |
- BXD65 |
- Pituitary |
- 84 |
- M |
-
-
- | 59 |
- R7120P |
- BXD66 |
- Pituitary |
- 257 |
- M |
-
-
- | 60 |
- R7140P |
- BXD68 |
- Pituitary |
- 76 |
- F |
-
-
- | 61 |
- R7101P |
- BXD68 |
- Pituitary |
- 76 |
- M |
-
-
- | 62 |
- R7074P |
- BXD69 |
- Pituitary |
- 69 |
- F |
-
-
- | 63 |
- R7139P |
- BXD69 |
- Pituitary |
- 81 |
- M |
-
-
- | 64 |
- R7141P |
- BXD65 |
- Pituitary |
- 76 |
- F |
-
-
- | 65 |
- R7137P_RW112 |
- BXD70 |
- Pituitary |
- 76 |
- M |
-
-
- | 66 |
- R7124P |
- BXD71 |
- Pituitary |
- 76 |
- F |
-
-
- | 67 |
- R7123P |
- BXD71 |
- Pituitary |
- 76 |
- M |
-
-
- | 68 |
- R7068P |
- BXD73 |
- Pituitary |
- 83 |
- M |
-
-
- | 69 |
- R7118P |
- BXD74 |
- Pituitary |
- 69 |
- F |
-
-
- | 70 |
- R7117P |
- BXD74 |
- Pituitary |
- 69 |
- M |
-
-
- | 71 |
- R7082P |
- BXD75 |
- Pituitary |
- 76 |
- F |
-
-
- | 72 |
- R7048P |
- BXD75 |
- Pituitary |
- 76 |
- M |
-
-
- | 73 |
- R7122P |
- BXD77 |
- Pituitary |
- 223 |
- M |
-
-
- | 74 |
- R7103P |
- BXD79 |
- Pituitary |
- 86 |
- F |
-
-
- | 75 |
- R7104P |
- BXD79 |
- Pituitary |
- 86 |
- M |
-
-
- | 76 |
- R7073P |
- BXD80 |
- Pituitary |
- 73 |
- F |
-
-
- | 77 |
- R7070P |
- BXD80 |
- Pituitary |
- 73 |
- M |
-
-
- | 78 |
- R7139P_RW138 |
- BXD83 |
- Pituitary |
- 81 |
- F |
-
-
- | 79 |
- R7137P |
- BXD83 |
- Pituitary |
- 76 |
- M |
-
-
- | 80 |
- R7085P |
- BXD84 |
- Pituitary |
- 76 |
- F |
-
-
- | 81 |
- R7081P |
- BXD84 |
- Pituitary |
- 76 |
- M |
-
-
- | 82 |
- R7105P |
- BXD85 |
- Pituitary |
- 73 |
- M |
-
-
- | 83 |
- R7144P |
- BXD87 |
- Pituitary |
- 83 |
- F |
-
-
- | 84 |
- R7136P_RW196 |
- BXD87 |
- Pituitary |
- 83 |
- M |
-
-
- | 85 |
- R7106P |
- BXD89 |
- Pituitary |
- 82 |
- F |
-
-
- | 86 |
- R7107P |
- BXD89 |
- Pituitary |
- 82 |
- M |
-
-
- | 87 |
- R7108P |
- BXD90 |
- Pituitary |
- 82 |
- F |
-
-
- | 88 |
- R7109P |
- BXD90 |
- Pituitary |
- 82 |
- M |
-
-
- | 89 |
- R7138P_RW170 |
- BXD95 |
- Pituitary |
- 73 |
- F |
-
-
- | 90 |
- R7111P |
- BXD97 |
- Pituitary |
- 71 |
- F |
-
-
- | 91 |
- R7112P |
- BXD97 |
- Pituitary |
- 71 |
- M |
-
-
- | 92 |
- R7113P |
- BXD99 |
- Pituitary |
- 77 |
- F |
-
-
- | 93 |
- R7114P |
- BXD99 |
- Pituitary |
- 77 |
- M |
-
-
- | 94 |
- R7072P |
- BXD100 |
- Pituitary |
- 83 |
- F |
-
-
- | 95 |
- R7087P |
- BXD100 |
- Pituitary |
- 88 |
- F |
-
-
- | 96 |
- R7086P |
- BXD100 |
- Pituitary |
- 83 |
- M |
-
-
- | 97 |
- R7088P |
- BXD101 |
- Pituitary |
- 88 |
- M |
-
-
- | 98 |
- R7053P |
- BXD102 |
- Pituitary |
- 88 |
- F |
-
-
- | 99 |
- R7046P |
- BXD102 |
- Pituitary |
- 88 |
- M |
-
-
- | 100 |
- R7090P |
- BXD103 |
- Pituitary |
- 78 |
- F |
-
-
- | 101 |
- R7067P |
- BXD103 |
- Pituitary |
- 78 |
- M |
-
-
-
- |
-
-
-
diff --git a/general/datasets/INIA_Pituitary_RMA_F_0612/experiment-design.rtf b/general/datasets/INIA_Pituitary_RMA_F_0612/experiment-design.rtf
deleted file mode 100644
index 13175b5..0000000
--- a/general/datasets/INIA_Pituitary_RMA_F_0612/experiment-design.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-Normative expression in the whole pituitary of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
-
-QUALITY CONTROL DATA
-
-
- - 737 probe sets with LRS of 46 or higher (LOD>10)
- - Highest LRS = 165.7
- - Review of top Mendelian transcripts consist with correct strain assignment
- - Final sex assignment is correct
-
diff --git a/general/datasets/INIA_Pituitary_RMA_F_0612/platform.rtf b/general/datasets/INIA_Pituitary_RMA_F_0612/platform.rtf
deleted file mode 100644
index 7057d48..0000000
--- a/general/datasets/INIA_Pituitary_RMA_F_0612/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/INIA_Pituitary_RMA_F_0612/processing.rtf b/general/datasets/INIA_Pituitary_RMA_F_0612/processing.rtf
deleted file mode 100644
index 55aad2e..0000000
--- a/general/datasets/INIA_Pituitary_RMA_F_0612/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/INIA_Pituitary_RMA_F_0612/summary.rtf b/general/datasets/INIA_Pituitary_RMA_F_0612/summary.rtf
deleted file mode 100644
index 14a715d..0000000
--- a/general/datasets/INIA_Pituitary_RMA_F_0612/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Gene expression data for the whole pituitary across 52 strains of mice. Sex Balance: Sex of samples has been double-checked. As of July 2012, for 42 strains we have separate data for both males and females (usually one array each). Three strains (BXD45, 63, and 95) are only represented by female samples and two strains (BXD65 and BXD77) are only represented by male samples. Five other strains (BXD24, 66, 73, 85, 101) are may represent combined male and female samples. These unpublished data are apparently error-free based on a review and analysis of transcripts with Mendelian segregation patterns (as of July 20, 2012). The data set contains 751 eQTLs with LOD scores above 10 (LRS>46). Peak LRS of 165.9 for Record ID 10513604. Data for BXD70 are somewhat problematic (see 10444135 and 10467784), perhaps due to a bad array, strain assignment error, or residual heterozygozity. S Roy double-checked (July 22) and thinks that Sample R7141P is more likely to be BXD65.
-
-Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/INIA_Pituitary_RMA_F_0612/tissue.rtf b/general/datasets/INIA_Pituitary_RMA_F_0612/tissue.rtf
deleted file mode 100644
index 3977f1e..0000000
--- a/general/datasets/INIA_Pituitary_RMA_F_0612/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Whole pituitary gland dissected by hand. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/INIA_Pituitary_RMA_M_0612/acknowledgment.rtf b/general/datasets/INIA_Pituitary_RMA_M_0612/acknowledgment.rtf
deleted file mode 100644
index f8bf764..0000000
--- a/general/datasets/INIA_Pituitary_RMA_M_0612/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NIAAA U01 support to RWW.
diff --git a/general/datasets/INIA_Pituitary_RMA_M_0612/cases.rtf b/general/datasets/INIA_Pituitary_RMA_M_0612/cases.rtf
deleted file mode 100644
index faf8ab0..0000000
--- a/general/datasets/INIA_Pituitary_RMA_M_0612/cases.rtf
+++ /dev/null
@@ -1,840 +0,0 @@
-Young adult mice raised in specific pathogen-free vivarium at UTHSC.
-
-ERROR CHECKING by Mozhui, Centeno and Roy: The changes have been applied in GeneNetwork (GN389 - Pituitary) as follow:
-
-SampleId - New Strain Assignment
-R7087P (was BXD101) = BXD100
-R7138P_RW170 (was BXD85) = BXD95
-R7156P (was C57BL/6J) = B6D2F1
-R7141P = BXD65
-
-
-
-
-
-
-
-
-
-
- | Index |
- Sample ID |
- Strain |
- Tissue |
- Age |
- Sex |
-
-
- | 1 |
- R7128P |
- B6D2F1 |
- Pituitary |
- 69 |
- F |
-
-
- | 2 |
- R7156P |
- B6D2F1 |
- Pituitary |
- 92 |
- M |
-
-
- | 3 |
- R7129P |
- B6D2F1 |
- Pituitary |
- 69 |
- M |
-
-
- | 4 |
- R7134P |
- D2B6F1 |
- Pituitary |
- 77 |
- F |
-
-
- | 5 |
- R7133P |
- D2B6F1 |
- Pituitary |
- 77 |
- M |
-
-
- | 6 |
- R7160P |
- C57BL/6J |
- Pituitary |
- 92 |
- F |
-
-
- | 7 |
- R7127P |
- C57BL/6J |
- Pituitary |
- 77 |
- M |
-
-
- | 8 |
- R7126P |
- DBA/2J |
- Pituitary |
- 77 |
- F |
-
-
- | 9 |
- R7157P |
- DBA/2J |
- Pituitary |
- 75 |
- F |
-
-
- | 10 |
- R7125P |
- DBA/2J |
- Pituitary |
- 68 |
- M |
-
-
- | 11 |
- R7155P |
- DBA/2J |
- Pituitary |
- 75 |
- M |
-
-
- | 12 |
- R7058P |
- BXD1 |
- Pituitary |
- 72 |
- F |
-
-
- | 13 |
- R7063P |
- BXD1 |
- Pituitary |
- 86 |
- M |
-
-
- | 14 |
- R7079P |
- BXD11 |
- Pituitary |
- 87 |
- F |
-
-
- | 15 |
- R7069P |
- BXD11 |
- Pituitary |
- 76 |
- M |
-
-
- | 16 |
- R7051P |
- BXD12 |
- Pituitary |
- 78 |
- F |
-
-
- | 17 |
- R7061P |
- BXD12 |
- Pituitary |
- 78 |
- M |
-
-
- | 18 |
- R7064P |
- BXD14 |
- Pituitary |
- 81 |
- F |
-
-
- | 19 |
- R7066P |
- BXD14 |
- Pituitary |
- 81 |
- M |
-
-
- | 20 |
- R7052P |
- BXD24 |
- Pituitary |
- 86 |
- M |
-
-
- | 21 |
- R7076P |
- BXD27 |
- Pituitary |
- 76 |
- F |
-
-
- | 22 |
- R7071P |
- BXD27 |
- Pituitary |
- 73 |
- M |
-
-
- | 23 |
- R7059P |
- BXD29 |
- Pituitary |
- 72 |
- F |
-
-
- | 24 |
- R7060P |
- BXD29 |
- Pituitary |
- 72 |
- M |
-
-
- | 25 |
- R7055P |
- BXD31 |
- Pituitary |
- 74 |
- F |
-
-
- | 26 |
- R7062P |
- BXD31 |
- Pituitary |
- 74 |
- M |
-
-
- | 27 |
- R7143P |
- BXD32 |
- Pituitary |
- 81 |
- F |
-
-
- | 28 |
- R7135P |
- BXD32 |
- Pituitary |
- 81 |
- M |
-
-
- | 29 |
- R7119P |
- BXD34 |
- Pituitary |
- 77 |
- F |
-
-
- | 30 |
- R7054P |
- BXD34 |
- Pituitary |
- 77 |
- M |
-
-
- | 31 |
- R7049P |
- BXD39 |
- Pituitary |
- 79 |
- F |
-
-
- | 32 |
- R7065P |
- BXD39 |
- Pituitary |
- 79 |
- M |
-
-
- | 33 |
- R7130P |
- BXD40 |
- Pituitary |
- 85 |
- F |
-
-
- | 34 |
- R7132P |
- BXD40 |
- Pituitary |
- 85 |
- M |
-
-
- | 35 |
- R7056P |
- BXD42 |
- Pituitary |
- 87 |
- F |
-
-
- | 36 |
- R7044P |
- BXD42 |
- Pituitary |
- 87 |
- M |
-
-
- | 37 |
- R7043P |
- BXD43 |
- Pituitary |
- 81 |
- F |
-
-
- | 38 |
- R7047P |
- BXD43 |
- Pituitary |
- 81 |
- M |
-
-
- | 39 |
- R7091P |
- BXD44 |
- Pituitary |
- 83 |
- F |
-
-
- | 40 |
- R7050P |
- BXD44 |
- Pituitary |
- 83 |
- M |
-
-
- | 41 |
- R7077P |
- BXD45 |
- Pituitary |
- 77 |
- F |
-
-
- | 42 |
- R7078P |
- BXD45 |
- Pituitary |
- 77 |
- F |
-
-
- | 43 |
- R7042P |
- BXD45 |
- Pituitary |
- 77 |
- F |
-
-
- | 44 |
- R7092P |
- BXD48 |
- Pituitary |
- 76 |
- F |
-
-
- | 45 |
- R7093P |
- BXD48 |
- Pituitary |
- 76 |
- M |
-
-
- | 46 |
- R7045P |
- BXD49 |
- Pituitary |
- 84 |
- F |
-
-
- | 47 |
- R7094P |
- BXD49 |
- Pituitary |
- 84 |
- M |
-
-
- | 48 |
- R7095P |
- BXD50 |
- Pituitary |
- 77 |
- F |
-
-
- | 49 |
- R7096P |
- BXD50 |
- Pituitary |
- 77 |
- M |
-
-
- | 50 |
- R7142P |
- BXD56 |
- Pituitary |
- 84 |
- F |
-
-
- | 51 |
- R7097P |
- BXD56 |
- Pituitary |
- 77 |
- M |
-
-
- | 52 |
- R7080P |
- BXD60 |
- Pituitary |
- 70 |
- F |
-
-
- | 53 |
- R7141P_RW204 |
- BXD60 |
- Pituitary |
- 76 |
- M |
-
-
- | 54 |
- R7075P |
- BXD62 |
- Pituitary |
- 83 |
- F |
-
-
- | 55 |
- R7083P |
- BXD62 |
- Pituitary |
- 83 |
- M |
-
-
- | 56 |
- R7084P |
- BXD62 |
- Pituitary |
- 83 |
- M |
-
-
- | 57 |
- R7098P |
- BXD63 |
- Pituitary |
- 77 |
- F |
-
-
- | 58 |
- R7100P |
- BXD65 |
- Pituitary |
- 84 |
- M |
-
-
- | 59 |
- R7120P |
- BXD66 |
- Pituitary |
- 257 |
- M |
-
-
- | 60 |
- R7140P |
- BXD68 |
- Pituitary |
- 76 |
- F |
-
-
- | 61 |
- R7101P |
- BXD68 |
- Pituitary |
- 76 |
- M |
-
-
- | 62 |
- R7074P |
- BXD69 |
- Pituitary |
- 69 |
- F |
-
-
- | 63 |
- R7139P |
- BXD69 |
- Pituitary |
- 81 |
- M |
-
-
- | 64 |
- R7141P |
- BXD65 |
- Pituitary |
- 76 |
- F |
-
-
- | 65 |
- R7137P_RW112 |
- BXD70 |
- Pituitary |
- 76 |
- M |
-
-
- | 66 |
- R7124P |
- BXD71 |
- Pituitary |
- 76 |
- F |
-
-
- | 67 |
- R7123P |
- BXD71 |
- Pituitary |
- 76 |
- M |
-
-
- | 68 |
- R7068P |
- BXD73 |
- Pituitary |
- 83 |
- M |
-
-
- | 69 |
- R7118P |
- BXD74 |
- Pituitary |
- 69 |
- F |
-
-
- | 70 |
- R7117P |
- BXD74 |
- Pituitary |
- 69 |
- M |
-
-
- | 71 |
- R7082P |
- BXD75 |
- Pituitary |
- 76 |
- F |
-
-
- | 72 |
- R7048P |
- BXD75 |
- Pituitary |
- 76 |
- M |
-
-
- | 73 |
- R7122P |
- BXD77 |
- Pituitary |
- 223 |
- M |
-
-
- | 74 |
- R7103P |
- BXD79 |
- Pituitary |
- 86 |
- F |
-
-
- | 75 |
- R7104P |
- BXD79 |
- Pituitary |
- 86 |
- M |
-
-
- | 76 |
- R7073P |
- BXD80 |
- Pituitary |
- 73 |
- F |
-
-
- | 77 |
- R7070P |
- BXD80 |
- Pituitary |
- 73 |
- M |
-
-
- | 78 |
- R7139P_RW138 |
- BXD83 |
- Pituitary |
- 81 |
- F |
-
-
- | 79 |
- R7137P |
- BXD83 |
- Pituitary |
- 76 |
- M |
-
-
- | 80 |
- R7085P |
- BXD84 |
- Pituitary |
- 76 |
- F |
-
-
- | 81 |
- R7081P |
- BXD84 |
- Pituitary |
- 76 |
- M |
-
-
- | 82 |
- R7105P |
- BXD85 |
- Pituitary |
- 73 |
- M |
-
-
- | 83 |
- R7144P |
- BXD87 |
- Pituitary |
- 83 |
- F |
-
-
- | 84 |
- R7136P_RW196 |
- BXD87 |
- Pituitary |
- 83 |
- M |
-
-
- | 85 |
- R7106P |
- BXD89 |
- Pituitary |
- 82 |
- F |
-
-
- | 86 |
- R7107P |
- BXD89 |
- Pituitary |
- 82 |
- M |
-
-
- | 87 |
- R7108P |
- BXD90 |
- Pituitary |
- 82 |
- F |
-
-
- | 88 |
- R7109P |
- BXD90 |
- Pituitary |
- 82 |
- M |
-
-
- | 89 |
- R7138P_RW170 |
- BXD95 |
- Pituitary |
- 73 |
- F |
-
-
- | 90 |
- R7111P |
- BXD97 |
- Pituitary |
- 71 |
- F |
-
-
- | 91 |
- R7112P |
- BXD97 |
- Pituitary |
- 71 |
- M |
-
-
- | 92 |
- R7113P |
- BXD99 |
- Pituitary |
- 77 |
- F |
-
-
- | 93 |
- R7114P |
- BXD99 |
- Pituitary |
- 77 |
- M |
-
-
- | 94 |
- R7072P |
- BXD100 |
- Pituitary |
- 83 |
- F |
-
-
- | 95 |
- R7087P |
- BXD100 |
- Pituitary |
- 88 |
- F |
-
-
- | 96 |
- R7086P |
- BXD100 |
- Pituitary |
- 83 |
- M |
-
-
- | 97 |
- R7088P |
- BXD101 |
- Pituitary |
- 88 |
- M |
-
-
- | 98 |
- R7053P |
- BXD102 |
- Pituitary |
- 88 |
- F |
-
-
- | 99 |
- R7046P |
- BXD102 |
- Pituitary |
- 88 |
- M |
-
-
- | 100 |
- R7090P |
- BXD103 |
- Pituitary |
- 78 |
- F |
-
-
- | 101 |
- R7067P |
- BXD103 |
- Pituitary |
- 78 |
- M |
-
-
-
- |
-
-
-
diff --git a/general/datasets/INIA_Pituitary_RMA_M_0612/experiment-design.rtf b/general/datasets/INIA_Pituitary_RMA_M_0612/experiment-design.rtf
deleted file mode 100644
index 13175b5..0000000
--- a/general/datasets/INIA_Pituitary_RMA_M_0612/experiment-design.rtf
+++ /dev/null
@@ -1,10 +0,0 @@
-Normative expression in the whole pituitary of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
-
-QUALITY CONTROL DATA
-
-
- - 737 probe sets with LRS of 46 or higher (LOD>10)
- - Highest LRS = 165.7
- - Review of top Mendelian transcripts consist with correct strain assignment
- - Final sex assignment is correct
-
diff --git a/general/datasets/INIA_Pituitary_RMA_M_0612/platform.rtf b/general/datasets/INIA_Pituitary_RMA_M_0612/platform.rtf
deleted file mode 100644
index 7057d48..0000000
--- a/general/datasets/INIA_Pituitary_RMA_M_0612/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/INIA_Pituitary_RMA_M_0612/processing.rtf b/general/datasets/INIA_Pituitary_RMA_M_0612/processing.rtf
deleted file mode 100644
index 55aad2e..0000000
--- a/general/datasets/INIA_Pituitary_RMA_M_0612/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/INIA_Pituitary_RMA_M_0612/summary.rtf b/general/datasets/INIA_Pituitary_RMA_M_0612/summary.rtf
deleted file mode 100644
index 14a715d..0000000
--- a/general/datasets/INIA_Pituitary_RMA_M_0612/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Gene expression data for the whole pituitary across 52 strains of mice. Sex Balance: Sex of samples has been double-checked. As of July 2012, for 42 strains we have separate data for both males and females (usually one array each). Three strains (BXD45, 63, and 95) are only represented by female samples and two strains (BXD65 and BXD77) are only represented by male samples. Five other strains (BXD24, 66, 73, 85, 101) are may represent combined male and female samples. These unpublished data are apparently error-free based on a review and analysis of transcripts with Mendelian segregation patterns (as of July 20, 2012). The data set contains 751 eQTLs with LOD scores above 10 (LRS>46). Peak LRS of 165.9 for Record ID 10513604. Data for BXD70 are somewhat problematic (see 10444135 and 10467784), perhaps due to a bad array, strain assignment error, or residual heterozygozity. S Roy double-checked (July 22) and thinks that Sample R7141P is more likely to be BXD65.
-
-Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/INIA_Pituitary_RMA_M_0612/tissue.rtf b/general/datasets/INIA_Pituitary_RMA_M_0612/tissue.rtf
deleted file mode 100644
index 3977f1e..0000000
--- a/general/datasets/INIA_Pituitary_RMA_M_0612/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Whole pituitary gland dissected by hand. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/INIA_UTHSC_Hip_AffyMTA1_May17/summary.rtf b/general/datasets/INIA_UTHSC_Hip_AffyMTA1_May17/summary.rtf
deleted file mode 100644
index 153d98d..0000000
--- a/general/datasets/INIA_UTHSC_Hip_AffyMTA1_May17/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In working progress...
diff --git a/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Apr17/cases.rtf b/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Apr17/cases.rtf
deleted file mode 100644
index 976f0ab..0000000
--- a/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Apr17/cases.rtf
+++ /dev/null
@@ -1,857 +0,0 @@
-
-
-
-
-
-
-
-
-
-
-
- | MicroarrayID |
- Mouse.ID |
- Strain |
- Pyrazole |
- TimePoint |
- Treatment |
- PCA Batch |
- DissectionBatch |
- ExtractionBatch |
- Concentration |
- RIN |
-
-
- | MB1 |
- 12 |
- C57BL/6J |
- PZ |
- 8h |
- CIE |
- B |
- A |
- 1 |
- 224.611 |
- 9.0 |
-
-
- | MB2 |
- 50 |
- DBA/2J |
- NO |
- 3d |
- AIR |
- B |
- A |
- 1 |
- 195.150 |
- 9.2 |
-
-
- | MB3 |
- 2 |
- C57BL/6J |
- PZ |
- 14d |
- AIR |
- B |
- A |
- 1 |
- 299.415 |
- 9.5 |
-
-
- | MB4 |
- 60 |
- DBA/2J |
- PZ |
- 7d |
- AIR |
- B |
- A |
- 1 |
- 300.033 |
- 7.6 |
-
-
- | MB5 |
- 4 |
- C57BL/6J |
- PZ |
- 14d |
- CIE |
- A |
- A |
- 1 |
- 249.226 |
- 7.2 |
-
-
- | MB6 |
- 69 |
- DBA/2J |
- PZ |
- 7d |
- AIR |
- A |
- A |
- 1 |
- 161.526 |
- 7.3 |
-
-
- | MB7 |
- 8 |
- C57BL/6J |
- PZ |
- 3d |
- CIE |
- B |
- A |
- 1 |
- 326.862 |
- 9.5 |
-
-
- | MB8 |
- 41 |
- DBA/2J |
- PZ |
- 8h |
- AIR |
- B |
- A |
- 1 |
- 352.559 |
- 7.9 |
-
-
- | MB9 |
- 75 |
- DBA/2J |
- PZ |
- 14d |
- AIR |
- B |
- B |
- 1 |
- 354.218 |
- 8.8 |
-
-
- | MB10 |
- 23 |
- C57BL/6J |
- PZ |
- 3d |
- AIR |
- B |
- B |
- 1 |
- 280.396 |
- 9.6 |
-
-
- | MB11 |
- 49 |
- DBA/2J |
- PZ |
- 3d |
- AIR |
- A |
- B |
- 1 |
- 180.312 |
- 7.2 |
-
-
- | MB12 |
- 58 |
- DBA/2J |
- PZ |
- 3d |
- CIE |
- B |
- B |
- 1 |
- 225.072 |
- NA |
-
-
- | MB13 |
- 21 |
- C57BL/6J |
- PZ |
- 14d |
- CIE |
- B |
- C |
- 1 |
- 299.623 |
- 7.4 |
-
-
- | MB14 |
- 63 |
- DBA/2J |
- PZ |
- 3d |
- CIE |
- B |
- C |
- 1 |
- 70.977 |
- 7.5 |
-
-
- | MB15 |
- 46 |
- DBA/2J |
- PZ |
- 8h |
- AIR |
- B |
- C |
- 1 |
- 284.115 |
- 7.9 |
-
-
- | MB16 |
- 45 |
- DBA/2J |
- PZ |
- 8h |
- AIR |
- B |
- C |
- 1 |
- 338.791 |
- 7.7 |
-
-
- | MB17 |
- 28 |
- C57BL/6J |
- NO |
- 3d |
- AIR |
- B |
- C |
- 1 |
- 449.851 |
- 7.8 |
-
-
- | MB18 |
- 78 |
- DBA/2J |
- PZ |
- 14d |
- AIR |
- B |
- C |
- 1 |
- 320.081 |
- 7.9 |
-
-
- | MB19 |
- 77 |
- DBA/2J |
- PZ |
- 14d |
- CIE |
- B |
- C |
- 1 |
- 234.795 |
- 7.8 |
-
-
- | MB20 |
- 71 |
- DBA/2J |
- PZ |
- 7d |
- CIE |
- B |
- C |
- 1 |
- 468.728 |
- 7.8 |
-
-
- | MB21 |
- 68 |
- DBA/2J |
- PZ |
- 7d |
- AIR |
- B |
- C |
- 1 |
- 296.386 |
- 7.9 |
-
-
- | MB22 |
- 29 |
- C57BL/6J |
- PZ |
- 8h |
- CIE |
- B |
- C |
- 1 |
- 398.481 |
- 8.0 |
-
-
- | MB23 |
- 67 |
- DBA/2J |
- PZ |
- 7d |
- CIE |
- B |
- A |
- 2 |
- 275.813 |
- 7.8 |
-
-
- | MB24 |
- 1 |
- C57BL/6J |
- PZ |
- 8h |
- AIR |
- A |
- A |
- 2 |
- 132.589 |
- 6.8 |
-
-
- | MB25 |
- 14 |
- C57BL/6J |
- NO |
- 3d |
- CIE |
- A |
- A |
- 2 |
- 189.666 |
- 7.9 |
-
-
- | MB26 |
- 42 |
- DBA/2J |
- PZ |
- 8h |
- CIE |
- B |
- A |
- 2 |
- 310.878 |
- 9.4 |
-
-
- | MB27 |
- 55 |
- DBA/2J |
- PZ |
- 3d |
- CIE |
- B |
- A |
- 2 |
- 211.576 |
- 9.0 |
-
-
- | MB28 |
- 73 |
- DBA/2J |
- PZ |
- 7d |
- CIE |
- B |
- A |
- 2 |
- 287.696 |
- 7.6 |
-
-
- | MB29 |
- 48 |
- DBA/2J |
- PZ |
- 3d |
- AIR |
- B |
- A |
- 2 |
- 317.532 |
- 7.8 |
-
-
- | MB30 |
- 61 |
- DBA/2J |
- PZ |
- 7d |
- AIR |
- B |
- B |
- 2 |
- 294.808 |
- 7.8 |
-
-
- | MB31 |
- 20 |
- C57BL/6J |
- PZ |
- 8h |
- CIE |
- B |
- B |
- 2 |
- 209.301 |
- 9.0 |
-
-
- | MB32 |
- 76 |
- DBA/2J |
- PZ |
- 14d |
- CIE |
- A |
- B |
- 2 |
- 120.953 |
- 8.2 |
-
-
- | MB33 |
- 5 |
- C57BL/6J |
- PZ |
- 14d |
- AIR |
- B |
- B |
- 2 |
- 271.808 |
- 8.8 |
-
-
- | MB34 |
- 37 |
- C57BL/6J |
- PZ |
- 7d |
- CIE |
- B |
- B |
- 2 |
- 289.261 |
- 8.0 |
-
-
- | MB35 |
- 19 |
- C57BL/6J |
- PZ |
- 3d |
- CIE |
- B |
- C |
- 2 |
- 306.294 |
- 9.1 |
-
-
- | MB36 |
- 56 |
- DBA/2J |
- PZ |
- 3d |
- AIR |
- B |
- C |
- 2 |
- 265.964 |
- 7.8 |
-
-
- | MB37 |
- 65 |
- DBA/2J |
- NO |
- 3d |
- CIE |
- B |
- C |
- 2 |
- 259.741 |
- 9.2 |
-
-
- | MB38 |
- 80 |
- DBA/2J |
- PZ |
- 14d |
- AIR |
- B |
- C |
- 2 |
- 371.000 |
- 8.0 |
-
-
- | MB39 |
- 31 |
- C57BL/6J |
- PZ |
- 14d |
- CIE |
- B |
- C |
- 2 |
- 349.451 |
- 7.7 |
-
-
- | MB40 |
- 39 |
- C57BL/6J |
- PZ |
- 7d |
- AIR |
- C |
- C |
- 2 |
- 403.083 |
- 8.9 |
-
-
- | MB41 |
- 62 |
- DBA/2J |
- PZ |
- 3d |
- CIE |
- C |
- C |
- 2 |
- 505.547 |
- 8.9 |
-
-
- | MB42 |
- 52 |
- DBA/2J |
- PZ |
- 8h |
- CIE |
- C |
- C |
- 2 |
- 441.549 |
- 8.8 |
-
-
- | MB43 |
- 51 |
- DBA/2J |
- PZ |
- 3d |
- AIR |
- C |
- C |
- 2 |
- 519.427 |
- 8.8 |
-
-
- | MB44 |
- 35 |
- C57BL/6J |
- NO |
- 3d |
- AIR |
- C |
- A |
- 3 |
- 772.361 |
- 8.8 |
-
-
- | MB45 |
- 72 |
- DBA/2J |
- PZ |
- 14d |
- AIR |
- C |
- A |
- 3 |
- 598.185 |
- 8.9 |
-
-
- | MB46 |
- 32 |
- C57BL/6J |
- PZ |
- 7d |
- CIE |
- C |
- A |
- 3 |
- 824.974 |
- 8.7 |
-
-
- | MB47 |
- 74 |
- DBA/2J |
- PZ |
- 14d |
- CIE |
- C |
- A |
- 3 |
- 495.046 |
- 9.4 |
-
-
- | MB48 |
- 54 |
- DBA/2J |
- PZ |
- 8h |
- CIE |
- C |
- A |
- 3 |
- 667.036 |
- 9.4 |
-
-
- | MB49 |
- 24 |
- C57BL/6J |
- PZ |
- 7d |
- AIR |
- C |
- A |
- 3 |
- 760.367 |
- 9.2 |
-
-
- | MB50 |
- 9 |
- C57BL/6J |
- PZ |
- 3d |
- AIR |
- C |
- A |
- 3 |
- 701.152 |
- 9.2 |
-
-
- | MB51 |
- 66 |
- DBA/2J |
- NO |
- 3d |
- CIE |
- C |
- B |
- 3 |
- 579.22 |
- 8.3 |
-
-
- | MB52 |
- 44 |
- DBA/2J |
- PZ |
- 8h |
- CIE |
- C |
- B |
- 3 |
- 636.091 |
- 9.4 |
-
-
- | MB53 |
- 34 |
- C57BL/6J |
- PZ |
- 7d |
- AIR |
- C |
- B |
- 3 |
- 739.127 |
- 9.5 |
-
-
- | MB54 |
- 7 |
- C57BL/6J |
- PZ |
- 8h |
- AIR |
- C |
- B |
- 3 |
- 667.933 |
- 9.2 |
-
-
- | MB55 |
- 36 |
- C57BL/6J |
- NO |
- 3d |
- CIE |
- C |
- C |
- 3 |
- 605.937 |
- 9.2 |
-
-
- | MB56 |
- 43 |
- DBA/2J |
- PZ |
- 8h |
- AIR |
- C |
- C |
- 3 |
- 639.161 |
- 9.5 |
-
-
- | MB57 |
- 70 |
- DBA/2J |
- PZ |
- 7d |
- CIE |
- C |
- C |
- 3 |
- 630.735 |
- 9.4 |
-
-
- | MB58 |
- 59 |
- DBA/2J |
- NO |
- 3d |
- AIR |
- C |
- C |
- 3 |
- 548.647 |
- 9.5 |
-
-
- | MB59 |
- 15 |
- C57BL/6J |
- PZ |
- 14d |
- AIR |
- C |
- C |
- 3 |
- 689.793 |
- 9.4 |
-
-
- | MB60 |
- 27 |
- C57BL/6J |
- PZ |
- 8h |
- AIR |
- C |
- C |
- 3 |
- 580.462 |
- 9.4 |
-
-
- | MB61 |
- 30 |
- C57BL/6J |
- PZ |
- 3d |
- AIR |
- C |
- C |
- 3 |
- 577.826 |
- 8.2 |
-
-
- | MB62 |
- 57 |
- DBA/2J |
- PZ |
- 3d |
- AIR |
- C |
- C |
- 3 |
- 581.164 |
- 9.0 |
-
-
- | MB63 |
- 38 |
- C57BL/6J |
- PZ |
- 3d |
- CIE |
- C |
- C |
- 3 |
- 748.421 |
- 8.6 |
-
-
- | MB64 |
- 47 |
- DBA/2J |
- PZ |
- 8h |
- AIR |
- C |
- C |
- 3 |
- 747.345 |
- 8.5 |
-
-
-
diff --git a/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Apr17/specifics.rtf b/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Apr17/specifics.rtf
deleted file mode 100644
index 729d375..0000000
--- a/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Apr17/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-SST-RMA Gene Level
diff --git a/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Apr17/summary.rtf b/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Apr17/summary.rtf
deleted file mode 100644
index 9baa040..0000000
--- a/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Apr17/summary.rtf
+++ /dev/null
@@ -1,31 +0,0 @@
-Overview:
-
-1. Treated and whole brains dissected at Medical University of South Carolina (Marcelo F. Lopez laboratory)
-
-2. Frozen brains sub-dissected at UTHSC (Megan K. Mulligan laboratory)
-
-3. RNA extraction (Qiagen RNeasy kit) at UTHSC (Mulligan and Williams laboratories)
-
-4. Hybridized to Affymetrix Clariom D (aka Affymetrix MTA 1.0 ST) array at UTHSC MRC (Lorne Rose, UTHSC Molecular Resource Center)
-
-5. Initial QC and normalization (COMBAT) at UTHSC (Megan K. Mulligan laboratory)
-
-6. Transcriptome entry and phenotype entry (Arthur Centeno, Megan K. Mulligan, and Robert W. Williams)
-
-
-
-Chronic ethanol exposure:
-
-Mice were allowed to self-administer alcohol (15% v/v vs. water) for 2 h a day (5 days a week) 6 weeks prior to treatment in order to establish baseline consumption. Access to 15% alcohol versus water started 30 min prior to the start of the dark cycle. Following establishment of baseline drinking, male mice representative of each strain were separated into groups to be exposed to either weekly cycles of CIE exposure (CIE group) or air control (AIR group) exposure.
-
-
-
-Mice assigned to the CIE treatment group were exposed to alcohol vapor for 16 h a day followed by 8 h of withdrawal for 4 days per week. Following the fourth vapor exposure, mice were given a 72-h abstinence/withdrawal period before resuming ethanol intake in the home cage for 5 days. Mice in the AIR control treatment group were similarly treated but exposed only to air in the inhalation chambers. This pattern of CIE or air control exposure followed by 5 days of ethanol self-administration was repeated for four cycles. A fifth cycle of CIE (or air) exposure followed the fourth ethanol intake evaluation period, and brain tissue was collected at multiple time points (8h, 3d, 7d, 14d) after the last cycle ended. Pyrazole (1 mmol/kg) was used to stabilize blood ethanol levels (BEC) and was administered to both CIE and AIR groups. A subset of mice received no pyrazole.
-
-
-
-Analysis:
-
-1. Normalization on Affymetrix Expression Console (SST-RMA Gene Level).
-
-2. Batch effect detected (RNA concentration dependent) and corrected in ComBat
diff --git a/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Ex_May17/cases.rtf b/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Ex_May17/cases.rtf
deleted file mode 100644
index 976f0ab..0000000
--- a/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Ex_May17/cases.rtf
+++ /dev/null
@@ -1,857 +0,0 @@
-
-
-
-
-
-
-
-
-
-
-
- | MicroarrayID |
- Mouse.ID |
- Strain |
- Pyrazole |
- TimePoint |
- Treatment |
- PCA Batch |
- DissectionBatch |
- ExtractionBatch |
- Concentration |
- RIN |
-
-
- | MB1 |
- 12 |
- C57BL/6J |
- PZ |
- 8h |
- CIE |
- B |
- A |
- 1 |
- 224.611 |
- 9.0 |
-
-
- | MB2 |
- 50 |
- DBA/2J |
- NO |
- 3d |
- AIR |
- B |
- A |
- 1 |
- 195.150 |
- 9.2 |
-
-
- | MB3 |
- 2 |
- C57BL/6J |
- PZ |
- 14d |
- AIR |
- B |
- A |
- 1 |
- 299.415 |
- 9.5 |
-
-
- | MB4 |
- 60 |
- DBA/2J |
- PZ |
- 7d |
- AIR |
- B |
- A |
- 1 |
- 300.033 |
- 7.6 |
-
-
- | MB5 |
- 4 |
- C57BL/6J |
- PZ |
- 14d |
- CIE |
- A |
- A |
- 1 |
- 249.226 |
- 7.2 |
-
-
- | MB6 |
- 69 |
- DBA/2J |
- PZ |
- 7d |
- AIR |
- A |
- A |
- 1 |
- 161.526 |
- 7.3 |
-
-
- | MB7 |
- 8 |
- C57BL/6J |
- PZ |
- 3d |
- CIE |
- B |
- A |
- 1 |
- 326.862 |
- 9.5 |
-
-
- | MB8 |
- 41 |
- DBA/2J |
- PZ |
- 8h |
- AIR |
- B |
- A |
- 1 |
- 352.559 |
- 7.9 |
-
-
- | MB9 |
- 75 |
- DBA/2J |
- PZ |
- 14d |
- AIR |
- B |
- B |
- 1 |
- 354.218 |
- 8.8 |
-
-
- | MB10 |
- 23 |
- C57BL/6J |
- PZ |
- 3d |
- AIR |
- B |
- B |
- 1 |
- 280.396 |
- 9.6 |
-
-
- | MB11 |
- 49 |
- DBA/2J |
- PZ |
- 3d |
- AIR |
- A |
- B |
- 1 |
- 180.312 |
- 7.2 |
-
-
- | MB12 |
- 58 |
- DBA/2J |
- PZ |
- 3d |
- CIE |
- B |
- B |
- 1 |
- 225.072 |
- NA |
-
-
- | MB13 |
- 21 |
- C57BL/6J |
- PZ |
- 14d |
- CIE |
- B |
- C |
- 1 |
- 299.623 |
- 7.4 |
-
-
- | MB14 |
- 63 |
- DBA/2J |
- PZ |
- 3d |
- CIE |
- B |
- C |
- 1 |
- 70.977 |
- 7.5 |
-
-
- | MB15 |
- 46 |
- DBA/2J |
- PZ |
- 8h |
- AIR |
- B |
- C |
- 1 |
- 284.115 |
- 7.9 |
-
-
- | MB16 |
- 45 |
- DBA/2J |
- PZ |
- 8h |
- AIR |
- B |
- C |
- 1 |
- 338.791 |
- 7.7 |
-
-
- | MB17 |
- 28 |
- C57BL/6J |
- NO |
- 3d |
- AIR |
- B |
- C |
- 1 |
- 449.851 |
- 7.8 |
-
-
- | MB18 |
- 78 |
- DBA/2J |
- PZ |
- 14d |
- AIR |
- B |
- C |
- 1 |
- 320.081 |
- 7.9 |
-
-
- | MB19 |
- 77 |
- DBA/2J |
- PZ |
- 14d |
- CIE |
- B |
- C |
- 1 |
- 234.795 |
- 7.8 |
-
-
- | MB20 |
- 71 |
- DBA/2J |
- PZ |
- 7d |
- CIE |
- B |
- C |
- 1 |
- 468.728 |
- 7.8 |
-
-
- | MB21 |
- 68 |
- DBA/2J |
- PZ |
- 7d |
- AIR |
- B |
- C |
- 1 |
- 296.386 |
- 7.9 |
-
-
- | MB22 |
- 29 |
- C57BL/6J |
- PZ |
- 8h |
- CIE |
- B |
- C |
- 1 |
- 398.481 |
- 8.0 |
-
-
- | MB23 |
- 67 |
- DBA/2J |
- PZ |
- 7d |
- CIE |
- B |
- A |
- 2 |
- 275.813 |
- 7.8 |
-
-
- | MB24 |
- 1 |
- C57BL/6J |
- PZ |
- 8h |
- AIR |
- A |
- A |
- 2 |
- 132.589 |
- 6.8 |
-
-
- | MB25 |
- 14 |
- C57BL/6J |
- NO |
- 3d |
- CIE |
- A |
- A |
- 2 |
- 189.666 |
- 7.9 |
-
-
- | MB26 |
- 42 |
- DBA/2J |
- PZ |
- 8h |
- CIE |
- B |
- A |
- 2 |
- 310.878 |
- 9.4 |
-
-
- | MB27 |
- 55 |
- DBA/2J |
- PZ |
- 3d |
- CIE |
- B |
- A |
- 2 |
- 211.576 |
- 9.0 |
-
-
- | MB28 |
- 73 |
- DBA/2J |
- PZ |
- 7d |
- CIE |
- B |
- A |
- 2 |
- 287.696 |
- 7.6 |
-
-
- | MB29 |
- 48 |
- DBA/2J |
- PZ |
- 3d |
- AIR |
- B |
- A |
- 2 |
- 317.532 |
- 7.8 |
-
-
- | MB30 |
- 61 |
- DBA/2J |
- PZ |
- 7d |
- AIR |
- B |
- B |
- 2 |
- 294.808 |
- 7.8 |
-
-
- | MB31 |
- 20 |
- C57BL/6J |
- PZ |
- 8h |
- CIE |
- B |
- B |
- 2 |
- 209.301 |
- 9.0 |
-
-
- | MB32 |
- 76 |
- DBA/2J |
- PZ |
- 14d |
- CIE |
- A |
- B |
- 2 |
- 120.953 |
- 8.2 |
-
-
- | MB33 |
- 5 |
- C57BL/6J |
- PZ |
- 14d |
- AIR |
- B |
- B |
- 2 |
- 271.808 |
- 8.8 |
-
-
- | MB34 |
- 37 |
- C57BL/6J |
- PZ |
- 7d |
- CIE |
- B |
- B |
- 2 |
- 289.261 |
- 8.0 |
-
-
- | MB35 |
- 19 |
- C57BL/6J |
- PZ |
- 3d |
- CIE |
- B |
- C |
- 2 |
- 306.294 |
- 9.1 |
-
-
- | MB36 |
- 56 |
- DBA/2J |
- PZ |
- 3d |
- AIR |
- B |
- C |
- 2 |
- 265.964 |
- 7.8 |
-
-
- | MB37 |
- 65 |
- DBA/2J |
- NO |
- 3d |
- CIE |
- B |
- C |
- 2 |
- 259.741 |
- 9.2 |
-
-
- | MB38 |
- 80 |
- DBA/2J |
- PZ |
- 14d |
- AIR |
- B |
- C |
- 2 |
- 371.000 |
- 8.0 |
-
-
- | MB39 |
- 31 |
- C57BL/6J |
- PZ |
- 14d |
- CIE |
- B |
- C |
- 2 |
- 349.451 |
- 7.7 |
-
-
- | MB40 |
- 39 |
- C57BL/6J |
- PZ |
- 7d |
- AIR |
- C |
- C |
- 2 |
- 403.083 |
- 8.9 |
-
-
- | MB41 |
- 62 |
- DBA/2J |
- PZ |
- 3d |
- CIE |
- C |
- C |
- 2 |
- 505.547 |
- 8.9 |
-
-
- | MB42 |
- 52 |
- DBA/2J |
- PZ |
- 8h |
- CIE |
- C |
- C |
- 2 |
- 441.549 |
- 8.8 |
-
-
- | MB43 |
- 51 |
- DBA/2J |
- PZ |
- 3d |
- AIR |
- C |
- C |
- 2 |
- 519.427 |
- 8.8 |
-
-
- | MB44 |
- 35 |
- C57BL/6J |
- NO |
- 3d |
- AIR |
- C |
- A |
- 3 |
- 772.361 |
- 8.8 |
-
-
- | MB45 |
- 72 |
- DBA/2J |
- PZ |
- 14d |
- AIR |
- C |
- A |
- 3 |
- 598.185 |
- 8.9 |
-
-
- | MB46 |
- 32 |
- C57BL/6J |
- PZ |
- 7d |
- CIE |
- C |
- A |
- 3 |
- 824.974 |
- 8.7 |
-
-
- | MB47 |
- 74 |
- DBA/2J |
- PZ |
- 14d |
- CIE |
- C |
- A |
- 3 |
- 495.046 |
- 9.4 |
-
-
- | MB48 |
- 54 |
- DBA/2J |
- PZ |
- 8h |
- CIE |
- C |
- A |
- 3 |
- 667.036 |
- 9.4 |
-
-
- | MB49 |
- 24 |
- C57BL/6J |
- PZ |
- 7d |
- AIR |
- C |
- A |
- 3 |
- 760.367 |
- 9.2 |
-
-
- | MB50 |
- 9 |
- C57BL/6J |
- PZ |
- 3d |
- AIR |
- C |
- A |
- 3 |
- 701.152 |
- 9.2 |
-
-
- | MB51 |
- 66 |
- DBA/2J |
- NO |
- 3d |
- CIE |
- C |
- B |
- 3 |
- 579.22 |
- 8.3 |
-
-
- | MB52 |
- 44 |
- DBA/2J |
- PZ |
- 8h |
- CIE |
- C |
- B |
- 3 |
- 636.091 |
- 9.4 |
-
-
- | MB53 |
- 34 |
- C57BL/6J |
- PZ |
- 7d |
- AIR |
- C |
- B |
- 3 |
- 739.127 |
- 9.5 |
-
-
- | MB54 |
- 7 |
- C57BL/6J |
- PZ |
- 8h |
- AIR |
- C |
- B |
- 3 |
- 667.933 |
- 9.2 |
-
-
- | MB55 |
- 36 |
- C57BL/6J |
- NO |
- 3d |
- CIE |
- C |
- C |
- 3 |
- 605.937 |
- 9.2 |
-
-
- | MB56 |
- 43 |
- DBA/2J |
- PZ |
- 8h |
- AIR |
- C |
- C |
- 3 |
- 639.161 |
- 9.5 |
-
-
- | MB57 |
- 70 |
- DBA/2J |
- PZ |
- 7d |
- CIE |
- C |
- C |
- 3 |
- 630.735 |
- 9.4 |
-
-
- | MB58 |
- 59 |
- DBA/2J |
- NO |
- 3d |
- AIR |
- C |
- C |
- 3 |
- 548.647 |
- 9.5 |
-
-
- | MB59 |
- 15 |
- C57BL/6J |
- PZ |
- 14d |
- AIR |
- C |
- C |
- 3 |
- 689.793 |
- 9.4 |
-
-
- | MB60 |
- 27 |
- C57BL/6J |
- PZ |
- 8h |
- AIR |
- C |
- C |
- 3 |
- 580.462 |
- 9.4 |
-
-
- | MB61 |
- 30 |
- C57BL/6J |
- PZ |
- 3d |
- AIR |
- C |
- C |
- 3 |
- 577.826 |
- 8.2 |
-
-
- | MB62 |
- 57 |
- DBA/2J |
- PZ |
- 3d |
- AIR |
- C |
- C |
- 3 |
- 581.164 |
- 9.0 |
-
-
- | MB63 |
- 38 |
- C57BL/6J |
- PZ |
- 3d |
- CIE |
- C |
- C |
- 3 |
- 748.421 |
- 8.6 |
-
-
- | MB64 |
- 47 |
- DBA/2J |
- PZ |
- 8h |
- AIR |
- C |
- C |
- 3 |
- 747.345 |
- 8.5 |
-
-
-
diff --git a/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Ex_May17/specifics.rtf b/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Ex_May17/specifics.rtf
deleted file mode 100644
index 7c1a914..0000000
--- a/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Ex_May17/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Exon Level
\ No newline at end of file
diff --git a/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Ex_May17/summary.rtf b/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Ex_May17/summary.rtf
deleted file mode 100644
index 9baa040..0000000
--- a/general/datasets/INIA_UTHSC_Mid_AffyMTA1_Ex_May17/summary.rtf
+++ /dev/null
@@ -1,31 +0,0 @@
-Overview:
-
-1. Treated and whole brains dissected at Medical University of South Carolina (Marcelo F. Lopez laboratory)
-
-2. Frozen brains sub-dissected at UTHSC (Megan K. Mulligan laboratory)
-
-3. RNA extraction (Qiagen RNeasy kit) at UTHSC (Mulligan and Williams laboratories)
-
-4. Hybridized to Affymetrix Clariom D (aka Affymetrix MTA 1.0 ST) array at UTHSC MRC (Lorne Rose, UTHSC Molecular Resource Center)
-
-5. Initial QC and normalization (COMBAT) at UTHSC (Megan K. Mulligan laboratory)
-
-6. Transcriptome entry and phenotype entry (Arthur Centeno, Megan K. Mulligan, and Robert W. Williams)
-
-
-
-Chronic ethanol exposure:
-
-Mice were allowed to self-administer alcohol (15% v/v vs. water) for 2 h a day (5 days a week) 6 weeks prior to treatment in order to establish baseline consumption. Access to 15% alcohol versus water started 30 min prior to the start of the dark cycle. Following establishment of baseline drinking, male mice representative of each strain were separated into groups to be exposed to either weekly cycles of CIE exposure (CIE group) or air control (AIR group) exposure.
-
-
-
-Mice assigned to the CIE treatment group were exposed to alcohol vapor for 16 h a day followed by 8 h of withdrawal for 4 days per week. Following the fourth vapor exposure, mice were given a 72-h abstinence/withdrawal period before resuming ethanol intake in the home cage for 5 days. Mice in the AIR control treatment group were similarly treated but exposed only to air in the inhalation chambers. This pattern of CIE or air control exposure followed by 5 days of ethanol self-administration was repeated for four cycles. A fifth cycle of CIE (or air) exposure followed the fourth ethanol intake evaluation period, and brain tissue was collected at multiple time points (8h, 3d, 7d, 14d) after the last cycle ended. Pyrazole (1 mmol/kg) was used to stabilize blood ethanol levels (BEC) and was administered to both CIE and AIR groups. A subset of mice received no pyrazole.
-
-
-
-Analysis:
-
-1. Normalization on Affymetrix Expression Console (SST-RMA Gene Level).
-
-2. Batch effect detected (RNA concentration dependent) and corrected in ComBat
diff --git a/general/datasets/INIA_UTHSC_PFC_AffyMTA1_May17/summary.rtf b/general/datasets/INIA_UTHSC_PFC_AffyMTA1_May17/summary.rtf
deleted file mode 100644
index 153d98d..0000000
--- a/general/datasets/INIA_UTHSC_PFC_AffyMTA1_May17/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In working progress...
diff --git a/general/datasets/INIA_UTHSC_Str_AffyMTA1_May17/summary.rtf b/general/datasets/INIA_UTHSC_Str_AffyMTA1_May17/summary.rtf
deleted file mode 100644
index 153d98d..0000000
--- a/general/datasets/INIA_UTHSC_Str_AffyMTA1_May17/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In working progress...
diff --git a/general/datasets/IRCM_AXBXA_HRI0213/summary.rtf b/general/datasets/IRCM_AXBXA_HRI0213/summary.rtf
deleted file mode 100644
index ce6cd68..0000000
--- a/general/datasets/IRCM_AXBXA_HRI0213/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Expression data from hearts from 24 different AxB/BxA. Also the data are normalized and log2 transformed. All mice are males and 12 weeks.
diff --git a/general/datasets/Ibr_m_0106_p/acknowledgment.rtf b/general/datasets/Ibr_m_0106_p/acknowledgment.rtf
new file mode 100644
index 0000000..a1563a6
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_p/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data were generously provided by the NIAAA and its INIA grant program to RWW, Thomas Sutter, and Daniel Goldowitz (U01AA013515, U01AA013499-03S1, U01AA013488, U01AA013503-03S1). Support for the continued development of the GeneNetwork and WebQTL was provided by a NIMH Human Brain Project grant (P20MH062009). All arrays were processed at the University of Memphis by Thomas Sutter and colleagues with support of the INIA Bioanalytical Core.
diff --git a/general/datasets/Ibr_m_0106_p/cases.rtf b/general/datasets/Ibr_m_0106_p/cases.rtf
new file mode 100644
index 0000000..8794b88
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_p/cases.rtf
@@ -0,0 +1,5 @@
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory. BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues
+
+
+All stock was obtained originally from The Jackson Laboratory between 1999 and 2003. Most BXD animals were born and housed at the University of Tennessee Health Science Center. Some cases were bred at the University of Memphis (Douglas Matthews) or the University of Alabama (John Mountz and Hui-Chen Hsu).
+
diff --git a/general/datasets/Ibr_m_0106_p/notes.rtf b/general/datasets/Ibr_m_0106_p/notes.rtf
new file mode 100644
index 0000000..72bad83
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_p/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW, YHQ, and EJC, Oct 2004. Updated by RWW, Nov 5, 2004; April 7, 2005; RNA/tissue preparation protocol updatedby JLP, Sept 2, 2005; Sept 26, 2005.
+
diff --git a/general/datasets/Ibr_m_0106_p/platform.rtf b/general/datasets/Ibr_m_0106_p/platform.rtf
new file mode 100644
index 0000000..028fe23
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_p/platform.rtf
@@ -0,0 +1,3 @@
+
+
+Affymetrix Mouse Genome 430A and B array pairs: The 430A and B array pairs consist of 992936 25-nucleotide probes that collectively estimate the expression of approximately 39,000 transcripts. The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequences as the 430 2.0 series. However, we have found that roughy 75000 probes differ from those on A and B arrays and those on the 430 2.0
diff --git a/general/datasets/Ibr_m_0106_p/processing.rtf b/general/datasets/Ibr_m_0106_p/processing.rtf
new file mode 100644
index 0000000..243e5c0
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_p/processing.rtf
@@ -0,0 +1,20 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the two batches (n = 34 and n = 71 array pairs) at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7a: The 430A and 430B arrays include a set of 100 shared probe sets (a total of 2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the 430A and 430B arrays to a common scale. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression correction to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a small offset. The result of this step is that the mean of the 430A expression is fixed at a value of 8, whereas that of the 430B chip is typically reduced to 7. The average of the merged 430A and 430B array data set is approximately 7.5.
+ - Step 7b: We recentered the merged 430A and 430B data sets to a mean of 8 and a standard deviation of 2. This involved reapplying Steps 3 through 5.
+ - Step 8: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). The original CEL files were read into the R environment (Ihaka and Gentleman 1996). Data were processed using the Robust Multichip Average (RMA) method (Irrizary et al. 2003). Values were log2 transformed. Probe set values listed in WebQTL are the averages of biological replicates within strain. A few technical replicates were averaged and treated as single samples. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+This data set include further normalization to produce final estimates of expression that can be compared directly to the other transforms (average of 8 units and stabilized standard deviation of 2 units within each array). Please seee Bolstad and colleagues (2003) for a helpful comparison of RMA and two other common methods of processing Affymetrix array data sets.
+
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets included on the microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium May 2004 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Ibr_m_0106_p/summary.rtf b/general/datasets/Ibr_m_0106_p/summary.rtf
new file mode 100644
index 0000000..6fe94b1
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_p/summary.rtf
@@ -0,0 +1,3 @@
+
+This April 2005 data freeze provides estimates of mRNA expression in adult forebrain and midbrain from 45 lines of mice including C57BL/6J, DBA/2J, their F1 hybrids, and 42 BXD recombinant inbred strains. Data were generated at UTHSC and the University of Memphis with support from grants from the NIAAA Integrative Neuroscience Initiative on Alcoholism (INIA). Samples were hybridized in small pools (n = 3) to a total of 105 Affymetrix M430A and B array pairs. This particular data set was processed using the RMA protocol. To simplify comparisons among transforms, RMA values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Ibr_m_0106_p/tissue.rtf b/general/datasets/Ibr_m_0106_p/tissue.rtf
new file mode 100644
index 0000000..841d879
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_p/tissue.rtf
@@ -0,0 +1,977 @@
+The INIA M430 brain Database (April05) consists of 105 Affymetrix 430A and 430B microarray pairs. Each pair was hybridized in sequence (A array first, B array second) with a pool of brain tissue (forebrain minus olfactory bulb, plus the entire midbrain) taken from three adult animals of closely matched age and the same sex. RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai. All samples were subsequently processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center of Excellence by Thomas R. Sutter, Shirlean Goodwin, and colleagues at the University of Memphis.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. We have not yet achieved this goal. Ten of 45 strains are still represented by single sex samples: BXD2 (F), BXD8 (F), BXD15 (F), BXD18 (F), BXD25 (F), BXD29 (F), BXD33 (M), BXD45 (F), BXD77 (M), and BXD90 (M). Eleven strains are represented by three independent samples with the following breakdown by sex: C57BL/6J (1F 2M), DBA/2J (2F 2M), B6D2F1 (2F 2M) + D2B6F1 (1F 1M), BXD6 (2F 1M), BXD13 (2F 1M), BXD14 (1F 2M), BXD28 (2F 1M), BXD34 (1F 2M), BXD36 (1F 2M), BXD38 (1F 2M), BXD42 (1F 2M).
+
+Batch Structure: Before running the first batch of 30 pairs of array (dated Jan04), we ran four test samples (Nov03). The main batch of 30 includes the four test samples (four technical replicates). The Nov03 data was combined with the Jan04 data and was treated as a single batch that consists of one male and one female pool from C57BL/6J, DBA/2J, the B6D2F1 hybrid, 11 female BXD samples, and 11 male BXD samples. The second large batch was run February 2005 (Feb05) and consists of 71 pairs of arrays. Batch effects were corrected at the individual probe level as described below.
+
+The table below summarizes information on strain, sex, age, sample name, batch result date, and source of mice.
+
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Age |
+ Sample_name |
+ Result date |
+ Source |
+
+
+ | 1 |
+ C57BL/6J |
+ F |
+ 65 |
+ R0903F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 2 |
+ C57BL/6J |
+ F |
+ 65 |
+ R0903F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 3 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 4 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 5 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 6 |
+ C57BL/6J |
+ M |
+ 76 |
+ R0997F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 7 |
+ D2B6F1 |
+ F |
+ 57 |
+ R1066F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 8 |
+ D2B6F1 |
+ M |
+ 59 |
+ R1381F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 9 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 10 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 11 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F2 |
+ Jan04 |
+ UTM RW |
+
+
+ | 12 |
+ DBA/2J |
+ F |
+ 64 |
+ R1123F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 13 |
+ DBA/2J |
+ M |
+ 60 |
+ R0918F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 14 |
+ DBA/2J |
+ M |
+ 60 |
+ R0918F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 15 |
+ DBA/2J |
+ M |
+ 73 |
+ R1009F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 16 |
+ B6D2F1 |
+ F |
+ 127 |
+ R0919F1 |
+ Jan04 |
+ UTM JB |
+
+
+ | 17 |
+ B6D2F1 |
+ F |
+ 127 |
+ R0919F2 |
+ Jan04 |
+ UTM JB |
+
+
+ | 18 |
+ B6D2F1 |
+ F |
+ 64 |
+ R1053F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 19 |
+ B6D2F1 |
+ F |
+ 64 |
+ R1053F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 20 |
+ B6D2F1 |
+ M |
+ 127 |
+ R0920F1 |
+ Jan04 |
+ UTM JB |
+
+
+ | 21 |
+ B6D2F1 |
+ M |
+ 127 |
+ R0920F2 |
+ Jan04 |
+ UTM JB |
+
+
+ | 22 |
+ B6D2F1 |
+ M |
+ 66 |
+ R1057F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 23 |
+ BXD1 |
+ M |
+ 181 |
+ R0956F1 |
+ Feb05 |
+ UTM JB |
+
+
+ | 24 |
+ BXD1 |
+ F |
+ 95 |
+ R0895F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 25 |
+ BXD2 |
+ F |
+ 142 |
+ R0907F1 |
+ Feb05 |
+ UAB |
+
+
+ | 26 |
+ BXD5 |
+ F |
+ 56 |
+ R0744F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 27 |
+ BXD5 |
+ M |
+ 71 |
+ R0728F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 28 |
+ BXD6 |
+ F |
+ 57 |
+ R1711F1 |
+ Feb05 |
+ JAX |
+
+
+ | 29 |
+ BXD6 |
+ F |
+ 92 |
+ R0901F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 30 |
+ BXD6 |
+ M |
+ 92 |
+ R0902F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 31 |
+ BXD8 |
+ F |
+ 72 |
+ R0167F1 |
+ Jan04 |
+ UAB |
+
+
+ | 32 |
+ BXD9 |
+ F |
+ 86 |
+ R0908F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 33 |
+ BXD9 |
+ M |
+ 86 |
+ R0909F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 34 |
+ BXD11 |
+ F |
+ 97 |
+ R0745F1 |
+ Feb05 |
+ UAB |
+
+
+ | 35 |
+ BXD11 |
+ M |
+ 92 |
+ R0666F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 36 |
+ BXD12 |
+ F |
+ 64 |
+ R0896F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 37 |
+ BXD12 |
+ M |
+ 64 |
+ R0897F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 38 |
+ BXD13 |
+ F |
+ 86 |
+ R0730F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 39 |
+ BXD13 |
+ F |
+ 86 |
+ R0748F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 40 |
+ BXD13 |
+ M |
+ 76 |
+ R0929F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 41 |
+ BXD14 |
+ M |
+ 91 |
+ R0912F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 42 |
+ BXD14 |
+ M |
+ 68 |
+ R1051F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 43 |
+ BXD15 |
+ F |
+ 80 |
+ R0928F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 44 |
+ BXD18 |
+ F |
+ 108 |
+ R0771F1 |
+ Jan04 |
+ UAB |
+
+
+ | 45 |
+ BXD19 |
+ M |
+ 157 |
+ R1229F1 |
+ Feb05 |
+ UTM JB |
+
+
+ | 46 |
+ BXD19 |
+ F |
+ 56 |
+ R0236F1 |
+ Jan04 |
+ UAB |
+
+
+ | 47 |
+ BXD21 |
+ F |
+ 67 |
+ R0740F1 |
+ Jan04 |
+ UAB |
+
+
+ | 48 |
+ BXD21 |
+ F |
+ 67 |
+ R0740F1 |
+ Feb05 |
+ UAB |
+
+
+ | 49 |
+ BXD23 |
+ F |
+ 66 |
+ R1035F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 50 |
+ BXD23 |
+ M |
+ 66 |
+ R1037F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 51 |
+ BXD23 |
+ F |
+ 88 |
+ R0815F1 |
+ Jan04 |
+ UAB |
+
+
+ | 52 |
+ BXD23 |
+ F |
+ 88 |
+ R0815F1 |
+ Feb05 |
+ UAB |
+
+
+ | 53 |
+ BXD24 |
+ F |
+ 71 |
+ R0914F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 54 |
+ BXD24 |
+ M |
+ 71 |
+ R0913F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 55 |
+ BXD25 |
+ F |
+ 74 |
+ R0373F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 56 |
+ BXD28 |
+ F |
+ 79 |
+ R0910F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 57 |
+ BXD28 |
+ M |
+ 79 |
+ R0911F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 58 |
+ BXD28 |
+ F |
+ 113 |
+ R0892F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 59 |
+ BXD29 |
+ F |
+ 76 |
+ R0693F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 60 |
+ BXD31 |
+ F |
+ 61 |
+ R1199F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 61 |
+ BXD31 |
+ M |
+ 61 |
+ R1141F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 62 |
+ BXD32 |
+ F |
+ 93 |
+ R0898F1 |
+ Jan04 |
+ UAB |
+
+
+ | 63 |
+ BXD32 |
+ F |
+ 76 |
+ R1214F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 64 |
+ BXD32 |
+ M |
+ 65 |
+ R1478F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 65 |
+ BXD33 |
+ M |
+ 77 |
+ R0915F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 66 |
+ BXD34 |
+ F |
+ 92 |
+ R0900F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 67 |
+ BXD34 |
+ M |
+ 56 |
+ R0617F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 68 |
+ BXD34 |
+ M |
+ 72 |
+ R0916F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 69 |
+ BXD36 |
+ F |
+ 61 |
+ R1145F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 70 |
+ BXD36 |
+ M |
+ 77 |
+ R0926F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 71 |
+ BXD36 |
+ M |
+ 61 |
+ R1211F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 72 |
+ BXD38 |
+ M |
+ 83 |
+ R1208F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 73 |
+ BXD38 |
+ F |
+ 69 |
+ R0729F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 74 |
+ BXD38 |
+ M |
+ 69 |
+ R0731F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 75 |
+ BXD39 |
+ F |
+ 76 |
+ R1712F1 |
+ Feb05 |
+ JAX |
+
+
+ | 76 |
+ BXD39 |
+ M |
+ 71 |
+ R0602F1 |
+ Feb05 |
+ UAB |
+
+
+ | 77 |
+ BXD40 |
+ F |
+ 184 |
+ R0741F1 |
+ Feb05 |
+ UAB |
+
+
+ | 78 |
+ BXD40 |
+ M |
+ 56 |
+ R0894F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 79 |
+ BXD42 |
+ F |
+ 100 |
+ R0742F1 |
+ Feb05 |
+ UAB |
+
+
+ | 80 |
+ BXD42 |
+ M |
+ 97 |
+ R0936F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 81 |
+ BXD42 |
+ M |
+ 105 |
+ R0937F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 82 |
+ BXD43 |
+ M |
+ 63 |
+ R1047F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 83 |
+ BXD44 |
+ F |
+ 57 |
+ R1069F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 84 |
+ BXD44 |
+ M |
+ 58 |
+ R1072F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 85 |
+ BXD45 |
+ F |
+ 58 |
+ R1398F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 86 |
+ BXD48 |
+ F |
+ 59 |
+ R0946F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 87 |
+ BXD48 |
+ M |
+ 64 |
+ R0970F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 88 |
+ BXD51 |
+ F |
+ 63 |
+ R1430F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 89 |
+ BXD51 |
+ M |
+ 65 |
+ R1001F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 90 |
+ BXD60 |
+ F |
+ 64 |
+ R0976F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 91 |
+ BXD60 |
+ M |
+ 59 |
+ R1075F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 92 |
+ BXD62 |
+ F |
+ 59 |
+ R1033F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 93 |
+ BXD62 |
+ M |
+ 58 |
+ R1027F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 94 |
+ BXD69 |
+ F |
+ 60 |
+ R1438F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 95 |
+ BXD69 |
+ M |
+ 64 |
+ R1193F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 96 |
+ BXD73 |
+ F |
+ 60 |
+ R1275F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 97 |
+ BXD73 |
+ M |
+ 76 |
+ R1442F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 98 |
+ BXD77 |
+ M |
+ 61 |
+ R1426F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 99 |
+ BXD86 |
+ F |
+ 77 |
+ R1414F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 100 |
+ BXD86 |
+ M |
+ 77 |
+ R1418F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 101 |
+ BXD87 |
+ F |
+ 89 |
+ R1713F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 102 |
+ BXD87 |
+ M |
+ 84 |
+ R1709F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 103 |
+ BXD90 |
+ M |
+ 61 |
+ R1452F |
+ Feb05 |
+ UTM RW |
+
+
+ | 104 |
+ BXD92 |
+ F |
+ 58 |
+ R1299F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 105 |
+ BXD92 |
+ M |
+ 59 |
+ R1307F1 |
+ Feb05 |
+ UTM RW |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Ibr_m_0106_r/acknowledgment.rtf b/general/datasets/Ibr_m_0106_r/acknowledgment.rtf
new file mode 100644
index 0000000..a1563a6
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data were generously provided by the NIAAA and its INIA grant program to RWW, Thomas Sutter, and Daniel Goldowitz (U01AA013515, U01AA013499-03S1, U01AA013488, U01AA013503-03S1). Support for the continued development of the GeneNetwork and WebQTL was provided by a NIMH Human Brain Project grant (P20MH062009). All arrays were processed at the University of Memphis by Thomas Sutter and colleagues with support of the INIA Bioanalytical Core.
diff --git a/general/datasets/Ibr_m_0106_r/cases.rtf b/general/datasets/Ibr_m_0106_r/cases.rtf
new file mode 100644
index 0000000..8794b88
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_r/cases.rtf
@@ -0,0 +1,5 @@
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory. BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues
+
+
+All stock was obtained originally from The Jackson Laboratory between 1999 and 2003. Most BXD animals were born and housed at the University of Tennessee Health Science Center. Some cases were bred at the University of Memphis (Douglas Matthews) or the University of Alabama (John Mountz and Hui-Chen Hsu).
+
diff --git a/general/datasets/Ibr_m_0106_r/notes.rtf b/general/datasets/Ibr_m_0106_r/notes.rtf
new file mode 100644
index 0000000..72bad83
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW, YHQ, and EJC, Oct 2004. Updated by RWW, Nov 5, 2004; April 7, 2005; RNA/tissue preparation protocol updatedby JLP, Sept 2, 2005; Sept 26, 2005.
+
diff --git a/general/datasets/Ibr_m_0106_r/platform.rtf b/general/datasets/Ibr_m_0106_r/platform.rtf
new file mode 100644
index 0000000..028fe23
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_r/platform.rtf
@@ -0,0 +1,3 @@
+
+
+Affymetrix Mouse Genome 430A and B array pairs: The 430A and B array pairs consist of 992936 25-nucleotide probes that collectively estimate the expression of approximately 39,000 transcripts. The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequences as the 430 2.0 series. However, we have found that roughy 75000 probes differ from those on A and B arrays and those on the 430 2.0
diff --git a/general/datasets/Ibr_m_0106_r/processing.rtf b/general/datasets/Ibr_m_0106_r/processing.rtf
new file mode 100644
index 0000000..243e5c0
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_r/processing.rtf
@@ -0,0 +1,20 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the two batches (n = 34 and n = 71 array pairs) at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7a: The 430A and 430B arrays include a set of 100 shared probe sets (a total of 2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the 430A and 430B arrays to a common scale. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression correction to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a small offset. The result of this step is that the mean of the 430A expression is fixed at a value of 8, whereas that of the 430B chip is typically reduced to 7. The average of the merged 430A and 430B array data set is approximately 7.5.
+ - Step 7b: We recentered the merged 430A and 430B data sets to a mean of 8 and a standard deviation of 2. This involved reapplying Steps 3 through 5.
+ - Step 8: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). The original CEL files were read into the R environment (Ihaka and Gentleman 1996). Data were processed using the Robust Multichip Average (RMA) method (Irrizary et al. 2003). Values were log2 transformed. Probe set values listed in WebQTL are the averages of biological replicates within strain. A few technical replicates were averaged and treated as single samples. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+This data set include further normalization to produce final estimates of expression that can be compared directly to the other transforms (average of 8 units and stabilized standard deviation of 2 units within each array). Please seee Bolstad and colleagues (2003) for a helpful comparison of RMA and two other common methods of processing Affymetrix array data sets.
+
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets included on the microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium May 2004 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Ibr_m_0106_r/summary.rtf b/general/datasets/Ibr_m_0106_r/summary.rtf
new file mode 100644
index 0000000..6fe94b1
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_r/summary.rtf
@@ -0,0 +1,3 @@
+
+This April 2005 data freeze provides estimates of mRNA expression in adult forebrain and midbrain from 45 lines of mice including C57BL/6J, DBA/2J, their F1 hybrids, and 42 BXD recombinant inbred strains. Data were generated at UTHSC and the University of Memphis with support from grants from the NIAAA Integrative Neuroscience Initiative on Alcoholism (INIA). Samples were hybridized in small pools (n = 3) to a total of 105 Affymetrix M430A and B array pairs. This particular data set was processed using the RMA protocol. To simplify comparisons among transforms, RMA values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Ibr_m_0106_r/tissue.rtf b/general/datasets/Ibr_m_0106_r/tissue.rtf
new file mode 100644
index 0000000..841d879
--- /dev/null
+++ b/general/datasets/Ibr_m_0106_r/tissue.rtf
@@ -0,0 +1,977 @@
+The INIA M430 brain Database (April05) consists of 105 Affymetrix 430A and 430B microarray pairs. Each pair was hybridized in sequence (A array first, B array second) with a pool of brain tissue (forebrain minus olfactory bulb, plus the entire midbrain) taken from three adult animals of closely matched age and the same sex. RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai. All samples were subsequently processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center of Excellence by Thomas R. Sutter, Shirlean Goodwin, and colleagues at the University of Memphis.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. We have not yet achieved this goal. Ten of 45 strains are still represented by single sex samples: BXD2 (F), BXD8 (F), BXD15 (F), BXD18 (F), BXD25 (F), BXD29 (F), BXD33 (M), BXD45 (F), BXD77 (M), and BXD90 (M). Eleven strains are represented by three independent samples with the following breakdown by sex: C57BL/6J (1F 2M), DBA/2J (2F 2M), B6D2F1 (2F 2M) + D2B6F1 (1F 1M), BXD6 (2F 1M), BXD13 (2F 1M), BXD14 (1F 2M), BXD28 (2F 1M), BXD34 (1F 2M), BXD36 (1F 2M), BXD38 (1F 2M), BXD42 (1F 2M).
+
+Batch Structure: Before running the first batch of 30 pairs of array (dated Jan04), we ran four test samples (Nov03). The main batch of 30 includes the four test samples (four technical replicates). The Nov03 data was combined with the Jan04 data and was treated as a single batch that consists of one male and one female pool from C57BL/6J, DBA/2J, the B6D2F1 hybrid, 11 female BXD samples, and 11 male BXD samples. The second large batch was run February 2005 (Feb05) and consists of 71 pairs of arrays. Batch effects were corrected at the individual probe level as described below.
+
+The table below summarizes information on strain, sex, age, sample name, batch result date, and source of mice.
+
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Age |
+ Sample_name |
+ Result date |
+ Source |
+
+
+ | 1 |
+ C57BL/6J |
+ F |
+ 65 |
+ R0903F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 2 |
+ C57BL/6J |
+ F |
+ 65 |
+ R0903F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 3 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 4 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 5 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 6 |
+ C57BL/6J |
+ M |
+ 76 |
+ R0997F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 7 |
+ D2B6F1 |
+ F |
+ 57 |
+ R1066F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 8 |
+ D2B6F1 |
+ M |
+ 59 |
+ R1381F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 9 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 10 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 11 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F2 |
+ Jan04 |
+ UTM RW |
+
+
+ | 12 |
+ DBA/2J |
+ F |
+ 64 |
+ R1123F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 13 |
+ DBA/2J |
+ M |
+ 60 |
+ R0918F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 14 |
+ DBA/2J |
+ M |
+ 60 |
+ R0918F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 15 |
+ DBA/2J |
+ M |
+ 73 |
+ R1009F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 16 |
+ B6D2F1 |
+ F |
+ 127 |
+ R0919F1 |
+ Jan04 |
+ UTM JB |
+
+
+ | 17 |
+ B6D2F1 |
+ F |
+ 127 |
+ R0919F2 |
+ Jan04 |
+ UTM JB |
+
+
+ | 18 |
+ B6D2F1 |
+ F |
+ 64 |
+ R1053F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 19 |
+ B6D2F1 |
+ F |
+ 64 |
+ R1053F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 20 |
+ B6D2F1 |
+ M |
+ 127 |
+ R0920F1 |
+ Jan04 |
+ UTM JB |
+
+
+ | 21 |
+ B6D2F1 |
+ M |
+ 127 |
+ R0920F2 |
+ Jan04 |
+ UTM JB |
+
+
+ | 22 |
+ B6D2F1 |
+ M |
+ 66 |
+ R1057F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 23 |
+ BXD1 |
+ M |
+ 181 |
+ R0956F1 |
+ Feb05 |
+ UTM JB |
+
+
+ | 24 |
+ BXD1 |
+ F |
+ 95 |
+ R0895F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 25 |
+ BXD2 |
+ F |
+ 142 |
+ R0907F1 |
+ Feb05 |
+ UAB |
+
+
+ | 26 |
+ BXD5 |
+ F |
+ 56 |
+ R0744F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 27 |
+ BXD5 |
+ M |
+ 71 |
+ R0728F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 28 |
+ BXD6 |
+ F |
+ 57 |
+ R1711F1 |
+ Feb05 |
+ JAX |
+
+
+ | 29 |
+ BXD6 |
+ F |
+ 92 |
+ R0901F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 30 |
+ BXD6 |
+ M |
+ 92 |
+ R0902F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 31 |
+ BXD8 |
+ F |
+ 72 |
+ R0167F1 |
+ Jan04 |
+ UAB |
+
+
+ | 32 |
+ BXD9 |
+ F |
+ 86 |
+ R0908F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 33 |
+ BXD9 |
+ M |
+ 86 |
+ R0909F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 34 |
+ BXD11 |
+ F |
+ 97 |
+ R0745F1 |
+ Feb05 |
+ UAB |
+
+
+ | 35 |
+ BXD11 |
+ M |
+ 92 |
+ R0666F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 36 |
+ BXD12 |
+ F |
+ 64 |
+ R0896F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 37 |
+ BXD12 |
+ M |
+ 64 |
+ R0897F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 38 |
+ BXD13 |
+ F |
+ 86 |
+ R0730F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 39 |
+ BXD13 |
+ F |
+ 86 |
+ R0748F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 40 |
+ BXD13 |
+ M |
+ 76 |
+ R0929F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 41 |
+ BXD14 |
+ M |
+ 91 |
+ R0912F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 42 |
+ BXD14 |
+ M |
+ 68 |
+ R1051F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 43 |
+ BXD15 |
+ F |
+ 80 |
+ R0928F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 44 |
+ BXD18 |
+ F |
+ 108 |
+ R0771F1 |
+ Jan04 |
+ UAB |
+
+
+ | 45 |
+ BXD19 |
+ M |
+ 157 |
+ R1229F1 |
+ Feb05 |
+ UTM JB |
+
+
+ | 46 |
+ BXD19 |
+ F |
+ 56 |
+ R0236F1 |
+ Jan04 |
+ UAB |
+
+
+ | 47 |
+ BXD21 |
+ F |
+ 67 |
+ R0740F1 |
+ Jan04 |
+ UAB |
+
+
+ | 48 |
+ BXD21 |
+ F |
+ 67 |
+ R0740F1 |
+ Feb05 |
+ UAB |
+
+
+ | 49 |
+ BXD23 |
+ F |
+ 66 |
+ R1035F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 50 |
+ BXD23 |
+ M |
+ 66 |
+ R1037F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 51 |
+ BXD23 |
+ F |
+ 88 |
+ R0815F1 |
+ Jan04 |
+ UAB |
+
+
+ | 52 |
+ BXD23 |
+ F |
+ 88 |
+ R0815F1 |
+ Feb05 |
+ UAB |
+
+
+ | 53 |
+ BXD24 |
+ F |
+ 71 |
+ R0914F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 54 |
+ BXD24 |
+ M |
+ 71 |
+ R0913F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 55 |
+ BXD25 |
+ F |
+ 74 |
+ R0373F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 56 |
+ BXD28 |
+ F |
+ 79 |
+ R0910F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 57 |
+ BXD28 |
+ M |
+ 79 |
+ R0911F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 58 |
+ BXD28 |
+ F |
+ 113 |
+ R0892F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 59 |
+ BXD29 |
+ F |
+ 76 |
+ R0693F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 60 |
+ BXD31 |
+ F |
+ 61 |
+ R1199F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 61 |
+ BXD31 |
+ M |
+ 61 |
+ R1141F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 62 |
+ BXD32 |
+ F |
+ 93 |
+ R0898F1 |
+ Jan04 |
+ UAB |
+
+
+ | 63 |
+ BXD32 |
+ F |
+ 76 |
+ R1214F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 64 |
+ BXD32 |
+ M |
+ 65 |
+ R1478F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 65 |
+ BXD33 |
+ M |
+ 77 |
+ R0915F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 66 |
+ BXD34 |
+ F |
+ 92 |
+ R0900F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 67 |
+ BXD34 |
+ M |
+ 56 |
+ R0617F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 68 |
+ BXD34 |
+ M |
+ 72 |
+ R0916F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 69 |
+ BXD36 |
+ F |
+ 61 |
+ R1145F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 70 |
+ BXD36 |
+ M |
+ 77 |
+ R0926F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 71 |
+ BXD36 |
+ M |
+ 61 |
+ R1211F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 72 |
+ BXD38 |
+ M |
+ 83 |
+ R1208F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 73 |
+ BXD38 |
+ F |
+ 69 |
+ R0729F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 74 |
+ BXD38 |
+ M |
+ 69 |
+ R0731F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 75 |
+ BXD39 |
+ F |
+ 76 |
+ R1712F1 |
+ Feb05 |
+ JAX |
+
+
+ | 76 |
+ BXD39 |
+ M |
+ 71 |
+ R0602F1 |
+ Feb05 |
+ UAB |
+
+
+ | 77 |
+ BXD40 |
+ F |
+ 184 |
+ R0741F1 |
+ Feb05 |
+ UAB |
+
+
+ | 78 |
+ BXD40 |
+ M |
+ 56 |
+ R0894F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 79 |
+ BXD42 |
+ F |
+ 100 |
+ R0742F1 |
+ Feb05 |
+ UAB |
+
+
+ | 80 |
+ BXD42 |
+ M |
+ 97 |
+ R0936F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 81 |
+ BXD42 |
+ M |
+ 105 |
+ R0937F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 82 |
+ BXD43 |
+ M |
+ 63 |
+ R1047F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 83 |
+ BXD44 |
+ F |
+ 57 |
+ R1069F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 84 |
+ BXD44 |
+ M |
+ 58 |
+ R1072F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 85 |
+ BXD45 |
+ F |
+ 58 |
+ R1398F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 86 |
+ BXD48 |
+ F |
+ 59 |
+ R0946F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 87 |
+ BXD48 |
+ M |
+ 64 |
+ R0970F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 88 |
+ BXD51 |
+ F |
+ 63 |
+ R1430F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 89 |
+ BXD51 |
+ M |
+ 65 |
+ R1001F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 90 |
+ BXD60 |
+ F |
+ 64 |
+ R0976F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 91 |
+ BXD60 |
+ M |
+ 59 |
+ R1075F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 92 |
+ BXD62 |
+ F |
+ 59 |
+ R1033F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 93 |
+ BXD62 |
+ M |
+ 58 |
+ R1027F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 94 |
+ BXD69 |
+ F |
+ 60 |
+ R1438F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 95 |
+ BXD69 |
+ M |
+ 64 |
+ R1193F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 96 |
+ BXD73 |
+ F |
+ 60 |
+ R1275F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 97 |
+ BXD73 |
+ M |
+ 76 |
+ R1442F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 98 |
+ BXD77 |
+ M |
+ 61 |
+ R1426F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 99 |
+ BXD86 |
+ F |
+ 77 |
+ R1414F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 100 |
+ BXD86 |
+ M |
+ 77 |
+ R1418F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 101 |
+ BXD87 |
+ F |
+ 89 |
+ R1713F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 102 |
+ BXD87 |
+ M |
+ 84 |
+ R1709F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 103 |
+ BXD90 |
+ M |
+ 61 |
+ R1452F |
+ Feb05 |
+ UTM RW |
+
+
+ | 104 |
+ BXD92 |
+ F |
+ 58 |
+ R1299F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 105 |
+ BXD92 |
+ M |
+ 59 |
+ R1307F1 |
+ Feb05 |
+ UTM RW |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Ibr_m_0204_m/acknowledgment.rtf b/general/datasets/Ibr_m_0204_m/acknowledgment.rtf
new file mode 100644
index 0000000..7b62a11
--- /dev/null
+++ b/general/datasets/Ibr_m_0204_m/acknowledgment.rtf
@@ -0,0 +1 @@
+Data for the microarrays were generously provided by support from NIAAA INIA grants to RWW and Thomas Sutter. Support for sample acquistion and WebQTL have been provided by NIMH Human Brain Project, and the Dunavant Chair of Excellence, University of Tennessee Health Science Center. All arrays were processed at the University of Memphis by Dr. Thomas Sutter and colleagues with support of the INIA Bioanalytical Core.
diff --git a/general/datasets/Ibr_m_0204_m/cases.rtf b/general/datasets/Ibr_m_0204_m/cases.rtf
new file mode 100644
index 0000000..9dc5cbe
--- /dev/null
+++ b/general/datasets/Ibr_m_0204_m/cases.rtf
@@ -0,0 +1,3 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B) and DBA/2J (D). Both B and D strains have been almost fully sequence (8x coverage for B by a public consortium and approximately 1.5x coverage for D by Celera).
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine.
diff --git a/general/datasets/Ibr_m_0204_m/notes.rtf b/general/datasets/Ibr_m_0204_m/notes.rtf
new file mode 100644
index 0000000..f3ea488
--- /dev/null
+++ b/general/datasets/Ibr_m_0204_m/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, Oct 2004. Updated by RWW, Nov 5, 2004.
diff --git a/general/datasets/Ibr_m_0204_m/platform.rtf b/general/datasets/Ibr_m_0204_m/platform.rtf
new file mode 100644
index 0000000..51cbff2
--- /dev/null
+++ b/general/datasets/Ibr_m_0204_m/platform.rtf
@@ -0,0 +1 @@
+Affymetrix 430A and 430B GeneChip Set: Expression data were generated using 430AB array pairs. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on either the Verify UCSC and Verify Ensembl links in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Ibr_m_0204_m/processing.rtf b/general/datasets/Ibr_m_0204_m/processing.rtf
new file mode 100644
index 0000000..4663b88
--- /dev/null
+++ b/general/datasets/Ibr_m_0204_m/processing.rtf
@@ -0,0 +1,29 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each probe signal.
+ - Step 3: We computed the Z scores for each probe signal.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B arrays include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes provide a way to calibrate expression of the A and B arrays to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: We corrected for technical variance introduced by two batches. Means separated by the first batch for each gene are corrected same as means of the second batch.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have modest numbers of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+
+
+
+Probe set data: The original expression values in the Affymetrix CEL files were read into PerfectMatch to generate the normalized PDNN data set.
+
+PDNN values of each array were subsequently normalized to a achieve a mean value of 8 units and a variance of 2 units.
+
+When necessary, we computed the arithmetic mean for technical replicates and treated these as single samples. We then computed the arithmetic mean for the set of 2 to 5 biological replicates for each strain.
+
+
+About the array probe sets names:
+
+
+Most probe sets on the mouse 430A and 430B arrays consist of a total of 22 probes, divided into 11 perfect match(PM) probes and 11 mismatch (MM) controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, several suffix characters that highlight design features, a a final A or B character to specify the array pair member. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene.
+
diff --git a/general/datasets/Ibr_m_0204_m/summary.rtf b/general/datasets/Ibr_m_0204_m/summary.rtf
new file mode 100644
index 0000000..c32676a
--- /dev/null
+++ b/general/datasets/Ibr_m_0204_m/summary.rtf
@@ -0,0 +1 @@
+This October 2004 data freeze provides initial estimates of mRNA expression in brains of adult BXD recombinant inbred mice measured using Affymetrix M430AB microarrays. In contast to the U74Av2 array, this new data set provides broader coverage (~45,000 transcripts) but does not include replicates or as many strains (25 vs 35). Data were generated at UTHSC and the University of Memphis with support from grants from the NIAAA Integrative Neuroscience Initiative on Alcoholism (INIA). Data were processed using the PDNN method of Zhang. To simplify comparison among transforms, PDNN values of each array were adjusted to an average of 8 units and a variance of 2 units.
diff --git a/general/datasets/Ibr_m_0204_m/tissue.rtf b/general/datasets/Ibr_m_0204_m/tissue.rtf
new file mode 100644
index 0000000..cac878a
--- /dev/null
+++ b/general/datasets/Ibr_m_0204_m/tissue.rtf
@@ -0,0 +1,261 @@
+The data set consists of a single batch of Affymetrix mouse expression 430A and 430B GeneChip array pairs. Each AB pair was hybridized in sequence (A array first, B array second) with a pool of brain tissue (forebrain minus olfactory bulb, plus the entire midbrain) taken from three adult animals of closely matched age and the same sex. RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai. All samples were subsequently processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center of Excellence by Thomas R. Sutter and colleagues at the University of Memphis. Before running the main batch of 30 pairs of array, we ran four "test" samples (one male and one female pool from each of the two parental strains, C57BL/6J and DBA/2J). The main set of 30 array pairs includes the same four samples (in other words we have four technical replicates), two F1 hybrid sample (each run two times for a within-batch technical replication), and 22 BXD strains. The data set therefore consists of one male and one female pool from C57BL/6J, DBA/2J, the B6D2F1 hybrid, 11 female BXD samples, and 11 male BXD samples. We should note that the four technical replicates between batches were eventually combined with a correction for a highly significant batch effect. This was done at both the probe and probe set levels to "align" the test batch values with the two main batches. (The ratio of the probe average in the four test arrays to the average of the same probe in the four corresponding main batch arrays was used as a correction factor.) The F1 within-batch technical replicates were simply averaged. In the next batch we will reverse the sex of the BXD samples to achieve a balance with at least 22 BXD strains with one male and one female sample each.
+
+The table below lists the arrays by strain, sex, age, sample identifier, and data results were obtained from the Bioanalytical Core at the University of Memphis. Each array was hybridized to a pool of mRNA from three mice.
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Date |
+
+
+ | B6D2F1 |
+ F |
+ 127 |
+ 919-F1 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ F |
+ 127 |
+ 919-F2 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 920-F1 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 920-F2 |
+ Jan04 |
+
+
+ | C57BL/6J |
+ F |
+ 65 |
+ 903-F1 |
+ Nov03 |
+
+
+ | C57BL/6J |
+ F |
+ 65 |
+ 903-F2 |
+ Jan03 |
+
+
+ | C57BL/6J |
+ M |
+ 66 |
+ 906-F1 |
+ Nov03 |
+
+
+ | C57BL/6J |
+ M |
+ 66 |
+ 906-F2 |
+ Jan04 |
+
+
+ | DBA/2J |
+ F |
+ 60 |
+ 917-F1 |
+ Nov03 |
+
+
+ | DBA/2J |
+ F |
+ 60 |
+ 917-F2 |
+ Jan04 |
+
+
+ | DBA/2J |
+ M |
+ 60 |
+ 918-F1 |
+ Nov03 |
+
+
+ | DBA/2J |
+ M |
+ 60 |
+ 918-F2 |
+ Jan04 |
+
+
+ | BXD1 |
+ F |
+ 95 |
+ 895-F1 |
+ Jan04 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 728-F1 |
+ Jan04 |
+
+
+ | BXD6 |
+ M |
+ 92 |
+ 902-F1 |
+ Jan04 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S167-F1 |
+ Jan04 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 909-F1 |
+ Jan04 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 897-F1 |
+ Jan04 |
+
+
+ | BXD13 |
+ F |
+ 86 |
+ 748-F1 |
+ Jan04 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 912-F1 |
+ Jan04 |
+
+
+ | BXD18 |
+ F |
+ 108 |
+ 771-F1 |
+ Jan04 |
+
+
+ | BXD19 |
+ F |
+ 56 |
+ S236-F1 |
+ Jan04 |
+
+
+ | BXD21 |
+ F |
+ 67 |
+ 740-F1 |
+ Jan04 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 815-F1 |
+ Jan04 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 913-F1 |
+ Jan04 |
+
+
+ | BXD25 |
+ F |
+ 74 |
+ S373-F1 |
+ Jan04 |
+
+
+ | BXD28 |
+ F |
+ 79 |
+ 910-F1 |
+ Jan04 |
+
+
+ | BXD29 |
+ F |
+ 76 |
+ 693-F1 |
+ Jan04 |
+
+
+ | BXD32 |
+ F |
+ 93 |
+ 898-F1 |
+ Jan04 |
+
+
+ | BXD33 |
+ M |
+ 77 |
+ 915-F1 |
+ Jan04 |
+
+
+ | BXD34 |
+ M |
+ 72 |
+ 916-F1 |
+ Jan04 |
+
+
+ | BXD36 |
+ M |
+ 77 |
+ 926-F1 |
+ Jan04 |
+
+
+ | BXD38 |
+ M |
+ 69 |
+ 731-F1 |
+ Jan04 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 936-F1 |
+ Jan04 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Ibr_m_0405_m/acknowledgment.rtf b/general/datasets/Ibr_m_0405_m/acknowledgment.rtf
new file mode 100644
index 0000000..a1563a6
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_m/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data were generously provided by the NIAAA and its INIA grant program to RWW, Thomas Sutter, and Daniel Goldowitz (U01AA013515, U01AA013499-03S1, U01AA013488, U01AA013503-03S1). Support for the continued development of the GeneNetwork and WebQTL was provided by a NIMH Human Brain Project grant (P20MH062009). All arrays were processed at the University of Memphis by Thomas Sutter and colleagues with support of the INIA Bioanalytical Core.
diff --git a/general/datasets/Ibr_m_0405_m/cases.rtf b/general/datasets/Ibr_m_0405_m/cases.rtf
new file mode 100644
index 0000000..8794b88
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_m/cases.rtf
@@ -0,0 +1,5 @@
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory. BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues
+
+
+All stock was obtained originally from The Jackson Laboratory between 1999 and 2003. Most BXD animals were born and housed at the University of Tennessee Health Science Center. Some cases were bred at the University of Memphis (Douglas Matthews) or the University of Alabama (John Mountz and Hui-Chen Hsu).
+
diff --git a/general/datasets/Ibr_m_0405_m/notes.rtf b/general/datasets/Ibr_m_0405_m/notes.rtf
new file mode 100644
index 0000000..72bad83
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_m/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW, YHQ, and EJC, Oct 2004. Updated by RWW, Nov 5, 2004; April 7, 2005; RNA/tissue preparation protocol updatedby JLP, Sept 2, 2005; Sept 26, 2005.
+
diff --git a/general/datasets/Ibr_m_0405_m/platform.rtf b/general/datasets/Ibr_m_0405_m/platform.rtf
new file mode 100644
index 0000000..028fe23
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_m/platform.rtf
@@ -0,0 +1,3 @@
+
+
+Affymetrix Mouse Genome 430A and B array pairs: The 430A and B array pairs consist of 992936 25-nucleotide probes that collectively estimate the expression of approximately 39,000 transcripts. The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequences as the 430 2.0 series. However, we have found that roughy 75000 probes differ from those on A and B arrays and those on the 430 2.0
diff --git a/general/datasets/Ibr_m_0405_m/processing.rtf b/general/datasets/Ibr_m_0405_m/processing.rtf
new file mode 100644
index 0000000..243e5c0
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_m/processing.rtf
@@ -0,0 +1,20 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the two batches (n = 34 and n = 71 array pairs) at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7a: The 430A and 430B arrays include a set of 100 shared probe sets (a total of 2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the 430A and 430B arrays to a common scale. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression correction to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a small offset. The result of this step is that the mean of the 430A expression is fixed at a value of 8, whereas that of the 430B chip is typically reduced to 7. The average of the merged 430A and 430B array data set is approximately 7.5.
+ - Step 7b: We recentered the merged 430A and 430B data sets to a mean of 8 and a standard deviation of 2. This involved reapplying Steps 3 through 5.
+ - Step 8: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). The original CEL files were read into the R environment (Ihaka and Gentleman 1996). Data were processed using the Robust Multichip Average (RMA) method (Irrizary et al. 2003). Values were log2 transformed. Probe set values listed in WebQTL are the averages of biological replicates within strain. A few technical replicates were averaged and treated as single samples. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+This data set include further normalization to produce final estimates of expression that can be compared directly to the other transforms (average of 8 units and stabilized standard deviation of 2 units within each array). Please seee Bolstad and colleagues (2003) for a helpful comparison of RMA and two other common methods of processing Affymetrix array data sets.
+
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets included on the microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium May 2004 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Ibr_m_0405_m/summary.rtf b/general/datasets/Ibr_m_0405_m/summary.rtf
new file mode 100644
index 0000000..6fe94b1
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_m/summary.rtf
@@ -0,0 +1,3 @@
+
+This April 2005 data freeze provides estimates of mRNA expression in adult forebrain and midbrain from 45 lines of mice including C57BL/6J, DBA/2J, their F1 hybrids, and 42 BXD recombinant inbred strains. Data were generated at UTHSC and the University of Memphis with support from grants from the NIAAA Integrative Neuroscience Initiative on Alcoholism (INIA). Samples were hybridized in small pools (n = 3) to a total of 105 Affymetrix M430A and B array pairs. This particular data set was processed using the RMA protocol. To simplify comparisons among transforms, RMA values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Ibr_m_0405_m/tissue.rtf b/general/datasets/Ibr_m_0405_m/tissue.rtf
new file mode 100644
index 0000000..841d879
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_m/tissue.rtf
@@ -0,0 +1,977 @@
+The INIA M430 brain Database (April05) consists of 105 Affymetrix 430A and 430B microarray pairs. Each pair was hybridized in sequence (A array first, B array second) with a pool of brain tissue (forebrain minus olfactory bulb, plus the entire midbrain) taken from three adult animals of closely matched age and the same sex. RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai. All samples were subsequently processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center of Excellence by Thomas R. Sutter, Shirlean Goodwin, and colleagues at the University of Memphis.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. We have not yet achieved this goal. Ten of 45 strains are still represented by single sex samples: BXD2 (F), BXD8 (F), BXD15 (F), BXD18 (F), BXD25 (F), BXD29 (F), BXD33 (M), BXD45 (F), BXD77 (M), and BXD90 (M). Eleven strains are represented by three independent samples with the following breakdown by sex: C57BL/6J (1F 2M), DBA/2J (2F 2M), B6D2F1 (2F 2M) + D2B6F1 (1F 1M), BXD6 (2F 1M), BXD13 (2F 1M), BXD14 (1F 2M), BXD28 (2F 1M), BXD34 (1F 2M), BXD36 (1F 2M), BXD38 (1F 2M), BXD42 (1F 2M).
+
+Batch Structure: Before running the first batch of 30 pairs of array (dated Jan04), we ran four test samples (Nov03). The main batch of 30 includes the four test samples (four technical replicates). The Nov03 data was combined with the Jan04 data and was treated as a single batch that consists of one male and one female pool from C57BL/6J, DBA/2J, the B6D2F1 hybrid, 11 female BXD samples, and 11 male BXD samples. The second large batch was run February 2005 (Feb05) and consists of 71 pairs of arrays. Batch effects were corrected at the individual probe level as described below.
+
+The table below summarizes information on strain, sex, age, sample name, batch result date, and source of mice.
+
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Age |
+ Sample_name |
+ Result date |
+ Source |
+
+
+ | 1 |
+ C57BL/6J |
+ F |
+ 65 |
+ R0903F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 2 |
+ C57BL/6J |
+ F |
+ 65 |
+ R0903F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 3 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 4 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 5 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 6 |
+ C57BL/6J |
+ M |
+ 76 |
+ R0997F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 7 |
+ D2B6F1 |
+ F |
+ 57 |
+ R1066F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 8 |
+ D2B6F1 |
+ M |
+ 59 |
+ R1381F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 9 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 10 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 11 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F2 |
+ Jan04 |
+ UTM RW |
+
+
+ | 12 |
+ DBA/2J |
+ F |
+ 64 |
+ R1123F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 13 |
+ DBA/2J |
+ M |
+ 60 |
+ R0918F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 14 |
+ DBA/2J |
+ M |
+ 60 |
+ R0918F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 15 |
+ DBA/2J |
+ M |
+ 73 |
+ R1009F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 16 |
+ B6D2F1 |
+ F |
+ 127 |
+ R0919F1 |
+ Jan04 |
+ UTM JB |
+
+
+ | 17 |
+ B6D2F1 |
+ F |
+ 127 |
+ R0919F2 |
+ Jan04 |
+ UTM JB |
+
+
+ | 18 |
+ B6D2F1 |
+ F |
+ 64 |
+ R1053F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 19 |
+ B6D2F1 |
+ F |
+ 64 |
+ R1053F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 20 |
+ B6D2F1 |
+ M |
+ 127 |
+ R0920F1 |
+ Jan04 |
+ UTM JB |
+
+
+ | 21 |
+ B6D2F1 |
+ M |
+ 127 |
+ R0920F2 |
+ Jan04 |
+ UTM JB |
+
+
+ | 22 |
+ B6D2F1 |
+ M |
+ 66 |
+ R1057F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 23 |
+ BXD1 |
+ M |
+ 181 |
+ R0956F1 |
+ Feb05 |
+ UTM JB |
+
+
+ | 24 |
+ BXD1 |
+ F |
+ 95 |
+ R0895F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 25 |
+ BXD2 |
+ F |
+ 142 |
+ R0907F1 |
+ Feb05 |
+ UAB |
+
+
+ | 26 |
+ BXD5 |
+ F |
+ 56 |
+ R0744F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 27 |
+ BXD5 |
+ M |
+ 71 |
+ R0728F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 28 |
+ BXD6 |
+ F |
+ 57 |
+ R1711F1 |
+ Feb05 |
+ JAX |
+
+
+ | 29 |
+ BXD6 |
+ F |
+ 92 |
+ R0901F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 30 |
+ BXD6 |
+ M |
+ 92 |
+ R0902F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 31 |
+ BXD8 |
+ F |
+ 72 |
+ R0167F1 |
+ Jan04 |
+ UAB |
+
+
+ | 32 |
+ BXD9 |
+ F |
+ 86 |
+ R0908F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 33 |
+ BXD9 |
+ M |
+ 86 |
+ R0909F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 34 |
+ BXD11 |
+ F |
+ 97 |
+ R0745F1 |
+ Feb05 |
+ UAB |
+
+
+ | 35 |
+ BXD11 |
+ M |
+ 92 |
+ R0666F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 36 |
+ BXD12 |
+ F |
+ 64 |
+ R0896F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 37 |
+ BXD12 |
+ M |
+ 64 |
+ R0897F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 38 |
+ BXD13 |
+ F |
+ 86 |
+ R0730F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 39 |
+ BXD13 |
+ F |
+ 86 |
+ R0748F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 40 |
+ BXD13 |
+ M |
+ 76 |
+ R0929F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 41 |
+ BXD14 |
+ M |
+ 91 |
+ R0912F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 42 |
+ BXD14 |
+ M |
+ 68 |
+ R1051F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 43 |
+ BXD15 |
+ F |
+ 80 |
+ R0928F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 44 |
+ BXD18 |
+ F |
+ 108 |
+ R0771F1 |
+ Jan04 |
+ UAB |
+
+
+ | 45 |
+ BXD19 |
+ M |
+ 157 |
+ R1229F1 |
+ Feb05 |
+ UTM JB |
+
+
+ | 46 |
+ BXD19 |
+ F |
+ 56 |
+ R0236F1 |
+ Jan04 |
+ UAB |
+
+
+ | 47 |
+ BXD21 |
+ F |
+ 67 |
+ R0740F1 |
+ Jan04 |
+ UAB |
+
+
+ | 48 |
+ BXD21 |
+ F |
+ 67 |
+ R0740F1 |
+ Feb05 |
+ UAB |
+
+
+ | 49 |
+ BXD23 |
+ F |
+ 66 |
+ R1035F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 50 |
+ BXD23 |
+ M |
+ 66 |
+ R1037F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 51 |
+ BXD23 |
+ F |
+ 88 |
+ R0815F1 |
+ Jan04 |
+ UAB |
+
+
+ | 52 |
+ BXD23 |
+ F |
+ 88 |
+ R0815F1 |
+ Feb05 |
+ UAB |
+
+
+ | 53 |
+ BXD24 |
+ F |
+ 71 |
+ R0914F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 54 |
+ BXD24 |
+ M |
+ 71 |
+ R0913F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 55 |
+ BXD25 |
+ F |
+ 74 |
+ R0373F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 56 |
+ BXD28 |
+ F |
+ 79 |
+ R0910F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 57 |
+ BXD28 |
+ M |
+ 79 |
+ R0911F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 58 |
+ BXD28 |
+ F |
+ 113 |
+ R0892F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 59 |
+ BXD29 |
+ F |
+ 76 |
+ R0693F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 60 |
+ BXD31 |
+ F |
+ 61 |
+ R1199F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 61 |
+ BXD31 |
+ M |
+ 61 |
+ R1141F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 62 |
+ BXD32 |
+ F |
+ 93 |
+ R0898F1 |
+ Jan04 |
+ UAB |
+
+
+ | 63 |
+ BXD32 |
+ F |
+ 76 |
+ R1214F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 64 |
+ BXD32 |
+ M |
+ 65 |
+ R1478F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 65 |
+ BXD33 |
+ M |
+ 77 |
+ R0915F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 66 |
+ BXD34 |
+ F |
+ 92 |
+ R0900F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 67 |
+ BXD34 |
+ M |
+ 56 |
+ R0617F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 68 |
+ BXD34 |
+ M |
+ 72 |
+ R0916F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 69 |
+ BXD36 |
+ F |
+ 61 |
+ R1145F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 70 |
+ BXD36 |
+ M |
+ 77 |
+ R0926F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 71 |
+ BXD36 |
+ M |
+ 61 |
+ R1211F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 72 |
+ BXD38 |
+ M |
+ 83 |
+ R1208F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 73 |
+ BXD38 |
+ F |
+ 69 |
+ R0729F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 74 |
+ BXD38 |
+ M |
+ 69 |
+ R0731F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 75 |
+ BXD39 |
+ F |
+ 76 |
+ R1712F1 |
+ Feb05 |
+ JAX |
+
+
+ | 76 |
+ BXD39 |
+ M |
+ 71 |
+ R0602F1 |
+ Feb05 |
+ UAB |
+
+
+ | 77 |
+ BXD40 |
+ F |
+ 184 |
+ R0741F1 |
+ Feb05 |
+ UAB |
+
+
+ | 78 |
+ BXD40 |
+ M |
+ 56 |
+ R0894F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 79 |
+ BXD42 |
+ F |
+ 100 |
+ R0742F1 |
+ Feb05 |
+ UAB |
+
+
+ | 80 |
+ BXD42 |
+ M |
+ 97 |
+ R0936F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 81 |
+ BXD42 |
+ M |
+ 105 |
+ R0937F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 82 |
+ BXD43 |
+ M |
+ 63 |
+ R1047F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 83 |
+ BXD44 |
+ F |
+ 57 |
+ R1069F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 84 |
+ BXD44 |
+ M |
+ 58 |
+ R1072F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 85 |
+ BXD45 |
+ F |
+ 58 |
+ R1398F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 86 |
+ BXD48 |
+ F |
+ 59 |
+ R0946F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 87 |
+ BXD48 |
+ M |
+ 64 |
+ R0970F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 88 |
+ BXD51 |
+ F |
+ 63 |
+ R1430F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 89 |
+ BXD51 |
+ M |
+ 65 |
+ R1001F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 90 |
+ BXD60 |
+ F |
+ 64 |
+ R0976F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 91 |
+ BXD60 |
+ M |
+ 59 |
+ R1075F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 92 |
+ BXD62 |
+ F |
+ 59 |
+ R1033F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 93 |
+ BXD62 |
+ M |
+ 58 |
+ R1027F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 94 |
+ BXD69 |
+ F |
+ 60 |
+ R1438F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 95 |
+ BXD69 |
+ M |
+ 64 |
+ R1193F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 96 |
+ BXD73 |
+ F |
+ 60 |
+ R1275F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 97 |
+ BXD73 |
+ M |
+ 76 |
+ R1442F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 98 |
+ BXD77 |
+ M |
+ 61 |
+ R1426F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 99 |
+ BXD86 |
+ F |
+ 77 |
+ R1414F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 100 |
+ BXD86 |
+ M |
+ 77 |
+ R1418F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 101 |
+ BXD87 |
+ F |
+ 89 |
+ R1713F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 102 |
+ BXD87 |
+ M |
+ 84 |
+ R1709F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 103 |
+ BXD90 |
+ M |
+ 61 |
+ R1452F |
+ Feb05 |
+ UTM RW |
+
+
+ | 104 |
+ BXD92 |
+ F |
+ 58 |
+ R1299F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 105 |
+ BXD92 |
+ M |
+ 59 |
+ R1307F1 |
+ Feb05 |
+ UTM RW |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Ibr_m_0405_p/acknowledgment.rtf b/general/datasets/Ibr_m_0405_p/acknowledgment.rtf
new file mode 100644
index 0000000..a1563a6
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_p/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data were generously provided by the NIAAA and its INIA grant program to RWW, Thomas Sutter, and Daniel Goldowitz (U01AA013515, U01AA013499-03S1, U01AA013488, U01AA013503-03S1). Support for the continued development of the GeneNetwork and WebQTL was provided by a NIMH Human Brain Project grant (P20MH062009). All arrays were processed at the University of Memphis by Thomas Sutter and colleagues with support of the INIA Bioanalytical Core.
diff --git a/general/datasets/Ibr_m_0405_p/cases.rtf b/general/datasets/Ibr_m_0405_p/cases.rtf
new file mode 100644
index 0000000..8794b88
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_p/cases.rtf
@@ -0,0 +1,5 @@
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory. BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues
+
+
+All stock was obtained originally from The Jackson Laboratory between 1999 and 2003. Most BXD animals were born and housed at the University of Tennessee Health Science Center. Some cases were bred at the University of Memphis (Douglas Matthews) or the University of Alabama (John Mountz and Hui-Chen Hsu).
+
diff --git a/general/datasets/Ibr_m_0405_p/notes.rtf b/general/datasets/Ibr_m_0405_p/notes.rtf
new file mode 100644
index 0000000..72bad83
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_p/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW, YHQ, and EJC, Oct 2004. Updated by RWW, Nov 5, 2004; April 7, 2005; RNA/tissue preparation protocol updatedby JLP, Sept 2, 2005; Sept 26, 2005.
+
diff --git a/general/datasets/Ibr_m_0405_p/platform.rtf b/general/datasets/Ibr_m_0405_p/platform.rtf
new file mode 100644
index 0000000..028fe23
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_p/platform.rtf
@@ -0,0 +1,3 @@
+
+
+Affymetrix Mouse Genome 430A and B array pairs: The 430A and B array pairs consist of 992936 25-nucleotide probes that collectively estimate the expression of approximately 39,000 transcripts. The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequences as the 430 2.0 series. However, we have found that roughy 75000 probes differ from those on A and B arrays and those on the 430 2.0
diff --git a/general/datasets/Ibr_m_0405_p/processing.rtf b/general/datasets/Ibr_m_0405_p/processing.rtf
new file mode 100644
index 0000000..243e5c0
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_p/processing.rtf
@@ -0,0 +1,20 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the two batches (n = 34 and n = 71 array pairs) at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7a: The 430A and 430B arrays include a set of 100 shared probe sets (a total of 2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the 430A and 430B arrays to a common scale. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression correction to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a small offset. The result of this step is that the mean of the 430A expression is fixed at a value of 8, whereas that of the 430B chip is typically reduced to 7. The average of the merged 430A and 430B array data set is approximately 7.5.
+ - Step 7b: We recentered the merged 430A and 430B data sets to a mean of 8 and a standard deviation of 2. This involved reapplying Steps 3 through 5.
+ - Step 8: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). The original CEL files were read into the R environment (Ihaka and Gentleman 1996). Data were processed using the Robust Multichip Average (RMA) method (Irrizary et al. 2003). Values were log2 transformed. Probe set values listed in WebQTL are the averages of biological replicates within strain. A few technical replicates were averaged and treated as single samples. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+This data set include further normalization to produce final estimates of expression that can be compared directly to the other transforms (average of 8 units and stabilized standard deviation of 2 units within each array). Please seee Bolstad and colleagues (2003) for a helpful comparison of RMA and two other common methods of processing Affymetrix array data sets.
+
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets included on the microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium May 2004 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Ibr_m_0405_p/summary.rtf b/general/datasets/Ibr_m_0405_p/summary.rtf
new file mode 100644
index 0000000..6fe94b1
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_p/summary.rtf
@@ -0,0 +1,3 @@
+
+This April 2005 data freeze provides estimates of mRNA expression in adult forebrain and midbrain from 45 lines of mice including C57BL/6J, DBA/2J, their F1 hybrids, and 42 BXD recombinant inbred strains. Data were generated at UTHSC and the University of Memphis with support from grants from the NIAAA Integrative Neuroscience Initiative on Alcoholism (INIA). Samples were hybridized in small pools (n = 3) to a total of 105 Affymetrix M430A and B array pairs. This particular data set was processed using the RMA protocol. To simplify comparisons among transforms, RMA values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Ibr_m_0405_p/tissue.rtf b/general/datasets/Ibr_m_0405_p/tissue.rtf
new file mode 100644
index 0000000..841d879
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_p/tissue.rtf
@@ -0,0 +1,977 @@
+The INIA M430 brain Database (April05) consists of 105 Affymetrix 430A and 430B microarray pairs. Each pair was hybridized in sequence (A array first, B array second) with a pool of brain tissue (forebrain minus olfactory bulb, plus the entire midbrain) taken from three adult animals of closely matched age and the same sex. RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai. All samples were subsequently processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center of Excellence by Thomas R. Sutter, Shirlean Goodwin, and colleagues at the University of Memphis.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. We have not yet achieved this goal. Ten of 45 strains are still represented by single sex samples: BXD2 (F), BXD8 (F), BXD15 (F), BXD18 (F), BXD25 (F), BXD29 (F), BXD33 (M), BXD45 (F), BXD77 (M), and BXD90 (M). Eleven strains are represented by three independent samples with the following breakdown by sex: C57BL/6J (1F 2M), DBA/2J (2F 2M), B6D2F1 (2F 2M) + D2B6F1 (1F 1M), BXD6 (2F 1M), BXD13 (2F 1M), BXD14 (1F 2M), BXD28 (2F 1M), BXD34 (1F 2M), BXD36 (1F 2M), BXD38 (1F 2M), BXD42 (1F 2M).
+
+Batch Structure: Before running the first batch of 30 pairs of array (dated Jan04), we ran four test samples (Nov03). The main batch of 30 includes the four test samples (four technical replicates). The Nov03 data was combined with the Jan04 data and was treated as a single batch that consists of one male and one female pool from C57BL/6J, DBA/2J, the B6D2F1 hybrid, 11 female BXD samples, and 11 male BXD samples. The second large batch was run February 2005 (Feb05) and consists of 71 pairs of arrays. Batch effects were corrected at the individual probe level as described below.
+
+The table below summarizes information on strain, sex, age, sample name, batch result date, and source of mice.
+
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Age |
+ Sample_name |
+ Result date |
+ Source |
+
+
+ | 1 |
+ C57BL/6J |
+ F |
+ 65 |
+ R0903F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 2 |
+ C57BL/6J |
+ F |
+ 65 |
+ R0903F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 3 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 4 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 5 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 6 |
+ C57BL/6J |
+ M |
+ 76 |
+ R0997F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 7 |
+ D2B6F1 |
+ F |
+ 57 |
+ R1066F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 8 |
+ D2B6F1 |
+ M |
+ 59 |
+ R1381F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 9 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 10 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 11 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F2 |
+ Jan04 |
+ UTM RW |
+
+
+ | 12 |
+ DBA/2J |
+ F |
+ 64 |
+ R1123F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 13 |
+ DBA/2J |
+ M |
+ 60 |
+ R0918F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 14 |
+ DBA/2J |
+ M |
+ 60 |
+ R0918F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 15 |
+ DBA/2J |
+ M |
+ 73 |
+ R1009F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 16 |
+ B6D2F1 |
+ F |
+ 127 |
+ R0919F1 |
+ Jan04 |
+ UTM JB |
+
+
+ | 17 |
+ B6D2F1 |
+ F |
+ 127 |
+ R0919F2 |
+ Jan04 |
+ UTM JB |
+
+
+ | 18 |
+ B6D2F1 |
+ F |
+ 64 |
+ R1053F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 19 |
+ B6D2F1 |
+ F |
+ 64 |
+ R1053F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 20 |
+ B6D2F1 |
+ M |
+ 127 |
+ R0920F1 |
+ Jan04 |
+ UTM JB |
+
+
+ | 21 |
+ B6D2F1 |
+ M |
+ 127 |
+ R0920F2 |
+ Jan04 |
+ UTM JB |
+
+
+ | 22 |
+ B6D2F1 |
+ M |
+ 66 |
+ R1057F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 23 |
+ BXD1 |
+ M |
+ 181 |
+ R0956F1 |
+ Feb05 |
+ UTM JB |
+
+
+ | 24 |
+ BXD1 |
+ F |
+ 95 |
+ R0895F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 25 |
+ BXD2 |
+ F |
+ 142 |
+ R0907F1 |
+ Feb05 |
+ UAB |
+
+
+ | 26 |
+ BXD5 |
+ F |
+ 56 |
+ R0744F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 27 |
+ BXD5 |
+ M |
+ 71 |
+ R0728F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 28 |
+ BXD6 |
+ F |
+ 57 |
+ R1711F1 |
+ Feb05 |
+ JAX |
+
+
+ | 29 |
+ BXD6 |
+ F |
+ 92 |
+ R0901F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 30 |
+ BXD6 |
+ M |
+ 92 |
+ R0902F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 31 |
+ BXD8 |
+ F |
+ 72 |
+ R0167F1 |
+ Jan04 |
+ UAB |
+
+
+ | 32 |
+ BXD9 |
+ F |
+ 86 |
+ R0908F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 33 |
+ BXD9 |
+ M |
+ 86 |
+ R0909F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 34 |
+ BXD11 |
+ F |
+ 97 |
+ R0745F1 |
+ Feb05 |
+ UAB |
+
+
+ | 35 |
+ BXD11 |
+ M |
+ 92 |
+ R0666F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 36 |
+ BXD12 |
+ F |
+ 64 |
+ R0896F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 37 |
+ BXD12 |
+ M |
+ 64 |
+ R0897F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 38 |
+ BXD13 |
+ F |
+ 86 |
+ R0730F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 39 |
+ BXD13 |
+ F |
+ 86 |
+ R0748F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 40 |
+ BXD13 |
+ M |
+ 76 |
+ R0929F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 41 |
+ BXD14 |
+ M |
+ 91 |
+ R0912F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 42 |
+ BXD14 |
+ M |
+ 68 |
+ R1051F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 43 |
+ BXD15 |
+ F |
+ 80 |
+ R0928F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 44 |
+ BXD18 |
+ F |
+ 108 |
+ R0771F1 |
+ Jan04 |
+ UAB |
+
+
+ | 45 |
+ BXD19 |
+ M |
+ 157 |
+ R1229F1 |
+ Feb05 |
+ UTM JB |
+
+
+ | 46 |
+ BXD19 |
+ F |
+ 56 |
+ R0236F1 |
+ Jan04 |
+ UAB |
+
+
+ | 47 |
+ BXD21 |
+ F |
+ 67 |
+ R0740F1 |
+ Jan04 |
+ UAB |
+
+
+ | 48 |
+ BXD21 |
+ F |
+ 67 |
+ R0740F1 |
+ Feb05 |
+ UAB |
+
+
+ | 49 |
+ BXD23 |
+ F |
+ 66 |
+ R1035F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 50 |
+ BXD23 |
+ M |
+ 66 |
+ R1037F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 51 |
+ BXD23 |
+ F |
+ 88 |
+ R0815F1 |
+ Jan04 |
+ UAB |
+
+
+ | 52 |
+ BXD23 |
+ F |
+ 88 |
+ R0815F1 |
+ Feb05 |
+ UAB |
+
+
+ | 53 |
+ BXD24 |
+ F |
+ 71 |
+ R0914F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 54 |
+ BXD24 |
+ M |
+ 71 |
+ R0913F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 55 |
+ BXD25 |
+ F |
+ 74 |
+ R0373F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 56 |
+ BXD28 |
+ F |
+ 79 |
+ R0910F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 57 |
+ BXD28 |
+ M |
+ 79 |
+ R0911F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 58 |
+ BXD28 |
+ F |
+ 113 |
+ R0892F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 59 |
+ BXD29 |
+ F |
+ 76 |
+ R0693F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 60 |
+ BXD31 |
+ F |
+ 61 |
+ R1199F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 61 |
+ BXD31 |
+ M |
+ 61 |
+ R1141F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 62 |
+ BXD32 |
+ F |
+ 93 |
+ R0898F1 |
+ Jan04 |
+ UAB |
+
+
+ | 63 |
+ BXD32 |
+ F |
+ 76 |
+ R1214F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 64 |
+ BXD32 |
+ M |
+ 65 |
+ R1478F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 65 |
+ BXD33 |
+ M |
+ 77 |
+ R0915F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 66 |
+ BXD34 |
+ F |
+ 92 |
+ R0900F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 67 |
+ BXD34 |
+ M |
+ 56 |
+ R0617F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 68 |
+ BXD34 |
+ M |
+ 72 |
+ R0916F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 69 |
+ BXD36 |
+ F |
+ 61 |
+ R1145F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 70 |
+ BXD36 |
+ M |
+ 77 |
+ R0926F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 71 |
+ BXD36 |
+ M |
+ 61 |
+ R1211F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 72 |
+ BXD38 |
+ M |
+ 83 |
+ R1208F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 73 |
+ BXD38 |
+ F |
+ 69 |
+ R0729F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 74 |
+ BXD38 |
+ M |
+ 69 |
+ R0731F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 75 |
+ BXD39 |
+ F |
+ 76 |
+ R1712F1 |
+ Feb05 |
+ JAX |
+
+
+ | 76 |
+ BXD39 |
+ M |
+ 71 |
+ R0602F1 |
+ Feb05 |
+ UAB |
+
+
+ | 77 |
+ BXD40 |
+ F |
+ 184 |
+ R0741F1 |
+ Feb05 |
+ UAB |
+
+
+ | 78 |
+ BXD40 |
+ M |
+ 56 |
+ R0894F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 79 |
+ BXD42 |
+ F |
+ 100 |
+ R0742F1 |
+ Feb05 |
+ UAB |
+
+
+ | 80 |
+ BXD42 |
+ M |
+ 97 |
+ R0936F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 81 |
+ BXD42 |
+ M |
+ 105 |
+ R0937F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 82 |
+ BXD43 |
+ M |
+ 63 |
+ R1047F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 83 |
+ BXD44 |
+ F |
+ 57 |
+ R1069F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 84 |
+ BXD44 |
+ M |
+ 58 |
+ R1072F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 85 |
+ BXD45 |
+ F |
+ 58 |
+ R1398F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 86 |
+ BXD48 |
+ F |
+ 59 |
+ R0946F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 87 |
+ BXD48 |
+ M |
+ 64 |
+ R0970F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 88 |
+ BXD51 |
+ F |
+ 63 |
+ R1430F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 89 |
+ BXD51 |
+ M |
+ 65 |
+ R1001F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 90 |
+ BXD60 |
+ F |
+ 64 |
+ R0976F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 91 |
+ BXD60 |
+ M |
+ 59 |
+ R1075F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 92 |
+ BXD62 |
+ F |
+ 59 |
+ R1033F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 93 |
+ BXD62 |
+ M |
+ 58 |
+ R1027F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 94 |
+ BXD69 |
+ F |
+ 60 |
+ R1438F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 95 |
+ BXD69 |
+ M |
+ 64 |
+ R1193F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 96 |
+ BXD73 |
+ F |
+ 60 |
+ R1275F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 97 |
+ BXD73 |
+ M |
+ 76 |
+ R1442F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 98 |
+ BXD77 |
+ M |
+ 61 |
+ R1426F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 99 |
+ BXD86 |
+ F |
+ 77 |
+ R1414F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 100 |
+ BXD86 |
+ M |
+ 77 |
+ R1418F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 101 |
+ BXD87 |
+ F |
+ 89 |
+ R1713F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 102 |
+ BXD87 |
+ M |
+ 84 |
+ R1709F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 103 |
+ BXD90 |
+ M |
+ 61 |
+ R1452F |
+ Feb05 |
+ UTM RW |
+
+
+ | 104 |
+ BXD92 |
+ F |
+ 58 |
+ R1299F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 105 |
+ BXD92 |
+ M |
+ 59 |
+ R1307F1 |
+ Feb05 |
+ UTM RW |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Ibr_m_0405_r/acknowledgment.rtf b/general/datasets/Ibr_m_0405_r/acknowledgment.rtf
new file mode 100644
index 0000000..a1563a6
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data were generously provided by the NIAAA and its INIA grant program to RWW, Thomas Sutter, and Daniel Goldowitz (U01AA013515, U01AA013499-03S1, U01AA013488, U01AA013503-03S1). Support for the continued development of the GeneNetwork and WebQTL was provided by a NIMH Human Brain Project grant (P20MH062009). All arrays were processed at the University of Memphis by Thomas Sutter and colleagues with support of the INIA Bioanalytical Core.
diff --git a/general/datasets/Ibr_m_0405_r/cases.rtf b/general/datasets/Ibr_m_0405_r/cases.rtf
new file mode 100644
index 0000000..8794b88
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_r/cases.rtf
@@ -0,0 +1,5 @@
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory. BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues
+
+
+All stock was obtained originally from The Jackson Laboratory between 1999 and 2003. Most BXD animals were born and housed at the University of Tennessee Health Science Center. Some cases were bred at the University of Memphis (Douglas Matthews) or the University of Alabama (John Mountz and Hui-Chen Hsu).
+
diff --git a/general/datasets/Ibr_m_0405_r/notes.rtf b/general/datasets/Ibr_m_0405_r/notes.rtf
new file mode 100644
index 0000000..72bad83
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW, YHQ, and EJC, Oct 2004. Updated by RWW, Nov 5, 2004; April 7, 2005; RNA/tissue preparation protocol updatedby JLP, Sept 2, 2005; Sept 26, 2005.
+
diff --git a/general/datasets/Ibr_m_0405_r/platform.rtf b/general/datasets/Ibr_m_0405_r/platform.rtf
new file mode 100644
index 0000000..028fe23
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_r/platform.rtf
@@ -0,0 +1,3 @@
+
+
+Affymetrix Mouse Genome 430A and B array pairs: The 430A and B array pairs consist of 992936 25-nucleotide probes that collectively estimate the expression of approximately 39,000 transcripts. The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequences as the 430 2.0 series. However, we have found that roughy 75000 probes differ from those on A and B arrays and those on the 430 2.0
diff --git a/general/datasets/Ibr_m_0405_r/processing.rtf b/general/datasets/Ibr_m_0405_r/processing.rtf
new file mode 100644
index 0000000..243e5c0
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_r/processing.rtf
@@ -0,0 +1,20 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the two batches (n = 34 and n = 71 array pairs) at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7a: The 430A and 430B arrays include a set of 100 shared probe sets (a total of 2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the 430A and 430B arrays to a common scale. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression correction to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a small offset. The result of this step is that the mean of the 430A expression is fixed at a value of 8, whereas that of the 430B chip is typically reduced to 7. The average of the merged 430A and 430B array data set is approximately 7.5.
+ - Step 7b: We recentered the merged 430A and 430B data sets to a mean of 8 and a standard deviation of 2. This involved reapplying Steps 3 through 5.
+ - Step 8: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). The original CEL files were read into the R environment (Ihaka and Gentleman 1996). Data were processed using the Robust Multichip Average (RMA) method (Irrizary et al. 2003). Values were log2 transformed. Probe set values listed in WebQTL are the averages of biological replicates within strain. A few technical replicates were averaged and treated as single samples. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+This data set include further normalization to produce final estimates of expression that can be compared directly to the other transforms (average of 8 units and stabilized standard deviation of 2 units within each array). Please seee Bolstad and colleagues (2003) for a helpful comparison of RMA and two other common methods of processing Affymetrix array data sets.
+
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets included on the microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium May 2004 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Ibr_m_0405_r/summary.rtf b/general/datasets/Ibr_m_0405_r/summary.rtf
new file mode 100644
index 0000000..6fe94b1
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_r/summary.rtf
@@ -0,0 +1,3 @@
+
+This April 2005 data freeze provides estimates of mRNA expression in adult forebrain and midbrain from 45 lines of mice including C57BL/6J, DBA/2J, their F1 hybrids, and 42 BXD recombinant inbred strains. Data were generated at UTHSC and the University of Memphis with support from grants from the NIAAA Integrative Neuroscience Initiative on Alcoholism (INIA). Samples were hybridized in small pools (n = 3) to a total of 105 Affymetrix M430A and B array pairs. This particular data set was processed using the RMA protocol. To simplify comparisons among transforms, RMA values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Ibr_m_0405_r/tissue.rtf b/general/datasets/Ibr_m_0405_r/tissue.rtf
new file mode 100644
index 0000000..841d879
--- /dev/null
+++ b/general/datasets/Ibr_m_0405_r/tissue.rtf
@@ -0,0 +1,977 @@
+The INIA M430 brain Database (April05) consists of 105 Affymetrix 430A and 430B microarray pairs. Each pair was hybridized in sequence (A array first, B array second) with a pool of brain tissue (forebrain minus olfactory bulb, plus the entire midbrain) taken from three adult animals of closely matched age and the same sex. RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai. All samples were subsequently processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center of Excellence by Thomas R. Sutter, Shirlean Goodwin, and colleagues at the University of Memphis.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. We have not yet achieved this goal. Ten of 45 strains are still represented by single sex samples: BXD2 (F), BXD8 (F), BXD15 (F), BXD18 (F), BXD25 (F), BXD29 (F), BXD33 (M), BXD45 (F), BXD77 (M), and BXD90 (M). Eleven strains are represented by three independent samples with the following breakdown by sex: C57BL/6J (1F 2M), DBA/2J (2F 2M), B6D2F1 (2F 2M) + D2B6F1 (1F 1M), BXD6 (2F 1M), BXD13 (2F 1M), BXD14 (1F 2M), BXD28 (2F 1M), BXD34 (1F 2M), BXD36 (1F 2M), BXD38 (1F 2M), BXD42 (1F 2M).
+
+Batch Structure: Before running the first batch of 30 pairs of array (dated Jan04), we ran four test samples (Nov03). The main batch of 30 includes the four test samples (four technical replicates). The Nov03 data was combined with the Jan04 data and was treated as a single batch that consists of one male and one female pool from C57BL/6J, DBA/2J, the B6D2F1 hybrid, 11 female BXD samples, and 11 male BXD samples. The second large batch was run February 2005 (Feb05) and consists of 71 pairs of arrays. Batch effects were corrected at the individual probe level as described below.
+
+The table below summarizes information on strain, sex, age, sample name, batch result date, and source of mice.
+
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Age |
+ Sample_name |
+ Result date |
+ Source |
+
+
+ | 1 |
+ C57BL/6J |
+ F |
+ 65 |
+ R0903F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 2 |
+ C57BL/6J |
+ F |
+ 65 |
+ R0903F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 3 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 4 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 5 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 6 |
+ C57BL/6J |
+ M |
+ 76 |
+ R0997F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 7 |
+ D2B6F1 |
+ F |
+ 57 |
+ R1066F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 8 |
+ D2B6F1 |
+ M |
+ 59 |
+ R1381F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 9 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 10 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 11 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F2 |
+ Jan04 |
+ UTM RW |
+
+
+ | 12 |
+ DBA/2J |
+ F |
+ 64 |
+ R1123F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 13 |
+ DBA/2J |
+ M |
+ 60 |
+ R0918F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 14 |
+ DBA/2J |
+ M |
+ 60 |
+ R0918F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 15 |
+ DBA/2J |
+ M |
+ 73 |
+ R1009F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 16 |
+ B6D2F1 |
+ F |
+ 127 |
+ R0919F1 |
+ Jan04 |
+ UTM JB |
+
+
+ | 17 |
+ B6D2F1 |
+ F |
+ 127 |
+ R0919F2 |
+ Jan04 |
+ UTM JB |
+
+
+ | 18 |
+ B6D2F1 |
+ F |
+ 64 |
+ R1053F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 19 |
+ B6D2F1 |
+ F |
+ 64 |
+ R1053F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 20 |
+ B6D2F1 |
+ M |
+ 127 |
+ R0920F1 |
+ Jan04 |
+ UTM JB |
+
+
+ | 21 |
+ B6D2F1 |
+ M |
+ 127 |
+ R0920F2 |
+ Jan04 |
+ UTM JB |
+
+
+ | 22 |
+ B6D2F1 |
+ M |
+ 66 |
+ R1057F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 23 |
+ BXD1 |
+ M |
+ 181 |
+ R0956F1 |
+ Feb05 |
+ UTM JB |
+
+
+ | 24 |
+ BXD1 |
+ F |
+ 95 |
+ R0895F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 25 |
+ BXD2 |
+ F |
+ 142 |
+ R0907F1 |
+ Feb05 |
+ UAB |
+
+
+ | 26 |
+ BXD5 |
+ F |
+ 56 |
+ R0744F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 27 |
+ BXD5 |
+ M |
+ 71 |
+ R0728F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 28 |
+ BXD6 |
+ F |
+ 57 |
+ R1711F1 |
+ Feb05 |
+ JAX |
+
+
+ | 29 |
+ BXD6 |
+ F |
+ 92 |
+ R0901F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 30 |
+ BXD6 |
+ M |
+ 92 |
+ R0902F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 31 |
+ BXD8 |
+ F |
+ 72 |
+ R0167F1 |
+ Jan04 |
+ UAB |
+
+
+ | 32 |
+ BXD9 |
+ F |
+ 86 |
+ R0908F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 33 |
+ BXD9 |
+ M |
+ 86 |
+ R0909F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 34 |
+ BXD11 |
+ F |
+ 97 |
+ R0745F1 |
+ Feb05 |
+ UAB |
+
+
+ | 35 |
+ BXD11 |
+ M |
+ 92 |
+ R0666F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 36 |
+ BXD12 |
+ F |
+ 64 |
+ R0896F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 37 |
+ BXD12 |
+ M |
+ 64 |
+ R0897F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 38 |
+ BXD13 |
+ F |
+ 86 |
+ R0730F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 39 |
+ BXD13 |
+ F |
+ 86 |
+ R0748F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 40 |
+ BXD13 |
+ M |
+ 76 |
+ R0929F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 41 |
+ BXD14 |
+ M |
+ 91 |
+ R0912F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 42 |
+ BXD14 |
+ M |
+ 68 |
+ R1051F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 43 |
+ BXD15 |
+ F |
+ 80 |
+ R0928F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 44 |
+ BXD18 |
+ F |
+ 108 |
+ R0771F1 |
+ Jan04 |
+ UAB |
+
+
+ | 45 |
+ BXD19 |
+ M |
+ 157 |
+ R1229F1 |
+ Feb05 |
+ UTM JB |
+
+
+ | 46 |
+ BXD19 |
+ F |
+ 56 |
+ R0236F1 |
+ Jan04 |
+ UAB |
+
+
+ | 47 |
+ BXD21 |
+ F |
+ 67 |
+ R0740F1 |
+ Jan04 |
+ UAB |
+
+
+ | 48 |
+ BXD21 |
+ F |
+ 67 |
+ R0740F1 |
+ Feb05 |
+ UAB |
+
+
+ | 49 |
+ BXD23 |
+ F |
+ 66 |
+ R1035F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 50 |
+ BXD23 |
+ M |
+ 66 |
+ R1037F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 51 |
+ BXD23 |
+ F |
+ 88 |
+ R0815F1 |
+ Jan04 |
+ UAB |
+
+
+ | 52 |
+ BXD23 |
+ F |
+ 88 |
+ R0815F1 |
+ Feb05 |
+ UAB |
+
+
+ | 53 |
+ BXD24 |
+ F |
+ 71 |
+ R0914F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 54 |
+ BXD24 |
+ M |
+ 71 |
+ R0913F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 55 |
+ BXD25 |
+ F |
+ 74 |
+ R0373F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 56 |
+ BXD28 |
+ F |
+ 79 |
+ R0910F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 57 |
+ BXD28 |
+ M |
+ 79 |
+ R0911F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 58 |
+ BXD28 |
+ F |
+ 113 |
+ R0892F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 59 |
+ BXD29 |
+ F |
+ 76 |
+ R0693F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 60 |
+ BXD31 |
+ F |
+ 61 |
+ R1199F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 61 |
+ BXD31 |
+ M |
+ 61 |
+ R1141F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 62 |
+ BXD32 |
+ F |
+ 93 |
+ R0898F1 |
+ Jan04 |
+ UAB |
+
+
+ | 63 |
+ BXD32 |
+ F |
+ 76 |
+ R1214F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 64 |
+ BXD32 |
+ M |
+ 65 |
+ R1478F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 65 |
+ BXD33 |
+ M |
+ 77 |
+ R0915F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 66 |
+ BXD34 |
+ F |
+ 92 |
+ R0900F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 67 |
+ BXD34 |
+ M |
+ 56 |
+ R0617F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 68 |
+ BXD34 |
+ M |
+ 72 |
+ R0916F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 69 |
+ BXD36 |
+ F |
+ 61 |
+ R1145F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 70 |
+ BXD36 |
+ M |
+ 77 |
+ R0926F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 71 |
+ BXD36 |
+ M |
+ 61 |
+ R1211F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 72 |
+ BXD38 |
+ M |
+ 83 |
+ R1208F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 73 |
+ BXD38 |
+ F |
+ 69 |
+ R0729F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 74 |
+ BXD38 |
+ M |
+ 69 |
+ R0731F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 75 |
+ BXD39 |
+ F |
+ 76 |
+ R1712F1 |
+ Feb05 |
+ JAX |
+
+
+ | 76 |
+ BXD39 |
+ M |
+ 71 |
+ R0602F1 |
+ Feb05 |
+ UAB |
+
+
+ | 77 |
+ BXD40 |
+ F |
+ 184 |
+ R0741F1 |
+ Feb05 |
+ UAB |
+
+
+ | 78 |
+ BXD40 |
+ M |
+ 56 |
+ R0894F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 79 |
+ BXD42 |
+ F |
+ 100 |
+ R0742F1 |
+ Feb05 |
+ UAB |
+
+
+ | 80 |
+ BXD42 |
+ M |
+ 97 |
+ R0936F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 81 |
+ BXD42 |
+ M |
+ 105 |
+ R0937F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 82 |
+ BXD43 |
+ M |
+ 63 |
+ R1047F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 83 |
+ BXD44 |
+ F |
+ 57 |
+ R1069F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 84 |
+ BXD44 |
+ M |
+ 58 |
+ R1072F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 85 |
+ BXD45 |
+ F |
+ 58 |
+ R1398F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 86 |
+ BXD48 |
+ F |
+ 59 |
+ R0946F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 87 |
+ BXD48 |
+ M |
+ 64 |
+ R0970F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 88 |
+ BXD51 |
+ F |
+ 63 |
+ R1430F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 89 |
+ BXD51 |
+ M |
+ 65 |
+ R1001F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 90 |
+ BXD60 |
+ F |
+ 64 |
+ R0976F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 91 |
+ BXD60 |
+ M |
+ 59 |
+ R1075F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 92 |
+ BXD62 |
+ F |
+ 59 |
+ R1033F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 93 |
+ BXD62 |
+ M |
+ 58 |
+ R1027F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 94 |
+ BXD69 |
+ F |
+ 60 |
+ R1438F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 95 |
+ BXD69 |
+ M |
+ 64 |
+ R1193F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 96 |
+ BXD73 |
+ F |
+ 60 |
+ R1275F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 97 |
+ BXD73 |
+ M |
+ 76 |
+ R1442F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 98 |
+ BXD77 |
+ M |
+ 61 |
+ R1426F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 99 |
+ BXD86 |
+ F |
+ 77 |
+ R1414F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 100 |
+ BXD86 |
+ M |
+ 77 |
+ R1418F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 101 |
+ BXD87 |
+ F |
+ 89 |
+ R1713F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 102 |
+ BXD87 |
+ M |
+ 84 |
+ R1709F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 103 |
+ BXD90 |
+ M |
+ 61 |
+ R1452F |
+ Feb05 |
+ UTM RW |
+
+
+ | 104 |
+ BXD92 |
+ F |
+ 58 |
+ R1299F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 105 |
+ BXD92 |
+ M |
+ 59 |
+ R1307F1 |
+ Feb05 |
+ UTM RW |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Ibr_m_0606_r/acknowledgment.rtf b/general/datasets/Ibr_m_0606_r/acknowledgment.rtf
new file mode 100644
index 0000000..a1563a6
--- /dev/null
+++ b/general/datasets/Ibr_m_0606_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Support for acquisition of microarray data were generously provided by the NIAAA and its INIA grant program to RWW, Thomas Sutter, and Daniel Goldowitz (U01AA013515, U01AA013499-03S1, U01AA013488, U01AA013503-03S1). Support for the continued development of the GeneNetwork and WebQTL was provided by a NIMH Human Brain Project grant (P20MH062009). All arrays were processed at the University of Memphis by Thomas Sutter and colleagues with support of the INIA Bioanalytical Core.
diff --git a/general/datasets/Ibr_m_0606_r/cases.rtf b/general/datasets/Ibr_m_0606_r/cases.rtf
new file mode 100644
index 0000000..8794b88
--- /dev/null
+++ b/general/datasets/Ibr_m_0606_r/cases.rtf
@@ -0,0 +1,5 @@
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory. BXD43 through BXD99 were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams in the late 1990s and early 2000s using advanced intercross progeny (Peirce et al. 2004). Many of the 50 new BXD strains are available from Lu Lu and colleagues
+
+
+All stock was obtained originally from The Jackson Laboratory between 1999 and 2003. Most BXD animals were born and housed at the University of Tennessee Health Science Center. Some cases were bred at the University of Memphis (Douglas Matthews) or the University of Alabama (John Mountz and Hui-Chen Hsu).
+
diff --git a/general/datasets/Ibr_m_0606_r/notes.rtf b/general/datasets/Ibr_m_0606_r/notes.rtf
new file mode 100644
index 0000000..72bad83
--- /dev/null
+++ b/general/datasets/Ibr_m_0606_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW, YHQ, and EJC, Oct 2004. Updated by RWW, Nov 5, 2004; April 7, 2005; RNA/tissue preparation protocol updatedby JLP, Sept 2, 2005; Sept 26, 2005.
+
diff --git a/general/datasets/Ibr_m_0606_r/platform.rtf b/general/datasets/Ibr_m_0606_r/platform.rtf
new file mode 100644
index 0000000..028fe23
--- /dev/null
+++ b/general/datasets/Ibr_m_0606_r/platform.rtf
@@ -0,0 +1,3 @@
+
+
+Affymetrix Mouse Genome 430A and B array pairs: The 430A and B array pairs consist of 992936 25-nucleotide probes that collectively estimate the expression of approximately 39,000 transcripts. The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequences as the 430 2.0 series. However, we have found that roughy 75000 probes differ from those on A and B arrays and those on the 430 2.0
diff --git a/general/datasets/Ibr_m_0606_r/processing.rtf b/general/datasets/Ibr_m_0606_r/processing.rtf
new file mode 100644
index 0000000..243e5c0
--- /dev/null
+++ b/general/datasets/Ibr_m_0606_r/processing.rtf
@@ -0,0 +1,20 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the two batches (n = 34 and n = 71 array pairs) at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7a: The 430A and 430B arrays include a set of 100 shared probe sets (a total of 2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the 430A and 430B arrays to a common scale. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression correction to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a small offset. The result of this step is that the mean of the 430A expression is fixed at a value of 8, whereas that of the 430B chip is typically reduced to 7. The average of the merged 430A and 430B array data set is approximately 7.5.
+ - Step 7b: We recentered the merged 430A and 430B data sets to a mean of 8 and a standard deviation of 2. This involved reapplying Steps 3 through 5.
+ - Step 8: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, source of animals, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). The original CEL files were read into the R environment (Ihaka and Gentleman 1996). Data were processed using the Robust Multichip Average (RMA) method (Irrizary et al. 2003). Values were log2 transformed. Probe set values listed in WebQTL are the averages of biological replicates within strain. A few technical replicates were averaged and treated as single samples. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+This data set include further normalization to produce final estimates of expression that can be compared directly to the other transforms (average of 8 units and stabilized standard deviation of 2 units within each array). Please seee Bolstad and colleagues (2003) for a helpful comparison of RMA and two other common methods of processing Affymetrix array data sets.
+
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets included on the microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium May 2004 Assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Ibr_m_0606_r/summary.rtf b/general/datasets/Ibr_m_0606_r/summary.rtf
new file mode 100644
index 0000000..6fe94b1
--- /dev/null
+++ b/general/datasets/Ibr_m_0606_r/summary.rtf
@@ -0,0 +1,3 @@
+
+This April 2005 data freeze provides estimates of mRNA expression in adult forebrain and midbrain from 45 lines of mice including C57BL/6J, DBA/2J, their F1 hybrids, and 42 BXD recombinant inbred strains. Data were generated at UTHSC and the University of Memphis with support from grants from the NIAAA Integrative Neuroscience Initiative on Alcoholism (INIA). Samples were hybridized in small pools (n = 3) to a total of 105 Affymetrix M430A and B array pairs. This particular data set was processed using the RMA protocol. To simplify comparisons among transforms, RMA values of each array were adjusted to an average of 8 units and a standard deviation of 2 units.
+
diff --git a/general/datasets/Ibr_m_0606_r/tissue.rtf b/general/datasets/Ibr_m_0606_r/tissue.rtf
new file mode 100644
index 0000000..841d879
--- /dev/null
+++ b/general/datasets/Ibr_m_0606_r/tissue.rtf
@@ -0,0 +1,977 @@
+The INIA M430 brain Database (April05) consists of 105 Affymetrix 430A and 430B microarray pairs. Each pair was hybridized in sequence (A array first, B array second) with a pool of brain tissue (forebrain minus olfactory bulb, plus the entire midbrain) taken from three adult animals of closely matched age and the same sex. RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai. All samples were subsequently processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center of Excellence by Thomas R. Sutter, Shirlean Goodwin, and colleagues at the University of Memphis.
+
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one of sample from each sex for all BXD strains. We have not yet achieved this goal. Ten of 45 strains are still represented by single sex samples: BXD2 (F), BXD8 (F), BXD15 (F), BXD18 (F), BXD25 (F), BXD29 (F), BXD33 (M), BXD45 (F), BXD77 (M), and BXD90 (M). Eleven strains are represented by three independent samples with the following breakdown by sex: C57BL/6J (1F 2M), DBA/2J (2F 2M), B6D2F1 (2F 2M) + D2B6F1 (1F 1M), BXD6 (2F 1M), BXD13 (2F 1M), BXD14 (1F 2M), BXD28 (2F 1M), BXD34 (1F 2M), BXD36 (1F 2M), BXD38 (1F 2M), BXD42 (1F 2M).
+
+Batch Structure: Before running the first batch of 30 pairs of array (dated Jan04), we ran four test samples (Nov03). The main batch of 30 includes the four test samples (four technical replicates). The Nov03 data was combined with the Jan04 data and was treated as a single batch that consists of one male and one female pool from C57BL/6J, DBA/2J, the B6D2F1 hybrid, 11 female BXD samples, and 11 male BXD samples. The second large batch was run February 2005 (Feb05) and consists of 71 pairs of arrays. Batch effects were corrected at the individual probe level as described below.
+
+The table below summarizes information on strain, sex, age, sample name, batch result date, and source of mice.
+
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Age |
+ Sample_name |
+ Result date |
+ Source |
+
+
+ | 1 |
+ C57BL/6J |
+ F |
+ 65 |
+ R0903F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 2 |
+ C57BL/6J |
+ F |
+ 65 |
+ R0903F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 3 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 4 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 5 |
+ C57BL/6J |
+ M |
+ 66 |
+ R0906F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 6 |
+ C57BL/6J |
+ M |
+ 76 |
+ R0997F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 7 |
+ D2B6F1 |
+ F |
+ 57 |
+ R1066F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 8 |
+ D2B6F1 |
+ M |
+ 59 |
+ R1381F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 9 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 10 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 11 |
+ DBA/2J |
+ F |
+ 60 |
+ R0917F2 |
+ Jan04 |
+ UTM RW |
+
+
+ | 12 |
+ DBA/2J |
+ F |
+ 64 |
+ R1123F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 13 |
+ DBA/2J |
+ M |
+ 60 |
+ R0918F1 |
+ Nov03 |
+ UTM RW |
+
+
+ | 14 |
+ DBA/2J |
+ M |
+ 60 |
+ R0918F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 15 |
+ DBA/2J |
+ M |
+ 73 |
+ R1009F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 16 |
+ B6D2F1 |
+ F |
+ 127 |
+ R0919F1 |
+ Jan04 |
+ UTM JB |
+
+
+ | 17 |
+ B6D2F1 |
+ F |
+ 127 |
+ R0919F2 |
+ Jan04 |
+ UTM JB |
+
+
+ | 18 |
+ B6D2F1 |
+ F |
+ 64 |
+ R1053F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 19 |
+ B6D2F1 |
+ F |
+ 64 |
+ R1053F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 20 |
+ B6D2F1 |
+ M |
+ 127 |
+ R0920F1 |
+ Jan04 |
+ UTM JB |
+
+
+ | 21 |
+ B6D2F1 |
+ M |
+ 127 |
+ R0920F2 |
+ Jan04 |
+ UTM JB |
+
+
+ | 22 |
+ B6D2F1 |
+ M |
+ 66 |
+ R1057F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 23 |
+ BXD1 |
+ M |
+ 181 |
+ R0956F1 |
+ Feb05 |
+ UTM JB |
+
+
+ | 24 |
+ BXD1 |
+ F |
+ 95 |
+ R0895F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 25 |
+ BXD2 |
+ F |
+ 142 |
+ R0907F1 |
+ Feb05 |
+ UAB |
+
+
+ | 26 |
+ BXD5 |
+ F |
+ 56 |
+ R0744F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 27 |
+ BXD5 |
+ M |
+ 71 |
+ R0728F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 28 |
+ BXD6 |
+ F |
+ 57 |
+ R1711F1 |
+ Feb05 |
+ JAX |
+
+
+ | 29 |
+ BXD6 |
+ F |
+ 92 |
+ R0901F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 30 |
+ BXD6 |
+ M |
+ 92 |
+ R0902F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 31 |
+ BXD8 |
+ F |
+ 72 |
+ R0167F1 |
+ Jan04 |
+ UAB |
+
+
+ | 32 |
+ BXD9 |
+ F |
+ 86 |
+ R0908F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 33 |
+ BXD9 |
+ M |
+ 86 |
+ R0909F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 34 |
+ BXD11 |
+ F |
+ 97 |
+ R0745F1 |
+ Feb05 |
+ UAB |
+
+
+ | 35 |
+ BXD11 |
+ M |
+ 92 |
+ R0666F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 36 |
+ BXD12 |
+ F |
+ 64 |
+ R0896F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 37 |
+ BXD12 |
+ M |
+ 64 |
+ R0897F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 38 |
+ BXD13 |
+ F |
+ 86 |
+ R0730F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 39 |
+ BXD13 |
+ F |
+ 86 |
+ R0748F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 40 |
+ BXD13 |
+ M |
+ 76 |
+ R0929F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 41 |
+ BXD14 |
+ M |
+ 91 |
+ R0912F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 42 |
+ BXD14 |
+ M |
+ 68 |
+ R1051F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 43 |
+ BXD15 |
+ F |
+ 80 |
+ R0928F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 44 |
+ BXD18 |
+ F |
+ 108 |
+ R0771F1 |
+ Jan04 |
+ UAB |
+
+
+ | 45 |
+ BXD19 |
+ M |
+ 157 |
+ R1229F1 |
+ Feb05 |
+ UTM JB |
+
+
+ | 46 |
+ BXD19 |
+ F |
+ 56 |
+ R0236F1 |
+ Jan04 |
+ UAB |
+
+
+ | 47 |
+ BXD21 |
+ F |
+ 67 |
+ R0740F1 |
+ Jan04 |
+ UAB |
+
+
+ | 48 |
+ BXD21 |
+ F |
+ 67 |
+ R0740F1 |
+ Feb05 |
+ UAB |
+
+
+ | 49 |
+ BXD23 |
+ F |
+ 66 |
+ R1035F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 50 |
+ BXD23 |
+ M |
+ 66 |
+ R1037F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 51 |
+ BXD23 |
+ F |
+ 88 |
+ R0815F1 |
+ Jan04 |
+ UAB |
+
+
+ | 52 |
+ BXD23 |
+ F |
+ 88 |
+ R0815F1 |
+ Feb05 |
+ UAB |
+
+
+ | 53 |
+ BXD24 |
+ F |
+ 71 |
+ R0914F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 54 |
+ BXD24 |
+ M |
+ 71 |
+ R0913F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 55 |
+ BXD25 |
+ F |
+ 74 |
+ R0373F1 |
+ Jan04 |
+ UTM RW |
+
+
+ | 56 |
+ BXD28 |
+ F |
+ 79 |
+ R0910F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 57 |
+ BXD28 |
+ M |
+ 79 |
+ R0911F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 58 |
+ BXD28 |
+ F |
+ 113 |
+ R0892F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 59 |
+ BXD29 |
+ F |
+ 76 |
+ R0693F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 60 |
+ BXD31 |
+ F |
+ 61 |
+ R1199F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 61 |
+ BXD31 |
+ M |
+ 61 |
+ R1141F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 62 |
+ BXD32 |
+ F |
+ 93 |
+ R0898F1 |
+ Jan04 |
+ UAB |
+
+
+ | 63 |
+ BXD32 |
+ F |
+ 76 |
+ R1214F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 64 |
+ BXD32 |
+ M |
+ 65 |
+ R1478F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 65 |
+ BXD33 |
+ M |
+ 77 |
+ R0915F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 66 |
+ BXD34 |
+ F |
+ 92 |
+ R0900F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 67 |
+ BXD34 |
+ M |
+ 56 |
+ R0617F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 68 |
+ BXD34 |
+ M |
+ 72 |
+ R0916F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 69 |
+ BXD36 |
+ F |
+ 61 |
+ R1145F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 70 |
+ BXD36 |
+ M |
+ 77 |
+ R0926F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 71 |
+ BXD36 |
+ M |
+ 61 |
+ R1211F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 72 |
+ BXD38 |
+ M |
+ 83 |
+ R1208F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 73 |
+ BXD38 |
+ F |
+ 69 |
+ R0729F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 74 |
+ BXD38 |
+ M |
+ 69 |
+ R0731F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 75 |
+ BXD39 |
+ F |
+ 76 |
+ R1712F1 |
+ Feb05 |
+ JAX |
+
+
+ | 76 |
+ BXD39 |
+ M |
+ 71 |
+ R0602F1 |
+ Feb05 |
+ UAB |
+
+
+ | 77 |
+ BXD40 |
+ F |
+ 184 |
+ R0741F1 |
+ Feb05 |
+ UAB |
+
+
+ | 78 |
+ BXD40 |
+ M |
+ 56 |
+ R0894F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 79 |
+ BXD42 |
+ F |
+ 100 |
+ R0742F1 |
+ Feb05 |
+ UAB |
+
+
+ | 80 |
+ BXD42 |
+ M |
+ 97 |
+ R0936F1 |
+ Jan04 |
+ UMemphis |
+
+
+ | 81 |
+ BXD42 |
+ M |
+ 105 |
+ R0937F1 |
+ Feb05 |
+ UMemphis |
+
+
+ | 82 |
+ BXD43 |
+ M |
+ 63 |
+ R1047F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 83 |
+ BXD44 |
+ F |
+ 57 |
+ R1069F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 84 |
+ BXD44 |
+ M |
+ 58 |
+ R1072F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 85 |
+ BXD45 |
+ F |
+ 58 |
+ R1398F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 86 |
+ BXD48 |
+ F |
+ 59 |
+ R0946F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 87 |
+ BXD48 |
+ M |
+ 64 |
+ R0970F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 88 |
+ BXD51 |
+ F |
+ 63 |
+ R1430F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 89 |
+ BXD51 |
+ M |
+ 65 |
+ R1001F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 90 |
+ BXD60 |
+ F |
+ 64 |
+ R0976F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 91 |
+ BXD60 |
+ M |
+ 59 |
+ R1075F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 92 |
+ BXD62 |
+ F |
+ 59 |
+ R1033F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 93 |
+ BXD62 |
+ M |
+ 58 |
+ R1027F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 94 |
+ BXD69 |
+ F |
+ 60 |
+ R1438F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 95 |
+ BXD69 |
+ M |
+ 64 |
+ R1193F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 96 |
+ BXD73 |
+ F |
+ 60 |
+ R1275F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 97 |
+ BXD73 |
+ M |
+ 76 |
+ R1442F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 98 |
+ BXD77 |
+ M |
+ 61 |
+ R1426F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 99 |
+ BXD86 |
+ F |
+ 77 |
+ R1414F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 100 |
+ BXD86 |
+ M |
+ 77 |
+ R1418F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 101 |
+ BXD87 |
+ F |
+ 89 |
+ R1713F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 102 |
+ BXD87 |
+ M |
+ 84 |
+ R1709F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 103 |
+ BXD90 |
+ M |
+ 61 |
+ R1452F |
+ Feb05 |
+ UTM RW |
+
+
+ | 104 |
+ BXD92 |
+ F |
+ 58 |
+ R1299F1 |
+ Feb05 |
+ UTM RW |
+
+
+ | 105 |
+ BXD92 |
+ M |
+ 59 |
+ R1307F1 |
+ Feb05 |
+ UTM RW |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Ibr_m_1004_m/acknowledgment.rtf b/general/datasets/Ibr_m_1004_m/acknowledgment.rtf
new file mode 100644
index 0000000..7b62a11
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_m/acknowledgment.rtf
@@ -0,0 +1 @@
+Data for the microarrays were generously provided by support from NIAAA INIA grants to RWW and Thomas Sutter. Support for sample acquistion and WebQTL have been provided by NIMH Human Brain Project, and the Dunavant Chair of Excellence, University of Tennessee Health Science Center. All arrays were processed at the University of Memphis by Dr. Thomas Sutter and colleagues with support of the INIA Bioanalytical Core.
diff --git a/general/datasets/Ibr_m_1004_m/cases.rtf b/general/datasets/Ibr_m_1004_m/cases.rtf
new file mode 100644
index 0000000..9dc5cbe
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_m/cases.rtf
@@ -0,0 +1,3 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B) and DBA/2J (D). Both B and D strains have been almost fully sequence (8x coverage for B by a public consortium and approximately 1.5x coverage for D by Celera).
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine.
diff --git a/general/datasets/Ibr_m_1004_m/notes.rtf b/general/datasets/Ibr_m_1004_m/notes.rtf
new file mode 100644
index 0000000..f3ea488
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_m/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, Oct 2004. Updated by RWW, Nov 5, 2004.
diff --git a/general/datasets/Ibr_m_1004_m/platform.rtf b/general/datasets/Ibr_m_1004_m/platform.rtf
new file mode 100644
index 0000000..51cbff2
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_m/platform.rtf
@@ -0,0 +1 @@
+Affymetrix 430A and 430B GeneChip Set: Expression data were generated using 430AB array pairs. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on either the Verify UCSC and Verify Ensembl links in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Ibr_m_1004_m/processing.rtf b/general/datasets/Ibr_m_1004_m/processing.rtf
new file mode 100644
index 0000000..4663b88
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_m/processing.rtf
@@ -0,0 +1,29 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each probe signal.
+ - Step 3: We computed the Z scores for each probe signal.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B arrays include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes provide a way to calibrate expression of the A and B arrays to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: We corrected for technical variance introduced by two batches. Means separated by the first batch for each gene are corrected same as means of the second batch.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have modest numbers of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+
+
+
+Probe set data: The original expression values in the Affymetrix CEL files were read into PerfectMatch to generate the normalized PDNN data set.
+
+PDNN values of each array were subsequently normalized to a achieve a mean value of 8 units and a variance of 2 units.
+
+When necessary, we computed the arithmetic mean for technical replicates and treated these as single samples. We then computed the arithmetic mean for the set of 2 to 5 biological replicates for each strain.
+
+
+About the array probe sets names:
+
+
+Most probe sets on the mouse 430A and 430B arrays consist of a total of 22 probes, divided into 11 perfect match(PM) probes and 11 mismatch (MM) controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, several suffix characters that highlight design features, a a final A or B character to specify the array pair member. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene.
+
diff --git a/general/datasets/Ibr_m_1004_m/summary.rtf b/general/datasets/Ibr_m_1004_m/summary.rtf
new file mode 100644
index 0000000..c32676a
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_m/summary.rtf
@@ -0,0 +1 @@
+This October 2004 data freeze provides initial estimates of mRNA expression in brains of adult BXD recombinant inbred mice measured using Affymetrix M430AB microarrays. In contast to the U74Av2 array, this new data set provides broader coverage (~45,000 transcripts) but does not include replicates or as many strains (25 vs 35). Data were generated at UTHSC and the University of Memphis with support from grants from the NIAAA Integrative Neuroscience Initiative on Alcoholism (INIA). Data were processed using the PDNN method of Zhang. To simplify comparison among transforms, PDNN values of each array were adjusted to an average of 8 units and a variance of 2 units.
diff --git a/general/datasets/Ibr_m_1004_m/tissue.rtf b/general/datasets/Ibr_m_1004_m/tissue.rtf
new file mode 100644
index 0000000..cac878a
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_m/tissue.rtf
@@ -0,0 +1,261 @@
+The data set consists of a single batch of Affymetrix mouse expression 430A and 430B GeneChip array pairs. Each AB pair was hybridized in sequence (A array first, B array second) with a pool of brain tissue (forebrain minus olfactory bulb, plus the entire midbrain) taken from three adult animals of closely matched age and the same sex. RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai. All samples were subsequently processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center of Excellence by Thomas R. Sutter and colleagues at the University of Memphis. Before running the main batch of 30 pairs of array, we ran four "test" samples (one male and one female pool from each of the two parental strains, C57BL/6J and DBA/2J). The main set of 30 array pairs includes the same four samples (in other words we have four technical replicates), two F1 hybrid sample (each run two times for a within-batch technical replication), and 22 BXD strains. The data set therefore consists of one male and one female pool from C57BL/6J, DBA/2J, the B6D2F1 hybrid, 11 female BXD samples, and 11 male BXD samples. We should note that the four technical replicates between batches were eventually combined with a correction for a highly significant batch effect. This was done at both the probe and probe set levels to "align" the test batch values with the two main batches. (The ratio of the probe average in the four test arrays to the average of the same probe in the four corresponding main batch arrays was used as a correction factor.) The F1 within-batch technical replicates were simply averaged. In the next batch we will reverse the sex of the BXD samples to achieve a balance with at least 22 BXD strains with one male and one female sample each.
+
+The table below lists the arrays by strain, sex, age, sample identifier, and data results were obtained from the Bioanalytical Core at the University of Memphis. Each array was hybridized to a pool of mRNA from three mice.
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Date |
+
+
+ | B6D2F1 |
+ F |
+ 127 |
+ 919-F1 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ F |
+ 127 |
+ 919-F2 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 920-F1 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 920-F2 |
+ Jan04 |
+
+
+ | C57BL/6J |
+ F |
+ 65 |
+ 903-F1 |
+ Nov03 |
+
+
+ | C57BL/6J |
+ F |
+ 65 |
+ 903-F2 |
+ Jan03 |
+
+
+ | C57BL/6J |
+ M |
+ 66 |
+ 906-F1 |
+ Nov03 |
+
+
+ | C57BL/6J |
+ M |
+ 66 |
+ 906-F2 |
+ Jan04 |
+
+
+ | DBA/2J |
+ F |
+ 60 |
+ 917-F1 |
+ Nov03 |
+
+
+ | DBA/2J |
+ F |
+ 60 |
+ 917-F2 |
+ Jan04 |
+
+
+ | DBA/2J |
+ M |
+ 60 |
+ 918-F1 |
+ Nov03 |
+
+
+ | DBA/2J |
+ M |
+ 60 |
+ 918-F2 |
+ Jan04 |
+
+
+ | BXD1 |
+ F |
+ 95 |
+ 895-F1 |
+ Jan04 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 728-F1 |
+ Jan04 |
+
+
+ | BXD6 |
+ M |
+ 92 |
+ 902-F1 |
+ Jan04 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S167-F1 |
+ Jan04 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 909-F1 |
+ Jan04 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 897-F1 |
+ Jan04 |
+
+
+ | BXD13 |
+ F |
+ 86 |
+ 748-F1 |
+ Jan04 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 912-F1 |
+ Jan04 |
+
+
+ | BXD18 |
+ F |
+ 108 |
+ 771-F1 |
+ Jan04 |
+
+
+ | BXD19 |
+ F |
+ 56 |
+ S236-F1 |
+ Jan04 |
+
+
+ | BXD21 |
+ F |
+ 67 |
+ 740-F1 |
+ Jan04 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 815-F1 |
+ Jan04 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 913-F1 |
+ Jan04 |
+
+
+ | BXD25 |
+ F |
+ 74 |
+ S373-F1 |
+ Jan04 |
+
+
+ | BXD28 |
+ F |
+ 79 |
+ 910-F1 |
+ Jan04 |
+
+
+ | BXD29 |
+ F |
+ 76 |
+ 693-F1 |
+ Jan04 |
+
+
+ | BXD32 |
+ F |
+ 93 |
+ 898-F1 |
+ Jan04 |
+
+
+ | BXD33 |
+ M |
+ 77 |
+ 915-F1 |
+ Jan04 |
+
+
+ | BXD34 |
+ M |
+ 72 |
+ 916-F1 |
+ Jan04 |
+
+
+ | BXD36 |
+ M |
+ 77 |
+ 926-F1 |
+ Jan04 |
+
+
+ | BXD38 |
+ M |
+ 69 |
+ 731-F1 |
+ Jan04 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 936-F1 |
+ Jan04 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Ibr_m_1004_p/acknowledgment.rtf b/general/datasets/Ibr_m_1004_p/acknowledgment.rtf
new file mode 100644
index 0000000..7b62a11
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_p/acknowledgment.rtf
@@ -0,0 +1 @@
+Data for the microarrays were generously provided by support from NIAAA INIA grants to RWW and Thomas Sutter. Support for sample acquistion and WebQTL have been provided by NIMH Human Brain Project, and the Dunavant Chair of Excellence, University of Tennessee Health Science Center. All arrays were processed at the University of Memphis by Dr. Thomas Sutter and colleagues with support of the INIA Bioanalytical Core.
diff --git a/general/datasets/Ibr_m_1004_p/cases.rtf b/general/datasets/Ibr_m_1004_p/cases.rtf
new file mode 100644
index 0000000..9dc5cbe
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_p/cases.rtf
@@ -0,0 +1,3 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B) and DBA/2J (D). Both B and D strains have been almost fully sequence (8x coverage for B by a public consortium and approximately 1.5x coverage for D by Celera).
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine.
diff --git a/general/datasets/Ibr_m_1004_p/notes.rtf b/general/datasets/Ibr_m_1004_p/notes.rtf
new file mode 100644
index 0000000..f3ea488
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_p/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, Oct 2004. Updated by RWW, Nov 5, 2004.
diff --git a/general/datasets/Ibr_m_1004_p/platform.rtf b/general/datasets/Ibr_m_1004_p/platform.rtf
new file mode 100644
index 0000000..51cbff2
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_p/platform.rtf
@@ -0,0 +1 @@
+Affymetrix 430A and 430B GeneChip Set: Expression data were generated using 430AB array pairs. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on either the Verify UCSC and Verify Ensembl links in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Ibr_m_1004_p/processing.rtf b/general/datasets/Ibr_m_1004_p/processing.rtf
new file mode 100644
index 0000000..4663b88
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_p/processing.rtf
@@ -0,0 +1,29 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each probe signal.
+ - Step 3: We computed the Z scores for each probe signal.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B arrays include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes provide a way to calibrate expression of the A and B arrays to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: We corrected for technical variance introduced by two batches. Means separated by the first batch for each gene are corrected same as means of the second batch.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have modest numbers of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+
+
+
+Probe set data: The original expression values in the Affymetrix CEL files were read into PerfectMatch to generate the normalized PDNN data set.
+
+PDNN values of each array were subsequently normalized to a achieve a mean value of 8 units and a variance of 2 units.
+
+When necessary, we computed the arithmetic mean for technical replicates and treated these as single samples. We then computed the arithmetic mean for the set of 2 to 5 biological replicates for each strain.
+
+
+About the array probe sets names:
+
+
+Most probe sets on the mouse 430A and 430B arrays consist of a total of 22 probes, divided into 11 perfect match(PM) probes and 11 mismatch (MM) controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, several suffix characters that highlight design features, a a final A or B character to specify the array pair member. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene.
+
diff --git a/general/datasets/Ibr_m_1004_p/summary.rtf b/general/datasets/Ibr_m_1004_p/summary.rtf
new file mode 100644
index 0000000..c32676a
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_p/summary.rtf
@@ -0,0 +1 @@
+This October 2004 data freeze provides initial estimates of mRNA expression in brains of adult BXD recombinant inbred mice measured using Affymetrix M430AB microarrays. In contast to the U74Av2 array, this new data set provides broader coverage (~45,000 transcripts) but does not include replicates or as many strains (25 vs 35). Data were generated at UTHSC and the University of Memphis with support from grants from the NIAAA Integrative Neuroscience Initiative on Alcoholism (INIA). Data were processed using the PDNN method of Zhang. To simplify comparison among transforms, PDNN values of each array were adjusted to an average of 8 units and a variance of 2 units.
diff --git a/general/datasets/Ibr_m_1004_p/tissue.rtf b/general/datasets/Ibr_m_1004_p/tissue.rtf
new file mode 100644
index 0000000..cac878a
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_p/tissue.rtf
@@ -0,0 +1,261 @@
+The data set consists of a single batch of Affymetrix mouse expression 430A and 430B GeneChip array pairs. Each AB pair was hybridized in sequence (A array first, B array second) with a pool of brain tissue (forebrain minus olfactory bulb, plus the entire midbrain) taken from three adult animals of closely matched age and the same sex. RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai. All samples were subsequently processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center of Excellence by Thomas R. Sutter and colleagues at the University of Memphis. Before running the main batch of 30 pairs of array, we ran four "test" samples (one male and one female pool from each of the two parental strains, C57BL/6J and DBA/2J). The main set of 30 array pairs includes the same four samples (in other words we have four technical replicates), two F1 hybrid sample (each run two times for a within-batch technical replication), and 22 BXD strains. The data set therefore consists of one male and one female pool from C57BL/6J, DBA/2J, the B6D2F1 hybrid, 11 female BXD samples, and 11 male BXD samples. We should note that the four technical replicates between batches were eventually combined with a correction for a highly significant batch effect. This was done at both the probe and probe set levels to "align" the test batch values with the two main batches. (The ratio of the probe average in the four test arrays to the average of the same probe in the four corresponding main batch arrays was used as a correction factor.) The F1 within-batch technical replicates were simply averaged. In the next batch we will reverse the sex of the BXD samples to achieve a balance with at least 22 BXD strains with one male and one female sample each.
+
+The table below lists the arrays by strain, sex, age, sample identifier, and data results were obtained from the Bioanalytical Core at the University of Memphis. Each array was hybridized to a pool of mRNA from three mice.
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Date |
+
+
+ | B6D2F1 |
+ F |
+ 127 |
+ 919-F1 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ F |
+ 127 |
+ 919-F2 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 920-F1 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 920-F2 |
+ Jan04 |
+
+
+ | C57BL/6J |
+ F |
+ 65 |
+ 903-F1 |
+ Nov03 |
+
+
+ | C57BL/6J |
+ F |
+ 65 |
+ 903-F2 |
+ Jan03 |
+
+
+ | C57BL/6J |
+ M |
+ 66 |
+ 906-F1 |
+ Nov03 |
+
+
+ | C57BL/6J |
+ M |
+ 66 |
+ 906-F2 |
+ Jan04 |
+
+
+ | DBA/2J |
+ F |
+ 60 |
+ 917-F1 |
+ Nov03 |
+
+
+ | DBA/2J |
+ F |
+ 60 |
+ 917-F2 |
+ Jan04 |
+
+
+ | DBA/2J |
+ M |
+ 60 |
+ 918-F1 |
+ Nov03 |
+
+
+ | DBA/2J |
+ M |
+ 60 |
+ 918-F2 |
+ Jan04 |
+
+
+ | BXD1 |
+ F |
+ 95 |
+ 895-F1 |
+ Jan04 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 728-F1 |
+ Jan04 |
+
+
+ | BXD6 |
+ M |
+ 92 |
+ 902-F1 |
+ Jan04 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S167-F1 |
+ Jan04 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 909-F1 |
+ Jan04 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 897-F1 |
+ Jan04 |
+
+
+ | BXD13 |
+ F |
+ 86 |
+ 748-F1 |
+ Jan04 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 912-F1 |
+ Jan04 |
+
+
+ | BXD18 |
+ F |
+ 108 |
+ 771-F1 |
+ Jan04 |
+
+
+ | BXD19 |
+ F |
+ 56 |
+ S236-F1 |
+ Jan04 |
+
+
+ | BXD21 |
+ F |
+ 67 |
+ 740-F1 |
+ Jan04 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 815-F1 |
+ Jan04 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 913-F1 |
+ Jan04 |
+
+
+ | BXD25 |
+ F |
+ 74 |
+ S373-F1 |
+ Jan04 |
+
+
+ | BXD28 |
+ F |
+ 79 |
+ 910-F1 |
+ Jan04 |
+
+
+ | BXD29 |
+ F |
+ 76 |
+ 693-F1 |
+ Jan04 |
+
+
+ | BXD32 |
+ F |
+ 93 |
+ 898-F1 |
+ Jan04 |
+
+
+ | BXD33 |
+ M |
+ 77 |
+ 915-F1 |
+ Jan04 |
+
+
+ | BXD34 |
+ M |
+ 72 |
+ 916-F1 |
+ Jan04 |
+
+
+ | BXD36 |
+ M |
+ 77 |
+ 926-F1 |
+ Jan04 |
+
+
+ | BXD38 |
+ M |
+ 69 |
+ 731-F1 |
+ Jan04 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 936-F1 |
+ Jan04 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Ibr_m_1004_r/acknowledgment.rtf b/general/datasets/Ibr_m_1004_r/acknowledgment.rtf
new file mode 100644
index 0000000..7b62a11
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data for the microarrays were generously provided by support from NIAAA INIA grants to RWW and Thomas Sutter. Support for sample acquistion and WebQTL have been provided by NIMH Human Brain Project, and the Dunavant Chair of Excellence, University of Tennessee Health Science Center. All arrays were processed at the University of Memphis by Dr. Thomas Sutter and colleagues with support of the INIA Bioanalytical Core.
diff --git a/general/datasets/Ibr_m_1004_r/cases.rtf b/general/datasets/Ibr_m_1004_r/cases.rtf
new file mode 100644
index 0000000..9dc5cbe
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_r/cases.rtf
@@ -0,0 +1,3 @@
+We have exploited a set of BXD recombinant inbred strains. The parental strains from which all BXD lines are derived are C57BL/6J (B) and DBA/2J (D). Both B and D strains have been almost fully sequence (8x coverage for B by a public consortium and approximately 1.5x coverage for D by Celera).
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine.
diff --git a/general/datasets/Ibr_m_1004_r/notes.rtf b/general/datasets/Ibr_m_1004_r/notes.rtf
new file mode 100644
index 0000000..f3ea488
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_r/notes.rtf
@@ -0,0 +1 @@
+This text file originally generated by RWW, YHQ, and EJC, Oct 2004. Updated by RWW, Nov 5, 2004.
diff --git a/general/datasets/Ibr_m_1004_r/platform.rtf b/general/datasets/Ibr_m_1004_r/platform.rtf
new file mode 100644
index 0000000..51cbff2
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_r/platform.rtf
@@ -0,0 +1 @@
+Affymetrix 430A and 430B GeneChip Set: Expression data were generated using 430AB array pairs. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on either the Verify UCSC and Verify Ensembl links in the Trait Data and Editing Form (right side of the Location line).
diff --git a/general/datasets/Ibr_m_1004_r/processing.rtf b/general/datasets/Ibr_m_1004_r/processing.rtf
new file mode 100644
index 0000000..4663b88
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_r/processing.rtf
@@ -0,0 +1,29 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each probe signal.
+ - Step 3: We computed the Z scores for each probe signal.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B arrays include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes provide a way to calibrate expression of the A and B arrays to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+ - Step 7: We corrected for technical variance introduced by two batches. Means separated by the first batch for each gene are corrected same as means of the second batch.
+ - Step 8: Finally, we compute the arithmetic mean of the values for the set of microarrays for each strain. In this data set we have modest numbers of replicates and for this reason we do not yet provide error terms for transcripts or probes. Note, that we have not (yet) corrected for variance introduced by differences in sex, age, or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We expect to add statistical controls and adjustments for these variables in subsequent versions of WebQTL.
+
+
+
+
+Probe set data: The original expression values in the Affymetrix CEL files were read into PerfectMatch to generate the normalized PDNN data set.
+
+PDNN values of each array were subsequently normalized to a achieve a mean value of 8 units and a variance of 2 units.
+
+When necessary, we computed the arithmetic mean for technical replicates and treated these as single samples. We then computed the arithmetic mean for the set of 2 to 5 biological replicates for each strain.
+
+
+About the array probe sets names:
+
+
+Most probe sets on the mouse 430A and 430B arrays consist of a total of 22 probes, divided into 11 perfect match(PM) probes and 11 mismatch (MM) controls. Each set of these 25-nucleotide-long probes has an identifier code that includes a unique number, an underscore character, several suffix characters that highlight design features, a a final A or B character to specify the array pair member. The most common probe set suffix is at. This code indicates that the probes should hybridize relatively selectively with the complementary anti-sense target (i.e., the complemenary RNA) produced from a single gene.
+
diff --git a/general/datasets/Ibr_m_1004_r/summary.rtf b/general/datasets/Ibr_m_1004_r/summary.rtf
new file mode 100644
index 0000000..c32676a
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_r/summary.rtf
@@ -0,0 +1 @@
+This October 2004 data freeze provides initial estimates of mRNA expression in brains of adult BXD recombinant inbred mice measured using Affymetrix M430AB microarrays. In contast to the U74Av2 array, this new data set provides broader coverage (~45,000 transcripts) but does not include replicates or as many strains (25 vs 35). Data were generated at UTHSC and the University of Memphis with support from grants from the NIAAA Integrative Neuroscience Initiative on Alcoholism (INIA). Data were processed using the PDNN method of Zhang. To simplify comparison among transforms, PDNN values of each array were adjusted to an average of 8 units and a variance of 2 units.
diff --git a/general/datasets/Ibr_m_1004_r/tissue.rtf b/general/datasets/Ibr_m_1004_r/tissue.rtf
new file mode 100644
index 0000000..cac878a
--- /dev/null
+++ b/general/datasets/Ibr_m_1004_r/tissue.rtf
@@ -0,0 +1,261 @@
+The data set consists of a single batch of Affymetrix mouse expression 430A and 430B GeneChip array pairs. Each AB pair was hybridized in sequence (A array first, B array second) with a pool of brain tissue (forebrain minus olfactory bulb, plus the entire midbrain) taken from three adult animals of closely matched age and the same sex. RNA was extracted at UTHSC by Lu Lu, Zhiping Jia, and Hongtao Zhai. All samples were subsequently processed in the INIA Bioanalytical Core at the W. Harry Feinstone Center of Excellence by Thomas R. Sutter and colleagues at the University of Memphis. Before running the main batch of 30 pairs of array, we ran four "test" samples (one male and one female pool from each of the two parental strains, C57BL/6J and DBA/2J). The main set of 30 array pairs includes the same four samples (in other words we have four technical replicates), two F1 hybrid sample (each run two times for a within-batch technical replication), and 22 BXD strains. The data set therefore consists of one male and one female pool from C57BL/6J, DBA/2J, the B6D2F1 hybrid, 11 female BXD samples, and 11 male BXD samples. We should note that the four technical replicates between batches were eventually combined with a correction for a highly significant batch effect. This was done at both the probe and probe set levels to "align" the test batch values with the two main batches. (The ratio of the probe average in the four test arrays to the average of the same probe in the four corresponding main batch arrays was used as a correction factor.) The F1 within-batch technical replicates were simply averaged. In the next batch we will reverse the sex of the BXD samples to achieve a balance with at least 22 BXD strains with one male and one female sample each.
+
+The table below lists the arrays by strain, sex, age, sample identifier, and data results were obtained from the Bioanalytical Core at the University of Memphis. Each array was hybridized to a pool of mRNA from three mice.
+
+
+
+
+
+
+
+
+ | Strain |
+ Sex |
+ Age |
+ SampleID |
+ Date |
+
+
+ | B6D2F1 |
+ F |
+ 127 |
+ 919-F1 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ F |
+ 127 |
+ 919-F2 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 920-F1 |
+ Jan04 |
+
+
+ | B6D2F1 |
+ M |
+ 127 |
+ 920-F2 |
+ Jan04 |
+
+
+ | C57BL/6J |
+ F |
+ 65 |
+ 903-F1 |
+ Nov03 |
+
+
+ | C57BL/6J |
+ F |
+ 65 |
+ 903-F2 |
+ Jan03 |
+
+
+ | C57BL/6J |
+ M |
+ 66 |
+ 906-F1 |
+ Nov03 |
+
+
+ | C57BL/6J |
+ M |
+ 66 |
+ 906-F2 |
+ Jan04 |
+
+
+ | DBA/2J |
+ F |
+ 60 |
+ 917-F1 |
+ Nov03 |
+
+
+ | DBA/2J |
+ F |
+ 60 |
+ 917-F2 |
+ Jan04 |
+
+
+ | DBA/2J |
+ M |
+ 60 |
+ 918-F1 |
+ Nov03 |
+
+
+ | DBA/2J |
+ M |
+ 60 |
+ 918-F2 |
+ Jan04 |
+
+
+ | BXD1 |
+ F |
+ 95 |
+ 895-F1 |
+ Jan04 |
+
+
+ | BXD5 |
+ M |
+ 71 |
+ 728-F1 |
+ Jan04 |
+
+
+ | BXD6 |
+ M |
+ 92 |
+ 902-F1 |
+ Jan04 |
+
+
+ | BXD8 |
+ F |
+ 72 |
+ S167-F1 |
+ Jan04 |
+
+
+ | BXD9 |
+ M |
+ 86 |
+ 909-F1 |
+ Jan04 |
+
+
+ | BXD12 |
+ M |
+ 64 |
+ 897-F1 |
+ Jan04 |
+
+
+ | BXD13 |
+ F |
+ 86 |
+ 748-F1 |
+ Jan04 |
+
+
+ | BXD14 |
+ M |
+ 91 |
+ 912-F1 |
+ Jan04 |
+
+
+ | BXD18 |
+ F |
+ 108 |
+ 771-F1 |
+ Jan04 |
+
+
+ | BXD19 |
+ F |
+ 56 |
+ S236-F1 |
+ Jan04 |
+
+
+ | BXD21 |
+ F |
+ 67 |
+ 740-F1 |
+ Jan04 |
+
+
+ | BXD23 |
+ F |
+ 88 |
+ 815-F1 |
+ Jan04 |
+
+
+ | BXD24 |
+ M |
+ 71 |
+ 913-F1 |
+ Jan04 |
+
+
+ | BXD25 |
+ F |
+ 74 |
+ S373-F1 |
+ Jan04 |
+
+
+ | BXD28 |
+ F |
+ 79 |
+ 910-F1 |
+ Jan04 |
+
+
+ | BXD29 |
+ F |
+ 76 |
+ 693-F1 |
+ Jan04 |
+
+
+ | BXD32 |
+ F |
+ 93 |
+ 898-F1 |
+ Jan04 |
+
+
+ | BXD33 |
+ M |
+ 77 |
+ 915-F1 |
+ Jan04 |
+
+
+ | BXD34 |
+ M |
+ 72 |
+ 916-F1 |
+ Jan04 |
+
+
+ | BXD36 |
+ M |
+ 77 |
+ 926-F1 |
+ Jan04 |
+
+
+ | BXD38 |
+ M |
+ 69 |
+ 731-F1 |
+ Jan04 |
+
+
+ | BXD42 |
+ M |
+ 97 |
+ 936-F1 |
+ Jan04 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Illum_bxd_pbl_1108/summary.rtf b/general/datasets/Illum_bxd_pbl_1108/summary.rtf
new file mode 100644
index 0000000..172b4ee
--- /dev/null
+++ b/general/datasets/Illum_bxd_pbl_1108/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 67, Name: UWA Illumina PBL (Nov08) RSN **
\ No newline at end of file
diff --git a/general/datasets/Illum_bxd_spl_1108/summary.rtf b/general/datasets/Illum_bxd_spl_1108/summary.rtf
new file mode 100644
index 0000000..7b131b7
--- /dev/null
+++ b/general/datasets/Illum_bxd_spl_1108/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 65, Name: UWA Illumina Spleen (Nov08) RSN **
\ No newline at end of file
diff --git a/general/datasets/Illum_bxd_thy_1108/summary.rtf b/general/datasets/Illum_bxd_thy_1108/summary.rtf
new file mode 100644
index 0000000..f075479
--- /dev/null
+++ b/general/datasets/Illum_bxd_thy_1108/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 66, Name: UWA Illumina Thymus (Nov08) RSN **
\ No newline at end of file
diff --git a/general/datasets/Illum_lxs_hipp_loess0807/acknowledgment.rtf b/general/datasets/Illum_lxs_hipp_loess0807/acknowledgment.rtf
new file mode 100644
index 0000000..d8f3e9a
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess0807/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Data source acknowledgment:
+
+Data were generated with funds to Lu Lu, Beth Bennett, Mike Miles, Melloni Cook from INIA. · Lu Lu, M.D. Grant Support: NIH U01AA13499, U24AA13513 (Lu Lu, PI)
diff --git a/general/datasets/Illum_lxs_hipp_loess0807/cases.rtf b/general/datasets/Illum_lxs_hipp_loess0807/cases.rtf
new file mode 100644
index 0000000..efa4371
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess0807/cases.rtf
@@ -0,0 +1,2140 @@
+Quality Control on Sex Labels: Sex of the samples was validated using sex-specific probe set.
+
+
+
+
+ |
+ Legend: We evaluated whether or not the sex of samples were labeled correctly by measuring the expression of Xist using probe ILM106520068. In this bar chart the expression of Xist is very low in LXS114 and has a low error term. This is because both arrays are male samples rather than 1 male and 1 female sample.
+
+
+
+ Data Table 1:
+
+
+ This table lists all arrays by order of strain (index) and includes data on tube ID, strain, age, sex, F generation number, number of animals in each sample pool (pool size), slide ID, slide position (A through F), scan date, and scan batch.
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ gener-
+ ation |
+ pool
+ size |
+ slide
+ ID |
+ slide
+ position |
+ batch
+ by slide |
+ scan
+ batch |
+
+
+ | 1 |
+ R2851H2 |
+ ILS |
+ 77 |
+ F |
+ >100 |
+ 4 |
+ 1523516003 |
+ B |
+ 1 |
+ 1 |
+
+
+ | 2 |
+ R0595H2 |
+ ILS |
+ 71 |
+ F |
+ >100 |
+ 2 |
+ 1523516030 |
+ B |
+ 4 |
+ 2 |
+
+
+ | 3 |
+ R2874H2 |
+ ILS |
+ 78 |
+ M |
+ >100 |
+ 4 |
+ 1523516011 |
+ B |
+ 2 |
+ 1 |
+
+
+ | 4 |
+ R0585H2 |
+ ILS |
+ 65 |
+ M |
+ >100 |
+ 2 |
+ 1523516028 |
+ A |
+ 3 |
+ 2 |
+
+
+ | 5 |
+ R3281H1 |
+ ILSXISSF1 |
+ 90 |
+ F |
+ NA |
+ 3 |
+ 1562224029 |
+ A |
+ 28 |
+ 13 |
+
+
+ | 6 |
+ R2857H2 |
+ ISS |
+ 75 |
+ F |
+ >100 |
+ 4 |
+ 1523516011 |
+ A |
+ 2 |
+ 1 |
+
+
+ | 7 |
+ R0589H2 |
+ ISS |
+ 73 |
+ F |
+ >100 |
+ 2 |
+ 1523516028 |
+ B |
+ 3 |
+ 2 |
+
+
+ | 8 |
+ R2955H2 |
+ ISS |
+ 53 |
+ M |
+ >100 |
+ 3 |
+ 1523516003 |
+ A |
+ 1 |
+ 1 |
+
+
+ | 9 |
+ R0578H2 |
+ ISS |
+ 67 |
+ M |
+ >100 |
+ 2 |
+ 1523516030 |
+ A |
+ 4 |
+ 2 |
+
+
+ | 10 |
+ R3282H1 |
+ ISSXILSF1 |
+ 97 |
+ M |
+ NA |
+ 3 |
+ 1562224029 |
+ B |
+ 28 |
+ 13 |
+
+
+ | 11 |
+ R2013H2 |
+ LXS10 |
+ 84 |
+ F |
+ 27 |
+ 2 |
+ 1562224049 |
+ E |
+ 18 |
+ 9 |
+
+
+ | 12 |
+ R1993H2 |
+ LXS10 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1562224036 |
+ E |
+ 17 |
+ 9 |
+
+
+ | 13 |
+ R1997H2 |
+ LXS100 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ A |
+ 18 |
+ 9 |
+
+
+ | 14 |
+ R1983H2 |
+ LXS100 |
+ 77 |
+ M |
+ 25 |
+ 2 |
+ 1562224047 |
+ F |
+ 16 |
+ 8 |
+
+
+ | 15 |
+ R2083H2 |
+ LXS101 |
+ 85 |
+ F |
+ 28 |
+ 2 |
+ 1562224050 |
+ B |
+ 19 |
+ 9 |
+
+
+ | 16 |
+ R2084H2 |
+ LXS101 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224050 |
+ C |
+ 19 |
+ 9 |
+
+
+ | 17 |
+ R2186H2 |
+ LXS102 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1523516001 |
+ C |
+ 9 |
+ 5 |
+
+
+ | 18 |
+ R2187H2 |
+ LXS102 |
+ 73 |
+ M |
+ 29 |
+ 2 |
+ 1562224053 |
+ C |
+ 20 |
+ 10 |
+
+
+ | 19 |
+ R2809H2 |
+ LXS103 |
+ 72 |
+ F |
+ 26 |
+ 2 |
+ 1562224034 |
+ C |
+ 23 |
+ 11 |
+
+
+ | 20 |
+ R2854H1 |
+ LXS103 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516006 |
+ D |
+ 6 |
+ 3 |
+
+
+ | 21 |
+ R2735H2 |
+ LXS107 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516028 |
+ D |
+ 3 |
+ 2 |
+
+
+ | 22 |
+ R2738H2 |
+ LXS107 |
+ 78 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ C |
+ 21 |
+ 10 |
+
+
+ | 23 |
+ R2840H2 |
+ LXS110 |
+ 67 |
+ F |
+ 25 |
+ 2 |
+ 1562224037 |
+ D |
+ 24 |
+ 11 |
+
+
+ | 24 |
+ R2157H2 |
+ LXS110 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516033 |
+ E |
+ 8 |
+ 4 |
+
+
+ | 25 |
+ R2172H2 |
+ LXS112 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ B |
+ 9 |
+ 5 |
+
+
+ | 26 |
+ R2841H2 |
+ LXS112 |
+ 84 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ D |
+ 27 |
+ 12 |
+
+
+ | 27 |
+ R2188H2 |
+ LXS114 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224053 |
+ D |
+ 20 |
+ 10 |
+
+
+ | 28 |
+ R2204H2 |
+ LXS114 |
+ 72 |
+ M |
+ 28 |
+ 2 |
+ 1523516001 |
+ D |
+ 9 |
+ 5 |
+
+
+ | 29 |
+ R2168H2 |
+ LXS115 |
+ 80 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ A |
+ 9 |
+ 5 |
+
+
+ | 30 |
+ R2085H2 |
+ LXS115 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ D |
+ 19 |
+ 9 |
+
+
+ | 31 |
+ R2811H2 |
+ LXS117 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224034 |
+ D |
+ 23 |
+ 11 |
+
+
+ | 32 |
+ R2212H2 |
+ LXS117 |
+ 74 |
+ M |
+ 27 |
+ 2 |
+ 1523516001 |
+ E |
+ 9 |
+ 5 |
+
+
+ | 33 |
+ R1992H2 |
+ LXS122 |
+ 86 |
+ F |
+ 26 |
+ 2 |
+ 1562224036 |
+ D |
+ 17 |
+ 9 |
+
+
+ | 34 |
+ R2219H2 |
+ LXS122 |
+ 72 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ A |
+ 21 |
+ 10 |
+
+
+ | 35 |
+ R2876H2 |
+ LXS123 |
+ 87 |
+ F |
+ 28 |
+ 2 |
+ 1562224038 |
+ C |
+ 25 |
+ 11 |
+
+
+ | 36 |
+ R2832H1 |
+ LXS123 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1523516011 |
+ E |
+ 2 |
+ 1 |
+
+
+ | 37 |
+ R2872H1 |
+ LXS124 |
+ 83 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ E |
+ 6 |
+ 3 |
+
+
+ | 38 |
+ R2871H2 |
+ LXS124 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224042 |
+ F |
+ 27 |
+ 12 |
+
+
+ | 39 |
+ R1909H2 |
+ LXS13 |
+ 79 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ D |
+ 13 |
+ 7 |
+
+
+ | 40 |
+ R1901H2 |
+ LXS13 |
+ 81 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ D |
+ 26 |
+ 12 |
+
+
+ | 41 |
+ R2023H2 |
+ LXS14 |
+ 86 |
+ F |
+ 25 |
+ 2 |
+ 1562224050 |
+ A |
+ 19 |
+ 9 |
+
+
+ | 42 |
+ R1612H2 |
+ LXS14 |
+ 85 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ A |
+ 10 |
+ 5 |
+
+
+ | 43 |
+ R1936H2 |
+ LXS16 |
+ 81 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ E |
+ 13 |
+ 7 |
+
+
+ | 44 |
+ R1912H2 |
+ LXS16 |
+ 81 |
+ M |
+ 25 |
+ 2 |
+ 1523516033 |
+ B |
+ 8 |
+ 4 |
+
+
+ | 45 |
+ R1961H2 |
+ LXS19 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516029 |
+ F |
+ 14 |
+ 7 |
+
+
+ | 46 |
+ R1904H2 |
+ LXS19 |
+ 66 |
+ M |
+ 26 |
+ 2 |
+ 1523516024 |
+ B |
+ 13 |
+ 7 |
+
+
+ | 47 |
+ R1883H2 |
+ LXS2 |
+ 71 |
+ F |
+ 27 |
+ 2 |
+ 1523516009 |
+ F |
+ 12 |
+ 6 |
+
+
+ | 48 |
+ R2753H2 |
+ LXS2 |
+ 74 |
+ M |
+ 28 |
+ 2 |
+ 1523516030 |
+ E |
+ 4 |
+ 2 |
+
+
+ | 49 |
+ R1729H2 |
+ LXS22 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516032 |
+ E |
+ 7 |
+ 4 |
+
+
+ | 50 |
+ R2743H2 |
+ LXS22 |
+ 79 |
+ M |
+ 27 |
+ 2 |
+ 1562224054 |
+ D |
+ 21 |
+ 10 |
+
+
+ | 51 |
+ R1966H2 |
+ LXS23 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224032 |
+ D |
+ 15 |
+ 8 |
+
+
+ | 52 |
+ R1971H2 |
+ LXS23 |
+ 73 |
+ M |
+ 26 |
+ 2 |
+ 1562224047 |
+ A |
+ 16 |
+ 8 |
+
+
+ | 53 |
+ R2795H2 |
+ LXS24 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516003 |
+ C |
+ 1 |
+ 1 |
+
+
+ | 54 |
+ R1755H2 |
+ LXS24 |
+ 56 |
+ M |
+ 25 |
+ 2 |
+ 1523516007 |
+ A |
+ 11 |
+ 6 |
+
+
+ | 55 |
+ R1986H2 |
+ LXS25 |
+ 75 |
+ F |
+ 27 |
+ 2 |
+ 1562224036 |
+ A |
+ 17 |
+ 9 |
+
+
+ | 56 |
+ R2006H2 |
+ LXS25 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1562224049 |
+ C |
+ 18 |
+ 9 |
+
+
+ | 57 |
+ R2014H2 |
+ LXS26 |
+ 82 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ F |
+ 18 |
+ 9 |
+
+
+ | 58 |
+ R2009H2 |
+ LXS26 |
+ 82 |
+ M |
+ 26 |
+ 2 |
+ 1562224049 |
+ D |
+ 18 |
+ 9 |
+
+
+ | 59 |
+ R2824H1 |
+ LXS28 |
+ 67 |
+ F |
+ 28 |
+ 2 |
+ 1562224042 |
+ A |
+ 27 |
+ 12 |
+
+
+ | 60 |
+ R1753H1 |
+ LXS28 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1562224041 |
+ F |
+ 26 |
+ 12 |
+
+
+ | 61 |
+ R2765H2 |
+ LXS3 |
+ 63 |
+ F |
+ 27 |
+ 2 |
+ 1523516005 |
+ B |
+ 5 |
+ 3 |
+
+
+ | 62 |
+ R1898H2 |
+ LXS3 |
+ 81 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ C |
+ 26 |
+ 12 |
+
+
+ | 63 |
+ R2764H2 |
+ LXS31 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1562224060 |
+ C |
+ 22 |
+ 10 |
+
+
+ | 64 |
+ R1908H2 |
+ LXS31 |
+ 80 |
+ M |
+ 28 |
+ 2 |
+ 1523516024 |
+ C |
+ 13 |
+ 7 |
+
+
+ | 65 |
+ R2758H2 |
+ LXS32 |
+ 70 |
+ F |
+ 26 |
+ 2 |
+ 1523516030 |
+ F |
+ 4 |
+ 2 |
+
+
+ | 66 |
+ R1743H1 |
+ LXS32 |
+ 67 |
+ M |
+ 25 |
+ 2 |
+ 1562224041 |
+ E |
+ 26 |
+ 12 |
+
+
+ | 67 |
+ R2794H2 |
+ LXS34 |
+ 75 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ B |
+ 23 |
+ 11 |
+
+
+ | 68 |
+ R2870H2 |
+ LXS34 |
+ 78 |
+ F |
+ 27 |
+ 2 |
+ 1562224029 |
+ C |
+ 28 |
+ 13 |
+
+
+ | 69 |
+ R2746H2 |
+ LXS35 |
+ 80 |
+ F |
+ 22 |
+ 2 |
+ 1523516030 |
+ C |
+ 4 |
+ 2 |
+
+
+ | 70 |
+ R2747H2 |
+ LXS35 |
+ 81 |
+ M |
+ 22 |
+ 2 |
+ 1562224060 |
+ A |
+ 22 |
+ 10 |
+
+
+ | 71 |
+ R1968H2 |
+ LXS36 |
+ 76 |
+ F |
+ 25 |
+ 2 |
+ 1562224032 |
+ E |
+ 15 |
+ 8 |
+
+
+ | 72 |
+ R1640H2 |
+ LXS36 |
+ 76 |
+ M |
+ 25 |
+ 2 |
+ 1523516032 |
+ C |
+ 7 |
+ 4 |
+
+
+ | 73 |
+ R2835H1 |
+ LXS38 |
+ 67 |
+ F |
+ 27 |
+ 2 |
+ 1523516011 |
+ F |
+ 2 |
+ 1 |
+
+
+ | 74 |
+ R2842H2 |
+ LXS38 |
+ 67 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ E |
+ 27 |
+ 12 |
+
+
+ | 75 |
+ R2210H2 |
+ LXS39 |
+ 81 |
+ F |
+ 28 |
+ 2 |
+ 1562224053 |
+ E |
+ 20 |
+ 10 |
+
+
+ | 76 |
+ R2736H2 |
+ LXS39 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516028 |
+ E |
+ 3 |
+ 2 |
+
+
+ | 77 |
+ R1978H2 |
+ LXS41 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1562224047 |
+ C |
+ 16 |
+ 8 |
+
+
+ | 78 |
+ R1783H2 |
+ LXS41 |
+ 56 |
+ M |
+ 26 |
+ 2 |
+ 1523516007 |
+ D |
+ 11 |
+ 6 |
+
+
+ | 79 |
+ R2822H2 |
+ LXS42 |
+ 66 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ F |
+ 23 |
+ 11 |
+
+
+ | 80 |
+ R2769H2 |
+ LXS42 |
+ 70 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ B |
+ 27 |
+ 12 |
+
+
+ | 81 |
+ R1974H2 |
+ LXS43 |
+ 84 |
+ F |
+ 26 |
+ 2 |
+ 1562224047 |
+ B |
+ 16 |
+ 8 |
+
+
+ | 82 |
+ R1733H2 |
+ LXS43 |
+ 72 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ C |
+ 10 |
+ 5 |
+
+
+ | 83 |
+ R1756H2 |
+ LXS46 |
+ 56 |
+ F |
+ 25 |
+ 2 |
+ 1523516007 |
+ B |
+ 11 |
+ 6 |
+
+
+ | 84 |
+ R1727H2 |
+ LXS46 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1523516032 |
+ D |
+ 7 |
+ 4 |
+
+
+ | 85 |
+ R1970H2 |
+ LXS48 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1562224032 |
+ F |
+ 15 |
+ 8 |
+
+
+ | 86 |
+ R1981H2 |
+ LXS48 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ C |
+ 27 |
+ 12 |
+
+
+ | 87 |
+ R1957H2 |
+ LXS49 |
+ 72 |
+ F |
+ 25 |
+ 2 |
+ 1523516029 |
+ C |
+ 14 |
+ 7 |
+
+
+ | 88 |
+ R2259H2 |
+ LXS49 |
+ 72 |
+ M |
+ 25 |
+ 2 |
+ 1523516028 |
+ C |
+ 3 |
+ 2 |
+
+
+ | 89 |
+ R2836H1 |
+ LXS5 |
+ 68 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ A |
+ 6 |
+ 3 |
+
+
+ | 90 |
+ R2213H2 |
+ LXS5 |
+ 80 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ F |
+ 20 |
+ 10 |
+
+
+ | 91 |
+ R2791H2 |
+ LXS50 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ A |
+ 23 |
+ 11 |
+
+
+ | 92 |
+ R1789H2 |
+ LXS50 |
+ 57 |
+ M |
+ 26 |
+ 2 |
+ 1523516033 |
+ A |
+ 8 |
+ 4 |
+
+
+ | 93 |
+ R1740H2 |
+ LXS51 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1523516032 |
+ F |
+ 7 |
+ 4 |
+
+
+ | 94 |
+ R1734H2 |
+ LXS51 |
+ 68 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ D |
+ 10 |
+ 5 |
+
+
+ | 95 |
+ R2786H2 |
+ LXS52 |
+ 61 |
+ F |
+ 27 |
+ 2 |
+ 1562224060 |
+ D |
+ 22 |
+ 10 |
+
+
+ | 96 |
+ R2768H2 |
+ LXS52 |
+ 61 |
+ M |
+ 27 |
+ 2 |
+ 1523516005 |
+ C |
+ 5 |
+ 3 |
+
+
+ | 97 |
+ R2154H2 |
+ LXS54 |
+ 70 |
+ F |
+ 27 |
+ 2 |
+ 1523516033 |
+ D |
+ 8 |
+ 4 |
+
+
+ | 98 |
+ R2155H2 |
+ LXS54 |
+ 70 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ A |
+ 20 |
+ 10 |
+
+
+ | 99 |
+ R1821H2 |
+ LXS55 |
+ 77 |
+ F |
+ 25 |
+ 2 |
+ 1523516009 |
+ C |
+ 12 |
+ 6 |
+
+
+ | 100 |
+ R1951H2 |
+ LXS55 |
+ 74 |
+ M |
+ 26 |
+ 2 |
+ 1523516024 |
+ F |
+ 13 |
+ 7 |
+
+
+ | 101 |
+ R2789H2 |
+ LXS56 |
+ 71 |
+ F |
+ 25 |
+ 2 |
+ 1523516005 |
+ F |
+ 5 |
+ 3 |
+
+
+ | 102 |
+ R2788H2 |
+ LXS56 |
+ 71 |
+ M |
+ 25 |
+ 2 |
+ 1562224060 |
+ F |
+ 22 |
+ 10 |
+
+
+ | 103 |
+ R2787H2 |
+ LXS59 |
+ 66 |
+ F |
+ 29 |
+ 2 |
+ 1562224060 |
+ E |
+ 22 |
+ 10 |
+
+
+ | 104 |
+ R2785H2 |
+ LXS59 |
+ 62 |
+ M |
+ 29 |
+ 2 |
+ 1523516005 |
+ E |
+ 5 |
+ 3 |
+
+
+ | 105 |
+ R1791H2 |
+ LXS60 |
+ 58 |
+ F |
+ 27 |
+ 2 |
+ 1562224038 |
+ D |
+ 25 |
+ 11 |
+
+
+ | 106 |
+ R1792H2 |
+ LXS60 |
+ 64 |
+ M |
+ 27 |
+ 2 |
+ 1523516007 |
+ E |
+ 11 |
+ 6 |
+
+
+ | 107 |
+ R1796H2 |
+ LXS62 |
+ 58 |
+ F |
+ 27 |
+ 2 |
+ 1523516007 |
+ F |
+ 11 |
+ 6 |
+
+
+ | 108 |
+ R1797H2 |
+ LXS62 |
+ 58 |
+ M |
+ 27 |
+ 2 |
+ 1562224038 |
+ E |
+ 25 |
+ 11 |
+
+
+ | 109 |
+ R2220H2 |
+ LXS64 |
+ 71 |
+ F |
+ 28 |
+ 2 |
+ 1523516001 |
+ F |
+ 9 |
+ 5 |
+
+
+ | 110 |
+ R2221H2 |
+ LXS64 |
+ 71 |
+ M |
+ 28 |
+ 2 |
+ 1562224054 |
+ B |
+ 21 |
+ 10 |
+
+
+ | 111 |
+ R1989H2 |
+ LXS66 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224036 |
+ B |
+ 17 |
+ 9 |
+
+
+ | 112 |
+ R1843H2 |
+ LXS66 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1523516009 |
+ E |
+ 12 |
+ 6 |
+
+
+ | 113 |
+ R2820H2 |
+ LXS68 |
+ 67 |
+ F |
+ 29 |
+ 2 |
+ 1523516003 |
+ E |
+ 1 |
+ 1 |
+
+
+ | 114 |
+ R2819H2 |
+ LXS68 |
+ 67 |
+ M |
+ 29 |
+ 2 |
+ 1562224034 |
+ E |
+ 23 |
+ 11 |
+
+
+ | 115 |
+ R1963H2 |
+ LXS7 |
+ 78 |
+ F |
+ 28 |
+ 2 |
+ 1562224032 |
+ B |
+ 15 |
+ 8 |
+
+
+ | 116 |
+ R1964H2 |
+ LXS7 |
+ 78 |
+ M |
+ 28 |
+ 2 |
+ 1562224032 |
+ C |
+ 15 |
+ 8 |
+
+
+ | 117 |
+ R2166H2 |
+ LXS70 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516033 |
+ F |
+ 8 |
+ 4 |
+
+
+ | 118 |
+ R2745H2 |
+ LXS70 |
+ 71 |
+ M |
+ 28 |
+ 2 |
+ 1562224054 |
+ F |
+ 21 |
+ 10 |
+
+
+ | 119 |
+ R2848H2 |
+ LXS72 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1562224038 |
+ A |
+ 25 |
+ 11 |
+
+
+ | 120 |
+ R1902H2 |
+ LXS72 |
+ 66 |
+ M |
+ 27 |
+ 2 |
+ 1523516024 |
+ A |
+ 13 |
+ 7 |
+
+
+ | 121 |
+ R2750H2 |
+ LXS73 |
+ 81 |
+ F |
+ 25 |
+ 2 |
+ 1523516030 |
+ D |
+ 4 |
+ 2 |
+
+
+ | 122 |
+ R1835H2 |
+ LXS73 |
+ 90 |
+ M |
+ 24 |
+ 2 |
+ 1523516009 |
+ D |
+ 12 |
+ 6 |
+
+
+ | 123 |
+ R1979H2 |
+ LXS75 |
+ 59 |
+ F |
+ 27 |
+ 2 |
+ 1562224047 |
+ D |
+ 16 |
+ 8 |
+
+
+ | 124 |
+ R2826H2 |
+ LXS75 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ F |
+ 1 |
+ 1 |
+
+
+ | 125 |
+ R2142H2 |
+ LXS76 |
+ 77 |
+ F |
+ 26 |
+ 2 |
+ 1562224050 |
+ E |
+ 19 |
+ 9 |
+
+
+ | 126 |
+ R1884H2 |
+ LXS76 |
+ 85 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ A |
+ 26 |
+ 12 |
+
+
+ | 127 |
+ R1959H2 |
+ LXS78 |
+ 69 |
+ F |
+ 26 |
+ 2 |
+ 1523516029 |
+ E |
+ 14 |
+ 7 |
+
+
+ | 128 |
+ R1958H2 |
+ LXS78 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516029 |
+ D |
+ 14 |
+ 7 |
+
+
+ | 129 |
+ R2845H1 |
+ LXS8 |
+ 70 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ C |
+ 6 |
+ 3 |
+
+
+ | 130 |
+ R2156H2 |
+ LXS8 |
+ 76 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ B |
+ 20 |
+ 10 |
+
+
+ | 131 |
+ R1955H2 |
+ LXS80 |
+ 71 |
+ F |
+ 25 |
+ 2 |
+ 1523516029 |
+ A |
+ 14 |
+ 7 |
+
+
+ | 132 |
+ R1956H2 |
+ LXS80 |
+ 71 |
+ M |
+ 25 |
+ 2 |
+ 1523516029 |
+ B |
+ 14 |
+ 7 |
+
+
+ | 133 |
+ R2830H1 |
+ LXS84 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ D |
+ 2 |
+ 1 |
+
+
+ | 134 |
+ R2829H2 |
+ LXS84 |
+ 66 |
+ M |
+ 26 |
+ 2 |
+ 1562224037 |
+ A |
+ 24 |
+ 11 |
+
+
+ | 135 |
+ R2839H2 |
+ LXS86 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ C |
+ 24 |
+ 11 |
+
+
+ | 136 |
+ R2838H1 |
+ LXS86 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516006 |
+ B |
+ 6 |
+ 3 |
+
+
+ | 137 |
+ R2882H1 |
+ LXS87 |
+ 66 |
+ F |
+ 27 |
+ 2 |
+ 1523516006 |
+ F |
+ 6 |
+ 3 |
+
+
+ | 138 |
+ R2744H2 |
+ LXS87 |
+ 71 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ E |
+ 21 |
+ 10 |
+
+
+ | 139 |
+ R2831H2 |
+ LXS88 |
+ 69 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ B |
+ 24 |
+ 11 |
+
+
+ | 140 |
+ R2762H2 |
+ LXS88 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1523516005 |
+ A |
+ 5 |
+ 3 |
+
+
+ | 141 |
+ R2828H1 |
+ LXS89 |
+ 75 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ C |
+ 2 |
+ 1 |
+
+
+ | 142 |
+ R1962H2 |
+ LXS89 |
+ 73 |
+ M |
+ 25 |
+ 2 |
+ 1562224032 |
+ A |
+ 15 |
+ 8 |
+
+
+ | 143 |
+ R1746H2 |
+ LXS9 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ F |
+ 10 |
+ 5 |
+
+
+ | 144 |
+ R2801H2 |
+ LXS9 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ D |
+ 1 |
+ 1 |
+
+
+ | 145 |
+ R1812H2 |
+ LXS90 |
+ 61 |
+ F |
+ 25 |
+ 2 |
+ 1562224038 |
+ F |
+ 25 |
+ 11 |
+
+
+ | 146 |
+ R1813H2 |
+ LXS90 |
+ 61 |
+ M |
+ 25 |
+ 2 |
+ 1523516009 |
+ A |
+ 12 |
+ 6 |
+
+
+ | 147 |
+ R1736H2 |
+ LXS92 |
+ 66 |
+ F |
+ 23 |
+ 2 |
+ 1523516015 |
+ E |
+ 10 |
+ 5 |
+
+
+ | 148 |
+ R1609H2 |
+ LXS92 |
+ 87 |
+ M |
+ 23 |
+ 2 |
+ 1523516032 |
+ A |
+ 7 |
+ 4 |
+
+
+ | 149 |
+ R1624H2 |
+ LXS93 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516032 |
+ B |
+ 7 |
+ 4 |
+
+
+ | 150 |
+ R1815H2 |
+ LXS93 |
+ 61 |
+ M |
+ 26 |
+ 2 |
+ 1523516009 |
+ B |
+ 12 |
+ 6 |
+
+
+ | 151 |
+ R1991H2 |
+ LXS94 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224036 |
+ C |
+ 17 |
+ 9 |
+
+
+ | 152 |
+ R2002H2 |
+ LXS94 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1562224049 |
+ B |
+ 18 |
+ 9 |
+
+
+ | 153 |
+ R1996H2 |
+ LXS96 |
+ 75 |
+ F |
+ 23 |
+ 2 |
+ 1562224036 |
+ F |
+ 17 |
+ 9 |
+
+
+ | 154 |
+ R1772H2 |
+ LXS96 |
+ 63 |
+ M |
+ 23 |
+ 2 |
+ 1523516007 |
+ C |
+ 11 |
+ 6 |
+
+
+ | 155 |
+ R2759H2 |
+ LXS97 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224060 |
+ B |
+ 22 |
+ 10 |
+
+
+ | 156 |
+ R2739H2 |
+ LXS97 |
+ 79 |
+ M |
+ 26 |
+ 2 |
+ 1523516028 |
+ F |
+ 3 |
+ 2 |
+
+
+ | 157 |
+ R2149H2 |
+ LXS98 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516033 |
+ C |
+ 8 |
+ 4 |
+
+
+ | 158 |
+ R1888H2 |
+ LXS98 |
+ 76 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ B |
+ 26 |
+ 12 |
+
+
+ | 159 |
+ R1644H2 |
+ LXS99 |
+ 79 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ B |
+ 10 |
+ 5 |
+
+
+ | 160 |
+ R2145H2 |
+ LXS99 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ F |
+ 19 |
+ 9 |
+
+
+
+ |
+
+
+
+
+
+ |
+
+
+ |
+ Downloading all data:
+
+ All data links (right-most column above) will be available as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
+ |
+
+
+
diff --git a/general/datasets/Illum_lxs_hipp_loess0807/citation.rtf b/general/datasets/Illum_lxs_hipp_loess0807/citation.rtf
new file mode 100644
index 0000000..29fd952
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess0807/citation.rtf
@@ -0,0 +1,3 @@
+Downloading all data:
+
+All data links (right-most column above) will be available as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
diff --git a/general/datasets/Illum_lxs_hipp_loess0807/contributors.rtf b/general/datasets/Illum_lxs_hipp_loess0807/contributors.rtf
new file mode 100644
index 0000000..775c0ee
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess0807/contributors.rtf
@@ -0,0 +1,5 @@
+About this text file:
+
+INFO file prepared by Xusheng Wang, Oct 24, 2007.
+
+Data set uploaded by Arthur Centeno, Aug 30, 2007.
diff --git a/general/datasets/Illum_lxs_hipp_loess0807/experiment-design.rtf b/general/datasets/Illum_lxs_hipp_loess0807/experiment-design.rtf
new file mode 100644
index 0000000..f477cb7
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess0807/experiment-design.rtf
@@ -0,0 +1 @@
+Experimental Design and Batch Structure: This data set consists arrays processed in 13 groups over a five month period (July 2006 to Dec 2006). Most groups consisted of 12 samples. All arrays in this data set were processed using a single protocol by a single operator, Feng Yiao. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between July 28 and Dec 21, 2006. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Illum_lxs_hipp_loess0807/notes.rtf b/general/datasets/Illum_lxs_hipp_loess0807/notes.rtf
new file mode 100644
index 0000000..938409b
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess0807/notes.rtf
@@ -0,0 +1,3 @@
+ANNOTATION: In spring of 2007, Robert W. Williams and Hongqiang Li reannotated the Illumina Mouse-6 array content. This new annotation is now incorporated into GeneNetwork. For 46166 probes on the Mouse 6 array platform (including control probes) we have identified 35975 NCBI Entrez Gene IDs; 26481 matched human Gene IDs; 23899 matched rat Gene IDs; 26883 NCBI HomoloGene IDs; and 12791 OMIM IDs.
+
+Position data for the 50-mer Illumina Mouse-6 array were initially downloaded from Sanger at http://www.sanger.ac.uk/Users/avc/Illumina/Mouse-6_V1.gff.gz but we then updated all positions by BLAT analysis from mm6 positions to mm8 positions (Hongqiang Li).
diff --git a/general/datasets/Illum_lxs_hipp_loess0807/platform.rtf b/general/datasets/Illum_lxs_hipp_loess0807/platform.rtf
new file mode 100644
index 0000000..2ac899d
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess0807/platform.rtf
@@ -0,0 +1,5 @@
+About the array platform:
+
+Illumina Sentrix Mouse-6 BeadArray Platform: The Mouse6 array consists of 46,116 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+Dunning M, Smith M, Thorne N, Tavare S (2006) beadarray: An R package to analyse Illumina BeadArrays. R News (the Newsletter of the P Project) 6:17-23. (see pages 17-23 of http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf).
diff --git a/general/datasets/Illum_lxs_hipp_loess0807/processing.rtf b/general/datasets/Illum_lxs_hipp_loess0807/processing.rtf
new file mode 100644
index 0000000..c3d0555
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess0807/processing.rtf
@@ -0,0 +1,3 @@
+About data processing:
+
+This data set uses the LOESS with Variance Stabilizing Transform (VST) and Background correction from the lumi package downloaded from Bioconductor (http://www.bioconductor.org/). For the more detailed information, please see the lumi package documentation.
diff --git a/general/datasets/Illum_lxs_hipp_loess0807/summary.rtf b/general/datasets/Illum_lxs_hipp_loess0807/summary.rtf
new file mode 100644
index 0000000..ebfc03f
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess0807/summary.rtf
@@ -0,0 +1,33 @@
+August 07 ILLUMINA Mouse-6 DATA SET RSN: The LXS Hippocampus Illumina Robust Spline Normalization with No Background correction data set provides estimates of mRNA expression in the hippocampus of 75 LXS recombinant inbred strains, the two parental strains, ILS/Ibg and ISS/Ibg (Inbred Long Sleep and Inbred Short Sleep strains from the Institute of Behavioral Genetics), and the two reciprocal F1 strains (ILSXISSF1, ISSXILSF1). All samples are from normal adult control animals raised in a standard laboratory environment. Subsequent data sets will provide estimates of mRNA expression following restraint stress, ethanol treatment, and stress followed by ethanol using many of the same strains (Lu Lu and colleagues).
+
+A total of 240 pooled hippocampal samples were processed using 40 Illumina Sentrix Mouse-6 v 1.0 oligomer microarray BeadArray slides. Twenty-seven Mouse-6 slides and a total of 160 samples passed stringent quality control and error checking. We should note that this is our first experience using the Illumina platform and the initial set of 13 slides were not included. This particular data set was processed using the Illumina "Robust Spline Normalization with No Background Correction" protocol. Values were log2 transformed and the current data range from 6.481 average (very low or no expression) to 24.852 (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Hippocampus Illumina (Aug 07) RSN data set, ### probes have LRS values >46.
+
+In comparison, here are the yields of QTLs with LOD>10 for other closely related data sets:
+
+
+ - 1050 for Hippocampus Illumina (Aug07) LOESS
+ - 1162 for Hippocampus Illumina (Aug07) LOESS_NB
+ - 1129 for Hippocampus Illumina (Aug07) QUANT
+ - 1176 for Hippocampus Illumina (Aug07) QUANT_NB
+ - NO DATA for Hippocampus Illumina (Aug07) RSN
+ - NO DATA for Hippocampus Illumina (Aug07) RSN_NB (THIS DATA SET)
+ - 1183 for Hippocampus Illumina (May 07) RankInv
+ - 1167 for Hippocampus Illumina (Oct06) Rank
+ - 1170 for Hippocampus Illumina (Oct06) RankInv
+
+
+The LRS achieved in the different version of the LXS Hippocampus data for probe ILM103520706 (Disabled 1; Dab1) are as follow
+
+
+ - 338.4 for Hippocampus Illumina (Aug07) LOESS
+ - 339.8 for Hippocampus Illumina (Aug07) LOESS_NB
+ - 370.2 for Hippocampus Illumina (Aug07) QUANT
+ - 363.5 for Hippocampus Illumina (Aug07) QUANT_NB
+ - 374.8 for Hippocampus Illumina (Aug07) RSN
+ - 363.0 for Hippocampus Illumina (Aug07) RSN_NB (THIS DATA SET)
+ - 360.3 for Hippocampus Illumina (May 07) RankInv
+ - 358.1 for Hippocampus Illumina (Oct06) Rank
+ - 358.8 for Hippocampus Illumina (Oct06) RankInv
+
diff --git a/general/datasets/Illum_lxs_hipp_loess0807/tissue.rtf b/general/datasets/Illum_lxs_hipp_loess0807/tissue.rtf
new file mode 100644
index 0000000..febccce
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess0807/tissue.rtf
@@ -0,0 +1,9 @@
+About the animals and tissue used to generate this set of data:
+
+All animals were raised at the IBG by Bennett and colleagues in an SPF facility. No cases were MHV positive. Mice were killed by cervical dislocation. Whole brain dissections were performed at the IBG by Bennett and colleagues and shipped in RNAlater to Lu Lu and colleagues at UTHSC. Most hippocampal dissections (all were bilateral) were performed by Zhiping Jia. Cerebella, olfactory bulbs, and brain stems were also dissected and stored at -80 deg C using further use. Hippocampal samples are very close to complete (see Lu et al., 2001 but probably include variable amounts of fimbria and choroid plexus (see expression of transthyretin, Ttr, as a marker of choroid plexus).
+
+A pool of dissected tissue from four hippocampi taken from two naive adults of the same strain, sex, and age was collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at UTHSC by Zhiping Jia.
+
+All animals used in this study were between 53 and 90 days of age (average of 72 days; see Table 1 below).
+
+
diff --git a/general/datasets/Illum_lxs_hipp_loess_nb0807/acknowledgment.rtf b/general/datasets/Illum_lxs_hipp_loess_nb0807/acknowledgment.rtf
new file mode 100644
index 0000000..d8f3e9a
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess_nb0807/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Data source acknowledgment:
+
+Data were generated with funds to Lu Lu, Beth Bennett, Mike Miles, Melloni Cook from INIA. · Lu Lu, M.D. Grant Support: NIH U01AA13499, U24AA13513 (Lu Lu, PI)
diff --git a/general/datasets/Illum_lxs_hipp_loess_nb0807/cases.rtf b/general/datasets/Illum_lxs_hipp_loess_nb0807/cases.rtf
new file mode 100644
index 0000000..efa4371
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess_nb0807/cases.rtf
@@ -0,0 +1,2140 @@
+Quality Control on Sex Labels: Sex of the samples was validated using sex-specific probe set.
+
+
+
+
+ |
+ Legend: We evaluated whether or not the sex of samples were labeled correctly by measuring the expression of Xist using probe ILM106520068. In this bar chart the expression of Xist is very low in LXS114 and has a low error term. This is because both arrays are male samples rather than 1 male and 1 female sample.
+
+
+
+ Data Table 1:
+
+
+ This table lists all arrays by order of strain (index) and includes data on tube ID, strain, age, sex, F generation number, number of animals in each sample pool (pool size), slide ID, slide position (A through F), scan date, and scan batch.
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ gener-
+ ation |
+ pool
+ size |
+ slide
+ ID |
+ slide
+ position |
+ batch
+ by slide |
+ scan
+ batch |
+
+
+ | 1 |
+ R2851H2 |
+ ILS |
+ 77 |
+ F |
+ >100 |
+ 4 |
+ 1523516003 |
+ B |
+ 1 |
+ 1 |
+
+
+ | 2 |
+ R0595H2 |
+ ILS |
+ 71 |
+ F |
+ >100 |
+ 2 |
+ 1523516030 |
+ B |
+ 4 |
+ 2 |
+
+
+ | 3 |
+ R2874H2 |
+ ILS |
+ 78 |
+ M |
+ >100 |
+ 4 |
+ 1523516011 |
+ B |
+ 2 |
+ 1 |
+
+
+ | 4 |
+ R0585H2 |
+ ILS |
+ 65 |
+ M |
+ >100 |
+ 2 |
+ 1523516028 |
+ A |
+ 3 |
+ 2 |
+
+
+ | 5 |
+ R3281H1 |
+ ILSXISSF1 |
+ 90 |
+ F |
+ NA |
+ 3 |
+ 1562224029 |
+ A |
+ 28 |
+ 13 |
+
+
+ | 6 |
+ R2857H2 |
+ ISS |
+ 75 |
+ F |
+ >100 |
+ 4 |
+ 1523516011 |
+ A |
+ 2 |
+ 1 |
+
+
+ | 7 |
+ R0589H2 |
+ ISS |
+ 73 |
+ F |
+ >100 |
+ 2 |
+ 1523516028 |
+ B |
+ 3 |
+ 2 |
+
+
+ | 8 |
+ R2955H2 |
+ ISS |
+ 53 |
+ M |
+ >100 |
+ 3 |
+ 1523516003 |
+ A |
+ 1 |
+ 1 |
+
+
+ | 9 |
+ R0578H2 |
+ ISS |
+ 67 |
+ M |
+ >100 |
+ 2 |
+ 1523516030 |
+ A |
+ 4 |
+ 2 |
+
+
+ | 10 |
+ R3282H1 |
+ ISSXILSF1 |
+ 97 |
+ M |
+ NA |
+ 3 |
+ 1562224029 |
+ B |
+ 28 |
+ 13 |
+
+
+ | 11 |
+ R2013H2 |
+ LXS10 |
+ 84 |
+ F |
+ 27 |
+ 2 |
+ 1562224049 |
+ E |
+ 18 |
+ 9 |
+
+
+ | 12 |
+ R1993H2 |
+ LXS10 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1562224036 |
+ E |
+ 17 |
+ 9 |
+
+
+ | 13 |
+ R1997H2 |
+ LXS100 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ A |
+ 18 |
+ 9 |
+
+
+ | 14 |
+ R1983H2 |
+ LXS100 |
+ 77 |
+ M |
+ 25 |
+ 2 |
+ 1562224047 |
+ F |
+ 16 |
+ 8 |
+
+
+ | 15 |
+ R2083H2 |
+ LXS101 |
+ 85 |
+ F |
+ 28 |
+ 2 |
+ 1562224050 |
+ B |
+ 19 |
+ 9 |
+
+
+ | 16 |
+ R2084H2 |
+ LXS101 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224050 |
+ C |
+ 19 |
+ 9 |
+
+
+ | 17 |
+ R2186H2 |
+ LXS102 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1523516001 |
+ C |
+ 9 |
+ 5 |
+
+
+ | 18 |
+ R2187H2 |
+ LXS102 |
+ 73 |
+ M |
+ 29 |
+ 2 |
+ 1562224053 |
+ C |
+ 20 |
+ 10 |
+
+
+ | 19 |
+ R2809H2 |
+ LXS103 |
+ 72 |
+ F |
+ 26 |
+ 2 |
+ 1562224034 |
+ C |
+ 23 |
+ 11 |
+
+
+ | 20 |
+ R2854H1 |
+ LXS103 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516006 |
+ D |
+ 6 |
+ 3 |
+
+
+ | 21 |
+ R2735H2 |
+ LXS107 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516028 |
+ D |
+ 3 |
+ 2 |
+
+
+ | 22 |
+ R2738H2 |
+ LXS107 |
+ 78 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ C |
+ 21 |
+ 10 |
+
+
+ | 23 |
+ R2840H2 |
+ LXS110 |
+ 67 |
+ F |
+ 25 |
+ 2 |
+ 1562224037 |
+ D |
+ 24 |
+ 11 |
+
+
+ | 24 |
+ R2157H2 |
+ LXS110 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516033 |
+ E |
+ 8 |
+ 4 |
+
+
+ | 25 |
+ R2172H2 |
+ LXS112 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ B |
+ 9 |
+ 5 |
+
+
+ | 26 |
+ R2841H2 |
+ LXS112 |
+ 84 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ D |
+ 27 |
+ 12 |
+
+
+ | 27 |
+ R2188H2 |
+ LXS114 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224053 |
+ D |
+ 20 |
+ 10 |
+
+
+ | 28 |
+ R2204H2 |
+ LXS114 |
+ 72 |
+ M |
+ 28 |
+ 2 |
+ 1523516001 |
+ D |
+ 9 |
+ 5 |
+
+
+ | 29 |
+ R2168H2 |
+ LXS115 |
+ 80 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ A |
+ 9 |
+ 5 |
+
+
+ | 30 |
+ R2085H2 |
+ LXS115 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ D |
+ 19 |
+ 9 |
+
+
+ | 31 |
+ R2811H2 |
+ LXS117 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224034 |
+ D |
+ 23 |
+ 11 |
+
+
+ | 32 |
+ R2212H2 |
+ LXS117 |
+ 74 |
+ M |
+ 27 |
+ 2 |
+ 1523516001 |
+ E |
+ 9 |
+ 5 |
+
+
+ | 33 |
+ R1992H2 |
+ LXS122 |
+ 86 |
+ F |
+ 26 |
+ 2 |
+ 1562224036 |
+ D |
+ 17 |
+ 9 |
+
+
+ | 34 |
+ R2219H2 |
+ LXS122 |
+ 72 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ A |
+ 21 |
+ 10 |
+
+
+ | 35 |
+ R2876H2 |
+ LXS123 |
+ 87 |
+ F |
+ 28 |
+ 2 |
+ 1562224038 |
+ C |
+ 25 |
+ 11 |
+
+
+ | 36 |
+ R2832H1 |
+ LXS123 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1523516011 |
+ E |
+ 2 |
+ 1 |
+
+
+ | 37 |
+ R2872H1 |
+ LXS124 |
+ 83 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ E |
+ 6 |
+ 3 |
+
+
+ | 38 |
+ R2871H2 |
+ LXS124 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224042 |
+ F |
+ 27 |
+ 12 |
+
+
+ | 39 |
+ R1909H2 |
+ LXS13 |
+ 79 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ D |
+ 13 |
+ 7 |
+
+
+ | 40 |
+ R1901H2 |
+ LXS13 |
+ 81 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ D |
+ 26 |
+ 12 |
+
+
+ | 41 |
+ R2023H2 |
+ LXS14 |
+ 86 |
+ F |
+ 25 |
+ 2 |
+ 1562224050 |
+ A |
+ 19 |
+ 9 |
+
+
+ | 42 |
+ R1612H2 |
+ LXS14 |
+ 85 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ A |
+ 10 |
+ 5 |
+
+
+ | 43 |
+ R1936H2 |
+ LXS16 |
+ 81 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ E |
+ 13 |
+ 7 |
+
+
+ | 44 |
+ R1912H2 |
+ LXS16 |
+ 81 |
+ M |
+ 25 |
+ 2 |
+ 1523516033 |
+ B |
+ 8 |
+ 4 |
+
+
+ | 45 |
+ R1961H2 |
+ LXS19 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516029 |
+ F |
+ 14 |
+ 7 |
+
+
+ | 46 |
+ R1904H2 |
+ LXS19 |
+ 66 |
+ M |
+ 26 |
+ 2 |
+ 1523516024 |
+ B |
+ 13 |
+ 7 |
+
+
+ | 47 |
+ R1883H2 |
+ LXS2 |
+ 71 |
+ F |
+ 27 |
+ 2 |
+ 1523516009 |
+ F |
+ 12 |
+ 6 |
+
+
+ | 48 |
+ R2753H2 |
+ LXS2 |
+ 74 |
+ M |
+ 28 |
+ 2 |
+ 1523516030 |
+ E |
+ 4 |
+ 2 |
+
+
+ | 49 |
+ R1729H2 |
+ LXS22 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516032 |
+ E |
+ 7 |
+ 4 |
+
+
+ | 50 |
+ R2743H2 |
+ LXS22 |
+ 79 |
+ M |
+ 27 |
+ 2 |
+ 1562224054 |
+ D |
+ 21 |
+ 10 |
+
+
+ | 51 |
+ R1966H2 |
+ LXS23 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224032 |
+ D |
+ 15 |
+ 8 |
+
+
+ | 52 |
+ R1971H2 |
+ LXS23 |
+ 73 |
+ M |
+ 26 |
+ 2 |
+ 1562224047 |
+ A |
+ 16 |
+ 8 |
+
+
+ | 53 |
+ R2795H2 |
+ LXS24 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516003 |
+ C |
+ 1 |
+ 1 |
+
+
+ | 54 |
+ R1755H2 |
+ LXS24 |
+ 56 |
+ M |
+ 25 |
+ 2 |
+ 1523516007 |
+ A |
+ 11 |
+ 6 |
+
+
+ | 55 |
+ R1986H2 |
+ LXS25 |
+ 75 |
+ F |
+ 27 |
+ 2 |
+ 1562224036 |
+ A |
+ 17 |
+ 9 |
+
+
+ | 56 |
+ R2006H2 |
+ LXS25 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1562224049 |
+ C |
+ 18 |
+ 9 |
+
+
+ | 57 |
+ R2014H2 |
+ LXS26 |
+ 82 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ F |
+ 18 |
+ 9 |
+
+
+ | 58 |
+ R2009H2 |
+ LXS26 |
+ 82 |
+ M |
+ 26 |
+ 2 |
+ 1562224049 |
+ D |
+ 18 |
+ 9 |
+
+
+ | 59 |
+ R2824H1 |
+ LXS28 |
+ 67 |
+ F |
+ 28 |
+ 2 |
+ 1562224042 |
+ A |
+ 27 |
+ 12 |
+
+
+ | 60 |
+ R1753H1 |
+ LXS28 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1562224041 |
+ F |
+ 26 |
+ 12 |
+
+
+ | 61 |
+ R2765H2 |
+ LXS3 |
+ 63 |
+ F |
+ 27 |
+ 2 |
+ 1523516005 |
+ B |
+ 5 |
+ 3 |
+
+
+ | 62 |
+ R1898H2 |
+ LXS3 |
+ 81 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ C |
+ 26 |
+ 12 |
+
+
+ | 63 |
+ R2764H2 |
+ LXS31 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1562224060 |
+ C |
+ 22 |
+ 10 |
+
+
+ | 64 |
+ R1908H2 |
+ LXS31 |
+ 80 |
+ M |
+ 28 |
+ 2 |
+ 1523516024 |
+ C |
+ 13 |
+ 7 |
+
+
+ | 65 |
+ R2758H2 |
+ LXS32 |
+ 70 |
+ F |
+ 26 |
+ 2 |
+ 1523516030 |
+ F |
+ 4 |
+ 2 |
+
+
+ | 66 |
+ R1743H1 |
+ LXS32 |
+ 67 |
+ M |
+ 25 |
+ 2 |
+ 1562224041 |
+ E |
+ 26 |
+ 12 |
+
+
+ | 67 |
+ R2794H2 |
+ LXS34 |
+ 75 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ B |
+ 23 |
+ 11 |
+
+
+ | 68 |
+ R2870H2 |
+ LXS34 |
+ 78 |
+ F |
+ 27 |
+ 2 |
+ 1562224029 |
+ C |
+ 28 |
+ 13 |
+
+
+ | 69 |
+ R2746H2 |
+ LXS35 |
+ 80 |
+ F |
+ 22 |
+ 2 |
+ 1523516030 |
+ C |
+ 4 |
+ 2 |
+
+
+ | 70 |
+ R2747H2 |
+ LXS35 |
+ 81 |
+ M |
+ 22 |
+ 2 |
+ 1562224060 |
+ A |
+ 22 |
+ 10 |
+
+
+ | 71 |
+ R1968H2 |
+ LXS36 |
+ 76 |
+ F |
+ 25 |
+ 2 |
+ 1562224032 |
+ E |
+ 15 |
+ 8 |
+
+
+ | 72 |
+ R1640H2 |
+ LXS36 |
+ 76 |
+ M |
+ 25 |
+ 2 |
+ 1523516032 |
+ C |
+ 7 |
+ 4 |
+
+
+ | 73 |
+ R2835H1 |
+ LXS38 |
+ 67 |
+ F |
+ 27 |
+ 2 |
+ 1523516011 |
+ F |
+ 2 |
+ 1 |
+
+
+ | 74 |
+ R2842H2 |
+ LXS38 |
+ 67 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ E |
+ 27 |
+ 12 |
+
+
+ | 75 |
+ R2210H2 |
+ LXS39 |
+ 81 |
+ F |
+ 28 |
+ 2 |
+ 1562224053 |
+ E |
+ 20 |
+ 10 |
+
+
+ | 76 |
+ R2736H2 |
+ LXS39 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516028 |
+ E |
+ 3 |
+ 2 |
+
+
+ | 77 |
+ R1978H2 |
+ LXS41 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1562224047 |
+ C |
+ 16 |
+ 8 |
+
+
+ | 78 |
+ R1783H2 |
+ LXS41 |
+ 56 |
+ M |
+ 26 |
+ 2 |
+ 1523516007 |
+ D |
+ 11 |
+ 6 |
+
+
+ | 79 |
+ R2822H2 |
+ LXS42 |
+ 66 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ F |
+ 23 |
+ 11 |
+
+
+ | 80 |
+ R2769H2 |
+ LXS42 |
+ 70 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ B |
+ 27 |
+ 12 |
+
+
+ | 81 |
+ R1974H2 |
+ LXS43 |
+ 84 |
+ F |
+ 26 |
+ 2 |
+ 1562224047 |
+ B |
+ 16 |
+ 8 |
+
+
+ | 82 |
+ R1733H2 |
+ LXS43 |
+ 72 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ C |
+ 10 |
+ 5 |
+
+
+ | 83 |
+ R1756H2 |
+ LXS46 |
+ 56 |
+ F |
+ 25 |
+ 2 |
+ 1523516007 |
+ B |
+ 11 |
+ 6 |
+
+
+ | 84 |
+ R1727H2 |
+ LXS46 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1523516032 |
+ D |
+ 7 |
+ 4 |
+
+
+ | 85 |
+ R1970H2 |
+ LXS48 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1562224032 |
+ F |
+ 15 |
+ 8 |
+
+
+ | 86 |
+ R1981H2 |
+ LXS48 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ C |
+ 27 |
+ 12 |
+
+
+ | 87 |
+ R1957H2 |
+ LXS49 |
+ 72 |
+ F |
+ 25 |
+ 2 |
+ 1523516029 |
+ C |
+ 14 |
+ 7 |
+
+
+ | 88 |
+ R2259H2 |
+ LXS49 |
+ 72 |
+ M |
+ 25 |
+ 2 |
+ 1523516028 |
+ C |
+ 3 |
+ 2 |
+
+
+ | 89 |
+ R2836H1 |
+ LXS5 |
+ 68 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ A |
+ 6 |
+ 3 |
+
+
+ | 90 |
+ R2213H2 |
+ LXS5 |
+ 80 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ F |
+ 20 |
+ 10 |
+
+
+ | 91 |
+ R2791H2 |
+ LXS50 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ A |
+ 23 |
+ 11 |
+
+
+ | 92 |
+ R1789H2 |
+ LXS50 |
+ 57 |
+ M |
+ 26 |
+ 2 |
+ 1523516033 |
+ A |
+ 8 |
+ 4 |
+
+
+ | 93 |
+ R1740H2 |
+ LXS51 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1523516032 |
+ F |
+ 7 |
+ 4 |
+
+
+ | 94 |
+ R1734H2 |
+ LXS51 |
+ 68 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ D |
+ 10 |
+ 5 |
+
+
+ | 95 |
+ R2786H2 |
+ LXS52 |
+ 61 |
+ F |
+ 27 |
+ 2 |
+ 1562224060 |
+ D |
+ 22 |
+ 10 |
+
+
+ | 96 |
+ R2768H2 |
+ LXS52 |
+ 61 |
+ M |
+ 27 |
+ 2 |
+ 1523516005 |
+ C |
+ 5 |
+ 3 |
+
+
+ | 97 |
+ R2154H2 |
+ LXS54 |
+ 70 |
+ F |
+ 27 |
+ 2 |
+ 1523516033 |
+ D |
+ 8 |
+ 4 |
+
+
+ | 98 |
+ R2155H2 |
+ LXS54 |
+ 70 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ A |
+ 20 |
+ 10 |
+
+
+ | 99 |
+ R1821H2 |
+ LXS55 |
+ 77 |
+ F |
+ 25 |
+ 2 |
+ 1523516009 |
+ C |
+ 12 |
+ 6 |
+
+
+ | 100 |
+ R1951H2 |
+ LXS55 |
+ 74 |
+ M |
+ 26 |
+ 2 |
+ 1523516024 |
+ F |
+ 13 |
+ 7 |
+
+
+ | 101 |
+ R2789H2 |
+ LXS56 |
+ 71 |
+ F |
+ 25 |
+ 2 |
+ 1523516005 |
+ F |
+ 5 |
+ 3 |
+
+
+ | 102 |
+ R2788H2 |
+ LXS56 |
+ 71 |
+ M |
+ 25 |
+ 2 |
+ 1562224060 |
+ F |
+ 22 |
+ 10 |
+
+
+ | 103 |
+ R2787H2 |
+ LXS59 |
+ 66 |
+ F |
+ 29 |
+ 2 |
+ 1562224060 |
+ E |
+ 22 |
+ 10 |
+
+
+ | 104 |
+ R2785H2 |
+ LXS59 |
+ 62 |
+ M |
+ 29 |
+ 2 |
+ 1523516005 |
+ E |
+ 5 |
+ 3 |
+
+
+ | 105 |
+ R1791H2 |
+ LXS60 |
+ 58 |
+ F |
+ 27 |
+ 2 |
+ 1562224038 |
+ D |
+ 25 |
+ 11 |
+
+
+ | 106 |
+ R1792H2 |
+ LXS60 |
+ 64 |
+ M |
+ 27 |
+ 2 |
+ 1523516007 |
+ E |
+ 11 |
+ 6 |
+
+
+ | 107 |
+ R1796H2 |
+ LXS62 |
+ 58 |
+ F |
+ 27 |
+ 2 |
+ 1523516007 |
+ F |
+ 11 |
+ 6 |
+
+
+ | 108 |
+ R1797H2 |
+ LXS62 |
+ 58 |
+ M |
+ 27 |
+ 2 |
+ 1562224038 |
+ E |
+ 25 |
+ 11 |
+
+
+ | 109 |
+ R2220H2 |
+ LXS64 |
+ 71 |
+ F |
+ 28 |
+ 2 |
+ 1523516001 |
+ F |
+ 9 |
+ 5 |
+
+
+ | 110 |
+ R2221H2 |
+ LXS64 |
+ 71 |
+ M |
+ 28 |
+ 2 |
+ 1562224054 |
+ B |
+ 21 |
+ 10 |
+
+
+ | 111 |
+ R1989H2 |
+ LXS66 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224036 |
+ B |
+ 17 |
+ 9 |
+
+
+ | 112 |
+ R1843H2 |
+ LXS66 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1523516009 |
+ E |
+ 12 |
+ 6 |
+
+
+ | 113 |
+ R2820H2 |
+ LXS68 |
+ 67 |
+ F |
+ 29 |
+ 2 |
+ 1523516003 |
+ E |
+ 1 |
+ 1 |
+
+
+ | 114 |
+ R2819H2 |
+ LXS68 |
+ 67 |
+ M |
+ 29 |
+ 2 |
+ 1562224034 |
+ E |
+ 23 |
+ 11 |
+
+
+ | 115 |
+ R1963H2 |
+ LXS7 |
+ 78 |
+ F |
+ 28 |
+ 2 |
+ 1562224032 |
+ B |
+ 15 |
+ 8 |
+
+
+ | 116 |
+ R1964H2 |
+ LXS7 |
+ 78 |
+ M |
+ 28 |
+ 2 |
+ 1562224032 |
+ C |
+ 15 |
+ 8 |
+
+
+ | 117 |
+ R2166H2 |
+ LXS70 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516033 |
+ F |
+ 8 |
+ 4 |
+
+
+ | 118 |
+ R2745H2 |
+ LXS70 |
+ 71 |
+ M |
+ 28 |
+ 2 |
+ 1562224054 |
+ F |
+ 21 |
+ 10 |
+
+
+ | 119 |
+ R2848H2 |
+ LXS72 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1562224038 |
+ A |
+ 25 |
+ 11 |
+
+
+ | 120 |
+ R1902H2 |
+ LXS72 |
+ 66 |
+ M |
+ 27 |
+ 2 |
+ 1523516024 |
+ A |
+ 13 |
+ 7 |
+
+
+ | 121 |
+ R2750H2 |
+ LXS73 |
+ 81 |
+ F |
+ 25 |
+ 2 |
+ 1523516030 |
+ D |
+ 4 |
+ 2 |
+
+
+ | 122 |
+ R1835H2 |
+ LXS73 |
+ 90 |
+ M |
+ 24 |
+ 2 |
+ 1523516009 |
+ D |
+ 12 |
+ 6 |
+
+
+ | 123 |
+ R1979H2 |
+ LXS75 |
+ 59 |
+ F |
+ 27 |
+ 2 |
+ 1562224047 |
+ D |
+ 16 |
+ 8 |
+
+
+ | 124 |
+ R2826H2 |
+ LXS75 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ F |
+ 1 |
+ 1 |
+
+
+ | 125 |
+ R2142H2 |
+ LXS76 |
+ 77 |
+ F |
+ 26 |
+ 2 |
+ 1562224050 |
+ E |
+ 19 |
+ 9 |
+
+
+ | 126 |
+ R1884H2 |
+ LXS76 |
+ 85 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ A |
+ 26 |
+ 12 |
+
+
+ | 127 |
+ R1959H2 |
+ LXS78 |
+ 69 |
+ F |
+ 26 |
+ 2 |
+ 1523516029 |
+ E |
+ 14 |
+ 7 |
+
+
+ | 128 |
+ R1958H2 |
+ LXS78 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516029 |
+ D |
+ 14 |
+ 7 |
+
+
+ | 129 |
+ R2845H1 |
+ LXS8 |
+ 70 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ C |
+ 6 |
+ 3 |
+
+
+ | 130 |
+ R2156H2 |
+ LXS8 |
+ 76 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ B |
+ 20 |
+ 10 |
+
+
+ | 131 |
+ R1955H2 |
+ LXS80 |
+ 71 |
+ F |
+ 25 |
+ 2 |
+ 1523516029 |
+ A |
+ 14 |
+ 7 |
+
+
+ | 132 |
+ R1956H2 |
+ LXS80 |
+ 71 |
+ M |
+ 25 |
+ 2 |
+ 1523516029 |
+ B |
+ 14 |
+ 7 |
+
+
+ | 133 |
+ R2830H1 |
+ LXS84 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ D |
+ 2 |
+ 1 |
+
+
+ | 134 |
+ R2829H2 |
+ LXS84 |
+ 66 |
+ M |
+ 26 |
+ 2 |
+ 1562224037 |
+ A |
+ 24 |
+ 11 |
+
+
+ | 135 |
+ R2839H2 |
+ LXS86 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ C |
+ 24 |
+ 11 |
+
+
+ | 136 |
+ R2838H1 |
+ LXS86 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516006 |
+ B |
+ 6 |
+ 3 |
+
+
+ | 137 |
+ R2882H1 |
+ LXS87 |
+ 66 |
+ F |
+ 27 |
+ 2 |
+ 1523516006 |
+ F |
+ 6 |
+ 3 |
+
+
+ | 138 |
+ R2744H2 |
+ LXS87 |
+ 71 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ E |
+ 21 |
+ 10 |
+
+
+ | 139 |
+ R2831H2 |
+ LXS88 |
+ 69 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ B |
+ 24 |
+ 11 |
+
+
+ | 140 |
+ R2762H2 |
+ LXS88 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1523516005 |
+ A |
+ 5 |
+ 3 |
+
+
+ | 141 |
+ R2828H1 |
+ LXS89 |
+ 75 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ C |
+ 2 |
+ 1 |
+
+
+ | 142 |
+ R1962H2 |
+ LXS89 |
+ 73 |
+ M |
+ 25 |
+ 2 |
+ 1562224032 |
+ A |
+ 15 |
+ 8 |
+
+
+ | 143 |
+ R1746H2 |
+ LXS9 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ F |
+ 10 |
+ 5 |
+
+
+ | 144 |
+ R2801H2 |
+ LXS9 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ D |
+ 1 |
+ 1 |
+
+
+ | 145 |
+ R1812H2 |
+ LXS90 |
+ 61 |
+ F |
+ 25 |
+ 2 |
+ 1562224038 |
+ F |
+ 25 |
+ 11 |
+
+
+ | 146 |
+ R1813H2 |
+ LXS90 |
+ 61 |
+ M |
+ 25 |
+ 2 |
+ 1523516009 |
+ A |
+ 12 |
+ 6 |
+
+
+ | 147 |
+ R1736H2 |
+ LXS92 |
+ 66 |
+ F |
+ 23 |
+ 2 |
+ 1523516015 |
+ E |
+ 10 |
+ 5 |
+
+
+ | 148 |
+ R1609H2 |
+ LXS92 |
+ 87 |
+ M |
+ 23 |
+ 2 |
+ 1523516032 |
+ A |
+ 7 |
+ 4 |
+
+
+ | 149 |
+ R1624H2 |
+ LXS93 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516032 |
+ B |
+ 7 |
+ 4 |
+
+
+ | 150 |
+ R1815H2 |
+ LXS93 |
+ 61 |
+ M |
+ 26 |
+ 2 |
+ 1523516009 |
+ B |
+ 12 |
+ 6 |
+
+
+ | 151 |
+ R1991H2 |
+ LXS94 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224036 |
+ C |
+ 17 |
+ 9 |
+
+
+ | 152 |
+ R2002H2 |
+ LXS94 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1562224049 |
+ B |
+ 18 |
+ 9 |
+
+
+ | 153 |
+ R1996H2 |
+ LXS96 |
+ 75 |
+ F |
+ 23 |
+ 2 |
+ 1562224036 |
+ F |
+ 17 |
+ 9 |
+
+
+ | 154 |
+ R1772H2 |
+ LXS96 |
+ 63 |
+ M |
+ 23 |
+ 2 |
+ 1523516007 |
+ C |
+ 11 |
+ 6 |
+
+
+ | 155 |
+ R2759H2 |
+ LXS97 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224060 |
+ B |
+ 22 |
+ 10 |
+
+
+ | 156 |
+ R2739H2 |
+ LXS97 |
+ 79 |
+ M |
+ 26 |
+ 2 |
+ 1523516028 |
+ F |
+ 3 |
+ 2 |
+
+
+ | 157 |
+ R2149H2 |
+ LXS98 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516033 |
+ C |
+ 8 |
+ 4 |
+
+
+ | 158 |
+ R1888H2 |
+ LXS98 |
+ 76 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ B |
+ 26 |
+ 12 |
+
+
+ | 159 |
+ R1644H2 |
+ LXS99 |
+ 79 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ B |
+ 10 |
+ 5 |
+
+
+ | 160 |
+ R2145H2 |
+ LXS99 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ F |
+ 19 |
+ 9 |
+
+
+
+ |
+
+
+
+
+
+ |
+
+
+ |
+ Downloading all data:
+
+ All data links (right-most column above) will be available as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
+ |
+
+
+
diff --git a/general/datasets/Illum_lxs_hipp_loess_nb0807/citation.rtf b/general/datasets/Illum_lxs_hipp_loess_nb0807/citation.rtf
new file mode 100644
index 0000000..29fd952
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess_nb0807/citation.rtf
@@ -0,0 +1,3 @@
+Downloading all data:
+
+All data links (right-most column above) will be available as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
diff --git a/general/datasets/Illum_lxs_hipp_loess_nb0807/contributors.rtf b/general/datasets/Illum_lxs_hipp_loess_nb0807/contributors.rtf
new file mode 100644
index 0000000..775c0ee
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess_nb0807/contributors.rtf
@@ -0,0 +1,5 @@
+About this text file:
+
+INFO file prepared by Xusheng Wang, Oct 24, 2007.
+
+Data set uploaded by Arthur Centeno, Aug 30, 2007.
diff --git a/general/datasets/Illum_lxs_hipp_loess_nb0807/experiment-design.rtf b/general/datasets/Illum_lxs_hipp_loess_nb0807/experiment-design.rtf
new file mode 100644
index 0000000..f477cb7
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess_nb0807/experiment-design.rtf
@@ -0,0 +1 @@
+Experimental Design and Batch Structure: This data set consists arrays processed in 13 groups over a five month period (July 2006 to Dec 2006). Most groups consisted of 12 samples. All arrays in this data set were processed using a single protocol by a single operator, Feng Yiao. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between July 28 and Dec 21, 2006. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Illum_lxs_hipp_loess_nb0807/notes.rtf b/general/datasets/Illum_lxs_hipp_loess_nb0807/notes.rtf
new file mode 100644
index 0000000..938409b
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess_nb0807/notes.rtf
@@ -0,0 +1,3 @@
+ANNOTATION: In spring of 2007, Robert W. Williams and Hongqiang Li reannotated the Illumina Mouse-6 array content. This new annotation is now incorporated into GeneNetwork. For 46166 probes on the Mouse 6 array platform (including control probes) we have identified 35975 NCBI Entrez Gene IDs; 26481 matched human Gene IDs; 23899 matched rat Gene IDs; 26883 NCBI HomoloGene IDs; and 12791 OMIM IDs.
+
+Position data for the 50-mer Illumina Mouse-6 array were initially downloaded from Sanger at http://www.sanger.ac.uk/Users/avc/Illumina/Mouse-6_V1.gff.gz but we then updated all positions by BLAT analysis from mm6 positions to mm8 positions (Hongqiang Li).
diff --git a/general/datasets/Illum_lxs_hipp_loess_nb0807/platform.rtf b/general/datasets/Illum_lxs_hipp_loess_nb0807/platform.rtf
new file mode 100644
index 0000000..2ac899d
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess_nb0807/platform.rtf
@@ -0,0 +1,5 @@
+About the array platform:
+
+Illumina Sentrix Mouse-6 BeadArray Platform: The Mouse6 array consists of 46,116 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+Dunning M, Smith M, Thorne N, Tavare S (2006) beadarray: An R package to analyse Illumina BeadArrays. R News (the Newsletter of the P Project) 6:17-23. (see pages 17-23 of http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf).
diff --git a/general/datasets/Illum_lxs_hipp_loess_nb0807/processing.rtf b/general/datasets/Illum_lxs_hipp_loess_nb0807/processing.rtf
new file mode 100644
index 0000000..c3d0555
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess_nb0807/processing.rtf
@@ -0,0 +1,3 @@
+About data processing:
+
+This data set uses the LOESS with Variance Stabilizing Transform (VST) and Background correction from the lumi package downloaded from Bioconductor (http://www.bioconductor.org/). For the more detailed information, please see the lumi package documentation.
diff --git a/general/datasets/Illum_lxs_hipp_loess_nb0807/summary.rtf b/general/datasets/Illum_lxs_hipp_loess_nb0807/summary.rtf
new file mode 100644
index 0000000..ebfc03f
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess_nb0807/summary.rtf
@@ -0,0 +1,33 @@
+August 07 ILLUMINA Mouse-6 DATA SET RSN: The LXS Hippocampus Illumina Robust Spline Normalization with No Background correction data set provides estimates of mRNA expression in the hippocampus of 75 LXS recombinant inbred strains, the two parental strains, ILS/Ibg and ISS/Ibg (Inbred Long Sleep and Inbred Short Sleep strains from the Institute of Behavioral Genetics), and the two reciprocal F1 strains (ILSXISSF1, ISSXILSF1). All samples are from normal adult control animals raised in a standard laboratory environment. Subsequent data sets will provide estimates of mRNA expression following restraint stress, ethanol treatment, and stress followed by ethanol using many of the same strains (Lu Lu and colleagues).
+
+A total of 240 pooled hippocampal samples were processed using 40 Illumina Sentrix Mouse-6 v 1.0 oligomer microarray BeadArray slides. Twenty-seven Mouse-6 slides and a total of 160 samples passed stringent quality control and error checking. We should note that this is our first experience using the Illumina platform and the initial set of 13 slides were not included. This particular data set was processed using the Illumina "Robust Spline Normalization with No Background Correction" protocol. Values were log2 transformed and the current data range from 6.481 average (very low or no expression) to 24.852 (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Hippocampus Illumina (Aug 07) RSN data set, ### probes have LRS values >46.
+
+In comparison, here are the yields of QTLs with LOD>10 for other closely related data sets:
+
+
+ - 1050 for Hippocampus Illumina (Aug07) LOESS
+ - 1162 for Hippocampus Illumina (Aug07) LOESS_NB
+ - 1129 for Hippocampus Illumina (Aug07) QUANT
+ - 1176 for Hippocampus Illumina (Aug07) QUANT_NB
+ - NO DATA for Hippocampus Illumina (Aug07) RSN
+ - NO DATA for Hippocampus Illumina (Aug07) RSN_NB (THIS DATA SET)
+ - 1183 for Hippocampus Illumina (May 07) RankInv
+ - 1167 for Hippocampus Illumina (Oct06) Rank
+ - 1170 for Hippocampus Illumina (Oct06) RankInv
+
+
+The LRS achieved in the different version of the LXS Hippocampus data for probe ILM103520706 (Disabled 1; Dab1) are as follow
+
+
+ - 338.4 for Hippocampus Illumina (Aug07) LOESS
+ - 339.8 for Hippocampus Illumina (Aug07) LOESS_NB
+ - 370.2 for Hippocampus Illumina (Aug07) QUANT
+ - 363.5 for Hippocampus Illumina (Aug07) QUANT_NB
+ - 374.8 for Hippocampus Illumina (Aug07) RSN
+ - 363.0 for Hippocampus Illumina (Aug07) RSN_NB (THIS DATA SET)
+ - 360.3 for Hippocampus Illumina (May 07) RankInv
+ - 358.1 for Hippocampus Illumina (Oct06) Rank
+ - 358.8 for Hippocampus Illumina (Oct06) RankInv
+
diff --git a/general/datasets/Illum_lxs_hipp_loess_nb0807/tissue.rtf b/general/datasets/Illum_lxs_hipp_loess_nb0807/tissue.rtf
new file mode 100644
index 0000000..febccce
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_loess_nb0807/tissue.rtf
@@ -0,0 +1,9 @@
+About the animals and tissue used to generate this set of data:
+
+All animals were raised at the IBG by Bennett and colleagues in an SPF facility. No cases were MHV positive. Mice were killed by cervical dislocation. Whole brain dissections were performed at the IBG by Bennett and colleagues and shipped in RNAlater to Lu Lu and colleagues at UTHSC. Most hippocampal dissections (all were bilateral) were performed by Zhiping Jia. Cerebella, olfactory bulbs, and brain stems were also dissected and stored at -80 deg C using further use. Hippocampal samples are very close to complete (see Lu et al., 2001 but probably include variable amounts of fimbria and choroid plexus (see expression of transthyretin, Ttr, as a marker of choroid plexus).
+
+A pool of dissected tissue from four hippocampi taken from two naive adults of the same strain, sex, and age was collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at UTHSC by Zhiping Jia.
+
+All animals used in this study were between 53 and 90 days of age (average of 72 days; see Table 1 below).
+
+
diff --git a/general/datasets/Illum_lxs_hipp_noe_1008/summary.rtf b/general/datasets/Illum_lxs_hipp_noe_1008/summary.rtf
new file mode 100644
index 0000000..f49829f
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_noe_1008/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 63, Name: Hippocampus Illumina NOS (Oct08) RankInv beta
\ No newline at end of file
diff --git a/general/datasets/Illum_lxs_hipp_non_1008/summary.rtf b/general/datasets/Illum_lxs_hipp_non_1008/summary.rtf
new file mode 100644
index 0000000..f49829f
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_non_1008/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 63, Name: Hippocampus Illumina NOS (Oct08) RankInv beta
\ No newline at end of file
diff --git a/general/datasets/Illum_lxs_hipp_nos_1008/summary.rtf b/general/datasets/Illum_lxs_hipp_nos_1008/summary.rtf
new file mode 100644
index 0000000..f49829f
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_nos_1008/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 63, Name: Hippocampus Illumina NOS (Oct08) RankInv beta
\ No newline at end of file
diff --git a/general/datasets/Illum_lxs_hipp_quant0807/acknowledgment.rtf b/general/datasets/Illum_lxs_hipp_quant0807/acknowledgment.rtf
new file mode 100644
index 0000000..d8f3e9a
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant0807/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Data source acknowledgment:
+
+Data were generated with funds to Lu Lu, Beth Bennett, Mike Miles, Melloni Cook from INIA. · Lu Lu, M.D. Grant Support: NIH U01AA13499, U24AA13513 (Lu Lu, PI)
diff --git a/general/datasets/Illum_lxs_hipp_quant0807/cases.rtf b/general/datasets/Illum_lxs_hipp_quant0807/cases.rtf
new file mode 100644
index 0000000..efa4371
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant0807/cases.rtf
@@ -0,0 +1,2140 @@
+Quality Control on Sex Labels: Sex of the samples was validated using sex-specific probe set.
+
+
+
+
+ |
+ Legend: We evaluated whether or not the sex of samples were labeled correctly by measuring the expression of Xist using probe ILM106520068. In this bar chart the expression of Xist is very low in LXS114 and has a low error term. This is because both arrays are male samples rather than 1 male and 1 female sample.
+
+
+
+ Data Table 1:
+
+
+ This table lists all arrays by order of strain (index) and includes data on tube ID, strain, age, sex, F generation number, number of animals in each sample pool (pool size), slide ID, slide position (A through F), scan date, and scan batch.
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ gener-
+ ation |
+ pool
+ size |
+ slide
+ ID |
+ slide
+ position |
+ batch
+ by slide |
+ scan
+ batch |
+
+
+ | 1 |
+ R2851H2 |
+ ILS |
+ 77 |
+ F |
+ >100 |
+ 4 |
+ 1523516003 |
+ B |
+ 1 |
+ 1 |
+
+
+ | 2 |
+ R0595H2 |
+ ILS |
+ 71 |
+ F |
+ >100 |
+ 2 |
+ 1523516030 |
+ B |
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
+ | 107 |
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+
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+
+ | 109 |
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+ 2 |
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+
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+
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+
+
+ | 112 |
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+ 2 |
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+
+
+ | 113 |
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+ 2 |
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+ 1 |
+ 1 |
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+
+ | 114 |
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+ 2 |
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+
+ | 115 |
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+ 2 |
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+
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+ 2 |
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+
+
+ | 117 |
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+ 27 |
+ 2 |
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+ 8 |
+ 4 |
+
+
+ | 118 |
+ R2745H2 |
+ LXS70 |
+ 71 |
+ M |
+ 28 |
+ 2 |
+ 1562224054 |
+ F |
+ 21 |
+ 10 |
+
+
+ | 119 |
+ R2848H2 |
+ LXS72 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1562224038 |
+ A |
+ 25 |
+ 11 |
+
+
+ | 120 |
+ R1902H2 |
+ LXS72 |
+ 66 |
+ M |
+ 27 |
+ 2 |
+ 1523516024 |
+ A |
+ 13 |
+ 7 |
+
+
+ | 121 |
+ R2750H2 |
+ LXS73 |
+ 81 |
+ F |
+ 25 |
+ 2 |
+ 1523516030 |
+ D |
+ 4 |
+ 2 |
+
+
+ | 122 |
+ R1835H2 |
+ LXS73 |
+ 90 |
+ M |
+ 24 |
+ 2 |
+ 1523516009 |
+ D |
+ 12 |
+ 6 |
+
+
+ | 123 |
+ R1979H2 |
+ LXS75 |
+ 59 |
+ F |
+ 27 |
+ 2 |
+ 1562224047 |
+ D |
+ 16 |
+ 8 |
+
+
+ | 124 |
+ R2826H2 |
+ LXS75 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ F |
+ 1 |
+ 1 |
+
+
+ | 125 |
+ R2142H2 |
+ LXS76 |
+ 77 |
+ F |
+ 26 |
+ 2 |
+ 1562224050 |
+ E |
+ 19 |
+ 9 |
+
+
+ | 126 |
+ R1884H2 |
+ LXS76 |
+ 85 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ A |
+ 26 |
+ 12 |
+
+
+ | 127 |
+ R1959H2 |
+ LXS78 |
+ 69 |
+ F |
+ 26 |
+ 2 |
+ 1523516029 |
+ E |
+ 14 |
+ 7 |
+
+
+ | 128 |
+ R1958H2 |
+ LXS78 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516029 |
+ D |
+ 14 |
+ 7 |
+
+
+ | 129 |
+ R2845H1 |
+ LXS8 |
+ 70 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ C |
+ 6 |
+ 3 |
+
+
+ | 130 |
+ R2156H2 |
+ LXS8 |
+ 76 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ B |
+ 20 |
+ 10 |
+
+
+ | 131 |
+ R1955H2 |
+ LXS80 |
+ 71 |
+ F |
+ 25 |
+ 2 |
+ 1523516029 |
+ A |
+ 14 |
+ 7 |
+
+
+ | 132 |
+ R1956H2 |
+ LXS80 |
+ 71 |
+ M |
+ 25 |
+ 2 |
+ 1523516029 |
+ B |
+ 14 |
+ 7 |
+
+
+ | 133 |
+ R2830H1 |
+ LXS84 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ D |
+ 2 |
+ 1 |
+
+
+ | 134 |
+ R2829H2 |
+ LXS84 |
+ 66 |
+ M |
+ 26 |
+ 2 |
+ 1562224037 |
+ A |
+ 24 |
+ 11 |
+
+
+ | 135 |
+ R2839H2 |
+ LXS86 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ C |
+ 24 |
+ 11 |
+
+
+ | 136 |
+ R2838H1 |
+ LXS86 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516006 |
+ B |
+ 6 |
+ 3 |
+
+
+ | 137 |
+ R2882H1 |
+ LXS87 |
+ 66 |
+ F |
+ 27 |
+ 2 |
+ 1523516006 |
+ F |
+ 6 |
+ 3 |
+
+
+ | 138 |
+ R2744H2 |
+ LXS87 |
+ 71 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ E |
+ 21 |
+ 10 |
+
+
+ | 139 |
+ R2831H2 |
+ LXS88 |
+ 69 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ B |
+ 24 |
+ 11 |
+
+
+ | 140 |
+ R2762H2 |
+ LXS88 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1523516005 |
+ A |
+ 5 |
+ 3 |
+
+
+ | 141 |
+ R2828H1 |
+ LXS89 |
+ 75 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ C |
+ 2 |
+ 1 |
+
+
+ | 142 |
+ R1962H2 |
+ LXS89 |
+ 73 |
+ M |
+ 25 |
+ 2 |
+ 1562224032 |
+ A |
+ 15 |
+ 8 |
+
+
+ | 143 |
+ R1746H2 |
+ LXS9 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ F |
+ 10 |
+ 5 |
+
+
+ | 144 |
+ R2801H2 |
+ LXS9 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ D |
+ 1 |
+ 1 |
+
+
+ | 145 |
+ R1812H2 |
+ LXS90 |
+ 61 |
+ F |
+ 25 |
+ 2 |
+ 1562224038 |
+ F |
+ 25 |
+ 11 |
+
+
+ | 146 |
+ R1813H2 |
+ LXS90 |
+ 61 |
+ M |
+ 25 |
+ 2 |
+ 1523516009 |
+ A |
+ 12 |
+ 6 |
+
+
+ | 147 |
+ R1736H2 |
+ LXS92 |
+ 66 |
+ F |
+ 23 |
+ 2 |
+ 1523516015 |
+ E |
+ 10 |
+ 5 |
+
+
+ | 148 |
+ R1609H2 |
+ LXS92 |
+ 87 |
+ M |
+ 23 |
+ 2 |
+ 1523516032 |
+ A |
+ 7 |
+ 4 |
+
+
+ | 149 |
+ R1624H2 |
+ LXS93 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516032 |
+ B |
+ 7 |
+ 4 |
+
+
+ | 150 |
+ R1815H2 |
+ LXS93 |
+ 61 |
+ M |
+ 26 |
+ 2 |
+ 1523516009 |
+ B |
+ 12 |
+ 6 |
+
+
+ | 151 |
+ R1991H2 |
+ LXS94 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224036 |
+ C |
+ 17 |
+ 9 |
+
+
+ | 152 |
+ R2002H2 |
+ LXS94 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1562224049 |
+ B |
+ 18 |
+ 9 |
+
+
+ | 153 |
+ R1996H2 |
+ LXS96 |
+ 75 |
+ F |
+ 23 |
+ 2 |
+ 1562224036 |
+ F |
+ 17 |
+ 9 |
+
+
+ | 154 |
+ R1772H2 |
+ LXS96 |
+ 63 |
+ M |
+ 23 |
+ 2 |
+ 1523516007 |
+ C |
+ 11 |
+ 6 |
+
+
+ | 155 |
+ R2759H2 |
+ LXS97 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224060 |
+ B |
+ 22 |
+ 10 |
+
+
+ | 156 |
+ R2739H2 |
+ LXS97 |
+ 79 |
+ M |
+ 26 |
+ 2 |
+ 1523516028 |
+ F |
+ 3 |
+ 2 |
+
+
+ | 157 |
+ R2149H2 |
+ LXS98 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516033 |
+ C |
+ 8 |
+ 4 |
+
+
+ | 158 |
+ R1888H2 |
+ LXS98 |
+ 76 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ B |
+ 26 |
+ 12 |
+
+
+ | 159 |
+ R1644H2 |
+ LXS99 |
+ 79 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ B |
+ 10 |
+ 5 |
+
+
+ | 160 |
+ R2145H2 |
+ LXS99 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ F |
+ 19 |
+ 9 |
+
+
+
+ |
+
+
+
+
+
+ |
+
+
+ |
+ Downloading all data:
+
+ All data links (right-most column above) will be available as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
+ |
+
+
+
diff --git a/general/datasets/Illum_lxs_hipp_quant0807/citation.rtf b/general/datasets/Illum_lxs_hipp_quant0807/citation.rtf
new file mode 100644
index 0000000..29fd952
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant0807/citation.rtf
@@ -0,0 +1,3 @@
+Downloading all data:
+
+All data links (right-most column above) will be available as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
diff --git a/general/datasets/Illum_lxs_hipp_quant0807/contributors.rtf b/general/datasets/Illum_lxs_hipp_quant0807/contributors.rtf
new file mode 100644
index 0000000..775c0ee
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant0807/contributors.rtf
@@ -0,0 +1,5 @@
+About this text file:
+
+INFO file prepared by Xusheng Wang, Oct 24, 2007.
+
+Data set uploaded by Arthur Centeno, Aug 30, 2007.
diff --git a/general/datasets/Illum_lxs_hipp_quant0807/experiment-design.rtf b/general/datasets/Illum_lxs_hipp_quant0807/experiment-design.rtf
new file mode 100644
index 0000000..f477cb7
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant0807/experiment-design.rtf
@@ -0,0 +1 @@
+Experimental Design and Batch Structure: This data set consists arrays processed in 13 groups over a five month period (July 2006 to Dec 2006). Most groups consisted of 12 samples. All arrays in this data set were processed using a single protocol by a single operator, Feng Yiao. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between July 28 and Dec 21, 2006. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Illum_lxs_hipp_quant0807/notes.rtf b/general/datasets/Illum_lxs_hipp_quant0807/notes.rtf
new file mode 100644
index 0000000..938409b
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant0807/notes.rtf
@@ -0,0 +1,3 @@
+ANNOTATION: In spring of 2007, Robert W. Williams and Hongqiang Li reannotated the Illumina Mouse-6 array content. This new annotation is now incorporated into GeneNetwork. For 46166 probes on the Mouse 6 array platform (including control probes) we have identified 35975 NCBI Entrez Gene IDs; 26481 matched human Gene IDs; 23899 matched rat Gene IDs; 26883 NCBI HomoloGene IDs; and 12791 OMIM IDs.
+
+Position data for the 50-mer Illumina Mouse-6 array were initially downloaded from Sanger at http://www.sanger.ac.uk/Users/avc/Illumina/Mouse-6_V1.gff.gz but we then updated all positions by BLAT analysis from mm6 positions to mm8 positions (Hongqiang Li).
diff --git a/general/datasets/Illum_lxs_hipp_quant0807/platform.rtf b/general/datasets/Illum_lxs_hipp_quant0807/platform.rtf
new file mode 100644
index 0000000..2ac899d
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant0807/platform.rtf
@@ -0,0 +1,5 @@
+About the array platform:
+
+Illumina Sentrix Mouse-6 BeadArray Platform: The Mouse6 array consists of 46,116 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+Dunning M, Smith M, Thorne N, Tavare S (2006) beadarray: An R package to analyse Illumina BeadArrays. R News (the Newsletter of the P Project) 6:17-23. (see pages 17-23 of http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf).
diff --git a/general/datasets/Illum_lxs_hipp_quant0807/processing.rtf b/general/datasets/Illum_lxs_hipp_quant0807/processing.rtf
new file mode 100644
index 0000000..c3d0555
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant0807/processing.rtf
@@ -0,0 +1,3 @@
+About data processing:
+
+This data set uses the LOESS with Variance Stabilizing Transform (VST) and Background correction from the lumi package downloaded from Bioconductor (http://www.bioconductor.org/). For the more detailed information, please see the lumi package documentation.
diff --git a/general/datasets/Illum_lxs_hipp_quant0807/summary.rtf b/general/datasets/Illum_lxs_hipp_quant0807/summary.rtf
new file mode 100644
index 0000000..ebfc03f
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant0807/summary.rtf
@@ -0,0 +1,33 @@
+August 07 ILLUMINA Mouse-6 DATA SET RSN: The LXS Hippocampus Illumina Robust Spline Normalization with No Background correction data set provides estimates of mRNA expression in the hippocampus of 75 LXS recombinant inbred strains, the two parental strains, ILS/Ibg and ISS/Ibg (Inbred Long Sleep and Inbred Short Sleep strains from the Institute of Behavioral Genetics), and the two reciprocal F1 strains (ILSXISSF1, ISSXILSF1). All samples are from normal adult control animals raised in a standard laboratory environment. Subsequent data sets will provide estimates of mRNA expression following restraint stress, ethanol treatment, and stress followed by ethanol using many of the same strains (Lu Lu and colleagues).
+
+A total of 240 pooled hippocampal samples were processed using 40 Illumina Sentrix Mouse-6 v 1.0 oligomer microarray BeadArray slides. Twenty-seven Mouse-6 slides and a total of 160 samples passed stringent quality control and error checking. We should note that this is our first experience using the Illumina platform and the initial set of 13 slides were not included. This particular data set was processed using the Illumina "Robust Spline Normalization with No Background Correction" protocol. Values were log2 transformed and the current data range from 6.481 average (very low or no expression) to 24.852 (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Hippocampus Illumina (Aug 07) RSN data set, ### probes have LRS values >46.
+
+In comparison, here are the yields of QTLs with LOD>10 for other closely related data sets:
+
+
+ - 1050 for Hippocampus Illumina (Aug07) LOESS
+ - 1162 for Hippocampus Illumina (Aug07) LOESS_NB
+ - 1129 for Hippocampus Illumina (Aug07) QUANT
+ - 1176 for Hippocampus Illumina (Aug07) QUANT_NB
+ - NO DATA for Hippocampus Illumina (Aug07) RSN
+ - NO DATA for Hippocampus Illumina (Aug07) RSN_NB (THIS DATA SET)
+ - 1183 for Hippocampus Illumina (May 07) RankInv
+ - 1167 for Hippocampus Illumina (Oct06) Rank
+ - 1170 for Hippocampus Illumina (Oct06) RankInv
+
+
+The LRS achieved in the different version of the LXS Hippocampus data for probe ILM103520706 (Disabled 1; Dab1) are as follow
+
+
+ - 338.4 for Hippocampus Illumina (Aug07) LOESS
+ - 339.8 for Hippocampus Illumina (Aug07) LOESS_NB
+ - 370.2 for Hippocampus Illumina (Aug07) QUANT
+ - 363.5 for Hippocampus Illumina (Aug07) QUANT_NB
+ - 374.8 for Hippocampus Illumina (Aug07) RSN
+ - 363.0 for Hippocampus Illumina (Aug07) RSN_NB (THIS DATA SET)
+ - 360.3 for Hippocampus Illumina (May 07) RankInv
+ - 358.1 for Hippocampus Illumina (Oct06) Rank
+ - 358.8 for Hippocampus Illumina (Oct06) RankInv
+
diff --git a/general/datasets/Illum_lxs_hipp_quant0807/tissue.rtf b/general/datasets/Illum_lxs_hipp_quant0807/tissue.rtf
new file mode 100644
index 0000000..febccce
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant0807/tissue.rtf
@@ -0,0 +1,9 @@
+About the animals and tissue used to generate this set of data:
+
+All animals were raised at the IBG by Bennett and colleagues in an SPF facility. No cases were MHV positive. Mice were killed by cervical dislocation. Whole brain dissections were performed at the IBG by Bennett and colleagues and shipped in RNAlater to Lu Lu and colleagues at UTHSC. Most hippocampal dissections (all were bilateral) were performed by Zhiping Jia. Cerebella, olfactory bulbs, and brain stems were also dissected and stored at -80 deg C using further use. Hippocampal samples are very close to complete (see Lu et al., 2001 but probably include variable amounts of fimbria and choroid plexus (see expression of transthyretin, Ttr, as a marker of choroid plexus).
+
+A pool of dissected tissue from four hippocampi taken from two naive adults of the same strain, sex, and age was collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at UTHSC by Zhiping Jia.
+
+All animals used in this study were between 53 and 90 days of age (average of 72 days; see Table 1 below).
+
+
diff --git a/general/datasets/Illum_lxs_hipp_quant_nb0807/acknowledgment.rtf b/general/datasets/Illum_lxs_hipp_quant_nb0807/acknowledgment.rtf
new file mode 100644
index 0000000..d8f3e9a
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant_nb0807/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Data source acknowledgment:
+
+Data were generated with funds to Lu Lu, Beth Bennett, Mike Miles, Melloni Cook from INIA. · Lu Lu, M.D. Grant Support: NIH U01AA13499, U24AA13513 (Lu Lu, PI)
diff --git a/general/datasets/Illum_lxs_hipp_quant_nb0807/cases.rtf b/general/datasets/Illum_lxs_hipp_quant_nb0807/cases.rtf
new file mode 100644
index 0000000..efa4371
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant_nb0807/cases.rtf
@@ -0,0 +1,2140 @@
+Quality Control on Sex Labels: Sex of the samples was validated using sex-specific probe set.
+
+
+
+
+ |
+ Legend: We evaluated whether or not the sex of samples were labeled correctly by measuring the expression of Xist using probe ILM106520068. In this bar chart the expression of Xist is very low in LXS114 and has a low error term. This is because both arrays are male samples rather than 1 male and 1 female sample.
+
+
+
+ Data Table 1:
+
+
+ This table lists all arrays by order of strain (index) and includes data on tube ID, strain, age, sex, F generation number, number of animals in each sample pool (pool size), slide ID, slide position (A through F), scan date, and scan batch.
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ gener-
+ ation |
+ pool
+ size |
+ slide
+ ID |
+ slide
+ position |
+ batch
+ by slide |
+ scan
+ batch |
+
+
+ | 1 |
+ R2851H2 |
+ ILS |
+ 77 |
+ F |
+ >100 |
+ 4 |
+ 1523516003 |
+ B |
+ 1 |
+ 1 |
+
+
+ | 2 |
+ R0595H2 |
+ ILS |
+ 71 |
+ F |
+ >100 |
+ 2 |
+ 1523516030 |
+ B |
+ 4 |
+ 2 |
+
+
+ | 3 |
+ R2874H2 |
+ ILS |
+ 78 |
+ M |
+ >100 |
+ 4 |
+ 1523516011 |
+ B |
+ 2 |
+ 1 |
+
+
+ | 4 |
+ R0585H2 |
+ ILS |
+ 65 |
+ M |
+ >100 |
+ 2 |
+ 1523516028 |
+ A |
+ 3 |
+ 2 |
+
+
+ | 5 |
+ R3281H1 |
+ ILSXISSF1 |
+ 90 |
+ F |
+ NA |
+ 3 |
+ 1562224029 |
+ A |
+ 28 |
+ 13 |
+
+
+ | 6 |
+ R2857H2 |
+ ISS |
+ 75 |
+ F |
+ >100 |
+ 4 |
+ 1523516011 |
+ A |
+ 2 |
+ 1 |
+
+
+ | 7 |
+ R0589H2 |
+ ISS |
+ 73 |
+ F |
+ >100 |
+ 2 |
+ 1523516028 |
+ B |
+ 3 |
+ 2 |
+
+
+ | 8 |
+ R2955H2 |
+ ISS |
+ 53 |
+ M |
+ >100 |
+ 3 |
+ 1523516003 |
+ A |
+ 1 |
+ 1 |
+
+
+ | 9 |
+ R0578H2 |
+ ISS |
+ 67 |
+ M |
+ >100 |
+ 2 |
+ 1523516030 |
+ A |
+ 4 |
+ 2 |
+
+
+ | 10 |
+ R3282H1 |
+ ISSXILSF1 |
+ 97 |
+ M |
+ NA |
+ 3 |
+ 1562224029 |
+ B |
+ 28 |
+ 13 |
+
+
+ | 11 |
+ R2013H2 |
+ LXS10 |
+ 84 |
+ F |
+ 27 |
+ 2 |
+ 1562224049 |
+ E |
+ 18 |
+ 9 |
+
+
+ | 12 |
+ R1993H2 |
+ LXS10 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1562224036 |
+ E |
+ 17 |
+ 9 |
+
+
+ | 13 |
+ R1997H2 |
+ LXS100 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ A |
+ 18 |
+ 9 |
+
+
+ | 14 |
+ R1983H2 |
+ LXS100 |
+ 77 |
+ M |
+ 25 |
+ 2 |
+ 1562224047 |
+ F |
+ 16 |
+ 8 |
+
+
+ | 15 |
+ R2083H2 |
+ LXS101 |
+ 85 |
+ F |
+ 28 |
+ 2 |
+ 1562224050 |
+ B |
+ 19 |
+ 9 |
+
+
+ | 16 |
+ R2084H2 |
+ LXS101 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224050 |
+ C |
+ 19 |
+ 9 |
+
+
+ | 17 |
+ R2186H2 |
+ LXS102 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1523516001 |
+ C |
+ 9 |
+ 5 |
+
+
+ | 18 |
+ R2187H2 |
+ LXS102 |
+ 73 |
+ M |
+ 29 |
+ 2 |
+ 1562224053 |
+ C |
+ 20 |
+ 10 |
+
+
+ | 19 |
+ R2809H2 |
+ LXS103 |
+ 72 |
+ F |
+ 26 |
+ 2 |
+ 1562224034 |
+ C |
+ 23 |
+ 11 |
+
+
+ | 20 |
+ R2854H1 |
+ LXS103 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516006 |
+ D |
+ 6 |
+ 3 |
+
+
+ | 21 |
+ R2735H2 |
+ LXS107 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516028 |
+ D |
+ 3 |
+ 2 |
+
+
+ | 22 |
+ R2738H2 |
+ LXS107 |
+ 78 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ C |
+ 21 |
+ 10 |
+
+
+ | 23 |
+ R2840H2 |
+ LXS110 |
+ 67 |
+ F |
+ 25 |
+ 2 |
+ 1562224037 |
+ D |
+ 24 |
+ 11 |
+
+
+ | 24 |
+ R2157H2 |
+ LXS110 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516033 |
+ E |
+ 8 |
+ 4 |
+
+
+ | 25 |
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+ 72 |
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+ 27 |
+ 2 |
+ 1523516001 |
+ B |
+ 9 |
+ 5 |
+
+
+ | 26 |
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+ 84 |
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+ 27 |
+ 2 |
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+ D |
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+ 12 |
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+
+ | 27 |
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+ 28 |
+ 2 |
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+ D |
+ 20 |
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+
+
+ | 28 |
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+ 28 |
+ 2 |
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+ D |
+ 9 |
+ 5 |
+
+
+ | 29 |
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+ 80 |
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+ 27 |
+ 2 |
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+ A |
+ 9 |
+ 5 |
+
+
+ | 30 |
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+ 27 |
+ 2 |
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+ D |
+ 19 |
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+
+
+ | 31 |
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+ 28 |
+ 2 |
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+ D |
+ 23 |
+ 11 |
+
+
+ | 32 |
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+ 27 |
+ 2 |
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+ E |
+ 9 |
+ 5 |
+
+
+ | 33 |
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+ 86 |
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+ 26 |
+ 2 |
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+ D |
+ 17 |
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+
+
+ | 34 |
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+ 26 |
+ 2 |
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+ 21 |
+ 10 |
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+
+ | 35 |
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+ 28 |
+ 2 |
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+ 25 |
+ 11 |
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+
+ | 36 |
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+ 27 |
+ 2 |
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+ E |
+ 2 |
+ 1 |
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+
+ | 37 |
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+ 83 |
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+ 28 |
+ 2 |
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+ 3 |
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+
+ | 38 |
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+ 2 |
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+
+ | 39 |
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+ 25 |
+ 2 |
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+ 13 |
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+
+ | 40 |
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+ 26 |
+ 2 |
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+ 12 |
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+
+ | 41 |
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+ 25 |
+ 2 |
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+ A |
+ 19 |
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+
+ | 42 |
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+ 26 |
+ 2 |
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+
+ | 43 |
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+ 2 |
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+ 13 |
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+
+ | 44 |
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+ 25 |
+ 2 |
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+ 8 |
+ 4 |
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+
+ | 45 |
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+ 26 |
+ 2 |
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+ 14 |
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+
+ | 46 |
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+ 26 |
+ 2 |
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+ 13 |
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+
+ | 47 |
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+ 27 |
+ 2 |
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+ 12 |
+ 6 |
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+
+ | 48 |
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+ LXS2 |
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+ 28 |
+ 2 |
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+ E |
+ 4 |
+ 2 |
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+
+ | 49 |
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+ 27 |
+ 2 |
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+ E |
+ 7 |
+ 4 |
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+
+ | 50 |
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+ 27 |
+ 2 |
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+ D |
+ 21 |
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+
+ | 51 |
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+ 73 |
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+ 26 |
+ 2 |
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+ D |
+ 15 |
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+
+ | 52 |
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+ 73 |
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+ 26 |
+ 2 |
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+ A |
+ 16 |
+ 8 |
+
+
+ | 53 |
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+ 74 |
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+ 26 |
+ 2 |
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+ C |
+ 1 |
+ 1 |
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+
+ | 54 |
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+ 56 |
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+ 25 |
+ 2 |
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+ A |
+ 11 |
+ 6 |
+
+
+ | 55 |
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+ 75 |
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+ 27 |
+ 2 |
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+ A |
+ 17 |
+ 9 |
+
+
+ | 56 |
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+ 75 |
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+ 27 |
+ 2 |
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+ C |
+ 18 |
+ 9 |
+
+
+ | 57 |
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+ 82 |
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+ 25 |
+ 2 |
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+ 18 |
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+
+
+ | 58 |
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+ 82 |
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+ 26 |
+ 2 |
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+ D |
+ 18 |
+ 9 |
+
+
+ | 59 |
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+ 28 |
+ 2 |
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+ 12 |
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+
+ | 60 |
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+ 2 |
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+ 26 |
+ 12 |
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+
+ | 61 |
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+ 2 |
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+ 3 |
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+
+ | 62 |
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+ 26 |
+ 2 |
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+ 12 |
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+
+ | 63 |
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+ 2 |
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+ 22 |
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+
+ | 64 |
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+ 28 |
+ 2 |
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+ 13 |
+ 7 |
+
+
+ | 65 |
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+ 26 |
+ 2 |
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+ 4 |
+ 2 |
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+
+ | 66 |
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+ 2 |
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+
+ | 67 |
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+ 2 |
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+ 11 |
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+
+ | 68 |
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+ 2 |
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+
+ | 69 |
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+ 2 |
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+
+ | 70 |
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+ 2 |
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+
+ | 71 |
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+ 2 |
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+ 15 |
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+
+
+ | 72 |
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+ 2 |
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+ 4 |
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+
+ | 73 |
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+ 2 |
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+ 2 |
+ 1 |
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+
+ | 74 |
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+ 2 |
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+
+ | 75 |
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+ 2 |
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+ 20 |
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+
+ | 76 |
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+ 2 |
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+ 3 |
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+
+ | 77 |
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+ 2 |
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+
+ | 78 |
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+ 2 |
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+
+ | 79 |
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+
+ | 80 |
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+ 2 |
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+
+ | 81 |
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+ 2 |
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+
+
+ | 82 |
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+ 2 |
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+
+ | 83 |
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+
+ | 84 |
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+ 2 |
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+
+ | 85 |
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+ 2 |
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+
+
+ | 86 |
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+ 2 |
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+
+ | 87 |
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+ 2 |
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+
+
+ | 88 |
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+ 2 |
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+ 3 |
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+
+ | 89 |
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+ 2 |
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+ 3 |
+
+
+ | 90 |
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+ 2 |
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+
+ | 91 |
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+ 2 |
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+
+ | 92 |
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+ 2 |
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+
+ | 93 |
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+ 2 |
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+
+ | 94 |
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+ 2 |
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+
+ | 95 |
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+
+ | 96 |
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+ 2 |
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+
+ | 97 |
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+ 2 |
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+
+
+ | 98 |
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+ 2 |
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+
+
+ | 99 |
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+ 2 |
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+
+
+ | 100 |
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+ 2 |
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+
+
+ | 101 |
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+ 2 |
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+
+
+ | 102 |
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+
+
+ | 103 |
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+ 2 |
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+
+
+ | 104 |
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+ 2 |
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+
+ | 105 |
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+ 2 |
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+
+ | 106 |
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+ 2 |
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+
+
+ | 107 |
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+ 2 |
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+
+ | 108 |
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+ 2 |
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+
+ | 109 |
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+ 2 |
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+
+
+ | 110 |
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+ 2 |
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+
+
+ | 111 |
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+ 2 |
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+
+
+ | 112 |
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+ 2 |
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+ 6 |
+
+
+ | 113 |
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+ 2 |
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+ 1 |
+ 1 |
+
+
+ | 114 |
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+ 2 |
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+
+
+ | 115 |
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+ 2 |
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+ 8 |
+
+
+ | 116 |
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+ 2 |
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+
+
+ | 117 |
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+ 2 |
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+ 4 |
+
+
+ | 118 |
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+ 2 |
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+
+
+ | 119 |
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+ 2 |
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+
+
+ | 120 |
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+ 2 |
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+ 7 |
+
+
+ | 121 |
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+ 2 |
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+ 4 |
+ 2 |
+
+
+ | 122 |
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+ 2 |
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+ 6 |
+
+
+ | 123 |
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+ 2 |
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+ 16 |
+ 8 |
+
+
+ | 124 |
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+ M |
+ 27 |
+ 2 |
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+ 1 |
+ 1 |
+
+
+ | 125 |
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+ 2 |
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+ 19 |
+ 9 |
+
+
+ | 126 |
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+ 26 |
+ 2 |
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+ A |
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+ 12 |
+
+
+ | 127 |
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+ 2 |
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+ E |
+ 14 |
+ 7 |
+
+
+ | 128 |
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+ M |
+ 26 |
+ 2 |
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+ D |
+ 14 |
+ 7 |
+
+
+ | 129 |
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+ LXS8 |
+ 70 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ C |
+ 6 |
+ 3 |
+
+
+ | 130 |
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+ 76 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ B |
+ 20 |
+ 10 |
+
+
+ | 131 |
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+ LXS80 |
+ 71 |
+ F |
+ 25 |
+ 2 |
+ 1523516029 |
+ A |
+ 14 |
+ 7 |
+
+
+ | 132 |
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+ LXS80 |
+ 71 |
+ M |
+ 25 |
+ 2 |
+ 1523516029 |
+ B |
+ 14 |
+ 7 |
+
+
+ | 133 |
+ R2830H1 |
+ LXS84 |
+ 66 |
+ F |
+ 26 |
+ 2 |
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+ D |
+ 2 |
+ 1 |
+
+
+ | 134 |
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+ LXS84 |
+ 66 |
+ M |
+ 26 |
+ 2 |
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+ A |
+ 24 |
+ 11 |
+
+
+ | 135 |
+ R2839H2 |
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+ 68 |
+ F |
+ 27 |
+ 2 |
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+ C |
+ 24 |
+ 11 |
+
+
+ | 136 |
+ R2838H1 |
+ LXS86 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516006 |
+ B |
+ 6 |
+ 3 |
+
+
+ | 137 |
+ R2882H1 |
+ LXS87 |
+ 66 |
+ F |
+ 27 |
+ 2 |
+ 1523516006 |
+ F |
+ 6 |
+ 3 |
+
+
+ | 138 |
+ R2744H2 |
+ LXS87 |
+ 71 |
+ M |
+ 26 |
+ 2 |
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+ E |
+ 21 |
+ 10 |
+
+
+ | 139 |
+ R2831H2 |
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+ 69 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ B |
+ 24 |
+ 11 |
+
+
+ | 140 |
+ R2762H2 |
+ LXS88 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1523516005 |
+ A |
+ 5 |
+ 3 |
+
+
+ | 141 |
+ R2828H1 |
+ LXS89 |
+ 75 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ C |
+ 2 |
+ 1 |
+
+
+ | 142 |
+ R1962H2 |
+ LXS89 |
+ 73 |
+ M |
+ 25 |
+ 2 |
+ 1562224032 |
+ A |
+ 15 |
+ 8 |
+
+
+ | 143 |
+ R1746H2 |
+ LXS9 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ F |
+ 10 |
+ 5 |
+
+
+ | 144 |
+ R2801H2 |
+ LXS9 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ D |
+ 1 |
+ 1 |
+
+
+ | 145 |
+ R1812H2 |
+ LXS90 |
+ 61 |
+ F |
+ 25 |
+ 2 |
+ 1562224038 |
+ F |
+ 25 |
+ 11 |
+
+
+ | 146 |
+ R1813H2 |
+ LXS90 |
+ 61 |
+ M |
+ 25 |
+ 2 |
+ 1523516009 |
+ A |
+ 12 |
+ 6 |
+
+
+ | 147 |
+ R1736H2 |
+ LXS92 |
+ 66 |
+ F |
+ 23 |
+ 2 |
+ 1523516015 |
+ E |
+ 10 |
+ 5 |
+
+
+ | 148 |
+ R1609H2 |
+ LXS92 |
+ 87 |
+ M |
+ 23 |
+ 2 |
+ 1523516032 |
+ A |
+ 7 |
+ 4 |
+
+
+ | 149 |
+ R1624H2 |
+ LXS93 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516032 |
+ B |
+ 7 |
+ 4 |
+
+
+ | 150 |
+ R1815H2 |
+ LXS93 |
+ 61 |
+ M |
+ 26 |
+ 2 |
+ 1523516009 |
+ B |
+ 12 |
+ 6 |
+
+
+ | 151 |
+ R1991H2 |
+ LXS94 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224036 |
+ C |
+ 17 |
+ 9 |
+
+
+ | 152 |
+ R2002H2 |
+ LXS94 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1562224049 |
+ B |
+ 18 |
+ 9 |
+
+
+ | 153 |
+ R1996H2 |
+ LXS96 |
+ 75 |
+ F |
+ 23 |
+ 2 |
+ 1562224036 |
+ F |
+ 17 |
+ 9 |
+
+
+ | 154 |
+ R1772H2 |
+ LXS96 |
+ 63 |
+ M |
+ 23 |
+ 2 |
+ 1523516007 |
+ C |
+ 11 |
+ 6 |
+
+
+ | 155 |
+ R2759H2 |
+ LXS97 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224060 |
+ B |
+ 22 |
+ 10 |
+
+
+ | 156 |
+ R2739H2 |
+ LXS97 |
+ 79 |
+ M |
+ 26 |
+ 2 |
+ 1523516028 |
+ F |
+ 3 |
+ 2 |
+
+
+ | 157 |
+ R2149H2 |
+ LXS98 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516033 |
+ C |
+ 8 |
+ 4 |
+
+
+ | 158 |
+ R1888H2 |
+ LXS98 |
+ 76 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ B |
+ 26 |
+ 12 |
+
+
+ | 159 |
+ R1644H2 |
+ LXS99 |
+ 79 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ B |
+ 10 |
+ 5 |
+
+
+ | 160 |
+ R2145H2 |
+ LXS99 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ F |
+ 19 |
+ 9 |
+
+
+
+ |
+
+
+
+
+
+ |
+
+
+ |
+ Downloading all data:
+
+ All data links (right-most column above) will be available as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
+ |
+
+
+
diff --git a/general/datasets/Illum_lxs_hipp_quant_nb0807/citation.rtf b/general/datasets/Illum_lxs_hipp_quant_nb0807/citation.rtf
new file mode 100644
index 0000000..29fd952
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant_nb0807/citation.rtf
@@ -0,0 +1,3 @@
+Downloading all data:
+
+All data links (right-most column above) will be available as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
diff --git a/general/datasets/Illum_lxs_hipp_quant_nb0807/contributors.rtf b/general/datasets/Illum_lxs_hipp_quant_nb0807/contributors.rtf
new file mode 100644
index 0000000..775c0ee
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant_nb0807/contributors.rtf
@@ -0,0 +1,5 @@
+About this text file:
+
+INFO file prepared by Xusheng Wang, Oct 24, 2007.
+
+Data set uploaded by Arthur Centeno, Aug 30, 2007.
diff --git a/general/datasets/Illum_lxs_hipp_quant_nb0807/experiment-design.rtf b/general/datasets/Illum_lxs_hipp_quant_nb0807/experiment-design.rtf
new file mode 100644
index 0000000..f477cb7
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant_nb0807/experiment-design.rtf
@@ -0,0 +1 @@
+Experimental Design and Batch Structure: This data set consists arrays processed in 13 groups over a five month period (July 2006 to Dec 2006). Most groups consisted of 12 samples. All arrays in this data set were processed using a single protocol by a single operator, Feng Yiao. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between July 28 and Dec 21, 2006. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Illum_lxs_hipp_quant_nb0807/notes.rtf b/general/datasets/Illum_lxs_hipp_quant_nb0807/notes.rtf
new file mode 100644
index 0000000..938409b
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant_nb0807/notes.rtf
@@ -0,0 +1,3 @@
+ANNOTATION: In spring of 2007, Robert W. Williams and Hongqiang Li reannotated the Illumina Mouse-6 array content. This new annotation is now incorporated into GeneNetwork. For 46166 probes on the Mouse 6 array platform (including control probes) we have identified 35975 NCBI Entrez Gene IDs; 26481 matched human Gene IDs; 23899 matched rat Gene IDs; 26883 NCBI HomoloGene IDs; and 12791 OMIM IDs.
+
+Position data for the 50-mer Illumina Mouse-6 array were initially downloaded from Sanger at http://www.sanger.ac.uk/Users/avc/Illumina/Mouse-6_V1.gff.gz but we then updated all positions by BLAT analysis from mm6 positions to mm8 positions (Hongqiang Li).
diff --git a/general/datasets/Illum_lxs_hipp_quant_nb0807/platform.rtf b/general/datasets/Illum_lxs_hipp_quant_nb0807/platform.rtf
new file mode 100644
index 0000000..2ac899d
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant_nb0807/platform.rtf
@@ -0,0 +1,5 @@
+About the array platform:
+
+Illumina Sentrix Mouse-6 BeadArray Platform: The Mouse6 array consists of 46,116 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+Dunning M, Smith M, Thorne N, Tavare S (2006) beadarray: An R package to analyse Illumina BeadArrays. R News (the Newsletter of the P Project) 6:17-23. (see pages 17-23 of http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf).
diff --git a/general/datasets/Illum_lxs_hipp_quant_nb0807/processing.rtf b/general/datasets/Illum_lxs_hipp_quant_nb0807/processing.rtf
new file mode 100644
index 0000000..c3d0555
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant_nb0807/processing.rtf
@@ -0,0 +1,3 @@
+About data processing:
+
+This data set uses the LOESS with Variance Stabilizing Transform (VST) and Background correction from the lumi package downloaded from Bioconductor (http://www.bioconductor.org/). For the more detailed information, please see the lumi package documentation.
diff --git a/general/datasets/Illum_lxs_hipp_quant_nb0807/summary.rtf b/general/datasets/Illum_lxs_hipp_quant_nb0807/summary.rtf
new file mode 100644
index 0000000..ebfc03f
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant_nb0807/summary.rtf
@@ -0,0 +1,33 @@
+August 07 ILLUMINA Mouse-6 DATA SET RSN: The LXS Hippocampus Illumina Robust Spline Normalization with No Background correction data set provides estimates of mRNA expression in the hippocampus of 75 LXS recombinant inbred strains, the two parental strains, ILS/Ibg and ISS/Ibg (Inbred Long Sleep and Inbred Short Sleep strains from the Institute of Behavioral Genetics), and the two reciprocal F1 strains (ILSXISSF1, ISSXILSF1). All samples are from normal adult control animals raised in a standard laboratory environment. Subsequent data sets will provide estimates of mRNA expression following restraint stress, ethanol treatment, and stress followed by ethanol using many of the same strains (Lu Lu and colleagues).
+
+A total of 240 pooled hippocampal samples were processed using 40 Illumina Sentrix Mouse-6 v 1.0 oligomer microarray BeadArray slides. Twenty-seven Mouse-6 slides and a total of 160 samples passed stringent quality control and error checking. We should note that this is our first experience using the Illumina platform and the initial set of 13 slides were not included. This particular data set was processed using the Illumina "Robust Spline Normalization with No Background Correction" protocol. Values were log2 transformed and the current data range from 6.481 average (very low or no expression) to 24.852 (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Hippocampus Illumina (Aug 07) RSN data set, ### probes have LRS values >46.
+
+In comparison, here are the yields of QTLs with LOD>10 for other closely related data sets:
+
+
+ - 1050 for Hippocampus Illumina (Aug07) LOESS
+ - 1162 for Hippocampus Illumina (Aug07) LOESS_NB
+ - 1129 for Hippocampus Illumina (Aug07) QUANT
+ - 1176 for Hippocampus Illumina (Aug07) QUANT_NB
+ - NO DATA for Hippocampus Illumina (Aug07) RSN
+ - NO DATA for Hippocampus Illumina (Aug07) RSN_NB (THIS DATA SET)
+ - 1183 for Hippocampus Illumina (May 07) RankInv
+ - 1167 for Hippocampus Illumina (Oct06) Rank
+ - 1170 for Hippocampus Illumina (Oct06) RankInv
+
+
+The LRS achieved in the different version of the LXS Hippocampus data for probe ILM103520706 (Disabled 1; Dab1) are as follow
+
+
+ - 338.4 for Hippocampus Illumina (Aug07) LOESS
+ - 339.8 for Hippocampus Illumina (Aug07) LOESS_NB
+ - 370.2 for Hippocampus Illumina (Aug07) QUANT
+ - 363.5 for Hippocampus Illumina (Aug07) QUANT_NB
+ - 374.8 for Hippocampus Illumina (Aug07) RSN
+ - 363.0 for Hippocampus Illumina (Aug07) RSN_NB (THIS DATA SET)
+ - 360.3 for Hippocampus Illumina (May 07) RankInv
+ - 358.1 for Hippocampus Illumina (Oct06) Rank
+ - 358.8 for Hippocampus Illumina (Oct06) RankInv
+
diff --git a/general/datasets/Illum_lxs_hipp_quant_nb0807/tissue.rtf b/general/datasets/Illum_lxs_hipp_quant_nb0807/tissue.rtf
new file mode 100644
index 0000000..febccce
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_quant_nb0807/tissue.rtf
@@ -0,0 +1,9 @@
+About the animals and tissue used to generate this set of data:
+
+All animals were raised at the IBG by Bennett and colleagues in an SPF facility. No cases were MHV positive. Mice were killed by cervical dislocation. Whole brain dissections were performed at the IBG by Bennett and colleagues and shipped in RNAlater to Lu Lu and colleagues at UTHSC. Most hippocampal dissections (all were bilateral) were performed by Zhiping Jia. Cerebella, olfactory bulbs, and brain stems were also dissected and stored at -80 deg C using further use. Hippocampal samples are very close to complete (see Lu et al., 2001 but probably include variable amounts of fimbria and choroid plexus (see expression of transthyretin, Ttr, as a marker of choroid plexus).
+
+A pool of dissected tissue from four hippocampi taken from two naive adults of the same strain, sex, and age was collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at UTHSC by Zhiping Jia.
+
+All animals used in this study were between 53 and 90 days of age (average of 72 days; see Table 1 below).
+
+
diff --git a/general/datasets/Illum_lxs_hipp_rse_1008/summary.rtf b/general/datasets/Illum_lxs_hipp_rse_1008/summary.rtf
new file mode 100644
index 0000000..f49829f
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rse_1008/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 63, Name: Hippocampus Illumina NOS (Oct08) RankInv beta
\ No newline at end of file
diff --git a/general/datasets/Illum_lxs_hipp_rsn0807/acknowledgment.rtf b/general/datasets/Illum_lxs_hipp_rsn0807/acknowledgment.rtf
new file mode 100644
index 0000000..d8f3e9a
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn0807/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Data source acknowledgment:
+
+Data were generated with funds to Lu Lu, Beth Bennett, Mike Miles, Melloni Cook from INIA. · Lu Lu, M.D. Grant Support: NIH U01AA13499, U24AA13513 (Lu Lu, PI)
diff --git a/general/datasets/Illum_lxs_hipp_rsn0807/cases.rtf b/general/datasets/Illum_lxs_hipp_rsn0807/cases.rtf
new file mode 100644
index 0000000..efa4371
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn0807/cases.rtf
@@ -0,0 +1,2140 @@
+Quality Control on Sex Labels: Sex of the samples was validated using sex-specific probe set.
+
+
+
+
+ |
+ Legend: We evaluated whether or not the sex of samples were labeled correctly by measuring the expression of Xist using probe ILM106520068. In this bar chart the expression of Xist is very low in LXS114 and has a low error term. This is because both arrays are male samples rather than 1 male and 1 female sample.
+
+
+
+ Data Table 1:
+
+
+ This table lists all arrays by order of strain (index) and includes data on tube ID, strain, age, sex, F generation number, number of animals in each sample pool (pool size), slide ID, slide position (A through F), scan date, and scan batch.
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ gener-
+ ation |
+ pool
+ size |
+ slide
+ ID |
+ slide
+ position |
+ batch
+ by slide |
+ scan
+ batch |
+
+
+ | 1 |
+ R2851H2 |
+ ILS |
+ 77 |
+ F |
+ >100 |
+ 4 |
+ 1523516003 |
+ B |
+ 1 |
+ 1 |
+
+
+ | 2 |
+ R0595H2 |
+ ILS |
+ 71 |
+ F |
+ >100 |
+ 2 |
+ 1523516030 |
+ B |
+ 4 |
+ 2 |
+
+
+ | 3 |
+ R2874H2 |
+ ILS |
+ 78 |
+ M |
+ >100 |
+ 4 |
+ 1523516011 |
+ B |
+ 2 |
+ 1 |
+
+
+ | 4 |
+ R0585H2 |
+ ILS |
+ 65 |
+ M |
+ >100 |
+ 2 |
+ 1523516028 |
+ A |
+ 3 |
+ 2 |
+
+
+ | 5 |
+ R3281H1 |
+ ILSXISSF1 |
+ 90 |
+ F |
+ NA |
+ 3 |
+ 1562224029 |
+ A |
+ 28 |
+ 13 |
+
+
+ | 6 |
+ R2857H2 |
+ ISS |
+ 75 |
+ F |
+ >100 |
+ 4 |
+ 1523516011 |
+ A |
+ 2 |
+ 1 |
+
+
+ | 7 |
+ R0589H2 |
+ ISS |
+ 73 |
+ F |
+ >100 |
+ 2 |
+ 1523516028 |
+ B |
+ 3 |
+ 2 |
+
+
+ | 8 |
+ R2955H2 |
+ ISS |
+ 53 |
+ M |
+ >100 |
+ 3 |
+ 1523516003 |
+ A |
+ 1 |
+ 1 |
+
+
+ | 9 |
+ R0578H2 |
+ ISS |
+ 67 |
+ M |
+ >100 |
+ 2 |
+ 1523516030 |
+ A |
+ 4 |
+ 2 |
+
+
+ | 10 |
+ R3282H1 |
+ ISSXILSF1 |
+ 97 |
+ M |
+ NA |
+ 3 |
+ 1562224029 |
+ B |
+ 28 |
+ 13 |
+
+
+ | 11 |
+ R2013H2 |
+ LXS10 |
+ 84 |
+ F |
+ 27 |
+ 2 |
+ 1562224049 |
+ E |
+ 18 |
+ 9 |
+
+
+ | 12 |
+ R1993H2 |
+ LXS10 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1562224036 |
+ E |
+ 17 |
+ 9 |
+
+
+ | 13 |
+ R1997H2 |
+ LXS100 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ A |
+ 18 |
+ 9 |
+
+
+ | 14 |
+ R1983H2 |
+ LXS100 |
+ 77 |
+ M |
+ 25 |
+ 2 |
+ 1562224047 |
+ F |
+ 16 |
+ 8 |
+
+
+ | 15 |
+ R2083H2 |
+ LXS101 |
+ 85 |
+ F |
+ 28 |
+ 2 |
+ 1562224050 |
+ B |
+ 19 |
+ 9 |
+
+
+ | 16 |
+ R2084H2 |
+ LXS101 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224050 |
+ C |
+ 19 |
+ 9 |
+
+
+ | 17 |
+ R2186H2 |
+ LXS102 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1523516001 |
+ C |
+ 9 |
+ 5 |
+
+
+ | 18 |
+ R2187H2 |
+ LXS102 |
+ 73 |
+ M |
+ 29 |
+ 2 |
+ 1562224053 |
+ C |
+ 20 |
+ 10 |
+
+
+ | 19 |
+ R2809H2 |
+ LXS103 |
+ 72 |
+ F |
+ 26 |
+ 2 |
+ 1562224034 |
+ C |
+ 23 |
+ 11 |
+
+
+ | 20 |
+ R2854H1 |
+ LXS103 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516006 |
+ D |
+ 6 |
+ 3 |
+
+
+ | 21 |
+ R2735H2 |
+ LXS107 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516028 |
+ D |
+ 3 |
+ 2 |
+
+
+ | 22 |
+ R2738H2 |
+ LXS107 |
+ 78 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ C |
+ 21 |
+ 10 |
+
+
+ | 23 |
+ R2840H2 |
+ LXS110 |
+ 67 |
+ F |
+ 25 |
+ 2 |
+ 1562224037 |
+ D |
+ 24 |
+ 11 |
+
+
+ | 24 |
+ R2157H2 |
+ LXS110 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516033 |
+ E |
+ 8 |
+ 4 |
+
+
+ | 25 |
+ R2172H2 |
+ LXS112 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ B |
+ 9 |
+ 5 |
+
+
+ | 26 |
+ R2841H2 |
+ LXS112 |
+ 84 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ D |
+ 27 |
+ 12 |
+
+
+ | 27 |
+ R2188H2 |
+ LXS114 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224053 |
+ D |
+ 20 |
+ 10 |
+
+
+ | 28 |
+ R2204H2 |
+ LXS114 |
+ 72 |
+ M |
+ 28 |
+ 2 |
+ 1523516001 |
+ D |
+ 9 |
+ 5 |
+
+
+ | 29 |
+ R2168H2 |
+ LXS115 |
+ 80 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ A |
+ 9 |
+ 5 |
+
+
+ | 30 |
+ R2085H2 |
+ LXS115 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ D |
+ 19 |
+ 9 |
+
+
+ | 31 |
+ R2811H2 |
+ LXS117 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224034 |
+ D |
+ 23 |
+ 11 |
+
+
+ | 32 |
+ R2212H2 |
+ LXS117 |
+ 74 |
+ M |
+ 27 |
+ 2 |
+ 1523516001 |
+ E |
+ 9 |
+ 5 |
+
+
+ | 33 |
+ R1992H2 |
+ LXS122 |
+ 86 |
+ F |
+ 26 |
+ 2 |
+ 1562224036 |
+ D |
+ 17 |
+ 9 |
+
+
+ | 34 |
+ R2219H2 |
+ LXS122 |
+ 72 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ A |
+ 21 |
+ 10 |
+
+
+ | 35 |
+ R2876H2 |
+ LXS123 |
+ 87 |
+ F |
+ 28 |
+ 2 |
+ 1562224038 |
+ C |
+ 25 |
+ 11 |
+
+
+ | 36 |
+ R2832H1 |
+ LXS123 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1523516011 |
+ E |
+ 2 |
+ 1 |
+
+
+ | 37 |
+ R2872H1 |
+ LXS124 |
+ 83 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ E |
+ 6 |
+ 3 |
+
+
+ | 38 |
+ R2871H2 |
+ LXS124 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224042 |
+ F |
+ 27 |
+ 12 |
+
+
+ | 39 |
+ R1909H2 |
+ LXS13 |
+ 79 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ D |
+ 13 |
+ 7 |
+
+
+ | 40 |
+ R1901H2 |
+ LXS13 |
+ 81 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ D |
+ 26 |
+ 12 |
+
+
+ | 41 |
+ R2023H2 |
+ LXS14 |
+ 86 |
+ F |
+ 25 |
+ 2 |
+ 1562224050 |
+ A |
+ 19 |
+ 9 |
+
+
+ | 42 |
+ R1612H2 |
+ LXS14 |
+ 85 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ A |
+ 10 |
+ 5 |
+
+
+ | 43 |
+ R1936H2 |
+ LXS16 |
+ 81 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ E |
+ 13 |
+ 7 |
+
+
+ | 44 |
+ R1912H2 |
+ LXS16 |
+ 81 |
+ M |
+ 25 |
+ 2 |
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+ B |
+ 8 |
+ 4 |
+
+
+ | 45 |
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+ LXS19 |
+ 66 |
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+ 26 |
+ 2 |
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+ F |
+ 14 |
+ 7 |
+
+
+ | 46 |
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+ 66 |
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+ 26 |
+ 2 |
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+ B |
+ 13 |
+ 7 |
+
+
+ | 47 |
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+ LXS2 |
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+ 27 |
+ 2 |
+ 1523516009 |
+ F |
+ 12 |
+ 6 |
+
+
+ | 48 |
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+ LXS2 |
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+ 28 |
+ 2 |
+ 1523516030 |
+ E |
+ 4 |
+ 2 |
+
+
+ | 49 |
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+ LXS22 |
+ 72 |
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+ 27 |
+ 2 |
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+ E |
+ 7 |
+ 4 |
+
+
+ | 50 |
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+ LXS22 |
+ 79 |
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+ 27 |
+ 2 |
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+ D |
+ 21 |
+ 10 |
+
+
+ | 51 |
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+ 73 |
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+ 26 |
+ 2 |
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+ D |
+ 15 |
+ 8 |
+
+
+ | 52 |
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+ 73 |
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+ 26 |
+ 2 |
+ 1562224047 |
+ A |
+ 16 |
+ 8 |
+
+
+ | 53 |
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+ 74 |
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+ 26 |
+ 2 |
+ 1523516003 |
+ C |
+ 1 |
+ 1 |
+
+
+ | 54 |
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+ 56 |
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+ 25 |
+ 2 |
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+ A |
+ 11 |
+ 6 |
+
+
+ | 55 |
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+ 75 |
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+ 27 |
+ 2 |
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+ A |
+ 17 |
+ 9 |
+
+
+ | 56 |
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+ 75 |
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+ 27 |
+ 2 |
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+ C |
+ 18 |
+ 9 |
+
+
+ | 57 |
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+ LXS26 |
+ 82 |
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+ 25 |
+ 2 |
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+ F |
+ 18 |
+ 9 |
+
+
+ | 58 |
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+ 82 |
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+ 26 |
+ 2 |
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+ D |
+ 18 |
+ 9 |
+
+
+ | 59 |
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+ 28 |
+ 2 |
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+ A |
+ 27 |
+ 12 |
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+
+ | 60 |
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+ 27 |
+ 2 |
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+ 26 |
+ 12 |
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+
+ | 61 |
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+ 27 |
+ 2 |
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+ 5 |
+ 3 |
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+
+ | 62 |
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+ 26 |
+ 2 |
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+ 12 |
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+
+ | 63 |
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+ 29 |
+ 2 |
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+ C |
+ 22 |
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+
+
+ | 64 |
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+ 80 |
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+ 28 |
+ 2 |
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+ C |
+ 13 |
+ 7 |
+
+
+ | 65 |
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+ 70 |
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+ 26 |
+ 2 |
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+ F |
+ 4 |
+ 2 |
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+
+ | 66 |
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+ 67 |
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+ 25 |
+ 2 |
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+ E |
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+ 12 |
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+
+ | 67 |
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+ 75 |
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+ 27 |
+ 2 |
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+ B |
+ 23 |
+ 11 |
+
+
+ | 68 |
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+ 78 |
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+ 27 |
+ 2 |
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+ C |
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+
+ | 69 |
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+ 80 |
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+ 22 |
+ 2 |
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+ C |
+ 4 |
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+
+ | 70 |
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+ 81 |
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+ 22 |
+ 2 |
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+ A |
+ 22 |
+ 10 |
+
+
+ | 71 |
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+ 76 |
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+ 25 |
+ 2 |
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+ E |
+ 15 |
+ 8 |
+
+
+ | 72 |
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+ 76 |
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+ 25 |
+ 2 |
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+ C |
+ 7 |
+ 4 |
+
+
+ | 73 |
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+ 67 |
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+ 27 |
+ 2 |
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+ F |
+ 2 |
+ 1 |
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+
+ | 74 |
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+ 67 |
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+ 27 |
+ 2 |
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+ E |
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+ 12 |
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+
+ | 75 |
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+ 81 |
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+ 28 |
+ 2 |
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+ E |
+ 20 |
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+
+
+ | 76 |
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+ 27 |
+ 2 |
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+ E |
+ 3 |
+ 2 |
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+
+ | 77 |
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+ 78 |
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+ 26 |
+ 2 |
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+ C |
+ 16 |
+ 8 |
+
+
+ | 78 |
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+ 56 |
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+ 26 |
+ 2 |
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+ D |
+ 11 |
+ 6 |
+
+
+ | 79 |
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+ 66 |
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+ 27 |
+ 2 |
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+ F |
+ 23 |
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+
+
+ | 80 |
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+ 70 |
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+ 27 |
+ 2 |
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+ B |
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+ 12 |
+
+
+ | 81 |
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+ 84 |
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+ 26 |
+ 2 |
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+ B |
+ 16 |
+ 8 |
+
+
+ | 82 |
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+ 72 |
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+ 26 |
+ 2 |
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+ C |
+ 10 |
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+
+
+ | 83 |
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+ 25 |
+ 2 |
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+ B |
+ 11 |
+ 6 |
+
+
+ | 84 |
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+ LXS46 |
+ 70 |
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+ 25 |
+ 2 |
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+ D |
+ 7 |
+ 4 |
+
+
+ | 85 |
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+ 72 |
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+ 27 |
+ 2 |
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+ F |
+ 15 |
+ 8 |
+
+
+ | 86 |
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+ 72 |
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+ 27 |
+ 2 |
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+ C |
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+ 12 |
+
+
+ | 87 |
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+ 72 |
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+ 25 |
+ 2 |
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+ C |
+ 14 |
+ 7 |
+
+
+ | 88 |
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+ 25 |
+ 2 |
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+ C |
+ 3 |
+ 2 |
+
+
+ | 89 |
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+ 68 |
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+ 28 |
+ 2 |
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+ A |
+ 6 |
+ 3 |
+
+
+ | 90 |
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+ 80 |
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+ 27 |
+ 2 |
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+ 20 |
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+
+
+ | 91 |
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+ 2 |
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+
+
+ | 92 |
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+ 2 |
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+ A |
+ 8 |
+ 4 |
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+
+ | 93 |
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+ 2 |
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+ 7 |
+ 4 |
+
+
+ | 94 |
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+ 26 |
+ 2 |
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+
+ | 95 |
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+ 2 |
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+ 22 |
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+
+
+ | 96 |
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+ 2 |
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+ 3 |
+
+
+ | 97 |
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+ 2 |
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+ D |
+ 8 |
+ 4 |
+
+
+ | 98 |
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+ 2 |
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+
+
+ | 99 |
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+ 25 |
+ 2 |
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+ C |
+ 12 |
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+
+
+ | 100 |
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+ 26 |
+ 2 |
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+ 13 |
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+
+
+ | 101 |
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+ 2 |
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+ 3 |
+
+
+ | 102 |
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+ 2 |
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+
+
+ | 103 |
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+ 2 |
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+
+
+ | 104 |
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+ 2 |
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+
+ | 105 |
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+ 2 |
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+
+ | 106 |
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+ 2 |
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+
+
+ | 107 |
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+ 2 |
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+
+
+ | 108 |
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+ 2 |
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+
+ | 109 |
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+ 2 |
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+
+
+ | 110 |
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+ 2 |
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+
+
+ | 111 |
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+ 2 |
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+
+
+ | 112 |
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+ 2 |
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+ 6 |
+
+
+ | 113 |
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+ 2 |
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+ 1 |
+ 1 |
+
+
+ | 114 |
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+ 2 |
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+
+
+ | 115 |
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+ 2 |
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+
+
+ | 116 |
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+ 2 |
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+
+
+ | 117 |
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+ 2 |
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+
+
+ | 118 |
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+ 2 |
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+
+
+ | 119 |
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+ 2 |
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+
+
+ | 120 |
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+ 2 |
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+
+
+ | 121 |
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+ 2 |
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+ 4 |
+ 2 |
+
+
+ | 122 |
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+ 2 |
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+ 6 |
+
+
+ | 123 |
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+ 2 |
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+
+
+ | 124 |
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+ 2 |
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+ 1 |
+ 1 |
+
+
+ | 125 |
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+ 2 |
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+
+
+ | 126 |
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+ 2 |
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+
+
+ | 127 |
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+ 2 |
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+ 14 |
+ 7 |
+
+
+ | 128 |
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+ 26 |
+ 2 |
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+ D |
+ 14 |
+ 7 |
+
+
+ | 129 |
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+ 28 |
+ 2 |
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+ C |
+ 6 |
+ 3 |
+
+
+ | 130 |
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+ 2 |
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+
+
+ | 131 |
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+ 2 |
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+ A |
+ 14 |
+ 7 |
+
+
+ | 132 |
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+ 25 |
+ 2 |
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+ 14 |
+ 7 |
+
+
+ | 133 |
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+ 26 |
+ 2 |
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+ 2 |
+ 1 |
+
+
+ | 134 |
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+ 2 |
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+
+
+ | 135 |
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+ 2 |
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+
+
+ | 136 |
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+ 2 |
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+ 6 |
+ 3 |
+
+
+ | 137 |
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+ 2 |
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+ 6 |
+ 3 |
+
+
+ | 138 |
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+ 2 |
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+
+
+ | 139 |
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+ 2 |
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+ 11 |
+
+
+ | 140 |
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+ 27 |
+ 2 |
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+ A |
+ 5 |
+ 3 |
+
+
+ | 141 |
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+ 26 |
+ 2 |
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+ 2 |
+ 1 |
+
+
+ | 142 |
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+ 25 |
+ 2 |
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+ 15 |
+ 8 |
+
+
+ | 143 |
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+ 26 |
+ 2 |
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+ 10 |
+ 5 |
+
+
+ | 144 |
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+ 68 |
+ M |
+ 27 |
+ 2 |
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+ D |
+ 1 |
+ 1 |
+
+
+ | 145 |
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+ 25 |
+ 2 |
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+ 11 |
+
+
+ | 146 |
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+ 25 |
+ 2 |
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+ A |
+ 12 |
+ 6 |
+
+
+ | 147 |
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+ 66 |
+ F |
+ 23 |
+ 2 |
+ 1523516015 |
+ E |
+ 10 |
+ 5 |
+
+
+ | 148 |
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+ LXS92 |
+ 87 |
+ M |
+ 23 |
+ 2 |
+ 1523516032 |
+ A |
+ 7 |
+ 4 |
+
+
+ | 149 |
+ R1624H2 |
+ LXS93 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516032 |
+ B |
+ 7 |
+ 4 |
+
+
+ | 150 |
+ R1815H2 |
+ LXS93 |
+ 61 |
+ M |
+ 26 |
+ 2 |
+ 1523516009 |
+ B |
+ 12 |
+ 6 |
+
+
+ | 151 |
+ R1991H2 |
+ LXS94 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224036 |
+ C |
+ 17 |
+ 9 |
+
+
+ | 152 |
+ R2002H2 |
+ LXS94 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1562224049 |
+ B |
+ 18 |
+ 9 |
+
+
+ | 153 |
+ R1996H2 |
+ LXS96 |
+ 75 |
+ F |
+ 23 |
+ 2 |
+ 1562224036 |
+ F |
+ 17 |
+ 9 |
+
+
+ | 154 |
+ R1772H2 |
+ LXS96 |
+ 63 |
+ M |
+ 23 |
+ 2 |
+ 1523516007 |
+ C |
+ 11 |
+ 6 |
+
+
+ | 155 |
+ R2759H2 |
+ LXS97 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224060 |
+ B |
+ 22 |
+ 10 |
+
+
+ | 156 |
+ R2739H2 |
+ LXS97 |
+ 79 |
+ M |
+ 26 |
+ 2 |
+ 1523516028 |
+ F |
+ 3 |
+ 2 |
+
+
+ | 157 |
+ R2149H2 |
+ LXS98 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516033 |
+ C |
+ 8 |
+ 4 |
+
+
+ | 158 |
+ R1888H2 |
+ LXS98 |
+ 76 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ B |
+ 26 |
+ 12 |
+
+
+ | 159 |
+ R1644H2 |
+ LXS99 |
+ 79 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ B |
+ 10 |
+ 5 |
+
+
+ | 160 |
+ R2145H2 |
+ LXS99 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ F |
+ 19 |
+ 9 |
+
+
+
+ |
+
+
+
+
+
+ |
+
+
+ |
+ Downloading all data:
+
+ All data links (right-most column above) will be available as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
+ |
+
+
+
diff --git a/general/datasets/Illum_lxs_hipp_rsn0807/citation.rtf b/general/datasets/Illum_lxs_hipp_rsn0807/citation.rtf
new file mode 100644
index 0000000..29fd952
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn0807/citation.rtf
@@ -0,0 +1,3 @@
+Downloading all data:
+
+All data links (right-most column above) will be available as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
diff --git a/general/datasets/Illum_lxs_hipp_rsn0807/contributors.rtf b/general/datasets/Illum_lxs_hipp_rsn0807/contributors.rtf
new file mode 100644
index 0000000..775c0ee
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn0807/contributors.rtf
@@ -0,0 +1,5 @@
+About this text file:
+
+INFO file prepared by Xusheng Wang, Oct 24, 2007.
+
+Data set uploaded by Arthur Centeno, Aug 30, 2007.
diff --git a/general/datasets/Illum_lxs_hipp_rsn0807/experiment-design.rtf b/general/datasets/Illum_lxs_hipp_rsn0807/experiment-design.rtf
new file mode 100644
index 0000000..f477cb7
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn0807/experiment-design.rtf
@@ -0,0 +1 @@
+Experimental Design and Batch Structure: This data set consists arrays processed in 13 groups over a five month period (July 2006 to Dec 2006). Most groups consisted of 12 samples. All arrays in this data set were processed using a single protocol by a single operator, Feng Yiao. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between July 28 and Dec 21, 2006. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Illum_lxs_hipp_rsn0807/notes.rtf b/general/datasets/Illum_lxs_hipp_rsn0807/notes.rtf
new file mode 100644
index 0000000..938409b
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn0807/notes.rtf
@@ -0,0 +1,3 @@
+ANNOTATION: In spring of 2007, Robert W. Williams and Hongqiang Li reannotated the Illumina Mouse-6 array content. This new annotation is now incorporated into GeneNetwork. For 46166 probes on the Mouse 6 array platform (including control probes) we have identified 35975 NCBI Entrez Gene IDs; 26481 matched human Gene IDs; 23899 matched rat Gene IDs; 26883 NCBI HomoloGene IDs; and 12791 OMIM IDs.
+
+Position data for the 50-mer Illumina Mouse-6 array were initially downloaded from Sanger at http://www.sanger.ac.uk/Users/avc/Illumina/Mouse-6_V1.gff.gz but we then updated all positions by BLAT analysis from mm6 positions to mm8 positions (Hongqiang Li).
diff --git a/general/datasets/Illum_lxs_hipp_rsn0807/platform.rtf b/general/datasets/Illum_lxs_hipp_rsn0807/platform.rtf
new file mode 100644
index 0000000..2ac899d
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn0807/platform.rtf
@@ -0,0 +1,5 @@
+About the array platform:
+
+Illumina Sentrix Mouse-6 BeadArray Platform: The Mouse6 array consists of 46,116 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+Dunning M, Smith M, Thorne N, Tavare S (2006) beadarray: An R package to analyse Illumina BeadArrays. R News (the Newsletter of the P Project) 6:17-23. (see pages 17-23 of http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf).
diff --git a/general/datasets/Illum_lxs_hipp_rsn0807/processing.rtf b/general/datasets/Illum_lxs_hipp_rsn0807/processing.rtf
new file mode 100644
index 0000000..c3d0555
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn0807/processing.rtf
@@ -0,0 +1,3 @@
+About data processing:
+
+This data set uses the LOESS with Variance Stabilizing Transform (VST) and Background correction from the lumi package downloaded from Bioconductor (http://www.bioconductor.org/). For the more detailed information, please see the lumi package documentation.
diff --git a/general/datasets/Illum_lxs_hipp_rsn0807/summary.rtf b/general/datasets/Illum_lxs_hipp_rsn0807/summary.rtf
new file mode 100644
index 0000000..ebfc03f
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn0807/summary.rtf
@@ -0,0 +1,33 @@
+August 07 ILLUMINA Mouse-6 DATA SET RSN: The LXS Hippocampus Illumina Robust Spline Normalization with No Background correction data set provides estimates of mRNA expression in the hippocampus of 75 LXS recombinant inbred strains, the two parental strains, ILS/Ibg and ISS/Ibg (Inbred Long Sleep and Inbred Short Sleep strains from the Institute of Behavioral Genetics), and the two reciprocal F1 strains (ILSXISSF1, ISSXILSF1). All samples are from normal adult control animals raised in a standard laboratory environment. Subsequent data sets will provide estimates of mRNA expression following restraint stress, ethanol treatment, and stress followed by ethanol using many of the same strains (Lu Lu and colleagues).
+
+A total of 240 pooled hippocampal samples were processed using 40 Illumina Sentrix Mouse-6 v 1.0 oligomer microarray BeadArray slides. Twenty-seven Mouse-6 slides and a total of 160 samples passed stringent quality control and error checking. We should note that this is our first experience using the Illumina platform and the initial set of 13 slides were not included. This particular data set was processed using the Illumina "Robust Spline Normalization with No Background Correction" protocol. Values were log2 transformed and the current data range from 6.481 average (very low or no expression) to 24.852 (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Hippocampus Illumina (Aug 07) RSN data set, ### probes have LRS values >46.
+
+In comparison, here are the yields of QTLs with LOD>10 for other closely related data sets:
+
+
+ - 1050 for Hippocampus Illumina (Aug07) LOESS
+ - 1162 for Hippocampus Illumina (Aug07) LOESS_NB
+ - 1129 for Hippocampus Illumina (Aug07) QUANT
+ - 1176 for Hippocampus Illumina (Aug07) QUANT_NB
+ - NO DATA for Hippocampus Illumina (Aug07) RSN
+ - NO DATA for Hippocampus Illumina (Aug07) RSN_NB (THIS DATA SET)
+ - 1183 for Hippocampus Illumina (May 07) RankInv
+ - 1167 for Hippocampus Illumina (Oct06) Rank
+ - 1170 for Hippocampus Illumina (Oct06) RankInv
+
+
+The LRS achieved in the different version of the LXS Hippocampus data for probe ILM103520706 (Disabled 1; Dab1) are as follow
+
+
+ - 338.4 for Hippocampus Illumina (Aug07) LOESS
+ - 339.8 for Hippocampus Illumina (Aug07) LOESS_NB
+ - 370.2 for Hippocampus Illumina (Aug07) QUANT
+ - 363.5 for Hippocampus Illumina (Aug07) QUANT_NB
+ - 374.8 for Hippocampus Illumina (Aug07) RSN
+ - 363.0 for Hippocampus Illumina (Aug07) RSN_NB (THIS DATA SET)
+ - 360.3 for Hippocampus Illumina (May 07) RankInv
+ - 358.1 for Hippocampus Illumina (Oct06) Rank
+ - 358.8 for Hippocampus Illumina (Oct06) RankInv
+
diff --git a/general/datasets/Illum_lxs_hipp_rsn0807/tissue.rtf b/general/datasets/Illum_lxs_hipp_rsn0807/tissue.rtf
new file mode 100644
index 0000000..febccce
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn0807/tissue.rtf
@@ -0,0 +1,9 @@
+About the animals and tissue used to generate this set of data:
+
+All animals were raised at the IBG by Bennett and colleagues in an SPF facility. No cases were MHV positive. Mice were killed by cervical dislocation. Whole brain dissections were performed at the IBG by Bennett and colleagues and shipped in RNAlater to Lu Lu and colleagues at UTHSC. Most hippocampal dissections (all were bilateral) were performed by Zhiping Jia. Cerebella, olfactory bulbs, and brain stems were also dissected and stored at -80 deg C using further use. Hippocampal samples are very close to complete (see Lu et al., 2001 but probably include variable amounts of fimbria and choroid plexus (see expression of transthyretin, Ttr, as a marker of choroid plexus).
+
+A pool of dissected tissue from four hippocampi taken from two naive adults of the same strain, sex, and age was collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at UTHSC by Zhiping Jia.
+
+All animals used in this study were between 53 and 90 days of age (average of 72 days; see Table 1 below).
+
+
diff --git a/general/datasets/Illum_lxs_hipp_rsn_nb0807/acknowledgment.rtf b/general/datasets/Illum_lxs_hipp_rsn_nb0807/acknowledgment.rtf
new file mode 100644
index 0000000..d8f3e9a
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn_nb0807/acknowledgment.rtf
@@ -0,0 +1,3 @@
+Data source acknowledgment:
+
+Data were generated with funds to Lu Lu, Beth Bennett, Mike Miles, Melloni Cook from INIA. · Lu Lu, M.D. Grant Support: NIH U01AA13499, U24AA13513 (Lu Lu, PI)
diff --git a/general/datasets/Illum_lxs_hipp_rsn_nb0807/cases.rtf b/general/datasets/Illum_lxs_hipp_rsn_nb0807/cases.rtf
new file mode 100644
index 0000000..efa4371
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn_nb0807/cases.rtf
@@ -0,0 +1,2140 @@
+Quality Control on Sex Labels: Sex of the samples was validated using sex-specific probe set.
+
+
+
+
+ |
+ Legend: We evaluated whether or not the sex of samples were labeled correctly by measuring the expression of Xist using probe ILM106520068. In this bar chart the expression of Xist is very low in LXS114 and has a low error term. This is because both arrays are male samples rather than 1 male and 1 female sample.
+
+
+
+ Data Table 1:
+
+
+ This table lists all arrays by order of strain (index) and includes data on tube ID, strain, age, sex, F generation number, number of animals in each sample pool (pool size), slide ID, slide position (A through F), scan date, and scan batch.
+
+
+
+
+
+
+
+
+
+ | index |
+ tube ID |
+ strain |
+ age |
+ sex |
+ gener-
+ ation |
+ pool
+ size |
+ slide
+ ID |
+ slide
+ position |
+ batch
+ by slide |
+ scan
+ batch |
+
+
+ | 1 |
+ R2851H2 |
+ ILS |
+ 77 |
+ F |
+ >100 |
+ 4 |
+ 1523516003 |
+ B |
+ 1 |
+ 1 |
+
+
+ | 2 |
+ R0595H2 |
+ ILS |
+ 71 |
+ F |
+ >100 |
+ 2 |
+ 1523516030 |
+ B |
+ 4 |
+ 2 |
+
+
+ | 3 |
+ R2874H2 |
+ ILS |
+ 78 |
+ M |
+ >100 |
+ 4 |
+ 1523516011 |
+ B |
+ 2 |
+ 1 |
+
+
+ | 4 |
+ R0585H2 |
+ ILS |
+ 65 |
+ M |
+ >100 |
+ 2 |
+ 1523516028 |
+ A |
+ 3 |
+ 2 |
+
+
+ | 5 |
+ R3281H1 |
+ ILSXISSF1 |
+ 90 |
+ F |
+ NA |
+ 3 |
+ 1562224029 |
+ A |
+ 28 |
+ 13 |
+
+
+ | 6 |
+ R2857H2 |
+ ISS |
+ 75 |
+ F |
+ >100 |
+ 4 |
+ 1523516011 |
+ A |
+ 2 |
+ 1 |
+
+
+ | 7 |
+ R0589H2 |
+ ISS |
+ 73 |
+ F |
+ >100 |
+ 2 |
+ 1523516028 |
+ B |
+ 3 |
+ 2 |
+
+
+ | 8 |
+ R2955H2 |
+ ISS |
+ 53 |
+ M |
+ >100 |
+ 3 |
+ 1523516003 |
+ A |
+ 1 |
+ 1 |
+
+
+ | 9 |
+ R0578H2 |
+ ISS |
+ 67 |
+ M |
+ >100 |
+ 2 |
+ 1523516030 |
+ A |
+ 4 |
+ 2 |
+
+
+ | 10 |
+ R3282H1 |
+ ISSXILSF1 |
+ 97 |
+ M |
+ NA |
+ 3 |
+ 1562224029 |
+ B |
+ 28 |
+ 13 |
+
+
+ | 11 |
+ R2013H2 |
+ LXS10 |
+ 84 |
+ F |
+ 27 |
+ 2 |
+ 1562224049 |
+ E |
+ 18 |
+ 9 |
+
+
+ | 12 |
+ R1993H2 |
+ LXS10 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1562224036 |
+ E |
+ 17 |
+ 9 |
+
+
+ | 13 |
+ R1997H2 |
+ LXS100 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ A |
+ 18 |
+ 9 |
+
+
+ | 14 |
+ R1983H2 |
+ LXS100 |
+ 77 |
+ M |
+ 25 |
+ 2 |
+ 1562224047 |
+ F |
+ 16 |
+ 8 |
+
+
+ | 15 |
+ R2083H2 |
+ LXS101 |
+ 85 |
+ F |
+ 28 |
+ 2 |
+ 1562224050 |
+ B |
+ 19 |
+ 9 |
+
+
+ | 16 |
+ R2084H2 |
+ LXS101 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224050 |
+ C |
+ 19 |
+ 9 |
+
+
+ | 17 |
+ R2186H2 |
+ LXS102 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1523516001 |
+ C |
+ 9 |
+ 5 |
+
+
+ | 18 |
+ R2187H2 |
+ LXS102 |
+ 73 |
+ M |
+ 29 |
+ 2 |
+ 1562224053 |
+ C |
+ 20 |
+ 10 |
+
+
+ | 19 |
+ R2809H2 |
+ LXS103 |
+ 72 |
+ F |
+ 26 |
+ 2 |
+ 1562224034 |
+ C |
+ 23 |
+ 11 |
+
+
+ | 20 |
+ R2854H1 |
+ LXS103 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516006 |
+ D |
+ 6 |
+ 3 |
+
+
+ | 21 |
+ R2735H2 |
+ LXS107 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516028 |
+ D |
+ 3 |
+ 2 |
+
+
+ | 22 |
+ R2738H2 |
+ LXS107 |
+ 78 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ C |
+ 21 |
+ 10 |
+
+
+ | 23 |
+ R2840H2 |
+ LXS110 |
+ 67 |
+ F |
+ 25 |
+ 2 |
+ 1562224037 |
+ D |
+ 24 |
+ 11 |
+
+
+ | 24 |
+ R2157H2 |
+ LXS110 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516033 |
+ E |
+ 8 |
+ 4 |
+
+
+ | 25 |
+ R2172H2 |
+ LXS112 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ B |
+ 9 |
+ 5 |
+
+
+ | 26 |
+ R2841H2 |
+ LXS112 |
+ 84 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ D |
+ 27 |
+ 12 |
+
+
+ | 27 |
+ R2188H2 |
+ LXS114 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224053 |
+ D |
+ 20 |
+ 10 |
+
+
+ | 28 |
+ R2204H2 |
+ LXS114 |
+ 72 |
+ M |
+ 28 |
+ 2 |
+ 1523516001 |
+ D |
+ 9 |
+ 5 |
+
+
+ | 29 |
+ R2168H2 |
+ LXS115 |
+ 80 |
+ F |
+ 27 |
+ 2 |
+ 1523516001 |
+ A |
+ 9 |
+ 5 |
+
+
+ | 30 |
+ R2085H2 |
+ LXS115 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ D |
+ 19 |
+ 9 |
+
+
+ | 31 |
+ R2811H2 |
+ LXS117 |
+ 72 |
+ F |
+ 28 |
+ 2 |
+ 1562224034 |
+ D |
+ 23 |
+ 11 |
+
+
+ | 32 |
+ R2212H2 |
+ LXS117 |
+ 74 |
+ M |
+ 27 |
+ 2 |
+ 1523516001 |
+ E |
+ 9 |
+ 5 |
+
+
+ | 33 |
+ R1992H2 |
+ LXS122 |
+ 86 |
+ F |
+ 26 |
+ 2 |
+ 1562224036 |
+ D |
+ 17 |
+ 9 |
+
+
+ | 34 |
+ R2219H2 |
+ LXS122 |
+ 72 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ A |
+ 21 |
+ 10 |
+
+
+ | 35 |
+ R2876H2 |
+ LXS123 |
+ 87 |
+ F |
+ 28 |
+ 2 |
+ 1562224038 |
+ C |
+ 25 |
+ 11 |
+
+
+ | 36 |
+ R2832H1 |
+ LXS123 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1523516011 |
+ E |
+ 2 |
+ 1 |
+
+
+ | 37 |
+ R2872H1 |
+ LXS124 |
+ 83 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ E |
+ 6 |
+ 3 |
+
+
+ | 38 |
+ R2871H2 |
+ LXS124 |
+ 85 |
+ M |
+ 28 |
+ 2 |
+ 1562224042 |
+ F |
+ 27 |
+ 12 |
+
+
+ | 39 |
+ R1909H2 |
+ LXS13 |
+ 79 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ D |
+ 13 |
+ 7 |
+
+
+ | 40 |
+ R1901H2 |
+ LXS13 |
+ 81 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ D |
+ 26 |
+ 12 |
+
+
+ | 41 |
+ R2023H2 |
+ LXS14 |
+ 86 |
+ F |
+ 25 |
+ 2 |
+ 1562224050 |
+ A |
+ 19 |
+ 9 |
+
+
+ | 42 |
+ R1612H2 |
+ LXS14 |
+ 85 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ A |
+ 10 |
+ 5 |
+
+
+ | 43 |
+ R1936H2 |
+ LXS16 |
+ 81 |
+ F |
+ 25 |
+ 2 |
+ 1523516024 |
+ E |
+ 13 |
+ 7 |
+
+
+ | 44 |
+ R1912H2 |
+ LXS16 |
+ 81 |
+ M |
+ 25 |
+ 2 |
+ 1523516033 |
+ B |
+ 8 |
+ 4 |
+
+
+ | 45 |
+ R1961H2 |
+ LXS19 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516029 |
+ F |
+ 14 |
+ 7 |
+
+
+ | 46 |
+ R1904H2 |
+ LXS19 |
+ 66 |
+ M |
+ 26 |
+ 2 |
+ 1523516024 |
+ B |
+ 13 |
+ 7 |
+
+
+ | 47 |
+ R1883H2 |
+ LXS2 |
+ 71 |
+ F |
+ 27 |
+ 2 |
+ 1523516009 |
+ F |
+ 12 |
+ 6 |
+
+
+ | 48 |
+ R2753H2 |
+ LXS2 |
+ 74 |
+ M |
+ 28 |
+ 2 |
+ 1523516030 |
+ E |
+ 4 |
+ 2 |
+
+
+ | 49 |
+ R1729H2 |
+ LXS22 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516032 |
+ E |
+ 7 |
+ 4 |
+
+
+ | 50 |
+ R2743H2 |
+ LXS22 |
+ 79 |
+ M |
+ 27 |
+ 2 |
+ 1562224054 |
+ D |
+ 21 |
+ 10 |
+
+
+ | 51 |
+ R1966H2 |
+ LXS23 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224032 |
+ D |
+ 15 |
+ 8 |
+
+
+ | 52 |
+ R1971H2 |
+ LXS23 |
+ 73 |
+ M |
+ 26 |
+ 2 |
+ 1562224047 |
+ A |
+ 16 |
+ 8 |
+
+
+ | 53 |
+ R2795H2 |
+ LXS24 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516003 |
+ C |
+ 1 |
+ 1 |
+
+
+ | 54 |
+ R1755H2 |
+ LXS24 |
+ 56 |
+ M |
+ 25 |
+ 2 |
+ 1523516007 |
+ A |
+ 11 |
+ 6 |
+
+
+ | 55 |
+ R1986H2 |
+ LXS25 |
+ 75 |
+ F |
+ 27 |
+ 2 |
+ 1562224036 |
+ A |
+ 17 |
+ 9 |
+
+
+ | 56 |
+ R2006H2 |
+ LXS25 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1562224049 |
+ C |
+ 18 |
+ 9 |
+
+
+ | 57 |
+ R2014H2 |
+ LXS26 |
+ 82 |
+ F |
+ 25 |
+ 2 |
+ 1562224049 |
+ F |
+ 18 |
+ 9 |
+
+
+ | 58 |
+ R2009H2 |
+ LXS26 |
+ 82 |
+ M |
+ 26 |
+ 2 |
+ 1562224049 |
+ D |
+ 18 |
+ 9 |
+
+
+ | 59 |
+ R2824H1 |
+ LXS28 |
+ 67 |
+ F |
+ 28 |
+ 2 |
+ 1562224042 |
+ A |
+ 27 |
+ 12 |
+
+
+ | 60 |
+ R1753H1 |
+ LXS28 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1562224041 |
+ F |
+ 26 |
+ 12 |
+
+
+ | 61 |
+ R2765H2 |
+ LXS3 |
+ 63 |
+ F |
+ 27 |
+ 2 |
+ 1523516005 |
+ B |
+ 5 |
+ 3 |
+
+
+ | 62 |
+ R1898H2 |
+ LXS3 |
+ 81 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ C |
+ 26 |
+ 12 |
+
+
+ | 63 |
+ R2764H2 |
+ LXS31 |
+ 73 |
+ F |
+ 29 |
+ 2 |
+ 1562224060 |
+ C |
+ 22 |
+ 10 |
+
+
+ | 64 |
+ R1908H2 |
+ LXS31 |
+ 80 |
+ M |
+ 28 |
+ 2 |
+ 1523516024 |
+ C |
+ 13 |
+ 7 |
+
+
+ | 65 |
+ R2758H2 |
+ LXS32 |
+ 70 |
+ F |
+ 26 |
+ 2 |
+ 1523516030 |
+ F |
+ 4 |
+ 2 |
+
+
+ | 66 |
+ R1743H1 |
+ LXS32 |
+ 67 |
+ M |
+ 25 |
+ 2 |
+ 1562224041 |
+ E |
+ 26 |
+ 12 |
+
+
+ | 67 |
+ R2794H2 |
+ LXS34 |
+ 75 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ B |
+ 23 |
+ 11 |
+
+
+ | 68 |
+ R2870H2 |
+ LXS34 |
+ 78 |
+ F |
+ 27 |
+ 2 |
+ 1562224029 |
+ C |
+ 28 |
+ 13 |
+
+
+ | 69 |
+ R2746H2 |
+ LXS35 |
+ 80 |
+ F |
+ 22 |
+ 2 |
+ 1523516030 |
+ C |
+ 4 |
+ 2 |
+
+
+ | 70 |
+ R2747H2 |
+ LXS35 |
+ 81 |
+ M |
+ 22 |
+ 2 |
+ 1562224060 |
+ A |
+ 22 |
+ 10 |
+
+
+ | 71 |
+ R1968H2 |
+ LXS36 |
+ 76 |
+ F |
+ 25 |
+ 2 |
+ 1562224032 |
+ E |
+ 15 |
+ 8 |
+
+
+ | 72 |
+ R1640H2 |
+ LXS36 |
+ 76 |
+ M |
+ 25 |
+ 2 |
+ 1523516032 |
+ C |
+ 7 |
+ 4 |
+
+
+ | 73 |
+ R2835H1 |
+ LXS38 |
+ 67 |
+ F |
+ 27 |
+ 2 |
+ 1523516011 |
+ F |
+ 2 |
+ 1 |
+
+
+ | 74 |
+ R2842H2 |
+ LXS38 |
+ 67 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ E |
+ 27 |
+ 12 |
+
+
+ | 75 |
+ R2210H2 |
+ LXS39 |
+ 81 |
+ F |
+ 28 |
+ 2 |
+ 1562224053 |
+ E |
+ 20 |
+ 10 |
+
+
+ | 76 |
+ R2736H2 |
+ LXS39 |
+ 75 |
+ M |
+ 27 |
+ 2 |
+ 1523516028 |
+ E |
+ 3 |
+ 2 |
+
+
+ | 77 |
+ R1978H2 |
+ LXS41 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1562224047 |
+ C |
+ 16 |
+ 8 |
+
+
+ | 78 |
+ R1783H2 |
+ LXS41 |
+ 56 |
+ M |
+ 26 |
+ 2 |
+ 1523516007 |
+ D |
+ 11 |
+ 6 |
+
+
+ | 79 |
+ R2822H2 |
+ LXS42 |
+ 66 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ F |
+ 23 |
+ 11 |
+
+
+ | 80 |
+ R2769H2 |
+ LXS42 |
+ 70 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ B |
+ 27 |
+ 12 |
+
+
+ | 81 |
+ R1974H2 |
+ LXS43 |
+ 84 |
+ F |
+ 26 |
+ 2 |
+ 1562224047 |
+ B |
+ 16 |
+ 8 |
+
+
+ | 82 |
+ R1733H2 |
+ LXS43 |
+ 72 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ C |
+ 10 |
+ 5 |
+
+
+ | 83 |
+ R1756H2 |
+ LXS46 |
+ 56 |
+ F |
+ 25 |
+ 2 |
+ 1523516007 |
+ B |
+ 11 |
+ 6 |
+
+
+ | 84 |
+ R1727H2 |
+ LXS46 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1523516032 |
+ D |
+ 7 |
+ 4 |
+
+
+ | 85 |
+ R1970H2 |
+ LXS48 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1562224032 |
+ F |
+ 15 |
+ 8 |
+
+
+ | 86 |
+ R1981H2 |
+ LXS48 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1562224042 |
+ C |
+ 27 |
+ 12 |
+
+
+ | 87 |
+ R1957H2 |
+ LXS49 |
+ 72 |
+ F |
+ 25 |
+ 2 |
+ 1523516029 |
+ C |
+ 14 |
+ 7 |
+
+
+ | 88 |
+ R2259H2 |
+ LXS49 |
+ 72 |
+ M |
+ 25 |
+ 2 |
+ 1523516028 |
+ C |
+ 3 |
+ 2 |
+
+
+ | 89 |
+ R2836H1 |
+ LXS5 |
+ 68 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ A |
+ 6 |
+ 3 |
+
+
+ | 90 |
+ R2213H2 |
+ LXS5 |
+ 80 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ F |
+ 20 |
+ 10 |
+
+
+ | 91 |
+ R2791H2 |
+ LXS50 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1562224034 |
+ A |
+ 23 |
+ 11 |
+
+
+ | 92 |
+ R1789H2 |
+ LXS50 |
+ 57 |
+ M |
+ 26 |
+ 2 |
+ 1523516033 |
+ A |
+ 8 |
+ 4 |
+
+
+ | 93 |
+ R1740H2 |
+ LXS51 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1523516032 |
+ F |
+ 7 |
+ 4 |
+
+
+ | 94 |
+ R1734H2 |
+ LXS51 |
+ 68 |
+ M |
+ 26 |
+ 2 |
+ 1523516015 |
+ D |
+ 10 |
+ 5 |
+
+
+ | 95 |
+ R2786H2 |
+ LXS52 |
+ 61 |
+ F |
+ 27 |
+ 2 |
+ 1562224060 |
+ D |
+ 22 |
+ 10 |
+
+
+ | 96 |
+ R2768H2 |
+ LXS52 |
+ 61 |
+ M |
+ 27 |
+ 2 |
+ 1523516005 |
+ C |
+ 5 |
+ 3 |
+
+
+ | 97 |
+ R2154H2 |
+ LXS54 |
+ 70 |
+ F |
+ 27 |
+ 2 |
+ 1523516033 |
+ D |
+ 8 |
+ 4 |
+
+
+ | 98 |
+ R2155H2 |
+ LXS54 |
+ 70 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ A |
+ 20 |
+ 10 |
+
+
+ | 99 |
+ R1821H2 |
+ LXS55 |
+ 77 |
+ F |
+ 25 |
+ 2 |
+ 1523516009 |
+ C |
+ 12 |
+ 6 |
+
+
+ | 100 |
+ R1951H2 |
+ LXS55 |
+ 74 |
+ M |
+ 26 |
+ 2 |
+ 1523516024 |
+ F |
+ 13 |
+ 7 |
+
+
+ | 101 |
+ R2789H2 |
+ LXS56 |
+ 71 |
+ F |
+ 25 |
+ 2 |
+ 1523516005 |
+ F |
+ 5 |
+ 3 |
+
+
+ | 102 |
+ R2788H2 |
+ LXS56 |
+ 71 |
+ M |
+ 25 |
+ 2 |
+ 1562224060 |
+ F |
+ 22 |
+ 10 |
+
+
+ | 103 |
+ R2787H2 |
+ LXS59 |
+ 66 |
+ F |
+ 29 |
+ 2 |
+ 1562224060 |
+ E |
+ 22 |
+ 10 |
+
+
+ | 104 |
+ R2785H2 |
+ LXS59 |
+ 62 |
+ M |
+ 29 |
+ 2 |
+ 1523516005 |
+ E |
+ 5 |
+ 3 |
+
+
+ | 105 |
+ R1791H2 |
+ LXS60 |
+ 58 |
+ F |
+ 27 |
+ 2 |
+ 1562224038 |
+ D |
+ 25 |
+ 11 |
+
+
+ | 106 |
+ R1792H2 |
+ LXS60 |
+ 64 |
+ M |
+ 27 |
+ 2 |
+ 1523516007 |
+ E |
+ 11 |
+ 6 |
+
+
+ | 107 |
+ R1796H2 |
+ LXS62 |
+ 58 |
+ F |
+ 27 |
+ 2 |
+ 1523516007 |
+ F |
+ 11 |
+ 6 |
+
+
+ | 108 |
+ R1797H2 |
+ LXS62 |
+ 58 |
+ M |
+ 27 |
+ 2 |
+ 1562224038 |
+ E |
+ 25 |
+ 11 |
+
+
+ | 109 |
+ R2220H2 |
+ LXS64 |
+ 71 |
+ F |
+ 28 |
+ 2 |
+ 1523516001 |
+ F |
+ 9 |
+ 5 |
+
+
+ | 110 |
+ R2221H2 |
+ LXS64 |
+ 71 |
+ M |
+ 28 |
+ 2 |
+ 1562224054 |
+ B |
+ 21 |
+ 10 |
+
+
+ | 111 |
+ R1989H2 |
+ LXS66 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224036 |
+ B |
+ 17 |
+ 9 |
+
+
+ | 112 |
+ R1843H2 |
+ LXS66 |
+ 78 |
+ M |
+ 27 |
+ 2 |
+ 1523516009 |
+ E |
+ 12 |
+ 6 |
+
+
+ | 113 |
+ R2820H2 |
+ LXS68 |
+ 67 |
+ F |
+ 29 |
+ 2 |
+ 1523516003 |
+ E |
+ 1 |
+ 1 |
+
+
+ | 114 |
+ R2819H2 |
+ LXS68 |
+ 67 |
+ M |
+ 29 |
+ 2 |
+ 1562224034 |
+ E |
+ 23 |
+ 11 |
+
+
+ | 115 |
+ R1963H2 |
+ LXS7 |
+ 78 |
+ F |
+ 28 |
+ 2 |
+ 1562224032 |
+ B |
+ 15 |
+ 8 |
+
+
+ | 116 |
+ R1964H2 |
+ LXS7 |
+ 78 |
+ M |
+ 28 |
+ 2 |
+ 1562224032 |
+ C |
+ 15 |
+ 8 |
+
+
+ | 117 |
+ R2166H2 |
+ LXS70 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1523516033 |
+ F |
+ 8 |
+ 4 |
+
+
+ | 118 |
+ R2745H2 |
+ LXS70 |
+ 71 |
+ M |
+ 28 |
+ 2 |
+ 1562224054 |
+ F |
+ 21 |
+ 10 |
+
+
+ | 119 |
+ R2848H2 |
+ LXS72 |
+ 72 |
+ F |
+ 27 |
+ 2 |
+ 1562224038 |
+ A |
+ 25 |
+ 11 |
+
+
+ | 120 |
+ R1902H2 |
+ LXS72 |
+ 66 |
+ M |
+ 27 |
+ 2 |
+ 1523516024 |
+ A |
+ 13 |
+ 7 |
+
+
+ | 121 |
+ R2750H2 |
+ LXS73 |
+ 81 |
+ F |
+ 25 |
+ 2 |
+ 1523516030 |
+ D |
+ 4 |
+ 2 |
+
+
+ | 122 |
+ R1835H2 |
+ LXS73 |
+ 90 |
+ M |
+ 24 |
+ 2 |
+ 1523516009 |
+ D |
+ 12 |
+ 6 |
+
+
+ | 123 |
+ R1979H2 |
+ LXS75 |
+ 59 |
+ F |
+ 27 |
+ 2 |
+ 1562224047 |
+ D |
+ 16 |
+ 8 |
+
+
+ | 124 |
+ R2826H2 |
+ LXS75 |
+ 72 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ F |
+ 1 |
+ 1 |
+
+
+ | 125 |
+ R2142H2 |
+ LXS76 |
+ 77 |
+ F |
+ 26 |
+ 2 |
+ 1562224050 |
+ E |
+ 19 |
+ 9 |
+
+
+ | 126 |
+ R1884H2 |
+ LXS76 |
+ 85 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ A |
+ 26 |
+ 12 |
+
+
+ | 127 |
+ R1959H2 |
+ LXS78 |
+ 69 |
+ F |
+ 26 |
+ 2 |
+ 1523516029 |
+ E |
+ 14 |
+ 7 |
+
+
+ | 128 |
+ R1958H2 |
+ LXS78 |
+ 69 |
+ M |
+ 26 |
+ 2 |
+ 1523516029 |
+ D |
+ 14 |
+ 7 |
+
+
+ | 129 |
+ R2845H1 |
+ LXS8 |
+ 70 |
+ F |
+ 28 |
+ 2 |
+ 1523516006 |
+ C |
+ 6 |
+ 3 |
+
+
+ | 130 |
+ R2156H2 |
+ LXS8 |
+ 76 |
+ M |
+ 27 |
+ 2 |
+ 1562224053 |
+ B |
+ 20 |
+ 10 |
+
+
+ | 131 |
+ R1955H2 |
+ LXS80 |
+ 71 |
+ F |
+ 25 |
+ 2 |
+ 1523516029 |
+ A |
+ 14 |
+ 7 |
+
+
+ | 132 |
+ R1956H2 |
+ LXS80 |
+ 71 |
+ M |
+ 25 |
+ 2 |
+ 1523516029 |
+ B |
+ 14 |
+ 7 |
+
+
+ | 133 |
+ R2830H1 |
+ LXS84 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ D |
+ 2 |
+ 1 |
+
+
+ | 134 |
+ R2829H2 |
+ LXS84 |
+ 66 |
+ M |
+ 26 |
+ 2 |
+ 1562224037 |
+ A |
+ 24 |
+ 11 |
+
+
+ | 135 |
+ R2839H2 |
+ LXS86 |
+ 68 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ C |
+ 24 |
+ 11 |
+
+
+ | 136 |
+ R2838H1 |
+ LXS86 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516006 |
+ B |
+ 6 |
+ 3 |
+
+
+ | 137 |
+ R2882H1 |
+ LXS87 |
+ 66 |
+ F |
+ 27 |
+ 2 |
+ 1523516006 |
+ F |
+ 6 |
+ 3 |
+
+
+ | 138 |
+ R2744H2 |
+ LXS87 |
+ 71 |
+ M |
+ 26 |
+ 2 |
+ 1562224054 |
+ E |
+ 21 |
+ 10 |
+
+
+ | 139 |
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+ LXS88 |
+ 69 |
+ F |
+ 27 |
+ 2 |
+ 1562224037 |
+ B |
+ 24 |
+ 11 |
+
+
+ | 140 |
+ R2762H2 |
+ LXS88 |
+ 71 |
+ M |
+ 27 |
+ 2 |
+ 1523516005 |
+ A |
+ 5 |
+ 3 |
+
+
+ | 141 |
+ R2828H1 |
+ LXS89 |
+ 75 |
+ F |
+ 26 |
+ 2 |
+ 1523516011 |
+ C |
+ 2 |
+ 1 |
+
+
+ | 142 |
+ R1962H2 |
+ LXS89 |
+ 73 |
+ M |
+ 25 |
+ 2 |
+ 1562224032 |
+ A |
+ 15 |
+ 8 |
+
+
+ | 143 |
+ R1746H2 |
+ LXS9 |
+ 66 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ F |
+ 10 |
+ 5 |
+
+
+ | 144 |
+ R2801H2 |
+ LXS9 |
+ 68 |
+ M |
+ 27 |
+ 2 |
+ 1523516003 |
+ D |
+ 1 |
+ 1 |
+
+
+ | 145 |
+ R1812H2 |
+ LXS90 |
+ 61 |
+ F |
+ 25 |
+ 2 |
+ 1562224038 |
+ F |
+ 25 |
+ 11 |
+
+
+ | 146 |
+ R1813H2 |
+ LXS90 |
+ 61 |
+ M |
+ 25 |
+ 2 |
+ 1523516009 |
+ A |
+ 12 |
+ 6 |
+
+
+ | 147 |
+ R1736H2 |
+ LXS92 |
+ 66 |
+ F |
+ 23 |
+ 2 |
+ 1523516015 |
+ E |
+ 10 |
+ 5 |
+
+
+ | 148 |
+ R1609H2 |
+ LXS92 |
+ 87 |
+ M |
+ 23 |
+ 2 |
+ 1523516032 |
+ A |
+ 7 |
+ 4 |
+
+
+ | 149 |
+ R1624H2 |
+ LXS93 |
+ 74 |
+ F |
+ 26 |
+ 2 |
+ 1523516032 |
+ B |
+ 7 |
+ 4 |
+
+
+ | 150 |
+ R1815H2 |
+ LXS93 |
+ 61 |
+ M |
+ 26 |
+ 2 |
+ 1523516009 |
+ B |
+ 12 |
+ 6 |
+
+
+ | 151 |
+ R1991H2 |
+ LXS94 |
+ 70 |
+ F |
+ 25 |
+ 2 |
+ 1562224036 |
+ C |
+ 17 |
+ 9 |
+
+
+ | 152 |
+ R2002H2 |
+ LXS94 |
+ 70 |
+ M |
+ 25 |
+ 2 |
+ 1562224049 |
+ B |
+ 18 |
+ 9 |
+
+
+ | 153 |
+ R1996H2 |
+ LXS96 |
+ 75 |
+ F |
+ 23 |
+ 2 |
+ 1562224036 |
+ F |
+ 17 |
+ 9 |
+
+
+ | 154 |
+ R1772H2 |
+ LXS96 |
+ 63 |
+ M |
+ 23 |
+ 2 |
+ 1523516007 |
+ C |
+ 11 |
+ 6 |
+
+
+ | 155 |
+ R2759H2 |
+ LXS97 |
+ 73 |
+ F |
+ 26 |
+ 2 |
+ 1562224060 |
+ B |
+ 22 |
+ 10 |
+
+
+ | 156 |
+ R2739H2 |
+ LXS97 |
+ 79 |
+ M |
+ 26 |
+ 2 |
+ 1523516028 |
+ F |
+ 3 |
+ 2 |
+
+
+ | 157 |
+ R2149H2 |
+ LXS98 |
+ 78 |
+ F |
+ 26 |
+ 2 |
+ 1523516033 |
+ C |
+ 8 |
+ 4 |
+
+
+ | 158 |
+ R1888H2 |
+ LXS98 |
+ 76 |
+ M |
+ 26 |
+ 2 |
+ 1562224041 |
+ B |
+ 26 |
+ 12 |
+
+
+ | 159 |
+ R1644H2 |
+ LXS99 |
+ 79 |
+ F |
+ 26 |
+ 2 |
+ 1523516015 |
+ B |
+ 10 |
+ 5 |
+
+
+ | 160 |
+ R2145H2 |
+ LXS99 |
+ 77 |
+ M |
+ 27 |
+ 2 |
+ 1562224050 |
+ F |
+ 19 |
+ 9 |
+
+
+
+ |
+
+
+
+
+
+ |
+
+
+ |
+ Downloading all data:
+
+ All data links (right-most column above) will be available as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
+ |
+
+
+
diff --git a/general/datasets/Illum_lxs_hipp_rsn_nb0807/citation.rtf b/general/datasets/Illum_lxs_hipp_rsn_nb0807/citation.rtf
new file mode 100644
index 0000000..29fd952
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn_nb0807/citation.rtf
@@ -0,0 +1,3 @@
+Downloading all data:
+
+All data links (right-most column above) will be available as soon as the global analysis of these data has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of data. Please contact Dr. Lu Lu if you have any questions on the use of these open data.
diff --git a/general/datasets/Illum_lxs_hipp_rsn_nb0807/contributors.rtf b/general/datasets/Illum_lxs_hipp_rsn_nb0807/contributors.rtf
new file mode 100644
index 0000000..775c0ee
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn_nb0807/contributors.rtf
@@ -0,0 +1,5 @@
+About this text file:
+
+INFO file prepared by Xusheng Wang, Oct 24, 2007.
+
+Data set uploaded by Arthur Centeno, Aug 30, 2007.
diff --git a/general/datasets/Illum_lxs_hipp_rsn_nb0807/experiment-design.rtf b/general/datasets/Illum_lxs_hipp_rsn_nb0807/experiment-design.rtf
new file mode 100644
index 0000000..f477cb7
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn_nb0807/experiment-design.rtf
@@ -0,0 +1 @@
+Experimental Design and Batch Structure: This data set consists arrays processed in 13 groups over a five month period (July 2006 to Dec 2006). Most groups consisted of 12 samples. All arrays in this data set were processed using a single protocol by a single operator, Feng Yiao. Processing was supervised directly by Dr. Lu Lu. All samples were scanned on a single Illumina Beadstation housed in the Hamilton Eye Institute between July 28 and Dec 21, 2006. Details on sample assignment to slides and batches is provide in the table below.
diff --git a/general/datasets/Illum_lxs_hipp_rsn_nb0807/notes.rtf b/general/datasets/Illum_lxs_hipp_rsn_nb0807/notes.rtf
new file mode 100644
index 0000000..938409b
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn_nb0807/notes.rtf
@@ -0,0 +1,3 @@
+ANNOTATION: In spring of 2007, Robert W. Williams and Hongqiang Li reannotated the Illumina Mouse-6 array content. This new annotation is now incorporated into GeneNetwork. For 46166 probes on the Mouse 6 array platform (including control probes) we have identified 35975 NCBI Entrez Gene IDs; 26481 matched human Gene IDs; 23899 matched rat Gene IDs; 26883 NCBI HomoloGene IDs; and 12791 OMIM IDs.
+
+Position data for the 50-mer Illumina Mouse-6 array were initially downloaded from Sanger at http://www.sanger.ac.uk/Users/avc/Illumina/Mouse-6_V1.gff.gz but we then updated all positions by BLAT analysis from mm6 positions to mm8 positions (Hongqiang Li).
diff --git a/general/datasets/Illum_lxs_hipp_rsn_nb0807/platform.rtf b/general/datasets/Illum_lxs_hipp_rsn_nb0807/platform.rtf
new file mode 100644
index 0000000..2ac899d
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn_nb0807/platform.rtf
@@ -0,0 +1,5 @@
+About the array platform:
+
+Illumina Sentrix Mouse-6 BeadArray Platform: The Mouse6 array consists of 46,116 unique probe sequences, each 50 nucleotides in length, that have been arrayed on glass slides using a novel bead technology.
+
+Dunning M, Smith M, Thorne N, Tavare S (2006) beadarray: An R package to analyse Illumina BeadArrays. R News (the Newsletter of the P Project) 6:17-23. (see pages 17-23 of http://CRAN.R-project.org/doc/Rnews/Rnews_2006-5.pdf).
diff --git a/general/datasets/Illum_lxs_hipp_rsn_nb0807/processing.rtf b/general/datasets/Illum_lxs_hipp_rsn_nb0807/processing.rtf
new file mode 100644
index 0000000..c3d0555
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn_nb0807/processing.rtf
@@ -0,0 +1,3 @@
+About data processing:
+
+This data set uses the LOESS with Variance Stabilizing Transform (VST) and Background correction from the lumi package downloaded from Bioconductor (http://www.bioconductor.org/). For the more detailed information, please see the lumi package documentation.
diff --git a/general/datasets/Illum_lxs_hipp_rsn_nb0807/summary.rtf b/general/datasets/Illum_lxs_hipp_rsn_nb0807/summary.rtf
new file mode 100644
index 0000000..ebfc03f
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn_nb0807/summary.rtf
@@ -0,0 +1,33 @@
+August 07 ILLUMINA Mouse-6 DATA SET RSN: The LXS Hippocampus Illumina Robust Spline Normalization with No Background correction data set provides estimates of mRNA expression in the hippocampus of 75 LXS recombinant inbred strains, the two parental strains, ILS/Ibg and ISS/Ibg (Inbred Long Sleep and Inbred Short Sleep strains from the Institute of Behavioral Genetics), and the two reciprocal F1 strains (ILSXISSF1, ISSXILSF1). All samples are from normal adult control animals raised in a standard laboratory environment. Subsequent data sets will provide estimates of mRNA expression following restraint stress, ethanol treatment, and stress followed by ethanol using many of the same strains (Lu Lu and colleagues).
+
+A total of 240 pooled hippocampal samples were processed using 40 Illumina Sentrix Mouse-6 v 1.0 oligomer microarray BeadArray slides. Twenty-seven Mouse-6 slides and a total of 160 samples passed stringent quality control and error checking. We should note that this is our first experience using the Illumina platform and the initial set of 13 slides were not included. This particular data set was processed using the Illumina "Robust Spline Normalization with No Background Correction" protocol. Values were log2 transformed and the current data range from 6.481 average (very low or no expression) to 24.852 (extremely high).
+
+As a measure of data quality we often count the number of probes that are associated with LOD scores of greater than 10 (LRS > 46). In this Hippocampus Illumina (Aug 07) RSN data set, ### probes have LRS values >46.
+
+In comparison, here are the yields of QTLs with LOD>10 for other closely related data sets:
+
+
+ - 1050 for Hippocampus Illumina (Aug07) LOESS
+ - 1162 for Hippocampus Illumina (Aug07) LOESS_NB
+ - 1129 for Hippocampus Illumina (Aug07) QUANT
+ - 1176 for Hippocampus Illumina (Aug07) QUANT_NB
+ - NO DATA for Hippocampus Illumina (Aug07) RSN
+ - NO DATA for Hippocampus Illumina (Aug07) RSN_NB (THIS DATA SET)
+ - 1183 for Hippocampus Illumina (May 07) RankInv
+ - 1167 for Hippocampus Illumina (Oct06) Rank
+ - 1170 for Hippocampus Illumina (Oct06) RankInv
+
+
+The LRS achieved in the different version of the LXS Hippocampus data for probe ILM103520706 (Disabled 1; Dab1) are as follow
+
+
+ - 338.4 for Hippocampus Illumina (Aug07) LOESS
+ - 339.8 for Hippocampus Illumina (Aug07) LOESS_NB
+ - 370.2 for Hippocampus Illumina (Aug07) QUANT
+ - 363.5 for Hippocampus Illumina (Aug07) QUANT_NB
+ - 374.8 for Hippocampus Illumina (Aug07) RSN
+ - 363.0 for Hippocampus Illumina (Aug07) RSN_NB (THIS DATA SET)
+ - 360.3 for Hippocampus Illumina (May 07) RankInv
+ - 358.1 for Hippocampus Illumina (Oct06) Rank
+ - 358.8 for Hippocampus Illumina (Oct06) RankInv
+
diff --git a/general/datasets/Illum_lxs_hipp_rsn_nb0807/tissue.rtf b/general/datasets/Illum_lxs_hipp_rsn_nb0807/tissue.rtf
new file mode 100644
index 0000000..febccce
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rsn_nb0807/tissue.rtf
@@ -0,0 +1,9 @@
+About the animals and tissue used to generate this set of data:
+
+All animals were raised at the IBG by Bennett and colleagues in an SPF facility. No cases were MHV positive. Mice were killed by cervical dislocation. Whole brain dissections were performed at the IBG by Bennett and colleagues and shipped in RNAlater to Lu Lu and colleagues at UTHSC. Most hippocampal dissections (all were bilateral) were performed by Zhiping Jia. Cerebella, olfactory bulbs, and brain stems were also dissected and stored at -80 deg C using further use. Hippocampal samples are very close to complete (see Lu et al., 2001 but probably include variable amounts of fimbria and choroid plexus (see expression of transthyretin, Ttr, as a marker of choroid plexus).
+
+A pool of dissected tissue from four hippocampi taken from two naive adults of the same strain, sex, and age was collected in one session and used to generate RNA samples. The great majority (75%) of animals were sacrificed between 9:30 AM and 11:30 AM. All animals were sacrificed between 9 AM and 5 PM during the light phase. All RNA samples were extracted at UTHSC by Zhiping Jia.
+
+All animals used in this study were between 53 and 90 days of age (average of 72 days; see Table 1 below).
+
+
diff --git a/general/datasets/Illum_lxs_hipp_rss_1008/summary.rtf b/general/datasets/Illum_lxs_hipp_rss_1008/summary.rtf
new file mode 100644
index 0000000..f49829f
--- /dev/null
+++ b/general/datasets/Illum_lxs_hipp_rss_1008/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 63, Name: Hippocampus Illumina NOS (Oct08) RankInv beta
\ No newline at end of file
diff --git a/general/datasets/Illum_retina_bxd_rankinv0410/acknowledgment.rtf b/general/datasets/Illum_retina_bxd_rankinv0410/acknowledgment.rtf
new file mode 100644
index 0000000..a41ff76
--- /dev/null
+++ b/general/datasets/Illum_retina_bxd_rankinv0410/acknowledgment.rtf
@@ -0,0 +1,13 @@
+The HEI Retinal Database is supported by National Eye Institute Grants:
+
+
+
+
+ - R01EY017841 (Dr. Eldon E. Geisert, PI)
+
+
+ - P030EY13080 (NEI Vision Core Grant), and
+
+
+ - A Unrestricted Grand from Research to Prevent Blindness (Dr. Barrett Haik, PI)
+
diff --git a/general/datasets/Illum_retina_bxd_rankinv0410/cases.rtf b/general/datasets/Illum_retina_bxd_rankinv0410/cases.rtf
new file mode 100644
index 0000000..b37d700
--- /dev/null
+++ b/general/datasets/Illum_retina_bxd_rankinv0410/cases.rtf
@@ -0,0 +1,14 @@
+
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 48 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
+
+BXD strains:
+
+
+ - The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s.
+ - In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset.
+ - The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+What Makes the G2 HEI Retina Database different from the HEI Retina Database Examination of Gfap expression across all of the strains in the HEI Retinal Dataset, reveals that some strains express very high levels of Gfap relative to others. For example, BXD24 expresses Gfap at a 9-fold higher level, than BXD22. It has been established that BXD24 acquired a mutation in Cep290 that results in early onset photoreceptor degeneration (Chang et al., 2006). This degeneration results in reactive gliosis throughout the retina. In addition to BXD24, other BXD strains expressed very high levels of Gfap including: BXD32, BXD49, BXD70, BXD83 and BXD89. For the G2 dataset all of these strains with potential reactive gliosis were removed from the dataset.
diff --git a/general/datasets/Illum_retina_bxd_rankinv0410/contributors.rtf b/general/datasets/Illum_retina_bxd_rankinv0410/contributors.rtf
new file mode 100644
index 0000000..b1f321b
--- /dev/null
+++ b/general/datasets/Illum_retina_bxd_rankinv0410/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Justin P. Templeton, Robert W. Williams
diff --git a/general/datasets/Illum_retina_bxd_rankinv0410/experiment-design.rtf b/general/datasets/Illum_retina_bxd_rankinv0410/experiment-design.rtf
new file mode 100644
index 0000000..4fff707
--- /dev/null
+++ b/general/datasets/Illum_retina_bxd_rankinv0410/experiment-design.rtf
@@ -0,0 +1,12 @@
+Expression profiling by array
+
+We used pooled RNA samples of retinas, usually two independent pools--two male, two female pool--for most lines of mice.
+
+All normalization was performed by William E. Orr in the HEI Vision Core Facility
+
+
+ - Computed the log base 2 of each raw signal value
+ - Calculated the mean and standard Deviation of each Mouse WG-6 v2.0 array
+ - Normalized each array using the formula, 2 (z-score of log2 [intensity]) The result is to produce arrays that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - computed the mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
diff --git a/general/datasets/Illum_retina_bxd_rankinv0410/experiment-type.rtf b/general/datasets/Illum_retina_bxd_rankinv0410/experiment-type.rtf
new file mode 100644
index 0000000..0546e04
--- /dev/null
+++ b/general/datasets/Illum_retina_bxd_rankinv0410/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array
\ No newline at end of file
diff --git a/general/datasets/Illum_retina_bxd_rankinv0410/notes.rtf b/general/datasets/Illum_retina_bxd_rankinv0410/notes.rtf
new file mode 100644
index 0000000..13ff99a
--- /dev/null
+++ b/general/datasets/Illum_retina_bxd_rankinv0410/notes.rtf
@@ -0,0 +1 @@
+This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/Illum_retina_bxd_rankinv0410/platform.rtf b/general/datasets/Illum_retina_bxd_rankinv0410/platform.rtf
new file mode 100644
index 0000000..2c52707
--- /dev/null
+++ b/general/datasets/Illum_retina_bxd_rankinv0410/platform.rtf
@@ -0,0 +1 @@
+Illumina MouseWG-6 v2.0 arrays: The Illumina Sentrix Mouse-6 BeadChip uses 50-nucleotide probes to interrogate approximately 46,000 sequences from the mouse transcriptome. For each array, the RNA was pooled from two retinas.
diff --git a/general/datasets/Illum_retina_bxd_rankinv0410/processing.rtf b/general/datasets/Illum_retina_bxd_rankinv0410/processing.rtf
new file mode 100644
index 0000000..97cc2be
--- /dev/null
+++ b/general/datasets/Illum_retina_bxd_rankinv0410/processing.rtf
@@ -0,0 +1,2654 @@
+Values of all 45,281 probe sets in this data set range from a low of 6.25 (Rho GTPase activating protein 11A, Arhgap11a, probe ID ILMN_2747167) to a high of 18.08 (Ubiquitin B, Ubb, probe ID ILMN_2516699). This corresponds to 11.83 units or a 1 to 3641 dynamic range of expression (2^11.83). We normalized raw signal values using Beadstudio’s rank invariant normalization algorithm. BXD62 was the strain used as the control group
+
+
+
+Sample Processing: Drs. Natalie E. Freeman-Anderson and Justin P. Templeton extracted the retinas from the mice and Dr. Natalie Freeman-Anderson processed all samples in the HEI Vision Core Facility. The tissue was homogenized and extracted according to the RNA-Stat-60 protocol as described by the manufacturer (Tel-Test, Friendswood, TX) listed above. The quality and purity of RNA was assessed using an Agilent Bioanalyzer 2100 system. The RNA from each sample was processed with the Illumina TotalPrep RNA Amplification Kit (Ambion, Austin, TX) to produce labeled cRNA. The cRNA for each sample was then hybridized to an Illumina Sentrix® Mouse-6-V2 BeadChip (Illumina, San Diego, CA)
+
+
+
+
+
+Quality control analysis of the raw image data was performed using the Illumina BeadStudio software. MIAME standards were used for all microarray data. Rank invariant normalization with BeadStudio software was used to calculate the data. Once this data was collected, the data was globally normalized across all samples using the formula 2 (z-score of log2 [intensity]) + 8.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
+
+Table 1: HEI Retina case IDs, including sample tube ID, strain, age, sex, and source of mice
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Age |
+ Sex |
+ Source of Animal |
+
+
+ | 1 |
+ 121608_11-C57BL/6JcFA |
+ C57BL/6J |
+ 69 |
+ F |
+ JAX |
+
+
+ | 2 |
+ 121608_12-C57BL/6JcFB |
+ C57BL/6J |
+ 69 |
+ F |
+ JAX |
+
+
+ | 3 |
+ KA7444-C57BL/6JcMC |
+ C57BL/6J |
+ 97 |
+ M |
+ UTHSC RW |
+
+
+ | 4 |
+ KA7444-C57BL/6JcMD |
+ C57BL/6J |
+ 97 |
+ M |
+ UTHSC RW |
+
+
+ | 5 |
+ 31209.05-DBA2JcFA |
+ DBA2J |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 6 |
+ 31209.05-DBA2JcFB |
+ DBA2J |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 7 |
+ 121608_13-DBA/2JcMA |
+ DBA/2J |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 8 |
+ 121608_14-DBA/2JcMB |
+ DBA/2J |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 9 |
+ KA7446-B6D2F1cFA |
+ B6D2F1 |
+ 92 |
+ F |
+ UTHSC RW |
+
+
+ | 10 |
+ KA7446-B6D2F1cFB |
+ B6D2F1 |
+ 92 |
+ F |
+ UTHSC RW |
+
+
+ | 11 |
+ KA7446-B6D2F1cMC |
+ B6D2F1 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 12 |
+ KA7446-B6D2F1cMD |
+ B6D2F1 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 13 |
+ KA7466-D2B6F1cFA |
+ D2B6F1 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 14 |
+ KA7466-D2B6F1cFB |
+ D2B6F1 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 15 |
+ KA7466-D2B6F1cMC |
+ D2B6F1 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 16 |
+ KA7466-D2B6F1cMD |
+ D2B6F1 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 17 |
+ 82609.13-1cFA |
+ BXD01 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 18 |
+ 82609.14-1cFB |
+ BXD01 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 19 |
+ KA7389-1cFA |
+ BXD01 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 20 |
+ KA7389-1cFB |
+ BXD01 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 21 |
+ KA7389-1cMC |
+ BXD01 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 22 |
+ KA7389-1cMD |
+ BXD01 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 23 |
+ KA7300-2cFA |
+ BXD02 |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 24 |
+ KA7300-2cFB |
+ BXD02 |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 25 |
+ 100909.01-2cMA |
+ BXD02 |
+ 65 |
+ M |
+ JAX |
+
+
+ | 26 |
+ 100909.02-2cMB |
+ BXD02 |
+ 65 |
+ M |
+ JAX |
+
+
+ | 27 |
+ KA6699-5cFA |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 28 |
+ KA6699-5cFB |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 29 |
+ KA6699-5cFC |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 30 |
+ KA6699-5cFD |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 31 |
+ 82609.09-5cMA |
+ BXD05 |
+ 60 |
+ M |
+ JAX |
+
+
+ | 32 |
+ 82609.1-5cMB |
+ BXD05 |
+ 60 |
+ M |
+ JAX |
+
+
+ | 33 |
+ KA6763-6cFA |
+ BXD06 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 34 |
+ KA6763-6cFB |
+ BXD06 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 35 |
+ 81209.06-6cMA |
+ BXD06 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 36 |
+ 81209.07-6cMB |
+ BXD06 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 37 |
+ 82609.07-8cFA |
+ BXD08 |
+ 68 |
+ F |
+ JAX |
+
+
+ | 38 |
+ 82609.08-8cFB |
+ BXD08 |
+ 68 |
+ F |
+ JAX |
+
+
+ | 39 |
+ JAX-8cMA |
+ BXD08 |
+ 76 |
+ M |
+ JAX |
+
+
+ | 40 |
+ JAX-8cMB |
+ BXD08 |
+ 76 |
+ M |
+ JAX |
+
+
+ | 41 |
+ KA7289-9cFA |
+ BXD09 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 42 |
+ KA7289-9cFB |
+ BXD09 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 43 |
+ KA7289-9cMC |
+ BXD09 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 44 |
+ KA7289-9cMD |
+ BXD09 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 45 |
+ JAX-11cFA |
+ BXD11 |
+ 84 |
+ F |
+ JAX |
+
+
+ | 46 |
+ JAX-11cFB |
+ BXD11 |
+ 84 |
+ F |
+ JAX |
+
+
+ | 47 |
+ JAX-11cMC |
+ BXD11 |
+ 71 |
+ M |
+ JAX |
+
+
+ | 48 |
+ JAX-11cMD |
+ BXD11 |
+ 71 |
+ M |
+ JAX |
+
+
+ | 49 |
+ 40209.07-12cFA |
+ BXD12 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 50 |
+ 40209.08-12cFB |
+ BXD12 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 51 |
+ 011309.01-12cMA |
+ BXD12 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 52 |
+ 011309.02-12cMB |
+ BXD12 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 53 |
+ KA7286-13cFA |
+ BXD13 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 54 |
+ KA7286-13cFB |
+ BXD13 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 55 |
+ KA7286-13cMC |
+ BXD13 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 56 |
+ KA7286-13cMD |
+ BXD13 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 57 |
+ KA7302-14cFA |
+ BXD14 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 58 |
+ KA7302-14cFB |
+ BXD14 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 59 |
+ 100909.05-14cMA |
+ BXD14 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 60 |
+ 100909.06-14cMB |
+ BXD14 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 61 |
+ KA7288-15cFA |
+ BXD15 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 62 |
+ KA7288-15cFB |
+ BXD15 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 63 |
+ KA7288-15cMC |
+ BXD15 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 64 |
+ KA7288-15cMD |
+ BXD15 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 65 |
+ 062509.01-16cFA |
+ BXD16 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 66 |
+ KA7267-16cMA |
+ BXD16 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 67 |
+ KA7267-16cMB |
+ BXD16 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 68 |
+ KA6686-18cFB |
+ BXD18 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 69 |
+ KA6686-18cFC |
+ BXD18 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 70 |
+ KA6686-18cME |
+ BXD18 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 71 |
+ KA6686-18cMF |
+ BXD18 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 72 |
+ KA6676-19cFB |
+ BXD19 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 73 |
+ KA6676-19cFC |
+ BXD19 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 74 |
+ KA6676-19cME |
+ BXD19 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 75 |
+ KA6676-19cMF |
+ BXD19 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 76 |
+ 060409.05-20cFA |
+ BXD20 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 77 |
+ 060409.06-20cFB |
+ BXD20 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 78 |
+ 021909.03-20cMA |
+ BXD20 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 79 |
+ 021909.04-20cMB |
+ BXD20 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 80 |
+ 82609.02-21cFC |
+ BXD21 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 81 |
+ 82609.03-21cFD |
+ BXD21 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 82 |
+ 121709.01-21cMA |
+ BXD21 |
+ 80 |
+ M |
+ JAX |
+
+
+ | 83 |
+ 121709.02-21cMB |
+ BXD21 |
+ 80 |
+ M |
+ JAX |
+
+
+ | 84 |
+ 121709.03-22cFA |
+ BXD22 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 85 |
+ 121709.04-22cFB |
+ BXD22 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 86 |
+ 092308_03-22cMA |
+ BXD22 |
+ 118 |
+ M |
+ UTHSC RW |
+
+
+ | 87 |
+ 092308_04-22cMB |
+ BXD22 |
+ 118 |
+ M |
+ UTHSC RW |
+
+
+ | 88 |
+ 80409.01-24AcFA |
+ BXD24A |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 89 |
+ 080409_02_24AcFB |
+ BXD24A |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 90 |
+ 82609.26-24AcFC |
+ BXD24A |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 91 |
+ 81209.03-24AcMC |
+ BXD24A |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 92 |
+ KA6678-24cFA |
+ BXD24 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 93 |
+ KA6678-24cFB |
+ BXD24 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 94 |
+ KA6678-24cME |
+ BXD24 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 95 |
+ KA6678-24cMF |
+ BXD24 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 96 |
+ 060409.07-27cFA |
+ BXD27 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 97 |
+ 060409.08-27cFB |
+ BXD27 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 98 |
+ 80409.03-27cMA |
+ BXD27 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 99 |
+ 80409.04-27cMB |
+ BXD27 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 100 |
+ JAX-28cFA |
+ BXD28 |
+ 67 |
+ F |
+ JAX |
+
+
+ | 101 |
+ JAX-28cFB |
+ BXD28 |
+ 67 |
+ F |
+ JAX |
+
+
+ | 102 |
+ JAX-28cMC |
+ BXD28 |
+ 67 |
+ M |
+ JAX |
+
+
+ | 103 |
+ JAX-28cMD |
+ BXD28 |
+ 67 |
+ M |
+ JAX |
+
+
+ | 104 |
+ 82609.11-29cFA |
+ BXD29 |
+ 66 |
+ F |
+ JAX |
+
+
+ | 105 |
+ 82609.12-29cFB |
+ BXD29 |
+ 66 |
+ F |
+ JAX |
+
+
+ | 106 |
+ 82609.04-29cMA |
+ BXD29 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 107 |
+ 82609.05-29cMB |
+ BXD29 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 108 |
+ JAX-31cMB |
+ BXD 31 |
+ 56 |
+ M |
+ JAX |
+
+
+ | 109 |
+ JAX-31cFC |
+ BXD 31 |
+ 69 |
+ F |
+ JAX |
+
+
+ | 110 |
+ JAX-31cFD |
+ BXD 31 |
+ 69 |
+ F |
+ JAX |
+
+
+ | 111 |
+ 011309.03-32cFA |
+ BXD32 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 112 |
+ 011309.04-32cFB |
+ BXD32 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 113 |
+ KA7318-32cFC |
+ BXD32 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 114 |
+ KA7319-32cMA |
+ BXD32 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 115 |
+ KA7319-32cMB |
+ BXD32 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 116 |
+ 100909.07-33cFA |
+ BXD33 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 117 |
+ 100909.08-33cFB |
+ BXD33 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 118 |
+ 022609.01-33cMA |
+ BXD33 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 119 |
+ 022609.02-33cMB |
+ BXD33 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 120 |
+ KA7416-34cFA |
+ BXD34 |
+ 97 |
+ F |
+ UTHSC RW |
+
+
+ | 121 |
+ KA7416-34cFB |
+ BXD34 |
+ 97 |
+ F |
+ UTHSC RW |
+
+
+ | 122 |
+ KA6321-34cMA |
+ BXD34 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 123 |
+ KA6321-34cMB |
+ BXD34 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 124 |
+ 060409.01-36cFA |
+ BXD36 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 125 |
+ 060409.02-36cFB |
+ BXD36 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 126 |
+ 060409.03-36cMC |
+ BXD36 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 127 |
+ KA6702-38cFA |
+ BXD38 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 128 |
+ KA6702-38cFB |
+ BXD38 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 129 |
+ 82609.24-38cFA |
+ BXD38 |
+ 85 |
+ F |
+ UTHSC RW |
+
+
+ | 130 |
+ 82609.25-38cFB |
+ BXD38 |
+ 85 |
+ F |
+ UTHSC RW |
+
+
+ | 131 |
+ 100909.03-38cMA |
+ BXD38 |
+ 61 |
+ M |
+ JAX |
+
+
+ | 132 |
+ 100909.04-38cMB |
+ BXD38 |
+ 61 |
+ M |
+ JAX |
+
+
+ | 133 |
+ 022609.05-39cFA |
+ BXD39 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 134 |
+ 022609.06-39cFB |
+ BXD39 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 135 |
+ 31209.01-39cMC |
+ BXD39 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 136 |
+ 92409.01-40cFA |
+ BXD40 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 137 |
+ 92409.02-40cFB |
+ BXD40 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 138 |
+ KA6173-40cMA |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 139 |
+ KA6173-40cMB |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 140 |
+ KA6173-40cMC |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 141 |
+ 091809.01-42cFA |
+ BXD42 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 142 |
+ 091809.02-42cFB |
+ BXD42 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 143 |
+ 021909.01-42cFA |
+ BXD42 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 144 |
+ 011309.06-42cMA |
+ BXD42 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 145 |
+ 011309.07-42cMB |
+ BXD42 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 146 |
+ 110408_02-43cFA |
+ BXD43 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 147 |
+ 110408_03-43cFB |
+ BXD43 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 148 |
+ KA6158-43cMA |
+ BXD43 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 149 |
+ KA6158-43cMB |
+ BXD43 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 150 |
+ 100308_01-44cFA |
+ BXD44 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 151 |
+ 102208_02-44cMD |
+ BXD44 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 152 |
+ 103009.03-45cFA |
+ BXD45 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 153 |
+ 103009.04-45cFB |
+ BXD45 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 154 |
+ 022609.03-45cFA |
+ BXD45 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 155 |
+ 022609.04-45cFB |
+ BXD45 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 156 |
+ 40309.05-45cMB |
+ BXD45 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 157 |
+ 40209.05-48cFB |
+ BXD48 |
+ 58 |
+ F |
+ VAMC |
+
+
+ | 158 |
+ 40209.06-48cFC |
+ BXD48 |
+ 58 |
+ F |
+ VAMC |
+
+
+ | 159 |
+ 81209.04-48cMA |
+ BXD48 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 160 |
+ 81209.05-48cMB |
+ BXD48 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 161 |
+ 81209.08-49cFA |
+ BXD49 |
+ 70 |
+ F |
+ VAMC |
+
+
+ | 162 |
+ 81209.09-49cFB |
+ BXD49 |
+ 70 |
+ F |
+ VAMC |
+
+
+ | 163 |
+ 40209.01-49cMA |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 164 |
+ 40209.02-49cMB |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 165 |
+ 40209.03-49cMC |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 166 |
+ KA737850cFA |
+ BXD50 |
+ 50 |
+ F |
+ UTHSC RW |
+
+
+ | 167 |
+ KA737850cFB |
+ BXD50 |
+ 50 |
+ F |
+ UTHSC RW |
+
+
+ | 168 |
+ 121908_01-50cMA |
+ BXD50 |
+ 49 |
+ M |
+ UTHSC RW |
+
+
+ | 169 |
+ 121908_02-50cMB |
+ BXD50 |
+ 49 |
+ M |
+ UTHSC RW |
+
+
+ | 170 |
+ 111208_01-51cFA |
+ BXD51 |
+ 99 |
+ F |
+ UTHSC RW |
+
+
+ | 171 |
+ 102208_03-51cMA |
+ BXD51 |
+ 56 |
+ M |
+ UTHSC RW |
+
+
+ | 172 |
+ 102208_04-51cMB |
+ BXD51 |
+ 56 |
+ M |
+ UTHSC RW |
+
+
+ | 173 |
+ 090208_14-53BcFA |
+ BXD53B |
+ 93 |
+ F |
+ UTHSC RW |
+
+
+ | 174 |
+ 090208_15-53BcFB |
+ BXD53B |
+ 93 |
+ F |
+ UTHSC RW |
+
+
+ | 175 |
+ 090208_16-53BcMC |
+ BXD53B |
+ 93 |
+ M |
+ UTHSC RW |
+
+
+ | 176 |
+ 090208_17-53BcMD |
+ BXD53B |
+ 93 |
+ M |
+ UTHSC RW |
+
+
+ | 177 |
+ 111208_05-55cFB |
+ BXD55 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 178 |
+ KA6183-55cMA |
+ BXD55 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 179 |
+ KA6183-55cMB |
+ BXD55 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 180 |
+ KA7362-56cFB |
+ BXD 56 |
+ 54 |
+ F |
+ UTHSC RW |
+
+
+ | 181 |
+ KA6088-56cMA |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 182 |
+ KA6088-56cMB |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 183 |
+ KA6088-56cMC |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 184 |
+ 21810.01-60RFA |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 185 |
+ 21810.02-60RFB |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 186 |
+ 21810.02-60RFC |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 187 |
+ SQ7325-60cMA |
+ BXD60 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 188 |
+ SQ7325-60cMB |
+ BXD60 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 189 |
+ 092308_10-61cFA |
+ BXD61 |
+ 110 |
+ F |
+ UTHSC RW |
+
+
+ | 190 |
+ 092308_11-61cFB |
+ BXD61 |
+ 110 |
+ F |
+ UTHSC RW |
+
+
+ | 191 |
+ 31909.01-61cMA |
+ BXD61 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 192 |
+ 31909.02-61cMB |
+ BXD61 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 193 |
+ KA7462-62cFA |
+ BXD62 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 194 |
+ KA7462-62cFB |
+ BXD62 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 195 |
+ KA5996-62cMA |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 196 |
+ KA5996-62cMB |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 197 |
+ KA5996-62cMC |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 198 |
+ 090309.01-63cFA |
+ BXD63 |
+ 69 |
+ F |
+ UTHSC RW |
+
+
+ | 199 |
+ 090309.02-63cFB |
+ BXD63 |
+ 69 |
+ F |
+ UTHSC RW |
+
+
+ | 200 |
+ 110609.01-63cMA |
+ BXD63 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 201 |
+ 110609.02-63cMB |
+ BXD63 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 202 |
+ 091809.03-65cFA |
+ BXD65 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 203 |
+ 091809.04-65cFB |
+ BXD65 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 204 |
+ 103009.01-65cMA |
+ BXD65 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 205 |
+ 103009.02-65cMB |
+ BXD65 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 206 |
+ 110408_05-66cFB |
+ BXD66 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 207 |
+ KA7165-66cMA |
+ BXD66 |
+ 95 |
+ M |
+ UTHSC RW |
+
+
+ | 208 |
+ KA7165-66cMB |
+ BXD66 |
+ 95 |
+ M |
+ UTHSC RW |
+
+
+ | 209 |
+ 90809.01-67cMA |
+ BXD67 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 210 |
+ 90809.02-67cMB |
+ BXD67 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 211 |
+ 110609.03-67cFA |
+ BXD67 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 212 |
+ 110609.04-67cFB |
+ BXD67 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 213 |
+ 120408_01-68cFA |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 214 |
+ 120408_02-68cFB |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 215 |
+ SQ7205-68cMA |
+ BXD68 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 216 |
+ SQ7205-68cMB |
+ BXD68 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 217 |
+ KA6316-68cMA |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 218 |
+ KA6316-68cMB |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 219 |
+ KA6316-68cMC |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 220 |
+ KA76-69cFA |
+ BXD69 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 221 |
+ KA76-69cFB |
+ BXD69 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 222 |
+ KA6074-69cMA |
+ BXD69 |
+ 90 |
+ M |
+ UTHSC RW |
+
+
+ | 223 |
+ KA6074-69cMB |
+ BXD69 |
+ 90 |
+ M |
+ UTHSC RW |
+
+
+ | 224 |
+ 121608_01-70cFA |
+ BXD70 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 225 |
+ 121608_02-70cFB |
+ BXD70 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 226 |
+ KA7394-70cMA |
+ BXD70 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 227 |
+ 81209.08-70cMA |
+ BXD70 |
+ 71 |
+ M |
+ VAMC |
+
+
+ | 228 |
+ 81209.09-70cMB |
+ BXD70 |
+ 71 |
+ M |
+ VAMC |
+
+
+ | 229 |
+ 052809.01-71cFA |
+ BXD71 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 230 |
+ 060409.09-71cMA |
+ BXD71 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 231 |
+ 060409.10-71cMB |
+ BXD71 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 232 |
+ 40809.01-73cFA |
+ BXD73 |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 233 |
+ 40809.02-73cFB |
+ BXD73 |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 234 |
+ 111708_01-73cFA |
+ BXD73 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 235 |
+ 111708_01-73cFB |
+ BXD73 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 236 |
+ KA6164-73cMB |
+ BXD73 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 237 |
+ KA6164-73cMC |
+ BXD73 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 238 |
+ 82609.22-74cFA |
+ BXD74 |
+ 68 |
+ F |
+ VAMC |
+
+
+ | 239 |
+ 82609.23-74cFB |
+ BXD74 |
+ 68 |
+ F |
+ VAMC |
+
+
+ | 240 |
+ 82609.20-74cMA |
+ BXD74 |
+ 68 |
+ M |
+ VAMC |
+
+
+ | 241 |
+ 82609.21-74cMB |
+ BXD74 |
+ 68 |
+ M |
+ VAMC |
+
+
+ | 242 |
+ KA733675cFA |
+ BXD75 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 243 |
+ KA733675cFB |
+ BXD75 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 244 |
+ KA38-75cMB |
+ BXD75 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 245 |
+ KA38-75cMC |
+ BXD75 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 246 |
+ 41509.01-77cFA |
+ BXD77 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 247 |
+ 41509.02-77cFB |
+ BXD77 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 248 |
+ 41509.03-77cMC |
+ BXD77 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 249 |
+ 41509.04-77cMD |
+ BXD77 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 250 |
+ 121608_03-80cFA |
+ BXD80 |
+ 77 |
+ F |
+ UTHSC RW |
+
+
+ | 251 |
+ 121608_05-80cMC |
+ BXD80 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 252 |
+ KA23-80cMC |
+ BXD80 |
+ 77 |
+ M |
+ UTHSC RW |
+
+
+ | 253 |
+ KA7305-81cFA |
+ BXD81 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 254 |
+ KA7305-81cFB |
+ BXD81 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 255 |
+ KA7305-81cMD |
+ BXD81 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 256 |
+ 060409.11-83cFA |
+ BXD83 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 257 |
+ KA24-83cFA |
+ BXD83 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 258 |
+ 121608_07-83cMA |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 259 |
+ 121608_08-83cMB |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 260 |
+ KA24-83cMD |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 261 |
+ 090409.05-84cFA |
+ BXD84 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 262 |
+ 090409.06-84cFB |
+ BXD84 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 263 |
+ KA6203-84cMA |
+ BXD84 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 264 |
+ KA6203-84cMB |
+ BXD84 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 265 |
+ 40309.02-85cFD |
+ BXD85 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 266 |
+ 40309.03-85cFE |
+ BXD85 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 267 |
+ 32609.01-85cMA |
+ BXD85 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 268 |
+ 32609.02-85cMB |
+ BXD85 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 269 |
+ 41509.05-86cFA |
+ BXD86 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 270 |
+ 41509.06-86cFB |
+ BXD86 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 271 |
+ KA6101-86cMA |
+ BXD86 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 272 |
+ KA6101-86cMC |
+ BXD86 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 273 |
+ 070909.02-87cFA |
+ BXD87 |
+ 86 |
+ F |
+ UTHSC RW |
+
+
+ | 274 |
+ 070909.03-87cFB |
+ BXD87 |
+ 86 |
+ F |
+ UTHSC RW |
+
+
+ | 275 |
+ KA7407-87cMA |
+ BXD87 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 276 |
+ KA7407-87cMB |
+ BXD87 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 277 |
+ 102208_05-89cFA |
+ BXD89 |
+ 82 |
+ F |
+ UTHSC RW |
+
+
+ | 278 |
+ KA5974-89cMA |
+ BXD89 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 279 |
+ KA5974-89cMB |
+ BXD89 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 280 |
+ 102208_06-89cMC |
+ BXD89 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 281 |
+ 72309.01-90cFA |
+ BXD90 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 282 |
+ 72309.02-90cFB |
+ BXD90 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 283 |
+ 090409.03-90cMA |
+ BXD90 |
+ 64 |
+ M |
+ VAMC |
+
+
+ | 284 |
+ 090409.04-90cMB |
+ BXD90 |
+ 64 |
+ M |
+ VAMC |
+
+
+ | 285 |
+ KA6094-92cMA |
+ BXD92 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 286 |
+ 020609.01-95cFA |
+ BXD95 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 287 |
+ 020609.02-95cFB |
+ BXD95 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 288 |
+ KA6181-95cMA |
+ BXD95 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 289 |
+ KA6181-95cMB |
+ BXD95 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 290 |
+ 31209.03-96cFA |
+ BXD96 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 291 |
+ 31209.04-96cFB |
+ BXD96 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 292 |
+ KA7246-96cMA |
+ BXD96 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 293 |
+ KA7246-96cMB |
+ BXD96 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 294 |
+ 81209.10-97cFA |
+ BXD97 |
+ 83 |
+ F |
+ VAMC |
+
+
+ | 295 |
+ 81209.11-97cFB |
+ BXD97 |
+ 83 |
+ F |
+ VAMC |
+
+
+ | 296 |
+ 81209.1-97cMA |
+ BXD97 |
+ 83 |
+ M |
+ VAMC |
+
+
+ | 297 |
+ 81209.11-97cMB |
+ BXD97 |
+ 83 |
+ M |
+ VAMC |
+
+
+ | 298 |
+ SQ7520-98cFA |
+ BXD98 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 299 |
+ SQ7520-98cFB |
+ BXD98 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 300 |
+ SQ7520-98cMC |
+ BXD98 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 301 |
+ SQ7520-98cMD |
+ BXD98 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 302 |
+ 82609.17-99cFA |
+ BXD99 |
+ 64 |
+ F |
+ VAMC |
+
+
+ | 303 |
+ 82609.18-99cFB |
+ BXD99 |
+ 64 |
+ F |
+ VAMC |
+
+
+ | 304 |
+ 81409.01-99cMA |
+ BXD99 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 305 |
+ 81409.02-99cMB |
+ BXD99 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 306 |
+ 121608_09-100cFA |
+ BXD100 |
+ 81 |
+ F |
+ UTHSC RW |
+
+
+ | 307 |
+ 121608_10-100cFB |
+ BXD100 |
+ 81 |
+ F |
+ UTHSC RW |
+
+
+ | 308 |
+ KA6001-100cMA |
+ BXD100 |
+ 111 |
+ M |
+ UTHSC RW |
+
+
+ | 309 |
+ KA6001-100cMB |
+ BXD100 |
+ 111 |
+ M |
+ UTHSC RW |
+
+
+ | 310 |
+ 81209.12-101cFA |
+ BXD101 |
+ 72 |
+ F |
+ VAMC |
+
+
+ | 311 |
+ 81209.13-101cFB |
+ BXD101 |
+ 72 |
+ F |
+ VAMC |
+
+
+ | 312 |
+ KA7296-101cMA |
+ BXD101 |
+ 75 |
+ M |
+ UTHSC RW |
+
+
+ | 313 |
+ KA7296-101cMB |
+ BXD101 |
+ 75 |
+ M |
+ UTHSC RW |
+
+
+ | 314 |
+ 92409.03-102cFA |
+ BXD102 |
+ 71 |
+ F |
+ VAMC |
+
+
+ | 315 |
+ 92409.04-102cFB |
+ BXD102 |
+ 71 |
+ F |
+ VAMC |
+
+
+ | 316 |
+ KA7380-102cMA |
+ BXD102 |
+ 115 |
+ M |
+ UTHSC RW |
+
+
+ | 317 |
+ 43009.01-103cFA |
+ BXD103 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 318 |
+ 43009.02-103cFB |
+ BXD103 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 319 |
+ KA79-103cFA |
+ BXD103 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 320 |
+ KA79-103cFB |
+ BXD103 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 321 |
+ KA79-103cMC |
+ BXD103 |
+ 48 |
+ M |
+ UTHSC RW |
+
+
+ | 322 |
+ 82609.15-103cMA |
+ BXD103 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 323 |
+ 82609.16-103cMB |
+ BXD103 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 324 |
+ 102909.01-BALBCcFA |
+ BALB/cByJ |
+ 78 |
+ F |
+ JAX |
+
+
+ | 325 |
+ 102909.02-BALBCcFB |
+ BALB/cByJ |
+ 78 |
+ F |
+ JAX |
+
+
+ | 326 |
+ 102909.03-BALBCcMA |
+ BALB/cByJ |
+ 78 |
+ M |
+ JAX |
+
+
+ | 327 |
+ 102909.04-BALBCcMB |
+ BALB/cByJ |
+ 78 |
+ M |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Illum_retina_bxd_rankinv0410/summary.rtf b/general/datasets/Illum_retina_bxd_rankinv0410/summary.rtf
new file mode 100644
index 0000000..44e98a7
--- /dev/null
+++ b/general/datasets/Illum_retina_bxd_rankinv0410/summary.rtf
@@ -0,0 +1,50 @@
+
+This is a subtractive dataset. The Normal retina dataset was subtracted from the ONC data set probe by probe to create a data set of the changes occurring following ONC. This data set can be used to define gene changes following ONC. It is not compatible with most of the bioinformatic tools available on GeneNetwork.
+
+HEI Retina Illumina V6.2 (April 2010) RankInv was normalized and scaled by William E. Orr and uploaded by Arthur Centeno and Xiaodong Zhou on April 7, 2010. This data set consists of either 69 BXD strains (Normal data set) or 75 BXD strains (Full data set), C57BL/6J, DBA/2J, both reciprocal F1s, and BALB/cByJ. A total of either 74 strains (Normal data set) or 80 strains (Full data set) were quantified.
+
+COMMENT on FULL versus NORMAL data sets: For many general uses there is no significant difference between FULL and NORMAL data sets. However, the FULL data set includes strains with high endogenous Gfap mRNA expression, indicative of reactive gliosis. For that reason, and to compare to OPTIC NERVE CRUSH (ONC), we removed data from six strains to make the NORMAL data set.
+
+The NORMAL data set exludes data from BXD24, BXD32, BXD49, BXD70, BXD83, and BXD89. BXD24 has known retinal degeneration and is now known officially as BXD24/TyJ-Cep290/J, JAX Stock number 000031. BXD32 has mild retinal degeneration. The NORMAL data set does include BXD24a, now also known as BXD24/TyJ (JAX Stock number 005243).
+
+The data are now open and available for analysis.
+
+Please cite: Freeman NE, Templeton JP, Orr WE, Lu L, Williams RW, Geisert EE (2011) Genetic networks in the mouse retina: Growth Associated Protein 43 and Phosphate Tensin Homology network. Molecular Vision 17:1355-1372. Full Text PDF or HTML
+
+This is rank invariant expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 6.25 to 18.08 (11.83 units), a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
+
+The lowest level of expression is 6.254 for ILMN_2747167 (Arhgap11a) from HEI Retina Illumina V6.2 (April 2010) RankInv **. Lowest single data about 5.842.
+
+The highest level of expression is 18.077 for ILMN_2516699 (Ubb). Highest single value is about 18.934.
+
+
+
+
+Other Related Publications
+
+
+
+
+
+ - Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link)
+ - Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674
+ - Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link)
+ - Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.(Link)
+
+
+
+
+
+
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
+
diff --git a/general/datasets/Illum_retina_bxd_rankinv0410/tissue.rtf b/general/datasets/Illum_retina_bxd_rankinv0410/tissue.rtf
new file mode 100644
index 0000000..766ab59
--- /dev/null
+++ b/general/datasets/Illum_retina_bxd_rankinv0410/tissue.rtf
@@ -0,0 +1,32 @@
+
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RNAlater at room temperature. Two retinas from one mouse were stored in a single tube.
+
+Each array was hybridized with a pool of cRNA from 2 retinas (1 mouse). Natalie Freeman-Anderson extracted RNA at UTHSC.
+
+
+
+Dissecting and preparing eyes for RNA extraction
+
+
+
+Retinas for RNA extraction were placed in RNA STAT-60 (Tel-Test Inc.) and processed per manufacturer’s instructions (in brief form below). Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+
+
+ - Homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue via syringe)
+ - Allow the homogenate to stand for 5-10 min at room temperature
+ - Add 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - Mix the sample vigorously for 15 sec and let the sample incubate at room temperature for 5-10 min
+ - Centrifuge at 12,000 g for 1 hr at 4°C
+ - Transfer the aqueous phase to a clean centrifuge tube
+ - Add 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - Vortex and incubate the sample at -20°C for 1 hr or overnight
+ - Centrifuge at 12,000 g for 1 hr
+ - Remove the supernatant and wash the RNA pellet with 75% ethanol
+ - Remove ethanol, let air dry (5-10 min)
+ - Dissolve the pellet in 50 μl of nuclease free water.
+
+
+
+
diff --git a/general/datasets/Inia_adrenal_rma_0612/cases.rtf b/general/datasets/Inia_adrenal_rma_0612/cases.rtf
new file mode 100644
index 0000000..f0b204b
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_0612/cases.rtf
@@ -0,0 +1,771 @@
+Young adult mice raised in specific pathogen-free vivarium at UTHSC.
+Table 1. Final strain correction by Khyobeni Mozhui on Mar 28, 2013.
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Tissue |
+ Sex |
+
+
+ | 1 |
+ R6947A |
+ BXD48 |
+ Adrenal |
+ M |
+
+
+ | 2 |
+ R6948A |
+ BXD90 |
+ Adrenal |
+ M |
+
+
+ | 3 |
+ R6949A |
+ BXD97 |
+ Adrenal |
+ M |
+
+
+ | 4 |
+ R6950A |
+ BXD87 |
+ Adrenal |
+ M |
+
+
+ | 5 |
+ R6952A |
+ BXD83 |
+ Adrenal |
+ F |
+
+
+ | 6 |
+ R6953A |
+ BXD67 |
+ Adrenal |
+ M |
+
+
+ | 7 |
+ R6954A |
+ BXD56 |
+ Adrenal |
+ M |
+
+
+ | 8 |
+ R6955A |
+ BXD48 |
+ Adrenal |
+ F |
+
+
+ | 9 |
+ R6956A |
+ BXD90 |
+ Adrenal |
+ F |
+
+
+ | 10 |
+ R6957A |
+ BXD89 |
+ Adrenal |
+ M |
+
+
+ | 11 |
+ R6958A |
+ BXD65 |
+ Adrenal |
+ M |
+
+
+ | 12 |
+ R6959A |
+ BXD65 |
+ Adrenal |
+ F |
+
+
+ | 13 |
+ R6960A |
+ BXD63 |
+ Adrenal |
+ F |
+
+
+ | 14 |
+ R6961A |
+ BXD63 |
+ Adrenal |
+ M |
+
+
+ | 15 |
+ R6963A |
+ BXD31 |
+ Adrenal |
+ M |
+
+
+ | 16 |
+ R6964A |
+ BXD31 |
+ Adrenal |
+ F |
+
+
+ | 17 |
+ R6965A |
+ BXD1 |
+ Adrenal |
+ F |
+
+
+ | 18 |
+ R6966A |
+ BXD1 |
+ Adrenal |
+ F |
+
+
+ | 19 |
+ R6967A |
+ BXD24 |
+ Adrenal |
+ F |
+
+
+ | 20 |
+ R6968A |
+ BXD34 |
+ Adrenal |
+ M |
+
+
+ | 21 |
+ R6969A |
+ BXD1 |
+ Adrenal |
+ M |
+
+
+ | 22 |
+ R6971A |
+ BXD27 |
+ Adrenal |
+ F |
+
+
+ | 23 |
+ R6972A |
+ BXD29 |
+ Adrenal |
+ M |
+
+
+ | 24 |
+ R6973A |
+ BXD12 |
+ Adrenal |
+ F |
+
+
+ | 25 |
+ R6974A |
+ BXD14 |
+ Adrenal |
+ F |
+
+
+ | 26 |
+ R6975A |
+ BXD99 |
+ Adrenal |
+ F |
+
+
+ | 27 |
+ R6976A |
+ BXD32 |
+ Adrenal |
+ F |
+
+
+ | 28 |
+ R6977A |
+ BXD97 |
+ Adrenal |
+ F |
+
+
+ | 29 |
+ R6978A |
+ BXD84 |
+ Adrenal |
+ M |
+
+
+ | 30 |
+ R6979A |
+ BXD39 |
+ Adrenal |
+ M |
+
+
+ | 31 |
+ R6980A |
+ BXD24 |
+ Adrenal |
+ M |
+
+
+ | 32 |
+ R6981A |
+ BXD50 |
+ Adrenal |
+ F |
+
+
+ | 33 |
+ R6982A |
+ BXD75 |
+ Adrenal |
+ M |
+
+
+ | 34 |
+ R6983A |
+ BXD42 |
+ Adrenal |
+ M |
+
+
+ | 35 |
+ R6984A |
+ BXD39 |
+ Adrenal |
+ F |
+
+
+ | 36 |
+ R6985A |
+ BXD34 |
+ Adrenal |
+ F |
+
+
+ | 37 |
+ R6986A |
+ BXD87 |
+ Adrenal |
+ F |
+
+
+ | 38 |
+ R6987A |
+ BXD50 |
+ Adrenal |
+ M |
+
+
+ | 39 |
+ R6989A |
+ BXD62 |
+ Adrenal |
+ M |
+
+
+ | 40 |
+ R6990A |
+ BXD70 |
+ Adrenal |
+ M |
+
+
+ | 41 |
+ R6991A |
+ BXD64 |
+ Adrenal |
+ F |
+
+
+ | 42 |
+ R6992A |
+ BXD84 |
+ Adrenal |
+ F |
+
+
+ | 43 |
+ R6993A |
+ BXD100 |
+ Adrenal |
+ F |
+
+
+ | 44 |
+ R6994A |
+ BXD62 |
+ Adrenal |
+ F |
+
+
+ | 45 |
+ R6996A |
+ BXD95 |
+ Adrenal |
+ M |
+
+
+ | 46 |
+ R6998A |
+ BXD32 |
+ Adrenal |
+ M |
+
+
+ | 47 |
+ R6999A |
+ BXD101 |
+ Adrenal |
+ F |
+
+
+ | 48 |
+ R7000A |
+ BXD49 |
+ Adrenal |
+ M |
+
+
+ | 49 |
+ R7002A |
+ BXD11 |
+ Adrenal |
+ M |
+
+
+ | 50 |
+ R7003A |
+ BXD100 |
+ Adrenal |
+ M |
+
+
+ | 51 |
+ R7004A |
+ BXD43 |
+ Adrenal |
+ F |
+
+
+ | 52 |
+ R7005A |
+ BXD103 |
+ Adrenal |
+ M |
+
+
+ | 53 |
+ R7006A |
+ BXD73 |
+ Adrenal |
+ F |
+
+
+ | 54 |
+ R7008A |
+ BXD43 |
+ Adrenal |
+ M |
+
+
+ | 55 |
+ R7009A |
+ BXD102 |
+ Adrenal |
+ F |
+
+
+ | 56 |
+ R7010A |
+ BXD69 |
+ Adrenal |
+ F |
+
+
+ | 57 |
+ R7011A |
+ BXD60 |
+ Adrenal |
+ M |
+
+
+ | 58 |
+ R7012A |
+ BXD45 |
+ Adrenal |
+ F |
+
+
+ | 59 |
+ R7013A |
+ BXD79 |
+ Adrenal |
+ M |
+
+
+ | 60 |
+ R7014A |
+ BXD40 |
+ Adrenal |
+ M |
+
+
+ | 61 |
+ R7015A |
+ BXD79 |
+ Adrenal |
+ F |
+
+
+ | 62 |
+ R7016A |
+ BXD40 |
+ Adrenal |
+ F |
+
+
+ | 63 |
+ R7017A |
+ BXD68 |
+ Adrenal |
+ F |
+
+
+ | 64 |
+ R7018A |
+ BXD85 |
+ Adrenal |
+ F |
+
+
+ | 65 |
+ R7019A |
+ BXD44 |
+ Adrenal |
+ F |
+
+
+ | 66 |
+ R7020A |
+ BXD70 |
+ Adrenal |
+ F |
+
+
+ | 67 |
+ R7021A |
+ BXD68 |
+ Adrenal |
+ M |
+
+
+ | 68 |
+ R7023A |
+ BXD44 |
+ Adrenal |
+ M |
+
+
+ | 69 |
+ R7024A |
+ BXD95 |
+ Adrenal |
+ F |
+
+
+ | 70 |
+ R7025A |
+ BXD56 |
+ Adrenal |
+ F |
+
+
+ | 71 |
+ R7032A |
+ BXD103 |
+ Adrenal |
+ F |
+
+
+ | 72 |
+ R7034A |
+ BXD24 |
+ Adrenal |
+ F |
+
+
+ | 73 |
+ R7035A |
+ BXD101 |
+ Adrenal |
+ M |
+
+
+ | 74 |
+ R7036A |
+ BXD29 |
+ Adrenal |
+ F |
+
+
+ | 75 |
+ R7037A |
+ BXD60 |
+ Adrenal |
+ F |
+
+
+ | 76 |
+ R7038A |
+ BXD69 |
+ Adrenal |
+ M |
+
+
+ | 77 |
+ R7039A |
+ BXD73 |
+ Adrenal |
+ M |
+
+
+ | 78 |
+ R7040A |
+ BXD80 |
+ Adrenal |
+ M |
+
+
+ | 79 |
+ R7041A |
+ BXD11 |
+ Adrenal |
+ F |
+
+
+ | 80 |
+ R7042A |
+ BXD74 |
+ Adrenal |
+ F |
+
+
+ | 81 |
+ R7043A |
+ BXD67 |
+ Adrenal |
+ F |
+
+
+ | 82 |
+ R7044A |
+ BXD67 |
+ Adrenal |
+ M |
+
+
+ | 83 |
+ R7046A |
+ C57BL/6J |
+ Adrenal |
+ F |
+
+
+ | 84 |
+ R7047A |
+ D2B6F1 |
+ Adrenal |
+ F |
+
+
+ | 85 |
+ R7048A |
+ B6D2F1 |
+ Adrenal |
+ M |
+
+
+ | 86 |
+ R7051A |
+ BXD80 |
+ Adrenal |
+ F |
+
+
+ | 87 |
+ R7053A |
+ BXD102 |
+ Adrenal |
+ M |
+
+
+ | 88 |
+ R7054A |
+ BXD49 |
+ Adrenal |
+ F |
+
+
+ | 89 |
+ R7055A |
+ BXD77 |
+ Adrenal |
+ F |
+
+
+ | 90 |
+ R7056A |
+ BXD77 |
+ Adrenal |
+ M |
+
+
+ | 91 |
+ R7057A |
+ BXD66 |
+ Adrenal |
+ M |
+
+
+ | 92 |
+ R7058A |
+ BXD66 |
+ Adrenal |
+ F |
+
+
+ | 93 |
+ R7059A |
+ BXD45 |
+ Adrenal |
+ F |
+
+
+ | 94 |
+ R7145A |
+ BXD67 |
+ Adrenal |
+ M |
+
+
+ | 95 |
+ R7147A |
+ BXD85 |
+ Adrenal |
+ M |
+
+
+ | 96 |
+ R7148A |
+ DBA/2J |
+ Adrenal |
+ F |
+
+
+ | 97 |
+ R7149A |
+ D2B6F1 |
+ Adrenal |
+ M |
+
+
+ | 98 |
+ R7150A |
+ D2B6F1 |
+ Adrenal |
+ F |
+
+
+ | 99 |
+ R7151A |
+ BXD27 |
+ Adrenal |
+ M |
+
+
+ | 100 |
+ R7152A |
+ B6D2F1 |
+ Adrenal |
+ M |
+
+
+ | 101 |
+ R7153A |
+ DBA/2J |
+ Adrenal |
+ M |
+
+
+ | 102 |
+ R7159A |
+ C57BL/6J |
+ Adrenal |
+ F |
+
+
+ | 103 |
+ R7161A |
+ C57BL/6J |
+ Adrenal |
+ M |
+
+
+ | 104 |
+ R7164A |
+ B6D2F1 |
+ Adrenal |
+ F |
+
+
+ | 105 |
+ R7166A |
+ B6D2F1 |
+ Adrenal |
+ M |
+
+
+ | 106 |
+ R7167A |
+ DBA/2J |
+ Adrenal |
+ F |
+
+
+ | 107 |
+ R7168A |
+ DBA/2J |
+ Adrenal |
+ M |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Inia_adrenal_rma_0612/experiment-design.rtf b/general/datasets/Inia_adrenal_rma_0612/experiment-design.rtf
new file mode 100644
index 0000000..b069873
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_0612/experiment-design.rtf
@@ -0,0 +1,3 @@
+Normative expression in the adrenals (whole organ) of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
+
+Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/Inia_adrenal_rma_0612/experiment-type.rtf b/general/datasets/Inia_adrenal_rma_0612/experiment-type.rtf
new file mode 100644
index 0000000..addb95f
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_0612/experiment-type.rtf
@@ -0,0 +1 @@
+Normative expression in the adrenals (whole organ) of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
\ No newline at end of file
diff --git a/general/datasets/Inia_adrenal_rma_0612/platform.rtf b/general/datasets/Inia_adrenal_rma_0612/platform.rtf
new file mode 100644
index 0000000..7057d48
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_0612/platform.rtf
@@ -0,0 +1 @@
+The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/Inia_adrenal_rma_0612/processing.rtf b/general/datasets/Inia_adrenal_rma_0612/processing.rtf
new file mode 100644
index 0000000..55aad2e
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_0612/processing.rtf
@@ -0,0 +1 @@
+Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/Inia_adrenal_rma_0612/summary.rtf b/general/datasets/Inia_adrenal_rma_0612/summary.rtf
new file mode 100644
index 0000000..9858a55
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_0612/summary.rtf
@@ -0,0 +1,17 @@
+Preliminary data WITH ERRORS of strain assignment as of July 20, 2012.
+
+Original Assignment had 253 probe sets with LRS >46.
+
+Corrections on Adrenal Data on July 25, 2012:
+R6963A(BXD31).....it should be BXD34
+R7018A(BXD85).....it should be BXD95
+R7152A(C57BL/6J)...it should be B6D2F1
+R7020A(BXD70).......it should be BXD65
+
+229 probe sets with LRS >46 after the corrections above from S. Roy of July 25, July 26 AM.
+
+More corrections from S. Roy (5 PM July 26)
+R6965A(BXD42).........should be BXD2
+R6973A(BXD12).........should be BXD8
+R6985A(BXD34).........should be BXD8
+R7151A(BXD99)..........should be BXD42
diff --git a/general/datasets/Inia_adrenal_rma_0612/tissue.rtf b/general/datasets/Inia_adrenal_rma_0612/tissue.rtf
new file mode 100644
index 0000000..54000a9
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_0612/tissue.rtf
@@ -0,0 +1 @@
+Whole adrenal gland. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/Inia_adrenal_rma_ex_0612/cases.rtf b/general/datasets/Inia_adrenal_rma_ex_0612/cases.rtf
new file mode 100644
index 0000000..f0b204b
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_ex_0612/cases.rtf
@@ -0,0 +1,771 @@
+Young adult mice raised in specific pathogen-free vivarium at UTHSC.
+Table 1. Final strain correction by Khyobeni Mozhui on Mar 28, 2013.
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Tissue |
+ Sex |
+
+
+ | 1 |
+ R6947A |
+ BXD48 |
+ Adrenal |
+ M |
+
+
+ | 2 |
+ R6948A |
+ BXD90 |
+ Adrenal |
+ M |
+
+
+ | 3 |
+ R6949A |
+ BXD97 |
+ Adrenal |
+ M |
+
+
+ | 4 |
+ R6950A |
+ BXD87 |
+ Adrenal |
+ M |
+
+
+ | 5 |
+ R6952A |
+ BXD83 |
+ Adrenal |
+ F |
+
+
+ | 6 |
+ R6953A |
+ BXD67 |
+ Adrenal |
+ M |
+
+
+ | 7 |
+ R6954A |
+ BXD56 |
+ Adrenal |
+ M |
+
+
+ | 8 |
+ R6955A |
+ BXD48 |
+ Adrenal |
+ F |
+
+
+ | 9 |
+ R6956A |
+ BXD90 |
+ Adrenal |
+ F |
+
+
+ | 10 |
+ R6957A |
+ BXD89 |
+ Adrenal |
+ M |
+
+
+ | 11 |
+ R6958A |
+ BXD65 |
+ Adrenal |
+ M |
+
+
+ | 12 |
+ R6959A |
+ BXD65 |
+ Adrenal |
+ F |
+
+
+ | 13 |
+ R6960A |
+ BXD63 |
+ Adrenal |
+ F |
+
+
+ | 14 |
+ R6961A |
+ BXD63 |
+ Adrenal |
+ M |
+
+
+ | 15 |
+ R6963A |
+ BXD31 |
+ Adrenal |
+ M |
+
+
+ | 16 |
+ R6964A |
+ BXD31 |
+ Adrenal |
+ F |
+
+
+ | 17 |
+ R6965A |
+ BXD1 |
+ Adrenal |
+ F |
+
+
+ | 18 |
+ R6966A |
+ BXD1 |
+ Adrenal |
+ F |
+
+
+ | 19 |
+ R6967A |
+ BXD24 |
+ Adrenal |
+ F |
+
+
+ | 20 |
+ R6968A |
+ BXD34 |
+ Adrenal |
+ M |
+
+
+ | 21 |
+ R6969A |
+ BXD1 |
+ Adrenal |
+ M |
+
+
+ | 22 |
+ R6971A |
+ BXD27 |
+ Adrenal |
+ F |
+
+
+ | 23 |
+ R6972A |
+ BXD29 |
+ Adrenal |
+ M |
+
+
+ | 24 |
+ R6973A |
+ BXD12 |
+ Adrenal |
+ F |
+
+
+ | 25 |
+ R6974A |
+ BXD14 |
+ Adrenal |
+ F |
+
+
+ | 26 |
+ R6975A |
+ BXD99 |
+ Adrenal |
+ F |
+
+
+ | 27 |
+ R6976A |
+ BXD32 |
+ Adrenal |
+ F |
+
+
+ | 28 |
+ R6977A |
+ BXD97 |
+ Adrenal |
+ F |
+
+
+ | 29 |
+ R6978A |
+ BXD84 |
+ Adrenal |
+ M |
+
+
+ | 30 |
+ R6979A |
+ BXD39 |
+ Adrenal |
+ M |
+
+
+ | 31 |
+ R6980A |
+ BXD24 |
+ Adrenal |
+ M |
+
+
+ | 32 |
+ R6981A |
+ BXD50 |
+ Adrenal |
+ F |
+
+
+ | 33 |
+ R6982A |
+ BXD75 |
+ Adrenal |
+ M |
+
+
+ | 34 |
+ R6983A |
+ BXD42 |
+ Adrenal |
+ M |
+
+
+ | 35 |
+ R6984A |
+ BXD39 |
+ Adrenal |
+ F |
+
+
+ | 36 |
+ R6985A |
+ BXD34 |
+ Adrenal |
+ F |
+
+
+ | 37 |
+ R6986A |
+ BXD87 |
+ Adrenal |
+ F |
+
+
+ | 38 |
+ R6987A |
+ BXD50 |
+ Adrenal |
+ M |
+
+
+ | 39 |
+ R6989A |
+ BXD62 |
+ Adrenal |
+ M |
+
+
+ | 40 |
+ R6990A |
+ BXD70 |
+ Adrenal |
+ M |
+
+
+ | 41 |
+ R6991A |
+ BXD64 |
+ Adrenal |
+ F |
+
+
+ | 42 |
+ R6992A |
+ BXD84 |
+ Adrenal |
+ F |
+
+
+ | 43 |
+ R6993A |
+ BXD100 |
+ Adrenal |
+ F |
+
+
+ | 44 |
+ R6994A |
+ BXD62 |
+ Adrenal |
+ F |
+
+
+ | 45 |
+ R6996A |
+ BXD95 |
+ Adrenal |
+ M |
+
+
+ | 46 |
+ R6998A |
+ BXD32 |
+ Adrenal |
+ M |
+
+
+ | 47 |
+ R6999A |
+ BXD101 |
+ Adrenal |
+ F |
+
+
+ | 48 |
+ R7000A |
+ BXD49 |
+ Adrenal |
+ M |
+
+
+ | 49 |
+ R7002A |
+ BXD11 |
+ Adrenal |
+ M |
+
+
+ | 50 |
+ R7003A |
+ BXD100 |
+ Adrenal |
+ M |
+
+
+ | 51 |
+ R7004A |
+ BXD43 |
+ Adrenal |
+ F |
+
+
+ | 52 |
+ R7005A |
+ BXD103 |
+ Adrenal |
+ M |
+
+
+ | 53 |
+ R7006A |
+ BXD73 |
+ Adrenal |
+ F |
+
+
+ | 54 |
+ R7008A |
+ BXD43 |
+ Adrenal |
+ M |
+
+
+ | 55 |
+ R7009A |
+ BXD102 |
+ Adrenal |
+ F |
+
+
+ | 56 |
+ R7010A |
+ BXD69 |
+ Adrenal |
+ F |
+
+
+ | 57 |
+ R7011A |
+ BXD60 |
+ Adrenal |
+ M |
+
+
+ | 58 |
+ R7012A |
+ BXD45 |
+ Adrenal |
+ F |
+
+
+ | 59 |
+ R7013A |
+ BXD79 |
+ Adrenal |
+ M |
+
+
+ | 60 |
+ R7014A |
+ BXD40 |
+ Adrenal |
+ M |
+
+
+ | 61 |
+ R7015A |
+ BXD79 |
+ Adrenal |
+ F |
+
+
+ | 62 |
+ R7016A |
+ BXD40 |
+ Adrenal |
+ F |
+
+
+ | 63 |
+ R7017A |
+ BXD68 |
+ Adrenal |
+ F |
+
+
+ | 64 |
+ R7018A |
+ BXD85 |
+ Adrenal |
+ F |
+
+
+ | 65 |
+ R7019A |
+ BXD44 |
+ Adrenal |
+ F |
+
+
+ | 66 |
+ R7020A |
+ BXD70 |
+ Adrenal |
+ F |
+
+
+ | 67 |
+ R7021A |
+ BXD68 |
+ Adrenal |
+ M |
+
+
+ | 68 |
+ R7023A |
+ BXD44 |
+ Adrenal |
+ M |
+
+
+ | 69 |
+ R7024A |
+ BXD95 |
+ Adrenal |
+ F |
+
+
+ | 70 |
+ R7025A |
+ BXD56 |
+ Adrenal |
+ F |
+
+
+ | 71 |
+ R7032A |
+ BXD103 |
+ Adrenal |
+ F |
+
+
+ | 72 |
+ R7034A |
+ BXD24 |
+ Adrenal |
+ F |
+
+
+ | 73 |
+ R7035A |
+ BXD101 |
+ Adrenal |
+ M |
+
+
+ | 74 |
+ R7036A |
+ BXD29 |
+ Adrenal |
+ F |
+
+
+ | 75 |
+ R7037A |
+ BXD60 |
+ Adrenal |
+ F |
+
+
+ | 76 |
+ R7038A |
+ BXD69 |
+ Adrenal |
+ M |
+
+
+ | 77 |
+ R7039A |
+ BXD73 |
+ Adrenal |
+ M |
+
+
+ | 78 |
+ R7040A |
+ BXD80 |
+ Adrenal |
+ M |
+
+
+ | 79 |
+ R7041A |
+ BXD11 |
+ Adrenal |
+ F |
+
+
+ | 80 |
+ R7042A |
+ BXD74 |
+ Adrenal |
+ F |
+
+
+ | 81 |
+ R7043A |
+ BXD67 |
+ Adrenal |
+ F |
+
+
+ | 82 |
+ R7044A |
+ BXD67 |
+ Adrenal |
+ M |
+
+
+ | 83 |
+ R7046A |
+ C57BL/6J |
+ Adrenal |
+ F |
+
+
+ | 84 |
+ R7047A |
+ D2B6F1 |
+ Adrenal |
+ F |
+
+
+ | 85 |
+ R7048A |
+ B6D2F1 |
+ Adrenal |
+ M |
+
+
+ | 86 |
+ R7051A |
+ BXD80 |
+ Adrenal |
+ F |
+
+
+ | 87 |
+ R7053A |
+ BXD102 |
+ Adrenal |
+ M |
+
+
+ | 88 |
+ R7054A |
+ BXD49 |
+ Adrenal |
+ F |
+
+
+ | 89 |
+ R7055A |
+ BXD77 |
+ Adrenal |
+ F |
+
+
+ | 90 |
+ R7056A |
+ BXD77 |
+ Adrenal |
+ M |
+
+
+ | 91 |
+ R7057A |
+ BXD66 |
+ Adrenal |
+ M |
+
+
+ | 92 |
+ R7058A |
+ BXD66 |
+ Adrenal |
+ F |
+
+
+ | 93 |
+ R7059A |
+ BXD45 |
+ Adrenal |
+ F |
+
+
+ | 94 |
+ R7145A |
+ BXD67 |
+ Adrenal |
+ M |
+
+
+ | 95 |
+ R7147A |
+ BXD85 |
+ Adrenal |
+ M |
+
+
+ | 96 |
+ R7148A |
+ DBA/2J |
+ Adrenal |
+ F |
+
+
+ | 97 |
+ R7149A |
+ D2B6F1 |
+ Adrenal |
+ M |
+
+
+ | 98 |
+ R7150A |
+ D2B6F1 |
+ Adrenal |
+ F |
+
+
+ | 99 |
+ R7151A |
+ BXD27 |
+ Adrenal |
+ M |
+
+
+ | 100 |
+ R7152A |
+ B6D2F1 |
+ Adrenal |
+ M |
+
+
+ | 101 |
+ R7153A |
+ DBA/2J |
+ Adrenal |
+ M |
+
+
+ | 102 |
+ R7159A |
+ C57BL/6J |
+ Adrenal |
+ F |
+
+
+ | 103 |
+ R7161A |
+ C57BL/6J |
+ Adrenal |
+ M |
+
+
+ | 104 |
+ R7164A |
+ B6D2F1 |
+ Adrenal |
+ F |
+
+
+ | 105 |
+ R7166A |
+ B6D2F1 |
+ Adrenal |
+ M |
+
+
+ | 106 |
+ R7167A |
+ DBA/2J |
+ Adrenal |
+ F |
+
+
+ | 107 |
+ R7168A |
+ DBA/2J |
+ Adrenal |
+ M |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Inia_adrenal_rma_ex_0612/experiment-design.rtf b/general/datasets/Inia_adrenal_rma_ex_0612/experiment-design.rtf
new file mode 100644
index 0000000..b069873
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_ex_0612/experiment-design.rtf
@@ -0,0 +1,3 @@
+Normative expression in the adrenals (whole organ) of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
+
+Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/Inia_adrenal_rma_ex_0612/platform.rtf b/general/datasets/Inia_adrenal_rma_ex_0612/platform.rtf
new file mode 100644
index 0000000..7057d48
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_ex_0612/platform.rtf
@@ -0,0 +1 @@
+The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/Inia_adrenal_rma_ex_0612/processing.rtf b/general/datasets/Inia_adrenal_rma_ex_0612/processing.rtf
new file mode 100644
index 0000000..55aad2e
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_ex_0612/processing.rtf
@@ -0,0 +1 @@
+Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/Inia_adrenal_rma_ex_0612/summary.rtf b/general/datasets/Inia_adrenal_rma_ex_0612/summary.rtf
new file mode 100644
index 0000000..9858a55
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_ex_0612/summary.rtf
@@ -0,0 +1,17 @@
+Preliminary data WITH ERRORS of strain assignment as of July 20, 2012.
+
+Original Assignment had 253 probe sets with LRS >46.
+
+Corrections on Adrenal Data on July 25, 2012:
+R6963A(BXD31).....it should be BXD34
+R7018A(BXD85).....it should be BXD95
+R7152A(C57BL/6J)...it should be B6D2F1
+R7020A(BXD70).......it should be BXD65
+
+229 probe sets with LRS >46 after the corrections above from S. Roy of July 25, July 26 AM.
+
+More corrections from S. Roy (5 PM July 26)
+R6965A(BXD42).........should be BXD2
+R6973A(BXD12).........should be BXD8
+R6985A(BXD34).........should be BXD8
+R7151A(BXD99)..........should be BXD42
diff --git a/general/datasets/Inia_adrenal_rma_ex_0612/tissue.rtf b/general/datasets/Inia_adrenal_rma_ex_0612/tissue.rtf
new file mode 100644
index 0000000..54000a9
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_ex_0612/tissue.rtf
@@ -0,0 +1 @@
+Whole adrenal gland. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/Inia_adrenal_rma_f_0612/cases.rtf b/general/datasets/Inia_adrenal_rma_f_0612/cases.rtf
new file mode 100644
index 0000000..f0b204b
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_f_0612/cases.rtf
@@ -0,0 +1,771 @@
+Young adult mice raised in specific pathogen-free vivarium at UTHSC.
+Table 1. Final strain correction by Khyobeni Mozhui on Mar 28, 2013.
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Tissue |
+ Sex |
+
+
+ | 1 |
+ R6947A |
+ BXD48 |
+ Adrenal |
+ M |
+
+
+ | 2 |
+ R6948A |
+ BXD90 |
+ Adrenal |
+ M |
+
+
+ | 3 |
+ R6949A |
+ BXD97 |
+ Adrenal |
+ M |
+
+
+ | 4 |
+ R6950A |
+ BXD87 |
+ Adrenal |
+ M |
+
+
+ | 5 |
+ R6952A |
+ BXD83 |
+ Adrenal |
+ F |
+
+
+ | 6 |
+ R6953A |
+ BXD67 |
+ Adrenal |
+ M |
+
+
+ | 7 |
+ R6954A |
+ BXD56 |
+ Adrenal |
+ M |
+
+
+ | 8 |
+ R6955A |
+ BXD48 |
+ Adrenal |
+ F |
+
+
+ | 9 |
+ R6956A |
+ BXD90 |
+ Adrenal |
+ F |
+
+
+ | 10 |
+ R6957A |
+ BXD89 |
+ Adrenal |
+ M |
+
+
+ | 11 |
+ R6958A |
+ BXD65 |
+ Adrenal |
+ M |
+
+
+ | 12 |
+ R6959A |
+ BXD65 |
+ Adrenal |
+ F |
+
+
+ | 13 |
+ R6960A |
+ BXD63 |
+ Adrenal |
+ F |
+
+
+ | 14 |
+ R6961A |
+ BXD63 |
+ Adrenal |
+ M |
+
+
+ | 15 |
+ R6963A |
+ BXD31 |
+ Adrenal |
+ M |
+
+
+ | 16 |
+ R6964A |
+ BXD31 |
+ Adrenal |
+ F |
+
+
+ | 17 |
+ R6965A |
+ BXD1 |
+ Adrenal |
+ F |
+
+
+ | 18 |
+ R6966A |
+ BXD1 |
+ Adrenal |
+ F |
+
+
+ | 19 |
+ R6967A |
+ BXD24 |
+ Adrenal |
+ F |
+
+
+ | 20 |
+ R6968A |
+ BXD34 |
+ Adrenal |
+ M |
+
+
+ | 21 |
+ R6969A |
+ BXD1 |
+ Adrenal |
+ M |
+
+
+ | 22 |
+ R6971A |
+ BXD27 |
+ Adrenal |
+ F |
+
+
+ | 23 |
+ R6972A |
+ BXD29 |
+ Adrenal |
+ M |
+
+
+ | 24 |
+ R6973A |
+ BXD12 |
+ Adrenal |
+ F |
+
+
+ | 25 |
+ R6974A |
+ BXD14 |
+ Adrenal |
+ F |
+
+
+ | 26 |
+ R6975A |
+ BXD99 |
+ Adrenal |
+ F |
+
+
+ | 27 |
+ R6976A |
+ BXD32 |
+ Adrenal |
+ F |
+
+
+ | 28 |
+ R6977A |
+ BXD97 |
+ Adrenal |
+ F |
+
+
+ | 29 |
+ R6978A |
+ BXD84 |
+ Adrenal |
+ M |
+
+
+ | 30 |
+ R6979A |
+ BXD39 |
+ Adrenal |
+ M |
+
+
+ | 31 |
+ R6980A |
+ BXD24 |
+ Adrenal |
+ M |
+
+
+ | 32 |
+ R6981A |
+ BXD50 |
+ Adrenal |
+ F |
+
+
+ | 33 |
+ R6982A |
+ BXD75 |
+ Adrenal |
+ M |
+
+
+ | 34 |
+ R6983A |
+ BXD42 |
+ Adrenal |
+ M |
+
+
+ | 35 |
+ R6984A |
+ BXD39 |
+ Adrenal |
+ F |
+
+
+ | 36 |
+ R6985A |
+ BXD34 |
+ Adrenal |
+ F |
+
+
+ | 37 |
+ R6986A |
+ BXD87 |
+ Adrenal |
+ F |
+
+
+ | 38 |
+ R6987A |
+ BXD50 |
+ Adrenal |
+ M |
+
+
+ | 39 |
+ R6989A |
+ BXD62 |
+ Adrenal |
+ M |
+
+
+ | 40 |
+ R6990A |
+ BXD70 |
+ Adrenal |
+ M |
+
+
+ | 41 |
+ R6991A |
+ BXD64 |
+ Adrenal |
+ F |
+
+
+ | 42 |
+ R6992A |
+ BXD84 |
+ Adrenal |
+ F |
+
+
+ | 43 |
+ R6993A |
+ BXD100 |
+ Adrenal |
+ F |
+
+
+ | 44 |
+ R6994A |
+ BXD62 |
+ Adrenal |
+ F |
+
+
+ | 45 |
+ R6996A |
+ BXD95 |
+ Adrenal |
+ M |
+
+
+ | 46 |
+ R6998A |
+ BXD32 |
+ Adrenal |
+ M |
+
+
+ | 47 |
+ R6999A |
+ BXD101 |
+ Adrenal |
+ F |
+
+
+ | 48 |
+ R7000A |
+ BXD49 |
+ Adrenal |
+ M |
+
+
+ | 49 |
+ R7002A |
+ BXD11 |
+ Adrenal |
+ M |
+
+
+ | 50 |
+ R7003A |
+ BXD100 |
+ Adrenal |
+ M |
+
+
+ | 51 |
+ R7004A |
+ BXD43 |
+ Adrenal |
+ F |
+
+
+ | 52 |
+ R7005A |
+ BXD103 |
+ Adrenal |
+ M |
+
+
+ | 53 |
+ R7006A |
+ BXD73 |
+ Adrenal |
+ F |
+
+
+ | 54 |
+ R7008A |
+ BXD43 |
+ Adrenal |
+ M |
+
+
+ | 55 |
+ R7009A |
+ BXD102 |
+ Adrenal |
+ F |
+
+
+ | 56 |
+ R7010A |
+ BXD69 |
+ Adrenal |
+ F |
+
+
+ | 57 |
+ R7011A |
+ BXD60 |
+ Adrenal |
+ M |
+
+
+ | 58 |
+ R7012A |
+ BXD45 |
+ Adrenal |
+ F |
+
+
+ | 59 |
+ R7013A |
+ BXD79 |
+ Adrenal |
+ M |
+
+
+ | 60 |
+ R7014A |
+ BXD40 |
+ Adrenal |
+ M |
+
+
+ | 61 |
+ R7015A |
+ BXD79 |
+ Adrenal |
+ F |
+
+
+ | 62 |
+ R7016A |
+ BXD40 |
+ Adrenal |
+ F |
+
+
+ | 63 |
+ R7017A |
+ BXD68 |
+ Adrenal |
+ F |
+
+
+ | 64 |
+ R7018A |
+ BXD85 |
+ Adrenal |
+ F |
+
+
+ | 65 |
+ R7019A |
+ BXD44 |
+ Adrenal |
+ F |
+
+
+ | 66 |
+ R7020A |
+ BXD70 |
+ Adrenal |
+ F |
+
+
+ | 67 |
+ R7021A |
+ BXD68 |
+ Adrenal |
+ M |
+
+
+ | 68 |
+ R7023A |
+ BXD44 |
+ Adrenal |
+ M |
+
+
+ | 69 |
+ R7024A |
+ BXD95 |
+ Adrenal |
+ F |
+
+
+ | 70 |
+ R7025A |
+ BXD56 |
+ Adrenal |
+ F |
+
+
+ | 71 |
+ R7032A |
+ BXD103 |
+ Adrenal |
+ F |
+
+
+ | 72 |
+ R7034A |
+ BXD24 |
+ Adrenal |
+ F |
+
+
+ | 73 |
+ R7035A |
+ BXD101 |
+ Adrenal |
+ M |
+
+
+ | 74 |
+ R7036A |
+ BXD29 |
+ Adrenal |
+ F |
+
+
+ | 75 |
+ R7037A |
+ BXD60 |
+ Adrenal |
+ F |
+
+
+ | 76 |
+ R7038A |
+ BXD69 |
+ Adrenal |
+ M |
+
+
+ | 77 |
+ R7039A |
+ BXD73 |
+ Adrenal |
+ M |
+
+
+ | 78 |
+ R7040A |
+ BXD80 |
+ Adrenal |
+ M |
+
+
+ | 79 |
+ R7041A |
+ BXD11 |
+ Adrenal |
+ F |
+
+
+ | 80 |
+ R7042A |
+ BXD74 |
+ Adrenal |
+ F |
+
+
+ | 81 |
+ R7043A |
+ BXD67 |
+ Adrenal |
+ F |
+
+
+ | 82 |
+ R7044A |
+ BXD67 |
+ Adrenal |
+ M |
+
+
+ | 83 |
+ R7046A |
+ C57BL/6J |
+ Adrenal |
+ F |
+
+
+ | 84 |
+ R7047A |
+ D2B6F1 |
+ Adrenal |
+ F |
+
+
+ | 85 |
+ R7048A |
+ B6D2F1 |
+ Adrenal |
+ M |
+
+
+ | 86 |
+ R7051A |
+ BXD80 |
+ Adrenal |
+ F |
+
+
+ | 87 |
+ R7053A |
+ BXD102 |
+ Adrenal |
+ M |
+
+
+ | 88 |
+ R7054A |
+ BXD49 |
+ Adrenal |
+ F |
+
+
+ | 89 |
+ R7055A |
+ BXD77 |
+ Adrenal |
+ F |
+
+
+ | 90 |
+ R7056A |
+ BXD77 |
+ Adrenal |
+ M |
+
+
+ | 91 |
+ R7057A |
+ BXD66 |
+ Adrenal |
+ M |
+
+
+ | 92 |
+ R7058A |
+ BXD66 |
+ Adrenal |
+ F |
+
+
+ | 93 |
+ R7059A |
+ BXD45 |
+ Adrenal |
+ F |
+
+
+ | 94 |
+ R7145A |
+ BXD67 |
+ Adrenal |
+ M |
+
+
+ | 95 |
+ R7147A |
+ BXD85 |
+ Adrenal |
+ M |
+
+
+ | 96 |
+ R7148A |
+ DBA/2J |
+ Adrenal |
+ F |
+
+
+ | 97 |
+ R7149A |
+ D2B6F1 |
+ Adrenal |
+ M |
+
+
+ | 98 |
+ R7150A |
+ D2B6F1 |
+ Adrenal |
+ F |
+
+
+ | 99 |
+ R7151A |
+ BXD27 |
+ Adrenal |
+ M |
+
+
+ | 100 |
+ R7152A |
+ B6D2F1 |
+ Adrenal |
+ M |
+
+
+ | 101 |
+ R7153A |
+ DBA/2J |
+ Adrenal |
+ M |
+
+
+ | 102 |
+ R7159A |
+ C57BL/6J |
+ Adrenal |
+ F |
+
+
+ | 103 |
+ R7161A |
+ C57BL/6J |
+ Adrenal |
+ M |
+
+
+ | 104 |
+ R7164A |
+ B6D2F1 |
+ Adrenal |
+ F |
+
+
+ | 105 |
+ R7166A |
+ B6D2F1 |
+ Adrenal |
+ M |
+
+
+ | 106 |
+ R7167A |
+ DBA/2J |
+ Adrenal |
+ F |
+
+
+ | 107 |
+ R7168A |
+ DBA/2J |
+ Adrenal |
+ M |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Inia_adrenal_rma_f_0612/experiment-design.rtf b/general/datasets/Inia_adrenal_rma_f_0612/experiment-design.rtf
new file mode 100644
index 0000000..b069873
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_f_0612/experiment-design.rtf
@@ -0,0 +1,3 @@
+Normative expression in the adrenals (whole organ) of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
+
+Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/Inia_adrenal_rma_f_0612/platform.rtf b/general/datasets/Inia_adrenal_rma_f_0612/platform.rtf
new file mode 100644
index 0000000..7057d48
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_f_0612/platform.rtf
@@ -0,0 +1 @@
+The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/Inia_adrenal_rma_f_0612/processing.rtf b/general/datasets/Inia_adrenal_rma_f_0612/processing.rtf
new file mode 100644
index 0000000..55aad2e
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_f_0612/processing.rtf
@@ -0,0 +1 @@
+Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/Inia_adrenal_rma_f_0612/summary.rtf b/general/datasets/Inia_adrenal_rma_f_0612/summary.rtf
new file mode 100644
index 0000000..9858a55
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_f_0612/summary.rtf
@@ -0,0 +1,17 @@
+Preliminary data WITH ERRORS of strain assignment as of July 20, 2012.
+
+Original Assignment had 253 probe sets with LRS >46.
+
+Corrections on Adrenal Data on July 25, 2012:
+R6963A(BXD31).....it should be BXD34
+R7018A(BXD85).....it should be BXD95
+R7152A(C57BL/6J)...it should be B6D2F1
+R7020A(BXD70).......it should be BXD65
+
+229 probe sets with LRS >46 after the corrections above from S. Roy of July 25, July 26 AM.
+
+More corrections from S. Roy (5 PM July 26)
+R6965A(BXD42).........should be BXD2
+R6973A(BXD12).........should be BXD8
+R6985A(BXD34).........should be BXD8
+R7151A(BXD99)..........should be BXD42
diff --git a/general/datasets/Inia_adrenal_rma_f_0612/tissue.rtf b/general/datasets/Inia_adrenal_rma_f_0612/tissue.rtf
new file mode 100644
index 0000000..54000a9
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_f_0612/tissue.rtf
@@ -0,0 +1 @@
+Whole adrenal gland. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/Inia_adrenal_rma_m_0612/cases.rtf b/general/datasets/Inia_adrenal_rma_m_0612/cases.rtf
new file mode 100644
index 0000000..f0b204b
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_m_0612/cases.rtf
@@ -0,0 +1,771 @@
+Young adult mice raised in specific pathogen-free vivarium at UTHSC.
+Table 1. Final strain correction by Khyobeni Mozhui on Mar 28, 2013.
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Tissue |
+ Sex |
+
+
+ | 1 |
+ R6947A |
+ BXD48 |
+ Adrenal |
+ M |
+
+
+ | 2 |
+ R6948A |
+ BXD90 |
+ Adrenal |
+ M |
+
+
+ | 3 |
+ R6949A |
+ BXD97 |
+ Adrenal |
+ M |
+
+
+ | 4 |
+ R6950A |
+ BXD87 |
+ Adrenal |
+ M |
+
+
+ | 5 |
+ R6952A |
+ BXD83 |
+ Adrenal |
+ F |
+
+
+ | 6 |
+ R6953A |
+ BXD67 |
+ Adrenal |
+ M |
+
+
+ | 7 |
+ R6954A |
+ BXD56 |
+ Adrenal |
+ M |
+
+
+ | 8 |
+ R6955A |
+ BXD48 |
+ Adrenal |
+ F |
+
+
+ | 9 |
+ R6956A |
+ BXD90 |
+ Adrenal |
+ F |
+
+
+ | 10 |
+ R6957A |
+ BXD89 |
+ Adrenal |
+ M |
+
+
+ | 11 |
+ R6958A |
+ BXD65 |
+ Adrenal |
+ M |
+
+
+ | 12 |
+ R6959A |
+ BXD65 |
+ Adrenal |
+ F |
+
+
+ | 13 |
+ R6960A |
+ BXD63 |
+ Adrenal |
+ F |
+
+
+ | 14 |
+ R6961A |
+ BXD63 |
+ Adrenal |
+ M |
+
+
+ | 15 |
+ R6963A |
+ BXD31 |
+ Adrenal |
+ M |
+
+
+ | 16 |
+ R6964A |
+ BXD31 |
+ Adrenal |
+ F |
+
+
+ | 17 |
+ R6965A |
+ BXD1 |
+ Adrenal |
+ F |
+
+
+ | 18 |
+ R6966A |
+ BXD1 |
+ Adrenal |
+ F |
+
+
+ | 19 |
+ R6967A |
+ BXD24 |
+ Adrenal |
+ F |
+
+
+ | 20 |
+ R6968A |
+ BXD34 |
+ Adrenal |
+ M |
+
+
+ | 21 |
+ R6969A |
+ BXD1 |
+ Adrenal |
+ M |
+
+
+ | 22 |
+ R6971A |
+ BXD27 |
+ Adrenal |
+ F |
+
+
+ | 23 |
+ R6972A |
+ BXD29 |
+ Adrenal |
+ M |
+
+
+ | 24 |
+ R6973A |
+ BXD12 |
+ Adrenal |
+ F |
+
+
+ | 25 |
+ R6974A |
+ BXD14 |
+ Adrenal |
+ F |
+
+
+ | 26 |
+ R6975A |
+ BXD99 |
+ Adrenal |
+ F |
+
+
+ | 27 |
+ R6976A |
+ BXD32 |
+ Adrenal |
+ F |
+
+
+ | 28 |
+ R6977A |
+ BXD97 |
+ Adrenal |
+ F |
+
+
+ | 29 |
+ R6978A |
+ BXD84 |
+ Adrenal |
+ M |
+
+
+ | 30 |
+ R6979A |
+ BXD39 |
+ Adrenal |
+ M |
+
+
+ | 31 |
+ R6980A |
+ BXD24 |
+ Adrenal |
+ M |
+
+
+ | 32 |
+ R6981A |
+ BXD50 |
+ Adrenal |
+ F |
+
+
+ | 33 |
+ R6982A |
+ BXD75 |
+ Adrenal |
+ M |
+
+
+ | 34 |
+ R6983A |
+ BXD42 |
+ Adrenal |
+ M |
+
+
+ | 35 |
+ R6984A |
+ BXD39 |
+ Adrenal |
+ F |
+
+
+ | 36 |
+ R6985A |
+ BXD34 |
+ Adrenal |
+ F |
+
+
+ | 37 |
+ R6986A |
+ BXD87 |
+ Adrenal |
+ F |
+
+
+ | 38 |
+ R6987A |
+ BXD50 |
+ Adrenal |
+ M |
+
+
+ | 39 |
+ R6989A |
+ BXD62 |
+ Adrenal |
+ M |
+
+
+ | 40 |
+ R6990A |
+ BXD70 |
+ Adrenal |
+ M |
+
+
+ | 41 |
+ R6991A |
+ BXD64 |
+ Adrenal |
+ F |
+
+
+ | 42 |
+ R6992A |
+ BXD84 |
+ Adrenal |
+ F |
+
+
+ | 43 |
+ R6993A |
+ BXD100 |
+ Adrenal |
+ F |
+
+
+ | 44 |
+ R6994A |
+ BXD62 |
+ Adrenal |
+ F |
+
+
+ | 45 |
+ R6996A |
+ BXD95 |
+ Adrenal |
+ M |
+
+
+ | 46 |
+ R6998A |
+ BXD32 |
+ Adrenal |
+ M |
+
+
+ | 47 |
+ R6999A |
+ BXD101 |
+ Adrenal |
+ F |
+
+
+ | 48 |
+ R7000A |
+ BXD49 |
+ Adrenal |
+ M |
+
+
+ | 49 |
+ R7002A |
+ BXD11 |
+ Adrenal |
+ M |
+
+
+ | 50 |
+ R7003A |
+ BXD100 |
+ Adrenal |
+ M |
+
+
+ | 51 |
+ R7004A |
+ BXD43 |
+ Adrenal |
+ F |
+
+
+ | 52 |
+ R7005A |
+ BXD103 |
+ Adrenal |
+ M |
+
+
+ | 53 |
+ R7006A |
+ BXD73 |
+ Adrenal |
+ F |
+
+
+ | 54 |
+ R7008A |
+ BXD43 |
+ Adrenal |
+ M |
+
+
+ | 55 |
+ R7009A |
+ BXD102 |
+ Adrenal |
+ F |
+
+
+ | 56 |
+ R7010A |
+ BXD69 |
+ Adrenal |
+ F |
+
+
+ | 57 |
+ R7011A |
+ BXD60 |
+ Adrenal |
+ M |
+
+
+ | 58 |
+ R7012A |
+ BXD45 |
+ Adrenal |
+ F |
+
+
+ | 59 |
+ R7013A |
+ BXD79 |
+ Adrenal |
+ M |
+
+
+ | 60 |
+ R7014A |
+ BXD40 |
+ Adrenal |
+ M |
+
+
+ | 61 |
+ R7015A |
+ BXD79 |
+ Adrenal |
+ F |
+
+
+ | 62 |
+ R7016A |
+ BXD40 |
+ Adrenal |
+ F |
+
+
+ | 63 |
+ R7017A |
+ BXD68 |
+ Adrenal |
+ F |
+
+
+ | 64 |
+ R7018A |
+ BXD85 |
+ Adrenal |
+ F |
+
+
+ | 65 |
+ R7019A |
+ BXD44 |
+ Adrenal |
+ F |
+
+
+ | 66 |
+ R7020A |
+ BXD70 |
+ Adrenal |
+ F |
+
+
+ | 67 |
+ R7021A |
+ BXD68 |
+ Adrenal |
+ M |
+
+
+ | 68 |
+ R7023A |
+ BXD44 |
+ Adrenal |
+ M |
+
+
+ | 69 |
+ R7024A |
+ BXD95 |
+ Adrenal |
+ F |
+
+
+ | 70 |
+ R7025A |
+ BXD56 |
+ Adrenal |
+ F |
+
+
+ | 71 |
+ R7032A |
+ BXD103 |
+ Adrenal |
+ F |
+
+
+ | 72 |
+ R7034A |
+ BXD24 |
+ Adrenal |
+ F |
+
+
+ | 73 |
+ R7035A |
+ BXD101 |
+ Adrenal |
+ M |
+
+
+ | 74 |
+ R7036A |
+ BXD29 |
+ Adrenal |
+ F |
+
+
+ | 75 |
+ R7037A |
+ BXD60 |
+ Adrenal |
+ F |
+
+
+ | 76 |
+ R7038A |
+ BXD69 |
+ Adrenal |
+ M |
+
+
+ | 77 |
+ R7039A |
+ BXD73 |
+ Adrenal |
+ M |
+
+
+ | 78 |
+ R7040A |
+ BXD80 |
+ Adrenal |
+ M |
+
+
+ | 79 |
+ R7041A |
+ BXD11 |
+ Adrenal |
+ F |
+
+
+ | 80 |
+ R7042A |
+ BXD74 |
+ Adrenal |
+ F |
+
+
+ | 81 |
+ R7043A |
+ BXD67 |
+ Adrenal |
+ F |
+
+
+ | 82 |
+ R7044A |
+ BXD67 |
+ Adrenal |
+ M |
+
+
+ | 83 |
+ R7046A |
+ C57BL/6J |
+ Adrenal |
+ F |
+
+
+ | 84 |
+ R7047A |
+ D2B6F1 |
+ Adrenal |
+ F |
+
+
+ | 85 |
+ R7048A |
+ B6D2F1 |
+ Adrenal |
+ M |
+
+
+ | 86 |
+ R7051A |
+ BXD80 |
+ Adrenal |
+ F |
+
+
+ | 87 |
+ R7053A |
+ BXD102 |
+ Adrenal |
+ M |
+
+
+ | 88 |
+ R7054A |
+ BXD49 |
+ Adrenal |
+ F |
+
+
+ | 89 |
+ R7055A |
+ BXD77 |
+ Adrenal |
+ F |
+
+
+ | 90 |
+ R7056A |
+ BXD77 |
+ Adrenal |
+ M |
+
+
+ | 91 |
+ R7057A |
+ BXD66 |
+ Adrenal |
+ M |
+
+
+ | 92 |
+ R7058A |
+ BXD66 |
+ Adrenal |
+ F |
+
+
+ | 93 |
+ R7059A |
+ BXD45 |
+ Adrenal |
+ F |
+
+
+ | 94 |
+ R7145A |
+ BXD67 |
+ Adrenal |
+ M |
+
+
+ | 95 |
+ R7147A |
+ BXD85 |
+ Adrenal |
+ M |
+
+
+ | 96 |
+ R7148A |
+ DBA/2J |
+ Adrenal |
+ F |
+
+
+ | 97 |
+ R7149A |
+ D2B6F1 |
+ Adrenal |
+ M |
+
+
+ | 98 |
+ R7150A |
+ D2B6F1 |
+ Adrenal |
+ F |
+
+
+ | 99 |
+ R7151A |
+ BXD27 |
+ Adrenal |
+ M |
+
+
+ | 100 |
+ R7152A |
+ B6D2F1 |
+ Adrenal |
+ M |
+
+
+ | 101 |
+ R7153A |
+ DBA/2J |
+ Adrenal |
+ M |
+
+
+ | 102 |
+ R7159A |
+ C57BL/6J |
+ Adrenal |
+ F |
+
+
+ | 103 |
+ R7161A |
+ C57BL/6J |
+ Adrenal |
+ M |
+
+
+ | 104 |
+ R7164A |
+ B6D2F1 |
+ Adrenal |
+ F |
+
+
+ | 105 |
+ R7166A |
+ B6D2F1 |
+ Adrenal |
+ M |
+
+
+ | 106 |
+ R7167A |
+ DBA/2J |
+ Adrenal |
+ F |
+
+
+ | 107 |
+ R7168A |
+ DBA/2J |
+ Adrenal |
+ M |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Inia_adrenal_rma_m_0612/experiment-design.rtf b/general/datasets/Inia_adrenal_rma_m_0612/experiment-design.rtf
new file mode 100644
index 0000000..b069873
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_m_0612/experiment-design.rtf
@@ -0,0 +1,3 @@
+Normative expression in the adrenals (whole organ) of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
+
+Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/Inia_adrenal_rma_m_0612/platform.rtf b/general/datasets/Inia_adrenal_rma_m_0612/platform.rtf
new file mode 100644
index 0000000..7057d48
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_m_0612/platform.rtf
@@ -0,0 +1 @@
+The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/Inia_adrenal_rma_m_0612/processing.rtf b/general/datasets/Inia_adrenal_rma_m_0612/processing.rtf
new file mode 100644
index 0000000..55aad2e
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_m_0612/processing.rtf
@@ -0,0 +1 @@
+Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/Inia_adrenal_rma_m_0612/summary.rtf b/general/datasets/Inia_adrenal_rma_m_0612/summary.rtf
new file mode 100644
index 0000000..9858a55
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_m_0612/summary.rtf
@@ -0,0 +1,17 @@
+Preliminary data WITH ERRORS of strain assignment as of July 20, 2012.
+
+Original Assignment had 253 probe sets with LRS >46.
+
+Corrections on Adrenal Data on July 25, 2012:
+R6963A(BXD31).....it should be BXD34
+R7018A(BXD85).....it should be BXD95
+R7152A(C57BL/6J)...it should be B6D2F1
+R7020A(BXD70).......it should be BXD65
+
+229 probe sets with LRS >46 after the corrections above from S. Roy of July 25, July 26 AM.
+
+More corrections from S. Roy (5 PM July 26)
+R6965A(BXD42).........should be BXD2
+R6973A(BXD12).........should be BXD8
+R6985A(BXD34).........should be BXD8
+R7151A(BXD99)..........should be BXD42
diff --git a/general/datasets/Inia_adrenal_rma_m_0612/tissue.rtf b/general/datasets/Inia_adrenal_rma_m_0612/tissue.rtf
new file mode 100644
index 0000000..54000a9
--- /dev/null
+++ b/general/datasets/Inia_adrenal_rma_m_0612/tissue.rtf
@@ -0,0 +1 @@
+Whole adrenal gland. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/Inia_amg_bla_ex_rma_1110/cases.rtf b/general/datasets/Inia_amg_bla_ex_rma_1110/cases.rtf
new file mode 100644
index 0000000..b02b19a
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_ex_rma_1110/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 58 strains, including 54 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1) were analyzed. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by K. Mozhui. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. Fifty strains have matched male and female samples. Five strains have male only samples (BXD5, 13, 16, 100 and 103). Three strains have only female samples (BXD44, 70, and 87.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/Inia_amg_bla_ex_rma_1110/contributors.rtf b/general/datasets/Inia_amg_bla_ex_rma_1110/contributors.rtf
new file mode 100644
index 0000000..f69a44f
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_ex_rma_1110/contributors.rtf
@@ -0,0 +1 @@
+Mozhui K, Williams RW
diff --git a/general/datasets/Inia_amg_bla_ex_rma_1110/experiment-design.rtf b/general/datasets/Inia_amg_bla_ex_rma_1110/experiment-design.rtf
new file mode 100644
index 0000000..126d431
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_ex_rma_1110/experiment-design.rtf
@@ -0,0 +1,1152 @@
+Data Evaluation Summary
+
+
+ - eQLTs with LOD >10 (LRS>46.1): n = 525
+ - eQTL with high LOD and LRS: Trait ID 10513604 (Hdhd3) LOD = 39.8, LRS = 183.5
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6853BL |
+ BLA |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6861BL |
+ BLA |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6851BL |
+ BLA |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6859BL |
+ BLA |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6863BL |
+ BLA |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6865BL |
+ BLA |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6857BL |
+ BLA |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6855BL |
+ BLA |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6799BL |
+ BLA |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6795BL |
+ BLA |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6787BL |
+ BLA |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6785BL |
+ BLA |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6819BL |
+ BLA |
+ BXD12 |
+ 78 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 14 |
+ R6789BL |
+ BLA |
+ BXD12 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 15 |
+ R6805BL |
+ BLA |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6291BL |
+ BLA |
+ BXD13 |
+ N/A |
+ M |
+ 6/11/09 |
+ N/A |
+
+
+ | 17 |
+ R6811BL |
+ BLA |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 18 |
+ R6825BL |
+ BLA |
+ BXD14 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 19 |
+ R6657BL |
+ BLA |
+ BXD16 |
+ N/A |
+ M |
+ 1/8/08 |
+ N/A |
+
+
+ | 20 |
+ R6054BL |
+ BLA |
+ BXD19 |
+ N/A |
+ F |
+ 2/26/08 |
+ N/A |
+
+
+ | 21 |
+ R6052BL |
+ BLA |
+ BXD19 |
+ N/A |
+ M |
+ 2/26/08 |
+ N/A |
+
+
+ | 22 |
+ R6803BL |
+ BLA |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 23 |
+ R6817BL |
+ BLA |
+ BXD24 |
+ 86 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6063BL |
+ BLA |
+ BXD25 |
+ N/A |
+ F |
+ 3/12/08 |
+ N/A |
+
+
+ | 25 |
+ R6062BL |
+ BLA |
+ BXD25 |
+ N/A |
+ M |
+ 3/12/08 |
+ N/A |
+
+
+ | 26 |
+ R6659BL |
+ BLA |
+ BXD27 |
+ N/A |
+ F |
+ 1/8/08 |
+ N/A |
+
+
+ | 27 |
+ R6791BL |
+ BLA |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 28 |
+ R6797BL |
+ BLA |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 29 |
+ R6793BL |
+ BLA |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 30 |
+ R6815BL |
+ BLA |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 31 |
+ R6801BL |
+ BLA |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 32 |
+ R6915BL |
+ BLA |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 33 |
+ R6845BL |
+ BLA |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 34 |
+ R6821BL |
+ BLA |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 35 |
+ R6807BL |
+ BLA |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 36 |
+ R6057BL |
+ BLA |
+ BXD38 |
+ N/A |
+ F |
+ 2/26/08 |
+ N/A |
+
+
+ | 37 |
+ R6056BL |
+ BLA |
+ BXD38 |
+ N/A |
+ M |
+ 2/26/08 |
+ N/A |
+
+
+ | 38 |
+ R6827BL |
+ BLA |
+ BXD39 |
+ 79 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 39 |
+ R6813BL |
+ BLA |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 40 |
+ R6847BL |
+ BLA |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 41 |
+ R6849BL |
+ BLA |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 42 |
+ R6809BL |
+ BLA |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 43 |
+ R6823BL |
+ BLA |
+ BXD42 |
+ 87 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 44 |
+ R6759BL |
+ BLA |
+ BXD43 |
+ 81 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 45 |
+ R6757BL |
+ BLA |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 46 |
+ R6745BL |
+ BLA |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 47 |
+ R6763BL |
+ BLA |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 48 |
+ R6761BL |
+ BLA |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 49 |
+ R6879BL |
+ BLA |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6881BL |
+ BLA |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6751BL |
+ BLA |
+ BXD49 |
+ 84 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 52 |
+ R6747BL |
+ BLA |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 53 |
+ R6104BL |
+ BLA |
+ BXD5 |
+ N/A |
+ f |
+ 10/23/09 |
+ N/A |
+
+
+ | 54 |
+ R6103BL |
+ BLA |
+ BXD5 |
+ N/A |
+ M |
+ 10/23/09 |
+ N/A |
+
+
+ | 55 |
+ R6889BL |
+ BLA |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6891BL |
+ BLA |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6074BL |
+ BLA |
+ BXD51 |
+ N/A |
+ F |
+ 3/12/08 |
+ N/A |
+
+
+ | 58 |
+ R6699BL |
+ BLA |
+ BXD51 |
+ N/A |
+ M |
+ 4/30/09 |
+ N/A |
+
+
+ | 59 |
+ R6917BL |
+ BLA |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 60 |
+ R6893BL |
+ BLA |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 61 |
+ R6769BL |
+ BLA |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 62 |
+ R6771BL |
+ BLA |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6655BL |
+ BLA |
+ BXD61 |
+ N/A |
+ F |
+ 1/29/08 |
+ N/A |
+
+
+ | 64 |
+ R6653BL |
+ BLA |
+ BXD61 |
+ N/A |
+ M |
+ 1/29/08 |
+ N/A |
+
+
+ | 65 |
+ R6835BL |
+ BLA |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 66 |
+ R6843BL |
+ BLA |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6887BL |
+ BLA |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6885BL |
+ BLA |
+ BXD63 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6877BL |
+ BLA |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6873BL |
+ BLA |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6929BL |
+ BLA |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6931BL |
+ BLA |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6775BL |
+ BLA |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 74 |
+ R6773BL |
+ BLA |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 75 |
+ R6925BL |
+ BLA |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6921BL |
+ BLA |
+ BXD70 |
+ 76 |
+ M |
+ 8/17/06 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6869BL |
+ BLA |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6871BL |
+ BLA |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 79 |
+ R6777BL |
+ BLA |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 80 |
+ R6779BL |
+ BLA |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 81 |
+ R6837BL |
+ BLA |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 82 |
+ R6829BL |
+ BLA |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 83 |
+ R6933BL |
+ BLA |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 84 |
+ R6935BL |
+ BLA |
+ BXD79 |
+ 87 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 85 |
+ R6781BL |
+ BLA |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 86 |
+ R6783BL |
+ BLA |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 87 |
+ R6913BL |
+ BLA |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 88 |
+ R6911BL |
+ BLA |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 89 |
+ R6841BL |
+ BLA |
+ BXD84 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 90 |
+ R6833BL |
+ BLA |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 91 |
+ R6937BL |
+ BLA |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 92 |
+ R6939BL |
+ BLA |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 93 |
+ R6909BL |
+ BLA |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 94 |
+ R6895BL |
+ BLA |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 95 |
+ R6897BL |
+ BLA |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 96 |
+ R6903BL |
+ BLA |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 97 |
+ R6905BL |
+ BLA |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 98 |
+ R6923BL |
+ BLA |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 99 |
+ R6927BL |
+ BLA |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 100 |
+ R6919BL |
+ BLA |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 101 |
+ R6867BL |
+ BLA |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 102 |
+ R6899BL |
+ BLA |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 103 |
+ R6901BL |
+ BLA |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 104 |
+ R6875BL |
+ BLA |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 105 |
+ R6883BL |
+ BLA |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 106 |
+ R6831BL |
+ BLA |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 107 |
+ R6943BL |
+ BLA |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 108 |
+ R6941BL |
+ BLA |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 109 |
+ R6753BL |
+ BLA |
+ BXD102 |
+ 88 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 110 |
+ R6755BL |
+ BLA |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 111 |
+ R6765BL |
+ BLA |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/Inia_amg_bla_ex_rma_1110/platform.rtf b/general/datasets/Inia_amg_bla_ex_rma_1110/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_ex_rma_1110/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_amg_bla_ex_rma_1110/processing.rtf b/general/datasets/Inia_amg_bla_ex_rma_1110/processing.rtf
new file mode 100644
index 0000000..a2a6c30
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_ex_rma_1110/processing.rtf
@@ -0,0 +1,16 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required no initial correction for batch effects and the data in this initial release do not incorporate any additional corrections. However, there are several confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Dissection variation: examine and use probe sets for Ttr as a correction for the inclusion of choroid plexus and non-parenchmymal tissue in samples. Transthyretin is only expressed in the choroid plexus (PMID 16698124
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the 54 probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases (58) in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest 54 probe sets in this amygdala data set accounts of 42% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the amygdala data set can be map as a trait. It is not associated with any QLTs that are even suggestive, and the highest LRS is about 10 on chromosomes 18 and 19. The second principal component trait, which accounts for only 5% of the "noise" variance, has a suggestive QTL (LRS of 12, high B allele) on chromosome 4 at about 90 Mb. We therefore do not think that there is significant risk of major false trans eQTL bands in this data set.
+
+
+Data Release. This data set was first uploaded into GeneNetwork November 25, 2010 and made accessible without a password to all users on December 1, 2010. The data set was orginally entered with two strain identification errors that were fixed Dec 10, 2010 by KM Mozhui and A Centeno (array R6659BL was originally listed as BXD16 but is BXD27; R6789BL was original listed as BXD27 is BXD12). The current data release has no known errors of sex or strain assignment.
+
+Data Status and Use. The data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/Inia_amg_bla_ex_rma_1110/specifics.rtf b/general/datasets/Inia_amg_bla_ex_rma_1110/specifics.rtf
new file mode 100644
index 0000000..2400c03
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_ex_rma_1110/specifics.rtf
@@ -0,0 +1 @@
+Exon Level
diff --git a/general/datasets/Inia_amg_bla_ex_rma_1110/summary.rtf b/general/datasets/Inia_amg_bla_ex_rma_1110/summary.rtf
new file mode 100644
index 0000000..41311b7
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_ex_rma_1110/summary.rtf
@@ -0,0 +1 @@
+This is a final error-checked release of an amygdala gene expression data set generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from the NIH NIAAA. The basolateral complex of the amygdala of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/Inia_amg_bla_ex_rma_1110/tissue.rtf b/general/datasets/Inia_amg_bla_ex_rma_1110/tissue.rtf
new file mode 100644
index 0000000..ea556c7
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_ex_rma_1110/tissue.rtf
@@ -0,0 +1,12 @@
+Dissection Protocol
+
+
+ - Animals were sacrificed by cervical dislocation and brains were immediately dissected from the head and stored in RNAlater (www.ambion.com) for 2 to 3 days at 4 deg C in a refrigerator.
+ - Brains were placed with ventral side up on a cutting surface and a partial coronal cut was made with a surgical blade at a level that corresponds approximately to the -2.5 mm behind the stereotaxic Bregma point (this cut is just a little rostral from the pontine fibres when viewed from the ventral side).
+ - Brains were placed in a coronal matrix (egg-style slicer) and a 2-mm thick coronal slab was taken just rostral to the initial cut.
+ - The 2-mm thick slab was placed on a clean glass slide and the hypothalamus was cut out and placed in a tube on dry ice.
+ - To dissect the BLA, the temporal lobes were detached by placing a scalpel in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then cut out and placed in a tube on dry ice.
+ - Tissue from two mice (right and left sides) and from the same strain and sex (an usually the same litter) were pooled. The only exceptions are BLA samples from strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue was obtained from only one animal per array).
+
+
+
diff --git a/general/datasets/Inia_amg_bla_rma_1110/cases.rtf b/general/datasets/Inia_amg_bla_rma_1110/cases.rtf
new file mode 100644
index 0000000..b02b19a
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_1110/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 58 strains, including 54 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1) were analyzed. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by K. Mozhui. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. Fifty strains have matched male and female samples. Five strains have male only samples (BXD5, 13, 16, 100 and 103). Three strains have only female samples (BXD44, 70, and 87.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/Inia_amg_bla_rma_1110/contributors.rtf b/general/datasets/Inia_amg_bla_rma_1110/contributors.rtf
new file mode 100644
index 0000000..f69a44f
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_1110/contributors.rtf
@@ -0,0 +1 @@
+Mozhui K, Williams RW
diff --git a/general/datasets/Inia_amg_bla_rma_1110/experiment-design.rtf b/general/datasets/Inia_amg_bla_rma_1110/experiment-design.rtf
new file mode 100644
index 0000000..126d431
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_1110/experiment-design.rtf
@@ -0,0 +1,1152 @@
+Data Evaluation Summary
+
+
+ - eQLTs with LOD >10 (LRS>46.1): n = 525
+ - eQTL with high LOD and LRS: Trait ID 10513604 (Hdhd3) LOD = 39.8, LRS = 183.5
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6853BL |
+ BLA |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6861BL |
+ BLA |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6851BL |
+ BLA |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6859BL |
+ BLA |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6863BL |
+ BLA |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6865BL |
+ BLA |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6857BL |
+ BLA |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6855BL |
+ BLA |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6799BL |
+ BLA |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6795BL |
+ BLA |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6787BL |
+ BLA |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6785BL |
+ BLA |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6819BL |
+ BLA |
+ BXD12 |
+ 78 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 14 |
+ R6789BL |
+ BLA |
+ BXD12 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 15 |
+ R6805BL |
+ BLA |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6291BL |
+ BLA |
+ BXD13 |
+ N/A |
+ M |
+ 6/11/09 |
+ N/A |
+
+
+ | 17 |
+ R6811BL |
+ BLA |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 18 |
+ R6825BL |
+ BLA |
+ BXD14 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 19 |
+ R6657BL |
+ BLA |
+ BXD16 |
+ N/A |
+ M |
+ 1/8/08 |
+ N/A |
+
+
+ | 20 |
+ R6054BL |
+ BLA |
+ BXD19 |
+ N/A |
+ F |
+ 2/26/08 |
+ N/A |
+
+
+ | 21 |
+ R6052BL |
+ BLA |
+ BXD19 |
+ N/A |
+ M |
+ 2/26/08 |
+ N/A |
+
+
+ | 22 |
+ R6803BL |
+ BLA |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 23 |
+ R6817BL |
+ BLA |
+ BXD24 |
+ 86 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6063BL |
+ BLA |
+ BXD25 |
+ N/A |
+ F |
+ 3/12/08 |
+ N/A |
+
+
+ | 25 |
+ R6062BL |
+ BLA |
+ BXD25 |
+ N/A |
+ M |
+ 3/12/08 |
+ N/A |
+
+
+ | 26 |
+ R6659BL |
+ BLA |
+ BXD27 |
+ N/A |
+ F |
+ 1/8/08 |
+ N/A |
+
+
+ | 27 |
+ R6791BL |
+ BLA |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 28 |
+ R6797BL |
+ BLA |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 29 |
+ R6793BL |
+ BLA |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 30 |
+ R6815BL |
+ BLA |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 31 |
+ R6801BL |
+ BLA |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 32 |
+ R6915BL |
+ BLA |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 33 |
+ R6845BL |
+ BLA |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 34 |
+ R6821BL |
+ BLA |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 35 |
+ R6807BL |
+ BLA |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 36 |
+ R6057BL |
+ BLA |
+ BXD38 |
+ N/A |
+ F |
+ 2/26/08 |
+ N/A |
+
+
+ | 37 |
+ R6056BL |
+ BLA |
+ BXD38 |
+ N/A |
+ M |
+ 2/26/08 |
+ N/A |
+
+
+ | 38 |
+ R6827BL |
+ BLA |
+ BXD39 |
+ 79 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 39 |
+ R6813BL |
+ BLA |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 40 |
+ R6847BL |
+ BLA |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 41 |
+ R6849BL |
+ BLA |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 42 |
+ R6809BL |
+ BLA |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 43 |
+ R6823BL |
+ BLA |
+ BXD42 |
+ 87 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 44 |
+ R6759BL |
+ BLA |
+ BXD43 |
+ 81 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 45 |
+ R6757BL |
+ BLA |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 46 |
+ R6745BL |
+ BLA |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 47 |
+ R6763BL |
+ BLA |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 48 |
+ R6761BL |
+ BLA |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 49 |
+ R6879BL |
+ BLA |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6881BL |
+ BLA |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6751BL |
+ BLA |
+ BXD49 |
+ 84 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 52 |
+ R6747BL |
+ BLA |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 53 |
+ R6104BL |
+ BLA |
+ BXD5 |
+ N/A |
+ f |
+ 10/23/09 |
+ N/A |
+
+
+ | 54 |
+ R6103BL |
+ BLA |
+ BXD5 |
+ N/A |
+ M |
+ 10/23/09 |
+ N/A |
+
+
+ | 55 |
+ R6889BL |
+ BLA |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6891BL |
+ BLA |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6074BL |
+ BLA |
+ BXD51 |
+ N/A |
+ F |
+ 3/12/08 |
+ N/A |
+
+
+ | 58 |
+ R6699BL |
+ BLA |
+ BXD51 |
+ N/A |
+ M |
+ 4/30/09 |
+ N/A |
+
+
+ | 59 |
+ R6917BL |
+ BLA |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 60 |
+ R6893BL |
+ BLA |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 61 |
+ R6769BL |
+ BLA |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 62 |
+ R6771BL |
+ BLA |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6655BL |
+ BLA |
+ BXD61 |
+ N/A |
+ F |
+ 1/29/08 |
+ N/A |
+
+
+ | 64 |
+ R6653BL |
+ BLA |
+ BXD61 |
+ N/A |
+ M |
+ 1/29/08 |
+ N/A |
+
+
+ | 65 |
+ R6835BL |
+ BLA |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 66 |
+ R6843BL |
+ BLA |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6887BL |
+ BLA |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6885BL |
+ BLA |
+ BXD63 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6877BL |
+ BLA |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6873BL |
+ BLA |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6929BL |
+ BLA |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6931BL |
+ BLA |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6775BL |
+ BLA |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 74 |
+ R6773BL |
+ BLA |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 75 |
+ R6925BL |
+ BLA |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6921BL |
+ BLA |
+ BXD70 |
+ 76 |
+ M |
+ 8/17/06 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6869BL |
+ BLA |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6871BL |
+ BLA |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 79 |
+ R6777BL |
+ BLA |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 80 |
+ R6779BL |
+ BLA |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 81 |
+ R6837BL |
+ BLA |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 82 |
+ R6829BL |
+ BLA |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 83 |
+ R6933BL |
+ BLA |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 84 |
+ R6935BL |
+ BLA |
+ BXD79 |
+ 87 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 85 |
+ R6781BL |
+ BLA |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 86 |
+ R6783BL |
+ BLA |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 87 |
+ R6913BL |
+ BLA |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 88 |
+ R6911BL |
+ BLA |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 89 |
+ R6841BL |
+ BLA |
+ BXD84 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 90 |
+ R6833BL |
+ BLA |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 91 |
+ R6937BL |
+ BLA |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 92 |
+ R6939BL |
+ BLA |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 93 |
+ R6909BL |
+ BLA |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 94 |
+ R6895BL |
+ BLA |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 95 |
+ R6897BL |
+ BLA |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 96 |
+ R6903BL |
+ BLA |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 97 |
+ R6905BL |
+ BLA |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 98 |
+ R6923BL |
+ BLA |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 99 |
+ R6927BL |
+ BLA |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 100 |
+ R6919BL |
+ BLA |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 101 |
+ R6867BL |
+ BLA |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 102 |
+ R6899BL |
+ BLA |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 103 |
+ R6901BL |
+ BLA |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 104 |
+ R6875BL |
+ BLA |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 105 |
+ R6883BL |
+ BLA |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 106 |
+ R6831BL |
+ BLA |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 107 |
+ R6943BL |
+ BLA |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 108 |
+ R6941BL |
+ BLA |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 109 |
+ R6753BL |
+ BLA |
+ BXD102 |
+ 88 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 110 |
+ R6755BL |
+ BLA |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 111 |
+ R6765BL |
+ BLA |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/Inia_amg_bla_rma_1110/platform.rtf b/general/datasets/Inia_amg_bla_rma_1110/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_1110/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_amg_bla_rma_1110/processing.rtf b/general/datasets/Inia_amg_bla_rma_1110/processing.rtf
new file mode 100644
index 0000000..a2a6c30
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_1110/processing.rtf
@@ -0,0 +1,16 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required no initial correction for batch effects and the data in this initial release do not incorporate any additional corrections. However, there are several confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Dissection variation: examine and use probe sets for Ttr as a correction for the inclusion of choroid plexus and non-parenchmymal tissue in samples. Transthyretin is only expressed in the choroid plexus (PMID 16698124
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the 54 probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases (58) in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest 54 probe sets in this amygdala data set accounts of 42% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the amygdala data set can be map as a trait. It is not associated with any QLTs that are even suggestive, and the highest LRS is about 10 on chromosomes 18 and 19. The second principal component trait, which accounts for only 5% of the "noise" variance, has a suggestive QTL (LRS of 12, high B allele) on chromosome 4 at about 90 Mb. We therefore do not think that there is significant risk of major false trans eQTL bands in this data set.
+
+
+Data Release. This data set was first uploaded into GeneNetwork November 25, 2010 and made accessible without a password to all users on December 1, 2010. The data set was orginally entered with two strain identification errors that were fixed Dec 10, 2010 by KM Mozhui and A Centeno (array R6659BL was originally listed as BXD16 but is BXD27; R6789BL was original listed as BXD27 is BXD12). The current data release has no known errors of sex or strain assignment.
+
+Data Status and Use. The data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/Inia_amg_bla_rma_1110/specifics.rtf b/general/datasets/Inia_amg_bla_rma_1110/specifics.rtf
new file mode 100644
index 0000000..d877bcf
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_1110/specifics.rtf
@@ -0,0 +1 @@
+Gene Level
diff --git a/general/datasets/Inia_amg_bla_rma_1110/summary.rtf b/general/datasets/Inia_amg_bla_rma_1110/summary.rtf
new file mode 100644
index 0000000..41311b7
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_1110/summary.rtf
@@ -0,0 +1 @@
+This is a final error-checked release of an amygdala gene expression data set generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from the NIH NIAAA. The basolateral complex of the amygdala of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/Inia_amg_bla_rma_1110/tissue.rtf b/general/datasets/Inia_amg_bla_rma_1110/tissue.rtf
new file mode 100644
index 0000000..ea556c7
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_1110/tissue.rtf
@@ -0,0 +1,12 @@
+Dissection Protocol
+
+
+ - Animals were sacrificed by cervical dislocation and brains were immediately dissected from the head and stored in RNAlater (www.ambion.com) for 2 to 3 days at 4 deg C in a refrigerator.
+ - Brains were placed with ventral side up on a cutting surface and a partial coronal cut was made with a surgical blade at a level that corresponds approximately to the -2.5 mm behind the stereotaxic Bregma point (this cut is just a little rostral from the pontine fibres when viewed from the ventral side).
+ - Brains were placed in a coronal matrix (egg-style slicer) and a 2-mm thick coronal slab was taken just rostral to the initial cut.
+ - The 2-mm thick slab was placed on a clean glass slide and the hypothalamus was cut out and placed in a tube on dry ice.
+ - To dissect the BLA, the temporal lobes were detached by placing a scalpel in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then cut out and placed in a tube on dry ice.
+ - Tissue from two mice (right and left sides) and from the same strain and sex (an usually the same litter) were pooled. The only exceptions are BLA samples from strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue was obtained from only one animal per array).
+
+
+
diff --git a/general/datasets/Inia_amg_bla_rma_f_1110/cases.rtf b/general/datasets/Inia_amg_bla_rma_f_1110/cases.rtf
new file mode 100644
index 0000000..b02b19a
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_f_1110/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 58 strains, including 54 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1) were analyzed. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by K. Mozhui. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. Fifty strains have matched male and female samples. Five strains have male only samples (BXD5, 13, 16, 100 and 103). Three strains have only female samples (BXD44, 70, and 87.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/Inia_amg_bla_rma_f_1110/contributors.rtf b/general/datasets/Inia_amg_bla_rma_f_1110/contributors.rtf
new file mode 100644
index 0000000..f69a44f
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_f_1110/contributors.rtf
@@ -0,0 +1 @@
+Mozhui K, Williams RW
diff --git a/general/datasets/Inia_amg_bla_rma_f_1110/experiment-design.rtf b/general/datasets/Inia_amg_bla_rma_f_1110/experiment-design.rtf
new file mode 100644
index 0000000..126d431
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_f_1110/experiment-design.rtf
@@ -0,0 +1,1152 @@
+Data Evaluation Summary
+
+
+ - eQLTs with LOD >10 (LRS>46.1): n = 525
+ - eQTL with high LOD and LRS: Trait ID 10513604 (Hdhd3) LOD = 39.8, LRS = 183.5
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6853BL |
+ BLA |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6861BL |
+ BLA |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6851BL |
+ BLA |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6859BL |
+ BLA |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6863BL |
+ BLA |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6865BL |
+ BLA |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6857BL |
+ BLA |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6855BL |
+ BLA |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6799BL |
+ BLA |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6795BL |
+ BLA |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6787BL |
+ BLA |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6785BL |
+ BLA |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6819BL |
+ BLA |
+ BXD12 |
+ 78 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 14 |
+ R6789BL |
+ BLA |
+ BXD12 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 15 |
+ R6805BL |
+ BLA |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6291BL |
+ BLA |
+ BXD13 |
+ N/A |
+ M |
+ 6/11/09 |
+ N/A |
+
+
+ | 17 |
+ R6811BL |
+ BLA |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 18 |
+ R6825BL |
+ BLA |
+ BXD14 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 19 |
+ R6657BL |
+ BLA |
+ BXD16 |
+ N/A |
+ M |
+ 1/8/08 |
+ N/A |
+
+
+ | 20 |
+ R6054BL |
+ BLA |
+ BXD19 |
+ N/A |
+ F |
+ 2/26/08 |
+ N/A |
+
+
+ | 21 |
+ R6052BL |
+ BLA |
+ BXD19 |
+ N/A |
+ M |
+ 2/26/08 |
+ N/A |
+
+
+ | 22 |
+ R6803BL |
+ BLA |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 23 |
+ R6817BL |
+ BLA |
+ BXD24 |
+ 86 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6063BL |
+ BLA |
+ BXD25 |
+ N/A |
+ F |
+ 3/12/08 |
+ N/A |
+
+
+ | 25 |
+ R6062BL |
+ BLA |
+ BXD25 |
+ N/A |
+ M |
+ 3/12/08 |
+ N/A |
+
+
+ | 26 |
+ R6659BL |
+ BLA |
+ BXD27 |
+ N/A |
+ F |
+ 1/8/08 |
+ N/A |
+
+
+ | 27 |
+ R6791BL |
+ BLA |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 28 |
+ R6797BL |
+ BLA |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 29 |
+ R6793BL |
+ BLA |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 30 |
+ R6815BL |
+ BLA |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 31 |
+ R6801BL |
+ BLA |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 32 |
+ R6915BL |
+ BLA |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 33 |
+ R6845BL |
+ BLA |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 34 |
+ R6821BL |
+ BLA |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 35 |
+ R6807BL |
+ BLA |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 36 |
+ R6057BL |
+ BLA |
+ BXD38 |
+ N/A |
+ F |
+ 2/26/08 |
+ N/A |
+
+
+ | 37 |
+ R6056BL |
+ BLA |
+ BXD38 |
+ N/A |
+ M |
+ 2/26/08 |
+ N/A |
+
+
+ | 38 |
+ R6827BL |
+ BLA |
+ BXD39 |
+ 79 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 39 |
+ R6813BL |
+ BLA |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 40 |
+ R6847BL |
+ BLA |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 41 |
+ R6849BL |
+ BLA |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 42 |
+ R6809BL |
+ BLA |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 43 |
+ R6823BL |
+ BLA |
+ BXD42 |
+ 87 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 44 |
+ R6759BL |
+ BLA |
+ BXD43 |
+ 81 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 45 |
+ R6757BL |
+ BLA |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 46 |
+ R6745BL |
+ BLA |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 47 |
+ R6763BL |
+ BLA |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 48 |
+ R6761BL |
+ BLA |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 49 |
+ R6879BL |
+ BLA |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6881BL |
+ BLA |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6751BL |
+ BLA |
+ BXD49 |
+ 84 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 52 |
+ R6747BL |
+ BLA |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 53 |
+ R6104BL |
+ BLA |
+ BXD5 |
+ N/A |
+ f |
+ 10/23/09 |
+ N/A |
+
+
+ | 54 |
+ R6103BL |
+ BLA |
+ BXD5 |
+ N/A |
+ M |
+ 10/23/09 |
+ N/A |
+
+
+ | 55 |
+ R6889BL |
+ BLA |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6891BL |
+ BLA |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6074BL |
+ BLA |
+ BXD51 |
+ N/A |
+ F |
+ 3/12/08 |
+ N/A |
+
+
+ | 58 |
+ R6699BL |
+ BLA |
+ BXD51 |
+ N/A |
+ M |
+ 4/30/09 |
+ N/A |
+
+
+ | 59 |
+ R6917BL |
+ BLA |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 60 |
+ R6893BL |
+ BLA |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 61 |
+ R6769BL |
+ BLA |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 62 |
+ R6771BL |
+ BLA |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6655BL |
+ BLA |
+ BXD61 |
+ N/A |
+ F |
+ 1/29/08 |
+ N/A |
+
+
+ | 64 |
+ R6653BL |
+ BLA |
+ BXD61 |
+ N/A |
+ M |
+ 1/29/08 |
+ N/A |
+
+
+ | 65 |
+ R6835BL |
+ BLA |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 66 |
+ R6843BL |
+ BLA |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6887BL |
+ BLA |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6885BL |
+ BLA |
+ BXD63 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6877BL |
+ BLA |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6873BL |
+ BLA |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6929BL |
+ BLA |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6931BL |
+ BLA |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6775BL |
+ BLA |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 74 |
+ R6773BL |
+ BLA |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 75 |
+ R6925BL |
+ BLA |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6921BL |
+ BLA |
+ BXD70 |
+ 76 |
+ M |
+ 8/17/06 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6869BL |
+ BLA |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6871BL |
+ BLA |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 79 |
+ R6777BL |
+ BLA |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 80 |
+ R6779BL |
+ BLA |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 81 |
+ R6837BL |
+ BLA |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 82 |
+ R6829BL |
+ BLA |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 83 |
+ R6933BL |
+ BLA |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 84 |
+ R6935BL |
+ BLA |
+ BXD79 |
+ 87 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 85 |
+ R6781BL |
+ BLA |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 86 |
+ R6783BL |
+ BLA |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 87 |
+ R6913BL |
+ BLA |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 88 |
+ R6911BL |
+ BLA |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 89 |
+ R6841BL |
+ BLA |
+ BXD84 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 90 |
+ R6833BL |
+ BLA |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 91 |
+ R6937BL |
+ BLA |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 92 |
+ R6939BL |
+ BLA |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 93 |
+ R6909BL |
+ BLA |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 94 |
+ R6895BL |
+ BLA |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 95 |
+ R6897BL |
+ BLA |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 96 |
+ R6903BL |
+ BLA |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 97 |
+ R6905BL |
+ BLA |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 98 |
+ R6923BL |
+ BLA |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 99 |
+ R6927BL |
+ BLA |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 100 |
+ R6919BL |
+ BLA |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 101 |
+ R6867BL |
+ BLA |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 102 |
+ R6899BL |
+ BLA |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 103 |
+ R6901BL |
+ BLA |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 104 |
+ R6875BL |
+ BLA |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 105 |
+ R6883BL |
+ BLA |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 106 |
+ R6831BL |
+ BLA |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 107 |
+ R6943BL |
+ BLA |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 108 |
+ R6941BL |
+ BLA |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 109 |
+ R6753BL |
+ BLA |
+ BXD102 |
+ 88 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 110 |
+ R6755BL |
+ BLA |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 111 |
+ R6765BL |
+ BLA |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/Inia_amg_bla_rma_f_1110/platform.rtf b/general/datasets/Inia_amg_bla_rma_f_1110/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_f_1110/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_amg_bla_rma_f_1110/processing.rtf b/general/datasets/Inia_amg_bla_rma_f_1110/processing.rtf
new file mode 100644
index 0000000..a2a6c30
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_f_1110/processing.rtf
@@ -0,0 +1,16 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required no initial correction for batch effects and the data in this initial release do not incorporate any additional corrections. However, there are several confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Dissection variation: examine and use probe sets for Ttr as a correction for the inclusion of choroid plexus and non-parenchmymal tissue in samples. Transthyretin is only expressed in the choroid plexus (PMID 16698124
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the 54 probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases (58) in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest 54 probe sets in this amygdala data set accounts of 42% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the amygdala data set can be map as a trait. It is not associated with any QLTs that are even suggestive, and the highest LRS is about 10 on chromosomes 18 and 19. The second principal component trait, which accounts for only 5% of the "noise" variance, has a suggestive QTL (LRS of 12, high B allele) on chromosome 4 at about 90 Mb. We therefore do not think that there is significant risk of major false trans eQTL bands in this data set.
+
+
+Data Release. This data set was first uploaded into GeneNetwork November 25, 2010 and made accessible without a password to all users on December 1, 2010. The data set was orginally entered with two strain identification errors that were fixed Dec 10, 2010 by KM Mozhui and A Centeno (array R6659BL was originally listed as BXD16 but is BXD27; R6789BL was original listed as BXD27 is BXD12). The current data release has no known errors of sex or strain assignment.
+
+Data Status and Use. The data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/Inia_amg_bla_rma_f_1110/summary.rtf b/general/datasets/Inia_amg_bla_rma_f_1110/summary.rtf
new file mode 100644
index 0000000..41311b7
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_f_1110/summary.rtf
@@ -0,0 +1 @@
+This is a final error-checked release of an amygdala gene expression data set generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from the NIH NIAAA. The basolateral complex of the amygdala of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/Inia_amg_bla_rma_f_1110/tissue.rtf b/general/datasets/Inia_amg_bla_rma_f_1110/tissue.rtf
new file mode 100644
index 0000000..ea556c7
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_f_1110/tissue.rtf
@@ -0,0 +1,12 @@
+Dissection Protocol
+
+
+ - Animals were sacrificed by cervical dislocation and brains were immediately dissected from the head and stored in RNAlater (www.ambion.com) for 2 to 3 days at 4 deg C in a refrigerator.
+ - Brains were placed with ventral side up on a cutting surface and a partial coronal cut was made with a surgical blade at a level that corresponds approximately to the -2.5 mm behind the stereotaxic Bregma point (this cut is just a little rostral from the pontine fibres when viewed from the ventral side).
+ - Brains were placed in a coronal matrix (egg-style slicer) and a 2-mm thick coronal slab was taken just rostral to the initial cut.
+ - The 2-mm thick slab was placed on a clean glass slide and the hypothalamus was cut out and placed in a tube on dry ice.
+ - To dissect the BLA, the temporal lobes were detached by placing a scalpel in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then cut out and placed in a tube on dry ice.
+ - Tissue from two mice (right and left sides) and from the same strain and sex (an usually the same litter) were pooled. The only exceptions are BLA samples from strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue was obtained from only one animal per array).
+
+
+
diff --git a/general/datasets/Inia_amg_bla_rma_m_1110/cases.rtf b/general/datasets/Inia_amg_bla_rma_m_1110/cases.rtf
new file mode 100644
index 0000000..b02b19a
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_m_1110/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 58 strains, including 54 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1) were analyzed. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by K. Mozhui. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. Fifty strains have matched male and female samples. Five strains have male only samples (BXD5, 13, 16, 100 and 103). Three strains have only female samples (BXD44, 70, and 87.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/Inia_amg_bla_rma_m_1110/contributors.rtf b/general/datasets/Inia_amg_bla_rma_m_1110/contributors.rtf
new file mode 100644
index 0000000..f69a44f
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_m_1110/contributors.rtf
@@ -0,0 +1 @@
+Mozhui K, Williams RW
diff --git a/general/datasets/Inia_amg_bla_rma_m_1110/experiment-design.rtf b/general/datasets/Inia_amg_bla_rma_m_1110/experiment-design.rtf
new file mode 100644
index 0000000..126d431
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_m_1110/experiment-design.rtf
@@ -0,0 +1,1152 @@
+Data Evaluation Summary
+
+
+ - eQLTs with LOD >10 (LRS>46.1): n = 525
+ - eQTL with high LOD and LRS: Trait ID 10513604 (Hdhd3) LOD = 39.8, LRS = 183.5
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6853BL |
+ BLA |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6861BL |
+ BLA |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6851BL |
+ BLA |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6859BL |
+ BLA |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6863BL |
+ BLA |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6865BL |
+ BLA |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6857BL |
+ BLA |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6855BL |
+ BLA |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6799BL |
+ BLA |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6795BL |
+ BLA |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6787BL |
+ BLA |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6785BL |
+ BLA |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6819BL |
+ BLA |
+ BXD12 |
+ 78 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 14 |
+ R6789BL |
+ BLA |
+ BXD12 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 15 |
+ R6805BL |
+ BLA |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6291BL |
+ BLA |
+ BXD13 |
+ N/A |
+ M |
+ 6/11/09 |
+ N/A |
+
+
+ | 17 |
+ R6811BL |
+ BLA |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 18 |
+ R6825BL |
+ BLA |
+ BXD14 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 19 |
+ R6657BL |
+ BLA |
+ BXD16 |
+ N/A |
+ M |
+ 1/8/08 |
+ N/A |
+
+
+ | 20 |
+ R6054BL |
+ BLA |
+ BXD19 |
+ N/A |
+ F |
+ 2/26/08 |
+ N/A |
+
+
+ | 21 |
+ R6052BL |
+ BLA |
+ BXD19 |
+ N/A |
+ M |
+ 2/26/08 |
+ N/A |
+
+
+ | 22 |
+ R6803BL |
+ BLA |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 23 |
+ R6817BL |
+ BLA |
+ BXD24 |
+ 86 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6063BL |
+ BLA |
+ BXD25 |
+ N/A |
+ F |
+ 3/12/08 |
+ N/A |
+
+
+ | 25 |
+ R6062BL |
+ BLA |
+ BXD25 |
+ N/A |
+ M |
+ 3/12/08 |
+ N/A |
+
+
+ | 26 |
+ R6659BL |
+ BLA |
+ BXD27 |
+ N/A |
+ F |
+ 1/8/08 |
+ N/A |
+
+
+ | 27 |
+ R6791BL |
+ BLA |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 28 |
+ R6797BL |
+ BLA |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 29 |
+ R6793BL |
+ BLA |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 30 |
+ R6815BL |
+ BLA |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 31 |
+ R6801BL |
+ BLA |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 32 |
+ R6915BL |
+ BLA |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 33 |
+ R6845BL |
+ BLA |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 34 |
+ R6821BL |
+ BLA |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 35 |
+ R6807BL |
+ BLA |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 36 |
+ R6057BL |
+ BLA |
+ BXD38 |
+ N/A |
+ F |
+ 2/26/08 |
+ N/A |
+
+
+ | 37 |
+ R6056BL |
+ BLA |
+ BXD38 |
+ N/A |
+ M |
+ 2/26/08 |
+ N/A |
+
+
+ | 38 |
+ R6827BL |
+ BLA |
+ BXD39 |
+ 79 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 39 |
+ R6813BL |
+ BLA |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 40 |
+ R6847BL |
+ BLA |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 41 |
+ R6849BL |
+ BLA |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 42 |
+ R6809BL |
+ BLA |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 43 |
+ R6823BL |
+ BLA |
+ BXD42 |
+ 87 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 44 |
+ R6759BL |
+ BLA |
+ BXD43 |
+ 81 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 45 |
+ R6757BL |
+ BLA |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 46 |
+ R6745BL |
+ BLA |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 47 |
+ R6763BL |
+ BLA |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 48 |
+ R6761BL |
+ BLA |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 49 |
+ R6879BL |
+ BLA |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6881BL |
+ BLA |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6751BL |
+ BLA |
+ BXD49 |
+ 84 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 52 |
+ R6747BL |
+ BLA |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 53 |
+ R6104BL |
+ BLA |
+ BXD5 |
+ N/A |
+ f |
+ 10/23/09 |
+ N/A |
+
+
+ | 54 |
+ R6103BL |
+ BLA |
+ BXD5 |
+ N/A |
+ M |
+ 10/23/09 |
+ N/A |
+
+
+ | 55 |
+ R6889BL |
+ BLA |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6891BL |
+ BLA |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6074BL |
+ BLA |
+ BXD51 |
+ N/A |
+ F |
+ 3/12/08 |
+ N/A |
+
+
+ | 58 |
+ R6699BL |
+ BLA |
+ BXD51 |
+ N/A |
+ M |
+ 4/30/09 |
+ N/A |
+
+
+ | 59 |
+ R6917BL |
+ BLA |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 60 |
+ R6893BL |
+ BLA |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 61 |
+ R6769BL |
+ BLA |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 62 |
+ R6771BL |
+ BLA |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6655BL |
+ BLA |
+ BXD61 |
+ N/A |
+ F |
+ 1/29/08 |
+ N/A |
+
+
+ | 64 |
+ R6653BL |
+ BLA |
+ BXD61 |
+ N/A |
+ M |
+ 1/29/08 |
+ N/A |
+
+
+ | 65 |
+ R6835BL |
+ BLA |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 66 |
+ R6843BL |
+ BLA |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6887BL |
+ BLA |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6885BL |
+ BLA |
+ BXD63 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6877BL |
+ BLA |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6873BL |
+ BLA |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6929BL |
+ BLA |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6931BL |
+ BLA |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6775BL |
+ BLA |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 74 |
+ R6773BL |
+ BLA |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 75 |
+ R6925BL |
+ BLA |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6921BL |
+ BLA |
+ BXD70 |
+ 76 |
+ M |
+ 8/17/06 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6869BL |
+ BLA |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6871BL |
+ BLA |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 79 |
+ R6777BL |
+ BLA |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 80 |
+ R6779BL |
+ BLA |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 81 |
+ R6837BL |
+ BLA |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 82 |
+ R6829BL |
+ BLA |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 83 |
+ R6933BL |
+ BLA |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 84 |
+ R6935BL |
+ BLA |
+ BXD79 |
+ 87 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 85 |
+ R6781BL |
+ BLA |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 86 |
+ R6783BL |
+ BLA |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 87 |
+ R6913BL |
+ BLA |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 88 |
+ R6911BL |
+ BLA |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 89 |
+ R6841BL |
+ BLA |
+ BXD84 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 90 |
+ R6833BL |
+ BLA |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 91 |
+ R6937BL |
+ BLA |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 92 |
+ R6939BL |
+ BLA |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 93 |
+ R6909BL |
+ BLA |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 94 |
+ R6895BL |
+ BLA |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 95 |
+ R6897BL |
+ BLA |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 96 |
+ R6903BL |
+ BLA |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 97 |
+ R6905BL |
+ BLA |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 98 |
+ R6923BL |
+ BLA |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 99 |
+ R6927BL |
+ BLA |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 100 |
+ R6919BL |
+ BLA |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 101 |
+ R6867BL |
+ BLA |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 102 |
+ R6899BL |
+ BLA |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 103 |
+ R6901BL |
+ BLA |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 104 |
+ R6875BL |
+ BLA |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 105 |
+ R6883BL |
+ BLA |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 106 |
+ R6831BL |
+ BLA |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 107 |
+ R6943BL |
+ BLA |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 108 |
+ R6941BL |
+ BLA |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 109 |
+ R6753BL |
+ BLA |
+ BXD102 |
+ 88 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 110 |
+ R6755BL |
+ BLA |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 111 |
+ R6765BL |
+ BLA |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/Inia_amg_bla_rma_m_1110/platform.rtf b/general/datasets/Inia_amg_bla_rma_m_1110/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_m_1110/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_amg_bla_rma_m_1110/processing.rtf b/general/datasets/Inia_amg_bla_rma_m_1110/processing.rtf
new file mode 100644
index 0000000..a2a6c30
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_m_1110/processing.rtf
@@ -0,0 +1,16 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required no initial correction for batch effects and the data in this initial release do not incorporate any additional corrections. However, there are several confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Dissection variation: examine and use probe sets for Ttr as a correction for the inclusion of choroid plexus and non-parenchmymal tissue in samples. Transthyretin is only expressed in the choroid plexus (PMID 16698124
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the 54 probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases (58) in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest 54 probe sets in this amygdala data set accounts of 42% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the amygdala data set can be map as a trait. It is not associated with any QLTs that are even suggestive, and the highest LRS is about 10 on chromosomes 18 and 19. The second principal component trait, which accounts for only 5% of the "noise" variance, has a suggestive QTL (LRS of 12, high B allele) on chromosome 4 at about 90 Mb. We therefore do not think that there is significant risk of major false trans eQTL bands in this data set.
+
+
+Data Release. This data set was first uploaded into GeneNetwork November 25, 2010 and made accessible without a password to all users on December 1, 2010. The data set was orginally entered with two strain identification errors that were fixed Dec 10, 2010 by KM Mozhui and A Centeno (array R6659BL was originally listed as BXD16 but is BXD27; R6789BL was original listed as BXD27 is BXD12). The current data release has no known errors of sex or strain assignment.
+
+Data Status and Use. The data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/Inia_amg_bla_rma_m_1110/specifics.rtf b/general/datasets/Inia_amg_bla_rma_m_1110/specifics.rtf
new file mode 100644
index 0000000..8c3a60b
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_m_1110/specifics.rtf
@@ -0,0 +1 @@
+Male samples only
diff --git a/general/datasets/Inia_amg_bla_rma_m_1110/summary.rtf b/general/datasets/Inia_amg_bla_rma_m_1110/summary.rtf
new file mode 100644
index 0000000..41311b7
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_m_1110/summary.rtf
@@ -0,0 +1 @@
+This is a final error-checked release of an amygdala gene expression data set generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from the NIH NIAAA. The basolateral complex of the amygdala of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/Inia_amg_bla_rma_m_1110/tissue.rtf b/general/datasets/Inia_amg_bla_rma_m_1110/tissue.rtf
new file mode 100644
index 0000000..ea556c7
--- /dev/null
+++ b/general/datasets/Inia_amg_bla_rma_m_1110/tissue.rtf
@@ -0,0 +1,12 @@
+Dissection Protocol
+
+
+ - Animals were sacrificed by cervical dislocation and brains were immediately dissected from the head and stored in RNAlater (www.ambion.com) for 2 to 3 days at 4 deg C in a refrigerator.
+ - Brains were placed with ventral side up on a cutting surface and a partial coronal cut was made with a surgical blade at a level that corresponds approximately to the -2.5 mm behind the stereotaxic Bregma point (this cut is just a little rostral from the pontine fibres when viewed from the ventral side).
+ - Brains were placed in a coronal matrix (egg-style slicer) and a 2-mm thick coronal slab was taken just rostral to the initial cut.
+ - The 2-mm thick slab was placed on a clean glass slide and the hypothalamus was cut out and placed in a tube on dry ice.
+ - To dissect the BLA, the temporal lobes were detached by placing a scalpel in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then cut out and placed in a tube on dry ice.
+ - Tissue from two mice (right and left sides) and from the same strain and sex (an usually the same litter) were pooled. The only exceptions are BLA samples from strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue was obtained from only one animal per array).
+
+
+
diff --git a/general/datasets/Inia_amgcoh_0311/cases.rtf b/general/datasets/Inia_amgcoh_0311/cases.rtf
new file mode 100644
index 0000000..b02b19a
--- /dev/null
+++ b/general/datasets/Inia_amgcoh_0311/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 58 strains, including 54 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1) were analyzed. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by K. Mozhui. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. Fifty strains have matched male and female samples. Five strains have male only samples (BXD5, 13, 16, 100 and 103). Three strains have only female samples (BXD44, 70, and 87.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/Inia_amgcoh_0311/contributors.rtf b/general/datasets/Inia_amgcoh_0311/contributors.rtf
new file mode 100644
index 0000000..f69a44f
--- /dev/null
+++ b/general/datasets/Inia_amgcoh_0311/contributors.rtf
@@ -0,0 +1 @@
+Mozhui K, Williams RW
diff --git a/general/datasets/Inia_amgcoh_0311/experiment-design.rtf b/general/datasets/Inia_amgcoh_0311/experiment-design.rtf
new file mode 100644
index 0000000..126d431
--- /dev/null
+++ b/general/datasets/Inia_amgcoh_0311/experiment-design.rtf
@@ -0,0 +1,1152 @@
+Data Evaluation Summary
+
+
+ - eQLTs with LOD >10 (LRS>46.1): n = 525
+ - eQTL with high LOD and LRS: Trait ID 10513604 (Hdhd3) LOD = 39.8, LRS = 183.5
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6853BL |
+ BLA |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6861BL |
+ BLA |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6851BL |
+ BLA |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6859BL |
+ BLA |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6863BL |
+ BLA |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6865BL |
+ BLA |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6857BL |
+ BLA |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6855BL |
+ BLA |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6799BL |
+ BLA |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6795BL |
+ BLA |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6787BL |
+ BLA |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6785BL |
+ BLA |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6819BL |
+ BLA |
+ BXD12 |
+ 78 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 14 |
+ R6789BL |
+ BLA |
+ BXD12 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 15 |
+ R6805BL |
+ BLA |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6291BL |
+ BLA |
+ BXD13 |
+ N/A |
+ M |
+ 6/11/09 |
+ N/A |
+
+
+ | 17 |
+ R6811BL |
+ BLA |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 18 |
+ R6825BL |
+ BLA |
+ BXD14 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 19 |
+ R6657BL |
+ BLA |
+ BXD16 |
+ N/A |
+ M |
+ 1/8/08 |
+ N/A |
+
+
+ | 20 |
+ R6054BL |
+ BLA |
+ BXD19 |
+ N/A |
+ F |
+ 2/26/08 |
+ N/A |
+
+
+ | 21 |
+ R6052BL |
+ BLA |
+ BXD19 |
+ N/A |
+ M |
+ 2/26/08 |
+ N/A |
+
+
+ | 22 |
+ R6803BL |
+ BLA |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 23 |
+ R6817BL |
+ BLA |
+ BXD24 |
+ 86 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6063BL |
+ BLA |
+ BXD25 |
+ N/A |
+ F |
+ 3/12/08 |
+ N/A |
+
+
+ | 25 |
+ R6062BL |
+ BLA |
+ BXD25 |
+ N/A |
+ M |
+ 3/12/08 |
+ N/A |
+
+
+ | 26 |
+ R6659BL |
+ BLA |
+ BXD27 |
+ N/A |
+ F |
+ 1/8/08 |
+ N/A |
+
+
+ | 27 |
+ R6791BL |
+ BLA |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 28 |
+ R6797BL |
+ BLA |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 29 |
+ R6793BL |
+ BLA |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 30 |
+ R6815BL |
+ BLA |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 31 |
+ R6801BL |
+ BLA |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 32 |
+ R6915BL |
+ BLA |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 33 |
+ R6845BL |
+ BLA |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 34 |
+ R6821BL |
+ BLA |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 35 |
+ R6807BL |
+ BLA |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 36 |
+ R6057BL |
+ BLA |
+ BXD38 |
+ N/A |
+ F |
+ 2/26/08 |
+ N/A |
+
+
+ | 37 |
+ R6056BL |
+ BLA |
+ BXD38 |
+ N/A |
+ M |
+ 2/26/08 |
+ N/A |
+
+
+ | 38 |
+ R6827BL |
+ BLA |
+ BXD39 |
+ 79 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 39 |
+ R6813BL |
+ BLA |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 40 |
+ R6847BL |
+ BLA |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 41 |
+ R6849BL |
+ BLA |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 42 |
+ R6809BL |
+ BLA |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 43 |
+ R6823BL |
+ BLA |
+ BXD42 |
+ 87 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 44 |
+ R6759BL |
+ BLA |
+ BXD43 |
+ 81 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 45 |
+ R6757BL |
+ BLA |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 46 |
+ R6745BL |
+ BLA |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 47 |
+ R6763BL |
+ BLA |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 48 |
+ R6761BL |
+ BLA |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 49 |
+ R6879BL |
+ BLA |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6881BL |
+ BLA |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6751BL |
+ BLA |
+ BXD49 |
+ 84 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 52 |
+ R6747BL |
+ BLA |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 53 |
+ R6104BL |
+ BLA |
+ BXD5 |
+ N/A |
+ f |
+ 10/23/09 |
+ N/A |
+
+
+ | 54 |
+ R6103BL |
+ BLA |
+ BXD5 |
+ N/A |
+ M |
+ 10/23/09 |
+ N/A |
+
+
+ | 55 |
+ R6889BL |
+ BLA |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6891BL |
+ BLA |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6074BL |
+ BLA |
+ BXD51 |
+ N/A |
+ F |
+ 3/12/08 |
+ N/A |
+
+
+ | 58 |
+ R6699BL |
+ BLA |
+ BXD51 |
+ N/A |
+ M |
+ 4/30/09 |
+ N/A |
+
+
+ | 59 |
+ R6917BL |
+ BLA |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 60 |
+ R6893BL |
+ BLA |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 61 |
+ R6769BL |
+ BLA |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 62 |
+ R6771BL |
+ BLA |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6655BL |
+ BLA |
+ BXD61 |
+ N/A |
+ F |
+ 1/29/08 |
+ N/A |
+
+
+ | 64 |
+ R6653BL |
+ BLA |
+ BXD61 |
+ N/A |
+ M |
+ 1/29/08 |
+ N/A |
+
+
+ | 65 |
+ R6835BL |
+ BLA |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 66 |
+ R6843BL |
+ BLA |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6887BL |
+ BLA |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6885BL |
+ BLA |
+ BXD63 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6877BL |
+ BLA |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6873BL |
+ BLA |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6929BL |
+ BLA |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6931BL |
+ BLA |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6775BL |
+ BLA |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 74 |
+ R6773BL |
+ BLA |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 75 |
+ R6925BL |
+ BLA |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6921BL |
+ BLA |
+ BXD70 |
+ 76 |
+ M |
+ 8/17/06 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6869BL |
+ BLA |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6871BL |
+ BLA |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 79 |
+ R6777BL |
+ BLA |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 80 |
+ R6779BL |
+ BLA |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 81 |
+ R6837BL |
+ BLA |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 82 |
+ R6829BL |
+ BLA |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 83 |
+ R6933BL |
+ BLA |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 84 |
+ R6935BL |
+ BLA |
+ BXD79 |
+ 87 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 85 |
+ R6781BL |
+ BLA |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 86 |
+ R6783BL |
+ BLA |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 87 |
+ R6913BL |
+ BLA |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 88 |
+ R6911BL |
+ BLA |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 89 |
+ R6841BL |
+ BLA |
+ BXD84 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 90 |
+ R6833BL |
+ BLA |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 91 |
+ R6937BL |
+ BLA |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 92 |
+ R6939BL |
+ BLA |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 93 |
+ R6909BL |
+ BLA |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 94 |
+ R6895BL |
+ BLA |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 95 |
+ R6897BL |
+ BLA |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 96 |
+ R6903BL |
+ BLA |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 97 |
+ R6905BL |
+ BLA |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 98 |
+ R6923BL |
+ BLA |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 99 |
+ R6927BL |
+ BLA |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 100 |
+ R6919BL |
+ BLA |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 101 |
+ R6867BL |
+ BLA |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 102 |
+ R6899BL |
+ BLA |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 103 |
+ R6901BL |
+ BLA |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 104 |
+ R6875BL |
+ BLA |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 105 |
+ R6883BL |
+ BLA |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 106 |
+ R6831BL |
+ BLA |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 107 |
+ R6943BL |
+ BLA |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 108 |
+ R6941BL |
+ BLA |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 109 |
+ R6753BL |
+ BLA |
+ BXD102 |
+ 88 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 110 |
+ R6755BL |
+ BLA |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 111 |
+ R6765BL |
+ BLA |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/Inia_amgcoh_0311/platform.rtf b/general/datasets/Inia_amgcoh_0311/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_amgcoh_0311/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_amgcoh_0311/processing.rtf b/general/datasets/Inia_amgcoh_0311/processing.rtf
new file mode 100644
index 0000000..a2a6c30
--- /dev/null
+++ b/general/datasets/Inia_amgcoh_0311/processing.rtf
@@ -0,0 +1,16 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required no initial correction for batch effects and the data in this initial release do not incorporate any additional corrections. However, there are several confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Dissection variation: examine and use probe sets for Ttr as a correction for the inclusion of choroid plexus and non-parenchmymal tissue in samples. Transthyretin is only expressed in the choroid plexus (PMID 16698124
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the 54 probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases (58) in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest 54 probe sets in this amygdala data set accounts of 42% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the amygdala data set can be map as a trait. It is not associated with any QLTs that are even suggestive, and the highest LRS is about 10 on chromosomes 18 and 19. The second principal component trait, which accounts for only 5% of the "noise" variance, has a suggestive QTL (LRS of 12, high B allele) on chromosome 4 at about 90 Mb. We therefore do not think that there is significant risk of major false trans eQTL bands in this data set.
+
+
+Data Release. This data set was first uploaded into GeneNetwork November 25, 2010 and made accessible without a password to all users on December 1, 2010. The data set was orginally entered with two strain identification errors that were fixed Dec 10, 2010 by KM Mozhui and A Centeno (array R6659BL was originally listed as BXD16 but is BXD27; R6789BL was original listed as BXD27 is BXD12). The current data release has no known errors of sex or strain assignment.
+
+Data Status and Use. The data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/Inia_amgcoh_0311/summary.rtf b/general/datasets/Inia_amgcoh_0311/summary.rtf
new file mode 100644
index 0000000..41311b7
--- /dev/null
+++ b/general/datasets/Inia_amgcoh_0311/summary.rtf
@@ -0,0 +1 @@
+This is a final error-checked release of an amygdala gene expression data set generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from the NIH NIAAA. The basolateral complex of the amygdala of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/Inia_amgcoh_0311/tissue.rtf b/general/datasets/Inia_amgcoh_0311/tissue.rtf
new file mode 100644
index 0000000..ea556c7
--- /dev/null
+++ b/general/datasets/Inia_amgcoh_0311/tissue.rtf
@@ -0,0 +1,12 @@
+Dissection Protocol
+
+
+ - Animals were sacrificed by cervical dislocation and brains were immediately dissected from the head and stored in RNAlater (www.ambion.com) for 2 to 3 days at 4 deg C in a refrigerator.
+ - Brains were placed with ventral side up on a cutting surface and a partial coronal cut was made with a surgical blade at a level that corresponds approximately to the -2.5 mm behind the stereotaxic Bregma point (this cut is just a little rostral from the pontine fibres when viewed from the ventral side).
+ - Brains were placed in a coronal matrix (egg-style slicer) and a 2-mm thick coronal slab was taken just rostral to the initial cut.
+ - The 2-mm thick slab was placed on a clean glass slide and the hypothalamus was cut out and placed in a tube on dry ice.
+ - To dissect the BLA, the temporal lobes were detached by placing a scalpel in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then cut out and placed in a tube on dry ice.
+ - Tissue from two mice (right and left sides) and from the same strain and sex (an usually the same litter) were pooled. The only exceptions are BLA samples from strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue was obtained from only one animal per array).
+
+
+
diff --git a/general/datasets/Inia_bxd_livdnam_1119/experiment-design.rtf b/general/datasets/Inia_bxd_livdnam_1119/experiment-design.rtf
new file mode 100644
index 0000000..5c63e07
--- /dev/null
+++ b/general/datasets/Inia_bxd_livdnam_1119/experiment-design.rtf
@@ -0,0 +1 @@
+Aging
diff --git a/general/datasets/Inia_bxd_livdnam_1119/platform.rtf b/general/datasets/Inia_bxd_livdnam_1119/platform.rtf
new file mode 100644
index 0000000..01ea9ea
--- /dev/null
+++ b/general/datasets/Inia_bxd_livdnam_1119/platform.rtf
@@ -0,0 +1 @@
+Pan-Mammalian DNAm Infinium array; this is a custom array
diff --git a/general/datasets/Inia_bxd_livdnam_1119/processing.rtf b/general/datasets/Inia_bxd_livdnam_1119/processing.rtf
new file mode 100644
index 0000000..5dc0f7f
--- /dev/null
+++ b/general/datasets/Inia_bxd_livdnam_1119/processing.rtf
@@ -0,0 +1 @@
+Beta-values after normalization
diff --git a/general/datasets/Inia_bxd_livdnam_1119/specifics.rtf b/general/datasets/Inia_bxd_livdnam_1119/specifics.rtf
new file mode 100644
index 0000000..925cbbe
--- /dev/null
+++ b/general/datasets/Inia_bxd_livdnam_1119/specifics.rtf
@@ -0,0 +1 @@
+Normalization Sesame
\ No newline at end of file
diff --git a/general/datasets/Inia_bxd_livdnam_1119/summary.rtf b/general/datasets/Inia_bxd_livdnam_1119/summary.rtf
new file mode 100644
index 0000000..0961144
--- /dev/null
+++ b/general/datasets/Inia_bxd_livdnam_1119/summary.rtf
@@ -0,0 +1 @@
+DNA from liver tissue profiled on the Illumina Pan-Mammalian Infinium microarray. This array was designed and developed by Steve Horvath at UCLA. Array hybridization, initial data QC, and normalization done at UCLA.
diff --git a/general/datasets/Inia_bxd_livdnaminfi_1020/experiment-design.rtf b/general/datasets/Inia_bxd_livdnaminfi_1020/experiment-design.rtf
new file mode 100644
index 0000000..5c63e07
--- /dev/null
+++ b/general/datasets/Inia_bxd_livdnaminfi_1020/experiment-design.rtf
@@ -0,0 +1 @@
+Aging
diff --git a/general/datasets/Inia_bxd_livdnaminfi_1020/platform.rtf b/general/datasets/Inia_bxd_livdnaminfi_1020/platform.rtf
new file mode 100644
index 0000000..01ea9ea
--- /dev/null
+++ b/general/datasets/Inia_bxd_livdnaminfi_1020/platform.rtf
@@ -0,0 +1 @@
+Pan-Mammalian DNAm Infinium array; this is a custom array
diff --git a/general/datasets/Inia_bxd_livdnaminfi_1020/processing.rtf b/general/datasets/Inia_bxd_livdnaminfi_1020/processing.rtf
new file mode 100644
index 0000000..5dc0f7f
--- /dev/null
+++ b/general/datasets/Inia_bxd_livdnaminfi_1020/processing.rtf
@@ -0,0 +1 @@
+Beta-values after normalization
diff --git a/general/datasets/Inia_bxd_livdnaminfi_1020/specifics.rtf b/general/datasets/Inia_bxd_livdnaminfi_1020/specifics.rtf
new file mode 100644
index 0000000..717d006
--- /dev/null
+++ b/general/datasets/Inia_bxd_livdnaminfi_1020/specifics.rtf
@@ -0,0 +1 @@
+Normalization minfi
\ No newline at end of file
diff --git a/general/datasets/Inia_bxd_livdnaminfi_1020/summary.rtf b/general/datasets/Inia_bxd_livdnaminfi_1020/summary.rtf
new file mode 100644
index 0000000..0961144
--- /dev/null
+++ b/general/datasets/Inia_bxd_livdnaminfi_1020/summary.rtf
@@ -0,0 +1 @@
+DNA from liver tissue profiled on the Illumina Pan-Mammalian Infinium microarray. This array was designed and developed by Steve Horvath at UCLA. Array hybridization, initial data QC, and normalization done at UCLA.
diff --git a/general/datasets/Inia_hyp_f_rma_1110/acknowledgment.rtf b/general/datasets/Inia_hyp_f_rma_1110/acknowledgment.rtf
new file mode 100644
index 0000000..2c3f2bd
--- /dev/null
+++ b/general/datasets/Inia_hyp_f_rma_1110/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/Inia_hyp_f_rma_1110/cases.rtf b/general/datasets/Inia_hyp_f_rma_1110/cases.rtf
new file mode 100644
index 0000000..f19e9c8
--- /dev/null
+++ b/general/datasets/Inia_hyp_f_rma_1110/cases.rtf
@@ -0,0 +1,916 @@
+The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6854HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6862HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6852HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6860HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6864HYP |
+ Hyp |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6866HYP |
+ Hyp |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6858HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6856HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6800HYP |
+ Hyp |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6796HYP |
+ Hyp |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6788HYP |
+ Hyp |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6786HYP |
+ Hyp |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6806HYP |
+ Hyp |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 14 |
+ R6812HYP |
+ Hyp |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 15 |
+ R6804HYP |
+ Hyp |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6792HYP |
+ Hyp |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 17 |
+ R6790HYP |
+ Hyp |
+ BXD27 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 18 |
+ R6798HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 19 |
+ R6794HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 20 |
+ R6816HYP |
+ Hyp |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 21 |
+ R6802HYP |
+ Hyp |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 22 |
+ R6916HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 23 |
+ R6846HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6822HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 25 |
+ R6808HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 26 |
+ R6814HYP |
+ Hyp |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 27 |
+ R6848HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 28 |
+ R6850HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 29 |
+ R6810HYP |
+ Hyp |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 30 |
+ R6758HYP |
+ Hyp |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 31 |
+ R6746HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 32 |
+ R6750HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 33 |
+ R6764HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 34 |
+ R6762HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 35 |
+ R6880HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 36 |
+ R6882HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 37 |
+ R6748HYP |
+ Hyp |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 38 |
+ R6890HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 39 |
+ R6892HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 40 |
+ R6918HYP |
+ Hyp |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 41 |
+ R6894HYP |
+ Hyp |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 42 |
+ R6770HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 43 |
+ R6772HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 44 |
+ R6836HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 45 |
+ R6844HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 46 |
+ R6888HYP |
+ Hyp |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 47 |
+ R6878HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 48 |
+ R6874HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 49 |
+ R6930HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6932HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6776HYP |
+ Hyp |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 52 |
+ R6774HYP |
+ Hyp |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 53 |
+ R6926HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 54 |
+ R6922HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 55 |
+ R6870HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6872HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6778HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 58 |
+ R6780HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 59 |
+ R6838HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 60 |
+ R6830HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 61 |
+ R6934HYP |
+ Hyp |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 62 |
+ R6782HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6784HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 64 |
+ R6914HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 65 |
+ R6912HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 66 |
+ R6834HYP |
+ Hyp |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6938HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6940HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6910HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6908HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6896HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6898HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6904HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 74 |
+ R6906HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 75 |
+ R6924HYP |
+ Hyp |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6928HYP |
+ Hyp |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6920HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6868HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 79 |
+ R6900HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 80 |
+ R6902HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 81 |
+ R6876HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 82 |
+ R6884HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 83 |
+ R6840HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 84 |
+ R6832HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 85 |
+ R6944HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 86 |
+ R6942HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 87 |
+ R6756HYP |
+ Hyp |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 88 |
+ R6768HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 89 |
+ R6766HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Inia_hyp_f_rma_1110/citation.rtf b/general/datasets/Inia_hyp_f_rma_1110/citation.rtf
new file mode 100644
index 0000000..17f95be
--- /dev/null
+++ b/general/datasets/Inia_hyp_f_rma_1110/citation.rtf
@@ -0,0 +1 @@
+Mozhui K, Lu L, Armstrong WE, Williams RW. Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci 2012;6:63. PMID:22593731
diff --git a/general/datasets/Inia_hyp_f_rma_1110/contributors.rtf b/general/datasets/Inia_hyp_f_rma_1110/contributors.rtf
new file mode 100644
index 0000000..aad2c8a
--- /dev/null
+++ b/general/datasets/Inia_hyp_f_rma_1110/contributors.rtf
@@ -0,0 +1,15 @@
+
+
+Mozhui K, Lu L, Armstrong WE, Williams RW (2012) Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci. 2012 May 11;6:63. doi: 10.3389/fnins.2012.00063. eCollection 2012.
+
+Abstract
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ significantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantified gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to define hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a). Transcripts associated with the endocrine system and neuropeptide signaling also differ significantly. Sex-differentiated transcripts often have well delimited expression within specific hypothalamic nuclei that have roles in reproduction. For instance, the estrogen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-specific hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modification and gene transcription. In females, the X chromosome paralog, Kdm6a, takes the place of Uty in the same network. We also find significant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-specific modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-specific modulators.
+
+eQTL; hypothalamus; sex-specificity; weighted gene coexpression networks
+
+
+ - PMID: 22593731 PMCID: PMC3350311 DOI: 10.3389/fnins.2012.00063
+
+
+
diff --git a/general/datasets/Inia_hyp_f_rma_1110/experiment-design.rtf b/general/datasets/Inia_hyp_f_rma_1110/experiment-design.rtf
new file mode 100644
index 0000000..443af4a
--- /dev/null
+++ b/general/datasets/Inia_hyp_f_rma_1110/experiment-design.rtf
@@ -0,0 +1,6 @@
+Hypothalamus was dissected from adult male and female mice and process for expression analysis.
+
+RNA isolation
+Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/Inia_hyp_f_rma_1110/platform.rtf b/general/datasets/Inia_hyp_f_rma_1110/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_hyp_f_rma_1110/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_hyp_f_rma_1110/processing.rtf b/general/datasets/Inia_hyp_f_rma_1110/processing.rtf
new file mode 100644
index 0000000..b3e8689
--- /dev/null
+++ b/general/datasets/Inia_hyp_f_rma_1110/processing.rtf
@@ -0,0 +1 @@
+Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/Inia_hyp_f_rma_1110/summary.rtf b/general/datasets/Inia_hyp_f_rma_1110/summary.rtf
new file mode 100644
index 0000000..02671d5
--- /dev/null
+++ b/general/datasets/Inia_hyp_f_rma_1110/summary.rtf
@@ -0,0 +1,16 @@
+These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
+
+Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
+
+Dissection protocol:
+
+
+ - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
+ - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
+ - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
+ - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
+ - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
+ - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
+
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/Inia_hyp_m_rma_1110/acknowledgment.rtf b/general/datasets/Inia_hyp_m_rma_1110/acknowledgment.rtf
new file mode 100644
index 0000000..2c3f2bd
--- /dev/null
+++ b/general/datasets/Inia_hyp_m_rma_1110/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/Inia_hyp_m_rma_1110/cases.rtf b/general/datasets/Inia_hyp_m_rma_1110/cases.rtf
new file mode 100644
index 0000000..f19e9c8
--- /dev/null
+++ b/general/datasets/Inia_hyp_m_rma_1110/cases.rtf
@@ -0,0 +1,916 @@
+The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6854HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6862HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6852HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6860HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6864HYP |
+ Hyp |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6866HYP |
+ Hyp |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6858HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6856HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6800HYP |
+ Hyp |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6796HYP |
+ Hyp |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6788HYP |
+ Hyp |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6786HYP |
+ Hyp |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6806HYP |
+ Hyp |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 14 |
+ R6812HYP |
+ Hyp |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 15 |
+ R6804HYP |
+ Hyp |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6792HYP |
+ Hyp |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 17 |
+ R6790HYP |
+ Hyp |
+ BXD27 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 18 |
+ R6798HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 19 |
+ R6794HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 20 |
+ R6816HYP |
+ Hyp |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 21 |
+ R6802HYP |
+ Hyp |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 22 |
+ R6916HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 23 |
+ R6846HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6822HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 25 |
+ R6808HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 26 |
+ R6814HYP |
+ Hyp |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 27 |
+ R6848HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 28 |
+ R6850HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 29 |
+ R6810HYP |
+ Hyp |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 30 |
+ R6758HYP |
+ Hyp |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 31 |
+ R6746HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 32 |
+ R6750HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 33 |
+ R6764HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 34 |
+ R6762HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 35 |
+ R6880HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 36 |
+ R6882HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 37 |
+ R6748HYP |
+ Hyp |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 38 |
+ R6890HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 39 |
+ R6892HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 40 |
+ R6918HYP |
+ Hyp |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 41 |
+ R6894HYP |
+ Hyp |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 42 |
+ R6770HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 43 |
+ R6772HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 44 |
+ R6836HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 45 |
+ R6844HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 46 |
+ R6888HYP |
+ Hyp |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 47 |
+ R6878HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 48 |
+ R6874HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 49 |
+ R6930HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6932HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6776HYP |
+ Hyp |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 52 |
+ R6774HYP |
+ Hyp |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 53 |
+ R6926HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 54 |
+ R6922HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 55 |
+ R6870HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6872HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6778HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 58 |
+ R6780HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 59 |
+ R6838HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 60 |
+ R6830HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 61 |
+ R6934HYP |
+ Hyp |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 62 |
+ R6782HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6784HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 64 |
+ R6914HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 65 |
+ R6912HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 66 |
+ R6834HYP |
+ Hyp |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6938HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6940HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6910HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6908HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6896HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6898HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6904HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 74 |
+ R6906HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 75 |
+ R6924HYP |
+ Hyp |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6928HYP |
+ Hyp |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6920HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6868HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 79 |
+ R6900HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 80 |
+ R6902HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 81 |
+ R6876HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 82 |
+ R6884HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 83 |
+ R6840HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 84 |
+ R6832HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 85 |
+ R6944HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 86 |
+ R6942HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 87 |
+ R6756HYP |
+ Hyp |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 88 |
+ R6768HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 89 |
+ R6766HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Inia_hyp_m_rma_1110/citation.rtf b/general/datasets/Inia_hyp_m_rma_1110/citation.rtf
new file mode 100644
index 0000000..17f95be
--- /dev/null
+++ b/general/datasets/Inia_hyp_m_rma_1110/citation.rtf
@@ -0,0 +1 @@
+Mozhui K, Lu L, Armstrong WE, Williams RW. Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci 2012;6:63. PMID:22593731
diff --git a/general/datasets/Inia_hyp_m_rma_1110/contributors.rtf b/general/datasets/Inia_hyp_m_rma_1110/contributors.rtf
new file mode 100644
index 0000000..aad2c8a
--- /dev/null
+++ b/general/datasets/Inia_hyp_m_rma_1110/contributors.rtf
@@ -0,0 +1,15 @@
+
+
+Mozhui K, Lu L, Armstrong WE, Williams RW (2012) Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci. 2012 May 11;6:63. doi: 10.3389/fnins.2012.00063. eCollection 2012.
+
+Abstract
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ significantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantified gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to define hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a). Transcripts associated with the endocrine system and neuropeptide signaling also differ significantly. Sex-differentiated transcripts often have well delimited expression within specific hypothalamic nuclei that have roles in reproduction. For instance, the estrogen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-specific hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modification and gene transcription. In females, the X chromosome paralog, Kdm6a, takes the place of Uty in the same network. We also find significant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-specific modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-specific modulators.
+
+eQTL; hypothalamus; sex-specificity; weighted gene coexpression networks
+
+
+ - PMID: 22593731 PMCID: PMC3350311 DOI: 10.3389/fnins.2012.00063
+
+
+
diff --git a/general/datasets/Inia_hyp_m_rma_1110/experiment-design.rtf b/general/datasets/Inia_hyp_m_rma_1110/experiment-design.rtf
new file mode 100644
index 0000000..443af4a
--- /dev/null
+++ b/general/datasets/Inia_hyp_m_rma_1110/experiment-design.rtf
@@ -0,0 +1,6 @@
+Hypothalamus was dissected from adult male and female mice and process for expression analysis.
+
+RNA isolation
+Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/Inia_hyp_m_rma_1110/platform.rtf b/general/datasets/Inia_hyp_m_rma_1110/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_hyp_m_rma_1110/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_hyp_m_rma_1110/processing.rtf b/general/datasets/Inia_hyp_m_rma_1110/processing.rtf
new file mode 100644
index 0000000..b3e8689
--- /dev/null
+++ b/general/datasets/Inia_hyp_m_rma_1110/processing.rtf
@@ -0,0 +1 @@
+Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/Inia_hyp_m_rma_1110/summary.rtf b/general/datasets/Inia_hyp_m_rma_1110/summary.rtf
new file mode 100644
index 0000000..02671d5
--- /dev/null
+++ b/general/datasets/Inia_hyp_m_rma_1110/summary.rtf
@@ -0,0 +1,16 @@
+These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
+
+Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
+
+Dissection protocol:
+
+
+ - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
+ - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
+ - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
+ - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
+ - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
+ - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
+
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/Inia_hyp_pca_0813/acknowledgment.rtf b/general/datasets/Inia_hyp_pca_0813/acknowledgment.rtf
new file mode 100644
index 0000000..2c3f2bd
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/Inia_hyp_pca_0813/cases.rtf b/general/datasets/Inia_hyp_pca_0813/cases.rtf
new file mode 100644
index 0000000..f19e9c8
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813/cases.rtf
@@ -0,0 +1,916 @@
+The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6854HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6862HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6852HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6860HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6864HYP |
+ Hyp |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6866HYP |
+ Hyp |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6858HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6856HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6800HYP |
+ Hyp |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6796HYP |
+ Hyp |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6788HYP |
+ Hyp |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6786HYP |
+ Hyp |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6806HYP |
+ Hyp |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 14 |
+ R6812HYP |
+ Hyp |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 15 |
+ R6804HYP |
+ Hyp |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6792HYP |
+ Hyp |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 17 |
+ R6790HYP |
+ Hyp |
+ BXD27 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 18 |
+ R6798HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 19 |
+ R6794HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 20 |
+ R6816HYP |
+ Hyp |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 21 |
+ R6802HYP |
+ Hyp |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 22 |
+ R6916HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 23 |
+ R6846HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6822HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 25 |
+ R6808HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 26 |
+ R6814HYP |
+ Hyp |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 27 |
+ R6848HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 28 |
+ R6850HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 29 |
+ R6810HYP |
+ Hyp |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 30 |
+ R6758HYP |
+ Hyp |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 31 |
+ R6746HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 32 |
+ R6750HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 33 |
+ R6764HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 34 |
+ R6762HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 35 |
+ R6880HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 36 |
+ R6882HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 37 |
+ R6748HYP |
+ Hyp |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 38 |
+ R6890HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 39 |
+ R6892HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 40 |
+ R6918HYP |
+ Hyp |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 41 |
+ R6894HYP |
+ Hyp |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 42 |
+ R6770HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 43 |
+ R6772HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 44 |
+ R6836HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 45 |
+ R6844HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 46 |
+ R6888HYP |
+ Hyp |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 47 |
+ R6878HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 48 |
+ R6874HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 49 |
+ R6930HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6932HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6776HYP |
+ Hyp |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 52 |
+ R6774HYP |
+ Hyp |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 53 |
+ R6926HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 54 |
+ R6922HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 55 |
+ R6870HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6872HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6778HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 58 |
+ R6780HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 59 |
+ R6838HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 60 |
+ R6830HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 61 |
+ R6934HYP |
+ Hyp |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 62 |
+ R6782HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6784HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 64 |
+ R6914HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 65 |
+ R6912HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 66 |
+ R6834HYP |
+ Hyp |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6938HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6940HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6910HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6908HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6896HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6898HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6904HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 74 |
+ R6906HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 75 |
+ R6924HYP |
+ Hyp |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6928HYP |
+ Hyp |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6920HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6868HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 79 |
+ R6900HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 80 |
+ R6902HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 81 |
+ R6876HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 82 |
+ R6884HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 83 |
+ R6840HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 84 |
+ R6832HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 85 |
+ R6944HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 86 |
+ R6942HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 87 |
+ R6756HYP |
+ Hyp |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 88 |
+ R6768HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 89 |
+ R6766HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Inia_hyp_pca_0813/citation.rtf b/general/datasets/Inia_hyp_pca_0813/citation.rtf
new file mode 100644
index 0000000..17f95be
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813/citation.rtf
@@ -0,0 +1 @@
+Mozhui K, Lu L, Armstrong WE, Williams RW. Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci 2012;6:63. PMID:22593731
diff --git a/general/datasets/Inia_hyp_pca_0813/contributors.rtf b/general/datasets/Inia_hyp_pca_0813/contributors.rtf
new file mode 100644
index 0000000..aad2c8a
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813/contributors.rtf
@@ -0,0 +1,15 @@
+
+
+Mozhui K, Lu L, Armstrong WE, Williams RW (2012) Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci. 2012 May 11;6:63. doi: 10.3389/fnins.2012.00063. eCollection 2012.
+
+Abstract
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ significantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantified gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to define hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a). Transcripts associated with the endocrine system and neuropeptide signaling also differ significantly. Sex-differentiated transcripts often have well delimited expression within specific hypothalamic nuclei that have roles in reproduction. For instance, the estrogen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-specific hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modification and gene transcription. In females, the X chromosome paralog, Kdm6a, takes the place of Uty in the same network. We also find significant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-specific modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-specific modulators.
+
+eQTL; hypothalamus; sex-specificity; weighted gene coexpression networks
+
+
+ - PMID: 22593731 PMCID: PMC3350311 DOI: 10.3389/fnins.2012.00063
+
+
+
diff --git a/general/datasets/Inia_hyp_pca_0813/experiment-design.rtf b/general/datasets/Inia_hyp_pca_0813/experiment-design.rtf
new file mode 100644
index 0000000..443af4a
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813/experiment-design.rtf
@@ -0,0 +1,6 @@
+Hypothalamus was dissected from adult male and female mice and process for expression analysis.
+
+RNA isolation
+Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/Inia_hyp_pca_0813/platform.rtf b/general/datasets/Inia_hyp_pca_0813/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_hyp_pca_0813/processing.rtf b/general/datasets/Inia_hyp_pca_0813/processing.rtf
new file mode 100644
index 0000000..b3e8689
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813/processing.rtf
@@ -0,0 +1 @@
+Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/Inia_hyp_pca_0813/summary.rtf b/general/datasets/Inia_hyp_pca_0813/summary.rtf
new file mode 100644
index 0000000..02671d5
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813/summary.rtf
@@ -0,0 +1,16 @@
+These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
+
+Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
+
+Dissection protocol:
+
+
+ - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
+ - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
+ - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
+ - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
+ - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
+ - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
+
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/Inia_hyp_pca_0813_v2/acknowledgment.rtf b/general/datasets/Inia_hyp_pca_0813_v2/acknowledgment.rtf
new file mode 100644
index 0000000..2c3f2bd
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v2/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/Inia_hyp_pca_0813_v2/cases.rtf b/general/datasets/Inia_hyp_pca_0813_v2/cases.rtf
new file mode 100644
index 0000000..f19e9c8
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v2/cases.rtf
@@ -0,0 +1,916 @@
+The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6854HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6862HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6852HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6860HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6864HYP |
+ Hyp |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6866HYP |
+ Hyp |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6858HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6856HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6800HYP |
+ Hyp |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6796HYP |
+ Hyp |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6788HYP |
+ Hyp |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6786HYP |
+ Hyp |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6806HYP |
+ Hyp |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 14 |
+ R6812HYP |
+ Hyp |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 15 |
+ R6804HYP |
+ Hyp |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6792HYP |
+ Hyp |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 17 |
+ R6790HYP |
+ Hyp |
+ BXD27 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 18 |
+ R6798HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 19 |
+ R6794HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 20 |
+ R6816HYP |
+ Hyp |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 21 |
+ R6802HYP |
+ Hyp |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 22 |
+ R6916HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 23 |
+ R6846HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6822HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 25 |
+ R6808HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 26 |
+ R6814HYP |
+ Hyp |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 27 |
+ R6848HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 28 |
+ R6850HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 29 |
+ R6810HYP |
+ Hyp |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 30 |
+ R6758HYP |
+ Hyp |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 31 |
+ R6746HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 32 |
+ R6750HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 33 |
+ R6764HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 34 |
+ R6762HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 35 |
+ R6880HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 36 |
+ R6882HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 37 |
+ R6748HYP |
+ Hyp |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 38 |
+ R6890HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 39 |
+ R6892HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 40 |
+ R6918HYP |
+ Hyp |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 41 |
+ R6894HYP |
+ Hyp |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 42 |
+ R6770HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 43 |
+ R6772HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 44 |
+ R6836HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 45 |
+ R6844HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 46 |
+ R6888HYP |
+ Hyp |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 47 |
+ R6878HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 48 |
+ R6874HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 49 |
+ R6930HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6932HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6776HYP |
+ Hyp |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 52 |
+ R6774HYP |
+ Hyp |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 53 |
+ R6926HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 54 |
+ R6922HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 55 |
+ R6870HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6872HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6778HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 58 |
+ R6780HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 59 |
+ R6838HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 60 |
+ R6830HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 61 |
+ R6934HYP |
+ Hyp |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 62 |
+ R6782HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6784HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 64 |
+ R6914HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 65 |
+ R6912HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 66 |
+ R6834HYP |
+ Hyp |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6938HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6940HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6910HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6908HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6896HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6898HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6904HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 74 |
+ R6906HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 75 |
+ R6924HYP |
+ Hyp |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6928HYP |
+ Hyp |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6920HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6868HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 79 |
+ R6900HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 80 |
+ R6902HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 81 |
+ R6876HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 82 |
+ R6884HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 83 |
+ R6840HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 84 |
+ R6832HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 85 |
+ R6944HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 86 |
+ R6942HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 87 |
+ R6756HYP |
+ Hyp |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 88 |
+ R6768HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 89 |
+ R6766HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Inia_hyp_pca_0813_v2/citation.rtf b/general/datasets/Inia_hyp_pca_0813_v2/citation.rtf
new file mode 100644
index 0000000..17f95be
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v2/citation.rtf
@@ -0,0 +1 @@
+Mozhui K, Lu L, Armstrong WE, Williams RW. Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci 2012;6:63. PMID:22593731
diff --git a/general/datasets/Inia_hyp_pca_0813_v2/contributors.rtf b/general/datasets/Inia_hyp_pca_0813_v2/contributors.rtf
new file mode 100644
index 0000000..aad2c8a
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v2/contributors.rtf
@@ -0,0 +1,15 @@
+
+
+Mozhui K, Lu L, Armstrong WE, Williams RW (2012) Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci. 2012 May 11;6:63. doi: 10.3389/fnins.2012.00063. eCollection 2012.
+
+Abstract
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ significantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantified gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to define hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a). Transcripts associated with the endocrine system and neuropeptide signaling also differ significantly. Sex-differentiated transcripts often have well delimited expression within specific hypothalamic nuclei that have roles in reproduction. For instance, the estrogen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-specific hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modification and gene transcription. In females, the X chromosome paralog, Kdm6a, takes the place of Uty in the same network. We also find significant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-specific modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-specific modulators.
+
+eQTL; hypothalamus; sex-specificity; weighted gene coexpression networks
+
+
+ - PMID: 22593731 PMCID: PMC3350311 DOI: 10.3389/fnins.2012.00063
+
+
+
diff --git a/general/datasets/Inia_hyp_pca_0813_v2/experiment-design.rtf b/general/datasets/Inia_hyp_pca_0813_v2/experiment-design.rtf
new file mode 100644
index 0000000..443af4a
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v2/experiment-design.rtf
@@ -0,0 +1,6 @@
+Hypothalamus was dissected from adult male and female mice and process for expression analysis.
+
+RNA isolation
+Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/Inia_hyp_pca_0813_v2/platform.rtf b/general/datasets/Inia_hyp_pca_0813_v2/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v2/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_hyp_pca_0813_v2/processing.rtf b/general/datasets/Inia_hyp_pca_0813_v2/processing.rtf
new file mode 100644
index 0000000..b3e8689
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v2/processing.rtf
@@ -0,0 +1 @@
+Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/Inia_hyp_pca_0813_v2/summary.rtf b/general/datasets/Inia_hyp_pca_0813_v2/summary.rtf
new file mode 100644
index 0000000..02671d5
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v2/summary.rtf
@@ -0,0 +1,16 @@
+These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
+
+Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
+
+Dissection protocol:
+
+
+ - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
+ - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
+ - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
+ - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
+ - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
+ - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
+
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/Inia_hyp_pca_0813_v3/acknowledgment.rtf b/general/datasets/Inia_hyp_pca_0813_v3/acknowledgment.rtf
new file mode 100644
index 0000000..2c3f2bd
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v3/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/Inia_hyp_pca_0813_v3/cases.rtf b/general/datasets/Inia_hyp_pca_0813_v3/cases.rtf
new file mode 100644
index 0000000..f19e9c8
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v3/cases.rtf
@@ -0,0 +1,916 @@
+The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6854HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6862HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6852HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6860HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6864HYP |
+ Hyp |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6866HYP |
+ Hyp |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6858HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6856HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6800HYP |
+ Hyp |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6796HYP |
+ Hyp |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6788HYP |
+ Hyp |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6786HYP |
+ Hyp |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6806HYP |
+ Hyp |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 14 |
+ R6812HYP |
+ Hyp |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 15 |
+ R6804HYP |
+ Hyp |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6792HYP |
+ Hyp |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 17 |
+ R6790HYP |
+ Hyp |
+ BXD27 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 18 |
+ R6798HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 19 |
+ R6794HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 20 |
+ R6816HYP |
+ Hyp |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 21 |
+ R6802HYP |
+ Hyp |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 22 |
+ R6916HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 23 |
+ R6846HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6822HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 25 |
+ R6808HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 26 |
+ R6814HYP |
+ Hyp |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 27 |
+ R6848HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 28 |
+ R6850HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 29 |
+ R6810HYP |
+ Hyp |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 30 |
+ R6758HYP |
+ Hyp |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 31 |
+ R6746HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 32 |
+ R6750HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 33 |
+ R6764HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 34 |
+ R6762HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 35 |
+ R6880HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 36 |
+ R6882HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 37 |
+ R6748HYP |
+ Hyp |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 38 |
+ R6890HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 39 |
+ R6892HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 40 |
+ R6918HYP |
+ Hyp |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 41 |
+ R6894HYP |
+ Hyp |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 42 |
+ R6770HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 43 |
+ R6772HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 44 |
+ R6836HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 45 |
+ R6844HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 46 |
+ R6888HYP |
+ Hyp |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 47 |
+ R6878HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 48 |
+ R6874HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 49 |
+ R6930HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6932HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6776HYP |
+ Hyp |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 52 |
+ R6774HYP |
+ Hyp |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 53 |
+ R6926HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 54 |
+ R6922HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 55 |
+ R6870HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6872HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6778HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 58 |
+ R6780HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 59 |
+ R6838HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 60 |
+ R6830HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 61 |
+ R6934HYP |
+ Hyp |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 62 |
+ R6782HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6784HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 64 |
+ R6914HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 65 |
+ R6912HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 66 |
+ R6834HYP |
+ Hyp |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6938HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6940HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6910HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6908HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6896HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6898HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6904HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 74 |
+ R6906HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 75 |
+ R6924HYP |
+ Hyp |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6928HYP |
+ Hyp |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6920HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6868HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 79 |
+ R6900HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 80 |
+ R6902HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 81 |
+ R6876HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 82 |
+ R6884HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 83 |
+ R6840HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 84 |
+ R6832HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 85 |
+ R6944HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 86 |
+ R6942HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 87 |
+ R6756HYP |
+ Hyp |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 88 |
+ R6768HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 89 |
+ R6766HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Inia_hyp_pca_0813_v3/citation.rtf b/general/datasets/Inia_hyp_pca_0813_v3/citation.rtf
new file mode 100644
index 0000000..17f95be
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v3/citation.rtf
@@ -0,0 +1 @@
+Mozhui K, Lu L, Armstrong WE, Williams RW. Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci 2012;6:63. PMID:22593731
diff --git a/general/datasets/Inia_hyp_pca_0813_v3/contributors.rtf b/general/datasets/Inia_hyp_pca_0813_v3/contributors.rtf
new file mode 100644
index 0000000..aad2c8a
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v3/contributors.rtf
@@ -0,0 +1,15 @@
+
+
+Mozhui K, Lu L, Armstrong WE, Williams RW (2012) Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci. 2012 May 11;6:63. doi: 10.3389/fnins.2012.00063. eCollection 2012.
+
+Abstract
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ significantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantified gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to define hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a). Transcripts associated with the endocrine system and neuropeptide signaling also differ significantly. Sex-differentiated transcripts often have well delimited expression within specific hypothalamic nuclei that have roles in reproduction. For instance, the estrogen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-specific hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modification and gene transcription. In females, the X chromosome paralog, Kdm6a, takes the place of Uty in the same network. We also find significant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-specific modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-specific modulators.
+
+eQTL; hypothalamus; sex-specificity; weighted gene coexpression networks
+
+
+ - PMID: 22593731 PMCID: PMC3350311 DOI: 10.3389/fnins.2012.00063
+
+
+
diff --git a/general/datasets/Inia_hyp_pca_0813_v3/experiment-design.rtf b/general/datasets/Inia_hyp_pca_0813_v3/experiment-design.rtf
new file mode 100644
index 0000000..443af4a
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v3/experiment-design.rtf
@@ -0,0 +1,6 @@
+Hypothalamus was dissected from adult male and female mice and process for expression analysis.
+
+RNA isolation
+Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/Inia_hyp_pca_0813_v3/platform.rtf b/general/datasets/Inia_hyp_pca_0813_v3/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v3/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_hyp_pca_0813_v3/processing.rtf b/general/datasets/Inia_hyp_pca_0813_v3/processing.rtf
new file mode 100644
index 0000000..b3e8689
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v3/processing.rtf
@@ -0,0 +1 @@
+Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/Inia_hyp_pca_0813_v3/summary.rtf b/general/datasets/Inia_hyp_pca_0813_v3/summary.rtf
new file mode 100644
index 0000000..02671d5
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v3/summary.rtf
@@ -0,0 +1,16 @@
+These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
+
+Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
+
+Dissection protocol:
+
+
+ - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
+ - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
+ - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
+ - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
+ - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
+ - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
+
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/Inia_hyp_pca_0813_v4/acknowledgment.rtf b/general/datasets/Inia_hyp_pca_0813_v4/acknowledgment.rtf
new file mode 100644
index 0000000..2c3f2bd
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v4/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/Inia_hyp_pca_0813_v4/cases.rtf b/general/datasets/Inia_hyp_pca_0813_v4/cases.rtf
new file mode 100644
index 0000000..f19e9c8
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v4/cases.rtf
@@ -0,0 +1,916 @@
+The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6854HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6862HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6852HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6860HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6864HYP |
+ Hyp |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6866HYP |
+ Hyp |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6858HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6856HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6800HYP |
+ Hyp |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6796HYP |
+ Hyp |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6788HYP |
+ Hyp |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6786HYP |
+ Hyp |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6806HYP |
+ Hyp |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 14 |
+ R6812HYP |
+ Hyp |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 15 |
+ R6804HYP |
+ Hyp |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6792HYP |
+ Hyp |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 17 |
+ R6790HYP |
+ Hyp |
+ BXD27 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 18 |
+ R6798HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 19 |
+ R6794HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 20 |
+ R6816HYP |
+ Hyp |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 21 |
+ R6802HYP |
+ Hyp |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 22 |
+ R6916HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 23 |
+ R6846HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6822HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 25 |
+ R6808HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 26 |
+ R6814HYP |
+ Hyp |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 27 |
+ R6848HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 28 |
+ R6850HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 29 |
+ R6810HYP |
+ Hyp |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 30 |
+ R6758HYP |
+ Hyp |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 31 |
+ R6746HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 32 |
+ R6750HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 33 |
+ R6764HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 34 |
+ R6762HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 35 |
+ R6880HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 36 |
+ R6882HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 37 |
+ R6748HYP |
+ Hyp |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 38 |
+ R6890HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 39 |
+ R6892HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 40 |
+ R6918HYP |
+ Hyp |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 41 |
+ R6894HYP |
+ Hyp |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 42 |
+ R6770HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 43 |
+ R6772HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 44 |
+ R6836HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 45 |
+ R6844HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 46 |
+ R6888HYP |
+ Hyp |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 47 |
+ R6878HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 48 |
+ R6874HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 49 |
+ R6930HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6932HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6776HYP |
+ Hyp |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 52 |
+ R6774HYP |
+ Hyp |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 53 |
+ R6926HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 54 |
+ R6922HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 55 |
+ R6870HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6872HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6778HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 58 |
+ R6780HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 59 |
+ R6838HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 60 |
+ R6830HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 61 |
+ R6934HYP |
+ Hyp |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 62 |
+ R6782HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6784HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 64 |
+ R6914HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 65 |
+ R6912HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 66 |
+ R6834HYP |
+ Hyp |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6938HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6940HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6910HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6908HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6896HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6898HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6904HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 74 |
+ R6906HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 75 |
+ R6924HYP |
+ Hyp |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6928HYP |
+ Hyp |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6920HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6868HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 79 |
+ R6900HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 80 |
+ R6902HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 81 |
+ R6876HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 82 |
+ R6884HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 83 |
+ R6840HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 84 |
+ R6832HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 85 |
+ R6944HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 86 |
+ R6942HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 87 |
+ R6756HYP |
+ Hyp |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 88 |
+ R6768HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 89 |
+ R6766HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Inia_hyp_pca_0813_v4/citation.rtf b/general/datasets/Inia_hyp_pca_0813_v4/citation.rtf
new file mode 100644
index 0000000..17f95be
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v4/citation.rtf
@@ -0,0 +1 @@
+Mozhui K, Lu L, Armstrong WE, Williams RW. Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci 2012;6:63. PMID:22593731
diff --git a/general/datasets/Inia_hyp_pca_0813_v4/contributors.rtf b/general/datasets/Inia_hyp_pca_0813_v4/contributors.rtf
new file mode 100644
index 0000000..aad2c8a
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v4/contributors.rtf
@@ -0,0 +1,15 @@
+
+
+Mozhui K, Lu L, Armstrong WE, Williams RW (2012) Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci. 2012 May 11;6:63. doi: 10.3389/fnins.2012.00063. eCollection 2012.
+
+Abstract
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ significantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantified gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to define hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a). Transcripts associated with the endocrine system and neuropeptide signaling also differ significantly. Sex-differentiated transcripts often have well delimited expression within specific hypothalamic nuclei that have roles in reproduction. For instance, the estrogen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-specific hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modification and gene transcription. In females, the X chromosome paralog, Kdm6a, takes the place of Uty in the same network. We also find significant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-specific modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-specific modulators.
+
+eQTL; hypothalamus; sex-specificity; weighted gene coexpression networks
+
+
+ - PMID: 22593731 PMCID: PMC3350311 DOI: 10.3389/fnins.2012.00063
+
+
+
diff --git a/general/datasets/Inia_hyp_pca_0813_v4/experiment-design.rtf b/general/datasets/Inia_hyp_pca_0813_v4/experiment-design.rtf
new file mode 100644
index 0000000..443af4a
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v4/experiment-design.rtf
@@ -0,0 +1,6 @@
+Hypothalamus was dissected from adult male and female mice and process for expression analysis.
+
+RNA isolation
+Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/Inia_hyp_pca_0813_v4/platform.rtf b/general/datasets/Inia_hyp_pca_0813_v4/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v4/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_hyp_pca_0813_v4/processing.rtf b/general/datasets/Inia_hyp_pca_0813_v4/processing.rtf
new file mode 100644
index 0000000..b3e8689
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v4/processing.rtf
@@ -0,0 +1 @@
+Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/Inia_hyp_pca_0813_v4/summary.rtf b/general/datasets/Inia_hyp_pca_0813_v4/summary.rtf
new file mode 100644
index 0000000..02671d5
--- /dev/null
+++ b/general/datasets/Inia_hyp_pca_0813_v4/summary.rtf
@@ -0,0 +1,16 @@
+These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
+
+Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
+
+Dissection protocol:
+
+
+ - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
+ - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
+ - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
+ - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
+ - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
+ - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
+
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/Inia_hyp_rma_1110/acknowledgment.rtf b/general/datasets/Inia_hyp_rma_1110/acknowledgment.rtf
new file mode 100644
index 0000000..2c3f2bd
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_1110/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/Inia_hyp_rma_1110/cases.rtf b/general/datasets/Inia_hyp_rma_1110/cases.rtf
new file mode 100644
index 0000000..f19e9c8
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_1110/cases.rtf
@@ -0,0 +1,916 @@
+The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6854HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6862HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6852HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6860HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6864HYP |
+ Hyp |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6866HYP |
+ Hyp |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6858HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6856HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6800HYP |
+ Hyp |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6796HYP |
+ Hyp |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6788HYP |
+ Hyp |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6786HYP |
+ Hyp |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6806HYP |
+ Hyp |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 14 |
+ R6812HYP |
+ Hyp |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 15 |
+ R6804HYP |
+ Hyp |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6792HYP |
+ Hyp |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 17 |
+ R6790HYP |
+ Hyp |
+ BXD27 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 18 |
+ R6798HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 19 |
+ R6794HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 20 |
+ R6816HYP |
+ Hyp |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 21 |
+ R6802HYP |
+ Hyp |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 22 |
+ R6916HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 23 |
+ R6846HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6822HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 25 |
+ R6808HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 26 |
+ R6814HYP |
+ Hyp |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 27 |
+ R6848HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 28 |
+ R6850HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 29 |
+ R6810HYP |
+ Hyp |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 30 |
+ R6758HYP |
+ Hyp |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 31 |
+ R6746HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 32 |
+ R6750HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 33 |
+ R6764HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 34 |
+ R6762HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 35 |
+ R6880HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 36 |
+ R6882HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 37 |
+ R6748HYP |
+ Hyp |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 38 |
+ R6890HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 39 |
+ R6892HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 40 |
+ R6918HYP |
+ Hyp |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 41 |
+ R6894HYP |
+ Hyp |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 42 |
+ R6770HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 43 |
+ R6772HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 44 |
+ R6836HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 45 |
+ R6844HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 46 |
+ R6888HYP |
+ Hyp |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 47 |
+ R6878HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 48 |
+ R6874HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 49 |
+ R6930HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6932HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6776HYP |
+ Hyp |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 52 |
+ R6774HYP |
+ Hyp |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 53 |
+ R6926HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 54 |
+ R6922HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 55 |
+ R6870HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6872HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6778HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 58 |
+ R6780HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 59 |
+ R6838HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 60 |
+ R6830HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 61 |
+ R6934HYP |
+ Hyp |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 62 |
+ R6782HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6784HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 64 |
+ R6914HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 65 |
+ R6912HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 66 |
+ R6834HYP |
+ Hyp |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6938HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6940HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6910HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6908HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6896HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6898HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6904HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 74 |
+ R6906HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 75 |
+ R6924HYP |
+ Hyp |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6928HYP |
+ Hyp |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6920HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6868HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 79 |
+ R6900HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 80 |
+ R6902HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 81 |
+ R6876HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 82 |
+ R6884HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 83 |
+ R6840HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 84 |
+ R6832HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 85 |
+ R6944HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 86 |
+ R6942HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 87 |
+ R6756HYP |
+ Hyp |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 88 |
+ R6768HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 89 |
+ R6766HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Inia_hyp_rma_1110/citation.rtf b/general/datasets/Inia_hyp_rma_1110/citation.rtf
new file mode 100644
index 0000000..17f95be
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_1110/citation.rtf
@@ -0,0 +1 @@
+Mozhui K, Lu L, Armstrong WE, Williams RW. Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci 2012;6:63. PMID:22593731
diff --git a/general/datasets/Inia_hyp_rma_1110/contributors.rtf b/general/datasets/Inia_hyp_rma_1110/contributors.rtf
new file mode 100644
index 0000000..aad2c8a
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_1110/contributors.rtf
@@ -0,0 +1,15 @@
+
+
+Mozhui K, Lu L, Armstrong WE, Williams RW (2012) Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci. 2012 May 11;6:63. doi: 10.3389/fnins.2012.00063. eCollection 2012.
+
+Abstract
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ significantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantified gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to define hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a). Transcripts associated with the endocrine system and neuropeptide signaling also differ significantly. Sex-differentiated transcripts often have well delimited expression within specific hypothalamic nuclei that have roles in reproduction. For instance, the estrogen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-specific hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modification and gene transcription. In females, the X chromosome paralog, Kdm6a, takes the place of Uty in the same network. We also find significant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-specific modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-specific modulators.
+
+eQTL; hypothalamus; sex-specificity; weighted gene coexpression networks
+
+
+ - PMID: 22593731 PMCID: PMC3350311 DOI: 10.3389/fnins.2012.00063
+
+
+
diff --git a/general/datasets/Inia_hyp_rma_1110/experiment-design.rtf b/general/datasets/Inia_hyp_rma_1110/experiment-design.rtf
new file mode 100644
index 0000000..443af4a
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_1110/experiment-design.rtf
@@ -0,0 +1,6 @@
+Hypothalamus was dissected from adult male and female mice and process for expression analysis.
+
+RNA isolation
+Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/Inia_hyp_rma_1110/platform.rtf b/general/datasets/Inia_hyp_rma_1110/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_1110/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_hyp_rma_1110/processing.rtf b/general/datasets/Inia_hyp_rma_1110/processing.rtf
new file mode 100644
index 0000000..b3e8689
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_1110/processing.rtf
@@ -0,0 +1 @@
+Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/Inia_hyp_rma_1110/summary.rtf b/general/datasets/Inia_hyp_rma_1110/summary.rtf
new file mode 100644
index 0000000..02671d5
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_1110/summary.rtf
@@ -0,0 +1,16 @@
+These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
+
+Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
+
+Dissection protocol:
+
+
+ - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
+ - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
+ - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
+ - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
+ - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
+ - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
+
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/Inia_hyp_rma_ex_1110/acknowledgment.rtf b/general/datasets/Inia_hyp_rma_ex_1110/acknowledgment.rtf
new file mode 100644
index 0000000..2c3f2bd
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_ex_1110/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported by Integrative Neuroscience Initiative on Alcoholism grants U01AA13499, U01AA017590, U01AA0016662. The authors are also grateful to Arthur Centeno and Lorne Rose, and the Molecular Resource Center at UTHSC.
diff --git a/general/datasets/Inia_hyp_rma_ex_1110/cases.rtf b/general/datasets/Inia_hyp_rma_ex_1110/cases.rtf
new file mode 100644
index 0000000..f19e9c8
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_ex_1110/cases.rtf
@@ -0,0 +1,916 @@
+The BXD recombinant inbred strains are derived from crossing the C57BL/6J (B6) and DBA/2J (D2) parental strains and inbreeding for over 20 generations (Taylor et al., 1999; Peirce et al., 2004). All mice used in this study were born and housed at the University of Tennessee Health Science Center. Mice were kept at an average of 3–4 per cage in a temperature-controlled vivarium (22 deg C) and maintained at a 12 h light/dark cycle. All animal protocols were approved by the Animal Care and Use Committee. We studied a total of 50 BXD strains, but only acquired matched male–female data pairs for 39 strains (35 BXD strains, parental B6 and D2, and two reciprocal F1 hybrids, B6D2F1 and D2B6F1). The average age of mice was 78 days. We provide more detail on the experimen-tal design and precise age and time of sacriï¬ce of all cases at stored in 4 deg C for 2–3 days. To dissect the hypothalamus, the brain was placed with the ventral side facing up in a coronal "brain cutting" matrix. Using the medial mammillary body as landmark, a vertical cut was made right along the posterior boundary of the hypothala-mus. A second vertical cut was made 2 mm from the ï¬rst cut. This edge lies slightly caudal to the optic chiasm and cuts through the retrochiasmatic nucleus. The hypothalamus was then sliced out from this 2 mm thick section. Each of the 39 mouse strains is represented by male and female samples (total of 78 microarray samples). Each individual sample consisted of tissue pooled from two mice of the same strain and sex that are usually littermates. The total number of mice used was 78 females and 78 males. RNA was puriï¬ed using the RNAeasy micro kit on the QIAcube system (Qiagen)2. RNA purity and concen-tration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+ Date sacrifice |
+ Time sacrifice |
+
+
+ | 1 |
+ R6854HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 2 |
+ R6862HYP |
+ Hyp |
+ C57BL/6J |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 3 |
+ R6852HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 4 |
+ R6860HYP |
+ Hyp |
+ D2B6F1 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 5 |
+ R6864HYP |
+ Hyp |
+ DBA/2J |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 6 |
+ R6866HYP |
+ Hyp |
+ DBA/2J |
+ 68 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 7 |
+ R6858HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 8 |
+ R6856HYP |
+ Hyp |
+ B6D2F1 |
+ 69 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 9 |
+ R6800HYP |
+ Hyp |
+ BXD1 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 10 |
+ R6796HYP |
+ Hyp |
+ BXD1 |
+ 85 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 11 |
+ R6788HYP |
+ Hyp |
+ BXD11 |
+ 87 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 12 |
+ R6786HYP |
+ Hyp |
+ BXD11 |
+ 76 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 13 |
+ R6806HYP |
+ Hyp |
+ BXD12 |
+ 77 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 14 |
+ R6812HYP |
+ Hyp |
+ BXD14 |
+ 81 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 15 |
+ R6804HYP |
+ Hyp |
+ BXD24 |
+ 85 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 16 |
+ R6792HYP |
+ Hyp |
+ BXD27 |
+ 75 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 17 |
+ R6790HYP |
+ Hyp |
+ BXD27 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 18 |
+ R6798HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 19 |
+ R6794HYP |
+ Hyp |
+ BXD29 |
+ 71 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 20 |
+ R6816HYP |
+ Hyp |
+ BXD31 |
+ 74 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 21 |
+ R6802HYP |
+ Hyp |
+ BXD31 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 22 |
+ R6916HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 23 |
+ R6846HYP |
+ Hyp |
+ BXD32 |
+ 81 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 24 |
+ R6822HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 25 |
+ R6808HYP |
+ Hyp |
+ BXD34 |
+ 77 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 26 |
+ R6814HYP |
+ Hyp |
+ BXD39 |
+ 79 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 27 |
+ R6848HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 28 |
+ R6850HYP |
+ Hyp |
+ BXD40 |
+ 85 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 29 |
+ R6810HYP |
+ Hyp |
+ BXD42 |
+ 87 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 30 |
+ R6758HYP |
+ Hyp |
+ BXD43 |
+ 81 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 31 |
+ R6746HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 32 |
+ R6750HYP |
+ Hyp |
+ BXD44 |
+ 83 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 33 |
+ R6764HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 34 |
+ R6762HYP |
+ Hyp |
+ BXD45 |
+ 77 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 35 |
+ R6880HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 36 |
+ R6882HYP |
+ Hyp |
+ BXD48 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 37 |
+ R6748HYP |
+ Hyp |
+ BXD49 |
+ 84 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 38 |
+ R6890HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 39 |
+ R6892HYP |
+ Hyp |
+ BXD50 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 40 |
+ R6918HYP |
+ Hyp |
+ BXD56 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 41 |
+ R6894HYP |
+ Hyp |
+ BXD56 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 42 |
+ R6770HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 43 |
+ R6772HYP |
+ Hyp |
+ BXD60 |
+ 70 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 44 |
+ R6836HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 45 |
+ R6844HYP |
+ Hyp |
+ BXD62 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 46 |
+ R6888HYP |
+ Hyp |
+ BXD63 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 47 |
+ R6878HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 48 |
+ R6874HYP |
+ Hyp |
+ BXD65 |
+ 84 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 49 |
+ R6930HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 50 |
+ R6932HYP |
+ Hyp |
+ BXD68 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 51 |
+ R6776HYP |
+ Hyp |
+ BXD69 |
+ 69 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 52 |
+ R6774HYP |
+ Hyp |
+ BXD69 |
+ 80 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 53 |
+ R6926HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 54 |
+ R6922HYP |
+ Hyp |
+ BXD70 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 55 |
+ R6870HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 56 |
+ R6872HYP |
+ Hyp |
+ BXD71 |
+ 76 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 57 |
+ R6778HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 58 |
+ R6780HYP |
+ Hyp |
+ BXD73 |
+ 83 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 59 |
+ R6838HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 60 |
+ R6830HYP |
+ Hyp |
+ BXD75 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 61 |
+ R6934HYP |
+ Hyp |
+ BXD79 |
+ 87 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 62 |
+ R6782HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ F |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 63 |
+ R6784HYP |
+ Hyp |
+ BXD80 |
+ 73 |
+ M |
+ 8/17/10 |
+ 1:15 PM to 5 PM |
+
+
+ | 64 |
+ R6914HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 65 |
+ R6912HYP |
+ Hyp |
+ BXD83 |
+ 81 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 66 |
+ R6834HYP |
+ Hyp |
+ BXD84 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 67 |
+ R6938HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 68 |
+ R6940HYP |
+ Hyp |
+ BXD85 |
+ 74 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 69 |
+ R6910HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 70 |
+ R6908HYP |
+ Hyp |
+ BXD87 |
+ 83 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 71 |
+ R6896HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 72 |
+ R6898HYP |
+ Hyp |
+ BXD89 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 73 |
+ R6904HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 74 |
+ R6906HYP |
+ Hyp |
+ BXD90 |
+ 82 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 75 |
+ R6924HYP |
+ Hyp |
+ BXD92 |
+ 86 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 76 |
+ R6928HYP |
+ Hyp |
+ BXD92 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 77 |
+ R6920HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 78 |
+ R6868HYP |
+ Hyp |
+ BXD95 |
+ 76 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 79 |
+ R6900HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 80 |
+ R6902HYP |
+ Hyp |
+ BXD97 |
+ 71 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 81 |
+ R6876HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 82 |
+ R6884HYP |
+ Hyp |
+ BXD99 |
+ 77 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 83 |
+ R6840HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ F |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 84 |
+ R6832HYP |
+ Hyp |
+ BXD100 |
+ 83 |
+ M |
+ 8/18/10 |
+ 8:45AM to 12:30 PM |
+
+
+ | 85 |
+ R6944HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ F |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 86 |
+ R6942HYP |
+ Hyp |
+ BXD101 |
+ 89 |
+ M |
+ 8/18/10 |
+ 1 PM to 6:45 PM |
+
+
+ | 87 |
+ R6756HYP |
+ Hyp |
+ BXD102 |
+ 88 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 88 |
+ R6768HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ F |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+ | 89 |
+ R6766HYP |
+ Hyp |
+ BXD103 |
+ 78 |
+ M |
+ 8/17/10 |
+ 9:30 AM to 12:30AM |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Inia_hyp_rma_ex_1110/citation.rtf b/general/datasets/Inia_hyp_rma_ex_1110/citation.rtf
new file mode 100644
index 0000000..17f95be
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_ex_1110/citation.rtf
@@ -0,0 +1 @@
+Mozhui K, Lu L, Armstrong WE, Williams RW. Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci 2012;6:63. PMID:22593731
diff --git a/general/datasets/Inia_hyp_rma_ex_1110/contributors.rtf b/general/datasets/Inia_hyp_rma_ex_1110/contributors.rtf
new file mode 100644
index 0000000..aad2c8a
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_ex_1110/contributors.rtf
@@ -0,0 +1,15 @@
+
+
+Mozhui K, Lu L, Armstrong WE, Williams RW (2012) Sex-specific modulation of gene expression networks in murine hypothalamus. Front Neurosci. 2012 May 11;6:63. doi: 10.3389/fnins.2012.00063. eCollection 2012.
+
+Abstract
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ significantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantified gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to define hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a). Transcripts associated with the endocrine system and neuropeptide signaling also differ significantly. Sex-differentiated transcripts often have well delimited expression within specific hypothalamic nuclei that have roles in reproduction. For instance, the estrogen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-specific hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modification and gene transcription. In females, the X chromosome paralog, Kdm6a, takes the place of Uty in the same network. We also find significant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-specific modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-specific modulators.
+
+eQTL; hypothalamus; sex-specificity; weighted gene coexpression networks
+
+
+ - PMID: 22593731 PMCID: PMC3350311 DOI: 10.3389/fnins.2012.00063
+
+
+
diff --git a/general/datasets/Inia_hyp_rma_ex_1110/experiment-design.rtf b/general/datasets/Inia_hyp_rma_ex_1110/experiment-design.rtf
new file mode 100644
index 0000000..443af4a
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_ex_1110/experiment-design.rtf
@@ -0,0 +1,6 @@
+Hypothalamus was dissected from adult male and female mice and process for expression analysis.
+
+RNA isolation
+Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+This preliminary data set is associated with 430 eQTLs with LOD scores above 10. Peak LRS is 146 for Trait ID 10513604 (Hdhd3).
diff --git a/general/datasets/Inia_hyp_rma_ex_1110/platform.rtf b/general/datasets/Inia_hyp_rma_ex_1110/platform.rtf
new file mode 100644
index 0000000..aba2206
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_ex_1110/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version] (GPL6246)
diff --git a/general/datasets/Inia_hyp_rma_ex_1110/processing.rtf b/general/datasets/Inia_hyp_rma_ex_1110/processing.rtf
new file mode 100644
index 0000000..b3e8689
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_ex_1110/processing.rtf
@@ -0,0 +1 @@
+Total RNA was processed using standard protocols and hybridized to the Affymetrix Mouse Gene 1.0 ST arrays4. This array contains 34,700 probe sets that target ∼29,000 well-deï¬ned transcripts (RefSeq mRNA isoforms). A single probe set is a collection of about 27 probes that target known exons within a single gene. The multiple probes design provides a more comprehensive cov-erage of transcripts from a single gene. Male and female samples were interleaved and processed together to avoid batch confounds. Details on the strain, age, and sex of each sample can be obtained from the information available for the INIA Hypothalamus Affy MoGene 1.0 ST (Nov10) data set on www.genenetwork.org. Probe set level intensity values were extracted from the CEL ï¬les using the Affymetrix GeneChip Operating Software. Data nor-malization was performed using the R package “Affy” available from www.Bioconductor.org. The Robust Multichip Averaging protocol was used to process the expression values. The array data was then log transformed and rescaled using a z-scoring procedure to set the mean of each sample at eight expression units with a SD of 2 units. The entire data set can be down-loaded from www.genenetwork.org using the accession number GN281 (http://www.genenetwork.org/webqtl/main.py?FormID = sharinginfo&GN_AccessionId = 281) and also from the NIH Gene Expression Omnibus5 using the GEO accession number GSE36674. For this study we used a subset of cases that were repre-sented by both male and female samples – 78 sex-balanced arrays. Statistical power provided by this sample size (N = 39 strains) was estimated using the R function power.t.test6 with the SD set at 0.17, which is the average value. Only transcripts with above aver-age expression (minimum expression value above 8.5 on a log2 scale) were included for further analysis (17,192 probe sets). We used a two-tailed paired t -test to identify transcripts with signiï¬-cant expression difference between males and females. We applied the Benjamini and Hochberg false discovery rate (FDR) method and selected differentially expressed transcripts using a 10% FDR criterion.
diff --git a/general/datasets/Inia_hyp_rma_ex_1110/summary.rtf b/general/datasets/Inia_hyp_rma_ex_1110/summary.rtf
new file mode 100644
index 0000000..02671d5
--- /dev/null
+++ b/general/datasets/Inia_hyp_rma_ex_1110/summary.rtf
@@ -0,0 +1,16 @@
+These hypothalamic gene expression data were generated by Khyobeni Mozhui, Lu Lu, and Robert W. Williams and colleagues with funding support from NIAAA. The data set includes samples from 50 strains, including 46 BXDs, both parental strains, and reciprocal F1 hybrids. Expression data were generated using the Affymetrix Mouse Gene 1.0 ST exon-style microarray (multiple probes in all known exons) by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. Hypothalamic tissue was dissected by K. Mozhui (description to follow) with special attention to time of day (every sample has time stamp). RNA was extracted by K. Mozhui. All other processing steps by the UTHSC MRC by L. Rose. Data were processed by Arthur Centeno.
+
+Data released initially Nov 25, 2010, updated March 7, 2011 by A. Centeno and K. Mozhui to add two additional arrays. Data appear to be error-free in terms of sex and strain assignments shown in the table below.
+
+Dissection protocol:
+
+
+ - Animals were sacrificed by quick cervical dislocation and brains were removed and stored in RNAlater (www.ambion.com) for 2 to 3 days
+ - Brain was placed with ventral side up and a partial cut was made with a blade at -2.5 from Bregma (just a little rostral from the pontine fibres when viewed from the ventral side)
+ - The brain was then place in a coronal matrix and a 2 mm section was made rostral to the first cut
+ - The 2mm Section was placed on a clean glass slide and hypothalamus was sliced out and placed in a tube on dry ice.
+ - To dissect out the BLA, the temporal lobes were detached by placing a scalple in the lateral ventricles and teasing it apart. The cortical amygdala was removed and the BLA was then sliced out and placed in a tube on dry ice.
+ - Tissues from two mice of the same strain and sex were pooled. The only exceptions to this are the BLA samples for strains BXD5, BXD13, BXD16, BXD19, BXD25, BXD38, BXD51, and BXD61 (tissue from only one animal).
+
+
+The hypothalamus contains nuclei and cell populations that are critical in reproduction and that differ signiï¬cantly between the sexes in structure and function. To examine the molecular and genetic basis for these differences, we quantiï¬ed gene expression in the hypothalamus of 39 pairs of adult male and female mice belonging to the BXD strains. This experimental design enabled us to deï¬ne hypothalamic gene coexpression networks and provided robust estimates of absolute expression differences. As expected, sex has the strongest effect on the expression of genes on the X and Y chromosomes (e.g., Uty, Xist, Kdm6a).Transcripts associated with the endocrine system and neuropeptide signaling also differ signiï¬cantly. Sex-differentiated transcripts often have well delimited expression within speciï¬c hypothalamic nuclei that have roles in reproduction. For instance, the estro-gen receptor (Esr1) and neurokinin B (Tac2) genes have intense expression in the medial preoptic and arcuate nuclei and comparatively high expression in females. Despite the strong effect of sex on single transcripts, the global pattern of covariance among transcripts is well preserved, and consequently, males and females have well matched coexpression modules. However, there are sex-speciï¬c hub genes in functionally equivalent modules. For example, only in males is the Y-linked gene, Uty, a highly connected transcript in a network that regulates chromatin modiï¬cation and gene transcription. In females, the X chromo-some paralog, Kdm6a, takes the place of Uty in the same network. We also ï¬nd signiï¬cant effect of sex on genetic regulation and the same network in males and females can be associated with markedly different regulatory loci. With the exception of a few sex-speciï¬c modules, our analysis reveals a system in which sets of functionally related transcripts are organized into stable sex-independent networks that are controlled at a higher level by sex-speciï¬c modulators.
diff --git a/general/datasets/Inia_lcm_1215/acknowledgment.rtf b/general/datasets/Inia_lcm_1215/acknowledgment.rtf
new file mode 100644
index 0000000..8b7d4ad
--- /dev/null
+++ b/general/datasets/Inia_lcm_1215/acknowledgment.rtf
@@ -0,0 +1 @@
+Thanks to NIH NIAAA and funding support was provided by INIA grants U01AA013499 and U01AA06662.
diff --git a/general/datasets/Inia_lcm_1215/cases.rtf b/general/datasets/Inia_lcm_1215/cases.rtf
new file mode 100644
index 0000000..4d95e2a
--- /dev/null
+++ b/general/datasets/Inia_lcm_1215/cases.rtf
@@ -0,0 +1 @@
+Male C57BL/6J and DBA/2J mice (10 weeks old upon arrival) were purchased from the Jackson Laboratory and assigned to either baseline untreated control (BAS), the air control (AIR), or CIE group. Mice were individually housed with free access to food (Harland Teklad, Madison, WI) and water throughout all phases of the experiments. Body weights were recorded weekly during ethanol-drinking weeks or daily during chronic intermittent ethanol (CIE) or air exposure (detailed below). Mice were housed in a temperature- and humidity-controlled an- imal facility under a reversed 12-h light/dark cycle (lights on at 0200 h). Mice were not food- or water-deprived at any time during the study. All procedures were approved by the Institutional Ani- mal Care and Use Committee at the Medical University of South Carolina (MUSC). Brain tissue was removed at MUSC and shipped to UTHSC for laser capture microdissection (LCM).
diff --git a/general/datasets/Inia_lcm_1215/contributors.rtf b/general/datasets/Inia_lcm_1215/contributors.rtf
new file mode 100644
index 0000000..edf124f
--- /dev/null
+++ b/general/datasets/Inia_lcm_1215/contributors.rtf
@@ -0,0 +1,5 @@
+Megan K. Mulligan, Khyobeni Mozhui, Ashutosh K. Pandey, Maren L. Smith, Suzhen Gong, Jesse Ingels, Michael F. Miles, Marcelo F. Lopez, Lu Lu, Robert W. Williams
+
+
+
+Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.alcohol.2016.09.001.
diff --git a/general/datasets/Inia_lcm_1215/platform.rtf b/general/datasets/Inia_lcm_1215/platform.rtf
new file mode 100644
index 0000000..25cb790
--- /dev/null
+++ b/general/datasets/Inia_lcm_1215/platform.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+(Updated Dec 9, 2015 by AC and RW)
+
+Annotation data for transcripts and genes were downloaded from ENSEMBL by Arthur Centeno, December 2015. We downloaded the entire transcript database at http://useast.ensembl.org/Mus_musculus/Info/Index.
+
+The positions of transcripts and genes on the mouse assembly are version GRCm38.p4 (mm10 equivalent). However, we converted all chromosome coordinates to the mm9 assembly to be consistent with all other GN1 data sets. However, for some sequences, mostly on Chr Y and the mitochondrial genome, the values are mm10 equivalent (we had no corresponding mm9 values).
+
+We also extracted sequence data corresponding to the transcripts whenever these data were available. However in some cases we do not have sequence data at all.
diff --git a/general/datasets/Inia_lcm_1215/processing.rtf b/general/datasets/Inia_lcm_1215/processing.rtf
new file mode 100644
index 0000000..f04ab87
--- /dev/null
+++ b/general/datasets/Inia_lcm_1215/processing.rtf
@@ -0,0 +1,5 @@
+RNA from tissue trapped in the CapSure LCM caps was extracted using the PicoPure RNA isolation kit (Life Technologies) according to the manufacturer's instructions (RNA was eluted from provided capture columns in 13.5-mL nuclease-free water). RNA quality was analyzed using a Bioanalyzer (Model 100, Agilent, Foster City, CA). Samples with an associated RNA integrity number (RIN) greater than 6 were subsequently used for RNA sequencing.
+
+
+
+Poly-A enriched mRNA was sequenced on two platforms, ABI SOLID 550XL Wildfire (65 samples) and Ion Proton (39 samples). Read length was 50 nt for the SOLID system and the average read length for the Proton system was ~180 nt. Reads generated on the SOLID system were aligned to the mm10 reference genome using the LifeScope aligner, and BAM files were subsequently generated using custom scripts for third-party downstream analysis. For the Proton system, reads were also aligned to the mm10 (Ensemble GRCm38) reference genome using TopHat2. Settings for TopHat2 are as follows: “-p 15 -N 4 –read-gap-length 6 –read-edit-dist 8 –max-insertion-length 6 –max-deletion-length 6 –max-intron-length 300000 –b2-very-sensitive”. Alignments on both platforms were splice-aware. RSeQC-2.6.1 (RPKM_count.py) was used to generate count data based on mm10 GENECODE Basic transcript annotation (43,320 transcripts detected). We selected this annotation for greater reproducibility with existing microarray data sets and to simplify downstream analysis by limiting the number of transcript models for each gene. On average, 2.5 million and 7.8 million reads uniquely aligned to transcript models on the SOLID and Proton platforms, respectively. Data were further filtered to remove tran- scripts that had less than 1 count in 90% or more samples. After filtering, 24,597 transcripts representing 12,011 unique genes remained (Supplemental Table 1). The variance stabilizing trans- form (R package DESeq2, FitType 1⁄4 local) was applied to the count data, and transformed data were corrected by dividing by transcript length to generate log2 reads per kilobase gene model (RPK) values. The use of two different sequencing platforms was corrected using batch correction (ComBat, Supplemental Fig. 3). All data filtering, transformations, and batch correction were performed using custom R scripts. Batch-corrected and transformed log2 RPK and log2 count values are available in Supplemental Tables 2 and 3, and log2 RPK data are also available at GeneNetwork [http://www. genenetwork.org/webqtl/main.py?FormID1⁄4sharinginfo&GN_ AccessionId1⁄4772; Group 1⁄4 Chronic Intermittent Ethanol, Type 1⁄4 LCM Brain Regions mRNA, Data set 1⁄4 INIA LCM (11 Regions) CIE/AIR RNA-seq Transcript Level (Dec15)].
diff --git a/general/datasets/Inia_lcm_1215/summary.rtf b/general/datasets/Inia_lcm_1215/summary.rtf
new file mode 100644
index 0000000..45d122d
--- /dev/null
+++ b/general/datasets/Inia_lcm_1215/summary.rtf
@@ -0,0 +1 @@
+This dataset is open. Please contact Dr. Megan K. Mulligan (mmulliga@uthsc.edu) or Dr. Robert W. Williams (rwilliams@uthsc.edu) if you need more information or low-level data access.
diff --git a/general/datasets/Inia_lcm_1215/tissue.rtf b/general/datasets/Inia_lcm_1215/tissue.rtf
new file mode 100644
index 0000000..6a51951
--- /dev/null
+++ b/general/datasets/Inia_lcm_1215/tissue.rtf
@@ -0,0 +1,5 @@
+Whole brain tissue was sectioned at 10 mm using a Leica cryostat and mounted in series with 6e8 sections per slide onto uncharged and uncoated glass slides. Mounted sections were dehydrated in 100% methanol (90 s), 70% ethanol (1 min), 95% ethanol (1 min), 100% ethanol (1 min 2), xylene (5 min). Slides were then allowed to air dry for 10 min under a fume hood.
+
+Series were created from distinct coronal sections (bregma po- sitions based on a C57BL/6J reference brain atlas) and individual regions were matched across section and harvested by LCM (Supplemental Fig. 2). Prelimbic (PrL) and infralimbic (ILC) cortex included a series spanning from bregma 1.98 to 1.54 mm. The accumbens core (NAc) and shell (NAs) series were collected from bregma 1.54 to 0.98 mm, and dorsolateral (DLS) and dorsomedial (DMS) striatum and bed nucleus stria terminalis (BST) were collected from bregma 0.38 to 0.10 mm. Basolateral (BLA) and central nucleus (CeA) of the amygdala series were collected from bregma 0.58 to 1.22 mm and hippocampus (CA1 and CA3) was collected from bregma 1.46 to 2.46 mm. Finally, the ventral tegmental area (VTA) and primary visual cortex (VCX) series were collected from bregma 3.28 to 3.80 mm.
+
+Arcturus XT (Life Technologies) was used to capture 13 brain areas. The infrared laser was then used to capture the tissue onto CapSure LCM caps (Life Technologies, laser spot power set to 70 mV with a duration of 25 msec).
diff --git a/general/datasets/Inia_lcm_cab_1215/acknowledgment.rtf b/general/datasets/Inia_lcm_cab_1215/acknowledgment.rtf
new file mode 100644
index 0000000..8b7d4ad
--- /dev/null
+++ b/general/datasets/Inia_lcm_cab_1215/acknowledgment.rtf
@@ -0,0 +1 @@
+Thanks to NIH NIAAA and funding support was provided by INIA grants U01AA013499 and U01AA06662.
diff --git a/general/datasets/Inia_lcm_cab_1215/cases.rtf b/general/datasets/Inia_lcm_cab_1215/cases.rtf
new file mode 100644
index 0000000..4d95e2a
--- /dev/null
+++ b/general/datasets/Inia_lcm_cab_1215/cases.rtf
@@ -0,0 +1 @@
+Male C57BL/6J and DBA/2J mice (10 weeks old upon arrival) were purchased from the Jackson Laboratory and assigned to either baseline untreated control (BAS), the air control (AIR), or CIE group. Mice were individually housed with free access to food (Harland Teklad, Madison, WI) and water throughout all phases of the experiments. Body weights were recorded weekly during ethanol-drinking weeks or daily during chronic intermittent ethanol (CIE) or air exposure (detailed below). Mice were housed in a temperature- and humidity-controlled an- imal facility under a reversed 12-h light/dark cycle (lights on at 0200 h). Mice were not food- or water-deprived at any time during the study. All procedures were approved by the Institutional Ani- mal Care and Use Committee at the Medical University of South Carolina (MUSC). Brain tissue was removed at MUSC and shipped to UTHSC for laser capture microdissection (LCM).
diff --git a/general/datasets/Inia_lcm_cab_1215/contributors.rtf b/general/datasets/Inia_lcm_cab_1215/contributors.rtf
new file mode 100644
index 0000000..edf124f
--- /dev/null
+++ b/general/datasets/Inia_lcm_cab_1215/contributors.rtf
@@ -0,0 +1,5 @@
+Megan K. Mulligan, Khyobeni Mozhui, Ashutosh K. Pandey, Maren L. Smith, Suzhen Gong, Jesse Ingels, Michael F. Miles, Marcelo F. Lopez, Lu Lu, Robert W. Williams
+
+
+
+Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.alcohol.2016.09.001.
diff --git a/general/datasets/Inia_lcm_cab_1215/platform.rtf b/general/datasets/Inia_lcm_cab_1215/platform.rtf
new file mode 100644
index 0000000..25cb790
--- /dev/null
+++ b/general/datasets/Inia_lcm_cab_1215/platform.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+(Updated Dec 9, 2015 by AC and RW)
+
+Annotation data for transcripts and genes were downloaded from ENSEMBL by Arthur Centeno, December 2015. We downloaded the entire transcript database at http://useast.ensembl.org/Mus_musculus/Info/Index.
+
+The positions of transcripts and genes on the mouse assembly are version GRCm38.p4 (mm10 equivalent). However, we converted all chromosome coordinates to the mm9 assembly to be consistent with all other GN1 data sets. However, for some sequences, mostly on Chr Y and the mitochondrial genome, the values are mm10 equivalent (we had no corresponding mm9 values).
+
+We also extracted sequence data corresponding to the transcripts whenever these data were available. However in some cases we do not have sequence data at all.
diff --git a/general/datasets/Inia_lcm_cab_1215/processing.rtf b/general/datasets/Inia_lcm_cab_1215/processing.rtf
new file mode 100644
index 0000000..f04ab87
--- /dev/null
+++ b/general/datasets/Inia_lcm_cab_1215/processing.rtf
@@ -0,0 +1,5 @@
+RNA from tissue trapped in the CapSure LCM caps was extracted using the PicoPure RNA isolation kit (Life Technologies) according to the manufacturer's instructions (RNA was eluted from provided capture columns in 13.5-mL nuclease-free water). RNA quality was analyzed using a Bioanalyzer (Model 100, Agilent, Foster City, CA). Samples with an associated RNA integrity number (RIN) greater than 6 were subsequently used for RNA sequencing.
+
+
+
+Poly-A enriched mRNA was sequenced on two platforms, ABI SOLID 550XL Wildfire (65 samples) and Ion Proton (39 samples). Read length was 50 nt for the SOLID system and the average read length for the Proton system was ~180 nt. Reads generated on the SOLID system were aligned to the mm10 reference genome using the LifeScope aligner, and BAM files were subsequently generated using custom scripts for third-party downstream analysis. For the Proton system, reads were also aligned to the mm10 (Ensemble GRCm38) reference genome using TopHat2. Settings for TopHat2 are as follows: “-p 15 -N 4 –read-gap-length 6 –read-edit-dist 8 –max-insertion-length 6 –max-deletion-length 6 –max-intron-length 300000 –b2-very-sensitive”. Alignments on both platforms were splice-aware. RSeQC-2.6.1 (RPKM_count.py) was used to generate count data based on mm10 GENECODE Basic transcript annotation (43,320 transcripts detected). We selected this annotation for greater reproducibility with existing microarray data sets and to simplify downstream analysis by limiting the number of transcript models for each gene. On average, 2.5 million and 7.8 million reads uniquely aligned to transcript models on the SOLID and Proton platforms, respectively. Data were further filtered to remove tran- scripts that had less than 1 count in 90% or more samples. After filtering, 24,597 transcripts representing 12,011 unique genes remained (Supplemental Table 1). The variance stabilizing trans- form (R package DESeq2, FitType 1⁄4 local) was applied to the count data, and transformed data were corrected by dividing by transcript length to generate log2 reads per kilobase gene model (RPK) values. The use of two different sequencing platforms was corrected using batch correction (ComBat, Supplemental Fig. 3). All data filtering, transformations, and batch correction were performed using custom R scripts. Batch-corrected and transformed log2 RPK and log2 count values are available in Supplemental Tables 2 and 3, and log2 RPK data are also available at GeneNetwork [http://www. genenetwork.org/webqtl/main.py?FormID1⁄4sharinginfo&GN_ AccessionId1⁄4772; Group 1⁄4 Chronic Intermittent Ethanol, Type 1⁄4 LCM Brain Regions mRNA, Data set 1⁄4 INIA LCM (11 Regions) CIE/AIR RNA-seq Transcript Level (Dec15)].
diff --git a/general/datasets/Inia_lcm_cab_1215/specifics.rtf b/general/datasets/Inia_lcm_cab_1215/specifics.rtf
new file mode 100644
index 0000000..61a050f
--- /dev/null
+++ b/general/datasets/Inia_lcm_cab_1215/specifics.rtf
@@ -0,0 +1,17 @@
+Published in Alcohol 2017:
+
+
+
+Alcohol. 2017 Feb;58:61-72. doi: 10.1016/j.alcohol.2016.09.001. Epub 2016 Oct 15.
+
+Genetic divergence in the transcriptional engram of chronic alcohol abuse: A laser-capture RNA-seq study of the mouse mesocorticolimbic system.
+
+Mulligan MK1, Mozhui K2, Pandey AK2, Smith ML3, Gong S2, Ingels J2, Miles MF3, Lopez MF4, Lu L2, Williams RW2.
+
+
+
+Abstract
+
+Genetic factors that influence the transition from initial drinking to dependence remain enigmatic. Recent studies have leveraged chronic intermittent ethanol (CIE) paradigms to measure changes in brain gene expression in a single strain at 0, 8, 72 h, and even 7 days following CIE. We extend these findings using LCM RNA-seq to profile expression in 11 brain regions in two inbred strains - C57BL/6J (B6) and DBA/2J (D2) - 72 h following multiple cycles of ethanol self-administration and CIE. Linear models identified differential expression based on treatment, region, strain, or interactions with treatment. Nearly 40% of genes showed a robust effect (FDR < 0.01) of region, and hippocampus CA1, cortex, bed nucleus stria terminalis, and nucleus accumbens core had the highest number of differentially expressed genes after treatment. Another 8% of differentially expressed genes demonstrated a robust effect of strain. As expected, based on similar studies in B6, treatment had a much smaller impact on expression; only 72 genes (p < 0.01) are modulated by treatment (independent of region or strain). Strikingly, many more genes (415) show a strain-specific and largely opposite response to treatment and are enriched in processes related to RNA metabolism, transcription factor activity, and mitochondrial function. Over 3 times as many changes in gene expression were detected in D2 compared to B6, and weighted gene co-expression network analysis (WGCNA) module comparison identified more modules enriched for treatment effects in D2. Substantial strain differences exist in the temporal pattern of transcriptional neuroadaptation to CIE, and these may drive individual differences in risk of addiction following excessive alcohol consumption.
+
+PMID:27894806; PMCID:PMC5450909; DOI:10.1016/j.alcohol.2016.09.001
diff --git a/general/datasets/Inia_lcm_cab_1215/summary.rtf b/general/datasets/Inia_lcm_cab_1215/summary.rtf
new file mode 100644
index 0000000..45d122d
--- /dev/null
+++ b/general/datasets/Inia_lcm_cab_1215/summary.rtf
@@ -0,0 +1 @@
+This dataset is open. Please contact Dr. Megan K. Mulligan (mmulliga@uthsc.edu) or Dr. Robert W. Williams (rwilliams@uthsc.edu) if you need more information or low-level data access.
diff --git a/general/datasets/Inia_lcm_cab_1215/tissue.rtf b/general/datasets/Inia_lcm_cab_1215/tissue.rtf
new file mode 100644
index 0000000..6a51951
--- /dev/null
+++ b/general/datasets/Inia_lcm_cab_1215/tissue.rtf
@@ -0,0 +1,5 @@
+Whole brain tissue was sectioned at 10 mm using a Leica cryostat and mounted in series with 6e8 sections per slide onto uncharged and uncoated glass slides. Mounted sections were dehydrated in 100% methanol (90 s), 70% ethanol (1 min), 95% ethanol (1 min), 100% ethanol (1 min 2), xylene (5 min). Slides were then allowed to air dry for 10 min under a fume hood.
+
+Series were created from distinct coronal sections (bregma po- sitions based on a C57BL/6J reference brain atlas) and individual regions were matched across section and harvested by LCM (Supplemental Fig. 2). Prelimbic (PrL) and infralimbic (ILC) cortex included a series spanning from bregma 1.98 to 1.54 mm. The accumbens core (NAc) and shell (NAs) series were collected from bregma 1.54 to 0.98 mm, and dorsolateral (DLS) and dorsomedial (DMS) striatum and bed nucleus stria terminalis (BST) were collected from bregma 0.38 to 0.10 mm. Basolateral (BLA) and central nucleus (CeA) of the amygdala series were collected from bregma 0.58 to 1.22 mm and hippocampus (CA1 and CA3) was collected from bregma 1.46 to 2.46 mm. Finally, the ventral tegmental area (VTA) and primary visual cortex (VCX) series were collected from bregma 3.28 to 3.80 mm.
+
+Arcturus XT (Life Technologies) was used to capture 13 brain areas. The infrared laser was then used to capture the tissue onto CapSure LCM caps (Life Technologies, laser spot power set to 70 mV with a duration of 25 msec).
diff --git a/general/datasets/Inia_lcmb_1215/acknowledgment.rtf b/general/datasets/Inia_lcmb_1215/acknowledgment.rtf
new file mode 100644
index 0000000..8b7d4ad
--- /dev/null
+++ b/general/datasets/Inia_lcmb_1215/acknowledgment.rtf
@@ -0,0 +1 @@
+Thanks to NIH NIAAA and funding support was provided by INIA grants U01AA013499 and U01AA06662.
diff --git a/general/datasets/Inia_lcmb_1215/cases.rtf b/general/datasets/Inia_lcmb_1215/cases.rtf
new file mode 100644
index 0000000..4d95e2a
--- /dev/null
+++ b/general/datasets/Inia_lcmb_1215/cases.rtf
@@ -0,0 +1 @@
+Male C57BL/6J and DBA/2J mice (10 weeks old upon arrival) were purchased from the Jackson Laboratory and assigned to either baseline untreated control (BAS), the air control (AIR), or CIE group. Mice were individually housed with free access to food (Harland Teklad, Madison, WI) and water throughout all phases of the experiments. Body weights were recorded weekly during ethanol-drinking weeks or daily during chronic intermittent ethanol (CIE) or air exposure (detailed below). Mice were housed in a temperature- and humidity-controlled an- imal facility under a reversed 12-h light/dark cycle (lights on at 0200 h). Mice were not food- or water-deprived at any time during the study. All procedures were approved by the Institutional Ani- mal Care and Use Committee at the Medical University of South Carolina (MUSC). Brain tissue was removed at MUSC and shipped to UTHSC for laser capture microdissection (LCM).
diff --git a/general/datasets/Inia_lcmb_1215/contributors.rtf b/general/datasets/Inia_lcmb_1215/contributors.rtf
new file mode 100644
index 0000000..edf124f
--- /dev/null
+++ b/general/datasets/Inia_lcmb_1215/contributors.rtf
@@ -0,0 +1,5 @@
+Megan K. Mulligan, Khyobeni Mozhui, Ashutosh K. Pandey, Maren L. Smith, Suzhen Gong, Jesse Ingels, Michael F. Miles, Marcelo F. Lopez, Lu Lu, Robert W. Williams
+
+
+
+Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.alcohol.2016.09.001.
diff --git a/general/datasets/Inia_lcmb_1215/platform.rtf b/general/datasets/Inia_lcmb_1215/platform.rtf
new file mode 100644
index 0000000..25cb790
--- /dev/null
+++ b/general/datasets/Inia_lcmb_1215/platform.rtf
@@ -0,0 +1,11 @@
+
+
+
+
+(Updated Dec 9, 2015 by AC and RW)
+
+Annotation data for transcripts and genes were downloaded from ENSEMBL by Arthur Centeno, December 2015. We downloaded the entire transcript database at http://useast.ensembl.org/Mus_musculus/Info/Index.
+
+The positions of transcripts and genes on the mouse assembly are version GRCm38.p4 (mm10 equivalent). However, we converted all chromosome coordinates to the mm9 assembly to be consistent with all other GN1 data sets. However, for some sequences, mostly on Chr Y and the mitochondrial genome, the values are mm10 equivalent (we had no corresponding mm9 values).
+
+We also extracted sequence data corresponding to the transcripts whenever these data were available. However in some cases we do not have sequence data at all.
diff --git a/general/datasets/Inia_lcmb_1215/processing.rtf b/general/datasets/Inia_lcmb_1215/processing.rtf
new file mode 100644
index 0000000..f04ab87
--- /dev/null
+++ b/general/datasets/Inia_lcmb_1215/processing.rtf
@@ -0,0 +1,5 @@
+RNA from tissue trapped in the CapSure LCM caps was extracted using the PicoPure RNA isolation kit (Life Technologies) according to the manufacturer's instructions (RNA was eluted from provided capture columns in 13.5-mL nuclease-free water). RNA quality was analyzed using a Bioanalyzer (Model 100, Agilent, Foster City, CA). Samples with an associated RNA integrity number (RIN) greater than 6 were subsequently used for RNA sequencing.
+
+
+
+Poly-A enriched mRNA was sequenced on two platforms, ABI SOLID 550XL Wildfire (65 samples) and Ion Proton (39 samples). Read length was 50 nt for the SOLID system and the average read length for the Proton system was ~180 nt. Reads generated on the SOLID system were aligned to the mm10 reference genome using the LifeScope aligner, and BAM files were subsequently generated using custom scripts for third-party downstream analysis. For the Proton system, reads were also aligned to the mm10 (Ensemble GRCm38) reference genome using TopHat2. Settings for TopHat2 are as follows: “-p 15 -N 4 –read-gap-length 6 –read-edit-dist 8 –max-insertion-length 6 –max-deletion-length 6 –max-intron-length 300000 –b2-very-sensitive”. Alignments on both platforms were splice-aware. RSeQC-2.6.1 (RPKM_count.py) was used to generate count data based on mm10 GENECODE Basic transcript annotation (43,320 transcripts detected). We selected this annotation for greater reproducibility with existing microarray data sets and to simplify downstream analysis by limiting the number of transcript models for each gene. On average, 2.5 million and 7.8 million reads uniquely aligned to transcript models on the SOLID and Proton platforms, respectively. Data were further filtered to remove tran- scripts that had less than 1 count in 90% or more samples. After filtering, 24,597 transcripts representing 12,011 unique genes remained (Supplemental Table 1). The variance stabilizing trans- form (R package DESeq2, FitType 1⁄4 local) was applied to the count data, and transformed data were corrected by dividing by transcript length to generate log2 reads per kilobase gene model (RPK) values. The use of two different sequencing platforms was corrected using batch correction (ComBat, Supplemental Fig. 3). All data filtering, transformations, and batch correction were performed using custom R scripts. Batch-corrected and transformed log2 RPK and log2 count values are available in Supplemental Tables 2 and 3, and log2 RPK data are also available at GeneNetwork [http://www. genenetwork.org/webqtl/main.py?FormID1⁄4sharinginfo&GN_ AccessionId1⁄4772; Group 1⁄4 Chronic Intermittent Ethanol, Type 1⁄4 LCM Brain Regions mRNA, Data set 1⁄4 INIA LCM (11 Regions) CIE/AIR RNA-seq Transcript Level (Dec15)].
diff --git a/general/datasets/Inia_lcmb_1215/summary.rtf b/general/datasets/Inia_lcmb_1215/summary.rtf
new file mode 100644
index 0000000..45d122d
--- /dev/null
+++ b/general/datasets/Inia_lcmb_1215/summary.rtf
@@ -0,0 +1 @@
+This dataset is open. Please contact Dr. Megan K. Mulligan (mmulliga@uthsc.edu) or Dr. Robert W. Williams (rwilliams@uthsc.edu) if you need more information or low-level data access.
diff --git a/general/datasets/Inia_lcmb_1215/tissue.rtf b/general/datasets/Inia_lcmb_1215/tissue.rtf
new file mode 100644
index 0000000..6a51951
--- /dev/null
+++ b/general/datasets/Inia_lcmb_1215/tissue.rtf
@@ -0,0 +1,5 @@
+Whole brain tissue was sectioned at 10 mm using a Leica cryostat and mounted in series with 6e8 sections per slide onto uncharged and uncoated glass slides. Mounted sections were dehydrated in 100% methanol (90 s), 70% ethanol (1 min), 95% ethanol (1 min), 100% ethanol (1 min 2), xylene (5 min). Slides were then allowed to air dry for 10 min under a fume hood.
+
+Series were created from distinct coronal sections (bregma po- sitions based on a C57BL/6J reference brain atlas) and individual regions were matched across section and harvested by LCM (Supplemental Fig. 2). Prelimbic (PrL) and infralimbic (ILC) cortex included a series spanning from bregma 1.98 to 1.54 mm. The accumbens core (NAc) and shell (NAs) series were collected from bregma 1.54 to 0.98 mm, and dorsolateral (DLS) and dorsomedial (DMS) striatum and bed nucleus stria terminalis (BST) were collected from bregma 0.38 to 0.10 mm. Basolateral (BLA) and central nucleus (CeA) of the amygdala series were collected from bregma 0.58 to 1.22 mm and hippocampus (CA1 and CA3) was collected from bregma 1.46 to 2.46 mm. Finally, the ventral tegmental area (VTA) and primary visual cortex (VCX) series were collected from bregma 3.28 to 3.80 mm.
+
+Arcturus XT (Life Technologies) was used to capture 13 brain areas. The infrared laser was then used to capture the tissue onto CapSure LCM caps (Life Technologies, laser spot power set to 70 mV with a duration of 25 msec).
diff --git a/general/datasets/Inia_macfas_ac_rma_0110/experiment-type.rtf b/general/datasets/Inia_macfas_ac_rma_0110/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Inia_macfas_ac_rma_0110/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Inia_macfas_ac_rma_0110/summary.rtf b/general/datasets/Inia_macfas_ac_rma_0110/summary.rtf
new file mode 100644
index 0000000..cbfec8d
--- /dev/null
+++ b/general/datasets/Inia_macfas_ac_rma_0110/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 88, Name: INIA Macaca fasicularis Nucleus Accumbens (Jan10)
\ No newline at end of file
diff --git a/general/datasets/Inia_macfas_amg_rma_0110/experiment-type.rtf b/general/datasets/Inia_macfas_amg_rma_0110/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Inia_macfas_amg_rma_0110/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Inia_macfas_amg_rma_0110/summary.rtf b/general/datasets/Inia_macfas_amg_rma_0110/summary.rtf
new file mode 100644
index 0000000..42959fa
--- /dev/null
+++ b/general/datasets/Inia_macfas_amg_rma_0110/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 90, Name: INIA Macaca fasicularis Amygdala (Jan10)
\ No newline at end of file
diff --git a/general/datasets/Inia_macfas_brain_rma_0110/experiment-type.rtf b/general/datasets/Inia_macfas_brain_rma_0110/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Inia_macfas_brain_rma_0110/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Inia_macfas_brain_rma_0110/notes.rtf b/general/datasets/Inia_macfas_brain_rma_0110/notes.rtf
new file mode 100644
index 0000000..958acba
--- /dev/null
+++ b/general/datasets/Inia_macfas_brain_rma_0110/notes.rtf
@@ -0,0 +1,5 @@
+Dr. Miles Note:
+
+The initial 16 animals from INIA cohort 3 are the samples that are in GeneNetwork -- and there we had 4 brain regions x 16 animals -- prefrontal cortex (Brodmann areas 24, 25 and 32 pooled together), nucleus acumen, hippocampus and amygdala.
+
+INIA cohort 3 includes 12 ethanol drinking female cynomolgous Indochinese monkeys and 4 control Indonesian monkeys.
diff --git a/general/datasets/Inia_macfas_brain_rma_0110/summary.rtf b/general/datasets/Inia_macfas_brain_rma_0110/summary.rtf
new file mode 100644
index 0000000..103b4c3
--- /dev/null
+++ b/general/datasets/Inia_macfas_brain_rma_0110/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 86, Name: INIA Macaca fasicularis Brain (Jan10)
diff --git a/general/datasets/Inia_macfas_hc_rma_0110/experiment-type.rtf b/general/datasets/Inia_macfas_hc_rma_0110/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Inia_macfas_hc_rma_0110/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Inia_macfas_hc_rma_0110/summary.rtf b/general/datasets/Inia_macfas_hc_rma_0110/summary.rtf
new file mode 100644
index 0000000..f305a05
--- /dev/null
+++ b/general/datasets/Inia_macfas_hc_rma_0110/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 89, Name: INIA Macaca fasicularis Hippocampus (Jan10)
\ No newline at end of file
diff --git a/general/datasets/Inia_macfas_pf_rma_0110/experiment-type.rtf b/general/datasets/Inia_macfas_pf_rma_0110/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Inia_macfas_pf_rma_0110/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Inia_macfas_pf_rma_0110/summary.rtf b/general/datasets/Inia_macfas_pf_rma_0110/summary.rtf
new file mode 100644
index 0000000..06ec6f0
--- /dev/null
+++ b/general/datasets/Inia_macfas_pf_rma_0110/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 87, Name: INIA Macaca fasicularis Prefrontal Cortex (Jan10)
\ No newline at end of file
diff --git a/general/datasets/Inia_pg_rma_0612/acknowledgment.rtf b/general/datasets/Inia_pg_rma_0612/acknowledgment.rtf
new file mode 100644
index 0000000..f8bf764
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_0612/acknowledgment.rtf
@@ -0,0 +1 @@
+NIAAA U01 support to RWW.
diff --git a/general/datasets/Inia_pg_rma_0612/cases.rtf b/general/datasets/Inia_pg_rma_0612/cases.rtf
new file mode 100644
index 0000000..faf8ab0
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_0612/cases.rtf
@@ -0,0 +1,840 @@
+Young adult mice raised in specific pathogen-free vivarium at UTHSC.
+
+ERROR CHECKING by Mozhui, Centeno and Roy: The changes have been applied in GeneNetwork (GN389 - Pituitary) as follow:
+
+SampleId - New Strain Assignment
+R7087P (was BXD101) = BXD100
+R7138P_RW170 (was BXD85) = BXD95
+R7156P (was C57BL/6J) = B6D2F1
+R7141P = BXD65
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Tissue |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R7128P |
+ B6D2F1 |
+ Pituitary |
+ 69 |
+ F |
+
+
+ | 2 |
+ R7156P |
+ B6D2F1 |
+ Pituitary |
+ 92 |
+ M |
+
+
+ | 3 |
+ R7129P |
+ B6D2F1 |
+ Pituitary |
+ 69 |
+ M |
+
+
+ | 4 |
+ R7134P |
+ D2B6F1 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 5 |
+ R7133P |
+ D2B6F1 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 6 |
+ R7160P |
+ C57BL/6J |
+ Pituitary |
+ 92 |
+ F |
+
+
+ | 7 |
+ R7127P |
+ C57BL/6J |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 8 |
+ R7126P |
+ DBA/2J |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 9 |
+ R7157P |
+ DBA/2J |
+ Pituitary |
+ 75 |
+ F |
+
+
+ | 10 |
+ R7125P |
+ DBA/2J |
+ Pituitary |
+ 68 |
+ M |
+
+
+ | 11 |
+ R7155P |
+ DBA/2J |
+ Pituitary |
+ 75 |
+ M |
+
+
+ | 12 |
+ R7058P |
+ BXD1 |
+ Pituitary |
+ 72 |
+ F |
+
+
+ | 13 |
+ R7063P |
+ BXD1 |
+ Pituitary |
+ 86 |
+ M |
+
+
+ | 14 |
+ R7079P |
+ BXD11 |
+ Pituitary |
+ 87 |
+ F |
+
+
+ | 15 |
+ R7069P |
+ BXD11 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 16 |
+ R7051P |
+ BXD12 |
+ Pituitary |
+ 78 |
+ F |
+
+
+ | 17 |
+ R7061P |
+ BXD12 |
+ Pituitary |
+ 78 |
+ M |
+
+
+ | 18 |
+ R7064P |
+ BXD14 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 19 |
+ R7066P |
+ BXD14 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 20 |
+ R7052P |
+ BXD24 |
+ Pituitary |
+ 86 |
+ M |
+
+
+ | 21 |
+ R7076P |
+ BXD27 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 22 |
+ R7071P |
+ BXD27 |
+ Pituitary |
+ 73 |
+ M |
+
+
+ | 23 |
+ R7059P |
+ BXD29 |
+ Pituitary |
+ 72 |
+ F |
+
+
+ | 24 |
+ R7060P |
+ BXD29 |
+ Pituitary |
+ 72 |
+ M |
+
+
+ | 25 |
+ R7055P |
+ BXD31 |
+ Pituitary |
+ 74 |
+ F |
+
+
+ | 26 |
+ R7062P |
+ BXD31 |
+ Pituitary |
+ 74 |
+ M |
+
+
+ | 27 |
+ R7143P |
+ BXD32 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 28 |
+ R7135P |
+ BXD32 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 29 |
+ R7119P |
+ BXD34 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 30 |
+ R7054P |
+ BXD34 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 31 |
+ R7049P |
+ BXD39 |
+ Pituitary |
+ 79 |
+ F |
+
+
+ | 32 |
+ R7065P |
+ BXD39 |
+ Pituitary |
+ 79 |
+ M |
+
+
+ | 33 |
+ R7130P |
+ BXD40 |
+ Pituitary |
+ 85 |
+ F |
+
+
+ | 34 |
+ R7132P |
+ BXD40 |
+ Pituitary |
+ 85 |
+ M |
+
+
+ | 35 |
+ R7056P |
+ BXD42 |
+ Pituitary |
+ 87 |
+ F |
+
+
+ | 36 |
+ R7044P |
+ BXD42 |
+ Pituitary |
+ 87 |
+ M |
+
+
+ | 37 |
+ R7043P |
+ BXD43 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 38 |
+ R7047P |
+ BXD43 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 39 |
+ R7091P |
+ BXD44 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 40 |
+ R7050P |
+ BXD44 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 41 |
+ R7077P |
+ BXD45 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 42 |
+ R7078P |
+ BXD45 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 43 |
+ R7042P |
+ BXD45 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 44 |
+ R7092P |
+ BXD48 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 45 |
+ R7093P |
+ BXD48 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 46 |
+ R7045P |
+ BXD49 |
+ Pituitary |
+ 84 |
+ F |
+
+
+ | 47 |
+ R7094P |
+ BXD49 |
+ Pituitary |
+ 84 |
+ M |
+
+
+ | 48 |
+ R7095P |
+ BXD50 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 49 |
+ R7096P |
+ BXD50 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 50 |
+ R7142P |
+ BXD56 |
+ Pituitary |
+ 84 |
+ F |
+
+
+ | 51 |
+ R7097P |
+ BXD56 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 52 |
+ R7080P |
+ BXD60 |
+ Pituitary |
+ 70 |
+ F |
+
+
+ | 53 |
+ R7141P_RW204 |
+ BXD60 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 54 |
+ R7075P |
+ BXD62 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 55 |
+ R7083P |
+ BXD62 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 56 |
+ R7084P |
+ BXD62 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 57 |
+ R7098P |
+ BXD63 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 58 |
+ R7100P |
+ BXD65 |
+ Pituitary |
+ 84 |
+ M |
+
+
+ | 59 |
+ R7120P |
+ BXD66 |
+ Pituitary |
+ 257 |
+ M |
+
+
+ | 60 |
+ R7140P |
+ BXD68 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 61 |
+ R7101P |
+ BXD68 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 62 |
+ R7074P |
+ BXD69 |
+ Pituitary |
+ 69 |
+ F |
+
+
+ | 63 |
+ R7139P |
+ BXD69 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 64 |
+ R7141P |
+ BXD65 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 65 |
+ R7137P_RW112 |
+ BXD70 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 66 |
+ R7124P |
+ BXD71 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 67 |
+ R7123P |
+ BXD71 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 68 |
+ R7068P |
+ BXD73 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 69 |
+ R7118P |
+ BXD74 |
+ Pituitary |
+ 69 |
+ F |
+
+
+ | 70 |
+ R7117P |
+ BXD74 |
+ Pituitary |
+ 69 |
+ M |
+
+
+ | 71 |
+ R7082P |
+ BXD75 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 72 |
+ R7048P |
+ BXD75 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 73 |
+ R7122P |
+ BXD77 |
+ Pituitary |
+ 223 |
+ M |
+
+
+ | 74 |
+ R7103P |
+ BXD79 |
+ Pituitary |
+ 86 |
+ F |
+
+
+ | 75 |
+ R7104P |
+ BXD79 |
+ Pituitary |
+ 86 |
+ M |
+
+
+ | 76 |
+ R7073P |
+ BXD80 |
+ Pituitary |
+ 73 |
+ F |
+
+
+ | 77 |
+ R7070P |
+ BXD80 |
+ Pituitary |
+ 73 |
+ M |
+
+
+ | 78 |
+ R7139P_RW138 |
+ BXD83 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 79 |
+ R7137P |
+ BXD83 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 80 |
+ R7085P |
+ BXD84 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 81 |
+ R7081P |
+ BXD84 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 82 |
+ R7105P |
+ BXD85 |
+ Pituitary |
+ 73 |
+ M |
+
+
+ | 83 |
+ R7144P |
+ BXD87 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 84 |
+ R7136P_RW196 |
+ BXD87 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 85 |
+ R7106P |
+ BXD89 |
+ Pituitary |
+ 82 |
+ F |
+
+
+ | 86 |
+ R7107P |
+ BXD89 |
+ Pituitary |
+ 82 |
+ M |
+
+
+ | 87 |
+ R7108P |
+ BXD90 |
+ Pituitary |
+ 82 |
+ F |
+
+
+ | 88 |
+ R7109P |
+ BXD90 |
+ Pituitary |
+ 82 |
+ M |
+
+
+ | 89 |
+ R7138P_RW170 |
+ BXD95 |
+ Pituitary |
+ 73 |
+ F |
+
+
+ | 90 |
+ R7111P |
+ BXD97 |
+ Pituitary |
+ 71 |
+ F |
+
+
+ | 91 |
+ R7112P |
+ BXD97 |
+ Pituitary |
+ 71 |
+ M |
+
+
+ | 92 |
+ R7113P |
+ BXD99 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 93 |
+ R7114P |
+ BXD99 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 94 |
+ R7072P |
+ BXD100 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 95 |
+ R7087P |
+ BXD100 |
+ Pituitary |
+ 88 |
+ F |
+
+
+ | 96 |
+ R7086P |
+ BXD100 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 97 |
+ R7088P |
+ BXD101 |
+ Pituitary |
+ 88 |
+ M |
+
+
+ | 98 |
+ R7053P |
+ BXD102 |
+ Pituitary |
+ 88 |
+ F |
+
+
+ | 99 |
+ R7046P |
+ BXD102 |
+ Pituitary |
+ 88 |
+ M |
+
+
+ | 100 |
+ R7090P |
+ BXD103 |
+ Pituitary |
+ 78 |
+ F |
+
+
+ | 101 |
+ R7067P |
+ BXD103 |
+ Pituitary |
+ 78 |
+ M |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Inia_pg_rma_0612/citation.rtf b/general/datasets/Inia_pg_rma_0612/citation.rtf
new file mode 100644
index 0000000..1ef65cb
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_0612/citation.rtf
@@ -0,0 +1 @@
+Contact RW Williams
diff --git a/general/datasets/Inia_pg_rma_0612/contributors.rtf b/general/datasets/Inia_pg_rma_0612/contributors.rtf
new file mode 100644
index 0000000..5178980
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_0612/contributors.rtf
@@ -0,0 +1 @@
+Mozhui K, Lu L, Adler A, Ingels J, Williams RW
diff --git a/general/datasets/Inia_pg_rma_0612/experiment-design.rtf b/general/datasets/Inia_pg_rma_0612/experiment-design.rtf
new file mode 100644
index 0000000..13175b5
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_0612/experiment-design.rtf
@@ -0,0 +1,10 @@
+Normative expression in the whole pituitary of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
+
+QUALITY CONTROL DATA
+
+
+ - 737 probe sets with LRS of 46 or higher (LOD>10)
+ - Highest LRS = 165.7
+ - Review of top Mendelian transcripts consist with correct strain assignment
+ - Final sex assignment is correct
+
diff --git a/general/datasets/Inia_pg_rma_0612/experiment-type.rtf b/general/datasets/Inia_pg_rma_0612/experiment-type.rtf
new file mode 100644
index 0000000..82d9546
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_0612/experiment-type.rtf
@@ -0,0 +1,10 @@
+Normative expression in the whole pituitary of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
+
+
+QUALITY CONTROL DATA
+
+- 737 probe sets with LRS of 46 or higher (LOD>10)
+
- Highest LRS = 165.7
+
- Review of top Mendelian transcripts consist with correct strain assignment
+
- Final sex assignment is correct
+
\ No newline at end of file
diff --git a/general/datasets/Inia_pg_rma_0612/platform.rtf b/general/datasets/Inia_pg_rma_0612/platform.rtf
new file mode 100644
index 0000000..7057d48
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_0612/platform.rtf
@@ -0,0 +1 @@
+The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/Inia_pg_rma_0612/processing.rtf b/general/datasets/Inia_pg_rma_0612/processing.rtf
new file mode 100644
index 0000000..55aad2e
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_0612/processing.rtf
@@ -0,0 +1 @@
+Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/Inia_pg_rma_0612/summary.rtf b/general/datasets/Inia_pg_rma_0612/summary.rtf
new file mode 100644
index 0000000..14a715d
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_0612/summary.rtf
@@ -0,0 +1,3 @@
+Gene expression data for the whole pituitary across 52 strains of mice. Sex Balance: Sex of samples has been double-checked. As of July 2012, for 42 strains we have separate data for both males and females (usually one array each). Three strains (BXD45, 63, and 95) are only represented by female samples and two strains (BXD65 and BXD77) are only represented by male samples. Five other strains (BXD24, 66, 73, 85, 101) are may represent combined male and female samples. These unpublished data are apparently error-free based on a review and analysis of transcripts with Mendelian segregation patterns (as of July 20, 2012). The data set contains 751 eQTLs with LOD scores above 10 (LRS>46). Peak LRS of 165.9 for Record ID 10513604. Data for BXD70 are somewhat problematic (see 10444135 and 10467784), perhaps due to a bad array, strain assignment error, or residual heterozygozity. S Roy double-checked (July 22) and thinks that Sample R7141P is more likely to be BXD65.
+
+Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/Inia_pg_rma_0612/tissue.rtf b/general/datasets/Inia_pg_rma_0612/tissue.rtf
new file mode 100644
index 0000000..3977f1e
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_0612/tissue.rtf
@@ -0,0 +1 @@
+Whole pituitary gland dissected by hand. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/Inia_pg_rma_ex_0612/acknowledgment.rtf b/general/datasets/Inia_pg_rma_ex_0612/acknowledgment.rtf
new file mode 100644
index 0000000..f8bf764
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_ex_0612/acknowledgment.rtf
@@ -0,0 +1 @@
+NIAAA U01 support to RWW.
diff --git a/general/datasets/Inia_pg_rma_ex_0612/cases.rtf b/general/datasets/Inia_pg_rma_ex_0612/cases.rtf
new file mode 100644
index 0000000..faf8ab0
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_ex_0612/cases.rtf
@@ -0,0 +1,840 @@
+Young adult mice raised in specific pathogen-free vivarium at UTHSC.
+
+ERROR CHECKING by Mozhui, Centeno and Roy: The changes have been applied in GeneNetwork (GN389 - Pituitary) as follow:
+
+SampleId - New Strain Assignment
+R7087P (was BXD101) = BXD100
+R7138P_RW170 (was BXD85) = BXD95
+R7156P (was C57BL/6J) = B6D2F1
+R7141P = BXD65
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Tissue |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R7128P |
+ B6D2F1 |
+ Pituitary |
+ 69 |
+ F |
+
+
+ | 2 |
+ R7156P |
+ B6D2F1 |
+ Pituitary |
+ 92 |
+ M |
+
+
+ | 3 |
+ R7129P |
+ B6D2F1 |
+ Pituitary |
+ 69 |
+ M |
+
+
+ | 4 |
+ R7134P |
+ D2B6F1 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 5 |
+ R7133P |
+ D2B6F1 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 6 |
+ R7160P |
+ C57BL/6J |
+ Pituitary |
+ 92 |
+ F |
+
+
+ | 7 |
+ R7127P |
+ C57BL/6J |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 8 |
+ R7126P |
+ DBA/2J |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 9 |
+ R7157P |
+ DBA/2J |
+ Pituitary |
+ 75 |
+ F |
+
+
+ | 10 |
+ R7125P |
+ DBA/2J |
+ Pituitary |
+ 68 |
+ M |
+
+
+ | 11 |
+ R7155P |
+ DBA/2J |
+ Pituitary |
+ 75 |
+ M |
+
+
+ | 12 |
+ R7058P |
+ BXD1 |
+ Pituitary |
+ 72 |
+ F |
+
+
+ | 13 |
+ R7063P |
+ BXD1 |
+ Pituitary |
+ 86 |
+ M |
+
+
+ | 14 |
+ R7079P |
+ BXD11 |
+ Pituitary |
+ 87 |
+ F |
+
+
+ | 15 |
+ R7069P |
+ BXD11 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 16 |
+ R7051P |
+ BXD12 |
+ Pituitary |
+ 78 |
+ F |
+
+
+ | 17 |
+ R7061P |
+ BXD12 |
+ Pituitary |
+ 78 |
+ M |
+
+
+ | 18 |
+ R7064P |
+ BXD14 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 19 |
+ R7066P |
+ BXD14 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 20 |
+ R7052P |
+ BXD24 |
+ Pituitary |
+ 86 |
+ M |
+
+
+ | 21 |
+ R7076P |
+ BXD27 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 22 |
+ R7071P |
+ BXD27 |
+ Pituitary |
+ 73 |
+ M |
+
+
+ | 23 |
+ R7059P |
+ BXD29 |
+ Pituitary |
+ 72 |
+ F |
+
+
+ | 24 |
+ R7060P |
+ BXD29 |
+ Pituitary |
+ 72 |
+ M |
+
+
+ | 25 |
+ R7055P |
+ BXD31 |
+ Pituitary |
+ 74 |
+ F |
+
+
+ | 26 |
+ R7062P |
+ BXD31 |
+ Pituitary |
+ 74 |
+ M |
+
+
+ | 27 |
+ R7143P |
+ BXD32 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 28 |
+ R7135P |
+ BXD32 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 29 |
+ R7119P |
+ BXD34 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 30 |
+ R7054P |
+ BXD34 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 31 |
+ R7049P |
+ BXD39 |
+ Pituitary |
+ 79 |
+ F |
+
+
+ | 32 |
+ R7065P |
+ BXD39 |
+ Pituitary |
+ 79 |
+ M |
+
+
+ | 33 |
+ R7130P |
+ BXD40 |
+ Pituitary |
+ 85 |
+ F |
+
+
+ | 34 |
+ R7132P |
+ BXD40 |
+ Pituitary |
+ 85 |
+ M |
+
+
+ | 35 |
+ R7056P |
+ BXD42 |
+ Pituitary |
+ 87 |
+ F |
+
+
+ | 36 |
+ R7044P |
+ BXD42 |
+ Pituitary |
+ 87 |
+ M |
+
+
+ | 37 |
+ R7043P |
+ BXD43 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 38 |
+ R7047P |
+ BXD43 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 39 |
+ R7091P |
+ BXD44 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 40 |
+ R7050P |
+ BXD44 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 41 |
+ R7077P |
+ BXD45 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 42 |
+ R7078P |
+ BXD45 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 43 |
+ R7042P |
+ BXD45 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 44 |
+ R7092P |
+ BXD48 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 45 |
+ R7093P |
+ BXD48 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 46 |
+ R7045P |
+ BXD49 |
+ Pituitary |
+ 84 |
+ F |
+
+
+ | 47 |
+ R7094P |
+ BXD49 |
+ Pituitary |
+ 84 |
+ M |
+
+
+ | 48 |
+ R7095P |
+ BXD50 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 49 |
+ R7096P |
+ BXD50 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 50 |
+ R7142P |
+ BXD56 |
+ Pituitary |
+ 84 |
+ F |
+
+
+ | 51 |
+ R7097P |
+ BXD56 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 52 |
+ R7080P |
+ BXD60 |
+ Pituitary |
+ 70 |
+ F |
+
+
+ | 53 |
+ R7141P_RW204 |
+ BXD60 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 54 |
+ R7075P |
+ BXD62 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 55 |
+ R7083P |
+ BXD62 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 56 |
+ R7084P |
+ BXD62 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 57 |
+ R7098P |
+ BXD63 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 58 |
+ R7100P |
+ BXD65 |
+ Pituitary |
+ 84 |
+ M |
+
+
+ | 59 |
+ R7120P |
+ BXD66 |
+ Pituitary |
+ 257 |
+ M |
+
+
+ | 60 |
+ R7140P |
+ BXD68 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 61 |
+ R7101P |
+ BXD68 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 62 |
+ R7074P |
+ BXD69 |
+ Pituitary |
+ 69 |
+ F |
+
+
+ | 63 |
+ R7139P |
+ BXD69 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 64 |
+ R7141P |
+ BXD65 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 65 |
+ R7137P_RW112 |
+ BXD70 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 66 |
+ R7124P |
+ BXD71 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 67 |
+ R7123P |
+ BXD71 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 68 |
+ R7068P |
+ BXD73 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 69 |
+ R7118P |
+ BXD74 |
+ Pituitary |
+ 69 |
+ F |
+
+
+ | 70 |
+ R7117P |
+ BXD74 |
+ Pituitary |
+ 69 |
+ M |
+
+
+ | 71 |
+ R7082P |
+ BXD75 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 72 |
+ R7048P |
+ BXD75 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 73 |
+ R7122P |
+ BXD77 |
+ Pituitary |
+ 223 |
+ M |
+
+
+ | 74 |
+ R7103P |
+ BXD79 |
+ Pituitary |
+ 86 |
+ F |
+
+
+ | 75 |
+ R7104P |
+ BXD79 |
+ Pituitary |
+ 86 |
+ M |
+
+
+ | 76 |
+ R7073P |
+ BXD80 |
+ Pituitary |
+ 73 |
+ F |
+
+
+ | 77 |
+ R7070P |
+ BXD80 |
+ Pituitary |
+ 73 |
+ M |
+
+
+ | 78 |
+ R7139P_RW138 |
+ BXD83 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 79 |
+ R7137P |
+ BXD83 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 80 |
+ R7085P |
+ BXD84 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 81 |
+ R7081P |
+ BXD84 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 82 |
+ R7105P |
+ BXD85 |
+ Pituitary |
+ 73 |
+ M |
+
+
+ | 83 |
+ R7144P |
+ BXD87 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 84 |
+ R7136P_RW196 |
+ BXD87 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 85 |
+ R7106P |
+ BXD89 |
+ Pituitary |
+ 82 |
+ F |
+
+
+ | 86 |
+ R7107P |
+ BXD89 |
+ Pituitary |
+ 82 |
+ M |
+
+
+ | 87 |
+ R7108P |
+ BXD90 |
+ Pituitary |
+ 82 |
+ F |
+
+
+ | 88 |
+ R7109P |
+ BXD90 |
+ Pituitary |
+ 82 |
+ M |
+
+
+ | 89 |
+ R7138P_RW170 |
+ BXD95 |
+ Pituitary |
+ 73 |
+ F |
+
+
+ | 90 |
+ R7111P |
+ BXD97 |
+ Pituitary |
+ 71 |
+ F |
+
+
+ | 91 |
+ R7112P |
+ BXD97 |
+ Pituitary |
+ 71 |
+ M |
+
+
+ | 92 |
+ R7113P |
+ BXD99 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 93 |
+ R7114P |
+ BXD99 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 94 |
+ R7072P |
+ BXD100 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 95 |
+ R7087P |
+ BXD100 |
+ Pituitary |
+ 88 |
+ F |
+
+
+ | 96 |
+ R7086P |
+ BXD100 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 97 |
+ R7088P |
+ BXD101 |
+ Pituitary |
+ 88 |
+ M |
+
+
+ | 98 |
+ R7053P |
+ BXD102 |
+ Pituitary |
+ 88 |
+ F |
+
+
+ | 99 |
+ R7046P |
+ BXD102 |
+ Pituitary |
+ 88 |
+ M |
+
+
+ | 100 |
+ R7090P |
+ BXD103 |
+ Pituitary |
+ 78 |
+ F |
+
+
+ | 101 |
+ R7067P |
+ BXD103 |
+ Pituitary |
+ 78 |
+ M |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Inia_pg_rma_ex_0612/citation.rtf b/general/datasets/Inia_pg_rma_ex_0612/citation.rtf
new file mode 100644
index 0000000..1ef65cb
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_ex_0612/citation.rtf
@@ -0,0 +1 @@
+Contact RW Williams
diff --git a/general/datasets/Inia_pg_rma_ex_0612/contributors.rtf b/general/datasets/Inia_pg_rma_ex_0612/contributors.rtf
new file mode 100644
index 0000000..5178980
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_ex_0612/contributors.rtf
@@ -0,0 +1 @@
+Mozhui K, Lu L, Adler A, Ingels J, Williams RW
diff --git a/general/datasets/Inia_pg_rma_ex_0612/experiment-design.rtf b/general/datasets/Inia_pg_rma_ex_0612/experiment-design.rtf
new file mode 100644
index 0000000..13175b5
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_ex_0612/experiment-design.rtf
@@ -0,0 +1,10 @@
+Normative expression in the whole pituitary of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
+
+QUALITY CONTROL DATA
+
+
+ - 737 probe sets with LRS of 46 or higher (LOD>10)
+ - Highest LRS = 165.7
+ - Review of top Mendelian transcripts consist with correct strain assignment
+ - Final sex assignment is correct
+
diff --git a/general/datasets/Inia_pg_rma_ex_0612/platform.rtf b/general/datasets/Inia_pg_rma_ex_0612/platform.rtf
new file mode 100644
index 0000000..7057d48
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_ex_0612/platform.rtf
@@ -0,0 +1 @@
+The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/Inia_pg_rma_ex_0612/processing.rtf b/general/datasets/Inia_pg_rma_ex_0612/processing.rtf
new file mode 100644
index 0000000..55aad2e
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_ex_0612/processing.rtf
@@ -0,0 +1 @@
+Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/Inia_pg_rma_ex_0612/summary.rtf b/general/datasets/Inia_pg_rma_ex_0612/summary.rtf
new file mode 100644
index 0000000..14a715d
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_ex_0612/summary.rtf
@@ -0,0 +1,3 @@
+Gene expression data for the whole pituitary across 52 strains of mice. Sex Balance: Sex of samples has been double-checked. As of July 2012, for 42 strains we have separate data for both males and females (usually one array each). Three strains (BXD45, 63, and 95) are only represented by female samples and two strains (BXD65 and BXD77) are only represented by male samples. Five other strains (BXD24, 66, 73, 85, 101) are may represent combined male and female samples. These unpublished data are apparently error-free based on a review and analysis of transcripts with Mendelian segregation patterns (as of July 20, 2012). The data set contains 751 eQTLs with LOD scores above 10 (LRS>46). Peak LRS of 165.9 for Record ID 10513604. Data for BXD70 are somewhat problematic (see 10444135 and 10467784), perhaps due to a bad array, strain assignment error, or residual heterozygozity. S Roy double-checked (July 22) and thinks that Sample R7141P is more likely to be BXD65.
+
+Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/Inia_pg_rma_ex_0612/tissue.rtf b/general/datasets/Inia_pg_rma_ex_0612/tissue.rtf
new file mode 100644
index 0000000..3977f1e
--- /dev/null
+++ b/general/datasets/Inia_pg_rma_ex_0612/tissue.rtf
@@ -0,0 +1 @@
+Whole pituitary gland dissected by hand. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/Inia_pituitary_rma_f_0612/acknowledgment.rtf b/general/datasets/Inia_pituitary_rma_f_0612/acknowledgment.rtf
new file mode 100644
index 0000000..f8bf764
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_f_0612/acknowledgment.rtf
@@ -0,0 +1 @@
+NIAAA U01 support to RWW.
diff --git a/general/datasets/Inia_pituitary_rma_f_0612/cases.rtf b/general/datasets/Inia_pituitary_rma_f_0612/cases.rtf
new file mode 100644
index 0000000..faf8ab0
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_f_0612/cases.rtf
@@ -0,0 +1,840 @@
+Young adult mice raised in specific pathogen-free vivarium at UTHSC.
+
+ERROR CHECKING by Mozhui, Centeno and Roy: The changes have been applied in GeneNetwork (GN389 - Pituitary) as follow:
+
+SampleId - New Strain Assignment
+R7087P (was BXD101) = BXD100
+R7138P_RW170 (was BXD85) = BXD95
+R7156P (was C57BL/6J) = B6D2F1
+R7141P = BXD65
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Tissue |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R7128P |
+ B6D2F1 |
+ Pituitary |
+ 69 |
+ F |
+
+
+ | 2 |
+ R7156P |
+ B6D2F1 |
+ Pituitary |
+ 92 |
+ M |
+
+
+ | 3 |
+ R7129P |
+ B6D2F1 |
+ Pituitary |
+ 69 |
+ M |
+
+
+ | 4 |
+ R7134P |
+ D2B6F1 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 5 |
+ R7133P |
+ D2B6F1 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 6 |
+ R7160P |
+ C57BL/6J |
+ Pituitary |
+ 92 |
+ F |
+
+
+ | 7 |
+ R7127P |
+ C57BL/6J |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 8 |
+ R7126P |
+ DBA/2J |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 9 |
+ R7157P |
+ DBA/2J |
+ Pituitary |
+ 75 |
+ F |
+
+
+ | 10 |
+ R7125P |
+ DBA/2J |
+ Pituitary |
+ 68 |
+ M |
+
+
+ | 11 |
+ R7155P |
+ DBA/2J |
+ Pituitary |
+ 75 |
+ M |
+
+
+ | 12 |
+ R7058P |
+ BXD1 |
+ Pituitary |
+ 72 |
+ F |
+
+
+ | 13 |
+ R7063P |
+ BXD1 |
+ Pituitary |
+ 86 |
+ M |
+
+
+ | 14 |
+ R7079P |
+ BXD11 |
+ Pituitary |
+ 87 |
+ F |
+
+
+ | 15 |
+ R7069P |
+ BXD11 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 16 |
+ R7051P |
+ BXD12 |
+ Pituitary |
+ 78 |
+ F |
+
+
+ | 17 |
+ R7061P |
+ BXD12 |
+ Pituitary |
+ 78 |
+ M |
+
+
+ | 18 |
+ R7064P |
+ BXD14 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 19 |
+ R7066P |
+ BXD14 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 20 |
+ R7052P |
+ BXD24 |
+ Pituitary |
+ 86 |
+ M |
+
+
+ | 21 |
+ R7076P |
+ BXD27 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 22 |
+ R7071P |
+ BXD27 |
+ Pituitary |
+ 73 |
+ M |
+
+
+ | 23 |
+ R7059P |
+ BXD29 |
+ Pituitary |
+ 72 |
+ F |
+
+
+ | 24 |
+ R7060P |
+ BXD29 |
+ Pituitary |
+ 72 |
+ M |
+
+
+ | 25 |
+ R7055P |
+ BXD31 |
+ Pituitary |
+ 74 |
+ F |
+
+
+ | 26 |
+ R7062P |
+ BXD31 |
+ Pituitary |
+ 74 |
+ M |
+
+
+ | 27 |
+ R7143P |
+ BXD32 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 28 |
+ R7135P |
+ BXD32 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 29 |
+ R7119P |
+ BXD34 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 30 |
+ R7054P |
+ BXD34 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 31 |
+ R7049P |
+ BXD39 |
+ Pituitary |
+ 79 |
+ F |
+
+
+ | 32 |
+ R7065P |
+ BXD39 |
+ Pituitary |
+ 79 |
+ M |
+
+
+ | 33 |
+ R7130P |
+ BXD40 |
+ Pituitary |
+ 85 |
+ F |
+
+
+ | 34 |
+ R7132P |
+ BXD40 |
+ Pituitary |
+ 85 |
+ M |
+
+
+ | 35 |
+ R7056P |
+ BXD42 |
+ Pituitary |
+ 87 |
+ F |
+
+
+ | 36 |
+ R7044P |
+ BXD42 |
+ Pituitary |
+ 87 |
+ M |
+
+
+ | 37 |
+ R7043P |
+ BXD43 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 38 |
+ R7047P |
+ BXD43 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 39 |
+ R7091P |
+ BXD44 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 40 |
+ R7050P |
+ BXD44 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 41 |
+ R7077P |
+ BXD45 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 42 |
+ R7078P |
+ BXD45 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 43 |
+ R7042P |
+ BXD45 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 44 |
+ R7092P |
+ BXD48 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 45 |
+ R7093P |
+ BXD48 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 46 |
+ R7045P |
+ BXD49 |
+ Pituitary |
+ 84 |
+ F |
+
+
+ | 47 |
+ R7094P |
+ BXD49 |
+ Pituitary |
+ 84 |
+ M |
+
+
+ | 48 |
+ R7095P |
+ BXD50 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 49 |
+ R7096P |
+ BXD50 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 50 |
+ R7142P |
+ BXD56 |
+ Pituitary |
+ 84 |
+ F |
+
+
+ | 51 |
+ R7097P |
+ BXD56 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 52 |
+ R7080P |
+ BXD60 |
+ Pituitary |
+ 70 |
+ F |
+
+
+ | 53 |
+ R7141P_RW204 |
+ BXD60 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 54 |
+ R7075P |
+ BXD62 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 55 |
+ R7083P |
+ BXD62 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 56 |
+ R7084P |
+ BXD62 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 57 |
+ R7098P |
+ BXD63 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 58 |
+ R7100P |
+ BXD65 |
+ Pituitary |
+ 84 |
+ M |
+
+
+ | 59 |
+ R7120P |
+ BXD66 |
+ Pituitary |
+ 257 |
+ M |
+
+
+ | 60 |
+ R7140P |
+ BXD68 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 61 |
+ R7101P |
+ BXD68 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 62 |
+ R7074P |
+ BXD69 |
+ Pituitary |
+ 69 |
+ F |
+
+
+ | 63 |
+ R7139P |
+ BXD69 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 64 |
+ R7141P |
+ BXD65 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 65 |
+ R7137P_RW112 |
+ BXD70 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 66 |
+ R7124P |
+ BXD71 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 67 |
+ R7123P |
+ BXD71 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 68 |
+ R7068P |
+ BXD73 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 69 |
+ R7118P |
+ BXD74 |
+ Pituitary |
+ 69 |
+ F |
+
+
+ | 70 |
+ R7117P |
+ BXD74 |
+ Pituitary |
+ 69 |
+ M |
+
+
+ | 71 |
+ R7082P |
+ BXD75 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 72 |
+ R7048P |
+ BXD75 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 73 |
+ R7122P |
+ BXD77 |
+ Pituitary |
+ 223 |
+ M |
+
+
+ | 74 |
+ R7103P |
+ BXD79 |
+ Pituitary |
+ 86 |
+ F |
+
+
+ | 75 |
+ R7104P |
+ BXD79 |
+ Pituitary |
+ 86 |
+ M |
+
+
+ | 76 |
+ R7073P |
+ BXD80 |
+ Pituitary |
+ 73 |
+ F |
+
+
+ | 77 |
+ R7070P |
+ BXD80 |
+ Pituitary |
+ 73 |
+ M |
+
+
+ | 78 |
+ R7139P_RW138 |
+ BXD83 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 79 |
+ R7137P |
+ BXD83 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 80 |
+ R7085P |
+ BXD84 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 81 |
+ R7081P |
+ BXD84 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 82 |
+ R7105P |
+ BXD85 |
+ Pituitary |
+ 73 |
+ M |
+
+
+ | 83 |
+ R7144P |
+ BXD87 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 84 |
+ R7136P_RW196 |
+ BXD87 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 85 |
+ R7106P |
+ BXD89 |
+ Pituitary |
+ 82 |
+ F |
+
+
+ | 86 |
+ R7107P |
+ BXD89 |
+ Pituitary |
+ 82 |
+ M |
+
+
+ | 87 |
+ R7108P |
+ BXD90 |
+ Pituitary |
+ 82 |
+ F |
+
+
+ | 88 |
+ R7109P |
+ BXD90 |
+ Pituitary |
+ 82 |
+ M |
+
+
+ | 89 |
+ R7138P_RW170 |
+ BXD95 |
+ Pituitary |
+ 73 |
+ F |
+
+
+ | 90 |
+ R7111P |
+ BXD97 |
+ Pituitary |
+ 71 |
+ F |
+
+
+ | 91 |
+ R7112P |
+ BXD97 |
+ Pituitary |
+ 71 |
+ M |
+
+
+ | 92 |
+ R7113P |
+ BXD99 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 93 |
+ R7114P |
+ BXD99 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 94 |
+ R7072P |
+ BXD100 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 95 |
+ R7087P |
+ BXD100 |
+ Pituitary |
+ 88 |
+ F |
+
+
+ | 96 |
+ R7086P |
+ BXD100 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 97 |
+ R7088P |
+ BXD101 |
+ Pituitary |
+ 88 |
+ M |
+
+
+ | 98 |
+ R7053P |
+ BXD102 |
+ Pituitary |
+ 88 |
+ F |
+
+
+ | 99 |
+ R7046P |
+ BXD102 |
+ Pituitary |
+ 88 |
+ M |
+
+
+ | 100 |
+ R7090P |
+ BXD103 |
+ Pituitary |
+ 78 |
+ F |
+
+
+ | 101 |
+ R7067P |
+ BXD103 |
+ Pituitary |
+ 78 |
+ M |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Inia_pituitary_rma_f_0612/citation.rtf b/general/datasets/Inia_pituitary_rma_f_0612/citation.rtf
new file mode 100644
index 0000000..1ef65cb
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_f_0612/citation.rtf
@@ -0,0 +1 @@
+Contact RW Williams
diff --git a/general/datasets/Inia_pituitary_rma_f_0612/contributors.rtf b/general/datasets/Inia_pituitary_rma_f_0612/contributors.rtf
new file mode 100644
index 0000000..5178980
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_f_0612/contributors.rtf
@@ -0,0 +1 @@
+Mozhui K, Lu L, Adler A, Ingels J, Williams RW
diff --git a/general/datasets/Inia_pituitary_rma_f_0612/experiment-design.rtf b/general/datasets/Inia_pituitary_rma_f_0612/experiment-design.rtf
new file mode 100644
index 0000000..13175b5
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_f_0612/experiment-design.rtf
@@ -0,0 +1,10 @@
+Normative expression in the whole pituitary of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
+
+QUALITY CONTROL DATA
+
+
+ - 737 probe sets with LRS of 46 or higher (LOD>10)
+ - Highest LRS = 165.7
+ - Review of top Mendelian transcripts consist with correct strain assignment
+ - Final sex assignment is correct
+
diff --git a/general/datasets/Inia_pituitary_rma_f_0612/platform.rtf b/general/datasets/Inia_pituitary_rma_f_0612/platform.rtf
new file mode 100644
index 0000000..7057d48
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_f_0612/platform.rtf
@@ -0,0 +1 @@
+The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/Inia_pituitary_rma_f_0612/processing.rtf b/general/datasets/Inia_pituitary_rma_f_0612/processing.rtf
new file mode 100644
index 0000000..55aad2e
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_f_0612/processing.rtf
@@ -0,0 +1 @@
+Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/Inia_pituitary_rma_f_0612/summary.rtf b/general/datasets/Inia_pituitary_rma_f_0612/summary.rtf
new file mode 100644
index 0000000..14a715d
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_f_0612/summary.rtf
@@ -0,0 +1,3 @@
+Gene expression data for the whole pituitary across 52 strains of mice. Sex Balance: Sex of samples has been double-checked. As of July 2012, for 42 strains we have separate data for both males and females (usually one array each). Three strains (BXD45, 63, and 95) are only represented by female samples and two strains (BXD65 and BXD77) are only represented by male samples. Five other strains (BXD24, 66, 73, 85, 101) are may represent combined male and female samples. These unpublished data are apparently error-free based on a review and analysis of transcripts with Mendelian segregation patterns (as of July 20, 2012). The data set contains 751 eQTLs with LOD scores above 10 (LRS>46). Peak LRS of 165.9 for Record ID 10513604. Data for BXD70 are somewhat problematic (see 10444135 and 10467784), perhaps due to a bad array, strain assignment error, or residual heterozygozity. S Roy double-checked (July 22) and thinks that Sample R7141P is more likely to be BXD65.
+
+Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/Inia_pituitary_rma_f_0612/tissue.rtf b/general/datasets/Inia_pituitary_rma_f_0612/tissue.rtf
new file mode 100644
index 0000000..3977f1e
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_f_0612/tissue.rtf
@@ -0,0 +1 @@
+Whole pituitary gland dissected by hand. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/Inia_pituitary_rma_m_0612/acknowledgment.rtf b/general/datasets/Inia_pituitary_rma_m_0612/acknowledgment.rtf
new file mode 100644
index 0000000..f8bf764
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_m_0612/acknowledgment.rtf
@@ -0,0 +1 @@
+NIAAA U01 support to RWW.
diff --git a/general/datasets/Inia_pituitary_rma_m_0612/cases.rtf b/general/datasets/Inia_pituitary_rma_m_0612/cases.rtf
new file mode 100644
index 0000000..faf8ab0
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_m_0612/cases.rtf
@@ -0,0 +1,840 @@
+Young adult mice raised in specific pathogen-free vivarium at UTHSC.
+
+ERROR CHECKING by Mozhui, Centeno and Roy: The changes have been applied in GeneNetwork (GN389 - Pituitary) as follow:
+
+SampleId - New Strain Assignment
+R7087P (was BXD101) = BXD100
+R7138P_RW170 (was BXD85) = BXD95
+R7156P (was C57BL/6J) = B6D2F1
+R7141P = BXD65
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Tissue |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R7128P |
+ B6D2F1 |
+ Pituitary |
+ 69 |
+ F |
+
+
+ | 2 |
+ R7156P |
+ B6D2F1 |
+ Pituitary |
+ 92 |
+ M |
+
+
+ | 3 |
+ R7129P |
+ B6D2F1 |
+ Pituitary |
+ 69 |
+ M |
+
+
+ | 4 |
+ R7134P |
+ D2B6F1 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 5 |
+ R7133P |
+ D2B6F1 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 6 |
+ R7160P |
+ C57BL/6J |
+ Pituitary |
+ 92 |
+ F |
+
+
+ | 7 |
+ R7127P |
+ C57BL/6J |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 8 |
+ R7126P |
+ DBA/2J |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 9 |
+ R7157P |
+ DBA/2J |
+ Pituitary |
+ 75 |
+ F |
+
+
+ | 10 |
+ R7125P |
+ DBA/2J |
+ Pituitary |
+ 68 |
+ M |
+
+
+ | 11 |
+ R7155P |
+ DBA/2J |
+ Pituitary |
+ 75 |
+ M |
+
+
+ | 12 |
+ R7058P |
+ BXD1 |
+ Pituitary |
+ 72 |
+ F |
+
+
+ | 13 |
+ R7063P |
+ BXD1 |
+ Pituitary |
+ 86 |
+ M |
+
+
+ | 14 |
+ R7079P |
+ BXD11 |
+ Pituitary |
+ 87 |
+ F |
+
+
+ | 15 |
+ R7069P |
+ BXD11 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 16 |
+ R7051P |
+ BXD12 |
+ Pituitary |
+ 78 |
+ F |
+
+
+ | 17 |
+ R7061P |
+ BXD12 |
+ Pituitary |
+ 78 |
+ M |
+
+
+ | 18 |
+ R7064P |
+ BXD14 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 19 |
+ R7066P |
+ BXD14 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 20 |
+ R7052P |
+ BXD24 |
+ Pituitary |
+ 86 |
+ M |
+
+
+ | 21 |
+ R7076P |
+ BXD27 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 22 |
+ R7071P |
+ BXD27 |
+ Pituitary |
+ 73 |
+ M |
+
+
+ | 23 |
+ R7059P |
+ BXD29 |
+ Pituitary |
+ 72 |
+ F |
+
+
+ | 24 |
+ R7060P |
+ BXD29 |
+ Pituitary |
+ 72 |
+ M |
+
+
+ | 25 |
+ R7055P |
+ BXD31 |
+ Pituitary |
+ 74 |
+ F |
+
+
+ | 26 |
+ R7062P |
+ BXD31 |
+ Pituitary |
+ 74 |
+ M |
+
+
+ | 27 |
+ R7143P |
+ BXD32 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 28 |
+ R7135P |
+ BXD32 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 29 |
+ R7119P |
+ BXD34 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 30 |
+ R7054P |
+ BXD34 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 31 |
+ R7049P |
+ BXD39 |
+ Pituitary |
+ 79 |
+ F |
+
+
+ | 32 |
+ R7065P |
+ BXD39 |
+ Pituitary |
+ 79 |
+ M |
+
+
+ | 33 |
+ R7130P |
+ BXD40 |
+ Pituitary |
+ 85 |
+ F |
+
+
+ | 34 |
+ R7132P |
+ BXD40 |
+ Pituitary |
+ 85 |
+ M |
+
+
+ | 35 |
+ R7056P |
+ BXD42 |
+ Pituitary |
+ 87 |
+ F |
+
+
+ | 36 |
+ R7044P |
+ BXD42 |
+ Pituitary |
+ 87 |
+ M |
+
+
+ | 37 |
+ R7043P |
+ BXD43 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 38 |
+ R7047P |
+ BXD43 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 39 |
+ R7091P |
+ BXD44 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 40 |
+ R7050P |
+ BXD44 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 41 |
+ R7077P |
+ BXD45 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 42 |
+ R7078P |
+ BXD45 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 43 |
+ R7042P |
+ BXD45 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 44 |
+ R7092P |
+ BXD48 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 45 |
+ R7093P |
+ BXD48 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 46 |
+ R7045P |
+ BXD49 |
+ Pituitary |
+ 84 |
+ F |
+
+
+ | 47 |
+ R7094P |
+ BXD49 |
+ Pituitary |
+ 84 |
+ M |
+
+
+ | 48 |
+ R7095P |
+ BXD50 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 49 |
+ R7096P |
+ BXD50 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 50 |
+ R7142P |
+ BXD56 |
+ Pituitary |
+ 84 |
+ F |
+
+
+ | 51 |
+ R7097P |
+ BXD56 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 52 |
+ R7080P |
+ BXD60 |
+ Pituitary |
+ 70 |
+ F |
+
+
+ | 53 |
+ R7141P_RW204 |
+ BXD60 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 54 |
+ R7075P |
+ BXD62 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 55 |
+ R7083P |
+ BXD62 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 56 |
+ R7084P |
+ BXD62 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 57 |
+ R7098P |
+ BXD63 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 58 |
+ R7100P |
+ BXD65 |
+ Pituitary |
+ 84 |
+ M |
+
+
+ | 59 |
+ R7120P |
+ BXD66 |
+ Pituitary |
+ 257 |
+ M |
+
+
+ | 60 |
+ R7140P |
+ BXD68 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 61 |
+ R7101P |
+ BXD68 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 62 |
+ R7074P |
+ BXD69 |
+ Pituitary |
+ 69 |
+ F |
+
+
+ | 63 |
+ R7139P |
+ BXD69 |
+ Pituitary |
+ 81 |
+ M |
+
+
+ | 64 |
+ R7141P |
+ BXD65 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 65 |
+ R7137P_RW112 |
+ BXD70 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 66 |
+ R7124P |
+ BXD71 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 67 |
+ R7123P |
+ BXD71 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 68 |
+ R7068P |
+ BXD73 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 69 |
+ R7118P |
+ BXD74 |
+ Pituitary |
+ 69 |
+ F |
+
+
+ | 70 |
+ R7117P |
+ BXD74 |
+ Pituitary |
+ 69 |
+ M |
+
+
+ | 71 |
+ R7082P |
+ BXD75 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 72 |
+ R7048P |
+ BXD75 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 73 |
+ R7122P |
+ BXD77 |
+ Pituitary |
+ 223 |
+ M |
+
+
+ | 74 |
+ R7103P |
+ BXD79 |
+ Pituitary |
+ 86 |
+ F |
+
+
+ | 75 |
+ R7104P |
+ BXD79 |
+ Pituitary |
+ 86 |
+ M |
+
+
+ | 76 |
+ R7073P |
+ BXD80 |
+ Pituitary |
+ 73 |
+ F |
+
+
+ | 77 |
+ R7070P |
+ BXD80 |
+ Pituitary |
+ 73 |
+ M |
+
+
+ | 78 |
+ R7139P_RW138 |
+ BXD83 |
+ Pituitary |
+ 81 |
+ F |
+
+
+ | 79 |
+ R7137P |
+ BXD83 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 80 |
+ R7085P |
+ BXD84 |
+ Pituitary |
+ 76 |
+ F |
+
+
+ | 81 |
+ R7081P |
+ BXD84 |
+ Pituitary |
+ 76 |
+ M |
+
+
+ | 82 |
+ R7105P |
+ BXD85 |
+ Pituitary |
+ 73 |
+ M |
+
+
+ | 83 |
+ R7144P |
+ BXD87 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 84 |
+ R7136P_RW196 |
+ BXD87 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 85 |
+ R7106P |
+ BXD89 |
+ Pituitary |
+ 82 |
+ F |
+
+
+ | 86 |
+ R7107P |
+ BXD89 |
+ Pituitary |
+ 82 |
+ M |
+
+
+ | 87 |
+ R7108P |
+ BXD90 |
+ Pituitary |
+ 82 |
+ F |
+
+
+ | 88 |
+ R7109P |
+ BXD90 |
+ Pituitary |
+ 82 |
+ M |
+
+
+ | 89 |
+ R7138P_RW170 |
+ BXD95 |
+ Pituitary |
+ 73 |
+ F |
+
+
+ | 90 |
+ R7111P |
+ BXD97 |
+ Pituitary |
+ 71 |
+ F |
+
+
+ | 91 |
+ R7112P |
+ BXD97 |
+ Pituitary |
+ 71 |
+ M |
+
+
+ | 92 |
+ R7113P |
+ BXD99 |
+ Pituitary |
+ 77 |
+ F |
+
+
+ | 93 |
+ R7114P |
+ BXD99 |
+ Pituitary |
+ 77 |
+ M |
+
+
+ | 94 |
+ R7072P |
+ BXD100 |
+ Pituitary |
+ 83 |
+ F |
+
+
+ | 95 |
+ R7087P |
+ BXD100 |
+ Pituitary |
+ 88 |
+ F |
+
+
+ | 96 |
+ R7086P |
+ BXD100 |
+ Pituitary |
+ 83 |
+ M |
+
+
+ | 97 |
+ R7088P |
+ BXD101 |
+ Pituitary |
+ 88 |
+ M |
+
+
+ | 98 |
+ R7053P |
+ BXD102 |
+ Pituitary |
+ 88 |
+ F |
+
+
+ | 99 |
+ R7046P |
+ BXD102 |
+ Pituitary |
+ 88 |
+ M |
+
+
+ | 100 |
+ R7090P |
+ BXD103 |
+ Pituitary |
+ 78 |
+ F |
+
+
+ | 101 |
+ R7067P |
+ BXD103 |
+ Pituitary |
+ 78 |
+ M |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Inia_pituitary_rma_m_0612/citation.rtf b/general/datasets/Inia_pituitary_rma_m_0612/citation.rtf
new file mode 100644
index 0000000..1ef65cb
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_m_0612/citation.rtf
@@ -0,0 +1 @@
+Contact RW Williams
diff --git a/general/datasets/Inia_pituitary_rma_m_0612/contributors.rtf b/general/datasets/Inia_pituitary_rma_m_0612/contributors.rtf
new file mode 100644
index 0000000..5178980
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_m_0612/contributors.rtf
@@ -0,0 +1 @@
+Mozhui K, Lu L, Adler A, Ingels J, Williams RW
diff --git a/general/datasets/Inia_pituitary_rma_m_0612/experiment-design.rtf b/general/datasets/Inia_pituitary_rma_m_0612/experiment-design.rtf
new file mode 100644
index 0000000..13175b5
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_m_0612/experiment-design.rtf
@@ -0,0 +1,10 @@
+Normative expression in the whole pituitary of young adult mice. In general, a sex-balanced samples (one array from male cases, one array from female cases) for BXD and parental strains.
+
+QUALITY CONTROL DATA
+
+
+ - 737 probe sets with LRS of 46 or higher (LOD>10)
+ - Highest LRS = 165.7
+ - Review of top Mendelian transcripts consist with correct strain assignment
+ - Final sex assignment is correct
+
diff --git a/general/datasets/Inia_pituitary_rma_m_0612/platform.rtf b/general/datasets/Inia_pituitary_rma_m_0612/platform.rtf
new file mode 100644
index 0000000..7057d48
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_m_0612/platform.rtf
@@ -0,0 +1 @@
+The GeneChip® Mouse Gene 1.0 ST Array is the latest product in the family of Affymetrix expression arrays offering whole-transcript coverage. Each of the 28,853 genes is represented on the array by approximately 27 probes spread across the full length of the gene, providing a more complete and more accurate picture of gene expression than 3'-based expression array designs. The small format of the array makes it a cost-effective expression profiling solution for new microarray users. Sense DNA targets are generated from as little as 100ng of total RNA. The Gene 1.0 ST Array is part of a complete solution for gene expression analysis that includes Whole Transcript (WT) Sense Target Labeling and Control Reagents, fluidics and scanning instrumentation and basic analysis software. The array contains the most up-to-date content of well-annotated genes, and data is analyzed using a simple workflow. The Gene 1.0 ST Array uses a subset of probes from the Mouse Exon 1.0 ST Array and covers only well-annotated content. Like the Exon 1.0 ST Array, "gene-level" analysis of multiple probes on different exons is summarized into an expression value representing all transcripts from the same gene.
diff --git a/general/datasets/Inia_pituitary_rma_m_0612/processing.rtf b/general/datasets/Inia_pituitary_rma_m_0612/processing.rtf
new file mode 100644
index 0000000..55aad2e
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_m_0612/processing.rtf
@@ -0,0 +1 @@
+Conventional Affymetrix gene level probe summarization (RMA) followed by log2 transformation and standard GeneNetwork variance stabilization (2z +8). The z scores are multiplied by 2 and we then add a value of 8 to all values. This eliminates negative values and results in a scale of expression for which 1 unit is roughly equivalent to a two fold absolute difference in mRNA concentration.
diff --git a/general/datasets/Inia_pituitary_rma_m_0612/summary.rtf b/general/datasets/Inia_pituitary_rma_m_0612/summary.rtf
new file mode 100644
index 0000000..14a715d
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_m_0612/summary.rtf
@@ -0,0 +1,3 @@
+Gene expression data for the whole pituitary across 52 strains of mice. Sex Balance: Sex of samples has been double-checked. As of July 2012, for 42 strains we have separate data for both males and females (usually one array each). Three strains (BXD45, 63, and 95) are only represented by female samples and two strains (BXD65 and BXD77) are only represented by male samples. Five other strains (BXD24, 66, 73, 85, 101) are may represent combined male and female samples. These unpublished data are apparently error-free based on a review and analysis of transcripts with Mendelian segregation patterns (as of July 20, 2012). The data set contains 751 eQTLs with LOD scores above 10 (LRS>46). Peak LRS of 165.9 for Record ID 10513604. Data for BXD70 are somewhat problematic (see 10444135 and 10467784), perhaps due to a bad array, strain assignment error, or residual heterozygozity. S Roy double-checked (July 22) and thinks that Sample R7141P is more likely to be BXD65.
+
+Part of a systematic genetic analysis of the hypothalamus-pituitary-adrenal axis in the BXD family of strains.
diff --git a/general/datasets/Inia_pituitary_rma_m_0612/tissue.rtf b/general/datasets/Inia_pituitary_rma_m_0612/tissue.rtf
new file mode 100644
index 0000000..3977f1e
--- /dev/null
+++ b/general/datasets/Inia_pituitary_rma_m_0612/tissue.rtf
@@ -0,0 +1 @@
+Whole pituitary gland dissected by hand. Dissections by Khyobeni Mozhui, Jesse Ingels, and Adrienne Adler at UTHSC.
diff --git a/general/datasets/Inia_uthsc_hip_affymta1_may17/summary.rtf b/general/datasets/Inia_uthsc_hip_affymta1_may17/summary.rtf
new file mode 100644
index 0000000..153d98d
--- /dev/null
+++ b/general/datasets/Inia_uthsc_hip_affymta1_may17/summary.rtf
@@ -0,0 +1 @@
+In working progress...
diff --git a/general/datasets/Inia_uthsc_mid_affymta1_apr17/cases.rtf b/general/datasets/Inia_uthsc_mid_affymta1_apr17/cases.rtf
new file mode 100644
index 0000000..976f0ab
--- /dev/null
+++ b/general/datasets/Inia_uthsc_mid_affymta1_apr17/cases.rtf
@@ -0,0 +1,857 @@
+
+
+
+
+
+
+
+
+
+
+
+ | MicroarrayID |
+ Mouse.ID |
+ Strain |
+ Pyrazole |
+ TimePoint |
+ Treatment |
+ PCA Batch |
+ DissectionBatch |
+ ExtractionBatch |
+ Concentration |
+ RIN |
+
+
+ | MB1 |
+ 12 |
+ C57BL/6J |
+ PZ |
+ 8h |
+ CIE |
+ B |
+ A |
+ 1 |
+ 224.611 |
+ 9.0 |
+
+
+ | MB2 |
+ 50 |
+ DBA/2J |
+ NO |
+ 3d |
+ AIR |
+ B |
+ A |
+ 1 |
+ 195.150 |
+ 9.2 |
+
+
+ | MB3 |
+ 2 |
+ C57BL/6J |
+ PZ |
+ 14d |
+ AIR |
+ B |
+ A |
+ 1 |
+ 299.415 |
+ 9.5 |
+
+
+ | MB4 |
+ 60 |
+ DBA/2J |
+ PZ |
+ 7d |
+ AIR |
+ B |
+ A |
+ 1 |
+ 300.033 |
+ 7.6 |
+
+
+ | MB5 |
+ 4 |
+ C57BL/6J |
+ PZ |
+ 14d |
+ CIE |
+ A |
+ A |
+ 1 |
+ 249.226 |
+ 7.2 |
+
+
+ | MB6 |
+ 69 |
+ DBA/2J |
+ PZ |
+ 7d |
+ AIR |
+ A |
+ A |
+ 1 |
+ 161.526 |
+ 7.3 |
+
+
+ | MB7 |
+ 8 |
+ C57BL/6J |
+ PZ |
+ 3d |
+ CIE |
+ B |
+ A |
+ 1 |
+ 326.862 |
+ 9.5 |
+
+
+ | MB8 |
+ 41 |
+ DBA/2J |
+ PZ |
+ 8h |
+ AIR |
+ B |
+ A |
+ 1 |
+ 352.559 |
+ 7.9 |
+
+
+ | MB9 |
+ 75 |
+ DBA/2J |
+ PZ |
+ 14d |
+ AIR |
+ B |
+ B |
+ 1 |
+ 354.218 |
+ 8.8 |
+
+
+ | MB10 |
+ 23 |
+ C57BL/6J |
+ PZ |
+ 3d |
+ AIR |
+ B |
+ B |
+ 1 |
+ 280.396 |
+ 9.6 |
+
+
+ | MB11 |
+ 49 |
+ DBA/2J |
+ PZ |
+ 3d |
+ AIR |
+ A |
+ B |
+ 1 |
+ 180.312 |
+ 7.2 |
+
+
+ | MB12 |
+ 58 |
+ DBA/2J |
+ PZ |
+ 3d |
+ CIE |
+ B |
+ B |
+ 1 |
+ 225.072 |
+ NA |
+
+
+ | MB13 |
+ 21 |
+ C57BL/6J |
+ PZ |
+ 14d |
+ CIE |
+ B |
+ C |
+ 1 |
+ 299.623 |
+ 7.4 |
+
+
+ | MB14 |
+ 63 |
+ DBA/2J |
+ PZ |
+ 3d |
+ CIE |
+ B |
+ C |
+ 1 |
+ 70.977 |
+ 7.5 |
+
+
+ | MB15 |
+ 46 |
+ DBA/2J |
+ PZ |
+ 8h |
+ AIR |
+ B |
+ C |
+ 1 |
+ 284.115 |
+ 7.9 |
+
+
+ | MB16 |
+ 45 |
+ DBA/2J |
+ PZ |
+ 8h |
+ AIR |
+ B |
+ C |
+ 1 |
+ 338.791 |
+ 7.7 |
+
+
+ | MB17 |
+ 28 |
+ C57BL/6J |
+ NO |
+ 3d |
+ AIR |
+ B |
+ C |
+ 1 |
+ 449.851 |
+ 7.8 |
+
+
+ | MB18 |
+ 78 |
+ DBA/2J |
+ PZ |
+ 14d |
+ AIR |
+ B |
+ C |
+ 1 |
+ 320.081 |
+ 7.9 |
+
+
+ | MB19 |
+ 77 |
+ DBA/2J |
+ PZ |
+ 14d |
+ CIE |
+ B |
+ C |
+ 1 |
+ 234.795 |
+ 7.8 |
+
+
+ | MB20 |
+ 71 |
+ DBA/2J |
+ PZ |
+ 7d |
+ CIE |
+ B |
+ C |
+ 1 |
+ 468.728 |
+ 7.8 |
+
+
+ | MB21 |
+ 68 |
+ DBA/2J |
+ PZ |
+ 7d |
+ AIR |
+ B |
+ C |
+ 1 |
+ 296.386 |
+ 7.9 |
+
+
+ | MB22 |
+ 29 |
+ C57BL/6J |
+ PZ |
+ 8h |
+ CIE |
+ B |
+ C |
+ 1 |
+ 398.481 |
+ 8.0 |
+
+
+ | MB23 |
+ 67 |
+ DBA/2J |
+ PZ |
+ 7d |
+ CIE |
+ B |
+ A |
+ 2 |
+ 275.813 |
+ 7.8 |
+
+
+ | MB24 |
+ 1 |
+ C57BL/6J |
+ PZ |
+ 8h |
+ AIR |
+ A |
+ A |
+ 2 |
+ 132.589 |
+ 6.8 |
+
+
+ | MB25 |
+ 14 |
+ C57BL/6J |
+ NO |
+ 3d |
+ CIE |
+ A |
+ A |
+ 2 |
+ 189.666 |
+ 7.9 |
+
+
+ | MB26 |
+ 42 |
+ DBA/2J |
+ PZ |
+ 8h |
+ CIE |
+ B |
+ A |
+ 2 |
+ 310.878 |
+ 9.4 |
+
+
+ | MB27 |
+ 55 |
+ DBA/2J |
+ PZ |
+ 3d |
+ CIE |
+ B |
+ A |
+ 2 |
+ 211.576 |
+ 9.0 |
+
+
+ | MB28 |
+ 73 |
+ DBA/2J |
+ PZ |
+ 7d |
+ CIE |
+ B |
+ A |
+ 2 |
+ 287.696 |
+ 7.6 |
+
+
+ | MB29 |
+ 48 |
+ DBA/2J |
+ PZ |
+ 3d |
+ AIR |
+ B |
+ A |
+ 2 |
+ 317.532 |
+ 7.8 |
+
+
+ | MB30 |
+ 61 |
+ DBA/2J |
+ PZ |
+ 7d |
+ AIR |
+ B |
+ B |
+ 2 |
+ 294.808 |
+ 7.8 |
+
+
+ | MB31 |
+ 20 |
+ C57BL/6J |
+ PZ |
+ 8h |
+ CIE |
+ B |
+ B |
+ 2 |
+ 209.301 |
+ 9.0 |
+
+
+ | MB32 |
+ 76 |
+ DBA/2J |
+ PZ |
+ 14d |
+ CIE |
+ A |
+ B |
+ 2 |
+ 120.953 |
+ 8.2 |
+
+
+ | MB33 |
+ 5 |
+ C57BL/6J |
+ PZ |
+ 14d |
+ AIR |
+ B |
+ B |
+ 2 |
+ 271.808 |
+ 8.8 |
+
+
+ | MB34 |
+ 37 |
+ C57BL/6J |
+ PZ |
+ 7d |
+ CIE |
+ B |
+ B |
+ 2 |
+ 289.261 |
+ 8.0 |
+
+
+ | MB35 |
+ 19 |
+ C57BL/6J |
+ PZ |
+ 3d |
+ CIE |
+ B |
+ C |
+ 2 |
+ 306.294 |
+ 9.1 |
+
+
+ | MB36 |
+ 56 |
+ DBA/2J |
+ PZ |
+ 3d |
+ AIR |
+ B |
+ C |
+ 2 |
+ 265.964 |
+ 7.8 |
+
+
+ | MB37 |
+ 65 |
+ DBA/2J |
+ NO |
+ 3d |
+ CIE |
+ B |
+ C |
+ 2 |
+ 259.741 |
+ 9.2 |
+
+
+ | MB38 |
+ 80 |
+ DBA/2J |
+ PZ |
+ 14d |
+ AIR |
+ B |
+ C |
+ 2 |
+ 371.000 |
+ 8.0 |
+
+
+ | MB39 |
+ 31 |
+ C57BL/6J |
+ PZ |
+ 14d |
+ CIE |
+ B |
+ C |
+ 2 |
+ 349.451 |
+ 7.7 |
+
+
+ | MB40 |
+ 39 |
+ C57BL/6J |
+ PZ |
+ 7d |
+ AIR |
+ C |
+ C |
+ 2 |
+ 403.083 |
+ 8.9 |
+
+
+ | MB41 |
+ 62 |
+ DBA/2J |
+ PZ |
+ 3d |
+ CIE |
+ C |
+ C |
+ 2 |
+ 505.547 |
+ 8.9 |
+
+
+ | MB42 |
+ 52 |
+ DBA/2J |
+ PZ |
+ 8h |
+ CIE |
+ C |
+ C |
+ 2 |
+ 441.549 |
+ 8.8 |
+
+
+ | MB43 |
+ 51 |
+ DBA/2J |
+ PZ |
+ 3d |
+ AIR |
+ C |
+ C |
+ 2 |
+ 519.427 |
+ 8.8 |
+
+
+ | MB44 |
+ 35 |
+ C57BL/6J |
+ NO |
+ 3d |
+ AIR |
+ C |
+ A |
+ 3 |
+ 772.361 |
+ 8.8 |
+
+
+ | MB45 |
+ 72 |
+ DBA/2J |
+ PZ |
+ 14d |
+ AIR |
+ C |
+ A |
+ 3 |
+ 598.185 |
+ 8.9 |
+
+
+ | MB46 |
+ 32 |
+ C57BL/6J |
+ PZ |
+ 7d |
+ CIE |
+ C |
+ A |
+ 3 |
+ 824.974 |
+ 8.7 |
+
+
+ | MB47 |
+ 74 |
+ DBA/2J |
+ PZ |
+ 14d |
+ CIE |
+ C |
+ A |
+ 3 |
+ 495.046 |
+ 9.4 |
+
+
+ | MB48 |
+ 54 |
+ DBA/2J |
+ PZ |
+ 8h |
+ CIE |
+ C |
+ A |
+ 3 |
+ 667.036 |
+ 9.4 |
+
+
+ | MB49 |
+ 24 |
+ C57BL/6J |
+ PZ |
+ 7d |
+ AIR |
+ C |
+ A |
+ 3 |
+ 760.367 |
+ 9.2 |
+
+
+ | MB50 |
+ 9 |
+ C57BL/6J |
+ PZ |
+ 3d |
+ AIR |
+ C |
+ A |
+ 3 |
+ 701.152 |
+ 9.2 |
+
+
+ | MB51 |
+ 66 |
+ DBA/2J |
+ NO |
+ 3d |
+ CIE |
+ C |
+ B |
+ 3 |
+ 579.22 |
+ 8.3 |
+
+
+ | MB52 |
+ 44 |
+ DBA/2J |
+ PZ |
+ 8h |
+ CIE |
+ C |
+ B |
+ 3 |
+ 636.091 |
+ 9.4 |
+
+
+ | MB53 |
+ 34 |
+ C57BL/6J |
+ PZ |
+ 7d |
+ AIR |
+ C |
+ B |
+ 3 |
+ 739.127 |
+ 9.5 |
+
+
+ | MB54 |
+ 7 |
+ C57BL/6J |
+ PZ |
+ 8h |
+ AIR |
+ C |
+ B |
+ 3 |
+ 667.933 |
+ 9.2 |
+
+
+ | MB55 |
+ 36 |
+ C57BL/6J |
+ NO |
+ 3d |
+ CIE |
+ C |
+ C |
+ 3 |
+ 605.937 |
+ 9.2 |
+
+
+ | MB56 |
+ 43 |
+ DBA/2J |
+ PZ |
+ 8h |
+ AIR |
+ C |
+ C |
+ 3 |
+ 639.161 |
+ 9.5 |
+
+
+ | MB57 |
+ 70 |
+ DBA/2J |
+ PZ |
+ 7d |
+ CIE |
+ C |
+ C |
+ 3 |
+ 630.735 |
+ 9.4 |
+
+
+ | MB58 |
+ 59 |
+ DBA/2J |
+ NO |
+ 3d |
+ AIR |
+ C |
+ C |
+ 3 |
+ 548.647 |
+ 9.5 |
+
+
+ | MB59 |
+ 15 |
+ C57BL/6J |
+ PZ |
+ 14d |
+ AIR |
+ C |
+ C |
+ 3 |
+ 689.793 |
+ 9.4 |
+
+
+ | MB60 |
+ 27 |
+ C57BL/6J |
+ PZ |
+ 8h |
+ AIR |
+ C |
+ C |
+ 3 |
+ 580.462 |
+ 9.4 |
+
+
+ | MB61 |
+ 30 |
+ C57BL/6J |
+ PZ |
+ 3d |
+ AIR |
+ C |
+ C |
+ 3 |
+ 577.826 |
+ 8.2 |
+
+
+ | MB62 |
+ 57 |
+ DBA/2J |
+ PZ |
+ 3d |
+ AIR |
+ C |
+ C |
+ 3 |
+ 581.164 |
+ 9.0 |
+
+
+ | MB63 |
+ 38 |
+ C57BL/6J |
+ PZ |
+ 3d |
+ CIE |
+ C |
+ C |
+ 3 |
+ 748.421 |
+ 8.6 |
+
+
+ | MB64 |
+ 47 |
+ DBA/2J |
+ PZ |
+ 8h |
+ AIR |
+ C |
+ C |
+ 3 |
+ 747.345 |
+ 8.5 |
+
+
+
diff --git a/general/datasets/Inia_uthsc_mid_affymta1_apr17/specifics.rtf b/general/datasets/Inia_uthsc_mid_affymta1_apr17/specifics.rtf
new file mode 100644
index 0000000..729d375
--- /dev/null
+++ b/general/datasets/Inia_uthsc_mid_affymta1_apr17/specifics.rtf
@@ -0,0 +1 @@
+SST-RMA Gene Level
diff --git a/general/datasets/Inia_uthsc_mid_affymta1_apr17/summary.rtf b/general/datasets/Inia_uthsc_mid_affymta1_apr17/summary.rtf
new file mode 100644
index 0000000..9baa040
--- /dev/null
+++ b/general/datasets/Inia_uthsc_mid_affymta1_apr17/summary.rtf
@@ -0,0 +1,31 @@
+Overview:
+
+1. Treated and whole brains dissected at Medical University of South Carolina (Marcelo F. Lopez laboratory)
+
+2. Frozen brains sub-dissected at UTHSC (Megan K. Mulligan laboratory)
+
+3. RNA extraction (Qiagen RNeasy kit) at UTHSC (Mulligan and Williams laboratories)
+
+4. Hybridized to Affymetrix Clariom D (aka Affymetrix MTA 1.0 ST) array at UTHSC MRC (Lorne Rose, UTHSC Molecular Resource Center)
+
+5. Initial QC and normalization (COMBAT) at UTHSC (Megan K. Mulligan laboratory)
+
+6. Transcriptome entry and phenotype entry (Arthur Centeno, Megan K. Mulligan, and Robert W. Williams)
+
+
+
+Chronic ethanol exposure:
+
+Mice were allowed to self-administer alcohol (15% v/v vs. water) for 2 h a day (5 days a week) 6 weeks prior to treatment in order to establish baseline consumption. Access to 15% alcohol versus water started 30 min prior to the start of the dark cycle. Following establishment of baseline drinking, male mice representative of each strain were separated into groups to be exposed to either weekly cycles of CIE exposure (CIE group) or air control (AIR group) exposure.
+
+
+
+Mice assigned to the CIE treatment group were exposed to alcohol vapor for 16 h a day followed by 8 h of withdrawal for 4 days per week. Following the fourth vapor exposure, mice were given a 72-h abstinence/withdrawal period before resuming ethanol intake in the home cage for 5 days. Mice in the AIR control treatment group were similarly treated but exposed only to air in the inhalation chambers. This pattern of CIE or air control exposure followed by 5 days of ethanol self-administration was repeated for four cycles. A fifth cycle of CIE (or air) exposure followed the fourth ethanol intake evaluation period, and brain tissue was collected at multiple time points (8h, 3d, 7d, 14d) after the last cycle ended. Pyrazole (1 mmol/kg) was used to stabilize blood ethanol levels (BEC) and was administered to both CIE and AIR groups. A subset of mice received no pyrazole.
+
+
+
+Analysis:
+
+1. Normalization on Affymetrix Expression Console (SST-RMA Gene Level).
+
+2. Batch effect detected (RNA concentration dependent) and corrected in ComBat
diff --git a/general/datasets/Inia_uthsc_mid_affymta1_ex_may17/cases.rtf b/general/datasets/Inia_uthsc_mid_affymta1_ex_may17/cases.rtf
new file mode 100644
index 0000000..976f0ab
--- /dev/null
+++ b/general/datasets/Inia_uthsc_mid_affymta1_ex_may17/cases.rtf
@@ -0,0 +1,857 @@
+
+
+
+
+
+
+
+
+
+
+
+ | MicroarrayID |
+ Mouse.ID |
+ Strain |
+ Pyrazole |
+ TimePoint |
+ Treatment |
+ PCA Batch |
+ DissectionBatch |
+ ExtractionBatch |
+ Concentration |
+ RIN |
+
+
+ | MB1 |
+ 12 |
+ C57BL/6J |
+ PZ |
+ 8h |
+ CIE |
+ B |
+ A |
+ 1 |
+ 224.611 |
+ 9.0 |
+
+
+ | MB2 |
+ 50 |
+ DBA/2J |
+ NO |
+ 3d |
+ AIR |
+ B |
+ A |
+ 1 |
+ 195.150 |
+ 9.2 |
+
+
+ | MB3 |
+ 2 |
+ C57BL/6J |
+ PZ |
+ 14d |
+ AIR |
+ B |
+ A |
+ 1 |
+ 299.415 |
+ 9.5 |
+
+
+ | MB4 |
+ 60 |
+ DBA/2J |
+ PZ |
+ 7d |
+ AIR |
+ B |
+ A |
+ 1 |
+ 300.033 |
+ 7.6 |
+
+
+ | MB5 |
+ 4 |
+ C57BL/6J |
+ PZ |
+ 14d |
+ CIE |
+ A |
+ A |
+ 1 |
+ 249.226 |
+ 7.2 |
+
+
+ | MB6 |
+ 69 |
+ DBA/2J |
+ PZ |
+ 7d |
+ AIR |
+ A |
+ A |
+ 1 |
+ 161.526 |
+ 7.3 |
+
+
+ | MB7 |
+ 8 |
+ C57BL/6J |
+ PZ |
+ 3d |
+ CIE |
+ B |
+ A |
+ 1 |
+ 326.862 |
+ 9.5 |
+
+
+ | MB8 |
+ 41 |
+ DBA/2J |
+ PZ |
+ 8h |
+ AIR |
+ B |
+ A |
+ 1 |
+ 352.559 |
+ 7.9 |
+
+
+ | MB9 |
+ 75 |
+ DBA/2J |
+ PZ |
+ 14d |
+ AIR |
+ B |
+ B |
+ 1 |
+ 354.218 |
+ 8.8 |
+
+
+ | MB10 |
+ 23 |
+ C57BL/6J |
+ PZ |
+ 3d |
+ AIR |
+ B |
+ B |
+ 1 |
+ 280.396 |
+ 9.6 |
+
+
+ | MB11 |
+ 49 |
+ DBA/2J |
+ PZ |
+ 3d |
+ AIR |
+ A |
+ B |
+ 1 |
+ 180.312 |
+ 7.2 |
+
+
+ | MB12 |
+ 58 |
+ DBA/2J |
+ PZ |
+ 3d |
+ CIE |
+ B |
+ B |
+ 1 |
+ 225.072 |
+ NA |
+
+
+ | MB13 |
+ 21 |
+ C57BL/6J |
+ PZ |
+ 14d |
+ CIE |
+ B |
+ C |
+ 1 |
+ 299.623 |
+ 7.4 |
+
+
+ | MB14 |
+ 63 |
+ DBA/2J |
+ PZ |
+ 3d |
+ CIE |
+ B |
+ C |
+ 1 |
+ 70.977 |
+ 7.5 |
+
+
+ | MB15 |
+ 46 |
+ DBA/2J |
+ PZ |
+ 8h |
+ AIR |
+ B |
+ C |
+ 1 |
+ 284.115 |
+ 7.9 |
+
+
+ | MB16 |
+ 45 |
+ DBA/2J |
+ PZ |
+ 8h |
+ AIR |
+ B |
+ C |
+ 1 |
+ 338.791 |
+ 7.7 |
+
+
+ | MB17 |
+ 28 |
+ C57BL/6J |
+ NO |
+ 3d |
+ AIR |
+ B |
+ C |
+ 1 |
+ 449.851 |
+ 7.8 |
+
+
+ | MB18 |
+ 78 |
+ DBA/2J |
+ PZ |
+ 14d |
+ AIR |
+ B |
+ C |
+ 1 |
+ 320.081 |
+ 7.9 |
+
+
+ | MB19 |
+ 77 |
+ DBA/2J |
+ PZ |
+ 14d |
+ CIE |
+ B |
+ C |
+ 1 |
+ 234.795 |
+ 7.8 |
+
+
+ | MB20 |
+ 71 |
+ DBA/2J |
+ PZ |
+ 7d |
+ CIE |
+ B |
+ C |
+ 1 |
+ 468.728 |
+ 7.8 |
+
+
+ | MB21 |
+ 68 |
+ DBA/2J |
+ PZ |
+ 7d |
+ AIR |
+ B |
+ C |
+ 1 |
+ 296.386 |
+ 7.9 |
+
+
+ | MB22 |
+ 29 |
+ C57BL/6J |
+ PZ |
+ 8h |
+ CIE |
+ B |
+ C |
+ 1 |
+ 398.481 |
+ 8.0 |
+
+
+ | MB23 |
+ 67 |
+ DBA/2J |
+ PZ |
+ 7d |
+ CIE |
+ B |
+ A |
+ 2 |
+ 275.813 |
+ 7.8 |
+
+
+ | MB24 |
+ 1 |
+ C57BL/6J |
+ PZ |
+ 8h |
+ AIR |
+ A |
+ A |
+ 2 |
+ 132.589 |
+ 6.8 |
+
+
+ | MB25 |
+ 14 |
+ C57BL/6J |
+ NO |
+ 3d |
+ CIE |
+ A |
+ A |
+ 2 |
+ 189.666 |
+ 7.9 |
+
+
+ | MB26 |
+ 42 |
+ DBA/2J |
+ PZ |
+ 8h |
+ CIE |
+ B |
+ A |
+ 2 |
+ 310.878 |
+ 9.4 |
+
+
+ | MB27 |
+ 55 |
+ DBA/2J |
+ PZ |
+ 3d |
+ CIE |
+ B |
+ A |
+ 2 |
+ 211.576 |
+ 9.0 |
+
+
+ | MB28 |
+ 73 |
+ DBA/2J |
+ PZ |
+ 7d |
+ CIE |
+ B |
+ A |
+ 2 |
+ 287.696 |
+ 7.6 |
+
+
+ | MB29 |
+ 48 |
+ DBA/2J |
+ PZ |
+ 3d |
+ AIR |
+ B |
+ A |
+ 2 |
+ 317.532 |
+ 7.8 |
+
+
+ | MB30 |
+ 61 |
+ DBA/2J |
+ PZ |
+ 7d |
+ AIR |
+ B |
+ B |
+ 2 |
+ 294.808 |
+ 7.8 |
+
+
+ | MB31 |
+ 20 |
+ C57BL/6J |
+ PZ |
+ 8h |
+ CIE |
+ B |
+ B |
+ 2 |
+ 209.301 |
+ 9.0 |
+
+
+ | MB32 |
+ 76 |
+ DBA/2J |
+ PZ |
+ 14d |
+ CIE |
+ A |
+ B |
+ 2 |
+ 120.953 |
+ 8.2 |
+
+
+ | MB33 |
+ 5 |
+ C57BL/6J |
+ PZ |
+ 14d |
+ AIR |
+ B |
+ B |
+ 2 |
+ 271.808 |
+ 8.8 |
+
+
+ | MB34 |
+ 37 |
+ C57BL/6J |
+ PZ |
+ 7d |
+ CIE |
+ B |
+ B |
+ 2 |
+ 289.261 |
+ 8.0 |
+
+
+ | MB35 |
+ 19 |
+ C57BL/6J |
+ PZ |
+ 3d |
+ CIE |
+ B |
+ C |
+ 2 |
+ 306.294 |
+ 9.1 |
+
+
+ | MB36 |
+ 56 |
+ DBA/2J |
+ PZ |
+ 3d |
+ AIR |
+ B |
+ C |
+ 2 |
+ 265.964 |
+ 7.8 |
+
+
+ | MB37 |
+ 65 |
+ DBA/2J |
+ NO |
+ 3d |
+ CIE |
+ B |
+ C |
+ 2 |
+ 259.741 |
+ 9.2 |
+
+
+ | MB38 |
+ 80 |
+ DBA/2J |
+ PZ |
+ 14d |
+ AIR |
+ B |
+ C |
+ 2 |
+ 371.000 |
+ 8.0 |
+
+
+ | MB39 |
+ 31 |
+ C57BL/6J |
+ PZ |
+ 14d |
+ CIE |
+ B |
+ C |
+ 2 |
+ 349.451 |
+ 7.7 |
+
+
+ | MB40 |
+ 39 |
+ C57BL/6J |
+ PZ |
+ 7d |
+ AIR |
+ C |
+ C |
+ 2 |
+ 403.083 |
+ 8.9 |
+
+
+ | MB41 |
+ 62 |
+ DBA/2J |
+ PZ |
+ 3d |
+ CIE |
+ C |
+ C |
+ 2 |
+ 505.547 |
+ 8.9 |
+
+
+ | MB42 |
+ 52 |
+ DBA/2J |
+ PZ |
+ 8h |
+ CIE |
+ C |
+ C |
+ 2 |
+ 441.549 |
+ 8.8 |
+
+
+ | MB43 |
+ 51 |
+ DBA/2J |
+ PZ |
+ 3d |
+ AIR |
+ C |
+ C |
+ 2 |
+ 519.427 |
+ 8.8 |
+
+
+ | MB44 |
+ 35 |
+ C57BL/6J |
+ NO |
+ 3d |
+ AIR |
+ C |
+ A |
+ 3 |
+ 772.361 |
+ 8.8 |
+
+
+ | MB45 |
+ 72 |
+ DBA/2J |
+ PZ |
+ 14d |
+ AIR |
+ C |
+ A |
+ 3 |
+ 598.185 |
+ 8.9 |
+
+
+ | MB46 |
+ 32 |
+ C57BL/6J |
+ PZ |
+ 7d |
+ CIE |
+ C |
+ A |
+ 3 |
+ 824.974 |
+ 8.7 |
+
+
+ | MB47 |
+ 74 |
+ DBA/2J |
+ PZ |
+ 14d |
+ CIE |
+ C |
+ A |
+ 3 |
+ 495.046 |
+ 9.4 |
+
+
+ | MB48 |
+ 54 |
+ DBA/2J |
+ PZ |
+ 8h |
+ CIE |
+ C |
+ A |
+ 3 |
+ 667.036 |
+ 9.4 |
+
+
+ | MB49 |
+ 24 |
+ C57BL/6J |
+ PZ |
+ 7d |
+ AIR |
+ C |
+ A |
+ 3 |
+ 760.367 |
+ 9.2 |
+
+
+ | MB50 |
+ 9 |
+ C57BL/6J |
+ PZ |
+ 3d |
+ AIR |
+ C |
+ A |
+ 3 |
+ 701.152 |
+ 9.2 |
+
+
+ | MB51 |
+ 66 |
+ DBA/2J |
+ NO |
+ 3d |
+ CIE |
+ C |
+ B |
+ 3 |
+ 579.22 |
+ 8.3 |
+
+
+ | MB52 |
+ 44 |
+ DBA/2J |
+ PZ |
+ 8h |
+ CIE |
+ C |
+ B |
+ 3 |
+ 636.091 |
+ 9.4 |
+
+
+ | MB53 |
+ 34 |
+ C57BL/6J |
+ PZ |
+ 7d |
+ AIR |
+ C |
+ B |
+ 3 |
+ 739.127 |
+ 9.5 |
+
+
+ | MB54 |
+ 7 |
+ C57BL/6J |
+ PZ |
+ 8h |
+ AIR |
+ C |
+ B |
+ 3 |
+ 667.933 |
+ 9.2 |
+
+
+ | MB55 |
+ 36 |
+ C57BL/6J |
+ NO |
+ 3d |
+ CIE |
+ C |
+ C |
+ 3 |
+ 605.937 |
+ 9.2 |
+
+
+ | MB56 |
+ 43 |
+ DBA/2J |
+ PZ |
+ 8h |
+ AIR |
+ C |
+ C |
+ 3 |
+ 639.161 |
+ 9.5 |
+
+
+ | MB57 |
+ 70 |
+ DBA/2J |
+ PZ |
+ 7d |
+ CIE |
+ C |
+ C |
+ 3 |
+ 630.735 |
+ 9.4 |
+
+
+ | MB58 |
+ 59 |
+ DBA/2J |
+ NO |
+ 3d |
+ AIR |
+ C |
+ C |
+ 3 |
+ 548.647 |
+ 9.5 |
+
+
+ | MB59 |
+ 15 |
+ C57BL/6J |
+ PZ |
+ 14d |
+ AIR |
+ C |
+ C |
+ 3 |
+ 689.793 |
+ 9.4 |
+
+
+ | MB60 |
+ 27 |
+ C57BL/6J |
+ PZ |
+ 8h |
+ AIR |
+ C |
+ C |
+ 3 |
+ 580.462 |
+ 9.4 |
+
+
+ | MB61 |
+ 30 |
+ C57BL/6J |
+ PZ |
+ 3d |
+ AIR |
+ C |
+ C |
+ 3 |
+ 577.826 |
+ 8.2 |
+
+
+ | MB62 |
+ 57 |
+ DBA/2J |
+ PZ |
+ 3d |
+ AIR |
+ C |
+ C |
+ 3 |
+ 581.164 |
+ 9.0 |
+
+
+ | MB63 |
+ 38 |
+ C57BL/6J |
+ PZ |
+ 3d |
+ CIE |
+ C |
+ C |
+ 3 |
+ 748.421 |
+ 8.6 |
+
+
+ | MB64 |
+ 47 |
+ DBA/2J |
+ PZ |
+ 8h |
+ AIR |
+ C |
+ C |
+ 3 |
+ 747.345 |
+ 8.5 |
+
+
+
diff --git a/general/datasets/Inia_uthsc_mid_affymta1_ex_may17/specifics.rtf b/general/datasets/Inia_uthsc_mid_affymta1_ex_may17/specifics.rtf
new file mode 100644
index 0000000..7c1a914
--- /dev/null
+++ b/general/datasets/Inia_uthsc_mid_affymta1_ex_may17/specifics.rtf
@@ -0,0 +1 @@
+Exon Level
\ No newline at end of file
diff --git a/general/datasets/Inia_uthsc_mid_affymta1_ex_may17/summary.rtf b/general/datasets/Inia_uthsc_mid_affymta1_ex_may17/summary.rtf
new file mode 100644
index 0000000..9baa040
--- /dev/null
+++ b/general/datasets/Inia_uthsc_mid_affymta1_ex_may17/summary.rtf
@@ -0,0 +1,31 @@
+Overview:
+
+1. Treated and whole brains dissected at Medical University of South Carolina (Marcelo F. Lopez laboratory)
+
+2. Frozen brains sub-dissected at UTHSC (Megan K. Mulligan laboratory)
+
+3. RNA extraction (Qiagen RNeasy kit) at UTHSC (Mulligan and Williams laboratories)
+
+4. Hybridized to Affymetrix Clariom D (aka Affymetrix MTA 1.0 ST) array at UTHSC MRC (Lorne Rose, UTHSC Molecular Resource Center)
+
+5. Initial QC and normalization (COMBAT) at UTHSC (Megan K. Mulligan laboratory)
+
+6. Transcriptome entry and phenotype entry (Arthur Centeno, Megan K. Mulligan, and Robert W. Williams)
+
+
+
+Chronic ethanol exposure:
+
+Mice were allowed to self-administer alcohol (15% v/v vs. water) for 2 h a day (5 days a week) 6 weeks prior to treatment in order to establish baseline consumption. Access to 15% alcohol versus water started 30 min prior to the start of the dark cycle. Following establishment of baseline drinking, male mice representative of each strain were separated into groups to be exposed to either weekly cycles of CIE exposure (CIE group) or air control (AIR group) exposure.
+
+
+
+Mice assigned to the CIE treatment group were exposed to alcohol vapor for 16 h a day followed by 8 h of withdrawal for 4 days per week. Following the fourth vapor exposure, mice were given a 72-h abstinence/withdrawal period before resuming ethanol intake in the home cage for 5 days. Mice in the AIR control treatment group were similarly treated but exposed only to air in the inhalation chambers. This pattern of CIE or air control exposure followed by 5 days of ethanol self-administration was repeated for four cycles. A fifth cycle of CIE (or air) exposure followed the fourth ethanol intake evaluation period, and brain tissue was collected at multiple time points (8h, 3d, 7d, 14d) after the last cycle ended. Pyrazole (1 mmol/kg) was used to stabilize blood ethanol levels (BEC) and was administered to both CIE and AIR groups. A subset of mice received no pyrazole.
+
+
+
+Analysis:
+
+1. Normalization on Affymetrix Expression Console (SST-RMA Gene Level).
+
+2. Batch effect detected (RNA concentration dependent) and corrected in ComBat
diff --git a/general/datasets/Inia_uthsc_pfc_affymta1_may17/summary.rtf b/general/datasets/Inia_uthsc_pfc_affymta1_may17/summary.rtf
new file mode 100644
index 0000000..153d98d
--- /dev/null
+++ b/general/datasets/Inia_uthsc_pfc_affymta1_may17/summary.rtf
@@ -0,0 +1 @@
+In working progress...
diff --git a/general/datasets/Inia_uthsc_str_affymta1_may17/summary.rtf b/general/datasets/Inia_uthsc_str_affymta1_may17/summary.rtf
new file mode 100644
index 0000000..153d98d
--- /dev/null
+++ b/general/datasets/Inia_uthsc_str_affymta1_may17/summary.rtf
@@ -0,0 +1 @@
+In working progress...
diff --git a/general/datasets/Iop_spl_rma_0509/notes.rtf b/general/datasets/Iop_spl_rma_0509/notes.rtf
new file mode 100644
index 0000000..b75c94f
--- /dev/null
+++ b/general/datasets/Iop_spl_rma_0509/notes.rtf
@@ -0,0 +1 @@
+Spleen mRNA expression levels are measured for 77 individual BXD RI mice from 24 different strains. The expressed gene set were characterised using the Affymetrix Mouse430_2.0 GeneChip which encompass over 34,000 known genes.
diff --git a/general/datasets/Iop_spl_rma_0509/summary.rtf b/general/datasets/Iop_spl_rma_0509/summary.rtf
new file mode 100644
index 0000000..53231ef
--- /dev/null
+++ b/general/datasets/Iop_spl_rma_0509/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 74, Name: IoP Affy MOE 430v2 Spleen (May09)
diff --git a/general/datasets/Ircm_axbxa_hri0213/summary.rtf b/general/datasets/Ircm_axbxa_hri0213/summary.rtf
new file mode 100644
index 0000000..ce6cd68
--- /dev/null
+++ b/general/datasets/Ircm_axbxa_hri0213/summary.rtf
@@ -0,0 +1 @@
+Expression data from hearts from 24 different AxB/BxA. Also the data are normalized and log2 transformed. All mice are males and 12 weeks.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/acknowledgment.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/acknowledgment.rtf
deleted file mode 100644
index 5ab8fd8..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This manuscript is dedicated to the memory of Pavlina Petkova, a wonderful scientist, colleague, and wonderful friend. We thank members of the Baker, Paigen, Petkov, and Carter laboratories for their discussion of the data and manuscript. This work was assisted by The Jackson Laboratory scientific services, which are supported through National Institutes of Health Cancer Core grant CA34196. BXD ESC lines were kindly provided by Anne Czechanski and Laura Reinholdt, funded by the Special Mouse Strain Resource OD011102-18. Funding for the work was provided by NIGMS F32-GM101736 and The Jackson Laboratory start-up funds supporting C.L.B., and P01-GM099640 to K.P. and G.W.C.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/cases.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/cases.rtf
deleted file mode 100644
index 5922df0..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-C57BL/6J (stock number 000664), DBA/2J (stock number 000671), B6D2 F1/J hybrid (stock number 100006), and all BXD RI mice were obtained from The Jackson Laboratory (Bar Harbor, ME). All animal experiments were approved by the Animal Care and Use Committee of The Jackson Laboratory (summary #04008 and #16043).
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/processing.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/processing.rtf
deleted file mode 100644
index d359653..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-All sequenced B6, D2, F1, and BXD H3K4me3 ChIP libraries, as well as all control input DNA samples were aligned utilizing bwa version 0.7.9a (Li and Durbin 2009). B6 parental samples were aligned to the Genome Reference Consortium Mouse Build 38 (mm10) and D2 parental samples were aligned to the de novo REL-1509 assembly, including all unplaced scaffolds, from the Mouse Genomes Project (Yalcin et al.2012).
-
-To ensure that H3K4me3 peaks were properly quantified across divergent genomes, we began by building a comprehensive “peakome” representing all potential H3K4me3 peaks found in the two parents. H3K4me3 peaks for B6 and D2 were called independently, utilizing alignment data from three replicate samples and one DNA input sample. Reads were filtered for a mapq alignment metric of 60 and an alignment sequence having no indels present across the entire length of the sequencing read, typically 100 bp H3K4me3 peaks were called utilizing MACS version 1.4.2 (Zhang et al. 2008) and peaks having a false discovery rate (FDR) of <1% found in two out of three replicates were accepted. Final genomic intervals for each H3K4me3 peak for each strain were derived by merging the peaks from the corresponding replicate samples using bedtools (Quinlan and Hall 2010). To link syntenic regions between B6 and D2 assemblies, which each have their own coordinate system, sequences from these genomic intervals were aligned to their alternative genome using reciprocal BLAST. In some cases, a sequence interval comprising an H3K4me3 peak in one strain aligned to multiple adjacent intervals in the alternative genome. If the sequences of these peaks in the alternate strain all fell within the boundaries of the single peak, they were merged. The boundaries of these merged peaks included the incorporated sequences from both strains. Because there are also H3K4me3 peaks that are strain specific, these peaks were accepted if, and only if, the mapped interval had a unique sequence that was found in the proper syntentic order within the alternative genome lacking that H3K4me3 peak. The final combined peakome between B6 and D2 mice was created by selecting only peaks appropriately linked across each strain, assuring that each H3K4me3 peak reciprocally aligned to only one peak in the alternative genome after merging, and that all peaks were in the same order along the chromosomes in both genomes (Supplemental Material, Table S2). Using the H3K4me3 peaks locations derived from the parental strains, final read counts for B6, D2, F1 hybrids, and BXDs were obtained by counting reads within the coordinate boundaries of the peakome intervals.
-
-To improve mapping accuracy and utilize known sequence variation between strains, all BXDs and F1hybrid samples were aligned separately to both the mm10 reference and the de novo D2 assembly. To reduce error in quantification of H3K4me3 levels due to genomic regions containing repetitive sequences, we removed reads with multiple alignments and retained reads with alignment metric of 60 that lacked small indels, which can often indicate misalignment. Subsequently, for each genomic interval in the peakome, final reads counts were summed for those that mapped uniquely to one of the assemblies along with those that mapped equally well to both B6 and D2 genome assemblies.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/specifics.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/specifics.rtf
deleted file mode 100644
index 7c4621d..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data has all of the normalization steps already applied. Normalized read counts. Essentially we used a method out of the R package edgeR to normalize for both read depth and composition, followed by log2 transformation, and then subtraction of PCA1.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/summary.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/summary.rtf
deleted file mode 100644
index 97965d8..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6404261/
-
-The epigenetic landscape varies greatly among cell types. Although a variety of writers, readers, and erasers of epigenetic features are known, we have little information about the underlying regulatory systems controlling the establishment and maintenance of these features. Here, we have explored how natural genetic variation affects the epigenome in mice. Studying levels of H3K4me3, a histone modification at sites such as promoters, enhancers, and recombination hotspots, we found tissue-specific trans-regulation of H3K4me3 levels in four highly diverse cell types: male germ cells, embryonic stem cells, hepatocytes, and cardiomyocytes. To identify the genetic loci involved, we measured H3K4me3 levels in male germ cells in a mapping population of 59 BXD recombinant inbred lines. We found extensive trans-regulation of H3K4me3 peaks, including six major histone quantitative trait loci (QTL). These chromatin regulatory loci act dominantly to suppress H3K4me3, which at hotspots reduces the likelihood of subsequent DNA double-strand breaks. QTL locations do not correspond with genes encoding enzymes known to metabolize chromatin features. Instead their locations match clusters of zinc finger genes, making these possible candidates that explain the dominant suppression of H3K4me3. Collectively, these data describe an extensive, set of chromatin regulatory loci that control the epigenetic landscape.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/tissue.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/tissue.rtf
deleted file mode 100644
index 65281a9..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_0820/tissue.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-Testicular germ cell enrichment was performed on 14-day postpartum male mice as previously reported (Baker et al. 2014). This cell preparation removes somatic Sertoli and Leydig cells and results in >90% enrichment of germ cells, of which nearly 50% are spermatogonia (Ball et al. 2016).
-
-Individual low-passage mouse ESCs were derived using protocols outlined in Czechanski et al. (2014). Briefly, 6- to 8-week-old females are mated to stud males and checked each morning for plugs. Pregnant females are euthanized on embryonic day 3.5 and the uterine horn is flushed to remove embryos. Embryos are visualized under a dissecting microscope and blastocysts are transferred to 2i (2i:CHIR99021 and PD0325901) (Ying et al. 2008) serum-free media for outgrowth of the inner cell mass. Blastocysts are allowed to hatch and attach to a mouse embryonic fibroblast (MEF) feeder layer, and the resulting outgrowth is monitored daily and fed for 8–11 days. The emergent ESCs are disaggregated and passaged onto new MEF feeders. Cultures during this time are closely monitored for unusually rapid growth (potentially indicating karyotypic instability), signs of deterioration including vacuolated cytoplasm, detachment of cells from colonies and debris, and possible signs of contamination. Successful ESC cultures were maintained on MEF feeders in serum containing 2i media supplemented with Leukemia inhibiting factor (2i/LIF) (Kiyonari et al. 2010) to maintain high levels of NANOG expression, which indicates ground-state pluripotency (Ying et al. 2008; Czechanski et al. 2014). Prior to preparing for chromatin isolation, mouse ESCs were enzymatically disassociated using trypsin and MEFs were removed by serial plating on gelatin-coated plates to which MEFs adsorb preferentially; for this, ESCs and MEFs are incubated in 2i/LIF media on fresh plates for 15 min to allow the larger MEFs to quickly attach to the plates. ESCs are aspirated and the plating procedure repeated once to further remove MEFs. ESCs were collected by centrifugation, resuspended in PBS, and cross-linked using formaldehyde.
-
-For hepatocyte isolation and purification, livers from 8-week-old female mice were perfused using a modified EGTA–collagenase perfusion protocol (Neufeld 1997). All perfusions and hepatocyte purifications were done at the same time of the day to avoid possible circadian effects on any studied parameter. EGTA buffer was used to flush the blood out of the liver and start to digest the desmosomes connecting the liver cells. After 35 ml of the 1× EGTA solution was passed through the liver, it was replaced with 7–10 ml of 1× Leffert’s buffer to flush out the EGTA, which otherwise chelates the calcium ions necessary for collagenase activity in the next step when the liver is digested by perfusion with 25–50 ml of Liberase solution (∼4.3 Wünsch units). After perfusion, the liver was removed from the abdominal cavity and passed through Nitex 80-μm nylon mesh, using extra ice-cold Leffert’s buffer with 0.02% CaCl2and a rubber policeman. Hepatocytes were purified from the remaining cells by two consecutive centrifugations for 4 min, 50 × g each, leaving the other, smaller cell types in suspension. After each spin, the solution was decanted as waste, and the enriched cell pellet of hepatocytes was resuspended in 30 ml ice-cold Leffert’s buffer with 0.02% CaCl2. After the second centrifugation, the cell pellet contained >98.6% hepatocytes.
-
-For cardiomyocyte isolation 8-week-old female mice were euthanized and the chest opened to expose the heart. The descending aorta and inferior vena cava were cut and an EDTA buffer was injected into the apex of the right ventricle to flush the heart. The ascending aorta was clamped and the heart transferred to a petri dish and fixed by perfusion of EDTA buffer containing 4% formaldehyde via the left ventricle. The formaldehyde was quenched by perfusing the heart with 125 mM glycine, and digested by perfusion with collagenase buffer. The ventricles were rent into smaller pieces, and triturated to complete cellular dissociation into a single-cell suspension. Cells were then filtered through a 100-μm strainer to remove tissue fragments and centrifuged at a very low speed to obtain a highly enriched fraction of fixed cardiomyocytes.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/acknowledgment.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/acknowledgment.rtf
deleted file mode 100644
index 5ab8fd8..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This manuscript is dedicated to the memory of Pavlina Petkova, a wonderful scientist, colleague, and wonderful friend. We thank members of the Baker, Paigen, Petkov, and Carter laboratories for their discussion of the data and manuscript. This work was assisted by The Jackson Laboratory scientific services, which are supported through National Institutes of Health Cancer Core grant CA34196. BXD ESC lines were kindly provided by Anne Czechanski and Laura Reinholdt, funded by the Special Mouse Strain Resource OD011102-18. Funding for the work was provided by NIGMS F32-GM101736 and The Jackson Laboratory start-up funds supporting C.L.B., and P01-GM099640 to K.P. and G.W.C.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/cases.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/cases.rtf
deleted file mode 100644
index 5922df0..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-C57BL/6J (stock number 000664), DBA/2J (stock number 000671), B6D2 F1/J hybrid (stock number 100006), and all BXD RI mice were obtained from The Jackson Laboratory (Bar Harbor, ME). All animal experiments were approved by the Animal Care and Use Committee of The Jackson Laboratory (summary #04008 and #16043).
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/processing.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/processing.rtf
deleted file mode 100644
index d359653..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-All sequenced B6, D2, F1, and BXD H3K4me3 ChIP libraries, as well as all control input DNA samples were aligned utilizing bwa version 0.7.9a (Li and Durbin 2009). B6 parental samples were aligned to the Genome Reference Consortium Mouse Build 38 (mm10) and D2 parental samples were aligned to the de novo REL-1509 assembly, including all unplaced scaffolds, from the Mouse Genomes Project (Yalcin et al.2012).
-
-To ensure that H3K4me3 peaks were properly quantified across divergent genomes, we began by building a comprehensive “peakome” representing all potential H3K4me3 peaks found in the two parents. H3K4me3 peaks for B6 and D2 were called independently, utilizing alignment data from three replicate samples and one DNA input sample. Reads were filtered for a mapq alignment metric of 60 and an alignment sequence having no indels present across the entire length of the sequencing read, typically 100 bp H3K4me3 peaks were called utilizing MACS version 1.4.2 (Zhang et al. 2008) and peaks having a false discovery rate (FDR) of <1% found in two out of three replicates were accepted. Final genomic intervals for each H3K4me3 peak for each strain were derived by merging the peaks from the corresponding replicate samples using bedtools (Quinlan and Hall 2010). To link syntenic regions between B6 and D2 assemblies, which each have their own coordinate system, sequences from these genomic intervals were aligned to their alternative genome using reciprocal BLAST. In some cases, a sequence interval comprising an H3K4me3 peak in one strain aligned to multiple adjacent intervals in the alternative genome. If the sequences of these peaks in the alternate strain all fell within the boundaries of the single peak, they were merged. The boundaries of these merged peaks included the incorporated sequences from both strains. Because there are also H3K4me3 peaks that are strain specific, these peaks were accepted if, and only if, the mapped interval had a unique sequence that was found in the proper syntentic order within the alternative genome lacking that H3K4me3 peak. The final combined peakome between B6 and D2 mice was created by selecting only peaks appropriately linked across each strain, assuring that each H3K4me3 peak reciprocally aligned to only one peak in the alternative genome after merging, and that all peaks were in the same order along the chromosomes in both genomes (Supplemental Material, Table S2). Using the H3K4me3 peaks locations derived from the parental strains, final read counts for B6, D2, F1 hybrids, and BXDs were obtained by counting reads within the coordinate boundaries of the peakome intervals.
-
-To improve mapping accuracy and utilize known sequence variation between strains, all BXDs and F1hybrid samples were aligned separately to both the mm10 reference and the de novo D2 assembly. To reduce error in quantification of H3K4me3 levels due to genomic regions containing repetitive sequences, we removed reads with multiple alignments and retained reads with alignment metric of 60 that lacked small indels, which can often indicate misalignment. Subsequently, for each genomic interval in the peakome, final reads counts were summed for those that mapped uniquely to one of the assemblies along with those that mapped equally well to both B6 and D2 genome assemblies.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/specifics.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/specifics.rtf
deleted file mode 100644
index bbaabc0..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-log2 transformed
\ No newline at end of file
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/summary.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/summary.rtf
deleted file mode 100644
index 97965d8..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6404261/
-
-The epigenetic landscape varies greatly among cell types. Although a variety of writers, readers, and erasers of epigenetic features are known, we have little information about the underlying regulatory systems controlling the establishment and maintenance of these features. Here, we have explored how natural genetic variation affects the epigenome in mice. Studying levels of H3K4me3, a histone modification at sites such as promoters, enhancers, and recombination hotspots, we found tissue-specific trans-regulation of H3K4me3 levels in four highly diverse cell types: male germ cells, embryonic stem cells, hepatocytes, and cardiomyocytes. To identify the genetic loci involved, we measured H3K4me3 levels in male germ cells in a mapping population of 59 BXD recombinant inbred lines. We found extensive trans-regulation of H3K4me3 peaks, including six major histone quantitative trait loci (QTL). These chromatin regulatory loci act dominantly to suppress H3K4me3, which at hotspots reduces the likelihood of subsequent DNA double-strand breaks. QTL locations do not correspond with genes encoding enzymes known to metabolize chromatin features. Instead their locations match clusters of zinc finger genes, making these possible candidates that explain the dominant suppression of H3K4me3. Collectively, these data describe an extensive, set of chromatin regulatory loci that control the epigenetic landscape.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/tissue.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/tissue.rtf
deleted file mode 100644
index 65281a9..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2_0820/tissue.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-Testicular germ cell enrichment was performed on 14-day postpartum male mice as previously reported (Baker et al. 2014). This cell preparation removes somatic Sertoli and Leydig cells and results in >90% enrichment of germ cells, of which nearly 50% are spermatogonia (Ball et al. 2016).
-
-Individual low-passage mouse ESCs were derived using protocols outlined in Czechanski et al. (2014). Briefly, 6- to 8-week-old females are mated to stud males and checked each morning for plugs. Pregnant females are euthanized on embryonic day 3.5 and the uterine horn is flushed to remove embryos. Embryos are visualized under a dissecting microscope and blastocysts are transferred to 2i (2i:CHIR99021 and PD0325901) (Ying et al. 2008) serum-free media for outgrowth of the inner cell mass. Blastocysts are allowed to hatch and attach to a mouse embryonic fibroblast (MEF) feeder layer, and the resulting outgrowth is monitored daily and fed for 8–11 days. The emergent ESCs are disaggregated and passaged onto new MEF feeders. Cultures during this time are closely monitored for unusually rapid growth (potentially indicating karyotypic instability), signs of deterioration including vacuolated cytoplasm, detachment of cells from colonies and debris, and possible signs of contamination. Successful ESC cultures were maintained on MEF feeders in serum containing 2i media supplemented with Leukemia inhibiting factor (2i/LIF) (Kiyonari et al. 2010) to maintain high levels of NANOG expression, which indicates ground-state pluripotency (Ying et al. 2008; Czechanski et al. 2014). Prior to preparing for chromatin isolation, mouse ESCs were enzymatically disassociated using trypsin and MEFs were removed by serial plating on gelatin-coated plates to which MEFs adsorb preferentially; for this, ESCs and MEFs are incubated in 2i/LIF media on fresh plates for 15 min to allow the larger MEFs to quickly attach to the plates. ESCs are aspirated and the plating procedure repeated once to further remove MEFs. ESCs were collected by centrifugation, resuspended in PBS, and cross-linked using formaldehyde.
-
-For hepatocyte isolation and purification, livers from 8-week-old female mice were perfused using a modified EGTA–collagenase perfusion protocol (Neufeld 1997). All perfusions and hepatocyte purifications were done at the same time of the day to avoid possible circadian effects on any studied parameter. EGTA buffer was used to flush the blood out of the liver and start to digest the desmosomes connecting the liver cells. After 35 ml of the 1× EGTA solution was passed through the liver, it was replaced with 7–10 ml of 1× Leffert’s buffer to flush out the EGTA, which otherwise chelates the calcium ions necessary for collagenase activity in the next step when the liver is digested by perfusion with 25–50 ml of Liberase solution (∼4.3 Wünsch units). After perfusion, the liver was removed from the abdominal cavity and passed through Nitex 80-μm nylon mesh, using extra ice-cold Leffert’s buffer with 0.02% CaCl2and a rubber policeman. Hepatocytes were purified from the remaining cells by two consecutive centrifugations for 4 min, 50 × g each, leaving the other, smaller cell types in suspension. After each spin, the solution was decanted as waste, and the enriched cell pellet of hepatocytes was resuspended in 30 ml ice-cold Leffert’s buffer with 0.02% CaCl2. After the second centrifugation, the cell pellet contained >98.6% hepatocytes.
-
-For cardiomyocyte isolation 8-week-old female mice were euthanized and the chest opened to expose the heart. The descending aorta and inferior vena cava were cut and an EDTA buffer was injected into the apex of the right ventricle to flush the heart. The ascending aorta was clamped and the heart transferred to a petri dish and fixed by perfusion of EDTA buffer containing 4% formaldehyde via the left ventricle. The formaldehyde was quenched by perfusing the heart with 125 mM glycine, and digested by perfusion with collagenase buffer. The ventricles were rent into smaller pieces, and triturated to complete cellular dissociation into a single-cell suspension. Cells were then filtered through a 100-μm strainer to remove tissue fragments and centrifuged at a very low speed to obtain a highly enriched fraction of fixed cardiomyocytes.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/acknowledgment.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/acknowledgment.rtf
deleted file mode 100644
index 5ab8fd8..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This manuscript is dedicated to the memory of Pavlina Petkova, a wonderful scientist, colleague, and wonderful friend. We thank members of the Baker, Paigen, Petkov, and Carter laboratories for their discussion of the data and manuscript. This work was assisted by The Jackson Laboratory scientific services, which are supported through National Institutes of Health Cancer Core grant CA34196. BXD ESC lines were kindly provided by Anne Czechanski and Laura Reinholdt, funded by the Special Mouse Strain Resource OD011102-18. Funding for the work was provided by NIGMS F32-GM101736 and The Jackson Laboratory start-up funds supporting C.L.B., and P01-GM099640 to K.P. and G.W.C.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/cases.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/cases.rtf
deleted file mode 100644
index 5922df0..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-C57BL/6J (stock number 000664), DBA/2J (stock number 000671), B6D2 F1/J hybrid (stock number 100006), and all BXD RI mice were obtained from The Jackson Laboratory (Bar Harbor, ME). All animal experiments were approved by the Animal Care and Use Committee of The Jackson Laboratory (summary #04008 and #16043).
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/processing.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/processing.rtf
deleted file mode 100644
index d359653..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-All sequenced B6, D2, F1, and BXD H3K4me3 ChIP libraries, as well as all control input DNA samples were aligned utilizing bwa version 0.7.9a (Li and Durbin 2009). B6 parental samples were aligned to the Genome Reference Consortium Mouse Build 38 (mm10) and D2 parental samples were aligned to the de novo REL-1509 assembly, including all unplaced scaffolds, from the Mouse Genomes Project (Yalcin et al.2012).
-
-To ensure that H3K4me3 peaks were properly quantified across divergent genomes, we began by building a comprehensive “peakome” representing all potential H3K4me3 peaks found in the two parents. H3K4me3 peaks for B6 and D2 were called independently, utilizing alignment data from three replicate samples and one DNA input sample. Reads were filtered for a mapq alignment metric of 60 and an alignment sequence having no indels present across the entire length of the sequencing read, typically 100 bp H3K4me3 peaks were called utilizing MACS version 1.4.2 (Zhang et al. 2008) and peaks having a false discovery rate (FDR) of <1% found in two out of three replicates were accepted. Final genomic intervals for each H3K4me3 peak for each strain were derived by merging the peaks from the corresponding replicate samples using bedtools (Quinlan and Hall 2010). To link syntenic regions between B6 and D2 assemblies, which each have their own coordinate system, sequences from these genomic intervals were aligned to their alternative genome using reciprocal BLAST. In some cases, a sequence interval comprising an H3K4me3 peak in one strain aligned to multiple adjacent intervals in the alternative genome. If the sequences of these peaks in the alternate strain all fell within the boundaries of the single peak, they were merged. The boundaries of these merged peaks included the incorporated sequences from both strains. Because there are also H3K4me3 peaks that are strain specific, these peaks were accepted if, and only if, the mapped interval had a unique sequence that was found in the proper syntentic order within the alternative genome lacking that H3K4me3 peak. The final combined peakome between B6 and D2 mice was created by selecting only peaks appropriately linked across each strain, assuring that each H3K4me3 peak reciprocally aligned to only one peak in the alternative genome after merging, and that all peaks were in the same order along the chromosomes in both genomes (Supplemental Material, Table S2). Using the H3K4me3 peaks locations derived from the parental strains, final read counts for B6, D2, F1 hybrids, and BXDs were obtained by counting reads within the coordinate boundaries of the peakome intervals.
-
-To improve mapping accuracy and utilize known sequence variation between strains, all BXDs and F1hybrid samples were aligned separately to both the mm10 reference and the de novo D2 assembly. To reduce error in quantification of H3K4me3 levels due to genomic regions containing repetitive sequences, we removed reads with multiple alignments and retained reads with alignment metric of 60 that lacked small indels, which can often indicate misalignment. Subsequently, for each genomic interval in the peakome, final reads counts were summed for those that mapped uniquely to one of the assemblies along with those that mapped equally well to both B6 and D2 genome assemblies.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/specifics.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/specifics.rtf
deleted file mode 100644
index ca16969..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-log2 z-score transformed
\ No newline at end of file
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/summary.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/summary.rtf
deleted file mode 100644
index 97965d8..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6404261/
-
-The epigenetic landscape varies greatly among cell types. Although a variety of writers, readers, and erasers of epigenetic features are known, we have little information about the underlying regulatory systems controlling the establishment and maintenance of these features. Here, we have explored how natural genetic variation affects the epigenome in mice. Studying levels of H3K4me3, a histone modification at sites such as promoters, enhancers, and recombination hotspots, we found tissue-specific trans-regulation of H3K4me3 levels in four highly diverse cell types: male germ cells, embryonic stem cells, hepatocytes, and cardiomyocytes. To identify the genetic loci involved, we measured H3K4me3 levels in male germ cells in a mapping population of 59 BXD recombinant inbred lines. We found extensive trans-regulation of H3K4me3 peaks, including six major histone quantitative trait loci (QTL). These chromatin regulatory loci act dominantly to suppress H3K4me3, which at hotspots reduces the likelihood of subsequent DNA double-strand breaks. QTL locations do not correspond with genes encoding enzymes known to metabolize chromatin features. Instead their locations match clusters of zinc finger genes, making these possible candidates that explain the dominant suppression of H3K4me3. Collectively, these data describe an extensive, set of chromatin regulatory loci that control the epigenetic landscape.
diff --git a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/tissue.rtf b/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/tissue.rtf
deleted file mode 100644
index 65281a9..0000000
--- a/general/datasets/JAX_BXD_Germ_Cells_edgeR_log2z_0820/tissue.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-Testicular germ cell enrichment was performed on 14-day postpartum male mice as previously reported (Baker et al. 2014). This cell preparation removes somatic Sertoli and Leydig cells and results in >90% enrichment of germ cells, of which nearly 50% are spermatogonia (Ball et al. 2016).
-
-Individual low-passage mouse ESCs were derived using protocols outlined in Czechanski et al. (2014). Briefly, 6- to 8-week-old females are mated to stud males and checked each morning for plugs. Pregnant females are euthanized on embryonic day 3.5 and the uterine horn is flushed to remove embryos. Embryos are visualized under a dissecting microscope and blastocysts are transferred to 2i (2i:CHIR99021 and PD0325901) (Ying et al. 2008) serum-free media for outgrowth of the inner cell mass. Blastocysts are allowed to hatch and attach to a mouse embryonic fibroblast (MEF) feeder layer, and the resulting outgrowth is monitored daily and fed for 8–11 days. The emergent ESCs are disaggregated and passaged onto new MEF feeders. Cultures during this time are closely monitored for unusually rapid growth (potentially indicating karyotypic instability), signs of deterioration including vacuolated cytoplasm, detachment of cells from colonies and debris, and possible signs of contamination. Successful ESC cultures were maintained on MEF feeders in serum containing 2i media supplemented with Leukemia inhibiting factor (2i/LIF) (Kiyonari et al. 2010) to maintain high levels of NANOG expression, which indicates ground-state pluripotency (Ying et al. 2008; Czechanski et al. 2014). Prior to preparing for chromatin isolation, mouse ESCs were enzymatically disassociated using trypsin and MEFs were removed by serial plating on gelatin-coated plates to which MEFs adsorb preferentially; for this, ESCs and MEFs are incubated in 2i/LIF media on fresh plates for 15 min to allow the larger MEFs to quickly attach to the plates. ESCs are aspirated and the plating procedure repeated once to further remove MEFs. ESCs were collected by centrifugation, resuspended in PBS, and cross-linked using formaldehyde.
-
-For hepatocyte isolation and purification, livers from 8-week-old female mice were perfused using a modified EGTA–collagenase perfusion protocol (Neufeld 1997). All perfusions and hepatocyte purifications were done at the same time of the day to avoid possible circadian effects on any studied parameter. EGTA buffer was used to flush the blood out of the liver and start to digest the desmosomes connecting the liver cells. After 35 ml of the 1× EGTA solution was passed through the liver, it was replaced with 7–10 ml of 1× Leffert’s buffer to flush out the EGTA, which otherwise chelates the calcium ions necessary for collagenase activity in the next step when the liver is digested by perfusion with 25–50 ml of Liberase solution (∼4.3 Wünsch units). After perfusion, the liver was removed from the abdominal cavity and passed through Nitex 80-μm nylon mesh, using extra ice-cold Leffert’s buffer with 0.02% CaCl2and a rubber policeman. Hepatocytes were purified from the remaining cells by two consecutive centrifugations for 4 min, 50 × g each, leaving the other, smaller cell types in suspension. After each spin, the solution was decanted as waste, and the enriched cell pellet of hepatocytes was resuspended in 30 ml ice-cold Leffert’s buffer with 0.02% CaCl2. After the second centrifugation, the cell pellet contained >98.6% hepatocytes.
-
-For cardiomyocyte isolation 8-week-old female mice were euthanized and the chest opened to expose the heart. The descending aorta and inferior vena cava were cut and an EDTA buffer was injected into the apex of the right ventricle to flush the heart. The ascending aorta was clamped and the heart transferred to a petri dish and fixed by perfusion of EDTA buffer containing 4% formaldehyde via the left ventricle. The formaldehyde was quenched by perfusing the heart with 125 mM glycine, and digested by perfusion with collagenase buffer. The ventricles were rent into smaller pieces, and triturated to complete cellular dissociation into a single-cell suspension. Cells were then filtered through a 100-μm strainer to remove tissue fragments and centrifuged at a very low speed to obtain a highly enriched fraction of fixed cardiomyocytes.
diff --git a/general/datasets/JAX_BXD_Hip_Pro_0219/specifics.rtf b/general/datasets/JAX_BXD_Hip_Pro_0219/specifics.rtf
deleted file mode 100644
index 57e3686..0000000
--- a/general/datasets/JAX_BXD_Hip_Pro_0219/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-BXD Hippocampal Proteome
\ No newline at end of file
diff --git a/general/datasets/JAX_BXD_Hip_Pro_0219/summary.rtf b/general/datasets/JAX_BXD_Hip_Pro_0219/summary.rtf
deleted file mode 100644
index c85fe16..0000000
--- a/general/datasets/JAX_BXD_Hip_Pro_0219/summary.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-Detail information about this dataset is in working progress.
-
-Database Name: JAX_BXD_Hippocampal_Proteome_Feb19
-GeneNetwork Accession Number: GN873
-For more information regarding this data set please visit: http://www.genenetwork.org/webqtl/main.py?FormID=sharinginfo&GN_AccessionId=873
-
-Data files available at https://files.genenetwork.org/current/GN873/
diff --git a/general/datasets/JAX_D2GM_RSeq_log2Z_0418/experiment-design.rtf b/general/datasets/JAX_D2GM_RSeq_log2Z_0418/experiment-design.rtf
deleted file mode 100644
index 5b2f4c9..0000000
--- a/general/datasets/JAX_D2GM_RSeq_log2Z_0418/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Retinal ganglion cell mRNA from 4 month (young) and 9 month (pre-glaucomatous) DBA/2J mice and age and sex-matched D2-Gpnmb+ controls
diff --git a/general/datasets/JAX_D2GM_RSeq_log2Z_0418/platform.rtf b/general/datasets/JAX_D2GM_RSeq_log2Z_0418/platform.rtf
deleted file mode 100644
index c967d36..0000000
--- a/general/datasets/JAX_D2GM_RSeq_log2Z_0418/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GPL17021Illumina HiSeq 2500 (Mus musculus)
diff --git a/general/datasets/JAX_D2GM_RSeq_log2Z_0418/specifics.rtf b/general/datasets/JAX_D2GM_RSeq_log2Z_0418/specifics.rtf
deleted file mode 100644
index f57a155..0000000
--- a/general/datasets/JAX_D2GM_RSeq_log2Z_0418/specifics.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA-Seq log2 Z-Score
-
-In general, the array data that we put in GeneNetwork has been logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/JAX_D2GM_RSeq_log2Z_0418/summary.rtf b/general/datasets/JAX_D2GM_RSeq_log2Z_0418/summary.rtf
deleted file mode 100644
index 1cf2292..0000000
--- a/general/datasets/JAX_D2GM_RSeq_log2Z_0418/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-RNA-seq analysis from young and pre-glaucomatous DBA/2J retinal ganglion cells and control (age and sex-matched, D2-Gpnmb+) retinal ganglion cells
diff --git a/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/acknowledgment.rtf b/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/acknowledgment.rtf
deleted file mode 100644
index 3201334..0000000
--- a/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/acknowledgment.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Authors would like to thank Electron Microscopy, Flow Cytometry, Histology, and Gene Expression Services at The Jackson Laboratory, Rick Libby for careful reading of the manuscript and discussion, Mimi de Vries for assistance with organizing and mouse colonies, Brynn Cardozo and Trip Freeburg for colony maintenance, Jocelyn Thomas for blood collections, Philipp Tauber for assistance with immunofluorescence, and Amy Bell for intraocular pressure measurements.
-
-EY011721 (SWMJ), EY021525 (GRH). Pete Williams is supported by the Karolinska Institutet in the form of a Board of Research Faculty Funded Career Position. Simon John is an Investigator of HHMI.
diff --git a/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/experiment-design.rtf b/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/experiment-design.rtf
deleted file mode 100644
index 1c50734..0000000
--- a/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-To understand the function of these infiltrating monocyte-like cells, we used RNA-sequencing to profile their transcriptomes. Based on their pro-inflammatory molecular signatures, we hypothesized and confirmed that monocyte-platelet interactions occur in glaucomatous tissue. Furthermore, to test monocyte function we used two approaches to inhibit their entry into the optic nerve head: (1) treatment with DS-SILY, a peptidoglycan that acts as a barrier to platelet adhesion to the vessel wall and to monocytes, and (2) genetic targeting of Itgam (CD11b, an immune cell receptor that enables immune cell extravasation).
diff --git a/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/processing.rtf b/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/processing.rtf
deleted file mode 100644
index acc1087..0000000
--- a/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-RNA-sequencing and analysis
-
-Monocytes from single optic nerve heads or from peripheral blood (restrained cheek bleed) were FAC sorted into 100 μl buffer RLT + 1% βME and frozen at − 80 °C until further processing. Samples were defrosted on ice and homogenized by syringe in RLT Buffer (total volume 300 μl). Total RNA was isolated using RNeasy micro kits as according to manufacturer’s protocols (Qiagen) including the optional DNase treatment step, and quality was assessed using an Agilent 2100 Bioanalyzer. The concentration was determined using a Ribogreen Assay from Invitrogen. Amplified dscDNA libraries were created using a Nugen Ovation RNA-seq System V2 and a primer titration was performed to remove primer dimers from the sample to allow sample inputs as low as 50 pg RNA. The SPIA dscDNA was sheared to 300 bp in length using a Diogenode Disruptor. Quality control was performed using an Agilent 2100 Bioanalyzer and a DNA 1000 chip assay. Library size produced was analysed using qPCR using the Library Quantitation kit/Illumina GA /ABI Prism (Kapa Biosystems). Libraries were barcoded, pooled, and sequenced 6 samples per lane on a HiSeq 2000 sequencer (Illumina) giving a depth of 30–35 million reads per sample.
-
-Following RNA-sequencing samples were subjected to quality control analysis by a custom quality control python script. Reads with 70% of their bases having a base quality score ≥ 30 were retained for further analysis. Read alignment was performed using TopHat v 2.0.7 [34] and expression estimation was performed using HTSeq [35] with supplied annotations and default parameters against the DBA/2 J mouse genome (build-mm10). Bamtools v 1.0.2 [36] were used to calculate the mapping statistics. Differential gene expression analysis between groups was performed using edgeR v 3.10.5 [37] following, batch correction using RUVSeq, the removal of outlier samples and lowly expressed genes by removing genes with less than five reads in more than two samples. Normalization was performed using the trimmed mean of M values (TMM). Unsupervised HC was performed in R (1-cor, Spearman’s rho). Following preliminary analysis, 1 sample was removed as an outlier. Adjustment for multiple testing was performed using false discovery rate (FDR). Genes were considered to be significantly differentially expression at a false discovery rate (FDR; q) of q < 0.05. Pathway analysis was performed in R, IPA (Ingenuity Pathway Analysis, Qiagen), and using publically available tools (see Results).
diff --git a/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/specifics.rtf b/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/specifics.rtf
deleted file mode 100644
index 954c19f..0000000
--- a/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-JAX DBA/2J Monocyte 1 vs PBMC RNA-Seq (Jun19)
\ No newline at end of file
diff --git a/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/summary.rtf b/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/summary.rtf
deleted file mode 100644
index b5e090d..0000000
--- a/general/datasets/JAX_D2_Mono1vPBMC_Ret_RNA_Seq_0619/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Glaucoma is characterized by the progressive dysfunction and loss of retinal ganglion cells. Recent work in animal models suggests that a critical neuroinflammatory event damages retinal ganglion cell axons in the optic nerve head during ocular hypertensive injury. We previously demonstrated that monocyte-like cells enter the optic nerve head in an ocular hypertensive mouse model of glaucoma (DBA/2 J), but their roles, if any, in mediating axon damage remain unclear.
-
-https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-018-0303-3
diff --git a/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/acknowledgment.rtf b/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/acknowledgment.rtf
deleted file mode 100644
index 3201334..0000000
--- a/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/acknowledgment.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-The Authors would like to thank Electron Microscopy, Flow Cytometry, Histology, and Gene Expression Services at The Jackson Laboratory, Rick Libby for careful reading of the manuscript and discussion, Mimi de Vries for assistance with organizing and mouse colonies, Brynn Cardozo and Trip Freeburg for colony maintenance, Jocelyn Thomas for blood collections, Philipp Tauber for assistance with immunofluorescence, and Amy Bell for intraocular pressure measurements.
-
-EY011721 (SWMJ), EY021525 (GRH). Pete Williams is supported by the Karolinska Institutet in the form of a Board of Research Faculty Funded Career Position. Simon John is an Investigator of HHMI.
diff --git a/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/experiment-design.rtf b/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/experiment-design.rtf
deleted file mode 100644
index 1c50734..0000000
--- a/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-To understand the function of these infiltrating monocyte-like cells, we used RNA-sequencing to profile their transcriptomes. Based on their pro-inflammatory molecular signatures, we hypothesized and confirmed that monocyte-platelet interactions occur in glaucomatous tissue. Furthermore, to test monocyte function we used two approaches to inhibit their entry into the optic nerve head: (1) treatment with DS-SILY, a peptidoglycan that acts as a barrier to platelet adhesion to the vessel wall and to monocytes, and (2) genetic targeting of Itgam (CD11b, an immune cell receptor that enables immune cell extravasation).
diff --git a/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/processing.rtf b/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/processing.rtf
deleted file mode 100644
index acc1087..0000000
--- a/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-RNA-sequencing and analysis
-
-Monocytes from single optic nerve heads or from peripheral blood (restrained cheek bleed) were FAC sorted into 100 μl buffer RLT + 1% βME and frozen at − 80 °C until further processing. Samples were defrosted on ice and homogenized by syringe in RLT Buffer (total volume 300 μl). Total RNA was isolated using RNeasy micro kits as according to manufacturer’s protocols (Qiagen) including the optional DNase treatment step, and quality was assessed using an Agilent 2100 Bioanalyzer. The concentration was determined using a Ribogreen Assay from Invitrogen. Amplified dscDNA libraries were created using a Nugen Ovation RNA-seq System V2 and a primer titration was performed to remove primer dimers from the sample to allow sample inputs as low as 50 pg RNA. The SPIA dscDNA was sheared to 300 bp in length using a Diogenode Disruptor. Quality control was performed using an Agilent 2100 Bioanalyzer and a DNA 1000 chip assay. Library size produced was analysed using qPCR using the Library Quantitation kit/Illumina GA /ABI Prism (Kapa Biosystems). Libraries were barcoded, pooled, and sequenced 6 samples per lane on a HiSeq 2000 sequencer (Illumina) giving a depth of 30–35 million reads per sample.
-
-Following RNA-sequencing samples were subjected to quality control analysis by a custom quality control python script. Reads with 70% of their bases having a base quality score ≥ 30 were retained for further analysis. Read alignment was performed using TopHat v 2.0.7 [34] and expression estimation was performed using HTSeq [35] with supplied annotations and default parameters against the DBA/2 J mouse genome (build-mm10). Bamtools v 1.0.2 [36] were used to calculate the mapping statistics. Differential gene expression analysis between groups was performed using edgeR v 3.10.5 [37] following, batch correction using RUVSeq, the removal of outlier samples and lowly expressed genes by removing genes with less than five reads in more than two samples. Normalization was performed using the trimmed mean of M values (TMM). Unsupervised HC was performed in R (1-cor, Spearman’s rho). Following preliminary analysis, 1 sample was removed as an outlier. Adjustment for multiple testing was performed using false discovery rate (FDR). Genes were considered to be significantly differentially expression at a false discovery rate (FDR; q) of q < 0.05. Pathway analysis was performed in R, IPA (Ingenuity Pathway Analysis, Qiagen), and using publically available tools (see Results).
diff --git a/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/specifics.rtf b/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/specifics.rtf
deleted file mode 100644
index ba732fb..0000000
--- a/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-JAX DBA/2J Monocyte 2 vs PBMC RNA-Seq (Jun19)
\ No newline at end of file
diff --git a/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/summary.rtf b/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/summary.rtf
deleted file mode 100644
index b5e090d..0000000
--- a/general/datasets/JAX_D2_Mono2vPBMC_Ret_RNA_Seq_0619/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Glaucoma is characterized by the progressive dysfunction and loss of retinal ganglion cells. Recent work in animal models suggests that a critical neuroinflammatory event damages retinal ganglion cell axons in the optic nerve head during ocular hypertensive injury. We previously demonstrated that monocyte-like cells enter the optic nerve head in an ocular hypertensive mouse model of glaucoma (DBA/2 J), but their roles, if any, in mediating axon damage remain unclear.
-
-https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-018-0303-3
diff --git a/general/datasets/JAX_liver_agil_MDP-0113/summary.rtf b/general/datasets/JAX_liver_agil_MDP-0113/summary.rtf
new file mode 100644
index 0000000..f6be413
--- /dev/null
+++ b/general/datasets/JAX_liver_agil_MDP-0113/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 160, Name: Harrill-Rusyn MDP Liver Acetaminophen Tox Study (G4121A, 2009)
\ No newline at end of file
diff --git a/general/datasets/JAX_liver_agil_MDP_0113/summary.rtf b/general/datasets/JAX_liver_agil_MDP_0113/summary.rtf
deleted file mode 100644
index f6be413..0000000
--- a/general/datasets/JAX_liver_agil_MDP_0113/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 160, Name: Harrill-Rusyn MDP Liver Acetaminophen Tox Study (G4121A, 2009)
\ No newline at end of file
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_0820/acknowledgment.rtf b/general/datasets/Jax_bxd_germ_cells_edger_0820/acknowledgment.rtf
new file mode 100644
index 0000000..5ab8fd8
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_0820/acknowledgment.rtf
@@ -0,0 +1 @@
+This manuscript is dedicated to the memory of Pavlina Petkova, a wonderful scientist, colleague, and wonderful friend. We thank members of the Baker, Paigen, Petkov, and Carter laboratories for their discussion of the data and manuscript. This work was assisted by The Jackson Laboratory scientific services, which are supported through National Institutes of Health Cancer Core grant CA34196. BXD ESC lines were kindly provided by Anne Czechanski and Laura Reinholdt, funded by the Special Mouse Strain Resource OD011102-18. Funding for the work was provided by NIGMS F32-GM101736 and The Jackson Laboratory start-up funds supporting C.L.B., and P01-GM099640 to K.P. and G.W.C.
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_0820/cases.rtf b/general/datasets/Jax_bxd_germ_cells_edger_0820/cases.rtf
new file mode 100644
index 0000000..5922df0
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_0820/cases.rtf
@@ -0,0 +1 @@
+C57BL/6J (stock number 000664), DBA/2J (stock number 000671), B6D2 F1/J hybrid (stock number 100006), and all BXD RI mice were obtained from The Jackson Laboratory (Bar Harbor, ME). All animal experiments were approved by the Animal Care and Use Committee of The Jackson Laboratory (summary #04008 and #16043).
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_0820/processing.rtf b/general/datasets/Jax_bxd_germ_cells_edger_0820/processing.rtf
new file mode 100644
index 0000000..d359653
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_0820/processing.rtf
@@ -0,0 +1,5 @@
+All sequenced B6, D2, F1, and BXD H3K4me3 ChIP libraries, as well as all control input DNA samples were aligned utilizing bwa version 0.7.9a (Li and Durbin 2009). B6 parental samples were aligned to the Genome Reference Consortium Mouse Build 38 (mm10) and D2 parental samples were aligned to the de novo REL-1509 assembly, including all unplaced scaffolds, from the Mouse Genomes Project (Yalcin et al.2012).
+
+To ensure that H3K4me3 peaks were properly quantified across divergent genomes, we began by building a comprehensive “peakome” representing all potential H3K4me3 peaks found in the two parents. H3K4me3 peaks for B6 and D2 were called independently, utilizing alignment data from three replicate samples and one DNA input sample. Reads were filtered for a mapq alignment metric of 60 and an alignment sequence having no indels present across the entire length of the sequencing read, typically 100 bp H3K4me3 peaks were called utilizing MACS version 1.4.2 (Zhang et al. 2008) and peaks having a false discovery rate (FDR) of <1% found in two out of three replicates were accepted. Final genomic intervals for each H3K4me3 peak for each strain were derived by merging the peaks from the corresponding replicate samples using bedtools (Quinlan and Hall 2010). To link syntenic regions between B6 and D2 assemblies, which each have their own coordinate system, sequences from these genomic intervals were aligned to their alternative genome using reciprocal BLAST. In some cases, a sequence interval comprising an H3K4me3 peak in one strain aligned to multiple adjacent intervals in the alternative genome. If the sequences of these peaks in the alternate strain all fell within the boundaries of the single peak, they were merged. The boundaries of these merged peaks included the incorporated sequences from both strains. Because there are also H3K4me3 peaks that are strain specific, these peaks were accepted if, and only if, the mapped interval had a unique sequence that was found in the proper syntentic order within the alternative genome lacking that H3K4me3 peak. The final combined peakome between B6 and D2 mice was created by selecting only peaks appropriately linked across each strain, assuring that each H3K4me3 peak reciprocally aligned to only one peak in the alternative genome after merging, and that all peaks were in the same order along the chromosomes in both genomes (Supplemental Material, Table S2). Using the H3K4me3 peaks locations derived from the parental strains, final read counts for B6, D2, F1 hybrids, and BXDs were obtained by counting reads within the coordinate boundaries of the peakome intervals.
+
+To improve mapping accuracy and utilize known sequence variation between strains, all BXDs and F1hybrid samples were aligned separately to both the mm10 reference and the de novo D2 assembly. To reduce error in quantification of H3K4me3 levels due to genomic regions containing repetitive sequences, we removed reads with multiple alignments and retained reads with alignment metric of 60 that lacked small indels, which can often indicate misalignment. Subsequently, for each genomic interval in the peakome, final reads counts were summed for those that mapped uniquely to one of the assemblies along with those that mapped equally well to both B6 and D2 genome assemblies.
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_0820/specifics.rtf b/general/datasets/Jax_bxd_germ_cells_edger_0820/specifics.rtf
new file mode 100644
index 0000000..7c4621d
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_0820/specifics.rtf
@@ -0,0 +1 @@
+This data has all of the normalization steps already applied. Normalized read counts. Essentially we used a method out of the R package edgeR to normalize for both read depth and composition, followed by log2 transformation, and then subtraction of PCA1.
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_0820/summary.rtf b/general/datasets/Jax_bxd_germ_cells_edger_0820/summary.rtf
new file mode 100644
index 0000000..97965d8
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_0820/summary.rtf
@@ -0,0 +1,3 @@
+https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6404261/
+
+The epigenetic landscape varies greatly among cell types. Although a variety of writers, readers, and erasers of epigenetic features are known, we have little information about the underlying regulatory systems controlling the establishment and maintenance of these features. Here, we have explored how natural genetic variation affects the epigenome in mice. Studying levels of H3K4me3, a histone modification at sites such as promoters, enhancers, and recombination hotspots, we found tissue-specific trans-regulation of H3K4me3 levels in four highly diverse cell types: male germ cells, embryonic stem cells, hepatocytes, and cardiomyocytes. To identify the genetic loci involved, we measured H3K4me3 levels in male germ cells in a mapping population of 59 BXD recombinant inbred lines. We found extensive trans-regulation of H3K4me3 peaks, including six major histone quantitative trait loci (QTL). These chromatin regulatory loci act dominantly to suppress H3K4me3, which at hotspots reduces the likelihood of subsequent DNA double-strand breaks. QTL locations do not correspond with genes encoding enzymes known to metabolize chromatin features. Instead their locations match clusters of zinc finger genes, making these possible candidates that explain the dominant suppression of H3K4me3. Collectively, these data describe an extensive, set of chromatin regulatory loci that control the epigenetic landscape.
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_0820/tissue.rtf b/general/datasets/Jax_bxd_germ_cells_edger_0820/tissue.rtf
new file mode 100644
index 0000000..65281a9
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_0820/tissue.rtf
@@ -0,0 +1,7 @@
+Testicular germ cell enrichment was performed on 14-day postpartum male mice as previously reported (Baker et al. 2014). This cell preparation removes somatic Sertoli and Leydig cells and results in >90% enrichment of germ cells, of which nearly 50% are spermatogonia (Ball et al. 2016).
+
+Individual low-passage mouse ESCs were derived using protocols outlined in Czechanski et al. (2014). Briefly, 6- to 8-week-old females are mated to stud males and checked each morning for plugs. Pregnant females are euthanized on embryonic day 3.5 and the uterine horn is flushed to remove embryos. Embryos are visualized under a dissecting microscope and blastocysts are transferred to 2i (2i:CHIR99021 and PD0325901) (Ying et al. 2008) serum-free media for outgrowth of the inner cell mass. Blastocysts are allowed to hatch and attach to a mouse embryonic fibroblast (MEF) feeder layer, and the resulting outgrowth is monitored daily and fed for 8–11 days. The emergent ESCs are disaggregated and passaged onto new MEF feeders. Cultures during this time are closely monitored for unusually rapid growth (potentially indicating karyotypic instability), signs of deterioration including vacuolated cytoplasm, detachment of cells from colonies and debris, and possible signs of contamination. Successful ESC cultures were maintained on MEF feeders in serum containing 2i media supplemented with Leukemia inhibiting factor (2i/LIF) (Kiyonari et al. 2010) to maintain high levels of NANOG expression, which indicates ground-state pluripotency (Ying et al. 2008; Czechanski et al. 2014). Prior to preparing for chromatin isolation, mouse ESCs were enzymatically disassociated using trypsin and MEFs were removed by serial plating on gelatin-coated plates to which MEFs adsorb preferentially; for this, ESCs and MEFs are incubated in 2i/LIF media on fresh plates for 15 min to allow the larger MEFs to quickly attach to the plates. ESCs are aspirated and the plating procedure repeated once to further remove MEFs. ESCs were collected by centrifugation, resuspended in PBS, and cross-linked using formaldehyde.
+
+For hepatocyte isolation and purification, livers from 8-week-old female mice were perfused using a modified EGTA–collagenase perfusion protocol (Neufeld 1997). All perfusions and hepatocyte purifications were done at the same time of the day to avoid possible circadian effects on any studied parameter. EGTA buffer was used to flush the blood out of the liver and start to digest the desmosomes connecting the liver cells. After 35 ml of the 1× EGTA solution was passed through the liver, it was replaced with 7–10 ml of 1× Leffert’s buffer to flush out the EGTA, which otherwise chelates the calcium ions necessary for collagenase activity in the next step when the liver is digested by perfusion with 25–50 ml of Liberase solution (∼4.3 Wünsch units). After perfusion, the liver was removed from the abdominal cavity and passed through Nitex 80-μm nylon mesh, using extra ice-cold Leffert’s buffer with 0.02% CaCl2and a rubber policeman. Hepatocytes were purified from the remaining cells by two consecutive centrifugations for 4 min, 50 × g each, leaving the other, smaller cell types in suspension. After each spin, the solution was decanted as waste, and the enriched cell pellet of hepatocytes was resuspended in 30 ml ice-cold Leffert’s buffer with 0.02% CaCl2. After the second centrifugation, the cell pellet contained >98.6% hepatocytes.
+
+For cardiomyocyte isolation 8-week-old female mice were euthanized and the chest opened to expose the heart. The descending aorta and inferior vena cava were cut and an EDTA buffer was injected into the apex of the right ventricle to flush the heart. The ascending aorta was clamped and the heart transferred to a petri dish and fixed by perfusion of EDTA buffer containing 4% formaldehyde via the left ventricle. The formaldehyde was quenched by perfusing the heart with 125 mM glycine, and digested by perfusion with collagenase buffer. The ventricles were rent into smaller pieces, and triturated to complete cellular dissociation into a single-cell suspension. Cells were then filtered through a 100-μm strainer to remove tissue fragments and centrifuged at a very low speed to obtain a highly enriched fraction of fixed cardiomyocytes.
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/acknowledgment.rtf b/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/acknowledgment.rtf
new file mode 100644
index 0000000..5ab8fd8
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/acknowledgment.rtf
@@ -0,0 +1 @@
+This manuscript is dedicated to the memory of Pavlina Petkova, a wonderful scientist, colleague, and wonderful friend. We thank members of the Baker, Paigen, Petkov, and Carter laboratories for their discussion of the data and manuscript. This work was assisted by The Jackson Laboratory scientific services, which are supported through National Institutes of Health Cancer Core grant CA34196. BXD ESC lines were kindly provided by Anne Czechanski and Laura Reinholdt, funded by the Special Mouse Strain Resource OD011102-18. Funding for the work was provided by NIGMS F32-GM101736 and The Jackson Laboratory start-up funds supporting C.L.B., and P01-GM099640 to K.P. and G.W.C.
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/cases.rtf b/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/cases.rtf
new file mode 100644
index 0000000..5922df0
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/cases.rtf
@@ -0,0 +1 @@
+C57BL/6J (stock number 000664), DBA/2J (stock number 000671), B6D2 F1/J hybrid (stock number 100006), and all BXD RI mice were obtained from The Jackson Laboratory (Bar Harbor, ME). All animal experiments were approved by the Animal Care and Use Committee of The Jackson Laboratory (summary #04008 and #16043).
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/processing.rtf b/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/processing.rtf
new file mode 100644
index 0000000..d359653
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/processing.rtf
@@ -0,0 +1,5 @@
+All sequenced B6, D2, F1, and BXD H3K4me3 ChIP libraries, as well as all control input DNA samples were aligned utilizing bwa version 0.7.9a (Li and Durbin 2009). B6 parental samples were aligned to the Genome Reference Consortium Mouse Build 38 (mm10) and D2 parental samples were aligned to the de novo REL-1509 assembly, including all unplaced scaffolds, from the Mouse Genomes Project (Yalcin et al.2012).
+
+To ensure that H3K4me3 peaks were properly quantified across divergent genomes, we began by building a comprehensive “peakome” representing all potential H3K4me3 peaks found in the two parents. H3K4me3 peaks for B6 and D2 were called independently, utilizing alignment data from three replicate samples and one DNA input sample. Reads were filtered for a mapq alignment metric of 60 and an alignment sequence having no indels present across the entire length of the sequencing read, typically 100 bp H3K4me3 peaks were called utilizing MACS version 1.4.2 (Zhang et al. 2008) and peaks having a false discovery rate (FDR) of <1% found in two out of three replicates were accepted. Final genomic intervals for each H3K4me3 peak for each strain were derived by merging the peaks from the corresponding replicate samples using bedtools (Quinlan and Hall 2010). To link syntenic regions between B6 and D2 assemblies, which each have their own coordinate system, sequences from these genomic intervals were aligned to their alternative genome using reciprocal BLAST. In some cases, a sequence interval comprising an H3K4me3 peak in one strain aligned to multiple adjacent intervals in the alternative genome. If the sequences of these peaks in the alternate strain all fell within the boundaries of the single peak, they were merged. The boundaries of these merged peaks included the incorporated sequences from both strains. Because there are also H3K4me3 peaks that are strain specific, these peaks were accepted if, and only if, the mapped interval had a unique sequence that was found in the proper syntentic order within the alternative genome lacking that H3K4me3 peak. The final combined peakome between B6 and D2 mice was created by selecting only peaks appropriately linked across each strain, assuring that each H3K4me3 peak reciprocally aligned to only one peak in the alternative genome after merging, and that all peaks were in the same order along the chromosomes in both genomes (Supplemental Material, Table S2). Using the H3K4me3 peaks locations derived from the parental strains, final read counts for B6, D2, F1 hybrids, and BXDs were obtained by counting reads within the coordinate boundaries of the peakome intervals.
+
+To improve mapping accuracy and utilize known sequence variation between strains, all BXDs and F1hybrid samples were aligned separately to both the mm10 reference and the de novo D2 assembly. To reduce error in quantification of H3K4me3 levels due to genomic regions containing repetitive sequences, we removed reads with multiple alignments and retained reads with alignment metric of 60 that lacked small indels, which can often indicate misalignment. Subsequently, for each genomic interval in the peakome, final reads counts were summed for those that mapped uniquely to one of the assemblies along with those that mapped equally well to both B6 and D2 genome assemblies.
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/specifics.rtf b/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/specifics.rtf
new file mode 100644
index 0000000..bbaabc0
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/specifics.rtf
@@ -0,0 +1 @@
+log2 transformed
\ No newline at end of file
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/summary.rtf b/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/summary.rtf
new file mode 100644
index 0000000..97965d8
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/summary.rtf
@@ -0,0 +1,3 @@
+https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6404261/
+
+The epigenetic landscape varies greatly among cell types. Although a variety of writers, readers, and erasers of epigenetic features are known, we have little information about the underlying regulatory systems controlling the establishment and maintenance of these features. Here, we have explored how natural genetic variation affects the epigenome in mice. Studying levels of H3K4me3, a histone modification at sites such as promoters, enhancers, and recombination hotspots, we found tissue-specific trans-regulation of H3K4me3 levels in four highly diverse cell types: male germ cells, embryonic stem cells, hepatocytes, and cardiomyocytes. To identify the genetic loci involved, we measured H3K4me3 levels in male germ cells in a mapping population of 59 BXD recombinant inbred lines. We found extensive trans-regulation of H3K4me3 peaks, including six major histone quantitative trait loci (QTL). These chromatin regulatory loci act dominantly to suppress H3K4me3, which at hotspots reduces the likelihood of subsequent DNA double-strand breaks. QTL locations do not correspond with genes encoding enzymes known to metabolize chromatin features. Instead their locations match clusters of zinc finger genes, making these possible candidates that explain the dominant suppression of H3K4me3. Collectively, these data describe an extensive, set of chromatin regulatory loci that control the epigenetic landscape.
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/tissue.rtf b/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/tissue.rtf
new file mode 100644
index 0000000..65281a9
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_log2_0820/tissue.rtf
@@ -0,0 +1,7 @@
+Testicular germ cell enrichment was performed on 14-day postpartum male mice as previously reported (Baker et al. 2014). This cell preparation removes somatic Sertoli and Leydig cells and results in >90% enrichment of germ cells, of which nearly 50% are spermatogonia (Ball et al. 2016).
+
+Individual low-passage mouse ESCs were derived using protocols outlined in Czechanski et al. (2014). Briefly, 6- to 8-week-old females are mated to stud males and checked each morning for plugs. Pregnant females are euthanized on embryonic day 3.5 and the uterine horn is flushed to remove embryos. Embryos are visualized under a dissecting microscope and blastocysts are transferred to 2i (2i:CHIR99021 and PD0325901) (Ying et al. 2008) serum-free media for outgrowth of the inner cell mass. Blastocysts are allowed to hatch and attach to a mouse embryonic fibroblast (MEF) feeder layer, and the resulting outgrowth is monitored daily and fed for 8–11 days. The emergent ESCs are disaggregated and passaged onto new MEF feeders. Cultures during this time are closely monitored for unusually rapid growth (potentially indicating karyotypic instability), signs of deterioration including vacuolated cytoplasm, detachment of cells from colonies and debris, and possible signs of contamination. Successful ESC cultures were maintained on MEF feeders in serum containing 2i media supplemented with Leukemia inhibiting factor (2i/LIF) (Kiyonari et al. 2010) to maintain high levels of NANOG expression, which indicates ground-state pluripotency (Ying et al. 2008; Czechanski et al. 2014). Prior to preparing for chromatin isolation, mouse ESCs were enzymatically disassociated using trypsin and MEFs were removed by serial plating on gelatin-coated plates to which MEFs adsorb preferentially; for this, ESCs and MEFs are incubated in 2i/LIF media on fresh plates for 15 min to allow the larger MEFs to quickly attach to the plates. ESCs are aspirated and the plating procedure repeated once to further remove MEFs. ESCs were collected by centrifugation, resuspended in PBS, and cross-linked using formaldehyde.
+
+For hepatocyte isolation and purification, livers from 8-week-old female mice were perfused using a modified EGTA–collagenase perfusion protocol (Neufeld 1997). All perfusions and hepatocyte purifications were done at the same time of the day to avoid possible circadian effects on any studied parameter. EGTA buffer was used to flush the blood out of the liver and start to digest the desmosomes connecting the liver cells. After 35 ml of the 1× EGTA solution was passed through the liver, it was replaced with 7–10 ml of 1× Leffert’s buffer to flush out the EGTA, which otherwise chelates the calcium ions necessary for collagenase activity in the next step when the liver is digested by perfusion with 25–50 ml of Liberase solution (∼4.3 Wünsch units). After perfusion, the liver was removed from the abdominal cavity and passed through Nitex 80-μm nylon mesh, using extra ice-cold Leffert’s buffer with 0.02% CaCl2and a rubber policeman. Hepatocytes were purified from the remaining cells by two consecutive centrifugations for 4 min, 50 × g each, leaving the other, smaller cell types in suspension. After each spin, the solution was decanted as waste, and the enriched cell pellet of hepatocytes was resuspended in 30 ml ice-cold Leffert’s buffer with 0.02% CaCl2. After the second centrifugation, the cell pellet contained >98.6% hepatocytes.
+
+For cardiomyocyte isolation 8-week-old female mice were euthanized and the chest opened to expose the heart. The descending aorta and inferior vena cava were cut and an EDTA buffer was injected into the apex of the right ventricle to flush the heart. The ascending aorta was clamped and the heart transferred to a petri dish and fixed by perfusion of EDTA buffer containing 4% formaldehyde via the left ventricle. The formaldehyde was quenched by perfusing the heart with 125 mM glycine, and digested by perfusion with collagenase buffer. The ventricles were rent into smaller pieces, and triturated to complete cellular dissociation into a single-cell suspension. Cells were then filtered through a 100-μm strainer to remove tissue fragments and centrifuged at a very low speed to obtain a highly enriched fraction of fixed cardiomyocytes.
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/acknowledgment.rtf b/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/acknowledgment.rtf
new file mode 100644
index 0000000..5ab8fd8
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/acknowledgment.rtf
@@ -0,0 +1 @@
+This manuscript is dedicated to the memory of Pavlina Petkova, a wonderful scientist, colleague, and wonderful friend. We thank members of the Baker, Paigen, Petkov, and Carter laboratories for their discussion of the data and manuscript. This work was assisted by The Jackson Laboratory scientific services, which are supported through National Institutes of Health Cancer Core grant CA34196. BXD ESC lines were kindly provided by Anne Czechanski and Laura Reinholdt, funded by the Special Mouse Strain Resource OD011102-18. Funding for the work was provided by NIGMS F32-GM101736 and The Jackson Laboratory start-up funds supporting C.L.B., and P01-GM099640 to K.P. and G.W.C.
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/cases.rtf b/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/cases.rtf
new file mode 100644
index 0000000..5922df0
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/cases.rtf
@@ -0,0 +1 @@
+C57BL/6J (stock number 000664), DBA/2J (stock number 000671), B6D2 F1/J hybrid (stock number 100006), and all BXD RI mice were obtained from The Jackson Laboratory (Bar Harbor, ME). All animal experiments were approved by the Animal Care and Use Committee of The Jackson Laboratory (summary #04008 and #16043).
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/processing.rtf b/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/processing.rtf
new file mode 100644
index 0000000..d359653
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/processing.rtf
@@ -0,0 +1,5 @@
+All sequenced B6, D2, F1, and BXD H3K4me3 ChIP libraries, as well as all control input DNA samples were aligned utilizing bwa version 0.7.9a (Li and Durbin 2009). B6 parental samples were aligned to the Genome Reference Consortium Mouse Build 38 (mm10) and D2 parental samples were aligned to the de novo REL-1509 assembly, including all unplaced scaffolds, from the Mouse Genomes Project (Yalcin et al.2012).
+
+To ensure that H3K4me3 peaks were properly quantified across divergent genomes, we began by building a comprehensive “peakome” representing all potential H3K4me3 peaks found in the two parents. H3K4me3 peaks for B6 and D2 were called independently, utilizing alignment data from three replicate samples and one DNA input sample. Reads were filtered for a mapq alignment metric of 60 and an alignment sequence having no indels present across the entire length of the sequencing read, typically 100 bp H3K4me3 peaks were called utilizing MACS version 1.4.2 (Zhang et al. 2008) and peaks having a false discovery rate (FDR) of <1% found in two out of three replicates were accepted. Final genomic intervals for each H3K4me3 peak for each strain were derived by merging the peaks from the corresponding replicate samples using bedtools (Quinlan and Hall 2010). To link syntenic regions between B6 and D2 assemblies, which each have their own coordinate system, sequences from these genomic intervals were aligned to their alternative genome using reciprocal BLAST. In some cases, a sequence interval comprising an H3K4me3 peak in one strain aligned to multiple adjacent intervals in the alternative genome. If the sequences of these peaks in the alternate strain all fell within the boundaries of the single peak, they were merged. The boundaries of these merged peaks included the incorporated sequences from both strains. Because there are also H3K4me3 peaks that are strain specific, these peaks were accepted if, and only if, the mapped interval had a unique sequence that was found in the proper syntentic order within the alternative genome lacking that H3K4me3 peak. The final combined peakome between B6 and D2 mice was created by selecting only peaks appropriately linked across each strain, assuring that each H3K4me3 peak reciprocally aligned to only one peak in the alternative genome after merging, and that all peaks were in the same order along the chromosomes in both genomes (Supplemental Material, Table S2). Using the H3K4me3 peaks locations derived from the parental strains, final read counts for B6, D2, F1 hybrids, and BXDs were obtained by counting reads within the coordinate boundaries of the peakome intervals.
+
+To improve mapping accuracy and utilize known sequence variation between strains, all BXDs and F1hybrid samples were aligned separately to both the mm10 reference and the de novo D2 assembly. To reduce error in quantification of H3K4me3 levels due to genomic regions containing repetitive sequences, we removed reads with multiple alignments and retained reads with alignment metric of 60 that lacked small indels, which can often indicate misalignment. Subsequently, for each genomic interval in the peakome, final reads counts were summed for those that mapped uniquely to one of the assemblies along with those that mapped equally well to both B6 and D2 genome assemblies.
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/specifics.rtf b/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/specifics.rtf
new file mode 100644
index 0000000..ca16969
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/specifics.rtf
@@ -0,0 +1 @@
+log2 z-score transformed
\ No newline at end of file
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/summary.rtf b/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/summary.rtf
new file mode 100644
index 0000000..97965d8
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/summary.rtf
@@ -0,0 +1,3 @@
+https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6404261/
+
+The epigenetic landscape varies greatly among cell types. Although a variety of writers, readers, and erasers of epigenetic features are known, we have little information about the underlying regulatory systems controlling the establishment and maintenance of these features. Here, we have explored how natural genetic variation affects the epigenome in mice. Studying levels of H3K4me3, a histone modification at sites such as promoters, enhancers, and recombination hotspots, we found tissue-specific trans-regulation of H3K4me3 levels in four highly diverse cell types: male germ cells, embryonic stem cells, hepatocytes, and cardiomyocytes. To identify the genetic loci involved, we measured H3K4me3 levels in male germ cells in a mapping population of 59 BXD recombinant inbred lines. We found extensive trans-regulation of H3K4me3 peaks, including six major histone quantitative trait loci (QTL). These chromatin regulatory loci act dominantly to suppress H3K4me3, which at hotspots reduces the likelihood of subsequent DNA double-strand breaks. QTL locations do not correspond with genes encoding enzymes known to metabolize chromatin features. Instead their locations match clusters of zinc finger genes, making these possible candidates that explain the dominant suppression of H3K4me3. Collectively, these data describe an extensive, set of chromatin regulatory loci that control the epigenetic landscape.
diff --git a/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/tissue.rtf b/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/tissue.rtf
new file mode 100644
index 0000000..65281a9
--- /dev/null
+++ b/general/datasets/Jax_bxd_germ_cells_edger_log2z_0820/tissue.rtf
@@ -0,0 +1,7 @@
+Testicular germ cell enrichment was performed on 14-day postpartum male mice as previously reported (Baker et al. 2014). This cell preparation removes somatic Sertoli and Leydig cells and results in >90% enrichment of germ cells, of which nearly 50% are spermatogonia (Ball et al. 2016).
+
+Individual low-passage mouse ESCs were derived using protocols outlined in Czechanski et al. (2014). Briefly, 6- to 8-week-old females are mated to stud males and checked each morning for plugs. Pregnant females are euthanized on embryonic day 3.5 and the uterine horn is flushed to remove embryos. Embryos are visualized under a dissecting microscope and blastocysts are transferred to 2i (2i:CHIR99021 and PD0325901) (Ying et al. 2008) serum-free media for outgrowth of the inner cell mass. Blastocysts are allowed to hatch and attach to a mouse embryonic fibroblast (MEF) feeder layer, and the resulting outgrowth is monitored daily and fed for 8–11 days. The emergent ESCs are disaggregated and passaged onto new MEF feeders. Cultures during this time are closely monitored for unusually rapid growth (potentially indicating karyotypic instability), signs of deterioration including vacuolated cytoplasm, detachment of cells from colonies and debris, and possible signs of contamination. Successful ESC cultures were maintained on MEF feeders in serum containing 2i media supplemented with Leukemia inhibiting factor (2i/LIF) (Kiyonari et al. 2010) to maintain high levels of NANOG expression, which indicates ground-state pluripotency (Ying et al. 2008; Czechanski et al. 2014). Prior to preparing for chromatin isolation, mouse ESCs were enzymatically disassociated using trypsin and MEFs were removed by serial plating on gelatin-coated plates to which MEFs adsorb preferentially; for this, ESCs and MEFs are incubated in 2i/LIF media on fresh plates for 15 min to allow the larger MEFs to quickly attach to the plates. ESCs are aspirated and the plating procedure repeated once to further remove MEFs. ESCs were collected by centrifugation, resuspended in PBS, and cross-linked using formaldehyde.
+
+For hepatocyte isolation and purification, livers from 8-week-old female mice were perfused using a modified EGTA–collagenase perfusion protocol (Neufeld 1997). All perfusions and hepatocyte purifications were done at the same time of the day to avoid possible circadian effects on any studied parameter. EGTA buffer was used to flush the blood out of the liver and start to digest the desmosomes connecting the liver cells. After 35 ml of the 1× EGTA solution was passed through the liver, it was replaced with 7–10 ml of 1× Leffert’s buffer to flush out the EGTA, which otherwise chelates the calcium ions necessary for collagenase activity in the next step when the liver is digested by perfusion with 25–50 ml of Liberase solution (∼4.3 Wünsch units). After perfusion, the liver was removed from the abdominal cavity and passed through Nitex 80-μm nylon mesh, using extra ice-cold Leffert’s buffer with 0.02% CaCl2and a rubber policeman. Hepatocytes were purified from the remaining cells by two consecutive centrifugations for 4 min, 50 × g each, leaving the other, smaller cell types in suspension. After each spin, the solution was decanted as waste, and the enriched cell pellet of hepatocytes was resuspended in 30 ml ice-cold Leffert’s buffer with 0.02% CaCl2. After the second centrifugation, the cell pellet contained >98.6% hepatocytes.
+
+For cardiomyocyte isolation 8-week-old female mice were euthanized and the chest opened to expose the heart. The descending aorta and inferior vena cava were cut and an EDTA buffer was injected into the apex of the right ventricle to flush the heart. The ascending aorta was clamped and the heart transferred to a petri dish and fixed by perfusion of EDTA buffer containing 4% formaldehyde via the left ventricle. The formaldehyde was quenched by perfusing the heart with 125 mM glycine, and digested by perfusion with collagenase buffer. The ventricles were rent into smaller pieces, and triturated to complete cellular dissociation into a single-cell suspension. Cells were then filtered through a 100-μm strainer to remove tissue fragments and centrifuged at a very low speed to obtain a highly enriched fraction of fixed cardiomyocytes.
diff --git a/general/datasets/Jax_bxd_hip_pro_0219/specifics.rtf b/general/datasets/Jax_bxd_hip_pro_0219/specifics.rtf
new file mode 100644
index 0000000..57e3686
--- /dev/null
+++ b/general/datasets/Jax_bxd_hip_pro_0219/specifics.rtf
@@ -0,0 +1 @@
+BXD Hippocampal Proteome
\ No newline at end of file
diff --git a/general/datasets/Jax_bxd_hip_pro_0219/summary.rtf b/general/datasets/Jax_bxd_hip_pro_0219/summary.rtf
new file mode 100644
index 0000000..c85fe16
--- /dev/null
+++ b/general/datasets/Jax_bxd_hip_pro_0219/summary.rtf
@@ -0,0 +1,7 @@
+Detail information about this dataset is in working progress.
+
+Database Name: JAX_BXD_Hippocampal_Proteome_Feb19
+GeneNetwork Accession Number: GN873
+For more information regarding this data set please visit: http://www.genenetwork.org/webqtl/main.py?FormID=sharinginfo&GN_AccessionId=873
+
+Data files available at https://files.genenetwork.org/current/GN873/
diff --git a/general/datasets/Jax_csb_l_0711/acknowledgment.rtf b/general/datasets/Jax_csb_l_0711/acknowledgment.rtf
new file mode 100644
index 0000000..04d1867
--- /dev/null
+++ b/general/datasets/Jax_csb_l_0711/acknowledgment.rtf
@@ -0,0 +1 @@
+Churchill GA, Paigen B, Shockley KR, Witmer D
diff --git a/general/datasets/Jax_csb_l_0711/cases.rtf b/general/datasets/Jax_csb_l_0711/cases.rtf
new file mode 100644
index 0000000..4c44710
--- /dev/null
+++ b/general/datasets/Jax_csb_l_0711/cases.rtf
@@ -0,0 +1,1030 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain ID |
+ HF=high-fat (30% fat)
+ 6C=low-fat (6% fat) |
+ Replicate Animal |
+
+
+ | 1 |
+ GSM264767 |
+ 129S1/SvImJ |
+ 6C |
+ Rep1 |
+
+
+ | 2 |
+ GSM264768 |
+ 129S1/SvImJ |
+ 6C |
+ Rep2 |
+
+
+ | 3 |
+ GSM264769 |
+ 129S1/SvImJ |
+ 6C |
+ Rep3 |
+
+
+ | 4 |
+ GSM264770 |
+ 129S1/SvImJ |
+ HF |
+ Rep1 |
+
+
+ | 5 |
+ GSM264771 |
+ 129S1/SvImJ |
+ HF |
+ Rep2 |
+
+
+ | 6 |
+ GSM264772 |
+ 129S1/SvImJ |
+ HF |
+ Rep3 |
+
+
+ | 7 |
+ GSM264773 |
+ 129S1/SvImJ |
+ 6C |
+ Rep1 |
+
+
+ | 8 |
+ GSM264774 |
+ 129S1/SvImJ |
+ 6C |
+ Rep2 |
+
+
+ | 9 |
+ GSM264775 |
+ 129S1/SvImJ |
+ 6C |
+ Rep3 |
+
+
+ | 10 |
+ GSM264776 |
+ 129S1/SvImJ |
+ HF |
+ Rep1 |
+
+
+ | 11 |
+ GSM264777 |
+ 129S1/SvImJ |
+ HF |
+ Rep2 |
+
+
+ | 12 |
+ GSM264778 |
+ 129S1/SvImJ |
+ HF |
+ Rep3 |
+
+
+ | 13 |
+ GSM264779 |
+ A/J |
+ 6C |
+ Rep1 |
+
+
+ | 14 |
+ GSM264780 |
+ A/J |
+ 6C |
+ Rep2 |
+
+
+ | 15 |
+ GSM264781 |
+ A/J |
+ 6C |
+ Rep3 |
+
+
+ | 16 |
+ GSM264782 |
+ A/J |
+ HF |
+ Rep1 |
+
+
+ | 17 |
+ GSM264783 |
+ A/J |
+ HF |
+ Rep2 |
+
+
+ | 18 |
+ GSM264784 |
+ A/J |
+ HF |
+ Rep3 |
+
+
+ | 19 |
+ GSM264785 |
+ A/J |
+ 6C |
+ Rep1 |
+
+
+ | 20 |
+ GSM264786 |
+ A/J |
+ 6C |
+ Rep2 |
+
+
+ | 21 |
+ GSM264787 |
+ A/J |
+ 6C |
+ Rep3 |
+
+
+ | 22 |
+ GSM264788 |
+ A/J |
+ HF |
+ Rep1 |
+
+
+ | 23 |
+ GSM264789 |
+ A/J |
+ HF |
+ Rep2 |
+
+
+ | 24 |
+ GSM264790 |
+ A/J |
+ HF |
+ Rep3 |
+
+
+ | 25 |
+ GSM264791 |
+ C57BL/6J |
+ 6C |
+ Rep1 |
+
+
+ | 26 |
+ GSM264792 |
+ C57BL/6J |
+ 6C |
+ Rep2 |
+
+
+ | 27 |
+ GSM264793 |
+ C57BL/6J |
+ 6C |
+ Rep3 |
+
+
+ | 28 |
+ GSM264794 |
+ C57BL/6J |
+ HF |
+ Rep1 |
+
+
+ | 29 |
+ GSM264795 |
+ C57BL/6J |
+ HF |
+ Rep2 |
+
+
+ | 30 |
+ GSM264796 |
+ C57BL/6J |
+ HF |
+ Rep3 |
+
+
+ | 31 |
+ GSM264797 |
+ C57BL/6J |
+ 6C |
+ Rep1 |
+
+
+ | 32 |
+ GSM264798 |
+ C57BL/6J |
+ 6C |
+ Rep2 |
+
+
+ | 33 |
+ GSM264799 |
+ C57BL/6J |
+ 6C |
+ Rep3 |
+
+
+ | 34 |
+ GSM264800 |
+ C57BL/6J |
+ HF |
+ Rep1 |
+
+
+ | 35 |
+ GSM264801 |
+ C57BL/6J |
+ HF |
+ Rep2 |
+
+
+ | 36 |
+ GSM264802 |
+ C57BL/6J |
+ HF |
+ Rep3 |
+
+
+ | 37 |
+ GSM264803 |
+ BALB/cJ |
+ 6C |
+ Rep1 |
+
+
+ | 38 |
+ GSM264804 |
+ BALB/cJ |
+ 6C |
+ Rep2 |
+
+
+ | 39 |
+ GSM264805 |
+ BALB/cJ |
+ 6C |
+ Rep3 |
+
+
+ | 40 |
+ GSM264806 |
+ BALB/cJ |
+ HF |
+ Rep1 |
+
+
+ | 41 |
+ GSM264807 |
+ BALB/cJ |
+ HF |
+ Rep2 |
+
+
+ | 42 |
+ GSM264808 |
+ BALB/cJ |
+ HF |
+ Rep3 |
+
+
+ | 43 |
+ GSM264809 |
+ BALB/cJ |
+ 6C |
+ Rep1 |
+
+
+ | 44 |
+ GSM264810 |
+ BALB/cJ |
+ 6C |
+ Rep2 |
+
+
+ | 45 |
+ GSM264811 |
+ BALB/cJ |
+ 6C |
+ Rep3 |
+
+
+ | 46 |
+ GSM264813 |
+ BALB/cJ |
+ HF |
+ Rep1 |
+
+
+ | 47 |
+ GSM264814 |
+ BALB/cJ |
+ HF |
+ Rep2 |
+
+
+ | 48 |
+ GSM264815 |
+ BALB/cJ |
+ HF |
+ Rep3 |
+
+
+ | 49 |
+ GSM264845 |
+ C3H/HeJ |
+ 6C |
+ Rep1 |
+
+
+ | 50 |
+ GSM264846 |
+ C3H/HeJ |
+ 6C |
+ Rep2 |
+
+
+ | 51 |
+ GSM264847 |
+ C3H/HeJ |
+ 6C |
+ Rep3 |
+
+
+ | 52 |
+ GSM264848 |
+ C3H/HeJ |
+ HF |
+ Rep1 |
+
+
+ | 53 |
+ GSM264849 |
+ C3H/HeJ |
+ HF |
+ Rep2 |
+
+
+ | 54 |
+ GSM264850 |
+ C3H/HeJ |
+ HF |
+ Rep3 |
+
+
+ | 55 |
+ GSM264852 |
+ C3H/HeJ |
+ 6C |
+ Rep1 |
+
+
+ | 56 |
+ GSM264853 |
+ C3H/HeJ |
+ 6C |
+ Rep2 |
+
+
+ | 57 |
+ GSM264855 |
+ C3H/HeJ |
+ 6C |
+ Rep3 |
+
+
+ | 58 |
+ GSM264856 |
+ C3H/HeJ |
+ HF |
+ Rep1 |
+
+
+ | 59 |
+ GSM264857 |
+ C3H/HeJ |
+ HF |
+ Rep2 |
+
+
+ | 60 |
+ GSM264858 |
+ C3H/HeJ |
+ HF |
+ Rep3 |
+
+
+ | 61 |
+ GSM264859 |
+ CAST/EiJ |
+ 6C |
+ Rep1 |
+
+
+ | 62 |
+ GSM264861 |
+ CAST/EiJ |
+ 6C |
+ Rep2 |
+
+
+ | 63 |
+ GSM264862 |
+ CAST/EiJ |
+ 6C |
+ Rep3 |
+
+
+ | 64 |
+ GSM264863 |
+ CAST/EiJ |
+ HF |
+ Rep1 |
+
+
+ | 65 |
+ GSM264864 |
+ CAST/EiJ |
+ HF |
+ Rep2 |
+
+
+ | 66 |
+ GSM264865 |
+ CAST/EiJ |
+ HF |
+ Rep3 |
+
+
+ | 67 |
+ GSM264866 |
+ CAST/EiJ |
+ 6C |
+ Rep1 |
+
+
+ | 68 |
+ GSM264867 |
+ CAST/EiJ |
+ 6C |
+ Rep2 |
+
+
+ | 69 |
+ GSM264868 |
+ CAST/EiJ |
+ 6C |
+ Rep3 |
+
+
+ | 70 |
+ GSM264869 |
+ CAST/EiJ |
+ HF |
+ Rep1 |
+
+
+ | 71 |
+ GSM264870 |
+ CAST/EiJ |
+ HF |
+ Rep2 |
+
+
+ | 72 |
+ GSM264871 |
+ CAST/EiJ |
+ HF |
+ Rep3 |
+
+
+ | 73 |
+ GSM264872 |
+ DBA/2J |
+ 6C |
+ Rep1 |
+
+
+ | 74 |
+ GSM264873 |
+ DBA/2J |
+ 6C |
+ Rep2 |
+
+
+ | 75 |
+ GSM264874 |
+ DBA/2J |
+ 6C |
+ Rep3 |
+
+
+ | 76 |
+ GSM264875 |
+ DBA/2J |
+ HF |
+ Rep1 |
+
+
+ | 77 |
+ GSM264876 |
+ DBA/2J |
+ HF |
+ Rep2 |
+
+
+ | 78 |
+ GSM264877 |
+ DBA/2J |
+ HF |
+ Rep3 |
+
+
+ | 79 |
+ GSM264890 |
+ DBA/2J |
+ 6C |
+ Rep1 |
+
+
+ | 80 |
+ GSM264891 |
+ DBA/2J |
+ 6C |
+ Rep2 |
+
+
+ | 81 |
+ GSM264892 |
+ DBA/2J |
+ 6C |
+ Rep3 |
+
+
+ | 82 |
+ GSM264893 |
+ DBA/2J |
+ HF |
+ Rep1 |
+
+
+ | 83 |
+ GSM264894 |
+ DBA/2J |
+ HF |
+ Rep2 |
+
+
+ | 84 |
+ GSM264895 |
+ DBA/2J |
+ HF |
+ Rep3 |
+
+
+ | 85 |
+ GSM264896 |
+ I/LnJ |
+ 6C |
+ Rep1 |
+
+
+ | 86 |
+ GSM264897 |
+ I/LnJ |
+ 6C |
+ Rep2 |
+
+
+ | 87 |
+ GSM264898 |
+ I/LnJ |
+ 6C |
+ Rep3 |
+
+
+ | 88 |
+ GSM264899 |
+ I/LnJ |
+ HF |
+ Rep1 |
+
+
+ | 89 |
+ GSM264900 |
+ I/LnJ |
+ HF |
+ Rep2 |
+
+
+ | 90 |
+ GSM264901 |
+ I/LnJ |
+ HF |
+ Rep3 |
+
+
+ | 91 |
+ GSM264902 |
+ I/LnJ |
+ 6C |
+ Rep1 |
+
+
+ | 92 |
+ GSM264903 |
+ I/LnJ |
+ 6C |
+ Rep2 |
+
+
+ | 93 |
+ GSM264904 |
+ I/LnJ |
+ 6C |
+ Rep3 |
+
+
+ | 94 |
+ GSM264905 |
+ I/LnJ |
+ HF |
+ Rep1 |
+
+
+ | 95 |
+ GSM264906 |
+ I/LnJ |
+ HF |
+ Rep2 |
+
+
+ | 96 |
+ GSM264907 |
+ I/LnJ |
+ HF |
+ Rep3 |
+
+
+ | 97 |
+ GSM264908 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep1 |
+
+
+ | 98 |
+ GSM264909 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep2 |
+
+
+ | 99 |
+ GSM264910 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep3 |
+
+
+ | 100 |
+ GSM264912 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep1 |
+
+
+ | 101 |
+ GSM264913 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep2 |
+
+
+ | 102 |
+ GSM264914 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep3 |
+
+
+ | 103 |
+ GSM264915 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep1 |
+
+
+ | 104 |
+ GSM264916 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep2 |
+
+
+ | 105 |
+ GSM264917 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep3 |
+
+
+ | 106 |
+ GSM264918 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep1 |
+
+
+ | 107 |
+ GSM264920 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep2 |
+
+
+ | 108 |
+ GSM264921 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep3 |
+
+
+ | 109 |
+ GSM264922 |
+ NZB/BlNJ |
+ 6C |
+ Rep1 |
+
+
+ | 110 |
+ GSM264924 |
+ NZB/BlNJ |
+ 6C |
+ Rep2 |
+
+
+ | 111 |
+ GSM264925 |
+ NZB/BlNJ |
+ 6C |
+ Rep3 |
+
+
+ | 112 |
+ GSM264926 |
+ NZB/BlNJ |
+ HF |
+ Rep1 |
+
+
+ | 113 |
+ GSM264928 |
+ NZB/BlNJ |
+ HF |
+ Rep2 |
+
+
+ | 114 |
+ GSM264929 |
+ NZB/BlNJ |
+ HF |
+ Rep3 |
+
+
+ | 115 |
+ GSM264930 |
+ NZB/BlNJ |
+ 6C |
+ Rep1 |
+
+
+ | 116 |
+ GSM264931 |
+ NZB/BlNJ |
+ 6C |
+ Rep2 |
+
+
+ | 117 |
+ GSM264932 |
+ NZB/BlNJ |
+ 6C |
+ Rep3 |
+
+
+ | 118 |
+ GSM264933 |
+ NZB/BlNJ |
+ HF |
+ Rep1 |
+
+
+ | 119 |
+ GSM264935 |
+ NZB/BlNJ |
+ HF |
+ Rep2 |
+
+
+ | 120 |
+ GSM264936 |
+ NZB/BlNJ |
+ HF |
+ Rep3 |
+
+
+ | 121 |
+ GSM265061 |
+ PERA/EiJ |
+ 6C |
+ Rep1 |
+
+
+ | 122 |
+ GSM265062 |
+ PERA/EiJ |
+ 6C |
+ Rep2 |
+
+
+ | 123 |
+ GSM265063 |
+ PERA/EiJ |
+ 6C |
+ Rep3 |
+
+
+ | 124 |
+ GSM265064 |
+ PERA/EiJ |
+ HF |
+ Rep1 |
+
+
+ | 125 |
+ GSM265065 |
+ PERA/EiJ |
+ HF |
+ Rep2 |
+
+
+ | 126 |
+ GSM265066 |
+ PERA/EiJ |
+ HF |
+ Rep3 |
+
+
+ | 127 |
+ GSM265067 |
+ PERA/EiJ |
+ 6C |
+ Rep1 |
+
+
+ | 128 |
+ GSM265068 |
+ PERA/EiJ |
+ 6C |
+ Rep2 |
+
+
+ | 129 |
+ GSM265069 |
+ PERA/EiJ |
+ 6C |
+ Rep3 |
+
+
+ | 130 |
+ GSM265070 |
+ PERA/EiJ |
+ HF |
+ Rep1 |
+
+
+ | 131 |
+ GSM265071 |
+ PERA/EiJ |
+ HF |
+ Rep2 |
+
+
+ | 132 |
+ GSM265072 |
+ PERA/EiJ |
+ HF |
+ Rep3 |
+
+
+ | 133 |
+ GSM265074 |
+ SM/J |
+ 6C |
+ Rep1 |
+
+
+ | 134 |
+ GSM265075 |
+ SM/J |
+ 6C |
+ Rep2 |
+
+
+ | 135 |
+ GSM265105 |
+ SM/J |
+ 6C |
+ Rep3 |
+
+
+ | 136 |
+ GSM265217 |
+ SM/J |
+ HF |
+ Rep1 |
+
+
+ | 137 |
+ GSM265248 |
+ SM/J |
+ HF |
+ Rep2 |
+
+
+ | 138 |
+ GSM265275 |
+ SM/J |
+ HF |
+ Rep3 |
+
+
+ | 139 |
+ GSM265324 |
+ SM/J |
+ 6C |
+ Rep1 |
+
+
+ | 140 |
+ GSM265331 |
+ SM/J |
+ 6C |
+ Rep2 |
+
+
+ | 141 |
+ GSM265357 |
+ SM/J |
+ 6C |
+ Rep3 |
+
+
+ | 142 |
+ GSM265358 |
+ SM/J |
+ HF |
+ Rep1 |
+
+
+ | 143 |
+ GSM265359 |
+ SM/J |
+ HF |
+ Rep2 |
+
+
+ | 144 |
+ GSM265360 |
+ SM/J |
+ HF |
+ Rep3 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Jax_csb_l_0711/citation.rtf b/general/datasets/Jax_csb_l_0711/citation.rtf
new file mode 100644
index 0000000..92dd7b6
--- /dev/null
+++ b/general/datasets/Jax_csb_l_0711/citation.rtf
@@ -0,0 +1 @@
+Burgess-Herbert SL, Cox A, Tsaih SW, Paigen B. Practical applications of the bioinformatics toolbox for narrowing quantitative trait loci. Genetics 2008 Dec;180(4):2227-35. PMID: 18845850 Shockley KR, Witmer D, Burgess-Herbert SL, Paigen B et al. Effects of atherogenic diet on hepatic gene expression across mouse strains. Physiol Genomics 2009 Nov 6;39(3):172-82. PMID: 19671657
diff --git a/general/datasets/Jax_csb_l_0711/contributors.rtf b/general/datasets/Jax_csb_l_0711/contributors.rtf
new file mode 100644
index 0000000..04d1867
--- /dev/null
+++ b/general/datasets/Jax_csb_l_0711/contributors.rtf
@@ -0,0 +1 @@
+Churchill GA, Paigen B, Shockley KR, Witmer D
diff --git a/general/datasets/Jax_csb_l_0711/experiment-design.rtf b/general/datasets/Jax_csb_l_0711/experiment-design.rtf
new file mode 100644
index 0000000..dc5fef5
--- /dev/null
+++ b/general/datasets/Jax_csb_l_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Expression profiling by array.
+
+One group of mice was fed an atherogenic high-fat (30% fat) diet containing cholic acid to increase fat uptake and another was fed a low-fat (6% fat) regular chow diet. Males and females from both diets were studied for mouse strains 129S1/SvImJ, A/J, BALB/cJ, C3H/HeJ, C57BL/6J, CAST/EiJ, DBA/2J, I/LnJ, MRL/MpJ-Tnfrsf6lpr/J, NZB/BINJ, PERA/Ei, and SM/J. All strains were sacrificed between 11- and 13 weeks of age except for CAST and PERA, which were harvested after 50 weeks of age. CAST and PERA were subsequently removed from our analysis based on discrepant harvest age, but can be found in our database (see below). Three replicate animals were used for each combination of diet, strain, and sex, resulting in a total of 120 mice surveyed for gene expression.
diff --git a/general/datasets/Jax_csb_l_0711/experiment-type.rtf b/general/datasets/Jax_csb_l_0711/experiment-type.rtf
new file mode 100644
index 0000000..b8429a3
--- /dev/null
+++ b/general/datasets/Jax_csb_l_0711/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array.
\ No newline at end of file
diff --git a/general/datasets/Jax_csb_l_0711/platform.rtf b/general/datasets/Jax_csb_l_0711/platform.rtf
new file mode 100644
index 0000000..459d486
--- /dev/null
+++ b/general/datasets/Jax_csb_l_0711/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array. Affymetrix submissions are typically submitted to GEO using the GEOarchive method described at http://www.ncbi.nlm.nih.gov/projects/geo/info/geo_affy.html All probe sets represented on the GeneChip Mouse Expression Set 430 are included on the GeneChip Mouse Genome 430 2.0 Array. The sequences from which these probe sets were derived were selected from GenBank«, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 107, June 2002) and then refined by analysis and comparison with the publicly available draft assembly of the mouse genome from the Whitehead Institute for Genome Research (MGSC, April 2002).
diff --git a/general/datasets/Jax_csb_l_0711/summary.rtf b/general/datasets/Jax_csb_l_0711/summary.rtf
new file mode 100644
index 0000000..a06430b
--- /dev/null
+++ b/general/datasets/Jax_csb_l_0711/summary.rtf
@@ -0,0 +1 @@
+High-fat diets are associated with increased obesity and metabolic disease in mice and humans. Here we used analysis of variance (ANOVA) to scrutinize a microarray data set consisting of 10 inbred strains of mice from both sexes fed atherogenic high-fat and control chow diets. An overall F-test was applied to the 40 unique groups of strain-diet-sex to identify 15,288 genes with altered transcription. Bootstrapping k-means clustering separated these changes into four strain-dependent expression patterns, including two sex-related profiles and two diet-related profiles. Sex-induced effects correspond to secretion (males) or fat and energy metabolism (females), whereas diet-induced changes relate to neurological processes (chow) or immune response (high-fat). The full set of pairwise contrasts for differences between strains within sex (90 different statistical tests) uncovered 32,379 total changes. These differences were unevenly distributed across strains and between sexes, indicating that strain-specific responses to high-fat diet differ between sexes. Correlations between expression levels and 8 obesity-related traits identified 5,274 associations between transcript abundance and measured phenotypic endpoints. From this number, 2,678 genes are positively correlated with total cholesterol levels and associate with immune-related categories while 2,596 genes are negatively correlated with cholesterol and connect to cholesterol synthesis. Keywords: gene expression analysis, strain comparision, effect of dietary fat, sex-specific effects
diff --git a/general/datasets/Jax_csb_l_0711/tissue.rtf b/general/datasets/Jax_csb_l_0711/tissue.rtf
new file mode 100644
index 0000000..778c4a2
--- /dev/null
+++ b/general/datasets/Jax_csb_l_0711/tissue.rtf
@@ -0,0 +1 @@
+Liver
diff --git a/general/datasets/Jax_csb_l_6c_0711/acknowledgment.rtf b/general/datasets/Jax_csb_l_6c_0711/acknowledgment.rtf
new file mode 100644
index 0000000..04d1867
--- /dev/null
+++ b/general/datasets/Jax_csb_l_6c_0711/acknowledgment.rtf
@@ -0,0 +1 @@
+Churchill GA, Paigen B, Shockley KR, Witmer D
diff --git a/general/datasets/Jax_csb_l_6c_0711/cases.rtf b/general/datasets/Jax_csb_l_6c_0711/cases.rtf
new file mode 100644
index 0000000..4c44710
--- /dev/null
+++ b/general/datasets/Jax_csb_l_6c_0711/cases.rtf
@@ -0,0 +1,1030 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain ID |
+ HF=high-fat (30% fat)
+ 6C=low-fat (6% fat) |
+ Replicate Animal |
+
+
+ | 1 |
+ GSM264767 |
+ 129S1/SvImJ |
+ 6C |
+ Rep1 |
+
+
+ | 2 |
+ GSM264768 |
+ 129S1/SvImJ |
+ 6C |
+ Rep2 |
+
+
+ | 3 |
+ GSM264769 |
+ 129S1/SvImJ |
+ 6C |
+ Rep3 |
+
+
+ | 4 |
+ GSM264770 |
+ 129S1/SvImJ |
+ HF |
+ Rep1 |
+
+
+ | 5 |
+ GSM264771 |
+ 129S1/SvImJ |
+ HF |
+ Rep2 |
+
+
+ | 6 |
+ GSM264772 |
+ 129S1/SvImJ |
+ HF |
+ Rep3 |
+
+
+ | 7 |
+ GSM264773 |
+ 129S1/SvImJ |
+ 6C |
+ Rep1 |
+
+
+ | 8 |
+ GSM264774 |
+ 129S1/SvImJ |
+ 6C |
+ Rep2 |
+
+
+ | 9 |
+ GSM264775 |
+ 129S1/SvImJ |
+ 6C |
+ Rep3 |
+
+
+ | 10 |
+ GSM264776 |
+ 129S1/SvImJ |
+ HF |
+ Rep1 |
+
+
+ | 11 |
+ GSM264777 |
+ 129S1/SvImJ |
+ HF |
+ Rep2 |
+
+
+ | 12 |
+ GSM264778 |
+ 129S1/SvImJ |
+ HF |
+ Rep3 |
+
+
+ | 13 |
+ GSM264779 |
+ A/J |
+ 6C |
+ Rep1 |
+
+
+ | 14 |
+ GSM264780 |
+ A/J |
+ 6C |
+ Rep2 |
+
+
+ | 15 |
+ GSM264781 |
+ A/J |
+ 6C |
+ Rep3 |
+
+
+ | 16 |
+ GSM264782 |
+ A/J |
+ HF |
+ Rep1 |
+
+
+ | 17 |
+ GSM264783 |
+ A/J |
+ HF |
+ Rep2 |
+
+
+ | 18 |
+ GSM264784 |
+ A/J |
+ HF |
+ Rep3 |
+
+
+ | 19 |
+ GSM264785 |
+ A/J |
+ 6C |
+ Rep1 |
+
+
+ | 20 |
+ GSM264786 |
+ A/J |
+ 6C |
+ Rep2 |
+
+
+ | 21 |
+ GSM264787 |
+ A/J |
+ 6C |
+ Rep3 |
+
+
+ | 22 |
+ GSM264788 |
+ A/J |
+ HF |
+ Rep1 |
+
+
+ | 23 |
+ GSM264789 |
+ A/J |
+ HF |
+ Rep2 |
+
+
+ | 24 |
+ GSM264790 |
+ A/J |
+ HF |
+ Rep3 |
+
+
+ | 25 |
+ GSM264791 |
+ C57BL/6J |
+ 6C |
+ Rep1 |
+
+
+ | 26 |
+ GSM264792 |
+ C57BL/6J |
+ 6C |
+ Rep2 |
+
+
+ | 27 |
+ GSM264793 |
+ C57BL/6J |
+ 6C |
+ Rep3 |
+
+
+ | 28 |
+ GSM264794 |
+ C57BL/6J |
+ HF |
+ Rep1 |
+
+
+ | 29 |
+ GSM264795 |
+ C57BL/6J |
+ HF |
+ Rep2 |
+
+
+ | 30 |
+ GSM264796 |
+ C57BL/6J |
+ HF |
+ Rep3 |
+
+
+ | 31 |
+ GSM264797 |
+ C57BL/6J |
+ 6C |
+ Rep1 |
+
+
+ | 32 |
+ GSM264798 |
+ C57BL/6J |
+ 6C |
+ Rep2 |
+
+
+ | 33 |
+ GSM264799 |
+ C57BL/6J |
+ 6C |
+ Rep3 |
+
+
+ | 34 |
+ GSM264800 |
+ C57BL/6J |
+ HF |
+ Rep1 |
+
+
+ | 35 |
+ GSM264801 |
+ C57BL/6J |
+ HF |
+ Rep2 |
+
+
+ | 36 |
+ GSM264802 |
+ C57BL/6J |
+ HF |
+ Rep3 |
+
+
+ | 37 |
+ GSM264803 |
+ BALB/cJ |
+ 6C |
+ Rep1 |
+
+
+ | 38 |
+ GSM264804 |
+ BALB/cJ |
+ 6C |
+ Rep2 |
+
+
+ | 39 |
+ GSM264805 |
+ BALB/cJ |
+ 6C |
+ Rep3 |
+
+
+ | 40 |
+ GSM264806 |
+ BALB/cJ |
+ HF |
+ Rep1 |
+
+
+ | 41 |
+ GSM264807 |
+ BALB/cJ |
+ HF |
+ Rep2 |
+
+
+ | 42 |
+ GSM264808 |
+ BALB/cJ |
+ HF |
+ Rep3 |
+
+
+ | 43 |
+ GSM264809 |
+ BALB/cJ |
+ 6C |
+ Rep1 |
+
+
+ | 44 |
+ GSM264810 |
+ BALB/cJ |
+ 6C |
+ Rep2 |
+
+
+ | 45 |
+ GSM264811 |
+ BALB/cJ |
+ 6C |
+ Rep3 |
+
+
+ | 46 |
+ GSM264813 |
+ BALB/cJ |
+ HF |
+ Rep1 |
+
+
+ | 47 |
+ GSM264814 |
+ BALB/cJ |
+ HF |
+ Rep2 |
+
+
+ | 48 |
+ GSM264815 |
+ BALB/cJ |
+ HF |
+ Rep3 |
+
+
+ | 49 |
+ GSM264845 |
+ C3H/HeJ |
+ 6C |
+ Rep1 |
+
+
+ | 50 |
+ GSM264846 |
+ C3H/HeJ |
+ 6C |
+ Rep2 |
+
+
+ | 51 |
+ GSM264847 |
+ C3H/HeJ |
+ 6C |
+ Rep3 |
+
+
+ | 52 |
+ GSM264848 |
+ C3H/HeJ |
+ HF |
+ Rep1 |
+
+
+ | 53 |
+ GSM264849 |
+ C3H/HeJ |
+ HF |
+ Rep2 |
+
+
+ | 54 |
+ GSM264850 |
+ C3H/HeJ |
+ HF |
+ Rep3 |
+
+
+ | 55 |
+ GSM264852 |
+ C3H/HeJ |
+ 6C |
+ Rep1 |
+
+
+ | 56 |
+ GSM264853 |
+ C3H/HeJ |
+ 6C |
+ Rep2 |
+
+
+ | 57 |
+ GSM264855 |
+ C3H/HeJ |
+ 6C |
+ Rep3 |
+
+
+ | 58 |
+ GSM264856 |
+ C3H/HeJ |
+ HF |
+ Rep1 |
+
+
+ | 59 |
+ GSM264857 |
+ C3H/HeJ |
+ HF |
+ Rep2 |
+
+
+ | 60 |
+ GSM264858 |
+ C3H/HeJ |
+ HF |
+ Rep3 |
+
+
+ | 61 |
+ GSM264859 |
+ CAST/EiJ |
+ 6C |
+ Rep1 |
+
+
+ | 62 |
+ GSM264861 |
+ CAST/EiJ |
+ 6C |
+ Rep2 |
+
+
+ | 63 |
+ GSM264862 |
+ CAST/EiJ |
+ 6C |
+ Rep3 |
+
+
+ | 64 |
+ GSM264863 |
+ CAST/EiJ |
+ HF |
+ Rep1 |
+
+
+ | 65 |
+ GSM264864 |
+ CAST/EiJ |
+ HF |
+ Rep2 |
+
+
+ | 66 |
+ GSM264865 |
+ CAST/EiJ |
+ HF |
+ Rep3 |
+
+
+ | 67 |
+ GSM264866 |
+ CAST/EiJ |
+ 6C |
+ Rep1 |
+
+
+ | 68 |
+ GSM264867 |
+ CAST/EiJ |
+ 6C |
+ Rep2 |
+
+
+ | 69 |
+ GSM264868 |
+ CAST/EiJ |
+ 6C |
+ Rep3 |
+
+
+ | 70 |
+ GSM264869 |
+ CAST/EiJ |
+ HF |
+ Rep1 |
+
+
+ | 71 |
+ GSM264870 |
+ CAST/EiJ |
+ HF |
+ Rep2 |
+
+
+ | 72 |
+ GSM264871 |
+ CAST/EiJ |
+ HF |
+ Rep3 |
+
+
+ | 73 |
+ GSM264872 |
+ DBA/2J |
+ 6C |
+ Rep1 |
+
+
+ | 74 |
+ GSM264873 |
+ DBA/2J |
+ 6C |
+ Rep2 |
+
+
+ | 75 |
+ GSM264874 |
+ DBA/2J |
+ 6C |
+ Rep3 |
+
+
+ | 76 |
+ GSM264875 |
+ DBA/2J |
+ HF |
+ Rep1 |
+
+
+ | 77 |
+ GSM264876 |
+ DBA/2J |
+ HF |
+ Rep2 |
+
+
+ | 78 |
+ GSM264877 |
+ DBA/2J |
+ HF |
+ Rep3 |
+
+
+ | 79 |
+ GSM264890 |
+ DBA/2J |
+ 6C |
+ Rep1 |
+
+
+ | 80 |
+ GSM264891 |
+ DBA/2J |
+ 6C |
+ Rep2 |
+
+
+ | 81 |
+ GSM264892 |
+ DBA/2J |
+ 6C |
+ Rep3 |
+
+
+ | 82 |
+ GSM264893 |
+ DBA/2J |
+ HF |
+ Rep1 |
+
+
+ | 83 |
+ GSM264894 |
+ DBA/2J |
+ HF |
+ Rep2 |
+
+
+ | 84 |
+ GSM264895 |
+ DBA/2J |
+ HF |
+ Rep3 |
+
+
+ | 85 |
+ GSM264896 |
+ I/LnJ |
+ 6C |
+ Rep1 |
+
+
+ | 86 |
+ GSM264897 |
+ I/LnJ |
+ 6C |
+ Rep2 |
+
+
+ | 87 |
+ GSM264898 |
+ I/LnJ |
+ 6C |
+ Rep3 |
+
+
+ | 88 |
+ GSM264899 |
+ I/LnJ |
+ HF |
+ Rep1 |
+
+
+ | 89 |
+ GSM264900 |
+ I/LnJ |
+ HF |
+ Rep2 |
+
+
+ | 90 |
+ GSM264901 |
+ I/LnJ |
+ HF |
+ Rep3 |
+
+
+ | 91 |
+ GSM264902 |
+ I/LnJ |
+ 6C |
+ Rep1 |
+
+
+ | 92 |
+ GSM264903 |
+ I/LnJ |
+ 6C |
+ Rep2 |
+
+
+ | 93 |
+ GSM264904 |
+ I/LnJ |
+ 6C |
+ Rep3 |
+
+
+ | 94 |
+ GSM264905 |
+ I/LnJ |
+ HF |
+ Rep1 |
+
+
+ | 95 |
+ GSM264906 |
+ I/LnJ |
+ HF |
+ Rep2 |
+
+
+ | 96 |
+ GSM264907 |
+ I/LnJ |
+ HF |
+ Rep3 |
+
+
+ | 97 |
+ GSM264908 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep1 |
+
+
+ | 98 |
+ GSM264909 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep2 |
+
+
+ | 99 |
+ GSM264910 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep3 |
+
+
+ | 100 |
+ GSM264912 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep1 |
+
+
+ | 101 |
+ GSM264913 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep2 |
+
+
+ | 102 |
+ GSM264914 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep3 |
+
+
+ | 103 |
+ GSM264915 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep1 |
+
+
+ | 104 |
+ GSM264916 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep2 |
+
+
+ | 105 |
+ GSM264917 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep3 |
+
+
+ | 106 |
+ GSM264918 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep1 |
+
+
+ | 107 |
+ GSM264920 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep2 |
+
+
+ | 108 |
+ GSM264921 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep3 |
+
+
+ | 109 |
+ GSM264922 |
+ NZB/BlNJ |
+ 6C |
+ Rep1 |
+
+
+ | 110 |
+ GSM264924 |
+ NZB/BlNJ |
+ 6C |
+ Rep2 |
+
+
+ | 111 |
+ GSM264925 |
+ NZB/BlNJ |
+ 6C |
+ Rep3 |
+
+
+ | 112 |
+ GSM264926 |
+ NZB/BlNJ |
+ HF |
+ Rep1 |
+
+
+ | 113 |
+ GSM264928 |
+ NZB/BlNJ |
+ HF |
+ Rep2 |
+
+
+ | 114 |
+ GSM264929 |
+ NZB/BlNJ |
+ HF |
+ Rep3 |
+
+
+ | 115 |
+ GSM264930 |
+ NZB/BlNJ |
+ 6C |
+ Rep1 |
+
+
+ | 116 |
+ GSM264931 |
+ NZB/BlNJ |
+ 6C |
+ Rep2 |
+
+
+ | 117 |
+ GSM264932 |
+ NZB/BlNJ |
+ 6C |
+ Rep3 |
+
+
+ | 118 |
+ GSM264933 |
+ NZB/BlNJ |
+ HF |
+ Rep1 |
+
+
+ | 119 |
+ GSM264935 |
+ NZB/BlNJ |
+ HF |
+ Rep2 |
+
+
+ | 120 |
+ GSM264936 |
+ NZB/BlNJ |
+ HF |
+ Rep3 |
+
+
+ | 121 |
+ GSM265061 |
+ PERA/EiJ |
+ 6C |
+ Rep1 |
+
+
+ | 122 |
+ GSM265062 |
+ PERA/EiJ |
+ 6C |
+ Rep2 |
+
+
+ | 123 |
+ GSM265063 |
+ PERA/EiJ |
+ 6C |
+ Rep3 |
+
+
+ | 124 |
+ GSM265064 |
+ PERA/EiJ |
+ HF |
+ Rep1 |
+
+
+ | 125 |
+ GSM265065 |
+ PERA/EiJ |
+ HF |
+ Rep2 |
+
+
+ | 126 |
+ GSM265066 |
+ PERA/EiJ |
+ HF |
+ Rep3 |
+
+
+ | 127 |
+ GSM265067 |
+ PERA/EiJ |
+ 6C |
+ Rep1 |
+
+
+ | 128 |
+ GSM265068 |
+ PERA/EiJ |
+ 6C |
+ Rep2 |
+
+
+ | 129 |
+ GSM265069 |
+ PERA/EiJ |
+ 6C |
+ Rep3 |
+
+
+ | 130 |
+ GSM265070 |
+ PERA/EiJ |
+ HF |
+ Rep1 |
+
+
+ | 131 |
+ GSM265071 |
+ PERA/EiJ |
+ HF |
+ Rep2 |
+
+
+ | 132 |
+ GSM265072 |
+ PERA/EiJ |
+ HF |
+ Rep3 |
+
+
+ | 133 |
+ GSM265074 |
+ SM/J |
+ 6C |
+ Rep1 |
+
+
+ | 134 |
+ GSM265075 |
+ SM/J |
+ 6C |
+ Rep2 |
+
+
+ | 135 |
+ GSM265105 |
+ SM/J |
+ 6C |
+ Rep3 |
+
+
+ | 136 |
+ GSM265217 |
+ SM/J |
+ HF |
+ Rep1 |
+
+
+ | 137 |
+ GSM265248 |
+ SM/J |
+ HF |
+ Rep2 |
+
+
+ | 138 |
+ GSM265275 |
+ SM/J |
+ HF |
+ Rep3 |
+
+
+ | 139 |
+ GSM265324 |
+ SM/J |
+ 6C |
+ Rep1 |
+
+
+ | 140 |
+ GSM265331 |
+ SM/J |
+ 6C |
+ Rep2 |
+
+
+ | 141 |
+ GSM265357 |
+ SM/J |
+ 6C |
+ Rep3 |
+
+
+ | 142 |
+ GSM265358 |
+ SM/J |
+ HF |
+ Rep1 |
+
+
+ | 143 |
+ GSM265359 |
+ SM/J |
+ HF |
+ Rep2 |
+
+
+ | 144 |
+ GSM265360 |
+ SM/J |
+ HF |
+ Rep3 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Jax_csb_l_6c_0711/citation.rtf b/general/datasets/Jax_csb_l_6c_0711/citation.rtf
new file mode 100644
index 0000000..92dd7b6
--- /dev/null
+++ b/general/datasets/Jax_csb_l_6c_0711/citation.rtf
@@ -0,0 +1 @@
+Burgess-Herbert SL, Cox A, Tsaih SW, Paigen B. Practical applications of the bioinformatics toolbox for narrowing quantitative trait loci. Genetics 2008 Dec;180(4):2227-35. PMID: 18845850 Shockley KR, Witmer D, Burgess-Herbert SL, Paigen B et al. Effects of atherogenic diet on hepatic gene expression across mouse strains. Physiol Genomics 2009 Nov 6;39(3):172-82. PMID: 19671657
diff --git a/general/datasets/Jax_csb_l_6c_0711/contributors.rtf b/general/datasets/Jax_csb_l_6c_0711/contributors.rtf
new file mode 100644
index 0000000..04d1867
--- /dev/null
+++ b/general/datasets/Jax_csb_l_6c_0711/contributors.rtf
@@ -0,0 +1 @@
+Churchill GA, Paigen B, Shockley KR, Witmer D
diff --git a/general/datasets/Jax_csb_l_6c_0711/experiment-design.rtf b/general/datasets/Jax_csb_l_6c_0711/experiment-design.rtf
new file mode 100644
index 0000000..dc5fef5
--- /dev/null
+++ b/general/datasets/Jax_csb_l_6c_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Expression profiling by array.
+
+One group of mice was fed an atherogenic high-fat (30% fat) diet containing cholic acid to increase fat uptake and another was fed a low-fat (6% fat) regular chow diet. Males and females from both diets were studied for mouse strains 129S1/SvImJ, A/J, BALB/cJ, C3H/HeJ, C57BL/6J, CAST/EiJ, DBA/2J, I/LnJ, MRL/MpJ-Tnfrsf6lpr/J, NZB/BINJ, PERA/Ei, and SM/J. All strains were sacrificed between 11- and 13 weeks of age except for CAST and PERA, which were harvested after 50 weeks of age. CAST and PERA were subsequently removed from our analysis based on discrepant harvest age, but can be found in our database (see below). Three replicate animals were used for each combination of diet, strain, and sex, resulting in a total of 120 mice surveyed for gene expression.
diff --git a/general/datasets/Jax_csb_l_6c_0711/experiment-type.rtf b/general/datasets/Jax_csb_l_6c_0711/experiment-type.rtf
new file mode 100644
index 0000000..b8429a3
--- /dev/null
+++ b/general/datasets/Jax_csb_l_6c_0711/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array.
\ No newline at end of file
diff --git a/general/datasets/Jax_csb_l_6c_0711/platform.rtf b/general/datasets/Jax_csb_l_6c_0711/platform.rtf
new file mode 100644
index 0000000..459d486
--- /dev/null
+++ b/general/datasets/Jax_csb_l_6c_0711/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array. Affymetrix submissions are typically submitted to GEO using the GEOarchive method described at http://www.ncbi.nlm.nih.gov/projects/geo/info/geo_affy.html All probe sets represented on the GeneChip Mouse Expression Set 430 are included on the GeneChip Mouse Genome 430 2.0 Array. The sequences from which these probe sets were derived were selected from GenBank«, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 107, June 2002) and then refined by analysis and comparison with the publicly available draft assembly of the mouse genome from the Whitehead Institute for Genome Research (MGSC, April 2002).
diff --git a/general/datasets/Jax_csb_l_6c_0711/summary.rtf b/general/datasets/Jax_csb_l_6c_0711/summary.rtf
new file mode 100644
index 0000000..a06430b
--- /dev/null
+++ b/general/datasets/Jax_csb_l_6c_0711/summary.rtf
@@ -0,0 +1 @@
+High-fat diets are associated with increased obesity and metabolic disease in mice and humans. Here we used analysis of variance (ANOVA) to scrutinize a microarray data set consisting of 10 inbred strains of mice from both sexes fed atherogenic high-fat and control chow diets. An overall F-test was applied to the 40 unique groups of strain-diet-sex to identify 15,288 genes with altered transcription. Bootstrapping k-means clustering separated these changes into four strain-dependent expression patterns, including two sex-related profiles and two diet-related profiles. Sex-induced effects correspond to secretion (males) or fat and energy metabolism (females), whereas diet-induced changes relate to neurological processes (chow) or immune response (high-fat). The full set of pairwise contrasts for differences between strains within sex (90 different statistical tests) uncovered 32,379 total changes. These differences were unevenly distributed across strains and between sexes, indicating that strain-specific responses to high-fat diet differ between sexes. Correlations between expression levels and 8 obesity-related traits identified 5,274 associations between transcript abundance and measured phenotypic endpoints. From this number, 2,678 genes are positively correlated with total cholesterol levels and associate with immune-related categories while 2,596 genes are negatively correlated with cholesterol and connect to cholesterol synthesis. Keywords: gene expression analysis, strain comparision, effect of dietary fat, sex-specific effects
diff --git a/general/datasets/Jax_csb_l_6c_0711/tissue.rtf b/general/datasets/Jax_csb_l_6c_0711/tissue.rtf
new file mode 100644
index 0000000..778c4a2
--- /dev/null
+++ b/general/datasets/Jax_csb_l_6c_0711/tissue.rtf
@@ -0,0 +1 @@
+Liver
diff --git a/general/datasets/Jax_csb_l_hf_0711/acknowledgment.rtf b/general/datasets/Jax_csb_l_hf_0711/acknowledgment.rtf
new file mode 100644
index 0000000..04d1867
--- /dev/null
+++ b/general/datasets/Jax_csb_l_hf_0711/acknowledgment.rtf
@@ -0,0 +1 @@
+Churchill GA, Paigen B, Shockley KR, Witmer D
diff --git a/general/datasets/Jax_csb_l_hf_0711/cases.rtf b/general/datasets/Jax_csb_l_hf_0711/cases.rtf
new file mode 100644
index 0000000..4c44710
--- /dev/null
+++ b/general/datasets/Jax_csb_l_hf_0711/cases.rtf
@@ -0,0 +1,1030 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain ID |
+ HF=high-fat (30% fat)
+ 6C=low-fat (6% fat) |
+ Replicate Animal |
+
+
+ | 1 |
+ GSM264767 |
+ 129S1/SvImJ |
+ 6C |
+ Rep1 |
+
+
+ | 2 |
+ GSM264768 |
+ 129S1/SvImJ |
+ 6C |
+ Rep2 |
+
+
+ | 3 |
+ GSM264769 |
+ 129S1/SvImJ |
+ 6C |
+ Rep3 |
+
+
+ | 4 |
+ GSM264770 |
+ 129S1/SvImJ |
+ HF |
+ Rep1 |
+
+
+ | 5 |
+ GSM264771 |
+ 129S1/SvImJ |
+ HF |
+ Rep2 |
+
+
+ | 6 |
+ GSM264772 |
+ 129S1/SvImJ |
+ HF |
+ Rep3 |
+
+
+ | 7 |
+ GSM264773 |
+ 129S1/SvImJ |
+ 6C |
+ Rep1 |
+
+
+ | 8 |
+ GSM264774 |
+ 129S1/SvImJ |
+ 6C |
+ Rep2 |
+
+
+ | 9 |
+ GSM264775 |
+ 129S1/SvImJ |
+ 6C |
+ Rep3 |
+
+
+ | 10 |
+ GSM264776 |
+ 129S1/SvImJ |
+ HF |
+ Rep1 |
+
+
+ | 11 |
+ GSM264777 |
+ 129S1/SvImJ |
+ HF |
+ Rep2 |
+
+
+ | 12 |
+ GSM264778 |
+ 129S1/SvImJ |
+ HF |
+ Rep3 |
+
+
+ | 13 |
+ GSM264779 |
+ A/J |
+ 6C |
+ Rep1 |
+
+
+ | 14 |
+ GSM264780 |
+ A/J |
+ 6C |
+ Rep2 |
+
+
+ | 15 |
+ GSM264781 |
+ A/J |
+ 6C |
+ Rep3 |
+
+
+ | 16 |
+ GSM264782 |
+ A/J |
+ HF |
+ Rep1 |
+
+
+ | 17 |
+ GSM264783 |
+ A/J |
+ HF |
+ Rep2 |
+
+
+ | 18 |
+ GSM264784 |
+ A/J |
+ HF |
+ Rep3 |
+
+
+ | 19 |
+ GSM264785 |
+ A/J |
+ 6C |
+ Rep1 |
+
+
+ | 20 |
+ GSM264786 |
+ A/J |
+ 6C |
+ Rep2 |
+
+
+ | 21 |
+ GSM264787 |
+ A/J |
+ 6C |
+ Rep3 |
+
+
+ | 22 |
+ GSM264788 |
+ A/J |
+ HF |
+ Rep1 |
+
+
+ | 23 |
+ GSM264789 |
+ A/J |
+ HF |
+ Rep2 |
+
+
+ | 24 |
+ GSM264790 |
+ A/J |
+ HF |
+ Rep3 |
+
+
+ | 25 |
+ GSM264791 |
+ C57BL/6J |
+ 6C |
+ Rep1 |
+
+
+ | 26 |
+ GSM264792 |
+ C57BL/6J |
+ 6C |
+ Rep2 |
+
+
+ | 27 |
+ GSM264793 |
+ C57BL/6J |
+ 6C |
+ Rep3 |
+
+
+ | 28 |
+ GSM264794 |
+ C57BL/6J |
+ HF |
+ Rep1 |
+
+
+ | 29 |
+ GSM264795 |
+ C57BL/6J |
+ HF |
+ Rep2 |
+
+
+ | 30 |
+ GSM264796 |
+ C57BL/6J |
+ HF |
+ Rep3 |
+
+
+ | 31 |
+ GSM264797 |
+ C57BL/6J |
+ 6C |
+ Rep1 |
+
+
+ | 32 |
+ GSM264798 |
+ C57BL/6J |
+ 6C |
+ Rep2 |
+
+
+ | 33 |
+ GSM264799 |
+ C57BL/6J |
+ 6C |
+ Rep3 |
+
+
+ | 34 |
+ GSM264800 |
+ C57BL/6J |
+ HF |
+ Rep1 |
+
+
+ | 35 |
+ GSM264801 |
+ C57BL/6J |
+ HF |
+ Rep2 |
+
+
+ | 36 |
+ GSM264802 |
+ C57BL/6J |
+ HF |
+ Rep3 |
+
+
+ | 37 |
+ GSM264803 |
+ BALB/cJ |
+ 6C |
+ Rep1 |
+
+
+ | 38 |
+ GSM264804 |
+ BALB/cJ |
+ 6C |
+ Rep2 |
+
+
+ | 39 |
+ GSM264805 |
+ BALB/cJ |
+ 6C |
+ Rep3 |
+
+
+ | 40 |
+ GSM264806 |
+ BALB/cJ |
+ HF |
+ Rep1 |
+
+
+ | 41 |
+ GSM264807 |
+ BALB/cJ |
+ HF |
+ Rep2 |
+
+
+ | 42 |
+ GSM264808 |
+ BALB/cJ |
+ HF |
+ Rep3 |
+
+
+ | 43 |
+ GSM264809 |
+ BALB/cJ |
+ 6C |
+ Rep1 |
+
+
+ | 44 |
+ GSM264810 |
+ BALB/cJ |
+ 6C |
+ Rep2 |
+
+
+ | 45 |
+ GSM264811 |
+ BALB/cJ |
+ 6C |
+ Rep3 |
+
+
+ | 46 |
+ GSM264813 |
+ BALB/cJ |
+ HF |
+ Rep1 |
+
+
+ | 47 |
+ GSM264814 |
+ BALB/cJ |
+ HF |
+ Rep2 |
+
+
+ | 48 |
+ GSM264815 |
+ BALB/cJ |
+ HF |
+ Rep3 |
+
+
+ | 49 |
+ GSM264845 |
+ C3H/HeJ |
+ 6C |
+ Rep1 |
+
+
+ | 50 |
+ GSM264846 |
+ C3H/HeJ |
+ 6C |
+ Rep2 |
+
+
+ | 51 |
+ GSM264847 |
+ C3H/HeJ |
+ 6C |
+ Rep3 |
+
+
+ | 52 |
+ GSM264848 |
+ C3H/HeJ |
+ HF |
+ Rep1 |
+
+
+ | 53 |
+ GSM264849 |
+ C3H/HeJ |
+ HF |
+ Rep2 |
+
+
+ | 54 |
+ GSM264850 |
+ C3H/HeJ |
+ HF |
+ Rep3 |
+
+
+ | 55 |
+ GSM264852 |
+ C3H/HeJ |
+ 6C |
+ Rep1 |
+
+
+ | 56 |
+ GSM264853 |
+ C3H/HeJ |
+ 6C |
+ Rep2 |
+
+
+ | 57 |
+ GSM264855 |
+ C3H/HeJ |
+ 6C |
+ Rep3 |
+
+
+ | 58 |
+ GSM264856 |
+ C3H/HeJ |
+ HF |
+ Rep1 |
+
+
+ | 59 |
+ GSM264857 |
+ C3H/HeJ |
+ HF |
+ Rep2 |
+
+
+ | 60 |
+ GSM264858 |
+ C3H/HeJ |
+ HF |
+ Rep3 |
+
+
+ | 61 |
+ GSM264859 |
+ CAST/EiJ |
+ 6C |
+ Rep1 |
+
+
+ | 62 |
+ GSM264861 |
+ CAST/EiJ |
+ 6C |
+ Rep2 |
+
+
+ | 63 |
+ GSM264862 |
+ CAST/EiJ |
+ 6C |
+ Rep3 |
+
+
+ | 64 |
+ GSM264863 |
+ CAST/EiJ |
+ HF |
+ Rep1 |
+
+
+ | 65 |
+ GSM264864 |
+ CAST/EiJ |
+ HF |
+ Rep2 |
+
+
+ | 66 |
+ GSM264865 |
+ CAST/EiJ |
+ HF |
+ Rep3 |
+
+
+ | 67 |
+ GSM264866 |
+ CAST/EiJ |
+ 6C |
+ Rep1 |
+
+
+ | 68 |
+ GSM264867 |
+ CAST/EiJ |
+ 6C |
+ Rep2 |
+
+
+ | 69 |
+ GSM264868 |
+ CAST/EiJ |
+ 6C |
+ Rep3 |
+
+
+ | 70 |
+ GSM264869 |
+ CAST/EiJ |
+ HF |
+ Rep1 |
+
+
+ | 71 |
+ GSM264870 |
+ CAST/EiJ |
+ HF |
+ Rep2 |
+
+
+ | 72 |
+ GSM264871 |
+ CAST/EiJ |
+ HF |
+ Rep3 |
+
+
+ | 73 |
+ GSM264872 |
+ DBA/2J |
+ 6C |
+ Rep1 |
+
+
+ | 74 |
+ GSM264873 |
+ DBA/2J |
+ 6C |
+ Rep2 |
+
+
+ | 75 |
+ GSM264874 |
+ DBA/2J |
+ 6C |
+ Rep3 |
+
+
+ | 76 |
+ GSM264875 |
+ DBA/2J |
+ HF |
+ Rep1 |
+
+
+ | 77 |
+ GSM264876 |
+ DBA/2J |
+ HF |
+ Rep2 |
+
+
+ | 78 |
+ GSM264877 |
+ DBA/2J |
+ HF |
+ Rep3 |
+
+
+ | 79 |
+ GSM264890 |
+ DBA/2J |
+ 6C |
+ Rep1 |
+
+
+ | 80 |
+ GSM264891 |
+ DBA/2J |
+ 6C |
+ Rep2 |
+
+
+ | 81 |
+ GSM264892 |
+ DBA/2J |
+ 6C |
+ Rep3 |
+
+
+ | 82 |
+ GSM264893 |
+ DBA/2J |
+ HF |
+ Rep1 |
+
+
+ | 83 |
+ GSM264894 |
+ DBA/2J |
+ HF |
+ Rep2 |
+
+
+ | 84 |
+ GSM264895 |
+ DBA/2J |
+ HF |
+ Rep3 |
+
+
+ | 85 |
+ GSM264896 |
+ I/LnJ |
+ 6C |
+ Rep1 |
+
+
+ | 86 |
+ GSM264897 |
+ I/LnJ |
+ 6C |
+ Rep2 |
+
+
+ | 87 |
+ GSM264898 |
+ I/LnJ |
+ 6C |
+ Rep3 |
+
+
+ | 88 |
+ GSM264899 |
+ I/LnJ |
+ HF |
+ Rep1 |
+
+
+ | 89 |
+ GSM264900 |
+ I/LnJ |
+ HF |
+ Rep2 |
+
+
+ | 90 |
+ GSM264901 |
+ I/LnJ |
+ HF |
+ Rep3 |
+
+
+ | 91 |
+ GSM264902 |
+ I/LnJ |
+ 6C |
+ Rep1 |
+
+
+ | 92 |
+ GSM264903 |
+ I/LnJ |
+ 6C |
+ Rep2 |
+
+
+ | 93 |
+ GSM264904 |
+ I/LnJ |
+ 6C |
+ Rep3 |
+
+
+ | 94 |
+ GSM264905 |
+ I/LnJ |
+ HF |
+ Rep1 |
+
+
+ | 95 |
+ GSM264906 |
+ I/LnJ |
+ HF |
+ Rep2 |
+
+
+ | 96 |
+ GSM264907 |
+ I/LnJ |
+ HF |
+ Rep3 |
+
+
+ | 97 |
+ GSM264908 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep1 |
+
+
+ | 98 |
+ GSM264909 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep2 |
+
+
+ | 99 |
+ GSM264910 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep3 |
+
+
+ | 100 |
+ GSM264912 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep1 |
+
+
+ | 101 |
+ GSM264913 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep2 |
+
+
+ | 102 |
+ GSM264914 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep3 |
+
+
+ | 103 |
+ GSM264915 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep1 |
+
+
+ | 104 |
+ GSM264916 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep2 |
+
+
+ | 105 |
+ GSM264917 |
+ MRL/MpJ-Fas/J |
+ 6C |
+ Rep3 |
+
+
+ | 106 |
+ GSM264918 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep1 |
+
+
+ | 107 |
+ GSM264920 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep2 |
+
+
+ | 108 |
+ GSM264921 |
+ MRL/MpJ-Fas/J |
+ HF |
+ Rep3 |
+
+
+ | 109 |
+ GSM264922 |
+ NZB/BlNJ |
+ 6C |
+ Rep1 |
+
+
+ | 110 |
+ GSM264924 |
+ NZB/BlNJ |
+ 6C |
+ Rep2 |
+
+
+ | 111 |
+ GSM264925 |
+ NZB/BlNJ |
+ 6C |
+ Rep3 |
+
+
+ | 112 |
+ GSM264926 |
+ NZB/BlNJ |
+ HF |
+ Rep1 |
+
+
+ | 113 |
+ GSM264928 |
+ NZB/BlNJ |
+ HF |
+ Rep2 |
+
+
+ | 114 |
+ GSM264929 |
+ NZB/BlNJ |
+ HF |
+ Rep3 |
+
+
+ | 115 |
+ GSM264930 |
+ NZB/BlNJ |
+ 6C |
+ Rep1 |
+
+
+ | 116 |
+ GSM264931 |
+ NZB/BlNJ |
+ 6C |
+ Rep2 |
+
+
+ | 117 |
+ GSM264932 |
+ NZB/BlNJ |
+ 6C |
+ Rep3 |
+
+
+ | 118 |
+ GSM264933 |
+ NZB/BlNJ |
+ HF |
+ Rep1 |
+
+
+ | 119 |
+ GSM264935 |
+ NZB/BlNJ |
+ HF |
+ Rep2 |
+
+
+ | 120 |
+ GSM264936 |
+ NZB/BlNJ |
+ HF |
+ Rep3 |
+
+
+ | 121 |
+ GSM265061 |
+ PERA/EiJ |
+ 6C |
+ Rep1 |
+
+
+ | 122 |
+ GSM265062 |
+ PERA/EiJ |
+ 6C |
+ Rep2 |
+
+
+ | 123 |
+ GSM265063 |
+ PERA/EiJ |
+ 6C |
+ Rep3 |
+
+
+ | 124 |
+ GSM265064 |
+ PERA/EiJ |
+ HF |
+ Rep1 |
+
+
+ | 125 |
+ GSM265065 |
+ PERA/EiJ |
+ HF |
+ Rep2 |
+
+
+ | 126 |
+ GSM265066 |
+ PERA/EiJ |
+ HF |
+ Rep3 |
+
+
+ | 127 |
+ GSM265067 |
+ PERA/EiJ |
+ 6C |
+ Rep1 |
+
+
+ | 128 |
+ GSM265068 |
+ PERA/EiJ |
+ 6C |
+ Rep2 |
+
+
+ | 129 |
+ GSM265069 |
+ PERA/EiJ |
+ 6C |
+ Rep3 |
+
+
+ | 130 |
+ GSM265070 |
+ PERA/EiJ |
+ HF |
+ Rep1 |
+
+
+ | 131 |
+ GSM265071 |
+ PERA/EiJ |
+ HF |
+ Rep2 |
+
+
+ | 132 |
+ GSM265072 |
+ PERA/EiJ |
+ HF |
+ Rep3 |
+
+
+ | 133 |
+ GSM265074 |
+ SM/J |
+ 6C |
+ Rep1 |
+
+
+ | 134 |
+ GSM265075 |
+ SM/J |
+ 6C |
+ Rep2 |
+
+
+ | 135 |
+ GSM265105 |
+ SM/J |
+ 6C |
+ Rep3 |
+
+
+ | 136 |
+ GSM265217 |
+ SM/J |
+ HF |
+ Rep1 |
+
+
+ | 137 |
+ GSM265248 |
+ SM/J |
+ HF |
+ Rep2 |
+
+
+ | 138 |
+ GSM265275 |
+ SM/J |
+ HF |
+ Rep3 |
+
+
+ | 139 |
+ GSM265324 |
+ SM/J |
+ 6C |
+ Rep1 |
+
+
+ | 140 |
+ GSM265331 |
+ SM/J |
+ 6C |
+ Rep2 |
+
+
+ | 141 |
+ GSM265357 |
+ SM/J |
+ 6C |
+ Rep3 |
+
+
+ | 142 |
+ GSM265358 |
+ SM/J |
+ HF |
+ Rep1 |
+
+
+ | 143 |
+ GSM265359 |
+ SM/J |
+ HF |
+ Rep2 |
+
+
+ | 144 |
+ GSM265360 |
+ SM/J |
+ HF |
+ Rep3 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Jax_csb_l_hf_0711/citation.rtf b/general/datasets/Jax_csb_l_hf_0711/citation.rtf
new file mode 100644
index 0000000..92dd7b6
--- /dev/null
+++ b/general/datasets/Jax_csb_l_hf_0711/citation.rtf
@@ -0,0 +1 @@
+Burgess-Herbert SL, Cox A, Tsaih SW, Paigen B. Practical applications of the bioinformatics toolbox for narrowing quantitative trait loci. Genetics 2008 Dec;180(4):2227-35. PMID: 18845850 Shockley KR, Witmer D, Burgess-Herbert SL, Paigen B et al. Effects of atherogenic diet on hepatic gene expression across mouse strains. Physiol Genomics 2009 Nov 6;39(3):172-82. PMID: 19671657
diff --git a/general/datasets/Jax_csb_l_hf_0711/contributors.rtf b/general/datasets/Jax_csb_l_hf_0711/contributors.rtf
new file mode 100644
index 0000000..04d1867
--- /dev/null
+++ b/general/datasets/Jax_csb_l_hf_0711/contributors.rtf
@@ -0,0 +1 @@
+Churchill GA, Paigen B, Shockley KR, Witmer D
diff --git a/general/datasets/Jax_csb_l_hf_0711/experiment-design.rtf b/general/datasets/Jax_csb_l_hf_0711/experiment-design.rtf
new file mode 100644
index 0000000..dc5fef5
--- /dev/null
+++ b/general/datasets/Jax_csb_l_hf_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Expression profiling by array.
+
+One group of mice was fed an atherogenic high-fat (30% fat) diet containing cholic acid to increase fat uptake and another was fed a low-fat (6% fat) regular chow diet. Males and females from both diets were studied for mouse strains 129S1/SvImJ, A/J, BALB/cJ, C3H/HeJ, C57BL/6J, CAST/EiJ, DBA/2J, I/LnJ, MRL/MpJ-Tnfrsf6lpr/J, NZB/BINJ, PERA/Ei, and SM/J. All strains were sacrificed between 11- and 13 weeks of age except for CAST and PERA, which were harvested after 50 weeks of age. CAST and PERA were subsequently removed from our analysis based on discrepant harvest age, but can be found in our database (see below). Three replicate animals were used for each combination of diet, strain, and sex, resulting in a total of 120 mice surveyed for gene expression.
diff --git a/general/datasets/Jax_csb_l_hf_0711/experiment-type.rtf b/general/datasets/Jax_csb_l_hf_0711/experiment-type.rtf
new file mode 100644
index 0000000..b8429a3
--- /dev/null
+++ b/general/datasets/Jax_csb_l_hf_0711/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array.
\ No newline at end of file
diff --git a/general/datasets/Jax_csb_l_hf_0711/platform.rtf b/general/datasets/Jax_csb_l_hf_0711/platform.rtf
new file mode 100644
index 0000000..459d486
--- /dev/null
+++ b/general/datasets/Jax_csb_l_hf_0711/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array. Affymetrix submissions are typically submitted to GEO using the GEOarchive method described at http://www.ncbi.nlm.nih.gov/projects/geo/info/geo_affy.html All probe sets represented on the GeneChip Mouse Expression Set 430 are included on the GeneChip Mouse Genome 430 2.0 Array. The sequences from which these probe sets were derived were selected from GenBank«, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 107, June 2002) and then refined by analysis and comparison with the publicly available draft assembly of the mouse genome from the Whitehead Institute for Genome Research (MGSC, April 2002).
diff --git a/general/datasets/Jax_csb_l_hf_0711/summary.rtf b/general/datasets/Jax_csb_l_hf_0711/summary.rtf
new file mode 100644
index 0000000..a06430b
--- /dev/null
+++ b/general/datasets/Jax_csb_l_hf_0711/summary.rtf
@@ -0,0 +1 @@
+High-fat diets are associated with increased obesity and metabolic disease in mice and humans. Here we used analysis of variance (ANOVA) to scrutinize a microarray data set consisting of 10 inbred strains of mice from both sexes fed atherogenic high-fat and control chow diets. An overall F-test was applied to the 40 unique groups of strain-diet-sex to identify 15,288 genes with altered transcription. Bootstrapping k-means clustering separated these changes into four strain-dependent expression patterns, including two sex-related profiles and two diet-related profiles. Sex-induced effects correspond to secretion (males) or fat and energy metabolism (females), whereas diet-induced changes relate to neurological processes (chow) or immune response (high-fat). The full set of pairwise contrasts for differences between strains within sex (90 different statistical tests) uncovered 32,379 total changes. These differences were unevenly distributed across strains and between sexes, indicating that strain-specific responses to high-fat diet differ between sexes. Correlations between expression levels and 8 obesity-related traits identified 5,274 associations between transcript abundance and measured phenotypic endpoints. From this number, 2,678 genes are positively correlated with total cholesterol levels and associate with immune-related categories while 2,596 genes are negatively correlated with cholesterol and connect to cholesterol synthesis. Keywords: gene expression analysis, strain comparision, effect of dietary fat, sex-specific effects
diff --git a/general/datasets/Jax_csb_l_hf_0711/tissue.rtf b/general/datasets/Jax_csb_l_hf_0711/tissue.rtf
new file mode 100644
index 0000000..778c4a2
--- /dev/null
+++ b/general/datasets/Jax_csb_l_hf_0711/tissue.rtf
@@ -0,0 +1 @@
+Liver
diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/acknowledgment.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/acknowledgment.rtf
new file mode 100644
index 0000000..3201334
--- /dev/null
+++ b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/acknowledgment.rtf
@@ -0,0 +1,3 @@
+The Authors would like to thank Electron Microscopy, Flow Cytometry, Histology, and Gene Expression Services at The Jackson Laboratory, Rick Libby for careful reading of the manuscript and discussion, Mimi de Vries for assistance with organizing and mouse colonies, Brynn Cardozo and Trip Freeburg for colony maintenance, Jocelyn Thomas for blood collections, Philipp Tauber for assistance with immunofluorescence, and Amy Bell for intraocular pressure measurements.
+
+EY011721 (SWMJ), EY021525 (GRH). Pete Williams is supported by the Karolinska Institutet in the form of a Board of Research Faculty Funded Career Position. Simon John is an Investigator of HHMI.
diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/citation.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/citation.rtf
new file mode 100644
index 0000000..e6a4aa3
--- /dev/null
+++ b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/citation.rtf
@@ -0,0 +1 @@
+Williams, P.A., Braine, C.E., Kizhatil, K. et al. Inhibition of monocyte-like cell extravasation protects from neurodegeneration in DBA/2J glaucoma.Mol Neurodegeneration 14, 6 (2019) https://doi.org/10.1186/s13024-018-0303-3
diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/experiment-design.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/experiment-design.rtf
new file mode 100644
index 0000000..1c50734
--- /dev/null
+++ b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/experiment-design.rtf
@@ -0,0 +1 @@
+To understand the function of these infiltrating monocyte-like cells, we used RNA-sequencing to profile their transcriptomes. Based on their pro-inflammatory molecular signatures, we hypothesized and confirmed that monocyte-platelet interactions occur in glaucomatous tissue. Furthermore, to test monocyte function we used two approaches to inhibit their entry into the optic nerve head: (1) treatment with DS-SILY, a peptidoglycan that acts as a barrier to platelet adhesion to the vessel wall and to monocytes, and (2) genetic targeting of Itgam (CD11b, an immune cell receptor that enables immune cell extravasation).
diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/processing.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/processing.rtf
new file mode 100644
index 0000000..acc1087
--- /dev/null
+++ b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/processing.rtf
@@ -0,0 +1,5 @@
+RNA-sequencing and analysis
+
+Monocytes from single optic nerve heads or from peripheral blood (restrained cheek bleed) were FAC sorted into 100 μl buffer RLT + 1% βME and frozen at − 80 °C until further processing. Samples were defrosted on ice and homogenized by syringe in RLT Buffer (total volume 300 μl). Total RNA was isolated using RNeasy micro kits as according to manufacturer’s protocols (Qiagen) including the optional DNase treatment step, and quality was assessed using an Agilent 2100 Bioanalyzer. The concentration was determined using a Ribogreen Assay from Invitrogen. Amplified dscDNA libraries were created using a Nugen Ovation RNA-seq System V2 and a primer titration was performed to remove primer dimers from the sample to allow sample inputs as low as 50 pg RNA. The SPIA dscDNA was sheared to 300 bp in length using a Diogenode Disruptor. Quality control was performed using an Agilent 2100 Bioanalyzer and a DNA 1000 chip assay. Library size produced was analysed using qPCR using the Library Quantitation kit/Illumina GA /ABI Prism (Kapa Biosystems). Libraries were barcoded, pooled, and sequenced 6 samples per lane on a HiSeq 2000 sequencer (Illumina) giving a depth of 30–35 million reads per sample.
+
+Following RNA-sequencing samples were subjected to quality control analysis by a custom quality control python script. Reads with 70% of their bases having a base quality score ≥ 30 were retained for further analysis. Read alignment was performed using TopHat v 2.0.7 [34] and expression estimation was performed using HTSeq [35] with supplied annotations and default parameters against the DBA/2 J mouse genome (build-mm10). Bamtools v 1.0.2 [36] were used to calculate the mapping statistics. Differential gene expression analysis between groups was performed using edgeR v 3.10.5 [37] following, batch correction using RUVSeq, the removal of outlier samples and lowly expressed genes by removing genes with less than five reads in more than two samples. Normalization was performed using the trimmed mean of M values (TMM). Unsupervised HC was performed in R (1-cor, Spearman’s rho). Following preliminary analysis, 1 sample was removed as an outlier. Adjustment for multiple testing was performed using false discovery rate (FDR). Genes were considered to be significantly differentially expression at a false discovery rate (FDR; q) of q < 0.05. Pathway analysis was performed in R, IPA (Ingenuity Pathway Analysis, Qiagen), and using publically available tools (see Results).
diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/specifics.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/specifics.rtf
new file mode 100644
index 0000000..954c19f
--- /dev/null
+++ b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/specifics.rtf
@@ -0,0 +1 @@
+JAX DBA/2J Monocyte 1 vs PBMC RNA-Seq (Jun19)
\ No newline at end of file
diff --git a/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/summary.rtf b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/summary.rtf
new file mode 100644
index 0000000..b5e090d
--- /dev/null
+++ b/general/datasets/Jax_d2_mono1vpbmc_ret_rna_seq_0619/summary.rtf
@@ -0,0 +1,3 @@
+Glaucoma is characterized by the progressive dysfunction and loss of retinal ganglion cells. Recent work in animal models suggests that a critical neuroinflammatory event damages retinal ganglion cell axons in the optic nerve head during ocular hypertensive injury. We previously demonstrated that monocyte-like cells enter the optic nerve head in an ocular hypertensive mouse model of glaucoma (DBA/2 J), but their roles, if any, in mediating axon damage remain unclear.
+
+https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-018-0303-3
diff --git a/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/acknowledgment.rtf b/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/acknowledgment.rtf
new file mode 100644
index 0000000..3201334
--- /dev/null
+++ b/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/acknowledgment.rtf
@@ -0,0 +1,3 @@
+The Authors would like to thank Electron Microscopy, Flow Cytometry, Histology, and Gene Expression Services at The Jackson Laboratory, Rick Libby for careful reading of the manuscript and discussion, Mimi de Vries for assistance with organizing and mouse colonies, Brynn Cardozo and Trip Freeburg for colony maintenance, Jocelyn Thomas for blood collections, Philipp Tauber for assistance with immunofluorescence, and Amy Bell for intraocular pressure measurements.
+
+EY011721 (SWMJ), EY021525 (GRH). Pete Williams is supported by the Karolinska Institutet in the form of a Board of Research Faculty Funded Career Position. Simon John is an Investigator of HHMI.
diff --git a/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/citation.rtf b/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/citation.rtf
new file mode 100644
index 0000000..e6a4aa3
--- /dev/null
+++ b/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/citation.rtf
@@ -0,0 +1 @@
+Williams, P.A., Braine, C.E., Kizhatil, K. et al. Inhibition of monocyte-like cell extravasation protects from neurodegeneration in DBA/2J glaucoma.Mol Neurodegeneration 14, 6 (2019) https://doi.org/10.1186/s13024-018-0303-3
diff --git a/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/experiment-design.rtf b/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/experiment-design.rtf
new file mode 100644
index 0000000..1c50734
--- /dev/null
+++ b/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/experiment-design.rtf
@@ -0,0 +1 @@
+To understand the function of these infiltrating monocyte-like cells, we used RNA-sequencing to profile their transcriptomes. Based on their pro-inflammatory molecular signatures, we hypothesized and confirmed that monocyte-platelet interactions occur in glaucomatous tissue. Furthermore, to test monocyte function we used two approaches to inhibit their entry into the optic nerve head: (1) treatment with DS-SILY, a peptidoglycan that acts as a barrier to platelet adhesion to the vessel wall and to monocytes, and (2) genetic targeting of Itgam (CD11b, an immune cell receptor that enables immune cell extravasation).
diff --git a/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/processing.rtf b/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/processing.rtf
new file mode 100644
index 0000000..acc1087
--- /dev/null
+++ b/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/processing.rtf
@@ -0,0 +1,5 @@
+RNA-sequencing and analysis
+
+Monocytes from single optic nerve heads or from peripheral blood (restrained cheek bleed) were FAC sorted into 100 μl buffer RLT + 1% βME and frozen at − 80 °C until further processing. Samples were defrosted on ice and homogenized by syringe in RLT Buffer (total volume 300 μl). Total RNA was isolated using RNeasy micro kits as according to manufacturer’s protocols (Qiagen) including the optional DNase treatment step, and quality was assessed using an Agilent 2100 Bioanalyzer. The concentration was determined using a Ribogreen Assay from Invitrogen. Amplified dscDNA libraries were created using a Nugen Ovation RNA-seq System V2 and a primer titration was performed to remove primer dimers from the sample to allow sample inputs as low as 50 pg RNA. The SPIA dscDNA was sheared to 300 bp in length using a Diogenode Disruptor. Quality control was performed using an Agilent 2100 Bioanalyzer and a DNA 1000 chip assay. Library size produced was analysed using qPCR using the Library Quantitation kit/Illumina GA /ABI Prism (Kapa Biosystems). Libraries were barcoded, pooled, and sequenced 6 samples per lane on a HiSeq 2000 sequencer (Illumina) giving a depth of 30–35 million reads per sample.
+
+Following RNA-sequencing samples were subjected to quality control analysis by a custom quality control python script. Reads with 70% of their bases having a base quality score ≥ 30 were retained for further analysis. Read alignment was performed using TopHat v 2.0.7 [34] and expression estimation was performed using HTSeq [35] with supplied annotations and default parameters against the DBA/2 J mouse genome (build-mm10). Bamtools v 1.0.2 [36] were used to calculate the mapping statistics. Differential gene expression analysis between groups was performed using edgeR v 3.10.5 [37] following, batch correction using RUVSeq, the removal of outlier samples and lowly expressed genes by removing genes with less than five reads in more than two samples. Normalization was performed using the trimmed mean of M values (TMM). Unsupervised HC was performed in R (1-cor, Spearman’s rho). Following preliminary analysis, 1 sample was removed as an outlier. Adjustment for multiple testing was performed using false discovery rate (FDR). Genes were considered to be significantly differentially expression at a false discovery rate (FDR; q) of q < 0.05. Pathway analysis was performed in R, IPA (Ingenuity Pathway Analysis, Qiagen), and using publically available tools (see Results).
diff --git a/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/specifics.rtf b/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/specifics.rtf
new file mode 100644
index 0000000..ba732fb
--- /dev/null
+++ b/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/specifics.rtf
@@ -0,0 +1 @@
+JAX DBA/2J Monocyte 2 vs PBMC RNA-Seq (Jun19)
\ No newline at end of file
diff --git a/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/summary.rtf b/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/summary.rtf
new file mode 100644
index 0000000..b5e090d
--- /dev/null
+++ b/general/datasets/Jax_d2_mono2vpbmc_ret_rna_seq_0619/summary.rtf
@@ -0,0 +1,3 @@
+Glaucoma is characterized by the progressive dysfunction and loss of retinal ganglion cells. Recent work in animal models suggests that a critical neuroinflammatory event damages retinal ganglion cell axons in the optic nerve head during ocular hypertensive injury. We previously demonstrated that monocyte-like cells enter the optic nerve head in an ocular hypertensive mouse model of glaucoma (DBA/2 J), but their roles, if any, in mediating axon damage remain unclear.
+
+https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-018-0303-3
diff --git a/general/datasets/Jax_d2gm_rseq_log2z_0418/citation.rtf b/general/datasets/Jax_d2gm_rseq_log2z_0418/citation.rtf
new file mode 100644
index 0000000..fe14fa7
--- /dev/null
+++ b/general/datasets/Jax_d2gm_rseq_log2z_0418/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Williams PA, Harder JM, Foxworth NE, Cochran KE et al. Vitamin B3 modulates mitochondrial vulnerability and prevents glaucoma in aged mice. Science 2017 Feb 17;355(6326):756-760. PMID: 28209901
+
diff --git a/general/datasets/Jax_d2gm_rseq_log2z_0418/experiment-design.rtf b/general/datasets/Jax_d2gm_rseq_log2z_0418/experiment-design.rtf
new file mode 100644
index 0000000..5b2f4c9
--- /dev/null
+++ b/general/datasets/Jax_d2gm_rseq_log2z_0418/experiment-design.rtf
@@ -0,0 +1 @@
+Retinal ganglion cell mRNA from 4 month (young) and 9 month (pre-glaucomatous) DBA/2J mice and age and sex-matched D2-Gpnmb+ controls
diff --git a/general/datasets/Jax_d2gm_rseq_log2z_0418/platform.rtf b/general/datasets/Jax_d2gm_rseq_log2z_0418/platform.rtf
new file mode 100644
index 0000000..c967d36
--- /dev/null
+++ b/general/datasets/Jax_d2gm_rseq_log2z_0418/platform.rtf
@@ -0,0 +1 @@
+GPL17021Illumina HiSeq 2500 (Mus musculus)
diff --git a/general/datasets/Jax_d2gm_rseq_log2z_0418/specifics.rtf b/general/datasets/Jax_d2gm_rseq_log2z_0418/specifics.rtf
new file mode 100644
index 0000000..f57a155
--- /dev/null
+++ b/general/datasets/Jax_d2gm_rseq_log2z_0418/specifics.rtf
@@ -0,0 +1,3 @@
+RNA-Seq log2 Z-Score
+
+In general, the array data that we put in GeneNetwork has been logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Jax_d2gm_rseq_log2z_0418/summary.rtf b/general/datasets/Jax_d2gm_rseq_log2z_0418/summary.rtf
new file mode 100644
index 0000000..1cf2292
--- /dev/null
+++ b/general/datasets/Jax_d2gm_rseq_log2z_0418/summary.rtf
@@ -0,0 +1 @@
+RNA-seq analysis from young and pre-glaucomatous DBA/2J retinal ganglion cells and control (age and sex-matched, D2-Gpnmb+) retinal ganglion cells
diff --git a/general/datasets/Jax_liver_agil_mdp_0113/experiment-type.rtf b/general/datasets/Jax_liver_agil_mdp_0113/experiment-type.rtf
new file mode 100644
index 0000000..073f544
--- /dev/null
+++ b/general/datasets/Jax_liver_agil_mdp_0113/experiment-type.rtf
@@ -0,0 +1,13 @@
+
+
+Liver histopathology.
+Paraffin-embedded liver tissue was cut to 5-μm sections in duplicate and stained with hematoxylin and eosin. Liver injury in the left liver lobe was blindly scored by A.H.H. and confirmed by a certified veterinary pathologist. Necrosis was quantified by unbiased stereology using a point-counting technique (Mouton, 2002). Briefly, a grid with 100 evenly spaced points was overlaid on printed images of liver sections taken at ×100 magnification. The total number of points lying in an area of necrosis was divided by the total number of points lying completely within the entire tissue section to determine a percent necrosis score (0–100%). The necrosis score for each animal in the study is publicly available from the Mouse Phenome Database (http://phenome.jax.org/pub-cgi/phenome/mpdcgi?rtn = projects/details&sym = Threadgill1).
+
+RNA isolation.
+To eliminate variability in transcript expression that might arise between liver lobes, the left liver lobe was selected for the remainder of the data analysis and gene expression profiling. RNA was extracted from the 30 mg of tissue derived from the left lobe of sample livers using the Qiagen RNeasy kit (Qiagen, Valencia, CA). RNA concentrations were measured using a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE), and quality was verified using the Agilent Bio-Analyzer (Agilent Technologies, Santa Clara, CA). RNA was determined to be of good quality for use in microarray hybridizations if the 28S:16S rRNA ratio was greater than 1.8 and the 260/280 nm absorbance ratio was in the range of 1.9–2.1.
+
+Microarray hybridizations.
+In this study, all RNA samples were hybridized to arrays individually; none were pooled. RNA amplifications and labeling were performed using Low RNA Input Linear Amplification kits (Agilent Technologies). For hybridization, 750 ng of total RNA from each mouse liver was amplified and labeled with fluorescent dye (Cy5). In parallel, 750 ng of a common reference RNA (Icoria, Inc., RTP, NC) was labeled with the fluorescent dye, Cy3, in order to standardize analysis of global gene expression between mouse strains (Bammler et al., 2005). Labeled cRNA was then processed and hybridized to Agilent Mouse Toxicology Arrays (catalog# 4121A, 22,575 features) according to the manufacturer's protocol. Details regarding the microarray probe set on the 4121A array are available via the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = GPL891). Following hybridization, arrays were washed using a custom protocol developed by Icoria, Inc. Briefly, array gaskets were removed under immersion in wash solution 1 (6× sodium chloride/sodium phosphate/EDTA [SSPE], 0.005% N-lauroylsarcosine). Arrays were washed with wash solution 1 and incubated for 1 min with gentle agitation on a magnetic stir plate. A second incubation was performed in wash solution 2 (0.06× SSPE, 0.005% N-lauroylsarcosine).
+
+Data analysis of significantly changed transcripts.
+Raw microarray intensity values were obtained from Agilent Feature Extraction software (v8.5) and archived in the UNC Microarray Database (http://genome.unc.edu). Raw data are available to the public through this database. The log2 ratio of Cy5/Cy3 intensity was normalized using locally weighted scatterplot smoothing to eliminate intensity bias of features. Transcripts with fewer than 70% available data across samples were excluded from the analysis, reducing the probe list to 15,509 transcript probes. Available data are defined as those probes that are neither saturated nor below the limit of quantification. Intensity ratios were transformed to eliminate hybridization batch effects using the batch normalization feature in Partek Genomics Suite (Partek, Inc., St Louis, MO). Analysis of significant transcripts was performed using an analysis of covariance (ANCOVA) model in Partek in which the main effects were mouse strain, treatment, the interaction of mouse strain and treatment, and the sample necrosis score. Transcripts were called significantly different if the p value was less than a threshold determined by a step-down false discovery rate (FDR, Benjamini and Liu, 1999) (α = 0.01) to correct for multiple comparisons across array features. Heat maps were generated using hierarchical agglomerative clustering.
\ No newline at end of file
diff --git a/general/datasets/Jax_liver_agil_mdp_0113/summary.rtf b/general/datasets/Jax_liver_agil_mdp_0113/summary.rtf
new file mode 100644
index 0000000..f6be413
--- /dev/null
+++ b/general/datasets/Jax_liver_agil_mdp_0113/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 160, Name: Harrill-Rusyn MDP Liver Acetaminophen Tox Study (G4121A, 2009)
\ No newline at end of file
diff --git a/general/datasets/Ki_2a_0405_m/acknowledgment.rtf b/general/datasets/Ki_2a_0405_m/acknowledgment.rtf
new file mode 100644
index 0000000..956eaca
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_m/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported with funds to TJA by the MRC Clinical Sciences Centre, the British Heart Foundation, and the Wellcome Trust Cardiovascular Functional Genomics Intiative; to NH from the German Ministry for Science and Education (National Genome Research Network); to MP and Vladimir Kren from the Grant Agency of the Czech Republic; to MP and TJA from the Wellcome Trust Collaborative Research Initiative grant, to Theodore W Kurtz from the NIH, to TWK and MP from a Fogarty International Research Collaboration Award. Microarrays were a generous donation of Affymetrix Inc. Michal Pravenec thanks the Howard Hughes Medical Institute for its support to him as an international research scholar.
diff --git a/general/datasets/Ki_2a_0405_m/cases.rtf b/general/datasets/Ki_2a_0405_m/cases.rtf
new file mode 100644
index 0000000..862deec
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_m/cases.rtf
@@ -0,0 +1,7 @@
+Data were generated using the HXB/BXH recombinant inbred strains of rats generated over the past 20 years in Prague. The parental strains from which all HXB lines are derived are SHR (SHR/OlaIpcv or HSR = H) and Brown Norway (BN.Lx/Cub= B). These strains have been used extensively to study cardiovascular system physiology and genetics.
+
+
+The HXB strains were bred by Michal Pravenec at the Institute of Physiology, Czech Academy of Sciences. The BXH strains were bred by Vladimir Kren (see Pravenec et al. 1989, 2004) at a similar animal facility at the Institute of Biology and Medical Genetics, 1st Medical Faculty, Charles University. These strains are at approximately the 6oth geenration of continuous inbreeding (F60).
+
+Animals used in the transcriptome analyses of kidney and fat (Hübner and colleagues, 2005) were weaned at 4 weeks. Those born at the Charles University were transferred to the Institute of Physiology. Animals were reared on a commerical rat chow (ST-1 from VELAZ, Czech Republic). Four males were house per cage. Cages were made of polystyrene and have a floor size of 22 x 38 cm and height of 23 cm. The bedding was changed twice a week. Light cycle was 12:12 on-off. Vivarium rooms were maintained at 23 deg. C. Rats were sexually naive. All males used in the initial transcriptome studies (Hubner et al., 2005) were born between May and August 2002. They were sacrificed unfastged by rapid cervical dislocation between 9 and 10 AM, following an approved animal protocol (Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague; Animal Protectiion Law of the Czech Republic (311/1997).
+
diff --git a/general/datasets/Ki_2a_0405_m/citation.rtf b/general/datasets/Ki_2a_0405_m/citation.rtf
new file mode 100644
index 0000000..a8b8cc0
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_m/citation.rtf
@@ -0,0 +1 @@
+PLoS One. 2008;3(12):e4033. doi: 10.1371/journal.pone.0004033. Epub 2008 Dec 29.
diff --git a/general/datasets/Ki_2a_0405_m/contributors.rtf b/general/datasets/Ki_2a_0405_m/contributors.rtf
new file mode 100644
index 0000000..0afa863
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_m/contributors.rtf
@@ -0,0 +1 @@
+Grieve IC1, Dickens NJ, Pravenec M, Kren V, Hubner N, Cook SA, Aitman TJ, Petretto E, Mangion J. Author information 1MRC Clinical Sciences Centre, Imperial College, Hammersmith Hospital, London, United Kingdom.
diff --git a/general/datasets/Ki_2a_0405_m/notes.rtf b/general/datasets/Ki_2a_0405_m/notes.rtf
new file mode 100644
index 0000000..1af325d
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_m/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by Robert Williams, Norbert Hübner, Michal Pravnec, Timothy Aitman, April 19, 2005. Updated by RWW, May 13, 2005.
+
diff --git a/general/datasets/Ki_2a_0405_m/platform.rtf b/general/datasets/Ki_2a_0405_m/platform.rtf
new file mode 100644
index 0000000..78c5815
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_m/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix 230A GeneChip: Expression data were generated using the Affymetrix 230A array. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Rat Genome Sequencing Consortium assembly.
+
diff --git a/general/datasets/Ki_2a_0405_m/processing.rtf b/general/datasets/Ki_2a_0405_m/processing.rtf
new file mode 100644
index 0000000..d75d1db
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_m/processing.rtf
@@ -0,0 +1,15 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of pixel measured in each cell.
+
+
+Probe set data: The original CEL values were log2 transformed and quantile normalized. We then took the antilog values of these quantile adjusted CEL values as input to the standard MAS5 algorithm. Probe set values listed in WebQTL pages are typically the averages of four biological replicates within strain.
+
+
+About Quality Control Procedures:
+
+
+RNA processing:RNA was extracted using Trizol reagent (Invitrogen) and purified using an RNeasy Mini kit from Qiagen. Double-stranded cDNA was generated without pooling. The Ambion MEGAscript T7 kit from Ambion was used to generate biotinylated cRNA for kidney. Fat samples were processed at this step using the Enzo Diagnostics Bioarray High Yield RNA Transcript labeling kit. See Hübner et al. 2005 for additional detail. One-hundred and twenty eight samples passed RNA quality control steps.
+
+Probe level QC: All 128 CEL files were collected into a single DataDesk 6.2 file. Probe data from pairs of arrays were plotted and compared. Eight arrays were considered potential outliers (despite having passed RNA quality control) and in the interest of minimizing technical variance, a decision was made to withhold them from the calculation of strain means used in WebQTL. The remaining 120 arrays were quantile normalized and reexamined in DataDesk to ensure reasonble colinearity of all array data sets.
+
+Probe set level QC: Probe set level QC involves counting the number of times that a single array data set from a single sample generates outliers at the level of the probe set consensus estimates of expression. With 120 arrays, any single array should generate a comparatively small fraction of the total number of outlier calls. This final step of array QC has NOT been implemented yet in this data set.
+
diff --git a/general/datasets/Ki_2a_0405_m/summary.rtf b/general/datasets/Ki_2a_0405_m/summary.rtf
new file mode 100644
index 0000000..44fd86e
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_m/summary.rtf
@@ -0,0 +1,19 @@
+This April 2005 data set provides estimates of mRNA expression in normal kidneys of 32 strains of rats. The set includes the hypertensive SHR strain, the normotensive BN strain, and 30 HXB/BXH recombinant inbred strains. Each strain was sampled in quadruplicate (6-week-old males). Animals and tissues were generated by Michal Pravenec and colleagues at the Czech Academy of Sciences (CAS). RNA samples were processed at the Max-Delbrück-Center (MDC), Berlin Buch by Nobert Hübner and colleagues. Transcriptome mapping was carried out by Timothy Aitman and colleagues at the Imperial College, London (ICL). Samples were hybridized individually to a total of 128 Affymetrix RAE230A array. This particular data set includes 120 arrays processed using a quantile normalized variant of the Affymetrix MAS5 protocol. The expression values of each array have been logged and adjusted to a mean of 8 and a stardard deviation of 2 (mean and variance stabilized). This data set complements the original MAS5 data set exploited by Hübner and colleagues 2005. Download the particular transform in an Excel work book with both strain means and SEMs.
+
+These data can also be viewed using the eQTL Explorer Java application by John Mangion, Tim Aitman, and colleagues (Mueller et al. 2006).
+
+Genome-wide co-expression analysis in multiple tissues.
+
+And see closely associate set of papers:
+
+
+ - Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease.
+ - Heritability and tissue specificity of expression quantitative trait loci.
+ - Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass.
+ - New insights into the genetic control of gene expression using a Bayesian multi-tissue approach.
+ - The genome sequence of the spontaneously hypertensive rat: Analysis and functional significance.
+ - A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.
+ - Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.
+ - Systems-level approaches reveal conservation of trans-regulated genes in the rat and genetic determinants of blood pressure in humans.
+
diff --git a/general/datasets/Ki_2a_0405_m/tissue.rtf b/general/datasets/Ki_2a_0405_m/tissue.rtf
new file mode 100644
index 0000000..8184532
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_m/tissue.rtf
@@ -0,0 +1,534 @@
+All tissues were collected at the age of 6 weeks. Kidneys and other organs were rapidly dissected and cleaned of fat, inserted into a vial, and immersed in liquid nitrogen for storage until RNA extraction.
+
+The table below lists the arrays by strain and sample identifier. Each array was hybridized with mRNA from a single young male rat.
+
+
+
+
+
+
+
+
+ | Strain |
+ SampleID |
+
+
+ | HSR |
+ HSR1 |
+
+
+ | HSR |
+ HSR2 |
+
+
+ | HSR |
+ HSR3 |
+
+
+ | HSR |
+ HSR4 |
+
+
+ | BN |
+ BN1 |
+
+
+ | BN |
+ BN2 |
+
+
+ | BN |
+ BN3 |
+
+
+ | BN |
+ BN4 |
+
+
+ | BN |
+ BN5 |
+
+
+ | HXB1 |
+ RI 01-1 |
+
+
+ | HXB1 |
+ RI 01-2 |
+
+
+ | HXB1 |
+ RI 01-3 |
+
+
+ | HXB1 |
+ RI 01-4 |
+
+
+ | HXB2 |
+ RI 02-1 |
+
+
+ | HXB2 |
+ RI 02-2 |
+
+
+ | HXB2 |
+ RI 02-3 |
+
+
+ | HXB2 |
+ *RI 02-4 |
+
+
+ | HXB3 |
+ RI 03-1 |
+
+
+ | HXB3 |
+ RI 03-2 |
+
+
+ | HXB3 |
+ RI 03-3 |
+
+
+ | HXB3 |
+ RI 03-4 |
+
+
+ | HXB4 |
+ RI 04-1 |
+
+
+ | HXB4 |
+ RI 04-2 |
+
+
+ | HXB4 |
+ RI 04-3 |
+
+
+ | HXB4 |
+ RI 04-4 |
+
+
+ | HXB5 |
+ RI 05-1 |
+
+
+ | HXB5 |
+ RI 05-2 |
+
+
+ | HXB5 |
+ RI 05-3 |
+
+
+ | HXB5 |
+ *RI 05-4 |
+
+
+ | HXB7 |
+ RI 07-1 |
+
+
+ | HXB7 |
+ RI 07-2 |
+
+
+ | HXB7 |
+ RI 07-3 |
+
+
+ | HXB7 |
+ RI 07-4 |
+
+
+ | HXB10 |
+ RI 10-1 |
+
+
+ | HXB10 |
+ RI 10-2 |
+
+
+ | HXB10 |
+ RI 10-3 |
+
+
+ | HXB10 |
+ RI 10-4 |
+
+
+ | HXB15 |
+ RI 15-1 |
+
+
+ | HXB15 |
+ RI 15-2 |
+
+
+ | HXB15 |
+ RI 15-3 |
+
+
+ | HXB15 |
+ RI 15-4 |
+
+
+ | HXB17 |
+ RI 17-1 |
+
+
+ | HXB17 |
+ RI 17-2 |
+
+
+ | HXB17 |
+ RI 17-3 |
+
+
+ | HXB17 |
+ RI 17-4 |
+
+
+ | HXB18 |
+ RI 18-1 |
+
+
+ | HXB18 |
+ RI 18-2 |
+
+
+ | HXB18 |
+ RI 18-3 |
+
+
+ | HXB18 |
+ RI 18-4 |
+
+
+ | HXB20 |
+ RI 20-1 |
+
+
+ | HXB20 |
+ RI 20-2 |
+
+
+ | HXB20 |
+ RI 20-3 |
+
+
+ | HXB20 |
+ RI 20-4 |
+
+
+ | HXB21 |
+ RI 21-1 |
+
+
+ | HXB21 |
+ RI 21-2 |
+
+
+ | HXB21 |
+ RI 21-3 |
+
+
+ | HXB21 |
+ RI 21-4 |
+
+
+ | HXB22 |
+ RI 22-1 |
+
+
+ | HXB22 |
+ RI 22-2 |
+
+
+ | HXB22 |
+ RI 22-3 |
+
+
+ | HXB22 |
+ RI 22-4 |
+
+
+ | HXB23 |
+ RI 23-1 |
+
+
+ | HXB23 |
+ RI 23-2 |
+
+
+ | HXB23 |
+ RI 23-3 |
+
+
+ | HXB23 |
+ RI 23-4 |
+
+
+ | HXB24 |
+ RI 24-1 |
+
+
+ | HXB24 |
+ RI 24-2 |
+
+
+ | HXB24 |
+ RI 24-3 |
+
+
+ | HXB24 |
+ *RI 24-4 |
+
+
+ | HXB25 |
+ RI 25-1 |
+
+
+ | HXB25 |
+ RI 25-2 |
+
+
+ | HXB25 |
+ RI 25-3 |
+
+
+ | HXB25 |
+ *RI 25-4 |
+
+
+ | HXB26 |
+ RI 26-1 |
+
+
+ | HXB26 |
+ RI 26-2 |
+
+
+ | HXB26 |
+ RI 26-3 |
+
+
+ | HXB26 |
+ RI 26-4 |
+
+
+ | HXB27 |
+ RI 27-1 |
+
+
+ | HXB27 |
+ RI 27-2 |
+
+
+ | HXB27 |
+ RI 27-3 |
+
+
+ | HXB27 |
+ RI 27-4 |
+
+
+ | HXB29 |
+ RI 29-1 |
+
+
+ | HXB29 |
+ RI 29-2 |
+
+
+ | HXB29 |
+ RI 29-3 |
+
+
+ | HXB29 |
+ *RI 29-4 |
+
+
+ | HXB31 |
+ RI 31-1 |
+
+
+ | HXB31 |
+ RI 31-2 |
+
+
+ | HXB31 |
+ RI 31-3 |
+
+
+ | HXB31 |
+ RI 31-4 |
+
+
+ | BXH2 |
+ RI 02c-1 |
+
+
+ | BXH2 |
+ RI 02c-2 |
+
+
+ | BXH2 |
+ RI 02c-3 |
+
+
+ | BXH2 |
+ RI 02c-4 |
+
+
+ | BXH3 |
+ RI 03c-1 |
+
+
+ | BXH3 |
+ RI 03c-2 |
+
+
+ | BXH3 |
+ RI 03c-3 |
+
+
+ | BXH3 |
+ RI 03c-4 |
+
+
+ | BXH5 |
+ RI 05c-1 |
+
+
+ | BXH5 |
+ RI 05c-2 |
+
+
+ | BXH5 |
+ RI 05c-3 |
+
+
+ | BXH5 |
+ *RI 05c-4 |
+
+
+ | BXH6 |
+ RI 06c-1 |
+
+
+ | BXH6 |
+ RI 06c-2 |
+
+
+ | BXH6 |
+ RI 06c-3 |
+
+
+ | BXH6 |
+ *RI 06c-4 |
+
+
+ | BXH8 |
+ RI 08c-1 |
+
+
+ | BXH8 |
+ RI 08c-2 |
+
+
+ | BXH8 |
+ RI 08c-3 |
+
+
+ | BXH8 |
+ RI 08c-4 |
+
+
+ | BXH9 |
+ RI 09c-1 |
+
+
+ | BXH9 |
+ RI 09c-2 |
+
+
+ | BXH9 |
+ RI 09c-3 |
+
+
+ | BXH9 |
+ RI 09c-4 |
+
+
+ | BXH10 |
+ RI 10c-1 |
+
+
+ | BXH10 |
+ RI 10c-2 |
+
+
+ | BXH10 |
+ RI 10c-3 |
+
+
+ | BXH11 |
+ RI 11c-1 |
+
+
+ | BXH11 |
+ RI 11c-2 |
+
+
+ | BXH11 |
+ RI 11c-3 |
+
+
+ | BXH11 |
+ *RI 11c-4 |
+
+
+ | BXH12 |
+ RI 12c-1 |
+
+
+ | BXH12 |
+ RI 12c-2 |
+
+
+ | BXH12 |
+ RI 12c-3 |
+
+
+ | BXH12 |
+ RI 12c-4 |
+
+
+ | BXH13 |
+ RI 13c-1 |
+
+
+ | BXH13 |
+ RI 13c-2 |
+
+
+ | BXH13 |
+ RI 13c-3 |
+
+
+ | BXH13 |
+ RI 13c-4 |
+
+
+
+ |
+
+
+
+
+*: These eight arrays were excluded in the final strain summary data. See section of Quality Control for further explanation.
diff --git a/general/datasets/Ki_2a_0405_r/acknowledgment.rtf b/general/datasets/Ki_2a_0405_r/acknowledgment.rtf
new file mode 100644
index 0000000..956eaca
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_r/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported with funds to TJA by the MRC Clinical Sciences Centre, the British Heart Foundation, and the Wellcome Trust Cardiovascular Functional Genomics Intiative; to NH from the German Ministry for Science and Education (National Genome Research Network); to MP and Vladimir Kren from the Grant Agency of the Czech Republic; to MP and TJA from the Wellcome Trust Collaborative Research Initiative grant, to Theodore W Kurtz from the NIH, to TWK and MP from a Fogarty International Research Collaboration Award. Microarrays were a generous donation of Affymetrix Inc. Michal Pravenec thanks the Howard Hughes Medical Institute for its support to him as an international research scholar.
diff --git a/general/datasets/Ki_2a_0405_r/cases.rtf b/general/datasets/Ki_2a_0405_r/cases.rtf
new file mode 100644
index 0000000..862deec
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_r/cases.rtf
@@ -0,0 +1,7 @@
+Data were generated using the HXB/BXH recombinant inbred strains of rats generated over the past 20 years in Prague. The parental strains from which all HXB lines are derived are SHR (SHR/OlaIpcv or HSR = H) and Brown Norway (BN.Lx/Cub= B). These strains have been used extensively to study cardiovascular system physiology and genetics.
+
+
+The HXB strains were bred by Michal Pravenec at the Institute of Physiology, Czech Academy of Sciences. The BXH strains were bred by Vladimir Kren (see Pravenec et al. 1989, 2004) at a similar animal facility at the Institute of Biology and Medical Genetics, 1st Medical Faculty, Charles University. These strains are at approximately the 6oth geenration of continuous inbreeding (F60).
+
+Animals used in the transcriptome analyses of kidney and fat (Hübner and colleagues, 2005) were weaned at 4 weeks. Those born at the Charles University were transferred to the Institute of Physiology. Animals were reared on a commerical rat chow (ST-1 from VELAZ, Czech Republic). Four males were house per cage. Cages were made of polystyrene and have a floor size of 22 x 38 cm and height of 23 cm. The bedding was changed twice a week. Light cycle was 12:12 on-off. Vivarium rooms were maintained at 23 deg. C. Rats were sexually naive. All males used in the initial transcriptome studies (Hubner et al., 2005) were born between May and August 2002. They were sacrificed unfastged by rapid cervical dislocation between 9 and 10 AM, following an approved animal protocol (Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague; Animal Protectiion Law of the Czech Republic (311/1997).
+
diff --git a/general/datasets/Ki_2a_0405_r/citation.rtf b/general/datasets/Ki_2a_0405_r/citation.rtf
new file mode 100644
index 0000000..a8b8cc0
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_r/citation.rtf
@@ -0,0 +1 @@
+PLoS One. 2008;3(12):e4033. doi: 10.1371/journal.pone.0004033. Epub 2008 Dec 29.
diff --git a/general/datasets/Ki_2a_0405_r/contributors.rtf b/general/datasets/Ki_2a_0405_r/contributors.rtf
new file mode 100644
index 0000000..0afa863
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_r/contributors.rtf
@@ -0,0 +1 @@
+Grieve IC1, Dickens NJ, Pravenec M, Kren V, Hubner N, Cook SA, Aitman TJ, Petretto E, Mangion J. Author information 1MRC Clinical Sciences Centre, Imperial College, Hammersmith Hospital, London, United Kingdom.
diff --git a/general/datasets/Ki_2a_0405_r/notes.rtf b/general/datasets/Ki_2a_0405_r/notes.rtf
new file mode 100644
index 0000000..1af325d
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by Robert Williams, Norbert Hübner, Michal Pravnec, Timothy Aitman, April 19, 2005. Updated by RWW, May 13, 2005.
+
diff --git a/general/datasets/Ki_2a_0405_r/platform.rtf b/general/datasets/Ki_2a_0405_r/platform.rtf
new file mode 100644
index 0000000..78c5815
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix 230A GeneChip: Expression data were generated using the Affymetrix 230A array. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Rat Genome Sequencing Consortium assembly.
+
diff --git a/general/datasets/Ki_2a_0405_r/processing.rtf b/general/datasets/Ki_2a_0405_r/processing.rtf
new file mode 100644
index 0000000..d75d1db
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_r/processing.rtf
@@ -0,0 +1,15 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of pixel measured in each cell.
+
+
+Probe set data: The original CEL values were log2 transformed and quantile normalized. We then took the antilog values of these quantile adjusted CEL values as input to the standard MAS5 algorithm. Probe set values listed in WebQTL pages are typically the averages of four biological replicates within strain.
+
+
+About Quality Control Procedures:
+
+
+RNA processing:RNA was extracted using Trizol reagent (Invitrogen) and purified using an RNeasy Mini kit from Qiagen. Double-stranded cDNA was generated without pooling. The Ambion MEGAscript T7 kit from Ambion was used to generate biotinylated cRNA for kidney. Fat samples were processed at this step using the Enzo Diagnostics Bioarray High Yield RNA Transcript labeling kit. See Hübner et al. 2005 for additional detail. One-hundred and twenty eight samples passed RNA quality control steps.
+
+Probe level QC: All 128 CEL files were collected into a single DataDesk 6.2 file. Probe data from pairs of arrays were plotted and compared. Eight arrays were considered potential outliers (despite having passed RNA quality control) and in the interest of minimizing technical variance, a decision was made to withhold them from the calculation of strain means used in WebQTL. The remaining 120 arrays were quantile normalized and reexamined in DataDesk to ensure reasonble colinearity of all array data sets.
+
+Probe set level QC: Probe set level QC involves counting the number of times that a single array data set from a single sample generates outliers at the level of the probe set consensus estimates of expression. With 120 arrays, any single array should generate a comparatively small fraction of the total number of outlier calls. This final step of array QC has NOT been implemented yet in this data set.
+
diff --git a/general/datasets/Ki_2a_0405_r/summary.rtf b/general/datasets/Ki_2a_0405_r/summary.rtf
new file mode 100644
index 0000000..44fd86e
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_r/summary.rtf
@@ -0,0 +1,19 @@
+This April 2005 data set provides estimates of mRNA expression in normal kidneys of 32 strains of rats. The set includes the hypertensive SHR strain, the normotensive BN strain, and 30 HXB/BXH recombinant inbred strains. Each strain was sampled in quadruplicate (6-week-old males). Animals and tissues were generated by Michal Pravenec and colleagues at the Czech Academy of Sciences (CAS). RNA samples were processed at the Max-Delbrück-Center (MDC), Berlin Buch by Nobert Hübner and colleagues. Transcriptome mapping was carried out by Timothy Aitman and colleagues at the Imperial College, London (ICL). Samples were hybridized individually to a total of 128 Affymetrix RAE230A array. This particular data set includes 120 arrays processed using a quantile normalized variant of the Affymetrix MAS5 protocol. The expression values of each array have been logged and adjusted to a mean of 8 and a stardard deviation of 2 (mean and variance stabilized). This data set complements the original MAS5 data set exploited by Hübner and colleagues 2005. Download the particular transform in an Excel work book with both strain means and SEMs.
+
+These data can also be viewed using the eQTL Explorer Java application by John Mangion, Tim Aitman, and colleagues (Mueller et al. 2006).
+
+Genome-wide co-expression analysis in multiple tissues.
+
+And see closely associate set of papers:
+
+
+ - Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease.
+ - Heritability and tissue specificity of expression quantitative trait loci.
+ - Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass.
+ - New insights into the genetic control of gene expression using a Bayesian multi-tissue approach.
+ - The genome sequence of the spontaneously hypertensive rat: Analysis and functional significance.
+ - A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.
+ - Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.
+ - Systems-level approaches reveal conservation of trans-regulated genes in the rat and genetic determinants of blood pressure in humans.
+
diff --git a/general/datasets/Ki_2a_0405_r/tissue.rtf b/general/datasets/Ki_2a_0405_r/tissue.rtf
new file mode 100644
index 0000000..8184532
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_r/tissue.rtf
@@ -0,0 +1,534 @@
+All tissues were collected at the age of 6 weeks. Kidneys and other organs were rapidly dissected and cleaned of fat, inserted into a vial, and immersed in liquid nitrogen for storage until RNA extraction.
+
+The table below lists the arrays by strain and sample identifier. Each array was hybridized with mRNA from a single young male rat.
+
+
+
+
+
+
+
+
+ | Strain |
+ SampleID |
+
+
+ | HSR |
+ HSR1 |
+
+
+ | HSR |
+ HSR2 |
+
+
+ | HSR |
+ HSR3 |
+
+
+ | HSR |
+ HSR4 |
+
+
+ | BN |
+ BN1 |
+
+
+ | BN |
+ BN2 |
+
+
+ | BN |
+ BN3 |
+
+
+ | BN |
+ BN4 |
+
+
+ | BN |
+ BN5 |
+
+
+ | HXB1 |
+ RI 01-1 |
+
+
+ | HXB1 |
+ RI 01-2 |
+
+
+ | HXB1 |
+ RI 01-3 |
+
+
+ | HXB1 |
+ RI 01-4 |
+
+
+ | HXB2 |
+ RI 02-1 |
+
+
+ | HXB2 |
+ RI 02-2 |
+
+
+ | HXB2 |
+ RI 02-3 |
+
+
+ | HXB2 |
+ *RI 02-4 |
+
+
+ | HXB3 |
+ RI 03-1 |
+
+
+ | HXB3 |
+ RI 03-2 |
+
+
+ | HXB3 |
+ RI 03-3 |
+
+
+ | HXB3 |
+ RI 03-4 |
+
+
+ | HXB4 |
+ RI 04-1 |
+
+
+ | HXB4 |
+ RI 04-2 |
+
+
+ | HXB4 |
+ RI 04-3 |
+
+
+ | HXB4 |
+ RI 04-4 |
+
+
+ | HXB5 |
+ RI 05-1 |
+
+
+ | HXB5 |
+ RI 05-2 |
+
+
+ | HXB5 |
+ RI 05-3 |
+
+
+ | HXB5 |
+ *RI 05-4 |
+
+
+ | HXB7 |
+ RI 07-1 |
+
+
+ | HXB7 |
+ RI 07-2 |
+
+
+ | HXB7 |
+ RI 07-3 |
+
+
+ | HXB7 |
+ RI 07-4 |
+
+
+ | HXB10 |
+ RI 10-1 |
+
+
+ | HXB10 |
+ RI 10-2 |
+
+
+ | HXB10 |
+ RI 10-3 |
+
+
+ | HXB10 |
+ RI 10-4 |
+
+
+ | HXB15 |
+ RI 15-1 |
+
+
+ | HXB15 |
+ RI 15-2 |
+
+
+ | HXB15 |
+ RI 15-3 |
+
+
+ | HXB15 |
+ RI 15-4 |
+
+
+ | HXB17 |
+ RI 17-1 |
+
+
+ | HXB17 |
+ RI 17-2 |
+
+
+ | HXB17 |
+ RI 17-3 |
+
+
+ | HXB17 |
+ RI 17-4 |
+
+
+ | HXB18 |
+ RI 18-1 |
+
+
+ | HXB18 |
+ RI 18-2 |
+
+
+ | HXB18 |
+ RI 18-3 |
+
+
+ | HXB18 |
+ RI 18-4 |
+
+
+ | HXB20 |
+ RI 20-1 |
+
+
+ | HXB20 |
+ RI 20-2 |
+
+
+ | HXB20 |
+ RI 20-3 |
+
+
+ | HXB20 |
+ RI 20-4 |
+
+
+ | HXB21 |
+ RI 21-1 |
+
+
+ | HXB21 |
+ RI 21-2 |
+
+
+ | HXB21 |
+ RI 21-3 |
+
+
+ | HXB21 |
+ RI 21-4 |
+
+
+ | HXB22 |
+ RI 22-1 |
+
+
+ | HXB22 |
+ RI 22-2 |
+
+
+ | HXB22 |
+ RI 22-3 |
+
+
+ | HXB22 |
+ RI 22-4 |
+
+
+ | HXB23 |
+ RI 23-1 |
+
+
+ | HXB23 |
+ RI 23-2 |
+
+
+ | HXB23 |
+ RI 23-3 |
+
+
+ | HXB23 |
+ RI 23-4 |
+
+
+ | HXB24 |
+ RI 24-1 |
+
+
+ | HXB24 |
+ RI 24-2 |
+
+
+ | HXB24 |
+ RI 24-3 |
+
+
+ | HXB24 |
+ *RI 24-4 |
+
+
+ | HXB25 |
+ RI 25-1 |
+
+
+ | HXB25 |
+ RI 25-2 |
+
+
+ | HXB25 |
+ RI 25-3 |
+
+
+ | HXB25 |
+ *RI 25-4 |
+
+
+ | HXB26 |
+ RI 26-1 |
+
+
+ | HXB26 |
+ RI 26-2 |
+
+
+ | HXB26 |
+ RI 26-3 |
+
+
+ | HXB26 |
+ RI 26-4 |
+
+
+ | HXB27 |
+ RI 27-1 |
+
+
+ | HXB27 |
+ RI 27-2 |
+
+
+ | HXB27 |
+ RI 27-3 |
+
+
+ | HXB27 |
+ RI 27-4 |
+
+
+ | HXB29 |
+ RI 29-1 |
+
+
+ | HXB29 |
+ RI 29-2 |
+
+
+ | HXB29 |
+ RI 29-3 |
+
+
+ | HXB29 |
+ *RI 29-4 |
+
+
+ | HXB31 |
+ RI 31-1 |
+
+
+ | HXB31 |
+ RI 31-2 |
+
+
+ | HXB31 |
+ RI 31-3 |
+
+
+ | HXB31 |
+ RI 31-4 |
+
+
+ | BXH2 |
+ RI 02c-1 |
+
+
+ | BXH2 |
+ RI 02c-2 |
+
+
+ | BXH2 |
+ RI 02c-3 |
+
+
+ | BXH2 |
+ RI 02c-4 |
+
+
+ | BXH3 |
+ RI 03c-1 |
+
+
+ | BXH3 |
+ RI 03c-2 |
+
+
+ | BXH3 |
+ RI 03c-3 |
+
+
+ | BXH3 |
+ RI 03c-4 |
+
+
+ | BXH5 |
+ RI 05c-1 |
+
+
+ | BXH5 |
+ RI 05c-2 |
+
+
+ | BXH5 |
+ RI 05c-3 |
+
+
+ | BXH5 |
+ *RI 05c-4 |
+
+
+ | BXH6 |
+ RI 06c-1 |
+
+
+ | BXH6 |
+ RI 06c-2 |
+
+
+ | BXH6 |
+ RI 06c-3 |
+
+
+ | BXH6 |
+ *RI 06c-4 |
+
+
+ | BXH8 |
+ RI 08c-1 |
+
+
+ | BXH8 |
+ RI 08c-2 |
+
+
+ | BXH8 |
+ RI 08c-3 |
+
+
+ | BXH8 |
+ RI 08c-4 |
+
+
+ | BXH9 |
+ RI 09c-1 |
+
+
+ | BXH9 |
+ RI 09c-2 |
+
+
+ | BXH9 |
+ RI 09c-3 |
+
+
+ | BXH9 |
+ RI 09c-4 |
+
+
+ | BXH10 |
+ RI 10c-1 |
+
+
+ | BXH10 |
+ RI 10c-2 |
+
+
+ | BXH10 |
+ RI 10c-3 |
+
+
+ | BXH11 |
+ RI 11c-1 |
+
+
+ | BXH11 |
+ RI 11c-2 |
+
+
+ | BXH11 |
+ RI 11c-3 |
+
+
+ | BXH11 |
+ *RI 11c-4 |
+
+
+ | BXH12 |
+ RI 12c-1 |
+
+
+ | BXH12 |
+ RI 12c-2 |
+
+
+ | BXH12 |
+ RI 12c-3 |
+
+
+ | BXH12 |
+ RI 12c-4 |
+
+
+ | BXH13 |
+ RI 13c-1 |
+
+
+ | BXH13 |
+ RI 13c-2 |
+
+
+ | BXH13 |
+ RI 13c-3 |
+
+
+ | BXH13 |
+ RI 13c-4 |
+
+
+
+ |
+
+
+
+
+*: These eight arrays were excluded in the final strain summary data. See section of Quality Control for further explanation.
diff --git a/general/datasets/Ki_2a_0405_rz/acknowledgment.rtf b/general/datasets/Ki_2a_0405_rz/acknowledgment.rtf
new file mode 100644
index 0000000..956eaca
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_rz/acknowledgment.rtf
@@ -0,0 +1 @@
+This work was supported with funds to TJA by the MRC Clinical Sciences Centre, the British Heart Foundation, and the Wellcome Trust Cardiovascular Functional Genomics Intiative; to NH from the German Ministry for Science and Education (National Genome Research Network); to MP and Vladimir Kren from the Grant Agency of the Czech Republic; to MP and TJA from the Wellcome Trust Collaborative Research Initiative grant, to Theodore W Kurtz from the NIH, to TWK and MP from a Fogarty International Research Collaboration Award. Microarrays were a generous donation of Affymetrix Inc. Michal Pravenec thanks the Howard Hughes Medical Institute for its support to him as an international research scholar.
diff --git a/general/datasets/Ki_2a_0405_rz/cases.rtf b/general/datasets/Ki_2a_0405_rz/cases.rtf
new file mode 100644
index 0000000..862deec
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_rz/cases.rtf
@@ -0,0 +1,7 @@
+Data were generated using the HXB/BXH recombinant inbred strains of rats generated over the past 20 years in Prague. The parental strains from which all HXB lines are derived are SHR (SHR/OlaIpcv or HSR = H) and Brown Norway (BN.Lx/Cub= B). These strains have been used extensively to study cardiovascular system physiology and genetics.
+
+
+The HXB strains were bred by Michal Pravenec at the Institute of Physiology, Czech Academy of Sciences. The BXH strains were bred by Vladimir Kren (see Pravenec et al. 1989, 2004) at a similar animal facility at the Institute of Biology and Medical Genetics, 1st Medical Faculty, Charles University. These strains are at approximately the 6oth geenration of continuous inbreeding (F60).
+
+Animals used in the transcriptome analyses of kidney and fat (Hübner and colleagues, 2005) were weaned at 4 weeks. Those born at the Charles University were transferred to the Institute of Physiology. Animals were reared on a commerical rat chow (ST-1 from VELAZ, Czech Republic). Four males were house per cage. Cages were made of polystyrene and have a floor size of 22 x 38 cm and height of 23 cm. The bedding was changed twice a week. Light cycle was 12:12 on-off. Vivarium rooms were maintained at 23 deg. C. Rats were sexually naive. All males used in the initial transcriptome studies (Hubner et al., 2005) were born between May and August 2002. They were sacrificed unfastged by rapid cervical dislocation between 9 and 10 AM, following an approved animal protocol (Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague; Animal Protectiion Law of the Czech Republic (311/1997).
+
diff --git a/general/datasets/Ki_2a_0405_rz/citation.rtf b/general/datasets/Ki_2a_0405_rz/citation.rtf
new file mode 100644
index 0000000..a8b8cc0
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_rz/citation.rtf
@@ -0,0 +1 @@
+PLoS One. 2008;3(12):e4033. doi: 10.1371/journal.pone.0004033. Epub 2008 Dec 29.
diff --git a/general/datasets/Ki_2a_0405_rz/contributors.rtf b/general/datasets/Ki_2a_0405_rz/contributors.rtf
new file mode 100644
index 0000000..0afa863
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_rz/contributors.rtf
@@ -0,0 +1 @@
+Grieve IC1, Dickens NJ, Pravenec M, Kren V, Hubner N, Cook SA, Aitman TJ, Petretto E, Mangion J. Author information 1MRC Clinical Sciences Centre, Imperial College, Hammersmith Hospital, London, United Kingdom.
diff --git a/general/datasets/Ki_2a_0405_rz/notes.rtf b/general/datasets/Ki_2a_0405_rz/notes.rtf
new file mode 100644
index 0000000..1af325d
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_rz/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by Robert Williams, Norbert Hübner, Michal Pravnec, Timothy Aitman, April 19, 2005. Updated by RWW, May 13, 2005.
+
diff --git a/general/datasets/Ki_2a_0405_rz/platform.rtf b/general/datasets/Ki_2a_0405_rz/platform.rtf
new file mode 100644
index 0000000..78c5815
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_rz/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix 230A GeneChip: Expression data were generated using the Affymetrix 230A array. The chromosomal locations of probe sets were determined by BLAT analysis of concatenated probe sequences using the Rat Genome Sequencing Consortium assembly.
+
diff --git a/general/datasets/Ki_2a_0405_rz/processing.rtf b/general/datasets/Ki_2a_0405_rz/processing.rtf
new file mode 100644
index 0000000..d75d1db
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_rz/processing.rtf
@@ -0,0 +1,15 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of pixel measured in each cell.
+
+
+Probe set data: The original CEL values were log2 transformed and quantile normalized. We then took the antilog values of these quantile adjusted CEL values as input to the standard MAS5 algorithm. Probe set values listed in WebQTL pages are typically the averages of four biological replicates within strain.
+
+
+About Quality Control Procedures:
+
+
+RNA processing:RNA was extracted using Trizol reagent (Invitrogen) and purified using an RNeasy Mini kit from Qiagen. Double-stranded cDNA was generated without pooling. The Ambion MEGAscript T7 kit from Ambion was used to generate biotinylated cRNA for kidney. Fat samples were processed at this step using the Enzo Diagnostics Bioarray High Yield RNA Transcript labeling kit. See Hübner et al. 2005 for additional detail. One-hundred and twenty eight samples passed RNA quality control steps.
+
+Probe level QC: All 128 CEL files were collected into a single DataDesk 6.2 file. Probe data from pairs of arrays were plotted and compared. Eight arrays were considered potential outliers (despite having passed RNA quality control) and in the interest of minimizing technical variance, a decision was made to withhold them from the calculation of strain means used in WebQTL. The remaining 120 arrays were quantile normalized and reexamined in DataDesk to ensure reasonble colinearity of all array data sets.
+
+Probe set level QC: Probe set level QC involves counting the number of times that a single array data set from a single sample generates outliers at the level of the probe set consensus estimates of expression. With 120 arrays, any single array should generate a comparatively small fraction of the total number of outlier calls. This final step of array QC has NOT been implemented yet in this data set.
+
diff --git a/general/datasets/Ki_2a_0405_rz/summary.rtf b/general/datasets/Ki_2a_0405_rz/summary.rtf
new file mode 100644
index 0000000..44fd86e
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_rz/summary.rtf
@@ -0,0 +1,19 @@
+This April 2005 data set provides estimates of mRNA expression in normal kidneys of 32 strains of rats. The set includes the hypertensive SHR strain, the normotensive BN strain, and 30 HXB/BXH recombinant inbred strains. Each strain was sampled in quadruplicate (6-week-old males). Animals and tissues were generated by Michal Pravenec and colleagues at the Czech Academy of Sciences (CAS). RNA samples were processed at the Max-Delbrück-Center (MDC), Berlin Buch by Nobert Hübner and colleagues. Transcriptome mapping was carried out by Timothy Aitman and colleagues at the Imperial College, London (ICL). Samples were hybridized individually to a total of 128 Affymetrix RAE230A array. This particular data set includes 120 arrays processed using a quantile normalized variant of the Affymetrix MAS5 protocol. The expression values of each array have been logged and adjusted to a mean of 8 and a stardard deviation of 2 (mean and variance stabilized). This data set complements the original MAS5 data set exploited by Hübner and colleagues 2005. Download the particular transform in an Excel work book with both strain means and SEMs.
+
+These data can also be viewed using the eQTL Explorer Java application by John Mangion, Tim Aitman, and colleagues (Mueller et al. 2006).
+
+Genome-wide co-expression analysis in multiple tissues.
+
+And see closely associate set of papers:
+
+
+ - Integrated transcriptional profiling and linkage analysis for identification of genes underlying disease.
+ - Heritability and tissue specificity of expression quantitative trait loci.
+ - Integrated genomic approaches implicate osteoglycin (Ogn) in the regulation of left ventricular mass.
+ - New insights into the genetic control of gene expression using a Bayesian multi-tissue approach.
+ - The genome sequence of the spontaneously hypertensive rat: Analysis and functional significance.
+ - A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.
+ - Integrated genomic approaches to identification of candidate genes underlying metabolic and cardiovascular phenotypes in the spontaneously hypertensive rat.
+ - Systems-level approaches reveal conservation of trans-regulated genes in the rat and genetic determinants of blood pressure in humans.
+
diff --git a/general/datasets/Ki_2a_0405_rz/tissue.rtf b/general/datasets/Ki_2a_0405_rz/tissue.rtf
new file mode 100644
index 0000000..8184532
--- /dev/null
+++ b/general/datasets/Ki_2a_0405_rz/tissue.rtf
@@ -0,0 +1,534 @@
+All tissues were collected at the age of 6 weeks. Kidneys and other organs were rapidly dissected and cleaned of fat, inserted into a vial, and immersed in liquid nitrogen for storage until RNA extraction.
+
+The table below lists the arrays by strain and sample identifier. Each array was hybridized with mRNA from a single young male rat.
+
+
+
+
+
+
+
+
+ | Strain |
+ SampleID |
+
+
+ | HSR |
+ HSR1 |
+
+
+ | HSR |
+ HSR2 |
+
+
+ | HSR |
+ HSR3 |
+
+
+ | HSR |
+ HSR4 |
+
+
+ | BN |
+ BN1 |
+
+
+ | BN |
+ BN2 |
+
+
+ | BN |
+ BN3 |
+
+
+ | BN |
+ BN4 |
+
+
+ | BN |
+ BN5 |
+
+
+ | HXB1 |
+ RI 01-1 |
+
+
+ | HXB1 |
+ RI 01-2 |
+
+
+ | HXB1 |
+ RI 01-3 |
+
+
+ | HXB1 |
+ RI 01-4 |
+
+
+ | HXB2 |
+ RI 02-1 |
+
+
+ | HXB2 |
+ RI 02-2 |
+
+
+ | HXB2 |
+ RI 02-3 |
+
+
+ | HXB2 |
+ *RI 02-4 |
+
+
+ | HXB3 |
+ RI 03-1 |
+
+
+ | HXB3 |
+ RI 03-2 |
+
+
+ | HXB3 |
+ RI 03-3 |
+
+
+ | HXB3 |
+ RI 03-4 |
+
+
+ | HXB4 |
+ RI 04-1 |
+
+
+ | HXB4 |
+ RI 04-2 |
+
+
+ | HXB4 |
+ RI 04-3 |
+
+
+ | HXB4 |
+ RI 04-4 |
+
+
+ | HXB5 |
+ RI 05-1 |
+
+
+ | HXB5 |
+ RI 05-2 |
+
+
+ | HXB5 |
+ RI 05-3 |
+
+
+ | HXB5 |
+ *RI 05-4 |
+
+
+ | HXB7 |
+ RI 07-1 |
+
+
+ | HXB7 |
+ RI 07-2 |
+
+
+ | HXB7 |
+ RI 07-3 |
+
+
+ | HXB7 |
+ RI 07-4 |
+
+
+ | HXB10 |
+ RI 10-1 |
+
+
+ | HXB10 |
+ RI 10-2 |
+
+
+ | HXB10 |
+ RI 10-3 |
+
+
+ | HXB10 |
+ RI 10-4 |
+
+
+ | HXB15 |
+ RI 15-1 |
+
+
+ | HXB15 |
+ RI 15-2 |
+
+
+ | HXB15 |
+ RI 15-3 |
+
+
+ | HXB15 |
+ RI 15-4 |
+
+
+ | HXB17 |
+ RI 17-1 |
+
+
+ | HXB17 |
+ RI 17-2 |
+
+
+ | HXB17 |
+ RI 17-3 |
+
+
+ | HXB17 |
+ RI 17-4 |
+
+
+ | HXB18 |
+ RI 18-1 |
+
+
+ | HXB18 |
+ RI 18-2 |
+
+
+ | HXB18 |
+ RI 18-3 |
+
+
+ | HXB18 |
+ RI 18-4 |
+
+
+ | HXB20 |
+ RI 20-1 |
+
+
+ | HXB20 |
+ RI 20-2 |
+
+
+ | HXB20 |
+ RI 20-3 |
+
+
+ | HXB20 |
+ RI 20-4 |
+
+
+ | HXB21 |
+ RI 21-1 |
+
+
+ | HXB21 |
+ RI 21-2 |
+
+
+ | HXB21 |
+ RI 21-3 |
+
+
+ | HXB21 |
+ RI 21-4 |
+
+
+ | HXB22 |
+ RI 22-1 |
+
+
+ | HXB22 |
+ RI 22-2 |
+
+
+ | HXB22 |
+ RI 22-3 |
+
+
+ | HXB22 |
+ RI 22-4 |
+
+
+ | HXB23 |
+ RI 23-1 |
+
+
+ | HXB23 |
+ RI 23-2 |
+
+
+ | HXB23 |
+ RI 23-3 |
+
+
+ | HXB23 |
+ RI 23-4 |
+
+
+ | HXB24 |
+ RI 24-1 |
+
+
+ | HXB24 |
+ RI 24-2 |
+
+
+ | HXB24 |
+ RI 24-3 |
+
+
+ | HXB24 |
+ *RI 24-4 |
+
+
+ | HXB25 |
+ RI 25-1 |
+
+
+ | HXB25 |
+ RI 25-2 |
+
+
+ | HXB25 |
+ RI 25-3 |
+
+
+ | HXB25 |
+ *RI 25-4 |
+
+
+ | HXB26 |
+ RI 26-1 |
+
+
+ | HXB26 |
+ RI 26-2 |
+
+
+ | HXB26 |
+ RI 26-3 |
+
+
+ | HXB26 |
+ RI 26-4 |
+
+
+ | HXB27 |
+ RI 27-1 |
+
+
+ | HXB27 |
+ RI 27-2 |
+
+
+ | HXB27 |
+ RI 27-3 |
+
+
+ | HXB27 |
+ RI 27-4 |
+
+
+ | HXB29 |
+ RI 29-1 |
+
+
+ | HXB29 |
+ RI 29-2 |
+
+
+ | HXB29 |
+ RI 29-3 |
+
+
+ | HXB29 |
+ *RI 29-4 |
+
+
+ | HXB31 |
+ RI 31-1 |
+
+
+ | HXB31 |
+ RI 31-2 |
+
+
+ | HXB31 |
+ RI 31-3 |
+
+
+ | HXB31 |
+ RI 31-4 |
+
+
+ | BXH2 |
+ RI 02c-1 |
+
+
+ | BXH2 |
+ RI 02c-2 |
+
+
+ | BXH2 |
+ RI 02c-3 |
+
+
+ | BXH2 |
+ RI 02c-4 |
+
+
+ | BXH3 |
+ RI 03c-1 |
+
+
+ | BXH3 |
+ RI 03c-2 |
+
+
+ | BXH3 |
+ RI 03c-3 |
+
+
+ | BXH3 |
+ RI 03c-4 |
+
+
+ | BXH5 |
+ RI 05c-1 |
+
+
+ | BXH5 |
+ RI 05c-2 |
+
+
+ | BXH5 |
+ RI 05c-3 |
+
+
+ | BXH5 |
+ *RI 05c-4 |
+
+
+ | BXH6 |
+ RI 06c-1 |
+
+
+ | BXH6 |
+ RI 06c-2 |
+
+
+ | BXH6 |
+ RI 06c-3 |
+
+
+ | BXH6 |
+ *RI 06c-4 |
+
+
+ | BXH8 |
+ RI 08c-1 |
+
+
+ | BXH8 |
+ RI 08c-2 |
+
+
+ | BXH8 |
+ RI 08c-3 |
+
+
+ | BXH8 |
+ RI 08c-4 |
+
+
+ | BXH9 |
+ RI 09c-1 |
+
+
+ | BXH9 |
+ RI 09c-2 |
+
+
+ | BXH9 |
+ RI 09c-3 |
+
+
+ | BXH9 |
+ RI 09c-4 |
+
+
+ | BXH10 |
+ RI 10c-1 |
+
+
+ | BXH10 |
+ RI 10c-2 |
+
+
+ | BXH10 |
+ RI 10c-3 |
+
+
+ | BXH11 |
+ RI 11c-1 |
+
+
+ | BXH11 |
+ RI 11c-2 |
+
+
+ | BXH11 |
+ RI 11c-3 |
+
+
+ | BXH11 |
+ *RI 11c-4 |
+
+
+ | BXH12 |
+ RI 12c-1 |
+
+
+ | BXH12 |
+ RI 12c-2 |
+
+
+ | BXH12 |
+ RI 12c-3 |
+
+
+ | BXH12 |
+ RI 12c-4 |
+
+
+ | BXH13 |
+ RI 13c-1 |
+
+
+ | BXH13 |
+ RI 13c-2 |
+
+
+ | BXH13 |
+ RI 13c-3 |
+
+
+ | BXH13 |
+ RI 13c-4 |
+
+
+
+ |
+
+
+
+
+*: These eight arrays were excluded in the final strain summary data. See section of Quality Control for further explanation.
diff --git a/general/datasets/Kin_ysm_a1c_0711/cases.rtf b/general/datasets/Kin_ysm_a1c_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_a1c_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_a1c_0711/citation.rtf b/general/datasets/Kin_ysm_a1c_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_a1c_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_a1c_0711/contributors.rtf b/general/datasets/Kin_ysm_a1c_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_a1c_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_a1c_0711/experiment-design.rtf b/general/datasets/Kin_ysm_a1c_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_a1c_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_a1c_0711/experiment-type.rtf b/general/datasets/Kin_ysm_a1c_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_a1c_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_a1c_0711/notes.rtf b/general/datasets/Kin_ysm_a1c_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_a1c_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_a1c_0711/processing.rtf b/general/datasets/Kin_ysm_a1c_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_a1c_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_a1c_0711/summary.rtf b/general/datasets/Kin_ysm_a1c_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_a1c_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_a1c_0711/tissue.rtf b/general/datasets/Kin_ysm_a1c_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_a1c_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_amy_0711/cases.rtf b/general/datasets/Kin_ysm_amy_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_amy_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_amy_0711/citation.rtf b/general/datasets/Kin_ysm_amy_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_amy_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_amy_0711/contributors.rtf b/general/datasets/Kin_ysm_amy_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_amy_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_amy_0711/experiment-design.rtf b/general/datasets/Kin_ysm_amy_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_amy_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_amy_0711/experiment-type.rtf b/general/datasets/Kin_ysm_amy_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_amy_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_amy_0711/notes.rtf b/general/datasets/Kin_ysm_amy_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_amy_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_amy_0711/processing.rtf b/general/datasets/Kin_ysm_amy_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_amy_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_amy_0711/summary.rtf b/general/datasets/Kin_ysm_amy_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_amy_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_amy_0711/tissue.rtf b/general/datasets/Kin_ysm_amy_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_amy_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_cbc_0711/cases.rtf b/general/datasets/Kin_ysm_cbc_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_cbc_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_cbc_0711/citation.rtf b/general/datasets/Kin_ysm_cbc_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_cbc_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_cbc_0711/contributors.rtf b/general/datasets/Kin_ysm_cbc_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_cbc_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_cbc_0711/experiment-design.rtf b/general/datasets/Kin_ysm_cbc_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_cbc_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_cbc_0711/experiment-type.rtf b/general/datasets/Kin_ysm_cbc_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_cbc_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_cbc_0711/notes.rtf b/general/datasets/Kin_ysm_cbc_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_cbc_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_cbc_0711/processing.rtf b/general/datasets/Kin_ysm_cbc_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_cbc_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_cbc_0711/summary.rtf b/general/datasets/Kin_ysm_cbc_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_cbc_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_cbc_0711/tissue.rtf b/general/datasets/Kin_ysm_cbc_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_cbc_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_dfc_0711/cases.rtf b/general/datasets/Kin_ysm_dfc_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_dfc_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_dfc_0711/citation.rtf b/general/datasets/Kin_ysm_dfc_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_dfc_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_dfc_0711/contributors.rtf b/general/datasets/Kin_ysm_dfc_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_dfc_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_dfc_0711/experiment-design.rtf b/general/datasets/Kin_ysm_dfc_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_dfc_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_dfc_0711/experiment-type.rtf b/general/datasets/Kin_ysm_dfc_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_dfc_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_dfc_0711/notes.rtf b/general/datasets/Kin_ysm_dfc_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_dfc_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_dfc_0711/processing.rtf b/general/datasets/Kin_ysm_dfc_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_dfc_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_dfc_0711/summary.rtf b/general/datasets/Kin_ysm_dfc_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_dfc_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_dfc_0711/tissue.rtf b/general/datasets/Kin_ysm_dfc_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_dfc_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_hip_0711/cases.rtf b/general/datasets/Kin_ysm_hip_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_hip_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_hip_0711/citation.rtf b/general/datasets/Kin_ysm_hip_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_hip_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_hip_0711/contributors.rtf b/general/datasets/Kin_ysm_hip_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_hip_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_hip_0711/experiment-design.rtf b/general/datasets/Kin_ysm_hip_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_hip_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_hip_0711/experiment-type.rtf b/general/datasets/Kin_ysm_hip_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_hip_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_hip_0711/notes.rtf b/general/datasets/Kin_ysm_hip_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_hip_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_hip_0711/processing.rtf b/general/datasets/Kin_ysm_hip_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_hip_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_hip_0711/summary.rtf b/general/datasets/Kin_ysm_hip_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_hip_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_hip_0711/tissue.rtf b/general/datasets/Kin_ysm_hip_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_hip_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_ipc_0711/cases.rtf b/general/datasets/Kin_ysm_ipc_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_ipc_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_ipc_0711/citation.rtf b/general/datasets/Kin_ysm_ipc_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_ipc_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_ipc_0711/contributors.rtf b/general/datasets/Kin_ysm_ipc_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_ipc_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_ipc_0711/experiment-design.rtf b/general/datasets/Kin_ysm_ipc_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_ipc_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_ipc_0711/experiment-type.rtf b/general/datasets/Kin_ysm_ipc_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_ipc_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_ipc_0711/notes.rtf b/general/datasets/Kin_ysm_ipc_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_ipc_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_ipc_0711/processing.rtf b/general/datasets/Kin_ysm_ipc_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_ipc_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_ipc_0711/summary.rtf b/general/datasets/Kin_ysm_ipc_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_ipc_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_ipc_0711/tissue.rtf b/general/datasets/Kin_ysm_ipc_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_ipc_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_itc_0711/cases.rtf b/general/datasets/Kin_ysm_itc_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_itc_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_itc_0711/citation.rtf b/general/datasets/Kin_ysm_itc_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_itc_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_itc_0711/contributors.rtf b/general/datasets/Kin_ysm_itc_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_itc_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_itc_0711/experiment-design.rtf b/general/datasets/Kin_ysm_itc_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_itc_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_itc_0711/experiment-type.rtf b/general/datasets/Kin_ysm_itc_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_itc_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_itc_0711/notes.rtf b/general/datasets/Kin_ysm_itc_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_itc_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_itc_0711/processing.rtf b/general/datasets/Kin_ysm_itc_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_itc_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_itc_0711/summary.rtf b/general/datasets/Kin_ysm_itc_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_itc_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_itc_0711/tissue.rtf b/general/datasets/Kin_ysm_itc_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_itc_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_m1c_0711/cases.rtf b/general/datasets/Kin_ysm_m1c_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_m1c_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_m1c_0711/citation.rtf b/general/datasets/Kin_ysm_m1c_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_m1c_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_m1c_0711/contributors.rtf b/general/datasets/Kin_ysm_m1c_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_m1c_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_m1c_0711/experiment-design.rtf b/general/datasets/Kin_ysm_m1c_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_m1c_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_m1c_0711/experiment-type.rtf b/general/datasets/Kin_ysm_m1c_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_m1c_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_m1c_0711/notes.rtf b/general/datasets/Kin_ysm_m1c_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_m1c_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_m1c_0711/processing.rtf b/general/datasets/Kin_ysm_m1c_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_m1c_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_m1c_0711/summary.rtf b/general/datasets/Kin_ysm_m1c_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_m1c_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_m1c_0711/tissue.rtf b/general/datasets/Kin_ysm_m1c_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_m1c_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_md_0711/cases.rtf b/general/datasets/Kin_ysm_md_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_md_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_md_0711/citation.rtf b/general/datasets/Kin_ysm_md_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_md_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_md_0711/contributors.rtf b/general/datasets/Kin_ysm_md_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_md_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_md_0711/experiment-design.rtf b/general/datasets/Kin_ysm_md_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_md_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_md_0711/experiment-type.rtf b/general/datasets/Kin_ysm_md_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_md_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_md_0711/notes.rtf b/general/datasets/Kin_ysm_md_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_md_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_md_0711/processing.rtf b/general/datasets/Kin_ysm_md_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_md_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_md_0711/summary.rtf b/general/datasets/Kin_ysm_md_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_md_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_md_0711/tissue.rtf b/general/datasets/Kin_ysm_md_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_md_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_mfc_0711/cases.rtf b/general/datasets/Kin_ysm_mfc_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_mfc_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_mfc_0711/citation.rtf b/general/datasets/Kin_ysm_mfc_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_mfc_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_mfc_0711/contributors.rtf b/general/datasets/Kin_ysm_mfc_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_mfc_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_mfc_0711/experiment-design.rtf b/general/datasets/Kin_ysm_mfc_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_mfc_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_mfc_0711/experiment-type.rtf b/general/datasets/Kin_ysm_mfc_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_mfc_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_mfc_0711/notes.rtf b/general/datasets/Kin_ysm_mfc_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_mfc_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_mfc_0711/processing.rtf b/general/datasets/Kin_ysm_mfc_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_mfc_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_mfc_0711/summary.rtf b/general/datasets/Kin_ysm_mfc_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_mfc_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_mfc_0711/tissue.rtf b/general/datasets/Kin_ysm_mfc_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_mfc_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_ofc_0711/cases.rtf b/general/datasets/Kin_ysm_ofc_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_ofc_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_ofc_0711/citation.rtf b/general/datasets/Kin_ysm_ofc_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_ofc_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_ofc_0711/contributors.rtf b/general/datasets/Kin_ysm_ofc_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_ofc_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_ofc_0711/experiment-design.rtf b/general/datasets/Kin_ysm_ofc_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_ofc_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_ofc_0711/experiment-type.rtf b/general/datasets/Kin_ysm_ofc_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_ofc_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_ofc_0711/notes.rtf b/general/datasets/Kin_ysm_ofc_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_ofc_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_ofc_0711/processing.rtf b/general/datasets/Kin_ysm_ofc_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_ofc_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_ofc_0711/summary.rtf b/general/datasets/Kin_ysm_ofc_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_ofc_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_ofc_0711/tissue.rtf b/general/datasets/Kin_ysm_ofc_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_ofc_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_s1c_0711/cases.rtf b/general/datasets/Kin_ysm_s1c_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_s1c_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_s1c_0711/citation.rtf b/general/datasets/Kin_ysm_s1c_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_s1c_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_s1c_0711/contributors.rtf b/general/datasets/Kin_ysm_s1c_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_s1c_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_s1c_0711/experiment-design.rtf b/general/datasets/Kin_ysm_s1c_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_s1c_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_s1c_0711/experiment-type.rtf b/general/datasets/Kin_ysm_s1c_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_s1c_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_s1c_0711/notes.rtf b/general/datasets/Kin_ysm_s1c_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_s1c_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_s1c_0711/processing.rtf b/general/datasets/Kin_ysm_s1c_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_s1c_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_s1c_0711/summary.rtf b/general/datasets/Kin_ysm_s1c_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_s1c_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_s1c_0711/tissue.rtf b/general/datasets/Kin_ysm_s1c_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_s1c_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_stc_0711/cases.rtf b/general/datasets/Kin_ysm_stc_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_stc_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_stc_0711/citation.rtf b/general/datasets/Kin_ysm_stc_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_stc_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_stc_0711/contributors.rtf b/general/datasets/Kin_ysm_stc_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_stc_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_stc_0711/experiment-design.rtf b/general/datasets/Kin_ysm_stc_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_stc_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_stc_0711/experiment-type.rtf b/general/datasets/Kin_ysm_stc_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_stc_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_stc_0711/notes.rtf b/general/datasets/Kin_ysm_stc_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_stc_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_stc_0711/processing.rtf b/general/datasets/Kin_ysm_stc_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_stc_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_stc_0711/summary.rtf b/general/datasets/Kin_ysm_stc_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_stc_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_stc_0711/tissue.rtf b/general/datasets/Kin_ysm_stc_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_stc_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_str_0711/cases.rtf b/general/datasets/Kin_ysm_str_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_str_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_str_0711/citation.rtf b/general/datasets/Kin_ysm_str_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_str_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_str_0711/contributors.rtf b/general/datasets/Kin_ysm_str_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_str_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_str_0711/experiment-design.rtf b/general/datasets/Kin_ysm_str_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_str_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_str_0711/experiment-type.rtf b/general/datasets/Kin_ysm_str_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_str_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_str_0711/notes.rtf b/general/datasets/Kin_ysm_str_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_str_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_str_0711/processing.rtf b/general/datasets/Kin_ysm_str_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_str_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_str_0711/summary.rtf b/general/datasets/Kin_ysm_str_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_str_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_str_0711/tissue.rtf b/general/datasets/Kin_ysm_str_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_str_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_v1c_0711/cases.rtf b/general/datasets/Kin_ysm_v1c_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_v1c_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_v1c_0711/citation.rtf b/general/datasets/Kin_ysm_v1c_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_v1c_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_v1c_0711/contributors.rtf b/general/datasets/Kin_ysm_v1c_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_v1c_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_v1c_0711/experiment-design.rtf b/general/datasets/Kin_ysm_v1c_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_v1c_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_v1c_0711/experiment-type.rtf b/general/datasets/Kin_ysm_v1c_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_v1c_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_v1c_0711/notes.rtf b/general/datasets/Kin_ysm_v1c_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_v1c_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_v1c_0711/processing.rtf b/general/datasets/Kin_ysm_v1c_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_v1c_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_v1c_0711/summary.rtf b/general/datasets/Kin_ysm_v1c_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_v1c_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_v1c_0711/tissue.rtf b/general/datasets/Kin_ysm_v1c_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_v1c_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/Kin_ysm_vfc_0711/cases.rtf b/general/datasets/Kin_ysm_vfc_0711/cases.rtf
new file mode 100644
index 0000000..7b0ef71
--- /dev/null
+++ b/general/datasets/Kin_ysm_vfc_0711/cases.rtf
@@ -0,0 +1,88 @@
+RNA was isolated from 13 brain regions, from both hemispheres, of four late mid-fetal human brains, with a total PMI of less than one hour, and hybridized to Affymetrix Human Exon 1.0 ST arrays. Affymetrix CEL files were imported into Partek GS using Robust Multichip Average (RMA) background correction, quantile normalization, and GC content correction. The normalized data were then converted to log-ratios, relative to arrays hybridized with RNA pooled from all regions of the same brain. Signal log-ratios are displayed here as green for negative (underexpression) and red for positive (overexpression).
+
+Table 1 | Periods of human development and adulthood as defined in this study.
+
+
+
+
+ | Period |
+ Description |
+ Age |
+
+
+ | 1 |
+ Embryonic |
+ 4≤ Age <8 Postconceptual weeks (PCW) |
+
+
+ | 2 |
+ Early fetal |
+ 8≤ Age <10 PCW |
+
+
+ | 3 |
+ Early fetal |
+ 10≤ Age <13 PCW |
+
+
+ | 4 |
+ Early midfetal |
+ 13≤ Age <16 PCW |
+
+
+ | 5 |
+ Early midfetal |
+ 16≤ Age <19 PCW |
+
+
+ | 6 |
+ Late midfetal |
+ 19≤ Age <24 PCW |
+
+
+ | 7 |
+ Late fetal |
+ 24≤ Age <38 PCW |
+
+
+ | 8 |
+ Neonatal and early infancy |
+ Birth≤ Age <6 Postnatal months (M) |
+
+
+ | 9 |
+ Late infancy |
+ 6 M≤ Age <12 M |
+
+
+ | 10 |
+ Early childhood |
+ 1≤ Age <6 Postnatal years (Y) |
+
+
+ | 11 |
+ Middle and late childhood |
+ 6≤ Age <12 Y |
+
+
+ | 12 |
+ Adolescence |
+ 12≤ Age <20 Y |
+
+
+ | 13 |
+ Young adulthood |
+ 20≤ Age <40 Y |
+
+
+ | 14 |
+ Middle adulthood |
+ 40≤ Age <60 Y |
+
+
+ | 15 |
+ Late adulthood |
+ 60 Y ≤ Age |
+
+
+
diff --git a/general/datasets/Kin_ysm_vfc_0711/citation.rtf b/general/datasets/Kin_ysm_vfc_0711/citation.rtf
new file mode 100644
index 0000000..d450820
--- /dev/null
+++ b/general/datasets/Kin_ysm_vfc_0711/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Johnson MB, Kawasawa YI, Mason CE, Krsnik Z et al. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 2009 May 28;62(4):494-509. PMID: 19477152
+
diff --git a/general/datasets/Kin_ysm_vfc_0711/contributors.rtf b/general/datasets/Kin_ysm_vfc_0711/contributors.rtf
new file mode 100644
index 0000000..2dfb810
--- /dev/null
+++ b/general/datasets/Kin_ysm_vfc_0711/contributors.rtf
@@ -0,0 +1 @@
+Johnson MB, Kawasawa YI, Sestan N
diff --git a/general/datasets/Kin_ysm_vfc_0711/experiment-design.rtf b/general/datasets/Kin_ysm_vfc_0711/experiment-design.rtf
new file mode 100644
index 0000000..963e517
--- /dev/null
+++ b/general/datasets/Kin_ysm_vfc_0711/experiment-design.rtf
@@ -0,0 +1,3 @@
+Human Brain Specimens and Tissue Processing This study was carried out using post-mortem human brain specimens collected from the Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM). Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed for neuropathological or developmental defects. Details of specimens, tissue processing, microdissection, and neuropathological assessment are given in the Supplemental Experimental Procedures and Table S1. These studies were approved by the Human Investigation Committees of AECOM and Yale University.
+
+For initial analysis, all neocortex samples were grouped together. In subsequent analyses, neocortex areas were compared with each other. In most analyses reported, left and right side samples were treated as additional biological replicates.
diff --git a/general/datasets/Kin_ysm_vfc_0711/experiment-type.rtf b/general/datasets/Kin_ysm_vfc_0711/experiment-type.rtf
new file mode 100644
index 0000000..beed8f4
--- /dev/null
+++ b/general/datasets/Kin_ysm_vfc_0711/experiment-type.rtf
@@ -0,0 +1,9 @@
+Human Brain Specimens and Tissue Processing
+This study was carried out using post-mortem human brain specimens collected from the
+Human Fetal Tissue Repository at the Albert Einstein College of Medicine (AECOM).
+Dissected tissue was fresh-frozen in Trizol for RNA and DNA extraction, with a post-mortem
+interval of less than 1 hour. Remaining tissue was fixed and frozen, and sections were analyzed
+for neuropathological or developmental defects. Details of specimens, tissue processing,
+microdissection, and neuropathological assessment are given in the Supplemental
+Experimental Procedures and Table S1. These studies were approved by the Human
+Investigation Committees of AECOM and Yale University.
\ No newline at end of file
diff --git a/general/datasets/Kin_ysm_vfc_0711/notes.rtf b/general/datasets/Kin_ysm_vfc_0711/notes.rtf
new file mode 100644
index 0000000..8d266d3
--- /dev/null
+++ b/general/datasets/Kin_ysm_vfc_0711/notes.rtf
@@ -0,0 +1 @@
+The raw microarray data are available via the NCBI Gene Expression Omnibus. Data in GeneNetwork as of July 2015 are only gene-level data. We could also enter exon-level data on request.
diff --git a/general/datasets/Kin_ysm_vfc_0711/processing.rtf b/general/datasets/Kin_ysm_vfc_0711/processing.rtf
new file mode 100644
index 0000000..1920ca7
--- /dev/null
+++ b/general/datasets/Kin_ysm_vfc_0711/processing.rtf
@@ -0,0 +1 @@
+Normalized method: Quantile normalization. Partek Genomics Suite version 6.5 (Partek Incorporated, St. Louis, MO, USA) was used to normalize raw exon array data and to summarize expression of the probe set and transcript cluster. Affymetrix CEL files that passed QC analyses were imported into Partek Genomics Suite using the default Partek settings: RMA background correction114, quantile normalization, mean probe set summarization, and log2-transformation. Only high-quality core probe sets, as defined by Affymetrix, were included. 105,271 core probes (within 62,448 probe sets out of 230,918 core probe sets) contained SNPs defined in the probe group file HuEx-1_0-st-v2.r2-SNPs-Excluded.pgf provided by Affymetrix, which is based on the dbSNP database (version 129, April 2008) and SNPinprobe_1.0 database. we removed SNP-containing probe sets during the normalization step in the Partek program to be control for SNP-related confounding effects. The median of all individual probe sets of one transcript cluster was used as the estimate of gene expression values.
diff --git a/general/datasets/Kin_ysm_vfc_0711/summary.rtf b/general/datasets/Kin_ysm_vfc_0711/summary.rtf
new file mode 100644
index 0000000..66a2289
--- /dev/null
+++ b/general/datasets/Kin_ysm_vfc_0711/summary.rtf
@@ -0,0 +1 @@
+Our understanding of the evolution, formation, and pathological disruption of human brain circuits is impeded by a lack of comprehensive data on the developing brain transcriptome. Thus, we have undertaken whole-genome, exon-level expression analysis of thirteen regions from left and right sides of the mid-fetal human brain, finding 76% of genes to be expressed, and 44% of these to be differentially regulated. These data reveal a large number of specific gene expression and alternative splicing patterns, as well as co-expression networks, associated with distinct regions and neurodevelopmental processes. Of particular relevance to cognitive specializations, we have characterized the transcriptional landscapes of prefrontal cortex and perisylvian speech and language areas, which exhibit a population-level global expression symmetry. Finally, we show that differentially expressed genes are more frequently associated with human-specific evolution of putative cis-regulatory elements. Altogether, these data provide a wealth of novel biological insights into the complex transcriptional and molecular underpinnings of human brain development and evolution.
diff --git a/general/datasets/Kin_ysm_vfc_0711/tissue.rtf b/general/datasets/Kin_ysm_vfc_0711/tissue.rtf
new file mode 100644
index 0000000..f08a838
--- /dev/null
+++ b/general/datasets/Kin_ysm_vfc_0711/tissue.rtf
@@ -0,0 +1,109 @@
+Tissue was microdissected from 13 regions, including 9 distinct neocortical areas, from both left and right sides of four late second trimester human brain specimens. Gene- and exon-level differential expression analyses were performed by mixed model, nested analysis of variance using the XRAY software from Biotique Systems. Further details available in Johnson, Kawasawa, et al., "Functional and Evolutionary Insights into Human Brain Development through Global Transcriptome Analysis" Neuron, Volume 62, Issue 4, 2009.
+
+Ethnicity codes are as follows: AA = African American, A = , A/E = X, As,= , H = , E = , CC = and n/a= unknown
+
+
+
+This track displays exon microarray expression data from the late mid-fetal human brain, generated by the Sestan Lab at Yale University. The data represent 13 brain regions, including nine areas of neocortex, and both hemispheres. By default, arrays are grouped by the median for each brain region, including each neocortical area. Alternatively, neocortex areas can be grouped together; arrays can be grouped by mean; or all 95 arrays can be shown individually.
+
+Table 2 | Ontology and nomenclature of analyzed brain regions and neocortical areas.
+
+
+
+
+ | Period 1 |
+ Period 2 |
+ Period 3 - 15 |
+
+
+ | FC: Frontal cerebral wall |
+ FC |
+ OFC: Orbital prefrontal cortex |
+
+
+ | |
+ |
+ DFC: Dorsolateral prefrontal cortex |
+
+
+ | |
+ |
+ VFC: Ventrolateral prefrontal cortex |
+
+
+ | |
+ |
+ MFC: Medial prefrontal cortex |
+
+
+ | |
+ |
+ M1C: Primary motor (M1) cortex |
+
+
+ | PC: Parietal cerebral wall |
+ PC |
+ S1C: Primary somatosensory (S1) cortex |
+
+
+ | |
+ |
+ IPC: Posterior inferior parietal cortex |
+
+
+ | TC: Temporal cerebral wall |
+ TC |
+  A1C: Primary auditory (A1) cortex |
+
+
+ | |
+ |
+ STC: Posterior superior temporal cortex |
+
+
+ | |
+ |
+ ITC: Inferior temporal cortex |
+
+
+ | OC: Occipital cerebral wall |
+ OC |
+ V1C: Primary visual (V1) cortex |
+
+
+ | HIP: Hippocampal anlage |
+ HIP |
+ HIP: Hippocampus |
+
+
+ | |
+ |
+ AMY: Amygdala |
+
+
+ | VF: Ventral forebrain |
+ CGE: Caudal ganglionic eminence |
+ STR: Striatum |
+
+
+ | |
+ LGE: Lateral ganglionic eminence |
+ |
+
+
+ | |
+ MGE: Medial ganglionic eminence |
+ |
+
+
+ | DIE: Diencephalon |
+ DTH: Dorsal thalamus |
+ MD: Mediodorsal nucleus of thalamus |
+
+
+ | URL: Upper (rostral) rhombic lip |
+ URL |
+ CBC: Cerebellar cortex |
+
+
+
diff --git a/general/datasets/LGSM_AIG34_50_56_GBSPublish/specifics.rtf b/general/datasets/LGSM_AIG34_50_56_GBSPublish/specifics.rtf
deleted file mode 100644
index ab45490..0000000
--- a/general/datasets/LGSM_AIG34_50_56_GBSPublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Phenotypes
\ No newline at end of file
diff --git a/general/datasets/LGSM_AIG34_50_56_GBSPublish/summary.rtf b/general/datasets/LGSM_AIG34_50_56_GBSPublish/summary.rtf
deleted file mode 100644
index 32329c0..0000000
--- a/general/datasets/LGSM_AIG34_50_56_GBSPublish/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Muscle bulk in adult healthy humans is highly variable even after accounting for height, age and sex. Low muscle mass, due to fewer and/or smaller constituent muscle fibers, would exacerbate the impact of muscle loss occurring in aging or disease. Genetic variability substantially influences muscle mass differences, but causative genes remain largely unknown. In a genome-wide association study (GWAS) on appendicular lean mass (ALM) in a population of 85,750 middle-age (38-49 years) individuals from the UK Biobank (UKB) we found 182 loci associated with ALM (P<5x10-8). We replicated associations for 78% of these loci (P<5x10-8) with ALM in a population of 181,862 elderly (60-74 years) individuals from UKB. We also conducted a GWAS on hindlimb skeletal muscle mass of 1,867 mice from an advanced intercross between two inbred strains (LG/J and SM/J) which identified 23 quantitative trait loci. 38 positional candidates distributed across 5 loci overlapped between the two species. In vitro studies of positional candidates confirmed CPNE1 and STC2 as modifiers of myogenesis. Collectively, these findings shed light on the genetics of muscle mass variability in humans and identify targets for the development of interventions for treatment of muscle loss. The overlapping results between humans and the mouse model GWAS point to shared genetic mechanisms across species.
-
-Reference collection
diff --git a/general/datasets/LGSM_AI_G34_39_43_GBSPublish/specifics.rtf b/general/datasets/LGSM_AI_G34_39_43_GBSPublish/specifics.rtf
deleted file mode 100644
index ab45490..0000000
--- a/general/datasets/LGSM_AI_G34_39_43_GBSPublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Phenotypes
\ No newline at end of file
diff --git a/general/datasets/LGSM_AI_G34_39_43_GBSPublish/summary.rtf b/general/datasets/LGSM_AI_G34_39_43_GBSPublish/summary.rtf
deleted file mode 100644
index 383339b..0000000
--- a/general/datasets/LGSM_AI_G34_39_43_GBSPublish/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-LGSM AI G39-43 Palmer (GBS)
diff --git a/general/datasets/LGSM_AI_G34_APublish/specifics.rtf b/general/datasets/LGSM_AI_G34_APublish/specifics.rtf
deleted file mode 100644
index ab45490..0000000
--- a/general/datasets/LGSM_AI_G34_APublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Phenotypes
\ No newline at end of file
diff --git a/general/datasets/LGSM_AI_G34_APublish/summary.rtf b/general/datasets/LGSM_AI_G34_APublish/summary.rtf
deleted file mode 100644
index 85836e3..0000000
--- a/general/datasets/LGSM_AI_G34_APublish/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-LGSM AI G34 Palmer (Array)
diff --git a/general/datasets/LGSM_AI_G34_GBSPublish/specifics.rtf b/general/datasets/LGSM_AI_G34_GBSPublish/specifics.rtf
deleted file mode 100644
index ab45490..0000000
--- a/general/datasets/LGSM_AI_G34_GBSPublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Phenotypes
\ No newline at end of file
diff --git a/general/datasets/LGSM_AI_G34_GBSPublish/summary.rtf b/general/datasets/LGSM_AI_G34_GBSPublish/summary.rtf
deleted file mode 100644
index 9899270..0000000
--- a/general/datasets/LGSM_AI_G34_GBSPublish/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-LGSM AI G34 Palmer (GBS)
diff --git a/general/datasets/LGSM_AI_G39_43_GBSPublish/specifics.rtf b/general/datasets/LGSM_AI_G39_43_GBSPublish/specifics.rtf
deleted file mode 100644
index ab45490..0000000
--- a/general/datasets/LGSM_AI_G39_43_GBSPublish/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Phenotypes
\ No newline at end of file
diff --git a/general/datasets/LGSM_AI_G39_43_GBSPublish/summary.rtf b/general/datasets/LGSM_AI_G39_43_GBSPublish/summary.rtf
deleted file mode 100644
index 5f4e985..0000000
--- a/general/datasets/LGSM_AI_G39_43_GBSPublish/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-LGSM AI G34 G39-43 Palmer (GBS)
diff --git a/general/datasets/LSRU_CC_ST_1219/acknowledgment.rtf b/general/datasets/LSRU_CC_ST_1219/acknowledgment.rtf
deleted file mode 100644
index 3b345f3..0000000
--- a/general/datasets/LSRU_CC_ST_1219/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-LS and MB would like to thank the Luxembourg National Research Fund (FNR) for the support (FNR CORE C15/BM/10406131 grant).
diff --git a/general/datasets/LSRU_CC_ST_1219/cases.rtf b/general/datasets/LSRU_CC_ST_1219/cases.rtf
deleted file mode 100644
index f519f24..0000000
--- a/general/datasets/LSRU_CC_ST_1219/cases.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-CC mice were bred by Dr. Klaus Schughart at the HZI, Braunschweig, Germany.
-
-Note: Only one of 8 - 10 male samples was processed for RNA-seq (unilateral dissection of VMB). Luxembourg team also has 8 - 10 female samples. 16 to 20 complete brain hemispheres fixed in paraformaldehyde for 48 hours and then transferred to PBS with sodium azide (now stored at 4 degree Celsius at BT1, 7 ave des Hauts-Fourneaux, L-4362 Esch-sur-Alzette).
-
-C57BL/6J, A/J, and DBA/2J were bred by University of Luxembourg.
diff --git a/general/datasets/LSRU_CC_ST_1219/experiment-design.rtf b/general/datasets/LSRU_CC_ST_1219/experiment-design.rtf
deleted file mode 100644
index e2c242d..0000000
--- a/general/datasets/LSRU_CC_ST_1219/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Single-end 75bp reads at a depth of about 30 million reads/sample. Processed by Yujuan Gui using both RPKM and TPM. Log2 of TPM+1 uploaded into GeneNetwork Dec 2019 by Arthur Centeno and Robert W. Williams.
-
-Half of the C57BL/6J and A/J were sequenced in Genomics Core Facility - EMBL Heidelberg with single-end 80bp reads at a depth of about 30 million reads/sample.
diff --git a/general/datasets/LSRU_CC_ST_1219/platform.rtf b/general/datasets/LSRU_CC_ST_1219/platform.rtf
deleted file mode 100644
index a9c7084..0000000
--- a/general/datasets/LSRU_CC_ST_1219/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Illumina NextSeq 5000
diff --git a/general/datasets/LSRU_CC_ST_1219/processing.rtf b/general/datasets/LSRU_CC_ST_1219/processing.rtf
deleted file mode 100644
index 3a35b8f..0000000
--- a/general/datasets/LSRU_CC_ST_1219/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Sequencing data processed by Yujuan Gui. Sequencing data were TPM transformed then log2.
diff --git a/general/datasets/LSRU_CC_ST_1219/specifics.rtf b/general/datasets/LSRU_CC_ST_1219/specifics.rtf
deleted file mode 100644
index 4609fdf..0000000
--- a/general/datasets/LSRU_CC_ST_1219/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-CC
\ No newline at end of file
diff --git a/general/datasets/LSRU_CC_ST_1219/summary.rtf b/general/datasets/LSRU_CC_ST_1219/summary.rtf
deleted file mode 100644
index aaf3176..0000000
--- a/general/datasets/LSRU_CC_ST_1219/summary.rtf
+++ /dev/null
@@ -1,13 +0,0 @@
-RNA-seq on ventral midbrains, all animals ~ 3-month old.
-
-Collaborative Cross: 1 male per strain for 32 CC strains.
-
-C57BL/6J, A/J, and DBA/2J: The value is the mean of 12 samples (6 males + 6 females).
-
-Team of Investigators:
-
-Lasse Sinkkkonen, Manuel Buttini, Yujuan Gui, and Melanie Thomas at the University of Luxembourg
-
-Data entered into GeneNetwork December 2019 by Arthur Centeno, Robert W. Williams, Yujuan Gui
-
-
diff --git a/general/datasets/LSRU_CC_ST_1219/tissue.rtf b/general/datasets/LSRU_CC_ST_1219/tissue.rtf
deleted file mode 100644
index e8f4aff..0000000
--- a/general/datasets/LSRU_CC_ST_1219/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Ventral midbrains
diff --git a/general/datasets/Lgsm_ai_g34_39_43_gbspublish/specifics.rtf b/general/datasets/Lgsm_ai_g34_39_43_gbspublish/specifics.rtf
new file mode 100644
index 0000000..ab45490
--- /dev/null
+++ b/general/datasets/Lgsm_ai_g34_39_43_gbspublish/specifics.rtf
@@ -0,0 +1 @@
+Phenotypes
\ No newline at end of file
diff --git a/general/datasets/Lgsm_ai_g34_39_43_gbspublish/summary.rtf b/general/datasets/Lgsm_ai_g34_39_43_gbspublish/summary.rtf
new file mode 100644
index 0000000..383339b
--- /dev/null
+++ b/general/datasets/Lgsm_ai_g34_39_43_gbspublish/summary.rtf
@@ -0,0 +1 @@
+LGSM AI G39-43 Palmer (GBS)
diff --git a/general/datasets/Lgsm_ai_g34_apublish/specifics.rtf b/general/datasets/Lgsm_ai_g34_apublish/specifics.rtf
new file mode 100644
index 0000000..ab45490
--- /dev/null
+++ b/general/datasets/Lgsm_ai_g34_apublish/specifics.rtf
@@ -0,0 +1 @@
+Phenotypes
\ No newline at end of file
diff --git a/general/datasets/Lgsm_ai_g34_apublish/summary.rtf b/general/datasets/Lgsm_ai_g34_apublish/summary.rtf
new file mode 100644
index 0000000..85836e3
--- /dev/null
+++ b/general/datasets/Lgsm_ai_g34_apublish/summary.rtf
@@ -0,0 +1 @@
+LGSM AI G34 Palmer (Array)
diff --git a/general/datasets/Lgsm_ai_g34_gbspublish/specifics.rtf b/general/datasets/Lgsm_ai_g34_gbspublish/specifics.rtf
new file mode 100644
index 0000000..ab45490
--- /dev/null
+++ b/general/datasets/Lgsm_ai_g34_gbspublish/specifics.rtf
@@ -0,0 +1 @@
+Phenotypes
\ No newline at end of file
diff --git a/general/datasets/Lgsm_ai_g34_gbspublish/summary.rtf b/general/datasets/Lgsm_ai_g34_gbspublish/summary.rtf
new file mode 100644
index 0000000..9899270
--- /dev/null
+++ b/general/datasets/Lgsm_ai_g34_gbspublish/summary.rtf
@@ -0,0 +1 @@
+LGSM AI G34 Palmer (GBS)
diff --git a/general/datasets/Lgsm_ai_g39_43_gbspublish/specifics.rtf b/general/datasets/Lgsm_ai_g39_43_gbspublish/specifics.rtf
new file mode 100644
index 0000000..ab45490
--- /dev/null
+++ b/general/datasets/Lgsm_ai_g39_43_gbspublish/specifics.rtf
@@ -0,0 +1 @@
+Phenotypes
\ No newline at end of file
diff --git a/general/datasets/Lgsm_ai_g39_43_gbspublish/summary.rtf b/general/datasets/Lgsm_ai_g39_43_gbspublish/summary.rtf
new file mode 100644
index 0000000..5f4e985
--- /dev/null
+++ b/general/datasets/Lgsm_ai_g39_43_gbspublish/summary.rtf
@@ -0,0 +1 @@
+LGSM AI G34 G39-43 Palmer (GBS)
diff --git a/general/datasets/Lgsm_aig34_50_56_gbspublish/contributors.rtf b/general/datasets/Lgsm_aig34_50_56_gbspublish/contributors.rtf
new file mode 100644
index 0000000..af3e1ca
--- /dev/null
+++ b/general/datasets/Lgsm_aig34_50_56_gbspublish/contributors.rtf
@@ -0,0 +1 @@
+Hernandez Cordero AI, Gonzales NM, Parker CC, Sokoloff G, Vandenbergh DJ, Cheng R, Abney M, Skol A, Douglas A, Palmer AA, Gregory JS, Lionikas A
diff --git a/general/datasets/Lgsm_aig34_50_56_gbspublish/specifics.rtf b/general/datasets/Lgsm_aig34_50_56_gbspublish/specifics.rtf
new file mode 100644
index 0000000..ab45490
--- /dev/null
+++ b/general/datasets/Lgsm_aig34_50_56_gbspublish/specifics.rtf
@@ -0,0 +1 @@
+Phenotypes
\ No newline at end of file
diff --git a/general/datasets/Lgsm_aig34_50_56_gbspublish/summary.rtf b/general/datasets/Lgsm_aig34_50_56_gbspublish/summary.rtf
new file mode 100644
index 0000000..32329c0
--- /dev/null
+++ b/general/datasets/Lgsm_aig34_50_56_gbspublish/summary.rtf
@@ -0,0 +1,3 @@
+Muscle bulk in adult healthy humans is highly variable even after accounting for height, age and sex. Low muscle mass, due to fewer and/or smaller constituent muscle fibers, would exacerbate the impact of muscle loss occurring in aging or disease. Genetic variability substantially influences muscle mass differences, but causative genes remain largely unknown. In a genome-wide association study (GWAS) on appendicular lean mass (ALM) in a population of 85,750 middle-age (38-49 years) individuals from the UK Biobank (UKB) we found 182 loci associated with ALM (P<5x10-8). We replicated associations for 78% of these loci (P<5x10-8) with ALM in a population of 181,862 elderly (60-74 years) individuals from UKB. We also conducted a GWAS on hindlimb skeletal muscle mass of 1,867 mice from an advanced intercross between two inbred strains (LG/J and SM/J) which identified 23 quantitative trait loci. 38 positional candidates distributed across 5 loci overlapped between the two species. In vitro studies of positional candidates confirmed CPNE1 and STC2 as modifiers of myogenesis. Collectively, these findings shed light on the genetics of muscle mass variability in humans and identify targets for the development of interventions for treatment of muscle loss. The overlapping results between humans and the mouse model GWAS point to shared genetic mechanisms across species.
+
+Reference collection
diff --git a/general/datasets/Linsenbardt_BoehmGeno/summary.rtf b/general/datasets/Linsenbardt_BoehmGeno/summary.rtf
deleted file mode 100644
index f8938b3..0000000
--- a/general/datasets/Linsenbardt_BoehmGeno/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Error-correcting for the genotypes for the first 96 EtOH-sensitived B6xD2 F2-S4 cases it's done. Genotypes are good and the kinship matrix and family structure all makes sense. You can certainly detect the family structure of this six generation cross. This data set can only be mapped correctly using your new Py-LMM code in GeneNetwork 2.
diff --git a/general/datasets/Linsenbardt_BoehmPublish/summary.rtf b/general/datasets/Linsenbardt_BoehmPublish/summary.rtf
deleted file mode 100644
index b04eab6..0000000
--- a/general/datasets/Linsenbardt_BoehmPublish/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Currently this dataset is private
diff --git a/general/datasets/Linsenbardt_boehmgeno/summary.rtf b/general/datasets/Linsenbardt_boehmgeno/summary.rtf
new file mode 100644
index 0000000..f8938b3
--- /dev/null
+++ b/general/datasets/Linsenbardt_boehmgeno/summary.rtf
@@ -0,0 +1 @@
+Error-correcting for the genotypes for the first 96 EtOH-sensitived B6xD2 F2-S4 cases it's done. Genotypes are good and the kinship matrix and family structure all makes sense. You can certainly detect the family structure of this six generation cross. This data set can only be mapped correctly using your new Py-LMM code in GeneNetwork 2.
diff --git a/general/datasets/Linsenbardt_boehmpublish/summary.rtf b/general/datasets/Linsenbardt_boehmpublish/summary.rtf
new file mode 100644
index 0000000..b04eab6
--- /dev/null
+++ b/general/datasets/Linsenbardt_boehmpublish/summary.rtf
@@ -0,0 +1 @@
+Currently this dataset is private
diff --git a/general/datasets/Lsru_cc_st_1219/acknowledgment.rtf b/general/datasets/Lsru_cc_st_1219/acknowledgment.rtf
new file mode 100644
index 0000000..3b345f3
--- /dev/null
+++ b/general/datasets/Lsru_cc_st_1219/acknowledgment.rtf
@@ -0,0 +1 @@
+LS and MB would like to thank the Luxembourg National Research Fund (FNR) for the support (FNR CORE C15/BM/10406131 grant).
diff --git a/general/datasets/Lsru_cc_st_1219/cases.rtf b/general/datasets/Lsru_cc_st_1219/cases.rtf
new file mode 100644
index 0000000..f519f24
--- /dev/null
+++ b/general/datasets/Lsru_cc_st_1219/cases.rtf
@@ -0,0 +1,5 @@
+CC mice were bred by Dr. Klaus Schughart at the HZI, Braunschweig, Germany.
+
+Note: Only one of 8 - 10 male samples was processed for RNA-seq (unilateral dissection of VMB). Luxembourg team also has 8 - 10 female samples. 16 to 20 complete brain hemispheres fixed in paraformaldehyde for 48 hours and then transferred to PBS with sodium azide (now stored at 4 degree Celsius at BT1, 7 ave des Hauts-Fourneaux, L-4362 Esch-sur-Alzette).
+
+C57BL/6J, A/J, and DBA/2J were bred by University of Luxembourg.
diff --git a/general/datasets/Lsru_cc_st_1219/citation.rtf b/general/datasets/Lsru_cc_st_1219/citation.rtf
new file mode 100644
index 0000000..94560c7
--- /dev/null
+++ b/general/datasets/Lsru_cc_st_1219/citation.rtf
@@ -0,0 +1 @@
+None as of December 2019
diff --git a/general/datasets/Lsru_cc_st_1219/contributors.rtf b/general/datasets/Lsru_cc_st_1219/contributors.rtf
new file mode 100644
index 0000000..c0e81ee
--- /dev/null
+++ b/general/datasets/Lsru_cc_st_1219/contributors.rtf
@@ -0,0 +1,5 @@
+manuel.buttini@uni.lu
+
+lasse.sinkkonen@uni.lu
+
+yujuan.gui@uni.lu
diff --git a/general/datasets/Lsru_cc_st_1219/experiment-design.rtf b/general/datasets/Lsru_cc_st_1219/experiment-design.rtf
new file mode 100644
index 0000000..e2c242d
--- /dev/null
+++ b/general/datasets/Lsru_cc_st_1219/experiment-design.rtf
@@ -0,0 +1,3 @@
+Single-end 75bp reads at a depth of about 30 million reads/sample. Processed by Yujuan Gui using both RPKM and TPM. Log2 of TPM+1 uploaded into GeneNetwork Dec 2019 by Arthur Centeno and Robert W. Williams.
+
+Half of the C57BL/6J and A/J were sequenced in Genomics Core Facility - EMBL Heidelberg with single-end 80bp reads at a depth of about 30 million reads/sample.
diff --git a/general/datasets/Lsru_cc_st_1219/platform.rtf b/general/datasets/Lsru_cc_st_1219/platform.rtf
new file mode 100644
index 0000000..a9c7084
--- /dev/null
+++ b/general/datasets/Lsru_cc_st_1219/platform.rtf
@@ -0,0 +1 @@
+Illumina NextSeq 5000
diff --git a/general/datasets/Lsru_cc_st_1219/processing.rtf b/general/datasets/Lsru_cc_st_1219/processing.rtf
new file mode 100644
index 0000000..3a35b8f
--- /dev/null
+++ b/general/datasets/Lsru_cc_st_1219/processing.rtf
@@ -0,0 +1 @@
+Sequencing data processed by Yujuan Gui. Sequencing data were TPM transformed then log2.
diff --git a/general/datasets/Lsru_cc_st_1219/specifics.rtf b/general/datasets/Lsru_cc_st_1219/specifics.rtf
new file mode 100644
index 0000000..4609fdf
--- /dev/null
+++ b/general/datasets/Lsru_cc_st_1219/specifics.rtf
@@ -0,0 +1 @@
+CC
\ No newline at end of file
diff --git a/general/datasets/Lsru_cc_st_1219/summary.rtf b/general/datasets/Lsru_cc_st_1219/summary.rtf
new file mode 100644
index 0000000..aaf3176
--- /dev/null
+++ b/general/datasets/Lsru_cc_st_1219/summary.rtf
@@ -0,0 +1,13 @@
+RNA-seq on ventral midbrains, all animals ~ 3-month old.
+
+Collaborative Cross: 1 male per strain for 32 CC strains.
+
+C57BL/6J, A/J, and DBA/2J: The value is the mean of 12 samples (6 males + 6 females).
+
+Team of Investigators:
+
+Lasse Sinkkkonen, Manuel Buttini, Yujuan Gui, and Melanie Thomas at the University of Luxembourg
+
+Data entered into GeneNetwork December 2019 by Arthur Centeno, Robert W. Williams, Yujuan Gui
+
+
diff --git a/general/datasets/Lsru_cc_st_1219/tissue.rtf b/general/datasets/Lsru_cc_st_1219/tissue.rtf
new file mode 100644
index 0000000..e8f4aff
--- /dev/null
+++ b/general/datasets/Lsru_cc_st_1219/tissue.rtf
@@ -0,0 +1 @@
+Ventral midbrains
diff --git a/general/datasets/Luca_gse23352hlt0613/citation.rtf b/general/datasets/Luca_gse23352hlt0613/citation.rtf
new file mode 100644
index 0000000..2aafa46
--- /dev/null
+++ b/general/datasets/Luca_gse23352hlt0613/citation.rtf
@@ -0,0 +1 @@
+Bossé Y, Postma DS, Sin DD, Lamontagne M et al. Molecular signature of smoking in human lung tissues. Cancer Res 2012 Aug 1;72(15):3753-63. PMID: 22659451
diff --git a/general/datasets/Luca_gse23352hlt0613/contributors.rtf b/general/datasets/Luca_gse23352hlt0613/contributors.rtf
new file mode 100644
index 0000000..a22a4a5
--- /dev/null
+++ b/general/datasets/Luca_gse23352hlt0613/contributors.rtf
@@ -0,0 +1 @@
+Bossé Y, Laviolette M
diff --git a/general/datasets/Luca_gse23352hlt0613/summary.rtf b/general/datasets/Luca_gse23352hlt0613/summary.rtf
new file mode 100644
index 0000000..9cb9538
--- /dev/null
+++ b/general/datasets/Luca_gse23352hlt0613/summary.rtf
@@ -0,0 +1,15 @@
+This SuperSeries is composed of the following SubSeries:
+
+
+
+
+ | GSE23352 Whole-genome gene expression profiles of non-tumorous human lung tissues: Laval set |
+
+
+ | GSE23529 Whole-genome gene expression profiles of non-tumorous human lung tissues: UBC set |
+
+
+ | GSE23545 Whole-genome gene expression profiles of non-tumorous human lung tissues: GRNG set |
+
+
+
diff --git a/general/datasets/Lv_g_0106_b/citation.rtf b/general/datasets/Lv_g_0106_b/citation.rtf
new file mode 100644
index 0000000..2f6dbd6
--- /dev/null
+++ b/general/datasets/Lv_g_0106_b/citation.rtf
@@ -0,0 +1 @@
+Genome-level analysis of genetic regulation of liver gene expression networks. Gatti D, Maki A, Chesler EJ, Kirova R, Kosyk O, Lu L, Manly KF, Williams RW, Perkins A, Langston MA, Threadgill DW, Rusyn I. Hepatology. 2007 Aug;46(2):548-57. PMID: 17542012
diff --git a/general/datasets/Lv_g_0106_b/platform.rtf b/general/datasets/Lv_g_0106_b/platform.rtf
new file mode 100644
index 0000000..dd35c6a
--- /dev/null
+++ b/general/datasets/Lv_g_0106_b/platform.rtf
@@ -0,0 +1 @@
+The arrays were Agilent two color arrays.
diff --git a/general/datasets/Lv_g_0106_b/processing.rtf b/general/datasets/Lv_g_0106_b/processing.rtf
new file mode 100644
index 0000000..ae2363c
--- /dev/null
+++ b/general/datasets/Lv_g_0106_b/processing.rtf
@@ -0,0 +1 @@
+We used a mix of C57BL/6J RNA as the reference (liver, kidney, lung, brain and spleen). Each measurement is the ratio of sample intensity over the reference intensity. The data was normalized using a robust LOWESS smoothing method that adjusts for non-linearity between the two color channels (see Yang Yee Hwa et. al., Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation, Nucl. Acid Res., 2002). We then took the log2 of these ratios. A value of 1 indicates that the expression of that gene in the sample is twice that of the reference. Since the reference, includes liver, the range of values is more modest than some other scales of gene expression. (From Dan Gatti, Sept 2012).
diff --git a/general/datasets/Lv_g_0106_b/summary.rtf b/general/datasets/Lv_g_0106_b/summary.rtf
new file mode 100644
index 0000000..fe91a13
--- /dev/null
+++ b/general/datasets/Lv_g_0106_b/summary.rtf
@@ -0,0 +1,9 @@
+Genome-level analysis of genetic regulation of liver gene expression networks
+
+Gatti D, Maki A, Chesler EJ, Kirova R, Kosyk O, Lu L, Manly KF, Williams RW, Perkins A, Langston MA, Threadgill DW, Rusyn I
+
+Hepatology. 2007 Aug;46(2):548-57
+
+Source: Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
+
+The liver is the primary site for the metabolism of nutrients, drugs, and chemical agents. Although metabolic pathways are complex and tightly regulated, genetic variation among individuals, reflected in variations in gene expression levels, introduces complexity into research on liver disease. This study dissected genetic networks that control liver gene expression through the combination of large-scale quantitative mRNA expression analysis with genetic mapping in a reference population of BXD recombinant inbred mouse strains for which extensive single-nucleotide polymorphism, haplotype, and phenotypic data are publicly available. We profiled gene expression in livers of naive mice of both sexes from C57BL/6J, DBA/2J, B6D2F1, and 37 BXD strains using Agilent oligonucleotide microarrays. These data were used to map quantitative trait loci (QTLs) responsible for variations in the expression of about 19,000 transcripts. We identified polymorphic local and distant QTLs, including several loci that control the expression of large numbers of genes in liver, by comparing the physical transcript position with the location of the controlling QTL. CONCLUSION: The data are available through a public web-based resource (www.genenetwork.org) that allows custom data mining, identification of coregulated transcripts and correlated phenotypes, cross-tissue, and cross-species comparisons, as well as testing of a broad array of hypotheses.
diff --git a/general/datasets/Lv_g_0106_f/citation.rtf b/general/datasets/Lv_g_0106_f/citation.rtf
new file mode 100644
index 0000000..2f6dbd6
--- /dev/null
+++ b/general/datasets/Lv_g_0106_f/citation.rtf
@@ -0,0 +1 @@
+Genome-level analysis of genetic regulation of liver gene expression networks. Gatti D, Maki A, Chesler EJ, Kirova R, Kosyk O, Lu L, Manly KF, Williams RW, Perkins A, Langston MA, Threadgill DW, Rusyn I. Hepatology. 2007 Aug;46(2):548-57. PMID: 17542012
diff --git a/general/datasets/Lv_g_0106_f/platform.rtf b/general/datasets/Lv_g_0106_f/platform.rtf
new file mode 100644
index 0000000..dd35c6a
--- /dev/null
+++ b/general/datasets/Lv_g_0106_f/platform.rtf
@@ -0,0 +1 @@
+The arrays were Agilent two color arrays.
diff --git a/general/datasets/Lv_g_0106_f/processing.rtf b/general/datasets/Lv_g_0106_f/processing.rtf
new file mode 100644
index 0000000..ae2363c
--- /dev/null
+++ b/general/datasets/Lv_g_0106_f/processing.rtf
@@ -0,0 +1 @@
+We used a mix of C57BL/6J RNA as the reference (liver, kidney, lung, brain and spleen). Each measurement is the ratio of sample intensity over the reference intensity. The data was normalized using a robust LOWESS smoothing method that adjusts for non-linearity between the two color channels (see Yang Yee Hwa et. al., Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation, Nucl. Acid Res., 2002). We then took the log2 of these ratios. A value of 1 indicates that the expression of that gene in the sample is twice that of the reference. Since the reference, includes liver, the range of values is more modest than some other scales of gene expression. (From Dan Gatti, Sept 2012).
diff --git a/general/datasets/Lv_g_0106_f/summary.rtf b/general/datasets/Lv_g_0106_f/summary.rtf
new file mode 100644
index 0000000..fe91a13
--- /dev/null
+++ b/general/datasets/Lv_g_0106_f/summary.rtf
@@ -0,0 +1,9 @@
+Genome-level analysis of genetic regulation of liver gene expression networks
+
+Gatti D, Maki A, Chesler EJ, Kirova R, Kosyk O, Lu L, Manly KF, Williams RW, Perkins A, Langston MA, Threadgill DW, Rusyn I
+
+Hepatology. 2007 Aug;46(2):548-57
+
+Source: Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
+
+The liver is the primary site for the metabolism of nutrients, drugs, and chemical agents. Although metabolic pathways are complex and tightly regulated, genetic variation among individuals, reflected in variations in gene expression levels, introduces complexity into research on liver disease. This study dissected genetic networks that control liver gene expression through the combination of large-scale quantitative mRNA expression analysis with genetic mapping in a reference population of BXD recombinant inbred mouse strains for which extensive single-nucleotide polymorphism, haplotype, and phenotypic data are publicly available. We profiled gene expression in livers of naive mice of both sexes from C57BL/6J, DBA/2J, B6D2F1, and 37 BXD strains using Agilent oligonucleotide microarrays. These data were used to map quantitative trait loci (QTLs) responsible for variations in the expression of about 19,000 transcripts. We identified polymorphic local and distant QTLs, including several loci that control the expression of large numbers of genes in liver, by comparing the physical transcript position with the location of the controlling QTL. CONCLUSION: The data are available through a public web-based resource (www.genenetwork.org) that allows custom data mining, identification of coregulated transcripts and correlated phenotypes, cross-tissue, and cross-species comparisons, as well as testing of a broad array of hypotheses.
diff --git a/general/datasets/Lv_g_0106_m/citation.rtf b/general/datasets/Lv_g_0106_m/citation.rtf
new file mode 100644
index 0000000..2f6dbd6
--- /dev/null
+++ b/general/datasets/Lv_g_0106_m/citation.rtf
@@ -0,0 +1 @@
+Genome-level analysis of genetic regulation of liver gene expression networks. Gatti D, Maki A, Chesler EJ, Kirova R, Kosyk O, Lu L, Manly KF, Williams RW, Perkins A, Langston MA, Threadgill DW, Rusyn I. Hepatology. 2007 Aug;46(2):548-57. PMID: 17542012
diff --git a/general/datasets/Lv_g_0106_m/platform.rtf b/general/datasets/Lv_g_0106_m/platform.rtf
new file mode 100644
index 0000000..dd35c6a
--- /dev/null
+++ b/general/datasets/Lv_g_0106_m/platform.rtf
@@ -0,0 +1 @@
+The arrays were Agilent two color arrays.
diff --git a/general/datasets/Lv_g_0106_m/processing.rtf b/general/datasets/Lv_g_0106_m/processing.rtf
new file mode 100644
index 0000000..ae2363c
--- /dev/null
+++ b/general/datasets/Lv_g_0106_m/processing.rtf
@@ -0,0 +1 @@
+We used a mix of C57BL/6J RNA as the reference (liver, kidney, lung, brain and spleen). Each measurement is the ratio of sample intensity over the reference intensity. The data was normalized using a robust LOWESS smoothing method that adjusts for non-linearity between the two color channels (see Yang Yee Hwa et. al., Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation, Nucl. Acid Res., 2002). We then took the log2 of these ratios. A value of 1 indicates that the expression of that gene in the sample is twice that of the reference. Since the reference, includes liver, the range of values is more modest than some other scales of gene expression. (From Dan Gatti, Sept 2012).
diff --git a/general/datasets/Lv_g_0106_m/summary.rtf b/general/datasets/Lv_g_0106_m/summary.rtf
new file mode 100644
index 0000000..fe91a13
--- /dev/null
+++ b/general/datasets/Lv_g_0106_m/summary.rtf
@@ -0,0 +1,9 @@
+Genome-level analysis of genetic regulation of liver gene expression networks
+
+Gatti D, Maki A, Chesler EJ, Kirova R, Kosyk O, Lu L, Manly KF, Williams RW, Perkins A, Langston MA, Threadgill DW, Rusyn I
+
+Hepatology. 2007 Aug;46(2):548-57
+
+Source: Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
+
+The liver is the primary site for the metabolism of nutrients, drugs, and chemical agents. Although metabolic pathways are complex and tightly regulated, genetic variation among individuals, reflected in variations in gene expression levels, introduces complexity into research on liver disease. This study dissected genetic networks that control liver gene expression through the combination of large-scale quantitative mRNA expression analysis with genetic mapping in a reference population of BXD recombinant inbred mouse strains for which extensive single-nucleotide polymorphism, haplotype, and phenotypic data are publicly available. We profiled gene expression in livers of naive mice of both sexes from C57BL/6J, DBA/2J, B6D2F1, and 37 BXD strains using Agilent oligonucleotide microarrays. These data were used to map quantitative trait loci (QTLs) responsible for variations in the expression of about 19,000 transcripts. We identified polymorphic local and distant QTLs, including several loci that control the expression of large numbers of genes in liver, by comparing the physical transcript position with the location of the controlling QTL. CONCLUSION: The data are available through a public web-based resource (www.genenetwork.org) that allows custom data mining, identification of coregulated transcripts and correlated phenotypes, cross-tissue, and cross-species comparisons, as well as testing of a broad array of hypotheses.
diff --git a/general/datasets/Lv_g_0704_a/citation.rtf b/general/datasets/Lv_g_0704_a/citation.rtf
new file mode 100644
index 0000000..2f6dbd6
--- /dev/null
+++ b/general/datasets/Lv_g_0704_a/citation.rtf
@@ -0,0 +1 @@
+Genome-level analysis of genetic regulation of liver gene expression networks. Gatti D, Maki A, Chesler EJ, Kirova R, Kosyk O, Lu L, Manly KF, Williams RW, Perkins A, Langston MA, Threadgill DW, Rusyn I. Hepatology. 2007 Aug;46(2):548-57. PMID: 17542012
diff --git a/general/datasets/Lv_g_0704_a/platform.rtf b/general/datasets/Lv_g_0704_a/platform.rtf
new file mode 100644
index 0000000..dd35c6a
--- /dev/null
+++ b/general/datasets/Lv_g_0704_a/platform.rtf
@@ -0,0 +1 @@
+The arrays were Agilent two color arrays.
diff --git a/general/datasets/Lv_g_0704_a/processing.rtf b/general/datasets/Lv_g_0704_a/processing.rtf
new file mode 100644
index 0000000..ae2363c
--- /dev/null
+++ b/general/datasets/Lv_g_0704_a/processing.rtf
@@ -0,0 +1 @@
+We used a mix of C57BL/6J RNA as the reference (liver, kidney, lung, brain and spleen). Each measurement is the ratio of sample intensity over the reference intensity. The data was normalized using a robust LOWESS smoothing method that adjusts for non-linearity between the two color channels (see Yang Yee Hwa et. al., Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation, Nucl. Acid Res., 2002). We then took the log2 of these ratios. A value of 1 indicates that the expression of that gene in the sample is twice that of the reference. Since the reference, includes liver, the range of values is more modest than some other scales of gene expression. (From Dan Gatti, Sept 2012).
diff --git a/general/datasets/Lv_g_0704_a/summary.rtf b/general/datasets/Lv_g_0704_a/summary.rtf
new file mode 100644
index 0000000..fe91a13
--- /dev/null
+++ b/general/datasets/Lv_g_0704_a/summary.rtf
@@ -0,0 +1,9 @@
+Genome-level analysis of genetic regulation of liver gene expression networks
+
+Gatti D, Maki A, Chesler EJ, Kirova R, Kosyk O, Lu L, Manly KF, Williams RW, Perkins A, Langston MA, Threadgill DW, Rusyn I
+
+Hepatology. 2007 Aug;46(2):548-57
+
+Source: Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
+
+The liver is the primary site for the metabolism of nutrients, drugs, and chemical agents. Although metabolic pathways are complex and tightly regulated, genetic variation among individuals, reflected in variations in gene expression levels, introduces complexity into research on liver disease. This study dissected genetic networks that control liver gene expression through the combination of large-scale quantitative mRNA expression analysis with genetic mapping in a reference population of BXD recombinant inbred mouse strains for which extensive single-nucleotide polymorphism, haplotype, and phenotypic data are publicly available. We profiled gene expression in livers of naive mice of both sexes from C57BL/6J, DBA/2J, B6D2F1, and 37 BXD strains using Agilent oligonucleotide microarrays. These data were used to map quantitative trait loci (QTLs) responsible for variations in the expression of about 19,000 transcripts. We identified polymorphic local and distant QTLs, including several loci that control the expression of large numbers of genes in liver, by comparing the physical transcript position with the location of the controlling QTL. CONCLUSION: The data are available through a public web-based resource (www.genenetwork.org) that allows custom data mining, identification of coregulated transcripts and correlated phenotypes, cross-tissue, and cross-species comparisons, as well as testing of a broad array of hypotheses.
diff --git a/general/datasets/Lv_g_0704_r/citation.rtf b/general/datasets/Lv_g_0704_r/citation.rtf
new file mode 100644
index 0000000..2f6dbd6
--- /dev/null
+++ b/general/datasets/Lv_g_0704_r/citation.rtf
@@ -0,0 +1 @@
+Genome-level analysis of genetic regulation of liver gene expression networks. Gatti D, Maki A, Chesler EJ, Kirova R, Kosyk O, Lu L, Manly KF, Williams RW, Perkins A, Langston MA, Threadgill DW, Rusyn I. Hepatology. 2007 Aug;46(2):548-57. PMID: 17542012
diff --git a/general/datasets/Lv_g_0704_r/platform.rtf b/general/datasets/Lv_g_0704_r/platform.rtf
new file mode 100644
index 0000000..dd35c6a
--- /dev/null
+++ b/general/datasets/Lv_g_0704_r/platform.rtf
@@ -0,0 +1 @@
+The arrays were Agilent two color arrays.
diff --git a/general/datasets/Lv_g_0704_r/processing.rtf b/general/datasets/Lv_g_0704_r/processing.rtf
new file mode 100644
index 0000000..ae2363c
--- /dev/null
+++ b/general/datasets/Lv_g_0704_r/processing.rtf
@@ -0,0 +1 @@
+We used a mix of C57BL/6J RNA as the reference (liver, kidney, lung, brain and spleen). Each measurement is the ratio of sample intensity over the reference intensity. The data was normalized using a robust LOWESS smoothing method that adjusts for non-linearity between the two color channels (see Yang Yee Hwa et. al., Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation, Nucl. Acid Res., 2002). We then took the log2 of these ratios. A value of 1 indicates that the expression of that gene in the sample is twice that of the reference. Since the reference, includes liver, the range of values is more modest than some other scales of gene expression. (From Dan Gatti, Sept 2012).
diff --git a/general/datasets/Lv_g_0704_r/summary.rtf b/general/datasets/Lv_g_0704_r/summary.rtf
new file mode 100644
index 0000000..fe91a13
--- /dev/null
+++ b/general/datasets/Lv_g_0704_r/summary.rtf
@@ -0,0 +1,9 @@
+Genome-level analysis of genetic regulation of liver gene expression networks
+
+Gatti D, Maki A, Chesler EJ, Kirova R, Kosyk O, Lu L, Manly KF, Williams RW, Perkins A, Langston MA, Threadgill DW, Rusyn I
+
+Hepatology. 2007 Aug;46(2):548-57
+
+Source: Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
+
+The liver is the primary site for the metabolism of nutrients, drugs, and chemical agents. Although metabolic pathways are complex and tightly regulated, genetic variation among individuals, reflected in variations in gene expression levels, introduces complexity into research on liver disease. This study dissected genetic networks that control liver gene expression through the combination of large-scale quantitative mRNA expression analysis with genetic mapping in a reference population of BXD recombinant inbred mouse strains for which extensive single-nucleotide polymorphism, haplotype, and phenotypic data are publicly available. We profiled gene expression in livers of naive mice of both sexes from C57BL/6J, DBA/2J, B6D2F1, and 37 BXD strains using Agilent oligonucleotide microarrays. These data were used to map quantitative trait loci (QTLs) responsible for variations in the expression of about 19,000 transcripts. We identified polymorphic local and distant QTLs, including several loci that control the expression of large numbers of genes in liver, by comparing the physical transcript position with the location of the controlling QTL. CONCLUSION: The data are available through a public web-based resource (www.genenetwork.org) that allows custom data mining, identification of coregulated transcripts and correlated phenotypes, cross-tissue, and cross-species comparisons, as well as testing of a broad array of hypotheses.
diff --git a/general/datasets/Lvf2_m_0704_m/acknowledgment.rtf b/general/datasets/Lvf2_m_0704_m/acknowledgment.rtf
new file mode 100644
index 0000000..42f7eec
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_m/acknowledgment.rtf
@@ -0,0 +1,3 @@
+This project was supported in part by NIH/NIDDK 5803701, NIH/NIDDK 66369-01 and American Diabetes Association 7-03-IG-01 to Alan D. Attie, USDA CSREES grants to the University of Wisconsin-Madison to Brian S. Yandell, and HHMI grant A-53-1200-4 to Christina Kendziorski.
+
+B6BTBRF2 Liver Database. All of the original (B6 x BTBR)F2-ob/ob liver mRNA M430AB array data were generated by Hong Lan and Alan Attie at The University of Wisconsin-Madison. For contact and citations and other information on these data sets, please review the INFO pages and contact Drs. Alan Attie, Christina Kendziorski, and Brian Yandell regarding use of this data set in publications or projects.
diff --git a/general/datasets/Lvf2_m_0704_m/cases.rtf b/general/datasets/Lvf2_m_0704_m/cases.rtf
new file mode 100644
index 0000000..ece7be7
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_m/cases.rtf
@@ -0,0 +1 @@
+The F2-ob/ob mice were chosen from a mapping panel that we created to map diabetes related physiological phenotypes (Stoehr et al. 2000). About 110 of these F2-ob/ob mice were also used to map mRNA abundance traits derived by quantitative real-time RT-PCR (Lan et al. 2003). The sixty F2-ob/ob mice that were used to generate microarray-derived mRNA abundance traits were selected from the 110 mice based on a selective phenotyping algorithm (Jin et al. 2004). The F2-ob/ob mice were housed at weaning at the University of Wisconsin-Madison animal care facility on a 12-h light/dark cycle. Mice were provided Purina Formulab Chow 5008 (6.5% fat) and acidified water ad libitum. Mice were killed at 14 weeks of age by CO2 asphyxiation after a 4-hour fast. The livers, along with other tissues, were immediately foil wrapped and frozen in liquid nitrogen, and subsequently transferred to -80 °C freezers for storage.
diff --git a/general/datasets/Lvf2_m_0704_m/citation.rtf b/general/datasets/Lvf2_m_0704_m/citation.rtf
new file mode 100644
index 0000000..48722e7
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_m/citation.rtf
@@ -0,0 +1,27 @@
+
+Lan H, Chen M, Byers JE, Yandell BS, Stapleton DS, Mata CM, Mui ET, Flowers MT, Schueler KL, Malnly KF, Williams RW, Kendziorski CM, Attie AD (2005) Combined expression trait correlations and expression quantitative trait locus mapping. Submitted, Aug. 2005.
+
+
+
+Broman KW, Wu H, Sen S, Churchill GA (2003) R/qtl: QTL mapping in experimental crosses. Bioinformatics 19: 889-890.
+
+
+
+Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, Speed TP (2003) Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res 31: e15.
+
+
+
+Jin C, Lan H, Attie AD, Churchill GA, Bulutuglo D, Yanell BS (2004) Selective phenotyping for increased efficiency in genetic mapping studies. Genetics 168:2285-2293.
+
+
+
+Lan H, Stoehr JP, Nadler ST, Schueler KL, Yandel BS, Attie AD (2003) Dimension reduction for mapping mRNA abundance as quantitative traits. Genetics 164: 1607-1614.
+
+
+
+Stoehr JP, Nadler ST, Schueler KL, Rabaglia ME, Yandell BS, Metz SA, Attie AD (2000) Genetic obesity unmasks nonlinear interactions between murine type 2 diabetes susceptibility loci. Diabetes 49: 1946-1954.
+
+
+
+Zhang L, Miles MF, Aldape KD (2003) A model of molecular interactions on short oligonucleotide microarrays. Nat Biotechnol 21: 818-821.
+
diff --git a/general/datasets/Lvf2_m_0704_m/notes.rtf b/general/datasets/Lvf2_m_0704_m/notes.rtf
new file mode 100644
index 0000000..5e9c255
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_m/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW and Alan Attie, July 2, 2004. Updated by RWW, Aug 20, 5, 2004; April 7, 2005; August 20, 2005.
+
diff --git a/general/datasets/Lvf2_m_0704_m/platform.rtf b/general/datasets/Lvf2_m_0704_m/platform.rtf
new file mode 100644
index 0000000..29c90d3
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_m/platform.rtf
@@ -0,0 +1,876 @@
+
+Affymetrix Mouse Genome 430A and 430B array pairs: The 430A and B array pairs collectively consist of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (some are variant transcipts and many are duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequence as the 430 2.0 series. However, roughy 75000 probes differ between those on A and B arrays and those on the 430 2.0.
+
+
+Liver samples were assayed individually using 60 M430A and B Affymetrix oligonucleotide microarray pairs. Each array ID is denoted by a 10-letter code: the first three letters represent the F2-ob/ob mouse ID number, the fourth letter (either A or B) denotes M430A or M430B arrays, and the last six letters represent the date the array was scanned (MMDDYY).
+
+All 120 M430A and B arrays used in this project were purchased at one time and had the same Affymetrix lot number. The table below lists the arrays by Animal ID, sex, and ArrayID.
+
+
+
+
+
+
+
+
+
+ |
+ Animal ID
+ |
+
+ sex
+ |
+
+ MOE430A ArrayID
+ |
+
+ MOE430B ArrayID
+ |
+
+
+ |
+ 2
+ |
+
+ M
+ |
+
+ 002A100203
+ |
+
+ 002B100503
+ |
+
+
+ |
+ 12
+ |
+
+ M
+ |
+
+ 012A100203
+ |
+
+ 012B100503
+ |
+
+
+ |
+ 22
+ |
+
+ M
+ |
+
+ 022A100203
+ |
+
+ 022B100503
+ |
+
+
+ |
+ 44
+ |
+
+ M
+ |
+
+ 044A100203
+ |
+
+ 044B100503
+ |
+
+
+ |
+ 46
+ |
+
+ M
+ |
+
+ 046A100203
+ |
+
+ 046B100503
+ |
+
+
+ |
+ 61
+ |
+
+ M
+ |
+
+ 061A100203
+ |
+
+ 061B100503
+ |
+
+
+ |
+ 100
+ |
+
+ M
+ |
+
+ 100A100303
+ |
+
+ 100B100503
+ |
+
+
+ |
+ 105
+ |
+
+ F
+ |
+
+ 105A100303
+ |
+
+ 105B100503
+ |
+
+
+ |
+ 111
+ |
+
+ F
+ |
+
+ 111A100303
+ |
+
+ 111B100503
+ |
+
+
+ |
+ 123
+ |
+
+ M
+ |
+
+ 123A100303
+ |
+
+ 123B100503
+ |
+
+
+ |
+ 156
+ |
+
+ F
+ |
+
+ 156A100303
+ |
+
+ 156B100503
+ |
+
+
+ |
+ 165
+ |
+
+ M
+ |
+
+ 165A100303
+ |
+
+ 165B100503
+ |
+
+
+ |
+ 167
+ |
+
+ M
+ |
+
+ 167A100303
+ |
+
+ 167B100503
+ |
+
+
+ |
+ 173
+ |
+
+ M
+ |
+
+ 173A100303
+ |
+
+ 173B100503
+ |
+
+
+ |
+ 186
+ |
+
+ F
+ |
+
+ 186A100203
+ |
+
+ 186B100503
+ |
+
+
+ |
+ 190
+ |
+
+ F
+ |
+
+ 190A100303
+ |
+
+ 190B100503
+ |
+
+
+ |
+ 194
+ |
+
+ M
+ |
+
+ 194A100303
+ |
+
+ 194B100503
+ |
+
+
+ |
+ 200
+ |
+
+ F
+ |
+
+ 200A100303
+ |
+
+ 200B100503
+ |
+
+
+ |
+ 207
+ |
+
+ F
+ |
+
+ 207A100303
+ |
+
+ 207B100503
+ |
+
+
+ |
+ 209
+ |
+
+ F
+ |
+
+ 209A100203
+ |
+
+ 209B100503
+ |
+
+
+ |
+ 212
+ |
+
+ F
+ |
+
+ 212A100303
+ |
+
+ 212B100503
+ |
+
+
+ |
+ 223
+ |
+
+ M
+ |
+
+ 223A100303
+ |
+
+ 223B100503
+ |
+
+
+ |
+ 224
+ |
+
+ M
+ |
+
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diff --git a/general/datasets/Lvf2_m_0704_m/processing.rtf b/general/datasets/Lvf2_m_0704_m/processing.rtf
new file mode 100644
index 0000000..3ed08db
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_m/processing.rtf
@@ -0,0 +1,14 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each cell.
+ - Step 3: We computed the Z scores for each cell.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B GeneChips include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the two GeneChips to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+
+Probe set data from the .CHP file: The expression data were generated using MAS5. The same simple steps described above were also applied to these values. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+The 60 mice were each genotyped at 194 MIT microsatellite markers an average of approximately 10 cM (and always < 30 cM) apart across the entire genome (Y chromsome, excepted). The genotyping error-check routine implemented within R/qtl (Broman et al. 2003) showed no likely errors at p <0.01 probability.
diff --git a/general/datasets/Lvf2_m_0704_m/summary.rtf b/general/datasets/Lvf2_m_0704_m/summary.rtf
new file mode 100644
index 0000000..9492e80
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_m/summary.rtf
@@ -0,0 +1,3 @@
+
+This August 2005 data freeze provides estimates of mRNA expression in adult liver from a selected set of 60 F2 animals generated by crossing strain C57BL/6J-ob/+ with BTBR and then intercrossing the F1-ob/+ progeny. The F2 progeny included, in a total of 350 progeny, 110 ob/ob progeny homozygous for the obese (ob) allele of leptin (Lep) on Chr 6. Sixty of the ob/ob progeny were selected for expression assays. This selection means that the data set is not useful for defining QTLs on Chr 6. Array data were generated at the University of Wisconsin by Alan Attie and colleagues. This data release accompanies the paper of Lan and colleagues (in submission, 2005). A set of 24 complementary phenotypes such as body weight, blood chemistry, and rtPCR results, are also available for these animals and an additional set of 50 F2s (see Phenotypes database. Samples were hybridized to 60 pairs of Affymetrix M430A and B arrays. This particular data set was processed using the RMA normalization method. To simplify comparison among transforms, RMA values of each array were adjusted to an average of 8 units and a standard deviation of two units.
+
diff --git a/general/datasets/Lvf2_m_0704_m/tissue.rtf b/general/datasets/Lvf2_m_0704_m/tissue.rtf
new file mode 100644
index 0000000..de3964c
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_m/tissue.rtf
@@ -0,0 +1,3 @@
+
+Liver samples were taken from 29 male and 31 females. Total RNA was isolated with RNAzol Reagent (Tel-Test, Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer's protocol. The extracted RNA was purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for concentration. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. RNA samples were converted to cDNA, and then biotin-labeled cRNA according to Affymetrix Expression Analysis Technical Manual. The labeled samples were hybridized to the M430A, and subsequently the M430B array. The hybridization, washing and scanning steps were carried out by Hong Lan using the Affymetrix core facility at the Gene Expression Center of University of Wisconsin-Madison.
+
diff --git a/general/datasets/Lvf2_m_0704_r/acknowledgment.rtf b/general/datasets/Lvf2_m_0704_r/acknowledgment.rtf
new file mode 100644
index 0000000..42f7eec
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_r/acknowledgment.rtf
@@ -0,0 +1,3 @@
+This project was supported in part by NIH/NIDDK 5803701, NIH/NIDDK 66369-01 and American Diabetes Association 7-03-IG-01 to Alan D. Attie, USDA CSREES grants to the University of Wisconsin-Madison to Brian S. Yandell, and HHMI grant A-53-1200-4 to Christina Kendziorski.
+
+B6BTBRF2 Liver Database. All of the original (B6 x BTBR)F2-ob/ob liver mRNA M430AB array data were generated by Hong Lan and Alan Attie at The University of Wisconsin-Madison. For contact and citations and other information on these data sets, please review the INFO pages and contact Drs. Alan Attie, Christina Kendziorski, and Brian Yandell regarding use of this data set in publications or projects.
diff --git a/general/datasets/Lvf2_m_0704_r/cases.rtf b/general/datasets/Lvf2_m_0704_r/cases.rtf
new file mode 100644
index 0000000..ece7be7
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_r/cases.rtf
@@ -0,0 +1 @@
+The F2-ob/ob mice were chosen from a mapping panel that we created to map diabetes related physiological phenotypes (Stoehr et al. 2000). About 110 of these F2-ob/ob mice were also used to map mRNA abundance traits derived by quantitative real-time RT-PCR (Lan et al. 2003). The sixty F2-ob/ob mice that were used to generate microarray-derived mRNA abundance traits were selected from the 110 mice based on a selective phenotyping algorithm (Jin et al. 2004). The F2-ob/ob mice were housed at weaning at the University of Wisconsin-Madison animal care facility on a 12-h light/dark cycle. Mice were provided Purina Formulab Chow 5008 (6.5% fat) and acidified water ad libitum. Mice were killed at 14 weeks of age by CO2 asphyxiation after a 4-hour fast. The livers, along with other tissues, were immediately foil wrapped and frozen in liquid nitrogen, and subsequently transferred to -80 °C freezers for storage.
diff --git a/general/datasets/Lvf2_m_0704_r/citation.rtf b/general/datasets/Lvf2_m_0704_r/citation.rtf
new file mode 100644
index 0000000..48722e7
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_r/citation.rtf
@@ -0,0 +1,27 @@
+
+Lan H, Chen M, Byers JE, Yandell BS, Stapleton DS, Mata CM, Mui ET, Flowers MT, Schueler KL, Malnly KF, Williams RW, Kendziorski CM, Attie AD (2005) Combined expression trait correlations and expression quantitative trait locus mapping. Submitted, Aug. 2005.
+
+
+
+Broman KW, Wu H, Sen S, Churchill GA (2003) R/qtl: QTL mapping in experimental crosses. Bioinformatics 19: 889-890.
+
+
+
+Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, Speed TP (2003) Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res 31: e15.
+
+
+
+Jin C, Lan H, Attie AD, Churchill GA, Bulutuglo D, Yanell BS (2004) Selective phenotyping for increased efficiency in genetic mapping studies. Genetics 168:2285-2293.
+
+
+
+Lan H, Stoehr JP, Nadler ST, Schueler KL, Yandel BS, Attie AD (2003) Dimension reduction for mapping mRNA abundance as quantitative traits. Genetics 164: 1607-1614.
+
+
+
+Stoehr JP, Nadler ST, Schueler KL, Rabaglia ME, Yandell BS, Metz SA, Attie AD (2000) Genetic obesity unmasks nonlinear interactions between murine type 2 diabetes susceptibility loci. Diabetes 49: 1946-1954.
+
+
+
+Zhang L, Miles MF, Aldape KD (2003) A model of molecular interactions on short oligonucleotide microarrays. Nat Biotechnol 21: 818-821.
+
diff --git a/general/datasets/Lvf2_m_0704_r/notes.rtf b/general/datasets/Lvf2_m_0704_r/notes.rtf
new file mode 100644
index 0000000..5e9c255
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by RWW and Alan Attie, July 2, 2004. Updated by RWW, Aug 20, 5, 2004; April 7, 2005; August 20, 2005.
+
diff --git a/general/datasets/Lvf2_m_0704_r/platform.rtf b/general/datasets/Lvf2_m_0704_r/platform.rtf
new file mode 100644
index 0000000..29c90d3
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_r/platform.rtf
@@ -0,0 +1,876 @@
+
+Affymetrix Mouse Genome 430A and 430B array pairs: The 430A and B array pairs collectively consist of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (some are variant transcipts and many are duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The arrays nominally contain the same probe sequence as the 430 2.0 series. However, roughy 75000 probes differ between those on A and B arrays and those on the 430 2.0.
+
+
+Liver samples were assayed individually using 60 M430A and B Affymetrix oligonucleotide microarray pairs. Each array ID is denoted by a 10-letter code: the first three letters represent the F2-ob/ob mouse ID number, the fourth letter (either A or B) denotes M430A or M430B arrays, and the last six letters represent the date the array was scanned (MMDDYY).
+
+All 120 M430A and B arrays used in this project were purchased at one time and had the same Affymetrix lot number. The table below lists the arrays by Animal ID, sex, and ArrayID.
+
+
+
+
+
+
+
+
+
+ |
+ Animal ID
+ |
+
+ sex
+ |
+
+ MOE430A ArrayID
+ |
+
+ MOE430B ArrayID
+ |
+
+
+ |
+ 2
+ |
+
+ M
+ |
+
+ 002A100203
+ |
+
+ 002B100503
+ |
+
+
+ |
+ 12
+ |
+
+ M
+ |
+
+ 012A100203
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+
+ 012B100503
+ |
+
+
+ |
+ 22
+ |
+
+ M
+ |
+
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+ 022B100503
+ |
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+
+ |
+ 44
+ |
+
+ M
+ |
+
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+ |
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+ 044B100503
+ |
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+
+ |
+ 46
+ |
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+ M
+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+
+ |
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+ |
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+ |
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+ |
+
+ 486B100803
+ |
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+ |
+ 489
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+ |
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+ |
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+ |
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+
+ |
+ 493
+ |
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+ F
+ |
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+ |
+
+ 493B100803
+ |
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+ |
+ 499
+ |
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+ M
+ |
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+ |
+
+ 499B100803
+ |
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+
+ |
+ 513
+ |
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+ |
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+ |
+
+ 513B100803
+ |
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+
+ |
+ 517
+ |
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+ M
+ |
+
+ 517A100703
+ |
+
+ 517B100803
+ |
+
+
+ |
+ 523
+ |
+
+ M
+ |
+
+ 523A100703
+ |
+
+ 523B100803
+ |
+
+
+ |
+ 549
+ |
+
+ M
+ |
+
+ 549A100703
+ |
+
+ 549B100803
+ |
+
+
+ |
+ 553
+ |
+
+ F
+ |
+
+ 553A100703
+ |
+
+ 553B100803
+ |
+
+
+ |
+ 554
+ |
+
+ F
+ |
+
+ 554A100703
+ |
+
+ 554B100803
+ |
+
+
+ |
+ 559
+ |
+
+ F
+ |
+
+ 559A100703
+ |
+
+ 559B100803
+ |
+
+
+ |
+ 560
+ |
+
+ F
+ |
+
+ 560A100703
+ |
+
+ 560B100803
+ |
+
+
+ |
+ 566
+ |
+
+ M
+ |
+
+ 566A100703
+ |
+
+ 566B100803
+ |
+
+
+ |
+ 608
+ |
+
+ F
+ |
+
+ 608A100703
+ |
+
+ 608B100803
+ |
+
+
+ |
+ 615
+ |
+
+ F
+ |
+
+ 615A100703
+ |
+
+ 615B100803
+ |
+
+
+ |
+ 617
+ |
+
+ M
+ |
+
+ 617A100703
+ |
+
+ 617B100803
+ |
+
+
+ |
+ 620
+ |
+
+ M
+ |
+
+ 620A100703
+ |
+
+ 620B100803
+ |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Lvf2_m_0704_r/processing.rtf b/general/datasets/Lvf2_m_0704_r/processing.rtf
new file mode 100644
index 0000000..3ed08db
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_r/processing.rtf
@@ -0,0 +1,14 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each cell.
+ - Step 3: We computed the Z scores for each cell.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B GeneChips include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the two GeneChips to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+
+Probe set data from the .CHP file: The expression data were generated using MAS5. The same simple steps described above were also applied to these values. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+The 60 mice were each genotyped at 194 MIT microsatellite markers an average of approximately 10 cM (and always < 30 cM) apart across the entire genome (Y chromsome, excepted). The genotyping error-check routine implemented within R/qtl (Broman et al. 2003) showed no likely errors at p <0.01 probability.
diff --git a/general/datasets/Lvf2_m_0704_r/summary.rtf b/general/datasets/Lvf2_m_0704_r/summary.rtf
new file mode 100644
index 0000000..9492e80
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_r/summary.rtf
@@ -0,0 +1,3 @@
+
+This August 2005 data freeze provides estimates of mRNA expression in adult liver from a selected set of 60 F2 animals generated by crossing strain C57BL/6J-ob/+ with BTBR and then intercrossing the F1-ob/+ progeny. The F2 progeny included, in a total of 350 progeny, 110 ob/ob progeny homozygous for the obese (ob) allele of leptin (Lep) on Chr 6. Sixty of the ob/ob progeny were selected for expression assays. This selection means that the data set is not useful for defining QTLs on Chr 6. Array data were generated at the University of Wisconsin by Alan Attie and colleagues. This data release accompanies the paper of Lan and colleagues (in submission, 2005). A set of 24 complementary phenotypes such as body weight, blood chemistry, and rtPCR results, are also available for these animals and an additional set of 50 F2s (see Phenotypes database. Samples were hybridized to 60 pairs of Affymetrix M430A and B arrays. This particular data set was processed using the RMA normalization method. To simplify comparison among transforms, RMA values of each array were adjusted to an average of 8 units and a standard deviation of two units.
+
diff --git a/general/datasets/Lvf2_m_0704_r/tissue.rtf b/general/datasets/Lvf2_m_0704_r/tissue.rtf
new file mode 100644
index 0000000..de3964c
--- /dev/null
+++ b/general/datasets/Lvf2_m_0704_r/tissue.rtf
@@ -0,0 +1,3 @@
+
+Liver samples were taken from 29 male and 31 females. Total RNA was isolated with RNAzol Reagent (Tel-Test, Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer's protocol. The extracted RNA was purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for concentration. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. RNA samples were converted to cDNA, and then biotin-labeled cRNA according to Affymetrix Expression Analysis Technical Manual. The labeled samples were hybridized to the M430A, and subsequently the M430B array. The hybridization, washing and scanning steps were carried out by Hong Lan using the Affymetrix core facility at the Gene Expression Center of University of Wisconsin-Madison.
+
diff --git a/general/datasets/Lxsgeno/summary.rtf b/general/datasets/Lxsgeno/summary.rtf
new file mode 100644
index 0000000..dc176b3
--- /dev/null
+++ b/general/datasets/Lxsgeno/summary.rtf
@@ -0,0 +1,21 @@
+
+The LXS genotype file used by WebQTL consists of a set of 2659 carefully error-checked SNPs and microsatellites typed across all 77 strains. Download all LXS genotypes as a 478 Kb text file.
+
+LXS strains were derived from a cross between the following 8 strains: A, AKR, BALB/c, C3H/2, C57BL, DBA/2, IS/Bi, and RIII. All of these strains were maintained at the Institute for Behavior Genetics, Bolder Colorado by Dr. Gerald McClearn and colleagues. C3H/2 is presumably the same as C3H/Crgl/2 (see paper by Green V (1981) Behavioral and Neural Biology 31:56). C57BL is presumably the same as C57BL/Crgl. IS/Bi is extinct.
+
+See Williams, Bennett, Johnson and colleagues (2004) for more details on the LXS panel.
+
+
+ About the genotypes used in these studies:
+
+WebQTL mapping algorithms rely on an initial set of 330 microsatellites genotyped in 2002 and 2003 at UTHSC (labeled Mit). The current expanded marker set (n = 2659) have been selected from a total of 13377 SNPs genotyped in collaboration with Jonathan Flint, Richard Mott, Beth Bennett, Lu Lu, and Jing Gu. Closely linked genetic markers often have the same strain distribution pattern (SDP) across the LXS strains. For computational efficiency, we only use a single marker associated with each SDP.
+
+All LXS strains are from the Institute of Behavioral Genetics, Boulder Colorado. They were generated by Beth Bennett, Tom Johnson, and colleagues over a ten-year period. All of these strains are beyond the 22 generation of serial sibling mating and are formally fully inbred.
+
+ Reference:
+
+
+Williams RW, Bennett B, Lu L, Gu J, DeFries JC, Carosone-Link P, Rikke B, Belknap JK, Johnson TE (2004) Genetic structure of the LXS panel of recombinant inbred mouse strains. Mammalian Genome 15:637-647
+
+
+This text file was originally written by RW Williams, July 26, 2005.
diff --git a/general/datasets/Lxspublish/acknowledgment.rtf b/general/datasets/Lxspublish/acknowledgment.rtf
new file mode 100644
index 0000000..3d302d7
--- /dev/null
+++ b/general/datasets/Lxspublish/acknowledgment.rtf
@@ -0,0 +1 @@
+The initial construction of this database was performed by Beth Bennett and colleagues at the University of Colorado, Boulder, and by Lu Lu and colleagues at the University of Tennessee Health Sciences Center.
diff --git a/general/datasets/Lxspublish/cases.rtf b/general/datasets/Lxspublish/cases.rtf
new file mode 100644
index 0000000..6bd4be6
--- /dev/null
+++ b/general/datasets/Lxspublish/cases.rtf
@@ -0,0 +1,7 @@
+The parental strains of the LXS set are Inbred Long-Sleep (ILS) and Inbred Short-Sleep (ISS) strains. These parental strains have been phenotyped intensively by behavioral geneticists and neuropharmacologists for a decade (e.g., Markel PD et al. 1995, Hanania and Zahniser 2004. The LXS strains have an intriguing history and trace back to an 8-way cross initiated in the 1950s by Gerald McClearn, the dean of mouse behavior genetics.
+
+The LXS panel has recently been genotyped at 330 microsatellite markers, and this panel can already be used to map Mendelian and quantitative trait loci. As an example, the current prototype LXS phenotype database contains information on coat color treated as an ordinal trait (1 = albino, 5 = black). This simple trait produces a QTL with an LRS score of 73 (LOD score of ~16) on Chr 7 with a peak within a few megabases of the tyrosinase gene.
+
+Submitting data and reporting errors:
+
+The utility of this resource increases greatly as new phenotypes are added to the database. To submit new data or report errors, please contact Beth Bennett at bennettb@colorado.edu or Lu Lu at lulu@uthsc.edu
diff --git a/general/datasets/Lxspublish/summary.rtf b/general/datasets/Lxspublish/summary.rtf
new file mode 100644
index 0000000..af9cf31
--- /dev/null
+++ b/general/datasets/Lxspublish/summary.rtf
@@ -0,0 +1 @@
+The set of 77 LXS recombinant inbred strains were generated at the Institute for Behavioral Genetics (University of Colorado, Boulder) by Beth Bennett, John DeFries, Tom Johnson, and colleages. Strains first became available for phenotyping in 2003. The large size of this panel ensures good power in genetic studies of a wide variety of complex traits.
diff --git a/general/datasets/Ma_m2_0706_p/acknowledgment.rtf b/general/datasets/Ma_m2_0706_p/acknowledgment.rtf
new file mode 100644
index 0000000..fea38e8
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_p/acknowledgment.rtf
@@ -0,0 +1,24 @@
+
+Data were generated with funds provided by a variety of public and private source to members of the Kidney Consortium. Members of the Kidney Consortium thank the following sources for financial support of this effort:
+
+
+ - Erwin Bottinger, M.D.
+ Grant Support: R01 DK60043-04
+ - Russell Chesney, M.D.
+ Grant Support: Le Bonheur Chair of Excellence in Pediatrics II
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Peter Mundel
+ Grant Support: NIH R01DK57683, NIH R01 DK 62472
+ - Paul Klotman
+ Grant Support: PO1 DK56492, PO1 DK56492.
+ - Matthew Breyer
+ Grant Support: DK-38226
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
+
diff --git a/general/datasets/Ma_m2_0706_p/cases.rtf b/general/datasets/Ma_m2_0706_p/cases.rtf
new file mode 100644
index 0000000..465b87c
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_p/cases.rtf
@@ -0,0 +1,44 @@
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 30 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred. We have also included 24 BXD lines generated by Lu and Peirce. All of these strains have been genotyped at 13,377 SNPs.
+
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 15 inbred strains and a pair of F1 hybrids; D2B6F1. These strains were selected for the following reasons: This panel will be a powerful tool in systems genetic analysis of a wide variety of traits, and will provide additional power in fine mapping modulators through an association analysis of sequence variants.
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+
+ - BTBR T+tf/J
+ Multiple recessive stock; Homozygotes show repeated waves of hair loss and regrowth, which begin in the nose and pass posteriorly along the body.
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - D2B6F1
+ F1 hybrid generated by crossing C57BL/6J with DBA/2J
+
+
+These inbred strains can be ordered from The Jackson Laboratory. BXD43 through BXD100 are available from Lu Lu and colleagues at UTHSC.P>
+
+
diff --git a/general/datasets/Ma_m2_0706_p/experiment-design.rtf b/general/datasets/Ma_m2_0706_p/experiment-design.rtf
new file mode 100644
index 0000000..464e50d
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_p/experiment-design.rtf
@@ -0,0 +1,1864 @@
+
+Sample Processing: : Samples were processed at the Mount Sinai School of Medicine in the laboratory of Dr. Erwin Bottinger. All processing steps were performed Kremena Star. Total RNA was extracted with TRIZOL, followed by Rneasy Mini Kit purification (QUAGEN) by Kremena Star at MSSM. RNA purity was evaluated using the 260/280 nm (protein contamination) and the 260/230 nm (TRIZOL contamination) absorbance ratios, and values had to be greater than 1.9 and 0.8 respectively. Most of the samples 260/280 nm values fell between 1.9 and 2.1 and the majority of the 260/230 nm measurements were in the range 1.8 to 2.3. RNA integrity was assessed with the Agilent Bioanalyzer 2100. We set a quality threshold at 28s/18s rRNA greater than 0.9 or RNA integrity number (RIN) of greater than 6.9. When the two metrics were in disagreement we gave priority on the RIN value as recommended by the Agilent Bioanalyzer 2100 technical support representative. Synthesis of cDNA template from total RNA was performed using the one-cyclecDNA synthesis kit from Affymetrix (Affymetrix, P/N 900431). The Affymetrix IVT-labeling kit ((Affymetrix, P/N 900449)) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 1.9 to 2.1). The cRNA is then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup (Affymetrix, P/N 900371). Fragmented cRNA samples were accessed with Agilent Bioanalyzer 2100 (cRNA frgments between 25 and 200 nucleotides are required for optimal hybridization and immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each isogenic group. Initially all strains were represented by male and female samples, however, not all data sets passed the quality control steps. Forty-two (thirty-one BXD, D2B6F1 and ten inbred strains) are represented by male and female samples.
+
+Experimental Design and Batch Structure: The data set consists of arrays processed in twenty-three groups over a six month period (March 2006 to July 2006). Each group consists of 4 to 12 arrays. All arrays were processed using the Affymetrix Eukaryotic Sample and Array Processing protocol (701024 Rev. 3), by a single operator, Kremena Star. All samples in a group were labeled on the same. The hybridization station accommodates up to 4 samples, and since most of the groups had 12 samples, processed in 3 batches on the same day. Samples were washed in groups of four and kept at 4° C until all 12 (or 4-12) arrays were ready to scan. Samples were scanned in sets of four.
+
+
+This table lists all arrays ordered by strain and includes Microarray ID, number of mice per pool, Microarray date, GAPDH 3`/5`Signal Ratio, Percent of transcripts present on the microarray chip, Strain, Generation, Sex, Age and Source of mice.
+
+
+
+
+
+ | Microarray_ID |
+ # mice |
+ Microarray Date |
+ GAPDH (3`/5`) |
+ % present |
+ strains |
+ generation |
+ sex |
+ age |
+ Mice Source |
+
+
+ | GKHI-KS-050603.07-051706 |
+ 3 |
+ 05/14/02 |
+ 0.73 |
+ 37.6 |
+ C57BL/6J |
+ |
+ M |
+ 56 |
+ UTM RW |
+
+
+ | GKHI-KS-070803.01-051706 |
+ 3 |
+ 05/14/02 |
+ 0.75 |
+ 41.6 |
+ C57BL/6J |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI-KS-DBA-Male-070706 |
+ 2 |
+ 07/06/02 |
+ 0.71 |
+ 37.3 |
+ DBA/2J |
+ |
+ M |
+ 56 |
+ JAX |
+
+
+ | GKHI_KS_121404.75-042106 |
+ 4 |
+ 04/18/02 |
+ |
+ |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_121404.75-033006 |
+ 4 |
+ 03/19/02 |
+ 0.73 |
+ 48.5 |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_121404.78-042006 |
+ 4 |
+ 04/17/02 |
+ 0.83 |
+ 40.6 |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_070804.39-042006 |
+ 4 |
+ 04/17/02 |
+ 0.82 |
+ 39.0 |
+ D2B6F1 |
+ |
+ M |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_030904.01-042006 |
+ 4 |
+ 04/17/02 |
+ 0.82 |
+ 35.9 |
+ D2B6F1 |
+ |
+ M |
+ 57 |
+ UTM RW |
+
+
+ | GKHI-KS-121404.73-070706 |
+ 2 |
+ 07/06/02 |
+ 0.76 |
+ 36.3 |
+ D2B6F1 |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI-KS-010705.38-051206 |
+ 5 |
+ 05/09/02 |
+ 0.81 |
+ 39.9 |
+ BXD1 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-060905.19 |
+ 5 |
+ 06/05/02 |
+ 0.75 |
+ 42.3 |
+ BXD1 |
+ |
+ M |
+ 68 |
+ UTM RW |
+
+
+ | GKHI-KS-051206.13-070706 |
+ 3 |
+ 07/06/02 |
+ 0.71 |
+ 36.3 |
+ BXD1 |
+ |
+ F |
+ 57 |
+ UTM RW |
+
+
+ | GKHI-KS-021304.10-051206 |
+ 4 |
+ 05/09/02 |
+ 0.81 |
+ 39.1 |
+ BXD2 |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-040303-04-050406 |
+ 3 |
+ 05/01/02 |
+ 0.80 |
+ 37.6 |
+ BXD5 |
+ |
+ F |
+ 56 |
+ UMemphis |
+
+
+ | GKHI-KS-010705-53-050306 |
+ 5 |
+ 05/01/02 |
+ 0.76 |
+ 37.1 |
+ BXD5 |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031103.01-062206 |
+ 3 |
+ 06/21/02 |
+ 0.75 |
+ 37.1 |
+ BXD5 |
+ |
+ M |
+ 71 |
+ UMemphis |
+
+
+ | GKHI-KS-040505-51-050306 |
+ 5 |
+ 05/01/02 |
+ 0.71 |
+ 35.5 |
+ BXD6 |
+ |
+ M |
+ 58 |
+ UTM RW |
+
+
+ | GKHI-KS-092705-29--050406 |
+ 5 |
+ 05/02/02 |
+ 0.75 |
+ 36.1 |
+ BXD6 |
+ 160 |
+ F |
+ 64 |
+ UTM RW |
+
+
+ | GKHI_KS_092404.01-042106 |
+ 4 |
+ 04/18/02 |
+ 0.71 |
+ 36.3 |
+ BXD8 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-051205-25-042706 |
+ 5 |
+ 04/23/02 |
+ 0.92 |
+ 37.9 |
+ BXD8 |
+ |
+ F |
+ 77 |
+ UTM RW |
+
+
+ | KS-021605-17-042606 |
+ 5 |
+ 04/22/02 |
+ 0.85 |
+ 40.8 |
+ BXD9 |
+ |
+ F |
+ 67 |
+ UTM RW |
+
+
+ | KS-032905-32-042606 |
+ 5 |
+ 04/22/02 |
+ 0.91 |
+ 36.8 |
+ BXD9 |
+ |
+ F |
+ 60 |
+ UTM RW |
+
+
+ | GKHI-KS-062006.08-070706 |
+ 3 |
+ 07/06/02 |
+ 0.74 |
+ 36.3 |
+ BXD9 |
+ |
+ M |
+ 78 |
+ UTM RW |
+
+
+ | GKHI-KS-031505.22-051206 |
+ 5 |
+ 05/09/02 |
+ 0.74 |
+ 39.5 |
+ BXD11 |
+ |
+ F |
+ 65 |
+ UTM RW |
+
+
+ | GKHI-KS-031605.01 |
+ 5 |
+ 06/05/02 |
+ 0.74 |
+ 43.4 |
+ BXD11 |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI_KS_102104.40-042106 |
+ 4 |
+ 04/18/02 |
+ 0.72 |
+ 38.5 |
+ BXD12 |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-112002.07-051106 |
+ 2 |
+ 05/08/02 |
+ 0.77 |
+ 42.0 |
+ BXD12 |
+ |
+ F |
+ 64 |
+ UMemphis |
+
+
+ | GKHI-KS-120904.33-051206 |
+ 4 |
+ 05/09/02 |
+ 0.71 |
+ 38.4 |
+ BXD13 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-042304.01 |
+ 4 |
+ 06/05/02 |
+ 0.71 |
+ 44.1 |
+ BXD13 |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020905.34-051106 |
+ 5 |
+ 05/08/02 |
+ 0.75 |
+ 40.7 |
+ BXD14 |
+ |
+ F |
+ 68 |
+ UTM RW |
+
+
+ | GKHI-KS-022405.46-051106 |
+ 5 |
+ 05/08/02 |
+ 0.71 |
+ 40.2 |
+ BXD14 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-091704.09-062206 |
+ 4 |
+ 06/21/02 |
+ 0.73 |
+ 39.0 |
+ BXD14 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-013004.45-062206 |
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+ | GKHI-KS-022405.43-051106 |
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+ | GKHI-KS-041604.10-051106 |
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+ | GKHI-KS-040805.10-051006 |
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+ | GKHI-KS-052804.09-051106 |
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+ | GKHI-KS-010705.47-051106 |
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+ | GKHI-KS-010705.44-070706 |
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+ | GKHI-KS-062905.07-051106 |
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+ | GKHI-KS-050405.21-051206 |
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+ | GKHI-KS-040705.24 |
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+
+ | GKHI-KS-110405.01-051006 |
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+ | GKHI-KS-110405.04-051006 |
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+ | GKHI-KS-040805.01-051206 |
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+ | GKHI-KS-040805.04-051006 |
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+ | GKHI_KS_091704.13-042106 |
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+ | GKHI-KS-040303-20-050206 |
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+ | GKHI-KS-021805.20-051006 |
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+ | GKHI-KS-090705.05-062206 |
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+
+ | GKHI-KS-090705.03-051006 |
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+
+ | GKHI-KS-022105.42-051006 |
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+ | GKHI-KS-032205.31-051006 |
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+
+ | GKHI-KS-060706.10-070706 |
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+
+ | GKHI-KS-012805-41-050506 |
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+ | GKHI-KS-012805-44-050506 |
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+ | GKHI-KS-012805-38-050506 |
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+ | GKHI-KS-012805-35-050506 |
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+ | GKHI-KS-012805-32-050506 |
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+ | GKHI-KS-100604-07-050506 |
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+
+ | GKHI-KS-021605.26-051706 |
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+
+ | GKHI-KS-112002.01-051206 |
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+
+ | GKHI-KS-072605-01-050506 |
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+
+ | GKHI-KS-091405-23-050506 |
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+
+ | GKHI-KS-111104-18-050506 |
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+ | GKHI-KS-031804-07-050506 |
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+ | GKHI-KS-092005.16-051206 |
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+
+ | GKHI-KS-031403.01-060806 |
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+ | GKHI-KS-090104.21-051106 |
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+ | GKHI-KS-040204.30 |
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+ | GKHI-KS-051805-16-050506 |
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+ | GKHI-KS-111902-04-050506 |
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+
+ | GKHI-KS-050604-01-050406 |
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+
+ | GKHI-KS-080905-43-050406 |
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+
+ | GKHI-KS-031004-01-050406 |
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+ | GKHI-KS-020504-01-050406 |
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+
+ | GKHI-KS-071504-01-050406 |
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+ | GKHI-KS-081104-05-050406 |
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+
+ | GKHI-KS-031204-01-050406 |
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+ | GKHI-KS-021104.06-051706 |
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+ | GKHI-KS-033005-21-050306 |
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+ | GKHI-KS-090204-01-050306 |
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+
+ | GKHI_KS-010704.01-040606 |
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+
+ | GKHI_KS_013004.38-042006 |
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+ | GKHI_KS_110105.30-042006 |
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+
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+
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+
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+
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+
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+
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+
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+
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+
+ | GKHI-KS-070605.43 |
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+
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+
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+
+ | KS-011305-11-042606 |
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+
+ | KS-110805-27-042606 |
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+
+ | KS-080404-28-042606 |
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+
+ | KS-080504-04-042606 |
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+
+ | KS-051705-57-042606 |
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+
+ | KS-032905-46-042606 |
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+
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+
+ | GKHI-KS-101105.26 |
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+
+
+ | GKHI_KS-062304.02-040606 |
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+
+
+ | GKHI_KS_071404.01-042006 |
+ 4 |
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+
+
+ | GKHI_KS_031005.17-042006 |
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+
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+
+
+ | GKHI-KS-012406.21-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-012406.24-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-030206.13-060806 |
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+
+ | GKHI-KS-030206.16-060806 |
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+
+ | GKHI-KS-011906.31-060806 |
+ 3 |
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+ |
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+
+ | GKHI-KS-011906.34-060806 |
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+ |
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+
+ | GKHI-KS-060806.04-070706 |
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+ |
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+
+
+ | GKHI-KS-071505.08-060806 |
+ 3 |
+ 06/07/02 |
+ 0.71 |
+ 37.4 |
+ C57BL/6ByJ |
+ |
+ F |
+ 51 |
+ JAX |
+
+
+ | GKHI-KS-071505.11-060806 |
+ 2 |
+ 06/07/02 |
+ 0.73 |
+ 39.2 |
+ C57BL/6ByJ |
+ |
+ F |
+ 51 |
+ JAX |
+
+
+ | GKHI-KS-030305.15-060806 |
+ 3 |
+ 06/07/02 |
+ 0.71 |
+ 37.4 |
+ CAST/Ei |
+ |
+ F |
+ 64 |
+ JAX |
+
+
+ | GKHI-KS-031005.35-060906 |
+ 3 |
+ 06/08/02 |
+ 0.70 |
+ 35.7 |
+ CAST/Ei |
+ |
+ M |
+ 64 |
+ JAX |
+
+
+ | GKHI-KS-022206.16-060906 |
+ 3 |
+ 06/08/02 |
+ 0.71 |
+ 37.9 |
+ KK/HlJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-022206.07-060906 |
+ 3 |
+ 06/08/02 |
+ 0.72 |
+ 35.5 |
+ KK/HlJ |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031606.01-060906 |
+ 3 |
+ 06/08/02 |
+ 0.86 |
+ 35.9 |
+ MOLF/Ei |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-022206.16-060906 |
+ 3 |
+ 06/08/02 |
+ 0.87 |
+ 37.4 |
+ MOLF/Ei |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012006.25-060906 |
+ 3 |
+ 06/08/02 |
+ 0.75 |
+ 38.3 |
+ NOD/LtJ |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012006.28-061306 |
+ 3 |
+ 06/11/02 |
+ 0.82 |
+ 37.1 |
+ NOD/LtJ |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-032306.04.060906 |
+ 3 |
+ 06/08/02 |
+ 0.73 |
+ 40.2 |
+ NZB/BlNJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-032306.07-060906 |
+ 3 |
+ 06/08/02 |
+ 0.74 |
+ 39.4 |
+ NZB/BlNJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020706.04-060906 |
+ 3 |
+ 06/08/02 |
+ 0.71 |
+ 41.6 |
+ NZW/LacJ |
+ |
+ F |
+ 65 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.19-060906 |
+ 3 |
+ 06/08/02 |
+ 0.77 |
+ 36.7 |
+ NZW/LacJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012406.33-061306 |
+ 3 |
+ 06/11/02 |
+ 0.95 |
+ 35.3 |
+ PWD/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012406.30-062006 |
+ 3 |
+ 06/18/02 |
+ 0.88 |
+ 36.3 |
+ PWD/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.01-062206 |
+ 3 |
+ 06/21/02 |
+ 1.02 |
+ 35.9 |
+ PWK/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.04-062206 |
+ 3 |
+ 06/21/02 |
+ 0.96 |
+ 38.7 |
+ PWK/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.07-062206 |
+ 3 |
+ 06/21/02 |
+ 0.98 |
+ 36.6 |
+ PWK/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.10-062206 |
+ 3 |
+ 06/21/02 |
+ 0.87 |
+ 35.2 |
+ PWK/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-052705.01-061306 |
+ 2 |
+ 06/11/02 |
+ 0.72 |
+ 38.3 |
+ WSB/EiJ |
+ |
+ F |
+ 52 |
+ UTM RW |
+
+
+ | GKHI-KS-051005.07-061306 |
+ 3 |
+ 06/11/02 |
+ 0.77 |
+ 38.0 |
+ WSB/EiJ |
+ |
+ M |
+ 58 |
+ JAX |
+
+
+
+
diff --git a/general/datasets/Ma_m2_0706_p/notes.rtf b/general/datasets/Ma_m2_0706_p/notes.rtf
new file mode 100644
index 0000000..d41fda1
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_p/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by Kremena Star on July 22 ,2006. Updated by KS on July 25, 2006.
+
diff --git a/general/datasets/Ma_m2_0706_p/platform.rtf b/general/datasets/Ma_m2_0706_p/platform.rtf
new file mode 100644
index 0000000..cb0e8d5
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_p/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
+
diff --git a/general/datasets/Ma_m2_0706_p/processing.rtf b/general/datasets/Ma_m2_0706_p/processing.rtf
new file mode 100644
index 0000000..b313d60
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_p/processing.rtf
@@ -0,0 +1,15 @@
+
+Probe set data from the CHP file: The expression values were generated using RMA. The same simple steps described above were also applied to these values.
+
+
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
+
+
+
+All data links (right-most column above) will be made active as sooon as the global analysis of these data by the Consoritum has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of the PDNN probe set data. Contact RW Williams regarding data access probelms.
+
diff --git a/general/datasets/Ma_m2_0706_p/summary.rtf b/general/datasets/Ma_m2_0706_p/summary.rtf
new file mode 100644
index 0000000..9055ba0
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_p/summary.rtf
@@ -0,0 +1 @@
+The July 2006 Kidney QTL Consortium data set provides estimates of mRNA expression in the adult kidney of 70 genetically diverse strains of mice including 54 BXD recombinant inbred strains, a set of 15 inbred strains, and 1 F1 hybrid; D2B6F1. Kidney samples were processed using a total of 153 Affymetrix Mouse Expression 430 2.0 microarrays (M430v2.0). This particular data set was processed using the RMA protocol. CAUTION: This dataset is not sex-balanced.
diff --git a/general/datasets/Ma_m2_0706_p/tissue.rtf b/general/datasets/Ma_m2_0706_p/tissue.rtf
new file mode 100644
index 0000000..5bc52e9
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_p/tissue.rtf
@@ -0,0 +1,3 @@
+
+BXD animals were obtained from UTHSC, and the Jackson Laboratory (Table 1). Animals were housed at UTHSC, at Harvard/BIDMC (Glenn Rosen), at the University of Memphis (Douglas Matthews), or the Jackson Laboratory before sacrifice (see Table 1). Mice were killed by cervical dislocation and kidneys were removed and placed in RNAlater prior to dissection. Kidneys were dissected whole and cleaned from the adrenal glands by Hong Tao Zhang in Dr. Lu’s lab. Kidneys from two to six animals per strain were pooled and shipped to Kremena Star at Mount Sinai School of Medicine (MSSM). Animals used in this study were between 50 and 99 days of age (average of 62 days; see Table 1).
+
diff --git a/general/datasets/Ma_m2_0706_r/acknowledgment.rtf b/general/datasets/Ma_m2_0706_r/acknowledgment.rtf
new file mode 100644
index 0000000..fea38e8
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_r/acknowledgment.rtf
@@ -0,0 +1,24 @@
+
+Data were generated with funds provided by a variety of public and private source to members of the Kidney Consortium. Members of the Kidney Consortium thank the following sources for financial support of this effort:
+
+
+ - Erwin Bottinger, M.D.
+ Grant Support: R01 DK60043-04
+ - Russell Chesney, M.D.
+ Grant Support: Le Bonheur Chair of Excellence in Pediatrics II
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Peter Mundel
+ Grant Support: NIH R01DK57683, NIH R01 DK 62472
+ - Paul Klotman
+ Grant Support: PO1 DK56492, PO1 DK56492.
+ - Matthew Breyer
+ Grant Support: DK-38226
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
+
diff --git a/general/datasets/Ma_m2_0706_r/cases.rtf b/general/datasets/Ma_m2_0706_r/cases.rtf
new file mode 100644
index 0000000..465b87c
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_r/cases.rtf
@@ -0,0 +1,44 @@
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 30 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred. We have also included 24 BXD lines generated by Lu and Peirce. All of these strains have been genotyped at 13,377 SNPs.
+
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 15 inbred strains and a pair of F1 hybrids; D2B6F1. These strains were selected for the following reasons: This panel will be a powerful tool in systems genetic analysis of a wide variety of traits, and will provide additional power in fine mapping modulators through an association analysis of sequence variants.
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+
+ - BTBR T+tf/J
+ Multiple recessive stock; Homozygotes show repeated waves of hair loss and regrowth, which begin in the nose and pass posteriorly along the body.
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - D2B6F1
+ F1 hybrid generated by crossing C57BL/6J with DBA/2J
+
+
+These inbred strains can be ordered from The Jackson Laboratory. BXD43 through BXD100 are available from Lu Lu and colleagues at UTHSC.P>
+
+
diff --git a/general/datasets/Ma_m2_0706_r/experiment-design.rtf b/general/datasets/Ma_m2_0706_r/experiment-design.rtf
new file mode 100644
index 0000000..464e50d
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_r/experiment-design.rtf
@@ -0,0 +1,1864 @@
+
+Sample Processing: : Samples were processed at the Mount Sinai School of Medicine in the laboratory of Dr. Erwin Bottinger. All processing steps were performed Kremena Star. Total RNA was extracted with TRIZOL, followed by Rneasy Mini Kit purification (QUAGEN) by Kremena Star at MSSM. RNA purity was evaluated using the 260/280 nm (protein contamination) and the 260/230 nm (TRIZOL contamination) absorbance ratios, and values had to be greater than 1.9 and 0.8 respectively. Most of the samples 260/280 nm values fell between 1.9 and 2.1 and the majority of the 260/230 nm measurements were in the range 1.8 to 2.3. RNA integrity was assessed with the Agilent Bioanalyzer 2100. We set a quality threshold at 28s/18s rRNA greater than 0.9 or RNA integrity number (RIN) of greater than 6.9. When the two metrics were in disagreement we gave priority on the RIN value as recommended by the Agilent Bioanalyzer 2100 technical support representative. Synthesis of cDNA template from total RNA was performed using the one-cyclecDNA synthesis kit from Affymetrix (Affymetrix, P/N 900431). The Affymetrix IVT-labeling kit ((Affymetrix, P/N 900449)) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 1.9 to 2.1). The cRNA is then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup (Affymetrix, P/N 900371). Fragmented cRNA samples were accessed with Agilent Bioanalyzer 2100 (cRNA frgments between 25 and 200 nucleotides are required for optimal hybridization and immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each isogenic group. Initially all strains were represented by male and female samples, however, not all data sets passed the quality control steps. Forty-two (thirty-one BXD, D2B6F1 and ten inbred strains) are represented by male and female samples.
+
+Experimental Design and Batch Structure: The data set consists of arrays processed in twenty-three groups over a six month period (March 2006 to July 2006). Each group consists of 4 to 12 arrays. All arrays were processed using the Affymetrix Eukaryotic Sample and Array Processing protocol (701024 Rev. 3), by a single operator, Kremena Star. All samples in a group were labeled on the same. The hybridization station accommodates up to 4 samples, and since most of the groups had 12 samples, processed in 3 batches on the same day. Samples were washed in groups of four and kept at 4° C until all 12 (or 4-12) arrays were ready to scan. Samples were scanned in sets of four.
+
+
+This table lists all arrays ordered by strain and includes Microarray ID, number of mice per pool, Microarray date, GAPDH 3`/5`Signal Ratio, Percent of transcripts present on the microarray chip, Strain, Generation, Sex, Age and Source of mice.
+
+
+
+
+
+ | Microarray_ID |
+ # mice |
+ Microarray Date |
+ GAPDH (3`/5`) |
+ % present |
+ strains |
+ generation |
+ sex |
+ age |
+ Mice Source |
+
+
+ | GKHI-KS-050603.07-051706 |
+ 3 |
+ 05/14/02 |
+ 0.73 |
+ 37.6 |
+ C57BL/6J |
+ |
+ M |
+ 56 |
+ UTM RW |
+
+
+ | GKHI-KS-070803.01-051706 |
+ 3 |
+ 05/14/02 |
+ 0.75 |
+ 41.6 |
+ C57BL/6J |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI-KS-DBA-Male-070706 |
+ 2 |
+ 07/06/02 |
+ 0.71 |
+ 37.3 |
+ DBA/2J |
+ |
+ M |
+ 56 |
+ JAX |
+
+
+ | GKHI_KS_121404.75-042106 |
+ 4 |
+ 04/18/02 |
+ |
+ |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_121404.75-033006 |
+ 4 |
+ 03/19/02 |
+ 0.73 |
+ 48.5 |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_121404.78-042006 |
+ 4 |
+ 04/17/02 |
+ 0.83 |
+ 40.6 |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_070804.39-042006 |
+ 4 |
+ 04/17/02 |
+ 0.82 |
+ 39.0 |
+ D2B6F1 |
+ |
+ M |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_030904.01-042006 |
+ 4 |
+ 04/17/02 |
+ 0.82 |
+ 35.9 |
+ D2B6F1 |
+ |
+ M |
+ 57 |
+ UTM RW |
+
+
+ | GKHI-KS-121404.73-070706 |
+ 2 |
+ 07/06/02 |
+ 0.76 |
+ 36.3 |
+ D2B6F1 |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI-KS-010705.38-051206 |
+ 5 |
+ 05/09/02 |
+ 0.81 |
+ 39.9 |
+ BXD1 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-060905.19 |
+ 5 |
+ 06/05/02 |
+ 0.75 |
+ 42.3 |
+ BXD1 |
+ |
+ M |
+ 68 |
+ UTM RW |
+
+
+ | GKHI-KS-051206.13-070706 |
+ 3 |
+ 07/06/02 |
+ 0.71 |
+ 36.3 |
+ BXD1 |
+ |
+ F |
+ 57 |
+ UTM RW |
+
+
+ | GKHI-KS-021304.10-051206 |
+ 4 |
+ 05/09/02 |
+ 0.81 |
+ 39.1 |
+ BXD2 |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-040303-04-050406 |
+ 3 |
+ 05/01/02 |
+ 0.80 |
+ 37.6 |
+ BXD5 |
+ |
+ F |
+ 56 |
+ UMemphis |
+
+
+ | GKHI-KS-010705-53-050306 |
+ 5 |
+ 05/01/02 |
+ 0.76 |
+ 37.1 |
+ BXD5 |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031103.01-062206 |
+ 3 |
+ 06/21/02 |
+ 0.75 |
+ 37.1 |
+ BXD5 |
+ |
+ M |
+ 71 |
+ UMemphis |
+
+
+ | GKHI-KS-040505-51-050306 |
+ 5 |
+ 05/01/02 |
+ 0.71 |
+ 35.5 |
+ BXD6 |
+ |
+ M |
+ 58 |
+ UTM RW |
+
+
+ | GKHI-KS-092705-29--050406 |
+ 5 |
+ 05/02/02 |
+ 0.75 |
+ 36.1 |
+ BXD6 |
+ 160 |
+ F |
+ 64 |
+ UTM RW |
+
+
+ | GKHI_KS_092404.01-042106 |
+ 4 |
+ 04/18/02 |
+ 0.71 |
+ 36.3 |
+ BXD8 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-051205-25-042706 |
+ 5 |
+ 04/23/02 |
+ 0.92 |
+ 37.9 |
+ BXD8 |
+ |
+ F |
+ 77 |
+ UTM RW |
+
+
+ | KS-021605-17-042606 |
+ 5 |
+ 04/22/02 |
+ 0.85 |
+ 40.8 |
+ BXD9 |
+ |
+ F |
+ 67 |
+ UTM RW |
+
+
+ | KS-032905-32-042606 |
+ 5 |
+ 04/22/02 |
+ 0.91 |
+ 36.8 |
+ BXD9 |
+ |
+ F |
+ 60 |
+ UTM RW |
+
+
+ | GKHI-KS-062006.08-070706 |
+ 3 |
+ 07/06/02 |
+ 0.74 |
+ 36.3 |
+ BXD9 |
+ |
+ M |
+ 78 |
+ UTM RW |
+
+
+ | GKHI-KS-031505.22-051206 |
+ 5 |
+ 05/09/02 |
+ 0.74 |
+ 39.5 |
+ BXD11 |
+ |
+ F |
+ 65 |
+ UTM RW |
+
+
+ | GKHI-KS-031605.01 |
+ 5 |
+ 06/05/02 |
+ 0.74 |
+ 43.4 |
+ BXD11 |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI_KS_102104.40-042106 |
+ 4 |
+ 04/18/02 |
+ 0.72 |
+ 38.5 |
+ BXD12 |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-112002.07-051106 |
+ 2 |
+ 05/08/02 |
+ 0.77 |
+ 42.0 |
+ BXD12 |
+ |
+ F |
+ 64 |
+ UMemphis |
+
+
+ | GKHI-KS-120904.33-051206 |
+ 4 |
+ 05/09/02 |
+ 0.71 |
+ 38.4 |
+ BXD13 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-042304.01 |
+ 4 |
+ 06/05/02 |
+ 0.71 |
+ 44.1 |
+ BXD13 |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020905.34-051106 |
+ 5 |
+ 05/08/02 |
+ 0.75 |
+ 40.7 |
+ BXD14 |
+ |
+ F |
+ 68 |
+ UTM RW |
+
+
+ | GKHI-KS-022405.46-051106 |
+ 5 |
+ 05/08/02 |
+ 0.71 |
+ 40.2 |
+ BXD14 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-091704.09-062206 |
+ 4 |
+ 06/21/02 |
+ 0.73 |
+ 39.0 |
+ BXD14 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-013004.45-062206 |
+ 4 |
+ 06/21/02 |
+ 0.76 |
+ 38.5 |
+ BXD15 |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-022405.43-051106 |
+ 5 |
+ 05/08/02 |
+ 0.73 |
+ 40.5 |
+ BXD15 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
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+
+ | GKHI-KS-041604.10-051106 |
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+
+ | GKHI-KS-031805.01-051106 |
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+
+ | GKHI-KS-031805.04-051106 |
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+
+ | GKHI-KS-040805.10-051006 |
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+
+ | GKHI-KS-052804.09-051106 |
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+
+ | GKHI-KS-010705.47-051106 |
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+
+ | GKHI-KS-010705.44-070706 |
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+
+ | GKHI-KS-062905.07-051106 |
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+
+ | GKHI-KS-072104.58-051106 |
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+
+ | GKHI-KS-050405.21-051206 |
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+
+ | GKHI-KS-040705.24 |
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+
+ | GKHI-KS-110405.01-051006 |
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+
+ | GKHI-KS-110405.04-051006 |
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+
+ | GKHI-KS-040805.01-051206 |
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+
+ | GKHI-KS-040805.04-051006 |
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+
+ | GKHI_KS_091704.13-042106 |
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+
+ | GKHI-KS-040303-20-050206 |
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+
+ | GKHI-KS-021805.20-051006 |
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+
+ | GKHI-KS-090705.05-062206 |
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+
+ | GKHI-KS-090705.03-051006 |
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+
+ | GKHI-KS-022105.42-051006 |
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+
+ | GKHI-KS-032205.31-051006 |
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+
+ | GKHI-KS-060706.10-070706 |
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+
+ | GKHI-KS-012805-41-050506 |
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+
+ | GKHI-KS-012805-44-050506 |
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+
+ | GKHI-KS-012805-38-050506 |
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+
+ | GKHI-KS-012805-35-050506 |
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+
+ | GKHI-KS-012805-32-050506 |
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+
+ | GKHI-KS-100604-07-050506 |
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+
+ | GKHI-KS-021605.26-051706 |
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+
+ | GKHI-KS-112002.01-051206 |
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+
+ | GKHI-KS-072605-01-050506 |
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+
+ | GKHI-KS-091405-23-050506 |
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+
+ | GKHI-KS-111104-18-050506 |
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+
+ | GKHI-KS-031804-07-050506 |
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+
+ | GKHI-KS-092005.16-051206 |
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+
+ | GKHI-KS-031403.01-060806 |
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+
+ | GKHI-KS-090104.21-051106 |
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+
+ | GKHI-KS-040204.30 |
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+
+ | GKHI-KS-051805-16-050506 |
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+
+ | GKHI-KS-111902-04-050506 |
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+
+ | GKHI-KS-050604-01-050406 |
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+
+ | GKHI-KS-080905-43-050406 |
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+
+ | GKHI-KS-031004-01-050406 |
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+
+ | GKHI-KS-020504-01-050406 |
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+
+ | GKHI-KS-071504-01-050406 |
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+
+ | GKHI-KS-081104-05-050406 |
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+
+ | GKHI-KS-031204-01-050406 |
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+
+ | GKHI-KS-021104.06-051706 |
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+
+ | GKHI-KS-033005-21-050306 |
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+
+ | GKHI-KS-090204-01-050306 |
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+
+ | GKHI_KS-010704.01-040606 |
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+
+ | GKHI_KS_013004.38-042006 |
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+
+ | GKHI-KS-030905-28-050206 |
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+
+ | GKHI-KS-050305-18-050206 |
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+
+ | GKHI_KS-121803.01-040706 |
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+
+ | GKHI_KS_021204.01-042006 |
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+
+ | GKHI-KS-020905-25-050206 |
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+
+ | GKHI-KS-040705.49-060806 |
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+
+ | GKHI-KS-040406.12-060806 |
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+
+ | GKHI_KS_110105.30-042006 |
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+
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+
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+
+ | GKHI-KS-042705-01-042706 |
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+
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+
+ | GKHI-KS-030805-40-042706 |
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+
+ | GKHI-KS-041905.172-062206 |
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+
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+
+ | GKHI-KS-041205-04-050406 |
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+
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+
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+
+ | GKHI-KS-070605.43 |
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+
+ | GKHI-KS-071205-31-042706 |
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+
+ | GKHI-KS-071205-2-042706 |
+ 5 |
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+
+ | KS-011305-11-042606 |
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+
+ | KS-110805-27-042606 |
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+
+ | KS-080404-28-042606 |
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+
+ | KS-080504-04-042606 |
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+
+ | KS-051705-57-042606 |
+ 5 |
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+
+ | KS-032905-46-042606 |
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+
+ | GKHI-KS-080905-49-042706 |
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+
+ | GKHI-KS-101105.26 |
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+
+
+ | GKHI_KS-062304.02-040606 |
+ 4 |
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+
+
+ | GKHI_KS_071404.01-042006 |
+ 4 |
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+
+
+ | GKHI_KS_031005.17-042006 |
+ 5 |
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+
+
+ | GKHI-KS-111505.12 |
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+
+
+ | GKHI-KS-012406.21-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-012406.24-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-030206.13-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-030206.16-060806 |
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+
+
+ | GKHI-KS-011906.31-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-011906.34-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-060806.04-070706 |
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+ |
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+
+
+ | GKHI-KS-071505.08-060806 |
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+ |
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+
+
+ | GKHI-KS-071505.11-060806 |
+ 2 |
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+ |
+ F |
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+
+
+ | GKHI-KS-030305.15-060806 |
+ 3 |
+ 06/07/02 |
+ 0.71 |
+ 37.4 |
+ CAST/Ei |
+ |
+ F |
+ 64 |
+ JAX |
+
+
+ | GKHI-KS-031005.35-060906 |
+ 3 |
+ 06/08/02 |
+ 0.70 |
+ 35.7 |
+ CAST/Ei |
+ |
+ M |
+ 64 |
+ JAX |
+
+
+ | GKHI-KS-022206.16-060906 |
+ 3 |
+ 06/08/02 |
+ 0.71 |
+ 37.9 |
+ KK/HlJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-022206.07-060906 |
+ 3 |
+ 06/08/02 |
+ 0.72 |
+ 35.5 |
+ KK/HlJ |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031606.01-060906 |
+ 3 |
+ 06/08/02 |
+ 0.86 |
+ 35.9 |
+ MOLF/Ei |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-022206.16-060906 |
+ 3 |
+ 06/08/02 |
+ 0.87 |
+ 37.4 |
+ MOLF/Ei |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012006.25-060906 |
+ 3 |
+ 06/08/02 |
+ 0.75 |
+ 38.3 |
+ NOD/LtJ |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012006.28-061306 |
+ 3 |
+ 06/11/02 |
+ 0.82 |
+ 37.1 |
+ NOD/LtJ |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-032306.04.060906 |
+ 3 |
+ 06/08/02 |
+ 0.73 |
+ 40.2 |
+ NZB/BlNJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-032306.07-060906 |
+ 3 |
+ 06/08/02 |
+ 0.74 |
+ 39.4 |
+ NZB/BlNJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020706.04-060906 |
+ 3 |
+ 06/08/02 |
+ 0.71 |
+ 41.6 |
+ NZW/LacJ |
+ |
+ F |
+ 65 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.19-060906 |
+ 3 |
+ 06/08/02 |
+ 0.77 |
+ 36.7 |
+ NZW/LacJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012406.33-061306 |
+ 3 |
+ 06/11/02 |
+ 0.95 |
+ 35.3 |
+ PWD/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012406.30-062006 |
+ 3 |
+ 06/18/02 |
+ 0.88 |
+ 36.3 |
+ PWD/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.01-062206 |
+ 3 |
+ 06/21/02 |
+ 1.02 |
+ 35.9 |
+ PWK/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.04-062206 |
+ 3 |
+ 06/21/02 |
+ 0.96 |
+ 38.7 |
+ PWK/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.07-062206 |
+ 3 |
+ 06/21/02 |
+ 0.98 |
+ 36.6 |
+ PWK/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.10-062206 |
+ 3 |
+ 06/21/02 |
+ 0.87 |
+ 35.2 |
+ PWK/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-052705.01-061306 |
+ 2 |
+ 06/11/02 |
+ 0.72 |
+ 38.3 |
+ WSB/EiJ |
+ |
+ F |
+ 52 |
+ UTM RW |
+
+
+ | GKHI-KS-051005.07-061306 |
+ 3 |
+ 06/11/02 |
+ 0.77 |
+ 38.0 |
+ WSB/EiJ |
+ |
+ M |
+ 58 |
+ JAX |
+
+
+
+
diff --git a/general/datasets/Ma_m2_0706_r/notes.rtf b/general/datasets/Ma_m2_0706_r/notes.rtf
new file mode 100644
index 0000000..d41fda1
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by Kremena Star on July 22 ,2006. Updated by KS on July 25, 2006.
+
diff --git a/general/datasets/Ma_m2_0706_r/platform.rtf b/general/datasets/Ma_m2_0706_r/platform.rtf
new file mode 100644
index 0000000..cb0e8d5
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
+
diff --git a/general/datasets/Ma_m2_0706_r/processing.rtf b/general/datasets/Ma_m2_0706_r/processing.rtf
new file mode 100644
index 0000000..b313d60
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_r/processing.rtf
@@ -0,0 +1,15 @@
+
+Probe set data from the CHP file: The expression values were generated using RMA. The same simple steps described above were also applied to these values.
+
+
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
+
+
+
+All data links (right-most column above) will be made active as sooon as the global analysis of these data by the Consoritum has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of the PDNN probe set data. Contact RW Williams regarding data access probelms.
+
diff --git a/general/datasets/Ma_m2_0706_r/summary.rtf b/general/datasets/Ma_m2_0706_r/summary.rtf
new file mode 100644
index 0000000..9055ba0
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_r/summary.rtf
@@ -0,0 +1 @@
+The July 2006 Kidney QTL Consortium data set provides estimates of mRNA expression in the adult kidney of 70 genetically diverse strains of mice including 54 BXD recombinant inbred strains, a set of 15 inbred strains, and 1 F1 hybrid; D2B6F1. Kidney samples were processed using a total of 153 Affymetrix Mouse Expression 430 2.0 microarrays (M430v2.0). This particular data set was processed using the RMA protocol. CAUTION: This dataset is not sex-balanced.
diff --git a/general/datasets/Ma_m2_0706_r/tissue.rtf b/general/datasets/Ma_m2_0706_r/tissue.rtf
new file mode 100644
index 0000000..5bc52e9
--- /dev/null
+++ b/general/datasets/Ma_m2_0706_r/tissue.rtf
@@ -0,0 +1,3 @@
+
+BXD animals were obtained from UTHSC, and the Jackson Laboratory (Table 1). Animals were housed at UTHSC, at Harvard/BIDMC (Glenn Rosen), at the University of Memphis (Douglas Matthews), or the Jackson Laboratory before sacrifice (see Table 1). Mice were killed by cervical dislocation and kidneys were removed and placed in RNAlater prior to dissection. Kidneys were dissected whole and cleaned from the adrenal glands by Hong Tao Zhang in Dr. Lu’s lab. Kidneys from two to six animals per strain were pooled and shipped to Kremena Star at Mount Sinai School of Medicine (MSSM). Animals used in this study were between 50 and 99 days of age (average of 62 days; see Table 1).
+
diff --git a/general/datasets/Ma_m2_0806_p/acknowledgment.rtf b/general/datasets/Ma_m2_0806_p/acknowledgment.rtf
new file mode 100644
index 0000000..fea38e8
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_p/acknowledgment.rtf
@@ -0,0 +1,24 @@
+
+Data were generated with funds provided by a variety of public and private source to members of the Kidney Consortium. Members of the Kidney Consortium thank the following sources for financial support of this effort:
+
+
+ - Erwin Bottinger, M.D.
+ Grant Support: R01 DK60043-04
+ - Russell Chesney, M.D.
+ Grant Support: Le Bonheur Chair of Excellence in Pediatrics II
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Peter Mundel
+ Grant Support: NIH R01DK57683, NIH R01 DK 62472
+ - Paul Klotman
+ Grant Support: PO1 DK56492, PO1 DK56492.
+ - Matthew Breyer
+ Grant Support: DK-38226
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
+
diff --git a/general/datasets/Ma_m2_0806_p/cases.rtf b/general/datasets/Ma_m2_0806_p/cases.rtf
new file mode 100644
index 0000000..465b87c
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_p/cases.rtf
@@ -0,0 +1,44 @@
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 30 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred. We have also included 24 BXD lines generated by Lu and Peirce. All of these strains have been genotyped at 13,377 SNPs.
+
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 15 inbred strains and a pair of F1 hybrids; D2B6F1. These strains were selected for the following reasons: This panel will be a powerful tool in systems genetic analysis of a wide variety of traits, and will provide additional power in fine mapping modulators through an association analysis of sequence variants.
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+
+ - BTBR T+tf/J
+ Multiple recessive stock; Homozygotes show repeated waves of hair loss and regrowth, which begin in the nose and pass posteriorly along the body.
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - D2B6F1
+ F1 hybrid generated by crossing C57BL/6J with DBA/2J
+
+
+These inbred strains can be ordered from The Jackson Laboratory. BXD43 through BXD100 are available from Lu Lu and colleagues at UTHSC.P>
+
+
diff --git a/general/datasets/Ma_m2_0806_p/experiment-design.rtf b/general/datasets/Ma_m2_0806_p/experiment-design.rtf
new file mode 100644
index 0000000..464e50d
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_p/experiment-design.rtf
@@ -0,0 +1,1864 @@
+
+Sample Processing: : Samples were processed at the Mount Sinai School of Medicine in the laboratory of Dr. Erwin Bottinger. All processing steps were performed Kremena Star. Total RNA was extracted with TRIZOL, followed by Rneasy Mini Kit purification (QUAGEN) by Kremena Star at MSSM. RNA purity was evaluated using the 260/280 nm (protein contamination) and the 260/230 nm (TRIZOL contamination) absorbance ratios, and values had to be greater than 1.9 and 0.8 respectively. Most of the samples 260/280 nm values fell between 1.9 and 2.1 and the majority of the 260/230 nm measurements were in the range 1.8 to 2.3. RNA integrity was assessed with the Agilent Bioanalyzer 2100. We set a quality threshold at 28s/18s rRNA greater than 0.9 or RNA integrity number (RIN) of greater than 6.9. When the two metrics were in disagreement we gave priority on the RIN value as recommended by the Agilent Bioanalyzer 2100 technical support representative. Synthesis of cDNA template from total RNA was performed using the one-cyclecDNA synthesis kit from Affymetrix (Affymetrix, P/N 900431). The Affymetrix IVT-labeling kit ((Affymetrix, P/N 900449)) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 1.9 to 2.1). The cRNA is then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup (Affymetrix, P/N 900371). Fragmented cRNA samples were accessed with Agilent Bioanalyzer 2100 (cRNA frgments between 25 and 200 nucleotides are required for optimal hybridization and immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each isogenic group. Initially all strains were represented by male and female samples, however, not all data sets passed the quality control steps. Forty-two (thirty-one BXD, D2B6F1 and ten inbred strains) are represented by male and female samples.
+
+Experimental Design and Batch Structure: The data set consists of arrays processed in twenty-three groups over a six month period (March 2006 to July 2006). Each group consists of 4 to 12 arrays. All arrays were processed using the Affymetrix Eukaryotic Sample and Array Processing protocol (701024 Rev. 3), by a single operator, Kremena Star. All samples in a group were labeled on the same. The hybridization station accommodates up to 4 samples, and since most of the groups had 12 samples, processed in 3 batches on the same day. Samples were washed in groups of four and kept at 4° C until all 12 (or 4-12) arrays were ready to scan. Samples were scanned in sets of four.
+
+
+This table lists all arrays ordered by strain and includes Microarray ID, number of mice per pool, Microarray date, GAPDH 3`/5`Signal Ratio, Percent of transcripts present on the microarray chip, Strain, Generation, Sex, Age and Source of mice.
+
+
+
+
+
+ | Microarray_ID |
+ # mice |
+ Microarray Date |
+ GAPDH (3`/5`) |
+ % present |
+ strains |
+ generation |
+ sex |
+ age |
+ Mice Source |
+
+
+ | GKHI-KS-050603.07-051706 |
+ 3 |
+ 05/14/02 |
+ 0.73 |
+ 37.6 |
+ C57BL/6J |
+ |
+ M |
+ 56 |
+ UTM RW |
+
+
+ | GKHI-KS-070803.01-051706 |
+ 3 |
+ 05/14/02 |
+ 0.75 |
+ 41.6 |
+ C57BL/6J |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI-KS-DBA-Male-070706 |
+ 2 |
+ 07/06/02 |
+ 0.71 |
+ 37.3 |
+ DBA/2J |
+ |
+ M |
+ 56 |
+ JAX |
+
+
+ | GKHI_KS_121404.75-042106 |
+ 4 |
+ 04/18/02 |
+ |
+ |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_121404.75-033006 |
+ 4 |
+ 03/19/02 |
+ 0.73 |
+ 48.5 |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_121404.78-042006 |
+ 4 |
+ 04/17/02 |
+ 0.83 |
+ 40.6 |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_070804.39-042006 |
+ 4 |
+ 04/17/02 |
+ 0.82 |
+ 39.0 |
+ D2B6F1 |
+ |
+ M |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_030904.01-042006 |
+ 4 |
+ 04/17/02 |
+ 0.82 |
+ 35.9 |
+ D2B6F1 |
+ |
+ M |
+ 57 |
+ UTM RW |
+
+
+ | GKHI-KS-121404.73-070706 |
+ 2 |
+ 07/06/02 |
+ 0.76 |
+ 36.3 |
+ D2B6F1 |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI-KS-010705.38-051206 |
+ 5 |
+ 05/09/02 |
+ 0.81 |
+ 39.9 |
+ BXD1 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-060905.19 |
+ 5 |
+ 06/05/02 |
+ 0.75 |
+ 42.3 |
+ BXD1 |
+ |
+ M |
+ 68 |
+ UTM RW |
+
+
+ | GKHI-KS-051206.13-070706 |
+ 3 |
+ 07/06/02 |
+ 0.71 |
+ 36.3 |
+ BXD1 |
+ |
+ F |
+ 57 |
+ UTM RW |
+
+
+ | GKHI-KS-021304.10-051206 |
+ 4 |
+ 05/09/02 |
+ 0.81 |
+ 39.1 |
+ BXD2 |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-040303-04-050406 |
+ 3 |
+ 05/01/02 |
+ 0.80 |
+ 37.6 |
+ BXD5 |
+ |
+ F |
+ 56 |
+ UMemphis |
+
+
+ | GKHI-KS-010705-53-050306 |
+ 5 |
+ 05/01/02 |
+ 0.76 |
+ 37.1 |
+ BXD5 |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031103.01-062206 |
+ 3 |
+ 06/21/02 |
+ 0.75 |
+ 37.1 |
+ BXD5 |
+ |
+ M |
+ 71 |
+ UMemphis |
+
+
+ | GKHI-KS-040505-51-050306 |
+ 5 |
+ 05/01/02 |
+ 0.71 |
+ 35.5 |
+ BXD6 |
+ |
+ M |
+ 58 |
+ UTM RW |
+
+
+ | GKHI-KS-092705-29--050406 |
+ 5 |
+ 05/02/02 |
+ 0.75 |
+ 36.1 |
+ BXD6 |
+ 160 |
+ F |
+ 64 |
+ UTM RW |
+
+
+ | GKHI_KS_092404.01-042106 |
+ 4 |
+ 04/18/02 |
+ 0.71 |
+ 36.3 |
+ BXD8 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-051205-25-042706 |
+ 5 |
+ 04/23/02 |
+ 0.92 |
+ 37.9 |
+ BXD8 |
+ |
+ F |
+ 77 |
+ UTM RW |
+
+
+ | KS-021605-17-042606 |
+ 5 |
+ 04/22/02 |
+ 0.85 |
+ 40.8 |
+ BXD9 |
+ |
+ F |
+ 67 |
+ UTM RW |
+
+
+ | KS-032905-32-042606 |
+ 5 |
+ 04/22/02 |
+ 0.91 |
+ 36.8 |
+ BXD9 |
+ |
+ F |
+ 60 |
+ UTM RW |
+
+
+ | GKHI-KS-062006.08-070706 |
+ 3 |
+ 07/06/02 |
+ 0.74 |
+ 36.3 |
+ BXD9 |
+ |
+ M |
+ 78 |
+ UTM RW |
+
+
+ | GKHI-KS-031505.22-051206 |
+ 5 |
+ 05/09/02 |
+ 0.74 |
+ 39.5 |
+ BXD11 |
+ |
+ F |
+ 65 |
+ UTM RW |
+
+
+ | GKHI-KS-031605.01 |
+ 5 |
+ 06/05/02 |
+ 0.74 |
+ 43.4 |
+ BXD11 |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI_KS_102104.40-042106 |
+ 4 |
+ 04/18/02 |
+ 0.72 |
+ 38.5 |
+ BXD12 |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-112002.07-051106 |
+ 2 |
+ 05/08/02 |
+ 0.77 |
+ 42.0 |
+ BXD12 |
+ |
+ F |
+ 64 |
+ UMemphis |
+
+
+ | GKHI-KS-120904.33-051206 |
+ 4 |
+ 05/09/02 |
+ 0.71 |
+ 38.4 |
+ BXD13 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-042304.01 |
+ 4 |
+ 06/05/02 |
+ 0.71 |
+ 44.1 |
+ BXD13 |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020905.34-051106 |
+ 5 |
+ 05/08/02 |
+ 0.75 |
+ 40.7 |
+ BXD14 |
+ |
+ F |
+ 68 |
+ UTM RW |
+
+
+ | GKHI-KS-022405.46-051106 |
+ 5 |
+ 05/08/02 |
+ 0.71 |
+ 40.2 |
+ BXD14 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-091704.09-062206 |
+ 4 |
+ 06/21/02 |
+ 0.73 |
+ 39.0 |
+ BXD14 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-013004.45-062206 |
+ 4 |
+ 06/21/02 |
+ 0.76 |
+ 38.5 |
+ BXD15 |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-022405.43-051106 |
+ 5 |
+ 05/08/02 |
+ 0.73 |
+ 40.5 |
+ BXD15 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-041604.10-051106 |
+ 4 |
+ 05/08/02 |
+ 0.73 |
+ 42.6 |
+ BXD15 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031805.01-051106 |
+ 5 |
+ 05/08/02 |
+ 0.79 |
+ 42.4 |
+ BXD16 |
+ |
+ F |
+ 59 |
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+
+ | GKHI-KS-031805.04-051106 |
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+
+ | GKHI-KS-040805.10-051006 |
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+
+ | GKHI-KS-052804.09-051106 |
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+
+ | GKHI-KS-010705.47-051106 |
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+
+ | GKHI-KS-010705.44-070706 |
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+
+ | GKHI-KS-062905.07-051106 |
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+
+ | GKHI-KS-072104.58-051106 |
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+
+ | GKHI-KS-050405.21-051206 |
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+
+ | GKHI-KS-040705.24 |
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+
+ | GKHI-KS-110405.01-051006 |
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+
+ | GKHI-KS-110405.04-051006 |
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+
+ | GKHI-KS-040805.01-051206 |
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+
+ | GKHI-KS-040805.04-051006 |
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+
+ | GKHI_KS_091704.13-042106 |
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+
+ | GKHI-KS-040303-20-050206 |
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+
+ | GKHI-KS-021805.20-051006 |
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+
+ | GKHI-KS-090705.05-062206 |
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+
+ | GKHI-KS-090705.03-051006 |
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+
+ | GKHI-KS-022105.42-051006 |
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+
+ | GKHI-KS-032205.31-051006 |
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+
+ | GKHI-KS-060706.10-070706 |
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+
+ | GKHI-KS-012805-41-050506 |
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+
+ | GKHI-KS-012805-44-050506 |
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+
+ | GKHI-KS-012805-38-050506 |
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+
+ | GKHI-KS-012805-35-050506 |
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+
+ | GKHI-KS-012805-32-050506 |
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+
+ | GKHI-KS-100604-07-050506 |
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+
+ | GKHI-KS-021605.26-051706 |
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+ F |
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+
+ | GKHI-KS-112002.01-051206 |
+ 2 |
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+
+ | GKHI-KS-072605-01-050506 |
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+
+ | GKHI-KS-091405-23-050506 |
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+
+ | GKHI-KS-111104-18-050506 |
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+
+ | GKHI-KS-031804-07-050506 |
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+
+ | GKHI-KS-092005.16-051206 |
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+
+ | GKHI-KS-031403.01-060806 |
+ 1 |
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+
+ | GKHI-KS-090104.21-051106 |
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+
+ | GKHI-KS-040204.30 |
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+
+ | GKHI-KS-051805-16-050506 |
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+
+ | GKHI-KS-111902-04-050506 |
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+
+ | GKHI-KS-050604-01-050406 |
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+
+ | GKHI-KS-080905-43-050406 |
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+
+ | GKHI-KS-031004-01-050406 |
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+
+ | GKHI-KS-020504-01-050406 |
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+
+ | GKHI-KS-071504-01-050406 |
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+
+ | GKHI-KS-081104-05-050406 |
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+
+ | GKHI-KS-031204-01-050406 |
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+
+ | GKHI-KS-021104.06-051706 |
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+
+ | GKHI-KS-033005-21-050306 |
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+
+ | GKHI-KS-090204-01-050306 |
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+
+ | GKHI_KS-010704.01-040606 |
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+
+ | GKHI_KS_013004.38-042006 |
+ 4 |
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+
+ | GKHI-KS-030905-28-050206 |
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+
+ | GKHI-KS-050305-18-050206 |
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+
+ | GKHI_KS-121803.01-040706 |
+ 3 |
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+
+ | GKHI_KS_021204.01-042006 |
+ 4 |
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+
+ | GKHI-KS-020905-25-050206 |
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+
+ | GKHI-KS-040705.49-060806 |
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+
+ | GKHI-KS-040406.12-060806 |
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+
+ | GKHI-KS-052405-36-050406 |
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+
+ | GKHI-KS-041205-01-050206 |
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+
+ | GKHI-KS-062305-01-050206 |
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+
+ | GKHI-KS-062305-09-050206 |
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+
+ | GKHI_KS_110105.30-042006 |
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+
+ | GKHI-KS-061504.64-062206 |
+ 4 |
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+
+ | GKHI_KS-050404.04-040606 |
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+
+ | GKHI-KS-042705-01-042706 |
+ 5 |
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+
+ | GKHI-KS-051705-59-042706 |
+ 5 |
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+
+
+ | GKHI-KS-030805-40-042706 |
+ 5 |
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+
+
+ | GKHI-KS-041905.172-062206 |
+ 5 |
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+
+ | GKHI-KS-072605-03-042706 |
+ 5 |
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+
+ | GKHI-KS-041205-04-050406 |
+ 5 |
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+
+ | GKHI-KS-041205.07 |
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+
+ | GKHI-KS-101805-35-050406 |
+ 5 |
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+
+
+ | GKHI-KS-070605.43 |
+ 5 |
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+
+
+ | GKHI-KS-071205-31-042706 |
+ 5 |
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+
+
+ | GKHI-KS-071205-2-042706 |
+ 5 |
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+
+
+ | KS-011305-11-042606 |
+ 5 |
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+
+
+ | KS-110805-27-042606 |
+ 5 |
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+
+
+ | KS-080404-28-042606 |
+ 4 |
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+
+
+ | KS-080504-04-042606 |
+ 4 |
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+
+
+ | KS-051705-57-042606 |
+ 5 |
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+
+
+ | KS-032905-46-042606 |
+ 5 |
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+
+
+ | GKHI-KS-080905-49-042706 |
+ 5 |
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+
+
+ | GKHI-KS-101105.26 |
+ 5 |
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+
+
+ | GKHI_KS-062304.02-040606 |
+ 4 |
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+
+
+ | GKHI_KS_071404.01-042006 |
+ 4 |
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+ UTM RW |
+
+
+ | GKHI_KS_031005.17-042006 |
+ 5 |
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+
+
+ | GKHI-KS-111505.12 |
+ 5 |
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+ UTM RW |
+
+
+ | GKHI-KS-012406.21-060806 |
+ 3 |
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+ |
+ F |
+ 60 |
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+
+
+ | GKHI-KS-012406.24-060806 |
+ 3 |
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+ |
+ F |
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+
+
+ | GKHI-KS-030206.13-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-030206.16-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-011906.31-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-011906.34-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-060806.04-070706 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-071505.08-060806 |
+ 3 |
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+ |
+ F |
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+
+
+ | GKHI-KS-071505.11-060806 |
+ 2 |
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+ |
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+
+
+ | GKHI-KS-030305.15-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-031005.35-060906 |
+ 3 |
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+ |
+ M |
+ 64 |
+ JAX |
+
+
+ | GKHI-KS-022206.16-060906 |
+ 3 |
+ 06/08/02 |
+ 0.71 |
+ 37.9 |
+ KK/HlJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-022206.07-060906 |
+ 3 |
+ 06/08/02 |
+ 0.72 |
+ 35.5 |
+ KK/HlJ |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031606.01-060906 |
+ 3 |
+ 06/08/02 |
+ 0.86 |
+ 35.9 |
+ MOLF/Ei |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-022206.16-060906 |
+ 3 |
+ 06/08/02 |
+ 0.87 |
+ 37.4 |
+ MOLF/Ei |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012006.25-060906 |
+ 3 |
+ 06/08/02 |
+ 0.75 |
+ 38.3 |
+ NOD/LtJ |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012006.28-061306 |
+ 3 |
+ 06/11/02 |
+ 0.82 |
+ 37.1 |
+ NOD/LtJ |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-032306.04.060906 |
+ 3 |
+ 06/08/02 |
+ 0.73 |
+ 40.2 |
+ NZB/BlNJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-032306.07-060906 |
+ 3 |
+ 06/08/02 |
+ 0.74 |
+ 39.4 |
+ NZB/BlNJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020706.04-060906 |
+ 3 |
+ 06/08/02 |
+ 0.71 |
+ 41.6 |
+ NZW/LacJ |
+ |
+ F |
+ 65 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.19-060906 |
+ 3 |
+ 06/08/02 |
+ 0.77 |
+ 36.7 |
+ NZW/LacJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012406.33-061306 |
+ 3 |
+ 06/11/02 |
+ 0.95 |
+ 35.3 |
+ PWD/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012406.30-062006 |
+ 3 |
+ 06/18/02 |
+ 0.88 |
+ 36.3 |
+ PWD/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.01-062206 |
+ 3 |
+ 06/21/02 |
+ 1.02 |
+ 35.9 |
+ PWK/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.04-062206 |
+ 3 |
+ 06/21/02 |
+ 0.96 |
+ 38.7 |
+ PWK/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.07-062206 |
+ 3 |
+ 06/21/02 |
+ 0.98 |
+ 36.6 |
+ PWK/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.10-062206 |
+ 3 |
+ 06/21/02 |
+ 0.87 |
+ 35.2 |
+ PWK/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-052705.01-061306 |
+ 2 |
+ 06/11/02 |
+ 0.72 |
+ 38.3 |
+ WSB/EiJ |
+ |
+ F |
+ 52 |
+ UTM RW |
+
+
+ | GKHI-KS-051005.07-061306 |
+ 3 |
+ 06/11/02 |
+ 0.77 |
+ 38.0 |
+ WSB/EiJ |
+ |
+ M |
+ 58 |
+ JAX |
+
+
+
+
diff --git a/general/datasets/Ma_m2_0806_p/notes.rtf b/general/datasets/Ma_m2_0806_p/notes.rtf
new file mode 100644
index 0000000..d41fda1
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_p/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by Kremena Star on July 22 ,2006. Updated by KS on July 25, 2006.
+
diff --git a/general/datasets/Ma_m2_0806_p/platform.rtf b/general/datasets/Ma_m2_0806_p/platform.rtf
new file mode 100644
index 0000000..cb0e8d5
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_p/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
+
diff --git a/general/datasets/Ma_m2_0806_p/processing.rtf b/general/datasets/Ma_m2_0806_p/processing.rtf
new file mode 100644
index 0000000..b313d60
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_p/processing.rtf
@@ -0,0 +1,15 @@
+
+Probe set data from the CHP file: The expression values were generated using RMA. The same simple steps described above were also applied to these values.
+
+
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
+
+
+
+All data links (right-most column above) will be made active as sooon as the global analysis of these data by the Consoritum has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of the PDNN probe set data. Contact RW Williams regarding data access probelms.
+
diff --git a/general/datasets/Ma_m2_0806_p/summary.rtf b/general/datasets/Ma_m2_0806_p/summary.rtf
new file mode 100644
index 0000000..9055ba0
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_p/summary.rtf
@@ -0,0 +1 @@
+The July 2006 Kidney QTL Consortium data set provides estimates of mRNA expression in the adult kidney of 70 genetically diverse strains of mice including 54 BXD recombinant inbred strains, a set of 15 inbred strains, and 1 F1 hybrid; D2B6F1. Kidney samples were processed using a total of 153 Affymetrix Mouse Expression 430 2.0 microarrays (M430v2.0). This particular data set was processed using the RMA protocol. CAUTION: This dataset is not sex-balanced.
diff --git a/general/datasets/Ma_m2_0806_p/tissue.rtf b/general/datasets/Ma_m2_0806_p/tissue.rtf
new file mode 100644
index 0000000..5bc52e9
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_p/tissue.rtf
@@ -0,0 +1,3 @@
+
+BXD animals were obtained from UTHSC, and the Jackson Laboratory (Table 1). Animals were housed at UTHSC, at Harvard/BIDMC (Glenn Rosen), at the University of Memphis (Douglas Matthews), or the Jackson Laboratory before sacrifice (see Table 1). Mice were killed by cervical dislocation and kidneys were removed and placed in RNAlater prior to dissection. Kidneys were dissected whole and cleaned from the adrenal glands by Hong Tao Zhang in Dr. Lu’s lab. Kidneys from two to six animals per strain were pooled and shipped to Kremena Star at Mount Sinai School of Medicine (MSSM). Animals used in this study were between 50 and 99 days of age (average of 62 days; see Table 1).
+
diff --git a/general/datasets/Ma_m2_0806_r/acknowledgment.rtf b/general/datasets/Ma_m2_0806_r/acknowledgment.rtf
new file mode 100644
index 0000000..fea38e8
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_r/acknowledgment.rtf
@@ -0,0 +1,24 @@
+
+Data were generated with funds provided by a variety of public and private source to members of the Kidney Consortium. Members of the Kidney Consortium thank the following sources for financial support of this effort:
+
+
+ - Erwin Bottinger, M.D.
+ Grant Support: R01 DK60043-04
+ - Russell Chesney, M.D.
+ Grant Support: Le Bonheur Chair of Excellence in Pediatrics II
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Peter Mundel
+ Grant Support: NIH R01DK57683, NIH R01 DK 62472
+ - Paul Klotman
+ Grant Support: PO1 DK56492, PO1 DK56492.
+ - Matthew Breyer
+ Grant Support: DK-38226
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
+
diff --git a/general/datasets/Ma_m2_0806_r/cases.rtf b/general/datasets/Ma_m2_0806_r/cases.rtf
new file mode 100644
index 0000000..465b87c
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_r/cases.rtf
@@ -0,0 +1,44 @@
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 30 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred. We have also included 24 BXD lines generated by Lu and Peirce. All of these strains have been genotyped at 13,377 SNPs.
+
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 15 inbred strains and a pair of F1 hybrids; D2B6F1. These strains were selected for the following reasons: This panel will be a powerful tool in systems genetic analysis of a wide variety of traits, and will provide additional power in fine mapping modulators through an association analysis of sequence variants.
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+
+ - BTBR T+tf/J
+ Multiple recessive stock; Homozygotes show repeated waves of hair loss and regrowth, which begin in the nose and pass posteriorly along the body.
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - D2B6F1
+ F1 hybrid generated by crossing C57BL/6J with DBA/2J
+
+
+These inbred strains can be ordered from The Jackson Laboratory. BXD43 through BXD100 are available from Lu Lu and colleagues at UTHSC.P>
+
+
diff --git a/general/datasets/Ma_m2_0806_r/experiment-design.rtf b/general/datasets/Ma_m2_0806_r/experiment-design.rtf
new file mode 100644
index 0000000..464e50d
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_r/experiment-design.rtf
@@ -0,0 +1,1864 @@
+
+Sample Processing: : Samples were processed at the Mount Sinai School of Medicine in the laboratory of Dr. Erwin Bottinger. All processing steps were performed Kremena Star. Total RNA was extracted with TRIZOL, followed by Rneasy Mini Kit purification (QUAGEN) by Kremena Star at MSSM. RNA purity was evaluated using the 260/280 nm (protein contamination) and the 260/230 nm (TRIZOL contamination) absorbance ratios, and values had to be greater than 1.9 and 0.8 respectively. Most of the samples 260/280 nm values fell between 1.9 and 2.1 and the majority of the 260/230 nm measurements were in the range 1.8 to 2.3. RNA integrity was assessed with the Agilent Bioanalyzer 2100. We set a quality threshold at 28s/18s rRNA greater than 0.9 or RNA integrity number (RIN) of greater than 6.9. When the two metrics were in disagreement we gave priority on the RIN value as recommended by the Agilent Bioanalyzer 2100 technical support representative. Synthesis of cDNA template from total RNA was performed using the one-cyclecDNA synthesis kit from Affymetrix (Affymetrix, P/N 900431). The Affymetrix IVT-labeling kit ((Affymetrix, P/N 900449)) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 1.9 to 2.1). The cRNA is then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup (Affymetrix, P/N 900371). Fragmented cRNA samples were accessed with Agilent Bioanalyzer 2100 (cRNA frgments between 25 and 200 nucleotides are required for optimal hybridization and immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each isogenic group. Initially all strains were represented by male and female samples, however, not all data sets passed the quality control steps. Forty-two (thirty-one BXD, D2B6F1 and ten inbred strains) are represented by male and female samples.
+
+Experimental Design and Batch Structure: The data set consists of arrays processed in twenty-three groups over a six month period (March 2006 to July 2006). Each group consists of 4 to 12 arrays. All arrays were processed using the Affymetrix Eukaryotic Sample and Array Processing protocol (701024 Rev. 3), by a single operator, Kremena Star. All samples in a group were labeled on the same. The hybridization station accommodates up to 4 samples, and since most of the groups had 12 samples, processed in 3 batches on the same day. Samples were washed in groups of four and kept at 4° C until all 12 (or 4-12) arrays were ready to scan. Samples were scanned in sets of four.
+
+
+This table lists all arrays ordered by strain and includes Microarray ID, number of mice per pool, Microarray date, GAPDH 3`/5`Signal Ratio, Percent of transcripts present on the microarray chip, Strain, Generation, Sex, Age and Source of mice.
+
+
+
+
+
+ | Microarray_ID |
+ # mice |
+ Microarray Date |
+ GAPDH (3`/5`) |
+ % present |
+ strains |
+ generation |
+ sex |
+ age |
+ Mice Source |
+
+
+ | GKHI-KS-050603.07-051706 |
+ 3 |
+ 05/14/02 |
+ 0.73 |
+ 37.6 |
+ C57BL/6J |
+ |
+ M |
+ 56 |
+ UTM RW |
+
+
+ | GKHI-KS-070803.01-051706 |
+ 3 |
+ 05/14/02 |
+ 0.75 |
+ 41.6 |
+ C57BL/6J |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI-KS-DBA-Male-070706 |
+ 2 |
+ 07/06/02 |
+ 0.71 |
+ 37.3 |
+ DBA/2J |
+ |
+ M |
+ 56 |
+ JAX |
+
+
+ | GKHI_KS_121404.75-042106 |
+ 4 |
+ 04/18/02 |
+ |
+ |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_121404.75-033006 |
+ 4 |
+ 03/19/02 |
+ 0.73 |
+ 48.5 |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_121404.78-042006 |
+ 4 |
+ 04/17/02 |
+ 0.83 |
+ 40.6 |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_070804.39-042006 |
+ 4 |
+ 04/17/02 |
+ 0.82 |
+ 39.0 |
+ D2B6F1 |
+ |
+ M |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_030904.01-042006 |
+ 4 |
+ 04/17/02 |
+ 0.82 |
+ 35.9 |
+ D2B6F1 |
+ |
+ M |
+ 57 |
+ UTM RW |
+
+
+ | GKHI-KS-121404.73-070706 |
+ 2 |
+ 07/06/02 |
+ 0.76 |
+ 36.3 |
+ D2B6F1 |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI-KS-010705.38-051206 |
+ 5 |
+ 05/09/02 |
+ 0.81 |
+ 39.9 |
+ BXD1 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-060905.19 |
+ 5 |
+ 06/05/02 |
+ 0.75 |
+ 42.3 |
+ BXD1 |
+ |
+ M |
+ 68 |
+ UTM RW |
+
+
+ | GKHI-KS-051206.13-070706 |
+ 3 |
+ 07/06/02 |
+ 0.71 |
+ 36.3 |
+ BXD1 |
+ |
+ F |
+ 57 |
+ UTM RW |
+
+
+ | GKHI-KS-021304.10-051206 |
+ 4 |
+ 05/09/02 |
+ 0.81 |
+ 39.1 |
+ BXD2 |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-040303-04-050406 |
+ 3 |
+ 05/01/02 |
+ 0.80 |
+ 37.6 |
+ BXD5 |
+ |
+ F |
+ 56 |
+ UMemphis |
+
+
+ | GKHI-KS-010705-53-050306 |
+ 5 |
+ 05/01/02 |
+ 0.76 |
+ 37.1 |
+ BXD5 |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031103.01-062206 |
+ 3 |
+ 06/21/02 |
+ 0.75 |
+ 37.1 |
+ BXD5 |
+ |
+ M |
+ 71 |
+ UMemphis |
+
+
+ | GKHI-KS-040505-51-050306 |
+ 5 |
+ 05/01/02 |
+ 0.71 |
+ 35.5 |
+ BXD6 |
+ |
+ M |
+ 58 |
+ UTM RW |
+
+
+ | GKHI-KS-092705-29--050406 |
+ 5 |
+ 05/02/02 |
+ 0.75 |
+ 36.1 |
+ BXD6 |
+ 160 |
+ F |
+ 64 |
+ UTM RW |
+
+
+ | GKHI_KS_092404.01-042106 |
+ 4 |
+ 04/18/02 |
+ 0.71 |
+ 36.3 |
+ BXD8 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-051205-25-042706 |
+ 5 |
+ 04/23/02 |
+ 0.92 |
+ 37.9 |
+ BXD8 |
+ |
+ F |
+ 77 |
+ UTM RW |
+
+
+ | KS-021605-17-042606 |
+ 5 |
+ 04/22/02 |
+ 0.85 |
+ 40.8 |
+ BXD9 |
+ |
+ F |
+ 67 |
+ UTM RW |
+
+
+ | KS-032905-32-042606 |
+ 5 |
+ 04/22/02 |
+ 0.91 |
+ 36.8 |
+ BXD9 |
+ |
+ F |
+ 60 |
+ UTM RW |
+
+
+ | GKHI-KS-062006.08-070706 |
+ 3 |
+ 07/06/02 |
+ 0.74 |
+ 36.3 |
+ BXD9 |
+ |
+ M |
+ 78 |
+ UTM RW |
+
+
+ | GKHI-KS-031505.22-051206 |
+ 5 |
+ 05/09/02 |
+ 0.74 |
+ 39.5 |
+ BXD11 |
+ |
+ F |
+ 65 |
+ UTM RW |
+
+
+ | GKHI-KS-031605.01 |
+ 5 |
+ 06/05/02 |
+ 0.74 |
+ 43.4 |
+ BXD11 |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI_KS_102104.40-042106 |
+ 4 |
+ 04/18/02 |
+ 0.72 |
+ 38.5 |
+ BXD12 |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-112002.07-051106 |
+ 2 |
+ 05/08/02 |
+ 0.77 |
+ 42.0 |
+ BXD12 |
+ |
+ F |
+ 64 |
+ UMemphis |
+
+
+ | GKHI-KS-120904.33-051206 |
+ 4 |
+ 05/09/02 |
+ 0.71 |
+ 38.4 |
+ BXD13 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-042304.01 |
+ 4 |
+ 06/05/02 |
+ 0.71 |
+ 44.1 |
+ BXD13 |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020905.34-051106 |
+ 5 |
+ 05/08/02 |
+ 0.75 |
+ 40.7 |
+ BXD14 |
+ |
+ F |
+ 68 |
+ UTM RW |
+
+
+ | GKHI-KS-022405.46-051106 |
+ 5 |
+ 05/08/02 |
+ 0.71 |
+ 40.2 |
+ BXD14 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-091704.09-062206 |
+ 4 |
+ 06/21/02 |
+ 0.73 |
+ 39.0 |
+ BXD14 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-013004.45-062206 |
+ 4 |
+ 06/21/02 |
+ 0.76 |
+ 38.5 |
+ BXD15 |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-022405.43-051106 |
+ 5 |
+ 05/08/02 |
+ 0.73 |
+ 40.5 |
+ BXD15 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-041604.10-051106 |
+ 4 |
+ 05/08/02 |
+ 0.73 |
+ 42.6 |
+ BXD15 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031805.01-051106 |
+ 5 |
+ 05/08/02 |
+ 0.79 |
+ 42.4 |
+ BXD16 |
+ |
+ F |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031805.04-051106 |
+ 5 |
+ 05/08/02 |
+ 0.77 |
+ 39.9 |
+ BXD16 |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-040805.10-051006 |
+ 5 |
+ 05/05/02 |
+ 0.93 |
+ 38.7 |
+ BXD18 |
+ |
+ F |
+ 59 |
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+
+ | GKHI-KS-052804.09-051106 |
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+
+ | GKHI-KS-010705.47-051106 |
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+
+ | GKHI-KS-010705.44-070706 |
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+
+ | GKHI-KS-062905.07-051106 |
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+
+ | GKHI-KS-072104.58-051106 |
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+
+ | GKHI-KS-050405.21-051206 |
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+
+ | GKHI-KS-040705.24 |
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+
+ | GKHI-KS-110405.01-051006 |
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+
+ | GKHI-KS-110405.04-051006 |
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+
+ | GKHI-KS-040805.01-051206 |
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+
+ | GKHI-KS-040805.04-051006 |
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+
+ | GKHI_KS_091704.13-042106 |
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+
+ | GKHI-KS-040303-20-050206 |
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+
+ | GKHI-KS-021805.20-051006 |
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+
+ | GKHI-KS-090705.05-062206 |
+ 5 |
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+
+ | GKHI-KS-090705.03-051006 |
+ 5 |
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+
+ | GKHI-KS-022105.42-051006 |
+ 5 |
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+
+ | GKHI-KS-032205.31-051006 |
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+
+ | GKHI-KS-060706.10-070706 |
+ 3 |
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+
+ | GKHI-KS-012805-41-050506 |
+ 5 |
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+
+ | GKHI-KS-012805-44-050506 |
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+
+ | GKHI-KS-012805-38-050506 |
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+
+ | GKHI-KS-012805-35-050506 |
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+
+ | GKHI-KS-012805-32-050506 |
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+
+ | GKHI-KS-100604-07-050506 |
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+
+ | GKHI-KS-021605.26-051706 |
+ 5 |
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+ F |
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+
+ | GKHI-KS-112002.01-051206 |
+ 2 |
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+
+ | GKHI-KS-072605-01-050506 |
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+
+ | GKHI-KS-091405-23-050506 |
+ 5 |
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+
+ | GKHI-KS-111104-18-050506 |
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+
+ | GKHI-KS-031804-07-050506 |
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+
+ | GKHI-KS-092005.16-051206 |
+ 5 |
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+
+ | GKHI-KS-031403.01-060806 |
+ 1 |
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+
+ | GKHI-KS-090104.21-051106 |
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+
+ | GKHI-KS-040204.30 |
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+
+ | GKHI-KS-051805-16-050506 |
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+
+ | GKHI-KS-111902-04-050506 |
+ 2 |
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+
+ | GKHI-KS-050604-01-050406 |
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+
+ | GKHI-KS-080905-43-050406 |
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+
+ | GKHI-KS-031004-01-050406 |
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+
+ | GKHI-KS-020504-01-050406 |
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+
+ | GKHI-KS-071504-01-050406 |
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+
+ | GKHI-KS-081104-05-050406 |
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+
+ | GKHI-KS-031204-01-050406 |
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+
+ | GKHI-KS-021104.06-051706 |
+ 4 |
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+
+ | GKHI-KS-033005-21-050306 |
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+
+ | GKHI-KS-090204-01-050306 |
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+
+ | GKHI_KS-010704.01-040606 |
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+
+ | GKHI_KS_013004.38-042006 |
+ 4 |
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+
+ | GKHI-KS-030905-28-050206 |
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+
+ | GKHI-KS-050305-18-050206 |
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+
+ | GKHI_KS-121803.01-040706 |
+ 3 |
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+
+ | GKHI_KS_021204.01-042006 |
+ 4 |
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+
+ | GKHI-KS-020905-25-050206 |
+ 5 |
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+
+ | GKHI-KS-040705.49-060806 |
+ 2 |
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+
+ | GKHI-KS-040406.12-060806 |
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+
+ | GKHI-KS-052405-36-050406 |
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+
+ | GKHI-KS-041205-01-050206 |
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+
+ | GKHI-KS-062305-01-050206 |
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+
+ | GKHI-KS-062305-09-050206 |
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+
+ | GKHI_KS_110105.30-042006 |
+ 5 |
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+
+
+ | GKHI-KS-061504.64-062206 |
+ 4 |
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+
+ | GKHI_KS-050404.04-040606 |
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+
+ | GKHI-KS-042705-01-042706 |
+ 5 |
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+
+ | GKHI-KS-051705-59-042706 |
+ 5 |
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+
+
+ | GKHI-KS-030805-40-042706 |
+ 5 |
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+
+
+ | GKHI-KS-041905.172-062206 |
+ 5 |
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+
+
+ | GKHI-KS-072605-03-042706 |
+ 5 |
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+
+
+ | GKHI-KS-041205-04-050406 |
+ 5 |
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+
+
+ | GKHI-KS-041205.07 |
+ 5 |
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+
+ | GKHI-KS-101805-35-050406 |
+ 5 |
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+
+
+ | GKHI-KS-070605.43 |
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+
+
+ | GKHI-KS-071205-31-042706 |
+ 5 |
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+
+
+ | GKHI-KS-071205-2-042706 |
+ 5 |
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+
+
+ | KS-011305-11-042606 |
+ 5 |
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+
+
+ | KS-110805-27-042606 |
+ 5 |
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+
+
+ | KS-080404-28-042606 |
+ 4 |
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+
+
+ | KS-080504-04-042606 |
+ 4 |
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+
+
+ | KS-051705-57-042606 |
+ 5 |
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+
+
+ | KS-032905-46-042606 |
+ 5 |
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+
+
+ | GKHI-KS-080905-49-042706 |
+ 5 |
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+
+
+ | GKHI-KS-101105.26 |
+ 5 |
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+ UTM RW |
+
+
+ | GKHI_KS-062304.02-040606 |
+ 4 |
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+ UTM RW |
+
+
+ | GKHI_KS_071404.01-042006 |
+ 4 |
+ 04/17/02 |
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+ UTM RW |
+
+
+ | GKHI_KS_031005.17-042006 |
+ 5 |
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+ UTM RW |
+
+
+ | GKHI-KS-111505.12 |
+ 5 |
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+ UTM RW |
+
+
+ | GKHI-KS-012406.21-060806 |
+ 3 |
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+ |
+ F |
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+
+
+ | GKHI-KS-012406.24-060806 |
+ 3 |
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+ |
+ F |
+ 60 |
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+
+
+ | GKHI-KS-030206.13-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-030206.16-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-011906.31-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-011906.34-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-060806.04-070706 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-071505.08-060806 |
+ 3 |
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+ |
+ F |
+ 51 |
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+
+
+ | GKHI-KS-071505.11-060806 |
+ 2 |
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+ |
+ F |
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+
+
+ | GKHI-KS-030305.15-060806 |
+ 3 |
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+ |
+ F |
+ 64 |
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+
+
+ | GKHI-KS-031005.35-060906 |
+ 3 |
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+ |
+ M |
+ 64 |
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+
+
+ | GKHI-KS-022206.16-060906 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-022206.07-060906 |
+ 3 |
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+ KK/HlJ |
+ |
+ M |
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+
+
+ | GKHI-KS-031606.01-060906 |
+ 3 |
+ 06/08/02 |
+ 0.86 |
+ 35.9 |
+ MOLF/Ei |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-022206.16-060906 |
+ 3 |
+ 06/08/02 |
+ 0.87 |
+ 37.4 |
+ MOLF/Ei |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012006.25-060906 |
+ 3 |
+ 06/08/02 |
+ 0.75 |
+ 38.3 |
+ NOD/LtJ |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012006.28-061306 |
+ 3 |
+ 06/11/02 |
+ 0.82 |
+ 37.1 |
+ NOD/LtJ |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-032306.04.060906 |
+ 3 |
+ 06/08/02 |
+ 0.73 |
+ 40.2 |
+ NZB/BlNJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-032306.07-060906 |
+ 3 |
+ 06/08/02 |
+ 0.74 |
+ 39.4 |
+ NZB/BlNJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020706.04-060906 |
+ 3 |
+ 06/08/02 |
+ 0.71 |
+ 41.6 |
+ NZW/LacJ |
+ |
+ F |
+ 65 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.19-060906 |
+ 3 |
+ 06/08/02 |
+ 0.77 |
+ 36.7 |
+ NZW/LacJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012406.33-061306 |
+ 3 |
+ 06/11/02 |
+ 0.95 |
+ 35.3 |
+ PWD/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012406.30-062006 |
+ 3 |
+ 06/18/02 |
+ 0.88 |
+ 36.3 |
+ PWD/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.01-062206 |
+ 3 |
+ 06/21/02 |
+ 1.02 |
+ 35.9 |
+ PWK/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.04-062206 |
+ 3 |
+ 06/21/02 |
+ 0.96 |
+ 38.7 |
+ PWK/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.07-062206 |
+ 3 |
+ 06/21/02 |
+ 0.98 |
+ 36.6 |
+ PWK/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.10-062206 |
+ 3 |
+ 06/21/02 |
+ 0.87 |
+ 35.2 |
+ PWK/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-052705.01-061306 |
+ 2 |
+ 06/11/02 |
+ 0.72 |
+ 38.3 |
+ WSB/EiJ |
+ |
+ F |
+ 52 |
+ UTM RW |
+
+
+ | GKHI-KS-051005.07-061306 |
+ 3 |
+ 06/11/02 |
+ 0.77 |
+ 38.0 |
+ WSB/EiJ |
+ |
+ M |
+ 58 |
+ JAX |
+
+
+
+
diff --git a/general/datasets/Ma_m2_0806_r/notes.rtf b/general/datasets/Ma_m2_0806_r/notes.rtf
new file mode 100644
index 0000000..d41fda1
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by Kremena Star on July 22 ,2006. Updated by KS on July 25, 2006.
+
diff --git a/general/datasets/Ma_m2_0806_r/platform.rtf b/general/datasets/Ma_m2_0806_r/platform.rtf
new file mode 100644
index 0000000..cb0e8d5
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
+
diff --git a/general/datasets/Ma_m2_0806_r/processing.rtf b/general/datasets/Ma_m2_0806_r/processing.rtf
new file mode 100644
index 0000000..b313d60
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_r/processing.rtf
@@ -0,0 +1,15 @@
+
+Probe set data from the CHP file: The expression values were generated using RMA. The same simple steps described above were also applied to these values.
+
+
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
+
+
+
+All data links (right-most column above) will be made active as sooon as the global analysis of these data by the Consoritum has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of the PDNN probe set data. Contact RW Williams regarding data access probelms.
+
diff --git a/general/datasets/Ma_m2_0806_r/summary.rtf b/general/datasets/Ma_m2_0806_r/summary.rtf
new file mode 100644
index 0000000..9055ba0
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_r/summary.rtf
@@ -0,0 +1 @@
+The July 2006 Kidney QTL Consortium data set provides estimates of mRNA expression in the adult kidney of 70 genetically diverse strains of mice including 54 BXD recombinant inbred strains, a set of 15 inbred strains, and 1 F1 hybrid; D2B6F1. Kidney samples were processed using a total of 153 Affymetrix Mouse Expression 430 2.0 microarrays (M430v2.0). This particular data set was processed using the RMA protocol. CAUTION: This dataset is not sex-balanced.
diff --git a/general/datasets/Ma_m2_0806_r/tissue.rtf b/general/datasets/Ma_m2_0806_r/tissue.rtf
new file mode 100644
index 0000000..5bc52e9
--- /dev/null
+++ b/general/datasets/Ma_m2_0806_r/tissue.rtf
@@ -0,0 +1,3 @@
+
+BXD animals were obtained from UTHSC, and the Jackson Laboratory (Table 1). Animals were housed at UTHSC, at Harvard/BIDMC (Glenn Rosen), at the University of Memphis (Douglas Matthews), or the Jackson Laboratory before sacrifice (see Table 1). Mice were killed by cervical dislocation and kidneys were removed and placed in RNAlater prior to dissection. Kidneys were dissected whole and cleaned from the adrenal glands by Hong Tao Zhang in Dr. Lu’s lab. Kidneys from two to six animals per strain were pooled and shipped to Kremena Star at Mount Sinai School of Medicine (MSSM). Animals used in this study were between 50 and 99 days of age (average of 62 days; see Table 1).
+
diff --git a/general/datasets/Ma_m2f_0706_r/acknowledgment.rtf b/general/datasets/Ma_m2f_0706_r/acknowledgment.rtf
new file mode 100644
index 0000000..fea38e8
--- /dev/null
+++ b/general/datasets/Ma_m2f_0706_r/acknowledgment.rtf
@@ -0,0 +1,24 @@
+
+Data were generated with funds provided by a variety of public and private source to members of the Kidney Consortium. Members of the Kidney Consortium thank the following sources for financial support of this effort:
+
+
+ - Erwin Bottinger, M.D.
+ Grant Support: R01 DK60043-04
+ - Russell Chesney, M.D.
+ Grant Support: Le Bonheur Chair of Excellence in Pediatrics II
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Peter Mundel
+ Grant Support: NIH R01DK57683, NIH R01 DK 62472
+ - Paul Klotman
+ Grant Support: PO1 DK56492, PO1 DK56492.
+ - Matthew Breyer
+ Grant Support: DK-38226
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
+
diff --git a/general/datasets/Ma_m2f_0706_r/cases.rtf b/general/datasets/Ma_m2f_0706_r/cases.rtf
new file mode 100644
index 0000000..465b87c
--- /dev/null
+++ b/general/datasets/Ma_m2f_0706_r/cases.rtf
@@ -0,0 +1,44 @@
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 30 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred. We have also included 24 BXD lines generated by Lu and Peirce. All of these strains have been genotyped at 13,377 SNPs.
+
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 15 inbred strains and a pair of F1 hybrids; D2B6F1. These strains were selected for the following reasons: This panel will be a powerful tool in systems genetic analysis of a wide variety of traits, and will provide additional power in fine mapping modulators through an association analysis of sequence variants.
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+
+ - BTBR T+tf/J
+ Multiple recessive stock; Homozygotes show repeated waves of hair loss and regrowth, which begin in the nose and pass posteriorly along the body.
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - D2B6F1
+ F1 hybrid generated by crossing C57BL/6J with DBA/2J
+
+
+These inbred strains can be ordered from The Jackson Laboratory. BXD43 through BXD100 are available from Lu Lu and colleagues at UTHSC.P>
+
+
diff --git a/general/datasets/Ma_m2f_0706_r/experiment-design.rtf b/general/datasets/Ma_m2f_0706_r/experiment-design.rtf
new file mode 100644
index 0000000..464e50d
--- /dev/null
+++ b/general/datasets/Ma_m2f_0706_r/experiment-design.rtf
@@ -0,0 +1,1864 @@
+
+Sample Processing: : Samples were processed at the Mount Sinai School of Medicine in the laboratory of Dr. Erwin Bottinger. All processing steps were performed Kremena Star. Total RNA was extracted with TRIZOL, followed by Rneasy Mini Kit purification (QUAGEN) by Kremena Star at MSSM. RNA purity was evaluated using the 260/280 nm (protein contamination) and the 260/230 nm (TRIZOL contamination) absorbance ratios, and values had to be greater than 1.9 and 0.8 respectively. Most of the samples 260/280 nm values fell between 1.9 and 2.1 and the majority of the 260/230 nm measurements were in the range 1.8 to 2.3. RNA integrity was assessed with the Agilent Bioanalyzer 2100. We set a quality threshold at 28s/18s rRNA greater than 0.9 or RNA integrity number (RIN) of greater than 6.9. When the two metrics were in disagreement we gave priority on the RIN value as recommended by the Agilent Bioanalyzer 2100 technical support representative. Synthesis of cDNA template from total RNA was performed using the one-cyclecDNA synthesis kit from Affymetrix (Affymetrix, P/N 900431). The Affymetrix IVT-labeling kit ((Affymetrix, P/N 900449)) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 1.9 to 2.1). The cRNA is then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup (Affymetrix, P/N 900371). Fragmented cRNA samples were accessed with Agilent Bioanalyzer 2100 (cRNA frgments between 25 and 200 nucleotides are required for optimal hybridization and immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each isogenic group. Initially all strains were represented by male and female samples, however, not all data sets passed the quality control steps. Forty-two (thirty-one BXD, D2B6F1 and ten inbred strains) are represented by male and female samples.
+
+Experimental Design and Batch Structure: The data set consists of arrays processed in twenty-three groups over a six month period (March 2006 to July 2006). Each group consists of 4 to 12 arrays. All arrays were processed using the Affymetrix Eukaryotic Sample and Array Processing protocol (701024 Rev. 3), by a single operator, Kremena Star. All samples in a group were labeled on the same. The hybridization station accommodates up to 4 samples, and since most of the groups had 12 samples, processed in 3 batches on the same day. Samples were washed in groups of four and kept at 4° C until all 12 (or 4-12) arrays were ready to scan. Samples were scanned in sets of four.
+
+
+This table lists all arrays ordered by strain and includes Microarray ID, number of mice per pool, Microarray date, GAPDH 3`/5`Signal Ratio, Percent of transcripts present on the microarray chip, Strain, Generation, Sex, Age and Source of mice.
+
+
+
+
+
+ | Microarray_ID |
+ # mice |
+ Microarray Date |
+ GAPDH (3`/5`) |
+ % present |
+ strains |
+ generation |
+ sex |
+ age |
+ Mice Source |
+
+
+ | GKHI-KS-050603.07-051706 |
+ 3 |
+ 05/14/02 |
+ 0.73 |
+ 37.6 |
+ C57BL/6J |
+ |
+ M |
+ 56 |
+ UTM RW |
+
+
+ | GKHI-KS-070803.01-051706 |
+ 3 |
+ 05/14/02 |
+ 0.75 |
+ 41.6 |
+ C57BL/6J |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI-KS-DBA-Male-070706 |
+ 2 |
+ 07/06/02 |
+ 0.71 |
+ 37.3 |
+ DBA/2J |
+ |
+ M |
+ 56 |
+ JAX |
+
+
+ | GKHI_KS_121404.75-042106 |
+ 4 |
+ 04/18/02 |
+ |
+ |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_121404.75-033006 |
+ 4 |
+ 03/19/02 |
+ 0.73 |
+ 48.5 |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_121404.78-042006 |
+ 4 |
+ 04/17/02 |
+ 0.83 |
+ 40.6 |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_070804.39-042006 |
+ 4 |
+ 04/17/02 |
+ 0.82 |
+ 39.0 |
+ D2B6F1 |
+ |
+ M |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_030904.01-042006 |
+ 4 |
+ 04/17/02 |
+ 0.82 |
+ 35.9 |
+ D2B6F1 |
+ |
+ M |
+ 57 |
+ UTM RW |
+
+
+ | GKHI-KS-121404.73-070706 |
+ 2 |
+ 07/06/02 |
+ 0.76 |
+ 36.3 |
+ D2B6F1 |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI-KS-010705.38-051206 |
+ 5 |
+ 05/09/02 |
+ 0.81 |
+ 39.9 |
+ BXD1 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-060905.19 |
+ 5 |
+ 06/05/02 |
+ 0.75 |
+ 42.3 |
+ BXD1 |
+ |
+ M |
+ 68 |
+ UTM RW |
+
+
+ | GKHI-KS-051206.13-070706 |
+ 3 |
+ 07/06/02 |
+ 0.71 |
+ 36.3 |
+ BXD1 |
+ |
+ F |
+ 57 |
+ UTM RW |
+
+
+ | GKHI-KS-021304.10-051206 |
+ 4 |
+ 05/09/02 |
+ 0.81 |
+ 39.1 |
+ BXD2 |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-040303-04-050406 |
+ 3 |
+ 05/01/02 |
+ 0.80 |
+ 37.6 |
+ BXD5 |
+ |
+ F |
+ 56 |
+ UMemphis |
+
+
+ | GKHI-KS-010705-53-050306 |
+ 5 |
+ 05/01/02 |
+ 0.76 |
+ 37.1 |
+ BXD5 |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031103.01-062206 |
+ 3 |
+ 06/21/02 |
+ 0.75 |
+ 37.1 |
+ BXD5 |
+ |
+ M |
+ 71 |
+ UMemphis |
+
+
+ | GKHI-KS-040505-51-050306 |
+ 5 |
+ 05/01/02 |
+ 0.71 |
+ 35.5 |
+ BXD6 |
+ |
+ M |
+ 58 |
+ UTM RW |
+
+
+ | GKHI-KS-092705-29--050406 |
+ 5 |
+ 05/02/02 |
+ 0.75 |
+ 36.1 |
+ BXD6 |
+ 160 |
+ F |
+ 64 |
+ UTM RW |
+
+
+ | GKHI_KS_092404.01-042106 |
+ 4 |
+ 04/18/02 |
+ 0.71 |
+ 36.3 |
+ BXD8 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-051205-25-042706 |
+ 5 |
+ 04/23/02 |
+ 0.92 |
+ 37.9 |
+ BXD8 |
+ |
+ F |
+ 77 |
+ UTM RW |
+
+
+ | KS-021605-17-042606 |
+ 5 |
+ 04/22/02 |
+ 0.85 |
+ 40.8 |
+ BXD9 |
+ |
+ F |
+ 67 |
+ UTM RW |
+
+
+ | KS-032905-32-042606 |
+ 5 |
+ 04/22/02 |
+ 0.91 |
+ 36.8 |
+ BXD9 |
+ |
+ F |
+ 60 |
+ UTM RW |
+
+
+ | GKHI-KS-062006.08-070706 |
+ 3 |
+ 07/06/02 |
+ 0.74 |
+ 36.3 |
+ BXD9 |
+ |
+ M |
+ 78 |
+ UTM RW |
+
+
+ | GKHI-KS-031505.22-051206 |
+ 5 |
+ 05/09/02 |
+ 0.74 |
+ 39.5 |
+ BXD11 |
+ |
+ F |
+ 65 |
+ UTM RW |
+
+
+ | GKHI-KS-031605.01 |
+ 5 |
+ 06/05/02 |
+ 0.74 |
+ 43.4 |
+ BXD11 |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI_KS_102104.40-042106 |
+ 4 |
+ 04/18/02 |
+ 0.72 |
+ 38.5 |
+ BXD12 |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-112002.07-051106 |
+ 2 |
+ 05/08/02 |
+ 0.77 |
+ 42.0 |
+ BXD12 |
+ |
+ F |
+ 64 |
+ UMemphis |
+
+
+ | GKHI-KS-120904.33-051206 |
+ 4 |
+ 05/09/02 |
+ 0.71 |
+ 38.4 |
+ BXD13 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-042304.01 |
+ 4 |
+ 06/05/02 |
+ 0.71 |
+ 44.1 |
+ BXD13 |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020905.34-051106 |
+ 5 |
+ 05/08/02 |
+ 0.75 |
+ 40.7 |
+ BXD14 |
+ |
+ F |
+ 68 |
+ UTM RW |
+
+
+ | GKHI-KS-022405.46-051106 |
+ 5 |
+ 05/08/02 |
+ 0.71 |
+ 40.2 |
+ BXD14 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-091704.09-062206 |
+ 4 |
+ 06/21/02 |
+ 0.73 |
+ 39.0 |
+ BXD14 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-013004.45-062206 |
+ 4 |
+ 06/21/02 |
+ 0.76 |
+ 38.5 |
+ BXD15 |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-022405.43-051106 |
+ 5 |
+ 05/08/02 |
+ 0.73 |
+ 40.5 |
+ BXD15 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-041604.10-051106 |
+ 4 |
+ 05/08/02 |
+ 0.73 |
+ 42.6 |
+ BXD15 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031805.01-051106 |
+ 5 |
+ 05/08/02 |
+ 0.79 |
+ 42.4 |
+ BXD16 |
+ |
+ F |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031805.04-051106 |
+ 5 |
+ 05/08/02 |
+ 0.77 |
+ 39.9 |
+ BXD16 |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-040805.10-051006 |
+ 5 |
+ 05/05/02 |
+ 0.93 |
+ 38.7 |
+ BXD18 |
+ |
+ F |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-052804.09-051106 |
+ 4 |
+ 05/05/02 |
+ 0.67 |
+ 37.6 |
+ BXD19 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-010705.47-051106 |
+ 5 |
+ 05/05/02 |
+ 0.73 |
+ 42.3 |
+ BXD19 |
+ |
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+
+ | GKHI-KS-010705.44-070706 |
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+
+ | GKHI-KS-062905.07-051106 |
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+
+ | GKHI-KS-072104.58-051106 |
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+
+ | GKHI-KS-050405.21-051206 |
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+
+ | GKHI-KS-040705.24 |
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+
+ | GKHI-KS-110405.01-051006 |
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+
+ | GKHI-KS-110405.04-051006 |
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+ M |
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+
+ | GKHI-KS-040805.01-051206 |
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+
+ | GKHI-KS-040805.04-051006 |
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+
+ | GKHI_KS_091704.13-042106 |
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+
+ | GKHI-KS-040303-20-050206 |
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+
+ | GKHI-KS-021805.20-051006 |
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+
+ | GKHI-KS-090705.05-062206 |
+ 5 |
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+ M |
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+
+ | GKHI-KS-090705.03-051006 |
+ 5 |
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+
+ | GKHI-KS-022105.42-051006 |
+ 5 |
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+
+ | GKHI-KS-032205.31-051006 |
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+ M |
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+
+ | GKHI-KS-060706.10-070706 |
+ 3 |
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+ F |
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+
+ | GKHI-KS-012805-41-050506 |
+ 5 |
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+
+ | GKHI-KS-012805-44-050506 |
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+
+ | GKHI-KS-012805-38-050506 |
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+
+ | GKHI-KS-012805-35-050506 |
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+
+ | GKHI-KS-012805-32-050506 |
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+
+ | GKHI-KS-100604-07-050506 |
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+
+ | GKHI-KS-021605.26-051706 |
+ 5 |
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+ F |
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+
+ | GKHI-KS-112002.01-051206 |
+ 2 |
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+
+ | GKHI-KS-072605-01-050506 |
+ 5 |
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+
+ | GKHI-KS-091405-23-050506 |
+ 5 |
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+
+ | GKHI-KS-111104-18-050506 |
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+
+ | GKHI-KS-031804-07-050506 |
+ 4 |
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+
+ | GKHI-KS-092005.16-051206 |
+ 5 |
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+
+ | GKHI-KS-031403.01-060806 |
+ 1 |
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+ M |
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+
+ | GKHI-KS-090104.21-051106 |
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+
+ | GKHI-KS-040204.30 |
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+
+ | GKHI-KS-051805-16-050506 |
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+
+ | GKHI-KS-111902-04-050506 |
+ 2 |
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+
+ | GKHI-KS-050604-01-050406 |
+ 4 |
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+
+ | GKHI-KS-080905-43-050406 |
+ 5 |
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+
+ | GKHI-KS-031004-01-050406 |
+ 4 |
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+
+ | GKHI-KS-020504-01-050406 |
+ 4 |
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+
+ | GKHI-KS-071504-01-050406 |
+ 4 |
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+
+ | GKHI-KS-081104-05-050406 |
+ 4 |
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+
+ | GKHI-KS-031204-01-050406 |
+ 4 |
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+
+ | GKHI-KS-021104.06-051706 |
+ 4 |
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+
+ | GKHI-KS-033005-21-050306 |
+ 5 |
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+
+ | GKHI-KS-090204-01-050306 |
+ 4 |
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+
+ | GKHI_KS-010704.01-040606 |
+ 4 |
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+
+ | GKHI_KS_013004.38-042006 |
+ 4 |
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+
+ | GKHI-KS-030905-28-050206 |
+ 5 |
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+
+ | GKHI-KS-050305-18-050206 |
+ 5 |
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+
+ | GKHI_KS-121803.01-040706 |
+ 3 |
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+
+
+ | GKHI_KS_021204.01-042006 |
+ 4 |
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+
+ | GKHI-KS-020905-25-050206 |
+ 5 |
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+
+ | GKHI-KS-040705.49-060806 |
+ 2 |
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+
+ | GKHI-KS-040406.12-060806 |
+ 2 |
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+
+ | GKHI-KS-052405-36-050406 |
+ 5 |
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+
+ | GKHI-KS-041205-01-050206 |
+ 5 |
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+
+ | GKHI-KS-062305-01-050206 |
+ 5 |
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+
+ | GKHI-KS-062305-09-050206 |
+ 5 |
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+
+ | GKHI_KS_110105.30-042006 |
+ 5 |
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+
+
+ | GKHI-KS-061504.64-062206 |
+ 4 |
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+
+
+ | GKHI_KS-050404.04-040606 |
+ 4 |
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+
+
+ | GKHI-KS-042705-01-042706 |
+ 5 |
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+
+
+ | GKHI-KS-051705-59-042706 |
+ 5 |
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+
+
+ | GKHI-KS-030805-40-042706 |
+ 5 |
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+
+
+ | GKHI-KS-041905.172-062206 |
+ 5 |
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+
+
+ | GKHI-KS-072605-03-042706 |
+ 5 |
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+
+
+ | GKHI-KS-041205-04-050406 |
+ 5 |
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+
+
+ | GKHI-KS-041205.07 |
+ 5 |
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+
+
+ | GKHI-KS-101805-35-050406 |
+ 5 |
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+
+
+ | GKHI-KS-070605.43 |
+ 5 |
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+
+
+ | GKHI-KS-071205-31-042706 |
+ 5 |
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+
+
+ | GKHI-KS-071205-2-042706 |
+ 5 |
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+
+
+ | KS-011305-11-042606 |
+ 5 |
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+
+
+ | KS-110805-27-042606 |
+ 5 |
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+
+
+ | KS-080404-28-042606 |
+ 4 |
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+
+
+ | KS-080504-04-042606 |
+ 4 |
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+
+
+ | KS-051705-57-042606 |
+ 5 |
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+
+
+ | KS-032905-46-042606 |
+ 5 |
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+ UTM RW |
+
+
+ | GKHI-KS-080905-49-042706 |
+ 5 |
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+ UTM RW |
+
+
+ | GKHI-KS-101105.26 |
+ 5 |
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+ UTM RW |
+
+
+ | GKHI_KS-062304.02-040606 |
+ 4 |
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+ UTM RW |
+
+
+ | GKHI_KS_071404.01-042006 |
+ 4 |
+ 04/17/02 |
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+ 21 |
+ F |
+ 62 |
+ UTM RW |
+
+
+ | GKHI_KS_031005.17-042006 |
+ 5 |
+ 04/17/02 |
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+ UTM RW |
+
+
+ | GKHI-KS-111505.12 |
+ 5 |
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+ UTM RW |
+
+
+ | GKHI-KS-012406.21-060806 |
+ 3 |
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+ |
+ F |
+ 60 |
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+
+
+ | GKHI-KS-012406.24-060806 |
+ 3 |
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+ |
+ F |
+ 60 |
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+
+
+ | GKHI-KS-030206.13-060806 |
+ 3 |
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+ |
+ F |
+ 61 |
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+
+
+ | GKHI-KS-030206.16-060806 |
+ 3 |
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+ |
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+ 61 |
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+
+
+ | GKHI-KS-011906.31-060806 |
+ 3 |
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+ |
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+ 60 |
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+
+
+ | GKHI-KS-011906.34-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-060806.04-070706 |
+ 3 |
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+ |
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+ 76 |
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+
+
+ | GKHI-KS-071505.08-060806 |
+ 3 |
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+ |
+ F |
+ 51 |
+ JAX |
+
+
+ | GKHI-KS-071505.11-060806 |
+ 2 |
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+ |
+ F |
+ 51 |
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+
+
+ | GKHI-KS-030305.15-060806 |
+ 3 |
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+ |
+ F |
+ 64 |
+ JAX |
+
+
+ | GKHI-KS-031005.35-060906 |
+ 3 |
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+ |
+ M |
+ 64 |
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+
+
+ | GKHI-KS-022206.16-060906 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-022206.07-060906 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-031606.01-060906 |
+ 3 |
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+ |
+ M |
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+
+
+ | GKHI-KS-022206.16-060906 |
+ 3 |
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+ 0.87 |
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+ MOLF/Ei |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012006.25-060906 |
+ 3 |
+ 06/08/02 |
+ 0.75 |
+ 38.3 |
+ NOD/LtJ |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012006.28-061306 |
+ 3 |
+ 06/11/02 |
+ 0.82 |
+ 37.1 |
+ NOD/LtJ |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-032306.04.060906 |
+ 3 |
+ 06/08/02 |
+ 0.73 |
+ 40.2 |
+ NZB/BlNJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-032306.07-060906 |
+ 3 |
+ 06/08/02 |
+ 0.74 |
+ 39.4 |
+ NZB/BlNJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020706.04-060906 |
+ 3 |
+ 06/08/02 |
+ 0.71 |
+ 41.6 |
+ NZW/LacJ |
+ |
+ F |
+ 65 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.19-060906 |
+ 3 |
+ 06/08/02 |
+ 0.77 |
+ 36.7 |
+ NZW/LacJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012406.33-061306 |
+ 3 |
+ 06/11/02 |
+ 0.95 |
+ 35.3 |
+ PWD/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012406.30-062006 |
+ 3 |
+ 06/18/02 |
+ 0.88 |
+ 36.3 |
+ PWD/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.01-062206 |
+ 3 |
+ 06/21/02 |
+ 1.02 |
+ 35.9 |
+ PWK/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.04-062206 |
+ 3 |
+ 06/21/02 |
+ 0.96 |
+ 38.7 |
+ PWK/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.07-062206 |
+ 3 |
+ 06/21/02 |
+ 0.98 |
+ 36.6 |
+ PWK/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.10-062206 |
+ 3 |
+ 06/21/02 |
+ 0.87 |
+ 35.2 |
+ PWK/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-052705.01-061306 |
+ 2 |
+ 06/11/02 |
+ 0.72 |
+ 38.3 |
+ WSB/EiJ |
+ |
+ F |
+ 52 |
+ UTM RW |
+
+
+ | GKHI-KS-051005.07-061306 |
+ 3 |
+ 06/11/02 |
+ 0.77 |
+ 38.0 |
+ WSB/EiJ |
+ |
+ M |
+ 58 |
+ JAX |
+
+
+
+
diff --git a/general/datasets/Ma_m2f_0706_r/notes.rtf b/general/datasets/Ma_m2f_0706_r/notes.rtf
new file mode 100644
index 0000000..d41fda1
--- /dev/null
+++ b/general/datasets/Ma_m2f_0706_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by Kremena Star on July 22 ,2006. Updated by KS on July 25, 2006.
+
diff --git a/general/datasets/Ma_m2f_0706_r/platform.rtf b/general/datasets/Ma_m2f_0706_r/platform.rtf
new file mode 100644
index 0000000..cb0e8d5
--- /dev/null
+++ b/general/datasets/Ma_m2f_0706_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
+
diff --git a/general/datasets/Ma_m2f_0706_r/processing.rtf b/general/datasets/Ma_m2f_0706_r/processing.rtf
new file mode 100644
index 0000000..b313d60
--- /dev/null
+++ b/general/datasets/Ma_m2f_0706_r/processing.rtf
@@ -0,0 +1,15 @@
+
+Probe set data from the CHP file: The expression values were generated using RMA. The same simple steps described above were also applied to these values.
+
+
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
+
+
+
+All data links (right-most column above) will be made active as sooon as the global analysis of these data by the Consoritum has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of the PDNN probe set data. Contact RW Williams regarding data access probelms.
+
diff --git a/general/datasets/Ma_m2f_0706_r/summary.rtf b/general/datasets/Ma_m2f_0706_r/summary.rtf
new file mode 100644
index 0000000..9055ba0
--- /dev/null
+++ b/general/datasets/Ma_m2f_0706_r/summary.rtf
@@ -0,0 +1 @@
+The July 2006 Kidney QTL Consortium data set provides estimates of mRNA expression in the adult kidney of 70 genetically diverse strains of mice including 54 BXD recombinant inbred strains, a set of 15 inbred strains, and 1 F1 hybrid; D2B6F1. Kidney samples were processed using a total of 153 Affymetrix Mouse Expression 430 2.0 microarrays (M430v2.0). This particular data set was processed using the RMA protocol. CAUTION: This dataset is not sex-balanced.
diff --git a/general/datasets/Ma_m2f_0706_r/tissue.rtf b/general/datasets/Ma_m2f_0706_r/tissue.rtf
new file mode 100644
index 0000000..5bc52e9
--- /dev/null
+++ b/general/datasets/Ma_m2f_0706_r/tissue.rtf
@@ -0,0 +1,3 @@
+
+BXD animals were obtained from UTHSC, and the Jackson Laboratory (Table 1). Animals were housed at UTHSC, at Harvard/BIDMC (Glenn Rosen), at the University of Memphis (Douglas Matthews), or the Jackson Laboratory before sacrifice (see Table 1). Mice were killed by cervical dislocation and kidneys were removed and placed in RNAlater prior to dissection. Kidneys were dissected whole and cleaned from the adrenal glands by Hong Tao Zhang in Dr. Lu’s lab. Kidneys from two to six animals per strain were pooled and shipped to Kremena Star at Mount Sinai School of Medicine (MSSM). Animals used in this study were between 50 and 99 days of age (average of 62 days; see Table 1).
+
diff --git a/general/datasets/Ma_m2m_0706_r/acknowledgment.rtf b/general/datasets/Ma_m2m_0706_r/acknowledgment.rtf
new file mode 100644
index 0000000..fea38e8
--- /dev/null
+++ b/general/datasets/Ma_m2m_0706_r/acknowledgment.rtf
@@ -0,0 +1,24 @@
+
+Data were generated with funds provided by a variety of public and private source to members of the Kidney Consortium. Members of the Kidney Consortium thank the following sources for financial support of this effort:
+
+
+ - Erwin Bottinger, M.D.
+ Grant Support: R01 DK60043-04
+ - Russell Chesney, M.D.
+ Grant Support: Le Bonheur Chair of Excellence in Pediatrics II
+ - Lu Lu, M.D.
+ Grant Support: NIH U01AA13499, U24AA13513
+ - Peter Mundel
+ Grant Support: NIH R01DK57683, NIH R01 DK 62472
+ - Paul Klotman
+ Grant Support: PO1 DK56492, PO1 DK56492.
+ - Matthew Breyer
+ Grant Support: DK-38226
+ - Kenneth F. Manly, Ph.D.
+ Grant Support: NIH P20MH062009 and U01CA105417
+ - Robert W. Williams, Ph.D.
+ Grant Support: NIH U01AA013499, P20MH062009, U01AA013499, U01AA013513
+
+
+
+
diff --git a/general/datasets/Ma_m2m_0706_r/cases.rtf b/general/datasets/Ma_m2m_0706_r/cases.rtf
new file mode 100644
index 0000000..465b87c
--- /dev/null
+++ b/general/datasets/Ma_m2m_0706_r/cases.rtf
@@ -0,0 +1,44 @@
+
+The BXD genetic reference panel of recombinant inbred strains consists of just over 80 strains. The BXDs in this data set include 30 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD42). All of these strains are fully inbred. We have also included 24 BXD lines generated by Lu and Peirce. All of these strains have been genotyped at 13,377 SNPs.
+
+
+Mouse Diversity Panel (MDP). We have profiled a MDP consisting 15 inbred strains and a pair of F1 hybrids; D2B6F1. These strains were selected for the following reasons: This panel will be a powerful tool in systems genetic analysis of a wide variety of traits, and will provide additional power in fine mapping modulators through an association analysis of sequence variants.
+
+
+ - genetic and phenotypic diversity, including use by the Phenome Project
+ - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
+ - their use by the Complex Trait Consortium to make the Collaborative Cross (Nairobi/Wellcome, Oak Ridge/DOE, and Perth/UWA)
+ - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
+ - availability from The Jackson Laboratory
+
+
+
+ - BTBR T+tf/J
+ Multiple recessive stock; Homozygotes show repeated waves of hair loss and regrowth, which begin in the nose and pass posteriorly along the body.
+ - C3H/HeJ
+ Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project A list
+ - C57BL/6J
+ Sequenced by NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list
+ - C57BL/6ByJ
+ Paternal substrain of B6 used to generate the CXB panel
+ - CAST/Ei
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project A list
+ - DBA/2J
+ Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project A list
+ - KK/HlJ
+ Sequenced by Perlegen/NIEHS
+ - NOD/LtJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project B list; diabetic
+ - PWD/PhJ
+ Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues
+ - PWK/PhJ
+ Collaborative Cross strain; Phenome Project D list
+ - WSB/EiJ
+ Collaborative Cross strain sequenced by NIEHS; Phenome Project C list
+ - D2B6F1
+ F1 hybrid generated by crossing C57BL/6J with DBA/2J
+
+
+These inbred strains can be ordered from The Jackson Laboratory. BXD43 through BXD100 are available from Lu Lu and colleagues at UTHSC.P>
+
+
diff --git a/general/datasets/Ma_m2m_0706_r/experiment-design.rtf b/general/datasets/Ma_m2m_0706_r/experiment-design.rtf
new file mode 100644
index 0000000..464e50d
--- /dev/null
+++ b/general/datasets/Ma_m2m_0706_r/experiment-design.rtf
@@ -0,0 +1,1864 @@
+
+Sample Processing: : Samples were processed at the Mount Sinai School of Medicine in the laboratory of Dr. Erwin Bottinger. All processing steps were performed Kremena Star. Total RNA was extracted with TRIZOL, followed by Rneasy Mini Kit purification (QUAGEN) by Kremena Star at MSSM. RNA purity was evaluated using the 260/280 nm (protein contamination) and the 260/230 nm (TRIZOL contamination) absorbance ratios, and values had to be greater than 1.9 and 0.8 respectively. Most of the samples 260/280 nm values fell between 1.9 and 2.1 and the majority of the 260/230 nm measurements were in the range 1.8 to 2.3. RNA integrity was assessed with the Agilent Bioanalyzer 2100. We set a quality threshold at 28s/18s rRNA greater than 0.9 or RNA integrity number (RIN) of greater than 6.9. When the two metrics were in disagreement we gave priority on the RIN value as recommended by the Agilent Bioanalyzer 2100 technical support representative. Synthesis of cDNA template from total RNA was performed using the one-cyclecDNA synthesis kit from Affymetrix (Affymetrix, P/N 900431). The Affymetrix IVT-labeling kit ((Affymetrix, P/N 900449)) was used to synthesize labeled cRNA. The cRNA was evaluated using both the 260/280 ratio (values of 1.9 to 2.1). The cRNA is then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup (Affymetrix, P/N 900371). Fragmented cRNA samples were accessed with Agilent Bioanalyzer 2100 (cRNA frgments between 25 and 200 nucleotides are required for optimal hybridization and immediately injected onto the array. The arrays were hybridized and washed following standard Affymetrix protocols.
+
+Replication and Sample Balance: We obtained a male sample pool and female sample pool from each isogenic group. Initially all strains were represented by male and female samples, however, not all data sets passed the quality control steps. Forty-two (thirty-one BXD, D2B6F1 and ten inbred strains) are represented by male and female samples.
+
+Experimental Design and Batch Structure: The data set consists of arrays processed in twenty-three groups over a six month period (March 2006 to July 2006). Each group consists of 4 to 12 arrays. All arrays were processed using the Affymetrix Eukaryotic Sample and Array Processing protocol (701024 Rev. 3), by a single operator, Kremena Star. All samples in a group were labeled on the same. The hybridization station accommodates up to 4 samples, and since most of the groups had 12 samples, processed in 3 batches on the same day. Samples were washed in groups of four and kept at 4° C until all 12 (or 4-12) arrays were ready to scan. Samples were scanned in sets of four.
+
+
+This table lists all arrays ordered by strain and includes Microarray ID, number of mice per pool, Microarray date, GAPDH 3`/5`Signal Ratio, Percent of transcripts present on the microarray chip, Strain, Generation, Sex, Age and Source of mice.
+
+
+
+
+
+ | Microarray_ID |
+ # mice |
+ Microarray Date |
+ GAPDH (3`/5`) |
+ % present |
+ strains |
+ generation |
+ sex |
+ age |
+ Mice Source |
+
+
+ | GKHI-KS-050603.07-051706 |
+ 3 |
+ 05/14/02 |
+ 0.73 |
+ 37.6 |
+ C57BL/6J |
+ |
+ M |
+ 56 |
+ UTM RW |
+
+
+ | GKHI-KS-070803.01-051706 |
+ 3 |
+ 05/14/02 |
+ 0.75 |
+ 41.6 |
+ C57BL/6J |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI-KS-DBA-Male-070706 |
+ 2 |
+ 07/06/02 |
+ 0.71 |
+ 37.3 |
+ DBA/2J |
+ |
+ M |
+ 56 |
+ JAX |
+
+
+ | GKHI_KS_121404.75-042106 |
+ 4 |
+ 04/18/02 |
+ |
+ |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_121404.75-033006 |
+ 4 |
+ 03/19/02 |
+ 0.73 |
+ 48.5 |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_121404.78-042006 |
+ 4 |
+ 04/17/02 |
+ 0.83 |
+ 40.6 |
+ DBA/2J |
+ |
+ F |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_070804.39-042006 |
+ 4 |
+ 04/17/02 |
+ 0.82 |
+ 39.0 |
+ D2B6F1 |
+ |
+ M |
+ 59 |
+ UTM RW |
+
+
+ | GKHI_KS_030904.01-042006 |
+ 4 |
+ 04/17/02 |
+ 0.82 |
+ 35.9 |
+ D2B6F1 |
+ |
+ M |
+ 57 |
+ UTM RW |
+
+
+ | GKHI-KS-121404.73-070706 |
+ 2 |
+ 07/06/02 |
+ 0.76 |
+ 36.3 |
+ D2B6F1 |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI-KS-010705.38-051206 |
+ 5 |
+ 05/09/02 |
+ 0.81 |
+ 39.9 |
+ BXD1 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-060905.19 |
+ 5 |
+ 06/05/02 |
+ 0.75 |
+ 42.3 |
+ BXD1 |
+ |
+ M |
+ 68 |
+ UTM RW |
+
+
+ | GKHI-KS-051206.13-070706 |
+ 3 |
+ 07/06/02 |
+ 0.71 |
+ 36.3 |
+ BXD1 |
+ |
+ F |
+ 57 |
+ UTM RW |
+
+
+ | GKHI-KS-021304.10-051206 |
+ 4 |
+ 05/09/02 |
+ 0.81 |
+ 39.1 |
+ BXD2 |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-040303-04-050406 |
+ 3 |
+ 05/01/02 |
+ 0.80 |
+ 37.6 |
+ BXD5 |
+ |
+ F |
+ 56 |
+ UMemphis |
+
+
+ | GKHI-KS-010705-53-050306 |
+ 5 |
+ 05/01/02 |
+ 0.76 |
+ 37.1 |
+ BXD5 |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031103.01-062206 |
+ 3 |
+ 06/21/02 |
+ 0.75 |
+ 37.1 |
+ BXD5 |
+ |
+ M |
+ 71 |
+ UMemphis |
+
+
+ | GKHI-KS-040505-51-050306 |
+ 5 |
+ 05/01/02 |
+ 0.71 |
+ 35.5 |
+ BXD6 |
+ |
+ M |
+ 58 |
+ UTM RW |
+
+
+ | GKHI-KS-092705-29--050406 |
+ 5 |
+ 05/02/02 |
+ 0.75 |
+ 36.1 |
+ BXD6 |
+ 160 |
+ F |
+ 64 |
+ UTM RW |
+
+
+ | GKHI_KS_092404.01-042106 |
+ 4 |
+ 04/18/02 |
+ 0.71 |
+ 36.3 |
+ BXD8 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-051205-25-042706 |
+ 5 |
+ 04/23/02 |
+ 0.92 |
+ 37.9 |
+ BXD8 |
+ |
+ F |
+ 77 |
+ UTM RW |
+
+
+ | KS-021605-17-042606 |
+ 5 |
+ 04/22/02 |
+ 0.85 |
+ 40.8 |
+ BXD9 |
+ |
+ F |
+ 67 |
+ UTM RW |
+
+
+ | KS-032905-32-042606 |
+ 5 |
+ 04/22/02 |
+ 0.91 |
+ 36.8 |
+ BXD9 |
+ |
+ F |
+ 60 |
+ UTM RW |
+
+
+ | GKHI-KS-062006.08-070706 |
+ 3 |
+ 07/06/02 |
+ 0.74 |
+ 36.3 |
+ BXD9 |
+ |
+ M |
+ 78 |
+ UTM RW |
+
+
+ | GKHI-KS-031505.22-051206 |
+ 5 |
+ 05/09/02 |
+ 0.74 |
+ 39.5 |
+ BXD11 |
+ |
+ F |
+ 65 |
+ UTM RW |
+
+
+ | GKHI-KS-031605.01 |
+ 5 |
+ 06/05/02 |
+ 0.74 |
+ 43.4 |
+ BXD11 |
+ |
+ F |
+ 69 |
+ UTM RW |
+
+
+ | GKHI_KS_102104.40-042106 |
+ 4 |
+ 04/18/02 |
+ 0.72 |
+ 38.5 |
+ BXD12 |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-112002.07-051106 |
+ 2 |
+ 05/08/02 |
+ 0.77 |
+ 42.0 |
+ BXD12 |
+ |
+ F |
+ 64 |
+ UMemphis |
+
+
+ | GKHI-KS-120904.33-051206 |
+ 4 |
+ 05/09/02 |
+ 0.71 |
+ 38.4 |
+ BXD13 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-042304.01 |
+ 4 |
+ 06/05/02 |
+ 0.71 |
+ 44.1 |
+ BXD13 |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020905.34-051106 |
+ 5 |
+ 05/08/02 |
+ 0.75 |
+ 40.7 |
+ BXD14 |
+ |
+ F |
+ 68 |
+ UTM RW |
+
+
+ | GKHI-KS-022405.46-051106 |
+ 5 |
+ 05/08/02 |
+ 0.71 |
+ 40.2 |
+ BXD14 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-091704.09-062206 |
+ 4 |
+ 06/21/02 |
+ 0.73 |
+ 39.0 |
+ BXD14 |
+ |
+ M |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-013004.45-062206 |
+ 4 |
+ 06/21/02 |
+ 0.76 |
+ 38.5 |
+ BXD15 |
+ |
+ M |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-022405.43-051106 |
+ 5 |
+ 05/08/02 |
+ 0.73 |
+ 40.5 |
+ BXD15 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-041604.10-051106 |
+ 4 |
+ 05/08/02 |
+ 0.73 |
+ 42.6 |
+ BXD15 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031805.01-051106 |
+ 5 |
+ 05/08/02 |
+ 0.79 |
+ 42.4 |
+ BXD16 |
+ |
+ F |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-031805.04-051106 |
+ 5 |
+ 05/08/02 |
+ 0.77 |
+ 39.9 |
+ BXD16 |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-040805.10-051006 |
+ 5 |
+ 05/05/02 |
+ 0.93 |
+ 38.7 |
+ BXD18 |
+ |
+ F |
+ 59 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-052804.09-051106 |
+ 4 |
+ 05/05/02 |
+ 0.67 |
+ 37.6 |
+ BXD19 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-010705.47-051106 |
+ 5 |
+ 05/05/02 |
+ 0.73 |
+ 42.3 |
+ BXD19 |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-010705.44-070706 |
+ 3 |
+ 07/06/02 |
+ 0.73 |
+ 36.1 |
+ BXD19 |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-062905.07-051106 |
+ 5 |
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+
+ | GKHI-KS-072104.58-051106 |
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+
+ | GKHI-KS-050405.21-051206 |
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+
+ | GKHI-KS-040705.24 |
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+
+ | GKHI-KS-110405.01-051006 |
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+ | GKHI-KS-110405.04-051006 |
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+
+ | GKHI-KS-040805.01-051206 |
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+
+ | GKHI-KS-040805.04-051006 |
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+
+ | GKHI_KS_091704.13-042106 |
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+
+ | GKHI-KS-040303-20-050206 |
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+
+ | GKHI-KS-021805.20-051006 |
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+
+ | GKHI-KS-090705.05-062206 |
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+
+ | GKHI-KS-090705.03-051006 |
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+
+ | GKHI-KS-022105.42-051006 |
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+
+ | GKHI-KS-032205.31-051006 |
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+
+ | GKHI-KS-060706.10-070706 |
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+
+ | GKHI-KS-012805-41-050506 |
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+
+ | GKHI-KS-012805-44-050506 |
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+
+ | GKHI-KS-012805-38-050506 |
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+
+ | GKHI-KS-012805-35-050506 |
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+
+ | GKHI-KS-012805-32-050506 |
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+
+ | GKHI-KS-100604-07-050506 |
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+
+ | GKHI-KS-021605.26-051706 |
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+
+ | GKHI-KS-112002.01-051206 |
+ 2 |
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+
+ | GKHI-KS-072605-01-050506 |
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+
+ | GKHI-KS-091405-23-050506 |
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+
+ | GKHI-KS-111104-18-050506 |
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+
+ | GKHI-KS-031804-07-050506 |
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+
+ | GKHI-KS-092005.16-051206 |
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+
+ | GKHI-KS-031403.01-060806 |
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+
+ | GKHI-KS-090104.21-051106 |
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+
+ | GKHI-KS-040204.30 |
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+
+ | GKHI-KS-051805-16-050506 |
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+
+ | GKHI-KS-111902-04-050506 |
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+
+ | GKHI-KS-050604-01-050406 |
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+
+ | GKHI-KS-080905-43-050406 |
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+
+ | GKHI-KS-031004-01-050406 |
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+
+ | GKHI-KS-020504-01-050406 |
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+
+ | GKHI-KS-071504-01-050406 |
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+
+ | GKHI-KS-081104-05-050406 |
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+
+ | GKHI-KS-031204-01-050406 |
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+
+ | GKHI-KS-021104.06-051706 |
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+
+ | GKHI-KS-033005-21-050306 |
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+
+ | GKHI-KS-090204-01-050306 |
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+
+ | GKHI_KS-010704.01-040606 |
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+
+ | GKHI_KS_013004.38-042006 |
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+
+ | GKHI-KS-030905-28-050206 |
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+
+ | GKHI-KS-050305-18-050206 |
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+
+ | GKHI_KS-121803.01-040706 |
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+
+ | GKHI_KS_021204.01-042006 |
+ 4 |
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+
+ | GKHI-KS-020905-25-050206 |
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+
+ | GKHI-KS-040705.49-060806 |
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+
+ | GKHI-KS-040406.12-060806 |
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+
+ | GKHI-KS-052405-36-050406 |
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+
+ | GKHI-KS-041205-01-050206 |
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+
+ | GKHI-KS-062305-01-050206 |
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+
+ | GKHI-KS-062305-09-050206 |
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+
+ | GKHI_KS_110105.30-042006 |
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+
+ | GKHI-KS-061504.64-062206 |
+ 4 |
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+
+ | GKHI_KS-050404.04-040606 |
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+
+ | GKHI-KS-042705-01-042706 |
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+
+ | GKHI-KS-051705-59-042706 |
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+
+ | GKHI-KS-030805-40-042706 |
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+
+ | GKHI-KS-041905.172-062206 |
+ 5 |
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+
+ | GKHI-KS-072605-03-042706 |
+ 5 |
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+
+ | GKHI-KS-041205-04-050406 |
+ 5 |
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+
+ | GKHI-KS-041205.07 |
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+
+ | GKHI-KS-101805-35-050406 |
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+
+ | GKHI-KS-070605.43 |
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+
+ | GKHI-KS-071205-31-042706 |
+ 5 |
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+
+ | GKHI-KS-071205-2-042706 |
+ 5 |
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+
+ | KS-011305-11-042606 |
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+
+
+ | KS-110805-27-042606 |
+ 5 |
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+
+
+ | KS-080404-28-042606 |
+ 4 |
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+
+
+ | KS-080504-04-042606 |
+ 4 |
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+
+
+ | KS-051705-57-042606 |
+ 5 |
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+
+
+ | KS-032905-46-042606 |
+ 5 |
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+
+
+ | GKHI-KS-080905-49-042706 |
+ 5 |
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+
+
+ | GKHI-KS-101105.26 |
+ 5 |
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+
+
+ | GKHI_KS-062304.02-040606 |
+ 4 |
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+
+
+ | GKHI_KS_071404.01-042006 |
+ 4 |
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+
+
+ | GKHI_KS_031005.17-042006 |
+ 5 |
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+
+
+ | GKHI-KS-111505.12 |
+ 5 |
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+
+
+ | GKHI-KS-012406.21-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-012406.24-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-030206.13-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-030206.16-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-011906.31-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-011906.34-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-060806.04-070706 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-071505.08-060806 |
+ 3 |
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+ |
+ F |
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+
+
+ | GKHI-KS-071505.11-060806 |
+ 2 |
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+ |
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+
+
+ | GKHI-KS-030305.15-060806 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-031005.35-060906 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-022206.16-060906 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-022206.07-060906 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-031606.01-060906 |
+ 3 |
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+ |
+ M |
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+
+
+ | GKHI-KS-022206.16-060906 |
+ 3 |
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+ |
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+
+
+ | GKHI-KS-012006.25-060906 |
+ 3 |
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+ NOD/LtJ |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012006.28-061306 |
+ 3 |
+ 06/11/02 |
+ 0.82 |
+ 37.1 |
+ NOD/LtJ |
+ |
+ F |
+ 58 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-032306.04.060906 |
+ 3 |
+ 06/08/02 |
+ 0.73 |
+ 40.2 |
+ NZB/BlNJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-032306.07-060906 |
+ 3 |
+ 06/08/02 |
+ 0.74 |
+ 39.4 |
+ NZB/BlNJ |
+ |
+ F |
+ 61 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020706.04-060906 |
+ 3 |
+ 06/08/02 |
+ 0.71 |
+ 41.6 |
+ NZW/LacJ |
+ |
+ F |
+ 65 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.19-060906 |
+ 3 |
+ 06/08/02 |
+ 0.77 |
+ 36.7 |
+ NZW/LacJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012406.33-061306 |
+ 3 |
+ 06/11/02 |
+ 0.95 |
+ 35.3 |
+ PWD/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-012406.30-062006 |
+ 3 |
+ 06/18/02 |
+ 0.88 |
+ 36.3 |
+ PWD/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.01-062206 |
+ 3 |
+ 06/21/02 |
+ 1.02 |
+ 35.9 |
+ PWK/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.04-062206 |
+ 3 |
+ 06/21/02 |
+ 0.96 |
+ 38.7 |
+ PWK/PhJ |
+ |
+ F |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.07-062206 |
+ 3 |
+ 06/21/02 |
+ 0.98 |
+ 36.6 |
+ PWK/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-020206.10-062206 |
+ 3 |
+ 06/21/02 |
+ 0.87 |
+ 35.2 |
+ PWK/PhJ |
+ |
+ M |
+ 60 |
+ Harvard/BIDMC |
+
+
+ | GKHI-KS-052705.01-061306 |
+ 2 |
+ 06/11/02 |
+ 0.72 |
+ 38.3 |
+ WSB/EiJ |
+ |
+ F |
+ 52 |
+ UTM RW |
+
+
+ | GKHI-KS-051005.07-061306 |
+ 3 |
+ 06/11/02 |
+ 0.77 |
+ 38.0 |
+ WSB/EiJ |
+ |
+ M |
+ 58 |
+ JAX |
+
+
+
+
diff --git a/general/datasets/Ma_m2m_0706_r/notes.rtf b/general/datasets/Ma_m2m_0706_r/notes.rtf
new file mode 100644
index 0000000..d41fda1
--- /dev/null
+++ b/general/datasets/Ma_m2m_0706_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by Kremena Star on July 22 ,2006. Updated by KS on July 25, 2006.
+
diff --git a/general/datasets/Ma_m2m_0706_r/platform.rtf b/general/datasets/Ma_m2m_0706_r/platform.rtf
new file mode 100644
index 0000000..cb0e8d5
--- /dev/null
+++ b/general/datasets/Ma_m2m_0706_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts and the majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using Unigene Build 107 by Affymetrix. The UTHSC group has recently reannotated all probe sets on this array, producing more accurate data on probe and probe set targets. All probes were aligned to the most recent assembly of the Mouse Genome (Build 34, mm6) using Jim Kent's BLAT program. Many of the probe sets have been manually curated by Jing Gu and Rob Williams.
+
diff --git a/general/datasets/Ma_m2m_0706_r/processing.rtf b/general/datasets/Ma_m2m_0706_r/processing.rtf
new file mode 100644
index 0000000..b313d60
--- /dev/null
+++ b/general/datasets/Ma_m2m_0706_r/processing.rtf
@@ -0,0 +1,15 @@
+
+Probe set data from the CHP file: The expression values were generated using RMA. The same simple steps described above were also applied to these values.
+
+
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients.
+
+Validation of strains and sex of each array data set: A subset of probes and probe sets with a Mendelian pattern of inheritance were used to construct a expression correlation matrix for all arrays and the ideal Mendelian expectation for each strain constructed from the genotypes. There should naturally be a very high correlation in the expression patterns of transcripts with Mendelian phenotypes within each strain, as well as with the genotype strain distribution pattern of markers for the strain.
+
+Sex of the samples was validated using sex-specific probe sets such as Xist and Dby.
+
+
+
+All data links (right-most column above) will be made active as sooon as the global analysis of these data by the Consoritum has been accepted for publication. Please see text on Data Sharing Policies, and Conditions and Limitations, and Contacts. Following publication, download a summary text file or Excel file of the PDNN probe set data. Contact RW Williams regarding data access probelms.
+
diff --git a/general/datasets/Ma_m2m_0706_r/summary.rtf b/general/datasets/Ma_m2m_0706_r/summary.rtf
new file mode 100644
index 0000000..9055ba0
--- /dev/null
+++ b/general/datasets/Ma_m2m_0706_r/summary.rtf
@@ -0,0 +1 @@
+The July 2006 Kidney QTL Consortium data set provides estimates of mRNA expression in the adult kidney of 70 genetically diverse strains of mice including 54 BXD recombinant inbred strains, a set of 15 inbred strains, and 1 F1 hybrid; D2B6F1. Kidney samples were processed using a total of 153 Affymetrix Mouse Expression 430 2.0 microarrays (M430v2.0). This particular data set was processed using the RMA protocol. CAUTION: This dataset is not sex-balanced.
diff --git a/general/datasets/Ma_m2m_0706_r/tissue.rtf b/general/datasets/Ma_m2m_0706_r/tissue.rtf
new file mode 100644
index 0000000..5bc52e9
--- /dev/null
+++ b/general/datasets/Ma_m2m_0706_r/tissue.rtf
@@ -0,0 +1,3 @@
+
+BXD animals were obtained from UTHSC, and the Jackson Laboratory (Table 1). Animals were housed at UTHSC, at Harvard/BIDMC (Glenn Rosen), at the University of Memphis (Douglas Matthews), or the Jackson Laboratory before sacrifice (see Table 1). Mice were killed by cervical dislocation and kidneys were removed and placed in RNAlater prior to dissection. Kidneys were dissected whole and cleaned from the adrenal glands by Hong Tao Zhang in Dr. Lu’s lab. Kidneys from two to six animals per strain were pooled and shipped to Kremena Star at Mount Sinai School of Medicine (MSSM). Animals used in this study were between 50 and 99 days of age (average of 62 days; see Table 1).
+
diff --git a/general/datasets/Ma_m_0704_m/acknowledgment.rtf b/general/datasets/Ma_m_0704_m/acknowledgment.rtf
new file mode 100644
index 0000000..2408013
--- /dev/null
+++ b/general/datasets/Ma_m_0704_m/acknowledgment.rtf
@@ -0,0 +1 @@
+All of the NCI mammary mRNA M430A and M430B data sets have been generated by Kent Hunter at the Laboratory of Population Genetics at the National Cancer Institute in Bethesda. For contact and citations and other information on these data sets please review the INFO pages and contact Dr. Hunter regarding use of this data set in publications or projects.
diff --git a/general/datasets/Ma_m_0704_m/cases.rtf b/general/datasets/Ma_m_0704_m/cases.rtf
new file mode 100644
index 0000000..615a0f3
--- /dev/null
+++ b/general/datasets/Ma_m_0704_m/cases.rtf
@@ -0,0 +1,4 @@
+The lines of mice used in this NCI-sponsored project consist of 18 groups of isogenic F1 progeny made by crossing females from each of 18 AKXD recombinant inbred strains (AKXD2, 3, 7, 9, 10, 11, 13, 14, 16, 18, 20, 21, 22, 23, 24, 25, 27, and 28) to male FVB/N mice that carry a transgene that consistently leads to the development of mammary tumors in females (e.g. Le Voyer et al., 2001). The formal nomenclature of the male transgenic line is FVB/N-TgN(MMTV-PyMT)634Mul. The genomes of each AKXD x FVB F1 consist of one set of FVB chromosomes (including the transgene) and one set of chromosomes inherited from one of the 18 AKXD RI strain mothers. Only the AKXD chromosomes are "recombinant" across this panel of F1 progeny, and the set therefore has a genetic architecture similar to backcross progeny. It is possible to map modifiers that influence tumor characteristics and expression patterns. It is also possible to study covariance of transcript expression levels in tumor tissue. For further background on this special mapping design please see Hunter and Williams (2002).
+
+The ancestral strains from which all AKXD strains are derived are AKR/J (AKR) and DBA/2J (D2 or D). DBA/2J has been partially sequenced (approximately 1.5x coverage by D by Celera Genomics). Significant genomic sequence data for AKR is not currently available. Chromosomes of the two parental strains have recombined in the different AKXD strains. All of these strains are available from The Jackson Laboratory as cryopreserved stocks. For additional background on recombinant inbred strains, please see http://www.nervenet.org/papers/bxn.html.
diff --git a/general/datasets/Ma_m_0704_m/notes.rtf b/general/datasets/Ma_m_0704_m/notes.rtf
new file mode 100644
index 0000000..4e0118b
--- /dev/null
+++ b/general/datasets/Ma_m_0704_m/notes.rtf
@@ -0,0 +1 @@
+Text originally written by Kent Hunter and Robert W. Williams, July 2004. Updated by RWW, Nov 6, 2004.
diff --git a/general/datasets/Ma_m_0704_m/platform.rtf b/general/datasets/Ma_m_0704_m/platform.rtf
new file mode 100644
index 0000000..4b22e44
--- /dev/null
+++ b/general/datasets/Ma_m_0704_m/platform.rtf
@@ -0,0 +1,643 @@
+All samples were processed and arrayed in the Laboratory of Population Genetics at the NCI. The table below lists the arrays by Samples, AKXD strain and Age.
+
+
+
+
+
+
+
+
+
+ |
+ Sample
+ |
+
+ AKXD strain
+ |
+
+ Age
+ |
+
+
+ |
+ AKXD2957
+ |
+
+ 2
+ |
+
+ 98
+ |
+
+
+ |
+ AKXD2959
+ |
+
+ 2
+ |
+
+ 96
+ |
+
+
+ |
+ AKXD1747
+ |
+
+ 3
+ |
+
+ 84
+ |
+
+
+ |
+ AKXD3446
+ |
+
+ 3
+ |
+
+ 91
+ |
+
+
+ |
+ AKXD4225
+ |
+
+ 3
+ |
+
+ 83
+ |
+
+
+ |
+ AKXD2543
+ |
+
+ 7
+ |
+
+ 82
+ |
+
+
+ |
+ AKXD2967
+ |
+
+ 7
+ |
+
+ 88
+ |
+
+
+ |
+ AKXD3336
+ |
+
+ 7
+ |
+
+ 95
+ |
+
+
+ |
+ AKXD2685
+ |
+
+ 9
+ |
+
+ 113
+ |
+
+
+ |
+ AKXD2710
+ |
+
+ 9
+ |
+
+ 109
+ |
+
+
+ |
+ AKXD2949
+ |
+
+ 9
+ |
+
+ 115
+ |
+
+
+ |
+ AKXD2618
+ |
+
+ 10
+ |
+
+ 99
+ |
+
+
+ |
+ AKXD2620
+ |
+
+ 10
+ |
+
+ 99
+ |
+
+
+ |
+ AKXD3023
+ |
+
+ 10
+ |
+
+ 94
+ |
+
+
+ |
+ AKXD1910
+ |
+
+ 11
+ |
+
+ 87
+ |
+
+
+ |
+ AKXD2824
+ |
+
+ 11
+ |
+
+ 92
+ |
+
+
+ |
+ AKXD2825
+ |
+
+ 11
+ |
+
+ 103
+ |
+
+
+ |
+ AKXD2635
+ |
+
+ 13
+ |
+
+ 83
+ |
+
+
+ |
+ AKXD2718
+ |
+
+ 13
+ |
+
+ 100
+ |
+
+
+ |
+ AKXD2721
+ |
+
+ 13
+ |
+
+ 91
+ |
+
+
+ |
+ AKXD2632
+ |
+
+ 14
+ |
+
+ 99
+ |
+
+
+ |
+ AKXD2640
+ |
+
+ 14
+ |
+
+ 100
+ |
+
+
+ |
+ AKXD3444
+ |
+
+ 14
+ |
+
+ 96
+ |
+
+
+ |
+ AKXD1636
+ |
+
+ 16
+ |
+
+ 112
+ |
+
+
+ |
+ AKXD3688
+ |
+
+ 16
+ |
+
+ 80
+ |
+
+
+ |
+ AKXD4152
+ |
+
+ 16
+ |
+
+ 91
+ |
+
+
+ |
+ AKXD1647
+ |
+
+ 18
+ |
+
+ 91
+ |
+
+
+ |
+ AKXD2616
+ |
+
+ 18
+ |
+
+ 91
+ |
+
+
+ |
+ AKXD2804
+ |
+
+ 18
+ |
+
+ 80
+ |
+
+
+ |
+ AKXD2456
+ |
+
+ 20
+ |
+
+ 100
+ |
+
+
+ |
+ AKXD2554
+ |
+
+ 20
+ |
+
+ 107
+ |
+
+
+ |
+ AKXD2829
+ |
+
+ 20
+ |
+
+ 105
+ |
+
+
+ |
+ AKXD1610
+ |
+
+ 21
+ |
+
+ 98
+ |
+
+
+ |
+ AKXD2611
+ |
+
+ 21
+ |
+
+ 88
+ |
+
+
+ |
+ AKXD2918
+ |
+
+ 21
+ |
+
+ 98
+ |
+
+
+ |
+ AKXD2460
+ |
+
+ 22
+ |
+
+ 107
+ |
+
+
+ |
+ AKXD2461
+ |
+
+ 22
+ |
+
+ 94
+ |
+
+
+ |
+ AKXD2463
+ |
+
+ 22
+ |
+
+ 110
+ |
+
+
+ |
+ AKXD2975
+ |
+
+ 23
+ |
+
+ 82
+ |
+
+
+ |
+ AKXD2976
+ |
+
+ 23
+ |
+
+ 86
+ |
+
+
+ |
+ AKXD3955
+ |
+
+ 23
+ |
+
+ 90
+ |
+
+
+ |
+ AKXD1494
+ |
+
+ 24
+ |
+
+ 103
+ |
+
+
+ |
+ AKXD1880
+ |
+
+ 24
+ |
+
+ 104
+ |
+
+
+ |
+ AKXD3030
+ |
+
+ 24
+ |
+
+ 89
+ |
+
+
+ |
+ AKXD1607
+ |
+
+ 25
+ |
+
+ 110
+ |
+
+
+ |
+ AKXD2326
+ |
+
+ 25
+ |
+
+ 92
+ |
+
+
+ |
+ AKXD2328
+ |
+
+ 25
+ |
+
+ 90
+ |
+
+
+ |
+ AKXD2629
+ |
+
+ 25
+ |
+
+ 96
+ |
+
+
+ |
+ AKXD1756
+ |
+
+ 27
+ |
+
+ 100
+ |
+
+
+ |
+ AKXD1757
+ |
+
+ 27
+ |
+
+ 98
+ |
+
+
+ |
+ AKXD1948
+ |
+
+ 27
+ |
+
+ 99
+ |
+
+
+ |
+ AKXD1950
+ |
+
+ 27
+ |
+
+ 97
+ |
+
+
+ |
+ AKXD2968
+ |
+
+ 27
+ |
+
+ 94
+ |
+
+
+ |
+ AKXD2809
+ |
+
+ 28
+ |
+
+ 88
+ |
+
+
+ |
+ AKXD2815
+ |
+
+ 28
+ |
+
+ 90
+ |
+
+
+ |
+ AKXD3432
+ |
+
+ 28
+ |
+
+ 91
+ |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Ma_m_0704_m/processing.rtf b/general/datasets/Ma_m_0704_m/processing.rtf
new file mode 100644
index 0000000..0d11078
--- /dev/null
+++ b/general/datasets/Ma_m_0704_m/processing.rtf
@@ -0,0 +1,15 @@
+Probe (cell) level data from the .CEL file: These .CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 to the .CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each cell.
+ - Step 3: We computed the Z scores for each cell.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B GeneChips include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the two GeneChips to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+
+Probe set data from the .CHP file: The expression data were generated using MAS5. The same simple steps described above were also applied to these values. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers on the 430A and 430B microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Ma_m_0704_m/summary.rtf b/general/datasets/Ma_m_0704_m/summary.rtf
new file mode 100644
index 0000000..6423e7c
--- /dev/null
+++ b/general/datasets/Ma_m_0704_m/summary.rtf
@@ -0,0 +1 @@
+Used the Affymetrix M430A and M430B pair of arrays (total of 45,137 probe sets). Data available as CEL files from GeneNetwork upon request.
diff --git a/general/datasets/Ma_m_0704_m/tissue.rtf b/general/datasets/Ma_m_0704_m/tissue.rtf
new file mode 100644
index 0000000..01385cb
--- /dev/null
+++ b/general/datasets/Ma_m_0704_m/tissue.rtf
@@ -0,0 +1 @@
+Mammary tumors used in this array experiment were derived from 18 sets of AKXD x FVB/N F1 females as described above. After the primary tumor was diagnosed, the animals were aged an additional 40 days to permit metastatic progression. Females were sacrificed and mammary tumors were harvested. Samples were processed and arrayed on Affymetrix M430A and M430B arrays. The majority of the samples were assayed on arrays obtained from the same lot number.
diff --git a/general/datasets/Ma_m_0704_r/acknowledgment.rtf b/general/datasets/Ma_m_0704_r/acknowledgment.rtf
new file mode 100644
index 0000000..2408013
--- /dev/null
+++ b/general/datasets/Ma_m_0704_r/acknowledgment.rtf
@@ -0,0 +1 @@
+All of the NCI mammary mRNA M430A and M430B data sets have been generated by Kent Hunter at the Laboratory of Population Genetics at the National Cancer Institute in Bethesda. For contact and citations and other information on these data sets please review the INFO pages and contact Dr. Hunter regarding use of this data set in publications or projects.
diff --git a/general/datasets/Ma_m_0704_r/cases.rtf b/general/datasets/Ma_m_0704_r/cases.rtf
new file mode 100644
index 0000000..615a0f3
--- /dev/null
+++ b/general/datasets/Ma_m_0704_r/cases.rtf
@@ -0,0 +1,4 @@
+The lines of mice used in this NCI-sponsored project consist of 18 groups of isogenic F1 progeny made by crossing females from each of 18 AKXD recombinant inbred strains (AKXD2, 3, 7, 9, 10, 11, 13, 14, 16, 18, 20, 21, 22, 23, 24, 25, 27, and 28) to male FVB/N mice that carry a transgene that consistently leads to the development of mammary tumors in females (e.g. Le Voyer et al., 2001). The formal nomenclature of the male transgenic line is FVB/N-TgN(MMTV-PyMT)634Mul. The genomes of each AKXD x FVB F1 consist of one set of FVB chromosomes (including the transgene) and one set of chromosomes inherited from one of the 18 AKXD RI strain mothers. Only the AKXD chromosomes are "recombinant" across this panel of F1 progeny, and the set therefore has a genetic architecture similar to backcross progeny. It is possible to map modifiers that influence tumor characteristics and expression patterns. It is also possible to study covariance of transcript expression levels in tumor tissue. For further background on this special mapping design please see Hunter and Williams (2002).
+
+The ancestral strains from which all AKXD strains are derived are AKR/J (AKR) and DBA/2J (D2 or D). DBA/2J has been partially sequenced (approximately 1.5x coverage by D by Celera Genomics). Significant genomic sequence data for AKR is not currently available. Chromosomes of the two parental strains have recombined in the different AKXD strains. All of these strains are available from The Jackson Laboratory as cryopreserved stocks. For additional background on recombinant inbred strains, please see http://www.nervenet.org/papers/bxn.html.
diff --git a/general/datasets/Ma_m_0704_r/notes.rtf b/general/datasets/Ma_m_0704_r/notes.rtf
new file mode 100644
index 0000000..4e0118b
--- /dev/null
+++ b/general/datasets/Ma_m_0704_r/notes.rtf
@@ -0,0 +1 @@
+Text originally written by Kent Hunter and Robert W. Williams, July 2004. Updated by RWW, Nov 6, 2004.
diff --git a/general/datasets/Ma_m_0704_r/platform.rtf b/general/datasets/Ma_m_0704_r/platform.rtf
new file mode 100644
index 0000000..4b22e44
--- /dev/null
+++ b/general/datasets/Ma_m_0704_r/platform.rtf
@@ -0,0 +1,643 @@
+All samples were processed and arrayed in the Laboratory of Population Genetics at the NCI. The table below lists the arrays by Samples, AKXD strain and Age.
+
+
+
+
+
+
+
+
+
+ |
+ Sample
+ |
+
+ AKXD strain
+ |
+
+ Age
+ |
+
+
+ |
+ AKXD2957
+ |
+
+ 2
+ |
+
+ 98
+ |
+
+
+ |
+ AKXD2959
+ |
+
+ 2
+ |
+
+ 96
+ |
+
+
+ |
+ AKXD1747
+ |
+
+ 3
+ |
+
+ 84
+ |
+
+
+ |
+ AKXD3446
+ |
+
+ 3
+ |
+
+ 91
+ |
+
+
+ |
+ AKXD4225
+ |
+
+ 3
+ |
+
+ 83
+ |
+
+
+ |
+ AKXD2543
+ |
+
+ 7
+ |
+
+ 82
+ |
+
+
+ |
+ AKXD2967
+ |
+
+ 7
+ |
+
+ 88
+ |
+
+
+ |
+ AKXD3336
+ |
+
+ 7
+ |
+
+ 95
+ |
+
+
+ |
+ AKXD2685
+ |
+
+ 9
+ |
+
+ 113
+ |
+
+
+ |
+ AKXD2710
+ |
+
+ 9
+ |
+
+ 109
+ |
+
+
+ |
+ AKXD2949
+ |
+
+ 9
+ |
+
+ 115
+ |
+
+
+ |
+ AKXD2618
+ |
+
+ 10
+ |
+
+ 99
+ |
+
+
+ |
+ AKXD2620
+ |
+
+ 10
+ |
+
+ 99
+ |
+
+
+ |
+ AKXD3023
+ |
+
+ 10
+ |
+
+ 94
+ |
+
+
+ |
+ AKXD1910
+ |
+
+ 11
+ |
+
+ 87
+ |
+
+
+ |
+ AKXD2824
+ |
+
+ 11
+ |
+
+ 92
+ |
+
+
+ |
+ AKXD2825
+ |
+
+ 11
+ |
+
+ 103
+ |
+
+
+ |
+ AKXD2635
+ |
+
+ 13
+ |
+
+ 83
+ |
+
+
+ |
+ AKXD2718
+ |
+
+ 13
+ |
+
+ 100
+ |
+
+
+ |
+ AKXD2721
+ |
+
+ 13
+ |
+
+ 91
+ |
+
+
+ |
+ AKXD2632
+ |
+
+ 14
+ |
+
+ 99
+ |
+
+
+ |
+ AKXD2640
+ |
+
+ 14
+ |
+
+ 100
+ |
+
+
+ |
+ AKXD3444
+ |
+
+ 14
+ |
+
+ 96
+ |
+
+
+ |
+ AKXD1636
+ |
+
+ 16
+ |
+
+ 112
+ |
+
+
+ |
+ AKXD3688
+ |
+
+ 16
+ |
+
+ 80
+ |
+
+
+ |
+ AKXD4152
+ |
+
+ 16
+ |
+
+ 91
+ |
+
+
+ |
+ AKXD1647
+ |
+
+ 18
+ |
+
+ 91
+ |
+
+
+ |
+ AKXD2616
+ |
+
+ 18
+ |
+
+ 91
+ |
+
+
+ |
+ AKXD2804
+ |
+
+ 18
+ |
+
+ 80
+ |
+
+
+ |
+ AKXD2456
+ |
+
+ 20
+ |
+
+ 100
+ |
+
+
+ |
+ AKXD2554
+ |
+
+ 20
+ |
+
+ 107
+ |
+
+
+ |
+ AKXD2829
+ |
+
+ 20
+ |
+
+ 105
+ |
+
+
+ |
+ AKXD1610
+ |
+
+ 21
+ |
+
+ 98
+ |
+
+
+ |
+ AKXD2611
+ |
+
+ 21
+ |
+
+ 88
+ |
+
+
+ |
+ AKXD2918
+ |
+
+ 21
+ |
+
+ 98
+ |
+
+
+ |
+ AKXD2460
+ |
+
+ 22
+ |
+
+ 107
+ |
+
+
+ |
+ AKXD2461
+ |
+
+ 22
+ |
+
+ 94
+ |
+
+
+ |
+ AKXD2463
+ |
+
+ 22
+ |
+
+ 110
+ |
+
+
+ |
+ AKXD2975
+ |
+
+ 23
+ |
+
+ 82
+ |
+
+
+ |
+ AKXD2976
+ |
+
+ 23
+ |
+
+ 86
+ |
+
+
+ |
+ AKXD3955
+ |
+
+ 23
+ |
+
+ 90
+ |
+
+
+ |
+ AKXD1494
+ |
+
+ 24
+ |
+
+ 103
+ |
+
+
+ |
+ AKXD1880
+ |
+
+ 24
+ |
+
+ 104
+ |
+
+
+ |
+ AKXD3030
+ |
+
+ 24
+ |
+
+ 89
+ |
+
+
+ |
+ AKXD1607
+ |
+
+ 25
+ |
+
+ 110
+ |
+
+
+ |
+ AKXD2326
+ |
+
+ 25
+ |
+
+ 92
+ |
+
+
+ |
+ AKXD2328
+ |
+
+ 25
+ |
+
+ 90
+ |
+
+
+ |
+ AKXD2629
+ |
+
+ 25
+ |
+
+ 96
+ |
+
+
+ |
+ AKXD1756
+ |
+
+ 27
+ |
+
+ 100
+ |
+
+
+ |
+ AKXD1757
+ |
+
+ 27
+ |
+
+ 98
+ |
+
+
+ |
+ AKXD1948
+ |
+
+ 27
+ |
+
+ 99
+ |
+
+
+ |
+ AKXD1950
+ |
+
+ 27
+ |
+
+ 97
+ |
+
+
+ |
+ AKXD2968
+ |
+
+ 27
+ |
+
+ 94
+ |
+
+
+ |
+ AKXD2809
+ |
+
+ 28
+ |
+
+ 88
+ |
+
+
+ |
+ AKXD2815
+ |
+
+ 28
+ |
+
+ 90
+ |
+
+
+ |
+ AKXD3432
+ |
+
+ 28
+ |
+
+ 91
+ |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Ma_m_0704_r/processing.rtf b/general/datasets/Ma_m_0704_r/processing.rtf
new file mode 100644
index 0000000..0d11078
--- /dev/null
+++ b/general/datasets/Ma_m_0704_r/processing.rtf
@@ -0,0 +1,15 @@
+Probe (cell) level data from the .CEL file: These .CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+ - Step 1: We added an offset of 1.0 to the .CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each cell.
+ - Step 3: We computed the Z scores for each cell.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B GeneChips include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes and probe sets provide a way to calibrate expression of the two GeneChips to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+
+Probe set data from the .CHP file: The expression data were generated using MAS5. The same simple steps described above were also applied to these values. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of probe sets and gene markers on the 430A and 430B microarrays were determined by BLAT analysis using the Mouse Genome Sequencing Consortium May 2004 (mm5) assembly (see http://genome.ucsc.edu/cgi-bin/hgBlat?command=start&org=mouse). We thank Dr. Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis.
diff --git a/general/datasets/Ma_m_0704_r/summary.rtf b/general/datasets/Ma_m_0704_r/summary.rtf
new file mode 100644
index 0000000..6423e7c
--- /dev/null
+++ b/general/datasets/Ma_m_0704_r/summary.rtf
@@ -0,0 +1 @@
+Used the Affymetrix M430A and M430B pair of arrays (total of 45,137 probe sets). Data available as CEL files from GeneNetwork upon request.
diff --git a/general/datasets/Ma_m_0704_r/tissue.rtf b/general/datasets/Ma_m_0704_r/tissue.rtf
new file mode 100644
index 0000000..01385cb
--- /dev/null
+++ b/general/datasets/Ma_m_0704_r/tissue.rtf
@@ -0,0 +1 @@
+Mammary tumors used in this array experiment were derived from 18 sets of AKXD x FVB/N F1 females as described above. After the primary tumor was diagnosed, the animals were aged an additional 40 days to permit metastatic progression. Females were sacrificed and mammary tumors were harvested. Samples were processed and arrayed on Affymetrix M430A and M430B arrays. The majority of the samples were assayed on arrays obtained from the same lot number.
diff --git a/general/datasets/Mdppublish/citation.rtf b/general/datasets/Mdppublish/citation.rtf
new file mode 100644
index 0000000..ace9bc3
--- /dev/null
+++ b/general/datasets/Mdppublish/citation.rtf
@@ -0,0 +1,17 @@
+When mentioning the MPD please use and cite this URL: http://www.jax.org/phenome. This is the MPD's best known location and is usually preferable to the longer dynamic system URLs that may appear in URL address fields.
+
+Publications:
+
+Grubb SC, Churchill GA, Bogue MA. A collaborative database of inbred mouse strain characteristics. Bioinformatics. 2004 Nov 1;20(16):2857-9. Epub 2004 May 6. PMID: 15130929
+
+Bogue MA, Grubb SC. The mouse phenome project. Genetica. 2004 Sep;122:71-74. PMID: 15619963
+
+To cite specific phenotyping data in the MPD, a format similar to this may be used. (Please be sure you have read and agree with our user agreement for taking and using MPD data.)
+
+Investigators. Project Title. MPD accession#. Mouse Phenome Database Web Site, The Jackson Laboratory, Bar Harbor, Maine USA. World Wide Web (URL: http://www.jax.org/phenome, month and year of download ).
+
+Example:
+
+Wahlsten D, Crabbe JC. Comparative study of activity, anxiety, motor learning, and spatial learning in two laboratories. MPD:108. Mouse Phenome Database Web Site, The Jackson Laboratory, Bar Harbor, ME USA. World Wide Web (URL: http://www.jax.org/phenome, July 2004).
+
+Each phenotyping project in the MPD is assigned an accession number having the format MPD:NNN, where NNN is an integer. Accession numbers are displayed in the projects index and the individual project detail pages.
diff --git a/general/datasets/Mdppublish/summary.rtf b/general/datasets/Mdppublish/summary.rtf
new file mode 100644
index 0000000..a5cb4f6
--- /dev/null
+++ b/general/datasets/Mdppublish/summary.rtf
@@ -0,0 +1,17 @@
+MDP: The great majority of data on the Mouse Diversity Panel is taken from the Phenome Project. Unlike the PHone Project, the MDP also includes limited data from the older literature.
+
+These data were downloaded from the Mouse Phenome Database at The Jackson Laboratory in June 2006 and implemented in GeneNetwork July 2006.
+
+The Mouse Phenome Database (MPD) and several other large data sets are being integrated into the GeneNetwork's Mouse Diversity Panel. To access these new data sets please select "MOUSE-GROUP-Mouse Diversity Panel". The Mouse Diversity Panel will eventually includes the MPD, additional strain data sets extracted from the published literature, the Wellcome Trust-CTC SNP collection, and several large gene expression data sets, including those for whole brain, hippocampus, cerebellum, and eye. (Implemented by Jintao Wang and Evan G. Williams.)
+
+
+
+
+
+Legend: Access to the new Mouse Diversity Panel data sets.
+
+
+
+
+
+Legend: Bar chart of white blood cell counts across 43 strains of mice taken from the Mouse Diversity Panel. Virutally all of the phenotype data are provided from the Mouse Phenome Project.
diff --git a/general/datasets/NHLBI_BXD_Aged_Heart_CD_RNA_Seq_1120/experiment-design.rtf b/general/datasets/NHLBI_BXD_Aged_Heart_CD_RNA_Seq_1120/experiment-design.rtf
deleted file mode 100644
index fbdad24..0000000
--- a/general/datasets/NHLBI_BXD_Aged_Heart_CD_RNA_Seq_1120/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA Extraction
-
-Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Approximately 30 mg of left ventricle tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/NHLBI_BXD_Aged_Heart_CD_RNA_Seq_1120/processing.rtf b/general/datasets/NHLBI_BXD_Aged_Heart_CD_RNA_Seq_1120/processing.rtf
deleted file mode 100644
index 8e460ff..0000000
--- a/general/datasets/NHLBI_BXD_Aged_Heart_CD_RNA_Seq_1120/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/NHLBI_BXD_Aged_Heart_CD_RNA_Seq_1120/specifics.rtf b/general/datasets/NHLBI_BXD_Aged_Heart_CD_RNA_Seq_1120/specifics.rtf
deleted file mode 100644
index d109d3c..0000000
--- a/general/datasets/NHLBI_BXD_Aged_Heart_CD_RNA_Seq_1120/specifics.rtf
+++ /dev/null
@@ -1,2770 +0,0 @@
-NHLBI BXD Aged Heart CD RNA-Seq (Nov20) TMP Log2
-
-About the cases used to generate this set of data:
-
-The study included 105 mice (~12 month) from B6, D2, B6D2F1,and 51 advanced intercross BXD strains (about 2 mice per strain). All mice were fed on chow diet (CD). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
-
-
-
-The table of samples that are finally used for this study.
-
-
-
-
- |
- Index
- |
-
- Sample ID
- |
-
- Case id
- |
-
- Strain
- |
-
- Fuyi_Sex_Final
- |
-
- Sac age/Day
- |
-
- Tissue
- |
-
- Diet
- |
-
-
- |
- 1
- |
-
- K100
- |
-
- *103017.77
- |
-
- BXD155
- |
-
- M
- |
-
- 362
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 2
- |
-
- K101
- |
-
- *071917.111
- |
-
- BXD184
- |
-
- M
- |
-
- 387
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 3
- |
-
- K104
- |
-
- *103017.75
- |
-
- BXD155
- |
-
- F
- |
-
- 362
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 4
- |
-
- K107
- |
-
- *071917.45
- |
-
- BXD73
- |
-
- F
- |
-
- 338
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 5
- |
-
- K108
- |
-
- *071917.72
- |
-
- BXD90
- |
-
- M
- |
-
- 330
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 6
- |
-
- K10
- |
-
- *062117.51
- |
-
- BXD150
- |
-
- F
- |
-
- 385
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 7
- |
-
- K112
- |
-
- *071917.74
- |
-
- BXD122
- |
-
- M
- |
-
- 331
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 8
- |
-
- K113
- |
-
- *071917.88
- |
-
- BXD144
- |
-
- M
- |
-
- 331
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 9
- |
-
- K114
- |
-
- *071917.47
- |
-
- BXD73
- |
-
- M
- |
-
- 338
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 10
- |
-
- K117
- |
-
- *071917.87
- |
-
- BXD144
- |
-
- F
- |
-
- 331
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 11
- |
-
- K118
- |
-
- *071917.73
- |
-
- BXD122
- |
-
- F
- |
-
- 331
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 12
- |
-
- K12
- |
-
- *062117.48
- |
-
- BXD125
- |
-
- F
- |
-
- 396
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 13
- |
-
- K13
- |
-
- *062117.54
- |
-
- BXD151
- |
-
- F
- |
-
- 396
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 14
- |
-
- K143
- |
-
- *071917.18
- |
-
- BXD48a
- |
-
- F
- |
-
- 387
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 15
- |
-
- K144
- |
-
- *071917.42
- |
-
- BXD71
- |
-
- F
- |
-
- 400
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 16
- |
-
- K147
- |
-
- *071917.31
- |
-
- BXD66
- |
-
- F
- |
-
- 331
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 17
- |
-
- K149
- |
-
- *071917.92
- |
-
- BXD156
- |
-
- F
- |
-
- 342
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 18
- |
-
- K14
- |
-
- *062117.55
- |
-
- BXD151
- |
-
- M
- |
-
- 396
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 19
- |
-
- K150
- |
-
- *071917.93
- |
-
- BXD156
- |
-
- M
- |
-
- 342
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 20
- |
-
- K152
- |
-
- *071917.107
- |
-
- BXD180
- |
-
- M
- |
-
- 341
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 21
- |
-
- K153
- |
-
- *071917.89
- |
-
- BXD152
- |
-
- F
- |
-
- 405
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 22
- |
-
- K155
- |
-
- *071917.70
- |
-
- BXD90
- |
-
- F
- |
-
- 330
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 23
- |
-
- K156
- |
-
- *071917.33
- |
-
- BXD66
- |
-
- M
- |
-
- 331
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 24
- |
-
- K15
- |
-
- *062117.34
- |
-
- BXD77
- |
-
- F
- |
-
- 355
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 25
- |
-
- K164
- |
-
- E092718.08
- |
-
- BXD40
- |
-
- F
- |
-
- 340
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 26
- |
-
- K165
- |
-
- E092718.09
- |
-
- BXD40
- |
-
- M
- |
-
- 340
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 27
- |
-
- K168
- |
-
- E100318.34
- |
-
- BXD102
- |
-
- F
- |
-
- 412
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 28
- |
-
- K169
- |
-
- E100318.35
- |
-
- BXD102
- |
-
- M
- |
-
- 412
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 29
- |
-
- K16
- |
-
- *062117.44
- |
-
- BXD123
- |
-
- F
- |
-
- 361
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 30
- |
-
- K172
- |
-
- *041118.01
- |
-
- C57BL/6J
- |
-
- F
- |
-
- 343
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 31
- |
-
- K173
- |
-
- *041118.03
- |
-
- C57BL/6J
- |
-
- M
- |
-
- 343
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 32
- |
-
- K175
- |
-
- *041118.05
- |
-
- DBA/2J
- |
-
- F
- |
-
- 435
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 33
- |
-
- K176
- |
-
- *041118.06
- |
-
- DBA/2J
- |
-
- M
- |
-
- 435
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 34
- |
-
- K177
- |
-
- 042314.10
- |
-
- B6D2F1
- |
-
- M
- |
-
- 364
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 35
- |
-
- K178
- |
-
- 042314.12
- |
-
- B6D2F1
- |
-
- F
- |
-
- 364
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 36
- |
-
- K17
- |
-
- *062117.41
- |
-
- BXD100
- |
-
- F
- |
-
- 449
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 37
- |
-
- K182
- |
-
- 083016.01
- |
-
- BXD32
- |
-
- F
- |
-
- 386
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 38
- |
-
- K183
- |
-
- 083016.02
- |
-
- BXD32
- |
-
- F
- |
-
- 386
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 39
- |
-
- K18
- |
-
- *062117.49
- |
-
- BXD125
- |
-
- M
- |
-
- 396
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 40
- |
-
- K19
- |
-
- *062117.45
- |
-
- BXD123
- |
-
- F
- |
-
- 361
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 41
- |
-
- K21
- |
-
- *062117.43
- |
-
- BXD100
- |
-
- M
- |
-
- 449
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 42
- |
-
- K22
- |
-
- *062117.28
- |
-
- BXD70
- |
-
- F
- |
-
- 359
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 43
- |
-
- K23
- |
-
- *062117.39
- |
-
- BXD87
- |
-
- F
- |
-
- 359
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 44
- |
-
- K24
- |
-
- *062117.52
- |
-
- BXD150
- |
-
- M
- |
-
- 385
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 45
- |
-
- K25
- |
-
- *062117.29
- |
-
- BXD70
- |
-
- M
- |
-
- 359
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 46
- |
-
- K27
- |
-
- *071917.54
- |
-
- BXD75
- |
-
- F
- |
-
- 366
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 47
- |
-
- K28
- |
-
- *071917.50
- |
-
- BXD73b
- |
-
- M
- |
-
- 422
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 48
- |
-
- K29
- |
-
- *071917.66
- |
-
- BXD86
- |
-
- M
- |
-
- 404
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 49
- |
-
- K2
- |
-
- *071917.106
- |
-
- BXD178
- |
-
- M
- |
-
- 359
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 50
- |
-
- K30
- |
-
- *103017.59
- |
-
- BXD113
- |
-
- F
- |
-
- 373
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 51
- |
-
- K32
- |
-
- *103017.83
- |
-
- BXD168
- |
-
- M
- |
-
- 398
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 52
- |
-
- K33
- |
-
- *103017.81
- |
-
- BXD168
- |
-
- F
- |
-
- 398
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 53
- |
-
- K35
- |
-
- *103017.74
- |
-
- BXD154
- |
-
- M
- |
-
- 417
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 54
- |
-
- K36
- |
-
- *103017.86
- |
-
- BXD195
- |
-
- F
- |
-
- 355
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 55
- |
-
- K38
- |
-
- *103017.61
- |
-
- BXD113
- |
-
- M
- |
-
- 373
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 56
- |
-
- K39
- |
-
- *103017.72
- |
-
- BXD154
- |
-
- F
- |
-
- 417
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 57
- |
-
- K40
- |
-
- *103017.51
- |
-
- BXD83
- |
-
- M
- |
-
- 407
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 58
- |
-
- K41
- |
-
- *103017.49
- |
-
- BXD83
- |
-
- F
- |
-
- 407
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 59
- |
-
- K42
- |
-
- *103017.87
- |
-
- BXD195
- |
-
- M
- |
-
- 355
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 60
- |
-
- K44
- |
-
- *062117.40
- |
-
- BXD87
- |
-
- M
- |
-
- 359
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 61
- |
-
- K49
- |
-
- *062117.63
- |
-
- BXD169
- |
-
- F
- |
-
- 352
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 62
- |
-
- K4
- |
-
- *071917.105
- |
-
- BXD178
- |
-
- F
- |
-
- 359
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 63
- |
-
- K50
- |
-
- *062117.04
- |
-
- BXD18
- |
-
- M
- |
-
- 379
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 64
- |
-
- K51
- |
-
- *062117.17
- |
-
- BXD48
- |
-
- F
- |
-
- 380
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 65
- |
-
- K53
- |
-
- *062117.06
- |
-
- BXD27
- |
-
- F
- |
-
- 435
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 66
- |
-
- K54
- |
-
- *062117.02
- |
-
- BXD15
- |
-
- M
- |
-
- 379
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 67
- |
-
- K56
- |
-
- *062117.15
- |
-
- BXD45
- |
-
- M
- |
-
- 437
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 68
- |
-
- K57
- |
-
- *062117.25
- |
-
- BXD63
- |
-
- F
- |
-
- 404
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 69
- |
-
- K59
- |
-
- *062117.01
- |
-
- BXD15
- |
-
- F
- |
-
- 379
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 70
- |
-
- K5
- |
-
- *071917.104
- |
-
- BXD161
- |
-
- M
- |
-
- 352
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 71
- |
-
- K60
- |
-
- *062117.13
- |
-
- BXD34
- |
-
- M
- |
-
- 411
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 72
- |
-
- K61
- |
-
- *062117.12
- |
-
- BXD34
- |
-
- F
- |
-
- 411
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 73
- |
-
- K62
- |
-
- *062117.26
- |
-
- BXD63
- |
-
- M
- |
-
- 404
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 74
- |
-
- K63
- |
-
- *062117.18
- |
-
- BXD48
- |
-
- M
- |
-
- 380
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 75
- |
-
- K65
- |
-
- *062117.03
- |
-
- BXD18
- |
-
- F
- |
-
- 379
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 76
- |
-
- K67
- |
-
- *062117.62
- |
-
- BXD169
- |
-
- F
- |
-
- 352
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 77
- |
-
- K68
- |
-
- *062117.14
- |
-
- BXD45
- |
-
- F
- |
-
- 437
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 78
- |
-
- K69
- |
-
- *062117.07
- |
-
- BXD27
- |
-
- M
- |
-
- 435
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 79
- |
-
- K6
- |
-
- *071917.100
- |
-
- BXD160
- |
-
- F
- |
-
- 446
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 80
- |
-
- K71
- |
-
- *071917.63
- |
-
- BXD79
- |
-
- F
- |
-
- 418
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 81
- |
-
- K73
- |
-
- *071917.64
- |
-
- BXD79
- |
-
- M
- |
-
- 418
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 82
- |
-
- K74
- |
-
- *071917.56
- |
-
- BXD75
- |
-
- M
- |
-
- 366
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 83
- |
-
- K76
- |
-
- *071917.65
- |
-
- BXD86
- |
-
- F
- |
-
- 404
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 84
- |
-
- K78
- |
-
- *071917.01
- |
-
- BXD16
- |
-
- F
- |
-
- 416
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 85
- |
-
- K79
- |
-
- *071917.03
- |
-
- BXD16
- |
-
- M
- |
-
- 416
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 86
- |
-
- K7
- |
-
- *071917.98
- |
-
- BXD157
- |
-
- M
- |
-
- 381
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 87
- |
-
- K80
- |
-
- *071917.26
- |
-
- BXD65
- |
-
- F
- |
-
- 423
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 88
- |
-
- K82
- |
-
- *071917.28
- |
-
- BXD65
- |
-
- M
- |
-
- 423
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 89
- |
-
- K83
- |
-
- *071917.44
- |
-
- BXD71
- |
-
- M
- |
-
- 400
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 90
- |
-
- K84
- |
-
- *071917.30
- |
-
- BXD65b
- |
-
- M
- |
-
- 351
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 91
- |
-
- K85
- |
-
- *071917.20
- |
-
- BXD48a
- |
-
- M
- |
-
- 387
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 92
- |
-
- K86
- |
-
- *071917.29
- |
-
- BXD65b
- |
-
- F
- |
-
- 351
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 93
- |
-
- K88
- |
-
- *071917.97
- |
-
- BXD157
- |
-
- M
- |
-
- 381
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 94
- |
-
- K89
- |
-
- *071917.101
- |
-
- BXD160
- |
-
- M
- |
-
- 446
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 95
- |
-
- K90
- |
-
- *071917.112
- |
-
- BXD186
- |
-
- F
- |
-
- 403
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 96
- |
-
- K91
- |
-
- *071917.102
- |
-
- BXD161
- |
-
- F
- |
-
- 352
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 97
- |
-
- K92
- |
-
- *071917.114
- |
-
- BXD186
- |
-
- M
- |
-
- 403
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 98
- |
-
- K93
- |
-
- *071917.90
- |
-
- BXD152
- |
-
- F
- |
-
- 405
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 99
- |
-
- K94
- |
-
- *071917.53
- |
-
- BXD74
- |
-
- M
- |
-
- 427
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 100
- |
-
- K95
- |
-
- *071917.48
- |
-
- BXD73b
- |
-
- F
- |
-
- 422
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 101
- |
-
- K96
- |
-
- *071917.52
- |
-
- BXD74
- |
-
- F
- |
-
- 427
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 102
- |
-
- K97
- |
-
- *062117.36
- |
-
- BXD84
- |
-
- F
- |
-
- 441
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 103
- |
-
- K98
- |
-
- *103017.58
- |
-
- BXD111
- |
-
- M
- |
-
- 441
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 104
- |
-
- K99
- |
-
- *103017.57
- |
-
- BXD111
- |
-
- F
- |
-
- 441
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 105
- |
-
- K9
- |
-
- *062117.33
- |
-
- BXD77
- |
-
- F
- |
-
- 355
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
-
diff --git a/general/datasets/NHLBI_BXD_Aged_Heart_CD_RNA_Seq_1120/tissue.rtf b/general/datasets/NHLBI_BXD_Aged_Heart_CD_RNA_Seq_1120/tissue.rtf
deleted file mode 100644
index 8d370c0..0000000
--- a/general/datasets/NHLBI_BXD_Aged_Heart_CD_RNA_Seq_1120/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Tissue Harvest
-
-The animals were sacrificed under saturated isoflurane. Whole heart from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/NHLBI_BXD_Aged_Heart_HFD_RNA_Seq_1120/experiment-design.rtf b/general/datasets/NHLBI_BXD_Aged_Heart_HFD_RNA_Seq_1120/experiment-design.rtf
deleted file mode 100644
index fbdad24..0000000
--- a/general/datasets/NHLBI_BXD_Aged_Heart_HFD_RNA_Seq_1120/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA Extraction
-
-Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Approximately 30 mg of left ventricle tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/NHLBI_BXD_Aged_Heart_HFD_RNA_Seq_1120/processing.rtf b/general/datasets/NHLBI_BXD_Aged_Heart_HFD_RNA_Seq_1120/processing.rtf
deleted file mode 100644
index 8e460ff..0000000
--- a/general/datasets/NHLBI_BXD_Aged_Heart_HFD_RNA_Seq_1120/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/NHLBI_BXD_Aged_Heart_HFD_RNA_Seq_1120/specifics.rtf b/general/datasets/NHLBI_BXD_Aged_Heart_HFD_RNA_Seq_1120/specifics.rtf
deleted file mode 100644
index 49d8e5b..0000000
--- a/general/datasets/NHLBI_BXD_Aged_Heart_HFD_RNA_Seq_1120/specifics.rtf
+++ /dev/null
@@ -1,1758 +0,0 @@
-NHLBI BXD Aged Heart HFD RNA-Seq (Nov20) TMP Log2
-
-About the cases used to generate this set of data:
-
-The study included 66 mice (~12 month) from B6, B6D2F1, D2B6F1, and 31 advanced intercross BXD strains (about 2 mice per strain). All mice were fed on high fat diet (HFD). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
-
-
-
-The table of samples that are finally used for this study.
-
-
-
-
- |
- Index
- |
-
- Sample ID
- |
-
- Case id
- |
-
- Strain
- |
-
- Fuyi_Sex_Final
- |
-
- Sac age/Day
- |
-
- Tissue
- |
-
- Diet
- |
-
-
- |
- 1
- |
-
- A12
- |
-
- 042214.06
- |
-
- BXD29
- |
-
- F
- |
-
- 369
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 2
- |
-
- A13
- |
-
- 042214.13
- |
-
- BXD86
- |
-
- F
- |
-
- 360
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 3
- |
-
- A14
- |
-
- 042214.14
- |
-
- BXD86
- |
-
- F
- |
-
- 360
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 4
- |
-
- A15
- |
-
- 042314.15
- |
-
- C57BL/6J
- |
-
- M
- |
-
- 363
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 5
- |
-
- A16
- |
-
- 042314.16
- |
-
- C57BL/6J
- |
-
- M
- |
-
- 363
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 6
- |
-
- A17
- |
-
- 042314.08
- |
-
- B6D2F1
- |
-
- M
- |
-
- 404
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 7
- |
-
- A18
- |
-
- 042314.07
- |
-
- B6D2F1
- |
-
- M
- |
-
- 404
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 8
- |
-
- A19
- |
-
- 042314.05
- |
-
- BXD64
- |
-
- F
- |
-
- 366
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 9
- |
-
- A20
- |
-
- 042314.06
- |
-
- BXD64
- |
-
- F
- |
-
- 366
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 10
- |
-
- A21
- |
-
- 042314.03
- |
-
- BXD100
- |
-
- F
- |
-
- 363
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 11
- |
-
- A22
- |
-
- 042314.04
- |
-
- BXD100
- |
-
- F
- |
-
- 363
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 12
- |
-
- A23
- |
-
- 042314.02
- |
-
- D2B6F1
- |
-
- F
- |
-
- 371
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 13
- |
-
- A24
- |
-
- 042314.01
- |
-
- D2B6F1
- |
-
- F
- |
-
- 371
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 14
- |
-
- A25
- |
-
- 021313.30
- |
-
- BXD87
- |
-
- F
- |
-
- 359
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 15
- |
-
- A26
- |
-
- 021313.29
- |
-
- BXD87
- |
-
- F
- |
-
- 359
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 16
- |
-
- A27
- |
-
- 042915.06
- |
-
- BXD29
- |
-
- F
- |
-
- 431
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 17
- |
-
- A28
- |
-
- 050115.03
- |
-
- BXD65b
- |
-
- F
- |
-
- 415
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 18
- |
-
- A29
- |
-
- 042915.10
- |
-
- BXD32
- |
-
- F
- |
-
- 441
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 19
- |
-
- A2
- |
-
- 042415.14
- |
-
- BXD102
- |
-
- F
- |
-
- 353
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 20
- |
-
- A30
- |
-
- 050115.04
- |
-
- BXD65b
- |
-
- F
- |
-
- 415
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 21
- |
-
- A31
- |
-
- 121515.16
- |
-
- BXD45
- |
-
- F
- |
-
- 350
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 22
- |
-
- A32
- |
-
- 012615.22
- |
-
- BXD50
- |
-
- F
- |
-
- 361
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 23
- |
-
- A33
- |
-
- 012615.21
- |
-
- BXD50
- |
-
- F
- |
-
- 361
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 24
- |
-
- A34
- |
-
- 121515.17
- |
-
- BXD45
- |
-
- F
- |
-
- 350
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 25
- |
-
- A36
- |
-
- 012615.13
- |
-
- BXD44
- |
-
- F
- |
-
- 379
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 26
- |
-
- A37
- |
-
- 012615.24
- |
-
- BXD75
- |
-
- F
- |
-
- 367
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 27
- |
-
- A3
- |
-
- 090512.12
- |
-
- BXD77
- |
-
- F
- |
-
- 353
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 28
- |
-
- A40
- |
-
- 012615.23
- |
-
- BXD75
- |
-
- F
- |
-
- 367
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 29
- |
-
- A41
- |
-
- 042915.16
- |
-
- BXD48a
- |
-
- F
- |
-
- 436
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 30
- |
-
- A42
- |
-
- 042915.15
- |
-
- BXD48a
- |
-
- F
- |
-
- 436
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 31
- |
-
- A43
- |
-
- 111414.15
- |
-
- BXD102
- |
-
- F
- |
-
- 351
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 32
- |
-
- A44
- |
-
- 012615.12
- |
-
- BXD44
- |
-
- F
- |
-
- 379
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 33
- |
-
- A45
- |
-
- 121214.12
- |
-
- BXD73
- |
-
- F
- |
-
- 361
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 34
- |
-
- A49
- |
-
- 121214.14
- |
-
- BXD40
- |
-
- F
- |
-
- 358
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 35
- |
-
- A4
- |
-
- 090512.11
- |
-
- BXD77
- |
-
- F
- |
-
- 353
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 36
- |
-
- A50
- |
-
- 010614.21
- |
-
- BXD90
- |
-
- F
- |
-
- 343
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 37
- |
-
- A51
- |
-
- 121214.04
- |
-
- BXD66
- |
-
- F
- |
-
- 367
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 38
- |
-
- A52
- |
-
- 121214.13
- |
-
- BXD40
- |
-
- F
- |
-
- 358
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 39
- |
-
- A53
- |
-
- 121214.11
- |
-
- BXD73
- |
-
- F
- |
-
- 361
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 40
- |
-
- A54
- |
-
- 021213.24
- |
-
- BXD84
- |
-
- F
- |
-
- 343
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 41
- |
-
- A55
- |
-
- 021213.18
- |
-
- BXD69
- |
-
- F
- |
-
- 347
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 42
- |
-
- A56
- |
-
- 021213.17
- |
-
- BXD69
- |
-
- F
- |
-
- 347
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 43
- |
-
- A57
- |
-
- 021213.16
- |
-
- BXD62
- |
-
- F
- |
-
- 343
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 44
- |
-
- A58
- |
-
- 021213.15
- |
-
- BXD62
- |
-
- F
- |
-
- 343
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 45
- |
-
- A59
- |
-
- 021113.11
- |
-
- BXD51
- |
-
- F
- |
-
- 357
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 46
- |
-
- A60
- |
-
- 010614.14
- |
-
- BXD65
- |
-
- F
- |
-
- 367
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 47
- |
-
- A61
- |
-
- 010614.13
- |
-
- BXD65
- |
-
- F
- |
-
- 367
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 48
- |
-
- A62
- |
-
- 021213.23
- |
-
- BXD84
- |
-
- F
- |
-
- 343
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 49
- |
-
- A63
- |
-
- 090514.03
- |
-
- BXD43
- |
-
- F
- |
-
- 367
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 50
- |
-
- A64
- |
-
- 090514.04
- |
-
- BXD43
- |
-
- F
- |
-
- 367
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 51
- |
-
- A65
- |
-
- 010614.22
- |
-
- BXD90
- |
-
- F
- |
-
- 343
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 52
- |
-
- A66
- |
-
- 010614.17
- |
-
- BXD73b
- |
-
- F
- |
-
- 385
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 53
- |
-
- A68
- |
-
- 121214.22
- |
-
- BXD39
- |
-
- F
- |
-
- 350
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 54
- |
-
- A69
- |
-
- 121214.21
- |
-
- BXD39
- |
-
- F
- |
-
- 350
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 55
- |
-
- A6
- |
-
- 090512.08
- |
-
- BXD66
- |
-
- F
- |
-
- 359
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 56
- |
-
- A70
- |
-
- 121214.18
- |
-
- BXD70
- |
-
- F
- |
-
- 357
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 57
- |
-
- A71
- |
-
- 121214.17
- |
-
- BXD70
- |
-
- F
- |
-
- 357
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 58
- |
-
- A72
- |
-
- 021313.33
- |
-
- BXD98
- |
-
- F
- |
-
- 360
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 59
- |
-
- A73
- |
-
- 021313.34
- |
-
- BXD98
- |
-
- F
- |
-
- 360
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 60
- |
-
- A74
- |
-
- 092216.09
- |
-
- BXD27
- |
-
- F
- |
-
- 387
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 61
- |
-
- A75
- |
-
- 092216.10
- |
-
- BXD27
- |
-
- F
- |
-
- 387
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 62
- |
-
- A77
- |
-
- 121615.02
- |
-
- BXD61
- |
-
- F
- |
-
- 364
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 63
- |
-
- A78
- |
-
- 121615.01
- |
-
- BXD61
- |
-
- F
- |
-
- 364
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 64
- |
-
- A7
- |
-
- 090512.01
- |
-
- BXD9
- |
-
- F
- |
-
- 347
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 65
- |
-
- A8
- |
-
- 090512.02
- |
-
- BXD9
- |
-
- F
- |
-
- 349
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
- |
- 66
- |
-
- A97
- |
-
- 050115.11
- |
-
- BXD73b
- |
-
- F
- |
-
- 474
- |
-
- Heart
- |
-
- High fat diet
- |
-
-
-
-
-
diff --git a/general/datasets/NHLBI_BXD_Aged_Heart_HFD_RNA_Seq_1120/tissue.rtf b/general/datasets/NHLBI_BXD_Aged_Heart_HFD_RNA_Seq_1120/tissue.rtf
deleted file mode 100644
index 8d370c0..0000000
--- a/general/datasets/NHLBI_BXD_Aged_Heart_HFD_RNA_Seq_1120/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Tissue Harvest
-
-The animals were sacrificed under saturated isoflurane. Whole heart from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/NHLBI_BXD_All_Ages_Heart_RNA_Seq_1120/experiment-design.rtf b/general/datasets/NHLBI_BXD_All_Ages_Heart_RNA_Seq_1120/experiment-design.rtf
deleted file mode 100644
index fbdad24..0000000
--- a/general/datasets/NHLBI_BXD_All_Ages_Heart_RNA_Seq_1120/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA Extraction
-
-Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Approximately 30 mg of left ventricle tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/NHLBI_BXD_All_Ages_Heart_RNA_Seq_1120/processing.rtf b/general/datasets/NHLBI_BXD_All_Ages_Heart_RNA_Seq_1120/processing.rtf
deleted file mode 100644
index 8e460ff..0000000
--- a/general/datasets/NHLBI_BXD_All_Ages_Heart_RNA_Seq_1120/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/NHLBI_BXD_All_Ages_Heart_RNA_Seq_1120/specifics.rtf b/general/datasets/NHLBI_BXD_All_Ages_Heart_RNA_Seq_1120/specifics.rtf
deleted file mode 100644
index 55635fc..0000000
--- a/general/datasets/NHLBI_BXD_All_Ages_Heart_RNA_Seq_1120/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NHLBI BXD All Ages Heart RNA-Seq (Nov20) TMP Log2
\ No newline at end of file
diff --git a/general/datasets/NHLBI_BXD_All_Ages_Heart_RNA_Seq_1120/tissue.rtf b/general/datasets/NHLBI_BXD_All_Ages_Heart_RNA_Seq_1120/tissue.rtf
deleted file mode 100644
index 8d370c0..0000000
--- a/general/datasets/NHLBI_BXD_All_Ages_Heart_RNA_Seq_1120/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Tissue Harvest
-
-The animals were sacrificed under saturated isoflurane. Whole heart from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_CMS_RNA/experiment-design.rtf b/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_CMS_RNA/experiment-design.rtf
deleted file mode 100644
index fbdad24..0000000
--- a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_CMS_RNA/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA Extraction
-
-Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Approximately 30 mg of left ventricle tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_CMS_RNA/processing.rtf b/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_CMS_RNA/processing.rtf
deleted file mode 100644
index 8e460ff..0000000
--- a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_CMS_RNA/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_CMS_RNA/specifics.rtf b/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_CMS_RNA/specifics.rtf
deleted file mode 100644
index 24b6e71..0000000
--- a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_CMS_RNA/specifics.rtf
+++ /dev/null
@@ -1,1907 +0,0 @@
-NHLBI BXD Young Adult Heart CD CMS RNA-Seq (Nov20) TMP Log2
-
-About the cases used to generate this set of data:
-
-The study included 64 mice (~6 month) from B6, D2, and 32 advanced intercross BXD strains (about 2 mice per strain). All mice were fed on chow diet (CD) and treated with chronic mild stress (CMS). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
-
-
-
-Chronic Mild Stress (CMS)
-
-During a period of 7 weeks, mice received 2 disturbances per day. These consisted of being exposed to wet bedding for 1 hour, 1 cm of water in the bottom of the cage with no bedding for 1 hour, no bedding for 1 hour, confinement in a 3 × 3 × 3 cm plastic box for 15 minutes, tilted cage at 45º for 1 hour, and exposure to foreign mouse or fox urine odor for 1 hour. The other stressor was a complete phase shift in the light:dark cycle over each weekend. Disruption of the light cycle (lights constantly on) occurred over the weekend (starting Friday 11:00 am) with the light cycle resuming at 11 am on Monday (lights off). The schedule was repeated weekly over the duration of the study.
-
-
-
-
-
-The table of samples that are finally used for this study.
-
-
-
-
- |
- Index
- |
-
- Sample ID
- |
-
- Case id
- |
-
- Strain
- |
-
- Fuyi_Sex_Final
- |
-
- Sac age/Day
- |
-
- Tissue
- |
-
- Diet
- |
-
- Treatment
- |
-
-
- |
- 1
- |
-
- C100
- |
-
- 090215.15
- |
-
- BXD68
- |
-
- F
- |
-
- 185
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 2
- |
-
- C101
- |
-
- 090215.16
- |
-
- BXD48
- |
-
- F
- |
-
- 171
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 3
- |
-
- C102
- |
-
- 090215.20
- |
-
- BXD79
- |
-
- F
- |
-
- 162
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 4
- |
-
- C103
- |
-
- 090215.21
- |
-
- BXD63
- |
-
- F
- |
-
- 169
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 5
- |
-
- C104
- |
-
- 090215.24
- |
-
- BXD32
- |
-
- F
- |
-
- 188
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 6
- |
-
- C105
- |
-
- 090215.28
- |
-
- BXD63
- |
-
- F
- |
-
- 169
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 7
- |
-
- C10
- |
-
- CMS102816.14
- |
-
- BXD77
- |
-
- F
- |
-
- 124
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 8
- |
-
- C112
- |
-
- CMS032917.33
- |
-
- BXD70
- |
-
- F
- |
-
- 162
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 9
- |
-
- C118
- |
-
- CMS082917.05
- |
-
- BXD77
- |
-
- F
- |
-
- 196
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 10
- |
-
- C11
- |
-
- CMS102816.15
- |
-
- BXD73b
- |
-
- F
- |
-
- 163
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 11
- |
-
- C13
- |
-
- CMS102816.17
- |
-
- BXD100
- |
-
- F
- |
-
- 139
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 12
- |
-
- C14
- |
-
- CMS102816.18
- |
-
- BXD43
- |
-
- F
- |
-
- 155
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 13
- |
-
- C15
- |
-
- CMS102816.19
- |
-
- BXD83
- |
-
- F
- |
-
- 168
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 14
- |
-
- C17
- |
-
- CMS102816.21
- |
-
- BXD65
- |
-
- F
- |
-
- 163
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 15
- |
-
- C19
- |
-
- CMS102816.05
- |
-
- DBA/2J
- |
-
- F
- |
-
- 156
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 16
- |
-
- C1
- |
-
- CMS082817.05
- |
-
- BXD48
- |
-
- F
- |
-
- 174
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 17
- |
-
- C21
- |
-
- CMS102816.07
- |
-
- DBA/2J
- |
-
- F
- |
-
- 156
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 18
- |
-
- C23
- |
-
- CMS102816.09
- |
-
- C57BL/6J
- |
-
- F
- |
-
- 159
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 19
- |
-
- C25
- |
-
- CMS102816.11
- |
-
- BXD100
- |
-
- F
- |
-
- 139
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 20
- |
-
- C28
- |
-
- CMS102716.16
- |
-
- BXD77
- |
-
- F
- |
-
- 123
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 21
- |
-
- C2
- |
-
- CMS083017.19
- |
-
- BXD24
- |
-
- F
- |
-
- 171
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 22
- |
-
- C30
- |
-
- CMS102716.19
- |
-
- BXD73a
- |
-
- F
- |
-
- 121
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 23
- |
-
- C31
- |
-
- CMS102716.20
- |
-
- BXD50
- |
-
- F
- |
-
- 161
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 24
- |
-
- C32
- |
-
- CMS102716.01
- |
-
- BXD83
- |
-
- F
- |
-
- 167
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 25
- |
-
- C34
- |
-
- CMS102716.10
- |
-
- BXD43
- |
-
- F
- |
-
- 144
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 26
- |
-
- C35
- |
-
- CMS102716.12
- |
-
- BXD62
- |
-
- F
- |
-
- 144
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 27
- |
-
- C36
- |
-
- CMS102716.03
- |
-
- BXD73a
- |
-
- F
- |
-
- 121
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 28
- |
-
- C38
- |
-
- CMS102716.06
- |
-
- BXD34
- |
-
- M
- |
-
- 157
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 29
- |
-
- C39
- |
-
- CMS102716.07
- |
-
- BXD24
- |
-
- F
- |
-
- 157
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 30
- |
-
- C3
- |
-
- CMS083017.18
- |
-
- BXD87
- |
-
- F
- |
-
- 174
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 31
- |
-
- C40
- |
-
- CMS102716.08
- |
-
- BXD60
- |
-
- F
- |
-
- 155
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 32
- |
-
- C41
- |
-
- CMS102716.09
- |
-
- BXD60
- |
-
- F
- |
-
- 142
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 33
- |
-
- C44
- |
-
- CMS033017.25
- |
-
- BXD78
- |
-
- F
- |
-
- 163
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 34
- |
-
- C45
- |
-
- CMS032817.28
- |
-
- BXD66
- |
-
- F
- |
-
- 168
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 35
- |
-
- C46
- |
-
- CMS032817.23
- |
-
- BXD86
- |
-
- F
- |
-
- 179
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 36
- |
-
- C47
- |
-
- CMS082817.24
- |
-
- BXD51
- |
-
- F
- |
-
- 186
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 37
- |
-
- C48
- |
-
- CMS082817.14
- |
-
- BXD65
- |
-
- F
- |
-
- 182
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 38
- |
-
- C49
- |
-
- CMS082817.07
- |
-
- BXD44
- |
-
- F
- |
-
- 202
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 39
- |
-
- C56
- |
-
- CMS102716.13
- |
-
- BXD77
- |
-
- F
- |
-
- 151
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 40
- |
-
- C60
- |
-
- CMS032917.33
- |
-
- BXD70
- |
-
- F
- |
-
- 162
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 41
- |
-
- C61
- |
-
- CMS032917.29
- |
-
- BXD71
- |
-
- F
- |
-
- 162
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 42
- |
-
- C62
- |
-
- CMS032917.26
- |
-
- BXD87
- |
-
- F
- |
-
- 173
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 43
- |
-
- C63
- |
-
- CMS032917.22
- |
-
- BXD71
- |
-
- F
- |
-
- 170
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 44
- |
-
- C64
- |
-
- CMS083017.07
- |
-
- BXD69
- |
-
- F
- |
-
- 202
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 45
- |
-
- C65
- |
-
- CMS082917.19
- |
-
- BXD44
- |
-
- F
- |
-
- 182
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 46
- |
-
- C66
- |
-
- CMS030716.03
- |
-
- BXD101
- |
-
- F
- |
-
- 196
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 47
- |
-
- C67
- |
-
- CMS030716.06
- |
-
- BXD69
- |
-
- F
- |
-
- 193
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 48
- |
-
- C68
- |
-
- CMS030716.12
- |
-
- BXD68
- |
-
- F
- |
-
- 166
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 49
- |
-
- C69
- |
-
- CMS030716.13
- |
-
- BXD55
- |
-
- F
- |
-
- 166
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 50
- |
-
- C70
- |
-
- CMS030716.18
- |
-
- BXD40
- |
-
- F
- |
-
- 182
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 51
- |
-
- C71
- |
-
- CMS030716.19
- |
-
- BXD40
- |
-
- F
- |
-
- 182
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 52
- |
-
- C73
- |
-
- CMS030716.32
- |
-
- BXD101
- |
-
- F
- |
-
- 196
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 53
- |
-
- C75
- |
-
- CMS030916.11
- |
-
- BXD79
- |
-
- F
- |
-
- 167
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 54
- |
-
- C76
- |
-
- CMS030916.14
- |
-
- BXD48a
- |
-
- F
- |
-
- 168
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 55
- |
-
- C77
- |
-
- CMS030916.20
- |
-
- BXD65b
- |
-
- F
- |
-
- 190
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 56
- |
-
- C79
- |
-
- CMS030916.23
- |
-
- BXD65b
- |
-
- F
- |
-
- 182
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 57
- |
-
- C80
- |
-
- CMS030916.28
- |
-
- BXD66
- |
-
- F
- |
-
- 162
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 58
- |
-
- C81
- |
-
- CMS030916.32
- |
-
- BXD86
- |
-
- F
- |
-
- 193
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 59
- |
-
- C84
- |
-
- CMS102816.03
- |
-
- C57BL/6J
- |
-
- F
- |
-
- 159
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 60
- |
-
- C85
- |
-
- CMS102716.11
- |
-
- BXD34
- |
-
- F
- |
-
- 157
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 61
- |
-
- C96
- |
-
- 090215.02
- |
-
- BXD62
- |
-
- F
- |
-
- 137
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 62
- |
-
- C97
- |
-
- 090215.05
- |
-
- BXD75
- |
-
- F
- |
-
- 180
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 63
- |
-
- C98
- |
-
- 090215.06
- |
-
- BXD32
- |
-
- F
- |
-
- 188
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
- |
- 64
- |
-
- C99
- |
-
- 090215.09
- |
-
- BXD75
- |
-
- F
- |
-
- 180
- |
-
- Heart
- |
-
- Chow diet
- |
-
- CMS
- |
-
-
-
diff --git a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_CMS_RNA/tissue.rtf b/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_CMS_RNA/tissue.rtf
deleted file mode 100644
index 8d370c0..0000000
--- a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_CMS_RNA/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Tissue Harvest
-
-The animals were sacrificed under saturated isoflurane. Whole heart from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_RNA_Seq/experiment-design.rtf b/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_RNA_Seq/experiment-design.rtf
deleted file mode 100644
index fbdad24..0000000
--- a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_RNA_Seq/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA Extraction
-
-Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Approximately 30 mg of left ventricle tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_RNA_Seq/processing.rtf b/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_RNA_Seq/processing.rtf
deleted file mode 100644
index 8e460ff..0000000
--- a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_RNA_Seq/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_RNA_Seq/specifics.rtf b/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_RNA_Seq/specifics.rtf
deleted file mode 100644
index 96fa0b5..0000000
--- a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_RNA_Seq/specifics.rtf
+++ /dev/null
@@ -1,2302 +0,0 @@
-NHLBI BXD Young Adult Heart CD RNA-Seq (Nov20) TMP Log2
-
-About the cases used to generate this set of data:
-
-The study included 87 mice (~6 month) from B6, D2, and 41 advanced intercross BXD strains (about 2 mice per strain). All mice were fed on chow diet (CD). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
-
-
-
-The table of samples that are finally used for this study.
-
-
-
-
- |
- Index
- |
-
- Sample ID
- |
-
- Case id
- |
-
- Strain
- |
-
- Fuyi_Sex_Final
- |
-
- Age (Day)
- |
-
- Tissue
- |
-
- Diet
- |
-
-
- |
- 1
- |
-
- H100
- |
-
- *091317.07
- |
-
- BXD61
- |
-
- M
- |
-
- 128
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 2
- |
-
- H101
- |
-
- *052417.59
- |
-
- BXD177
- |
-
- F
- |
-
- 125
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 3
- |
-
- H102
- |
-
- *052417.26
- |
-
- BXD73a
- |
-
- F
- |
-
- 141
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 4
- |
-
- H103
- |
-
- *060717.02
- |
-
- BXD9
- |
-
- M
- |
-
- 149
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 5
- |
-
- H109
- |
-
- *052417.49
- |
-
- BXD152
- |
-
- F
- |
-
- 147
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 6
- |
-
- H110
- |
-
- *052417.35
- |
-
- BXD86
- |
-
- F
- |
-
- 127
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 7
- |
-
- H112
- |
-
- *052417.24
- |
-
- BXD73
- |
-
- F
- |
-
- 173
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 8
- |
-
- H113
- |
-
- *052417.25
- |
-
- BXD73
- |
-
- M
- |
-
- 173
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 9
- |
-
- H116
- |
-
- *121917.28
- |
-
- BXD180
- |
-
- F
- |
-
- 120
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 10
- |
-
- H11
- |
-
- *121917.20
- |
-
- BXD111
- |
-
- M
- |
-
- 122
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 11
- |
-
- H120
- |
-
- *111417.04
- |
-
- BXD40
- |
-
- M
- |
-
- 133
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 12
- |
-
- H121
- |
-
- *091317.02
- |
-
- BXD48a
- |
-
- M
- |
-
- 125
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 13
- |
-
- H122
- |
-
- *092717.59
- |
-
- BXD154
- |
-
- F
- |
-
- 135
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 14
- |
-
- H124
- |
-
- *092717.60
- |
-
- BXD154
- |
-
- F
- |
-
- 135
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 15
- |
-
- H126
- |
-
- *092717.65
- |
-
- BXD155
- |
-
- F
- |
-
- 133
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 16
- |
-
- H127
- |
-
- *092717.67
- |
-
- BXD169
- |
-
- M
- |
-
- 133
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 17
- |
-
- H129
- |
-
- *092717.37
- |
-
- BXD78
- |
-
- F
- |
-
- 133
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 18
- |
-
- H12
- |
-
- *121917.21
- |
-
- BXD111
- |
-
- M
- |
-
- 122
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 19
- |
-
- H130
- |
-
- AGE050118.27
- |
-
- DBA/2J
- |
-
- F
- |
-
- 167
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 20
- |
-
- H131
- |
-
- AGE050118.28
- |
-
- DBA/2J
- |
-
- F
- |
-
- 167
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 21
- |
-
- H132
- |
-
- AGE050118.29
- |
-
- DBA/2J
- |
-
- M
- |
-
- 167
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 22
- |
-
- H138
- |
-
- *112118.32
- |
-
- C57BL/6J
- |
-
- F
- |
-
- 208
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 23
- |
-
- H139
- |
-
- *112118.33
- |
-
- C57BL/6J
- |
-
- F
- |
-
- 208
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 24
- |
-
- H140
- |
-
- *112118.34
- |
-
- C57BL/6J
- |
-
- F
- |
-
- 208
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 25
- |
-
- H14
- |
-
- *092017.36
- |
-
- BXD113
- |
-
- F
- |
-
- 132
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 26
- |
-
- H15
- |
-
- *092017.37
- |
-
- BXD113
- |
-
- M
- |
-
- 132
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 27
- |
-
- H16
- |
-
- *060717.15
- |
-
- BXD123
- |
-
- F
- |
-
- 182
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 28
- |
-
- H17
- |
-
- *060717.16
- |
-
- BXD123
- |
-
- M
- |
-
- 182
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 29
- |
-
- H19
- |
-
- *052417.44
- |
-
- BXD128 (WAS b)
- |
-
- F
- |
-
- 161
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 30
- |
-
- H20
- |
-
- *052417.45
- |
-
- BXD128 (WAS b)
- |
-
- F
- |
-
- 161
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 31
- |
-
- H21
- |
-
- *092017.38
- |
-
- BXD144
- |
-
- F
- |
-
- 133
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 32
- |
-
- H23
- |
-
- *092017.39
- |
-
- BXD144
- |
-
- M
- |
-
- 133
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 33
- |
-
- H25
- |
-
- *060717.03
- |
-
- BXD15
- |
-
- F
- |
-
- 143
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 34
- |
-
- H26
- |
-
- *060717.04
- |
-
- BXD15
- |
-
- F
- |
-
- 143
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 35
- |
-
- H27
- |
-
- *052417.47
- |
-
- BXD151
- |
-
- F
- |
-
- 127
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 36
- |
-
- H28
- |
-
- *092017.40
- |
-
- BXD151
- |
-
- M
- |
-
- 133
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 37
- |
-
- H30
- |
-
- *052417.51
- |
-
- BXD152
- |
-
- M
- |
-
- 147
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 38
- |
-
- H31
- |
-
- *052417.54
- |
-
- BXD155
- |
-
- M
- |
-
- 119
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 39
- |
-
- H32
- |
-
- *091317.01
- |
-
- BXD16
- |
-
- F
- |
-
- 128
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 40
- |
-
- H33
- |
-
- *111417.11
- |
-
- BXD169
- |
-
- F
- |
-
- 121
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 41
- |
-
- H36
- |
-
- *121917.16
- |
-
- BXD171
- |
-
- F
- |
-
- 124
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 42
- |
-
- H38
- |
-
- *092017.41
- |
-
- BXD171
- |
-
- M
- |
-
- 133
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 43
- |
-
- H41
- |
-
- *052417.60
- |
-
- BXD177
- |
-
- M
- |
-
- 125
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 44
- |
-
- H43
- |
-
- *052417.62
- |
-
- BXD180
- |
-
- M
- |
-
- 119
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 45
- |
-
- H44
- |
-
- *052417.32
- |
-
- BXD83
- |
-
- F
- |
-
- 155
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 46
- |
-
- H46
- |
-
- *052417.28
- |
-
- BXD73a
- |
-
- M
- |
-
- 141
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 47
- |
-
- H48
- |
-
- *052417.40
- |
-
- BXD89
- |
-
- M
- |
-
- 173
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 48
- |
-
- H49
- |
-
- *060717.09
- |
-
- BXD63
- |
-
- F
- |
-
- 160
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 49
- |
-
- H50
- |
-
- *060717.06
- |
-
- BXD24
- |
-
- M
- |
-
- 138
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 50
- |
-
- H51
- |
-
- *060717.07
- |
-
- BXD48
- |
-
- F
- |
-
- 134
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 51
- |
-
- H52
- |
-
- *060717.08
- |
-
- BXD48
- |
-
- F
- |
-
- 134
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 52
- |
-
- H53
- |
-
- *060717.11
- |
-
- BXD63
- |
-
- M
- |
-
- 160
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 53
- |
-
- H54
- |
-
- *052417.22
- |
-
- BXD62
- |
-
- M
- |
-
- 165
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 54
- |
-
- H55
- |
-
- *052417.17
- |
-
- BXD51
- |
-
- F
- |
-
- 154
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 55
- |
-
- H56
- |
-
- *052417.15
- |
-
- BXD50
- |
-
- F
- |
-
- 167
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 56
- |
-
- H57
- |
-
- *052417.08
- |
-
- BXD32
- |
-
- M
- |
-
- 156
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 57
- |
-
- H59
- |
-
- *052417.21
- |
-
- BXD62
- |
-
- F
- |
-
- 165
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 58
- |
-
- H60
- |
-
- *052417.19
- |
-
- BXD51
- |
-
- M
- |
-
- 154
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 59
- |
-
- H61
- |
-
- *052417.16
- |
-
- BXD50
- |
-
- M
- |
-
- 167
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 60
- |
-
- H62
- |
-
- *052417.37
- |
-
- BXD86
- |
-
- M
- |
-
- 127
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 61
- |
-
- H63
- |
-
- *052417.29
- |
-
- BXD73b
- |
-
- F
- |
-
- 145
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 62
- |
-
- H64
- |
-
- *052417.31
- |
-
- BXD73b
- |
-
- M
- |
-
- 145
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 63
- |
-
- H65
- |
-
- *121917.01
- |
-
- BXD43
- |
-
- F
- |
-
- 126
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 64
- |
-
- H66
- |
-
- *121917.13
- |
-
- BXD45
- |
-
- M
- |
-
- 126
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 65
- |
-
- H67
- |
-
- *121917.12
- |
-
- BXD45
- |
-
- F
- |
-
- 126
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 66
- |
-
- H68
- |
-
- *121917.02
- |
-
- BXD43
- |
-
- F
- |
-
- 126
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 67
- |
-
- H69
- |
-
- *071917.35
- |
-
- BXD68
- |
-
- M
- |
-
- 134
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 68
- |
-
- H71
- |
-
- *092017.32
- |
-
- BXD83
- |
-
- M
- |
-
- 136
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 69
- |
-
- H72
- |
-
- *092017.30
- |
-
- BXD78
- |
-
- M
- |
-
- 132
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 70
- |
-
- H74
- |
-
- *092017.29
- |
-
- BXD75
- |
-
- M
- |
-
- 133
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 71
- |
-
- H76
- |
-
- *092017.26
- |
-
- BXD75
- |
-
- F
- |
-
- 133
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 72
- |
-
- H78
- |
-
- *092017.05
- |
-
- BXD40
- |
-
- F
- |
-
- 128
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 73
- |
-
- H79
- |
-
- *092017.02
- |
-
- BXD24
- |
-
- F
- |
-
- 131
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 74
- |
-
- H80
- |
-
- *092017.01
- |
-
- BXD9
- |
-
- F
- |
-
- 129
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 75
- |
-
- H81
- |
-
- *092017.12
- |
-
- BXD65
- |
-
- F
- |
-
- 132
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 76
- |
-
- H83
- |
-
- *092017.33
- |
-
- BXD89
- |
-
- F
- |
-
- 136
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 77
- |
-
- H84
- |
-
- *092017.23
- |
-
- BXD70
- |
-
- F
- |
-
- 130
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 78
- |
-
- H85
- |
-
- *092017.22
- |
-
- BXD70
- |
-
- F
- |
-
- 127
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 79
- |
-
- H86
- |
-
- *092017.07
- |
-
- BXD44
- |
-
- F
- |
-
- 128
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 80
- |
-
- H89
- |
-
- *092017.14
- |
-
- BXD65
- |
-
- M
- |
-
- 132
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 81
- |
-
- H90
- |
-
- *092017.03
- |
-
- BXD32
- |
-
- F
- |
-
- 131
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 82
- |
-
- H91
- |
-
- *092017.20
- |
-
- BXD65b
- |
-
- M
- |
-
- 130
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 83
- |
-
- H92
- |
-
- *092017.09
- |
-
- BXD44
- |
-
- F
- |
-
- 128
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 84
- |
-
- H94
- |
-
- *092017.18
- |
-
- BXD65b
- |
-
- F
- |
-
- 130
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 85
- |
-
- H96
- |
-
- *091317.06
- |
-
- BXD61
- |
-
- M
- |
-
- 128
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 86
- |
-
- H97
- |
-
- *091317.12
- |
-
- BXD68
- |
-
- F
- |
-
- 132
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
- |
- 87
- |
-
- H99
- |
-
- *091317.04
- |
-
- BXD48a
- |
-
- M
- |
-
- 125
- |
-
- Heart
- |
-
- Chow diet
- |
-
-
-
diff --git a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_RNA_Seq/tissue.rtf b/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_RNA_Seq/tissue.rtf
deleted file mode 100644
index 8d370c0..0000000
--- a/general/datasets/NHLBI_BXD_Young_Adult_Heart_CD_RNA_Seq/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Tissue Harvest
-
-The animals were sacrificed under saturated isoflurane. Whole heart from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/cases.rtf b/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/cases.rtf
deleted file mode 100644
index 08a20a8..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/cases.rtf
+++ /dev/null
@@ -1,4848 +0,0 @@
-The study included 241 females (aged 50 to 90 ± 2 days at the start of the experiment) from B6, D2, and 35 advanced intercross BXD strains (about 2 mice per strain and per condition). Mice were divided into 4 groups of Control (CTL, 53 mice for 31 strains), Chronic Mild Stress (CMS, 64 mice for 32 strains), Drinking in Dark (DID, 64 mice for 35 strains), and CMS+DID (60 mice for 35 strains). Mice in CTL were normally handled, while mice in other groups were singly housed in shoebox cages, with food and water provided ad libitum except when the water was replaced by 20% (v/v) EtOH (see below) for DID and CMS+DID groups (detailed treatments and schemes are showing in the Table and Figure). The ambient temperature was 21 ± 2°C, and the light cycle was 7:00/19:00 for CTL, and 23:00/11:00 the rest groups lights on/off. The animals were weighed weekly to assess health and to provide the basis for calculating the amount of EtOH consumed in grams per kilogram. All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
-
-The table of samples that are finally used for this study.
-
-
-
-
- |
- Index
- |
-
- ID
- |
-
- Strain
- |
-
- Sex
- |
-
- Treatment Group
- |
-
- Tissue
- |
-
-
- |
- 1
- |
-
- CMS030716_12
- |
-
- BXD68
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 2
- |
-
- CMS030716_18
- |
-
- BXD40
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 3
- |
-
- CMS030716_19
- |
-
- BXD40
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 4
- |
-
- CMS030916_02
- |
-
- BXD101
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 5
- |
-
- CMS030916_09
- |
-
- BXD101
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 6
- |
-
- CMS030916_11
- |
-
- BXD79
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 7
- |
-
- CMS030916_14
- |
-
- BXD48a
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 8
- |
-
- CMS030916_20
- |
-
- BXD65b
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 9
- |
-
- CMS030916_23
- |
-
- BXD65b
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 10
- |
-
- CMS030916_32
- |
-
- BXD86
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 11
- |
-
- CMS032817_02
- |
-
- BXD48
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 12
- |
-
- CMS032817_28
- |
-
- BXD66
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 13
- |
-
- CMS032917_08
- |
-
- BXD48
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 14
- |
-
- CMS032917_24
- |
-
- BXD70
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 15
- |
-
- CMS032917_26
- |
-
- BXD87
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 16
- |
-
- CMS032917_33
- |
-
- BXD70
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 17
- |
-
- CMS033017_05
- |
-
- BXD78
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 18
- |
-
- CMS033017_25
- |
-
- BXD78
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 19
- |
-
- CMS061218_12
- |
-
- BXD87
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 20
- |
-
- CMS061218_13
- |
-
- BXD60
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 21
- |
-
- CMS061218_14
- |
-
- BXD71
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 22
- |
-
- CMS071216_17
- |
-
- BXD24
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 23
- |
-
- CMS071216_23
- |
-
- BXD73B
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
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- hippocampus
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-
-
- |
- 124
- |
-
- S32415_09
- |
-
- BXD68
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 125
- |
-
- CMS030716_05
- |
-
- BXD44
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 126
- |
-
- CMS030716_14
- |
-
- BXD40
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 127
- |
-
- CMS030716_21
- |
-
- BXD68
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 128
- |
-
- CMS030716_24
- |
-
- BXD48a
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 129
- |
-
- CMS030716_28
- |
-
- BXD79
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 130
- |
-
- CMS030716_33
- |
-
- BXD65b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 131
- |
-
- CMS030916_04
- |
-
- BXD55
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 132
- |
-
- CMS030916_06
- |
-
- BXD65b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 133
- |
-
- CMS030916_07
- |
-
- BXD60
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 134
- |
-
- CMS030916_10
- |
-
- BXD63
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 135
- |
-
- CMS030916_18
- |
-
- BXD65b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 136
- |
-
- CMS030916_22
- |
-
- BXD79
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 137
- |
-
- CMS030916_24
- |
-
- BXD63
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 138
- |
-
- CMS030916_29
- |
-
- BXD55
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 139
- |
-
- CMS030916_33
- |
-
- BXD69
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 140
- |
-
- CMS032817_08
- |
-
- BXD73
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 141
- |
-
- CMS032817_24
- |
-
- BXD70
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 142
- |
-
- CMS032917_07
- |
-
- BXD70
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 143
- |
-
- CMS032917_19
- |
-
- BXD78
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 144
- |
-
- CMS032917_21
- |
-
- BXD86
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 145
- |
-
- CMS032917_23
- |
-
- BXD66
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 146
- |
-
- CMS032917_30
- |
-
- BXD78
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 147
- |
-
- CMS032917_31
- |
-
- BXD48
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 148
- |
-
- CMS032917_32
- |
-
- BXD71
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 149
- |
-
- CMS033017_16
- |
-
- BXD62
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 150
- |
-
- CMS033017_29
- |
-
- BXD83
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 151
- |
-
- CMS071216_04
- |
-
- BXD90
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 152
- |
-
- CMS071216_09
- |
-
- BXD77
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 153
- |
-
- CMS071216_16
- |
-
- BXD65
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 154
- |
-
- CMS071216_22
- |
-
- BXD48a
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 155
- |
-
- CMS071316_15
- |
-
- BXD90
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 156
- |
-
- CMS071316_16
- |
-
- BXD50
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 157
- |
-
- CMS071316_27
- |
-
- BXD65
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 158
- |
-
- CMS071316_30
- |
-
- BXD51
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 159
- |
-
- CMS071416_10
- |
-
- BXD44
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 160
- |
-
- CMS071416_21
- |
-
- BXD69
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 161
- |
-
- CMS082817_12
- |
-
- BXD51
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 162
- |
-
- CMS082817_16
- |
-
- BXD101
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 163
- |
-
- CMS082817_22
- |
-
- BXD101
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 164
- |
-
- CMS082817_23
- |
-
- BXD24
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 165
- |
-
- CMS082917_13
- |
-
- BXD40
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 166
- |
-
- CMS082917_22
- |
-
- BXD87
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 167
- |
-
- CMS083017_10
- |
-
- BXD24
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 168
- |
-
- CMS102215_20
- |
-
- BXD73B
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 169
- |
-
- CMS111716_02
- |
-
- BXD75
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 170
- |
-
- CMS111716_05
- |
-
- BXD43
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 171
- |
-
- CMS111716_08
- |
-
- BXD75
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 172
- |
-
- CMS111716_10
- |
-
- BXD32
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 173
- |
-
- CMS111716_16
- |
-
- BXD100
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 174
- |
-
- CMS111716_20
- |
-
- BXD60
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 175
- |
-
- CMS111716_22
- |
-
- BXD83
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 176
- |
-
- CMS111716_23
- |
-
- BXD73b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 177
- |
-
- CMS111716_25
- |
-
- BXD73a
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 178
- |
-
- CMS111816_01
- |
-
- BXD34
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 179
- |
-
- CMS111816_03
- |
-
- BXD48
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 180
- |
-
- CMS111816_08
- |
-
- BXD43
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 181
- |
-
- CMS111816_11
- |
-
- BXD87
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 182
- |
-
- CMS111816_14
- |
-
- BXD60
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 183
- |
-
- CMS111816_16
- |
-
- BXD73b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 184
- |
-
- CMS111816_17
- |
-
- BXD77
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 185
- |
-
- CMS111816_20
- |
-
- BXD73a
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 186
- |
-
- CMS111816_28
- |
-
- BXD50
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 187
- |
-
- S32515_12
- |
-
- BXD68
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 188
- |
-
- S32515_16
- |
-
- C57BL/6J
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 189
- |
-
- 13118_35
- |
-
- BXD62
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 190
- |
-
- 13118_41
- |
-
- BXD66
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 191
- |
-
- 13118_56
- |
-
- BXD75
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 192
- |
-
- 31218_19
- |
-
- BXD65b
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 193
- |
-
- 31218_3
- |
-
- BXD73a
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 194
- |
-
- 31218_36
- |
-
- BXD78
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 195
- |
-
- AGE041118_03
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 196
- |
-
- AGE050118_07
- |
-
- BXD55
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 197
- |
-
- AGE050118_12
- |
-
- BXD73
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 198
- |
-
- AGE050118_16
- |
-
- BXD77
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 199
- |
-
- AGE050118_21
- |
-
- BXD86
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 200
- |
-
- AGE050118_23
- |
-
- BXD86
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 201
- |
-
- AGE050118_27
- |
-
- DBA/2J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 202
- |
-
- AGE061818_02
- |
-
- BXD100
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 203
- |
-
- BL013118_12
- |
-
- BXD34
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 204
- |
-
- BL013118_13
- |
-
- BXD34
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 205
- |
-
- CMS092118_24
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 206
- |
-
- E100118_16
- |
-
- BXD65
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 207
- |
-
- MT052417_09
- |
-
- BXD40
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 208
- |
-
- MT052417_17
- |
-
- BXD51
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 209
- |
-
- S13118_07
- |
-
- BXD24
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 210
- |
-
- S13118_08
- |
-
- BXD24
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 211
- |
-
- S13118_15
- |
-
- BXD40
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 212
- |
-
- S13118_18
- |
-
- BXD43
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 213
- |
-
- S13118_19
- |
-
- BXD43
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 214
- |
-
- S13118_23
- |
-
- BXD48
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 215
- |
-
- S13118_24
- |
-
- BXD48
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 216
- |
-
- S13118_26
- |
-
- BXD48a
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 217
- |
-
- S13118_36
- |
-
- BXD62
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 218
- |
-
- S13118_38
- |
-
- BXD65
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 219
- |
-
- S13118_42
- |
-
- BXD66
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 220
- |
-
- S13118_44
- |
-
- BXD68
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 221
- |
-
- S13118_58
- |
-
- BXD79
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 222
- |
-
- S13118_64
- |
-
- BXD90
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 223
- |
-
- S13118_65
- |
-
- BXD90
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 224
- |
-
- S13118_7
- |
-
- BXD101
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 225
- |
-
- S31218_01
- |
-
- BXD32
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 226
- |
-
- S31218_02
- |
-
- BXD32
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 227
- |
-
- S31218_04
- |
-
- BXD44
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 228
- |
-
- S31218_15
- |
-
- BXD63
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 229
- |
-
- S31218_16
- |
-
- BXD63
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 230
- |
-
- S31218_18
- |
-
- BXD65b
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 231
- |
-
- S31218_1
- |
-
- BXD51
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 232
- |
-
- S31218_21
- |
-
- BXD69
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 233
- |
-
- S31218_22
- |
-
- BXD69
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 234
- |
-
- S31218_24
- |
-
- BXD70
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 235
- |
-
- S31218_25
- |
-
- BXD70
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 236
- |
-
- S31218_27
- |
-
- BXD71
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 237
- |
-
- S31218_28
- |
-
- BXD71
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 238
- |
-
- S31218_31
- |
-
- BXD73a
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 239
- |
-
- S31218_35
- |
-
- BXD78
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 240
- |
-
- S32718_01
- |
-
- DBA/2J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 241
- |
-
- S32718_03
- |
-
- DBA/2J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
-
diff --git a/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/experiment-design.rtf b/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/experiment-design.rtf
deleted file mode 100644
index 54fad3e..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/experiment-design.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-Alcohol consumption was evaluated using the DID method. The protocol calls for 4 consecutive days of testing. Each day, starting on a Tuesday 3 h after lights were turned off, the water bottles were removed from the cages and replaced with 15 ml centrifuge tubes filled with 20% (v/v) ethanol from 95% USP ethanol. On days 1–3 (Tuesday through Thursday) the length of exposure was 2 h and on the 4th day (Friday) the exposure was 4 h. No alcohol was offered in the intervening period (Saturday through Monday). This protocol was repeated weekly for 16 weeks (Table). Tubes were weighed immediately before and after the exposure period. Volume consumed was converted to g/kg body weight of ethanol.
-
-During a period of 7 weeks, mice received 2 disturbances per day (see Figure). These consisted of being exposed to wet bedding for 1 hour, 1 cm of water in the bottom of the cage with no bedding for 1 hour, no bedding for 1 hour, confinement in a 3 × 3 × 3 cm plastic box for 15 minutes, tilted cage at 45º for 1 hour, and exposure to foreign mouse or fox urine odor for 1 hour. The other stressor was a complete phase shift in the light:dark cycle over each weekend. Disruption of the light cycle (lights constantly on) occurred over the weekend (starting Friday 11:00 am) with the light cycle resuming at 11 am on Monday (lights off). The schedule was repeated weekly over the duration of the study.
-
-Treatment Periods
-
-The entire protocol took 16 weeks to complete and was subdivided into 3 periods: baseline (initial 5 weeks), CMS (next 7 weeks), and postâ€CMS (final 4 weeks). Alcohol was offered as described above for all periods and experimental groups. During the intervening 7â€week CMS period, control animals were subjected to normal housing and experimental (stress) animals were subjected to CMS.
diff --git a/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/processing.rtf b/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/processing.rtf
deleted file mode 100644
index 7d83d76..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/specifics.rtf b/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/specifics.rtf
deleted file mode 100644
index c2753aa..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NIAAA BXD Hippocampus CMS-DID RNA-Seq (Oct20) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/tissue.rtf b/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/tissue.rtf
deleted file mode 100644
index 30cdeea..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CMS_DID_RNAseq1020/tissue.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-Tissue Harvest and RNA extraction
-
-The animals were sacrificed under saturated isoflurane. Brains from the animals were dissected under a cold plate (≤4o C), and hippocampus were weighted and snap frozen in dry ice bath with isopentane and stored at −80°C until RNA extraction.
-
-RNA Extraction
-
-Total RNA was extracted using Direct-zol RNA Miniprep Plus Kits (Zymo Research, Irvine, CA, USA) according to the manufacturer’s instructions. Approximately 15 mg of hippocampus tissue was added into a 2 ml tube containing 1 ml TRI Reagent® and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 min in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 rpm followed by incubating for 5 min. 0.1 ml of 1‑bromo-3‑chloropropane was add into the homogenate, shaken vigorously for 15 s, and centrifuged for 15 min at 12,000×g at 4 °C. 600 µl upper aqueous was then transferred into a new collection tube containing 600 µl 100% ethanol. The mixture was loaded into a Zymo-Spin IIC column, wash once with RNA Prep Buffer and twice with RNA Wash Buffer. All RNA had been treated with DNase to eliminate possible DNA contamination, and further precipitated with ethanol. RNA purity and integrity were verified by a nanodrop spectrophotometer and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).
diff --git a/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/cases.rtf b/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/cases.rtf
deleted file mode 100644
index 08a20a8..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/cases.rtf
+++ /dev/null
@@ -1,4848 +0,0 @@
-The study included 241 females (aged 50 to 90 ± 2 days at the start of the experiment) from B6, D2, and 35 advanced intercross BXD strains (about 2 mice per strain and per condition). Mice were divided into 4 groups of Control (CTL, 53 mice for 31 strains), Chronic Mild Stress (CMS, 64 mice for 32 strains), Drinking in Dark (DID, 64 mice for 35 strains), and CMS+DID (60 mice for 35 strains). Mice in CTL were normally handled, while mice in other groups were singly housed in shoebox cages, with food and water provided ad libitum except when the water was replaced by 20% (v/v) EtOH (see below) for DID and CMS+DID groups (detailed treatments and schemes are showing in the Table and Figure). The ambient temperature was 21 ± 2°C, and the light cycle was 7:00/19:00 for CTL, and 23:00/11:00 the rest groups lights on/off. The animals were weighed weekly to assess health and to provide the basis for calculating the amount of EtOH consumed in grams per kilogram. All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
-
-The table of samples that are finally used for this study.
-
-
-
-
- |
- Index
- |
-
- ID
- |
-
- Strain
- |
-
- Sex
- |
-
- Treatment Group
- |
-
- Tissue
- |
-
-
- |
- 1
- |
-
- CMS030716_12
- |
-
- BXD68
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 2
- |
-
- CMS030716_18
- |
-
- BXD40
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 3
- |
-
- CMS030716_19
- |
-
- BXD40
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 4
- |
-
- CMS030916_02
- |
-
- BXD101
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 5
- |
-
- CMS030916_09
- |
-
- BXD101
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 6
- |
-
- CMS030916_11
- |
-
- BXD79
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 7
- |
-
- CMS030916_14
- |
-
- BXD48a
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 8
- |
-
- CMS030916_20
- |
-
- BXD65b
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 9
- |
-
- CMS030916_23
- |
-
- BXD65b
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 10
- |
-
- CMS030916_32
- |
-
- BXD86
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 11
- |
-
- CMS032817_02
- |
-
- BXD48
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 12
- |
-
- CMS032817_28
- |
-
- BXD66
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 13
- |
-
- CMS032917_08
- |
-
- BXD48
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 14
- |
-
- CMS032917_24
- |
-
- BXD70
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 15
- |
-
- CMS032917_26
- |
-
- BXD87
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 16
- |
-
- CMS032917_33
- |
-
- BXD70
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 17
- |
-
- CMS033017_05
- |
-
- BXD78
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 18
- |
-
- CMS033017_25
- |
-
- BXD78
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 19
- |
-
- CMS061218_12
- |
-
- BXD87
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 20
- |
-
- CMS061218_13
- |
-
- BXD60
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 21
- |
-
- CMS061218_14
- |
-
- BXD71
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 22
- |
-
- CMS071216_17
- |
-
- BXD24
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 23
- |
-
- CMS071216_23
- |
-
- BXD73B
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 24
- |
-
- CMS071216_25
- |
-
- BXD48a
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 25
- |
-
- CMS071316_06
- |
-
- BXD90
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 26
- |
-
- CMS071316_08
- |
-
- BXD66
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 27
- |
-
- CMS071316_14
- |
-
- BXD87
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 28
- |
-
- CMS071316_17
- |
-
- BXD62
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 29
- |
-
- CMS071316_18
- |
-
- BXD65
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 30
- |
-
- CMS071316_32
- |
-
- BXD90
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 31
- |
-
- CMS071416_06
- |
-
- BXD50
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 32
- |
-
- CMS082817_07
- |
-
- BXD44
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 33
- |
-
- CMS082817_25
- |
-
- BXD71
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 34
- |
-
- CMS082917_16
- |
-
- BXD79
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 35
- |
-
- CMS083017_07
- |
-
- BXD69
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 36
- |
-
- CMS083017_25
- |
-
- BXD32
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 37
- |
-
- CMS092018_01
- |
-
- DBA/2J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 38
- |
-
- CMS092018_05
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 39
- |
-
- CMS092118_08
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 40
- |
-
- CMS102716_01
- |
-
- BXD83
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 41
- |
-
- CMS102716_02
- |
-
- BXD75
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 42
- |
-
- CMS102716_03
- |
-
- BXD73a
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 43
- |
-
- CMS102716_05
- |
-
- BXD73a
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 44
- |
-
- CMS102716_06
- |
-
- BXD34
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 45
- |
-
- CMS102716_07
- |
-
- BXD24
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 46
- |
-
- CMS102716_08
- |
-
- BXD60
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 47
- |
-
- CMS102716_11
- |
-
- BXD34
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 48
- |
-
- CMS102716_12
- |
-
- BXD62
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 49
- |
-
- CMS102716_14
- |
-
- BXD83
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 50
- |
-
- CMS102716_15
- |
-
- BXD69
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 51
- |
-
- CMS102716_16
- |
-
- BXD77
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 52
- |
-
- CMS102716_20
- |
-
- BXD50
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 53
- |
-
- CMS102816_02
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 54
- |
-
- CMS102816_03
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 55
- |
-
- CMS102816_04
- |
-
- DBA/2J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 56
- |
-
- CMS102816_06
- |
-
- DBA/2J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 57
- |
-
- CMS102816_10
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
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- |
-
- CMS071316_30
- |
-
- BXD51
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 159
- |
-
- CMS071416_10
- |
-
- BXD44
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 160
- |
-
- CMS071416_21
- |
-
- BXD69
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 161
- |
-
- CMS082817_12
- |
-
- BXD51
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 162
- |
-
- CMS082817_16
- |
-
- BXD101
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 163
- |
-
- CMS082817_22
- |
-
- BXD101
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 164
- |
-
- CMS082817_23
- |
-
- BXD24
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 165
- |
-
- CMS082917_13
- |
-
- BXD40
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 166
- |
-
- CMS082917_22
- |
-
- BXD87
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 167
- |
-
- CMS083017_10
- |
-
- BXD24
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 168
- |
-
- CMS102215_20
- |
-
- BXD73B
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 169
- |
-
- CMS111716_02
- |
-
- BXD75
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 170
- |
-
- CMS111716_05
- |
-
- BXD43
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 171
- |
-
- CMS111716_08
- |
-
- BXD75
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 172
- |
-
- CMS111716_10
- |
-
- BXD32
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 173
- |
-
- CMS111716_16
- |
-
- BXD100
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 174
- |
-
- CMS111716_20
- |
-
- BXD60
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 175
- |
-
- CMS111716_22
- |
-
- BXD83
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 176
- |
-
- CMS111716_23
- |
-
- BXD73b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 177
- |
-
- CMS111716_25
- |
-
- BXD73a
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 178
- |
-
- CMS111816_01
- |
-
- BXD34
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 179
- |
-
- CMS111816_03
- |
-
- BXD48
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 180
- |
-
- CMS111816_08
- |
-
- BXD43
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 181
- |
-
- CMS111816_11
- |
-
- BXD87
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 182
- |
-
- CMS111816_14
- |
-
- BXD60
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 183
- |
-
- CMS111816_16
- |
-
- BXD73b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 184
- |
-
- CMS111816_17
- |
-
- BXD77
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 185
- |
-
- CMS111816_20
- |
-
- BXD73a
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 186
- |
-
- CMS111816_28
- |
-
- BXD50
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 187
- |
-
- S32515_12
- |
-
- BXD68
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 188
- |
-
- S32515_16
- |
-
- C57BL/6J
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 189
- |
-
- 13118_35
- |
-
- BXD62
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 190
- |
-
- 13118_41
- |
-
- BXD66
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 191
- |
-
- 13118_56
- |
-
- BXD75
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 192
- |
-
- 31218_19
- |
-
- BXD65b
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 193
- |
-
- 31218_3
- |
-
- BXD73a
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 194
- |
-
- 31218_36
- |
-
- BXD78
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 195
- |
-
- AGE041118_03
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 196
- |
-
- AGE050118_07
- |
-
- BXD55
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 197
- |
-
- AGE050118_12
- |
-
- BXD73
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 198
- |
-
- AGE050118_16
- |
-
- BXD77
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 199
- |
-
- AGE050118_21
- |
-
- BXD86
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 200
- |
-
- AGE050118_23
- |
-
- BXD86
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 201
- |
-
- AGE050118_27
- |
-
- DBA/2J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 202
- |
-
- AGE061818_02
- |
-
- BXD100
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 203
- |
-
- BL013118_12
- |
-
- BXD34
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 204
- |
-
- BL013118_13
- |
-
- BXD34
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 205
- |
-
- CMS092118_24
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 206
- |
-
- E100118_16
- |
-
- BXD65
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 207
- |
-
- MT052417_09
- |
-
- BXD40
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 208
- |
-
- MT052417_17
- |
-
- BXD51
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 209
- |
-
- S13118_07
- |
-
- BXD24
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 210
- |
-
- S13118_08
- |
-
- BXD24
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 211
- |
-
- S13118_15
- |
-
- BXD40
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 212
- |
-
- S13118_18
- |
-
- BXD43
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 213
- |
-
- S13118_19
- |
-
- BXD43
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 214
- |
-
- S13118_23
- |
-
- BXD48
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 215
- |
-
- S13118_24
- |
-
- BXD48
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 216
- |
-
- S13118_26
- |
-
- BXD48a
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 217
- |
-
- S13118_36
- |
-
- BXD62
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 218
- |
-
- S13118_38
- |
-
- BXD65
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 219
- |
-
- S13118_42
- |
-
- BXD66
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 220
- |
-
- S13118_44
- |
-
- BXD68
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 221
- |
-
- S13118_58
- |
-
- BXD79
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 222
- |
-
- S13118_64
- |
-
- BXD90
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 223
- |
-
- S13118_65
- |
-
- BXD90
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 224
- |
-
- S13118_7
- |
-
- BXD101
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 225
- |
-
- S31218_01
- |
-
- BXD32
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 226
- |
-
- S31218_02
- |
-
- BXD32
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 227
- |
-
- S31218_04
- |
-
- BXD44
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 228
- |
-
- S31218_15
- |
-
- BXD63
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 229
- |
-
- S31218_16
- |
-
- BXD63
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 230
- |
-
- S31218_18
- |
-
- BXD65b
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 231
- |
-
- S31218_1
- |
-
- BXD51
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 232
- |
-
- S31218_21
- |
-
- BXD69
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 233
- |
-
- S31218_22
- |
-
- BXD69
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 234
- |
-
- S31218_24
- |
-
- BXD70
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 235
- |
-
- S31218_25
- |
-
- BXD70
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 236
- |
-
- S31218_27
- |
-
- BXD71
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 237
- |
-
- S31218_28
- |
-
- BXD71
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 238
- |
-
- S31218_31
- |
-
- BXD73a
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 239
- |
-
- S31218_35
- |
-
- BXD78
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 240
- |
-
- S32718_01
- |
-
- DBA/2J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 241
- |
-
- S32718_03
- |
-
- DBA/2J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
-
diff --git a/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/experiment-design.rtf b/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/experiment-design.rtf
deleted file mode 100644
index 54fad3e..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/experiment-design.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-Alcohol consumption was evaluated using the DID method. The protocol calls for 4 consecutive days of testing. Each day, starting on a Tuesday 3 h after lights were turned off, the water bottles were removed from the cages and replaced with 15 ml centrifuge tubes filled with 20% (v/v) ethanol from 95% USP ethanol. On days 1–3 (Tuesday through Thursday) the length of exposure was 2 h and on the 4th day (Friday) the exposure was 4 h. No alcohol was offered in the intervening period (Saturday through Monday). This protocol was repeated weekly for 16 weeks (Table). Tubes were weighed immediately before and after the exposure period. Volume consumed was converted to g/kg body weight of ethanol.
-
-During a period of 7 weeks, mice received 2 disturbances per day (see Figure). These consisted of being exposed to wet bedding for 1 hour, 1 cm of water in the bottom of the cage with no bedding for 1 hour, no bedding for 1 hour, confinement in a 3 × 3 × 3 cm plastic box for 15 minutes, tilted cage at 45º for 1 hour, and exposure to foreign mouse or fox urine odor for 1 hour. The other stressor was a complete phase shift in the light:dark cycle over each weekend. Disruption of the light cycle (lights constantly on) occurred over the weekend (starting Friday 11:00 am) with the light cycle resuming at 11 am on Monday (lights off). The schedule was repeated weekly over the duration of the study.
-
-Treatment Periods
-
-The entire protocol took 16 weeks to complete and was subdivided into 3 periods: baseline (initial 5 weeks), CMS (next 7 weeks), and postâ€CMS (final 4 weeks). Alcohol was offered as described above for all periods and experimental groups. During the intervening 7â€week CMS period, control animals were subjected to normal housing and experimental (stress) animals were subjected to CMS.
diff --git a/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/processing.rtf b/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/processing.rtf
deleted file mode 100644
index 7d83d76..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/specifics.rtf b/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/specifics.rtf
deleted file mode 100644
index 5089c79..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NIAAA BXD Hippocampus CMS RNA-Seq (Oct20) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/tissue.rtf b/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/tissue.rtf
deleted file mode 100644
index 30cdeea..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CMS_RNAseq1020/tissue.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-Tissue Harvest and RNA extraction
-
-The animals were sacrificed under saturated isoflurane. Brains from the animals were dissected under a cold plate (≤4o C), and hippocampus were weighted and snap frozen in dry ice bath with isopentane and stored at −80°C until RNA extraction.
-
-RNA Extraction
-
-Total RNA was extracted using Direct-zol RNA Miniprep Plus Kits (Zymo Research, Irvine, CA, USA) according to the manufacturer’s instructions. Approximately 15 mg of hippocampus tissue was added into a 2 ml tube containing 1 ml TRI Reagent® and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 min in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 rpm followed by incubating for 5 min. 0.1 ml of 1‑bromo-3‑chloropropane was add into the homogenate, shaken vigorously for 15 s, and centrifuged for 15 min at 12,000×g at 4 °C. 600 µl upper aqueous was then transferred into a new collection tube containing 600 µl 100% ethanol. The mixture was loaded into a Zymo-Spin IIC column, wash once with RNA Prep Buffer and twice with RNA Wash Buffer. All RNA had been treated with DNase to eliminate possible DNA contamination, and further precipitated with ethanol. RNA purity and integrity were verified by a nanodrop spectrophotometer and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).
diff --git a/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/cases.rtf b/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/cases.rtf
deleted file mode 100644
index 08a20a8..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/cases.rtf
+++ /dev/null
@@ -1,4848 +0,0 @@
-The study included 241 females (aged 50 to 90 ± 2 days at the start of the experiment) from B6, D2, and 35 advanced intercross BXD strains (about 2 mice per strain and per condition). Mice were divided into 4 groups of Control (CTL, 53 mice for 31 strains), Chronic Mild Stress (CMS, 64 mice for 32 strains), Drinking in Dark (DID, 64 mice for 35 strains), and CMS+DID (60 mice for 35 strains). Mice in CTL were normally handled, while mice in other groups were singly housed in shoebox cages, with food and water provided ad libitum except when the water was replaced by 20% (v/v) EtOH (see below) for DID and CMS+DID groups (detailed treatments and schemes are showing in the Table and Figure). The ambient temperature was 21 ± 2°C, and the light cycle was 7:00/19:00 for CTL, and 23:00/11:00 the rest groups lights on/off. The animals were weighed weekly to assess health and to provide the basis for calculating the amount of EtOH consumed in grams per kilogram. All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
-
-The table of samples that are finally used for this study.
-
-
-
-
- |
- Index
- |
-
- ID
- |
-
- Strain
- |
-
- Sex
- |
-
- Treatment Group
- |
-
- Tissue
- |
-
-
- |
- 1
- |
-
- CMS030716_12
- |
-
- BXD68
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 2
- |
-
- CMS030716_18
- |
-
- BXD40
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 3
- |
-
- CMS030716_19
- |
-
- BXD40
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 4
- |
-
- CMS030916_02
- |
-
- BXD101
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 5
- |
-
- CMS030916_09
- |
-
- BXD101
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 6
- |
-
- CMS030916_11
- |
-
- BXD79
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 7
- |
-
- CMS030916_14
- |
-
- BXD48a
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 8
- |
-
- CMS030916_20
- |
-
- BXD65b
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 9
- |
-
- CMS030916_23
- |
-
- BXD65b
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 10
- |
-
- CMS030916_32
- |
-
- BXD86
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 11
- |
-
- CMS032817_02
- |
-
- BXD48
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 12
- |
-
- CMS032817_28
- |
-
- BXD66
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 13
- |
-
- CMS032917_08
- |
-
- BXD48
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 14
- |
-
- CMS032917_24
- |
-
- BXD70
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 15
- |
-
- CMS032917_26
- |
-
- BXD87
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 16
- |
-
- CMS032917_33
- |
-
- BXD70
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 17
- |
-
- CMS033017_05
- |
-
- BXD78
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 18
- |
-
- CMS033017_25
- |
-
- BXD78
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 19
- |
-
- CMS061218_12
- |
-
- BXD87
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 20
- |
-
- CMS061218_13
- |
-
- BXD60
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 21
- |
-
- CMS061218_14
- |
-
- BXD71
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 22
- |
-
- CMS071216_17
- |
-
- BXD24
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 23
- |
-
- CMS071216_23
- |
-
- BXD73B
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 24
- |
-
- CMS071216_25
- |
-
- BXD48a
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 25
- |
-
- CMS071316_06
- |
-
- BXD90
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 26
- |
-
- CMS071316_08
- |
-
- BXD66
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 27
- |
-
- CMS071316_14
- |
-
- BXD87
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 28
- |
-
- CMS071316_17
- |
-
- BXD62
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 29
- |
-
- CMS071316_18
- |
-
- BXD65
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 30
- |
-
- CMS071316_32
- |
-
- BXD90
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 31
- |
-
- CMS071416_06
- |
-
- BXD50
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 32
- |
-
- CMS082817_07
- |
-
- BXD44
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 33
- |
-
- CMS082817_25
- |
-
- BXD71
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 34
- |
-
- CMS082917_16
- |
-
- BXD79
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 35
- |
-
- CMS083017_07
- |
-
- BXD69
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 36
- |
-
- CMS083017_25
- |
-
- BXD32
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 37
- |
-
- CMS092018_01
- |
-
- DBA/2J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 38
- |
-
- CMS092018_05
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 39
- |
-
- CMS092118_08
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 40
- |
-
- CMS102716_01
- |
-
- BXD83
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 41
- |
-
- CMS102716_02
- |
-
- BXD75
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 42
- |
-
- CMS102716_03
- |
-
- BXD73a
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 43
- |
-
- CMS102716_05
- |
-
- BXD73a
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 44
- |
-
- CMS102716_06
- |
-
- BXD34
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 45
- |
-
- CMS102716_07
- |
-
- BXD24
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 46
- |
-
- CMS102716_08
- |
-
- BXD60
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 47
- |
-
- CMS102716_11
- |
-
- BXD34
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 48
- |
-
- CMS102716_12
- |
-
- BXD62
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 49
- |
-
- CMS102716_14
- |
-
- BXD83
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 50
- |
-
- CMS102716_15
- |
-
- BXD69
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 51
- |
-
- CMS102716_16
- |
-
- BXD77
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 52
- |
-
- CMS102716_20
- |
-
- BXD50
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 53
- |
-
- CMS102816_02
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 54
- |
-
- CMS102816_03
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 55
- |
-
- CMS102816_04
- |
-
- DBA/2J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 56
- |
-
- CMS102816_06
- |
-
- DBA/2J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 57
- |
-
- CMS102816_10
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 58
- |
-
- CMS102816_11
- |
-
- BXD100
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 59
- |
-
- CMS102816_13
- |
-
- BXD75
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 60
- |
-
- CMS102816_14
- |
-
- BXD77
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 61
- |
-
- CMS102816_17
- |
-
- BXD100
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 62
- |
-
- CMS102816_18
- |
-
- BXD43
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 63
- |
-
- CMS102816_20
- |
-
- BXD32
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 64
- |
-
- CMS102816_21
- |
-
- BXD65
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 65
- |
-
- CMS030716_01
- |
-
- BXD55
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 66
- |
-
- CMS030716_08
- |
-
- BXD63
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 67
- |
-
- CMS030716_09
- |
-
- BXD65b
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 68
- |
-
- CMS030716_15
- |
-
- BXD69
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 69
- |
-
- CMS030716_27
- |
-
- BXD86
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 70
- |
-
- CMS030716_29
- |
-
- BXD55
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 71
- |
-
- CMS030716_30
- |
-
- BXD62
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 72
- |
-
- CMS030716_31
- |
-
- BXD65b
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 73
- |
-
- CMS030916_15
- |
-
- BXD69
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 74
- |
-
- CMS030916_16
- |
-
- BXD68
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 75
- |
-
- CMS030916_17
- |
-
- BXD40
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 76
- |
-
- CMS030916_26
- |
-
- BXD79
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 77
- |
-
- CMS032817_10
- |
-
- BXD87
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 78
- |
-
- CMS032817_18
- |
-
- BXD70
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 79
- |
-
- CMS032817_25
- |
-
- BXD48
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 80
- |
-
- CMS032817_27
- |
-
- BXD83
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 81
- |
-
- CMS032817_31
- |
-
- BXD71
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 82
- |
-
- CMS032817_32
- |
-
- BXD70
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 83
- |
-
- CMS032917_15
- |
-
- BXD86
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 84
- |
-
- CMS032917_17
- |
-
- BXD71
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 85
- |
-
- CMS032917_25
- |
-
- BXD78
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 86
- |
-
- CMS033017_04
- |
-
- BXD78
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 87
- |
-
- CMS033017_11
- |
-
- BXD83
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 88
- |
-
- CMS033017_13
- |
-
- BXD73
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 89
- |
-
- CMS071216_01
- |
-
- BXD50
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 90
- |
-
- CMS071216_24
- |
-
- BXD100
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
- |
-
-
- |
- 91
- |
-
- CMS071316_05
- |
-
- BXD51
- |
-
- F
- |
-
- CMS+DID
- |
-
- hippocampus
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- 92
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- CMS071316_20
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- BXD65
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- CMS+DID
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- hippocampus
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- 93
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- CMS071316_22
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- BXD90
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- hippocampus
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- 94
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- CMS071316_29
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- hippocampus
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- 95
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- CMS071416_01
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- BXD100
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- hippocampus
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- 96
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- CMS071416_08
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- BXD24
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- CMS+DID
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- hippocampus
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- 97
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- CMS071416_13
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- BXD48a
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- F
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- CMS+DID
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- hippocampus
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- 98
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- CMS071416_19
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- BXD32
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- F
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- CMS+DID
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- hippocampus
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-
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- 99
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- CMS071416_27
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- BXD63
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- F
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- CMS+DID
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- hippocampus
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-
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- 100
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- CMS082817_02
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- BXD48
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- F
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- CMS+DID
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- hippocampus
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-
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- 101
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- CMS082817_03
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- BXD40
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- F
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- CMS+DID
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- hippocampus
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- 102
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- CMS082817_09
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- DBA/2J
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- F
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- CMS+DID
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- hippocampus
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- 103
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- CMS082817_28
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- BXD79
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- CMS+DID
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- hippocampus
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- 104
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- CMS082917_07
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- BXD43
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- CMS+DID
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- hippocampus
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- 105
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- CMS082917_10
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- BXD44
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- 106
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- CMS082917_18
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- BXD32
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- 107
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- CMS082917_21
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- BXD24
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- 108
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- CMS082917_29
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- BXD87
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- 109
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- CMS083017_02
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- BXD101
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- hippocampus
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- 110
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- CMS083017_03
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- BXD66
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- hippocampus
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- 111
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- DBA/2J
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- 112
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- CMS083017_28
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- hippocampus
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- 113
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- CMS111716_07
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- hippocampus
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- 114
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- hippocampus
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- 115
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- hippocampus
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- 116
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- hippocampus
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- 117
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- hippocampus
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- 118
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- 119
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- 120
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- 121
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- 122
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- hippocampus
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- 123
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- 124
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- 125
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- 126
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- 127
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- BXD68
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- hippocampus
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- 128
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- hippocampus
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-
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- 129
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- DID
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- hippocampus
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-
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- 130
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- DID
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- hippocampus
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-
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- 131
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- DID
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- hippocampus
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-
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- 132
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- CMS030916_06
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- BXD65b
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- F
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- DID
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-
- hippocampus
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-
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- 133
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- CMS030916_07
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- BXD60
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-
- F
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-
- DID
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-
- hippocampus
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-
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- 134
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- CMS030916_10
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- BXD63
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- DID
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-
- hippocampus
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-
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- 135
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- CMS030916_18
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- DID
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-
- hippocampus
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-
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- 136
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- CMS030916_22
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- BXD79
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-
- F
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-
- DID
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-
- hippocampus
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-
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- 137
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- CMS030916_24
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- BXD63
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-
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-
- DID
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-
- hippocampus
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-
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- 138
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- CMS030916_29
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- BXD55
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-
- F
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-
- DID
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-
- hippocampus
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-
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- 139
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- CMS030916_33
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-
- BXD69
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-
- F
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-
- DID
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-
- hippocampus
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-
-
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- 140
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-
- CMS032817_08
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-
- BXD73
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-
- F
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-
- DID
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-
- hippocampus
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-
-
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- 141
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-
- CMS032817_24
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-
- BXD70
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-
- F
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-
- DID
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-
- hippocampus
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-
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- 142
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-
- CMS032917_07
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-
- BXD70
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-
- F
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-
- DID
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-
- hippocampus
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-
-
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- 143
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- CMS032917_19
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-
- BXD78
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-
- F
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-
- DID
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-
- hippocampus
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-
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- 144
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- CMS032917_21
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- BXD86
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-
- F
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-
- DID
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-
- hippocampus
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-
-
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- 145
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- CMS032917_23
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- BXD66
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-
- F
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-
- DID
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-
- hippocampus
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-
-
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- 146
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- CMS032917_30
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-
- BXD78
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-
- F
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-
- DID
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-
- hippocampus
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-
-
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- 147
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- CMS032917_31
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-
- F
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-
- DID
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-
- hippocampus
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-
-
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- 148
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- CMS032917_32
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-
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-
- DID
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-
- hippocampus
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-
-
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- 149
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- CMS033017_16
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-
- BXD62
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-
- F
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-
- DID
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-
- hippocampus
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-
-
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- 150
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-
- CMS033017_29
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-
- BXD83
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-
- F
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-
- DID
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-
- hippocampus
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-
-
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- 151
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-
- CMS071216_04
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-
- BXD90
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-
- F
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-
- DID
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-
- hippocampus
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-
-
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- 152
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-
- CMS071216_09
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-
- BXD77
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-
- F
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-
- DID
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-
- hippocampus
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-
-
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- 153
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-
- CMS071216_16
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-
- BXD65
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-
- F
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-
- DID
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-
- hippocampus
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-
-
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- 154
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-
- CMS071216_22
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-
- BXD48a
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-
- F
- |
-
- DID
- |
-
- hippocampus
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-
-
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- 155
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-
- CMS071316_15
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-
- BXD90
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-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
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- 156
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-
- CMS071316_16
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-
- BXD50
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
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- 157
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-
- CMS071316_27
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-
- BXD65
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
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- 158
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-
- CMS071316_30
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-
- BXD51
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
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- 159
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-
- CMS071416_10
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-
- BXD44
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
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- 160
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-
- CMS071416_21
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-
- BXD69
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
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- 161
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-
- CMS082817_12
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-
- BXD51
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
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- 162
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-
- CMS082817_16
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-
- BXD101
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
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- 163
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-
- CMS082817_22
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-
- BXD101
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
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- 164
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-
- CMS082817_23
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-
- BXD24
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
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- 165
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-
- CMS082917_13
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-
- BXD40
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 166
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-
- CMS082917_22
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-
- BXD87
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 167
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-
- CMS083017_10
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-
- BXD24
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 168
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-
- CMS102215_20
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-
- BXD73B
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 169
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-
- CMS111716_02
- |
-
- BXD75
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 170
- |
-
- CMS111716_05
- |
-
- BXD43
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 171
- |
-
- CMS111716_08
- |
-
- BXD75
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 172
- |
-
- CMS111716_10
- |
-
- BXD32
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 173
- |
-
- CMS111716_16
- |
-
- BXD100
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 174
- |
-
- CMS111716_20
- |
-
- BXD60
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 175
- |
-
- CMS111716_22
- |
-
- BXD83
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 176
- |
-
- CMS111716_23
- |
-
- BXD73b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 177
- |
-
- CMS111716_25
- |
-
- BXD73a
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 178
- |
-
- CMS111816_01
- |
-
- BXD34
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 179
- |
-
- CMS111816_03
- |
-
- BXD48
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 180
- |
-
- CMS111816_08
- |
-
- BXD43
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 181
- |
-
- CMS111816_11
- |
-
- BXD87
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 182
- |
-
- CMS111816_14
- |
-
- BXD60
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 183
- |
-
- CMS111816_16
- |
-
- BXD73b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 184
- |
-
- CMS111816_17
- |
-
- BXD77
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 185
- |
-
- CMS111816_20
- |
-
- BXD73a
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 186
- |
-
- CMS111816_28
- |
-
- BXD50
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 187
- |
-
- S32515_12
- |
-
- BXD68
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 188
- |
-
- S32515_16
- |
-
- C57BL/6J
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 189
- |
-
- 13118_35
- |
-
- BXD62
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 190
- |
-
- 13118_41
- |
-
- BXD66
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 191
- |
-
- 13118_56
- |
-
- BXD75
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 192
- |
-
- 31218_19
- |
-
- BXD65b
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 193
- |
-
- 31218_3
- |
-
- BXD73a
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 194
- |
-
- 31218_36
- |
-
- BXD78
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 195
- |
-
- AGE041118_03
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 196
- |
-
- AGE050118_07
- |
-
- BXD55
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 197
- |
-
- AGE050118_12
- |
-
- BXD73
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 198
- |
-
- AGE050118_16
- |
-
- BXD77
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 199
- |
-
- AGE050118_21
- |
-
- BXD86
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 200
- |
-
- AGE050118_23
- |
-
- BXD86
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 201
- |
-
- AGE050118_27
- |
-
- DBA/2J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 202
- |
-
- AGE061818_02
- |
-
- BXD100
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 203
- |
-
- BL013118_12
- |
-
- BXD34
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 204
- |
-
- BL013118_13
- |
-
- BXD34
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 205
- |
-
- CMS092118_24
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 206
- |
-
- E100118_16
- |
-
- BXD65
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 207
- |
-
- MT052417_09
- |
-
- BXD40
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 208
- |
-
- MT052417_17
- |
-
- BXD51
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 209
- |
-
- S13118_07
- |
-
- BXD24
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 210
- |
-
- S13118_08
- |
-
- BXD24
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 211
- |
-
- S13118_15
- |
-
- BXD40
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 212
- |
-
- S13118_18
- |
-
- BXD43
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 213
- |
-
- S13118_19
- |
-
- BXD43
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 214
- |
-
- S13118_23
- |
-
- BXD48
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 215
- |
-
- S13118_24
- |
-
- BXD48
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 216
- |
-
- S13118_26
- |
-
- BXD48a
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 217
- |
-
- S13118_36
- |
-
- BXD62
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 218
- |
-
- S13118_38
- |
-
- BXD65
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 219
- |
-
- S13118_42
- |
-
- BXD66
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 220
- |
-
- S13118_44
- |
-
- BXD68
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 221
- |
-
- S13118_58
- |
-
- BXD79
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 222
- |
-
- S13118_64
- |
-
- BXD90
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 223
- |
-
- S13118_65
- |
-
- BXD90
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 224
- |
-
- S13118_7
- |
-
- BXD101
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 225
- |
-
- S31218_01
- |
-
- BXD32
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 226
- |
-
- S31218_02
- |
-
- BXD32
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 227
- |
-
- S31218_04
- |
-
- BXD44
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 228
- |
-
- S31218_15
- |
-
- BXD63
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 229
- |
-
- S31218_16
- |
-
- BXD63
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 230
- |
-
- S31218_18
- |
-
- BXD65b
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 231
- |
-
- S31218_1
- |
-
- BXD51
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 232
- |
-
- S31218_21
- |
-
- BXD69
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 233
- |
-
- S31218_22
- |
-
- BXD69
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 234
- |
-
- S31218_24
- |
-
- BXD70
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 235
- |
-
- S31218_25
- |
-
- BXD70
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 236
- |
-
- S31218_27
- |
-
- BXD71
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 237
- |
-
- S31218_28
- |
-
- BXD71
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 238
- |
-
- S31218_31
- |
-
- BXD73a
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 239
- |
-
- S31218_35
- |
-
- BXD78
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 240
- |
-
- S32718_01
- |
-
- DBA/2J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 241
- |
-
- S32718_03
- |
-
- DBA/2J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
-
diff --git a/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/experiment-design.rtf b/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/experiment-design.rtf
deleted file mode 100644
index 54fad3e..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/experiment-design.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-Alcohol consumption was evaluated using the DID method. The protocol calls for 4 consecutive days of testing. Each day, starting on a Tuesday 3 h after lights were turned off, the water bottles were removed from the cages and replaced with 15 ml centrifuge tubes filled with 20% (v/v) ethanol from 95% USP ethanol. On days 1–3 (Tuesday through Thursday) the length of exposure was 2 h and on the 4th day (Friday) the exposure was 4 h. No alcohol was offered in the intervening period (Saturday through Monday). This protocol was repeated weekly for 16 weeks (Table). Tubes were weighed immediately before and after the exposure period. Volume consumed was converted to g/kg body weight of ethanol.
-
-During a period of 7 weeks, mice received 2 disturbances per day (see Figure). These consisted of being exposed to wet bedding for 1 hour, 1 cm of water in the bottom of the cage with no bedding for 1 hour, no bedding for 1 hour, confinement in a 3 × 3 × 3 cm plastic box for 15 minutes, tilted cage at 45º for 1 hour, and exposure to foreign mouse or fox urine odor for 1 hour. The other stressor was a complete phase shift in the light:dark cycle over each weekend. Disruption of the light cycle (lights constantly on) occurred over the weekend (starting Friday 11:00 am) with the light cycle resuming at 11 am on Monday (lights off). The schedule was repeated weekly over the duration of the study.
-
-Treatment Periods
-
-The entire protocol took 16 weeks to complete and was subdivided into 3 periods: baseline (initial 5 weeks), CMS (next 7 weeks), and postâ€CMS (final 4 weeks). Alcohol was offered as described above for all periods and experimental groups. During the intervening 7â€week CMS period, control animals were subjected to normal housing and experimental (stress) animals were subjected to CMS.
diff --git a/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/processing.rtf b/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/processing.rtf
deleted file mode 100644
index 7d83d76..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/specifics.rtf b/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/specifics.rtf
deleted file mode 100644
index 072040e..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NIAAA BXD Hippocampus CTL RNA-Seq (Oct20) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/tissue.rtf b/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/tissue.rtf
deleted file mode 100644
index 30cdeea..0000000
--- a/general/datasets/NIAAA_BXD_Hip_CTL_RNAseq1020/tissue.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-Tissue Harvest and RNA extraction
-
-The animals were sacrificed under saturated isoflurane. Brains from the animals were dissected under a cold plate (≤4o C), and hippocampus were weighted and snap frozen in dry ice bath with isopentane and stored at −80°C until RNA extraction.
-
-RNA Extraction
-
-Total RNA was extracted using Direct-zol RNA Miniprep Plus Kits (Zymo Research, Irvine, CA, USA) according to the manufacturer’s instructions. Approximately 15 mg of hippocampus tissue was added into a 2 ml tube containing 1 ml TRI Reagent® and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 min in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 rpm followed by incubating for 5 min. 0.1 ml of 1‑bromo-3‑chloropropane was add into the homogenate, shaken vigorously for 15 s, and centrifuged for 15 min at 12,000×g at 4 °C. 600 µl upper aqueous was then transferred into a new collection tube containing 600 µl 100% ethanol. The mixture was loaded into a Zymo-Spin IIC column, wash once with RNA Prep Buffer and twice with RNA Wash Buffer. All RNA had been treated with DNase to eliminate possible DNA contamination, and further precipitated with ethanol. RNA purity and integrity were verified by a nanodrop spectrophotometer and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).
diff --git a/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/cases.rtf b/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/cases.rtf
deleted file mode 100644
index 08a20a8..0000000
--- a/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/cases.rtf
+++ /dev/null
@@ -1,4848 +0,0 @@
-The study included 241 females (aged 50 to 90 ± 2 days at the start of the experiment) from B6, D2, and 35 advanced intercross BXD strains (about 2 mice per strain and per condition). Mice were divided into 4 groups of Control (CTL, 53 mice for 31 strains), Chronic Mild Stress (CMS, 64 mice for 32 strains), Drinking in Dark (DID, 64 mice for 35 strains), and CMS+DID (60 mice for 35 strains). Mice in CTL were normally handled, while mice in other groups were singly housed in shoebox cages, with food and water provided ad libitum except when the water was replaced by 20% (v/v) EtOH (see below) for DID and CMS+DID groups (detailed treatments and schemes are showing in the Table and Figure). The ambient temperature was 21 ± 2°C, and the light cycle was 7:00/19:00 for CTL, and 23:00/11:00 the rest groups lights on/off. The animals were weighed weekly to assess health and to provide the basis for calculating the amount of EtOH consumed in grams per kilogram. All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
-
-The table of samples that are finally used for this study.
-
-
-
-
- |
- Index
- |
-
- ID
- |
-
- Strain
- |
-
- Sex
- |
-
- Treatment Group
- |
-
- Tissue
- |
-
-
- |
- 1
- |
-
- CMS030716_12
- |
-
- BXD68
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 2
- |
-
- CMS030716_18
- |
-
- BXD40
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 3
- |
-
- CMS030716_19
- |
-
- BXD40
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 4
- |
-
- CMS030916_02
- |
-
- BXD101
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 5
- |
-
- CMS030916_09
- |
-
- BXD101
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 6
- |
-
- CMS030916_11
- |
-
- BXD79
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 7
- |
-
- CMS030916_14
- |
-
- BXD48a
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 8
- |
-
- CMS030916_20
- |
-
- BXD65b
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 9
- |
-
- CMS030916_23
- |
-
- BXD65b
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 10
- |
-
- CMS030916_32
- |
-
- BXD86
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 11
- |
-
- CMS032817_02
- |
-
- BXD48
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 12
- |
-
- CMS032817_28
- |
-
- BXD66
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 13
- |
-
- CMS032917_08
- |
-
- BXD48
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 14
- |
-
- CMS032917_24
- |
-
- BXD70
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 15
- |
-
- CMS032917_26
- |
-
- BXD87
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 16
- |
-
- CMS032917_33
- |
-
- BXD70
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 17
- |
-
- CMS033017_05
- |
-
- BXD78
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 18
- |
-
- CMS033017_25
- |
-
- BXD78
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 19
- |
-
- CMS061218_12
- |
-
- BXD87
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 20
- |
-
- CMS061218_13
- |
-
- BXD60
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 21
- |
-
- CMS061218_14
- |
-
- BXD71
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 22
- |
-
- CMS071216_17
- |
-
- BXD24
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 23
- |
-
- CMS071216_23
- |
-
- BXD73B
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 24
- |
-
- CMS071216_25
- |
-
- BXD48a
- |
-
- F
- |
-
- CMS
- |
-
- hippocampus
- |
-
-
- |
- 25
- |
-
- CMS071316_06
- |
-
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- CMS030716_05
- |
-
- BXD44
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 126
- |
-
- CMS030716_14
- |
-
- BXD40
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 127
- |
-
- CMS030716_21
- |
-
- BXD68
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 128
- |
-
- CMS030716_24
- |
-
- BXD48a
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 129
- |
-
- CMS030716_28
- |
-
- BXD79
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 130
- |
-
- CMS030716_33
- |
-
- BXD65b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 131
- |
-
- CMS030916_04
- |
-
- BXD55
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 132
- |
-
- CMS030916_06
- |
-
- BXD65b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 133
- |
-
- CMS030916_07
- |
-
- BXD60
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 134
- |
-
- CMS030916_10
- |
-
- BXD63
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 135
- |
-
- CMS030916_18
- |
-
- BXD65b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 136
- |
-
- CMS030916_22
- |
-
- BXD79
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 137
- |
-
- CMS030916_24
- |
-
- BXD63
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 138
- |
-
- CMS030916_29
- |
-
- BXD55
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 139
- |
-
- CMS030916_33
- |
-
- BXD69
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 140
- |
-
- CMS032817_08
- |
-
- BXD73
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 141
- |
-
- CMS032817_24
- |
-
- BXD70
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 142
- |
-
- CMS032917_07
- |
-
- BXD70
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 143
- |
-
- CMS032917_19
- |
-
- BXD78
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 144
- |
-
- CMS032917_21
- |
-
- BXD86
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 145
- |
-
- CMS032917_23
- |
-
- BXD66
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 146
- |
-
- CMS032917_30
- |
-
- BXD78
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 147
- |
-
- CMS032917_31
- |
-
- BXD48
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 148
- |
-
- CMS032917_32
- |
-
- BXD71
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 149
- |
-
- CMS033017_16
- |
-
- BXD62
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 150
- |
-
- CMS033017_29
- |
-
- BXD83
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 151
- |
-
- CMS071216_04
- |
-
- BXD90
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 152
- |
-
- CMS071216_09
- |
-
- BXD77
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 153
- |
-
- CMS071216_16
- |
-
- BXD65
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 154
- |
-
- CMS071216_22
- |
-
- BXD48a
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 155
- |
-
- CMS071316_15
- |
-
- BXD90
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 156
- |
-
- CMS071316_16
- |
-
- BXD50
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 157
- |
-
- CMS071316_27
- |
-
- BXD65
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 158
- |
-
- CMS071316_30
- |
-
- BXD51
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 159
- |
-
- CMS071416_10
- |
-
- BXD44
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 160
- |
-
- CMS071416_21
- |
-
- BXD69
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 161
- |
-
- CMS082817_12
- |
-
- BXD51
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 162
- |
-
- CMS082817_16
- |
-
- BXD101
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 163
- |
-
- CMS082817_22
- |
-
- BXD101
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 164
- |
-
- CMS082817_23
- |
-
- BXD24
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 165
- |
-
- CMS082917_13
- |
-
- BXD40
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 166
- |
-
- CMS082917_22
- |
-
- BXD87
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 167
- |
-
- CMS083017_10
- |
-
- BXD24
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 168
- |
-
- CMS102215_20
- |
-
- BXD73B
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 169
- |
-
- CMS111716_02
- |
-
- BXD75
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 170
- |
-
- CMS111716_05
- |
-
- BXD43
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 171
- |
-
- CMS111716_08
- |
-
- BXD75
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 172
- |
-
- CMS111716_10
- |
-
- BXD32
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 173
- |
-
- CMS111716_16
- |
-
- BXD100
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 174
- |
-
- CMS111716_20
- |
-
- BXD60
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 175
- |
-
- CMS111716_22
- |
-
- BXD83
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 176
- |
-
- CMS111716_23
- |
-
- BXD73b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 177
- |
-
- CMS111716_25
- |
-
- BXD73a
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 178
- |
-
- CMS111816_01
- |
-
- BXD34
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 179
- |
-
- CMS111816_03
- |
-
- BXD48
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 180
- |
-
- CMS111816_08
- |
-
- BXD43
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 181
- |
-
- CMS111816_11
- |
-
- BXD87
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 182
- |
-
- CMS111816_14
- |
-
- BXD60
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 183
- |
-
- CMS111816_16
- |
-
- BXD73b
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 184
- |
-
- CMS111816_17
- |
-
- BXD77
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 185
- |
-
- CMS111816_20
- |
-
- BXD73a
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 186
- |
-
- CMS111816_28
- |
-
- BXD50
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 187
- |
-
- S32515_12
- |
-
- BXD68
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 188
- |
-
- S32515_16
- |
-
- C57BL/6J
- |
-
- F
- |
-
- DID
- |
-
- hippocampus
- |
-
-
- |
- 189
- |
-
- 13118_35
- |
-
- BXD62
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 190
- |
-
- 13118_41
- |
-
- BXD66
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 191
- |
-
- 13118_56
- |
-
- BXD75
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 192
- |
-
- 31218_19
- |
-
- BXD65b
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 193
- |
-
- 31218_3
- |
-
- BXD73a
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 194
- |
-
- 31218_36
- |
-
- BXD78
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 195
- |
-
- AGE041118_03
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 196
- |
-
- AGE050118_07
- |
-
- BXD55
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 197
- |
-
- AGE050118_12
- |
-
- BXD73
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 198
- |
-
- AGE050118_16
- |
-
- BXD77
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 199
- |
-
- AGE050118_21
- |
-
- BXD86
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 200
- |
-
- AGE050118_23
- |
-
- BXD86
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 201
- |
-
- AGE050118_27
- |
-
- DBA/2J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 202
- |
-
- AGE061818_02
- |
-
- BXD100
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 203
- |
-
- BL013118_12
- |
-
- BXD34
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 204
- |
-
- BL013118_13
- |
-
- BXD34
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 205
- |
-
- CMS092118_24
- |
-
- C57BL/6J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 206
- |
-
- E100118_16
- |
-
- BXD65
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 207
- |
-
- MT052417_09
- |
-
- BXD40
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 208
- |
-
- MT052417_17
- |
-
- BXD51
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 209
- |
-
- S13118_07
- |
-
- BXD24
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 210
- |
-
- S13118_08
- |
-
- BXD24
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 211
- |
-
- S13118_15
- |
-
- BXD40
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 212
- |
-
- S13118_18
- |
-
- BXD43
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 213
- |
-
- S13118_19
- |
-
- BXD43
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 214
- |
-
- S13118_23
- |
-
- BXD48
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 215
- |
-
- S13118_24
- |
-
- BXD48
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 216
- |
-
- S13118_26
- |
-
- BXD48a
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 217
- |
-
- S13118_36
- |
-
- BXD62
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 218
- |
-
- S13118_38
- |
-
- BXD65
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 219
- |
-
- S13118_42
- |
-
- BXD66
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 220
- |
-
- S13118_44
- |
-
- BXD68
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 221
- |
-
- S13118_58
- |
-
- BXD79
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 222
- |
-
- S13118_64
- |
-
- BXD90
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 223
- |
-
- S13118_65
- |
-
- BXD90
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 224
- |
-
- S13118_7
- |
-
- BXD101
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 225
- |
-
- S31218_01
- |
-
- BXD32
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 226
- |
-
- S31218_02
- |
-
- BXD32
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 227
- |
-
- S31218_04
- |
-
- BXD44
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 228
- |
-
- S31218_15
- |
-
- BXD63
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 229
- |
-
- S31218_16
- |
-
- BXD63
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 230
- |
-
- S31218_18
- |
-
- BXD65b
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 231
- |
-
- S31218_1
- |
-
- BXD51
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 232
- |
-
- S31218_21
- |
-
- BXD69
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 233
- |
-
- S31218_22
- |
-
- BXD69
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 234
- |
-
- S31218_24
- |
-
- BXD70
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 235
- |
-
- S31218_25
- |
-
- BXD70
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 236
- |
-
- S31218_27
- |
-
- BXD71
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 237
- |
-
- S31218_28
- |
-
- BXD71
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 238
- |
-
- S31218_31
- |
-
- BXD73a
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 239
- |
-
- S31218_35
- |
-
- BXD78
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 240
- |
-
- S32718_01
- |
-
- DBA/2J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
- |
- 241
- |
-
- S32718_03
- |
-
- DBA/2J
- |
-
- F
- |
-
- CTL
- |
-
- hippocampus
- |
-
-
-
diff --git a/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/experiment-design.rtf b/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/experiment-design.rtf
deleted file mode 100644
index 54fad3e..0000000
--- a/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/experiment-design.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-Alcohol consumption was evaluated using the DID method. The protocol calls for 4 consecutive days of testing. Each day, starting on a Tuesday 3 h after lights were turned off, the water bottles were removed from the cages and replaced with 15 ml centrifuge tubes filled with 20% (v/v) ethanol from 95% USP ethanol. On days 1–3 (Tuesday through Thursday) the length of exposure was 2 h and on the 4th day (Friday) the exposure was 4 h. No alcohol was offered in the intervening period (Saturday through Monday). This protocol was repeated weekly for 16 weeks (Table). Tubes were weighed immediately before and after the exposure period. Volume consumed was converted to g/kg body weight of ethanol.
-
-During a period of 7 weeks, mice received 2 disturbances per day (see Figure). These consisted of being exposed to wet bedding for 1 hour, 1 cm of water in the bottom of the cage with no bedding for 1 hour, no bedding for 1 hour, confinement in a 3 × 3 × 3 cm plastic box for 15 minutes, tilted cage at 45º for 1 hour, and exposure to foreign mouse or fox urine odor for 1 hour. The other stressor was a complete phase shift in the light:dark cycle over each weekend. Disruption of the light cycle (lights constantly on) occurred over the weekend (starting Friday 11:00 am) with the light cycle resuming at 11 am on Monday (lights off). The schedule was repeated weekly over the duration of the study.
-
-Treatment Periods
-
-The entire protocol took 16 weeks to complete and was subdivided into 3 periods: baseline (initial 5 weeks), CMS (next 7 weeks), and postâ€CMS (final 4 weeks). Alcohol was offered as described above for all periods and experimental groups. During the intervening 7â€week CMS period, control animals were subjected to normal housing and experimental (stress) animals were subjected to CMS.
diff --git a/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/processing.rtf b/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/processing.rtf
deleted file mode 100644
index 7d83d76..0000000
--- a/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/specifics.rtf b/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/specifics.rtf
deleted file mode 100644
index 017deac..0000000
--- a/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NIAAA BXD Hippocampus DID RNA-Seq (Oct20) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/tissue.rtf b/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/tissue.rtf
deleted file mode 100644
index 30cdeea..0000000
--- a/general/datasets/NIAAA_BXD_Hip_DID_RNAseq1020/tissue.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-Tissue Harvest and RNA extraction
-
-The animals were sacrificed under saturated isoflurane. Brains from the animals were dissected under a cold plate (≤4o C), and hippocampus were weighted and snap frozen in dry ice bath with isopentane and stored at −80°C until RNA extraction.
-
-RNA Extraction
-
-Total RNA was extracted using Direct-zol RNA Miniprep Plus Kits (Zymo Research, Irvine, CA, USA) according to the manufacturer’s instructions. Approximately 15 mg of hippocampus tissue was added into a 2 ml tube containing 1 ml TRI Reagent® and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 min in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 rpm followed by incubating for 5 min. 0.1 ml of 1‑bromo-3‑chloropropane was add into the homogenate, shaken vigorously for 15 s, and centrifuged for 15 min at 12,000×g at 4 °C. 600 µl upper aqueous was then transferred into a new collection tube containing 600 µl 100% ethanol. The mixture was loaded into a Zymo-Spin IIC column, wash once with RNA Prep Buffer and twice with RNA Wash Buffer. All RNA had been treated with DNase to eliminate possible DNA contamination, and further precipitated with ethanol. RNA purity and integrity were verified by a nanodrop spectrophotometer and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).
diff --git a/general/datasets/NIA_AgBXD_Liv_CDHFD_rna_seq_0818/specifics.rtf b/general/datasets/NIA_AgBXD_Liv_CDHFD_rna_seq_0818/specifics.rtf
deleted file mode 100644
index 8ee3ead..0000000
--- a/general/datasets/NIA_AgBXD_Liv_CDHFD_rna_seq_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-CD+HFD
\ No newline at end of file
diff --git a/general/datasets/NIA_AgBXD_Liv_CDHFD_rna_seq_0818/summary.rtf b/general/datasets/NIA_AgBXD_Liv_CDHFD_rna_seq_0818/summary.rtf
deleted file mode 100644
index f32b018..0000000
--- a/general/datasets/NIA_AgBXD_Liv_CDHFD_rna_seq_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Impact of diet and genetics on survival in BXD GRP. Overall, on a population level of 84 unique BXD strains (666 mice on CD and 688 on HFD) when all strains were averaged the CD cohort lived significantly longer than the HFD cohort if genetics is not considered. (This dataset still unpublished). For more information or for access to this dataset please contact the person in the contact list above.
diff --git a/general/datasets/NIA_AgBXD_Liv_CD_rna_seq_0818/specifics.rtf b/general/datasets/NIA_AgBXD_Liv_CD_rna_seq_0818/specifics.rtf
deleted file mode 100644
index be3025c..0000000
--- a/general/datasets/NIA_AgBXD_Liv_CD_rna_seq_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-CD Control diet.
\ No newline at end of file
diff --git a/general/datasets/NIA_AgBXD_Liv_CD_rna_seq_0818/summary.rtf b/general/datasets/NIA_AgBXD_Liv_CD_rna_seq_0818/summary.rtf
deleted file mode 100644
index f32b018..0000000
--- a/general/datasets/NIA_AgBXD_Liv_CD_rna_seq_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Impact of diet and genetics on survival in BXD GRP. Overall, on a population level of 84 unique BXD strains (666 mice on CD and 688 on HFD) when all strains were averaged the CD cohort lived significantly longer than the HFD cohort if genetics is not considered. (This dataset still unpublished). For more information or for access to this dataset please contact the person in the contact list above.
diff --git a/general/datasets/NIA_AgBXD_Liv_HFD_rna_seq_0818/specifics.rtf b/general/datasets/NIA_AgBXD_Liv_HFD_rna_seq_0818/specifics.rtf
deleted file mode 100644
index a21c56e..0000000
--- a/general/datasets/NIA_AgBXD_Liv_HFD_rna_seq_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-HFD High fat diet.
\ No newline at end of file
diff --git a/general/datasets/NIA_AgBXD_Liv_HFD_rna_seq_0818/summary.rtf b/general/datasets/NIA_AgBXD_Liv_HFD_rna_seq_0818/summary.rtf
deleted file mode 100644
index f32b018..0000000
--- a/general/datasets/NIA_AgBXD_Liv_HFD_rna_seq_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Impact of diet and genetics on survival in BXD GRP. Overall, on a population level of 84 unique BXD strains (666 mice on CD and 688 on HFD) when all strains were averaged the CD cohort lived significantly longer than the HFD cohort if genetics is not considered. (This dataset still unpublished). For more information or for access to this dataset please contact the person in the contact list above.
diff --git a/general/datasets/Nci_agil_mam_tum_rma_0409/summary.rtf b/general/datasets/Nci_agil_mam_tum_rma_0409/summary.rtf
new file mode 100644
index 0000000..adb7c9d
--- /dev/null
+++ b/general/datasets/Nci_agil_mam_tum_rma_0409/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 71, Name: NCI Mammary LMT miRNA v2 (Apr09) RMA
\ No newline at end of file
diff --git a/general/datasets/Nci_mam_tum_rma_0409/experiment-type.rtf b/general/datasets/Nci_mam_tum_rma_0409/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Nci_mam_tum_rma_0409/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Nci_mam_tum_rma_0409/summary.rtf b/general/datasets/Nci_mam_tum_rma_0409/summary.rtf
new file mode 100644
index 0000000..bc18abd
--- /dev/null
+++ b/general/datasets/Nci_mam_tum_rma_0409/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 72, Name: NCI Mammary M430v2 (Apr09) RMA
\ No newline at end of file
diff --git a/general/datasets/Ncsu_droswb_lc_rma_0111/acknowledgment.rtf b/general/datasets/Ncsu_droswb_lc_rma_0111/acknowledgment.rtf
new file mode 100644
index 0000000..3a00fd4
--- /dev/null
+++ b/general/datasets/Ncsu_droswb_lc_rma_0111/acknowledgment.rtf
@@ -0,0 +1 @@
+Mackay laboratory: http://mackay.gnets.ncsu.edu/MackaySite/Homepage.html
diff --git a/general/datasets/Ncsu_droswb_lc_rma_0111/cases.rtf b/general/datasets/Ncsu_droswb_lc_rma_0111/cases.rtf
new file mode 100644
index 0000000..333a904
--- /dev/null
+++ b/general/datasets/Ncsu_droswb_lc_rma_0111/cases.rtf
@@ -0,0 +1,3 @@
+The raw microarray data are deposited in the ArrayExpress database (www.ebi.ac.uk/arrayexpress,) under accession number E-MEXP-1594
+
+We have derived a population of 192 inbred lines by 20 generations of full sib inbreeding of isofemale lines collected from the Raleigh, NC population. A White Paper to obtain complete genome sequences of these lines (link to pdf of White Paper) has been approved by the National Institutes of Health National Human Genome Research Institute, using a combination of 454 XLR long read pyrosequencing and paired end Solexa short read (currently 45 bp) technology. The sequencing is being done at the Baylor College of Medicine Sequencing Center, in collaboration with Richard Gibbs and Stephen Richards.
diff --git a/general/datasets/Ncsu_droswb_lc_rma_0111/citation.rtf b/general/datasets/Ncsu_droswb_lc_rma_0111/citation.rtf
new file mode 100644
index 0000000..8d1d5d7
--- /dev/null
+++ b/general/datasets/Ncsu_droswb_lc_rma_0111/citation.rtf
@@ -0,0 +1 @@
+Ayroles JF, Carbone MA, Stone EA, Jordan KW, Lyman RF, Magwire MM, Rollmann SM, Duncan LH, Lawrence F, Anholt RR, Mackay TF (2009) Systems genetics of complex traits in Drosophila melanogaster. Nat Genet 41(3):299-307. PMID: 19234471
diff --git a/general/datasets/Ncsu_droswb_lc_rma_0111/contributors.rtf b/general/datasets/Ncsu_droswb_lc_rma_0111/contributors.rtf
new file mode 100644
index 0000000..3e69a35
--- /dev/null
+++ b/general/datasets/Ncsu_droswb_lc_rma_0111/contributors.rtf
@@ -0,0 +1,3 @@
+Ayroles JF, Carbone MA, Stone EA, Jordan KW, Lyman RF, Magwire MM, Rollmann SM, Duncan LH, Lawrence F, Anholt RR, Mackay TF.
+
+Data entry by Arthur Centeno, UTHSC.
diff --git a/general/datasets/Ncsu_droswb_lc_rma_0111/experiment-design.rtf b/general/datasets/Ncsu_droswb_lc_rma_0111/experiment-design.rtf
new file mode 100644
index 0000000..387a16a
--- /dev/null
+++ b/general/datasets/Ncsu_droswb_lc_rma_0111/experiment-design.rtf
@@ -0,0 +1,5 @@
+We derived inbred lines from the Raleigh, USA population by 20 generations of full-sib mating. We used the C(2L)RM-P1, b1; C(2R)RM-SKIA, cn1bw1 compound autosome (CA) stock for fitness assays. P-element mutations and co-isogenic control lines were a gift of H. Bellen (Howard Hughes Medical Institute, Baylor College of Medicine). We reared flies on cornmeal-molasses-agar medium at 25 °C, 60–75% relative humidity and a 12-h light-dark cycle unless otherwise specified.
+
+Organismal phenotypes.
+
+For the starvation stress resistance group, we placed ten same-sex, 2-d-old flies in vials containing 1.5% agar and 5 ml water, and scored survival every eight hours (N = 5 vials/sex/line). For the chill coma recovery group, we placed 3- to 7-d-old flies in empty vials on ice for three hours, and recorded the time for each individual to right itself after transfer to room temperature (N = 20 flies/sex/line). For longevity, we placed five 1- to 2-d-old same-sex virgin flies into vials containing 5 ml medium, and recorded survival every two days (N = 5 vials/sex/line). For locomotor reactivity, we placed single 3- to 7-d-old flies into vials containing 5 ml medium. The following day, between 8 am and 12 pm, we mechanically disturbed each fly19, and recorded the total activity in the 45 s immediately following the disturbance. We obtained two replicate measurements of 20 flies/sex/replicate/line. For the copulation latency group, we aspirated pairs of 3- to 7-d-old virgin flies into vials containing 5 ml medium between 8 am and 12 pm, and recorded the number of minutes until initiation of copulation, for a maximum of 120 min (N = 24 pairs/line). For the reproductive fitness group, we used the competitive index technique45, 46. We reared all wild-type and CA parents in constant density (10 pairs) vials. We placed six 3- to 4-d-old virgin CA males and females and three 3- to 4-d-old wild-type males and females in a vial containing 10 ml medium, discarding the flies after 7 d. The competitive index was the ratio of the number of wild type to the total number of progeny emerging by day 17 (N = 20 replicate vials/line).
diff --git a/general/datasets/Ncsu_droswb_lc_rma_0111/experiment-type.rtf b/general/datasets/Ncsu_droswb_lc_rma_0111/experiment-type.rtf
new file mode 100644
index 0000000..22e3439
--- /dev/null
+++ b/general/datasets/Ncsu_droswb_lc_rma_0111/experiment-type.rtf
@@ -0,0 +1 @@
+We derived inbred lines from the Raleigh, USA population by 20 generations of full-sib mating. We used the C(2L)RM-P1, b1; C(2R)RM-SKIA, cn1bw1 compound autosome (CA) stock for fitness assays. P-element mutations and co-isogenic control lines were a gift of H. Bellen (Howard Hughes Medical Institute, Baylor College of Medicine). We reared flies on cornmeal-molasses-agar medium at 25 °C, 60–75% relative humidity and a 12-h light-dark cycle unless otherwise specified.
\ No newline at end of file
diff --git a/general/datasets/Ncsu_droswb_lc_rma_0111/notes.rtf b/general/datasets/Ncsu_droswb_lc_rma_0111/notes.rtf
new file mode 100644
index 0000000..790f36a
--- /dev/null
+++ b/general/datasets/Ncsu_droswb_lc_rma_0111/notes.rtf
@@ -0,0 +1,3 @@
+Please see Mackay lab link: http://mackay.gnets.ncsu.edu/MackaySite/DGRP_files/The40ExpressionDataMatrix10096.txt
+
+ArrayExpress: accession number E-MEXP-1594
diff --git a/general/datasets/Ncsu_droswb_lc_rma_0111/platform.rtf b/general/datasets/Ncsu_droswb_lc_rma_0111/platform.rtf
new file mode 100644
index 0000000..74f3b36
--- /dev/null
+++ b/general/datasets/Ncsu_droswb_lc_rma_0111/platform.rtf
@@ -0,0 +1,3 @@
+We used Affymetrix Drosophila 2.0 arrays to assess transcript profiles of 3- to 5-d-old flies from the inbred lines. All samples were frozen between 1 and 3 pm. We extracted RNA from two independent pools (25 flies/sex/line), and hybridized 10 g fragmented cRNA to each array. We randomized RNA extraction, labeling and array hybridization across all samples, and normalized the raw array data across sexes and lines using a median standardization.
+
+Each transcript is represented by 14 perfect-match 25-bp oligonucleotides. To identify perfect-match probes with SFPs between the wild-derived lines and the strain used to design the array, we quantified the maximal degree to which the variation between lines could be reduced by partitioning the lines into two allelic classes. We computed the sum of squared deviations from each class mean and expressed their sum as a fraction of the total sum of squares. The smallest fraction across all bipartitions was used to score each probe. We identified 3,136 candidate SFPs with scores 0.1 (a tenfold reduction in the sum of squares). We validated polymorphisms in 20 of 21 of these SFPs by designing primers flanking the SFP and sequencing the PCR products (data not shown).
diff --git a/general/datasets/Ncsu_droswb_lc_rma_0111/processing.rtf b/general/datasets/Ncsu_droswb_lc_rma_0111/processing.rtf
new file mode 100644
index 0000000..33266b5
--- /dev/null
+++ b/general/datasets/Ncsu_droswb_lc_rma_0111/processing.rtf
@@ -0,0 +1,3 @@
+Our measure of expression for each probe set was the median log2 signal intensity of perfect-match probes without SFPs. We used negative control probes to estimate the background intensity, and removed probes below this threshold.
+
+Data may have been normalized prior to entry into GeneNetwork using 2z + 8 transform. This method simply stabilizes the variance of all array data sets, and resets the z score to 8 (rather than 0).
diff --git a/general/datasets/Ncsu_droswb_lc_rma_0111/summary.rtf b/general/datasets/Ncsu_droswb_lc_rma_0111/summary.rtf
new file mode 100644
index 0000000..68b99df
--- /dev/null
+++ b/general/datasets/Ncsu_droswb_lc_rma_0111/summary.rtf
@@ -0,0 +1,2 @@
+Determining the genetic architecture of complex traits is challenging because phenotypic variation arises from interactions between multiple, environmentally sensitive alleles. We quantified genomewide transcript abundance and phenotypes for six ecologically relevant traits in D. melanogaster wild-derived inbred lines. We observed 10,096 genetically variable transcripts and high heritabilities for all organismal phenotypes. The transcriptome is highly genetically inter-correlated, forming 241 transcriptional modules. Modules are enriched for transcripts in common pathways, gene ontology categories, tissue-specific expression, and transcription factor binding sites. The high transcriptional connectivity allows us to infer genetic networks and the function of predicted genes based on annotations of other genes in the network. Regressions of organismal phenotypes on transcript abundance implicate several hundred candidate genes that form modules of biologically meaningful correlated transcripts affecting each phenotype. Overlapping transcripts in modules associated with different traits provides insight into the molecular basis of pleiotropy between complex traits.
+Full Article
diff --git a/general/datasets/Ncsu_droswb_lc_rma_0111/tissue.rtf b/general/datasets/Ncsu_droswb_lc_rma_0111/tissue.rtf
new file mode 100644
index 0000000..0ba4e81
--- /dev/null
+++ b/general/datasets/Ncsu_droswb_lc_rma_0111/tissue.rtf
@@ -0,0 +1 @@
+Whole body. 3- to 5-d-old flies from the inbred lines. All samples were frozen between 1 and 3 pm. We extracted RNA from two independent pools (25 flies/sex/line)We derived inbred lines from the Raleigh, USA population by 20 generations of full-sib mating. We used the C(2L)RM-P1, b1; C(2R)RM-SKIA, cn1bw1 compound autosome (CA) stock for fitness assays. P-element mutations and co-isogenic control lines were a gift of H. Bellen (Howard Hughes Medical Institute, Baylor College of Medicine). We reared flies on cornmeal-molasses-agar medium at 25 °C, 60–75% relative humidity and a 12-h light-dark cycle unless otherwise specified.
diff --git a/general/datasets/Nhlbi_bxd_aged_heart_cd_rna_seq_1120/experiment-design.rtf b/general/datasets/Nhlbi_bxd_aged_heart_cd_rna_seq_1120/experiment-design.rtf
new file mode 100644
index 0000000..fbdad24
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_aged_heart_cd_rna_seq_1120/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Extraction
+
+Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Approximately 30 mg of left ventricle tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/Nhlbi_bxd_aged_heart_cd_rna_seq_1120/processing.rtf b/general/datasets/Nhlbi_bxd_aged_heart_cd_rna_seq_1120/processing.rtf
new file mode 100644
index 0000000..8e460ff
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_aged_heart_cd_rna_seq_1120/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/Nhlbi_bxd_aged_heart_cd_rna_seq_1120/specifics.rtf b/general/datasets/Nhlbi_bxd_aged_heart_cd_rna_seq_1120/specifics.rtf
new file mode 100644
index 0000000..d109d3c
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_aged_heart_cd_rna_seq_1120/specifics.rtf
@@ -0,0 +1,2770 @@
+NHLBI BXD Aged Heart CD RNA-Seq (Nov20) TMP Log2
+
+About the cases used to generate this set of data:
+
+The study included 105 mice (~12 month) from B6, D2, B6D2F1,and 51 advanced intercross BXD strains (about 2 mice per strain). All mice were fed on chow diet (CD). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+
+
+The table of samples that are finally used for this study.
+
+
+
+
+ |
+ Index
+ |
+
+ Sample ID
+ |
+
+ Case id
+ |
+
+ Strain
+ |
+
+ Fuyi_Sex_Final
+ |
+
+ Sac age/Day
+ |
+
+ Tissue
+ |
+
+ Diet
+ |
+
+
+ |
+ 1
+ |
+
+ K100
+ |
+
+ *103017.77
+ |
+
+ BXD155
+ |
+
+ M
+ |
+
+ 362
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 2
+ |
+
+ K101
+ |
+
+ *071917.111
+ |
+
+ BXD184
+ |
+
+ M
+ |
+
+ 387
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 3
+ |
+
+ K104
+ |
+
+ *103017.75
+ |
+
+ BXD155
+ |
+
+ F
+ |
+
+ 362
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 4
+ |
+
+ K107
+ |
+
+ *071917.45
+ |
+
+ BXD73
+ |
+
+ F
+ |
+
+ 338
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 5
+ |
+
+ K108
+ |
+
+ *071917.72
+ |
+
+ BXD90
+ |
+
+ M
+ |
+
+ 330
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 6
+ |
+
+ K10
+ |
+
+ *062117.51
+ |
+
+ BXD150
+ |
+
+ F
+ |
+
+ 385
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 7
+ |
+
+ K112
+ |
+
+ *071917.74
+ |
+
+ BXD122
+ |
+
+ M
+ |
+
+ 331
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 8
+ |
+
+ K113
+ |
+
+ *071917.88
+ |
+
+ BXD144
+ |
+
+ M
+ |
+
+ 331
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 9
+ |
+
+ K114
+ |
+
+ *071917.47
+ |
+
+ BXD73
+ |
+
+ M
+ |
+
+ 338
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 10
+ |
+
+ K117
+ |
+
+ *071917.87
+ |
+
+ BXD144
+ |
+
+ F
+ |
+
+ 331
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 11
+ |
+
+ K118
+ |
+
+ *071917.73
+ |
+
+ BXD122
+ |
+
+ F
+ |
+
+ 331
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 12
+ |
+
+ K12
+ |
+
+ *062117.48
+ |
+
+ BXD125
+ |
+
+ F
+ |
+
+ 396
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 13
+ |
+
+ K13
+ |
+
+ *062117.54
+ |
+
+ BXD151
+ |
+
+ F
+ |
+
+ 396
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 14
+ |
+
+ K143
+ |
+
+ *071917.18
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ 387
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 15
+ |
+
+ K144
+ |
+
+ *071917.42
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ 400
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 16
+ |
+
+ K147
+ |
+
+ *071917.31
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ 331
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 17
+ |
+
+ K149
+ |
+
+ *071917.92
+ |
+
+ BXD156
+ |
+
+ F
+ |
+
+ 342
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 18
+ |
+
+ K14
+ |
+
+ *062117.55
+ |
+
+ BXD151
+ |
+
+ M
+ |
+
+ 396
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 19
+ |
+
+ K150
+ |
+
+ *071917.93
+ |
+
+ BXD156
+ |
+
+ M
+ |
+
+ 342
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 20
+ |
+
+ K152
+ |
+
+ *071917.107
+ |
+
+ BXD180
+ |
+
+ M
+ |
+
+ 341
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 21
+ |
+
+ K153
+ |
+
+ *071917.89
+ |
+
+ BXD152
+ |
+
+ F
+ |
+
+ 405
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 22
+ |
+
+ K155
+ |
+
+ *071917.70
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ 330
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 23
+ |
+
+ K156
+ |
+
+ *071917.33
+ |
+
+ BXD66
+ |
+
+ M
+ |
+
+ 331
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 24
+ |
+
+ K15
+ |
+
+ *062117.34
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ 355
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 25
+ |
+
+ K164
+ |
+
+ E092718.08
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ 340
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 26
+ |
+
+ K165
+ |
+
+ E092718.09
+ |
+
+ BXD40
+ |
+
+ M
+ |
+
+ 340
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 27
+ |
+
+ K168
+ |
+
+ E100318.34
+ |
+
+ BXD102
+ |
+
+ F
+ |
+
+ 412
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 28
+ |
+
+ K169
+ |
+
+ E100318.35
+ |
+
+ BXD102
+ |
+
+ M
+ |
+
+ 412
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 29
+ |
+
+ K16
+ |
+
+ *062117.44
+ |
+
+ BXD123
+ |
+
+ F
+ |
+
+ 361
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 30
+ |
+
+ K172
+ |
+
+ *041118.01
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ 343
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 31
+ |
+
+ K173
+ |
+
+ *041118.03
+ |
+
+ C57BL/6J
+ |
+
+ M
+ |
+
+ 343
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 32
+ |
+
+ K175
+ |
+
+ *041118.05
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ 435
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 33
+ |
+
+ K176
+ |
+
+ *041118.06
+ |
+
+ DBA/2J
+ |
+
+ M
+ |
+
+ 435
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 34
+ |
+
+ K177
+ |
+
+ 042314.10
+ |
+
+ B6D2F1
+ |
+
+ M
+ |
+
+ 364
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 35
+ |
+
+ K178
+ |
+
+ 042314.12
+ |
+
+ B6D2F1
+ |
+
+ F
+ |
+
+ 364
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 36
+ |
+
+ K17
+ |
+
+ *062117.41
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ 449
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 37
+ |
+
+ K182
+ |
+
+ 083016.01
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ 386
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 38
+ |
+
+ K183
+ |
+
+ 083016.02
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ 386
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 39
+ |
+
+ K18
+ |
+
+ *062117.49
+ |
+
+ BXD125
+ |
+
+ M
+ |
+
+ 396
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 40
+ |
+
+ K19
+ |
+
+ *062117.45
+ |
+
+ BXD123
+ |
+
+ F
+ |
+
+ 361
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 41
+ |
+
+ K21
+ |
+
+ *062117.43
+ |
+
+ BXD100
+ |
+
+ M
+ |
+
+ 449
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 42
+ |
+
+ K22
+ |
+
+ *062117.28
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ 359
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 43
+ |
+
+ K23
+ |
+
+ *062117.39
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ 359
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 44
+ |
+
+ K24
+ |
+
+ *062117.52
+ |
+
+ BXD150
+ |
+
+ M
+ |
+
+ 385
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 45
+ |
+
+ K25
+ |
+
+ *062117.29
+ |
+
+ BXD70
+ |
+
+ M
+ |
+
+ 359
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 46
+ |
+
+ K27
+ |
+
+ *071917.54
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ 366
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 47
+ |
+
+ K28
+ |
+
+ *071917.50
+ |
+
+ BXD73b
+ |
+
+ M
+ |
+
+ 422
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 48
+ |
+
+ K29
+ |
+
+ *071917.66
+ |
+
+ BXD86
+ |
+
+ M
+ |
+
+ 404
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 49
+ |
+
+ K2
+ |
+
+ *071917.106
+ |
+
+ BXD178
+ |
+
+ M
+ |
+
+ 359
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 50
+ |
+
+ K30
+ |
+
+ *103017.59
+ |
+
+ BXD113
+ |
+
+ F
+ |
+
+ 373
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 51
+ |
+
+ K32
+ |
+
+ *103017.83
+ |
+
+ BXD168
+ |
+
+ M
+ |
+
+ 398
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 52
+ |
+
+ K33
+ |
+
+ *103017.81
+ |
+
+ BXD168
+ |
+
+ F
+ |
+
+ 398
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 53
+ |
+
+ K35
+ |
+
+ *103017.74
+ |
+
+ BXD154
+ |
+
+ M
+ |
+
+ 417
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 54
+ |
+
+ K36
+ |
+
+ *103017.86
+ |
+
+ BXD195
+ |
+
+ F
+ |
+
+ 355
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 55
+ |
+
+ K38
+ |
+
+ *103017.61
+ |
+
+ BXD113
+ |
+
+ M
+ |
+
+ 373
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 56
+ |
+
+ K39
+ |
+
+ *103017.72
+ |
+
+ BXD154
+ |
+
+ F
+ |
+
+ 417
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 57
+ |
+
+ K40
+ |
+
+ *103017.51
+ |
+
+ BXD83
+ |
+
+ M
+ |
+
+ 407
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 58
+ |
+
+ K41
+ |
+
+ *103017.49
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ 407
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 59
+ |
+
+ K42
+ |
+
+ *103017.87
+ |
+
+ BXD195
+ |
+
+ M
+ |
+
+ 355
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 60
+ |
+
+ K44
+ |
+
+ *062117.40
+ |
+
+ BXD87
+ |
+
+ M
+ |
+
+ 359
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 61
+ |
+
+ K49
+ |
+
+ *062117.63
+ |
+
+ BXD169
+ |
+
+ F
+ |
+
+ 352
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 62
+ |
+
+ K4
+ |
+
+ *071917.105
+ |
+
+ BXD178
+ |
+
+ F
+ |
+
+ 359
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 63
+ |
+
+ K50
+ |
+
+ *062117.04
+ |
+
+ BXD18
+ |
+
+ M
+ |
+
+ 379
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 64
+ |
+
+ K51
+ |
+
+ *062117.17
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ 380
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 65
+ |
+
+ K53
+ |
+
+ *062117.06
+ |
+
+ BXD27
+ |
+
+ F
+ |
+
+ 435
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 66
+ |
+
+ K54
+ |
+
+ *062117.02
+ |
+
+ BXD15
+ |
+
+ M
+ |
+
+ 379
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 67
+ |
+
+ K56
+ |
+
+ *062117.15
+ |
+
+ BXD45
+ |
+
+ M
+ |
+
+ 437
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 68
+ |
+
+ K57
+ |
+
+ *062117.25
+ |
+
+ BXD63
+ |
+
+ F
+ |
+
+ 404
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 69
+ |
+
+ K59
+ |
+
+ *062117.01
+ |
+
+ BXD15
+ |
+
+ F
+ |
+
+ 379
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 70
+ |
+
+ K5
+ |
+
+ *071917.104
+ |
+
+ BXD161
+ |
+
+ M
+ |
+
+ 352
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 71
+ |
+
+ K60
+ |
+
+ *062117.13
+ |
+
+ BXD34
+ |
+
+ M
+ |
+
+ 411
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 72
+ |
+
+ K61
+ |
+
+ *062117.12
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ 411
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 73
+ |
+
+ K62
+ |
+
+ *062117.26
+ |
+
+ BXD63
+ |
+
+ M
+ |
+
+ 404
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 74
+ |
+
+ K63
+ |
+
+ *062117.18
+ |
+
+ BXD48
+ |
+
+ M
+ |
+
+ 380
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 75
+ |
+
+ K65
+ |
+
+ *062117.03
+ |
+
+ BXD18
+ |
+
+ F
+ |
+
+ 379
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 76
+ |
+
+ K67
+ |
+
+ *062117.62
+ |
+
+ BXD169
+ |
+
+ F
+ |
+
+ 352
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 77
+ |
+
+ K68
+ |
+
+ *062117.14
+ |
+
+ BXD45
+ |
+
+ F
+ |
+
+ 437
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 78
+ |
+
+ K69
+ |
+
+ *062117.07
+ |
+
+ BXD27
+ |
+
+ M
+ |
+
+ 435
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 79
+ |
+
+ K6
+ |
+
+ *071917.100
+ |
+
+ BXD160
+ |
+
+ F
+ |
+
+ 446
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 80
+ |
+
+ K71
+ |
+
+ *071917.63
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ 418
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 81
+ |
+
+ K73
+ |
+
+ *071917.64
+ |
+
+ BXD79
+ |
+
+ M
+ |
+
+ 418
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 82
+ |
+
+ K74
+ |
+
+ *071917.56
+ |
+
+ BXD75
+ |
+
+ M
+ |
+
+ 366
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 83
+ |
+
+ K76
+ |
+
+ *071917.65
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ 404
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 84
+ |
+
+ K78
+ |
+
+ *071917.01
+ |
+
+ BXD16
+ |
+
+ F
+ |
+
+ 416
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 85
+ |
+
+ K79
+ |
+
+ *071917.03
+ |
+
+ BXD16
+ |
+
+ M
+ |
+
+ 416
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 86
+ |
+
+ K7
+ |
+
+ *071917.98
+ |
+
+ BXD157
+ |
+
+ M
+ |
+
+ 381
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 87
+ |
+
+ K80
+ |
+
+ *071917.26
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ 423
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 88
+ |
+
+ K82
+ |
+
+ *071917.28
+ |
+
+ BXD65
+ |
+
+ M
+ |
+
+ 423
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 89
+ |
+
+ K83
+ |
+
+ *071917.44
+ |
+
+ BXD71
+ |
+
+ M
+ |
+
+ 400
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 90
+ |
+
+ K84
+ |
+
+ *071917.30
+ |
+
+ BXD65b
+ |
+
+ M
+ |
+
+ 351
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 91
+ |
+
+ K85
+ |
+
+ *071917.20
+ |
+
+ BXD48a
+ |
+
+ M
+ |
+
+ 387
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 92
+ |
+
+ K86
+ |
+
+ *071917.29
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ 351
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 93
+ |
+
+ K88
+ |
+
+ *071917.97
+ |
+
+ BXD157
+ |
+
+ M
+ |
+
+ 381
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 94
+ |
+
+ K89
+ |
+
+ *071917.101
+ |
+
+ BXD160
+ |
+
+ M
+ |
+
+ 446
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 95
+ |
+
+ K90
+ |
+
+ *071917.112
+ |
+
+ BXD186
+ |
+
+ F
+ |
+
+ 403
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 96
+ |
+
+ K91
+ |
+
+ *071917.102
+ |
+
+ BXD161
+ |
+
+ F
+ |
+
+ 352
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 97
+ |
+
+ K92
+ |
+
+ *071917.114
+ |
+
+ BXD186
+ |
+
+ M
+ |
+
+ 403
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 98
+ |
+
+ K93
+ |
+
+ *071917.90
+ |
+
+ BXD152
+ |
+
+ F
+ |
+
+ 405
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 99
+ |
+
+ K94
+ |
+
+ *071917.53
+ |
+
+ BXD74
+ |
+
+ M
+ |
+
+ 427
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 100
+ |
+
+ K95
+ |
+
+ *071917.48
+ |
+
+ BXD73b
+ |
+
+ F
+ |
+
+ 422
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 101
+ |
+
+ K96
+ |
+
+ *071917.52
+ |
+
+ BXD74
+ |
+
+ F
+ |
+
+ 427
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 102
+ |
+
+ K97
+ |
+
+ *062117.36
+ |
+
+ BXD84
+ |
+
+ F
+ |
+
+ 441
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 103
+ |
+
+ K98
+ |
+
+ *103017.58
+ |
+
+ BXD111
+ |
+
+ M
+ |
+
+ 441
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 104
+ |
+
+ K99
+ |
+
+ *103017.57
+ |
+
+ BXD111
+ |
+
+ F
+ |
+
+ 441
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 105
+ |
+
+ K9
+ |
+
+ *062117.33
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ 355
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+
diff --git a/general/datasets/Nhlbi_bxd_aged_heart_cd_rna_seq_1120/tissue.rtf b/general/datasets/Nhlbi_bxd_aged_heart_cd_rna_seq_1120/tissue.rtf
new file mode 100644
index 0000000..8d370c0
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_aged_heart_cd_rna_seq_1120/tissue.rtf
@@ -0,0 +1,3 @@
+Tissue Harvest
+
+The animals were sacrificed under saturated isoflurane. Whole heart from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Nhlbi_bxd_aged_heart_hfd_rna_seq_1120/experiment-design.rtf b/general/datasets/Nhlbi_bxd_aged_heart_hfd_rna_seq_1120/experiment-design.rtf
new file mode 100644
index 0000000..fbdad24
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_aged_heart_hfd_rna_seq_1120/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Extraction
+
+Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Approximately 30 mg of left ventricle tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/Nhlbi_bxd_aged_heart_hfd_rna_seq_1120/processing.rtf b/general/datasets/Nhlbi_bxd_aged_heart_hfd_rna_seq_1120/processing.rtf
new file mode 100644
index 0000000..8e460ff
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_aged_heart_hfd_rna_seq_1120/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/Nhlbi_bxd_aged_heart_hfd_rna_seq_1120/specifics.rtf b/general/datasets/Nhlbi_bxd_aged_heart_hfd_rna_seq_1120/specifics.rtf
new file mode 100644
index 0000000..49d8e5b
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_aged_heart_hfd_rna_seq_1120/specifics.rtf
@@ -0,0 +1,1758 @@
+NHLBI BXD Aged Heart HFD RNA-Seq (Nov20) TMP Log2
+
+About the cases used to generate this set of data:
+
+The study included 66 mice (~12 month) from B6, B6D2F1, D2B6F1, and 31 advanced intercross BXD strains (about 2 mice per strain). All mice were fed on high fat diet (HFD). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+
+
+The table of samples that are finally used for this study.
+
+
+
+
+ |
+ Index
+ |
+
+ Sample ID
+ |
+
+ Case id
+ |
+
+ Strain
+ |
+
+ Fuyi_Sex_Final
+ |
+
+ Sac age/Day
+ |
+
+ Tissue
+ |
+
+ Diet
+ |
+
+
+ |
+ 1
+ |
+
+ A12
+ |
+
+ 042214.06
+ |
+
+ BXD29
+ |
+
+ F
+ |
+
+ 369
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 2
+ |
+
+ A13
+ |
+
+ 042214.13
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ 360
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 3
+ |
+
+ A14
+ |
+
+ 042214.14
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ 360
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 4
+ |
+
+ A15
+ |
+
+ 042314.15
+ |
+
+ C57BL/6J
+ |
+
+ M
+ |
+
+ 363
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 5
+ |
+
+ A16
+ |
+
+ 042314.16
+ |
+
+ C57BL/6J
+ |
+
+ M
+ |
+
+ 363
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 6
+ |
+
+ A17
+ |
+
+ 042314.08
+ |
+
+ B6D2F1
+ |
+
+ M
+ |
+
+ 404
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 7
+ |
+
+ A18
+ |
+
+ 042314.07
+ |
+
+ B6D2F1
+ |
+
+ M
+ |
+
+ 404
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 8
+ |
+
+ A19
+ |
+
+ 042314.05
+ |
+
+ BXD64
+ |
+
+ F
+ |
+
+ 366
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 9
+ |
+
+ A20
+ |
+
+ 042314.06
+ |
+
+ BXD64
+ |
+
+ F
+ |
+
+ 366
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 10
+ |
+
+ A21
+ |
+
+ 042314.03
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ 363
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 11
+ |
+
+ A22
+ |
+
+ 042314.04
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ 363
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 12
+ |
+
+ A23
+ |
+
+ 042314.02
+ |
+
+ D2B6F1
+ |
+
+ F
+ |
+
+ 371
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 13
+ |
+
+ A24
+ |
+
+ 042314.01
+ |
+
+ D2B6F1
+ |
+
+ F
+ |
+
+ 371
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 14
+ |
+
+ A25
+ |
+
+ 021313.30
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ 359
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 15
+ |
+
+ A26
+ |
+
+ 021313.29
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ 359
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 16
+ |
+
+ A27
+ |
+
+ 042915.06
+ |
+
+ BXD29
+ |
+
+ F
+ |
+
+ 431
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 17
+ |
+
+ A28
+ |
+
+ 050115.03
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ 415
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 18
+ |
+
+ A29
+ |
+
+ 042915.10
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ 441
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 19
+ |
+
+ A2
+ |
+
+ 042415.14
+ |
+
+ BXD102
+ |
+
+ F
+ |
+
+ 353
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 20
+ |
+
+ A30
+ |
+
+ 050115.04
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ 415
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 21
+ |
+
+ A31
+ |
+
+ 121515.16
+ |
+
+ BXD45
+ |
+
+ F
+ |
+
+ 350
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 22
+ |
+
+ A32
+ |
+
+ 012615.22
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ 361
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 23
+ |
+
+ A33
+ |
+
+ 012615.21
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ 361
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 24
+ |
+
+ A34
+ |
+
+ 121515.17
+ |
+
+ BXD45
+ |
+
+ F
+ |
+
+ 350
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 25
+ |
+
+ A36
+ |
+
+ 012615.13
+ |
+
+ BXD44
+ |
+
+ F
+ |
+
+ 379
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 26
+ |
+
+ A37
+ |
+
+ 012615.24
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ 367
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 27
+ |
+
+ A3
+ |
+
+ 090512.12
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ 353
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 28
+ |
+
+ A40
+ |
+
+ 012615.23
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ 367
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 29
+ |
+
+ A41
+ |
+
+ 042915.16
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ 436
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 30
+ |
+
+ A42
+ |
+
+ 042915.15
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ 436
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 31
+ |
+
+ A43
+ |
+
+ 111414.15
+ |
+
+ BXD102
+ |
+
+ F
+ |
+
+ 351
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 32
+ |
+
+ A44
+ |
+
+ 012615.12
+ |
+
+ BXD44
+ |
+
+ F
+ |
+
+ 379
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 33
+ |
+
+ A45
+ |
+
+ 121214.12
+ |
+
+ BXD73
+ |
+
+ F
+ |
+
+ 361
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 34
+ |
+
+ A49
+ |
+
+ 121214.14
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ 358
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 35
+ |
+
+ A4
+ |
+
+ 090512.11
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ 353
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 36
+ |
+
+ A50
+ |
+
+ 010614.21
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ 343
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 37
+ |
+
+ A51
+ |
+
+ 121214.04
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ 367
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 38
+ |
+
+ A52
+ |
+
+ 121214.13
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ 358
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 39
+ |
+
+ A53
+ |
+
+ 121214.11
+ |
+
+ BXD73
+ |
+
+ F
+ |
+
+ 361
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 40
+ |
+
+ A54
+ |
+
+ 021213.24
+ |
+
+ BXD84
+ |
+
+ F
+ |
+
+ 343
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 41
+ |
+
+ A55
+ |
+
+ 021213.18
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ 347
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 42
+ |
+
+ A56
+ |
+
+ 021213.17
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ 347
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 43
+ |
+
+ A57
+ |
+
+ 021213.16
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ 343
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 44
+ |
+
+ A58
+ |
+
+ 021213.15
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ 343
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 45
+ |
+
+ A59
+ |
+
+ 021113.11
+ |
+
+ BXD51
+ |
+
+ F
+ |
+
+ 357
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 46
+ |
+
+ A60
+ |
+
+ 010614.14
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ 367
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 47
+ |
+
+ A61
+ |
+
+ 010614.13
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ 367
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 48
+ |
+
+ A62
+ |
+
+ 021213.23
+ |
+
+ BXD84
+ |
+
+ F
+ |
+
+ 343
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 49
+ |
+
+ A63
+ |
+
+ 090514.03
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ 367
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 50
+ |
+
+ A64
+ |
+
+ 090514.04
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ 367
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 51
+ |
+
+ A65
+ |
+
+ 010614.22
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ 343
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 52
+ |
+
+ A66
+ |
+
+ 010614.17
+ |
+
+ BXD73b
+ |
+
+ F
+ |
+
+ 385
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 53
+ |
+
+ A68
+ |
+
+ 121214.22
+ |
+
+ BXD39
+ |
+
+ F
+ |
+
+ 350
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 54
+ |
+
+ A69
+ |
+
+ 121214.21
+ |
+
+ BXD39
+ |
+
+ F
+ |
+
+ 350
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 55
+ |
+
+ A6
+ |
+
+ 090512.08
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ 359
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 56
+ |
+
+ A70
+ |
+
+ 121214.18
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ 357
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 57
+ |
+
+ A71
+ |
+
+ 121214.17
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ 357
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 58
+ |
+
+ A72
+ |
+
+ 021313.33
+ |
+
+ BXD98
+ |
+
+ F
+ |
+
+ 360
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 59
+ |
+
+ A73
+ |
+
+ 021313.34
+ |
+
+ BXD98
+ |
+
+ F
+ |
+
+ 360
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 60
+ |
+
+ A74
+ |
+
+ 092216.09
+ |
+
+ BXD27
+ |
+
+ F
+ |
+
+ 387
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 61
+ |
+
+ A75
+ |
+
+ 092216.10
+ |
+
+ BXD27
+ |
+
+ F
+ |
+
+ 387
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 62
+ |
+
+ A77
+ |
+
+ 121615.02
+ |
+
+ BXD61
+ |
+
+ F
+ |
+
+ 364
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 63
+ |
+
+ A78
+ |
+
+ 121615.01
+ |
+
+ BXD61
+ |
+
+ F
+ |
+
+ 364
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 64
+ |
+
+ A7
+ |
+
+ 090512.01
+ |
+
+ BXD9
+ |
+
+ F
+ |
+
+ 347
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 65
+ |
+
+ A8
+ |
+
+ 090512.02
+ |
+
+ BXD9
+ |
+
+ F
+ |
+
+ 349
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+ |
+ 66
+ |
+
+ A97
+ |
+
+ 050115.11
+ |
+
+ BXD73b
+ |
+
+ F
+ |
+
+ 474
+ |
+
+ Heart
+ |
+
+ High fat diet
+ |
+
+
+
+
+
diff --git a/general/datasets/Nhlbi_bxd_aged_heart_hfd_rna_seq_1120/tissue.rtf b/general/datasets/Nhlbi_bxd_aged_heart_hfd_rna_seq_1120/tissue.rtf
new file mode 100644
index 0000000..8d370c0
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_aged_heart_hfd_rna_seq_1120/tissue.rtf
@@ -0,0 +1,3 @@
+Tissue Harvest
+
+The animals were sacrificed under saturated isoflurane. Whole heart from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Nhlbi_bxd_all_ages_heart_rna_seq_1120/experiment-design.rtf b/general/datasets/Nhlbi_bxd_all_ages_heart_rna_seq_1120/experiment-design.rtf
new file mode 100644
index 0000000..fbdad24
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_all_ages_heart_rna_seq_1120/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Extraction
+
+Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Approximately 30 mg of left ventricle tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/Nhlbi_bxd_all_ages_heart_rna_seq_1120/processing.rtf b/general/datasets/Nhlbi_bxd_all_ages_heart_rna_seq_1120/processing.rtf
new file mode 100644
index 0000000..8e460ff
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_all_ages_heart_rna_seq_1120/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/Nhlbi_bxd_all_ages_heart_rna_seq_1120/specifics.rtf b/general/datasets/Nhlbi_bxd_all_ages_heart_rna_seq_1120/specifics.rtf
new file mode 100644
index 0000000..55635fc
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_all_ages_heart_rna_seq_1120/specifics.rtf
@@ -0,0 +1 @@
+NHLBI BXD All Ages Heart RNA-Seq (Nov20) TMP Log2
\ No newline at end of file
diff --git a/general/datasets/Nhlbi_bxd_all_ages_heart_rna_seq_1120/tissue.rtf b/general/datasets/Nhlbi_bxd_all_ages_heart_rna_seq_1120/tissue.rtf
new file mode 100644
index 0000000..8d370c0
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_all_ages_heart_rna_seq_1120/tissue.rtf
@@ -0,0 +1,3 @@
+Tissue Harvest
+
+The animals were sacrificed under saturated isoflurane. Whole heart from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Nhlbi_bxd_young_adult_heart_cd_cms_rna/experiment-design.rtf b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_cms_rna/experiment-design.rtf
new file mode 100644
index 0000000..fbdad24
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_cms_rna/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Extraction
+
+Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Approximately 30 mg of left ventricle tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/Nhlbi_bxd_young_adult_heart_cd_cms_rna/processing.rtf b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_cms_rna/processing.rtf
new file mode 100644
index 0000000..8e460ff
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_cms_rna/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/Nhlbi_bxd_young_adult_heart_cd_cms_rna/specifics.rtf b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_cms_rna/specifics.rtf
new file mode 100644
index 0000000..24b6e71
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_cms_rna/specifics.rtf
@@ -0,0 +1,1907 @@
+NHLBI BXD Young Adult Heart CD CMS RNA-Seq (Nov20) TMP Log2
+
+About the cases used to generate this set of data:
+
+The study included 64 mice (~6 month) from B6, D2, and 32 advanced intercross BXD strains (about 2 mice per strain). All mice were fed on chow diet (CD) and treated with chronic mild stress (CMS). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+
+
+Chronic Mild Stress (CMS)
+
+During a period of 7 weeks, mice received 2 disturbances per day. These consisted of being exposed to wet bedding for 1 hour, 1 cm of water in the bottom of the cage with no bedding for 1 hour, no bedding for 1 hour, confinement in a 3 × 3 × 3 cm plastic box for 15 minutes, tilted cage at 45º for 1 hour, and exposure to foreign mouse or fox urine odor for 1 hour. The other stressor was a complete phase shift in the light:dark cycle over each weekend. Disruption of the light cycle (lights constantly on) occurred over the weekend (starting Friday 11:00 am) with the light cycle resuming at 11 am on Monday (lights off). The schedule was repeated weekly over the duration of the study.
+
+
+
+
+
+The table of samples that are finally used for this study.
+
+
+
+
+ |
+ Index
+ |
+
+ Sample ID
+ |
+
+ Case id
+ |
+
+ Strain
+ |
+
+ Fuyi_Sex_Final
+ |
+
+ Sac age/Day
+ |
+
+ Tissue
+ |
+
+ Diet
+ |
+
+ Treatment
+ |
+
+
+ |
+ 1
+ |
+
+ C100
+ |
+
+ 090215.15
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ 185
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 2
+ |
+
+ C101
+ |
+
+ 090215.16
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ 171
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 3
+ |
+
+ C102
+ |
+
+ 090215.20
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ 162
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 4
+ |
+
+ C103
+ |
+
+ 090215.21
+ |
+
+ BXD63
+ |
+
+ F
+ |
+
+ 169
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 5
+ |
+
+ C104
+ |
+
+ 090215.24
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ 188
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 6
+ |
+
+ C105
+ |
+
+ 090215.28
+ |
+
+ BXD63
+ |
+
+ F
+ |
+
+ 169
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 7
+ |
+
+ C10
+ |
+
+ CMS102816.14
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ 124
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 8
+ |
+
+ C112
+ |
+
+ CMS032917.33
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ 162
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 9
+ |
+
+ C118
+ |
+
+ CMS082917.05
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ 196
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 10
+ |
+
+ C11
+ |
+
+ CMS102816.15
+ |
+
+ BXD73b
+ |
+
+ F
+ |
+
+ 163
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 11
+ |
+
+ C13
+ |
+
+ CMS102816.17
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ 139
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 12
+ |
+
+ C14
+ |
+
+ CMS102816.18
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ 155
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 13
+ |
+
+ C15
+ |
+
+ CMS102816.19
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ 168
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 14
+ |
+
+ C17
+ |
+
+ CMS102816.21
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ 163
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 15
+ |
+
+ C19
+ |
+
+ CMS102816.05
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ 156
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 16
+ |
+
+ C1
+ |
+
+ CMS082817.05
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ 174
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 17
+ |
+
+ C21
+ |
+
+ CMS102816.07
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ 156
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 18
+ |
+
+ C23
+ |
+
+ CMS102816.09
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ 159
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 19
+ |
+
+ C25
+ |
+
+ CMS102816.11
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ 139
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 20
+ |
+
+ C28
+ |
+
+ CMS102716.16
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ 123
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 21
+ |
+
+ C2
+ |
+
+ CMS083017.19
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ 171
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 22
+ |
+
+ C30
+ |
+
+ CMS102716.19
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ 121
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 23
+ |
+
+ C31
+ |
+
+ CMS102716.20
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ 161
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 24
+ |
+
+ C32
+ |
+
+ CMS102716.01
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ 167
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 25
+ |
+
+ C34
+ |
+
+ CMS102716.10
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ 144
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 26
+ |
+
+ C35
+ |
+
+ CMS102716.12
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ 144
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 27
+ |
+
+ C36
+ |
+
+ CMS102716.03
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ 121
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 28
+ |
+
+ C38
+ |
+
+ CMS102716.06
+ |
+
+ BXD34
+ |
+
+ M
+ |
+
+ 157
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 29
+ |
+
+ C39
+ |
+
+ CMS102716.07
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ 157
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 30
+ |
+
+ C3
+ |
+
+ CMS083017.18
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ 174
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 31
+ |
+
+ C40
+ |
+
+ CMS102716.08
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ 155
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 32
+ |
+
+ C41
+ |
+
+ CMS102716.09
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ 142
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 33
+ |
+
+ C44
+ |
+
+ CMS033017.25
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ 163
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 34
+ |
+
+ C45
+ |
+
+ CMS032817.28
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ 168
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 35
+ |
+
+ C46
+ |
+
+ CMS032817.23
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ 179
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 36
+ |
+
+ C47
+ |
+
+ CMS082817.24
+ |
+
+ BXD51
+ |
+
+ F
+ |
+
+ 186
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 37
+ |
+
+ C48
+ |
+
+ CMS082817.14
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ 182
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 38
+ |
+
+ C49
+ |
+
+ CMS082817.07
+ |
+
+ BXD44
+ |
+
+ F
+ |
+
+ 202
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 39
+ |
+
+ C56
+ |
+
+ CMS102716.13
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ 151
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 40
+ |
+
+ C60
+ |
+
+ CMS032917.33
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ 162
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 41
+ |
+
+ C61
+ |
+
+ CMS032917.29
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ 162
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 42
+ |
+
+ C62
+ |
+
+ CMS032917.26
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ 173
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 43
+ |
+
+ C63
+ |
+
+ CMS032917.22
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ 170
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 44
+ |
+
+ C64
+ |
+
+ CMS083017.07
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ 202
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 45
+ |
+
+ C65
+ |
+
+ CMS082917.19
+ |
+
+ BXD44
+ |
+
+ F
+ |
+
+ 182
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 46
+ |
+
+ C66
+ |
+
+ CMS030716.03
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ 196
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 47
+ |
+
+ C67
+ |
+
+ CMS030716.06
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ 193
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 48
+ |
+
+ C68
+ |
+
+ CMS030716.12
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ 166
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 49
+ |
+
+ C69
+ |
+
+ CMS030716.13
+ |
+
+ BXD55
+ |
+
+ F
+ |
+
+ 166
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 50
+ |
+
+ C70
+ |
+
+ CMS030716.18
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ 182
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 51
+ |
+
+ C71
+ |
+
+ CMS030716.19
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ 182
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 52
+ |
+
+ C73
+ |
+
+ CMS030716.32
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ 196
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 53
+ |
+
+ C75
+ |
+
+ CMS030916.11
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ 167
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 54
+ |
+
+ C76
+ |
+
+ CMS030916.14
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ 168
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 55
+ |
+
+ C77
+ |
+
+ CMS030916.20
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ 190
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 56
+ |
+
+ C79
+ |
+
+ CMS030916.23
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ 182
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 57
+ |
+
+ C80
+ |
+
+ CMS030916.28
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ 162
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 58
+ |
+
+ C81
+ |
+
+ CMS030916.32
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ 193
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 59
+ |
+
+ C84
+ |
+
+ CMS102816.03
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ 159
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 60
+ |
+
+ C85
+ |
+
+ CMS102716.11
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ 157
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 61
+ |
+
+ C96
+ |
+
+ 090215.02
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ 137
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 62
+ |
+
+ C97
+ |
+
+ 090215.05
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ 180
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 63
+ |
+
+ C98
+ |
+
+ 090215.06
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ 188
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+ |
+ 64
+ |
+
+ C99
+ |
+
+ 090215.09
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ 180
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+ CMS
+ |
+
+
+
diff --git a/general/datasets/Nhlbi_bxd_young_adult_heart_cd_cms_rna/tissue.rtf b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_cms_rna/tissue.rtf
new file mode 100644
index 0000000..8d370c0
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_cms_rna/tissue.rtf
@@ -0,0 +1,3 @@
+Tissue Harvest
+
+The animals were sacrificed under saturated isoflurane. Whole heart from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Nhlbi_bxd_young_adult_heart_cd_rna_seq/experiment-design.rtf b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_rna_seq/experiment-design.rtf
new file mode 100644
index 0000000..fbdad24
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_rna_seq/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Extraction
+
+Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Approximately 30 mg of left ventricle tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/Nhlbi_bxd_young_adult_heart_cd_rna_seq/processing.rtf b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_rna_seq/processing.rtf
new file mode 100644
index 0000000..8e460ff
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_rna_seq/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/Nhlbi_bxd_young_adult_heart_cd_rna_seq/specifics.rtf b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_rna_seq/specifics.rtf
new file mode 100644
index 0000000..96fa0b5
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_rna_seq/specifics.rtf
@@ -0,0 +1,2302 @@
+NHLBI BXD Young Adult Heart CD RNA-Seq (Nov20) TMP Log2
+
+About the cases used to generate this set of data:
+
+The study included 87 mice (~6 month) from B6, D2, and 41 advanced intercross BXD strains (about 2 mice per strain). All mice were fed on chow diet (CD). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+
+
+The table of samples that are finally used for this study.
+
+
+
+
+ |
+ Index
+ |
+
+ Sample ID
+ |
+
+ Case id
+ |
+
+ Strain
+ |
+
+ Fuyi_Sex_Final
+ |
+
+ Age (Day)
+ |
+
+ Tissue
+ |
+
+ Diet
+ |
+
+
+ |
+ 1
+ |
+
+ H100
+ |
+
+ *091317.07
+ |
+
+ BXD61
+ |
+
+ M
+ |
+
+ 128
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 2
+ |
+
+ H101
+ |
+
+ *052417.59
+ |
+
+ BXD177
+ |
+
+ F
+ |
+
+ 125
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 3
+ |
+
+ H102
+ |
+
+ *052417.26
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ 141
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 4
+ |
+
+ H103
+ |
+
+ *060717.02
+ |
+
+ BXD9
+ |
+
+ M
+ |
+
+ 149
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 5
+ |
+
+ H109
+ |
+
+ *052417.49
+ |
+
+ BXD152
+ |
+
+ F
+ |
+
+ 147
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 6
+ |
+
+ H110
+ |
+
+ *052417.35
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ 127
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 7
+ |
+
+ H112
+ |
+
+ *052417.24
+ |
+
+ BXD73
+ |
+
+ F
+ |
+
+ 173
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 8
+ |
+
+ H113
+ |
+
+ *052417.25
+ |
+
+ BXD73
+ |
+
+ M
+ |
+
+ 173
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 9
+ |
+
+ H116
+ |
+
+ *121917.28
+ |
+
+ BXD180
+ |
+
+ F
+ |
+
+ 120
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 10
+ |
+
+ H11
+ |
+
+ *121917.20
+ |
+
+ BXD111
+ |
+
+ M
+ |
+
+ 122
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 11
+ |
+
+ H120
+ |
+
+ *111417.04
+ |
+
+ BXD40
+ |
+
+ M
+ |
+
+ 133
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 12
+ |
+
+ H121
+ |
+
+ *091317.02
+ |
+
+ BXD48a
+ |
+
+ M
+ |
+
+ 125
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 13
+ |
+
+ H122
+ |
+
+ *092717.59
+ |
+
+ BXD154
+ |
+
+ F
+ |
+
+ 135
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 14
+ |
+
+ H124
+ |
+
+ *092717.60
+ |
+
+ BXD154
+ |
+
+ F
+ |
+
+ 135
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 15
+ |
+
+ H126
+ |
+
+ *092717.65
+ |
+
+ BXD155
+ |
+
+ F
+ |
+
+ 133
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 16
+ |
+
+ H127
+ |
+
+ *092717.67
+ |
+
+ BXD169
+ |
+
+ M
+ |
+
+ 133
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 17
+ |
+
+ H129
+ |
+
+ *092717.37
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ 133
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 18
+ |
+
+ H12
+ |
+
+ *121917.21
+ |
+
+ BXD111
+ |
+
+ M
+ |
+
+ 122
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 19
+ |
+
+ H130
+ |
+
+ AGE050118.27
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ 167
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 20
+ |
+
+ H131
+ |
+
+ AGE050118.28
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ 167
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 21
+ |
+
+ H132
+ |
+
+ AGE050118.29
+ |
+
+ DBA/2J
+ |
+
+ M
+ |
+
+ 167
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 22
+ |
+
+ H138
+ |
+
+ *112118.32
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ 208
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 23
+ |
+
+ H139
+ |
+
+ *112118.33
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ 208
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 24
+ |
+
+ H140
+ |
+
+ *112118.34
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ 208
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 25
+ |
+
+ H14
+ |
+
+ *092017.36
+ |
+
+ BXD113
+ |
+
+ F
+ |
+
+ 132
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 26
+ |
+
+ H15
+ |
+
+ *092017.37
+ |
+
+ BXD113
+ |
+
+ M
+ |
+
+ 132
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 27
+ |
+
+ H16
+ |
+
+ *060717.15
+ |
+
+ BXD123
+ |
+
+ F
+ |
+
+ 182
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 28
+ |
+
+ H17
+ |
+
+ *060717.16
+ |
+
+ BXD123
+ |
+
+ M
+ |
+
+ 182
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 29
+ |
+
+ H19
+ |
+
+ *052417.44
+ |
+
+ BXD128 (WAS b)
+ |
+
+ F
+ |
+
+ 161
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 30
+ |
+
+ H20
+ |
+
+ *052417.45
+ |
+
+ BXD128 (WAS b)
+ |
+
+ F
+ |
+
+ 161
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 31
+ |
+
+ H21
+ |
+
+ *092017.38
+ |
+
+ BXD144
+ |
+
+ F
+ |
+
+ 133
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 32
+ |
+
+ H23
+ |
+
+ *092017.39
+ |
+
+ BXD144
+ |
+
+ M
+ |
+
+ 133
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 33
+ |
+
+ H25
+ |
+
+ *060717.03
+ |
+
+ BXD15
+ |
+
+ F
+ |
+
+ 143
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 34
+ |
+
+ H26
+ |
+
+ *060717.04
+ |
+
+ BXD15
+ |
+
+ F
+ |
+
+ 143
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 35
+ |
+
+ H27
+ |
+
+ *052417.47
+ |
+
+ BXD151
+ |
+
+ F
+ |
+
+ 127
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 36
+ |
+
+ H28
+ |
+
+ *092017.40
+ |
+
+ BXD151
+ |
+
+ M
+ |
+
+ 133
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 37
+ |
+
+ H30
+ |
+
+ *052417.51
+ |
+
+ BXD152
+ |
+
+ M
+ |
+
+ 147
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 38
+ |
+
+ H31
+ |
+
+ *052417.54
+ |
+
+ BXD155
+ |
+
+ M
+ |
+
+ 119
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 39
+ |
+
+ H32
+ |
+
+ *091317.01
+ |
+
+ BXD16
+ |
+
+ F
+ |
+
+ 128
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 40
+ |
+
+ H33
+ |
+
+ *111417.11
+ |
+
+ BXD169
+ |
+
+ F
+ |
+
+ 121
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 41
+ |
+
+ H36
+ |
+
+ *121917.16
+ |
+
+ BXD171
+ |
+
+ F
+ |
+
+ 124
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 42
+ |
+
+ H38
+ |
+
+ *092017.41
+ |
+
+ BXD171
+ |
+
+ M
+ |
+
+ 133
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 43
+ |
+
+ H41
+ |
+
+ *052417.60
+ |
+
+ BXD177
+ |
+
+ M
+ |
+
+ 125
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 44
+ |
+
+ H43
+ |
+
+ *052417.62
+ |
+
+ BXD180
+ |
+
+ M
+ |
+
+ 119
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 45
+ |
+
+ H44
+ |
+
+ *052417.32
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ 155
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 46
+ |
+
+ H46
+ |
+
+ *052417.28
+ |
+
+ BXD73a
+ |
+
+ M
+ |
+
+ 141
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 47
+ |
+
+ H48
+ |
+
+ *052417.40
+ |
+
+ BXD89
+ |
+
+ M
+ |
+
+ 173
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 48
+ |
+
+ H49
+ |
+
+ *060717.09
+ |
+
+ BXD63
+ |
+
+ F
+ |
+
+ 160
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 49
+ |
+
+ H50
+ |
+
+ *060717.06
+ |
+
+ BXD24
+ |
+
+ M
+ |
+
+ 138
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 50
+ |
+
+ H51
+ |
+
+ *060717.07
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ 134
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 51
+ |
+
+ H52
+ |
+
+ *060717.08
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ 134
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 52
+ |
+
+ H53
+ |
+
+ *060717.11
+ |
+
+ BXD63
+ |
+
+ M
+ |
+
+ 160
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 53
+ |
+
+ H54
+ |
+
+ *052417.22
+ |
+
+ BXD62
+ |
+
+ M
+ |
+
+ 165
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 54
+ |
+
+ H55
+ |
+
+ *052417.17
+ |
+
+ BXD51
+ |
+
+ F
+ |
+
+ 154
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 55
+ |
+
+ H56
+ |
+
+ *052417.15
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ 167
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 56
+ |
+
+ H57
+ |
+
+ *052417.08
+ |
+
+ BXD32
+ |
+
+ M
+ |
+
+ 156
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 57
+ |
+
+ H59
+ |
+
+ *052417.21
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ 165
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 58
+ |
+
+ H60
+ |
+
+ *052417.19
+ |
+
+ BXD51
+ |
+
+ M
+ |
+
+ 154
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 59
+ |
+
+ H61
+ |
+
+ *052417.16
+ |
+
+ BXD50
+ |
+
+ M
+ |
+
+ 167
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 60
+ |
+
+ H62
+ |
+
+ *052417.37
+ |
+
+ BXD86
+ |
+
+ M
+ |
+
+ 127
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 61
+ |
+
+ H63
+ |
+
+ *052417.29
+ |
+
+ BXD73b
+ |
+
+ F
+ |
+
+ 145
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 62
+ |
+
+ H64
+ |
+
+ *052417.31
+ |
+
+ BXD73b
+ |
+
+ M
+ |
+
+ 145
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 63
+ |
+
+ H65
+ |
+
+ *121917.01
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ 126
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 64
+ |
+
+ H66
+ |
+
+ *121917.13
+ |
+
+ BXD45
+ |
+
+ M
+ |
+
+ 126
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 65
+ |
+
+ H67
+ |
+
+ *121917.12
+ |
+
+ BXD45
+ |
+
+ F
+ |
+
+ 126
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 66
+ |
+
+ H68
+ |
+
+ *121917.02
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ 126
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 67
+ |
+
+ H69
+ |
+
+ *071917.35
+ |
+
+ BXD68
+ |
+
+ M
+ |
+
+ 134
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 68
+ |
+
+ H71
+ |
+
+ *092017.32
+ |
+
+ BXD83
+ |
+
+ M
+ |
+
+ 136
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 69
+ |
+
+ H72
+ |
+
+ *092017.30
+ |
+
+ BXD78
+ |
+
+ M
+ |
+
+ 132
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 70
+ |
+
+ H74
+ |
+
+ *092017.29
+ |
+
+ BXD75
+ |
+
+ M
+ |
+
+ 133
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 71
+ |
+
+ H76
+ |
+
+ *092017.26
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ 133
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 72
+ |
+
+ H78
+ |
+
+ *092017.05
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ 128
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 73
+ |
+
+ H79
+ |
+
+ *092017.02
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ 131
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 74
+ |
+
+ H80
+ |
+
+ *092017.01
+ |
+
+ BXD9
+ |
+
+ F
+ |
+
+ 129
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 75
+ |
+
+ H81
+ |
+
+ *092017.12
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ 132
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 76
+ |
+
+ H83
+ |
+
+ *092017.33
+ |
+
+ BXD89
+ |
+
+ F
+ |
+
+ 136
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 77
+ |
+
+ H84
+ |
+
+ *092017.23
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ 130
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 78
+ |
+
+ H85
+ |
+
+ *092017.22
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ 127
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 79
+ |
+
+ H86
+ |
+
+ *092017.07
+ |
+
+ BXD44
+ |
+
+ F
+ |
+
+ 128
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 80
+ |
+
+ H89
+ |
+
+ *092017.14
+ |
+
+ BXD65
+ |
+
+ M
+ |
+
+ 132
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 81
+ |
+
+ H90
+ |
+
+ *092017.03
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ 131
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 82
+ |
+
+ H91
+ |
+
+ *092017.20
+ |
+
+ BXD65b
+ |
+
+ M
+ |
+
+ 130
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 83
+ |
+
+ H92
+ |
+
+ *092017.09
+ |
+
+ BXD44
+ |
+
+ F
+ |
+
+ 128
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 84
+ |
+
+ H94
+ |
+
+ *092017.18
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ 130
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 85
+ |
+
+ H96
+ |
+
+ *091317.06
+ |
+
+ BXD61
+ |
+
+ M
+ |
+
+ 128
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 86
+ |
+
+ H97
+ |
+
+ *091317.12
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ 132
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+ |
+ 87
+ |
+
+ H99
+ |
+
+ *091317.04
+ |
+
+ BXD48a
+ |
+
+ M
+ |
+
+ 125
+ |
+
+ Heart
+ |
+
+ Chow diet
+ |
+
+
+
diff --git a/general/datasets/Nhlbi_bxd_young_adult_heart_cd_rna_seq/tissue.rtf b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_rna_seq/tissue.rtf
new file mode 100644
index 0000000..8d370c0
--- /dev/null
+++ b/general/datasets/Nhlbi_bxd_young_adult_heart_cd_rna_seq/tissue.rtf
@@ -0,0 +1,3 @@
+Tissue Harvest
+
+The animals were sacrificed under saturated isoflurane. Whole heart from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Nia_agbxd_liv_cd_rna_seq_0818/specifics.rtf b/general/datasets/Nia_agbxd_liv_cd_rna_seq_0818/specifics.rtf
new file mode 100644
index 0000000..be3025c
--- /dev/null
+++ b/general/datasets/Nia_agbxd_liv_cd_rna_seq_0818/specifics.rtf
@@ -0,0 +1 @@
+CD Control diet.
\ No newline at end of file
diff --git a/general/datasets/Nia_agbxd_liv_cd_rna_seq_0818/summary.rtf b/general/datasets/Nia_agbxd_liv_cd_rna_seq_0818/summary.rtf
new file mode 100644
index 0000000..f32b018
--- /dev/null
+++ b/general/datasets/Nia_agbxd_liv_cd_rna_seq_0818/summary.rtf
@@ -0,0 +1 @@
+Impact of diet and genetics on survival in BXD GRP. Overall, on a population level of 84 unique BXD strains (666 mice on CD and 688 on HFD) when all strains were averaged the CD cohort lived significantly longer than the HFD cohort if genetics is not considered. (This dataset still unpublished). For more information or for access to this dataset please contact the person in the contact list above.
diff --git a/general/datasets/Nia_agbxd_liv_cdhfd_rna_seq_0818/specifics.rtf b/general/datasets/Nia_agbxd_liv_cdhfd_rna_seq_0818/specifics.rtf
new file mode 100644
index 0000000..8ee3ead
--- /dev/null
+++ b/general/datasets/Nia_agbxd_liv_cdhfd_rna_seq_0818/specifics.rtf
@@ -0,0 +1 @@
+CD+HFD
\ No newline at end of file
diff --git a/general/datasets/Nia_agbxd_liv_cdhfd_rna_seq_0818/summary.rtf b/general/datasets/Nia_agbxd_liv_cdhfd_rna_seq_0818/summary.rtf
new file mode 100644
index 0000000..f32b018
--- /dev/null
+++ b/general/datasets/Nia_agbxd_liv_cdhfd_rna_seq_0818/summary.rtf
@@ -0,0 +1 @@
+Impact of diet and genetics on survival in BXD GRP. Overall, on a population level of 84 unique BXD strains (666 mice on CD and 688 on HFD) when all strains were averaged the CD cohort lived significantly longer than the HFD cohort if genetics is not considered. (This dataset still unpublished). For more information or for access to this dataset please contact the person in the contact list above.
diff --git a/general/datasets/Nia_agbxd_liv_hfd_rna_seq_0818/specifics.rtf b/general/datasets/Nia_agbxd_liv_hfd_rna_seq_0818/specifics.rtf
new file mode 100644
index 0000000..a21c56e
--- /dev/null
+++ b/general/datasets/Nia_agbxd_liv_hfd_rna_seq_0818/specifics.rtf
@@ -0,0 +1 @@
+HFD High fat diet.
\ No newline at end of file
diff --git a/general/datasets/Nia_agbxd_liv_hfd_rna_seq_0818/summary.rtf b/general/datasets/Nia_agbxd_liv_hfd_rna_seq_0818/summary.rtf
new file mode 100644
index 0000000..f32b018
--- /dev/null
+++ b/general/datasets/Nia_agbxd_liv_hfd_rna_seq_0818/summary.rtf
@@ -0,0 +1 @@
+Impact of diet and genetics on survival in BXD GRP. Overall, on a population level of 84 unique BXD strains (666 mice on CD and 688 on HFD) when all strains were averaged the CD cohort lived significantly longer than the HFD cohort if genetics is not considered. (This dataset still unpublished). For more information or for access to this dataset please contact the person in the contact list above.
diff --git a/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/cases.rtf b/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/cases.rtf
new file mode 100644
index 0000000..08a20a8
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/cases.rtf
@@ -0,0 +1,4848 @@
+The study included 241 females (aged 50 to 90 ± 2 days at the start of the experiment) from B6, D2, and 35 advanced intercross BXD strains (about 2 mice per strain and per condition). Mice were divided into 4 groups of Control (CTL, 53 mice for 31 strains), Chronic Mild Stress (CMS, 64 mice for 32 strains), Drinking in Dark (DID, 64 mice for 35 strains), and CMS+DID (60 mice for 35 strains). Mice in CTL were normally handled, while mice in other groups were singly housed in shoebox cages, with food and water provided ad libitum except when the water was replaced by 20% (v/v) EtOH (see below) for DID and CMS+DID groups (detailed treatments and schemes are showing in the Table and Figure). The ambient temperature was 21 ± 2°C, and the light cycle was 7:00/19:00 for CTL, and 23:00/11:00 the rest groups lights on/off. The animals were weighed weekly to assess health and to provide the basis for calculating the amount of EtOH consumed in grams per kilogram. All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+The table of samples that are finally used for this study.
+
+
+
+
+ |
+ Index
+ |
+
+ ID
+ |
+
+ Strain
+ |
+
+ Sex
+ |
+
+ Treatment Group
+ |
+
+ Tissue
+ |
+
+
+ |
+ 1
+ |
+
+ CMS030716_12
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 2
+ |
+
+ CMS030716_18
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 3
+ |
+
+ CMS030716_19
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 4
+ |
+
+ CMS030916_02
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 5
+ |
+
+ CMS030916_09
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 6
+ |
+
+ CMS030916_11
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 7
+ |
+
+ CMS030916_14
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 8
+ |
+
+ CMS030916_20
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 9
+ |
+
+ CMS030916_23
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 10
+ |
+
+ CMS030916_32
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 11
+ |
+
+ CMS032817_02
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 12
+ |
+
+ CMS032817_28
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 13
+ |
+
+ CMS032917_08
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 14
+ |
+
+ CMS032917_24
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 15
+ |
+
+ CMS032917_26
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 16
+ |
+
+ CMS032917_33
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 17
+ |
+
+ CMS033017_05
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 18
+ |
+
+ CMS033017_25
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 19
+ |
+
+ CMS061218_12
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 20
+ |
+
+ CMS061218_13
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 21
+ |
+
+ CMS061218_14
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 22
+ |
+
+ CMS071216_17
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 23
+ |
+
+ CMS071216_23
+ |
+
+ BXD73B
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 24
+ |
+
+ CMS071216_25
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 25
+ |
+
+ CMS071316_06
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 26
+ |
+
+ CMS071316_08
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 27
+ |
+
+ CMS071316_14
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 28
+ |
+
+ CMS071316_17
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 29
+ |
+
+ CMS071316_18
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 30
+ |
+
+ CMS071316_32
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 31
+ |
+
+ CMS071416_06
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 32
+ |
+
+ CMS082817_07
+ |
+
+ BXD44
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 33
+ |
+
+ CMS082817_25
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 34
+ |
+
+ CMS082917_16
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 35
+ |
+
+ CMS083017_07
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 36
+ |
+
+ CMS083017_25
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 37
+ |
+
+ CMS092018_01
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 38
+ |
+
+ CMS092018_05
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 39
+ |
+
+ CMS092118_08
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 40
+ |
+
+ CMS102716_01
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 41
+ |
+
+ CMS102716_02
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 42
+ |
+
+ CMS102716_03
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 43
+ |
+
+ CMS102716_05
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 44
+ |
+
+ CMS102716_06
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 45
+ |
+
+ CMS102716_07
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 46
+ |
+
+ CMS102716_08
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 47
+ |
+
+ CMS102716_11
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 48
+ |
+
+ CMS102716_12
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 49
+ |
+
+ CMS102716_14
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 50
+ |
+
+ CMS102716_15
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 51
+ |
+
+ CMS102716_16
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 52
+ |
+
+ CMS102716_20
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 53
+ |
+
+ CMS102816_02
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 54
+ |
+
+ CMS102816_03
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 55
+ |
+
+ CMS102816_04
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 56
+ |
+
+ CMS102816_06
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 57
+ |
+
+ CMS102816_10
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 58
+ |
+
+ CMS102816_11
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 59
+ |
+
+ CMS102816_13
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 60
+ |
+
+ CMS102816_14
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 61
+ |
+
+ CMS102816_17
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 62
+ |
+
+ CMS102816_18
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 63
+ |
+
+ CMS102816_20
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 64
+ |
+
+ CMS102816_21
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 65
+ |
+
+ CMS030716_01
+ |
+
+ BXD55
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 66
+ |
+
+ CMS030716_08
+ |
+
+ BXD63
+ |
+
+ F
+ |
+
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+ |
+
+
+ |
+ 167
+ |
+
+ CMS083017_10
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 168
+ |
+
+ CMS102215_20
+ |
+
+ BXD73B
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 169
+ |
+
+ CMS111716_02
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 170
+ |
+
+ CMS111716_05
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 171
+ |
+
+ CMS111716_08
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 172
+ |
+
+ CMS111716_10
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 173
+ |
+
+ CMS111716_16
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 174
+ |
+
+ CMS111716_20
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 175
+ |
+
+ CMS111716_22
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 176
+ |
+
+ CMS111716_23
+ |
+
+ BXD73b
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 177
+ |
+
+ CMS111716_25
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 178
+ |
+
+ CMS111816_01
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 179
+ |
+
+ CMS111816_03
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 180
+ |
+
+ CMS111816_08
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 181
+ |
+
+ CMS111816_11
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 182
+ |
+
+ CMS111816_14
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 183
+ |
+
+ CMS111816_16
+ |
+
+ BXD73b
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 184
+ |
+
+ CMS111816_17
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 185
+ |
+
+ CMS111816_20
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 186
+ |
+
+ CMS111816_28
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 187
+ |
+
+ S32515_12
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 188
+ |
+
+ S32515_16
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 189
+ |
+
+ 13118_35
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 190
+ |
+
+ 13118_41
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 191
+ |
+
+ 13118_56
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 192
+ |
+
+ 31218_19
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 193
+ |
+
+ 31218_3
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 194
+ |
+
+ 31218_36
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 195
+ |
+
+ AGE041118_03
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 196
+ |
+
+ AGE050118_07
+ |
+
+ BXD55
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 197
+ |
+
+ AGE050118_12
+ |
+
+ BXD73
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 198
+ |
+
+ AGE050118_16
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 199
+ |
+
+ AGE050118_21
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 200
+ |
+
+ AGE050118_23
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 201
+ |
+
+ AGE050118_27
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 202
+ |
+
+ AGE061818_02
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 203
+ |
+
+ BL013118_12
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 204
+ |
+
+ BL013118_13
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 205
+ |
+
+ CMS092118_24
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 206
+ |
+
+ E100118_16
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 207
+ |
+
+ MT052417_09
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 208
+ |
+
+ MT052417_17
+ |
+
+ BXD51
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 209
+ |
+
+ S13118_07
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 210
+ |
+
+ S13118_08
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 211
+ |
+
+ S13118_15
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 212
+ |
+
+ S13118_18
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 213
+ |
+
+ S13118_19
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 214
+ |
+
+ S13118_23
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 215
+ |
+
+ S13118_24
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 216
+ |
+
+ S13118_26
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 217
+ |
+
+ S13118_36
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 218
+ |
+
+ S13118_38
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 219
+ |
+
+ S13118_42
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 220
+ |
+
+ S13118_44
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 221
+ |
+
+ S13118_58
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 222
+ |
+
+ S13118_64
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 223
+ |
+
+ S13118_65
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 224
+ |
+
+ S13118_7
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 225
+ |
+
+ S31218_01
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 226
+ |
+
+ S31218_02
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 227
+ |
+
+ S31218_04
+ |
+
+ BXD44
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 228
+ |
+
+ S31218_15
+ |
+
+ BXD63
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 229
+ |
+
+ S31218_16
+ |
+
+ BXD63
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 230
+ |
+
+ S31218_18
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 231
+ |
+
+ S31218_1
+ |
+
+ BXD51
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 232
+ |
+
+ S31218_21
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 233
+ |
+
+ S31218_22
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 234
+ |
+
+ S31218_24
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 235
+ |
+
+ S31218_25
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 236
+ |
+
+ S31218_27
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 237
+ |
+
+ S31218_28
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 238
+ |
+
+ S31218_31
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 239
+ |
+
+ S31218_35
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 240
+ |
+
+ S32718_01
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 241
+ |
+
+ S32718_03
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+
diff --git a/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/experiment-design.rtf b/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/experiment-design.rtf
new file mode 100644
index 0000000..54fad3e
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/experiment-design.rtf
@@ -0,0 +1,7 @@
+Alcohol consumption was evaluated using the DID method. The protocol calls for 4 consecutive days of testing. Each day, starting on a Tuesday 3 h after lights were turned off, the water bottles were removed from the cages and replaced with 15 ml centrifuge tubes filled with 20% (v/v) ethanol from 95% USP ethanol. On days 1–3 (Tuesday through Thursday) the length of exposure was 2 h and on the 4th day (Friday) the exposure was 4 h. No alcohol was offered in the intervening period (Saturday through Monday). This protocol was repeated weekly for 16 weeks (Table). Tubes were weighed immediately before and after the exposure period. Volume consumed was converted to g/kg body weight of ethanol.
+
+During a period of 7 weeks, mice received 2 disturbances per day (see Figure). These consisted of being exposed to wet bedding for 1 hour, 1 cm of water in the bottom of the cage with no bedding for 1 hour, no bedding for 1 hour, confinement in a 3 × 3 × 3 cm plastic box for 15 minutes, tilted cage at 45º for 1 hour, and exposure to foreign mouse or fox urine odor for 1 hour. The other stressor was a complete phase shift in the light:dark cycle over each weekend. Disruption of the light cycle (lights constantly on) occurred over the weekend (starting Friday 11:00 am) with the light cycle resuming at 11 am on Monday (lights off). The schedule was repeated weekly over the duration of the study.
+
+Treatment Periods
+
+The entire protocol took 16 weeks to complete and was subdivided into 3 periods: baseline (initial 5 weeks), CMS (next 7 weeks), and postâ€CMS (final 4 weeks). Alcohol was offered as described above for all periods and experimental groups. During the intervening 7â€week CMS period, control animals were subjected to normal housing and experimental (stress) animals were subjected to CMS.
diff --git a/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/processing.rtf b/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/processing.rtf
new file mode 100644
index 0000000..7d83d76
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/specifics.rtf b/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/specifics.rtf
new file mode 100644
index 0000000..c2753aa
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/specifics.rtf
@@ -0,0 +1 @@
+NIAAA BXD Hippocampus CMS-DID RNA-Seq (Oct20) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/tissue.rtf b/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/tissue.rtf
new file mode 100644
index 0000000..30cdeea
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_cms_did_rnaseq1020/tissue.rtf
@@ -0,0 +1,7 @@
+Tissue Harvest and RNA extraction
+
+The animals were sacrificed under saturated isoflurane. Brains from the animals were dissected under a cold plate (≤4o C), and hippocampus were weighted and snap frozen in dry ice bath with isopentane and stored at −80°C until RNA extraction.
+
+RNA Extraction
+
+Total RNA was extracted using Direct-zol RNA Miniprep Plus Kits (Zymo Research, Irvine, CA, USA) according to the manufacturer’s instructions. Approximately 15 mg of hippocampus tissue was added into a 2 ml tube containing 1 ml TRI Reagent® and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 min in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 rpm followed by incubating for 5 min. 0.1 ml of 1‑bromo-3‑chloropropane was add into the homogenate, shaken vigorously for 15 s, and centrifuged for 15 min at 12,000×g at 4 °C. 600 µl upper aqueous was then transferred into a new collection tube containing 600 µl 100% ethanol. The mixture was loaded into a Zymo-Spin IIC column, wash once with RNA Prep Buffer and twice with RNA Wash Buffer. All RNA had been treated with DNase to eliminate possible DNA contamination, and further precipitated with ethanol. RNA purity and integrity were verified by a nanodrop spectrophotometer and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).
diff --git a/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/cases.rtf b/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/cases.rtf
new file mode 100644
index 0000000..08a20a8
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/cases.rtf
@@ -0,0 +1,4848 @@
+The study included 241 females (aged 50 to 90 ± 2 days at the start of the experiment) from B6, D2, and 35 advanced intercross BXD strains (about 2 mice per strain and per condition). Mice were divided into 4 groups of Control (CTL, 53 mice for 31 strains), Chronic Mild Stress (CMS, 64 mice for 32 strains), Drinking in Dark (DID, 64 mice for 35 strains), and CMS+DID (60 mice for 35 strains). Mice in CTL were normally handled, while mice in other groups were singly housed in shoebox cages, with food and water provided ad libitum except when the water was replaced by 20% (v/v) EtOH (see below) for DID and CMS+DID groups (detailed treatments and schemes are showing in the Table and Figure). The ambient temperature was 21 ± 2°C, and the light cycle was 7:00/19:00 for CTL, and 23:00/11:00 the rest groups lights on/off. The animals were weighed weekly to assess health and to provide the basis for calculating the amount of EtOH consumed in grams per kilogram. All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+The table of samples that are finally used for this study.
+
+
+
+
+ |
+ Index
+ |
+
+ ID
+ |
+
+ Strain
+ |
+
+ Sex
+ |
+
+ Treatment Group
+ |
+
+ Tissue
+ |
+
+
+ |
+ 1
+ |
+
+ CMS030716_12
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 2
+ |
+
+ CMS030716_18
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 3
+ |
+
+ CMS030716_19
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 4
+ |
+
+ CMS030916_02
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 5
+ |
+
+ CMS030916_09
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 6
+ |
+
+ CMS030916_11
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 7
+ |
+
+ CMS030916_14
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 8
+ |
+
+ CMS030916_20
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 9
+ |
+
+ CMS030916_23
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 10
+ |
+
+ CMS030916_32
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 11
+ |
+
+ CMS032817_02
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 12
+ |
+
+ CMS032817_28
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 13
+ |
+
+ CMS032917_08
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 14
+ |
+
+ CMS032917_24
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 15
+ |
+
+ CMS032917_26
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 16
+ |
+
+ CMS032917_33
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 17
+ |
+
+ CMS033017_05
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 18
+ |
+
+ CMS033017_25
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 19
+ |
+
+ CMS061218_12
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 20
+ |
+
+ CMS061218_13
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 21
+ |
+
+ CMS061218_14
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 22
+ |
+
+ CMS071216_17
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 23
+ |
+
+ CMS071216_23
+ |
+
+ BXD73B
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 24
+ |
+
+ CMS071216_25
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 25
+ |
+
+ CMS071316_06
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 26
+ |
+
+ CMS071316_08
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 27
+ |
+
+ CMS071316_14
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 28
+ |
+
+ CMS071316_17
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 29
+ |
+
+ CMS071316_18
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 30
+ |
+
+ CMS071316_32
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 31
+ |
+
+ CMS071416_06
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 32
+ |
+
+ CMS082817_07
+ |
+
+ BXD44
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 33
+ |
+
+ CMS082817_25
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 34
+ |
+
+ CMS082917_16
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 35
+ |
+
+ CMS083017_07
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 36
+ |
+
+ CMS083017_25
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 37
+ |
+
+ CMS092018_01
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 38
+ |
+
+ CMS092018_05
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 39
+ |
+
+ CMS092118_08
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 40
+ |
+
+ CMS102716_01
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 41
+ |
+
+ CMS102716_02
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 42
+ |
+
+ CMS102716_03
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 43
+ |
+
+ CMS102716_05
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 44
+ |
+
+ CMS102716_06
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 45
+ |
+
+ CMS102716_07
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 46
+ |
+
+ CMS102716_08
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 47
+ |
+
+ CMS102716_11
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 48
+ |
+
+ CMS102716_12
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 49
+ |
+
+ CMS102716_14
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 50
+ |
+
+ CMS102716_15
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 51
+ |
+
+ CMS102716_16
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 52
+ |
+
+ CMS102716_20
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 53
+ |
+
+ CMS102816_02
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 54
+ |
+
+ CMS102816_03
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 55
+ |
+
+ CMS102816_04
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 56
+ |
+
+ CMS102816_06
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 57
+ |
+
+ CMS102816_10
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 58
+ |
+
+ CMS102816_11
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 59
+ |
+
+ CMS102816_13
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 60
+ |
+
+ CMS102816_14
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 61
+ |
+
+ CMS102816_17
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 62
+ |
+
+ CMS102816_18
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 63
+ |
+
+ CMS102816_20
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 64
+ |
+
+ CMS102816_21
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 65
+ |
+
+ CMS030716_01
+ |
+
+ BXD55
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 66
+ |
+
+ CMS030716_08
+ |
+
+ BXD63
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 67
+ |
+
+ CMS030716_09
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 68
+ |
+
+ CMS030716_15
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 69
+ |
+
+ CMS030716_27
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 70
+ |
+
+ CMS030716_29
+ |
+
+ BXD55
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 71
+ |
+
+ CMS030716_30
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 72
+ |
+
+ CMS030716_31
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 73
+ |
+
+ CMS030916_15
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 74
+ |
+
+ CMS030916_16
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 75
+ |
+
+ CMS030916_17
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 76
+ |
+
+ CMS030916_26
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 77
+ |
+
+ CMS032817_10
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 78
+ |
+
+ CMS032817_18
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 79
+ |
+
+ CMS032817_25
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 80
+ |
+
+ CMS032817_27
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 81
+ |
+
+ CMS032817_31
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 82
+ |
+
+ CMS032817_32
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 83
+ |
+
+ CMS032917_15
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 84
+ |
+
+ CMS032917_17
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 85
+ |
+
+ CMS032917_25
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 86
+ |
+
+ CMS033017_04
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 87
+ |
+
+ CMS033017_11
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 88
+ |
+
+ CMS033017_13
+ |
+
+ BXD73
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 89
+ |
+
+ CMS071216_01
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 90
+ |
+
+ CMS071216_24
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 91
+ |
+
+ CMS071316_05
+ |
+
+ BXD51
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 92
+ |
+
+ CMS071316_20
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 93
+ |
+
+ CMS071316_22
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 94
+ |
+
+ CMS071316_29
+ |
+
+ BXD51
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 95
+ |
+
+ CMS071416_01
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 96
+ |
+
+ CMS071416_08
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CMS+DID
+ |
+
+ hippocampus
+ |
+
+
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+ |
+
+ AGE050118_16
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 199
+ |
+
+ AGE050118_21
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 200
+ |
+
+ AGE050118_23
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 201
+ |
+
+ AGE050118_27
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 202
+ |
+
+ AGE061818_02
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 203
+ |
+
+ BL013118_12
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 204
+ |
+
+ BL013118_13
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 205
+ |
+
+ CMS092118_24
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 206
+ |
+
+ E100118_16
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 207
+ |
+
+ MT052417_09
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 208
+ |
+
+ MT052417_17
+ |
+
+ BXD51
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 209
+ |
+
+ S13118_07
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 210
+ |
+
+ S13118_08
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 211
+ |
+
+ S13118_15
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 212
+ |
+
+ S13118_18
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 213
+ |
+
+ S13118_19
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 214
+ |
+
+ S13118_23
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 215
+ |
+
+ S13118_24
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 216
+ |
+
+ S13118_26
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 217
+ |
+
+ S13118_36
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 218
+ |
+
+ S13118_38
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 219
+ |
+
+ S13118_42
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 220
+ |
+
+ S13118_44
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 221
+ |
+
+ S13118_58
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 222
+ |
+
+ S13118_64
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 223
+ |
+
+ S13118_65
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 224
+ |
+
+ S13118_7
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 225
+ |
+
+ S31218_01
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 226
+ |
+
+ S31218_02
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 227
+ |
+
+ S31218_04
+ |
+
+ BXD44
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 228
+ |
+
+ S31218_15
+ |
+
+ BXD63
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 229
+ |
+
+ S31218_16
+ |
+
+ BXD63
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 230
+ |
+
+ S31218_18
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 231
+ |
+
+ S31218_1
+ |
+
+ BXD51
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 232
+ |
+
+ S31218_21
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 233
+ |
+
+ S31218_22
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 234
+ |
+
+ S31218_24
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 235
+ |
+
+ S31218_25
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 236
+ |
+
+ S31218_27
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 237
+ |
+
+ S31218_28
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 238
+ |
+
+ S31218_31
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 239
+ |
+
+ S31218_35
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 240
+ |
+
+ S32718_01
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 241
+ |
+
+ S32718_03
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+
diff --git a/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/experiment-design.rtf b/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/experiment-design.rtf
new file mode 100644
index 0000000..54fad3e
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/experiment-design.rtf
@@ -0,0 +1,7 @@
+Alcohol consumption was evaluated using the DID method. The protocol calls for 4 consecutive days of testing. Each day, starting on a Tuesday 3 h after lights were turned off, the water bottles were removed from the cages and replaced with 15 ml centrifuge tubes filled with 20% (v/v) ethanol from 95% USP ethanol. On days 1–3 (Tuesday through Thursday) the length of exposure was 2 h and on the 4th day (Friday) the exposure was 4 h. No alcohol was offered in the intervening period (Saturday through Monday). This protocol was repeated weekly for 16 weeks (Table). Tubes were weighed immediately before and after the exposure period. Volume consumed was converted to g/kg body weight of ethanol.
+
+During a period of 7 weeks, mice received 2 disturbances per day (see Figure). These consisted of being exposed to wet bedding for 1 hour, 1 cm of water in the bottom of the cage with no bedding for 1 hour, no bedding for 1 hour, confinement in a 3 × 3 × 3 cm plastic box for 15 minutes, tilted cage at 45º for 1 hour, and exposure to foreign mouse or fox urine odor for 1 hour. The other stressor was a complete phase shift in the light:dark cycle over each weekend. Disruption of the light cycle (lights constantly on) occurred over the weekend (starting Friday 11:00 am) with the light cycle resuming at 11 am on Monday (lights off). The schedule was repeated weekly over the duration of the study.
+
+Treatment Periods
+
+The entire protocol took 16 weeks to complete and was subdivided into 3 periods: baseline (initial 5 weeks), CMS (next 7 weeks), and postâ€CMS (final 4 weeks). Alcohol was offered as described above for all periods and experimental groups. During the intervening 7â€week CMS period, control animals were subjected to normal housing and experimental (stress) animals were subjected to CMS.
diff --git a/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/processing.rtf b/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/processing.rtf
new file mode 100644
index 0000000..7d83d76
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/specifics.rtf b/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/specifics.rtf
new file mode 100644
index 0000000..5089c79
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/specifics.rtf
@@ -0,0 +1 @@
+NIAAA BXD Hippocampus CMS RNA-Seq (Oct20) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/tissue.rtf b/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/tissue.rtf
new file mode 100644
index 0000000..30cdeea
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_cms_rnaseq1020/tissue.rtf
@@ -0,0 +1,7 @@
+Tissue Harvest and RNA extraction
+
+The animals were sacrificed under saturated isoflurane. Brains from the animals were dissected under a cold plate (≤4o C), and hippocampus were weighted and snap frozen in dry ice bath with isopentane and stored at −80°C until RNA extraction.
+
+RNA Extraction
+
+Total RNA was extracted using Direct-zol RNA Miniprep Plus Kits (Zymo Research, Irvine, CA, USA) according to the manufacturer’s instructions. Approximately 15 mg of hippocampus tissue was added into a 2 ml tube containing 1 ml TRI Reagent® and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 min in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 rpm followed by incubating for 5 min. 0.1 ml of 1‑bromo-3‑chloropropane was add into the homogenate, shaken vigorously for 15 s, and centrifuged for 15 min at 12,000×g at 4 °C. 600 µl upper aqueous was then transferred into a new collection tube containing 600 µl 100% ethanol. The mixture was loaded into a Zymo-Spin IIC column, wash once with RNA Prep Buffer and twice with RNA Wash Buffer. All RNA had been treated with DNase to eliminate possible DNA contamination, and further precipitated with ethanol. RNA purity and integrity were verified by a nanodrop spectrophotometer and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).
diff --git a/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/cases.rtf b/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/cases.rtf
new file mode 100644
index 0000000..08a20a8
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/cases.rtf
@@ -0,0 +1,4848 @@
+The study included 241 females (aged 50 to 90 ± 2 days at the start of the experiment) from B6, D2, and 35 advanced intercross BXD strains (about 2 mice per strain and per condition). Mice were divided into 4 groups of Control (CTL, 53 mice for 31 strains), Chronic Mild Stress (CMS, 64 mice for 32 strains), Drinking in Dark (DID, 64 mice for 35 strains), and CMS+DID (60 mice for 35 strains). Mice in CTL were normally handled, while mice in other groups were singly housed in shoebox cages, with food and water provided ad libitum except when the water was replaced by 20% (v/v) EtOH (see below) for DID and CMS+DID groups (detailed treatments and schemes are showing in the Table and Figure). The ambient temperature was 21 ± 2°C, and the light cycle was 7:00/19:00 for CTL, and 23:00/11:00 the rest groups lights on/off. The animals were weighed weekly to assess health and to provide the basis for calculating the amount of EtOH consumed in grams per kilogram. All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+The table of samples that are finally used for this study.
+
+
+
+
+ |
+ Index
+ |
+
+ ID
+ |
+
+ Strain
+ |
+
+ Sex
+ |
+
+ Treatment Group
+ |
+
+ Tissue
+ |
+
+
+ |
+ 1
+ |
+
+ CMS030716_12
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 2
+ |
+
+ CMS030716_18
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 3
+ |
+
+ CMS030716_19
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 4
+ |
+
+ CMS030916_02
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 5
+ |
+
+ CMS030916_09
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 6
+ |
+
+ CMS030916_11
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 7
+ |
+
+ CMS030916_14
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 8
+ |
+
+ CMS030916_20
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 9
+ |
+
+ CMS030916_23
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 10
+ |
+
+ CMS030916_32
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 11
+ |
+
+ CMS032817_02
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 12
+ |
+
+ CMS032817_28
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 13
+ |
+
+ CMS032917_08
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 14
+ |
+
+ CMS032917_24
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 15
+ |
+
+ CMS032917_26
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 16
+ |
+
+ CMS032917_33
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 17
+ |
+
+ CMS033017_05
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 18
+ |
+
+ CMS033017_25
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 19
+ |
+
+ CMS061218_12
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 20
+ |
+
+ CMS061218_13
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 21
+ |
+
+ CMS061218_14
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 22
+ |
+
+ CMS071216_17
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 23
+ |
+
+ CMS071216_23
+ |
+
+ BXD73B
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 24
+ |
+
+ CMS071216_25
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 25
+ |
+
+ CMS071316_06
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 26
+ |
+
+ CMS071316_08
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 27
+ |
+
+ CMS071316_14
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 28
+ |
+
+ CMS071316_17
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 29
+ |
+
+ CMS071316_18
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 30
+ |
+
+ CMS071316_32
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CMS
+ |
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+ |
+
+ S31218_22
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 234
+ |
+
+ S31218_24
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 235
+ |
+
+ S31218_25
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 236
+ |
+
+ S31218_27
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 237
+ |
+
+ S31218_28
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 238
+ |
+
+ S31218_31
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 239
+ |
+
+ S31218_35
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 240
+ |
+
+ S32718_01
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 241
+ |
+
+ S32718_03
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+
diff --git a/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/experiment-design.rtf b/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/experiment-design.rtf
new file mode 100644
index 0000000..54fad3e
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/experiment-design.rtf
@@ -0,0 +1,7 @@
+Alcohol consumption was evaluated using the DID method. The protocol calls for 4 consecutive days of testing. Each day, starting on a Tuesday 3 h after lights were turned off, the water bottles were removed from the cages and replaced with 15 ml centrifuge tubes filled with 20% (v/v) ethanol from 95% USP ethanol. On days 1–3 (Tuesday through Thursday) the length of exposure was 2 h and on the 4th day (Friday) the exposure was 4 h. No alcohol was offered in the intervening period (Saturday through Monday). This protocol was repeated weekly for 16 weeks (Table). Tubes were weighed immediately before and after the exposure period. Volume consumed was converted to g/kg body weight of ethanol.
+
+During a period of 7 weeks, mice received 2 disturbances per day (see Figure). These consisted of being exposed to wet bedding for 1 hour, 1 cm of water in the bottom of the cage with no bedding for 1 hour, no bedding for 1 hour, confinement in a 3 × 3 × 3 cm plastic box for 15 minutes, tilted cage at 45º for 1 hour, and exposure to foreign mouse or fox urine odor for 1 hour. The other stressor was a complete phase shift in the light:dark cycle over each weekend. Disruption of the light cycle (lights constantly on) occurred over the weekend (starting Friday 11:00 am) with the light cycle resuming at 11 am on Monday (lights off). The schedule was repeated weekly over the duration of the study.
+
+Treatment Periods
+
+The entire protocol took 16 weeks to complete and was subdivided into 3 periods: baseline (initial 5 weeks), CMS (next 7 weeks), and postâ€CMS (final 4 weeks). Alcohol was offered as described above for all periods and experimental groups. During the intervening 7â€week CMS period, control animals were subjected to normal housing and experimental (stress) animals were subjected to CMS.
diff --git a/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/processing.rtf b/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/processing.rtf
new file mode 100644
index 0000000..7d83d76
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/specifics.rtf b/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/specifics.rtf
new file mode 100644
index 0000000..072040e
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/specifics.rtf
@@ -0,0 +1 @@
+NIAAA BXD Hippocampus CTL RNA-Seq (Oct20) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/tissue.rtf b/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/tissue.rtf
new file mode 100644
index 0000000..30cdeea
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_ctl_rnaseq1020/tissue.rtf
@@ -0,0 +1,7 @@
+Tissue Harvest and RNA extraction
+
+The animals were sacrificed under saturated isoflurane. Brains from the animals were dissected under a cold plate (≤4o C), and hippocampus were weighted and snap frozen in dry ice bath with isopentane and stored at −80°C until RNA extraction.
+
+RNA Extraction
+
+Total RNA was extracted using Direct-zol RNA Miniprep Plus Kits (Zymo Research, Irvine, CA, USA) according to the manufacturer’s instructions. Approximately 15 mg of hippocampus tissue was added into a 2 ml tube containing 1 ml TRI Reagent® and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 min in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 rpm followed by incubating for 5 min. 0.1 ml of 1‑bromo-3‑chloropropane was add into the homogenate, shaken vigorously for 15 s, and centrifuged for 15 min at 12,000×g at 4 °C. 600 µl upper aqueous was then transferred into a new collection tube containing 600 µl 100% ethanol. The mixture was loaded into a Zymo-Spin IIC column, wash once with RNA Prep Buffer and twice with RNA Wash Buffer. All RNA had been treated with DNase to eliminate possible DNA contamination, and further precipitated with ethanol. RNA purity and integrity were verified by a nanodrop spectrophotometer and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).
diff --git a/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/cases.rtf b/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/cases.rtf
new file mode 100644
index 0000000..08a20a8
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/cases.rtf
@@ -0,0 +1,4848 @@
+The study included 241 females (aged 50 to 90 ± 2 days at the start of the experiment) from B6, D2, and 35 advanced intercross BXD strains (about 2 mice per strain and per condition). Mice were divided into 4 groups of Control (CTL, 53 mice for 31 strains), Chronic Mild Stress (CMS, 64 mice for 32 strains), Drinking in Dark (DID, 64 mice for 35 strains), and CMS+DID (60 mice for 35 strains). Mice in CTL were normally handled, while mice in other groups were singly housed in shoebox cages, with food and water provided ad libitum except when the water was replaced by 20% (v/v) EtOH (see below) for DID and CMS+DID groups (detailed treatments and schemes are showing in the Table and Figure). The ambient temperature was 21 ± 2°C, and the light cycle was 7:00/19:00 for CTL, and 23:00/11:00 the rest groups lights on/off. The animals were weighed weekly to assess health and to provide the basis for calculating the amount of EtOH consumed in grams per kilogram. All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+The table of samples that are finally used for this study.
+
+
+
+
+ |
+ Index
+ |
+
+ ID
+ |
+
+ Strain
+ |
+
+ Sex
+ |
+
+ Treatment Group
+ |
+
+ Tissue
+ |
+
+
+ |
+ 1
+ |
+
+ CMS030716_12
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 2
+ |
+
+ CMS030716_18
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 3
+ |
+
+ CMS030716_19
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 4
+ |
+
+ CMS030916_02
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 5
+ |
+
+ CMS030916_09
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 6
+ |
+
+ CMS030916_11
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 7
+ |
+
+ CMS030916_14
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 8
+ |
+
+ CMS030916_20
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 9
+ |
+
+ CMS030916_23
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 10
+ |
+
+ CMS030916_32
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 11
+ |
+
+ CMS032817_02
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 12
+ |
+
+ CMS032817_28
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 13
+ |
+
+ CMS032917_08
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 14
+ |
+
+ CMS032917_24
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 15
+ |
+
+ CMS032917_26
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 16
+ |
+
+ CMS032917_33
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 17
+ |
+
+ CMS033017_05
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 18
+ |
+
+ CMS033017_25
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 19
+ |
+
+ CMS061218_12
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 20
+ |
+
+ CMS061218_13
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 21
+ |
+
+ CMS061218_14
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 22
+ |
+
+ CMS071216_17
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 23
+ |
+
+ CMS071216_23
+ |
+
+ BXD73B
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 24
+ |
+
+ CMS071216_25
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 25
+ |
+
+ CMS071316_06
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 26
+ |
+
+ CMS071316_08
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 27
+ |
+
+ CMS071316_14
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 28
+ |
+
+ CMS071316_17
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 29
+ |
+
+ CMS071316_18
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 30
+ |
+
+ CMS071316_32
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 31
+ |
+
+ CMS071416_06
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 32
+ |
+
+ CMS082817_07
+ |
+
+ BXD44
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 33
+ |
+
+ CMS082817_25
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 34
+ |
+
+ CMS082917_16
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 35
+ |
+
+ CMS083017_07
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 36
+ |
+
+ CMS083017_25
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 37
+ |
+
+ CMS092018_01
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 38
+ |
+
+ CMS092018_05
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 39
+ |
+
+ CMS092118_08
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 40
+ |
+
+ CMS102716_01
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 41
+ |
+
+ CMS102716_02
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 42
+ |
+
+ CMS102716_03
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 43
+ |
+
+ CMS102716_05
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 44
+ |
+
+ CMS102716_06
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 45
+ |
+
+ CMS102716_07
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 46
+ |
+
+ CMS102716_08
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 47
+ |
+
+ CMS102716_11
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 48
+ |
+
+ CMS102716_12
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 49
+ |
+
+ CMS102716_14
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 50
+ |
+
+ CMS102716_15
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 51
+ |
+
+ CMS102716_16
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 52
+ |
+
+ CMS102716_20
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 53
+ |
+
+ CMS102816_02
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 54
+ |
+
+ CMS102816_03
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 55
+ |
+
+ CMS102816_04
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 56
+ |
+
+ CMS102816_06
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 57
+ |
+
+ CMS102816_10
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 58
+ |
+
+ CMS102816_11
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 59
+ |
+
+ CMS102816_13
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 60
+ |
+
+ CMS102816_14
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 61
+ |
+
+ CMS102816_17
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 62
+ |
+
+ CMS102816_18
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 63
+ |
+
+ CMS102816_20
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 64
+ |
+
+ CMS102816_21
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CMS
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 65
+ |
+
+ CMS030716_01
+ |
+
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+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 166
+ |
+
+ CMS082917_22
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 167
+ |
+
+ CMS083017_10
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 168
+ |
+
+ CMS102215_20
+ |
+
+ BXD73B
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 169
+ |
+
+ CMS111716_02
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 170
+ |
+
+ CMS111716_05
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 171
+ |
+
+ CMS111716_08
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 172
+ |
+
+ CMS111716_10
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 173
+ |
+
+ CMS111716_16
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 174
+ |
+
+ CMS111716_20
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 175
+ |
+
+ CMS111716_22
+ |
+
+ BXD83
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 176
+ |
+
+ CMS111716_23
+ |
+
+ BXD73b
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 177
+ |
+
+ CMS111716_25
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 178
+ |
+
+ CMS111816_01
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 179
+ |
+
+ CMS111816_03
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 180
+ |
+
+ CMS111816_08
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 181
+ |
+
+ CMS111816_11
+ |
+
+ BXD87
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 182
+ |
+
+ CMS111816_14
+ |
+
+ BXD60
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 183
+ |
+
+ CMS111816_16
+ |
+
+ BXD73b
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 184
+ |
+
+ CMS111816_17
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 185
+ |
+
+ CMS111816_20
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 186
+ |
+
+ CMS111816_28
+ |
+
+ BXD50
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 187
+ |
+
+ S32515_12
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 188
+ |
+
+ S32515_16
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ DID
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 189
+ |
+
+ 13118_35
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 190
+ |
+
+ 13118_41
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 191
+ |
+
+ 13118_56
+ |
+
+ BXD75
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 192
+ |
+
+ 31218_19
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 193
+ |
+
+ 31218_3
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 194
+ |
+
+ 31218_36
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 195
+ |
+
+ AGE041118_03
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 196
+ |
+
+ AGE050118_07
+ |
+
+ BXD55
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 197
+ |
+
+ AGE050118_12
+ |
+
+ BXD73
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 198
+ |
+
+ AGE050118_16
+ |
+
+ BXD77
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 199
+ |
+
+ AGE050118_21
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 200
+ |
+
+ AGE050118_23
+ |
+
+ BXD86
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 201
+ |
+
+ AGE050118_27
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 202
+ |
+
+ AGE061818_02
+ |
+
+ BXD100
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 203
+ |
+
+ BL013118_12
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 204
+ |
+
+ BL013118_13
+ |
+
+ BXD34
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 205
+ |
+
+ CMS092118_24
+ |
+
+ C57BL/6J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 206
+ |
+
+ E100118_16
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 207
+ |
+
+ MT052417_09
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 208
+ |
+
+ MT052417_17
+ |
+
+ BXD51
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 209
+ |
+
+ S13118_07
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 210
+ |
+
+ S13118_08
+ |
+
+ BXD24
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 211
+ |
+
+ S13118_15
+ |
+
+ BXD40
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 212
+ |
+
+ S13118_18
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 213
+ |
+
+ S13118_19
+ |
+
+ BXD43
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 214
+ |
+
+ S13118_23
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 215
+ |
+
+ S13118_24
+ |
+
+ BXD48
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 216
+ |
+
+ S13118_26
+ |
+
+ BXD48a
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 217
+ |
+
+ S13118_36
+ |
+
+ BXD62
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 218
+ |
+
+ S13118_38
+ |
+
+ BXD65
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 219
+ |
+
+ S13118_42
+ |
+
+ BXD66
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 220
+ |
+
+ S13118_44
+ |
+
+ BXD68
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 221
+ |
+
+ S13118_58
+ |
+
+ BXD79
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 222
+ |
+
+ S13118_64
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 223
+ |
+
+ S13118_65
+ |
+
+ BXD90
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 224
+ |
+
+ S13118_7
+ |
+
+ BXD101
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 225
+ |
+
+ S31218_01
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 226
+ |
+
+ S31218_02
+ |
+
+ BXD32
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 227
+ |
+
+ S31218_04
+ |
+
+ BXD44
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 228
+ |
+
+ S31218_15
+ |
+
+ BXD63
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 229
+ |
+
+ S31218_16
+ |
+
+ BXD63
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 230
+ |
+
+ S31218_18
+ |
+
+ BXD65b
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 231
+ |
+
+ S31218_1
+ |
+
+ BXD51
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 232
+ |
+
+ S31218_21
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 233
+ |
+
+ S31218_22
+ |
+
+ BXD69
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 234
+ |
+
+ S31218_24
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 235
+ |
+
+ S31218_25
+ |
+
+ BXD70
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 236
+ |
+
+ S31218_27
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 237
+ |
+
+ S31218_28
+ |
+
+ BXD71
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 238
+ |
+
+ S31218_31
+ |
+
+ BXD73a
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 239
+ |
+
+ S31218_35
+ |
+
+ BXD78
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 240
+ |
+
+ S32718_01
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+ |
+ 241
+ |
+
+ S32718_03
+ |
+
+ DBA/2J
+ |
+
+ F
+ |
+
+ CTL
+ |
+
+ hippocampus
+ |
+
+
+
diff --git a/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/experiment-design.rtf b/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/experiment-design.rtf
new file mode 100644
index 0000000..54fad3e
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/experiment-design.rtf
@@ -0,0 +1,7 @@
+Alcohol consumption was evaluated using the DID method. The protocol calls for 4 consecutive days of testing. Each day, starting on a Tuesday 3 h after lights were turned off, the water bottles were removed from the cages and replaced with 15 ml centrifuge tubes filled with 20% (v/v) ethanol from 95% USP ethanol. On days 1–3 (Tuesday through Thursday) the length of exposure was 2 h and on the 4th day (Friday) the exposure was 4 h. No alcohol was offered in the intervening period (Saturday through Monday). This protocol was repeated weekly for 16 weeks (Table). Tubes were weighed immediately before and after the exposure period. Volume consumed was converted to g/kg body weight of ethanol.
+
+During a period of 7 weeks, mice received 2 disturbances per day (see Figure). These consisted of being exposed to wet bedding for 1 hour, 1 cm of water in the bottom of the cage with no bedding for 1 hour, no bedding for 1 hour, confinement in a 3 × 3 × 3 cm plastic box for 15 minutes, tilted cage at 45º for 1 hour, and exposure to foreign mouse or fox urine odor for 1 hour. The other stressor was a complete phase shift in the light:dark cycle over each weekend. Disruption of the light cycle (lights constantly on) occurred over the weekend (starting Friday 11:00 am) with the light cycle resuming at 11 am on Monday (lights off). The schedule was repeated weekly over the duration of the study.
+
+Treatment Periods
+
+The entire protocol took 16 weeks to complete and was subdivided into 3 periods: baseline (initial 5 weeks), CMS (next 7 weeks), and postâ€CMS (final 4 weeks). Alcohol was offered as described above for all periods and experimental groups. During the intervening 7â€week CMS period, control animals were subjected to normal housing and experimental (stress) animals were subjected to CMS.
diff --git a/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/processing.rtf b/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/processing.rtf
new file mode 100644
index 0000000..7d83d76
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/specifics.rtf b/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/specifics.rtf
new file mode 100644
index 0000000..017deac
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/specifics.rtf
@@ -0,0 +1 @@
+NIAAA BXD Hippocampus DID RNA-Seq (Oct20) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/tissue.rtf b/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/tissue.rtf
new file mode 100644
index 0000000..30cdeea
--- /dev/null
+++ b/general/datasets/Niaaa_bxd_hip_did_rnaseq1020/tissue.rtf
@@ -0,0 +1,7 @@
+Tissue Harvest and RNA extraction
+
+The animals were sacrificed under saturated isoflurane. Brains from the animals were dissected under a cold plate (≤4o C), and hippocampus were weighted and snap frozen in dry ice bath with isopentane and stored at −80°C until RNA extraction.
+
+RNA Extraction
+
+Total RNA was extracted using Direct-zol RNA Miniprep Plus Kits (Zymo Research, Irvine, CA, USA) according to the manufacturer’s instructions. Approximately 15 mg of hippocampus tissue was added into a 2 ml tube containing 1 ml TRI Reagent® and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 min in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 rpm followed by incubating for 5 min. 0.1 ml of 1‑bromo-3‑chloropropane was add into the homogenate, shaken vigorously for 15 s, and centrifuged for 15 min at 12,000×g at 4 °C. 600 µl upper aqueous was then transferred into a new collection tube containing 600 µl 100% ethanol. The mixture was loaded into a Zymo-Spin IIC column, wash once with RNA Prep Buffer and twice with RNA Wash Buffer. All RNA had been treated with DNase to eliminate possible DNA contamination, and further precipitated with ethanol. RNA purity and integrity were verified by a nanodrop spectrophotometer and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).
diff --git a/general/datasets/None/summary.rtf b/general/datasets/None/summary.rtf
new file mode 100644
index 0000000..5c22bc2
--- /dev/null
+++ b/general/datasets/None/summary.rtf
@@ -0,0 +1,40 @@
+Question: I have generated some phenotype data that I would like to put into GeneNetwork. How should I name my traits?
+
+Answer: Phenotype trait names in GeneNetwork should have this general form when possible:
+
+
+ - Your description should start with very short list of "approved" general category and ontology terms. These terms are used to subdivide the entire collection of phenotypes by system, organ, or level of analysis. Some examples may help: "Central nervous system", "Immune system", "Metabolism", "Development", or "Urogenital system". Capitalize this list as you would a standard English sentence. Separate terms by commas and then end the terms with a colon. For example, "Central nervous system, pharmacology, endocrinology:" is a valid set of three terms. These terms do not really describe your trait, but are used by you and other users to figure out how many traits there are in specific categories.
+
+ Before making up your own terms, please review the current terms in GeneNetwork and find some terms/ontology categories that look good to you. If you have questions contact one of us on the GeneNetwork development team.
+ - After the colon start with your description of the phenotype you have generated. For example: "Ethanol response..." or "Anxiety assay...", "Brain weight...". The first letter should almost always be capitalized.
+ - Do not start with a generic uninformative word such as "Mean", "Maximum", "Mechanical", "Count", "Number", "Difference", "Baseline", "Induction", "Decrease", "New", "Adjusted", "Distance", "Right", "Left", "Bilateral", "Time", "Total", "Percentage", "Percent". The reason is that the traits should be alphabetized and categorized in a conceptually useful way; not by something "dumb" like the "total" or "percent".
+ - Do not start with a specific instrumental assay such as "Morris water maze" or "Dowel test..." or "Porsolt test behavior". Many of these tests will be unknown to other users. Try to use a term that reflects the intent of the assay (Motor coordination test, Learning and memory assay, Allergic airway response). This may be difficult, particularly for tests such as the Porsolt swim test and the Morris water maze that measure aspects of many different traits (anxiety, activity level, spatial navigation, visual acuity etc). But in the interest of clarity of intent rather than precision of measurement, please follow this suggestion. The actual assay instrument can be listed after the primary and secondary trait descriptions.
+ - Many traits can be difficult to categorize in a consistent way. For example a trait such as "ventral midbrain copper level in males" could be labeled "copper level in the ventral midbrain." There is no right or wrong way to do this, but the convention should be to choose the order that you think will be most useful to other users in terms of comprehension and consistency with other existing phenotypes. Review related phenotypes before you start naming your own. You will find good and bad examples.
+ - Dose and route of drug delivery. If the phenotype is a pharmacological phenotype, whenever practical enter the doses and routes of injection in parentheses after the name of the general trait. For example, "Cocaine response (40 mg/kg ip)". We would prefer to use "ip" and "iv" rather than i.p. and i.v., but this is not a strong preference. If a protocol requires multiple treatments, please include them if possible. For example, "Cocaine response (3 x 3.2 mg/kg ip, Days 2, 3, 4),...").
+ - Series of more precise definitions of the phenotype and the subject(s) will often follow with commas used as separators. If possible make this understandable to almost any user, even at the risk of being wordy.
+
For example, "Cocaine response (3 x 3.2 mg/kg ip, Days 2, 3, and 4), conditioned place preference (CPP), change in time in cocaine-paired compartment relative to baseline (Day 5 minus Day 1) for 50 to 90-day-old males and females [sec]"
+
+ - Sex. If the data are for males please write out "in males" or "of male" or "for males". Do not just add a comma such as " , males" or "(M)". This should usually go at the end of the description.
+ - Age and condition of subjects can be added if you think it is essential or helpful. However, do not bother with a generic addition "adult" since that is what most users will reasonably assume. If you would like to add an age range then use this format "in 100 to 200-day-old males and females" or "of 3 to 4-month-old males".
+ - Mandatory units of measurement between square brackets [min] or [sec] or [n bream breaks/10 min test]. If you are using an ordinal scale, then describe the scale within the brackets. If the units are simply a ratio or percentage then use [ratio] or [%].
+
+
+Other advice on trait descriptions:
+
+
+ - Do Not Capitalize Each Word in a Description. (e.g, Ethanol Response, Distance traveled after saline - Distance traveled after ethanol for males and females [cm in a 0-5 min test period] )
+ - Do not use "-" as a minus sign. The dash is too confusing and may sometimes be used as a hyphen. Spell out "minus"
+ - No not use ALL CAP in a trait description (e.g., TOTAL)
+ - Do use commas when appropriate. For example, Morphine response severity of abdominal constriction for males needs a comma between "response" and "severity"
+ - Do not use extraneous words such as "time SPENT on rotarod". "time on rotarod" is good enough.
+ - Do not start with text or abbreviations that will not be understandable to all users, such as "RSS female and male..."
+ - Please us a space between a number and the units: Prepulse inhibition at 70 dB for females (not 70db). Please use the correct form of the abbreviation.
+ - Use American spelling. [RWW, September 10, 2009]
+
+
+Examples of accepted phenotype descriptions: (by Amelie Baud. Wellcome Trust Centre for Human Genetics, Oxford, UK.)
+
+
+ - Central nervous system, behavior: Anxiety assay, locomotor activity in novel cage between minutes 25 and 30 in novel cage, normalized by Box-Cox transformation [cm]
+ - Metabolism: Glycemia (intraperitoneal glucose tolerance test), area under the curve between minutes 0 and 120 after injection, normalized by Box-Cox transformation [mM.min-1]
+
diff --git a/general/datasets/OHSU_HS-CC_ILMStr_0211/summary.rtf b/general/datasets/OHSU_HS-CC_ILMStr_0211/summary.rtf
new file mode 100644
index 0000000..e096b10
--- /dev/null
+++ b/general/datasets/OHSU_HS-CC_ILMStr_0211/summary.rtf
@@ -0,0 +1,2 @@
+The current study focused on the extent genetic diversity within a species (Mus musculus) affects gene co-expression network structure. To examine this issue, we have created a new mouse resource, a heterogeneous stock (HS) formed from the same eight inbred strains that have been used to create the collaborative cross (CC). The eight inbred strains capture > 90% of the genetic diversity available within the species. For contrast with the HS-CC, a C57BL/6J (B6) × DBA/2J (D2) F2 intercross and the HS4, derived from crossing the B6, D2, BALB/cJ and LP/J strains, were used. Brain (striatum) gene expression data were obtained using the Illumina Mouse WG 6.1 array, and the data sets were interrogated using a weighted gene co-expression network analysis (WGCNA).
+Read full article: Genetic diversity and striatal gene networks: focus on the heterogeneous stock-collaborative cross (HS-CC) mouse.
diff --git a/general/datasets/OHSU_HS_CC_ILMStr_0211/summary.rtf b/general/datasets/OHSU_HS_CC_ILMStr_0211/summary.rtf
deleted file mode 100644
index e096b10..0000000
--- a/general/datasets/OHSU_HS_CC_ILMStr_0211/summary.rtf
+++ /dev/null
@@ -1,2 +0,0 @@
-The current study focused on the extent genetic diversity within a species (Mus musculus) affects gene co-expression network structure. To examine this issue, we have created a new mouse resource, a heterogeneous stock (HS) formed from the same eight inbred strains that have been used to create the collaborative cross (CC). The eight inbred strains capture > 90% of the genetic diversity available within the species. For contrast with the HS-CC, a C57BL/6J (B6) × DBA/2J (D2) F2 intercross and the HS4, derived from crossing the B6, D2, BALB/cJ and LP/J strains, were used. Brain (striatum) gene expression data were obtained using the Illumina Mouse WG 6.1 array, and the data sets were interrogated using a weighted gene co-expression network analysis (WGCNA).
-Read full article: Genetic diversity and striatal gene networks: focus on the heterogeneous stock-collaborative cross (HS-CC) mouse.
diff --git a/general/datasets/ONCRetExMoGene2_0413/acknowledgment.rtf b/general/datasets/ONCRetExMoGene2_0413/acknowledgment.rtf
deleted file mode 100644
index 13c6b1e..0000000
--- a/general/datasets/ONCRetExMoGene2_0413/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/ONCRetExMoGene2_0413/cases.rtf b/general/datasets/ONCRetExMoGene2_0413/cases.rtf
deleted file mode 100644
index 6b36c70..0000000
--- a/general/datasets/ONCRetExMoGene2_0413/cases.rtf
+++ /dev/null
@@ -1,1728 +0,0 @@
-Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
-
-
-
-
-
-
-
-
-
- | Index |
- EIGC ID (LIMS ID) |
- Strain |
- Sex |
- Age at harvest |
- RIN Score |
-
-
- | 1 |
- 602 |
- BXD9 |
- F |
- 133 |
- 9.1 |
-
-
- | 2 |
- 603 |
- BXD9 |
- M |
- 100 |
- 9.5 |
-
-
- | 3 |
- 604 |
- BXD40 |
- F |
- 100 |
- 9.4 |
-
-
- | 4 |
- 605 |
- BXD40 |
- M |
- 100 |
- 9.1 |
-
-
- | 5 |
- 606 |
- BXD48 |
- F |
- 75 |
- 9.1 |
-
-
- | 6 |
- 607 |
- BXD48 |
- M |
- 75 |
- 8.6 |
-
-
- | 7 |
- 608 |
- BXD63 |
- F |
- 75 |
- 9.2 |
-
-
- | 8 |
- 609 |
- BXD63 |
- M |
- 61 |
- 9.4 |
-
-
- | 9 |
- 612 |
- BXD73 |
- M |
- 108 |
- 10 |
-
-
- | 10 |
- 614 |
- BXD87 |
- M |
- 85 |
- 9.2 |
-
-
- | 11 |
- 615 |
- BXD87 |
- F |
- 85 |
- 9.9 |
-
-
- | 12 |
- 616 |
- BXD69 |
- F |
- 76 |
- 9.3 |
-
-
- | 13 |
- 617 |
- BXD69 |
- M |
- 100 |
- 10 |
-
-
- | 14 |
- 618 |
- BXD51 |
- M |
- 82 |
- 8.9 |
-
-
- | 15 |
- 619 |
- BXD92 (BXD65b) |
- M |
- 82 |
- 8.8 |
-
-
- | 16 |
- 620 |
- BXD92 (BXD65b) |
- F |
- 82 |
- 8.8 |
-
-
- | 17 |
- 635 |
- BXD100 |
- M |
- 70 |
- 9 |
-
-
- | 18 |
- 636 |
- BXD100 |
- M |
- 70 |
- 8.8 |
-
-
- | 19 |
- 652 |
- BXD92 (BXD65b) |
- F |
- 64 |
- 9 |
-
-
- | 20 |
- 653 |
- BXD87 |
- F |
- 67 |
- 9.7 |
-
-
- | 21 |
- 654 |
- BXD87 |
- M |
- 67 |
- 8.9 |
-
-
- | 22 |
- 655 |
- BXD63 |
- M |
- 71 |
- 9 |
-
-
- | 23 |
- 660 |
- BXD69 |
- M |
- 97 |
- 10 |
-
-
- | 24 |
- 687 |
- BXD6 |
- M |
- 85 |
- 7.7 |
-
-
- | 25 |
- 688 |
- BXD6 |
- M |
- 85 |
- 9.4 |
-
-
- | 26 |
- 690 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 27 |
- 691 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 28 |
- 692 |
- BXD12 |
- M |
- 83 |
- 10 |
-
-
- | 29 |
- 695 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 30 |
- 696 |
- BXD5 |
- M |
- 77 |
- 10 |
-
-
- | 31 |
- 698 |
- BXD5 |
- F |
- 77 |
- 9.9 |
-
-
- | 32 |
- 699 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 33 |
- 701 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 34 |
- 702 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 35 |
- 705 |
- BXD8 |
- F |
- 77 |
- 9.2 |
-
-
- | 36 |
- 707 |
- BXD15 |
- F |
- 77 |
- 9.4 |
-
-
- | 37 |
- 708 |
- BXD15 |
- F |
- 77 |
- 9.1 |
-
-
- | 38 |
- 710 |
- BXD15 |
- M |
- 77 |
- 9.1 |
-
-
- | 39 |
- 713 |
- BXD22 |
- F |
- 71 |
- 9.5 |
-
-
- | 40 |
- 714 |
- BXD22 |
- F |
- 71 |
- 9.7 |
-
-
- | 41 |
- 716 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 42 |
- 717 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 43 |
- 719 |
- BXD14 |
- F |
- 70 |
- 9.2 |
-
-
- | 44 |
- 722 |
- BXD14 |
- M |
- 70 |
- 8.9 |
-
-
- | 45 |
- 723 |
- BXD14 |
- M |
- 70 |
- 9.2 |
-
-
- | 46 |
- 725 |
- BXD18 |
- F |
- 70 |
- 9 |
-
-
- | 47 |
- 726 |
- BXD18 |
- F |
- 70 |
- 9.1 |
-
-
- | 48 |
- 728 |
- BXD18 |
- M |
- 70 |
- 9.1 |
-
-
- | 49 |
- 729 |
- BXD18 |
- M |
- 70 |
- 9.2 |
-
-
- | 50 |
- 731 |
- BXD19 |
- F |
- 66 |
- 9.3 |
-
-
- | 51 |
- 732 |
- BXD19 |
- F |
- 66 |
- 9.4 |
-
-
- | 52 |
- 734 |
- BXD19 |
- M |
- 66 |
- 9.8 |
-
-
- | 53 |
- 735 |
- BXD19 |
- M |
- 66 |
- 9.4 |
-
-
- | 54 |
- 737 |
- BXD21 |
- F |
- 71 |
- 9.7 |
-
-
- | 55 |
- 738 |
- BXD21 |
- F |
- 71 |
- 9.6 |
-
-
- | 56 |
- 740 |
- BXD21 |
- M |
- 71 |
- 9.1 |
-
-
- | 57 |
- 741 |
- BXD21 |
- M |
- 71 |
- 9.7 |
-
-
- | 58 |
- 743 |
- BXD2 |
- F |
- 70 |
- 8.3 |
-
-
- | 59 |
- 744 |
- BXD2 |
- F |
- 70 |
- 8.6 |
-
-
- | 60 |
- 746 |
- BXD2 |
- M |
- 70 |
- 7.5 |
-
-
- | 61 |
- 747 |
- BXD2 |
- M |
- 77 |
- 8.6 |
-
-
- | 62 |
- 768 |
- BXD48 |
- M |
- 121 |
- 9.4 |
-
-
- | 63 |
- 770 |
- BXD92 (BXD65b) |
- M |
- 65 |
- 10 |
-
-
- | 64 |
- 771 |
- BXD101 |
- F |
- 85 |
- 8.3 |
-
-
- | 65 |
- 772 |
- BXD101 |
- F |
- 85 |
- 9.3 |
-
-
- | 66 |
- 773 |
- BXD101 |
- M |
- 86 |
- 9.5 |
-
-
- | 67 |
- 774 |
- BXD101 |
- M |
- 86 |
- 9.8 |
-
-
- | 68 |
- 775 |
- BXD102 |
- F |
- 66 |
- 9.5 |
-
-
- | 69 |
- 776 |
- BXD102 |
- F |
- 66 |
- 10 |
-
-
- | 70 |
- 777 |
- BXD102 |
- M |
- 84 |
- 9.6 |
-
-
- | 71 |
- 787 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 72 |
- 788 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 73 |
- 789 |
- BXD63 |
- F |
- 115 |
- 9.7 |
-
-
- | 74 |
- 790 |
- BXD100 |
- F |
- 72 |
- 9.8 |
-
-
- | 75 |
- 791 |
- BXD100 |
- F |
- 72 |
- 10 |
-
-
- | 76 |
- 818 |
- BXD51 |
- F |
- 77 |
- 9.7 |
-
-
- | 77 |
- 819 |
- BXD51 |
- F |
- 77 |
- 9.6 |
-
-
- | 78 |
- 820 |
- BXD51 |
- M |
- 72 |
- 9.7 |
-
-
- | 79 |
- 821 |
- BXD65 |
- M |
- 72 |
- 9.6 |
-
-
- | 80 |
- 822 |
- BXD65 |
- M |
- 65 |
- 9.5 |
-
-
- | 81 |
- 825 |
- BXD65 |
- F |
- 72 |
- 9.5 |
-
-
- | 82 |
- 827 |
- BXD86 |
- M |
- 69 |
- 9.1 |
-
-
- | 83 |
- 828 |
- BXD86 |
- M |
- 69 |
- 9.4 |
-
-
- | 84 |
- 829 |
- BXD90 |
- F |
- 69 |
- 9.6 |
-
-
- | 85 |
- 831 |
- BXD9 |
- M |
- 127 |
- 9.7 |
-
-
- | 86 |
- 832 |
- BXD39 |
- F |
- 99 |
- 9.4 |
-
-
- | 87 |
- 833 |
- BXD39 |
- F |
- 107 |
- 9.3 |
-
-
- | 88 |
- 834 |
- BXD60 |
- F |
- 107 |
- 9.5 |
-
-
- | 89 |
- 836 |
- BXD84 |
- M |
- 103 |
- 9.7 |
-
-
- | 90 |
- 846 |
- BXD39 |
- M |
- 63 |
- 9.7 |
-
-
- | 91 |
- 847 |
- BXD39 |
- M |
- 63 |
- 9.8 |
-
-
- | 92 |
- 849 |
- BXD20 |
- F |
- 70 |
- 10 |
-
-
- | 93 |
- 850 |
- BXD20 |
- M |
- 70 |
- 10 |
-
-
- | 94 |
- 851 |
- BXD20 |
- * |
- 70 |
- 9.5 |
-
-
- | 95 |
- 855 |
- DBA/2J |
- F |
- 78 |
- 9.7 |
-
-
- | 96 |
- 856 |
- DBA/2J |
- F |
- 78 |
- 10 |
-
-
- | 97 |
- 857 |
- DBA/2J |
- M |
- 78 |
- 10 |
-
-
- | 98 |
- 858 |
- DBA/2J |
- M |
- 78 |
- 9.9 |
-
-
- | 99 |
- 859 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 100 |
- 860 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 101 |
- 861 |
- C57BL/6J |
- M |
- 78 |
- 10 |
-
-
- | 102 |
- 862 |
- C57BL/6J |
- M |
- 78 |
- 9.6 |
-
-
- | 103 |
- EGE10907-0172_890_20844 |
- BXD28 |
- M |
- 75 |
- 10 |
-
-
- | 104 |
- EGE10907-0173_891_20845 |
- BXD28 |
- M |
- 75 |
- 9.7 |
-
-
- | 105 |
- EGE10907-0174_892_20846 |
- BXD28 |
- F |
- 75 |
- 9.7 |
-
-
- | 106 |
- EGE10907-0176_895_20848 |
- BXD33 |
- M |
- 75 |
- 9.88 |
-
-
- | 107 |
- EGE10907-0177_896_20849 |
- BXD33 |
- F |
- 75 |
- 10 |
-
-
- | 108 |
- EGE10907-0178_897_20850 |
- BXD33 |
- F |
- 75 |
- 9.4 |
-
-
- | 109 |
- EGE10907-0179_898_20851 |
- BXD36 |
- M |
- 75 |
- 9.4 |
-
-
- | 110 |
- EGE10907-0180_899_20852 |
- BXD36 |
- F |
- 75 |
- 9.5 |
-
-
- | 111 |
- EGE10907-0181_900_20853 |
- BXD36 |
- F |
- 75 |
- 9.1 |
-
-
- | 112 |
- EGE10907-0182_910_20854 |
- BXD27 |
- M |
- 70 |
- 9.7 |
-
-
- | 113 |
- EGE10907-0183_990_20855 |
- BXD9 |
- F |
- 98 |
- 9.4 |
-
-
- | 114 |
- EGE10907-0184_991_20856 |
- BXD16 |
- F |
- 113 |
- 10 |
-
-
- | 115 |
- EGE10907-0185_992_20857 |
- BXD16 |
- M |
- 113 |
- 9 |
-
-
- | 116 |
- EGE10907-0186_993_20858 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 117 |
- EGE10907-0187_994_20859 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 118 |
- EGE10907-0188_996_20860 |
- BXD48 |
- F |
- 98 |
- 9.4 |
-
-
- | 119 |
- EGE10907-0189_997_20861 |
- BXD73 |
- M |
- 106 |
- 10 |
-
-
- | 120 |
- EGE10907-0190_999_20862 |
- BXD11 |
- F |
- 121 |
- 9.6 |
-
-
- | 121 |
- EGE10907-0191_100_20863 |
- BXD11 |
- F |
- 121 |
- 9.9 |
-
-
- | 122 |
- EGE10907-0192_1010_21276 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 123 |
- EGE10907-0193_1011_21277 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 124 |
- EGE10907-0194_1012_21278 |
- BXD16 |
- F |
- 65 |
- 10 |
-
-
- | 125 |
- EGE10907-0195_1015_21279 |
- BXD16 |
- M |
- 65 |
- 10 |
-
-
- | 126 |
- EGE10907-0196_1019_21280 |
- BXD33 |
- M |
- 75 |
- 10 |
-
-
- | 127 |
- EGE10907-0197_1020_21281 |
- BXD36 |
- M |
- 78 |
- 10 |
-
-
- | 128 |
- EGE10907-0198_1021_21282 |
- BXD38 |
- F |
- 70 |
- 9.8 |
-
-
- | 129 |
- EGE10907-0199_1022_21283 |
- BXD38 |
- F |
- 70 |
- 10 |
-
-
- | 130 |
- EGE10907-0200_1023_21284 |
- BXD38 |
- M |
- 70 |
- 9.7 |
-
-
- | 131 |
- EGE10907-0201_1047_21285 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 132 |
- EGE10907-0202_1048_21286 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 133 |
- EGE10907-0203_1049_21287 |
- BXD38 |
- M |
- 77 |
- 10 |
-
-
- | 134 |
- EGE10907-0204_1050_21288 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 135 |
- EGE10907-0205_1051_21289 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 136 |
- EGE10907-0206_1052_21290 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 137 |
- EGE10907-0207_1053_21291 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 138 |
- EGE10907-0208_1054_21292 |
- BXD90 |
- F |
- 71 |
- 10 |
-
-
- | 139 |
- EGE10907-0209_1055_21293 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 140 |
- EGE10907-0210_1056_21294 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 141 |
- EGE10907-0211_1148_21295 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 142 |
- EGE10907-0212_1149_21296 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 143 |
- EGE10907-0213_1150_21297 |
- BXD31 |
- M |
- 90 |
- 10 |
-
-
- | 144 |
- EGE10907-0214_1151_21298 |
- BXD31 |
- M |
- 90 |
- 9.9 |
-
-
- | 145 |
- EGE10907-0215_1152_21299 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 146 |
- EGE10907-0216_21429 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 147 |
- EGE10907-0217_21430 |
- BXD42 |
- M |
- 83 |
- 10 |
-
-
- | 148 |
- EGE10907-0218_21431 |
- BXD42 |
- M |
- 83 |
- 9.3 |
-
-
- | 149 |
- EGE10907-0219_21432 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 150 |
- EGE10907-0220_21433 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 151 |
- EGE10907-0221_21434 |
- BXD50 |
- F |
- 92 |
- 10 |
-
-
- | 152 |
- EGE10907-0222_21435 |
- BXD1 |
- M |
- 73 |
- 9.6 |
-
-
- | 153 |
- EGE10907-0223_21436 |
- BXD13 |
- F |
- 71 |
- 9.7 |
-
-
- | 154 |
- EGE10907-0224_21437 |
- BXD1 |
- M |
- 71 |
- 9.5 |
-
-
- | 155 |
- EGE10907-0225_21438 |
- BXD13 |
- F |
- 71 |
- 9.6 |
-
-
- | 156 |
- EGE10907-0226_21439 |
- BXD43 |
- F |
- 85 |
- 10 |
-
-
- | 157 |
- EGE10907-0227_21452 |
- BXD43 |
- F |
- 85 |
- 9.6 |
-
-
- | 158 |
- EGE10907-0229_21442 |
- BXD43 |
- M |
- 85 |
- 8.2 |
-
-
- | 159 |
- EGE10907-0230_21443 |
- BXD50 |
- M |
- 69 |
- 9.4 |
-
-
- | 160 |
- EGE10907-0231_21444 |
- BXD1 |
- F |
- 68 |
- 9.4 |
-
-
- | 161 |
- EGE10907-0232_21445 |
- BXD1 |
- F |
- 68 |
- 9.6 |
-
-
- | 162 |
- EGE10907-0233_21446 |
- BXD29 |
- M |
- 65 |
- 9.5 |
-
-
- | 163 |
- EGE10907-0234_21447 |
- BXD29 |
- M |
- 65 |
- 10 |
-
-
- | 164 |
- EGE10907-0235_21448 |
- BXD75 |
- F |
- 68 |
- 10 |
-
-
- | 165 |
- EGE10907-0236_21449 |
- BXD75 |
- M |
- 68 |
- 10 |
-
-
- | 166 |
- EGE10907-0237_21450 |
- BXD96 |
- F |
- 67 |
- 9.9 |
-
-
- | 167 |
- EGE10907-0238_21931 |
- BXD99 |
- M |
- 71 |
- 7.9 |
-
-
- | 168 |
- EGE10907-0239_21932 |
- BXD99 |
- M |
- 71 |
- 9.7 |
-
-
- | 169 |
- EGE10907-0240_21933 |
- BXD67 |
- F |
- 68 |
- 8.8 |
-
-
- | 170 |
- EGE10907-0241_21934 |
- BXD67 |
- F |
- 68 |
- 8.5 |
-
-
- | 171 |
- EGE10907-0242_21935 |
- BXD67 |
- M |
- 68 |
- 9.5 |
-
-
- | 172 |
- EGE10907-0243_21936 |
- BXD67 |
- M |
- 68 |
- 9.6 |
-
-
- | 173 |
- EGE10907-0244_21937 |
- BXD6 |
- F |
- 68 |
- 9.6 |
-
-
- | 174 |
- EGE10907-0245_21938 |
- BXD12 |
- M |
- 82 |
- 9.5 |
-
-
- | 175 |
- EGE10907-0246_21939 |
- BXD60 |
- F |
- 72 |
- 9.6 |
-
-
- | 176 |
- EGE10907-0247_21940 |
- BXD65 |
- F |
- 75 |
- 9.1 |
-
-
- | 177 |
- EGE10907-0248_21941 |
- BXD75 |
- F |
- 69 |
- 8.8 |
-
-
- | 178 |
- EGE10907-0249_21942_(MoGene-2_0-st) |
- BXD75 |
- M |
- 69 |
- 9.2 |
-
-
- | 179 |
- EGE10907-0250_21943 |
- BXD8 |
- F |
- 97 |
- 9.1 |
-
-
- | 180 |
- EGE10907-0251_21944 |
- BXD85 |
- F |
- 79 |
- 8.6 |
-
-
- | 181 |
- EGE10907-0252_21945 |
- BXD85 |
- M |
- 79 |
- 9.1 |
-
-
- | 182 |
- EGE10907-0253_21946 |
- BXD85 |
- M |
- 79 |
- 9.4 |
-
-
- | 183 |
- EGE10907-0254_21947 |
- BXD102 |
- M |
- 94 |
- 8.6 |
-
-
- | 184 |
- EGE10907-0255_21948 |
- BXD99 |
- F |
- 83 |
- 9 |
-
-
- | 185 |
- EGE10907-0256_21949 |
- BXD69 |
- F |
- 68 |
- 9 |
-
-
- | 186 |
- EGE10907-0257_21950 |
- BXD84 |
- F |
- 74 |
- 9.5 |
-
-
- | 187 |
- EGE10907-0258_21951 |
- BXD84 |
- F |
- 74 |
- 9.4 |
-
-
- | 188 |
- EGE10907-0259_21952 |
- BXD84 |
- M |
- 74 |
- 8.6 |
-
-
- | 189 |
- EGE10907-0260_21451 |
- BXD96 |
- M |
- 67 |
- 9.2 |
-
-
- | 190 |
- EGE10907-0261_21452 |
- BXD99 |
- F |
- 71 |
- 8.9 |
-
-
- | 191 |
- EGE10907-0262_21931 |
- BXD6 |
- F |
- 66 |
- 9.4 |
-
-
- | 192 |
- EGE10907-0263_21932 |
- BXD14 |
- F |
- 69 |
- 8.5 |
-
-
- | 193 |
- EGE10907-0264_21933 |
- BXD34 |
- M |
- 79 |
- 9.1 |
-
-
- | 194 |
- EGE10907-0265_21934 |
- BXD34 |
- M |
- 79 |
- 9.9 |
-
-
- | 195 |
- EGE10907-0266_21935 |
- BXD40 |
- F |
- 75 |
- 9.6 |
-
-
- | 196 |
- EGE10907-0267_21936 |
- BXD40 |
- M |
- 78 |
- 9.7 |
-
-
- | 197 |
- EGE10907-0268_21937 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 198 |
- EGE10907-0269_21938 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 199 |
- EGE10907-0270_21939 |
- BXD56 |
- M |
- 72 |
- 9.6 |
-
-
- | 200 |
- EGE10907-0271_21940 |
- BXD56 |
- M |
- 72 |
- 9.4 |
-
-
- | 201 |
- EGE10907-0272_21941 |
- BXD71 |
- F |
- 72 |
- 9.9 |
-
-
- | 202 |
- EGE10907-0273_21942 |
- BXD71 |
- F |
- 75 |
- 9.4 |
-
-
- | 203 |
- EGE10907-0274_21943 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 204 |
- EGE10907-0275_21944 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 205 |
- EGE10907-0276_21945 |
- BXD27 |
- M |
- 65 |
- 10 |
-
-
- | 206 |
- EGE10907-0277_21946 |
- BXD15 |
- M |
- 65 |
- 10 |
-
-
- | 207 |
- EGE10907-0278_21947 |
- BXD20 |
- F |
- 125 |
- 10 |
-
-
- | 208 |
- EGE10907-0279_21948 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 209 |
- EGE10907-0280_21949 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 210 |
- EGE10907-0281_21950 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 211 |
- EGE10907-0282_21951 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 212 |
- EGE10907-0283_21952 |
- BXD85 |
- F |
- 87 |
- 10 |
-
-
- | 213 |
- EGE10907-0284_21451 |
- BXD43 |
- M |
- 75 |
- 9.8 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/ONCRetExMoGene2_0413/platform.rtf b/general/datasets/ONCRetExMoGene2_0413/platform.rtf
deleted file mode 100644
index 19fc38c..0000000
--- a/general/datasets/ONCRetExMoGene2_0413/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/ONCRetExMoGene2_0413/processing.rtf b/general/datasets/ONCRetExMoGene2_0413/processing.rtf
deleted file mode 100644
index a7b767e..0000000
--- a/general/datasets/ONCRetExMoGene2_0413/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/ONCRetExMoGene2_0413/summary.rtf b/general/datasets/ONCRetExMoGene2_0413/summary.rtf
deleted file mode 100644
index 96a87e5..0000000
--- a/general/datasets/ONCRetExMoGene2_0413/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/ONCRetExMoGene2_0413/tissue.rtf b/general/datasets/ONCRetExMoGene2_0413/tissue.rtf
deleted file mode 100644
index 056d7eb..0000000
--- a/general/datasets/ONCRetExMoGene2_0413/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/ONCRetMoGene2_0413/acknowledgment.rtf b/general/datasets/ONCRetMoGene2_0413/acknowledgment.rtf
deleted file mode 100644
index 13c6b1e..0000000
--- a/general/datasets/ONCRetMoGene2_0413/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/ONCRetMoGene2_0413/cases.rtf b/general/datasets/ONCRetMoGene2_0413/cases.rtf
deleted file mode 100644
index 6b36c70..0000000
--- a/general/datasets/ONCRetMoGene2_0413/cases.rtf
+++ /dev/null
@@ -1,1728 +0,0 @@
-Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
-
-
-
-
-
-
-
-
-
- | Index |
- EIGC ID (LIMS ID) |
- Strain |
- Sex |
- Age at harvest |
- RIN Score |
-
-
- | 1 |
- 602 |
- BXD9 |
- F |
- 133 |
- 9.1 |
-
-
- | 2 |
- 603 |
- BXD9 |
- M |
- 100 |
- 9.5 |
-
-
- | 3 |
- 604 |
- BXD40 |
- F |
- 100 |
- 9.4 |
-
-
- | 4 |
- 605 |
- BXD40 |
- M |
- 100 |
- 9.1 |
-
-
- | 5 |
- 606 |
- BXD48 |
- F |
- 75 |
- 9.1 |
-
-
- | 6 |
- 607 |
- BXD48 |
- M |
- 75 |
- 8.6 |
-
-
- | 7 |
- 608 |
- BXD63 |
- F |
- 75 |
- 9.2 |
-
-
- | 8 |
- 609 |
- BXD63 |
- M |
- 61 |
- 9.4 |
-
-
- | 9 |
- 612 |
- BXD73 |
- M |
- 108 |
- 10 |
-
-
- | 10 |
- 614 |
- BXD87 |
- M |
- 85 |
- 9.2 |
-
-
- | 11 |
- 615 |
- BXD87 |
- F |
- 85 |
- 9.9 |
-
-
- | 12 |
- 616 |
- BXD69 |
- F |
- 76 |
- 9.3 |
-
-
- | 13 |
- 617 |
- BXD69 |
- M |
- 100 |
- 10 |
-
-
- | 14 |
- 618 |
- BXD51 |
- M |
- 82 |
- 8.9 |
-
-
- | 15 |
- 619 |
- BXD92 (BXD65b) |
- M |
- 82 |
- 8.8 |
-
-
- | 16 |
- 620 |
- BXD92 (BXD65b) |
- F |
- 82 |
- 8.8 |
-
-
- | 17 |
- 635 |
- BXD100 |
- M |
- 70 |
- 9 |
-
-
- | 18 |
- 636 |
- BXD100 |
- M |
- 70 |
- 8.8 |
-
-
- | 19 |
- 652 |
- BXD92 (BXD65b) |
- F |
- 64 |
- 9 |
-
-
- | 20 |
- 653 |
- BXD87 |
- F |
- 67 |
- 9.7 |
-
-
- | 21 |
- 654 |
- BXD87 |
- M |
- 67 |
- 8.9 |
-
-
- | 22 |
- 655 |
- BXD63 |
- M |
- 71 |
- 9 |
-
-
- | 23 |
- 660 |
- BXD69 |
- M |
- 97 |
- 10 |
-
-
- | 24 |
- 687 |
- BXD6 |
- M |
- 85 |
- 7.7 |
-
-
- | 25 |
- 688 |
- BXD6 |
- M |
- 85 |
- 9.4 |
-
-
- | 26 |
- 690 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 27 |
- 691 |
- BXD12 |
- F |
- 83 |
- 10 |
-
-
- | 28 |
- 692 |
- BXD12 |
- M |
- 83 |
- 10 |
-
-
- | 29 |
- 695 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 30 |
- 696 |
- BXD5 |
- M |
- 77 |
- 10 |
-
-
- | 31 |
- 698 |
- BXD5 |
- F |
- 77 |
- 9.9 |
-
-
- | 32 |
- 699 |
- BXD5 |
- F |
- 77 |
- 10 |
-
-
- | 33 |
- 701 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 34 |
- 702 |
- BXD8 |
- M |
- 79 |
- 10 |
-
-
- | 35 |
- 705 |
- BXD8 |
- F |
- 77 |
- 9.2 |
-
-
- | 36 |
- 707 |
- BXD15 |
- F |
- 77 |
- 9.4 |
-
-
- | 37 |
- 708 |
- BXD15 |
- F |
- 77 |
- 9.1 |
-
-
- | 38 |
- 710 |
- BXD15 |
- M |
- 77 |
- 9.1 |
-
-
- | 39 |
- 713 |
- BXD22 |
- F |
- 71 |
- 9.5 |
-
-
- | 40 |
- 714 |
- BXD22 |
- F |
- 71 |
- 9.7 |
-
-
- | 41 |
- 716 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 42 |
- 717 |
- BXD22 |
- M |
- 71 |
- 9.1 |
-
-
- | 43 |
- 719 |
- BXD14 |
- F |
- 70 |
- 9.2 |
-
-
- | 44 |
- 722 |
- BXD14 |
- M |
- 70 |
- 8.9 |
-
-
- | 45 |
- 723 |
- BXD14 |
- M |
- 70 |
- 9.2 |
-
-
- | 46 |
- 725 |
- BXD18 |
- F |
- 70 |
- 9 |
-
-
- | 47 |
- 726 |
- BXD18 |
- F |
- 70 |
- 9.1 |
-
-
- | 48 |
- 728 |
- BXD18 |
- M |
- 70 |
- 9.1 |
-
-
- | 49 |
- 729 |
- BXD18 |
- M |
- 70 |
- 9.2 |
-
-
- | 50 |
- 731 |
- BXD19 |
- F |
- 66 |
- 9.3 |
-
-
- | 51 |
- 732 |
- BXD19 |
- F |
- 66 |
- 9.4 |
-
-
- | 52 |
- 734 |
- BXD19 |
- M |
- 66 |
- 9.8 |
-
-
- | 53 |
- 735 |
- BXD19 |
- M |
- 66 |
- 9.4 |
-
-
- | 54 |
- 737 |
- BXD21 |
- F |
- 71 |
- 9.7 |
-
-
- | 55 |
- 738 |
- BXD21 |
- F |
- 71 |
- 9.6 |
-
-
- | 56 |
- 740 |
- BXD21 |
- M |
- 71 |
- 9.1 |
-
-
- | 57 |
- 741 |
- BXD21 |
- M |
- 71 |
- 9.7 |
-
-
- | 58 |
- 743 |
- BXD2 |
- F |
- 70 |
- 8.3 |
-
-
- | 59 |
- 744 |
- BXD2 |
- F |
- 70 |
- 8.6 |
-
-
- | 60 |
- 746 |
- BXD2 |
- M |
- 70 |
- 7.5 |
-
-
- | 61 |
- 747 |
- BXD2 |
- M |
- 77 |
- 8.6 |
-
-
- | 62 |
- 768 |
- BXD48 |
- M |
- 121 |
- 9.4 |
-
-
- | 63 |
- 770 |
- BXD92 (BXD65b) |
- M |
- 65 |
- 10 |
-
-
- | 64 |
- 771 |
- BXD101 |
- F |
- 85 |
- 8.3 |
-
-
- | 65 |
- 772 |
- BXD101 |
- F |
- 85 |
- 9.3 |
-
-
- | 66 |
- 773 |
- BXD101 |
- M |
- 86 |
- 9.5 |
-
-
- | 67 |
- 774 |
- BXD101 |
- M |
- 86 |
- 9.8 |
-
-
- | 68 |
- 775 |
- BXD102 |
- F |
- 66 |
- 9.5 |
-
-
- | 69 |
- 776 |
- BXD102 |
- F |
- 66 |
- 10 |
-
-
- | 70 |
- 777 |
- BXD102 |
- M |
- 84 |
- 9.6 |
-
-
- | 71 |
- 787 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 72 |
- 788 |
- BXD60 |
- M |
- 86 |
- 9.9 |
-
-
- | 73 |
- 789 |
- BXD63 |
- F |
- 115 |
- 9.7 |
-
-
- | 74 |
- 790 |
- BXD100 |
- F |
- 72 |
- 9.8 |
-
-
- | 75 |
- 791 |
- BXD100 |
- F |
- 72 |
- 10 |
-
-
- | 76 |
- 818 |
- BXD51 |
- F |
- 77 |
- 9.7 |
-
-
- | 77 |
- 819 |
- BXD51 |
- F |
- 77 |
- 9.6 |
-
-
- | 78 |
- 820 |
- BXD51 |
- M |
- 72 |
- 9.7 |
-
-
- | 79 |
- 821 |
- BXD65 |
- M |
- 72 |
- 9.6 |
-
-
- | 80 |
- 822 |
- BXD65 |
- M |
- 65 |
- 9.5 |
-
-
- | 81 |
- 825 |
- BXD65 |
- F |
- 72 |
- 9.5 |
-
-
- | 82 |
- 827 |
- BXD86 |
- M |
- 69 |
- 9.1 |
-
-
- | 83 |
- 828 |
- BXD86 |
- M |
- 69 |
- 9.4 |
-
-
- | 84 |
- 829 |
- BXD90 |
- F |
- 69 |
- 9.6 |
-
-
- | 85 |
- 831 |
- BXD9 |
- M |
- 127 |
- 9.7 |
-
-
- | 86 |
- 832 |
- BXD39 |
- F |
- 99 |
- 9.4 |
-
-
- | 87 |
- 833 |
- BXD39 |
- F |
- 107 |
- 9.3 |
-
-
- | 88 |
- 834 |
- BXD60 |
- F |
- 107 |
- 9.5 |
-
-
- | 89 |
- 836 |
- BXD84 |
- M |
- 103 |
- 9.7 |
-
-
- | 90 |
- 846 |
- BXD39 |
- M |
- 63 |
- 9.7 |
-
-
- | 91 |
- 847 |
- BXD39 |
- M |
- 63 |
- 9.8 |
-
-
- | 92 |
- 849 |
- BXD20 |
- F |
- 70 |
- 10 |
-
-
- | 93 |
- 850 |
- BXD20 |
- M |
- 70 |
- 10 |
-
-
- | 94 |
- 851 |
- BXD20 |
- * |
- 70 |
- 9.5 |
-
-
- | 95 |
- 855 |
- DBA/2J |
- F |
- 78 |
- 9.7 |
-
-
- | 96 |
- 856 |
- DBA/2J |
- F |
- 78 |
- 10 |
-
-
- | 97 |
- 857 |
- DBA/2J |
- M |
- 78 |
- 10 |
-
-
- | 98 |
- 858 |
- DBA/2J |
- M |
- 78 |
- 9.9 |
-
-
- | 99 |
- 859 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 100 |
- 860 |
- C57BL/6J |
- F |
- 78 |
- 10 |
-
-
- | 101 |
- 861 |
- C57BL/6J |
- M |
- 78 |
- 10 |
-
-
- | 102 |
- 862 |
- C57BL/6J |
- M |
- 78 |
- 9.6 |
-
-
- | 103 |
- EGE10907-0172_890_20844 |
- BXD28 |
- M |
- 75 |
- 10 |
-
-
- | 104 |
- EGE10907-0173_891_20845 |
- BXD28 |
- M |
- 75 |
- 9.7 |
-
-
- | 105 |
- EGE10907-0174_892_20846 |
- BXD28 |
- F |
- 75 |
- 9.7 |
-
-
- | 106 |
- EGE10907-0176_895_20848 |
- BXD33 |
- M |
- 75 |
- 9.88 |
-
-
- | 107 |
- EGE10907-0177_896_20849 |
- BXD33 |
- F |
- 75 |
- 10 |
-
-
- | 108 |
- EGE10907-0178_897_20850 |
- BXD33 |
- F |
- 75 |
- 9.4 |
-
-
- | 109 |
- EGE10907-0179_898_20851 |
- BXD36 |
- M |
- 75 |
- 9.4 |
-
-
- | 110 |
- EGE10907-0180_899_20852 |
- BXD36 |
- F |
- 75 |
- 9.5 |
-
-
- | 111 |
- EGE10907-0181_900_20853 |
- BXD36 |
- F |
- 75 |
- 9.1 |
-
-
- | 112 |
- EGE10907-0182_910_20854 |
- BXD27 |
- M |
- 70 |
- 9.7 |
-
-
- | 113 |
- EGE10907-0183_990_20855 |
- BXD9 |
- F |
- 98 |
- 9.4 |
-
-
- | 114 |
- EGE10907-0184_991_20856 |
- BXD16 |
- F |
- 113 |
- 10 |
-
-
- | 115 |
- EGE10907-0185_992_20857 |
- BXD16 |
- M |
- 113 |
- 9 |
-
-
- | 116 |
- EGE10907-0186_993_20858 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 117 |
- EGE10907-0187_994_20859 |
- BXD27 |
- F |
- 96 |
- 9.4 |
-
-
- | 118 |
- EGE10907-0188_996_20860 |
- BXD48 |
- F |
- 98 |
- 9.4 |
-
-
- | 119 |
- EGE10907-0189_997_20861 |
- BXD73 |
- M |
- 106 |
- 10 |
-
-
- | 120 |
- EGE10907-0190_999_20862 |
- BXD11 |
- F |
- 121 |
- 9.6 |
-
-
- | 121 |
- EGE10907-0191_100_20863 |
- BXD11 |
- F |
- 121 |
- 9.9 |
-
-
- | 122 |
- EGE10907-0192_1010_21276 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 123 |
- EGE10907-0193_1011_21277 |
- BXD13 |
- M |
- 69 |
- 9.8 |
-
-
- | 124 |
- EGE10907-0194_1012_21278 |
- BXD16 |
- F |
- 65 |
- 10 |
-
-
- | 125 |
- EGE10907-0195_1015_21279 |
- BXD16 |
- M |
- 65 |
- 10 |
-
-
- | 126 |
- EGE10907-0196_1019_21280 |
- BXD33 |
- M |
- 75 |
- 10 |
-
-
- | 127 |
- EGE10907-0197_1020_21281 |
- BXD36 |
- M |
- 78 |
- 10 |
-
-
- | 128 |
- EGE10907-0198_1021_21282 |
- BXD38 |
- F |
- 70 |
- 9.8 |
-
-
- | 129 |
- EGE10907-0199_1022_21283 |
- BXD38 |
- F |
- 70 |
- 10 |
-
-
- | 130 |
- EGE10907-0200_1023_21284 |
- BXD38 |
- M |
- 70 |
- 9.7 |
-
-
- | 131 |
- EGE10907-0201_1047_21285 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 132 |
- EGE10907-0202_1048_21286 |
- BXD11 |
- M |
- 65 |
- 10 |
-
-
- | 133 |
- EGE10907-0203_1049_21287 |
- BXD38 |
- M |
- 77 |
- 10 |
-
-
- | 134 |
- EGE10907-0204_1050_21288 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 135 |
- EGE10907-0205_1051_21289 |
- BXD73 |
- F |
- 70 |
- 10 |
-
-
- | 136 |
- EGE10907-0206_1052_21290 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 137 |
- EGE10907-0207_1053_21291 |
- BXD86 |
- F |
- 69 |
- 10 |
-
-
- | 138 |
- EGE10907-0208_1054_21292 |
- BXD90 |
- F |
- 71 |
- 10 |
-
-
- | 139 |
- EGE10907-0209_1055_21293 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 140 |
- EGE10907-0210_1056_21294 |
- BXD90 |
- M |
- 71 |
- 10 |
-
-
- | 141 |
- EGE10907-0211_1148_21295 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 142 |
- EGE10907-0212_1149_21296 |
- BXD31 |
- F |
- 90 |
- 10 |
-
-
- | 143 |
- EGE10907-0213_1150_21297 |
- BXD31 |
- M |
- 90 |
- 10 |
-
-
- | 144 |
- EGE10907-0214_1151_21298 |
- BXD31 |
- M |
- 90 |
- 9.9 |
-
-
- | 145 |
- EGE10907-0215_1152_21299 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 146 |
- EGE10907-0216_21429 |
- BXD42 |
- F |
- 83 |
- 10 |
-
-
- | 147 |
- EGE10907-0217_21430 |
- BXD42 |
- M |
- 83 |
- 10 |
-
-
- | 148 |
- EGE10907-0218_21431 |
- BXD42 |
- M |
- 83 |
- 9.3 |
-
-
- | 149 |
- EGE10907-0219_21432 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 150 |
- EGE10907-0220_21433 |
- BXD50 |
- F |
- 92 |
- 9.6 |
-
-
- | 151 |
- EGE10907-0221_21434 |
- BXD50 |
- F |
- 92 |
- 10 |
-
-
- | 152 |
- EGE10907-0222_21435 |
- BXD1 |
- M |
- 73 |
- 9.6 |
-
-
- | 153 |
- EGE10907-0223_21436 |
- BXD13 |
- F |
- 71 |
- 9.7 |
-
-
- | 154 |
- EGE10907-0224_21437 |
- BXD1 |
- M |
- 71 |
- 9.5 |
-
-
- | 155 |
- EGE10907-0225_21438 |
- BXD13 |
- F |
- 71 |
- 9.6 |
-
-
- | 156 |
- EGE10907-0226_21439 |
- BXD43 |
- F |
- 85 |
- 10 |
-
-
- | 157 |
- EGE10907-0227_21452 |
- BXD43 |
- F |
- 85 |
- 9.6 |
-
-
- | 158 |
- EGE10907-0229_21442 |
- BXD43 |
- M |
- 85 |
- 8.2 |
-
-
- | 159 |
- EGE10907-0230_21443 |
- BXD50 |
- M |
- 69 |
- 9.4 |
-
-
- | 160 |
- EGE10907-0231_21444 |
- BXD1 |
- F |
- 68 |
- 9.4 |
-
-
- | 161 |
- EGE10907-0232_21445 |
- BXD1 |
- F |
- 68 |
- 9.6 |
-
-
- | 162 |
- EGE10907-0233_21446 |
- BXD29 |
- M |
- 65 |
- 9.5 |
-
-
- | 163 |
- EGE10907-0234_21447 |
- BXD29 |
- M |
- 65 |
- 10 |
-
-
- | 164 |
- EGE10907-0235_21448 |
- BXD75 |
- F |
- 68 |
- 10 |
-
-
- | 165 |
- EGE10907-0236_21449 |
- BXD75 |
- M |
- 68 |
- 10 |
-
-
- | 166 |
- EGE10907-0237_21450 |
- BXD96 |
- F |
- 67 |
- 9.9 |
-
-
- | 167 |
- EGE10907-0238_21931 |
- BXD99 |
- M |
- 71 |
- 7.9 |
-
-
- | 168 |
- EGE10907-0239_21932 |
- BXD99 |
- M |
- 71 |
- 9.7 |
-
-
- | 169 |
- EGE10907-0240_21933 |
- BXD67 |
- F |
- 68 |
- 8.8 |
-
-
- | 170 |
- EGE10907-0241_21934 |
- BXD67 |
- F |
- 68 |
- 8.5 |
-
-
- | 171 |
- EGE10907-0242_21935 |
- BXD67 |
- M |
- 68 |
- 9.5 |
-
-
- | 172 |
- EGE10907-0243_21936 |
- BXD67 |
- M |
- 68 |
- 9.6 |
-
-
- | 173 |
- EGE10907-0244_21937 |
- BXD6 |
- F |
- 68 |
- 9.6 |
-
-
- | 174 |
- EGE10907-0245_21938 |
- BXD12 |
- M |
- 82 |
- 9.5 |
-
-
- | 175 |
- EGE10907-0246_21939 |
- BXD60 |
- F |
- 72 |
- 9.6 |
-
-
- | 176 |
- EGE10907-0247_21940 |
- BXD65 |
- F |
- 75 |
- 9.1 |
-
-
- | 177 |
- EGE10907-0248_21941 |
- BXD75 |
- F |
- 69 |
- 8.8 |
-
-
- | 178 |
- EGE10907-0249_21942_(MoGene-2_0-st) |
- BXD75 |
- M |
- 69 |
- 9.2 |
-
-
- | 179 |
- EGE10907-0250_21943 |
- BXD8 |
- F |
- 97 |
- 9.1 |
-
-
- | 180 |
- EGE10907-0251_21944 |
- BXD85 |
- F |
- 79 |
- 8.6 |
-
-
- | 181 |
- EGE10907-0252_21945 |
- BXD85 |
- M |
- 79 |
- 9.1 |
-
-
- | 182 |
- EGE10907-0253_21946 |
- BXD85 |
- M |
- 79 |
- 9.4 |
-
-
- | 183 |
- EGE10907-0254_21947 |
- BXD102 |
- M |
- 94 |
- 8.6 |
-
-
- | 184 |
- EGE10907-0255_21948 |
- BXD99 |
- F |
- 83 |
- 9 |
-
-
- | 185 |
- EGE10907-0256_21949 |
- BXD69 |
- F |
- 68 |
- 9 |
-
-
- | 186 |
- EGE10907-0257_21950 |
- BXD84 |
- F |
- 74 |
- 9.5 |
-
-
- | 187 |
- EGE10907-0258_21951 |
- BXD84 |
- F |
- 74 |
- 9.4 |
-
-
- | 188 |
- EGE10907-0259_21952 |
- BXD84 |
- M |
- 74 |
- 8.6 |
-
-
- | 189 |
- EGE10907-0260_21451 |
- BXD96 |
- M |
- 67 |
- 9.2 |
-
-
- | 190 |
- EGE10907-0261_21452 |
- BXD99 |
- F |
- 71 |
- 8.9 |
-
-
- | 191 |
- EGE10907-0262_21931 |
- BXD6 |
- F |
- 66 |
- 9.4 |
-
-
- | 192 |
- EGE10907-0263_21932 |
- BXD14 |
- F |
- 69 |
- 8.5 |
-
-
- | 193 |
- EGE10907-0264_21933 |
- BXD34 |
- M |
- 79 |
- 9.1 |
-
-
- | 194 |
- EGE10907-0265_21934 |
- BXD34 |
- M |
- 79 |
- 9.9 |
-
-
- | 195 |
- EGE10907-0266_21935 |
- BXD40 |
- F |
- 75 |
- 9.6 |
-
-
- | 196 |
- EGE10907-0267_21936 |
- BXD40 |
- M |
- 78 |
- 9.7 |
-
-
- | 197 |
- EGE10907-0268_21937 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 198 |
- EGE10907-0269_21938 |
- BXD56 |
- F |
- 72 |
- 9.7 |
-
-
- | 199 |
- EGE10907-0270_21939 |
- BXD56 |
- M |
- 72 |
- 9.6 |
-
-
- | 200 |
- EGE10907-0271_21940 |
- BXD56 |
- M |
- 72 |
- 9.4 |
-
-
- | 201 |
- EGE10907-0272_21941 |
- BXD71 |
- F |
- 72 |
- 9.9 |
-
-
- | 202 |
- EGE10907-0273_21942 |
- BXD71 |
- F |
- 75 |
- 9.4 |
-
-
- | 203 |
- EGE10907-0274_21943 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 204 |
- EGE10907-0275_21944 |
- BXD71 |
- M |
- 75 |
- 10 |
-
-
- | 205 |
- EGE10907-0276_21945 |
- BXD27 |
- M |
- 65 |
- 10 |
-
-
- | 206 |
- EGE10907-0277_21946 |
- BXD15 |
- M |
- 65 |
- 10 |
-
-
- | 207 |
- EGE10907-0278_21947 |
- BXD20 |
- F |
- 125 |
- 10 |
-
-
- | 208 |
- EGE10907-0279_21948 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 209 |
- EGE10907-0280_21949 |
- BXD29 |
- F |
- 77 |
- 10 |
-
-
- | 210 |
- EGE10907-0281_21950 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 211 |
- EGE10907-0282_21951 |
- BXD34 |
- F |
- 74 |
- 10 |
-
-
- | 212 |
- EGE10907-0283_21952 |
- BXD85 |
- F |
- 87 |
- 10 |
-
-
- | 213 |
- EGE10907-0284_21451 |
- BXD43 |
- M |
- 75 |
- 9.8 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/ONCRetMoGene2_0413/platform.rtf b/general/datasets/ONCRetMoGene2_0413/platform.rtf
deleted file mode 100644
index 19fc38c..0000000
--- a/general/datasets/ONCRetMoGene2_0413/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/ONCRetMoGene2_0413/processing.rtf b/general/datasets/ONCRetMoGene2_0413/processing.rtf
deleted file mode 100644
index a7b767e..0000000
--- a/general/datasets/ONCRetMoGene2_0413/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/ONCRetMoGene2_0413/summary.rtf b/general/datasets/ONCRetMoGene2_0413/summary.rtf
deleted file mode 100644
index 96a87e5..0000000
--- a/general/datasets/ONCRetMoGene2_0413/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/ONCRetMoGene2_0413/tissue.rtf b/general/datasets/ONCRetMoGene2_0413/tissue.rtf
deleted file mode 100644
index 056d7eb..0000000
--- a/general/datasets/ONCRetMoGene2_0413/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/Ohsu_hs_cc_ilmstr_0211/summary.rtf b/general/datasets/Ohsu_hs_cc_ilmstr_0211/summary.rtf
new file mode 100644
index 0000000..e096b10
--- /dev/null
+++ b/general/datasets/Ohsu_hs_cc_ilmstr_0211/summary.rtf
@@ -0,0 +1,2 @@
+The current study focused on the extent genetic diversity within a species (Mus musculus) affects gene co-expression network structure. To examine this issue, we have created a new mouse resource, a heterogeneous stock (HS) formed from the same eight inbred strains that have been used to create the collaborative cross (CC). The eight inbred strains capture > 90% of the genetic diversity available within the species. For contrast with the HS-CC, a C57BL/6J (B6) × DBA/2J (D2) F2 intercross and the HS4, derived from crossing the B6, D2, BALB/cJ and LP/J strains, were used. Brain (striatum) gene expression data were obtained using the Illumina Mouse WG 6.1 array, and the data sets were interrogated using a weighted gene co-expression network analysis (WGCNA).
+Read full article: Genetic diversity and striatal gene networks: focus on the heterogeneous stock-collaborative cross (HS-CC) mouse.
diff --git a/general/datasets/Oncretexmogene2_0413/acknowledgment.rtf b/general/datasets/Oncretexmogene2_0413/acknowledgment.rtf
new file mode 100644
index 0000000..13c6b1e
--- /dev/null
+++ b/general/datasets/Oncretexmogene2_0413/acknowledgment.rtf
@@ -0,0 +1 @@
+DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/Oncretexmogene2_0413/cases.rtf b/general/datasets/Oncretexmogene2_0413/cases.rtf
new file mode 100644
index 0000000..6b36c70
--- /dev/null
+++ b/general/datasets/Oncretexmogene2_0413/cases.rtf
@@ -0,0 +1,1728 @@
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+
+
+
+
+
+ | Index |
+ EIGC ID (LIMS ID) |
+ Strain |
+ Sex |
+ Age at harvest |
+ RIN Score |
+
+
+ | 1 |
+ 602 |
+ BXD9 |
+ F |
+ 133 |
+ 9.1 |
+
+
+ | 2 |
+ 603 |
+ BXD9 |
+ M |
+ 100 |
+ 9.5 |
+
+
+ | 3 |
+ 604 |
+ BXD40 |
+ F |
+ 100 |
+ 9.4 |
+
+
+ | 4 |
+ 605 |
+ BXD40 |
+ M |
+ 100 |
+ 9.1 |
+
+
+ | 5 |
+ 606 |
+ BXD48 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 6 |
+ 607 |
+ BXD48 |
+ M |
+ 75 |
+ 8.6 |
+
+
+ | 7 |
+ 608 |
+ BXD63 |
+ F |
+ 75 |
+ 9.2 |
+
+
+ | 8 |
+ 609 |
+ BXD63 |
+ M |
+ 61 |
+ 9.4 |
+
+
+ | 9 |
+ 612 |
+ BXD73 |
+ M |
+ 108 |
+ 10 |
+
+
+ | 10 |
+ 614 |
+ BXD87 |
+ M |
+ 85 |
+ 9.2 |
+
+
+ | 11 |
+ 615 |
+ BXD87 |
+ F |
+ 85 |
+ 9.9 |
+
+
+ | 12 |
+ 616 |
+ BXD69 |
+ F |
+ 76 |
+ 9.3 |
+
+
+ | 13 |
+ 617 |
+ BXD69 |
+ M |
+ 100 |
+ 10 |
+
+
+ | 14 |
+ 618 |
+ BXD51 |
+ M |
+ 82 |
+ 8.9 |
+
+
+ | 15 |
+ 619 |
+ BXD92 (BXD65b) |
+ M |
+ 82 |
+ 8.8 |
+
+
+ | 16 |
+ 620 |
+ BXD92 (BXD65b) |
+ F |
+ 82 |
+ 8.8 |
+
+
+ | 17 |
+ 635 |
+ BXD100 |
+ M |
+ 70 |
+ 9 |
+
+
+ | 18 |
+ 636 |
+ BXD100 |
+ M |
+ 70 |
+ 8.8 |
+
+
+ | 19 |
+ 652 |
+ BXD92 (BXD65b) |
+ F |
+ 64 |
+ 9 |
+
+
+ | 20 |
+ 653 |
+ BXD87 |
+ F |
+ 67 |
+ 9.7 |
+
+
+ | 21 |
+ 654 |
+ BXD87 |
+ M |
+ 67 |
+ 8.9 |
+
+
+ | 22 |
+ 655 |
+ BXD63 |
+ M |
+ 71 |
+ 9 |
+
+
+ | 23 |
+ 660 |
+ BXD69 |
+ M |
+ 97 |
+ 10 |
+
+
+ | 24 |
+ 687 |
+ BXD6 |
+ M |
+ 85 |
+ 7.7 |
+
+
+ | 25 |
+ 688 |
+ BXD6 |
+ M |
+ 85 |
+ 9.4 |
+
+
+ | 26 |
+ 690 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 27 |
+ 691 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 28 |
+ 692 |
+ BXD12 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 29 |
+ 695 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 30 |
+ 696 |
+ BXD5 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 31 |
+ 698 |
+ BXD5 |
+ F |
+ 77 |
+ 9.9 |
+
+
+ | 32 |
+ 699 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 33 |
+ 701 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 34 |
+ 702 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 35 |
+ 705 |
+ BXD8 |
+ F |
+ 77 |
+ 9.2 |
+
+
+ | 36 |
+ 707 |
+ BXD15 |
+ F |
+ 77 |
+ 9.4 |
+
+
+ | 37 |
+ 708 |
+ BXD15 |
+ F |
+ 77 |
+ 9.1 |
+
+
+ | 38 |
+ 710 |
+ BXD15 |
+ M |
+ 77 |
+ 9.1 |
+
+
+ | 39 |
+ 713 |
+ BXD22 |
+ F |
+ 71 |
+ 9.5 |
+
+
+ | 40 |
+ 714 |
+ BXD22 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 41 |
+ 716 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 42 |
+ 717 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 43 |
+ 719 |
+ BXD14 |
+ F |
+ 70 |
+ 9.2 |
+
+
+ | 44 |
+ 722 |
+ BXD14 |
+ M |
+ 70 |
+ 8.9 |
+
+
+ | 45 |
+ 723 |
+ BXD14 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 46 |
+ 725 |
+ BXD18 |
+ F |
+ 70 |
+ 9 |
+
+
+ | 47 |
+ 726 |
+ BXD18 |
+ F |
+ 70 |
+ 9.1 |
+
+
+ | 48 |
+ 728 |
+ BXD18 |
+ M |
+ 70 |
+ 9.1 |
+
+
+ | 49 |
+ 729 |
+ BXD18 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 50 |
+ 731 |
+ BXD19 |
+ F |
+ 66 |
+ 9.3 |
+
+
+ | 51 |
+ 732 |
+ BXD19 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 52 |
+ 734 |
+ BXD19 |
+ M |
+ 66 |
+ 9.8 |
+
+
+ | 53 |
+ 735 |
+ BXD19 |
+ M |
+ 66 |
+ 9.4 |
+
+
+ | 54 |
+ 737 |
+ BXD21 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 55 |
+ 738 |
+ BXD21 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 56 |
+ 740 |
+ BXD21 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 57 |
+ 741 |
+ BXD21 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 58 |
+ 743 |
+ BXD2 |
+ F |
+ 70 |
+ 8.3 |
+
+
+ | 59 |
+ 744 |
+ BXD2 |
+ F |
+ 70 |
+ 8.6 |
+
+
+ | 60 |
+ 746 |
+ BXD2 |
+ M |
+ 70 |
+ 7.5 |
+
+
+ | 61 |
+ 747 |
+ BXD2 |
+ M |
+ 77 |
+ 8.6 |
+
+
+ | 62 |
+ 768 |
+ BXD48 |
+ M |
+ 121 |
+ 9.4 |
+
+
+ | 63 |
+ 770 |
+ BXD92 (BXD65b) |
+ M |
+ 65 |
+ 10 |
+
+
+ | 64 |
+ 771 |
+ BXD101 |
+ F |
+ 85 |
+ 8.3 |
+
+
+ | 65 |
+ 772 |
+ BXD101 |
+ F |
+ 85 |
+ 9.3 |
+
+
+ | 66 |
+ 773 |
+ BXD101 |
+ M |
+ 86 |
+ 9.5 |
+
+
+ | 67 |
+ 774 |
+ BXD101 |
+ M |
+ 86 |
+ 9.8 |
+
+
+ | 68 |
+ 775 |
+ BXD102 |
+ F |
+ 66 |
+ 9.5 |
+
+
+ | 69 |
+ 776 |
+ BXD102 |
+ F |
+ 66 |
+ 10 |
+
+
+ | 70 |
+ 777 |
+ BXD102 |
+ M |
+ 84 |
+ 9.6 |
+
+
+ | 71 |
+ 787 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 72 |
+ 788 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 73 |
+ 789 |
+ BXD63 |
+ F |
+ 115 |
+ 9.7 |
+
+
+ | 74 |
+ 790 |
+ BXD100 |
+ F |
+ 72 |
+ 9.8 |
+
+
+ | 75 |
+ 791 |
+ BXD100 |
+ F |
+ 72 |
+ 10 |
+
+
+ | 76 |
+ 818 |
+ BXD51 |
+ F |
+ 77 |
+ 9.7 |
+
+
+ | 77 |
+ 819 |
+ BXD51 |
+ F |
+ 77 |
+ 9.6 |
+
+
+ | 78 |
+ 820 |
+ BXD51 |
+ M |
+ 72 |
+ 9.7 |
+
+
+ | 79 |
+ 821 |
+ BXD65 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 80 |
+ 822 |
+ BXD65 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 81 |
+ 825 |
+ BXD65 |
+ F |
+ 72 |
+ 9.5 |
+
+
+ | 82 |
+ 827 |
+ BXD86 |
+ M |
+ 69 |
+ 9.1 |
+
+
+ | 83 |
+ 828 |
+ BXD86 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 84 |
+ 829 |
+ BXD90 |
+ F |
+ 69 |
+ 9.6 |
+
+
+ | 85 |
+ 831 |
+ BXD9 |
+ M |
+ 127 |
+ 9.7 |
+
+
+ | 86 |
+ 832 |
+ BXD39 |
+ F |
+ 99 |
+ 9.4 |
+
+
+ | 87 |
+ 833 |
+ BXD39 |
+ F |
+ 107 |
+ 9.3 |
+
+
+ | 88 |
+ 834 |
+ BXD60 |
+ F |
+ 107 |
+ 9.5 |
+
+
+ | 89 |
+ 836 |
+ BXD84 |
+ M |
+ 103 |
+ 9.7 |
+
+
+ | 90 |
+ 846 |
+ BXD39 |
+ M |
+ 63 |
+ 9.7 |
+
+
+ | 91 |
+ 847 |
+ BXD39 |
+ M |
+ 63 |
+ 9.8 |
+
+
+ | 92 |
+ 849 |
+ BXD20 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 93 |
+ 850 |
+ BXD20 |
+ M |
+ 70 |
+ 10 |
+
+
+ | 94 |
+ 851 |
+ BXD20 |
+ * |
+ 70 |
+ 9.5 |
+
+
+ | 95 |
+ 855 |
+ DBA/2J |
+ F |
+ 78 |
+ 9.7 |
+
+
+ | 96 |
+ 856 |
+ DBA/2J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 97 |
+ 857 |
+ DBA/2J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 98 |
+ 858 |
+ DBA/2J |
+ M |
+ 78 |
+ 9.9 |
+
+
+ | 99 |
+ 859 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 100 |
+ 860 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 101 |
+ 861 |
+ C57BL/6J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 102 |
+ 862 |
+ C57BL/6J |
+ M |
+ 78 |
+ 9.6 |
+
+
+ | 103 |
+ EGE10907-0172_890_20844 |
+ BXD28 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 104 |
+ EGE10907-0173_891_20845 |
+ BXD28 |
+ M |
+ 75 |
+ 9.7 |
+
+
+ | 105 |
+ EGE10907-0174_892_20846 |
+ BXD28 |
+ F |
+ 75 |
+ 9.7 |
+
+
+ | 106 |
+ EGE10907-0176_895_20848 |
+ BXD33 |
+ M |
+ 75 |
+ 9.88 |
+
+
+ | 107 |
+ EGE10907-0177_896_20849 |
+ BXD33 |
+ F |
+ 75 |
+ 10 |
+
+
+ | 108 |
+ EGE10907-0178_897_20850 |
+ BXD33 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 109 |
+ EGE10907-0179_898_20851 |
+ BXD36 |
+ M |
+ 75 |
+ 9.4 |
+
+
+ | 110 |
+ EGE10907-0180_899_20852 |
+ BXD36 |
+ F |
+ 75 |
+ 9.5 |
+
+
+ | 111 |
+ EGE10907-0181_900_20853 |
+ BXD36 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 112 |
+ EGE10907-0182_910_20854 |
+ BXD27 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 113 |
+ EGE10907-0183_990_20855 |
+ BXD9 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 114 |
+ EGE10907-0184_991_20856 |
+ BXD16 |
+ F |
+ 113 |
+ 10 |
+
+
+ | 115 |
+ EGE10907-0185_992_20857 |
+ BXD16 |
+ M |
+ 113 |
+ 9 |
+
+
+ | 116 |
+ EGE10907-0186_993_20858 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 117 |
+ EGE10907-0187_994_20859 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 118 |
+ EGE10907-0188_996_20860 |
+ BXD48 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 119 |
+ EGE10907-0189_997_20861 |
+ BXD73 |
+ M |
+ 106 |
+ 10 |
+
+
+ | 120 |
+ EGE10907-0190_999_20862 |
+ BXD11 |
+ F |
+ 121 |
+ 9.6 |
+
+
+ | 121 |
+ EGE10907-0191_100_20863 |
+ BXD11 |
+ F |
+ 121 |
+ 9.9 |
+
+
+ | 122 |
+ EGE10907-0192_1010_21276 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 123 |
+ EGE10907-0193_1011_21277 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 124 |
+ EGE10907-0194_1012_21278 |
+ BXD16 |
+ F |
+ 65 |
+ 10 |
+
+
+ | 125 |
+ EGE10907-0195_1015_21279 |
+ BXD16 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 126 |
+ EGE10907-0196_1019_21280 |
+ BXD33 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 127 |
+ EGE10907-0197_1020_21281 |
+ BXD36 |
+ M |
+ 78 |
+ 10 |
+
+
+ | 128 |
+ EGE10907-0198_1021_21282 |
+ BXD38 |
+ F |
+ 70 |
+ 9.8 |
+
+
+ | 129 |
+ EGE10907-0199_1022_21283 |
+ BXD38 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 130 |
+ EGE10907-0200_1023_21284 |
+ BXD38 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 131 |
+ EGE10907-0201_1047_21285 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 132 |
+ EGE10907-0202_1048_21286 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 133 |
+ EGE10907-0203_1049_21287 |
+ BXD38 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 134 |
+ EGE10907-0204_1050_21288 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 135 |
+ EGE10907-0205_1051_21289 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 136 |
+ EGE10907-0206_1052_21290 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 137 |
+ EGE10907-0207_1053_21291 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 138 |
+ EGE10907-0208_1054_21292 |
+ BXD90 |
+ F |
+ 71 |
+ 10 |
+
+
+ | 139 |
+ EGE10907-0209_1055_21293 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 140 |
+ EGE10907-0210_1056_21294 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 141 |
+ EGE10907-0211_1148_21295 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 142 |
+ EGE10907-0212_1149_21296 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 143 |
+ EGE10907-0213_1150_21297 |
+ BXD31 |
+ M |
+ 90 |
+ 10 |
+
+
+ | 144 |
+ EGE10907-0214_1151_21298 |
+ BXD31 |
+ M |
+ 90 |
+ 9.9 |
+
+
+ | 145 |
+ EGE10907-0215_1152_21299 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 146 |
+ EGE10907-0216_21429 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 147 |
+ EGE10907-0217_21430 |
+ BXD42 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 148 |
+ EGE10907-0218_21431 |
+ BXD42 |
+ M |
+ 83 |
+ 9.3 |
+
+
+ | 149 |
+ EGE10907-0219_21432 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 150 |
+ EGE10907-0220_21433 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 151 |
+ EGE10907-0221_21434 |
+ BXD50 |
+ F |
+ 92 |
+ 10 |
+
+
+ | 152 |
+ EGE10907-0222_21435 |
+ BXD1 |
+ M |
+ 73 |
+ 9.6 |
+
+
+ | 153 |
+ EGE10907-0223_21436 |
+ BXD13 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 154 |
+ EGE10907-0224_21437 |
+ BXD1 |
+ M |
+ 71 |
+ 9.5 |
+
+
+ | 155 |
+ EGE10907-0225_21438 |
+ BXD13 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 156 |
+ EGE10907-0226_21439 |
+ BXD43 |
+ F |
+ 85 |
+ 10 |
+
+
+ | 157 |
+ EGE10907-0227_21452 |
+ BXD43 |
+ F |
+ 85 |
+ 9.6 |
+
+
+ | 158 |
+ EGE10907-0229_21442 |
+ BXD43 |
+ M |
+ 85 |
+ 8.2 |
+
+
+ | 159 |
+ EGE10907-0230_21443 |
+ BXD50 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 160 |
+ EGE10907-0231_21444 |
+ BXD1 |
+ F |
+ 68 |
+ 9.4 |
+
+
+ | 161 |
+ EGE10907-0232_21445 |
+ BXD1 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 162 |
+ EGE10907-0233_21446 |
+ BXD29 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 163 |
+ EGE10907-0234_21447 |
+ BXD29 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 164 |
+ EGE10907-0235_21448 |
+ BXD75 |
+ F |
+ 68 |
+ 10 |
+
+
+ | 165 |
+ EGE10907-0236_21449 |
+ BXD75 |
+ M |
+ 68 |
+ 10 |
+
+
+ | 166 |
+ EGE10907-0237_21450 |
+ BXD96 |
+ F |
+ 67 |
+ 9.9 |
+
+
+ | 167 |
+ EGE10907-0238_21931 |
+ BXD99 |
+ M |
+ 71 |
+ 7.9 |
+
+
+ | 168 |
+ EGE10907-0239_21932 |
+ BXD99 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 169 |
+ EGE10907-0240_21933 |
+ BXD67 |
+ F |
+ 68 |
+ 8.8 |
+
+
+ | 170 |
+ EGE10907-0241_21934 |
+ BXD67 |
+ F |
+ 68 |
+ 8.5 |
+
+
+ | 171 |
+ EGE10907-0242_21935 |
+ BXD67 |
+ M |
+ 68 |
+ 9.5 |
+
+
+ | 172 |
+ EGE10907-0243_21936 |
+ BXD67 |
+ M |
+ 68 |
+ 9.6 |
+
+
+ | 173 |
+ EGE10907-0244_21937 |
+ BXD6 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 174 |
+ EGE10907-0245_21938 |
+ BXD12 |
+ M |
+ 82 |
+ 9.5 |
+
+
+ | 175 |
+ EGE10907-0246_21939 |
+ BXD60 |
+ F |
+ 72 |
+ 9.6 |
+
+
+ | 176 |
+ EGE10907-0247_21940 |
+ BXD65 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 177 |
+ EGE10907-0248_21941 |
+ BXD75 |
+ F |
+ 69 |
+ 8.8 |
+
+
+ | 178 |
+ EGE10907-0249_21942_(MoGene-2_0-st) |
+ BXD75 |
+ M |
+ 69 |
+ 9.2 |
+
+
+ | 179 |
+ EGE10907-0250_21943 |
+ BXD8 |
+ F |
+ 97 |
+ 9.1 |
+
+
+ | 180 |
+ EGE10907-0251_21944 |
+ BXD85 |
+ F |
+ 79 |
+ 8.6 |
+
+
+ | 181 |
+ EGE10907-0252_21945 |
+ BXD85 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 182 |
+ EGE10907-0253_21946 |
+ BXD85 |
+ M |
+ 79 |
+ 9.4 |
+
+
+ | 183 |
+ EGE10907-0254_21947 |
+ BXD102 |
+ M |
+ 94 |
+ 8.6 |
+
+
+ | 184 |
+ EGE10907-0255_21948 |
+ BXD99 |
+ F |
+ 83 |
+ 9 |
+
+
+ | 185 |
+ EGE10907-0256_21949 |
+ BXD69 |
+ F |
+ 68 |
+ 9 |
+
+
+ | 186 |
+ EGE10907-0257_21950 |
+ BXD84 |
+ F |
+ 74 |
+ 9.5 |
+
+
+ | 187 |
+ EGE10907-0258_21951 |
+ BXD84 |
+ F |
+ 74 |
+ 9.4 |
+
+
+ | 188 |
+ EGE10907-0259_21952 |
+ BXD84 |
+ M |
+ 74 |
+ 8.6 |
+
+
+ | 189 |
+ EGE10907-0260_21451 |
+ BXD96 |
+ M |
+ 67 |
+ 9.2 |
+
+
+ | 190 |
+ EGE10907-0261_21452 |
+ BXD99 |
+ F |
+ 71 |
+ 8.9 |
+
+
+ | 191 |
+ EGE10907-0262_21931 |
+ BXD6 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 192 |
+ EGE10907-0263_21932 |
+ BXD14 |
+ F |
+ 69 |
+ 8.5 |
+
+
+ | 193 |
+ EGE10907-0264_21933 |
+ BXD34 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 194 |
+ EGE10907-0265_21934 |
+ BXD34 |
+ M |
+ 79 |
+ 9.9 |
+
+
+ | 195 |
+ EGE10907-0266_21935 |
+ BXD40 |
+ F |
+ 75 |
+ 9.6 |
+
+
+ | 196 |
+ EGE10907-0267_21936 |
+ BXD40 |
+ M |
+ 78 |
+ 9.7 |
+
+
+ | 197 |
+ EGE10907-0268_21937 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 198 |
+ EGE10907-0269_21938 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 199 |
+ EGE10907-0270_21939 |
+ BXD56 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 200 |
+ EGE10907-0271_21940 |
+ BXD56 |
+ M |
+ 72 |
+ 9.4 |
+
+
+ | 201 |
+ EGE10907-0272_21941 |
+ BXD71 |
+ F |
+ 72 |
+ 9.9 |
+
+
+ | 202 |
+ EGE10907-0273_21942 |
+ BXD71 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 203 |
+ EGE10907-0274_21943 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 204 |
+ EGE10907-0275_21944 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 205 |
+ EGE10907-0276_21945 |
+ BXD27 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 206 |
+ EGE10907-0277_21946 |
+ BXD15 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 207 |
+ EGE10907-0278_21947 |
+ BXD20 |
+ F |
+ 125 |
+ 10 |
+
+
+ | 208 |
+ EGE10907-0279_21948 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 209 |
+ EGE10907-0280_21949 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 210 |
+ EGE10907-0281_21950 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 211 |
+ EGE10907-0282_21951 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 212 |
+ EGE10907-0283_21952 |
+ BXD85 |
+ F |
+ 87 |
+ 10 |
+
+
+ | 213 |
+ EGE10907-0284_21451 |
+ BXD43 |
+ M |
+ 75 |
+ 9.8 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Oncretexmogene2_0413/citation.rtf b/general/datasets/Oncretexmogene2_0413/citation.rtf
new file mode 100644
index 0000000..d84717d
--- /dev/null
+++ b/general/datasets/Oncretexmogene2_0413/citation.rtf
@@ -0,0 +1,3 @@
+Related Publications: Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link) Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674 Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link) Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful: NEIBank collection of ESTs and SAGE data. RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases.
diff --git a/general/datasets/Oncretexmogene2_0413/contributors.rtf b/general/datasets/Oncretexmogene2_0413/contributors.rtf
new file mode 100644
index 0000000..11fece2
--- /dev/null
+++ b/general/datasets/Oncretexmogene2_0413/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, XiangDi Wang, Justin P. Templeton and Robert W. Williams.
diff --git a/general/datasets/Oncretexmogene2_0413/experiment-type.rtf b/general/datasets/Oncretexmogene2_0413/experiment-type.rtf
new file mode 100644
index 0000000..2d74654
--- /dev/null
+++ b/general/datasets/Oncretexmogene2_0413/experiment-type.rtf
@@ -0,0 +1,3 @@
+Dissecting and preparing eyes for RNA extraction
+
+RNA was extracted from retinas using the RNeasy Mini Kit (Qiagen) and the Quiagen Qiacube. For RNA amplification and cDNA preparation we used the Ambion® WT Expression Kit (Life Technologies Cat#: 4411974). For Fragmentation and Labeling the WT Terminal Labeling Kit from Affymetrix (Cat#: 900671) was used.
\ No newline at end of file
diff --git a/general/datasets/Oncretexmogene2_0413/platform.rtf b/general/datasets/Oncretexmogene2_0413/platform.rtf
new file mode 100644
index 0000000..19fc38c
--- /dev/null
+++ b/general/datasets/Oncretexmogene2_0413/platform.rtf
@@ -0,0 +1 @@
+The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/Oncretexmogene2_0413/processing.rtf b/general/datasets/Oncretexmogene2_0413/processing.rtf
new file mode 100644
index 0000000..a7b767e
--- /dev/null
+++ b/general/datasets/Oncretexmogene2_0413/processing.rtf
@@ -0,0 +1 @@
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Oncretexmogene2_0413/summary.rtf b/general/datasets/Oncretexmogene2_0413/summary.rtf
new file mode 100644
index 0000000..96a87e5
--- /dev/null
+++ b/general/datasets/Oncretexmogene2_0413/summary.rtf
@@ -0,0 +1 @@
+The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/Oncretexmogene2_0413/tissue.rtf b/general/datasets/Oncretexmogene2_0413/tissue.rtf
new file mode 100644
index 0000000..056d7eb
--- /dev/null
+++ b/general/datasets/Oncretexmogene2_0413/tissue.rtf
@@ -0,0 +1 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/Oncretilm6_0412/acknowledgment.rtf b/general/datasets/Oncretilm6_0412/acknowledgment.rtf
new file mode 100644
index 0000000..a41ff76
--- /dev/null
+++ b/general/datasets/Oncretilm6_0412/acknowledgment.rtf
@@ -0,0 +1,13 @@
+The HEI Retinal Database is supported by National Eye Institute Grants:
+
+
+
+
+ - R01EY017841 (Dr. Eldon E. Geisert, PI)
+
+
+ - P030EY13080 (NEI Vision Core Grant), and
+
+
+ - A Unrestricted Grand from Research to Prevent Blindness (Dr. Barrett Haik, PI)
+
diff --git a/general/datasets/Oncretilm6_0412/cases.rtf b/general/datasets/Oncretilm6_0412/cases.rtf
new file mode 100644
index 0000000..b37d700
--- /dev/null
+++ b/general/datasets/Oncretilm6_0412/cases.rtf
@@ -0,0 +1,14 @@
+
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 48 and maximum age is 118 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J.
+
+BXD strains:
+
+
+ - The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s.
+ - In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset.
+ - The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+What Makes the G2 HEI Retina Database different from the HEI Retina Database Examination of Gfap expression across all of the strains in the HEI Retinal Dataset, reveals that some strains express very high levels of Gfap relative to others. For example, BXD24 expresses Gfap at a 9-fold higher level, than BXD22. It has been established that BXD24 acquired a mutation in Cep290 that results in early onset photoreceptor degeneration (Chang et al., 2006). This degeneration results in reactive gliosis throughout the retina. In addition to BXD24, other BXD strains expressed very high levels of Gfap including: BXD32, BXD49, BXD70, BXD83 and BXD89. For the G2 dataset all of these strains with potential reactive gliosis were removed from the dataset.
diff --git a/general/datasets/Oncretilm6_0412/contributors.rtf b/general/datasets/Oncretilm6_0412/contributors.rtf
new file mode 100644
index 0000000..b1f321b
--- /dev/null
+++ b/general/datasets/Oncretilm6_0412/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, Natalie E. Freeman-Anderson, Justin P. Templeton, Robert W. Williams
diff --git a/general/datasets/Oncretilm6_0412/experiment-design.rtf b/general/datasets/Oncretilm6_0412/experiment-design.rtf
new file mode 100644
index 0000000..4fff707
--- /dev/null
+++ b/general/datasets/Oncretilm6_0412/experiment-design.rtf
@@ -0,0 +1,12 @@
+Expression profiling by array
+
+We used pooled RNA samples of retinas, usually two independent pools--two male, two female pool--for most lines of mice.
+
+All normalization was performed by William E. Orr in the HEI Vision Core Facility
+
+
+ - Computed the log base 2 of each raw signal value
+ - Calculated the mean and standard Deviation of each Mouse WG-6 v2.0 array
+ - Normalized each array using the formula, 2 (z-score of log2 [intensity]) The result is to produce arrays that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - computed the mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
+
diff --git a/general/datasets/Oncretilm6_0412/experiment-type.rtf b/general/datasets/Oncretilm6_0412/experiment-type.rtf
new file mode 100644
index 0000000..0546e04
--- /dev/null
+++ b/general/datasets/Oncretilm6_0412/experiment-type.rtf
@@ -0,0 +1 @@
+Expression profiling by array
\ No newline at end of file
diff --git a/general/datasets/Oncretilm6_0412/notes.rtf b/general/datasets/Oncretilm6_0412/notes.rtf
new file mode 100644
index 0000000..13ff99a
--- /dev/null
+++ b/general/datasets/Oncretilm6_0412/notes.rtf
@@ -0,0 +1 @@
+This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/Oncretilm6_0412/platform.rtf b/general/datasets/Oncretilm6_0412/platform.rtf
new file mode 100644
index 0000000..2c52707
--- /dev/null
+++ b/general/datasets/Oncretilm6_0412/platform.rtf
@@ -0,0 +1 @@
+Illumina MouseWG-6 v2.0 arrays: The Illumina Sentrix Mouse-6 BeadChip uses 50-nucleotide probes to interrogate approximately 46,000 sequences from the mouse transcriptome. For each array, the RNA was pooled from two retinas.
diff --git a/general/datasets/Oncretilm6_0412/processing.rtf b/general/datasets/Oncretilm6_0412/processing.rtf
new file mode 100644
index 0000000..97cc2be
--- /dev/null
+++ b/general/datasets/Oncretilm6_0412/processing.rtf
@@ -0,0 +1,2654 @@
+Values of all 45,281 probe sets in this data set range from a low of 6.25 (Rho GTPase activating protein 11A, Arhgap11a, probe ID ILMN_2747167) to a high of 18.08 (Ubiquitin B, Ubb, probe ID ILMN_2516699). This corresponds to 11.83 units or a 1 to 3641 dynamic range of expression (2^11.83). We normalized raw signal values using Beadstudio’s rank invariant normalization algorithm. BXD62 was the strain used as the control group
+
+
+
+Sample Processing: Drs. Natalie E. Freeman-Anderson and Justin P. Templeton extracted the retinas from the mice and Dr. Natalie Freeman-Anderson processed all samples in the HEI Vision Core Facility. The tissue was homogenized and extracted according to the RNA-Stat-60 protocol as described by the manufacturer (Tel-Test, Friendswood, TX) listed above. The quality and purity of RNA was assessed using an Agilent Bioanalyzer 2100 system. The RNA from each sample was processed with the Illumina TotalPrep RNA Amplification Kit (Ambion, Austin, TX) to produce labeled cRNA. The cRNA for each sample was then hybridized to an Illumina Sentrix® Mouse-6-V2 BeadChip (Illumina, San Diego, CA)
+
+
+
+
+
+Quality control analysis of the raw image data was performed using the Illumina BeadStudio software. MIAME standards were used for all microarray data. Rank invariant normalization with BeadStudio software was used to calculate the data. Once this data was collected, the data was globally normalized across all samples using the formula 2 (z-score of log2 [intensity]) + 8.
+
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
+
+Table 1: HEI Retina case IDs, including sample tube ID, strain, age, sex, and source of mice
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain |
+ Age |
+ Sex |
+ Source of Animal |
+
+
+ | 1 |
+ 121608_11-C57BL/6JcFA |
+ C57BL/6J |
+ 69 |
+ F |
+ JAX |
+
+
+ | 2 |
+ 121608_12-C57BL/6JcFB |
+ C57BL/6J |
+ 69 |
+ F |
+ JAX |
+
+
+ | 3 |
+ KA7444-C57BL/6JcMC |
+ C57BL/6J |
+ 97 |
+ M |
+ UTHSC RW |
+
+
+ | 4 |
+ KA7444-C57BL/6JcMD |
+ C57BL/6J |
+ 97 |
+ M |
+ UTHSC RW |
+
+
+ | 5 |
+ 31209.05-DBA2JcFA |
+ DBA2J |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 6 |
+ 31209.05-DBA2JcFB |
+ DBA2J |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 7 |
+ 121608_13-DBA/2JcMA |
+ DBA/2J |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 8 |
+ 121608_14-DBA/2JcMB |
+ DBA/2J |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 9 |
+ KA7446-B6D2F1cFA |
+ B6D2F1 |
+ 92 |
+ F |
+ UTHSC RW |
+
+
+ | 10 |
+ KA7446-B6D2F1cFB |
+ B6D2F1 |
+ 92 |
+ F |
+ UTHSC RW |
+
+
+ | 11 |
+ KA7446-B6D2F1cMC |
+ B6D2F1 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 12 |
+ KA7446-B6D2F1cMD |
+ B6D2F1 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 13 |
+ KA7466-D2B6F1cFA |
+ D2B6F1 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 14 |
+ KA7466-D2B6F1cFB |
+ D2B6F1 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 15 |
+ KA7466-D2B6F1cMC |
+ D2B6F1 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 16 |
+ KA7466-D2B6F1cMD |
+ D2B6F1 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 17 |
+ 82609.13-1cFA |
+ BXD01 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 18 |
+ 82609.14-1cFB |
+ BXD01 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 19 |
+ KA7389-1cFA |
+ BXD01 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 20 |
+ KA7389-1cFB |
+ BXD01 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 21 |
+ KA7389-1cMC |
+ BXD01 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 22 |
+ KA7389-1cMD |
+ BXD01 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 23 |
+ KA7300-2cFA |
+ BXD02 |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 24 |
+ KA7300-2cFB |
+ BXD02 |
+ 75 |
+ F |
+ UTHSC RW |
+
+
+ | 25 |
+ 100909.01-2cMA |
+ BXD02 |
+ 65 |
+ M |
+ JAX |
+
+
+ | 26 |
+ 100909.02-2cMB |
+ BXD02 |
+ 65 |
+ M |
+ JAX |
+
+
+ | 27 |
+ KA6699-5cFA |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 28 |
+ KA6699-5cFB |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 29 |
+ KA6699-5cFC |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 30 |
+ KA6699-5cFD |
+ BXD05 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 31 |
+ 82609.09-5cMA |
+ BXD05 |
+ 60 |
+ M |
+ JAX |
+
+
+ | 32 |
+ 82609.1-5cMB |
+ BXD05 |
+ 60 |
+ M |
+ JAX |
+
+
+ | 33 |
+ KA6763-6cFA |
+ BXD06 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 34 |
+ KA6763-6cFB |
+ BXD06 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 35 |
+ 81209.06-6cMA |
+ BXD06 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 36 |
+ 81209.07-6cMB |
+ BXD06 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 37 |
+ 82609.07-8cFA |
+ BXD08 |
+ 68 |
+ F |
+ JAX |
+
+
+ | 38 |
+ 82609.08-8cFB |
+ BXD08 |
+ 68 |
+ F |
+ JAX |
+
+
+ | 39 |
+ JAX-8cMA |
+ BXD08 |
+ 76 |
+ M |
+ JAX |
+
+
+ | 40 |
+ JAX-8cMB |
+ BXD08 |
+ 76 |
+ M |
+ JAX |
+
+
+ | 41 |
+ KA7289-9cFA |
+ BXD09 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 42 |
+ KA7289-9cFB |
+ BXD09 |
+ 87 |
+ F |
+ UTHSC RW |
+
+
+ | 43 |
+ KA7289-9cMC |
+ BXD09 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 44 |
+ KA7289-9cMD |
+ BXD09 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 45 |
+ JAX-11cFA |
+ BXD11 |
+ 84 |
+ F |
+ JAX |
+
+
+ | 46 |
+ JAX-11cFB |
+ BXD11 |
+ 84 |
+ F |
+ JAX |
+
+
+ | 47 |
+ JAX-11cMC |
+ BXD11 |
+ 71 |
+ M |
+ JAX |
+
+
+ | 48 |
+ JAX-11cMD |
+ BXD11 |
+ 71 |
+ M |
+ JAX |
+
+
+ | 49 |
+ 40209.07-12cFA |
+ BXD12 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 50 |
+ 40209.08-12cFB |
+ BXD12 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 51 |
+ 011309.01-12cMA |
+ BXD12 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 52 |
+ 011309.02-12cMB |
+ BXD12 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 53 |
+ KA7286-13cFA |
+ BXD13 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 54 |
+ KA7286-13cFB |
+ BXD13 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 55 |
+ KA7286-13cMC |
+ BXD13 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 56 |
+ KA7286-13cMD |
+ BXD13 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 57 |
+ KA7302-14cFA |
+ BXD14 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 58 |
+ KA7302-14cFB |
+ BXD14 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 59 |
+ 100909.05-14cMA |
+ BXD14 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 60 |
+ 100909.06-14cMB |
+ BXD14 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 61 |
+ KA7288-15cFA |
+ BXD15 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 62 |
+ KA7288-15cFB |
+ BXD15 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 63 |
+ KA7288-15cMC |
+ BXD15 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 64 |
+ KA7288-15cMD |
+ BXD15 |
+ 89 |
+ M |
+ UTHSC RW |
+
+
+ | 65 |
+ 062509.01-16cFA |
+ BXD16 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 66 |
+ KA7267-16cMA |
+ BXD16 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 67 |
+ KA7267-16cMB |
+ BXD16 |
+ 91 |
+ M |
+ UTHSC RW |
+
+
+ | 68 |
+ KA6686-18cFB |
+ BXD18 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 69 |
+ KA6686-18cFC |
+ BXD18 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 70 |
+ KA6686-18cME |
+ BXD18 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 71 |
+ KA6686-18cMF |
+ BXD18 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 72 |
+ KA6676-19cFB |
+ BXD19 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 73 |
+ KA6676-19cFC |
+ BXD19 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 74 |
+ KA6676-19cME |
+ BXD19 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 75 |
+ KA6676-19cMF |
+ BXD19 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 76 |
+ 060409.05-20cFA |
+ BXD20 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 77 |
+ 060409.06-20cFB |
+ BXD20 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 78 |
+ 021909.03-20cMA |
+ BXD20 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 79 |
+ 021909.04-20cMB |
+ BXD20 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 80 |
+ 82609.02-21cFC |
+ BXD21 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 81 |
+ 82609.03-21cFD |
+ BXD21 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 82 |
+ 121709.01-21cMA |
+ BXD21 |
+ 80 |
+ M |
+ JAX |
+
+
+ | 83 |
+ 121709.02-21cMB |
+ BXD21 |
+ 80 |
+ M |
+ JAX |
+
+
+ | 84 |
+ 121709.03-22cFA |
+ BXD22 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 85 |
+ 121709.04-22cFB |
+ BXD22 |
+ 62 |
+ F |
+ JAX |
+
+
+ | 86 |
+ 092308_03-22cMA |
+ BXD22 |
+ 118 |
+ M |
+ UTHSC RW |
+
+
+ | 87 |
+ 092308_04-22cMB |
+ BXD22 |
+ 118 |
+ M |
+ UTHSC RW |
+
+
+ | 88 |
+ 80409.01-24AcFA |
+ BXD24A |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 89 |
+ 080409_02_24AcFB |
+ BXD24A |
+ 72 |
+ F |
+ UTHSC RW |
+
+
+ | 90 |
+ 82609.26-24AcFC |
+ BXD24A |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 91 |
+ 81209.03-24AcMC |
+ BXD24A |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 92 |
+ KA6678-24cFA |
+ BXD24 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 93 |
+ KA6678-24cFB |
+ BXD24 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 94 |
+ KA6678-24cME |
+ BXD24 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 95 |
+ KA6678-24cMF |
+ BXD24 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 96 |
+ 060409.07-27cFA |
+ BXD27 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 97 |
+ 060409.08-27cFB |
+ BXD27 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 98 |
+ 80409.03-27cMA |
+ BXD27 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 99 |
+ 80409.04-27cMB |
+ BXD27 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 100 |
+ JAX-28cFA |
+ BXD28 |
+ 67 |
+ F |
+ JAX |
+
+
+ | 101 |
+ JAX-28cFB |
+ BXD28 |
+ 67 |
+ F |
+ JAX |
+
+
+ | 102 |
+ JAX-28cMC |
+ BXD28 |
+ 67 |
+ M |
+ JAX |
+
+
+ | 103 |
+ JAX-28cMD |
+ BXD28 |
+ 67 |
+ M |
+ JAX |
+
+
+ | 104 |
+ 82609.11-29cFA |
+ BXD29 |
+ 66 |
+ F |
+ JAX |
+
+
+ | 105 |
+ 82609.12-29cFB |
+ BXD29 |
+ 66 |
+ F |
+ JAX |
+
+
+ | 106 |
+ 82609.04-29cMA |
+ BXD29 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 107 |
+ 82609.05-29cMB |
+ BXD29 |
+ 66 |
+ M |
+ JAX |
+
+
+ | 108 |
+ JAX-31cMB |
+ BXD 31 |
+ 56 |
+ M |
+ JAX |
+
+
+ | 109 |
+ JAX-31cFC |
+ BXD 31 |
+ 69 |
+ F |
+ JAX |
+
+
+ | 110 |
+ JAX-31cFD |
+ BXD 31 |
+ 69 |
+ F |
+ JAX |
+
+
+ | 111 |
+ 011309.03-32cFA |
+ BXD32 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 112 |
+ 011309.04-32cFB |
+ BXD32 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 113 |
+ KA7318-32cFC |
+ BXD32 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 114 |
+ KA7319-32cMA |
+ BXD32 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 115 |
+ KA7319-32cMB |
+ BXD32 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 116 |
+ 100909.07-33cFA |
+ BXD33 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 117 |
+ 100909.08-33cFB |
+ BXD33 |
+ 65 |
+ F |
+ JAX |
+
+
+ | 118 |
+ 022609.01-33cMA |
+ BXD33 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 119 |
+ 022609.02-33cMB |
+ BXD33 |
+ 92 |
+ M |
+ UTHSC RW |
+
+
+ | 120 |
+ KA7416-34cFA |
+ BXD34 |
+ 97 |
+ F |
+ UTHSC RW |
+
+
+ | 121 |
+ KA7416-34cFB |
+ BXD34 |
+ 97 |
+ F |
+ UTHSC RW |
+
+
+ | 122 |
+ KA6321-34cMA |
+ BXD34 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 123 |
+ KA6321-34cMB |
+ BXD34 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 124 |
+ 060409.01-36cFA |
+ BXD36 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 125 |
+ 060409.02-36cFB |
+ BXD36 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 126 |
+ 060409.03-36cMC |
+ BXD36 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 127 |
+ KA6702-38cFA |
+ BXD38 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 128 |
+ KA6702-38cFB |
+ BXD38 |
+ 63 |
+ F |
+ UTHSC RW |
+
+
+ | 129 |
+ 82609.24-38cFA |
+ BXD38 |
+ 85 |
+ F |
+ UTHSC RW |
+
+
+ | 130 |
+ 82609.25-38cFB |
+ BXD38 |
+ 85 |
+ F |
+ UTHSC RW |
+
+
+ | 131 |
+ 100909.03-38cMA |
+ BXD38 |
+ 61 |
+ M |
+ JAX |
+
+
+ | 132 |
+ 100909.04-38cMB |
+ BXD38 |
+ 61 |
+ M |
+ JAX |
+
+
+ | 133 |
+ 022609.05-39cFA |
+ BXD39 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 134 |
+ 022609.06-39cFB |
+ BXD39 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 135 |
+ 31209.01-39cMC |
+ BXD39 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 136 |
+ 92409.01-40cFA |
+ BXD40 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 137 |
+ 92409.02-40cFB |
+ BXD40 |
+ 64 |
+ F |
+ UTHSC RW |
+
+
+ | 138 |
+ KA6173-40cMA |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 139 |
+ KA6173-40cMB |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 140 |
+ KA6173-40cMC |
+ BXD40 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 141 |
+ 091809.01-42cFA |
+ BXD42 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 142 |
+ 091809.02-42cFB |
+ BXD42 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 143 |
+ 021909.01-42cFA |
+ BXD42 |
+ 89 |
+ F |
+ UTHSC RW |
+
+
+ | 144 |
+ 011309.06-42cMA |
+ BXD42 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 145 |
+ 011309.07-42cMB |
+ BXD42 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 146 |
+ 110408_02-43cFA |
+ BXD43 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 147 |
+ 110408_03-43cFB |
+ BXD43 |
+ 61 |
+ F |
+ UTHSC RW |
+
+
+ | 148 |
+ KA6158-43cMA |
+ BXD43 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 149 |
+ KA6158-43cMB |
+ BXD43 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 150 |
+ 100308_01-44cFA |
+ BXD44 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 151 |
+ 102208_02-44cMD |
+ BXD44 |
+ 64 |
+ M |
+ UTHSC RW |
+
+
+ | 152 |
+ 103009.03-45cFA |
+ BXD45 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 153 |
+ 103009.04-45cFB |
+ BXD45 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 154 |
+ 022609.03-45cFA |
+ BXD45 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 155 |
+ 022609.04-45cFB |
+ BXD45 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 156 |
+ 40309.05-45cMB |
+ BXD45 |
+ 65 |
+ M |
+ UTHSC RW |
+
+
+ | 157 |
+ 40209.05-48cFB |
+ BXD48 |
+ 58 |
+ F |
+ VAMC |
+
+
+ | 158 |
+ 40209.06-48cFC |
+ BXD48 |
+ 58 |
+ F |
+ VAMC |
+
+
+ | 159 |
+ 81209.04-48cMA |
+ BXD48 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 160 |
+ 81209.05-48cMB |
+ BXD48 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 161 |
+ 81209.08-49cFA |
+ BXD49 |
+ 70 |
+ F |
+ VAMC |
+
+
+ | 162 |
+ 81209.09-49cFB |
+ BXD49 |
+ 70 |
+ F |
+ VAMC |
+
+
+ | 163 |
+ 40209.01-49cMA |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 164 |
+ 40209.02-49cMB |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 165 |
+ 40209.03-49cMC |
+ BXD49 |
+ 87 |
+ M |
+ VAMC |
+
+
+ | 166 |
+ KA737850cFA |
+ BXD50 |
+ 50 |
+ F |
+ UTHSC RW |
+
+
+ | 167 |
+ KA737850cFB |
+ BXD50 |
+ 50 |
+ F |
+ UTHSC RW |
+
+
+ | 168 |
+ 121908_01-50cMA |
+ BXD50 |
+ 49 |
+ M |
+ UTHSC RW |
+
+
+ | 169 |
+ 121908_02-50cMB |
+ BXD50 |
+ 49 |
+ M |
+ UTHSC RW |
+
+
+ | 170 |
+ 111208_01-51cFA |
+ BXD51 |
+ 99 |
+ F |
+ UTHSC RW |
+
+
+ | 171 |
+ 102208_03-51cMA |
+ BXD51 |
+ 56 |
+ M |
+ UTHSC RW |
+
+
+ | 172 |
+ 102208_04-51cMB |
+ BXD51 |
+ 56 |
+ M |
+ UTHSC RW |
+
+
+ | 173 |
+ 090208_14-53BcFA |
+ BXD53B |
+ 93 |
+ F |
+ UTHSC RW |
+
+
+ | 174 |
+ 090208_15-53BcFB |
+ BXD53B |
+ 93 |
+ F |
+ UTHSC RW |
+
+
+ | 175 |
+ 090208_16-53BcMC |
+ BXD53B |
+ 93 |
+ M |
+ UTHSC RW |
+
+
+ | 176 |
+ 090208_17-53BcMD |
+ BXD53B |
+ 93 |
+ M |
+ UTHSC RW |
+
+
+ | 177 |
+ 111208_05-55cFB |
+ BXD55 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 178 |
+ KA6183-55cMA |
+ BXD55 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 179 |
+ KA6183-55cMB |
+ BXD55 |
+ 63 |
+ M |
+ UTHSC RW |
+
+
+ | 180 |
+ KA7362-56cFB |
+ BXD 56 |
+ 54 |
+ F |
+ UTHSC RW |
+
+
+ | 181 |
+ KA6088-56cMA |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 182 |
+ KA6088-56cMB |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 183 |
+ KA6088-56cMC |
+ BXD56 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 184 |
+ 21810.01-60RFA |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 185 |
+ 21810.02-60RFB |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 186 |
+ 21810.02-60RFC |
+ BXD 60 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 187 |
+ SQ7325-60cMA |
+ BXD60 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 188 |
+ SQ7325-60cMB |
+ BXD60 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 189 |
+ 092308_10-61cFA |
+ BXD61 |
+ 110 |
+ F |
+ UTHSC RW |
+
+
+ | 190 |
+ 092308_11-61cFB |
+ BXD61 |
+ 110 |
+ F |
+ UTHSC RW |
+
+
+ | 191 |
+ 31909.01-61cMA |
+ BXD61 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 192 |
+ 31909.02-61cMB |
+ BXD61 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 193 |
+ KA7462-62cFA |
+ BXD62 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 194 |
+ KA7462-62cFB |
+ BXD62 |
+ 76 |
+ F |
+ UTHSC RW |
+
+
+ | 195 |
+ KA5996-62cMA |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 196 |
+ KA5996-62cMB |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 197 |
+ KA5996-62cMC |
+ BXD62 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 198 |
+ 090309.01-63cFA |
+ BXD63 |
+ 69 |
+ F |
+ UTHSC RW |
+
+
+ | 199 |
+ 090309.02-63cFB |
+ BXD63 |
+ 69 |
+ F |
+ UTHSC RW |
+
+
+ | 200 |
+ 110609.01-63cMA |
+ BXD63 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 201 |
+ 110609.02-63cMB |
+ BXD63 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 202 |
+ 091809.03-65cFA |
+ BXD65 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 203 |
+ 091809.04-65cFB |
+ BXD65 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 204 |
+ 103009.01-65cMA |
+ BXD65 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 205 |
+ 103009.02-65cMB |
+ BXD65 |
+ 74 |
+ M |
+ UTHSC RW |
+
+
+ | 206 |
+ 110408_05-66cFB |
+ BXD66 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 207 |
+ KA7165-66cMA |
+ BXD66 |
+ 95 |
+ M |
+ UTHSC RW |
+
+
+ | 208 |
+ KA7165-66cMB |
+ BXD66 |
+ 95 |
+ M |
+ UTHSC RW |
+
+
+ | 209 |
+ 90809.01-67cMA |
+ BXD67 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 210 |
+ 90809.02-67cMB |
+ BXD67 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 211 |
+ 110609.03-67cFA |
+ BXD67 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 212 |
+ 110609.04-67cFB |
+ BXD67 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 213 |
+ 120408_01-68cFA |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 214 |
+ 120408_02-68cFB |
+ BXD68 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 215 |
+ SQ7205-68cMA |
+ BXD68 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 216 |
+ SQ7205-68cMB |
+ BXD68 |
+ 87 |
+ M |
+ UTHSC RW |
+
+
+ | 217 |
+ KA6316-68cMA |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 218 |
+ KA6316-68cMB |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 219 |
+ KA6316-68cMC |
+ BXD68 |
+ 76 |
+ M |
+ UTHSC RW |
+
+
+ | 220 |
+ KA76-69cFA |
+ BXD69 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 221 |
+ KA76-69cFB |
+ BXD69 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 222 |
+ KA6074-69cMA |
+ BXD69 |
+ 90 |
+ M |
+ UTHSC RW |
+
+
+ | 223 |
+ KA6074-69cMB |
+ BXD69 |
+ 90 |
+ M |
+ UTHSC RW |
+
+
+ | 224 |
+ 121608_01-70cFA |
+ BXD70 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 225 |
+ 121608_02-70cFB |
+ BXD70 |
+ 80 |
+ F |
+ UTHSC RW |
+
+
+ | 226 |
+ KA7394-70cMA |
+ BXD70 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 227 |
+ 81209.08-70cMA |
+ BXD70 |
+ 71 |
+ M |
+ VAMC |
+
+
+ | 228 |
+ 81209.09-70cMB |
+ BXD70 |
+ 71 |
+ M |
+ VAMC |
+
+
+ | 229 |
+ 052809.01-71cFA |
+ BXD71 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 230 |
+ 060409.09-71cMA |
+ BXD71 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 231 |
+ 060409.10-71cMB |
+ BXD71 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 232 |
+ 40809.01-73cFA |
+ BXD73 |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 233 |
+ 40809.02-73cFB |
+ BXD73 |
+ 83 |
+ F |
+ UTHSC RW |
+
+
+ | 234 |
+ 111708_01-73cFA |
+ BXD73 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 235 |
+ 111708_01-73cFB |
+ BXD73 |
+ 55 |
+ F |
+ UTHSC RW |
+
+
+ | 236 |
+ KA6164-73cMB |
+ BXD73 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 237 |
+ KA6164-73cMC |
+ BXD73 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 238 |
+ 82609.22-74cFA |
+ BXD74 |
+ 68 |
+ F |
+ VAMC |
+
+
+ | 239 |
+ 82609.23-74cFB |
+ BXD74 |
+ 68 |
+ F |
+ VAMC |
+
+
+ | 240 |
+ 82609.20-74cMA |
+ BXD74 |
+ 68 |
+ M |
+ VAMC |
+
+
+ | 241 |
+ 82609.21-74cMB |
+ BXD74 |
+ 68 |
+ M |
+ VAMC |
+
+
+ | 242 |
+ KA733675cFA |
+ BXD75 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 243 |
+ KA733675cFB |
+ BXD75 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 244 |
+ KA38-75cMB |
+ BXD75 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 245 |
+ KA38-75cMC |
+ BXD75 |
+ 62 |
+ M |
+ UTHSC RW |
+
+
+ | 246 |
+ 41509.01-77cFA |
+ BXD77 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 247 |
+ 41509.02-77cFB |
+ BXD77 |
+ 70 |
+ F |
+ UTHSC RW |
+
+
+ | 248 |
+ 41509.03-77cMC |
+ BXD77 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 249 |
+ 41509.04-77cMD |
+ BXD77 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 250 |
+ 121608_03-80cFA |
+ BXD80 |
+ 77 |
+ F |
+ UTHSC RW |
+
+
+ | 251 |
+ 121608_05-80cMC |
+ BXD80 |
+ 70 |
+ M |
+ UTHSC RW |
+
+
+ | 252 |
+ KA23-80cMC |
+ BXD80 |
+ 77 |
+ M |
+ UTHSC RW |
+
+
+ | 253 |
+ KA7305-81cFA |
+ BXD81 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 254 |
+ KA7305-81cFB |
+ BXD81 |
+ 51 |
+ F |
+ UTHSC RW |
+
+
+ | 255 |
+ KA7305-81cMD |
+ BXD81 |
+ 51 |
+ M |
+ UTHSC RW |
+
+
+ | 256 |
+ 060409.11-83cFA |
+ BXD83 |
+ 65 |
+ F |
+ UTHSC RW |
+
+
+ | 257 |
+ KA24-83cFA |
+ BXD83 |
+ 78 |
+ F |
+ UTHSC RW |
+
+
+ | 258 |
+ 121608_07-83cMA |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 259 |
+ 121608_08-83cMB |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 260 |
+ KA24-83cMD |
+ BXD83 |
+ 78 |
+ M |
+ UTHSC RW |
+
+
+ | 261 |
+ 090409.05-84cFA |
+ BXD84 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 262 |
+ 090409.06-84cFB |
+ BXD84 |
+ 65 |
+ F |
+ VAMC |
+
+
+ | 263 |
+ KA6203-84cMA |
+ BXD84 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 264 |
+ KA6203-84cMB |
+ BXD84 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 265 |
+ 40309.02-85cFD |
+ BXD85 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 266 |
+ 40309.03-85cFE |
+ BXD85 |
+ 58 |
+ F |
+ UTHSC RW |
+
+
+ | 267 |
+ 32609.01-85cMA |
+ BXD85 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 268 |
+ 32609.02-85cMB |
+ BXD85 |
+ 67 |
+ M |
+ UTHSC RW |
+
+
+ | 269 |
+ 41509.05-86cFA |
+ BXD86 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 270 |
+ 41509.06-86cFB |
+ BXD86 |
+ 73 |
+ F |
+ UTHSC RW |
+
+
+ | 271 |
+ KA6101-86cMA |
+ BXD86 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 272 |
+ KA6101-86cMC |
+ BXD86 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 273 |
+ 070909.02-87cFA |
+ BXD87 |
+ 86 |
+ F |
+ UTHSC RW |
+
+
+ | 274 |
+ 070909.03-87cFB |
+ BXD87 |
+ 86 |
+ F |
+ UTHSC RW |
+
+
+ | 275 |
+ KA7407-87cMA |
+ BXD87 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 276 |
+ KA7407-87cMB |
+ BXD87 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 277 |
+ 102208_05-89cFA |
+ BXD89 |
+ 82 |
+ F |
+ UTHSC RW |
+
+
+ | 278 |
+ KA5974-89cMA |
+ BXD89 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 279 |
+ KA5974-89cMB |
+ BXD89 |
+ 113 |
+ M |
+ UTHSC RW |
+
+
+ | 280 |
+ 102208_06-89cMC |
+ BXD89 |
+ 82 |
+ M |
+ UTHSC RW |
+
+
+ | 281 |
+ 72309.01-90cFA |
+ BXD90 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 282 |
+ 72309.02-90cFB |
+ BXD90 |
+ 67 |
+ F |
+ UTHSC RW |
+
+
+ | 283 |
+ 090409.03-90cMA |
+ BXD90 |
+ 64 |
+ M |
+ VAMC |
+
+
+ | 284 |
+ 090409.04-90cMB |
+ BXD90 |
+ 64 |
+ M |
+ VAMC |
+
+
+ | 285 |
+ KA6094-92cMA |
+ BXD92 |
+ 85 |
+ M |
+ UTHSC RW |
+
+
+ | 286 |
+ 020609.01-95cFA |
+ BXD95 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 287 |
+ 020609.02-95cFB |
+ BXD95 |
+ 71 |
+ F |
+ UTHSC RW |
+
+
+ | 288 |
+ KA6181-95cMA |
+ BXD95 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 289 |
+ KA6181-95cMB |
+ BXD95 |
+ 61 |
+ M |
+ UTHSC RW |
+
+
+ | 290 |
+ 31209.03-96cFA |
+ BXD96 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 291 |
+ 31209.04-96cFB |
+ BXD96 |
+ 62 |
+ F |
+ UTHSC RW |
+
+
+ | 292 |
+ KA7246-96cMA |
+ BXD96 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 293 |
+ KA7246-96cMB |
+ BXD96 |
+ 73 |
+ M |
+ UTHSC RW |
+
+
+ | 294 |
+ 81209.10-97cFA |
+ BXD97 |
+ 83 |
+ F |
+ VAMC |
+
+
+ | 295 |
+ 81209.11-97cFB |
+ BXD97 |
+ 83 |
+ F |
+ VAMC |
+
+
+ | 296 |
+ 81209.1-97cMA |
+ BXD97 |
+ 83 |
+ M |
+ VAMC |
+
+
+ | 297 |
+ 81209.11-97cMB |
+ BXD97 |
+ 83 |
+ M |
+ VAMC |
+
+
+ | 298 |
+ SQ7520-98cFA |
+ BXD98 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 299 |
+ SQ7520-98cFB |
+ BXD98 |
+ 59 |
+ F |
+ UTHSC RW |
+
+
+ | 300 |
+ SQ7520-98cMC |
+ BXD98 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 301 |
+ SQ7520-98cMD |
+ BXD98 |
+ 59 |
+ M |
+ UTHSC RW |
+
+
+ | 302 |
+ 82609.17-99cFA |
+ BXD99 |
+ 64 |
+ F |
+ VAMC |
+
+
+ | 303 |
+ 82609.18-99cFB |
+ BXD99 |
+ 64 |
+ F |
+ VAMC |
+
+
+ | 304 |
+ 81409.01-99cMA |
+ BXD99 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 305 |
+ 81409.02-99cMB |
+ BXD99 |
+ 66 |
+ M |
+ UTHSC RW |
+
+
+ | 306 |
+ 121608_09-100cFA |
+ BXD100 |
+ 81 |
+ F |
+ UTHSC RW |
+
+
+ | 307 |
+ 121608_10-100cFB |
+ BXD100 |
+ 81 |
+ F |
+ UTHSC RW |
+
+
+ | 308 |
+ KA6001-100cMA |
+ BXD100 |
+ 111 |
+ M |
+ UTHSC RW |
+
+
+ | 309 |
+ KA6001-100cMB |
+ BXD100 |
+ 111 |
+ M |
+ UTHSC RW |
+
+
+ | 310 |
+ 81209.12-101cFA |
+ BXD101 |
+ 72 |
+ F |
+ VAMC |
+
+
+ | 311 |
+ 81209.13-101cFB |
+ BXD101 |
+ 72 |
+ F |
+ VAMC |
+
+
+ | 312 |
+ KA7296-101cMA |
+ BXD101 |
+ 75 |
+ M |
+ UTHSC RW |
+
+
+ | 313 |
+ KA7296-101cMB |
+ BXD101 |
+ 75 |
+ M |
+ UTHSC RW |
+
+
+ | 314 |
+ 92409.03-102cFA |
+ BXD102 |
+ 71 |
+ F |
+ VAMC |
+
+
+ | 315 |
+ 92409.04-102cFB |
+ BXD102 |
+ 71 |
+ F |
+ VAMC |
+
+
+ | 316 |
+ KA7380-102cMA |
+ BXD102 |
+ 115 |
+ M |
+ UTHSC RW |
+
+
+ | 317 |
+ 43009.01-103cFA |
+ BXD103 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 318 |
+ 43009.02-103cFB |
+ BXD103 |
+ 68 |
+ F |
+ UTHSC RW |
+
+
+ | 319 |
+ KA79-103cFA |
+ BXD103 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 320 |
+ KA79-103cFB |
+ BXD103 |
+ 48 |
+ F |
+ UTHSC RW |
+
+
+ | 321 |
+ KA79-103cMC |
+ BXD103 |
+ 48 |
+ M |
+ UTHSC RW |
+
+
+ | 322 |
+ 82609.15-103cMA |
+ BXD103 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 323 |
+ 82609.16-103cMB |
+ BXD103 |
+ 69 |
+ M |
+ VAMC |
+
+
+ | 324 |
+ 102909.01-BALBCcFA |
+ BALB/cByJ |
+ 78 |
+ F |
+ JAX |
+
+
+ | 325 |
+ 102909.02-BALBCcFB |
+ BALB/cByJ |
+ 78 |
+ F |
+ JAX |
+
+
+ | 326 |
+ 102909.03-BALBCcMA |
+ BALB/cByJ |
+ 78 |
+ M |
+ JAX |
+
+
+ | 327 |
+ 102909.04-BALBCcMB |
+ BALB/cByJ |
+ 78 |
+ M |
+ JAX |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Oncretilm6_0412/summary.rtf b/general/datasets/Oncretilm6_0412/summary.rtf
new file mode 100644
index 0000000..44e98a7
--- /dev/null
+++ b/general/datasets/Oncretilm6_0412/summary.rtf
@@ -0,0 +1,50 @@
+
+This is a subtractive dataset. The Normal retina dataset was subtracted from the ONC data set probe by probe to create a data set of the changes occurring following ONC. This data set can be used to define gene changes following ONC. It is not compatible with most of the bioinformatic tools available on GeneNetwork.
+
+HEI Retina Illumina V6.2 (April 2010) RankInv was normalized and scaled by William E. Orr and uploaded by Arthur Centeno and Xiaodong Zhou on April 7, 2010. This data set consists of either 69 BXD strains (Normal data set) or 75 BXD strains (Full data set), C57BL/6J, DBA/2J, both reciprocal F1s, and BALB/cByJ. A total of either 74 strains (Normal data set) or 80 strains (Full data set) were quantified.
+
+COMMENT on FULL versus NORMAL data sets: For many general uses there is no significant difference between FULL and NORMAL data sets. However, the FULL data set includes strains with high endogenous Gfap mRNA expression, indicative of reactive gliosis. For that reason, and to compare to OPTIC NERVE CRUSH (ONC), we removed data from six strains to make the NORMAL data set.
+
+The NORMAL data set exludes data from BXD24, BXD32, BXD49, BXD70, BXD83, and BXD89. BXD24 has known retinal degeneration and is now known officially as BXD24/TyJ-Cep290/J, JAX Stock number 000031. BXD32 has mild retinal degeneration. The NORMAL data set does include BXD24a, now also known as BXD24/TyJ (JAX Stock number 005243).
+
+The data are now open and available for analysis.
+
+Please cite: Freeman NE, Templeton JP, Orr WE, Lu L, Williams RW, Geisert EE (2011) Genetic networks in the mouse retina: Growth Associated Protein 43 and Phosphate Tensin Homology network. Molecular Vision 17:1355-1372. Full Text PDF or HTML
+
+This is rank invariant expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 6.25 to 18.08 (11.83 units), a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
+
+The lowest level of expression is 6.254 for ILMN_2747167 (Arhgap11a) from HEI Retina Illumina V6.2 (April 2010) RankInv **. Lowest single data about 5.842.
+
+The highest level of expression is 18.077 for ILMN_2516699 (Ubb). Highest single value is about 18.934.
+
+
+
+
+Other Related Publications
+
+
+
+
+
+ - Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link)
+ - Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674
+ - Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link)
+ - Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.(Link)
+
+
+
+
+
+
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful:
+
+
+ - NEIBank collection of ESTs and SAGE data.
+ - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
+ - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
+ - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
+ - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
+ - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
+
+
diff --git a/general/datasets/Oncretilm6_0412/tissue.rtf b/general/datasets/Oncretilm6_0412/tissue.rtf
new file mode 100644
index 0000000..766ab59
--- /dev/null
+++ b/general/datasets/Oncretilm6_0412/tissue.rtf
@@ -0,0 +1,32 @@
+
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RNAlater at room temperature. Two retinas from one mouse were stored in a single tube.
+
+Each array was hybridized with a pool of cRNA from 2 retinas (1 mouse). Natalie Freeman-Anderson extracted RNA at UTHSC.
+
+
+
+Dissecting and preparing eyes for RNA extraction
+
+
+
+Retinas for RNA extraction were placed in RNA STAT-60 (Tel-Test Inc.) and processed per manufacturer’s instructions (in brief form below). Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
+
+
+
+
+ - Homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue via syringe)
+ - Allow the homogenate to stand for 5-10 min at room temperature
+ - Add 0.2 ml of chloroform per 1 ml RNA STAT-60
+ - Mix the sample vigorously for 15 sec and let the sample incubate at room temperature for 5-10 min
+ - Centrifuge at 12,000 g for 1 hr at 4°C
+ - Transfer the aqueous phase to a clean centrifuge tube
+ - Add 0.5 ml of isopropanol per 1 ml RNA STAT-60
+ - Vortex and incubate the sample at -20°C for 1 hr or overnight
+ - Centrifuge at 12,000 g for 1 hr
+ - Remove the supernatant and wash the RNA pellet with 75% ethanol
+ - Remove ethanol, let air dry (5-10 min)
+ - Dissolve the pellet in 50 μl of nuclease free water.
+
+
+
+
diff --git a/general/datasets/Oncretmogene2_0413/acknowledgment.rtf b/general/datasets/Oncretmogene2_0413/acknowledgment.rtf
new file mode 100644
index 0000000..13c6b1e
--- /dev/null
+++ b/general/datasets/Oncretmogene2_0413/acknowledgment.rtf
@@ -0,0 +1 @@
+DoD funding (W81XWH-12-0255) Genetic Networks Activated by Blast Injury to the Eye (Eldon E. Geisert).
diff --git a/general/datasets/Oncretmogene2_0413/cases.rtf b/general/datasets/Oncretmogene2_0413/cases.rtf
new file mode 100644
index 0000000..6b36c70
--- /dev/null
+++ b/general/datasets/Oncretmogene2_0413/cases.rtf
@@ -0,0 +1,1728 @@
+Almost all animals are young adults between 60 and 90 days of age (Table 1, minimum age is 50 and maximum age is 134 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, and reciprocal F1s between C57BL/6J and DBA/2J. BXD strains: The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. In 2004, BXD24/TyJ developed a spontaneous mutation, rd16 which resulted in retinal degeneration and was renamed BXD24b/TyJ (BXD24 in this database). The strain, BXD24a, was cryo-recovered in 2004 from 1988 embryo stocks (F80) and does not exhibit retinal degeneration. In 2009, BXD24b was renamed BXD24/TyJ-Cep290rd16/J by JAX Labs to reflect the discovery of the genetic basis of the mutation. At the same time BXD24a was then referred to just as BXD24/TyJ by Jax Labs, but still called BXD24a in this dataset. The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEI data set.
+
+
+
+
+
+
+
+
+
+ | Index |
+ EIGC ID (LIMS ID) |
+ Strain |
+ Sex |
+ Age at harvest |
+ RIN Score |
+
+
+ | 1 |
+ 602 |
+ BXD9 |
+ F |
+ 133 |
+ 9.1 |
+
+
+ | 2 |
+ 603 |
+ BXD9 |
+ M |
+ 100 |
+ 9.5 |
+
+
+ | 3 |
+ 604 |
+ BXD40 |
+ F |
+ 100 |
+ 9.4 |
+
+
+ | 4 |
+ 605 |
+ BXD40 |
+ M |
+ 100 |
+ 9.1 |
+
+
+ | 5 |
+ 606 |
+ BXD48 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 6 |
+ 607 |
+ BXD48 |
+ M |
+ 75 |
+ 8.6 |
+
+
+ | 7 |
+ 608 |
+ BXD63 |
+ F |
+ 75 |
+ 9.2 |
+
+
+ | 8 |
+ 609 |
+ BXD63 |
+ M |
+ 61 |
+ 9.4 |
+
+
+ | 9 |
+ 612 |
+ BXD73 |
+ M |
+ 108 |
+ 10 |
+
+
+ | 10 |
+ 614 |
+ BXD87 |
+ M |
+ 85 |
+ 9.2 |
+
+
+ | 11 |
+ 615 |
+ BXD87 |
+ F |
+ 85 |
+ 9.9 |
+
+
+ | 12 |
+ 616 |
+ BXD69 |
+ F |
+ 76 |
+ 9.3 |
+
+
+ | 13 |
+ 617 |
+ BXD69 |
+ M |
+ 100 |
+ 10 |
+
+
+ | 14 |
+ 618 |
+ BXD51 |
+ M |
+ 82 |
+ 8.9 |
+
+
+ | 15 |
+ 619 |
+ BXD92 (BXD65b) |
+ M |
+ 82 |
+ 8.8 |
+
+
+ | 16 |
+ 620 |
+ BXD92 (BXD65b) |
+ F |
+ 82 |
+ 8.8 |
+
+
+ | 17 |
+ 635 |
+ BXD100 |
+ M |
+ 70 |
+ 9 |
+
+
+ | 18 |
+ 636 |
+ BXD100 |
+ M |
+ 70 |
+ 8.8 |
+
+
+ | 19 |
+ 652 |
+ BXD92 (BXD65b) |
+ F |
+ 64 |
+ 9 |
+
+
+ | 20 |
+ 653 |
+ BXD87 |
+ F |
+ 67 |
+ 9.7 |
+
+
+ | 21 |
+ 654 |
+ BXD87 |
+ M |
+ 67 |
+ 8.9 |
+
+
+ | 22 |
+ 655 |
+ BXD63 |
+ M |
+ 71 |
+ 9 |
+
+
+ | 23 |
+ 660 |
+ BXD69 |
+ M |
+ 97 |
+ 10 |
+
+
+ | 24 |
+ 687 |
+ BXD6 |
+ M |
+ 85 |
+ 7.7 |
+
+
+ | 25 |
+ 688 |
+ BXD6 |
+ M |
+ 85 |
+ 9.4 |
+
+
+ | 26 |
+ 690 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 27 |
+ 691 |
+ BXD12 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 28 |
+ 692 |
+ BXD12 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 29 |
+ 695 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 30 |
+ 696 |
+ BXD5 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 31 |
+ 698 |
+ BXD5 |
+ F |
+ 77 |
+ 9.9 |
+
+
+ | 32 |
+ 699 |
+ BXD5 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 33 |
+ 701 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 34 |
+ 702 |
+ BXD8 |
+ M |
+ 79 |
+ 10 |
+
+
+ | 35 |
+ 705 |
+ BXD8 |
+ F |
+ 77 |
+ 9.2 |
+
+
+ | 36 |
+ 707 |
+ BXD15 |
+ F |
+ 77 |
+ 9.4 |
+
+
+ | 37 |
+ 708 |
+ BXD15 |
+ F |
+ 77 |
+ 9.1 |
+
+
+ | 38 |
+ 710 |
+ BXD15 |
+ M |
+ 77 |
+ 9.1 |
+
+
+ | 39 |
+ 713 |
+ BXD22 |
+ F |
+ 71 |
+ 9.5 |
+
+
+ | 40 |
+ 714 |
+ BXD22 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 41 |
+ 716 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 42 |
+ 717 |
+ BXD22 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 43 |
+ 719 |
+ BXD14 |
+ F |
+ 70 |
+ 9.2 |
+
+
+ | 44 |
+ 722 |
+ BXD14 |
+ M |
+ 70 |
+ 8.9 |
+
+
+ | 45 |
+ 723 |
+ BXD14 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 46 |
+ 725 |
+ BXD18 |
+ F |
+ 70 |
+ 9 |
+
+
+ | 47 |
+ 726 |
+ BXD18 |
+ F |
+ 70 |
+ 9.1 |
+
+
+ | 48 |
+ 728 |
+ BXD18 |
+ M |
+ 70 |
+ 9.1 |
+
+
+ | 49 |
+ 729 |
+ BXD18 |
+ M |
+ 70 |
+ 9.2 |
+
+
+ | 50 |
+ 731 |
+ BXD19 |
+ F |
+ 66 |
+ 9.3 |
+
+
+ | 51 |
+ 732 |
+ BXD19 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 52 |
+ 734 |
+ BXD19 |
+ M |
+ 66 |
+ 9.8 |
+
+
+ | 53 |
+ 735 |
+ BXD19 |
+ M |
+ 66 |
+ 9.4 |
+
+
+ | 54 |
+ 737 |
+ BXD21 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 55 |
+ 738 |
+ BXD21 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 56 |
+ 740 |
+ BXD21 |
+ M |
+ 71 |
+ 9.1 |
+
+
+ | 57 |
+ 741 |
+ BXD21 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 58 |
+ 743 |
+ BXD2 |
+ F |
+ 70 |
+ 8.3 |
+
+
+ | 59 |
+ 744 |
+ BXD2 |
+ F |
+ 70 |
+ 8.6 |
+
+
+ | 60 |
+ 746 |
+ BXD2 |
+ M |
+ 70 |
+ 7.5 |
+
+
+ | 61 |
+ 747 |
+ BXD2 |
+ M |
+ 77 |
+ 8.6 |
+
+
+ | 62 |
+ 768 |
+ BXD48 |
+ M |
+ 121 |
+ 9.4 |
+
+
+ | 63 |
+ 770 |
+ BXD92 (BXD65b) |
+ M |
+ 65 |
+ 10 |
+
+
+ | 64 |
+ 771 |
+ BXD101 |
+ F |
+ 85 |
+ 8.3 |
+
+
+ | 65 |
+ 772 |
+ BXD101 |
+ F |
+ 85 |
+ 9.3 |
+
+
+ | 66 |
+ 773 |
+ BXD101 |
+ M |
+ 86 |
+ 9.5 |
+
+
+ | 67 |
+ 774 |
+ BXD101 |
+ M |
+ 86 |
+ 9.8 |
+
+
+ | 68 |
+ 775 |
+ BXD102 |
+ F |
+ 66 |
+ 9.5 |
+
+
+ | 69 |
+ 776 |
+ BXD102 |
+ F |
+ 66 |
+ 10 |
+
+
+ | 70 |
+ 777 |
+ BXD102 |
+ M |
+ 84 |
+ 9.6 |
+
+
+ | 71 |
+ 787 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 72 |
+ 788 |
+ BXD60 |
+ M |
+ 86 |
+ 9.9 |
+
+
+ | 73 |
+ 789 |
+ BXD63 |
+ F |
+ 115 |
+ 9.7 |
+
+
+ | 74 |
+ 790 |
+ BXD100 |
+ F |
+ 72 |
+ 9.8 |
+
+
+ | 75 |
+ 791 |
+ BXD100 |
+ F |
+ 72 |
+ 10 |
+
+
+ | 76 |
+ 818 |
+ BXD51 |
+ F |
+ 77 |
+ 9.7 |
+
+
+ | 77 |
+ 819 |
+ BXD51 |
+ F |
+ 77 |
+ 9.6 |
+
+
+ | 78 |
+ 820 |
+ BXD51 |
+ M |
+ 72 |
+ 9.7 |
+
+
+ | 79 |
+ 821 |
+ BXD65 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 80 |
+ 822 |
+ BXD65 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 81 |
+ 825 |
+ BXD65 |
+ F |
+ 72 |
+ 9.5 |
+
+
+ | 82 |
+ 827 |
+ BXD86 |
+ M |
+ 69 |
+ 9.1 |
+
+
+ | 83 |
+ 828 |
+ BXD86 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 84 |
+ 829 |
+ BXD90 |
+ F |
+ 69 |
+ 9.6 |
+
+
+ | 85 |
+ 831 |
+ BXD9 |
+ M |
+ 127 |
+ 9.7 |
+
+
+ | 86 |
+ 832 |
+ BXD39 |
+ F |
+ 99 |
+ 9.4 |
+
+
+ | 87 |
+ 833 |
+ BXD39 |
+ F |
+ 107 |
+ 9.3 |
+
+
+ | 88 |
+ 834 |
+ BXD60 |
+ F |
+ 107 |
+ 9.5 |
+
+
+ | 89 |
+ 836 |
+ BXD84 |
+ M |
+ 103 |
+ 9.7 |
+
+
+ | 90 |
+ 846 |
+ BXD39 |
+ M |
+ 63 |
+ 9.7 |
+
+
+ | 91 |
+ 847 |
+ BXD39 |
+ M |
+ 63 |
+ 9.8 |
+
+
+ | 92 |
+ 849 |
+ BXD20 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 93 |
+ 850 |
+ BXD20 |
+ M |
+ 70 |
+ 10 |
+
+
+ | 94 |
+ 851 |
+ BXD20 |
+ * |
+ 70 |
+ 9.5 |
+
+
+ | 95 |
+ 855 |
+ DBA/2J |
+ F |
+ 78 |
+ 9.7 |
+
+
+ | 96 |
+ 856 |
+ DBA/2J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 97 |
+ 857 |
+ DBA/2J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 98 |
+ 858 |
+ DBA/2J |
+ M |
+ 78 |
+ 9.9 |
+
+
+ | 99 |
+ 859 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 100 |
+ 860 |
+ C57BL/6J |
+ F |
+ 78 |
+ 10 |
+
+
+ | 101 |
+ 861 |
+ C57BL/6J |
+ M |
+ 78 |
+ 10 |
+
+
+ | 102 |
+ 862 |
+ C57BL/6J |
+ M |
+ 78 |
+ 9.6 |
+
+
+ | 103 |
+ EGE10907-0172_890_20844 |
+ BXD28 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 104 |
+ EGE10907-0173_891_20845 |
+ BXD28 |
+ M |
+ 75 |
+ 9.7 |
+
+
+ | 105 |
+ EGE10907-0174_892_20846 |
+ BXD28 |
+ F |
+ 75 |
+ 9.7 |
+
+
+ | 106 |
+ EGE10907-0176_895_20848 |
+ BXD33 |
+ M |
+ 75 |
+ 9.88 |
+
+
+ | 107 |
+ EGE10907-0177_896_20849 |
+ BXD33 |
+ F |
+ 75 |
+ 10 |
+
+
+ | 108 |
+ EGE10907-0178_897_20850 |
+ BXD33 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 109 |
+ EGE10907-0179_898_20851 |
+ BXD36 |
+ M |
+ 75 |
+ 9.4 |
+
+
+ | 110 |
+ EGE10907-0180_899_20852 |
+ BXD36 |
+ F |
+ 75 |
+ 9.5 |
+
+
+ | 111 |
+ EGE10907-0181_900_20853 |
+ BXD36 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 112 |
+ EGE10907-0182_910_20854 |
+ BXD27 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 113 |
+ EGE10907-0183_990_20855 |
+ BXD9 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 114 |
+ EGE10907-0184_991_20856 |
+ BXD16 |
+ F |
+ 113 |
+ 10 |
+
+
+ | 115 |
+ EGE10907-0185_992_20857 |
+ BXD16 |
+ M |
+ 113 |
+ 9 |
+
+
+ | 116 |
+ EGE10907-0186_993_20858 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 117 |
+ EGE10907-0187_994_20859 |
+ BXD27 |
+ F |
+ 96 |
+ 9.4 |
+
+
+ | 118 |
+ EGE10907-0188_996_20860 |
+ BXD48 |
+ F |
+ 98 |
+ 9.4 |
+
+
+ | 119 |
+ EGE10907-0189_997_20861 |
+ BXD73 |
+ M |
+ 106 |
+ 10 |
+
+
+ | 120 |
+ EGE10907-0190_999_20862 |
+ BXD11 |
+ F |
+ 121 |
+ 9.6 |
+
+
+ | 121 |
+ EGE10907-0191_100_20863 |
+ BXD11 |
+ F |
+ 121 |
+ 9.9 |
+
+
+ | 122 |
+ EGE10907-0192_1010_21276 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 123 |
+ EGE10907-0193_1011_21277 |
+ BXD13 |
+ M |
+ 69 |
+ 9.8 |
+
+
+ | 124 |
+ EGE10907-0194_1012_21278 |
+ BXD16 |
+ F |
+ 65 |
+ 10 |
+
+
+ | 125 |
+ EGE10907-0195_1015_21279 |
+ BXD16 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 126 |
+ EGE10907-0196_1019_21280 |
+ BXD33 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 127 |
+ EGE10907-0197_1020_21281 |
+ BXD36 |
+ M |
+ 78 |
+ 10 |
+
+
+ | 128 |
+ EGE10907-0198_1021_21282 |
+ BXD38 |
+ F |
+ 70 |
+ 9.8 |
+
+
+ | 129 |
+ EGE10907-0199_1022_21283 |
+ BXD38 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 130 |
+ EGE10907-0200_1023_21284 |
+ BXD38 |
+ M |
+ 70 |
+ 9.7 |
+
+
+ | 131 |
+ EGE10907-0201_1047_21285 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 132 |
+ EGE10907-0202_1048_21286 |
+ BXD11 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 133 |
+ EGE10907-0203_1049_21287 |
+ BXD38 |
+ M |
+ 77 |
+ 10 |
+
+
+ | 134 |
+ EGE10907-0204_1050_21288 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 135 |
+ EGE10907-0205_1051_21289 |
+ BXD73 |
+ F |
+ 70 |
+ 10 |
+
+
+ | 136 |
+ EGE10907-0206_1052_21290 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 137 |
+ EGE10907-0207_1053_21291 |
+ BXD86 |
+ F |
+ 69 |
+ 10 |
+
+
+ | 138 |
+ EGE10907-0208_1054_21292 |
+ BXD90 |
+ F |
+ 71 |
+ 10 |
+
+
+ | 139 |
+ EGE10907-0209_1055_21293 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 140 |
+ EGE10907-0210_1056_21294 |
+ BXD90 |
+ M |
+ 71 |
+ 10 |
+
+
+ | 141 |
+ EGE10907-0211_1148_21295 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 142 |
+ EGE10907-0212_1149_21296 |
+ BXD31 |
+ F |
+ 90 |
+ 10 |
+
+
+ | 143 |
+ EGE10907-0213_1150_21297 |
+ BXD31 |
+ M |
+ 90 |
+ 10 |
+
+
+ | 144 |
+ EGE10907-0214_1151_21298 |
+ BXD31 |
+ M |
+ 90 |
+ 9.9 |
+
+
+ | 145 |
+ EGE10907-0215_1152_21299 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 146 |
+ EGE10907-0216_21429 |
+ BXD42 |
+ F |
+ 83 |
+ 10 |
+
+
+ | 147 |
+ EGE10907-0217_21430 |
+ BXD42 |
+ M |
+ 83 |
+ 10 |
+
+
+ | 148 |
+ EGE10907-0218_21431 |
+ BXD42 |
+ M |
+ 83 |
+ 9.3 |
+
+
+ | 149 |
+ EGE10907-0219_21432 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 150 |
+ EGE10907-0220_21433 |
+ BXD50 |
+ F |
+ 92 |
+ 9.6 |
+
+
+ | 151 |
+ EGE10907-0221_21434 |
+ BXD50 |
+ F |
+ 92 |
+ 10 |
+
+
+ | 152 |
+ EGE10907-0222_21435 |
+ BXD1 |
+ M |
+ 73 |
+ 9.6 |
+
+
+ | 153 |
+ EGE10907-0223_21436 |
+ BXD13 |
+ F |
+ 71 |
+ 9.7 |
+
+
+ | 154 |
+ EGE10907-0224_21437 |
+ BXD1 |
+ M |
+ 71 |
+ 9.5 |
+
+
+ | 155 |
+ EGE10907-0225_21438 |
+ BXD13 |
+ F |
+ 71 |
+ 9.6 |
+
+
+ | 156 |
+ EGE10907-0226_21439 |
+ BXD43 |
+ F |
+ 85 |
+ 10 |
+
+
+ | 157 |
+ EGE10907-0227_21452 |
+ BXD43 |
+ F |
+ 85 |
+ 9.6 |
+
+
+ | 158 |
+ EGE10907-0229_21442 |
+ BXD43 |
+ M |
+ 85 |
+ 8.2 |
+
+
+ | 159 |
+ EGE10907-0230_21443 |
+ BXD50 |
+ M |
+ 69 |
+ 9.4 |
+
+
+ | 160 |
+ EGE10907-0231_21444 |
+ BXD1 |
+ F |
+ 68 |
+ 9.4 |
+
+
+ | 161 |
+ EGE10907-0232_21445 |
+ BXD1 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 162 |
+ EGE10907-0233_21446 |
+ BXD29 |
+ M |
+ 65 |
+ 9.5 |
+
+
+ | 163 |
+ EGE10907-0234_21447 |
+ BXD29 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 164 |
+ EGE10907-0235_21448 |
+ BXD75 |
+ F |
+ 68 |
+ 10 |
+
+
+ | 165 |
+ EGE10907-0236_21449 |
+ BXD75 |
+ M |
+ 68 |
+ 10 |
+
+
+ | 166 |
+ EGE10907-0237_21450 |
+ BXD96 |
+ F |
+ 67 |
+ 9.9 |
+
+
+ | 167 |
+ EGE10907-0238_21931 |
+ BXD99 |
+ M |
+ 71 |
+ 7.9 |
+
+
+ | 168 |
+ EGE10907-0239_21932 |
+ BXD99 |
+ M |
+ 71 |
+ 9.7 |
+
+
+ | 169 |
+ EGE10907-0240_21933 |
+ BXD67 |
+ F |
+ 68 |
+ 8.8 |
+
+
+ | 170 |
+ EGE10907-0241_21934 |
+ BXD67 |
+ F |
+ 68 |
+ 8.5 |
+
+
+ | 171 |
+ EGE10907-0242_21935 |
+ BXD67 |
+ M |
+ 68 |
+ 9.5 |
+
+
+ | 172 |
+ EGE10907-0243_21936 |
+ BXD67 |
+ M |
+ 68 |
+ 9.6 |
+
+
+ | 173 |
+ EGE10907-0244_21937 |
+ BXD6 |
+ F |
+ 68 |
+ 9.6 |
+
+
+ | 174 |
+ EGE10907-0245_21938 |
+ BXD12 |
+ M |
+ 82 |
+ 9.5 |
+
+
+ | 175 |
+ EGE10907-0246_21939 |
+ BXD60 |
+ F |
+ 72 |
+ 9.6 |
+
+
+ | 176 |
+ EGE10907-0247_21940 |
+ BXD65 |
+ F |
+ 75 |
+ 9.1 |
+
+
+ | 177 |
+ EGE10907-0248_21941 |
+ BXD75 |
+ F |
+ 69 |
+ 8.8 |
+
+
+ | 178 |
+ EGE10907-0249_21942_(MoGene-2_0-st) |
+ BXD75 |
+ M |
+ 69 |
+ 9.2 |
+
+
+ | 179 |
+ EGE10907-0250_21943 |
+ BXD8 |
+ F |
+ 97 |
+ 9.1 |
+
+
+ | 180 |
+ EGE10907-0251_21944 |
+ BXD85 |
+ F |
+ 79 |
+ 8.6 |
+
+
+ | 181 |
+ EGE10907-0252_21945 |
+ BXD85 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 182 |
+ EGE10907-0253_21946 |
+ BXD85 |
+ M |
+ 79 |
+ 9.4 |
+
+
+ | 183 |
+ EGE10907-0254_21947 |
+ BXD102 |
+ M |
+ 94 |
+ 8.6 |
+
+
+ | 184 |
+ EGE10907-0255_21948 |
+ BXD99 |
+ F |
+ 83 |
+ 9 |
+
+
+ | 185 |
+ EGE10907-0256_21949 |
+ BXD69 |
+ F |
+ 68 |
+ 9 |
+
+
+ | 186 |
+ EGE10907-0257_21950 |
+ BXD84 |
+ F |
+ 74 |
+ 9.5 |
+
+
+ | 187 |
+ EGE10907-0258_21951 |
+ BXD84 |
+ F |
+ 74 |
+ 9.4 |
+
+
+ | 188 |
+ EGE10907-0259_21952 |
+ BXD84 |
+ M |
+ 74 |
+ 8.6 |
+
+
+ | 189 |
+ EGE10907-0260_21451 |
+ BXD96 |
+ M |
+ 67 |
+ 9.2 |
+
+
+ | 190 |
+ EGE10907-0261_21452 |
+ BXD99 |
+ F |
+ 71 |
+ 8.9 |
+
+
+ | 191 |
+ EGE10907-0262_21931 |
+ BXD6 |
+ F |
+ 66 |
+ 9.4 |
+
+
+ | 192 |
+ EGE10907-0263_21932 |
+ BXD14 |
+ F |
+ 69 |
+ 8.5 |
+
+
+ | 193 |
+ EGE10907-0264_21933 |
+ BXD34 |
+ M |
+ 79 |
+ 9.1 |
+
+
+ | 194 |
+ EGE10907-0265_21934 |
+ BXD34 |
+ M |
+ 79 |
+ 9.9 |
+
+
+ | 195 |
+ EGE10907-0266_21935 |
+ BXD40 |
+ F |
+ 75 |
+ 9.6 |
+
+
+ | 196 |
+ EGE10907-0267_21936 |
+ BXD40 |
+ M |
+ 78 |
+ 9.7 |
+
+
+ | 197 |
+ EGE10907-0268_21937 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 198 |
+ EGE10907-0269_21938 |
+ BXD56 |
+ F |
+ 72 |
+ 9.7 |
+
+
+ | 199 |
+ EGE10907-0270_21939 |
+ BXD56 |
+ M |
+ 72 |
+ 9.6 |
+
+
+ | 200 |
+ EGE10907-0271_21940 |
+ BXD56 |
+ M |
+ 72 |
+ 9.4 |
+
+
+ | 201 |
+ EGE10907-0272_21941 |
+ BXD71 |
+ F |
+ 72 |
+ 9.9 |
+
+
+ | 202 |
+ EGE10907-0273_21942 |
+ BXD71 |
+ F |
+ 75 |
+ 9.4 |
+
+
+ | 203 |
+ EGE10907-0274_21943 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 204 |
+ EGE10907-0275_21944 |
+ BXD71 |
+ M |
+ 75 |
+ 10 |
+
+
+ | 205 |
+ EGE10907-0276_21945 |
+ BXD27 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 206 |
+ EGE10907-0277_21946 |
+ BXD15 |
+ M |
+ 65 |
+ 10 |
+
+
+ | 207 |
+ EGE10907-0278_21947 |
+ BXD20 |
+ F |
+ 125 |
+ 10 |
+
+
+ | 208 |
+ EGE10907-0279_21948 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 209 |
+ EGE10907-0280_21949 |
+ BXD29 |
+ F |
+ 77 |
+ 10 |
+
+
+ | 210 |
+ EGE10907-0281_21950 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 211 |
+ EGE10907-0282_21951 |
+ BXD34 |
+ F |
+ 74 |
+ 10 |
+
+
+ | 212 |
+ EGE10907-0283_21952 |
+ BXD85 |
+ F |
+ 87 |
+ 10 |
+
+
+ | 213 |
+ EGE10907-0284_21451 |
+ BXD43 |
+ M |
+ 75 |
+ 9.8 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Oncretmogene2_0413/citation.rtf b/general/datasets/Oncretmogene2_0413/citation.rtf
new file mode 100644
index 0000000..d84717d
--- /dev/null
+++ b/general/datasets/Oncretmogene2_0413/citation.rtf
@@ -0,0 +1,3 @@
+Related Publications: Geisert EE, Lu L, Freeman-Anderson NE, Templeton JP, Nassr M, Wang X, Gu W, Jiao Y, Williams RW.:Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice. Molecular Vision 2009 Aug 31;15:1730-63, (Link) Geisert EE, Jr., Williams RW: The Mouse Eye Transcriptome: Cellular Signatures, Molecular Networks, and Candidate Genes for Human Disease. In Eye, Retina, and Visual System of the Mouse. Edited by Chalupa LM, Williams RW. Cambridge: The MIT Press; 2008:659-674 Peirce JL, Lu L, Gu J, Silver LM, Williams RW: A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet 2004, 5:7. (Link) Templeton JP, Nassr M, Vazquez-Chona F, Freeman-Anderson NE, Orr WE, Williams RW, Geisert EE: Differential response of C57BL/6J mouse and DBA/2J mouse to optic nerve crush. BMC Neurosci. 2009, July 30;10:90.
+
+Other Data Sets Users of these mouse retina data may also find the following complementary resources useful: NEIBank collection of ESTs and SAGE data. RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases.
diff --git a/general/datasets/Oncretmogene2_0413/contributors.rtf b/general/datasets/Oncretmogene2_0413/contributors.rtf
new file mode 100644
index 0000000..11fece2
--- /dev/null
+++ b/general/datasets/Oncretmogene2_0413/contributors.rtf
@@ -0,0 +1 @@
+Eldon E. Geisert, Lu Lu, XiangDi Wang, Justin P. Templeton and Robert W. Williams.
diff --git a/general/datasets/Oncretmogene2_0413/experiment-type.rtf b/general/datasets/Oncretmogene2_0413/experiment-type.rtf
new file mode 100644
index 0000000..2d74654
--- /dev/null
+++ b/general/datasets/Oncretmogene2_0413/experiment-type.rtf
@@ -0,0 +1,3 @@
+Dissecting and preparing eyes for RNA extraction
+
+RNA was extracted from retinas using the RNeasy Mini Kit (Qiagen) and the Quiagen Qiacube. For RNA amplification and cDNA preparation we used the Ambion® WT Expression Kit (Life Technologies Cat#: 4411974). For Fragmentation and Labeling the WT Terminal Labeling Kit from Affymetrix (Cat#: 900671) was used.
\ No newline at end of file
diff --git a/general/datasets/Oncretmogene2_0413/platform.rtf b/general/datasets/Oncretmogene2_0413/platform.rtf
new file mode 100644
index 0000000..19fc38c
--- /dev/null
+++ b/general/datasets/Oncretmogene2_0413/platform.rtf
@@ -0,0 +1 @@
+The Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. Nonetheless, there is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs.
diff --git a/general/datasets/Oncretmogene2_0413/processing.rtf b/general/datasets/Oncretmogene2_0413/processing.rtf
new file mode 100644
index 0000000..a7b767e
--- /dev/null
+++ b/general/datasets/Oncretmogene2_0413/processing.rtf
@@ -0,0 +1 @@
+Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well-balanced sample of males and females, in general without within-strain-by-sex replication.
diff --git a/general/datasets/Oncretmogene2_0413/summary.rtf b/general/datasets/Oncretmogene2_0413/summary.rtf
new file mode 100644
index 0000000..96a87e5
--- /dev/null
+++ b/general/datasets/Oncretmogene2_0413/summary.rtf
@@ -0,0 +1 @@
+The DoD dataset was constructed using the Affymetrics GeneChip® Mouse Gene 2.0 ST microarrays. This relatively recent microarray was specifically designed to represent the whole-transcriptome. It includes probes to measure mRNA, long intergenic non-coding RNAs and microRNAs. Researchers have identified many transcripts in the mouse genome that do not have protein coding potential. Most of these non-coding RNAs have little functional annotation. There is considerable evidence that these non-coding RNAs play important roles in development of the retina and the progression of disease. The coverage in the new ST 2.0 array includes over 28,000 coding transcripts and over 7,000 non-coding transcripts. There are also probes on the array covering 590 microRNAs. This is RMA expression data that has been normalized using what we call a 2z+8 scale, but without special correction for batch effects. The data for each strains were computed as the mean of four samples per strain. Expression values on a log2 scale range from 3.77 to 14.62, a nominal range of approximately 3600-fold. After taking the log2 of the original non-logged expression estimates, we convert data within an array to a z score. We then multiply the z score by 2. Finally, we add 8 units to ensure that no values are negative. The result is a scale with a mean of 8 units and a standard deviation of 2 units. A two-fold difference in expression is equivalent roughly to 1 unit on this scale.
diff --git a/general/datasets/Oncretmogene2_0413/tissue.rtf b/general/datasets/Oncretmogene2_0413/tissue.rtf
new file mode 100644
index 0000000..056d7eb
--- /dev/null
+++ b/general/datasets/Oncretmogene2_0413/tissue.rtf
@@ -0,0 +1 @@
+Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Retinas were removed immediately and placed in RiboLock (RiboLock: Thermo Scientific RiboLock RNase #EO0381 40U/µl 2500U) at room temperature. Individual retinas from the mouse were stored in each tube. RNA was isolated using a Qiacube with the resultant RIN scores ranging from 8.5 to 10.0.
diff --git a/general/datasets/Oxukhs_ilmhipp_ri0510/cases.rtf b/general/datasets/Oxukhs_ilmhipp_ri0510/cases.rtf
new file mode 100644
index 0000000..d216153
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmhipp_ri0510/cases.rtf
@@ -0,0 +1 @@
+HS Northport stock (see https://www.nature.com/articles/ng1840) descended from eight inbred progenitor strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6J, DBA/2J and LP/J). For details, please see Demarest, K., Koyner, J., McCaughran, J. Jr., Cipp, L. & Hitzemann, R. Further characterization and high-resolution mapping of quantitative trait loci for ethanol-induced locomotor activity. Behav. Genet. 31, 79–91 (2001).
diff --git a/general/datasets/Oxukhs_ilmhipp_ri0510/citation.rtf b/general/datasets/Oxukhs_ilmhipp_ri0510/citation.rtf
new file mode 100644
index 0000000..4b2926f
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmhipp_ri0510/citation.rtf
@@ -0,0 +1,5 @@
+Key Citation: Huang GJ, Shifman S, Valdar W, Johannesson M, Yalcin B, Taylor MS, Taylor JM, Mott R, Flint J (2009) High resolution mapping of expression QTLs in heterogeneous stock mice in multiple tissues. Genome Res 19:1133-1140 PubMed 19376938
+
+Contact: Richard Mott. Email: Richard.Mott at well.ox.ac.uk University of Oxford
+
+Data entered by A. Centeno on May 20, 2010
diff --git a/general/datasets/Oxukhs_ilmhipp_ri0510/experiment-type.rtf b/general/datasets/Oxukhs_ilmhipp_ri0510/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmhipp_ri0510/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Oxukhs_ilmhipp_ri0510/platform.rtf b/general/datasets/Oxukhs_ilmhipp_ri0510/platform.rtf
new file mode 100644
index 0000000..c8db2c0
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmhipp_ri0510/platform.rtf
@@ -0,0 +1 @@
+Array design: A-MEXP-533 - Illumina Mouse-6 v1 Expression BeadChip
diff --git a/general/datasets/Oxukhs_ilmhipp_ri0510/summary.rtf b/general/datasets/Oxukhs_ilmhipp_ri0510/summary.rtf
new file mode 100644
index 0000000..5b53e35
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmhipp_ri0510/summary.rtf
@@ -0,0 +1 @@
+A proportion of the genetic variants underlying complex phenotypes do so through their effects on gene expression, so an important challenge in complex trait analysis is to discover the genetic basis for the variation in transcript abundance. So far, the potential of mapping both quantitative trait loci (QTLs) and expression quantitative trait loci (eQTLs) in rodents has been limited by the low mapping resolution inherent in crosses between inbred strains. We provide a megabase resolution map of thousands of eQTLs in hippocampus, lung, and liver samples from heterogeneous stock (HS) mice in which 843 QTLs have also been mapped at megabase resolution. We exploit dense mouse SNP data to show that artifacts due to allele-specific hybridization occur in _30% of the cis-acting eQTLs and, by comparison with exon expression data, we show that alternative splicing of the 3_ end of the genes accounts for <1% of cis-acting eQTLs. Approximately one third of cis-acting eQTLs and one half of trans-acting eQTLs are tissue specific. We have created an important systems biology resource for the genetic analysis of complex traits in a key model organism.
diff --git a/general/datasets/Oxukhs_ilmliver_ri0510/cases.rtf b/general/datasets/Oxukhs_ilmliver_ri0510/cases.rtf
new file mode 100644
index 0000000..fcc2f2d
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmliver_ri0510/cases.rtf
@@ -0,0 +1 @@
+HS Northport stock (see https://www.nature.com/articles/ng1840) descended from eight inbred progenitor strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6J, DBA/2J and LP/J). For details, please see Demarest, K., Koyner, J., McCaughran, J. Jr., Cipp, L. & Hitzemann, R. Further characterization and high-resolution mapping of quantitative trait loci for ethanol-induced locomotor activity. Behav. Genet.31, 79–91 (2001).
diff --git a/general/datasets/Oxukhs_ilmliver_ri0510/citation.rtf b/general/datasets/Oxukhs_ilmliver_ri0510/citation.rtf
new file mode 100644
index 0000000..82113fe
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmliver_ri0510/citation.rtf
@@ -0,0 +1,5 @@
+Citations: High resolution mapping of expression QTLs in heterogeneous stock mice in multiple tissues. Huang GJ, Shifman S, Valdar W, Johannesson M, Yalcin B, Taylor MS, Taylor JM, Mott R, Flint J. Genome Res 19(6):1133-40 (Genome Res), PubMed 19376938
+
+Contact: Richard Mott. Email: Richard.Mott at well.ox.ac.uk University of Oxford
+
+Data entered by A. Centeno on May 20, 2010
diff --git a/general/datasets/Oxukhs_ilmliver_ri0510/experiment-type.rtf b/general/datasets/Oxukhs_ilmliver_ri0510/experiment-type.rtf
new file mode 100644
index 0000000..5fac908
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmliver_ri0510/experiment-type.rtf
@@ -0,0 +1 @@
+See http://genome.cshlp.org/content/19/6/1133.long
\ No newline at end of file
diff --git a/general/datasets/Oxukhs_ilmliver_ri0510/platform.rtf b/general/datasets/Oxukhs_ilmliver_ri0510/platform.rtf
new file mode 100644
index 0000000..add8a75
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmliver_ri0510/platform.rtf
@@ -0,0 +1 @@
+Organism: Mus musculus. Tissue: Liver. Array design: A-MEXP-533 - Illumina Mouse-6 v1 Expression BeadChip
diff --git a/general/datasets/Oxukhs_ilmliver_ri0510/summary.rtf b/general/datasets/Oxukhs_ilmliver_ri0510/summary.rtf
new file mode 100644
index 0000000..5b53e35
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmliver_ri0510/summary.rtf
@@ -0,0 +1 @@
+A proportion of the genetic variants underlying complex phenotypes do so through their effects on gene expression, so an important challenge in complex trait analysis is to discover the genetic basis for the variation in transcript abundance. So far, the potential of mapping both quantitative trait loci (QTLs) and expression quantitative trait loci (eQTLs) in rodents has been limited by the low mapping resolution inherent in crosses between inbred strains. We provide a megabase resolution map of thousands of eQTLs in hippocampus, lung, and liver samples from heterogeneous stock (HS) mice in which 843 QTLs have also been mapped at megabase resolution. We exploit dense mouse SNP data to show that artifacts due to allele-specific hybridization occur in _30% of the cis-acting eQTLs and, by comparison with exon expression data, we show that alternative splicing of the 3_ end of the genes accounts for <1% of cis-acting eQTLs. Approximately one third of cis-acting eQTLs and one half of trans-acting eQTLs are tissue specific. We have created an important systems biology resource for the genetic analysis of complex traits in a key model organism.
diff --git a/general/datasets/Oxukhs_ilmlung_ri0510/cases.rtf b/general/datasets/Oxukhs_ilmlung_ri0510/cases.rtf
new file mode 100644
index 0000000..fcc2f2d
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmlung_ri0510/cases.rtf
@@ -0,0 +1 @@
+HS Northport stock (see https://www.nature.com/articles/ng1840) descended from eight inbred progenitor strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6J, DBA/2J and LP/J). For details, please see Demarest, K., Koyner, J., McCaughran, J. Jr., Cipp, L. & Hitzemann, R. Further characterization and high-resolution mapping of quantitative trait loci for ethanol-induced locomotor activity. Behav. Genet.31, 79–91 (2001).
diff --git a/general/datasets/Oxukhs_ilmlung_ri0510/citation.rtf b/general/datasets/Oxukhs_ilmlung_ri0510/citation.rtf
new file mode 100644
index 0000000..82113fe
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmlung_ri0510/citation.rtf
@@ -0,0 +1,5 @@
+Citations: High resolution mapping of expression QTLs in heterogeneous stock mice in multiple tissues. Huang GJ, Shifman S, Valdar W, Johannesson M, Yalcin B, Taylor MS, Taylor JM, Mott R, Flint J. Genome Res 19(6):1133-40 (Genome Res), PubMed 19376938
+
+Contact: Richard Mott. Email: Richard.Mott at well.ox.ac.uk University of Oxford
+
+Data entered by A. Centeno on May 20, 2010
diff --git a/general/datasets/Oxukhs_ilmlung_ri0510/platform.rtf b/general/datasets/Oxukhs_ilmlung_ri0510/platform.rtf
new file mode 100644
index 0000000..56e6161
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmlung_ri0510/platform.rtf
@@ -0,0 +1 @@
+Organism: Mus musculus. Tissue: Lung. Array design: A-MEXP-533 - Illumina Mouse-6 v1 Expression BeadChip
diff --git a/general/datasets/Oxukhs_ilmlung_ri0510/summary.rtf b/general/datasets/Oxukhs_ilmlung_ri0510/summary.rtf
new file mode 100644
index 0000000..5b53e35
--- /dev/null
+++ b/general/datasets/Oxukhs_ilmlung_ri0510/summary.rtf
@@ -0,0 +1 @@
+A proportion of the genetic variants underlying complex phenotypes do so through their effects on gene expression, so an important challenge in complex trait analysis is to discover the genetic basis for the variation in transcript abundance. So far, the potential of mapping both quantitative trait loci (QTLs) and expression quantitative trait loci (eQTLs) in rodents has been limited by the low mapping resolution inherent in crosses between inbred strains. We provide a megabase resolution map of thousands of eQTLs in hippocampus, lung, and liver samples from heterogeneous stock (HS) mice in which 843 QTLs have also been mapped at megabase resolution. We exploit dense mouse SNP data to show that artifacts due to allele-specific hybridization occur in _30% of the cis-acting eQTLs and, by comparison with exon expression data, we show that alternative splicing of the 3_ end of the genes accounts for <1% of cis-acting eQTLs. Approximately one third of cis-acting eQTLs and one half of trans-acting eQTLs are tissue specific. We have created an important systems biology resource for the genetic analysis of complex traits in a key model organism.
diff --git a/general/datasets/PGenRatBrn_rna_0520/acknowledgment.rtf b/general/datasets/PGenRatBrn_rna_0520/acknowledgment.rtf
deleted file mode 100644
index b5348f4..0000000
--- a/general/datasets/PGenRatBrn_rna_0520/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Data were generated with funds provided by NIAAA, NIDA, the Banbury Fund, Czech Academy of Sciences, and The National BioResource Project-Rat. Dr. Michal Pravenec of the Czech Academy of Sciences kindly provided the tissues from the HXB/BXH recombinant inbred panel. Dr. Masahide Asano of the University of Kyoto kindly provided tissues from the F344/Stm and LE/Stm strains. Dr. Melinda Dwinell will be providing tissues for many of the remaining HRDP strains. We would like to thank Spencer Mahaffey, Jennifer Mahaffey, Yinni Yu, Seija Tililanen, Lauren Vanderlinden, and Harry Smith for help with extracting RNA, generating libraries, and processing data. We would also like to acknowledge the support of UNLV National Supercomputing Institute (UNLV NSI) by providing access to supercomputing resources to support analysis of sequencing data.
diff --git a/general/datasets/PGenRatBrn_rna_0520/cases.rtf b/general/datasets/PGenRatBrn_rna_0520/cases.rtf
deleted file mode 100644
index 022c897..0000000
--- a/general/datasets/PGenRatBrn_rna_0520/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-For this data set, a subset of the Hybrid Rat Diversity Panel (HRDP) was used that included 30 HXB/BXH recombinant inbred strains and 15 classic inbred strains for a total of 45 inbred strains. Male rats at the age of 90 days were used for this study. The animals from the 30 RI strains and the 2 progenitor strains of the HXB/BXH RI panel (SHR/OlaIpcv and BN-Lx/Cub) were bred and maintained at the Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic. The 11 classic inbred strains were purchased from US Vendors (either Charles River or Envigo) and shipped to the University of Colorado Anschutz Medical Campus where they were acclimated prior to sacrifice. The remaining 2 classic inbred strains are the progenitor strains of the LEXF/FXLE RI panel and were bred and maintained at the National BioResource Project for the Rat in Japan. In Colorado, rats were sacrificed by rapid CO2 exposure. In the Czech Republic, rats were sacrificed by cervical dislocation. All experiments involving the harvesting of whole brain of the HXB/BXH RI panel and two progenitor strains were performed in accordance with the Animal Protection Law of the Czech Republic and were approved by the Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague. All experiments involving the harvesting of whole brain of the 11 classic inbred strains maintained at the University of Colorado Anschutz Medical Campus were approved by the Institutional Animal Care and Use Committee of the University of Colorado Anschutz Medical Campus and were performed in accordance with the guidelines in the NIH Guide for the Care and Use of Laboratory Animals. Animal experiments involving the F344/Stm and LE/Stm strains were conducted in accordance with the Fundamental Guidelines for Proper Conduct of Animal Experiment and Related Activities in Academic Research Institutions under the jurisdiction of the Ministry of Education, Culture, Sports, Science and Technology of Japan, and were approved by the Committee on Animal Experimentation at Kyoto University, Japan.
diff --git a/general/datasets/PGenRatBrn_rna_0520/experiment-design.rtf b/general/datasets/PGenRatBrn_rna_0520/experiment-design.rtf
deleted file mode 100644
index 3ff2342..0000000
--- a/general/datasets/PGenRatBrn_rna_0520/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Predisposition database. RNA expression levels were measured on rats that had not been exposed to any type of intervention (e.g., alcohol, drugs, stress).
diff --git a/general/datasets/PGenRatBrn_rna_0520/platform.rtf b/general/datasets/PGenRatBrn_rna_0520/platform.rtf
deleted file mode 100644
index da38d8b..0000000
--- a/general/datasets/PGenRatBrn_rna_0520/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Total RNA was isolated from 3 biological replicates of each of the HRDP v5 strains using QIAzol (Qiagen, Valencia, CA, USA).The RNAeasy Plus Universal Midi Kit (Qiagen) was used to separate long (>200 nt) and short (<200 nt, miRNA-enriched) fractions. The long RNA fraction was purified using the RNeasy Mini Kit (Qiagen). Four microliters of a 1:100 dilution of either ERCC Spikeâ€In Mix 1 or Mix 2 (Thermo Fisher Scientific, Wilmington, DE) was added to each extracted RNA sample. Sequencing libraries for the long RNA fraction were constructed using the Illumina TruSeq Stranded Total RNA Sample Preparation Kit with Ribo-Zero ribosomal RNA reduction chemistry (Illumina) in accordance with the manufacturer’s instructions. An Agilent Technologies Bioanalyzer 2100 was utilized to assess sequencing library quality. A loading control was included in each sequencing batch. The loading control was a library generated from an SHR animal. Samples were sequenced (depending on batch either 2X100 or 2x150 paired end reads) on an Ilumina sequencer.
diff --git a/general/datasets/PGenRatBrn_rna_0520/processing.rtf b/general/datasets/PGenRatBrn_rna_0520/processing.rtf
deleted file mode 100644
index 4c9da95..0000000
--- a/general/datasets/PGenRatBrn_rna_0520/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Prior to alignment, reads were demultiplexed and read fragments were trimmed for adaptors and for quality using Cutadapt (version 1.9.1;(Martin, 2011)). Reads were eliminated if the trimmed length of either read fragment was <20 nucleotides. Next, bowtie2(v 2.2.6) (4) was used to align reads to ribosomal RNA, and the unmapped reads were retained. These will be referred to as “cleaned” reads. The RNA-Seq Expectation Maximization (RSEM v1.2.31) algorithm (Li and Dewey 2011) was used to estimate the number of aligned reads for individual Ensembl transcripts (version 96). The number of reads aligned to each Ensembl gene was calculated as the sum of the number of reads aligned to individual Ensembl transcripts annotated to that gene.
-
-Prior to normalization and transformation, a detection above background filter was applied where we required a gene to have at least 2/3 of the samples have 1 count or more to be considered expressed above background. All genes that did not pass this detection above background criteria were removed. Count values were normalized using RUVg (PMID: 25150836) and transformed using the regularized log function (PMID: 25516281).
diff --git a/general/datasets/PGenRatBrn_rna_0520/specifics.rtf b/general/datasets/PGenRatBrn_rna_0520/specifics.rtf
deleted file mode 100644
index f98e245..0000000
--- a/general/datasets/PGenRatBrn_rna_0520/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Non zeros included.
\ No newline at end of file
diff --git a/general/datasets/PGenRatBrn_rna_0520/summary.rtf b/general/datasets/PGenRatBrn_rna_0520/summary.rtf
deleted file mode 100644
index a70b10f..0000000
--- a/general/datasets/PGenRatBrn_rna_0520/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set was generated as part of the RGAP project funded by NIAAA (R24 AA013162; MPI – Tabakoff, Hoffman, Saba) at the University of Colorado Anschutz Medical Campus. The processing of the RNA-Seq data was also supported by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223; MPI – Williams, Saba). These data represent the RNA expression levels of Ensembl genes in brain. Ribosomal RNA depleted total RNA was used to generate paired end libraries. Levels were estimated in 45 (version 5) strains of the Hybrid Rat Diversity Panel (HRDP) including 30 HXB/BXH recombinant inbred strain and 15 classic inbred strains. Two to three biological replicates per strain were included in the strain-level means. Male rats were used for all analyses.
diff --git a/general/datasets/PGenRatBrn_rna_0520/tissue.rtf b/general/datasets/PGenRatBrn_rna_0520/tissue.rtf
deleted file mode 100644
index 732bdc1..0000000
--- a/general/datasets/PGenRatBrn_rna_0520/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Upon sacrifice, brains (including cerebellum and brain stem) were rapidly removed, sectioned sagittally into two hemispheres, and stored in liquid nitrogen. Each hemisphere was stored separately at -80â°C until used for RNA extraction. Tissues from the Czech Republic and Japan were shipped on dry ice to the University of Colorado Anschutz Medical Campus for RNA extraction and cDNA library preparation
diff --git a/general/datasets/PGenRatBrn_rna_z_0520/acknowledgment.rtf b/general/datasets/PGenRatBrn_rna_z_0520/acknowledgment.rtf
deleted file mode 100644
index b5348f4..0000000
--- a/general/datasets/PGenRatBrn_rna_z_0520/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Data were generated with funds provided by NIAAA, NIDA, the Banbury Fund, Czech Academy of Sciences, and The National BioResource Project-Rat. Dr. Michal Pravenec of the Czech Academy of Sciences kindly provided the tissues from the HXB/BXH recombinant inbred panel. Dr. Masahide Asano of the University of Kyoto kindly provided tissues from the F344/Stm and LE/Stm strains. Dr. Melinda Dwinell will be providing tissues for many of the remaining HRDP strains. We would like to thank Spencer Mahaffey, Jennifer Mahaffey, Yinni Yu, Seija Tililanen, Lauren Vanderlinden, and Harry Smith for help with extracting RNA, generating libraries, and processing data. We would also like to acknowledge the support of UNLV National Supercomputing Institute (UNLV NSI) by providing access to supercomputing resources to support analysis of sequencing data.
diff --git a/general/datasets/PGenRatBrn_rna_z_0520/cases.rtf b/general/datasets/PGenRatBrn_rna_z_0520/cases.rtf
deleted file mode 100644
index 022c897..0000000
--- a/general/datasets/PGenRatBrn_rna_z_0520/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-For this data set, a subset of the Hybrid Rat Diversity Panel (HRDP) was used that included 30 HXB/BXH recombinant inbred strains and 15 classic inbred strains for a total of 45 inbred strains. Male rats at the age of 90 days were used for this study. The animals from the 30 RI strains and the 2 progenitor strains of the HXB/BXH RI panel (SHR/OlaIpcv and BN-Lx/Cub) were bred and maintained at the Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic. The 11 classic inbred strains were purchased from US Vendors (either Charles River or Envigo) and shipped to the University of Colorado Anschutz Medical Campus where they were acclimated prior to sacrifice. The remaining 2 classic inbred strains are the progenitor strains of the LEXF/FXLE RI panel and were bred and maintained at the National BioResource Project for the Rat in Japan. In Colorado, rats were sacrificed by rapid CO2 exposure. In the Czech Republic, rats were sacrificed by cervical dislocation. All experiments involving the harvesting of whole brain of the HXB/BXH RI panel and two progenitor strains were performed in accordance with the Animal Protection Law of the Czech Republic and were approved by the Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague. All experiments involving the harvesting of whole brain of the 11 classic inbred strains maintained at the University of Colorado Anschutz Medical Campus were approved by the Institutional Animal Care and Use Committee of the University of Colorado Anschutz Medical Campus and were performed in accordance with the guidelines in the NIH Guide for the Care and Use of Laboratory Animals. Animal experiments involving the F344/Stm and LE/Stm strains were conducted in accordance with the Fundamental Guidelines for Proper Conduct of Animal Experiment and Related Activities in Academic Research Institutions under the jurisdiction of the Ministry of Education, Culture, Sports, Science and Technology of Japan, and were approved by the Committee on Animal Experimentation at Kyoto University, Japan.
diff --git a/general/datasets/PGenRatBrn_rna_z_0520/experiment-design.rtf b/general/datasets/PGenRatBrn_rna_z_0520/experiment-design.rtf
deleted file mode 100644
index 3ff2342..0000000
--- a/general/datasets/PGenRatBrn_rna_z_0520/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Predisposition database. RNA expression levels were measured on rats that had not been exposed to any type of intervention (e.g., alcohol, drugs, stress).
diff --git a/general/datasets/PGenRatBrn_rna_z_0520/platform.rtf b/general/datasets/PGenRatBrn_rna_z_0520/platform.rtf
deleted file mode 100644
index da38d8b..0000000
--- a/general/datasets/PGenRatBrn_rna_z_0520/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Total RNA was isolated from 3 biological replicates of each of the HRDP v5 strains using QIAzol (Qiagen, Valencia, CA, USA).The RNAeasy Plus Universal Midi Kit (Qiagen) was used to separate long (>200 nt) and short (<200 nt, miRNA-enriched) fractions. The long RNA fraction was purified using the RNeasy Mini Kit (Qiagen). Four microliters of a 1:100 dilution of either ERCC Spikeâ€In Mix 1 or Mix 2 (Thermo Fisher Scientific, Wilmington, DE) was added to each extracted RNA sample. Sequencing libraries for the long RNA fraction were constructed using the Illumina TruSeq Stranded Total RNA Sample Preparation Kit with Ribo-Zero ribosomal RNA reduction chemistry (Illumina) in accordance with the manufacturer’s instructions. An Agilent Technologies Bioanalyzer 2100 was utilized to assess sequencing library quality. A loading control was included in each sequencing batch. The loading control was a library generated from an SHR animal. Samples were sequenced (depending on batch either 2X100 or 2x150 paired end reads) on an Ilumina sequencer.
diff --git a/general/datasets/PGenRatBrn_rna_z_0520/processing.rtf b/general/datasets/PGenRatBrn_rna_z_0520/processing.rtf
deleted file mode 100644
index 4c9da95..0000000
--- a/general/datasets/PGenRatBrn_rna_z_0520/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Prior to alignment, reads were demultiplexed and read fragments were trimmed for adaptors and for quality using Cutadapt (version 1.9.1;(Martin, 2011)). Reads were eliminated if the trimmed length of either read fragment was <20 nucleotides. Next, bowtie2(v 2.2.6) (4) was used to align reads to ribosomal RNA, and the unmapped reads were retained. These will be referred to as “cleaned” reads. The RNA-Seq Expectation Maximization (RSEM v1.2.31) algorithm (Li and Dewey 2011) was used to estimate the number of aligned reads for individual Ensembl transcripts (version 96). The number of reads aligned to each Ensembl gene was calculated as the sum of the number of reads aligned to individual Ensembl transcripts annotated to that gene.
-
-Prior to normalization and transformation, a detection above background filter was applied where we required a gene to have at least 2/3 of the samples have 1 count or more to be considered expressed above background. All genes that did not pass this detection above background criteria were removed. Count values were normalized using RUVg (PMID: 25150836) and transformed using the regularized log function (PMID: 25516281).
diff --git a/general/datasets/PGenRatBrn_rna_z_0520/specifics.rtf b/general/datasets/PGenRatBrn_rna_z_0520/specifics.rtf
deleted file mode 100644
index edb176d..0000000
--- a/general/datasets/PGenRatBrn_rna_z_0520/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-zeros included
\ No newline at end of file
diff --git a/general/datasets/PGenRatBrn_rna_z_0520/summary.rtf b/general/datasets/PGenRatBrn_rna_z_0520/summary.rtf
deleted file mode 100644
index a70b10f..0000000
--- a/general/datasets/PGenRatBrn_rna_z_0520/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set was generated as part of the RGAP project funded by NIAAA (R24 AA013162; MPI – Tabakoff, Hoffman, Saba) at the University of Colorado Anschutz Medical Campus. The processing of the RNA-Seq data was also supported by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223; MPI – Williams, Saba). These data represent the RNA expression levels of Ensembl genes in brain. Ribosomal RNA depleted total RNA was used to generate paired end libraries. Levels were estimated in 45 (version 5) strains of the Hybrid Rat Diversity Panel (HRDP) including 30 HXB/BXH recombinant inbred strain and 15 classic inbred strains. Two to three biological replicates per strain were included in the strain-level means. Male rats were used for all analyses.
diff --git a/general/datasets/PGenRatBrn_rna_z_0520/tissue.rtf b/general/datasets/PGenRatBrn_rna_z_0520/tissue.rtf
deleted file mode 100644
index 732bdc1..0000000
--- a/general/datasets/PGenRatBrn_rna_z_0520/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Upon sacrifice, brains (including cerebellum and brain stem) were rapidly removed, sectioned sagittally into two hemispheres, and stored in liquid nitrogen. Each hemisphere was stored separately at -80â°C until used for RNA extraction. Tissues from the Czech Republic and Japan were shipped on dry ice to the University of Colorado Anschutz Medical Campus for RNA extraction and cDNA library preparation
diff --git a/general/datasets/PGenRatLiv_rna_0520/acknowledgment.rtf b/general/datasets/PGenRatLiv_rna_0520/acknowledgment.rtf
deleted file mode 100644
index b5348f4..0000000
--- a/general/datasets/PGenRatLiv_rna_0520/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Data were generated with funds provided by NIAAA, NIDA, the Banbury Fund, Czech Academy of Sciences, and The National BioResource Project-Rat. Dr. Michal Pravenec of the Czech Academy of Sciences kindly provided the tissues from the HXB/BXH recombinant inbred panel. Dr. Masahide Asano of the University of Kyoto kindly provided tissues from the F344/Stm and LE/Stm strains. Dr. Melinda Dwinell will be providing tissues for many of the remaining HRDP strains. We would like to thank Spencer Mahaffey, Jennifer Mahaffey, Yinni Yu, Seija Tililanen, Lauren Vanderlinden, and Harry Smith for help with extracting RNA, generating libraries, and processing data. We would also like to acknowledge the support of UNLV National Supercomputing Institute (UNLV NSI) by providing access to supercomputing resources to support analysis of sequencing data.
diff --git a/general/datasets/PGenRatLiv_rna_0520/cases.rtf b/general/datasets/PGenRatLiv_rna_0520/cases.rtf
deleted file mode 100644
index 69ff672..0000000
--- a/general/datasets/PGenRatLiv_rna_0520/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-For this data set, a subset of the Hybrid Rat Diversity Panel (HRDP) was used that included 30 HXB/BXH recombinant inbred strains and 15 classic inbred strains for a total of 45 inbred strains. Male rats at the age of 90 days were used for this study. The animals from the 30 RI strains and the 2 progenitor strains of the HXB/BXH RI panel (SHR/OlaIpcv and BN-Lx/Cub) were bred and maintained at the Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic. The 11 classic inbred strains were purchased from US Vendors (either Charles River or Envigo) and shipped to the University of Colorado Anschutz Medical Campus where they were acclimated prior to sacrifice. The remaining 2 classic inbred strains are the progenitor strains of the LEXF/FXLE RI panel and were bred and maintained at the National BioResource Project for the Rat in Japan. In Colorado, rats were sacrificed by rapid CO2 exposure. In the Czech Republic, rats were sacrificed by cervical dislocation. All experiments involving the HXB/BXH RI panel and two progenitor strains were performed in accordance with the Animal Protection Law of the Czech Republic and were approved by the Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague. All experiments involving the 11 classic inbred strains maintained at the University of Colorado Anschutz Medical Campus were approved by the Institutional Animal Care and Use Committee of the University of Colorado Anschutz Medical Campus and were performed in accordance with the guidelines in the NIH Guide for the Care and Use of Laboratory Animals. Animal experiments involving the F344/Stm and LE/Stm strains were conducted in accordance with the Fundamental Guidelines for Proper Conduct of Animal Experiment and Related Activities in Academic Research Institutions under the jurisdiction of the Ministry of Education, Culture, Sports, Science and Technology of Japan, and were approved by the Committee on Animal Experimentation at Kyoto University, Japan.
diff --git a/general/datasets/PGenRatLiv_rna_0520/experiment-design.rtf b/general/datasets/PGenRatLiv_rna_0520/experiment-design.rtf
deleted file mode 100644
index 3ff2342..0000000
--- a/general/datasets/PGenRatLiv_rna_0520/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Predisposition database. RNA expression levels were measured on rats that had not been exposed to any type of intervention (e.g., alcohol, drugs, stress).
diff --git a/general/datasets/PGenRatLiv_rna_0520/platform.rtf b/general/datasets/PGenRatLiv_rna_0520/platform.rtf
deleted file mode 100644
index da38d8b..0000000
--- a/general/datasets/PGenRatLiv_rna_0520/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Total RNA was isolated from 3 biological replicates of each of the HRDP v5 strains using QIAzol (Qiagen, Valencia, CA, USA).The RNAeasy Plus Universal Midi Kit (Qiagen) was used to separate long (>200 nt) and short (<200 nt, miRNA-enriched) fractions. The long RNA fraction was purified using the RNeasy Mini Kit (Qiagen). Four microliters of a 1:100 dilution of either ERCC Spikeâ€In Mix 1 or Mix 2 (Thermo Fisher Scientific, Wilmington, DE) was added to each extracted RNA sample. Sequencing libraries for the long RNA fraction were constructed using the Illumina TruSeq Stranded Total RNA Sample Preparation Kit with Ribo-Zero ribosomal RNA reduction chemistry (Illumina) in accordance with the manufacturer’s instructions. An Agilent Technologies Bioanalyzer 2100 was utilized to assess sequencing library quality. A loading control was included in each sequencing batch. The loading control was a library generated from an SHR animal. Samples were sequenced (depending on batch either 2X100 or 2x150 paired end reads) on an Ilumina sequencer.
diff --git a/general/datasets/PGenRatLiv_rna_0520/processing.rtf b/general/datasets/PGenRatLiv_rna_0520/processing.rtf
deleted file mode 100644
index 4c9da95..0000000
--- a/general/datasets/PGenRatLiv_rna_0520/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Prior to alignment, reads were demultiplexed and read fragments were trimmed for adaptors and for quality using Cutadapt (version 1.9.1;(Martin, 2011)). Reads were eliminated if the trimmed length of either read fragment was <20 nucleotides. Next, bowtie2(v 2.2.6) (4) was used to align reads to ribosomal RNA, and the unmapped reads were retained. These will be referred to as “cleaned” reads. The RNA-Seq Expectation Maximization (RSEM v1.2.31) algorithm (Li and Dewey 2011) was used to estimate the number of aligned reads for individual Ensembl transcripts (version 96). The number of reads aligned to each Ensembl gene was calculated as the sum of the number of reads aligned to individual Ensembl transcripts annotated to that gene.
-
-Prior to normalization and transformation, a detection above background filter was applied where we required a gene to have at least 2/3 of the samples have 1 count or more to be considered expressed above background. All genes that did not pass this detection above background criteria were removed. Count values were normalized using RUVg (PMID: 25150836) and transformed using the regularized log function (PMID: 25516281).
diff --git a/general/datasets/PGenRatLiv_rna_0520/specifics.rtf b/general/datasets/PGenRatLiv_rna_0520/specifics.rtf
deleted file mode 100644
index 7169dc3..0000000
--- a/general/datasets/PGenRatLiv_rna_0520/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-zeros no included
\ No newline at end of file
diff --git a/general/datasets/PGenRatLiv_rna_0520/summary.rtf b/general/datasets/PGenRatLiv_rna_0520/summary.rtf
deleted file mode 100644
index 3ced7f9..0000000
--- a/general/datasets/PGenRatLiv_rna_0520/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set was generated as part of the RGAP project funded by NIAAA (R24 AA013162; MPI – Tabakoff, Hoffman, Saba) at the University of Colorado Anschutz Medical Campus. The processing of the RNA-Seq data was also supported by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223; MPI – Williams, Saba). These data represent the RNA expression levels of Ensembl genes in liver. Ribosomal RNA depleted total RNA was used to generate paired end libraries. Levels were estimated in 45 (version 5) strains of the Hybrid Rat Diversity Panel (HRDP) including 30 HXB/BXH recombinant inbred strain and 15 classic inbred strains. Two to three biological replicates per strain were included in the strain-level means. Male rats were used for all analyses.
diff --git a/general/datasets/PGenRatLiv_rna_0520/tissue.rtf b/general/datasets/PGenRatLiv_rna_0520/tissue.rtf
deleted file mode 100644
index 117c7a1..0000000
--- a/general/datasets/PGenRatLiv_rna_0520/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Upon sacrifice, livers were rapidly removed and stored in liquid nitrogen. Livers were stored at -80â°C until used for RNA extraction. Tissues from the Czech Republic and Japan were shipped on dry ice to the University of Colorado Anschutz Medical Campus for RNA extraction and cDNA library preparation
diff --git a/general/datasets/PGenRatLiv_rna_z_0520/acknowledgment.rtf b/general/datasets/PGenRatLiv_rna_z_0520/acknowledgment.rtf
deleted file mode 100644
index b5348f4..0000000
--- a/general/datasets/PGenRatLiv_rna_z_0520/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Data were generated with funds provided by NIAAA, NIDA, the Banbury Fund, Czech Academy of Sciences, and The National BioResource Project-Rat. Dr. Michal Pravenec of the Czech Academy of Sciences kindly provided the tissues from the HXB/BXH recombinant inbred panel. Dr. Masahide Asano of the University of Kyoto kindly provided tissues from the F344/Stm and LE/Stm strains. Dr. Melinda Dwinell will be providing tissues for many of the remaining HRDP strains. We would like to thank Spencer Mahaffey, Jennifer Mahaffey, Yinni Yu, Seija Tililanen, Lauren Vanderlinden, and Harry Smith for help with extracting RNA, generating libraries, and processing data. We would also like to acknowledge the support of UNLV National Supercomputing Institute (UNLV NSI) by providing access to supercomputing resources to support analysis of sequencing data.
diff --git a/general/datasets/PGenRatLiv_rna_z_0520/cases.rtf b/general/datasets/PGenRatLiv_rna_z_0520/cases.rtf
deleted file mode 100644
index 69ff672..0000000
--- a/general/datasets/PGenRatLiv_rna_z_0520/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-For this data set, a subset of the Hybrid Rat Diversity Panel (HRDP) was used that included 30 HXB/BXH recombinant inbred strains and 15 classic inbred strains for a total of 45 inbred strains. Male rats at the age of 90 days were used for this study. The animals from the 30 RI strains and the 2 progenitor strains of the HXB/BXH RI panel (SHR/OlaIpcv and BN-Lx/Cub) were bred and maintained at the Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic. The 11 classic inbred strains were purchased from US Vendors (either Charles River or Envigo) and shipped to the University of Colorado Anschutz Medical Campus where they were acclimated prior to sacrifice. The remaining 2 classic inbred strains are the progenitor strains of the LEXF/FXLE RI panel and were bred and maintained at the National BioResource Project for the Rat in Japan. In Colorado, rats were sacrificed by rapid CO2 exposure. In the Czech Republic, rats were sacrificed by cervical dislocation. All experiments involving the HXB/BXH RI panel and two progenitor strains were performed in accordance with the Animal Protection Law of the Czech Republic and were approved by the Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague. All experiments involving the 11 classic inbred strains maintained at the University of Colorado Anschutz Medical Campus were approved by the Institutional Animal Care and Use Committee of the University of Colorado Anschutz Medical Campus and were performed in accordance with the guidelines in the NIH Guide for the Care and Use of Laboratory Animals. Animal experiments involving the F344/Stm and LE/Stm strains were conducted in accordance with the Fundamental Guidelines for Proper Conduct of Animal Experiment and Related Activities in Academic Research Institutions under the jurisdiction of the Ministry of Education, Culture, Sports, Science and Technology of Japan, and were approved by the Committee on Animal Experimentation at Kyoto University, Japan.
diff --git a/general/datasets/PGenRatLiv_rna_z_0520/experiment-design.rtf b/general/datasets/PGenRatLiv_rna_z_0520/experiment-design.rtf
deleted file mode 100644
index 3ff2342..0000000
--- a/general/datasets/PGenRatLiv_rna_z_0520/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Predisposition database. RNA expression levels were measured on rats that had not been exposed to any type of intervention (e.g., alcohol, drugs, stress).
diff --git a/general/datasets/PGenRatLiv_rna_z_0520/platform.rtf b/general/datasets/PGenRatLiv_rna_z_0520/platform.rtf
deleted file mode 100644
index da38d8b..0000000
--- a/general/datasets/PGenRatLiv_rna_z_0520/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Total RNA was isolated from 3 biological replicates of each of the HRDP v5 strains using QIAzol (Qiagen, Valencia, CA, USA).The RNAeasy Plus Universal Midi Kit (Qiagen) was used to separate long (>200 nt) and short (<200 nt, miRNA-enriched) fractions. The long RNA fraction was purified using the RNeasy Mini Kit (Qiagen). Four microliters of a 1:100 dilution of either ERCC Spikeâ€In Mix 1 or Mix 2 (Thermo Fisher Scientific, Wilmington, DE) was added to each extracted RNA sample. Sequencing libraries for the long RNA fraction were constructed using the Illumina TruSeq Stranded Total RNA Sample Preparation Kit with Ribo-Zero ribosomal RNA reduction chemistry (Illumina) in accordance with the manufacturer’s instructions. An Agilent Technologies Bioanalyzer 2100 was utilized to assess sequencing library quality. A loading control was included in each sequencing batch. The loading control was a library generated from an SHR animal. Samples were sequenced (depending on batch either 2X100 or 2x150 paired end reads) on an Ilumina sequencer.
diff --git a/general/datasets/PGenRatLiv_rna_z_0520/processing.rtf b/general/datasets/PGenRatLiv_rna_z_0520/processing.rtf
deleted file mode 100644
index 4c9da95..0000000
--- a/general/datasets/PGenRatLiv_rna_z_0520/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Prior to alignment, reads were demultiplexed and read fragments were trimmed for adaptors and for quality using Cutadapt (version 1.9.1;(Martin, 2011)). Reads were eliminated if the trimmed length of either read fragment was <20 nucleotides. Next, bowtie2(v 2.2.6) (4) was used to align reads to ribosomal RNA, and the unmapped reads were retained. These will be referred to as “cleaned” reads. The RNA-Seq Expectation Maximization (RSEM v1.2.31) algorithm (Li and Dewey 2011) was used to estimate the number of aligned reads for individual Ensembl transcripts (version 96). The number of reads aligned to each Ensembl gene was calculated as the sum of the number of reads aligned to individual Ensembl transcripts annotated to that gene.
-
-Prior to normalization and transformation, a detection above background filter was applied where we required a gene to have at least 2/3 of the samples have 1 count or more to be considered expressed above background. All genes that did not pass this detection above background criteria were removed. Count values were normalized using RUVg (PMID: 25150836) and transformed using the regularized log function (PMID: 25516281).
diff --git a/general/datasets/PGenRatLiv_rna_z_0520/specifics.rtf b/general/datasets/PGenRatLiv_rna_z_0520/specifics.rtf
deleted file mode 100644
index edb176d..0000000
--- a/general/datasets/PGenRatLiv_rna_z_0520/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-zeros included
\ No newline at end of file
diff --git a/general/datasets/PGenRatLiv_rna_z_0520/summary.rtf b/general/datasets/PGenRatLiv_rna_z_0520/summary.rtf
deleted file mode 100644
index 3ced7f9..0000000
--- a/general/datasets/PGenRatLiv_rna_z_0520/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set was generated as part of the RGAP project funded by NIAAA (R24 AA013162; MPI – Tabakoff, Hoffman, Saba) at the University of Colorado Anschutz Medical Campus. The processing of the RNA-Seq data was also supported by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223; MPI – Williams, Saba). These data represent the RNA expression levels of Ensembl genes in liver. Ribosomal RNA depleted total RNA was used to generate paired end libraries. Levels were estimated in 45 (version 5) strains of the Hybrid Rat Diversity Panel (HRDP) including 30 HXB/BXH recombinant inbred strain and 15 classic inbred strains. Two to three biological replicates per strain were included in the strain-level means. Male rats were used for all analyses.
diff --git a/general/datasets/PGenRatLiv_rna_z_0520/tissue.rtf b/general/datasets/PGenRatLiv_rna_z_0520/tissue.rtf
deleted file mode 100644
index 117c7a1..0000000
--- a/general/datasets/PGenRatLiv_rna_z_0520/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Upon sacrifice, livers were rapidly removed and stored in liquid nitrogen. Livers were stored at -80â°C until used for RNA extraction. Tissues from the Czech Republic and Japan were shipped on dry ice to the University of Colorado Anschutz Medical Campus for RNA extraction and cDNA library preparation
diff --git a/general/datasets/PSU_B6D2F2_0812/platform.rtf b/general/datasets/PSU_B6D2F2_0812/platform.rtf
deleted file mode 100644
index 7b362a7..0000000
--- a/general/datasets/PSU_B6D2F2_0812/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Affymetrix Mouse Genome 430 2.0 Array. All probe sets represented on the GeneChip Mouse Expression Set 430 are included on the GeneChip Mouse Genome 430 2.0 Array. The sequences from which these probe sets were derived were selected from GenBank«, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 107, June 2002) and then refined by analysis and comparison with the publicly available draft assembly of the mouse genome from the Whitehead Institute for Genome Research (MGSC, April 2002).
diff --git a/general/datasets/PSU_B6D2F2_0812/summary.rtf b/general/datasets/PSU_B6D2F2_0812/summary.rtf
deleted file mode 100644
index f7a3b5d..0000000
--- a/general/datasets/PSU_B6D2F2_0812/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 153, Name: PSU B6D2F2 Muscle Affy Mouse Genome 430 2.0 (Aug12)
diff --git a/general/datasets/PSU_B6D2F2_M0812/platform.rtf b/general/datasets/PSU_B6D2F2_M0812/platform.rtf
deleted file mode 100644
index 7b362a7..0000000
--- a/general/datasets/PSU_B6D2F2_M0812/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Affymetrix Mouse Genome 430 2.0 Array. All probe sets represented on the GeneChip Mouse Expression Set 430 are included on the GeneChip Mouse Genome 430 2.0 Array. The sequences from which these probe sets were derived were selected from GenBank«, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 107, June 2002) and then refined by analysis and comparison with the publicly available draft assembly of the mouse genome from the Whitehead Institute for Genome Research (MGSC, April 2002).
diff --git a/general/datasets/PSU_B6D2F2_M0812/summary.rtf b/general/datasets/PSU_B6D2F2_M0812/summary.rtf
deleted file mode 100644
index f7a3b5d..0000000
--- a/general/datasets/PSU_B6D2F2_M0812/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 153, Name: PSU B6D2F2 Muscle Affy Mouse Genome 430 2.0 (Aug12)
diff --git a/general/datasets/Pgenratbrn_rna_0520/acknowledgment.rtf b/general/datasets/Pgenratbrn_rna_0520/acknowledgment.rtf
new file mode 100644
index 0000000..b5348f4
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_0520/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds provided by NIAAA, NIDA, the Banbury Fund, Czech Academy of Sciences, and The National BioResource Project-Rat. Dr. Michal Pravenec of the Czech Academy of Sciences kindly provided the tissues from the HXB/BXH recombinant inbred panel. Dr. Masahide Asano of the University of Kyoto kindly provided tissues from the F344/Stm and LE/Stm strains. Dr. Melinda Dwinell will be providing tissues for many of the remaining HRDP strains. We would like to thank Spencer Mahaffey, Jennifer Mahaffey, Yinni Yu, Seija Tililanen, Lauren Vanderlinden, and Harry Smith for help with extracting RNA, generating libraries, and processing data. We would also like to acknowledge the support of UNLV National Supercomputing Institute (UNLV NSI) by providing access to supercomputing resources to support analysis of sequencing data.
diff --git a/general/datasets/Pgenratbrn_rna_0520/cases.rtf b/general/datasets/Pgenratbrn_rna_0520/cases.rtf
new file mode 100644
index 0000000..022c897
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_0520/cases.rtf
@@ -0,0 +1 @@
+For this data set, a subset of the Hybrid Rat Diversity Panel (HRDP) was used that included 30 HXB/BXH recombinant inbred strains and 15 classic inbred strains for a total of 45 inbred strains. Male rats at the age of 90 days were used for this study. The animals from the 30 RI strains and the 2 progenitor strains of the HXB/BXH RI panel (SHR/OlaIpcv and BN-Lx/Cub) were bred and maintained at the Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic. The 11 classic inbred strains were purchased from US Vendors (either Charles River or Envigo) and shipped to the University of Colorado Anschutz Medical Campus where they were acclimated prior to sacrifice. The remaining 2 classic inbred strains are the progenitor strains of the LEXF/FXLE RI panel and were bred and maintained at the National BioResource Project for the Rat in Japan. In Colorado, rats were sacrificed by rapid CO2 exposure. In the Czech Republic, rats were sacrificed by cervical dislocation. All experiments involving the harvesting of whole brain of the HXB/BXH RI panel and two progenitor strains were performed in accordance with the Animal Protection Law of the Czech Republic and were approved by the Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague. All experiments involving the harvesting of whole brain of the 11 classic inbred strains maintained at the University of Colorado Anschutz Medical Campus were approved by the Institutional Animal Care and Use Committee of the University of Colorado Anschutz Medical Campus and were performed in accordance with the guidelines in the NIH Guide for the Care and Use of Laboratory Animals. Animal experiments involving the F344/Stm and LE/Stm strains were conducted in accordance with the Fundamental Guidelines for Proper Conduct of Animal Experiment and Related Activities in Academic Research Institutions under the jurisdiction of the Ministry of Education, Culture, Sports, Science and Technology of Japan, and were approved by the Committee on Animal Experimentation at Kyoto University, Japan.
diff --git a/general/datasets/Pgenratbrn_rna_0520/citation.rtf b/general/datasets/Pgenratbrn_rna_0520/citation.rtf
new file mode 100644
index 0000000..cac3b01
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_0520/citation.rtf
@@ -0,0 +1 @@
+Tabakoff B., Smith H., Vanderlinden L.A., Hoffman P.L., Saba L.M. (2019) Networking in Biology: The Hybrid Rat Diversity Panel. In: Hayman G., Smith J., Dwinell M., Shimoyama M. (eds) Rat Genomics. Methods in Molecular Biology, vol 2018. Humana, New York, NY
diff --git a/general/datasets/Pgenratbrn_rna_0520/contributors.rtf b/general/datasets/Pgenratbrn_rna_0520/contributors.rtf
new file mode 100644
index 0000000..b32b308
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_0520/contributors.rtf
@@ -0,0 +1,23 @@
+Boris Tabakoff, PhD
+University of Colorado Anschutz Medical Campus
+Grant Support: NIAAA R24 AA013162
+
+Paula Hoffman, PhD
+University of Colorado Anschutz Medical Campus
+Grant Support: NIAAA R24 AA013162
+
+Laura Saba, PhD
+University of Colorado Anschutz Medical Campus
+Grant Support: NIAAA R24 AA013162 and NIDA P30 DA044223
+
+Michal Pravenec PhD
+The Czech Academy of Sciences
+Grant Support: Academic premium of the Czech Academy of Sciences (AP1502)
+
+Masahide Asano, PhD
+Institute of Laboratory Animals, Graduate School of Medicine, Kyoto University
+Grant Support: The National BioResource Project-Rat (Grant Number: 964706, 19 km 0210167j0001)
+
+Melinda Dwinell, PhD
+Medical College of Wisconsin
+Grant Support: R24 OD024617
diff --git a/general/datasets/Pgenratbrn_rna_0520/experiment-design.rtf b/general/datasets/Pgenratbrn_rna_0520/experiment-design.rtf
new file mode 100644
index 0000000..3ff2342
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_0520/experiment-design.rtf
@@ -0,0 +1 @@
+Predisposition database. RNA expression levels were measured on rats that had not been exposed to any type of intervention (e.g., alcohol, drugs, stress).
diff --git a/general/datasets/Pgenratbrn_rna_0520/platform.rtf b/general/datasets/Pgenratbrn_rna_0520/platform.rtf
new file mode 100644
index 0000000..da38d8b
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_0520/platform.rtf
@@ -0,0 +1 @@
+Total RNA was isolated from 3 biological replicates of each of the HRDP v5 strains using QIAzol (Qiagen, Valencia, CA, USA).The RNAeasy Plus Universal Midi Kit (Qiagen) was used to separate long (>200 nt) and short (<200 nt, miRNA-enriched) fractions. The long RNA fraction was purified using the RNeasy Mini Kit (Qiagen). Four microliters of a 1:100 dilution of either ERCC Spikeâ€In Mix 1 or Mix 2 (Thermo Fisher Scientific, Wilmington, DE) was added to each extracted RNA sample. Sequencing libraries for the long RNA fraction were constructed using the Illumina TruSeq Stranded Total RNA Sample Preparation Kit with Ribo-Zero ribosomal RNA reduction chemistry (Illumina) in accordance with the manufacturer’s instructions. An Agilent Technologies Bioanalyzer 2100 was utilized to assess sequencing library quality. A loading control was included in each sequencing batch. The loading control was a library generated from an SHR animal. Samples were sequenced (depending on batch either 2X100 or 2x150 paired end reads) on an Ilumina sequencer.
diff --git a/general/datasets/Pgenratbrn_rna_0520/processing.rtf b/general/datasets/Pgenratbrn_rna_0520/processing.rtf
new file mode 100644
index 0000000..4c9da95
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_0520/processing.rtf
@@ -0,0 +1,3 @@
+Prior to alignment, reads were demultiplexed and read fragments were trimmed for adaptors and for quality using Cutadapt (version 1.9.1;(Martin, 2011)). Reads were eliminated if the trimmed length of either read fragment was <20 nucleotides. Next, bowtie2(v 2.2.6) (4) was used to align reads to ribosomal RNA, and the unmapped reads were retained. These will be referred to as “cleaned” reads. The RNA-Seq Expectation Maximization (RSEM v1.2.31) algorithm (Li and Dewey 2011) was used to estimate the number of aligned reads for individual Ensembl transcripts (version 96). The number of reads aligned to each Ensembl gene was calculated as the sum of the number of reads aligned to individual Ensembl transcripts annotated to that gene.
+
+Prior to normalization and transformation, a detection above background filter was applied where we required a gene to have at least 2/3 of the samples have 1 count or more to be considered expressed above background. All genes that did not pass this detection above background criteria were removed. Count values were normalized using RUVg (PMID: 25150836) and transformed using the regularized log function (PMID: 25516281).
diff --git a/general/datasets/Pgenratbrn_rna_0520/specifics.rtf b/general/datasets/Pgenratbrn_rna_0520/specifics.rtf
new file mode 100644
index 0000000..f98e245
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_0520/specifics.rtf
@@ -0,0 +1 @@
+Non zeros included.
\ No newline at end of file
diff --git a/general/datasets/Pgenratbrn_rna_0520/summary.rtf b/general/datasets/Pgenratbrn_rna_0520/summary.rtf
new file mode 100644
index 0000000..a70b10f
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_0520/summary.rtf
@@ -0,0 +1 @@
+This data set was generated as part of the RGAP project funded by NIAAA (R24 AA013162; MPI – Tabakoff, Hoffman, Saba) at the University of Colorado Anschutz Medical Campus. The processing of the RNA-Seq data was also supported by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223; MPI – Williams, Saba). These data represent the RNA expression levels of Ensembl genes in brain. Ribosomal RNA depleted total RNA was used to generate paired end libraries. Levels were estimated in 45 (version 5) strains of the Hybrid Rat Diversity Panel (HRDP) including 30 HXB/BXH recombinant inbred strain and 15 classic inbred strains. Two to three biological replicates per strain were included in the strain-level means. Male rats were used for all analyses.
diff --git a/general/datasets/Pgenratbrn_rna_0520/tissue.rtf b/general/datasets/Pgenratbrn_rna_0520/tissue.rtf
new file mode 100644
index 0000000..732bdc1
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_0520/tissue.rtf
@@ -0,0 +1 @@
+Upon sacrifice, brains (including cerebellum and brain stem) were rapidly removed, sectioned sagittally into two hemispheres, and stored in liquid nitrogen. Each hemisphere was stored separately at -80â°C until used for RNA extraction. Tissues from the Czech Republic and Japan were shipped on dry ice to the University of Colorado Anschutz Medical Campus for RNA extraction and cDNA library preparation
diff --git a/general/datasets/Pgenratbrn_rna_z_0520/acknowledgment.rtf b/general/datasets/Pgenratbrn_rna_z_0520/acknowledgment.rtf
new file mode 100644
index 0000000..b5348f4
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_z_0520/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds provided by NIAAA, NIDA, the Banbury Fund, Czech Academy of Sciences, and The National BioResource Project-Rat. Dr. Michal Pravenec of the Czech Academy of Sciences kindly provided the tissues from the HXB/BXH recombinant inbred panel. Dr. Masahide Asano of the University of Kyoto kindly provided tissues from the F344/Stm and LE/Stm strains. Dr. Melinda Dwinell will be providing tissues for many of the remaining HRDP strains. We would like to thank Spencer Mahaffey, Jennifer Mahaffey, Yinni Yu, Seija Tililanen, Lauren Vanderlinden, and Harry Smith for help with extracting RNA, generating libraries, and processing data. We would also like to acknowledge the support of UNLV National Supercomputing Institute (UNLV NSI) by providing access to supercomputing resources to support analysis of sequencing data.
diff --git a/general/datasets/Pgenratbrn_rna_z_0520/cases.rtf b/general/datasets/Pgenratbrn_rna_z_0520/cases.rtf
new file mode 100644
index 0000000..022c897
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_z_0520/cases.rtf
@@ -0,0 +1 @@
+For this data set, a subset of the Hybrid Rat Diversity Panel (HRDP) was used that included 30 HXB/BXH recombinant inbred strains and 15 classic inbred strains for a total of 45 inbred strains. Male rats at the age of 90 days were used for this study. The animals from the 30 RI strains and the 2 progenitor strains of the HXB/BXH RI panel (SHR/OlaIpcv and BN-Lx/Cub) were bred and maintained at the Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic. The 11 classic inbred strains were purchased from US Vendors (either Charles River or Envigo) and shipped to the University of Colorado Anschutz Medical Campus where they were acclimated prior to sacrifice. The remaining 2 classic inbred strains are the progenitor strains of the LEXF/FXLE RI panel and were bred and maintained at the National BioResource Project for the Rat in Japan. In Colorado, rats were sacrificed by rapid CO2 exposure. In the Czech Republic, rats were sacrificed by cervical dislocation. All experiments involving the harvesting of whole brain of the HXB/BXH RI panel and two progenitor strains were performed in accordance with the Animal Protection Law of the Czech Republic and were approved by the Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague. All experiments involving the harvesting of whole brain of the 11 classic inbred strains maintained at the University of Colorado Anschutz Medical Campus were approved by the Institutional Animal Care and Use Committee of the University of Colorado Anschutz Medical Campus and were performed in accordance with the guidelines in the NIH Guide for the Care and Use of Laboratory Animals. Animal experiments involving the F344/Stm and LE/Stm strains were conducted in accordance with the Fundamental Guidelines for Proper Conduct of Animal Experiment and Related Activities in Academic Research Institutions under the jurisdiction of the Ministry of Education, Culture, Sports, Science and Technology of Japan, and were approved by the Committee on Animal Experimentation at Kyoto University, Japan.
diff --git a/general/datasets/Pgenratbrn_rna_z_0520/citation.rtf b/general/datasets/Pgenratbrn_rna_z_0520/citation.rtf
new file mode 100644
index 0000000..cac3b01
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_z_0520/citation.rtf
@@ -0,0 +1 @@
+Tabakoff B., Smith H., Vanderlinden L.A., Hoffman P.L., Saba L.M. (2019) Networking in Biology: The Hybrid Rat Diversity Panel. In: Hayman G., Smith J., Dwinell M., Shimoyama M. (eds) Rat Genomics. Methods in Molecular Biology, vol 2018. Humana, New York, NY
diff --git a/general/datasets/Pgenratbrn_rna_z_0520/contributors.rtf b/general/datasets/Pgenratbrn_rna_z_0520/contributors.rtf
new file mode 100644
index 0000000..b32b308
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_z_0520/contributors.rtf
@@ -0,0 +1,23 @@
+Boris Tabakoff, PhD
+University of Colorado Anschutz Medical Campus
+Grant Support: NIAAA R24 AA013162
+
+Paula Hoffman, PhD
+University of Colorado Anschutz Medical Campus
+Grant Support: NIAAA R24 AA013162
+
+Laura Saba, PhD
+University of Colorado Anschutz Medical Campus
+Grant Support: NIAAA R24 AA013162 and NIDA P30 DA044223
+
+Michal Pravenec PhD
+The Czech Academy of Sciences
+Grant Support: Academic premium of the Czech Academy of Sciences (AP1502)
+
+Masahide Asano, PhD
+Institute of Laboratory Animals, Graduate School of Medicine, Kyoto University
+Grant Support: The National BioResource Project-Rat (Grant Number: 964706, 19 km 0210167j0001)
+
+Melinda Dwinell, PhD
+Medical College of Wisconsin
+Grant Support: R24 OD024617
diff --git a/general/datasets/Pgenratbrn_rna_z_0520/experiment-design.rtf b/general/datasets/Pgenratbrn_rna_z_0520/experiment-design.rtf
new file mode 100644
index 0000000..3ff2342
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_z_0520/experiment-design.rtf
@@ -0,0 +1 @@
+Predisposition database. RNA expression levels were measured on rats that had not been exposed to any type of intervention (e.g., alcohol, drugs, stress).
diff --git a/general/datasets/Pgenratbrn_rna_z_0520/platform.rtf b/general/datasets/Pgenratbrn_rna_z_0520/platform.rtf
new file mode 100644
index 0000000..da38d8b
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_z_0520/platform.rtf
@@ -0,0 +1 @@
+Total RNA was isolated from 3 biological replicates of each of the HRDP v5 strains using QIAzol (Qiagen, Valencia, CA, USA).The RNAeasy Plus Universal Midi Kit (Qiagen) was used to separate long (>200 nt) and short (<200 nt, miRNA-enriched) fractions. The long RNA fraction was purified using the RNeasy Mini Kit (Qiagen). Four microliters of a 1:100 dilution of either ERCC Spikeâ€In Mix 1 or Mix 2 (Thermo Fisher Scientific, Wilmington, DE) was added to each extracted RNA sample. Sequencing libraries for the long RNA fraction were constructed using the Illumina TruSeq Stranded Total RNA Sample Preparation Kit with Ribo-Zero ribosomal RNA reduction chemistry (Illumina) in accordance with the manufacturer’s instructions. An Agilent Technologies Bioanalyzer 2100 was utilized to assess sequencing library quality. A loading control was included in each sequencing batch. The loading control was a library generated from an SHR animal. Samples were sequenced (depending on batch either 2X100 or 2x150 paired end reads) on an Ilumina sequencer.
diff --git a/general/datasets/Pgenratbrn_rna_z_0520/processing.rtf b/general/datasets/Pgenratbrn_rna_z_0520/processing.rtf
new file mode 100644
index 0000000..4c9da95
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_z_0520/processing.rtf
@@ -0,0 +1,3 @@
+Prior to alignment, reads were demultiplexed and read fragments were trimmed for adaptors and for quality using Cutadapt (version 1.9.1;(Martin, 2011)). Reads were eliminated if the trimmed length of either read fragment was <20 nucleotides. Next, bowtie2(v 2.2.6) (4) was used to align reads to ribosomal RNA, and the unmapped reads were retained. These will be referred to as “cleaned” reads. The RNA-Seq Expectation Maximization (RSEM v1.2.31) algorithm (Li and Dewey 2011) was used to estimate the number of aligned reads for individual Ensembl transcripts (version 96). The number of reads aligned to each Ensembl gene was calculated as the sum of the number of reads aligned to individual Ensembl transcripts annotated to that gene.
+
+Prior to normalization and transformation, a detection above background filter was applied where we required a gene to have at least 2/3 of the samples have 1 count or more to be considered expressed above background. All genes that did not pass this detection above background criteria were removed. Count values were normalized using RUVg (PMID: 25150836) and transformed using the regularized log function (PMID: 25516281).
diff --git a/general/datasets/Pgenratbrn_rna_z_0520/specifics.rtf b/general/datasets/Pgenratbrn_rna_z_0520/specifics.rtf
new file mode 100644
index 0000000..edb176d
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_z_0520/specifics.rtf
@@ -0,0 +1 @@
+zeros included
\ No newline at end of file
diff --git a/general/datasets/Pgenratbrn_rna_z_0520/summary.rtf b/general/datasets/Pgenratbrn_rna_z_0520/summary.rtf
new file mode 100644
index 0000000..a70b10f
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_z_0520/summary.rtf
@@ -0,0 +1 @@
+This data set was generated as part of the RGAP project funded by NIAAA (R24 AA013162; MPI – Tabakoff, Hoffman, Saba) at the University of Colorado Anschutz Medical Campus. The processing of the RNA-Seq data was also supported by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223; MPI – Williams, Saba). These data represent the RNA expression levels of Ensembl genes in brain. Ribosomal RNA depleted total RNA was used to generate paired end libraries. Levels were estimated in 45 (version 5) strains of the Hybrid Rat Diversity Panel (HRDP) including 30 HXB/BXH recombinant inbred strain and 15 classic inbred strains. Two to three biological replicates per strain were included in the strain-level means. Male rats were used for all analyses.
diff --git a/general/datasets/Pgenratbrn_rna_z_0520/tissue.rtf b/general/datasets/Pgenratbrn_rna_z_0520/tissue.rtf
new file mode 100644
index 0000000..732bdc1
--- /dev/null
+++ b/general/datasets/Pgenratbrn_rna_z_0520/tissue.rtf
@@ -0,0 +1 @@
+Upon sacrifice, brains (including cerebellum and brain stem) were rapidly removed, sectioned sagittally into two hemispheres, and stored in liquid nitrogen. Each hemisphere was stored separately at -80â°C until used for RNA extraction. Tissues from the Czech Republic and Japan were shipped on dry ice to the University of Colorado Anschutz Medical Campus for RNA extraction and cDNA library preparation
diff --git a/general/datasets/Pgenratliv_rna_0520/acknowledgment.rtf b/general/datasets/Pgenratliv_rna_0520/acknowledgment.rtf
new file mode 100644
index 0000000..b5348f4
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_0520/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds provided by NIAAA, NIDA, the Banbury Fund, Czech Academy of Sciences, and The National BioResource Project-Rat. Dr. Michal Pravenec of the Czech Academy of Sciences kindly provided the tissues from the HXB/BXH recombinant inbred panel. Dr. Masahide Asano of the University of Kyoto kindly provided tissues from the F344/Stm and LE/Stm strains. Dr. Melinda Dwinell will be providing tissues for many of the remaining HRDP strains. We would like to thank Spencer Mahaffey, Jennifer Mahaffey, Yinni Yu, Seija Tililanen, Lauren Vanderlinden, and Harry Smith for help with extracting RNA, generating libraries, and processing data. We would also like to acknowledge the support of UNLV National Supercomputing Institute (UNLV NSI) by providing access to supercomputing resources to support analysis of sequencing data.
diff --git a/general/datasets/Pgenratliv_rna_0520/cases.rtf b/general/datasets/Pgenratliv_rna_0520/cases.rtf
new file mode 100644
index 0000000..69ff672
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_0520/cases.rtf
@@ -0,0 +1 @@
+For this data set, a subset of the Hybrid Rat Diversity Panel (HRDP) was used that included 30 HXB/BXH recombinant inbred strains and 15 classic inbred strains for a total of 45 inbred strains. Male rats at the age of 90 days were used for this study. The animals from the 30 RI strains and the 2 progenitor strains of the HXB/BXH RI panel (SHR/OlaIpcv and BN-Lx/Cub) were bred and maintained at the Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic. The 11 classic inbred strains were purchased from US Vendors (either Charles River or Envigo) and shipped to the University of Colorado Anschutz Medical Campus where they were acclimated prior to sacrifice. The remaining 2 classic inbred strains are the progenitor strains of the LEXF/FXLE RI panel and were bred and maintained at the National BioResource Project for the Rat in Japan. In Colorado, rats were sacrificed by rapid CO2 exposure. In the Czech Republic, rats were sacrificed by cervical dislocation. All experiments involving the HXB/BXH RI panel and two progenitor strains were performed in accordance with the Animal Protection Law of the Czech Republic and were approved by the Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague. All experiments involving the 11 classic inbred strains maintained at the University of Colorado Anschutz Medical Campus were approved by the Institutional Animal Care and Use Committee of the University of Colorado Anschutz Medical Campus and were performed in accordance with the guidelines in the NIH Guide for the Care and Use of Laboratory Animals. Animal experiments involving the F344/Stm and LE/Stm strains were conducted in accordance with the Fundamental Guidelines for Proper Conduct of Animal Experiment and Related Activities in Academic Research Institutions under the jurisdiction of the Ministry of Education, Culture, Sports, Science and Technology of Japan, and were approved by the Committee on Animal Experimentation at Kyoto University, Japan.
diff --git a/general/datasets/Pgenratliv_rna_0520/citation.rtf b/general/datasets/Pgenratliv_rna_0520/citation.rtf
new file mode 100644
index 0000000..cac3b01
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_0520/citation.rtf
@@ -0,0 +1 @@
+Tabakoff B., Smith H., Vanderlinden L.A., Hoffman P.L., Saba L.M. (2019) Networking in Biology: The Hybrid Rat Diversity Panel. In: Hayman G., Smith J., Dwinell M., Shimoyama M. (eds) Rat Genomics. Methods in Molecular Biology, vol 2018. Humana, New York, NY
diff --git a/general/datasets/Pgenratliv_rna_0520/contributors.rtf b/general/datasets/Pgenratliv_rna_0520/contributors.rtf
new file mode 100644
index 0000000..b32b308
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_0520/contributors.rtf
@@ -0,0 +1,23 @@
+Boris Tabakoff, PhD
+University of Colorado Anschutz Medical Campus
+Grant Support: NIAAA R24 AA013162
+
+Paula Hoffman, PhD
+University of Colorado Anschutz Medical Campus
+Grant Support: NIAAA R24 AA013162
+
+Laura Saba, PhD
+University of Colorado Anschutz Medical Campus
+Grant Support: NIAAA R24 AA013162 and NIDA P30 DA044223
+
+Michal Pravenec PhD
+The Czech Academy of Sciences
+Grant Support: Academic premium of the Czech Academy of Sciences (AP1502)
+
+Masahide Asano, PhD
+Institute of Laboratory Animals, Graduate School of Medicine, Kyoto University
+Grant Support: The National BioResource Project-Rat (Grant Number: 964706, 19 km 0210167j0001)
+
+Melinda Dwinell, PhD
+Medical College of Wisconsin
+Grant Support: R24 OD024617
diff --git a/general/datasets/Pgenratliv_rna_0520/experiment-design.rtf b/general/datasets/Pgenratliv_rna_0520/experiment-design.rtf
new file mode 100644
index 0000000..3ff2342
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_0520/experiment-design.rtf
@@ -0,0 +1 @@
+Predisposition database. RNA expression levels were measured on rats that had not been exposed to any type of intervention (e.g., alcohol, drugs, stress).
diff --git a/general/datasets/Pgenratliv_rna_0520/platform.rtf b/general/datasets/Pgenratliv_rna_0520/platform.rtf
new file mode 100644
index 0000000..da38d8b
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_0520/platform.rtf
@@ -0,0 +1 @@
+Total RNA was isolated from 3 biological replicates of each of the HRDP v5 strains using QIAzol (Qiagen, Valencia, CA, USA).The RNAeasy Plus Universal Midi Kit (Qiagen) was used to separate long (>200 nt) and short (<200 nt, miRNA-enriched) fractions. The long RNA fraction was purified using the RNeasy Mini Kit (Qiagen). Four microliters of a 1:100 dilution of either ERCC Spikeâ€In Mix 1 or Mix 2 (Thermo Fisher Scientific, Wilmington, DE) was added to each extracted RNA sample. Sequencing libraries for the long RNA fraction were constructed using the Illumina TruSeq Stranded Total RNA Sample Preparation Kit with Ribo-Zero ribosomal RNA reduction chemistry (Illumina) in accordance with the manufacturer’s instructions. An Agilent Technologies Bioanalyzer 2100 was utilized to assess sequencing library quality. A loading control was included in each sequencing batch. The loading control was a library generated from an SHR animal. Samples were sequenced (depending on batch either 2X100 or 2x150 paired end reads) on an Ilumina sequencer.
diff --git a/general/datasets/Pgenratliv_rna_0520/processing.rtf b/general/datasets/Pgenratliv_rna_0520/processing.rtf
new file mode 100644
index 0000000..4c9da95
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_0520/processing.rtf
@@ -0,0 +1,3 @@
+Prior to alignment, reads were demultiplexed and read fragments were trimmed for adaptors and for quality using Cutadapt (version 1.9.1;(Martin, 2011)). Reads were eliminated if the trimmed length of either read fragment was <20 nucleotides. Next, bowtie2(v 2.2.6) (4) was used to align reads to ribosomal RNA, and the unmapped reads were retained. These will be referred to as “cleaned” reads. The RNA-Seq Expectation Maximization (RSEM v1.2.31) algorithm (Li and Dewey 2011) was used to estimate the number of aligned reads for individual Ensembl transcripts (version 96). The number of reads aligned to each Ensembl gene was calculated as the sum of the number of reads aligned to individual Ensembl transcripts annotated to that gene.
+
+Prior to normalization and transformation, a detection above background filter was applied where we required a gene to have at least 2/3 of the samples have 1 count or more to be considered expressed above background. All genes that did not pass this detection above background criteria were removed. Count values were normalized using RUVg (PMID: 25150836) and transformed using the regularized log function (PMID: 25516281).
diff --git a/general/datasets/Pgenratliv_rna_0520/specifics.rtf b/general/datasets/Pgenratliv_rna_0520/specifics.rtf
new file mode 100644
index 0000000..7169dc3
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_0520/specifics.rtf
@@ -0,0 +1 @@
+zeros no included
\ No newline at end of file
diff --git a/general/datasets/Pgenratliv_rna_0520/summary.rtf b/general/datasets/Pgenratliv_rna_0520/summary.rtf
new file mode 100644
index 0000000..3ced7f9
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_0520/summary.rtf
@@ -0,0 +1 @@
+This data set was generated as part of the RGAP project funded by NIAAA (R24 AA013162; MPI – Tabakoff, Hoffman, Saba) at the University of Colorado Anschutz Medical Campus. The processing of the RNA-Seq data was also supported by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223; MPI – Williams, Saba). These data represent the RNA expression levels of Ensembl genes in liver. Ribosomal RNA depleted total RNA was used to generate paired end libraries. Levels were estimated in 45 (version 5) strains of the Hybrid Rat Diversity Panel (HRDP) including 30 HXB/BXH recombinant inbred strain and 15 classic inbred strains. Two to three biological replicates per strain were included in the strain-level means. Male rats were used for all analyses.
diff --git a/general/datasets/Pgenratliv_rna_0520/tissue.rtf b/general/datasets/Pgenratliv_rna_0520/tissue.rtf
new file mode 100644
index 0000000..117c7a1
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_0520/tissue.rtf
@@ -0,0 +1 @@
+Upon sacrifice, livers were rapidly removed and stored in liquid nitrogen. Livers were stored at -80â°C until used for RNA extraction. Tissues from the Czech Republic and Japan were shipped on dry ice to the University of Colorado Anschutz Medical Campus for RNA extraction and cDNA library preparation
diff --git a/general/datasets/Pgenratliv_rna_z_0520/acknowledgment.rtf b/general/datasets/Pgenratliv_rna_z_0520/acknowledgment.rtf
new file mode 100644
index 0000000..b5348f4
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_z_0520/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds provided by NIAAA, NIDA, the Banbury Fund, Czech Academy of Sciences, and The National BioResource Project-Rat. Dr. Michal Pravenec of the Czech Academy of Sciences kindly provided the tissues from the HXB/BXH recombinant inbred panel. Dr. Masahide Asano of the University of Kyoto kindly provided tissues from the F344/Stm and LE/Stm strains. Dr. Melinda Dwinell will be providing tissues for many of the remaining HRDP strains. We would like to thank Spencer Mahaffey, Jennifer Mahaffey, Yinni Yu, Seija Tililanen, Lauren Vanderlinden, and Harry Smith for help with extracting RNA, generating libraries, and processing data. We would also like to acknowledge the support of UNLV National Supercomputing Institute (UNLV NSI) by providing access to supercomputing resources to support analysis of sequencing data.
diff --git a/general/datasets/Pgenratliv_rna_z_0520/cases.rtf b/general/datasets/Pgenratliv_rna_z_0520/cases.rtf
new file mode 100644
index 0000000..69ff672
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_z_0520/cases.rtf
@@ -0,0 +1 @@
+For this data set, a subset of the Hybrid Rat Diversity Panel (HRDP) was used that included 30 HXB/BXH recombinant inbred strains and 15 classic inbred strains for a total of 45 inbred strains. Male rats at the age of 90 days were used for this study. The animals from the 30 RI strains and the 2 progenitor strains of the HXB/BXH RI panel (SHR/OlaIpcv and BN-Lx/Cub) were bred and maintained at the Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic. The 11 classic inbred strains were purchased from US Vendors (either Charles River or Envigo) and shipped to the University of Colorado Anschutz Medical Campus where they were acclimated prior to sacrifice. The remaining 2 classic inbred strains are the progenitor strains of the LEXF/FXLE RI panel and were bred and maintained at the National BioResource Project for the Rat in Japan. In Colorado, rats were sacrificed by rapid CO2 exposure. In the Czech Republic, rats were sacrificed by cervical dislocation. All experiments involving the HXB/BXH RI panel and two progenitor strains were performed in accordance with the Animal Protection Law of the Czech Republic and were approved by the Ethics Committee of the Institute of Physiology, Czech Academy of Sciences, Prague. All experiments involving the 11 classic inbred strains maintained at the University of Colorado Anschutz Medical Campus were approved by the Institutional Animal Care and Use Committee of the University of Colorado Anschutz Medical Campus and were performed in accordance with the guidelines in the NIH Guide for the Care and Use of Laboratory Animals. Animal experiments involving the F344/Stm and LE/Stm strains were conducted in accordance with the Fundamental Guidelines for Proper Conduct of Animal Experiment and Related Activities in Academic Research Institutions under the jurisdiction of the Ministry of Education, Culture, Sports, Science and Technology of Japan, and were approved by the Committee on Animal Experimentation at Kyoto University, Japan.
diff --git a/general/datasets/Pgenratliv_rna_z_0520/citation.rtf b/general/datasets/Pgenratliv_rna_z_0520/citation.rtf
new file mode 100644
index 0000000..cac3b01
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_z_0520/citation.rtf
@@ -0,0 +1 @@
+Tabakoff B., Smith H., Vanderlinden L.A., Hoffman P.L., Saba L.M. (2019) Networking in Biology: The Hybrid Rat Diversity Panel. In: Hayman G., Smith J., Dwinell M., Shimoyama M. (eds) Rat Genomics. Methods in Molecular Biology, vol 2018. Humana, New York, NY
diff --git a/general/datasets/Pgenratliv_rna_z_0520/contributors.rtf b/general/datasets/Pgenratliv_rna_z_0520/contributors.rtf
new file mode 100644
index 0000000..b32b308
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_z_0520/contributors.rtf
@@ -0,0 +1,23 @@
+Boris Tabakoff, PhD
+University of Colorado Anschutz Medical Campus
+Grant Support: NIAAA R24 AA013162
+
+Paula Hoffman, PhD
+University of Colorado Anschutz Medical Campus
+Grant Support: NIAAA R24 AA013162
+
+Laura Saba, PhD
+University of Colorado Anschutz Medical Campus
+Grant Support: NIAAA R24 AA013162 and NIDA P30 DA044223
+
+Michal Pravenec PhD
+The Czech Academy of Sciences
+Grant Support: Academic premium of the Czech Academy of Sciences (AP1502)
+
+Masahide Asano, PhD
+Institute of Laboratory Animals, Graduate School of Medicine, Kyoto University
+Grant Support: The National BioResource Project-Rat (Grant Number: 964706, 19 km 0210167j0001)
+
+Melinda Dwinell, PhD
+Medical College of Wisconsin
+Grant Support: R24 OD024617
diff --git a/general/datasets/Pgenratliv_rna_z_0520/experiment-design.rtf b/general/datasets/Pgenratliv_rna_z_0520/experiment-design.rtf
new file mode 100644
index 0000000..3ff2342
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_z_0520/experiment-design.rtf
@@ -0,0 +1 @@
+Predisposition database. RNA expression levels were measured on rats that had not been exposed to any type of intervention (e.g., alcohol, drugs, stress).
diff --git a/general/datasets/Pgenratliv_rna_z_0520/platform.rtf b/general/datasets/Pgenratliv_rna_z_0520/platform.rtf
new file mode 100644
index 0000000..da38d8b
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_z_0520/platform.rtf
@@ -0,0 +1 @@
+Total RNA was isolated from 3 biological replicates of each of the HRDP v5 strains using QIAzol (Qiagen, Valencia, CA, USA).The RNAeasy Plus Universal Midi Kit (Qiagen) was used to separate long (>200 nt) and short (<200 nt, miRNA-enriched) fractions. The long RNA fraction was purified using the RNeasy Mini Kit (Qiagen). Four microliters of a 1:100 dilution of either ERCC Spikeâ€In Mix 1 or Mix 2 (Thermo Fisher Scientific, Wilmington, DE) was added to each extracted RNA sample. Sequencing libraries for the long RNA fraction were constructed using the Illumina TruSeq Stranded Total RNA Sample Preparation Kit with Ribo-Zero ribosomal RNA reduction chemistry (Illumina) in accordance with the manufacturer’s instructions. An Agilent Technologies Bioanalyzer 2100 was utilized to assess sequencing library quality. A loading control was included in each sequencing batch. The loading control was a library generated from an SHR animal. Samples were sequenced (depending on batch either 2X100 or 2x150 paired end reads) on an Ilumina sequencer.
diff --git a/general/datasets/Pgenratliv_rna_z_0520/processing.rtf b/general/datasets/Pgenratliv_rna_z_0520/processing.rtf
new file mode 100644
index 0000000..4c9da95
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_z_0520/processing.rtf
@@ -0,0 +1,3 @@
+Prior to alignment, reads were demultiplexed and read fragments were trimmed for adaptors and for quality using Cutadapt (version 1.9.1;(Martin, 2011)). Reads were eliminated if the trimmed length of either read fragment was <20 nucleotides. Next, bowtie2(v 2.2.6) (4) was used to align reads to ribosomal RNA, and the unmapped reads were retained. These will be referred to as “cleaned” reads. The RNA-Seq Expectation Maximization (RSEM v1.2.31) algorithm (Li and Dewey 2011) was used to estimate the number of aligned reads for individual Ensembl transcripts (version 96). The number of reads aligned to each Ensembl gene was calculated as the sum of the number of reads aligned to individual Ensembl transcripts annotated to that gene.
+
+Prior to normalization and transformation, a detection above background filter was applied where we required a gene to have at least 2/3 of the samples have 1 count or more to be considered expressed above background. All genes that did not pass this detection above background criteria were removed. Count values were normalized using RUVg (PMID: 25150836) and transformed using the regularized log function (PMID: 25516281).
diff --git a/general/datasets/Pgenratliv_rna_z_0520/specifics.rtf b/general/datasets/Pgenratliv_rna_z_0520/specifics.rtf
new file mode 100644
index 0000000..edb176d
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_z_0520/specifics.rtf
@@ -0,0 +1 @@
+zeros included
\ No newline at end of file
diff --git a/general/datasets/Pgenratliv_rna_z_0520/summary.rtf b/general/datasets/Pgenratliv_rna_z_0520/summary.rtf
new file mode 100644
index 0000000..3ced7f9
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_z_0520/summary.rtf
@@ -0,0 +1 @@
+This data set was generated as part of the RGAP project funded by NIAAA (R24 AA013162; MPI – Tabakoff, Hoffman, Saba) at the University of Colorado Anschutz Medical Campus. The processing of the RNA-Seq data was also supported by the NIDA Center of Excellence in Omics, Systems Genetics, and the Addictome (P30 DA044223; MPI – Williams, Saba). These data represent the RNA expression levels of Ensembl genes in liver. Ribosomal RNA depleted total RNA was used to generate paired end libraries. Levels were estimated in 45 (version 5) strains of the Hybrid Rat Diversity Panel (HRDP) including 30 HXB/BXH recombinant inbred strain and 15 classic inbred strains. Two to three biological replicates per strain were included in the strain-level means. Male rats were used for all analyses.
diff --git a/general/datasets/Pgenratliv_rna_z_0520/tissue.rtf b/general/datasets/Pgenratliv_rna_z_0520/tissue.rtf
new file mode 100644
index 0000000..117c7a1
--- /dev/null
+++ b/general/datasets/Pgenratliv_rna_z_0520/tissue.rtf
@@ -0,0 +1 @@
+Upon sacrifice, livers were rapidly removed and stored in liquid nitrogen. Livers were stored at -80â°C until used for RNA extraction. Tissues from the Czech Republic and Japan were shipped on dry ice to the University of Colorado Anschutz Medical Campus for RNA extraction and cDNA library preparation
diff --git a/general/datasets/PoplarPublish/acknowledgment.rtf b/general/datasets/PoplarPublish/acknowledgment.rtf
deleted file mode 100644
index b137fef..0000000
--- a/general/datasets/PoplarPublish/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We thank L. E. Gunter, M. S. Azam, E. Drewes, N. Farzaneh, L. Liao, E. Moreno, L. Muenter and L. Quamme for data monitoring, collection and image presentation. We also thank anonymous reviewers for their suggestions and revisions in improving the manuscript. This work was supported by the Genome British Columbia Applied Genomics Innovation Program (Project 103BIO) and Genome Canada Large-Scale Applied Research Project (Project 168BIO) funds to R.D.G., J.E., Q.C.B.C., Y.A.E-K., S.D.M. and C.J.D. and by funds within the BioEnergy Science Center, a US Department of Energy Bioenergy Research Facility under contract DE–AC05–00OR22725.
diff --git a/general/datasets/PoplarPublish/platform.rtf b/general/datasets/PoplarPublish/platform.rtf
deleted file mode 100644
index 228a076..0000000
--- a/general/datasets/PoplarPublish/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Illumina iSelect Infinium 34K Populus SNP genotyping array
diff --git a/general/datasets/PoplarPublish/processing.rtf b/general/datasets/PoplarPublish/processing.rtf
deleted file mode 100644
index 9a6b788..0000000
--- a/general/datasets/PoplarPublish/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-http://bioenergycenter.org/besc/gwas/
diff --git a/general/datasets/PoplarPublish/summary.rtf b/general/datasets/PoplarPublish/summary.rtf
deleted file mode 100644
index ab9c38a..0000000
--- a/general/datasets/PoplarPublish/summary.rtf
+++ /dev/null
@@ -1,8 +0,0 @@
-Full article available here.
-
-
- - In order to uncover the genetic basis of phenotypic trait variation, we used 448 unrelated wild accessions of black cottonwood (Populus trichocarpa) from much of its range in western North America. Extensive data from large-scale trait phenotyping (with spatial and temporal replications within a common garden) and genotyping (with a 34 K Populus single nucleotide polymorphism (SNP) array) of all accessions were used for gene discovery in a genome-wide association study (GWAS).
- - We performed GWAS with 40 biomass, ecophysiology and phenology traits and 29 355 filtered SNPs representing 3518 genes. The association analyses were carried out using a Unified Mixed Model accounting for population structure effects among accessions.
- - We uncovered 410 significant SNPs using a Bonferroni-corrected threshold (P<1.79106). Markers were found across 19 chromosomes, explained 1–13% of trait variation, and implicated 275 unique genes in trait associations. Phenology had the largest number of associated genes (240 genes), followed by biomass (53 genes) and ecophysiology traits (25 genes).
- - The GWAS results propose numerous loci for further investigation. Many traits had significant associations with multiple genes, underscoring their genetic complexity. Genes were also identified with multiple trait associations within and/or across trait categories. In some cases, traits were genetically correlated while in others they were not.
-
diff --git a/general/datasets/Poplarpublish/acknowledgment.rtf b/general/datasets/Poplarpublish/acknowledgment.rtf
new file mode 100644
index 0000000..b137fef
--- /dev/null
+++ b/general/datasets/Poplarpublish/acknowledgment.rtf
@@ -0,0 +1 @@
+We thank L. E. Gunter, M. S. Azam, E. Drewes, N. Farzaneh, L. Liao, E. Moreno, L. Muenter and L. Quamme for data monitoring, collection and image presentation. We also thank anonymous reviewers for their suggestions and revisions in improving the manuscript. This work was supported by the Genome British Columbia Applied Genomics Innovation Program (Project 103BIO) and Genome Canada Large-Scale Applied Research Project (Project 168BIO) funds to R.D.G., J.E., Q.C.B.C., Y.A.E-K., S.D.M. and C.J.D. and by funds within the BioEnergy Science Center, a US Department of Energy Bioenergy Research Facility under contract DE–AC05–00OR22725.
diff --git a/general/datasets/Poplarpublish/citation.rtf b/general/datasets/Poplarpublish/citation.rtf
new file mode 100644
index 0000000..84e4c06
--- /dev/null
+++ b/general/datasets/Poplarpublish/citation.rtf
@@ -0,0 +1,3 @@
+Athena D. McKown1*, Jaroslav Kla´psˇteˇ1,2*, Robert D. Guy1, Armando Geraldes3, Ilga Porth1,4, Jan Hannemann5, Michael Friedmann3, Wellington Muchero6, Gerald A. Tuskan6, J€urgen Ehlting5, Quentin C. B. Cronk3, Yousry A. El-Kassaby1, Shawn D. Mansfield4 and Carl J. Douglas3
+
+1Department of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, Forest Sciences Centre, 2424 Main Mall, Vancouver, BC, V6T 1Z4, Canada; 2Department of Dendrology and Forest Tree Breeding, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague 165 21, Czech Republic; 3Department of Botany, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada; 4Department of Wood Science, Faculty of Forestry, University of British Columbia, Forest Sciences Centre, 2424 Main Mall, Vancouver, BC, V6T 1Z4, Canada; 5Department of Biology and Centre for Forest Biology, University of Victoria, Victoria, BC, V8W 3N5, Canada; 6BioSciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
diff --git a/general/datasets/Poplarpublish/platform.rtf b/general/datasets/Poplarpublish/platform.rtf
new file mode 100644
index 0000000..228a076
--- /dev/null
+++ b/general/datasets/Poplarpublish/platform.rtf
@@ -0,0 +1 @@
+Illumina iSelect Infinium 34K Populus SNP genotyping array
diff --git a/general/datasets/Poplarpublish/processing.rtf b/general/datasets/Poplarpublish/processing.rtf
new file mode 100644
index 0000000..9a6b788
--- /dev/null
+++ b/general/datasets/Poplarpublish/processing.rtf
@@ -0,0 +1 @@
+http://bioenergycenter.org/besc/gwas/
diff --git a/general/datasets/Poplarpublish/summary.rtf b/general/datasets/Poplarpublish/summary.rtf
new file mode 100644
index 0000000..ab9c38a
--- /dev/null
+++ b/general/datasets/Poplarpublish/summary.rtf
@@ -0,0 +1,8 @@
+Full article available here.
+
+
+ - In order to uncover the genetic basis of phenotypic trait variation, we used 448 unrelated wild accessions of black cottonwood (Populus trichocarpa) from much of its range in western North America. Extensive data from large-scale trait phenotyping (with spatial and temporal replications within a common garden) and genotyping (with a 34 K Populus single nucleotide polymorphism (SNP) array) of all accessions were used for gene discovery in a genome-wide association study (GWAS).
+ - We performed GWAS with 40 biomass, ecophysiology and phenology traits and 29 355 filtered SNPs representing 3518 genes. The association analyses were carried out using a Unified Mixed Model accounting for population structure effects among accessions.
+ - We uncovered 410 significant SNPs using a Bonferroni-corrected threshold (P<1.79106). Markers were found across 19 chromosomes, explained 1–13% of trait variation, and implicated 275 unique genes in trait associations. Phenology had the largest number of associated genes (240 genes), followed by biomass (53 genes) and ecophysiology traits (25 genes).
+ - The GWAS results propose numerous loci for further investigation. Many traits had significant associations with multiple genes, underscoring their genetic complexity. Genes were also identified with multiple trait associations within and/or across trait categories. In some cases, traits were genetically correlated while in others they were not.
+
diff --git a/general/datasets/Psu_b6d2f2_0812/experiment-type.rtf b/general/datasets/Psu_b6d2f2_0812/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Psu_b6d2f2_0812/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Psu_b6d2f2_0812/platform.rtf b/general/datasets/Psu_b6d2f2_0812/platform.rtf
new file mode 100644
index 0000000..7b362a7
--- /dev/null
+++ b/general/datasets/Psu_b6d2f2_0812/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 Array. All probe sets represented on the GeneChip Mouse Expression Set 430 are included on the GeneChip Mouse Genome 430 2.0 Array. The sequences from which these probe sets were derived were selected from GenBank«, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 107, June 2002) and then refined by analysis and comparison with the publicly available draft assembly of the mouse genome from the Whitehead Institute for Genome Research (MGSC, April 2002).
diff --git a/general/datasets/Psu_b6d2f2_0812/summary.rtf b/general/datasets/Psu_b6d2f2_0812/summary.rtf
new file mode 100644
index 0000000..f7a3b5d
--- /dev/null
+++ b/general/datasets/Psu_b6d2f2_0812/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 153, Name: PSU B6D2F2 Muscle Affy Mouse Genome 430 2.0 (Aug12)
diff --git a/general/datasets/Psu_b6d2f2_m0812/platform.rtf b/general/datasets/Psu_b6d2f2_m0812/platform.rtf
new file mode 100644
index 0000000..7b362a7
--- /dev/null
+++ b/general/datasets/Psu_b6d2f2_m0812/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Mouse Genome 430 2.0 Array. All probe sets represented on the GeneChip Mouse Expression Set 430 are included on the GeneChip Mouse Genome 430 2.0 Array. The sequences from which these probe sets were derived were selected from GenBank«, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 107, June 2002) and then refined by analysis and comparison with the publicly available draft assembly of the mouse genome from the Whitehead Institute for Genome Research (MGSC, April 2002).
diff --git a/general/datasets/Psu_b6d2f2_m0812/summary.rtf b/general/datasets/Psu_b6d2f2_m0812/summary.rtf
new file mode 100644
index 0000000..f7a3b5d
--- /dev/null
+++ b/general/datasets/Psu_b6d2f2_m0812/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 153, Name: PSU B6D2F2 Muscle Affy Mouse Genome 430 2.0 (Aug12)
diff --git a/general/datasets/RTI_RCMRC_BXDFecMet0814/acknowledgment.rtf b/general/datasets/RTI_RCMRC_BXDFecMet0814/acknowledgment.rtf
deleted file mode 100644
index 57f0c02..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMet0814/acknowledgment.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-This work done in collaboration with RTI under a special pilot project grant from the RCMRC Center.
-
-1. Dr. Susan Sumner. PI of grant
-
-2. Dr. Robert Clarke. Lead investigator on this project
-
-3. Surja Dhungana
diff --git a/general/datasets/RTI_RCMRC_BXDFecMet0814/cases.rtf b/general/datasets/RTI_RCMRC_BXDFecMet0814/cases.rtf
deleted file mode 100644
index f06f259..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMet0814/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-All animals are females sacrificed as part of an NIA grant to RW Williams to study effects of diet on aging (longevity) in the BXD strains. A subset of females were sacrificed at specific ages for tissue harvesting and fecal pelltets from these animals were removed from the large intestine by K. Mozhui and snap frozen in liquid nitrogen prior to shipping to RTI.
-
-Three large data sets in GeneNetwork with a common set of 4091 metabolite entries per data set (high fat, chow diet, and combined) and for as many as 18 strains.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMet0814/experiment-design.rtf b/general/datasets/RTI_RCMRC_BXDFecMet0814/experiment-design.rtf
deleted file mode 100644
index 4ee0a7b..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMet0814/experiment-design.rtf
+++ /dev/null
@@ -1,17 +0,0 @@
-Sample Preparation Summary
-
-
- - Feces were extracted in 95:5 water:methanol
- - Extracts were prepared for UPLC-QTOF-MS analysis
-
-
-Instruments for LC-MS Analysis
-Waters SYNAPT G2 QTOF with Acquity UPLC (Waters Corporation, MA)
-MS data collected over 50-1000 m/z was collected in the positive and negative ion modes.
-
-UPLC-MS Solutions(Reversed Phase)
-Mobile Phase A (Reversed-Phase)—Water with 0.1% Formic Acid
-Mobile Phase B (Reversed-Phase)—Methanol with 0.1% Formic Acid
-Column: Waters Acquity BEH HSS T3, 2.1 x 100 mm at 50 °C
-
-
diff --git a/general/datasets/RTI_RCMRC_BXDFecMet0814/notes.rtf b/general/datasets/RTI_RCMRC_BXDFecMet0814/notes.rtf
deleted file mode 100644
index 8da96fa..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMet0814/notes.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-For symbols of metabolites if the differences were greater than .0003 proportional m/z units (m/z difference divided by m/z value) then the symbol was labeled "circa" after the atomic composition.
-
-For description of metabolites if the proportional difference of the m/z ratio between Evan's EPFL Polar metabolite assignments and RTI assignments was very low (<.0001 proportional m/z units) then the symbol and description was taken directly from Evan's metabolite file, but if differences were between 0.0001 and about .0003 proportional m/z units then the descriptions were labeled "Putative" . If the differences were greater than .0003 units, then the descriptions were labeled "Provisional". For example, "Provisional assignment. Vanilpyruvic acid is a catecholamine metabolite and precursor to vanilactic acid. Accumulation in urine is indicative of Aromatic L-aminoacid decarboxylase deficiency (PMID 16288991)."
-
- by Rob Williams and Arthur Centeno, Aug 25, 2014
diff --git a/general/datasets/RTI_RCMRC_BXDFecMet0814/platform.rtf b/general/datasets/RTI_RCMRC_BXDFecMet0814/platform.rtf
deleted file mode 100644
index 072286a..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMet0814/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This is LC-MS data. Analysis exploited a Chenomx library at RTI with many updated metabolite identifications from the standard Chenomx library. Note that a single m/z ratio can correspond to multiple metabolites.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMet0814/summary.rtf b/general/datasets/RTI_RCMRC_BXDFecMet0814/summary.rtf
deleted file mode 100644
index 10218c7..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMet0814/summary.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-The goal of this project is to study expression of a large set of defined and undefined metabolites in fecal samples from a genetically diverse set of BXD mouse strains (females) raised either on a high fat diet or low fat diet. Samples were taken from animals at sacrifices directly from the large intestine.
-
-Aim: Effect of genetics and diet on fecal metabolomics
-
-Use UPLC-MS Broad Spectrum Metabolomics to study:
-
-
-
-To capture the most signal, all samples were analyzed under positive and negative ion mode using a reversed-phase separation.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMet0814/tissue.rtf b/general/datasets/RTI_RCMRC_BXDFecMet0814/tissue.rtf
deleted file mode 100644
index 3a26107..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMet0814/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Fresh fecal pellets taken directly at dissection from the lower GI tract by Dr. Khyobeni Mozhui.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/acknowledgment.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHF0814/acknowledgment.rtf
deleted file mode 100644
index 57f0c02..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/acknowledgment.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-This work done in collaboration with RTI under a special pilot project grant from the RCMRC Center.
-
-1. Dr. Susan Sumner. PI of grant
-
-2. Dr. Robert Clarke. Lead investigator on this project
-
-3. Surja Dhungana
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/cases.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHF0814/cases.rtf
deleted file mode 100644
index f06f259..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-All animals are females sacrificed as part of an NIA grant to RW Williams to study effects of diet on aging (longevity) in the BXD strains. A subset of females were sacrificed at specific ages for tissue harvesting and fecal pelltets from these animals were removed from the large intestine by K. Mozhui and snap frozen in liquid nitrogen prior to shipping to RTI.
-
-Three large data sets in GeneNetwork with a common set of 4091 metabolite entries per data set (high fat, chow diet, and combined) and for as many as 18 strains.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/experiment-design.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHF0814/experiment-design.rtf
deleted file mode 100644
index 4ee0a7b..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/experiment-design.rtf
+++ /dev/null
@@ -1,17 +0,0 @@
-Sample Preparation Summary
-
-
- - Feces were extracted in 95:5 water:methanol
- - Extracts were prepared for UPLC-QTOF-MS analysis
-
-
-Instruments for LC-MS Analysis
-Waters SYNAPT G2 QTOF with Acquity UPLC (Waters Corporation, MA)
-MS data collected over 50-1000 m/z was collected in the positive and negative ion modes.
-
-UPLC-MS Solutions(Reversed Phase)
-Mobile Phase A (Reversed-Phase)—Water with 0.1% Formic Acid
-Mobile Phase B (Reversed-Phase)—Methanol with 0.1% Formic Acid
-Column: Waters Acquity BEH HSS T3, 2.1 x 100 mm at 50 °C
-
-
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/notes.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHF0814/notes.rtf
deleted file mode 100644
index 8da96fa..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/notes.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-For symbols of metabolites if the differences were greater than .0003 proportional m/z units (m/z difference divided by m/z value) then the symbol was labeled "circa" after the atomic composition.
-
-For description of metabolites if the proportional difference of the m/z ratio between Evan's EPFL Polar metabolite assignments and RTI assignments was very low (<.0001 proportional m/z units) then the symbol and description was taken directly from Evan's metabolite file, but if differences were between 0.0001 and about .0003 proportional m/z units then the descriptions were labeled "Putative" . If the differences were greater than .0003 units, then the descriptions were labeled "Provisional". For example, "Provisional assignment. Vanilpyruvic acid is a catecholamine metabolite and precursor to vanilactic acid. Accumulation in urine is indicative of Aromatic L-aminoacid decarboxylase deficiency (PMID 16288991)."
-
- by Rob Williams and Arthur Centeno, Aug 25, 2014
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/platform.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHF0814/platform.rtf
deleted file mode 100644
index 072286a..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This is LC-MS data. Analysis exploited a Chenomx library at RTI with many updated metabolite identifications from the standard Chenomx library. Note that a single m/z ratio can correspond to multiple metabolites.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/summary.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHF0814/summary.rtf
deleted file mode 100644
index 10218c7..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/summary.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-The goal of this project is to study expression of a large set of defined and undefined metabolites in fecal samples from a genetically diverse set of BXD mouse strains (females) raised either on a high fat diet or low fat diet. Samples were taken from animals at sacrifices directly from the large intestine.
-
-Aim: Effect of genetics and diet on fecal metabolomics
-
-Use UPLC-MS Broad Spectrum Metabolomics to study:
-
-
-
-To capture the most signal, all samples were analyzed under positive and negative ion mode using a reversed-phase separation.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/tissue.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHF0814/tissue.rtf
deleted file mode 100644
index 3a26107..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHF0814/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Fresh fecal pellets taken directly at dissection from the lower GI tract by Dr. Khyobeni Mozhui.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/acknowledgment.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/acknowledgment.rtf
deleted file mode 100644
index 57f0c02..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/acknowledgment.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-This work done in collaboration with RTI under a special pilot project grant from the RCMRC Center.
-
-1. Dr. Susan Sumner. PI of grant
-
-2. Dr. Robert Clarke. Lead investigator on this project
-
-3. Surja Dhungana
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/cases.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/cases.rtf
deleted file mode 100644
index f06f259..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-All animals are females sacrificed as part of an NIA grant to RW Williams to study effects of diet on aging (longevity) in the BXD strains. A subset of females were sacrificed at specific ages for tissue harvesting and fecal pelltets from these animals were removed from the large intestine by K. Mozhui and snap frozen in liquid nitrogen prior to shipping to RTI.
-
-Three large data sets in GeneNetwork with a common set of 4091 metabolite entries per data set (high fat, chow diet, and combined) and for as many as 18 strains.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/experiment-design.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/experiment-design.rtf
deleted file mode 100644
index 4ee0a7b..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/experiment-design.rtf
+++ /dev/null
@@ -1,17 +0,0 @@
-Sample Preparation Summary
-
-
- - Feces were extracted in 95:5 water:methanol
- - Extracts were prepared for UPLC-QTOF-MS analysis
-
-
-Instruments for LC-MS Analysis
-Waters SYNAPT G2 QTOF with Acquity UPLC (Waters Corporation, MA)
-MS data collected over 50-1000 m/z was collected in the positive and negative ion modes.
-
-UPLC-MS Solutions(Reversed Phase)
-Mobile Phase A (Reversed-Phase)—Water with 0.1% Formic Acid
-Mobile Phase B (Reversed-Phase)—Methanol with 0.1% Formic Acid
-Column: Waters Acquity BEH HSS T3, 2.1 x 100 mm at 50 °C
-
-
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/notes.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/notes.rtf
deleted file mode 100644
index 8da96fa..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/notes.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-For symbols of metabolites if the differences were greater than .0003 proportional m/z units (m/z difference divided by m/z value) then the symbol was labeled "circa" after the atomic composition.
-
-For description of metabolites if the proportional difference of the m/z ratio between Evan's EPFL Polar metabolite assignments and RTI assignments was very low (<.0001 proportional m/z units) then the symbol and description was taken directly from Evan's metabolite file, but if differences were between 0.0001 and about .0003 proportional m/z units then the descriptions were labeled "Putative" . If the differences were greater than .0003 units, then the descriptions were labeled "Provisional". For example, "Provisional assignment. Vanilpyruvic acid is a catecholamine metabolite and precursor to vanilactic acid. Accumulation in urine is indicative of Aromatic L-aminoacid decarboxylase deficiency (PMID 16288991)."
-
- by Rob Williams and Arthur Centeno, Aug 25, 2014
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/platform.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/platform.rtf
deleted file mode 100644
index 072286a..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This is LC-MS data. Analysis exploited a Chenomx library at RTI with many updated metabolite identifications from the standard Chenomx library. Note that a single m/z ratio can correspond to multiple metabolites.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/summary.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/summary.rtf
deleted file mode 100644
index 10218c7..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/summary.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-The goal of this project is to study expression of a large set of defined and undefined metabolites in fecal samples from a genetically diverse set of BXD mouse strains (females) raised either on a high fat diet or low fat diet. Samples were taken from animals at sacrifices directly from the large intestine.
-
-Aim: Effect of genetics and diet on fecal metabolomics
-
-Use UPLC-MS Broad Spectrum Metabolomics to study:
-
-
-
-To capture the most signal, all samples were analyzed under positive and negative ion mode using a reversed-phase separation.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/tissue.rtf b/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/tissue.rtf
deleted file mode 100644
index 3a26107..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetHFlog0814/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Fresh fecal pellets taken directly at dissection from the lower GI tract by Dr. Khyobeni Mozhui.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/acknowledgment.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLF0814/acknowledgment.rtf
deleted file mode 100644
index 57f0c02..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/acknowledgment.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-This work done in collaboration with RTI under a special pilot project grant from the RCMRC Center.
-
-1. Dr. Susan Sumner. PI of grant
-
-2. Dr. Robert Clarke. Lead investigator on this project
-
-3. Surja Dhungana
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/cases.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLF0814/cases.rtf
deleted file mode 100644
index f06f259..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-All animals are females sacrificed as part of an NIA grant to RW Williams to study effects of diet on aging (longevity) in the BXD strains. A subset of females were sacrificed at specific ages for tissue harvesting and fecal pelltets from these animals were removed from the large intestine by K. Mozhui and snap frozen in liquid nitrogen prior to shipping to RTI.
-
-Three large data sets in GeneNetwork with a common set of 4091 metabolite entries per data set (high fat, chow diet, and combined) and for as many as 18 strains.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/experiment-design.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLF0814/experiment-design.rtf
deleted file mode 100644
index 4ee0a7b..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/experiment-design.rtf
+++ /dev/null
@@ -1,17 +0,0 @@
-Sample Preparation Summary
-
-
- - Feces were extracted in 95:5 water:methanol
- - Extracts were prepared for UPLC-QTOF-MS analysis
-
-
-Instruments for LC-MS Analysis
-Waters SYNAPT G2 QTOF with Acquity UPLC (Waters Corporation, MA)
-MS data collected over 50-1000 m/z was collected in the positive and negative ion modes.
-
-UPLC-MS Solutions(Reversed Phase)
-Mobile Phase A (Reversed-Phase)—Water with 0.1% Formic Acid
-Mobile Phase B (Reversed-Phase)—Methanol with 0.1% Formic Acid
-Column: Waters Acquity BEH HSS T3, 2.1 x 100 mm at 50 °C
-
-
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/notes.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLF0814/notes.rtf
deleted file mode 100644
index 8da96fa..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/notes.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-For symbols of metabolites if the differences were greater than .0003 proportional m/z units (m/z difference divided by m/z value) then the symbol was labeled "circa" after the atomic composition.
-
-For description of metabolites if the proportional difference of the m/z ratio between Evan's EPFL Polar metabolite assignments and RTI assignments was very low (<.0001 proportional m/z units) then the symbol and description was taken directly from Evan's metabolite file, but if differences were between 0.0001 and about .0003 proportional m/z units then the descriptions were labeled "Putative" . If the differences were greater than .0003 units, then the descriptions were labeled "Provisional". For example, "Provisional assignment. Vanilpyruvic acid is a catecholamine metabolite and precursor to vanilactic acid. Accumulation in urine is indicative of Aromatic L-aminoacid decarboxylase deficiency (PMID 16288991)."
-
- by Rob Williams and Arthur Centeno, Aug 25, 2014
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/platform.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLF0814/platform.rtf
deleted file mode 100644
index 072286a..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This is LC-MS data. Analysis exploited a Chenomx library at RTI with many updated metabolite identifications from the standard Chenomx library. Note that a single m/z ratio can correspond to multiple metabolites.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/summary.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLF0814/summary.rtf
deleted file mode 100644
index 10218c7..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/summary.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-The goal of this project is to study expression of a large set of defined and undefined metabolites in fecal samples from a genetically diverse set of BXD mouse strains (females) raised either on a high fat diet or low fat diet. Samples were taken from animals at sacrifices directly from the large intestine.
-
-Aim: Effect of genetics and diet on fecal metabolomics
-
-Use UPLC-MS Broad Spectrum Metabolomics to study:
-
-
-
-To capture the most signal, all samples were analyzed under positive and negative ion mode using a reversed-phase separation.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/tissue.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLF0814/tissue.rtf
deleted file mode 100644
index 3a26107..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLF0814/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Fresh fecal pellets taken directly at dissection from the lower GI tract by Dr. Khyobeni Mozhui.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/acknowledgment.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/acknowledgment.rtf
deleted file mode 100644
index 57f0c02..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/acknowledgment.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-This work done in collaboration with RTI under a special pilot project grant from the RCMRC Center.
-
-1. Dr. Susan Sumner. PI of grant
-
-2. Dr. Robert Clarke. Lead investigator on this project
-
-3. Surja Dhungana
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/cases.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/cases.rtf
deleted file mode 100644
index f06f259..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-All animals are females sacrificed as part of an NIA grant to RW Williams to study effects of diet on aging (longevity) in the BXD strains. A subset of females were sacrificed at specific ages for tissue harvesting and fecal pelltets from these animals were removed from the large intestine by K. Mozhui and snap frozen in liquid nitrogen prior to shipping to RTI.
-
-Three large data sets in GeneNetwork with a common set of 4091 metabolite entries per data set (high fat, chow diet, and combined) and for as many as 18 strains.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/experiment-design.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/experiment-design.rtf
deleted file mode 100644
index 4ee0a7b..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/experiment-design.rtf
+++ /dev/null
@@ -1,17 +0,0 @@
-Sample Preparation Summary
-
-
- - Feces were extracted in 95:5 water:methanol
- - Extracts were prepared for UPLC-QTOF-MS analysis
-
-
-Instruments for LC-MS Analysis
-Waters SYNAPT G2 QTOF with Acquity UPLC (Waters Corporation, MA)
-MS data collected over 50-1000 m/z was collected in the positive and negative ion modes.
-
-UPLC-MS Solutions(Reversed Phase)
-Mobile Phase A (Reversed-Phase)—Water with 0.1% Formic Acid
-Mobile Phase B (Reversed-Phase)—Methanol with 0.1% Formic Acid
-Column: Waters Acquity BEH HSS T3, 2.1 x 100 mm at 50 °C
-
-
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/notes.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/notes.rtf
deleted file mode 100644
index 8da96fa..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/notes.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-For symbols of metabolites if the differences were greater than .0003 proportional m/z units (m/z difference divided by m/z value) then the symbol was labeled "circa" after the atomic composition.
-
-For description of metabolites if the proportional difference of the m/z ratio between Evan's EPFL Polar metabolite assignments and RTI assignments was very low (<.0001 proportional m/z units) then the symbol and description was taken directly from Evan's metabolite file, but if differences were between 0.0001 and about .0003 proportional m/z units then the descriptions were labeled "Putative" . If the differences were greater than .0003 units, then the descriptions were labeled "Provisional". For example, "Provisional assignment. Vanilpyruvic acid is a catecholamine metabolite and precursor to vanilactic acid. Accumulation in urine is indicative of Aromatic L-aminoacid decarboxylase deficiency (PMID 16288991)."
-
- by Rob Williams and Arthur Centeno, Aug 25, 2014
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/platform.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/platform.rtf
deleted file mode 100644
index 072286a..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This is LC-MS data. Analysis exploited a Chenomx library at RTI with many updated metabolite identifications from the standard Chenomx library. Note that a single m/z ratio can correspond to multiple metabolites.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/summary.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/summary.rtf
deleted file mode 100644
index 10218c7..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/summary.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-The goal of this project is to study expression of a large set of defined and undefined metabolites in fecal samples from a genetically diverse set of BXD mouse strains (females) raised either on a high fat diet or low fat diet. Samples were taken from animals at sacrifices directly from the large intestine.
-
-Aim: Effect of genetics and diet on fecal metabolomics
-
-Use UPLC-MS Broad Spectrum Metabolomics to study:
-
-
-
-To capture the most signal, all samples were analyzed under positive and negative ion mode using a reversed-phase separation.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/tissue.rtf b/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/tissue.rtf
deleted file mode 100644
index 3a26107..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetLFlog0814/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Fresh fecal pellets taken directly at dissection from the lower GI tract by Dr. Khyobeni Mozhui.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/acknowledgment.rtf b/general/datasets/RTI_RCMRC_BXDFecMetlog0814/acknowledgment.rtf
deleted file mode 100644
index 57f0c02..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/acknowledgment.rtf
+++ /dev/null
@@ -1,7 +0,0 @@
-This work done in collaboration with RTI under a special pilot project grant from the RCMRC Center.
-
-1. Dr. Susan Sumner. PI of grant
-
-2. Dr. Robert Clarke. Lead investigator on this project
-
-3. Surja Dhungana
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/cases.rtf b/general/datasets/RTI_RCMRC_BXDFecMetlog0814/cases.rtf
deleted file mode 100644
index f06f259..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-All animals are females sacrificed as part of an NIA grant to RW Williams to study effects of diet on aging (longevity) in the BXD strains. A subset of females were sacrificed at specific ages for tissue harvesting and fecal pelltets from these animals were removed from the large intestine by K. Mozhui and snap frozen in liquid nitrogen prior to shipping to RTI.
-
-Three large data sets in GeneNetwork with a common set of 4091 metabolite entries per data set (high fat, chow diet, and combined) and for as many as 18 strains.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/experiment-design.rtf b/general/datasets/RTI_RCMRC_BXDFecMetlog0814/experiment-design.rtf
deleted file mode 100644
index 4ee0a7b..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/experiment-design.rtf
+++ /dev/null
@@ -1,17 +0,0 @@
-Sample Preparation Summary
-
-
- - Feces were extracted in 95:5 water:methanol
- - Extracts were prepared for UPLC-QTOF-MS analysis
-
-
-Instruments for LC-MS Analysis
-Waters SYNAPT G2 QTOF with Acquity UPLC (Waters Corporation, MA)
-MS data collected over 50-1000 m/z was collected in the positive and negative ion modes.
-
-UPLC-MS Solutions(Reversed Phase)
-Mobile Phase A (Reversed-Phase)—Water with 0.1% Formic Acid
-Mobile Phase B (Reversed-Phase)—Methanol with 0.1% Formic Acid
-Column: Waters Acquity BEH HSS T3, 2.1 x 100 mm at 50 °C
-
-
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/notes.rtf b/general/datasets/RTI_RCMRC_BXDFecMetlog0814/notes.rtf
deleted file mode 100644
index 8da96fa..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/notes.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-For symbols of metabolites if the differences were greater than .0003 proportional m/z units (m/z difference divided by m/z value) then the symbol was labeled "circa" after the atomic composition.
-
-For description of metabolites if the proportional difference of the m/z ratio between Evan's EPFL Polar metabolite assignments and RTI assignments was very low (<.0001 proportional m/z units) then the symbol and description was taken directly from Evan's metabolite file, but if differences were between 0.0001 and about .0003 proportional m/z units then the descriptions were labeled "Putative" . If the differences were greater than .0003 units, then the descriptions were labeled "Provisional". For example, "Provisional assignment. Vanilpyruvic acid is a catecholamine metabolite and precursor to vanilactic acid. Accumulation in urine is indicative of Aromatic L-aminoacid decarboxylase deficiency (PMID 16288991)."
-
- by Rob Williams and Arthur Centeno, Aug 25, 2014
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/platform.rtf b/general/datasets/RTI_RCMRC_BXDFecMetlog0814/platform.rtf
deleted file mode 100644
index 072286a..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This is LC-MS data. Analysis exploited a Chenomx library at RTI with many updated metabolite identifications from the standard Chenomx library. Note that a single m/z ratio can correspond to multiple metabolites.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/summary.rtf b/general/datasets/RTI_RCMRC_BXDFecMetlog0814/summary.rtf
deleted file mode 100644
index 10218c7..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/summary.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-The goal of this project is to study expression of a large set of defined and undefined metabolites in fecal samples from a genetically diverse set of BXD mouse strains (females) raised either on a high fat diet or low fat diet. Samples were taken from animals at sacrifices directly from the large intestine.
-
-Aim: Effect of genetics and diet on fecal metabolomics
-
-Use UPLC-MS Broad Spectrum Metabolomics to study:
-
-
-
-To capture the most signal, all samples were analyzed under positive and negative ion mode using a reversed-phase separation.
diff --git a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/tissue.rtf b/general/datasets/RTI_RCMRC_BXDFecMetlog0814/tissue.rtf
deleted file mode 100644
index 3a26107..0000000
--- a/general/datasets/RTI_RCMRC_BXDFecMetlog0814/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Fresh fecal pellets taken directly at dissection from the lower GI tract by Dr. Khyobeni Mozhui.
diff --git a/general/datasets/Riken_Wu_BXD_CDHF_WAdip_0920/experiment-design.rtf b/general/datasets/Riken_Wu_BXD_CDHF_WAdip_0920/experiment-design.rtf
deleted file mode 100644
index 6bd1793..0000000
--- a/general/datasets/Riken_Wu_BXD_CDHF_WAdip_0920/experiment-design.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Sample preparation for proteomic analysis
-
-Proteins were extracted from adipose tissue samples in lysis buffer containing 12 mM sodium deoxycholate, 12 mM sodium N-dodecanoylsarcosinate, and 100 mM Tris.Cl pH 9.0, with cOmplete, mini, EDTA-free Protease Inhibitor Cocktail (Roche, Switzerland), using homogenization with a glass dounce followed by sonication for 15 minutes using a Bioruptor water bath sonicator on high power, with cycles of one min sonication followed by one min rest (Cosmo Bio Co. Ltd., Japan). The samples were centrifuged at 18,000 x g, for 20 min at 4 oC and the supernatant fractions were taken. Protein concentrations were determined using a Pierce BCA Assay Kit (Thermo Fisher Scientific, USA), according to manufacturer’s instructions. Samples were prepared for liquid chromatography tandem mass spectrometry (LC-M/MS) using the Phase Transfer Surfactant Method (Masuda et al., 2008; Masuda et al., 2009), with minor modifications as previously described (Mostafa et al., 2020). Afterwards, dried Lys-C/tryptic peptides were dissolved in 0.1% TFA and desalted using MonoSpin C18 columns (GL Sciences Inc., Japan). Peptides were eluted from C18 columns in 0.1% (v/v) TFA in 50% (v/v) acetonitrile and dried in a centrifugal vacuum concentrator. Tryptic peptides were dissolved in 0.1% (v/v) formic acid, 3% (v/v) acetonitrile in water for MS analysis and the peptide concentrations were determined using a Pierce Quantitative Colorimetric Peptide Assay Kit (Thermo Fisher). A portion of the peptides from the samples were pooled and fractionated using a Pierce High pH Reversed-Phase (HPRP) Peptide Fractionation Kit (Thermo Fisher) to generate a spectral library.
-
-MS measurement
-
-Samples were measured using a Q Exactive Plus Orbitrap LC–MS/MS System (Thermo Fisher), equipped with a Nanospray Flex ion source. Peptides were separated on 3-µm particle, 75-µm inner diameter, 12-cm filling length C18 columns (Nikkyo Technos Co., Ltd., Japan). For each sample, 600 ng was injected and the samples were measured with data-independent acquisition (DIA). For HPRP fractions, 450 ng was injected and the samples were measured with data-dependent acquisition (DDA). LC-MS/MS conditions were as previously described (Mostafa et al., 2020), except for DDA the first mass for MS2 scans was not fixed and for DIA the AGC target of DIA segments was 3e6.
-
-Protein identification and quantification
-
-Raw files from DDA measurements were searched against a mouse-specific database (uniprot-reviewed_Mus_musculus_10090_.fasta) using Proteome Discoverer v2.4 software (Thermo Fisher). Filtered output was used to generate a sample-specific spectral library using Spectronaut software (Biognosys, Switzerland). Raw files from DIA measurements were used for quantitative data extraction with the generated spectral library, as previously described (Mostafa et al., 2020). FDR was estimated with the mProphet approach (Reiter et al., 2011) and set to 0.01 at both peptide precursor level and protein level (Rosenberger et al., 2017).
-
-References
-
-Masuda, T., Tomita, M., and Ishihama, Y. (2008) Phase transfer surfactant-aided trypsin digestion for membrane proteome analysis. J. Proteome Res. 7, 731-740.
-
-Masuda, T., Saito, N., Tomita, M., and Ishihama, Y. (2009) Unbiased quantification of Escherichia coli membrane proteome using phase transfer surfactants. Mol. Cell. Proteomics 8, 2770-2777.
-
-Mostafa, D., Yanagiya, A., Georgiadou, E., Wu, Y., Stylianides, T., Rutter, G. A., Suzuki, T., & Yamamoto, T. (2020). Loss of β-cell identity and diabetic phenotype in mice caused by disruption of CNOT3-dependent mRNA deadenylation. Commun. Biol. 3, 476.
-
-Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Hengartner, M. O., and Aebersold, R. (2011) mProphet: automated data processing and statistical validation for large scale SRM experiments. Nat. Methods 8, 430–435.
-
-Rosenberger, G., Bludau, I., Schmitt, U., Heusel, M., Hunter, C. L., Liu, Y., MacCoss, M. J., MacLean, B. X., Nesvizhskii, A. I., Pedrioli, P. G. A., Reiter, L., Röst, H. L., Tate, S., Ting, Y. S., Collins, B. C., and Aebersold, R. (2017) Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses. Nat. Methods 14, 921–927.
diff --git a/general/datasets/Riken_Wu_BXD_CDHF_WAdip_0920/specifics.rtf b/general/datasets/Riken_Wu_BXD_CDHF_WAdip_0920/specifics.rtf
deleted file mode 100644
index 68167de..0000000
--- a/general/datasets/Riken_Wu_BXD_CDHF_WAdip_0920/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Riken-Wu BXD CD-HF White Adipose Proteome (Sep20)
\ No newline at end of file
diff --git a/general/datasets/Riken_Wu_BXD_CD_WAdip_0920/experiment-design.rtf b/general/datasets/Riken_Wu_BXD_CD_WAdip_0920/experiment-design.rtf
deleted file mode 100644
index 6bd1793..0000000
--- a/general/datasets/Riken_Wu_BXD_CD_WAdip_0920/experiment-design.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Sample preparation for proteomic analysis
-
-Proteins were extracted from adipose tissue samples in lysis buffer containing 12 mM sodium deoxycholate, 12 mM sodium N-dodecanoylsarcosinate, and 100 mM Tris.Cl pH 9.0, with cOmplete, mini, EDTA-free Protease Inhibitor Cocktail (Roche, Switzerland), using homogenization with a glass dounce followed by sonication for 15 minutes using a Bioruptor water bath sonicator on high power, with cycles of one min sonication followed by one min rest (Cosmo Bio Co. Ltd., Japan). The samples were centrifuged at 18,000 x g, for 20 min at 4 oC and the supernatant fractions were taken. Protein concentrations were determined using a Pierce BCA Assay Kit (Thermo Fisher Scientific, USA), according to manufacturer’s instructions. Samples were prepared for liquid chromatography tandem mass spectrometry (LC-M/MS) using the Phase Transfer Surfactant Method (Masuda et al., 2008; Masuda et al., 2009), with minor modifications as previously described (Mostafa et al., 2020). Afterwards, dried Lys-C/tryptic peptides were dissolved in 0.1% TFA and desalted using MonoSpin C18 columns (GL Sciences Inc., Japan). Peptides were eluted from C18 columns in 0.1% (v/v) TFA in 50% (v/v) acetonitrile and dried in a centrifugal vacuum concentrator. Tryptic peptides were dissolved in 0.1% (v/v) formic acid, 3% (v/v) acetonitrile in water for MS analysis and the peptide concentrations were determined using a Pierce Quantitative Colorimetric Peptide Assay Kit (Thermo Fisher). A portion of the peptides from the samples were pooled and fractionated using a Pierce High pH Reversed-Phase (HPRP) Peptide Fractionation Kit (Thermo Fisher) to generate a spectral library.
-
-MS measurement
-
-Samples were measured using a Q Exactive Plus Orbitrap LC–MS/MS System (Thermo Fisher), equipped with a Nanospray Flex ion source. Peptides were separated on 3-µm particle, 75-µm inner diameter, 12-cm filling length C18 columns (Nikkyo Technos Co., Ltd., Japan). For each sample, 600 ng was injected and the samples were measured with data-independent acquisition (DIA). For HPRP fractions, 450 ng was injected and the samples were measured with data-dependent acquisition (DDA). LC-MS/MS conditions were as previously described (Mostafa et al., 2020), except for DDA the first mass for MS2 scans was not fixed and for DIA the AGC target of DIA segments was 3e6.
-
-Protein identification and quantification
-
-Raw files from DDA measurements were searched against a mouse-specific database (uniprot-reviewed_Mus_musculus_10090_.fasta) using Proteome Discoverer v2.4 software (Thermo Fisher). Filtered output was used to generate a sample-specific spectral library using Spectronaut software (Biognosys, Switzerland). Raw files from DIA measurements were used for quantitative data extraction with the generated spectral library, as previously described (Mostafa et al., 2020). FDR was estimated with the mProphet approach (Reiter et al., 2011) and set to 0.01 at both peptide precursor level and protein level (Rosenberger et al., 2017).
-
-References
-
-Masuda, T., Tomita, M., and Ishihama, Y. (2008) Phase transfer surfactant-aided trypsin digestion for membrane proteome analysis. J. Proteome Res. 7, 731-740.
-
-Masuda, T., Saito, N., Tomita, M., and Ishihama, Y. (2009) Unbiased quantification of Escherichia coli membrane proteome using phase transfer surfactants. Mol. Cell. Proteomics 8, 2770-2777.
-
-Mostafa, D., Yanagiya, A., Georgiadou, E., Wu, Y., Stylianides, T., Rutter, G. A., Suzuki, T., & Yamamoto, T. (2020). Loss of β-cell identity and diabetic phenotype in mice caused by disruption of CNOT3-dependent mRNA deadenylation. Commun. Biol. 3, 476.
-
-Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Hengartner, M. O., and Aebersold, R. (2011) mProphet: automated data processing and statistical validation for large scale SRM experiments. Nat. Methods 8, 430–435.
-
-Rosenberger, G., Bludau, I., Schmitt, U., Heusel, M., Hunter, C. L., Liu, Y., MacCoss, M. J., MacLean, B. X., Nesvizhskii, A. I., Pedrioli, P. G. A., Reiter, L., Röst, H. L., Tate, S., Ting, Y. S., Collins, B. C., and Aebersold, R. (2017) Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses. Nat. Methods 14, 921–927.
diff --git a/general/datasets/Riken_Wu_BXD_CD_WAdip_0920/specifics.rtf b/general/datasets/Riken_Wu_BXD_CD_WAdip_0920/specifics.rtf
deleted file mode 100644
index 04d0771..0000000
--- a/general/datasets/Riken_Wu_BXD_CD_WAdip_0920/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-BXD CD White Adipose Proteome (Sep20)
\ No newline at end of file
diff --git a/general/datasets/Riken_Wu_BXD_HF_WAdip_0920/experiment-design.rtf b/general/datasets/Riken_Wu_BXD_HF_WAdip_0920/experiment-design.rtf
deleted file mode 100644
index 6bd1793..0000000
--- a/general/datasets/Riken_Wu_BXD_HF_WAdip_0920/experiment-design.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Sample preparation for proteomic analysis
-
-Proteins were extracted from adipose tissue samples in lysis buffer containing 12 mM sodium deoxycholate, 12 mM sodium N-dodecanoylsarcosinate, and 100 mM Tris.Cl pH 9.0, with cOmplete, mini, EDTA-free Protease Inhibitor Cocktail (Roche, Switzerland), using homogenization with a glass dounce followed by sonication for 15 minutes using a Bioruptor water bath sonicator on high power, with cycles of one min sonication followed by one min rest (Cosmo Bio Co. Ltd., Japan). The samples were centrifuged at 18,000 x g, for 20 min at 4 oC and the supernatant fractions were taken. Protein concentrations were determined using a Pierce BCA Assay Kit (Thermo Fisher Scientific, USA), according to manufacturer’s instructions. Samples were prepared for liquid chromatography tandem mass spectrometry (LC-M/MS) using the Phase Transfer Surfactant Method (Masuda et al., 2008; Masuda et al., 2009), with minor modifications as previously described (Mostafa et al., 2020). Afterwards, dried Lys-C/tryptic peptides were dissolved in 0.1% TFA and desalted using MonoSpin C18 columns (GL Sciences Inc., Japan). Peptides were eluted from C18 columns in 0.1% (v/v) TFA in 50% (v/v) acetonitrile and dried in a centrifugal vacuum concentrator. Tryptic peptides were dissolved in 0.1% (v/v) formic acid, 3% (v/v) acetonitrile in water for MS analysis and the peptide concentrations were determined using a Pierce Quantitative Colorimetric Peptide Assay Kit (Thermo Fisher). A portion of the peptides from the samples were pooled and fractionated using a Pierce High pH Reversed-Phase (HPRP) Peptide Fractionation Kit (Thermo Fisher) to generate a spectral library.
-
-MS measurement
-
-Samples were measured using a Q Exactive Plus Orbitrap LC–MS/MS System (Thermo Fisher), equipped with a Nanospray Flex ion source. Peptides were separated on 3-µm particle, 75-µm inner diameter, 12-cm filling length C18 columns (Nikkyo Technos Co., Ltd., Japan). For each sample, 600 ng was injected and the samples were measured with data-independent acquisition (DIA). For HPRP fractions, 450 ng was injected and the samples were measured with data-dependent acquisition (DDA). LC-MS/MS conditions were as previously described (Mostafa et al., 2020), except for DDA the first mass for MS2 scans was not fixed and for DIA the AGC target of DIA segments was 3e6.
-
-Protein identification and quantification
-
-Raw files from DDA measurements were searched against a mouse-specific database (uniprot-reviewed_Mus_musculus_10090_.fasta) using Proteome Discoverer v2.4 software (Thermo Fisher). Filtered output was used to generate a sample-specific spectral library using Spectronaut software (Biognosys, Switzerland). Raw files from DIA measurements were used for quantitative data extraction with the generated spectral library, as previously described (Mostafa et al., 2020). FDR was estimated with the mProphet approach (Reiter et al., 2011) and set to 0.01 at both peptide precursor level and protein level (Rosenberger et al., 2017).
-
-References
-
-Masuda, T., Tomita, M., and Ishihama, Y. (2008) Phase transfer surfactant-aided trypsin digestion for membrane proteome analysis. J. Proteome Res. 7, 731-740.
-
-Masuda, T., Saito, N., Tomita, M., and Ishihama, Y. (2009) Unbiased quantification of Escherichia coli membrane proteome using phase transfer surfactants. Mol. Cell. Proteomics 8, 2770-2777.
-
-Mostafa, D., Yanagiya, A., Georgiadou, E., Wu, Y., Stylianides, T., Rutter, G. A., Suzuki, T., & Yamamoto, T. (2020). Loss of β-cell identity and diabetic phenotype in mice caused by disruption of CNOT3-dependent mRNA deadenylation. Commun. Biol. 3, 476.
-
-Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Hengartner, M. O., and Aebersold, R. (2011) mProphet: automated data processing and statistical validation for large scale SRM experiments. Nat. Methods 8, 430–435.
-
-Rosenberger, G., Bludau, I., Schmitt, U., Heusel, M., Hunter, C. L., Liu, Y., MacCoss, M. J., MacLean, B. X., Nesvizhskii, A. I., Pedrioli, P. G. A., Reiter, L., Röst, H. L., Tate, S., Ting, Y. S., Collins, B. C., and Aebersold, R. (2017) Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses. Nat. Methods 14, 921–927.
diff --git a/general/datasets/Riken_Wu_BXD_HF_WAdip_0920/specifics.rtf b/general/datasets/Riken_Wu_BXD_HF_WAdip_0920/specifics.rtf
deleted file mode 100644
index e405714..0000000
--- a/general/datasets/Riken_Wu_BXD_HF_WAdip_0920/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-BXD HF White Adipose Proteome (Sep20)
\ No newline at end of file
diff --git a/general/datasets/Riken_Wu_BXD_WAdip_0720/experiment-design.rtf b/general/datasets/Riken_Wu_BXD_WAdip_0720/experiment-design.rtf
deleted file mode 100644
index 6bd1793..0000000
--- a/general/datasets/Riken_Wu_BXD_WAdip_0720/experiment-design.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Sample preparation for proteomic analysis
-
-Proteins were extracted from adipose tissue samples in lysis buffer containing 12 mM sodium deoxycholate, 12 mM sodium N-dodecanoylsarcosinate, and 100 mM Tris.Cl pH 9.0, with cOmplete, mini, EDTA-free Protease Inhibitor Cocktail (Roche, Switzerland), using homogenization with a glass dounce followed by sonication for 15 minutes using a Bioruptor water bath sonicator on high power, with cycles of one min sonication followed by one min rest (Cosmo Bio Co. Ltd., Japan). The samples were centrifuged at 18,000 x g, for 20 min at 4 oC and the supernatant fractions were taken. Protein concentrations were determined using a Pierce BCA Assay Kit (Thermo Fisher Scientific, USA), according to manufacturer’s instructions. Samples were prepared for liquid chromatography tandem mass spectrometry (LC-M/MS) using the Phase Transfer Surfactant Method (Masuda et al., 2008; Masuda et al., 2009), with minor modifications as previously described (Mostafa et al., 2020). Afterwards, dried Lys-C/tryptic peptides were dissolved in 0.1% TFA and desalted using MonoSpin C18 columns (GL Sciences Inc., Japan). Peptides were eluted from C18 columns in 0.1% (v/v) TFA in 50% (v/v) acetonitrile and dried in a centrifugal vacuum concentrator. Tryptic peptides were dissolved in 0.1% (v/v) formic acid, 3% (v/v) acetonitrile in water for MS analysis and the peptide concentrations were determined using a Pierce Quantitative Colorimetric Peptide Assay Kit (Thermo Fisher). A portion of the peptides from the samples were pooled and fractionated using a Pierce High pH Reversed-Phase (HPRP) Peptide Fractionation Kit (Thermo Fisher) to generate a spectral library.
-
-MS measurement
-
-Samples were measured using a Q Exactive Plus Orbitrap LC–MS/MS System (Thermo Fisher), equipped with a Nanospray Flex ion source. Peptides were separated on 3-µm particle, 75-µm inner diameter, 12-cm filling length C18 columns (Nikkyo Technos Co., Ltd., Japan). For each sample, 600 ng was injected and the samples were measured with data-independent acquisition (DIA). For HPRP fractions, 450 ng was injected and the samples were measured with data-dependent acquisition (DDA). LC-MS/MS conditions were as previously described (Mostafa et al., 2020), except for DDA the first mass for MS2 scans was not fixed and for DIA the AGC target of DIA segments was 3e6.
-
-Protein identification and quantification
-
-Raw files from DDA measurements were searched against a mouse-specific database (uniprot-reviewed_Mus_musculus_10090_.fasta) using Proteome Discoverer v2.4 software (Thermo Fisher). Filtered output was used to generate a sample-specific spectral library using Spectronaut software (Biognosys, Switzerland). Raw files from DIA measurements were used for quantitative data extraction with the generated spectral library, as previously described (Mostafa et al., 2020). FDR was estimated with the mProphet approach (Reiter et al., 2011) and set to 0.01 at both peptide precursor level and protein level (Rosenberger et al., 2017).
-
-References
-
-Masuda, T., Tomita, M., and Ishihama, Y. (2008) Phase transfer surfactant-aided trypsin digestion for membrane proteome analysis. J. Proteome Res. 7, 731-740.
-
-Masuda, T., Saito, N., Tomita, M., and Ishihama, Y. (2009) Unbiased quantification of Escherichia coli membrane proteome using phase transfer surfactants. Mol. Cell. Proteomics 8, 2770-2777.
-
-Mostafa, D., Yanagiya, A., Georgiadou, E., Wu, Y., Stylianides, T., Rutter, G. A., Suzuki, T., & Yamamoto, T. (2020). Loss of β-cell identity and diabetic phenotype in mice caused by disruption of CNOT3-dependent mRNA deadenylation. Commun. Biol. 3, 476.
-
-Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Hengartner, M. O., and Aebersold, R. (2011) mProphet: automated data processing and statistical validation for large scale SRM experiments. Nat. Methods 8, 430–435.
-
-Rosenberger, G., Bludau, I., Schmitt, U., Heusel, M., Hunter, C. L., Liu, Y., MacCoss, M. J., MacLean, B. X., Nesvizhskii, A. I., Pedrioli, P. G. A., Reiter, L., Röst, H. L., Tate, S., Ting, Y. S., Collins, B. C., and Aebersold, R. (2017) Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses. Nat. Methods 14, 921–927.
diff --git a/general/datasets/Riken_Wu_BXD_WAdip_0720/specifics.rtf b/general/datasets/Riken_Wu_BXD_WAdip_0720/specifics.rtf
deleted file mode 100644
index e42b3b9..0000000
--- a/general/datasets/Riken_Wu_BXD_WAdip_0720/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-BXD White Adipose Proteome Individual (Sep20)
\ No newline at end of file
diff --git a/general/datasets/Riken_wu_bxd_cd_wadip_0920/experiment-design.rtf b/general/datasets/Riken_wu_bxd_cd_wadip_0920/experiment-design.rtf
new file mode 100644
index 0000000..6bd1793
--- /dev/null
+++ b/general/datasets/Riken_wu_bxd_cd_wadip_0920/experiment-design.rtf
@@ -0,0 +1,23 @@
+Sample preparation for proteomic analysis
+
+Proteins were extracted from adipose tissue samples in lysis buffer containing 12 mM sodium deoxycholate, 12 mM sodium N-dodecanoylsarcosinate, and 100 mM Tris.Cl pH 9.0, with cOmplete, mini, EDTA-free Protease Inhibitor Cocktail (Roche, Switzerland), using homogenization with a glass dounce followed by sonication for 15 minutes using a Bioruptor water bath sonicator on high power, with cycles of one min sonication followed by one min rest (Cosmo Bio Co. Ltd., Japan). The samples were centrifuged at 18,000 x g, for 20 min at 4 oC and the supernatant fractions were taken. Protein concentrations were determined using a Pierce BCA Assay Kit (Thermo Fisher Scientific, USA), according to manufacturer’s instructions. Samples were prepared for liquid chromatography tandem mass spectrometry (LC-M/MS) using the Phase Transfer Surfactant Method (Masuda et al., 2008; Masuda et al., 2009), with minor modifications as previously described (Mostafa et al., 2020). Afterwards, dried Lys-C/tryptic peptides were dissolved in 0.1% TFA and desalted using MonoSpin C18 columns (GL Sciences Inc., Japan). Peptides were eluted from C18 columns in 0.1% (v/v) TFA in 50% (v/v) acetonitrile and dried in a centrifugal vacuum concentrator. Tryptic peptides were dissolved in 0.1% (v/v) formic acid, 3% (v/v) acetonitrile in water for MS analysis and the peptide concentrations were determined using a Pierce Quantitative Colorimetric Peptide Assay Kit (Thermo Fisher). A portion of the peptides from the samples were pooled and fractionated using a Pierce High pH Reversed-Phase (HPRP) Peptide Fractionation Kit (Thermo Fisher) to generate a spectral library.
+
+MS measurement
+
+Samples were measured using a Q Exactive Plus Orbitrap LC–MS/MS System (Thermo Fisher), equipped with a Nanospray Flex ion source. Peptides were separated on 3-µm particle, 75-µm inner diameter, 12-cm filling length C18 columns (Nikkyo Technos Co., Ltd., Japan). For each sample, 600 ng was injected and the samples were measured with data-independent acquisition (DIA). For HPRP fractions, 450 ng was injected and the samples were measured with data-dependent acquisition (DDA). LC-MS/MS conditions were as previously described (Mostafa et al., 2020), except for DDA the first mass for MS2 scans was not fixed and for DIA the AGC target of DIA segments was 3e6.
+
+Protein identification and quantification
+
+Raw files from DDA measurements were searched against a mouse-specific database (uniprot-reviewed_Mus_musculus_10090_.fasta) using Proteome Discoverer v2.4 software (Thermo Fisher). Filtered output was used to generate a sample-specific spectral library using Spectronaut software (Biognosys, Switzerland). Raw files from DIA measurements were used for quantitative data extraction with the generated spectral library, as previously described (Mostafa et al., 2020). FDR was estimated with the mProphet approach (Reiter et al., 2011) and set to 0.01 at both peptide precursor level and protein level (Rosenberger et al., 2017).
+
+References
+
+Masuda, T., Tomita, M., and Ishihama, Y. (2008) Phase transfer surfactant-aided trypsin digestion for membrane proteome analysis. J. Proteome Res. 7, 731-740.
+
+Masuda, T., Saito, N., Tomita, M., and Ishihama, Y. (2009) Unbiased quantification of Escherichia coli membrane proteome using phase transfer surfactants. Mol. Cell. Proteomics 8, 2770-2777.
+
+Mostafa, D., Yanagiya, A., Georgiadou, E., Wu, Y., Stylianides, T., Rutter, G. A., Suzuki, T., & Yamamoto, T. (2020). Loss of β-cell identity and diabetic phenotype in mice caused by disruption of CNOT3-dependent mRNA deadenylation. Commun. Biol. 3, 476.
+
+Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Hengartner, M. O., and Aebersold, R. (2011) mProphet: automated data processing and statistical validation for large scale SRM experiments. Nat. Methods 8, 430–435.
+
+Rosenberger, G., Bludau, I., Schmitt, U., Heusel, M., Hunter, C. L., Liu, Y., MacCoss, M. J., MacLean, B. X., Nesvizhskii, A. I., Pedrioli, P. G. A., Reiter, L., Röst, H. L., Tate, S., Ting, Y. S., Collins, B. C., and Aebersold, R. (2017) Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses. Nat. Methods 14, 921–927.
diff --git a/general/datasets/Riken_wu_bxd_cd_wadip_0920/specifics.rtf b/general/datasets/Riken_wu_bxd_cd_wadip_0920/specifics.rtf
new file mode 100644
index 0000000..04d0771
--- /dev/null
+++ b/general/datasets/Riken_wu_bxd_cd_wadip_0920/specifics.rtf
@@ -0,0 +1 @@
+BXD CD White Adipose Proteome (Sep20)
\ No newline at end of file
diff --git a/general/datasets/Riken_wu_bxd_cdhf_wadip_0920/experiment-design.rtf b/general/datasets/Riken_wu_bxd_cdhf_wadip_0920/experiment-design.rtf
new file mode 100644
index 0000000..6bd1793
--- /dev/null
+++ b/general/datasets/Riken_wu_bxd_cdhf_wadip_0920/experiment-design.rtf
@@ -0,0 +1,23 @@
+Sample preparation for proteomic analysis
+
+Proteins were extracted from adipose tissue samples in lysis buffer containing 12 mM sodium deoxycholate, 12 mM sodium N-dodecanoylsarcosinate, and 100 mM Tris.Cl pH 9.0, with cOmplete, mini, EDTA-free Protease Inhibitor Cocktail (Roche, Switzerland), using homogenization with a glass dounce followed by sonication for 15 minutes using a Bioruptor water bath sonicator on high power, with cycles of one min sonication followed by one min rest (Cosmo Bio Co. Ltd., Japan). The samples were centrifuged at 18,000 x g, for 20 min at 4 oC and the supernatant fractions were taken. Protein concentrations were determined using a Pierce BCA Assay Kit (Thermo Fisher Scientific, USA), according to manufacturer’s instructions. Samples were prepared for liquid chromatography tandem mass spectrometry (LC-M/MS) using the Phase Transfer Surfactant Method (Masuda et al., 2008; Masuda et al., 2009), with minor modifications as previously described (Mostafa et al., 2020). Afterwards, dried Lys-C/tryptic peptides were dissolved in 0.1% TFA and desalted using MonoSpin C18 columns (GL Sciences Inc., Japan). Peptides were eluted from C18 columns in 0.1% (v/v) TFA in 50% (v/v) acetonitrile and dried in a centrifugal vacuum concentrator. Tryptic peptides were dissolved in 0.1% (v/v) formic acid, 3% (v/v) acetonitrile in water for MS analysis and the peptide concentrations were determined using a Pierce Quantitative Colorimetric Peptide Assay Kit (Thermo Fisher). A portion of the peptides from the samples were pooled and fractionated using a Pierce High pH Reversed-Phase (HPRP) Peptide Fractionation Kit (Thermo Fisher) to generate a spectral library.
+
+MS measurement
+
+Samples were measured using a Q Exactive Plus Orbitrap LC–MS/MS System (Thermo Fisher), equipped with a Nanospray Flex ion source. Peptides were separated on 3-µm particle, 75-µm inner diameter, 12-cm filling length C18 columns (Nikkyo Technos Co., Ltd., Japan). For each sample, 600 ng was injected and the samples were measured with data-independent acquisition (DIA). For HPRP fractions, 450 ng was injected and the samples were measured with data-dependent acquisition (DDA). LC-MS/MS conditions were as previously described (Mostafa et al., 2020), except for DDA the first mass for MS2 scans was not fixed and for DIA the AGC target of DIA segments was 3e6.
+
+Protein identification and quantification
+
+Raw files from DDA measurements were searched against a mouse-specific database (uniprot-reviewed_Mus_musculus_10090_.fasta) using Proteome Discoverer v2.4 software (Thermo Fisher). Filtered output was used to generate a sample-specific spectral library using Spectronaut software (Biognosys, Switzerland). Raw files from DIA measurements were used for quantitative data extraction with the generated spectral library, as previously described (Mostafa et al., 2020). FDR was estimated with the mProphet approach (Reiter et al., 2011) and set to 0.01 at both peptide precursor level and protein level (Rosenberger et al., 2017).
+
+References
+
+Masuda, T., Tomita, M., and Ishihama, Y. (2008) Phase transfer surfactant-aided trypsin digestion for membrane proteome analysis. J. Proteome Res. 7, 731-740.
+
+Masuda, T., Saito, N., Tomita, M., and Ishihama, Y. (2009) Unbiased quantification of Escherichia coli membrane proteome using phase transfer surfactants. Mol. Cell. Proteomics 8, 2770-2777.
+
+Mostafa, D., Yanagiya, A., Georgiadou, E., Wu, Y., Stylianides, T., Rutter, G. A., Suzuki, T., & Yamamoto, T. (2020). Loss of β-cell identity and diabetic phenotype in mice caused by disruption of CNOT3-dependent mRNA deadenylation. Commun. Biol. 3, 476.
+
+Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Hengartner, M. O., and Aebersold, R. (2011) mProphet: automated data processing and statistical validation for large scale SRM experiments. Nat. Methods 8, 430–435.
+
+Rosenberger, G., Bludau, I., Schmitt, U., Heusel, M., Hunter, C. L., Liu, Y., MacCoss, M. J., MacLean, B. X., Nesvizhskii, A. I., Pedrioli, P. G. A., Reiter, L., Röst, H. L., Tate, S., Ting, Y. S., Collins, B. C., and Aebersold, R. (2017) Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses. Nat. Methods 14, 921–927.
diff --git a/general/datasets/Riken_wu_bxd_cdhf_wadip_0920/specifics.rtf b/general/datasets/Riken_wu_bxd_cdhf_wadip_0920/specifics.rtf
new file mode 100644
index 0000000..68167de
--- /dev/null
+++ b/general/datasets/Riken_wu_bxd_cdhf_wadip_0920/specifics.rtf
@@ -0,0 +1 @@
+Riken-Wu BXD CD-HF White Adipose Proteome (Sep20)
\ No newline at end of file
diff --git a/general/datasets/Riken_wu_bxd_hf_wadip_0920/experiment-design.rtf b/general/datasets/Riken_wu_bxd_hf_wadip_0920/experiment-design.rtf
new file mode 100644
index 0000000..6bd1793
--- /dev/null
+++ b/general/datasets/Riken_wu_bxd_hf_wadip_0920/experiment-design.rtf
@@ -0,0 +1,23 @@
+Sample preparation for proteomic analysis
+
+Proteins were extracted from adipose tissue samples in lysis buffer containing 12 mM sodium deoxycholate, 12 mM sodium N-dodecanoylsarcosinate, and 100 mM Tris.Cl pH 9.0, with cOmplete, mini, EDTA-free Protease Inhibitor Cocktail (Roche, Switzerland), using homogenization with a glass dounce followed by sonication for 15 minutes using a Bioruptor water bath sonicator on high power, with cycles of one min sonication followed by one min rest (Cosmo Bio Co. Ltd., Japan). The samples were centrifuged at 18,000 x g, for 20 min at 4 oC and the supernatant fractions were taken. Protein concentrations were determined using a Pierce BCA Assay Kit (Thermo Fisher Scientific, USA), according to manufacturer’s instructions. Samples were prepared for liquid chromatography tandem mass spectrometry (LC-M/MS) using the Phase Transfer Surfactant Method (Masuda et al., 2008; Masuda et al., 2009), with minor modifications as previously described (Mostafa et al., 2020). Afterwards, dried Lys-C/tryptic peptides were dissolved in 0.1% TFA and desalted using MonoSpin C18 columns (GL Sciences Inc., Japan). Peptides were eluted from C18 columns in 0.1% (v/v) TFA in 50% (v/v) acetonitrile and dried in a centrifugal vacuum concentrator. Tryptic peptides were dissolved in 0.1% (v/v) formic acid, 3% (v/v) acetonitrile in water for MS analysis and the peptide concentrations were determined using a Pierce Quantitative Colorimetric Peptide Assay Kit (Thermo Fisher). A portion of the peptides from the samples were pooled and fractionated using a Pierce High pH Reversed-Phase (HPRP) Peptide Fractionation Kit (Thermo Fisher) to generate a spectral library.
+
+MS measurement
+
+Samples were measured using a Q Exactive Plus Orbitrap LC–MS/MS System (Thermo Fisher), equipped with a Nanospray Flex ion source. Peptides were separated on 3-µm particle, 75-µm inner diameter, 12-cm filling length C18 columns (Nikkyo Technos Co., Ltd., Japan). For each sample, 600 ng was injected and the samples were measured with data-independent acquisition (DIA). For HPRP fractions, 450 ng was injected and the samples were measured with data-dependent acquisition (DDA). LC-MS/MS conditions were as previously described (Mostafa et al., 2020), except for DDA the first mass for MS2 scans was not fixed and for DIA the AGC target of DIA segments was 3e6.
+
+Protein identification and quantification
+
+Raw files from DDA measurements were searched against a mouse-specific database (uniprot-reviewed_Mus_musculus_10090_.fasta) using Proteome Discoverer v2.4 software (Thermo Fisher). Filtered output was used to generate a sample-specific spectral library using Spectronaut software (Biognosys, Switzerland). Raw files from DIA measurements were used for quantitative data extraction with the generated spectral library, as previously described (Mostafa et al., 2020). FDR was estimated with the mProphet approach (Reiter et al., 2011) and set to 0.01 at both peptide precursor level and protein level (Rosenberger et al., 2017).
+
+References
+
+Masuda, T., Tomita, M., and Ishihama, Y. (2008) Phase transfer surfactant-aided trypsin digestion for membrane proteome analysis. J. Proteome Res. 7, 731-740.
+
+Masuda, T., Saito, N., Tomita, M., and Ishihama, Y. (2009) Unbiased quantification of Escherichia coli membrane proteome using phase transfer surfactants. Mol. Cell. Proteomics 8, 2770-2777.
+
+Mostafa, D., Yanagiya, A., Georgiadou, E., Wu, Y., Stylianides, T., Rutter, G. A., Suzuki, T., & Yamamoto, T. (2020). Loss of β-cell identity and diabetic phenotype in mice caused by disruption of CNOT3-dependent mRNA deadenylation. Commun. Biol. 3, 476.
+
+Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Hengartner, M. O., and Aebersold, R. (2011) mProphet: automated data processing and statistical validation for large scale SRM experiments. Nat. Methods 8, 430–435.
+
+Rosenberger, G., Bludau, I., Schmitt, U., Heusel, M., Hunter, C. L., Liu, Y., MacCoss, M. J., MacLean, B. X., Nesvizhskii, A. I., Pedrioli, P. G. A., Reiter, L., Röst, H. L., Tate, S., Ting, Y. S., Collins, B. C., and Aebersold, R. (2017) Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses. Nat. Methods 14, 921–927.
diff --git a/general/datasets/Riken_wu_bxd_hf_wadip_0920/specifics.rtf b/general/datasets/Riken_wu_bxd_hf_wadip_0920/specifics.rtf
new file mode 100644
index 0000000..e405714
--- /dev/null
+++ b/general/datasets/Riken_wu_bxd_hf_wadip_0920/specifics.rtf
@@ -0,0 +1 @@
+BXD HF White Adipose Proteome (Sep20)
\ No newline at end of file
diff --git a/general/datasets/Riken_wu_bxd_wadip_0720/experiment-design.rtf b/general/datasets/Riken_wu_bxd_wadip_0720/experiment-design.rtf
new file mode 100644
index 0000000..6bd1793
--- /dev/null
+++ b/general/datasets/Riken_wu_bxd_wadip_0720/experiment-design.rtf
@@ -0,0 +1,23 @@
+Sample preparation for proteomic analysis
+
+Proteins were extracted from adipose tissue samples in lysis buffer containing 12 mM sodium deoxycholate, 12 mM sodium N-dodecanoylsarcosinate, and 100 mM Tris.Cl pH 9.0, with cOmplete, mini, EDTA-free Protease Inhibitor Cocktail (Roche, Switzerland), using homogenization with a glass dounce followed by sonication for 15 minutes using a Bioruptor water bath sonicator on high power, with cycles of one min sonication followed by one min rest (Cosmo Bio Co. Ltd., Japan). The samples were centrifuged at 18,000 x g, for 20 min at 4 oC and the supernatant fractions were taken. Protein concentrations were determined using a Pierce BCA Assay Kit (Thermo Fisher Scientific, USA), according to manufacturer’s instructions. Samples were prepared for liquid chromatography tandem mass spectrometry (LC-M/MS) using the Phase Transfer Surfactant Method (Masuda et al., 2008; Masuda et al., 2009), with minor modifications as previously described (Mostafa et al., 2020). Afterwards, dried Lys-C/tryptic peptides were dissolved in 0.1% TFA and desalted using MonoSpin C18 columns (GL Sciences Inc., Japan). Peptides were eluted from C18 columns in 0.1% (v/v) TFA in 50% (v/v) acetonitrile and dried in a centrifugal vacuum concentrator. Tryptic peptides were dissolved in 0.1% (v/v) formic acid, 3% (v/v) acetonitrile in water for MS analysis and the peptide concentrations were determined using a Pierce Quantitative Colorimetric Peptide Assay Kit (Thermo Fisher). A portion of the peptides from the samples were pooled and fractionated using a Pierce High pH Reversed-Phase (HPRP) Peptide Fractionation Kit (Thermo Fisher) to generate a spectral library.
+
+MS measurement
+
+Samples were measured using a Q Exactive Plus Orbitrap LC–MS/MS System (Thermo Fisher), equipped with a Nanospray Flex ion source. Peptides were separated on 3-µm particle, 75-µm inner diameter, 12-cm filling length C18 columns (Nikkyo Technos Co., Ltd., Japan). For each sample, 600 ng was injected and the samples were measured with data-independent acquisition (DIA). For HPRP fractions, 450 ng was injected and the samples were measured with data-dependent acquisition (DDA). LC-MS/MS conditions were as previously described (Mostafa et al., 2020), except for DDA the first mass for MS2 scans was not fixed and for DIA the AGC target of DIA segments was 3e6.
+
+Protein identification and quantification
+
+Raw files from DDA measurements were searched against a mouse-specific database (uniprot-reviewed_Mus_musculus_10090_.fasta) using Proteome Discoverer v2.4 software (Thermo Fisher). Filtered output was used to generate a sample-specific spectral library using Spectronaut software (Biognosys, Switzerland). Raw files from DIA measurements were used for quantitative data extraction with the generated spectral library, as previously described (Mostafa et al., 2020). FDR was estimated with the mProphet approach (Reiter et al., 2011) and set to 0.01 at both peptide precursor level and protein level (Rosenberger et al., 2017).
+
+References
+
+Masuda, T., Tomita, M., and Ishihama, Y. (2008) Phase transfer surfactant-aided trypsin digestion for membrane proteome analysis. J. Proteome Res. 7, 731-740.
+
+Masuda, T., Saito, N., Tomita, M., and Ishihama, Y. (2009) Unbiased quantification of Escherichia coli membrane proteome using phase transfer surfactants. Mol. Cell. Proteomics 8, 2770-2777.
+
+Mostafa, D., Yanagiya, A., Georgiadou, E., Wu, Y., Stylianides, T., Rutter, G. A., Suzuki, T., & Yamamoto, T. (2020). Loss of β-cell identity and diabetic phenotype in mice caused by disruption of CNOT3-dependent mRNA deadenylation. Commun. Biol. 3, 476.
+
+Reiter, L., Rinner, O., Picotti, P., Hüttenhain, R., Beck, M., Hengartner, M. O., and Aebersold, R. (2011) mProphet: automated data processing and statistical validation for large scale SRM experiments. Nat. Methods 8, 430–435.
+
+Rosenberger, G., Bludau, I., Schmitt, U., Heusel, M., Hunter, C. L., Liu, Y., MacCoss, M. J., MacLean, B. X., Nesvizhskii, A. I., Pedrioli, P. G. A., Reiter, L., Röst, H. L., Tate, S., Ting, Y. S., Collins, B. C., and Aebersold, R. (2017) Statistical control of peptide and protein error rates in large-scale targeted data-independent acquisition analyses. Nat. Methods 14, 921–927.
diff --git a/general/datasets/Riken_wu_bxd_wadip_0720/specifics.rtf b/general/datasets/Riken_wu_bxd_wadip_0720/specifics.rtf
new file mode 100644
index 0000000..e42b3b9
--- /dev/null
+++ b/general/datasets/Riken_wu_bxd_wadip_0720/specifics.rtf
@@ -0,0 +1 @@
+BXD White Adipose Proteome Individual (Sep20)
\ No newline at end of file
diff --git a/general/datasets/Rtc_1106_r/acknowledgment.rtf b/general/datasets/Rtc_1106_r/acknowledgment.rtf
new file mode 100644
index 0000000..3246da5
--- /dev/null
+++ b/general/datasets/Rtc_1106_r/acknowledgment.rtf
@@ -0,0 +1,5 @@
+
+These data were generated by Prof. Dr. Klaus Schughart (Department of Experimental Mouse Genetics) and Dr. Dunja Bruder (Research Group Immune Regulation) at the Helmholtz Center for Infection Research with the help of Dr. Lothar Gröbe (FACS sorting, Research Group Mucosal Immunity).
+
+Funding was provided by the Helmholtz Association and publicly funded research projects awarded to Drs. Klaus Schughart and Dunja Bruder.
+
diff --git a/general/datasets/Rtc_1106_r/cases.rtf b/general/datasets/Rtc_1106_r/cases.rtf
new file mode 100644
index 0000000..5ae01c7
--- /dev/null
+++ b/general/datasets/Rtc_1106_r/cases.rtf
@@ -0,0 +1,914 @@
+
+Parental and 31 BXD lines were studied. Mice were received from The Jackson Laboratory, or from The Oak Ridge National and were bred in the facility of the Neuro-BSIK consortium (VU University Amsterdam). The data set includes expression values for 18 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD40), as well as the two parental strains, C57BL/6J and DBA/2J. All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding.
+
+BXD spleen sample pools (from 2-3 mice) were obtained from a pathogen-free mice of the Dutch Mouse Phenomics Consortium (MPC) in Amsterdam. Mice were imported into the central animal facility at the HZI and kept in a pathogen-free vivarium. Mice were euthanized using CO2 and spleenocytes were prepared. Most mice were between 17 and 22 weeks of age when samples were collected. FACS sorting was used to select the CD4-positive T cells. These cells were further separated into CD4+CD25+ and CD4+CD25- pools.
+
+Error-checking strain identity. A set of more than 20 probe sets with Mendelian segregation patterns in this HZI data set were used to confirm strain identify in early June, 2007. Two errors were detected and rectified. As of June 22, 2007, data are registered correctly. Prior to June 22, 2007, data listed as strains BXD33 and BXD39 were essentially hybrid (mixed) data sets.
+
+On Aug 23, 2007, we loaded the final QTL Reaper data into GeneNetwork for the corrected data set. The maximum LRS generated by any probe set is 84.6 for 1436240_at (Tra2a). A total of 41 probe sets are associated with QTLs that have LRS values above 46 (LOD > 10).
+
+Sex of samples is listed below in Table 1. In brief, data for BXD14 and 23 are male-only samples, whereas BXD12, 16, 31, 34, 36 and C57BL/6J are from female-only samples. All other samples (DBA/2J, BXD1, 2, 6, 9, 11, 18, 21 32, 33, 39, 40) consist of one male and one female array. The sex of samples can be independently validated using the Xist probe set (1427262_at).
+
+
+
+Figure 1: The expression of Xist can be used as an independent marker for sex. Xist is expressed at very low levels (noise) in male samples (far left) and at high values in females (far right). Sex-balanced samples (middle) have high variance due to the inclusion of one array per sex.
+
+ Table 1
+
+
+
+
+
+
+
+
+
+ | Index |
+ ProbeSet ID |
+ Sample Description |
+ Sex |
+ Strain |
+ cd25 |
+ Microarray |
+ Short Description |
+ Age |
+ Pool No. |
+ Pool members (animal number) |
+ Date of preparation |
+
+
+ | 1 |
+ HZI1008 |
+ BXD-06f (f1) CD25+ |
+ F |
+ BXD6 |
+ CD25+ |
+ Yes |
+ BXD-06f |
+ 17 |
+ f1 |
+ 1,3,4 |
+ 1-31-2006 |
+
+
+ | 2 |
+ HZI1009 |
+ BXD-06m (m2) CD25+ |
+ M |
+ BXD6 |
+ CD25+ |
+ Yes |
+ BXD-06m |
+ 18 |
+ m2 |
+ 5,6,7 |
+ 1-31-2006 |
+
+
+ | 3 |
+ HZI1010 |
+ BXD-14m (m3) CD25+ |
+ M |
+ BXD14 |
+ CD25+ |
+ Yes |
+ BXD-14m |
+ 17 |
+ m3 |
+ 1,3,4 |
+ 1-31-2006 |
+
+
+ | 4 |
+ HZI1013 |
+ BXD-40f (f6) CD25+ |
+ F |
+ BXD40 |
+ CD25+ |
+ Yes |
+ BXD-40f |
+ 17 |
+ f6 |
+ 1,2,3 |
+ 2-1-2006 |
+
+
+ | 5 |
+ HZI1014 |
+ BXD-40m (m7) CD25+ |
+ M |
+ BXD40 |
+ CD25+ |
+ Yes |
+ BXD-40m |
+ 17 |
+ m7 |
+ 5,6,7 |
+ 2-2-2006 |
+
+
+ | 6 |
+ HZI1015 |
+ BXD-02f (f8) CD25+ |
+ F |
+ BXD2 |
+ CD25+ |
+ Yes |
+ BXD-02f |
+ 17 |
+ f8 |
+ 1,2,3 |
+ 2-14-2006 |
+
+
+ | 7 |
+ HZI1016 |
+ BXD-02m (m20) CD25+ |
+ M |
+ BXD2 |
+ CD25+ |
+ Yes |
+ BXD-02m |
+ 21 |
+ m20 |
+ 4,5,6 |
+ 4-6-2006 |
+
+
+ | 8 |
+ HZI1017 |
+ BXD-11f (f30) CD25+ |
+ F |
+ BXD11 |
+ CD25+ |
+ Yes |
+ BXD-11f |
+ 17 |
+ f30 |
+ 3,4,5 |
+ 5-11-2006 |
+
+
+ | 9 |
+ HZI1018 |
+ BXD-11m (m9) CD25+ |
+ M |
+ BXD11 |
+ CD25+ |
+ Yes |
+ BXD-11m |
+ 18 |
+ m9 |
+ 1,2 |
+ 2-14-2006 |
+
+
+ | 10 |
+ HZI1019 |
+ BXD-12f (f10) CD25+ |
+ F |
+ BXD12 |
+ CD25+ |
+ Yes |
+ BXD-12f |
+ 17 |
+ f10 |
+ 1,2,3 |
+ 2-14-2006 |
+
+
+ | 11 |
+ HZI1020 |
+ BXD-39f (f23) CD25+ |
+ F |
+ BXD39 |
+ CD25+ |
+ Yes |
+ BXD-39f |
+ 19 |
+ f23 |
+ 4,5,6 |
+ 4-11-2006 |
+
+
+ | 12 |
+ HZI1021 |
+ BXD-33m (m11) CD25+ |
+ M |
+ BXD33 |
+ CD25+ |
+ Yes |
+ BXD-33m |
+ 17 |
+ m11 |
+ 1,2 |
+ 2-14-2006 |
+
+
+ | 13 |
+ HZI1022 |
+ BXD-18f (f14) CD25+ |
+ F |
+ BXD18 |
+ CD25+ |
+ Yes |
+ BXD-18f |
+ 17 |
+ f14 |
+ 3,4,5 |
+ 2-15-2006 |
+
+
+ | 14 |
+ HZI1023 |
+ BXD-18m (m13) CD25+ |
+ M |
+ BXD18 |
+ CD25+ |
+ Yes |
+ BXD-18m |
+ 18 |
+ m13 |
+ 7,8 |
+ 2-15-2006 |
+
+
+ | 15 |
+ HZI1024 |
+ BXD-23m (m15) CD25+ |
+ M |
+ BXD23 |
+ CD25+ |
+ Yes |
+ BXD-23m |
+ 18 |
+ m15 |
+ 1,2,3 |
+ 2-15-2006 |
+
+
+ | 16 |
+ HZI1026 |
+ BXD-09f (f17) CD25+ |
+ F |
+ BXD9 |
+ CD25+ |
+ Yes |
+ BXD-09f |
+ 21 |
+ f17 |
+ 1,2,3 |
+ 4-5-2006 |
+
+
+ | 17 |
+ HZI1028 |
+ BXD-09m (m35) CD25+ |
+ M |
+ BXD9 |
+ CD25+ |
+ Yes |
+ BXD-09m |
+ 15 |
+ m35 |
+ 7,8,9 |
+ 7-7-2006 |
+
+
+ | 18 |
+ HZI1029 |
+ BXD-32f (f18) CD25+ |
+ F |
+ BXD32 |
+ CD25+ |
+ Yes |
+ BXD-32f |
+ 21 |
+ f18 |
+ 1,2,3 |
+ 4-6-2006 |
+
+
+ | 19 |
+ HZI1030 |
+ BXD-32m (m19) CD25+ |
+ M |
+ BXD32 |
+ CD25+ |
+ Yes |
+ BXD-32m |
+ 22 |
+ m19 |
+ 1,2,3 |
+ 4-6-2006 |
+
+
+ | 20 |
+ HZI1031 |
+ BXD-33f (f22) CD25+ |
+ F |
+ BXD33 |
+ CD25+ |
+ Yes |
+ BXD-33f |
+ 18 |
+ f22 |
+ 2,3,4 |
+ 4-11-2006 |
+
+
+ | 21 |
+ HZI1032 |
+ BXD-39m (m29) CD25+ |
+ M |
+ BXD39 |
+ CD25+ |
+ Yes |
+ BXD-39m |
+ 17 |
+ m29 |
+ 5,6,7 |
+ 5-10-2006 |
+
+
+ | 22 |
+ HZI1033 |
+ BXD-01f (f32) CD25+ |
+ F |
+ BXD1 |
+ CD25+ |
+ Yes |
+ BXD-01f |
+ 18 |
+ f32 |
+ 3,4 |
+ 7-6-2006 |
+
+
+ | 23 |
+ HZI1034 |
+ BXD-01m (m31) CD25+ |
+ M |
+ BXD1 |
+ CD25+ |
+ Yes |
+ BXD-01m |
+ 18 |
+ m31 |
+ 1,2 |
+ 7-6-2006 |
+
+
+ | 24 |
+ HZI1035 |
+ BXD-16f (f26) CD25+ |
+ F |
+ BXD16 |
+ CD25+ |
+ Yes |
+ BXD-16f |
+ 18 |
+ f26 |
+ 1,2,3 |
+ 4-12-2006 |
+
+
+ | 25 |
+ HZI1036 |
+ BXD-21f (f25) CD25+ |
+ F |
+ BXD21 |
+ CD25+ |
+ Yes |
+ BXD-21f |
+ 19 |
+ f25 |
+ 5,6,7 |
+ 4-12-2006 |
+
+
+ | 26 |
+ HZI1037 |
+ BXD-21m (m24) CD25+ |
+ M |
+ BXD21 |
+ CD25+ |
+ Yes |
+ BXD-21m |
+ 18 |
+ m24 |
+ 1,2,3 |
+ 4-12-2006 |
+
+
+ | 27 |
+ HZI1039 |
+ BXD-31f (f34) CD25+ |
+ F |
+ BXD31 |
+ CD25+ |
+ Yes |
+ BXD-31f |
+ 16 |
+ f34 |
+ 1,2,3 |
+ 7-7-2006 |
+
+
+ | 28 |
+ HZI1040 |
+ C57BL/6Jf (f28) CD25+ |
+ F |
+ C57BL/6J |
+ CD25+ |
+ Yes |
+ C57BL/6Jf |
+ 16 |
+ f28 |
+ 1,2,3 |
+ 5-10-2006 |
+
+
+ | 29 |
+ HZI1041 |
+ DBA/2Jf (f27) CD25+ |
+ F |
+ DBA/2J |
+ CD25+ |
+ Yes |
+ DBA/2Jf |
+ 16 |
+ f27 |
+ 5,6,7 |
+ 5-10-2006 |
+
+
+ | 30 |
+ HZI1042 |
+ DBA/2Jm (m21) CD25+ |
+ M |
+ DBA/2J |
+ CD25+ |
+ Yes |
+ DBA/2Jm |
+ 21 |
+ m21 |
+ 1,2,3 |
+ 4-11-2006 |
+
+
+ | 31 |
+ HZI1487 |
+ BXD-08f (f67) CD25+ |
+ F |
+ BXD8 |
+ CD25+ |
+ Yes |
+ BXD-08f |
+ 11 |
+ f67 |
+ 4,5,6 |
+ 6-25-2007 |
+
+
+ | 32 |
+ HZI1488 |
+ BXD-08m (m66) CD25+ |
+ M |
+ BXD8 |
+ CD25+ |
+ Yes |
+ BXD-08m |
+ 17 |
+ m66 |
+ 1,2,3 |
+ 6-25-2007 |
+
+
+ | 33 |
+ HZI1489 |
+ BXD-16m (m36) CD25+ |
+ M |
+ BXD16 |
+ CD25+ |
+ Yes |
+ BXD-16m |
+ 20, 16 |
+ m36 |
+ 5,6,7 |
+ 8-28-2006 |
+
+
+ | 34 |
+ HZI1490 |
+ BXD-12m (m42) CD25+ |
+ M |
+ BXD12 |
+ CD25+ |
+ Yes |
+ BXD-12m |
+ 20 |
+ m42 |
+ 5,6,7 |
+ 10-23-2006 |
+
+
+ | 35 |
+ HZI1491 |
+ BXD-13f (f44) CD25+ |
+ F |
+ BXD13 |
+ CD25+ |
+ Yes |
+ BXD-13f |
+ 15 |
+ f44 |
+ 1,2,3 |
+ 12-13-2006 |
+
+
+ | 36 |
+ HZI1492 |
+ BXD-13m (m45) CD25+ |
+ M |
+ BXD13 |
+ CD25+ |
+ Yes |
+ BXD-13m |
+ 15 |
+ m45 |
+ 4,5,6,7 |
+ 12-13-2006 |
+
+
+ | 37 |
+ HZI1493 |
+ BXD-14f (f48) CD25+ |
+ F |
+ BXD14 |
+ CD25+ |
+ Yes |
+ BXD-14f |
+ 16 |
+ f48 |
+ 5,6,7 |
+ 2-15-2007 |
+
+
+ | 38 |
+ HZI1494 |
+ BXD-19f (f64) CD25+ |
+ F |
+ BXD19 |
+ CD25+ |
+ Yes |
+ BXD-19f |
+ 19 |
+ f64 |
+ 7,8,9 |
+ 6-20-2007 |
+
+
+ | 39 |
+ HZI1495 |
+ BXD-19m (m46) CD25+ |
+ M |
+ BXD19 |
+ CD25+ |
+ Yes |
+ BXD-19m |
+ 16 |
+ m46 |
+ 4,5,6 |
+ 12-15-2006 |
+
+
+ | 40 |
+ HZI1499 |
+ BXD-28m (m43) CD25+ |
+ M |
+ BXD28 |
+ CD25+ |
+ Yes |
+ BXD-28m |
+ 17,2 |
+ m43 |
+ 1,2,3 |
+ 10-23-2006 |
+
+
+ | 41 |
+ HZI1500 |
+ BXD-42f (f49) CD25+ |
+ F |
+ BXD42 |
+ CD25+ |
+ Yes |
+ BXD-42f |
+ 17 |
+ f49 |
+ ?? |
+ 3-8-2007 |
+
+
+ | 42 |
+ HZI1502 |
+ F1 (BXD)m (f50) CD25+ |
+ M |
+ B6D2F1 |
+ CD25+ |
+ Yes |
+ F1 (BXD)m |
+ 15 |
+ m51 |
+ 1,2,3, |
+ 4-18-2007 |
+
+
+ | 43 |
+ HZI1503 |
+ F1 (BXD)m (m51) CD25+ |
+ F |
+ B6D2F1 |
+ CD25+ |
+ Yes |
+ F1 (BXD)f |
+ 15 |
+ f50 |
+ 1,2,3 |
+ 4-18-2007 |
+
+
+ | 44 |
+ HZI1504 |
+ BXD-86f (f52) CD25+ |
+ F |
+ BXD86 |
+ CD25+ |
+ Yes |
+ BXD-86f |
+ 16 |
+ f52 |
+ 1,2,3 |
+ 4-18-2007 |
+
+
+ | 45 |
+ HZI1505 |
+ BXD-43f (f53) CD25+ |
+ F |
+ BXD43 |
+ CD25+ |
+ Yes |
+ BXD-43f |
+ 16 |
+ f53 |
+ 1,2,3 |
+ 4-23-2007 |
+
+
+ | 46 |
+ HZI1506 |
+ BXD-44f (f54) CD25+ |
+ F |
+ BXD44 |
+ CD25+ |
+ Yes |
+ BXD-44f |
+ 18 |
+ f54 |
+ 1,2,3 |
+ 4-23-2007 |
+
+
+ | 47 |
+ HZI1507 |
+ BXD-45f (f55) CD25+ |
+ F |
+ BXD45 |
+ CD25+ |
+ Yes |
+ BXD-45f |
+ 19 |
+ f55 |
+ 1,2,3 |
+ 4-23-2007 |
+
+
+ | 48 |
+ HZI1508 |
+ BXD-62f (f56) CD25+ |
+ F |
+ BXD62 |
+ CD25+ |
+ Yes |
+ BXD-62f |
+ 17 |
+ f56 |
+ 1,2,3 |
+ 4-26-2007 |
+
+
+ | 49 |
+ HZI1509 |
+ BXD-73f (f57) CD25+ |
+ F |
+ BXD73 |
+ CD25+ |
+ Yes |
+ BXD-73f |
+ 18 |
+ f57 |
+ 1,2,3 |
+ 4-26-2007 |
+
+
+ | 50 |
+ HZI1510 |
+ BXD-51f (f59) CD25+ |
+ F |
+ BXD51 |
+ CD25+ |
+ Yes |
+ BXD-51f |
+ 22 |
+ f59 |
+ 1,2,3 |
+ 6-18-2007 |
+
+
+ | 51 |
+ HZI1523 |
+ BXD-75f (f58) CD25+ |
+ F |
+ BXD75 |
+ CD25+ |
+ Yes |
+ BXD-75f |
+ 15,17 |
+ f58 |
+ 1,2,3 |
+ 4-26-2007 |
+
+
+ | 52 |
+ HZI1525 |
+ BXD-29m (m37) CD25+ |
+ M |
+ BXD29 |
+ CD25+ |
+ Yes |
+ BXD-29m |
+ 20, 16 |
+ m37 |
+ 1,2,3 |
+ 8-29-2006 |
+
+
+ | 53 |
+ HZI1526 |
+ BXD-34f (f4) CD25+ |
+ F |
+ BXD34 |
+ CD25+ |
+ Yes |
+ BXD-34f |
+ 17 |
+ f4 |
+ 1,2,3 |
+ 2-1-2006 |
+
+
+ | 54 |
+ HZI1940 |
+ BXD-27m (m39) CD25+ |
+ M |
+ BXD27 |
+ CD25+ |
+ Yes |
+ BXD-27m |
+ 18 - 20 |
+ m39 |
+ 1,3,4 |
+ 9-1-2006 |
+
+
+ | 55 |
+ HZI1941 |
+ BXD-42m (m47) CD25+ |
+ M |
+ BXD42 |
+ CD25+ |
+ Yes |
+ BXD-42m |
+ 15,16 |
+ m47 |
+ 1,2,3 |
+ 12-15-2006 |
+
+
+ | 56 |
+ HZI1942 |
+ BXD-34m (m5) CD25+ |
+ M |
+ BXD34 |
+ CD25+ |
+ Yes |
+ BXD-34m |
+ 17 |
+ m5 |
+ 5,7,8 |
+ 2-1-2006 |
+
+
+ | 57 |
+ HZI1943 |
+ BXD-38f (f70) CD25+ |
+ F |
+ BXD38 |
+ CD25+ |
+ Yes |
+ BXD-38f |
+ 13 |
+ f70 |
+ 4,5,6,7 |
+ 2-1-2008 |
+
+
+ | 58 |
+ HZI1944 |
+ BXD-31m (m69) CD25+ |
+ M |
+ BXD31 |
+ CD25+ |
+ Yes |
+ BXD-31m |
+ 14 |
+ m69 |
+ 4,5,6 |
+ 2-1-2008 |
+
+
+ | 59 |
+ HZI1945 |
+ BXD-27f (f12) CD25+ |
+ F |
+ BXD27 |
+ CD25+ |
+ Yes |
+ BXD-27f |
+ 18 |
+ f12 |
+ 1,2 |
+ 2-15-2006 |
+
+
+ | 60 |
+ HZI1946 |
+ BXD-38m (m63) CD25+ |
+ M |
+ BXD38 |
+ CD25+ |
+ Yes |
+ BXD-38m |
+ 18 |
+ m63 |
+ 1,2,3 |
+ 6-20-2007 |
+
+
+ | 61 |
+ HZI1947 |
+ BXD-23f (f62) CD25+ |
+ F |
+ BXD23 |
+ CD25+ |
+ Yes |
+ BXD-23f |
+ 21 |
+ f62 |
+ 1,2,3 |
+ 6-20-2007 |
+
+
+ | 62 |
+ HZI1948 |
+ BXD-28f (f61) CD25+ |
+ F |
+ BXD28 |
+ CD25+ |
+ Yes |
+ BXD-28f |
+ 22 |
+ f61 |
+ 1,2,3 |
+ 6-18-2007 |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Rtc_1106_r/experiment-design.rtf b/general/datasets/Rtc_1106_r/experiment-design.rtf
new file mode 100644
index 0000000..a69dffc
--- /dev/null
+++ b/general/datasets/Rtc_1106_r/experiment-design.rtf
@@ -0,0 +1,7 @@
+
+Parental and BXD lines were received from Jackson Laboratory, or from Oak Ridge Laboratory (BXD43, BXD51, BXD61, BXD62, BXD65, BXD68, BXD69, BXD73, BXD75, BXD87, BXD90), and were bred in the facility of the Neuro-BSIK consortium (VU University Amsterdam). Female mice, 3 per strain, were housed on sawdust in standard Makrolon type II cages with food (Harlan Teklad 2018) and water ad libitum under specific pathogen free conditions. For the analysis, mice were transferred to the animal facility in Braunschweig and adapted for at least two weeks to the new environment before preparing the spleen cells. All protocols involving mice were approved by national animal welfare committees.
+
+For sorting of Tregs and Th cells, splenocytes from 31 BXD recombinant inbred strains, as well as from the parental strains DBA/2J and C57BL/6J, were isolated by flushing the spleens with erythrocyte lysis buffer. Cells were collected by centrifugation, resuspended in cold FACS-buffer (PBS / 2% FCS / 0,5 mM EDTA). After passing the cells through a 100 µm cell strainer and an additional washing step with FACS-buffer, splenocytes were stained with anti-CD4-APC and anti-CD25-PE for 10 minutes at 4 °C, washed and resuspended in FACS-buffer. CD4+ T cells were separated into CD4+CD25+ Tregs and CD4+CD25- Th cells using a MoFlo cell sorter (Cytomation) and purity of the sorted T cell subsets reached 95-97%.
+
+Quality and integrity of the total RNA isolated from 1x105 cells was controlled by running all samples on an Agilent Technologies 2100 Bioanalyzer (Agilent Technologies; Waldbronn, Germany). RNA amplification and labeling was done according to manufactures protocol (Small Sample Target Labeling Assay Version II, Affymetrix; Santa Clara, CA). The concentration of biotin-labeled cRNA was determined by UV absorbance. In all cases, 10 µg of each biotinylated cRNA preparation were fragmented and placed in a hybridization cocktail containing four biotinylated hybridization controls (BioB, BioC, BioD, and Cre) as recommended by the manufacturer. Samples were hybridized to an identical lot of Affymetrix MOE430 2.0 for 16 hours at 46 °C. After hybridisation the GeneChips were washed and stained using the Affymetrix´s recommended EukGE-WS2v5 protocol for GeneChip Fluidics FS400 station. Images were scanned using GeneChip Scanner 3000 under the control of GCOS 1.3 software package (Affymetrix; Santa Clara, CA).
+
diff --git a/general/datasets/Rtc_1106_r/notes.rtf b/general/datasets/Rtc_1106_r/notes.rtf
new file mode 100644
index 0000000..dbd0c60
--- /dev/null
+++ b/general/datasets/Rtc_1106_r/notes.rtf
@@ -0,0 +1 @@
+This text file was generated by KS on July, 18 2011.
diff --git a/general/datasets/Rtc_1106_r/platform.rtf b/general/datasets/Rtc_1106_r/platform.rtf
new file mode 100644
index 0000000..ed42a9b
--- /dev/null
+++ b/general/datasets/Rtc_1106_r/platform.rtf
@@ -0,0 +1,3 @@
+
+The Affymetrix M430 2.0 array consists of approximately 992,936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts, including a majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using NCBI Build 107 by Affymetrix. The UTHSC GN group continuously reannotated probe sets on this array, producing more accurate data on probe and probe set targets. All probes have also be aligned to the most recent assembly of the Mouse Genome using Jim Kent's BLAT program.
+
diff --git a/general/datasets/Rtc_1106_r/processing.rtf b/general/datasets/Rtc_1106_r/processing.rtf
new file mode 100644
index 0000000..b8d49b7
--- /dev/null
+++ b/general/datasets/Rtc_1106_r/processing.rtf
@@ -0,0 +1,6 @@
+
+Microarray data then was preprocessed using the RMA method [bolstad] and subsequently batch corrected [Alberts et al]. In this study, RNA was extracted at three different points in time for the Treg samples and also microarray processing was performed at three different points in time. Similarly, the Th samples were processed in two batches. Therefore, we performed a batch correction for both cell types using the following ANOVA model before further analysis of the data.
+yi = μ + Bi + ei
+Where yi is the expression level of the ith microarray, μ is the overall mean, Bi is the batch to which the ith individual belongs and ei is the residual error.
+Batch corrected data sets were then preprocessed before transferring them to the GeneNetwork (GN) database: Adding an offset of 1 unit to each signal intensity value to ensure that the logarithm of all values were positive, computing the log2 value, performing a quantile normalization of the log2 values for the total set of arrays using the same initial steps used by the RMA transform, computing the Z scores for each cell value, multiplying all Z scores by 2 and adding 8 to the value of all Z scores. The advantage of this variant of a Z transformation is that all values are positive and that 1 unit represents approximately a 2-fold difference in expression as determined using the spike-in control probe sets. The mean values were subsequently calculated if multiple samples from one BXD line were recorded (male and females or replicates).
+
diff --git a/general/datasets/Rtc_1106_r/summary.rtf b/general/datasets/Rtc_1106_r/summary.rtf
new file mode 100644
index 0000000..2094b06
--- /dev/null
+++ b/general/datasets/Rtc_1106_r/summary.rtf
@@ -0,0 +1,3 @@
+ERROR-CHECKED FIRST PHASE PRIVATE TEST DATA SET. This data set provides estimates of gene expression in regulatory T cells (CD4+CD25+) of BXD strains. Data were generated by Prof. Dr. Klaus Schughart and colleagues at the Helmholtz Centre for Infection Research (HZI). Samples were processed using a total of 35 Affymetrix MOE 430 2.0 short oligomer microarrays, of which 33 passed stringent quality control and error checking.
+This is a private test data set. Please contact Dr. Klaus Schughart for early access.
+
diff --git a/general/datasets/Rthc_0211_r/acknowledgment.rtf b/general/datasets/Rthc_0211_r/acknowledgment.rtf
new file mode 100644
index 0000000..3246da5
--- /dev/null
+++ b/general/datasets/Rthc_0211_r/acknowledgment.rtf
@@ -0,0 +1,5 @@
+
+These data were generated by Prof. Dr. Klaus Schughart (Department of Experimental Mouse Genetics) and Dr. Dunja Bruder (Research Group Immune Regulation) at the Helmholtz Center for Infection Research with the help of Dr. Lothar Gröbe (FACS sorting, Research Group Mucosal Immunity).
+
+Funding was provided by the Helmholtz Association and publicly funded research projects awarded to Drs. Klaus Schughart and Dunja Bruder.
+
diff --git a/general/datasets/Rthc_0211_r/cases.rtf b/general/datasets/Rthc_0211_r/cases.rtf
new file mode 100644
index 0000000..5f97723
--- /dev/null
+++ b/general/datasets/Rthc_0211_r/cases.rtf
@@ -0,0 +1,824 @@
+
+Parental and 31 BXD lines were studied. Mice were received from Jackson Laboratory, or from The Oak Ridge National and were bred in the facility of the Neuro-BSIK consortium (VU University Amsterdam). The data set includes expression values for 18 of the BXD strains made by Benjamin Taylor at the Jackson Laboratory in the 1970s and 1990s (BXD1 through BXD40, as well as the two parental strains, C57BL/6J and DBA/2J. All of these strains are fully inbred, many well beyond the 100th filial (F) generation of inbreeding.
+
+BXD spleen sample pools (from 2-3 mice) were obtained from a pathogen-free mice of the Dutch Mouse Phenomics Consortium (MPC) in Amsterdam. Mice were imported into the central animal facility at the HZI and kept in a pathogen-free vivarium. Mice were euthanized using CO2 and spleenocytes wre prepared. Most mice were between 17 and 22 weeks of age when samples were collected. FACS sorting was used to select the CD4-positive T cells. These cells were further separated into CD4+CD25+ and CD4+CD25- pools.
+
+Error-checking strain identity. A set of more than 20 probe sets with Mendelian segregation patterns in this HZI data set were used to confirm strain identify in early June, 2007. Two errors were detected and rectified. As of June 22, 2007, data are registered correctly. Prior to June 22, 2007, data listed as strains BXD33 and BXD39 were essentially hybrid (mixed) data sets.
+
+On Aug 23, 2007, we loaded the final QTL Reaper data into GeneNetwork for the corrected data set. The maximum LRS generated by any probe set is 84.6 for 1436240_at (Tra2a). A total of 41 probe sets are associated with QTLs that have LRS values above 46 (LOD > 10).
+
+ Table 1
+
+
+
+
+
+
+
+
+
+ | Index |
+ ProbeSet ID |
+ Sample Description |
+ Sex |
+ Strain |
+ cd25 |
+ Microarray |
+ Short Description |
+ Age |
+ Pool No. |
+ Pool members (animal number) |
+ Date of preparation |
+
+
+ | 1 |
+ HZI1176 |
+ BXD-06f (f1) CD25 |
+ F |
+ BXD6 |
+ CD25- |
+ Yes |
+ BXD-06f |
+ 17 |
+ f1 |
+ 1,3,4 |
+ 1-31-2006 |
+
+
+ | 2 |
+ HZI1177 |
+ BXD-06m (m2) CD25 |
+ M |
+ BXD6 |
+ CD25- |
+ Yes |
+ BXD-06m |
+ 18 |
+ m2 |
+ 5,6,7 |
+ 1-31-2006 |
+
+
+ | 3 |
+ HZI1178 |
+ BXD-14m (m3) CD25 |
+ M |
+ BXD14 |
+ CD25- |
+ Yes |
+ BXD-14m |
+ 17 |
+ m3 |
+ 1,3,4 |
+ 1-31-2006 |
+
+
+ | 4 |
+ HZI1179 |
+ BXD-34f (f4) CD25 |
+ F |
+ BXD34 |
+ CD25- |
+ Yes |
+ BXD-34f |
+ 17 |
+ f4 |
+ 1,2,3 |
+ 2-1-2006 |
+
+
+ | 5 |
+ HZI1180 |
+ BXD-34m (m5) CD25 |
+ M |
+ BXD34 |
+ CD25- |
+ Yes |
+ BXD-34m |
+ 17 |
+ m5 |
+ 5,7,8 |
+ 2-1-2006 |
+
+
+ | 6 |
+ HZI1181 |
+ BXD-40f (f6) CD25 |
+ F |
+ BXD40 |
+ CD25- |
+ Yes |
+ BXD-40f |
+ 17 |
+ f6 |
+ 1,2,3 |
+ 2-1-2006 |
+
+
+ | 7 |
+ HZI1182 |
+ BXD-40m (m7) CD25 |
+ M |
+ BXD40 |
+ CD25- |
+ Yes |
+ BXD-40m |
+ 17 |
+ m7 |
+ 5,6,7 |
+ 2-2-2006 |
+
+
+ | 8 |
+ HZI1183 |
+ BXD-02f (f8) CD25 |
+ F |
+ BXD2 |
+ CD25- |
+ Yes |
+ BXD-02f |
+ 17 |
+ f8 |
+ 1,2,3 |
+ 2-14-2006 |
+
+
+ | 9 |
+ HZI1184 |
+ BXD-02m (m20) CD25 |
+ M |
+ BXD2 |
+ CD25- |
+ Yes |
+ BXD-02m |
+ 21 |
+ m20 |
+ 4,5,6 |
+ 4-6-2006 |
+
+
+ | 10 |
+ HZI1185 |
+ BXD-11f (f30) CD25 |
+ F |
+ BXD11 |
+ CD25- |
+ Yes |
+ BXD-11f |
+ 17 |
+ f30 |
+ 3,4,5 |
+ 5-11-2006 |
+
+
+ | 11 |
+ HZI1186 |
+ BXD-11m (m9) CD25 |
+ M |
+ BXD11 |
+ CD25- |
+ Yes |
+ BXD-11m |
+ 18 |
+ m9 |
+ 1,2 |
+ 2-14-2006 |
+
+
+ | 12 |
+ HZI1187 |
+ BXD-12f (f10) CD25 |
+ F |
+ BXD12 |
+ CD25- |
+ Yes |
+ BXD-12f |
+ 17 |
+ f10 |
+ 1,2,3 |
+ 2-14-2006 |
+
+
+ | 13 |
+ HZI1188 |
+ BXD-39f (f23) CD25 |
+ F |
+ BXD39 |
+ CD25- |
+ Yes |
+ BXD-39f |
+ 19 |
+ f23 |
+ 4,5,6 |
+ 4-11-2006 |
+
+
+ | 14 |
+ HZI1191 |
+ BXD-18m (m13) CD25 |
+ M |
+ BXD18 |
+ CD25- |
+ Yes |
+ BXD-18m |
+ 18 |
+ m13 |
+ 7,8 |
+ 2-15-2006 |
+
+
+ | 15 |
+ HZI1192 |
+ BXD-23m (m15) CD25 |
+ M |
+ BXD23 |
+ CD25- |
+ Yes |
+ BXD-23m |
+ 18 |
+ m15 |
+ 1,2,3 |
+ 2-15-2006 |
+
+
+ | 16 |
+ HZI1194 |
+ BXD-09f (f17) CD25 |
+ F |
+ BXD9 |
+ CD25- |
+ Yes |
+ BXD-09f |
+ 21 |
+ f17 |
+ 1,2,3 |
+ 4-5-2006 |
+
+
+ | 17 |
+ HZI1195 |
+ BXD-09m (m16) CD25 |
+ M |
+ BXD9 |
+ CD25- |
+ Yes |
+ BXD-09m2 |
+ 21 |
+ m16 |
+ 5,6 |
+ 4-5-2006 |
+
+
+ | 18 |
+ HZI1196 |
+ BXD-09m (m35) CD25 |
+ M |
+ BXD9 |
+ CD25- |
+ Yes |
+ BXD-09m |
+ 15 |
+ m35 |
+ 7,8,9 |
+ 7-7-2006 |
+
+
+ | 19 |
+ HZI1197 |
+ BXD-32f (f18) CD25 |
+ F |
+ BXD32 |
+ CD25- |
+ Yes |
+ BXD-32f |
+ 21 |
+ f18 |
+ 1,2,3 |
+ 4-6-2006 |
+
+
+ | 20 |
+ HZI1198 |
+ BXD-32m (m19) CD25 |
+ M |
+ BXD32 |
+ CD25- |
+ Yes |
+ BXD-32m |
+ 22 |
+ m19 |
+ 1,2,3 |
+ 4-6-2006 |
+
+
+ | 21 |
+ HZI1199 |
+ BXD-33f (f22) CD25 |
+ F |
+ BXD33 |
+ CD25- |
+ Yes |
+ BXD-33f |
+ 18 |
+ f22 |
+ 2,3,4 |
+ 4-11-2006 |
+
+
+ | 22 |
+ HZI1200 |
+ BXD-39m (m29) CD25 |
+ M |
+ BXD39 |
+ CD25- |
+ Yes |
+ BXD-39m |
+ 17 |
+ m29 |
+ 5,6,7 |
+ 5-10-2006 |
+
+
+ | 23 |
+ HZI1201 |
+ BXD-01f (f32) CD25 |
+ F |
+ BXD1 |
+ CD25- |
+ Yes |
+ BXD-01f |
+ 18 |
+ f32 |
+ 3,4 |
+ 7-6-2006 |
+
+
+ | 24 |
+ HZI1202 |
+ BXD-01m (m31) CD25 |
+ M |
+ BXD1 |
+ CD25- |
+ Yes |
+ BXD-01m |
+ 18 |
+ m31 |
+ 1,2 |
+ 7-6-2006 |
+
+
+ | 25 |
+ HZI1203 |
+ BXD-16f (f26) CD25 |
+ F |
+ BXD16 |
+ CD25- |
+ Yes |
+ BXD-16f |
+ 18 |
+ f26 |
+ 1,2,3 |
+ 4-12-2006 |
+
+
+ | 26 |
+ HZI1204 |
+ BXD-21f (f25) CD25 |
+ F |
+ BXD21 |
+ CD25- |
+ Yes |
+ BXD-21f |
+ 19 |
+ f25 |
+ 5,6,7 |
+ 4-12-2006 |
+
+
+ | 27 |
+ HZI1205 |
+ BXD-21m (m24) CD25 |
+ M |
+ BXD21 |
+ CD25- |
+ Yes |
+ BXD-21m |
+ 18 |
+ m24 |
+ 1,2,3 |
+ 4-12-2006 |
+
+
+ | 28 |
+ HZI1208 |
+ C57BL/6Jf (f28) CD25 |
+ F |
+ C57BL/6J |
+ CD25- |
+ Yes |
+ C57BL/6Jf |
+ 16 |
+ f28 |
+ 1,2,3 |
+ 5-10-2006 |
+
+
+ | 29 |
+ HZI1209 |
+ DBA/2Jf (f27) CD25 |
+ F |
+ DBA/2J |
+ CD25- |
+ Yes |
+ DBA/2Jf |
+ 16 |
+ f27 |
+ 5,6,7 |
+ 5-10-2006 |
+
+
+ | 30 |
+ HZI1210 |
+ DBA/2Jm (m21) CD25 |
+ M |
+ DBA/2J |
+ CD25- |
+ Yes |
+ DBA/2Jm |
+ 21 |
+ m21 |
+ 1,2,3 |
+ 4-11-2006 |
+
+
+ | 31 |
+ HZI2473 |
+ BXD-13 m 45 |
+ M |
+ BXD13 |
+ CD25- |
+ Yes |
+ BXD-13m |
+ 15 |
+ m45 |
+ 4,5,6,7 |
+ 12-13-2006 |
+
+
+ | 32 |
+ HZI2474 |
+ BXD-19 m 46 |
+ M |
+ BXD19 |
+ CD25- |
+ Yes |
+ BXD-19m |
+ 16 |
+ m46 |
+ 4,5,6 |
+ 12-15-2006 |
+
+
+ | 33 |
+ HZI2475 |
+ BXD-28 m 43 |
+ M |
+ BXD28 |
+ CD25- |
+ Yes |
+ BXD-28m |
+ 17,2 |
+ m43 |
+ 1,2,3 |
+ 10-23-2006 |
+
+
+ | 34 |
+ HZI2476 |
+ BXD-29 m 37 |
+ M |
+ BXD29 |
+ CD25- |
+ Yes |
+ BXD-29m |
+ 20, 16 |
+ m37 |
+ 1,2,3 |
+ 8-29-2006 |
+
+
+ | 35 |
+ HZI2477 |
+ BXD-31 m 69 |
+ M |
+ BXD31 |
+ CD25- |
+ Yes |
+ BXD-31m |
+ 14 |
+ m69 |
+ 4,5,6 |
+ 2-1-2008 |
+
+
+ | 36 |
+ HZI2478 |
+ BXD-33 m 11 |
+ M |
+ BXD33 |
+ CD25- |
+ Yes |
+ BXD-33m |
+ 17 |
+ m11 |
+ 1,2 |
+ 2-14-2006 |
+
+
+ | 37 |
+ HZI2479 |
+ BXD-38 m 63 |
+ M |
+ BXD38 |
+ CD25- |
+ Yes |
+ BXD-38m |
+ 18 |
+ m63 |
+ 1,2,3 |
+ 6-20-2007 |
+
+
+ | 38 |
+ HZI2480 |
+ BXD-42 m 47 |
+ M |
+ BXD42 |
+ CD25- |
+ Yes |
+ BXD-42m |
+ 15,16 |
+ m47 |
+ 1,2,3 |
+ 12-15-2006 |
+
+
+ | 39 |
+ HZI2481 |
+ BXD-42 m 65 |
+ M |
+ BXD42 |
+ CD25- |
+ Yes |
+ BXD-42m |
+ 15,16 |
+ m47 |
+ 1,2,3 |
+ 12-15-2006 |
+
+
+ | 40 |
+ HZI2482 |
+ BXD-13 f 44 |
+ F |
+ BXD13 |
+ CD25- |
+ Yes |
+ BXD-13f |
+ 15 |
+ f44 |
+ 1,2,3 |
+ 12-13-2006 |
+
+
+ | 41 |
+ HZI2483 |
+ BXD-18 F 14 |
+ F |
+ BXD18 |
+ CD25- |
+ Yes |
+ BXD-18f |
+ 17 |
+ f14 |
+ 3,4,5 |
+ 2-15-2006 |
+
+
+ | 42 |
+ HZI2484 |
+ BXD-19 f 38 |
+ F |
+ BXD19 |
+ CD25- |
+ Yes |
+ BXD-19f2 |
+ 21 |
+ f38 |
+ 1,2,3 |
+ 9-1-2006 |
+
+
+ | 43 |
+ HZI2485 |
+ BXD-19 f 64 |
+ F |
+ BXD19 |
+ CD25- |
+ Yes |
+ BXD-19f |
+ 19 |
+ f64 |
+ 7,8,9 |
+ 6-20-2007 |
+
+
+ | 44 |
+ HZI2486 |
+ BXD-28 f 61 |
+ F |
+ BXD28 |
+ CD25- |
+ Yes |
+ BXD-28f |
+ 22 |
+ f61 |
+ 1,2,3 |
+ 6-18-2007 |
+
+
+ | 45 |
+ HZI2487 |
+ BXD-29 f 40 |
+ F |
+ BXD29 |
+ CD25- |
+ Yes |
+ BXD-29f |
+ 15 - 16 |
+ f40 |
+ 4,5,6 |
+ 9-25-2006 |
+
+
+ | 46 |
+ HZI2488 |
+ BXD-31 f 34 |
+ F |
+ BXD31 |
+ CD25- |
+ Yes |
+ BXD-31f |
+ 16 |
+ f34 |
+ 1,2,3 |
+ 7-7-2006 |
+
+
+ | 47 |
+ HZI2489 |
+ BXD-38 f 70 |
+ F |
+ BXD38 |
+ CD25- |
+ Yes |
+ BXD-38f |
+ 13 |
+ f70 |
+ 4,5,6,7 |
+ 2-1-2008 |
+
+
+ | 48 |
+ HZI2490 |
+ BXD-42 f 49 |
+ F |
+ BXD42 |
+ CD25- |
+ Yes |
+ BXD-42f |
+ 17 |
+ f49 |
+ ?? |
+ 3-8-2007 |
+
+
+ | 49 |
+ HZI2491 |
+ BXD-43 f 53 |
+ F |
+ BXD43 |
+ CD25- |
+ Yes |
+ BXD-43f |
+ 16 |
+ f53 |
+ 1,2,3 |
+ 4-23-2007 |
+
+
+ | 50 |
+ HZI2492 |
+ BXD-44 f 54 |
+ F |
+ BXD44 |
+ CD25- |
+ Yes |
+ BXD-44f |
+ 18 |
+ f54 |
+ 1,2,3 |
+ 4-23-2007 |
+
+
+ | 51 |
+ HZI2493 |
+ BXD-45 f 55 |
+ F |
+ BXD45 |
+ CD25- |
+ Yes |
+ BXD-45f |
+ 19 |
+ f55 |
+ 1,2,3 |
+ 4-23-2007 |
+
+
+ | 52 |
+ HZI2494 |
+ BXD-51 f 59 |
+ F |
+ BXD51 |
+ CD25- |
+ Yes |
+ BXD-51f |
+ 22 |
+ f59 |
+ 1,2,3 |
+ 6-18-2007 |
+
+
+ | 53 |
+ HZI2495 |
+ BXD-62 f 56 |
+ F |
+ BXD62 |
+ CD25- |
+ Yes |
+ BXD-62f |
+ 17 |
+ f56 |
+ 1,2,3 |
+ 4-26-2007 |
+
+
+ | 54 |
+ HZI2496 |
+ BXD-73 f 57 |
+ F |
+ BXD73 |
+ CD25- |
+ Yes |
+ BXD-73f |
+ 18 |
+ f57 |
+ 1,2,3 |
+ 4-26-2007 |
+
+
+ | 55 |
+ HZI2497 |
+ BXD-75 f 58 |
+ F |
+ BXD75 |
+ CD25- |
+ Yes |
+ BXD-75f |
+ 15,17 |
+ f58 |
+ 1,2,3 |
+ 4-26-2007 |
+
+
+ | 56 |
+ HZI2498 |
+ BXD-86 f 52 |
+ F |
+ BXD86 |
+ CD25- |
+ Yes |
+ BXD-86f |
+ 16 |
+ f52 |
+ 1,2,3 |
+ 4-18-2007 |
+
+
+
+ |
+
+
+
+
+
diff --git a/general/datasets/Rthc_0211_r/experiment-design.rtf b/general/datasets/Rthc_0211_r/experiment-design.rtf
new file mode 100644
index 0000000..2b4d4cc
--- /dev/null
+++ b/general/datasets/Rthc_0211_r/experiment-design.rtf
@@ -0,0 +1,7 @@
+
+Parental and BXD lines were received from Jackson Laboratory, or from Oak Ridge Laboratory (BXD43, BXD51, BXD61, BXD62, BXD65, BXD68, BXD69, BXD73, BXD75, BXD87, BXD90), and were bred in the facility of the Neuro-BSIK consortium (VU University Amsterdam). Female mice 3 per strain were housed on sawdust in standard Makrolon type II cages with food (Harlan Teklad 2018) and water ad libitum under specific pathogen free conditions. For the analysis, mice were transferred to the animal facility in Braunschweig and adapted for at least two weeks to the new environment before preparing the spleen cells. All protocols involving mice were approved by national animal welfare committees.
+
+For sorting of Tregs and Th cells, splenocytes from 31 BXD recombinant inbred strains as well as from the parental mouse lines DBA/2J and C57BL/6J were isolated by flushing the spleens with erythrocyte-lysis-buffer. Cells were collected by centrifugation, re-suspended in cold FACS-buffer (PBS / 2% FCS / 0,5 mM EDTA). After passing the cells through a 100 µm cell strainer and an additional washing step with FACS-buffer, splenocytes were stained with anti-CD4-APC and anti-CD25-PE for 10 minutes at 4°C, washed and re-suspended in FACS-buffer. CD4+ T cells were separated into CD4+CD25+ Tregs and CD4+CD25- Th cells using a MoFlo cell sorter (Cytomation) and purity of the sorted T cell subsets reached 95-97%.
+
+Quality and integrity of the total RNA isolated from 1x105 cells was controlled by running all samples on an Agilent Technologies 2100 Bioanalyzer (Agilent Technologies; Waldbronn, Germany). RNA amplification and labeling was done according to manufactures protocol (Small Sample Target Labeling Assay Version II, Affymetrix; Santa Clara, CA). The concentration of biotin-labeled cRNA was determined by UV absorbance. In all cases, 10 µg of each biotinylated cRNA preparation were fragmented and placed in a hybridization cocktail containing four biotinylated hybridization controls (BioB, BioC, BioD, and Cre) as recommended by the manufacturer. Samples were hybridized to an identical lot of Affymetrix MOE430 2.0 for 16 hours at 46°C. After hybridisation the GeneChips were washed and stained using the Affymetrix´s recommended EukGE-WS2v5 protocol for GeneChip® Fluidics FS400 station. Images were scanned using GeneChip® Scanner 3000 under the control of GCOS 1.3 software package (Affymetrix; Santa Clara, CA).
+
diff --git a/general/datasets/Rthc_0211_r/experiment-type.rtf b/general/datasets/Rthc_0211_r/experiment-type.rtf
new file mode 100644
index 0000000..0139307
--- /dev/null
+++ b/general/datasets/Rthc_0211_r/experiment-type.rtf
@@ -0,0 +1,4 @@
+Parental and BXD lines were received from Jackson Laboratory, or from Oak Ridge Laboratory (BXD43, BXD51, BXD61, BXD62, BXD65, BXD68, BXD69, BXD73, BXD75, BXD87, BXD90), and were bred in the facility of the Neuro-BSIK consortium (VU University Amsterdam). Female mice 3 per strain were housed on sawdust in standard Makrolon type II cages with food (Harlan Teklad 2018) and water ad libitum under specific pathogen free conditions. For the analysis, mice were transferred to the animal facility in Braunschweig and adapted for at least two weeks to the new environment before preparing the spleen cells. All protocols involving mice were approved by national animal welfare committees.
+ For sorting of Tregs and Th cells, splenocytes from 31 BXD recombinant inbred strains as well as from the parental mouse lines DBA/2J and C57BL/6J were isolated by flushing the spleens with erythrocyte-lysis-buffer. Cells were collected by centrifugation, re-suspended in cold FACS-buffer (PBS / 2% FCS / 0,5 mM EDTA). After passing the cells through a 100 µm cell strainer and an additional washing step with FACS-buffer, splenocytes were stained with anti-CD4-APC and anti-CD25-PE for 10 minutes at 4°C, washed and re-suspended in FACS-buffer. CD4+ T cells were separated into CD4+CD25+ Tregs and CD4+CD25- Th cells using a MoFlo cell sorter (Cytomation) and purity of the sorted T cell subsets reached 95-97%.
+ Quality and integrity of the total RNA isolated from 1x105 cells was controlled by running all samples on an Agilent Technologies 2100 Bioanalyzer (Agilent Technologies; Waldbronn, Germany). RNA amplification and labeling was done according to manufactures protocol (Small Sample Target Labeling Assay Version II, Affymetrix; Santa Clara, CA). The concentration of biotin-labeled cRNA was determined by UV absorbance. In all cases, 10 µg of each biotinylated cRNA preparation were fragmented and placed in a hybridization cocktail containing four biotinylated hybridization controls (BioB, BioC, BioD, and Cre) as recommended by the manufacturer. Samples were hybridized to an identical lot of Affymetrix MOE430 2.0 for 16 hours at 46°C. After hybridisation the GeneChips were washed and stained using the Affymetrix´s recommended EukGE-WS2v5 protocol for GeneChip® Fluidics FS400 station. Images were scanned using GeneChip® Scanner 3000 under the control of GCOS 1.3 software package (Affymetrix; Santa Clara, CA).
+
\ No newline at end of file
diff --git a/general/datasets/Rthc_0211_r/notes.rtf b/general/datasets/Rthc_0211_r/notes.rtf
new file mode 100644
index 0000000..dbd0c60
--- /dev/null
+++ b/general/datasets/Rthc_0211_r/notes.rtf
@@ -0,0 +1 @@
+This text file was generated by KS on July, 18 2011.
diff --git a/general/datasets/Rthc_0211_r/platform.rtf b/general/datasets/Rthc_0211_r/platform.rtf
new file mode 100644
index 0000000..ed42a9b
--- /dev/null
+++ b/general/datasets/Rthc_0211_r/platform.rtf
@@ -0,0 +1,3 @@
+
+The Affymetrix M430 2.0 array consists of approximately 992,936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts, including a majority of known genes and expressed sequence tags. The array sequences were selected late in 2002 using NCBI Build 107 by Affymetrix. The UTHSC GN group continuously reannotated probe sets on this array, producing more accurate data on probe and probe set targets. All probes have also be aligned to the most recent assembly of the Mouse Genome using Jim Kent's BLAT program.
+
diff --git a/general/datasets/Rthc_0211_r/processing.rtf b/general/datasets/Rthc_0211_r/processing.rtf
new file mode 100644
index 0000000..b8d49b7
--- /dev/null
+++ b/general/datasets/Rthc_0211_r/processing.rtf
@@ -0,0 +1,6 @@
+
+Microarray data then was preprocessed using the RMA method [bolstad] and subsequently batch corrected [Alberts et al]. In this study, RNA was extracted at three different points in time for the Treg samples and also microarray processing was performed at three different points in time. Similarly, the Th samples were processed in two batches. Therefore, we performed a batch correction for both cell types using the following ANOVA model before further analysis of the data.
+yi = μ + Bi + ei
+Where yi is the expression level of the ith microarray, μ is the overall mean, Bi is the batch to which the ith individual belongs and ei is the residual error.
+Batch corrected data sets were then preprocessed before transferring them to the GeneNetwork (GN) database: Adding an offset of 1 unit to each signal intensity value to ensure that the logarithm of all values were positive, computing the log2 value, performing a quantile normalization of the log2 values for the total set of arrays using the same initial steps used by the RMA transform, computing the Z scores for each cell value, multiplying all Z scores by 2 and adding 8 to the value of all Z scores. The advantage of this variant of a Z transformation is that all values are positive and that 1 unit represents approximately a 2-fold difference in expression as determined using the spike-in control probe sets. The mean values were subsequently calculated if multiple samples from one BXD line were recorded (male and females or replicates).
+
diff --git a/general/datasets/Rthc_0211_r/summary.rtf b/general/datasets/Rthc_0211_r/summary.rtf
new file mode 100644
index 0000000..4fd2899
--- /dev/null
+++ b/general/datasets/Rthc_0211_r/summary.rtf
@@ -0,0 +1,4 @@
+ERROR-CHECKED FIRST PHASE PRIVATE TEST DATA SET. This data set provides estimates of gene expression in helper T cells (CD4+CD25+) of BXD strains. Data were generated by Prof. Dr. Klaus Schughart and colleagues at the Helmholtz Centre for Infection Research (HZI). Samples were processed using a total of 35 Affymetrix MOE 430 2.0 short oligomer microarrays, of which 33 passed stringent quality control and error checking.
+
+This is a private test data set. Please contact Dr. Klaus Schughart for early access.
+
diff --git a/general/datasets/Rti_rcmrc_bxdfecmet0814/acknowledgment.rtf b/general/datasets/Rti_rcmrc_bxdfecmet0814/acknowledgment.rtf
new file mode 100644
index 0000000..57f0c02
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmet0814/acknowledgment.rtf
@@ -0,0 +1,7 @@
+This work done in collaboration with RTI under a special pilot project grant from the RCMRC Center.
+
+1. Dr. Susan Sumner. PI of grant
+
+2. Dr. Robert Clarke. Lead investigator on this project
+
+3. Surja Dhungana
diff --git a/general/datasets/Rti_rcmrc_bxdfecmet0814/cases.rtf b/general/datasets/Rti_rcmrc_bxdfecmet0814/cases.rtf
new file mode 100644
index 0000000..f06f259
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmet0814/cases.rtf
@@ -0,0 +1,3 @@
+All animals are females sacrificed as part of an NIA grant to RW Williams to study effects of diet on aging (longevity) in the BXD strains. A subset of females were sacrificed at specific ages for tissue harvesting and fecal pelltets from these animals were removed from the large intestine by K. Mozhui and snap frozen in liquid nitrogen prior to shipping to RTI.
+
+Three large data sets in GeneNetwork with a common set of 4091 metabolite entries per data set (high fat, chow diet, and combined) and for as many as 18 strains.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmet0814/citation.rtf b/general/datasets/Rti_rcmrc_bxdfecmet0814/citation.rtf
new file mode 100644
index 0000000..e85e0ae
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmet0814/citation.rtf
@@ -0,0 +1 @@
+None as of Nov 2015
diff --git a/general/datasets/Rti_rcmrc_bxdfecmet0814/contributors.rtf b/general/datasets/Rti_rcmrc_bxdfecmet0814/contributors.rtf
new file mode 100644
index 0000000..09093bb
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmet0814/contributors.rtf
@@ -0,0 +1,9 @@
+1. Susan Sumner. PI of grant
+
+2. Robert Clarke. Lead investigator on this project
+
+3. Robert W. Williams. Lead geneticist and data entry
+
+4. Khyobeni Mozhui: Fecal tissue collection from aging colony samples
+
+5. Lu Lu: worked on experimental design, organized tissue acquistion, and prepared summary Excel spreadsheets of animals to be used.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmet0814/experiment-design.rtf b/general/datasets/Rti_rcmrc_bxdfecmet0814/experiment-design.rtf
new file mode 100644
index 0000000..4ee0a7b
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmet0814/experiment-design.rtf
@@ -0,0 +1,17 @@
+Sample Preparation Summary
+
+
+ - Feces were extracted in 95:5 water:methanol
+ - Extracts were prepared for UPLC-QTOF-MS analysis
+
+
+Instruments for LC-MS Analysis
+Waters SYNAPT G2 QTOF with Acquity UPLC (Waters Corporation, MA)
+MS data collected over 50-1000 m/z was collected in the positive and negative ion modes.
+
+UPLC-MS Solutions(Reversed Phase)
+Mobile Phase A (Reversed-Phase)—Water with 0.1% Formic Acid
+Mobile Phase B (Reversed-Phase)—Methanol with 0.1% Formic Acid
+Column: Waters Acquity BEH HSS T3, 2.1 x 100 mm at 50 °C
+
+
diff --git a/general/datasets/Rti_rcmrc_bxdfecmet0814/notes.rtf b/general/datasets/Rti_rcmrc_bxdfecmet0814/notes.rtf
new file mode 100644
index 0000000..8da96fa
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmet0814/notes.rtf
@@ -0,0 +1,5 @@
+For symbols of metabolites if the differences were greater than .0003 proportional m/z units (m/z difference divided by m/z value) then the symbol was labeled "circa" after the atomic composition.
+
+For description of metabolites if the proportional difference of the m/z ratio between Evan's EPFL Polar metabolite assignments and RTI assignments was very low (<.0001 proportional m/z units) then the symbol and description was taken directly from Evan's metabolite file, but if differences were between 0.0001 and about .0003 proportional m/z units then the descriptions were labeled "Putative" . If the differences were greater than .0003 units, then the descriptions were labeled "Provisional". For example, "Provisional assignment. Vanilpyruvic acid is a catecholamine metabolite and precursor to vanilactic acid. Accumulation in urine is indicative of Aromatic L-aminoacid decarboxylase deficiency (PMID 16288991)."
+
+ by Rob Williams and Arthur Centeno, Aug 25, 2014
diff --git a/general/datasets/Rti_rcmrc_bxdfecmet0814/platform.rtf b/general/datasets/Rti_rcmrc_bxdfecmet0814/platform.rtf
new file mode 100644
index 0000000..072286a
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmet0814/platform.rtf
@@ -0,0 +1 @@
+This is LC-MS data. Analysis exploited a Chenomx library at RTI with many updated metabolite identifications from the standard Chenomx library. Note that a single m/z ratio can correspond to multiple metabolites.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmet0814/summary.rtf b/general/datasets/Rti_rcmrc_bxdfecmet0814/summary.rtf
new file mode 100644
index 0000000..10218c7
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmet0814/summary.rtf
@@ -0,0 +1,11 @@
+The goal of this project is to study expression of a large set of defined and undefined metabolites in fecal samples from a genetically diverse set of BXD mouse strains (females) raised either on a high fat diet or low fat diet. Samples were taken from animals at sacrifices directly from the large intestine.
+
+Aim: Effect of genetics and diet on fecal metabolomics
+
+Use UPLC-MS Broad Spectrum Metabolomics to study:
+
+
+
+To capture the most signal, all samples were analyzed under positive and negative ion mode using a reversed-phase separation.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmet0814/tissue.rtf b/general/datasets/Rti_rcmrc_bxdfecmet0814/tissue.rtf
new file mode 100644
index 0000000..3a26107
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmet0814/tissue.rtf
@@ -0,0 +1 @@
+Fresh fecal pellets taken directly at dissection from the lower GI tract by Dr. Khyobeni Mozhui.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethf0814/acknowledgment.rtf b/general/datasets/Rti_rcmrc_bxdfecmethf0814/acknowledgment.rtf
new file mode 100644
index 0000000..57f0c02
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethf0814/acknowledgment.rtf
@@ -0,0 +1,7 @@
+This work done in collaboration with RTI under a special pilot project grant from the RCMRC Center.
+
+1. Dr. Susan Sumner. PI of grant
+
+2. Dr. Robert Clarke. Lead investigator on this project
+
+3. Surja Dhungana
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethf0814/cases.rtf b/general/datasets/Rti_rcmrc_bxdfecmethf0814/cases.rtf
new file mode 100644
index 0000000..f06f259
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethf0814/cases.rtf
@@ -0,0 +1,3 @@
+All animals are females sacrificed as part of an NIA grant to RW Williams to study effects of diet on aging (longevity) in the BXD strains. A subset of females were sacrificed at specific ages for tissue harvesting and fecal pelltets from these animals were removed from the large intestine by K. Mozhui and snap frozen in liquid nitrogen prior to shipping to RTI.
+
+Three large data sets in GeneNetwork with a common set of 4091 metabolite entries per data set (high fat, chow diet, and combined) and for as many as 18 strains.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethf0814/citation.rtf b/general/datasets/Rti_rcmrc_bxdfecmethf0814/citation.rtf
new file mode 100644
index 0000000..e85e0ae
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethf0814/citation.rtf
@@ -0,0 +1 @@
+None as of Nov 2015
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethf0814/contributors.rtf b/general/datasets/Rti_rcmrc_bxdfecmethf0814/contributors.rtf
new file mode 100644
index 0000000..09093bb
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethf0814/contributors.rtf
@@ -0,0 +1,9 @@
+1. Susan Sumner. PI of grant
+
+2. Robert Clarke. Lead investigator on this project
+
+3. Robert W. Williams. Lead geneticist and data entry
+
+4. Khyobeni Mozhui: Fecal tissue collection from aging colony samples
+
+5. Lu Lu: worked on experimental design, organized tissue acquistion, and prepared summary Excel spreadsheets of animals to be used.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethf0814/experiment-design.rtf b/general/datasets/Rti_rcmrc_bxdfecmethf0814/experiment-design.rtf
new file mode 100644
index 0000000..4ee0a7b
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethf0814/experiment-design.rtf
@@ -0,0 +1,17 @@
+Sample Preparation Summary
+
+
+ - Feces were extracted in 95:5 water:methanol
+ - Extracts were prepared for UPLC-QTOF-MS analysis
+
+
+Instruments for LC-MS Analysis
+Waters SYNAPT G2 QTOF with Acquity UPLC (Waters Corporation, MA)
+MS data collected over 50-1000 m/z was collected in the positive and negative ion modes.
+
+UPLC-MS Solutions(Reversed Phase)
+Mobile Phase A (Reversed-Phase)—Water with 0.1% Formic Acid
+Mobile Phase B (Reversed-Phase)—Methanol with 0.1% Formic Acid
+Column: Waters Acquity BEH HSS T3, 2.1 x 100 mm at 50 °C
+
+
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethf0814/notes.rtf b/general/datasets/Rti_rcmrc_bxdfecmethf0814/notes.rtf
new file mode 100644
index 0000000..8da96fa
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethf0814/notes.rtf
@@ -0,0 +1,5 @@
+For symbols of metabolites if the differences were greater than .0003 proportional m/z units (m/z difference divided by m/z value) then the symbol was labeled "circa" after the atomic composition.
+
+For description of metabolites if the proportional difference of the m/z ratio between Evan's EPFL Polar metabolite assignments and RTI assignments was very low (<.0001 proportional m/z units) then the symbol and description was taken directly from Evan's metabolite file, but if differences were between 0.0001 and about .0003 proportional m/z units then the descriptions were labeled "Putative" . If the differences were greater than .0003 units, then the descriptions were labeled "Provisional". For example, "Provisional assignment. Vanilpyruvic acid is a catecholamine metabolite and precursor to vanilactic acid. Accumulation in urine is indicative of Aromatic L-aminoacid decarboxylase deficiency (PMID 16288991)."
+
+ by Rob Williams and Arthur Centeno, Aug 25, 2014
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethf0814/platform.rtf b/general/datasets/Rti_rcmrc_bxdfecmethf0814/platform.rtf
new file mode 100644
index 0000000..072286a
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethf0814/platform.rtf
@@ -0,0 +1 @@
+This is LC-MS data. Analysis exploited a Chenomx library at RTI with many updated metabolite identifications from the standard Chenomx library. Note that a single m/z ratio can correspond to multiple metabolites.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethf0814/summary.rtf b/general/datasets/Rti_rcmrc_bxdfecmethf0814/summary.rtf
new file mode 100644
index 0000000..10218c7
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethf0814/summary.rtf
@@ -0,0 +1,11 @@
+The goal of this project is to study expression of a large set of defined and undefined metabolites in fecal samples from a genetically diverse set of BXD mouse strains (females) raised either on a high fat diet or low fat diet. Samples were taken from animals at sacrifices directly from the large intestine.
+
+Aim: Effect of genetics and diet on fecal metabolomics
+
+Use UPLC-MS Broad Spectrum Metabolomics to study:
+
+
+
+To capture the most signal, all samples were analyzed under positive and negative ion mode using a reversed-phase separation.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethf0814/tissue.rtf b/general/datasets/Rti_rcmrc_bxdfecmethf0814/tissue.rtf
new file mode 100644
index 0000000..3a26107
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethf0814/tissue.rtf
@@ -0,0 +1 @@
+Fresh fecal pellets taken directly at dissection from the lower GI tract by Dr. Khyobeni Mozhui.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethflog0814/acknowledgment.rtf b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/acknowledgment.rtf
new file mode 100644
index 0000000..57f0c02
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/acknowledgment.rtf
@@ -0,0 +1,7 @@
+This work done in collaboration with RTI under a special pilot project grant from the RCMRC Center.
+
+1. Dr. Susan Sumner. PI of grant
+
+2. Dr. Robert Clarke. Lead investigator on this project
+
+3. Surja Dhungana
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethflog0814/cases.rtf b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/cases.rtf
new file mode 100644
index 0000000..f06f259
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/cases.rtf
@@ -0,0 +1,3 @@
+All animals are females sacrificed as part of an NIA grant to RW Williams to study effects of diet on aging (longevity) in the BXD strains. A subset of females were sacrificed at specific ages for tissue harvesting and fecal pelltets from these animals were removed from the large intestine by K. Mozhui and snap frozen in liquid nitrogen prior to shipping to RTI.
+
+Three large data sets in GeneNetwork with a common set of 4091 metabolite entries per data set (high fat, chow diet, and combined) and for as many as 18 strains.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethflog0814/citation.rtf b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/citation.rtf
new file mode 100644
index 0000000..e85e0ae
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/citation.rtf
@@ -0,0 +1 @@
+None as of Nov 2015
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethflog0814/contributors.rtf b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/contributors.rtf
new file mode 100644
index 0000000..09093bb
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/contributors.rtf
@@ -0,0 +1,9 @@
+1. Susan Sumner. PI of grant
+
+2. Robert Clarke. Lead investigator on this project
+
+3. Robert W. Williams. Lead geneticist and data entry
+
+4. Khyobeni Mozhui: Fecal tissue collection from aging colony samples
+
+5. Lu Lu: worked on experimental design, organized tissue acquistion, and prepared summary Excel spreadsheets of animals to be used.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethflog0814/experiment-design.rtf b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/experiment-design.rtf
new file mode 100644
index 0000000..4ee0a7b
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/experiment-design.rtf
@@ -0,0 +1,17 @@
+Sample Preparation Summary
+
+
+ - Feces were extracted in 95:5 water:methanol
+ - Extracts were prepared for UPLC-QTOF-MS analysis
+
+
+Instruments for LC-MS Analysis
+Waters SYNAPT G2 QTOF with Acquity UPLC (Waters Corporation, MA)
+MS data collected over 50-1000 m/z was collected in the positive and negative ion modes.
+
+UPLC-MS Solutions(Reversed Phase)
+Mobile Phase A (Reversed-Phase)—Water with 0.1% Formic Acid
+Mobile Phase B (Reversed-Phase)—Methanol with 0.1% Formic Acid
+Column: Waters Acquity BEH HSS T3, 2.1 x 100 mm at 50 °C
+
+
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethflog0814/notes.rtf b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/notes.rtf
new file mode 100644
index 0000000..8da96fa
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/notes.rtf
@@ -0,0 +1,5 @@
+For symbols of metabolites if the differences were greater than .0003 proportional m/z units (m/z difference divided by m/z value) then the symbol was labeled "circa" after the atomic composition.
+
+For description of metabolites if the proportional difference of the m/z ratio between Evan's EPFL Polar metabolite assignments and RTI assignments was very low (<.0001 proportional m/z units) then the symbol and description was taken directly from Evan's metabolite file, but if differences were between 0.0001 and about .0003 proportional m/z units then the descriptions were labeled "Putative" . If the differences were greater than .0003 units, then the descriptions were labeled "Provisional". For example, "Provisional assignment. Vanilpyruvic acid is a catecholamine metabolite and precursor to vanilactic acid. Accumulation in urine is indicative of Aromatic L-aminoacid decarboxylase deficiency (PMID 16288991)."
+
+ by Rob Williams and Arthur Centeno, Aug 25, 2014
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethflog0814/platform.rtf b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/platform.rtf
new file mode 100644
index 0000000..072286a
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/platform.rtf
@@ -0,0 +1 @@
+This is LC-MS data. Analysis exploited a Chenomx library at RTI with many updated metabolite identifications from the standard Chenomx library. Note that a single m/z ratio can correspond to multiple metabolites.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethflog0814/summary.rtf b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/summary.rtf
new file mode 100644
index 0000000..10218c7
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/summary.rtf
@@ -0,0 +1,11 @@
+The goal of this project is to study expression of a large set of defined and undefined metabolites in fecal samples from a genetically diverse set of BXD mouse strains (females) raised either on a high fat diet or low fat diet. Samples were taken from animals at sacrifices directly from the large intestine.
+
+Aim: Effect of genetics and diet on fecal metabolomics
+
+Use UPLC-MS Broad Spectrum Metabolomics to study:
+
+
+
+To capture the most signal, all samples were analyzed under positive and negative ion mode using a reversed-phase separation.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmethflog0814/tissue.rtf b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/tissue.rtf
new file mode 100644
index 0000000..3a26107
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmethflog0814/tissue.rtf
@@ -0,0 +1 @@
+Fresh fecal pellets taken directly at dissection from the lower GI tract by Dr. Khyobeni Mozhui.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlf0814/acknowledgment.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/acknowledgment.rtf
new file mode 100644
index 0000000..57f0c02
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/acknowledgment.rtf
@@ -0,0 +1,7 @@
+This work done in collaboration with RTI under a special pilot project grant from the RCMRC Center.
+
+1. Dr. Susan Sumner. PI of grant
+
+2. Dr. Robert Clarke. Lead investigator on this project
+
+3. Surja Dhungana
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlf0814/cases.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/cases.rtf
new file mode 100644
index 0000000..f06f259
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/cases.rtf
@@ -0,0 +1,3 @@
+All animals are females sacrificed as part of an NIA grant to RW Williams to study effects of diet on aging (longevity) in the BXD strains. A subset of females were sacrificed at specific ages for tissue harvesting and fecal pelltets from these animals were removed from the large intestine by K. Mozhui and snap frozen in liquid nitrogen prior to shipping to RTI.
+
+Three large data sets in GeneNetwork with a common set of 4091 metabolite entries per data set (high fat, chow diet, and combined) and for as many as 18 strains.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlf0814/citation.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/citation.rtf
new file mode 100644
index 0000000..e85e0ae
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/citation.rtf
@@ -0,0 +1 @@
+None as of Nov 2015
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlf0814/contributors.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/contributors.rtf
new file mode 100644
index 0000000..09093bb
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/contributors.rtf
@@ -0,0 +1,9 @@
+1. Susan Sumner. PI of grant
+
+2. Robert Clarke. Lead investigator on this project
+
+3. Robert W. Williams. Lead geneticist and data entry
+
+4. Khyobeni Mozhui: Fecal tissue collection from aging colony samples
+
+5. Lu Lu: worked on experimental design, organized tissue acquistion, and prepared summary Excel spreadsheets of animals to be used.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlf0814/experiment-design.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/experiment-design.rtf
new file mode 100644
index 0000000..4ee0a7b
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/experiment-design.rtf
@@ -0,0 +1,17 @@
+Sample Preparation Summary
+
+
+ - Feces were extracted in 95:5 water:methanol
+ - Extracts were prepared for UPLC-QTOF-MS analysis
+
+
+Instruments for LC-MS Analysis
+Waters SYNAPT G2 QTOF with Acquity UPLC (Waters Corporation, MA)
+MS data collected over 50-1000 m/z was collected in the positive and negative ion modes.
+
+UPLC-MS Solutions(Reversed Phase)
+Mobile Phase A (Reversed-Phase)—Water with 0.1% Formic Acid
+Mobile Phase B (Reversed-Phase)—Methanol with 0.1% Formic Acid
+Column: Waters Acquity BEH HSS T3, 2.1 x 100 mm at 50 °C
+
+
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlf0814/notes.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/notes.rtf
new file mode 100644
index 0000000..8da96fa
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/notes.rtf
@@ -0,0 +1,5 @@
+For symbols of metabolites if the differences were greater than .0003 proportional m/z units (m/z difference divided by m/z value) then the symbol was labeled "circa" after the atomic composition.
+
+For description of metabolites if the proportional difference of the m/z ratio between Evan's EPFL Polar metabolite assignments and RTI assignments was very low (<.0001 proportional m/z units) then the symbol and description was taken directly from Evan's metabolite file, but if differences were between 0.0001 and about .0003 proportional m/z units then the descriptions were labeled "Putative" . If the differences were greater than .0003 units, then the descriptions were labeled "Provisional". For example, "Provisional assignment. Vanilpyruvic acid is a catecholamine metabolite and precursor to vanilactic acid. Accumulation in urine is indicative of Aromatic L-aminoacid decarboxylase deficiency (PMID 16288991)."
+
+ by Rob Williams and Arthur Centeno, Aug 25, 2014
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlf0814/platform.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/platform.rtf
new file mode 100644
index 0000000..072286a
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/platform.rtf
@@ -0,0 +1 @@
+This is LC-MS data. Analysis exploited a Chenomx library at RTI with many updated metabolite identifications from the standard Chenomx library. Note that a single m/z ratio can correspond to multiple metabolites.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlf0814/summary.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/summary.rtf
new file mode 100644
index 0000000..10218c7
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/summary.rtf
@@ -0,0 +1,11 @@
+The goal of this project is to study expression of a large set of defined and undefined metabolites in fecal samples from a genetically diverse set of BXD mouse strains (females) raised either on a high fat diet or low fat diet. Samples were taken from animals at sacrifices directly from the large intestine.
+
+Aim: Effect of genetics and diet on fecal metabolomics
+
+Use UPLC-MS Broad Spectrum Metabolomics to study:
+
+
+
+To capture the most signal, all samples were analyzed under positive and negative ion mode using a reversed-phase separation.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlf0814/tissue.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/tissue.rtf
new file mode 100644
index 0000000..3a26107
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlf0814/tissue.rtf
@@ -0,0 +1 @@
+Fresh fecal pellets taken directly at dissection from the lower GI tract by Dr. Khyobeni Mozhui.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/acknowledgment.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/acknowledgment.rtf
new file mode 100644
index 0000000..57f0c02
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/acknowledgment.rtf
@@ -0,0 +1,7 @@
+This work done in collaboration with RTI under a special pilot project grant from the RCMRC Center.
+
+1. Dr. Susan Sumner. PI of grant
+
+2. Dr. Robert Clarke. Lead investigator on this project
+
+3. Surja Dhungana
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/cases.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/cases.rtf
new file mode 100644
index 0000000..f06f259
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/cases.rtf
@@ -0,0 +1,3 @@
+All animals are females sacrificed as part of an NIA grant to RW Williams to study effects of diet on aging (longevity) in the BXD strains. A subset of females were sacrificed at specific ages for tissue harvesting and fecal pelltets from these animals were removed from the large intestine by K. Mozhui and snap frozen in liquid nitrogen prior to shipping to RTI.
+
+Three large data sets in GeneNetwork with a common set of 4091 metabolite entries per data set (high fat, chow diet, and combined) and for as many as 18 strains.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/citation.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/citation.rtf
new file mode 100644
index 0000000..e85e0ae
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/citation.rtf
@@ -0,0 +1 @@
+None as of Nov 2015
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/contributors.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/contributors.rtf
new file mode 100644
index 0000000..09093bb
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/contributors.rtf
@@ -0,0 +1,9 @@
+1. Susan Sumner. PI of grant
+
+2. Robert Clarke. Lead investigator on this project
+
+3. Robert W. Williams. Lead geneticist and data entry
+
+4. Khyobeni Mozhui: Fecal tissue collection from aging colony samples
+
+5. Lu Lu: worked on experimental design, organized tissue acquistion, and prepared summary Excel spreadsheets of animals to be used.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/experiment-design.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/experiment-design.rtf
new file mode 100644
index 0000000..4ee0a7b
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/experiment-design.rtf
@@ -0,0 +1,17 @@
+Sample Preparation Summary
+
+
+ - Feces were extracted in 95:5 water:methanol
+ - Extracts were prepared for UPLC-QTOF-MS analysis
+
+
+Instruments for LC-MS Analysis
+Waters SYNAPT G2 QTOF with Acquity UPLC (Waters Corporation, MA)
+MS data collected over 50-1000 m/z was collected in the positive and negative ion modes.
+
+UPLC-MS Solutions(Reversed Phase)
+Mobile Phase A (Reversed-Phase)—Water with 0.1% Formic Acid
+Mobile Phase B (Reversed-Phase)—Methanol with 0.1% Formic Acid
+Column: Waters Acquity BEH HSS T3, 2.1 x 100 mm at 50 °C
+
+
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/notes.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/notes.rtf
new file mode 100644
index 0000000..8da96fa
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/notes.rtf
@@ -0,0 +1,5 @@
+For symbols of metabolites if the differences were greater than .0003 proportional m/z units (m/z difference divided by m/z value) then the symbol was labeled "circa" after the atomic composition.
+
+For description of metabolites if the proportional difference of the m/z ratio between Evan's EPFL Polar metabolite assignments and RTI assignments was very low (<.0001 proportional m/z units) then the symbol and description was taken directly from Evan's metabolite file, but if differences were between 0.0001 and about .0003 proportional m/z units then the descriptions were labeled "Putative" . If the differences were greater than .0003 units, then the descriptions were labeled "Provisional". For example, "Provisional assignment. Vanilpyruvic acid is a catecholamine metabolite and precursor to vanilactic acid. Accumulation in urine is indicative of Aromatic L-aminoacid decarboxylase deficiency (PMID 16288991)."
+
+ by Rob Williams and Arthur Centeno, Aug 25, 2014
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/platform.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/platform.rtf
new file mode 100644
index 0000000..072286a
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/platform.rtf
@@ -0,0 +1 @@
+This is LC-MS data. Analysis exploited a Chenomx library at RTI with many updated metabolite identifications from the standard Chenomx library. Note that a single m/z ratio can correspond to multiple metabolites.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/summary.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/summary.rtf
new file mode 100644
index 0000000..10218c7
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/summary.rtf
@@ -0,0 +1,11 @@
+The goal of this project is to study expression of a large set of defined and undefined metabolites in fecal samples from a genetically diverse set of BXD mouse strains (females) raised either on a high fat diet or low fat diet. Samples were taken from animals at sacrifices directly from the large intestine.
+
+Aim: Effect of genetics and diet on fecal metabolomics
+
+Use UPLC-MS Broad Spectrum Metabolomics to study:
+
+
+
+To capture the most signal, all samples were analyzed under positive and negative ion mode using a reversed-phase separation.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/tissue.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/tissue.rtf
new file mode 100644
index 0000000..3a26107
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlflog0814/tissue.rtf
@@ -0,0 +1 @@
+Fresh fecal pellets taken directly at dissection from the lower GI tract by Dr. Khyobeni Mozhui.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlog0814/acknowledgment.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/acknowledgment.rtf
new file mode 100644
index 0000000..57f0c02
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/acknowledgment.rtf
@@ -0,0 +1,7 @@
+This work done in collaboration with RTI under a special pilot project grant from the RCMRC Center.
+
+1. Dr. Susan Sumner. PI of grant
+
+2. Dr. Robert Clarke. Lead investigator on this project
+
+3. Surja Dhungana
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlog0814/cases.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/cases.rtf
new file mode 100644
index 0000000..f06f259
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/cases.rtf
@@ -0,0 +1,3 @@
+All animals are females sacrificed as part of an NIA grant to RW Williams to study effects of diet on aging (longevity) in the BXD strains. A subset of females were sacrificed at specific ages for tissue harvesting and fecal pelltets from these animals were removed from the large intestine by K. Mozhui and snap frozen in liquid nitrogen prior to shipping to RTI.
+
+Three large data sets in GeneNetwork with a common set of 4091 metabolite entries per data set (high fat, chow diet, and combined) and for as many as 18 strains.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlog0814/citation.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/citation.rtf
new file mode 100644
index 0000000..e85e0ae
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/citation.rtf
@@ -0,0 +1 @@
+None as of Nov 2015
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlog0814/contributors.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/contributors.rtf
new file mode 100644
index 0000000..09093bb
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/contributors.rtf
@@ -0,0 +1,9 @@
+1. Susan Sumner. PI of grant
+
+2. Robert Clarke. Lead investigator on this project
+
+3. Robert W. Williams. Lead geneticist and data entry
+
+4. Khyobeni Mozhui: Fecal tissue collection from aging colony samples
+
+5. Lu Lu: worked on experimental design, organized tissue acquistion, and prepared summary Excel spreadsheets of animals to be used.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlog0814/experiment-design.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/experiment-design.rtf
new file mode 100644
index 0000000..4ee0a7b
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/experiment-design.rtf
@@ -0,0 +1,17 @@
+Sample Preparation Summary
+
+
+ - Feces were extracted in 95:5 water:methanol
+ - Extracts were prepared for UPLC-QTOF-MS analysis
+
+
+Instruments for LC-MS Analysis
+Waters SYNAPT G2 QTOF with Acquity UPLC (Waters Corporation, MA)
+MS data collected over 50-1000 m/z was collected in the positive and negative ion modes.
+
+UPLC-MS Solutions(Reversed Phase)
+Mobile Phase A (Reversed-Phase)—Water with 0.1% Formic Acid
+Mobile Phase B (Reversed-Phase)—Methanol with 0.1% Formic Acid
+Column: Waters Acquity BEH HSS T3, 2.1 x 100 mm at 50 °C
+
+
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlog0814/notes.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/notes.rtf
new file mode 100644
index 0000000..8da96fa
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/notes.rtf
@@ -0,0 +1,5 @@
+For symbols of metabolites if the differences were greater than .0003 proportional m/z units (m/z difference divided by m/z value) then the symbol was labeled "circa" after the atomic composition.
+
+For description of metabolites if the proportional difference of the m/z ratio between Evan's EPFL Polar metabolite assignments and RTI assignments was very low (<.0001 proportional m/z units) then the symbol and description was taken directly from Evan's metabolite file, but if differences were between 0.0001 and about .0003 proportional m/z units then the descriptions were labeled "Putative" . If the differences were greater than .0003 units, then the descriptions were labeled "Provisional". For example, "Provisional assignment. Vanilpyruvic acid is a catecholamine metabolite and precursor to vanilactic acid. Accumulation in urine is indicative of Aromatic L-aminoacid decarboxylase deficiency (PMID 16288991)."
+
+ by Rob Williams and Arthur Centeno, Aug 25, 2014
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlog0814/platform.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/platform.rtf
new file mode 100644
index 0000000..072286a
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/platform.rtf
@@ -0,0 +1 @@
+This is LC-MS data. Analysis exploited a Chenomx library at RTI with many updated metabolite identifications from the standard Chenomx library. Note that a single m/z ratio can correspond to multiple metabolites.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlog0814/summary.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/summary.rtf
new file mode 100644
index 0000000..10218c7
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/summary.rtf
@@ -0,0 +1,11 @@
+The goal of this project is to study expression of a large set of defined and undefined metabolites in fecal samples from a genetically diverse set of BXD mouse strains (females) raised either on a high fat diet or low fat diet. Samples were taken from animals at sacrifices directly from the large intestine.
+
+Aim: Effect of genetics and diet on fecal metabolomics
+
+Use UPLC-MS Broad Spectrum Metabolomics to study:
+
+
+
+To capture the most signal, all samples were analyzed under positive and negative ion mode using a reversed-phase separation.
diff --git a/general/datasets/Rti_rcmrc_bxdfecmetlog0814/tissue.rtf b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/tissue.rtf
new file mode 100644
index 0000000..3a26107
--- /dev/null
+++ b/general/datasets/Rti_rcmrc_bxdfecmetlog0814/tissue.rtf
@@ -0,0 +1 @@
+Fresh fecal pellets taken directly at dissection from the lower GI tract by Dr. Khyobeni Mozhui.
diff --git a/general/datasets/STJ_PLN_0912/summary.rtf b/general/datasets/STJ_PLN_0912/summary.rtf
deleted file mode 100644
index fd9009a..0000000
--- a/general/datasets/STJ_PLN_0912/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 154, Name: St Jude BXD Popliteal Lymph Node Affy HT MG-430 PM (Sep12)
\ No newline at end of file
diff --git a/general/datasets/SUH_Liv_RMAEx_0611/processing.rtf b/general/datasets/SUH_Liv_RMAEx_0611/processing.rtf
deleted file mode 100644
index ca7e79b..0000000
--- a/general/datasets/SUH_Liv_RMAEx_0611/processing.rtf
+++ /dev/null
@@ -1,660 +0,0 @@
-QC Results: This data set consists of expression data for 33 strains. A total of 166 probe sets are associated with LOD scores above 10 and the highest linkage score of 22 for Rpl3 (probe set 10430669). Strain distribution patterns of eQTLs with a Mendelian expression pattern match those of their closest markers perfectly, verifying that there are no errors of strain assignment in this data set.
-
-Analysis of XIST probe set 1060617 confirms that most strains are purely female. However, only males were available for BXD1 and BXD6. BXD28 and BXD33 data are based on the average of two female samples and one male sample. All other strains are purely female.
-
-Data were analyzed by Rabea Hall and Dr. Frank Lammert at the Universitätsklinikum des Saarlandes in Homburg, Germany.
-
-Contacts: rabea.hall at uks.eu, Rabea.Hall at uniklinikum-saarland.de, and frank.lammert at uks.eu
-
-Table updated 7-19-2011
-
-
-
-
-
-
-
-
-
- | Index |
- Sample ID |
- Strain ID |
- Treatment |
-
-
- | 1 |
- 504 |
- B6D2F1 |
- CCl4 |
-
-
- | 2 |
- 506 |
- B6D2F1 |
- CCl4 |
-
-
- | 3 |
- 508 |
- B6D2F1 |
- CCl4 |
-
-
- | 4 |
- 414 |
- C57BL/6J |
- CCl4 |
-
-
- | 5 |
- 488 |
- C57BL/6J |
- CCl4 |
-
-
- | 6 |
- 489 |
- C57BL/6J |
- CCl4 |
-
-
- | 7 |
- B6J1 |
- C57BL/6J |
- untreated control |
-
-
- | 8 |
- B6J2 |
- C57BL/6J |
- untreated control |
-
-
- | 9 |
- B6J3 |
- C57BL/6J |
- untreated control |
-
-
- | 10 |
- 449 |
- DBA/2J |
- CCl4 |
-
-
- | 11 |
- 450 |
- DBA/2J |
- CCl4 |
-
-
- | 12 |
- 451 |
- DBA/2J |
- CCl4 |
-
-
- | 13 |
- 219.1 |
- DBA/2J |
- untreated control |
-
-
- | 14 |
- 219.2 |
- DBA/2J |
- untreated control |
-
-
- | 15 |
- 219.3 |
- DBA/2J |
- untreated control |
-
-
- | 16 |
- 276 |
- BXD1 |
- CCl4 |
-
-
- | 17 |
- 278 |
- BXD1 |
- CCl4 |
-
-
- | 18 |
- 279 |
- BXD1 |
- CCl4 |
-
-
- | 19 |
- 353 |
- BXD2 |
- CCl4 |
-
-
- | 20 |
- 357 |
- BXD2 |
- CCl4 |
-
-
- | 21 |
- 358 |
- BXD2 |
- CCl4 |
-
-
- | 22 |
- 272 |
- BXD6 |
- CCl4 |
-
-
- | 23 |
- 273 |
- BXD6 |
- CCl4 |
-
-
- | 24 |
- 274 |
- BXD6 |
- CCl4 |
-
-
- | 25 |
- 405 |
- BXD11 |
- CCl4 |
-
-
- | 26 |
- 406 |
- BXD11 |
- CCl4 |
-
-
- | 27 |
- 408 |
- BXD11 |
- CCl4 |
-
-
- | 28 |
- 239 |
- BXD12 |
- CCl4 |
-
-
- | 29 |
- 240 |
- BXD12 |
- CCl4 |
-
-
- | 30 |
- 241 |
- BXD12 |
- CCl4 |
-
-
- | 31 |
- 553 |
- BXD13 |
- CCl4 |
-
-
- | 32 |
- 554 |
- BXD13 |
- CCl4 |
-
-
- | 33 |
- 555 |
- BXD13 |
- CCl4 |
-
-
- | 34 |
- 249 |
- BXD14 |
- CCl4 |
-
-
- | 35 |
- 250 |
- BXD14 |
- CCl4 |
-
-
- | 36 |
- 288 |
- BXD14 |
- CCl4 |
-
-
- | 37 |
- 191 |
- BXD19 |
- CCl4 |
-
-
- | 38 |
- 644 |
- BXD19 |
- CCl4 |
-
-
- | 39 |
- 645 |
- BXD19 |
- CCl4 |
-
-
- | 40 |
- 442 |
- BXD24a |
- CCl4 |
-
-
- | 41 |
- 443 |
- BXD24a |
- CCl4 |
-
-
- | 42 |
- 444 |
- BXD24a |
- CCl4 |
-
-
- | 43 |
- 216 |
- BXD27 |
- CCl4 |
-
-
- | 44 |
- 218 |
- BXD27 |
- CCl4 |
-
-
- | 45 |
- 290 |
- BXD27 |
- CCl4 |
-
-
- | 46 |
- 28 |
- BXD28 |
- CCl4 |
-
-
- | 47 |
- 71 |
- BXD28 |
- CCl4 |
-
-
- | 48 |
- 129 |
- BXD28 |
- CCl4 |
-
-
- | 49 |
- 219 |
- BXD31 |
- CCl4 |
-
-
- | 50 |
- 220 |
- BXD31 |
- CCl4 |
-
-
- | 51 |
- 231 |
- BXD31 |
- CCl4 |
-
-
- | 52 |
- 549 |
- BXD32 |
- CCl4 |
-
-
- | 53 |
- 550 |
- BXD32 |
- CCl4 |
-
-
- | 54 |
- 551 |
- BXD32 |
- CCl4 |
-
-
- | 55 |
- 139 |
- BXD33 |
- CCl4 |
-
-
- | 56 |
- 140 |
- BXD33 |
- CCl4 |
-
-
- | 57 |
- 559 |
- BXD33 |
- CCl4 |
-
-
- | 58 |
- 132 |
- BXD34 |
- CCl4 |
-
-
- | 59 |
- 146 |
- BXD34 |
- CCl4 |
-
-
- | 60 |
- 147 |
- BXD34 |
- CCl4 |
-
-
- | 61 |
- 293 |
- BXD39 |
- CCl4 |
-
-
- | 62 |
- 597 |
- BXD39 |
- CCl4 |
-
-
- | 63 |
- 599 |
- BXD39 |
- CCl4 |
-
-
- | 64 |
- 154 |
- BXD40 |
- CCl4 |
-
-
- | 65 |
- 570 |
- BXD40 |
- CCl4 |
-
-
- | 66 |
- 572 |
- BXD40 |
- CCl4 |
-
-
- | 67 |
- 361 |
- BXD42 |
- CCl4 |
-
-
- | 68 |
- 362 |
- BXD42 |
- CCl4 |
-
-
- | 69 |
- 373 |
- BXD42 |
- CCl4 |
-
-
- | 70 |
- 428 |
- BXD43 |
- CCl4 |
-
-
- | 71 |
- 429 |
- BXD43 |
- CCl4 |
-
-
- | 72 |
- 556 |
- BXD43 |
- CCl4 |
-
-
- | 73 |
- 472 |
- BXD51 |
- CCl4 |
-
-
- | 74 |
- 473 |
- BXD51 |
- CCl4 |
-
-
- | 75 |
- 474 |
- BXD51 |
- CCl4 |
-
-
- | 76 |
- 533 |
- BXD55 |
- CCl4 |
-
-
- | 77 |
- 534 |
- BXD55 |
- CCl4 |
-
-
- | 78 |
- 535 |
- BXD55 |
- CCl4 |
-
-
- | 79 |
- 519 |
- BXD62 |
- CCl4 |
-
-
- | 80 |
- 520 |
- BXD62 |
- CCl4 |
-
-
- | 81 |
- 521 |
- BXD62 |
- CCl4 |
-
-
- | 82 |
- 463 |
- BXD65 |
- CCl4 |
-
-
- | 83 |
- 464 |
- BXD65 |
- CCl4 |
-
-
- | 84 |
- 465 |
- BXD65 |
- CCl4 |
-
-
- | 85 |
- 327 |
- BXD69 |
- CCl4 |
-
-
- | 86 |
- 346 |
- BXD69 |
- CCl4 |
-
-
- | 87 |
- 347 |
- BXD69 |
- CCl4 |
-
-
- | 88 |
- 614 |
- BXD73 |
- CCl4 |
-
-
- | 89 |
- 616 |
- BXD73 |
- CCl4 |
-
-
- | 90 |
- 619 |
- BXD73 |
- CCl4 |
-
-
- | 91 |
- 395 |
- BXD75 |
- CCl4 |
-
-
- | 92 |
- 482 |
- BXD75 |
- CCl4 |
-
-
- | 93 |
- 483 |
- BXD75 |
- CCl4 |
-
-
- | 94 |
- 317 |
- BXD87 |
- CCl4 |
-
-
- | 95 |
- 319 |
- BXD87 |
- CCl4 |
-
-
- | 96 |
- 322 |
- BXD87 |
- CCl4 |
-
-
- | 97 |
- 374 |
- BXD90 |
- CCl4 |
-
-
- | 98 |
- 388 |
- BXD90 |
- CCl4 |
-
-
- | 99 |
- 389 |
- BXD90 |
- CCl4 |
-
-
- | 100 |
- 402 |
- BXD96 |
- CCl4 |
-
-
- | 101 |
- 403 |
- BXD96 |
- CCl4 |
-
-
- | 102 |
- 404 |
- BXD96 |
- CCl4 |
-
-
- | 103 |
- 584 |
- BXD98 |
- CCl4 |
-
-
- | 104 |
- 585 |
- BXD98 |
- CCl4 |
-
-
- | 105 |
- 607 |
- BXD98 |
- CCl4 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/SUH_Liv_RMAEx_0611/summary.rtf b/general/datasets/SUH_Liv_RMAEx_0611/summary.rtf
deleted file mode 100644
index 2684b46..0000000
--- a/general/datasets/SUH_Liv_RMAEx_0611/summary.rtf
+++ /dev/null
@@ -1,22 +0,0 @@
-Saarland University Homburg (SUH) Carbon Tetrachloride-Treated BXD Mouse Affymetrix Mouse Gene 1.0 ST Array data set
-
-This experimental liver gene expression data set (~100 Affymetrix exon-type arrays), was generated by Frank Lammert, Sonja Hillebrandt, Rabea Hall, and colleagues at the Saarland University Medical Center in Homburg, Germany. This work is part of the German Network for Systems Genetics (GeNeSys).
-
-Expression data after carbon tetrachloride treatment (CCl4, also known as Halon, Freon, carbon tet, or tetrachloromethane) were generated using RNA sample from 30 BXD strains, both parental strains (C57BL/6J, DBA/2J), and B6D2 F1 hybrids. The great majority of cases were females and were treated with carbon tetrachloride injections over a six week period. Three arrays were run for each strain using independent liver samples.
-
-PURPOSE: The overall goal of the project is to understand the etiology of liver fibrogenesis using carbon tetracholoride as a toxin and inducer of liver disease. Liver fibrogenesis, or scarring of the liver, is the common end-stage of chronic liver diseases, in particular after chronic viral infections. In Germany along complications associated with liver fibrosis cause approximately 10,000 deaths per year. In the past decade key molecular pathomechanisms of hepatic fibrogenesis due to chronic viral infections have been identified. Activated hepatic stellate cells (HSCs) drive the process of de novo deposition of abnormal extracellular matrix, which is modulated by complex interactions between cytokines, receptors, and matrix components.
-
-Several studies have demonstrated that the course and progression of the fibrogenic response to chronic liver injury is highly variability among individuals. This marked variabilityhas been attributed to etiology, age, gender, and environmental factors. In humans these genetic disease fibrosis predisposition factors have not yet to be studied systematically.
-
-Our group recently identified a gene variant that contributes to liver fibrogenesis by using QTL mapping in an experimental crosses between fibrosis-susceptible and resistant strains of mice (Hillebrandt et al., 2005). We demonstrated that sequence differences in the HC gene that encodes complement factor C5 (also known as hemolytic complement), are responsible for this strain difference. Common haplotype-tagging polymorphisms of the human HC gene were shown to be associated with advanced fibrosis in chronic hepatitis C virus infection. Thus, the mouse analysis led to the identification of an unknown gene underlying human susceptibility to liver fibrosis, supporting the idea that HC has a causal role in chronic inflammatory disorders and organ fibrogenesis across species.
-
-As part of the GeNeSys program we have studied liver fibrogenesis in the BXD family of strains as a model for chronic liver injury. This expression data set is used to map complex genetic traits that modulate gene expression and determine gene networks during liver fibrogenesis in GRPs.
-
-The following assays are complete or are in progress:
-
-
- - Liver fibrosis studies: Phenotyping protocols include standard histology, morphometry, biochemical quantification of hepatic collagen contents, serum surrogate markers of fibrosis, immunohistochemistry, and expression profiling of proinflammatory and profibrogenic genes by qRT-PCR and Affymetrix microarrays (this data set).
- - Characterization of liver cells: Liver immune cell fractions will be isolated and sorted according to SOPs developed in the Lammert laboratory. In addition, in cooperation with the technology platforms of the HepatoSys Network of Excellence, we will characterize primary HSCs that play critical roles in liver fibrogenesis with respect to proinflammatory responses during chronic liver inflammation.
-
-
-PROTOCOL for carbon tetrachloride (CCl4) treatment (parental strains, F1, and BXD lines). Animals were injected with CCl4 (12 x 0.7 mg/kg ip) over a 6-week period on days 1 and 4 of each week. Intraperitoneal injections were begun between the ages of 6-8 weeks. Animals were sacrificed after 6 weeks of treatment at 12 to 14 weeks of age. Untreated control mice from only the two parental strains were also sacrificed at 12-14 weeks of age
diff --git a/general/datasets/SUH_Liv_RMAEx_0611/tissue.rtf b/general/datasets/SUH_Liv_RMAEx_0611/tissue.rtf
deleted file mode 100644
index 05a7607..0000000
--- a/general/datasets/SUH_Liv_RMAEx_0611/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Tissue: Livers were snap frozen in liquid nitrogen immediately after harvesting. RNA was extracted and submitted to the UTHSC Molecular Resource Core for expression profiling. Expression data were generated by Lorne Rose, William Taylor and colleagues. Data were entered into GeneNetwork by Arthur Centeno, June 17, 2011. Data were quality controlled by R. W. Williams.
diff --git a/general/datasets/Sa_m2_0405_m/acknowledgment.rtf b/general/datasets/Sa_m2_0405_m/acknowledgment.rtf
new file mode 100644
index 0000000..94eec11
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_m/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to Glenn Rosen from P20 MH62009 (see below for specifics). Samples and arrays were processed by the Genomics Core at Beth Israel Deaconess Medical Center by Towia Libermann and colleagues.
+
diff --git a/general/datasets/Sa_m2_0405_m/cases.rtf b/general/datasets/Sa_m2_0405_m/cases.rtf
new file mode 100644
index 0000000..491788f
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_m/cases.rtf
@@ -0,0 +1,5 @@
+
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+
+
diff --git a/general/datasets/Sa_m2_0405_m/experiment-design.rtf b/general/datasets/Sa_m2_0405_m/experiment-design.rtf
new file mode 100644
index 0000000..cb07f36
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_m/experiment-design.rtf
@@ -0,0 +1,5 @@
+RNA was extracted by Rosen and colleagues and was then processed by the BIDMC Genomics Core. Labeled cRNA was generated using the Amersham Biosciences cRNA synthesis kit protocol.
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one sample from each sex for all BXD strains. We have not yet achieved this goal. Twenty-three of 33 strains are represented by male and female samples. The remaining 8 strains are still represented by single sex samples: BXD11 (F), BXD13 (F), BXD19 (F), BXD20 (F), BXD22 (M), BXD23 (M), BXD24 (M), BXD32 (M), C57BL/6J (M), and DBA/2J (M).
+
+Batch Structure: This data set consists of arrays processed in three batches with several reruns for the first batch. All arrays were processed using a single protocol. All data have been corrected for batch effects as described below.
+
diff --git a/general/datasets/Sa_m2_0405_m/notes.rtf b/general/datasets/Sa_m2_0405_m/notes.rtf
new file mode 100644
index 0000000..0af01e6
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_m/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by GDR, RWW, and YHQ on Nov 2004. Updated by RWW Nov 17, 2004; GDR and RWW, Dec 23, 2004; RWW and GDR April 8, 2005.
+
diff --git a/general/datasets/Sa_m2_0405_m/platform.rtf b/general/datasets/Sa_m2_0405_m/platform.rtf
new file mode 100644
index 0000000..30c2f8c
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_m/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are near duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequence as the 430A and B series. However, we have found that roughy 75000 probes differ from those on A and B arrays.
+
diff --git a/general/datasets/Sa_m2_0405_m/processing.rtf b/general/datasets/Sa_m2_0405_m/processing.rtf
new file mode 100644
index 0000000..2e46796
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_m/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the batches at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels. Data quality control: A total of 62 samples passed RNA quality control.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients (62x61/2). Arrays with probe data that was not homogeneous when compared to any other arrays was flagged. If the correlation at the probe level was less than approximately 0.92 we deleted that array data set. Three arrays we lost during this process (BXD19_M_Str_Batch03, BXD23_F_Str_Batch03, and BXD24_F_Str_Batch03).
+
+Probe set level QC: The final normalized strain averages were evaluated for outliers. This involved counting the number of times that the probe set value for a particular strain was beyond two standard deviations of the mean of all strains. (We used the PDNN transform as our reference probe set data for this QC step.) Two strains, each represented by single arrays, generated greater than 5,000 outlier counts (10% of the number of probe sets). These two arrays generated a great number of outliers across the entire range of expression and since we do not yet have replicate arrays for either of these two strains we opted to delete them from the final April 2005 striatum data sets.
diff --git a/general/datasets/Sa_m2_0405_m/summary.rtf b/general/datasets/Sa_m2_0405_m/summary.rtf
new file mode 100644
index 0000000..e674c86
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_m/summary.rtf
@@ -0,0 +1 @@
+This April 2005 data freeze provides estimates of mRNA expression in the striatum (caudate nucleus of the forebrain) of 33 lines of mice including C57BL/6J, DBA/2J, and 31 BXD recombinant inbred strains. Data were generated using Affymetrix Mouse Genome 430 2.0 short oligomer microarrays at Beth Israel Deaconess Medical Center (BIDMC, Boston MA) by Glenn D. Rosen with the support of a Human Brain Project (HBP) grant. Approximately 250 brain samples (males and females) from 33 strains were used in this experiment. Samples were hybridized to a total of 59 arrays. This particular data set was processed using the Microarray Suite 5 protocol (MAS 5). To simplify comparison among different transforms, MAS5 values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Sa_m2_0405_m/tissue.rtf b/general/datasets/Sa_m2_0405_m/tissue.rtf
new file mode 100644
index 0000000..6503813
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_m/tissue.rtf
@@ -0,0 +1,440 @@
+
+Animals were obtained from The Jackson Laboratory and housed for several weeks at BIDMC until they reached ~2 months of age (range from 55 to 62 days). Mice were killed by cervical dislocation and brains were removed and placed in RNAlater for 20 to 25 minutes prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both striata were dissected using a medial approach by GD Rosen that typically yields 5 to 7 mg of tissue per side. The purity of this dissection has been validated by an analysis of acetylcholinestase activity. A pool of dissected tissue from 3 or 4 adults (approximately 25 to 30 mg of tissue) of the same strain, sex, and age was collected in one session and used to generate cRNA samples.
+
+
+The table below lists the arrays by strain, sex, sample name, and batch ID. Each array was hybridized to a pool of mRNA from 3 to 4 mice. All mice were between 55 and 62 days.
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Sample_name |
+ BatchId |
+
+
+ | 1 |
+ C57BL/6J |
+ M |
+ Chip41_Batch02_B6_M_Str |
+ Batch02 |
+
+
+ | 2 |
+ C57BL/6J |
+ M |
+ Chip11_Batch03_B6_M_Str |
+ Batch03 |
+
+
+ | 3 |
+ BXD1 |
+ F |
+ Chip03_Batch03_BXD1_F_Str |
+ Batch03 |
+
+
+ | 4 |
+ BXD1 |
+ M |
+ Chip04_Batch03_BXD1_M_Str |
+ Batch03 |
+
+
+ | 5 |
+ BXD2 |
+ F |
+ Chip20_Rerun01_BXD2_F_Str |
+ Rerun01 |
+
+
+ | 6 |
+ BXD2 |
+ M |
+ Chip05_Batch01_BXD2_M_Str |
+ Batch01 |
+
+
+ | 7 |
+ BXD5 |
+ F |
+ Chip10_Batch03_BXD5_F_Str |
+ Batch03 |
+
+
+ | 8 |
+ BXD5 |
+ M |
+ Chip12_Batch03_BXD5_M_Str |
+ Batch03 |
+
+
+ | 9 |
+ BXD6 |
+ F |
+ Chip38_Batch02_BXD6_F_Str |
+ Batch02 |
+
+
+ | 10 |
+ BXD6 |
+ M |
+ Chip39_Batch02_BXD6_M_Str |
+ Batch02 |
+
+
+ | 11 |
+ BXD8 |
+ F |
+ Chip07_Batch03_BXD8_F_Str |
+ Batch03 |
+
+
+ | 12 |
+ BXD8 |
+ M |
+ Chip02_Batch03_BXD8_M_Str |
+ Batch03 |
+
+
+ | 13 |
+ BXD9 |
+ F |
+ Chip16_Batch01_BXD9_F_Str |
+ Batch01 |
+
+
+ | 14 |
+ BXD9 |
+ M |
+ Chip10_Batch01_BXD9_M_Str |
+ Batch01 |
+
+
+ | 15 |
+ BXD11 |
+ F |
+ Chip31_Batch02_BXD11_F_Str |
+ Batch02 |
+
+
+ | 16 |
+ BXD12 |
+ F |
+ Chip11_Batch01_BXD12_F_Str |
+ Batch01 |
+
+
+ | 17 |
+ BXD12 |
+ M |
+ Chip18_Batch03_BXD12_M_Str |
+ Batch03 |
+
+
+ | 18 |
+ BXD13 |
+ F |
+ Chip33_Batch02_BXD13_F_Str |
+ Batch02 |
+
+
+ | 19 |
+ BXD14 |
+ F |
+ Chip48_Batch02_BXD14_F_Str |
+ Batch02 |
+
+
+ | 20 |
+ BXD14 |
+ M |
+ Chip47_Rerun01_BXD14_M_Str |
+ Rerun01 |
+
+
+ | 21 |
+ BXD15 |
+ F |
+ Chip21_Batch01_BXD15_F_Str |
+ Batch01 |
+
+
+ | 22 |
+ BXD15 |
+ M |
+ Chip13_Batch01_BXD15_M_Str |
+ Batch01 |
+
+
+ | 23 |
+ BXD16 |
+ F |
+ Chip36_Batch02_BXD16_F_Str |
+ Batch02 |
+
+
+ | 24 |
+ BXD16 |
+ M |
+ Chip44_Rerun01_BXD16_M_Str |
+ Rerun01 |
+
+
+ | 25 |
+ BXD18 |
+ F |
+ Chip15_Batch03_BXD18_F_Str |
+ Batch03 |
+
+
+ | 26 |
+ BXD18 |
+ M |
+ Chip19_Batch03_BXD18_M_Str |
+ Batch03 |
+
+
+ | 27 |
+ BXD19 |
+ F |
+ Chip19_Batch01_BXD19_F_Str |
+ Batch01 |
+
+
+ | 28 |
+ BXD20 |
+ F |
+ Chip14_Batch03_BXD20_F_Str |
+ Batch03 |
+
+
+ | 29 |
+ BXD21 |
+ F |
+ Chip18_Batch01_BXD21_F_Str |
+ Batch01 |
+
+
+ | 30 |
+ BXD21 |
+ M |
+ Chip09_Batch01_BXD21_M_Str |
+ Batch01 |
+
+
+ | 31 |
+ BXD22 |
+ M |
+ Chip13_Batch03_BXD22_M_Str |
+ Batch03 |
+
+
+ | 32 |
+ BXD23 |
+ M |
+ Chip01_Batch03_BXD23_M_Str |
+ Batch03 |
+
+
+ | 33 |
+ BXD24 |
+ M |
+ Chip17_Batch03_BXD24_M_Str |
+ Batch03 |
+
+
+ | 34 |
+ BXD27 |
+ F |
+ Chip29_Batch02_BXD27_F_Str |
+ Batch02 |
+
+
+ | 35 |
+ BXD27 |
+ M |
+ Chip40_Batch02_BXD27_M_Str |
+ Batch02 |
+
+
+ | 36 |
+ BXD28 |
+ F |
+ Chip06_Batch01_BXD28_F_Str |
+ Batch01 |
+
+
+ | 37 |
+ BXD28 |
+ M |
+ Chip23_Batch01_BXD28_M_Str |
+ Batch01 |
+
+
+ | 38 |
+ BXD29 |
+ F |
+ Chip45_Batch02_BXD29_F_Str |
+ Batch02 |
+
+
+ | 39 |
+ BXD29 |
+ M |
+ Chip42_Batch02_BXD29_M_Str |
+ Batch02 |
+
+
+ | 40 |
+ BXD31 |
+ F |
+ Chip14_Batch01_BXD31_F_Str |
+ Batch01 |
+
+
+ | 41 |
+ BXD31 |
+ M |
+ Chip09_Batch03_BXD31_M_Str |
+ Batch03 |
+
+
+ | 42 |
+ BXD32 |
+ M |
+ Chip30_Batch02_BXD32_M_Str |
+ Batch02 |
+
+
+ | 43 |
+ BXD33 |
+ F |
+ Chip27_Rerun01_BXD33_F_Str |
+ Rerun01 |
+
+
+ | 44 |
+ BXD33 |
+ M |
+ Chip34_Batch02_BXD33_M_Str |
+ Batch02 |
+
+
+ | 45 |
+ BXD34 |
+ F |
+ Chip03_Batch01_BXD34_F_Str |
+ Batch01 |
+
+
+ | 46 |
+ BXD34 |
+ M |
+ Chip07_Batch01_BXD34_M_Str |
+ Batch01 |
+
+
+ | 47 |
+ BXD36 |
+ F |
+ Chip22_Batch03_BXD36_F_Str |
+ Batch03 |
+
+
+ | 48 |
+ BXD36 |
+ M |
+ Chip24_Batch03_BXD36_M_Str |
+ Batch03 |
+
+
+ | 49 |
+ BXD38 |
+ F |
+ Chip17_Batch01_BXD38_F_Str |
+ Batch01 |
+
+
+ | 50 |
+ BXD38 |
+ M |
+ Chip24_Batch01_BXD38_M_Str |
+ Batch01 |
+
+
+ | 51 |
+ BXD39 |
+ M |
+ Chip20_Batch03_BXD39_M_Str |
+ Batch03 |
+
+
+ | 52 |
+ BXD39 |
+ F |
+ Chip23_Batch03_BXD39_F_Str |
+ Batch03 |
+
+
+ | 53 |
+ BXD39 |
+ M |
+ Chip43_Rerun01_BXD39_M_Str |
+ Rerun01 |
+
+
+ | 54 |
+ BXD40 |
+ F |
+ Chip08_Rerun01_BXD40_F_Str |
+ Rerun01 |
+
+
+ | 55 |
+ BXD40 |
+ M |
+ Chip22_Batch01_BXD40_M_Str |
+ Batch01 |
+
+
+ | 56 |
+ BXD42 |
+ F |
+ Chip35_Batch02_BXD42_F_Str |
+ Batch02 |
+
+
+ | 57 |
+ BXD42 |
+ M |
+ Chip32_Batch02_BXD42_M_Str |
+ Batch02 |
+
+
+ | 58 |
+ DBA/2J |
+ M |
+ Chip02_Batch01_D2_M_Str |
+ Batch01 |
+
+
+ | 59 |
+ DBA/2J |
+ M |
+ Chip05_Batch03_D2_M_Str |
+ Batch03 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Sa_m2_0405_mc/acknowledgment.rtf b/general/datasets/Sa_m2_0405_mc/acknowledgment.rtf
new file mode 100644
index 0000000..94eec11
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_mc/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to Glenn Rosen from P20 MH62009 (see below for specifics). Samples and arrays were processed by the Genomics Core at Beth Israel Deaconess Medical Center by Towia Libermann and colleagues.
+
diff --git a/general/datasets/Sa_m2_0405_mc/cases.rtf b/general/datasets/Sa_m2_0405_mc/cases.rtf
new file mode 100644
index 0000000..491788f
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_mc/cases.rtf
@@ -0,0 +1,5 @@
+
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+
+
diff --git a/general/datasets/Sa_m2_0405_mc/experiment-design.rtf b/general/datasets/Sa_m2_0405_mc/experiment-design.rtf
new file mode 100644
index 0000000..cb07f36
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_mc/experiment-design.rtf
@@ -0,0 +1,5 @@
+RNA was extracted by Rosen and colleagues and was then processed by the BIDMC Genomics Core. Labeled cRNA was generated using the Amersham Biosciences cRNA synthesis kit protocol.
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one sample from each sex for all BXD strains. We have not yet achieved this goal. Twenty-three of 33 strains are represented by male and female samples. The remaining 8 strains are still represented by single sex samples: BXD11 (F), BXD13 (F), BXD19 (F), BXD20 (F), BXD22 (M), BXD23 (M), BXD24 (M), BXD32 (M), C57BL/6J (M), and DBA/2J (M).
+
+Batch Structure: This data set consists of arrays processed in three batches with several reruns for the first batch. All arrays were processed using a single protocol. All data have been corrected for batch effects as described below.
+
diff --git a/general/datasets/Sa_m2_0405_mc/notes.rtf b/general/datasets/Sa_m2_0405_mc/notes.rtf
new file mode 100644
index 0000000..0af01e6
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_mc/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by GDR, RWW, and YHQ on Nov 2004. Updated by RWW Nov 17, 2004; GDR and RWW, Dec 23, 2004; RWW and GDR April 8, 2005.
+
diff --git a/general/datasets/Sa_m2_0405_mc/platform.rtf b/general/datasets/Sa_m2_0405_mc/platform.rtf
new file mode 100644
index 0000000..30c2f8c
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_mc/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are near duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequence as the 430A and B series. However, we have found that roughy 75000 probes differ from those on A and B arrays.
+
diff --git a/general/datasets/Sa_m2_0405_mc/processing.rtf b/general/datasets/Sa_m2_0405_mc/processing.rtf
new file mode 100644
index 0000000..2e46796
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_mc/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the batches at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels. Data quality control: A total of 62 samples passed RNA quality control.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients (62x61/2). Arrays with probe data that was not homogeneous when compared to any other arrays was flagged. If the correlation at the probe level was less than approximately 0.92 we deleted that array data set. Three arrays we lost during this process (BXD19_M_Str_Batch03, BXD23_F_Str_Batch03, and BXD24_F_Str_Batch03).
+
+Probe set level QC: The final normalized strain averages were evaluated for outliers. This involved counting the number of times that the probe set value for a particular strain was beyond two standard deviations of the mean of all strains. (We used the PDNN transform as our reference probe set data for this QC step.) Two strains, each represented by single arrays, generated greater than 5,000 outlier counts (10% of the number of probe sets). These two arrays generated a great number of outliers across the entire range of expression and since we do not yet have replicate arrays for either of these two strains we opted to delete them from the final April 2005 striatum data sets.
diff --git a/general/datasets/Sa_m2_0405_mc/summary.rtf b/general/datasets/Sa_m2_0405_mc/summary.rtf
new file mode 100644
index 0000000..e674c86
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_mc/summary.rtf
@@ -0,0 +1 @@
+This April 2005 data freeze provides estimates of mRNA expression in the striatum (caudate nucleus of the forebrain) of 33 lines of mice including C57BL/6J, DBA/2J, and 31 BXD recombinant inbred strains. Data were generated using Affymetrix Mouse Genome 430 2.0 short oligomer microarrays at Beth Israel Deaconess Medical Center (BIDMC, Boston MA) by Glenn D. Rosen with the support of a Human Brain Project (HBP) grant. Approximately 250 brain samples (males and females) from 33 strains were used in this experiment. Samples were hybridized to a total of 59 arrays. This particular data set was processed using the Microarray Suite 5 protocol (MAS 5). To simplify comparison among different transforms, MAS5 values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Sa_m2_0405_mc/tissue.rtf b/general/datasets/Sa_m2_0405_mc/tissue.rtf
new file mode 100644
index 0000000..6503813
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_mc/tissue.rtf
@@ -0,0 +1,440 @@
+
+Animals were obtained from The Jackson Laboratory and housed for several weeks at BIDMC until they reached ~2 months of age (range from 55 to 62 days). Mice were killed by cervical dislocation and brains were removed and placed in RNAlater for 20 to 25 minutes prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both striata were dissected using a medial approach by GD Rosen that typically yields 5 to 7 mg of tissue per side. The purity of this dissection has been validated by an analysis of acetylcholinestase activity. A pool of dissected tissue from 3 or 4 adults (approximately 25 to 30 mg of tissue) of the same strain, sex, and age was collected in one session and used to generate cRNA samples.
+
+
+The table below lists the arrays by strain, sex, sample name, and batch ID. Each array was hybridized to a pool of mRNA from 3 to 4 mice. All mice were between 55 and 62 days.
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Sample_name |
+ BatchId |
+
+
+ | 1 |
+ C57BL/6J |
+ M |
+ Chip41_Batch02_B6_M_Str |
+ Batch02 |
+
+
+ | 2 |
+ C57BL/6J |
+ M |
+ Chip11_Batch03_B6_M_Str |
+ Batch03 |
+
+
+ | 3 |
+ BXD1 |
+ F |
+ Chip03_Batch03_BXD1_F_Str |
+ Batch03 |
+
+
+ | 4 |
+ BXD1 |
+ M |
+ Chip04_Batch03_BXD1_M_Str |
+ Batch03 |
+
+
+ | 5 |
+ BXD2 |
+ F |
+ Chip20_Rerun01_BXD2_F_Str |
+ Rerun01 |
+
+
+ | 6 |
+ BXD2 |
+ M |
+ Chip05_Batch01_BXD2_M_Str |
+ Batch01 |
+
+
+ | 7 |
+ BXD5 |
+ F |
+ Chip10_Batch03_BXD5_F_Str |
+ Batch03 |
+
+
+ | 8 |
+ BXD5 |
+ M |
+ Chip12_Batch03_BXD5_M_Str |
+ Batch03 |
+
+
+ | 9 |
+ BXD6 |
+ F |
+ Chip38_Batch02_BXD6_F_Str |
+ Batch02 |
+
+
+ | 10 |
+ BXD6 |
+ M |
+ Chip39_Batch02_BXD6_M_Str |
+ Batch02 |
+
+
+ | 11 |
+ BXD8 |
+ F |
+ Chip07_Batch03_BXD8_F_Str |
+ Batch03 |
+
+
+ | 12 |
+ BXD8 |
+ M |
+ Chip02_Batch03_BXD8_M_Str |
+ Batch03 |
+
+
+ | 13 |
+ BXD9 |
+ F |
+ Chip16_Batch01_BXD9_F_Str |
+ Batch01 |
+
+
+ | 14 |
+ BXD9 |
+ M |
+ Chip10_Batch01_BXD9_M_Str |
+ Batch01 |
+
+
+ | 15 |
+ BXD11 |
+ F |
+ Chip31_Batch02_BXD11_F_Str |
+ Batch02 |
+
+
+ | 16 |
+ BXD12 |
+ F |
+ Chip11_Batch01_BXD12_F_Str |
+ Batch01 |
+
+
+ | 17 |
+ BXD12 |
+ M |
+ Chip18_Batch03_BXD12_M_Str |
+ Batch03 |
+
+
+ | 18 |
+ BXD13 |
+ F |
+ Chip33_Batch02_BXD13_F_Str |
+ Batch02 |
+
+
+ | 19 |
+ BXD14 |
+ F |
+ Chip48_Batch02_BXD14_F_Str |
+ Batch02 |
+
+
+ | 20 |
+ BXD14 |
+ M |
+ Chip47_Rerun01_BXD14_M_Str |
+ Rerun01 |
+
+
+ | 21 |
+ BXD15 |
+ F |
+ Chip21_Batch01_BXD15_F_Str |
+ Batch01 |
+
+
+ | 22 |
+ BXD15 |
+ M |
+ Chip13_Batch01_BXD15_M_Str |
+ Batch01 |
+
+
+ | 23 |
+ BXD16 |
+ F |
+ Chip36_Batch02_BXD16_F_Str |
+ Batch02 |
+
+
+ | 24 |
+ BXD16 |
+ M |
+ Chip44_Rerun01_BXD16_M_Str |
+ Rerun01 |
+
+
+ | 25 |
+ BXD18 |
+ F |
+ Chip15_Batch03_BXD18_F_Str |
+ Batch03 |
+
+
+ | 26 |
+ BXD18 |
+ M |
+ Chip19_Batch03_BXD18_M_Str |
+ Batch03 |
+
+
+ | 27 |
+ BXD19 |
+ F |
+ Chip19_Batch01_BXD19_F_Str |
+ Batch01 |
+
+
+ | 28 |
+ BXD20 |
+ F |
+ Chip14_Batch03_BXD20_F_Str |
+ Batch03 |
+
+
+ | 29 |
+ BXD21 |
+ F |
+ Chip18_Batch01_BXD21_F_Str |
+ Batch01 |
+
+
+ | 30 |
+ BXD21 |
+ M |
+ Chip09_Batch01_BXD21_M_Str |
+ Batch01 |
+
+
+ | 31 |
+ BXD22 |
+ M |
+ Chip13_Batch03_BXD22_M_Str |
+ Batch03 |
+
+
+ | 32 |
+ BXD23 |
+ M |
+ Chip01_Batch03_BXD23_M_Str |
+ Batch03 |
+
+
+ | 33 |
+ BXD24 |
+ M |
+ Chip17_Batch03_BXD24_M_Str |
+ Batch03 |
+
+
+ | 34 |
+ BXD27 |
+ F |
+ Chip29_Batch02_BXD27_F_Str |
+ Batch02 |
+
+
+ | 35 |
+ BXD27 |
+ M |
+ Chip40_Batch02_BXD27_M_Str |
+ Batch02 |
+
+
+ | 36 |
+ BXD28 |
+ F |
+ Chip06_Batch01_BXD28_F_Str |
+ Batch01 |
+
+
+ | 37 |
+ BXD28 |
+ M |
+ Chip23_Batch01_BXD28_M_Str |
+ Batch01 |
+
+
+ | 38 |
+ BXD29 |
+ F |
+ Chip45_Batch02_BXD29_F_Str |
+ Batch02 |
+
+
+ | 39 |
+ BXD29 |
+ M |
+ Chip42_Batch02_BXD29_M_Str |
+ Batch02 |
+
+
+ | 40 |
+ BXD31 |
+ F |
+ Chip14_Batch01_BXD31_F_Str |
+ Batch01 |
+
+
+ | 41 |
+ BXD31 |
+ M |
+ Chip09_Batch03_BXD31_M_Str |
+ Batch03 |
+
+
+ | 42 |
+ BXD32 |
+ M |
+ Chip30_Batch02_BXD32_M_Str |
+ Batch02 |
+
+
+ | 43 |
+ BXD33 |
+ F |
+ Chip27_Rerun01_BXD33_F_Str |
+ Rerun01 |
+
+
+ | 44 |
+ BXD33 |
+ M |
+ Chip34_Batch02_BXD33_M_Str |
+ Batch02 |
+
+
+ | 45 |
+ BXD34 |
+ F |
+ Chip03_Batch01_BXD34_F_Str |
+ Batch01 |
+
+
+ | 46 |
+ BXD34 |
+ M |
+ Chip07_Batch01_BXD34_M_Str |
+ Batch01 |
+
+
+ | 47 |
+ BXD36 |
+ F |
+ Chip22_Batch03_BXD36_F_Str |
+ Batch03 |
+
+
+ | 48 |
+ BXD36 |
+ M |
+ Chip24_Batch03_BXD36_M_Str |
+ Batch03 |
+
+
+ | 49 |
+ BXD38 |
+ F |
+ Chip17_Batch01_BXD38_F_Str |
+ Batch01 |
+
+
+ | 50 |
+ BXD38 |
+ M |
+ Chip24_Batch01_BXD38_M_Str |
+ Batch01 |
+
+
+ | 51 |
+ BXD39 |
+ M |
+ Chip20_Batch03_BXD39_M_Str |
+ Batch03 |
+
+
+ | 52 |
+ BXD39 |
+ F |
+ Chip23_Batch03_BXD39_F_Str |
+ Batch03 |
+
+
+ | 53 |
+ BXD39 |
+ M |
+ Chip43_Rerun01_BXD39_M_Str |
+ Rerun01 |
+
+
+ | 54 |
+ BXD40 |
+ F |
+ Chip08_Rerun01_BXD40_F_Str |
+ Rerun01 |
+
+
+ | 55 |
+ BXD40 |
+ M |
+ Chip22_Batch01_BXD40_M_Str |
+ Batch01 |
+
+
+ | 56 |
+ BXD42 |
+ F |
+ Chip35_Batch02_BXD42_F_Str |
+ Batch02 |
+
+
+ | 57 |
+ BXD42 |
+ M |
+ Chip32_Batch02_BXD42_M_Str |
+ Batch02 |
+
+
+ | 58 |
+ DBA/2J |
+ M |
+ Chip02_Batch01_D2_M_Str |
+ Batch01 |
+
+
+ | 59 |
+ DBA/2J |
+ M |
+ Chip05_Batch03_D2_M_Str |
+ Batch03 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Sa_m2_0405_p/acknowledgment.rtf b/general/datasets/Sa_m2_0405_p/acknowledgment.rtf
new file mode 100644
index 0000000..94eec11
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_p/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to Glenn Rosen from P20 MH62009 (see below for specifics). Samples and arrays were processed by the Genomics Core at Beth Israel Deaconess Medical Center by Towia Libermann and colleagues.
+
diff --git a/general/datasets/Sa_m2_0405_p/cases.rtf b/general/datasets/Sa_m2_0405_p/cases.rtf
new file mode 100644
index 0000000..491788f
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_p/cases.rtf
@@ -0,0 +1,5 @@
+
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+
+
diff --git a/general/datasets/Sa_m2_0405_p/experiment-design.rtf b/general/datasets/Sa_m2_0405_p/experiment-design.rtf
new file mode 100644
index 0000000..cb07f36
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_p/experiment-design.rtf
@@ -0,0 +1,5 @@
+RNA was extracted by Rosen and colleagues and was then processed by the BIDMC Genomics Core. Labeled cRNA was generated using the Amersham Biosciences cRNA synthesis kit protocol.
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one sample from each sex for all BXD strains. We have not yet achieved this goal. Twenty-three of 33 strains are represented by male and female samples. The remaining 8 strains are still represented by single sex samples: BXD11 (F), BXD13 (F), BXD19 (F), BXD20 (F), BXD22 (M), BXD23 (M), BXD24 (M), BXD32 (M), C57BL/6J (M), and DBA/2J (M).
+
+Batch Structure: This data set consists of arrays processed in three batches with several reruns for the first batch. All arrays were processed using a single protocol. All data have been corrected for batch effects as described below.
+
diff --git a/general/datasets/Sa_m2_0405_p/notes.rtf b/general/datasets/Sa_m2_0405_p/notes.rtf
new file mode 100644
index 0000000..0af01e6
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_p/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by GDR, RWW, and YHQ on Nov 2004. Updated by RWW Nov 17, 2004; GDR and RWW, Dec 23, 2004; RWW and GDR April 8, 2005.
+
diff --git a/general/datasets/Sa_m2_0405_p/platform.rtf b/general/datasets/Sa_m2_0405_p/platform.rtf
new file mode 100644
index 0000000..30c2f8c
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_p/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are near duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequence as the 430A and B series. However, we have found that roughy 75000 probes differ from those on A and B arrays.
+
diff --git a/general/datasets/Sa_m2_0405_p/processing.rtf b/general/datasets/Sa_m2_0405_p/processing.rtf
new file mode 100644
index 0000000..2e46796
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_p/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the batches at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels. Data quality control: A total of 62 samples passed RNA quality control.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients (62x61/2). Arrays with probe data that was not homogeneous when compared to any other arrays was flagged. If the correlation at the probe level was less than approximately 0.92 we deleted that array data set. Three arrays we lost during this process (BXD19_M_Str_Batch03, BXD23_F_Str_Batch03, and BXD24_F_Str_Batch03).
+
+Probe set level QC: The final normalized strain averages were evaluated for outliers. This involved counting the number of times that the probe set value for a particular strain was beyond two standard deviations of the mean of all strains. (We used the PDNN transform as our reference probe set data for this QC step.) Two strains, each represented by single arrays, generated greater than 5,000 outlier counts (10% of the number of probe sets). These two arrays generated a great number of outliers across the entire range of expression and since we do not yet have replicate arrays for either of these two strains we opted to delete them from the final April 2005 striatum data sets.
diff --git a/general/datasets/Sa_m2_0405_p/summary.rtf b/general/datasets/Sa_m2_0405_p/summary.rtf
new file mode 100644
index 0000000..e674c86
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_p/summary.rtf
@@ -0,0 +1 @@
+This April 2005 data freeze provides estimates of mRNA expression in the striatum (caudate nucleus of the forebrain) of 33 lines of mice including C57BL/6J, DBA/2J, and 31 BXD recombinant inbred strains. Data were generated using Affymetrix Mouse Genome 430 2.0 short oligomer microarrays at Beth Israel Deaconess Medical Center (BIDMC, Boston MA) by Glenn D. Rosen with the support of a Human Brain Project (HBP) grant. Approximately 250 brain samples (males and females) from 33 strains were used in this experiment. Samples were hybridized to a total of 59 arrays. This particular data set was processed using the Microarray Suite 5 protocol (MAS 5). To simplify comparison among different transforms, MAS5 values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Sa_m2_0405_p/tissue.rtf b/general/datasets/Sa_m2_0405_p/tissue.rtf
new file mode 100644
index 0000000..6503813
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_p/tissue.rtf
@@ -0,0 +1,440 @@
+
+Animals were obtained from The Jackson Laboratory and housed for several weeks at BIDMC until they reached ~2 months of age (range from 55 to 62 days). Mice were killed by cervical dislocation and brains were removed and placed in RNAlater for 20 to 25 minutes prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both striata were dissected using a medial approach by GD Rosen that typically yields 5 to 7 mg of tissue per side. The purity of this dissection has been validated by an analysis of acetylcholinestase activity. A pool of dissected tissue from 3 or 4 adults (approximately 25 to 30 mg of tissue) of the same strain, sex, and age was collected in one session and used to generate cRNA samples.
+
+
+The table below lists the arrays by strain, sex, sample name, and batch ID. Each array was hybridized to a pool of mRNA from 3 to 4 mice. All mice were between 55 and 62 days.
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Sample_name |
+ BatchId |
+
+
+ | 1 |
+ C57BL/6J |
+ M |
+ Chip41_Batch02_B6_M_Str |
+ Batch02 |
+
+
+ | 2 |
+ C57BL/6J |
+ M |
+ Chip11_Batch03_B6_M_Str |
+ Batch03 |
+
+
+ | 3 |
+ BXD1 |
+ F |
+ Chip03_Batch03_BXD1_F_Str |
+ Batch03 |
+
+
+ | 4 |
+ BXD1 |
+ M |
+ Chip04_Batch03_BXD1_M_Str |
+ Batch03 |
+
+
+ | 5 |
+ BXD2 |
+ F |
+ Chip20_Rerun01_BXD2_F_Str |
+ Rerun01 |
+
+
+ | 6 |
+ BXD2 |
+ M |
+ Chip05_Batch01_BXD2_M_Str |
+ Batch01 |
+
+
+ | 7 |
+ BXD5 |
+ F |
+ Chip10_Batch03_BXD5_F_Str |
+ Batch03 |
+
+
+ | 8 |
+ BXD5 |
+ M |
+ Chip12_Batch03_BXD5_M_Str |
+ Batch03 |
+
+
+ | 9 |
+ BXD6 |
+ F |
+ Chip38_Batch02_BXD6_F_Str |
+ Batch02 |
+
+
+ | 10 |
+ BXD6 |
+ M |
+ Chip39_Batch02_BXD6_M_Str |
+ Batch02 |
+
+
+ | 11 |
+ BXD8 |
+ F |
+ Chip07_Batch03_BXD8_F_Str |
+ Batch03 |
+
+
+ | 12 |
+ BXD8 |
+ M |
+ Chip02_Batch03_BXD8_M_Str |
+ Batch03 |
+
+
+ | 13 |
+ BXD9 |
+ F |
+ Chip16_Batch01_BXD9_F_Str |
+ Batch01 |
+
+
+ | 14 |
+ BXD9 |
+ M |
+ Chip10_Batch01_BXD9_M_Str |
+ Batch01 |
+
+
+ | 15 |
+ BXD11 |
+ F |
+ Chip31_Batch02_BXD11_F_Str |
+ Batch02 |
+
+
+ | 16 |
+ BXD12 |
+ F |
+ Chip11_Batch01_BXD12_F_Str |
+ Batch01 |
+
+
+ | 17 |
+ BXD12 |
+ M |
+ Chip18_Batch03_BXD12_M_Str |
+ Batch03 |
+
+
+ | 18 |
+ BXD13 |
+ F |
+ Chip33_Batch02_BXD13_F_Str |
+ Batch02 |
+
+
+ | 19 |
+ BXD14 |
+ F |
+ Chip48_Batch02_BXD14_F_Str |
+ Batch02 |
+
+
+ | 20 |
+ BXD14 |
+ M |
+ Chip47_Rerun01_BXD14_M_Str |
+ Rerun01 |
+
+
+ | 21 |
+ BXD15 |
+ F |
+ Chip21_Batch01_BXD15_F_Str |
+ Batch01 |
+
+
+ | 22 |
+ BXD15 |
+ M |
+ Chip13_Batch01_BXD15_M_Str |
+ Batch01 |
+
+
+ | 23 |
+ BXD16 |
+ F |
+ Chip36_Batch02_BXD16_F_Str |
+ Batch02 |
+
+
+ | 24 |
+ BXD16 |
+ M |
+ Chip44_Rerun01_BXD16_M_Str |
+ Rerun01 |
+
+
+ | 25 |
+ BXD18 |
+ F |
+ Chip15_Batch03_BXD18_F_Str |
+ Batch03 |
+
+
+ | 26 |
+ BXD18 |
+ M |
+ Chip19_Batch03_BXD18_M_Str |
+ Batch03 |
+
+
+ | 27 |
+ BXD19 |
+ F |
+ Chip19_Batch01_BXD19_F_Str |
+ Batch01 |
+
+
+ | 28 |
+ BXD20 |
+ F |
+ Chip14_Batch03_BXD20_F_Str |
+ Batch03 |
+
+
+ | 29 |
+ BXD21 |
+ F |
+ Chip18_Batch01_BXD21_F_Str |
+ Batch01 |
+
+
+ | 30 |
+ BXD21 |
+ M |
+ Chip09_Batch01_BXD21_M_Str |
+ Batch01 |
+
+
+ | 31 |
+ BXD22 |
+ M |
+ Chip13_Batch03_BXD22_M_Str |
+ Batch03 |
+
+
+ | 32 |
+ BXD23 |
+ M |
+ Chip01_Batch03_BXD23_M_Str |
+ Batch03 |
+
+
+ | 33 |
+ BXD24 |
+ M |
+ Chip17_Batch03_BXD24_M_Str |
+ Batch03 |
+
+
+ | 34 |
+ BXD27 |
+ F |
+ Chip29_Batch02_BXD27_F_Str |
+ Batch02 |
+
+
+ | 35 |
+ BXD27 |
+ M |
+ Chip40_Batch02_BXD27_M_Str |
+ Batch02 |
+
+
+ | 36 |
+ BXD28 |
+ F |
+ Chip06_Batch01_BXD28_F_Str |
+ Batch01 |
+
+
+ | 37 |
+ BXD28 |
+ M |
+ Chip23_Batch01_BXD28_M_Str |
+ Batch01 |
+
+
+ | 38 |
+ BXD29 |
+ F |
+ Chip45_Batch02_BXD29_F_Str |
+ Batch02 |
+
+
+ | 39 |
+ BXD29 |
+ M |
+ Chip42_Batch02_BXD29_M_Str |
+ Batch02 |
+
+
+ | 40 |
+ BXD31 |
+ F |
+ Chip14_Batch01_BXD31_F_Str |
+ Batch01 |
+
+
+ | 41 |
+ BXD31 |
+ M |
+ Chip09_Batch03_BXD31_M_Str |
+ Batch03 |
+
+
+ | 42 |
+ BXD32 |
+ M |
+ Chip30_Batch02_BXD32_M_Str |
+ Batch02 |
+
+
+ | 43 |
+ BXD33 |
+ F |
+ Chip27_Rerun01_BXD33_F_Str |
+ Rerun01 |
+
+
+ | 44 |
+ BXD33 |
+ M |
+ Chip34_Batch02_BXD33_M_Str |
+ Batch02 |
+
+
+ | 45 |
+ BXD34 |
+ F |
+ Chip03_Batch01_BXD34_F_Str |
+ Batch01 |
+
+
+ | 46 |
+ BXD34 |
+ M |
+ Chip07_Batch01_BXD34_M_Str |
+ Batch01 |
+
+
+ | 47 |
+ BXD36 |
+ F |
+ Chip22_Batch03_BXD36_F_Str |
+ Batch03 |
+
+
+ | 48 |
+ BXD36 |
+ M |
+ Chip24_Batch03_BXD36_M_Str |
+ Batch03 |
+
+
+ | 49 |
+ BXD38 |
+ F |
+ Chip17_Batch01_BXD38_F_Str |
+ Batch01 |
+
+
+ | 50 |
+ BXD38 |
+ M |
+ Chip24_Batch01_BXD38_M_Str |
+ Batch01 |
+
+
+ | 51 |
+ BXD39 |
+ M |
+ Chip20_Batch03_BXD39_M_Str |
+ Batch03 |
+
+
+ | 52 |
+ BXD39 |
+ F |
+ Chip23_Batch03_BXD39_F_Str |
+ Batch03 |
+
+
+ | 53 |
+ BXD39 |
+ M |
+ Chip43_Rerun01_BXD39_M_Str |
+ Rerun01 |
+
+
+ | 54 |
+ BXD40 |
+ F |
+ Chip08_Rerun01_BXD40_F_Str |
+ Rerun01 |
+
+
+ | 55 |
+ BXD40 |
+ M |
+ Chip22_Batch01_BXD40_M_Str |
+ Batch01 |
+
+
+ | 56 |
+ BXD42 |
+ F |
+ Chip35_Batch02_BXD42_F_Str |
+ Batch02 |
+
+
+ | 57 |
+ BXD42 |
+ M |
+ Chip32_Batch02_BXD42_M_Str |
+ Batch02 |
+
+
+ | 58 |
+ DBA/2J |
+ M |
+ Chip02_Batch01_D2_M_Str |
+ Batch01 |
+
+
+ | 59 |
+ DBA/2J |
+ M |
+ Chip05_Batch03_D2_M_Str |
+ Batch03 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Sa_m2_0405_pc/acknowledgment.rtf b/general/datasets/Sa_m2_0405_pc/acknowledgment.rtf
new file mode 100644
index 0000000..94eec11
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_pc/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to Glenn Rosen from P20 MH62009 (see below for specifics). Samples and arrays were processed by the Genomics Core at Beth Israel Deaconess Medical Center by Towia Libermann and colleagues.
+
diff --git a/general/datasets/Sa_m2_0405_pc/cases.rtf b/general/datasets/Sa_m2_0405_pc/cases.rtf
new file mode 100644
index 0000000..491788f
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_pc/cases.rtf
@@ -0,0 +1,5 @@
+
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+
+
diff --git a/general/datasets/Sa_m2_0405_pc/experiment-design.rtf b/general/datasets/Sa_m2_0405_pc/experiment-design.rtf
new file mode 100644
index 0000000..cb07f36
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_pc/experiment-design.rtf
@@ -0,0 +1,5 @@
+RNA was extracted by Rosen and colleagues and was then processed by the BIDMC Genomics Core. Labeled cRNA was generated using the Amersham Biosciences cRNA synthesis kit protocol.
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one sample from each sex for all BXD strains. We have not yet achieved this goal. Twenty-three of 33 strains are represented by male and female samples. The remaining 8 strains are still represented by single sex samples: BXD11 (F), BXD13 (F), BXD19 (F), BXD20 (F), BXD22 (M), BXD23 (M), BXD24 (M), BXD32 (M), C57BL/6J (M), and DBA/2J (M).
+
+Batch Structure: This data set consists of arrays processed in three batches with several reruns for the first batch. All arrays were processed using a single protocol. All data have been corrected for batch effects as described below.
+
diff --git a/general/datasets/Sa_m2_0405_pc/notes.rtf b/general/datasets/Sa_m2_0405_pc/notes.rtf
new file mode 100644
index 0000000..0af01e6
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_pc/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by GDR, RWW, and YHQ on Nov 2004. Updated by RWW Nov 17, 2004; GDR and RWW, Dec 23, 2004; RWW and GDR April 8, 2005.
+
diff --git a/general/datasets/Sa_m2_0405_pc/platform.rtf b/general/datasets/Sa_m2_0405_pc/platform.rtf
new file mode 100644
index 0000000..30c2f8c
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_pc/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are near duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequence as the 430A and B series. However, we have found that roughy 75000 probes differ from those on A and B arrays.
+
diff --git a/general/datasets/Sa_m2_0405_pc/processing.rtf b/general/datasets/Sa_m2_0405_pc/processing.rtf
new file mode 100644
index 0000000..2e46796
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_pc/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the batches at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels. Data quality control: A total of 62 samples passed RNA quality control.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients (62x61/2). Arrays with probe data that was not homogeneous when compared to any other arrays was flagged. If the correlation at the probe level was less than approximately 0.92 we deleted that array data set. Three arrays we lost during this process (BXD19_M_Str_Batch03, BXD23_F_Str_Batch03, and BXD24_F_Str_Batch03).
+
+Probe set level QC: The final normalized strain averages were evaluated for outliers. This involved counting the number of times that the probe set value for a particular strain was beyond two standard deviations of the mean of all strains. (We used the PDNN transform as our reference probe set data for this QC step.) Two strains, each represented by single arrays, generated greater than 5,000 outlier counts (10% of the number of probe sets). These two arrays generated a great number of outliers across the entire range of expression and since we do not yet have replicate arrays for either of these two strains we opted to delete them from the final April 2005 striatum data sets.
diff --git a/general/datasets/Sa_m2_0405_pc/summary.rtf b/general/datasets/Sa_m2_0405_pc/summary.rtf
new file mode 100644
index 0000000..e674c86
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_pc/summary.rtf
@@ -0,0 +1 @@
+This April 2005 data freeze provides estimates of mRNA expression in the striatum (caudate nucleus of the forebrain) of 33 lines of mice including C57BL/6J, DBA/2J, and 31 BXD recombinant inbred strains. Data were generated using Affymetrix Mouse Genome 430 2.0 short oligomer microarrays at Beth Israel Deaconess Medical Center (BIDMC, Boston MA) by Glenn D. Rosen with the support of a Human Brain Project (HBP) grant. Approximately 250 brain samples (males and females) from 33 strains were used in this experiment. Samples were hybridized to a total of 59 arrays. This particular data set was processed using the Microarray Suite 5 protocol (MAS 5). To simplify comparison among different transforms, MAS5 values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Sa_m2_0405_pc/tissue.rtf b/general/datasets/Sa_m2_0405_pc/tissue.rtf
new file mode 100644
index 0000000..6503813
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_pc/tissue.rtf
@@ -0,0 +1,440 @@
+
+Animals were obtained from The Jackson Laboratory and housed for several weeks at BIDMC until they reached ~2 months of age (range from 55 to 62 days). Mice were killed by cervical dislocation and brains were removed and placed in RNAlater for 20 to 25 minutes prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both striata were dissected using a medial approach by GD Rosen that typically yields 5 to 7 mg of tissue per side. The purity of this dissection has been validated by an analysis of acetylcholinestase activity. A pool of dissected tissue from 3 or 4 adults (approximately 25 to 30 mg of tissue) of the same strain, sex, and age was collected in one session and used to generate cRNA samples.
+
+
+The table below lists the arrays by strain, sex, sample name, and batch ID. Each array was hybridized to a pool of mRNA from 3 to 4 mice. All mice were between 55 and 62 days.
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Sample_name |
+ BatchId |
+
+
+ | 1 |
+ C57BL/6J |
+ M |
+ Chip41_Batch02_B6_M_Str |
+ Batch02 |
+
+
+ | 2 |
+ C57BL/6J |
+ M |
+ Chip11_Batch03_B6_M_Str |
+ Batch03 |
+
+
+ | 3 |
+ BXD1 |
+ F |
+ Chip03_Batch03_BXD1_F_Str |
+ Batch03 |
+
+
+ | 4 |
+ BXD1 |
+ M |
+ Chip04_Batch03_BXD1_M_Str |
+ Batch03 |
+
+
+ | 5 |
+ BXD2 |
+ F |
+ Chip20_Rerun01_BXD2_F_Str |
+ Rerun01 |
+
+
+ | 6 |
+ BXD2 |
+ M |
+ Chip05_Batch01_BXD2_M_Str |
+ Batch01 |
+
+
+ | 7 |
+ BXD5 |
+ F |
+ Chip10_Batch03_BXD5_F_Str |
+ Batch03 |
+
+
+ | 8 |
+ BXD5 |
+ M |
+ Chip12_Batch03_BXD5_M_Str |
+ Batch03 |
+
+
+ | 9 |
+ BXD6 |
+ F |
+ Chip38_Batch02_BXD6_F_Str |
+ Batch02 |
+
+
+ | 10 |
+ BXD6 |
+ M |
+ Chip39_Batch02_BXD6_M_Str |
+ Batch02 |
+
+
+ | 11 |
+ BXD8 |
+ F |
+ Chip07_Batch03_BXD8_F_Str |
+ Batch03 |
+
+
+ | 12 |
+ BXD8 |
+ M |
+ Chip02_Batch03_BXD8_M_Str |
+ Batch03 |
+
+
+ | 13 |
+ BXD9 |
+ F |
+ Chip16_Batch01_BXD9_F_Str |
+ Batch01 |
+
+
+ | 14 |
+ BXD9 |
+ M |
+ Chip10_Batch01_BXD9_M_Str |
+ Batch01 |
+
+
+ | 15 |
+ BXD11 |
+ F |
+ Chip31_Batch02_BXD11_F_Str |
+ Batch02 |
+
+
+ | 16 |
+ BXD12 |
+ F |
+ Chip11_Batch01_BXD12_F_Str |
+ Batch01 |
+
+
+ | 17 |
+ BXD12 |
+ M |
+ Chip18_Batch03_BXD12_M_Str |
+ Batch03 |
+
+
+ | 18 |
+ BXD13 |
+ F |
+ Chip33_Batch02_BXD13_F_Str |
+ Batch02 |
+
+
+ | 19 |
+ BXD14 |
+ F |
+ Chip48_Batch02_BXD14_F_Str |
+ Batch02 |
+
+
+ | 20 |
+ BXD14 |
+ M |
+ Chip47_Rerun01_BXD14_M_Str |
+ Rerun01 |
+
+
+ | 21 |
+ BXD15 |
+ F |
+ Chip21_Batch01_BXD15_F_Str |
+ Batch01 |
+
+
+ | 22 |
+ BXD15 |
+ M |
+ Chip13_Batch01_BXD15_M_Str |
+ Batch01 |
+
+
+ | 23 |
+ BXD16 |
+ F |
+ Chip36_Batch02_BXD16_F_Str |
+ Batch02 |
+
+
+ | 24 |
+ BXD16 |
+ M |
+ Chip44_Rerun01_BXD16_M_Str |
+ Rerun01 |
+
+
+ | 25 |
+ BXD18 |
+ F |
+ Chip15_Batch03_BXD18_F_Str |
+ Batch03 |
+
+
+ | 26 |
+ BXD18 |
+ M |
+ Chip19_Batch03_BXD18_M_Str |
+ Batch03 |
+
+
+ | 27 |
+ BXD19 |
+ F |
+ Chip19_Batch01_BXD19_F_Str |
+ Batch01 |
+
+
+ | 28 |
+ BXD20 |
+ F |
+ Chip14_Batch03_BXD20_F_Str |
+ Batch03 |
+
+
+ | 29 |
+ BXD21 |
+ F |
+ Chip18_Batch01_BXD21_F_Str |
+ Batch01 |
+
+
+ | 30 |
+ BXD21 |
+ M |
+ Chip09_Batch01_BXD21_M_Str |
+ Batch01 |
+
+
+ | 31 |
+ BXD22 |
+ M |
+ Chip13_Batch03_BXD22_M_Str |
+ Batch03 |
+
+
+ | 32 |
+ BXD23 |
+ M |
+ Chip01_Batch03_BXD23_M_Str |
+ Batch03 |
+
+
+ | 33 |
+ BXD24 |
+ M |
+ Chip17_Batch03_BXD24_M_Str |
+ Batch03 |
+
+
+ | 34 |
+ BXD27 |
+ F |
+ Chip29_Batch02_BXD27_F_Str |
+ Batch02 |
+
+
+ | 35 |
+ BXD27 |
+ M |
+ Chip40_Batch02_BXD27_M_Str |
+ Batch02 |
+
+
+ | 36 |
+ BXD28 |
+ F |
+ Chip06_Batch01_BXD28_F_Str |
+ Batch01 |
+
+
+ | 37 |
+ BXD28 |
+ M |
+ Chip23_Batch01_BXD28_M_Str |
+ Batch01 |
+
+
+ | 38 |
+ BXD29 |
+ F |
+ Chip45_Batch02_BXD29_F_Str |
+ Batch02 |
+
+
+ | 39 |
+ BXD29 |
+ M |
+ Chip42_Batch02_BXD29_M_Str |
+ Batch02 |
+
+
+ | 40 |
+ BXD31 |
+ F |
+ Chip14_Batch01_BXD31_F_Str |
+ Batch01 |
+
+
+ | 41 |
+ BXD31 |
+ M |
+ Chip09_Batch03_BXD31_M_Str |
+ Batch03 |
+
+
+ | 42 |
+ BXD32 |
+ M |
+ Chip30_Batch02_BXD32_M_Str |
+ Batch02 |
+
+
+ | 43 |
+ BXD33 |
+ F |
+ Chip27_Rerun01_BXD33_F_Str |
+ Rerun01 |
+
+
+ | 44 |
+ BXD33 |
+ M |
+ Chip34_Batch02_BXD33_M_Str |
+ Batch02 |
+
+
+ | 45 |
+ BXD34 |
+ F |
+ Chip03_Batch01_BXD34_F_Str |
+ Batch01 |
+
+
+ | 46 |
+ BXD34 |
+ M |
+ Chip07_Batch01_BXD34_M_Str |
+ Batch01 |
+
+
+ | 47 |
+ BXD36 |
+ F |
+ Chip22_Batch03_BXD36_F_Str |
+ Batch03 |
+
+
+ | 48 |
+ BXD36 |
+ M |
+ Chip24_Batch03_BXD36_M_Str |
+ Batch03 |
+
+
+ | 49 |
+ BXD38 |
+ F |
+ Chip17_Batch01_BXD38_F_Str |
+ Batch01 |
+
+
+ | 50 |
+ BXD38 |
+ M |
+ Chip24_Batch01_BXD38_M_Str |
+ Batch01 |
+
+
+ | 51 |
+ BXD39 |
+ M |
+ Chip20_Batch03_BXD39_M_Str |
+ Batch03 |
+
+
+ | 52 |
+ BXD39 |
+ F |
+ Chip23_Batch03_BXD39_F_Str |
+ Batch03 |
+
+
+ | 53 |
+ BXD39 |
+ M |
+ Chip43_Rerun01_BXD39_M_Str |
+ Rerun01 |
+
+
+ | 54 |
+ BXD40 |
+ F |
+ Chip08_Rerun01_BXD40_F_Str |
+ Rerun01 |
+
+
+ | 55 |
+ BXD40 |
+ M |
+ Chip22_Batch01_BXD40_M_Str |
+ Batch01 |
+
+
+ | 56 |
+ BXD42 |
+ F |
+ Chip35_Batch02_BXD42_F_Str |
+ Batch02 |
+
+
+ | 57 |
+ BXD42 |
+ M |
+ Chip32_Batch02_BXD42_M_Str |
+ Batch02 |
+
+
+ | 58 |
+ DBA/2J |
+ M |
+ Chip02_Batch01_D2_M_Str |
+ Batch01 |
+
+
+ | 59 |
+ DBA/2J |
+ M |
+ Chip05_Batch03_D2_M_Str |
+ Batch03 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Sa_m2_0405_r/acknowledgment.rtf b/general/datasets/Sa_m2_0405_r/acknowledgment.rtf
new file mode 100644
index 0000000..94eec11
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_r/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to Glenn Rosen from P20 MH62009 (see below for specifics). Samples and arrays were processed by the Genomics Core at Beth Israel Deaconess Medical Center by Towia Libermann and colleagues.
+
diff --git a/general/datasets/Sa_m2_0405_r/cases.rtf b/general/datasets/Sa_m2_0405_r/cases.rtf
new file mode 100644
index 0000000..491788f
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_r/cases.rtf
@@ -0,0 +1,5 @@
+
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+
+
diff --git a/general/datasets/Sa_m2_0405_r/experiment-design.rtf b/general/datasets/Sa_m2_0405_r/experiment-design.rtf
new file mode 100644
index 0000000..cb07f36
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_r/experiment-design.rtf
@@ -0,0 +1,5 @@
+RNA was extracted by Rosen and colleagues and was then processed by the BIDMC Genomics Core. Labeled cRNA was generated using the Amersham Biosciences cRNA synthesis kit protocol.
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one sample from each sex for all BXD strains. We have not yet achieved this goal. Twenty-three of 33 strains are represented by male and female samples. The remaining 8 strains are still represented by single sex samples: BXD11 (F), BXD13 (F), BXD19 (F), BXD20 (F), BXD22 (M), BXD23 (M), BXD24 (M), BXD32 (M), C57BL/6J (M), and DBA/2J (M).
+
+Batch Structure: This data set consists of arrays processed in three batches with several reruns for the first batch. All arrays were processed using a single protocol. All data have been corrected for batch effects as described below.
+
diff --git a/general/datasets/Sa_m2_0405_r/notes.rtf b/general/datasets/Sa_m2_0405_r/notes.rtf
new file mode 100644
index 0000000..0af01e6
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by GDR, RWW, and YHQ on Nov 2004. Updated by RWW Nov 17, 2004; GDR and RWW, Dec 23, 2004; RWW and GDR April 8, 2005.
+
diff --git a/general/datasets/Sa_m2_0405_r/platform.rtf b/general/datasets/Sa_m2_0405_r/platform.rtf
new file mode 100644
index 0000000..30c2f8c
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are near duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequence as the 430A and B series. However, we have found that roughy 75000 probes differ from those on A and B arrays.
+
diff --git a/general/datasets/Sa_m2_0405_r/processing.rtf b/general/datasets/Sa_m2_0405_r/processing.rtf
new file mode 100644
index 0000000..2e46796
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_r/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the batches at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels. Data quality control: A total of 62 samples passed RNA quality control.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients (62x61/2). Arrays with probe data that was not homogeneous when compared to any other arrays was flagged. If the correlation at the probe level was less than approximately 0.92 we deleted that array data set. Three arrays we lost during this process (BXD19_M_Str_Batch03, BXD23_F_Str_Batch03, and BXD24_F_Str_Batch03).
+
+Probe set level QC: The final normalized strain averages were evaluated for outliers. This involved counting the number of times that the probe set value for a particular strain was beyond two standard deviations of the mean of all strains. (We used the PDNN transform as our reference probe set data for this QC step.) Two strains, each represented by single arrays, generated greater than 5,000 outlier counts (10% of the number of probe sets). These two arrays generated a great number of outliers across the entire range of expression and since we do not yet have replicate arrays for either of these two strains we opted to delete them from the final April 2005 striatum data sets.
diff --git a/general/datasets/Sa_m2_0405_r/summary.rtf b/general/datasets/Sa_m2_0405_r/summary.rtf
new file mode 100644
index 0000000..e674c86
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_r/summary.rtf
@@ -0,0 +1 @@
+This April 2005 data freeze provides estimates of mRNA expression in the striatum (caudate nucleus of the forebrain) of 33 lines of mice including C57BL/6J, DBA/2J, and 31 BXD recombinant inbred strains. Data were generated using Affymetrix Mouse Genome 430 2.0 short oligomer microarrays at Beth Israel Deaconess Medical Center (BIDMC, Boston MA) by Glenn D. Rosen with the support of a Human Brain Project (HBP) grant. Approximately 250 brain samples (males and females) from 33 strains were used in this experiment. Samples were hybridized to a total of 59 arrays. This particular data set was processed using the Microarray Suite 5 protocol (MAS 5). To simplify comparison among different transforms, MAS5 values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Sa_m2_0405_r/tissue.rtf b/general/datasets/Sa_m2_0405_r/tissue.rtf
new file mode 100644
index 0000000..6503813
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_r/tissue.rtf
@@ -0,0 +1,440 @@
+
+Animals were obtained from The Jackson Laboratory and housed for several weeks at BIDMC until they reached ~2 months of age (range from 55 to 62 days). Mice were killed by cervical dislocation and brains were removed and placed in RNAlater for 20 to 25 minutes prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both striata were dissected using a medial approach by GD Rosen that typically yields 5 to 7 mg of tissue per side. The purity of this dissection has been validated by an analysis of acetylcholinestase activity. A pool of dissected tissue from 3 or 4 adults (approximately 25 to 30 mg of tissue) of the same strain, sex, and age was collected in one session and used to generate cRNA samples.
+
+
+The table below lists the arrays by strain, sex, sample name, and batch ID. Each array was hybridized to a pool of mRNA from 3 to 4 mice. All mice were between 55 and 62 days.
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Sample_name |
+ BatchId |
+
+
+ | 1 |
+ C57BL/6J |
+ M |
+ Chip41_Batch02_B6_M_Str |
+ Batch02 |
+
+
+ | 2 |
+ C57BL/6J |
+ M |
+ Chip11_Batch03_B6_M_Str |
+ Batch03 |
+
+
+ | 3 |
+ BXD1 |
+ F |
+ Chip03_Batch03_BXD1_F_Str |
+ Batch03 |
+
+
+ | 4 |
+ BXD1 |
+ M |
+ Chip04_Batch03_BXD1_M_Str |
+ Batch03 |
+
+
+ | 5 |
+ BXD2 |
+ F |
+ Chip20_Rerun01_BXD2_F_Str |
+ Rerun01 |
+
+
+ | 6 |
+ BXD2 |
+ M |
+ Chip05_Batch01_BXD2_M_Str |
+ Batch01 |
+
+
+ | 7 |
+ BXD5 |
+ F |
+ Chip10_Batch03_BXD5_F_Str |
+ Batch03 |
+
+
+ | 8 |
+ BXD5 |
+ M |
+ Chip12_Batch03_BXD5_M_Str |
+ Batch03 |
+
+
+ | 9 |
+ BXD6 |
+ F |
+ Chip38_Batch02_BXD6_F_Str |
+ Batch02 |
+
+
+ | 10 |
+ BXD6 |
+ M |
+ Chip39_Batch02_BXD6_M_Str |
+ Batch02 |
+
+
+ | 11 |
+ BXD8 |
+ F |
+ Chip07_Batch03_BXD8_F_Str |
+ Batch03 |
+
+
+ | 12 |
+ BXD8 |
+ M |
+ Chip02_Batch03_BXD8_M_Str |
+ Batch03 |
+
+
+ | 13 |
+ BXD9 |
+ F |
+ Chip16_Batch01_BXD9_F_Str |
+ Batch01 |
+
+
+ | 14 |
+ BXD9 |
+ M |
+ Chip10_Batch01_BXD9_M_Str |
+ Batch01 |
+
+
+ | 15 |
+ BXD11 |
+ F |
+ Chip31_Batch02_BXD11_F_Str |
+ Batch02 |
+
+
+ | 16 |
+ BXD12 |
+ F |
+ Chip11_Batch01_BXD12_F_Str |
+ Batch01 |
+
+
+ | 17 |
+ BXD12 |
+ M |
+ Chip18_Batch03_BXD12_M_Str |
+ Batch03 |
+
+
+ | 18 |
+ BXD13 |
+ F |
+ Chip33_Batch02_BXD13_F_Str |
+ Batch02 |
+
+
+ | 19 |
+ BXD14 |
+ F |
+ Chip48_Batch02_BXD14_F_Str |
+ Batch02 |
+
+
+ | 20 |
+ BXD14 |
+ M |
+ Chip47_Rerun01_BXD14_M_Str |
+ Rerun01 |
+
+
+ | 21 |
+ BXD15 |
+ F |
+ Chip21_Batch01_BXD15_F_Str |
+ Batch01 |
+
+
+ | 22 |
+ BXD15 |
+ M |
+ Chip13_Batch01_BXD15_M_Str |
+ Batch01 |
+
+
+ | 23 |
+ BXD16 |
+ F |
+ Chip36_Batch02_BXD16_F_Str |
+ Batch02 |
+
+
+ | 24 |
+ BXD16 |
+ M |
+ Chip44_Rerun01_BXD16_M_Str |
+ Rerun01 |
+
+
+ | 25 |
+ BXD18 |
+ F |
+ Chip15_Batch03_BXD18_F_Str |
+ Batch03 |
+
+
+ | 26 |
+ BXD18 |
+ M |
+ Chip19_Batch03_BXD18_M_Str |
+ Batch03 |
+
+
+ | 27 |
+ BXD19 |
+ F |
+ Chip19_Batch01_BXD19_F_Str |
+ Batch01 |
+
+
+ | 28 |
+ BXD20 |
+ F |
+ Chip14_Batch03_BXD20_F_Str |
+ Batch03 |
+
+
+ | 29 |
+ BXD21 |
+ F |
+ Chip18_Batch01_BXD21_F_Str |
+ Batch01 |
+
+
+ | 30 |
+ BXD21 |
+ M |
+ Chip09_Batch01_BXD21_M_Str |
+ Batch01 |
+
+
+ | 31 |
+ BXD22 |
+ M |
+ Chip13_Batch03_BXD22_M_Str |
+ Batch03 |
+
+
+ | 32 |
+ BXD23 |
+ M |
+ Chip01_Batch03_BXD23_M_Str |
+ Batch03 |
+
+
+ | 33 |
+ BXD24 |
+ M |
+ Chip17_Batch03_BXD24_M_Str |
+ Batch03 |
+
+
+ | 34 |
+ BXD27 |
+ F |
+ Chip29_Batch02_BXD27_F_Str |
+ Batch02 |
+
+
+ | 35 |
+ BXD27 |
+ M |
+ Chip40_Batch02_BXD27_M_Str |
+ Batch02 |
+
+
+ | 36 |
+ BXD28 |
+ F |
+ Chip06_Batch01_BXD28_F_Str |
+ Batch01 |
+
+
+ | 37 |
+ BXD28 |
+ M |
+ Chip23_Batch01_BXD28_M_Str |
+ Batch01 |
+
+
+ | 38 |
+ BXD29 |
+ F |
+ Chip45_Batch02_BXD29_F_Str |
+ Batch02 |
+
+
+ | 39 |
+ BXD29 |
+ M |
+ Chip42_Batch02_BXD29_M_Str |
+ Batch02 |
+
+
+ | 40 |
+ BXD31 |
+ F |
+ Chip14_Batch01_BXD31_F_Str |
+ Batch01 |
+
+
+ | 41 |
+ BXD31 |
+ M |
+ Chip09_Batch03_BXD31_M_Str |
+ Batch03 |
+
+
+ | 42 |
+ BXD32 |
+ M |
+ Chip30_Batch02_BXD32_M_Str |
+ Batch02 |
+
+
+ | 43 |
+ BXD33 |
+ F |
+ Chip27_Rerun01_BXD33_F_Str |
+ Rerun01 |
+
+
+ | 44 |
+ BXD33 |
+ M |
+ Chip34_Batch02_BXD33_M_Str |
+ Batch02 |
+
+
+ | 45 |
+ BXD34 |
+ F |
+ Chip03_Batch01_BXD34_F_Str |
+ Batch01 |
+
+
+ | 46 |
+ BXD34 |
+ M |
+ Chip07_Batch01_BXD34_M_Str |
+ Batch01 |
+
+
+ | 47 |
+ BXD36 |
+ F |
+ Chip22_Batch03_BXD36_F_Str |
+ Batch03 |
+
+
+ | 48 |
+ BXD36 |
+ M |
+ Chip24_Batch03_BXD36_M_Str |
+ Batch03 |
+
+
+ | 49 |
+ BXD38 |
+ F |
+ Chip17_Batch01_BXD38_F_Str |
+ Batch01 |
+
+
+ | 50 |
+ BXD38 |
+ M |
+ Chip24_Batch01_BXD38_M_Str |
+ Batch01 |
+
+
+ | 51 |
+ BXD39 |
+ M |
+ Chip20_Batch03_BXD39_M_Str |
+ Batch03 |
+
+
+ | 52 |
+ BXD39 |
+ F |
+ Chip23_Batch03_BXD39_F_Str |
+ Batch03 |
+
+
+ | 53 |
+ BXD39 |
+ M |
+ Chip43_Rerun01_BXD39_M_Str |
+ Rerun01 |
+
+
+ | 54 |
+ BXD40 |
+ F |
+ Chip08_Rerun01_BXD40_F_Str |
+ Rerun01 |
+
+
+ | 55 |
+ BXD40 |
+ M |
+ Chip22_Batch01_BXD40_M_Str |
+ Batch01 |
+
+
+ | 56 |
+ BXD42 |
+ F |
+ Chip35_Batch02_BXD42_F_Str |
+ Batch02 |
+
+
+ | 57 |
+ BXD42 |
+ M |
+ Chip32_Batch02_BXD42_M_Str |
+ Batch02 |
+
+
+ | 58 |
+ DBA/2J |
+ M |
+ Chip02_Batch01_D2_M_Str |
+ Batch01 |
+
+
+ | 59 |
+ DBA/2J |
+ M |
+ Chip05_Batch03_D2_M_Str |
+ Batch03 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Sa_m2_0405_rc/acknowledgment.rtf b/general/datasets/Sa_m2_0405_rc/acknowledgment.rtf
new file mode 100644
index 0000000..94eec11
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rc/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to Glenn Rosen from P20 MH62009 (see below for specifics). Samples and arrays were processed by the Genomics Core at Beth Israel Deaconess Medical Center by Towia Libermann and colleagues.
+
diff --git a/general/datasets/Sa_m2_0405_rc/cases.rtf b/general/datasets/Sa_m2_0405_rc/cases.rtf
new file mode 100644
index 0000000..491788f
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rc/cases.rtf
@@ -0,0 +1,5 @@
+
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+
+
diff --git a/general/datasets/Sa_m2_0405_rc/experiment-design.rtf b/general/datasets/Sa_m2_0405_rc/experiment-design.rtf
new file mode 100644
index 0000000..cb07f36
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rc/experiment-design.rtf
@@ -0,0 +1,5 @@
+RNA was extracted by Rosen and colleagues and was then processed by the BIDMC Genomics Core. Labeled cRNA was generated using the Amersham Biosciences cRNA synthesis kit protocol.
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one sample from each sex for all BXD strains. We have not yet achieved this goal. Twenty-three of 33 strains are represented by male and female samples. The remaining 8 strains are still represented by single sex samples: BXD11 (F), BXD13 (F), BXD19 (F), BXD20 (F), BXD22 (M), BXD23 (M), BXD24 (M), BXD32 (M), C57BL/6J (M), and DBA/2J (M).
+
+Batch Structure: This data set consists of arrays processed in three batches with several reruns for the first batch. All arrays were processed using a single protocol. All data have been corrected for batch effects as described below.
+
diff --git a/general/datasets/Sa_m2_0405_rc/notes.rtf b/general/datasets/Sa_m2_0405_rc/notes.rtf
new file mode 100644
index 0000000..0af01e6
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rc/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by GDR, RWW, and YHQ on Nov 2004. Updated by RWW Nov 17, 2004; GDR and RWW, Dec 23, 2004; RWW and GDR April 8, 2005.
+
diff --git a/general/datasets/Sa_m2_0405_rc/platform.rtf b/general/datasets/Sa_m2_0405_rc/platform.rtf
new file mode 100644
index 0000000..30c2f8c
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rc/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are near duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequence as the 430A and B series. However, we have found that roughy 75000 probes differ from those on A and B arrays.
+
diff --git a/general/datasets/Sa_m2_0405_rc/processing.rtf b/general/datasets/Sa_m2_0405_rc/processing.rtf
new file mode 100644
index 0000000..2e46796
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rc/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the batches at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels. Data quality control: A total of 62 samples passed RNA quality control.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients (62x61/2). Arrays with probe data that was not homogeneous when compared to any other arrays was flagged. If the correlation at the probe level was less than approximately 0.92 we deleted that array data set. Three arrays we lost during this process (BXD19_M_Str_Batch03, BXD23_F_Str_Batch03, and BXD24_F_Str_Batch03).
+
+Probe set level QC: The final normalized strain averages were evaluated for outliers. This involved counting the number of times that the probe set value for a particular strain was beyond two standard deviations of the mean of all strains. (We used the PDNN transform as our reference probe set data for this QC step.) Two strains, each represented by single arrays, generated greater than 5,000 outlier counts (10% of the number of probe sets). These two arrays generated a great number of outliers across the entire range of expression and since we do not yet have replicate arrays for either of these two strains we opted to delete them from the final April 2005 striatum data sets.
diff --git a/general/datasets/Sa_m2_0405_rc/summary.rtf b/general/datasets/Sa_m2_0405_rc/summary.rtf
new file mode 100644
index 0000000..e674c86
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rc/summary.rtf
@@ -0,0 +1 @@
+This April 2005 data freeze provides estimates of mRNA expression in the striatum (caudate nucleus of the forebrain) of 33 lines of mice including C57BL/6J, DBA/2J, and 31 BXD recombinant inbred strains. Data were generated using Affymetrix Mouse Genome 430 2.0 short oligomer microarrays at Beth Israel Deaconess Medical Center (BIDMC, Boston MA) by Glenn D. Rosen with the support of a Human Brain Project (HBP) grant. Approximately 250 brain samples (males and females) from 33 strains were used in this experiment. Samples were hybridized to a total of 59 arrays. This particular data set was processed using the Microarray Suite 5 protocol (MAS 5). To simplify comparison among different transforms, MAS5 values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Sa_m2_0405_rc/tissue.rtf b/general/datasets/Sa_m2_0405_rc/tissue.rtf
new file mode 100644
index 0000000..6503813
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rc/tissue.rtf
@@ -0,0 +1,440 @@
+
+Animals were obtained from The Jackson Laboratory and housed for several weeks at BIDMC until they reached ~2 months of age (range from 55 to 62 days). Mice were killed by cervical dislocation and brains were removed and placed in RNAlater for 20 to 25 minutes prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both striata were dissected using a medial approach by GD Rosen that typically yields 5 to 7 mg of tissue per side. The purity of this dissection has been validated by an analysis of acetylcholinestase activity. A pool of dissected tissue from 3 or 4 adults (approximately 25 to 30 mg of tissue) of the same strain, sex, and age was collected in one session and used to generate cRNA samples.
+
+
+The table below lists the arrays by strain, sex, sample name, and batch ID. Each array was hybridized to a pool of mRNA from 3 to 4 mice. All mice were between 55 and 62 days.
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Sample_name |
+ BatchId |
+
+
+ | 1 |
+ C57BL/6J |
+ M |
+ Chip41_Batch02_B6_M_Str |
+ Batch02 |
+
+
+ | 2 |
+ C57BL/6J |
+ M |
+ Chip11_Batch03_B6_M_Str |
+ Batch03 |
+
+
+ | 3 |
+ BXD1 |
+ F |
+ Chip03_Batch03_BXD1_F_Str |
+ Batch03 |
+
+
+ | 4 |
+ BXD1 |
+ M |
+ Chip04_Batch03_BXD1_M_Str |
+ Batch03 |
+
+
+ | 5 |
+ BXD2 |
+ F |
+ Chip20_Rerun01_BXD2_F_Str |
+ Rerun01 |
+
+
+ | 6 |
+ BXD2 |
+ M |
+ Chip05_Batch01_BXD2_M_Str |
+ Batch01 |
+
+
+ | 7 |
+ BXD5 |
+ F |
+ Chip10_Batch03_BXD5_F_Str |
+ Batch03 |
+
+
+ | 8 |
+ BXD5 |
+ M |
+ Chip12_Batch03_BXD5_M_Str |
+ Batch03 |
+
+
+ | 9 |
+ BXD6 |
+ F |
+ Chip38_Batch02_BXD6_F_Str |
+ Batch02 |
+
+
+ | 10 |
+ BXD6 |
+ M |
+ Chip39_Batch02_BXD6_M_Str |
+ Batch02 |
+
+
+ | 11 |
+ BXD8 |
+ F |
+ Chip07_Batch03_BXD8_F_Str |
+ Batch03 |
+
+
+ | 12 |
+ BXD8 |
+ M |
+ Chip02_Batch03_BXD8_M_Str |
+ Batch03 |
+
+
+ | 13 |
+ BXD9 |
+ F |
+ Chip16_Batch01_BXD9_F_Str |
+ Batch01 |
+
+
+ | 14 |
+ BXD9 |
+ M |
+ Chip10_Batch01_BXD9_M_Str |
+ Batch01 |
+
+
+ | 15 |
+ BXD11 |
+ F |
+ Chip31_Batch02_BXD11_F_Str |
+ Batch02 |
+
+
+ | 16 |
+ BXD12 |
+ F |
+ Chip11_Batch01_BXD12_F_Str |
+ Batch01 |
+
+
+ | 17 |
+ BXD12 |
+ M |
+ Chip18_Batch03_BXD12_M_Str |
+ Batch03 |
+
+
+ | 18 |
+ BXD13 |
+ F |
+ Chip33_Batch02_BXD13_F_Str |
+ Batch02 |
+
+
+ | 19 |
+ BXD14 |
+ F |
+ Chip48_Batch02_BXD14_F_Str |
+ Batch02 |
+
+
+ | 20 |
+ BXD14 |
+ M |
+ Chip47_Rerun01_BXD14_M_Str |
+ Rerun01 |
+
+
+ | 21 |
+ BXD15 |
+ F |
+ Chip21_Batch01_BXD15_F_Str |
+ Batch01 |
+
+
+ | 22 |
+ BXD15 |
+ M |
+ Chip13_Batch01_BXD15_M_Str |
+ Batch01 |
+
+
+ | 23 |
+ BXD16 |
+ F |
+ Chip36_Batch02_BXD16_F_Str |
+ Batch02 |
+
+
+ | 24 |
+ BXD16 |
+ M |
+ Chip44_Rerun01_BXD16_M_Str |
+ Rerun01 |
+
+
+ | 25 |
+ BXD18 |
+ F |
+ Chip15_Batch03_BXD18_F_Str |
+ Batch03 |
+
+
+ | 26 |
+ BXD18 |
+ M |
+ Chip19_Batch03_BXD18_M_Str |
+ Batch03 |
+
+
+ | 27 |
+ BXD19 |
+ F |
+ Chip19_Batch01_BXD19_F_Str |
+ Batch01 |
+
+
+ | 28 |
+ BXD20 |
+ F |
+ Chip14_Batch03_BXD20_F_Str |
+ Batch03 |
+
+
+ | 29 |
+ BXD21 |
+ F |
+ Chip18_Batch01_BXD21_F_Str |
+ Batch01 |
+
+
+ | 30 |
+ BXD21 |
+ M |
+ Chip09_Batch01_BXD21_M_Str |
+ Batch01 |
+
+
+ | 31 |
+ BXD22 |
+ M |
+ Chip13_Batch03_BXD22_M_Str |
+ Batch03 |
+
+
+ | 32 |
+ BXD23 |
+ M |
+ Chip01_Batch03_BXD23_M_Str |
+ Batch03 |
+
+
+ | 33 |
+ BXD24 |
+ M |
+ Chip17_Batch03_BXD24_M_Str |
+ Batch03 |
+
+
+ | 34 |
+ BXD27 |
+ F |
+ Chip29_Batch02_BXD27_F_Str |
+ Batch02 |
+
+
+ | 35 |
+ BXD27 |
+ M |
+ Chip40_Batch02_BXD27_M_Str |
+ Batch02 |
+
+
+ | 36 |
+ BXD28 |
+ F |
+ Chip06_Batch01_BXD28_F_Str |
+ Batch01 |
+
+
+ | 37 |
+ BXD28 |
+ M |
+ Chip23_Batch01_BXD28_M_Str |
+ Batch01 |
+
+
+ | 38 |
+ BXD29 |
+ F |
+ Chip45_Batch02_BXD29_F_Str |
+ Batch02 |
+
+
+ | 39 |
+ BXD29 |
+ M |
+ Chip42_Batch02_BXD29_M_Str |
+ Batch02 |
+
+
+ | 40 |
+ BXD31 |
+ F |
+ Chip14_Batch01_BXD31_F_Str |
+ Batch01 |
+
+
+ | 41 |
+ BXD31 |
+ M |
+ Chip09_Batch03_BXD31_M_Str |
+ Batch03 |
+
+
+ | 42 |
+ BXD32 |
+ M |
+ Chip30_Batch02_BXD32_M_Str |
+ Batch02 |
+
+
+ | 43 |
+ BXD33 |
+ F |
+ Chip27_Rerun01_BXD33_F_Str |
+ Rerun01 |
+
+
+ | 44 |
+ BXD33 |
+ M |
+ Chip34_Batch02_BXD33_M_Str |
+ Batch02 |
+
+
+ | 45 |
+ BXD34 |
+ F |
+ Chip03_Batch01_BXD34_F_Str |
+ Batch01 |
+
+
+ | 46 |
+ BXD34 |
+ M |
+ Chip07_Batch01_BXD34_M_Str |
+ Batch01 |
+
+
+ | 47 |
+ BXD36 |
+ F |
+ Chip22_Batch03_BXD36_F_Str |
+ Batch03 |
+
+
+ | 48 |
+ BXD36 |
+ M |
+ Chip24_Batch03_BXD36_M_Str |
+ Batch03 |
+
+
+ | 49 |
+ BXD38 |
+ F |
+ Chip17_Batch01_BXD38_F_Str |
+ Batch01 |
+
+
+ | 50 |
+ BXD38 |
+ M |
+ Chip24_Batch01_BXD38_M_Str |
+ Batch01 |
+
+
+ | 51 |
+ BXD39 |
+ M |
+ Chip20_Batch03_BXD39_M_Str |
+ Batch03 |
+
+
+ | 52 |
+ BXD39 |
+ F |
+ Chip23_Batch03_BXD39_F_Str |
+ Batch03 |
+
+
+ | 53 |
+ BXD39 |
+ M |
+ Chip43_Rerun01_BXD39_M_Str |
+ Rerun01 |
+
+
+ | 54 |
+ BXD40 |
+ F |
+ Chip08_Rerun01_BXD40_F_Str |
+ Rerun01 |
+
+
+ | 55 |
+ BXD40 |
+ M |
+ Chip22_Batch01_BXD40_M_Str |
+ Batch01 |
+
+
+ | 56 |
+ BXD42 |
+ F |
+ Chip35_Batch02_BXD42_F_Str |
+ Batch02 |
+
+
+ | 57 |
+ BXD42 |
+ M |
+ Chip32_Batch02_BXD42_M_Str |
+ Batch02 |
+
+
+ | 58 |
+ DBA/2J |
+ M |
+ Chip02_Batch01_D2_M_Str |
+ Batch01 |
+
+
+ | 59 |
+ DBA/2J |
+ M |
+ Chip05_Batch03_D2_M_Str |
+ Batch03 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Sa_m2_0405_rr/acknowledgment.rtf b/general/datasets/Sa_m2_0405_rr/acknowledgment.rtf
new file mode 100644
index 0000000..94eec11
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rr/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to Glenn Rosen from P20 MH62009 (see below for specifics). Samples and arrays were processed by the Genomics Core at Beth Israel Deaconess Medical Center by Towia Libermann and colleagues.
+
diff --git a/general/datasets/Sa_m2_0405_rr/cases.rtf b/general/datasets/Sa_m2_0405_rr/cases.rtf
new file mode 100644
index 0000000..491788f
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rr/cases.rtf
@@ -0,0 +1,5 @@
+
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+
+
diff --git a/general/datasets/Sa_m2_0405_rr/experiment-design.rtf b/general/datasets/Sa_m2_0405_rr/experiment-design.rtf
new file mode 100644
index 0000000..cb07f36
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rr/experiment-design.rtf
@@ -0,0 +1,5 @@
+RNA was extracted by Rosen and colleagues and was then processed by the BIDMC Genomics Core. Labeled cRNA was generated using the Amersham Biosciences cRNA synthesis kit protocol.
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one sample from each sex for all BXD strains. We have not yet achieved this goal. Twenty-three of 33 strains are represented by male and female samples. The remaining 8 strains are still represented by single sex samples: BXD11 (F), BXD13 (F), BXD19 (F), BXD20 (F), BXD22 (M), BXD23 (M), BXD24 (M), BXD32 (M), C57BL/6J (M), and DBA/2J (M).
+
+Batch Structure: This data set consists of arrays processed in three batches with several reruns for the first batch. All arrays were processed using a single protocol. All data have been corrected for batch effects as described below.
+
diff --git a/general/datasets/Sa_m2_0405_rr/notes.rtf b/general/datasets/Sa_m2_0405_rr/notes.rtf
new file mode 100644
index 0000000..0af01e6
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rr/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by GDR, RWW, and YHQ on Nov 2004. Updated by RWW Nov 17, 2004; GDR and RWW, Dec 23, 2004; RWW and GDR April 8, 2005.
+
diff --git a/general/datasets/Sa_m2_0405_rr/platform.rtf b/general/datasets/Sa_m2_0405_rr/platform.rtf
new file mode 100644
index 0000000..30c2f8c
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rr/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are near duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequence as the 430A and B series. However, we have found that roughy 75000 probes differ from those on A and B arrays.
+
diff --git a/general/datasets/Sa_m2_0405_rr/processing.rtf b/general/datasets/Sa_m2_0405_rr/processing.rtf
new file mode 100644
index 0000000..2e46796
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rr/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the batches at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels. Data quality control: A total of 62 samples passed RNA quality control.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients (62x61/2). Arrays with probe data that was not homogeneous when compared to any other arrays was flagged. If the correlation at the probe level was less than approximately 0.92 we deleted that array data set. Three arrays we lost during this process (BXD19_M_Str_Batch03, BXD23_F_Str_Batch03, and BXD24_F_Str_Batch03).
+
+Probe set level QC: The final normalized strain averages were evaluated for outliers. This involved counting the number of times that the probe set value for a particular strain was beyond two standard deviations of the mean of all strains. (We used the PDNN transform as our reference probe set data for this QC step.) Two strains, each represented by single arrays, generated greater than 5,000 outlier counts (10% of the number of probe sets). These two arrays generated a great number of outliers across the entire range of expression and since we do not yet have replicate arrays for either of these two strains we opted to delete them from the final April 2005 striatum data sets.
diff --git a/general/datasets/Sa_m2_0405_rr/summary.rtf b/general/datasets/Sa_m2_0405_rr/summary.rtf
new file mode 100644
index 0000000..e674c86
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rr/summary.rtf
@@ -0,0 +1 @@
+This April 2005 data freeze provides estimates of mRNA expression in the striatum (caudate nucleus of the forebrain) of 33 lines of mice including C57BL/6J, DBA/2J, and 31 BXD recombinant inbred strains. Data were generated using Affymetrix Mouse Genome 430 2.0 short oligomer microarrays at Beth Israel Deaconess Medical Center (BIDMC, Boston MA) by Glenn D. Rosen with the support of a Human Brain Project (HBP) grant. Approximately 250 brain samples (males and females) from 33 strains were used in this experiment. Samples were hybridized to a total of 59 arrays. This particular data set was processed using the Microarray Suite 5 protocol (MAS 5). To simplify comparison among different transforms, MAS5 values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Sa_m2_0405_rr/tissue.rtf b/general/datasets/Sa_m2_0405_rr/tissue.rtf
new file mode 100644
index 0000000..6503813
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_rr/tissue.rtf
@@ -0,0 +1,440 @@
+
+Animals were obtained from The Jackson Laboratory and housed for several weeks at BIDMC until they reached ~2 months of age (range from 55 to 62 days). Mice were killed by cervical dislocation and brains were removed and placed in RNAlater for 20 to 25 minutes prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both striata were dissected using a medial approach by GD Rosen that typically yields 5 to 7 mg of tissue per side. The purity of this dissection has been validated by an analysis of acetylcholinestase activity. A pool of dissected tissue from 3 or 4 adults (approximately 25 to 30 mg of tissue) of the same strain, sex, and age was collected in one session and used to generate cRNA samples.
+
+
+The table below lists the arrays by strain, sex, sample name, and batch ID. Each array was hybridized to a pool of mRNA from 3 to 4 mice. All mice were between 55 and 62 days.
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Sample_name |
+ BatchId |
+
+
+ | 1 |
+ C57BL/6J |
+ M |
+ Chip41_Batch02_B6_M_Str |
+ Batch02 |
+
+
+ | 2 |
+ C57BL/6J |
+ M |
+ Chip11_Batch03_B6_M_Str |
+ Batch03 |
+
+
+ | 3 |
+ BXD1 |
+ F |
+ Chip03_Batch03_BXD1_F_Str |
+ Batch03 |
+
+
+ | 4 |
+ BXD1 |
+ M |
+ Chip04_Batch03_BXD1_M_Str |
+ Batch03 |
+
+
+ | 5 |
+ BXD2 |
+ F |
+ Chip20_Rerun01_BXD2_F_Str |
+ Rerun01 |
+
+
+ | 6 |
+ BXD2 |
+ M |
+ Chip05_Batch01_BXD2_M_Str |
+ Batch01 |
+
+
+ | 7 |
+ BXD5 |
+ F |
+ Chip10_Batch03_BXD5_F_Str |
+ Batch03 |
+
+
+ | 8 |
+ BXD5 |
+ M |
+ Chip12_Batch03_BXD5_M_Str |
+ Batch03 |
+
+
+ | 9 |
+ BXD6 |
+ F |
+ Chip38_Batch02_BXD6_F_Str |
+ Batch02 |
+
+
+ | 10 |
+ BXD6 |
+ M |
+ Chip39_Batch02_BXD6_M_Str |
+ Batch02 |
+
+
+ | 11 |
+ BXD8 |
+ F |
+ Chip07_Batch03_BXD8_F_Str |
+ Batch03 |
+
+
+ | 12 |
+ BXD8 |
+ M |
+ Chip02_Batch03_BXD8_M_Str |
+ Batch03 |
+
+
+ | 13 |
+ BXD9 |
+ F |
+ Chip16_Batch01_BXD9_F_Str |
+ Batch01 |
+
+
+ | 14 |
+ BXD9 |
+ M |
+ Chip10_Batch01_BXD9_M_Str |
+ Batch01 |
+
+
+ | 15 |
+ BXD11 |
+ F |
+ Chip31_Batch02_BXD11_F_Str |
+ Batch02 |
+
+
+ | 16 |
+ BXD12 |
+ F |
+ Chip11_Batch01_BXD12_F_Str |
+ Batch01 |
+
+
+ | 17 |
+ BXD12 |
+ M |
+ Chip18_Batch03_BXD12_M_Str |
+ Batch03 |
+
+
+ | 18 |
+ BXD13 |
+ F |
+ Chip33_Batch02_BXD13_F_Str |
+ Batch02 |
+
+
+ | 19 |
+ BXD14 |
+ F |
+ Chip48_Batch02_BXD14_F_Str |
+ Batch02 |
+
+
+ | 20 |
+ BXD14 |
+ M |
+ Chip47_Rerun01_BXD14_M_Str |
+ Rerun01 |
+
+
+ | 21 |
+ BXD15 |
+ F |
+ Chip21_Batch01_BXD15_F_Str |
+ Batch01 |
+
+
+ | 22 |
+ BXD15 |
+ M |
+ Chip13_Batch01_BXD15_M_Str |
+ Batch01 |
+
+
+ | 23 |
+ BXD16 |
+ F |
+ Chip36_Batch02_BXD16_F_Str |
+ Batch02 |
+
+
+ | 24 |
+ BXD16 |
+ M |
+ Chip44_Rerun01_BXD16_M_Str |
+ Rerun01 |
+
+
+ | 25 |
+ BXD18 |
+ F |
+ Chip15_Batch03_BXD18_F_Str |
+ Batch03 |
+
+
+ | 26 |
+ BXD18 |
+ M |
+ Chip19_Batch03_BXD18_M_Str |
+ Batch03 |
+
+
+ | 27 |
+ BXD19 |
+ F |
+ Chip19_Batch01_BXD19_F_Str |
+ Batch01 |
+
+
+ | 28 |
+ BXD20 |
+ F |
+ Chip14_Batch03_BXD20_F_Str |
+ Batch03 |
+
+
+ | 29 |
+ BXD21 |
+ F |
+ Chip18_Batch01_BXD21_F_Str |
+ Batch01 |
+
+
+ | 30 |
+ BXD21 |
+ M |
+ Chip09_Batch01_BXD21_M_Str |
+ Batch01 |
+
+
+ | 31 |
+ BXD22 |
+ M |
+ Chip13_Batch03_BXD22_M_Str |
+ Batch03 |
+
+
+ | 32 |
+ BXD23 |
+ M |
+ Chip01_Batch03_BXD23_M_Str |
+ Batch03 |
+
+
+ | 33 |
+ BXD24 |
+ M |
+ Chip17_Batch03_BXD24_M_Str |
+ Batch03 |
+
+
+ | 34 |
+ BXD27 |
+ F |
+ Chip29_Batch02_BXD27_F_Str |
+ Batch02 |
+
+
+ | 35 |
+ BXD27 |
+ M |
+ Chip40_Batch02_BXD27_M_Str |
+ Batch02 |
+
+
+ | 36 |
+ BXD28 |
+ F |
+ Chip06_Batch01_BXD28_F_Str |
+ Batch01 |
+
+
+ | 37 |
+ BXD28 |
+ M |
+ Chip23_Batch01_BXD28_M_Str |
+ Batch01 |
+
+
+ | 38 |
+ BXD29 |
+ F |
+ Chip45_Batch02_BXD29_F_Str |
+ Batch02 |
+
+
+ | 39 |
+ BXD29 |
+ M |
+ Chip42_Batch02_BXD29_M_Str |
+ Batch02 |
+
+
+ | 40 |
+ BXD31 |
+ F |
+ Chip14_Batch01_BXD31_F_Str |
+ Batch01 |
+
+
+ | 41 |
+ BXD31 |
+ M |
+ Chip09_Batch03_BXD31_M_Str |
+ Batch03 |
+
+
+ | 42 |
+ BXD32 |
+ M |
+ Chip30_Batch02_BXD32_M_Str |
+ Batch02 |
+
+
+ | 43 |
+ BXD33 |
+ F |
+ Chip27_Rerun01_BXD33_F_Str |
+ Rerun01 |
+
+
+ | 44 |
+ BXD33 |
+ M |
+ Chip34_Batch02_BXD33_M_Str |
+ Batch02 |
+
+
+ | 45 |
+ BXD34 |
+ F |
+ Chip03_Batch01_BXD34_F_Str |
+ Batch01 |
+
+
+ | 46 |
+ BXD34 |
+ M |
+ Chip07_Batch01_BXD34_M_Str |
+ Batch01 |
+
+
+ | 47 |
+ BXD36 |
+ F |
+ Chip22_Batch03_BXD36_F_Str |
+ Batch03 |
+
+
+ | 48 |
+ BXD36 |
+ M |
+ Chip24_Batch03_BXD36_M_Str |
+ Batch03 |
+
+
+ | 49 |
+ BXD38 |
+ F |
+ Chip17_Batch01_BXD38_F_Str |
+ Batch01 |
+
+
+ | 50 |
+ BXD38 |
+ M |
+ Chip24_Batch01_BXD38_M_Str |
+ Batch01 |
+
+
+ | 51 |
+ BXD39 |
+ M |
+ Chip20_Batch03_BXD39_M_Str |
+ Batch03 |
+
+
+ | 52 |
+ BXD39 |
+ F |
+ Chip23_Batch03_BXD39_F_Str |
+ Batch03 |
+
+
+ | 53 |
+ BXD39 |
+ M |
+ Chip43_Rerun01_BXD39_M_Str |
+ Rerun01 |
+
+
+ | 54 |
+ BXD40 |
+ F |
+ Chip08_Rerun01_BXD40_F_Str |
+ Rerun01 |
+
+
+ | 55 |
+ BXD40 |
+ M |
+ Chip22_Batch01_BXD40_M_Str |
+ Batch01 |
+
+
+ | 56 |
+ BXD42 |
+ F |
+ Chip35_Batch02_BXD42_F_Str |
+ Batch02 |
+
+
+ | 57 |
+ BXD42 |
+ M |
+ Chip32_Batch02_BXD42_M_Str |
+ Batch02 |
+
+
+ | 58 |
+ DBA/2J |
+ M |
+ Chip02_Batch01_D2_M_Str |
+ Batch01 |
+
+
+ | 59 |
+ DBA/2J |
+ M |
+ Chip05_Batch03_D2_M_Str |
+ Batch03 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Sa_m2_0405_ss/acknowledgment.rtf b/general/datasets/Sa_m2_0405_ss/acknowledgment.rtf
new file mode 100644
index 0000000..94eec11
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_ss/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to Glenn Rosen from P20 MH62009 (see below for specifics). Samples and arrays were processed by the Genomics Core at Beth Israel Deaconess Medical Center by Towia Libermann and colleagues.
+
diff --git a/general/datasets/Sa_m2_0405_ss/cases.rtf b/general/datasets/Sa_m2_0405_ss/cases.rtf
new file mode 100644
index 0000000..491788f
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_ss/cases.rtf
@@ -0,0 +1,5 @@
+
+We have used a set of BXD recombinant inbred strains generated by crossing C57BL/6J (B6 or B) with DBA/2J (D2 or D). The BXDs are particularly useful for systems genetics because both parental strains have been sequenced (8x coverage of B6 and 1.5x coverage for D). Physical maps in WebQTL incorporate approximately 1.75 million B vs D SNPs from Celera. BXD2 through BXD32 were bred by Benjamin A. Taylor starting in the late 1970s. BXD33 through 42 were bred by Taylor in the 1990s. These strains are available from The Jackson Laboratory.
+
+
+
diff --git a/general/datasets/Sa_m2_0405_ss/experiment-design.rtf b/general/datasets/Sa_m2_0405_ss/experiment-design.rtf
new file mode 100644
index 0000000..cb07f36
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_ss/experiment-design.rtf
@@ -0,0 +1,5 @@
+RNA was extracted by Rosen and colleagues and was then processed by the BIDMC Genomics Core. Labeled cRNA was generated using the Amersham Biosciences cRNA synthesis kit protocol.
+Replication and Sample Balance: Our goal is to obtain data for independent biological sample pools from at least one sample from each sex for all BXD strains. We have not yet achieved this goal. Twenty-three of 33 strains are represented by male and female samples. The remaining 8 strains are still represented by single sex samples: BXD11 (F), BXD13 (F), BXD19 (F), BXD20 (F), BXD22 (M), BXD23 (M), BXD24 (M), BXD32 (M), C57BL/6J (M), and DBA/2J (M).
+
+Batch Structure: This data set consists of arrays processed in three batches with several reruns for the first batch. All arrays were processed using a single protocol. All data have been corrected for batch effects as described below.
+
diff --git a/general/datasets/Sa_m2_0405_ss/notes.rtf b/general/datasets/Sa_m2_0405_ss/notes.rtf
new file mode 100644
index 0000000..0af01e6
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_ss/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by GDR, RWW, and YHQ on Nov 2004. Updated by RWW Nov 17, 2004; GDR and RWW, Dec 23, 2004; RWW and GDR April 8, 2005.
+
diff --git a/general/datasets/Sa_m2_0405_ss/platform.rtf b/general/datasets/Sa_m2_0405_ss/platform.rtf
new file mode 100644
index 0000000..30c2f8c
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_ss/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are near duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequence as the 430A and B series. However, we have found that roughy 75000 probes differ from those on A and B arrays.
+
diff --git a/general/datasets/Sa_m2_0405_ss/processing.rtf b/general/datasets/Sa_m2_0405_ss/processing.rtf
new file mode 100644
index 0000000..2e46796
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_ss/processing.rtf
@@ -0,0 +1,17 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell.
+
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We performed a quantile normalization of the log base 2 values for the total set of 105 arrays (processed as two batches) using the same initial steps used by the RMA transform.
+ - Step 3: We computed the Z scores for each cell value.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We eliminated much of the systematic technical variance introduced by the batches at the probe level. To do this we calculated the ratio of each batch mean to the mean of both batches and used this as a single multiplicative probe-specific batch correction factor. The consequence of this simple correction is that the mean probe signal value for each batch is the same.
+ - Step 7: Finally, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples. Note, that we have not (yet) corrected for variance introduced by differences in sex or any interaction terms. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file. We eventually hope to add statistical controls and adjustments for some of these variables.
+
+
+Probe set data: The expression data were processed by Yanhua Qu (UTHSC). Probe set data were generated from the fully normalized CEL files (quantile and batch corrected) using the standard MAS 5 Tukey biweight procedure. A 1-unit difference represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels. Data quality control: A total of 62 samples passed RNA quality control.
+
+Probe level QC: Log2 probe data of all arrays were inspected in DataDesk before and after quantile normalization. Inspection involved examining scatterplots of pairs of arrays for signal homogeneity (i.e., high correlation and linearity of the bivariate plots) and looking at all pairs of correlation coefficients (62x61/2). Arrays with probe data that was not homogeneous when compared to any other arrays was flagged. If the correlation at the probe level was less than approximately 0.92 we deleted that array data set. Three arrays we lost during this process (BXD19_M_Str_Batch03, BXD23_F_Str_Batch03, and BXD24_F_Str_Batch03).
+
+Probe set level QC: The final normalized strain averages were evaluated for outliers. This involved counting the number of times that the probe set value for a particular strain was beyond two standard deviations of the mean of all strains. (We used the PDNN transform as our reference probe set data for this QC step.) Two strains, each represented by single arrays, generated greater than 5,000 outlier counts (10% of the number of probe sets). These two arrays generated a great number of outliers across the entire range of expression and since we do not yet have replicate arrays for either of these two strains we opted to delete them from the final April 2005 striatum data sets.
diff --git a/general/datasets/Sa_m2_0405_ss/summary.rtf b/general/datasets/Sa_m2_0405_ss/summary.rtf
new file mode 100644
index 0000000..e674c86
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_ss/summary.rtf
@@ -0,0 +1 @@
+This April 2005 data freeze provides estimates of mRNA expression in the striatum (caudate nucleus of the forebrain) of 33 lines of mice including C57BL/6J, DBA/2J, and 31 BXD recombinant inbred strains. Data were generated using Affymetrix Mouse Genome 430 2.0 short oligomer microarrays at Beth Israel Deaconess Medical Center (BIDMC, Boston MA) by Glenn D. Rosen with the support of a Human Brain Project (HBP) grant. Approximately 250 brain samples (males and females) from 33 strains were used in this experiment. Samples were hybridized to a total of 59 arrays. This particular data set was processed using the Microarray Suite 5 protocol (MAS 5). To simplify comparison among different transforms, MAS5 values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units.
diff --git a/general/datasets/Sa_m2_0405_ss/tissue.rtf b/general/datasets/Sa_m2_0405_ss/tissue.rtf
new file mode 100644
index 0000000..6503813
--- /dev/null
+++ b/general/datasets/Sa_m2_0405_ss/tissue.rtf
@@ -0,0 +1,440 @@
+
+Animals were obtained from The Jackson Laboratory and housed for several weeks at BIDMC until they reached ~2 months of age (range from 55 to 62 days). Mice were killed by cervical dislocation and brains were removed and placed in RNAlater for 20 to 25 minutes prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both striata were dissected using a medial approach by GD Rosen that typically yields 5 to 7 mg of tissue per side. The purity of this dissection has been validated by an analysis of acetylcholinestase activity. A pool of dissected tissue from 3 or 4 adults (approximately 25 to 30 mg of tissue) of the same strain, sex, and age was collected in one session and used to generate cRNA samples.
+
+
+The table below lists the arrays by strain, sex, sample name, and batch ID. Each array was hybridized to a pool of mRNA from 3 to 4 mice. All mice were between 55 and 62 days.
+
+
+
+
+
+
+
+
+
+ | Id |
+ Strain |
+ Sex |
+ Sample_name |
+ BatchId |
+
+
+ | 1 |
+ C57BL/6J |
+ M |
+ Chip41_Batch02_B6_M_Str |
+ Batch02 |
+
+
+ | 2 |
+ C57BL/6J |
+ M |
+ Chip11_Batch03_B6_M_Str |
+ Batch03 |
+
+
+ | 3 |
+ BXD1 |
+ F |
+ Chip03_Batch03_BXD1_F_Str |
+ Batch03 |
+
+
+ | 4 |
+ BXD1 |
+ M |
+ Chip04_Batch03_BXD1_M_Str |
+ Batch03 |
+
+
+ | 5 |
+ BXD2 |
+ F |
+ Chip20_Rerun01_BXD2_F_Str |
+ Rerun01 |
+
+
+ | 6 |
+ BXD2 |
+ M |
+ Chip05_Batch01_BXD2_M_Str |
+ Batch01 |
+
+
+ | 7 |
+ BXD5 |
+ F |
+ Chip10_Batch03_BXD5_F_Str |
+ Batch03 |
+
+
+ | 8 |
+ BXD5 |
+ M |
+ Chip12_Batch03_BXD5_M_Str |
+ Batch03 |
+
+
+ | 9 |
+ BXD6 |
+ F |
+ Chip38_Batch02_BXD6_F_Str |
+ Batch02 |
+
+
+ | 10 |
+ BXD6 |
+ M |
+ Chip39_Batch02_BXD6_M_Str |
+ Batch02 |
+
+
+ | 11 |
+ BXD8 |
+ F |
+ Chip07_Batch03_BXD8_F_Str |
+ Batch03 |
+
+
+ | 12 |
+ BXD8 |
+ M |
+ Chip02_Batch03_BXD8_M_Str |
+ Batch03 |
+
+
+ | 13 |
+ BXD9 |
+ F |
+ Chip16_Batch01_BXD9_F_Str |
+ Batch01 |
+
+
+ | 14 |
+ BXD9 |
+ M |
+ Chip10_Batch01_BXD9_M_Str |
+ Batch01 |
+
+
+ | 15 |
+ BXD11 |
+ F |
+ Chip31_Batch02_BXD11_F_Str |
+ Batch02 |
+
+
+ | 16 |
+ BXD12 |
+ F |
+ Chip11_Batch01_BXD12_F_Str |
+ Batch01 |
+
+
+ | 17 |
+ BXD12 |
+ M |
+ Chip18_Batch03_BXD12_M_Str |
+ Batch03 |
+
+
+ | 18 |
+ BXD13 |
+ F |
+ Chip33_Batch02_BXD13_F_Str |
+ Batch02 |
+
+
+ | 19 |
+ BXD14 |
+ F |
+ Chip48_Batch02_BXD14_F_Str |
+ Batch02 |
+
+
+ | 20 |
+ BXD14 |
+ M |
+ Chip47_Rerun01_BXD14_M_Str |
+ Rerun01 |
+
+
+ | 21 |
+ BXD15 |
+ F |
+ Chip21_Batch01_BXD15_F_Str |
+ Batch01 |
+
+
+ | 22 |
+ BXD15 |
+ M |
+ Chip13_Batch01_BXD15_M_Str |
+ Batch01 |
+
+
+ | 23 |
+ BXD16 |
+ F |
+ Chip36_Batch02_BXD16_F_Str |
+ Batch02 |
+
+
+ | 24 |
+ BXD16 |
+ M |
+ Chip44_Rerun01_BXD16_M_Str |
+ Rerun01 |
+
+
+ | 25 |
+ BXD18 |
+ F |
+ Chip15_Batch03_BXD18_F_Str |
+ Batch03 |
+
+
+ | 26 |
+ BXD18 |
+ M |
+ Chip19_Batch03_BXD18_M_Str |
+ Batch03 |
+
+
+ | 27 |
+ BXD19 |
+ F |
+ Chip19_Batch01_BXD19_F_Str |
+ Batch01 |
+
+
+ | 28 |
+ BXD20 |
+ F |
+ Chip14_Batch03_BXD20_F_Str |
+ Batch03 |
+
+
+ | 29 |
+ BXD21 |
+ F |
+ Chip18_Batch01_BXD21_F_Str |
+ Batch01 |
+
+
+ | 30 |
+ BXD21 |
+ M |
+ Chip09_Batch01_BXD21_M_Str |
+ Batch01 |
+
+
+ | 31 |
+ BXD22 |
+ M |
+ Chip13_Batch03_BXD22_M_Str |
+ Batch03 |
+
+
+ | 32 |
+ BXD23 |
+ M |
+ Chip01_Batch03_BXD23_M_Str |
+ Batch03 |
+
+
+ | 33 |
+ BXD24 |
+ M |
+ Chip17_Batch03_BXD24_M_Str |
+ Batch03 |
+
+
+ | 34 |
+ BXD27 |
+ F |
+ Chip29_Batch02_BXD27_F_Str |
+ Batch02 |
+
+
+ | 35 |
+ BXD27 |
+ M |
+ Chip40_Batch02_BXD27_M_Str |
+ Batch02 |
+
+
+ | 36 |
+ BXD28 |
+ F |
+ Chip06_Batch01_BXD28_F_Str |
+ Batch01 |
+
+
+ | 37 |
+ BXD28 |
+ M |
+ Chip23_Batch01_BXD28_M_Str |
+ Batch01 |
+
+
+ | 38 |
+ BXD29 |
+ F |
+ Chip45_Batch02_BXD29_F_Str |
+ Batch02 |
+
+
+ | 39 |
+ BXD29 |
+ M |
+ Chip42_Batch02_BXD29_M_Str |
+ Batch02 |
+
+
+ | 40 |
+ BXD31 |
+ F |
+ Chip14_Batch01_BXD31_F_Str |
+ Batch01 |
+
+
+ | 41 |
+ BXD31 |
+ M |
+ Chip09_Batch03_BXD31_M_Str |
+ Batch03 |
+
+
+ | 42 |
+ BXD32 |
+ M |
+ Chip30_Batch02_BXD32_M_Str |
+ Batch02 |
+
+
+ | 43 |
+ BXD33 |
+ F |
+ Chip27_Rerun01_BXD33_F_Str |
+ Rerun01 |
+
+
+ | 44 |
+ BXD33 |
+ M |
+ Chip34_Batch02_BXD33_M_Str |
+ Batch02 |
+
+
+ | 45 |
+ BXD34 |
+ F |
+ Chip03_Batch01_BXD34_F_Str |
+ Batch01 |
+
+
+ | 46 |
+ BXD34 |
+ M |
+ Chip07_Batch01_BXD34_M_Str |
+ Batch01 |
+
+
+ | 47 |
+ BXD36 |
+ F |
+ Chip22_Batch03_BXD36_F_Str |
+ Batch03 |
+
+
+ | 48 |
+ BXD36 |
+ M |
+ Chip24_Batch03_BXD36_M_Str |
+ Batch03 |
+
+
+ | 49 |
+ BXD38 |
+ F |
+ Chip17_Batch01_BXD38_F_Str |
+ Batch01 |
+
+
+ | 50 |
+ BXD38 |
+ M |
+ Chip24_Batch01_BXD38_M_Str |
+ Batch01 |
+
+
+ | 51 |
+ BXD39 |
+ M |
+ Chip20_Batch03_BXD39_M_Str |
+ Batch03 |
+
+
+ | 52 |
+ BXD39 |
+ F |
+ Chip23_Batch03_BXD39_F_Str |
+ Batch03 |
+
+
+ | 53 |
+ BXD39 |
+ M |
+ Chip43_Rerun01_BXD39_M_Str |
+ Rerun01 |
+
+
+ | 54 |
+ BXD40 |
+ F |
+ Chip08_Rerun01_BXD40_F_Str |
+ Rerun01 |
+
+
+ | 55 |
+ BXD40 |
+ M |
+ Chip22_Batch01_BXD40_M_Str |
+ Batch01 |
+
+
+ | 56 |
+ BXD42 |
+ F |
+ Chip35_Batch02_BXD42_F_Str |
+ Batch02 |
+
+
+ | 57 |
+ BXD42 |
+ M |
+ Chip32_Batch02_BXD42_M_Str |
+ Batch02 |
+
+
+ | 58 |
+ DBA/2J |
+ M |
+ Chip02_Batch01_D2_M_Str |
+ Batch01 |
+
+
+ | 59 |
+ DBA/2J |
+ M |
+ Chip05_Batch03_D2_M_Str |
+ Batch03 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Sa_m2_0905_m/acknowledgment.rtf b/general/datasets/Sa_m2_0905_m/acknowledgment.rtf
new file mode 100644
index 0000000..e7f05c1
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_m/acknowledgment.rtf
@@ -0,0 +1,5 @@
+
+This project was supported by two Department of Veterans Affairs Merit Review Awards (to JK Belknap and R Hitzemann, respectively), AA10760 (Portland Alcohol Research Center), AA06243, AA13484, AA11034, DA05228 and MH51372.
+
+Please contact either John Belknap or Robert Hitzemann at the Dept. of Behavioral Neuroscience, Oregon Health & Science University (L470), or Research Service (R&D5), Portland VA Medical Ctr., Portland, OR 97239 USA.
+
diff --git a/general/datasets/Sa_m2_0905_m/cases.rtf b/general/datasets/Sa_m2_0905_m/cases.rtf
new file mode 100644
index 0000000..4f69ca9
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_m/cases.rtf
@@ -0,0 +1,3 @@
+Fifty-six B6D2F2 samples, each taken from a single brain hemisphere from an individual mouse, were assayed using 56 M430A&B Affymetrix short oligomer microarrays. [The remaining hemisphere will be used later for an anaysis of specific brain regions.] Each array ID (see table below) includes a three letter code; the first letter usually denotes sex of the case (note that we have made a few corrections and there are therefore several sex-discordant IDs), the second letter denotes the hemisphere (R or L), and the third letter is the mouse number within each cell. The F2 mice were experimentally naive, born within a 3-day period from second litters of each dam, and housed at weaning (20- to 24-days-of-age) in like-sex groups of 3 to 4 mice for females and 2 to 3 mice for males in standard mouse shoebox cages within Thoren racks. All 56 F2 mice were killed at 77 to 79 days-of-age by cervical dislocation on December 17, 2003. The brains were immediately split at the midline and then quickly frozen on dry ice. The brains were stored for about two weeks at -80 degrees C until further use.
+
+The F2 was derived as follows: C57BL/6J (B6) and DBA/2J (D2) breeders were obtained from The Jackson Laboratory, and two generations later their progeny were crossed to produce B6D2F1 and D2B6F1 hybrid at the Portland VA Veterinary Medical Unit (AAALAC approved). The reciprocal F1s were mated to create an F2 population with both progenitor X and Y chromosomes about equally represented.
diff --git a/general/datasets/Sa_m2_0905_m/citation.rtf b/general/datasets/Sa_m2_0905_m/citation.rtf
new file mode 100644
index 0000000..8e8e73d
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_m/citation.rtf
@@ -0,0 +1,15 @@
+
+Hitzemann R, Reed C, Malmanger B, Lawler M, Hitzemann B, Cunningham B, McWeeney S, Belknap J, Harrington C, Buck K, Phillips T, Crabbe J. (2004) On the integration of alcohol-related quantitative trait loci and gene expression analyses.. Alcohol Clin Exp Res. 2004 Oct;28(10):1437-48. PMID:15597075
+
+
+
+Irizarry, RA, Bolstad, BM, Collin, F, Cope, LM, Hobbs, B, Speed, TP (2003) Summaries of Affymetrix GeneChip probe level data. Nuc Acids Res 31:1-15.
+
+
+
+Lincoln, SE, Lander, ES (1992) Systematic detection of errors in genetic linkage data. Genomics 14:604-610.
+
+
+
+Zhang, L, Miles, MF, Aldape, KD (2003) A model of molecular interactions on short oligonucleotide microarrays. Nat Biotech 21:818-821.
+
diff --git a/general/datasets/Sa_m2_0905_m/contributors.rtf b/general/datasets/Sa_m2_0905_m/contributors.rtf
new file mode 100644
index 0000000..fa18035
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_m/contributors.rtf
@@ -0,0 +1,7 @@
+BACKGROUND:Quantitative trait loci (QTLs) have been detected for a wide variety of ethanol-related phenotypes, including acute and chronic ethanol withdrawal, acute locomotor activation, and ethanol preference. This study was undertaken to determine whether the process of moving from QTL to quantitative trait gene (QTG) could be accelerated by the integration of functional genomics (gene expression) into the analysis strategy.
+
+METHODS:Six ethanol-related QTLs, all detected in C57BL/6J and DBA/2J intercrosses were entered into the analysis. Each of the QTLs had been confirmed in independent genetic models at least once; the cumulative probabilities for QTL existence ranged from 10 to 10. Brain gene expression data for the C57BL/6 and DBA/2 strains (n = 6 per strain) and an F2 intercross sample (n = 56) derived from these strains were obtained by using the Affymetrix U74Av2 and 430A arrays; additional data with the U74Av2 array were available for the extended amygdala, dorsomedial striatum, and hippocampus. Low-level analysis was performed by using multiple methods to determine the likelihood that a transcript was truly differentially expressed. For the 430A array data, the F2 sample was used to determine which of the differentially expressed transcripts within the QTL intervals were cis-regulated and, thus, strong candidates for QTGs.
+
+RESULTS:Within the 6 QTL intervals, 39 transcripts (430A array) were identified as being highly likely to be differentially expressed between the C57BL/6 and DBA/2 strains at a false discovery rate of 0.01 or better. Twenty-eight of these transcripts showed significant (logarithm of odds > or =3.6) to highly significant (logarithm of odds >7) cis-regulation. The process correctly detected Mpdz (chromosome 4) as a candidate QTG for acute withdrawal.
+
+CONCLUSIONS:Although improvements are needed in the expression databases, the integration of QTL and gene expression analyses seems to have potential as a high-throughput strategy for moving from QTL to QTG.
diff --git a/general/datasets/Sa_m2_0905_m/notes.rtf b/general/datasets/Sa_m2_0905_m/notes.rtf
new file mode 100644
index 0000000..7fafba3
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_m/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file was originally generated by John Belknap, March 2004. Updated by RWW, October 31, 2004, EJC June 21, 2005.
+
diff --git a/general/datasets/Sa_m2_0905_m/platform.rtf b/general/datasets/Sa_m2_0905_m/platform.rtf
new file mode 100644
index 0000000..f0ee528
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_m/platform.rtf
@@ -0,0 +1,1154 @@
+All 56 430A&B arrays used in this project were purchased at one time and had the same Affymetrix lot number. The table below lists the arrays by Case ID, Array ID, Side, Cage ID and Sex.
+
+
+
+
+
+
+
+
+ |
+ Order
+ |
+
+ CaseID
+ |
+
+ ArrayID
+ |
+
+ Side
+ |
+
+ CageID
+ |
+
+ Sex
+ |
+
+
+ |
+ 1
+ |
+
+ 20
+ |
+
+ FL10
+ |
+
+ L
+ |
+
+ H1
+ |
+
+ F
+ |
+
+
+ |
+ 2
+ |
+
+ 2
+ |
+
+ FL11
+ |
+
+ L
+ |
+
+ H2
+ |
+
+ F
+ |
+
+
+ |
+ 3
+ |
+
+ 5
+ |
+
+ FL12
+ |
+
+ L
+ |
+
+ H3
+ |
+
+ F
+ |
+
+
+ |
+ 4
+ |
+
+ 63
+ |
+
+ FL13
+ |
+
+ L
+ |
+
+ H4
+ |
+
+ F
+ |
+
+
+ |
+ 5
+ |
+
+ 6
+ |
+
+ FL14
+ |
+
+ L
+ |
+
+ K2
+ |
+
+ F
+ |
+
+
+ |
+ 6
+ |
+
+ 10
+ |
+
+ FL15
+ |
+
+ L
+ |
+
+ Q2
+ |
+
+ F
+ |
+
+
+ |
+ 7
+ |
+
+ 52
+ |
+
+ FL2
+ |
+
+ L
+ |
+
+ E1
+ |
+
+ F
+ |
+
+
+ |
+ 8
+ |
+
+ 53
+ |
+
+ FL3
+ |
+
+ L
+ |
+
+ E2
+ |
+
+ F
+ |
+
+
+ |
+ 9
+ |
+
+ 42
+ |
+
+ FL4
+ |
+
+ L
+ |
+
+ E3
+ |
+
+ F
+ |
+
+
+ |
+ 10
+ |
+
+ 31
+ |
+
+ FL5
+ |
+
+ L
+ |
+
+ E4
+ |
+
+ F
+ |
+
+
+ |
+ 11
+ |
+
+ 14
+ |
+
+ FL6
+ |
+
+ L
+ |
+
+ F1
+ |
+
+ M
+ |
+
+
+ |
+ 12
+ |
+
+ 48
+ |
+
+ FL7
+ |
+
+ L
+ |
+
+ F2
+ |
+
+ F
+ |
+
+
+ |
+ 13
+ |
+
+ 60
+ |
+
+ FL8
+ |
+
+ L
+ |
+
+ F3
+ |
+
+ M
+ |
+
+
+ |
+ 14
+ |
+
+ 54
+ |
+
+ FL9
+ |
+
+ L
+ |
+
+ F4
+ |
+
+ F
+ |
+
+
+ |
+ 15
+ |
+
+ 35
+ |
+
+ FR10
+ |
+
+ R
+ |
+
+ K3
+ |
+
+ F
+ |
+
+
+ |
+ 16
+ |
+
+ 11
+ |
+
+ FR11
+ |
+
+ R
+ |
+
+ O1
+ |
+
+ F
+ |
+
+
+ |
+ 17
+ |
+
+ 21
+ |
+
+ FR12
+ |
+
+ R
+ |
+
+ O2
+ |
+
+ F
+ |
+
+
+ |
+ 18
+ |
+
+ 23
+ |
+
+ FR13
+ |
+
+ R
+ |
+
+ Q1
+ |
+
+ F
+ |
+
+
+ |
+ 19
+ |
+
+ 15
+ |
+
+ FR14
+ |
+
+ R
+ |
+
+ Q3
+ |
+
+ F
+ |
+
+
+ |
+ 20
+ |
+
+ 4
+ |
+
+ FR15
+ |
+
+ R
+ |
+
+ Q4
+ |
+
+ F
+ |
+
+
+ |
+ 21
+ |
+
+ 41
+ |
+
+ FR2
+ |
+
+ R
+ |
+
+ A2
+ |
+
+ F
+ |
+
+
+ |
+ 22
+ |
+
+ 44
+ |
+
+ FR3
+ |
+
+ R
+ |
+
+ A3
+ |
+
+ F
+ |
+
+
+ |
+ 23
+ |
+
+ 37
+ |
+
+ FR4
+ |
+
+ R
+ |
+
+ C1
+ |
+
+ F
+ |
+
+
+ |
+ 24
+ |
+
+ 8
+ |
+
+ FR5
+ |
+
+ R
+ |
+
+ C2
+ |
+
+ F
+ |
+
+
+ |
+ 25
+ |
+
+ 19
+ |
+
+ FR6
+ |
+
+ R
+ |
+
+ C3
+ |
+
+ F
+ |
+
+
+ |
+ 26
+ |
+
+ 40
+ |
+
+ FR7
+ |
+
+ R
+ |
+
+ C4
+ |
+
+ F
+ |
+
+
+ |
+ 27
+ |
+
+ 62
+ |
+
+ FR8
+ |
+
+ R
+ |
+
+ D2
+ |
+
+ M
+ |
+
+
+ |
+ 28
+ |
+
+ 39
+ |
+
+ FR9
+ |
+
+ R
+ |
+
+ D3
+ |
+
+ F
+ |
+
+
+ |
+ 29
+ |
+
+ 13
+ |
+
+ ML1
+ |
+
+ L
+ |
+
+ B1
+ |
+
+ M
+ |
+
+
+ |
+ 30
+ |
+
+ 22
+ |
+
+ ML10
+ |
+
+ L
+ |
+
+ L2
+ |
+
+ M
+ |
+
+
+ |
+ 31
+ |
+
+ 38
+ |
+
+ ML11
+ |
+
+ L
+ |
+
+ L4
+ |
+
+ M
+ |
+
+
+ |
+ 32
+ |
+
+ 43
+ |
+
+ ML12
+ |
+
+ L
+ |
+
+ M1
+ |
+
+ M
+ |
+
+
+ |
+ 33
+ |
+
+ 58
+ |
+
+ ML13
+ |
+
+ L
+ |
+
+ N2
+ |
+
+ M
+ |
+
+
+ |
+ 34
+ |
+
+ 7
+ |
+
+ ML14
+ |
+
+ L
+ |
+
+ R1
+ |
+
+ M
+ |
+
+
+ |
+ 35
+ |
+
+ 30
+ |
+
+ ML15
+ |
+
+ L
+ |
+
+ R3
+ |
+
+ M
+ |
+
+
+ |
+ 36
+ |
+
+ 46
+ |
+
+ ML3
+ |
+
+ L
+ |
+
+ G1
+ |
+
+ M
+ |
+
+
+ |
+ 37
+ |
+
+ 57
+ |
+
+ ML4
+ |
+
+ L
+ |
+
+ G2
+ |
+
+ M
+ |
+
+
+ |
+ 38
+ |
+
+ 51
+ |
+
+ ML5
+ |
+
+ L
+ |
+
+ I1
+ |
+
+ M
+ |
+
+
+ |
+ 39
+ |
+
+ 27
+ |
+
+ ML6
+ |
+
+ L
+ |
+
+ I2
+ |
+
+ M
+ |
+
+
+ |
+ 40
+ |
+
+ 50
+ |
+
+ ML7
+ |
+
+ L
+ |
+
+ J2
+ |
+
+ M
+ |
+
+
+ |
+ 41
+ |
+
+ 16
+ |
+
+ FL1
+ |
+
+ L
+ |
+
+ O2
+ |
+
+ M
+ |
+
+
+ |
+ 42
+ |
+
+ 3
+ |
+
+ ML9
+ |
+
+ L
+ |
+
+ L1
+ |
+
+ M
+ |
+
+
+ |
+ 43
+ |
+
+ 47
+ |
+
+ MR10
+ |
+
+ R
+ |
+
+ R2
+ |
+
+ M
+ |
+
+
+ |
+ 44
+ |
+
+ 56
+ |
+
+ MR11
+ |
+
+ R
+ |
+
+ S1
+ |
+
+ M
+ |
+
+
+ |
+ 45
+ |
+
+ 1
+ |
+
+ MR12
+ |
+
+ R
+ |
+
+ S2
+ |
+
+ M
+ |
+
+
+ |
+ 46
+ |
+
+ 55
+ |
+
+ MR13
+ |
+
+ R
+ |
+
+ T1
+ |
+
+ M
+ |
+
+
+ |
+ 47
+ |
+
+ 34
+ |
+
+ MR14
+ |
+
+ R
+ |
+
+ U1
+ |
+
+ M
+ |
+
+
+ |
+ 48
+ |
+
+ 25
+ |
+
+ MR15
+ |
+
+ R
+ |
+
+ U2
+ |
+
+ M
+ |
+
+
+ |
+ 49
+ |
+
+ 59
+ |
+
+ MR2
+ |
+
+ R
+ |
+
+ J1
+ |
+
+ M
+ |
+
+
+ |
+ 50
+ |
+
+ 32
+ |
+
+ MR3
+ |
+
+ R
+ |
+
+ M2
+ |
+
+ M
+ |
+
+
+ |
+ 51
+ |
+
+ 24
+ |
+
+ MR4
+ |
+
+ R
+ |
+
+ M3
+ |
+
+ M
+ |
+
+
+ |
+ 52
+ |
+
+ 12
+ |
+
+ MR5
+ |
+
+ R
+ |
+
+ M4
+ |
+
+ M
+ |
+
+
+ |
+ 53
+ |
+
+ 9
+ |
+
+ MR6
+ |
+
+ R
+ |
+
+ N1
+ |
+
+ M
+ |
+
+
+ |
+ 54
+ |
+
+ 36
+ |
+
+ MR7
+ |
+
+ R
+ |
+
+ N3
+ |
+
+ M
+ |
+
+
+ |
+ 55
+ |
+
+ 28
+ |
+
+ MR8
+ |
+
+ R
+ |
+
+ P1
+ |
+
+ M
+ |
+
+
+ |
+ 56
+ |
+
+ 33
+ |
+
+ MR9
+ |
+
+ R
+ |
+
+ P2
+ |
+
+ M
+ |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Sa_m2_0905_m/processing.rtf b/general/datasets/Sa_m2_0905_m/processing.rtf
new file mode 100644
index 0000000..8a23d84
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_m/processing.rtf
@@ -0,0 +1,26 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are the 75% quantiles from a set of 91 pixel values per cell. Probe values were processed as follows:
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We took the log base 2 of each probe signal.
+ - Step 3: We computed the Z scores for each probe signal.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B arrays include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes provide a way to calibrate expression of the A and B arrays to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+
+
+Probe set data from the TXT file: These TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+
+About the marker set:
+
+
+The 56 mice were each genotyped at 309 MIT microsatellite markers distributed across the genome, including the Y chromosome. The genotyping error check routine (Lincoln and Lander, 1992) implemented within R/qtl (Broman et al., 2003) showed no likely errors at p <.01 probability. Initial genotypes were generated at OHSU. Approximately 200 genotypes were generated at UTHSC by Jing Gu and Shuhua Qi.
+
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of M430A and M430B probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium March 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
+
diff --git a/general/datasets/Sa_m2_0905_m/summary.rtf b/general/datasets/Sa_m2_0905_m/summary.rtf
new file mode 100644
index 0000000..6f477fe
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_m/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimate of mRNA expression in adult brains of F2 intercross mice (C57BL/6J x DBA/2J F2) measured using Affymetrix M430A and M430B microarray pairs. Data were generated at The Oregon Health Sciences University (OHSU) in Portland, Oregon, by John Belknap and Robert Hitzemann. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA or PDNN transforms.
diff --git a/general/datasets/Sa_m2_0905_m/tissue.rtf b/general/datasets/Sa_m2_0905_m/tissue.rtf
new file mode 100644
index 0000000..ef85488
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_m/tissue.rtf
@@ -0,0 +1 @@
+Brain samples were from 31 male and 25 females and between 28 right and 28 left hemispheres distributed with good balance across the two sexes. The tissue arrayed included the forebrain, midbrain, one olfactory bulb, the cerebellum; and the rostral part of the medulla. The medulla was trimmed transversely at the caudal aspect of the cerebellum. The sagittal cut was made from a dorsal to ventral direction. (Note that several of the other brain transcriptome databases do not include olfactory bulb or cerebellum.) Total RNA was isolated with TRIZOL Reagent (Life Technologies Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer’s protocol. The extracted RNA was then purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for purity; only samples with an A260/280 ratio greater than 1.8 were used. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. Samples containing at least 10 micrograms of total RNA were sent to the OHSU Gene Microarray Shared Resource facility for analysis. The procedures used at the facility precisely follow the manufacturer’s specifications. Details can be found at http://www.ohsu.edu/gmsr/amc. Following labeling, all samples were hybridized to the GeneChip Test3 array for quality control. If target performance did not meet recommended thresholds, the sample would have been discarded. All labeled samples passed the threshold and were hybridized to the 430A and 430B array pairs.
diff --git a/general/datasets/Sa_m2_0905_p/acknowledgment.rtf b/general/datasets/Sa_m2_0905_p/acknowledgment.rtf
new file mode 100644
index 0000000..e7f05c1
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_p/acknowledgment.rtf
@@ -0,0 +1,5 @@
+
+This project was supported by two Department of Veterans Affairs Merit Review Awards (to JK Belknap and R Hitzemann, respectively), AA10760 (Portland Alcohol Research Center), AA06243, AA13484, AA11034, DA05228 and MH51372.
+
+Please contact either John Belknap or Robert Hitzemann at the Dept. of Behavioral Neuroscience, Oregon Health & Science University (L470), or Research Service (R&D5), Portland VA Medical Ctr., Portland, OR 97239 USA.
+
diff --git a/general/datasets/Sa_m2_0905_p/cases.rtf b/general/datasets/Sa_m2_0905_p/cases.rtf
new file mode 100644
index 0000000..4f69ca9
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_p/cases.rtf
@@ -0,0 +1,3 @@
+Fifty-six B6D2F2 samples, each taken from a single brain hemisphere from an individual mouse, were assayed using 56 M430A&B Affymetrix short oligomer microarrays. [The remaining hemisphere will be used later for an anaysis of specific brain regions.] Each array ID (see table below) includes a three letter code; the first letter usually denotes sex of the case (note that we have made a few corrections and there are therefore several sex-discordant IDs), the second letter denotes the hemisphere (R or L), and the third letter is the mouse number within each cell. The F2 mice were experimentally naive, born within a 3-day period from second litters of each dam, and housed at weaning (20- to 24-days-of-age) in like-sex groups of 3 to 4 mice for females and 2 to 3 mice for males in standard mouse shoebox cages within Thoren racks. All 56 F2 mice were killed at 77 to 79 days-of-age by cervical dislocation on December 17, 2003. The brains were immediately split at the midline and then quickly frozen on dry ice. The brains were stored for about two weeks at -80 degrees C until further use.
+
+The F2 was derived as follows: C57BL/6J (B6) and DBA/2J (D2) breeders were obtained from The Jackson Laboratory, and two generations later their progeny were crossed to produce B6D2F1 and D2B6F1 hybrid at the Portland VA Veterinary Medical Unit (AAALAC approved). The reciprocal F1s were mated to create an F2 population with both progenitor X and Y chromosomes about equally represented.
diff --git a/general/datasets/Sa_m2_0905_p/citation.rtf b/general/datasets/Sa_m2_0905_p/citation.rtf
new file mode 100644
index 0000000..8e8e73d
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_p/citation.rtf
@@ -0,0 +1,15 @@
+
+Hitzemann R, Reed C, Malmanger B, Lawler M, Hitzemann B, Cunningham B, McWeeney S, Belknap J, Harrington C, Buck K, Phillips T, Crabbe J. (2004) On the integration of alcohol-related quantitative trait loci and gene expression analyses.. Alcohol Clin Exp Res. 2004 Oct;28(10):1437-48. PMID:15597075
+
+
+
+Irizarry, RA, Bolstad, BM, Collin, F, Cope, LM, Hobbs, B, Speed, TP (2003) Summaries of Affymetrix GeneChip probe level data. Nuc Acids Res 31:1-15.
+
+
+
+Lincoln, SE, Lander, ES (1992) Systematic detection of errors in genetic linkage data. Genomics 14:604-610.
+
+
+
+Zhang, L, Miles, MF, Aldape, KD (2003) A model of molecular interactions on short oligonucleotide microarrays. Nat Biotech 21:818-821.
+
diff --git a/general/datasets/Sa_m2_0905_p/contributors.rtf b/general/datasets/Sa_m2_0905_p/contributors.rtf
new file mode 100644
index 0000000..fa18035
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_p/contributors.rtf
@@ -0,0 +1,7 @@
+BACKGROUND:Quantitative trait loci (QTLs) have been detected for a wide variety of ethanol-related phenotypes, including acute and chronic ethanol withdrawal, acute locomotor activation, and ethanol preference. This study was undertaken to determine whether the process of moving from QTL to quantitative trait gene (QTG) could be accelerated by the integration of functional genomics (gene expression) into the analysis strategy.
+
+METHODS:Six ethanol-related QTLs, all detected in C57BL/6J and DBA/2J intercrosses were entered into the analysis. Each of the QTLs had been confirmed in independent genetic models at least once; the cumulative probabilities for QTL existence ranged from 10 to 10. Brain gene expression data for the C57BL/6 and DBA/2 strains (n = 6 per strain) and an F2 intercross sample (n = 56) derived from these strains were obtained by using the Affymetrix U74Av2 and 430A arrays; additional data with the U74Av2 array were available for the extended amygdala, dorsomedial striatum, and hippocampus. Low-level analysis was performed by using multiple methods to determine the likelihood that a transcript was truly differentially expressed. For the 430A array data, the F2 sample was used to determine which of the differentially expressed transcripts within the QTL intervals were cis-regulated and, thus, strong candidates for QTGs.
+
+RESULTS:Within the 6 QTL intervals, 39 transcripts (430A array) were identified as being highly likely to be differentially expressed between the C57BL/6 and DBA/2 strains at a false discovery rate of 0.01 or better. Twenty-eight of these transcripts showed significant (logarithm of odds > or =3.6) to highly significant (logarithm of odds >7) cis-regulation. The process correctly detected Mpdz (chromosome 4) as a candidate QTG for acute withdrawal.
+
+CONCLUSIONS:Although improvements are needed in the expression databases, the integration of QTL and gene expression analyses seems to have potential as a high-throughput strategy for moving from QTL to QTG.
diff --git a/general/datasets/Sa_m2_0905_p/notes.rtf b/general/datasets/Sa_m2_0905_p/notes.rtf
new file mode 100644
index 0000000..7fafba3
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_p/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file was originally generated by John Belknap, March 2004. Updated by RWW, October 31, 2004, EJC June 21, 2005.
+
diff --git a/general/datasets/Sa_m2_0905_p/platform.rtf b/general/datasets/Sa_m2_0905_p/platform.rtf
new file mode 100644
index 0000000..f0ee528
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_p/platform.rtf
@@ -0,0 +1,1154 @@
+All 56 430A&B arrays used in this project were purchased at one time and had the same Affymetrix lot number. The table below lists the arrays by Case ID, Array ID, Side, Cage ID and Sex.
+
+
+
+
+
+
+
+
+ |
+ Order
+ |
+
+ CaseID
+ |
+
+ ArrayID
+ |
+
+ Side
+ |
+
+ CageID
+ |
+
+ Sex
+ |
+
+
+ |
+ 1
+ |
+
+ 20
+ |
+
+ FL10
+ |
+
+ L
+ |
+
+ H1
+ |
+
+ F
+ |
+
+
+ |
+ 2
+ |
+
+ 2
+ |
+
+ FL11
+ |
+
+ L
+ |
+
+ H2
+ |
+
+ F
+ |
+
+
+ |
+ 3
+ |
+
+ 5
+ |
+
+ FL12
+ |
+
+ L
+ |
+
+ H3
+ |
+
+ F
+ |
+
+
+ |
+ 4
+ |
+
+ 63
+ |
+
+ FL13
+ |
+
+ L
+ |
+
+ H4
+ |
+
+ F
+ |
+
+
+ |
+ 5
+ |
+
+ 6
+ |
+
+ FL14
+ |
+
+ L
+ |
+
+ K2
+ |
+
+ F
+ |
+
+
+ |
+ 6
+ |
+
+ 10
+ |
+
+ FL15
+ |
+
+ L
+ |
+
+ Q2
+ |
+
+ F
+ |
+
+
+ |
+ 7
+ |
+
+ 52
+ |
+
+ FL2
+ |
+
+ L
+ |
+
+ E1
+ |
+
+ F
+ |
+
+
+ |
+ 8
+ |
+
+ 53
+ |
+
+ FL3
+ |
+
+ L
+ |
+
+ E2
+ |
+
+ F
+ |
+
+
+ |
+ 9
+ |
+
+ 42
+ |
+
+ FL4
+ |
+
+ L
+ |
+
+ E3
+ |
+
+ F
+ |
+
+
+ |
+ 10
+ |
+
+ 31
+ |
+
+ FL5
+ |
+
+ L
+ |
+
+ E4
+ |
+
+ F
+ |
+
+
+ |
+ 11
+ |
+
+ 14
+ |
+
+ FL6
+ |
+
+ L
+ |
+
+ F1
+ |
+
+ M
+ |
+
+
+ |
+ 12
+ |
+
+ 48
+ |
+
+ FL7
+ |
+
+ L
+ |
+
+ F2
+ |
+
+ F
+ |
+
+
+ |
+ 13
+ |
+
+ 60
+ |
+
+ FL8
+ |
+
+ L
+ |
+
+ F3
+ |
+
+ M
+ |
+
+
+ |
+ 14
+ |
+
+ 54
+ |
+
+ FL9
+ |
+
+ L
+ |
+
+ F4
+ |
+
+ F
+ |
+
+
+ |
+ 15
+ |
+
+ 35
+ |
+
+ FR10
+ |
+
+ R
+ |
+
+ K3
+ |
+
+ F
+ |
+
+
+ |
+ 16
+ |
+
+ 11
+ |
+
+ FR11
+ |
+
+ R
+ |
+
+ O1
+ |
+
+ F
+ |
+
+
+ |
+ 17
+ |
+
+ 21
+ |
+
+ FR12
+ |
+
+ R
+ |
+
+ O2
+ |
+
+ F
+ |
+
+
+ |
+ 18
+ |
+
+ 23
+ |
+
+ FR13
+ |
+
+ R
+ |
+
+ Q1
+ |
+
+ F
+ |
+
+
+ |
+ 19
+ |
+
+ 15
+ |
+
+ FR14
+ |
+
+ R
+ |
+
+ Q3
+ |
+
+ F
+ |
+
+
+ |
+ 20
+ |
+
+ 4
+ |
+
+ FR15
+ |
+
+ R
+ |
+
+ Q4
+ |
+
+ F
+ |
+
+
+ |
+ 21
+ |
+
+ 41
+ |
+
+ FR2
+ |
+
+ R
+ |
+
+ A2
+ |
+
+ F
+ |
+
+
+ |
+ 22
+ |
+
+ 44
+ |
+
+ FR3
+ |
+
+ R
+ |
+
+ A3
+ |
+
+ F
+ |
+
+
+ |
+ 23
+ |
+
+ 37
+ |
+
+ FR4
+ |
+
+ R
+ |
+
+ C1
+ |
+
+ F
+ |
+
+
+ |
+ 24
+ |
+
+ 8
+ |
+
+ FR5
+ |
+
+ R
+ |
+
+ C2
+ |
+
+ F
+ |
+
+
+ |
+ 25
+ |
+
+ 19
+ |
+
+ FR6
+ |
+
+ R
+ |
+
+ C3
+ |
+
+ F
+ |
+
+
+ |
+ 26
+ |
+
+ 40
+ |
+
+ FR7
+ |
+
+ R
+ |
+
+ C4
+ |
+
+ F
+ |
+
+
+ |
+ 27
+ |
+
+ 62
+ |
+
+ FR8
+ |
+
+ R
+ |
+
+ D2
+ |
+
+ M
+ |
+
+
+ |
+ 28
+ |
+
+ 39
+ |
+
+ FR9
+ |
+
+ R
+ |
+
+ D3
+ |
+
+ F
+ |
+
+
+ |
+ 29
+ |
+
+ 13
+ |
+
+ ML1
+ |
+
+ L
+ |
+
+ B1
+ |
+
+ M
+ |
+
+
+ |
+ 30
+ |
+
+ 22
+ |
+
+ ML10
+ |
+
+ L
+ |
+
+ L2
+ |
+
+ M
+ |
+
+
+ |
+ 31
+ |
+
+ 38
+ |
+
+ ML11
+ |
+
+ L
+ |
+
+ L4
+ |
+
+ M
+ |
+
+
+ |
+ 32
+ |
+
+ 43
+ |
+
+ ML12
+ |
+
+ L
+ |
+
+ M1
+ |
+
+ M
+ |
+
+
+ |
+ 33
+ |
+
+ 58
+ |
+
+ ML13
+ |
+
+ L
+ |
+
+ N2
+ |
+
+ M
+ |
+
+
+ |
+ 34
+ |
+
+ 7
+ |
+
+ ML14
+ |
+
+ L
+ |
+
+ R1
+ |
+
+ M
+ |
+
+
+ |
+ 35
+ |
+
+ 30
+ |
+
+ ML15
+ |
+
+ L
+ |
+
+ R3
+ |
+
+ M
+ |
+
+
+ |
+ 36
+ |
+
+ 46
+ |
+
+ ML3
+ |
+
+ L
+ |
+
+ G1
+ |
+
+ M
+ |
+
+
+ |
+ 37
+ |
+
+ 57
+ |
+
+ ML4
+ |
+
+ L
+ |
+
+ G2
+ |
+
+ M
+ |
+
+
+ |
+ 38
+ |
+
+ 51
+ |
+
+ ML5
+ |
+
+ L
+ |
+
+ I1
+ |
+
+ M
+ |
+
+
+ |
+ 39
+ |
+
+ 27
+ |
+
+ ML6
+ |
+
+ L
+ |
+
+ I2
+ |
+
+ M
+ |
+
+
+ |
+ 40
+ |
+
+ 50
+ |
+
+ ML7
+ |
+
+ L
+ |
+
+ J2
+ |
+
+ M
+ |
+
+
+ |
+ 41
+ |
+
+ 16
+ |
+
+ FL1
+ |
+
+ L
+ |
+
+ O2
+ |
+
+ M
+ |
+
+
+ |
+ 42
+ |
+
+ 3
+ |
+
+ ML9
+ |
+
+ L
+ |
+
+ L1
+ |
+
+ M
+ |
+
+
+ |
+ 43
+ |
+
+ 47
+ |
+
+ MR10
+ |
+
+ R
+ |
+
+ R2
+ |
+
+ M
+ |
+
+
+ |
+ 44
+ |
+
+ 56
+ |
+
+ MR11
+ |
+
+ R
+ |
+
+ S1
+ |
+
+ M
+ |
+
+
+ |
+ 45
+ |
+
+ 1
+ |
+
+ MR12
+ |
+
+ R
+ |
+
+ S2
+ |
+
+ M
+ |
+
+
+ |
+ 46
+ |
+
+ 55
+ |
+
+ MR13
+ |
+
+ R
+ |
+
+ T1
+ |
+
+ M
+ |
+
+
+ |
+ 47
+ |
+
+ 34
+ |
+
+ MR14
+ |
+
+ R
+ |
+
+ U1
+ |
+
+ M
+ |
+
+
+ |
+ 48
+ |
+
+ 25
+ |
+
+ MR15
+ |
+
+ R
+ |
+
+ U2
+ |
+
+ M
+ |
+
+
+ |
+ 49
+ |
+
+ 59
+ |
+
+ MR2
+ |
+
+ R
+ |
+
+ J1
+ |
+
+ M
+ |
+
+
+ |
+ 50
+ |
+
+ 32
+ |
+
+ MR3
+ |
+
+ R
+ |
+
+ M2
+ |
+
+ M
+ |
+
+
+ |
+ 51
+ |
+
+ 24
+ |
+
+ MR4
+ |
+
+ R
+ |
+
+ M3
+ |
+
+ M
+ |
+
+
+ |
+ 52
+ |
+
+ 12
+ |
+
+ MR5
+ |
+
+ R
+ |
+
+ M4
+ |
+
+ M
+ |
+
+
+ |
+ 53
+ |
+
+ 9
+ |
+
+ MR6
+ |
+
+ R
+ |
+
+ N1
+ |
+
+ M
+ |
+
+
+ |
+ 54
+ |
+
+ 36
+ |
+
+ MR7
+ |
+
+ R
+ |
+
+ N3
+ |
+
+ M
+ |
+
+
+ |
+ 55
+ |
+
+ 28
+ |
+
+ MR8
+ |
+
+ R
+ |
+
+ P1
+ |
+
+ M
+ |
+
+
+ |
+ 56
+ |
+
+ 33
+ |
+
+ MR9
+ |
+
+ R
+ |
+
+ P2
+ |
+
+ M
+ |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Sa_m2_0905_p/processing.rtf b/general/datasets/Sa_m2_0905_p/processing.rtf
new file mode 100644
index 0000000..8a23d84
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_p/processing.rtf
@@ -0,0 +1,26 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are the 75% quantiles from a set of 91 pixel values per cell. Probe values were processed as follows:
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We took the log base 2 of each probe signal.
+ - Step 3: We computed the Z scores for each probe signal.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B arrays include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes provide a way to calibrate expression of the A and B arrays to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+
+
+Probe set data from the TXT file: These TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+
+About the marker set:
+
+
+The 56 mice were each genotyped at 309 MIT microsatellite markers distributed across the genome, including the Y chromosome. The genotyping error check routine (Lincoln and Lander, 1992) implemented within R/qtl (Broman et al., 2003) showed no likely errors at p <.01 probability. Initial genotypes were generated at OHSU. Approximately 200 genotypes were generated at UTHSC by Jing Gu and Shuhua Qi.
+
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of M430A and M430B probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium March 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
+
diff --git a/general/datasets/Sa_m2_0905_p/summary.rtf b/general/datasets/Sa_m2_0905_p/summary.rtf
new file mode 100644
index 0000000..6f477fe
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_p/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimate of mRNA expression in adult brains of F2 intercross mice (C57BL/6J x DBA/2J F2) measured using Affymetrix M430A and M430B microarray pairs. Data were generated at The Oregon Health Sciences University (OHSU) in Portland, Oregon, by John Belknap and Robert Hitzemann. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA or PDNN transforms.
diff --git a/general/datasets/Sa_m2_0905_p/tissue.rtf b/general/datasets/Sa_m2_0905_p/tissue.rtf
new file mode 100644
index 0000000..ef85488
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_p/tissue.rtf
@@ -0,0 +1 @@
+Brain samples were from 31 male and 25 females and between 28 right and 28 left hemispheres distributed with good balance across the two sexes. The tissue arrayed included the forebrain, midbrain, one olfactory bulb, the cerebellum; and the rostral part of the medulla. The medulla was trimmed transversely at the caudal aspect of the cerebellum. The sagittal cut was made from a dorsal to ventral direction. (Note that several of the other brain transcriptome databases do not include olfactory bulb or cerebellum.) Total RNA was isolated with TRIZOL Reagent (Life Technologies Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer’s protocol. The extracted RNA was then purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for purity; only samples with an A260/280 ratio greater than 1.8 were used. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. Samples containing at least 10 micrograms of total RNA were sent to the OHSU Gene Microarray Shared Resource facility for analysis. The procedures used at the facility precisely follow the manufacturer’s specifications. Details can be found at http://www.ohsu.edu/gmsr/amc. Following labeling, all samples were hybridized to the GeneChip Test3 array for quality control. If target performance did not meet recommended thresholds, the sample would have been discarded. All labeled samples passed the threshold and were hybridized to the 430A and 430B array pairs.
diff --git a/general/datasets/Sa_m2_0905_r/acknowledgment.rtf b/general/datasets/Sa_m2_0905_r/acknowledgment.rtf
new file mode 100644
index 0000000..e7f05c1
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_r/acknowledgment.rtf
@@ -0,0 +1,5 @@
+
+This project was supported by two Department of Veterans Affairs Merit Review Awards (to JK Belknap and R Hitzemann, respectively), AA10760 (Portland Alcohol Research Center), AA06243, AA13484, AA11034, DA05228 and MH51372.
+
+Please contact either John Belknap or Robert Hitzemann at the Dept. of Behavioral Neuroscience, Oregon Health & Science University (L470), or Research Service (R&D5), Portland VA Medical Ctr., Portland, OR 97239 USA.
+
diff --git a/general/datasets/Sa_m2_0905_r/cases.rtf b/general/datasets/Sa_m2_0905_r/cases.rtf
new file mode 100644
index 0000000..4f69ca9
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_r/cases.rtf
@@ -0,0 +1,3 @@
+Fifty-six B6D2F2 samples, each taken from a single brain hemisphere from an individual mouse, were assayed using 56 M430A&B Affymetrix short oligomer microarrays. [The remaining hemisphere will be used later for an anaysis of specific brain regions.] Each array ID (see table below) includes a three letter code; the first letter usually denotes sex of the case (note that we have made a few corrections and there are therefore several sex-discordant IDs), the second letter denotes the hemisphere (R or L), and the third letter is the mouse number within each cell. The F2 mice were experimentally naive, born within a 3-day period from second litters of each dam, and housed at weaning (20- to 24-days-of-age) in like-sex groups of 3 to 4 mice for females and 2 to 3 mice for males in standard mouse shoebox cages within Thoren racks. All 56 F2 mice were killed at 77 to 79 days-of-age by cervical dislocation on December 17, 2003. The brains were immediately split at the midline and then quickly frozen on dry ice. The brains were stored for about two weeks at -80 degrees C until further use.
+
+The F2 was derived as follows: C57BL/6J (B6) and DBA/2J (D2) breeders were obtained from The Jackson Laboratory, and two generations later their progeny were crossed to produce B6D2F1 and D2B6F1 hybrid at the Portland VA Veterinary Medical Unit (AAALAC approved). The reciprocal F1s were mated to create an F2 population with both progenitor X and Y chromosomes about equally represented.
diff --git a/general/datasets/Sa_m2_0905_r/citation.rtf b/general/datasets/Sa_m2_0905_r/citation.rtf
new file mode 100644
index 0000000..8e8e73d
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_r/citation.rtf
@@ -0,0 +1,15 @@
+
+Hitzemann R, Reed C, Malmanger B, Lawler M, Hitzemann B, Cunningham B, McWeeney S, Belknap J, Harrington C, Buck K, Phillips T, Crabbe J. (2004) On the integration of alcohol-related quantitative trait loci and gene expression analyses.. Alcohol Clin Exp Res. 2004 Oct;28(10):1437-48. PMID:15597075
+
+
+
+Irizarry, RA, Bolstad, BM, Collin, F, Cope, LM, Hobbs, B, Speed, TP (2003) Summaries of Affymetrix GeneChip probe level data. Nuc Acids Res 31:1-15.
+
+
+
+Lincoln, SE, Lander, ES (1992) Systematic detection of errors in genetic linkage data. Genomics 14:604-610.
+
+
+
+Zhang, L, Miles, MF, Aldape, KD (2003) A model of molecular interactions on short oligonucleotide microarrays. Nat Biotech 21:818-821.
+
diff --git a/general/datasets/Sa_m2_0905_r/contributors.rtf b/general/datasets/Sa_m2_0905_r/contributors.rtf
new file mode 100644
index 0000000..fa18035
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_r/contributors.rtf
@@ -0,0 +1,7 @@
+BACKGROUND:Quantitative trait loci (QTLs) have been detected for a wide variety of ethanol-related phenotypes, including acute and chronic ethanol withdrawal, acute locomotor activation, and ethanol preference. This study was undertaken to determine whether the process of moving from QTL to quantitative trait gene (QTG) could be accelerated by the integration of functional genomics (gene expression) into the analysis strategy.
+
+METHODS:Six ethanol-related QTLs, all detected in C57BL/6J and DBA/2J intercrosses were entered into the analysis. Each of the QTLs had been confirmed in independent genetic models at least once; the cumulative probabilities for QTL existence ranged from 10 to 10. Brain gene expression data for the C57BL/6 and DBA/2 strains (n = 6 per strain) and an F2 intercross sample (n = 56) derived from these strains were obtained by using the Affymetrix U74Av2 and 430A arrays; additional data with the U74Av2 array were available for the extended amygdala, dorsomedial striatum, and hippocampus. Low-level analysis was performed by using multiple methods to determine the likelihood that a transcript was truly differentially expressed. For the 430A array data, the F2 sample was used to determine which of the differentially expressed transcripts within the QTL intervals were cis-regulated and, thus, strong candidates for QTGs.
+
+RESULTS:Within the 6 QTL intervals, 39 transcripts (430A array) were identified as being highly likely to be differentially expressed between the C57BL/6 and DBA/2 strains at a false discovery rate of 0.01 or better. Twenty-eight of these transcripts showed significant (logarithm of odds > or =3.6) to highly significant (logarithm of odds >7) cis-regulation. The process correctly detected Mpdz (chromosome 4) as a candidate QTG for acute withdrawal.
+
+CONCLUSIONS:Although improvements are needed in the expression databases, the integration of QTL and gene expression analyses seems to have potential as a high-throughput strategy for moving from QTL to QTG.
diff --git a/general/datasets/Sa_m2_0905_r/notes.rtf b/general/datasets/Sa_m2_0905_r/notes.rtf
new file mode 100644
index 0000000..7fafba3
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file was originally generated by John Belknap, March 2004. Updated by RWW, October 31, 2004, EJC June 21, 2005.
+
diff --git a/general/datasets/Sa_m2_0905_r/platform.rtf b/general/datasets/Sa_m2_0905_r/platform.rtf
new file mode 100644
index 0000000..f0ee528
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_r/platform.rtf
@@ -0,0 +1,1154 @@
+All 56 430A&B arrays used in this project were purchased at one time and had the same Affymetrix lot number. The table below lists the arrays by Case ID, Array ID, Side, Cage ID and Sex.
+
+
+
+
+
+
+
+
+ |
+ Order
+ |
+
+ CaseID
+ |
+
+ ArrayID
+ |
+
+ Side
+ |
+
+ CageID
+ |
+
+ Sex
+ |
+
+
+ |
+ 1
+ |
+
+ 20
+ |
+
+ FL10
+ |
+
+ L
+ |
+
+ H1
+ |
+
+ F
+ |
+
+
+ |
+ 2
+ |
+
+ 2
+ |
+
+ FL11
+ |
+
+ L
+ |
+
+ H2
+ |
+
+ F
+ |
+
+
+ |
+ 3
+ |
+
+ 5
+ |
+
+ FL12
+ |
+
+ L
+ |
+
+ H3
+ |
+
+ F
+ |
+
+
+ |
+ 4
+ |
+
+ 63
+ |
+
+ FL13
+ |
+
+ L
+ |
+
+ H4
+ |
+
+ F
+ |
+
+
+ |
+ 5
+ |
+
+ 6
+ |
+
+ FL14
+ |
+
+ L
+ |
+
+ K2
+ |
+
+ F
+ |
+
+
+ |
+ 6
+ |
+
+ 10
+ |
+
+ FL15
+ |
+
+ L
+ |
+
+ Q2
+ |
+
+ F
+ |
+
+
+ |
+ 7
+ |
+
+ 52
+ |
+
+ FL2
+ |
+
+ L
+ |
+
+ E1
+ |
+
+ F
+ |
+
+
+ |
+ 8
+ |
+
+ 53
+ |
+
+ FL3
+ |
+
+ L
+ |
+
+ E2
+ |
+
+ F
+ |
+
+
+ |
+ 9
+ |
+
+ 42
+ |
+
+ FL4
+ |
+
+ L
+ |
+
+ E3
+ |
+
+ F
+ |
+
+
+ |
+ 10
+ |
+
+ 31
+ |
+
+ FL5
+ |
+
+ L
+ |
+
+ E4
+ |
+
+ F
+ |
+
+
+ |
+ 11
+ |
+
+ 14
+ |
+
+ FL6
+ |
+
+ L
+ |
+
+ F1
+ |
+
+ M
+ |
+
+
+ |
+ 12
+ |
+
+ 48
+ |
+
+ FL7
+ |
+
+ L
+ |
+
+ F2
+ |
+
+ F
+ |
+
+
+ |
+ 13
+ |
+
+ 60
+ |
+
+ FL8
+ |
+
+ L
+ |
+
+ F3
+ |
+
+ M
+ |
+
+
+ |
+ 14
+ |
+
+ 54
+ |
+
+ FL9
+ |
+
+ L
+ |
+
+ F4
+ |
+
+ F
+ |
+
+
+ |
+ 15
+ |
+
+ 35
+ |
+
+ FR10
+ |
+
+ R
+ |
+
+ K3
+ |
+
+ F
+ |
+
+
+ |
+ 16
+ |
+
+ 11
+ |
+
+ FR11
+ |
+
+ R
+ |
+
+ O1
+ |
+
+ F
+ |
+
+
+ |
+ 17
+ |
+
+ 21
+ |
+
+ FR12
+ |
+
+ R
+ |
+
+ O2
+ |
+
+ F
+ |
+
+
+ |
+ 18
+ |
+
+ 23
+ |
+
+ FR13
+ |
+
+ R
+ |
+
+ Q1
+ |
+
+ F
+ |
+
+
+ |
+ 19
+ |
+
+ 15
+ |
+
+ FR14
+ |
+
+ R
+ |
+
+ Q3
+ |
+
+ F
+ |
+
+
+ |
+ 20
+ |
+
+ 4
+ |
+
+ FR15
+ |
+
+ R
+ |
+
+ Q4
+ |
+
+ F
+ |
+
+
+ |
+ 21
+ |
+
+ 41
+ |
+
+ FR2
+ |
+
+ R
+ |
+
+ A2
+ |
+
+ F
+ |
+
+
+ |
+ 22
+ |
+
+ 44
+ |
+
+ FR3
+ |
+
+ R
+ |
+
+ A3
+ |
+
+ F
+ |
+
+
+ |
+ 23
+ |
+
+ 37
+ |
+
+ FR4
+ |
+
+ R
+ |
+
+ C1
+ |
+
+ F
+ |
+
+
+ |
+ 24
+ |
+
+ 8
+ |
+
+ FR5
+ |
+
+ R
+ |
+
+ C2
+ |
+
+ F
+ |
+
+
+ |
+ 25
+ |
+
+ 19
+ |
+
+ FR6
+ |
+
+ R
+ |
+
+ C3
+ |
+
+ F
+ |
+
+
+ |
+ 26
+ |
+
+ 40
+ |
+
+ FR7
+ |
+
+ R
+ |
+
+ C4
+ |
+
+ F
+ |
+
+
+ |
+ 27
+ |
+
+ 62
+ |
+
+ FR8
+ |
+
+ R
+ |
+
+ D2
+ |
+
+ M
+ |
+
+
+ |
+ 28
+ |
+
+ 39
+ |
+
+ FR9
+ |
+
+ R
+ |
+
+ D3
+ |
+
+ F
+ |
+
+
+ |
+ 29
+ |
+
+ 13
+ |
+
+ ML1
+ |
+
+ L
+ |
+
+ B1
+ |
+
+ M
+ |
+
+
+ |
+ 30
+ |
+
+ 22
+ |
+
+ ML10
+ |
+
+ L
+ |
+
+ L2
+ |
+
+ M
+ |
+
+
+ |
+ 31
+ |
+
+ 38
+ |
+
+ ML11
+ |
+
+ L
+ |
+
+ L4
+ |
+
+ M
+ |
+
+
+ |
+ 32
+ |
+
+ 43
+ |
+
+ ML12
+ |
+
+ L
+ |
+
+ M1
+ |
+
+ M
+ |
+
+
+ |
+ 33
+ |
+
+ 58
+ |
+
+ ML13
+ |
+
+ L
+ |
+
+ N2
+ |
+
+ M
+ |
+
+
+ |
+ 34
+ |
+
+ 7
+ |
+
+ ML14
+ |
+
+ L
+ |
+
+ R1
+ |
+
+ M
+ |
+
+
+ |
+ 35
+ |
+
+ 30
+ |
+
+ ML15
+ |
+
+ L
+ |
+
+ R3
+ |
+
+ M
+ |
+
+
+ |
+ 36
+ |
+
+ 46
+ |
+
+ ML3
+ |
+
+ L
+ |
+
+ G1
+ |
+
+ M
+ |
+
+
+ |
+ 37
+ |
+
+ 57
+ |
+
+ ML4
+ |
+
+ L
+ |
+
+ G2
+ |
+
+ M
+ |
+
+
+ |
+ 38
+ |
+
+ 51
+ |
+
+ ML5
+ |
+
+ L
+ |
+
+ I1
+ |
+
+ M
+ |
+
+
+ |
+ 39
+ |
+
+ 27
+ |
+
+ ML6
+ |
+
+ L
+ |
+
+ I2
+ |
+
+ M
+ |
+
+
+ |
+ 40
+ |
+
+ 50
+ |
+
+ ML7
+ |
+
+ L
+ |
+
+ J2
+ |
+
+ M
+ |
+
+
+ |
+ 41
+ |
+
+ 16
+ |
+
+ FL1
+ |
+
+ L
+ |
+
+ O2
+ |
+
+ M
+ |
+
+
+ |
+ 42
+ |
+
+ 3
+ |
+
+ ML9
+ |
+
+ L
+ |
+
+ L1
+ |
+
+ M
+ |
+
+
+ |
+ 43
+ |
+
+ 47
+ |
+
+ MR10
+ |
+
+ R
+ |
+
+ R2
+ |
+
+ M
+ |
+
+
+ |
+ 44
+ |
+
+ 56
+ |
+
+ MR11
+ |
+
+ R
+ |
+
+ S1
+ |
+
+ M
+ |
+
+
+ |
+ 45
+ |
+
+ 1
+ |
+
+ MR12
+ |
+
+ R
+ |
+
+ S2
+ |
+
+ M
+ |
+
+
+ |
+ 46
+ |
+
+ 55
+ |
+
+ MR13
+ |
+
+ R
+ |
+
+ T1
+ |
+
+ M
+ |
+
+
+ |
+ 47
+ |
+
+ 34
+ |
+
+ MR14
+ |
+
+ R
+ |
+
+ U1
+ |
+
+ M
+ |
+
+
+ |
+ 48
+ |
+
+ 25
+ |
+
+ MR15
+ |
+
+ R
+ |
+
+ U2
+ |
+
+ M
+ |
+
+
+ |
+ 49
+ |
+
+ 59
+ |
+
+ MR2
+ |
+
+ R
+ |
+
+ J1
+ |
+
+ M
+ |
+
+
+ |
+ 50
+ |
+
+ 32
+ |
+
+ MR3
+ |
+
+ R
+ |
+
+ M2
+ |
+
+ M
+ |
+
+
+ |
+ 51
+ |
+
+ 24
+ |
+
+ MR4
+ |
+
+ R
+ |
+
+ M3
+ |
+
+ M
+ |
+
+
+ |
+ 52
+ |
+
+ 12
+ |
+
+ MR5
+ |
+
+ R
+ |
+
+ M4
+ |
+
+ M
+ |
+
+
+ |
+ 53
+ |
+
+ 9
+ |
+
+ MR6
+ |
+
+ R
+ |
+
+ N1
+ |
+
+ M
+ |
+
+
+ |
+ 54
+ |
+
+ 36
+ |
+
+ MR7
+ |
+
+ R
+ |
+
+ N3
+ |
+
+ M
+ |
+
+
+ |
+ 55
+ |
+
+ 28
+ |
+
+ MR8
+ |
+
+ R
+ |
+
+ P1
+ |
+
+ M
+ |
+
+
+ |
+ 56
+ |
+
+ 33
+ |
+
+ MR9
+ |
+
+ R
+ |
+
+ P2
+ |
+
+ M
+ |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Sa_m2_0905_r/processing.rtf b/general/datasets/Sa_m2_0905_r/processing.rtf
new file mode 100644
index 0000000..8a23d84
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_r/processing.rtf
@@ -0,0 +1,26 @@
+Probe (cell) level data from the CEL file: These CEL values produced by GCOS are the 75% quantiles from a set of 91 pixel values per cell. Probe values were processed as follows:
+
+ - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
+ - Step 2: We took the log base 2 of each probe signal.
+ - Step 3: We computed the Z scores for each probe signal.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6a: The 430A and 430B arrays include a set of 100 shared probe sets (2200 probes) that have identical sequences. These probes provide a way to calibrate expression of the A and B arrays to a common scale. The absolute mean expression on the 430B array is almost invariably lower than that on the 430A array. To bring the two arrays into alignment, we regressed Z scores of the common set of probes to obtain a linear regression corrections to rescale the 430B arrays to the 430A array. In our case this involved multiplying all 430B Z scores by the slope of the regression and adding or subtracting a very small offset. The result of this step is that the mean of the 430A GeneChip expression is fixed at a value of 8, whereas that of the 430B chip is typically 7. Thus average of A and B arrays is approximately 7.5.
+ - Step 6b: We recenter the whole set of 430A and B transcripts to a mean of 8 and a standard deviation of 2. This involves reapplying Steps 3 through 5 above but now using the entire set of probes and probe sets from a merged 430A and B data set.
+
+
+Probe set data from the TXT file: These TXT files were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1-unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
+
+
+About the marker set:
+
+
+The 56 mice were each genotyped at 309 MIT microsatellite markers distributed across the genome, including the Y chromosome. The genotyping error check routine (Lincoln and Lander, 1992) implemented within R/qtl (Broman et al., 2003) showed no likely errors at p <.01 probability. Initial genotypes were generated at OHSU. Approximately 200 genotypes were generated at UTHSC by Jing Gu and Shuhua Qi.
+
+
+About the chromosome and megabase position values:
+
+The chromosomal locations of M430A and M430B probe sets were determined by BLAT analysis of concatenated probe sequences using the Mouse Genome Sequencing Consortium March 2005 (mm6) assembly. This BLAT analysis is performed periodically by Yanhua Qu as each new build of the mouse genome is released. We thank Yan Cui (UTHSC) for allowing us to use his Linux cluster to perform this analysis. It is possible to confirm the BLAT alignment results yourself simply by clicking on the Verify link in the Trait Data and Editing Form (right side of the Location line).
+
+
+
diff --git a/general/datasets/Sa_m2_0905_r/summary.rtf b/general/datasets/Sa_m2_0905_r/summary.rtf
new file mode 100644
index 0000000..6f477fe
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_r/summary.rtf
@@ -0,0 +1 @@
+This August 2005 data freeze provides estimate of mRNA expression in adult brains of F2 intercross mice (C57BL/6J x DBA/2J F2) measured using Affymetrix M430A and M430B microarray pairs. Data were generated at The Oregon Health Sciences University (OHSU) in Portland, Oregon, by John Belknap and Robert Hitzemann. Data were processed using the Microarray Suite 5 (MAS 5) protocol of Affymetrix. To simplify comparison between transforms, MAS 5 values of each array were log2 transformed and adjusted to an average of 8 units. In general, MAS 5 data do not perform as well as RMA or PDNN transforms.
diff --git a/general/datasets/Sa_m2_0905_r/tissue.rtf b/general/datasets/Sa_m2_0905_r/tissue.rtf
new file mode 100644
index 0000000..ef85488
--- /dev/null
+++ b/general/datasets/Sa_m2_0905_r/tissue.rtf
@@ -0,0 +1 @@
+Brain samples were from 31 male and 25 females and between 28 right and 28 left hemispheres distributed with good balance across the two sexes. The tissue arrayed included the forebrain, midbrain, one olfactory bulb, the cerebellum; and the rostral part of the medulla. The medulla was trimmed transversely at the caudal aspect of the cerebellum. The sagittal cut was made from a dorsal to ventral direction. (Note that several of the other brain transcriptome databases do not include olfactory bulb or cerebellum.) Total RNA was isolated with TRIZOL Reagent (Life Technologies Inc.) using a modification of the single-step acid guanidinium isothiocyanate phenol-chloroform extraction method according to the manufacturer’s protocol. The extracted RNA was then purified using RNeasy (Qiagen, Inc.). RNA samples were evaluated by UV spectroscopy for purity; only samples with an A260/280 ratio greater than 1.8 were used. RNA quality was monitored by visualization on an ethidium bromide-stained denaturing formaldehyde agarose gel. Samples containing at least 10 micrograms of total RNA were sent to the OHSU Gene Microarray Shared Resource facility for analysis. The procedures used at the facility precisely follow the manufacturer’s specifications. Details can be found at http://www.ohsu.edu/gmsr/amc. Following labeling, all samples were hybridized to the GeneChip Test3 array for quality control. If target performance did not meet recommended thresholds, the sample would have been discarded. All labeled samples passed the threshold and were hybridized to the 430A and 430B array pairs.
diff --git a/general/datasets/Sa_m2_1104_g/acknowledgment.rtf b/general/datasets/Sa_m2_1104_g/acknowledgment.rtf
new file mode 100644
index 0000000..909ea42
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_g/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to Glenn Rosen from P20 MH62009 (see below for specifics). Samples and arrays were processed by the Genomics Core at Beth Israel Deaconess Medical Center by Towia Libermann and colleagues.
+
diff --git a/general/datasets/Sa_m2_1104_g/cases.rtf b/general/datasets/Sa_m2_1104_g/cases.rtf
new file mode 100644
index 0000000..63bba4c
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_g/cases.rtf
@@ -0,0 +1,184 @@
+
+This data set includes estimate of gene expression for 24 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), and 22 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period (see the WebQTL BXD Published Phenotypes database). A significant advantage of this RI set is that both parental strains (B6 and D2) have been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine.
+
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from 3 to 4 mice.
+
+
+
+
+Select the strain name in the table above to review details about the specific cases and to view the array quality control image processed using the PerfectMatch program by Li Zhang.
+
diff --git a/general/datasets/Sa_m2_1104_g/experiment-design.rtf b/general/datasets/Sa_m2_1104_g/experiment-design.rtf
new file mode 100644
index 0000000..1b0f0b3
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_g/experiment-design.rtf
@@ -0,0 +1,5 @@
+
+Animals were obtained from The Jackson Laboratory and housed for several weeks at BIDMC until they reached ~2 months of age (range from 55 to 62 days). Mice were killed by cervical dislocation and brains were removed and placed in RNAlater for 5 to 10 minutes prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both striata were dissected using a medial approach by Rosen that typically yields 5 to 7 mg of tissue per side. The purity of this dissection has been validated by an analysis of acetylcholinestase activity. A pool of dissected tissue from 3 or 4 adults (approximately 25-30 mg of tissue from 6 striata) of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Rought 90 to 95% of all cells in the striatum are medium spiny neurons (Gerfen, 1992, for a review of the structure and function of the neostriatum).
+
+mRNA processing: We used the Amersham Biosciences cRNA synthesis kit protocol.
+
diff --git a/general/datasets/Sa_m2_1104_g/notes.rtf b/general/datasets/Sa_m2_1104_g/notes.rtf
new file mode 100644
index 0000000..e37761f
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_g/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by GDR, RWW, and YHQ Nov 2004. Updated by RWW Nov 17, 2004; GDR and RWW, Dec 23, 2004.
+
diff --git a/general/datasets/Sa_m2_1104_g/platform.rtf b/general/datasets/Sa_m2_1104_g/platform.rtf
new file mode 100644
index 0000000..bd1a9e0
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_g/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are actually duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequence as the 430A and B series. However, we have found that roughy 75000 probes differ from those on A and B arrays.
+
diff --git a/general/datasets/Sa_m2_1104_g/processing.rtf b/general/datasets/Sa_m2_1104_g/processing.rtf
new file mode 100644
index 0000000..5473eda
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_g/processing.rtf
@@ -0,0 +1,11 @@
+Affymetrix CEL files obtained from the BIDMC Genomics Core were processed as follows.
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each cell.
+ - Step 3: We computed the Z score for each cell.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We plotted these modified Z score probe level expression estimates in DataDesk. Male-female scatterplots of the probe signals were compared strain by strain to highlight poor array data sets. A total of 36 arrays passed this stringent quality control step.
+ - Step 7: We computed the arithmetic mean of the values for the set of microarrays for each of the individual strains. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the CHP file: The expression values were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1 unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
diff --git a/general/datasets/Sa_m2_1104_g/summary.rtf b/general/datasets/Sa_m2_1104_g/summary.rtf
new file mode 100644
index 0000000..427768f
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_g/summary.rtf
@@ -0,0 +1 @@
+This November 2004 data freeze provides estimates of mRNA expression in the striatum (caudate nucleus of the forebrain) of BXD recombinant inbred mice measured using Affymetrix Mouse Genome 430 2.0 short oligomer microarrays. Data were generated at Beth Israel Deaconess Medical Center (BIDMC, Boston MA) by Glenn D. Rosen with the support of a Human Brain Project (HBP) grant. Approximately 125 brain samples from 24 strains were used in this initial experiment. Data were processed using the Affymetrix Microarray Suite 5 (MAS 5) transform. To simplify comparison among Nov04 data sets, values of each array have been log2 transformed and adjusted to an average expression of 8 units.
diff --git a/general/datasets/Sa_m2_1104_m/acknowledgment.rtf b/general/datasets/Sa_m2_1104_m/acknowledgment.rtf
new file mode 100644
index 0000000..909ea42
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_m/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to Glenn Rosen from P20 MH62009 (see below for specifics). Samples and arrays were processed by the Genomics Core at Beth Israel Deaconess Medical Center by Towia Libermann and colleagues.
+
diff --git a/general/datasets/Sa_m2_1104_m/cases.rtf b/general/datasets/Sa_m2_1104_m/cases.rtf
new file mode 100644
index 0000000..63bba4c
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_m/cases.rtf
@@ -0,0 +1,184 @@
+
+This data set includes estimate of gene expression for 24 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), and 22 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period (see the WebQTL BXD Published Phenotypes database). A significant advantage of this RI set is that both parental strains (B6 and D2) have been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine.
+
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from 3 to 4 mice.
+
+
+
+
+Select the strain name in the table above to review details about the specific cases and to view the array quality control image processed using the PerfectMatch program by Li Zhang.
+
diff --git a/general/datasets/Sa_m2_1104_m/experiment-design.rtf b/general/datasets/Sa_m2_1104_m/experiment-design.rtf
new file mode 100644
index 0000000..1b0f0b3
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_m/experiment-design.rtf
@@ -0,0 +1,5 @@
+
+Animals were obtained from The Jackson Laboratory and housed for several weeks at BIDMC until they reached ~2 months of age (range from 55 to 62 days). Mice were killed by cervical dislocation and brains were removed and placed in RNAlater for 5 to 10 minutes prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both striata were dissected using a medial approach by Rosen that typically yields 5 to 7 mg of tissue per side. The purity of this dissection has been validated by an analysis of acetylcholinestase activity. A pool of dissected tissue from 3 or 4 adults (approximately 25-30 mg of tissue from 6 striata) of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Rought 90 to 95% of all cells in the striatum are medium spiny neurons (Gerfen, 1992, for a review of the structure and function of the neostriatum).
+
+mRNA processing: We used the Amersham Biosciences cRNA synthesis kit protocol.
+
diff --git a/general/datasets/Sa_m2_1104_m/notes.rtf b/general/datasets/Sa_m2_1104_m/notes.rtf
new file mode 100644
index 0000000..e37761f
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_m/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by GDR, RWW, and YHQ Nov 2004. Updated by RWW Nov 17, 2004; GDR and RWW, Dec 23, 2004.
+
diff --git a/general/datasets/Sa_m2_1104_m/platform.rtf b/general/datasets/Sa_m2_1104_m/platform.rtf
new file mode 100644
index 0000000..bd1a9e0
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_m/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are actually duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequence as the 430A and B series. However, we have found that roughy 75000 probes differ from those on A and B arrays.
+
diff --git a/general/datasets/Sa_m2_1104_m/processing.rtf b/general/datasets/Sa_m2_1104_m/processing.rtf
new file mode 100644
index 0000000..5473eda
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_m/processing.rtf
@@ -0,0 +1,11 @@
+Affymetrix CEL files obtained from the BIDMC Genomics Core were processed as follows.
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each cell.
+ - Step 3: We computed the Z score for each cell.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We plotted these modified Z score probe level expression estimates in DataDesk. Male-female scatterplots of the probe signals were compared strain by strain to highlight poor array data sets. A total of 36 arrays passed this stringent quality control step.
+ - Step 7: We computed the arithmetic mean of the values for the set of microarrays for each of the individual strains. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the CHP file: The expression values were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1 unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
diff --git a/general/datasets/Sa_m2_1104_m/summary.rtf b/general/datasets/Sa_m2_1104_m/summary.rtf
new file mode 100644
index 0000000..427768f
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_m/summary.rtf
@@ -0,0 +1 @@
+This November 2004 data freeze provides estimates of mRNA expression in the striatum (caudate nucleus of the forebrain) of BXD recombinant inbred mice measured using Affymetrix Mouse Genome 430 2.0 short oligomer microarrays. Data were generated at Beth Israel Deaconess Medical Center (BIDMC, Boston MA) by Glenn D. Rosen with the support of a Human Brain Project (HBP) grant. Approximately 125 brain samples from 24 strains were used in this initial experiment. Data were processed using the Affymetrix Microarray Suite 5 (MAS 5) transform. To simplify comparison among Nov04 data sets, values of each array have been log2 transformed and adjusted to an average expression of 8 units.
diff --git a/general/datasets/Sa_m2_1104_p/acknowledgment.rtf b/general/datasets/Sa_m2_1104_p/acknowledgment.rtf
new file mode 100644
index 0000000..909ea42
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_p/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to Glenn Rosen from P20 MH62009 (see below for specifics). Samples and arrays were processed by the Genomics Core at Beth Israel Deaconess Medical Center by Towia Libermann and colleagues.
+
diff --git a/general/datasets/Sa_m2_1104_p/cases.rtf b/general/datasets/Sa_m2_1104_p/cases.rtf
new file mode 100644
index 0000000..63bba4c
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_p/cases.rtf
@@ -0,0 +1,184 @@
+
+This data set includes estimate of gene expression for 24 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), and 22 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period (see the WebQTL BXD Published Phenotypes database). A significant advantage of this RI set is that both parental strains (B6 and D2) have been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine.
+
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from 3 to 4 mice.
+
+
+
+
+Select the strain name in the table above to review details about the specific cases and to view the array quality control image processed using the PerfectMatch program by Li Zhang.
+
diff --git a/general/datasets/Sa_m2_1104_p/experiment-design.rtf b/general/datasets/Sa_m2_1104_p/experiment-design.rtf
new file mode 100644
index 0000000..1b0f0b3
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_p/experiment-design.rtf
@@ -0,0 +1,5 @@
+
+Animals were obtained from The Jackson Laboratory and housed for several weeks at BIDMC until they reached ~2 months of age (range from 55 to 62 days). Mice were killed by cervical dislocation and brains were removed and placed in RNAlater for 5 to 10 minutes prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both striata were dissected using a medial approach by Rosen that typically yields 5 to 7 mg of tissue per side. The purity of this dissection has been validated by an analysis of acetylcholinestase activity. A pool of dissected tissue from 3 or 4 adults (approximately 25-30 mg of tissue from 6 striata) of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Rought 90 to 95% of all cells in the striatum are medium spiny neurons (Gerfen, 1992, for a review of the structure and function of the neostriatum).
+
+mRNA processing: We used the Amersham Biosciences cRNA synthesis kit protocol.
+
diff --git a/general/datasets/Sa_m2_1104_p/notes.rtf b/general/datasets/Sa_m2_1104_p/notes.rtf
new file mode 100644
index 0000000..e37761f
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_p/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by GDR, RWW, and YHQ Nov 2004. Updated by RWW Nov 17, 2004; GDR and RWW, Dec 23, 2004.
+
diff --git a/general/datasets/Sa_m2_1104_p/platform.rtf b/general/datasets/Sa_m2_1104_p/platform.rtf
new file mode 100644
index 0000000..bd1a9e0
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_p/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are actually duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequence as the 430A and B series. However, we have found that roughy 75000 probes differ from those on A and B arrays.
+
diff --git a/general/datasets/Sa_m2_1104_p/processing.rtf b/general/datasets/Sa_m2_1104_p/processing.rtf
new file mode 100644
index 0000000..5473eda
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_p/processing.rtf
@@ -0,0 +1,11 @@
+Affymetrix CEL files obtained from the BIDMC Genomics Core were processed as follows.
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each cell.
+ - Step 3: We computed the Z score for each cell.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We plotted these modified Z score probe level expression estimates in DataDesk. Male-female scatterplots of the probe signals were compared strain by strain to highlight poor array data sets. A total of 36 arrays passed this stringent quality control step.
+ - Step 7: We computed the arithmetic mean of the values for the set of microarrays for each of the individual strains. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the CHP file: The expression values were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1 unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
diff --git a/general/datasets/Sa_m2_1104_p/summary.rtf b/general/datasets/Sa_m2_1104_p/summary.rtf
new file mode 100644
index 0000000..427768f
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_p/summary.rtf
@@ -0,0 +1 @@
+This November 2004 data freeze provides estimates of mRNA expression in the striatum (caudate nucleus of the forebrain) of BXD recombinant inbred mice measured using Affymetrix Mouse Genome 430 2.0 short oligomer microarrays. Data were generated at Beth Israel Deaconess Medical Center (BIDMC, Boston MA) by Glenn D. Rosen with the support of a Human Brain Project (HBP) grant. Approximately 125 brain samples from 24 strains were used in this initial experiment. Data were processed using the Affymetrix Microarray Suite 5 (MAS 5) transform. To simplify comparison among Nov04 data sets, values of each array have been log2 transformed and adjusted to an average expression of 8 units.
diff --git a/general/datasets/Sa_m2_1104_r/acknowledgment.rtf b/general/datasets/Sa_m2_1104_r/acknowledgment.rtf
new file mode 100644
index 0000000..909ea42
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_r/acknowledgment.rtf
@@ -0,0 +1,3 @@
+
+Data were generated with funds to Glenn Rosen from P20 MH62009 (see below for specifics). Samples and arrays were processed by the Genomics Core at Beth Israel Deaconess Medical Center by Towia Libermann and colleagues.
+
diff --git a/general/datasets/Sa_m2_1104_r/cases.rtf b/general/datasets/Sa_m2_1104_r/cases.rtf
new file mode 100644
index 0000000..63bba4c
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_r/cases.rtf
@@ -0,0 +1,184 @@
+
+This data set includes estimate of gene expression for 24 genetically uniform lines of mice: C57BL/6J (B6, or simply B), DBA/2J (D2 or D), and 22 BXD recombinant inbred (RI) strains derived by crossing female B6 mice with male D2 mice and then inbreeding progeny for over 21 generations. This set of RI strains is a remarkable resource because these strains have been extensively phenotyped for hundreds of interesting traits over a 25-year period (see the WebQTL BXD Published Phenotypes database). A significant advantage of this RI set is that both parental strains (B6 and D2) have been extensively sequenced and are known to differ at approximately 1.8 million SNPs. Coding variants (mostly single nucleotide polymorphisms and insertion-deletions) that may produce interesting phenotypes can be rapidly identified in this particular RI set.
+
+BXD1 through BXD32 were produced by Benjamin A. Taylor starting in the late 1970s. BXD33 through BXD42 were also produced by Taylor, but from a second set of crosses initiated in the early 1990s. These strains are all available from the Jackson Laboratory, Bar Harbor, Maine.
+
+
+The table below lists the arrays by strain, sex, and age. Each array was hybridized to a pool of mRNA from 3 to 4 mice.
+
+
+
+
+Select the strain name in the table above to review details about the specific cases and to view the array quality control image processed using the PerfectMatch program by Li Zhang.
+
diff --git a/general/datasets/Sa_m2_1104_r/experiment-design.rtf b/general/datasets/Sa_m2_1104_r/experiment-design.rtf
new file mode 100644
index 0000000..1b0f0b3
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_r/experiment-design.rtf
@@ -0,0 +1,5 @@
+
+Animals were obtained from The Jackson Laboratory and housed for several weeks at BIDMC until they reached ~2 months of age (range from 55 to 62 days). Mice were killed by cervical dislocation and brains were removed and placed in RNAlater for 5 to 10 minutes prior to dissection. Cerebella and olfactory bulbs were removed; brains were hemisected, and both striata were dissected using a medial approach by Rosen that typically yields 5 to 7 mg of tissue per side. The purity of this dissection has been validated by an analysis of acetylcholinestase activity. A pool of dissected tissue from 3 or 4 adults (approximately 25-30 mg of tissue from 6 striata) of the same strain, sex, and age was collected in one session and used to generate cRNA samples. Rought 90 to 95% of all cells in the striatum are medium spiny neurons (Gerfen, 1992, for a review of the structure and function of the neostriatum).
+
+mRNA processing: We used the Amersham Biosciences cRNA synthesis kit protocol.
+
diff --git a/general/datasets/Sa_m2_1104_r/notes.rtf b/general/datasets/Sa_m2_1104_r/notes.rtf
new file mode 100644
index 0000000..e37761f
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_r/notes.rtf
@@ -0,0 +1,3 @@
+
+This text file originally generated by GDR, RWW, and YHQ Nov 2004. Updated by RWW Nov 17, 2004; GDR and RWW, Dec 23, 2004.
+
diff --git a/general/datasets/Sa_m2_1104_r/platform.rtf b/general/datasets/Sa_m2_1104_r/platform.rtf
new file mode 100644
index 0000000..bd1a9e0
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_r/platform.rtf
@@ -0,0 +1,3 @@
+
+Affymetrix Mouse Genome 430 2.0 array: The 430v2 array consists of 992936 useful 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many are actually duplicates). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequence as the 430A and B series. However, we have found that roughy 75000 probes differ from those on A and B arrays.
+
diff --git a/general/datasets/Sa_m2_1104_r/processing.rtf b/general/datasets/Sa_m2_1104_r/processing.rtf
new file mode 100644
index 0000000..5473eda
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_r/processing.rtf
@@ -0,0 +1,11 @@
+Affymetrix CEL files obtained from the BIDMC Genomics Core were processed as follows.
+
+ - Step 1: We added an offset of 1 to the CEL expression values for each cell to ensure that all values could be logged without generating negative values.
+ - Step 2: We took the log base 2 of each cell.
+ - Step 3: We computed the Z score for each cell.
+ - Step 4: We multiplied all Z scores by 2.
+ - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
+ - Step 6: We plotted these modified Z score probe level expression estimates in DataDesk. Male-female scatterplots of the probe signals were compared strain by strain to highlight poor array data sets. A total of 36 arrays passed this stringent quality control step.
+ - Step 7: We computed the arithmetic mean of the values for the set of microarrays for each of the individual strains. We have not corrected for background beyond the background correction implemented by Affymetrix in generating the CEL file.
+
+Probe set data from the CHP file: The expression values were generated using the MAS 5. The same simple steps described above were also applied to these values. Every microarray data set therefore has a mean expression of 8 with a standard deviation of 2. A 1 unit difference therefor represents roughly a two-fold difference in expression level. Expression levels below 5 are usually close to background noise levels.
diff --git a/general/datasets/Sa_m2_1104_r/summary.rtf b/general/datasets/Sa_m2_1104_r/summary.rtf
new file mode 100644
index 0000000..427768f
--- /dev/null
+++ b/general/datasets/Sa_m2_1104_r/summary.rtf
@@ -0,0 +1 @@
+This November 2004 data freeze provides estimates of mRNA expression in the striatum (caudate nucleus of the forebrain) of BXD recombinant inbred mice measured using Affymetrix Mouse Genome 430 2.0 short oligomer microarrays. Data were generated at Beth Israel Deaconess Medical Center (BIDMC, Boston MA) by Glenn D. Rosen with the support of a Human Brain Project (HBP) grant. Approximately 125 brain samples from 24 strains were used in this initial experiment. Data were processed using the Affymetrix Microarray Suite 5 (MAS 5) transform. To simplify comparison among Nov04 data sets, values of each array have been log2 transformed and adjusted to an average expression of 8 units.
diff --git a/general/datasets/ScrBXDACC4G0513/summary.rtf b/general/datasets/ScrBXDACC4G0513/summary.rtf
deleted file mode 100644
index 07eb887..0000000
--- a/general/datasets/ScrBXDACC4G0513/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 173, Name: Scripps BXD ACC 4 Groups Affy Mouse Gene 1.0 ST (May13) RMA Gene Level **
\ No newline at end of file
diff --git a/general/datasets/Scrbxdacc4g0513/summary.rtf b/general/datasets/Scrbxdacc4g0513/summary.rtf
new file mode 100644
index 0000000..07eb887
--- /dev/null
+++ b/general/datasets/Scrbxdacc4g0513/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 173, Name: Scripps BXD ACC 4 Groups Affy Mouse Gene 1.0 ST (May13) RMA Gene Level **
\ No newline at end of file
diff --git a/general/datasets/Stj_pln_0912/experiment-type.rtf b/general/datasets/Stj_pln_0912/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Stj_pln_0912/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Stj_pln_0912/summary.rtf b/general/datasets/Stj_pln_0912/summary.rtf
new file mode 100644
index 0000000..fd9009a
--- /dev/null
+++ b/general/datasets/Stj_pln_0912/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 154, Name: St Jude BXD Popliteal Lymph Node Affy HT MG-430 PM (Sep12)
\ No newline at end of file
diff --git a/general/datasets/Striatum_exon_0209/cases.rtf b/general/datasets/Striatum_exon_0209/cases.rtf
new file mode 100644
index 0000000..e4db26e
--- /dev/null
+++ b/general/datasets/Striatum_exon_0209/cases.rtf
@@ -0,0 +1,947 @@
+A movie of the dissection of the brain, including the striatum, by Dr. Glenn Rosen.
+
+About the strains used to generate this set of data
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tube No. |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R3025SA |
+ 1705 |
+ Striatum |
+ 129S1/SvImJ |
+ 60 |
+ F |
+
+
+ | 2 |
+ R3026SA |
+ 1375 |
+ Striatum |
+ 129S1/SvImJ |
+ 59 |
+ M |
+
+
+ | 3 |
+ R3027SA |
+ 1435 |
+ Striatum |
+ A/J |
+ 59 |
+ F |
+
+
+ | 4 |
+ R3028SA |
+ 1455 |
+ Striatum |
+ A/J |
+ 59 |
+ M |
+
+
+ | 5 |
+ R3029SA |
+ 1395 |
+ Striatum |
+ AKR/J |
+ 59 |
+ F |
+
+
+ | 6 |
+ R3030SA |
+ 1415 |
+ Striatum |
+ AKR/J |
+ 59 |
+ M |
+
+
+ | 7 |
+ R3031SA |
+ 1227 |
+ Striatum |
+ B6D2F1 |
+ 59 |
+ F |
+
+
+ | 8 |
+ R3032SA |
+ 1225 |
+ Striatum |
+ B6D2F1 |
+ 59 |
+ M |
+
+
+ | 9 |
+ R3033SA |
+ 1495 |
+ Striatum |
+ BALB/cByJ |
+ 59 |
+ F |
+
+
+ | 10 |
+ R3034SA |
+ 1475 |
+ Striatum |
+ BALB/cByJ |
+ 59 |
+ M |
+
+
+ | 11 |
+ R3035SA |
+ 1665 |
+ Striatum |
+ BTBRT<+>tf/J |
+ 59 |
+ F |
+
+
+ | 12 |
+ R3036SA |
+ 1615 |
+ Striatum |
+ BTBRT<+>tf/J |
+ 60 |
+ M |
+
+
+ | 13 |
+ R3037SA |
+ 457 |
+ Striatum |
+ BXD1 |
+ 59 |
+ F |
+
+
+ | 14 |
+ R3038SA |
+ 927 |
+ Striatum |
+ BXD1 |
+ 59 |
+ M |
+
+
+ | 15 |
+ R3055SA |
+ 487 |
+ Striatum |
+ BXD2 |
+ 61 |
+ F |
+
+
+ | 16 |
+ R3056SA |
+ 477 |
+ Striatum |
+ BXD2 |
+ 61 |
+ M |
+
+
+ | 17 |
+ R3089SA |
+ 977 |
+ Striatum |
+ BXD5 |
+ 58 |
+ F |
+
+
+ | 18 |
+ R3090SA |
+ 967 |
+ Striatum |
+ BXD5 |
+ 58 |
+ M |
+
+
+ | 19 |
+ R3091SA |
+ 557 |
+ Striatum |
+ BXD6 |
+ 59 |
+ F |
+
+
+ | 20 |
+ R3092SA |
+ 547 |
+ Striatum |
+ BXD6 |
+ 59 |
+ M |
+
+
+ | 21 |
+ R3093SA |
+ 717 |
+ Striatum |
+ BXD8 |
+ 61 |
+ F |
+
+
+ | 22 |
+ R3094SA |
+ 707 |
+ Striatum |
+ BXD8 |
+ 61 |
+ M |
+
+
+ | 23 |
+ R3095SA |
+ 647 |
+ Striatum |
+ BXD9 |
+ 60 |
+ F |
+
+
+ | 24 |
+ R3096SA |
+ 637 |
+ Striatum |
+ BXD9 |
+ 60 |
+ M |
+
+
+ | 25 |
+ R3039SA |
+ 517 |
+ Striatum |
+ BXD11 |
+ 59 |
+ F |
+
+
+ | 26 |
+ R3040SA |
+ 787 |
+ Striatum |
+ BXD11 |
+ 59 |
+ M |
+
+
+ | 27 |
+ R3041SA |
+ 817 |
+ Striatum |
+ BXD12 |
+ 62 |
+ F |
+
+
+ | 28 |
+ R3042SA |
+ 807 |
+ Striatum |
+ BXD12 |
+ 59 |
+ M |
+
+
+ | 29 |
+ R3043SA |
+ 877 |
+ Striatum |
+ BXD13 |
+ 60 |
+ F |
+
+
+ | 30 |
+ R3044SA |
+ 867 |
+ Striatum |
+ BXD13 |
+ 60 |
+ M |
+
+
+ | 31 |
+ R3045SA |
+ 1067 |
+ Striatum |
+ BXD14 |
+ 59 |
+ F |
+
+
+ | 32 |
+ R3144SA |
+ 1077 |
+ Striatum |
+ BXD14 |
+ 59 |
+ M |
+
+
+ | 33 |
+ R3047SA |
+ 1057 |
+ Striatum |
+ BXD15 |
+ 60 |
+ F |
+
+
+ | 34 |
+ R3048SA |
+ 1047 |
+ Striatum |
+ BXD15 |
+ 60 |
+ M |
+
+
+ | 35 |
+ R3049SA |
+ 767 |
+ Striatum |
+ BXD16 |
+ 61 |
+ F |
+
+
+ | 36 |
+ R3050SA |
+ 777 |
+ Striatum |
+ BXD16 |
+ 61 |
+ M |
+
+
+ | 37 |
+ R3051SA |
+ 1177 |
+ Striatum |
+ BXD18 |
+ 59 |
+ F |
+
+
+ | 38 |
+ R3052SA |
+ 1167 |
+ Striatum |
+ BXD18 |
+ 59 |
+ M |
+
+
+ | 39 |
+ R3053SA |
+ 957 |
+ Striatum |
+ BXD19 |
+ 60 |
+ F |
+
+
+ | 40 |
+ R3054SA |
+ 947 |
+ Striatum |
+ BXD19 |
+ 60 |
+ M |
+
+
+ | 41 |
+ R3057SA |
+ 1255 |
+ Striatum |
+ BXD20 |
+ 60 |
+ F |
+
+
+ | 42 |
+ R3058SA |
+ 1245 |
+ Striatum |
+ BXD20 |
+ 60 |
+ M |
+
+
+ | 43 |
+ R3059SA |
+ 1197 |
+ Striatum |
+ BXD21 |
+ 48 |
+ F |
+
+
+ | 44 |
+ R3060SA |
+ 1187 |
+ Striatum |
+ BXD21 |
+ 48 |
+ M |
+
+
+ | 45 |
+ R3061SA |
+ 1235 |
+ Striatum |
+ BXD22 |
+ 58 |
+ F |
+
+
+ | 46 |
+ R3062SA |
+ 1275 |
+ Striatum |
+ BXD22 |
+ 60 |
+ M |
+
+
+ | 47 |
+ R3063SA |
+ 1137 |
+ Striatum |
+ BXD23 |
+ 60 |
+ F |
+
+
+ | 48 |
+ R3064SA |
+ 1127 |
+ Striatum |
+ BXD23 |
+ 60 |
+ M |
+
+
+ | 49 |
+ R3065SA |
+ 437 |
+ Striatum |
+ BXD24 |
+ 59 |
+ F |
+
+
+ | 50 |
+ R3066SA |
+ 587 |
+ Striatum |
+ BXD24 |
+ 60 |
+ M |
+
+
+ | 51 |
+ R3067SA |
+ 1107 |
+ Striatum |
+ BXD27 |
+ 60 |
+ F |
+
+
+ | 52 |
+ R3068SA |
+ 1117 |
+ Striatum |
+ BXD27 |
+ 60 |
+ M |
+
+
+ | 53 |
+ R3069SA |
+ 1027 |
+ Striatum |
+ BXD28 |
+ 60 |
+ F |
+
+
+ | 54 |
+ R3070SA |
+ 1037 |
+ Striatum |
+ BXD28 |
+ 60 |
+ M |
+
+
+ | 55 |
+ R3071SA |
+ 1007 |
+ Striatum |
+ BXD29 |
+ 58 |
+ F |
+
+
+ | 56 |
+ R3072SA |
+ 1017 |
+ Striatum |
+ BXD29 |
+ 58 |
+ M |
+
+
+ | 57 |
+ R3073SA |
+ 997 |
+ Striatum |
+ BxD31 |
+ 60 |
+ F |
+
+
+ | 58 |
+ R3074SA |
+ 987 |
+ Striatum |
+ BxD31 |
+ 60 |
+ M |
+
+
+ | 59 |
+ R3075SA |
+ 917 |
+ Striatum |
+ BXD32 |
+ 57 |
+ F |
+
+
+ | 60 |
+ R3076SA |
+ 907 |
+ Striatum |
+ BXD32 |
+ 57 |
+ M |
+
+
+ | 61 |
+ R3077SA |
+ 897 |
+ Striatum |
+ BXD33 |
+ 59 |
+ F |
+
+
+ | 62 |
+ R3078SA |
+ 887 |
+ Striatum |
+ BXD33 |
+ 59 |
+ M |
+
+
+ | 63 |
+ R3079SA |
+ 837 |
+ Striatum |
+ BXD34 |
+ 60 |
+ F |
+
+
+ | 64 |
+ R3080SA |
+ 827 |
+ Striatum |
+ BXD34 |
+ 60 |
+ M |
+
+
+ | 65 |
+ R3081SA |
+ 857 |
+ Striatum |
+ BXD36 |
+ 57 |
+ F |
+
+
+ | 66 |
+ R3082SA |
+ 847 |
+ Striatum |
+ BXD36 |
+ 57 |
+ M |
+
+
+ | 67 |
+ R3083SA |
+ 697 |
+ Striatum |
+ BXD38 |
+ 60 |
+ F |
+
+
+ | 68 |
+ R3084SA |
+ 687 |
+ Striatum |
+ BXD38 |
+ 60 |
+ M |
+
+
+ | 69 |
+ R3085SA |
+ 677 |
+ Striatum |
+ BXD40 |
+ 60 |
+ F |
+
+
+ | 70 |
+ R3086SA |
+ 667 |
+ Striatum |
+ BXD40 |
+ 60 |
+ M |
+
+
+ | 71 |
+ R3087SA |
+ 577 |
+ Striatum |
+ BXD42 |
+ 58 |
+ F |
+
+
+ | 72 |
+ R3088SA |
+ 567 |
+ Striatum |
+ BXD42 |
+ 58 |
+ M |
+
+
+ | 73 |
+ R3097SA |
+ 1975 |
+ Striatum |
+ BXSB/MpJ |
+ 61 |
+ F |
+
+
+ | 74 |
+ R3098SA |
+ 1945 |
+ Striatum |
+ BXSB/MpJ |
+ 61 |
+ M |
+
+
+ | 75 |
+ R3099SA |
+ 1575 |
+ Striatum |
+ C3H/HeJ |
+ 60 |
+ F |
+
+
+ | 76 |
+ R3100SA |
+ 1595 |
+ Striatum |
+ C3H/HeJ |
+ 60 |
+ M |
+
+
+ | 77 |
+ R3101SA |
+ 1228 |
+ Striatum |
+ C57BL/6J |
+ 58 |
+ F |
+
+
+ | 78 |
+ R3102SA |
+ 343 |
+ Striatum |
+ C57BL/6J |
+ 59 |
+ M |
+
+
+ | 79 |
+ R3103SA (sample removed) |
+ 2305 |
+ Striatum |
+ CAST/Ei |
+ 61 |
+ F |
+
+
+ | 80 |
+ R3104SA (sample removed) |
+ 2285 |
+ Striatum |
+ CAST/Ei |
+ 59 |
+ M |
+
+
+ | 81 |
+ R3105SA |
+ 1223 |
+ Striatum |
+ DBA/2J |
+ 58 |
+ F |
+
+
+ | 82 |
+ R3106SA |
+ 344 |
+ Striatum |
+ DBA/2J |
+ 59 |
+ M |
+
+
+ | 83 |
+ R3107SA |
+ 1535 |
+ Striatum |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 84 |
+ R3108SA |
+ 1555 |
+ Striatum |
+ FVB/NJ |
+ 60 |
+ M |
+
+
+ | 85 |
+ R3109SA |
+ 1845 |
+ Striatum |
+ KK/HlJ |
+ 61 |
+ F |
+
+
+ | 86 |
+ R3110SA |
+ 1835 |
+ Striatum |
+ KK/HlJ |
+ 61 |
+ M |
+
+
+ | 87 |
+ R3111SA |
+ 1865 |
+ Striatum |
+ MOLF/EiJ |
+ 60 |
+ F |
+
+
+ | 88 |
+ R3112SA |
+ 1855 |
+ Striatum |
+ MOLF/EiJ |
+ 60 |
+ M |
+
+
+ | 89 |
+ R3113SA |
+ 1295 |
+ Striatum |
+ NOD/LtJ |
+ 58 |
+ F |
+
+
+ | 90 |
+ R3114SA |
+ 1315 |
+ Striatum |
+ NOD/LtJ |
+ 58 |
+ M |
+
+
+ | 91 |
+ R3115SA |
+ 2075 |
+ Striatum |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 92 |
+ R3116SA |
+ 1515 |
+ Striatum |
+ NZB/BlNJ |
+ 58 |
+ M |
+
+
+ | 93 |
+ R3117SA |
+ 1745 |
+ Striatum |
+ NZO/HlLtJ |
+ 61 |
+ F |
+
+
+ | 94 |
+ R3118SA |
+ 1725 |
+ Striatum |
+ NZO/HlLtJ |
+ 61 |
+ M |
+
+
+ | 95 |
+ R3119SA |
+ 1805 |
+ Striatum |
+ NZW/LacJ |
+ 65 |
+ F |
+
+
+ | 96 |
+ R3120SA |
+ 1685 |
+ Striatum |
+ NZW/LacJ |
+ 70 |
+ M |
+
+
+ | 97 |
+ R3121SA |
+ 1875 |
+ Striatum |
+ PWD/PhJ |
+ 70 |
+ F |
+
+
+ | 98 |
+ R3122SA |
+ 1885 |
+ Striatum |
+ PWD/PhJ |
+ 70 |
+ M |
+
+
+ | 99 |
+ R3123SA |
+ 1765 |
+ Striatum |
+ PWK/PhJ |
+ 59 |
+ F |
+
+
+ | 100 |
+ R3124SA |
+ 1785 |
+ Striatum |
+ PWK/PhJ |
+ 60 |
+ M |
+
+
+ | 101 |
+ R3125SA |
+ 1825 |
+ Striatum |
+ WSB/EiJ |
+ 71 |
+ F |
+
+
+ | 102 |
+ R3126SA |
+ 1655 |
+ Striatum |
+ WSB/EiJ |
+ 71 |
+ M |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Striatum_exon_0209/notes.rtf b/general/datasets/Striatum_exon_0209/notes.rtf
new file mode 100644
index 0000000..677a1bd
--- /dev/null
+++ b/general/datasets/Striatum_exon_0209/notes.rtf
@@ -0,0 +1 @@
+Final and fully corrected Exon 1.0 ST array data. Entered by Arthur Centeno. Data error-checking by Manjunatha N. Jagalur . Tissue collected by Glenn Rosen. Array processing by Weikuan Gu.
diff --git a/general/datasets/Striatum_exon_1212/cases.rtf b/general/datasets/Striatum_exon_1212/cases.rtf
new file mode 100644
index 0000000..e4db26e
--- /dev/null
+++ b/general/datasets/Striatum_exon_1212/cases.rtf
@@ -0,0 +1,947 @@
+A movie of the dissection of the brain, including the striatum, by Dr. Glenn Rosen.
+
+About the strains used to generate this set of data
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Tube No. |
+ Tissue |
+ Strain |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R3025SA |
+ 1705 |
+ Striatum |
+ 129S1/SvImJ |
+ 60 |
+ F |
+
+
+ | 2 |
+ R3026SA |
+ 1375 |
+ Striatum |
+ 129S1/SvImJ |
+ 59 |
+ M |
+
+
+ | 3 |
+ R3027SA |
+ 1435 |
+ Striatum |
+ A/J |
+ 59 |
+ F |
+
+
+ | 4 |
+ R3028SA |
+ 1455 |
+ Striatum |
+ A/J |
+ 59 |
+ M |
+
+
+ | 5 |
+ R3029SA |
+ 1395 |
+ Striatum |
+ AKR/J |
+ 59 |
+ F |
+
+
+ | 6 |
+ R3030SA |
+ 1415 |
+ Striatum |
+ AKR/J |
+ 59 |
+ M |
+
+
+ | 7 |
+ R3031SA |
+ 1227 |
+ Striatum |
+ B6D2F1 |
+ 59 |
+ F |
+
+
+ | 8 |
+ R3032SA |
+ 1225 |
+ Striatum |
+ B6D2F1 |
+ 59 |
+ M |
+
+
+ | 9 |
+ R3033SA |
+ 1495 |
+ Striatum |
+ BALB/cByJ |
+ 59 |
+ F |
+
+
+ | 10 |
+ R3034SA |
+ 1475 |
+ Striatum |
+ BALB/cByJ |
+ 59 |
+ M |
+
+
+ | 11 |
+ R3035SA |
+ 1665 |
+ Striatum |
+ BTBRT<+>tf/J |
+ 59 |
+ F |
+
+
+ | 12 |
+ R3036SA |
+ 1615 |
+ Striatum |
+ BTBRT<+>tf/J |
+ 60 |
+ M |
+
+
+ | 13 |
+ R3037SA |
+ 457 |
+ Striatum |
+ BXD1 |
+ 59 |
+ F |
+
+
+ | 14 |
+ R3038SA |
+ 927 |
+ Striatum |
+ BXD1 |
+ 59 |
+ M |
+
+
+ | 15 |
+ R3055SA |
+ 487 |
+ Striatum |
+ BXD2 |
+ 61 |
+ F |
+
+
+ | 16 |
+ R3056SA |
+ 477 |
+ Striatum |
+ BXD2 |
+ 61 |
+ M |
+
+
+ | 17 |
+ R3089SA |
+ 977 |
+ Striatum |
+ BXD5 |
+ 58 |
+ F |
+
+
+ | 18 |
+ R3090SA |
+ 967 |
+ Striatum |
+ BXD5 |
+ 58 |
+ M |
+
+
+ | 19 |
+ R3091SA |
+ 557 |
+ Striatum |
+ BXD6 |
+ 59 |
+ F |
+
+
+ | 20 |
+ R3092SA |
+ 547 |
+ Striatum |
+ BXD6 |
+ 59 |
+ M |
+
+
+ | 21 |
+ R3093SA |
+ 717 |
+ Striatum |
+ BXD8 |
+ 61 |
+ F |
+
+
+ | 22 |
+ R3094SA |
+ 707 |
+ Striatum |
+ BXD8 |
+ 61 |
+ M |
+
+
+ | 23 |
+ R3095SA |
+ 647 |
+ Striatum |
+ BXD9 |
+ 60 |
+ F |
+
+
+ | 24 |
+ R3096SA |
+ 637 |
+ Striatum |
+ BXD9 |
+ 60 |
+ M |
+
+
+ | 25 |
+ R3039SA |
+ 517 |
+ Striatum |
+ BXD11 |
+ 59 |
+ F |
+
+
+ | 26 |
+ R3040SA |
+ 787 |
+ Striatum |
+ BXD11 |
+ 59 |
+ M |
+
+
+ | 27 |
+ R3041SA |
+ 817 |
+ Striatum |
+ BXD12 |
+ 62 |
+ F |
+
+
+ | 28 |
+ R3042SA |
+ 807 |
+ Striatum |
+ BXD12 |
+ 59 |
+ M |
+
+
+ | 29 |
+ R3043SA |
+ 877 |
+ Striatum |
+ BXD13 |
+ 60 |
+ F |
+
+
+ | 30 |
+ R3044SA |
+ 867 |
+ Striatum |
+ BXD13 |
+ 60 |
+ M |
+
+
+ | 31 |
+ R3045SA |
+ 1067 |
+ Striatum |
+ BXD14 |
+ 59 |
+ F |
+
+
+ | 32 |
+ R3144SA |
+ 1077 |
+ Striatum |
+ BXD14 |
+ 59 |
+ M |
+
+
+ | 33 |
+ R3047SA |
+ 1057 |
+ Striatum |
+ BXD15 |
+ 60 |
+ F |
+
+
+ | 34 |
+ R3048SA |
+ 1047 |
+ Striatum |
+ BXD15 |
+ 60 |
+ M |
+
+
+ | 35 |
+ R3049SA |
+ 767 |
+ Striatum |
+ BXD16 |
+ 61 |
+ F |
+
+
+ | 36 |
+ R3050SA |
+ 777 |
+ Striatum |
+ BXD16 |
+ 61 |
+ M |
+
+
+ | 37 |
+ R3051SA |
+ 1177 |
+ Striatum |
+ BXD18 |
+ 59 |
+ F |
+
+
+ | 38 |
+ R3052SA |
+ 1167 |
+ Striatum |
+ BXD18 |
+ 59 |
+ M |
+
+
+ | 39 |
+ R3053SA |
+ 957 |
+ Striatum |
+ BXD19 |
+ 60 |
+ F |
+
+
+ | 40 |
+ R3054SA |
+ 947 |
+ Striatum |
+ BXD19 |
+ 60 |
+ M |
+
+
+ | 41 |
+ R3057SA |
+ 1255 |
+ Striatum |
+ BXD20 |
+ 60 |
+ F |
+
+
+ | 42 |
+ R3058SA |
+ 1245 |
+ Striatum |
+ BXD20 |
+ 60 |
+ M |
+
+
+ | 43 |
+ R3059SA |
+ 1197 |
+ Striatum |
+ BXD21 |
+ 48 |
+ F |
+
+
+ | 44 |
+ R3060SA |
+ 1187 |
+ Striatum |
+ BXD21 |
+ 48 |
+ M |
+
+
+ | 45 |
+ R3061SA |
+ 1235 |
+ Striatum |
+ BXD22 |
+ 58 |
+ F |
+
+
+ | 46 |
+ R3062SA |
+ 1275 |
+ Striatum |
+ BXD22 |
+ 60 |
+ M |
+
+
+ | 47 |
+ R3063SA |
+ 1137 |
+ Striatum |
+ BXD23 |
+ 60 |
+ F |
+
+
+ | 48 |
+ R3064SA |
+ 1127 |
+ Striatum |
+ BXD23 |
+ 60 |
+ M |
+
+
+ | 49 |
+ R3065SA |
+ 437 |
+ Striatum |
+ BXD24 |
+ 59 |
+ F |
+
+
+ | 50 |
+ R3066SA |
+ 587 |
+ Striatum |
+ BXD24 |
+ 60 |
+ M |
+
+
+ | 51 |
+ R3067SA |
+ 1107 |
+ Striatum |
+ BXD27 |
+ 60 |
+ F |
+
+
+ | 52 |
+ R3068SA |
+ 1117 |
+ Striatum |
+ BXD27 |
+ 60 |
+ M |
+
+
+ | 53 |
+ R3069SA |
+ 1027 |
+ Striatum |
+ BXD28 |
+ 60 |
+ F |
+
+
+ | 54 |
+ R3070SA |
+ 1037 |
+ Striatum |
+ BXD28 |
+ 60 |
+ M |
+
+
+ | 55 |
+ R3071SA |
+ 1007 |
+ Striatum |
+ BXD29 |
+ 58 |
+ F |
+
+
+ | 56 |
+ R3072SA |
+ 1017 |
+ Striatum |
+ BXD29 |
+ 58 |
+ M |
+
+
+ | 57 |
+ R3073SA |
+ 997 |
+ Striatum |
+ BxD31 |
+ 60 |
+ F |
+
+
+ | 58 |
+ R3074SA |
+ 987 |
+ Striatum |
+ BxD31 |
+ 60 |
+ M |
+
+
+ | 59 |
+ R3075SA |
+ 917 |
+ Striatum |
+ BXD32 |
+ 57 |
+ F |
+
+
+ | 60 |
+ R3076SA |
+ 907 |
+ Striatum |
+ BXD32 |
+ 57 |
+ M |
+
+
+ | 61 |
+ R3077SA |
+ 897 |
+ Striatum |
+ BXD33 |
+ 59 |
+ F |
+
+
+ | 62 |
+ R3078SA |
+ 887 |
+ Striatum |
+ BXD33 |
+ 59 |
+ M |
+
+
+ | 63 |
+ R3079SA |
+ 837 |
+ Striatum |
+ BXD34 |
+ 60 |
+ F |
+
+
+ | 64 |
+ R3080SA |
+ 827 |
+ Striatum |
+ BXD34 |
+ 60 |
+ M |
+
+
+ | 65 |
+ R3081SA |
+ 857 |
+ Striatum |
+ BXD36 |
+ 57 |
+ F |
+
+
+ | 66 |
+ R3082SA |
+ 847 |
+ Striatum |
+ BXD36 |
+ 57 |
+ M |
+
+
+ | 67 |
+ R3083SA |
+ 697 |
+ Striatum |
+ BXD38 |
+ 60 |
+ F |
+
+
+ | 68 |
+ R3084SA |
+ 687 |
+ Striatum |
+ BXD38 |
+ 60 |
+ M |
+
+
+ | 69 |
+ R3085SA |
+ 677 |
+ Striatum |
+ BXD40 |
+ 60 |
+ F |
+
+
+ | 70 |
+ R3086SA |
+ 667 |
+ Striatum |
+ BXD40 |
+ 60 |
+ M |
+
+
+ | 71 |
+ R3087SA |
+ 577 |
+ Striatum |
+ BXD42 |
+ 58 |
+ F |
+
+
+ | 72 |
+ R3088SA |
+ 567 |
+ Striatum |
+ BXD42 |
+ 58 |
+ M |
+
+
+ | 73 |
+ R3097SA |
+ 1975 |
+ Striatum |
+ BXSB/MpJ |
+ 61 |
+ F |
+
+
+ | 74 |
+ R3098SA |
+ 1945 |
+ Striatum |
+ BXSB/MpJ |
+ 61 |
+ M |
+
+
+ | 75 |
+ R3099SA |
+ 1575 |
+ Striatum |
+ C3H/HeJ |
+ 60 |
+ F |
+
+
+ | 76 |
+ R3100SA |
+ 1595 |
+ Striatum |
+ C3H/HeJ |
+ 60 |
+ M |
+
+
+ | 77 |
+ R3101SA |
+ 1228 |
+ Striatum |
+ C57BL/6J |
+ 58 |
+ F |
+
+
+ | 78 |
+ R3102SA |
+ 343 |
+ Striatum |
+ C57BL/6J |
+ 59 |
+ M |
+
+
+ | 79 |
+ R3103SA (sample removed) |
+ 2305 |
+ Striatum |
+ CAST/Ei |
+ 61 |
+ F |
+
+
+ | 80 |
+ R3104SA (sample removed) |
+ 2285 |
+ Striatum |
+ CAST/Ei |
+ 59 |
+ M |
+
+
+ | 81 |
+ R3105SA |
+ 1223 |
+ Striatum |
+ DBA/2J |
+ 58 |
+ F |
+
+
+ | 82 |
+ R3106SA |
+ 344 |
+ Striatum |
+ DBA/2J |
+ 59 |
+ M |
+
+
+ | 83 |
+ R3107SA |
+ 1535 |
+ Striatum |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 84 |
+ R3108SA |
+ 1555 |
+ Striatum |
+ FVB/NJ |
+ 60 |
+ M |
+
+
+ | 85 |
+ R3109SA |
+ 1845 |
+ Striatum |
+ KK/HlJ |
+ 61 |
+ F |
+
+
+ | 86 |
+ R3110SA |
+ 1835 |
+ Striatum |
+ KK/HlJ |
+ 61 |
+ M |
+
+
+ | 87 |
+ R3111SA |
+ 1865 |
+ Striatum |
+ MOLF/EiJ |
+ 60 |
+ F |
+
+
+ | 88 |
+ R3112SA |
+ 1855 |
+ Striatum |
+ MOLF/EiJ |
+ 60 |
+ M |
+
+
+ | 89 |
+ R3113SA |
+ 1295 |
+ Striatum |
+ NOD/LtJ |
+ 58 |
+ F |
+
+
+ | 90 |
+ R3114SA |
+ 1315 |
+ Striatum |
+ NOD/LtJ |
+ 58 |
+ M |
+
+
+ | 91 |
+ R3115SA |
+ 2075 |
+ Striatum |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 92 |
+ R3116SA |
+ 1515 |
+ Striatum |
+ NZB/BlNJ |
+ 58 |
+ M |
+
+
+ | 93 |
+ R3117SA |
+ 1745 |
+ Striatum |
+ NZO/HlLtJ |
+ 61 |
+ F |
+
+
+ | 94 |
+ R3118SA |
+ 1725 |
+ Striatum |
+ NZO/HlLtJ |
+ 61 |
+ M |
+
+
+ | 95 |
+ R3119SA |
+ 1805 |
+ Striatum |
+ NZW/LacJ |
+ 65 |
+ F |
+
+
+ | 96 |
+ R3120SA |
+ 1685 |
+ Striatum |
+ NZW/LacJ |
+ 70 |
+ M |
+
+
+ | 97 |
+ R3121SA |
+ 1875 |
+ Striatum |
+ PWD/PhJ |
+ 70 |
+ F |
+
+
+ | 98 |
+ R3122SA |
+ 1885 |
+ Striatum |
+ PWD/PhJ |
+ 70 |
+ M |
+
+
+ | 99 |
+ R3123SA |
+ 1765 |
+ Striatum |
+ PWK/PhJ |
+ 59 |
+ F |
+
+
+ | 100 |
+ R3124SA |
+ 1785 |
+ Striatum |
+ PWK/PhJ |
+ 60 |
+ M |
+
+
+ | 101 |
+ R3125SA |
+ 1825 |
+ Striatum |
+ WSB/EiJ |
+ 71 |
+ F |
+
+
+ | 102 |
+ R3126SA |
+ 1655 |
+ Striatum |
+ WSB/EiJ |
+ 71 |
+ M |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Striatum_exon_1212/notes.rtf b/general/datasets/Striatum_exon_1212/notes.rtf
new file mode 100644
index 0000000..677a1bd
--- /dev/null
+++ b/general/datasets/Striatum_exon_1212/notes.rtf
@@ -0,0 +1 @@
+Final and fully corrected Exon 1.0 ST array data. Entered by Arthur Centeno. Data error-checking by Manjunatha N. Jagalur . Tissue collected by Glenn Rosen. Array processing by Weikuan Gu.
diff --git a/general/datasets/Stspl_1107_r/summary.rtf b/general/datasets/Stspl_1107_r/summary.rtf
new file mode 100644
index 0000000..b74d6b2
--- /dev/null
+++ b/general/datasets/Stspl_1107_r/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 43, Name: Stuart Spleen M430v2 (Nov07)
\ No newline at end of file
diff --git a/general/datasets/Suh_liv_rma_0611/experiment-type.rtf b/general/datasets/Suh_liv_rma_0611/experiment-type.rtf
new file mode 100644
index 0000000..a92f1f2
--- /dev/null
+++ b/general/datasets/Suh_liv_rma_0611/experiment-type.rtf
@@ -0,0 +1,158 @@
+This experimental liver gene expression data set (~100 Affymetrix exon-type arrays), was generated by Frank Lammert, Sonja Hillebrandt, Rabea Hall, and colleagues at the Saarland University Medical Center in Homburg, Germany. This work is part of the German Network for Systems Genetics (GeNeSys).
+
+
Expression data after carbon tetrachloride treatment (CCl4, also known as Halon, Freon, carbon tet, or tetrachloromethane) were generated using RNA sample from 30 BXD strains, both parental strains (C57BL/6J, DBA/2J), and B6D2 F1 hybrids. The great majority of cases were females and were treated with carbon tetrachloride injections over a six week period. Three arrays were run for each strain using independent liver samples.
+
+
PURPOSE: The overall goal of the project is to understand the etiology of liver fibrogenesis using carbon tetracholoride as a toxin and inducer of liver disease. Liver fibrogenesis, or scarring of the liver, is the common end-stage of chronic liver diseases, in particular after chronic viral infections. In Germany along complications associated with liver fibrosis cause approximately 10,000 deaths per year. In the past decade key molecular pathomechanisms of hepatic fibrogenesis due to chronic viral infections have been identified. Activated hepatic stellate cells (HSCs) drive the process of de novo deposition of abnormal extracellular matrix, which is modulated by complex interactions between cytokines, receptors, and matrix components.
+
+
Several studies have demonstrated that the course and progression of the fibrogenic response to chronic liver injury is highly variability among individuals. This marked variabilityhas been attributed to etiology, age, gender, and environmental factors. In humans these genetic disease fibrosis predisposition factors have not yet to be studied systematically.
+
+
Our group recently identified a gene variant that contributes to liver fibrogenesis by using QTL mapping in an experimental crosses between fibrosis-susceptible and resistant strains of mice (Hillebrandt et al., 2005). We demonstrated that sequence differences in the HC gene that encodes complement factor C5 (also known as hemolytic complement), are responsible for this strain difference. Common haplotype-tagging polymorphisms of the human HC gene were shown to be associated with advanced fibrosis in chronic hepatitis C virus infection. Thus, the mouse analysis led to the identification of an unknown gene underlying human susceptibility to liver fibrosis, supporting the idea that HC has a causal role in chronic inflammatory disorders and organ fibrogenesis across species.
+
+
As part of the GeNeSys program we have studied liver fibrogenesis in the BXD family of strains as a model for chronic liver injury. This expression data set is used to map complex genetic traits that modulate gene expression and determine gene networks during liver fibrogenesis in GRPs.
+
+
The following assays are complete or are in progress:
+
+
+- Liver fibrosis studies: Phenotyping protocols include standard histology, morphometry, biochemical quantification of hepatic collagen contents, serum surrogate markers of fibrosis, immunohistochemistry, and expression profiling of proinflammatory and profibrogenic genes by qRT-PCR and Affymetrix microarrays (this data set).
+
+
+
- Characterization of liver cells: Liver immune cell fractions will be isolated and sorted according to SOPs developed in the Lammert laboratory. In addition, in cooperation with the technology platforms of the HepatoSys Network of Excellence, we will characterize primary HSCs that play critical roles in liver fibrogenesis with respect to proinflammatory responses during chronic liver inflammation.
+
+
+
+
+PROTOCOL for carbon tetrachloride (CCl4) treatment (parental strains, F1, and BXD lines). Animals were injected with CCl4 (12 x 0.7 mg/kg ip) over a 6-week period on days 1 and 4 of each week. Intraperitoneal injections were begun between the ages of 6-8 weeks. Animals were sacrificed after 6 weeks of treatment at 12 to 14 weeks of age. Untreated control mice from only the two parental strains were also sacrificed at 12-14 weeks of age
+
+
+Tissue: Livers were snap frozen in liquid nitrogen immediately after harvesting. RNA was extracted and submitted to the UTHSC Molecular Resource Core for expression profiling. Expression data were generated by Lorne Rose, William Taylor and colleagues. Data were entered into GeneNetwork by Arthur Centeno, June 17, 2011. Data were quality controlled by R. W. Williams.
+
+QC Results: This data set consists of expression data for 33 strains. A total of 166 probe sets are associated with LOD scores above 10 and the highest linkage score of 22 for Rpl3 (probe set 10430669). Strain distribution patterns of eQTLs with a Mendelian expression pattern match those of their closest markers perfectly, verifying that there are no errors of strain assignment in this data set.
+
+
Analysis of XIST probe set 1060617 confirms that most strains are purely female. However, only males were available for BXD1 and BXD6. BXD28 and BXD33 data are based on the average of two female samples and one male sample. All other strains are purely female.
+
+
Data were analyzed by Rabea Hall and Dr. Frank Lammert at the Universitätsklinikum des Saarlandes in Homburg, Germany.
+
+
Contacts: rabea.hall at uks.eu, Rabea.Hall at uniklinikum-saarland.de, and frank.lammert at uks.eu
+
+
+
+
+
Table updated 7-19-2011
+
+
+
+
+
+| Index | Sample ID | Strain ID | Treatment |
+| 1 | 504 | B6D2F1 | CCl4 |
+| 2 | 506 | B6D2F1 | CCl4 |
+| 3 | 508 | B6D2F1 | CCl4 |
+| 4 | 414 | C57BL/6J | CCl4 |
+| 5 | 488 | C57BL/6J | CCl4 |
+| 6 | 489 | C57BL/6J | CCl4 |
+| 7 | B6J1 | C57BL/6J | untreated control |
+| 8 | B6J2 | C57BL/6J | untreated control |
+| 9 | B6J3 | C57BL/6J | untreated control |
+| 10 | 449 | DBA/2J | CCl4 |
+| 11 | 450 | DBA/2J | CCl4 |
+| 12 | 451 | DBA/2J | CCl4 |
+| 13 | 219.1 | DBA/2J | untreated control |
+| 14 | 219.2 | DBA/2J | untreated control |
+| 15 | 219.3 | DBA/2J | untreated control |
+| 16 | 276 | BXD1 | CCl4 |
+| 17 | 278 | BXD1 | CCl4 |
+| 18 | 279 | BXD1 | CCl4 |
+| 19 | 353 | BXD2 | CCl4 |
+| 20 | 357 | BXD2 | CCl4 |
+| 21 | 358 | BXD2 | CCl4 |
+| 22 | 272 | BXD6 | CCl4 |
+| 23 | 273 | BXD6 | CCl4 |
+| 24 | 274 | BXD6 | CCl4 |
+| 25 | 405 | BXD11 | CCl4 |
+| 26 | 406 | BXD11 | CCl4 |
+| 27 | 408 | BXD11 | CCl4 |
+| 28 | 239 | BXD12 | CCl4 |
+| 29 | 240 | BXD12 | CCl4 |
+| 30 | 241 | BXD12 | CCl4 |
+| 31 | 553 | BXD13 | CCl4 |
+| 32 | 554 | BXD13 | CCl4 |
+| 33 | 555 | BXD13 | CCl4 |
+| 34 | 249 | BXD14 | CCl4 |
+| 35 | 250 | BXD14 | CCl4 |
+| 36 | 288 | BXD14 | CCl4 |
+| 37 | 191 | BXD19 | CCl4 |
+| 38 | 644 | BXD19 | CCl4 |
+| 39 | 645 | BXD19 | CCl4 |
+| 40 | 442 | BXD24a | CCl4 |
+| 41 | 443 | BXD24a | CCl4 |
+| 42 | 444 | BXD24a | CCl4 |
+| 43 | 216 | BXD27 | CCl4 |
+| 44 | 218 | BXD27 | CCl4 |
+| 45 | 290 | BXD27 | CCl4 |
+| 46 | 28 | BXD28 | CCl4 |
+| 47 | 71 | BXD28 | CCl4 |
+| 48 | 129 | BXD28 | CCl4 |
+| 49 | 219 | BXD31 | CCl4 |
+| 50 | 220 | BXD31 | CCl4 |
+| 51 | 231 | BXD31 | CCl4 |
+| 52 | 549 | BXD32 | CCl4 |
+| 53 | 550 | BXD32 | CCl4 |
+| 54 | 551 | BXD32 | CCl4 |
+| 55 | 139 | BXD33 | CCl4 |
+| 56 | 140 | BXD33 | CCl4 |
+| 57 | 559 | BXD33 | CCl4 |
+| 58 | 132 | BXD34 | CCl4 |
+| 59 | 146 | BXD34 | CCl4 |
+| 60 | 147 | BXD34 | CCl4 |
+| 61 | 293 | BXD39 | CCl4 |
+| 62 | 597 | BXD39 | CCl4 |
+| 63 | 599 | BXD39 | CCl4 |
+| 64 | 154 | BXD40 | CCl4 |
+| 65 | 570 | BXD40 | CCl4 |
+| 66 | 572 | BXD40 | CCl4 |
+| 67 | 361 | BXD42 | CCl4 |
+| 68 | 362 | BXD42 | CCl4 |
+| 69 | 373 | BXD42 | CCl4 |
+| 70 | 428 | BXD43 | CCl4 |
+| 71 | 429 | BXD43 | CCl4 |
+| 72 | 556 | BXD43 | CCl4 |
+| 73 | 472 | BXD51 | CCl4 |
+| 74 | 473 | BXD51 | CCl4 |
+| 75 | 474 | BXD51 | CCl4 |
+| 76 | 533 | BXD55 | CCl4 |
+| 77 | 534 | BXD55 | CCl4 |
+| 78 | 535 | BXD55 | CCl4 |
+| 79 | 519 | BXD62 | CCl4 |
+| 80 | 520 | BXD62 | CCl4 |
+| 81 | 521 | BXD62 | CCl4 |
+| 82 | 463 | BXD65 | CCl4 |
+| 83 | 464 | BXD65 | CCl4 |
+| 84 | 465 | BXD65 | CCl4 |
+| 85 | 327 | BXD69 | CCl4 |
+| 86 | 346 | BXD69 | CCl4 |
+| 87 | 347 | BXD69 | CCl4 |
+| 88 | 614 | BXD73 | CCl4 |
+| 89 | 616 | BXD73 | CCl4 |
+| 90 | 619 | BXD73 | CCl4 |
+| 91 | 395 | BXD75 | CCl4 |
+| 92 | 482 | BXD75 | CCl4 |
+| 93 | 483 | BXD75 | CCl4 |
+| 94 | 317 | BXD87 | CCl4 |
+| 95 | 319 | BXD87 | CCl4 |
+| 96 | 322 | BXD87 | CCl4 |
+| 97 | 374 | BXD90 | CCl4 |
+| 98 | 388 | BXD90 | CCl4 |
+| 99 | 389 | BXD90 | CCl4 |
+| 100 | 402 | BXD96 | CCl4 |
+| 101 | 403 | BXD96 | CCl4 |
+| 102 | 404 | BXD96 | CCl4 |
+| 103 | 584 | BXD98 | CCl4 |
+| 104 | 585 | BXD98 | CCl4 |
+| 105 | 607 | BXD98 | CCl4 |
+
+
+
+ |
+
+
+
\ No newline at end of file
diff --git a/general/datasets/Suh_liv_rma_0611/processing.rtf b/general/datasets/Suh_liv_rma_0611/processing.rtf
new file mode 100644
index 0000000..ca7e79b
--- /dev/null
+++ b/general/datasets/Suh_liv_rma_0611/processing.rtf
@@ -0,0 +1,660 @@
+QC Results: This data set consists of expression data for 33 strains. A total of 166 probe sets are associated with LOD scores above 10 and the highest linkage score of 22 for Rpl3 (probe set 10430669). Strain distribution patterns of eQTLs with a Mendelian expression pattern match those of their closest markers perfectly, verifying that there are no errors of strain assignment in this data set.
+
+Analysis of XIST probe set 1060617 confirms that most strains are purely female. However, only males were available for BXD1 and BXD6. BXD28 and BXD33 data are based on the average of two female samples and one male sample. All other strains are purely female.
+
+Data were analyzed by Rabea Hall and Dr. Frank Lammert at the Universitätsklinikum des Saarlandes in Homburg, Germany.
+
+Contacts: rabea.hall at uks.eu, Rabea.Hall at uniklinikum-saarland.de, and frank.lammert at uks.eu
+
+Table updated 7-19-2011
+
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain ID |
+ Treatment |
+
+
+ | 1 |
+ 504 |
+ B6D2F1 |
+ CCl4 |
+
+
+ | 2 |
+ 506 |
+ B6D2F1 |
+ CCl4 |
+
+
+ | 3 |
+ 508 |
+ B6D2F1 |
+ CCl4 |
+
+
+ | 4 |
+ 414 |
+ C57BL/6J |
+ CCl4 |
+
+
+ | 5 |
+ 488 |
+ C57BL/6J |
+ CCl4 |
+
+
+ | 6 |
+ 489 |
+ C57BL/6J |
+ CCl4 |
+
+
+ | 7 |
+ B6J1 |
+ C57BL/6J |
+ untreated control |
+
+
+ | 8 |
+ B6J2 |
+ C57BL/6J |
+ untreated control |
+
+
+ | 9 |
+ B6J3 |
+ C57BL/6J |
+ untreated control |
+
+
+ | 10 |
+ 449 |
+ DBA/2J |
+ CCl4 |
+
+
+ | 11 |
+ 450 |
+ DBA/2J |
+ CCl4 |
+
+
+ | 12 |
+ 451 |
+ DBA/2J |
+ CCl4 |
+
+
+ | 13 |
+ 219.1 |
+ DBA/2J |
+ untreated control |
+
+
+ | 14 |
+ 219.2 |
+ DBA/2J |
+ untreated control |
+
+
+ | 15 |
+ 219.3 |
+ DBA/2J |
+ untreated control |
+
+
+ | 16 |
+ 276 |
+ BXD1 |
+ CCl4 |
+
+
+ | 17 |
+ 278 |
+ BXD1 |
+ CCl4 |
+
+
+ | 18 |
+ 279 |
+ BXD1 |
+ CCl4 |
+
+
+ | 19 |
+ 353 |
+ BXD2 |
+ CCl4 |
+
+
+ | 20 |
+ 357 |
+ BXD2 |
+ CCl4 |
+
+
+ | 21 |
+ 358 |
+ BXD2 |
+ CCl4 |
+
+
+ | 22 |
+ 272 |
+ BXD6 |
+ CCl4 |
+
+
+ | 23 |
+ 273 |
+ BXD6 |
+ CCl4 |
+
+
+ | 24 |
+ 274 |
+ BXD6 |
+ CCl4 |
+
+
+ | 25 |
+ 405 |
+ BXD11 |
+ CCl4 |
+
+
+ | 26 |
+ 406 |
+ BXD11 |
+ CCl4 |
+
+
+ | 27 |
+ 408 |
+ BXD11 |
+ CCl4 |
+
+
+ | 28 |
+ 239 |
+ BXD12 |
+ CCl4 |
+
+
+ | 29 |
+ 240 |
+ BXD12 |
+ CCl4 |
+
+
+ | 30 |
+ 241 |
+ BXD12 |
+ CCl4 |
+
+
+ | 31 |
+ 553 |
+ BXD13 |
+ CCl4 |
+
+
+ | 32 |
+ 554 |
+ BXD13 |
+ CCl4 |
+
+
+ | 33 |
+ 555 |
+ BXD13 |
+ CCl4 |
+
+
+ | 34 |
+ 249 |
+ BXD14 |
+ CCl4 |
+
+
+ | 35 |
+ 250 |
+ BXD14 |
+ CCl4 |
+
+
+ | 36 |
+ 288 |
+ BXD14 |
+ CCl4 |
+
+
+ | 37 |
+ 191 |
+ BXD19 |
+ CCl4 |
+
+
+ | 38 |
+ 644 |
+ BXD19 |
+ CCl4 |
+
+
+ | 39 |
+ 645 |
+ BXD19 |
+ CCl4 |
+
+
+ | 40 |
+ 442 |
+ BXD24a |
+ CCl4 |
+
+
+ | 41 |
+ 443 |
+ BXD24a |
+ CCl4 |
+
+
+ | 42 |
+ 444 |
+ BXD24a |
+ CCl4 |
+
+
+ | 43 |
+ 216 |
+ BXD27 |
+ CCl4 |
+
+
+ | 44 |
+ 218 |
+ BXD27 |
+ CCl4 |
+
+
+ | 45 |
+ 290 |
+ BXD27 |
+ CCl4 |
+
+
+ | 46 |
+ 28 |
+ BXD28 |
+ CCl4 |
+
+
+ | 47 |
+ 71 |
+ BXD28 |
+ CCl4 |
+
+
+ | 48 |
+ 129 |
+ BXD28 |
+ CCl4 |
+
+
+ | 49 |
+ 219 |
+ BXD31 |
+ CCl4 |
+
+
+ | 50 |
+ 220 |
+ BXD31 |
+ CCl4 |
+
+
+ | 51 |
+ 231 |
+ BXD31 |
+ CCl4 |
+
+
+ | 52 |
+ 549 |
+ BXD32 |
+ CCl4 |
+
+
+ | 53 |
+ 550 |
+ BXD32 |
+ CCl4 |
+
+
+ | 54 |
+ 551 |
+ BXD32 |
+ CCl4 |
+
+
+ | 55 |
+ 139 |
+ BXD33 |
+ CCl4 |
+
+
+ | 56 |
+ 140 |
+ BXD33 |
+ CCl4 |
+
+
+ | 57 |
+ 559 |
+ BXD33 |
+ CCl4 |
+
+
+ | 58 |
+ 132 |
+ BXD34 |
+ CCl4 |
+
+
+ | 59 |
+ 146 |
+ BXD34 |
+ CCl4 |
+
+
+ | 60 |
+ 147 |
+ BXD34 |
+ CCl4 |
+
+
+ | 61 |
+ 293 |
+ BXD39 |
+ CCl4 |
+
+
+ | 62 |
+ 597 |
+ BXD39 |
+ CCl4 |
+
+
+ | 63 |
+ 599 |
+ BXD39 |
+ CCl4 |
+
+
+ | 64 |
+ 154 |
+ BXD40 |
+ CCl4 |
+
+
+ | 65 |
+ 570 |
+ BXD40 |
+ CCl4 |
+
+
+ | 66 |
+ 572 |
+ BXD40 |
+ CCl4 |
+
+
+ | 67 |
+ 361 |
+ BXD42 |
+ CCl4 |
+
+
+ | 68 |
+ 362 |
+ BXD42 |
+ CCl4 |
+
+
+ | 69 |
+ 373 |
+ BXD42 |
+ CCl4 |
+
+
+ | 70 |
+ 428 |
+ BXD43 |
+ CCl4 |
+
+
+ | 71 |
+ 429 |
+ BXD43 |
+ CCl4 |
+
+
+ | 72 |
+ 556 |
+ BXD43 |
+ CCl4 |
+
+
+ | 73 |
+ 472 |
+ BXD51 |
+ CCl4 |
+
+
+ | 74 |
+ 473 |
+ BXD51 |
+ CCl4 |
+
+
+ | 75 |
+ 474 |
+ BXD51 |
+ CCl4 |
+
+
+ | 76 |
+ 533 |
+ BXD55 |
+ CCl4 |
+
+
+ | 77 |
+ 534 |
+ BXD55 |
+ CCl4 |
+
+
+ | 78 |
+ 535 |
+ BXD55 |
+ CCl4 |
+
+
+ | 79 |
+ 519 |
+ BXD62 |
+ CCl4 |
+
+
+ | 80 |
+ 520 |
+ BXD62 |
+ CCl4 |
+
+
+ | 81 |
+ 521 |
+ BXD62 |
+ CCl4 |
+
+
+ | 82 |
+ 463 |
+ BXD65 |
+ CCl4 |
+
+
+ | 83 |
+ 464 |
+ BXD65 |
+ CCl4 |
+
+
+ | 84 |
+ 465 |
+ BXD65 |
+ CCl4 |
+
+
+ | 85 |
+ 327 |
+ BXD69 |
+ CCl4 |
+
+
+ | 86 |
+ 346 |
+ BXD69 |
+ CCl4 |
+
+
+ | 87 |
+ 347 |
+ BXD69 |
+ CCl4 |
+
+
+ | 88 |
+ 614 |
+ BXD73 |
+ CCl4 |
+
+
+ | 89 |
+ 616 |
+ BXD73 |
+ CCl4 |
+
+
+ | 90 |
+ 619 |
+ BXD73 |
+ CCl4 |
+
+
+ | 91 |
+ 395 |
+ BXD75 |
+ CCl4 |
+
+
+ | 92 |
+ 482 |
+ BXD75 |
+ CCl4 |
+
+
+ | 93 |
+ 483 |
+ BXD75 |
+ CCl4 |
+
+
+ | 94 |
+ 317 |
+ BXD87 |
+ CCl4 |
+
+
+ | 95 |
+ 319 |
+ BXD87 |
+ CCl4 |
+
+
+ | 96 |
+ 322 |
+ BXD87 |
+ CCl4 |
+
+
+ | 97 |
+ 374 |
+ BXD90 |
+ CCl4 |
+
+
+ | 98 |
+ 388 |
+ BXD90 |
+ CCl4 |
+
+
+ | 99 |
+ 389 |
+ BXD90 |
+ CCl4 |
+
+
+ | 100 |
+ 402 |
+ BXD96 |
+ CCl4 |
+
+
+ | 101 |
+ 403 |
+ BXD96 |
+ CCl4 |
+
+
+ | 102 |
+ 404 |
+ BXD96 |
+ CCl4 |
+
+
+ | 103 |
+ 584 |
+ BXD98 |
+ CCl4 |
+
+
+ | 104 |
+ 585 |
+ BXD98 |
+ CCl4 |
+
+
+ | 105 |
+ 607 |
+ BXD98 |
+ CCl4 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Suh_liv_rma_0611/summary.rtf b/general/datasets/Suh_liv_rma_0611/summary.rtf
new file mode 100644
index 0000000..2684b46
--- /dev/null
+++ b/general/datasets/Suh_liv_rma_0611/summary.rtf
@@ -0,0 +1,22 @@
+Saarland University Homburg (SUH) Carbon Tetrachloride-Treated BXD Mouse Affymetrix Mouse Gene 1.0 ST Array data set
+
+This experimental liver gene expression data set (~100 Affymetrix exon-type arrays), was generated by Frank Lammert, Sonja Hillebrandt, Rabea Hall, and colleagues at the Saarland University Medical Center in Homburg, Germany. This work is part of the German Network for Systems Genetics (GeNeSys).
+
+Expression data after carbon tetrachloride treatment (CCl4, also known as Halon, Freon, carbon tet, or tetrachloromethane) were generated using RNA sample from 30 BXD strains, both parental strains (C57BL/6J, DBA/2J), and B6D2 F1 hybrids. The great majority of cases were females and were treated with carbon tetrachloride injections over a six week period. Three arrays were run for each strain using independent liver samples.
+
+PURPOSE: The overall goal of the project is to understand the etiology of liver fibrogenesis using carbon tetracholoride as a toxin and inducer of liver disease. Liver fibrogenesis, or scarring of the liver, is the common end-stage of chronic liver diseases, in particular after chronic viral infections. In Germany along complications associated with liver fibrosis cause approximately 10,000 deaths per year. In the past decade key molecular pathomechanisms of hepatic fibrogenesis due to chronic viral infections have been identified. Activated hepatic stellate cells (HSCs) drive the process of de novo deposition of abnormal extracellular matrix, which is modulated by complex interactions between cytokines, receptors, and matrix components.
+
+Several studies have demonstrated that the course and progression of the fibrogenic response to chronic liver injury is highly variability among individuals. This marked variabilityhas been attributed to etiology, age, gender, and environmental factors. In humans these genetic disease fibrosis predisposition factors have not yet to be studied systematically.
+
+Our group recently identified a gene variant that contributes to liver fibrogenesis by using QTL mapping in an experimental crosses between fibrosis-susceptible and resistant strains of mice (Hillebrandt et al., 2005). We demonstrated that sequence differences in the HC gene that encodes complement factor C5 (also known as hemolytic complement), are responsible for this strain difference. Common haplotype-tagging polymorphisms of the human HC gene were shown to be associated with advanced fibrosis in chronic hepatitis C virus infection. Thus, the mouse analysis led to the identification of an unknown gene underlying human susceptibility to liver fibrosis, supporting the idea that HC has a causal role in chronic inflammatory disorders and organ fibrogenesis across species.
+
+As part of the GeNeSys program we have studied liver fibrogenesis in the BXD family of strains as a model for chronic liver injury. This expression data set is used to map complex genetic traits that modulate gene expression and determine gene networks during liver fibrogenesis in GRPs.
+
+The following assays are complete or are in progress:
+
+
+ - Liver fibrosis studies: Phenotyping protocols include standard histology, morphometry, biochemical quantification of hepatic collagen contents, serum surrogate markers of fibrosis, immunohistochemistry, and expression profiling of proinflammatory and profibrogenic genes by qRT-PCR and Affymetrix microarrays (this data set).
+ - Characterization of liver cells: Liver immune cell fractions will be isolated and sorted according to SOPs developed in the Lammert laboratory. In addition, in cooperation with the technology platforms of the HepatoSys Network of Excellence, we will characterize primary HSCs that play critical roles in liver fibrogenesis with respect to proinflammatory responses during chronic liver inflammation.
+
+
+PROTOCOL for carbon tetrachloride (CCl4) treatment (parental strains, F1, and BXD lines). Animals were injected with CCl4 (12 x 0.7 mg/kg ip) over a 6-week period on days 1 and 4 of each week. Intraperitoneal injections were begun between the ages of 6-8 weeks. Animals were sacrificed after 6 weeks of treatment at 12 to 14 weeks of age. Untreated control mice from only the two parental strains were also sacrificed at 12-14 weeks of age
diff --git a/general/datasets/Suh_liv_rma_0611/tissue.rtf b/general/datasets/Suh_liv_rma_0611/tissue.rtf
new file mode 100644
index 0000000..05a7607
--- /dev/null
+++ b/general/datasets/Suh_liv_rma_0611/tissue.rtf
@@ -0,0 +1 @@
+Tissue: Livers were snap frozen in liquid nitrogen immediately after harvesting. RNA was extracted and submitted to the UTHSC Molecular Resource Core for expression profiling. Expression data were generated by Lorne Rose, William Taylor and colleagues. Data were entered into GeneNetwork by Arthur Centeno, June 17, 2011. Data were quality controlled by R. W. Williams.
diff --git a/general/datasets/Suh_liv_rmaex_0611/processing.rtf b/general/datasets/Suh_liv_rmaex_0611/processing.rtf
new file mode 100644
index 0000000..ca7e79b
--- /dev/null
+++ b/general/datasets/Suh_liv_rmaex_0611/processing.rtf
@@ -0,0 +1,660 @@
+QC Results: This data set consists of expression data for 33 strains. A total of 166 probe sets are associated with LOD scores above 10 and the highest linkage score of 22 for Rpl3 (probe set 10430669). Strain distribution patterns of eQTLs with a Mendelian expression pattern match those of their closest markers perfectly, verifying that there are no errors of strain assignment in this data set.
+
+Analysis of XIST probe set 1060617 confirms that most strains are purely female. However, only males were available for BXD1 and BXD6. BXD28 and BXD33 data are based on the average of two female samples and one male sample. All other strains are purely female.
+
+Data were analyzed by Rabea Hall and Dr. Frank Lammert at the Universitätsklinikum des Saarlandes in Homburg, Germany.
+
+Contacts: rabea.hall at uks.eu, Rabea.Hall at uniklinikum-saarland.de, and frank.lammert at uks.eu
+
+Table updated 7-19-2011
+
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Strain ID |
+ Treatment |
+
+
+ | 1 |
+ 504 |
+ B6D2F1 |
+ CCl4 |
+
+
+ | 2 |
+ 506 |
+ B6D2F1 |
+ CCl4 |
+
+
+ | 3 |
+ 508 |
+ B6D2F1 |
+ CCl4 |
+
+
+ | 4 |
+ 414 |
+ C57BL/6J |
+ CCl4 |
+
+
+ | 5 |
+ 488 |
+ C57BL/6J |
+ CCl4 |
+
+
+ | 6 |
+ 489 |
+ C57BL/6J |
+ CCl4 |
+
+
+ | 7 |
+ B6J1 |
+ C57BL/6J |
+ untreated control |
+
+
+ | 8 |
+ B6J2 |
+ C57BL/6J |
+ untreated control |
+
+
+ | 9 |
+ B6J3 |
+ C57BL/6J |
+ untreated control |
+
+
+ | 10 |
+ 449 |
+ DBA/2J |
+ CCl4 |
+
+
+ | 11 |
+ 450 |
+ DBA/2J |
+ CCl4 |
+
+
+ | 12 |
+ 451 |
+ DBA/2J |
+ CCl4 |
+
+
+ | 13 |
+ 219.1 |
+ DBA/2J |
+ untreated control |
+
+
+ | 14 |
+ 219.2 |
+ DBA/2J |
+ untreated control |
+
+
+ | 15 |
+ 219.3 |
+ DBA/2J |
+ untreated control |
+
+
+ | 16 |
+ 276 |
+ BXD1 |
+ CCl4 |
+
+
+ | 17 |
+ 278 |
+ BXD1 |
+ CCl4 |
+
+
+ | 18 |
+ 279 |
+ BXD1 |
+ CCl4 |
+
+
+ | 19 |
+ 353 |
+ BXD2 |
+ CCl4 |
+
+
+ | 20 |
+ 357 |
+ BXD2 |
+ CCl4 |
+
+
+ | 21 |
+ 358 |
+ BXD2 |
+ CCl4 |
+
+
+ | 22 |
+ 272 |
+ BXD6 |
+ CCl4 |
+
+
+ | 23 |
+ 273 |
+ BXD6 |
+ CCl4 |
+
+
+ | 24 |
+ 274 |
+ BXD6 |
+ CCl4 |
+
+
+ | 25 |
+ 405 |
+ BXD11 |
+ CCl4 |
+
+
+ | 26 |
+ 406 |
+ BXD11 |
+ CCl4 |
+
+
+ | 27 |
+ 408 |
+ BXD11 |
+ CCl4 |
+
+
+ | 28 |
+ 239 |
+ BXD12 |
+ CCl4 |
+
+
+ | 29 |
+ 240 |
+ BXD12 |
+ CCl4 |
+
+
+ | 30 |
+ 241 |
+ BXD12 |
+ CCl4 |
+
+
+ | 31 |
+ 553 |
+ BXD13 |
+ CCl4 |
+
+
+ | 32 |
+ 554 |
+ BXD13 |
+ CCl4 |
+
+
+ | 33 |
+ 555 |
+ BXD13 |
+ CCl4 |
+
+
+ | 34 |
+ 249 |
+ BXD14 |
+ CCl4 |
+
+
+ | 35 |
+ 250 |
+ BXD14 |
+ CCl4 |
+
+
+ | 36 |
+ 288 |
+ BXD14 |
+ CCl4 |
+
+
+ | 37 |
+ 191 |
+ BXD19 |
+ CCl4 |
+
+
+ | 38 |
+ 644 |
+ BXD19 |
+ CCl4 |
+
+
+ | 39 |
+ 645 |
+ BXD19 |
+ CCl4 |
+
+
+ | 40 |
+ 442 |
+ BXD24a |
+ CCl4 |
+
+
+ | 41 |
+ 443 |
+ BXD24a |
+ CCl4 |
+
+
+ | 42 |
+ 444 |
+ BXD24a |
+ CCl4 |
+
+
+ | 43 |
+ 216 |
+ BXD27 |
+ CCl4 |
+
+
+ | 44 |
+ 218 |
+ BXD27 |
+ CCl4 |
+
+
+ | 45 |
+ 290 |
+ BXD27 |
+ CCl4 |
+
+
+ | 46 |
+ 28 |
+ BXD28 |
+ CCl4 |
+
+
+ | 47 |
+ 71 |
+ BXD28 |
+ CCl4 |
+
+
+ | 48 |
+ 129 |
+ BXD28 |
+ CCl4 |
+
+
+ | 49 |
+ 219 |
+ BXD31 |
+ CCl4 |
+
+
+ | 50 |
+ 220 |
+ BXD31 |
+ CCl4 |
+
+
+ | 51 |
+ 231 |
+ BXD31 |
+ CCl4 |
+
+
+ | 52 |
+ 549 |
+ BXD32 |
+ CCl4 |
+
+
+ | 53 |
+ 550 |
+ BXD32 |
+ CCl4 |
+
+
+ | 54 |
+ 551 |
+ BXD32 |
+ CCl4 |
+
+
+ | 55 |
+ 139 |
+ BXD33 |
+ CCl4 |
+
+
+ | 56 |
+ 140 |
+ BXD33 |
+ CCl4 |
+
+
+ | 57 |
+ 559 |
+ BXD33 |
+ CCl4 |
+
+
+ | 58 |
+ 132 |
+ BXD34 |
+ CCl4 |
+
+
+ | 59 |
+ 146 |
+ BXD34 |
+ CCl4 |
+
+
+ | 60 |
+ 147 |
+ BXD34 |
+ CCl4 |
+
+
+ | 61 |
+ 293 |
+ BXD39 |
+ CCl4 |
+
+
+ | 62 |
+ 597 |
+ BXD39 |
+ CCl4 |
+
+
+ | 63 |
+ 599 |
+ BXD39 |
+ CCl4 |
+
+
+ | 64 |
+ 154 |
+ BXD40 |
+ CCl4 |
+
+
+ | 65 |
+ 570 |
+ BXD40 |
+ CCl4 |
+
+
+ | 66 |
+ 572 |
+ BXD40 |
+ CCl4 |
+
+
+ | 67 |
+ 361 |
+ BXD42 |
+ CCl4 |
+
+
+ | 68 |
+ 362 |
+ BXD42 |
+ CCl4 |
+
+
+ | 69 |
+ 373 |
+ BXD42 |
+ CCl4 |
+
+
+ | 70 |
+ 428 |
+ BXD43 |
+ CCl4 |
+
+
+ | 71 |
+ 429 |
+ BXD43 |
+ CCl4 |
+
+
+ | 72 |
+ 556 |
+ BXD43 |
+ CCl4 |
+
+
+ | 73 |
+ 472 |
+ BXD51 |
+ CCl4 |
+
+
+ | 74 |
+ 473 |
+ BXD51 |
+ CCl4 |
+
+
+ | 75 |
+ 474 |
+ BXD51 |
+ CCl4 |
+
+
+ | 76 |
+ 533 |
+ BXD55 |
+ CCl4 |
+
+
+ | 77 |
+ 534 |
+ BXD55 |
+ CCl4 |
+
+
+ | 78 |
+ 535 |
+ BXD55 |
+ CCl4 |
+
+
+ | 79 |
+ 519 |
+ BXD62 |
+ CCl4 |
+
+
+ | 80 |
+ 520 |
+ BXD62 |
+ CCl4 |
+
+
+ | 81 |
+ 521 |
+ BXD62 |
+ CCl4 |
+
+
+ | 82 |
+ 463 |
+ BXD65 |
+ CCl4 |
+
+
+ | 83 |
+ 464 |
+ BXD65 |
+ CCl4 |
+
+
+ | 84 |
+ 465 |
+ BXD65 |
+ CCl4 |
+
+
+ | 85 |
+ 327 |
+ BXD69 |
+ CCl4 |
+
+
+ | 86 |
+ 346 |
+ BXD69 |
+ CCl4 |
+
+
+ | 87 |
+ 347 |
+ BXD69 |
+ CCl4 |
+
+
+ | 88 |
+ 614 |
+ BXD73 |
+ CCl4 |
+
+
+ | 89 |
+ 616 |
+ BXD73 |
+ CCl4 |
+
+
+ | 90 |
+ 619 |
+ BXD73 |
+ CCl4 |
+
+
+ | 91 |
+ 395 |
+ BXD75 |
+ CCl4 |
+
+
+ | 92 |
+ 482 |
+ BXD75 |
+ CCl4 |
+
+
+ | 93 |
+ 483 |
+ BXD75 |
+ CCl4 |
+
+
+ | 94 |
+ 317 |
+ BXD87 |
+ CCl4 |
+
+
+ | 95 |
+ 319 |
+ BXD87 |
+ CCl4 |
+
+
+ | 96 |
+ 322 |
+ BXD87 |
+ CCl4 |
+
+
+ | 97 |
+ 374 |
+ BXD90 |
+ CCl4 |
+
+
+ | 98 |
+ 388 |
+ BXD90 |
+ CCl4 |
+
+
+ | 99 |
+ 389 |
+ BXD90 |
+ CCl4 |
+
+
+ | 100 |
+ 402 |
+ BXD96 |
+ CCl4 |
+
+
+ | 101 |
+ 403 |
+ BXD96 |
+ CCl4 |
+
+
+ | 102 |
+ 404 |
+ BXD96 |
+ CCl4 |
+
+
+ | 103 |
+ 584 |
+ BXD98 |
+ CCl4 |
+
+
+ | 104 |
+ 585 |
+ BXD98 |
+ CCl4 |
+
+
+ | 105 |
+ 607 |
+ BXD98 |
+ CCl4 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Suh_liv_rmaex_0611/summary.rtf b/general/datasets/Suh_liv_rmaex_0611/summary.rtf
new file mode 100644
index 0000000..2684b46
--- /dev/null
+++ b/general/datasets/Suh_liv_rmaex_0611/summary.rtf
@@ -0,0 +1,22 @@
+Saarland University Homburg (SUH) Carbon Tetrachloride-Treated BXD Mouse Affymetrix Mouse Gene 1.0 ST Array data set
+
+This experimental liver gene expression data set (~100 Affymetrix exon-type arrays), was generated by Frank Lammert, Sonja Hillebrandt, Rabea Hall, and colleagues at the Saarland University Medical Center in Homburg, Germany. This work is part of the German Network for Systems Genetics (GeNeSys).
+
+Expression data after carbon tetrachloride treatment (CCl4, also known as Halon, Freon, carbon tet, or tetrachloromethane) were generated using RNA sample from 30 BXD strains, both parental strains (C57BL/6J, DBA/2J), and B6D2 F1 hybrids. The great majority of cases were females and were treated with carbon tetrachloride injections over a six week period. Three arrays were run for each strain using independent liver samples.
+
+PURPOSE: The overall goal of the project is to understand the etiology of liver fibrogenesis using carbon tetracholoride as a toxin and inducer of liver disease. Liver fibrogenesis, or scarring of the liver, is the common end-stage of chronic liver diseases, in particular after chronic viral infections. In Germany along complications associated with liver fibrosis cause approximately 10,000 deaths per year. In the past decade key molecular pathomechanisms of hepatic fibrogenesis due to chronic viral infections have been identified. Activated hepatic stellate cells (HSCs) drive the process of de novo deposition of abnormal extracellular matrix, which is modulated by complex interactions between cytokines, receptors, and matrix components.
+
+Several studies have demonstrated that the course and progression of the fibrogenic response to chronic liver injury is highly variability among individuals. This marked variabilityhas been attributed to etiology, age, gender, and environmental factors. In humans these genetic disease fibrosis predisposition factors have not yet to be studied systematically.
+
+Our group recently identified a gene variant that contributes to liver fibrogenesis by using QTL mapping in an experimental crosses between fibrosis-susceptible and resistant strains of mice (Hillebrandt et al., 2005). We demonstrated that sequence differences in the HC gene that encodes complement factor C5 (also known as hemolytic complement), are responsible for this strain difference. Common haplotype-tagging polymorphisms of the human HC gene were shown to be associated with advanced fibrosis in chronic hepatitis C virus infection. Thus, the mouse analysis led to the identification of an unknown gene underlying human susceptibility to liver fibrosis, supporting the idea that HC has a causal role in chronic inflammatory disorders and organ fibrogenesis across species.
+
+As part of the GeNeSys program we have studied liver fibrogenesis in the BXD family of strains as a model for chronic liver injury. This expression data set is used to map complex genetic traits that modulate gene expression and determine gene networks during liver fibrogenesis in GRPs.
+
+The following assays are complete or are in progress:
+
+
+ - Liver fibrosis studies: Phenotyping protocols include standard histology, morphometry, biochemical quantification of hepatic collagen contents, serum surrogate markers of fibrosis, immunohistochemistry, and expression profiling of proinflammatory and profibrogenic genes by qRT-PCR and Affymetrix microarrays (this data set).
+ - Characterization of liver cells: Liver immune cell fractions will be isolated and sorted according to SOPs developed in the Lammert laboratory. In addition, in cooperation with the technology platforms of the HepatoSys Network of Excellence, we will characterize primary HSCs that play critical roles in liver fibrogenesis with respect to proinflammatory responses during chronic liver inflammation.
+
+
+PROTOCOL for carbon tetrachloride (CCl4) treatment (parental strains, F1, and BXD lines). Animals were injected with CCl4 (12 x 0.7 mg/kg ip) over a 6-week period on days 1 and 4 of each week. Intraperitoneal injections were begun between the ages of 6-8 weeks. Animals were sacrificed after 6 weeks of treatment at 12 to 14 weeks of age. Untreated control mice from only the two parental strains were also sacrificed at 12-14 weeks of age
diff --git a/general/datasets/Suh_liv_rmaex_0611/tissue.rtf b/general/datasets/Suh_liv_rmaex_0611/tissue.rtf
new file mode 100644
index 0000000..05a7607
--- /dev/null
+++ b/general/datasets/Suh_liv_rmaex_0611/tissue.rtf
@@ -0,0 +1 @@
+Tissue: Livers were snap frozen in liquid nitrogen immediately after harvesting. RNA was extracted and submitted to the UTHSC Molecular Resource Core for expression profiling. Expression data were generated by Lorne Rose, William Taylor and colleagues. Data were entered into GeneNetwork by Arthur Centeno, June 17, 2011. Data were quality controlled by R. W. Williams.
diff --git a/general/datasets/Sxmpublish/summary.rtf b/general/datasets/Sxmpublish/summary.rtf
new file mode 100644
index 0000000..941152c
--- /dev/null
+++ b/general/datasets/Sxmpublish/summary.rtf
@@ -0,0 +1,482 @@
+Barley Phenotype Database
+
+Steptoe x Morex (SxM):
+North American Barley Genome Project (NABGP) dataset
+Hayes, P. M., B. H. Liu, S. J. Knapp, F. Chen, B. Jones, T. Blake, J. Franckowiak, D Rasmusson, M. Sorrells, S. E. Ullrich, D. Wesenberg and A. Kleinhofs. 1993. Quantitative trait locus effects and environmental interaction in a sample of North American barley germplasm. Theor. Appl. Genet. 87: 392-401. The data set is available at the http://wheat.pw.usda.gov/ggpages/SxM/phenotypes.html
+
+It comprises the following agronomic and malting quality traits:
+
+
+ - Grain yield (MT/ha)
+ - Lodging (%)
+ - Height (cm)
+ - Heading date (days after January 1)
+ - Grain protein (%)
+ - Alpha amylase (20 Deg units)
+ - Diastatic power (Deg)
+ - Malt extract (%)
+
+
+Agronomic and malting quality traits were measured in 16 and 9 environments, respectively. The phenotype data files are coded for each environment as follows:
+Environment # Location Year Cooperator
+
+
+ - Crookston, Minnesota 1992 D. Rasmusson (rasmu002@maroon.tc.umn.edu)
+ - Ithaca, New York 1992 M. Sorrells (mes12@cornell.edu)
+ - Guelph, Ontario 1992 D. Falk (dfalk@crop.uoguelph.ca)
+ - Pullman, Washington 1992 S. Ullrich (ullrich@wsu.edu)
+ - Brandon, Manitoba 1992 W. Legge (legge@mbrsbr.agr.ca)
+ - Outlook, Saskatchewan 1992 R. Irvine
+ - Goodale, Saskatchewan 1992 B. Rossnagel (rossnagel@sask.uask.ca)
+ - Saskatoon, Saskatchewan 1992 B. Rossnagel (rossnagel@sask.uask.ca)
+ - Tetonia, Idaho D. Wesenberg (fax: 208-397-4165) 1992
+ - Bozeman, Montana (irrigated) 1992 T. Blake (blake@hordeum.oscs.montana.edu)
+ - Bozeman, Montana (dryland) 1992 T. Blake (blake@hordeum.oscs.montana.edu)
+ - Aberdeen, Idaho 1991 D. Wesenberg (fax: 208-397-4165)
+ - Klamath Falls, Oregon 1991 P. Hayes (hayesp@css.orst.edu)
+ - Pullman, Washington 1991 S. Ullrich (ullrich@wsu.edu)
+ - Bozeman, Montana (irrigated) 1991 T. Blake (blake@hordeum.oscs.montana.edu)
+ - Bozeman, Montana (dryland) 1991 T. Blake (blake@hordeum.oscs.montana.edu)
+
+
+Other data sets
+ENSAT-INP: Ecole Nationale Supérieure Agronomique de Toulouse, Institut National Polytechnique (ENSAT-INP), France
+UM: University of Minnesota, USA
+JLU: Justus Liebig University, Germany
+UW: University of Wageningen, Netherlands
+SCRI: Scottish Crop Research Institute, UK
+WSU: Washington State University, USA
+
+α-amylase (NABGP)
+(see description of the NABGP dataset)
+
+Diastatic power (NABGP)
+(see description of the NABGP dataset)
+
+Disease resistance, bacterial streak, Xanthomonas campestris (ENSAT-INP)
+El Attari H., Rebai A., Hayes P. M.; Barrault G.; Dechamp-Guillaume G.; Sarrafi A. Potential of doubled-haploid lines and localization of quantitative trait loci (QTL) for partial resistance to bacterial leaf streak (Xanthomonas campestris pv. hordei) in barley. Theoretical and Applied Genetics 1998, vol. 96, no1, pp. 95-100.
+
+Two experiments were undertaken in a randomized complete block design with three replicates, in a controlled growth chamber. Twenty seeds per replicate were planted in plastic containers (60 x 40 x 8 cm) containing moistened vermiculite. At the two-leaf stage seedlings were inoculated with an Iranian strain of the pathogen.
+
+Disease resistance, head blight, Fusarium graminearum (UM) or FHB data set
+Prom, L. K., B. J. Steffenson, B. Salas, T. G. Fetch Jr., and H. H. Casper. 1997. Barley accessions resistant to Fusarium head blight and the accumulation of deoxyvalenol. Cereal Res. Comm. 25:807-808.
+
+Prom, L.K., Horsley, R.D., Steffenson, B.J., and Schwarz, P.B. 1999. Development of Fusarium head blight and accumulation of deoxynivalenol in barley sampled at different growth stages. J. Am. Soc. Brew. Chem. 57:60-63.
+
+Steffenson, B. J. 2003. Fusarium head blight of barley: Impact, epidemics, management, and strategies for identifying and utilizing genetic resistance. Pages 241-295: In: K. J. Leonard and W.R. Bushnell, eds. 2003. Fusarium Head Blight of Wheat and Barley. APS Press. St. Paul. 512 pp.
+
+Tacke, B. K., and H. H. Casper. 1996. Determination of deoxyvalenol in wheat, barley, and malt by column cleanup and gas chromatography with electron capture detection. J. Assoc. Off. Anal. Chem. 79:472-475.
+
+FHB and DON assays
+Parents and DH progeny from the Steptoe/Morex were assessed for FHB severity (in %) and DON accumulation (in ppm) at three different environments in 1994 and 1995: Fargo, ND in both 1994 and 1995 and Langdon, ND in 1995. A randomized complete block design was used in the three environments and included a single replicate. Progeny and parents were planted in short rows (10-20 seeds) spaced 0.33 cm apart in two adjacent rows. Planting, maintenance of plots, and inoculation protocols were as described by (Prom et al. 1997). Disease assessments were made when the parents and DH progeny were at the mid-dough stage of development (growth stage 84-86) (Zadoks et al. 1974). The percent severity of FHB was determined by counting the number of infected kernels (those with greater than one-fourth of their surface area showing disease symptoms) and dividing that quantity by the total number of kernels in that spike multiplied by 100 (Prom et al. 1997). These assessments were made on 10-20 randomly selected spikes per plot as described by Prom et al. (1997). When the plants were mature, all spikes from each plot were harvested, dried, and threshed. DON assays were made using the method developed by Tacke and Casper (Tacke and Casper 1996). For this assay, a random six-gram sample of seed was used from each parent and DH line (Prom et al. 1999).
+
+File names in the dataset:
+DON94F.TXT final
+amount of vomitoxin in samples vom ppm
+
+DONP195F.TXT final
+DON levels in ppm planting date 1 (Fargo 1995)
+
+DONP295F.TXT final
+DON levels in ppm planting date 2 (Fargo 1995)
+
+DONP295L.TXT final
+DON levels in ppm planting date 2 (Langdon 1995)
+
+DON94F.TXT final
+amount of vomitoxin vom ppm
+
+FGINC04.94
+incidence of Fusarium graminearum isolated from seed in all severity classes.
+
+FGINC14.94
+incidence of Fusarium graminearum isolated from seeds with a severity rating of 1, 2, 3, or 4.
+
+FGINC24.94
+incidence of Fusarium graminearum isolated from seeds with a severity rating of 2, 3, or 4.
+
+FGINC34.94
+incidence of Fusarium graminearum isolated from seeds with a severity rating of 3 or 4.
+
+FHB1494F.TXT
+incidence of Fusarium head blight (visual rating) with a severity rating of 1, 2, 3, or 4.
+
+FHB1494F.TXT final
+incidence of Fusarium head blight (visual rating) with a severity rating of 1, 2, 3, or 4.
+
+FHB2494F.TXT
+no heading
+
+FHB2494F.TXT final
+no heading
+
+FHB3494F.TXT
+incidence of Fusarium head blight (visual rating) when severity categories 3 or 4 only are considered blighted.
+
+FHB3494F.TXT final
+incidence of Fusarium head blight (visual rating) when severity categories 3 or 4 only are considered blighted.
+
+FHBINC14.94
+incidence of Fusarium head blight (visual rating) with a severity rating of 1, 2, 3, or 4.
+
+FHBINC34.94
+incidence of Fusarium head blight (visual rating) when severity categories 3 or 4 only are considered blighted.
+
+FHBSE94F.TXT
+severity of Fusarium head blight
+
+FHBSE94F.TXT final
+severity of Fusarium head blight
+
+FHBSEV.94
+severity of Fusarium head blight
+
+FPPLTT95.TXT final
+Fusarium Poae Isolations from seed 1995 (Fargo PD1, Fargo PD2, and Langdon PD2)
+
+FSPD195F.TXT final
+Percentage of FHB infection in S/M lines from the first planting date at Fargo 1995
+
+FSPD295F.TXT final
+Percentage of FHB infection in S/M lines from the second planting date at Fargo 1995
+
+FSPD295L.TXT final
+Percentage of FHB infection in S/M lines from the second planting date at Langdon 1995
+
+GRSTG94F.TXT
+developmental stages of the Steptoe/Morex population
+The first column is the SM line,
+the second is Zadok's Growth Stage,
+the third estimated days to mid-milk and
+the 4th days to heading (St. Paul).
+
+GRSTG94F.TXT final
+developmental stages of the Steptoe/Morex population
+The first column is the SM line,
+the second is Zadok's Growth Stage,
+the third estimated days to mid-milk and
+the 4th days to heading (St. Paul).
+
+GRTHSTGE.94
+developmental stages of the Steptoe/Morex population
+The first column is the SM line,
+the second is Zadok's Growth Stage,
+the third estimated days to mid-milk and the 4th days to heading (St. Paul).
+
+GZP0494F.TXT
+incidence of Fusarium graminearum isolated from seed in all severity classes.
+
+GZP0494F.TXT final
+incidence of Fusarium graminearum isolated from seed in all severity classes.
+
+GZP1494F.TXT
+incidence of Fusarium graminearum isolated from seeds with a severity rating of 1, 2, 3, or 4.
+
+GZP1494F.TXT final
+incidence of Fusarium graminearum isolated from seeds with a severity rating of 1, 2, 3, or 4.
+
+GZP2494F.TXT
+incidence of Fusarium graminearum isolated from seeds with a severity rating of 2, 3, or 4.
+
+GZP2494F.TXT final
+incidence of Fusarium graminearum isolated from seeds with a severity rating of 2, 3, or 4.
+ND94
+
+GZP3494F.TXT
+incidence of Fusarium graminearum isolated from seeds with a severity rating of 3 or 4.
+
+GZP3494F.TXT final
+incidence of Fusarium graminearum isolated from seeds with a severity rating of 3 or 4.
+
+GZPLT95.TXT final
+no heading
+
+HDPD295L.TXT final
+1995 LANGDON - number of days until heading (planted June 9)
+
+SEVPD1F95.TXT
+Percentage of FHB infection in S/M lines from the first planting date at Fargo 1995
+
+SEVPD2F95.TXT
+Percentage of FHB infection in S/M lines
+from the second planting date at Fargo 1995
+
+SEVPD2L95.TXT
+Percentage of FHB infection in S/M lines from the second planting date at Langdon 1995
+
+SMDNSITY.95 (Converted)
+head density ratings (field 1995)spikelets/cm
+
+SMFHB1.95F
+1st planting date Fargo
+
+SMFHB2.95F
+2nd planting date Fargo
+
+SMFHB2.95L
+2nd planting date Langdon
+
+SPDEN95F.TXT final
+spikelet density ratings (Fargo 1995)
+
+SPDEN95L.TXT final
+spikelet density ratings (Langdon 1995) spikelets/cm
+
+SPIKELET DENSITY FARGO 95
+spikelet density ratings (Fargo 1995) spikelets/cm
+
+SPIKELET DENSITY LANGDON 95
+spikelet density ratings (Langdon 1995) spikelets/cm
+
+SPKDENF95.TXT
+spikelet density ratings (Fargo 1995) spikelets/cm
+
+SPKDENL95.TXT
+spikelet density ratings (Langdon 1995) spikelets/cm
+
+VOMPPM.94
+No headings
+
+Disease resistance, leaf scald, Rhynchosporium secalis (JLU)
+Schweizer GF, Herz M, Mikolajewski S, Brenner M, Hartl L, Baumer M (2004) Genetic mapping of a novel scald resistance gene Rrs15CI8288 in barley. 9th International Barley Genetics Symposium, Brno, Czech Republic, 20-26 June 2004. Proceedings:258-265).
+
+Jackson LF, Webster RK (1976) Race differentiation, distribution and frequency of Rhynchosporium secalis in California. Phytopathology 66:719-725.
+
+Schweizer G, Baumer M, Daniel G, Rugel H, Röder MS (1995) RFLP-markers linked to scald (Rhynchosporium secalis) resistance gene Rh2 in barley. Theor Appl Genet 90:920-924.
+
+Disease resistance assay R. secalis
+
+General description
+Disease severity was assessed at seedling stage in a greenhouse chamber. Therefore, the plants were sown and grown at a temperature of 16-18°C in 9x9 cm plastic pots whereas each line was represented by four individuals. The plants were inoculated at the three-leaves stage, approximately 20 days after sowing. The parents as well as some differential genotypes (resistant: Atlas; susceptible: Alexis, Hendrix, Steffi) were included as internal controls.
+The single-spore isolate 271 (Straßmoos, Bavaria) of R. secalis, provided by Dr. Sachs, BBA Kleinmachnow, was grown for approximately 20 days on Lima bean agar (Difco, Detroit, USA) in Petri-dishes at 16°C in the dark. The spores were harvested after addition of water by gently rubbing of the mycel with a glass rod. The advanced spore suspension was decanted, filtrated and adjusted to 2-300.000 spores/ml. One inoculum preparation was used for the inoculation of all seedlings. by covering the inoculated plants with black plastic hoods for 48 hours high humidity and darkness were maintained to provide optimal infection conditions. 10-14 days after infection plants were assessed visually for scald symptoms on the lamina of the second leaf approximately according to the scale described by Jackson & Webster (1976). The third leaf was later consult to verify the infection. The final score of scald severity per DH line was achieved by averaging the scoring results of the four included plants.
+
+Detailed description
+The Steptoe/Morex DH mapping population and reference cultivars were tested for reaction to Rhynchosporium secalis according to Schweizer et al. 1995 with some modifications. The single-spore isolate “271” (Straßmoos, LfL-Bavaria, Germany) of R. secalis, provided by Dr. Sachs was grown for approximately 20 days on 2.3% (w/v) Lima bean agar (Difco Laboratories) in Petri-dishes at 16°C in the dark. For inoculation a conidial suspension was prepared by rinsing the plates with water and filtering the mycel through gauze. The spore concentration was adjusted to 200.000 spores/ml-1. One inoculum preparation was used for all seedlings in a given experiment.
+Seedlings at the 2- to 3-leaf stage (3 weeks after sowing) were sprayed uniformly with inoculum (approximately 0.25 ml per plant) and left for 20 min to dry. Inoculated plants were then lightly sprayed with water and kept for 48h in a dark moist chamber at 18°C. DH lines (four independent plants/DH line) were assessed 10-14 days after inoculation visually for scald symptoms on the lamina of the second leaf (the third leaf was used as further control) according to the scale described by Jackson & Webster (1976). Differential genotypes ´Atlas´ (res) and ´Steffi´ (susc) and the parents Steptoe and Morex were used as reference cultivars.
+
+Disease resistance, net blotch, Pyrenophora teres (UM)
+Steffenson, B.J., Hayes, P.M., and Kleinhofs, A. 1996. Genetics of seedling and adult plant resistance to net blotch (Pyrenophora teres f. teres) and spot blotch (Cochliobolus sativus) in barley. Theor. Appl. Genet. 92:552-558.
+
+Burleigh JR, Loubane, M (1984) Plot size effects on disease progress and yield of wheat infected by Mycosphaerella graminicola and barley infected by Pyrenophora teres. Phytopathology 74:545--549
+
+Fetch, T.G., Jr., and Steffenson, B.J. 1999. Rating scales for assessing infection responses of barley infected with Cochliobolus sativus. Plant Dis. 83:213-217.
+
+James WC (1971) A manual of disease assessment keys for plant diseases. Can Dep Agric Publ 1458
+
+Tekauz, A (1985) A numerical scale to classify reactions of barley to Pyrenophora teres. Can J Plant Pathol 7:181—183
+
+Fetch, T. G., Jr., and Steffenson, B. J. 1999. Rating scales for assessing infection responses of
+barley infected with Cochliobolus sativus. Plant Dis. 83:213-217.
+
+Seedling evaluations
+For seedling evaluations, four to six seeds of parents and DH lines were sown in plastic cones (3.8 cm diameter and 21 cm length) filled with a peat moss:perlite (3:1) potting mix and grown at 22-26C in a greenhouse. Fertilization was provided at planting with water soluble (15-0-15, N-P-K) and controlled release (14-14-14, N-P-K) formulations. When the second leaves of plants were fully expanded (14 days after planting), inoculations were made with conidial suspensions of the individual pathogens using an atomizer pressured by an air pump at 414 kPa. Inoculations with isolate ND89-19 of P. t. f. teres and ND85F of C. sativus were made using a concentration of 5,000 and 8,000 conidia/ml, respectively. The volume of the inoculum suspension applied to each plant was approximately 0.15 ml. To facilitate even distribution and adherence of conidia, 10 ul of Tween® 20 (polyoxyethylene-20-sorbitan monolaurate) was added for every 100 ml of the inoculum suspension. Plants were allowed to dry slightly after inoculation before being placed in chambers maintained near saturation by periodic mistings from ultrasonic humidifiers. After a 16 hour infection period in complete darkness, the plants were allowed to dry slowly for approximately four hours before being returned to the greenhouse. Assessments of the infection response (IR) were made 9--11 days post-inoculation using the rating scale of Tekauz (1985) for net blotch and Fetch and Steffenson (1999) for spot blotch. The experiment was conducted in a randomized complete block design with two replicates and was repeated twice.
+
+Adult plant evaluations
+Parents and DH lines were also evaluated to the net and spot blotch pathogens in the field at Langdon and Fargo, North Dakota, respectively. The host entries were sown in hill plots (8--15 seeds/hill) spaced 0.3 m apart in paired rows. Susceptible barley genotypes (cultivar Hector for net blotch and line ND 5883 for spot blotch) were planted around the paired rows of hill plots to increase disease development in the nurseries. When most of the DH lines were at the mid-tillering stage of development, the susceptible spreader plants were inoculated with barley straw infected with either isolate ND89-19 of P. t. f. teres or ND85F of C. sativus. This infected barley straw was taken from the previous season's crop at the respective locations. Assessments of disease severity (percentage of leaf area affected by disease) were made at the mid-dough stage of development using standard disease area diagrams (Burleigh and Loubane [1984] for net blotch and James [1971] for spot blotch). The experimental design was a randomized complete block with three replications. Evaluations for net blotch reaction were made in 1991 only and for spot blotch both in 1991 and 1992.
+
+Disease resistance, leaf rust, Puccinia hordei (UW)
+Marcel TC, Varshney RK, Barbieri M, Jafary H, de Kock MJ, Graner A, Niks RE: A high-density consensus map of barley to compare the distribution of QTLs for partial resistance to Puccinia hordei and of defence gene homologues. Theor.Appl.Genet. 2007, 114:487-500.
+
+Disease evaluations at seedling plant stage
+The standard barley leaf rust isolate 1.2.1 (P. hordei Otth) was used to evaluate the level of partial resistance of the 150 DH lines of StMx at seedling stage in a greenhouse compartment. The disease experiments were conducted in six replications in time and within each replication one seedling of each DH line was inoculated. The seeds were sown in trays of 37 x 39 cm, each of them containing two rows of 10–15 seeds. In each tray one seed of each parental line, Steptoe and Morex and of the control lines, L94 and Vada, were sown. The inoculation was performed with about 200 spores per cm2. The latency period (LP) on each seedling was evaluated and the relative latency period (RLP50S) was calculated, relative to the LP on L94.
+
+Disease resistance, spot blotch, Cochliobolus sativus (UM)
+See the net blotch description
+
+Disease resistance, stem rust, Puccinia graminis (UM)
+Stakman EC, Stewart DM, Loegering WQ (1962) Identification of physiologic races of Puccinia graminis var. tritici. USDA Agricultural Research Service Bulletin 617.
+
+Miller JD, J.W.Lambert (1965) Variability and inheritance of reaction of barley to race
+32 l5B of stem rust. Aqron J 47:373-377.
+
+Druka, A., Potokina, E., Luo, Z., Bonar, N., Druka, I., Zhang, L., Marshall, D.F., Steffenson, B.J., Close, T.J., Wise, R.P., Kleinhofs, A., Williams, R.W., Kearsey, M.J. and Waugh, R. 2008. Exploiting regulatory variation to identify genes underlying quantitative resistance to the wheat stem rust pathogen Puccinia graminis f. sp. tritici in barley. Theoretical and Applied Genetics. 117(2):261-72
+
+Stem rust infection phenotyping
+Each of the St/Mx DH lines was challenged with the stem rust fungus race Pgt-MCC in 5 replications over 2 years (1990 and 1991). Phenotypic scores were made 12 to 14 days after inoculation according to the infection type (IT) scale of Stakman et al. (1962) as modified by Miller and Lambert (Miller and Lambert 1965). Under the Stakman system, IT 0 indicates no visible infection; only a necrotic “fleck” (i.e. hypersensitive response) with no sporulation; IT 1 designates a minute uredinium (i.e. sporulating pustule) surrounded by necrosis; IT 2 designates a small uredinium often surrounded by chlorosis; IT 3 designates a moderate sized uredinium sometimes surrounded by chlorosis; and IT 4 designates a large uredinium. Since barley exhibits chlorosis in association with most ITs (excluding IT 0, and IT 1), Miller and Lambert modified the Stakman system and classified ITs 2, 3, and 4 on the basis of uredinium size alone. Barley often exhibits a mixture of different ITs on a single plant—the “mesothetic” reaction described by Stakman et al (1962). ITs on the St/Mx DH lines were recorded according to prevalence. In most cases, the one or two most common ITs comprised over 75% of the total observed and were used to assign the general binary classes of resistant and susceptible. ITs 0, 1 and 2 were
+3 considered indicative of host resistance (i.e. a low infection type), whereas IT 3 and 4
+4 were indicative of host susceptibility (a high infection type). The classic “diamond
+5 shaped” uredinium of IT 4 was not observed on plants in the St/Mx population.
+
+Emergence of the second leaf (SCRI)
+Seeds of all 150 recombinant lines from the Steptoe x Morex DH population and the parents, Steptoe and Morex were planted in the 24 x 30 cm pots filled with the ‘Cereal Mix’ and placed on the automatically irrigated glasshouse benches (cubicle AO59). Three sterilized seeds per line were sown in each of four replicate pots. Placement of the pots was randomized across the glasshouse space. Temperature in the cubicle was set at 20° with 16-hr light/15° 8-hr dark periods. Intensity of the supplementary light was 400 µE m–1 sec–1.
+
+Single leaf frequency
+After 20 days, seedlings were counted based on number of emerged visible leaves (either single or two). Frequency of the single leaf across all four replicates within the recombinant line was used for QTL mapping.
+
+Ratio
+The lengths of the leaf blades were measured for the seedlings that have two visible leaves. Ratio of the length of both blades was used for QTL mapping.
+
+Endosperm modification (SCRI)
+Jorgensen (1988) Carlsberg Res. Commun. 53:277
+
+ImageJ is a public domain Java image processing program.
+Rasband, W.S., ImageJ, U. S. National Institutes of Health, Bethesda, Maryland, USA, http://rsb.info.nih.gov/ij/, 1997-2008.
+
+Abramoff, M.D., Magelhaes, P.J., Ram, S.J. "Image Processing with ImageJ". Biophotonics International, volume 11, issue 7, pp. 36-42, 2004.
+
+Druka, A., Muehlbauer, G., Druka, I., Caldo, R., Baumann, U., Rostoks, N., Schreiber, A., Wise, R., Close, T., Kleinhofs, A., Graner, A., Schulman, A., Langridge, P., Sato, K., Hayes, P., McNicol, J., Marshall, D., Waugh, R. 2006. An atlas of gene expression from seed to seed through barley development. Functional Integrative Genomics 6, 202-211.
+
+Plant material was generated essentially as described previously (Druka et al 2006) but with some modifications specific to these studies. To obtain embryo-derived tissue from the germinating grain, 30–50 sterilized seeds per line of the trial set were germinated on a petri plate between three layers of wet 3-mm filter paper in the dark, for 16 hr at 17° and 8 hr at 12°, for 96 hr total. 6-10 similarly looking or ‘average’ seeds were cut in half longitudally, and stained with calcuflor.
+
+Calcufluor staining
+1) 30 sec - 1min 0.1% calcufluor (H2O);
+2) 10 sec 70% EtOH;
+3) Dry shortly;
+4) 30-60 sec 0.1% fast green H2O;
+5) blot off residual stain, put under the UV microscope at 400 nm to take photographs.
+Photographs were taken by using Leica DM IL Inverted contrasting microscope Leica Microsystems. Image analysis was by using ImageJ software.
+
+Fermentability (SCRI)
+Fermentability is the proportion of fermentable material in a malt extract. It is measured using a standard yeast strain following 48 hrs fermentation according to the IoB Recommended Methods for Analysis (1992) buut modified for small aliquots as described by Swanson & Thomas (1996)
+
+Fermentable malt extract (SCRI)
+Fermentable malt extract is the total amount of fermentable material in a sample of barley grain and is the product of hot water extract and ferementability
+
+Flecking of leaves (SCRI)
+Leaf flecking is a visual score of the degree of flag and flag leaf-1 coverage by dark brown leasions that are not attributable to known foliar pathogens or pests. It is scored on a 1-8 scale with 1 = 0 and 9=100% coverage
+
+Germination (WSU)
+See Dormancy and Pre-harvest sprouting
+
+Grain length F0-F9 (SCRI)
+Number of seeds from a sample of approx 100 cleaned grain that have passed over a 2.5mm sieve and are between 2.5 and 3 mm in width as determined by MARVIN 4.0 analysis of a digital image (www.gta-sensorik.com)
+
+Grain length, average (SCRI)
+Grain length is the average length of a sample of approx 100 cleaned sseds that have passed over a 2.5mm sieve. Seed length is determined by analysis of digital images using the Marvin 4.0 system (www.gta-sensorik.com).
+
+Grain nitrogen (SCRI)
+Grain nitrogen is the estimated % nitrogen content of a sample of cleaned grain that has passed over a 2.5mm sieve. It was measured by a FOSS 1251 Near Infra Red Transmittance grain analyser (www.foss.dk)
+
+Grain protein (NABGP)
+(see description of the NABGP dataset).
+
+Grain shape (width/length) (SCRI)
+Grain shape is the average grain width divided by the average grain length.
+
+Grain surface area (SCRI)
+Grain surface area is the average area 2D area of a sample of approx 100 leaned barley grain that have passed over a 2.5mm sieve. Surface area is determined by analysis of digital images using the Marvin 4.0 system (www.gta-sensorik.com).
+
+Grain width (average) (SCRI)
+Grain width is the average width of a sample of approx 100 cleaned seeds that have passed over a 2.5mm sieve. Seed width is determined by analysis of digital images using the Marvin 4.0 system (www.gta-sensorik.com).
+
+Grain width F0-F9 (SCRI)
+Number of seeds from a sample of approx 100 cleaned grain that have passed over a 2.5mm sieve and are between 2.5 and 3 mm in width as determined by MARVIN 4.0 analysis of a digital image (www.gta-sensorik.com).
+
+Head length (SCRI)
+Length (cm) of ear from collar to base of awn of last spikelet measured on a random sample from a field grown barley plot.
+
+Heading date - glasshouse (SCRI)
+Seeds of all 150 recombinant lines from the Steptoe x Morex DH population and the parents, Steptoe and Morex were planted in the 24 x 30 cm pots filled with the ‘Cereal Mix’ and placed on the automatically irrigated glasshouse benches (cubicle AO59). Three sterilized seeds per line were sown in each of four replicate pots. Placement of the pots was randomized across the glasshouse space. Temperature in the cubicle was set at 20° with 16-hr light/15° 8-hr dark periods. Intensity of the supplementary light was 400 µE m–1 sec–1.
+
+Heading date was measured as number of days to anthesis. Anthesis was determined by observing the colour and the response of anthers to the mechanical disturbance. Anthers should be yellow and a slight mechanical disturbance should cause shedding of the pollen meaning that anthesis is about to happen.
+
+Heading date (NABGP)
+(see description of the NABGP dataset)
+
+Heading date (SCRI)
+Days after May31st on which 50% of the plot first reached DGS53
+
+Heading date (UM)
+Steffenson, B. J. 2003. Fusarium head blight of barley: Impact, epidemics, management, and strategies for identifying and utilizing genetic resistance. Pages 241-295: In: K. J. Leonard and W.R. Bushnell, eds. 2003. Fusarium Head Blight of Wheat and Barley. APS Press. St. Paul. 512 pp.
+
+Zadoks, J. C., T. T. Chang, and C. F. Konzak. 1974. A decimal code for the growth stages of cereals. Weed. Res. 14:415-421.
+
+Morphological and agronomic trait assessment
+Various morphological (especially spike characters) and agronomic traits may affect the development of FHB on lines in the field (Steffenson 2003). To determine the possible contribution of such factors on FHB severity, assessments were made on heading date, plant height, spike, and the number of nodes per cm of rachis in the spike (kernel density). Heading date was defined as the number of days from planting to when 50% of the plants in a plot had emerged spikes. Plant height was the number of cm from the ground to the tip of the spike, excluding the awns. Spike angle was rated at maturity on a scale of 1 to 3 where spikes bending less than 45 degrees from vertical were scored as 1; those bending from 45-120 degrees from vertical were scored as 2, and those bending greater than 120 degrees from vertical were scored as 3. The number of nodes per cm of rachis was measured on four randomly selected spikes for each parent and DH line.
+
+Hot water extract (SCRI)
+Amount of material extracted by hot water from a clean 25g sample of barley grain that has passed over a 2.5mm sieve following micro-malting under standard conditions of steeping and air rests. Hot water extract is measured by refractometry and expressed as Lintner degrees per kg. NB, this is equivalent to malt extract but the micro-malting protocol will be different.
+
+Lodging (NABGP)
+(see description of the NABGP dataset)
+
+Lodging (SCRI)
+Lodging is the proportion of the plot that is less than 45 degrees from horizontal. It is measured on a 1-9 scale with 1=0 and 9=100%.
+
+Malt extract (NABGP)
+(see description of the NABGP dataset)
+
+Malt extract (SCRI)
+See HWE
+
+Maturity (SCRI)
+Maturity is a visual estimate of the relative physiological maturity of a plot with 1=early and 9=late.
+
+Milling energy (SCRI)
+Milling energy is the amount of energy required to mill a weighed sample of clean grain that has passed over a 2.5mm sieve. It is expressed as Joules per 5g grain ane measured using the Comparamill.
+
+Moisture content in the grain (SCRI)
+Estimate of moisture in sample by NIT after drying and storage!
+
+Necrotic spotting doughy stage (SCRI)
+Spotting at the doughy stage is a visual score of the degree of flag and flag leaf-1 coverage by dark brown lesions that are considered to be due to infection by Ramularia collo-cygni. It is scored on a 1-9 scale with 1 = 0 and 9=100% covereage
+
+Normalised difference vegetation index (SCRI)
+NDVI is ((ref660nm-ref770nm)/(ref660nm+ref770nm)) as measured by the Greenseeker (www.ntechindustries.com) at GS61
+
+Normalised difference vegetation index @GS43 (SCRI)
+NDVI is ((ref660nm-ref770nm)/(ref660nm+ref770nm)) as measured by the Greenseeker (www.ntechindustries.com) at GS43
+
+Plant height (NABGP)
+(see description of the NABGP dataset)
+
+Plant height (SCRI)
+Height is the height(cm) of a plot from the ground to the collar at GS71+
+
+Dormancy and pre-harvest sprouting (WSU)
+AOSA (1988) Association of Official Seed Analysis rules for testing seeds. J Seed Technol 12 (3).
+Ullrich, S.E., J.A. Clancy, I.A. del Blanco, H. Lee, V.A. Jitkov, F. Han, A. Kleinhofs, and K. Matsui. 2007. Genetic analysis of preharvest sprouting in a six-row barley cross. Molecular Breeding. Submitted.
+
+Hayes, P. M., B. H. Liu, S. J. Knapp, F. Chen, B. Jones, T. Blake, J. Franckowiak, D Rasmusson, M. Sorrells, S. E. Ullrich, D. Wesenberg and A. Kleinhofs. 1993. Quantitative trait locus effects and environmental interaction in a sample of North American barley germplasm. Theor. Appl. Genet. 87: 392-401.
+
+Han, F., and S.E. Ullrich. 1994. Mapping of quantitative trait loci for malting quality traits in barley. Barley Genetics Newsletter 23:84-97.
+
+Ullrich, S. E., P. M. Hayes, W. E. Dyer, T. K. Blake, and J. A. Clancy. 1993. Quantitative trait locus analysis of seed dormancy in "Steptoe" barley. p. 136-145. In: M. K. Walker-Simmons and J. L. Reid (eds.) Preharvest sprouting in cereals 1992. Amer.Assoc. Cereal Chemist, St. Paul.
+
+Oberthur, L., T.K. Blake, W.E. Dyer, and S.E. Ullrich. 1995. Genetic analysis of seed dormancy in barley (Hordeum vulgare L.). J. Quant. Trait Loci (on line), available: http://probe.nalusda.gov. 8000/other docs/jqtl/jqtl 1995-05/ dormancy.html.
+
+Han, F., S.E. Ullrich, S. Chirat, S. Menteur, L. Jestin, A. Sarrafi, P.M. Hayes, B.L. Jones, T.K. Blake, D.M. Wesenberg, A. Kleinhofs, and A. Kilian. 1995. Mapping of b-glucan content and b-glucanase activity loci in barley grain and malt. Theor. Appl. Genet. 91:921-927.
+
+Clancy, J.A., F. Han, and S.E. Ullrich. 2003. Comparative mapping of b-amylase activity QTLs among three barley crosses. Crop Sci.43:1043-1052.
+
+Ullrich, S.E., J.A. Clancy, I.A. del Blanco, H. Lee, V.A. Jitkov, F. Han, A. Kleinhofs, and K. Matsui. 2007. Genetic analysis of preharvest sprouting in a six-row barley cross. Molecular Breeding. Submitted.
+
+Dormancy as measured by germination tests
+Dormancy defined as the failure of viable mature seed to germinate under favorable conditions was measured indirectly by measuring germination percentage, as there is no known direct test for dormancy. Two different after-ripening periods (0 and 14 days) were included in the study to measure the state of and change in dormancy over time. Genetic sub-traits for dormancy based on physiological activity/state could include the development of dormancy as seeds mature, the state of dormancy at maturity, and the dissipation of dormancy with time following maturity. The latter two situations were considered in this study. Germination percentage has also been used to measure susceptibility/resistance to preharvest sprouting (PHS) as well, but it is also a very indirect measure, which assumes that dormancy is the opposite of PHS, which may or may not be entirely true.
+
+Seeds were harvested at physiological maturity (as determined when green color was lost from the spike). Heads were collected and stored in a -20°C freezer prior to germination tests of the seeds to arrest physiological activity. Germination tests were carried out after two different post-harvest after-ripening periods at room temperature; 0 d and 14 d for materials grown in field and glasshouse environments. For each after-ripening period, two replications of 100 seeds were germinated at 20°C on moist filter paper in a petri dish. Standard germination tests were performed (AOSA 1988). After 7 d the number of germinated seeds were counted and expressed as a percentage of the total.
+
+Pre-harvest Sprouting (PHS) experiment in the greenhouse.
+Trait scores:
+0 = no visible roots
+1 = roots <or = 3/ no shoots
+2 = roots < or = 5/ shoots < or = 3
+3 = roots < or = 8/ shoots < or = 5
+4 = roots and shoots over 25% but < 50% of head
+5 roots and shoots over 50% of head
+
+Predicted spirit yield (SCRI)
+PSY is fermentable extract multiplied vy a constant to give the yield of spirit(l) per tonne of malt (Dolan, 1982).
+
+Soluble nitrogen content of wort (SCRI)
+Soluble nitrogen content is the amount of nirogen that has been solubilised in a hot water extract follwing micro-malting under standard conditions (see Hot Water Extract, HWE). It is measure by UV spectrophotometry (Haselmore & Gill, 1995).
+
+Spike density (UM)
+Steffenson, B. J. 2003. Fusarium head blight of barley: Impact, epidemics, management, and strategies for identifying and utilizing genetic resistance. Pages 241-295: In: K. J. Leonard and W.R. Bushnell, eds. 2003. Fusarium Head Blight of Wheat and Barley. APS Press. St. Paul. 512 pp.
+
+Zadoks, J. C., T. T. Chang, and C. F. Konzak. 1974. A decimal code for the growth stages of cereals. Weed. Res. 14:415-421.
+
+Morphological and agronomic trait assessment
+Various morphological (especially spike characters) and agronomic traits may affect the development of Fusarium Head Blight (FHB) on lines in the field (Steffenson 2003). To determine the possible contribution of such factors on FHB severity, assessments were made on heading date, plant height, spike, and the number of nodes per cm of rachis in the spike (kernel density). Heading date was defined as the number of days from planting to when 50% of the plants in a plot had emerged spikes. Plant height was the number of cm from the ground to the tip of the spike, excluding the awns. Spike angle was rated at maturity on a scale of 1 to 3 where spikes bending less than 45 degrees from vertical were scored as 1; those bending from 45-120 degrees from vertical were scored as 2, and those bending greater than 120 degrees from vertical were scored as 3. The number of nodes per cm of rachis was measured on four randomly selected spikes for each parent and DH line.
+
+Thousand grain weight (SCRI)
+Thousand grain weight is measured by counting and weighing a clean sample of grain that has passed over a 2.5 mm sieve using MARVIN 4.0 (www.gta-sensorik.com)
+
+Vegetation index (SCRI)
+This is Infra Red Vegetation Index, IRVI (ref660nm/ref770nm) as measured by the Greenseeker (www.ntechindustries.com) at GS61.
+
+Vegetation index @ GS43 (SCRI)
+This is Infra Red Vegetation Index, IRVI (ref660nm/ref770nm) as measured by the Greenseeker (www.ntechindustries.com) at GS43.
+
+Yield (MT/ha) (NABGP)
+(see description of the NABGP dataset).
diff --git a/general/datasets/TIGEM_hg38_ret_rna_seq_0916/acknowledgment.rtf b/general/datasets/TIGEM_hg38_ret_rna_seq_0916/acknowledgment.rtf
deleted file mode 100644
index 54bc7ff..0000000
--- a/general/datasets/TIGEM_hg38_ret_rna_seq_0916/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors are grateful to Mohit Parekh from the Fondazione Banca degli Occhi del Veneto (FBOV) for the collection of human retina samples. The authors would also like to thank Manuela Dionisi (technician) and Vincenzo Nigro (Head) of the Next Generation Sequencing Facility (TIGEM). This work was supported by FondazioneTelethon Grant (TGM11SB2) to SB and (TGM11SB1) toDdB and to the EU FP7 Radiant project (305626) to DdB.
diff --git a/general/datasets/TIGEM_hg38_ret_rna_seq_0916/cases.rtf b/general/datasets/TIGEM_hg38_ret_rna_seq_0916/cases.rtf
deleted file mode 100644
index 71f6c2f..0000000
--- a/general/datasets/TIGEM_hg38_ret_rna_seq_0916/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Human retina sample collection
-
-Retina samples were collected at Fondazione Banca degli Occhi del Veneto (FBOV) from 50 different donors for cornea transplantation in compliance with the tenets of the Declaration of Helsinki and after an informed consent allowing the use of tissues for research purposes was signed by the donor's next of kin (for a description of donors Supplementary Table S1). Each harvested tissue was accompanied with the FBOV progressive number and with details on the age and gender of donor, the cause of death and the total post-mortem time (T). To limit the possible effects of post-mortem time on RNA integrity and transcriptomic profiles, retinal tissues were isolated only from eye bulbs with a total post-mortem interval (T) ≤ 26 h. The average post-mortem time of the samples was 20.5 h (ranging from 6 to 26 h). For the same reason, bulbs deriving from multi-organ donors were excluded from the analysis. In order to limit cross-contamination with adjacent tissues, we established a protocol for the dissection of the retina from the eye bulbs (14). The dissected retinal tissue was visually inspected to exclude any cross-contamination with the pigmented RPE/choroid and was immediately submerged in RNA Stabilization Reagent (RNA later; QIAGEN).
diff --git a/general/datasets/TIGEM_hg38_ret_rna_seq_0916/experiment-design.rtf b/general/datasets/TIGEM_hg38_ret_rna_seq_0916/experiment-design.rtf
deleted file mode 100644
index f9da145..0000000
--- a/general/datasets/TIGEM_hg38_ret_rna_seq_0916/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA extraction, library preparation and sequencing
-
-Total RNA was extracted from the 50 human retina samples using the miRNeasy Kit (QIAGEN) according to the manufacturer's instructions. RNA was quantified using a NanoDrop ND-8000 spectrophotometer (NanoDrop Technologies) and the integrity was evaluated using an RNA 6000 Nano chip on a Bioanalyzer (Agilent Technologies). The RNA of the 50 samples had an average RNA integrity number (RIN) of 8.7 (ranging from 7.2 to 9.7). Libraries were prepared according to manufacturer's instructions (TruSeq RNA Sample Preparation kit) with an initial amount of 4 μg of total RNA. Quality control of library templates was performed using a High Sensitivity DNA Assay kit (Agilent Technologies) on a Bioanalyzer (Agilent Technologies). Qubit quantification platform was used to normalize samples for the library preparation (Qubit 2.0 Fluorometer, Life Technologies). Libraries were sequenced via a paired-end chemistry on an Illumina HiSeq1000 platform with an average yield of ∼6 Mb.
diff --git a/general/datasets/TIGEM_hg38_ret_rna_seq_0916/processing.rtf b/general/datasets/TIGEM_hg38_ret_rna_seq_0916/processing.rtf
deleted file mode 100644
index 7d8d4b3..0000000
--- a/general/datasets/TIGEM_hg38_ret_rna_seq_0916/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Data analysis
-
-The exploratory analysis, whose steps are shown in Figure 1, was carried out with the ‘tuxedo’ software suite (Trapnell et al., 2010) and led to the definition of the Observed Transcriptome (ObsT). The conservative analysis (Figure 1) was carried out by running the RNA-Seq by Expectation-Maximization (RSEM) package (Li & Dewey, 2011) and led to the definition of the RefT.
diff --git a/general/datasets/TIGEM_hg38_ret_rna_seq_0916/summary.rtf b/general/datasets/TIGEM_hg38_ret_rna_seq_0916/summary.rtf
deleted file mode 100644
index 52d3ca2..0000000
--- a/general/datasets/TIGEM_hg38_ret_rna_seq_0916/summary.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Citation: ​ Pinelli M, Carissimo A, Cutillo L, Lai CH, Mutarelli M, Moretti MN, Singh MV, Karali M, Carrella D, Pizzo M, Russo F, Ferrari S, Ponzin D, Angelini C, Banfi S, di Bernardo D (2016) An atlas of gene expression and gene co-regulation in the human retina. Nucleic acids research 44 (12), 5773-5784
-
-
-
-The human retina is a specialized tissue involved in light stimulus transduction. Despite its unique biology, an accurate reference transcriptome is still missing. Here, we performed gene expression analysis (RNA-seq) of 50 retinal samples from non-visually impaired post-mortem donors. We identified novel transcripts with high confidence (Observed Transcriptome (ObsT)) and quantified the expression level of known transcripts (Reference Transcriptome (RefT)). The ObsT included 77 623 transcripts (23 960 genes) covering 137 Mb (35 Mb new transcribed genome). Most of the transcripts (92%) were multi-exonic: 81% with known isoforms, 16% with new isoforms and 3% belonging to new genes. The RefT included 13 792 genes across 94 521 known transcripts. Mitochondrial genes were among the most highly expressed, accounting for about 10% of the reads. Of all the protein-coding genes in Gencode, 65% are expressed in the retina. We exploited inter-individual variability in gene expression to infer a gene co-expression network and to identify genes specifically expressed in photoreceptor cells. We experimentally validated the photoreceptors localization of three genes in human retina that had not been previously reported. RNA-seq data and the gene co-expression network are available online (http://retina.tigem.it).
diff --git a/general/datasets/TSRI-DRG-AffyMOE430_0113-MDP/summary.rtf b/general/datasets/TSRI-DRG-AffyMOE430_0113-MDP/summary.rtf
new file mode 100644
index 0000000..643b371
--- /dev/null
+++ b/general/datasets/TSRI-DRG-AffyMOE430_0113-MDP/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 159, Name: TSRI DRG Affy Mouse Genome 430 2.0 (Jan13) RMA MDP **
\ No newline at end of file
diff --git a/general/datasets/TSRI_DRG_AffyMOE430_0113_MDP/summary.rtf b/general/datasets/TSRI_DRG_AffyMOE430_0113_MDP/summary.rtf
deleted file mode 100644
index 643b371..0000000
--- a/general/datasets/TSRI_DRG_AffyMOE430_0113_MDP/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 159, Name: TSRI DRG Affy Mouse Genome 430 2.0 (Jan13) RMA MDP **
\ No newline at end of file
diff --git a/general/datasets/Tigem_hg38_ret_rna_seq_0916/acknowledgment.rtf b/general/datasets/Tigem_hg38_ret_rna_seq_0916/acknowledgment.rtf
new file mode 100644
index 0000000..54bc7ff
--- /dev/null
+++ b/general/datasets/Tigem_hg38_ret_rna_seq_0916/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors are grateful to Mohit Parekh from the Fondazione Banca degli Occhi del Veneto (FBOV) for the collection of human retina samples. The authors would also like to thank Manuela Dionisi (technician) and Vincenzo Nigro (Head) of the Next Generation Sequencing Facility (TIGEM). This work was supported by FondazioneTelethon Grant (TGM11SB2) to SB and (TGM11SB1) toDdB and to the EU FP7 Radiant project (305626) to DdB.
diff --git a/general/datasets/Tigem_hg38_ret_rna_seq_0916/cases.rtf b/general/datasets/Tigem_hg38_ret_rna_seq_0916/cases.rtf
new file mode 100644
index 0000000..71f6c2f
--- /dev/null
+++ b/general/datasets/Tigem_hg38_ret_rna_seq_0916/cases.rtf
@@ -0,0 +1,3 @@
+Human retina sample collection
+
+Retina samples were collected at Fondazione Banca degli Occhi del Veneto (FBOV) from 50 different donors for cornea transplantation in compliance with the tenets of the Declaration of Helsinki and after an informed consent allowing the use of tissues for research purposes was signed by the donor's next of kin (for a description of donors Supplementary Table S1). Each harvested tissue was accompanied with the FBOV progressive number and with details on the age and gender of donor, the cause of death and the total post-mortem time (T). To limit the possible effects of post-mortem time on RNA integrity and transcriptomic profiles, retinal tissues were isolated only from eye bulbs with a total post-mortem interval (T) ≤ 26 h. The average post-mortem time of the samples was 20.5 h (ranging from 6 to 26 h). For the same reason, bulbs deriving from multi-organ donors were excluded from the analysis. In order to limit cross-contamination with adjacent tissues, we established a protocol for the dissection of the retina from the eye bulbs (14). The dissected retinal tissue was visually inspected to exclude any cross-contamination with the pigmented RPE/choroid and was immediately submerged in RNA Stabilization Reagent (RNA later; QIAGEN).
diff --git a/general/datasets/Tigem_hg38_ret_rna_seq_0916/contributors.rtf b/general/datasets/Tigem_hg38_ret_rna_seq_0916/contributors.rtf
new file mode 100644
index 0000000..7684e13
--- /dev/null
+++ b/general/datasets/Tigem_hg38_ret_rna_seq_0916/contributors.rtf
@@ -0,0 +1,50 @@
+
+ - Michele Pinelli1,†,
+ - Annamaria Carissimo1,†,
+ - Luisa Cutillo1,2,†,
+ - Ching-Hung Lai1,†,
+ - Margherita Mutarelli1,†,
+ - Maria Nicoletta Moretti1,†,
+ - Marwah Veer Singh1,
+ - Marianthi Karali1,
+ - Diego Carrella1,
+ - Mariateresa Pizzo1,
+ - Francesco Russo3,
+ - Stefano Ferrari4,
+ - Diego Ponzin4,
+ - Claudia Angelini3,
+ - Sandro Banfi1,5,* and
+ - Diego di Bernardo1,6,*
+
+
+-Author Affiliations
+
+
+ -
+
+ 1Telethon Institute of Genetics and Medicine (TIGEM), Via Campi Flegrei 34, 80078 Pozzuoli, Italy
+
+ -
+ 2Dipartimento Studi Aziendali e Quantitativi (DISAQ), Università degli studi di Napoli ‘Parthenope’, Via Generale Parisi, 80132 Napoli, Italy
+
+ -
+ 3Istituto per le Applicazioni del Calcolo, Consiglio Nazionale delle Ricerca, Via Pietro Castellino 111, 80131 Napoli, Italy
+
+ -
+ 4Fondazione Banca degli Occhi del Veneto, Via Paccagnella 11, 30174 Zelarino (Venice), Italy
+
+ -
+ 5Medical Genetics, Department of Biochemistry, Biophysics and General Pathology, Second University of Naples, via Luigi De Crecchio 7, 80138 Naples (NA), Italy
+
+ -
+ 6Dept. Of Chemical, Materials and Industrial Production Engineering, University of Naples ‘Federico II’, Piazzale Tecchio 80, 80125 Naples, Italy
+
+
+
++Author Notes
+
+
+ - ↵*To whom correspondence should be addressed. Tel: +39 81 192 30 600; Fax: +39 81 192 30 651; Email: dibernardo@tigem.it
+ - ↵Correspondence may also be addressed to Sandro Banfi. Tel: +39 81 192 30 600; Fax: +39 81 192 30 651; Email: banfi@tigem.it
+ - ↵†These authors contributed equally to this work as the first authors.
+
diff --git a/general/datasets/Tigem_hg38_ret_rna_seq_0916/experiment-design.rtf b/general/datasets/Tigem_hg38_ret_rna_seq_0916/experiment-design.rtf
new file mode 100644
index 0000000..f9da145
--- /dev/null
+++ b/general/datasets/Tigem_hg38_ret_rna_seq_0916/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA extraction, library preparation and sequencing
+
+Total RNA was extracted from the 50 human retina samples using the miRNeasy Kit (QIAGEN) according to the manufacturer's instructions. RNA was quantified using a NanoDrop ND-8000 spectrophotometer (NanoDrop Technologies) and the integrity was evaluated using an RNA 6000 Nano chip on a Bioanalyzer (Agilent Technologies). The RNA of the 50 samples had an average RNA integrity number (RIN) of 8.7 (ranging from 7.2 to 9.7). Libraries were prepared according to manufacturer's instructions (TruSeq RNA Sample Preparation kit) with an initial amount of 4 μg of total RNA. Quality control of library templates was performed using a High Sensitivity DNA Assay kit (Agilent Technologies) on a Bioanalyzer (Agilent Technologies). Qubit quantification platform was used to normalize samples for the library preparation (Qubit 2.0 Fluorometer, Life Technologies). Libraries were sequenced via a paired-end chemistry on an Illumina HiSeq1000 platform with an average yield of ∼6 Mb.
diff --git a/general/datasets/Tigem_hg38_ret_rna_seq_0916/processing.rtf b/general/datasets/Tigem_hg38_ret_rna_seq_0916/processing.rtf
new file mode 100644
index 0000000..7d8d4b3
--- /dev/null
+++ b/general/datasets/Tigem_hg38_ret_rna_seq_0916/processing.rtf
@@ -0,0 +1,3 @@
+Data analysis
+
+The exploratory analysis, whose steps are shown in Figure 1, was carried out with the ‘tuxedo’ software suite (Trapnell et al., 2010) and led to the definition of the Observed Transcriptome (ObsT). The conservative analysis (Figure 1) was carried out by running the RNA-Seq by Expectation-Maximization (RSEM) package (Li & Dewey, 2011) and led to the definition of the RefT.
diff --git a/general/datasets/Tigem_hg38_ret_rna_seq_0916/summary.rtf b/general/datasets/Tigem_hg38_ret_rna_seq_0916/summary.rtf
new file mode 100644
index 0000000..52d3ca2
--- /dev/null
+++ b/general/datasets/Tigem_hg38_ret_rna_seq_0916/summary.rtf
@@ -0,0 +1,5 @@
+Citation: ​ Pinelli M, Carissimo A, Cutillo L, Lai CH, Mutarelli M, Moretti MN, Singh MV, Karali M, Carrella D, Pizzo M, Russo F, Ferrari S, Ponzin D, Angelini C, Banfi S, di Bernardo D (2016) An atlas of gene expression and gene co-regulation in the human retina. Nucleic acids research 44 (12), 5773-5784
+
+
+
+The human retina is a specialized tissue involved in light stimulus transduction. Despite its unique biology, an accurate reference transcriptome is still missing. Here, we performed gene expression analysis (RNA-seq) of 50 retinal samples from non-visually impaired post-mortem donors. We identified novel transcripts with high confidence (Observed Transcriptome (ObsT)) and quantified the expression level of known transcripts (Reference Transcriptome (RefT)). The ObsT included 77 623 transcripts (23 960 genes) covering 137 Mb (35 Mb new transcribed genome). Most of the transcripts (92%) were multi-exonic: 81% with known isoforms, 16% with new isoforms and 3% belonging to new genes. The RefT included 13 792 genes across 94 521 known transcripts. Mitochondrial genes were among the most highly expressed, accounting for about 10% of the reads. Of all the protein-coding genes in Gencode, 65% are expressed in the retina. We exploited inter-individual variability in gene expression to infer a gene co-expression network and to identify genes specifically expressed in photoreceptor cells. We experimentally validated the photoreceptors localization of three genes in human retina that had not been previously reported. RNA-seq data and the gene co-expression network are available online (http://retina.tigem.it).
diff --git a/general/datasets/Tsri_drg_affymoe430_0113_mdp/summary.rtf b/general/datasets/Tsri_drg_affymoe430_0113_mdp/summary.rtf
new file mode 100644
index 0000000..643b371
--- /dev/null
+++ b/general/datasets/Tsri_drg_affymoe430_0113_mdp/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 159, Name: TSRI DRG Affy Mouse Genome 430 2.0 (Jan13) RMA MDP **
\ No newline at end of file
diff --git a/general/datasets/UBC_GSE23529HLT0613/summary.rtf b/general/datasets/UBC_GSE23529HLT0613/summary.rtf
deleted file mode 100644
index 9cb9538..0000000
--- a/general/datasets/UBC_GSE23529HLT0613/summary.rtf
+++ /dev/null
@@ -1,15 +0,0 @@
-This SuperSeries is composed of the following SubSeries:
-
-
-
-
- | GSE23352 Whole-genome gene expression profiles of non-tumorous human lung tissues: Laval set |
-
-
- | GSE23529 Whole-genome gene expression profiles of non-tumorous human lung tissues: UBC set |
-
-
- | GSE23545 Whole-genome gene expression profiles of non-tumorous human lung tissues: GRNG set |
-
-
-
diff --git a/general/datasets/UCAMC_LXSBrEtOH_RNA_Seq_0216/specifics.rtf b/general/datasets/UCAMC_LXSBrEtOH_RNA_Seq_0216/specifics.rtf
deleted file mode 100644
index ecd3498..0000000
--- a/general/datasets/UCAMC_LXSBrEtOH_RNA_Seq_0216/specifics.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Summary: RNA-seq in the LXS RI Panel Following an Intraperitoneal Injection of Ethanol
-
-RNA-seq-derived gene expression was determined from the LXS recombinant inbred strains and the two parental strains (ILS/Ibg and ISS/Ibg) that had been treated with 5 g/kg ethanol (20% v/v in normal saline, ip) 8 hours before being sacrificed. (This is a companion to a similar dataset in which the same strains were treated with normal saline [ip] and sacrificed at 8 hours). Breeders were obtained from the Jackson Laboratory and experimental mice were bred in-house at the University of Colorado Anschutz Medical Campus. All samples were from whole brain (minus cerebellum and olfactory bulbs) of male mice at an average age of 80 days (SEM: +/- 0.4; range: 56-106; median: 81). The rationale for the dosing and the implicit overall rationale for this experiment can be found in Radcliffe et al. (2006); Radcliffe et al. (2013); Darlington et al. (2013); and Bennett et al. (2015).
-
-A total of 396 mice representing 44 LXS RI strains and the ILS and ISS were used. Following total RNA isolation, an equal amount of RNA from three mice of each strain was quantitatively pooled and then the samples were enriched for poly-A RNA using the Dynabeads mRNA Purification kit (Invitrogen) as directed by the manufacturer. Paired-end (2x100, expected size of 300 bp), strand-specific, cluster-ready libraries were prepared from the poly-A enriched RNA using the ScriptSeq RNA-Seq Library Preparation Kit v2 (Illumina). Three libraries per strain were prepared, 132 in total. Due to poor quality or other technical difficulties, 5 libraries were eliminated leaving a total of 44 strains (including ILS and ISS) comprised of 40 strains with n=3, 3 strains with n=2 and 1 strains with n=1. Tophat (Trapnell et al., 2009) was used to map reads to RI-specific genomes; i.e., the ILS and ISS were sequenced (see Bennett et al., 2015) and with the use of genotype data from the LXS (see Saba et al., 2011), a genome was created for each RI strain. Mapped reads were then quantified at the gene level using HTSeq (Anders et al., 2015) with Ensembl full gene annotations and then converted to FPKM using the formula FPKM=fragments/kb exon/million mapped reads/2 (note that this assumes that both reads of a pair were successfully mapped; for a small percentage of the reads this was not the case and these were treated separately and added in). FPKM values were converted to log2 (FPKM+1) which gives a value of 0 for FPKM=0, 1 for FPKM=1, 2 for FPKM=3, 3 for FPKM=7, 4 for FPKM=15, and so on.
diff --git a/general/datasets/UCAMC_LXSBrSal_RNA_Seq_0216/specifics.rtf b/general/datasets/UCAMC_LXSBrSal_RNA_Seq_0216/specifics.rtf
deleted file mode 100644
index 89ef78d..0000000
--- a/general/datasets/UCAMC_LXSBrSal_RNA_Seq_0216/specifics.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Summary: RNA-seq in the LXS RI Panel Following an Intraperitoneal Injection of Saline
-
-RNA-seq-derived gene expression was determined from the LXS recombinant inbred strains and the two parental strains (ILS/Ibg and ISS/Ibg) that had been treated with normal saline (ip) 8 hours before being sacrificed. (This is a companion to a similar dataset in which the same strains were treated with 5 g/kg ethanol [20% v/v in normal saline, ip] and sacrificed at 8 hours). Breeders were obtained from the Jackson Laboratory and experimental mice were bred in-house at the University of Colorado Anschutz Medical Campus. All samples were from whole brain (minus cerebellum and olfactory bulbs) of male mice at an average age of 80 days (SEM: +/- 0.3; range: 58-106; median: 82). The rationale for the dosing and the implicit overall rationale for this experiment can be found in Radcliffe et al. (2006); Radcliffe et al. (2013); Darlington et al. (2013); and Bennett et al. (2015).
-
-A total of 396 mice representing 43 LXS RI strains and the ILS and ISS were used. Following total RNA isolation, an equal amount of RNA from three mice of each strain was quantitatively pooled and then the samples were enriched for poly-A RNA using the Dynabeads mRNA Purification kit (Invitrogen) as directed by the manufacturer. Paired-end (2x100, expected size of 300 bp), strand-specific, cluster-ready libraries were prepared from the poly-A enriched RNA using the ScriptSeq RNA-Seq Library Preparation Kit v2 (Illumina). Three libraries per strain were prepared, 132 in total. Due to poor quality or other technical difficulties, 9 libraries were eliminated leaving a total of 41 strains (including ILS and ISS) comprised of 36 strains with n=3, 3 strains with n=2 and 2 strains with n=1. Tophat (Trapnell et al., 2009) was used to map reads to RI-specific genomes; i.e., the ILS and ISS were sequenced (see Bennett et al., 2015) and with the use of genotype data from the LXS (see Saba et al., 2011), a genome was created for each RI strain. Mapped reads were then quantified at the gene level using HTSeq (Anders et al., 2015) with Ensembl full gene annotations and then converted to FPKM using the formula FPKM=fragments/kb exon/million mapped reads/2 (note that this assumes that both reads of a pair were successfully mapped; for a small percentage of the reads this was not the case and these were treated separately and added in). FPKM values were converted to log2 (FPKM+1) which gives a value of 0 for FPKM=0, 1 for FPKM=1, 2 for FPKM=3, 3 for FPKM=7, 4 for FPKM=15, and so on.
diff --git a/general/datasets/UCI_EC_0913/experiment-design.rtf b/general/datasets/UCI_EC_0913/experiment-design.rtf
deleted file mode 100644
index f6a3038..0000000
--- a/general/datasets/UCI_EC_0913/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Postmortem brain tissue was collected from ADRC brain banks. Cases were preferentially selected where 3 or more brain regions were available.
diff --git a/general/datasets/UCI_EC_0913/summary.rtf b/general/datasets/UCI_EC_0913/summary.rtf
deleted file mode 100644
index fea08e6..0000000
--- a/general/datasets/UCI_EC_0913/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Gene expression profiles were assessed in the hippocampus (HC), entorhinal cortex (EC), superior frontal gyrus (SG), and postcentral gyrus (PCG) across the lifespan of 63 cognitively intact individuals from 20-99 years old. New perspectives on the global gene changes that are associated with brain aging emerged, revealing two overarching concepts. First, different regions of the forebrain exhibited substantially different gene profile changes with age. For example, comparing equally powered groups, 5,029 probe sets were significantly altered with age (20-59 vs. 60-99) in the superior frontal gyrus, compared with 1,110 in the entorhinal cortex. Prominent change occurred in the 6th-7th decades across cortical regions, suggesting that this period is a critical transition point in brain aging, particularly in males. Second, clear gender differences in brain aging were evident across the lifespan, suggesting that the brain undergoes sexually dimorphic changes in gene expression not only in development but also in later life. Globally across all brain regions, males showed more gene change than females. Further, Gene Ontology analysis revealed that different categories of genes were predominantly affected in males vs. females. Notably, the male brain was characterized by global decreased catabolic and anabolic capacity with aging, with downregulated genes heavily enriched in energy production and protein synthesis/transport categories. Increased immune activation was a prominent feature of aging in both sexes, with more widespread activation in the female brain. These data open new opportunities to explore age-dependent changes in gene expression that set the balance between neurodegeneration and compensatory mechanisms in the brain, and suggest that this balance is set differently in males and females, an intriguing and novel idea. HgU133plus2.0 microarray chips were used to profile gene expression in 4 brain regions of cognitively intact humans, across the adult lifespan (ages 20-99).
diff --git a/general/datasets/UCI_HC_0913/experiment-design.rtf b/general/datasets/UCI_HC_0913/experiment-design.rtf
deleted file mode 100644
index f6a3038..0000000
--- a/general/datasets/UCI_HC_0913/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Postmortem brain tissue was collected from ADRC brain banks. Cases were preferentially selected where 3 or more brain regions were available.
diff --git a/general/datasets/UCI_HC_0913/summary.rtf b/general/datasets/UCI_HC_0913/summary.rtf
deleted file mode 100644
index fea08e6..0000000
--- a/general/datasets/UCI_HC_0913/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Gene expression profiles were assessed in the hippocampus (HC), entorhinal cortex (EC), superior frontal gyrus (SG), and postcentral gyrus (PCG) across the lifespan of 63 cognitively intact individuals from 20-99 years old. New perspectives on the global gene changes that are associated with brain aging emerged, revealing two overarching concepts. First, different regions of the forebrain exhibited substantially different gene profile changes with age. For example, comparing equally powered groups, 5,029 probe sets were significantly altered with age (20-59 vs. 60-99) in the superior frontal gyrus, compared with 1,110 in the entorhinal cortex. Prominent change occurred in the 6th-7th decades across cortical regions, suggesting that this period is a critical transition point in brain aging, particularly in males. Second, clear gender differences in brain aging were evident across the lifespan, suggesting that the brain undergoes sexually dimorphic changes in gene expression not only in development but also in later life. Globally across all brain regions, males showed more gene change than females. Further, Gene Ontology analysis revealed that different categories of genes were predominantly affected in males vs. females. Notably, the male brain was characterized by global decreased catabolic and anabolic capacity with aging, with downregulated genes heavily enriched in energy production and protein synthesis/transport categories. Increased immune activation was a prominent feature of aging in both sexes, with more widespread activation in the female brain. These data open new opportunities to explore age-dependent changes in gene expression that set the balance between neurodegeneration and compensatory mechanisms in the brain, and suggest that this balance is set differently in males and females, an intriguing and novel idea. HgU133plus2.0 microarray chips were used to profile gene expression in 4 brain regions of cognitively intact humans, across the adult lifespan (ages 20-99).
diff --git a/general/datasets/UCI_PCG_0913/experiment-design.rtf b/general/datasets/UCI_PCG_0913/experiment-design.rtf
deleted file mode 100644
index f6a3038..0000000
--- a/general/datasets/UCI_PCG_0913/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Postmortem brain tissue was collected from ADRC brain banks. Cases were preferentially selected where 3 or more brain regions were available.
diff --git a/general/datasets/UCI_PCG_0913/summary.rtf b/general/datasets/UCI_PCG_0913/summary.rtf
deleted file mode 100644
index fea08e6..0000000
--- a/general/datasets/UCI_PCG_0913/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Gene expression profiles were assessed in the hippocampus (HC), entorhinal cortex (EC), superior frontal gyrus (SG), and postcentral gyrus (PCG) across the lifespan of 63 cognitively intact individuals from 20-99 years old. New perspectives on the global gene changes that are associated with brain aging emerged, revealing two overarching concepts. First, different regions of the forebrain exhibited substantially different gene profile changes with age. For example, comparing equally powered groups, 5,029 probe sets were significantly altered with age (20-59 vs. 60-99) in the superior frontal gyrus, compared with 1,110 in the entorhinal cortex. Prominent change occurred in the 6th-7th decades across cortical regions, suggesting that this period is a critical transition point in brain aging, particularly in males. Second, clear gender differences in brain aging were evident across the lifespan, suggesting that the brain undergoes sexually dimorphic changes in gene expression not only in development but also in later life. Globally across all brain regions, males showed more gene change than females. Further, Gene Ontology analysis revealed that different categories of genes were predominantly affected in males vs. females. Notably, the male brain was characterized by global decreased catabolic and anabolic capacity with aging, with downregulated genes heavily enriched in energy production and protein synthesis/transport categories. Increased immune activation was a prominent feature of aging in both sexes, with more widespread activation in the female brain. These data open new opportunities to explore age-dependent changes in gene expression that set the balance between neurodegeneration and compensatory mechanisms in the brain, and suggest that this balance is set differently in males and females, an intriguing and novel idea. HgU133plus2.0 microarray chips were used to profile gene expression in 4 brain regions of cognitively intact humans, across the adult lifespan (ages 20-99).
diff --git a/general/datasets/UCI_SG_0913/experiment-design.rtf b/general/datasets/UCI_SG_0913/experiment-design.rtf
deleted file mode 100644
index f6a3038..0000000
--- a/general/datasets/UCI_SG_0913/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Postmortem brain tissue was collected from ADRC brain banks. Cases were preferentially selected where 3 or more brain regions were available.
diff --git a/general/datasets/UCI_SG_0913/summary.rtf b/general/datasets/UCI_SG_0913/summary.rtf
deleted file mode 100644
index fea08e6..0000000
--- a/general/datasets/UCI_SG_0913/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Gene expression profiles were assessed in the hippocampus (HC), entorhinal cortex (EC), superior frontal gyrus (SG), and postcentral gyrus (PCG) across the lifespan of 63 cognitively intact individuals from 20-99 years old. New perspectives on the global gene changes that are associated with brain aging emerged, revealing two overarching concepts. First, different regions of the forebrain exhibited substantially different gene profile changes with age. For example, comparing equally powered groups, 5,029 probe sets were significantly altered with age (20-59 vs. 60-99) in the superior frontal gyrus, compared with 1,110 in the entorhinal cortex. Prominent change occurred in the 6th-7th decades across cortical regions, suggesting that this period is a critical transition point in brain aging, particularly in males. Second, clear gender differences in brain aging were evident across the lifespan, suggesting that the brain undergoes sexually dimorphic changes in gene expression not only in development but also in later life. Globally across all brain regions, males showed more gene change than females. Further, Gene Ontology analysis revealed that different categories of genes were predominantly affected in males vs. females. Notably, the male brain was characterized by global decreased catabolic and anabolic capacity with aging, with downregulated genes heavily enriched in energy production and protein synthesis/transport categories. Increased immune activation was a prominent feature of aging in both sexes, with more widespread activation in the female brain. These data open new opportunities to explore age-dependent changes in gene expression that set the balance between neurodegeneration and compensatory mechanisms in the brain, and suggest that this balance is set differently in males and females, an intriguing and novel idea. HgU133plus2.0 microarray chips were used to profile gene expression in 4 brain regions of cognitively intact humans, across the adult lifespan (ages 20-99).
diff --git a/general/datasets/UCLA_AXB_BXA_Aor_Jan16/experiment-design.rtf b/general/datasets/UCLA_AXB_BXA_Aor_Jan16/experiment-design.rtf
deleted file mode 100644
index 1113b37..0000000
--- a/general/datasets/UCLA_AXB_BXA_Aor_Jan16/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GWAS for expression in aortas of F1 offspring of inbred strains crossed with C57BL/6J carrying ApoE-Leiden and CETP transgenes fed chow diet for 8 weeks followed by Western diet for 16 weeks
diff --git a/general/datasets/UCLA_AXB_BXA_Aor_Jan16/platform.rtf b/general/datasets/UCLA_AXB_BXA_Aor_Jan16/platform.rtf
deleted file mode 100644
index 41439e8..0000000
--- a/general/datasets/UCLA_AXB_BXA_Aor_Jan16/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GPL11180 HT_MG-430_PM] Affymetrix HT MG-430 PM Array Plate
diff --git a/general/datasets/UCLA_AXB_BXA_Aor_Jan16/specifics.rtf b/general/datasets/UCLA_AXB_BXA_Aor_Jan16/specifics.rtf
deleted file mode 100644
index 8cdd2b9..0000000
--- a/general/datasets/UCLA_AXB_BXA_Aor_Jan16/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Group AXB/BXA
\ No newline at end of file
diff --git a/general/datasets/UCLA_AXB_BXA_Aor_Jan16/summary.rtf b/general/datasets/UCLA_AXB_BXA_Aor_Jan16/summary.rtf
deleted file mode 100644
index 59e49a1..0000000
--- a/general/datasets/UCLA_AXB_BXA_Aor_Jan16/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Identify genes in the aorta whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. 104 of these strains were bred onto a C57BL/6J background carrying transgenes for both ApoE-Leiden and cholesteryl ester transfer protein (CETP). The RMA values of genes were used for genome wide association as described in Davis et al PLOS Genetics 2015. These data are used to identify candidate genes at loci associated with atherosclerotic lesion size.
diff --git a/general/datasets/UCLA_AXB_BXA_Femur_0113_RSN/summary.rtf b/general/datasets/UCLA_AXB_BXA_Femur_0113_RSN/summary.rtf
deleted file mode 100644
index aaa3dd1..0000000
--- a/general/datasets/UCLA_AXB_BXA_Femur_0113_RSN/summary.rtf
+++ /dev/null
@@ -1,15 +0,0 @@
-Summary of DatasetId 163, Name: UCLA GSE27483 AXB/BXA Bone Femur ILM Mouse WG-6 v1, v1.1 (Jan13)
-
-J Bone Miner Res. 2009 Jan;24(1):105-16. doi: 10.1359/jbmr.080908.
-
-An integrative genetics approach to identify candidate genes regulating BMD: combining linkage, gene expression, and association
-
-Farber CR, van Nas A, Ghazalpour A, Aten JE, Doss S, Sos B, Schadt EE, Ingram-Drake L, Davis RC, Horvath S, Smith DJ, Drake TA, Lusis AJ
-
-Abstract
-
-Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J x C3H/HeJ (BXH) F(2) mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F(2) mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bonemass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification.
-
-
- - PMID:18767929, PMCID: PMC2661539, DOI:10.1359/jbmr.080908
-
diff --git a/general/datasets/UCLA_AXB_BXA_Liv_Jan16/experiment-design.rtf b/general/datasets/UCLA_AXB_BXA_Liv_Jan16/experiment-design.rtf
deleted file mode 100644
index 715a1a3..0000000
--- a/general/datasets/UCLA_AXB_BXA_Liv_Jan16/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GWAS for expression in livers of F1 offspring of inbred strains crossed with C57BL/6J carrying ApoE-Leiden and CETP transgenes fed chow diet for 8 weeks followed by Western diet for 16 weeks
diff --git a/general/datasets/UCLA_AXB_BXA_Liv_Jan16/platform.rtf b/general/datasets/UCLA_AXB_BXA_Liv_Jan16/platform.rtf
deleted file mode 100644
index 7659aeb..0000000
--- a/general/datasets/UCLA_AXB_BXA_Liv_Jan16/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GPL11180 HT_MG-430_PM] Affymetrix HT MG-430 PM Array Plate
diff --git a/general/datasets/UCLA_AXB_BXA_Liv_Jan16/specifics.rtf b/general/datasets/UCLA_AXB_BXA_Liv_Jan16/specifics.rtf
deleted file mode 100644
index 8cdd2b9..0000000
--- a/general/datasets/UCLA_AXB_BXA_Liv_Jan16/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Group AXB/BXA
\ No newline at end of file
diff --git a/general/datasets/UCLA_AXB_BXA_Liv_Jan16/summary.rtf b/general/datasets/UCLA_AXB_BXA_Liv_Jan16/summary.rtf
deleted file mode 100644
index 9ffc1be..0000000
--- a/general/datasets/UCLA_AXB_BXA_Liv_Jan16/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Identify genes in the liver whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. 104 of these strains were bred onto a C57BL/6J background carrying transgenes for both ApoE-Leiden and cholesteryl ester transfer protein (CETP). The RMA values of genes were used for genome wide association as described in Davis et al PLOS Genetics 2015. These data are used to identify candidate genes at loci associated with atherosclerotic lesion size.
diff --git a/general/datasets/UCLA_BXD-on_Femur_0113_RSN/acknowledgment.rtf b/general/datasets/UCLA_BXD-on_Femur_0113_RSN/acknowledgment.rtf
new file mode 100644
index 0000000..841713a
--- /dev/null
+++ b/general/datasets/UCLA_BXD-on_Femur_0113_RSN/acknowledgment.rtf
@@ -0,0 +1 @@
+Calabrese G, Bennett BJ, Orozco L, Kang HM, Eskin E, Dombret C, De Backer O, Lusis AJ, Farber CR.
diff --git a/general/datasets/UCLA_BXD-on_Femur_0113_RSN/experiment-design.rtf b/general/datasets/UCLA_BXD-on_Femur_0113_RSN/experiment-design.rtf
new file mode 100644
index 0000000..6a72392
--- /dev/null
+++ b/general/datasets/UCLA_BXD-on_Femur_0113_RSN/experiment-design.rtf
@@ -0,0 +1 @@
+RNA from cortical bone (femoral diaphysis free of marrow) were profiled from 99 Hybrid Mouse Diversity Panel strains were profiled. Sixteen-week old male mice were used in this study. A total of 1-3 mice per strain were arrayed.
diff --git a/general/datasets/UCLA_BXD-on_Femur_0113_RSN/platform.rtf b/general/datasets/UCLA_BXD-on_Femur_0113_RSN/platform.rtf
new file mode 100644
index 0000000..578985c
--- /dev/null
+++ b/general/datasets/UCLA_BXD-on_Femur_0113_RSN/platform.rtf
@@ -0,0 +1 @@
+Illumina mouse-6 v1.1 expression beadchip
diff --git a/general/datasets/UCLA_BXD-on_Femur_0113_RSN/processing.rtf b/general/datasets/UCLA_BXD-on_Femur_0113_RSN/processing.rtf
new file mode 100644
index 0000000..9f66d05
--- /dev/null
+++ b/general/datasets/UCLA_BXD-on_Femur_0113_RSN/processing.rtf
@@ -0,0 +1 @@
+The expression values were transformed using the Variance Stabilizing Transformation (VST), and normalized with the Robust Spline Normalization (RSN) algorithm using the LumiR R package. After normalization, the ComBat software was used to adjust for batch effects using an empirical Bayes method.
diff --git a/general/datasets/UCLA_BXD-on_Femur_0113_RSN/summary.rtf b/general/datasets/UCLA_BXD-on_Femur_0113_RSN/summary.rtf
new file mode 100644
index 0000000..df75fa6
--- /dev/null
+++ b/general/datasets/UCLA_BXD-on_Femur_0113_RSN/summary.rtf
@@ -0,0 +1 @@
+Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis was used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal and femoral BMD revealed four significant associations (-log10P > 5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12 and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism though which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression gene module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cell of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.
diff --git a/general/datasets/UCLA_BXD_Aor_Jan16/experiment-design.rtf b/general/datasets/UCLA_BXD_Aor_Jan16/experiment-design.rtf
deleted file mode 100644
index 1113b37..0000000
--- a/general/datasets/UCLA_BXD_Aor_Jan16/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GWAS for expression in aortas of F1 offspring of inbred strains crossed with C57BL/6J carrying ApoE-Leiden and CETP transgenes fed chow diet for 8 weeks followed by Western diet for 16 weeks
diff --git a/general/datasets/UCLA_BXD_Aor_Jan16/platform.rtf b/general/datasets/UCLA_BXD_Aor_Jan16/platform.rtf
deleted file mode 100644
index 41439e8..0000000
--- a/general/datasets/UCLA_BXD_Aor_Jan16/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GPL11180 HT_MG-430_PM] Affymetrix HT MG-430 PM Array Plate
diff --git a/general/datasets/UCLA_BXD_Aor_Jan16/specifics.rtf b/general/datasets/UCLA_BXD_Aor_Jan16/specifics.rtf
deleted file mode 100644
index 3864d15..0000000
--- a/general/datasets/UCLA_BXD_Aor_Jan16/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Group BXD
\ No newline at end of file
diff --git a/general/datasets/UCLA_BXD_Aor_Jan16/summary.rtf b/general/datasets/UCLA_BXD_Aor_Jan16/summary.rtf
deleted file mode 100644
index 59e49a1..0000000
--- a/general/datasets/UCLA_BXD_Aor_Jan16/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Identify genes in the aorta whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. 104 of these strains were bred onto a C57BL/6J background carrying transgenes for both ApoE-Leiden and cholesteryl ester transfer protein (CETP). The RMA values of genes were used for genome wide association as described in Davis et al PLOS Genetics 2015. These data are used to identify candidate genes at loci associated with atherosclerotic lesion size.
diff --git a/general/datasets/UCLA_BXD_Liv_Jan16/experiment-design.rtf b/general/datasets/UCLA_BXD_Liv_Jan16/experiment-design.rtf
deleted file mode 100644
index 715a1a3..0000000
--- a/general/datasets/UCLA_BXD_Liv_Jan16/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GWAS for expression in livers of F1 offspring of inbred strains crossed with C57BL/6J carrying ApoE-Leiden and CETP transgenes fed chow diet for 8 weeks followed by Western diet for 16 weeks
diff --git a/general/datasets/UCLA_BXD_Liv_Jan16/platform.rtf b/general/datasets/UCLA_BXD_Liv_Jan16/platform.rtf
deleted file mode 100644
index 7659aeb..0000000
--- a/general/datasets/UCLA_BXD_Liv_Jan16/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GPL11180 HT_MG-430_PM] Affymetrix HT MG-430 PM Array Plate
diff --git a/general/datasets/UCLA_BXD_Liv_Jan16/summary.rtf b/general/datasets/UCLA_BXD_Liv_Jan16/summary.rtf
deleted file mode 100644
index 9ffc1be..0000000
--- a/general/datasets/UCLA_BXD_Liv_Jan16/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Identify genes in the liver whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. 104 of these strains were bred onto a C57BL/6J background carrying transgenes for both ApoE-Leiden and cholesteryl ester transfer protein (CETP). The RMA values of genes were used for genome wide association as described in Davis et al PLOS Genetics 2015. These data are used to identify candidate genes at loci associated with atherosclerotic lesion size.
diff --git a/general/datasets/UCLA_BXD_on_Femur_0113_RSN/acknowledgment.rtf b/general/datasets/UCLA_BXD_on_Femur_0113_RSN/acknowledgment.rtf
deleted file mode 100644
index 841713a..0000000
--- a/general/datasets/UCLA_BXD_on_Femur_0113_RSN/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Calabrese G, Bennett BJ, Orozco L, Kang HM, Eskin E, Dombret C, De Backer O, Lusis AJ, Farber CR.
diff --git a/general/datasets/UCLA_BXD_on_Femur_0113_RSN/experiment-design.rtf b/general/datasets/UCLA_BXD_on_Femur_0113_RSN/experiment-design.rtf
deleted file mode 100644
index 6a72392..0000000
--- a/general/datasets/UCLA_BXD_on_Femur_0113_RSN/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-RNA from cortical bone (femoral diaphysis free of marrow) were profiled from 99 Hybrid Mouse Diversity Panel strains were profiled. Sixteen-week old male mice were used in this study. A total of 1-3 mice per strain were arrayed.
diff --git a/general/datasets/UCLA_BXD_on_Femur_0113_RSN/platform.rtf b/general/datasets/UCLA_BXD_on_Femur_0113_RSN/platform.rtf
deleted file mode 100644
index 578985c..0000000
--- a/general/datasets/UCLA_BXD_on_Femur_0113_RSN/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Illumina mouse-6 v1.1 expression beadchip
diff --git a/general/datasets/UCLA_BXD_on_Femur_0113_RSN/processing.rtf b/general/datasets/UCLA_BXD_on_Femur_0113_RSN/processing.rtf
deleted file mode 100644
index 9f66d05..0000000
--- a/general/datasets/UCLA_BXD_on_Femur_0113_RSN/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The expression values were transformed using the Variance Stabilizing Transformation (VST), and normalized with the Robust Spline Normalization (RSN) algorithm using the LumiR R package. After normalization, the ComBat software was used to adjust for batch effects using an empirical Bayes method.
diff --git a/general/datasets/UCLA_BXD_on_Femur_0113_RSN/summary.rtf b/general/datasets/UCLA_BXD_on_Femur_0113_RSN/summary.rtf
deleted file mode 100644
index df75fa6..0000000
--- a/general/datasets/UCLA_BXD_on_Femur_0113_RSN/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis was used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal and femoral BMD revealed four significant associations (-log10P > 5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12 and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism though which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression gene module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cell of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.
diff --git a/general/datasets/UCLA_BXH_Femur_0113_RSN/summary.rtf b/general/datasets/UCLA_BXH_Femur_0113_RSN/summary.rtf
deleted file mode 100644
index b5cf311..0000000
--- a/general/datasets/UCLA_BXH_Femur_0113_RSN/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 164, Name: UCLA GSE27483 BXH Bone Femur ILM Mouse WG-6 v1, v1.1 (Jan13)
\ No newline at end of file
diff --git a/general/datasets/UCLA_CXB_Aor_Jan16/experiment-design.rtf b/general/datasets/UCLA_CXB_Aor_Jan16/experiment-design.rtf
deleted file mode 100644
index 1113b37..0000000
--- a/general/datasets/UCLA_CXB_Aor_Jan16/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GWAS for expression in aortas of F1 offspring of inbred strains crossed with C57BL/6J carrying ApoE-Leiden and CETP transgenes fed chow diet for 8 weeks followed by Western diet for 16 weeks
diff --git a/general/datasets/UCLA_CXB_Aor_Jan16/platform.rtf b/general/datasets/UCLA_CXB_Aor_Jan16/platform.rtf
deleted file mode 100644
index 41439e8..0000000
--- a/general/datasets/UCLA_CXB_Aor_Jan16/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GPL11180 HT_MG-430_PM] Affymetrix HT MG-430 PM Array Plate
diff --git a/general/datasets/UCLA_CXB_Aor_Jan16/specifics.rtf b/general/datasets/UCLA_CXB_Aor_Jan16/specifics.rtf
deleted file mode 100644
index 20dd05b..0000000
--- a/general/datasets/UCLA_CXB_Aor_Jan16/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Group CXB
\ No newline at end of file
diff --git a/general/datasets/UCLA_CXB_Aor_Jan16/summary.rtf b/general/datasets/UCLA_CXB_Aor_Jan16/summary.rtf
deleted file mode 100644
index 59e49a1..0000000
--- a/general/datasets/UCLA_CXB_Aor_Jan16/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Identify genes in the aorta whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. 104 of these strains were bred onto a C57BL/6J background carrying transgenes for both ApoE-Leiden and cholesteryl ester transfer protein (CETP). The RMA values of genes were used for genome wide association as described in Davis et al PLOS Genetics 2015. These data are used to identify candidate genes at loci associated with atherosclerotic lesion size.
diff --git a/general/datasets/UCLA_CXB_Liv_Jan16/experiment-design.rtf b/general/datasets/UCLA_CXB_Liv_Jan16/experiment-design.rtf
deleted file mode 100644
index 715a1a3..0000000
--- a/general/datasets/UCLA_CXB_Liv_Jan16/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GWAS for expression in livers of F1 offspring of inbred strains crossed with C57BL/6J carrying ApoE-Leiden and CETP transgenes fed chow diet for 8 weeks followed by Western diet for 16 weeks
diff --git a/general/datasets/UCLA_CXB_Liv_Jan16/platform.rtf b/general/datasets/UCLA_CXB_Liv_Jan16/platform.rtf
deleted file mode 100644
index 7659aeb..0000000
--- a/general/datasets/UCLA_CXB_Liv_Jan16/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GPL11180 HT_MG-430_PM] Affymetrix HT MG-430 PM Array Plate
diff --git a/general/datasets/UCLA_CXB_Liv_Jan16/specifics.rtf b/general/datasets/UCLA_CXB_Liv_Jan16/specifics.rtf
deleted file mode 100644
index 20dd05b..0000000
--- a/general/datasets/UCLA_CXB_Liv_Jan16/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Group CXB
\ No newline at end of file
diff --git a/general/datasets/UCLA_CXB_Liv_Jan16/summary.rtf b/general/datasets/UCLA_CXB_Liv_Jan16/summary.rtf
deleted file mode 100644
index 9ffc1be..0000000
--- a/general/datasets/UCLA_CXB_Liv_Jan16/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Identify genes in the liver whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. 104 of these strains were bred onto a C57BL/6J background carrying transgenes for both ApoE-Leiden and cholesteryl ester transfer protein (CETP). The RMA values of genes were used for genome wide association as described in Davis et al PLOS Genetics 2015. These data are used to identify candidate genes at loci associated with atherosclerotic lesion size.
diff --git a/general/datasets/UCLA_MDP_Femur_0113_RSN/acknowledgment.rtf b/general/datasets/UCLA_MDP_Femur_0113_RSN/acknowledgment.rtf
deleted file mode 100644
index 841713a..0000000
--- a/general/datasets/UCLA_MDP_Femur_0113_RSN/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Calabrese G, Bennett BJ, Orozco L, Kang HM, Eskin E, Dombret C, De Backer O, Lusis AJ, Farber CR.
diff --git a/general/datasets/UCLA_MDP_Femur_0113_RSN/experiment-design.rtf b/general/datasets/UCLA_MDP_Femur_0113_RSN/experiment-design.rtf
deleted file mode 100644
index 6a72392..0000000
--- a/general/datasets/UCLA_MDP_Femur_0113_RSN/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-RNA from cortical bone (femoral diaphysis free of marrow) were profiled from 99 Hybrid Mouse Diversity Panel strains were profiled. Sixteen-week old male mice were used in this study. A total of 1-3 mice per strain were arrayed.
diff --git a/general/datasets/UCLA_MDP_Femur_0113_RSN/platform.rtf b/general/datasets/UCLA_MDP_Femur_0113_RSN/platform.rtf
deleted file mode 100644
index 578985c..0000000
--- a/general/datasets/UCLA_MDP_Femur_0113_RSN/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Illumina mouse-6 v1.1 expression beadchip
diff --git a/general/datasets/UCLA_MDP_Femur_0113_RSN/processing.rtf b/general/datasets/UCLA_MDP_Femur_0113_RSN/processing.rtf
deleted file mode 100644
index 9f66d05..0000000
--- a/general/datasets/UCLA_MDP_Femur_0113_RSN/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The expression values were transformed using the Variance Stabilizing Transformation (VST), and normalized with the Robust Spline Normalization (RSN) algorithm using the LumiR R package. After normalization, the ComBat software was used to adjust for batch effects using an empirical Bayes method.
diff --git a/general/datasets/UCLA_MDP_Femur_0113_RSN/summary.rtf b/general/datasets/UCLA_MDP_Femur_0113_RSN/summary.rtf
deleted file mode 100644
index df75fa6..0000000
--- a/general/datasets/UCLA_MDP_Femur_0113_RSN/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis was used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal and femoral BMD revealed four significant associations (-log10P > 5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12 and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism though which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression gene module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cell of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.
diff --git a/general/datasets/UCSD_AIL_HIP_RNA_Seq_0418/specifics.rtf b/general/datasets/UCSD_AIL_HIP_RNA_Seq_0418/specifics.rtf
deleted file mode 100644
index f3a4dfd..0000000
--- a/general/datasets/UCSD_AIL_HIP_RNA_Seq_0418/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Hippocampus
\ No newline at end of file
diff --git a/general/datasets/UCSD_AIL_HIP_RNA_Seq_0418/summary.rtf b/general/datasets/UCSD_AIL_HIP_RNA_Seq_0418/summary.rtf
deleted file mode 100644
index 37e2d16..0000000
--- a/general/datasets/UCSD_AIL_HIP_RNA_Seq_0418/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Genome wide association analyses (GWAS) in model organisms have numerous advantages compared to human GWAS, including the ability to use populations with well-defined genetic diversity, the ability to collect tissue for gene expression analysis and the ability to perform experimental manipulations. We examined behavioral, physiological, and gene expression traits in 1,063 male and female mice from a 50-generation intercross between two inbred strains (LG/J and SM/J). We used genotyping by sequencing in conjunction with whole genome sequence data from the two founder strains to obtain genotypes at 4.3 million SNPs. As expected, all alleles were common (mean MAF=0.35) and linkage disequilibrium degraded rapidly, providing excellent power and sub-megabase mapping precision. We identified 126 genome-wide significant loci for 50 traits and integrated this information with 7,081 cis-eQTLs and 1,476 trans-eQTLs identified in hippocampus, striatum and prefrontal cortex. We replicated several loci that were identified using an earlier generation of this intercross, including an association between locomotor activity and a locus containing a single gene, Csmd1. We also showed that Csmd1 mutant mice recapitulated the locomotor phenotype. Our results demonstrate the utility of this population, identify numerous novel associations, and provide examples of replication in an independent cohort, which is customary in human genetics, and replication by experimental manipulation, which is a unique advantage of model organisms.
diff --git a/general/datasets/UCSD_AIL_HIP_RNA_Seq_log2_0418/specifics.rtf b/general/datasets/UCSD_AIL_HIP_RNA_Seq_log2_0418/specifics.rtf
deleted file mode 100644
index 843d470..0000000
--- a/general/datasets/UCSD_AIL_HIP_RNA_Seq_log2_0418/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Log2
\ No newline at end of file
diff --git a/general/datasets/UCSD_AIL_HIP_RNA_Seq_log2_0418/summary.rtf b/general/datasets/UCSD_AIL_HIP_RNA_Seq_log2_0418/summary.rtf
deleted file mode 100644
index 37e2d16..0000000
--- a/general/datasets/UCSD_AIL_HIP_RNA_Seq_log2_0418/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Genome wide association analyses (GWAS) in model organisms have numerous advantages compared to human GWAS, including the ability to use populations with well-defined genetic diversity, the ability to collect tissue for gene expression analysis and the ability to perform experimental manipulations. We examined behavioral, physiological, and gene expression traits in 1,063 male and female mice from a 50-generation intercross between two inbred strains (LG/J and SM/J). We used genotyping by sequencing in conjunction with whole genome sequence data from the two founder strains to obtain genotypes at 4.3 million SNPs. As expected, all alleles were common (mean MAF=0.35) and linkage disequilibrium degraded rapidly, providing excellent power and sub-megabase mapping precision. We identified 126 genome-wide significant loci for 50 traits and integrated this information with 7,081 cis-eQTLs and 1,476 trans-eQTLs identified in hippocampus, striatum and prefrontal cortex. We replicated several loci that were identified using an earlier generation of this intercross, including an association between locomotor activity and a locus containing a single gene, Csmd1. We also showed that Csmd1 mutant mice recapitulated the locomotor phenotype. Our results demonstrate the utility of this population, identify numerous novel associations, and provide examples of replication in an independent cohort, which is customary in human genetics, and replication by experimental manipulation, which is a unique advantage of model organisms.
diff --git a/general/datasets/UCSD_AIL_PFC_RNA_Seq_0418/specifics.rtf b/general/datasets/UCSD_AIL_PFC_RNA_Seq_0418/specifics.rtf
deleted file mode 100644
index 30656c6..0000000
--- a/general/datasets/UCSD_AIL_PFC_RNA_Seq_0418/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Prefrontal Cortex
\ No newline at end of file
diff --git a/general/datasets/UCSD_AIL_PFC_RNA_Seq_0418/summary.rtf b/general/datasets/UCSD_AIL_PFC_RNA_Seq_0418/summary.rtf
deleted file mode 100644
index 37e2d16..0000000
--- a/general/datasets/UCSD_AIL_PFC_RNA_Seq_0418/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Genome wide association analyses (GWAS) in model organisms have numerous advantages compared to human GWAS, including the ability to use populations with well-defined genetic diversity, the ability to collect tissue for gene expression analysis and the ability to perform experimental manipulations. We examined behavioral, physiological, and gene expression traits in 1,063 male and female mice from a 50-generation intercross between two inbred strains (LG/J and SM/J). We used genotyping by sequencing in conjunction with whole genome sequence data from the two founder strains to obtain genotypes at 4.3 million SNPs. As expected, all alleles were common (mean MAF=0.35) and linkage disequilibrium degraded rapidly, providing excellent power and sub-megabase mapping precision. We identified 126 genome-wide significant loci for 50 traits and integrated this information with 7,081 cis-eQTLs and 1,476 trans-eQTLs identified in hippocampus, striatum and prefrontal cortex. We replicated several loci that were identified using an earlier generation of this intercross, including an association between locomotor activity and a locus containing a single gene, Csmd1. We also showed that Csmd1 mutant mice recapitulated the locomotor phenotype. Our results demonstrate the utility of this population, identify numerous novel associations, and provide examples of replication in an independent cohort, which is customary in human genetics, and replication by experimental manipulation, which is a unique advantage of model organisms.
diff --git a/general/datasets/UCSD_AIL_PFC_RNA_Seq_log2_0418/specifics.rtf b/general/datasets/UCSD_AIL_PFC_RNA_Seq_log2_0418/specifics.rtf
deleted file mode 100644
index 843d470..0000000
--- a/general/datasets/UCSD_AIL_PFC_RNA_Seq_log2_0418/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Log2
\ No newline at end of file
diff --git a/general/datasets/UCSD_AIL_PFC_RNA_Seq_log2_0418/summary.rtf b/general/datasets/UCSD_AIL_PFC_RNA_Seq_log2_0418/summary.rtf
deleted file mode 100644
index 37e2d16..0000000
--- a/general/datasets/UCSD_AIL_PFC_RNA_Seq_log2_0418/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Genome wide association analyses (GWAS) in model organisms have numerous advantages compared to human GWAS, including the ability to use populations with well-defined genetic diversity, the ability to collect tissue for gene expression analysis and the ability to perform experimental manipulations. We examined behavioral, physiological, and gene expression traits in 1,063 male and female mice from a 50-generation intercross between two inbred strains (LG/J and SM/J). We used genotyping by sequencing in conjunction with whole genome sequence data from the two founder strains to obtain genotypes at 4.3 million SNPs. As expected, all alleles were common (mean MAF=0.35) and linkage disequilibrium degraded rapidly, providing excellent power and sub-megabase mapping precision. We identified 126 genome-wide significant loci for 50 traits and integrated this information with 7,081 cis-eQTLs and 1,476 trans-eQTLs identified in hippocampus, striatum and prefrontal cortex. We replicated several loci that were identified using an earlier generation of this intercross, including an association between locomotor activity and a locus containing a single gene, Csmd1. We also showed that Csmd1 mutant mice recapitulated the locomotor phenotype. Our results demonstrate the utility of this population, identify numerous novel associations, and provide examples of replication in an independent cohort, which is customary in human genetics, and replication by experimental manipulation, which is a unique advantage of model organisms.
diff --git a/general/datasets/UCSD_AIL_STR_RNA_Seq_0418/specifics.rtf b/general/datasets/UCSD_AIL_STR_RNA_Seq_0418/specifics.rtf
deleted file mode 100644
index fe51d98..0000000
--- a/general/datasets/UCSD_AIL_STR_RNA_Seq_0418/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Striatum
\ No newline at end of file
diff --git a/general/datasets/UCSD_AIL_STR_RNA_Seq_0418/summary.rtf b/general/datasets/UCSD_AIL_STR_RNA_Seq_0418/summary.rtf
deleted file mode 100644
index 37e2d16..0000000
--- a/general/datasets/UCSD_AIL_STR_RNA_Seq_0418/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Genome wide association analyses (GWAS) in model organisms have numerous advantages compared to human GWAS, including the ability to use populations with well-defined genetic diversity, the ability to collect tissue for gene expression analysis and the ability to perform experimental manipulations. We examined behavioral, physiological, and gene expression traits in 1,063 male and female mice from a 50-generation intercross between two inbred strains (LG/J and SM/J). We used genotyping by sequencing in conjunction with whole genome sequence data from the two founder strains to obtain genotypes at 4.3 million SNPs. As expected, all alleles were common (mean MAF=0.35) and linkage disequilibrium degraded rapidly, providing excellent power and sub-megabase mapping precision. We identified 126 genome-wide significant loci for 50 traits and integrated this information with 7,081 cis-eQTLs and 1,476 trans-eQTLs identified in hippocampus, striatum and prefrontal cortex. We replicated several loci that were identified using an earlier generation of this intercross, including an association between locomotor activity and a locus containing a single gene, Csmd1. We also showed that Csmd1 mutant mice recapitulated the locomotor phenotype. Our results demonstrate the utility of this population, identify numerous novel associations, and provide examples of replication in an independent cohort, which is customary in human genetics, and replication by experimental manipulation, which is a unique advantage of model organisms.
diff --git a/general/datasets/UCSD_AIL_STR_RNA_Seq_log2_0418/specifics.rtf b/general/datasets/UCSD_AIL_STR_RNA_Seq_log2_0418/specifics.rtf
deleted file mode 100644
index 843d470..0000000
--- a/general/datasets/UCSD_AIL_STR_RNA_Seq_log2_0418/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Log2
\ No newline at end of file
diff --git a/general/datasets/UCSD_AIL_STR_RNA_Seq_log2_0418/summary.rtf b/general/datasets/UCSD_AIL_STR_RNA_Seq_log2_0418/summary.rtf
deleted file mode 100644
index 37e2d16..0000000
--- a/general/datasets/UCSD_AIL_STR_RNA_Seq_log2_0418/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Genome wide association analyses (GWAS) in model organisms have numerous advantages compared to human GWAS, including the ability to use populations with well-defined genetic diversity, the ability to collect tissue for gene expression analysis and the ability to perform experimental manipulations. We examined behavioral, physiological, and gene expression traits in 1,063 male and female mice from a 50-generation intercross between two inbred strains (LG/J and SM/J). We used genotyping by sequencing in conjunction with whole genome sequence data from the two founder strains to obtain genotypes at 4.3 million SNPs. As expected, all alleles were common (mean MAF=0.35) and linkage disequilibrium degraded rapidly, providing excellent power and sub-megabase mapping precision. We identified 126 genome-wide significant loci for 50 traits and integrated this information with 7,081 cis-eQTLs and 1,476 trans-eQTLs identified in hippocampus, striatum and prefrontal cortex. We replicated several loci that were identified using an earlier generation of this intercross, including an association between locomotor activity and a locus containing a single gene, Csmd1. We also showed that Csmd1 mutant mice recapitulated the locomotor phenotype. Our results demonstrate the utility of this population, identify numerous novel associations, and provide examples of replication in an independent cohort, which is customary in human genetics, and replication by experimental manipulation, which is a unique advantage of model organisms.
diff --git a/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/acknowledgment.rtf b/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/acknowledgment.rtf
deleted file mode 100644
index 24f8c40..0000000
--- a/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors wish to acknowledge technical assistance from: D. Godfrey, S. Lionikaite, V. Lionikaite, A.S. Lionikiene and J. Zekos as well as technical and intellectual input from M. Abney, J. Borevitz, K. Broman, N. Cai, R. Cheng, N. Cox, R. Davies, J. Flint, L. Goodstadt, P. Grabowski, B. Harr, E. Leffler, R. Mott, J. Nicod, J. Novembre, A. Price, M. Stephens, D. Weeks and X. Zhou. This project was funded by NIH R01GM097737 and P50DA037844 (A.A.P.), NIH T32DA07255 (C.C.P.), NIH T32GM07197 (N.M.G.), NIH R01AR056280 (D.A.B.), NIH R01AR060234 (C.L.A.-B.), the Fellowship from the Human Frontiers Science Program (P.C.) and the Howard Hughes Medical Institute (J.K.P.).
diff --git a/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/cases.rtf b/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/cases.rtf
deleted file mode 100644
index 97eed8a..0000000
--- a/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Phenotype, genotype and RNA-seq gene expression data is available at
-
-http://datadryad.org/resource/doi:10.5061/dryad.2rs41
diff --git a/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/processing.rtf b/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/processing.rtf
deleted file mode 100644
index 9c368fa..0000000
--- a/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-FPKM data were quantitle normalized for each ENSEMBL gene (mRNA) model (Identifiers such as ENSMUSG00000093778). Every gene/mRNA therefore has a mean expression value of 0 and a perfectly normal distribution, even if the original distribution was bimodal. The QQ plots is GN will be straight lines. There is no data at all on expression level in this original data set downloaded from http://dx.doi.org/10.5061/dryad.2rs41
diff --git a/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/specifics.rtf b/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/specifics.rtf
deleted file mode 100644
index 780e837..0000000
--- a/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Hippocampus
quantitle normalized
\ No newline at end of file
diff --git a/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/summary.rtf b/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/summary.rtf
deleted file mode 100644
index 0639fe7..0000000
--- a/general/datasets/UCSD_CFW_HIP_RNA_Seq_0117/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice. Full article available here.
diff --git a/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/acknowledgment.rtf b/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/acknowledgment.rtf
deleted file mode 100644
index 24f8c40..0000000
--- a/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors wish to acknowledge technical assistance from: D. Godfrey, S. Lionikaite, V. Lionikaite, A.S. Lionikiene and J. Zekos as well as technical and intellectual input from M. Abney, J. Borevitz, K. Broman, N. Cai, R. Cheng, N. Cox, R. Davies, J. Flint, L. Goodstadt, P. Grabowski, B. Harr, E. Leffler, R. Mott, J. Nicod, J. Novembre, A. Price, M. Stephens, D. Weeks and X. Zhou. This project was funded by NIH R01GM097737 and P50DA037844 (A.A.P.), NIH T32DA07255 (C.C.P.), NIH T32GM07197 (N.M.G.), NIH R01AR056280 (D.A.B.), NIH R01AR060234 (C.L.A.-B.), the Fellowship from the Human Frontiers Science Program (P.C.) and the Howard Hughes Medical Institute (J.K.P.).
diff --git a/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/cases.rtf b/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/cases.rtf
deleted file mode 100644
index 97eed8a..0000000
--- a/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Phenotype, genotype and RNA-seq gene expression data is available at
-
-http://datadryad.org/resource/doi:10.5061/dryad.2rs41
diff --git a/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/processing.rtf b/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/processing.rtf
deleted file mode 100644
index 9c368fa..0000000
--- a/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-FPKM data were quantitle normalized for each ENSEMBL gene (mRNA) model (Identifiers such as ENSMUSG00000093778). Every gene/mRNA therefore has a mean expression value of 0 and a perfectly normal distribution, even if the original distribution was bimodal. The QQ plots is GN will be straight lines. There is no data at all on expression level in this original data set downloaded from http://dx.doi.org/10.5061/dryad.2rs41
diff --git a/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/specifics.rtf b/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/specifics.rtf
deleted file mode 100644
index 0ef5311..0000000
--- a/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/specifics.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Notes: We took the raw fpkm values provided by Apurva from file GN811-UCSD_CFW_RNA-Seq_HIP_raw_FPKM.txt.zip (11M) and transformed to log2 Z-scored. (GN811-UCSD_CFW_RNA-Seq_HIP_log2_ZScore.txt.zip (4.0M))
-
-RNA-Seq Log2 Z-score
-
-In general, the array data that we put in GeneNetwork has been logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having a standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/summary.rtf b/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/summary.rtf
deleted file mode 100644
index 0639fe7..0000000
--- a/general/datasets/UCSD_CFW_HIP_RNA_Seq_log2_0117/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice. Full article available here.
diff --git a/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/acknowledgment.rtf b/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/acknowledgment.rtf
deleted file mode 100644
index 24f8c40..0000000
--- a/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors wish to acknowledge technical assistance from: D. Godfrey, S. Lionikaite, V. Lionikaite, A.S. Lionikiene and J. Zekos as well as technical and intellectual input from M. Abney, J. Borevitz, K. Broman, N. Cai, R. Cheng, N. Cox, R. Davies, J. Flint, L. Goodstadt, P. Grabowski, B. Harr, E. Leffler, R. Mott, J. Nicod, J. Novembre, A. Price, M. Stephens, D. Weeks and X. Zhou. This project was funded by NIH R01GM097737 and P50DA037844 (A.A.P.), NIH T32DA07255 (C.C.P.), NIH T32GM07197 (N.M.G.), NIH R01AR056280 (D.A.B.), NIH R01AR060234 (C.L.A.-B.), the Fellowship from the Human Frontiers Science Program (P.C.) and the Howard Hughes Medical Institute (J.K.P.).
diff --git a/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/cases.rtf b/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/cases.rtf
deleted file mode 100644
index 97eed8a..0000000
--- a/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Phenotype, genotype and RNA-seq gene expression data is available at
-
-http://datadryad.org/resource/doi:10.5061/dryad.2rs41
diff --git a/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/processing.rtf b/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/processing.rtf
deleted file mode 100644
index 9c368fa..0000000
--- a/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-FPKM data were quantitle normalized for each ENSEMBL gene (mRNA) model (Identifiers such as ENSMUSG00000093778). Every gene/mRNA therefore has a mean expression value of 0 and a perfectly normal distribution, even if the original distribution was bimodal. The QQ plots is GN will be straight lines. There is no data at all on expression level in this original data set downloaded from http://dx.doi.org/10.5061/dryad.2rs41
diff --git a/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/specifics.rtf b/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/specifics.rtf
deleted file mode 100644
index 30656c6..0000000
--- a/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Prefrontal Cortex
\ No newline at end of file
diff --git a/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/summary.rtf b/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/summary.rtf
deleted file mode 100644
index 0639fe7..0000000
--- a/general/datasets/UCSD_CFW_PFC_RNA_Seq_0117/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice. Full article available here.
diff --git a/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/acknowledgment.rtf b/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/acknowledgment.rtf
deleted file mode 100644
index 24f8c40..0000000
--- a/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors wish to acknowledge technical assistance from: D. Godfrey, S. Lionikaite, V. Lionikaite, A.S. Lionikiene and J. Zekos as well as technical and intellectual input from M. Abney, J. Borevitz, K. Broman, N. Cai, R. Cheng, N. Cox, R. Davies, J. Flint, L. Goodstadt, P. Grabowski, B. Harr, E. Leffler, R. Mott, J. Nicod, J. Novembre, A. Price, M. Stephens, D. Weeks and X. Zhou. This project was funded by NIH R01GM097737 and P50DA037844 (A.A.P.), NIH T32DA07255 (C.C.P.), NIH T32GM07197 (N.M.G.), NIH R01AR056280 (D.A.B.), NIH R01AR060234 (C.L.A.-B.), the Fellowship from the Human Frontiers Science Program (P.C.) and the Howard Hughes Medical Institute (J.K.P.).
diff --git a/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/cases.rtf b/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/cases.rtf
deleted file mode 100644
index 97eed8a..0000000
--- a/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Phenotype, genotype and RNA-seq gene expression data is available at
-
-http://datadryad.org/resource/doi:10.5061/dryad.2rs41
diff --git a/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/processing.rtf b/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/processing.rtf
deleted file mode 100644
index 9c368fa..0000000
--- a/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-FPKM data were quantitle normalized for each ENSEMBL gene (mRNA) model (Identifiers such as ENSMUSG00000093778). Every gene/mRNA therefore has a mean expression value of 0 and a perfectly normal distribution, even if the original distribution was bimodal. The QQ plots is GN will be straight lines. There is no data at all on expression level in this original data set downloaded from http://dx.doi.org/10.5061/dryad.2rs41
diff --git a/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/specifics.rtf b/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/specifics.rtf
deleted file mode 100644
index 6077f41..0000000
--- a/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/specifics.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA-Seq Log2 Z-score
-
-In general, the array data that we put in GeneNetwork has been logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/summary.rtf b/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/summary.rtf
deleted file mode 100644
index 0639fe7..0000000
--- a/general/datasets/UCSD_CFW_PFC_RNA_Seq_log2_0117/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice. Full article available here.
diff --git a/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/acknowledgment.rtf b/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/acknowledgment.rtf
deleted file mode 100644
index 24f8c40..0000000
--- a/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors wish to acknowledge technical assistance from: D. Godfrey, S. Lionikaite, V. Lionikaite, A.S. Lionikiene and J. Zekos as well as technical and intellectual input from M. Abney, J. Borevitz, K. Broman, N. Cai, R. Cheng, N. Cox, R. Davies, J. Flint, L. Goodstadt, P. Grabowski, B. Harr, E. Leffler, R. Mott, J. Nicod, J. Novembre, A. Price, M. Stephens, D. Weeks and X. Zhou. This project was funded by NIH R01GM097737 and P50DA037844 (A.A.P.), NIH T32DA07255 (C.C.P.), NIH T32GM07197 (N.M.G.), NIH R01AR056280 (D.A.B.), NIH R01AR060234 (C.L.A.-B.), the Fellowship from the Human Frontiers Science Program (P.C.) and the Howard Hughes Medical Institute (J.K.P.).
diff --git a/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/cases.rtf b/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/cases.rtf
deleted file mode 100644
index 97eed8a..0000000
--- a/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Phenotype, genotype and RNA-seq gene expression data is available at
-
-http://datadryad.org/resource/doi:10.5061/dryad.2rs41
diff --git a/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/processing.rtf b/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/processing.rtf
deleted file mode 100644
index 9c368fa..0000000
--- a/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-FPKM data were quantitle normalized for each ENSEMBL gene (mRNA) model (Identifiers such as ENSMUSG00000093778). Every gene/mRNA therefore has a mean expression value of 0 and a perfectly normal distribution, even if the original distribution was bimodal. The QQ plots is GN will be straight lines. There is no data at all on expression level in this original data set downloaded from http://dx.doi.org/10.5061/dryad.2rs41
diff --git a/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/specifics.rtf b/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/specifics.rtf
deleted file mode 100644
index 0e70b6c..0000000
--- a/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Striatum
diff --git a/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/summary.rtf b/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/summary.rtf
deleted file mode 100644
index 0639fe7..0000000
--- a/general/datasets/UCSD_CFW_SPL_RNA_Seq_0117/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice. Full article available here.
diff --git a/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/acknowledgment.rtf b/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/acknowledgment.rtf
deleted file mode 100644
index 24f8c40..0000000
--- a/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The authors wish to acknowledge technical assistance from: D. Godfrey, S. Lionikaite, V. Lionikaite, A.S. Lionikiene and J. Zekos as well as technical and intellectual input from M. Abney, J. Borevitz, K. Broman, N. Cai, R. Cheng, N. Cox, R. Davies, J. Flint, L. Goodstadt, P. Grabowski, B. Harr, E. Leffler, R. Mott, J. Nicod, J. Novembre, A. Price, M. Stephens, D. Weeks and X. Zhou. This project was funded by NIH R01GM097737 and P50DA037844 (A.A.P.), NIH T32DA07255 (C.C.P.), NIH T32GM07197 (N.M.G.), NIH R01AR056280 (D.A.B.), NIH R01AR060234 (C.L.A.-B.), the Fellowship from the Human Frontiers Science Program (P.C.) and the Howard Hughes Medical Institute (J.K.P.).
diff --git a/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/cases.rtf b/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/cases.rtf
deleted file mode 100644
index 97eed8a..0000000
--- a/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Phenotype, genotype and RNA-seq gene expression data is available at
-
-http://datadryad.org/resource/doi:10.5061/dryad.2rs41
diff --git a/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/processing.rtf b/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/processing.rtf
deleted file mode 100644
index 9c368fa..0000000
--- a/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-FPKM data were quantitle normalized for each ENSEMBL gene (mRNA) model (Identifiers such as ENSMUSG00000093778). Every gene/mRNA therefore has a mean expression value of 0 and a perfectly normal distribution, even if the original distribution was bimodal. The QQ plots is GN will be straight lines. There is no data at all on expression level in this original data set downloaded from http://dx.doi.org/10.5061/dryad.2rs41
diff --git a/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/specifics.rtf b/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/specifics.rtf
deleted file mode 100644
index 6077f41..0000000
--- a/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/specifics.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA-Seq Log2 Z-score
-
-In general, the array data that we put in GeneNetwork has been logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/summary.rtf b/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/summary.rtf
deleted file mode 100644
index 0639fe7..0000000
--- a/general/datasets/UCSD_CFW_STR_RNA_Seq_log2_0117/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice. Full article available here.
diff --git a/general/datasets/UConn_RGC_RSeq_log2_0918/specifics.rtf b/general/datasets/UConn_RGC_RSeq_log2_0918/specifics.rtf
deleted file mode 100644
index 843d470..0000000
--- a/general/datasets/UConn_RGC_RSeq_log2_0918/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Log2
\ No newline at end of file
diff --git a/general/datasets/UConn_RGC_RSeq_log2_0918/summary.rtf b/general/datasets/UConn_RGC_RSeq_log2_0918/summary.rtf
deleted file mode 100644
index aab94b8..0000000
--- a/general/datasets/UConn_RGC_RSeq_log2_0918/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Retinal ganglion cells (RGCs) convey the major output of information collected from the eye to the brain. Thirty subtypes of RGCs have been identified to date. Here, we analyze 6225 RGCs (average of 5000 genes per cell) from right and left eyes by single-cell RNA-seq and classify them into 40 subtypes using clustering algorithms. We identify additional subtypes and markers, as well as transcription factors predicted to cooperate in specifying RGC subtypes. Zic1, a marker of the right eye-enriched subtype, is validated by immunostaining in situ. Runx1 and Fst, the markers of other subtypes, are validated in purified RGCs by fluorescent in situ hybridization (FISH) and immunostaining. We show the extent of gene expression variability needed for subtype segregation, and we show a hierarchy in diversification from a cell-type population to subtypes. Finally, we present a website for comparing the gene expression of RGC subtypes.
-
-https://www.nature.com/articles/s41467-018-05134-3
diff --git a/general/datasets/UConn_RGC_RSeq_r_0918/specifics.rtf b/general/datasets/UConn_RGC_RSeq_r_0918/specifics.rtf
deleted file mode 100644
index 8c82808..0000000
--- a/general/datasets/UConn_RGC_RSeq_r_0918/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Raw data
\ No newline at end of file
diff --git a/general/datasets/UConn_RGC_RSeq_r_0918/summary.rtf b/general/datasets/UConn_RGC_RSeq_r_0918/summary.rtf
deleted file mode 100644
index aab94b8..0000000
--- a/general/datasets/UConn_RGC_RSeq_r_0918/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Retinal ganglion cells (RGCs) convey the major output of information collected from the eye to the brain. Thirty subtypes of RGCs have been identified to date. Here, we analyze 6225 RGCs (average of 5000 genes per cell) from right and left eyes by single-cell RNA-seq and classify them into 40 subtypes using clustering algorithms. We identify additional subtypes and markers, as well as transcription factors predicted to cooperate in specifying RGC subtypes. Zic1, a marker of the right eye-enriched subtype, is validated by immunostaining in situ. Runx1 and Fst, the markers of other subtypes, are validated in purified RGCs by fluorescent in situ hybridization (FISH) and immunostaining. We show the extent of gene expression variability needed for subtype segregation, and we show a hierarchy in diversification from a cell-type population to subtypes. Finally, we present a website for comparing the gene expression of RGC subtypes.
-
-https://www.nature.com/articles/s41467-018-05134-3
diff --git a/general/datasets/UConn_RGC_RSeq_s_0918/specifics.rtf b/general/datasets/UConn_RGC_RSeq_s_0918/specifics.rtf
deleted file mode 100644
index 394e70a..0000000
--- a/general/datasets/UConn_RGC_RSeq_s_0918/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Siamak normalization mapped to our DB
\ No newline at end of file
diff --git a/general/datasets/UConn_RGC_RSeq_s_0918/summary.rtf b/general/datasets/UConn_RGC_RSeq_s_0918/summary.rtf
deleted file mode 100644
index aab94b8..0000000
--- a/general/datasets/UConn_RGC_RSeq_s_0918/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Retinal ganglion cells (RGCs) convey the major output of information collected from the eye to the brain. Thirty subtypes of RGCs have been identified to date. Here, we analyze 6225 RGCs (average of 5000 genes per cell) from right and left eyes by single-cell RNA-seq and classify them into 40 subtypes using clustering algorithms. We identify additional subtypes and markers, as well as transcription factors predicted to cooperate in specifying RGC subtypes. Zic1, a marker of the right eye-enriched subtype, is validated by immunostaining in situ. Runx1 and Fst, the markers of other subtypes, are validated in purified RGCs by fluorescent in situ hybridization (FISH) and immunostaining. We show the extent of gene expression variability needed for subtype segregation, and we show a hierarchy in diversification from a cell-type population to subtypes. Finally, we present a website for comparing the gene expression of RGC subtypes.
-
-https://www.nature.com/articles/s41467-018-05134-3
diff --git a/general/datasets/UFL_MDP_Hipp0814/summary.rtf b/general/datasets/UFL_MDP_Hipp0814/summary.rtf
deleted file mode 100644
index 5bf7963..0000000
--- a/general/datasets/UFL_MDP_Hipp0814/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Information regarding of this data set will become available soon
diff --git a/general/datasets/UND_NIDA_HXB_BXH_IndBP_log2z8_0321/cases.rtf b/general/datasets/UND_NIDA_HXB_BXH_IndBP_log2z8_0321/cases.rtf
deleted file mode 100644
index ce39718..0000000
--- a/general/datasets/UND_NIDA_HXB_BXH_IndBP_log2z8_0321/cases.rtf
+++ /dev/null
@@ -1,1075 +0,0 @@
-
-
-
- |
- Index
- |
-
- Strain
- |
-
- Sex
- |
-
- TMT Batch
- |
-
- TMT Channel
- |
-
-
- |
- 1
- |
-
- SHR
- |
-
- M
- |
-
- 1
- |
-
- sig127C
- |
-
-
- |
- 2
- |
-
- SHR
- |
-
- F
- |
-
- 1
- |
-
- sig128N
- |
-
-
- |
- 3
- |
-
- BN.Lx
- |
-
- M
- |
-
- 1
- |
-
- sig129C
- |
-
-
- |
- 4
- |
-
- BN.Lx
- |
-
- F
- |
-
- 1
- |
-
- sig131N
- |
-
-
- |
- 5
- |
-
- HXB18
- |
-
- F
- |
-
- 1
- |
-
- sig126
- |
-
-
- |
- 6
- |
-
- HXB18
- |
-
- M
- |
-
- 1
- |
-
- sig127N
- |
-
-
- |
- 7
- |
-
- BXH3
- |
-
- M
- |
-
- 1
- |
-
- sig131C
- |
-
-
- |
- 8
- |
-
- BXH3
- |
-
- F
- |
-
- 1
- |
-
- sig132N
- |
-
-
- |
- 9
- |
-
- BXH12
- |
-
- M
- |
-
- 1
- |
-
- sig132C
- |
-
-
- |
- 10
- |
-
- BXH12
- |
-
- F
- |
-
- 1
- |
-
- sig133N
- |
-
-
- |
- 11
- |
-
- BXH13
- |
-
- M
- |
-
- 1
- |
-
- sig133C
- |
-
-
- |
- 12
- |
-
- BXH13
- |
-
- F
- |
-
- 1
- |
-
- sig134N
- |
-
-
- |
- 13
- |
-
- BXH6
- |
-
- M
- |
-
- 2
- |
-
- sig127N
- |
-
-
- |
- 14
- |
-
- BXH6
- |
-
- F
- |
-
- 2
- |
-
- sig127C
- |
-
-
- |
- 15
- |
-
- BXH8
- |
-
- M
- |
-
- 2
- |
-
- sig128N
- |
-
-
- |
- 16
- |
-
- BXH8
- |
-
- F
- |
-
- 2
- |
-
- sig128C
- |
-
-
- |
- 17
- |
-
- HXB1
- |
-
- M
- |
-
- 2
- |
-
- sig129N
- |
-
-
- |
- 18
- |
-
- HXB1
- |
-
- F
- |
-
- 2
- |
-
- sig129C
- |
-
-
- |
- 19
- |
-
- HXB10
- |
-
- M
- |
-
- 2
- |
-
- sig130N
- |
-
-
- |
- 20
- |
-
- HXB10
- |
-
- F
- |
-
- 2
- |
-
- sig130C
- |
-
-
- |
- 21
- |
-
- HXB13
- |
-
- M
- |
-
- 2
- |
-
- sig131N
- |
-
-
- |
- 22
- |
-
- HXB13
- |
-
- F
- |
-
- 2
- |
-
- sig131C
- |
-
-
- |
- 23
- |
-
- HXB15
- |
-
- M
- |
-
- 2
- |
-
- sig132N
- |
-
-
- |
- 24
- |
-
- HXB15
- |
-
- F
- |
-
- 2
- |
-
- sig132C
- |
-
-
- |
- 25
- |
-
- HXB17
- |
-
- M
- |
-
- 2
- |
-
- sig133N
- |
-
-
- |
- 26
- |
-
- HXB17
- |
-
- F
- |
-
- 2
- |
-
- sig133C
- |
-
-
- |
- 27
- |
-
- HXB4
- |
-
- M
- |
-
- 2
- |
-
- sig134N
- |
-
-
- |
- 28
- |
-
- HXB4
- |
-
- F
- |
-
- 3
- |
-
- sig127N
- |
-
-
- |
- 29
- |
-
- HXB2
- |
-
- M
- |
-
- 3
- |
-
- sig127C
- |
-
-
- |
- 30
- |
-
- HXB2
- |
-
- F
- |
-
- 3
- |
-
- sig128N
- |
-
-
- |
- 31
- |
-
- HXB20
- |
-
- M
- |
-
- 3
- |
-
- sig128C
- |
-
-
- |
- 32
- |
-
- HXB20
- |
-
- F
- |
-
- 3
- |
-
- sig129N
- |
-
-
- |
- 33
- |
-
- HXB22
- |
-
- M
- |
-
- 3
- |
-
- sig129C
- |
-
-
- |
- 34
- |
-
- HXB22
- |
-
- F
- |
-
- 3
- |
-
- sig130N
- |
-
-
- |
- 35
- |
-
- HXB29
- |
-
- M
- |
-
- 3
- |
-
- sig130C
- |
-
-
- |
- 36
- |
-
- HXB29
- |
-
- F
- |
-
- 3
- |
-
- sig131N
- |
-
-
- |
- 37
- |
-
- HXB3
- |
-
- M
- |
-
- 3
- |
-
- sig131C
- |
-
-
- |
- 38
- |
-
- HXB3
- |
-
- F
- |
-
- 3
- |
-
- sig132N
- |
-
-
- |
- 39
- |
-
- HXB31
- |
-
- M
- |
-
- 3
- |
-
- sig132C
- |
-
-
- |
- 40
- |
-
- HXB31
- |
-
- F
- |
-
- 3
- |
-
- sig133N
- |
-
-
- |
- 41
- |
-
- HXB7
- |
-
- M
- |
-
- 3
- |
-
- sig133C
- |
-
-
- |
- 42
- |
-
- HXB7
- |
-
- F
- |
-
- 3
- |
-
- sig134N
- |
-
-
- |
- 43
- |
-
- BXH5
- |
-
- F
- |
-
- 4
- |
-
- sig126
- |
-
-
- |
- 44
- |
-
- BXH5
- |
-
- M
- |
-
- 4
- |
-
- sig127N
- |
-
-
- |
- 45
- |
-
- BXH9
- |
-
- F
- |
-
- 4
- |
-
- sig127C
- |
-
-
- |
- 46
- |
-
- BXH9
- |
-
- M
- |
-
- 4
- |
-
- sig128N
- |
-
-
- |
- 47
- |
-
- BXH10
- |
-
- F
- |
-
- 4
- |
-
- sig128C
- |
-
-
- |
- 48
- |
-
- BXH10
- |
-
- M
- |
-
- 4
- |
-
- sig129N
- |
-
-
- |
- 49
- |
-
- BXH11
- |
-
- F
- |
-
- 4
- |
-
- sig129C
- |
-
-
- |
- 50
- |
-
- BXH11
- |
-
- M
- |
-
- 4
- |
-
- sig130N
- |
-
-
- |
- 51
- |
-
- HXB5
- |
-
- F
- |
-
- 4
- |
-
- sig130C
- |
-
-
- |
- 52
- |
-
- HXB5
- |
-
- M
- |
-
- 4
- |
-
- sig131N
- |
-
-
- |
- 53
- |
-
- HXB21
- |
-
- F
- |
-
- 5
- |
-
- sig126
- |
-
-
- |
- 54
- |
-
- HXB21
- |
-
- M
- |
-
- 5
- |
-
- sig127N
- |
-
-
- |
- 55
- |
-
- HXB23
- |
-
- F
- |
-
- 5
- |
-
- sig127C
- |
-
-
- |
- 56
- |
-
- HXB23
- |
-
- M
- |
-
- 5
- |
-
- sig128N
- |
-
-
- |
- 57
- |
-
- HXB24
- |
-
- F
- |
-
- 5
- |
-
- sig128C
- |
-
-
- |
- 58
- |
-
- HXB24
- |
-
- M
- |
-
- 5
- |
-
- sig129N
- |
-
-
- |
- 59
- |
-
- HXB25
- |
-
- F
- |
-
- 5
- |
-
- sig129C
- |
-
-
- |
- 60
- |
-
- HXB25
- |
-
- M
- |
-
- 5
- |
-
- sig130N
- |
-
-
- |
- 61
- |
-
- HXB27
- |
-
- F
- |
-
- 5
- |
-
- sig130C
- |
-
-
- |
- 62
- |
-
- HXB27
- |
-
- M
- |
-
- 5
- |
-
- sig131N
- |
-
-
-
diff --git a/general/datasets/UND_NIDA_HXB_BXH_IndBP_log2z8_0321/processing.rtf b/general/datasets/UND_NIDA_HXB_BXH_IndBP_log2z8_0321/processing.rtf
deleted file mode 100644
index c05f172..0000000
--- a/general/datasets/UND_NIDA_HXB_BXH_IndBP_log2z8_0321/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Sample processing protocol: The proteomic data were generated with 3 batches of 16-plex and 2 batches of 11-plex TMT experiments. The rat brain samples from 31 HXB/BXH strains with replicates (i.e., male and female) were lysed, digested, and labeled with either 11 or 16 different TMT tags. The TMT-labeled peptides were pooled with an equal amount of each and fractionated into 42 fractions in a concatenated fashion on an RP-HPLC column (4.6 mm x 250 mm) under basic pH conditions. each fraction was run sequentially on a column (75 μm x 20 cm for the whole proteome, 50 μm x ∼30 cm for phosphoproteome, 1.9 μm C18 resin from Dr. Maisch GmbH, 65°C to reduce backpressure) interfaced with a Q Exactive HF Orbitrap or Fusion MS (Thermo Fisher). Peptides were eluted by a 2-3 hr gradient (buffer A: 0.2% formic acid, 5% DMSO; buffer B: buffer A plus 65% acetonitrile). MS settings included the MS1 scan (410-1600 m/z, 60,000 or 120,000 resolution, 1 × 106 AGC and 50 ms maximal ion time) and 20 data-dependent MS2 scans (fixed first mass of 120 m/z, 60,000 resolution, 1 × 105 AGC, 100-150 ms maximal ion time, HCD, 35%–38% normalized collision energy, ∼1.0 m/z isolation window).
-
-Data processing protocol: The MS/MS raw files are processed using the JUMP searching engine against the UniProt mouse database. Searches were performed using 8 ppm mass tolerance for precursor ions due to JUMP’s auto mass correction function and 15 ppm for fragment ions, allowing up to two missed trypsin cleavage sites. TMT tags on lysine residues and peptide N termini (+229.162932 Da) were used for static modifications and the dynamic modifications include oxidation of methionine residues (+15.99492 Da). The assigned peptides are filtered by minimal peptide length, maximum miscleavages, mass-to-charge accuracy and matching scores. The peptides are then divided into groups according to peptide length, trypticity, modification, miscleavage, and charge and then further filtered by matching scores to reduce protein or phosphopeptide FDR to below 1%. Proteins or phosphopeptides were quantified by summing reporter ion counts across all matched PSMs using our in-house software.
-
-Protein quantification: We first extracted the TMT reporter ion intensities of each PSM and corrected the raw intensities based on the isotopic distribution of each labeling reagent. We discarded PSMs with low intensities (i.e., the minimum intensity of 1,000 and the median intensity of 5,000). After normalizing abundance with the trimmed median intensity of all PSMs, we calculated the mean-centered intensities across samples (e.g., relative intensities between each sample and the mean) and summarized protein relative intensities by averaging related PSMs. Finally, we derived protein absolute intensities by multiplying the relative intensities by the grand mean of the three most highly abundant PSMs. We first used the internal standard to normalize 3 batches of 16-plex experiments and 2 batches of 11-plex experiments. We then used the LIMMA batch removal function to normalize all five batches of TMT experiments.
diff --git a/general/datasets/UND_NIDA_HXB_BXH_IndBP_log2z8_0321/specifics.rtf b/general/datasets/UND_NIDA_HXB_BXH_IndBP_log2z8_0321/specifics.rtf
deleted file mode 100644
index 2fa1f25..0000000
--- a/general/datasets/UND_NIDA_HXB_BXH_IndBP_log2z8_0321/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Brain Proteome Individual (protein level)
\ No newline at end of file
diff --git a/general/datasets/UND_NIDA_HXB_BXH_IndBP_log2z8_0321/summary.rtf b/general/datasets/UND_NIDA_HXB_BXH_IndBP_log2z8_0321/summary.rtf
deleted file mode 100644
index 94c8e6e..0000000
--- a/general/datasets/UND_NIDA_HXB_BXH_IndBP_log2z8_0321/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Brain proteome data. Deep proteome data were generated using whole brain tissue from both parents and 29 members of the HXB family, one male and one female per strain. Proteins in these samples were identified and quantified using the tandem-mass-tag (TMT) labeling strategy coupled with two-dimensional liquid chromatography-tandem mass spectrometry (LC/LC-MS/MS).
-
-This rat whole brain proteome data provide protein expression of 31 HXB/BXH strains, including 29 RI strains, and two parental strains, SHR/OlaIpcv and BN-Lx/Cub. A total of 8,124 proteins were quantified across all 31 strains.
diff --git a/general/datasets/UND_NIDA_HXB_BXH_IndBPep_log2z8_0321/cases.rtf b/general/datasets/UND_NIDA_HXB_BXH_IndBPep_log2z8_0321/cases.rtf
deleted file mode 100644
index ce39718..0000000
--- a/general/datasets/UND_NIDA_HXB_BXH_IndBPep_log2z8_0321/cases.rtf
+++ /dev/null
@@ -1,1075 +0,0 @@
-
-
-
- |
- Index
- |
-
- Strain
- |
-
- Sex
- |
-
- TMT Batch
- |
-
- TMT Channel
- |
-
-
- |
- 1
- |
-
- SHR
- |
-
- M
- |
-
- 1
- |
-
- sig127C
- |
-
-
- |
- 2
- |
-
- SHR
- |
-
- F
- |
-
- 1
- |
-
- sig128N
- |
-
-
- |
- 3
- |
-
- BN.Lx
- |
-
- M
- |
-
- 1
- |
-
- sig129C
- |
-
-
- |
- 4
- |
-
- BN.Lx
- |
-
- F
- |
-
- 1
- |
-
- sig131N
- |
-
-
- |
- 5
- |
-
- HXB18
- |
-
- F
- |
-
- 1
- |
-
- sig126
- |
-
-
- |
- 6
- |
-
- HXB18
- |
-
- M
- |
-
- 1
- |
-
- sig127N
- |
-
-
- |
- 7
- |
-
- BXH3
- |
-
- M
- |
-
- 1
- |
-
- sig131C
- |
-
-
- |
- 8
- |
-
- BXH3
- |
-
- F
- |
-
- 1
- |
-
- sig132N
- |
-
-
- |
- 9
- |
-
- BXH12
- |
-
- M
- |
-
- 1
- |
-
- sig132C
- |
-
-
- |
- 10
- |
-
- BXH12
- |
-
- F
- |
-
- 1
- |
-
- sig133N
- |
-
-
- |
- 11
- |
-
- BXH13
- |
-
- M
- |
-
- 1
- |
-
- sig133C
- |
-
-
- |
- 12
- |
-
- BXH13
- |
-
- F
- |
-
- 1
- |
-
- sig134N
- |
-
-
- |
- 13
- |
-
- BXH6
- |
-
- M
- |
-
- 2
- |
-
- sig127N
- |
-
-
- |
- 14
- |
-
- BXH6
- |
-
- F
- |
-
- 2
- |
-
- sig127C
- |
-
-
- |
- 15
- |
-
- BXH8
- |
-
- M
- |
-
- 2
- |
-
- sig128N
- |
-
-
- |
- 16
- |
-
- BXH8
- |
-
- F
- |
-
- 2
- |
-
- sig128C
- |
-
-
- |
- 17
- |
-
- HXB1
- |
-
- M
- |
-
- 2
- |
-
- sig129N
- |
-
-
- |
- 18
- |
-
- HXB1
- |
-
- F
- |
-
- 2
- |
-
- sig129C
- |
-
-
- |
- 19
- |
-
- HXB10
- |
-
- M
- |
-
- 2
- |
-
- sig130N
- |
-
-
- |
- 20
- |
-
- HXB10
- |
-
- F
- |
-
- 2
- |
-
- sig130C
- |
-
-
- |
- 21
- |
-
- HXB13
- |
-
- M
- |
-
- 2
- |
-
- sig131N
- |
-
-
- |
- 22
- |
-
- HXB13
- |
-
- F
- |
-
- 2
- |
-
- sig131C
- |
-
-
- |
- 23
- |
-
- HXB15
- |
-
- M
- |
-
- 2
- |
-
- sig132N
- |
-
-
- |
- 24
- |
-
- HXB15
- |
-
- F
- |
-
- 2
- |
-
- sig132C
- |
-
-
- |
- 25
- |
-
- HXB17
- |
-
- M
- |
-
- 2
- |
-
- sig133N
- |
-
-
- |
- 26
- |
-
- HXB17
- |
-
- F
- |
-
- 2
- |
-
- sig133C
- |
-
-
- |
- 27
- |
-
- HXB4
- |
-
- M
- |
-
- 2
- |
-
- sig134N
- |
-
-
- |
- 28
- |
-
- HXB4
- |
-
- F
- |
-
- 3
- |
-
- sig127N
- |
-
-
- |
- 29
- |
-
- HXB2
- |
-
- M
- |
-
- 3
- |
-
- sig127C
- |
-
-
- |
- 30
- |
-
- HXB2
- |
-
- F
- |
-
- 3
- |
-
- sig128N
- |
-
-
- |
- 31
- |
-
- HXB20
- |
-
- M
- |
-
- 3
- |
-
- sig128C
- |
-
-
- |
- 32
- |
-
- HXB20
- |
-
- F
- |
-
- 3
- |
-
- sig129N
- |
-
-
- |
- 33
- |
-
- HXB22
- |
-
- M
- |
-
- 3
- |
-
- sig129C
- |
-
-
- |
- 34
- |
-
- HXB22
- |
-
- F
- |
-
- 3
- |
-
- sig130N
- |
-
-
- |
- 35
- |
-
- HXB29
- |
-
- M
- |
-
- 3
- |
-
- sig130C
- |
-
-
- |
- 36
- |
-
- HXB29
- |
-
- F
- |
-
- 3
- |
-
- sig131N
- |
-
-
- |
- 37
- |
-
- HXB3
- |
-
- M
- |
-
- 3
- |
-
- sig131C
- |
-
-
- |
- 38
- |
-
- HXB3
- |
-
- F
- |
-
- 3
- |
-
- sig132N
- |
-
-
- |
- 39
- |
-
- HXB31
- |
-
- M
- |
-
- 3
- |
-
- sig132C
- |
-
-
- |
- 40
- |
-
- HXB31
- |
-
- F
- |
-
- 3
- |
-
- sig133N
- |
-
-
- |
- 41
- |
-
- HXB7
- |
-
- M
- |
-
- 3
- |
-
- sig133C
- |
-
-
- |
- 42
- |
-
- HXB7
- |
-
- F
- |
-
- 3
- |
-
- sig134N
- |
-
-
- |
- 43
- |
-
- BXH5
- |
-
- F
- |
-
- 4
- |
-
- sig126
- |
-
-
- |
- 44
- |
-
- BXH5
- |
-
- M
- |
-
- 4
- |
-
- sig127N
- |
-
-
- |
- 45
- |
-
- BXH9
- |
-
- F
- |
-
- 4
- |
-
- sig127C
- |
-
-
- |
- 46
- |
-
- BXH9
- |
-
- M
- |
-
- 4
- |
-
- sig128N
- |
-
-
- |
- 47
- |
-
- BXH10
- |
-
- F
- |
-
- 4
- |
-
- sig128C
- |
-
-
- |
- 48
- |
-
- BXH10
- |
-
- M
- |
-
- 4
- |
-
- sig129N
- |
-
-
- |
- 49
- |
-
- BXH11
- |
-
- F
- |
-
- 4
- |
-
- sig129C
- |
-
-
- |
- 50
- |
-
- BXH11
- |
-
- M
- |
-
- 4
- |
-
- sig130N
- |
-
-
- |
- 51
- |
-
- HXB5
- |
-
- F
- |
-
- 4
- |
-
- sig130C
- |
-
-
- |
- 52
- |
-
- HXB5
- |
-
- M
- |
-
- 4
- |
-
- sig131N
- |
-
-
- |
- 53
- |
-
- HXB21
- |
-
- F
- |
-
- 5
- |
-
- sig126
- |
-
-
- |
- 54
- |
-
- HXB21
- |
-
- M
- |
-
- 5
- |
-
- sig127N
- |
-
-
- |
- 55
- |
-
- HXB23
- |
-
- F
- |
-
- 5
- |
-
- sig127C
- |
-
-
- |
- 56
- |
-
- HXB23
- |
-
- M
- |
-
- 5
- |
-
- sig128N
- |
-
-
- |
- 57
- |
-
- HXB24
- |
-
- F
- |
-
- 5
- |
-
- sig128C
- |
-
-
- |
- 58
- |
-
- HXB24
- |
-
- M
- |
-
- 5
- |
-
- sig129N
- |
-
-
- |
- 59
- |
-
- HXB25
- |
-
- F
- |
-
- 5
- |
-
- sig129C
- |
-
-
- |
- 60
- |
-
- HXB25
- |
-
- M
- |
-
- 5
- |
-
- sig130N
- |
-
-
- |
- 61
- |
-
- HXB27
- |
-
- F
- |
-
- 5
- |
-
- sig130C
- |
-
-
- |
- 62
- |
-
- HXB27
- |
-
- M
- |
-
- 5
- |
-
- sig131N
- |
-
-
-
diff --git a/general/datasets/UND_NIDA_HXB_BXH_IndBPep_log2z8_0321/processing.rtf b/general/datasets/UND_NIDA_HXB_BXH_IndBPep_log2z8_0321/processing.rtf
deleted file mode 100644
index c05f172..0000000
--- a/general/datasets/UND_NIDA_HXB_BXH_IndBPep_log2z8_0321/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-Sample processing protocol: The proteomic data were generated with 3 batches of 16-plex and 2 batches of 11-plex TMT experiments. The rat brain samples from 31 HXB/BXH strains with replicates (i.e., male and female) were lysed, digested, and labeled with either 11 or 16 different TMT tags. The TMT-labeled peptides were pooled with an equal amount of each and fractionated into 42 fractions in a concatenated fashion on an RP-HPLC column (4.6 mm x 250 mm) under basic pH conditions. each fraction was run sequentially on a column (75 μm x 20 cm for the whole proteome, 50 μm x ∼30 cm for phosphoproteome, 1.9 μm C18 resin from Dr. Maisch GmbH, 65°C to reduce backpressure) interfaced with a Q Exactive HF Orbitrap or Fusion MS (Thermo Fisher). Peptides were eluted by a 2-3 hr gradient (buffer A: 0.2% formic acid, 5% DMSO; buffer B: buffer A plus 65% acetonitrile). MS settings included the MS1 scan (410-1600 m/z, 60,000 or 120,000 resolution, 1 × 106 AGC and 50 ms maximal ion time) and 20 data-dependent MS2 scans (fixed first mass of 120 m/z, 60,000 resolution, 1 × 105 AGC, 100-150 ms maximal ion time, HCD, 35%–38% normalized collision energy, ∼1.0 m/z isolation window).
-
-Data processing protocol: The MS/MS raw files are processed using the JUMP searching engine against the UniProt mouse database. Searches were performed using 8 ppm mass tolerance for precursor ions due to JUMP’s auto mass correction function and 15 ppm for fragment ions, allowing up to two missed trypsin cleavage sites. TMT tags on lysine residues and peptide N termini (+229.162932 Da) were used for static modifications and the dynamic modifications include oxidation of methionine residues (+15.99492 Da). The assigned peptides are filtered by minimal peptide length, maximum miscleavages, mass-to-charge accuracy and matching scores. The peptides are then divided into groups according to peptide length, trypticity, modification, miscleavage, and charge and then further filtered by matching scores to reduce protein or phosphopeptide FDR to below 1%. Proteins or phosphopeptides were quantified by summing reporter ion counts across all matched PSMs using our in-house software.
-
-Protein quantification: We first extracted the TMT reporter ion intensities of each PSM and corrected the raw intensities based on the isotopic distribution of each labeling reagent. We discarded PSMs with low intensities (i.e., the minimum intensity of 1,000 and the median intensity of 5,000). After normalizing abundance with the trimmed median intensity of all PSMs, we calculated the mean-centered intensities across samples (e.g., relative intensities between each sample and the mean) and summarized protein relative intensities by averaging related PSMs. Finally, we derived protein absolute intensities by multiplying the relative intensities by the grand mean of the three most highly abundant PSMs. We first used the internal standard to normalize 3 batches of 16-plex experiments and 2 batches of 11-plex experiments. We then used the LIMMA batch removal function to normalize all five batches of TMT experiments.
diff --git a/general/datasets/UND_NIDA_HXB_BXH_IndBPep_log2z8_0321/specifics.rtf b/general/datasets/UND_NIDA_HXB_BXH_IndBPep_log2z8_0321/specifics.rtf
deleted file mode 100644
index f255583..0000000
--- a/general/datasets/UND_NIDA_HXB_BXH_IndBPep_log2z8_0321/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-UND NIDA Brain Proteome Individual (peptide-level) log2z+8 (Mar21)
\ No newline at end of file
diff --git a/general/datasets/UND_NIDA_HXB_BXH_IndBPep_log2z8_0321/summary.rtf b/general/datasets/UND_NIDA_HXB_BXH_IndBPep_log2z8_0321/summary.rtf
deleted file mode 100644
index 94c8e6e..0000000
--- a/general/datasets/UND_NIDA_HXB_BXH_IndBPep_log2z8_0321/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Brain proteome data. Deep proteome data were generated using whole brain tissue from both parents and 29 members of the HXB family, one male and one female per strain. Proteins in these samples were identified and quantified using the tandem-mass-tag (TMT) labeling strategy coupled with two-dimensional liquid chromatography-tandem mass spectrometry (LC/LC-MS/MS).
-
-This rat whole brain proteome data provide protein expression of 31 HXB/BXH strains, including 29 RI strains, and two parental strains, SHR/OlaIpcv and BN-Lx/Cub. A total of 8,124 proteins were quantified across all 31 strains.
diff --git a/general/datasets/UTHSCWGU88BFMG1013/summary.rtf b/general/datasets/UTHSCWGU88BFMG1013/summary.rtf
deleted file mode 100644
index 5798608..0000000
--- a/general/datasets/UTHSCWGU88BFMG1013/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This group of datasets is confidential. Please refer to the contact information above.
diff --git a/general/datasets/UTHSC_B6D2RI_H_0912/summary.rtf b/general/datasets/UTHSC_B6D2RI_H_0912/summary.rtf
deleted file mode 100644
index a0fc73e..0000000
--- a/general/datasets/UTHSC_B6D2RI_H_0912/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 155, Name: UTHSC B6D2RI Aged Hippocampus Affy Mouse Gene 1.0 ST (Sep12)
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXDAgedEx_1116/cases.rtf b/general/datasets/UTHSC_BXDAgedEx_1116/cases.rtf
deleted file mode 100644
index fba3fbb..0000000
--- a/general/datasets/UTHSC_BXDAgedEx_1116/cases.rtf
+++ /dev/null
@@ -1,1894 +0,0 @@
-
-
-
-
-
-
-
-
- | Index |
- Sample |
- Strain |
- Sex |
- Age |
- Batch |
-
-
- | 1 |
- R7264H |
- C57BL/6J_1 |
- M |
- 489 |
- 1 |
-
-
- | 2 |
- 052008.03 |
- C57BL/6J_2 |
- F |
- 650 |
- 2 |
-
-
- | 3 |
- R7289H |
- C57BL/6J_3 |
- M |
- 756 |
- 1 |
-
-
- | 4 |
- 052008.01 |
- C57BL/6J_4 |
- M |
- 756 |
- 2 |
-
-
- | 5 |
- R7269H |
- DBA/2J_1 |
- M |
- 367 |
- 1 |
-
-
- | 6 |
- R7185H |
- DBA/2J_2 |
- F |
- 433 |
- 1 |
-
-
- | 7 |
- R7301H |
- DBA/2J_3 |
- F |
- 566 |
- 1 |
-
-
- | 8 |
- R7265H |
- D2B6F1_1 |
- M |
- 492 |
- 1 |
-
-
- | 9 |
- R7304H |
- D2B6F1_2 |
- F |
- 495 |
- 1 |
-
-
- | 10 |
- R7276H |
- BXD1_1 |
- M |
- 323 |
- 1 |
-
-
- | 11 |
- R7281H |
- BXD1_2 |
- F |
- 448 |
- 1 |
-
-
- | 12 |
- 051209.20 |
- BXD1_3 |
- F |
- 477 |
- 2 |
-
-
- | 13 |
- R7261H |
- BXD2_1 |
- M |
- 394 |
- 1 |
-
-
- | 14 |
- R7256H |
- BXD2_2 |
- F |
- 456 |
- 1 |
-
-
- | 15 |
- 022807.04 |
- BXD2_3 |
- M |
- 483 |
- 2 |
-
-
- | 16 |
- 042909.46 |
- BXD2_4 |
- M |
- 609 |
- 2 |
-
-
- | 17 |
- 042909.47 |
- BXD2_5 |
- F |
- 609 |
- 2 |
-
-
- | 18 |
- R7223H |
- BXD6_1 |
- M |
- 526 |
- 1 |
-
-
- | 19 |
- R7198H |
- BXD8_1 |
- F |
- 433 |
- 1 |
-
-
- | 20 |
- R7200H |
- BXD8_2 |
- F |
- 460 |
- 1 |
-
-
- | 21 |
- R7203H |
- BXD8_3 |
- M |
- 471 |
- 1 |
-
-
- | 22 |
- R7294H |
- BXD9_1 |
- F |
- 456 |
- 1 |
-
-
- | 23 |
- 052008.17 |
- BXD9_2 |
- M |
- 631 |
- 2 |
-
-
- | 24 |
- 052008.18 |
- BXD9_3 |
- M |
- 631 |
- 2 |
-
-
- | 25 |
- R7300H |
- BXD11_1 |
- M |
- 457 |
- 1 |
-
-
- | 26 |
- R7227H |
- BXD11_2 |
- F |
- 536 |
- 1 |
-
-
- | 27 |
- 021113.01 |
- BXD11_3 |
- F |
- 741 |
- 2 |
-
-
- | 28 |
- 021113.02 |
- BXD11_4 |
- F |
- 741 |
- 2 |
-
-
- | 29 |
- R7183H |
- BXD12_1 |
- F |
- 506 |
- 1 |
-
-
- | 30 |
- R7233H |
- BXD12_2 |
- F |
- 561 |
- 1 |
-
-
- | 31 |
- R7234H |
- BXD12_3 |
- M |
- 606 |
- 1 |
-
-
- | 32 |
- 020409.01 |
- BXD12_4 |
- F |
- 850 |
- 2 |
-
-
- | 33 |
- 020409.03 |
- BXD12_5 |
- M |
- 850 |
- 2 |
-
-
- | 34 |
- R7238H |
- BXD14_1 |
- F |
- 605 |
- 1 |
-
-
- | 35 |
- R7235H |
- BXD14_2 |
- M |
- 605 |
- 1 |
-
-
- | 36 |
- 022807.11 |
- BXD16_1 |
- F |
- 455 |
- 2 |
-
-
- | 37 |
- R7239H |
- BXD16_2 |
- M |
- 475 |
- 1 |
-
-
- | 38 |
- R7236H |
- BXD16_3 |
- F |
- 561 |
- 1 |
-
-
- | 39 |
- R7229H |
- BXD18_1 |
- F |
- 493 |
- 1 |
-
-
- | 40 |
- 020409.28 |
- BXD18_2 |
- F |
- 548 |
- 2 |
-
-
- | 41 |
- R7268H |
- BXD19_1 |
- M |
- 492 |
- 1 |
-
-
- | 42 |
- R7267H |
- BXD19_2 |
- F |
- 551 |
- 1 |
-
-
- | 43 |
- R7263H |
- BXD20_1 |
- M |
- 489 |
- 1 |
-
-
- | 44 |
- R7232H |
- BXD20_2 |
- M |
- 506 |
- 1 |
-
-
- | 45 |
- R7230H |
- BXD21_1 |
- F |
- 537 |
- 1 |
-
-
- | 46 |
- R7260H |
- BXD22_1 |
- F |
- 502 |
- 1 |
-
-
- | 47 |
- R7262H |
- BXD22_2 |
- M |
- 596 |
- 1 |
-
-
- | 48 |
- 020409.08 |
- BXD22_3 |
- F |
- 675 |
- 2 |
-
-
- | 49 |
- R7257H |
- BXD23_1 |
- M |
- 462 |
- 1 |
-
-
- | 50 |
- R7258H |
- BXD23_2 |
- F |
- 502 |
- 1 |
-
-
- | 51 |
- 020107.15 |
- BXD23_3 |
- M |
- 512 |
- 2 |
-
-
- | 52 |
- R7228H |
- BXD24_1 |
- F |
- 415 |
- 1 |
-
-
- | 53 |
- R7255H |
- BXD24_2 |
- F |
- 456 |
- 1 |
-
-
- | 54 |
- R7231H |
- BXD24_3 |
- M |
- 470 |
- 1 |
-
-
- | 55 |
- 020409.21 |
- BXD24_4 |
- F |
- 636 |
- 2 |
-
-
- | 56 |
- 020409.29 |
- BXD24_5 |
- F |
- 639 |
- 2 |
-
-
- | 57 |
- 052008.36 |
- BXD25_1 |
- F |
- 430 |
- 2 |
-
-
- | 58 |
- R7252H |
- BXD25_2 |
- F |
- 454 |
- 1 |
-
-
- | 59 |
- 052008.115 |
- BXD25_3 |
- M |
- 709 |
- 2 |
-
-
- | 60 |
- R7286H |
- BXD27_1 |
- F |
- 472 |
- 1 |
-
-
- | 61 |
- R7170H |
- BXD27_2 |
- F |
- 472 |
- 1 |
-
-
- | 62 |
- R7254H |
- BXD28_1 |
- M |
- 493 |
- 1 |
-
-
- | 63 |
- R7251H |
- BXD28_2 |
- F |
- 543 |
- 1 |
-
-
- | 64 |
- 020107.18 |
- BXD28_3 |
- M |
- 605 |
- 2 |
-
-
- | 65 |
- R7259H |
- BXD29_1 |
- F |
- 483 |
- 1 |
-
-
- | 66 |
- 040109.92 |
- BXD31_1 |
- F |
- 445 |
- 2 |
-
-
- | 67 |
- 031407.18 |
- BXD31_2 |
- F |
- 467 |
- 2 |
-
-
- | 68 |
- 020409.31 |
- BXD31_3 |
- F |
- 648 |
- 2 |
-
-
- | 69 |
- 042909.71 |
- BXD32_1 |
- M |
- 566 |
- 2 |
-
-
- | 70 |
- R7244H |
- BXD33_1 |
- F |
- 448 |
- 1 |
-
-
- | 71 |
- R7253H |
- BXD33_2 |
- M |
- 464 |
- 1 |
-
-
- | 72 |
- R7174H |
- BXD33_3 |
- F |
- 471 |
- 1 |
-
-
- | 73 |
- R7270H |
- BXD33_4 |
- M |
- 662 |
- 1 |
-
-
- | 74 |
- 040109.79 |
- BXD33_5 |
- F |
- 683 |
- 2 |
-
-
- | 75 |
- 050609.35 |
- BXD34_1 |
- F |
- 414 |
- 2 |
-
-
- | 76 |
- 052008.51 |
- BXD34_2 |
- F |
- 549 |
- 2 |
-
-
- | 77 |
- 101513.06 |
- BXD34_3 |
- F |
- 554 |
- 2 |
-
-
- | 78 |
- 101513.07 |
- BXD34_4 |
- F |
- 748 |
- 2 |
-
-
- | 79 |
- R7247H |
- BXD38_1 |
- M |
- 446 |
- 1 |
-
-
- | 80 |
- R7242H |
- BXD38_3 |
- F |
- 464 |
- 1 |
-
-
- | 81 |
- 020107.25 |
- BXD38_4 |
- M |
- 530 |
- 2 |
-
-
- | 82 |
- R7173H |
- BXD39_1 |
- F |
- 500 |
- 1 |
-
-
- | 83 |
- R7175H |
- BXD39_2 |
- M |
- 500 |
- 1 |
-
-
- | 84 |
- R7250H |
- BXD39_3 |
- M |
- 536 |
- 1 |
-
-
- | 85 |
- 020409.19 |
- BXD39_4 |
- F |
- 661 |
- 2 |
-
-
- | 86 |
- R7288H |
- BXD40_1 |
- F |
- 451 |
- 1 |
-
-
- | 87 |
- 051209.56 |
- BXD40_2 |
- F |
- 451 |
- 2 |
-
-
- | 88 |
- R7210H |
- BXD40_3 |
- M |
- 470 |
- 1 |
-
-
- | 89 |
- R7197H |
- BXD40_4 |
- M |
- 614 |
- 1 |
-
-
- | 90 |
- 042909.19 |
- BXD40_5 |
- F |
- 633 |
- 2 |
-
-
- | 91 |
- 020409.73 |
- BXD40_6 |
- F |
- 728 |
- 2 |
-
-
- | 92 |
- R7246H |
- BXD42_1 |
- M |
- 446 |
- 1 |
-
-
- | 93 |
- R7266H |
- BXD42_2 |
- F |
- 486 |
- 1 |
-
-
- | 94 |
- R7280H |
- BXD42_3 |
- F |
- 518 |
- 1 |
-
-
- | 95 |
- R7249H |
- BXD43_1 |
- F |
- 454 |
- 1 |
-
-
- | 96 |
- R7248H |
- BXD43_2 |
- M |
- 462 |
- 1 |
-
-
- | 97 |
- 050609.76 |
- BXD43_3 |
- M |
- 616 |
- 2 |
-
-
- | 98 |
- R7241H |
- BXD44_1 |
- M |
- 415 |
- 1 |
-
-
- | 99 |
- R7279H |
- BXD44_2 |
- M |
- 419 |
- 1 |
-
-
- | 100 |
- R7243H |
- BXD44_3 |
- F |
- 438 |
- 1 |
-
-
- | 101 |
- 042607.13 |
- BXD44_4 |
- F |
- 564 |
- 2 |
-
-
- | 102 |
- 042607.14 |
- BXD44_5 |
- F |
- 564 |
- 2 |
-
-
- | 103 |
- R7176H |
- BXD45_1 |
- F |
- 451 |
- 1 |
-
-
- | 104 |
- 040109.88 |
- BXD45_2 |
- M |
- 631 |
- 2 |
-
-
- | 105 |
- R7245H |
- BXD48_1 |
- F |
- 499 |
- 1 |
-
-
- | 106 |
- R7220H |
- BXD48_2 |
- M |
- 526 |
- 1 |
-
-
- | 107 |
- 051209.29 |
- BXD48_3 |
- M |
- 740 |
- 2 |
-
-
- | 108 |
- 101513.10 |
- BXD48_4 |
- F |
- 740 |
- 2 |
-
-
- | 109 |
- R7299H |
- BXD48a_1 |
- F |
- 479 |
- 1 |
-
-
- | 110 |
- R7297H |
- BXD48a_2 |
- M |
- 479 |
- 1 |
-
-
- | 111 |
- 051209.01 |
- BXD48a_3 |
- F |
- 479 |
- 2 |
-
-
- | 112 |
- 051209.03 |
- BXD48a_4 |
- M |
- 479 |
- 2 |
-
-
- | 113 |
- 051209.52 |
- BXD48a_5 |
- F |
- 608 |
- 2 |
-
-
- | 114 |
- 051209.65 |
- BXD48a_6 |
- M |
- 748 |
- 2 |
-
-
- | 115 |
- R7224H |
- BXD50_1 |
- F |
- 530 |
- 1 |
-
-
- | 116 |
- R7221H |
- BXD50_2 |
- M |
- 530 |
- 1 |
-
-
- | 117 |
- 050609.04 |
- BXD50_3 |
- F |
- 778 |
- 2 |
-
-
- | 118 |
- R7177H |
- BXD51_1 |
- F |
- 487 |
- 1 |
-
-
- | 119 |
- R7290H |
- BXD51_2 |
- M |
- 407 |
- 1 |
-
-
- | 120 |
- 041709.11 |
- BXD51_3 |
- M |
- 621 |
- 2 |
-
-
- | 121 |
- R7222H |
- BXD55_1 |
- M |
- 528 |
- 1 |
-
-
- | 122 |
- R7225H |
- BXD55_2 |
- F |
- 587 |
- 1 |
-
-
- | 123 |
- 052008.134 |
- BXD55_3 |
- F |
- 778 |
- 2 |
-
-
- | 124 |
- 052008.135 |
- BXD55_4 |
- F |
- 766 |
- 2 |
-
-
- | 125 |
- R7178H |
- BXD56_1 |
- M |
- 501 |
- 1 |
-
-
- | 126 |
- 051209.66 |
- BXD56_2 |
- M |
- 694 |
- 2 |
-
-
- | 127 |
- 052008.139 |
- BXD56_3 |
- F |
- 734 |
- 2 |
-
-
- | 128 |
- 042909.52 |
- BXD60_1 |
- M |
- 457 |
- 2 |
-
-
- | 129 |
- 101513.14 |
- BXD60_2 |
- F |
- 759 |
- 2 |
-
-
- | 130 |
- 052008.63 |
- BXD61_1 |
- M |
- 650 |
- 2 |
-
-
- | 131 |
- 020409.14 |
- BXD61_2 |
- F |
- 702 |
- 2 |
-
-
- | 132 |
- 121214.20 |
- BXD62_1 |
- F |
- 353 |
- 2 |
-
-
- | 133 |
- R7291H |
- BXD62_2 |
- M |
- 439 |
- 1 |
-
-
- | 134 |
- 040109.91 |
- BXD62_3 |
- F |
- 699 |
- 2 |
-
-
- | 135 |
- R7218H |
- BXD63_1 |
- M |
- 438 |
- 1 |
-
-
- | 136 |
- R7215H |
- BXD63_2 |
- F |
- 475 |
- 1 |
-
-
- | 137 |
- 050609.28 |
- BXD63_3 |
- M |
- 972 |
- 2 |
-
-
- | 138 |
- R7219H |
- BXD64_1 |
- M |
- 528 |
- 1 |
-
-
- | 139 |
- R7216H |
- BXD64_2 |
- F |
- 587 |
- 1 |
-
-
- | 140 |
- R7217H |
- BXD65_1 |
- F |
- 425 |
- 1 |
-
-
- | 141 |
- 050609.39 |
- BXD65_2 |
- M |
- 601 |
- 2 |
-
-
- | 142 |
- 052008.67 |
- BXD65_3 |
- F |
- 808 |
- 2 |
-
-
- | 143 |
- R7273H |
- BXD65a_1 |
- F |
- 389 |
- 1 |
-
-
- | 144 |
- R7277H |
- BXD65a_2 |
- M |
- 715 |
- 1 |
-
-
- | 145 |
- 061407.15 |
- BXD65a_3 |
- F |
- 536 |
- 2 |
-
-
- | 146 |
- 061407.16 |
- BXD65a_4 |
- F |
- 536 |
- 2 |
-
-
- | 147 |
- R7271H |
- BXD65b_1 |
- M |
- 483 |
- 1 |
-
-
- | 148 |
- R7302H |
- BXD66_1 |
- F |
- 446 |
- 1 |
-
-
- | 149 |
- R7214H |
- BXD66_2 |
- M |
- 463 |
- 1 |
-
-
- | 150 |
- 042507.19 |
- BXD66_3 |
- M |
- 557 |
- 2 |
-
-
- | 151 |
- 042507.20 |
- BXD66_4 |
- F |
- 557 |
- 2 |
-
-
- | 152 |
- R7278H |
- BXD67_1 |
- F |
- 415 |
- 1 |
-
-
- | 153 |
- R7213H |
- BXD67_2 |
- M |
- 425 |
- 1 |
-
-
- | 154 |
- R7240H |
- BXD67_3 |
- F |
- 499 |
- 1 |
-
-
- | 155 |
- 042607.11 |
- BXD67_4 |
- F |
- 606 |
- 2 |
-
-
- | 156 |
- 052008.71 |
- BXD67_5 |
- F |
- 649 |
- 2 |
-
-
- | 157 |
- R7211H |
- BXD68_1 |
- F |
- 415 |
- 1 |
-
-
- | 158 |
- R7212H |
- BXD68_2 |
- M |
- 421 |
- 1 |
-
-
- | 159 |
- 042607.27 |
- BXD68_3 |
- F |
- 623 |
- 2 |
-
-
- | 160 |
- 042607.28 |
- BXD68_4 |
- F |
- 623 |
- 2 |
-
-
- | 161 |
- R7305H |
- BXD69_1 |
- F |
- 504 |
- 1 |
-
-
- | 162 |
- 061913.13 |
- BXD69_2 |
- F |
- 558 |
- 2 |
-
-
- | 163 |
- 112707.08 |
- BXD69_3 |
- F |
- 602 |
- 2 |
-
-
- | 164 |
- R7207H |
- BXD70_1 |
- F |
- 458 |
- 1 |
-
-
- | 165 |
- R7204H |
- BXD70_2 |
- M |
- 460 |
- 1 |
-
-
- | 166 |
- 042909.28 |
- BXD70_3 |
- F |
- 761 |
- 2 |
-
-
- | 167 |
- 042909.29 |
- BXD70_4 |
- F |
- 761 |
- 2 |
-
-
- | 168 |
- R7205H |
- BXD71_1 |
- M |
- 471 |
- 1 |
-
-
- | 169 |
- R7208H |
- BXD71_2 |
- F |
- 474 |
- 1 |
-
-
- | 170 |
- 020409.11 |
- BXD71_3 |
- F |
- 701 |
- 2 |
-
-
- | 171 |
- 020409.49 |
- BXD71_4 |
- F |
- 582 |
- 2 |
-
-
- | 172 |
- R7209H |
- BXD73_1 |
- F |
- 470 |
- 1 |
-
-
- | 173 |
- R7206H |
- BXD73_2 |
- M |
- 464 |
- 1 |
-
-
- | 174 |
- 011007.16 |
- BXD73_3 |
- F |
- 544 |
- 2 |
-
-
- | 175 |
- 052008.81 |
- BXD73_4 |
- F |
- 642 |
- 2 |
-
-
- | 176 |
- R7181H |
- BXD73a_1 |
- F |
- 443 |
- 1 |
-
-
- | 177 |
- 061407.18 |
- BXD73a_2 |
- F |
- 443 |
- 2 |
-
-
- | 178 |
- R7182H |
- BXD73a_3 |
- M |
- 614 |
- 1 |
-
-
- | 179 |
- 052008.86 |
- BXD73a_4 |
- M |
- 710 |
- 2 |
-
-
- | 180 |
- 031407.10 |
- BXD74_1 |
- M |
- 804 |
- 2 |
-
-
- | 181 |
- 011107.08 |
- BXD75_1 |
- F |
- 535 |
- 2 |
-
-
- | 182 |
- R7188H |
- BXD76_1 |
- F |
- 408 |
- 1 |
-
-
- | 183 |
- R7187H |
- BXD76_2 |
- M |
- 564 |
- 1 |
-
-
- | 184 |
- R7179H |
- BXD76_3 |
- M |
- 579 |
- 1 |
-
-
- | 185 |
- R7292HR |
- BXD77_1 |
- M |
- 347 |
- 1 |
-
-
- | 186 |
- R7201H |
- BXD77_2 |
- F |
- 454 |
- 1 |
-
-
- | 187 |
- 052008.83 |
- BXD77_3 |
- F |
- 659 |
- 2 |
-
-
- | 188 |
- R7202H |
- BXD79_1 |
- M |
- 485 |
- 1 |
-
-
- | 189 |
- R7199H |
- BXD79_2 |
- F |
- 515 |
- 1 |
-
-
- | 190 |
- R7298H |
- BXD79_3 |
- M |
- 704 |
- 1 |
-
-
- | 191 |
- 050609.25 |
- BXD81_1 |
- F |
- 434 |
- 2 |
-
-
- | 192 |
- R7190H |
- BXD81_2 |
- F |
- 458 |
- 1 |
-
-
- | 193 |
- R7196H |
- BXD81_3 |
- M |
- 515 |
- 1 |
-
-
- | 194 |
- R7184H |
- BXD83_1 |
- M |
- 441 |
- 1 |
-
-
- | 195 |
- 061307.30 |
- BXD83_2 |
- F |
- 612 |
- 2 |
-
-
- | 196 |
- 121907.10 |
- BXD83_3 |
- M |
- 617 |
- 2 |
-
-
- | 197 |
- R7195H |
- BXD84_1 |
- M |
- 474 |
- 1 |
-
-
- | 198 |
- R7296H |
- BXD84_2 |
- M |
- 484 |
- 1 |
-
-
- | 199 |
- R7192H |
- BXD84_3 |
- F |
- 522 |
- 1 |
-
-
- | 200 |
- 020409.80 |
- BXD84_4 |
- F |
- 564 |
- 2 |
-
-
- | 201 |
- 112707.12 |
- BXD84_5 |
- F |
- 592 |
- 2 |
-
-
- | 202 |
- R7272H |
- BXD85_1 |
- M |
- 425 |
- 1 |
-
-
- | 203 |
- R7193H |
- BXD85_2 |
- F |
- 506 |
- 1 |
-
-
- | 204 |
- 020409.12 |
- BXD85_3 |
- F |
- 702 |
- 2 |
-
-
- | 205 |
- 020409.13 |
- BXD85_4 |
- F |
- 702 |
- 2 |
-
-
- | 206 |
- R7191H |
- BXD86_1 |
- M |
- 425 |
- 1 |
-
-
- | 207 |
- 020409.35 |
- BXD86_2 |
- F |
- 613 |
- 2 |
-
-
- | 208 |
- 020409.36 |
- BXD86_3 |
- F |
- 613 |
- 2 |
-
-
- | 209 |
- R7194H |
- BXD87_1 |
- F |
- 425 |
- 1 |
-
-
- | 210 |
- R7303HR |
- BXD87_2 |
- M |
- 478 |
- 1 |
-
-
- | 211 |
- R7186H |
- BXD87_3 |
- M |
- 442 |
- 1 |
-
-
- | 212 |
- 052008.97 |
- BXD87_4 |
- F |
- 666 |
- 2 |
-
-
- | 213 |
- 052008.98 |
- BXD87_5 |
- M |
- 666 |
- 2 |
-
-
- | 214 |
- R7295H |
- BXD89_1 |
- F |
- 446 |
- 1 |
-
-
- | 215 |
- 052008.100 |
- BXD89_2 |
- M |
- 616 |
- 2 |
-
-
- | 216 |
- R7287H |
- BXD90_1 |
- M |
- 434 |
- 1 |
-
-
- | 217 |
- R7293H |
- BXD90_2 |
- M |
- 558 |
- 1 |
-
-
- | 218 |
- 052008.105 |
- BXD90_3 |
- F |
- 452 |
- 2 |
-
-
- | 219 |
- R7180H |
- BXD95_1 |
- F |
- 467 |
- 1 |
-
-
- | 220 |
- R7169H |
- BXD95_2 |
- M |
- 467 |
- 1 |
-
-
- | 221 |
- 100914.09 |
- BXD95_3 |
- F |
- 536 |
- 2 |
-
-
- | 222 |
- R7237H |
- BXD98_1 |
- M |
- 605 |
- 1 |
-
-
- | 223 |
- R7171H |
- BXD98_2 |
- F |
- 639 |
- 1 |
-
-
- | 224 |
- R7275H |
- BXD98_3 |
- F |
- 488 |
- 1 |
-
-
- | 225 |
- R7189H |
- BXD99_1 |
- M |
- 524 |
- 1 |
-
-
- | 226 |
- R7172H |
- BXD99_2 |
- F |
- 471 |
- 1 |
-
-
- | 227 |
- R7282H |
- BXD100_1 |
- F |
- 463 |
- 1 |
-
-
- | 228 |
- R7283H |
- BXD100_2 |
- M |
- 507 |
- 1 |
-
-
- | 229 |
- R7274H |
- BXD100_3 |
- M |
- 577 |
- 1 |
-
-
- | 230 |
- R7226H |
- BXD100_4 |
- F |
- 464 |
- 1 |
-
-
- | 231 |
- 051209.62 |
- BXD100_5 |
- M |
- 577 |
- 2 |
-
-
- | 232 |
- R7284H |
- BXD101_1 |
- F |
- 490 |
- 1 |
-
-
- | 233 |
- R7285H |
- BXD101_2 |
- M |
- 408 |
- 1 |
-
-
- | 234 |
- 051112.10 |
- BXD101_3 |
- F |
- 223 |
- 2 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_BXDAgedEx_1116/specifics.rtf b/general/datasets/UTHSC_BXDAgedEx_1116/specifics.rtf
deleted file mode 100644
index 7c1a914..0000000
--- a/general/datasets/UTHSC_BXDAgedEx_1116/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Exon Level
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXDAgedEx_1116/summary.rtf b/general/datasets/UTHSC_BXDAgedEx_1116/summary.rtf
deleted file mode 100644
index 73a0125..0000000
--- a/general/datasets/UTHSC_BXDAgedEx_1116/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is now public.
diff --git a/general/datasets/UTHSC_BXDAged_0615/cases.rtf b/general/datasets/UTHSC_BXDAged_0615/cases.rtf
deleted file mode 100644
index fba3fbb..0000000
--- a/general/datasets/UTHSC_BXDAged_0615/cases.rtf
+++ /dev/null
@@ -1,1894 +0,0 @@
-
-
-
-
-
-
-
-
- | Index |
- Sample |
- Strain |
- Sex |
- Age |
- Batch |
-
-
- | 1 |
- R7264H |
- C57BL/6J_1 |
- M |
- 489 |
- 1 |
-
-
- | 2 |
- 052008.03 |
- C57BL/6J_2 |
- F |
- 650 |
- 2 |
-
-
- | 3 |
- R7289H |
- C57BL/6J_3 |
- M |
- 756 |
- 1 |
-
-
- | 4 |
- 052008.01 |
- C57BL/6J_4 |
- M |
- 756 |
- 2 |
-
-
- | 5 |
- R7269H |
- DBA/2J_1 |
- M |
- 367 |
- 1 |
-
-
- | 6 |
- R7185H |
- DBA/2J_2 |
- F |
- 433 |
- 1 |
-
-
- | 7 |
- R7301H |
- DBA/2J_3 |
- F |
- 566 |
- 1 |
-
-
- | 8 |
- R7265H |
- D2B6F1_1 |
- M |
- 492 |
- 1 |
-
-
- | 9 |
- R7304H |
- D2B6F1_2 |
- F |
- 495 |
- 1 |
-
-
- | 10 |
- R7276H |
- BXD1_1 |
- M |
- 323 |
- 1 |
-
-
- | 11 |
- R7281H |
- BXD1_2 |
- F |
- 448 |
- 1 |
-
-
- | 12 |
- 051209.20 |
- BXD1_3 |
- F |
- 477 |
- 2 |
-
-
- | 13 |
- R7261H |
- BXD2_1 |
- M |
- 394 |
- 1 |
-
-
- | 14 |
- R7256H |
- BXD2_2 |
- F |
- 456 |
- 1 |
-
-
- | 15 |
- 022807.04 |
- BXD2_3 |
- M |
- 483 |
- 2 |
-
-
- | 16 |
- 042909.46 |
- BXD2_4 |
- M |
- 609 |
- 2 |
-
-
- | 17 |
- 042909.47 |
- BXD2_5 |
- F |
- 609 |
- 2 |
-
-
- | 18 |
- R7223H |
- BXD6_1 |
- M |
- 526 |
- 1 |
-
-
- | 19 |
- R7198H |
- BXD8_1 |
- F |
- 433 |
- 1 |
-
-
- | 20 |
- R7200H |
- BXD8_2 |
- F |
- 460 |
- 1 |
-
-
- | 21 |
- R7203H |
- BXD8_3 |
- M |
- 471 |
- 1 |
-
-
- | 22 |
- R7294H |
- BXD9_1 |
- F |
- 456 |
- 1 |
-
-
- | 23 |
- 052008.17 |
- BXD9_2 |
- M |
- 631 |
- 2 |
-
-
- | 24 |
- 052008.18 |
- BXD9_3 |
- M |
- 631 |
- 2 |
-
-
- | 25 |
- R7300H |
- BXD11_1 |
- M |
- 457 |
- 1 |
-
-
- | 26 |
- R7227H |
- BXD11_2 |
- F |
- 536 |
- 1 |
-
-
- | 27 |
- 021113.01 |
- BXD11_3 |
- F |
- 741 |
- 2 |
-
-
- | 28 |
- 021113.02 |
- BXD11_4 |
- F |
- 741 |
- 2 |
-
-
- | 29 |
- R7183H |
- BXD12_1 |
- F |
- 506 |
- 1 |
-
-
- | 30 |
- R7233H |
- BXD12_2 |
- F |
- 561 |
- 1 |
-
-
- | 31 |
- R7234H |
- BXD12_3 |
- M |
- 606 |
- 1 |
-
-
- | 32 |
- 020409.01 |
- BXD12_4 |
- F |
- 850 |
- 2 |
-
-
- | 33 |
- 020409.03 |
- BXD12_5 |
- M |
- 850 |
- 2 |
-
-
- | 34 |
- R7238H |
- BXD14_1 |
- F |
- 605 |
- 1 |
-
-
- | 35 |
- R7235H |
- BXD14_2 |
- M |
- 605 |
- 1 |
-
-
- | 36 |
- 022807.11 |
- BXD16_1 |
- F |
- 455 |
- 2 |
-
-
- | 37 |
- R7239H |
- BXD16_2 |
- M |
- 475 |
- 1 |
-
-
- | 38 |
- R7236H |
- BXD16_3 |
- F |
- 561 |
- 1 |
-
-
- | 39 |
- R7229H |
- BXD18_1 |
- F |
- 493 |
- 1 |
-
-
- | 40 |
- 020409.28 |
- BXD18_2 |
- F |
- 548 |
- 2 |
-
-
- | 41 |
- R7268H |
- BXD19_1 |
- M |
- 492 |
- 1 |
-
-
- | 42 |
- R7267H |
- BXD19_2 |
- F |
- 551 |
- 1 |
-
-
- | 43 |
- R7263H |
- BXD20_1 |
- M |
- 489 |
- 1 |
-
-
- | 44 |
- R7232H |
- BXD20_2 |
- M |
- 506 |
- 1 |
-
-
- | 45 |
- R7230H |
- BXD21_1 |
- F |
- 537 |
- 1 |
-
-
- | 46 |
- R7260H |
- BXD22_1 |
- F |
- 502 |
- 1 |
-
-
- | 47 |
- R7262H |
- BXD22_2 |
- M |
- 596 |
- 1 |
-
-
- | 48 |
- 020409.08 |
- BXD22_3 |
- F |
- 675 |
- 2 |
-
-
- | 49 |
- R7257H |
- BXD23_1 |
- M |
- 462 |
- 1 |
-
-
- | 50 |
- R7258H |
- BXD23_2 |
- F |
- 502 |
- 1 |
-
-
- | 51 |
- 020107.15 |
- BXD23_3 |
- M |
- 512 |
- 2 |
-
-
- | 52 |
- R7228H |
- BXD24_1 |
- F |
- 415 |
- 1 |
-
-
- | 53 |
- R7255H |
- BXD24_2 |
- F |
- 456 |
- 1 |
-
-
- | 54 |
- R7231H |
- BXD24_3 |
- M |
- 470 |
- 1 |
-
-
- | 55 |
- 020409.21 |
- BXD24_4 |
- F |
- 636 |
- 2 |
-
-
- | 56 |
- 020409.29 |
- BXD24_5 |
- F |
- 639 |
- 2 |
-
-
- | 57 |
- 052008.36 |
- BXD25_1 |
- F |
- 430 |
- 2 |
-
-
- | 58 |
- R7252H |
- BXD25_2 |
- F |
- 454 |
- 1 |
-
-
- | 59 |
- 052008.115 |
- BXD25_3 |
- M |
- 709 |
- 2 |
-
-
- | 60 |
- R7286H |
- BXD27_1 |
- F |
- 472 |
- 1 |
-
-
- | 61 |
- R7170H |
- BXD27_2 |
- F |
- 472 |
- 1 |
-
-
- | 62 |
- R7254H |
- BXD28_1 |
- M |
- 493 |
- 1 |
-
-
- | 63 |
- R7251H |
- BXD28_2 |
- F |
- 543 |
- 1 |
-
-
- | 64 |
- 020107.18 |
- BXD28_3 |
- M |
- 605 |
- 2 |
-
-
- | 65 |
- R7259H |
- BXD29_1 |
- F |
- 483 |
- 1 |
-
-
- | 66 |
- 040109.92 |
- BXD31_1 |
- F |
- 445 |
- 2 |
-
-
- | 67 |
- 031407.18 |
- BXD31_2 |
- F |
- 467 |
- 2 |
-
-
- | 68 |
- 020409.31 |
- BXD31_3 |
- F |
- 648 |
- 2 |
-
-
- | 69 |
- 042909.71 |
- BXD32_1 |
- M |
- 566 |
- 2 |
-
-
- | 70 |
- R7244H |
- BXD33_1 |
- F |
- 448 |
- 1 |
-
-
- | 71 |
- R7253H |
- BXD33_2 |
- M |
- 464 |
- 1 |
-
-
- | 72 |
- R7174H |
- BXD33_3 |
- F |
- 471 |
- 1 |
-
-
- | 73 |
- R7270H |
- BXD33_4 |
- M |
- 662 |
- 1 |
-
-
- | 74 |
- 040109.79 |
- BXD33_5 |
- F |
- 683 |
- 2 |
-
-
- | 75 |
- 050609.35 |
- BXD34_1 |
- F |
- 414 |
- 2 |
-
-
- | 76 |
- 052008.51 |
- BXD34_2 |
- F |
- 549 |
- 2 |
-
-
- | 77 |
- 101513.06 |
- BXD34_3 |
- F |
- 554 |
- 2 |
-
-
- | 78 |
- 101513.07 |
- BXD34_4 |
- F |
- 748 |
- 2 |
-
-
- | 79 |
- R7247H |
- BXD38_1 |
- M |
- 446 |
- 1 |
-
-
- | 80 |
- R7242H |
- BXD38_3 |
- F |
- 464 |
- 1 |
-
-
- | 81 |
- 020107.25 |
- BXD38_4 |
- M |
- 530 |
- 2 |
-
-
- | 82 |
- R7173H |
- BXD39_1 |
- F |
- 500 |
- 1 |
-
-
- | 83 |
- R7175H |
- BXD39_2 |
- M |
- 500 |
- 1 |
-
-
- | 84 |
- R7250H |
- BXD39_3 |
- M |
- 536 |
- 1 |
-
-
- | 85 |
- 020409.19 |
- BXD39_4 |
- F |
- 661 |
- 2 |
-
-
- | 86 |
- R7288H |
- BXD40_1 |
- F |
- 451 |
- 1 |
-
-
- | 87 |
- 051209.56 |
- BXD40_2 |
- F |
- 451 |
- 2 |
-
-
- | 88 |
- R7210H |
- BXD40_3 |
- M |
- 470 |
- 1 |
-
-
- | 89 |
- R7197H |
- BXD40_4 |
- M |
- 614 |
- 1 |
-
-
- | 90 |
- 042909.19 |
- BXD40_5 |
- F |
- 633 |
- 2 |
-
-
- | 91 |
- 020409.73 |
- BXD40_6 |
- F |
- 728 |
- 2 |
-
-
- | 92 |
- R7246H |
- BXD42_1 |
- M |
- 446 |
- 1 |
-
-
- | 93 |
- R7266H |
- BXD42_2 |
- F |
- 486 |
- 1 |
-
-
- | 94 |
- R7280H |
- BXD42_3 |
- F |
- 518 |
- 1 |
-
-
- | 95 |
- R7249H |
- BXD43_1 |
- F |
- 454 |
- 1 |
-
-
- | 96 |
- R7248H |
- BXD43_2 |
- M |
- 462 |
- 1 |
-
-
- | 97 |
- 050609.76 |
- BXD43_3 |
- M |
- 616 |
- 2 |
-
-
- | 98 |
- R7241H |
- BXD44_1 |
- M |
- 415 |
- 1 |
-
-
- | 99 |
- R7279H |
- BXD44_2 |
- M |
- 419 |
- 1 |
-
-
- | 100 |
- R7243H |
- BXD44_3 |
- F |
- 438 |
- 1 |
-
-
- | 101 |
- 042607.13 |
- BXD44_4 |
- F |
- 564 |
- 2 |
-
-
- | 102 |
- 042607.14 |
- BXD44_5 |
- F |
- 564 |
- 2 |
-
-
- | 103 |
- R7176H |
- BXD45_1 |
- F |
- 451 |
- 1 |
-
-
- | 104 |
- 040109.88 |
- BXD45_2 |
- M |
- 631 |
- 2 |
-
-
- | 105 |
- R7245H |
- BXD48_1 |
- F |
- 499 |
- 1 |
-
-
- | 106 |
- R7220H |
- BXD48_2 |
- M |
- 526 |
- 1 |
-
-
- | 107 |
- 051209.29 |
- BXD48_3 |
- M |
- 740 |
- 2 |
-
-
- | 108 |
- 101513.10 |
- BXD48_4 |
- F |
- 740 |
- 2 |
-
-
- | 109 |
- R7299H |
- BXD48a_1 |
- F |
- 479 |
- 1 |
-
-
- | 110 |
- R7297H |
- BXD48a_2 |
- M |
- 479 |
- 1 |
-
-
- | 111 |
- 051209.01 |
- BXD48a_3 |
- F |
- 479 |
- 2 |
-
-
- | 112 |
- 051209.03 |
- BXD48a_4 |
- M |
- 479 |
- 2 |
-
-
- | 113 |
- 051209.52 |
- BXD48a_5 |
- F |
- 608 |
- 2 |
-
-
- | 114 |
- 051209.65 |
- BXD48a_6 |
- M |
- 748 |
- 2 |
-
-
- | 115 |
- R7224H |
- BXD50_1 |
- F |
- 530 |
- 1 |
-
-
- | 116 |
- R7221H |
- BXD50_2 |
- M |
- 530 |
- 1 |
-
-
- | 117 |
- 050609.04 |
- BXD50_3 |
- F |
- 778 |
- 2 |
-
-
- | 118 |
- R7177H |
- BXD51_1 |
- F |
- 487 |
- 1 |
-
-
- | 119 |
- R7290H |
- BXD51_2 |
- M |
- 407 |
- 1 |
-
-
- | 120 |
- 041709.11 |
- BXD51_3 |
- M |
- 621 |
- 2 |
-
-
- | 121 |
- R7222H |
- BXD55_1 |
- M |
- 528 |
- 1 |
-
-
- | 122 |
- R7225H |
- BXD55_2 |
- F |
- 587 |
- 1 |
-
-
- | 123 |
- 052008.134 |
- BXD55_3 |
- F |
- 778 |
- 2 |
-
-
- | 124 |
- 052008.135 |
- BXD55_4 |
- F |
- 766 |
- 2 |
-
-
- | 125 |
- R7178H |
- BXD56_1 |
- M |
- 501 |
- 1 |
-
-
- | 126 |
- 051209.66 |
- BXD56_2 |
- M |
- 694 |
- 2 |
-
-
- | 127 |
- 052008.139 |
- BXD56_3 |
- F |
- 734 |
- 2 |
-
-
- | 128 |
- 042909.52 |
- BXD60_1 |
- M |
- 457 |
- 2 |
-
-
- | 129 |
- 101513.14 |
- BXD60_2 |
- F |
- 759 |
- 2 |
-
-
- | 130 |
- 052008.63 |
- BXD61_1 |
- M |
- 650 |
- 2 |
-
-
- | 131 |
- 020409.14 |
- BXD61_2 |
- F |
- 702 |
- 2 |
-
-
- | 132 |
- 121214.20 |
- BXD62_1 |
- F |
- 353 |
- 2 |
-
-
- | 133 |
- R7291H |
- BXD62_2 |
- M |
- 439 |
- 1 |
-
-
- | 134 |
- 040109.91 |
- BXD62_3 |
- F |
- 699 |
- 2 |
-
-
- | 135 |
- R7218H |
- BXD63_1 |
- M |
- 438 |
- 1 |
-
-
- | 136 |
- R7215H |
- BXD63_2 |
- F |
- 475 |
- 1 |
-
-
- | 137 |
- 050609.28 |
- BXD63_3 |
- M |
- 972 |
- 2 |
-
-
- | 138 |
- R7219H |
- BXD64_1 |
- M |
- 528 |
- 1 |
-
-
- | 139 |
- R7216H |
- BXD64_2 |
- F |
- 587 |
- 1 |
-
-
- | 140 |
- R7217H |
- BXD65_1 |
- F |
- 425 |
- 1 |
-
-
- | 141 |
- 050609.39 |
- BXD65_2 |
- M |
- 601 |
- 2 |
-
-
- | 142 |
- 052008.67 |
- BXD65_3 |
- F |
- 808 |
- 2 |
-
-
- | 143 |
- R7273H |
- BXD65a_1 |
- F |
- 389 |
- 1 |
-
-
- | 144 |
- R7277H |
- BXD65a_2 |
- M |
- 715 |
- 1 |
-
-
- | 145 |
- 061407.15 |
- BXD65a_3 |
- F |
- 536 |
- 2 |
-
-
- | 146 |
- 061407.16 |
- BXD65a_4 |
- F |
- 536 |
- 2 |
-
-
- | 147 |
- R7271H |
- BXD65b_1 |
- M |
- 483 |
- 1 |
-
-
- | 148 |
- R7302H |
- BXD66_1 |
- F |
- 446 |
- 1 |
-
-
- | 149 |
- R7214H |
- BXD66_2 |
- M |
- 463 |
- 1 |
-
-
- | 150 |
- 042507.19 |
- BXD66_3 |
- M |
- 557 |
- 2 |
-
-
- | 151 |
- 042507.20 |
- BXD66_4 |
- F |
- 557 |
- 2 |
-
-
- | 152 |
- R7278H |
- BXD67_1 |
- F |
- 415 |
- 1 |
-
-
- | 153 |
- R7213H |
- BXD67_2 |
- M |
- 425 |
- 1 |
-
-
- | 154 |
- R7240H |
- BXD67_3 |
- F |
- 499 |
- 1 |
-
-
- | 155 |
- 042607.11 |
- BXD67_4 |
- F |
- 606 |
- 2 |
-
-
- | 156 |
- 052008.71 |
- BXD67_5 |
- F |
- 649 |
- 2 |
-
-
- | 157 |
- R7211H |
- BXD68_1 |
- F |
- 415 |
- 1 |
-
-
- | 158 |
- R7212H |
- BXD68_2 |
- M |
- 421 |
- 1 |
-
-
- | 159 |
- 042607.27 |
- BXD68_3 |
- F |
- 623 |
- 2 |
-
-
- | 160 |
- 042607.28 |
- BXD68_4 |
- F |
- 623 |
- 2 |
-
-
- | 161 |
- R7305H |
- BXD69_1 |
- F |
- 504 |
- 1 |
-
-
- | 162 |
- 061913.13 |
- BXD69_2 |
- F |
- 558 |
- 2 |
-
-
- | 163 |
- 112707.08 |
- BXD69_3 |
- F |
- 602 |
- 2 |
-
-
- | 164 |
- R7207H |
- BXD70_1 |
- F |
- 458 |
- 1 |
-
-
- | 165 |
- R7204H |
- BXD70_2 |
- M |
- 460 |
- 1 |
-
-
- | 166 |
- 042909.28 |
- BXD70_3 |
- F |
- 761 |
- 2 |
-
-
- | 167 |
- 042909.29 |
- BXD70_4 |
- F |
- 761 |
- 2 |
-
-
- | 168 |
- R7205H |
- BXD71_1 |
- M |
- 471 |
- 1 |
-
-
- | 169 |
- R7208H |
- BXD71_2 |
- F |
- 474 |
- 1 |
-
-
- | 170 |
- 020409.11 |
- BXD71_3 |
- F |
- 701 |
- 2 |
-
-
- | 171 |
- 020409.49 |
- BXD71_4 |
- F |
- 582 |
- 2 |
-
-
- | 172 |
- R7209H |
- BXD73_1 |
- F |
- 470 |
- 1 |
-
-
- | 173 |
- R7206H |
- BXD73_2 |
- M |
- 464 |
- 1 |
-
-
- | 174 |
- 011007.16 |
- BXD73_3 |
- F |
- 544 |
- 2 |
-
-
- | 175 |
- 052008.81 |
- BXD73_4 |
- F |
- 642 |
- 2 |
-
-
- | 176 |
- R7181H |
- BXD73a_1 |
- F |
- 443 |
- 1 |
-
-
- | 177 |
- 061407.18 |
- BXD73a_2 |
- F |
- 443 |
- 2 |
-
-
- | 178 |
- R7182H |
- BXD73a_3 |
- M |
- 614 |
- 1 |
-
-
- | 179 |
- 052008.86 |
- BXD73a_4 |
- M |
- 710 |
- 2 |
-
-
- | 180 |
- 031407.10 |
- BXD74_1 |
- M |
- 804 |
- 2 |
-
-
- | 181 |
- 011107.08 |
- BXD75_1 |
- F |
- 535 |
- 2 |
-
-
- | 182 |
- R7188H |
- BXD76_1 |
- F |
- 408 |
- 1 |
-
-
- | 183 |
- R7187H |
- BXD76_2 |
- M |
- 564 |
- 1 |
-
-
- | 184 |
- R7179H |
- BXD76_3 |
- M |
- 579 |
- 1 |
-
-
- | 185 |
- R7292HR |
- BXD77_1 |
- M |
- 347 |
- 1 |
-
-
- | 186 |
- R7201H |
- BXD77_2 |
- F |
- 454 |
- 1 |
-
-
- | 187 |
- 052008.83 |
- BXD77_3 |
- F |
- 659 |
- 2 |
-
-
- | 188 |
- R7202H |
- BXD79_1 |
- M |
- 485 |
- 1 |
-
-
- | 189 |
- R7199H |
- BXD79_2 |
- F |
- 515 |
- 1 |
-
-
- | 190 |
- R7298H |
- BXD79_3 |
- M |
- 704 |
- 1 |
-
-
- | 191 |
- 050609.25 |
- BXD81_1 |
- F |
- 434 |
- 2 |
-
-
- | 192 |
- R7190H |
- BXD81_2 |
- F |
- 458 |
- 1 |
-
-
- | 193 |
- R7196H |
- BXD81_3 |
- M |
- 515 |
- 1 |
-
-
- | 194 |
- R7184H |
- BXD83_1 |
- M |
- 441 |
- 1 |
-
-
- | 195 |
- 061307.30 |
- BXD83_2 |
- F |
- 612 |
- 2 |
-
-
- | 196 |
- 121907.10 |
- BXD83_3 |
- M |
- 617 |
- 2 |
-
-
- | 197 |
- R7195H |
- BXD84_1 |
- M |
- 474 |
- 1 |
-
-
- | 198 |
- R7296H |
- BXD84_2 |
- M |
- 484 |
- 1 |
-
-
- | 199 |
- R7192H |
- BXD84_3 |
- F |
- 522 |
- 1 |
-
-
- | 200 |
- 020409.80 |
- BXD84_4 |
- F |
- 564 |
- 2 |
-
-
- | 201 |
- 112707.12 |
- BXD84_5 |
- F |
- 592 |
- 2 |
-
-
- | 202 |
- R7272H |
- BXD85_1 |
- M |
- 425 |
- 1 |
-
-
- | 203 |
- R7193H |
- BXD85_2 |
- F |
- 506 |
- 1 |
-
-
- | 204 |
- 020409.12 |
- BXD85_3 |
- F |
- 702 |
- 2 |
-
-
- | 205 |
- 020409.13 |
- BXD85_4 |
- F |
- 702 |
- 2 |
-
-
- | 206 |
- R7191H |
- BXD86_1 |
- M |
- 425 |
- 1 |
-
-
- | 207 |
- 020409.35 |
- BXD86_2 |
- F |
- 613 |
- 2 |
-
-
- | 208 |
- 020409.36 |
- BXD86_3 |
- F |
- 613 |
- 2 |
-
-
- | 209 |
- R7194H |
- BXD87_1 |
- F |
- 425 |
- 1 |
-
-
- | 210 |
- R7303HR |
- BXD87_2 |
- M |
- 478 |
- 1 |
-
-
- | 211 |
- R7186H |
- BXD87_3 |
- M |
- 442 |
- 1 |
-
-
- | 212 |
- 052008.97 |
- BXD87_4 |
- F |
- 666 |
- 2 |
-
-
- | 213 |
- 052008.98 |
- BXD87_5 |
- M |
- 666 |
- 2 |
-
-
- | 214 |
- R7295H |
- BXD89_1 |
- F |
- 446 |
- 1 |
-
-
- | 215 |
- 052008.100 |
- BXD89_2 |
- M |
- 616 |
- 2 |
-
-
- | 216 |
- R7287H |
- BXD90_1 |
- M |
- 434 |
- 1 |
-
-
- | 217 |
- R7293H |
- BXD90_2 |
- M |
- 558 |
- 1 |
-
-
- | 218 |
- 052008.105 |
- BXD90_3 |
- F |
- 452 |
- 2 |
-
-
- | 219 |
- R7180H |
- BXD95_1 |
- F |
- 467 |
- 1 |
-
-
- | 220 |
- R7169H |
- BXD95_2 |
- M |
- 467 |
- 1 |
-
-
- | 221 |
- 100914.09 |
- BXD95_3 |
- F |
- 536 |
- 2 |
-
-
- | 222 |
- R7237H |
- BXD98_1 |
- M |
- 605 |
- 1 |
-
-
- | 223 |
- R7171H |
- BXD98_2 |
- F |
- 639 |
- 1 |
-
-
- | 224 |
- R7275H |
- BXD98_3 |
- F |
- 488 |
- 1 |
-
-
- | 225 |
- R7189H |
- BXD99_1 |
- M |
- 524 |
- 1 |
-
-
- | 226 |
- R7172H |
- BXD99_2 |
- F |
- 471 |
- 1 |
-
-
- | 227 |
- R7282H |
- BXD100_1 |
- F |
- 463 |
- 1 |
-
-
- | 228 |
- R7283H |
- BXD100_2 |
- M |
- 507 |
- 1 |
-
-
- | 229 |
- R7274H |
- BXD100_3 |
- M |
- 577 |
- 1 |
-
-
- | 230 |
- R7226H |
- BXD100_4 |
- F |
- 464 |
- 1 |
-
-
- | 231 |
- 051209.62 |
- BXD100_5 |
- M |
- 577 |
- 2 |
-
-
- | 232 |
- R7284H |
- BXD101_1 |
- F |
- 490 |
- 1 |
-
-
- | 233 |
- R7285H |
- BXD101_2 |
- M |
- 408 |
- 1 |
-
-
- | 234 |
- 051112.10 |
- BXD101_3 |
- F |
- 223 |
- 2 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_BXDAged_0615/specifics.rtf b/general/datasets/UTHSC_BXDAged_0615/specifics.rtf
deleted file mode 100644
index d877bcf..0000000
--- a/general/datasets/UTHSC_BXDAged_0615/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Gene Level
diff --git a/general/datasets/UTHSC_BXDAged_0615/summary.rtf b/general/datasets/UTHSC_BXDAged_0615/summary.rtf
deleted file mode 100644
index 73a0125..0000000
--- a/general/datasets/UTHSC_BXDAged_0615/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is now public.
diff --git a/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/cases.rtf b/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/cases.rtf
deleted file mode 100644
index 9fbf83b..0000000
--- a/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/cases.rtf
+++ /dev/null
@@ -1,4336 +0,0 @@
-The study included 187 mice (12~18 month) from B6, D2, D2-Gpmnb, B6D2F1, D2B6F1, and 87 advanced intercross BXD strains (about 2 mice per strain). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
-
-
-
-The table of samples that are finally used for this study.
-
-
-
-
- |
- Index
- |
-
- RNA ID
- |
-
- case ID
- |
-
- DA_corrected_strain
- |
-
- Corrected Sex
- |
-
- AgeAtDeath days
- |
-
- Tissue
- |
-
-
- |
- 1
- |
-
- E18
- |
-
- 050115.16
- |
-
- BXD75
- |
-
- Female
- |
-
- 460
- |
-
- Eyeball
- |
-
-
- |
- 2
- |
-
- E19
- |
-
- 050115.17
- |
-
- BXD75
- |
-
- Female
- |
-
- 460
- |
-
- Eyeball
- |
-
-
- |
- 3
- |
-
- E21
- |
-
- 042715.10
- |
-
- D2B6F1
- |
-
- Female
- |
-
- 500
- |
-
- Eyeball
- |
-
-
- |
- 4
- |
-
- E22
- |
-
- 050115.19
- |
-
- BXD79
- |
-
- Female
- |
-
- 468
- |
-
- Eyeball
- |
-
-
- |
- 5
- |
-
- E31
- |
-
- 121515.13
- |
-
- BXD45
- |
-
- Female
- |
-
- 507
- |
-
- Eyeball
- |
-
-
- |
- 6
- |
-
- E33
- |
-
- 012615.10
- |
-
- BXD45
- |
-
- Female
- |
-
- 384
- |
-
- Eyeball
- |
-
-
- |
- 7
- |
-
- E34
- |
-
- 012615.04
- |
-
- BXD62
- |
-
- Female
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 8
- |
-
- E40
- |
-
- 021213.21
- |
-
- BXD79
- |
-
- Female
- |
-
- 378
- |
-
- Eyeball
- |
-
-
- |
- 9
- |
-
- E49
- |
-
- 021213.13
- |
-
- BXD60
- |
-
- Female
- |
-
- 530
- |
-
- Eyeball
- |
-
-
- |
- 10
- |
-
- E60
- |
-
- 101713.01
- |
-
- BXD60
- |
-
- Female
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 11
- |
-
- E62
- |
-
- 090612.07
- |
-
- BXD73b
- |
-
- Female
- |
-
- 377
- |
-
- Eyeball
- |
-
-
- |
- 12
- |
-
- E63
- |
-
- 090612.08
- |
-
- BXD73b
- |
-
- Female
- |
-
- 377
- |
-
- Eyeball
- |
-
-
- |
- 13
- |
-
- E65
- |
-
- 050912.04
- |
-
- BXD34
- |
-
- Female
- |
-
- 419
- |
-
- Eyeball
- |
-
-
- |
- 14
- |
-
- E67
- |
-
- 42214.08
- |
-
- BXD40
- |
-
- Female
- |
-
- 362
- |
-
- Eyeball
- |
-
-
- |
- 15
- |
-
- E72
- |
-
- 42214.04
- |
-
- BXD24
- |
-
- Female
- |
-
- 377
- |
-
- Eyeball
- |
-
-
- |
- 16
- |
-
- E75
- |
-
- 42214.03
- |
-
- BXD24
- |
-
- Female
- |
-
- 377
- |
-
- Eyeball
- |
-
-
- |
- 17
- |
-
- E78
- |
-
- 42314.1
- |
-
- B6D2F1
- |
-
- Male
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 18
- |
-
- E82
- |
-
- 121615.05
- |
-
- BXD62
- |
-
- Female
- |
-
- 525
- |
-
- Eyeball
- |
-
-
- |
- 19
- |
-
- E87
- |
-
- 101014.10
- |
-
- BXD95
- |
-
- Female
- |
-
- 536
- |
-
- Eyeball
- |
-
-
- |
- 20
- |
-
- E89
- |
-
- 121615.22
- |
-
- BXD89
- |
-
- Female
- |
-
- 444
- |
-
- Eyeball
- |
-
-
- |
- 21
- |
-
- E90
- |
-
- 101014.09
- |
-
- BXD95
- |
-
- Female
- |
-
- 536
- |
-
- Eyeball
- |
-
-
- |
- 22
- |
-
- E99
- |
-
- 121214.15
- |
-
- BXD70
- |
-
- Female
- |
-
- 357
- |
-
- Eyeball
- |
-
-
- |
- 23
- |
-
- E100
- |
-
- 121214.16
- |
-
- BXD70
- |
-
- Female
- |
-
- 357
- |
-
- Eyeball
- |
-
-
- |
- 24
- |
-
- E124
- |
-
- 042214.18
- |
-
- D2B6F1
- |
-
- Male
- |
-
- 397
- |
-
- Eyeball
- |
-
-
- |
- 25
- |
-
- E152
- |
-
- 050912.04
- |
-
- BXD48a
- |
-
- Female
- |
-
- 419
- |
-
- Eyeball
- |
-
-
- |
- 26
- |
-
- E158
- |
-
- 101713.02
- |
-
- BXD100
- |
-
- Female
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 27
- |
-
- E224
- |
-
- 021313.26
- |
-
- BXD84
- |
-
- Female
- |
-
- 385
- |
-
- Eyeball
- |
-
-
- |
- 28
- |
-
- E264
- |
-
- *050318.12
- |
-
- BXD69
- |
-
- Male
- |
-
- 387
- |
-
- Eyeball
- |
-
-
- |
- 29
- |
-
- E288
- |
-
- *110918.106
- |
-
- BXD211
- |
-
- Male
- |
-
- 404
- |
-
- Eyeball
- |
-
-
- |
- 30
- |
-
- E289
- |
-
- *110918.105
- |
-
- BXD211
- |
-
- Female
- |
-
- 404
- |
-
- Eyeball
- |
-
-
- |
- 31
- |
-
- E290
- |
-
- *100218.04
- |
-
- BXD44
- |
-
- Female
- |
-
- 530
- |
-
- Eyeball
- |
-
-
- |
- 32
- |
-
- E291
- |
-
- *100218.05
- |
-
- BXD44
- |
-
- Male
- |
-
- 530
- |
-
- Eyeball
- |
-
-
- |
- 33
- |
-
- E292
- |
-
- *100218.18
- |
-
- BXD68
- |
-
- Female
- |
-
- 516
- |
-
- Eyeball
- |
-
-
- |
- 34
- |
-
- E293
- |
-
- *100218.20
- |
-
- BXD68
- |
-
- Male
- |
-
- 516
- |
-
- Eyeball
- |
-
-
- |
- 35
- |
-
- E294
- |
-
- *100218.36
- |
-
- BXD84
- |
-
- Female
- |
-
- 516
- |
-
- Eyeball
- |
-
-
- |
- 36
- |
-
- E298
- |
-
- *100218.73
- |
-
- BXD184
- |
-
- Female
- |
-
- 512
- |
-
- Eyeball
- |
-
-
- |
- 37
- |
-
- E299
- |
-
- *100218.74
- |
-
- BXD184
- |
-
- Male
- |
-
- 512
- |
-
- Eyeball
- |
-
-
- |
- 38
- |
-
- E303
- |
-
- AGE061218.98
- |
-
- BXD177
- |
-
- Female
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 39
- |
-
- E304
- |
-
- AGE061218.108
- |
-
- BXD195
- |
-
- Male
- |
-
- 386
- |
-
- Eyeball
- |
-
-
- |
- 40
- |
-
- E306
- |
-
- AGE061218.107
- |
-
- BXD195
- |
-
- Female
- |
-
- 386
- |
-
- Eyeball
- |
-
-
- |
- 41
- |
-
- E308
- |
-
- AGE061218.99
- |
-
- BXD177
- |
-
- Male
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 42
- |
-
- E310
- |
-
- AGE061218.90
- |
-
- BXD168
- |
-
- Male
- |
-
- 538
- |
-
- Eyeball
- |
-
-
- |
- 43
- |
-
- E311
- |
-
- AGE061218.85
- |
-
- BXD160
- |
-
- Male
- |
-
- 390
- |
-
- Eyeball
- |
-
-
- |
- 44
- |
-
- E312
- |
-
- AGE061218.71
- |
-
- BXD150
- |
-
- Male
- |
-
- 398
- |
-
- Eyeball
- |
-
-
- |
- 45
- |
-
- E313
- |
-
- AGE061218.22
- |
-
- BXD34
- |
-
- Male
- |
-
- 369
- |
-
- Eyeball
- |
-
-
- |
- 46
- |
-
- E314
- |
-
- AGE061218.21
- |
-
- BXD34
- |
-
- Female
- |
-
- 369
- |
-
- Eyeball
- |
-
-
- |
- 47
- |
-
- E331
- |
-
- *110918.07
- |
-
- BXD28
- |
-
- Male
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 48
- |
-
- E334
- |
-
- *110918.02
- |
-
- BXD18
- |
-
- Male
- |
-
- 452
- |
-
- Eyeball
- |
-
-
- |
- 49
- |
-
- E335
- |
-
- *110918.01
- |
-
- BXD18
- |
-
- Female
- |
-
- 452
- |
-
- Eyeball
- |
-
-
- |
- 50
- |
-
- E340
- |
-
- *110918.51
- |
-
- BXD98
- |
-
- Male
- |
-
- 359
- |
-
- Eyeball
- |
-
-
- |
- 51
- |
-
- E341
- |
-
- *110918.50
- |
-
- BXD98
- |
-
- Female
- |
-
- 359
- |
-
- Eyeball
- |
-
-
- |
- 52
- |
-
- E344
- |
-
- *083019.05
- |
-
- BXD9
- |
-
- Female
- |
-
- 373
- |
-
- Eyeball
- |
-
-
- |
- 53
- |
-
- E345
- |
-
- *083019.06
- |
-
- BXD9
- |
-
- Male
- |
-
- 373
- |
-
- Eyeball
- |
-
-
- |
- 54
- |
-
- E346
- |
-
- *083019.22
- |
-
- BXD31
- |
-
- Male
- |
-
- 391
- |
-
- Eyeball
- |
-
-
- |
- 55
- |
-
- E347
- |
-
- *083019.23
- |
-
- BXD43
- |
-
- Female
- |
-
- 391
- |
-
- Eyeball
- |
-
-
- |
- 56
- |
-
- E349
- |
-
- *083019.26
- |
-
- BXD43
- |
-
- Male
- |
-
- 367
- |
-
- Eyeball
- |
-
-
- |
- 57
- |
-
- E350
- |
-
- *083019.30
- |
-
- BXD50
- |
-
- Female
- |
-
- 408
- |
-
- Eyeball
- |
-
-
- |
- 58
- |
-
- E351
- |
-
- *083019.31
- |
-
- BXD50
- |
-
- Female
- |
-
- 408
- |
-
- Eyeball
- |
-
-
- |
- 59
- |
-
- E352
- |
-
- *083019.33
- |
-
- BXD51
- |
-
- Female
- |
-
- 368
- |
-
- Eyeball
- |
-
-
- |
- 60
- |
-
- E353
- |
-
- *083019.34
- |
-
- BXD51
- |
-
- Male
- |
-
- 368
- |
-
- Eyeball
- |
-
-
- |
- 61
- |
-
- E354
- |
-
- *083019.38
- |
-
- BXD66
- |
-
- Male
- |
-
- 430
- |
-
- Eyeball
- |
-
-
- |
- 62
- |
-
- E355
- |
-
- *083019.39
- |
-
- BXD66
- |
-
- Male
- |
-
- 430
- |
-
- Eyeball
- |
-
-
- |
- 63
- |
-
- E356
- |
-
- *083019.45
- |
-
- BXD73
- |
-
- Female
- |
-
- 451
- |
-
- Eyeball
- |
-
-
- |
- 64
- |
-
- E357
- |
-
- *083019.46
- |
-
- BXD73
- |
-
- Male
- |
-
- 451
- |
-
- Eyeball
- |
-
-
- |
- 65
- |
-
- E358
- |
-
- *083019.48
- |
-
- BXD75
- |
-
- Female
- |
-
- 369
- |
-
- Eyeball
- |
-
-
- |
- 66
- |
-
- E359
- |
-
- *083019.49
- |
-
- BXD75
- |
-
- Male
- |
-
- 369
- |
-
- Eyeball
- |
-
-
- |
- 67
- |
-
- E360
- |
-
- *083019.50
- |
-
- BXD78
- |
-
- Female
- |
-
- 432
- |
-
- Eyeball
- |
-
-
- |
- 68
- |
-
- E361
- |
-
- *083019.51
- |
-
- BXD78
- |
-
- Male
- |
-
- 432
- |
-
- Eyeball
- |
-
-
- |
- 69
- |
-
- E363
- |
-
- *083019.55
- |
-
- BXD87
- |
-
- Female
- |
-
- 444
- |
-
- Eyeball
- |
-
-
- |
- 70
- |
-
- E364
- |
-
- *083019.56
- |
-
- BXD87
- |
-
- Male
- |
-
- 444
- |
-
- Eyeball
- |
-
-
- |
- 71
- |
-
- E365
- |
-
- *083019.57
- |
-
- BXD89
- |
-
- Female
- |
-
- 446
- |
-
- Eyeball
- |
-
-
- |
- 72
- |
-
- E366
- |
-
- *083019.66
- |
-
- BXD113
- |
-
- Female
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 73
- |
-
- E367
- |
-
- *083019.67
- |
-
- BXD113
- |
-
- Male
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 74
- |
-
- E368
- |
-
- *090119.04
- |
-
- BXD123
- |
-
- Female
- |
-
- 441
- |
-
- Eyeball
- |
-
-
- |
- 75
- |
-
- E369
- |
-
- *090119.05
- |
-
- BXD123
- |
-
- Male
- |
-
- 441
- |
-
- Eyeball
- |
-
-
- |
- 76
- |
-
- E370
- |
-
- *090119.09
- |
-
- BXD141
- |
-
- Female
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 77
- |
-
- E371
- |
-
- *090119.11
- |
-
- BXD141
- |
-
- Male
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 78
- |
-
- E372
- |
-
- *090119.15
- |
-
- BXD151
- |
-
- Female
- |
-
- 439
- |
-
- Eyeball
- |
-
-
- |
- 79
- |
-
- E373
- |
-
- *090119.16
- |
-
- BXD151
- |
-
- Male
- |
-
- 439
- |
-
- Eyeball
- |
-
-
- |
- 80
- |
-
- E374
- |
-
- *090119.18
- |
-
- BXD152
- |
-
- Female
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 81
- |
-
- E375
- |
-
- *090119.19
- |
-
- BXD152
- |
-
- Male
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 82
- |
-
- E376
- |
-
- *090119.20
- |
-
- BXD154
- |
-
- Female
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 83
- |
-
- E377
- |
-
- *090119.22
- |
-
- BXD154
- |
-
- Male
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 84
- |
-
- E378
- |
-
- *090119.24
- |
-
- BXD155
- |
-
- Female
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 85
- |
-
- E379
- |
-
- *090119.25
- |
-
- BXD155
- |
-
- Male
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 86
- |
-
- E380
- |
-
- *090119.27
- |
-
- BXD161
- |
-
- Female
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 87
- |
-
- E381
- |
-
- *090119.28
- |
-
- BXD161
- |
-
- Male
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 88
- |
-
- E382
- |
-
- *090119.34
- |
-
- BXD170
- |
-
- Male
- |
-
- 438
- |
-
- Eyeball
- |
-
-
- |
- 89
- |
-
- E383
- |
-
- *090119.36
- |
-
- BXD171
- |
-
- Female
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 90
- |
-
- E384
- |
-
- *090119.37
- |
-
- BXD171
- |
-
- Male
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 91
- |
-
- E385
- |
-
- *090119.41
- |
-
- BXD178
- |
-
- Female
- |
-
- 493
- |
-
- Eyeball
- |
-
-
- |
- 92
- |
-
- E386
- |
-
- *090119.42
- |
-
- BXD178
- |
-
- Female
- |
-
- 493
- |
-
- Eyeball
- |
-
-
- |
- 93
- |
-
- E387
- |
-
- *090119.44
- |
-
- BXD180
- |
-
- Female
- |
-
- 375
- |
-
- Eyeball
- |
-
-
- |
- 94
- |
-
- E390
- |
-
- *090119.48
- |
-
- BXD190
- |
-
- Male
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 95
- |
-
- E391
- |
-
- *090119.52
- |
-
- BXD197
- |
-
- Female
- |
-
- 433
- |
-
- Eyeball
- |
-
-
- |
- 96
- |
-
- E392
- |
-
- *090119.53
- |
-
- BXD197
- |
-
- Male
- |
-
- 433
- |
-
- Eyeball
- |
-
-
- |
- 97
- |
-
- E395
- |
-
- *090119.57
- |
-
- BXD202
- |
-
- Female
- |
-
- 427
- |
-
- Eyeball
- |
-
-
- |
- 98
- |
-
- E399
- |
-
- *090119.67
- |
-
- BXD218
- |
-
- Female
- |
-
- 412
- |
-
- Eyeball
- |
-
-
- |
- 99
- |
-
- E400
- |
-
- *090119.68
- |
-
- BXD218
- |
-
- Male
- |
-
- 412
- |
-
- Eyeball
- |
-
-
- |
- 100
- |
-
- E448
- |
-
- *100819.101
- |
-
- BXD111
- |
-
- Female
- |
-
- 373
- |
-
- Eyeball
- |
-
-
- |
- 101
- |
-
- E449
- |
-
- *100819.102
- |
-
- BXD111
- |
-
- Male
- |
-
- 373
- |
-
- Eyeball
- |
-
-
- |
- 102
- |
-
- E450
- |
-
- *100819.104
- |
-
- BXD122
- |
-
- Female
- |
-
- 383
- |
-
- Eyeball
- |
-
-
- |
- 103
- |
-
- E451
- |
-
- *100819.105
- |
-
- BXD122
- |
-
- Male
- |
-
- 383
- |
-
- Eyeball
- |
-
-
- |
- 104
- |
-
- E452
- |
-
- *100819.107
- |
-
- BXD124
- |
-
- Female
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 105
- |
-
- E453
- |
-
- *100819.108
- |
-
- BXD124
- |
-
- Male
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 106
- |
-
- E454
- |
-
- *100819.110
- |
-
- BXD125
- |
-
- Female
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 107
- |
-
- E455
- |
-
- *100819.111
- |
-
- BXD125
- |
-
- Male
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 108
- |
-
- E459
- |
-
- *100819.131
- |
-
- BXD172
- |
-
- Female
- |
-
- 375
- |
-
- Eyeball
- |
-
-
- |
- 109
- |
-
- E460
- |
-
- *100819.132
- |
-
- BXD172
- |
-
- Male
- |
-
- 375
- |
-
- Eyeball
- |
-
-
- |
- 110
- |
-
- E482
- |
-
- *052220.14
- |
-
- BXD71
- |
-
- Female
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 111
- |
-
- E483
- |
-
- *052220.10
- |
-
- BXD11
- |
-
- Female
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 112
- |
-
- E484
- |
-
- *052220.07
- |
-
- BXD65
- |
-
- Male
- |
-
- 528
- |
-
- Eyeball
- |
-
-
- |
- 113
- |
-
- E485
- |
-
- *052220.03
- |
-
- BXD194
- |
-
- Male
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 114
- |
-
- E486
- |
-
- *052220.19
- |
-
- BXD15
- |
-
- Female
- |
-
- 415
- |
-
- Eyeball
- |
-
-
- |
- 115
- |
-
- E487
- |
-
- *052220.02
- |
-
- BXD194
- |
-
- Female
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 116
- |
-
- E488
- |
-
- *052220.12
- |
-
- BXD1
- |
-
- Female
- |
-
- 429
- |
-
- Eyeball
- |
-
-
- |
- 117
- |
-
- E489
- |
-
- *052220.18
- |
-
- BXD216
- |
-
- Male
- |
-
- 401
- |
-
- Eyeball
- |
-
-
- |
- 118
- |
-
- E490
- |
-
- *052220.13
- |
-
- BXD1
- |
-
- Male
- |
-
- 429
- |
-
- Eyeball
- |
-
-
- |
- 119
- |
-
- E494
- |
-
- *052220.15
- |
-
- BXD71
- |
-
- Male
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 120
- |
-
- E496
- |
-
- *052220.08
- |
-
- BXD170
- |
-
- Male
- |
-
- 360
- |
-
- Eyeball
- |
-
-
- |
- 121
- |
-
- E498
- |
-
- *052220.06
- |
-
- BXD65
- |
-
- Female
- |
-
- 528
- |
-
- Eyeball
- |
-
-
- |
- 122
- |
-
- E499
- |
-
- *052220.05
- |
-
- C57BL/6J
- |
-
- Male
- |
-
- 424
- |
-
- Eyeball
- |
-
-
- |
- 123
- |
-
- E501
- |
-
- *052220.21
- |
-
- BXD73a
- |
-
- Female
- |
-
- 408
- |
-
- Eyeball
- |
-
-
- |
- 124
- |
-
- E502
- |
-
- *052220.11
- |
-
- BXD11
- |
-
- Male
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 125
- |
-
- E503
- |
-
- *052220.22
- |
-
- DBA/2J-Gpnmb
- |
-
- Female
- |
-
- 439
- |
-
- Eyeball
- |
-
-
- |
- 126
- |
-
- E504
- |
-
- *052220.20
- |
-
- BXD15
- |
-
- Male
- |
-
- 415
- |
-
- Eyeball
- |
-
-
- |
- 127
- |
-
- E541
- |
-
- 042915.08
- |
-
- BXD29
- |
-
- Female
- |
-
- 478
- |
-
- Eyeball
- |
-
-
- |
- 128
- |
-
- E542
- |
-
- 050115.01
- |
-
- BXD65b
- |
-
- Female
- |
-
- 415
- |
-
- Eyeball
- |
-
-
- |
- 129
- |
-
- E543
- |
-
- 042915.07
- |
-
- BXD29
- |
-
- Female
- |
-
- 431
- |
-
- Eyeball
- |
-
-
- |
- 130
- |
-
- E544
- |
-
- 042314.12
- |
-
- B6D2F1
- |
-
- Female
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 131
- |
-
- E548
- |
-
- *061119.02
- |
-
- C57BL/6J
- |
-
- Female
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 132
- |
-
- E549
- |
-
- *061119.03
- |
-
- C57BL/6J
- |
-
- Male
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 133
- |
-
- E551
- |
-
- *061119.11
- |
-
- DBA/2J
- |
-
- Female
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 134
- |
-
- E552
- |
-
- *061119.12
- |
-
- DBA/2J
- |
-
- Male
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 135
- |
-
- E554
- |
-
- *061119.15
- |
-
- DBA/2J
- |
-
- Male
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 136
- |
-
- E556
- |
-
- *061119.22
- |
-
- DBA/2J
- |
-
- Male
- |
-
- 380
- |
-
- Eyeball
- |
-
-
- |
- 137
- |
-
- E561
- |
-
- *061219.12
- |
-
- BXD27
- |
-
- Female
- |
-
- 494
- |
-
- Eyeball
- |
-
-
- |
- 138
- |
-
- E564
- |
-
- *061219.14
- |
-
- BXD27
- |
-
- Male
- |
-
- 494
- |
-
- Eyeball
- |
-
-
- |
- 139
- |
-
- E565
- |
-
- *060419.04
- |
-
- BXD32
- |
-
- Female
- |
-
- 425
- |
-
- Eyeball
- |
-
-
- |
- 140
- |
-
- E566
- |
-
- *060419.05
- |
-
- BXD32
- |
-
- Male
- |
-
- 425
- |
-
- Eyeball
- |
-
-
- |
- 141
- |
-
- E567
- |
-
- *070919.01
- |
-
- BXD86
- |
-
- Female
- |
-
- 381
- |
-
- Eyeball
- |
-
-
- |
- 142
- |
-
- E569
- |
-
- *070919.03
- |
-
- BXD86
- |
-
- Male
- |
-
- 381
- |
-
- Eyeball
- |
-
-
- |
- 143
- |
-
- E576
- |
-
- *072519.11
- |
-
- BXD191
- |
-
- Male
- |
-
- 477
- |
-
- Eyeball
- |
-
-
- |
- 144
- |
-
- E577
- |
-
- *072519.09
- |
-
- BXD190
- |
-
- Male
- |
-
- 434
- |
-
- Eyeball
- |
-
-
- |
- 145
- |
-
- E582
- |
-
- *073019.16
- |
-
- BXD216
- |
-
- Male
- |
-
- 459
- |
-
- Eyeball
- |
-
-
- |
- 146
- |
-
- E591
- |
-
- *061319.04
- |
-
- BXD48
- |
-
- Female
- |
-
- 425
- |
-
- Eyeball
- |
-
-
- |
- 147
- |
-
- E592
- |
-
- *061319.05
- |
-
- BXD48
- |
-
- Male
- |
-
- 425
- |
-
- Eyeball
- |
-
-
- |
- 148
- |
-
- E593
- |
-
- *061319.21
- |
-
- BXD61
- |
-
- Male
- |
-
- 459
- |
-
- Eyeball
- |
-
-
- |
- 149
- |
-
- E600
- |
-
- *050318.10
- |
-
- BXD69
- |
-
- Female
- |
-
- 387
- |
-
- Eyeball
- |
-
-
- |
- 150
- |
-
- E601
- |
-
- *013020.53
- |
-
- BXD102
- |
-
- Male
- |
-
- 416
- |
-
- Eyeball
- |
-
-
- |
- 151
- |
-
- E603
- |
-
- *013020.25
- |
-
- BXD65b
- |
-
- Male
- |
-
- 505
- |
-
- Eyeball
- |
-
-
- |
- 152
- |
-
- E605
- |
-
- *013020.54
- |
-
- BXD102
- |
-
- Female
- |
-
- 416
- |
-
- Eyeball
- |
-
-
- |
- 153
- |
-
- E620
- |
-
- *012420.26
- |
-
- BXD128a
- |
-
- Male
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 154
- |
-
- E625
- |
-
- *110918.54
- |
-
- BXD101
- |
-
- Male
- |
-
- 361
- |
-
- Eyeball
- |
-
-
- |
- 155
- |
-
- E626
- |
-
- *110918.53
- |
-
- BXD101
- |
-
- Female
- |
-
- 361
- |
-
- Eyeball
- |
-
-
- |
- 156
- |
-
- E631
- |
-
- *083019.14
- |
-
- BXD16
- |
-
- Female
- |
-
- 363
- |
-
- Eyeball
- |
-
-
- |
- 157
- |
-
- E635
- |
-
- *083019.35
- |
-
- BXD61
- |
-
- Male
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 158
- |
-
- E638
- |
-
- *083019.60
- |
-
- BXD90
- |
-
- Female
- |
-
- 378
- |
-
- Eyeball
- |
-
-
- |
- 159
- |
-
- E639
- |
-
- *083019.62
- |
-
- BXD90
- |
-
- Male
- |
-
- 378
- |
-
- Eyeball
- |
-
-
- |
- 160
- |
-
- E662
- |
-
- *100819.153
- |
-
- BXD202
- |
-
- Male
- |
-
- 410
- |
-
- Eyeball
- |
-
-
- |
- 161
- |
-
- E663
- |
-
- *100819.157
- |
-
- BXD205
- |
-
- Female
- |
-
- 371
- |
-
- Eyeball
- |
-
-
- |
- 162
- |
-
- E664
- |
-
- *100819.158
- |
-
- BXD205
- |
-
- Male
- |
-
- 372
- |
-
- Eyeball
- |
-
-
- |
- 163
- |
-
- E665
- |
-
- *100819.163
- |
-
- BXD213
- |
-
- Female
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 164
- |
-
- E666
- |
-
- *100819.164
- |
-
- BXD213
- |
-
- Male
- |
-
- 397
- |
-
- Eyeball
- |
-
-
- |
- 165
- |
-
- E667
- |
-
- *100819.168
- |
-
- BXD223
- |
-
- Female
- |
-
- 419
- |
-
- Eyeball
- |
-
-
- |
- 166
- |
-
- E668
- |
-
- *100819.169
- |
-
- BXD223
- |
-
- Male
- |
-
- 420
- |
-
- Eyeball
- |
-
-
- |
- 167
- |
-
- E672
- |
-
- *052920.10
- |
-
- BXD83
- |
-
- Male
- |
-
- 380
- |
-
- Eyeball
- |
-
-
- |
- 168
- |
-
- E675
- |
-
- *052920.13
- |
-
- DBA/2J-Gpnmb
- |
-
- Female
- |
-
- 452
- |
-
- Eyeball
- |
-
-
- |
- 169
- |
-
- E679
- |
-
- *052920.12
- |
-
- DBA/2J-Gpnmb
- |
-
- Female
- |
-
- 458
- |
-
- Eyeball
- |
-
-
- |
- 170
- |
-
- E680
- |
-
- *052920.01
- |
-
- BXD43
- |
-
- Female
- |
-
- 465
- |
-
- Eyeball
- |
-
-
- |
- 171
- |
-
- E682
- |
-
- *052920.02
- |
-
- C57BL/6J
- |
-
- Female
- |
-
- 433
- |
-
- Eyeball
- |
-
-
- |
- 172
- |
-
- E685
- |
-
- *052920.09
- |
-
- BXD83
- |
-
- Female
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 173
- |
-
- E699
- |
-
- *072120.14
- |
-
- BXD40
- |
-
- Male
- |
-
- 458
- |
-
- Eyeball
- |
-
-
- |
- 174
- |
-
- E709
- |
-
- *072120.24
- |
-
- BXD150
- |
-
- Female
- |
-
- 433
- |
-
- Eyeball
- |
-
-
- |
- 175
- |
-
- E712
- |
-
- *072120.27
- |
-
- BXD160
- |
-
- Female
- |
-
- 367
- |
-
- Eyeball
- |
-
-
- |
- 176
- |
-
- E726
- |
-
- *072120.41
- |
-
- BXD16
- |
-
- Female
- |
-
- 367
- |
-
- Eyeball
- |
-
-
- |
- 177
- |
-
- E733
- |
-
- *072120.48
- |
-
- BXD60
- |
-
- Female
- |
-
- 558
- |
-
- Eyeball
- |
-
-
- |
- 178
- |
-
- E735
- |
-
- *072120.50
- |
-
- BXD180
- |
-
- Male
- |
-
- 473
- |
-
- Eyeball
- |
-
-
- |
- 179
- |
-
- E738
- |
-
- *072120.53
- |
-
- BXD128a
- |
-
- Female
- |
-
- 387
- |
-
- Eyeball
- |
-
-
- |
- 180
- |
-
- E745
- |
-
- *072120.60
- |
-
- BXD199
- |
-
- Female
- |
-
- 457
- |
-
- Eyeball
- |
-
-
- |
- 181
- |
-
- E746
- |
-
- *072120.61
- |
-
- BXD199
- |
-
- Male
- |
-
- 457
- |
-
- Eyeball
- |
-
-
- |
- 182
- |
-
- E749
- |
-
- *072120.64
- |
-
- BXD2
- |
-
- Female
- |
-
- 399
- |
-
- Eyeball
- |
-
-
- |
- 183
- |
-
- E750
- |
-
- *072120.65
- |
-
- BXD2
- |
-
- Male
- |
-
- 399
- |
-
- Eyeball
- |
-
-
- |
- 184
- |
-
- E753
- |
-
- *072120.68
- |
-
- BXD169
- |
-
- Female
- |
-
- 441
- |
-
- Eyeball
- |
-
-
- |
- 185
- |
-
- E754
- |
-
- *072120.69
- |
-
- BXD169
- |
-
- Male
- |
-
- 441
- |
-
- Eyeball
- |
-
-
- |
- 186
- |
-
- E759
- |
-
- *072120.72
- |
-
- BXD187
- |
-
- Female
- |
-
- 354
- |
-
- Eyeball
- |
-
-
- |
- 187
- |
-
- E760
- |
-
- *072120.73
- |
-
- BXD187
- |
-
- Male
- |
-
- 354
- |
-
- Eyeball
- |
-
-
-
-
-
diff --git a/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/experiment-design.rtf b/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/experiment-design.rtf
deleted file mode 100644
index e7afcee..0000000
--- a/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA Extraction
-
-Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. according to the manufacturer’s instructions. Approximately 30 mg of PFC tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 7.0 were used for library preparation
diff --git a/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/notes.rtf b/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/notes.rtf
deleted file mode 100644
index d622df7..0000000
--- a/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/notes.rtf
+++ /dev/null
@@ -1 +0,0 @@
-UTHSC BXD Young Aged Eye RNA-Seq (Apr22) DESeq2 rlog2
diff --git a/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/processing.rtf b/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/processing.rtf
deleted file mode 100644
index 7ddb89f..0000000
--- a/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (mm11 Mus_musculus.GRCm39, release 104) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Rows with no gene symbol name were deleted. Indices of the reference genome were built using STAR version 2.5.2b and paired-end reads were aligned to the reference genome. FeatureCount from package RsubRead, version 1.32.4, was used to count the number of read mapped to each gene. Raw counts were then normalized and log2 transformed using function rlogTransformation from the DESeq2 package (version 1.16.1) and an increment was added to the normalized values to make all values positive.
diff --git a/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/specifics.rtf b/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/specifics.rtf
deleted file mode 100644
index 2e5de4e..0000000
--- a/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-UTHSC BXD Old Aged Eye RNA-Seq (Apr22) DESeq2 rlog2
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/tissue.rtf b/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/tissue.rtf
deleted file mode 100644
index 126ab9f..0000000
--- a/general/datasets/UTHSC_BXDOldEyeRNAseq_DESeq2_rlog2_0422/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Tissue Harvest
-
-The animals were sacrificed under saturated isoflurane. Eyeballs from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/cases.rtf b/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/cases.rtf
deleted file mode 100644
index 9fbf83b..0000000
--- a/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/cases.rtf
+++ /dev/null
@@ -1,4336 +0,0 @@
-The study included 187 mice (12~18 month) from B6, D2, D2-Gpmnb, B6D2F1, D2B6F1, and 87 advanced intercross BXD strains (about 2 mice per strain). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
-
-
-
-The table of samples that are finally used for this study.
-
-
-
-
- |
- Index
- |
-
- RNA ID
- |
-
- case ID
- |
-
- DA_corrected_strain
- |
-
- Corrected Sex
- |
-
- AgeAtDeath days
- |
-
- Tissue
- |
-
-
- |
- 1
- |
-
- E18
- |
-
- 050115.16
- |
-
- BXD75
- |
-
- Female
- |
-
- 460
- |
-
- Eyeball
- |
-
-
- |
- 2
- |
-
- E19
- |
-
- 050115.17
- |
-
- BXD75
- |
-
- Female
- |
-
- 460
- |
-
- Eyeball
- |
-
-
- |
- 3
- |
-
- E21
- |
-
- 042715.10
- |
-
- D2B6F1
- |
-
- Female
- |
-
- 500
- |
-
- Eyeball
- |
-
-
- |
- 4
- |
-
- E22
- |
-
- 050115.19
- |
-
- BXD79
- |
-
- Female
- |
-
- 468
- |
-
- Eyeball
- |
-
-
- |
- 5
- |
-
- E31
- |
-
- 121515.13
- |
-
- BXD45
- |
-
- Female
- |
-
- 507
- |
-
- Eyeball
- |
-
-
- |
- 6
- |
-
- E33
- |
-
- 012615.10
- |
-
- BXD45
- |
-
- Female
- |
-
- 384
- |
-
- Eyeball
- |
-
-
- |
- 7
- |
-
- E34
- |
-
- 012615.04
- |
-
- BXD62
- |
-
- Female
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 8
- |
-
- E40
- |
-
- 021213.21
- |
-
- BXD79
- |
-
- Female
- |
-
- 378
- |
-
- Eyeball
- |
-
-
- |
- 9
- |
-
- E49
- |
-
- 021213.13
- |
-
- BXD60
- |
-
- Female
- |
-
- 530
- |
-
- Eyeball
- |
-
-
- |
- 10
- |
-
- E60
- |
-
- 101713.01
- |
-
- BXD60
- |
-
- Female
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 11
- |
-
- E62
- |
-
- 090612.07
- |
-
- BXD73b
- |
-
- Female
- |
-
- 377
- |
-
- Eyeball
- |
-
-
- |
- 12
- |
-
- E63
- |
-
- 090612.08
- |
-
- BXD73b
- |
-
- Female
- |
-
- 377
- |
-
- Eyeball
- |
-
-
- |
- 13
- |
-
- E65
- |
-
- 050912.04
- |
-
- BXD34
- |
-
- Female
- |
-
- 419
- |
-
- Eyeball
- |
-
-
- |
- 14
- |
-
- E67
- |
-
- 42214.08
- |
-
- BXD40
- |
-
- Female
- |
-
- 362
- |
-
- Eyeball
- |
-
-
- |
- 15
- |
-
- E72
- |
-
- 42214.04
- |
-
- BXD24
- |
-
- Female
- |
-
- 377
- |
-
- Eyeball
- |
-
-
- |
- 16
- |
-
- E75
- |
-
- 42214.03
- |
-
- BXD24
- |
-
- Female
- |
-
- 377
- |
-
- Eyeball
- |
-
-
- |
- 17
- |
-
- E78
- |
-
- 42314.1
- |
-
- B6D2F1
- |
-
- Male
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 18
- |
-
- E82
- |
-
- 121615.05
- |
-
- BXD62
- |
-
- Female
- |
-
- 525
- |
-
- Eyeball
- |
-
-
- |
- 19
- |
-
- E87
- |
-
- 101014.10
- |
-
- BXD95
- |
-
- Female
- |
-
- 536
- |
-
- Eyeball
- |
-
-
- |
- 20
- |
-
- E89
- |
-
- 121615.22
- |
-
- BXD89
- |
-
- Female
- |
-
- 444
- |
-
- Eyeball
- |
-
-
- |
- 21
- |
-
- E90
- |
-
- 101014.09
- |
-
- BXD95
- |
-
- Female
- |
-
- 536
- |
-
- Eyeball
- |
-
-
- |
- 22
- |
-
- E99
- |
-
- 121214.15
- |
-
- BXD70
- |
-
- Female
- |
-
- 357
- |
-
- Eyeball
- |
-
-
- |
- 23
- |
-
- E100
- |
-
- 121214.16
- |
-
- BXD70
- |
-
- Female
- |
-
- 357
- |
-
- Eyeball
- |
-
-
- |
- 24
- |
-
- E124
- |
-
- 042214.18
- |
-
- D2B6F1
- |
-
- Male
- |
-
- 397
- |
-
- Eyeball
- |
-
-
- |
- 25
- |
-
- E152
- |
-
- 050912.04
- |
-
- BXD48a
- |
-
- Female
- |
-
- 419
- |
-
- Eyeball
- |
-
-
- |
- 26
- |
-
- E158
- |
-
- 101713.02
- |
-
- BXD100
- |
-
- Female
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 27
- |
-
- E224
- |
-
- 021313.26
- |
-
- BXD84
- |
-
- Female
- |
-
- 385
- |
-
- Eyeball
- |
-
-
- |
- 28
- |
-
- E264
- |
-
- *050318.12
- |
-
- BXD69
- |
-
- Male
- |
-
- 387
- |
-
- Eyeball
- |
-
-
- |
- 29
- |
-
- E288
- |
-
- *110918.106
- |
-
- BXD211
- |
-
- Male
- |
-
- 404
- |
-
- Eyeball
- |
-
-
- |
- 30
- |
-
- E289
- |
-
- *110918.105
- |
-
- BXD211
- |
-
- Female
- |
-
- 404
- |
-
- Eyeball
- |
-
-
- |
- 31
- |
-
- E290
- |
-
- *100218.04
- |
-
- BXD44
- |
-
- Female
- |
-
- 530
- |
-
- Eyeball
- |
-
-
- |
- 32
- |
-
- E291
- |
-
- *100218.05
- |
-
- BXD44
- |
-
- Male
- |
-
- 530
- |
-
- Eyeball
- |
-
-
- |
- 33
- |
-
- E292
- |
-
- *100218.18
- |
-
- BXD68
- |
-
- Female
- |
-
- 516
- |
-
- Eyeball
- |
-
-
- |
- 34
- |
-
- E293
- |
-
- *100218.20
- |
-
- BXD68
- |
-
- Male
- |
-
- 516
- |
-
- Eyeball
- |
-
-
- |
- 35
- |
-
- E294
- |
-
- *100218.36
- |
-
- BXD84
- |
-
- Female
- |
-
- 516
- |
-
- Eyeball
- |
-
-
- |
- 36
- |
-
- E298
- |
-
- *100218.73
- |
-
- BXD184
- |
-
- Female
- |
-
- 512
- |
-
- Eyeball
- |
-
-
- |
- 37
- |
-
- E299
- |
-
- *100218.74
- |
-
- BXD184
- |
-
- Male
- |
-
- 512
- |
-
- Eyeball
- |
-
-
- |
- 38
- |
-
- E303
- |
-
- AGE061218.98
- |
-
- BXD177
- |
-
- Female
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 39
- |
-
- E304
- |
-
- AGE061218.108
- |
-
- BXD195
- |
-
- Male
- |
-
- 386
- |
-
- Eyeball
- |
-
-
- |
- 40
- |
-
- E306
- |
-
- AGE061218.107
- |
-
- BXD195
- |
-
- Female
- |
-
- 386
- |
-
- Eyeball
- |
-
-
- |
- 41
- |
-
- E308
- |
-
- AGE061218.99
- |
-
- BXD177
- |
-
- Male
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 42
- |
-
- E310
- |
-
- AGE061218.90
- |
-
- BXD168
- |
-
- Male
- |
-
- 538
- |
-
- Eyeball
- |
-
-
- |
- 43
- |
-
- E311
- |
-
- AGE061218.85
- |
-
- BXD160
- |
-
- Male
- |
-
- 390
- |
-
- Eyeball
- |
-
-
- |
- 44
- |
-
- E312
- |
-
- AGE061218.71
- |
-
- BXD150
- |
-
- Male
- |
-
- 398
- |
-
- Eyeball
- |
-
-
- |
- 45
- |
-
- E313
- |
-
- AGE061218.22
- |
-
- BXD34
- |
-
- Male
- |
-
- 369
- |
-
- Eyeball
- |
-
-
- |
- 46
- |
-
- E314
- |
-
- AGE061218.21
- |
-
- BXD34
- |
-
- Female
- |
-
- 369
- |
-
- Eyeball
- |
-
-
- |
- 47
- |
-
- E331
- |
-
- *110918.07
- |
-
- BXD28
- |
-
- Male
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 48
- |
-
- E334
- |
-
- *110918.02
- |
-
- BXD18
- |
-
- Male
- |
-
- 452
- |
-
- Eyeball
- |
-
-
- |
- 49
- |
-
- E335
- |
-
- *110918.01
- |
-
- BXD18
- |
-
- Female
- |
-
- 452
- |
-
- Eyeball
- |
-
-
- |
- 50
- |
-
- E340
- |
-
- *110918.51
- |
-
- BXD98
- |
-
- Male
- |
-
- 359
- |
-
- Eyeball
- |
-
-
- |
- 51
- |
-
- E341
- |
-
- *110918.50
- |
-
- BXD98
- |
-
- Female
- |
-
- 359
- |
-
- Eyeball
- |
-
-
- |
- 52
- |
-
- E344
- |
-
- *083019.05
- |
-
- BXD9
- |
-
- Female
- |
-
- 373
- |
-
- Eyeball
- |
-
-
- |
- 53
- |
-
- E345
- |
-
- *083019.06
- |
-
- BXD9
- |
-
- Male
- |
-
- 373
- |
-
- Eyeball
- |
-
-
- |
- 54
- |
-
- E346
- |
-
- *083019.22
- |
-
- BXD31
- |
-
- Male
- |
-
- 391
- |
-
- Eyeball
- |
-
-
- |
- 55
- |
-
- E347
- |
-
- *083019.23
- |
-
- BXD43
- |
-
- Female
- |
-
- 391
- |
-
- Eyeball
- |
-
-
- |
- 56
- |
-
- E349
- |
-
- *083019.26
- |
-
- BXD43
- |
-
- Male
- |
-
- 367
- |
-
- Eyeball
- |
-
-
- |
- 57
- |
-
- E350
- |
-
- *083019.30
- |
-
- BXD50
- |
-
- Female
- |
-
- 408
- |
-
- Eyeball
- |
-
-
- |
- 58
- |
-
- E351
- |
-
- *083019.31
- |
-
- BXD50
- |
-
- Female
- |
-
- 408
- |
-
- Eyeball
- |
-
-
- |
- 59
- |
-
- E352
- |
-
- *083019.33
- |
-
- BXD51
- |
-
- Female
- |
-
- 368
- |
-
- Eyeball
- |
-
-
- |
- 60
- |
-
- E353
- |
-
- *083019.34
- |
-
- BXD51
- |
-
- Male
- |
-
- 368
- |
-
- Eyeball
- |
-
-
- |
- 61
- |
-
- E354
- |
-
- *083019.38
- |
-
- BXD66
- |
-
- Male
- |
-
- 430
- |
-
- Eyeball
- |
-
-
- |
- 62
- |
-
- E355
- |
-
- *083019.39
- |
-
- BXD66
- |
-
- Male
- |
-
- 430
- |
-
- Eyeball
- |
-
-
- |
- 63
- |
-
- E356
- |
-
- *083019.45
- |
-
- BXD73
- |
-
- Female
- |
-
- 451
- |
-
- Eyeball
- |
-
-
- |
- 64
- |
-
- E357
- |
-
- *083019.46
- |
-
- BXD73
- |
-
- Male
- |
-
- 451
- |
-
- Eyeball
- |
-
-
- |
- 65
- |
-
- E358
- |
-
- *083019.48
- |
-
- BXD75
- |
-
- Female
- |
-
- 369
- |
-
- Eyeball
- |
-
-
- |
- 66
- |
-
- E359
- |
-
- *083019.49
- |
-
- BXD75
- |
-
- Male
- |
-
- 369
- |
-
- Eyeball
- |
-
-
- |
- 67
- |
-
- E360
- |
-
- *083019.50
- |
-
- BXD78
- |
-
- Female
- |
-
- 432
- |
-
- Eyeball
- |
-
-
- |
- 68
- |
-
- E361
- |
-
- *083019.51
- |
-
- BXD78
- |
-
- Male
- |
-
- 432
- |
-
- Eyeball
- |
-
-
- |
- 69
- |
-
- E363
- |
-
- *083019.55
- |
-
- BXD87
- |
-
- Female
- |
-
- 444
- |
-
- Eyeball
- |
-
-
- |
- 70
- |
-
- E364
- |
-
- *083019.56
- |
-
- BXD87
- |
-
- Male
- |
-
- 444
- |
-
- Eyeball
- |
-
-
- |
- 71
- |
-
- E365
- |
-
- *083019.57
- |
-
- BXD89
- |
-
- Female
- |
-
- 446
- |
-
- Eyeball
- |
-
-
- |
- 72
- |
-
- E366
- |
-
- *083019.66
- |
-
- BXD113
- |
-
- Female
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 73
- |
-
- E367
- |
-
- *083019.67
- |
-
- BXD113
- |
-
- Male
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 74
- |
-
- E368
- |
-
- *090119.04
- |
-
- BXD123
- |
-
- Female
- |
-
- 441
- |
-
- Eyeball
- |
-
-
- |
- 75
- |
-
- E369
- |
-
- *090119.05
- |
-
- BXD123
- |
-
- Male
- |
-
- 441
- |
-
- Eyeball
- |
-
-
- |
- 76
- |
-
- E370
- |
-
- *090119.09
- |
-
- BXD141
- |
-
- Female
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 77
- |
-
- E371
- |
-
- *090119.11
- |
-
- BXD141
- |
-
- Male
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 78
- |
-
- E372
- |
-
- *090119.15
- |
-
- BXD151
- |
-
- Female
- |
-
- 439
- |
-
- Eyeball
- |
-
-
- |
- 79
- |
-
- E373
- |
-
- *090119.16
- |
-
- BXD151
- |
-
- Male
- |
-
- 439
- |
-
- Eyeball
- |
-
-
- |
- 80
- |
-
- E374
- |
-
- *090119.18
- |
-
- BXD152
- |
-
- Female
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 81
- |
-
- E375
- |
-
- *090119.19
- |
-
- BXD152
- |
-
- Male
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 82
- |
-
- E376
- |
-
- *090119.20
- |
-
- BXD154
- |
-
- Female
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 83
- |
-
- E377
- |
-
- *090119.22
- |
-
- BXD154
- |
-
- Male
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 84
- |
-
- E378
- |
-
- *090119.24
- |
-
- BXD155
- |
-
- Female
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 85
- |
-
- E379
- |
-
- *090119.25
- |
-
- BXD155
- |
-
- Male
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 86
- |
-
- E380
- |
-
- *090119.27
- |
-
- BXD161
- |
-
- Female
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 87
- |
-
- E381
- |
-
- *090119.28
- |
-
- BXD161
- |
-
- Male
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 88
- |
-
- E382
- |
-
- *090119.34
- |
-
- BXD170
- |
-
- Male
- |
-
- 438
- |
-
- Eyeball
- |
-
-
- |
- 89
- |
-
- E383
- |
-
- *090119.36
- |
-
- BXD171
- |
-
- Female
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 90
- |
-
- E384
- |
-
- *090119.37
- |
-
- BXD171
- |
-
- Male
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 91
- |
-
- E385
- |
-
- *090119.41
- |
-
- BXD178
- |
-
- Female
- |
-
- 493
- |
-
- Eyeball
- |
-
-
- |
- 92
- |
-
- E386
- |
-
- *090119.42
- |
-
- BXD178
- |
-
- Female
- |
-
- 493
- |
-
- Eyeball
- |
-
-
- |
- 93
- |
-
- E387
- |
-
- *090119.44
- |
-
- BXD180
- |
-
- Female
- |
-
- 375
- |
-
- Eyeball
- |
-
-
- |
- 94
- |
-
- E390
- |
-
- *090119.48
- |
-
- BXD190
- |
-
- Male
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 95
- |
-
- E391
- |
-
- *090119.52
- |
-
- BXD197
- |
-
- Female
- |
-
- 433
- |
-
- Eyeball
- |
-
-
- |
- 96
- |
-
- E392
- |
-
- *090119.53
- |
-
- BXD197
- |
-
- Male
- |
-
- 433
- |
-
- Eyeball
- |
-
-
- |
- 97
- |
-
- E395
- |
-
- *090119.57
- |
-
- BXD202
- |
-
- Female
- |
-
- 427
- |
-
- Eyeball
- |
-
-
- |
- 98
- |
-
- E399
- |
-
- *090119.67
- |
-
- BXD218
- |
-
- Female
- |
-
- 412
- |
-
- Eyeball
- |
-
-
- |
- 99
- |
-
- E400
- |
-
- *090119.68
- |
-
- BXD218
- |
-
- Male
- |
-
- 412
- |
-
- Eyeball
- |
-
-
- |
- 100
- |
-
- E448
- |
-
- *100819.101
- |
-
- BXD111
- |
-
- Female
- |
-
- 373
- |
-
- Eyeball
- |
-
-
- |
- 101
- |
-
- E449
- |
-
- *100819.102
- |
-
- BXD111
- |
-
- Male
- |
-
- 373
- |
-
- Eyeball
- |
-
-
- |
- 102
- |
-
- E450
- |
-
- *100819.104
- |
-
- BXD122
- |
-
- Female
- |
-
- 383
- |
-
- Eyeball
- |
-
-
- |
- 103
- |
-
- E451
- |
-
- *100819.105
- |
-
- BXD122
- |
-
- Male
- |
-
- 383
- |
-
- Eyeball
- |
-
-
- |
- 104
- |
-
- E452
- |
-
- *100819.107
- |
-
- BXD124
- |
-
- Female
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 105
- |
-
- E453
- |
-
- *100819.108
- |
-
- BXD124
- |
-
- Male
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 106
- |
-
- E454
- |
-
- *100819.110
- |
-
- BXD125
- |
-
- Female
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 107
- |
-
- E455
- |
-
- *100819.111
- |
-
- BXD125
- |
-
- Male
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 108
- |
-
- E459
- |
-
- *100819.131
- |
-
- BXD172
- |
-
- Female
- |
-
- 375
- |
-
- Eyeball
- |
-
-
- |
- 109
- |
-
- E460
- |
-
- *100819.132
- |
-
- BXD172
- |
-
- Male
- |
-
- 375
- |
-
- Eyeball
- |
-
-
- |
- 110
- |
-
- E482
- |
-
- *052220.14
- |
-
- BXD71
- |
-
- Female
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 111
- |
-
- E483
- |
-
- *052220.10
- |
-
- BXD11
- |
-
- Female
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 112
- |
-
- E484
- |
-
- *052220.07
- |
-
- BXD65
- |
-
- Male
- |
-
- 528
- |
-
- Eyeball
- |
-
-
- |
- 113
- |
-
- E485
- |
-
- *052220.03
- |
-
- BXD194
- |
-
- Male
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 114
- |
-
- E486
- |
-
- *052220.19
- |
-
- BXD15
- |
-
- Female
- |
-
- 415
- |
-
- Eyeball
- |
-
-
- |
- 115
- |
-
- E487
- |
-
- *052220.02
- |
-
- BXD194
- |
-
- Female
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 116
- |
-
- E488
- |
-
- *052220.12
- |
-
- BXD1
- |
-
- Female
- |
-
- 429
- |
-
- Eyeball
- |
-
-
- |
- 117
- |
-
- E489
- |
-
- *052220.18
- |
-
- BXD216
- |
-
- Male
- |
-
- 401
- |
-
- Eyeball
- |
-
-
- |
- 118
- |
-
- E490
- |
-
- *052220.13
- |
-
- BXD1
- |
-
- Male
- |
-
- 429
- |
-
- Eyeball
- |
-
-
- |
- 119
- |
-
- E494
- |
-
- *052220.15
- |
-
- BXD71
- |
-
- Male
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 120
- |
-
- E496
- |
-
- *052220.08
- |
-
- BXD170
- |
-
- Male
- |
-
- 360
- |
-
- Eyeball
- |
-
-
- |
- 121
- |
-
- E498
- |
-
- *052220.06
- |
-
- BXD65
- |
-
- Female
- |
-
- 528
- |
-
- Eyeball
- |
-
-
- |
- 122
- |
-
- E499
- |
-
- *052220.05
- |
-
- C57BL/6J
- |
-
- Male
- |
-
- 424
- |
-
- Eyeball
- |
-
-
- |
- 123
- |
-
- E501
- |
-
- *052220.21
- |
-
- BXD73a
- |
-
- Female
- |
-
- 408
- |
-
- Eyeball
- |
-
-
- |
- 124
- |
-
- E502
- |
-
- *052220.11
- |
-
- BXD11
- |
-
- Male
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 125
- |
-
- E503
- |
-
- *052220.22
- |
-
- DBA/2J-Gpnmb
- |
-
- Female
- |
-
- 439
- |
-
- Eyeball
- |
-
-
- |
- 126
- |
-
- E504
- |
-
- *052220.20
- |
-
- BXD15
- |
-
- Male
- |
-
- 415
- |
-
- Eyeball
- |
-
-
- |
- 127
- |
-
- E541
- |
-
- 042915.08
- |
-
- BXD29
- |
-
- Female
- |
-
- 478
- |
-
- Eyeball
- |
-
-
- |
- 128
- |
-
- E542
- |
-
- 050115.01
- |
-
- BXD65b
- |
-
- Female
- |
-
- 415
- |
-
- Eyeball
- |
-
-
- |
- 129
- |
-
- E543
- |
-
- 042915.07
- |
-
- BXD29
- |
-
- Female
- |
-
- 431
- |
-
- Eyeball
- |
-
-
- |
- 130
- |
-
- E544
- |
-
- 042314.12
- |
-
- B6D2F1
- |
-
- Female
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 131
- |
-
- E548
- |
-
- *061119.02
- |
-
- C57BL/6J
- |
-
- Female
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 132
- |
-
- E549
- |
-
- *061119.03
- |
-
- C57BL/6J
- |
-
- Male
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 133
- |
-
- E551
- |
-
- *061119.11
- |
-
- DBA/2J
- |
-
- Female
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 134
- |
-
- E552
- |
-
- *061119.12
- |
-
- DBA/2J
- |
-
- Male
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 135
- |
-
- E554
- |
-
- *061119.15
- |
-
- DBA/2J
- |
-
- Male
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 136
- |
-
- E556
- |
-
- *061119.22
- |
-
- DBA/2J
- |
-
- Male
- |
-
- 380
- |
-
- Eyeball
- |
-
-
- |
- 137
- |
-
- E561
- |
-
- *061219.12
- |
-
- BXD27
- |
-
- Female
- |
-
- 494
- |
-
- Eyeball
- |
-
-
- |
- 138
- |
-
- E564
- |
-
- *061219.14
- |
-
- BXD27
- |
-
- Male
- |
-
- 494
- |
-
- Eyeball
- |
-
-
- |
- 139
- |
-
- E565
- |
-
- *060419.04
- |
-
- BXD32
- |
-
- Female
- |
-
- 425
- |
-
- Eyeball
- |
-
-
- |
- 140
- |
-
- E566
- |
-
- *060419.05
- |
-
- BXD32
- |
-
- Male
- |
-
- 425
- |
-
- Eyeball
- |
-
-
- |
- 141
- |
-
- E567
- |
-
- *070919.01
- |
-
- BXD86
- |
-
- Female
- |
-
- 381
- |
-
- Eyeball
- |
-
-
- |
- 142
- |
-
- E569
- |
-
- *070919.03
- |
-
- BXD86
- |
-
- Male
- |
-
- 381
- |
-
- Eyeball
- |
-
-
- |
- 143
- |
-
- E576
- |
-
- *072519.11
- |
-
- BXD191
- |
-
- Male
- |
-
- 477
- |
-
- Eyeball
- |
-
-
- |
- 144
- |
-
- E577
- |
-
- *072519.09
- |
-
- BXD190
- |
-
- Male
- |
-
- 434
- |
-
- Eyeball
- |
-
-
- |
- 145
- |
-
- E582
- |
-
- *073019.16
- |
-
- BXD216
- |
-
- Male
- |
-
- 459
- |
-
- Eyeball
- |
-
-
- |
- 146
- |
-
- E591
- |
-
- *061319.04
- |
-
- BXD48
- |
-
- Female
- |
-
- 425
- |
-
- Eyeball
- |
-
-
- |
- 147
- |
-
- E592
- |
-
- *061319.05
- |
-
- BXD48
- |
-
- Male
- |
-
- 425
- |
-
- Eyeball
- |
-
-
- |
- 148
- |
-
- E593
- |
-
- *061319.21
- |
-
- BXD61
- |
-
- Male
- |
-
- 459
- |
-
- Eyeball
- |
-
-
- |
- 149
- |
-
- E600
- |
-
- *050318.10
- |
-
- BXD69
- |
-
- Female
- |
-
- 387
- |
-
- Eyeball
- |
-
-
- |
- 150
- |
-
- E601
- |
-
- *013020.53
- |
-
- BXD102
- |
-
- Male
- |
-
- 416
- |
-
- Eyeball
- |
-
-
- |
- 151
- |
-
- E603
- |
-
- *013020.25
- |
-
- BXD65b
- |
-
- Male
- |
-
- 505
- |
-
- Eyeball
- |
-
-
- |
- 152
- |
-
- E605
- |
-
- *013020.54
- |
-
- BXD102
- |
-
- Female
- |
-
- 416
- |
-
- Eyeball
- |
-
-
- |
- 153
- |
-
- E620
- |
-
- *012420.26
- |
-
- BXD128a
- |
-
- Male
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 154
- |
-
- E625
- |
-
- *110918.54
- |
-
- BXD101
- |
-
- Male
- |
-
- 361
- |
-
- Eyeball
- |
-
-
- |
- 155
- |
-
- E626
- |
-
- *110918.53
- |
-
- BXD101
- |
-
- Female
- |
-
- 361
- |
-
- Eyeball
- |
-
-
- |
- 156
- |
-
- E631
- |
-
- *083019.14
- |
-
- BXD16
- |
-
- Female
- |
-
- 363
- |
-
- Eyeball
- |
-
-
- |
- 157
- |
-
- E635
- |
-
- *083019.35
- |
-
- BXD61
- |
-
- Male
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 158
- |
-
- E638
- |
-
- *083019.60
- |
-
- BXD90
- |
-
- Female
- |
-
- 378
- |
-
- Eyeball
- |
-
-
- |
- 159
- |
-
- E639
- |
-
- *083019.62
- |
-
- BXD90
- |
-
- Male
- |
-
- 378
- |
-
- Eyeball
- |
-
-
- |
- 160
- |
-
- E662
- |
-
- *100819.153
- |
-
- BXD202
- |
-
- Male
- |
-
- 410
- |
-
- Eyeball
- |
-
-
- |
- 161
- |
-
- E663
- |
-
- *100819.157
- |
-
- BXD205
- |
-
- Female
- |
-
- 371
- |
-
- Eyeball
- |
-
-
- |
- 162
- |
-
- E664
- |
-
- *100819.158
- |
-
- BXD205
- |
-
- Male
- |
-
- 372
- |
-
- Eyeball
- |
-
-
- |
- 163
- |
-
- E665
- |
-
- *100819.163
- |
-
- BXD213
- |
-
- Female
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 164
- |
-
- E666
- |
-
- *100819.164
- |
-
- BXD213
- |
-
- Male
- |
-
- 397
- |
-
- Eyeball
- |
-
-
- |
- 165
- |
-
- E667
- |
-
- *100819.168
- |
-
- BXD223
- |
-
- Female
- |
-
- 419
- |
-
- Eyeball
- |
-
-
- |
- 166
- |
-
- E668
- |
-
- *100819.169
- |
-
- BXD223
- |
-
- Male
- |
-
- 420
- |
-
- Eyeball
- |
-
-
- |
- 167
- |
-
- E672
- |
-
- *052920.10
- |
-
- BXD83
- |
-
- Male
- |
-
- 380
- |
-
- Eyeball
- |
-
-
- |
- 168
- |
-
- E675
- |
-
- *052920.13
- |
-
- DBA/2J-Gpnmb
- |
-
- Female
- |
-
- 452
- |
-
- Eyeball
- |
-
-
- |
- 169
- |
-
- E679
- |
-
- *052920.12
- |
-
- DBA/2J-Gpnmb
- |
-
- Female
- |
-
- 458
- |
-
- Eyeball
- |
-
-
- |
- 170
- |
-
- E680
- |
-
- *052920.01
- |
-
- BXD43
- |
-
- Female
- |
-
- 465
- |
-
- Eyeball
- |
-
-
- |
- 171
- |
-
- E682
- |
-
- *052920.02
- |
-
- C57BL/6J
- |
-
- Female
- |
-
- 433
- |
-
- Eyeball
- |
-
-
- |
- 172
- |
-
- E685
- |
-
- *052920.09
- |
-
- BXD83
- |
-
- Female
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 173
- |
-
- E699
- |
-
- *072120.14
- |
-
- BXD40
- |
-
- Male
- |
-
- 458
- |
-
- Eyeball
- |
-
-
- |
- 174
- |
-
- E709
- |
-
- *072120.24
- |
-
- BXD150
- |
-
- Female
- |
-
- 433
- |
-
- Eyeball
- |
-
-
- |
- 175
- |
-
- E712
- |
-
- *072120.27
- |
-
- BXD160
- |
-
- Female
- |
-
- 367
- |
-
- Eyeball
- |
-
-
- |
- 176
- |
-
- E726
- |
-
- *072120.41
- |
-
- BXD16
- |
-
- Female
- |
-
- 367
- |
-
- Eyeball
- |
-
-
- |
- 177
- |
-
- E733
- |
-
- *072120.48
- |
-
- BXD60
- |
-
- Female
- |
-
- 558
- |
-
- Eyeball
- |
-
-
- |
- 178
- |
-
- E735
- |
-
- *072120.50
- |
-
- BXD180
- |
-
- Male
- |
-
- 473
- |
-
- Eyeball
- |
-
-
- |
- 179
- |
-
- E738
- |
-
- *072120.53
- |
-
- BXD128a
- |
-
- Female
- |
-
- 387
- |
-
- Eyeball
- |
-
-
- |
- 180
- |
-
- E745
- |
-
- *072120.60
- |
-
- BXD199
- |
-
- Female
- |
-
- 457
- |
-
- Eyeball
- |
-
-
- |
- 181
- |
-
- E746
- |
-
- *072120.61
- |
-
- BXD199
- |
-
- Male
- |
-
- 457
- |
-
- Eyeball
- |
-
-
- |
- 182
- |
-
- E749
- |
-
- *072120.64
- |
-
- BXD2
- |
-
- Female
- |
-
- 399
- |
-
- Eyeball
- |
-
-
- |
- 183
- |
-
- E750
- |
-
- *072120.65
- |
-
- BXD2
- |
-
- Male
- |
-
- 399
- |
-
- Eyeball
- |
-
-
- |
- 184
- |
-
- E753
- |
-
- *072120.68
- |
-
- BXD169
- |
-
- Female
- |
-
- 441
- |
-
- Eyeball
- |
-
-
- |
- 185
- |
-
- E754
- |
-
- *072120.69
- |
-
- BXD169
- |
-
- Male
- |
-
- 441
- |
-
- Eyeball
- |
-
-
- |
- 186
- |
-
- E759
- |
-
- *072120.72
- |
-
- BXD187
- |
-
- Female
- |
-
- 354
- |
-
- Eyeball
- |
-
-
- |
- 187
- |
-
- E760
- |
-
- *072120.73
- |
-
- BXD187
- |
-
- Male
- |
-
- 354
- |
-
- Eyeball
- |
-
-
-
-
-
diff --git a/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/experiment-design.rtf b/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/experiment-design.rtf
deleted file mode 100644
index e7afcee..0000000
--- a/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA Extraction
-
-Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. according to the manufacturer’s instructions. Approximately 30 mg of PFC tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 7.0 were used for library preparation
diff --git a/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/notes.rtf b/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/notes.rtf
deleted file mode 100644
index d622df7..0000000
--- a/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/notes.rtf
+++ /dev/null
@@ -1 +0,0 @@
-UTHSC BXD Young Aged Eye RNA-Seq (Apr22) DESeq2 rlog2
diff --git a/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/processing.rtf b/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/processing.rtf
deleted file mode 100644
index 7ddb89f..0000000
--- a/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (mm11 Mus_musculus.GRCm39, release 104) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Rows with no gene symbol name were deleted. Indices of the reference genome were built using STAR version 2.5.2b and paired-end reads were aligned to the reference genome. FeatureCount from package RsubRead, version 1.32.4, was used to count the number of read mapped to each gene. Raw counts were then normalized and log2 transformed using function rlogTransformation from the DESeq2 package (version 1.16.1) and an increment was added to the normalized values to make all values positive.
diff --git a/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/tissue.rtf b/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/tissue.rtf
deleted file mode 100644
index 126ab9f..0000000
--- a/general/datasets/UTHSC_BXDYgEyeRNAseq_DESeq2_rlog2_0422/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Tissue Harvest
-
-The animals were sacrificed under saturated isoflurane. Eyeballs from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/UTHSC_BXD_AgeHipp0515/cases.rtf b/general/datasets/UTHSC_BXD_AgeHipp0515/cases.rtf
deleted file mode 100644
index 2b37c95..0000000
--- a/general/datasets/UTHSC_BXD_AgeHipp0515/cases.rtf
+++ /dev/null
@@ -1,1258 +0,0 @@
-The study includes 137 mice (11~25 months old) from 73 strains (B6, D2, DBF1, and 70 BXD strains). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
-
-The table of samples that are finally used for this study:
-
-
-
-
-
-
-
-
-
-
-
-
- | Index |
- Strain |
- Sex |
- RNA ID |
- Age |
- Phase |
- Tissue |
-
-
- | 1 |
- BXD1 |
- F |
- R7281H |
- 448 |
- II |
- Hippocampus |
-
-
- | 2 |
- BXD1 |
- M |
- R7276H |
- 323 |
- II |
- Hippocampus |
-
-
- | 3 |
- BXD2 |
- M |
- R7261H |
- 394 |
- I |
- Hippocampus |
-
-
- | 4 |
- BXD2 |
- F |
- R7256H |
- 456 |
- I |
- Hippocampus |
-
-
- | 5 |
- BXD6 |
- M |
- R7223H |
- 526 |
- I |
- Hippocampus |
-
-
- | 6 |
- BXD8 |
- M |
- R7203H |
- 471 |
- I |
- Hippocampus |
-
-
- | 7 |
- BXD8 |
- F |
- R7200H |
- 460 |
- I |
- Hippocampus |
-
-
- | 8 |
- BXD8 |
- F |
- R7198H |
- 433 |
- I |
- Hippocampus |
-
-
- | 9 |
- BXD9 |
- F |
- R7294H |
- 456 |
- II |
- Hippocampus |
-
-
- | 10 |
- BXD11 |
- M |
- R7300H |
- 457 |
- II |
- Hippocampus |
-
-
- | 11 |
- BXD11 |
- F |
- R7227H |
- 536 |
- I |
- Hippocampus |
-
-
- | 12 |
- BXD12 |
- F |
- R7183H |
- 506 |
- I |
- Hippocampus |
-
-
- | 13 |
- BXD12 |
- F |
- R7233H |
- 561 |
- I |
- Hippocampus |
-
-
- | 14 |
- BXD12 |
- M |
- R7234H |
- 606 |
- I |
- Hippocampus |
-
-
- | 15 |
- BXD14 |
- F |
- R7238H |
- 605 |
- I |
- Hippocampus |
-
-
- | 16 |
- BXD14 |
- M |
- R7235H |
- 605 |
- I |
- Hippocampus |
-
-
- | 17 |
- BXD16 |
- F |
- R7236H |
- 561 |
- I |
- Hippocampus |
-
-
- | 18 |
- BXD16 |
- M |
- R7239H |
- 475 |
- I |
- Hippocampus |
-
-
- | 19 |
- BXD18 |
- F |
- R7229H |
- 493 |
- I |
- Hippocampus |
-
-
- | 20 |
- BXD19 |
- F |
- R7267H |
- 551 |
- I |
- Hippocampus |
-
-
- | 21 |
- BXD19 |
- M |
- R7268H |
- 492 |
- I |
- Hippocampus |
-
-
- | 22 |
- BXD20 |
- M |
- R7232H |
- 506 |
- I |
- Hippocampus |
-
-
- | 23 |
- BXD20 |
- M |
- R7263H |
- 489 |
- I |
- Hippocampus |
-
-
- | 24 |
- BXD21 |
- F |
- R7230H |
- 537 |
- I |
- Hippocampus |
-
-
- | 25 |
- BXD22 |
- F |
- R7260H |
- 502 |
- I |
- Hippocampus |
-
-
- | 26 |
- BXD22 |
- M |
- R7262H |
- 596 |
- I |
- Hippocampus |
-
-
- | 27 |
- BXD23 |
- F |
- R7258H |
- 502 |
- I |
- Hippocampus |
-
-
- | 28 |
- BXD23 |
- M |
- R7257H |
- 462 |
- I |
- Hippocampus |
-
-
- | 29 |
- BXD24 |
- M |
- R7231H |
- 470 |
- I |
- Hippocampus |
-
-
- | 30 |
- BXD24 |
- F |
- R7228H |
- 415 |
- I |
- Hippocampus |
-
-
- | 31 |
- BXD24 |
- F |
- R7255H |
- 456 |
- I |
- Hippocampus |
-
-
- | 32 |
- BXD25 |
- F |
- R7252H |
- 454 |
- I |
- Hippocampus |
-
-
- | 33 |
- BXD27 |
- F |
- R7286H |
- 472 |
- II |
- Hippocampus |
-
-
- | 34 |
- BXD27 |
- F |
- R7170H |
- 472 |
- I |
- Hippocampus |
-
-
- | 35 |
- BXD28 |
- M |
- R7254H |
- 493 |
- I |
- Hippocampus |
-
-
- | 36 |
- BXD28 |
- F |
- R7251H |
- 543 |
- I |
- Hippocampus |
-
-
- | 37 |
- BXD29 |
- F |
- R7259H |
- 483 |
- I |
- Hippocampus |
-
-
- | 38 |
- BXD33 |
- M |
- R7253H |
- 464 |
- I |
- Hippocampus |
-
-
- | 39 |
- BXD33 |
- F |
- R7174H |
- 471 |
- I |
- Hippocampus |
-
-
- | 40 |
- BXD33 |
- F |
- R7244H |
- 448 |
- I |
- Hippocampus |
-
-
- | 41 |
- BXD33 |
- M |
- R7270H |
- 662 |
- I |
- Hippocampus |
-
-
- | 42 |
- BXD38 |
- F |
- R7242H |
- 464 |
- I |
- Hippocampus |
-
-
- | 43 |
- BXD38 |
- M |
- R7247H |
- 446 |
- I |
- Hippocampus |
-
-
- | 44 |
- BXD39 |
- M |
- R7250H |
- 536 |
- I |
- Hippocampus |
-
-
- | 45 |
- BXD39 |
- F |
- R7173H |
- 500 |
- I |
- Hippocampus |
-
-
- | 46 |
- BXD39 |
- M |
- R7175H |
- 500 |
- I |
- Hippocampus |
-
-
- | 47 |
- BXD40 |
- F |
- R7288H |
- 451 |
- II |
- Hippocampus |
-
-
- | 48 |
- BXD40 |
- M |
- R7210H |
- 470 |
- I |
- Hippocampus |
-
-
- | 49 |
- BXD40 |
- M |
- R7197H |
- 614 |
- I |
- Hippocampus |
-
-
- | 50 |
- BXD42 |
- F |
- R7280H |
- 518 |
- II |
- Hippocampus |
-
-
- | 51 |
- BXD42 |
- M |
- R7246H |
- 446 |
- I |
- Hippocampus |
-
-
- | 52 |
- BXD42 |
- F |
- R7266H |
- 486 |
- I |
- Hippocampus |
-
-
- | 53 |
- BXD43 |
- F |
- R7249H |
- 454 |
- I |
- Hippocampus |
-
-
- | 54 |
- BXD43 |
- M |
- R7248H |
- 462 |
- I |
- Hippocampus |
-
-
- | 55 |
- BXD44 |
- M |
- R7241H |
- 415 |
- I |
- Hippocampus |
-
-
- | 56 |
- BXD44 |
- M |
- R7279H |
- 419 |
- II |
- Hippocampus |
-
-
- | 57 |
- BXD44 |
- F |
- R7243H |
- 438 |
- I |
- Hippocampus |
-
-
- | 58 |
- BXD45 |
- F |
- R7176H |
- 451 |
- I |
- Hippocampus |
-
-
- | 59 |
- BXD48 |
- F |
- R7245H |
- 499 |
- I |
- Hippocampus |
-
-
- | 60 |
- BXD48 |
- M |
- R7220H |
- 526 |
- I |
- Hippocampus |
-
-
- | 61 |
- BXD48a |
- F |
- R7299H |
- 479 |
- II |
- Hippocampus |
-
-
- | 62 |
- BXD48a |
- M |
- R7297H |
- 479 |
- II |
- Hippocampus |
-
-
- | 63 |
- BXD50 |
- F |
- R7224H |
- 530 |
- I |
- Hippocampus |
-
-
- | 64 |
- BXD50 |
- M |
- R7221H |
- 530 |
- I |
- Hippocampus |
-
-
- | 65 |
- BXD51 |
- F |
- R7177H |
- 487 |
- I |
- Hippocampus |
-
-
- | 66 |
- BXD51 |
- M |
- R7290H |
- 407 |
- II |
- Hippocampus |
-
-
- | 67 |
- BXD55 |
- M |
- R7222H |
- 528 |
- I |
- Hippocampus |
-
-
- | 68 |
- BXD55 |
- F |
- R7225H |
- 587 |
- I |
- Hippocampus |
-
-
- | 69 |
- BXD56 |
- M |
- R7178H |
- 501 |
- I |
- Hippocampus |
-
-
- | 70 |
- BXD62 |
- M |
- R7291H |
- 439 |
- II |
- Hippocampus |
-
-
- | 71 |
- BXD63 |
- M |
- R7218H |
- 438 |
- I |
- Hippocampus |
-
-
- | 72 |
- BXD63 |
- F |
- R7215H |
- 475 |
- I |
- Hippocampus |
-
-
- | 73 |
- BXD64 |
- M |
- R7219H |
- 528 |
- I |
- Hippocampus |
-
-
- | 74 |
- BXD64 |
- F |
- R7216H |
- 587 |
- I |
- Hippocampus |
-
-
- | 75 |
- BXD65 |
- F |
- R7217H |
- 425 |
- I |
- Hippocampus |
-
-
- | 76 |
- BXD65a |
- F |
- R7273H |
- 389 |
- II |
- Hippocampus |
-
-
- | 77 |
- BXD65a |
- M |
- R7277H |
- 715 |
- II |
- Hippocampus |
-
-
- | 78 |
- BXD65b |
- M |
- R7271H |
- 483 |
- II |
- Hippocampus |
-
-
- | 79 |
- BXD66 |
- M |
- R7214H |
- 463 |
- I |
- Hippocampus |
-
-
- | 80 |
- BXD66 |
- F |
- R7302H |
- 446 |
- III |
- Hippocampus |
-
-
- | 81 |
- BXD67 |
- F |
- R7240H |
- 499 |
- I |
- Hippocampus |
-
-
- | 82 |
- BXD67 |
- M |
- R7213H |
- 425 |
- I |
- Hippocampus |
-
-
- | 83 |
- BXD67 |
- F |
- R7278H |
- 415 |
- II |
- Hippocampus |
-
-
- | 84 |
- BXD68 |
- M |
- R7212H |
- 421 |
- I |
- Hippocampus |
-
-
- | 85 |
- BXD68 |
- F |
- R7211H |
- 415 |
- I |
- Hippocampus |
-
-
- | 86 |
- BXD69 |
- F |
- R7305H |
- 504 |
- III |
- Hippocampus |
-
-
- | 87 |
- BXD70 |
- F |
- R7207H |
- 458 |
- I |
- Hippocampus |
-
-
- | 88 |
- BXD70 |
- M |
- R7204H |
- 460 |
- I |
- Hippocampus |
-
-
- | 89 |
- BXD71 |
- M |
- R7205H |
- 471 |
- I |
- Hippocampus |
-
-
- | 90 |
- BXD71 |
- F |
- R7208H |
- 474 |
- I |
- Hippocampus |
-
-
- | 91 |
- BXD73 |
- F |
- R7209H |
- 470 |
- I |
- Hippocampus |
-
-
- | 92 |
- BXD73 |
- M |
- R7206H |
- 464 |
- I |
- Hippocampus |
-
-
- | 93 |
- BXD73a |
- F |
- R7181H |
- 443 |
- I |
- Hippocampus |
-
-
- | 94 |
- BXD73a |
- M |
- R7182H |
- 614 |
- I |
- Hippocampus |
-
-
- | 95 |
- BXD76 |
- M |
- R7179H |
- 579 |
- I |
- Hippocampus |
-
-
- | 96 |
- BXD76 |
- F |
- R7188H |
- 408 |
- I |
- Hippocampus |
-
-
- | 97 |
- BXD76 |
- M |
- R7187H |
- 564 |
- I |
- Hippocampus |
-
-
- | 98 |
- BXD77 |
- M |
- R7292H |
- 347 |
- II |
- Hippocampus |
-
-
- | 99 |
- BXD77 |
- F |
- R7201H |
- 454 |
- I |
- Hippocampus |
-
-
- | 100 |
- BXD79 |
- M |
- R7202H |
- 485 |
- I |
- Hippocampus |
-
-
- | 101 |
- BXD79 |
- F |
- R7199H |
- 515 |
- I |
- Hippocampus |
-
-
- | 102 |
- BXD79 |
- M |
- R7298H |
- 704 |
- II |
- Hippocampus |
-
-
- | 103 |
- BXD81 |
- M |
- R7196H |
- 515 |
- I |
- Hippocampus |
-
-
- | 104 |
- BXD81 |
- F |
- R7190H |
- 458 |
- I |
- Hippocampus |
-
-
- | 105 |
- BXD83 |
- M |
- R7184H |
- 441 |
- I |
- Hippocampus |
-
-
- | 106 |
- BXD84 |
- M |
- R7195H |
- 474 |
- I |
- Hippocampus |
-
-
- | 107 |
- BXD84 |
- M |
- R7296H |
- 484 |
- II |
- Hippocampus |
-
-
- | 108 |
- BXD84 |
- F |
- R7192H |
- 522 |
- I |
- Hippocampus |
-
-
- | 109 |
- BXD85 |
- M |
- R7272H |
- 425 |
- II |
- Hippocampus |
-
-
- | 110 |
- BXD85 |
- F |
- R7193H |
- 506 |
- I |
- Hippocampus |
-
-
- | 111 |
- BXD86 |
- M |
- R7191H |
- 425 |
- I |
- Hippocampus |
-
-
- | 112 |
- BXD87 |
- F |
- R7194H |
- 425 |
- I |
- Hippocampus |
-
-
- | 113 |
- BXD87 |
- M |
- R7303H |
- 478 |
- III |
- Hippocampus |
-
-
- | 114 |
- BXD87 |
- M |
- R7186H |
- 442 |
- I |
- Hippocampus |
-
-
- | 115 |
- BXD89 |
- F |
- R7295H |
- 446 |
- II |
- Hippocampus |
-
-
- | 116 |
- BXD90 |
- M |
- R7287H |
- 434 |
- II |
- Hippocampus |
-
-
- | 117 |
- BXD90 |
- M |
- R7293H |
- 558 |
- II |
- Hippocampus |
-
-
- | 118 |
- BXD95 |
- F |
- R7180H |
- 467 |
- I |
- Hippocampus |
-
-
- | 119 |
- BXD95 |
- M |
- R7169H |
- 467 |
- I |
- Hippocampus |
-
-
- | 120 |
- BXD98 |
- M |
- R7237H |
- 605 |
- I |
- Hippocampus |
-
-
- | 121 |
- BXD98 |
- F |
- R7171H |
- 639 |
- I |
- Hippocampus |
-
-
- | 122 |
- BXD98 |
- F |
- R7275H |
- 488 |
- II |
- Hippocampus |
-
-
- | 123 |
- BXD99 |
- M |
- R7189H |
- 524 |
- I |
- Hippocampus |
-
-
- | 124 |
- BXD99 |
- F |
- R7172H |
- 471 |
- I |
- Hippocampus |
-
-
- | 125 |
- BXD100 |
- F |
- R7282H |
- 463 |
- II |
- Hippocampus |
-
-
- | 126 |
- BXD100 |
- M |
- R7283H |
- 507 |
- II |
- Hippocampus |
-
-
- | 127 |
- BXD100 |
- M |
- R7274H |
- 577 |
- II |
- Hippocampus |
-
-
- | 128 |
- BXD100 |
- F |
- R7226H |
- 464 |
- I |
- Hippocampus |
-
-
- | 129 |
- BXD101 |
- F |
- R7284H |
- 490 |
- II |
- Hippocampus |
-
-
- | 130 |
- BXD101 |
- M |
- R7285H |
- 408 |
- II |
- Hippocampus |
-
-
- | 131 |
- C57BL/6J |
- M |
- R7264H |
- 489 |
- I |
- Hippocampus |
-
-
- | 132 |
- C57BL/6J |
- M |
- R7289H |
- 756 |
- II |
- Hippocampus |
-
-
- | 133 |
- D2B6F1 |
- M |
- R7265H |
- 492 |
- I |
- Hippocampus |
-
-
- | 134 |
- D2B6F1 |
- F |
- R7304H |
- 495 |
- III |
- Hippocampus |
-
-
- | 135 |
- DBA/2J |
- F |
- R7185H |
- 433 |
- I |
- Hippocampus |
-
-
- | 136 |
- DBA/2J |
- M |
- R7269H |
- 367 |
- I |
- Hippocampus |
-
-
- | 137 |
- DBA/2J |
- F |
- R7301H |
- 566 |
- III |
- Hippocampus |
-
-
-
diff --git a/general/datasets/UTHSC_BXD_AgeHipp0515/experiment-design.rtf b/general/datasets/UTHSC_BXD_AgeHipp0515/experiment-design.rtf
deleted file mode 100644
index d6b2d5b..0000000
--- a/general/datasets/UTHSC_BXD_AgeHipp0515/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA Extraction
-
-RNA was extracted using the RNeasy mini kit (Qiagen, Valencia, CA, USA) according to the manufactures’ procedure. 2100 BioAnalyzer (Agilent Technologies) was used to evaluate RNA integrity and quality. Samples with RNA Integrity Numbers (RIN values) > 8.0 were run on Affy MoGene1.0 ST at the UTHSC
diff --git a/general/datasets/UTHSC_BXD_AgeHipp0515/processing.rtf b/general/datasets/UTHSC_BXD_AgeHipp0515/processing.rtf
deleted file mode 100644
index e951515..0000000
--- a/general/datasets/UTHSC_BXD_AgeHipp0515/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-About data processing:
-
-Raw microarray data were normalized using the Robust Multichip Array (RMA) method. The expression data were then re-normalized using a modified Z score.
diff --git a/general/datasets/UTHSC_BXD_AgeHipp0515/specifics.rtf b/general/datasets/UTHSC_BXD_AgeHipp0515/specifics.rtf
deleted file mode 100644
index 3d4ba9a..0000000
--- a/general/datasets/UTHSC_BXD_AgeHipp0515/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-UTHSC BXD Aged Hippocampus Affy MoGene1.0 ST (May15) RMA Gene Level **
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_AgeHipp0515/tissue.rtf b/general/datasets/UTHSC_BXD_AgeHipp0515/tissue.rtf
deleted file mode 100644
index 3166717..0000000
--- a/general/datasets/UTHSC_BXD_AgeHipp0515/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Tissue Harvest
-
-The animals were sacrificed under saturated isoflurane. Hippocampus from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/UTHSC_BXD_Aged_Eye_RNAseq_TPM_Log2_1120/experiment-design.rtf b/general/datasets/UTHSC_BXD_Aged_Eye_RNAseq_TPM_Log2_1120/experiment-design.rtf
deleted file mode 100644
index 2f8cedc..0000000
--- a/general/datasets/UTHSC_BXD_Aged_Eye_RNAseq_TPM_Log2_1120/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Total RNA was extracted using Trizol® reagent (Invitrogen, Grand Island, NY, USA) according to the manufacturer’s instructions. Approximately 30 mg of PFC tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been treated with DNase to avoid DNA contamination, and verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/UTHSC_BXD_Aged_Eye_RNAseq_TPM_Log2_1120/processing.rtf b/general/datasets/UTHSC_BXD_Aged_Eye_RNAseq_TPM_Log2_1120/processing.rtf
deleted file mode 100644
index 8e460ff..0000000
--- a/general/datasets/UTHSC_BXD_Aged_Eye_RNAseq_TPM_Log2_1120/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/UTHSC_BXD_Aged_Eye_RNAseq_TPM_Log2_1120/specifics.rtf b/general/datasets/UTHSC_BXD_Aged_Eye_RNAseq_TPM_Log2_1120/specifics.rtf
deleted file mode 100644
index 4d2bd9f..0000000
--- a/general/datasets/UTHSC_BXD_Aged_Eye_RNAseq_TPM_Log2_1120/specifics.rtf
+++ /dev/null
@@ -1,4332 +0,0 @@
-BXD Eye (12~18 Month) RNA-Seq (Oct30) TPM Log2
-
-The table of samples that are finally used for this study.
-
-
-
-
- |
- Index
- |
-
- RNA ID
- |
-
- case ID
- |
-
- DA_corrected_strain
- |
-
- Corrected Sex
- |
-
- AgeAtDeath days
- |
-
- Tissue
- |
-
-
- |
- 1
- |
-
- E18
- |
-
- 050115.16
- |
-
- BXD75
- |
-
- Female
- |
-
- 460
- |
-
- Eyeball
- |
-
-
- |
- 2
- |
-
- E19
- |
-
- 050115.17
- |
-
- BXD75
- |
-
- Female
- |
-
- 460
- |
-
- Eyeball
- |
-
-
- |
- 3
- |
-
- E21
- |
-
- 042715.10
- |
-
- D2B6F1
- |
-
- Female
- |
-
- 500
- |
-
- Eyeball
- |
-
-
- |
- 4
- |
-
- E22
- |
-
- 050115.19
- |
-
- BXD79
- |
-
- Female
- |
-
- 468
- |
-
- Eyeball
- |
-
-
- |
- 5
- |
-
- E31
- |
-
- 121515.13
- |
-
- BXD45
- |
-
- Female
- |
-
- 507
- |
-
- Eyeball
- |
-
-
- |
- 6
- |
-
- E33
- |
-
- 012615.10
- |
-
- BXD45
- |
-
- Female
- |
-
- 384
- |
-
- Eyeball
- |
-
-
- |
- 7
- |
-
- E34
- |
-
- 012615.04
- |
-
- BXD62
- |
-
- Female
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 8
- |
-
- E40
- |
-
- 021213.21
- |
-
- BXD79
- |
-
- Female
- |
-
- 378
- |
-
- Eyeball
- |
-
-
- |
- 9
- |
-
- E49
- |
-
- 021213.13
- |
-
- BXD60
- |
-
- Female
- |
-
- 530
- |
-
- Eyeball
- |
-
-
- |
- 10
- |
-
- E60
- |
-
- 101713.01
- |
-
- BXD60
- |
-
- Female
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 11
- |
-
- E62
- |
-
- 090612.07
- |
-
- BXD73b
- |
-
- Female
- |
-
- 377
- |
-
- Eyeball
- |
-
-
- |
- 12
- |
-
- E63
- |
-
- 090612.08
- |
-
- BXD73b
- |
-
- Female
- |
-
- 377
- |
-
- Eyeball
- |
-
-
- |
- 13
- |
-
- E65
- |
-
- 050912.04
- |
-
- BXD34
- |
-
- Female
- |
-
- 419
- |
-
- Eyeball
- |
-
-
- |
- 14
- |
-
- E67
- |
-
- 42214.08
- |
-
- BXD40
- |
-
- Female
- |
-
- 362
- |
-
- Eyeball
- |
-
-
- |
- 15
- |
-
- E72
- |
-
- 42214.04
- |
-
- BXD24
- |
-
- Female
- |
-
- 377
- |
-
- Eyeball
- |
-
-
- |
- 16
- |
-
- E75
- |
-
- 42214.03
- |
-
- BXD24
- |
-
- Female
- |
-
- 377
- |
-
- Eyeball
- |
-
-
- |
- 17
- |
-
- E78
- |
-
- 42314.1
- |
-
- B6D2F1
- |
-
- Male
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 18
- |
-
- E82
- |
-
- 121615.05
- |
-
- BXD62
- |
-
- Female
- |
-
- 525
- |
-
- Eyeball
- |
-
-
- |
- 19
- |
-
- E87
- |
-
- 101014.10
- |
-
- BXD95
- |
-
- Female
- |
-
- 536
- |
-
- Eyeball
- |
-
-
- |
- 20
- |
-
- E89
- |
-
- 121615.22
- |
-
- BXD89
- |
-
- Female
- |
-
- 444
- |
-
- Eyeball
- |
-
-
- |
- 21
- |
-
- E90
- |
-
- 101014.09
- |
-
- BXD95
- |
-
- Female
- |
-
- 536
- |
-
- Eyeball
- |
-
-
- |
- 22
- |
-
- E99
- |
-
- 121214.15
- |
-
- BXD70
- |
-
- Female
- |
-
- 357
- |
-
- Eyeball
- |
-
-
- |
- 23
- |
-
- E100
- |
-
- 121214.16
- |
-
- BXD70
- |
-
- Female
- |
-
- 357
- |
-
- Eyeball
- |
-
-
- |
- 24
- |
-
- E124
- |
-
- 042214.18
- |
-
- D2B6F1
- |
-
- Male
- |
-
- 397
- |
-
- Eyeball
- |
-
-
- |
- 25
- |
-
- E152
- |
-
- 050912.04
- |
-
- BXD48a
- |
-
- Female
- |
-
- 419
- |
-
- Eyeball
- |
-
-
- |
- 26
- |
-
- E158
- |
-
- 101713.02
- |
-
- BXD100
- |
-
- Female
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 27
- |
-
- E224
- |
-
- 021313.26
- |
-
- BXD84
- |
-
- Female
- |
-
- 385
- |
-
- Eyeball
- |
-
-
- |
- 28
- |
-
- E264
- |
-
- *050318.12
- |
-
- BXD69
- |
-
- Male
- |
-
- 387
- |
-
- Eyeball
- |
-
-
- |
- 29
- |
-
- E288
- |
-
- *110918.106
- |
-
- BXD211
- |
-
- Male
- |
-
- 404
- |
-
- Eyeball
- |
-
-
- |
- 30
- |
-
- E289
- |
-
- *110918.105
- |
-
- BXD211
- |
-
- Female
- |
-
- 404
- |
-
- Eyeball
- |
-
-
- |
- 31
- |
-
- E290
- |
-
- *100218.04
- |
-
- BXD44
- |
-
- Female
- |
-
- 530
- |
-
- Eyeball
- |
-
-
- |
- 32
- |
-
- E291
- |
-
- *100218.05
- |
-
- BXD44
- |
-
- Male
- |
-
- 530
- |
-
- Eyeball
- |
-
-
- |
- 33
- |
-
- E292
- |
-
- *100218.18
- |
-
- BXD68
- |
-
- Female
- |
-
- 516
- |
-
- Eyeball
- |
-
-
- |
- 34
- |
-
- E293
- |
-
- *100218.20
- |
-
- BXD68
- |
-
- Male
- |
-
- 516
- |
-
- Eyeball
- |
-
-
- |
- 35
- |
-
- E294
- |
-
- *100218.36
- |
-
- BXD84
- |
-
- Female
- |
-
- 516
- |
-
- Eyeball
- |
-
-
- |
- 36
- |
-
- E298
- |
-
- *100218.73
- |
-
- BXD184
- |
-
- Female
- |
-
- 512
- |
-
- Eyeball
- |
-
-
- |
- 37
- |
-
- E299
- |
-
- *100218.74
- |
-
- BXD184
- |
-
- Male
- |
-
- 512
- |
-
- Eyeball
- |
-
-
- |
- 38
- |
-
- E303
- |
-
- AGE061218.98
- |
-
- BXD177
- |
-
- Female
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 39
- |
-
- E304
- |
-
- AGE061218.108
- |
-
- BXD195
- |
-
- Male
- |
-
- 386
- |
-
- Eyeball
- |
-
-
- |
- 40
- |
-
- E306
- |
-
- AGE061218.107
- |
-
- BXD195
- |
-
- Female
- |
-
- 386
- |
-
- Eyeball
- |
-
-
- |
- 41
- |
-
- E308
- |
-
- AGE061218.99
- |
-
- BXD177
- |
-
- Male
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 42
- |
-
- E310
- |
-
- AGE061218.90
- |
-
- BXD168
- |
-
- Male
- |
-
- 538
- |
-
- Eyeball
- |
-
-
- |
- 43
- |
-
- E311
- |
-
- AGE061218.85
- |
-
- BXD160
- |
-
- Male
- |
-
- 390
- |
-
- Eyeball
- |
-
-
- |
- 44
- |
-
- E312
- |
-
- AGE061218.71
- |
-
- BXD150
- |
-
- Male
- |
-
- 398
- |
-
- Eyeball
- |
-
-
- |
- 45
- |
-
- E313
- |
-
- AGE061218.22
- |
-
- BXD34
- |
-
- Male
- |
-
- 369
- |
-
- Eyeball
- |
-
-
- |
- 46
- |
-
- E314
- |
-
- AGE061218.21
- |
-
- BXD34
- |
-
- Female
- |
-
- 369
- |
-
- Eyeball
- |
-
-
- |
- 47
- |
-
- E331
- |
-
- *110918.07
- |
-
- BXD28
- |
-
- Male
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 48
- |
-
- E334
- |
-
- *110918.02
- |
-
- BXD18
- |
-
- Male
- |
-
- 452
- |
-
- Eyeball
- |
-
-
- |
- 49
- |
-
- E335
- |
-
- *110918.01
- |
-
- BXD18
- |
-
- Female
- |
-
- 452
- |
-
- Eyeball
- |
-
-
- |
- 50
- |
-
- E340
- |
-
- *110918.51
- |
-
- BXD98
- |
-
- Male
- |
-
- 359
- |
-
- Eyeball
- |
-
-
- |
- 51
- |
-
- E341
- |
-
- *110918.50
- |
-
- BXD98
- |
-
- Female
- |
-
- 359
- |
-
- Eyeball
- |
-
-
- |
- 52
- |
-
- E344
- |
-
- *083019.05
- |
-
- BXD9
- |
-
- Female
- |
-
- 373
- |
-
- Eyeball
- |
-
-
- |
- 53
- |
-
- E345
- |
-
- *083019.06
- |
-
- BXD9
- |
-
- Male
- |
-
- 373
- |
-
- Eyeball
- |
-
-
- |
- 54
- |
-
- E346
- |
-
- *083019.22
- |
-
- BXD31
- |
-
- Male
- |
-
- 391
- |
-
- Eyeball
- |
-
-
- |
- 55
- |
-
- E347
- |
-
- *083019.23
- |
-
- BXD43
- |
-
- Female
- |
-
- 391
- |
-
- Eyeball
- |
-
-
- |
- 56
- |
-
- E349
- |
-
- *083019.26
- |
-
- BXD43
- |
-
- Male
- |
-
- 367
- |
-
- Eyeball
- |
-
-
- |
- 57
- |
-
- E350
- |
-
- *083019.30
- |
-
- BXD50
- |
-
- Female
- |
-
- 408
- |
-
- Eyeball
- |
-
-
- |
- 58
- |
-
- E351
- |
-
- *083019.31
- |
-
- BXD50
- |
-
- Female
- |
-
- 408
- |
-
- Eyeball
- |
-
-
- |
- 59
- |
-
- E352
- |
-
- *083019.33
- |
-
- BXD51
- |
-
- Female
- |
-
- 368
- |
-
- Eyeball
- |
-
-
- |
- 60
- |
-
- E353
- |
-
- *083019.34
- |
-
- BXD51
- |
-
- Male
- |
-
- 368
- |
-
- Eyeball
- |
-
-
- |
- 61
- |
-
- E354
- |
-
- *083019.38
- |
-
- BXD66
- |
-
- Male
- |
-
- 430
- |
-
- Eyeball
- |
-
-
- |
- 62
- |
-
- E355
- |
-
- *083019.39
- |
-
- BXD66
- |
-
- Male
- |
-
- 430
- |
-
- Eyeball
- |
-
-
- |
- 63
- |
-
- E356
- |
-
- *083019.45
- |
-
- BXD73
- |
-
- Female
- |
-
- 451
- |
-
- Eyeball
- |
-
-
- |
- 64
- |
-
- E357
- |
-
- *083019.46
- |
-
- BXD73
- |
-
- Male
- |
-
- 451
- |
-
- Eyeball
- |
-
-
- |
- 65
- |
-
- E358
- |
-
- *083019.48
- |
-
- BXD75
- |
-
- Female
- |
-
- 369
- |
-
- Eyeball
- |
-
-
- |
- 66
- |
-
- E359
- |
-
- *083019.49
- |
-
- BXD75
- |
-
- Male
- |
-
- 369
- |
-
- Eyeball
- |
-
-
- |
- 67
- |
-
- E360
- |
-
- *083019.50
- |
-
- BXD78
- |
-
- Female
- |
-
- 432
- |
-
- Eyeball
- |
-
-
- |
- 68
- |
-
- E361
- |
-
- *083019.51
- |
-
- BXD78
- |
-
- Male
- |
-
- 432
- |
-
- Eyeball
- |
-
-
- |
- 69
- |
-
- E363
- |
-
- *083019.55
- |
-
- BXD87
- |
-
- Female
- |
-
- 444
- |
-
- Eyeball
- |
-
-
- |
- 70
- |
-
- E364
- |
-
- *083019.56
- |
-
- BXD87
- |
-
- Male
- |
-
- 444
- |
-
- Eyeball
- |
-
-
- |
- 71
- |
-
- E365
- |
-
- *083019.57
- |
-
- BXD89
- |
-
- Female
- |
-
- 446
- |
-
- Eyeball
- |
-
-
- |
- 72
- |
-
- E366
- |
-
- *083019.66
- |
-
- BXD113
- |
-
- Female
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 73
- |
-
- E367
- |
-
- *083019.67
- |
-
- BXD113
- |
-
- Male
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 74
- |
-
- E368
- |
-
- *090119.04
- |
-
- BXD123
- |
-
- Female
- |
-
- 441
- |
-
- Eyeball
- |
-
-
- |
- 75
- |
-
- E369
- |
-
- *090119.05
- |
-
- BXD123
- |
-
- Male
- |
-
- 441
- |
-
- Eyeball
- |
-
-
- |
- 76
- |
-
- E370
- |
-
- *090119.09
- |
-
- BXD141
- |
-
- Female
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 77
- |
-
- E371
- |
-
- *090119.11
- |
-
- BXD141
- |
-
- Male
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 78
- |
-
- E372
- |
-
- *090119.15
- |
-
- BXD151
- |
-
- Female
- |
-
- 439
- |
-
- Eyeball
- |
-
-
- |
- 79
- |
-
- E373
- |
-
- *090119.16
- |
-
- BXD151
- |
-
- Male
- |
-
- 439
- |
-
- Eyeball
- |
-
-
- |
- 80
- |
-
- E374
- |
-
- *090119.18
- |
-
- BXD152
- |
-
- Female
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 81
- |
-
- E375
- |
-
- *090119.19
- |
-
- BXD152
- |
-
- Male
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 82
- |
-
- E376
- |
-
- *090119.20
- |
-
- BXD154
- |
-
- Female
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 83
- |
-
- E377
- |
-
- *090119.22
- |
-
- BXD154
- |
-
- Male
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 84
- |
-
- E378
- |
-
- *090119.24
- |
-
- BXD155
- |
-
- Female
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 85
- |
-
- E379
- |
-
- *090119.25
- |
-
- BXD155
- |
-
- Male
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 86
- |
-
- E380
- |
-
- *090119.27
- |
-
- BXD161
- |
-
- Female
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 87
- |
-
- E381
- |
-
- *090119.28
- |
-
- BXD161
- |
-
- Male
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 88
- |
-
- E382
- |
-
- *090119.34
- |
-
- BXD170
- |
-
- Male
- |
-
- 438
- |
-
- Eyeball
- |
-
-
- |
- 89
- |
-
- E383
- |
-
- *090119.36
- |
-
- BXD171
- |
-
- Female
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 90
- |
-
- E384
- |
-
- *090119.37
- |
-
- BXD171
- |
-
- Male
- |
-
- 370
- |
-
- Eyeball
- |
-
-
- |
- 91
- |
-
- E385
- |
-
- *090119.41
- |
-
- BXD178
- |
-
- Female
- |
-
- 493
- |
-
- Eyeball
- |
-
-
- |
- 92
- |
-
- E386
- |
-
- *090119.42
- |
-
- BXD178
- |
-
- Female
- |
-
- 493
- |
-
- Eyeball
- |
-
-
- |
- 93
- |
-
- E387
- |
-
- *090119.44
- |
-
- BXD180
- |
-
- Female
- |
-
- 375
- |
-
- Eyeball
- |
-
-
- |
- 94
- |
-
- E390
- |
-
- *090119.48
- |
-
- BXD190
- |
-
- Male
- |
-
- 374
- |
-
- Eyeball
- |
-
-
- |
- 95
- |
-
- E391
- |
-
- *090119.52
- |
-
- BXD197
- |
-
- Female
- |
-
- 433
- |
-
- Eyeball
- |
-
-
- |
- 96
- |
-
- E392
- |
-
- *090119.53
- |
-
- BXD197
- |
-
- Male
- |
-
- 433
- |
-
- Eyeball
- |
-
-
- |
- 97
- |
-
- E395
- |
-
- *090119.57
- |
-
- BXD202
- |
-
- Female
- |
-
- 427
- |
-
- Eyeball
- |
-
-
- |
- 98
- |
-
- E399
- |
-
- *090119.67
- |
-
- BXD218
- |
-
- Female
- |
-
- 412
- |
-
- Eyeball
- |
-
-
- |
- 99
- |
-
- E400
- |
-
- *090119.68
- |
-
- BXD218
- |
-
- Male
- |
-
- 412
- |
-
- Eyeball
- |
-
-
- |
- 100
- |
-
- E448
- |
-
- *100819.101
- |
-
- BXD111
- |
-
- Female
- |
-
- 373
- |
-
- Eyeball
- |
-
-
- |
- 101
- |
-
- E449
- |
-
- *100819.102
- |
-
- BXD111
- |
-
- Male
- |
-
- 373
- |
-
- Eyeball
- |
-
-
- |
- 102
- |
-
- E450
- |
-
- *100819.104
- |
-
- BXD122
- |
-
- Female
- |
-
- 383
- |
-
- Eyeball
- |
-
-
- |
- 103
- |
-
- E451
- |
-
- *100819.105
- |
-
- BXD122
- |
-
- Male
- |
-
- 383
- |
-
- Eyeball
- |
-
-
- |
- 104
- |
-
- E452
- |
-
- *100819.107
- |
-
- BXD124
- |
-
- Female
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 105
- |
-
- E453
- |
-
- *100819.108
- |
-
- BXD124
- |
-
- Male
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 106
- |
-
- E454
- |
-
- *100819.110
- |
-
- BXD125
- |
-
- Female
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 107
- |
-
- E455
- |
-
- *100819.111
- |
-
- BXD125
- |
-
- Male
- |
-
- 376
- |
-
- Eyeball
- |
-
-
- |
- 108
- |
-
- E459
- |
-
- *100819.131
- |
-
- BXD172
- |
-
- Female
- |
-
- 375
- |
-
- Eyeball
- |
-
-
- |
- 109
- |
-
- E460
- |
-
- *100819.132
- |
-
- BXD172
- |
-
- Male
- |
-
- 375
- |
-
- Eyeball
- |
-
-
- |
- 110
- |
-
- E482
- |
-
- *052220.14
- |
-
- BXD71
- |
-
- Female
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 111
- |
-
- E483
- |
-
- *052220.10
- |
-
- BXD11
- |
-
- Female
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 112
- |
-
- E484
- |
-
- *052220.07
- |
-
- BXD65
- |
-
- Male
- |
-
- 528
- |
-
- Eyeball
- |
-
-
- |
- 113
- |
-
- E485
- |
-
- *052220.03
- |
-
- BXD194
- |
-
- Male
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 114
- |
-
- E486
- |
-
- *052220.19
- |
-
- BXD15
- |
-
- Female
- |
-
- 415
- |
-
- Eyeball
- |
-
-
- |
- 115
- |
-
- E487
- |
-
- *052220.02
- |
-
- BXD194
- |
-
- Female
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 116
- |
-
- E488
- |
-
- *052220.12
- |
-
- BXD1
- |
-
- Female
- |
-
- 429
- |
-
- Eyeball
- |
-
-
- |
- 117
- |
-
- E489
- |
-
- *052220.18
- |
-
- BXD216
- |
-
- Male
- |
-
- 401
- |
-
- Eyeball
- |
-
-
- |
- 118
- |
-
- E490
- |
-
- *052220.13
- |
-
- BXD1
- |
-
- Male
- |
-
- 429
- |
-
- Eyeball
- |
-
-
- |
- 119
- |
-
- E494
- |
-
- *052220.15
- |
-
- BXD71
- |
-
- Male
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 120
- |
-
- E496
- |
-
- *052220.08
- |
-
- BXD170
- |
-
- Male
- |
-
- 360
- |
-
- Eyeball
- |
-
-
- |
- 121
- |
-
- E498
- |
-
- *052220.06
- |
-
- BXD65
- |
-
- Female
- |
-
- 528
- |
-
- Eyeball
- |
-
-
- |
- 122
- |
-
- E499
- |
-
- *052220.05
- |
-
- C57BL/6J
- |
-
- Male
- |
-
- 424
- |
-
- Eyeball
- |
-
-
- |
- 123
- |
-
- E501
- |
-
- *052220.21
- |
-
- BXD73a
- |
-
- Female
- |
-
- 408
- |
-
- Eyeball
- |
-
-
- |
- 124
- |
-
- E502
- |
-
- *052220.11
- |
-
- BXD11
- |
-
- Male
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 125
- |
-
- E503
- |
-
- *052220.22
- |
-
- DBA/2J-Gpnmb
- |
-
- Female
- |
-
- 439
- |
-
- Eyeball
- |
-
-
- |
- 126
- |
-
- E504
- |
-
- *052220.20
- |
-
- BXD15
- |
-
- Male
- |
-
- 415
- |
-
- Eyeball
- |
-
-
- |
- 127
- |
-
- E541
- |
-
- 042915.08
- |
-
- BXD29
- |
-
- Female
- |
-
- 478
- |
-
- Eyeball
- |
-
-
- |
- 128
- |
-
- E542
- |
-
- 050115.01
- |
-
- BXD65b
- |
-
- Female
- |
-
- 415
- |
-
- Eyeball
- |
-
-
- |
- 129
- |
-
- E543
- |
-
- 042915.07
- |
-
- BXD29
- |
-
- Female
- |
-
- 431
- |
-
- Eyeball
- |
-
-
- |
- 130
- |
-
- E544
- |
-
- 042314.12
- |
-
- B6D2F1
- |
-
- Female
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 131
- |
-
- E548
- |
-
- *061119.02
- |
-
- C57BL/6J
- |
-
- Female
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 132
- |
-
- E549
- |
-
- *061119.03
- |
-
- C57BL/6J
- |
-
- Male
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 133
- |
-
- E551
- |
-
- *061119.11
- |
-
- DBA/2J
- |
-
- Female
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 134
- |
-
- E552
- |
-
- *061119.12
- |
-
- DBA/2J
- |
-
- Male
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 135
- |
-
- E554
- |
-
- *061119.15
- |
-
- DBA/2J
- |
-
- Male
- |
-
- 392
- |
-
- Eyeball
- |
-
-
- |
- 136
- |
-
- E556
- |
-
- *061119.22
- |
-
- DBA/2J
- |
-
- Male
- |
-
- 380
- |
-
- Eyeball
- |
-
-
- |
- 137
- |
-
- E561
- |
-
- *061219.12
- |
-
- BXD27
- |
-
- Female
- |
-
- 494
- |
-
- Eyeball
- |
-
-
- |
- 138
- |
-
- E564
- |
-
- *061219.14
- |
-
- BXD27
- |
-
- Male
- |
-
- 494
- |
-
- Eyeball
- |
-
-
- |
- 139
- |
-
- E565
- |
-
- *060419.04
- |
-
- BXD32
- |
-
- Female
- |
-
- 425
- |
-
- Eyeball
- |
-
-
- |
- 140
- |
-
- E566
- |
-
- *060419.05
- |
-
- BXD32
- |
-
- Male
- |
-
- 425
- |
-
- Eyeball
- |
-
-
- |
- 141
- |
-
- E567
- |
-
- *070919.01
- |
-
- BXD86
- |
-
- Female
- |
-
- 381
- |
-
- Eyeball
- |
-
-
- |
- 142
- |
-
- E569
- |
-
- *070919.03
- |
-
- BXD86
- |
-
- Male
- |
-
- 381
- |
-
- Eyeball
- |
-
-
- |
- 143
- |
-
- E576
- |
-
- *072519.11
- |
-
- BXD191
- |
-
- Male
- |
-
- 477
- |
-
- Eyeball
- |
-
-
- |
- 144
- |
-
- E577
- |
-
- *072519.09
- |
-
- BXD190
- |
-
- Male
- |
-
- 434
- |
-
- Eyeball
- |
-
-
- |
- 145
- |
-
- E582
- |
-
- *073019.16
- |
-
- BXD216
- |
-
- Male
- |
-
- 459
- |
-
- Eyeball
- |
-
-
- |
- 146
- |
-
- E591
- |
-
- *061319.04
- |
-
- BXD48
- |
-
- Female
- |
-
- 425
- |
-
- Eyeball
- |
-
-
- |
- 147
- |
-
- E592
- |
-
- *061319.05
- |
-
- BXD48
- |
-
- Male
- |
-
- 425
- |
-
- Eyeball
- |
-
-
- |
- 148
- |
-
- E593
- |
-
- *061319.21
- |
-
- BXD61
- |
-
- Male
- |
-
- 459
- |
-
- Eyeball
- |
-
-
- |
- 149
- |
-
- E600
- |
-
- *050318.10
- |
-
- BXD69
- |
-
- Female
- |
-
- 387
- |
-
- Eyeball
- |
-
-
- |
- 150
- |
-
- E601
- |
-
- *013020.53
- |
-
- BXD102
- |
-
- Male
- |
-
- 416
- |
-
- Eyeball
- |
-
-
- |
- 151
- |
-
- E603
- |
-
- *013020.25
- |
-
- BXD65b
- |
-
- Male
- |
-
- 505
- |
-
- Eyeball
- |
-
-
- |
- 152
- |
-
- E605
- |
-
- *013020.54
- |
-
- BXD102
- |
-
- Female
- |
-
- 416
- |
-
- Eyeball
- |
-
-
- |
- 153
- |
-
- E620
- |
-
- *012420.26
- |
-
- BXD128a
- |
-
- Male
- |
-
- 366
- |
-
- Eyeball
- |
-
-
- |
- 154
- |
-
- E625
- |
-
- *110918.54
- |
-
- BXD101
- |
-
- Male
- |
-
- 361
- |
-
- Eyeball
- |
-
-
- |
- 155
- |
-
- E626
- |
-
- *110918.53
- |
-
- BXD101
- |
-
- Female
- |
-
- 361
- |
-
- Eyeball
- |
-
-
- |
- 156
- |
-
- E631
- |
-
- *083019.14
- |
-
- BXD16
- |
-
- Female
- |
-
- 363
- |
-
- Eyeball
- |
-
-
- |
- 157
- |
-
- E635
- |
-
- *083019.35
- |
-
- BXD61
- |
-
- Male
- |
-
- 364
- |
-
- Eyeball
- |
-
-
- |
- 158
- |
-
- E638
- |
-
- *083019.60
- |
-
- BXD90
- |
-
- Female
- |
-
- 378
- |
-
- Eyeball
- |
-
-
- |
- 159
- |
-
- E639
- |
-
- *083019.62
- |
-
- BXD90
- |
-
- Male
- |
-
- 378
- |
-
- Eyeball
- |
-
-
- |
- 160
- |
-
- E662
- |
-
- *100819.153
- |
-
- BXD202
- |
-
- Male
- |
-
- 410
- |
-
- Eyeball
- |
-
-
- |
- 161
- |
-
- E663
- |
-
- *100819.157
- |
-
- BXD205
- |
-
- Female
- |
-
- 371
- |
-
- Eyeball
- |
-
-
- |
- 162
- |
-
- E664
- |
-
- *100819.158
- |
-
- BXD205
- |
-
- Male
- |
-
- 372
- |
-
- Eyeball
- |
-
-
- |
- 163
- |
-
- E665
- |
-
- *100819.163
- |
-
- BXD213
- |
-
- Female
- |
-
- 396
- |
-
- Eyeball
- |
-
-
- |
- 164
- |
-
- E666
- |
-
- *100819.164
- |
-
- BXD213
- |
-
- Male
- |
-
- 397
- |
-
- Eyeball
- |
-
-
- |
- 165
- |
-
- E667
- |
-
- *100819.168
- |
-
- BXD223
- |
-
- Female
- |
-
- 419
- |
-
- Eyeball
- |
-
-
- |
- 166
- |
-
- E668
- |
-
- *100819.169
- |
-
- BXD223
- |
-
- Male
- |
-
- 420
- |
-
- Eyeball
- |
-
-
- |
- 167
- |
-
- E672
- |
-
- *052920.10
- |
-
- BXD83
- |
-
- Male
- |
-
- 380
- |
-
- Eyeball
- |
-
-
- |
- 168
- |
-
- E675
- |
-
- *052920.13
- |
-
- DBA/2J-Gpnmb
- |
-
- Female
- |
-
- 452
- |
-
- Eyeball
- |
-
-
- |
- 169
- |
-
- E679
- |
-
- *052920.12
- |
-
- DBA/2J-Gpnmb
- |
-
- Female
- |
-
- 458
- |
-
- Eyeball
- |
-
-
- |
- 170
- |
-
- E680
- |
-
- *052920.01
- |
-
- BXD43
- |
-
- Female
- |
-
- 465
- |
-
- Eyeball
- |
-
-
- |
- 171
- |
-
- E682
- |
-
- *052920.02
- |
-
- C57BL/6J
- |
-
- Female
- |
-
- 433
- |
-
- Eyeball
- |
-
-
- |
- 172
- |
-
- E685
- |
-
- *052920.09
- |
-
- BXD83
- |
-
- Female
- |
-
- 379
- |
-
- Eyeball
- |
-
-
- |
- 173
- |
-
- E699
- |
-
- *072120.14
- |
-
- BXD40
- |
-
- Male
- |
-
- 458
- |
-
- Eyeball
- |
-
-
- |
- 174
- |
-
- E709
- |
-
- *072120.24
- |
-
- BXD150
- |
-
- Female
- |
-
- 433
- |
-
- Eyeball
- |
-
-
- |
- 175
- |
-
- E712
- |
-
- *072120.27
- |
-
- BXD160
- |
-
- Female
- |
-
- 367
- |
-
- Eyeball
- |
-
-
- |
- 176
- |
-
- E726
- |
-
- *072120.41
- |
-
- BXD16
- |
-
- Female
- |
-
- 367
- |
-
- Eyeball
- |
-
-
- |
- 177
- |
-
- E733
- |
-
- *072120.48
- |
-
- BXD60
- |
-
- Female
- |
-
- 558
- |
-
- Eyeball
- |
-
-
- |
- 178
- |
-
- E735
- |
-
- *072120.50
- |
-
- BXD180
- |
-
- Male
- |
-
- 473
- |
-
- Eyeball
- |
-
-
- |
- 179
- |
-
- E738
- |
-
- *072120.53
- |
-
- BXD128a
- |
-
- Female
- |
-
- 387
- |
-
- Eyeball
- |
-
-
- |
- 180
- |
-
- E745
- |
-
- *072120.60
- |
-
- BXD199
- |
-
- Female
- |
-
- 457
- |
-
- Eyeball
- |
-
-
- |
- 181
- |
-
- E746
- |
-
- *072120.61
- |
-
- BXD199
- |
-
- Male
- |
-
- 457
- |
-
- Eyeball
- |
-
-
- |
- 182
- |
-
- E749
- |
-
- *072120.64
- |
-
- BXD2
- |
-
- Female
- |
-
- 399
- |
-
- Eyeball
- |
-
-
- |
- 183
- |
-
- E750
- |
-
- *072120.65
- |
-
- BXD2
- |
-
- Male
- |
-
- 399
- |
-
- Eyeball
- |
-
-
- |
- 184
- |
-
- E753
- |
-
- *072120.68
- |
-
- BXD169
- |
-
- Female
- |
-
- 441
- |
-
- Eyeball
- |
-
-
- |
- 185
- |
-
- E754
- |
-
- *072120.69
- |
-
- BXD169
- |
-
- Male
- |
-
- 441
- |
-
- Eyeball
- |
-
-
- |
- 186
- |
-
- E759
- |
-
- *072120.72
- |
-
- BXD187
- |
-
- Female
- |
-
- 354
- |
-
- Eyeball
- |
-
-
- |
- 187
- |
-
- E760
- |
-
- *072120.73
- |
-
- BXD187
- |
-
- Male
- |
-
- 354
- |
-
- Eyeball
- |
-
-
-
diff --git a/general/datasets/UTHSC_BXD_Aged_Eye_RNAseq_TPM_Log2_1120/tissue.rtf b/general/datasets/UTHSC_BXD_Aged_Eye_RNAseq_TPM_Log2_1120/tissue.rtf
deleted file mode 100644
index bbfb410..0000000
--- a/general/datasets/UTHSC_BXD_Aged_Eye_RNAseq_TPM_Log2_1120/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The animals were sacrificed under saturated isoflurane. Eyeballs from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/UTHSC_BXD_All_Ages_Eye_RNAseq_TPM_Log/experiment-design.rtf b/general/datasets/UTHSC_BXD_All_Ages_Eye_RNAseq_TPM_Log/experiment-design.rtf
deleted file mode 100644
index 2f8cedc..0000000
--- a/general/datasets/UTHSC_BXD_All_Ages_Eye_RNAseq_TPM_Log/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Total RNA was extracted using Trizol® reagent (Invitrogen, Grand Island, NY, USA) according to the manufacturer’s instructions. Approximately 30 mg of PFC tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been treated with DNase to avoid DNA contamination, and verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/UTHSC_BXD_All_Ages_Eye_RNAseq_TPM_Log/processing.rtf b/general/datasets/UTHSC_BXD_All_Ages_Eye_RNAseq_TPM_Log/processing.rtf
deleted file mode 100644
index 8e460ff..0000000
--- a/general/datasets/UTHSC_BXD_All_Ages_Eye_RNAseq_TPM_Log/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/UTHSC_BXD_All_Ages_Eye_RNAseq_TPM_Log/specifics.rtf b/general/datasets/UTHSC_BXD_All_Ages_Eye_RNAseq_TPM_Log/specifics.rtf
deleted file mode 100644
index 8b003fb..0000000
--- a/general/datasets/UTHSC_BXD_All_Ages_Eye_RNAseq_TPM_Log/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-UTHSC BXD All Ages Eye RNA-Seq (Nov20) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_All_Ages_Eye_RNAseq_TPM_Log/tissue.rtf b/general/datasets/UTHSC_BXD_All_Ages_Eye_RNAseq_TPM_Log/tissue.rtf
deleted file mode 100644
index bbfb410..0000000
--- a/general/datasets/UTHSC_BXD_All_Ages_Eye_RNAseq_TPM_Log/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The animals were sacrificed under saturated isoflurane. Eyeballs from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/UTHSC_BXD_H_0912/cases.rtf b/general/datasets/UTHSC_BXD_H_0912/cases.rtf
deleted file mode 100644
index 2b37c95..0000000
--- a/general/datasets/UTHSC_BXD_H_0912/cases.rtf
+++ /dev/null
@@ -1,1258 +0,0 @@
-The study includes 137 mice (11~25 months old) from 73 strains (B6, D2, DBF1, and 70 BXD strains). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
-
-The table of samples that are finally used for this study:
-
-
-
-
-
-
-
-
-
-
-
-
- | Index |
- Strain |
- Sex |
- RNA ID |
- Age |
- Phase |
- Tissue |
-
-
- | 1 |
- BXD1 |
- F |
- R7281H |
- 448 |
- II |
- Hippocampus |
-
-
- | 2 |
- BXD1 |
- M |
- R7276H |
- 323 |
- II |
- Hippocampus |
-
-
- | 3 |
- BXD2 |
- M |
- R7261H |
- 394 |
- I |
- Hippocampus |
-
-
- | 4 |
- BXD2 |
- F |
- R7256H |
- 456 |
- I |
- Hippocampus |
-
-
- | 5 |
- BXD6 |
- M |
- R7223H |
- 526 |
- I |
- Hippocampus |
-
-
- | 6 |
- BXD8 |
- M |
- R7203H |
- 471 |
- I |
- Hippocampus |
-
-
- | 7 |
- BXD8 |
- F |
- R7200H |
- 460 |
- I |
- Hippocampus |
-
-
- | 8 |
- BXD8 |
- F |
- R7198H |
- 433 |
- I |
- Hippocampus |
-
-
- | 9 |
- BXD9 |
- F |
- R7294H |
- 456 |
- II |
- Hippocampus |
-
-
- | 10 |
- BXD11 |
- M |
- R7300H |
- 457 |
- II |
- Hippocampus |
-
-
- | 11 |
- BXD11 |
- F |
- R7227H |
- 536 |
- I |
- Hippocampus |
-
-
- | 12 |
- BXD12 |
- F |
- R7183H |
- 506 |
- I |
- Hippocampus |
-
-
- | 13 |
- BXD12 |
- F |
- R7233H |
- 561 |
- I |
- Hippocampus |
-
-
- | 14 |
- BXD12 |
- M |
- R7234H |
- 606 |
- I |
- Hippocampus |
-
-
- | 15 |
- BXD14 |
- F |
- R7238H |
- 605 |
- I |
- Hippocampus |
-
-
- | 16 |
- BXD14 |
- M |
- R7235H |
- 605 |
- I |
- Hippocampus |
-
-
- | 17 |
- BXD16 |
- F |
- R7236H |
- 561 |
- I |
- Hippocampus |
-
-
- | 18 |
- BXD16 |
- M |
- R7239H |
- 475 |
- I |
- Hippocampus |
-
-
- | 19 |
- BXD18 |
- F |
- R7229H |
- 493 |
- I |
- Hippocampus |
-
-
- | 20 |
- BXD19 |
- F |
- R7267H |
- 551 |
- I |
- Hippocampus |
-
-
- | 21 |
- BXD19 |
- M |
- R7268H |
- 492 |
- I |
- Hippocampus |
-
-
- | 22 |
- BXD20 |
- M |
- R7232H |
- 506 |
- I |
- Hippocampus |
-
-
- | 23 |
- BXD20 |
- M |
- R7263H |
- 489 |
- I |
- Hippocampus |
-
-
- | 24 |
- BXD21 |
- F |
- R7230H |
- 537 |
- I |
- Hippocampus |
-
-
- | 25 |
- BXD22 |
- F |
- R7260H |
- 502 |
- I |
- Hippocampus |
-
-
- | 26 |
- BXD22 |
- M |
- R7262H |
- 596 |
- I |
- Hippocampus |
-
-
- | 27 |
- BXD23 |
- F |
- R7258H |
- 502 |
- I |
- Hippocampus |
-
-
- | 28 |
- BXD23 |
- M |
- R7257H |
- 462 |
- I |
- Hippocampus |
-
-
- | 29 |
- BXD24 |
- M |
- R7231H |
- 470 |
- I |
- Hippocampus |
-
-
- | 30 |
- BXD24 |
- F |
- R7228H |
- 415 |
- I |
- Hippocampus |
-
-
- | 31 |
- BXD24 |
- F |
- R7255H |
- 456 |
- I |
- Hippocampus |
-
-
- | 32 |
- BXD25 |
- F |
- R7252H |
- 454 |
- I |
- Hippocampus |
-
-
- | 33 |
- BXD27 |
- F |
- R7286H |
- 472 |
- II |
- Hippocampus |
-
-
- | 34 |
- BXD27 |
- F |
- R7170H |
- 472 |
- I |
- Hippocampus |
-
-
- | 35 |
- BXD28 |
- M |
- R7254H |
- 493 |
- I |
- Hippocampus |
-
-
- | 36 |
- BXD28 |
- F |
- R7251H |
- 543 |
- I |
- Hippocampus |
-
-
- | 37 |
- BXD29 |
- F |
- R7259H |
- 483 |
- I |
- Hippocampus |
-
-
- | 38 |
- BXD33 |
- M |
- R7253H |
- 464 |
- I |
- Hippocampus |
-
-
- | 39 |
- BXD33 |
- F |
- R7174H |
- 471 |
- I |
- Hippocampus |
-
-
- | 40 |
- BXD33 |
- F |
- R7244H |
- 448 |
- I |
- Hippocampus |
-
-
- | 41 |
- BXD33 |
- M |
- R7270H |
- 662 |
- I |
- Hippocampus |
-
-
- | 42 |
- BXD38 |
- F |
- R7242H |
- 464 |
- I |
- Hippocampus |
-
-
- | 43 |
- BXD38 |
- M |
- R7247H |
- 446 |
- I |
- Hippocampus |
-
-
- | 44 |
- BXD39 |
- M |
- R7250H |
- 536 |
- I |
- Hippocampus |
-
-
- | 45 |
- BXD39 |
- F |
- R7173H |
- 500 |
- I |
- Hippocampus |
-
-
- | 46 |
- BXD39 |
- M |
- R7175H |
- 500 |
- I |
- Hippocampus |
-
-
- | 47 |
- BXD40 |
- F |
- R7288H |
- 451 |
- II |
- Hippocampus |
-
-
- | 48 |
- BXD40 |
- M |
- R7210H |
- 470 |
- I |
- Hippocampus |
-
-
- | 49 |
- BXD40 |
- M |
- R7197H |
- 614 |
- I |
- Hippocampus |
-
-
- | 50 |
- BXD42 |
- F |
- R7280H |
- 518 |
- II |
- Hippocampus |
-
-
- | 51 |
- BXD42 |
- M |
- R7246H |
- 446 |
- I |
- Hippocampus |
-
-
- | 52 |
- BXD42 |
- F |
- R7266H |
- 486 |
- I |
- Hippocampus |
-
-
- | 53 |
- BXD43 |
- F |
- R7249H |
- 454 |
- I |
- Hippocampus |
-
-
- | 54 |
- BXD43 |
- M |
- R7248H |
- 462 |
- I |
- Hippocampus |
-
-
- | 55 |
- BXD44 |
- M |
- R7241H |
- 415 |
- I |
- Hippocampus |
-
-
- | 56 |
- BXD44 |
- M |
- R7279H |
- 419 |
- II |
- Hippocampus |
-
-
- | 57 |
- BXD44 |
- F |
- R7243H |
- 438 |
- I |
- Hippocampus |
-
-
- | 58 |
- BXD45 |
- F |
- R7176H |
- 451 |
- I |
- Hippocampus |
-
-
- | 59 |
- BXD48 |
- F |
- R7245H |
- 499 |
- I |
- Hippocampus |
-
-
- | 60 |
- BXD48 |
- M |
- R7220H |
- 526 |
- I |
- Hippocampus |
-
-
- | 61 |
- BXD48a |
- F |
- R7299H |
- 479 |
- II |
- Hippocampus |
-
-
- | 62 |
- BXD48a |
- M |
- R7297H |
- 479 |
- II |
- Hippocampus |
-
-
- | 63 |
- BXD50 |
- F |
- R7224H |
- 530 |
- I |
- Hippocampus |
-
-
- | 64 |
- BXD50 |
- M |
- R7221H |
- 530 |
- I |
- Hippocampus |
-
-
- | 65 |
- BXD51 |
- F |
- R7177H |
- 487 |
- I |
- Hippocampus |
-
-
- | 66 |
- BXD51 |
- M |
- R7290H |
- 407 |
- II |
- Hippocampus |
-
-
- | 67 |
- BXD55 |
- M |
- R7222H |
- 528 |
- I |
- Hippocampus |
-
-
- | 68 |
- BXD55 |
- F |
- R7225H |
- 587 |
- I |
- Hippocampus |
-
-
- | 69 |
- BXD56 |
- M |
- R7178H |
- 501 |
- I |
- Hippocampus |
-
-
- | 70 |
- BXD62 |
- M |
- R7291H |
- 439 |
- II |
- Hippocampus |
-
-
- | 71 |
- BXD63 |
- M |
- R7218H |
- 438 |
- I |
- Hippocampus |
-
-
- | 72 |
- BXD63 |
- F |
- R7215H |
- 475 |
- I |
- Hippocampus |
-
-
- | 73 |
- BXD64 |
- M |
- R7219H |
- 528 |
- I |
- Hippocampus |
-
-
- | 74 |
- BXD64 |
- F |
- R7216H |
- 587 |
- I |
- Hippocampus |
-
-
- | 75 |
- BXD65 |
- F |
- R7217H |
- 425 |
- I |
- Hippocampus |
-
-
- | 76 |
- BXD65a |
- F |
- R7273H |
- 389 |
- II |
- Hippocampus |
-
-
- | 77 |
- BXD65a |
- M |
- R7277H |
- 715 |
- II |
- Hippocampus |
-
-
- | 78 |
- BXD65b |
- M |
- R7271H |
- 483 |
- II |
- Hippocampus |
-
-
- | 79 |
- BXD66 |
- M |
- R7214H |
- 463 |
- I |
- Hippocampus |
-
-
- | 80 |
- BXD66 |
- F |
- R7302H |
- 446 |
- III |
- Hippocampus |
-
-
- | 81 |
- BXD67 |
- F |
- R7240H |
- 499 |
- I |
- Hippocampus |
-
-
- | 82 |
- BXD67 |
- M |
- R7213H |
- 425 |
- I |
- Hippocampus |
-
-
- | 83 |
- BXD67 |
- F |
- R7278H |
- 415 |
- II |
- Hippocampus |
-
-
- | 84 |
- BXD68 |
- M |
- R7212H |
- 421 |
- I |
- Hippocampus |
-
-
- | 85 |
- BXD68 |
- F |
- R7211H |
- 415 |
- I |
- Hippocampus |
-
-
- | 86 |
- BXD69 |
- F |
- R7305H |
- 504 |
- III |
- Hippocampus |
-
-
- | 87 |
- BXD70 |
- F |
- R7207H |
- 458 |
- I |
- Hippocampus |
-
-
- | 88 |
- BXD70 |
- M |
- R7204H |
- 460 |
- I |
- Hippocampus |
-
-
- | 89 |
- BXD71 |
- M |
- R7205H |
- 471 |
- I |
- Hippocampus |
-
-
- | 90 |
- BXD71 |
- F |
- R7208H |
- 474 |
- I |
- Hippocampus |
-
-
- | 91 |
- BXD73 |
- F |
- R7209H |
- 470 |
- I |
- Hippocampus |
-
-
- | 92 |
- BXD73 |
- M |
- R7206H |
- 464 |
- I |
- Hippocampus |
-
-
- | 93 |
- BXD73a |
- F |
- R7181H |
- 443 |
- I |
- Hippocampus |
-
-
- | 94 |
- BXD73a |
- M |
- R7182H |
- 614 |
- I |
- Hippocampus |
-
-
- | 95 |
- BXD76 |
- M |
- R7179H |
- 579 |
- I |
- Hippocampus |
-
-
- | 96 |
- BXD76 |
- F |
- R7188H |
- 408 |
- I |
- Hippocampus |
-
-
- | 97 |
- BXD76 |
- M |
- R7187H |
- 564 |
- I |
- Hippocampus |
-
-
- | 98 |
- BXD77 |
- M |
- R7292H |
- 347 |
- II |
- Hippocampus |
-
-
- | 99 |
- BXD77 |
- F |
- R7201H |
- 454 |
- I |
- Hippocampus |
-
-
- | 100 |
- BXD79 |
- M |
- R7202H |
- 485 |
- I |
- Hippocampus |
-
-
- | 101 |
- BXD79 |
- F |
- R7199H |
- 515 |
- I |
- Hippocampus |
-
-
- | 102 |
- BXD79 |
- M |
- R7298H |
- 704 |
- II |
- Hippocampus |
-
-
- | 103 |
- BXD81 |
- M |
- R7196H |
- 515 |
- I |
- Hippocampus |
-
-
- | 104 |
- BXD81 |
- F |
- R7190H |
- 458 |
- I |
- Hippocampus |
-
-
- | 105 |
- BXD83 |
- M |
- R7184H |
- 441 |
- I |
- Hippocampus |
-
-
- | 106 |
- BXD84 |
- M |
- R7195H |
- 474 |
- I |
- Hippocampus |
-
-
- | 107 |
- BXD84 |
- M |
- R7296H |
- 484 |
- II |
- Hippocampus |
-
-
- | 108 |
- BXD84 |
- F |
- R7192H |
- 522 |
- I |
- Hippocampus |
-
-
- | 109 |
- BXD85 |
- M |
- R7272H |
- 425 |
- II |
- Hippocampus |
-
-
- | 110 |
- BXD85 |
- F |
- R7193H |
- 506 |
- I |
- Hippocampus |
-
-
- | 111 |
- BXD86 |
- M |
- R7191H |
- 425 |
- I |
- Hippocampus |
-
-
- | 112 |
- BXD87 |
- F |
- R7194H |
- 425 |
- I |
- Hippocampus |
-
-
- | 113 |
- BXD87 |
- M |
- R7303H |
- 478 |
- III |
- Hippocampus |
-
-
- | 114 |
- BXD87 |
- M |
- R7186H |
- 442 |
- I |
- Hippocampus |
-
-
- | 115 |
- BXD89 |
- F |
- R7295H |
- 446 |
- II |
- Hippocampus |
-
-
- | 116 |
- BXD90 |
- M |
- R7287H |
- 434 |
- II |
- Hippocampus |
-
-
- | 117 |
- BXD90 |
- M |
- R7293H |
- 558 |
- II |
- Hippocampus |
-
-
- | 118 |
- BXD95 |
- F |
- R7180H |
- 467 |
- I |
- Hippocampus |
-
-
- | 119 |
- BXD95 |
- M |
- R7169H |
- 467 |
- I |
- Hippocampus |
-
-
- | 120 |
- BXD98 |
- M |
- R7237H |
- 605 |
- I |
- Hippocampus |
-
-
- | 121 |
- BXD98 |
- F |
- R7171H |
- 639 |
- I |
- Hippocampus |
-
-
- | 122 |
- BXD98 |
- F |
- R7275H |
- 488 |
- II |
- Hippocampus |
-
-
- | 123 |
- BXD99 |
- M |
- R7189H |
- 524 |
- I |
- Hippocampus |
-
-
- | 124 |
- BXD99 |
- F |
- R7172H |
- 471 |
- I |
- Hippocampus |
-
-
- | 125 |
- BXD100 |
- F |
- R7282H |
- 463 |
- II |
- Hippocampus |
-
-
- | 126 |
- BXD100 |
- M |
- R7283H |
- 507 |
- II |
- Hippocampus |
-
-
- | 127 |
- BXD100 |
- M |
- R7274H |
- 577 |
- II |
- Hippocampus |
-
-
- | 128 |
- BXD100 |
- F |
- R7226H |
- 464 |
- I |
- Hippocampus |
-
-
- | 129 |
- BXD101 |
- F |
- R7284H |
- 490 |
- II |
- Hippocampus |
-
-
- | 130 |
- BXD101 |
- M |
- R7285H |
- 408 |
- II |
- Hippocampus |
-
-
- | 131 |
- C57BL/6J |
- M |
- R7264H |
- 489 |
- I |
- Hippocampus |
-
-
- | 132 |
- C57BL/6J |
- M |
- R7289H |
- 756 |
- II |
- Hippocampus |
-
-
- | 133 |
- D2B6F1 |
- M |
- R7265H |
- 492 |
- I |
- Hippocampus |
-
-
- | 134 |
- D2B6F1 |
- F |
- R7304H |
- 495 |
- III |
- Hippocampus |
-
-
- | 135 |
- DBA/2J |
- F |
- R7185H |
- 433 |
- I |
- Hippocampus |
-
-
- | 136 |
- DBA/2J |
- M |
- R7269H |
- 367 |
- I |
- Hippocampus |
-
-
- | 137 |
- DBA/2J |
- F |
- R7301H |
- 566 |
- III |
- Hippocampus |
-
-
-
diff --git a/general/datasets/UTHSC_BXD_H_0912/experiment-design.rtf b/general/datasets/UTHSC_BXD_H_0912/experiment-design.rtf
deleted file mode 100644
index d6b2d5b..0000000
--- a/general/datasets/UTHSC_BXD_H_0912/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA Extraction
-
-RNA was extracted using the RNeasy mini kit (Qiagen, Valencia, CA, USA) according to the manufactures’ procedure. 2100 BioAnalyzer (Agilent Technologies) was used to evaluate RNA integrity and quality. Samples with RNA Integrity Numbers (RIN values) > 8.0 were run on Affy MoGene1.0 ST at the UTHSC
diff --git a/general/datasets/UTHSC_BXD_H_0912/processing.rtf b/general/datasets/UTHSC_BXD_H_0912/processing.rtf
deleted file mode 100644
index e951515..0000000
--- a/general/datasets/UTHSC_BXD_H_0912/processing.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-About data processing:
-
-Raw microarray data were normalized using the Robust Multichip Array (RMA) method. The expression data were then re-normalized using a modified Z score.
diff --git a/general/datasets/UTHSC_BXD_H_0912/specifics.rtf b/general/datasets/UTHSC_BXD_H_0912/specifics.rtf
deleted file mode 100644
index 0888a16..0000000
--- a/general/datasets/UTHSC_BXD_H_0912/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Exon Level Data
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_H_0912/tissue.rtf b/general/datasets/UTHSC_BXD_H_0912/tissue.rtf
deleted file mode 100644
index 3166717..0000000
--- a/general/datasets/UTHSC_BXD_H_0912/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Tissue Harvest
-
-The animals were sacrificed under saturated isoflurane. Hippocampus from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/UTHSC_BXD_Harv_Liv_0118/cases.rtf b/general/datasets/UTHSC_BXD_Harv_Liv_0118/cases.rtf
deleted file mode 100644
index 18fdd1d..0000000
--- a/general/datasets/UTHSC_BXD_Harv_Liv_0118/cases.rtf
+++ /dev/null
@@ -1,1371 +0,0 @@
-
-
-
-
-
-
-
-
-
-
-
- | CaseID |
- Strain |
- Diet |
- Sex |
- Age |
- EarTag Current |
- GN-SampleID |
-
-
- | 062013.09 |
- C57BL/6J |
- HF |
- F |
- 544 |
- 514 |
- H0514 |
-
-
- | 091914.09 |
- C57BL/6J |
- CD |
- F |
- 537 |
- 1103 |
- H1103 |
-
-
- | 012615.26 |
- C57BL/6J |
- CD |
- M |
- 361 |
- 1590 |
- H1590 |
-
-
- | 102414.06 |
- C57BL/6J |
- HF |
- F |
- 182 |
- 1681 |
- H1681 |
-
-
- | 062013.12 |
- D2B6F1 |
- CD |
- F |
- 545 |
- 646 |
- H0646 |
-
-
- | 062013.13 |
- D2B6F1 |
- HF |
- F |
- 540 |
- 642 |
- H0642 |
-
-
- | 101713.20 |
- D2B6F1 |
- HF |
- F |
- 214 |
- 1150 |
- H1150 |
-
-
- | 101713.18 |
- D2B6F1 |
- CD |
- F |
- 210 |
- 1154 |
- H1154 |
-
-
- | 083016.07 |
- DBA/2J |
- CD |
- F |
- 764 |
- 1818 |
- H1818 |
-
-
- | 091914.05 |
- DBA/2J |
- HF |
- F |
- 549 |
- 1142 |
- H1142 |
-
-
- | 091914.07 |
- DBA/2J |
- HF |
- M |
- 544 |
- 1140 |
- H1140 |
-
-
- | 101713.10 |
- DBA/2J |
- CD |
- F |
- 212 |
- 1147 |
- H1147 |
-
-
- | 101713.11 |
- DBA/2J |
- HF |
- F |
- 212 |
- 1144 |
- H1144 |
-
-
- | 121214.29 |
- B6D2F1 |
- CD |
- F |
- 640 |
- 1227 |
- H1227 |
-
-
- | 012615.07 |
- B6D2F1 |
- CD |
- F |
- 552 |
- 1569 |
- H1569 |
-
-
- | 102616.04 |
- B6D2F1 |
- HF |
- F |
- 547 |
- 2288 |
- H2288 |
-
-
- | 102616.05 |
- B6D2F1 |
- HF |
- F |
- 547 |
- 2290 |
- H2290 |
-
-
- | 101713.13 |
- B6D2F1 |
- CD |
- F |
- 216 |
- 1223 |
- H1223 |
-
-
- | 101713.15 |
- B6D2F1 |
- HF |
- F |
- 216 |
- 1302 |
- H1302 |
-
-
- | 082214.11 |
- BXD9 |
- CD |
- F |
- 548 |
- 1006 |
- H1006 |
-
-
- | 082214.09 |
- BXD9 |
- HF |
- F |
- 548 |
- 1009 |
- H1009 |
-
-
- | 102616.12 |
- BXD9 |
- CD |
- F |
- 245 |
- 2577 |
- H2577 |
-
-
- | 083016.08 |
- BXD24 |
- HF |
- F |
- 688 |
- 2259 |
- H2259 |
-
-
- | 012615.19 |
- BXD24 |
- CD |
- F |
- 205 |
- 1792 |
- H1792 |
-
-
- | 012615.08 |
- BXD29 |
- CD |
- F |
- 724 |
- 1044 |
- H1044 |
-
-
- | 111314.10 |
- BXD29 |
- HF |
- F |
- 630 |
- 1037 |
- H1037 |
-
-
- | 061913.04 |
- BXD29 |
- HF |
- F |
- 577 |
- 669 |
- H0669 |
-
-
- | 111314.11 |
- BXD29 |
- CD |
- F |
- 574 |
- 1040 |
- H1040 |
-
-
- | 061913.01 |
- BXD29 |
- CD |
- F |
- 572 |
- 742 |
- H0742 |
-
-
- | 121515.05 |
- BXD29 |
- HF |
- F |
- 182 |
- 2349 |
- H2349 |
-
-
- | 101014.02 |
- BXD32 |
- HF |
- F |
- 539 |
- 1137 |
- H1137 |
-
-
- | 083016.01 |
- BXD32 |
- CD |
- F |
- 386 |
- 2494 |
- H2494 |
-
-
- | 042015.22 |
- BXD32 |
- CD |
- F |
- 200 |
- 2034 |
- H2034 |
-
-
- | 042015.20 |
- BXD32 |
- HF |
- F |
- 200 |
- 2030 |
- H2030 |
-
-
- | 101513.05 |
- BXD34 |
- CD |
- F |
- 554 |
- 765 |
- H0765 |
-
-
- | 101014.05 |
- BXD34 |
- HF |
- F |
- 537 |
- 1052 |
- H1052 |
-
-
- | 101513.02 |
- BXD34 |
- CD |
- F |
- 201 |
- 1054 |
- H1054 |
-
-
- | 101513.04 |
- BXD34 |
- HF |
- F |
- 197 |
- 1056 |
- H1056 |
-
-
- | 010614.06 |
- BXD39 |
- CD |
- F |
- 730 |
- 673 |
- H0673 |
-
-
- | 102414.02 |
- BXD39 |
- CD |
- F |
- 550 |
- 1322 |
- H1322 |
-
-
- | 121214.22 |
- BXD39 |
- HF |
- F |
- 350 |
- 1474 |
- H1474 |
-
-
- | 121214.21 |
- BXD39 |
- HF |
- F |
- 350 |
- 1473 |
- H1473 |
-
-
- | 061913.06 |
- BXD40 |
- CD |
- F |
- 578 |
- 680 |
- H0680 |
-
-
- | 121214.13 |
- BXD40 |
- HF |
- F |
- 358 |
- 1593 |
- H1593 |
-
-
- | 111314.05 |
- BXD40 |
- HF |
- F |
- 291 |
- 1488 |
- H1488 |
-
-
- | 102414.08 |
- BXD40 |
- CD |
- F |
- 180 |
- 1691 |
- H1691 |
-
-
- | 102414.12 |
- BXD44 |
- HF |
- F |
- 715 |
- 1687 |
- H1687 |
-
-
- | 012615.15 |
- BXD44 |
- CD |
- F |
- 379 |
- 1505 |
- H1505 |
-
-
- | 012615.12 |
- BXD44 |
- HF |
- F |
- 379 |
- 1501 |
- H1501 |
-
-
- | 042015.07 |
- BXD44 |
- CD |
- F |
- 240 |
- 1822 |
- H1822 |
-
-
- | 042015.10 |
- BXD44 |
- HF |
- F |
- 240 |
- 1825 |
- H1825 |
-
-
- | 121515.12 |
- BXD45 |
- CD |
- F |
- 507 |
- 1826 |
- H1826 |
-
-
- | 121515.15 |
- BXD45 |
- HF |
- F |
- 503 |
- 1940 |
- H1940 |
-
-
- | 012615.11 |
- BXD45 |
- CD |
- F |
- 384 |
- 1762 |
- H1762 |
-
-
- | 042915.13 |
- BXD48 |
- HF |
- F |
- 595 |
- 1377 |
- H1377 |
-
-
- | 121515.18 |
- BXD48 |
- CD |
- F |
- 518 |
- 1835 |
- H1835 |
-
-
- | 042015.24 |
- BXD48 |
- HF |
- F |
- 189 |
- 2046 |
- H2046 |
-
-
- | 042015.27 |
- BXD48 |
- CD |
- F |
- 188 |
- 2054 |
- H2054 |
-
-
- | 062013.06 |
- BXD48a |
- HF |
- F |
- 543 |
- 699 |
- H0699 |
-
-
- | 051112.05 |
- BXD48a |
- CD |
- F |
- 233 |
- 209 |
- H0209 |
-
-
- | 051112.04 |
- BXD48a |
- HF |
- F |
- 233 |
- 210 |
- H0210 |
-
-
- | 010614.07 |
- BXD53 |
- HF |
- F |
- 713 |
- 833 |
- H0833 |
-
-
- | 062013.16 |
- BXD53 |
- CD |
- F |
- 571 |
- 848 |
- H0848 |
-
-
- | 021213.14 |
- BXD60 |
- CD |
- F |
- 530 |
- 171 |
- H0171 |
-
-
- | 050912.08 |
- BXD60 |
- CD |
- F |
- 235 |
- 235 |
- H0235 |
-
-
- | 121515.23 |
- BXD61 |
- CD |
- F |
- 524 |
- 1841 |
- H1841 |
-
-
- | 121515.25 |
- BXD61 |
- HF |
- F |
- 524 |
- 1843 |
- H1843 |
-
-
- | 111414.02 |
- BXD61 |
- CD |
- F |
- 188 |
- 1770 |
- H1770 |
-
-
- | 111414.03 |
- BXD61 |
- HF |
- F |
- 188 |
- 1922 |
- H1922 |
-
-
- | 111414.04 |
- BXD61 |
- HF |
- F |
- 188 |
- 1722 |
- H1722 |
-
-
- | 082214.10 |
- BXD62 |
- HF |
- F |
- 548 |
- 1315 |
- H1315 |
-
-
- | 042915.19 |
- BXD62 |
- HF |
- F |
- 488 |
- 1434 |
- H1434 |
-
-
- | 121214.20 |
- BXD62 |
- CD |
- F |
- 353 |
- 1436 |
- H1436 |
-
-
- | 042015.05 |
- BXD62 |
- CD |
- F |
- 253 |
- 1847 |
- H1847 |
-
-
- | 102616.17 |
- BXD63 |
- HF |
- F |
- 752 |
- 2091 |
- H2091 |
-
-
- | 083016.03 |
- BXD63 |
- CD |
- F |
- 751 |
- 1872 |
- H1872 |
-
-
- | 121214.24 |
- BXD63 |
- CD |
- F |
- 344 |
- 1414 |
- H1414 |
-
-
- | 121214.26 |
- BXD63 |
- HF |
- F |
- 344 |
- 1416 |
- H1416 |
-
-
- | 090412.08 |
- BXD63 |
- CD |
- F |
- 218 |
- 818 |
- H0818 |
-
-
- | 111414.09 |
- BXD63 |
- HF |
- F |
- 186 |
- 1715 |
- H1715 |
-
-
- | 121615.09 |
- BXD65 |
- CD |
- F |
- 541 |
- 1787 |
- H1787 |
-
-
- | 121615.06 |
- BXD65 |
- HF |
- F |
- 541 |
- 1784 |
- H1784 |
-
-
- | 051012.01 |
- BXD65 |
- HF |
- F |
- 230 |
- 458 |
- H0458 |
-
-
- | 042015.13 |
- BXD65 |
- CD |
- F |
- 222 |
- 2098 |
- H2098 |
-
-
- | 121615.12 |
- BXD65b |
- CD |
- F |
- 527 |
- 1793 |
- H1793 |
-
-
- | 121615.11 |
- BXD65b |
- HF |
- F |
- 527 |
- 1790 |
- H1790 |
-
-
- | 111414.05 |
- BXD65b |
- CD |
- F |
- 187 |
- 1766 |
- H1766 |
-
-
- | 102414.18 |
- BXD65b |
- HF |
- F |
- 174 |
- 1713 |
- H1713 |
-
-
- | 121214.04 |
- BXD66 |
- HF |
- F |
- 367 |
- 1560 |
- H1560 |
-
-
- | 121214.19 |
- BXD66 |
- CD |
- F |
- 354 |
- 1558 |
- H1558 |
-
-
- | 042415.08 |
- BXD66 |
- CD |
- F |
- 184 |
- 2128 |
- H2128 |
-
-
- | 042415.05 |
- BXD66 |
- HF |
- F |
- 184 |
- 2124 |
- H2124 |
-
-
- | 082214.02 |
- BXD68 |
- CD |
- F |
- 545 |
- 1080 |
- H1080 |
-
-
- | 082214.08 |
- BXD68 |
- HF |
- F |
- 545 |
- 1290 |
- H1290 |
-
-
- | 101613.05 |
- BXD68 |
- CD |
- F |
- 201 |
- 1068 |
- H1068 |
-
-
- | 101613.08 |
- BXD68 |
- HF |
- F |
- 201 |
- 1071 |
- H1071 |
-
-
- | 061913.13 |
- BXD69 |
- CD |
- F |
- 558 |
- 591 |
- H0591 |
-
-
- | 121214.23 |
- BXD69 |
- HF |
- F |
- 528 |
- 1328 |
- H1328 |
-
-
- | 101613.09 |
- BXD69 |
- HF |
- F |
- 210 |
- 1087 |
- H1087 |
-
-
- | 042415.23 |
- BXD69 |
- CD |
- F |
- 157 |
- 2142 |
- H2142 |
-
-
- | 121615.14 |
- BXD70 |
- HF |
- F |
- 578 |
- 1728 |
- H1728 |
-
-
- | 121214.16 |
- BXD70 |
- CD |
- F |
- 357 |
- 1512 |
- H1512 |
-
-
- | 050115.06 |
- BXD70 |
- CD |
- F |
- 261 |
- 1855 |
- H1855 |
-
-
- | 051012.08 |
- BXD70 |
- HF |
- F |
- 239 |
- 188 |
- H0188 |
-
-
- | 121615.17 |
- BXD73 |
- CD |
- F |
- 539 |
- 1906 |
- H1906 |
-
-
- | 121214.10 |
- BXD73 |
- CD |
- F |
- 361 |
- 1451 |
- H1451 |
-
-
- | 121214.11 |
- BXD73 |
- HF |
- F |
- 361 |
- 1447 |
- H1447 |
-
-
- | 042015.18 |
- BXD73 |
- HF |
- F |
- 206 |
- 2071 |
- H2071 |
-
-
- | 050115.15 |
- BXD73b |
- CD |
- F |
- 497 |
- 1466 |
- H1466 |
-
-
- | 050115.12 |
- BXD73b |
- HF |
- F |
- 474 |
- 1545 |
- H1545 |
-
-
- | 051112.12 |
- BXD73b |
- CD |
- F |
- 238 |
- 184 |
- H0184 |
-
-
- | 051112.14 |
- BXD73b |
- HF |
- F |
- 237 |
- 183 |
- H0183 |
-
-
- | 121615.19 |
- BXD77 |
- HF |
- F |
- 511 |
- 1866 |
- H1866 |
-
-
- | 050115.17 |
- BXD77 |
- CD |
- F |
- 460 |
- 1398 |
- H1398 |
-
-
- | 061913.18 |
- BXD79 |
- HF |
- F |
- 571 |
- 583 |
- H0583 |
-
-
- | 050115.19 |
- BXD79 |
- CD |
- F |
- 468 |
- 1555 |
- H1555 |
-
-
- | 090412.10 |
- BXD79 |
- CD |
- F |
- 217 |
- 825 |
- H0825 |
-
-
- | 061913.19 |
- BXD87 |
- CD |
- F |
- 581 |
- 296 |
- H0296 |
-
-
- | 121615.21 |
- BXD87 |
- HF |
- F |
- 512 |
- 1945 |
- H1945 |
-
-
- | 051012.14 |
- BXD87 |
- HF |
- F |
- 241 |
- 243 |
- H0243 |
-
-
- | 090612.10 |
- BXD87 |
- CD |
- F |
- 200 |
- 550 |
- H0550 |
-
-
- | 101014.04 |
- BXD89 |
- HF |
- F |
- 539 |
- 1321 |
- H1321 |
-
-
- | 051112.01 |
- BXD89 |
- HF |
- F |
- 243 |
- 176 |
- H0176 |
-
-
- | 090612.14 |
- BXD89 |
- CD |
- F |
- 193 |
- 555 |
- H0555 |
-
-
- | 062013.03 |
- BXD90 |
- HF |
- F |
- 570 |
- 736 |
- H0736 |
-
-
- | 062013.02 |
- BXD90 |
- CD |
- F |
- 549 |
- 756 |
- H0756 |
-
-
- | 101613.19 |
- BXD90 |
- HF |
- F |
- 218 |
- 1093 |
- H1093 |
-
-
- | 102414.03 |
- BXD90 |
- CD |
- F |
- 188 |
- 1702 |
- H1702 |
-
-
- | 062013.17 |
- BXD91 |
- CD |
- F |
- 562 |
- 883 |
- H0883 |
-
-
- | 062013.19 |
- BXD91 |
- HF |
- F |
- 562 |
- 881 |
- H0881 |
-
-
- | 102414.20 |
- BXD95 |
- HF |
- F |
- 550 |
- 1273 |
- H1273 |
-
-
- | 101014.10 |
- BXD95 |
- CD |
- F |
- 536 |
- 1742 |
- H1742 |
-
-
- | 101613.21 |
- BXD95 |
- HF |
- F |
- 213 |
- 1275 |
- H1275 |
-
-
- | 012615.17 |
- BXD98 |
- CD |
- F |
- 384 |
- 1769 |
- H1769 |
-
-
- | 012615.16 |
- BXD98 |
- CD |
- F |
- 384 |
- 1524 |
- H1524 |
-
-
- | 111414.14 |
- BXD99 |
- CD |
- F |
- 535 |
- 1354 |
- H1354 |
-
-
- | 050914.05 |
- BXD99 |
- HF |
- F |
- 182 |
- 1355 |
- H1355 |
-
-
- | 111314.15 |
- BXD100 |
- CD |
- F |
- 567 |
- 1190 |
- H1190 |
-
-
- | 050914.04 |
- BXD100 |
- HF |
- F |
- 537 |
- 1187 |
- H1187 |
-
-
- | 051112.07 |
- BXD100 |
- CD |
- F |
- 223 |
- 247 |
- H0247 |
-
-
- | 051112.08 |
- BXD100 |
- CD |
- F |
- 223 |
- 248 |
- H0248 |
-
-
- | 042415.12 |
- BXD100 |
- HF |
- F |
- 176 |
- 2085 |
- H2085 |
-
-
- | 102616.20 |
- BXD101 |
- CD |
- F |
- 756 |
- 2114 |
- H2114 |
-
-
- | 042715.19 |
- BXD101 |
- HF |
- F |
- 493 |
- 1422 |
- H1422 |
-
-
- | 111414.20 |
- BXD101 |
- CD |
- F |
- 349 |
- 1425 |
- H1425 |
-
-
- | 051112.09 |
- BXD101 |
- CD |
- F |
- 223 |
- 468 |
- H0468 |
-
-
- | 042915.01 |
- BXD102 |
- CD |
- F |
- 501 |
- 1499 |
- H1499 |
-
-
- | 121214.07 |
- BXD102 |
- HF |
- F |
- 366 |
- 1498 |
- H1498 |
-
-
- | 053014.01 |
- BXD102 |
- CD |
- F |
- 183 |
- 1363 |
- H1363 |
-
-
- | 052814.04 |
- BXD102 |
- HF |
- F |
- 183 |
- 1361 |
- H1361 |
-
-
-
diff --git a/general/datasets/UTHSC_BXD_Harv_Liv_0118/processing.rtf b/general/datasets/UTHSC_BXD_Harv_Liv_0118/processing.rtf
deleted file mode 100644
index 4504c49..0000000
--- a/general/datasets/UTHSC_BXD_Harv_Liv_0118/processing.rtf
+++ /dev/null
@@ -1,26883 +0,0 @@
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- | 150 UTHSC Aging Liver RNA Selected for Novogene Submission |
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- | All Samples approximately 110ng/ul with a total of approximately 3ug RNA |
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- | File last updated by A.Centeno 1-3-18 |
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- | Pearson Product-Moment Correlation |
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- | No Selector |
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- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- Age |
- 216 |
- 552 |
- 640 |
- 223 |
- 223 |
- 567 |
- 223 |
- 349 |
- 756 |
- 183 |
- 501 |
- 205 |
- 572 |
- 574 |
- 724 |
- 200 |
- 386 |
- 201 |
- 554 |
- 550 |
- 730 |
- 180 |
- 578 |
- 240 |
- 379 |
- 384 |
- 507 |
- 188 |
- 518 |
- 233 |
- 571 |
- 235 |
- 530 |
- 188 |
- 524 |
- 253 |
- 353 |
- 218 |
- 344 |
- 751 |
- 222 |
- 541 |
- 187 |
- 527 |
- 184 |
- 354 |
- 201 |
- 545 |
- 157 |
- 558 |
- 261 |
- 357 |
- 361 |
- 539 |
- 238 |
- 497 |
- 460 |
- 217 |
- 468 |
- 200 |
- 581 |
- 193 |
- 245 |
- 548 |
- 188 |
- 549 |
- 562 |
- 536 |
- 384 |
- 384 |
- 535 |
- 361 |
- 537 |
- 210 |
- 545 |
- 212 |
- 764 |
- 216 |
- 547 |
- 547 |
- 176 |
- 537 |
- 493 |
- 183 |
- 366 |
- 688 |
- 182 |
- 577 |
- 630 |
- 200 |
- 539 |
- 197 |
- 537 |
- 350 |
- 350 |
- 291 |
- 358 |
- 240 |
- 379 |
- 715 |
- 503 |
- 189 |
- 595 |
- 233 |
- 543 |
- 713 |
- 188 |
- 188 |
- 524 |
- 488 |
- 548 |
- 186 |
- 344 |
- 752 |
- 230 |
- 541 |
- 174 |
- 527 |
- 184 |
- 367 |
- 201 |
- 545 |
- 210 |
- 528 |
- 239 |
- 578 |
- 206 |
- 361 |
- 237 |
- 474 |
- 511 |
- 571 |
- 241 |
- 512 |
- 243 |
- 539 |
- 548 |
- 218 |
- 570 |
- 562 |
- 213 |
- 550 |
- 182 |
- 544 |
- 182 |
- 214 |
- 540 |
- 212 |
- 544 |
- 549 |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- Sex |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- M |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- M |
- F |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- JI-ID |
- 307 |
- 151 |
- 136 |
- 268 |
- 269 |
- 92 |
- 3 |
- 117 |
- 179 |
- 83 |
- 270 |
- 163 |
- 299 |
- 314 |
- 141 |
- 259 |
- 131 |
- 170 |
- 180 |
- 276 |
- 168 |
- 289 |
- 285 |
- 264 |
- 157 |
- 145 |
- 281 |
- 260 |
- 275 |
- 25 |
- 308 |
- 104 |
- 51 |
- 132 |
- 324 |
- 257 |
- 178 |
- 293 |
- 134 |
- 133 |
- 107 |
- 322 |
- 320 |
- 313 |
- 112 |
- 113 |
- 271 |
- 74 |
- 114 |
- 41 |
- 207 |
- 197 |
- 203 |
- 213 |
- 98 |
- 253 |
- 255 |
- 272 |
- 91 |
- 6 |
- 286 |
- 310 |
- 230 |
- 73 |
- 304 |
- 311 |
- 21 |
- 277 |
- 146 |
- 182 |
- 278 |
- 162 |
- 273 |
- 300 |
- 298 |
- 67 |
- 121 |
- 306 |
- 279 |
- 296 |
- 254 |
- 77 |
- 290 |
- 284 |
- 195 |
- 140 |
- 317 |
- 295 |
- 119 |
- 261 |
- 318 |
- 283 |
- 292 |
- 129 |
- 204 |
- 280 |
- 202 |
- 258 |
- 158 |
- 144 |
- 303 |
- 263 |
- 238 |
- 239 |
- 287 |
- 143 |
- 128 |
- 323 |
- 316 |
- 242 |
- 302 |
- 125 |
- 123 |
- 135 |
- 265 |
- 212 |
- 315 |
- 321 |
- 262 |
- 122 |
- 59 |
- 71 |
- 58 |
- 109 |
- 266 |
- 294 |
- 224 |
- 196 |
- 97 |
- 256 |
- 319 |
- 24 |
- 2 |
- 326 |
- 267 |
- 282 |
- 312 |
- 297 |
- 274 |
- 325 |
- 288 |
- 236 |
- 305 |
- 309 |
- 235 |
- 301 |
- 291 |
- 16 |
- 181 |
- 190 |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- CaseID |
- 101713.13 |
- 012615.07 |
- 121214.29 |
- 051112.07 |
- 051112.08 |
- 111314.15 |
- 051112.09 |
- 111414.20 |
- 102616.20 |
- 053014.01 |
- 042915.01 |
- 012615.19 |
- 061913.01 |
- 111314.11 |
- 012615.08 |
- 042015.22 |
- 083016.01 |
- 101513.02 |
- 101513.05 |
- 102414.02 |
- 010614.06 |
- 102414.08 |
- 061913.06 |
- 042015.07 |
- 012615.15 |
- 012615.11 |
- 121515.12 |
- 042015.27 |
- 121515.18 |
- 051112.05 |
- 062013.16 |
- 050912.08 |
- 021213.14 |
- 111414.02 |
- 121515.23 |
- 042015.05 |
- 121214.20 |
- 090412.08 |
- 121214.24 |
- 083016.03 |
- 042015.13 |
- 121615.09 |
- 111414.05 |
- 121615.12 |
- 042415.08 |
- 121214.19 |
- 101613.05 |
- 082214.02 |
- 042415.23 |
- 061913.13 |
- 050115.06 |
- 121214.16 |
- 121214.10 |
- 121615.17 |
- 051112.12 |
- 050115.15 |
- 050115.17 |
- 090412.10 |
- 050115.19 |
- 090612.10 |
- 061913.19 |
- 090612.14 |
- 102616.12 |
- 082214.11 |
- 102414.03 |
- 062013.02 |
- 062013.17 |
- 101014.10 |
- 012615.17 |
- 012615.16 |
- 111414.14 |
- 012615.26 |
- 091914.09 |
- 101713.18 |
- 062013.12 |
- 101713.10 |
- 083016.07 |
- 101713.15 |
- 102616.04 |
- 102616.05 |
- 042415.12 |
- 050914.04 |
- 042715.19 |
- 052814.04 |
- 121214.07 |
- 083016.08 |
- 121515.05 |
- 061913.04 |
- 111314.10 |
- 042015.20 |
- 101014.02 |
- 101513.04 |
- 101014.05 |
- 121214.22 |
- 121214.21 |
- 111314.05 |
- 121214.13 |
- 042015.10 |
- 012615.12 |
- 102414.12 |
- 121515.15 |
- 042015.24 |
- 042915.13 |
- 051112.04 |
- 062013.06 |
- 010614.07 |
- 111414.03 |
- 111414.04 |
- 121515.25 |
- 042915.19 |
- 082214.10 |
- 111414.09 |
- 121214.26 |
- 102616.17 |
- 051012.01 |
- 121615.06 |
- 102414.18 |
- 121615.11 |
- 042415.05 |
- 121214.04 |
- 101613.08 |
- 082214.08 |
- 101613.09 |
- 121214.23 |
- 051012.08 |
- 121615.14 |
- 042015.18 |
- 121214.11 |
- 051112.14 |
- 050115.12 |
- 121615.19 |
- 061913.18 |
- 051012.14 |
- 121615.21 |
- 051112.01 |
- 101014.04 |
- 082214.09 |
- 101613.19 |
- 062013.03 |
- 062013.19 |
- 101613.21 |
- 102414.20 |
- 050914.05 |
- 062013.09 |
- 102414.06 |
- 101713.20 |
- 062013.13 |
- 101713.11 |
- 091914.07 |
- 091914.05 |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- Diet |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- Strain |
- B6D2F1 |
- B6D2F1 |
- B6D2F1 |
- BXD100 |
- BXD100 |
- BXD100 |
- BXD101 |
- BXD101 |
- BXD101 |
- BXD102 |
- BXD102 |
- BXD24 |
- BXD29 |
- BXD29 |
- BXD29 |
- BXD32 |
- BXD32 |
- BXD34 |
- BXD34 |
- BXD39 |
- BXD39 |
- BXD40 |
- BXD40 |
- BXD44 |
- BXD44 |
- BXD45 |
- BXD45 |
- BXD48 |
- BXD48 |
- BXD48a |
- BXD53 |
- BXD60 |
- BXD60 |
- BXD61 |
- BXD61 |
- BXD62 |
- BXD62 |
- BXD63 |
- BXD63 |
- BXD63 |
- BXD65 |
- BXD65 |
- BXD65b |
- BXD65b |
- BXD66 |
- BXD66 |
- BXD68 |
- BXD68 |
- BXD69 |
- BXD69 |
- BXD70 |
- BXD70 |
- BXD73 |
- BXD73 |
- BXD73b |
- BXD73b |
- BXD77 |
- BXD79 |
- BXD79 |
- BXD87 |
- BXD87 |
- BXD89 |
- BXD9 |
- BXD9 |
- BXD90 |
- BXD90 |
- BXD91 |
- BXD95 |
- BXD98 |
- BXD98 |
- BXD99 |
- C57BL/6J |
- C57BL/6J |
- D2B6F1 |
- D2B6F1 |
- DBA/2J |
- DBA/2J |
- B6D2F1 |
- B6D2F1 |
- B6D2F1 |
- BXD100 |
- BXD100 |
- BXD101 |
- BXD102 |
- BXD102 |
- BXD24 |
- BXD29 |
- BXD29 |
- BXD29 |
- BXD32 |
- BXD32 |
- BXD34 |
- BXD34 |
- BXD39 |
- BXD39 |
- BXD40 |
- BXD40 |
- BXD44 |
- BXD44 |
- BXD44 |
- BXD45 |
- BXD48 |
- BXD48 |
- BXD48a |
- BXD48a |
- BXD53 |
- BXD61 |
- BXD61 |
- BXD61 |
- BXD62 |
- BXD62 |
- BXD63 |
- BXD63 |
- BXD63 |
- BXD65 |
- BXD65 |
- BXD65b |
- BXD65b |
- BXD66 |
- BXD66 |
- BXD68 |
- BXD68 |
- BXD69 |
- BXD69 |
- BXD70 |
- BXD70 |
- BXD73 |
- BXD73 |
- BXD73b |
- BXD73b |
- BXD77 |
- BXD79 |
- BXD87 |
- BXD87 |
- BXD89 |
- BXD89 |
- BXD9 |
- BXD90 |
- BXD90 |
- BXD91 |
- BXD95 |
- BXD95 |
- BXD99 |
- C57BL/6J |
- C57BL/6J |
- D2B6F1 |
- D2B6F1 |
- DBA/2J |
- DBA/2J |
- DBA/2J |
- |
- |
- |
-
-
- | Tissue |
- Age |
- Sex |
- JI-ID |
- CaseID |
- Diet |
- Strain |
- EarTag |
- H1223 |
- H1569 |
- H1227 |
- H0247 |
- H0248 |
- H1190 |
- H0468 |
- H1425 |
- H2114 |
- H1363 |
- H1499 |
- H1792 |
- H0742 |
- H1040 |
- H1044 |
- H2034 |
- H2494 |
- H1054 |
- H0765 |
- H1322 |
- H0673 |
- H1691 |
- H0680 |
- H1822 |
- H1505 |
- H1762 |
- H1826 |
- H2054 |
- H1835 |
- H0209 |
- H0848 |
- H0235 |
- H0171 |
- H1770 |
- H1841 |
- H1847 |
- H1436 |
- H0818 |
- H1414 |
- H1872 |
- H2098 |
- H1787 |
- H1766 |
- H1793 |
- H2128 |
- H1558 |
- H1068 |
- H1080 |
- H2142 |
- H0591 |
- H1855 |
- H1512 |
- H1451 |
- H1906 |
- H0184 |
- H1466 |
- H1398 |
- H0825 |
- H1555 |
- H0550 |
- H0296 |
- H0555 |
- H2577 |
- H1006 |
- H1702 |
- H0756 |
- H0883 |
- H1742 |
- H1769 |
- H1524 |
- H1354 |
- H1590 |
- H1103 |
- H1154 |
- H0646 |
- H1147 |
- H1818 |
- H1302 |
- H2288 |
- H2290 |
- H2085 |
- H1187 |
- H1422 |
- H1361 |
- H1498 |
- H2259 |
- H2349 |
- H0669 |
- H1037 |
- H2030 |
- H1137 |
- H1056 |
- H1052 |
- H1474 |
- H1473 |
- H1488 |
- H1593 |
- H1825 |
- H1501 |
- H1687 |
- H1940 |
- H2046 |
- H1377 |
- H0210 |
- H0699 |
- H0833 |
- H1922 |
- H1722 |
- H1843 |
- H1434 |
- H1315 |
- H1715 |
- H1416 |
- H2091 |
- H0458 |
- H1784 |
- H1713 |
- H1790 |
- H2124 |
- H1560 |
- H1071 |
- H1290 |
- H1087 |
- H1328 |
- H0188 |
- H1728 |
- H2071 |
- H1447 |
- H0183 |
- H1545 |
- H1866 |
- H0583 |
- H0243 |
- H1945 |
- H0176 |
- H1321 |
- H1009 |
- H1093 |
- H0736 |
- H0881 |
- H1275 |
- H1273 |
- H1355 |
- H0514 |
- H1681 |
- H1150 |
- H0642 |
- H1144 |
- H1140 |
- H1142 |
- |
- min |
- Average |
-
-
- | Liver |
- 216 |
- F |
- 307 |
- 101713.13 |
- CD |
- B6D2F1 |
- H1223 |
- 1 |
- 0.919 |
- 0.921 |
- 0.992 |
- 0.983 |
- 0.985 |
- 0.992 |
- 0.96 |
- 0.877 |
- 0.988 |
- 0.976 |
- 0.987 |
- 0.982 |
- 0.989 |
- 0.97 |
- 0.983 |
- 0.971 |
- 0.957 |
- 0.984 |
- 0.986 |
- 0.979 |
- 0.993 |
- 0.99 |
- 0.992 |
- 0.982 |
- 0.972 |
- 0.973 |
- 0.974 |
- 0.989 |
- 0.99 |
- 0.989 |
- 0.987 |
- 0.946 |
- 0.976 |
- 0.985 |
- 0.975 |
- 0.929 |
- 0.99 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.985 |
- 0.985 |
- 0.99 |
- 0.983 |
- 0.94 |
- 0.984 |
- 0.982 |
- 0.989 |
- 0.982 |
- 0.989 |
- 0.961 |
- 0.977 |
- 0.98 |
- 0.989 |
- 0.99 |
- 0.979 |
- 0.98 |
- 0.989 |
- 0.985 |
- 0.979 |
- 0.968 |
- 0.984 |
- 0.897 |
- 0.987 |
- 0.985 |
- 0.972 |
- 0.988 |
- 0.966 |
- 0.939 |
- 0.982 |
- 0.935 |
- 0.989 |
- 0.992 |
- 0.983 |
- 0.985 |
- 0.971 |
- 0.994 |
- 0.989 |
- 0.99 |
- 0.986 |
- 0.988 |
- 0.975 |
- 0.982 |
- 0.985 |
- 0.959 |
- 0.99 |
- 0.991 |
- 0.97 |
- 0.985 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.988 |
- 0.984 |
- 0.971 |
- 0.978 |
- 0.976 |
- 0.987 |
- 0.983 |
- 0.97 |
- 0.979 |
- 0.982 |
- 0.99 |
- 0.98 |
- 0.988 |
- 0.987 |
- 0.984 |
- 0.951 |
- 0.972 |
- 0.982 |
- 0.964 |
- 0.986 |
- 0.972 |
- 0.987 |
- 0.984 |
- 0.986 |
- 0.986 |
- 0.986 |
- 0.975 |
- 0.985 |
- 0.965 |
- 0.986 |
- 0.989 |
- 0.988 |
- 0.968 |
- 0.982 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.986 |
- 0.98 |
- 0.987 |
- 0.985 |
- 0.983 |
- 0.988 |
- 0.988 |
- 0.925 |
- 0.99 |
- 0.984 |
- 0.988 |
- 0.99 |
- 0.984 |
- 0.935 |
- 0.969 |
- 0.932 |
- |
- 0.877 |
- 0.98 |
-
-
- | Liver |
- 552 |
- F |
- 151 |
- 012615.07 |
- CD |
- B6D2F1 |
- H1569 |
- 0.919 |
- 1 |
- 0.997 |
- 0.93 |
- 0.939 |
- 0.945 |
- 0.916 |
- 0.935 |
- 0.962 |
- 0.928 |
- 0.945 |
- 0.934 |
- 0.932 |
- 0.923 |
- 0.952 |
- 0.938 |
- 0.943 |
- 0.935 |
- 0.941 |
- 0.936 |
- 0.923 |
- 0.925 |
- 0.922 |
- 0.926 |
- 0.93 |
- 0.951 |
- 0.952 |
- 0.943 |
- 0.943 |
- 0.927 |
- 0.919 |
- 0.928 |
- 0.95 |
- 0.922 |
- 0.92 |
- 0.956 |
- 0.944 |
- 0.924 |
- 0.932 |
- 0.923 |
- 0.931 |
- 0.926 |
- 0.921 |
- 0.927 |
- 0.929 |
- 0.95 |
- 0.922 |
- 0.936 |
- 0.925 |
- 0.935 |
- 0.929 |
- 0.935 |
- 0.948 |
- 0.943 |
- 0.929 |
- 0.927 |
- 0.943 |
- 0.914 |
- 0.935 |
- 0.931 |
- 0.932 |
- 0.942 |
- 0.932 |
- 0.943 |
- 0.919 |
- 0.92 |
- 0.955 |
- 0.928 |
- 0.946 |
- 0.931 |
- 0.939 |
- 0.931 |
- 0.932 |
- 0.916 |
- 0.921 |
- 0.931 |
- 0.942 |
- 0.923 |
- 0.938 |
- 0.932 |
- 0.927 |
- 0.931 |
- 0.944 |
- 0.927 |
- 0.933 |
- 0.949 |
- 0.923 |
- 0.924 |
- 0.934 |
- 0.927 |
- 0.923 |
- 0.943 |
- 0.946 |
- 0.941 |
- 0.94 |
- 0.933 |
- 0.942 |
- 0.941 |
- 0.95 |
- 0.939 |
- 0.944 |
- 0.937 |
- 0.96 |
- 0.941 |
- 0.943 |
- 0.915 |
- 0.922 |
- 0.922 |
- 0.92 |
- 0.948 |
- 0.932 |
- 0.922 |
- 0.925 |
- 0.943 |
- 0.927 |
- 0.955 |
- 0.92 |
- 0.935 |
- 0.923 |
- 0.927 |
- 0.93 |
- 0.95 |
- 0.927 |
- 0.957 |
- 0.936 |
- 0.929 |
- 0.93 |
- 0.945 |
- 0.935 |
- 0.939 |
- 0.922 |
- 0.948 |
- 0.942 |
- 0.915 |
- 0.921 |
- 0.946 |
- 0.932 |
- 0.922 |
- 0.941 |
- 0.928 |
- 0.929 |
- 0.95 |
- 0.922 |
- 0.933 |
- 0.934 |
- 0.927 |
- 0.917 |
- 0.931 |
- 0.935 |
- 0.949 |
- |
- 0.914 |
- 0.93 |
-
-
- | Liver |
- 640 |
- F |
- 136 |
- 121214.29 |
- CD |
- B6D2F1 |
- H1227 |
- 0.921 |
- 0.997 |
- 1 |
- 0.931 |
- 0.941 |
- 0.945 |
- 0.918 |
- 0.933 |
- 0.959 |
- 0.929 |
- 0.947 |
- 0.935 |
- 0.933 |
- 0.925 |
- 0.952 |
- 0.938 |
- 0.942 |
- 0.933 |
- 0.943 |
- 0.938 |
- 0.923 |
- 0.926 |
- 0.924 |
- 0.928 |
- 0.931 |
- 0.95 |
- 0.952 |
- 0.942 |
- 0.945 |
- 0.929 |
- 0.921 |
- 0.928 |
- 0.953 |
- 0.923 |
- 0.922 |
- 0.956 |
- 0.941 |
- 0.926 |
- 0.933 |
- 0.925 |
- 0.931 |
- 0.928 |
- 0.923 |
- 0.928 |
- 0.929 |
- 0.948 |
- 0.924 |
- 0.937 |
- 0.927 |
- 0.937 |
- 0.93 |
- 0.935 |
- 0.948 |
- 0.944 |
- 0.931 |
- 0.929 |
- 0.943 |
- 0.914 |
- 0.937 |
- 0.932 |
- 0.935 |
- 0.945 |
- 0.932 |
- 0.945 |
- 0.921 |
- 0.923 |
- 0.956 |
- 0.93 |
- 0.945 |
- 0.93 |
- 0.94 |
- 0.929 |
- 0.933 |
- 0.918 |
- 0.921 |
- 0.932 |
- 0.942 |
- 0.926 |
- 0.94 |
- 0.934 |
- 0.927 |
- 0.933 |
- 0.947 |
- 0.928 |
- 0.933 |
- 0.949 |
- 0.925 |
- 0.926 |
- 0.932 |
- 0.928 |
- 0.925 |
- 0.945 |
- 0.948 |
- 0.941 |
- 0.941 |
- 0.934 |
- 0.945 |
- 0.94 |
- 0.952 |
- 0.94 |
- 0.946 |
- 0.938 |
- 0.96 |
- 0.941 |
- 0.944 |
- 0.917 |
- 0.924 |
- 0.924 |
- 0.924 |
- 0.949 |
- 0.934 |
- 0.922 |
- 0.926 |
- 0.942 |
- 0.929 |
- 0.956 |
- 0.922 |
- 0.938 |
- 0.923 |
- 0.93 |
- 0.931 |
- 0.951 |
- 0.928 |
- 0.957 |
- 0.938 |
- 0.93 |
- 0.931 |
- 0.945 |
- 0.936 |
- 0.94 |
- 0.924 |
- 0.949 |
- 0.945 |
- 0.917 |
- 0.923 |
- 0.948 |
- 0.936 |
- 0.924 |
- 0.943 |
- 0.931 |
- 0.931 |
- 0.95 |
- 0.924 |
- 0.936 |
- 0.935 |
- 0.928 |
- 0.917 |
- 0.929 |
- 0.937 |
- 0.946 |
- |
- 0.914 |
- 0.94 |
-
-
- | Liver |
- 223 |
- F |
- 268 |
- 051112.07 |
- CD |
- BXD100 |
- H0247 |
- 0.992 |
- 0.93 |
- 0.931 |
- 1 |
- 0.985 |
- 0.989 |
- 0.987 |
- 0.966 |
- 0.894 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.985 |
- 0.97 |
- 0.982 |
- 0.972 |
- 0.958 |
- 0.985 |
- 0.988 |
- 0.981 |
- 0.99 |
- 0.986 |
- 0.989 |
- 0.98 |
- 0.974 |
- 0.975 |
- 0.975 |
- 0.991 |
- 0.987 |
- 0.988 |
- 0.987 |
- 0.952 |
- 0.974 |
- 0.984 |
- 0.979 |
- 0.933 |
- 0.987 |
- 0.982 |
- 0.982 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.988 |
- 0.984 |
- 0.946 |
- 0.979 |
- 0.982 |
- 0.985 |
- 0.979 |
- 0.99 |
- 0.961 |
- 0.978 |
- 0.98 |
- 0.986 |
- 0.987 |
- 0.978 |
- 0.98 |
- 0.989 |
- 0.983 |
- 0.974 |
- 0.969 |
- 0.983 |
- 0.906 |
- 0.984 |
- 0.982 |
- 0.975 |
- 0.987 |
- 0.965 |
- 0.939 |
- 0.98 |
- 0.935 |
- 0.991 |
- 0.987 |
- 0.982 |
- 0.983 |
- 0.971 |
- 0.989 |
- 0.989 |
- 0.988 |
- 0.985 |
- 0.989 |
- 0.977 |
- 0.985 |
- 0.985 |
- 0.962 |
- 0.986 |
- 0.989 |
- 0.972 |
- 0.981 |
- 0.98 |
- 0.986 |
- 0.985 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.984 |
- 0.972 |
- 0.979 |
- 0.976 |
- 0.988 |
- 0.983 |
- 0.974 |
- 0.98 |
- 0.986 |
- 0.988 |
- 0.98 |
- 0.986 |
- 0.983 |
- 0.986 |
- 0.952 |
- 0.969 |
- 0.98 |
- 0.969 |
- 0.981 |
- 0.975 |
- 0.982 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.976 |
- 0.983 |
- 0.966 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.97 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.976 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.986 |
- 0.984 |
- 0.935 |
- 0.985 |
- 0.983 |
- 0.989 |
- 0.988 |
- 0.982 |
- 0.935 |
- 0.967 |
- 0.938 |
- |
- 0.894 |
- 0.98 |
-
-
- | Liver |
- 223 |
- F |
- 269 |
- 051112.08 |
- CD |
- BXD100 |
- H0248 |
- 0.983 |
- 0.939 |
- 0.941 |
- 0.985 |
- 1 |
- 0.985 |
- 0.985 |
- 0.959 |
- 0.907 |
- 0.983 |
- 0.978 |
- 0.978 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.976 |
- 0.965 |
- 0.953 |
- 0.976 |
- 0.979 |
- 0.97 |
- 0.98 |
- 0.986 |
- 0.984 |
- 0.974 |
- 0.974 |
- 0.975 |
- 0.969 |
- 0.985 |
- 0.983 |
- 0.978 |
- 0.982 |
- 0.955 |
- 0.973 |
- 0.97 |
- 0.978 |
- 0.943 |
- 0.979 |
- 0.972 |
- 0.968 |
- 0.975 |
- 0.977 |
- 0.971 |
- 0.982 |
- 0.976 |
- 0.957 |
- 0.987 |
- 0.982 |
- 0.981 |
- 0.984 |
- 0.979 |
- 0.963 |
- 0.975 |
- 0.986 |
- 0.984 |
- 0.983 |
- 0.974 |
- 0.966 |
- 0.979 |
- 0.976 |
- 0.984 |
- 0.97 |
- 0.973 |
- 0.915 |
- 0.976 |
- 0.98 |
- 0.972 |
- 0.978 |
- 0.967 |
- 0.942 |
- 0.979 |
- 0.942 |
- 0.981 |
- 0.985 |
- 0.976 |
- 0.976 |
- 0.969 |
- 0.987 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.981 |
- 0.976 |
- 0.98 |
- 0.958 |
- 0.98 |
- 0.982 |
- 0.964 |
- 0.975 |
- 0.968 |
- 0.977 |
- 0.977 |
- 0.971 |
- 0.971 |
- 0.983 |
- 0.976 |
- 0.967 |
- 0.98 |
- 0.97 |
- 0.982 |
- 0.977 |
- 0.978 |
- 0.983 |
- 0.985 |
- 0.978 |
- 0.967 |
- 0.974 |
- 0.972 |
- 0.98 |
- 0.96 |
- 0.965 |
- 0.967 |
- 0.971 |
- 0.987 |
- 0.972 |
- 0.974 |
- 0.98 |
- 0.975 |
- 0.984 |
- 0.982 |
- 0.982 |
- 0.979 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.979 |
- 0.969 |
- 0.974 |
- 0.982 |
- 0.973 |
- 0.98 |
- 0.976 |
- 0.968 |
- 0.983 |
- 0.981 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.941 |
- 0.98 |
- 0.978 |
- 0.982 |
- 0.98 |
- 0.976 |
- 0.942 |
- 0.961 |
- 0.948 |
- |
- 0.907 |
- 0.97 |
-
-
- | Liver |
- 567 |
- F |
- 92 |
- 111314.15 |
- CD |
- BXD100 |
- H1190 |
- 0.985 |
- 0.945 |
- 0.945 |
- 0.989 |
- 0.985 |
- 1 |
- 0.981 |
- 0.965 |
- 0.913 |
- 0.983 |
- 0.984 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.988 |
- 0.972 |
- 0.965 |
- 0.986 |
- 0.987 |
- 0.985 |
- 0.987 |
- 0.984 |
- 0.986 |
- 0.977 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.989 |
- 0.988 |
- 0.983 |
- 0.987 |
- 0.962 |
- 0.971 |
- 0.977 |
- 0.982 |
- 0.939 |
- 0.983 |
- 0.976 |
- 0.977 |
- 0.985 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.981 |
- 0.957 |
- 0.977 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.988 |
- 0.96 |
- 0.978 |
- 0.983 |
- 0.985 |
- 0.988 |
- 0.977 |
- 0.981 |
- 0.99 |
- 0.978 |
- 0.981 |
- 0.974 |
- 0.979 |
- 0.924 |
- 0.982 |
- 0.98 |
- 0.977 |
- 0.983 |
- 0.969 |
- 0.938 |
- 0.98 |
- 0.94 |
- 0.989 |
- 0.981 |
- 0.982 |
- 0.978 |
- 0.971 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.984 |
- 0.987 |
- 0.983 |
- 0.985 |
- 0.984 |
- 0.968 |
- 0.981 |
- 0.986 |
- 0.973 |
- 0.984 |
- 0.98 |
- 0.986 |
- 0.987 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.971 |
- 0.981 |
- 0.974 |
- 0.989 |
- 0.982 |
- 0.976 |
- 0.981 |
- 0.988 |
- 0.983 |
- 0.975 |
- 0.983 |
- 0.979 |
- 0.985 |
- 0.959 |
- 0.966 |
- 0.977 |
- 0.975 |
- 0.979 |
- 0.977 |
- 0.978 |
- 0.984 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.973 |
- 0.981 |
- 0.987 |
- 0.989 |
- 0.97 |
- 0.984 |
- 0.985 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.976 |
- 0.978 |
- 0.988 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.951 |
- 0.981 |
- 0.982 |
- 0.988 |
- 0.985 |
- 0.983 |
- 0.94 |
- 0.969 |
- 0.949 |
- |
- 0.913 |
- 0.98 |
-
-
- | Liver |
- 223 |
- F |
- 3 |
- 051112.09 |
- CD |
- BXD101 |
- H0468 |
- 0.992 |
- 0.916 |
- 0.918 |
- 0.987 |
- 0.985 |
- 0.981 |
- 1 |
- 0.961 |
- 0.877 |
- 0.987 |
- 0.971 |
- 0.982 |
- 0.98 |
- 0.984 |
- 0.969 |
- 0.977 |
- 0.967 |
- 0.958 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.987 |
- 0.99 |
- 0.988 |
- 0.979 |
- 0.972 |
- 0.972 |
- 0.971 |
- 0.985 |
- 0.986 |
- 0.987 |
- 0.986 |
- 0.94 |
- 0.979 |
- 0.98 |
- 0.972 |
- 0.932 |
- 0.988 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.988 |
- 0.981 |
- 0.945 |
- 0.989 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.984 |
- 0.961 |
- 0.972 |
- 0.979 |
- 0.985 |
- 0.986 |
- 0.976 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.976 |
- 0.962 |
- 0.981 |
- 0.893 |
- 0.98 |
- 0.981 |
- 0.97 |
- 0.983 |
- 0.964 |
- 0.944 |
- 0.981 |
- 0.938 |
- 0.987 |
- 1 |
- 0.985 |
- 0.984 |
- 0.968 |
- 0.993 |
- 0.986 |
- 0.987 |
- 0.988 |
- 0.986 |
- 0.973 |
- 0.981 |
- 0.985 |
- 0.957 |
- 0.988 |
- 0.988 |
- 0.97 |
- 0.984 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.974 |
- 0.986 |
- 0.977 |
- 0.969 |
- 0.979 |
- 0.972 |
- 0.98 |
- 0.982 |
- 0.97 |
- 0.98 |
- 0.981 |
- 0.988 |
- 0.976 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.951 |
- 0.974 |
- 0.979 |
- 0.969 |
- 0.988 |
- 0.97 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.988 |
- 0.988 |
- 0.973 |
- 0.985 |
- 0.966 |
- 0.985 |
- 0.985 |
- 0.982 |
- 0.968 |
- 0.976 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.977 |
- 0.977 |
- 0.987 |
- 0.975 |
- 0.981 |
- 0.988 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.921 |
- 0.988 |
- 0.981 |
- 0.987 |
- 0.989 |
- 0.986 |
- 0.938 |
- 0.966 |
- 0.94 |
- |
- 0.877 |
- 0.98 |
-
-
- | Liver |
- 349 |
- F |
- 117 |
- 111414.20 |
- CD |
- BXD101 |
- H1425 |
- 0.96 |
- 0.935 |
- 0.933 |
- 0.966 |
- 0.959 |
- 0.965 |
- 0.961 |
- 1 |
- 0.922 |
- 0.96 |
- 0.949 |
- 0.971 |
- 0.952 |
- 0.957 |
- 0.963 |
- 0.959 |
- 0.978 |
- 0.972 |
- 0.962 |
- 0.966 |
- 0.962 |
- 0.966 |
- 0.963 |
- 0.965 |
- 0.976 |
- 0.977 |
- 0.976 |
- 0.983 |
- 0.968 |
- 0.962 |
- 0.966 |
- 0.967 |
- 0.919 |
- 0.974 |
- 0.978 |
- 0.977 |
- 0.968 |
- 0.969 |
- 0.982 |
- 0.973 |
- 0.969 |
- 0.962 |
- 0.968 |
- 0.964 |
- 0.977 |
- 0.965 |
- 0.946 |
- 0.96 |
- 0.964 |
- 0.966 |
- 0.969 |
- 0.979 |
- 0.979 |
- 0.958 |
- 0.964 |
- 0.962 |
- 0.976 |
- 0.964 |
- 0.97 |
- 0.975 |
- 0.942 |
- 0.931 |
- 0.972 |
- 0.879 |
- 0.953 |
- 0.951 |
- 0.968 |
- 0.965 |
- 0.973 |
- 0.966 |
- 0.975 |
- 0.964 |
- 0.962 |
- 0.961 |
- 0.974 |
- 0.975 |
- 0.98 |
- 0.956 |
- 0.966 |
- 0.966 |
- 0.966 |
- 0.956 |
- 0.944 |
- 0.956 |
- 0.972 |
- 0.966 |
- 0.964 |
- 0.964 |
- 0.983 |
- 0.965 |
- 0.96 |
- 0.965 |
- 0.969 |
- 0.981 |
- 0.981 |
- 0.964 |
- 0.965 |
- 0.981 |
- 0.966 |
- 0.978 |
- 0.958 |
- 0.972 |
- 0.97 |
- 0.968 |
- 0.956 |
- 0.963 |
- 0.97 |
- 0.96 |
- 0.95 |
- 0.972 |
- 0.914 |
- 0.979 |
- 0.977 |
- 0.972 |
- 0.962 |
- 0.968 |
- 0.964 |
- 0.95 |
- 0.966 |
- 0.958 |
- 0.958 |
- 0.948 |
- 0.962 |
- 0.955 |
- 0.974 |
- 0.969 |
- 0.965 |
- 0.982 |
- 0.97 |
- 0.974 |
- 0.968 |
- 0.972 |
- 0.965 |
- 0.965 |
- 0.954 |
- 0.955 |
- 0.949 |
- 0.961 |
- 0.973 |
- 0.955 |
- 0.97 |
- 0.908 |
- 0.958 |
- 0.949 |
- 0.966 |
- 0.963 |
- 0.97 |
- 0.964 |
- 0.964 |
- 0.965 |
- |
- 0.879 |
- 0.96 |
-
-
- | Liver |
- 756 |
- F |
- 179 |
- 102616.20 |
- CD |
- BXD101 |
- H2114 |
- 0.877 |
- 0.962 |
- 0.959 |
- 0.894 |
- 0.907 |
- 0.913 |
- 0.877 |
- 0.922 |
- 1 |
- 0.894 |
- 0.917 |
- 0.897 |
- 0.897 |
- 0.887 |
- 0.926 |
- 0.902 |
- 0.922 |
- 0.909 |
- 0.905 |
- 0.903 |
- 0.885 |
- 0.886 |
- 0.884 |
- 0.889 |
- 0.902 |
- 0.928 |
- 0.928 |
- 0.915 |
- 0.907 |
- 0.891 |
- 0.883 |
- 0.894 |
- 0.919 |
- 0.893 |
- 0.891 |
- 0.933 |
- 0.939 |
- 0.884 |
- 0.901 |
- 0.888 |
- 0.893 |
- 0.888 |
- 0.888 |
- 0.887 |
- 0.897 |
- 0.932 |
- 0.883 |
- 0.903 |
- 0.884 |
- 0.9 |
- 0.893 |
- 0.916 |
- 0.923 |
- 0.91 |
- 0.892 |
- 0.891 |
- 0.914 |
- 0.878 |
- 0.901 |
- 0.898 |
- 0.894 |
- 0.901 |
- 0.895 |
- 0.918 |
- 0.882 |
- 0.884 |
- 0.925 |
- 0.893 |
- 0.929 |
- 0.918 |
- 0.909 |
- 0.922 |
- 0.894 |
- 0.877 |
- 0.89 |
- 0.898 |
- 0.92 |
- 0.881 |
- 0.901 |
- 0.895 |
- 0.89 |
- 0.892 |
- 0.917 |
- 0.892 |
- 0.898 |
- 0.926 |
- 0.887 |
- 0.886 |
- 0.914 |
- 0.887 |
- 0.888 |
- 0.908 |
- 0.913 |
- 0.911 |
- 0.911 |
- 0.896 |
- 0.904 |
- 0.919 |
- 0.919 |
- 0.914 |
- 0.905 |
- 0.899 |
- 0.932 |
- 0.91 |
- 0.907 |
- 0.878 |
- 0.891 |
- 0.882 |
- 0.88 |
- 0.916 |
- 0.896 |
- 0.895 |
- 0.892 |
- 0.922 |
- 0.889 |
- 0.925 |
- 0.88 |
- 0.895 |
- 0.885 |
- 0.889 |
- 0.894 |
- 0.919 |
- 0.892 |
- 0.926 |
- 0.901 |
- 0.892 |
- 0.892 |
- 0.926 |
- 0.904 |
- 0.906 |
- 0.889 |
- 0.916 |
- 0.904 |
- 0.879 |
- 0.88 |
- 0.918 |
- 0.889 |
- 0.884 |
- 0.91 |
- 0.888 |
- 0.892 |
- 0.939 |
- 0.88 |
- 0.894 |
- 0.895 |
- 0.889 |
- 0.882 |
- 0.922 |
- 0.903 |
- 0.941 |
- |
- 0.877 |
- 0.90 |
-
-
- | Liver |
- 183 |
- F |
- 83 |
- 053014.01 |
- CD |
- BXD102 |
- H1363 |
- 0.988 |
- 0.928 |
- 0.929 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.987 |
- 0.96 |
- 0.894 |
- 1 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.985 |
- 0.973 |
- 0.979 |
- 0.972 |
- 0.96 |
- 0.979 |
- 0.981 |
- 0.971 |
- 0.985 |
- 0.985 |
- 0.987 |
- 0.981 |
- 0.976 |
- 0.976 |
- 0.971 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.951 |
- 0.976 |
- 0.976 |
- 0.975 |
- 0.935 |
- 0.982 |
- 0.975 |
- 0.976 |
- 0.984 |
- 0.982 |
- 0.982 |
- 0.985 |
- 0.979 |
- 0.945 |
- 0.983 |
- 0.983 |
- 0.98 |
- 0.977 |
- 0.983 |
- 0.959 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.977 |
- 0.974 |
- 0.983 |
- 0.982 |
- 0.976 |
- 0.969 |
- 0.977 |
- 0.906 |
- 0.984 |
- 0.98 |
- 0.975 |
- 0.982 |
- 0.973 |
- 0.948 |
- 0.981 |
- 0.943 |
- 0.985 |
- 0.987 |
- 0.976 |
- 0.982 |
- 0.97 |
- 0.987 |
- 0.984 |
- 0.985 |
- 0.984 |
- 0.985 |
- 0.976 |
- 0.988 |
- 0.987 |
- 0.964 |
- 0.986 |
- 0.984 |
- 0.971 |
- 0.981 |
- 0.977 |
- 0.98 |
- 0.979 |
- 0.974 |
- 0.974 |
- 0.985 |
- 0.977 |
- 0.969 |
- 0.98 |
- 0.972 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.977 |
- 0.979 |
- 0.981 |
- 0.978 |
- 0.981 |
- 0.976 |
- 0.981 |
- 0.953 |
- 0.97 |
- 0.975 |
- 0.965 |
- 0.983 |
- 0.975 |
- 0.98 |
- 0.981 |
- 0.983 |
- 0.987 |
- 0.985 |
- 0.976 |
- 0.982 |
- 0.97 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.967 |
- 0.975 |
- 0.979 |
- 0.977 |
- 0.981 |
- 0.977 |
- 0.974 |
- 0.981 |
- 0.977 |
- 0.98 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.98 |
- 0.932 |
- 0.982 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.976 |
- 0.943 |
- 0.968 |
- 0.94 |
- |
- 0.894 |
- 0.98 |
-
-
- | Liver |
- 501 |
- F |
- 270 |
- 042915.01 |
- CD |
- BXD102 |
- H1499 |
- 0.976 |
- 0.945 |
- 0.947 |
- 0.981 |
- 0.978 |
- 0.984 |
- 0.971 |
- 0.949 |
- 0.917 |
- 0.979 |
- 1 |
- 0.97 |
- 0.977 |
- 0.971 |
- 0.968 |
- 0.978 |
- 0.963 |
- 0.949 |
- 0.978 |
- 0.98 |
- 0.969 |
- 0.974 |
- 0.969 |
- 0.974 |
- 0.961 |
- 0.969 |
- 0.97 |
- 0.962 |
- 0.982 |
- 0.975 |
- 0.97 |
- 0.973 |
- 0.97 |
- 0.959 |
- 0.962 |
- 0.976 |
- 0.921 |
- 0.971 |
- 0.962 |
- 0.966 |
- 0.974 |
- 0.975 |
- 0.969 |
- 0.979 |
- 0.967 |
- 0.938 |
- 0.973 |
- 0.978 |
- 0.973 |
- 0.968 |
- 0.975 |
- 0.941 |
- 0.968 |
- 0.977 |
- 0.973 |
- 0.975 |
- 0.965 |
- 0.963 |
- 0.976 |
- 0.969 |
- 0.969 |
- 0.974 |
- 0.965 |
- 0.927 |
- 0.972 |
- 0.968 |
- 0.97 |
- 0.972 |
- 0.956 |
- 0.927 |
- 0.968 |
- 0.922 |
- 0.982 |
- 0.971 |
- 0.961 |
- 0.969 |
- 0.961 |
- 0.977 |
- 0.982 |
- 0.979 |
- 0.973 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.977 |
- 0.957 |
- 0.972 |
- 0.974 |
- 0.957 |
- 0.97 |
- 0.97 |
- 0.978 |
- 0.977 |
- 0.968 |
- 0.967 |
- 0.974 |
- 0.979 |
- 0.953 |
- 0.971 |
- 0.958 |
- 0.985 |
- 0.973 |
- 0.97 |
- 0.97 |
- 0.984 |
- 0.97 |
- 0.968 |
- 0.976 |
- 0.972 |
- 0.977 |
- 0.96 |
- 0.95 |
- 0.963 |
- 0.966 |
- 0.967 |
- 0.97 |
- 0.968 |
- 0.978 |
- 0.973 |
- 0.975 |
- 0.972 |
- 0.98 |
- 0.971 |
- 0.965 |
- 0.971 |
- 0.974 |
- 0.975 |
- 0.958 |
- 0.971 |
- 0.972 |
- 0.971 |
- 0.977 |
- 0.979 |
- 0.959 |
- 0.966 |
- 0.983 |
- 0.979 |
- 0.965 |
- 0.972 |
- 0.977 |
- 0.968 |
- 0.955 |
- 0.973 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.963 |
- 0.922 |
- 0.96 |
- 0.932 |
- |
- 0.917 |
- 0.97 |
-
-
- | Liver |
- 205 |
- F |
- 163 |
- 012615.19 |
- CD |
- BXD24 |
- H1792 |
- 0.987 |
- 0.934 |
- 0.935 |
- 0.984 |
- 0.978 |
- 0.985 |
- 0.982 |
- 0.971 |
- 0.897 |
- 0.981 |
- 0.97 |
- 1 |
- 0.978 |
- 0.982 |
- 0.978 |
- 0.987 |
- 0.974 |
- 0.971 |
- 0.982 |
- 0.983 |
- 0.979 |
- 0.989 |
- 0.986 |
- 0.989 |
- 0.986 |
- 0.978 |
- 0.978 |
- 0.984 |
- 0.983 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.947 |
- 0.977 |
- 0.985 |
- 0.982 |
- 0.946 |
- 0.987 |
- 0.985 |
- 0.983 |
- 0.987 |
- 0.981 |
- 0.979 |
- 0.985 |
- 0.986 |
- 0.956 |
- 0.973 |
- 0.977 |
- 0.988 |
- 0.981 |
- 0.989 |
- 0.972 |
- 0.983 |
- 0.974 |
- 0.986 |
- 0.986 |
- 0.982 |
- 0.981 |
- 0.988 |
- 0.982 |
- 0.976 |
- 0.962 |
- 0.988 |
- 0.899 |
- 0.983 |
- 0.977 |
- 0.976 |
- 0.984 |
- 0.975 |
- 0.951 |
- 0.985 |
- 0.954 |
- 0.983 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.977 |
- 0.984 |
- 0.987 |
- 0.987 |
- 0.981 |
- 0.979 |
- 0.969 |
- 0.977 |
- 0.985 |
- 0.971 |
- 0.984 |
- 0.986 |
- 0.978 |
- 0.986 |
- 0.978 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.984 |
- 0.981 |
- 0.986 |
- 0.97 |
- 0.978 |
- 0.977 |
- 0.984 |
- 0.976 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.947 |
- 0.976 |
- 0.983 |
- 0.97 |
- 0.982 |
- 0.976 |
- 0.985 |
- 0.976 |
- 0.984 |
- 0.98 |
- 0.979 |
- 0.971 |
- 0.98 |
- 0.968 |
- 0.986 |
- 0.989 |
- 0.987 |
- 0.975 |
- 0.982 |
- 0.988 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.979 |
- 0.975 |
- 0.98 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.988 |
- 0.928 |
- 0.982 |
- 0.977 |
- 0.987 |
- 0.986 |
- 0.985 |
- 0.954 |
- 0.977 |
- 0.949 |
- |
- 0.897 |
- 0.98 |
-
-
- | Liver |
- 572 |
- F |
- 299 |
- 061913.01 |
- CD |
- BXD29 |
- H0742 |
- 0.982 |
- 0.932 |
- 0.933 |
- 0.983 |
- 0.981 |
- 0.983 |
- 0.98 |
- 0.952 |
- 0.897 |
- 0.982 |
- 0.977 |
- 0.978 |
- 1 |
- 0.988 |
- 0.972 |
- 0.977 |
- 0.965 |
- 0.953 |
- 0.979 |
- 0.982 |
- 0.973 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.973 |
- 0.97 |
- 0.97 |
- 0.963 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.96 |
- 0.971 |
- 0.973 |
- 0.973 |
- 0.925 |
- 0.977 |
- 0.968 |
- 0.969 |
- 0.98 |
- 0.98 |
- 0.975 |
- 0.983 |
- 0.977 |
- 0.943 |
- 0.977 |
- 0.98 |
- 0.976 |
- 0.97 |
- 0.984 |
- 0.953 |
- 0.973 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.969 |
- 0.972 |
- 0.983 |
- 0.971 |
- 0.979 |
- 0.967 |
- 0.976 |
- 0.912 |
- 0.985 |
- 0.984 |
- 0.974 |
- 0.983 |
- 0.966 |
- 0.935 |
- 0.975 |
- 0.934 |
- 0.985 |
- 0.98 |
- 0.976 |
- 0.971 |
- 0.965 |
- 0.983 |
- 0.986 |
- 0.984 |
- 0.973 |
- 0.979 |
- 0.975 |
- 0.981 |
- 0.976 |
- 0.963 |
- 0.985 |
- 0.987 |
- 0.971 |
- 0.971 |
- 0.974 |
- 0.979 |
- 0.979 |
- 0.969 |
- 0.968 |
- 0.985 |
- 0.975 |
- 0.961 |
- 0.977 |
- 0.965 |
- 0.984 |
- 0.973 |
- 0.969 |
- 0.976 |
- 0.985 |
- 0.979 |
- 0.973 |
- 0.98 |
- 0.98 |
- 0.976 |
- 0.964 |
- 0.959 |
- 0.967 |
- 0.964 |
- 0.977 |
- 0.974 |
- 0.974 |
- 0.979 |
- 0.978 |
- 0.982 |
- 0.979 |
- 0.976 |
- 0.973 |
- 0.967 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.963 |
- 0.974 |
- 0.979 |
- 0.977 |
- 0.976 |
- 0.975 |
- 0.967 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.977 |
- 0.981 |
- 0.982 |
- 0.977 |
- 0.944 |
- 0.978 |
- 0.98 |
- 0.984 |
- 0.979 |
- 0.975 |
- 0.934 |
- 0.961 |
- 0.938 |
- |
- 0.897 |
- 0.97 |
-
-
- | Liver |
- 574 |
- F |
- 314 |
- 111314.11 |
- CD |
- BXD29 |
- H1040 |
- 0.989 |
- 0.923 |
- 0.925 |
- 0.985 |
- 0.979 |
- 0.982 |
- 0.984 |
- 0.957 |
- 0.887 |
- 0.985 |
- 0.971 |
- 0.982 |
- 0.988 |
- 1 |
- 0.972 |
- 0.978 |
- 0.97 |
- 0.955 |
- 0.982 |
- 0.984 |
- 0.973 |
- 0.986 |
- 0.986 |
- 0.988 |
- 0.983 |
- 0.969 |
- 0.969 |
- 0.968 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.984 |
- 0.949 |
- 0.973 |
- 0.981 |
- 0.973 |
- 0.93 |
- 0.981 |
- 0.976 |
- 0.978 |
- 0.983 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.978 |
- 0.939 |
- 0.977 |
- 0.98 |
- 0.979 |
- 0.974 |
- 0.986 |
- 0.957 |
- 0.975 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.976 |
- 0.974 |
- 0.987 |
- 0.978 |
- 0.978 |
- 0.965 |
- 0.981 |
- 0.904 |
- 0.986 |
- 0.984 |
- 0.973 |
- 0.987 |
- 0.97 |
- 0.94 |
- 0.979 |
- 0.938 |
- 0.984 |
- 0.984 |
- 0.979 |
- 0.978 |
- 0.969 |
- 0.986 |
- 0.987 |
- 0.986 |
- 0.979 |
- 0.983 |
- 0.974 |
- 0.979 |
- 0.981 |
- 0.963 |
- 0.99 |
- 0.991 |
- 0.977 |
- 0.977 |
- 0.978 |
- 0.982 |
- 0.982 |
- 0.975 |
- 0.975 |
- 0.987 |
- 0.978 |
- 0.969 |
- 0.978 |
- 0.973 |
- 0.983 |
- 0.976 |
- 0.972 |
- 0.976 |
- 0.979 |
- 0.982 |
- 0.978 |
- 0.983 |
- 0.985 |
- 0.982 |
- 0.956 |
- 0.968 |
- 0.976 |
- 0.96 |
- 0.982 |
- 0.973 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.982 |
- 0.984 |
- 0.974 |
- 0.982 |
- 0.965 |
- 0.981 |
- 0.985 |
- 0.982 |
- 0.966 |
- 0.978 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.978 |
- 0.975 |
- 0.981 |
- 0.976 |
- 0.982 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.982 |
- 0.932 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.978 |
- 0.938 |
- 0.966 |
- 0.935 |
- |
- 0.887 |
- 0.97 |
-
-
- | Liver |
- 724 |
- F |
- 141 |
- 012615.08 |
- CD |
- BXD29 |
- H1044 |
- 0.97 |
- 0.952 |
- 0.952 |
- 0.97 |
- 0.978 |
- 0.981 |
- 0.969 |
- 0.963 |
- 0.926 |
- 0.973 |
- 0.968 |
- 0.978 |
- 0.972 |
- 0.972 |
- 1 |
- 0.976 |
- 0.967 |
- 0.962 |
- 0.971 |
- 0.977 |
- 0.967 |
- 0.972 |
- 0.974 |
- 0.975 |
- 0.974 |
- 0.974 |
- 0.974 |
- 0.974 |
- 0.978 |
- 0.977 |
- 0.97 |
- 0.973 |
- 0.958 |
- 0.964 |
- 0.966 |
- 0.978 |
- 0.953 |
- 0.971 |
- 0.97 |
- 0.965 |
- 0.974 |
- 0.971 |
- 0.962 |
- 0.973 |
- 0.971 |
- 0.962 |
- 0.968 |
- 0.973 |
- 0.971 |
- 0.976 |
- 0.974 |
- 0.964 |
- 0.977 |
- 0.976 |
- 0.972 |
- 0.977 |
- 0.976 |
- 0.966 |
- 0.974 |
- 0.969 |
- 0.976 |
- 0.967 |
- 0.968 |
- 0.919 |
- 0.969 |
- 0.969 |
- 0.975 |
- 0.972 |
- 0.976 |
- 0.953 |
- 0.98 |
- 0.952 |
- 0.975 |
- 0.969 |
- 0.972 |
- 0.969 |
- 0.969 |
- 0.971 |
- 0.974 |
- 0.973 |
- 0.974 |
- 0.972 |
- 0.972 |
- 0.968 |
- 0.974 |
- 0.969 |
- 0.972 |
- 0.975 |
- 0.97 |
- 0.973 |
- 0.964 |
- 0.973 |
- 0.974 |
- 0.973 |
- 0.972 |
- 0.974 |
- 0.974 |
- 0.972 |
- 0.978 |
- 0.974 |
- 0.974 |
- 0.978 |
- 0.976 |
- 0.972 |
- 0.975 |
- 0.968 |
- 0.963 |
- 0.967 |
- 0.963 |
- 0.977 |
- 0.948 |
- 0.961 |
- 0.967 |
- 0.972 |
- 0.974 |
- 0.975 |
- 0.964 |
- 0.973 |
- 0.969 |
- 0.971 |
- 0.971 |
- 0.977 |
- 0.971 |
- 0.977 |
- 0.973 |
- 0.973 |
- 0.975 |
- 0.97 |
- 0.971 |
- 0.976 |
- 0.967 |
- 0.977 |
- 0.974 |
- 0.968 |
- 0.967 |
- 0.975 |
- 0.968 |
- 0.973 |
- 0.977 |
- 0.97 |
- 0.972 |
- 0.942 |
- 0.968 |
- 0.967 |
- 0.976 |
- 0.973 |
- 0.97 |
- 0.952 |
- 0.964 |
- 0.957 |
- |
- 0.919 |
- 0.97 |
-
-
- | Liver |
- 200 |
- F |
- 259 |
- 042015.22 |
- CD |
- BXD32 |
- H2034 |
- 0.983 |
- 0.938 |
- 0.938 |
- 0.982 |
- 0.976 |
- 0.988 |
- 0.977 |
- 0.959 |
- 0.902 |
- 0.979 |
- 0.978 |
- 0.987 |
- 0.977 |
- 0.978 |
- 0.976 |
- 1 |
- 0.973 |
- 0.966 |
- 0.982 |
- 0.982 |
- 0.981 |
- 0.986 |
- 0.978 |
- 0.982 |
- 0.976 |
- 0.971 |
- 0.971 |
- 0.974 |
- 0.982 |
- 0.985 |
- 0.979 |
- 0.984 |
- 0.954 |
- 0.965 |
- 0.974 |
- 0.978 |
- 0.931 |
- 0.98 |
- 0.975 |
- 0.975 |
- 0.983 |
- 0.976 |
- 0.973 |
- 0.981 |
- 0.977 |
- 0.948 |
- 0.972 |
- 0.977 |
- 0.983 |
- 0.975 |
- 0.986 |
- 0.954 |
- 0.974 |
- 0.975 |
- 0.981 |
- 0.985 |
- 0.972 |
- 0.981 |
- 0.988 |
- 0.977 |
- 0.977 |
- 0.967 |
- 0.979 |
- 0.913 |
- 0.981 |
- 0.974 |
- 0.969 |
- 0.98 |
- 0.967 |
- 0.934 |
- 0.975 |
- 0.937 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.977 |
- 0.967 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.976 |
- 0.977 |
- 0.976 |
- 0.978 |
- 0.978 |
- 0.962 |
- 0.977 |
- 0.981 |
- 0.969 |
- 0.988 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.976 |
- 0.975 |
- 0.979 |
- 0.979 |
- 0.968 |
- 0.975 |
- 0.972 |
- 0.983 |
- 0.981 |
- 0.967 |
- 0.976 |
- 0.98 |
- 0.979 |
- 0.969 |
- 0.98 |
- 0.978 |
- 0.981 |
- 0.952 |
- 0.963 |
- 0.975 |
- 0.968 |
- 0.975 |
- 0.969 |
- 0.978 |
- 0.975 |
- 0.981 |
- 0.976 |
- 0.977 |
- 0.977 |
- 0.98 |
- 0.966 |
- 0.978 |
- 0.985 |
- 0.987 |
- 0.963 |
- 0.981 |
- 0.982 |
- 0.978 |
- 0.981 |
- 0.979 |
- 0.979 |
- 0.973 |
- 0.982 |
- 0.98 |
- 0.976 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.942 |
- 0.976 |
- 0.977 |
- 0.983 |
- 0.984 |
- 0.98 |
- 0.937 |
- 0.97 |
- 0.942 |
- |
- 0.902 |
- 0.97 |
-
-
- | Liver |
- 386 |
- F |
- 131 |
- 083016.01 |
- CD |
- BXD32 |
- H2494 |
- 0.971 |
- 0.943 |
- 0.942 |
- 0.972 |
- 0.965 |
- 0.972 |
- 0.967 |
- 0.978 |
- 0.922 |
- 0.972 |
- 0.963 |
- 0.974 |
- 0.965 |
- 0.97 |
- 0.967 |
- 0.973 |
- 1 |
- 0.969 |
- 0.977 |
- 0.973 |
- 0.957 |
- 0.972 |
- 0.969 |
- 0.972 |
- 0.979 |
- 0.979 |
- 0.979 |
- 0.978 |
- 0.976 |
- 0.967 |
- 0.971 |
- 0.969 |
- 0.938 |
- 0.979 |
- 0.981 |
- 0.985 |
- 0.959 |
- 0.972 |
- 0.982 |
- 0.976 |
- 0.973 |
- 0.971 |
- 0.978 |
- 0.971 |
- 0.975 |
- 0.954 |
- 0.96 |
- 0.97 |
- 0.969 |
- 0.967 |
- 0.974 |
- 0.972 |
- 0.982 |
- 0.971 |
- 0.974 |
- 0.967 |
- 0.979 |
- 0.967 |
- 0.982 |
- 0.983 |
- 0.959 |
- 0.952 |
- 0.978 |
- 0.896 |
- 0.968 |
- 0.969 |
- 0.977 |
- 0.971 |
- 0.978 |
- 0.959 |
- 0.975 |
- 0.958 |
- 0.968 |
- 0.967 |
- 0.972 |
- 0.983 |
- 0.989 |
- 0.968 |
- 0.976 |
- 0.975 |
- 0.964 |
- 0.963 |
- 0.956 |
- 0.968 |
- 0.972 |
- 0.975 |
- 0.972 |
- 0.97 |
- 0.983 |
- 0.969 |
- 0.975 |
- 0.979 |
- 0.981 |
- 0.981 |
- 0.981 |
- 0.973 |
- 0.973 |
- 0.977 |
- 0.976 |
- 0.976 |
- 0.97 |
- 0.971 |
- 0.978 |
- 0.971 |
- 0.965 |
- 0.969 |
- 0.978 |
- 0.969 |
- 0.966 |
- 0.978 |
- 0.928 |
- 0.979 |
- 0.977 |
- 0.969 |
- 0.967 |
- 0.977 |
- 0.97 |
- 0.962 |
- 0.968 |
- 0.966 |
- 0.971 |
- 0.963 |
- 0.968 |
- 0.962 |
- 0.977 |
- 0.973 |
- 0.97 |
- 0.982 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.978 |
- 0.973 |
- 0.974 |
- 0.965 |
- 0.969 |
- 0.964 |
- 0.967 |
- 0.981 |
- 0.964 |
- 0.973 |
- 0.921 |
- 0.967 |
- 0.961 |
- 0.968 |
- 0.969 |
- 0.967 |
- 0.958 |
- 0.973 |
- 0.959 |
- |
- 0.896 |
- 0.97 |
-
-
- | Liver |
- 201 |
- F |
- 170 |
- 101513.02 |
- CD |
- BXD34 |
- H1054 |
- 0.957 |
- 0.935 |
- 0.933 |
- 0.958 |
- 0.953 |
- 0.965 |
- 0.958 |
- 0.972 |
- 0.909 |
- 0.96 |
- 0.949 |
- 0.971 |
- 0.953 |
- 0.955 |
- 0.962 |
- 0.966 |
- 0.969 |
- 1 |
- 0.967 |
- 0.959 |
- 0.963 |
- 0.964 |
- 0.96 |
- 0.965 |
- 0.973 |
- 0.971 |
- 0.97 |
- 0.976 |
- 0.963 |
- 0.96 |
- 0.958 |
- 0.964 |
- 0.929 |
- 0.96 |
- 0.968 |
- 0.973 |
- 0.95 |
- 0.962 |
- 0.969 |
- 0.964 |
- 0.971 |
- 0.959 |
- 0.958 |
- 0.963 |
- 0.972 |
- 0.957 |
- 0.947 |
- 0.956 |
- 0.961 |
- 0.96 |
- 0.967 |
- 0.964 |
- 0.974 |
- 0.951 |
- 0.96 |
- 0.96 |
- 0.972 |
- 0.968 |
- 0.967 |
- 0.966 |
- 0.949 |
- 0.941 |
- 0.971 |
- 0.88 |
- 0.956 |
- 0.95 |
- 0.973 |
- 0.963 |
- 0.969 |
- 0.958 |
- 0.97 |
- 0.962 |
- 0.959 |
- 0.958 |
- 0.969 |
- 0.966 |
- 0.969 |
- 0.956 |
- 0.969 |
- 0.969 |
- 0.959 |
- 0.958 |
- 0.95 |
- 0.962 |
- 0.974 |
- 0.973 |
- 0.962 |
- 0.962 |
- 0.972 |
- 0.972 |
- 0.969 |
- 0.968 |
- 0.972 |
- 0.967 |
- 0.965 |
- 0.968 |
- 0.965 |
- 0.973 |
- 0.968 |
- 0.972 |
- 0.959 |
- 0.969 |
- 0.966 |
- 0.964 |
- 0.956 |
- 0.955 |
- 0.96 |
- 0.964 |
- 0.952 |
- 0.967 |
- 0.926 |
- 0.961 |
- 0.967 |
- 0.967 |
- 0.962 |
- 0.973 |
- 0.962 |
- 0.957 |
- 0.97 |
- 0.964 |
- 0.961 |
- 0.951 |
- 0.964 |
- 0.959 |
- 0.968 |
- 0.969 |
- 0.964 |
- 0.97 |
- 0.964 |
- 0.969 |
- 0.962 |
- 0.967 |
- 0.965 |
- 0.963 |
- 0.956 |
- 0.958 |
- 0.956 |
- 0.962 |
- 0.974 |
- 0.954 |
- 0.965 |
- 0.914 |
- 0.957 |
- 0.952 |
- 0.965 |
- 0.966 |
- 0.965 |
- 0.962 |
- 0.99 |
- 0.972 |
- |
- 0.88 |
- 0.96 |
-
-
- | Liver |
- 554 |
- F |
- 180 |
- 101513.05 |
- CD |
- BXD34 |
- H0765 |
- 0.984 |
- 0.941 |
- 0.943 |
- 0.985 |
- 0.976 |
- 0.986 |
- 0.978 |
- 0.962 |
- 0.905 |
- 0.979 |
- 0.978 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.971 |
- 0.982 |
- 0.977 |
- 0.967 |
- 1 |
- 0.984 |
- 0.975 |
- 0.983 |
- 0.979 |
- 0.984 |
- 0.978 |
- 0.973 |
- 0.973 |
- 0.974 |
- 0.986 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.958 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.936 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.981 |
- 0.979 |
- 0.983 |
- 0.977 |
- 0.945 |
- 0.976 |
- 0.983 |
- 0.981 |
- 0.975 |
- 0.985 |
- 0.96 |
- 0.978 |
- 0.977 |
- 0.983 |
- 0.98 |
- 0.976 |
- 0.977 |
- 0.988 |
- 0.979 |
- 0.975 |
- 0.972 |
- 0.981 |
- 0.915 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.983 |
- 0.966 |
- 0.939 |
- 0.976 |
- 0.939 |
- 0.984 |
- 0.978 |
- 0.977 |
- 0.979 |
- 0.974 |
- 0.983 |
- 0.989 |
- 0.989 |
- 0.976 |
- 0.984 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.975 |
- 0.981 |
- 0.985 |
- 0.975 |
- 0.979 |
- 0.986 |
- 0.997 |
- 0.997 |
- 0.981 |
- 0.981 |
- 0.984 |
- 0.985 |
- 0.972 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.98 |
- 0.976 |
- 0.977 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.986 |
- 0.956 |
- 0.969 |
- 0.98 |
- 0.97 |
- 0.976 |
- 0.982 |
- 0.981 |
- 0.984 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.982 |
- 0.979 |
- 0.969 |
- 0.983 |
- 0.986 |
- 0.984 |
- 0.971 |
- 0.983 |
- 0.984 |
- 0.985 |
- 0.986 |
- 0.985 |
- 0.979 |
- 0.975 |
- 0.982 |
- 0.987 |
- 0.977 |
- 0.984 |
- 0.984 |
- 0.98 |
- 0.94 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.984 |
- 0.977 |
- 0.939 |
- 0.977 |
- 0.944 |
- |
- 0.905 |
- 0.98 |
-
-
- | Liver |
- 550 |
- F |
- 276 |
- 102414.02 |
- CD |
- BXD39 |
- H1322 |
- 0.986 |
- 0.936 |
- 0.938 |
- 0.988 |
- 0.979 |
- 0.987 |
- 0.978 |
- 0.966 |
- 0.903 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.977 |
- 0.982 |
- 0.973 |
- 0.959 |
- 0.984 |
- 1 |
- 0.981 |
- 0.986 |
- 0.983 |
- 0.985 |
- 0.979 |
- 0.975 |
- 0.975 |
- 0.976 |
- 0.989 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.957 |
- 0.973 |
- 0.981 |
- 0.979 |
- 0.936 |
- 0.984 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.979 |
- 0.947 |
- 0.974 |
- 0.981 |
- 0.982 |
- 0.977 |
- 0.987 |
- 0.961 |
- 0.98 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.977 |
- 0.978 |
- 0.988 |
- 0.98 |
- 0.976 |
- 0.971 |
- 0.979 |
- 0.913 |
- 0.983 |
- 0.979 |
- 0.975 |
- 0.985 |
- 0.967 |
- 0.939 |
- 0.981 |
- 0.935 |
- 0.987 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.975 |
- 0.983 |
- 0.986 |
- 0.985 |
- 0.979 |
- 0.983 |
- 0.973 |
- 0.982 |
- 0.981 |
- 0.966 |
- 0.984 |
- 0.986 |
- 0.973 |
- 0.978 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.984 |
- 0.971 |
- 0.978 |
- 0.975 |
- 0.985 |
- 0.981 |
- 0.973 |
- 0.976 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.983 |
- 0.952 |
- 0.968 |
- 0.978 |
- 0.968 |
- 0.975 |
- 0.975 |
- 0.977 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.976 |
- 0.976 |
- 0.976 |
- 0.966 |
- 0.981 |
- 0.986 |
- 0.985 |
- 0.97 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.976 |
- 0.974 |
- 0.98 |
- 0.982 |
- 0.975 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.938 |
- 0.982 |
- 0.979 |
- 0.984 |
- 0.983 |
- 0.978 |
- 0.935 |
- 0.968 |
- 0.938 |
- |
- 0.903 |
- 0.98 |
-
-
- | Liver |
- 730 |
- F |
- 168 |
- 010614.06 |
- CD |
- BXD39 |
- H0673 |
- 0.979 |
- 0.923 |
- 0.923 |
- 0.981 |
- 0.97 |
- 0.985 |
- 0.977 |
- 0.962 |
- 0.885 |
- 0.971 |
- 0.969 |
- 0.979 |
- 0.973 |
- 0.973 |
- 0.967 |
- 0.981 |
- 0.957 |
- 0.963 |
- 0.975 |
- 0.981 |
- 1 |
- 0.982 |
- 0.977 |
- 0.978 |
- 0.97 |
- 0.965 |
- 0.964 |
- 0.971 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.944 |
- 0.961 |
- 0.972 |
- 0.968 |
- 0.923 |
- 0.98 |
- 0.972 |
- 0.976 |
- 0.979 |
- 0.974 |
- 0.966 |
- 0.979 |
- 0.978 |
- 0.947 |
- 0.966 |
- 0.972 |
- 0.977 |
- 0.971 |
- 0.983 |
- 0.95 |
- 0.966 |
- 0.966 |
- 0.976 |
- 0.981 |
- 0.967 |
- 0.981 |
- 0.98 |
- 0.969 |
- 0.967 |
- 0.954 |
- 0.976 |
- 0.896 |
- 0.972 |
- 0.966 |
- 0.964 |
- 0.977 |
- 0.955 |
- 0.928 |
- 0.969 |
- 0.928 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.969 |
- 0.957 |
- 0.978 |
- 0.983 |
- 0.981 |
- 0.979 |
- 0.977 |
- 0.969 |
- 0.977 |
- 0.978 |
- 0.954 |
- 0.976 |
- 0.983 |
- 0.968 |
- 0.984 |
- 0.975 |
- 0.976 |
- 0.977 |
- 0.979 |
- 0.978 |
- 0.976 |
- 0.974 |
- 0.966 |
- 0.97 |
- 0.969 |
- 0.979 |
- 0.981 |
- 0.96 |
- 0.974 |
- 0.98 |
- 0.979 |
- 0.967 |
- 0.98 |
- 0.972 |
- 0.977 |
- 0.947 |
- 0.96 |
- 0.978 |
- 0.971 |
- 0.971 |
- 0.964 |
- 0.974 |
- 0.973 |
- 0.984 |
- 0.975 |
- 0.973 |
- 0.969 |
- 0.978 |
- 0.959 |
- 0.976 |
- 0.984 |
- 0.986 |
- 0.958 |
- 0.977 |
- 0.977 |
- 0.98 |
- 0.977 |
- 0.974 |
- 0.971 |
- 0.969 |
- 0.976 |
- 0.976 |
- 0.972 |
- 0.97 |
- 0.98 |
- 0.979 |
- 0.932 |
- 0.975 |
- 0.975 |
- 0.985 |
- 0.985 |
- 0.986 |
- 0.928 |
- 0.96 |
- 0.94 |
- |
- 0.885 |
- 0.97 |
-
-
- | Liver |
- 180 |
- F |
- 289 |
- 102414.08 |
- CD |
- BXD40 |
- H1691 |
- 0.993 |
- 0.925 |
- 0.926 |
- 0.99 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.966 |
- 0.886 |
- 0.985 |
- 0.974 |
- 0.989 |
- 0.98 |
- 0.986 |
- 0.972 |
- 0.986 |
- 0.972 |
- 0.964 |
- 0.983 |
- 0.986 |
- 0.982 |
- 1 |
- 0.99 |
- 0.99 |
- 0.984 |
- 0.974 |
- 0.974 |
- 0.978 |
- 0.987 |
- 0.989 |
- 0.987 |
- 0.988 |
- 0.946 |
- 0.975 |
- 0.985 |
- 0.976 |
- 0.935 |
- 0.989 |
- 0.983 |
- 0.984 |
- 0.988 |
- 0.983 |
- 0.983 |
- 0.988 |
- 0.983 |
- 0.946 |
- 0.977 |
- 0.979 |
- 0.988 |
- 0.98 |
- 0.99 |
- 0.963 |
- 0.978 |
- 0.978 |
- 0.986 |
- 0.989 |
- 0.98 |
- 0.983 |
- 0.99 |
- 0.983 |
- 0.977 |
- 0.966 |
- 0.986 |
- 0.9 |
- 0.986 |
- 0.98 |
- 0.972 |
- 0.988 |
- 0.968 |
- 0.941 |
- 0.982 |
- 0.941 |
- 0.988 |
- 0.987 |
- 0.983 |
- 0.983 |
- 0.972 |
- 0.989 |
- 0.988 |
- 0.988 |
- 0.984 |
- 0.986 |
- 0.974 |
- 0.981 |
- 0.985 |
- 0.962 |
- 0.988 |
- 0.989 |
- 0.974 |
- 0.987 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.989 |
- 0.986 |
- 0.975 |
- 0.978 |
- 0.979 |
- 0.985 |
- 0.984 |
- 0.971 |
- 0.979 |
- 0.979 |
- 0.987 |
- 0.98 |
- 0.987 |
- 0.984 |
- 0.984 |
- 0.949 |
- 0.973 |
- 0.983 |
- 0.966 |
- 0.984 |
- 0.972 |
- 0.986 |
- 0.981 |
- 0.988 |
- 0.983 |
- 0.982 |
- 0.973 |
- 0.985 |
- 0.965 |
- 0.985 |
- 0.99 |
- 0.989 |
- 0.969 |
- 0.983 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.986 |
- 0.983 |
- 0.983 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.985 |
- 0.988 |
- 0.928 |
- 0.986 |
- 0.981 |
- 0.989 |
- 0.988 |
- 0.985 |
- 0.941 |
- 0.971 |
- 0.938 |
- |
- 0.886 |
- 0.98 |
-
-
- | Liver |
- 578 |
- F |
- 285 |
- 061913.06 |
- CD |
- BXD40 |
- H0680 |
- 0.99 |
- 0.922 |
- 0.924 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.99 |
- 0.963 |
- 0.884 |
- 0.985 |
- 0.969 |
- 0.986 |
- 0.984 |
- 0.986 |
- 0.974 |
- 0.978 |
- 0.969 |
- 0.96 |
- 0.979 |
- 0.983 |
- 0.977 |
- 0.99 |
- 1 |
- 0.991 |
- 0.982 |
- 0.974 |
- 0.974 |
- 0.973 |
- 0.985 |
- 0.988 |
- 0.988 |
- 0.985 |
- 0.944 |
- 0.979 |
- 0.984 |
- 0.974 |
- 0.937 |
- 0.988 |
- 0.981 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.98 |
- 0.988 |
- 0.984 |
- 0.951 |
- 0.983 |
- 0.982 |
- 0.986 |
- 0.984 |
- 0.988 |
- 0.967 |
- 0.978 |
- 0.981 |
- 0.989 |
- 0.988 |
- 0.976 |
- 0.978 |
- 0.986 |
- 0.981 |
- 0.982 |
- 0.964 |
- 0.984 |
- 0.899 |
- 0.985 |
- 0.986 |
- 0.974 |
- 0.986 |
- 0.967 |
- 0.943 |
- 0.983 |
- 0.945 |
- 0.986 |
- 0.99 |
- 0.988 |
- 0.981 |
- 0.972 |
- 0.99 |
- 0.987 |
- 0.988 |
- 0.984 |
- 0.984 |
- 0.971 |
- 0.98 |
- 0.983 |
- 0.963 |
- 0.987 |
- 0.991 |
- 0.973 |
- 0.982 |
- 0.978 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.976 |
- 0.991 |
- 0.982 |
- 0.972 |
- 0.98 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.969 |
- 0.98 |
- 0.982 |
- 0.987 |
- 0.977 |
- 0.983 |
- 0.981 |
- 0.979 |
- 0.953 |
- 0.974 |
- 0.979 |
- 0.968 |
- 0.989 |
- 0.974 |
- 0.984 |
- 0.98 |
- 0.984 |
- 0.987 |
- 0.983 |
- 0.973 |
- 0.981 |
- 0.969 |
- 0.987 |
- 0.989 |
- 0.985 |
- 0.971 |
- 0.979 |
- 0.986 |
- 0.983 |
- 0.979 |
- 0.982 |
- 0.98 |
- 0.986 |
- 0.976 |
- 0.982 |
- 0.988 |
- 0.987 |
- 0.985 |
- 0.987 |
- 0.926 |
- 0.987 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.987 |
- 0.945 |
- 0.968 |
- 0.942 |
- |
- 0.884 |
- 0.98 |
-
-
- | Liver |
- 240 |
- F |
- 264 |
- 042015.07 |
- CD |
- BXD44 |
- H1822 |
- 0.992 |
- 0.926 |
- 0.928 |
- 0.989 |
- 0.984 |
- 0.986 |
- 0.988 |
- 0.965 |
- 0.889 |
- 0.987 |
- 0.974 |
- 0.989 |
- 0.984 |
- 0.988 |
- 0.975 |
- 0.982 |
- 0.972 |
- 0.965 |
- 0.984 |
- 0.985 |
- 0.978 |
- 0.99 |
- 0.991 |
- 1 |
- 0.99 |
- 0.975 |
- 0.976 |
- 0.977 |
- 0.987 |
- 0.989 |
- 0.985 |
- 0.987 |
- 0.947 |
- 0.977 |
- 0.985 |
- 0.979 |
- 0.938 |
- 0.987 |
- 0.982 |
- 0.982 |
- 0.986 |
- 0.982 |
- 0.981 |
- 0.988 |
- 0.986 |
- 0.949 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.982 |
- 0.99 |
- 0.965 |
- 0.982 |
- 0.981 |
- 0.988 |
- 0.989 |
- 0.98 |
- 0.978 |
- 0.988 |
- 0.982 |
- 0.98 |
- 0.965 |
- 0.987 |
- 0.899 |
- 0.986 |
- 0.983 |
- 0.976 |
- 0.989 |
- 0.973 |
- 0.946 |
- 0.985 |
- 0.946 |
- 0.986 |
- 0.988 |
- 0.984 |
- 0.982 |
- 0.975 |
- 0.989 |
- 0.989 |
- 0.989 |
- 0.985 |
- 0.986 |
- 0.974 |
- 0.982 |
- 0.988 |
- 0.967 |
- 0.989 |
- 0.99 |
- 0.975 |
- 0.984 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.979 |
- 0.978 |
- 0.991 |
- 0.983 |
- 0.979 |
- 0.984 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.974 |
- 0.98 |
- 0.981 |
- 0.985 |
- 0.979 |
- 0.986 |
- 0.984 |
- 0.983 |
- 0.953 |
- 0.973 |
- 0.981 |
- 0.968 |
- 0.988 |
- 0.976 |
- 0.984 |
- 0.982 |
- 0.987 |
- 0.987 |
- 0.986 |
- 0.975 |
- 0.985 |
- 0.969 |
- 0.987 |
- 0.99 |
- 0.987 |
- 0.973 |
- 0.98 |
- 0.988 |
- 0.983 |
- 0.983 |
- 0.983 |
- 0.98 |
- 0.985 |
- 0.979 |
- 0.983 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.986 |
- 0.929 |
- 0.986 |
- 0.98 |
- 0.988 |
- 0.987 |
- 0.983 |
- 0.946 |
- 0.973 |
- 0.945 |
- |
- 0.889 |
- 0.98 |
-
-
- | Liver |
- 379 |
- F |
- 157 |
- 012615.15 |
- CD |
- BXD44 |
- H1505 |
- 0.982 |
- 0.93 |
- 0.931 |
- 0.98 |
- 0.974 |
- 0.977 |
- 0.979 |
- 0.976 |
- 0.902 |
- 0.981 |
- 0.961 |
- 0.986 |
- 0.973 |
- 0.983 |
- 0.974 |
- 0.976 |
- 0.979 |
- 0.973 |
- 0.978 |
- 0.979 |
- 0.97 |
- 0.984 |
- 0.982 |
- 0.99 |
- 1 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.979 |
- 0.981 |
- 0.934 |
- 0.976 |
- 0.986 |
- 0.981 |
- 0.956 |
- 0.98 |
- 0.985 |
- 0.98 |
- 0.982 |
- 0.973 |
- 0.977 |
- 0.978 |
- 0.985 |
- 0.956 |
- 0.967 |
- 0.973 |
- 0.978 |
- 0.977 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.971 |
- 0.98 |
- 0.979 |
- 0.985 |
- 0.973 |
- 0.984 |
- 0.981 |
- 0.967 |
- 0.951 |
- 0.987 |
- 0.89 |
- 0.977 |
- 0.973 |
- 0.978 |
- 0.983 |
- 0.984 |
- 0.966 |
- 0.986 |
- 0.964 |
- 0.976 |
- 0.979 |
- 0.983 |
- 0.981 |
- 0.981 |
- 0.977 |
- 0.982 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.961 |
- 0.972 |
- 0.984 |
- 0.973 |
- 0.984 |
- 0.981 |
- 0.983 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.981 |
- 0.98 |
- 0.979 |
- 0.985 |
- 0.976 |
- 0.989 |
- 0.983 |
- 0.99 |
- 0.974 |
- 0.98 |
- 0.977 |
- 0.977 |
- 0.969 |
- 0.977 |
- 0.975 |
- 0.977 |
- 0.975 |
- 0.981 |
- 0.938 |
- 0.977 |
- 0.981 |
- 0.966 |
- 0.981 |
- 0.978 |
- 0.977 |
- 0.97 |
- 0.98 |
- 0.977 |
- 0.98 |
- 0.964 |
- 0.981 |
- 0.967 |
- 0.984 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.976 |
- 0.985 |
- 0.978 |
- 0.981 |
- 0.976 |
- 0.977 |
- 0.976 |
- 0.968 |
- 0.97 |
- 0.979 |
- 0.983 |
- 0.973 |
- 0.981 |
- 0.919 |
- 0.974 |
- 0.968 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.964 |
- 0.977 |
- 0.96 |
- |
- 0.89 |
- 0.97 |
-
-
- | Liver |
- 384 |
- F |
- 145 |
- 012615.11 |
- CD |
- BXD45 |
- H1762 |
- 0.972 |
- 0.951 |
- 0.95 |
- 0.974 |
- 0.974 |
- 0.977 |
- 0.972 |
- 0.977 |
- 0.928 |
- 0.976 |
- 0.969 |
- 0.978 |
- 0.97 |
- 0.969 |
- 0.974 |
- 0.971 |
- 0.979 |
- 0.971 |
- 0.973 |
- 0.975 |
- 0.965 |
- 0.974 |
- 0.974 |
- 0.975 |
- 0.979 |
- 1 |
- 0.997 |
- 0.983 |
- 0.98 |
- 0.973 |
- 0.972 |
- 0.971 |
- 0.944 |
- 0.978 |
- 0.976 |
- 0.986 |
- 0.968 |
- 0.978 |
- 0.979 |
- 0.971 |
- 0.975 |
- 0.975 |
- 0.973 |
- 0.979 |
- 0.981 |
- 0.97 |
- 0.968 |
- 0.976 |
- 0.974 |
- 0.979 |
- 0.976 |
- 0.981 |
- 0.988 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.985 |
- 0.964 |
- 0.977 |
- 0.98 |
- 0.96 |
- 0.956 |
- 0.976 |
- 0.903 |
- 0.969 |
- 0.966 |
- 0.979 |
- 0.971 |
- 0.982 |
- 0.973 |
- 0.984 |
- 0.967 |
- 0.975 |
- 0.972 |
- 0.974 |
- 0.98 |
- 0.983 |
- 0.972 |
- 0.976 |
- 0.975 |
- 0.975 |
- 0.969 |
- 0.962 |
- 0.97 |
- 0.982 |
- 0.968 |
- 0.979 |
- 0.973 |
- 0.975 |
- 0.971 |
- 0.966 |
- 0.974 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.976 |
- 0.974 |
- 0.981 |
- 0.978 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.972 |
- 0.969 |
- 0.971 |
- 0.971 |
- 0.96 |
- 0.977 |
- 0.938 |
- 0.975 |
- 0.973 |
- 0.972 |
- 0.973 |
- 0.979 |
- 0.969 |
- 0.966 |
- 0.974 |
- 0.973 |
- 0.969 |
- 0.967 |
- 0.969 |
- 0.969 |
- 0.978 |
- 0.976 |
- 0.971 |
- 0.986 |
- 0.971 |
- 0.98 |
- 0.969 |
- 0.977 |
- 0.974 |
- 0.968 |
- 0.966 |
- 0.97 |
- 0.965 |
- 0.97 |
- 0.984 |
- 0.967 |
- 0.975 |
- 0.928 |
- 0.97 |
- 0.967 |
- 0.976 |
- 0.971 |
- 0.97 |
- 0.967 |
- 0.971 |
- 0.968 |
- |
- 0.903 |
- 0.97 |
-
-
- | Liver |
- 507 |
- F |
- 281 |
- 121515.12 |
- CD |
- BXD45 |
- H1826 |
- 0.973 |
- 0.952 |
- 0.952 |
- 0.975 |
- 0.975 |
- 0.977 |
- 0.972 |
- 0.976 |
- 0.928 |
- 0.976 |
- 0.97 |
- 0.978 |
- 0.97 |
- 0.969 |
- 0.974 |
- 0.971 |
- 0.979 |
- 0.97 |
- 0.973 |
- 0.975 |
- 0.964 |
- 0.974 |
- 0.974 |
- 0.976 |
- 0.979 |
- 0.997 |
- 1 |
- 0.983 |
- 0.981 |
- 0.973 |
- 0.972 |
- 0.971 |
- 0.945 |
- 0.978 |
- 0.977 |
- 0.986 |
- 0.968 |
- 0.978 |
- 0.98 |
- 0.972 |
- 0.975 |
- 0.976 |
- 0.974 |
- 0.979 |
- 0.981 |
- 0.969 |
- 0.969 |
- 0.976 |
- 0.975 |
- 0.98 |
- 0.976 |
- 0.982 |
- 0.989 |
- 0.974 |
- 0.973 |
- 0.973 |
- 0.985 |
- 0.964 |
- 0.977 |
- 0.981 |
- 0.961 |
- 0.957 |
- 0.976 |
- 0.904 |
- 0.97 |
- 0.967 |
- 0.979 |
- 0.972 |
- 0.982 |
- 0.973 |
- 0.985 |
- 0.967 |
- 0.975 |
- 0.972 |
- 0.974 |
- 0.981 |
- 0.984 |
- 0.973 |
- 0.976 |
- 0.976 |
- 0.975 |
- 0.97 |
- 0.963 |
- 0.971 |
- 0.982 |
- 0.968 |
- 0.979 |
- 0.973 |
- 0.974 |
- 0.971 |
- 0.967 |
- 0.975 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.976 |
- 0.975 |
- 0.981 |
- 0.978 |
- 0.981 |
- 0.978 |
- 0.978 |
- 0.979 |
- 0.977 |
- 0.972 |
- 0.97 |
- 0.972 |
- 0.972 |
- 0.961 |
- 0.978 |
- 0.939 |
- 0.975 |
- 0.974 |
- 0.972 |
- 0.974 |
- 0.979 |
- 0.97 |
- 0.966 |
- 0.974 |
- 0.974 |
- 0.969 |
- 0.968 |
- 0.969 |
- 0.969 |
- 0.979 |
- 0.976 |
- 0.971 |
- 0.986 |
- 0.971 |
- 0.98 |
- 0.969 |
- 0.978 |
- 0.975 |
- 0.969 |
- 0.967 |
- 0.97 |
- 0.966 |
- 0.97 |
- 0.984 |
- 0.968 |
- 0.975 |
- 0.928 |
- 0.971 |
- 0.968 |
- 0.975 |
- 0.971 |
- 0.969 |
- 0.967 |
- 0.972 |
- 0.967 |
- |
- 0.904 |
- 0.97 |
-
-
- | Liver |
- 188 |
- F |
- 260 |
- 042015.27 |
- CD |
- BXD48 |
- H2054 |
- 0.974 |
- 0.943 |
- 0.942 |
- 0.975 |
- 0.969 |
- 0.976 |
- 0.971 |
- 0.983 |
- 0.915 |
- 0.971 |
- 0.962 |
- 0.984 |
- 0.963 |
- 0.968 |
- 0.974 |
- 0.974 |
- 0.978 |
- 0.976 |
- 0.974 |
- 0.976 |
- 0.971 |
- 0.978 |
- 0.973 |
- 0.977 |
- 0.983 |
- 0.983 |
- 0.983 |
- 1 |
- 0.981 |
- 0.973 |
- 0.974 |
- 0.974 |
- 0.933 |
- 0.973 |
- 0.98 |
- 0.983 |
- 0.965 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.981 |
- 0.97 |
- 0.974 |
- 0.976 |
- 0.983 |
- 0.965 |
- 0.96 |
- 0.967 |
- 0.978 |
- 0.978 |
- 0.978 |
- 0.982 |
- 0.987 |
- 0.964 |
- 0.975 |
- 0.973 |
- 0.986 |
- 0.971 |
- 0.979 |
- 0.979 |
- 0.959 |
- 0.948 |
- 0.985 |
- 0.89 |
- 0.968 |
- 0.962 |
- 0.977 |
- 0.974 |
- 0.98 |
- 0.97 |
- 0.983 |
- 0.969 |
- 0.973 |
- 0.971 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.97 |
- 0.977 |
- 0.976 |
- 0.975 |
- 0.968 |
- 0.956 |
- 0.967 |
- 0.983 |
- 0.968 |
- 0.976 |
- 0.973 |
- 0.979 |
- 0.979 |
- 0.968 |
- 0.975 |
- 0.977 |
- 0.984 |
- 0.984 |
- 0.974 |
- 0.978 |
- 0.985 |
- 0.976 |
- 0.985 |
- 0.97 |
- 0.988 |
- 0.978 |
- 0.978 |
- 0.969 |
- 0.971 |
- 0.972 |
- 0.974 |
- 0.964 |
- 0.978 |
- 0.929 |
- 0.976 |
- 0.982 |
- 0.971 |
- 0.973 |
- 0.977 |
- 0.975 |
- 0.963 |
- 0.976 |
- 0.969 |
- 0.969 |
- 0.959 |
- 0.971 |
- 0.963 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.984 |
- 0.975 |
- 0.983 |
- 0.974 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.968 |
- 0.966 |
- 0.966 |
- 0.972 |
- 0.981 |
- 0.969 |
- 0.98 |
- 0.92 |
- 0.972 |
- 0.964 |
- 0.978 |
- 0.973 |
- 0.974 |
- 0.969 |
- 0.977 |
- 0.963 |
- |
- 0.89 |
- 0.97 |
-
-
- | Liver |
- 518 |
- F |
- 275 |
- 121515.18 |
- CD |
- BXD48 |
- H1835 |
- 0.989 |
- 0.943 |
- 0.945 |
- 0.991 |
- 0.985 |
- 0.989 |
- 0.985 |
- 0.968 |
- 0.907 |
- 0.985 |
- 0.982 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.978 |
- 0.982 |
- 0.976 |
- 0.963 |
- 0.986 |
- 0.989 |
- 0.979 |
- 0.987 |
- 0.985 |
- 0.987 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.981 |
- 1 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.959 |
- 0.977 |
- 0.982 |
- 0.983 |
- 0.943 |
- 0.986 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.987 |
- 0.984 |
- 0.989 |
- 0.982 |
- 0.955 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.987 |
- 0.967 |
- 0.983 |
- 0.984 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.977 |
- 0.989 |
- 0.984 |
- 0.978 |
- 0.973 |
- 0.982 |
- 0.916 |
- 0.983 |
- 0.982 |
- 0.98 |
- 0.987 |
- 0.972 |
- 0.949 |
- 0.984 |
- 0.943 |
- 0.99 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.977 |
- 0.988 |
- 0.989 |
- 0.988 |
- 0.985 |
- 0.986 |
- 0.977 |
- 0.984 |
- 0.986 |
- 0.968 |
- 0.988 |
- 0.988 |
- 0.974 |
- 0.981 |
- 0.981 |
- 0.987 |
- 0.987 |
- 0.983 |
- 0.982 |
- 0.985 |
- 0.985 |
- 0.974 |
- 0.982 |
- 0.977 |
- 0.989 |
- 0.988 |
- 0.982 |
- 0.984 |
- 0.989 |
- 0.985 |
- 0.981 |
- 0.985 |
- 0.981 |
- 0.986 |
- 0.957 |
- 0.971 |
- 0.98 |
- 0.972 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.972 |
- 0.984 |
- 0.986 |
- 0.985 |
- 0.976 |
- 0.982 |
- 0.986 |
- 0.985 |
- 0.986 |
- 0.985 |
- 0.976 |
- 0.98 |
- 0.983 |
- 0.985 |
- 0.98 |
- 0.986 |
- 0.984 |
- 0.983 |
- 0.941 |
- 0.985 |
- 0.983 |
- 0.987 |
- 0.984 |
- 0.979 |
- 0.943 |
- 0.971 |
- 0.948 |
- |
- 0.907 |
- 0.98 |
-
-
- | Liver |
- 233 |
- F |
- 25 |
- 051112.05 |
- CD |
- BXD48a |
- H0209 |
- 0.99 |
- 0.927 |
- 0.929 |
- 0.987 |
- 0.983 |
- 0.988 |
- 0.986 |
- 0.962 |
- 0.891 |
- 0.983 |
- 0.975 |
- 0.986 |
- 0.982 |
- 0.985 |
- 0.977 |
- 0.985 |
- 0.967 |
- 0.96 |
- 0.98 |
- 0.985 |
- 0.981 |
- 0.989 |
- 0.988 |
- 0.989 |
- 0.979 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.985 |
- 1 |
- 0.984 |
- 0.988 |
- 0.951 |
- 0.973 |
- 0.979 |
- 0.975 |
- 0.937 |
- 0.987 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.986 |
- 0.981 |
- 0.949 |
- 0.98 |
- 0.982 |
- 0.987 |
- 0.983 |
- 0.988 |
- 0.963 |
- 0.98 |
- 0.985 |
- 0.99 |
- 1 |
- 0.976 |
- 0.98 |
- 0.988 |
- 0.981 |
- 0.981 |
- 0.967 |
- 0.979 |
- 0.905 |
- 0.982 |
- 0.98 |
- 0.97 |
- 0.986 |
- 0.967 |
- 0.94 |
- 0.982 |
- 0.938 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.981 |
- 0.971 |
- 0.988 |
- 0.987 |
- 0.987 |
- 0.986 |
- 0.985 |
- 0.976 |
- 0.979 |
- 0.982 |
- 0.96 |
- 0.984 |
- 0.988 |
- 0.971 |
- 0.986 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.984 |
- 0.98 |
- 0.972 |
- 0.978 |
- 0.976 |
- 0.985 |
- 0.982 |
- 0.969 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.954 |
- 0.97 |
- 0.979 |
- 0.97 |
- 0.983 |
- 0.97 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.978 |
- 0.984 |
- 0.97 |
- 0.983 |
- 0.989 |
- 0.991 |
- 0.97 |
- 0.985 |
- 0.99 |
- 0.982 |
- 0.983 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.985 |
- 0.985 |
- 0.933 |
- 0.984 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.985 |
- 0.938 |
- 0.966 |
- 0.94 |
- |
- 0.891 |
- 0.98 |
-
-
- | Liver |
- 571 |
- F |
- 308 |
- 062013.16 |
- CD |
- BXD53 |
- H0848 |
- 0.989 |
- 0.919 |
- 0.921 |
- 0.988 |
- 0.978 |
- 0.983 |
- 0.987 |
- 0.966 |
- 0.883 |
- 0.981 |
- 0.97 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.97 |
- 0.979 |
- 0.971 |
- 0.958 |
- 0.981 |
- 0.983 |
- 0.979 |
- 0.987 |
- 0.988 |
- 0.985 |
- 0.979 |
- 0.972 |
- 0.972 |
- 0.974 |
- 0.985 |
- 0.984 |
- 1 |
- 0.984 |
- 0.943 |
- 0.978 |
- 0.986 |
- 0.975 |
- 0.932 |
- 0.987 |
- 0.984 |
- 0.984 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.987 |
- 0.983 |
- 0.946 |
- 0.976 |
- 0.978 |
- 0.986 |
- 0.979 |
- 0.987 |
- 0.964 |
- 0.974 |
- 0.975 |
- 0.988 |
- 0.984 |
- 0.974 |
- 0.981 |
- 0.986 |
- 0.98 |
- 0.975 |
- 0.961 |
- 0.983 |
- 0.895 |
- 0.983 |
- 0.984 |
- 0.973 |
- 0.984 |
- 0.964 |
- 0.939 |
- 0.978 |
- 0.941 |
- 0.988 |
- 0.987 |
- 0.989 |
- 0.98 |
- 0.97 |
- 0.988 |
- 0.987 |
- 0.989 |
- 0.98 |
- 0.983 |
- 0.968 |
- 0.981 |
- 0.98 |
- 0.964 |
- 0.983 |
- 0.988 |
- 0.976 |
- 0.979 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.979 |
- 0.97 |
- 0.979 |
- 0.975 |
- 0.982 |
- 0.982 |
- 0.965 |
- 0.978 |
- 0.981 |
- 0.997 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.947 |
- 0.975 |
- 0.983 |
- 0.97 |
- 0.982 |
- 0.973 |
- 0.987 |
- 0.978 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.969 |
- 0.98 |
- 0.964 |
- 0.985 |
- 0.988 |
- 0.985 |
- 0.969 |
- 0.982 |
- 0.984 |
- 0.987 |
- 0.981 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.976 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.988 |
- 0.987 |
- 0.924 |
- 0.985 |
- 0.983 |
- 0.986 |
- 0.988 |
- 0.989 |
- 0.941 |
- 0.966 |
- 0.936 |
- |
- 0.883 |
- 0.98 |
-
-
- | Liver |
- 235 |
- F |
- 104 |
- 050912.08 |
- CD |
- BXD60 |
- H0235 |
- 0.987 |
- 0.928 |
- 0.928 |
- 0.987 |
- 0.982 |
- 0.987 |
- 0.986 |
- 0.967 |
- 0.894 |
- 0.982 |
- 0.973 |
- 0.983 |
- 0.98 |
- 0.984 |
- 0.973 |
- 0.984 |
- 0.969 |
- 0.964 |
- 0.979 |
- 0.982 |
- 0.984 |
- 0.988 |
- 0.985 |
- 0.987 |
- 0.981 |
- 0.971 |
- 0.971 |
- 0.974 |
- 0.984 |
- 0.988 |
- 0.984 |
- 1 |
- 0.947 |
- 0.972 |
- 0.981 |
- 0.976 |
- 0.938 |
- 0.982 |
- 0.977 |
- 0.977 |
- 0.984 |
- 0.978 |
- 0.976 |
- 0.983 |
- 0.983 |
- 0.95 |
- 0.976 |
- 0.98 |
- 0.982 |
- 0.979 |
- 0.987 |
- 0.959 |
- 0.975 |
- 0.978 |
- 0.984 |
- 0.988 |
- 0.974 |
- 0.981 |
- 0.986 |
- 0.979 |
- 0.975 |
- 0.96 |
- 0.982 |
- 0.902 |
- 0.978 |
- 0.974 |
- 0.97 |
- 0.985 |
- 0.967 |
- 0.942 |
- 0.979 |
- 0.94 |
- 0.984 |
- 0.986 |
- 0.984 |
- 0.979 |
- 0.968 |
- 0.984 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.976 |
- 0.979 |
- 0.983 |
- 0.96 |
- 0.984 |
- 0.987 |
- 0.975 |
- 0.986 |
- 0.978 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.977 |
- 0.985 |
- 0.978 |
- 0.973 |
- 0.976 |
- 0.976 |
- 0.983 |
- 0.98 |
- 0.974 |
- 0.981 |
- 0.982 |
- 0.984 |
- 0.974 |
- 0.982 |
- 0.978 |
- 0.983 |
- 0.95 |
- 0.967 |
- 0.979 |
- 0.969 |
- 0.983 |
- 0.97 |
- 0.98 |
- 0.979 |
- 0.987 |
- 0.983 |
- 0.985 |
- 0.977 |
- 0.988 |
- 0.968 |
- 0.982 |
- 0.987 |
- 0.987 |
- 0.968 |
- 0.982 |
- 0.984 |
- 0.982 |
- 0.983 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.982 |
- 0.983 |
- 0.934 |
- 0.98 |
- 0.977 |
- 0.989 |
- 0.987 |
- 0.985 |
- 0.94 |
- 0.965 |
- 0.947 |
- |
- 0.894 |
- 0.98 |
-
-
- | Liver |
- 530 |
- F |
- 51 |
- 021213.14 |
- CD |
- BXD60 |
- H0171 |
- 0.946 |
- 0.95 |
- 0.953 |
- 0.952 |
- 0.955 |
- 0.962 |
- 0.94 |
- 0.919 |
- 0.919 |
- 0.951 |
- 0.97 |
- 0.947 |
- 0.96 |
- 0.949 |
- 0.958 |
- 0.954 |
- 0.938 |
- 0.929 |
- 0.958 |
- 0.957 |
- 0.944 |
- 0.946 |
- 0.944 |
- 0.947 |
- 0.934 |
- 0.944 |
- 0.945 |
- 0.933 |
- 0.959 |
- 0.951 |
- 0.943 |
- 0.947 |
- 1 |
- 0.932 |
- 0.932 |
- 0.953 |
- 0.904 |
- 0.942 |
- 0.933 |
- 0.937 |
- 0.95 |
- 0.954 |
- 0.939 |
- 0.951 |
- 0.94 |
- 0.923 |
- 0.949 |
- 0.96 |
- 0.944 |
- 0.942 |
- 0.951 |
- 0.915 |
- 0.945 |
- 0.961 |
- 0.948 |
- 0.951 |
- 0.941 |
- 0.936 |
- 0.951 |
- 0.941 |
- 0.958 |
- 0.973 |
- 0.938 |
- 0.943 |
- 0.949 |
- 0.95 |
- 0.958 |
- 0.951 |
- 0.937 |
- 0.901 |
- 0.946 |
- 0.9 |
- 0.959 |
- 0.94 |
- 0.933 |
- 0.941 |
- 0.939 |
- 0.951 |
- 0.959 |
- 0.955 |
- 0.945 |
- 0.958 |
- 0.97 |
- 0.955 |
- 0.945 |
- 0.953 |
- 0.945 |
- 0.949 |
- 0.934 |
- 0.941 |
- 0.947 |
- 0.959 |
- 0.958 |
- 0.943 |
- 0.943 |
- 0.952 |
- 0.959 |
- 0.928 |
- 0.956 |
- 0.932 |
- 0.963 |
- 0.946 |
- 0.952 |
- 0.945 |
- 0.965 |
- 0.943 |
- 0.944 |
- 0.95 |
- 0.951 |
- 0.957 |
- 0.97 |
- 0.922 |
- 0.935 |
- 0.947 |
- 0.941 |
- 0.958 |
- 0.938 |
- 0.965 |
- 0.946 |
- 0.953 |
- 0.949 |
- 0.971 |
- 0.944 |
- 0.96 |
- 0.946 |
- 0.949 |
- 0.951 |
- 0.932 |
- 0.947 |
- 0.949 |
- 0.944 |
- 0.957 |
- 0.959 |
- 0.933 |
- 0.941 |
- 0.966 |
- 0.961 |
- 0.94 |
- 0.951 |
- 0.957 |
- 0.943 |
- 0.964 |
- 0.948 |
- 0.964 |
- 0.953 |
- 0.95 |
- 0.935 |
- 0.9 |
- 0.94 |
- 0.915 |
- |
- 0.9 |
- 0.95 |
-
-
- | Liver |
- 188 |
- F |
- 132 |
- 111414.02 |
- CD |
- BXD61 |
- H1770 |
- 0.976 |
- 0.922 |
- 0.923 |
- 0.974 |
- 0.973 |
- 0.971 |
- 0.979 |
- 0.974 |
- 0.893 |
- 0.976 |
- 0.959 |
- 0.977 |
- 0.971 |
- 0.973 |
- 0.964 |
- 0.965 |
- 0.979 |
- 0.96 |
- 0.972 |
- 0.973 |
- 0.961 |
- 0.975 |
- 0.979 |
- 0.977 |
- 0.976 |
- 0.978 |
- 0.978 |
- 0.973 |
- 0.977 |
- 0.973 |
- 0.978 |
- 0.972 |
- 0.932 |
- 1 |
- 0.986 |
- 0.976 |
- 0.948 |
- 0.981 |
- 0.983 |
- 0.979 |
- 0.977 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.98 |
- 0.951 |
- 0.973 |
- 0.976 |
- 0.978 |
- 0.973 |
- 0.975 |
- 0.974 |
- 0.978 |
- 0.974 |
- 0.977 |
- 0.973 |
- 0.975 |
- 0.972 |
- 0.978 |
- 0.985 |
- 0.961 |
- 0.949 |
- 0.976 |
- 0.884 |
- 0.973 |
- 0.975 |
- 0.971 |
- 0.975 |
- 0.968 |
- 0.954 |
- 0.979 |
- 0.953 |
- 0.973 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.977 |
- 0.977 |
- 0.969 |
- 0.954 |
- 0.969 |
- 0.977 |
- 0.964 |
- 0.978 |
- 0.975 |
- 0.978 |
- 0.971 |
- 0.974 |
- 0.973 |
- 0.974 |
- 0.98 |
- 0.98 |
- 0.975 |
- 0.972 |
- 0.971 |
- 0.975 |
- 0.972 |
- 0.967 |
- 0.973 |
- 0.969 |
- 0.972 |
- 0.966 |
- 0.976 |
- 0.986 |
- 0.978 |
- 0.968 |
- 0.973 |
- 0.932 |
- 0.986 |
- 0.98 |
- 0.97 |
- 0.976 |
- 0.971 |
- 0.979 |
- 0.965 |
- 0.974 |
- 0.976 |
- 0.971 |
- 0.961 |
- 0.967 |
- 0.959 |
- 0.979 |
- 0.976 |
- 0.971 |
- 0.978 |
- 0.974 |
- 0.978 |
- 0.975 |
- 0.973 |
- 0.972 |
- 0.978 |
- 0.972 |
- 0.96 |
- 0.966 |
- 0.977 |
- 0.982 |
- 0.97 |
- 0.98 |
- 0.909 |
- 0.977 |
- 0.965 |
- 0.974 |
- 0.972 |
- 0.975 |
- 0.953 |
- 0.965 |
- 0.944 |
- |
- 0.884 |
- 0.97 |
-
-
- | Liver |
- 524 |
- F |
- 324 |
- 121515.23 |
- CD |
- BXD61 |
- H1841 |
- 0.985 |
- 0.92 |
- 0.922 |
- 0.984 |
- 0.97 |
- 0.977 |
- 0.98 |
- 0.978 |
- 0.891 |
- 0.976 |
- 0.962 |
- 0.985 |
- 0.973 |
- 0.981 |
- 0.966 |
- 0.974 |
- 0.981 |
- 0.968 |
- 0.981 |
- 0.981 |
- 0.972 |
- 0.985 |
- 0.984 |
- 0.985 |
- 0.986 |
- 0.976 |
- 0.977 |
- 0.98 |
- 0.982 |
- 0.979 |
- 0.986 |
- 0.981 |
- 0.932 |
- 0.986 |
- 1 |
- 0.979 |
- 0.946 |
- 0.983 |
- 0.988 |
- 0.986 |
- 0.983 |
- 0.981 |
- 0.986 |
- 0.983 |
- 0.986 |
- 0.949 |
- 0.966 |
- 0.973 |
- 0.981 |
- 0.976 |
- 0.986 |
- 0.975 |
- 0.983 |
- 0.969 |
- 0.983 |
- 0.979 |
- 0.982 |
- 0.979 |
- 0.987 |
- 0.983 |
- 0.963 |
- 0.951 |
- 0.987 |
- 0.883 |
- 0.979 |
- 0.978 |
- 0.974 |
- 0.985 |
- 0.972 |
- 0.953 |
- 0.982 |
- 0.954 |
- 0.979 |
- 0.98 |
- 0.986 |
- 0.983 |
- 0.982 |
- 0.98 |
- 0.984 |
- 0.986 |
- 0.976 |
- 0.976 |
- 0.958 |
- 0.973 |
- 0.981 |
- 0.969 |
- 0.984 |
- 0.985 |
- 0.983 |
- 0.977 |
- 0.982 |
- 0.982 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.979 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.976 |
- 0.979 |
- 0.968 |
- 0.975 |
- 0.97 |
- 0.985 |
- 0.987 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.932 |
- 0.98 |
- 0.986 |
- 0.966 |
- 0.978 |
- 0.974 |
- 0.984 |
- 0.97 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.961 |
- 0.976 |
- 0.957 |
- 0.985 |
- 0.986 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.985 |
- 0.988 |
- 0.98 |
- 0.979 |
- 0.984 |
- 0.974 |
- 0.969 |
- 0.974 |
- 0.978 |
- 0.984 |
- 0.978 |
- 0.985 |
- 0.913 |
- 0.98 |
- 0.972 |
- 0.98 |
- 0.981 |
- 0.982 |
- 0.954 |
- 0.974 |
- 0.947 |
- |
- 0.883 |
- 0.97 |
-
-
- | Liver |
- 253 |
- F |
- 257 |
- 042015.05 |
- CD |
- BXD62 |
- H1847 |
- 0.975 |
- 0.956 |
- 0.956 |
- 0.979 |
- 0.978 |
- 0.982 |
- 0.972 |
- 0.977 |
- 0.933 |
- 0.975 |
- 0.976 |
- 0.982 |
- 0.973 |
- 0.973 |
- 0.978 |
- 0.978 |
- 0.985 |
- 0.973 |
- 0.981 |
- 0.979 |
- 0.968 |
- 0.976 |
- 0.974 |
- 0.979 |
- 0.981 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.983 |
- 0.975 |
- 0.975 |
- 0.976 |
- 0.953 |
- 0.976 |
- 0.979 |
- 1 |
- 0.966 |
- 0.977 |
- 0.982 |
- 0.975 |
- 0.979 |
- 0.975 |
- 0.975 |
- 0.979 |
- 0.982 |
- 0.965 |
- 0.969 |
- 0.976 |
- 0.977 |
- 0.977 |
- 0.98 |
- 0.975 |
- 0.988 |
- 0.977 |
- 0.979 |
- 0.975 |
- 0.985 |
- 0.969 |
- 0.983 |
- 0.981 |
- 0.966 |
- 0.962 |
- 0.981 |
- 0.91 |
- 0.971 |
- 0.97 |
- 0.983 |
- 0.976 |
- 0.98 |
- 0.962 |
- 0.984 |
- 0.961 |
- 0.977 |
- 0.972 |
- 0.975 |
- 0.981 |
- 0.984 |
- 0.974 |
- 0.982 |
- 0.98 |
- 0.973 |
- 0.972 |
- 0.971 |
- 0.973 |
- 0.981 |
- 0.975 |
- 0.977 |
- 0.976 |
- 0.978 |
- 0.974 |
- 0.973 |
- 0.983 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.979 |
- 0.978 |
- 0.972 |
- 0.975 |
- 0.976 |
- 0.97 |
- 0.986 |
- 0.948 |
- 0.972 |
- 0.976 |
- 0.977 |
- 0.975 |
- 0.983 |
- 0.973 |
- 0.972 |
- 0.976 |
- 0.975 |
- 0.976 |
- 0.975 |
- 0.974 |
- 0.971 |
- 0.983 |
- 0.979 |
- 0.976 |
- 0.985 |
- 0.979 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.98 |
- 0.971 |
- 0.97 |
- 0.978 |
- 0.973 |
- 0.972 |
- 0.986 |
- 0.973 |
- 0.977 |
- 0.938 |
- 0.974 |
- 0.972 |
- 0.979 |
- 0.976 |
- 0.971 |
- 0.961 |
- 0.977 |
- 0.967 |
- |
- 0.91 |
- 0.98 |
-
-
- | Liver |
- 353 |
- F |
- 178 |
- 121214.20 |
- CD |
- BXD62 |
- H1436 |
- 0.929 |
- 0.944 |
- 0.941 |
- 0.933 |
- 0.943 |
- 0.939 |
- 0.932 |
- 0.968 |
- 0.939 |
- 0.935 |
- 0.921 |
- 0.946 |
- 0.925 |
- 0.93 |
- 0.953 |
- 0.931 |
- 0.959 |
- 0.95 |
- 0.936 |
- 0.936 |
- 0.923 |
- 0.935 |
- 0.937 |
- 0.938 |
- 0.956 |
- 0.968 |
- 0.968 |
- 0.965 |
- 0.943 |
- 0.937 |
- 0.932 |
- 0.938 |
- 0.904 |
- 0.948 |
- 0.946 |
- 0.966 |
- 1 |
- 0.939 |
- 0.956 |
- 0.94 |
- 0.936 |
- 0.931 |
- 0.936 |
- 0.932 |
- 0.949 |
- 0.969 |
- 0.929 |
- 0.938 |
- 0.934 |
- 0.954 |
- 0.935 |
- 0.98 |
- 0.968 |
- 0.943 |
- 0.939 |
- 0.937 |
- 0.963 |
- 0.924 |
- 0.941 |
- 0.951 |
- 0.928 |
- 0.911 |
- 0.946 |
- 0.875 |
- 0.92 |
- 0.924 |
- 0.952 |
- 0.935 |
- 0.971 |
- 0.977 |
- 0.96 |
- 0.976 |
- 0.928 |
- 0.932 |
- 0.942 |
- 0.951 |
- 0.967 |
- 0.929 |
- 0.936 |
- 0.934 |
- 0.94 |
- 0.927 |
- 0.923 |
- 0.921 |
- 0.946 |
- 0.949 |
- 0.94 |
- 0.934 |
- 0.956 |
- 0.937 |
- 0.926 |
- 0.939 |
- 0.944 |
- 0.953 |
- 0.953 |
- 0.938 |
- 0.937 |
- 0.974 |
- 0.953 |
- 0.969 |
- 0.929 |
- 0.944 |
- 0.962 |
- 0.95 |
- 0.928 |
- 0.927 |
- 0.938 |
- 0.925 |
- 0.919 |
- 0.955 |
- 0.902 |
- 0.955 |
- 0.944 |
- 0.949 |
- 0.944 |
- 0.952 |
- 0.931 |
- 0.923 |
- 0.932 |
- 0.934 |
- 0.938 |
- 0.935 |
- 0.938 |
- 0.949 |
- 0.951 |
- 0.938 |
- 0.934 |
- 0.975 |
- 0.942 |
- 0.951 |
- 0.932 |
- 0.955 |
- 0.937 |
- 0.935 |
- 0.932 |
- 0.928 |
- 0.922 |
- 0.937 |
- 0.953 |
- 0.925 |
- 0.944 |
- 0.893 |
- 0.931 |
- 0.919 |
- 0.936 |
- 0.932 |
- 0.935 |
- 0.976 |
- 0.944 |
- 0.975 |
- |
- 0.875 |
- 0.94 |
-
-
- | Liver |
- 218 |
- F |
- 293 |
- 090412.08 |
- CD |
- BXD63 |
- H0818 |
- 0.99 |
- 0.924 |
- 0.926 |
- 0.987 |
- 0.979 |
- 0.983 |
- 0.988 |
- 0.969 |
- 0.884 |
- 0.982 |
- 0.971 |
- 0.987 |
- 0.977 |
- 0.981 |
- 0.971 |
- 0.98 |
- 0.972 |
- 0.962 |
- 0.98 |
- 0.984 |
- 0.98 |
- 0.989 |
- 0.988 |
- 0.987 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.981 |
- 0.986 |
- 0.987 |
- 0.987 |
- 0.982 |
- 0.942 |
- 0.981 |
- 0.983 |
- 0.977 |
- 0.939 |
- 1 |
- 0.99 |
- 0.99 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.989 |
- 0.984 |
- 0.948 |
- 0.98 |
- 0.982 |
- 0.99 |
- 0.983 |
- 0.987 |
- 0.97 |
- 0.98 |
- 0.977 |
- 0.986 |
- 0.987 |
- 0.98 |
- 0.979 |
- 0.985 |
- 0.987 |
- 0.973 |
- 0.961 |
- 0.984 |
- 0.896 |
- 0.981 |
- 0.979 |
- 0.972 |
- 0.983 |
- 0.966 |
- 0.947 |
- 0.984 |
- 0.944 |
- 0.987 |
- 0.988 |
- 0.985 |
- 0.987 |
- 0.976 |
- 0.989 |
- 0.985 |
- 0.987 |
- 0.987 |
- 0.982 |
- 0.966 |
- 0.979 |
- 0.985 |
- 0.96 |
- 0.987 |
- 0.986 |
- 0.974 |
- 0.984 |
- 0.977 |
- 0.981 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.974 |
- 0.978 |
- 0.977 |
- 0.98 |
- 0.987 |
- 0.968 |
- 0.978 |
- 0.978 |
- 0.987 |
- 0.98 |
- 0.986 |
- 0.978 |
- 0.981 |
- 0.947 |
- 0.983 |
- 0.99 |
- 0.975 |
- 0.982 |
- 0.972 |
- 0.986 |
- 0.976 |
- 0.984 |
- 0.981 |
- 0.979 |
- 0.97 |
- 0.979 |
- 0.963 |
- 0.987 |
- 0.988 |
- 0.985 |
- 0.975 |
- 0.98 |
- 0.986 |
- 0.984 |
- 0.981 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.973 |
- 0.981 |
- 0.983 |
- 0.983 |
- 0.984 |
- 0.987 |
- 0.922 |
- 0.988 |
- 0.981 |
- 0.986 |
- 0.986 |
- 0.986 |
- 0.944 |
- 0.97 |
- 0.938 |
- |
- 0.884 |
- 0.98 |
-
-
- | Liver |
- 344 |
- F |
- 134 |
- 121214.24 |
- CD |
- BXD63 |
- H1414 |
- 0.982 |
- 0.932 |
- 0.933 |
- 0.982 |
- 0.972 |
- 0.976 |
- 0.98 |
- 0.982 |
- 0.901 |
- 0.975 |
- 0.962 |
- 0.985 |
- 0.968 |
- 0.976 |
- 0.97 |
- 0.975 |
- 0.982 |
- 0.969 |
- 0.979 |
- 0.98 |
- 0.972 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.985 |
- 0.979 |
- 0.98 |
- 0.986 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.977 |
- 0.933 |
- 0.983 |
- 0.988 |
- 0.982 |
- 0.956 |
- 0.99 |
- 1 |
- 0.991 |
- 0.981 |
- 0.978 |
- 0.983 |
- 0.98 |
- 0.983 |
- 0.956 |
- 0.967 |
- 0.974 |
- 0.984 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.984 |
- 0.971 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.976 |
- 0.984 |
- 0.986 |
- 0.965 |
- 0.951 |
- 0.987 |
- 0.89 |
- 0.972 |
- 0.973 |
- 0.975 |
- 0.979 |
- 0.973 |
- 0.959 |
- 0.983 |
- 0.96 |
- 0.978 |
- 0.98 |
- 0.985 |
- 0.986 |
- 0.984 |
- 0.979 |
- 0.981 |
- 0.983 |
- 0.977 |
- 0.973 |
- 0.957 |
- 0.97 |
- 0.98 |
- 0.97 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.978 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.989 |
- 0.988 |
- 0.978 |
- 0.981 |
- 0.983 |
- 0.979 |
- 0.985 |
- 0.973 |
- 0.984 |
- 0.973 |
- 0.977 |
- 0.971 |
- 0.982 |
- 0.98 |
- 0.978 |
- 0.974 |
- 0.982 |
- 0.934 |
- 0.989 |
- 0.991 |
- 0.976 |
- 0.978 |
- 0.975 |
- 0.984 |
- 0.968 |
- 0.976 |
- 0.973 |
- 0.975 |
- 0.963 |
- 0.976 |
- 0.963 |
- 0.988 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.987 |
- 0.984 |
- 0.982 |
- 0.981 |
- 0.983 |
- 0.975 |
- 0.968 |
- 0.973 |
- 0.979 |
- 0.983 |
- 0.978 |
- 0.985 |
- 0.916 |
- 0.979 |
- 0.972 |
- 0.98 |
- 0.981 |
- 0.983 |
- 0.96 |
- 0.975 |
- 0.951 |
- |
- 0.89 |
- 0.98 |
-
-
- | Liver |
- 751 |
- F |
- 133 |
- 083016.03 |
- CD |
- BXD63 |
- H1872 |
- 0.984 |
- 0.923 |
- 0.925 |
- 0.982 |
- 0.968 |
- 0.977 |
- 0.98 |
- 0.973 |
- 0.888 |
- 0.976 |
- 0.966 |
- 0.983 |
- 0.969 |
- 0.978 |
- 0.965 |
- 0.975 |
- 0.976 |
- 0.964 |
- 0.982 |
- 0.98 |
- 0.976 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.98 |
- 0.971 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.977 |
- 0.937 |
- 0.979 |
- 0.986 |
- 0.975 |
- 0.94 |
- 0.99 |
- 0.991 |
- 1 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.979 |
- 0.941 |
- 0.969 |
- 0.974 |
- 0.984 |
- 0.977 |
- 0.983 |
- 0.967 |
- 0.978 |
- 0.97 |
- 0.983 |
- 0.979 |
- 0.978 |
- 0.978 |
- 0.984 |
- 0.984 |
- 0.966 |
- 0.955 |
- 0.984 |
- 0.89 |
- 0.975 |
- 0.975 |
- 0.973 |
- 0.981 |
- 0.966 |
- 0.947 |
- 0.979 |
- 0.945 |
- 0.98 |
- 0.98 |
- 0.98 |
- 0.984 |
- 0.977 |
- 0.983 |
- 0.984 |
- 0.986 |
- 0.981 |
- 0.979 |
- 0.962 |
- 0.975 |
- 0.982 |
- 0.967 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.982 |
- 0.982 |
- 0.989 |
- 0.989 |
- 0.979 |
- 0.985 |
- 0.977 |
- 0.977 |
- 0.98 |
- 0.975 |
- 0.987 |
- 0.968 |
- 0.973 |
- 0.971 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.98 |
- 0.983 |
- 0.938 |
- 0.986 |
- 0.996 |
- 0.973 |
- 0.976 |
- 0.973 |
- 0.987 |
- 0.973 |
- 0.981 |
- 0.976 |
- 0.976 |
- 0.963 |
- 0.978 |
- 0.96 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.976 |
- 0.983 |
- 0.985 |
- 0.987 |
- 0.983 |
- 0.985 |
- 0.987 |
- 0.975 |
- 0.969 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.982 |
- 0.985 |
- 0.917 |
- 0.984 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.981 |
- 0.945 |
- 0.973 |
- 0.937 |
- |
- 0.888 |
- 0.97 |
-
-
- | Liver |
- 222 |
- F |
- 107 |
- 042015.13 |
- CD |
- BXD65 |
- H2098 |
- 0.986 |
- 0.931 |
- 0.931 |
- 0.985 |
- 0.975 |
- 0.985 |
- 0.983 |
- 0.969 |
- 0.893 |
- 0.984 |
- 0.974 |
- 0.987 |
- 0.98 |
- 0.983 |
- 0.974 |
- 0.983 |
- 0.973 |
- 0.971 |
- 0.982 |
- 0.983 |
- 0.979 |
- 0.988 |
- 0.984 |
- 0.986 |
- 0.982 |
- 0.975 |
- 0.975 |
- 0.981 |
- 0.986 |
- 0.983 |
- 0.985 |
- 0.984 |
- 0.95 |
- 0.977 |
- 0.983 |
- 0.979 |
- 0.936 |
- 0.985 |
- 0.981 |
- 0.984 |
- 1 |
- 0.987 |
- 0.986 |
- 0.989 |
- 0.984 |
- 0.948 |
- 0.972 |
- 0.977 |
- 0.985 |
- 0.975 |
- 0.988 |
- 0.962 |
- 0.979 |
- 0.974 |
- 0.983 |
- 0.983 |
- 0.979 |
- 0.986 |
- 0.987 |
- 0.982 |
- 0.971 |
- 0.966 |
- 0.985 |
- 0.9 |
- 0.984 |
- 0.978 |
- 0.981 |
- 0.986 |
- 0.971 |
- 0.946 |
- 0.981 |
- 0.946 |
- 0.987 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.971 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.982 |
- 0.983 |
- 0.971 |
- 0.984 |
- 0.988 |
- 0.971 |
- 0.984 |
- 0.985 |
- 0.978 |
- 0.986 |
- 0.983 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.974 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.986 |
- 0.973 |
- 0.976 |
- 0.98 |
- 0.984 |
- 0.982 |
- 0.989 |
- 0.98 |
- 0.982 |
- 0.947 |
- 0.972 |
- 0.984 |
- 0.97 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.983 |
- 0.988 |
- 0.984 |
- 0.981 |
- 0.97 |
- 0.98 |
- 0.968 |
- 0.981 |
- 0.985 |
- 0.985 |
- 0.971 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.984 |
- 0.932 |
- 0.982 |
- 0.978 |
- 0.989 |
- 0.984 |
- 0.98 |
- 0.946 |
- 0.977 |
- 0.942 |
- |
- 0.893 |
- 0.98 |
-
-
- | Liver |
- 541 |
- F |
- 322 |
- 121615.09 |
- CD |
- BXD65 |
- H1787 |
- 0.985 |
- 0.926 |
- 0.928 |
- 0.984 |
- 0.977 |
- 0.984 |
- 0.982 |
- 0.962 |
- 0.888 |
- 0.982 |
- 0.975 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.971 |
- 0.976 |
- 0.971 |
- 0.959 |
- 0.981 |
- 0.984 |
- 0.974 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.973 |
- 0.975 |
- 0.976 |
- 0.97 |
- 0.987 |
- 0.982 |
- 0.984 |
- 0.978 |
- 0.954 |
- 0.981 |
- 0.981 |
- 0.975 |
- 0.931 |
- 0.983 |
- 0.978 |
- 0.98 |
- 0.987 |
- 1 |
- 0.987 |
- 0.992 |
- 0.98 |
- 0.943 |
- 0.978 |
- 0.981 |
- 0.982 |
- 0.976 |
- 0.984 |
- 0.96 |
- 0.976 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.974 |
- 0.98 |
- 0.984 |
- 0.981 |
- 0.975 |
- 0.97 |
- 0.973 |
- 0.899 |
- 0.983 |
- 0.983 |
- 0.977 |
- 0.981 |
- 0.962 |
- 0.937 |
- 0.979 |
- 0.934 |
- 0.986 |
- 0.982 |
- 0.978 |
- 0.981 |
- 0.974 |
- 0.986 |
- 0.984 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.971 |
- 0.982 |
- 0.982 |
- 0.965 |
- 0.984 |
- 0.985 |
- 0.972 |
- 0.977 |
- 0.984 |
- 0.982 |
- 0.981 |
- 0.979 |
- 0.979 |
- 0.982 |
- 0.983 |
- 0.964 |
- 0.976 |
- 0.968 |
- 0.982 |
- 0.979 |
- 0.969 |
- 0.973 |
- 0.981 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.976 |
- 0.978 |
- 0.949 |
- 0.971 |
- 0.979 |
- 0.97 |
- 0.979 |
- 0.977 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.985 |
- 0.975 |
- 0.972 |
- 0.973 |
- 0.964 |
- 0.979 |
- 0.983 |
- 0.981 |
- 0.968 |
- 0.979 |
- 0.979 |
- 0.984 |
- 0.978 |
- 0.983 |
- 0.98 |
- 0.975 |
- 0.976 |
- 0.98 |
- 0.978 |
- 0.984 |
- 0.982 |
- 0.979 |
- 0.927 |
- 0.985 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.979 |
- 0.934 |
- 0.969 |
- 0.935 |
- |
- 0.888 |
- 0.97 |
-
-
- | Liver |
- 187 |
- F |
- 320 |
- 111414.05 |
- CD |
- BXD65b |
- H1766 |
- 0.985 |
- 0.921 |
- 0.923 |
- 0.983 |
- 0.971 |
- 0.976 |
- 0.981 |
- 0.968 |
- 0.888 |
- 0.982 |
- 0.969 |
- 0.979 |
- 0.975 |
- 0.98 |
- 0.962 |
- 0.973 |
- 0.978 |
- 0.958 |
- 0.979 |
- 0.98 |
- 0.966 |
- 0.983 |
- 0.98 |
- 0.981 |
- 0.977 |
- 0.973 |
- 0.974 |
- 0.974 |
- 0.984 |
- 0.977 |
- 0.983 |
- 0.976 |
- 0.939 |
- 0.986 |
- 0.986 |
- 0.975 |
- 0.936 |
- 0.983 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.987 |
- 1 |
- 0.987 |
- 0.978 |
- 0.94 |
- 0.972 |
- 0.976 |
- 0.982 |
- 0.973 |
- 0.98 |
- 0.965 |
- 0.977 |
- 0.975 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.976 |
- 0.985 |
- 0.984 |
- 0.964 |
- 0.959 |
- 0.979 |
- 0.892 |
- 0.982 |
- 0.981 |
- 0.974 |
- 0.98 |
- 0.966 |
- 0.945 |
- 0.976 |
- 0.944 |
- 0.98 |
- 0.981 |
- 0.976 |
- 0.984 |
- 0.977 |
- 0.983 |
- 0.981 |
- 0.984 |
- 0.977 |
- 0.977 |
- 0.962 |
- 0.977 |
- 0.979 |
- 0.964 |
- 0.982 |
- 0.981 |
- 0.976 |
- 0.975 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.978 |
- 0.979 |
- 0.968 |
- 0.975 |
- 0.972 |
- 0.976 |
- 0.978 |
- 0.968 |
- 0.973 |
- 0.97 |
- 0.983 |
- 0.987 |
- 0.984 |
- 0.979 |
- 0.978 |
- 0.939 |
- 0.98 |
- 0.982 |
- 0.963 |
- 0.978 |
- 0.974 |
- 0.987 |
- 0.974 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.964 |
- 0.972 |
- 0.957 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.973 |
- 0.979 |
- 0.98 |
- 0.982 |
- 0.978 |
- 0.979 |
- 0.982 |
- 0.976 |
- 0.968 |
- 0.977 |
- 0.978 |
- 0.982 |
- 0.978 |
- 0.981 |
- 0.916 |
- 0.981 |
- 0.975 |
- 0.978 |
- 0.977 |
- 0.974 |
- 0.944 |
- 0.969 |
- 0.932 |
- |
- 0.888 |
- 0.97 |
-
-
- | Liver |
- 527 |
- F |
- 313 |
- 121615.12 |
- CD |
- BXD65b |
- H1793 |
- 0.99 |
- 0.927 |
- 0.928 |
- 0.988 |
- 0.982 |
- 0.986 |
- 0.988 |
- 0.964 |
- 0.887 |
- 0.985 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.973 |
- 0.981 |
- 0.971 |
- 0.963 |
- 0.983 |
- 0.985 |
- 0.979 |
- 0.988 |
- 0.988 |
- 0.988 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.976 |
- 0.989 |
- 0.986 |
- 0.987 |
- 0.983 |
- 0.951 |
- 0.981 |
- 0.983 |
- 0.979 |
- 0.932 |
- 0.989 |
- 0.98 |
- 0.982 |
- 0.989 |
- 0.992 |
- 0.987 |
- 1 |
- 0.985 |
- 0.947 |
- 0.982 |
- 0.984 |
- 0.988 |
- 0.982 |
- 0.987 |
- 0.962 |
- 0.98 |
- 0.981 |
- 0.985 |
- 0.986 |
- 0.978 |
- 0.98 |
- 0.987 |
- 0.984 |
- 0.974 |
- 0.967 |
- 0.981 |
- 0.9 |
- 0.985 |
- 0.982 |
- 0.978 |
- 0.984 |
- 0.966 |
- 0.943 |
- 0.983 |
- 0.939 |
- 0.989 |
- 0.988 |
- 0.983 |
- 0.984 |
- 0.974 |
- 0.99 |
- 0.988 |
- 0.989 |
- 0.987 |
- 0.985 |
- 0.974 |
- 0.985 |
- 0.988 |
- 0.963 |
- 0.988 |
- 0.988 |
- 0.972 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.987 |
- 0.985 |
- 0.968 |
- 0.979 |
- 0.973 |
- 0.985 |
- 0.985 |
- 0.971 |
- 0.978 |
- 0.984 |
- 0.987 |
- 0.982 |
- 0.989 |
- 0.98 |
- 0.98 |
- 0.952 |
- 0.974 |
- 0.981 |
- 0.972 |
- 0.985 |
- 0.978 |
- 0.987 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.98 |
- 0.975 |
- 0.979 |
- 0.966 |
- 0.984 |
- 0.987 |
- 0.985 |
- 0.972 |
- 0.978 |
- 0.985 |
- 0.983 |
- 0.98 |
- 0.985 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.983 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.929 |
- 0.988 |
- 0.984 |
- 0.988 |
- 0.986 |
- 0.983 |
- 0.939 |
- 0.971 |
- 0.939 |
- |
- 0.887 |
- 0.98 |
-
-
- | Liver |
- 184 |
- F |
- 112 |
- 042415.08 |
- CD |
- BXD66 |
- H2128 |
- 0.983 |
- 0.929 |
- 0.929 |
- 0.984 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.977 |
- 0.897 |
- 0.979 |
- 0.967 |
- 0.986 |
- 0.977 |
- 0.978 |
- 0.971 |
- 0.977 |
- 0.975 |
- 0.972 |
- 0.977 |
- 0.979 |
- 0.978 |
- 0.983 |
- 0.984 |
- 0.986 |
- 0.985 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.983 |
- 0.983 |
- 0.94 |
- 0.98 |
- 0.986 |
- 0.982 |
- 0.949 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.984 |
- 0.98 |
- 0.978 |
- 0.985 |
- 1 |
- 0.961 |
- 0.97 |
- 0.978 |
- 0.98 |
- 0.978 |
- 0.987 |
- 0.973 |
- 0.984 |
- 0.971 |
- 0.981 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.966 |
- 0.952 |
- 0.985 |
- 0.889 |
- 0.978 |
- 0.973 |
- 0.978 |
- 0.982 |
- 0.974 |
- 0.957 |
- 0.983 |
- 0.954 |
- 0.981 |
- 0.981 |
- 0.987 |
- 0.982 |
- 0.979 |
- 0.979 |
- 0.984 |
- 0.984 |
- 0.98 |
- 0.976 |
- 0.964 |
- 0.977 |
- 0.986 |
- 0.967 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.976 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.978 |
- 0.979 |
- 0.978 |
- 0.981 |
- 0.978 |
- 0.982 |
- 0.973 |
- 0.978 |
- 0.979 |
- 0.981 |
- 0.977 |
- 0.982 |
- 0.972 |
- 0.979 |
- 0.942 |
- 0.975 |
- 0.981 |
- 0.973 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.974 |
- 0.989 |
- 0.985 |
- 0.977 |
- 0.967 |
- 0.978 |
- 0.966 |
- 0.984 |
- 0.986 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.985 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.975 |
- 0.975 |
- 0.973 |
- 0.972 |
- 0.979 |
- 0.985 |
- 0.976 |
- 0.982 |
- 0.924 |
- 0.979 |
- 0.972 |
- 0.984 |
- 0.981 |
- 0.985 |
- 0.954 |
- 0.972 |
- 0.957 |
- |
- 0.889 |
- 0.98 |
-
-
- | Liver |
- 354 |
- F |
- 113 |
- 121214.19 |
- CD |
- BXD66 |
- H1558 |
- 0.94 |
- 0.95 |
- 0.948 |
- 0.946 |
- 0.957 |
- 0.957 |
- 0.945 |
- 0.965 |
- 0.932 |
- 0.945 |
- 0.938 |
- 0.956 |
- 0.943 |
- 0.939 |
- 0.962 |
- 0.948 |
- 0.954 |
- 0.957 |
- 0.945 |
- 0.947 |
- 0.947 |
- 0.946 |
- 0.951 |
- 0.949 |
- 0.956 |
- 0.97 |
- 0.969 |
- 0.965 |
- 0.955 |
- 0.949 |
- 0.946 |
- 0.95 |
- 0.923 |
- 0.951 |
- 0.949 |
- 0.965 |
- 0.969 |
- 0.948 |
- 0.956 |
- 0.941 |
- 0.948 |
- 0.943 |
- 0.94 |
- 0.947 |
- 0.961 |
- 1 |
- 0.942 |
- 0.949 |
- 0.946 |
- 0.958 |
- 0.948 |
- 0.969 |
- 0.967 |
- 0.953 |
- 0.949 |
- 0.949 |
- 0.962 |
- 0.941 |
- 0.951 |
- 0.953 |
- 0.944 |
- 0.931 |
- 0.952 |
- 0.9 |
- 0.939 |
- 0.939 |
- 0.959 |
- 0.946 |
- 0.966 |
- 0.958 |
- 0.961 |
- 0.96 |
- 0.946 |
- 0.945 |
- 0.957 |
- 0.953 |
- 0.961 |
- 0.942 |
- 0.949 |
- 0.947 |
- 0.95 |
- 0.94 |
- 0.94 |
- 0.939 |
- 0.954 |
- 0.951 |
- 0.947 |
- 0.947 |
- 0.956 |
- 0.948 |
- 0.936 |
- 0.948 |
- 0.952 |
- 0.954 |
- 0.953 |
- 0.95 |
- 0.944 |
- 0.966 |
- 0.959 |
- 0.963 |
- 0.946 |
- 0.953 |
- 0.96 |
- 0.96 |
- 0.949 |
- 0.943 |
- 0.939 |
- 0.937 |
- 0.929 |
- 0.956 |
- 0.921 |
- 0.952 |
- 0.946 |
- 0.961 |
- 0.953 |
- 0.959 |
- 0.94 |
- 0.939 |
- 0.948 |
- 0.949 |
- 0.946 |
- 0.949 |
- 0.945 |
- 0.959 |
- 0.955 |
- 0.95 |
- 0.948 |
- 0.967 |
- 0.948 |
- 0.958 |
- 0.941 |
- 0.956 |
- 0.944 |
- 0.941 |
- 0.944 |
- 0.947 |
- 0.936 |
- 0.95 |
- 0.961 |
- 0.94 |
- 0.954 |
- 0.917 |
- 0.94 |
- 0.934 |
- 0.951 |
- 0.945 |
- 0.953 |
- 0.96 |
- 0.946 |
- 0.973 |
- |
- 0.9 |
- 0.95 |
-
-
- | Liver |
- 201 |
- F |
- 271 |
- 101613.05 |
- CD |
- BXD68 |
- H1068 |
- 0.984 |
- 0.922 |
- 0.924 |
- 0.979 |
- 0.987 |
- 0.977 |
- 0.989 |
- 0.946 |
- 0.883 |
- 0.983 |
- 0.973 |
- 0.973 |
- 0.977 |
- 0.977 |
- 0.968 |
- 0.972 |
- 0.96 |
- 0.947 |
- 0.976 |
- 0.974 |
- 0.966 |
- 0.977 |
- 0.983 |
- 0.981 |
- 0.967 |
- 0.968 |
- 0.969 |
- 0.96 |
- 0.981 |
- 0.98 |
- 0.976 |
- 0.976 |
- 0.949 |
- 0.973 |
- 0.966 |
- 0.969 |
- 0.929 |
- 0.98 |
- 0.967 |
- 0.969 |
- 0.972 |
- 0.978 |
- 0.972 |
- 0.982 |
- 0.97 |
- 0.942 |
- 1 |
- 0.987 |
- 0.978 |
- 0.98 |
- 0.975 |
- 0.952 |
- 0.967 |
- 0.984 |
- 0.979 |
- 0.98 |
- 0.968 |
- 0.967 |
- 0.975 |
- 0.978 |
- 0.98 |
- 0.968 |
- 0.968 |
- 0.905 |
- 0.974 |
- 0.977 |
- 0.964 |
- 0.974 |
- 0.958 |
- 0.934 |
- 0.977 |
- 0.927 |
- 0.981 |
- 0.989 |
- 0.971 |
- 0.978 |
- 0.963 |
- 0.989 |
- 0.977 |
- 0.978 |
- 0.983 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.977 |
- 0.951 |
- 0.981 |
- 0.98 |
- 0.956 |
- 0.976 |
- 0.971 |
- 0.977 |
- 0.976 |
- 0.966 |
- 0.965 |
- 0.979 |
- 0.972 |
- 0.957 |
- 0.974 |
- 0.962 |
- 0.977 |
- 0.973 |
- 0.968 |
- 0.975 |
- 0.979 |
- 0.976 |
- 0.97 |
- 0.976 |
- 0.97 |
- 0.975 |
- 0.959 |
- 0.964 |
- 0.967 |
- 0.965 |
- 0.982 |
- 0.964 |
- 0.973 |
- 0.978 |
- 0.973 |
- 0.984 |
- 0.986 |
- 0.982 |
- 0.977 |
- 0.967 |
- 0.977 |
- 0.976 |
- 0.975 |
- 0.961 |
- 0.968 |
- 0.974 |
- 0.97 |
- 0.975 |
- 0.972 |
- 0.969 |
- 0.982 |
- 0.974 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.978 |
- 0.976 |
- 0.929 |
- 0.985 |
- 0.976 |
- 0.978 |
- 0.979 |
- 0.973 |
- 0.927 |
- 0.958 |
- 0.933 |
- |
- 0.883 |
- 0.97 |
-
-
- | Liver |
- 545 |
- F |
- 74 |
- 082214.02 |
- CD |
- BXD68 |
- H1080 |
- 0.982 |
- 0.936 |
- 0.937 |
- 0.982 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.96 |
- 0.903 |
- 0.983 |
- 0.978 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.973 |
- 0.977 |
- 0.97 |
- 0.956 |
- 0.983 |
- 0.981 |
- 0.972 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.973 |
- 0.976 |
- 0.976 |
- 0.967 |
- 0.984 |
- 0.982 |
- 0.978 |
- 0.98 |
- 0.96 |
- 0.976 |
- 0.973 |
- 0.976 |
- 0.938 |
- 0.982 |
- 0.974 |
- 0.974 |
- 0.977 |
- 0.981 |
- 0.976 |
- 0.984 |
- 0.978 |
- 0.949 |
- 0.987 |
- 1 |
- 0.978 |
- 0.977 |
- 0.98 |
- 0.96 |
- 0.974 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.972 |
- 0.97 |
- 0.981 |
- 0.981 |
- 0.976 |
- 0.967 |
- 0.972 |
- 0.921 |
- 0.976 |
- 0.976 |
- 0.973 |
- 0.982 |
- 0.966 |
- 0.942 |
- 0.981 |
- 0.935 |
- 0.983 |
- 0.983 |
- 0.976 |
- 0.981 |
- 0.972 |
- 0.983 |
- 0.982 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.975 |
- 0.98 |
- 0.979 |
- 0.963 |
- 0.982 |
- 0.982 |
- 0.97 |
- 0.977 |
- 0.975 |
- 0.984 |
- 0.984 |
- 0.974 |
- 0.973 |
- 0.98 |
- 0.976 |
- 0.965 |
- 0.977 |
- 0.967 |
- 0.98 |
- 0.975 |
- 0.974 |
- 0.977 |
- 0.982 |
- 0.977 |
- 0.976 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.964 |
- 0.97 |
- 0.974 |
- 0.973 |
- 0.977 |
- 0.973 |
- 0.973 |
- 0.979 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.978 |
- 0.971 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.968 |
- 0.974 |
- 0.98 |
- 0.977 |
- 0.98 |
- 0.976 |
- 0.97 |
- 0.975 |
- 0.977 |
- 0.979 |
- 0.976 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.942 |
- 0.982 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.976 |
- 0.935 |
- 0.962 |
- 0.942 |
- |
- 0.903 |
- 0.97 |
-
-
- | Liver |
- 157 |
- F |
- 114 |
- 042415.23 |
- CD |
- BXD69 |
- H2142 |
- 0.989 |
- 0.925 |
- 0.927 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.985 |
- 0.964 |
- 0.884 |
- 0.98 |
- 0.973 |
- 0.988 |
- 0.976 |
- 0.979 |
- 0.971 |
- 0.983 |
- 0.969 |
- 0.961 |
- 0.981 |
- 0.982 |
- 0.977 |
- 0.988 |
- 0.986 |
- 0.986 |
- 0.978 |
- 0.974 |
- 0.975 |
- 0.978 |
- 0.984 |
- 0.987 |
- 0.986 |
- 0.982 |
- 0.944 |
- 0.978 |
- 0.981 |
- 0.977 |
- 0.934 |
- 0.99 |
- 0.984 |
- 0.984 |
- 0.985 |
- 0.982 |
- 0.982 |
- 0.988 |
- 0.98 |
- 0.946 |
- 0.978 |
- 0.978 |
- 1 |
- 0.989 |
- 0.985 |
- 0.966 |
- 0.978 |
- 0.978 |
- 0.988 |
- 0.987 |
- 0.977 |
- 0.978 |
- 0.986 |
- 0.984 |
- 0.976 |
- 0.963 |
- 0.983 |
- 0.897 |
- 0.982 |
- 0.98 |
- 0.971 |
- 0.982 |
- 0.963 |
- 0.94 |
- 0.982 |
- 0.942 |
- 0.984 |
- 0.985 |
- 0.982 |
- 0.984 |
- 0.972 |
- 0.988 |
- 0.984 |
- 0.986 |
- 0.984 |
- 0.982 |
- 0.969 |
- 0.977 |
- 0.982 |
- 0.96 |
- 0.982 |
- 0.984 |
- 0.968 |
- 0.984 |
- 0.978 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.983 |
- 0.971 |
- 0.978 |
- 0.976 |
- 0.982 |
- 0.986 |
- 0.966 |
- 0.977 |
- 0.978 |
- 0.985 |
- 0.977 |
- 0.986 |
- 0.981 |
- 0.98 |
- 0.947 |
- 0.974 |
- 0.982 |
- 0.969 |
- 0.982 |
- 0.971 |
- 0.987 |
- 0.976 |
- 0.981 |
- 0.98 |
- 0.977 |
- 0.971 |
- 0.982 |
- 0.968 |
- 0.986 |
- 0.987 |
- 0.987 |
- 0.972 |
- 0.981 |
- 0.987 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.985 |
- 0.982 |
- 0.975 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.986 |
- 0.988 |
- 0.924 |
- 0.987 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.942 |
- 0.972 |
- 0.935 |
- |
- 0.884 |
- 0.98 |
-
-
- | Liver |
- 558 |
- F |
- 41 |
- 061913.13 |
- CD |
- BXD69 |
- H0591 |
- 0.982 |
- 0.935 |
- 0.937 |
- 0.979 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.966 |
- 0.9 |
- 0.977 |
- 0.968 |
- 0.981 |
- 0.97 |
- 0.974 |
- 0.976 |
- 0.975 |
- 0.967 |
- 0.96 |
- 0.975 |
- 0.977 |
- 0.971 |
- 0.98 |
- 0.984 |
- 0.982 |
- 0.977 |
- 0.979 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.942 |
- 0.973 |
- 0.976 |
- 0.977 |
- 0.954 |
- 0.983 |
- 0.98 |
- 0.977 |
- 0.975 |
- 0.976 |
- 0.973 |
- 0.982 |
- 0.978 |
- 0.958 |
- 0.98 |
- 0.977 |
- 0.989 |
- 1 |
- 0.977 |
- 0.974 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.967 |
- 0.979 |
- 0.98 |
- 0.976 |
- 0.959 |
- 0.976 |
- 0.901 |
- 0.97 |
- 0.973 |
- 0.971 |
- 0.976 |
- 0.968 |
- 0.954 |
- 0.986 |
- 0.95 |
- 0.977 |
- 0.983 |
- 0.978 |
- 0.98 |
- 0.975 |
- 0.983 |
- 0.978 |
- 0.979 |
- 0.985 |
- 0.979 |
- 0.969 |
- 0.969 |
- 0.981 |
- 0.959 |
- 0.98 |
- 0.98 |
- 0.965 |
- 0.979 |
- 0.97 |
- 0.976 |
- 0.976 |
- 0.978 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.979 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.973 |
- 0.978 |
- 0.976 |
- 0.978 |
- 0.969 |
- 0.976 |
- 0.971 |
- 0.979 |
- 0.948 |
- 0.971 |
- 0.976 |
- 0.97 |
- 0.983 |
- 0.971 |
- 0.977 |
- 0.974 |
- 0.975 |
- 0.98 |
- 0.977 |
- 0.973 |
- 0.982 |
- 0.976 |
- 0.984 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.975 |
- 0.984 |
- 0.975 |
- 0.979 |
- 0.978 |
- 0.974 |
- 0.978 |
- 0.972 |
- 0.977 |
- 0.981 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.924 |
- 0.983 |
- 0.974 |
- 0.979 |
- 0.98 |
- 0.978 |
- 0.95 |
- 0.968 |
- 0.952 |
- |
- 0.9 |
- 0.97 |
-
-
- | Liver |
- 261 |
- F |
- 207 |
- 050115.06 |
- CD |
- BXD70 |
- H1855 |
- 0.989 |
- 0.929 |
- 0.93 |
- 0.99 |
- 0.979 |
- 0.988 |
- 0.984 |
- 0.969 |
- 0.893 |
- 0.983 |
- 0.975 |
- 0.989 |
- 0.984 |
- 0.986 |
- 0.974 |
- 0.986 |
- 0.974 |
- 0.967 |
- 0.985 |
- 0.987 |
- 0.983 |
- 0.99 |
- 0.988 |
- 0.99 |
- 0.984 |
- 0.976 |
- 0.976 |
- 0.978 |
- 0.987 |
- 0.988 |
- 0.987 |
- 0.987 |
- 0.951 |
- 0.975 |
- 0.986 |
- 0.98 |
- 0.935 |
- 0.987 |
- 0.983 |
- 0.983 |
- 0.988 |
- 0.984 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.948 |
- 0.975 |
- 0.98 |
- 0.985 |
- 0.977 |
- 1 |
- 0.967 |
- 0.981 |
- 0.977 |
- 0.987 |
- 0.988 |
- 0.979 |
- 0.984 |
- 0.99 |
- 0.981 |
- 0.976 |
- 0.966 |
- 0.986 |
- 0.901 |
- 0.985 |
- 0.981 |
- 0.976 |
- 0.988 |
- 0.97 |
- 0.942 |
- 0.983 |
- 0.941 |
- 0.988 |
- 0.984 |
- 0.986 |
- 0.981 |
- 0.975 |
- 0.985 |
- 0.99 |
- 0.989 |
- 0.981 |
- 0.983 |
- 0.972 |
- 0.983 |
- 0.985 |
- 0.968 |
- 0.986 |
- 0.989 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.986 |
- 0.986 |
- 0.982 |
- 0.981 |
- 0.987 |
- 0.984 |
- 0.974 |
- 0.979 |
- 0.978 |
- 0.986 |
- 0.984 |
- 0.971 |
- 0.978 |
- 0.983 |
- 0.987 |
- 0.979 |
- 0.986 |
- 0.982 |
- 0.984 |
- 0.95 |
- 0.972 |
- 0.983 |
- 0.971 |
- 0.98 |
- 0.976 |
- 0.982 |
- 0.98 |
- 0.987 |
- 0.982 |
- 0.982 |
- 0.974 |
- 0.982 |
- 0.967 |
- 0.988 |
- 0.994 |
- 0.99 |
- 0.971 |
- 0.984 |
- 0.988 |
- 0.986 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.986 |
- 0.934 |
- 0.984 |
- 0.98 |
- 0.989 |
- 0.988 |
- 0.986 |
- 0.941 |
- 0.972 |
- 0.943 |
- |
- 0.893 |
- 0.98 |
-
-
- | Liver |
- 357 |
- F |
- 197 |
- 121214.16 |
- CD |
- BXD70 |
- H1512 |
- 0.961 |
- 0.935 |
- 0.935 |
- 0.961 |
- 0.963 |
- 0.96 |
- 0.961 |
- 0.979 |
- 0.916 |
- 0.959 |
- 0.941 |
- 0.972 |
- 0.953 |
- 0.957 |
- 0.964 |
- 0.954 |
- 0.972 |
- 0.964 |
- 0.96 |
- 0.961 |
- 0.95 |
- 0.963 |
- 0.967 |
- 0.965 |
- 0.976 |
- 0.981 |
- 0.982 |
- 0.982 |
- 0.967 |
- 0.963 |
- 0.964 |
- 0.959 |
- 0.915 |
- 0.974 |
- 0.975 |
- 0.975 |
- 0.98 |
- 0.97 |
- 0.981 |
- 0.967 |
- 0.962 |
- 0.96 |
- 0.965 |
- 0.962 |
- 0.973 |
- 0.969 |
- 0.952 |
- 0.96 |
- 0.966 |
- 0.974 |
- 0.967 |
- 1 |
- 0.984 |
- 0.959 |
- 0.967 |
- 0.963 |
- 0.98 |
- 0.953 |
- 0.966 |
- 0.973 |
- 0.949 |
- 0.932 |
- 0.972 |
- 0.877 |
- 0.954 |
- 0.956 |
- 0.968 |
- 0.962 |
- 0.978 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.957 |
- 0.961 |
- 0.972 |
- 0.973 |
- 0.981 |
- 0.959 |
- 0.962 |
- 0.963 |
- 0.963 |
- 0.953 |
- 0.938 |
- 0.949 |
- 0.968 |
- 0.962 |
- 0.967 |
- 0.962 |
- 0.973 |
- 0.96 |
- 0.954 |
- 0.962 |
- 0.965 |
- 0.973 |
- 0.972 |
- 0.963 |
- 0.96 |
- 0.985 |
- 0.97 |
- 0.983 |
- 0.954 |
- 0.968 |
- 0.966 |
- 0.97 |
- 0.951 |
- 0.96 |
- 0.961 |
- 0.956 |
- 0.95 |
- 0.967 |
- 0.917 |
- 0.976 |
- 0.97 |
- 0.963 |
- 0.967 |
- 0.968 |
- 0.963 |
- 0.947 |
- 0.958 |
- 0.957 |
- 0.957 |
- 0.948 |
- 0.957 |
- 0.958 |
- 0.978 |
- 0.969 |
- 0.961 |
- 0.987 |
- 0.964 |
- 0.974 |
- 0.962 |
- 0.967 |
- 0.96 |
- 0.965 |
- 0.96 |
- 0.948 |
- 0.949 |
- 0.965 |
- 0.975 |
- 0.955 |
- 0.97 |
- 0.899 |
- 0.96 |
- 0.947 |
- 0.961 |
- 0.959 |
- 0.965 |
- 0.976 |
- 0.965 |
- 0.969 |
- |
- 0.877 |
- 0.96 |
-
-
- | Liver |
- 361 |
- F |
- 203 |
- 121214.10 |
- CD |
- BXD73 |
- H1451 |
- 0.977 |
- 0.948 |
- 0.948 |
- 0.978 |
- 0.975 |
- 0.978 |
- 0.972 |
- 0.979 |
- 0.923 |
- 0.976 |
- 0.968 |
- 0.983 |
- 0.973 |
- 0.975 |
- 0.977 |
- 0.974 |
- 0.982 |
- 0.974 |
- 0.978 |
- 0.98 |
- 0.966 |
- 0.978 |
- 0.978 |
- 0.982 |
- 0.986 |
- 0.988 |
- 0.989 |
- 0.987 |
- 0.983 |
- 0.98 |
- 0.974 |
- 0.975 |
- 0.945 |
- 0.978 |
- 0.983 |
- 0.988 |
- 0.968 |
- 0.98 |
- 0.984 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.977 |
- 0.98 |
- 0.984 |
- 0.967 |
- 0.967 |
- 0.974 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.984 |
- 1 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.988 |
- 0.968 |
- 0.983 |
- 0.982 |
- 0.965 |
- 0.956 |
- 0.983 |
- 0.901 |
- 0.973 |
- 0.971 |
- 0.982 |
- 0.979 |
- 0.984 |
- 0.971 |
- 0.987 |
- 0.967 |
- 0.975 |
- 0.972 |
- 0.977 |
- 0.982 |
- 0.988 |
- 0.974 |
- 0.981 |
- 0.979 |
- 0.975 |
- 0.972 |
- 0.962 |
- 0.971 |
- 0.983 |
- 0.974 |
- 0.981 |
- 0.978 |
- 0.98 |
- 0.974 |
- 0.972 |
- 0.979 |
- 0.981 |
- 0.981 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.986 |
- 0.98 |
- 0.987 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.971 |
- 0.972 |
- 0.978 |
- 0.976 |
- 0.969 |
- 0.981 |
- 0.939 |
- 0.976 |
- 0.978 |
- 0.971 |
- 0.976 |
- 0.982 |
- 0.972 |
- 0.968 |
- 0.977 |
- 0.975 |
- 0.972 |
- 0.967 |
- 0.972 |
- 0.971 |
- 0.983 |
- 0.981 |
- 0.979 |
- 0.992 |
- 0.979 |
- 0.988 |
- 0.975 |
- 0.981 |
- 0.98 |
- 0.974 |
- 0.971 |
- 0.971 |
- 0.969 |
- 0.973 |
- 0.987 |
- 0.971 |
- 0.978 |
- 0.927 |
- 0.974 |
- 0.968 |
- 0.978 |
- 0.973 |
- 0.971 |
- 0.967 |
- 0.977 |
- 0.968 |
- |
- 0.901 |
- 0.98 |
-
-
- | Liver |
- 539 |
- F |
- 213 |
- 121615.17 |
- CD |
- BXD73 |
- H1906 |
- 0.98 |
- 0.943 |
- 0.944 |
- 0.98 |
- 0.986 |
- 0.983 |
- 0.979 |
- 0.958 |
- 0.91 |
- 0.981 |
- 0.977 |
- 0.974 |
- 0.98 |
- 0.98 |
- 0.976 |
- 0.975 |
- 0.971 |
- 0.951 |
- 0.977 |
- 0.982 |
- 0.966 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.971 |
- 0.973 |
- 0.974 |
- 0.964 |
- 0.984 |
- 0.985 |
- 0.975 |
- 0.978 |
- 0.961 |
- 0.974 |
- 0.969 |
- 0.977 |
- 0.943 |
- 0.977 |
- 0.971 |
- 0.97 |
- 0.974 |
- 0.979 |
- 0.975 |
- 0.981 |
- 0.971 |
- 0.953 |
- 0.984 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.977 |
- 0.959 |
- 0.979 |
- 1 |
- 0.984 |
- 0.985 |
- 0.973 |
- 0.966 |
- 0.982 |
- 0.979 |
- 0.981 |
- 0.973 |
- 0.969 |
- 0.924 |
- 0.975 |
- 0.979 |
- 0.972 |
- 0.978 |
- 0.966 |
- 0.938 |
- 0.979 |
- 0.935 |
- 0.98 |
- 0.979 |
- 0.971 |
- 0.979 |
- 0.975 |
- 0.983 |
- 0.98 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.973 |
- 0.975 |
- 0.962 |
- 0.979 |
- 0.981 |
- 0.967 |
- 0.972 |
- 0.971 |
- 0.978 |
- 0.979 |
- 0.973 |
- 0.974 |
- 0.979 |
- 0.976 |
- 0.964 |
- 0.978 |
- 0.966 |
- 0.981 |
- 0.972 |
- 0.977 |
- 0.976 |
- 0.98 |
- 0.974 |
- 0.974 |
- 0.972 |
- 0.972 |
- 0.98 |
- 0.961 |
- 0.967 |
- 0.968 |
- 0.97 |
- 0.979 |
- 0.972 |
- 0.97 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.976 |
- 0.975 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.972 |
- 0.978 |
- 0.983 |
- 0.973 |
- 0.98 |
- 0.976 |
- 0.969 |
- 0.978 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.981 |
- 0.978 |
- 0.977 |
- 0.942 |
- 0.979 |
- 0.975 |
- 0.978 |
- 0.975 |
- 0.971 |
- 0.935 |
- 0.959 |
- 0.943 |
- |
- 0.91 |
- 0.97 |
-
-
- | Liver |
- 238 |
- F |
- 98 |
- 051112.12 |
- CD |
- BXD73b |
- H0184 |
- 0.989 |
- 0.929 |
- 0.931 |
- 0.986 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.964 |
- 0.892 |
- 0.981 |
- 0.973 |
- 0.986 |
- 0.983 |
- 0.985 |
- 0.972 |
- 0.981 |
- 0.974 |
- 0.96 |
- 0.983 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.989 |
- 0.988 |
- 0.98 |
- 0.973 |
- 0.973 |
- 0.975 |
- 0.986 |
- 0.99 |
- 0.988 |
- 0.984 |
- 0.948 |
- 0.977 |
- 0.983 |
- 0.979 |
- 0.939 |
- 0.986 |
- 0.984 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.982 |
- 0.985 |
- 0.981 |
- 0.949 |
- 0.979 |
- 0.98 |
- 0.988 |
- 0.983 |
- 0.987 |
- 0.967 |
- 0.981 |
- 0.984 |
- 1 |
- 0.99 |
- 0.976 |
- 0.978 |
- 0.989 |
- 0.982 |
- 0.982 |
- 0.964 |
- 0.984 |
- 0.902 |
- 0.983 |
- 0.985 |
- 0.974 |
- 0.985 |
- 0.966 |
- 0.939 |
- 0.979 |
- 0.943 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.982 |
- 0.975 |
- 0.989 |
- 0.988 |
- 0.989 |
- 0.98 |
- 0.982 |
- 0.971 |
- 0.979 |
- 0.98 |
- 0.965 |
- 0.983 |
- 0.99 |
- 0.975 |
- 0.981 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.986 |
- 0.983 |
- 0.972 |
- 0.981 |
- 0.976 |
- 0.984 |
- 0.981 |
- 0.971 |
- 0.981 |
- 0.982 |
- 0.988 |
- 0.979 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.953 |
- 0.974 |
- 0.981 |
- 0.97 |
- 0.985 |
- 0.974 |
- 0.986 |
- 0.978 |
- 0.981 |
- 0.983 |
- 0.983 |
- 0.975 |
- 0.981 |
- 0.969 |
- 0.989 |
- 0.989 |
- 0.991 |
- 0.976 |
- 0.99 |
- 0.992 |
- 0.987 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.986 |
- 0.978 |
- 0.983 |
- 0.987 |
- 0.986 |
- 0.988 |
- 0.989 |
- 0.93 |
- 0.986 |
- 0.981 |
- 0.986 |
- 0.987 |
- 0.985 |
- 0.943 |
- 0.97 |
- 0.941 |
- |
- 0.892 |
- 0.98 |
-
-
- | Liver |
- 497 |
- F |
- 253 |
- 050115.15 |
- CD |
- BXD73b |
- H1466 |
- 0.99 |
- 0.927 |
- 0.929 |
- 0.987 |
- 0.983 |
- 0.988 |
- 0.986 |
- 0.962 |
- 0.891 |
- 0.983 |
- 0.975 |
- 0.986 |
- 0.982 |
- 0.985 |
- 0.977 |
- 0.985 |
- 0.967 |
- 0.96 |
- 0.98 |
- 0.985 |
- 0.981 |
- 0.989 |
- 0.988 |
- 0.989 |
- 0.979 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.985 |
- 1 |
- 0.984 |
- 0.988 |
- 0.951 |
- 0.973 |
- 0.979 |
- 0.975 |
- 0.937 |
- 0.987 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.986 |
- 0.981 |
- 0.949 |
- 0.98 |
- 0.982 |
- 0.987 |
- 0.983 |
- 0.988 |
- 0.963 |
- 0.98 |
- 0.985 |
- 0.99 |
- 1 |
- 0.976 |
- 0.98 |
- 0.988 |
- 0.981 |
- 0.981 |
- 0.967 |
- 0.979 |
- 0.905 |
- 0.982 |
- 0.98 |
- 0.97 |
- 0.986 |
- 0.967 |
- 0.94 |
- 0.982 |
- 0.938 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.981 |
- 0.971 |
- 0.988 |
- 0.987 |
- 0.987 |
- 0.986 |
- 0.985 |
- 0.976 |
- 0.979 |
- 0.982 |
- 0.96 |
- 0.984 |
- 0.988 |
- 0.971 |
- 0.986 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.984 |
- 0.98 |
- 0.972 |
- 0.978 |
- 0.976 |
- 0.985 |
- 0.982 |
- 0.969 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.954 |
- 0.97 |
- 0.979 |
- 0.97 |
- 0.983 |
- 0.97 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.978 |
- 0.984 |
- 0.97 |
- 0.983 |
- 0.989 |
- 0.991 |
- 0.97 |
- 0.985 |
- 0.99 |
- 0.982 |
- 0.983 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.985 |
- 0.985 |
- 0.933 |
- 0.984 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.985 |
- 0.938 |
- 0.966 |
- 0.94 |
- |
- 0.891 |
- 0.98 |
-
-
- | Liver |
- 460 |
- F |
- 255 |
- 050115.17 |
- CD |
- BXD77 |
- H1398 |
- 0.979 |
- 0.943 |
- 0.943 |
- 0.978 |
- 0.974 |
- 0.977 |
- 0.976 |
- 0.976 |
- 0.914 |
- 0.977 |
- 0.965 |
- 0.982 |
- 0.969 |
- 0.976 |
- 0.976 |
- 0.972 |
- 0.979 |
- 0.972 |
- 0.976 |
- 0.977 |
- 0.967 |
- 0.98 |
- 0.976 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.985 |
- 0.986 |
- 0.983 |
- 0.976 |
- 0.974 |
- 0.974 |
- 0.941 |
- 0.975 |
- 0.982 |
- 0.985 |
- 0.963 |
- 0.98 |
- 0.983 |
- 0.978 |
- 0.979 |
- 0.974 |
- 0.975 |
- 0.978 |
- 0.982 |
- 0.962 |
- 0.968 |
- 0.972 |
- 0.977 |
- 0.981 |
- 0.979 |
- 0.98 |
- 0.988 |
- 0.973 |
- 0.976 |
- 0.976 |
- 1 |
- 0.967 |
- 0.98 |
- 0.983 |
- 0.963 |
- 0.959 |
- 0.982 |
- 0.898 |
- 0.972 |
- 0.969 |
- 0.98 |
- 0.979 |
- 0.983 |
- 0.97 |
- 0.987 |
- 0.961 |
- 0.976 |
- 0.976 |
- 0.975 |
- 0.983 |
- 0.983 |
- 0.975 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.974 |
- 0.964 |
- 0.968 |
- 0.984 |
- 0.97 |
- 0.984 |
- 0.977 |
- 0.976 |
- 0.976 |
- 0.971 |
- 0.978 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.978 |
- 0.985 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.977 |
- 0.97 |
- 0.972 |
- 0.975 |
- 0.977 |
- 0.969 |
- 0.982 |
- 0.937 |
- 0.974 |
- 0.978 |
- 0.969 |
- 0.976 |
- 0.98 |
- 0.973 |
- 0.972 |
- 0.977 |
- 0.975 |
- 0.975 |
- 0.966 |
- 0.975 |
- 0.969 |
- 0.982 |
- 0.978 |
- 0.975 |
- 0.984 |
- 0.974 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.978 |
- 0.975 |
- 0.973 |
- 0.972 |
- 0.97 |
- 0.974 |
- 0.984 |
- 0.97 |
- 0.979 |
- 0.924 |
- 0.974 |
- 0.967 |
- 0.978 |
- 0.974 |
- 0.972 |
- 0.961 |
- 0.977 |
- 0.963 |
- |
- 0.898 |
- 0.97 |
-
-
- | Liver |
- 217 |
- F |
- 272 |
- 090412.10 |
- CD |
- BXD79 |
- H0825 |
- 0.98 |
- 0.914 |
- 0.914 |
- 0.98 |
- 0.966 |
- 0.981 |
- 0.978 |
- 0.964 |
- 0.878 |
- 0.974 |
- 0.963 |
- 0.981 |
- 0.972 |
- 0.974 |
- 0.966 |
- 0.981 |
- 0.967 |
- 0.968 |
- 0.977 |
- 0.978 |
- 0.981 |
- 0.983 |
- 0.978 |
- 0.978 |
- 0.973 |
- 0.964 |
- 0.964 |
- 0.971 |
- 0.977 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.936 |
- 0.972 |
- 0.979 |
- 0.969 |
- 0.924 |
- 0.979 |
- 0.976 |
- 0.978 |
- 0.986 |
- 0.98 |
- 0.976 |
- 0.98 |
- 0.979 |
- 0.941 |
- 0.967 |
- 0.97 |
- 0.978 |
- 0.967 |
- 0.984 |
- 0.953 |
- 0.968 |
- 0.966 |
- 0.978 |
- 0.98 |
- 0.967 |
- 1 |
- 0.985 |
- 0.974 |
- 0.967 |
- 0.957 |
- 0.976 |
- 0.885 |
- 0.978 |
- 0.972 |
- 0.965 |
- 0.977 |
- 0.957 |
- 0.931 |
- 0.971 |
- 0.935 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.974 |
- 0.962 |
- 0.978 |
- 0.979 |
- 0.981 |
- 0.973 |
- 0.975 |
- 0.962 |
- 0.977 |
- 0.978 |
- 0.961 |
- 0.976 |
- 0.98 |
- 0.973 |
- 0.984 |
- 0.983 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.976 |
- 0.976 |
- 0.975 |
- 0.964 |
- 0.969 |
- 0.967 |
- 0.974 |
- 0.978 |
- 0.959 |
- 0.969 |
- 0.974 |
- 0.981 |
- 0.976 |
- 0.98 |
- 0.971 |
- 0.975 |
- 0.936 |
- 0.967 |
- 0.979 |
- 0.968 |
- 0.97 |
- 0.965 |
- 0.977 |
- 0.972 |
- 0.981 |
- 0.975 |
- 0.973 |
- 0.964 |
- 0.974 |
- 0.954 |
- 0.973 |
- 0.982 |
- 0.983 |
- 0.961 |
- 0.981 |
- 0.976 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.982 |
- 0.97 |
- 0.971 |
- 0.972 |
- 0.973 |
- 0.974 |
- 0.975 |
- 0.978 |
- 0.919 |
- 0.976 |
- 0.969 |
- 0.981 |
- 0.983 |
- 0.984 |
- 0.935 |
- 0.969 |
- 0.934 |
- |
- 0.878 |
- 0.97 |
-
-
- | Liver |
- 468 |
- F |
- 91 |
- 050115.19 |
- CD |
- BXD79 |
- H1555 |
- 0.989 |
- 0.935 |
- 0.937 |
- 0.989 |
- 0.979 |
- 0.99 |
- 0.982 |
- 0.97 |
- 0.901 |
- 0.983 |
- 0.976 |
- 0.988 |
- 0.983 |
- 0.987 |
- 0.974 |
- 0.988 |
- 0.982 |
- 0.967 |
- 0.988 |
- 0.988 |
- 0.98 |
- 0.99 |
- 0.986 |
- 0.988 |
- 0.984 |
- 0.977 |
- 0.977 |
- 0.979 |
- 0.989 |
- 0.988 |
- 0.986 |
- 0.986 |
- 0.951 |
- 0.978 |
- 0.987 |
- 0.983 |
- 0.941 |
- 0.985 |
- 0.984 |
- 0.984 |
- 0.987 |
- 0.984 |
- 0.985 |
- 0.987 |
- 0.984 |
- 0.951 |
- 0.975 |
- 0.981 |
- 0.986 |
- 0.979 |
- 0.99 |
- 0.966 |
- 0.983 |
- 0.982 |
- 0.989 |
- 0.988 |
- 0.98 |
- 0.985 |
- 1 |
- 0.986 |
- 0.977 |
- 0.967 |
- 0.985 |
- 0.908 |
- 0.986 |
- 0.983 |
- 0.978 |
- 0.986 |
- 0.973 |
- 0.944 |
- 0.981 |
- 0.945 |
- 0.986 |
- 0.982 |
- 0.983 |
- 0.986 |
- 0.979 |
- 0.986 |
- 0.99 |
- 0.99 |
- 0.98 |
- 0.983 |
- 0.973 |
- 0.981 |
- 0.983 |
- 0.97 |
- 0.986 |
- 0.989 |
- 0.979 |
- 0.984 |
- 0.985 |
- 0.989 |
- 0.989 |
- 0.985 |
- 0.984 |
- 0.985 |
- 0.984 |
- 0.977 |
- 0.981 |
- 0.98 |
- 0.986 |
- 0.983 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.985 |
- 0.983 |
- 0.986 |
- 0.985 |
- 0.987 |
- 0.949 |
- 0.975 |
- 0.983 |
- 0.969 |
- 0.98 |
- 0.978 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.982 |
- 0.977 |
- 0.982 |
- 0.968 |
- 0.985 |
- 0.99 |
- 0.99 |
- 0.976 |
- 0.988 |
- 0.99 |
- 0.987 |
- 0.987 |
- 0.984 |
- 0.985 |
- 0.978 |
- 0.981 |
- 0.983 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.986 |
- 0.934 |
- 0.983 |
- 0.98 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.945 |
- 0.974 |
- 0.945 |
- |
- 0.901 |
- 0.98 |
-
-
- | Liver |
- 200 |
- F |
- 6 |
- 090612.10 |
- CD |
- BXD87 |
- H0550 |
- 0.985 |
- 0.931 |
- 0.932 |
- 0.983 |
- 0.976 |
- 0.978 |
- 0.984 |
- 0.975 |
- 0.898 |
- 0.982 |
- 0.969 |
- 0.982 |
- 0.971 |
- 0.978 |
- 0.969 |
- 0.977 |
- 0.983 |
- 0.966 |
- 0.979 |
- 0.98 |
- 0.969 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.979 |
- 0.941 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.951 |
- 0.987 |
- 0.986 |
- 0.984 |
- 0.982 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.953 |
- 0.978 |
- 0.981 |
- 0.984 |
- 0.98 |
- 0.981 |
- 0.973 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.983 |
- 0.974 |
- 0.986 |
- 1 |
- 0.967 |
- 0.959 |
- 0.98 |
- 0.896 |
- 0.976 |
- 0.975 |
- 0.974 |
- 0.979 |
- 0.973 |
- 0.957 |
- 0.985 |
- 0.946 |
- 0.978 |
- 0.984 |
- 0.978 |
- 1 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.977 |
- 0.965 |
- 0.975 |
- 0.983 |
- 0.965 |
- 0.984 |
- 0.981 |
- 0.977 |
- 0.982 |
- 0.978 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.976 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.972 |
- 0.979 |
- 0.983 |
- 0.98 |
- 0.972 |
- 0.983 |
- 0.94 |
- 0.984 |
- 0.984 |
- 0.972 |
- 0.977 |
- 0.974 |
- 0.98 |
- 0.973 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.97 |
- 0.979 |
- 0.967 |
- 0.984 |
- 0.982 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.984 |
- 0.98 |
- 0.983 |
- 0.979 |
- 0.98 |
- 0.976 |
- 0.971 |
- 0.975 |
- 0.979 |
- 0.983 |
- 0.976 |
- 0.982 |
- 0.918 |
- 0.983 |
- 0.97 |
- 0.978 |
- 0.979 |
- 0.977 |
- 0.946 |
- 0.973 |
- 0.949 |
- |
- 0.896 |
- 0.98 |
-
-
- | Liver |
- 581 |
- F |
- 286 |
- 061913.19 |
- CD |
- BXD87 |
- H0296 |
- 0.979 |
- 0.932 |
- 0.935 |
- 0.974 |
- 0.984 |
- 0.981 |
- 0.976 |
- 0.942 |
- 0.894 |
- 0.976 |
- 0.969 |
- 0.976 |
- 0.979 |
- 0.978 |
- 0.976 |
- 0.977 |
- 0.959 |
- 0.949 |
- 0.975 |
- 0.976 |
- 0.967 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.967 |
- 0.96 |
- 0.961 |
- 0.959 |
- 0.978 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.958 |
- 0.961 |
- 0.963 |
- 0.966 |
- 0.928 |
- 0.973 |
- 0.965 |
- 0.966 |
- 0.971 |
- 0.975 |
- 0.964 |
- 0.974 |
- 0.966 |
- 0.944 |
- 0.98 |
- 0.976 |
- 0.976 |
- 0.976 |
- 0.976 |
- 0.949 |
- 0.965 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.963 |
- 0.967 |
- 0.977 |
- 0.967 |
- 1 |
- 0.972 |
- 0.967 |
- 0.915 |
- 0.976 |
- 0.98 |
- 0.965 |
- 0.975 |
- 0.958 |
- 0.925 |
- 0.971 |
- 0.932 |
- 0.976 |
- 0.976 |
- 0.971 |
- 0.967 |
- 0.961 |
- 0.982 |
- 0.977 |
- 0.978 |
- 0.974 |
- 0.98 |
- 0.977 |
- 0.971 |
- 0.969 |
- 0.959 |
- 0.972 |
- 0.98 |
- 0.958 |
- 0.973 |
- 0.971 |
- 0.976 |
- 0.974 |
- 0.966 |
- 0.966 |
- 0.979 |
- 0.974 |
- 0.958 |
- 0.976 |
- 0.963 |
- 0.977 |
- 0.971 |
- 0.966 |
- 0.973 |
- 0.979 |
- 0.975 |
- 0.963 |
- 0.97 |
- 0.975 |
- 0.975 |
- 0.963 |
- 0.957 |
- 0.963 |
- 0.963 |
- 0.98 |
- 0.965 |
- 0.971 |
- 0.978 |
- 0.969 |
- 0.979 |
- 0.977 |
- 0.98 |
- 0.974 |
- 0.972 |
- 0.976 |
- 0.977 |
- 0.98 |
- 0.956 |
- 0.973 |
- 0.977 |
- 0.972 |
- 0.975 |
- 0.974 |
- 0.973 |
- 0.98 |
- 0.977 |
- 0.979 |
- 0.981 |
- 0.976 |
- 0.98 |
- 0.977 |
- 0.941 |
- 0.978 |
- 0.975 |
- 0.976 |
- 0.978 |
- 0.974 |
- 0.932 |
- 0.959 |
- 0.934 |
- |
- 0.894 |
- 0.97 |
-
-
- | Liver |
- 193 |
- F |
- 310 |
- 090612.14 |
- CD |
- BXD89 |
- H0555 |
- 0.968 |
- 0.942 |
- 0.945 |
- 0.969 |
- 0.97 |
- 0.974 |
- 0.962 |
- 0.931 |
- 0.901 |
- 0.969 |
- 0.974 |
- 0.962 |
- 0.967 |
- 0.965 |
- 0.967 |
- 0.967 |
- 0.952 |
- 0.941 |
- 0.972 |
- 0.971 |
- 0.954 |
- 0.966 |
- 0.964 |
- 0.965 |
- 0.951 |
- 0.956 |
- 0.957 |
- 0.948 |
- 0.973 |
- 0.967 |
- 0.961 |
- 0.96 |
- 0.973 |
- 0.949 |
- 0.951 |
- 0.962 |
- 0.911 |
- 0.961 |
- 0.951 |
- 0.955 |
- 0.966 |
- 0.97 |
- 0.959 |
- 0.967 |
- 0.952 |
- 0.931 |
- 0.968 |
- 0.967 |
- 0.963 |
- 0.959 |
- 0.966 |
- 0.932 |
- 0.956 |
- 0.973 |
- 0.964 |
- 0.967 |
- 0.959 |
- 0.957 |
- 0.967 |
- 0.959 |
- 0.972 |
- 1 |
- 0.953 |
- 0.939 |
- 0.97 |
- 0.969 |
- 0.967 |
- 0.964 |
- 0.946 |
- 0.911 |
- 0.96 |
- 0.911 |
- 0.972 |
- 0.962 |
- 0.95 |
- 0.959 |
- 0.951 |
- 0.972 |
- 0.97 |
- 0.968 |
- 0.962 |
- 0.974 |
- 0.975 |
- 0.968 |
- 0.962 |
- 0.958 |
- 0.963 |
- 0.966 |
- 0.943 |
- 0.962 |
- 0.964 |
- 0.973 |
- 0.971 |
- 0.958 |
- 0.958 |
- 0.967 |
- 0.973 |
- 0.942 |
- 0.967 |
- 0.947 |
- 0.976 |
- 0.961 |
- 0.962 |
- 0.957 |
- 0.971 |
- 0.961 |
- 0.959 |
- 0.965 |
- 0.965 |
- 0.969 |
- 0.956 |
- 0.94 |
- 0.951 |
- 0.95 |
- 0.961 |
- 0.967 |
- 0.959 |
- 0.98 |
- 0.961 |
- 0.968 |
- 0.964 |
- 0.976 |
- 0.959 |
- 0.962 |
- 0.96 |
- 0.963 |
- 0.965 |
- 0.944 |
- 0.963 |
- 0.962 |
- 0.96 |
- 0.969 |
- 0.973 |
- 0.957 |
- 0.966 |
- 0.98 |
- 0.976 |
- 0.96 |
- 0.968 |
- 0.97 |
- 0.962 |
- 0.947 |
- 0.968 |
- 0.971 |
- 0.966 |
- 0.967 |
- 0.951 |
- 0.911 |
- 0.957 |
- 0.919 |
- |
- 0.901 |
- 0.96 |
-
-
- | Liver |
- 245 |
- F |
- 230 |
- 102616.12 |
- CD |
- BXD9 |
- H2577 |
- 0.984 |
- 0.932 |
- 0.932 |
- 0.983 |
- 0.973 |
- 0.979 |
- 0.981 |
- 0.972 |
- 0.895 |
- 0.977 |
- 0.965 |
- 0.988 |
- 0.976 |
- 0.981 |
- 0.968 |
- 0.979 |
- 0.978 |
- 0.971 |
- 0.981 |
- 0.979 |
- 0.976 |
- 0.986 |
- 0.984 |
- 0.987 |
- 0.987 |
- 0.976 |
- 0.976 |
- 0.985 |
- 0.982 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.938 |
- 0.976 |
- 0.987 |
- 0.981 |
- 0.946 |
- 0.984 |
- 0.987 |
- 0.984 |
- 0.985 |
- 0.973 |
- 0.979 |
- 0.981 |
- 0.985 |
- 0.952 |
- 0.968 |
- 0.972 |
- 0.983 |
- 0.976 |
- 0.986 |
- 0.972 |
- 0.983 |
- 0.969 |
- 0.984 |
- 0.979 |
- 0.982 |
- 0.976 |
- 0.985 |
- 0.98 |
- 0.967 |
- 0.953 |
- 1 |
- 0.893 |
- 0.979 |
- 0.974 |
- 0.979 |
- 0.983 |
- 0.974 |
- 0.955 |
- 0.98 |
- 0.959 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.98 |
- 0.976 |
- 0.98 |
- 0.987 |
- 0.986 |
- 0.975 |
- 0.975 |
- 0.962 |
- 0.975 |
- 0.982 |
- 0.971 |
- 0.983 |
- 0.983 |
- 0.98 |
- 0.98 |
- 0.975 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.986 |
- 0.981 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.977 |
- 0.983 |
- 0.972 |
- 0.98 |
- 0.974 |
- 0.982 |
- 0.975 |
- 0.983 |
- 0.982 |
- 0.982 |
- 0.942 |
- 0.976 |
- 0.984 |
- 0.967 |
- 0.982 |
- 0.979 |
- 0.985 |
- 0.972 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.964 |
- 0.979 |
- 0.964 |
- 0.987 |
- 0.986 |
- 0.982 |
- 0.977 |
- 0.979 |
- 0.987 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.978 |
- 0.98 |
- 0.972 |
- 0.98 |
- 0.981 |
- 0.983 |
- 0.98 |
- 0.986 |
- 0.923 |
- 0.979 |
- 0.976 |
- 0.986 |
- 0.984 |
- 0.981 |
- 0.959 |
- 0.977 |
- 0.952 |
- |
- 0.893 |
- 0.98 |
-
-
- | Liver |
- 548 |
- F |
- 73 |
- 082214.11 |
- CD |
- BXD9 |
- H1006 |
- 0.897 |
- 0.943 |
- 0.945 |
- 0.906 |
- 0.915 |
- 0.924 |
- 0.893 |
- 0.879 |
- 0.918 |
- 0.906 |
- 0.927 |
- 0.899 |
- 0.912 |
- 0.904 |
- 0.919 |
- 0.913 |
- 0.896 |
- 0.88 |
- 0.915 |
- 0.913 |
- 0.896 |
- 0.9 |
- 0.899 |
- 0.899 |
- 0.89 |
- 0.903 |
- 0.904 |
- 0.89 |
- 0.916 |
- 0.905 |
- 0.895 |
- 0.902 |
- 0.943 |
- 0.884 |
- 0.883 |
- 0.91 |
- 0.875 |
- 0.896 |
- 0.89 |
- 0.89 |
- 0.9 |
- 0.899 |
- 0.892 |
- 0.9 |
- 0.889 |
- 0.9 |
- 0.905 |
- 0.921 |
- 0.897 |
- 0.901 |
- 0.901 |
- 0.877 |
- 0.901 |
- 0.924 |
- 0.902 |
- 0.905 |
- 0.898 |
- 0.885 |
- 0.908 |
- 0.896 |
- 0.915 |
- 0.939 |
- 0.893 |
- 1 |
- 0.9 |
- 0.902 |
- 0.917 |
- 0.905 |
- 0.899 |
- 0.863 |
- 0.901 |
- 0.863 |
- 0.911 |
- 0.893 |
- 0.889 |
- 0.896 |
- 0.895 |
- 0.902 |
- 0.91 |
- 0.903 |
- 0.9 |
- 0.912 |
- 0.929 |
- 0.906 |
- 0.897 |
- 0.912 |
- 0.896 |
- 0.901 |
- 0.889 |
- 0.896 |
- 0.896 |
- 0.916 |
- 0.916 |
- 0.9 |
- 0.9 |
- 0.906 |
- 0.911 |
- 0.888 |
- 0.915 |
- 0.89 |
- 0.918 |
- 0.899 |
- 0.916 |
- 0.904 |
- 0.919 |
- 0.894 |
- 0.892 |
- 0.896 |
- 0.9 |
- 0.915 |
- 0.926 |
- 0.88 |
- 0.889 |
- 0.905 |
- 0.895 |
- 0.917 |
- 0.889 |
- 0.92 |
- 0.894 |
- 0.902 |
- 0.906 |
- 0.937 |
- 0.899 |
- 0.926 |
- 0.898 |
- 0.9 |
- 0.903 |
- 0.891 |
- 0.903 |
- 0.904 |
- 0.895 |
- 0.915 |
- 0.911 |
- 0.883 |
- 0.896 |
- 0.927 |
- 0.918 |
- 0.892 |
- 0.902 |
- 0.907 |
- 0.897 |
- 0.952 |
- 0.899 |
- 0.915 |
- 0.906 |
- 0.901 |
- 0.888 |
- 0.863 |
- 0.888 |
- 0.883 |
- |
- 0.863 |
- 0.90 |
-
-
- | Liver |
- 188 |
- F |
- 304 |
- 102414.03 |
- CD |
- BXD90 |
- H1702 |
- 0.987 |
- 0.919 |
- 0.921 |
- 0.984 |
- 0.976 |
- 0.982 |
- 0.98 |
- 0.953 |
- 0.882 |
- 0.984 |
- 0.972 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.969 |
- 0.981 |
- 0.968 |
- 0.956 |
- 0.98 |
- 0.983 |
- 0.972 |
- 0.986 |
- 0.985 |
- 0.986 |
- 0.977 |
- 0.969 |
- 0.97 |
- 0.968 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.978 |
- 0.949 |
- 0.973 |
- 0.979 |
- 0.971 |
- 0.92 |
- 0.981 |
- 0.972 |
- 0.975 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.985 |
- 0.978 |
- 0.939 |
- 0.974 |
- 0.976 |
- 0.982 |
- 0.97 |
- 0.985 |
- 0.954 |
- 0.973 |
- 0.975 |
- 0.983 |
- 0.982 |
- 0.972 |
- 0.978 |
- 0.986 |
- 0.976 |
- 0.976 |
- 0.97 |
- 0.979 |
- 0.9 |
- 1 |
- 0.99 |
- 0.971 |
- 0.984 |
- 0.966 |
- 0.932 |
- 0.973 |
- 0.935 |
- 0.984 |
- 0.98 |
- 0.977 |
- 0.976 |
- 0.967 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.974 |
- 0.979 |
- 0.969 |
- 0.981 |
- 0.977 |
- 0.96 |
- 0.985 |
- 0.985 |
- 0.968 |
- 0.976 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.97 |
- 0.97 |
- 0.984 |
- 0.977 |
- 0.962 |
- 0.974 |
- 0.967 |
- 0.982 |
- 0.976 |
- 0.962 |
- 0.972 |
- 0.977 |
- 0.983 |
- 0.977 |
- 0.984 |
- 0.983 |
- 0.974 |
- 0.952 |
- 0.964 |
- 0.973 |
- 0.958 |
- 0.978 |
- 0.971 |
- 0.981 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.976 |
- 0.969 |
- 0.972 |
- 0.958 |
- 0.977 |
- 0.983 |
- 0.982 |
- 0.962 |
- 0.976 |
- 0.98 |
- 0.98 |
- 0.974 |
- 0.977 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.979 |
- 0.982 |
- 0.984 |
- 0.981 |
- 0.982 |
- 0.93 |
- 0.979 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.976 |
- 0.935 |
- 0.967 |
- 0.929 |
- |
- 0.882 |
- 0.97 |
-
-
- | Liver |
- 549 |
- F |
- 311 |
- 062013.02 |
- CD |
- BXD90 |
- H0756 |
- 0.985 |
- 0.92 |
- 0.923 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.951 |
- 0.884 |
- 0.98 |
- 0.968 |
- 0.977 |
- 0.984 |
- 0.984 |
- 0.969 |
- 0.974 |
- 0.969 |
- 0.95 |
- 0.979 |
- 0.979 |
- 0.966 |
- 0.98 |
- 0.986 |
- 0.983 |
- 0.973 |
- 0.966 |
- 0.967 |
- 0.962 |
- 0.982 |
- 0.98 |
- 0.984 |
- 0.974 |
- 0.95 |
- 0.975 |
- 0.978 |
- 0.97 |
- 0.924 |
- 0.979 |
- 0.973 |
- 0.975 |
- 0.978 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.973 |
- 0.939 |
- 0.977 |
- 0.976 |
- 0.98 |
- 0.973 |
- 0.981 |
- 0.956 |
- 0.971 |
- 0.979 |
- 0.985 |
- 0.98 |
- 0.969 |
- 0.972 |
- 0.983 |
- 0.975 |
- 0.98 |
- 0.969 |
- 0.974 |
- 0.902 |
- 0.99 |
- 1 |
- 0.971 |
- 0.981 |
- 0.963 |
- 0.93 |
- 0.973 |
- 0.935 |
- 0.982 |
- 0.981 |
- 0.978 |
- 0.975 |
- 0.969 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.974 |
- 0.978 |
- 0.969 |
- 0.978 |
- 0.972 |
- 0.962 |
- 0.981 |
- 0.985 |
- 0.968 |
- 0.97 |
- 0.978 |
- 0.98 |
- 0.978 |
- 0.971 |
- 0.97 |
- 0.983 |
- 0.975 |
- 0.96 |
- 0.978 |
- 0.966 |
- 0.979 |
- 0.972 |
- 0.964 |
- 0.973 |
- 0.977 |
- 0.984 |
- 0.977 |
- 0.979 |
- 0.983 |
- 0.975 |
- 0.954 |
- 0.967 |
- 0.972 |
- 0.961 |
- 0.98 |
- 0.971 |
- 0.98 |
- 0.978 |
- 0.974 |
- 0.98 |
- 0.976 |
- 0.971 |
- 0.971 |
- 0.963 |
- 0.978 |
- 0.98 |
- 0.979 |
- 0.963 |
- 0.976 |
- 0.979 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.979 |
- 0.981 |
- 0.975 |
- 0.979 |
- 0.985 |
- 0.986 |
- 0.983 |
- 0.98 |
- 0.929 |
- 0.981 |
- 0.978 |
- 0.977 |
- 0.979 |
- 0.976 |
- 0.935 |
- 0.963 |
- 0.929 |
- |
- 0.884 |
- 0.97 |
-
-
- | Liver |
- 562 |
- F |
- 21 |
- 062013.17 |
- CD |
- BXD91 |
- H0883 |
- 0.972 |
- 0.955 |
- 0.956 |
- 0.975 |
- 0.972 |
- 0.977 |
- 0.97 |
- 0.968 |
- 0.925 |
- 0.975 |
- 0.97 |
- 0.976 |
- 0.974 |
- 0.973 |
- 0.975 |
- 0.969 |
- 0.977 |
- 0.973 |
- 0.982 |
- 0.975 |
- 0.964 |
- 0.972 |
- 0.974 |
- 0.976 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.977 |
- 0.98 |
- 0.97 |
- 0.973 |
- 0.97 |
- 0.958 |
- 0.971 |
- 0.974 |
- 0.983 |
- 0.952 |
- 0.972 |
- 0.975 |
- 0.973 |
- 0.981 |
- 0.977 |
- 0.974 |
- 0.978 |
- 0.978 |
- 0.959 |
- 0.964 |
- 0.973 |
- 0.971 |
- 0.971 |
- 0.976 |
- 0.968 |
- 0.982 |
- 0.972 |
- 0.974 |
- 0.97 |
- 0.98 |
- 0.965 |
- 0.978 |
- 0.974 |
- 0.965 |
- 0.967 |
- 0.979 |
- 0.917 |
- 0.971 |
- 0.971 |
- 1 |
- 0.976 |
- 0.975 |
- 0.959 |
- 0.978 |
- 0.957 |
- 0.977 |
- 0.97 |
- 0.972 |
- 0.974 |
- 0.976 |
- 0.973 |
- 0.983 |
- 0.982 |
- 0.97 |
- 0.976 |
- 0.969 |
- 0.975 |
- 0.98 |
- 0.985 |
- 0.976 |
- 0.976 |
- 0.977 |
- 0.969 |
- 0.973 |
- 0.983 |
- 0.984 |
- 0.976 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.976 |
- 0.987 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.984 |
- 0.975 |
- 0.976 |
- 0.97 |
- 0.973 |
- 0.976 |
- 0.972 |
- 0.981 |
- 0.952 |
- 0.968 |
- 0.973 |
- 0.971 |
- 0.976 |
- 1 |
- 0.975 |
- 0.983 |
- 0.975 |
- 0.978 |
- 0.974 |
- 0.971 |
- 0.971 |
- 0.98 |
- 0.979 |
- 0.976 |
- 0.972 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.966 |
- 0.97 |
- 0.975 |
- 0.974 |
- 0.973 |
- 0.987 |
- 0.974 |
- 0.974 |
- 0.941 |
- 0.973 |
- 0.975 |
- 0.978 |
- 0.974 |
- 0.968 |
- 0.957 |
- 0.979 |
- 0.963 |
- |
- 0.917 |
- 0.97 |
-
-
- | Liver |
- 536 |
- F |
- 277 |
- 101014.10 |
- CD |
- BXD95 |
- H1742 |
- 0.988 |
- 0.928 |
- 0.93 |
- 0.987 |
- 0.978 |
- 0.983 |
- 0.983 |
- 0.965 |
- 0.893 |
- 0.982 |
- 0.972 |
- 0.984 |
- 0.983 |
- 0.987 |
- 0.972 |
- 0.98 |
- 0.971 |
- 0.963 |
- 0.983 |
- 0.985 |
- 0.977 |
- 0.988 |
- 0.986 |
- 0.989 |
- 0.983 |
- 0.971 |
- 0.972 |
- 0.974 |
- 0.987 |
- 0.986 |
- 0.984 |
- 0.985 |
- 0.951 |
- 0.975 |
- 0.985 |
- 0.976 |
- 0.935 |
- 0.983 |
- 0.979 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.98 |
- 0.984 |
- 0.982 |
- 0.946 |
- 0.974 |
- 0.982 |
- 0.982 |
- 0.976 |
- 0.988 |
- 0.962 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.986 |
- 0.979 |
- 0.977 |
- 0.986 |
- 0.979 |
- 0.975 |
- 0.964 |
- 0.983 |
- 0.905 |
- 0.984 |
- 0.981 |
- 0.976 |
- 1 |
- 0.971 |
- 0.942 |
- 0.983 |
- 0.94 |
- 0.986 |
- 0.983 |
- 0.982 |
- 0.979 |
- 0.972 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.98 |
- 0.983 |
- 0.972 |
- 0.98 |
- 0.983 |
- 0.968 |
- 0.986 |
- 0.988 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.978 |
- 0.977 |
- 0.986 |
- 0.982 |
- 0.972 |
- 0.977 |
- 0.976 |
- 0.983 |
- 0.98 |
- 0.971 |
- 0.976 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.986 |
- 0.985 |
- 0.982 |
- 0.956 |
- 0.969 |
- 0.98 |
- 0.966 |
- 0.979 |
- 0.976 |
- 0.979 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.982 |
- 0.973 |
- 0.98 |
- 0.966 |
- 0.983 |
- 0.988 |
- 0.985 |
- 0.97 |
- 0.979 |
- 0.985 |
- 0.985 |
- 0.982 |
- 0.982 |
- 0.977 |
- 0.98 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.986 |
- 0.937 |
- 0.983 |
- 0.979 |
- 0.986 |
- 0.984 |
- 0.981 |
- 0.94 |
- 0.97 |
- 0.941 |
- |
- 0.893 |
- 0.98 |
-
-
- | Liver |
- 384 |
- F |
- 146 |
- 012615.17 |
- CD |
- BXD98 |
- H1769 |
- 0.966 |
- 0.946 |
- 0.945 |
- 0.965 |
- 0.967 |
- 0.969 |
- 0.964 |
- 0.973 |
- 0.929 |
- 0.973 |
- 0.956 |
- 0.975 |
- 0.966 |
- 0.97 |
- 0.976 |
- 0.967 |
- 0.978 |
- 0.969 |
- 0.966 |
- 0.967 |
- 0.955 |
- 0.968 |
- 0.967 |
- 0.973 |
- 0.984 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.972 |
- 0.967 |
- 0.964 |
- 0.967 |
- 0.937 |
- 0.968 |
- 0.972 |
- 0.98 |
- 0.971 |
- 0.966 |
- 0.973 |
- 0.966 |
- 0.971 |
- 0.962 |
- 0.966 |
- 0.966 |
- 0.974 |
- 0.966 |
- 0.958 |
- 0.966 |
- 0.963 |
- 0.968 |
- 0.97 |
- 0.978 |
- 0.984 |
- 0.966 |
- 0.966 |
- 0.967 |
- 0.983 |
- 0.957 |
- 0.973 |
- 0.973 |
- 0.958 |
- 0.946 |
- 0.974 |
- 0.899 |
- 0.966 |
- 0.963 |
- 0.975 |
- 0.971 |
- 1 |
- 0.98 |
- 0.98 |
- 0.974 |
- 0.965 |
- 0.964 |
- 0.968 |
- 0.973 |
- 0.978 |
- 0.962 |
- 0.971 |
- 0.969 |
- 0.965 |
- 0.96 |
- 0.958 |
- 0.96 |
- 0.975 |
- 0.97 |
- 0.973 |
- 0.967 |
- 0.978 |
- 0.966 |
- 0.96 |
- 0.968 |
- 0.971 |
- 0.97 |
- 0.969 |
- 0.973 |
- 0.963 |
- 0.983 |
- 0.975 |
- 0.982 |
- 0.965 |
- 0.97 |
- 0.978 |
- 0.971 |
- 0.96 |
- 0.961 |
- 0.964 |
- 0.962 |
- 0.958 |
- 0.975 |
- 0.934 |
- 0.969 |
- 0.968 |
- 0.964 |
- 0.97 |
- 0.975 |
- 0.962 |
- 0.959 |
- 0.965 |
- 0.965 |
- 0.968 |
- 0.961 |
- 0.968 |
- 0.968 |
- 0.972 |
- 0.97 |
- 0.965 |
- 0.979 |
- 0.964 |
- 0.974 |
- 0.963 |
- 0.975 |
- 0.963 |
- 0.966 |
- 0.962 |
- 0.962 |
- 0.955 |
- 0.966 |
- 0.976 |
- 0.958 |
- 0.97 |
- 0.925 |
- 0.958 |
- 0.955 |
- 0.969 |
- 0.964 |
- 0.963 |
- 0.974 |
- 0.969 |
- 0.971 |
- |
- 0.899 |
- 0.97 |
-
-
- | Liver |
- 384 |
- F |
- 182 |
- 012615.16 |
- CD |
- BXD98 |
- H1524 |
- 0.939 |
- 0.931 |
- 0.93 |
- 0.939 |
- 0.942 |
- 0.938 |
- 0.944 |
- 0.966 |
- 0.918 |
- 0.948 |
- 0.927 |
- 0.951 |
- 0.935 |
- 0.94 |
- 0.953 |
- 0.934 |
- 0.959 |
- 0.958 |
- 0.939 |
- 0.939 |
- 0.928 |
- 0.941 |
- 0.943 |
- 0.946 |
- 0.966 |
- 0.973 |
- 0.973 |
- 0.97 |
- 0.949 |
- 0.94 |
- 0.939 |
- 0.942 |
- 0.901 |
- 0.954 |
- 0.953 |
- 0.962 |
- 0.977 |
- 0.947 |
- 0.959 |
- 0.947 |
- 0.946 |
- 0.937 |
- 0.945 |
- 0.943 |
- 0.957 |
- 0.958 |
- 0.934 |
- 0.942 |
- 0.94 |
- 0.954 |
- 0.942 |
- 0.978 |
- 0.971 |
- 0.938 |
- 0.939 |
- 0.94 |
- 0.97 |
- 0.931 |
- 0.944 |
- 0.957 |
- 0.925 |
- 0.911 |
- 0.955 |
- 0.863 |
- 0.932 |
- 0.93 |
- 0.959 |
- 0.942 |
- 0.98 |
- 1 |
- 0.966 |
- 0.976 |
- 0.937 |
- 0.944 |
- 0.948 |
- 0.957 |
- 0.964 |
- 0.938 |
- 0.943 |
- 0.944 |
- 0.947 |
- 0.935 |
- 0.925 |
- 0.934 |
- 0.958 |
- 0.952 |
- 0.953 |
- 0.939 |
- 0.96 |
- 0.945 |
- 0.932 |
- 0.941 |
- 0.946 |
- 0.952 |
- 0.952 |
- 0.947 |
- 0.94 |
- 0.975 |
- 0.955 |
- 0.972 |
- 0.935 |
- 0.955 |
- 0.963 |
- 0.952 |
- 0.931 |
- 0.934 |
- 0.943 |
- 0.938 |
- 0.925 |
- 0.953 |
- 0.898 |
- 0.957 |
- 0.951 |
- 0.946 |
- 0.949 |
- 0.959 |
- 0.941 |
- 0.931 |
- 0.941 |
- 0.942 |
- 0.943 |
- 0.929 |
- 0.945 |
- 0.949 |
- 0.954 |
- 0.943 |
- 0.935 |
- 0.974 |
- 0.939 |
- 0.952 |
- 0.937 |
- 0.953 |
- 0.94 |
- 0.94 |
- 0.938 |
- 0.929 |
- 0.926 |
- 0.943 |
- 0.957 |
- 0.929 |
- 0.946 |
- 0.886 |
- 0.936 |
- 0.927 |
- 0.944 |
- 0.938 |
- 0.938 |
- 0.976 |
- 0.954 |
- 0.972 |
- |
- 0.863 |
- 0.95 |
-
-
- | Liver |
- 535 |
- F |
- 278 |
- 111414.14 |
- CD |
- BXD99 |
- H1354 |
- 0.982 |
- 0.939 |
- 0.94 |
- 0.98 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.975 |
- 0.909 |
- 0.981 |
- 0.968 |
- 0.985 |
- 0.975 |
- 0.979 |
- 0.98 |
- 0.975 |
- 0.975 |
- 0.97 |
- 0.976 |
- 0.981 |
- 0.969 |
- 0.982 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.984 |
- 0.985 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.978 |
- 0.979 |
- 0.946 |
- 0.979 |
- 0.982 |
- 0.984 |
- 0.96 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.976 |
- 0.983 |
- 0.983 |
- 0.961 |
- 0.977 |
- 0.981 |
- 0.982 |
- 0.986 |
- 0.983 |
- 0.979 |
- 0.987 |
- 0.979 |
- 0.979 |
- 0.982 |
- 0.987 |
- 0.971 |
- 0.981 |
- 0.985 |
- 0.971 |
- 0.96 |
- 0.98 |
- 0.901 |
- 0.973 |
- 0.973 |
- 0.978 |
- 0.983 |
- 0.98 |
- 0.966 |
- 1 |
- 0.958 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.984 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.984 |
- 0.978 |
- 0.967 |
- 0.972 |
- 0.986 |
- 0.969 |
- 0.986 |
- 0.981 |
- 0.977 |
- 0.979 |
- 0.972 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.98 |
- 0.982 |
- 0.98 |
- 0.982 |
- 0.979 |
- 0.984 |
- 0.977 |
- 0.983 |
- 0.98 |
- 0.976 |
- 0.973 |
- 0.976 |
- 0.977 |
- 0.979 |
- 0.97 |
- 0.981 |
- 0.946 |
- 0.976 |
- 0.979 |
- 0.973 |
- 0.981 |
- 0.978 |
- 0.975 |
- 0.974 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.972 |
- 0.978 |
- 0.972 |
- 0.985 |
- 0.983 |
- 0.977 |
- 0.982 |
- 0.974 |
- 0.984 |
- 0.976 |
- 0.981 |
- 0.98 |
- 0.975 |
- 0.976 |
- 0.972 |
- 0.973 |
- 0.977 |
- 0.984 |
- 0.974 |
- 0.981 |
- 0.925 |
- 0.983 |
- 0.971 |
- 0.981 |
- 0.978 |
- 0.976 |
- 0.958 |
- 0.974 |
- 0.959 |
- |
- 0.901 |
- 0.98 |
-
-
- | Liver |
- 361 |
- M |
- 162 |
- 012615.26 |
- CD |
- C57BL/6J |
- H1590 |
- 0.935 |
- 0.931 |
- 0.929 |
- 0.935 |
- 0.942 |
- 0.94 |
- 0.938 |
- 0.964 |
- 0.922 |
- 0.943 |
- 0.922 |
- 0.954 |
- 0.934 |
- 0.938 |
- 0.952 |
- 0.937 |
- 0.958 |
- 0.962 |
- 0.939 |
- 0.935 |
- 0.928 |
- 0.941 |
- 0.945 |
- 0.946 |
- 0.964 |
- 0.967 |
- 0.967 |
- 0.969 |
- 0.943 |
- 0.938 |
- 0.941 |
- 0.94 |
- 0.9 |
- 0.953 |
- 0.954 |
- 0.961 |
- 0.976 |
- 0.944 |
- 0.96 |
- 0.945 |
- 0.946 |
- 0.934 |
- 0.944 |
- 0.939 |
- 0.954 |
- 0.96 |
- 0.927 |
- 0.935 |
- 0.942 |
- 0.95 |
- 0.941 |
- 0.976 |
- 0.967 |
- 0.935 |
- 0.943 |
- 0.938 |
- 0.961 |
- 0.935 |
- 0.945 |
- 0.946 |
- 0.932 |
- 0.911 |
- 0.959 |
- 0.863 |
- 0.935 |
- 0.935 |
- 0.957 |
- 0.94 |
- 0.974 |
- 0.976 |
- 0.958 |
- 1 |
- 0.936 |
- 0.938 |
- 0.952 |
- 0.946 |
- 0.96 |
- 0.935 |
- 0.942 |
- 0.944 |
- 0.94 |
- 0.93 |
- 0.923 |
- 0.931 |
- 0.95 |
- 0.955 |
- 0.945 |
- 0.939 |
- 0.962 |
- 0.942 |
- 0.932 |
- 0.942 |
- 0.947 |
- 0.951 |
- 0.95 |
- 0.948 |
- 0.939 |
- 0.973 |
- 0.958 |
- 0.97 |
- 0.931 |
- 0.95 |
- 0.955 |
- 0.953 |
- 0.93 |
- 0.936 |
- 0.939 |
- 0.936 |
- 0.931 |
- 0.949 |
- 0.903 |
- 0.958 |
- 0.949 |
- 0.945 |
- 0.953 |
- 0.957 |
- 0.946 |
- 0.926 |
- 0.938 |
- 0.938 |
- 0.94 |
- 0.928 |
- 0.941 |
- 0.945 |
- 0.954 |
- 0.945 |
- 0.937 |
- 0.97 |
- 0.942 |
- 0.954 |
- 0.936 |
- 0.949 |
- 0.939 |
- 0.945 |
- 0.941 |
- 0.927 |
- 0.927 |
- 0.948 |
- 0.959 |
- 0.933 |
- 0.951 |
- 0.89 |
- 0.932 |
- 0.93 |
- 0.944 |
- 0.941 |
- 0.943 |
- 1 |
- 0.957 |
- 0.968 |
- |
- 0.863 |
- 0.94 |
-
-
- | Liver |
- 537 |
- F |
- 273 |
- 091914.09 |
- CD |
- C57BL/6J |
- H1103 |
- 0.989 |
- 0.932 |
- 0.933 |
- 0.991 |
- 0.981 |
- 0.989 |
- 0.987 |
- 0.962 |
- 0.894 |
- 0.985 |
- 0.982 |
- 0.983 |
- 0.985 |
- 0.984 |
- 0.975 |
- 0.981 |
- 0.968 |
- 0.959 |
- 0.984 |
- 0.987 |
- 0.982 |
- 0.988 |
- 0.986 |
- 0.986 |
- 0.976 |
- 0.975 |
- 0.975 |
- 0.973 |
- 0.99 |
- 0.986 |
- 0.988 |
- 0.984 |
- 0.959 |
- 0.973 |
- 0.979 |
- 0.977 |
- 0.928 |
- 0.987 |
- 0.978 |
- 0.98 |
- 0.987 |
- 0.986 |
- 0.98 |
- 0.989 |
- 0.981 |
- 0.946 |
- 0.981 |
- 0.983 |
- 0.984 |
- 0.977 |
- 0.988 |
- 0.957 |
- 0.975 |
- 0.98 |
- 0.984 |
- 0.986 |
- 0.976 |
- 0.98 |
- 0.986 |
- 0.978 |
- 0.976 |
- 0.972 |
- 0.98 |
- 0.911 |
- 0.984 |
- 0.982 |
- 0.977 |
- 0.986 |
- 0.965 |
- 0.937 |
- 0.979 |
- 0.936 |
- 1 |
- 0.987 |
- 0.982 |
- 0.978 |
- 0.965 |
- 0.989 |
- 0.989 |
- 0.989 |
- 0.983 |
- 0.987 |
- 0.978 |
- 0.988 |
- 0.984 |
- 0.964 |
- 0.985 |
- 0.988 |
- 0.972 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.984 |
- 0.978 |
- 0.977 |
- 0.986 |
- 0.984 |
- 0.966 |
- 0.979 |
- 0.97 |
- 0.989 |
- 0.984 |
- 0.971 |
- 0.979 |
- 0.987 |
- 0.989 |
- 0.979 |
- 0.987 |
- 0.982 |
- 0.984 |
- 0.959 |
- 0.967 |
- 0.979 |
- 0.972 |
- 0.98 |
- 0.977 |
- 0.981 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.978 |
- 0.981 |
- 0.968 |
- 0.982 |
- 0.986 |
- 0.986 |
- 0.967 |
- 0.98 |
- 0.982 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.976 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.987 |
- 0.983 |
- 0.941 |
- 0.986 |
- 0.989 |
- 0.993 |
- 0.988 |
- 0.983 |
- 0.936 |
- 0.966 |
- 0.935 |
- |
- 0.894 |
- 0.98 |
-
-
- | Liver |
- 210 |
- F |
- 300 |
- 101713.18 |
- CD |
- D2B6F1 |
- H1154 |
- 0.992 |
- 0.916 |
- 0.918 |
- 0.987 |
- 0.985 |
- 0.981 |
- 1 |
- 0.961 |
- 0.877 |
- 0.987 |
- 0.971 |
- 0.982 |
- 0.98 |
- 0.984 |
- 0.969 |
- 0.977 |
- 0.967 |
- 0.958 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.987 |
- 0.99 |
- 0.988 |
- 0.979 |
- 0.972 |
- 0.972 |
- 0.971 |
- 0.985 |
- 0.986 |
- 0.987 |
- 0.986 |
- 0.94 |
- 0.979 |
- 0.98 |
- 0.972 |
- 0.932 |
- 0.988 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.988 |
- 0.981 |
- 0.945 |
- 0.989 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.984 |
- 0.961 |
- 0.972 |
- 0.979 |
- 0.985 |
- 0.986 |
- 0.976 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.976 |
- 0.962 |
- 0.981 |
- 0.893 |
- 0.98 |
- 0.981 |
- 0.97 |
- 0.983 |
- 0.964 |
- 0.944 |
- 0.981 |
- 0.938 |
- 0.987 |
- 1 |
- 0.985 |
- 0.984 |
- 0.968 |
- 0.993 |
- 0.986 |
- 0.987 |
- 0.988 |
- 0.986 |
- 0.973 |
- 0.981 |
- 0.985 |
- 0.957 |
- 0.988 |
- 0.988 |
- 0.97 |
- 0.984 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.974 |
- 0.986 |
- 0.977 |
- 0.969 |
- 0.979 |
- 0.972 |
- 0.98 |
- 0.982 |
- 0.97 |
- 0.98 |
- 0.981 |
- 0.988 |
- 0.976 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.951 |
- 0.974 |
- 0.979 |
- 0.969 |
- 0.988 |
- 0.97 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.988 |
- 0.988 |
- 0.973 |
- 0.985 |
- 0.966 |
- 0.985 |
- 0.985 |
- 0.982 |
- 0.968 |
- 0.976 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.977 |
- 0.977 |
- 0.987 |
- 0.975 |
- 0.981 |
- 0.988 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.921 |
- 0.988 |
- 0.981 |
- 0.987 |
- 0.989 |
- 0.986 |
- 0.938 |
- 0.966 |
- 0.94 |
- |
- 0.877 |
- 0.98 |
-
-
- | Liver |
- 545 |
- F |
- 298 |
- 062013.12 |
- CD |
- D2B6F1 |
- H0646 |
- 0.983 |
- 0.921 |
- 0.921 |
- 0.982 |
- 0.976 |
- 0.982 |
- 0.985 |
- 0.974 |
- 0.89 |
- 0.976 |
- 0.961 |
- 0.985 |
- 0.976 |
- 0.979 |
- 0.972 |
- 0.978 |
- 0.972 |
- 0.969 |
- 0.977 |
- 0.979 |
- 0.981 |
- 0.983 |
- 0.988 |
- 0.984 |
- 0.983 |
- 0.974 |
- 0.974 |
- 0.978 |
- 0.981 |
- 0.983 |
- 0.989 |
- 0.984 |
- 0.933 |
- 0.978 |
- 0.986 |
- 0.975 |
- 0.942 |
- 0.985 |
- 0.985 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.976 |
- 0.983 |
- 0.987 |
- 0.957 |
- 0.971 |
- 0.976 |
- 0.982 |
- 0.978 |
- 0.986 |
- 0.972 |
- 0.977 |
- 0.971 |
- 0.985 |
- 0.983 |
- 0.975 |
- 0.983 |
- 0.983 |
- 0.978 |
- 0.971 |
- 0.95 |
- 0.984 |
- 0.889 |
- 0.977 |
- 0.978 |
- 0.972 |
- 0.982 |
- 0.968 |
- 0.948 |
- 0.98 |
- 0.952 |
- 0.982 |
- 0.985 |
- 1 |
- 0.978 |
- 0.973 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.979 |
- 0.976 |
- 0.961 |
- 0.976 |
- 0.98 |
- 0.966 |
- 0.98 |
- 0.986 |
- 0.981 |
- 0.98 |
- 0.976 |
- 0.978 |
- 0.98 |
- 0.979 |
- 0.978 |
- 0.983 |
- 0.973 |
- 0.976 |
- 0.978 |
- 0.978 |
- 0.974 |
- 0.98 |
- 0.964 |
- 0.979 |
- 0.979 |
- 0.988 |
- 0.973 |
- 0.978 |
- 0.974 |
- 0.977 |
- 0.942 |
- 0.977 |
- 0.982 |
- 0.975 |
- 0.982 |
- 0.972 |
- 0.982 |
- 0.97 |
- 0.981 |
- 0.978 |
- 0.978 |
- 0.966 |
- 0.979 |
- 0.963 |
- 0.985 |
- 0.988 |
- 0.983 |
- 0.973 |
- 0.98 |
- 0.985 |
- 0.984 |
- 0.977 |
- 0.973 |
- 0.979 |
- 0.978 |
- 0.971 |
- 0.972 |
- 0.984 |
- 0.983 |
- 0.98 |
- 0.985 |
- 0.922 |
- 0.979 |
- 0.974 |
- 0.983 |
- 0.987 |
- 0.994 |
- 0.952 |
- 0.968 |
- 0.953 |
- |
- 0.889 |
- 0.97 |
-
-
- | Liver |
- 212 |
- F |
- 67 |
- 101713.10 |
- CD |
- DBA/2J |
- H1147 |
- 0.985 |
- 0.931 |
- 0.932 |
- 0.983 |
- 0.976 |
- 0.978 |
- 0.984 |
- 0.975 |
- 0.898 |
- 0.982 |
- 0.969 |
- 0.982 |
- 0.971 |
- 0.978 |
- 0.969 |
- 0.977 |
- 0.983 |
- 0.966 |
- 0.979 |
- 0.98 |
- 0.969 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.979 |
- 0.941 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.951 |
- 0.987 |
- 0.986 |
- 0.984 |
- 0.982 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.953 |
- 0.978 |
- 0.981 |
- 0.984 |
- 0.98 |
- 0.981 |
- 0.973 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.983 |
- 0.974 |
- 0.986 |
- 1 |
- 0.967 |
- 0.959 |
- 0.98 |
- 0.896 |
- 0.976 |
- 0.975 |
- 0.974 |
- 0.979 |
- 0.973 |
- 0.957 |
- 0.985 |
- 0.946 |
- 0.978 |
- 0.984 |
- 0.978 |
- 1 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.977 |
- 0.965 |
- 0.975 |
- 0.983 |
- 0.965 |
- 0.984 |
- 0.981 |
- 0.977 |
- 0.982 |
- 0.978 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.976 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.972 |
- 0.979 |
- 0.983 |
- 0.98 |
- 0.972 |
- 0.983 |
- 0.94 |
- 0.984 |
- 0.984 |
- 0.972 |
- 0.977 |
- 0.974 |
- 0.98 |
- 0.973 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.97 |
- 0.979 |
- 0.967 |
- 0.984 |
- 0.982 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.984 |
- 0.98 |
- 0.983 |
- 0.979 |
- 0.98 |
- 0.976 |
- 0.971 |
- 0.975 |
- 0.979 |
- 0.983 |
- 0.976 |
- 0.982 |
- 0.918 |
- 0.983 |
- 0.97 |
- 0.978 |
- 0.979 |
- 0.977 |
- 0.946 |
- 0.973 |
- 0.949 |
- |
- 0.896 |
- 0.98 |
-
-
- | Liver |
- 764 |
- F |
- 121 |
- 083016.07 |
- CD |
- DBA/2J |
- H1818 |
- 0.971 |
- 0.942 |
- 0.942 |
- 0.971 |
- 0.969 |
- 0.971 |
- 0.968 |
- 0.98 |
- 0.92 |
- 0.97 |
- 0.961 |
- 0.977 |
- 0.965 |
- 0.969 |
- 0.969 |
- 0.967 |
- 0.989 |
- 0.969 |
- 0.974 |
- 0.975 |
- 0.957 |
- 0.972 |
- 0.972 |
- 0.975 |
- 0.981 |
- 0.983 |
- 0.984 |
- 0.98 |
- 0.977 |
- 0.971 |
- 0.97 |
- 0.968 |
- 0.939 |
- 0.982 |
- 0.982 |
- 0.984 |
- 0.967 |
- 0.976 |
- 0.984 |
- 0.977 |
- 0.971 |
- 0.974 |
- 0.977 |
- 0.974 |
- 0.979 |
- 0.961 |
- 0.963 |
- 0.972 |
- 0.972 |
- 0.975 |
- 0.975 |
- 0.981 |
- 0.988 |
- 0.975 |
- 0.975 |
- 0.971 |
- 0.983 |
- 0.962 |
- 0.979 |
- 0.985 |
- 0.961 |
- 0.951 |
- 0.976 |
- 0.895 |
- 0.967 |
- 0.969 |
- 0.976 |
- 0.972 |
- 0.978 |
- 0.964 |
- 0.984 |
- 0.96 |
- 0.965 |
- 0.968 |
- 0.973 |
- 0.985 |
- 1 |
- 0.969 |
- 0.974 |
- 0.974 |
- 0.969 |
- 0.964 |
- 0.954 |
- 0.962 |
- 0.975 |
- 0.973 |
- 0.975 |
- 0.972 |
- 0.98 |
- 0.968 |
- 0.972 |
- 0.976 |
- 0.978 |
- 0.982 |
- 0.982 |
- 0.973 |
- 0.975 |
- 0.98 |
- 0.975 |
- 0.98 |
- 0.968 |
- 0.972 |
- 0.977 |
- 0.971 |
- 0.964 |
- 0.967 |
- 0.978 |
- 0.968 |
- 0.963 |
- 0.976 |
- 0.931 |
- 0.982 |
- 0.978 |
- 0.97 |
- 0.971 |
- 0.976 |
- 0.969 |
- 0.961 |
- 0.969 |
- 0.969 |
- 0.967 |
- 0.963 |
- 0.965 |
- 0.963 |
- 0.98 |
- 0.976 |
- 0.969 |
- 0.987 |
- 0.975 |
- 0.982 |
- 0.973 |
- 0.976 |
- 0.975 |
- 0.973 |
- 0.965 |
- 0.964 |
- 0.963 |
- 0.969 |
- 0.984 |
- 0.965 |
- 0.974 |
- 0.916 |
- 0.97 |
- 0.959 |
- 0.966 |
- 0.967 |
- 0.968 |
- 0.96 |
- 0.974 |
- 0.963 |
- |
- 0.895 |
- 0.97 |
-
-
- | Liver |
- 216 |
- F |
- 306 |
- 101713.15 |
- HF |
- B6D2F1 |
- H1302 |
- 0.994 |
- 0.923 |
- 0.926 |
- 0.989 |
- 0.987 |
- 0.984 |
- 0.993 |
- 0.956 |
- 0.881 |
- 0.987 |
- 0.977 |
- 0.984 |
- 0.983 |
- 0.986 |
- 0.971 |
- 0.981 |
- 0.968 |
- 0.956 |
- 0.983 |
- 0.983 |
- 0.978 |
- 0.989 |
- 0.99 |
- 0.989 |
- 0.977 |
- 0.972 |
- 0.973 |
- 0.97 |
- 0.988 |
- 0.988 |
- 0.988 |
- 0.984 |
- 0.951 |
- 0.977 |
- 0.98 |
- 0.974 |
- 0.929 |
- 0.989 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.986 |
- 0.983 |
- 0.99 |
- 0.979 |
- 0.942 |
- 0.989 |
- 0.983 |
- 0.988 |
- 0.983 |
- 0.985 |
- 0.959 |
- 0.974 |
- 0.983 |
- 0.989 |
- 0.988 |
- 0.975 |
- 0.978 |
- 0.986 |
- 0.983 |
- 0.982 |
- 0.972 |
- 0.98 |
- 0.902 |
- 0.984 |
- 0.985 |
- 0.973 |
- 0.984 |
- 0.962 |
- 0.938 |
- 0.98 |
- 0.935 |
- 0.989 |
- 0.993 |
- 0.982 |
- 0.983 |
- 0.969 |
- 1 |
- 0.989 |
- 0.991 |
- 0.987 |
- 0.989 |
- 0.978 |
- 0.984 |
- 0.985 |
- 0.96 |
- 0.988 |
- 0.989 |
- 0.968 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.977 |
- 0.987 |
- 0.984 |
- 0.967 |
- 0.982 |
- 0.973 |
- 0.986 |
- 0.984 |
- 0.97 |
- 0.981 |
- 0.984 |
- 0.988 |
- 0.979 |
- 0.988 |
- 0.985 |
- 0.984 |
- 0.957 |
- 0.972 |
- 0.98 |
- 0.968 |
- 0.988 |
- 0.973 |
- 0.988 |
- 0.986 |
- 0.984 |
- 0.989 |
- 0.986 |
- 0.978 |
- 0.984 |
- 0.969 |
- 0.985 |
- 0.987 |
- 0.986 |
- 0.968 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.988 |
- 0.98 |
- 0.988 |
- 0.988 |
- 0.985 |
- 0.99 |
- 0.987 |
- 0.929 |
- 0.991 |
- 0.986 |
- 0.988 |
- 0.991 |
- 0.984 |
- 0.935 |
- 0.969 |
- 0.934 |
- |
- 0.881 |
- 0.98 |
-
-
- | Liver |
- 547 |
- F |
- 279 |
- 102616.04 |
- HF |
- B6D2F1 |
- H2288 |
- 0.989 |
- 0.938 |
- 0.94 |
- 0.989 |
- 0.981 |
- 0.988 |
- 0.986 |
- 0.966 |
- 0.901 |
- 0.984 |
- 0.982 |
- 0.987 |
- 0.986 |
- 0.987 |
- 0.974 |
- 0.985 |
- 0.976 |
- 0.969 |
- 0.989 |
- 0.986 |
- 0.983 |
- 0.988 |
- 0.987 |
- 0.989 |
- 0.982 |
- 0.976 |
- 0.976 |
- 0.977 |
- 0.989 |
- 0.987 |
- 0.987 |
- 0.986 |
- 0.959 |
- 0.975 |
- 0.984 |
- 0.982 |
- 0.936 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.988 |
- 0.984 |
- 0.981 |
- 0.988 |
- 0.984 |
- 0.949 |
- 0.977 |
- 0.982 |
- 0.984 |
- 0.978 |
- 0.99 |
- 0.962 |
- 0.981 |
- 0.98 |
- 0.988 |
- 0.987 |
- 0.98 |
- 0.979 |
- 0.99 |
- 0.982 |
- 0.977 |
- 0.97 |
- 0.987 |
- 0.91 |
- 0.984 |
- 0.981 |
- 0.983 |
- 0.988 |
- 0.971 |
- 0.943 |
- 0.981 |
- 0.942 |
- 0.989 |
- 0.986 |
- 0.984 |
- 0.982 |
- 0.974 |
- 0.989 |
- 1 |
- 0.996 |
- 0.982 |
- 0.987 |
- 0.98 |
- 0.986 |
- 0.987 |
- 0.973 |
- 0.987 |
- 0.991 |
- 0.979 |
- 0.984 |
- 0.985 |
- 0.989 |
- 0.989 |
- 0.983 |
- 0.982 |
- 0.991 |
- 0.987 |
- 0.974 |
- 0.984 |
- 0.978 |
- 0.99 |
- 0.985 |
- 0.977 |
- 0.982 |
- 0.987 |
- 0.987 |
- 0.982 |
- 0.99 |
- 0.988 |
- 0.988 |
- 0.959 |
- 0.972 |
- 0.983 |
- 0.974 |
- 0.983 |
- 0.983 |
- 0.985 |
- 0.985 |
- 0.988 |
- 0.986 |
- 0.985 |
- 0.979 |
- 0.984 |
- 0.973 |
- 0.988 |
- 0.992 |
- 0.988 |
- 0.973 |
- 0.984 |
- 0.989 |
- 0.988 |
- 0.988 |
- 0.987 |
- 0.979 |
- 0.982 |
- 0.985 |
- 0.987 |
- 0.983 |
- 0.987 |
- 0.989 |
- 0.987 |
- 0.942 |
- 0.985 |
- 0.988 |
- 0.991 |
- 0.99 |
- 0.984 |
- 0.942 |
- 0.976 |
- 0.948 |
- |
- 0.901 |
- 0.98 |
-
-
- | Liver |
- 547 |
- F |
- 296 |
- 102616.05 |
- HF |
- B6D2F1 |
- H2290 |
- 0.99 |
- 0.932 |
- 0.934 |
- 0.988 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.966 |
- 0.895 |
- 0.985 |
- 0.979 |
- 0.987 |
- 0.984 |
- 0.986 |
- 0.973 |
- 0.984 |
- 0.975 |
- 0.969 |
- 0.989 |
- 0.985 |
- 0.981 |
- 0.988 |
- 0.988 |
- 0.989 |
- 0.982 |
- 0.975 |
- 0.976 |
- 0.976 |
- 0.988 |
- 0.987 |
- 0.989 |
- 0.985 |
- 0.955 |
- 0.977 |
- 0.986 |
- 0.98 |
- 0.934 |
- 0.987 |
- 0.983 |
- 0.986 |
- 0.987 |
- 0.985 |
- 0.984 |
- 0.989 |
- 0.984 |
- 0.947 |
- 0.978 |
- 0.982 |
- 0.986 |
- 0.979 |
- 0.989 |
- 0.963 |
- 0.979 |
- 0.978 |
- 0.989 |
- 0.987 |
- 0.978 |
- 0.981 |
- 0.99 |
- 0.983 |
- 0.978 |
- 0.968 |
- 0.986 |
- 0.903 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.987 |
- 0.969 |
- 0.944 |
- 0.981 |
- 0.944 |
- 0.989 |
- 0.987 |
- 0.986 |
- 0.983 |
- 0.974 |
- 0.991 |
- 0.996 |
- 1 |
- 0.983 |
- 0.988 |
- 0.978 |
- 0.988 |
- 0.986 |
- 0.973 |
- 0.986 |
- 0.991 |
- 0.98 |
- 0.985 |
- 0.987 |
- 0.989 |
- 0.989 |
- 0.983 |
- 0.982 |
- 0.99 |
- 0.987 |
- 0.975 |
- 0.985 |
- 0.979 |
- 0.988 |
- 0.985 |
- 0.974 |
- 0.982 |
- 0.985 |
- 0.989 |
- 0.983 |
- 0.99 |
- 0.989 |
- 0.987 |
- 0.956 |
- 0.975 |
- 0.985 |
- 0.973 |
- 0.985 |
- 0.982 |
- 0.989 |
- 0.985 |
- 0.988 |
- 0.988 |
- 0.984 |
- 0.976 |
- 0.984 |
- 0.971 |
- 0.989 |
- 0.992 |
- 0.988 |
- 0.973 |
- 0.985 |
- 0.989 |
- 0.989 |
- 0.987 |
- 0.987 |
- 0.983 |
- 0.982 |
- 0.982 |
- 0.987 |
- 0.987 |
- 0.988 |
- 0.99 |
- 0.988 |
- 0.935 |
- 0.988 |
- 0.989 |
- 0.989 |
- 0.992 |
- 0.987 |
- 0.944 |
- 0.978 |
- 0.946 |
- |
- 0.895 |
- 0.98 |
-
-
- | Liver |
- 176 |
- F |
- 254 |
- 042415.12 |
- HF |
- BXD100 |
- H2085 |
- 0.986 |
- 0.927 |
- 0.927 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.988 |
- 0.966 |
- 0.89 |
- 0.984 |
- 0.973 |
- 0.981 |
- 0.973 |
- 0.979 |
- 0.974 |
- 0.976 |
- 0.964 |
- 0.959 |
- 0.976 |
- 0.979 |
- 0.979 |
- 0.984 |
- 0.984 |
- 0.985 |
- 0.977 |
- 0.975 |
- 0.975 |
- 0.975 |
- 0.985 |
- 0.986 |
- 0.98 |
- 0.984 |
- 0.945 |
- 0.977 |
- 0.976 |
- 0.973 |
- 0.94 |
- 0.987 |
- 0.977 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.977 |
- 0.987 |
- 0.98 |
- 0.95 |
- 0.983 |
- 0.983 |
- 0.984 |
- 0.985 |
- 0.981 |
- 0.963 |
- 0.975 |
- 0.979 |
- 0.98 |
- 0.986 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.983 |
- 0.974 |
- 0.962 |
- 0.975 |
- 0.9 |
- 0.974 |
- 0.974 |
- 0.97 |
- 0.98 |
- 0.965 |
- 0.947 |
- 0.984 |
- 0.94 |
- 0.983 |
- 0.988 |
- 0.979 |
- 0.983 |
- 0.969 |
- 0.987 |
- 0.982 |
- 0.983 |
- 1 |
- 0.988 |
- 0.974 |
- 0.979 |
- 0.989 |
- 0.958 |
- 0.985 |
- 0.983 |
- 0.968 |
- 0.985 |
- 0.974 |
- 0.976 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.972 |
- 0.976 |
- 0.974 |
- 0.979 |
- 0.986 |
- 0.974 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.983 |
- 0.972 |
- 0.981 |
- 0.95 |
- 0.975 |
- 0.981 |
- 0.972 |
- 0.983 |
- 0.97 |
- 0.979 |
- 0.979 |
- 0.985 |
- 0.985 |
- 0.98 |
- 0.975 |
- 0.982 |
- 0.969 |
- 0.982 |
- 0.982 |
- 0.982 |
- 0.971 |
- 0.974 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.981 |
- 0.975 |
- 0.98 |
- 0.974 |
- 0.979 |
- 0.983 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.926 |
- 0.986 |
- 0.978 |
- 0.986 |
- 0.982 |
- 0.98 |
- 0.94 |
- 0.965 |
- 0.942 |
- |
- 0.89 |
- 0.97 |
-
-
- | Liver |
- 537 |
- F |
- 77 |
- 050914.04 |
- HF |
- BXD100 |
- H1187 |
- 0.988 |
- 0.931 |
- 0.933 |
- 0.989 |
- 0.985 |
- 0.987 |
- 0.986 |
- 0.956 |
- 0.892 |
- 0.985 |
- 0.98 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.972 |
- 0.977 |
- 0.963 |
- 0.958 |
- 0.984 |
- 0.983 |
- 0.977 |
- 0.986 |
- 0.984 |
- 0.986 |
- 0.975 |
- 0.969 |
- 0.97 |
- 0.968 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.958 |
- 0.969 |
- 0.976 |
- 0.972 |
- 0.927 |
- 0.982 |
- 0.973 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.977 |
- 0.985 |
- 0.976 |
- 0.94 |
- 0.981 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.983 |
- 0.953 |
- 0.972 |
- 0.98 |
- 0.982 |
- 0.985 |
- 0.974 |
- 0.975 |
- 0.983 |
- 0.977 |
- 0.98 |
- 0.974 |
- 0.975 |
- 0.912 |
- 0.979 |
- 0.978 |
- 0.976 |
- 0.983 |
- 0.96 |
- 0.935 |
- 0.978 |
- 0.93 |
- 0.987 |
- 0.986 |
- 0.976 |
- 0.977 |
- 0.964 |
- 0.989 |
- 0.987 |
- 0.988 |
- 0.988 |
- 1 |
- 0.984 |
- 0.983 |
- 0.986 |
- 0.964 |
- 0.983 |
- 0.986 |
- 0.966 |
- 0.983 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.978 |
- 0.977 |
- 0.985 |
- 0.985 |
- 0.966 |
- 0.98 |
- 0.971 |
- 0.986 |
- 0.981 |
- 0.975 |
- 0.976 |
- 0.984 |
- 0.982 |
- 0.978 |
- 0.985 |
- 0.982 |
- 0.984 |
- 0.958 |
- 0.964 |
- 0.976 |
- 0.967 |
- 0.982 |
- 0.976 |
- 0.981 |
- 0.989 |
- 0.984 |
- 0.988 |
- 0.982 |
- 0.979 |
- 0.983 |
- 0.972 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.965 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.974 |
- 0.981 |
- 0.983 |
- 0.987 |
- 0.982 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.94 |
- 0.987 |
- 0.986 |
- 0.986 |
- 0.986 |
- 0.978 |
- 0.93 |
- 0.969 |
- 0.935 |
- |
- 0.892 |
- 0.98 |
-
-
- | Liver |
- 493 |
- F |
- 290 |
- 042715.19 |
- HF |
- BXD101 |
- H1422 |
- 0.975 |
- 0.944 |
- 0.947 |
- 0.977 |
- 0.981 |
- 0.983 |
- 0.973 |
- 0.944 |
- 0.917 |
- 0.976 |
- 0.985 |
- 0.969 |
- 0.975 |
- 0.974 |
- 0.972 |
- 0.976 |
- 0.956 |
- 0.95 |
- 0.977 |
- 0.973 |
- 0.969 |
- 0.974 |
- 0.971 |
- 0.974 |
- 0.961 |
- 0.962 |
- 0.963 |
- 0.956 |
- 0.977 |
- 0.976 |
- 0.968 |
- 0.976 |
- 0.97 |
- 0.954 |
- 0.958 |
- 0.971 |
- 0.923 |
- 0.966 |
- 0.957 |
- 0.962 |
- 0.971 |
- 0.971 |
- 0.962 |
- 0.974 |
- 0.964 |
- 0.94 |
- 0.975 |
- 0.975 |
- 0.969 |
- 0.969 |
- 0.972 |
- 0.938 |
- 0.962 |
- 0.977 |
- 0.971 |
- 0.976 |
- 0.964 |
- 0.962 |
- 0.973 |
- 0.965 |
- 0.977 |
- 0.975 |
- 0.962 |
- 0.929 |
- 0.969 |
- 0.969 |
- 0.969 |
- 0.972 |
- 0.958 |
- 0.925 |
- 0.967 |
- 0.923 |
- 0.978 |
- 0.973 |
- 0.961 |
- 0.965 |
- 0.954 |
- 0.978 |
- 0.98 |
- 0.978 |
- 0.974 |
- 0.984 |
- 1 |
- 0.975 |
- 0.974 |
- 0.958 |
- 0.971 |
- 0.974 |
- 0.955 |
- 0.973 |
- 0.971 |
- 0.977 |
- 0.977 |
- 0.964 |
- 0.964 |
- 0.977 |
- 0.975 |
- 0.955 |
- 0.974 |
- 0.96 |
- 0.983 |
- 0.97 |
- 0.973 |
- 0.97 |
- 0.983 |
- 0.968 |
- 0.963 |
- 0.973 |
- 0.972 |
- 0.978 |
- 0.968 |
- 0.947 |
- 0.959 |
- 0.966 |
- 0.973 |
- 0.969 |
- 0.967 |
- 0.984 |
- 0.972 |
- 0.978 |
- 0.976 |
- 0.985 |
- 0.977 |
- 0.972 |
- 0.97 |
- 0.973 |
- 0.975 |
- 0.954 |
- 0.969 |
- 0.971 |
- 0.969 |
- 0.978 |
- 0.975 |
- 0.961 |
- 0.971 |
- 0.985 |
- 0.981 |
- 0.971 |
- 0.971 |
- 0.978 |
- 0.969 |
- 0.96 |
- 0.972 |
- 0.981 |
- 0.977 |
- 0.977 |
- 0.965 |
- 0.923 |
- 0.96 |
- 0.938 |
- |
- 0.917 |
- 0.97 |
-
-
- | Liver |
- 183 |
- F |
- 284 |
- 052814.04 |
- HF |
- BXD102 |
- H1361 |
- 0.982 |
- 0.927 |
- 0.928 |
- 0.985 |
- 0.976 |
- 0.985 |
- 0.981 |
- 0.956 |
- 0.892 |
- 0.988 |
- 0.983 |
- 0.977 |
- 0.981 |
- 0.979 |
- 0.968 |
- 0.978 |
- 0.968 |
- 0.962 |
- 0.982 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.972 |
- 0.97 |
- 0.971 |
- 0.967 |
- 0.984 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.955 |
- 0.969 |
- 0.973 |
- 0.973 |
- 0.921 |
- 0.979 |
- 0.97 |
- 0.975 |
- 0.984 |
- 0.982 |
- 0.977 |
- 0.985 |
- 0.977 |
- 0.939 |
- 0.975 |
- 0.98 |
- 0.977 |
- 0.969 |
- 0.983 |
- 0.949 |
- 0.971 |
- 0.973 |
- 0.979 |
- 0.979 |
- 0.968 |
- 0.977 |
- 0.981 |
- 0.975 |
- 0.971 |
- 0.968 |
- 0.975 |
- 0.906 |
- 0.981 |
- 0.978 |
- 0.975 |
- 0.98 |
- 0.96 |
- 0.934 |
- 0.972 |
- 0.931 |
- 0.988 |
- 0.981 |
- 0.976 |
- 0.975 |
- 0.962 |
- 0.984 |
- 0.986 |
- 0.988 |
- 0.979 |
- 0.983 |
- 0.975 |
- 1 |
- 0.985 |
- 0.965 |
- 0.98 |
- 0.983 |
- 0.97 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.982 |
- 0.973 |
- 0.972 |
- 0.983 |
- 0.98 |
- 0.961 |
- 0.978 |
- 0.965 |
- 0.984 |
- 0.978 |
- 0.969 |
- 0.974 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.984 |
- 0.978 |
- 0.978 |
- 0.954 |
- 0.962 |
- 0.974 |
- 0.966 |
- 0.975 |
- 0.975 |
- 0.978 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.98 |
- 0.974 |
- 0.978 |
- 0.965 |
- 0.976 |
- 0.981 |
- 0.982 |
- 0.963 |
- 0.977 |
- 0.977 |
- 0.979 |
- 0.978 |
- 0.98 |
- 0.971 |
- 0.975 |
- 0.98 |
- 0.982 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.977 |
- 0.938 |
- 0.982 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.976 |
- 0.931 |
- 0.968 |
- 0.936 |
- |
- 0.892 |
- 0.97 |
-
-
- | Liver |
- 366 |
- F |
- 195 |
- 121214.07 |
- HF |
- BXD102 |
- H1498 |
- 0.985 |
- 0.933 |
- 0.933 |
- 0.985 |
- 0.98 |
- 0.984 |
- 0.985 |
- 0.972 |
- 0.898 |
- 0.987 |
- 0.977 |
- 0.985 |
- 0.976 |
- 0.981 |
- 0.974 |
- 0.978 |
- 0.972 |
- 0.974 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.985 |
- 0.983 |
- 0.988 |
- 0.984 |
- 0.982 |
- 0.982 |
- 0.983 |
- 0.986 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.945 |
- 0.977 |
- 0.981 |
- 0.981 |
- 0.946 |
- 0.985 |
- 0.98 |
- 0.982 |
- 0.988 |
- 0.982 |
- 0.979 |
- 0.988 |
- 0.986 |
- 0.954 |
- 0.977 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.985 |
- 0.968 |
- 0.983 |
- 0.975 |
- 0.98 |
- 0.982 |
- 0.984 |
- 0.978 |
- 0.983 |
- 0.983 |
- 0.969 |
- 0.962 |
- 0.982 |
- 0.897 |
- 0.977 |
- 0.972 |
- 0.98 |
- 0.983 |
- 0.975 |
- 0.958 |
- 0.986 |
- 0.95 |
- 0.984 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.975 |
- 0.985 |
- 0.987 |
- 0.986 |
- 0.989 |
- 0.986 |
- 0.974 |
- 0.985 |
- 1 |
- 0.968 |
- 0.988 |
- 0.984 |
- 0.976 |
- 0.987 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.987 |
- 0.984 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.983 |
- 0.987 |
- 0.979 |
- 0.979 |
- 0.979 |
- 0.979 |
- 0.98 |
- 0.987 |
- 0.974 |
- 0.983 |
- 0.945 |
- 0.973 |
- 0.982 |
- 0.971 |
- 0.983 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.99 |
- 0.987 |
- 0.982 |
- 0.972 |
- 0.983 |
- 0.97 |
- 0.983 |
- 0.985 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.977 |
- 0.979 |
- 0.977 |
- 0.979 |
- 0.98 |
- 0.985 |
- 0.978 |
- 0.982 |
- 0.928 |
- 0.983 |
- 0.977 |
- 0.988 |
- 0.983 |
- 0.979 |
- 0.95 |
- 0.978 |
- 0.954 |
- |
- 0.897 |
- 0.98 |
-
-
- | Liver |
- 688 |
- F |
- 140 |
- 083016.08 |
- HF |
- BXD24 |
- H2259 |
- 0.959 |
- 0.949 |
- 0.949 |
- 0.962 |
- 0.958 |
- 0.968 |
- 0.957 |
- 0.966 |
- 0.926 |
- 0.964 |
- 0.957 |
- 0.971 |
- 0.963 |
- 0.963 |
- 0.969 |
- 0.962 |
- 0.975 |
- 0.973 |
- 0.975 |
- 0.966 |
- 0.954 |
- 0.962 |
- 0.963 |
- 0.967 |
- 0.973 |
- 0.968 |
- 0.968 |
- 0.968 |
- 0.968 |
- 0.96 |
- 0.964 |
- 0.96 |
- 0.953 |
- 0.964 |
- 0.969 |
- 0.975 |
- 0.949 |
- 0.96 |
- 0.97 |
- 0.967 |
- 0.971 |
- 0.965 |
- 0.964 |
- 0.963 |
- 0.967 |
- 0.951 |
- 0.951 |
- 0.963 |
- 0.96 |
- 0.959 |
- 0.968 |
- 0.962 |
- 0.974 |
- 0.962 |
- 0.965 |
- 0.96 |
- 0.97 |
- 0.961 |
- 0.97 |
- 0.965 |
- 0.959 |
- 0.958 |
- 0.971 |
- 0.912 |
- 0.96 |
- 0.962 |
- 0.985 |
- 0.968 |
- 0.97 |
- 0.952 |
- 0.969 |
- 0.955 |
- 0.964 |
- 0.957 |
- 0.966 |
- 0.965 |
- 0.973 |
- 0.96 |
- 0.973 |
- 0.973 |
- 0.958 |
- 0.964 |
- 0.958 |
- 0.965 |
- 0.968 |
- 1 |
- 0.962 |
- 0.965 |
- 0.977 |
- 0.961 |
- 0.971 |
- 0.977 |
- 0.979 |
- 0.972 |
- 0.971 |
- 0.971 |
- 0.972 |
- 0.972 |
- 0.979 |
- 0.972 |
- 0.963 |
- 0.966 |
- 0.973 |
- 0.964 |
- 0.963 |
- 0.961 |
- 0.968 |
- 0.965 |
- 0.963 |
- 0.973 |
- 0.944 |
- 0.964 |
- 0.968 |
- 0.965 |
- 0.962 |
- 0.985 |
- 0.964 |
- 0.969 |
- 0.964 |
- 0.966 |
- 0.965 |
- 0.962 |
- 0.961 |
- 0.972 |
- 0.97 |
- 0.968 |
- 0.964 |
- 0.971 |
- 0.969 |
- 0.971 |
- 0.967 |
- 0.973 |
- 0.972 |
- 0.964 |
- 0.958 |
- 0.963 |
- 0.964 |
- 0.963 |
- 0.976 |
- 0.964 |
- 0.965 |
- 0.933 |
- 0.961 |
- 0.963 |
- 0.966 |
- 0.966 |
- 0.961 |
- 0.955 |
- 0.976 |
- 0.958 |
- |
- 0.912 |
- 0.96 |
-
-
- | Liver |
- 182 |
- F |
- 317 |
- 121515.05 |
- HF |
- BXD29 |
- H2349 |
- 0.99 |
- 0.923 |
- 0.925 |
- 0.986 |
- 0.98 |
- 0.981 |
- 0.988 |
- 0.964 |
- 0.887 |
- 0.986 |
- 0.972 |
- 0.984 |
- 0.985 |
- 0.99 |
- 0.972 |
- 0.977 |
- 0.972 |
- 0.962 |
- 0.981 |
- 0.984 |
- 0.976 |
- 0.988 |
- 0.987 |
- 0.989 |
- 0.984 |
- 0.979 |
- 0.979 |
- 0.976 |
- 0.988 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.945 |
- 0.978 |
- 0.984 |
- 0.977 |
- 0.94 |
- 0.987 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.988 |
- 0.984 |
- 0.947 |
- 0.981 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.986 |
- 0.967 |
- 0.981 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.984 |
- 0.972 |
- 0.963 |
- 0.983 |
- 0.896 |
- 0.985 |
- 0.981 |
- 0.976 |
- 0.986 |
- 0.973 |
- 0.953 |
- 0.986 |
- 0.945 |
- 0.985 |
- 0.988 |
- 0.98 |
- 0.984 |
- 0.975 |
- 0.988 |
- 0.987 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.971 |
- 0.98 |
- 0.988 |
- 0.962 |
- 1 |
- 0.991 |
- 0.976 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.978 |
- 0.977 |
- 0.988 |
- 0.98 |
- 0.975 |
- 0.977 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.974 |
- 0.978 |
- 0.978 |
- 0.982 |
- 0.982 |
- 0.987 |
- 0.979 |
- 0.981 |
- 0.95 |
- 0.973 |
- 0.98 |
- 0.966 |
- 0.984 |
- 0.976 |
- 0.981 |
- 0.98 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.972 |
- 0.981 |
- 0.964 |
- 0.984 |
- 0.986 |
- 0.982 |
- 0.974 |
- 0.975 |
- 0.984 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.978 |
- 0.981 |
- 0.975 |
- 0.98 |
- 0.981 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.924 |
- 0.985 |
- 0.979 |
- 0.986 |
- 0.983 |
- 0.98 |
- 0.945 |
- 0.971 |
- 0.943 |
- |
- 0.887 |
- 0.98 |
-
-
- | Liver |
- 577 |
- F |
- 295 |
- 061913.04 |
- HF |
- BXD29 |
- H0669 |
- 0.991 |
- 0.924 |
- 0.926 |
- 0.989 |
- 0.982 |
- 0.986 |
- 0.988 |
- 0.964 |
- 0.886 |
- 0.984 |
- 0.974 |
- 0.986 |
- 0.987 |
- 0.991 |
- 0.975 |
- 0.981 |
- 0.97 |
- 0.962 |
- 0.985 |
- 0.986 |
- 0.983 |
- 0.989 |
- 0.991 |
- 0.99 |
- 0.981 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.988 |
- 0.988 |
- 0.988 |
- 0.987 |
- 0.949 |
- 0.975 |
- 0.985 |
- 0.976 |
- 0.934 |
- 0.986 |
- 0.98 |
- 0.982 |
- 0.985 |
- 0.985 |
- 0.981 |
- 0.988 |
- 0.984 |
- 0.947 |
- 0.98 |
- 0.982 |
- 0.984 |
- 0.98 |
- 0.989 |
- 0.962 |
- 0.978 |
- 0.981 |
- 0.99 |
- 0.988 |
- 0.977 |
- 0.98 |
- 0.989 |
- 0.981 |
- 0.98 |
- 0.966 |
- 0.983 |
- 0.901 |
- 0.985 |
- 0.985 |
- 0.976 |
- 0.988 |
- 0.967 |
- 0.939 |
- 0.981 |
- 0.939 |
- 0.988 |
- 0.988 |
- 0.986 |
- 0.981 |
- 0.972 |
- 0.989 |
- 0.991 |
- 0.991 |
- 0.983 |
- 0.986 |
- 0.974 |
- 0.983 |
- 0.984 |
- 0.965 |
- 0.991 |
- 1 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.986 |
- 0.986 |
- 0.98 |
- 0.98 |
- 0.989 |
- 0.982 |
- 0.972 |
- 0.981 |
- 0.977 |
- 0.986 |
- 0.982 |
- 0.971 |
- 0.98 |
- 0.984 |
- 0.988 |
- 0.981 |
- 0.987 |
- 0.987 |
- 0.984 |
- 0.955 |
- 0.972 |
- 0.981 |
- 0.968 |
- 0.985 |
- 0.976 |
- 0.985 |
- 0.983 |
- 0.987 |
- 0.987 |
- 0.984 |
- 0.976 |
- 0.983 |
- 0.967 |
- 0.987 |
- 0.991 |
- 0.989 |
- 0.971 |
- 0.983 |
- 0.988 |
- 0.988 |
- 0.984 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.98 |
- 0.985 |
- 0.986 |
- 0.987 |
- 0.988 |
- 0.988 |
- 0.931 |
- 0.988 |
- 0.984 |
- 0.988 |
- 0.99 |
- 0.987 |
- 0.939 |
- 0.97 |
- 0.94 |
- |
- 0.886 |
- 0.98 |
-
-
- | Liver |
- 630 |
- F |
- 119 |
- 111314.10 |
- HF |
- BXD29 |
- H1037 |
- 0.97 |
- 0.934 |
- 0.932 |
- 0.972 |
- 0.964 |
- 0.973 |
- 0.97 |
- 0.983 |
- 0.914 |
- 0.971 |
- 0.957 |
- 0.978 |
- 0.971 |
- 0.977 |
- 0.97 |
- 0.969 |
- 0.983 |
- 0.972 |
- 0.975 |
- 0.973 |
- 0.968 |
- 0.974 |
- 0.973 |
- 0.975 |
- 0.983 |
- 0.975 |
- 0.974 |
- 0.979 |
- 0.974 |
- 0.971 |
- 0.976 |
- 0.975 |
- 0.934 |
- 0.978 |
- 0.983 |
- 0.978 |
- 0.956 |
- 0.974 |
- 0.983 |
- 0.979 |
- 0.978 |
- 0.972 |
- 0.976 |
- 0.972 |
- 0.981 |
- 0.956 |
- 0.956 |
- 0.97 |
- 0.968 |
- 0.965 |
- 0.979 |
- 0.973 |
- 0.98 |
- 0.967 |
- 0.975 |
- 0.971 |
- 0.976 |
- 0.973 |
- 0.979 |
- 0.977 |
- 0.958 |
- 0.943 |
- 0.98 |
- 0.889 |
- 0.968 |
- 0.968 |
- 0.977 |
- 0.976 |
- 0.978 |
- 0.96 |
- 0.977 |
- 0.962 |
- 0.972 |
- 0.97 |
- 0.981 |
- 0.977 |
- 0.98 |
- 0.968 |
- 0.979 |
- 0.98 |
- 0.968 |
- 0.966 |
- 0.955 |
- 0.97 |
- 0.976 |
- 0.977 |
- 0.976 |
- 0.979 |
- 1 |
- 0.97 |
- 0.973 |
- 0.976 |
- 0.979 |
- 0.983 |
- 0.983 |
- 0.977 |
- 0.972 |
- 0.98 |
- 0.977 |
- 0.979 |
- 0.968 |
- 0.974 |
- 0.974 |
- 0.973 |
- 0.968 |
- 0.973 |
- 0.979 |
- 0.972 |
- 0.968 |
- 0.978 |
- 0.933 |
- 0.981 |
- 0.982 |
- 0.973 |
- 0.97 |
- 0.977 |
- 0.973 |
- 0.964 |
- 0.974 |
- 0.97 |
- 0.972 |
- 0.96 |
- 0.972 |
- 0.963 |
- 0.979 |
- 0.979 |
- 0.974 |
- 0.98 |
- 0.978 |
- 0.98 |
- 0.979 |
- 0.978 |
- 0.972 |
- 0.975 |
- 0.965 |
- 0.965 |
- 0.962 |
- 0.971 |
- 0.98 |
- 0.968 |
- 0.977 |
- 0.922 |
- 0.967 |
- 0.964 |
- 0.976 |
- 0.974 |
- 0.978 |
- 0.962 |
- 0.969 |
- 0.96 |
- |
- 0.889 |
- 0.97 |
-
-
- | Liver |
- 200 |
- F |
- 261 |
- 042015.20 |
- HF |
- BXD32 |
- H2030 |
- 0.985 |
- 0.927 |
- 0.928 |
- 0.981 |
- 0.975 |
- 0.984 |
- 0.984 |
- 0.965 |
- 0.887 |
- 0.981 |
- 0.97 |
- 0.986 |
- 0.971 |
- 0.977 |
- 0.973 |
- 0.988 |
- 0.969 |
- 0.972 |
- 0.979 |
- 0.978 |
- 0.984 |
- 0.987 |
- 0.982 |
- 0.984 |
- 0.978 |
- 0.971 |
- 0.971 |
- 0.979 |
- 0.981 |
- 0.986 |
- 0.979 |
- 0.986 |
- 0.941 |
- 0.971 |
- 0.977 |
- 0.974 |
- 0.937 |
- 0.984 |
- 0.978 |
- 0.982 |
- 0.986 |
- 0.977 |
- 0.975 |
- 0.983 |
- 0.98 |
- 0.948 |
- 0.976 |
- 0.977 |
- 0.984 |
- 0.979 |
- 0.984 |
- 0.96 |
- 0.974 |
- 0.972 |
- 0.981 |
- 0.986 |
- 0.976 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.973 |
- 0.962 |
- 0.98 |
- 0.896 |
- 0.976 |
- 0.97 |
- 0.969 |
- 0.98 |
- 0.966 |
- 0.945 |
- 0.979 |
- 0.942 |
- 0.981 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.968 |
- 0.985 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.983 |
- 0.973 |
- 0.979 |
- 0.987 |
- 0.961 |
- 0.982 |
- 0.983 |
- 0.97 |
- 1 |
- 0.983 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.973 |
- 0.975 |
- 0.976 |
- 0.98 |
- 0.987 |
- 0.97 |
- 0.976 |
- 0.976 |
- 0.979 |
- 0.976 |
- 0.984 |
- 0.975 |
- 0.983 |
- 0.943 |
- 0.97 |
- 0.983 |
- 0.97 |
- 0.981 |
- 0.969 |
- 0.982 |
- 0.977 |
- 0.988 |
- 0.982 |
- 0.981 |
- 0.973 |
- 0.985 |
- 0.967 |
- 0.98 |
- 0.985 |
- 0.987 |
- 0.969 |
- 0.981 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.984 |
- 0.927 |
- 0.982 |
- 0.974 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.942 |
- 0.975 |
- 0.946 |
- |
- 0.887 |
- 0.97 |
-
-
- | Liver |
- 539 |
- F |
- 318 |
- 101014.02 |
- HF |
- BXD32 |
- H1137 |
- 0.982 |
- 0.923 |
- 0.925 |
- 0.98 |
- 0.968 |
- 0.98 |
- 0.977 |
- 0.96 |
- 0.888 |
- 0.977 |
- 0.97 |
- 0.978 |
- 0.974 |
- 0.978 |
- 0.964 |
- 0.98 |
- 0.975 |
- 0.969 |
- 0.986 |
- 0.98 |
- 0.975 |
- 0.981 |
- 0.978 |
- 0.98 |
- 0.973 |
- 0.966 |
- 0.967 |
- 0.968 |
- 0.981 |
- 0.978 |
- 0.979 |
- 0.978 |
- 0.947 |
- 0.974 |
- 0.982 |
- 0.973 |
- 0.926 |
- 0.977 |
- 0.976 |
- 0.982 |
- 0.983 |
- 0.984 |
- 0.981 |
- 0.982 |
- 0.976 |
- 0.936 |
- 0.971 |
- 0.975 |
- 0.978 |
- 0.97 |
- 0.982 |
- 0.954 |
- 0.972 |
- 0.971 |
- 0.981 |
- 0.978 |
- 0.971 |
- 0.983 |
- 0.985 |
- 0.978 |
- 0.971 |
- 0.964 |
- 0.975 |
- 0.896 |
- 0.979 |
- 0.978 |
- 0.973 |
- 0.981 |
- 0.96 |
- 0.932 |
- 0.972 |
- 0.932 |
- 0.979 |
- 0.977 |
- 0.976 |
- 0.978 |
- 0.972 |
- 0.981 |
- 0.985 |
- 0.987 |
- 0.974 |
- 0.981 |
- 0.971 |
- 0.981 |
- 0.979 |
- 0.971 |
- 0.979 |
- 0.982 |
- 0.973 |
- 0.983 |
- 1 |
- 0.987 |
- 0.986 |
- 0.98 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.966 |
- 0.975 |
- 0.97 |
- 0.98 |
- 0.976 |
- 0.968 |
- 0.97 |
- 0.975 |
- 0.979 |
- 0.985 |
- 0.985 |
- 0.98 |
- 0.979 |
- 0.946 |
- 0.968 |
- 0.98 |
- 0.966 |
- 0.972 |
- 0.973 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.97 |
- 0.977 |
- 0.962 |
- 0.977 |
- 0.983 |
- 0.982 |
- 0.967 |
- 0.983 |
- 0.979 |
- 0.986 |
- 0.979 |
- 0.981 |
- 0.983 |
- 0.973 |
- 0.976 |
- 0.982 |
- 0.975 |
- 0.98 |
- 0.979 |
- 0.977 |
- 0.928 |
- 0.982 |
- 0.976 |
- 0.977 |
- 0.982 |
- 0.977 |
- 0.932 |
- 0.978 |
- 0.939 |
- |
- 0.888 |
- 0.97 |
-
-
- | Liver |
- 197 |
- F |
- 283 |
- 101513.04 |
- HF |
- BXD34 |
- H1056 |
- 0.984 |
- 0.943 |
- 0.945 |
- 0.986 |
- 0.977 |
- 0.986 |
- 0.978 |
- 0.965 |
- 0.908 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.979 |
- 0.982 |
- 0.973 |
- 0.983 |
- 0.979 |
- 0.968 |
- 0.997 |
- 0.985 |
- 0.976 |
- 0.984 |
- 0.98 |
- 0.984 |
- 0.98 |
- 0.974 |
- 0.975 |
- 0.975 |
- 0.987 |
- 0.981 |
- 0.982 |
- 0.98 |
- 0.959 |
- 0.973 |
- 0.982 |
- 0.983 |
- 0.939 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.983 |
- 0.982 |
- 0.98 |
- 0.984 |
- 0.979 |
- 0.948 |
- 0.977 |
- 0.984 |
- 0.981 |
- 0.976 |
- 0.986 |
- 0.962 |
- 0.979 |
- 0.978 |
- 0.984 |
- 0.981 |
- 0.978 |
- 0.978 |
- 0.989 |
- 0.98 |
- 0.976 |
- 0.973 |
- 0.982 |
- 0.916 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.984 |
- 0.968 |
- 0.941 |
- 0.978 |
- 0.942 |
- 0.984 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.989 |
- 0.989 |
- 0.976 |
- 0.984 |
- 0.977 |
- 0.982 |
- 0.981 |
- 0.977 |
- 0.982 |
- 0.986 |
- 0.976 |
- 0.979 |
- 0.987 |
- 1 |
- 0.997 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.974 |
- 0.985 |
- 0.977 |
- 0.986 |
- 0.981 |
- 0.978 |
- 0.978 |
- 0.983 |
- 0.981 |
- 0.981 |
- 0.985 |
- 0.985 |
- 0.987 |
- 0.956 |
- 0.971 |
- 0.981 |
- 0.971 |
- 0.977 |
- 0.983 |
- 0.981 |
- 0.984 |
- 0.981 |
- 0.981 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.971 |
- 0.984 |
- 0.987 |
- 0.984 |
- 0.973 |
- 0.984 |
- 0.985 |
- 0.986 |
- 0.987 |
- 0.986 |
- 0.979 |
- 0.976 |
- 0.983 |
- 0.987 |
- 0.978 |
- 0.985 |
- 0.984 |
- 0.981 |
- 0.942 |
- 0.983 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.978 |
- 0.942 |
- 0.978 |
- 0.947 |
- |
- 0.908 |
- 0.98 |
-
-
- | Liver |
- 537 |
- F |
- 292 |
- 101014.05 |
- HF |
- BXD34 |
- H1052 |
- 0.983 |
- 0.946 |
- 0.948 |
- 0.985 |
- 0.977 |
- 0.987 |
- 0.978 |
- 0.969 |
- 0.913 |
- 0.979 |
- 0.977 |
- 0.983 |
- 0.979 |
- 0.982 |
- 0.974 |
- 0.983 |
- 0.981 |
- 0.972 |
- 0.997 |
- 0.985 |
- 0.977 |
- 0.983 |
- 0.98 |
- 0.984 |
- 0.981 |
- 0.977 |
- 0.977 |
- 0.977 |
- 0.987 |
- 0.981 |
- 0.981 |
- 0.981 |
- 0.958 |
- 0.974 |
- 0.983 |
- 0.984 |
- 0.944 |
- 0.981 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.98 |
- 0.952 |
- 0.976 |
- 0.984 |
- 0.98 |
- 0.976 |
- 0.986 |
- 0.965 |
- 0.981 |
- 0.979 |
- 0.983 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.989 |
- 0.981 |
- 0.974 |
- 0.971 |
- 0.983 |
- 0.916 |
- 0.979 |
- 0.978 |
- 0.984 |
- 0.984 |
- 0.971 |
- 0.946 |
- 0.979 |
- 0.947 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.982 |
- 0.989 |
- 0.989 |
- 0.977 |
- 0.983 |
- 0.977 |
- 0.982 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.986 |
- 0.979 |
- 0.98 |
- 0.986 |
- 0.997 |
- 1 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.985 |
- 0.976 |
- 0.986 |
- 0.979 |
- 0.985 |
- 0.981 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.988 |
- 0.955 |
- 0.972 |
- 0.981 |
- 0.974 |
- 0.977 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.981 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.972 |
- 0.985 |
- 0.987 |
- 0.984 |
- 0.976 |
- 0.984 |
- 0.986 |
- 0.986 |
- 0.988 |
- 0.985 |
- 0.979 |
- 0.975 |
- 0.983 |
- 0.985 |
- 0.978 |
- 0.986 |
- 0.982 |
- 0.981 |
- 0.942 |
- 0.982 |
- 0.982 |
- 0.983 |
- 0.984 |
- 0.979 |
- 0.947 |
- 0.979 |
- 0.953 |
- |
- 0.913 |
- 0.98 |
-
-
- | Liver |
- 350 |
- F |
- 129 |
- 121214.22 |
- HF |
- BXD39 |
- H1474 |
- 0.979 |
- 0.941 |
- 0.941 |
- 0.981 |
- 0.971 |
- 0.981 |
- 0.975 |
- 0.981 |
- 0.911 |
- 0.974 |
- 0.968 |
- 0.982 |
- 0.969 |
- 0.975 |
- 0.973 |
- 0.976 |
- 0.981 |
- 0.967 |
- 0.981 |
- 0.984 |
- 0.979 |
- 0.982 |
- 0.977 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.977 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.978 |
- 0.943 |
- 0.98 |
- 0.984 |
- 0.981 |
- 0.953 |
- 0.984 |
- 0.989 |
- 0.989 |
- 0.981 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.979 |
- 0.954 |
- 0.966 |
- 0.974 |
- 0.98 |
- 0.978 |
- 0.982 |
- 0.973 |
- 0.981 |
- 0.973 |
- 0.981 |
- 0.979 |
- 0.981 |
- 0.977 |
- 0.985 |
- 0.984 |
- 0.966 |
- 0.958 |
- 0.981 |
- 0.9 |
- 0.97 |
- 0.971 |
- 0.976 |
- 0.978 |
- 0.97 |
- 0.952 |
- 0.98 |
- 0.951 |
- 0.978 |
- 0.975 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.977 |
- 0.983 |
- 0.983 |
- 0.98 |
- 0.978 |
- 0.964 |
- 0.973 |
- 0.981 |
- 0.972 |
- 0.978 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.984 |
- 1 |
- 0.997 |
- 0.976 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.977 |
- 0.986 |
- 0.977 |
- 0.976 |
- 0.973 |
- 0.978 |
- 0.983 |
- 0.979 |
- 0.973 |
- 0.984 |
- 0.936 |
- 0.984 |
- 0.99 |
- 0.976 |
- 0.974 |
- 0.976 |
- 0.98 |
- 0.972 |
- 0.979 |
- 0.974 |
- 0.973 |
- 0.969 |
- 0.976 |
- 0.966 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.98 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.97 |
- 0.973 |
- 0.975 |
- 0.975 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.926 |
- 0.979 |
- 0.973 |
- 0.981 |
- 0.981 |
- 0.98 |
- 0.951 |
- 0.971 |
- 0.949 |
- |
- 0.9 |
- 0.98 |
-
-
- | Liver |
- 350 |
- F |
- 204 |
- 121214.21 |
- HF |
- BXD39 |
- H1473 |
- 0.979 |
- 0.94 |
- 0.941 |
- 0.981 |
- 0.971 |
- 0.98 |
- 0.974 |
- 0.981 |
- 0.911 |
- 0.974 |
- 0.967 |
- 0.981 |
- 0.968 |
- 0.975 |
- 0.972 |
- 0.975 |
- 0.981 |
- 0.965 |
- 0.981 |
- 0.984 |
- 0.978 |
- 0.981 |
- 0.976 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.976 |
- 0.984 |
- 0.982 |
- 0.978 |
- 0.979 |
- 0.977 |
- 0.943 |
- 0.98 |
- 0.984 |
- 0.98 |
- 0.953 |
- 0.983 |
- 0.988 |
- 0.989 |
- 0.981 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.953 |
- 0.965 |
- 0.973 |
- 0.98 |
- 0.977 |
- 0.981 |
- 0.972 |
- 0.981 |
- 0.974 |
- 0.98 |
- 0.978 |
- 0.98 |
- 0.976 |
- 0.984 |
- 0.983 |
- 0.966 |
- 0.958 |
- 0.98 |
- 0.9 |
- 0.97 |
- 0.97 |
- 0.976 |
- 0.977 |
- 0.969 |
- 0.952 |
- 0.98 |
- 0.95 |
- 0.977 |
- 0.974 |
- 0.978 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.977 |
- 0.964 |
- 0.972 |
- 0.98 |
- 0.971 |
- 0.977 |
- 0.98 |
- 0.983 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.983 |
- 0.997 |
- 1 |
- 0.975 |
- 0.984 |
- 0.98 |
- 0.979 |
- 0.981 |
- 0.976 |
- 0.985 |
- 0.977 |
- 0.976 |
- 0.973 |
- 0.977 |
- 0.984 |
- 0.978 |
- 0.973 |
- 0.984 |
- 0.935 |
- 0.984 |
- 0.989 |
- 0.975 |
- 0.973 |
- 0.976 |
- 0.98 |
- 0.972 |
- 0.978 |
- 0.973 |
- 0.972 |
- 0.968 |
- 0.975 |
- 0.966 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.97 |
- 0.972 |
- 0.974 |
- 0.974 |
- 0.98 |
- 0.977 |
- 0.982 |
- 0.925 |
- 0.979 |
- 0.972 |
- 0.98 |
- 0.98 |
- 0.978 |
- 0.95 |
- 0.971 |
- 0.948 |
- |
- 0.9 |
- 0.97 |
-
-
- | Liver |
- 291 |
- F |
- 280 |
- 111314.05 |
- HF |
- BXD40 |
- H1488 |
- 0.988 |
- 0.933 |
- 0.934 |
- 0.986 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.964 |
- 0.896 |
- 0.985 |
- 0.974 |
- 0.985 |
- 0.985 |
- 0.987 |
- 0.974 |
- 0.979 |
- 0.973 |
- 0.968 |
- 0.984 |
- 0.981 |
- 0.976 |
- 0.989 |
- 0.991 |
- 0.991 |
- 0.985 |
- 0.976 |
- 0.976 |
- 0.974 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.985 |
- 0.952 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.938 |
- 0.982 |
- 0.978 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.978 |
- 0.987 |
- 0.985 |
- 0.95 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.987 |
- 0.963 |
- 0.98 |
- 0.979 |
- 0.986 |
- 0.984 |
- 0.979 |
- 0.976 |
- 0.985 |
- 0.979 |
- 0.979 |
- 0.967 |
- 0.986 |
- 0.906 |
- 0.984 |
- 0.983 |
- 0.981 |
- 0.986 |
- 0.973 |
- 0.947 |
- 0.982 |
- 0.948 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.979 |
- 0.973 |
- 0.987 |
- 0.991 |
- 0.99 |
- 0.982 |
- 0.985 |
- 0.977 |
- 0.983 |
- 0.987 |
- 0.971 |
- 0.988 |
- 0.989 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.976 |
- 0.975 |
- 1 |
- 0.986 |
- 0.974 |
- 0.983 |
- 0.978 |
- 0.985 |
- 0.98 |
- 0.978 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.978 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.957 |
- 0.97 |
- 0.978 |
- 0.97 |
- 0.988 |
- 0.981 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.988 |
- 0.986 |
- 0.976 |
- 0.984 |
- 0.972 |
- 0.986 |
- 0.988 |
- 0.984 |
- 0.972 |
- 0.978 |
- 0.985 |
- 0.982 |
- 0.983 |
- 0.986 |
- 0.976 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.986 |
- 0.988 |
- 0.983 |
- 0.984 |
- 0.936 |
- 0.983 |
- 0.982 |
- 0.988 |
- 0.987 |
- 0.982 |
- 0.948 |
- 0.974 |
- 0.951 |
- |
- 0.896 |
- 0.98 |
-
-
- | Liver |
- 358 |
- F |
- 202 |
- 121214.13 |
- HF |
- BXD40 |
- H1593 |
- 0.984 |
- 0.942 |
- 0.945 |
- 0.984 |
- 0.976 |
- 0.983 |
- 0.977 |
- 0.965 |
- 0.904 |
- 0.977 |
- 0.979 |
- 0.983 |
- 0.975 |
- 0.978 |
- 0.974 |
- 0.979 |
- 0.973 |
- 0.965 |
- 0.985 |
- 0.984 |
- 0.974 |
- 0.986 |
- 0.982 |
- 0.983 |
- 0.976 |
- 0.974 |
- 0.975 |
- 0.978 |
- 0.985 |
- 0.98 |
- 0.979 |
- 0.978 |
- 0.959 |
- 0.972 |
- 0.979 |
- 0.98 |
- 0.937 |
- 0.983 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.985 |
- 0.978 |
- 0.944 |
- 0.972 |
- 0.976 |
- 0.983 |
- 0.978 |
- 0.984 |
- 0.96 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.98 |
- 0.978 |
- 0.975 |
- 0.984 |
- 0.979 |
- 0.974 |
- 0.973 |
- 0.981 |
- 0.911 |
- 0.977 |
- 0.975 |
- 0.981 |
- 0.982 |
- 0.963 |
- 0.94 |
- 0.98 |
- 0.939 |
- 0.984 |
- 0.977 |
- 0.973 |
- 0.979 |
- 0.975 |
- 0.984 |
- 0.987 |
- 0.987 |
- 0.981 |
- 0.985 |
- 0.975 |
- 0.98 |
- 0.984 |
- 0.972 |
- 0.98 |
- 0.982 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.984 |
- 0.986 |
- 1 |
- 0.971 |
- 0.98 |
- 0.975 |
- 0.985 |
- 0.986 |
- 0.976 |
- 0.975 |
- 0.981 |
- 0.978 |
- 0.982 |
- 0.986 |
- 0.981 |
- 0.984 |
- 0.95 |
- 0.97 |
- 0.982 |
- 0.969 |
- 0.977 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.976 |
- 0.974 |
- 0.976 |
- 0.969 |
- 0.983 |
- 0.984 |
- 0.983 |
- 0.973 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.984 |
- 1 |
- 0.978 |
- 0.976 |
- 0.981 |
- 0.987 |
- 0.977 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.938 |
- 0.986 |
- 0.983 |
- 0.985 |
- 0.984 |
- 0.974 |
- 0.939 |
- 0.977 |
- 0.941 |
- |
- 0.904 |
- 0.98 |
-
-
- | Liver |
- 240 |
- F |
- 258 |
- 042015.10 |
- HF |
- BXD44 |
- H1825 |
- 0.971 |
- 0.941 |
- 0.94 |
- 0.972 |
- 0.967 |
- 0.971 |
- 0.969 |
- 0.981 |
- 0.919 |
- 0.969 |
- 0.953 |
- 0.981 |
- 0.961 |
- 0.969 |
- 0.972 |
- 0.968 |
- 0.977 |
- 0.973 |
- 0.972 |
- 0.971 |
- 0.966 |
- 0.975 |
- 0.972 |
- 0.979 |
- 0.989 |
- 0.981 |
- 0.981 |
- 0.985 |
- 0.974 |
- 0.972 |
- 0.97 |
- 0.973 |
- 0.928 |
- 0.971 |
- 0.98 |
- 0.981 |
- 0.974 |
- 0.974 |
- 0.983 |
- 0.977 |
- 0.974 |
- 0.964 |
- 0.968 |
- 0.968 |
- 0.979 |
- 0.966 |
- 0.957 |
- 0.965 |
- 0.971 |
- 0.977 |
- 0.974 |
- 0.985 |
- 0.986 |
- 0.964 |
- 0.972 |
- 0.972 |
- 0.985 |
- 0.964 |
- 0.977 |
- 0.976 |
- 0.958 |
- 0.942 |
- 0.981 |
- 0.888 |
- 0.962 |
- 0.96 |
- 0.976 |
- 0.972 |
- 0.983 |
- 0.975 |
- 0.982 |
- 0.973 |
- 0.966 |
- 0.969 |
- 0.976 |
- 0.976 |
- 0.98 |
- 0.967 |
- 0.974 |
- 0.975 |
- 0.972 |
- 0.966 |
- 0.955 |
- 0.961 |
- 0.978 |
- 0.972 |
- 0.975 |
- 0.972 |
- 0.98 |
- 0.973 |
- 0.966 |
- 0.974 |
- 0.976 |
- 0.981 |
- 0.98 |
- 0.974 |
- 0.971 |
- 1 |
- 0.981 |
- 0.997 |
- 0.967 |
- 0.978 |
- 0.976 |
- 0.975 |
- 0.961 |
- 0.967 |
- 0.969 |
- 0.969 |
- 0.964 |
- 0.98 |
- 0.928 |
- 0.976 |
- 0.979 |
- 0.966 |
- 0.974 |
- 0.976 |
- 0.971 |
- 0.962 |
- 0.971 |
- 0.967 |
- 0.97 |
- 0.959 |
- 0.974 |
- 0.967 |
- 0.98 |
- 0.977 |
- 0.973 |
- 0.986 |
- 0.974 |
- 0.981 |
- 0.971 |
- 0.98 |
- 0.971 |
- 0.971 |
- 0.965 |
- 0.961 |
- 0.961 |
- 0.97 |
- 0.978 |
- 0.966 |
- 0.976 |
- 0.915 |
- 0.967 |
- 0.959 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.971 |
- |
- 0.888 |
- 0.97 |
-
-
- | Liver |
- 379 |
- F |
- 158 |
- 012615.12 |
- HF |
- BXD44 |
- H1501 |
- 0.978 |
- 0.95 |
- 0.952 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.966 |
- 0.919 |
- 0.98 |
- 0.971 |
- 0.982 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.976 |
- 0.968 |
- 0.984 |
- 0.978 |
- 0.97 |
- 0.978 |
- 0.98 |
- 0.984 |
- 0.983 |
- 0.978 |
- 0.978 |
- 0.976 |
- 0.982 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.956 |
- 0.975 |
- 0.976 |
- 0.982 |
- 0.953 |
- 0.978 |
- 0.979 |
- 0.977 |
- 0.98 |
- 0.976 |
- 0.975 |
- 0.979 |
- 0.978 |
- 0.959 |
- 0.974 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.97 |
- 0.98 |
- 0.978 |
- 0.981 |
- 0.978 |
- 0.978 |
- 0.969 |
- 0.981 |
- 0.978 |
- 0.976 |
- 0.967 |
- 0.981 |
- 0.915 |
- 0.974 |
- 0.978 |
- 0.987 |
- 0.977 |
- 0.975 |
- 0.955 |
- 0.979 |
- 0.958 |
- 0.979 |
- 0.979 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.976 |
- 0.98 |
- 0.974 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.977 |
- 0.981 |
- 0.977 |
- 0.975 |
- 0.975 |
- 0.985 |
- 0.986 |
- 0.98 |
- 0.979 |
- 0.983 |
- 0.98 |
- 0.981 |
- 1 |
- 0.983 |
- 0.98 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.973 |
- 0.977 |
- 0.977 |
- 0.985 |
- 0.957 |
- 0.974 |
- 0.977 |
- 0.973 |
- 0.981 |
- 0.987 |
- 0.979 |
- 0.981 |
- 0.974 |
- 0.981 |
- 0.981 |
- 0.978 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.98 |
- 0.978 |
- 0.977 |
- 0.978 |
- 0.983 |
- 0.976 |
- 0.985 |
- 0.98 |
- 0.974 |
- 0.977 |
- 0.976 |
- 0.979 |
- 0.981 |
- 0.986 |
- 0.982 |
- 0.981 |
- 0.939 |
- 0.98 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.976 |
- 0.958 |
- 0.975 |
- 0.96 |
- |
- 0.915 |
- 0.98 |
-
-
- | Liver |
- 715 |
- F |
- 144 |
- 102414.12 |
- HF |
- BXD44 |
- H1687 |
- 0.976 |
- 0.939 |
- 0.94 |
- 0.976 |
- 0.97 |
- 0.974 |
- 0.972 |
- 0.978 |
- 0.914 |
- 0.972 |
- 0.958 |
- 0.984 |
- 0.965 |
- 0.973 |
- 0.974 |
- 0.972 |
- 0.976 |
- 0.972 |
- 0.976 |
- 0.975 |
- 0.969 |
- 0.979 |
- 0.976 |
- 0.983 |
- 0.99 |
- 0.981 |
- 0.981 |
- 0.985 |
- 0.977 |
- 0.976 |
- 0.975 |
- 0.976 |
- 0.932 |
- 0.972 |
- 0.983 |
- 0.982 |
- 0.969 |
- 0.977 |
- 0.985 |
- 0.98 |
- 0.976 |
- 0.968 |
- 0.972 |
- 0.973 |
- 0.981 |
- 0.963 |
- 0.962 |
- 0.967 |
- 0.976 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.987 |
- 0.966 |
- 0.976 |
- 0.976 |
- 0.985 |
- 0.967 |
- 0.98 |
- 0.978 |
- 0.963 |
- 0.947 |
- 0.983 |
- 0.89 |
- 0.967 |
- 0.966 |
- 0.978 |
- 0.976 |
- 0.982 |
- 0.972 |
- 0.984 |
- 0.97 |
- 0.97 |
- 0.972 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.973 |
- 0.978 |
- 0.979 |
- 0.974 |
- 0.971 |
- 0.96 |
- 0.965 |
- 0.98 |
- 0.972 |
- 0.979 |
- 0.977 |
- 0.979 |
- 0.976 |
- 0.97 |
- 0.977 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.978 |
- 0.975 |
- 0.997 |
- 0.983 |
- 1 |
- 0.972 |
- 0.981 |
- 0.976 |
- 0.977 |
- 0.965 |
- 0.972 |
- 0.971 |
- 0.974 |
- 0.97 |
- 0.982 |
- 0.932 |
- 0.976 |
- 0.981 |
- 0.966 |
- 0.977 |
- 0.978 |
- 0.975 |
- 0.967 |
- 0.975 |
- 0.972 |
- 0.973 |
- 0.962 |
- 0.977 |
- 0.969 |
- 0.983 |
- 0.98 |
- 0.976 |
- 0.985 |
- 0.976 |
- 0.983 |
- 0.975 |
- 0.982 |
- 0.975 |
- 0.975 |
- 0.969 |
- 0.965 |
- 0.968 |
- 0.974 |
- 0.98 |
- 0.972 |
- 0.98 |
- 0.917 |
- 0.972 |
- 0.965 |
- 0.976 |
- 0.977 |
- 0.975 |
- 0.97 |
- 0.976 |
- 0.967 |
- |
- 0.89 |
- 0.97 |
-
-
- | Liver |
- 503 |
- F |
- 303 |
- 121515.15 |
- HF |
- BXD45 |
- H1940 |
- 0.987 |
- 0.944 |
- 0.946 |
- 0.988 |
- 0.982 |
- 0.989 |
- 0.98 |
- 0.958 |
- 0.905 |
- 0.982 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.974 |
- 0.983 |
- 0.97 |
- 0.959 |
- 0.986 |
- 0.985 |
- 0.979 |
- 0.985 |
- 0.981 |
- 0.985 |
- 0.974 |
- 0.977 |
- 0.978 |
- 0.97 |
- 0.989 |
- 0.985 |
- 0.982 |
- 0.983 |
- 0.963 |
- 0.967 |
- 0.976 |
- 0.98 |
- 0.929 |
- 0.98 |
- 0.973 |
- 0.975 |
- 0.983 |
- 0.982 |
- 0.976 |
- 0.985 |
- 0.978 |
- 0.946 |
- 0.977 |
- 0.98 |
- 0.982 |
- 0.978 |
- 0.986 |
- 0.954 |
- 0.977 |
- 0.981 |
- 0.984 |
- 0.985 |
- 0.977 |
- 0.974 |
- 0.986 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.977 |
- 0.918 |
- 0.982 |
- 0.979 |
- 0.978 |
- 0.983 |
- 0.965 |
- 0.935 |
- 0.977 |
- 0.931 |
- 0.989 |
- 0.98 |
- 0.974 |
- 0.977 |
- 0.968 |
- 0.986 |
- 0.99 |
- 0.988 |
- 0.979 |
- 0.986 |
- 0.983 |
- 0.984 |
- 0.983 |
- 0.963 |
- 0.983 |
- 0.986 |
- 0.968 |
- 0.98 |
- 0.98 |
- 0.986 |
- 0.985 |
- 0.977 |
- 0.976 |
- 0.985 |
- 0.985 |
- 0.967 |
- 0.98 |
- 0.972 |
- 1 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.988 |
- 0.982 |
- 0.976 |
- 0.984 |
- 0.982 |
- 0.985 |
- 0.958 |
- 0.961 |
- 0.974 |
- 0.967 |
- 0.978 |
- 0.978 |
- 0.978 |
- 0.986 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.973 |
- 0.98 |
- 0.986 |
- 0.986 |
- 0.968 |
- 0.982 |
- 0.983 |
- 0.982 |
- 0.985 |
- 0.985 |
- 0.972 |
- 0.978 |
- 0.989 |
- 0.986 |
- 0.977 |
- 0.982 |
- 0.986 |
- 0.981 |
- 0.948 |
- 0.981 |
- 0.985 |
- 0.988 |
- 0.984 |
- 0.976 |
- 0.931 |
- 0.969 |
- 0.941 |
- |
- 0.905 |
- 0.98 |
-
-
- | Liver |
- 189 |
- F |
- 263 |
- 042015.24 |
- HF |
- BXD48 |
- H2046 |
- 0.983 |
- 0.937 |
- 0.938 |
- 0.983 |
- 0.977 |
- 0.982 |
- 0.982 |
- 0.972 |
- 0.899 |
- 0.978 |
- 0.973 |
- 0.986 |
- 0.973 |
- 0.976 |
- 0.978 |
- 0.981 |
- 0.971 |
- 0.969 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.984 |
- 0.981 |
- 0.983 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.988 |
- 0.988 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.946 |
- 0.973 |
- 0.979 |
- 0.98 |
- 0.944 |
- 0.987 |
- 0.984 |
- 0.987 |
- 0.986 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.982 |
- 0.953 |
- 0.973 |
- 0.975 |
- 0.986 |
- 0.983 |
- 0.984 |
- 0.968 |
- 0.98 |
- 0.972 |
- 0.981 |
- 0.982 |
- 0.982 |
- 0.978 |
- 0.983 |
- 0.982 |
- 0.971 |
- 0.961 |
- 0.983 |
- 0.899 |
- 0.976 |
- 0.972 |
- 0.977 |
- 0.98 |
- 0.97 |
- 0.955 |
- 0.983 |
- 0.95 |
- 0.984 |
- 0.982 |
- 0.98 |
- 0.982 |
- 0.972 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.986 |
- 0.981 |
- 0.97 |
- 0.978 |
- 0.987 |
- 0.966 |
- 0.982 |
- 0.982 |
- 0.974 |
- 0.987 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.985 |
- 0.98 |
- 0.986 |
- 0.978 |
- 0.979 |
- 0.981 |
- 0.981 |
- 1 |
- 0.976 |
- 0.979 |
- 0.981 |
- 0.981 |
- 0.976 |
- 0.985 |
- 0.975 |
- 0.983 |
- 0.944 |
- 0.975 |
- 0.986 |
- 0.973 |
- 0.98 |
- 0.977 |
- 0.984 |
- 0.977 |
- 0.984 |
- 0.979 |
- 0.977 |
- 0.969 |
- 0.98 |
- 0.969 |
- 0.985 |
- 0.984 |
- 0.985 |
- 0.976 |
- 0.979 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.986 |
- 0.981 |
- 0.976 |
- 0.975 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.986 |
- 0.928 |
- 0.983 |
- 0.979 |
- 0.987 |
- 0.985 |
- 0.981 |
- 0.95 |
- 0.975 |
- 0.948 |
- |
- 0.899 |
- 0.98 |
-
-
- | Liver |
- 595 |
- F |
- 238 |
- 042915.13 |
- HF |
- BXD48 |
- H1377 |
- 0.97 |
- 0.96 |
- 0.96 |
- 0.974 |
- 0.978 |
- 0.976 |
- 0.97 |
- 0.97 |
- 0.932 |
- 0.976 |
- 0.97 |
- 0.97 |
- 0.969 |
- 0.972 |
- 0.976 |
- 0.967 |
- 0.978 |
- 0.966 |
- 0.976 |
- 0.973 |
- 0.96 |
- 0.971 |
- 0.969 |
- 0.974 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.978 |
- 0.982 |
- 0.969 |
- 0.965 |
- 0.974 |
- 0.952 |
- 0.969 |
- 0.968 |
- 0.983 |
- 0.962 |
- 0.968 |
- 0.973 |
- 0.968 |
- 0.973 |
- 0.969 |
- 0.968 |
- 0.971 |
- 0.973 |
- 0.96 |
- 0.968 |
- 0.974 |
- 0.966 |
- 0.973 |
- 0.971 |
- 0.966 |
- 0.98 |
- 0.977 |
- 0.971 |
- 0.969 |
- 0.98 |
- 0.959 |
- 0.976 |
- 0.977 |
- 0.966 |
- 0.962 |
- 0.972 |
- 0.916 |
- 0.962 |
- 0.964 |
- 0.984 |
- 0.971 |
- 0.978 |
- 0.963 |
- 0.98 |
- 0.955 |
- 0.971 |
- 0.97 |
- 0.964 |
- 0.977 |
- 0.977 |
- 0.97 |
- 0.977 |
- 0.974 |
- 0.974 |
- 0.975 |
- 0.973 |
- 0.969 |
- 0.979 |
- 0.973 |
- 0.974 |
- 0.971 |
- 0.974 |
- 0.97 |
- 0.968 |
- 0.978 |
- 0.98 |
- 0.977 |
- 0.977 |
- 0.978 |
- 0.976 |
- 0.976 |
- 0.981 |
- 0.976 |
- 0.977 |
- 0.976 |
- 1 |
- 0.978 |
- 0.976 |
- 0.963 |
- 0.97 |
- 0.966 |
- 0.963 |
- 0.983 |
- 0.947 |
- 0.967 |
- 0.968 |
- 0.971 |
- 0.976 |
- 0.984 |
- 0.965 |
- 0.976 |
- 0.97 |
- 0.976 |
- 0.977 |
- 0.975 |
- 0.975 |
- 0.979 |
- 0.977 |
- 0.971 |
- 0.969 |
- 0.978 |
- 0.971 |
- 0.977 |
- 0.967 |
- 0.983 |
- 0.976 |
- 0.961 |
- 0.969 |
- 0.975 |
- 0.97 |
- 0.97 |
- 0.98 |
- 0.966 |
- 0.971 |
- 0.939 |
- 0.968 |
- 0.968 |
- 0.976 |
- 0.969 |
- 0.962 |
- 0.955 |
- 0.97 |
- 0.966 |
- |
- 0.916 |
- 0.97 |
-
-
- | Liver |
- 233 |
- F |
- 239 |
- 051112.04 |
- HF |
- BXD48a |
- H0210 |
- 0.979 |
- 0.941 |
- 0.941 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.968 |
- 0.91 |
- 0.977 |
- 0.97 |
- 0.978 |
- 0.976 |
- 0.976 |
- 0.972 |
- 0.976 |
- 0.971 |
- 0.964 |
- 0.977 |
- 0.976 |
- 0.974 |
- 0.979 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.977 |
- 0.977 |
- 0.978 |
- 0.984 |
- 0.978 |
- 0.978 |
- 0.981 |
- 0.945 |
- 0.972 |
- 0.975 |
- 0.979 |
- 0.95 |
- 0.978 |
- 0.977 |
- 0.973 |
- 0.976 |
- 0.973 |
- 0.973 |
- 0.978 |
- 0.978 |
- 0.96 |
- 0.975 |
- 0.977 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.97 |
- 0.977 |
- 0.976 |
- 0.981 |
- 0.978 |
- 0.977 |
- 0.969 |
- 0.98 |
- 0.975 |
- 0.973 |
- 0.957 |
- 0.98 |
- 0.904 |
- 0.972 |
- 0.973 |
- 0.975 |
- 0.976 |
- 0.971 |
- 0.952 |
- 0.976 |
- 0.953 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.975 |
- 0.971 |
- 0.981 |
- 0.982 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.97 |
- 0.974 |
- 0.979 |
- 0.964 |
- 0.978 |
- 0.98 |
- 0.973 |
- 0.976 |
- 0.97 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.976 |
- 0.98 |
- 0.975 |
- 0.975 |
- 0.98 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.978 |
- 1 |
- 0.982 |
- 0.977 |
- 0.968 |
- 0.974 |
- 0.973 |
- 0.982 |
- 0.951 |
- 0.971 |
- 0.974 |
- 0.97 |
- 0.983 |
- 0.975 |
- 0.977 |
- 0.973 |
- 0.976 |
- 0.977 |
- 0.979 |
- 0.974 |
- 0.977 |
- 0.97 |
- 0.984 |
- 0.98 |
- 0.979 |
- 0.974 |
- 0.977 |
- 0.982 |
- 0.976 |
- 0.982 |
- 0.975 |
- 0.969 |
- 0.977 |
- 0.974 |
- 0.974 |
- 0.982 |
- 0.981 |
- 0.978 |
- 0.981 |
- 0.933 |
- 0.975 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.979 |
- 0.953 |
- 0.967 |
- 0.957 |
- |
- 0.904 |
- 0.97 |
-
-
- | Liver |
- 543 |
- F |
- 287 |
- 062013.06 |
- HF |
- BXD48a |
- H0699 |
- 0.982 |
- 0.943 |
- 0.944 |
- 0.986 |
- 0.985 |
- 0.988 |
- 0.981 |
- 0.956 |
- 0.907 |
- 0.979 |
- 0.984 |
- 0.977 |
- 0.985 |
- 0.979 |
- 0.975 |
- 0.98 |
- 0.965 |
- 0.956 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.969 |
- 0.972 |
- 0.972 |
- 0.969 |
- 0.989 |
- 0.982 |
- 0.981 |
- 0.982 |
- 0.965 |
- 0.966 |
- 0.97 |
- 0.978 |
- 0.928 |
- 0.978 |
- 0.971 |
- 0.971 |
- 0.98 |
- 0.981 |
- 0.97 |
- 0.984 |
- 0.979 |
- 0.949 |
- 0.979 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.983 |
- 0.951 |
- 0.971 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.97 |
- 0.974 |
- 0.981 |
- 0.972 |
- 0.979 |
- 0.971 |
- 0.974 |
- 0.919 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.979 |
- 0.96 |
- 0.931 |
- 0.973 |
- 0.93 |
- 0.987 |
- 0.981 |
- 0.979 |
- 0.972 |
- 0.964 |
- 0.984 |
- 0.987 |
- 0.985 |
- 0.979 |
- 0.984 |
- 0.983 |
- 0.983 |
- 0.979 |
- 0.963 |
- 0.978 |
- 0.984 |
- 0.968 |
- 0.976 |
- 0.975 |
- 0.983 |
- 0.982 |
- 0.973 |
- 0.973 |
- 0.983 |
- 0.981 |
- 0.961 |
- 0.98 |
- 0.965 |
- 0.988 |
- 0.981 |
- 0.976 |
- 0.982 |
- 1 |
- 0.981 |
- 0.969 |
- 0.979 |
- 0.976 |
- 0.981 |
- 0.965 |
- 0.959 |
- 0.97 |
- 0.974 |
- 0.978 |
- 0.976 |
- 0.975 |
- 0.984 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.983 |
- 0.978 |
- 0.972 |
- 0.979 |
- 0.983 |
- 0.983 |
- 0.964 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.966 |
- 0.976 |
- 0.986 |
- 0.982 |
- 0.978 |
- 0.981 |
- 0.985 |
- 0.978 |
- 0.952 |
- 0.98 |
- 0.985 |
- 0.986 |
- 0.984 |
- 0.98 |
- 0.93 |
- 0.963 |
- 0.943 |
- |
- 0.907 |
- 0.97 |
-
-
- | Liver |
- 713 |
- F |
- 143 |
- 010614.07 |
- HF |
- BXD53 |
- H0833 |
- 0.99 |
- 0.915 |
- 0.917 |
- 0.988 |
- 0.978 |
- 0.983 |
- 0.988 |
- 0.963 |
- 0.878 |
- 0.981 |
- 0.97 |
- 0.984 |
- 0.979 |
- 0.982 |
- 0.968 |
- 0.979 |
- 0.969 |
- 0.955 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.987 |
- 0.987 |
- 0.985 |
- 0.977 |
- 0.969 |
- 0.97 |
- 0.971 |
- 0.985 |
- 0.984 |
- 0.997 |
- 0.984 |
- 0.943 |
- 0.976 |
- 0.985 |
- 0.972 |
- 0.927 |
- 0.987 |
- 0.982 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.987 |
- 0.981 |
- 0.943 |
- 0.976 |
- 0.977 |
- 0.985 |
- 0.978 |
- 0.987 |
- 0.96 |
- 0.972 |
- 0.974 |
- 0.988 |
- 0.984 |
- 0.972 |
- 0.981 |
- 0.985 |
- 0.979 |
- 0.975 |
- 0.961 |
- 0.982 |
- 0.894 |
- 0.983 |
- 0.984 |
- 0.97 |
- 0.983 |
- 0.961 |
- 0.934 |
- 0.976 |
- 0.936 |
- 0.989 |
- 0.988 |
- 0.988 |
- 0.979 |
- 0.967 |
- 0.988 |
- 0.987 |
- 0.989 |
- 0.98 |
- 0.982 |
- 0.968 |
- 0.982 |
- 0.979 |
- 0.961 |
- 0.982 |
- 0.988 |
- 0.973 |
- 0.979 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.978 |
- 0.977 |
- 0.982 |
- 0.978 |
- 0.967 |
- 0.977 |
- 0.972 |
- 0.982 |
- 0.981 |
- 0.963 |
- 0.977 |
- 0.981 |
- 1 |
- 0.978 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.947 |
- 0.972 |
- 0.982 |
- 0.968 |
- 0.981 |
- 0.97 |
- 0.986 |
- 0.978 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.969 |
- 0.98 |
- 0.962 |
- 0.983 |
- 0.987 |
- 0.986 |
- 0.965 |
- 0.982 |
- 0.983 |
- 0.987 |
- 0.981 |
- 0.978 |
- 0.982 |
- 0.981 |
- 0.976 |
- 0.981 |
- 0.984 |
- 0.981 |
- 0.988 |
- 0.986 |
- 0.923 |
- 0.985 |
- 0.983 |
- 0.986 |
- 0.988 |
- 0.988 |
- 0.936 |
- 0.963 |
- 0.931 |
- |
- 0.878 |
- 0.97 |
-
-
- | Liver |
- 188 |
- F |
- 128 |
- 111414.03 |
- HF |
- BXD61 |
- H1922 |
- 0.98 |
- 0.922 |
- 0.924 |
- 0.98 |
- 0.967 |
- 0.975 |
- 0.976 |
- 0.97 |
- 0.891 |
- 0.978 |
- 0.968 |
- 0.976 |
- 0.973 |
- 0.978 |
- 0.963 |
- 0.969 |
- 0.978 |
- 0.96 |
- 0.98 |
- 0.98 |
- 0.967 |
- 0.98 |
- 0.977 |
- 0.979 |
- 0.975 |
- 0.971 |
- 0.972 |
- 0.972 |
- 0.981 |
- 0.975 |
- 0.979 |
- 0.974 |
- 0.944 |
- 0.986 |
- 0.987 |
- 0.975 |
- 0.938 |
- 0.98 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.987 |
- 0.982 |
- 0.977 |
- 0.939 |
- 0.97 |
- 0.976 |
- 0.977 |
- 0.969 |
- 0.979 |
- 0.961 |
- 0.978 |
- 0.974 |
- 0.979 |
- 0.975 |
- 0.975 |
- 0.976 |
- 0.983 |
- 0.983 |
- 0.963 |
- 0.959 |
- 0.975 |
- 0.892 |
- 0.977 |
- 0.977 |
- 0.973 |
- 0.982 |
- 0.964 |
- 0.943 |
- 0.977 |
- 0.939 |
- 0.979 |
- 0.976 |
- 0.973 |
- 0.983 |
- 0.978 |
- 0.979 |
- 0.982 |
- 0.983 |
- 0.977 |
- 0.978 |
- 0.963 |
- 0.977 |
- 0.98 |
- 0.968 |
- 0.982 |
- 0.981 |
- 0.979 |
- 0.976 |
- 0.985 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.984 |
- 0.978 |
- 0.982 |
- 0.969 |
- 0.973 |
- 0.971 |
- 0.976 |
- 0.976 |
- 0.97 |
- 0.968 |
- 0.969 |
- 0.978 |
- 1 |
- 0.986 |
- 0.979 |
- 0.979 |
- 0.938 |
- 0.978 |
- 0.983 |
- 0.966 |
- 0.971 |
- 0.973 |
- 0.978 |
- 0.973 |
- 0.981 |
- 0.979 |
- 0.972 |
- 0.964 |
- 0.97 |
- 0.958 |
- 0.978 |
- 0.98 |
- 0.977 |
- 0.974 |
- 0.98 |
- 0.98 |
- 0.984 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.97 |
- 0.968 |
- 0.975 |
- 0.972 |
- 0.981 |
- 0.975 |
- 0.979 |
- 0.92 |
- 0.981 |
- 0.973 |
- 0.977 |
- 0.976 |
- 0.972 |
- 0.939 |
- 0.97 |
- 0.934 |
- |
- 0.891 |
- 0.97 |
-
-
- | Liver |
- 188 |
- F |
- 323 |
- 111414.04 |
- HF |
- BXD61 |
- H1722 |
- 0.988 |
- 0.922 |
- 0.924 |
- 0.986 |
- 0.974 |
- 0.983 |
- 0.984 |
- 0.96 |
- 0.882 |
- 0.981 |
- 0.976 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.967 |
- 0.98 |
- 0.969 |
- 0.964 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.987 |
- 0.983 |
- 0.986 |
- 0.977 |
- 0.971 |
- 0.972 |
- 0.974 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.95 |
- 0.978 |
- 0.985 |
- 0.976 |
- 0.925 |
- 0.986 |
- 0.978 |
- 0.986 |
- 0.989 |
- 0.985 |
- 0.984 |
- 0.989 |
- 0.982 |
- 0.937 |
- 0.976 |
- 0.978 |
- 0.986 |
- 0.976 |
- 0.986 |
- 0.956 |
- 0.976 |
- 0.972 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.98 |
- 0.986 |
- 0.98 |
- 0.97 |
- 0.965 |
- 0.983 |
- 0.896 |
- 0.984 |
- 0.979 |
- 0.976 |
- 0.986 |
- 0.962 |
- 0.938 |
- 0.979 |
- 0.936 |
- 0.987 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.968 |
- 0.988 |
- 0.99 |
- 0.99 |
- 0.983 |
- 0.985 |
- 0.973 |
- 0.984 |
- 0.987 |
- 0.965 |
- 0.987 |
- 0.987 |
- 0.972 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.986 |
- 0.969 |
- 0.977 |
- 0.974 |
- 0.984 |
- 0.985 |
- 0.966 |
- 0.974 |
- 0.979 |
- 0.984 |
- 0.986 |
- 1 |
- 0.988 |
- 0.981 |
- 0.952 |
- 0.969 |
- 0.984 |
- 0.966 |
- 0.978 |
- 0.976 |
- 0.987 |
- 0.982 |
- 0.989 |
- 0.986 |
- 0.98 |
- 0.97 |
- 0.98 |
- 0.962 |
- 0.981 |
- 0.986 |
- 0.984 |
- 0.969 |
- 0.978 |
- 0.982 |
- 0.986 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.979 |
- 0.977 |
- 0.986 |
- 0.98 |
- 0.982 |
- 0.986 |
- 0.984 |
- 0.929 |
- 0.988 |
- 0.985 |
- 0.988 |
- 0.986 |
- 0.979 |
- 0.936 |
- 0.976 |
- 0.933 |
- |
- 0.882 |
- 0.98 |
-
-
- | Liver |
- 524 |
- F |
- 316 |
- 121515.25 |
- HF |
- BXD61 |
- H1843 |
- 0.987 |
- 0.92 |
- 0.924 |
- 0.983 |
- 0.972 |
- 0.979 |
- 0.978 |
- 0.95 |
- 0.88 |
- 0.976 |
- 0.972 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.963 |
- 0.978 |
- 0.966 |
- 0.952 |
- 0.985 |
- 0.981 |
- 0.972 |
- 0.984 |
- 0.981 |
- 0.984 |
- 0.975 |
- 0.96 |
- 0.961 |
- 0.964 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.978 |
- 0.951 |
- 0.968 |
- 0.982 |
- 0.97 |
- 0.919 |
- 0.978 |
- 0.974 |
- 0.98 |
- 0.98 |
- 0.976 |
- 0.979 |
- 0.98 |
- 0.972 |
- 0.929 |
- 0.97 |
- 0.973 |
- 0.981 |
- 0.971 |
- 0.982 |
- 0.95 |
- 0.969 |
- 0.972 |
- 0.985 |
- 0.98 |
- 0.969 |
- 0.971 |
- 0.985 |
- 0.972 |
- 0.975 |
- 0.965 |
- 0.982 |
- 0.9 |
- 0.983 |
- 0.983 |
- 0.972 |
- 0.985 |
- 0.958 |
- 0.925 |
- 0.97 |
- 0.931 |
- 0.982 |
- 0.978 |
- 0.974 |
- 0.972 |
- 0.963 |
- 0.985 |
- 0.988 |
- 0.989 |
- 0.972 |
- 0.982 |
- 0.972 |
- 0.978 |
- 0.974 |
- 0.963 |
- 0.979 |
- 0.987 |
- 0.968 |
- 0.975 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.973 |
- 0.973 |
- 0.984 |
- 0.981 |
- 0.964 |
- 0.977 |
- 0.97 |
- 0.982 |
- 0.975 |
- 0.963 |
- 0.973 |
- 0.976 |
- 0.984 |
- 0.979 |
- 0.988 |
- 1 |
- 0.981 |
- 0.956 |
- 0.962 |
- 0.976 |
- 0.955 |
- 0.978 |
- 0.972 |
- 0.984 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.978 |
- 0.969 |
- 0.977 |
- 0.96 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.96 |
- 0.979 |
- 0.982 |
- 0.986 |
- 0.981 |
- 0.981 |
- 0.977 |
- 0.98 |
- 0.976 |
- 0.987 |
- 0.98 |
- 0.978 |
- 0.988 |
- 0.984 |
- 0.932 |
- 0.983 |
- 0.985 |
- 0.982 |
- 0.984 |
- 0.975 |
- 0.931 |
- 0.969 |
- 0.924 |
- |
- 0.88 |
- 0.97 |
-
-
- | Liver |
- 488 |
- F |
- 242 |
- 042915.19 |
- HF |
- BXD62 |
- H1434 |
- 0.984 |
- 0.948 |
- 0.949 |
- 0.986 |
- 0.98 |
- 0.985 |
- 0.98 |
- 0.972 |
- 0.916 |
- 0.981 |
- 0.977 |
- 0.984 |
- 0.976 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.978 |
- 0.967 |
- 0.986 |
- 0.983 |
- 0.977 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.986 |
- 0.983 |
- 0.981 |
- 0.983 |
- 0.957 |
- 0.973 |
- 0.98 |
- 0.986 |
- 0.955 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.982 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.979 |
- 0.956 |
- 0.975 |
- 0.98 |
- 0.98 |
- 0.979 |
- 0.984 |
- 0.967 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.975 |
- 0.987 |
- 0.983 |
- 0.975 |
- 0.969 |
- 0.982 |
- 0.915 |
- 0.974 |
- 0.975 |
- 0.981 |
- 0.982 |
- 0.975 |
- 0.953 |
- 0.981 |
- 0.949 |
- 0.984 |
- 0.98 |
- 0.977 |
- 0.983 |
- 0.976 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.981 |
- 0.984 |
- 0.978 |
- 0.978 |
- 0.983 |
- 0.973 |
- 0.981 |
- 0.984 |
- 0.978 |
- 0.983 |
- 0.979 |
- 0.987 |
- 0.988 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.981 |
- 0.979 |
- 0.981 |
- 0.981 |
- 1 |
- 0.956 |
- 0.973 |
- 0.982 |
- 0.974 |
- 0.98 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.98 |
- 0.984 |
- 0.975 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.977 |
- 0.985 |
- 0.986 |
- 0.983 |
- 1 |
- 0.984 |
- 0.977 |
- 0.977 |
- 0.982 |
- 0.983 |
- 0.978 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.94 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.986 |
- 0.978 |
- 0.949 |
- 0.974 |
- 0.955 |
- |
- 0.915 |
- 0.98 |
-
-
- | Liver |
- 548 |
- F |
- 302 |
- 082214.10 |
- HF |
- BXD62 |
- H1315 |
- 0.951 |
- 0.932 |
- 0.934 |
- 0.952 |
- 0.96 |
- 0.959 |
- 0.951 |
- 0.914 |
- 0.896 |
- 0.953 |
- 0.96 |
- 0.947 |
- 0.964 |
- 0.956 |
- 0.948 |
- 0.952 |
- 0.928 |
- 0.926 |
- 0.956 |
- 0.952 |
- 0.947 |
- 0.949 |
- 0.953 |
- 0.953 |
- 0.938 |
- 0.938 |
- 0.939 |
- 0.929 |
- 0.957 |
- 0.954 |
- 0.947 |
- 0.95 |
- 0.97 |
- 0.932 |
- 0.932 |
- 0.948 |
- 0.902 |
- 0.947 |
- 0.934 |
- 0.938 |
- 0.947 |
- 0.949 |
- 0.939 |
- 0.952 |
- 0.942 |
- 0.921 |
- 0.959 |
- 0.964 |
- 0.947 |
- 0.948 |
- 0.95 |
- 0.917 |
- 0.939 |
- 0.961 |
- 0.953 |
- 0.954 |
- 0.937 |
- 0.936 |
- 0.949 |
- 0.94 |
- 0.963 |
- 0.956 |
- 0.942 |
- 0.926 |
- 0.952 |
- 0.954 |
- 0.952 |
- 0.956 |
- 0.934 |
- 0.898 |
- 0.946 |
- 0.903 |
- 0.959 |
- 0.951 |
- 0.942 |
- 0.94 |
- 0.931 |
- 0.957 |
- 0.959 |
- 0.956 |
- 0.95 |
- 0.958 |
- 0.968 |
- 0.954 |
- 0.945 |
- 0.944 |
- 0.95 |
- 0.955 |
- 0.933 |
- 0.943 |
- 0.946 |
- 0.956 |
- 0.955 |
- 0.936 |
- 0.935 |
- 0.957 |
- 0.95 |
- 0.928 |
- 0.957 |
- 0.932 |
- 0.958 |
- 0.944 |
- 0.947 |
- 0.951 |
- 0.965 |
- 0.947 |
- 0.938 |
- 0.952 |
- 0.956 |
- 0.956 |
- 1 |
- 0.924 |
- 0.936 |
- 0.947 |
- 0.952 |
- 0.952 |
- 0.944 |
- 0.964 |
- 0.948 |
- 0.958 |
- 0.958 |
- 0.969 |
- 0.952 |
- 0.958 |
- 0.952 |
- 0.953 |
- 0.951 |
- 0.928 |
- 0.941 |
- 0.95 |
- 0.946 |
- 0.956 |
- 0.95 |
- 0.932 |
- 0.953 |
- 0.958 |
- 0.961 |
- 0.951 |
- 0.95 |
- 0.963 |
- 0.948 |
- 0.954 |
- 0.953 |
- 0.969 |
- 0.957 |
- 0.955 |
- 0.944 |
- 0.903 |
- 0.935 |
- 0.913 |
- |
- 0.896 |
- 0.95 |
-
-
- | Liver |
- 186 |
- F |
- 125 |
- 111414.09 |
- HF |
- BXD63 |
- H1715 |
- 0.972 |
- 0.922 |
- 0.922 |
- 0.969 |
- 0.965 |
- 0.966 |
- 0.974 |
- 0.979 |
- 0.895 |
- 0.97 |
- 0.95 |
- 0.976 |
- 0.959 |
- 0.968 |
- 0.961 |
- 0.963 |
- 0.979 |
- 0.961 |
- 0.969 |
- 0.968 |
- 0.96 |
- 0.973 |
- 0.974 |
- 0.973 |
- 0.977 |
- 0.975 |
- 0.975 |
- 0.976 |
- 0.971 |
- 0.97 |
- 0.975 |
- 0.967 |
- 0.922 |
- 0.986 |
- 0.98 |
- 0.972 |
- 0.955 |
- 0.983 |
- 0.989 |
- 0.986 |
- 0.972 |
- 0.971 |
- 0.98 |
- 0.974 |
- 0.975 |
- 0.952 |
- 0.964 |
- 0.97 |
- 0.974 |
- 0.971 |
- 0.972 |
- 0.976 |
- 0.976 |
- 0.967 |
- 0.974 |
- 0.97 |
- 0.974 |
- 0.967 |
- 0.975 |
- 0.984 |
- 0.957 |
- 0.94 |
- 0.976 |
- 0.88 |
- 0.964 |
- 0.967 |
- 0.968 |
- 0.969 |
- 0.969 |
- 0.957 |
- 0.976 |
- 0.958 |
- 0.967 |
- 0.974 |
- 0.977 |
- 0.984 |
- 0.982 |
- 0.972 |
- 0.972 |
- 0.975 |
- 0.975 |
- 0.964 |
- 0.947 |
- 0.962 |
- 0.973 |
- 0.964 |
- 0.973 |
- 0.972 |
- 0.981 |
- 0.97 |
- 0.968 |
- 0.971 |
- 0.972 |
- 0.984 |
- 0.984 |
- 0.97 |
- 0.97 |
- 0.976 |
- 0.974 |
- 0.976 |
- 0.961 |
- 0.975 |
- 0.967 |
- 0.971 |
- 0.959 |
- 0.972 |
- 0.978 |
- 0.969 |
- 0.962 |
- 0.973 |
- 0.924 |
- 1 |
- 0.988 |
- 0.973 |
- 0.973 |
- 0.968 |
- 0.978 |
- 0.958 |
- 0.969 |
- 0.968 |
- 0.967 |
- 0.955 |
- 0.967 |
- 0.956 |
- 0.98 |
- 0.975 |
- 0.97 |
- 0.979 |
- 0.974 |
- 0.979 |
- 0.973 |
- 0.973 |
- 0.97 |
- 0.98 |
- 0.967 |
- 0.954 |
- 0.961 |
- 0.975 |
- 0.977 |
- 0.967 |
- 0.978 |
- 0.901 |
- 0.972 |
- 0.962 |
- 0.971 |
- 0.971 |
- 0.976 |
- 0.958 |
- 0.964 |
- 0.946 |
- |
- 0.88 |
- 0.97 |
-
-
- | Liver |
- 344 |
- F |
- 123 |
- 121214.26 |
- HF |
- BXD63 |
- H1416 |
- 0.982 |
- 0.925 |
- 0.926 |
- 0.98 |
- 0.967 |
- 0.977 |
- 0.979 |
- 0.977 |
- 0.892 |
- 0.975 |
- 0.963 |
- 0.983 |
- 0.967 |
- 0.976 |
- 0.967 |
- 0.975 |
- 0.977 |
- 0.967 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.983 |
- 0.979 |
- 0.981 |
- 0.981 |
- 0.973 |
- 0.974 |
- 0.982 |
- 0.98 |
- 0.979 |
- 0.983 |
- 0.979 |
- 0.935 |
- 0.98 |
- 0.986 |
- 0.976 |
- 0.944 |
- 0.99 |
- 0.991 |
- 0.996 |
- 0.984 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.981 |
- 0.946 |
- 0.967 |
- 0.974 |
- 0.982 |
- 0.976 |
- 0.983 |
- 0.97 |
- 0.978 |
- 0.968 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.963 |
- 0.951 |
- 0.984 |
- 0.889 |
- 0.973 |
- 0.972 |
- 0.973 |
- 0.98 |
- 0.968 |
- 0.951 |
- 0.979 |
- 0.949 |
- 0.979 |
- 0.979 |
- 0.982 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.983 |
- 0.985 |
- 0.981 |
- 0.976 |
- 0.959 |
- 0.974 |
- 0.982 |
- 0.968 |
- 0.98 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.99 |
- 0.989 |
- 0.978 |
- 0.982 |
- 0.979 |
- 0.977 |
- 0.981 |
- 0.974 |
- 0.986 |
- 0.968 |
- 0.974 |
- 0.97 |
- 0.982 |
- 0.983 |
- 0.984 |
- 0.976 |
- 0.982 |
- 0.936 |
- 0.988 |
- 1 |
- 0.976 |
- 0.974 |
- 0.973 |
- 0.985 |
- 0.971 |
- 0.982 |
- 0.975 |
- 0.976 |
- 0.963 |
- 0.978 |
- 0.961 |
- 0.985 |
- 0.985 |
- 0.982 |
- 0.977 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.982 |
- 0.982 |
- 0.986 |
- 0.973 |
- 0.968 |
- 0.975 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.984 |
- 0.917 |
- 0.981 |
- 0.975 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.949 |
- 0.972 |
- 0.943 |
- |
- 0.889 |
- 0.97 |
-
-
- | Liver |
- 752 |
- F |
- 135 |
- 102616.17 |
- HF |
- BXD63 |
- H2091 |
- 0.964 |
- 0.943 |
- 0.942 |
- 0.969 |
- 0.971 |
- 0.975 |
- 0.969 |
- 0.972 |
- 0.922 |
- 0.965 |
- 0.966 |
- 0.97 |
- 0.964 |
- 0.96 |
- 0.972 |
- 0.968 |
- 0.969 |
- 0.967 |
- 0.97 |
- 0.968 |
- 0.971 |
- 0.966 |
- 0.968 |
- 0.968 |
- 0.966 |
- 0.972 |
- 0.972 |
- 0.971 |
- 0.972 |
- 0.97 |
- 0.97 |
- 0.969 |
- 0.947 |
- 0.97 |
- 0.966 |
- 0.977 |
- 0.949 |
- 0.975 |
- 0.976 |
- 0.973 |
- 0.97 |
- 0.97 |
- 0.963 |
- 0.972 |
- 0.973 |
- 0.961 |
- 0.965 |
- 0.973 |
- 0.969 |
- 0.97 |
- 0.971 |
- 0.963 |
- 0.971 |
- 0.97 |
- 0.97 |
- 0.97 |
- 0.969 |
- 0.968 |
- 0.969 |
- 0.972 |
- 0.963 |
- 0.95 |
- 0.967 |
- 0.905 |
- 0.958 |
- 0.961 |
- 0.971 |
- 0.966 |
- 0.964 |
- 0.946 |
- 0.973 |
- 0.945 |
- 0.972 |
- 0.969 |
- 0.975 |
- 0.972 |
- 0.97 |
- 0.968 |
- 0.974 |
- 0.973 |
- 0.972 |
- 0.967 |
- 0.966 |
- 0.966 |
- 0.971 |
- 0.965 |
- 0.966 |
- 0.968 |
- 0.973 |
- 0.97 |
- 0.966 |
- 0.971 |
- 0.974 |
- 0.976 |
- 0.975 |
- 0.97 |
- 0.969 |
- 0.966 |
- 0.973 |
- 0.966 |
- 0.967 |
- 0.973 |
- 0.971 |
- 0.97 |
- 0.974 |
- 0.968 |
- 0.966 |
- 0.966 |
- 0.955 |
- 0.974 |
- 0.947 |
- 0.973 |
- 0.976 |
- 1 |
- 0.966 |
- 0.971 |
- 0.964 |
- 0.967 |
- 0.968 |
- 0.969 |
- 0.967 |
- 0.97 |
- 0.968 |
- 0.969 |
- 0.974 |
- 0.972 |
- 0.971 |
- 0.971 |
- 0.971 |
- 0.974 |
- 0.971 |
- 0.974 |
- 0.969 |
- 0.967 |
- 0.962 |
- 0.971 |
- 0.963 |
- 0.968 |
- 0.973 |
- 0.968 |
- 0.97 |
- 0.936 |
- 0.968 |
- 0.967 |
- 0.973 |
- 0.971 |
- 0.976 |
- 0.945 |
- 0.961 |
- 0.959 |
- |
- 0.905 |
- 0.97 |
-
-
- | Liver |
- 230 |
- F |
- 265 |
- 051012.01 |
- HF |
- BXD65 |
- H0458 |
- 0.986 |
- 0.927 |
- 0.929 |
- 0.981 |
- 0.987 |
- 0.979 |
- 0.988 |
- 0.962 |
- 0.889 |
- 0.983 |
- 0.967 |
- 0.982 |
- 0.977 |
- 0.982 |
- 0.974 |
- 0.975 |
- 0.967 |
- 0.962 |
- 0.976 |
- 0.975 |
- 0.971 |
- 0.984 |
- 0.989 |
- 0.988 |
- 0.981 |
- 0.973 |
- 0.974 |
- 0.973 |
- 0.981 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.941 |
- 0.976 |
- 0.978 |
- 0.975 |
- 0.944 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.98 |
- 0.953 |
- 0.982 |
- 0.977 |
- 0.982 |
- 0.983 |
- 0.98 |
- 0.967 |
- 0.976 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.976 |
- 0.97 |
- 0.98 |
- 0.977 |
- 0.98 |
- 0.961 |
- 0.982 |
- 0.895 |
- 0.978 |
- 0.98 |
- 0.976 |
- 0.979 |
- 0.97 |
- 0.949 |
- 0.981 |
- 0.953 |
- 0.98 |
- 0.988 |
- 0.982 |
- 0.977 |
- 0.971 |
- 0.988 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.973 |
- 0.975 |
- 0.983 |
- 0.962 |
- 0.984 |
- 0.985 |
- 0.97 |
- 0.981 |
- 0.972 |
- 0.977 |
- 0.977 |
- 0.974 |
- 0.973 |
- 0.988 |
- 0.977 |
- 0.974 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.978 |
- 0.981 |
- 0.971 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.952 |
- 0.973 |
- 0.974 |
- 0.966 |
- 1 |
- 0.976 |
- 0.986 |
- 0.981 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.973 |
- 0.983 |
- 0.971 |
- 0.987 |
- 0.984 |
- 0.98 |
- 0.971 |
- 0.975 |
- 0.984 |
- 0.977 |
- 0.98 |
- 0.977 |
- 0.975 |
- 0.988 |
- 0.973 |
- 0.979 |
- 0.991 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.923 |
- 0.981 |
- 0.978 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.953 |
- 0.969 |
- 0.949 |
- |
- 0.889 |
- 0.97 |
-
-
- | Liver |
- 541 |
- F |
- 212 |
- 121615.06 |
- HF |
- BXD65 |
- H1784 |
- 0.972 |
- 0.955 |
- 0.956 |
- 0.975 |
- 0.972 |
- 0.977 |
- 0.97 |
- 0.968 |
- 0.925 |
- 0.975 |
- 0.97 |
- 0.976 |
- 0.974 |
- 0.973 |
- 0.975 |
- 0.969 |
- 0.977 |
- 0.973 |
- 0.982 |
- 0.975 |
- 0.964 |
- 0.972 |
- 0.974 |
- 0.976 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.977 |
- 0.98 |
- 0.97 |
- 0.973 |
- 0.97 |
- 0.958 |
- 0.971 |
- 0.974 |
- 0.983 |
- 0.952 |
- 0.972 |
- 0.975 |
- 0.973 |
- 0.981 |
- 0.977 |
- 0.974 |
- 0.978 |
- 0.978 |
- 0.959 |
- 0.964 |
- 0.973 |
- 0.971 |
- 0.971 |
- 0.976 |
- 0.968 |
- 0.982 |
- 0.972 |
- 0.974 |
- 0.97 |
- 0.98 |
- 0.965 |
- 0.978 |
- 0.974 |
- 0.965 |
- 0.967 |
- 0.979 |
- 0.917 |
- 0.971 |
- 0.971 |
- 1 |
- 0.976 |
- 0.975 |
- 0.959 |
- 0.978 |
- 0.957 |
- 0.977 |
- 0.97 |
- 0.972 |
- 0.974 |
- 0.976 |
- 0.973 |
- 0.983 |
- 0.982 |
- 0.97 |
- 0.976 |
- 0.969 |
- 0.975 |
- 0.98 |
- 0.985 |
- 0.976 |
- 0.976 |
- 0.977 |
- 0.969 |
- 0.973 |
- 0.983 |
- 0.984 |
- 0.976 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.976 |
- 0.987 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.984 |
- 0.975 |
- 0.976 |
- 0.97 |
- 0.973 |
- 0.976 |
- 0.972 |
- 0.981 |
- 0.952 |
- 0.968 |
- 0.973 |
- 0.971 |
- 0.976 |
- 1 |
- 0.975 |
- 0.983 |
- 0.975 |
- 0.978 |
- 0.974 |
- 0.971 |
- 0.971 |
- 0.98 |
- 0.979 |
- 0.976 |
- 0.972 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.966 |
- 0.97 |
- 0.975 |
- 0.974 |
- 0.973 |
- 0.987 |
- 0.974 |
- 0.974 |
- 0.941 |
- 0.973 |
- 0.975 |
- 0.978 |
- 0.974 |
- 0.968 |
- 0.957 |
- 0.979 |
- 0.963 |
- |
- 0.917 |
- 0.97 |
-
-
- | Liver |
- 174 |
- F |
- 315 |
- 102414.18 |
- HF |
- BXD65b |
- H1713 |
- 0.987 |
- 0.92 |
- 0.922 |
- 0.982 |
- 0.974 |
- 0.978 |
- 0.985 |
- 0.964 |
- 0.88 |
- 0.98 |
- 0.968 |
- 0.985 |
- 0.974 |
- 0.98 |
- 0.964 |
- 0.978 |
- 0.97 |
- 0.962 |
- 0.981 |
- 0.977 |
- 0.974 |
- 0.986 |
- 0.984 |
- 0.984 |
- 0.977 |
- 0.969 |
- 0.97 |
- 0.975 |
- 0.98 |
- 0.981 |
- 0.987 |
- 0.98 |
- 0.938 |
- 0.979 |
- 0.984 |
- 0.973 |
- 0.931 |
- 0.986 |
- 0.984 |
- 0.987 |
- 0.986 |
- 0.982 |
- 0.987 |
- 0.987 |
- 0.978 |
- 0.94 |
- 0.973 |
- 0.973 |
- 0.987 |
- 0.977 |
- 0.982 |
- 0.963 |
- 0.972 |
- 0.97 |
- 0.986 |
- 0.981 |
- 0.973 |
- 0.977 |
- 0.984 |
- 0.98 |
- 0.971 |
- 0.959 |
- 0.985 |
- 0.889 |
- 0.981 |
- 0.98 |
- 0.975 |
- 0.979 |
- 0.962 |
- 0.941 |
- 0.975 |
- 0.946 |
- 0.981 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.969 |
- 0.988 |
- 0.985 |
- 0.989 |
- 0.979 |
- 0.981 |
- 0.967 |
- 0.978 |
- 0.981 |
- 0.964 |
- 0.981 |
- 0.985 |
- 0.973 |
- 0.982 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.971 |
- 0.979 |
- 0.975 |
- 0.978 |
- 0.984 |
- 0.965 |
- 0.977 |
- 0.975 |
- 0.986 |
- 0.978 |
- 0.987 |
- 0.984 |
- 0.98 |
- 0.944 |
- 0.978 |
- 0.985 |
- 0.964 |
- 0.986 |
- 0.975 |
- 1 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.978 |
- 0.965 |
- 0.979 |
- 0.961 |
- 0.987 |
- 0.986 |
- 0.983 |
- 0.969 |
- 0.982 |
- 0.984 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.97 |
- 0.982 |
- 0.987 |
- 0.983 |
- 0.987 |
- 0.989 |
- 0.919 |
- 0.985 |
- 0.983 |
- 0.984 |
- 0.988 |
- 0.983 |
- 0.946 |
- 0.974 |
- 0.933 |
- |
- 0.88 |
- 0.97 |
-
-
- | Liver |
- 527 |
- F |
- 321 |
- 121615.11 |
- HF |
- BXD65b |
- H1790 |
- 0.984 |
- 0.935 |
- 0.938 |
- 0.983 |
- 0.98 |
- 0.984 |
- 0.981 |
- 0.95 |
- 0.895 |
- 0.981 |
- 0.978 |
- 0.976 |
- 0.979 |
- 0.981 |
- 0.973 |
- 0.975 |
- 0.962 |
- 0.957 |
- 0.984 |
- 0.979 |
- 0.973 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.97 |
- 0.966 |
- 0.966 |
- 0.963 |
- 0.984 |
- 0.98 |
- 0.978 |
- 0.979 |
- 0.965 |
- 0.965 |
- 0.97 |
- 0.972 |
- 0.923 |
- 0.976 |
- 0.968 |
- 0.973 |
- 0.983 |
- 0.984 |
- 0.974 |
- 0.984 |
- 0.974 |
- 0.939 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.974 |
- 0.98 |
- 0.947 |
- 0.968 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.972 |
- 0.972 |
- 0.98 |
- 0.973 |
- 0.978 |
- 0.98 |
- 0.972 |
- 0.92 |
- 0.978 |
- 0.978 |
- 0.983 |
- 0.98 |
- 0.959 |
- 0.931 |
- 0.974 |
- 0.926 |
- 0.985 |
- 0.981 |
- 0.97 |
- 0.973 |
- 0.961 |
- 0.986 |
- 0.985 |
- 0.985 |
- 0.979 |
- 0.989 |
- 0.984 |
- 0.981 |
- 0.981 |
- 0.969 |
- 0.98 |
- 0.983 |
- 0.964 |
- 0.977 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.972 |
- 0.972 |
- 0.985 |
- 0.983 |
- 0.962 |
- 0.981 |
- 0.967 |
- 0.986 |
- 0.977 |
- 0.976 |
- 0.973 |
- 0.984 |
- 0.978 |
- 0.973 |
- 0.982 |
- 0.98 |
- 0.982 |
- 0.964 |
- 0.958 |
- 0.971 |
- 0.967 |
- 0.981 |
- 0.983 |
- 0.978 |
- 1 |
- 0.98 |
- 0.986 |
- 0.981 |
- 0.981 |
- 0.98 |
- 0.976 |
- 0.976 |
- 0.981 |
- 0.979 |
- 0.959 |
- 0.975 |
- 0.976 |
- 0.978 |
- 0.982 |
- 0.983 |
- 0.969 |
- 0.978 |
- 0.984 |
- 0.986 |
- 0.978 |
- 0.98 |
- 0.984 |
- 0.976 |
- 0.944 |
- 0.982 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.973 |
- 0.926 |
- 0.968 |
- 0.935 |
- |
- 0.895 |
- 0.97 |
-
-
- | Liver |
- 184 |
- F |
- 262 |
- 042415.05 |
- HF |
- BXD66 |
- H2124 |
- 0.986 |
- 0.923 |
- 0.923 |
- 0.985 |
- 0.975 |
- 0.985 |
- 0.983 |
- 0.966 |
- 0.885 |
- 0.983 |
- 0.973 |
- 0.984 |
- 0.978 |
- 0.981 |
- 0.969 |
- 0.981 |
- 0.968 |
- 0.97 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.988 |
- 0.984 |
- 0.987 |
- 0.98 |
- 0.974 |
- 0.974 |
- 0.976 |
- 0.984 |
- 0.985 |
- 0.982 |
- 0.987 |
- 0.946 |
- 0.974 |
- 0.982 |
- 0.976 |
- 0.932 |
- 0.984 |
- 0.976 |
- 0.981 |
- 0.988 |
- 0.983 |
- 0.978 |
- 0.988 |
- 0.989 |
- 0.948 |
- 0.973 |
- 0.978 |
- 0.981 |
- 0.975 |
- 0.987 |
- 0.958 |
- 0.977 |
- 0.973 |
- 0.981 |
- 0.985 |
- 0.977 |
- 0.981 |
- 0.985 |
- 0.979 |
- 0.969 |
- 0.961 |
- 0.982 |
- 0.894 |
- 0.981 |
- 0.974 |
- 0.975 |
- 0.985 |
- 0.965 |
- 0.941 |
- 0.98 |
- 0.938 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.979 |
- 0.969 |
- 0.984 |
- 0.988 |
- 0.988 |
- 0.985 |
- 0.984 |
- 0.972 |
- 0.985 |
- 0.99 |
- 0.964 |
- 0.986 |
- 0.987 |
- 0.974 |
- 0.988 |
- 0.983 |
- 0.981 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.986 |
- 0.983 |
- 0.971 |
- 0.974 |
- 0.975 |
- 0.983 |
- 0.984 |
- 0.97 |
- 0.976 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.989 |
- 0.978 |
- 0.98 |
- 0.948 |
- 0.969 |
- 0.982 |
- 0.968 |
- 0.979 |
- 0.975 |
- 0.981 |
- 0.98 |
- 1 |
- 0.99 |
- 0.98 |
- 0.971 |
- 0.982 |
- 0.964 |
- 0.98 |
- 0.987 |
- 0.985 |
- 0.969 |
- 0.978 |
- 0.983 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.977 |
- 0.977 |
- 0.977 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.928 |
- 0.984 |
- 0.979 |
- 0.989 |
- 0.985 |
- 0.982 |
- 0.938 |
- 0.973 |
- 0.943 |
- |
- 0.885 |
- 0.98 |
-
-
- | Liver |
- 367 |
- F |
- 122 |
- 121214.04 |
- HF |
- BXD66 |
- H1560 |
- 0.986 |
- 0.927 |
- 0.93 |
- 0.983 |
- 0.984 |
- 0.983 |
- 0.988 |
- 0.958 |
- 0.889 |
- 0.987 |
- 0.975 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.971 |
- 0.976 |
- 0.966 |
- 0.964 |
- 0.981 |
- 0.979 |
- 0.975 |
- 0.983 |
- 0.987 |
- 0.987 |
- 0.977 |
- 0.973 |
- 0.974 |
- 0.969 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.953 |
- 0.976 |
- 0.977 |
- 0.975 |
- 0.934 |
- 0.981 |
- 0.973 |
- 0.976 |
- 0.984 |
- 0.985 |
- 0.978 |
- 0.987 |
- 0.985 |
- 0.949 |
- 0.984 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.982 |
- 0.957 |
- 0.975 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.975 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.979 |
- 0.968 |
- 0.977 |
- 0.902 |
- 0.981 |
- 0.98 |
- 0.978 |
- 0.982 |
- 0.965 |
- 0.942 |
- 0.981 |
- 0.938 |
- 0.984 |
- 0.988 |
- 0.978 |
- 0.98 |
- 0.969 |
- 0.989 |
- 0.986 |
- 0.988 |
- 0.985 |
- 0.988 |
- 0.978 |
- 0.984 |
- 0.987 |
- 0.966 |
- 0.986 |
- 0.987 |
- 0.97 |
- 0.982 |
- 0.982 |
- 0.981 |
- 0.981 |
- 0.974 |
- 0.973 |
- 0.988 |
- 0.981 |
- 0.967 |
- 0.981 |
- 0.972 |
- 0.983 |
- 0.979 |
- 0.976 |
- 0.977 |
- 0.983 |
- 0.982 |
- 0.979 |
- 0.986 |
- 0.978 |
- 0.98 |
- 0.958 |
- 0.968 |
- 0.975 |
- 0.969 |
- 0.985 |
- 0.978 |
- 0.981 |
- 0.986 |
- 0.99 |
- 1 |
- 0.985 |
- 0.977 |
- 0.982 |
- 0.972 |
- 0.982 |
- 0.984 |
- 0.981 |
- 0.968 |
- 0.975 |
- 0.981 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.974 |
- 0.983 |
- 0.978 |
- 0.983 |
- 0.984 |
- 0.986 |
- 0.983 |
- 0.982 |
- 0.932 |
- 0.987 |
- 0.982 |
- 0.986 |
- 0.985 |
- 0.979 |
- 0.938 |
- 0.972 |
- 0.944 |
- |
- 0.889 |
- 0.98 |
-
-
- | Liver |
- 201 |
- F |
- 59 |
- 101613.08 |
- HF |
- BXD68 |
- H1071 |
- 0.986 |
- 0.93 |
- 0.931 |
- 0.983 |
- 0.982 |
- 0.982 |
- 0.988 |
- 0.958 |
- 0.894 |
- 0.985 |
- 0.972 |
- 0.979 |
- 0.979 |
- 0.984 |
- 0.971 |
- 0.977 |
- 0.971 |
- 0.961 |
- 0.984 |
- 0.976 |
- 0.973 |
- 0.982 |
- 0.983 |
- 0.986 |
- 0.98 |
- 0.969 |
- 0.969 |
- 0.969 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.949 |
- 0.971 |
- 0.975 |
- 0.976 |
- 0.938 |
- 0.979 |
- 0.975 |
- 0.976 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.98 |
- 0.977 |
- 0.946 |
- 0.986 |
- 0.984 |
- 0.977 |
- 0.977 |
- 0.982 |
- 0.957 |
- 0.972 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.975 |
- 0.973 |
- 0.982 |
- 0.979 |
- 0.977 |
- 0.964 |
- 0.981 |
- 0.906 |
- 0.976 |
- 0.976 |
- 0.974 |
- 0.982 |
- 0.968 |
- 0.943 |
- 0.978 |
- 0.94 |
- 0.983 |
- 0.988 |
- 0.978 |
- 0.979 |
- 0.967 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.976 |
- 0.98 |
- 0.982 |
- 0.965 |
- 0.983 |
- 0.984 |
- 0.972 |
- 0.981 |
- 0.977 |
- 0.985 |
- 0.985 |
- 0.973 |
- 0.972 |
- 0.986 |
- 0.976 |
- 0.97 |
- 0.981 |
- 0.973 |
- 0.981 |
- 0.977 |
- 0.977 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.972 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.958 |
- 0.967 |
- 0.976 |
- 0.967 |
- 0.983 |
- 0.974 |
- 0.978 |
- 0.981 |
- 0.98 |
- 0.985 |
- 1 |
- 0.981 |
- 0.988 |
- 0.972 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.968 |
- 0.977 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.976 |
- 0.971 |
- 0.985 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.935 |
- 0.983 |
- 0.978 |
- 0.985 |
- 0.985 |
- 0.978 |
- 0.94 |
- 0.968 |
- 0.947 |
- |
- 0.894 |
- 0.97 |
-
-
- | Liver |
- 545 |
- F |
- 71 |
- 082214.08 |
- HF |
- BXD68 |
- H1290 |
- 0.975 |
- 0.95 |
- 0.951 |
- 0.976 |
- 0.982 |
- 0.985 |
- 0.973 |
- 0.948 |
- 0.919 |
- 0.976 |
- 0.98 |
- 0.971 |
- 0.976 |
- 0.974 |
- 0.977 |
- 0.977 |
- 0.963 |
- 0.951 |
- 0.982 |
- 0.976 |
- 0.969 |
- 0.973 |
- 0.973 |
- 0.975 |
- 0.964 |
- 0.967 |
- 0.968 |
- 0.959 |
- 0.979 |
- 0.978 |
- 0.969 |
- 0.977 |
- 0.971 |
- 0.961 |
- 0.961 |
- 0.975 |
- 0.935 |
- 0.97 |
- 0.963 |
- 0.963 |
- 0.97 |
- 0.972 |
- 0.964 |
- 0.975 |
- 0.967 |
- 0.949 |
- 0.982 |
- 0.986 |
- 0.971 |
- 0.973 |
- 0.974 |
- 0.948 |
- 0.967 |
- 0.983 |
- 0.975 |
- 0.978 |
- 0.966 |
- 0.964 |
- 0.977 |
- 0.97 |
- 0.98 |
- 0.976 |
- 0.964 |
- 0.937 |
- 0.969 |
- 0.971 |
- 0.971 |
- 0.973 |
- 0.961 |
- 0.929 |
- 0.972 |
- 0.928 |
- 0.978 |
- 0.973 |
- 0.966 |
- 0.97 |
- 0.963 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.975 |
- 0.979 |
- 0.985 |
- 0.974 |
- 0.972 |
- 0.962 |
- 0.972 |
- 0.976 |
- 0.96 |
- 0.973 |
- 0.97 |
- 0.982 |
- 0.982 |
- 0.969 |
- 0.968 |
- 0.976 |
- 0.974 |
- 0.959 |
- 0.978 |
- 0.962 |
- 0.982 |
- 0.969 |
- 0.975 |
- 0.974 |
- 0.983 |
- 0.969 |
- 0.964 |
- 0.97 |
- 0.969 |
- 0.98 |
- 0.969 |
- 0.955 |
- 0.963 |
- 0.97 |
- 0.973 |
- 0.971 |
- 0.965 |
- 0.981 |
- 0.971 |
- 0.977 |
- 0.981 |
- 1 |
- 0.976 |
- 0.978 |
- 0.973 |
- 0.975 |
- 0.976 |
- 0.959 |
- 0.972 |
- 0.974 |
- 0.969 |
- 0.98 |
- 0.974 |
- 0.962 |
- 0.971 |
- 0.984 |
- 0.98 |
- 0.971 |
- 0.973 |
- 0.976 |
- 0.97 |
- 0.959 |
- 0.974 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.968 |
- 0.928 |
- 0.958 |
- 0.944 |
- |
- 0.919 |
- 0.97 |
-
-
- | Liver |
- 210 |
- F |
- 58 |
- 101613.09 |
- HF |
- BXD69 |
- H1087 |
- 0.985 |
- 0.927 |
- 0.928 |
- 0.983 |
- 0.979 |
- 0.982 |
- 0.985 |
- 0.962 |
- 0.892 |
- 0.982 |
- 0.971 |
- 0.98 |
- 0.973 |
- 0.982 |
- 0.971 |
- 0.98 |
- 0.968 |
- 0.964 |
- 0.979 |
- 0.976 |
- 0.978 |
- 0.985 |
- 0.981 |
- 0.985 |
- 0.981 |
- 0.969 |
- 0.969 |
- 0.971 |
- 0.979 |
- 0.984 |
- 0.98 |
- 0.988 |
- 0.944 |
- 0.967 |
- 0.976 |
- 0.974 |
- 0.938 |
- 0.979 |
- 0.976 |
- 0.978 |
- 0.98 |
- 0.973 |
- 0.972 |
- 0.979 |
- 0.978 |
- 0.945 |
- 0.977 |
- 0.978 |
- 0.982 |
- 0.982 |
- 0.982 |
- 0.957 |
- 0.972 |
- 0.976 |
- 0.981 |
- 0.984 |
- 0.975 |
- 0.974 |
- 0.982 |
- 0.979 |
- 0.974 |
- 0.959 |
- 0.979 |
- 0.899 |
- 0.972 |
- 0.971 |
- 0.971 |
- 0.98 |
- 0.968 |
- 0.945 |
- 0.978 |
- 0.941 |
- 0.981 |
- 0.985 |
- 0.979 |
- 0.979 |
- 0.965 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.983 |
- 0.977 |
- 0.978 |
- 0.983 |
- 0.961 |
- 0.981 |
- 0.983 |
- 0.972 |
- 0.985 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.976 |
- 0.975 |
- 0.984 |
- 0.976 |
- 0.974 |
- 0.978 |
- 0.977 |
- 0.981 |
- 0.98 |
- 0.975 |
- 0.977 |
- 0.978 |
- 0.98 |
- 0.97 |
- 0.98 |
- 0.977 |
- 0.984 |
- 0.952 |
- 0.967 |
- 0.978 |
- 0.968 |
- 0.983 |
- 0.971 |
- 0.979 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.988 |
- 0.976 |
- 1 |
- 0.975 |
- 0.983 |
- 0.984 |
- 0.983 |
- 0.967 |
- 0.978 |
- 0.981 |
- 0.98 |
- 0.984 |
- 0.976 |
- 0.973 |
- 0.98 |
- 0.978 |
- 0.98 |
- 0.981 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.931 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.987 |
- 0.981 |
- 0.941 |
- 0.968 |
- 0.947 |
- |
- 0.892 |
- 0.97 |
-
-
- | Liver |
- 528 |
- F |
- 109 |
- 121214.23 |
- HF |
- BXD69 |
- H1328 |
- 0.965 |
- 0.957 |
- 0.957 |
- 0.966 |
- 0.975 |
- 0.973 |
- 0.966 |
- 0.955 |
- 0.926 |
- 0.97 |
- 0.965 |
- 0.968 |
- 0.967 |
- 0.965 |
- 0.977 |
- 0.966 |
- 0.962 |
- 0.959 |
- 0.969 |
- 0.966 |
- 0.959 |
- 0.965 |
- 0.969 |
- 0.969 |
- 0.967 |
- 0.969 |
- 0.969 |
- 0.963 |
- 0.972 |
- 0.97 |
- 0.964 |
- 0.968 |
- 0.96 |
- 0.959 |
- 0.957 |
- 0.971 |
- 0.949 |
- 0.963 |
- 0.963 |
- 0.96 |
- 0.968 |
- 0.964 |
- 0.957 |
- 0.966 |
- 0.966 |
- 0.959 |
- 0.967 |
- 0.971 |
- 0.968 |
- 0.976 |
- 0.967 |
- 0.958 |
- 0.971 |
- 0.975 |
- 0.969 |
- 0.97 |
- 0.969 |
- 0.954 |
- 0.968 |
- 0.967 |
- 0.972 |
- 0.962 |
- 0.964 |
- 0.926 |
- 0.958 |
- 0.963 |
- 0.98 |
- 0.966 |
- 0.968 |
- 0.949 |
- 0.972 |
- 0.945 |
- 0.968 |
- 0.966 |
- 0.963 |
- 0.967 |
- 0.963 |
- 0.969 |
- 0.973 |
- 0.971 |
- 0.969 |
- 0.972 |
- 0.972 |
- 0.965 |
- 0.97 |
- 0.972 |
- 0.964 |
- 0.967 |
- 0.963 |
- 0.967 |
- 0.962 |
- 0.971 |
- 0.972 |
- 0.966 |
- 0.966 |
- 0.972 |
- 0.969 |
- 0.967 |
- 0.982 |
- 0.969 |
- 0.973 |
- 0.969 |
- 0.979 |
- 0.97 |
- 0.972 |
- 0.962 |
- 0.958 |
- 0.962 |
- 0.96 |
- 0.975 |
- 0.958 |
- 0.956 |
- 0.961 |
- 0.969 |
- 0.971 |
- 0.98 |
- 0.961 |
- 0.976 |
- 0.964 |
- 0.972 |
- 0.972 |
- 0.978 |
- 0.975 |
- 1 |
- 0.971 |
- 0.968 |
- 0.969 |
- 0.966 |
- 0.966 |
- 0.972 |
- 0.96 |
- 0.975 |
- 0.969 |
- 0.957 |
- 0.967 |
- 0.972 |
- 0.968 |
- 0.969 |
- 0.972 |
- 0.968 |
- 0.968 |
- 0.947 |
- 0.966 |
- 0.968 |
- 0.972 |
- 0.968 |
- 0.963 |
- 0.945 |
- 0.963 |
- 0.958 |
- |
- 0.926 |
- 0.97 |
-
-
- | Liver |
- 239 |
- F |
- 266 |
- 051012.08 |
- HF |
- BXD70 |
- H0188 |
- 0.986 |
- 0.936 |
- 0.938 |
- 0.984 |
- 0.982 |
- 0.981 |
- 0.985 |
- 0.974 |
- 0.901 |
- 0.979 |
- 0.971 |
- 0.986 |
- 0.977 |
- 0.981 |
- 0.973 |
- 0.978 |
- 0.977 |
- 0.968 |
- 0.983 |
- 0.981 |
- 0.976 |
- 0.985 |
- 0.987 |
- 0.987 |
- 0.984 |
- 0.978 |
- 0.979 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.985 |
- 0.982 |
- 0.946 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.951 |
- 0.987 |
- 0.988 |
- 0.986 |
- 0.981 |
- 0.979 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.955 |
- 0.977 |
- 0.98 |
- 0.986 |
- 0.984 |
- 0.988 |
- 0.978 |
- 0.983 |
- 0.978 |
- 0.989 |
- 0.983 |
- 0.982 |
- 0.973 |
- 0.985 |
- 0.984 |
- 0.976 |
- 0.96 |
- 0.987 |
- 0.898 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.983 |
- 0.972 |
- 0.954 |
- 0.985 |
- 0.954 |
- 0.982 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.988 |
- 0.989 |
- 0.982 |
- 0.981 |
- 0.97 |
- 0.976 |
- 0.983 |
- 0.97 |
- 0.984 |
- 0.987 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.984 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.986 |
- 0.983 |
- 0.98 |
- 0.984 |
- 0.983 |
- 0.98 |
- 0.985 |
- 0.977 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.985 |
- 0.952 |
- 0.98 |
- 0.985 |
- 0.974 |
- 0.987 |
- 0.979 |
- 0.987 |
- 0.976 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.973 |
- 0.983 |
- 0.971 |
- 1 |
- 0.992 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.99 |
- 0.985 |
- 0.985 |
- 0.983 |
- 0.98 |
- 0.983 |
- 0.976 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.986 |
- 0.99 |
- 0.929 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.987 |
- 0.985 |
- 0.954 |
- 0.976 |
- 0.952 |
- |
- 0.898 |
- 0.98 |
-
-
- | Liver |
- 578 |
- F |
- 294 |
- 121615.14 |
- HF |
- BXD70 |
- H1728 |
- 0.989 |
- 0.929 |
- 0.93 |
- 0.988 |
- 0.98 |
- 0.987 |
- 0.985 |
- 0.969 |
- 0.892 |
- 0.981 |
- 0.974 |
- 0.989 |
- 0.982 |
- 0.985 |
- 0.973 |
- 0.985 |
- 0.973 |
- 0.969 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.99 |
- 0.989 |
- 0.99 |
- 0.984 |
- 0.976 |
- 0.976 |
- 0.978 |
- 0.986 |
- 0.989 |
- 0.988 |
- 0.987 |
- 0.949 |
- 0.976 |
- 0.986 |
- 0.979 |
- 0.938 |
- 0.988 |
- 0.985 |
- 0.985 |
- 0.985 |
- 0.983 |
- 0.98 |
- 0.987 |
- 0.986 |
- 0.95 |
- 0.976 |
- 0.981 |
- 0.987 |
- 0.98 |
- 0.994 |
- 0.969 |
- 0.981 |
- 0.978 |
- 0.989 |
- 0.989 |
- 0.978 |
- 0.982 |
- 0.99 |
- 0.982 |
- 0.977 |
- 0.963 |
- 0.986 |
- 0.9 |
- 0.983 |
- 0.98 |
- 0.976 |
- 0.988 |
- 0.97 |
- 0.943 |
- 0.983 |
- 0.945 |
- 0.986 |
- 0.985 |
- 0.988 |
- 0.982 |
- 0.976 |
- 0.987 |
- 0.992 |
- 0.992 |
- 0.982 |
- 0.984 |
- 0.973 |
- 0.981 |
- 0.985 |
- 0.968 |
- 0.986 |
- 0.991 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.987 |
- 0.987 |
- 0.983 |
- 0.982 |
- 0.988 |
- 0.984 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.986 |
- 0.984 |
- 0.971 |
- 0.98 |
- 0.983 |
- 0.987 |
- 0.98 |
- 0.986 |
- 0.984 |
- 0.985 |
- 0.953 |
- 0.975 |
- 0.985 |
- 0.972 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.981 |
- 0.987 |
- 0.984 |
- 0.981 |
- 0.975 |
- 0.984 |
- 0.968 |
- 0.992 |
- 1 |
- 0.99 |
- 0.973 |
- 0.985 |
- 0.99 |
- 0.988 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.984 |
- 0.986 |
- 0.988 |
- 0.989 |
- 0.933 |
- 0.985 |
- 0.984 |
- 0.988 |
- 0.991 |
- 0.989 |
- 0.945 |
- 0.974 |
- 0.945 |
- |
- 0.892 |
- 0.98 |
-
-
- | Liver |
- 206 |
- F |
- 224 |
- 042015.18 |
- HF |
- BXD73 |
- H2071 |
- 0.988 |
- 0.93 |
- 0.931 |
- 0.987 |
- 0.979 |
- 0.989 |
- 0.982 |
- 0.965 |
- 0.892 |
- 0.98 |
- 0.975 |
- 0.987 |
- 0.98 |
- 0.982 |
- 0.975 |
- 0.987 |
- 0.97 |
- 0.964 |
- 0.984 |
- 0.985 |
- 0.986 |
- 0.989 |
- 0.985 |
- 0.987 |
- 0.978 |
- 0.971 |
- 0.971 |
- 0.976 |
- 0.985 |
- 0.991 |
- 0.985 |
- 0.987 |
- 0.951 |
- 0.971 |
- 0.98 |
- 0.976 |
- 0.934 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.985 |
- 0.981 |
- 0.977 |
- 0.985 |
- 0.982 |
- 0.948 |
- 0.975 |
- 0.979 |
- 0.987 |
- 0.98 |
- 0.99 |
- 0.961 |
- 0.979 |
- 0.98 |
- 0.991 |
- 0.991 |
- 0.975 |
- 0.983 |
- 0.99 |
- 0.979 |
- 0.98 |
- 0.965 |
- 0.982 |
- 0.903 |
- 0.982 |
- 0.979 |
- 0.972 |
- 0.985 |
- 0.965 |
- 0.935 |
- 0.977 |
- 0.937 |
- 0.986 |
- 0.982 |
- 0.983 |
- 0.979 |
- 0.969 |
- 0.986 |
- 0.988 |
- 0.988 |
- 0.982 |
- 0.984 |
- 0.975 |
- 0.982 |
- 0.982 |
- 0.964 |
- 0.982 |
- 0.989 |
- 0.974 |
- 0.987 |
- 0.982 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.973 |
- 0.978 |
- 0.976 |
- 0.986 |
- 0.985 |
- 0.969 |
- 0.979 |
- 0.983 |
- 0.986 |
- 0.977 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.951 |
- 0.97 |
- 0.982 |
- 0.971 |
- 0.98 |
- 0.972 |
- 0.983 |
- 0.979 |
- 0.985 |
- 0.981 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.969 |
- 0.985 |
- 0.99 |
- 1 |
- 0.972 |
- 0.989 |
- 0.99 |
- 0.986 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.98 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.986 |
- 0.988 |
- 0.936 |
- 0.984 |
- 0.98 |
- 0.989 |
- 0.988 |
- 0.987 |
- 0.937 |
- 0.969 |
- 0.94 |
- |
- 0.892 |
- 0.98 |
-
-
- | Liver |
- 361 |
- F |
- 196 |
- 121214.11 |
- HF |
- BXD73 |
- H1447 |
- 0.968 |
- 0.945 |
- 0.945 |
- 0.97 |
- 0.969 |
- 0.97 |
- 0.968 |
- 0.982 |
- 0.926 |
- 0.967 |
- 0.958 |
- 0.975 |
- 0.963 |
- 0.966 |
- 0.97 |
- 0.963 |
- 0.982 |
- 0.97 |
- 0.971 |
- 0.97 |
- 0.958 |
- 0.969 |
- 0.971 |
- 0.973 |
- 0.98 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.976 |
- 0.97 |
- 0.969 |
- 0.968 |
- 0.932 |
- 0.978 |
- 0.979 |
- 0.985 |
- 0.975 |
- 0.975 |
- 0.983 |
- 0.976 |
- 0.971 |
- 0.968 |
- 0.973 |
- 0.972 |
- 0.978 |
- 0.967 |
- 0.961 |
- 0.968 |
- 0.972 |
- 0.977 |
- 0.971 |
- 0.987 |
- 0.992 |
- 0.972 |
- 0.976 |
- 0.97 |
- 0.984 |
- 0.961 |
- 0.976 |
- 0.98 |
- 0.956 |
- 0.944 |
- 0.977 |
- 0.891 |
- 0.962 |
- 0.963 |
- 0.978 |
- 0.97 |
- 0.979 |
- 0.974 |
- 0.982 |
- 0.97 |
- 0.967 |
- 0.968 |
- 0.973 |
- 0.98 |
- 0.987 |
- 0.968 |
- 0.973 |
- 0.973 |
- 0.971 |
- 0.965 |
- 0.954 |
- 0.963 |
- 0.978 |
- 0.971 |
- 0.974 |
- 0.971 |
- 0.98 |
- 0.969 |
- 0.967 |
- 0.973 |
- 0.976 |
- 0.98 |
- 0.98 |
- 0.972 |
- 0.973 |
- 0.986 |
- 0.977 |
- 0.985 |
- 0.968 |
- 0.976 |
- 0.978 |
- 0.974 |
- 0.964 |
- 0.965 |
- 0.974 |
- 0.969 |
- 0.96 |
- 0.977 |
- 0.928 |
- 0.979 |
- 0.977 |
- 0.971 |
- 0.971 |
- 0.978 |
- 0.969 |
- 0.959 |
- 0.969 |
- 0.968 |
- 0.968 |
- 0.959 |
- 0.967 |
- 0.966 |
- 0.98 |
- 0.973 |
- 0.972 |
- 1 |
- 0.976 |
- 0.984 |
- 0.971 |
- 0.977 |
- 0.973 |
- 0.97 |
- 0.965 |
- 0.962 |
- 0.962 |
- 0.969 |
- 0.983 |
- 0.964 |
- 0.974 |
- 0.917 |
- 0.969 |
- 0.96 |
- 0.97 |
- 0.966 |
- 0.967 |
- 0.97 |
- 0.973 |
- 0.97 |
- |
- 0.891 |
- 0.97 |
-
-
- | Liver |
- 237 |
- F |
- 97 |
- 051112.14 |
- HF |
- BXD73b |
- H0183 |
- 0.982 |
- 0.935 |
- 0.936 |
- 0.983 |
- 0.974 |
- 0.984 |
- 0.976 |
- 0.97 |
- 0.904 |
- 0.975 |
- 0.971 |
- 0.982 |
- 0.974 |
- 0.978 |
- 0.971 |
- 0.981 |
- 0.978 |
- 0.964 |
- 0.983 |
- 0.983 |
- 0.977 |
- 0.983 |
- 0.979 |
- 0.98 |
- 0.976 |
- 0.971 |
- 0.971 |
- 0.975 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.982 |
- 0.947 |
- 0.974 |
- 0.982 |
- 0.979 |
- 0.942 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.98 |
- 0.979 |
- 0.979 |
- 0.978 |
- 0.976 |
- 0.948 |
- 0.968 |
- 0.974 |
- 0.981 |
- 0.975 |
- 0.984 |
- 0.964 |
- 0.979 |
- 0.978 |
- 0.99 |
- 0.985 |
- 0.974 |
- 0.981 |
- 0.988 |
- 0.979 |
- 0.973 |
- 0.963 |
- 0.979 |
- 0.903 |
- 0.976 |
- 0.976 |
- 0.973 |
- 0.979 |
- 0.964 |
- 0.939 |
- 0.974 |
- 0.942 |
- 0.98 |
- 0.976 |
- 0.98 |
- 0.979 |
- 0.975 |
- 0.981 |
- 0.984 |
- 0.985 |
- 0.974 |
- 0.979 |
- 0.969 |
- 0.977 |
- 0.976 |
- 0.969 |
- 0.975 |
- 0.983 |
- 0.978 |
- 0.981 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.986 |
- 0.986 |
- 0.978 |
- 0.982 |
- 0.974 |
- 0.978 |
- 0.976 |
- 0.982 |
- 0.979 |
- 0.971 |
- 0.977 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.978 |
- 0.979 |
- 0.985 |
- 0.941 |
- 0.974 |
- 0.982 |
- 0.971 |
- 0.975 |
- 0.973 |
- 0.982 |
- 0.975 |
- 0.978 |
- 0.975 |
- 0.977 |
- 0.972 |
- 0.978 |
- 0.966 |
- 0.983 |
- 0.985 |
- 0.989 |
- 0.976 |
- 1 |
- 0.988 |
- 0.987 |
- 0.985 |
- 0.982 |
- 0.981 |
- 0.975 |
- 0.978 |
- 0.979 |
- 0.978 |
- 0.981 |
- 0.982 |
- 0.984 |
- 0.932 |
- 0.979 |
- 0.975 |
- 0.982 |
- 0.984 |
- 0.982 |
- 0.942 |
- 0.971 |
- 0.943 |
- |
- 0.903 |
- 0.97 |
-
-
- | Liver |
- 474 |
- F |
- 256 |
- 050115.12 |
- HF |
- BXD73b |
- H1545 |
- 0.986 |
- 0.939 |
- 0.94 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.974 |
- 0.906 |
- 0.979 |
- 0.972 |
- 0.988 |
- 0.979 |
- 0.983 |
- 0.976 |
- 0.982 |
- 0.978 |
- 0.969 |
- 0.984 |
- 0.984 |
- 0.977 |
- 0.986 |
- 0.986 |
- 0.988 |
- 0.985 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.986 |
- 0.99 |
- 0.984 |
- 0.984 |
- 0.949 |
- 0.978 |
- 0.985 |
- 0.984 |
- 0.951 |
- 0.986 |
- 0.987 |
- 0.985 |
- 0.983 |
- 0.979 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.958 |
- 0.974 |
- 0.98 |
- 0.987 |
- 0.984 |
- 0.988 |
- 0.974 |
- 0.988 |
- 0.983 |
- 0.992 |
- 0.99 |
- 0.982 |
- 0.976 |
- 0.99 |
- 0.984 |
- 0.977 |
- 0.962 |
- 0.987 |
- 0.904 |
- 0.98 |
- 0.979 |
- 0.98 |
- 0.985 |
- 0.974 |
- 0.952 |
- 0.984 |
- 0.954 |
- 0.982 |
- 0.982 |
- 0.985 |
- 0.984 |
- 0.982 |
- 0.985 |
- 0.989 |
- 0.989 |
- 0.982 |
- 0.981 |
- 0.971 |
- 0.977 |
- 0.984 |
- 0.971 |
- 0.984 |
- 0.988 |
- 0.98 |
- 0.982 |
- 0.979 |
- 0.985 |
- 0.986 |
- 0.985 |
- 0.985 |
- 0.985 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.983 |
- 0.983 |
- 0.985 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.986 |
- 0.95 |
- 0.979 |
- 0.984 |
- 0.974 |
- 0.984 |
- 0.98 |
- 0.984 |
- 0.976 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.974 |
- 0.981 |
- 0.972 |
- 0.99 |
- 0.99 |
- 0.99 |
- 0.984 |
- 0.988 |
- 1 |
- 0.985 |
- 0.986 |
- 0.985 |
- 0.982 |
- 0.981 |
- 0.978 |
- 0.98 |
- 0.985 |
- 0.988 |
- 0.984 |
- 0.989 |
- 0.933 |
- 0.983 |
- 0.979 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.954 |
- 0.975 |
- 0.953 |
- |
- 0.904 |
- 0.98 |
-
-
- | Liver |
- 511 |
- F |
- 319 |
- 121615.19 |
- HF |
- BXD77 |
- H1866 |
- 0.986 |
- 0.922 |
- 0.924 |
- 0.986 |
- 0.973 |
- 0.983 |
- 0.981 |
- 0.968 |
- 0.889 |
- 0.977 |
- 0.971 |
- 0.982 |
- 0.977 |
- 0.983 |
- 0.967 |
- 0.978 |
- 0.975 |
- 0.962 |
- 0.985 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.978 |
- 0.969 |
- 0.969 |
- 0.974 |
- 0.985 |
- 0.982 |
- 0.987 |
- 0.982 |
- 0.944 |
- 0.975 |
- 0.988 |
- 0.976 |
- 0.932 |
- 0.984 |
- 0.984 |
- 0.987 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.941 |
- 0.97 |
- 0.977 |
- 0.982 |
- 0.975 |
- 0.986 |
- 0.962 |
- 0.975 |
- 0.973 |
- 0.987 |
- 0.982 |
- 0.979 |
- 0.981 |
- 0.987 |
- 0.98 |
- 0.972 |
- 0.96 |
- 0.981 |
- 0.895 |
- 0.98 |
- 0.981 |
- 0.972 |
- 0.985 |
- 0.963 |
- 0.937 |
- 0.976 |
- 0.936 |
- 0.984 |
- 0.981 |
- 0.984 |
- 0.98 |
- 0.973 |
- 0.984 |
- 0.988 |
- 0.989 |
- 0.977 |
- 0.982 |
- 0.969 |
- 0.979 |
- 0.979 |
- 0.967 |
- 0.983 |
- 0.988 |
- 0.979 |
- 0.98 |
- 0.986 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.982 |
- 0.971 |
- 0.976 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.967 |
- 0.976 |
- 0.98 |
- 0.987 |
- 0.984 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.946 |
- 0.973 |
- 0.986 |
- 0.971 |
- 0.977 |
- 0.972 |
- 0.984 |
- 0.978 |
- 0.982 |
- 0.979 |
- 0.978 |
- 0.969 |
- 0.98 |
- 0.96 |
- 0.985 |
- 0.988 |
- 0.986 |
- 0.971 |
- 0.987 |
- 0.985 |
- 1 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.977 |
- 0.977 |
- 0.981 |
- 0.98 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.928 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.985 |
- 0.985 |
- 0.936 |
- 0.971 |
- 0.937 |
- |
- 0.889 |
- 0.98 |
-
-
- | Liver |
- 571 |
- F |
- 24 |
- 061913.18 |
- HF |
- BXD79 |
- H0583 |
- 0.984 |
- 0.948 |
- 0.949 |
- 0.986 |
- 0.98 |
- 0.985 |
- 0.98 |
- 0.972 |
- 0.916 |
- 0.981 |
- 0.977 |
- 0.984 |
- 0.976 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.978 |
- 0.967 |
- 0.986 |
- 0.983 |
- 0.977 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.986 |
- 0.983 |
- 0.981 |
- 0.983 |
- 0.957 |
- 0.973 |
- 0.98 |
- 0.986 |
- 0.955 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.982 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.979 |
- 0.956 |
- 0.975 |
- 0.98 |
- 0.98 |
- 0.979 |
- 0.984 |
- 0.967 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.975 |
- 0.987 |
- 0.983 |
- 0.975 |
- 0.969 |
- 0.982 |
- 0.915 |
- 0.974 |
- 0.975 |
- 0.981 |
- 0.982 |
- 0.975 |
- 0.953 |
- 0.981 |
- 0.949 |
- 0.984 |
- 0.98 |
- 0.977 |
- 0.983 |
- 0.976 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.981 |
- 0.984 |
- 0.978 |
- 0.978 |
- 0.983 |
- 0.973 |
- 0.981 |
- 0.984 |
- 0.978 |
- 0.983 |
- 0.979 |
- 0.987 |
- 0.988 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.981 |
- 0.979 |
- 0.981 |
- 0.981 |
- 1 |
- 0.956 |
- 0.973 |
- 0.982 |
- 0.974 |
- 0.98 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.98 |
- 0.984 |
- 0.975 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.977 |
- 0.985 |
- 0.986 |
- 0.983 |
- 1 |
- 0.984 |
- 0.977 |
- 0.977 |
- 0.982 |
- 0.983 |
- 0.978 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.94 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.986 |
- 0.978 |
- 0.949 |
- 0.974 |
- 0.955 |
- |
- 0.915 |
- 0.98 |
-
-
- | Liver |
- 241 |
- F |
- 2 |
- 051012.14 |
- HF |
- BXD87 |
- H0243 |
- 0.984 |
- 0.942 |
- 0.945 |
- 0.984 |
- 0.976 |
- 0.983 |
- 0.977 |
- 0.965 |
- 0.904 |
- 0.977 |
- 0.979 |
- 0.983 |
- 0.975 |
- 0.978 |
- 0.974 |
- 0.979 |
- 0.973 |
- 0.965 |
- 0.985 |
- 0.984 |
- 0.974 |
- 0.986 |
- 0.982 |
- 0.983 |
- 0.976 |
- 0.974 |
- 0.975 |
- 0.978 |
- 0.985 |
- 0.98 |
- 0.979 |
- 0.978 |
- 0.959 |
- 0.972 |
- 0.979 |
- 0.98 |
- 0.937 |
- 0.983 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.985 |
- 0.978 |
- 0.944 |
- 0.972 |
- 0.976 |
- 0.983 |
- 0.978 |
- 0.984 |
- 0.96 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.98 |
- 0.978 |
- 0.975 |
- 0.984 |
- 0.979 |
- 0.974 |
- 0.973 |
- 0.981 |
- 0.911 |
- 0.977 |
- 0.975 |
- 0.981 |
- 0.982 |
- 0.963 |
- 0.94 |
- 0.98 |
- 0.939 |
- 0.984 |
- 0.977 |
- 0.973 |
- 0.979 |
- 0.975 |
- 0.984 |
- 0.987 |
- 0.987 |
- 0.981 |
- 0.985 |
- 0.975 |
- 0.98 |
- 0.984 |
- 0.972 |
- 0.98 |
- 0.982 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.984 |
- 0.986 |
- 1 |
- 0.971 |
- 0.98 |
- 0.975 |
- 0.985 |
- 0.986 |
- 0.976 |
- 0.975 |
- 0.981 |
- 0.978 |
- 0.982 |
- 0.986 |
- 0.981 |
- 0.984 |
- 0.95 |
- 0.97 |
- 0.982 |
- 0.969 |
- 0.977 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.976 |
- 0.974 |
- 0.976 |
- 0.969 |
- 0.983 |
- 0.984 |
- 0.983 |
- 0.973 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.984 |
- 1 |
- 0.978 |
- 0.976 |
- 0.981 |
- 0.987 |
- 0.977 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.938 |
- 0.986 |
- 0.983 |
- 0.985 |
- 0.984 |
- 0.974 |
- 0.939 |
- 0.977 |
- 0.941 |
- |
- 0.904 |
- 0.98 |
-
-
- | Liver |
- 512 |
- F |
- 326 |
- 121615.21 |
- HF |
- BXD87 |
- H1945 |
- 0.982 |
- 0.915 |
- 0.917 |
- 0.976 |
- 0.968 |
- 0.976 |
- 0.977 |
- 0.965 |
- 0.879 |
- 0.974 |
- 0.959 |
- 0.984 |
- 0.967 |
- 0.975 |
- 0.968 |
- 0.979 |
- 0.974 |
- 0.963 |
- 0.979 |
- 0.976 |
- 0.971 |
- 0.983 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.968 |
- 0.969 |
- 0.975 |
- 0.976 |
- 0.98 |
- 0.982 |
- 0.973 |
- 0.933 |
- 0.978 |
- 0.984 |
- 0.971 |
- 0.935 |
- 0.983 |
- 0.983 |
- 0.987 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.98 |
- 0.975 |
- 0.941 |
- 0.969 |
- 0.97 |
- 0.985 |
- 0.974 |
- 0.981 |
- 0.965 |
- 0.974 |
- 0.969 |
- 0.982 |
- 0.98 |
- 0.975 |
- 0.982 |
- 0.985 |
- 0.98 |
- 0.973 |
- 0.957 |
- 0.978 |
- 0.883 |
- 0.979 |
- 0.979 |
- 0.966 |
- 0.977 |
- 0.966 |
- 0.94 |
- 0.975 |
- 0.945 |
- 0.976 |
- 0.977 |
- 0.979 |
- 0.98 |
- 0.973 |
- 0.981 |
- 0.979 |
- 0.983 |
- 0.975 |
- 0.974 |
- 0.961 |
- 0.971 |
- 0.977 |
- 0.964 |
- 0.978 |
- 0.98 |
- 0.975 |
- 0.982 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.976 |
- 0.978 |
- 0.971 |
- 0.974 |
- 0.975 |
- 0.972 |
- 0.981 |
- 0.961 |
- 0.969 |
- 0.966 |
- 0.982 |
- 0.982 |
- 0.981 |
- 0.977 |
- 0.977 |
- 0.932 |
- 0.98 |
- 0.986 |
- 0.967 |
- 0.975 |
- 0.966 |
- 0.984 |
- 0.969 |
- 0.977 |
- 0.974 |
- 0.971 |
- 0.962 |
- 0.973 |
- 0.957 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.97 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.977 |
- 0.978 |
- 1 |
- 0.974 |
- 0.967 |
- 0.974 |
- 0.98 |
- 0.979 |
- 0.977 |
- 0.984 |
- 0.911 |
- 0.98 |
- 0.971 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.945 |
- 0.972 |
- 0.933 |
- |
- 0.879 |
- 0.97 |
-
-
- | Liver |
- 243 |
- F |
- 267 |
- 051112.01 |
- HF |
- BXD89 |
- H0176 |
- 0.986 |
- 0.921 |
- 0.923 |
- 0.982 |
- 0.983 |
- 0.978 |
- 0.987 |
- 0.954 |
- 0.88 |
- 0.981 |
- 0.966 |
- 0.979 |
- 0.977 |
- 0.981 |
- 0.967 |
- 0.973 |
- 0.965 |
- 0.956 |
- 0.975 |
- 0.974 |
- 0.969 |
- 0.983 |
- 0.986 |
- 0.985 |
- 0.976 |
- 0.966 |
- 0.967 |
- 0.968 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.98 |
- 0.941 |
- 0.972 |
- 0.974 |
- 0.97 |
- 0.932 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.979 |
- 0.975 |
- 0.976 |
- 0.981 |
- 0.975 |
- 0.944 |
- 0.982 |
- 0.975 |
- 0.982 |
- 0.978 |
- 0.98 |
- 0.96 |
- 0.971 |
- 0.978 |
- 0.986 |
- 0.981 |
- 0.973 |
- 0.97 |
- 0.978 |
- 0.976 |
- 0.98 |
- 0.966 |
- 0.98 |
- 0.896 |
- 0.98 |
- 0.981 |
- 0.97 |
- 0.98 |
- 0.962 |
- 0.938 |
- 0.976 |
- 0.941 |
- 0.98 |
- 0.987 |
- 0.978 |
- 0.976 |
- 0.965 |
- 0.988 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.981 |
- 0.971 |
- 0.975 |
- 0.979 |
- 0.958 |
- 0.981 |
- 0.983 |
- 0.965 |
- 0.979 |
- 0.973 |
- 0.976 |
- 0.975 |
- 0.97 |
- 0.97 |
- 0.985 |
- 0.976 |
- 0.965 |
- 0.977 |
- 0.969 |
- 0.978 |
- 0.976 |
- 0.969 |
- 0.977 |
- 0.976 |
- 0.981 |
- 0.97 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.953 |
- 0.967 |
- 0.973 |
- 0.962 |
- 0.988 |
- 0.97 |
- 0.983 |
- 0.978 |
- 0.977 |
- 0.983 |
- 0.985 |
- 0.971 |
- 0.98 |
- 0.967 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.965 |
- 0.975 |
- 0.981 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.974 |
- 1 |
- 0.977 |
- 0.98 |
- 0.988 |
- 0.982 |
- 0.982 |
- 0.986 |
- 0.926 |
- 0.984 |
- 0.976 |
- 0.983 |
- 0.982 |
- 0.978 |
- 0.941 |
- 0.967 |
- 0.939 |
- |
- 0.88 |
- 0.97 |
-
-
- | Liver |
- 539 |
- F |
- 282 |
- 101014.04 |
- HF |
- BXD89 |
- H1321 |
- 0.98 |
- 0.946 |
- 0.948 |
- 0.984 |
- 0.981 |
- 0.988 |
- 0.975 |
- 0.955 |
- 0.918 |
- 0.977 |
- 0.983 |
- 0.975 |
- 0.978 |
- 0.976 |
- 0.975 |
- 0.982 |
- 0.969 |
- 0.958 |
- 0.982 |
- 0.98 |
- 0.976 |
- 0.979 |
- 0.976 |
- 0.979 |
- 0.968 |
- 0.97 |
- 0.97 |
- 0.966 |
- 0.983 |
- 0.98 |
- 0.976 |
- 0.98 |
- 0.966 |
- 0.96 |
- 0.969 |
- 0.978 |
- 0.928 |
- 0.973 |
- 0.968 |
- 0.969 |
- 0.978 |
- 0.976 |
- 0.968 |
- 0.979 |
- 0.973 |
- 0.947 |
- 0.974 |
- 0.977 |
- 0.975 |
- 0.972 |
- 0.982 |
- 0.948 |
- 0.971 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.972 |
- 0.971 |
- 0.981 |
- 0.971 |
- 0.977 |
- 0.98 |
- 0.972 |
- 0.927 |
- 0.977 |
- 0.975 |
- 0.975 |
- 0.979 |
- 0.962 |
- 0.929 |
- 0.972 |
- 0.927 |
- 0.985 |
- 0.975 |
- 0.971 |
- 0.971 |
- 0.964 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.974 |
- 0.983 |
- 0.985 |
- 0.98 |
- 0.977 |
- 0.963 |
- 0.975 |
- 0.98 |
- 0.965 |
- 0.976 |
- 0.976 |
- 0.983 |
- 0.983 |
- 0.973 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.961 |
- 0.976 |
- 0.965 |
- 0.989 |
- 0.975 |
- 0.975 |
- 0.974 |
- 0.986 |
- 0.976 |
- 0.968 |
- 0.977 |
- 0.976 |
- 0.982 |
- 0.958 |
- 0.954 |
- 0.968 |
- 0.971 |
- 0.973 |
- 0.975 |
- 0.97 |
- 0.984 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.984 |
- 0.978 |
- 0.972 |
- 0.976 |
- 0.981 |
- 0.982 |
- 0.962 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.982 |
- 0.981 |
- 0.967 |
- 0.977 |
- 1 |
- 0.983 |
- 0.973 |
- 0.979 |
- 0.98 |
- 0.976 |
- 0.96 |
- 0.977 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.973 |
- 0.927 |
- 0.966 |
- 0.944 |
- |
- 0.918 |
- 0.97 |
-
-
- | Liver |
- 548 |
- F |
- 312 |
- 082214.09 |
- HF |
- BXD9 |
- H1009 |
- 0.987 |
- 0.932 |
- 0.936 |
- 0.985 |
- 0.979 |
- 0.984 |
- 0.981 |
- 0.949 |
- 0.889 |
- 0.98 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.968 |
- 0.98 |
- 0.964 |
- 0.956 |
- 0.987 |
- 0.982 |
- 0.976 |
- 0.985 |
- 0.982 |
- 0.983 |
- 0.97 |
- 0.965 |
- 0.966 |
- 0.966 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.961 |
- 0.966 |
- 0.974 |
- 0.973 |
- 0.922 |
- 0.981 |
- 0.973 |
- 0.978 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.984 |
- 0.972 |
- 0.936 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.977 |
- 0.981 |
- 0.949 |
- 0.969 |
- 0.978 |
- 0.983 |
- 0.982 |
- 0.97 |
- 0.972 |
- 0.983 |
- 0.975 |
- 0.979 |
- 0.976 |
- 0.98 |
- 0.918 |
- 0.979 |
- 0.979 |
- 0.974 |
- 0.981 |
- 0.955 |
- 0.926 |
- 0.973 |
- 0.927 |
- 0.985 |
- 0.981 |
- 0.972 |
- 0.975 |
- 0.963 |
- 0.988 |
- 0.987 |
- 0.987 |
- 0.979 |
- 0.987 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.964 |
- 0.98 |
- 0.985 |
- 0.962 |
- 0.98 |
- 0.982 |
- 0.987 |
- 0.985 |
- 0.975 |
- 0.974 |
- 0.984 |
- 0.987 |
- 0.961 |
- 0.979 |
- 0.968 |
- 0.986 |
- 0.979 |
- 0.97 |
- 0.974 |
- 0.982 |
- 0.981 |
- 0.975 |
- 0.986 |
- 0.987 |
- 0.983 |
- 0.961 |
- 0.961 |
- 0.975 |
- 0.963 |
- 0.979 |
- 0.974 |
- 0.982 |
- 0.986 |
- 0.981 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.968 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.962 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.983 |
- 0.987 |
- 0.974 |
- 0.98 |
- 0.983 |
- 1 |
- 0.979 |
- 0.979 |
- 0.987 |
- 0.98 |
- 0.941 |
- 0.987 |
- 0.987 |
- 0.984 |
- 0.985 |
- 0.975 |
- 0.927 |
- 0.971 |
- 0.93 |
- |
- 0.889 |
- 0.97 |
-
-
- | Liver |
- 218 |
- F |
- 297 |
- 101613.19 |
- HF |
- BXD90 |
- H1093 |
- 0.985 |
- 0.922 |
- 0.924 |
- 0.98 |
- 0.985 |
- 0.979 |
- 0.988 |
- 0.961 |
- 0.884 |
- 0.981 |
- 0.965 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.973 |
- 0.976 |
- 0.967 |
- 0.962 |
- 0.977 |
- 0.975 |
- 0.972 |
- 0.983 |
- 0.988 |
- 0.986 |
- 0.979 |
- 0.97 |
- 0.97 |
- 0.972 |
- 0.98 |
- 0.983 |
- 0.985 |
- 0.981 |
- 0.94 |
- 0.977 |
- 0.978 |
- 0.972 |
- 0.937 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.983 |
- 0.979 |
- 0.95 |
- 0.98 |
- 0.976 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.965 |
- 0.973 |
- 0.977 |
- 0.987 |
- 0.983 |
- 0.974 |
- 0.973 |
- 0.981 |
- 0.979 |
- 0.981 |
- 0.96 |
- 0.981 |
- 0.892 |
- 0.982 |
- 0.985 |
- 0.973 |
- 0.98 |
- 0.966 |
- 0.943 |
- 0.977 |
- 0.948 |
- 0.98 |
- 0.988 |
- 0.984 |
- 0.979 |
- 0.969 |
- 0.988 |
- 0.983 |
- 0.987 |
- 0.983 |
- 0.982 |
- 0.971 |
- 0.976 |
- 0.98 |
- 0.963 |
- 0.981 |
- 0.986 |
- 0.971 |
- 0.981 |
- 0.975 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.974 |
- 0.986 |
- 0.977 |
- 0.97 |
- 0.981 |
- 0.974 |
- 0.977 |
- 0.981 |
- 0.97 |
- 0.982 |
- 0.978 |
- 0.984 |
- 0.972 |
- 0.98 |
- 0.98 |
- 0.978 |
- 0.951 |
- 0.975 |
- 0.978 |
- 0.968 |
- 0.991 |
- 0.973 |
- 0.987 |
- 0.978 |
- 0.98 |
- 0.984 |
- 0.982 |
- 0.971 |
- 0.981 |
- 0.969 |
- 0.987 |
- 0.984 |
- 0.983 |
- 0.969 |
- 0.978 |
- 0.985 |
- 0.98 |
- 0.978 |
- 0.977 |
- 0.98 |
- 0.988 |
- 0.973 |
- 0.979 |
- 1 |
- 0.987 |
- 0.985 |
- 0.988 |
- 0.923 |
- 0.983 |
- 0.979 |
- 0.983 |
- 0.985 |
- 0.985 |
- 0.948 |
- 0.97 |
- 0.944 |
- |
- 0.884 |
- 0.97 |
-
-
- | Liver |
- 570 |
- F |
- 274 |
- 062013.03 |
- HF |
- BXD90 |
- H0736 |
- 0.983 |
- 0.941 |
- 0.943 |
- 0.983 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.973 |
- 0.91 |
- 0.982 |
- 0.972 |
- 0.984 |
- 0.981 |
- 0.981 |
- 0.977 |
- 0.976 |
- 0.981 |
- 0.974 |
- 0.984 |
- 0.982 |
- 0.97 |
- 0.982 |
- 0.987 |
- 0.986 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.983 |
- 0.978 |
- 0.951 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.953 |
- 0.983 |
- 0.983 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.986 |
- 0.985 |
- 0.961 |
- 0.977 |
- 0.978 |
- 0.982 |
- 0.981 |
- 0.984 |
- 0.975 |
- 0.987 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.984 |
- 0.974 |
- 0.985 |
- 0.983 |
- 0.976 |
- 0.968 |
- 0.983 |
- 0.902 |
- 0.984 |
- 0.986 |
- 0.987 |
- 0.982 |
- 0.976 |
- 0.957 |
- 0.984 |
- 0.959 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.984 |
- 0.985 |
- 0.987 |
- 0.988 |
- 0.98 |
- 0.981 |
- 0.971 |
- 0.98 |
- 0.985 |
- 0.976 |
- 0.985 |
- 0.987 |
- 0.98 |
- 0.977 |
- 0.98 |
- 0.985 |
- 0.986 |
- 0.98 |
- 0.98 |
- 0.988 |
- 0.985 |
- 0.978 |
- 0.986 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.981 |
- 0.981 |
- 0.982 |
- 0.978 |
- 0.983 |
- 0.95 |
- 0.977 |
- 0.979 |
- 0.973 |
- 0.985 |
- 0.987 |
- 0.983 |
- 0.98 |
- 0.982 |
- 0.986 |
- 0.979 |
- 0.973 |
- 0.976 |
- 0.972 |
- 0.987 |
- 0.986 |
- 0.981 |
- 0.983 |
- 0.981 |
- 0.988 |
- 0.981 |
- 0.983 |
- 0.985 |
- 0.979 |
- 0.982 |
- 0.979 |
- 0.979 |
- 0.987 |
- 1 |
- 0.982 |
- 0.986 |
- 0.931 |
- 0.983 |
- 0.979 |
- 0.983 |
- 0.983 |
- 0.98 |
- 0.959 |
- 0.981 |
- 0.96 |
- |
- 0.902 |
- 0.98 |
-
-
- | Liver |
- 562 |
- F |
- 325 |
- 062013.19 |
- HF |
- BXD91 |
- H0881 |
- 0.988 |
- 0.928 |
- 0.931 |
- 0.986 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.955 |
- 0.888 |
- 0.979 |
- 0.977 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.97 |
- 0.98 |
- 0.964 |
- 0.954 |
- 0.984 |
- 0.983 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.973 |
- 0.967 |
- 0.968 |
- 0.969 |
- 0.984 |
- 0.985 |
- 0.988 |
- 0.982 |
- 0.957 |
- 0.97 |
- 0.978 |
- 0.973 |
- 0.925 |
- 0.984 |
- 0.978 |
- 0.982 |
- 0.981 |
- 0.982 |
- 0.978 |
- 0.985 |
- 0.976 |
- 0.94 |
- 0.978 |
- 0.978 |
- 0.986 |
- 0.98 |
- 0.984 |
- 0.955 |
- 0.971 |
- 0.978 |
- 0.988 |
- 0.985 |
- 0.97 |
- 0.975 |
- 0.984 |
- 0.976 |
- 0.98 |
- 0.97 |
- 0.98 |
- 0.907 |
- 0.981 |
- 0.983 |
- 0.974 |
- 0.982 |
- 0.958 |
- 0.929 |
- 0.974 |
- 0.933 |
- 0.987 |
- 0.984 |
- 0.98 |
- 0.976 |
- 0.965 |
- 0.99 |
- 0.989 |
- 0.99 |
- 0.979 |
- 0.986 |
- 0.978 |
- 0.981 |
- 0.978 |
- 0.964 |
- 0.981 |
- 0.988 |
- 0.968 |
- 0.978 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.978 |
- 0.977 |
- 0.983 |
- 0.983 |
- 0.966 |
- 0.982 |
- 0.972 |
- 0.986 |
- 0.981 |
- 0.966 |
- 0.978 |
- 0.985 |
- 0.988 |
- 0.975 |
- 0.986 |
- 0.988 |
- 0.982 |
- 0.963 |
- 0.967 |
- 0.979 |
- 0.968 |
- 0.982 |
- 0.974 |
- 0.987 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.98 |
- 0.976 |
- 0.981 |
- 0.968 |
- 0.986 |
- 0.988 |
- 0.986 |
- 0.964 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.982 |
- 0.983 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.987 |
- 0.985 |
- 0.982 |
- 1 |
- 0.988 |
- 0.938 |
- 0.987 |
- 0.991 |
- 0.987 |
- 0.99 |
- 0.984 |
- 0.933 |
- 0.967 |
- 0.931 |
- |
- 0.888 |
- 0.98 |
-
-
- | Liver |
- 213 |
- F |
- 288 |
- 101613.21 |
- HF |
- BXD95 |
- H1275 |
- 0.988 |
- 0.929 |
- 0.931 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.985 |
- 0.97 |
- 0.892 |
- 0.98 |
- 0.968 |
- 0.988 |
- 0.977 |
- 0.982 |
- 0.972 |
- 0.981 |
- 0.973 |
- 0.965 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.988 |
- 0.987 |
- 0.986 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.98 |
- 0.983 |
- 0.985 |
- 0.987 |
- 0.983 |
- 0.943 |
- 0.98 |
- 0.985 |
- 0.977 |
- 0.944 |
- 0.987 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.979 |
- 0.981 |
- 0.984 |
- 0.982 |
- 0.954 |
- 0.976 |
- 0.977 |
- 0.988 |
- 0.982 |
- 0.986 |
- 0.97 |
- 0.978 |
- 0.977 |
- 0.989 |
- 0.985 |
- 0.979 |
- 0.978 |
- 0.986 |
- 0.982 |
- 0.977 |
- 0.962 |
- 0.986 |
- 0.897 |
- 0.982 |
- 0.98 |
- 0.974 |
- 0.986 |
- 0.97 |
- 0.946 |
- 0.981 |
- 0.951 |
- 0.983 |
- 0.985 |
- 0.985 |
- 0.982 |
- 0.974 |
- 0.987 |
- 0.987 |
- 0.988 |
- 0.982 |
- 0.981 |
- 0.969 |
- 0.977 |
- 0.982 |
- 0.965 |
- 0.983 |
- 0.988 |
- 0.977 |
- 0.984 |
- 0.977 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.982 |
- 0.976 |
- 0.981 |
- 0.98 |
- 0.981 |
- 0.986 |
- 0.971 |
- 0.981 |
- 0.978 |
- 0.986 |
- 0.979 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.948 |
- 0.978 |
- 0.984 |
- 0.97 |
- 0.985 |
- 0.974 |
- 0.989 |
- 0.976 |
- 0.982 |
- 0.982 |
- 0.981 |
- 0.97 |
- 0.981 |
- 0.968 |
- 0.99 |
- 0.989 |
- 0.988 |
- 0.974 |
- 0.984 |
- 0.989 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.976 |
- 0.98 |
- 0.988 |
- 0.986 |
- 0.988 |
- 1 |
- 0.929 |
- 0.985 |
- 0.98 |
- 0.987 |
- 0.988 |
- 0.987 |
- 0.951 |
- 0.972 |
- 0.944 |
- |
- 0.892 |
- 0.98 |
-
-
- | Liver |
- 550 |
- F |
- 236 |
- 102414.20 |
- HF |
- BXD95 |
- H1273 |
- 0.925 |
- 0.95 |
- 0.95 |
- 0.935 |
- 0.941 |
- 0.951 |
- 0.921 |
- 0.908 |
- 0.939 |
- 0.932 |
- 0.955 |
- 0.928 |
- 0.944 |
- 0.932 |
- 0.942 |
- 0.942 |
- 0.921 |
- 0.914 |
- 0.94 |
- 0.938 |
- 0.932 |
- 0.928 |
- 0.926 |
- 0.929 |
- 0.919 |
- 0.928 |
- 0.928 |
- 0.92 |
- 0.941 |
- 0.933 |
- 0.924 |
- 0.934 |
- 0.964 |
- 0.909 |
- 0.913 |
- 0.938 |
- 0.893 |
- 0.922 |
- 0.916 |
- 0.917 |
- 0.932 |
- 0.927 |
- 0.916 |
- 0.929 |
- 0.924 |
- 0.917 |
- 0.929 |
- 0.942 |
- 0.924 |
- 0.924 |
- 0.934 |
- 0.899 |
- 0.927 |
- 0.942 |
- 0.93 |
- 0.933 |
- 0.924 |
- 0.919 |
- 0.934 |
- 0.918 |
- 0.941 |
- 0.947 |
- 0.923 |
- 0.952 |
- 0.93 |
- 0.929 |
- 0.941 |
- 0.937 |
- 0.925 |
- 0.886 |
- 0.925 |
- 0.89 |
- 0.941 |
- 0.921 |
- 0.922 |
- 0.918 |
- 0.916 |
- 0.929 |
- 0.942 |
- 0.935 |
- 0.926 |
- 0.94 |
- 0.96 |
- 0.938 |
- 0.928 |
- 0.933 |
- 0.924 |
- 0.931 |
- 0.922 |
- 0.927 |
- 0.928 |
- 0.942 |
- 0.942 |
- 0.926 |
- 0.925 |
- 0.936 |
- 0.938 |
- 0.915 |
- 0.939 |
- 0.917 |
- 0.948 |
- 0.928 |
- 0.939 |
- 0.933 |
- 0.952 |
- 0.923 |
- 0.92 |
- 0.929 |
- 0.932 |
- 0.94 |
- 0.954 |
- 0.901 |
- 0.917 |
- 0.936 |
- 0.923 |
- 0.941 |
- 0.919 |
- 0.944 |
- 0.928 |
- 0.932 |
- 0.935 |
- 0.959 |
- 0.931 |
- 0.947 |
- 0.929 |
- 0.933 |
- 0.936 |
- 0.917 |
- 0.932 |
- 0.933 |
- 0.928 |
- 0.94 |
- 0.938 |
- 0.911 |
- 0.926 |
- 0.96 |
- 0.941 |
- 0.923 |
- 0.931 |
- 0.938 |
- 0.929 |
- 1 |
- 0.926 |
- 0.945 |
- 0.939 |
- 0.933 |
- 0.923 |
- 0.89 |
- 0.918 |
- 0.913 |
- |
- 0.886 |
- 0.93 |
-
-
- | Liver |
- 182 |
- F |
- 305 |
- 050914.05 |
- HF |
- BXD99 |
- H1355 |
- 0.99 |
- 0.922 |
- 0.924 |
- 0.985 |
- 0.98 |
- 0.981 |
- 0.988 |
- 0.958 |
- 0.88 |
- 0.982 |
- 0.973 |
- 0.982 |
- 0.978 |
- 0.981 |
- 0.968 |
- 0.976 |
- 0.967 |
- 0.957 |
- 0.983 |
- 0.982 |
- 0.975 |
- 0.986 |
- 0.987 |
- 0.986 |
- 0.974 |
- 0.97 |
- 0.971 |
- 0.972 |
- 0.985 |
- 0.984 |
- 0.985 |
- 0.98 |
- 0.948 |
- 0.977 |
- 0.98 |
- 0.974 |
- 0.931 |
- 0.988 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.985 |
- 0.981 |
- 0.988 |
- 0.979 |
- 0.94 |
- 0.985 |
- 0.982 |
- 0.987 |
- 0.983 |
- 0.984 |
- 0.96 |
- 0.974 |
- 0.979 |
- 0.986 |
- 0.984 |
- 0.974 |
- 0.976 |
- 0.983 |
- 0.983 |
- 0.978 |
- 0.968 |
- 0.979 |
- 0.899 |
- 0.979 |
- 0.981 |
- 0.973 |
- 0.983 |
- 0.958 |
- 0.936 |
- 0.983 |
- 0.932 |
- 0.986 |
- 0.988 |
- 0.979 |
- 0.983 |
- 0.97 |
- 0.991 |
- 0.985 |
- 0.988 |
- 0.986 |
- 0.987 |
- 0.972 |
- 0.982 |
- 0.983 |
- 0.961 |
- 0.985 |
- 0.988 |
- 0.967 |
- 0.982 |
- 0.982 |
- 0.983 |
- 0.982 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.986 |
- 0.967 |
- 0.98 |
- 0.972 |
- 0.981 |
- 0.983 |
- 0.968 |
- 0.975 |
- 0.98 |
- 0.985 |
- 0.981 |
- 0.988 |
- 0.983 |
- 0.981 |
- 0.953 |
- 0.972 |
- 0.981 |
- 0.968 |
- 0.981 |
- 0.973 |
- 0.985 |
- 0.982 |
- 0.984 |
- 0.987 |
- 0.983 |
- 0.974 |
- 0.979 |
- 0.966 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.969 |
- 0.979 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.986 |
- 0.98 |
- 0.984 |
- 0.977 |
- 0.987 |
- 0.983 |
- 0.983 |
- 0.987 |
- 0.985 |
- 0.926 |
- 1 |
- 0.984 |
- 0.984 |
- 0.986 |
- 0.981 |
- 0.932 |
- 0.97 |
- 0.933 |
- |
- 0.88 |
- 0.98 |
-
-
- | Liver |
- 544 |
- F |
- 309 |
- 062013.09 |
- HF |
- C57BL/6J |
- H0514 |
- 0.984 |
- 0.933 |
- 0.936 |
- 0.983 |
- 0.978 |
- 0.982 |
- 0.981 |
- 0.949 |
- 0.894 |
- 0.979 |
- 0.982 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.967 |
- 0.977 |
- 0.961 |
- 0.952 |
- 0.984 |
- 0.979 |
- 0.975 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.968 |
- 0.967 |
- 0.968 |
- 0.964 |
- 0.983 |
- 0.98 |
- 0.983 |
- 0.977 |
- 0.964 |
- 0.965 |
- 0.972 |
- 0.972 |
- 0.919 |
- 0.981 |
- 0.972 |
- 0.978 |
- 0.978 |
- 0.979 |
- 0.975 |
- 0.984 |
- 0.972 |
- 0.934 |
- 0.976 |
- 0.979 |
- 0.98 |
- 0.974 |
- 0.98 |
- 0.947 |
- 0.968 |
- 0.975 |
- 0.981 |
- 0.98 |
- 0.967 |
- 0.969 |
- 0.98 |
- 0.97 |
- 0.975 |
- 0.971 |
- 0.976 |
- 0.915 |
- 0.977 |
- 0.978 |
- 0.975 |
- 0.979 |
- 0.955 |
- 0.927 |
- 0.971 |
- 0.93 |
- 0.989 |
- 0.981 |
- 0.974 |
- 0.97 |
- 0.959 |
- 0.986 |
- 0.988 |
- 0.989 |
- 0.978 |
- 0.986 |
- 0.981 |
- 0.983 |
- 0.977 |
- 0.963 |
- 0.979 |
- 0.984 |
- 0.964 |
- 0.974 |
- 0.976 |
- 0.984 |
- 0.982 |
- 0.973 |
- 0.972 |
- 0.982 |
- 0.983 |
- 0.959 |
- 0.979 |
- 0.965 |
- 0.985 |
- 0.979 |
- 0.968 |
- 0.975 |
- 0.985 |
- 0.983 |
- 0.973 |
- 0.985 |
- 0.985 |
- 0.981 |
- 0.969 |
- 0.962 |
- 0.975 |
- 0.967 |
- 0.978 |
- 0.975 |
- 0.983 |
- 0.985 |
- 0.979 |
- 0.982 |
- 0.978 |
- 0.977 |
- 0.978 |
- 0.968 |
- 0.982 |
- 0.984 |
- 0.98 |
- 0.96 |
- 0.975 |
- 0.979 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.971 |
- 0.976 |
- 0.98 |
- 0.987 |
- 0.979 |
- 0.979 |
- 0.991 |
- 0.98 |
- 0.945 |
- 0.984 |
- 1 |
- 0.986 |
- 0.986 |
- 0.976 |
- 0.93 |
- 0.965 |
- 0.926 |
- |
- 0.894 |
- 0.97 |
-
-
- | Liver |
- 182 |
- F |
- 235 |
- 102414.06 |
- HF |
- C57BL/6J |
- H1681 |
- 0.988 |
- 0.934 |
- 0.935 |
- 0.989 |
- 0.982 |
- 0.988 |
- 0.987 |
- 0.966 |
- 0.895 |
- 0.985 |
- 0.977 |
- 0.987 |
- 0.984 |
- 0.985 |
- 0.976 |
- 0.983 |
- 0.968 |
- 0.965 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.989 |
- 0.987 |
- 0.988 |
- 0.981 |
- 0.976 |
- 0.975 |
- 0.978 |
- 0.987 |
- 0.987 |
- 0.986 |
- 0.989 |
- 0.953 |
- 0.974 |
- 0.98 |
- 0.979 |
- 0.936 |
- 0.986 |
- 0.98 |
- 0.982 |
- 0.989 |
- 0.982 |
- 0.978 |
- 0.988 |
- 0.984 |
- 0.951 |
- 0.978 |
- 0.981 |
- 0.984 |
- 0.979 |
- 0.989 |
- 0.961 |
- 0.978 |
- 0.978 |
- 0.986 |
- 0.987 |
- 0.978 |
- 0.981 |
- 0.986 |
- 0.978 |
- 0.976 |
- 0.966 |
- 0.986 |
- 0.906 |
- 0.982 |
- 0.977 |
- 0.978 |
- 0.986 |
- 0.969 |
- 0.944 |
- 0.981 |
- 0.944 |
- 0.993 |
- 0.987 |
- 0.983 |
- 0.978 |
- 0.966 |
- 0.988 |
- 0.991 |
- 0.989 |
- 0.986 |
- 0.986 |
- 0.977 |
- 0.985 |
- 0.988 |
- 0.966 |
- 0.986 |
- 0.988 |
- 0.976 |
- 0.986 |
- 0.977 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.988 |
- 0.985 |
- 0.973 |
- 0.981 |
- 0.976 |
- 0.988 |
- 0.987 |
- 0.976 |
- 0.982 |
- 0.986 |
- 0.986 |
- 0.977 |
- 0.988 |
- 0.982 |
- 0.986 |
- 0.957 |
- 0.971 |
- 0.982 |
- 0.973 |
- 0.984 |
- 0.978 |
- 0.984 |
- 0.984 |
- 0.989 |
- 0.986 |
- 0.985 |
- 0.977 |
- 0.985 |
- 0.972 |
- 0.985 |
- 0.988 |
- 0.989 |
- 0.97 |
- 0.982 |
- 0.986 |
- 0.982 |
- 0.986 |
- 0.985 |
- 0.976 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.983 |
- 0.987 |
- 0.987 |
- 0.939 |
- 0.984 |
- 0.986 |
- 1 |
- 0.989 |
- 0.985 |
- 0.944 |
- 0.969 |
- 0.943 |
- |
- 0.895 |
- 0.98 |
-
-
- | Liver |
- 214 |
- F |
- 301 |
- 101713.20 |
- HF |
- D2B6F1 |
- H1150 |
- 0.99 |
- 0.927 |
- 0.928 |
- 0.988 |
- 0.98 |
- 0.985 |
- 0.989 |
- 0.963 |
- 0.889 |
- 0.983 |
- 0.975 |
- 0.986 |
- 0.979 |
- 0.983 |
- 0.973 |
- 0.984 |
- 0.969 |
- 0.966 |
- 0.984 |
- 0.983 |
- 0.985 |
- 0.988 |
- 0.987 |
- 0.987 |
- 0.979 |
- 0.971 |
- 0.971 |
- 0.973 |
- 0.984 |
- 0.987 |
- 0.988 |
- 0.987 |
- 0.95 |
- 0.972 |
- 0.981 |
- 0.976 |
- 0.932 |
- 0.986 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.977 |
- 0.986 |
- 0.981 |
- 0.945 |
- 0.979 |
- 0.979 |
- 0.984 |
- 0.98 |
- 0.988 |
- 0.959 |
- 0.973 |
- 0.975 |
- 0.987 |
- 0.987 |
- 0.974 |
- 0.983 |
- 0.986 |
- 0.979 |
- 0.978 |
- 0.967 |
- 0.984 |
- 0.901 |
- 0.98 |
- 0.979 |
- 0.974 |
- 0.984 |
- 0.964 |
- 0.938 |
- 0.978 |
- 0.941 |
- 0.988 |
- 0.989 |
- 0.987 |
- 0.979 |
- 0.967 |
- 0.991 |
- 0.99 |
- 0.992 |
- 0.982 |
- 0.986 |
- 0.977 |
- 0.983 |
- 0.983 |
- 0.966 |
- 0.983 |
- 0.99 |
- 0.974 |
- 0.986 |
- 0.982 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.987 |
- 0.984 |
- 0.973 |
- 0.982 |
- 0.977 |
- 0.984 |
- 0.985 |
- 0.969 |
- 0.98 |
- 0.984 |
- 0.988 |
- 0.976 |
- 0.986 |
- 0.984 |
- 0.986 |
- 0.955 |
- 0.971 |
- 0.983 |
- 0.971 |
- 0.984 |
- 0.974 |
- 0.988 |
- 0.983 |
- 0.985 |
- 0.985 |
- 0.985 |
- 0.976 |
- 0.987 |
- 0.968 |
- 0.987 |
- 0.991 |
- 0.988 |
- 0.966 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.986 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.985 |
- 0.985 |
- 0.983 |
- 0.99 |
- 0.988 |
- 0.933 |
- 0.986 |
- 0.986 |
- 0.989 |
- 1 |
- 0.989 |
- 0.941 |
- 0.972 |
- 0.941 |
- |
- 0.889 |
- 0.98 |
-
-
- | Liver |
- 540 |
- F |
- 291 |
- 062013.13 |
- HF |
- D2B6F1 |
- H0642 |
- 0.984 |
- 0.917 |
- 0.917 |
- 0.982 |
- 0.976 |
- 0.983 |
- 0.986 |
- 0.97 |
- 0.882 |
- 0.976 |
- 0.963 |
- 0.985 |
- 0.975 |
- 0.978 |
- 0.97 |
- 0.98 |
- 0.967 |
- 0.965 |
- 0.977 |
- 0.978 |
- 0.986 |
- 0.985 |
- 0.987 |
- 0.983 |
- 0.978 |
- 0.97 |
- 0.969 |
- 0.974 |
- 0.979 |
- 0.985 |
- 0.989 |
- 0.985 |
- 0.935 |
- 0.975 |
- 0.982 |
- 0.971 |
- 0.935 |
- 0.986 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.979 |
- 0.974 |
- 0.983 |
- 0.985 |
- 0.953 |
- 0.973 |
- 0.976 |
- 0.983 |
- 0.978 |
- 0.986 |
- 0.965 |
- 0.971 |
- 0.971 |
- 0.985 |
- 0.985 |
- 0.972 |
- 0.984 |
- 0.983 |
- 0.977 |
- 0.974 |
- 0.951 |
- 0.981 |
- 0.888 |
- 0.976 |
- 0.976 |
- 0.968 |
- 0.981 |
- 0.963 |
- 0.938 |
- 0.976 |
- 0.943 |
- 0.983 |
- 0.986 |
- 0.994 |
- 0.977 |
- 0.968 |
- 0.984 |
- 0.984 |
- 0.987 |
- 0.98 |
- 0.978 |
- 0.965 |
- 0.976 |
- 0.979 |
- 0.961 |
- 0.98 |
- 0.987 |
- 0.978 |
- 0.983 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.978 |
- 0.982 |
- 0.974 |
- 0.973 |
- 0.976 |
- 0.975 |
- 0.976 |
- 0.981 |
- 0.962 |
- 0.979 |
- 0.98 |
- 0.988 |
- 0.972 |
- 0.979 |
- 0.975 |
- 0.978 |
- 0.944 |
- 0.976 |
- 0.983 |
- 0.976 |
- 0.981 |
- 0.968 |
- 0.983 |
- 0.973 |
- 0.982 |
- 0.979 |
- 0.978 |
- 0.968 |
- 0.981 |
- 0.963 |
- 0.985 |
- 0.989 |
- 0.987 |
- 0.967 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.978 |
- 0.974 |
- 0.981 |
- 0.978 |
- 0.973 |
- 0.975 |
- 0.985 |
- 0.98 |
- 0.984 |
- 0.987 |
- 0.923 |
- 0.981 |
- 0.976 |
- 0.985 |
- 0.989 |
- 1 |
- 0.943 |
- 0.964 |
- 0.945 |
- |
- 0.882 |
- 0.97 |
-
-
- | Liver |
- 212 |
- F |
- 16 |
- 101713.11 |
- HF |
- DBA/2J |
- H1144 |
- 0.935 |
- 0.931 |
- 0.929 |
- 0.935 |
- 0.942 |
- 0.94 |
- 0.938 |
- 0.964 |
- 0.922 |
- 0.943 |
- 0.922 |
- 0.954 |
- 0.934 |
- 0.938 |
- 0.952 |
- 0.937 |
- 0.958 |
- 0.962 |
- 0.939 |
- 0.935 |
- 0.928 |
- 0.941 |
- 0.945 |
- 0.946 |
- 0.964 |
- 0.967 |
- 0.967 |
- 0.969 |
- 0.943 |
- 0.938 |
- 0.941 |
- 0.94 |
- 0.9 |
- 0.953 |
- 0.954 |
- 0.961 |
- 0.976 |
- 0.944 |
- 0.96 |
- 0.945 |
- 0.946 |
- 0.934 |
- 0.944 |
- 0.939 |
- 0.954 |
- 0.96 |
- 0.927 |
- 0.935 |
- 0.942 |
- 0.95 |
- 0.941 |
- 0.976 |
- 0.967 |
- 0.935 |
- 0.943 |
- 0.938 |
- 0.961 |
- 0.935 |
- 0.945 |
- 0.946 |
- 0.932 |
- 0.911 |
- 0.959 |
- 0.863 |
- 0.935 |
- 0.935 |
- 0.957 |
- 0.94 |
- 0.974 |
- 0.976 |
- 0.958 |
- 1 |
- 0.936 |
- 0.938 |
- 0.952 |
- 0.946 |
- 0.96 |
- 0.935 |
- 0.942 |
- 0.944 |
- 0.94 |
- 0.93 |
- 0.923 |
- 0.931 |
- 0.95 |
- 0.955 |
- 0.945 |
- 0.939 |
- 0.962 |
- 0.942 |
- 0.932 |
- 0.942 |
- 0.947 |
- 0.951 |
- 0.95 |
- 0.948 |
- 0.939 |
- 0.973 |
- 0.958 |
- 0.97 |
- 0.931 |
- 0.95 |
- 0.955 |
- 0.953 |
- 0.93 |
- 0.936 |
- 0.939 |
- 0.936 |
- 0.931 |
- 0.949 |
- 0.903 |
- 0.958 |
- 0.949 |
- 0.945 |
- 0.953 |
- 0.957 |
- 0.946 |
- 0.926 |
- 0.938 |
- 0.938 |
- 0.94 |
- 0.928 |
- 0.941 |
- 0.945 |
- 0.954 |
- 0.945 |
- 0.937 |
- 0.97 |
- 0.942 |
- 0.954 |
- 0.936 |
- 0.949 |
- 0.939 |
- 0.945 |
- 0.941 |
- 0.927 |
- 0.927 |
- 0.948 |
- 0.959 |
- 0.933 |
- 0.951 |
- 0.89 |
- 0.932 |
- 0.93 |
- 0.944 |
- 0.941 |
- 0.943 |
- 1 |
- 0.957 |
- 0.968 |
- |
- 0.863 |
- 0.94 |
-
-
- | Liver |
- 544 |
- M |
- 181 |
- 091914.07 |
- HF |
- DBA/2J |
- H1140 |
- 0.969 |
- 0.935 |
- 0.937 |
- 0.967 |
- 0.961 |
- 0.969 |
- 0.966 |
- 0.964 |
- 0.903 |
- 0.968 |
- 0.96 |
- 0.977 |
- 0.961 |
- 0.966 |
- 0.964 |
- 0.97 |
- 0.973 |
- 0.99 |
- 0.977 |
- 0.968 |
- 0.96 |
- 0.971 |
- 0.968 |
- 0.973 |
- 0.977 |
- 0.971 |
- 0.972 |
- 0.977 |
- 0.971 |
- 0.966 |
- 0.966 |
- 0.965 |
- 0.94 |
- 0.965 |
- 0.974 |
- 0.977 |
- 0.944 |
- 0.97 |
- 0.975 |
- 0.973 |
- 0.977 |
- 0.969 |
- 0.969 |
- 0.971 |
- 0.972 |
- 0.946 |
- 0.958 |
- 0.962 |
- 0.972 |
- 0.968 |
- 0.972 |
- 0.965 |
- 0.977 |
- 0.959 |
- 0.97 |
- 0.966 |
- 0.977 |
- 0.969 |
- 0.974 |
- 0.973 |
- 0.959 |
- 0.957 |
- 0.977 |
- 0.888 |
- 0.967 |
- 0.963 |
- 0.979 |
- 0.97 |
- 0.969 |
- 0.954 |
- 0.974 |
- 0.957 |
- 0.966 |
- 0.966 |
- 0.968 |
- 0.973 |
- 0.974 |
- 0.969 |
- 0.976 |
- 0.978 |
- 0.965 |
- 0.969 |
- 0.96 |
- 0.968 |
- 0.978 |
- 0.976 |
- 0.971 |
- 0.97 |
- 0.969 |
- 0.975 |
- 0.978 |
- 0.978 |
- 0.979 |
- 0.971 |
- 0.971 |
- 0.974 |
- 0.977 |
- 0.973 |
- 0.975 |
- 0.976 |
- 0.969 |
- 0.975 |
- 0.97 |
- 0.967 |
- 0.963 |
- 0.963 |
- 0.97 |
- 0.976 |
- 0.969 |
- 0.974 |
- 0.935 |
- 0.964 |
- 0.972 |
- 0.961 |
- 0.969 |
- 0.979 |
- 0.974 |
- 0.968 |
- 0.973 |
- 0.972 |
- 0.968 |
- 0.958 |
- 0.968 |
- 0.963 |
- 0.976 |
- 0.974 |
- 0.969 |
- 0.973 |
- 0.971 |
- 0.975 |
- 0.971 |
- 0.974 |
- 0.977 |
- 0.972 |
- 0.967 |
- 0.966 |
- 0.971 |
- 0.97 |
- 0.981 |
- 0.967 |
- 0.972 |
- 0.918 |
- 0.97 |
- 0.965 |
- 0.969 |
- 0.972 |
- 0.964 |
- 0.957 |
- 1 |
- 0.957 |
- |
- 0.888 |
- 0.97 |
-
-
- | Liver |
- 549 |
- F |
- 190 |
- 091914.05 |
- HF |
- DBA/2J |
- H1142 |
- 0.932 |
- 0.949 |
- 0.946 |
- 0.938 |
- 0.948 |
- 0.949 |
- 0.94 |
- 0.965 |
- 0.941 |
- 0.94 |
- 0.932 |
- 0.949 |
- 0.938 |
- 0.935 |
- 0.957 |
- 0.942 |
- 0.959 |
- 0.972 |
- 0.944 |
- 0.938 |
- 0.94 |
- 0.938 |
- 0.942 |
- 0.945 |
- 0.96 |
- 0.968 |
- 0.967 |
- 0.963 |
- 0.948 |
- 0.94 |
- 0.936 |
- 0.947 |
- 0.915 |
- 0.944 |
- 0.947 |
- 0.967 |
- 0.975 |
- 0.938 |
- 0.951 |
- 0.937 |
- 0.942 |
- 0.935 |
- 0.932 |
- 0.939 |
- 0.957 |
- 0.973 |
- 0.933 |
- 0.942 |
- 0.935 |
- 0.952 |
- 0.943 |
- 0.969 |
- 0.968 |
- 0.943 |
- 0.941 |
- 0.94 |
- 0.963 |
- 0.934 |
- 0.945 |
- 0.949 |
- 0.934 |
- 0.919 |
- 0.952 |
- 0.883 |
- 0.929 |
- 0.929 |
- 0.963 |
- 0.941 |
- 0.971 |
- 0.972 |
- 0.959 |
- 0.968 |
- 0.935 |
- 0.94 |
- 0.953 |
- 0.949 |
- 0.963 |
- 0.934 |
- 0.948 |
- 0.946 |
- 0.942 |
- 0.935 |
- 0.938 |
- 0.936 |
- 0.954 |
- 0.958 |
- 0.943 |
- 0.94 |
- 0.96 |
- 0.946 |
- 0.939 |
- 0.947 |
- 0.953 |
- 0.949 |
- 0.948 |
- 0.951 |
- 0.941 |
- 0.971 |
- 0.96 |
- 0.967 |
- 0.941 |
- 0.948 |
- 0.966 |
- 0.957 |
- 0.943 |
- 0.931 |
- 0.934 |
- 0.933 |
- 0.924 |
- 0.955 |
- 0.913 |
- 0.946 |
- 0.943 |
- 0.959 |
- 0.949 |
- 0.963 |
- 0.933 |
- 0.935 |
- 0.943 |
- 0.944 |
- 0.947 |
- 0.944 |
- 0.947 |
- 0.958 |
- 0.952 |
- 0.945 |
- 0.94 |
- 0.97 |
- 0.943 |
- 0.953 |
- 0.937 |
- 0.955 |
- 0.941 |
- 0.933 |
- 0.939 |
- 0.944 |
- 0.93 |
- 0.944 |
- 0.96 |
- 0.931 |
- 0.944 |
- 0.913 |
- 0.933 |
- 0.926 |
- 0.943 |
- 0.941 |
- 0.945 |
- 0.968 |
- 0.957 |
- 1 |
- |
- 0.883 |
- 0.95 |
-
-
- | |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- Min |
- 0.877 |
- 0.914 |
- 0.914 |
- 0.894 |
- 0.907 |
- 0.913 |
- 0.877 |
- 0.879 |
- 0.877 |
- 0.894 |
- 0.917 |
- 0.897 |
- 0.897 |
- 0.887 |
- 0.919 |
- 0.902 |
- 0.896 |
- 0.88 |
- 0.905 |
- 0.903 |
- 0.885 |
- 0.886 |
- 0.884 |
- 0.889 |
- 0.89 |
- 0.903 |
- 0.904 |
- 0.89 |
- 0.907 |
- 0.891 |
- 0.883 |
- 0.894 |
- 0.9 |
- 0.884 |
- 0.883 |
- 0.91 |
- 0.875 |
- 0.884 |
- 0.89 |
- 0.888 |
- 0.893 |
- 0.888 |
- 0.888 |
- 0.887 |
- 0.889 |
- 0.9 |
- 0.883 |
- 0.903 |
- 0.884 |
- 0.9 |
- 0.893 |
- 0.877 |
- 0.901 |
- 0.91 |
- 0.892 |
- 0.891 |
- 0.898 |
- 0.878 |
- 0.901 |
- 0.896 |
- 0.894 |
- 0.901 |
- 0.893 |
- 0.863 |
- 0.882 |
- 0.884 |
- 0.917 |
- 0.893 |
- 0.899 |
- 0.863 |
- 0.901 |
- 0.863 |
- 0.894 |
- 0.877 |
- 0.889 |
- 0.896 |
- 0.895 |
- 0.881 |
- 0.901 |
- 0.895 |
- 0.89 |
- 0.892 |
- 0.917 |
- 0.892 |
- 0.897 |
- 0.912 |
- 0.887 |
- 0.886 |
- 0.889 |
- 0.887 |
- 0.888 |
- 0.908 |
- 0.913 |
- 0.9 |
- 0.9 |
- 0.896 |
- 0.904 |
- 0.888 |
- 0.915 |
- 0.89 |
- 0.905 |
- 0.899 |
- 0.916 |
- 0.904 |
- 0.907 |
- 0.878 |
- 0.891 |
- 0.882 |
- 0.88 |
- 0.915 |
- 0.896 |
- 0.88 |
- 0.889 |
- 0.905 |
- 0.889 |
- 0.917 |
- 0.88 |
- 0.895 |
- 0.885 |
- 0.889 |
- 0.894 |
- 0.919 |
- 0.892 |
- 0.926 |
- 0.898 |
- 0.892 |
- 0.892 |
- 0.891 |
- 0.903 |
- 0.904 |
- 0.889 |
- 0.915 |
- 0.904 |
- 0.879 |
- 0.88 |
- 0.918 |
- 0.889 |
- 0.884 |
- 0.902 |
- 0.888 |
- 0.892 |
- 0.886 |
- 0.88 |
- 0.894 |
- 0.895 |
- 0.889 |
- 0.882 |
- 0.863 |
- 0.888 |
- 0.883 |
- |
- min |
- average |
-
-
- | |
- |
- |
- |
- |
- |
- |
- Average |
- 0.97756 |
- 0.93466 |
- 0.93572 |
- 0.977506667 |
- 0.973973333 |
- 0.977946667 |
- 0.975493333 |
- 0.963486667 |
- 0.90262 |
- 0.97514 |
- 0.968173333 |
- 0.97762 |
- 0.972413333 |
- 0.974673333 |
- 0.969886667 |
- 0.973686667 |
- 0.969613333 |
- 0.961593333 |
- 0.976486667 |
- 0.975906667 |
- 0.96964 |
- 0.97762 |
- 0.976953333 |
- 0.978366667 |
- 0.974806667 |
- 0.972206667 |
- 0.972566667 |
- 0.972233333 |
- 0.97908 |
- 0.97666 |
- 0.97576 |
- 0.97558 |
- 0.946613333 |
- 0.9703 |
- 0.97476 |
- 0.97526 |
- 0.941373333 |
- 0.97684 |
- 0.975266667 |
- 0.9745 |
- 0.976933333 |
- 0.974533333 |
- 0.9729 |
- 0.977533333 |
- 0.975493333 |
- 0.9497 |
- 0.9698 |
- 0.973826667 |
- 0.975773333 |
- 0.973746667 |
- 0.97796 |
- 0.962326667 |
- 0.975153333 |
- 0.9728 |
- 0.977426667 |
- 0.97666 |
- 0.974006667 |
- 0.969673333 |
- 0.978873333 |
- 0.975313333 |
- 0.968826667 |
- 0.959866667 |
- 0.975613333 |
- 0.90348 |
- 0.972453333 |
- 0.971593333 |
- 0.973173333 |
- 0.97614 |
- 0.966853333 |
- 0.945306667 |
- 0.975946667 |
- 0.94446 |
- 0.97698 |
- 0.975493333 |
- 0.974506667 |
- 0.975313333 |
- 0.970326667 |
- 0.9773 |
- 0.979746667 |
- 0.979673333 |
- 0.97476 |
- 0.975386667 |
- 0.967573333 |
- 0.9728 |
- 0.977166667 |
- 0.96468 |
- 0.976573333 |
- 0.97796 |
- 0.970653333 |
- 0.974686667 |
- 0.972506667 |
- 0.977466667 |
- 0.977986667 |
- 0.975166667 |
- 0.974586667 |
- 0.977833333 |
- 0.976026667 |
- 0.970193333 |
- 0.976033333 |
- 0.972746667 |
- 0.9761 |
- 0.976293333 |
- 0.970913333 |
- 0.973486667 |
- 0.974113333 |
- 0.974686667 |
- 0.97198 |
- 0.975646667 |
- 0.97186 |
- 0.97794 |
- 0.946553333 |
- 0.967726667 |
- 0.97422 |
- 0.966993333 |
- 0.974926667 |
- 0.973173333 |
- 0.974446667 |
- 0.97308 |
- 0.975346667 |
- 0.975633333 |
- 0.97448 |
- 0.969666667 |
- 0.9739 |
- 0.96608 |
- 0.978153333 |
- 0.97868 |
- 0.976826667 |
- 0.969986667 |
- 0.97468 |
- 0.97894 |
- 0.97516 |
- 0.97794 |
- 0.976026667 |
- 0.971426667 |
- 0.972306667 |
- 0.972466667 |
- 0.973773333 |
- 0.97452 |
- 0.978466667 |
- 0.975233333 |
- 0.977166667 |
- 0.930506667 |
- 0.975353333 |
- 0.9727 |
- 0.978113333 |
- 0.9772 |
- 0.973826667 |
- 0.94446 |
- 0.967473333 |
- 0.946173333 |
- |
- 0.90262 |
- 0.970757511 |
-
-
-
diff --git a/general/datasets/UTHSC_BXD_Harv_Liv_0118/specifics.rtf b/general/datasets/UTHSC_BXD_Harv_Liv_0118/specifics.rtf
deleted file mode 100644
index e492142..0000000
--- a/general/datasets/UTHSC_BXD_Harv_Liv_0118/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-RNA-Seq Log2
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_Harv_Liv_0118/summary.rtf b/general/datasets/UTHSC_BXD_Harv_Liv_0118/summary.rtf
deleted file mode 100644
index 153d98d..0000000
--- a/general/datasets/UTHSC_BXD_Harv_Liv_0118/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In working progress...
diff --git a/general/datasets/UTHSC_BXD_Harv_Liv_1019/cases.rtf b/general/datasets/UTHSC_BXD_Harv_Liv_1019/cases.rtf
deleted file mode 100644
index 18fdd1d..0000000
--- a/general/datasets/UTHSC_BXD_Harv_Liv_1019/cases.rtf
+++ /dev/null
@@ -1,1371 +0,0 @@
-
-
-
-
-
-
-
-
-
-
-
- | CaseID |
- Strain |
- Diet |
- Sex |
- Age |
- EarTag Current |
- GN-SampleID |
-
-
- | 062013.09 |
- C57BL/6J |
- HF |
- F |
- 544 |
- 514 |
- H0514 |
-
-
- | 091914.09 |
- C57BL/6J |
- CD |
- F |
- 537 |
- 1103 |
- H1103 |
-
-
- | 012615.26 |
- C57BL/6J |
- CD |
- M |
- 361 |
- 1590 |
- H1590 |
-
-
- | 102414.06 |
- C57BL/6J |
- HF |
- F |
- 182 |
- 1681 |
- H1681 |
-
-
- | 062013.12 |
- D2B6F1 |
- CD |
- F |
- 545 |
- 646 |
- H0646 |
-
-
- | 062013.13 |
- D2B6F1 |
- HF |
- F |
- 540 |
- 642 |
- H0642 |
-
-
- | 101713.20 |
- D2B6F1 |
- HF |
- F |
- 214 |
- 1150 |
- H1150 |
-
-
- | 101713.18 |
- D2B6F1 |
- CD |
- F |
- 210 |
- 1154 |
- H1154 |
-
-
- | 083016.07 |
- DBA/2J |
- CD |
- F |
- 764 |
- 1818 |
- H1818 |
-
-
- | 091914.05 |
- DBA/2J |
- HF |
- F |
- 549 |
- 1142 |
- H1142 |
-
-
- | 091914.07 |
- DBA/2J |
- HF |
- M |
- 544 |
- 1140 |
- H1140 |
-
-
- | 101713.10 |
- DBA/2J |
- CD |
- F |
- 212 |
- 1147 |
- H1147 |
-
-
- | 101713.11 |
- DBA/2J |
- HF |
- F |
- 212 |
- 1144 |
- H1144 |
-
-
- | 121214.29 |
- B6D2F1 |
- CD |
- F |
- 640 |
- 1227 |
- H1227 |
-
-
- | 012615.07 |
- B6D2F1 |
- CD |
- F |
- 552 |
- 1569 |
- H1569 |
-
-
- | 102616.04 |
- B6D2F1 |
- HF |
- F |
- 547 |
- 2288 |
- H2288 |
-
-
- | 102616.05 |
- B6D2F1 |
- HF |
- F |
- 547 |
- 2290 |
- H2290 |
-
-
- | 101713.13 |
- B6D2F1 |
- CD |
- F |
- 216 |
- 1223 |
- H1223 |
-
-
- | 101713.15 |
- B6D2F1 |
- HF |
- F |
- 216 |
- 1302 |
- H1302 |
-
-
- | 082214.11 |
- BXD9 |
- CD |
- F |
- 548 |
- 1006 |
- H1006 |
-
-
- | 082214.09 |
- BXD9 |
- HF |
- F |
- 548 |
- 1009 |
- H1009 |
-
-
- | 102616.12 |
- BXD9 |
- CD |
- F |
- 245 |
- 2577 |
- H2577 |
-
-
- | 083016.08 |
- BXD24 |
- HF |
- F |
- 688 |
- 2259 |
- H2259 |
-
-
- | 012615.19 |
- BXD24 |
- CD |
- F |
- 205 |
- 1792 |
- H1792 |
-
-
- | 012615.08 |
- BXD29 |
- CD |
- F |
- 724 |
- 1044 |
- H1044 |
-
-
- | 111314.10 |
- BXD29 |
- HF |
- F |
- 630 |
- 1037 |
- H1037 |
-
-
- | 061913.04 |
- BXD29 |
- HF |
- F |
- 577 |
- 669 |
- H0669 |
-
-
- | 111314.11 |
- BXD29 |
- CD |
- F |
- 574 |
- 1040 |
- H1040 |
-
-
- | 061913.01 |
- BXD29 |
- CD |
- F |
- 572 |
- 742 |
- H0742 |
-
-
- | 121515.05 |
- BXD29 |
- HF |
- F |
- 182 |
- 2349 |
- H2349 |
-
-
- | 101014.02 |
- BXD32 |
- HF |
- F |
- 539 |
- 1137 |
- H1137 |
-
-
- | 083016.01 |
- BXD32 |
- CD |
- F |
- 386 |
- 2494 |
- H2494 |
-
-
- | 042015.22 |
- BXD32 |
- CD |
- F |
- 200 |
- 2034 |
- H2034 |
-
-
- | 042015.20 |
- BXD32 |
- HF |
- F |
- 200 |
- 2030 |
- H2030 |
-
-
- | 101513.05 |
- BXD34 |
- CD |
- F |
- 554 |
- 765 |
- H0765 |
-
-
- | 101014.05 |
- BXD34 |
- HF |
- F |
- 537 |
- 1052 |
- H1052 |
-
-
- | 101513.02 |
- BXD34 |
- CD |
- F |
- 201 |
- 1054 |
- H1054 |
-
-
- | 101513.04 |
- BXD34 |
- HF |
- F |
- 197 |
- 1056 |
- H1056 |
-
-
- | 010614.06 |
- BXD39 |
- CD |
- F |
- 730 |
- 673 |
- H0673 |
-
-
- | 102414.02 |
- BXD39 |
- CD |
- F |
- 550 |
- 1322 |
- H1322 |
-
-
- | 121214.22 |
- BXD39 |
- HF |
- F |
- 350 |
- 1474 |
- H1474 |
-
-
- | 121214.21 |
- BXD39 |
- HF |
- F |
- 350 |
- 1473 |
- H1473 |
-
-
- | 061913.06 |
- BXD40 |
- CD |
- F |
- 578 |
- 680 |
- H0680 |
-
-
- | 121214.13 |
- BXD40 |
- HF |
- F |
- 358 |
- 1593 |
- H1593 |
-
-
- | 111314.05 |
- BXD40 |
- HF |
- F |
- 291 |
- 1488 |
- H1488 |
-
-
- | 102414.08 |
- BXD40 |
- CD |
- F |
- 180 |
- 1691 |
- H1691 |
-
-
- | 102414.12 |
- BXD44 |
- HF |
- F |
- 715 |
- 1687 |
- H1687 |
-
-
- | 012615.15 |
- BXD44 |
- CD |
- F |
- 379 |
- 1505 |
- H1505 |
-
-
- | 012615.12 |
- BXD44 |
- HF |
- F |
- 379 |
- 1501 |
- H1501 |
-
-
- | 042015.07 |
- BXD44 |
- CD |
- F |
- 240 |
- 1822 |
- H1822 |
-
-
- | 042015.10 |
- BXD44 |
- HF |
- F |
- 240 |
- 1825 |
- H1825 |
-
-
- | 121515.12 |
- BXD45 |
- CD |
- F |
- 507 |
- 1826 |
- H1826 |
-
-
- | 121515.15 |
- BXD45 |
- HF |
- F |
- 503 |
- 1940 |
- H1940 |
-
-
- | 012615.11 |
- BXD45 |
- CD |
- F |
- 384 |
- 1762 |
- H1762 |
-
-
- | 042915.13 |
- BXD48 |
- HF |
- F |
- 595 |
- 1377 |
- H1377 |
-
-
- | 121515.18 |
- BXD48 |
- CD |
- F |
- 518 |
- 1835 |
- H1835 |
-
-
- | 042015.24 |
- BXD48 |
- HF |
- F |
- 189 |
- 2046 |
- H2046 |
-
-
- | 042015.27 |
- BXD48 |
- CD |
- F |
- 188 |
- 2054 |
- H2054 |
-
-
- | 062013.06 |
- BXD48a |
- HF |
- F |
- 543 |
- 699 |
- H0699 |
-
-
- | 051112.05 |
- BXD48a |
- CD |
- F |
- 233 |
- 209 |
- H0209 |
-
-
- | 051112.04 |
- BXD48a |
- HF |
- F |
- 233 |
- 210 |
- H0210 |
-
-
- | 010614.07 |
- BXD53 |
- HF |
- F |
- 713 |
- 833 |
- H0833 |
-
-
- | 062013.16 |
- BXD53 |
- CD |
- F |
- 571 |
- 848 |
- H0848 |
-
-
- | 021213.14 |
- BXD60 |
- CD |
- F |
- 530 |
- 171 |
- H0171 |
-
-
- | 050912.08 |
- BXD60 |
- CD |
- F |
- 235 |
- 235 |
- H0235 |
-
-
- | 121515.23 |
- BXD61 |
- CD |
- F |
- 524 |
- 1841 |
- H1841 |
-
-
- | 121515.25 |
- BXD61 |
- HF |
- F |
- 524 |
- 1843 |
- H1843 |
-
-
- | 111414.02 |
- BXD61 |
- CD |
- F |
- 188 |
- 1770 |
- H1770 |
-
-
- | 111414.03 |
- BXD61 |
- HF |
- F |
- 188 |
- 1922 |
- H1922 |
-
-
- | 111414.04 |
- BXD61 |
- HF |
- F |
- 188 |
- 1722 |
- H1722 |
-
-
- | 082214.10 |
- BXD62 |
- HF |
- F |
- 548 |
- 1315 |
- H1315 |
-
-
- | 042915.19 |
- BXD62 |
- HF |
- F |
- 488 |
- 1434 |
- H1434 |
-
-
- | 121214.20 |
- BXD62 |
- CD |
- F |
- 353 |
- 1436 |
- H1436 |
-
-
- | 042015.05 |
- BXD62 |
- CD |
- F |
- 253 |
- 1847 |
- H1847 |
-
-
- | 102616.17 |
- BXD63 |
- HF |
- F |
- 752 |
- 2091 |
- H2091 |
-
-
- | 083016.03 |
- BXD63 |
- CD |
- F |
- 751 |
- 1872 |
- H1872 |
-
-
- | 121214.24 |
- BXD63 |
- CD |
- F |
- 344 |
- 1414 |
- H1414 |
-
-
- | 121214.26 |
- BXD63 |
- HF |
- F |
- 344 |
- 1416 |
- H1416 |
-
-
- | 090412.08 |
- BXD63 |
- CD |
- F |
- 218 |
- 818 |
- H0818 |
-
-
- | 111414.09 |
- BXD63 |
- HF |
- F |
- 186 |
- 1715 |
- H1715 |
-
-
- | 121615.09 |
- BXD65 |
- CD |
- F |
- 541 |
- 1787 |
- H1787 |
-
-
- | 121615.06 |
- BXD65 |
- HF |
- F |
- 541 |
- 1784 |
- H1784 |
-
-
- | 051012.01 |
- BXD65 |
- HF |
- F |
- 230 |
- 458 |
- H0458 |
-
-
- | 042015.13 |
- BXD65 |
- CD |
- F |
- 222 |
- 2098 |
- H2098 |
-
-
- | 121615.12 |
- BXD65b |
- CD |
- F |
- 527 |
- 1793 |
- H1793 |
-
-
- | 121615.11 |
- BXD65b |
- HF |
- F |
- 527 |
- 1790 |
- H1790 |
-
-
- | 111414.05 |
- BXD65b |
- CD |
- F |
- 187 |
- 1766 |
- H1766 |
-
-
- | 102414.18 |
- BXD65b |
- HF |
- F |
- 174 |
- 1713 |
- H1713 |
-
-
- | 121214.04 |
- BXD66 |
- HF |
- F |
- 367 |
- 1560 |
- H1560 |
-
-
- | 121214.19 |
- BXD66 |
- CD |
- F |
- 354 |
- 1558 |
- H1558 |
-
-
- | 042415.08 |
- BXD66 |
- CD |
- F |
- 184 |
- 2128 |
- H2128 |
-
-
- | 042415.05 |
- BXD66 |
- HF |
- F |
- 184 |
- 2124 |
- H2124 |
-
-
- | 082214.02 |
- BXD68 |
- CD |
- F |
- 545 |
- 1080 |
- H1080 |
-
-
- | 082214.08 |
- BXD68 |
- HF |
- F |
- 545 |
- 1290 |
- H1290 |
-
-
- | 101613.05 |
- BXD68 |
- CD |
- F |
- 201 |
- 1068 |
- H1068 |
-
-
- | 101613.08 |
- BXD68 |
- HF |
- F |
- 201 |
- 1071 |
- H1071 |
-
-
- | 061913.13 |
- BXD69 |
- CD |
- F |
- 558 |
- 591 |
- H0591 |
-
-
- | 121214.23 |
- BXD69 |
- HF |
- F |
- 528 |
- 1328 |
- H1328 |
-
-
- | 101613.09 |
- BXD69 |
- HF |
- F |
- 210 |
- 1087 |
- H1087 |
-
-
- | 042415.23 |
- BXD69 |
- CD |
- F |
- 157 |
- 2142 |
- H2142 |
-
-
- | 121615.14 |
- BXD70 |
- HF |
- F |
- 578 |
- 1728 |
- H1728 |
-
-
- | 121214.16 |
- BXD70 |
- CD |
- F |
- 357 |
- 1512 |
- H1512 |
-
-
- | 050115.06 |
- BXD70 |
- CD |
- F |
- 261 |
- 1855 |
- H1855 |
-
-
- | 051012.08 |
- BXD70 |
- HF |
- F |
- 239 |
- 188 |
- H0188 |
-
-
- | 121615.17 |
- BXD73 |
- CD |
- F |
- 539 |
- 1906 |
- H1906 |
-
-
- | 121214.10 |
- BXD73 |
- CD |
- F |
- 361 |
- 1451 |
- H1451 |
-
-
- | 121214.11 |
- BXD73 |
- HF |
- F |
- 361 |
- 1447 |
- H1447 |
-
-
- | 042015.18 |
- BXD73 |
- HF |
- F |
- 206 |
- 2071 |
- H2071 |
-
-
- | 050115.15 |
- BXD73b |
- CD |
- F |
- 497 |
- 1466 |
- H1466 |
-
-
- | 050115.12 |
- BXD73b |
- HF |
- F |
- 474 |
- 1545 |
- H1545 |
-
-
- | 051112.12 |
- BXD73b |
- CD |
- F |
- 238 |
- 184 |
- H0184 |
-
-
- | 051112.14 |
- BXD73b |
- HF |
- F |
- 237 |
- 183 |
- H0183 |
-
-
- | 121615.19 |
- BXD77 |
- HF |
- F |
- 511 |
- 1866 |
- H1866 |
-
-
- | 050115.17 |
- BXD77 |
- CD |
- F |
- 460 |
- 1398 |
- H1398 |
-
-
- | 061913.18 |
- BXD79 |
- HF |
- F |
- 571 |
- 583 |
- H0583 |
-
-
- | 050115.19 |
- BXD79 |
- CD |
- F |
- 468 |
- 1555 |
- H1555 |
-
-
- | 090412.10 |
- BXD79 |
- CD |
- F |
- 217 |
- 825 |
- H0825 |
-
-
- | 061913.19 |
- BXD87 |
- CD |
- F |
- 581 |
- 296 |
- H0296 |
-
-
- | 121615.21 |
- BXD87 |
- HF |
- F |
- 512 |
- 1945 |
- H1945 |
-
-
- | 051012.14 |
- BXD87 |
- HF |
- F |
- 241 |
- 243 |
- H0243 |
-
-
- | 090612.10 |
- BXD87 |
- CD |
- F |
- 200 |
- 550 |
- H0550 |
-
-
- | 101014.04 |
- BXD89 |
- HF |
- F |
- 539 |
- 1321 |
- H1321 |
-
-
- | 051112.01 |
- BXD89 |
- HF |
- F |
- 243 |
- 176 |
- H0176 |
-
-
- | 090612.14 |
- BXD89 |
- CD |
- F |
- 193 |
- 555 |
- H0555 |
-
-
- | 062013.03 |
- BXD90 |
- HF |
- F |
- 570 |
- 736 |
- H0736 |
-
-
- | 062013.02 |
- BXD90 |
- CD |
- F |
- 549 |
- 756 |
- H0756 |
-
-
- | 101613.19 |
- BXD90 |
- HF |
- F |
- 218 |
- 1093 |
- H1093 |
-
-
- | 102414.03 |
- BXD90 |
- CD |
- F |
- 188 |
- 1702 |
- H1702 |
-
-
- | 062013.17 |
- BXD91 |
- CD |
- F |
- 562 |
- 883 |
- H0883 |
-
-
- | 062013.19 |
- BXD91 |
- HF |
- F |
- 562 |
- 881 |
- H0881 |
-
-
- | 102414.20 |
- BXD95 |
- HF |
- F |
- 550 |
- 1273 |
- H1273 |
-
-
- | 101014.10 |
- BXD95 |
- CD |
- F |
- 536 |
- 1742 |
- H1742 |
-
-
- | 101613.21 |
- BXD95 |
- HF |
- F |
- 213 |
- 1275 |
- H1275 |
-
-
- | 012615.17 |
- BXD98 |
- CD |
- F |
- 384 |
- 1769 |
- H1769 |
-
-
- | 012615.16 |
- BXD98 |
- CD |
- F |
- 384 |
- 1524 |
- H1524 |
-
-
- | 111414.14 |
- BXD99 |
- CD |
- F |
- 535 |
- 1354 |
- H1354 |
-
-
- | 050914.05 |
- BXD99 |
- HF |
- F |
- 182 |
- 1355 |
- H1355 |
-
-
- | 111314.15 |
- BXD100 |
- CD |
- F |
- 567 |
- 1190 |
- H1190 |
-
-
- | 050914.04 |
- BXD100 |
- HF |
- F |
- 537 |
- 1187 |
- H1187 |
-
-
- | 051112.07 |
- BXD100 |
- CD |
- F |
- 223 |
- 247 |
- H0247 |
-
-
- | 051112.08 |
- BXD100 |
- CD |
- F |
- 223 |
- 248 |
- H0248 |
-
-
- | 042415.12 |
- BXD100 |
- HF |
- F |
- 176 |
- 2085 |
- H2085 |
-
-
- | 102616.20 |
- BXD101 |
- CD |
- F |
- 756 |
- 2114 |
- H2114 |
-
-
- | 042715.19 |
- BXD101 |
- HF |
- F |
- 493 |
- 1422 |
- H1422 |
-
-
- | 111414.20 |
- BXD101 |
- CD |
- F |
- 349 |
- 1425 |
- H1425 |
-
-
- | 051112.09 |
- BXD101 |
- CD |
- F |
- 223 |
- 468 |
- H0468 |
-
-
- | 042915.01 |
- BXD102 |
- CD |
- F |
- 501 |
- 1499 |
- H1499 |
-
-
- | 121214.07 |
- BXD102 |
- HF |
- F |
- 366 |
- 1498 |
- H1498 |
-
-
- | 053014.01 |
- BXD102 |
- CD |
- F |
- 183 |
- 1363 |
- H1363 |
-
-
- | 052814.04 |
- BXD102 |
- HF |
- F |
- 183 |
- 1361 |
- H1361 |
-
-
-
diff --git a/general/datasets/UTHSC_BXD_Harv_Liv_1019/processing.rtf b/general/datasets/UTHSC_BXD_Harv_Liv_1019/processing.rtf
deleted file mode 100644
index 4504c49..0000000
--- a/general/datasets/UTHSC_BXD_Harv_Liv_1019/processing.rtf
+++ /dev/null
@@ -1,26883 +0,0 @@
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- | 150 UTHSC Aging Liver RNA Selected for Novogene Submission |
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- | All Samples approximately 110ng/ul with a total of approximately 3ug RNA |
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- | File last updated by A.Centeno 1-3-18 |
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- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
-
-
- | No Selector |
- |
- |
- |
- |
- |
- Tissue |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- Liver |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- Age |
- 216 |
- 552 |
- 640 |
- 223 |
- 223 |
- 567 |
- 223 |
- 349 |
- 756 |
- 183 |
- 501 |
- 205 |
- 572 |
- 574 |
- 724 |
- 200 |
- 386 |
- 201 |
- 554 |
- 550 |
- 730 |
- 180 |
- 578 |
- 240 |
- 379 |
- 384 |
- 507 |
- 188 |
- 518 |
- 233 |
- 571 |
- 235 |
- 530 |
- 188 |
- 524 |
- 253 |
- 353 |
- 218 |
- 344 |
- 751 |
- 222 |
- 541 |
- 187 |
- 527 |
- 184 |
- 354 |
- 201 |
- 545 |
- 157 |
- 558 |
- 261 |
- 357 |
- 361 |
- 539 |
- 238 |
- 497 |
- 460 |
- 217 |
- 468 |
- 200 |
- 581 |
- 193 |
- 245 |
- 548 |
- 188 |
- 549 |
- 562 |
- 536 |
- 384 |
- 384 |
- 535 |
- 361 |
- 537 |
- 210 |
- 545 |
- 212 |
- 764 |
- 216 |
- 547 |
- 547 |
- 176 |
- 537 |
- 493 |
- 183 |
- 366 |
- 688 |
- 182 |
- 577 |
- 630 |
- 200 |
- 539 |
- 197 |
- 537 |
- 350 |
- 350 |
- 291 |
- 358 |
- 240 |
- 379 |
- 715 |
- 503 |
- 189 |
- 595 |
- 233 |
- 543 |
- 713 |
- 188 |
- 188 |
- 524 |
- 488 |
- 548 |
- 186 |
- 344 |
- 752 |
- 230 |
- 541 |
- 174 |
- 527 |
- 184 |
- 367 |
- 201 |
- 545 |
- 210 |
- 528 |
- 239 |
- 578 |
- 206 |
- 361 |
- 237 |
- 474 |
- 511 |
- 571 |
- 241 |
- 512 |
- 243 |
- 539 |
- 548 |
- 218 |
- 570 |
- 562 |
- 213 |
- 550 |
- 182 |
- 544 |
- 182 |
- 214 |
- 540 |
- 212 |
- 544 |
- 549 |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- Sex |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- M |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- F |
- M |
- F |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- JI-ID |
- 307 |
- 151 |
- 136 |
- 268 |
- 269 |
- 92 |
- 3 |
- 117 |
- 179 |
- 83 |
- 270 |
- 163 |
- 299 |
- 314 |
- 141 |
- 259 |
- 131 |
- 170 |
- 180 |
- 276 |
- 168 |
- 289 |
- 285 |
- 264 |
- 157 |
- 145 |
- 281 |
- 260 |
- 275 |
- 25 |
- 308 |
- 104 |
- 51 |
- 132 |
- 324 |
- 257 |
- 178 |
- 293 |
- 134 |
- 133 |
- 107 |
- 322 |
- 320 |
- 313 |
- 112 |
- 113 |
- 271 |
- 74 |
- 114 |
- 41 |
- 207 |
- 197 |
- 203 |
- 213 |
- 98 |
- 253 |
- 255 |
- 272 |
- 91 |
- 6 |
- 286 |
- 310 |
- 230 |
- 73 |
- 304 |
- 311 |
- 21 |
- 277 |
- 146 |
- 182 |
- 278 |
- 162 |
- 273 |
- 300 |
- 298 |
- 67 |
- 121 |
- 306 |
- 279 |
- 296 |
- 254 |
- 77 |
- 290 |
- 284 |
- 195 |
- 140 |
- 317 |
- 295 |
- 119 |
- 261 |
- 318 |
- 283 |
- 292 |
- 129 |
- 204 |
- 280 |
- 202 |
- 258 |
- 158 |
- 144 |
- 303 |
- 263 |
- 238 |
- 239 |
- 287 |
- 143 |
- 128 |
- 323 |
- 316 |
- 242 |
- 302 |
- 125 |
- 123 |
- 135 |
- 265 |
- 212 |
- 315 |
- 321 |
- 262 |
- 122 |
- 59 |
- 71 |
- 58 |
- 109 |
- 266 |
- 294 |
- 224 |
- 196 |
- 97 |
- 256 |
- 319 |
- 24 |
- 2 |
- 326 |
- 267 |
- 282 |
- 312 |
- 297 |
- 274 |
- 325 |
- 288 |
- 236 |
- 305 |
- 309 |
- 235 |
- 301 |
- 291 |
- 16 |
- 181 |
- 190 |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- CaseID |
- 101713.13 |
- 012615.07 |
- 121214.29 |
- 051112.07 |
- 051112.08 |
- 111314.15 |
- 051112.09 |
- 111414.20 |
- 102616.20 |
- 053014.01 |
- 042915.01 |
- 012615.19 |
- 061913.01 |
- 111314.11 |
- 012615.08 |
- 042015.22 |
- 083016.01 |
- 101513.02 |
- 101513.05 |
- 102414.02 |
- 010614.06 |
- 102414.08 |
- 061913.06 |
- 042015.07 |
- 012615.15 |
- 012615.11 |
- 121515.12 |
- 042015.27 |
- 121515.18 |
- 051112.05 |
- 062013.16 |
- 050912.08 |
- 021213.14 |
- 111414.02 |
- 121515.23 |
- 042015.05 |
- 121214.20 |
- 090412.08 |
- 121214.24 |
- 083016.03 |
- 042015.13 |
- 121615.09 |
- 111414.05 |
- 121615.12 |
- 042415.08 |
- 121214.19 |
- 101613.05 |
- 082214.02 |
- 042415.23 |
- 061913.13 |
- 050115.06 |
- 121214.16 |
- 121214.10 |
- 121615.17 |
- 051112.12 |
- 050115.15 |
- 050115.17 |
- 090412.10 |
- 050115.19 |
- 090612.10 |
- 061913.19 |
- 090612.14 |
- 102616.12 |
- 082214.11 |
- 102414.03 |
- 062013.02 |
- 062013.17 |
- 101014.10 |
- 012615.17 |
- 012615.16 |
- 111414.14 |
- 012615.26 |
- 091914.09 |
- 101713.18 |
- 062013.12 |
- 101713.10 |
- 083016.07 |
- 101713.15 |
- 102616.04 |
- 102616.05 |
- 042415.12 |
- 050914.04 |
- 042715.19 |
- 052814.04 |
- 121214.07 |
- 083016.08 |
- 121515.05 |
- 061913.04 |
- 111314.10 |
- 042015.20 |
- 101014.02 |
- 101513.04 |
- 101014.05 |
- 121214.22 |
- 121214.21 |
- 111314.05 |
- 121214.13 |
- 042015.10 |
- 012615.12 |
- 102414.12 |
- 121515.15 |
- 042015.24 |
- 042915.13 |
- 051112.04 |
- 062013.06 |
- 010614.07 |
- 111414.03 |
- 111414.04 |
- 121515.25 |
- 042915.19 |
- 082214.10 |
- 111414.09 |
- 121214.26 |
- 102616.17 |
- 051012.01 |
- 121615.06 |
- 102414.18 |
- 121615.11 |
- 042415.05 |
- 121214.04 |
- 101613.08 |
- 082214.08 |
- 101613.09 |
- 121214.23 |
- 051012.08 |
- 121615.14 |
- 042015.18 |
- 121214.11 |
- 051112.14 |
- 050115.12 |
- 121615.19 |
- 061913.18 |
- 051012.14 |
- 121615.21 |
- 051112.01 |
- 101014.04 |
- 082214.09 |
- 101613.19 |
- 062013.03 |
- 062013.19 |
- 101613.21 |
- 102414.20 |
- 050914.05 |
- 062013.09 |
- 102414.06 |
- 101713.20 |
- 062013.13 |
- 101713.11 |
- 091914.07 |
- 091914.05 |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- Diet |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- CD |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- HF |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- Strain |
- B6D2F1 |
- B6D2F1 |
- B6D2F1 |
- BXD100 |
- BXD100 |
- BXD100 |
- BXD101 |
- BXD101 |
- BXD101 |
- BXD102 |
- BXD102 |
- BXD24 |
- BXD29 |
- BXD29 |
- BXD29 |
- BXD32 |
- BXD32 |
- BXD34 |
- BXD34 |
- BXD39 |
- BXD39 |
- BXD40 |
- BXD40 |
- BXD44 |
- BXD44 |
- BXD45 |
- BXD45 |
- BXD48 |
- BXD48 |
- BXD48a |
- BXD53 |
- BXD60 |
- BXD60 |
- BXD61 |
- BXD61 |
- BXD62 |
- BXD62 |
- BXD63 |
- BXD63 |
- BXD63 |
- BXD65 |
- BXD65 |
- BXD65b |
- BXD65b |
- BXD66 |
- BXD66 |
- BXD68 |
- BXD68 |
- BXD69 |
- BXD69 |
- BXD70 |
- BXD70 |
- BXD73 |
- BXD73 |
- BXD73b |
- BXD73b |
- BXD77 |
- BXD79 |
- BXD79 |
- BXD87 |
- BXD87 |
- BXD89 |
- BXD9 |
- BXD9 |
- BXD90 |
- BXD90 |
- BXD91 |
- BXD95 |
- BXD98 |
- BXD98 |
- BXD99 |
- C57BL/6J |
- C57BL/6J |
- D2B6F1 |
- D2B6F1 |
- DBA/2J |
- DBA/2J |
- B6D2F1 |
- B6D2F1 |
- B6D2F1 |
- BXD100 |
- BXD100 |
- BXD101 |
- BXD102 |
- BXD102 |
- BXD24 |
- BXD29 |
- BXD29 |
- BXD29 |
- BXD32 |
- BXD32 |
- BXD34 |
- BXD34 |
- BXD39 |
- BXD39 |
- BXD40 |
- BXD40 |
- BXD44 |
- BXD44 |
- BXD44 |
- BXD45 |
- BXD48 |
- BXD48 |
- BXD48a |
- BXD48a |
- BXD53 |
- BXD61 |
- BXD61 |
- BXD61 |
- BXD62 |
- BXD62 |
- BXD63 |
- BXD63 |
- BXD63 |
- BXD65 |
- BXD65 |
- BXD65b |
- BXD65b |
- BXD66 |
- BXD66 |
- BXD68 |
- BXD68 |
- BXD69 |
- BXD69 |
- BXD70 |
- BXD70 |
- BXD73 |
- BXD73 |
- BXD73b |
- BXD73b |
- BXD77 |
- BXD79 |
- BXD87 |
- BXD87 |
- BXD89 |
- BXD89 |
- BXD9 |
- BXD90 |
- BXD90 |
- BXD91 |
- BXD95 |
- BXD95 |
- BXD99 |
- C57BL/6J |
- C57BL/6J |
- D2B6F1 |
- D2B6F1 |
- DBA/2J |
- DBA/2J |
- DBA/2J |
- |
- |
- |
-
-
- | Tissue |
- Age |
- Sex |
- JI-ID |
- CaseID |
- Diet |
- Strain |
- EarTag |
- H1223 |
- H1569 |
- H1227 |
- H0247 |
- H0248 |
- H1190 |
- H0468 |
- H1425 |
- H2114 |
- H1363 |
- H1499 |
- H1792 |
- H0742 |
- H1040 |
- H1044 |
- H2034 |
- H2494 |
- H1054 |
- H0765 |
- H1322 |
- H0673 |
- H1691 |
- H0680 |
- H1822 |
- H1505 |
- H1762 |
- H1826 |
- H2054 |
- H1835 |
- H0209 |
- H0848 |
- H0235 |
- H0171 |
- H1770 |
- H1841 |
- H1847 |
- H1436 |
- H0818 |
- H1414 |
- H1872 |
- H2098 |
- H1787 |
- H1766 |
- H1793 |
- H2128 |
- H1558 |
- H1068 |
- H1080 |
- H2142 |
- H0591 |
- H1855 |
- H1512 |
- H1451 |
- H1906 |
- H0184 |
- H1466 |
- H1398 |
- H0825 |
- H1555 |
- H0550 |
- H0296 |
- H0555 |
- H2577 |
- H1006 |
- H1702 |
- H0756 |
- H0883 |
- H1742 |
- H1769 |
- H1524 |
- H1354 |
- H1590 |
- H1103 |
- H1154 |
- H0646 |
- H1147 |
- H1818 |
- H1302 |
- H2288 |
- H2290 |
- H2085 |
- H1187 |
- H1422 |
- H1361 |
- H1498 |
- H2259 |
- H2349 |
- H0669 |
- H1037 |
- H2030 |
- H1137 |
- H1056 |
- H1052 |
- H1474 |
- H1473 |
- H1488 |
- H1593 |
- H1825 |
- H1501 |
- H1687 |
- H1940 |
- H2046 |
- H1377 |
- H0210 |
- H0699 |
- H0833 |
- H1922 |
- H1722 |
- H1843 |
- H1434 |
- H1315 |
- H1715 |
- H1416 |
- H2091 |
- H0458 |
- H1784 |
- H1713 |
- H1790 |
- H2124 |
- H1560 |
- H1071 |
- H1290 |
- H1087 |
- H1328 |
- H0188 |
- H1728 |
- H2071 |
- H1447 |
- H0183 |
- H1545 |
- H1866 |
- H0583 |
- H0243 |
- H1945 |
- H0176 |
- H1321 |
- H1009 |
- H1093 |
- H0736 |
- H0881 |
- H1275 |
- H1273 |
- H1355 |
- H0514 |
- H1681 |
- H1150 |
- H0642 |
- H1144 |
- H1140 |
- H1142 |
- |
- min |
- Average |
-
-
- | Liver |
- 216 |
- F |
- 307 |
- 101713.13 |
- CD |
- B6D2F1 |
- H1223 |
- 1 |
- 0.919 |
- 0.921 |
- 0.992 |
- 0.983 |
- 0.985 |
- 0.992 |
- 0.96 |
- 0.877 |
- 0.988 |
- 0.976 |
- 0.987 |
- 0.982 |
- 0.989 |
- 0.97 |
- 0.983 |
- 0.971 |
- 0.957 |
- 0.984 |
- 0.986 |
- 0.979 |
- 0.993 |
- 0.99 |
- 0.992 |
- 0.982 |
- 0.972 |
- 0.973 |
- 0.974 |
- 0.989 |
- 0.99 |
- 0.989 |
- 0.987 |
- 0.946 |
- 0.976 |
- 0.985 |
- 0.975 |
- 0.929 |
- 0.99 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.985 |
- 0.985 |
- 0.99 |
- 0.983 |
- 0.94 |
- 0.984 |
- 0.982 |
- 0.989 |
- 0.982 |
- 0.989 |
- 0.961 |
- 0.977 |
- 0.98 |
- 0.989 |
- 0.99 |
- 0.979 |
- 0.98 |
- 0.989 |
- 0.985 |
- 0.979 |
- 0.968 |
- 0.984 |
- 0.897 |
- 0.987 |
- 0.985 |
- 0.972 |
- 0.988 |
- 0.966 |
- 0.939 |
- 0.982 |
- 0.935 |
- 0.989 |
- 0.992 |
- 0.983 |
- 0.985 |
- 0.971 |
- 0.994 |
- 0.989 |
- 0.99 |
- 0.986 |
- 0.988 |
- 0.975 |
- 0.982 |
- 0.985 |
- 0.959 |
- 0.99 |
- 0.991 |
- 0.97 |
- 0.985 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.988 |
- 0.984 |
- 0.971 |
- 0.978 |
- 0.976 |
- 0.987 |
- 0.983 |
- 0.97 |
- 0.979 |
- 0.982 |
- 0.99 |
- 0.98 |
- 0.988 |
- 0.987 |
- 0.984 |
- 0.951 |
- 0.972 |
- 0.982 |
- 0.964 |
- 0.986 |
- 0.972 |
- 0.987 |
- 0.984 |
- 0.986 |
- 0.986 |
- 0.986 |
- 0.975 |
- 0.985 |
- 0.965 |
- 0.986 |
- 0.989 |
- 0.988 |
- 0.968 |
- 0.982 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.986 |
- 0.98 |
- 0.987 |
- 0.985 |
- 0.983 |
- 0.988 |
- 0.988 |
- 0.925 |
- 0.99 |
- 0.984 |
- 0.988 |
- 0.99 |
- 0.984 |
- 0.935 |
- 0.969 |
- 0.932 |
- |
- 0.877 |
- 0.98 |
-
-
- | Liver |
- 552 |
- F |
- 151 |
- 012615.07 |
- CD |
- B6D2F1 |
- H1569 |
- 0.919 |
- 1 |
- 0.997 |
- 0.93 |
- 0.939 |
- 0.945 |
- 0.916 |
- 0.935 |
- 0.962 |
- 0.928 |
- 0.945 |
- 0.934 |
- 0.932 |
- 0.923 |
- 0.952 |
- 0.938 |
- 0.943 |
- 0.935 |
- 0.941 |
- 0.936 |
- 0.923 |
- 0.925 |
- 0.922 |
- 0.926 |
- 0.93 |
- 0.951 |
- 0.952 |
- 0.943 |
- 0.943 |
- 0.927 |
- 0.919 |
- 0.928 |
- 0.95 |
- 0.922 |
- 0.92 |
- 0.956 |
- 0.944 |
- 0.924 |
- 0.932 |
- 0.923 |
- 0.931 |
- 0.926 |
- 0.921 |
- 0.927 |
- 0.929 |
- 0.95 |
- 0.922 |
- 0.936 |
- 0.925 |
- 0.935 |
- 0.929 |
- 0.935 |
- 0.948 |
- 0.943 |
- 0.929 |
- 0.927 |
- 0.943 |
- 0.914 |
- 0.935 |
- 0.931 |
- 0.932 |
- 0.942 |
- 0.932 |
- 0.943 |
- 0.919 |
- 0.92 |
- 0.955 |
- 0.928 |
- 0.946 |
- 0.931 |
- 0.939 |
- 0.931 |
- 0.932 |
- 0.916 |
- 0.921 |
- 0.931 |
- 0.942 |
- 0.923 |
- 0.938 |
- 0.932 |
- 0.927 |
- 0.931 |
- 0.944 |
- 0.927 |
- 0.933 |
- 0.949 |
- 0.923 |
- 0.924 |
- 0.934 |
- 0.927 |
- 0.923 |
- 0.943 |
- 0.946 |
- 0.941 |
- 0.94 |
- 0.933 |
- 0.942 |
- 0.941 |
- 0.95 |
- 0.939 |
- 0.944 |
- 0.937 |
- 0.96 |
- 0.941 |
- 0.943 |
- 0.915 |
- 0.922 |
- 0.922 |
- 0.92 |
- 0.948 |
- 0.932 |
- 0.922 |
- 0.925 |
- 0.943 |
- 0.927 |
- 0.955 |
- 0.92 |
- 0.935 |
- 0.923 |
- 0.927 |
- 0.93 |
- 0.95 |
- 0.927 |
- 0.957 |
- 0.936 |
- 0.929 |
- 0.93 |
- 0.945 |
- 0.935 |
- 0.939 |
- 0.922 |
- 0.948 |
- 0.942 |
- 0.915 |
- 0.921 |
- 0.946 |
- 0.932 |
- 0.922 |
- 0.941 |
- 0.928 |
- 0.929 |
- 0.95 |
- 0.922 |
- 0.933 |
- 0.934 |
- 0.927 |
- 0.917 |
- 0.931 |
- 0.935 |
- 0.949 |
- |
- 0.914 |
- 0.93 |
-
-
- | Liver |
- 640 |
- F |
- 136 |
- 121214.29 |
- CD |
- B6D2F1 |
- H1227 |
- 0.921 |
- 0.997 |
- 1 |
- 0.931 |
- 0.941 |
- 0.945 |
- 0.918 |
- 0.933 |
- 0.959 |
- 0.929 |
- 0.947 |
- 0.935 |
- 0.933 |
- 0.925 |
- 0.952 |
- 0.938 |
- 0.942 |
- 0.933 |
- 0.943 |
- 0.938 |
- 0.923 |
- 0.926 |
- 0.924 |
- 0.928 |
- 0.931 |
- 0.95 |
- 0.952 |
- 0.942 |
- 0.945 |
- 0.929 |
- 0.921 |
- 0.928 |
- 0.953 |
- 0.923 |
- 0.922 |
- 0.956 |
- 0.941 |
- 0.926 |
- 0.933 |
- 0.925 |
- 0.931 |
- 0.928 |
- 0.923 |
- 0.928 |
- 0.929 |
- 0.948 |
- 0.924 |
- 0.937 |
- 0.927 |
- 0.937 |
- 0.93 |
- 0.935 |
- 0.948 |
- 0.944 |
- 0.931 |
- 0.929 |
- 0.943 |
- 0.914 |
- 0.937 |
- 0.932 |
- 0.935 |
- 0.945 |
- 0.932 |
- 0.945 |
- 0.921 |
- 0.923 |
- 0.956 |
- 0.93 |
- 0.945 |
- 0.93 |
- 0.94 |
- 0.929 |
- 0.933 |
- 0.918 |
- 0.921 |
- 0.932 |
- 0.942 |
- 0.926 |
- 0.94 |
- 0.934 |
- 0.927 |
- 0.933 |
- 0.947 |
- 0.928 |
- 0.933 |
- 0.949 |
- 0.925 |
- 0.926 |
- 0.932 |
- 0.928 |
- 0.925 |
- 0.945 |
- 0.948 |
- 0.941 |
- 0.941 |
- 0.934 |
- 0.945 |
- 0.94 |
- 0.952 |
- 0.94 |
- 0.946 |
- 0.938 |
- 0.96 |
- 0.941 |
- 0.944 |
- 0.917 |
- 0.924 |
- 0.924 |
- 0.924 |
- 0.949 |
- 0.934 |
- 0.922 |
- 0.926 |
- 0.942 |
- 0.929 |
- 0.956 |
- 0.922 |
- 0.938 |
- 0.923 |
- 0.93 |
- 0.931 |
- 0.951 |
- 0.928 |
- 0.957 |
- 0.938 |
- 0.93 |
- 0.931 |
- 0.945 |
- 0.936 |
- 0.94 |
- 0.924 |
- 0.949 |
- 0.945 |
- 0.917 |
- 0.923 |
- 0.948 |
- 0.936 |
- 0.924 |
- 0.943 |
- 0.931 |
- 0.931 |
- 0.95 |
- 0.924 |
- 0.936 |
- 0.935 |
- 0.928 |
- 0.917 |
- 0.929 |
- 0.937 |
- 0.946 |
- |
- 0.914 |
- 0.94 |
-
-
- | Liver |
- 223 |
- F |
- 268 |
- 051112.07 |
- CD |
- BXD100 |
- H0247 |
- 0.992 |
- 0.93 |
- 0.931 |
- 1 |
- 0.985 |
- 0.989 |
- 0.987 |
- 0.966 |
- 0.894 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.985 |
- 0.97 |
- 0.982 |
- 0.972 |
- 0.958 |
- 0.985 |
- 0.988 |
- 0.981 |
- 0.99 |
- 0.986 |
- 0.989 |
- 0.98 |
- 0.974 |
- 0.975 |
- 0.975 |
- 0.991 |
- 0.987 |
- 0.988 |
- 0.987 |
- 0.952 |
- 0.974 |
- 0.984 |
- 0.979 |
- 0.933 |
- 0.987 |
- 0.982 |
- 0.982 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.988 |
- 0.984 |
- 0.946 |
- 0.979 |
- 0.982 |
- 0.985 |
- 0.979 |
- 0.99 |
- 0.961 |
- 0.978 |
- 0.98 |
- 0.986 |
- 0.987 |
- 0.978 |
- 0.98 |
- 0.989 |
- 0.983 |
- 0.974 |
- 0.969 |
- 0.983 |
- 0.906 |
- 0.984 |
- 0.982 |
- 0.975 |
- 0.987 |
- 0.965 |
- 0.939 |
- 0.98 |
- 0.935 |
- 0.991 |
- 0.987 |
- 0.982 |
- 0.983 |
- 0.971 |
- 0.989 |
- 0.989 |
- 0.988 |
- 0.985 |
- 0.989 |
- 0.977 |
- 0.985 |
- 0.985 |
- 0.962 |
- 0.986 |
- 0.989 |
- 0.972 |
- 0.981 |
- 0.98 |
- 0.986 |
- 0.985 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.984 |
- 0.972 |
- 0.979 |
- 0.976 |
- 0.988 |
- 0.983 |
- 0.974 |
- 0.98 |
- 0.986 |
- 0.988 |
- 0.98 |
- 0.986 |
- 0.983 |
- 0.986 |
- 0.952 |
- 0.969 |
- 0.98 |
- 0.969 |
- 0.981 |
- 0.975 |
- 0.982 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.976 |
- 0.983 |
- 0.966 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.97 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.976 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.986 |
- 0.984 |
- 0.935 |
- 0.985 |
- 0.983 |
- 0.989 |
- 0.988 |
- 0.982 |
- 0.935 |
- 0.967 |
- 0.938 |
- |
- 0.894 |
- 0.98 |
-
-
- | Liver |
- 223 |
- F |
- 269 |
- 051112.08 |
- CD |
- BXD100 |
- H0248 |
- 0.983 |
- 0.939 |
- 0.941 |
- 0.985 |
- 1 |
- 0.985 |
- 0.985 |
- 0.959 |
- 0.907 |
- 0.983 |
- 0.978 |
- 0.978 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.976 |
- 0.965 |
- 0.953 |
- 0.976 |
- 0.979 |
- 0.97 |
- 0.98 |
- 0.986 |
- 0.984 |
- 0.974 |
- 0.974 |
- 0.975 |
- 0.969 |
- 0.985 |
- 0.983 |
- 0.978 |
- 0.982 |
- 0.955 |
- 0.973 |
- 0.97 |
- 0.978 |
- 0.943 |
- 0.979 |
- 0.972 |
- 0.968 |
- 0.975 |
- 0.977 |
- 0.971 |
- 0.982 |
- 0.976 |
- 0.957 |
- 0.987 |
- 0.982 |
- 0.981 |
- 0.984 |
- 0.979 |
- 0.963 |
- 0.975 |
- 0.986 |
- 0.984 |
- 0.983 |
- 0.974 |
- 0.966 |
- 0.979 |
- 0.976 |
- 0.984 |
- 0.97 |
- 0.973 |
- 0.915 |
- 0.976 |
- 0.98 |
- 0.972 |
- 0.978 |
- 0.967 |
- 0.942 |
- 0.979 |
- 0.942 |
- 0.981 |
- 0.985 |
- 0.976 |
- 0.976 |
- 0.969 |
- 0.987 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.981 |
- 0.976 |
- 0.98 |
- 0.958 |
- 0.98 |
- 0.982 |
- 0.964 |
- 0.975 |
- 0.968 |
- 0.977 |
- 0.977 |
- 0.971 |
- 0.971 |
- 0.983 |
- 0.976 |
- 0.967 |
- 0.98 |
- 0.97 |
- 0.982 |
- 0.977 |
- 0.978 |
- 0.983 |
- 0.985 |
- 0.978 |
- 0.967 |
- 0.974 |
- 0.972 |
- 0.98 |
- 0.96 |
- 0.965 |
- 0.967 |
- 0.971 |
- 0.987 |
- 0.972 |
- 0.974 |
- 0.98 |
- 0.975 |
- 0.984 |
- 0.982 |
- 0.982 |
- 0.979 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.979 |
- 0.969 |
- 0.974 |
- 0.982 |
- 0.973 |
- 0.98 |
- 0.976 |
- 0.968 |
- 0.983 |
- 0.981 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.941 |
- 0.98 |
- 0.978 |
- 0.982 |
- 0.98 |
- 0.976 |
- 0.942 |
- 0.961 |
- 0.948 |
- |
- 0.907 |
- 0.97 |
-
-
- | Liver |
- 567 |
- F |
- 92 |
- 111314.15 |
- CD |
- BXD100 |
- H1190 |
- 0.985 |
- 0.945 |
- 0.945 |
- 0.989 |
- 0.985 |
- 1 |
- 0.981 |
- 0.965 |
- 0.913 |
- 0.983 |
- 0.984 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.988 |
- 0.972 |
- 0.965 |
- 0.986 |
- 0.987 |
- 0.985 |
- 0.987 |
- 0.984 |
- 0.986 |
- 0.977 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.989 |
- 0.988 |
- 0.983 |
- 0.987 |
- 0.962 |
- 0.971 |
- 0.977 |
- 0.982 |
- 0.939 |
- 0.983 |
- 0.976 |
- 0.977 |
- 0.985 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.981 |
- 0.957 |
- 0.977 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.988 |
- 0.96 |
- 0.978 |
- 0.983 |
- 0.985 |
- 0.988 |
- 0.977 |
- 0.981 |
- 0.99 |
- 0.978 |
- 0.981 |
- 0.974 |
- 0.979 |
- 0.924 |
- 0.982 |
- 0.98 |
- 0.977 |
- 0.983 |
- 0.969 |
- 0.938 |
- 0.98 |
- 0.94 |
- 0.989 |
- 0.981 |
- 0.982 |
- 0.978 |
- 0.971 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.984 |
- 0.987 |
- 0.983 |
- 0.985 |
- 0.984 |
- 0.968 |
- 0.981 |
- 0.986 |
- 0.973 |
- 0.984 |
- 0.98 |
- 0.986 |
- 0.987 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.971 |
- 0.981 |
- 0.974 |
- 0.989 |
- 0.982 |
- 0.976 |
- 0.981 |
- 0.988 |
- 0.983 |
- 0.975 |
- 0.983 |
- 0.979 |
- 0.985 |
- 0.959 |
- 0.966 |
- 0.977 |
- 0.975 |
- 0.979 |
- 0.977 |
- 0.978 |
- 0.984 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.973 |
- 0.981 |
- 0.987 |
- 0.989 |
- 0.97 |
- 0.984 |
- 0.985 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.976 |
- 0.978 |
- 0.988 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.951 |
- 0.981 |
- 0.982 |
- 0.988 |
- 0.985 |
- 0.983 |
- 0.94 |
- 0.969 |
- 0.949 |
- |
- 0.913 |
- 0.98 |
-
-
- | Liver |
- 223 |
- F |
- 3 |
- 051112.09 |
- CD |
- BXD101 |
- H0468 |
- 0.992 |
- 0.916 |
- 0.918 |
- 0.987 |
- 0.985 |
- 0.981 |
- 1 |
- 0.961 |
- 0.877 |
- 0.987 |
- 0.971 |
- 0.982 |
- 0.98 |
- 0.984 |
- 0.969 |
- 0.977 |
- 0.967 |
- 0.958 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.987 |
- 0.99 |
- 0.988 |
- 0.979 |
- 0.972 |
- 0.972 |
- 0.971 |
- 0.985 |
- 0.986 |
- 0.987 |
- 0.986 |
- 0.94 |
- 0.979 |
- 0.98 |
- 0.972 |
- 0.932 |
- 0.988 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.988 |
- 0.981 |
- 0.945 |
- 0.989 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.984 |
- 0.961 |
- 0.972 |
- 0.979 |
- 0.985 |
- 0.986 |
- 0.976 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.976 |
- 0.962 |
- 0.981 |
- 0.893 |
- 0.98 |
- 0.981 |
- 0.97 |
- 0.983 |
- 0.964 |
- 0.944 |
- 0.981 |
- 0.938 |
- 0.987 |
- 1 |
- 0.985 |
- 0.984 |
- 0.968 |
- 0.993 |
- 0.986 |
- 0.987 |
- 0.988 |
- 0.986 |
- 0.973 |
- 0.981 |
- 0.985 |
- 0.957 |
- 0.988 |
- 0.988 |
- 0.97 |
- 0.984 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.974 |
- 0.986 |
- 0.977 |
- 0.969 |
- 0.979 |
- 0.972 |
- 0.98 |
- 0.982 |
- 0.97 |
- 0.98 |
- 0.981 |
- 0.988 |
- 0.976 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.951 |
- 0.974 |
- 0.979 |
- 0.969 |
- 0.988 |
- 0.97 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.988 |
- 0.988 |
- 0.973 |
- 0.985 |
- 0.966 |
- 0.985 |
- 0.985 |
- 0.982 |
- 0.968 |
- 0.976 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.977 |
- 0.977 |
- 0.987 |
- 0.975 |
- 0.981 |
- 0.988 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.921 |
- 0.988 |
- 0.981 |
- 0.987 |
- 0.989 |
- 0.986 |
- 0.938 |
- 0.966 |
- 0.94 |
- |
- 0.877 |
- 0.98 |
-
-
- | Liver |
- 349 |
- F |
- 117 |
- 111414.20 |
- CD |
- BXD101 |
- H1425 |
- 0.96 |
- 0.935 |
- 0.933 |
- 0.966 |
- 0.959 |
- 0.965 |
- 0.961 |
- 1 |
- 0.922 |
- 0.96 |
- 0.949 |
- 0.971 |
- 0.952 |
- 0.957 |
- 0.963 |
- 0.959 |
- 0.978 |
- 0.972 |
- 0.962 |
- 0.966 |
- 0.962 |
- 0.966 |
- 0.963 |
- 0.965 |
- 0.976 |
- 0.977 |
- 0.976 |
- 0.983 |
- 0.968 |
- 0.962 |
- 0.966 |
- 0.967 |
- 0.919 |
- 0.974 |
- 0.978 |
- 0.977 |
- 0.968 |
- 0.969 |
- 0.982 |
- 0.973 |
- 0.969 |
- 0.962 |
- 0.968 |
- 0.964 |
- 0.977 |
- 0.965 |
- 0.946 |
- 0.96 |
- 0.964 |
- 0.966 |
- 0.969 |
- 0.979 |
- 0.979 |
- 0.958 |
- 0.964 |
- 0.962 |
- 0.976 |
- 0.964 |
- 0.97 |
- 0.975 |
- 0.942 |
- 0.931 |
- 0.972 |
- 0.879 |
- 0.953 |
- 0.951 |
- 0.968 |
- 0.965 |
- 0.973 |
- 0.966 |
- 0.975 |
- 0.964 |
- 0.962 |
- 0.961 |
- 0.974 |
- 0.975 |
- 0.98 |
- 0.956 |
- 0.966 |
- 0.966 |
- 0.966 |
- 0.956 |
- 0.944 |
- 0.956 |
- 0.972 |
- 0.966 |
- 0.964 |
- 0.964 |
- 0.983 |
- 0.965 |
- 0.96 |
- 0.965 |
- 0.969 |
- 0.981 |
- 0.981 |
- 0.964 |
- 0.965 |
- 0.981 |
- 0.966 |
- 0.978 |
- 0.958 |
- 0.972 |
- 0.97 |
- 0.968 |
- 0.956 |
- 0.963 |
- 0.97 |
- 0.96 |
- 0.95 |
- 0.972 |
- 0.914 |
- 0.979 |
- 0.977 |
- 0.972 |
- 0.962 |
- 0.968 |
- 0.964 |
- 0.95 |
- 0.966 |
- 0.958 |
- 0.958 |
- 0.948 |
- 0.962 |
- 0.955 |
- 0.974 |
- 0.969 |
- 0.965 |
- 0.982 |
- 0.97 |
- 0.974 |
- 0.968 |
- 0.972 |
- 0.965 |
- 0.965 |
- 0.954 |
- 0.955 |
- 0.949 |
- 0.961 |
- 0.973 |
- 0.955 |
- 0.97 |
- 0.908 |
- 0.958 |
- 0.949 |
- 0.966 |
- 0.963 |
- 0.97 |
- 0.964 |
- 0.964 |
- 0.965 |
- |
- 0.879 |
- 0.96 |
-
-
- | Liver |
- 756 |
- F |
- 179 |
- 102616.20 |
- CD |
- BXD101 |
- H2114 |
- 0.877 |
- 0.962 |
- 0.959 |
- 0.894 |
- 0.907 |
- 0.913 |
- 0.877 |
- 0.922 |
- 1 |
- 0.894 |
- 0.917 |
- 0.897 |
- 0.897 |
- 0.887 |
- 0.926 |
- 0.902 |
- 0.922 |
- 0.909 |
- 0.905 |
- 0.903 |
- 0.885 |
- 0.886 |
- 0.884 |
- 0.889 |
- 0.902 |
- 0.928 |
- 0.928 |
- 0.915 |
- 0.907 |
- 0.891 |
- 0.883 |
- 0.894 |
- 0.919 |
- 0.893 |
- 0.891 |
- 0.933 |
- 0.939 |
- 0.884 |
- 0.901 |
- 0.888 |
- 0.893 |
- 0.888 |
- 0.888 |
- 0.887 |
- 0.897 |
- 0.932 |
- 0.883 |
- 0.903 |
- 0.884 |
- 0.9 |
- 0.893 |
- 0.916 |
- 0.923 |
- 0.91 |
- 0.892 |
- 0.891 |
- 0.914 |
- 0.878 |
- 0.901 |
- 0.898 |
- 0.894 |
- 0.901 |
- 0.895 |
- 0.918 |
- 0.882 |
- 0.884 |
- 0.925 |
- 0.893 |
- 0.929 |
- 0.918 |
- 0.909 |
- 0.922 |
- 0.894 |
- 0.877 |
- 0.89 |
- 0.898 |
- 0.92 |
- 0.881 |
- 0.901 |
- 0.895 |
- 0.89 |
- 0.892 |
- 0.917 |
- 0.892 |
- 0.898 |
- 0.926 |
- 0.887 |
- 0.886 |
- 0.914 |
- 0.887 |
- 0.888 |
- 0.908 |
- 0.913 |
- 0.911 |
- 0.911 |
- 0.896 |
- 0.904 |
- 0.919 |
- 0.919 |
- 0.914 |
- 0.905 |
- 0.899 |
- 0.932 |
- 0.91 |
- 0.907 |
- 0.878 |
- 0.891 |
- 0.882 |
- 0.88 |
- 0.916 |
- 0.896 |
- 0.895 |
- 0.892 |
- 0.922 |
- 0.889 |
- 0.925 |
- 0.88 |
- 0.895 |
- 0.885 |
- 0.889 |
- 0.894 |
- 0.919 |
- 0.892 |
- 0.926 |
- 0.901 |
- 0.892 |
- 0.892 |
- 0.926 |
- 0.904 |
- 0.906 |
- 0.889 |
- 0.916 |
- 0.904 |
- 0.879 |
- 0.88 |
- 0.918 |
- 0.889 |
- 0.884 |
- 0.91 |
- 0.888 |
- 0.892 |
- 0.939 |
- 0.88 |
- 0.894 |
- 0.895 |
- 0.889 |
- 0.882 |
- 0.922 |
- 0.903 |
- 0.941 |
- |
- 0.877 |
- 0.90 |
-
-
- | Liver |
- 183 |
- F |
- 83 |
- 053014.01 |
- CD |
- BXD102 |
- H1363 |
- 0.988 |
- 0.928 |
- 0.929 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.987 |
- 0.96 |
- 0.894 |
- 1 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.985 |
- 0.973 |
- 0.979 |
- 0.972 |
- 0.96 |
- 0.979 |
- 0.981 |
- 0.971 |
- 0.985 |
- 0.985 |
- 0.987 |
- 0.981 |
- 0.976 |
- 0.976 |
- 0.971 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.951 |
- 0.976 |
- 0.976 |
- 0.975 |
- 0.935 |
- 0.982 |
- 0.975 |
- 0.976 |
- 0.984 |
- 0.982 |
- 0.982 |
- 0.985 |
- 0.979 |
- 0.945 |
- 0.983 |
- 0.983 |
- 0.98 |
- 0.977 |
- 0.983 |
- 0.959 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.977 |
- 0.974 |
- 0.983 |
- 0.982 |
- 0.976 |
- 0.969 |
- 0.977 |
- 0.906 |
- 0.984 |
- 0.98 |
- 0.975 |
- 0.982 |
- 0.973 |
- 0.948 |
- 0.981 |
- 0.943 |
- 0.985 |
- 0.987 |
- 0.976 |
- 0.982 |
- 0.97 |
- 0.987 |
- 0.984 |
- 0.985 |
- 0.984 |
- 0.985 |
- 0.976 |
- 0.988 |
- 0.987 |
- 0.964 |
- 0.986 |
- 0.984 |
- 0.971 |
- 0.981 |
- 0.977 |
- 0.98 |
- 0.979 |
- 0.974 |
- 0.974 |
- 0.985 |
- 0.977 |
- 0.969 |
- 0.98 |
- 0.972 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.977 |
- 0.979 |
- 0.981 |
- 0.978 |
- 0.981 |
- 0.976 |
- 0.981 |
- 0.953 |
- 0.97 |
- 0.975 |
- 0.965 |
- 0.983 |
- 0.975 |
- 0.98 |
- 0.981 |
- 0.983 |
- 0.987 |
- 0.985 |
- 0.976 |
- 0.982 |
- 0.97 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.967 |
- 0.975 |
- 0.979 |
- 0.977 |
- 0.981 |
- 0.977 |
- 0.974 |
- 0.981 |
- 0.977 |
- 0.98 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.98 |
- 0.932 |
- 0.982 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.976 |
- 0.943 |
- 0.968 |
- 0.94 |
- |
- 0.894 |
- 0.98 |
-
-
- | Liver |
- 501 |
- F |
- 270 |
- 042915.01 |
- CD |
- BXD102 |
- H1499 |
- 0.976 |
- 0.945 |
- 0.947 |
- 0.981 |
- 0.978 |
- 0.984 |
- 0.971 |
- 0.949 |
- 0.917 |
- 0.979 |
- 1 |
- 0.97 |
- 0.977 |
- 0.971 |
- 0.968 |
- 0.978 |
- 0.963 |
- 0.949 |
- 0.978 |
- 0.98 |
- 0.969 |
- 0.974 |
- 0.969 |
- 0.974 |
- 0.961 |
- 0.969 |
- 0.97 |
- 0.962 |
- 0.982 |
- 0.975 |
- 0.97 |
- 0.973 |
- 0.97 |
- 0.959 |
- 0.962 |
- 0.976 |
- 0.921 |
- 0.971 |
- 0.962 |
- 0.966 |
- 0.974 |
- 0.975 |
- 0.969 |
- 0.979 |
- 0.967 |
- 0.938 |
- 0.973 |
- 0.978 |
- 0.973 |
- 0.968 |
- 0.975 |
- 0.941 |
- 0.968 |
- 0.977 |
- 0.973 |
- 0.975 |
- 0.965 |
- 0.963 |
- 0.976 |
- 0.969 |
- 0.969 |
- 0.974 |
- 0.965 |
- 0.927 |
- 0.972 |
- 0.968 |
- 0.97 |
- 0.972 |
- 0.956 |
- 0.927 |
- 0.968 |
- 0.922 |
- 0.982 |
- 0.971 |
- 0.961 |
- 0.969 |
- 0.961 |
- 0.977 |
- 0.982 |
- 0.979 |
- 0.973 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.977 |
- 0.957 |
- 0.972 |
- 0.974 |
- 0.957 |
- 0.97 |
- 0.97 |
- 0.978 |
- 0.977 |
- 0.968 |
- 0.967 |
- 0.974 |
- 0.979 |
- 0.953 |
- 0.971 |
- 0.958 |
- 0.985 |
- 0.973 |
- 0.97 |
- 0.97 |
- 0.984 |
- 0.97 |
- 0.968 |
- 0.976 |
- 0.972 |
- 0.977 |
- 0.96 |
- 0.95 |
- 0.963 |
- 0.966 |
- 0.967 |
- 0.97 |
- 0.968 |
- 0.978 |
- 0.973 |
- 0.975 |
- 0.972 |
- 0.98 |
- 0.971 |
- 0.965 |
- 0.971 |
- 0.974 |
- 0.975 |
- 0.958 |
- 0.971 |
- 0.972 |
- 0.971 |
- 0.977 |
- 0.979 |
- 0.959 |
- 0.966 |
- 0.983 |
- 0.979 |
- 0.965 |
- 0.972 |
- 0.977 |
- 0.968 |
- 0.955 |
- 0.973 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.963 |
- 0.922 |
- 0.96 |
- 0.932 |
- |
- 0.917 |
- 0.97 |
-
-
- | Liver |
- 205 |
- F |
- 163 |
- 012615.19 |
- CD |
- BXD24 |
- H1792 |
- 0.987 |
- 0.934 |
- 0.935 |
- 0.984 |
- 0.978 |
- 0.985 |
- 0.982 |
- 0.971 |
- 0.897 |
- 0.981 |
- 0.97 |
- 1 |
- 0.978 |
- 0.982 |
- 0.978 |
- 0.987 |
- 0.974 |
- 0.971 |
- 0.982 |
- 0.983 |
- 0.979 |
- 0.989 |
- 0.986 |
- 0.989 |
- 0.986 |
- 0.978 |
- 0.978 |
- 0.984 |
- 0.983 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.947 |
- 0.977 |
- 0.985 |
- 0.982 |
- 0.946 |
- 0.987 |
- 0.985 |
- 0.983 |
- 0.987 |
- 0.981 |
- 0.979 |
- 0.985 |
- 0.986 |
- 0.956 |
- 0.973 |
- 0.977 |
- 0.988 |
- 0.981 |
- 0.989 |
- 0.972 |
- 0.983 |
- 0.974 |
- 0.986 |
- 0.986 |
- 0.982 |
- 0.981 |
- 0.988 |
- 0.982 |
- 0.976 |
- 0.962 |
- 0.988 |
- 0.899 |
- 0.983 |
- 0.977 |
- 0.976 |
- 0.984 |
- 0.975 |
- 0.951 |
- 0.985 |
- 0.954 |
- 0.983 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.977 |
- 0.984 |
- 0.987 |
- 0.987 |
- 0.981 |
- 0.979 |
- 0.969 |
- 0.977 |
- 0.985 |
- 0.971 |
- 0.984 |
- 0.986 |
- 0.978 |
- 0.986 |
- 0.978 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.984 |
- 0.981 |
- 0.986 |
- 0.97 |
- 0.978 |
- 0.977 |
- 0.984 |
- 0.976 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.947 |
- 0.976 |
- 0.983 |
- 0.97 |
- 0.982 |
- 0.976 |
- 0.985 |
- 0.976 |
- 0.984 |
- 0.98 |
- 0.979 |
- 0.971 |
- 0.98 |
- 0.968 |
- 0.986 |
- 0.989 |
- 0.987 |
- 0.975 |
- 0.982 |
- 0.988 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.979 |
- 0.975 |
- 0.98 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.988 |
- 0.928 |
- 0.982 |
- 0.977 |
- 0.987 |
- 0.986 |
- 0.985 |
- 0.954 |
- 0.977 |
- 0.949 |
- |
- 0.897 |
- 0.98 |
-
-
- | Liver |
- 572 |
- F |
- 299 |
- 061913.01 |
- CD |
- BXD29 |
- H0742 |
- 0.982 |
- 0.932 |
- 0.933 |
- 0.983 |
- 0.981 |
- 0.983 |
- 0.98 |
- 0.952 |
- 0.897 |
- 0.982 |
- 0.977 |
- 0.978 |
- 1 |
- 0.988 |
- 0.972 |
- 0.977 |
- 0.965 |
- 0.953 |
- 0.979 |
- 0.982 |
- 0.973 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.973 |
- 0.97 |
- 0.97 |
- 0.963 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.96 |
- 0.971 |
- 0.973 |
- 0.973 |
- 0.925 |
- 0.977 |
- 0.968 |
- 0.969 |
- 0.98 |
- 0.98 |
- 0.975 |
- 0.983 |
- 0.977 |
- 0.943 |
- 0.977 |
- 0.98 |
- 0.976 |
- 0.97 |
- 0.984 |
- 0.953 |
- 0.973 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.969 |
- 0.972 |
- 0.983 |
- 0.971 |
- 0.979 |
- 0.967 |
- 0.976 |
- 0.912 |
- 0.985 |
- 0.984 |
- 0.974 |
- 0.983 |
- 0.966 |
- 0.935 |
- 0.975 |
- 0.934 |
- 0.985 |
- 0.98 |
- 0.976 |
- 0.971 |
- 0.965 |
- 0.983 |
- 0.986 |
- 0.984 |
- 0.973 |
- 0.979 |
- 0.975 |
- 0.981 |
- 0.976 |
- 0.963 |
- 0.985 |
- 0.987 |
- 0.971 |
- 0.971 |
- 0.974 |
- 0.979 |
- 0.979 |
- 0.969 |
- 0.968 |
- 0.985 |
- 0.975 |
- 0.961 |
- 0.977 |
- 0.965 |
- 0.984 |
- 0.973 |
- 0.969 |
- 0.976 |
- 0.985 |
- 0.979 |
- 0.973 |
- 0.98 |
- 0.98 |
- 0.976 |
- 0.964 |
- 0.959 |
- 0.967 |
- 0.964 |
- 0.977 |
- 0.974 |
- 0.974 |
- 0.979 |
- 0.978 |
- 0.982 |
- 0.979 |
- 0.976 |
- 0.973 |
- 0.967 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.963 |
- 0.974 |
- 0.979 |
- 0.977 |
- 0.976 |
- 0.975 |
- 0.967 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.977 |
- 0.981 |
- 0.982 |
- 0.977 |
- 0.944 |
- 0.978 |
- 0.98 |
- 0.984 |
- 0.979 |
- 0.975 |
- 0.934 |
- 0.961 |
- 0.938 |
- |
- 0.897 |
- 0.97 |
-
-
- | Liver |
- 574 |
- F |
- 314 |
- 111314.11 |
- CD |
- BXD29 |
- H1040 |
- 0.989 |
- 0.923 |
- 0.925 |
- 0.985 |
- 0.979 |
- 0.982 |
- 0.984 |
- 0.957 |
- 0.887 |
- 0.985 |
- 0.971 |
- 0.982 |
- 0.988 |
- 1 |
- 0.972 |
- 0.978 |
- 0.97 |
- 0.955 |
- 0.982 |
- 0.984 |
- 0.973 |
- 0.986 |
- 0.986 |
- 0.988 |
- 0.983 |
- 0.969 |
- 0.969 |
- 0.968 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.984 |
- 0.949 |
- 0.973 |
- 0.981 |
- 0.973 |
- 0.93 |
- 0.981 |
- 0.976 |
- 0.978 |
- 0.983 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.978 |
- 0.939 |
- 0.977 |
- 0.98 |
- 0.979 |
- 0.974 |
- 0.986 |
- 0.957 |
- 0.975 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.976 |
- 0.974 |
- 0.987 |
- 0.978 |
- 0.978 |
- 0.965 |
- 0.981 |
- 0.904 |
- 0.986 |
- 0.984 |
- 0.973 |
- 0.987 |
- 0.97 |
- 0.94 |
- 0.979 |
- 0.938 |
- 0.984 |
- 0.984 |
- 0.979 |
- 0.978 |
- 0.969 |
- 0.986 |
- 0.987 |
- 0.986 |
- 0.979 |
- 0.983 |
- 0.974 |
- 0.979 |
- 0.981 |
- 0.963 |
- 0.99 |
- 0.991 |
- 0.977 |
- 0.977 |
- 0.978 |
- 0.982 |
- 0.982 |
- 0.975 |
- 0.975 |
- 0.987 |
- 0.978 |
- 0.969 |
- 0.978 |
- 0.973 |
- 0.983 |
- 0.976 |
- 0.972 |
- 0.976 |
- 0.979 |
- 0.982 |
- 0.978 |
- 0.983 |
- 0.985 |
- 0.982 |
- 0.956 |
- 0.968 |
- 0.976 |
- 0.96 |
- 0.982 |
- 0.973 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.982 |
- 0.984 |
- 0.974 |
- 0.982 |
- 0.965 |
- 0.981 |
- 0.985 |
- 0.982 |
- 0.966 |
- 0.978 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.978 |
- 0.975 |
- 0.981 |
- 0.976 |
- 0.982 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.982 |
- 0.932 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.978 |
- 0.938 |
- 0.966 |
- 0.935 |
- |
- 0.887 |
- 0.97 |
-
-
- | Liver |
- 724 |
- F |
- 141 |
- 012615.08 |
- CD |
- BXD29 |
- H1044 |
- 0.97 |
- 0.952 |
- 0.952 |
- 0.97 |
- 0.978 |
- 0.981 |
- 0.969 |
- 0.963 |
- 0.926 |
- 0.973 |
- 0.968 |
- 0.978 |
- 0.972 |
- 0.972 |
- 1 |
- 0.976 |
- 0.967 |
- 0.962 |
- 0.971 |
- 0.977 |
- 0.967 |
- 0.972 |
- 0.974 |
- 0.975 |
- 0.974 |
- 0.974 |
- 0.974 |
- 0.974 |
- 0.978 |
- 0.977 |
- 0.97 |
- 0.973 |
- 0.958 |
- 0.964 |
- 0.966 |
- 0.978 |
- 0.953 |
- 0.971 |
- 0.97 |
- 0.965 |
- 0.974 |
- 0.971 |
- 0.962 |
- 0.973 |
- 0.971 |
- 0.962 |
- 0.968 |
- 0.973 |
- 0.971 |
- 0.976 |
- 0.974 |
- 0.964 |
- 0.977 |
- 0.976 |
- 0.972 |
- 0.977 |
- 0.976 |
- 0.966 |
- 0.974 |
- 0.969 |
- 0.976 |
- 0.967 |
- 0.968 |
- 0.919 |
- 0.969 |
- 0.969 |
- 0.975 |
- 0.972 |
- 0.976 |
- 0.953 |
- 0.98 |
- 0.952 |
- 0.975 |
- 0.969 |
- 0.972 |
- 0.969 |
- 0.969 |
- 0.971 |
- 0.974 |
- 0.973 |
- 0.974 |
- 0.972 |
- 0.972 |
- 0.968 |
- 0.974 |
- 0.969 |
- 0.972 |
- 0.975 |
- 0.97 |
- 0.973 |
- 0.964 |
- 0.973 |
- 0.974 |
- 0.973 |
- 0.972 |
- 0.974 |
- 0.974 |
- 0.972 |
- 0.978 |
- 0.974 |
- 0.974 |
- 0.978 |
- 0.976 |
- 0.972 |
- 0.975 |
- 0.968 |
- 0.963 |
- 0.967 |
- 0.963 |
- 0.977 |
- 0.948 |
- 0.961 |
- 0.967 |
- 0.972 |
- 0.974 |
- 0.975 |
- 0.964 |
- 0.973 |
- 0.969 |
- 0.971 |
- 0.971 |
- 0.977 |
- 0.971 |
- 0.977 |
- 0.973 |
- 0.973 |
- 0.975 |
- 0.97 |
- 0.971 |
- 0.976 |
- 0.967 |
- 0.977 |
- 0.974 |
- 0.968 |
- 0.967 |
- 0.975 |
- 0.968 |
- 0.973 |
- 0.977 |
- 0.97 |
- 0.972 |
- 0.942 |
- 0.968 |
- 0.967 |
- 0.976 |
- 0.973 |
- 0.97 |
- 0.952 |
- 0.964 |
- 0.957 |
- |
- 0.919 |
- 0.97 |
-
-
- | Liver |
- 200 |
- F |
- 259 |
- 042015.22 |
- CD |
- BXD32 |
- H2034 |
- 0.983 |
- 0.938 |
- 0.938 |
- 0.982 |
- 0.976 |
- 0.988 |
- 0.977 |
- 0.959 |
- 0.902 |
- 0.979 |
- 0.978 |
- 0.987 |
- 0.977 |
- 0.978 |
- 0.976 |
- 1 |
- 0.973 |
- 0.966 |
- 0.982 |
- 0.982 |
- 0.981 |
- 0.986 |
- 0.978 |
- 0.982 |
- 0.976 |
- 0.971 |
- 0.971 |
- 0.974 |
- 0.982 |
- 0.985 |
- 0.979 |
- 0.984 |
- 0.954 |
- 0.965 |
- 0.974 |
- 0.978 |
- 0.931 |
- 0.98 |
- 0.975 |
- 0.975 |
- 0.983 |
- 0.976 |
- 0.973 |
- 0.981 |
- 0.977 |
- 0.948 |
- 0.972 |
- 0.977 |
- 0.983 |
- 0.975 |
- 0.986 |
- 0.954 |
- 0.974 |
- 0.975 |
- 0.981 |
- 0.985 |
- 0.972 |
- 0.981 |
- 0.988 |
- 0.977 |
- 0.977 |
- 0.967 |
- 0.979 |
- 0.913 |
- 0.981 |
- 0.974 |
- 0.969 |
- 0.98 |
- 0.967 |
- 0.934 |
- 0.975 |
- 0.937 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.977 |
- 0.967 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.976 |
- 0.977 |
- 0.976 |
- 0.978 |
- 0.978 |
- 0.962 |
- 0.977 |
- 0.981 |
- 0.969 |
- 0.988 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.976 |
- 0.975 |
- 0.979 |
- 0.979 |
- 0.968 |
- 0.975 |
- 0.972 |
- 0.983 |
- 0.981 |
- 0.967 |
- 0.976 |
- 0.98 |
- 0.979 |
- 0.969 |
- 0.98 |
- 0.978 |
- 0.981 |
- 0.952 |
- 0.963 |
- 0.975 |
- 0.968 |
- 0.975 |
- 0.969 |
- 0.978 |
- 0.975 |
- 0.981 |
- 0.976 |
- 0.977 |
- 0.977 |
- 0.98 |
- 0.966 |
- 0.978 |
- 0.985 |
- 0.987 |
- 0.963 |
- 0.981 |
- 0.982 |
- 0.978 |
- 0.981 |
- 0.979 |
- 0.979 |
- 0.973 |
- 0.982 |
- 0.98 |
- 0.976 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.942 |
- 0.976 |
- 0.977 |
- 0.983 |
- 0.984 |
- 0.98 |
- 0.937 |
- 0.97 |
- 0.942 |
- |
- 0.902 |
- 0.97 |
-
-
- | Liver |
- 386 |
- F |
- 131 |
- 083016.01 |
- CD |
- BXD32 |
- H2494 |
- 0.971 |
- 0.943 |
- 0.942 |
- 0.972 |
- 0.965 |
- 0.972 |
- 0.967 |
- 0.978 |
- 0.922 |
- 0.972 |
- 0.963 |
- 0.974 |
- 0.965 |
- 0.97 |
- 0.967 |
- 0.973 |
- 1 |
- 0.969 |
- 0.977 |
- 0.973 |
- 0.957 |
- 0.972 |
- 0.969 |
- 0.972 |
- 0.979 |
- 0.979 |
- 0.979 |
- 0.978 |
- 0.976 |
- 0.967 |
- 0.971 |
- 0.969 |
- 0.938 |
- 0.979 |
- 0.981 |
- 0.985 |
- 0.959 |
- 0.972 |
- 0.982 |
- 0.976 |
- 0.973 |
- 0.971 |
- 0.978 |
- 0.971 |
- 0.975 |
- 0.954 |
- 0.96 |
- 0.97 |
- 0.969 |
- 0.967 |
- 0.974 |
- 0.972 |
- 0.982 |
- 0.971 |
- 0.974 |
- 0.967 |
- 0.979 |
- 0.967 |
- 0.982 |
- 0.983 |
- 0.959 |
- 0.952 |
- 0.978 |
- 0.896 |
- 0.968 |
- 0.969 |
- 0.977 |
- 0.971 |
- 0.978 |
- 0.959 |
- 0.975 |
- 0.958 |
- 0.968 |
- 0.967 |
- 0.972 |
- 0.983 |
- 0.989 |
- 0.968 |
- 0.976 |
- 0.975 |
- 0.964 |
- 0.963 |
- 0.956 |
- 0.968 |
- 0.972 |
- 0.975 |
- 0.972 |
- 0.97 |
- 0.983 |
- 0.969 |
- 0.975 |
- 0.979 |
- 0.981 |
- 0.981 |
- 0.981 |
- 0.973 |
- 0.973 |
- 0.977 |
- 0.976 |
- 0.976 |
- 0.97 |
- 0.971 |
- 0.978 |
- 0.971 |
- 0.965 |
- 0.969 |
- 0.978 |
- 0.969 |
- 0.966 |
- 0.978 |
- 0.928 |
- 0.979 |
- 0.977 |
- 0.969 |
- 0.967 |
- 0.977 |
- 0.97 |
- 0.962 |
- 0.968 |
- 0.966 |
- 0.971 |
- 0.963 |
- 0.968 |
- 0.962 |
- 0.977 |
- 0.973 |
- 0.97 |
- 0.982 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.978 |
- 0.973 |
- 0.974 |
- 0.965 |
- 0.969 |
- 0.964 |
- 0.967 |
- 0.981 |
- 0.964 |
- 0.973 |
- 0.921 |
- 0.967 |
- 0.961 |
- 0.968 |
- 0.969 |
- 0.967 |
- 0.958 |
- 0.973 |
- 0.959 |
- |
- 0.896 |
- 0.97 |
-
-
- | Liver |
- 201 |
- F |
- 170 |
- 101513.02 |
- CD |
- BXD34 |
- H1054 |
- 0.957 |
- 0.935 |
- 0.933 |
- 0.958 |
- 0.953 |
- 0.965 |
- 0.958 |
- 0.972 |
- 0.909 |
- 0.96 |
- 0.949 |
- 0.971 |
- 0.953 |
- 0.955 |
- 0.962 |
- 0.966 |
- 0.969 |
- 1 |
- 0.967 |
- 0.959 |
- 0.963 |
- 0.964 |
- 0.96 |
- 0.965 |
- 0.973 |
- 0.971 |
- 0.97 |
- 0.976 |
- 0.963 |
- 0.96 |
- 0.958 |
- 0.964 |
- 0.929 |
- 0.96 |
- 0.968 |
- 0.973 |
- 0.95 |
- 0.962 |
- 0.969 |
- 0.964 |
- 0.971 |
- 0.959 |
- 0.958 |
- 0.963 |
- 0.972 |
- 0.957 |
- 0.947 |
- 0.956 |
- 0.961 |
- 0.96 |
- 0.967 |
- 0.964 |
- 0.974 |
- 0.951 |
- 0.96 |
- 0.96 |
- 0.972 |
- 0.968 |
- 0.967 |
- 0.966 |
- 0.949 |
- 0.941 |
- 0.971 |
- 0.88 |
- 0.956 |
- 0.95 |
- 0.973 |
- 0.963 |
- 0.969 |
- 0.958 |
- 0.97 |
- 0.962 |
- 0.959 |
- 0.958 |
- 0.969 |
- 0.966 |
- 0.969 |
- 0.956 |
- 0.969 |
- 0.969 |
- 0.959 |
- 0.958 |
- 0.95 |
- 0.962 |
- 0.974 |
- 0.973 |
- 0.962 |
- 0.962 |
- 0.972 |
- 0.972 |
- 0.969 |
- 0.968 |
- 0.972 |
- 0.967 |
- 0.965 |
- 0.968 |
- 0.965 |
- 0.973 |
- 0.968 |
- 0.972 |
- 0.959 |
- 0.969 |
- 0.966 |
- 0.964 |
- 0.956 |
- 0.955 |
- 0.96 |
- 0.964 |
- 0.952 |
- 0.967 |
- 0.926 |
- 0.961 |
- 0.967 |
- 0.967 |
- 0.962 |
- 0.973 |
- 0.962 |
- 0.957 |
- 0.97 |
- 0.964 |
- 0.961 |
- 0.951 |
- 0.964 |
- 0.959 |
- 0.968 |
- 0.969 |
- 0.964 |
- 0.97 |
- 0.964 |
- 0.969 |
- 0.962 |
- 0.967 |
- 0.965 |
- 0.963 |
- 0.956 |
- 0.958 |
- 0.956 |
- 0.962 |
- 0.974 |
- 0.954 |
- 0.965 |
- 0.914 |
- 0.957 |
- 0.952 |
- 0.965 |
- 0.966 |
- 0.965 |
- 0.962 |
- 0.99 |
- 0.972 |
- |
- 0.88 |
- 0.96 |
-
-
- | Liver |
- 554 |
- F |
- 180 |
- 101513.05 |
- CD |
- BXD34 |
- H0765 |
- 0.984 |
- 0.941 |
- 0.943 |
- 0.985 |
- 0.976 |
- 0.986 |
- 0.978 |
- 0.962 |
- 0.905 |
- 0.979 |
- 0.978 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.971 |
- 0.982 |
- 0.977 |
- 0.967 |
- 1 |
- 0.984 |
- 0.975 |
- 0.983 |
- 0.979 |
- 0.984 |
- 0.978 |
- 0.973 |
- 0.973 |
- 0.974 |
- 0.986 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.958 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.936 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.981 |
- 0.979 |
- 0.983 |
- 0.977 |
- 0.945 |
- 0.976 |
- 0.983 |
- 0.981 |
- 0.975 |
- 0.985 |
- 0.96 |
- 0.978 |
- 0.977 |
- 0.983 |
- 0.98 |
- 0.976 |
- 0.977 |
- 0.988 |
- 0.979 |
- 0.975 |
- 0.972 |
- 0.981 |
- 0.915 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.983 |
- 0.966 |
- 0.939 |
- 0.976 |
- 0.939 |
- 0.984 |
- 0.978 |
- 0.977 |
- 0.979 |
- 0.974 |
- 0.983 |
- 0.989 |
- 0.989 |
- 0.976 |
- 0.984 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.975 |
- 0.981 |
- 0.985 |
- 0.975 |
- 0.979 |
- 0.986 |
- 0.997 |
- 0.997 |
- 0.981 |
- 0.981 |
- 0.984 |
- 0.985 |
- 0.972 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.98 |
- 0.976 |
- 0.977 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.986 |
- 0.956 |
- 0.969 |
- 0.98 |
- 0.97 |
- 0.976 |
- 0.982 |
- 0.981 |
- 0.984 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.982 |
- 0.979 |
- 0.969 |
- 0.983 |
- 0.986 |
- 0.984 |
- 0.971 |
- 0.983 |
- 0.984 |
- 0.985 |
- 0.986 |
- 0.985 |
- 0.979 |
- 0.975 |
- 0.982 |
- 0.987 |
- 0.977 |
- 0.984 |
- 0.984 |
- 0.98 |
- 0.94 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.984 |
- 0.977 |
- 0.939 |
- 0.977 |
- 0.944 |
- |
- 0.905 |
- 0.98 |
-
-
- | Liver |
- 550 |
- F |
- 276 |
- 102414.02 |
- CD |
- BXD39 |
- H1322 |
- 0.986 |
- 0.936 |
- 0.938 |
- 0.988 |
- 0.979 |
- 0.987 |
- 0.978 |
- 0.966 |
- 0.903 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.977 |
- 0.982 |
- 0.973 |
- 0.959 |
- 0.984 |
- 1 |
- 0.981 |
- 0.986 |
- 0.983 |
- 0.985 |
- 0.979 |
- 0.975 |
- 0.975 |
- 0.976 |
- 0.989 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.957 |
- 0.973 |
- 0.981 |
- 0.979 |
- 0.936 |
- 0.984 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.979 |
- 0.947 |
- 0.974 |
- 0.981 |
- 0.982 |
- 0.977 |
- 0.987 |
- 0.961 |
- 0.98 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.977 |
- 0.978 |
- 0.988 |
- 0.98 |
- 0.976 |
- 0.971 |
- 0.979 |
- 0.913 |
- 0.983 |
- 0.979 |
- 0.975 |
- 0.985 |
- 0.967 |
- 0.939 |
- 0.981 |
- 0.935 |
- 0.987 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.975 |
- 0.983 |
- 0.986 |
- 0.985 |
- 0.979 |
- 0.983 |
- 0.973 |
- 0.982 |
- 0.981 |
- 0.966 |
- 0.984 |
- 0.986 |
- 0.973 |
- 0.978 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.984 |
- 0.971 |
- 0.978 |
- 0.975 |
- 0.985 |
- 0.981 |
- 0.973 |
- 0.976 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.983 |
- 0.952 |
- 0.968 |
- 0.978 |
- 0.968 |
- 0.975 |
- 0.975 |
- 0.977 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.976 |
- 0.976 |
- 0.976 |
- 0.966 |
- 0.981 |
- 0.986 |
- 0.985 |
- 0.97 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.976 |
- 0.974 |
- 0.98 |
- 0.982 |
- 0.975 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.938 |
- 0.982 |
- 0.979 |
- 0.984 |
- 0.983 |
- 0.978 |
- 0.935 |
- 0.968 |
- 0.938 |
- |
- 0.903 |
- 0.98 |
-
-
- | Liver |
- 730 |
- F |
- 168 |
- 010614.06 |
- CD |
- BXD39 |
- H0673 |
- 0.979 |
- 0.923 |
- 0.923 |
- 0.981 |
- 0.97 |
- 0.985 |
- 0.977 |
- 0.962 |
- 0.885 |
- 0.971 |
- 0.969 |
- 0.979 |
- 0.973 |
- 0.973 |
- 0.967 |
- 0.981 |
- 0.957 |
- 0.963 |
- 0.975 |
- 0.981 |
- 1 |
- 0.982 |
- 0.977 |
- 0.978 |
- 0.97 |
- 0.965 |
- 0.964 |
- 0.971 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.944 |
- 0.961 |
- 0.972 |
- 0.968 |
- 0.923 |
- 0.98 |
- 0.972 |
- 0.976 |
- 0.979 |
- 0.974 |
- 0.966 |
- 0.979 |
- 0.978 |
- 0.947 |
- 0.966 |
- 0.972 |
- 0.977 |
- 0.971 |
- 0.983 |
- 0.95 |
- 0.966 |
- 0.966 |
- 0.976 |
- 0.981 |
- 0.967 |
- 0.981 |
- 0.98 |
- 0.969 |
- 0.967 |
- 0.954 |
- 0.976 |
- 0.896 |
- 0.972 |
- 0.966 |
- 0.964 |
- 0.977 |
- 0.955 |
- 0.928 |
- 0.969 |
- 0.928 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.969 |
- 0.957 |
- 0.978 |
- 0.983 |
- 0.981 |
- 0.979 |
- 0.977 |
- 0.969 |
- 0.977 |
- 0.978 |
- 0.954 |
- 0.976 |
- 0.983 |
- 0.968 |
- 0.984 |
- 0.975 |
- 0.976 |
- 0.977 |
- 0.979 |
- 0.978 |
- 0.976 |
- 0.974 |
- 0.966 |
- 0.97 |
- 0.969 |
- 0.979 |
- 0.981 |
- 0.96 |
- 0.974 |
- 0.98 |
- 0.979 |
- 0.967 |
- 0.98 |
- 0.972 |
- 0.977 |
- 0.947 |
- 0.96 |
- 0.978 |
- 0.971 |
- 0.971 |
- 0.964 |
- 0.974 |
- 0.973 |
- 0.984 |
- 0.975 |
- 0.973 |
- 0.969 |
- 0.978 |
- 0.959 |
- 0.976 |
- 0.984 |
- 0.986 |
- 0.958 |
- 0.977 |
- 0.977 |
- 0.98 |
- 0.977 |
- 0.974 |
- 0.971 |
- 0.969 |
- 0.976 |
- 0.976 |
- 0.972 |
- 0.97 |
- 0.98 |
- 0.979 |
- 0.932 |
- 0.975 |
- 0.975 |
- 0.985 |
- 0.985 |
- 0.986 |
- 0.928 |
- 0.96 |
- 0.94 |
- |
- 0.885 |
- 0.97 |
-
-
- | Liver |
- 180 |
- F |
- 289 |
- 102414.08 |
- CD |
- BXD40 |
- H1691 |
- 0.993 |
- 0.925 |
- 0.926 |
- 0.99 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.966 |
- 0.886 |
- 0.985 |
- 0.974 |
- 0.989 |
- 0.98 |
- 0.986 |
- 0.972 |
- 0.986 |
- 0.972 |
- 0.964 |
- 0.983 |
- 0.986 |
- 0.982 |
- 1 |
- 0.99 |
- 0.99 |
- 0.984 |
- 0.974 |
- 0.974 |
- 0.978 |
- 0.987 |
- 0.989 |
- 0.987 |
- 0.988 |
- 0.946 |
- 0.975 |
- 0.985 |
- 0.976 |
- 0.935 |
- 0.989 |
- 0.983 |
- 0.984 |
- 0.988 |
- 0.983 |
- 0.983 |
- 0.988 |
- 0.983 |
- 0.946 |
- 0.977 |
- 0.979 |
- 0.988 |
- 0.98 |
- 0.99 |
- 0.963 |
- 0.978 |
- 0.978 |
- 0.986 |
- 0.989 |
- 0.98 |
- 0.983 |
- 0.99 |
- 0.983 |
- 0.977 |
- 0.966 |
- 0.986 |
- 0.9 |
- 0.986 |
- 0.98 |
- 0.972 |
- 0.988 |
- 0.968 |
- 0.941 |
- 0.982 |
- 0.941 |
- 0.988 |
- 0.987 |
- 0.983 |
- 0.983 |
- 0.972 |
- 0.989 |
- 0.988 |
- 0.988 |
- 0.984 |
- 0.986 |
- 0.974 |
- 0.981 |
- 0.985 |
- 0.962 |
- 0.988 |
- 0.989 |
- 0.974 |
- 0.987 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.989 |
- 0.986 |
- 0.975 |
- 0.978 |
- 0.979 |
- 0.985 |
- 0.984 |
- 0.971 |
- 0.979 |
- 0.979 |
- 0.987 |
- 0.98 |
- 0.987 |
- 0.984 |
- 0.984 |
- 0.949 |
- 0.973 |
- 0.983 |
- 0.966 |
- 0.984 |
- 0.972 |
- 0.986 |
- 0.981 |
- 0.988 |
- 0.983 |
- 0.982 |
- 0.973 |
- 0.985 |
- 0.965 |
- 0.985 |
- 0.99 |
- 0.989 |
- 0.969 |
- 0.983 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.986 |
- 0.983 |
- 0.983 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.985 |
- 0.988 |
- 0.928 |
- 0.986 |
- 0.981 |
- 0.989 |
- 0.988 |
- 0.985 |
- 0.941 |
- 0.971 |
- 0.938 |
- |
- 0.886 |
- 0.98 |
-
-
- | Liver |
- 578 |
- F |
- 285 |
- 061913.06 |
- CD |
- BXD40 |
- H0680 |
- 0.99 |
- 0.922 |
- 0.924 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.99 |
- 0.963 |
- 0.884 |
- 0.985 |
- 0.969 |
- 0.986 |
- 0.984 |
- 0.986 |
- 0.974 |
- 0.978 |
- 0.969 |
- 0.96 |
- 0.979 |
- 0.983 |
- 0.977 |
- 0.99 |
- 1 |
- 0.991 |
- 0.982 |
- 0.974 |
- 0.974 |
- 0.973 |
- 0.985 |
- 0.988 |
- 0.988 |
- 0.985 |
- 0.944 |
- 0.979 |
- 0.984 |
- 0.974 |
- 0.937 |
- 0.988 |
- 0.981 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.98 |
- 0.988 |
- 0.984 |
- 0.951 |
- 0.983 |
- 0.982 |
- 0.986 |
- 0.984 |
- 0.988 |
- 0.967 |
- 0.978 |
- 0.981 |
- 0.989 |
- 0.988 |
- 0.976 |
- 0.978 |
- 0.986 |
- 0.981 |
- 0.982 |
- 0.964 |
- 0.984 |
- 0.899 |
- 0.985 |
- 0.986 |
- 0.974 |
- 0.986 |
- 0.967 |
- 0.943 |
- 0.983 |
- 0.945 |
- 0.986 |
- 0.99 |
- 0.988 |
- 0.981 |
- 0.972 |
- 0.99 |
- 0.987 |
- 0.988 |
- 0.984 |
- 0.984 |
- 0.971 |
- 0.98 |
- 0.983 |
- 0.963 |
- 0.987 |
- 0.991 |
- 0.973 |
- 0.982 |
- 0.978 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.976 |
- 0.991 |
- 0.982 |
- 0.972 |
- 0.98 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.969 |
- 0.98 |
- 0.982 |
- 0.987 |
- 0.977 |
- 0.983 |
- 0.981 |
- 0.979 |
- 0.953 |
- 0.974 |
- 0.979 |
- 0.968 |
- 0.989 |
- 0.974 |
- 0.984 |
- 0.98 |
- 0.984 |
- 0.987 |
- 0.983 |
- 0.973 |
- 0.981 |
- 0.969 |
- 0.987 |
- 0.989 |
- 0.985 |
- 0.971 |
- 0.979 |
- 0.986 |
- 0.983 |
- 0.979 |
- 0.982 |
- 0.98 |
- 0.986 |
- 0.976 |
- 0.982 |
- 0.988 |
- 0.987 |
- 0.985 |
- 0.987 |
- 0.926 |
- 0.987 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.987 |
- 0.945 |
- 0.968 |
- 0.942 |
- |
- 0.884 |
- 0.98 |
-
-
- | Liver |
- 240 |
- F |
- 264 |
- 042015.07 |
- CD |
- BXD44 |
- H1822 |
- 0.992 |
- 0.926 |
- 0.928 |
- 0.989 |
- 0.984 |
- 0.986 |
- 0.988 |
- 0.965 |
- 0.889 |
- 0.987 |
- 0.974 |
- 0.989 |
- 0.984 |
- 0.988 |
- 0.975 |
- 0.982 |
- 0.972 |
- 0.965 |
- 0.984 |
- 0.985 |
- 0.978 |
- 0.99 |
- 0.991 |
- 1 |
- 0.99 |
- 0.975 |
- 0.976 |
- 0.977 |
- 0.987 |
- 0.989 |
- 0.985 |
- 0.987 |
- 0.947 |
- 0.977 |
- 0.985 |
- 0.979 |
- 0.938 |
- 0.987 |
- 0.982 |
- 0.982 |
- 0.986 |
- 0.982 |
- 0.981 |
- 0.988 |
- 0.986 |
- 0.949 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.982 |
- 0.99 |
- 0.965 |
- 0.982 |
- 0.981 |
- 0.988 |
- 0.989 |
- 0.98 |
- 0.978 |
- 0.988 |
- 0.982 |
- 0.98 |
- 0.965 |
- 0.987 |
- 0.899 |
- 0.986 |
- 0.983 |
- 0.976 |
- 0.989 |
- 0.973 |
- 0.946 |
- 0.985 |
- 0.946 |
- 0.986 |
- 0.988 |
- 0.984 |
- 0.982 |
- 0.975 |
- 0.989 |
- 0.989 |
- 0.989 |
- 0.985 |
- 0.986 |
- 0.974 |
- 0.982 |
- 0.988 |
- 0.967 |
- 0.989 |
- 0.99 |
- 0.975 |
- 0.984 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.979 |
- 0.978 |
- 0.991 |
- 0.983 |
- 0.979 |
- 0.984 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.974 |
- 0.98 |
- 0.981 |
- 0.985 |
- 0.979 |
- 0.986 |
- 0.984 |
- 0.983 |
- 0.953 |
- 0.973 |
- 0.981 |
- 0.968 |
- 0.988 |
- 0.976 |
- 0.984 |
- 0.982 |
- 0.987 |
- 0.987 |
- 0.986 |
- 0.975 |
- 0.985 |
- 0.969 |
- 0.987 |
- 0.99 |
- 0.987 |
- 0.973 |
- 0.98 |
- 0.988 |
- 0.983 |
- 0.983 |
- 0.983 |
- 0.98 |
- 0.985 |
- 0.979 |
- 0.983 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.986 |
- 0.929 |
- 0.986 |
- 0.98 |
- 0.988 |
- 0.987 |
- 0.983 |
- 0.946 |
- 0.973 |
- 0.945 |
- |
- 0.889 |
- 0.98 |
-
-
- | Liver |
- 379 |
- F |
- 157 |
- 012615.15 |
- CD |
- BXD44 |
- H1505 |
- 0.982 |
- 0.93 |
- 0.931 |
- 0.98 |
- 0.974 |
- 0.977 |
- 0.979 |
- 0.976 |
- 0.902 |
- 0.981 |
- 0.961 |
- 0.986 |
- 0.973 |
- 0.983 |
- 0.974 |
- 0.976 |
- 0.979 |
- 0.973 |
- 0.978 |
- 0.979 |
- 0.97 |
- 0.984 |
- 0.982 |
- 0.99 |
- 1 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.979 |
- 0.981 |
- 0.934 |
- 0.976 |
- 0.986 |
- 0.981 |
- 0.956 |
- 0.98 |
- 0.985 |
- 0.98 |
- 0.982 |
- 0.973 |
- 0.977 |
- 0.978 |
- 0.985 |
- 0.956 |
- 0.967 |
- 0.973 |
- 0.978 |
- 0.977 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.971 |
- 0.98 |
- 0.979 |
- 0.985 |
- 0.973 |
- 0.984 |
- 0.981 |
- 0.967 |
- 0.951 |
- 0.987 |
- 0.89 |
- 0.977 |
- 0.973 |
- 0.978 |
- 0.983 |
- 0.984 |
- 0.966 |
- 0.986 |
- 0.964 |
- 0.976 |
- 0.979 |
- 0.983 |
- 0.981 |
- 0.981 |
- 0.977 |
- 0.982 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.961 |
- 0.972 |
- 0.984 |
- 0.973 |
- 0.984 |
- 0.981 |
- 0.983 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.981 |
- 0.98 |
- 0.979 |
- 0.985 |
- 0.976 |
- 0.989 |
- 0.983 |
- 0.99 |
- 0.974 |
- 0.98 |
- 0.977 |
- 0.977 |
- 0.969 |
- 0.977 |
- 0.975 |
- 0.977 |
- 0.975 |
- 0.981 |
- 0.938 |
- 0.977 |
- 0.981 |
- 0.966 |
- 0.981 |
- 0.978 |
- 0.977 |
- 0.97 |
- 0.98 |
- 0.977 |
- 0.98 |
- 0.964 |
- 0.981 |
- 0.967 |
- 0.984 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.976 |
- 0.985 |
- 0.978 |
- 0.981 |
- 0.976 |
- 0.977 |
- 0.976 |
- 0.968 |
- 0.97 |
- 0.979 |
- 0.983 |
- 0.973 |
- 0.981 |
- 0.919 |
- 0.974 |
- 0.968 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.964 |
- 0.977 |
- 0.96 |
- |
- 0.89 |
- 0.97 |
-
-
- | Liver |
- 384 |
- F |
- 145 |
- 012615.11 |
- CD |
- BXD45 |
- H1762 |
- 0.972 |
- 0.951 |
- 0.95 |
- 0.974 |
- 0.974 |
- 0.977 |
- 0.972 |
- 0.977 |
- 0.928 |
- 0.976 |
- 0.969 |
- 0.978 |
- 0.97 |
- 0.969 |
- 0.974 |
- 0.971 |
- 0.979 |
- 0.971 |
- 0.973 |
- 0.975 |
- 0.965 |
- 0.974 |
- 0.974 |
- 0.975 |
- 0.979 |
- 1 |
- 0.997 |
- 0.983 |
- 0.98 |
- 0.973 |
- 0.972 |
- 0.971 |
- 0.944 |
- 0.978 |
- 0.976 |
- 0.986 |
- 0.968 |
- 0.978 |
- 0.979 |
- 0.971 |
- 0.975 |
- 0.975 |
- 0.973 |
- 0.979 |
- 0.981 |
- 0.97 |
- 0.968 |
- 0.976 |
- 0.974 |
- 0.979 |
- 0.976 |
- 0.981 |
- 0.988 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.985 |
- 0.964 |
- 0.977 |
- 0.98 |
- 0.96 |
- 0.956 |
- 0.976 |
- 0.903 |
- 0.969 |
- 0.966 |
- 0.979 |
- 0.971 |
- 0.982 |
- 0.973 |
- 0.984 |
- 0.967 |
- 0.975 |
- 0.972 |
- 0.974 |
- 0.98 |
- 0.983 |
- 0.972 |
- 0.976 |
- 0.975 |
- 0.975 |
- 0.969 |
- 0.962 |
- 0.97 |
- 0.982 |
- 0.968 |
- 0.979 |
- 0.973 |
- 0.975 |
- 0.971 |
- 0.966 |
- 0.974 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.976 |
- 0.974 |
- 0.981 |
- 0.978 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.972 |
- 0.969 |
- 0.971 |
- 0.971 |
- 0.96 |
- 0.977 |
- 0.938 |
- 0.975 |
- 0.973 |
- 0.972 |
- 0.973 |
- 0.979 |
- 0.969 |
- 0.966 |
- 0.974 |
- 0.973 |
- 0.969 |
- 0.967 |
- 0.969 |
- 0.969 |
- 0.978 |
- 0.976 |
- 0.971 |
- 0.986 |
- 0.971 |
- 0.98 |
- 0.969 |
- 0.977 |
- 0.974 |
- 0.968 |
- 0.966 |
- 0.97 |
- 0.965 |
- 0.97 |
- 0.984 |
- 0.967 |
- 0.975 |
- 0.928 |
- 0.97 |
- 0.967 |
- 0.976 |
- 0.971 |
- 0.97 |
- 0.967 |
- 0.971 |
- 0.968 |
- |
- 0.903 |
- 0.97 |
-
-
- | Liver |
- 507 |
- F |
- 281 |
- 121515.12 |
- CD |
- BXD45 |
- H1826 |
- 0.973 |
- 0.952 |
- 0.952 |
- 0.975 |
- 0.975 |
- 0.977 |
- 0.972 |
- 0.976 |
- 0.928 |
- 0.976 |
- 0.97 |
- 0.978 |
- 0.97 |
- 0.969 |
- 0.974 |
- 0.971 |
- 0.979 |
- 0.97 |
- 0.973 |
- 0.975 |
- 0.964 |
- 0.974 |
- 0.974 |
- 0.976 |
- 0.979 |
- 0.997 |
- 1 |
- 0.983 |
- 0.981 |
- 0.973 |
- 0.972 |
- 0.971 |
- 0.945 |
- 0.978 |
- 0.977 |
- 0.986 |
- 0.968 |
- 0.978 |
- 0.98 |
- 0.972 |
- 0.975 |
- 0.976 |
- 0.974 |
- 0.979 |
- 0.981 |
- 0.969 |
- 0.969 |
- 0.976 |
- 0.975 |
- 0.98 |
- 0.976 |
- 0.982 |
- 0.989 |
- 0.974 |
- 0.973 |
- 0.973 |
- 0.985 |
- 0.964 |
- 0.977 |
- 0.981 |
- 0.961 |
- 0.957 |
- 0.976 |
- 0.904 |
- 0.97 |
- 0.967 |
- 0.979 |
- 0.972 |
- 0.982 |
- 0.973 |
- 0.985 |
- 0.967 |
- 0.975 |
- 0.972 |
- 0.974 |
- 0.981 |
- 0.984 |
- 0.973 |
- 0.976 |
- 0.976 |
- 0.975 |
- 0.97 |
- 0.963 |
- 0.971 |
- 0.982 |
- 0.968 |
- 0.979 |
- 0.973 |
- 0.974 |
- 0.971 |
- 0.967 |
- 0.975 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.976 |
- 0.975 |
- 0.981 |
- 0.978 |
- 0.981 |
- 0.978 |
- 0.978 |
- 0.979 |
- 0.977 |
- 0.972 |
- 0.97 |
- 0.972 |
- 0.972 |
- 0.961 |
- 0.978 |
- 0.939 |
- 0.975 |
- 0.974 |
- 0.972 |
- 0.974 |
- 0.979 |
- 0.97 |
- 0.966 |
- 0.974 |
- 0.974 |
- 0.969 |
- 0.968 |
- 0.969 |
- 0.969 |
- 0.979 |
- 0.976 |
- 0.971 |
- 0.986 |
- 0.971 |
- 0.98 |
- 0.969 |
- 0.978 |
- 0.975 |
- 0.969 |
- 0.967 |
- 0.97 |
- 0.966 |
- 0.97 |
- 0.984 |
- 0.968 |
- 0.975 |
- 0.928 |
- 0.971 |
- 0.968 |
- 0.975 |
- 0.971 |
- 0.969 |
- 0.967 |
- 0.972 |
- 0.967 |
- |
- 0.904 |
- 0.97 |
-
-
- | Liver |
- 188 |
- F |
- 260 |
- 042015.27 |
- CD |
- BXD48 |
- H2054 |
- 0.974 |
- 0.943 |
- 0.942 |
- 0.975 |
- 0.969 |
- 0.976 |
- 0.971 |
- 0.983 |
- 0.915 |
- 0.971 |
- 0.962 |
- 0.984 |
- 0.963 |
- 0.968 |
- 0.974 |
- 0.974 |
- 0.978 |
- 0.976 |
- 0.974 |
- 0.976 |
- 0.971 |
- 0.978 |
- 0.973 |
- 0.977 |
- 0.983 |
- 0.983 |
- 0.983 |
- 1 |
- 0.981 |
- 0.973 |
- 0.974 |
- 0.974 |
- 0.933 |
- 0.973 |
- 0.98 |
- 0.983 |
- 0.965 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.981 |
- 0.97 |
- 0.974 |
- 0.976 |
- 0.983 |
- 0.965 |
- 0.96 |
- 0.967 |
- 0.978 |
- 0.978 |
- 0.978 |
- 0.982 |
- 0.987 |
- 0.964 |
- 0.975 |
- 0.973 |
- 0.986 |
- 0.971 |
- 0.979 |
- 0.979 |
- 0.959 |
- 0.948 |
- 0.985 |
- 0.89 |
- 0.968 |
- 0.962 |
- 0.977 |
- 0.974 |
- 0.98 |
- 0.97 |
- 0.983 |
- 0.969 |
- 0.973 |
- 0.971 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.97 |
- 0.977 |
- 0.976 |
- 0.975 |
- 0.968 |
- 0.956 |
- 0.967 |
- 0.983 |
- 0.968 |
- 0.976 |
- 0.973 |
- 0.979 |
- 0.979 |
- 0.968 |
- 0.975 |
- 0.977 |
- 0.984 |
- 0.984 |
- 0.974 |
- 0.978 |
- 0.985 |
- 0.976 |
- 0.985 |
- 0.97 |
- 0.988 |
- 0.978 |
- 0.978 |
- 0.969 |
- 0.971 |
- 0.972 |
- 0.974 |
- 0.964 |
- 0.978 |
- 0.929 |
- 0.976 |
- 0.982 |
- 0.971 |
- 0.973 |
- 0.977 |
- 0.975 |
- 0.963 |
- 0.976 |
- 0.969 |
- 0.969 |
- 0.959 |
- 0.971 |
- 0.963 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.984 |
- 0.975 |
- 0.983 |
- 0.974 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.968 |
- 0.966 |
- 0.966 |
- 0.972 |
- 0.981 |
- 0.969 |
- 0.98 |
- 0.92 |
- 0.972 |
- 0.964 |
- 0.978 |
- 0.973 |
- 0.974 |
- 0.969 |
- 0.977 |
- 0.963 |
- |
- 0.89 |
- 0.97 |
-
-
- | Liver |
- 518 |
- F |
- 275 |
- 121515.18 |
- CD |
- BXD48 |
- H1835 |
- 0.989 |
- 0.943 |
- 0.945 |
- 0.991 |
- 0.985 |
- 0.989 |
- 0.985 |
- 0.968 |
- 0.907 |
- 0.985 |
- 0.982 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.978 |
- 0.982 |
- 0.976 |
- 0.963 |
- 0.986 |
- 0.989 |
- 0.979 |
- 0.987 |
- 0.985 |
- 0.987 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.981 |
- 1 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.959 |
- 0.977 |
- 0.982 |
- 0.983 |
- 0.943 |
- 0.986 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.987 |
- 0.984 |
- 0.989 |
- 0.982 |
- 0.955 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.987 |
- 0.967 |
- 0.983 |
- 0.984 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.977 |
- 0.989 |
- 0.984 |
- 0.978 |
- 0.973 |
- 0.982 |
- 0.916 |
- 0.983 |
- 0.982 |
- 0.98 |
- 0.987 |
- 0.972 |
- 0.949 |
- 0.984 |
- 0.943 |
- 0.99 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.977 |
- 0.988 |
- 0.989 |
- 0.988 |
- 0.985 |
- 0.986 |
- 0.977 |
- 0.984 |
- 0.986 |
- 0.968 |
- 0.988 |
- 0.988 |
- 0.974 |
- 0.981 |
- 0.981 |
- 0.987 |
- 0.987 |
- 0.983 |
- 0.982 |
- 0.985 |
- 0.985 |
- 0.974 |
- 0.982 |
- 0.977 |
- 0.989 |
- 0.988 |
- 0.982 |
- 0.984 |
- 0.989 |
- 0.985 |
- 0.981 |
- 0.985 |
- 0.981 |
- 0.986 |
- 0.957 |
- 0.971 |
- 0.98 |
- 0.972 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.972 |
- 0.984 |
- 0.986 |
- 0.985 |
- 0.976 |
- 0.982 |
- 0.986 |
- 0.985 |
- 0.986 |
- 0.985 |
- 0.976 |
- 0.98 |
- 0.983 |
- 0.985 |
- 0.98 |
- 0.986 |
- 0.984 |
- 0.983 |
- 0.941 |
- 0.985 |
- 0.983 |
- 0.987 |
- 0.984 |
- 0.979 |
- 0.943 |
- 0.971 |
- 0.948 |
- |
- 0.907 |
- 0.98 |
-
-
- | Liver |
- 233 |
- F |
- 25 |
- 051112.05 |
- CD |
- BXD48a |
- H0209 |
- 0.99 |
- 0.927 |
- 0.929 |
- 0.987 |
- 0.983 |
- 0.988 |
- 0.986 |
- 0.962 |
- 0.891 |
- 0.983 |
- 0.975 |
- 0.986 |
- 0.982 |
- 0.985 |
- 0.977 |
- 0.985 |
- 0.967 |
- 0.96 |
- 0.98 |
- 0.985 |
- 0.981 |
- 0.989 |
- 0.988 |
- 0.989 |
- 0.979 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.985 |
- 1 |
- 0.984 |
- 0.988 |
- 0.951 |
- 0.973 |
- 0.979 |
- 0.975 |
- 0.937 |
- 0.987 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.986 |
- 0.981 |
- 0.949 |
- 0.98 |
- 0.982 |
- 0.987 |
- 0.983 |
- 0.988 |
- 0.963 |
- 0.98 |
- 0.985 |
- 0.99 |
- 1 |
- 0.976 |
- 0.98 |
- 0.988 |
- 0.981 |
- 0.981 |
- 0.967 |
- 0.979 |
- 0.905 |
- 0.982 |
- 0.98 |
- 0.97 |
- 0.986 |
- 0.967 |
- 0.94 |
- 0.982 |
- 0.938 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.981 |
- 0.971 |
- 0.988 |
- 0.987 |
- 0.987 |
- 0.986 |
- 0.985 |
- 0.976 |
- 0.979 |
- 0.982 |
- 0.96 |
- 0.984 |
- 0.988 |
- 0.971 |
- 0.986 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.984 |
- 0.98 |
- 0.972 |
- 0.978 |
- 0.976 |
- 0.985 |
- 0.982 |
- 0.969 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.954 |
- 0.97 |
- 0.979 |
- 0.97 |
- 0.983 |
- 0.97 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.978 |
- 0.984 |
- 0.97 |
- 0.983 |
- 0.989 |
- 0.991 |
- 0.97 |
- 0.985 |
- 0.99 |
- 0.982 |
- 0.983 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.985 |
- 0.985 |
- 0.933 |
- 0.984 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.985 |
- 0.938 |
- 0.966 |
- 0.94 |
- |
- 0.891 |
- 0.98 |
-
-
- | Liver |
- 571 |
- F |
- 308 |
- 062013.16 |
- CD |
- BXD53 |
- H0848 |
- 0.989 |
- 0.919 |
- 0.921 |
- 0.988 |
- 0.978 |
- 0.983 |
- 0.987 |
- 0.966 |
- 0.883 |
- 0.981 |
- 0.97 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.97 |
- 0.979 |
- 0.971 |
- 0.958 |
- 0.981 |
- 0.983 |
- 0.979 |
- 0.987 |
- 0.988 |
- 0.985 |
- 0.979 |
- 0.972 |
- 0.972 |
- 0.974 |
- 0.985 |
- 0.984 |
- 1 |
- 0.984 |
- 0.943 |
- 0.978 |
- 0.986 |
- 0.975 |
- 0.932 |
- 0.987 |
- 0.984 |
- 0.984 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.987 |
- 0.983 |
- 0.946 |
- 0.976 |
- 0.978 |
- 0.986 |
- 0.979 |
- 0.987 |
- 0.964 |
- 0.974 |
- 0.975 |
- 0.988 |
- 0.984 |
- 0.974 |
- 0.981 |
- 0.986 |
- 0.98 |
- 0.975 |
- 0.961 |
- 0.983 |
- 0.895 |
- 0.983 |
- 0.984 |
- 0.973 |
- 0.984 |
- 0.964 |
- 0.939 |
- 0.978 |
- 0.941 |
- 0.988 |
- 0.987 |
- 0.989 |
- 0.98 |
- 0.97 |
- 0.988 |
- 0.987 |
- 0.989 |
- 0.98 |
- 0.983 |
- 0.968 |
- 0.981 |
- 0.98 |
- 0.964 |
- 0.983 |
- 0.988 |
- 0.976 |
- 0.979 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.979 |
- 0.97 |
- 0.979 |
- 0.975 |
- 0.982 |
- 0.982 |
- 0.965 |
- 0.978 |
- 0.981 |
- 0.997 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.947 |
- 0.975 |
- 0.983 |
- 0.97 |
- 0.982 |
- 0.973 |
- 0.987 |
- 0.978 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.969 |
- 0.98 |
- 0.964 |
- 0.985 |
- 0.988 |
- 0.985 |
- 0.969 |
- 0.982 |
- 0.984 |
- 0.987 |
- 0.981 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.976 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.988 |
- 0.987 |
- 0.924 |
- 0.985 |
- 0.983 |
- 0.986 |
- 0.988 |
- 0.989 |
- 0.941 |
- 0.966 |
- 0.936 |
- |
- 0.883 |
- 0.98 |
-
-
- | Liver |
- 235 |
- F |
- 104 |
- 050912.08 |
- CD |
- BXD60 |
- H0235 |
- 0.987 |
- 0.928 |
- 0.928 |
- 0.987 |
- 0.982 |
- 0.987 |
- 0.986 |
- 0.967 |
- 0.894 |
- 0.982 |
- 0.973 |
- 0.983 |
- 0.98 |
- 0.984 |
- 0.973 |
- 0.984 |
- 0.969 |
- 0.964 |
- 0.979 |
- 0.982 |
- 0.984 |
- 0.988 |
- 0.985 |
- 0.987 |
- 0.981 |
- 0.971 |
- 0.971 |
- 0.974 |
- 0.984 |
- 0.988 |
- 0.984 |
- 1 |
- 0.947 |
- 0.972 |
- 0.981 |
- 0.976 |
- 0.938 |
- 0.982 |
- 0.977 |
- 0.977 |
- 0.984 |
- 0.978 |
- 0.976 |
- 0.983 |
- 0.983 |
- 0.95 |
- 0.976 |
- 0.98 |
- 0.982 |
- 0.979 |
- 0.987 |
- 0.959 |
- 0.975 |
- 0.978 |
- 0.984 |
- 0.988 |
- 0.974 |
- 0.981 |
- 0.986 |
- 0.979 |
- 0.975 |
- 0.96 |
- 0.982 |
- 0.902 |
- 0.978 |
- 0.974 |
- 0.97 |
- 0.985 |
- 0.967 |
- 0.942 |
- 0.979 |
- 0.94 |
- 0.984 |
- 0.986 |
- 0.984 |
- 0.979 |
- 0.968 |
- 0.984 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.976 |
- 0.979 |
- 0.983 |
- 0.96 |
- 0.984 |
- 0.987 |
- 0.975 |
- 0.986 |
- 0.978 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.977 |
- 0.985 |
- 0.978 |
- 0.973 |
- 0.976 |
- 0.976 |
- 0.983 |
- 0.98 |
- 0.974 |
- 0.981 |
- 0.982 |
- 0.984 |
- 0.974 |
- 0.982 |
- 0.978 |
- 0.983 |
- 0.95 |
- 0.967 |
- 0.979 |
- 0.969 |
- 0.983 |
- 0.97 |
- 0.98 |
- 0.979 |
- 0.987 |
- 0.983 |
- 0.985 |
- 0.977 |
- 0.988 |
- 0.968 |
- 0.982 |
- 0.987 |
- 0.987 |
- 0.968 |
- 0.982 |
- 0.984 |
- 0.982 |
- 0.983 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.982 |
- 0.983 |
- 0.934 |
- 0.98 |
- 0.977 |
- 0.989 |
- 0.987 |
- 0.985 |
- 0.94 |
- 0.965 |
- 0.947 |
- |
- 0.894 |
- 0.98 |
-
-
- | Liver |
- 530 |
- F |
- 51 |
- 021213.14 |
- CD |
- BXD60 |
- H0171 |
- 0.946 |
- 0.95 |
- 0.953 |
- 0.952 |
- 0.955 |
- 0.962 |
- 0.94 |
- 0.919 |
- 0.919 |
- 0.951 |
- 0.97 |
- 0.947 |
- 0.96 |
- 0.949 |
- 0.958 |
- 0.954 |
- 0.938 |
- 0.929 |
- 0.958 |
- 0.957 |
- 0.944 |
- 0.946 |
- 0.944 |
- 0.947 |
- 0.934 |
- 0.944 |
- 0.945 |
- 0.933 |
- 0.959 |
- 0.951 |
- 0.943 |
- 0.947 |
- 1 |
- 0.932 |
- 0.932 |
- 0.953 |
- 0.904 |
- 0.942 |
- 0.933 |
- 0.937 |
- 0.95 |
- 0.954 |
- 0.939 |
- 0.951 |
- 0.94 |
- 0.923 |
- 0.949 |
- 0.96 |
- 0.944 |
- 0.942 |
- 0.951 |
- 0.915 |
- 0.945 |
- 0.961 |
- 0.948 |
- 0.951 |
- 0.941 |
- 0.936 |
- 0.951 |
- 0.941 |
- 0.958 |
- 0.973 |
- 0.938 |
- 0.943 |
- 0.949 |
- 0.95 |
- 0.958 |
- 0.951 |
- 0.937 |
- 0.901 |
- 0.946 |
- 0.9 |
- 0.959 |
- 0.94 |
- 0.933 |
- 0.941 |
- 0.939 |
- 0.951 |
- 0.959 |
- 0.955 |
- 0.945 |
- 0.958 |
- 0.97 |
- 0.955 |
- 0.945 |
- 0.953 |
- 0.945 |
- 0.949 |
- 0.934 |
- 0.941 |
- 0.947 |
- 0.959 |
- 0.958 |
- 0.943 |
- 0.943 |
- 0.952 |
- 0.959 |
- 0.928 |
- 0.956 |
- 0.932 |
- 0.963 |
- 0.946 |
- 0.952 |
- 0.945 |
- 0.965 |
- 0.943 |
- 0.944 |
- 0.95 |
- 0.951 |
- 0.957 |
- 0.97 |
- 0.922 |
- 0.935 |
- 0.947 |
- 0.941 |
- 0.958 |
- 0.938 |
- 0.965 |
- 0.946 |
- 0.953 |
- 0.949 |
- 0.971 |
- 0.944 |
- 0.96 |
- 0.946 |
- 0.949 |
- 0.951 |
- 0.932 |
- 0.947 |
- 0.949 |
- 0.944 |
- 0.957 |
- 0.959 |
- 0.933 |
- 0.941 |
- 0.966 |
- 0.961 |
- 0.94 |
- 0.951 |
- 0.957 |
- 0.943 |
- 0.964 |
- 0.948 |
- 0.964 |
- 0.953 |
- 0.95 |
- 0.935 |
- 0.9 |
- 0.94 |
- 0.915 |
- |
- 0.9 |
- 0.95 |
-
-
- | Liver |
- 188 |
- F |
- 132 |
- 111414.02 |
- CD |
- BXD61 |
- H1770 |
- 0.976 |
- 0.922 |
- 0.923 |
- 0.974 |
- 0.973 |
- 0.971 |
- 0.979 |
- 0.974 |
- 0.893 |
- 0.976 |
- 0.959 |
- 0.977 |
- 0.971 |
- 0.973 |
- 0.964 |
- 0.965 |
- 0.979 |
- 0.96 |
- 0.972 |
- 0.973 |
- 0.961 |
- 0.975 |
- 0.979 |
- 0.977 |
- 0.976 |
- 0.978 |
- 0.978 |
- 0.973 |
- 0.977 |
- 0.973 |
- 0.978 |
- 0.972 |
- 0.932 |
- 1 |
- 0.986 |
- 0.976 |
- 0.948 |
- 0.981 |
- 0.983 |
- 0.979 |
- 0.977 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.98 |
- 0.951 |
- 0.973 |
- 0.976 |
- 0.978 |
- 0.973 |
- 0.975 |
- 0.974 |
- 0.978 |
- 0.974 |
- 0.977 |
- 0.973 |
- 0.975 |
- 0.972 |
- 0.978 |
- 0.985 |
- 0.961 |
- 0.949 |
- 0.976 |
- 0.884 |
- 0.973 |
- 0.975 |
- 0.971 |
- 0.975 |
- 0.968 |
- 0.954 |
- 0.979 |
- 0.953 |
- 0.973 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.977 |
- 0.977 |
- 0.969 |
- 0.954 |
- 0.969 |
- 0.977 |
- 0.964 |
- 0.978 |
- 0.975 |
- 0.978 |
- 0.971 |
- 0.974 |
- 0.973 |
- 0.974 |
- 0.98 |
- 0.98 |
- 0.975 |
- 0.972 |
- 0.971 |
- 0.975 |
- 0.972 |
- 0.967 |
- 0.973 |
- 0.969 |
- 0.972 |
- 0.966 |
- 0.976 |
- 0.986 |
- 0.978 |
- 0.968 |
- 0.973 |
- 0.932 |
- 0.986 |
- 0.98 |
- 0.97 |
- 0.976 |
- 0.971 |
- 0.979 |
- 0.965 |
- 0.974 |
- 0.976 |
- 0.971 |
- 0.961 |
- 0.967 |
- 0.959 |
- 0.979 |
- 0.976 |
- 0.971 |
- 0.978 |
- 0.974 |
- 0.978 |
- 0.975 |
- 0.973 |
- 0.972 |
- 0.978 |
- 0.972 |
- 0.96 |
- 0.966 |
- 0.977 |
- 0.982 |
- 0.97 |
- 0.98 |
- 0.909 |
- 0.977 |
- 0.965 |
- 0.974 |
- 0.972 |
- 0.975 |
- 0.953 |
- 0.965 |
- 0.944 |
- |
- 0.884 |
- 0.97 |
-
-
- | Liver |
- 524 |
- F |
- 324 |
- 121515.23 |
- CD |
- BXD61 |
- H1841 |
- 0.985 |
- 0.92 |
- 0.922 |
- 0.984 |
- 0.97 |
- 0.977 |
- 0.98 |
- 0.978 |
- 0.891 |
- 0.976 |
- 0.962 |
- 0.985 |
- 0.973 |
- 0.981 |
- 0.966 |
- 0.974 |
- 0.981 |
- 0.968 |
- 0.981 |
- 0.981 |
- 0.972 |
- 0.985 |
- 0.984 |
- 0.985 |
- 0.986 |
- 0.976 |
- 0.977 |
- 0.98 |
- 0.982 |
- 0.979 |
- 0.986 |
- 0.981 |
- 0.932 |
- 0.986 |
- 1 |
- 0.979 |
- 0.946 |
- 0.983 |
- 0.988 |
- 0.986 |
- 0.983 |
- 0.981 |
- 0.986 |
- 0.983 |
- 0.986 |
- 0.949 |
- 0.966 |
- 0.973 |
- 0.981 |
- 0.976 |
- 0.986 |
- 0.975 |
- 0.983 |
- 0.969 |
- 0.983 |
- 0.979 |
- 0.982 |
- 0.979 |
- 0.987 |
- 0.983 |
- 0.963 |
- 0.951 |
- 0.987 |
- 0.883 |
- 0.979 |
- 0.978 |
- 0.974 |
- 0.985 |
- 0.972 |
- 0.953 |
- 0.982 |
- 0.954 |
- 0.979 |
- 0.98 |
- 0.986 |
- 0.983 |
- 0.982 |
- 0.98 |
- 0.984 |
- 0.986 |
- 0.976 |
- 0.976 |
- 0.958 |
- 0.973 |
- 0.981 |
- 0.969 |
- 0.984 |
- 0.985 |
- 0.983 |
- 0.977 |
- 0.982 |
- 0.982 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.979 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.976 |
- 0.979 |
- 0.968 |
- 0.975 |
- 0.97 |
- 0.985 |
- 0.987 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.932 |
- 0.98 |
- 0.986 |
- 0.966 |
- 0.978 |
- 0.974 |
- 0.984 |
- 0.97 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.961 |
- 0.976 |
- 0.957 |
- 0.985 |
- 0.986 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.985 |
- 0.988 |
- 0.98 |
- 0.979 |
- 0.984 |
- 0.974 |
- 0.969 |
- 0.974 |
- 0.978 |
- 0.984 |
- 0.978 |
- 0.985 |
- 0.913 |
- 0.98 |
- 0.972 |
- 0.98 |
- 0.981 |
- 0.982 |
- 0.954 |
- 0.974 |
- 0.947 |
- |
- 0.883 |
- 0.97 |
-
-
- | Liver |
- 253 |
- F |
- 257 |
- 042015.05 |
- CD |
- BXD62 |
- H1847 |
- 0.975 |
- 0.956 |
- 0.956 |
- 0.979 |
- 0.978 |
- 0.982 |
- 0.972 |
- 0.977 |
- 0.933 |
- 0.975 |
- 0.976 |
- 0.982 |
- 0.973 |
- 0.973 |
- 0.978 |
- 0.978 |
- 0.985 |
- 0.973 |
- 0.981 |
- 0.979 |
- 0.968 |
- 0.976 |
- 0.974 |
- 0.979 |
- 0.981 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.983 |
- 0.975 |
- 0.975 |
- 0.976 |
- 0.953 |
- 0.976 |
- 0.979 |
- 1 |
- 0.966 |
- 0.977 |
- 0.982 |
- 0.975 |
- 0.979 |
- 0.975 |
- 0.975 |
- 0.979 |
- 0.982 |
- 0.965 |
- 0.969 |
- 0.976 |
- 0.977 |
- 0.977 |
- 0.98 |
- 0.975 |
- 0.988 |
- 0.977 |
- 0.979 |
- 0.975 |
- 0.985 |
- 0.969 |
- 0.983 |
- 0.981 |
- 0.966 |
- 0.962 |
- 0.981 |
- 0.91 |
- 0.971 |
- 0.97 |
- 0.983 |
- 0.976 |
- 0.98 |
- 0.962 |
- 0.984 |
- 0.961 |
- 0.977 |
- 0.972 |
- 0.975 |
- 0.981 |
- 0.984 |
- 0.974 |
- 0.982 |
- 0.98 |
- 0.973 |
- 0.972 |
- 0.971 |
- 0.973 |
- 0.981 |
- 0.975 |
- 0.977 |
- 0.976 |
- 0.978 |
- 0.974 |
- 0.973 |
- 0.983 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.979 |
- 0.978 |
- 0.972 |
- 0.975 |
- 0.976 |
- 0.97 |
- 0.986 |
- 0.948 |
- 0.972 |
- 0.976 |
- 0.977 |
- 0.975 |
- 0.983 |
- 0.973 |
- 0.972 |
- 0.976 |
- 0.975 |
- 0.976 |
- 0.975 |
- 0.974 |
- 0.971 |
- 0.983 |
- 0.979 |
- 0.976 |
- 0.985 |
- 0.979 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.98 |
- 0.971 |
- 0.97 |
- 0.978 |
- 0.973 |
- 0.972 |
- 0.986 |
- 0.973 |
- 0.977 |
- 0.938 |
- 0.974 |
- 0.972 |
- 0.979 |
- 0.976 |
- 0.971 |
- 0.961 |
- 0.977 |
- 0.967 |
- |
- 0.91 |
- 0.98 |
-
-
- | Liver |
- 353 |
- F |
- 178 |
- 121214.20 |
- CD |
- BXD62 |
- H1436 |
- 0.929 |
- 0.944 |
- 0.941 |
- 0.933 |
- 0.943 |
- 0.939 |
- 0.932 |
- 0.968 |
- 0.939 |
- 0.935 |
- 0.921 |
- 0.946 |
- 0.925 |
- 0.93 |
- 0.953 |
- 0.931 |
- 0.959 |
- 0.95 |
- 0.936 |
- 0.936 |
- 0.923 |
- 0.935 |
- 0.937 |
- 0.938 |
- 0.956 |
- 0.968 |
- 0.968 |
- 0.965 |
- 0.943 |
- 0.937 |
- 0.932 |
- 0.938 |
- 0.904 |
- 0.948 |
- 0.946 |
- 0.966 |
- 1 |
- 0.939 |
- 0.956 |
- 0.94 |
- 0.936 |
- 0.931 |
- 0.936 |
- 0.932 |
- 0.949 |
- 0.969 |
- 0.929 |
- 0.938 |
- 0.934 |
- 0.954 |
- 0.935 |
- 0.98 |
- 0.968 |
- 0.943 |
- 0.939 |
- 0.937 |
- 0.963 |
- 0.924 |
- 0.941 |
- 0.951 |
- 0.928 |
- 0.911 |
- 0.946 |
- 0.875 |
- 0.92 |
- 0.924 |
- 0.952 |
- 0.935 |
- 0.971 |
- 0.977 |
- 0.96 |
- 0.976 |
- 0.928 |
- 0.932 |
- 0.942 |
- 0.951 |
- 0.967 |
- 0.929 |
- 0.936 |
- 0.934 |
- 0.94 |
- 0.927 |
- 0.923 |
- 0.921 |
- 0.946 |
- 0.949 |
- 0.94 |
- 0.934 |
- 0.956 |
- 0.937 |
- 0.926 |
- 0.939 |
- 0.944 |
- 0.953 |
- 0.953 |
- 0.938 |
- 0.937 |
- 0.974 |
- 0.953 |
- 0.969 |
- 0.929 |
- 0.944 |
- 0.962 |
- 0.95 |
- 0.928 |
- 0.927 |
- 0.938 |
- 0.925 |
- 0.919 |
- 0.955 |
- 0.902 |
- 0.955 |
- 0.944 |
- 0.949 |
- 0.944 |
- 0.952 |
- 0.931 |
- 0.923 |
- 0.932 |
- 0.934 |
- 0.938 |
- 0.935 |
- 0.938 |
- 0.949 |
- 0.951 |
- 0.938 |
- 0.934 |
- 0.975 |
- 0.942 |
- 0.951 |
- 0.932 |
- 0.955 |
- 0.937 |
- 0.935 |
- 0.932 |
- 0.928 |
- 0.922 |
- 0.937 |
- 0.953 |
- 0.925 |
- 0.944 |
- 0.893 |
- 0.931 |
- 0.919 |
- 0.936 |
- 0.932 |
- 0.935 |
- 0.976 |
- 0.944 |
- 0.975 |
- |
- 0.875 |
- 0.94 |
-
-
- | Liver |
- 218 |
- F |
- 293 |
- 090412.08 |
- CD |
- BXD63 |
- H0818 |
- 0.99 |
- 0.924 |
- 0.926 |
- 0.987 |
- 0.979 |
- 0.983 |
- 0.988 |
- 0.969 |
- 0.884 |
- 0.982 |
- 0.971 |
- 0.987 |
- 0.977 |
- 0.981 |
- 0.971 |
- 0.98 |
- 0.972 |
- 0.962 |
- 0.98 |
- 0.984 |
- 0.98 |
- 0.989 |
- 0.988 |
- 0.987 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.981 |
- 0.986 |
- 0.987 |
- 0.987 |
- 0.982 |
- 0.942 |
- 0.981 |
- 0.983 |
- 0.977 |
- 0.939 |
- 1 |
- 0.99 |
- 0.99 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.989 |
- 0.984 |
- 0.948 |
- 0.98 |
- 0.982 |
- 0.99 |
- 0.983 |
- 0.987 |
- 0.97 |
- 0.98 |
- 0.977 |
- 0.986 |
- 0.987 |
- 0.98 |
- 0.979 |
- 0.985 |
- 0.987 |
- 0.973 |
- 0.961 |
- 0.984 |
- 0.896 |
- 0.981 |
- 0.979 |
- 0.972 |
- 0.983 |
- 0.966 |
- 0.947 |
- 0.984 |
- 0.944 |
- 0.987 |
- 0.988 |
- 0.985 |
- 0.987 |
- 0.976 |
- 0.989 |
- 0.985 |
- 0.987 |
- 0.987 |
- 0.982 |
- 0.966 |
- 0.979 |
- 0.985 |
- 0.96 |
- 0.987 |
- 0.986 |
- 0.974 |
- 0.984 |
- 0.977 |
- 0.981 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.974 |
- 0.978 |
- 0.977 |
- 0.98 |
- 0.987 |
- 0.968 |
- 0.978 |
- 0.978 |
- 0.987 |
- 0.98 |
- 0.986 |
- 0.978 |
- 0.981 |
- 0.947 |
- 0.983 |
- 0.99 |
- 0.975 |
- 0.982 |
- 0.972 |
- 0.986 |
- 0.976 |
- 0.984 |
- 0.981 |
- 0.979 |
- 0.97 |
- 0.979 |
- 0.963 |
- 0.987 |
- 0.988 |
- 0.985 |
- 0.975 |
- 0.98 |
- 0.986 |
- 0.984 |
- 0.981 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.973 |
- 0.981 |
- 0.983 |
- 0.983 |
- 0.984 |
- 0.987 |
- 0.922 |
- 0.988 |
- 0.981 |
- 0.986 |
- 0.986 |
- 0.986 |
- 0.944 |
- 0.97 |
- 0.938 |
- |
- 0.884 |
- 0.98 |
-
-
- | Liver |
- 344 |
- F |
- 134 |
- 121214.24 |
- CD |
- BXD63 |
- H1414 |
- 0.982 |
- 0.932 |
- 0.933 |
- 0.982 |
- 0.972 |
- 0.976 |
- 0.98 |
- 0.982 |
- 0.901 |
- 0.975 |
- 0.962 |
- 0.985 |
- 0.968 |
- 0.976 |
- 0.97 |
- 0.975 |
- 0.982 |
- 0.969 |
- 0.979 |
- 0.98 |
- 0.972 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.985 |
- 0.979 |
- 0.98 |
- 0.986 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.977 |
- 0.933 |
- 0.983 |
- 0.988 |
- 0.982 |
- 0.956 |
- 0.99 |
- 1 |
- 0.991 |
- 0.981 |
- 0.978 |
- 0.983 |
- 0.98 |
- 0.983 |
- 0.956 |
- 0.967 |
- 0.974 |
- 0.984 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.984 |
- 0.971 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.976 |
- 0.984 |
- 0.986 |
- 0.965 |
- 0.951 |
- 0.987 |
- 0.89 |
- 0.972 |
- 0.973 |
- 0.975 |
- 0.979 |
- 0.973 |
- 0.959 |
- 0.983 |
- 0.96 |
- 0.978 |
- 0.98 |
- 0.985 |
- 0.986 |
- 0.984 |
- 0.979 |
- 0.981 |
- 0.983 |
- 0.977 |
- 0.973 |
- 0.957 |
- 0.97 |
- 0.98 |
- 0.97 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.978 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.989 |
- 0.988 |
- 0.978 |
- 0.981 |
- 0.983 |
- 0.979 |
- 0.985 |
- 0.973 |
- 0.984 |
- 0.973 |
- 0.977 |
- 0.971 |
- 0.982 |
- 0.98 |
- 0.978 |
- 0.974 |
- 0.982 |
- 0.934 |
- 0.989 |
- 0.991 |
- 0.976 |
- 0.978 |
- 0.975 |
- 0.984 |
- 0.968 |
- 0.976 |
- 0.973 |
- 0.975 |
- 0.963 |
- 0.976 |
- 0.963 |
- 0.988 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.987 |
- 0.984 |
- 0.982 |
- 0.981 |
- 0.983 |
- 0.975 |
- 0.968 |
- 0.973 |
- 0.979 |
- 0.983 |
- 0.978 |
- 0.985 |
- 0.916 |
- 0.979 |
- 0.972 |
- 0.98 |
- 0.981 |
- 0.983 |
- 0.96 |
- 0.975 |
- 0.951 |
- |
- 0.89 |
- 0.98 |
-
-
- | Liver |
- 751 |
- F |
- 133 |
- 083016.03 |
- CD |
- BXD63 |
- H1872 |
- 0.984 |
- 0.923 |
- 0.925 |
- 0.982 |
- 0.968 |
- 0.977 |
- 0.98 |
- 0.973 |
- 0.888 |
- 0.976 |
- 0.966 |
- 0.983 |
- 0.969 |
- 0.978 |
- 0.965 |
- 0.975 |
- 0.976 |
- 0.964 |
- 0.982 |
- 0.98 |
- 0.976 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.98 |
- 0.971 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.977 |
- 0.937 |
- 0.979 |
- 0.986 |
- 0.975 |
- 0.94 |
- 0.99 |
- 0.991 |
- 1 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.979 |
- 0.941 |
- 0.969 |
- 0.974 |
- 0.984 |
- 0.977 |
- 0.983 |
- 0.967 |
- 0.978 |
- 0.97 |
- 0.983 |
- 0.979 |
- 0.978 |
- 0.978 |
- 0.984 |
- 0.984 |
- 0.966 |
- 0.955 |
- 0.984 |
- 0.89 |
- 0.975 |
- 0.975 |
- 0.973 |
- 0.981 |
- 0.966 |
- 0.947 |
- 0.979 |
- 0.945 |
- 0.98 |
- 0.98 |
- 0.98 |
- 0.984 |
- 0.977 |
- 0.983 |
- 0.984 |
- 0.986 |
- 0.981 |
- 0.979 |
- 0.962 |
- 0.975 |
- 0.982 |
- 0.967 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.982 |
- 0.982 |
- 0.989 |
- 0.989 |
- 0.979 |
- 0.985 |
- 0.977 |
- 0.977 |
- 0.98 |
- 0.975 |
- 0.987 |
- 0.968 |
- 0.973 |
- 0.971 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.98 |
- 0.983 |
- 0.938 |
- 0.986 |
- 0.996 |
- 0.973 |
- 0.976 |
- 0.973 |
- 0.987 |
- 0.973 |
- 0.981 |
- 0.976 |
- 0.976 |
- 0.963 |
- 0.978 |
- 0.96 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.976 |
- 0.983 |
- 0.985 |
- 0.987 |
- 0.983 |
- 0.985 |
- 0.987 |
- 0.975 |
- 0.969 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.982 |
- 0.985 |
- 0.917 |
- 0.984 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.981 |
- 0.945 |
- 0.973 |
- 0.937 |
- |
- 0.888 |
- 0.97 |
-
-
- | Liver |
- 222 |
- F |
- 107 |
- 042015.13 |
- CD |
- BXD65 |
- H2098 |
- 0.986 |
- 0.931 |
- 0.931 |
- 0.985 |
- 0.975 |
- 0.985 |
- 0.983 |
- 0.969 |
- 0.893 |
- 0.984 |
- 0.974 |
- 0.987 |
- 0.98 |
- 0.983 |
- 0.974 |
- 0.983 |
- 0.973 |
- 0.971 |
- 0.982 |
- 0.983 |
- 0.979 |
- 0.988 |
- 0.984 |
- 0.986 |
- 0.982 |
- 0.975 |
- 0.975 |
- 0.981 |
- 0.986 |
- 0.983 |
- 0.985 |
- 0.984 |
- 0.95 |
- 0.977 |
- 0.983 |
- 0.979 |
- 0.936 |
- 0.985 |
- 0.981 |
- 0.984 |
- 1 |
- 0.987 |
- 0.986 |
- 0.989 |
- 0.984 |
- 0.948 |
- 0.972 |
- 0.977 |
- 0.985 |
- 0.975 |
- 0.988 |
- 0.962 |
- 0.979 |
- 0.974 |
- 0.983 |
- 0.983 |
- 0.979 |
- 0.986 |
- 0.987 |
- 0.982 |
- 0.971 |
- 0.966 |
- 0.985 |
- 0.9 |
- 0.984 |
- 0.978 |
- 0.981 |
- 0.986 |
- 0.971 |
- 0.946 |
- 0.981 |
- 0.946 |
- 0.987 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.971 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.982 |
- 0.983 |
- 0.971 |
- 0.984 |
- 0.988 |
- 0.971 |
- 0.984 |
- 0.985 |
- 0.978 |
- 0.986 |
- 0.983 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.974 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.986 |
- 0.973 |
- 0.976 |
- 0.98 |
- 0.984 |
- 0.982 |
- 0.989 |
- 0.98 |
- 0.982 |
- 0.947 |
- 0.972 |
- 0.984 |
- 0.97 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.983 |
- 0.988 |
- 0.984 |
- 0.981 |
- 0.97 |
- 0.98 |
- 0.968 |
- 0.981 |
- 0.985 |
- 0.985 |
- 0.971 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.984 |
- 0.932 |
- 0.982 |
- 0.978 |
- 0.989 |
- 0.984 |
- 0.98 |
- 0.946 |
- 0.977 |
- 0.942 |
- |
- 0.893 |
- 0.98 |
-
-
- | Liver |
- 541 |
- F |
- 322 |
- 121615.09 |
- CD |
- BXD65 |
- H1787 |
- 0.985 |
- 0.926 |
- 0.928 |
- 0.984 |
- 0.977 |
- 0.984 |
- 0.982 |
- 0.962 |
- 0.888 |
- 0.982 |
- 0.975 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.971 |
- 0.976 |
- 0.971 |
- 0.959 |
- 0.981 |
- 0.984 |
- 0.974 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.973 |
- 0.975 |
- 0.976 |
- 0.97 |
- 0.987 |
- 0.982 |
- 0.984 |
- 0.978 |
- 0.954 |
- 0.981 |
- 0.981 |
- 0.975 |
- 0.931 |
- 0.983 |
- 0.978 |
- 0.98 |
- 0.987 |
- 1 |
- 0.987 |
- 0.992 |
- 0.98 |
- 0.943 |
- 0.978 |
- 0.981 |
- 0.982 |
- 0.976 |
- 0.984 |
- 0.96 |
- 0.976 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.974 |
- 0.98 |
- 0.984 |
- 0.981 |
- 0.975 |
- 0.97 |
- 0.973 |
- 0.899 |
- 0.983 |
- 0.983 |
- 0.977 |
- 0.981 |
- 0.962 |
- 0.937 |
- 0.979 |
- 0.934 |
- 0.986 |
- 0.982 |
- 0.978 |
- 0.981 |
- 0.974 |
- 0.986 |
- 0.984 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.971 |
- 0.982 |
- 0.982 |
- 0.965 |
- 0.984 |
- 0.985 |
- 0.972 |
- 0.977 |
- 0.984 |
- 0.982 |
- 0.981 |
- 0.979 |
- 0.979 |
- 0.982 |
- 0.983 |
- 0.964 |
- 0.976 |
- 0.968 |
- 0.982 |
- 0.979 |
- 0.969 |
- 0.973 |
- 0.981 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.976 |
- 0.978 |
- 0.949 |
- 0.971 |
- 0.979 |
- 0.97 |
- 0.979 |
- 0.977 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.985 |
- 0.975 |
- 0.972 |
- 0.973 |
- 0.964 |
- 0.979 |
- 0.983 |
- 0.981 |
- 0.968 |
- 0.979 |
- 0.979 |
- 0.984 |
- 0.978 |
- 0.983 |
- 0.98 |
- 0.975 |
- 0.976 |
- 0.98 |
- 0.978 |
- 0.984 |
- 0.982 |
- 0.979 |
- 0.927 |
- 0.985 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.979 |
- 0.934 |
- 0.969 |
- 0.935 |
- |
- 0.888 |
- 0.97 |
-
-
- | Liver |
- 187 |
- F |
- 320 |
- 111414.05 |
- CD |
- BXD65b |
- H1766 |
- 0.985 |
- 0.921 |
- 0.923 |
- 0.983 |
- 0.971 |
- 0.976 |
- 0.981 |
- 0.968 |
- 0.888 |
- 0.982 |
- 0.969 |
- 0.979 |
- 0.975 |
- 0.98 |
- 0.962 |
- 0.973 |
- 0.978 |
- 0.958 |
- 0.979 |
- 0.98 |
- 0.966 |
- 0.983 |
- 0.98 |
- 0.981 |
- 0.977 |
- 0.973 |
- 0.974 |
- 0.974 |
- 0.984 |
- 0.977 |
- 0.983 |
- 0.976 |
- 0.939 |
- 0.986 |
- 0.986 |
- 0.975 |
- 0.936 |
- 0.983 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.987 |
- 1 |
- 0.987 |
- 0.978 |
- 0.94 |
- 0.972 |
- 0.976 |
- 0.982 |
- 0.973 |
- 0.98 |
- 0.965 |
- 0.977 |
- 0.975 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.976 |
- 0.985 |
- 0.984 |
- 0.964 |
- 0.959 |
- 0.979 |
- 0.892 |
- 0.982 |
- 0.981 |
- 0.974 |
- 0.98 |
- 0.966 |
- 0.945 |
- 0.976 |
- 0.944 |
- 0.98 |
- 0.981 |
- 0.976 |
- 0.984 |
- 0.977 |
- 0.983 |
- 0.981 |
- 0.984 |
- 0.977 |
- 0.977 |
- 0.962 |
- 0.977 |
- 0.979 |
- 0.964 |
- 0.982 |
- 0.981 |
- 0.976 |
- 0.975 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.978 |
- 0.979 |
- 0.968 |
- 0.975 |
- 0.972 |
- 0.976 |
- 0.978 |
- 0.968 |
- 0.973 |
- 0.97 |
- 0.983 |
- 0.987 |
- 0.984 |
- 0.979 |
- 0.978 |
- 0.939 |
- 0.98 |
- 0.982 |
- 0.963 |
- 0.978 |
- 0.974 |
- 0.987 |
- 0.974 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.964 |
- 0.972 |
- 0.957 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.973 |
- 0.979 |
- 0.98 |
- 0.982 |
- 0.978 |
- 0.979 |
- 0.982 |
- 0.976 |
- 0.968 |
- 0.977 |
- 0.978 |
- 0.982 |
- 0.978 |
- 0.981 |
- 0.916 |
- 0.981 |
- 0.975 |
- 0.978 |
- 0.977 |
- 0.974 |
- 0.944 |
- 0.969 |
- 0.932 |
- |
- 0.888 |
- 0.97 |
-
-
- | Liver |
- 527 |
- F |
- 313 |
- 121615.12 |
- CD |
- BXD65b |
- H1793 |
- 0.99 |
- 0.927 |
- 0.928 |
- 0.988 |
- 0.982 |
- 0.986 |
- 0.988 |
- 0.964 |
- 0.887 |
- 0.985 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.973 |
- 0.981 |
- 0.971 |
- 0.963 |
- 0.983 |
- 0.985 |
- 0.979 |
- 0.988 |
- 0.988 |
- 0.988 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.976 |
- 0.989 |
- 0.986 |
- 0.987 |
- 0.983 |
- 0.951 |
- 0.981 |
- 0.983 |
- 0.979 |
- 0.932 |
- 0.989 |
- 0.98 |
- 0.982 |
- 0.989 |
- 0.992 |
- 0.987 |
- 1 |
- 0.985 |
- 0.947 |
- 0.982 |
- 0.984 |
- 0.988 |
- 0.982 |
- 0.987 |
- 0.962 |
- 0.98 |
- 0.981 |
- 0.985 |
- 0.986 |
- 0.978 |
- 0.98 |
- 0.987 |
- 0.984 |
- 0.974 |
- 0.967 |
- 0.981 |
- 0.9 |
- 0.985 |
- 0.982 |
- 0.978 |
- 0.984 |
- 0.966 |
- 0.943 |
- 0.983 |
- 0.939 |
- 0.989 |
- 0.988 |
- 0.983 |
- 0.984 |
- 0.974 |
- 0.99 |
- 0.988 |
- 0.989 |
- 0.987 |
- 0.985 |
- 0.974 |
- 0.985 |
- 0.988 |
- 0.963 |
- 0.988 |
- 0.988 |
- 0.972 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.987 |
- 0.985 |
- 0.968 |
- 0.979 |
- 0.973 |
- 0.985 |
- 0.985 |
- 0.971 |
- 0.978 |
- 0.984 |
- 0.987 |
- 0.982 |
- 0.989 |
- 0.98 |
- 0.98 |
- 0.952 |
- 0.974 |
- 0.981 |
- 0.972 |
- 0.985 |
- 0.978 |
- 0.987 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.98 |
- 0.975 |
- 0.979 |
- 0.966 |
- 0.984 |
- 0.987 |
- 0.985 |
- 0.972 |
- 0.978 |
- 0.985 |
- 0.983 |
- 0.98 |
- 0.985 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.983 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.929 |
- 0.988 |
- 0.984 |
- 0.988 |
- 0.986 |
- 0.983 |
- 0.939 |
- 0.971 |
- 0.939 |
- |
- 0.887 |
- 0.98 |
-
-
- | Liver |
- 184 |
- F |
- 112 |
- 042415.08 |
- CD |
- BXD66 |
- H2128 |
- 0.983 |
- 0.929 |
- 0.929 |
- 0.984 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.977 |
- 0.897 |
- 0.979 |
- 0.967 |
- 0.986 |
- 0.977 |
- 0.978 |
- 0.971 |
- 0.977 |
- 0.975 |
- 0.972 |
- 0.977 |
- 0.979 |
- 0.978 |
- 0.983 |
- 0.984 |
- 0.986 |
- 0.985 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.983 |
- 0.983 |
- 0.94 |
- 0.98 |
- 0.986 |
- 0.982 |
- 0.949 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.984 |
- 0.98 |
- 0.978 |
- 0.985 |
- 1 |
- 0.961 |
- 0.97 |
- 0.978 |
- 0.98 |
- 0.978 |
- 0.987 |
- 0.973 |
- 0.984 |
- 0.971 |
- 0.981 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.966 |
- 0.952 |
- 0.985 |
- 0.889 |
- 0.978 |
- 0.973 |
- 0.978 |
- 0.982 |
- 0.974 |
- 0.957 |
- 0.983 |
- 0.954 |
- 0.981 |
- 0.981 |
- 0.987 |
- 0.982 |
- 0.979 |
- 0.979 |
- 0.984 |
- 0.984 |
- 0.98 |
- 0.976 |
- 0.964 |
- 0.977 |
- 0.986 |
- 0.967 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.976 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.978 |
- 0.979 |
- 0.978 |
- 0.981 |
- 0.978 |
- 0.982 |
- 0.973 |
- 0.978 |
- 0.979 |
- 0.981 |
- 0.977 |
- 0.982 |
- 0.972 |
- 0.979 |
- 0.942 |
- 0.975 |
- 0.981 |
- 0.973 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.974 |
- 0.989 |
- 0.985 |
- 0.977 |
- 0.967 |
- 0.978 |
- 0.966 |
- 0.984 |
- 0.986 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.985 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.975 |
- 0.975 |
- 0.973 |
- 0.972 |
- 0.979 |
- 0.985 |
- 0.976 |
- 0.982 |
- 0.924 |
- 0.979 |
- 0.972 |
- 0.984 |
- 0.981 |
- 0.985 |
- 0.954 |
- 0.972 |
- 0.957 |
- |
- 0.889 |
- 0.98 |
-
-
- | Liver |
- 354 |
- F |
- 113 |
- 121214.19 |
- CD |
- BXD66 |
- H1558 |
- 0.94 |
- 0.95 |
- 0.948 |
- 0.946 |
- 0.957 |
- 0.957 |
- 0.945 |
- 0.965 |
- 0.932 |
- 0.945 |
- 0.938 |
- 0.956 |
- 0.943 |
- 0.939 |
- 0.962 |
- 0.948 |
- 0.954 |
- 0.957 |
- 0.945 |
- 0.947 |
- 0.947 |
- 0.946 |
- 0.951 |
- 0.949 |
- 0.956 |
- 0.97 |
- 0.969 |
- 0.965 |
- 0.955 |
- 0.949 |
- 0.946 |
- 0.95 |
- 0.923 |
- 0.951 |
- 0.949 |
- 0.965 |
- 0.969 |
- 0.948 |
- 0.956 |
- 0.941 |
- 0.948 |
- 0.943 |
- 0.94 |
- 0.947 |
- 0.961 |
- 1 |
- 0.942 |
- 0.949 |
- 0.946 |
- 0.958 |
- 0.948 |
- 0.969 |
- 0.967 |
- 0.953 |
- 0.949 |
- 0.949 |
- 0.962 |
- 0.941 |
- 0.951 |
- 0.953 |
- 0.944 |
- 0.931 |
- 0.952 |
- 0.9 |
- 0.939 |
- 0.939 |
- 0.959 |
- 0.946 |
- 0.966 |
- 0.958 |
- 0.961 |
- 0.96 |
- 0.946 |
- 0.945 |
- 0.957 |
- 0.953 |
- 0.961 |
- 0.942 |
- 0.949 |
- 0.947 |
- 0.95 |
- 0.94 |
- 0.94 |
- 0.939 |
- 0.954 |
- 0.951 |
- 0.947 |
- 0.947 |
- 0.956 |
- 0.948 |
- 0.936 |
- 0.948 |
- 0.952 |
- 0.954 |
- 0.953 |
- 0.95 |
- 0.944 |
- 0.966 |
- 0.959 |
- 0.963 |
- 0.946 |
- 0.953 |
- 0.96 |
- 0.96 |
- 0.949 |
- 0.943 |
- 0.939 |
- 0.937 |
- 0.929 |
- 0.956 |
- 0.921 |
- 0.952 |
- 0.946 |
- 0.961 |
- 0.953 |
- 0.959 |
- 0.94 |
- 0.939 |
- 0.948 |
- 0.949 |
- 0.946 |
- 0.949 |
- 0.945 |
- 0.959 |
- 0.955 |
- 0.95 |
- 0.948 |
- 0.967 |
- 0.948 |
- 0.958 |
- 0.941 |
- 0.956 |
- 0.944 |
- 0.941 |
- 0.944 |
- 0.947 |
- 0.936 |
- 0.95 |
- 0.961 |
- 0.94 |
- 0.954 |
- 0.917 |
- 0.94 |
- 0.934 |
- 0.951 |
- 0.945 |
- 0.953 |
- 0.96 |
- 0.946 |
- 0.973 |
- |
- 0.9 |
- 0.95 |
-
-
- | Liver |
- 201 |
- F |
- 271 |
- 101613.05 |
- CD |
- BXD68 |
- H1068 |
- 0.984 |
- 0.922 |
- 0.924 |
- 0.979 |
- 0.987 |
- 0.977 |
- 0.989 |
- 0.946 |
- 0.883 |
- 0.983 |
- 0.973 |
- 0.973 |
- 0.977 |
- 0.977 |
- 0.968 |
- 0.972 |
- 0.96 |
- 0.947 |
- 0.976 |
- 0.974 |
- 0.966 |
- 0.977 |
- 0.983 |
- 0.981 |
- 0.967 |
- 0.968 |
- 0.969 |
- 0.96 |
- 0.981 |
- 0.98 |
- 0.976 |
- 0.976 |
- 0.949 |
- 0.973 |
- 0.966 |
- 0.969 |
- 0.929 |
- 0.98 |
- 0.967 |
- 0.969 |
- 0.972 |
- 0.978 |
- 0.972 |
- 0.982 |
- 0.97 |
- 0.942 |
- 1 |
- 0.987 |
- 0.978 |
- 0.98 |
- 0.975 |
- 0.952 |
- 0.967 |
- 0.984 |
- 0.979 |
- 0.98 |
- 0.968 |
- 0.967 |
- 0.975 |
- 0.978 |
- 0.98 |
- 0.968 |
- 0.968 |
- 0.905 |
- 0.974 |
- 0.977 |
- 0.964 |
- 0.974 |
- 0.958 |
- 0.934 |
- 0.977 |
- 0.927 |
- 0.981 |
- 0.989 |
- 0.971 |
- 0.978 |
- 0.963 |
- 0.989 |
- 0.977 |
- 0.978 |
- 0.983 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.977 |
- 0.951 |
- 0.981 |
- 0.98 |
- 0.956 |
- 0.976 |
- 0.971 |
- 0.977 |
- 0.976 |
- 0.966 |
- 0.965 |
- 0.979 |
- 0.972 |
- 0.957 |
- 0.974 |
- 0.962 |
- 0.977 |
- 0.973 |
- 0.968 |
- 0.975 |
- 0.979 |
- 0.976 |
- 0.97 |
- 0.976 |
- 0.97 |
- 0.975 |
- 0.959 |
- 0.964 |
- 0.967 |
- 0.965 |
- 0.982 |
- 0.964 |
- 0.973 |
- 0.978 |
- 0.973 |
- 0.984 |
- 0.986 |
- 0.982 |
- 0.977 |
- 0.967 |
- 0.977 |
- 0.976 |
- 0.975 |
- 0.961 |
- 0.968 |
- 0.974 |
- 0.97 |
- 0.975 |
- 0.972 |
- 0.969 |
- 0.982 |
- 0.974 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.978 |
- 0.976 |
- 0.929 |
- 0.985 |
- 0.976 |
- 0.978 |
- 0.979 |
- 0.973 |
- 0.927 |
- 0.958 |
- 0.933 |
- |
- 0.883 |
- 0.97 |
-
-
- | Liver |
- 545 |
- F |
- 74 |
- 082214.02 |
- CD |
- BXD68 |
- H1080 |
- 0.982 |
- 0.936 |
- 0.937 |
- 0.982 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.96 |
- 0.903 |
- 0.983 |
- 0.978 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.973 |
- 0.977 |
- 0.97 |
- 0.956 |
- 0.983 |
- 0.981 |
- 0.972 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.973 |
- 0.976 |
- 0.976 |
- 0.967 |
- 0.984 |
- 0.982 |
- 0.978 |
- 0.98 |
- 0.96 |
- 0.976 |
- 0.973 |
- 0.976 |
- 0.938 |
- 0.982 |
- 0.974 |
- 0.974 |
- 0.977 |
- 0.981 |
- 0.976 |
- 0.984 |
- 0.978 |
- 0.949 |
- 0.987 |
- 1 |
- 0.978 |
- 0.977 |
- 0.98 |
- 0.96 |
- 0.974 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.972 |
- 0.97 |
- 0.981 |
- 0.981 |
- 0.976 |
- 0.967 |
- 0.972 |
- 0.921 |
- 0.976 |
- 0.976 |
- 0.973 |
- 0.982 |
- 0.966 |
- 0.942 |
- 0.981 |
- 0.935 |
- 0.983 |
- 0.983 |
- 0.976 |
- 0.981 |
- 0.972 |
- 0.983 |
- 0.982 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.975 |
- 0.98 |
- 0.979 |
- 0.963 |
- 0.982 |
- 0.982 |
- 0.97 |
- 0.977 |
- 0.975 |
- 0.984 |
- 0.984 |
- 0.974 |
- 0.973 |
- 0.98 |
- 0.976 |
- 0.965 |
- 0.977 |
- 0.967 |
- 0.98 |
- 0.975 |
- 0.974 |
- 0.977 |
- 0.982 |
- 0.977 |
- 0.976 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.964 |
- 0.97 |
- 0.974 |
- 0.973 |
- 0.977 |
- 0.973 |
- 0.973 |
- 0.979 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.978 |
- 0.971 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.968 |
- 0.974 |
- 0.98 |
- 0.977 |
- 0.98 |
- 0.976 |
- 0.97 |
- 0.975 |
- 0.977 |
- 0.979 |
- 0.976 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.942 |
- 0.982 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.976 |
- 0.935 |
- 0.962 |
- 0.942 |
- |
- 0.903 |
- 0.97 |
-
-
- | Liver |
- 157 |
- F |
- 114 |
- 042415.23 |
- CD |
- BXD69 |
- H2142 |
- 0.989 |
- 0.925 |
- 0.927 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.985 |
- 0.964 |
- 0.884 |
- 0.98 |
- 0.973 |
- 0.988 |
- 0.976 |
- 0.979 |
- 0.971 |
- 0.983 |
- 0.969 |
- 0.961 |
- 0.981 |
- 0.982 |
- 0.977 |
- 0.988 |
- 0.986 |
- 0.986 |
- 0.978 |
- 0.974 |
- 0.975 |
- 0.978 |
- 0.984 |
- 0.987 |
- 0.986 |
- 0.982 |
- 0.944 |
- 0.978 |
- 0.981 |
- 0.977 |
- 0.934 |
- 0.99 |
- 0.984 |
- 0.984 |
- 0.985 |
- 0.982 |
- 0.982 |
- 0.988 |
- 0.98 |
- 0.946 |
- 0.978 |
- 0.978 |
- 1 |
- 0.989 |
- 0.985 |
- 0.966 |
- 0.978 |
- 0.978 |
- 0.988 |
- 0.987 |
- 0.977 |
- 0.978 |
- 0.986 |
- 0.984 |
- 0.976 |
- 0.963 |
- 0.983 |
- 0.897 |
- 0.982 |
- 0.98 |
- 0.971 |
- 0.982 |
- 0.963 |
- 0.94 |
- 0.982 |
- 0.942 |
- 0.984 |
- 0.985 |
- 0.982 |
- 0.984 |
- 0.972 |
- 0.988 |
- 0.984 |
- 0.986 |
- 0.984 |
- 0.982 |
- 0.969 |
- 0.977 |
- 0.982 |
- 0.96 |
- 0.982 |
- 0.984 |
- 0.968 |
- 0.984 |
- 0.978 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.983 |
- 0.971 |
- 0.978 |
- 0.976 |
- 0.982 |
- 0.986 |
- 0.966 |
- 0.977 |
- 0.978 |
- 0.985 |
- 0.977 |
- 0.986 |
- 0.981 |
- 0.98 |
- 0.947 |
- 0.974 |
- 0.982 |
- 0.969 |
- 0.982 |
- 0.971 |
- 0.987 |
- 0.976 |
- 0.981 |
- 0.98 |
- 0.977 |
- 0.971 |
- 0.982 |
- 0.968 |
- 0.986 |
- 0.987 |
- 0.987 |
- 0.972 |
- 0.981 |
- 0.987 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.985 |
- 0.982 |
- 0.975 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.986 |
- 0.988 |
- 0.924 |
- 0.987 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.942 |
- 0.972 |
- 0.935 |
- |
- 0.884 |
- 0.98 |
-
-
- | Liver |
- 558 |
- F |
- 41 |
- 061913.13 |
- CD |
- BXD69 |
- H0591 |
- 0.982 |
- 0.935 |
- 0.937 |
- 0.979 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.966 |
- 0.9 |
- 0.977 |
- 0.968 |
- 0.981 |
- 0.97 |
- 0.974 |
- 0.976 |
- 0.975 |
- 0.967 |
- 0.96 |
- 0.975 |
- 0.977 |
- 0.971 |
- 0.98 |
- 0.984 |
- 0.982 |
- 0.977 |
- 0.979 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.942 |
- 0.973 |
- 0.976 |
- 0.977 |
- 0.954 |
- 0.983 |
- 0.98 |
- 0.977 |
- 0.975 |
- 0.976 |
- 0.973 |
- 0.982 |
- 0.978 |
- 0.958 |
- 0.98 |
- 0.977 |
- 0.989 |
- 1 |
- 0.977 |
- 0.974 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.967 |
- 0.979 |
- 0.98 |
- 0.976 |
- 0.959 |
- 0.976 |
- 0.901 |
- 0.97 |
- 0.973 |
- 0.971 |
- 0.976 |
- 0.968 |
- 0.954 |
- 0.986 |
- 0.95 |
- 0.977 |
- 0.983 |
- 0.978 |
- 0.98 |
- 0.975 |
- 0.983 |
- 0.978 |
- 0.979 |
- 0.985 |
- 0.979 |
- 0.969 |
- 0.969 |
- 0.981 |
- 0.959 |
- 0.98 |
- 0.98 |
- 0.965 |
- 0.979 |
- 0.97 |
- 0.976 |
- 0.976 |
- 0.978 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.979 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.973 |
- 0.978 |
- 0.976 |
- 0.978 |
- 0.969 |
- 0.976 |
- 0.971 |
- 0.979 |
- 0.948 |
- 0.971 |
- 0.976 |
- 0.97 |
- 0.983 |
- 0.971 |
- 0.977 |
- 0.974 |
- 0.975 |
- 0.98 |
- 0.977 |
- 0.973 |
- 0.982 |
- 0.976 |
- 0.984 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.975 |
- 0.984 |
- 0.975 |
- 0.979 |
- 0.978 |
- 0.974 |
- 0.978 |
- 0.972 |
- 0.977 |
- 0.981 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.924 |
- 0.983 |
- 0.974 |
- 0.979 |
- 0.98 |
- 0.978 |
- 0.95 |
- 0.968 |
- 0.952 |
- |
- 0.9 |
- 0.97 |
-
-
- | Liver |
- 261 |
- F |
- 207 |
- 050115.06 |
- CD |
- BXD70 |
- H1855 |
- 0.989 |
- 0.929 |
- 0.93 |
- 0.99 |
- 0.979 |
- 0.988 |
- 0.984 |
- 0.969 |
- 0.893 |
- 0.983 |
- 0.975 |
- 0.989 |
- 0.984 |
- 0.986 |
- 0.974 |
- 0.986 |
- 0.974 |
- 0.967 |
- 0.985 |
- 0.987 |
- 0.983 |
- 0.99 |
- 0.988 |
- 0.99 |
- 0.984 |
- 0.976 |
- 0.976 |
- 0.978 |
- 0.987 |
- 0.988 |
- 0.987 |
- 0.987 |
- 0.951 |
- 0.975 |
- 0.986 |
- 0.98 |
- 0.935 |
- 0.987 |
- 0.983 |
- 0.983 |
- 0.988 |
- 0.984 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.948 |
- 0.975 |
- 0.98 |
- 0.985 |
- 0.977 |
- 1 |
- 0.967 |
- 0.981 |
- 0.977 |
- 0.987 |
- 0.988 |
- 0.979 |
- 0.984 |
- 0.99 |
- 0.981 |
- 0.976 |
- 0.966 |
- 0.986 |
- 0.901 |
- 0.985 |
- 0.981 |
- 0.976 |
- 0.988 |
- 0.97 |
- 0.942 |
- 0.983 |
- 0.941 |
- 0.988 |
- 0.984 |
- 0.986 |
- 0.981 |
- 0.975 |
- 0.985 |
- 0.99 |
- 0.989 |
- 0.981 |
- 0.983 |
- 0.972 |
- 0.983 |
- 0.985 |
- 0.968 |
- 0.986 |
- 0.989 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.986 |
- 0.986 |
- 0.982 |
- 0.981 |
- 0.987 |
- 0.984 |
- 0.974 |
- 0.979 |
- 0.978 |
- 0.986 |
- 0.984 |
- 0.971 |
- 0.978 |
- 0.983 |
- 0.987 |
- 0.979 |
- 0.986 |
- 0.982 |
- 0.984 |
- 0.95 |
- 0.972 |
- 0.983 |
- 0.971 |
- 0.98 |
- 0.976 |
- 0.982 |
- 0.98 |
- 0.987 |
- 0.982 |
- 0.982 |
- 0.974 |
- 0.982 |
- 0.967 |
- 0.988 |
- 0.994 |
- 0.99 |
- 0.971 |
- 0.984 |
- 0.988 |
- 0.986 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.986 |
- 0.934 |
- 0.984 |
- 0.98 |
- 0.989 |
- 0.988 |
- 0.986 |
- 0.941 |
- 0.972 |
- 0.943 |
- |
- 0.893 |
- 0.98 |
-
-
- | Liver |
- 357 |
- F |
- 197 |
- 121214.16 |
- CD |
- BXD70 |
- H1512 |
- 0.961 |
- 0.935 |
- 0.935 |
- 0.961 |
- 0.963 |
- 0.96 |
- 0.961 |
- 0.979 |
- 0.916 |
- 0.959 |
- 0.941 |
- 0.972 |
- 0.953 |
- 0.957 |
- 0.964 |
- 0.954 |
- 0.972 |
- 0.964 |
- 0.96 |
- 0.961 |
- 0.95 |
- 0.963 |
- 0.967 |
- 0.965 |
- 0.976 |
- 0.981 |
- 0.982 |
- 0.982 |
- 0.967 |
- 0.963 |
- 0.964 |
- 0.959 |
- 0.915 |
- 0.974 |
- 0.975 |
- 0.975 |
- 0.98 |
- 0.97 |
- 0.981 |
- 0.967 |
- 0.962 |
- 0.96 |
- 0.965 |
- 0.962 |
- 0.973 |
- 0.969 |
- 0.952 |
- 0.96 |
- 0.966 |
- 0.974 |
- 0.967 |
- 1 |
- 0.984 |
- 0.959 |
- 0.967 |
- 0.963 |
- 0.98 |
- 0.953 |
- 0.966 |
- 0.973 |
- 0.949 |
- 0.932 |
- 0.972 |
- 0.877 |
- 0.954 |
- 0.956 |
- 0.968 |
- 0.962 |
- 0.978 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.957 |
- 0.961 |
- 0.972 |
- 0.973 |
- 0.981 |
- 0.959 |
- 0.962 |
- 0.963 |
- 0.963 |
- 0.953 |
- 0.938 |
- 0.949 |
- 0.968 |
- 0.962 |
- 0.967 |
- 0.962 |
- 0.973 |
- 0.96 |
- 0.954 |
- 0.962 |
- 0.965 |
- 0.973 |
- 0.972 |
- 0.963 |
- 0.96 |
- 0.985 |
- 0.97 |
- 0.983 |
- 0.954 |
- 0.968 |
- 0.966 |
- 0.97 |
- 0.951 |
- 0.96 |
- 0.961 |
- 0.956 |
- 0.95 |
- 0.967 |
- 0.917 |
- 0.976 |
- 0.97 |
- 0.963 |
- 0.967 |
- 0.968 |
- 0.963 |
- 0.947 |
- 0.958 |
- 0.957 |
- 0.957 |
- 0.948 |
- 0.957 |
- 0.958 |
- 0.978 |
- 0.969 |
- 0.961 |
- 0.987 |
- 0.964 |
- 0.974 |
- 0.962 |
- 0.967 |
- 0.96 |
- 0.965 |
- 0.96 |
- 0.948 |
- 0.949 |
- 0.965 |
- 0.975 |
- 0.955 |
- 0.97 |
- 0.899 |
- 0.96 |
- 0.947 |
- 0.961 |
- 0.959 |
- 0.965 |
- 0.976 |
- 0.965 |
- 0.969 |
- |
- 0.877 |
- 0.96 |
-
-
- | Liver |
- 361 |
- F |
- 203 |
- 121214.10 |
- CD |
- BXD73 |
- H1451 |
- 0.977 |
- 0.948 |
- 0.948 |
- 0.978 |
- 0.975 |
- 0.978 |
- 0.972 |
- 0.979 |
- 0.923 |
- 0.976 |
- 0.968 |
- 0.983 |
- 0.973 |
- 0.975 |
- 0.977 |
- 0.974 |
- 0.982 |
- 0.974 |
- 0.978 |
- 0.98 |
- 0.966 |
- 0.978 |
- 0.978 |
- 0.982 |
- 0.986 |
- 0.988 |
- 0.989 |
- 0.987 |
- 0.983 |
- 0.98 |
- 0.974 |
- 0.975 |
- 0.945 |
- 0.978 |
- 0.983 |
- 0.988 |
- 0.968 |
- 0.98 |
- 0.984 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.977 |
- 0.98 |
- 0.984 |
- 0.967 |
- 0.967 |
- 0.974 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.984 |
- 1 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.988 |
- 0.968 |
- 0.983 |
- 0.982 |
- 0.965 |
- 0.956 |
- 0.983 |
- 0.901 |
- 0.973 |
- 0.971 |
- 0.982 |
- 0.979 |
- 0.984 |
- 0.971 |
- 0.987 |
- 0.967 |
- 0.975 |
- 0.972 |
- 0.977 |
- 0.982 |
- 0.988 |
- 0.974 |
- 0.981 |
- 0.979 |
- 0.975 |
- 0.972 |
- 0.962 |
- 0.971 |
- 0.983 |
- 0.974 |
- 0.981 |
- 0.978 |
- 0.98 |
- 0.974 |
- 0.972 |
- 0.979 |
- 0.981 |
- 0.981 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.986 |
- 0.98 |
- 0.987 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.971 |
- 0.972 |
- 0.978 |
- 0.976 |
- 0.969 |
- 0.981 |
- 0.939 |
- 0.976 |
- 0.978 |
- 0.971 |
- 0.976 |
- 0.982 |
- 0.972 |
- 0.968 |
- 0.977 |
- 0.975 |
- 0.972 |
- 0.967 |
- 0.972 |
- 0.971 |
- 0.983 |
- 0.981 |
- 0.979 |
- 0.992 |
- 0.979 |
- 0.988 |
- 0.975 |
- 0.981 |
- 0.98 |
- 0.974 |
- 0.971 |
- 0.971 |
- 0.969 |
- 0.973 |
- 0.987 |
- 0.971 |
- 0.978 |
- 0.927 |
- 0.974 |
- 0.968 |
- 0.978 |
- 0.973 |
- 0.971 |
- 0.967 |
- 0.977 |
- 0.968 |
- |
- 0.901 |
- 0.98 |
-
-
- | Liver |
- 539 |
- F |
- 213 |
- 121615.17 |
- CD |
- BXD73 |
- H1906 |
- 0.98 |
- 0.943 |
- 0.944 |
- 0.98 |
- 0.986 |
- 0.983 |
- 0.979 |
- 0.958 |
- 0.91 |
- 0.981 |
- 0.977 |
- 0.974 |
- 0.98 |
- 0.98 |
- 0.976 |
- 0.975 |
- 0.971 |
- 0.951 |
- 0.977 |
- 0.982 |
- 0.966 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.971 |
- 0.973 |
- 0.974 |
- 0.964 |
- 0.984 |
- 0.985 |
- 0.975 |
- 0.978 |
- 0.961 |
- 0.974 |
- 0.969 |
- 0.977 |
- 0.943 |
- 0.977 |
- 0.971 |
- 0.97 |
- 0.974 |
- 0.979 |
- 0.975 |
- 0.981 |
- 0.971 |
- 0.953 |
- 0.984 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.977 |
- 0.959 |
- 0.979 |
- 1 |
- 0.984 |
- 0.985 |
- 0.973 |
- 0.966 |
- 0.982 |
- 0.979 |
- 0.981 |
- 0.973 |
- 0.969 |
- 0.924 |
- 0.975 |
- 0.979 |
- 0.972 |
- 0.978 |
- 0.966 |
- 0.938 |
- 0.979 |
- 0.935 |
- 0.98 |
- 0.979 |
- 0.971 |
- 0.979 |
- 0.975 |
- 0.983 |
- 0.98 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.973 |
- 0.975 |
- 0.962 |
- 0.979 |
- 0.981 |
- 0.967 |
- 0.972 |
- 0.971 |
- 0.978 |
- 0.979 |
- 0.973 |
- 0.974 |
- 0.979 |
- 0.976 |
- 0.964 |
- 0.978 |
- 0.966 |
- 0.981 |
- 0.972 |
- 0.977 |
- 0.976 |
- 0.98 |
- 0.974 |
- 0.974 |
- 0.972 |
- 0.972 |
- 0.98 |
- 0.961 |
- 0.967 |
- 0.968 |
- 0.97 |
- 0.979 |
- 0.972 |
- 0.97 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.976 |
- 0.975 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.972 |
- 0.978 |
- 0.983 |
- 0.973 |
- 0.98 |
- 0.976 |
- 0.969 |
- 0.978 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.981 |
- 0.978 |
- 0.977 |
- 0.942 |
- 0.979 |
- 0.975 |
- 0.978 |
- 0.975 |
- 0.971 |
- 0.935 |
- 0.959 |
- 0.943 |
- |
- 0.91 |
- 0.97 |
-
-
- | Liver |
- 238 |
- F |
- 98 |
- 051112.12 |
- CD |
- BXD73b |
- H0184 |
- 0.989 |
- 0.929 |
- 0.931 |
- 0.986 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.964 |
- 0.892 |
- 0.981 |
- 0.973 |
- 0.986 |
- 0.983 |
- 0.985 |
- 0.972 |
- 0.981 |
- 0.974 |
- 0.96 |
- 0.983 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.989 |
- 0.988 |
- 0.98 |
- 0.973 |
- 0.973 |
- 0.975 |
- 0.986 |
- 0.99 |
- 0.988 |
- 0.984 |
- 0.948 |
- 0.977 |
- 0.983 |
- 0.979 |
- 0.939 |
- 0.986 |
- 0.984 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.982 |
- 0.985 |
- 0.981 |
- 0.949 |
- 0.979 |
- 0.98 |
- 0.988 |
- 0.983 |
- 0.987 |
- 0.967 |
- 0.981 |
- 0.984 |
- 1 |
- 0.99 |
- 0.976 |
- 0.978 |
- 0.989 |
- 0.982 |
- 0.982 |
- 0.964 |
- 0.984 |
- 0.902 |
- 0.983 |
- 0.985 |
- 0.974 |
- 0.985 |
- 0.966 |
- 0.939 |
- 0.979 |
- 0.943 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.982 |
- 0.975 |
- 0.989 |
- 0.988 |
- 0.989 |
- 0.98 |
- 0.982 |
- 0.971 |
- 0.979 |
- 0.98 |
- 0.965 |
- 0.983 |
- 0.99 |
- 0.975 |
- 0.981 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.986 |
- 0.983 |
- 0.972 |
- 0.981 |
- 0.976 |
- 0.984 |
- 0.981 |
- 0.971 |
- 0.981 |
- 0.982 |
- 0.988 |
- 0.979 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.953 |
- 0.974 |
- 0.981 |
- 0.97 |
- 0.985 |
- 0.974 |
- 0.986 |
- 0.978 |
- 0.981 |
- 0.983 |
- 0.983 |
- 0.975 |
- 0.981 |
- 0.969 |
- 0.989 |
- 0.989 |
- 0.991 |
- 0.976 |
- 0.99 |
- 0.992 |
- 0.987 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.986 |
- 0.978 |
- 0.983 |
- 0.987 |
- 0.986 |
- 0.988 |
- 0.989 |
- 0.93 |
- 0.986 |
- 0.981 |
- 0.986 |
- 0.987 |
- 0.985 |
- 0.943 |
- 0.97 |
- 0.941 |
- |
- 0.892 |
- 0.98 |
-
-
- | Liver |
- 497 |
- F |
- 253 |
- 050115.15 |
- CD |
- BXD73b |
- H1466 |
- 0.99 |
- 0.927 |
- 0.929 |
- 0.987 |
- 0.983 |
- 0.988 |
- 0.986 |
- 0.962 |
- 0.891 |
- 0.983 |
- 0.975 |
- 0.986 |
- 0.982 |
- 0.985 |
- 0.977 |
- 0.985 |
- 0.967 |
- 0.96 |
- 0.98 |
- 0.985 |
- 0.981 |
- 0.989 |
- 0.988 |
- 0.989 |
- 0.979 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.985 |
- 1 |
- 0.984 |
- 0.988 |
- 0.951 |
- 0.973 |
- 0.979 |
- 0.975 |
- 0.937 |
- 0.987 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.986 |
- 0.981 |
- 0.949 |
- 0.98 |
- 0.982 |
- 0.987 |
- 0.983 |
- 0.988 |
- 0.963 |
- 0.98 |
- 0.985 |
- 0.99 |
- 1 |
- 0.976 |
- 0.98 |
- 0.988 |
- 0.981 |
- 0.981 |
- 0.967 |
- 0.979 |
- 0.905 |
- 0.982 |
- 0.98 |
- 0.97 |
- 0.986 |
- 0.967 |
- 0.94 |
- 0.982 |
- 0.938 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.981 |
- 0.971 |
- 0.988 |
- 0.987 |
- 0.987 |
- 0.986 |
- 0.985 |
- 0.976 |
- 0.979 |
- 0.982 |
- 0.96 |
- 0.984 |
- 0.988 |
- 0.971 |
- 0.986 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.984 |
- 0.98 |
- 0.972 |
- 0.978 |
- 0.976 |
- 0.985 |
- 0.982 |
- 0.969 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.954 |
- 0.97 |
- 0.979 |
- 0.97 |
- 0.983 |
- 0.97 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.978 |
- 0.984 |
- 0.97 |
- 0.983 |
- 0.989 |
- 0.991 |
- 0.97 |
- 0.985 |
- 0.99 |
- 0.982 |
- 0.983 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.985 |
- 0.985 |
- 0.933 |
- 0.984 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.985 |
- 0.938 |
- 0.966 |
- 0.94 |
- |
- 0.891 |
- 0.98 |
-
-
- | Liver |
- 460 |
- F |
- 255 |
- 050115.17 |
- CD |
- BXD77 |
- H1398 |
- 0.979 |
- 0.943 |
- 0.943 |
- 0.978 |
- 0.974 |
- 0.977 |
- 0.976 |
- 0.976 |
- 0.914 |
- 0.977 |
- 0.965 |
- 0.982 |
- 0.969 |
- 0.976 |
- 0.976 |
- 0.972 |
- 0.979 |
- 0.972 |
- 0.976 |
- 0.977 |
- 0.967 |
- 0.98 |
- 0.976 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.985 |
- 0.986 |
- 0.983 |
- 0.976 |
- 0.974 |
- 0.974 |
- 0.941 |
- 0.975 |
- 0.982 |
- 0.985 |
- 0.963 |
- 0.98 |
- 0.983 |
- 0.978 |
- 0.979 |
- 0.974 |
- 0.975 |
- 0.978 |
- 0.982 |
- 0.962 |
- 0.968 |
- 0.972 |
- 0.977 |
- 0.981 |
- 0.979 |
- 0.98 |
- 0.988 |
- 0.973 |
- 0.976 |
- 0.976 |
- 1 |
- 0.967 |
- 0.98 |
- 0.983 |
- 0.963 |
- 0.959 |
- 0.982 |
- 0.898 |
- 0.972 |
- 0.969 |
- 0.98 |
- 0.979 |
- 0.983 |
- 0.97 |
- 0.987 |
- 0.961 |
- 0.976 |
- 0.976 |
- 0.975 |
- 0.983 |
- 0.983 |
- 0.975 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.974 |
- 0.964 |
- 0.968 |
- 0.984 |
- 0.97 |
- 0.984 |
- 0.977 |
- 0.976 |
- 0.976 |
- 0.971 |
- 0.978 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.978 |
- 0.985 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.977 |
- 0.97 |
- 0.972 |
- 0.975 |
- 0.977 |
- 0.969 |
- 0.982 |
- 0.937 |
- 0.974 |
- 0.978 |
- 0.969 |
- 0.976 |
- 0.98 |
- 0.973 |
- 0.972 |
- 0.977 |
- 0.975 |
- 0.975 |
- 0.966 |
- 0.975 |
- 0.969 |
- 0.982 |
- 0.978 |
- 0.975 |
- 0.984 |
- 0.974 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.978 |
- 0.975 |
- 0.973 |
- 0.972 |
- 0.97 |
- 0.974 |
- 0.984 |
- 0.97 |
- 0.979 |
- 0.924 |
- 0.974 |
- 0.967 |
- 0.978 |
- 0.974 |
- 0.972 |
- 0.961 |
- 0.977 |
- 0.963 |
- |
- 0.898 |
- 0.97 |
-
-
- | Liver |
- 217 |
- F |
- 272 |
- 090412.10 |
- CD |
- BXD79 |
- H0825 |
- 0.98 |
- 0.914 |
- 0.914 |
- 0.98 |
- 0.966 |
- 0.981 |
- 0.978 |
- 0.964 |
- 0.878 |
- 0.974 |
- 0.963 |
- 0.981 |
- 0.972 |
- 0.974 |
- 0.966 |
- 0.981 |
- 0.967 |
- 0.968 |
- 0.977 |
- 0.978 |
- 0.981 |
- 0.983 |
- 0.978 |
- 0.978 |
- 0.973 |
- 0.964 |
- 0.964 |
- 0.971 |
- 0.977 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.936 |
- 0.972 |
- 0.979 |
- 0.969 |
- 0.924 |
- 0.979 |
- 0.976 |
- 0.978 |
- 0.986 |
- 0.98 |
- 0.976 |
- 0.98 |
- 0.979 |
- 0.941 |
- 0.967 |
- 0.97 |
- 0.978 |
- 0.967 |
- 0.984 |
- 0.953 |
- 0.968 |
- 0.966 |
- 0.978 |
- 0.98 |
- 0.967 |
- 1 |
- 0.985 |
- 0.974 |
- 0.967 |
- 0.957 |
- 0.976 |
- 0.885 |
- 0.978 |
- 0.972 |
- 0.965 |
- 0.977 |
- 0.957 |
- 0.931 |
- 0.971 |
- 0.935 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.974 |
- 0.962 |
- 0.978 |
- 0.979 |
- 0.981 |
- 0.973 |
- 0.975 |
- 0.962 |
- 0.977 |
- 0.978 |
- 0.961 |
- 0.976 |
- 0.98 |
- 0.973 |
- 0.984 |
- 0.983 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.976 |
- 0.976 |
- 0.975 |
- 0.964 |
- 0.969 |
- 0.967 |
- 0.974 |
- 0.978 |
- 0.959 |
- 0.969 |
- 0.974 |
- 0.981 |
- 0.976 |
- 0.98 |
- 0.971 |
- 0.975 |
- 0.936 |
- 0.967 |
- 0.979 |
- 0.968 |
- 0.97 |
- 0.965 |
- 0.977 |
- 0.972 |
- 0.981 |
- 0.975 |
- 0.973 |
- 0.964 |
- 0.974 |
- 0.954 |
- 0.973 |
- 0.982 |
- 0.983 |
- 0.961 |
- 0.981 |
- 0.976 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.982 |
- 0.97 |
- 0.971 |
- 0.972 |
- 0.973 |
- 0.974 |
- 0.975 |
- 0.978 |
- 0.919 |
- 0.976 |
- 0.969 |
- 0.981 |
- 0.983 |
- 0.984 |
- 0.935 |
- 0.969 |
- 0.934 |
- |
- 0.878 |
- 0.97 |
-
-
- | Liver |
- 468 |
- F |
- 91 |
- 050115.19 |
- CD |
- BXD79 |
- H1555 |
- 0.989 |
- 0.935 |
- 0.937 |
- 0.989 |
- 0.979 |
- 0.99 |
- 0.982 |
- 0.97 |
- 0.901 |
- 0.983 |
- 0.976 |
- 0.988 |
- 0.983 |
- 0.987 |
- 0.974 |
- 0.988 |
- 0.982 |
- 0.967 |
- 0.988 |
- 0.988 |
- 0.98 |
- 0.99 |
- 0.986 |
- 0.988 |
- 0.984 |
- 0.977 |
- 0.977 |
- 0.979 |
- 0.989 |
- 0.988 |
- 0.986 |
- 0.986 |
- 0.951 |
- 0.978 |
- 0.987 |
- 0.983 |
- 0.941 |
- 0.985 |
- 0.984 |
- 0.984 |
- 0.987 |
- 0.984 |
- 0.985 |
- 0.987 |
- 0.984 |
- 0.951 |
- 0.975 |
- 0.981 |
- 0.986 |
- 0.979 |
- 0.99 |
- 0.966 |
- 0.983 |
- 0.982 |
- 0.989 |
- 0.988 |
- 0.98 |
- 0.985 |
- 1 |
- 0.986 |
- 0.977 |
- 0.967 |
- 0.985 |
- 0.908 |
- 0.986 |
- 0.983 |
- 0.978 |
- 0.986 |
- 0.973 |
- 0.944 |
- 0.981 |
- 0.945 |
- 0.986 |
- 0.982 |
- 0.983 |
- 0.986 |
- 0.979 |
- 0.986 |
- 0.99 |
- 0.99 |
- 0.98 |
- 0.983 |
- 0.973 |
- 0.981 |
- 0.983 |
- 0.97 |
- 0.986 |
- 0.989 |
- 0.979 |
- 0.984 |
- 0.985 |
- 0.989 |
- 0.989 |
- 0.985 |
- 0.984 |
- 0.985 |
- 0.984 |
- 0.977 |
- 0.981 |
- 0.98 |
- 0.986 |
- 0.983 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.985 |
- 0.983 |
- 0.986 |
- 0.985 |
- 0.987 |
- 0.949 |
- 0.975 |
- 0.983 |
- 0.969 |
- 0.98 |
- 0.978 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.982 |
- 0.977 |
- 0.982 |
- 0.968 |
- 0.985 |
- 0.99 |
- 0.99 |
- 0.976 |
- 0.988 |
- 0.99 |
- 0.987 |
- 0.987 |
- 0.984 |
- 0.985 |
- 0.978 |
- 0.981 |
- 0.983 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.986 |
- 0.934 |
- 0.983 |
- 0.98 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.945 |
- 0.974 |
- 0.945 |
- |
- 0.901 |
- 0.98 |
-
-
- | Liver |
- 200 |
- F |
- 6 |
- 090612.10 |
- CD |
- BXD87 |
- H0550 |
- 0.985 |
- 0.931 |
- 0.932 |
- 0.983 |
- 0.976 |
- 0.978 |
- 0.984 |
- 0.975 |
- 0.898 |
- 0.982 |
- 0.969 |
- 0.982 |
- 0.971 |
- 0.978 |
- 0.969 |
- 0.977 |
- 0.983 |
- 0.966 |
- 0.979 |
- 0.98 |
- 0.969 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.979 |
- 0.941 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.951 |
- 0.987 |
- 0.986 |
- 0.984 |
- 0.982 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.953 |
- 0.978 |
- 0.981 |
- 0.984 |
- 0.98 |
- 0.981 |
- 0.973 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.983 |
- 0.974 |
- 0.986 |
- 1 |
- 0.967 |
- 0.959 |
- 0.98 |
- 0.896 |
- 0.976 |
- 0.975 |
- 0.974 |
- 0.979 |
- 0.973 |
- 0.957 |
- 0.985 |
- 0.946 |
- 0.978 |
- 0.984 |
- 0.978 |
- 1 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.977 |
- 0.965 |
- 0.975 |
- 0.983 |
- 0.965 |
- 0.984 |
- 0.981 |
- 0.977 |
- 0.982 |
- 0.978 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.976 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.972 |
- 0.979 |
- 0.983 |
- 0.98 |
- 0.972 |
- 0.983 |
- 0.94 |
- 0.984 |
- 0.984 |
- 0.972 |
- 0.977 |
- 0.974 |
- 0.98 |
- 0.973 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.97 |
- 0.979 |
- 0.967 |
- 0.984 |
- 0.982 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.984 |
- 0.98 |
- 0.983 |
- 0.979 |
- 0.98 |
- 0.976 |
- 0.971 |
- 0.975 |
- 0.979 |
- 0.983 |
- 0.976 |
- 0.982 |
- 0.918 |
- 0.983 |
- 0.97 |
- 0.978 |
- 0.979 |
- 0.977 |
- 0.946 |
- 0.973 |
- 0.949 |
- |
- 0.896 |
- 0.98 |
-
-
- | Liver |
- 581 |
- F |
- 286 |
- 061913.19 |
- CD |
- BXD87 |
- H0296 |
- 0.979 |
- 0.932 |
- 0.935 |
- 0.974 |
- 0.984 |
- 0.981 |
- 0.976 |
- 0.942 |
- 0.894 |
- 0.976 |
- 0.969 |
- 0.976 |
- 0.979 |
- 0.978 |
- 0.976 |
- 0.977 |
- 0.959 |
- 0.949 |
- 0.975 |
- 0.976 |
- 0.967 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.967 |
- 0.96 |
- 0.961 |
- 0.959 |
- 0.978 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.958 |
- 0.961 |
- 0.963 |
- 0.966 |
- 0.928 |
- 0.973 |
- 0.965 |
- 0.966 |
- 0.971 |
- 0.975 |
- 0.964 |
- 0.974 |
- 0.966 |
- 0.944 |
- 0.98 |
- 0.976 |
- 0.976 |
- 0.976 |
- 0.976 |
- 0.949 |
- 0.965 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.963 |
- 0.967 |
- 0.977 |
- 0.967 |
- 1 |
- 0.972 |
- 0.967 |
- 0.915 |
- 0.976 |
- 0.98 |
- 0.965 |
- 0.975 |
- 0.958 |
- 0.925 |
- 0.971 |
- 0.932 |
- 0.976 |
- 0.976 |
- 0.971 |
- 0.967 |
- 0.961 |
- 0.982 |
- 0.977 |
- 0.978 |
- 0.974 |
- 0.98 |
- 0.977 |
- 0.971 |
- 0.969 |
- 0.959 |
- 0.972 |
- 0.98 |
- 0.958 |
- 0.973 |
- 0.971 |
- 0.976 |
- 0.974 |
- 0.966 |
- 0.966 |
- 0.979 |
- 0.974 |
- 0.958 |
- 0.976 |
- 0.963 |
- 0.977 |
- 0.971 |
- 0.966 |
- 0.973 |
- 0.979 |
- 0.975 |
- 0.963 |
- 0.97 |
- 0.975 |
- 0.975 |
- 0.963 |
- 0.957 |
- 0.963 |
- 0.963 |
- 0.98 |
- 0.965 |
- 0.971 |
- 0.978 |
- 0.969 |
- 0.979 |
- 0.977 |
- 0.98 |
- 0.974 |
- 0.972 |
- 0.976 |
- 0.977 |
- 0.98 |
- 0.956 |
- 0.973 |
- 0.977 |
- 0.972 |
- 0.975 |
- 0.974 |
- 0.973 |
- 0.98 |
- 0.977 |
- 0.979 |
- 0.981 |
- 0.976 |
- 0.98 |
- 0.977 |
- 0.941 |
- 0.978 |
- 0.975 |
- 0.976 |
- 0.978 |
- 0.974 |
- 0.932 |
- 0.959 |
- 0.934 |
- |
- 0.894 |
- 0.97 |
-
-
- | Liver |
- 193 |
- F |
- 310 |
- 090612.14 |
- CD |
- BXD89 |
- H0555 |
- 0.968 |
- 0.942 |
- 0.945 |
- 0.969 |
- 0.97 |
- 0.974 |
- 0.962 |
- 0.931 |
- 0.901 |
- 0.969 |
- 0.974 |
- 0.962 |
- 0.967 |
- 0.965 |
- 0.967 |
- 0.967 |
- 0.952 |
- 0.941 |
- 0.972 |
- 0.971 |
- 0.954 |
- 0.966 |
- 0.964 |
- 0.965 |
- 0.951 |
- 0.956 |
- 0.957 |
- 0.948 |
- 0.973 |
- 0.967 |
- 0.961 |
- 0.96 |
- 0.973 |
- 0.949 |
- 0.951 |
- 0.962 |
- 0.911 |
- 0.961 |
- 0.951 |
- 0.955 |
- 0.966 |
- 0.97 |
- 0.959 |
- 0.967 |
- 0.952 |
- 0.931 |
- 0.968 |
- 0.967 |
- 0.963 |
- 0.959 |
- 0.966 |
- 0.932 |
- 0.956 |
- 0.973 |
- 0.964 |
- 0.967 |
- 0.959 |
- 0.957 |
- 0.967 |
- 0.959 |
- 0.972 |
- 1 |
- 0.953 |
- 0.939 |
- 0.97 |
- 0.969 |
- 0.967 |
- 0.964 |
- 0.946 |
- 0.911 |
- 0.96 |
- 0.911 |
- 0.972 |
- 0.962 |
- 0.95 |
- 0.959 |
- 0.951 |
- 0.972 |
- 0.97 |
- 0.968 |
- 0.962 |
- 0.974 |
- 0.975 |
- 0.968 |
- 0.962 |
- 0.958 |
- 0.963 |
- 0.966 |
- 0.943 |
- 0.962 |
- 0.964 |
- 0.973 |
- 0.971 |
- 0.958 |
- 0.958 |
- 0.967 |
- 0.973 |
- 0.942 |
- 0.967 |
- 0.947 |
- 0.976 |
- 0.961 |
- 0.962 |
- 0.957 |
- 0.971 |
- 0.961 |
- 0.959 |
- 0.965 |
- 0.965 |
- 0.969 |
- 0.956 |
- 0.94 |
- 0.951 |
- 0.95 |
- 0.961 |
- 0.967 |
- 0.959 |
- 0.98 |
- 0.961 |
- 0.968 |
- 0.964 |
- 0.976 |
- 0.959 |
- 0.962 |
- 0.96 |
- 0.963 |
- 0.965 |
- 0.944 |
- 0.963 |
- 0.962 |
- 0.96 |
- 0.969 |
- 0.973 |
- 0.957 |
- 0.966 |
- 0.98 |
- 0.976 |
- 0.96 |
- 0.968 |
- 0.97 |
- 0.962 |
- 0.947 |
- 0.968 |
- 0.971 |
- 0.966 |
- 0.967 |
- 0.951 |
- 0.911 |
- 0.957 |
- 0.919 |
- |
- 0.901 |
- 0.96 |
-
-
- | Liver |
- 245 |
- F |
- 230 |
- 102616.12 |
- CD |
- BXD9 |
- H2577 |
- 0.984 |
- 0.932 |
- 0.932 |
- 0.983 |
- 0.973 |
- 0.979 |
- 0.981 |
- 0.972 |
- 0.895 |
- 0.977 |
- 0.965 |
- 0.988 |
- 0.976 |
- 0.981 |
- 0.968 |
- 0.979 |
- 0.978 |
- 0.971 |
- 0.981 |
- 0.979 |
- 0.976 |
- 0.986 |
- 0.984 |
- 0.987 |
- 0.987 |
- 0.976 |
- 0.976 |
- 0.985 |
- 0.982 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.938 |
- 0.976 |
- 0.987 |
- 0.981 |
- 0.946 |
- 0.984 |
- 0.987 |
- 0.984 |
- 0.985 |
- 0.973 |
- 0.979 |
- 0.981 |
- 0.985 |
- 0.952 |
- 0.968 |
- 0.972 |
- 0.983 |
- 0.976 |
- 0.986 |
- 0.972 |
- 0.983 |
- 0.969 |
- 0.984 |
- 0.979 |
- 0.982 |
- 0.976 |
- 0.985 |
- 0.98 |
- 0.967 |
- 0.953 |
- 1 |
- 0.893 |
- 0.979 |
- 0.974 |
- 0.979 |
- 0.983 |
- 0.974 |
- 0.955 |
- 0.98 |
- 0.959 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.98 |
- 0.976 |
- 0.98 |
- 0.987 |
- 0.986 |
- 0.975 |
- 0.975 |
- 0.962 |
- 0.975 |
- 0.982 |
- 0.971 |
- 0.983 |
- 0.983 |
- 0.98 |
- 0.98 |
- 0.975 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.986 |
- 0.981 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.977 |
- 0.983 |
- 0.972 |
- 0.98 |
- 0.974 |
- 0.982 |
- 0.975 |
- 0.983 |
- 0.982 |
- 0.982 |
- 0.942 |
- 0.976 |
- 0.984 |
- 0.967 |
- 0.982 |
- 0.979 |
- 0.985 |
- 0.972 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.964 |
- 0.979 |
- 0.964 |
- 0.987 |
- 0.986 |
- 0.982 |
- 0.977 |
- 0.979 |
- 0.987 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.978 |
- 0.98 |
- 0.972 |
- 0.98 |
- 0.981 |
- 0.983 |
- 0.98 |
- 0.986 |
- 0.923 |
- 0.979 |
- 0.976 |
- 0.986 |
- 0.984 |
- 0.981 |
- 0.959 |
- 0.977 |
- 0.952 |
- |
- 0.893 |
- 0.98 |
-
-
- | Liver |
- 548 |
- F |
- 73 |
- 082214.11 |
- CD |
- BXD9 |
- H1006 |
- 0.897 |
- 0.943 |
- 0.945 |
- 0.906 |
- 0.915 |
- 0.924 |
- 0.893 |
- 0.879 |
- 0.918 |
- 0.906 |
- 0.927 |
- 0.899 |
- 0.912 |
- 0.904 |
- 0.919 |
- 0.913 |
- 0.896 |
- 0.88 |
- 0.915 |
- 0.913 |
- 0.896 |
- 0.9 |
- 0.899 |
- 0.899 |
- 0.89 |
- 0.903 |
- 0.904 |
- 0.89 |
- 0.916 |
- 0.905 |
- 0.895 |
- 0.902 |
- 0.943 |
- 0.884 |
- 0.883 |
- 0.91 |
- 0.875 |
- 0.896 |
- 0.89 |
- 0.89 |
- 0.9 |
- 0.899 |
- 0.892 |
- 0.9 |
- 0.889 |
- 0.9 |
- 0.905 |
- 0.921 |
- 0.897 |
- 0.901 |
- 0.901 |
- 0.877 |
- 0.901 |
- 0.924 |
- 0.902 |
- 0.905 |
- 0.898 |
- 0.885 |
- 0.908 |
- 0.896 |
- 0.915 |
- 0.939 |
- 0.893 |
- 1 |
- 0.9 |
- 0.902 |
- 0.917 |
- 0.905 |
- 0.899 |
- 0.863 |
- 0.901 |
- 0.863 |
- 0.911 |
- 0.893 |
- 0.889 |
- 0.896 |
- 0.895 |
- 0.902 |
- 0.91 |
- 0.903 |
- 0.9 |
- 0.912 |
- 0.929 |
- 0.906 |
- 0.897 |
- 0.912 |
- 0.896 |
- 0.901 |
- 0.889 |
- 0.896 |
- 0.896 |
- 0.916 |
- 0.916 |
- 0.9 |
- 0.9 |
- 0.906 |
- 0.911 |
- 0.888 |
- 0.915 |
- 0.89 |
- 0.918 |
- 0.899 |
- 0.916 |
- 0.904 |
- 0.919 |
- 0.894 |
- 0.892 |
- 0.896 |
- 0.9 |
- 0.915 |
- 0.926 |
- 0.88 |
- 0.889 |
- 0.905 |
- 0.895 |
- 0.917 |
- 0.889 |
- 0.92 |
- 0.894 |
- 0.902 |
- 0.906 |
- 0.937 |
- 0.899 |
- 0.926 |
- 0.898 |
- 0.9 |
- 0.903 |
- 0.891 |
- 0.903 |
- 0.904 |
- 0.895 |
- 0.915 |
- 0.911 |
- 0.883 |
- 0.896 |
- 0.927 |
- 0.918 |
- 0.892 |
- 0.902 |
- 0.907 |
- 0.897 |
- 0.952 |
- 0.899 |
- 0.915 |
- 0.906 |
- 0.901 |
- 0.888 |
- 0.863 |
- 0.888 |
- 0.883 |
- |
- 0.863 |
- 0.90 |
-
-
- | Liver |
- 188 |
- F |
- 304 |
- 102414.03 |
- CD |
- BXD90 |
- H1702 |
- 0.987 |
- 0.919 |
- 0.921 |
- 0.984 |
- 0.976 |
- 0.982 |
- 0.98 |
- 0.953 |
- 0.882 |
- 0.984 |
- 0.972 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.969 |
- 0.981 |
- 0.968 |
- 0.956 |
- 0.98 |
- 0.983 |
- 0.972 |
- 0.986 |
- 0.985 |
- 0.986 |
- 0.977 |
- 0.969 |
- 0.97 |
- 0.968 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.978 |
- 0.949 |
- 0.973 |
- 0.979 |
- 0.971 |
- 0.92 |
- 0.981 |
- 0.972 |
- 0.975 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.985 |
- 0.978 |
- 0.939 |
- 0.974 |
- 0.976 |
- 0.982 |
- 0.97 |
- 0.985 |
- 0.954 |
- 0.973 |
- 0.975 |
- 0.983 |
- 0.982 |
- 0.972 |
- 0.978 |
- 0.986 |
- 0.976 |
- 0.976 |
- 0.97 |
- 0.979 |
- 0.9 |
- 1 |
- 0.99 |
- 0.971 |
- 0.984 |
- 0.966 |
- 0.932 |
- 0.973 |
- 0.935 |
- 0.984 |
- 0.98 |
- 0.977 |
- 0.976 |
- 0.967 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.974 |
- 0.979 |
- 0.969 |
- 0.981 |
- 0.977 |
- 0.96 |
- 0.985 |
- 0.985 |
- 0.968 |
- 0.976 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.97 |
- 0.97 |
- 0.984 |
- 0.977 |
- 0.962 |
- 0.974 |
- 0.967 |
- 0.982 |
- 0.976 |
- 0.962 |
- 0.972 |
- 0.977 |
- 0.983 |
- 0.977 |
- 0.984 |
- 0.983 |
- 0.974 |
- 0.952 |
- 0.964 |
- 0.973 |
- 0.958 |
- 0.978 |
- 0.971 |
- 0.981 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.976 |
- 0.969 |
- 0.972 |
- 0.958 |
- 0.977 |
- 0.983 |
- 0.982 |
- 0.962 |
- 0.976 |
- 0.98 |
- 0.98 |
- 0.974 |
- 0.977 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.979 |
- 0.982 |
- 0.984 |
- 0.981 |
- 0.982 |
- 0.93 |
- 0.979 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.976 |
- 0.935 |
- 0.967 |
- 0.929 |
- |
- 0.882 |
- 0.97 |
-
-
- | Liver |
- 549 |
- F |
- 311 |
- 062013.02 |
- CD |
- BXD90 |
- H0756 |
- 0.985 |
- 0.92 |
- 0.923 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.951 |
- 0.884 |
- 0.98 |
- 0.968 |
- 0.977 |
- 0.984 |
- 0.984 |
- 0.969 |
- 0.974 |
- 0.969 |
- 0.95 |
- 0.979 |
- 0.979 |
- 0.966 |
- 0.98 |
- 0.986 |
- 0.983 |
- 0.973 |
- 0.966 |
- 0.967 |
- 0.962 |
- 0.982 |
- 0.98 |
- 0.984 |
- 0.974 |
- 0.95 |
- 0.975 |
- 0.978 |
- 0.97 |
- 0.924 |
- 0.979 |
- 0.973 |
- 0.975 |
- 0.978 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.973 |
- 0.939 |
- 0.977 |
- 0.976 |
- 0.98 |
- 0.973 |
- 0.981 |
- 0.956 |
- 0.971 |
- 0.979 |
- 0.985 |
- 0.98 |
- 0.969 |
- 0.972 |
- 0.983 |
- 0.975 |
- 0.98 |
- 0.969 |
- 0.974 |
- 0.902 |
- 0.99 |
- 1 |
- 0.971 |
- 0.981 |
- 0.963 |
- 0.93 |
- 0.973 |
- 0.935 |
- 0.982 |
- 0.981 |
- 0.978 |
- 0.975 |
- 0.969 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.974 |
- 0.978 |
- 0.969 |
- 0.978 |
- 0.972 |
- 0.962 |
- 0.981 |
- 0.985 |
- 0.968 |
- 0.97 |
- 0.978 |
- 0.98 |
- 0.978 |
- 0.971 |
- 0.97 |
- 0.983 |
- 0.975 |
- 0.96 |
- 0.978 |
- 0.966 |
- 0.979 |
- 0.972 |
- 0.964 |
- 0.973 |
- 0.977 |
- 0.984 |
- 0.977 |
- 0.979 |
- 0.983 |
- 0.975 |
- 0.954 |
- 0.967 |
- 0.972 |
- 0.961 |
- 0.98 |
- 0.971 |
- 0.98 |
- 0.978 |
- 0.974 |
- 0.98 |
- 0.976 |
- 0.971 |
- 0.971 |
- 0.963 |
- 0.978 |
- 0.98 |
- 0.979 |
- 0.963 |
- 0.976 |
- 0.979 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.979 |
- 0.981 |
- 0.975 |
- 0.979 |
- 0.985 |
- 0.986 |
- 0.983 |
- 0.98 |
- 0.929 |
- 0.981 |
- 0.978 |
- 0.977 |
- 0.979 |
- 0.976 |
- 0.935 |
- 0.963 |
- 0.929 |
- |
- 0.884 |
- 0.97 |
-
-
- | Liver |
- 562 |
- F |
- 21 |
- 062013.17 |
- CD |
- BXD91 |
- H0883 |
- 0.972 |
- 0.955 |
- 0.956 |
- 0.975 |
- 0.972 |
- 0.977 |
- 0.97 |
- 0.968 |
- 0.925 |
- 0.975 |
- 0.97 |
- 0.976 |
- 0.974 |
- 0.973 |
- 0.975 |
- 0.969 |
- 0.977 |
- 0.973 |
- 0.982 |
- 0.975 |
- 0.964 |
- 0.972 |
- 0.974 |
- 0.976 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.977 |
- 0.98 |
- 0.97 |
- 0.973 |
- 0.97 |
- 0.958 |
- 0.971 |
- 0.974 |
- 0.983 |
- 0.952 |
- 0.972 |
- 0.975 |
- 0.973 |
- 0.981 |
- 0.977 |
- 0.974 |
- 0.978 |
- 0.978 |
- 0.959 |
- 0.964 |
- 0.973 |
- 0.971 |
- 0.971 |
- 0.976 |
- 0.968 |
- 0.982 |
- 0.972 |
- 0.974 |
- 0.97 |
- 0.98 |
- 0.965 |
- 0.978 |
- 0.974 |
- 0.965 |
- 0.967 |
- 0.979 |
- 0.917 |
- 0.971 |
- 0.971 |
- 1 |
- 0.976 |
- 0.975 |
- 0.959 |
- 0.978 |
- 0.957 |
- 0.977 |
- 0.97 |
- 0.972 |
- 0.974 |
- 0.976 |
- 0.973 |
- 0.983 |
- 0.982 |
- 0.97 |
- 0.976 |
- 0.969 |
- 0.975 |
- 0.98 |
- 0.985 |
- 0.976 |
- 0.976 |
- 0.977 |
- 0.969 |
- 0.973 |
- 0.983 |
- 0.984 |
- 0.976 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.976 |
- 0.987 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.984 |
- 0.975 |
- 0.976 |
- 0.97 |
- 0.973 |
- 0.976 |
- 0.972 |
- 0.981 |
- 0.952 |
- 0.968 |
- 0.973 |
- 0.971 |
- 0.976 |
- 1 |
- 0.975 |
- 0.983 |
- 0.975 |
- 0.978 |
- 0.974 |
- 0.971 |
- 0.971 |
- 0.98 |
- 0.979 |
- 0.976 |
- 0.972 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.966 |
- 0.97 |
- 0.975 |
- 0.974 |
- 0.973 |
- 0.987 |
- 0.974 |
- 0.974 |
- 0.941 |
- 0.973 |
- 0.975 |
- 0.978 |
- 0.974 |
- 0.968 |
- 0.957 |
- 0.979 |
- 0.963 |
- |
- 0.917 |
- 0.97 |
-
-
- | Liver |
- 536 |
- F |
- 277 |
- 101014.10 |
- CD |
- BXD95 |
- H1742 |
- 0.988 |
- 0.928 |
- 0.93 |
- 0.987 |
- 0.978 |
- 0.983 |
- 0.983 |
- 0.965 |
- 0.893 |
- 0.982 |
- 0.972 |
- 0.984 |
- 0.983 |
- 0.987 |
- 0.972 |
- 0.98 |
- 0.971 |
- 0.963 |
- 0.983 |
- 0.985 |
- 0.977 |
- 0.988 |
- 0.986 |
- 0.989 |
- 0.983 |
- 0.971 |
- 0.972 |
- 0.974 |
- 0.987 |
- 0.986 |
- 0.984 |
- 0.985 |
- 0.951 |
- 0.975 |
- 0.985 |
- 0.976 |
- 0.935 |
- 0.983 |
- 0.979 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.98 |
- 0.984 |
- 0.982 |
- 0.946 |
- 0.974 |
- 0.982 |
- 0.982 |
- 0.976 |
- 0.988 |
- 0.962 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.986 |
- 0.979 |
- 0.977 |
- 0.986 |
- 0.979 |
- 0.975 |
- 0.964 |
- 0.983 |
- 0.905 |
- 0.984 |
- 0.981 |
- 0.976 |
- 1 |
- 0.971 |
- 0.942 |
- 0.983 |
- 0.94 |
- 0.986 |
- 0.983 |
- 0.982 |
- 0.979 |
- 0.972 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.98 |
- 0.983 |
- 0.972 |
- 0.98 |
- 0.983 |
- 0.968 |
- 0.986 |
- 0.988 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.978 |
- 0.977 |
- 0.986 |
- 0.982 |
- 0.972 |
- 0.977 |
- 0.976 |
- 0.983 |
- 0.98 |
- 0.971 |
- 0.976 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.986 |
- 0.985 |
- 0.982 |
- 0.956 |
- 0.969 |
- 0.98 |
- 0.966 |
- 0.979 |
- 0.976 |
- 0.979 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.982 |
- 0.973 |
- 0.98 |
- 0.966 |
- 0.983 |
- 0.988 |
- 0.985 |
- 0.97 |
- 0.979 |
- 0.985 |
- 0.985 |
- 0.982 |
- 0.982 |
- 0.977 |
- 0.98 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.986 |
- 0.937 |
- 0.983 |
- 0.979 |
- 0.986 |
- 0.984 |
- 0.981 |
- 0.94 |
- 0.97 |
- 0.941 |
- |
- 0.893 |
- 0.98 |
-
-
- | Liver |
- 384 |
- F |
- 146 |
- 012615.17 |
- CD |
- BXD98 |
- H1769 |
- 0.966 |
- 0.946 |
- 0.945 |
- 0.965 |
- 0.967 |
- 0.969 |
- 0.964 |
- 0.973 |
- 0.929 |
- 0.973 |
- 0.956 |
- 0.975 |
- 0.966 |
- 0.97 |
- 0.976 |
- 0.967 |
- 0.978 |
- 0.969 |
- 0.966 |
- 0.967 |
- 0.955 |
- 0.968 |
- 0.967 |
- 0.973 |
- 0.984 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.972 |
- 0.967 |
- 0.964 |
- 0.967 |
- 0.937 |
- 0.968 |
- 0.972 |
- 0.98 |
- 0.971 |
- 0.966 |
- 0.973 |
- 0.966 |
- 0.971 |
- 0.962 |
- 0.966 |
- 0.966 |
- 0.974 |
- 0.966 |
- 0.958 |
- 0.966 |
- 0.963 |
- 0.968 |
- 0.97 |
- 0.978 |
- 0.984 |
- 0.966 |
- 0.966 |
- 0.967 |
- 0.983 |
- 0.957 |
- 0.973 |
- 0.973 |
- 0.958 |
- 0.946 |
- 0.974 |
- 0.899 |
- 0.966 |
- 0.963 |
- 0.975 |
- 0.971 |
- 1 |
- 0.98 |
- 0.98 |
- 0.974 |
- 0.965 |
- 0.964 |
- 0.968 |
- 0.973 |
- 0.978 |
- 0.962 |
- 0.971 |
- 0.969 |
- 0.965 |
- 0.96 |
- 0.958 |
- 0.96 |
- 0.975 |
- 0.97 |
- 0.973 |
- 0.967 |
- 0.978 |
- 0.966 |
- 0.96 |
- 0.968 |
- 0.971 |
- 0.97 |
- 0.969 |
- 0.973 |
- 0.963 |
- 0.983 |
- 0.975 |
- 0.982 |
- 0.965 |
- 0.97 |
- 0.978 |
- 0.971 |
- 0.96 |
- 0.961 |
- 0.964 |
- 0.962 |
- 0.958 |
- 0.975 |
- 0.934 |
- 0.969 |
- 0.968 |
- 0.964 |
- 0.97 |
- 0.975 |
- 0.962 |
- 0.959 |
- 0.965 |
- 0.965 |
- 0.968 |
- 0.961 |
- 0.968 |
- 0.968 |
- 0.972 |
- 0.97 |
- 0.965 |
- 0.979 |
- 0.964 |
- 0.974 |
- 0.963 |
- 0.975 |
- 0.963 |
- 0.966 |
- 0.962 |
- 0.962 |
- 0.955 |
- 0.966 |
- 0.976 |
- 0.958 |
- 0.97 |
- 0.925 |
- 0.958 |
- 0.955 |
- 0.969 |
- 0.964 |
- 0.963 |
- 0.974 |
- 0.969 |
- 0.971 |
- |
- 0.899 |
- 0.97 |
-
-
- | Liver |
- 384 |
- F |
- 182 |
- 012615.16 |
- CD |
- BXD98 |
- H1524 |
- 0.939 |
- 0.931 |
- 0.93 |
- 0.939 |
- 0.942 |
- 0.938 |
- 0.944 |
- 0.966 |
- 0.918 |
- 0.948 |
- 0.927 |
- 0.951 |
- 0.935 |
- 0.94 |
- 0.953 |
- 0.934 |
- 0.959 |
- 0.958 |
- 0.939 |
- 0.939 |
- 0.928 |
- 0.941 |
- 0.943 |
- 0.946 |
- 0.966 |
- 0.973 |
- 0.973 |
- 0.97 |
- 0.949 |
- 0.94 |
- 0.939 |
- 0.942 |
- 0.901 |
- 0.954 |
- 0.953 |
- 0.962 |
- 0.977 |
- 0.947 |
- 0.959 |
- 0.947 |
- 0.946 |
- 0.937 |
- 0.945 |
- 0.943 |
- 0.957 |
- 0.958 |
- 0.934 |
- 0.942 |
- 0.94 |
- 0.954 |
- 0.942 |
- 0.978 |
- 0.971 |
- 0.938 |
- 0.939 |
- 0.94 |
- 0.97 |
- 0.931 |
- 0.944 |
- 0.957 |
- 0.925 |
- 0.911 |
- 0.955 |
- 0.863 |
- 0.932 |
- 0.93 |
- 0.959 |
- 0.942 |
- 0.98 |
- 1 |
- 0.966 |
- 0.976 |
- 0.937 |
- 0.944 |
- 0.948 |
- 0.957 |
- 0.964 |
- 0.938 |
- 0.943 |
- 0.944 |
- 0.947 |
- 0.935 |
- 0.925 |
- 0.934 |
- 0.958 |
- 0.952 |
- 0.953 |
- 0.939 |
- 0.96 |
- 0.945 |
- 0.932 |
- 0.941 |
- 0.946 |
- 0.952 |
- 0.952 |
- 0.947 |
- 0.94 |
- 0.975 |
- 0.955 |
- 0.972 |
- 0.935 |
- 0.955 |
- 0.963 |
- 0.952 |
- 0.931 |
- 0.934 |
- 0.943 |
- 0.938 |
- 0.925 |
- 0.953 |
- 0.898 |
- 0.957 |
- 0.951 |
- 0.946 |
- 0.949 |
- 0.959 |
- 0.941 |
- 0.931 |
- 0.941 |
- 0.942 |
- 0.943 |
- 0.929 |
- 0.945 |
- 0.949 |
- 0.954 |
- 0.943 |
- 0.935 |
- 0.974 |
- 0.939 |
- 0.952 |
- 0.937 |
- 0.953 |
- 0.94 |
- 0.94 |
- 0.938 |
- 0.929 |
- 0.926 |
- 0.943 |
- 0.957 |
- 0.929 |
- 0.946 |
- 0.886 |
- 0.936 |
- 0.927 |
- 0.944 |
- 0.938 |
- 0.938 |
- 0.976 |
- 0.954 |
- 0.972 |
- |
- 0.863 |
- 0.95 |
-
-
- | Liver |
- 535 |
- F |
- 278 |
- 111414.14 |
- CD |
- BXD99 |
- H1354 |
- 0.982 |
- 0.939 |
- 0.94 |
- 0.98 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.975 |
- 0.909 |
- 0.981 |
- 0.968 |
- 0.985 |
- 0.975 |
- 0.979 |
- 0.98 |
- 0.975 |
- 0.975 |
- 0.97 |
- 0.976 |
- 0.981 |
- 0.969 |
- 0.982 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.984 |
- 0.985 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.978 |
- 0.979 |
- 0.946 |
- 0.979 |
- 0.982 |
- 0.984 |
- 0.96 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.976 |
- 0.983 |
- 0.983 |
- 0.961 |
- 0.977 |
- 0.981 |
- 0.982 |
- 0.986 |
- 0.983 |
- 0.979 |
- 0.987 |
- 0.979 |
- 0.979 |
- 0.982 |
- 0.987 |
- 0.971 |
- 0.981 |
- 0.985 |
- 0.971 |
- 0.96 |
- 0.98 |
- 0.901 |
- 0.973 |
- 0.973 |
- 0.978 |
- 0.983 |
- 0.98 |
- 0.966 |
- 1 |
- 0.958 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.984 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.984 |
- 0.978 |
- 0.967 |
- 0.972 |
- 0.986 |
- 0.969 |
- 0.986 |
- 0.981 |
- 0.977 |
- 0.979 |
- 0.972 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.98 |
- 0.982 |
- 0.98 |
- 0.982 |
- 0.979 |
- 0.984 |
- 0.977 |
- 0.983 |
- 0.98 |
- 0.976 |
- 0.973 |
- 0.976 |
- 0.977 |
- 0.979 |
- 0.97 |
- 0.981 |
- 0.946 |
- 0.976 |
- 0.979 |
- 0.973 |
- 0.981 |
- 0.978 |
- 0.975 |
- 0.974 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.972 |
- 0.978 |
- 0.972 |
- 0.985 |
- 0.983 |
- 0.977 |
- 0.982 |
- 0.974 |
- 0.984 |
- 0.976 |
- 0.981 |
- 0.98 |
- 0.975 |
- 0.976 |
- 0.972 |
- 0.973 |
- 0.977 |
- 0.984 |
- 0.974 |
- 0.981 |
- 0.925 |
- 0.983 |
- 0.971 |
- 0.981 |
- 0.978 |
- 0.976 |
- 0.958 |
- 0.974 |
- 0.959 |
- |
- 0.901 |
- 0.98 |
-
-
- | Liver |
- 361 |
- M |
- 162 |
- 012615.26 |
- CD |
- C57BL/6J |
- H1590 |
- 0.935 |
- 0.931 |
- 0.929 |
- 0.935 |
- 0.942 |
- 0.94 |
- 0.938 |
- 0.964 |
- 0.922 |
- 0.943 |
- 0.922 |
- 0.954 |
- 0.934 |
- 0.938 |
- 0.952 |
- 0.937 |
- 0.958 |
- 0.962 |
- 0.939 |
- 0.935 |
- 0.928 |
- 0.941 |
- 0.945 |
- 0.946 |
- 0.964 |
- 0.967 |
- 0.967 |
- 0.969 |
- 0.943 |
- 0.938 |
- 0.941 |
- 0.94 |
- 0.9 |
- 0.953 |
- 0.954 |
- 0.961 |
- 0.976 |
- 0.944 |
- 0.96 |
- 0.945 |
- 0.946 |
- 0.934 |
- 0.944 |
- 0.939 |
- 0.954 |
- 0.96 |
- 0.927 |
- 0.935 |
- 0.942 |
- 0.95 |
- 0.941 |
- 0.976 |
- 0.967 |
- 0.935 |
- 0.943 |
- 0.938 |
- 0.961 |
- 0.935 |
- 0.945 |
- 0.946 |
- 0.932 |
- 0.911 |
- 0.959 |
- 0.863 |
- 0.935 |
- 0.935 |
- 0.957 |
- 0.94 |
- 0.974 |
- 0.976 |
- 0.958 |
- 1 |
- 0.936 |
- 0.938 |
- 0.952 |
- 0.946 |
- 0.96 |
- 0.935 |
- 0.942 |
- 0.944 |
- 0.94 |
- 0.93 |
- 0.923 |
- 0.931 |
- 0.95 |
- 0.955 |
- 0.945 |
- 0.939 |
- 0.962 |
- 0.942 |
- 0.932 |
- 0.942 |
- 0.947 |
- 0.951 |
- 0.95 |
- 0.948 |
- 0.939 |
- 0.973 |
- 0.958 |
- 0.97 |
- 0.931 |
- 0.95 |
- 0.955 |
- 0.953 |
- 0.93 |
- 0.936 |
- 0.939 |
- 0.936 |
- 0.931 |
- 0.949 |
- 0.903 |
- 0.958 |
- 0.949 |
- 0.945 |
- 0.953 |
- 0.957 |
- 0.946 |
- 0.926 |
- 0.938 |
- 0.938 |
- 0.94 |
- 0.928 |
- 0.941 |
- 0.945 |
- 0.954 |
- 0.945 |
- 0.937 |
- 0.97 |
- 0.942 |
- 0.954 |
- 0.936 |
- 0.949 |
- 0.939 |
- 0.945 |
- 0.941 |
- 0.927 |
- 0.927 |
- 0.948 |
- 0.959 |
- 0.933 |
- 0.951 |
- 0.89 |
- 0.932 |
- 0.93 |
- 0.944 |
- 0.941 |
- 0.943 |
- 1 |
- 0.957 |
- 0.968 |
- |
- 0.863 |
- 0.94 |
-
-
- | Liver |
- 537 |
- F |
- 273 |
- 091914.09 |
- CD |
- C57BL/6J |
- H1103 |
- 0.989 |
- 0.932 |
- 0.933 |
- 0.991 |
- 0.981 |
- 0.989 |
- 0.987 |
- 0.962 |
- 0.894 |
- 0.985 |
- 0.982 |
- 0.983 |
- 0.985 |
- 0.984 |
- 0.975 |
- 0.981 |
- 0.968 |
- 0.959 |
- 0.984 |
- 0.987 |
- 0.982 |
- 0.988 |
- 0.986 |
- 0.986 |
- 0.976 |
- 0.975 |
- 0.975 |
- 0.973 |
- 0.99 |
- 0.986 |
- 0.988 |
- 0.984 |
- 0.959 |
- 0.973 |
- 0.979 |
- 0.977 |
- 0.928 |
- 0.987 |
- 0.978 |
- 0.98 |
- 0.987 |
- 0.986 |
- 0.98 |
- 0.989 |
- 0.981 |
- 0.946 |
- 0.981 |
- 0.983 |
- 0.984 |
- 0.977 |
- 0.988 |
- 0.957 |
- 0.975 |
- 0.98 |
- 0.984 |
- 0.986 |
- 0.976 |
- 0.98 |
- 0.986 |
- 0.978 |
- 0.976 |
- 0.972 |
- 0.98 |
- 0.911 |
- 0.984 |
- 0.982 |
- 0.977 |
- 0.986 |
- 0.965 |
- 0.937 |
- 0.979 |
- 0.936 |
- 1 |
- 0.987 |
- 0.982 |
- 0.978 |
- 0.965 |
- 0.989 |
- 0.989 |
- 0.989 |
- 0.983 |
- 0.987 |
- 0.978 |
- 0.988 |
- 0.984 |
- 0.964 |
- 0.985 |
- 0.988 |
- 0.972 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.984 |
- 0.978 |
- 0.977 |
- 0.986 |
- 0.984 |
- 0.966 |
- 0.979 |
- 0.97 |
- 0.989 |
- 0.984 |
- 0.971 |
- 0.979 |
- 0.987 |
- 0.989 |
- 0.979 |
- 0.987 |
- 0.982 |
- 0.984 |
- 0.959 |
- 0.967 |
- 0.979 |
- 0.972 |
- 0.98 |
- 0.977 |
- 0.981 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.978 |
- 0.981 |
- 0.968 |
- 0.982 |
- 0.986 |
- 0.986 |
- 0.967 |
- 0.98 |
- 0.982 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.976 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.987 |
- 0.983 |
- 0.941 |
- 0.986 |
- 0.989 |
- 0.993 |
- 0.988 |
- 0.983 |
- 0.936 |
- 0.966 |
- 0.935 |
- |
- 0.894 |
- 0.98 |
-
-
- | Liver |
- 210 |
- F |
- 300 |
- 101713.18 |
- CD |
- D2B6F1 |
- H1154 |
- 0.992 |
- 0.916 |
- 0.918 |
- 0.987 |
- 0.985 |
- 0.981 |
- 1 |
- 0.961 |
- 0.877 |
- 0.987 |
- 0.971 |
- 0.982 |
- 0.98 |
- 0.984 |
- 0.969 |
- 0.977 |
- 0.967 |
- 0.958 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.987 |
- 0.99 |
- 0.988 |
- 0.979 |
- 0.972 |
- 0.972 |
- 0.971 |
- 0.985 |
- 0.986 |
- 0.987 |
- 0.986 |
- 0.94 |
- 0.979 |
- 0.98 |
- 0.972 |
- 0.932 |
- 0.988 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.988 |
- 0.981 |
- 0.945 |
- 0.989 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.984 |
- 0.961 |
- 0.972 |
- 0.979 |
- 0.985 |
- 0.986 |
- 0.976 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.976 |
- 0.962 |
- 0.981 |
- 0.893 |
- 0.98 |
- 0.981 |
- 0.97 |
- 0.983 |
- 0.964 |
- 0.944 |
- 0.981 |
- 0.938 |
- 0.987 |
- 1 |
- 0.985 |
- 0.984 |
- 0.968 |
- 0.993 |
- 0.986 |
- 0.987 |
- 0.988 |
- 0.986 |
- 0.973 |
- 0.981 |
- 0.985 |
- 0.957 |
- 0.988 |
- 0.988 |
- 0.97 |
- 0.984 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.974 |
- 0.986 |
- 0.977 |
- 0.969 |
- 0.979 |
- 0.972 |
- 0.98 |
- 0.982 |
- 0.97 |
- 0.98 |
- 0.981 |
- 0.988 |
- 0.976 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.951 |
- 0.974 |
- 0.979 |
- 0.969 |
- 0.988 |
- 0.97 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.988 |
- 0.988 |
- 0.973 |
- 0.985 |
- 0.966 |
- 0.985 |
- 0.985 |
- 0.982 |
- 0.968 |
- 0.976 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.977 |
- 0.977 |
- 0.987 |
- 0.975 |
- 0.981 |
- 0.988 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.921 |
- 0.988 |
- 0.981 |
- 0.987 |
- 0.989 |
- 0.986 |
- 0.938 |
- 0.966 |
- 0.94 |
- |
- 0.877 |
- 0.98 |
-
-
- | Liver |
- 545 |
- F |
- 298 |
- 062013.12 |
- CD |
- D2B6F1 |
- H0646 |
- 0.983 |
- 0.921 |
- 0.921 |
- 0.982 |
- 0.976 |
- 0.982 |
- 0.985 |
- 0.974 |
- 0.89 |
- 0.976 |
- 0.961 |
- 0.985 |
- 0.976 |
- 0.979 |
- 0.972 |
- 0.978 |
- 0.972 |
- 0.969 |
- 0.977 |
- 0.979 |
- 0.981 |
- 0.983 |
- 0.988 |
- 0.984 |
- 0.983 |
- 0.974 |
- 0.974 |
- 0.978 |
- 0.981 |
- 0.983 |
- 0.989 |
- 0.984 |
- 0.933 |
- 0.978 |
- 0.986 |
- 0.975 |
- 0.942 |
- 0.985 |
- 0.985 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.976 |
- 0.983 |
- 0.987 |
- 0.957 |
- 0.971 |
- 0.976 |
- 0.982 |
- 0.978 |
- 0.986 |
- 0.972 |
- 0.977 |
- 0.971 |
- 0.985 |
- 0.983 |
- 0.975 |
- 0.983 |
- 0.983 |
- 0.978 |
- 0.971 |
- 0.95 |
- 0.984 |
- 0.889 |
- 0.977 |
- 0.978 |
- 0.972 |
- 0.982 |
- 0.968 |
- 0.948 |
- 0.98 |
- 0.952 |
- 0.982 |
- 0.985 |
- 1 |
- 0.978 |
- 0.973 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.979 |
- 0.976 |
- 0.961 |
- 0.976 |
- 0.98 |
- 0.966 |
- 0.98 |
- 0.986 |
- 0.981 |
- 0.98 |
- 0.976 |
- 0.978 |
- 0.98 |
- 0.979 |
- 0.978 |
- 0.983 |
- 0.973 |
- 0.976 |
- 0.978 |
- 0.978 |
- 0.974 |
- 0.98 |
- 0.964 |
- 0.979 |
- 0.979 |
- 0.988 |
- 0.973 |
- 0.978 |
- 0.974 |
- 0.977 |
- 0.942 |
- 0.977 |
- 0.982 |
- 0.975 |
- 0.982 |
- 0.972 |
- 0.982 |
- 0.97 |
- 0.981 |
- 0.978 |
- 0.978 |
- 0.966 |
- 0.979 |
- 0.963 |
- 0.985 |
- 0.988 |
- 0.983 |
- 0.973 |
- 0.98 |
- 0.985 |
- 0.984 |
- 0.977 |
- 0.973 |
- 0.979 |
- 0.978 |
- 0.971 |
- 0.972 |
- 0.984 |
- 0.983 |
- 0.98 |
- 0.985 |
- 0.922 |
- 0.979 |
- 0.974 |
- 0.983 |
- 0.987 |
- 0.994 |
- 0.952 |
- 0.968 |
- 0.953 |
- |
- 0.889 |
- 0.97 |
-
-
- | Liver |
- 212 |
- F |
- 67 |
- 101713.10 |
- CD |
- DBA/2J |
- H1147 |
- 0.985 |
- 0.931 |
- 0.932 |
- 0.983 |
- 0.976 |
- 0.978 |
- 0.984 |
- 0.975 |
- 0.898 |
- 0.982 |
- 0.969 |
- 0.982 |
- 0.971 |
- 0.978 |
- 0.969 |
- 0.977 |
- 0.983 |
- 0.966 |
- 0.979 |
- 0.98 |
- 0.969 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.979 |
- 0.941 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.951 |
- 0.987 |
- 0.986 |
- 0.984 |
- 0.982 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.953 |
- 0.978 |
- 0.981 |
- 0.984 |
- 0.98 |
- 0.981 |
- 0.973 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.983 |
- 0.974 |
- 0.986 |
- 1 |
- 0.967 |
- 0.959 |
- 0.98 |
- 0.896 |
- 0.976 |
- 0.975 |
- 0.974 |
- 0.979 |
- 0.973 |
- 0.957 |
- 0.985 |
- 0.946 |
- 0.978 |
- 0.984 |
- 0.978 |
- 1 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.977 |
- 0.965 |
- 0.975 |
- 0.983 |
- 0.965 |
- 0.984 |
- 0.981 |
- 0.977 |
- 0.982 |
- 0.978 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.976 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.982 |
- 0.977 |
- 0.975 |
- 0.972 |
- 0.979 |
- 0.983 |
- 0.98 |
- 0.972 |
- 0.983 |
- 0.94 |
- 0.984 |
- 0.984 |
- 0.972 |
- 0.977 |
- 0.974 |
- 0.98 |
- 0.973 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.97 |
- 0.979 |
- 0.967 |
- 0.984 |
- 0.982 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.984 |
- 0.98 |
- 0.983 |
- 0.979 |
- 0.98 |
- 0.976 |
- 0.971 |
- 0.975 |
- 0.979 |
- 0.983 |
- 0.976 |
- 0.982 |
- 0.918 |
- 0.983 |
- 0.97 |
- 0.978 |
- 0.979 |
- 0.977 |
- 0.946 |
- 0.973 |
- 0.949 |
- |
- 0.896 |
- 0.98 |
-
-
- | Liver |
- 764 |
- F |
- 121 |
- 083016.07 |
- CD |
- DBA/2J |
- H1818 |
- 0.971 |
- 0.942 |
- 0.942 |
- 0.971 |
- 0.969 |
- 0.971 |
- 0.968 |
- 0.98 |
- 0.92 |
- 0.97 |
- 0.961 |
- 0.977 |
- 0.965 |
- 0.969 |
- 0.969 |
- 0.967 |
- 0.989 |
- 0.969 |
- 0.974 |
- 0.975 |
- 0.957 |
- 0.972 |
- 0.972 |
- 0.975 |
- 0.981 |
- 0.983 |
- 0.984 |
- 0.98 |
- 0.977 |
- 0.971 |
- 0.97 |
- 0.968 |
- 0.939 |
- 0.982 |
- 0.982 |
- 0.984 |
- 0.967 |
- 0.976 |
- 0.984 |
- 0.977 |
- 0.971 |
- 0.974 |
- 0.977 |
- 0.974 |
- 0.979 |
- 0.961 |
- 0.963 |
- 0.972 |
- 0.972 |
- 0.975 |
- 0.975 |
- 0.981 |
- 0.988 |
- 0.975 |
- 0.975 |
- 0.971 |
- 0.983 |
- 0.962 |
- 0.979 |
- 0.985 |
- 0.961 |
- 0.951 |
- 0.976 |
- 0.895 |
- 0.967 |
- 0.969 |
- 0.976 |
- 0.972 |
- 0.978 |
- 0.964 |
- 0.984 |
- 0.96 |
- 0.965 |
- 0.968 |
- 0.973 |
- 0.985 |
- 1 |
- 0.969 |
- 0.974 |
- 0.974 |
- 0.969 |
- 0.964 |
- 0.954 |
- 0.962 |
- 0.975 |
- 0.973 |
- 0.975 |
- 0.972 |
- 0.98 |
- 0.968 |
- 0.972 |
- 0.976 |
- 0.978 |
- 0.982 |
- 0.982 |
- 0.973 |
- 0.975 |
- 0.98 |
- 0.975 |
- 0.98 |
- 0.968 |
- 0.972 |
- 0.977 |
- 0.971 |
- 0.964 |
- 0.967 |
- 0.978 |
- 0.968 |
- 0.963 |
- 0.976 |
- 0.931 |
- 0.982 |
- 0.978 |
- 0.97 |
- 0.971 |
- 0.976 |
- 0.969 |
- 0.961 |
- 0.969 |
- 0.969 |
- 0.967 |
- 0.963 |
- 0.965 |
- 0.963 |
- 0.98 |
- 0.976 |
- 0.969 |
- 0.987 |
- 0.975 |
- 0.982 |
- 0.973 |
- 0.976 |
- 0.975 |
- 0.973 |
- 0.965 |
- 0.964 |
- 0.963 |
- 0.969 |
- 0.984 |
- 0.965 |
- 0.974 |
- 0.916 |
- 0.97 |
- 0.959 |
- 0.966 |
- 0.967 |
- 0.968 |
- 0.96 |
- 0.974 |
- 0.963 |
- |
- 0.895 |
- 0.97 |
-
-
- | Liver |
- 216 |
- F |
- 306 |
- 101713.15 |
- HF |
- B6D2F1 |
- H1302 |
- 0.994 |
- 0.923 |
- 0.926 |
- 0.989 |
- 0.987 |
- 0.984 |
- 0.993 |
- 0.956 |
- 0.881 |
- 0.987 |
- 0.977 |
- 0.984 |
- 0.983 |
- 0.986 |
- 0.971 |
- 0.981 |
- 0.968 |
- 0.956 |
- 0.983 |
- 0.983 |
- 0.978 |
- 0.989 |
- 0.99 |
- 0.989 |
- 0.977 |
- 0.972 |
- 0.973 |
- 0.97 |
- 0.988 |
- 0.988 |
- 0.988 |
- 0.984 |
- 0.951 |
- 0.977 |
- 0.98 |
- 0.974 |
- 0.929 |
- 0.989 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.986 |
- 0.983 |
- 0.99 |
- 0.979 |
- 0.942 |
- 0.989 |
- 0.983 |
- 0.988 |
- 0.983 |
- 0.985 |
- 0.959 |
- 0.974 |
- 0.983 |
- 0.989 |
- 0.988 |
- 0.975 |
- 0.978 |
- 0.986 |
- 0.983 |
- 0.982 |
- 0.972 |
- 0.98 |
- 0.902 |
- 0.984 |
- 0.985 |
- 0.973 |
- 0.984 |
- 0.962 |
- 0.938 |
- 0.98 |
- 0.935 |
- 0.989 |
- 0.993 |
- 0.982 |
- 0.983 |
- 0.969 |
- 1 |
- 0.989 |
- 0.991 |
- 0.987 |
- 0.989 |
- 0.978 |
- 0.984 |
- 0.985 |
- 0.96 |
- 0.988 |
- 0.989 |
- 0.968 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.977 |
- 0.987 |
- 0.984 |
- 0.967 |
- 0.982 |
- 0.973 |
- 0.986 |
- 0.984 |
- 0.97 |
- 0.981 |
- 0.984 |
- 0.988 |
- 0.979 |
- 0.988 |
- 0.985 |
- 0.984 |
- 0.957 |
- 0.972 |
- 0.98 |
- 0.968 |
- 0.988 |
- 0.973 |
- 0.988 |
- 0.986 |
- 0.984 |
- 0.989 |
- 0.986 |
- 0.978 |
- 0.984 |
- 0.969 |
- 0.985 |
- 0.987 |
- 0.986 |
- 0.968 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.988 |
- 0.98 |
- 0.988 |
- 0.988 |
- 0.985 |
- 0.99 |
- 0.987 |
- 0.929 |
- 0.991 |
- 0.986 |
- 0.988 |
- 0.991 |
- 0.984 |
- 0.935 |
- 0.969 |
- 0.934 |
- |
- 0.881 |
- 0.98 |
-
-
- | Liver |
- 547 |
- F |
- 279 |
- 102616.04 |
- HF |
- B6D2F1 |
- H2288 |
- 0.989 |
- 0.938 |
- 0.94 |
- 0.989 |
- 0.981 |
- 0.988 |
- 0.986 |
- 0.966 |
- 0.901 |
- 0.984 |
- 0.982 |
- 0.987 |
- 0.986 |
- 0.987 |
- 0.974 |
- 0.985 |
- 0.976 |
- 0.969 |
- 0.989 |
- 0.986 |
- 0.983 |
- 0.988 |
- 0.987 |
- 0.989 |
- 0.982 |
- 0.976 |
- 0.976 |
- 0.977 |
- 0.989 |
- 0.987 |
- 0.987 |
- 0.986 |
- 0.959 |
- 0.975 |
- 0.984 |
- 0.982 |
- 0.936 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.988 |
- 0.984 |
- 0.981 |
- 0.988 |
- 0.984 |
- 0.949 |
- 0.977 |
- 0.982 |
- 0.984 |
- 0.978 |
- 0.99 |
- 0.962 |
- 0.981 |
- 0.98 |
- 0.988 |
- 0.987 |
- 0.98 |
- 0.979 |
- 0.99 |
- 0.982 |
- 0.977 |
- 0.97 |
- 0.987 |
- 0.91 |
- 0.984 |
- 0.981 |
- 0.983 |
- 0.988 |
- 0.971 |
- 0.943 |
- 0.981 |
- 0.942 |
- 0.989 |
- 0.986 |
- 0.984 |
- 0.982 |
- 0.974 |
- 0.989 |
- 1 |
- 0.996 |
- 0.982 |
- 0.987 |
- 0.98 |
- 0.986 |
- 0.987 |
- 0.973 |
- 0.987 |
- 0.991 |
- 0.979 |
- 0.984 |
- 0.985 |
- 0.989 |
- 0.989 |
- 0.983 |
- 0.982 |
- 0.991 |
- 0.987 |
- 0.974 |
- 0.984 |
- 0.978 |
- 0.99 |
- 0.985 |
- 0.977 |
- 0.982 |
- 0.987 |
- 0.987 |
- 0.982 |
- 0.99 |
- 0.988 |
- 0.988 |
- 0.959 |
- 0.972 |
- 0.983 |
- 0.974 |
- 0.983 |
- 0.983 |
- 0.985 |
- 0.985 |
- 0.988 |
- 0.986 |
- 0.985 |
- 0.979 |
- 0.984 |
- 0.973 |
- 0.988 |
- 0.992 |
- 0.988 |
- 0.973 |
- 0.984 |
- 0.989 |
- 0.988 |
- 0.988 |
- 0.987 |
- 0.979 |
- 0.982 |
- 0.985 |
- 0.987 |
- 0.983 |
- 0.987 |
- 0.989 |
- 0.987 |
- 0.942 |
- 0.985 |
- 0.988 |
- 0.991 |
- 0.99 |
- 0.984 |
- 0.942 |
- 0.976 |
- 0.948 |
- |
- 0.901 |
- 0.98 |
-
-
- | Liver |
- 547 |
- F |
- 296 |
- 102616.05 |
- HF |
- B6D2F1 |
- H2290 |
- 0.99 |
- 0.932 |
- 0.934 |
- 0.988 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.966 |
- 0.895 |
- 0.985 |
- 0.979 |
- 0.987 |
- 0.984 |
- 0.986 |
- 0.973 |
- 0.984 |
- 0.975 |
- 0.969 |
- 0.989 |
- 0.985 |
- 0.981 |
- 0.988 |
- 0.988 |
- 0.989 |
- 0.982 |
- 0.975 |
- 0.976 |
- 0.976 |
- 0.988 |
- 0.987 |
- 0.989 |
- 0.985 |
- 0.955 |
- 0.977 |
- 0.986 |
- 0.98 |
- 0.934 |
- 0.987 |
- 0.983 |
- 0.986 |
- 0.987 |
- 0.985 |
- 0.984 |
- 0.989 |
- 0.984 |
- 0.947 |
- 0.978 |
- 0.982 |
- 0.986 |
- 0.979 |
- 0.989 |
- 0.963 |
- 0.979 |
- 0.978 |
- 0.989 |
- 0.987 |
- 0.978 |
- 0.981 |
- 0.99 |
- 0.983 |
- 0.978 |
- 0.968 |
- 0.986 |
- 0.903 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.987 |
- 0.969 |
- 0.944 |
- 0.981 |
- 0.944 |
- 0.989 |
- 0.987 |
- 0.986 |
- 0.983 |
- 0.974 |
- 0.991 |
- 0.996 |
- 1 |
- 0.983 |
- 0.988 |
- 0.978 |
- 0.988 |
- 0.986 |
- 0.973 |
- 0.986 |
- 0.991 |
- 0.98 |
- 0.985 |
- 0.987 |
- 0.989 |
- 0.989 |
- 0.983 |
- 0.982 |
- 0.99 |
- 0.987 |
- 0.975 |
- 0.985 |
- 0.979 |
- 0.988 |
- 0.985 |
- 0.974 |
- 0.982 |
- 0.985 |
- 0.989 |
- 0.983 |
- 0.99 |
- 0.989 |
- 0.987 |
- 0.956 |
- 0.975 |
- 0.985 |
- 0.973 |
- 0.985 |
- 0.982 |
- 0.989 |
- 0.985 |
- 0.988 |
- 0.988 |
- 0.984 |
- 0.976 |
- 0.984 |
- 0.971 |
- 0.989 |
- 0.992 |
- 0.988 |
- 0.973 |
- 0.985 |
- 0.989 |
- 0.989 |
- 0.987 |
- 0.987 |
- 0.983 |
- 0.982 |
- 0.982 |
- 0.987 |
- 0.987 |
- 0.988 |
- 0.99 |
- 0.988 |
- 0.935 |
- 0.988 |
- 0.989 |
- 0.989 |
- 0.992 |
- 0.987 |
- 0.944 |
- 0.978 |
- 0.946 |
- |
- 0.895 |
- 0.98 |
-
-
- | Liver |
- 176 |
- F |
- 254 |
- 042415.12 |
- HF |
- BXD100 |
- H2085 |
- 0.986 |
- 0.927 |
- 0.927 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.988 |
- 0.966 |
- 0.89 |
- 0.984 |
- 0.973 |
- 0.981 |
- 0.973 |
- 0.979 |
- 0.974 |
- 0.976 |
- 0.964 |
- 0.959 |
- 0.976 |
- 0.979 |
- 0.979 |
- 0.984 |
- 0.984 |
- 0.985 |
- 0.977 |
- 0.975 |
- 0.975 |
- 0.975 |
- 0.985 |
- 0.986 |
- 0.98 |
- 0.984 |
- 0.945 |
- 0.977 |
- 0.976 |
- 0.973 |
- 0.94 |
- 0.987 |
- 0.977 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.977 |
- 0.987 |
- 0.98 |
- 0.95 |
- 0.983 |
- 0.983 |
- 0.984 |
- 0.985 |
- 0.981 |
- 0.963 |
- 0.975 |
- 0.979 |
- 0.98 |
- 0.986 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.983 |
- 0.974 |
- 0.962 |
- 0.975 |
- 0.9 |
- 0.974 |
- 0.974 |
- 0.97 |
- 0.98 |
- 0.965 |
- 0.947 |
- 0.984 |
- 0.94 |
- 0.983 |
- 0.988 |
- 0.979 |
- 0.983 |
- 0.969 |
- 0.987 |
- 0.982 |
- 0.983 |
- 1 |
- 0.988 |
- 0.974 |
- 0.979 |
- 0.989 |
- 0.958 |
- 0.985 |
- 0.983 |
- 0.968 |
- 0.985 |
- 0.974 |
- 0.976 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.972 |
- 0.976 |
- 0.974 |
- 0.979 |
- 0.986 |
- 0.974 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.983 |
- 0.972 |
- 0.981 |
- 0.95 |
- 0.975 |
- 0.981 |
- 0.972 |
- 0.983 |
- 0.97 |
- 0.979 |
- 0.979 |
- 0.985 |
- 0.985 |
- 0.98 |
- 0.975 |
- 0.982 |
- 0.969 |
- 0.982 |
- 0.982 |
- 0.982 |
- 0.971 |
- 0.974 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.981 |
- 0.975 |
- 0.98 |
- 0.974 |
- 0.979 |
- 0.983 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.926 |
- 0.986 |
- 0.978 |
- 0.986 |
- 0.982 |
- 0.98 |
- 0.94 |
- 0.965 |
- 0.942 |
- |
- 0.89 |
- 0.97 |
-
-
- | Liver |
- 537 |
- F |
- 77 |
- 050914.04 |
- HF |
- BXD100 |
- H1187 |
- 0.988 |
- 0.931 |
- 0.933 |
- 0.989 |
- 0.985 |
- 0.987 |
- 0.986 |
- 0.956 |
- 0.892 |
- 0.985 |
- 0.98 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.972 |
- 0.977 |
- 0.963 |
- 0.958 |
- 0.984 |
- 0.983 |
- 0.977 |
- 0.986 |
- 0.984 |
- 0.986 |
- 0.975 |
- 0.969 |
- 0.97 |
- 0.968 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.958 |
- 0.969 |
- 0.976 |
- 0.972 |
- 0.927 |
- 0.982 |
- 0.973 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.977 |
- 0.985 |
- 0.976 |
- 0.94 |
- 0.981 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.983 |
- 0.953 |
- 0.972 |
- 0.98 |
- 0.982 |
- 0.985 |
- 0.974 |
- 0.975 |
- 0.983 |
- 0.977 |
- 0.98 |
- 0.974 |
- 0.975 |
- 0.912 |
- 0.979 |
- 0.978 |
- 0.976 |
- 0.983 |
- 0.96 |
- 0.935 |
- 0.978 |
- 0.93 |
- 0.987 |
- 0.986 |
- 0.976 |
- 0.977 |
- 0.964 |
- 0.989 |
- 0.987 |
- 0.988 |
- 0.988 |
- 1 |
- 0.984 |
- 0.983 |
- 0.986 |
- 0.964 |
- 0.983 |
- 0.986 |
- 0.966 |
- 0.983 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.978 |
- 0.977 |
- 0.985 |
- 0.985 |
- 0.966 |
- 0.98 |
- 0.971 |
- 0.986 |
- 0.981 |
- 0.975 |
- 0.976 |
- 0.984 |
- 0.982 |
- 0.978 |
- 0.985 |
- 0.982 |
- 0.984 |
- 0.958 |
- 0.964 |
- 0.976 |
- 0.967 |
- 0.982 |
- 0.976 |
- 0.981 |
- 0.989 |
- 0.984 |
- 0.988 |
- 0.982 |
- 0.979 |
- 0.983 |
- 0.972 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.965 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.974 |
- 0.981 |
- 0.983 |
- 0.987 |
- 0.982 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.94 |
- 0.987 |
- 0.986 |
- 0.986 |
- 0.986 |
- 0.978 |
- 0.93 |
- 0.969 |
- 0.935 |
- |
- 0.892 |
- 0.98 |
-
-
- | Liver |
- 493 |
- F |
- 290 |
- 042715.19 |
- HF |
- BXD101 |
- H1422 |
- 0.975 |
- 0.944 |
- 0.947 |
- 0.977 |
- 0.981 |
- 0.983 |
- 0.973 |
- 0.944 |
- 0.917 |
- 0.976 |
- 0.985 |
- 0.969 |
- 0.975 |
- 0.974 |
- 0.972 |
- 0.976 |
- 0.956 |
- 0.95 |
- 0.977 |
- 0.973 |
- 0.969 |
- 0.974 |
- 0.971 |
- 0.974 |
- 0.961 |
- 0.962 |
- 0.963 |
- 0.956 |
- 0.977 |
- 0.976 |
- 0.968 |
- 0.976 |
- 0.97 |
- 0.954 |
- 0.958 |
- 0.971 |
- 0.923 |
- 0.966 |
- 0.957 |
- 0.962 |
- 0.971 |
- 0.971 |
- 0.962 |
- 0.974 |
- 0.964 |
- 0.94 |
- 0.975 |
- 0.975 |
- 0.969 |
- 0.969 |
- 0.972 |
- 0.938 |
- 0.962 |
- 0.977 |
- 0.971 |
- 0.976 |
- 0.964 |
- 0.962 |
- 0.973 |
- 0.965 |
- 0.977 |
- 0.975 |
- 0.962 |
- 0.929 |
- 0.969 |
- 0.969 |
- 0.969 |
- 0.972 |
- 0.958 |
- 0.925 |
- 0.967 |
- 0.923 |
- 0.978 |
- 0.973 |
- 0.961 |
- 0.965 |
- 0.954 |
- 0.978 |
- 0.98 |
- 0.978 |
- 0.974 |
- 0.984 |
- 1 |
- 0.975 |
- 0.974 |
- 0.958 |
- 0.971 |
- 0.974 |
- 0.955 |
- 0.973 |
- 0.971 |
- 0.977 |
- 0.977 |
- 0.964 |
- 0.964 |
- 0.977 |
- 0.975 |
- 0.955 |
- 0.974 |
- 0.96 |
- 0.983 |
- 0.97 |
- 0.973 |
- 0.97 |
- 0.983 |
- 0.968 |
- 0.963 |
- 0.973 |
- 0.972 |
- 0.978 |
- 0.968 |
- 0.947 |
- 0.959 |
- 0.966 |
- 0.973 |
- 0.969 |
- 0.967 |
- 0.984 |
- 0.972 |
- 0.978 |
- 0.976 |
- 0.985 |
- 0.977 |
- 0.972 |
- 0.97 |
- 0.973 |
- 0.975 |
- 0.954 |
- 0.969 |
- 0.971 |
- 0.969 |
- 0.978 |
- 0.975 |
- 0.961 |
- 0.971 |
- 0.985 |
- 0.981 |
- 0.971 |
- 0.971 |
- 0.978 |
- 0.969 |
- 0.96 |
- 0.972 |
- 0.981 |
- 0.977 |
- 0.977 |
- 0.965 |
- 0.923 |
- 0.96 |
- 0.938 |
- |
- 0.917 |
- 0.97 |
-
-
- | Liver |
- 183 |
- F |
- 284 |
- 052814.04 |
- HF |
- BXD102 |
- H1361 |
- 0.982 |
- 0.927 |
- 0.928 |
- 0.985 |
- 0.976 |
- 0.985 |
- 0.981 |
- 0.956 |
- 0.892 |
- 0.988 |
- 0.983 |
- 0.977 |
- 0.981 |
- 0.979 |
- 0.968 |
- 0.978 |
- 0.968 |
- 0.962 |
- 0.982 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.972 |
- 0.97 |
- 0.971 |
- 0.967 |
- 0.984 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.955 |
- 0.969 |
- 0.973 |
- 0.973 |
- 0.921 |
- 0.979 |
- 0.97 |
- 0.975 |
- 0.984 |
- 0.982 |
- 0.977 |
- 0.985 |
- 0.977 |
- 0.939 |
- 0.975 |
- 0.98 |
- 0.977 |
- 0.969 |
- 0.983 |
- 0.949 |
- 0.971 |
- 0.973 |
- 0.979 |
- 0.979 |
- 0.968 |
- 0.977 |
- 0.981 |
- 0.975 |
- 0.971 |
- 0.968 |
- 0.975 |
- 0.906 |
- 0.981 |
- 0.978 |
- 0.975 |
- 0.98 |
- 0.96 |
- 0.934 |
- 0.972 |
- 0.931 |
- 0.988 |
- 0.981 |
- 0.976 |
- 0.975 |
- 0.962 |
- 0.984 |
- 0.986 |
- 0.988 |
- 0.979 |
- 0.983 |
- 0.975 |
- 1 |
- 0.985 |
- 0.965 |
- 0.98 |
- 0.983 |
- 0.97 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.982 |
- 0.973 |
- 0.972 |
- 0.983 |
- 0.98 |
- 0.961 |
- 0.978 |
- 0.965 |
- 0.984 |
- 0.978 |
- 0.969 |
- 0.974 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.984 |
- 0.978 |
- 0.978 |
- 0.954 |
- 0.962 |
- 0.974 |
- 0.966 |
- 0.975 |
- 0.975 |
- 0.978 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.98 |
- 0.974 |
- 0.978 |
- 0.965 |
- 0.976 |
- 0.981 |
- 0.982 |
- 0.963 |
- 0.977 |
- 0.977 |
- 0.979 |
- 0.978 |
- 0.98 |
- 0.971 |
- 0.975 |
- 0.98 |
- 0.982 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.977 |
- 0.938 |
- 0.982 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.976 |
- 0.931 |
- 0.968 |
- 0.936 |
- |
- 0.892 |
- 0.97 |
-
-
- | Liver |
- 366 |
- F |
- 195 |
- 121214.07 |
- HF |
- BXD102 |
- H1498 |
- 0.985 |
- 0.933 |
- 0.933 |
- 0.985 |
- 0.98 |
- 0.984 |
- 0.985 |
- 0.972 |
- 0.898 |
- 0.987 |
- 0.977 |
- 0.985 |
- 0.976 |
- 0.981 |
- 0.974 |
- 0.978 |
- 0.972 |
- 0.974 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.985 |
- 0.983 |
- 0.988 |
- 0.984 |
- 0.982 |
- 0.982 |
- 0.983 |
- 0.986 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.945 |
- 0.977 |
- 0.981 |
- 0.981 |
- 0.946 |
- 0.985 |
- 0.98 |
- 0.982 |
- 0.988 |
- 0.982 |
- 0.979 |
- 0.988 |
- 0.986 |
- 0.954 |
- 0.977 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.985 |
- 0.968 |
- 0.983 |
- 0.975 |
- 0.98 |
- 0.982 |
- 0.984 |
- 0.978 |
- 0.983 |
- 0.983 |
- 0.969 |
- 0.962 |
- 0.982 |
- 0.897 |
- 0.977 |
- 0.972 |
- 0.98 |
- 0.983 |
- 0.975 |
- 0.958 |
- 0.986 |
- 0.95 |
- 0.984 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.975 |
- 0.985 |
- 0.987 |
- 0.986 |
- 0.989 |
- 0.986 |
- 0.974 |
- 0.985 |
- 1 |
- 0.968 |
- 0.988 |
- 0.984 |
- 0.976 |
- 0.987 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.987 |
- 0.984 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.983 |
- 0.987 |
- 0.979 |
- 0.979 |
- 0.979 |
- 0.979 |
- 0.98 |
- 0.987 |
- 0.974 |
- 0.983 |
- 0.945 |
- 0.973 |
- 0.982 |
- 0.971 |
- 0.983 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.99 |
- 0.987 |
- 0.982 |
- 0.972 |
- 0.983 |
- 0.97 |
- 0.983 |
- 0.985 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.977 |
- 0.979 |
- 0.977 |
- 0.979 |
- 0.98 |
- 0.985 |
- 0.978 |
- 0.982 |
- 0.928 |
- 0.983 |
- 0.977 |
- 0.988 |
- 0.983 |
- 0.979 |
- 0.95 |
- 0.978 |
- 0.954 |
- |
- 0.897 |
- 0.98 |
-
-
- | Liver |
- 688 |
- F |
- 140 |
- 083016.08 |
- HF |
- BXD24 |
- H2259 |
- 0.959 |
- 0.949 |
- 0.949 |
- 0.962 |
- 0.958 |
- 0.968 |
- 0.957 |
- 0.966 |
- 0.926 |
- 0.964 |
- 0.957 |
- 0.971 |
- 0.963 |
- 0.963 |
- 0.969 |
- 0.962 |
- 0.975 |
- 0.973 |
- 0.975 |
- 0.966 |
- 0.954 |
- 0.962 |
- 0.963 |
- 0.967 |
- 0.973 |
- 0.968 |
- 0.968 |
- 0.968 |
- 0.968 |
- 0.96 |
- 0.964 |
- 0.96 |
- 0.953 |
- 0.964 |
- 0.969 |
- 0.975 |
- 0.949 |
- 0.96 |
- 0.97 |
- 0.967 |
- 0.971 |
- 0.965 |
- 0.964 |
- 0.963 |
- 0.967 |
- 0.951 |
- 0.951 |
- 0.963 |
- 0.96 |
- 0.959 |
- 0.968 |
- 0.962 |
- 0.974 |
- 0.962 |
- 0.965 |
- 0.96 |
- 0.97 |
- 0.961 |
- 0.97 |
- 0.965 |
- 0.959 |
- 0.958 |
- 0.971 |
- 0.912 |
- 0.96 |
- 0.962 |
- 0.985 |
- 0.968 |
- 0.97 |
- 0.952 |
- 0.969 |
- 0.955 |
- 0.964 |
- 0.957 |
- 0.966 |
- 0.965 |
- 0.973 |
- 0.96 |
- 0.973 |
- 0.973 |
- 0.958 |
- 0.964 |
- 0.958 |
- 0.965 |
- 0.968 |
- 1 |
- 0.962 |
- 0.965 |
- 0.977 |
- 0.961 |
- 0.971 |
- 0.977 |
- 0.979 |
- 0.972 |
- 0.971 |
- 0.971 |
- 0.972 |
- 0.972 |
- 0.979 |
- 0.972 |
- 0.963 |
- 0.966 |
- 0.973 |
- 0.964 |
- 0.963 |
- 0.961 |
- 0.968 |
- 0.965 |
- 0.963 |
- 0.973 |
- 0.944 |
- 0.964 |
- 0.968 |
- 0.965 |
- 0.962 |
- 0.985 |
- 0.964 |
- 0.969 |
- 0.964 |
- 0.966 |
- 0.965 |
- 0.962 |
- 0.961 |
- 0.972 |
- 0.97 |
- 0.968 |
- 0.964 |
- 0.971 |
- 0.969 |
- 0.971 |
- 0.967 |
- 0.973 |
- 0.972 |
- 0.964 |
- 0.958 |
- 0.963 |
- 0.964 |
- 0.963 |
- 0.976 |
- 0.964 |
- 0.965 |
- 0.933 |
- 0.961 |
- 0.963 |
- 0.966 |
- 0.966 |
- 0.961 |
- 0.955 |
- 0.976 |
- 0.958 |
- |
- 0.912 |
- 0.96 |
-
-
- | Liver |
- 182 |
- F |
- 317 |
- 121515.05 |
- HF |
- BXD29 |
- H2349 |
- 0.99 |
- 0.923 |
- 0.925 |
- 0.986 |
- 0.98 |
- 0.981 |
- 0.988 |
- 0.964 |
- 0.887 |
- 0.986 |
- 0.972 |
- 0.984 |
- 0.985 |
- 0.99 |
- 0.972 |
- 0.977 |
- 0.972 |
- 0.962 |
- 0.981 |
- 0.984 |
- 0.976 |
- 0.988 |
- 0.987 |
- 0.989 |
- 0.984 |
- 0.979 |
- 0.979 |
- 0.976 |
- 0.988 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.945 |
- 0.978 |
- 0.984 |
- 0.977 |
- 0.94 |
- 0.987 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.988 |
- 0.984 |
- 0.947 |
- 0.981 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.986 |
- 0.967 |
- 0.981 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.984 |
- 0.972 |
- 0.963 |
- 0.983 |
- 0.896 |
- 0.985 |
- 0.981 |
- 0.976 |
- 0.986 |
- 0.973 |
- 0.953 |
- 0.986 |
- 0.945 |
- 0.985 |
- 0.988 |
- 0.98 |
- 0.984 |
- 0.975 |
- 0.988 |
- 0.987 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.971 |
- 0.98 |
- 0.988 |
- 0.962 |
- 1 |
- 0.991 |
- 0.976 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.978 |
- 0.977 |
- 0.988 |
- 0.98 |
- 0.975 |
- 0.977 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.974 |
- 0.978 |
- 0.978 |
- 0.982 |
- 0.982 |
- 0.987 |
- 0.979 |
- 0.981 |
- 0.95 |
- 0.973 |
- 0.98 |
- 0.966 |
- 0.984 |
- 0.976 |
- 0.981 |
- 0.98 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.972 |
- 0.981 |
- 0.964 |
- 0.984 |
- 0.986 |
- 0.982 |
- 0.974 |
- 0.975 |
- 0.984 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.978 |
- 0.981 |
- 0.975 |
- 0.98 |
- 0.981 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.924 |
- 0.985 |
- 0.979 |
- 0.986 |
- 0.983 |
- 0.98 |
- 0.945 |
- 0.971 |
- 0.943 |
- |
- 0.887 |
- 0.98 |
-
-
- | Liver |
- 577 |
- F |
- 295 |
- 061913.04 |
- HF |
- BXD29 |
- H0669 |
- 0.991 |
- 0.924 |
- 0.926 |
- 0.989 |
- 0.982 |
- 0.986 |
- 0.988 |
- 0.964 |
- 0.886 |
- 0.984 |
- 0.974 |
- 0.986 |
- 0.987 |
- 0.991 |
- 0.975 |
- 0.981 |
- 0.97 |
- 0.962 |
- 0.985 |
- 0.986 |
- 0.983 |
- 0.989 |
- 0.991 |
- 0.99 |
- 0.981 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.988 |
- 0.988 |
- 0.988 |
- 0.987 |
- 0.949 |
- 0.975 |
- 0.985 |
- 0.976 |
- 0.934 |
- 0.986 |
- 0.98 |
- 0.982 |
- 0.985 |
- 0.985 |
- 0.981 |
- 0.988 |
- 0.984 |
- 0.947 |
- 0.98 |
- 0.982 |
- 0.984 |
- 0.98 |
- 0.989 |
- 0.962 |
- 0.978 |
- 0.981 |
- 0.99 |
- 0.988 |
- 0.977 |
- 0.98 |
- 0.989 |
- 0.981 |
- 0.98 |
- 0.966 |
- 0.983 |
- 0.901 |
- 0.985 |
- 0.985 |
- 0.976 |
- 0.988 |
- 0.967 |
- 0.939 |
- 0.981 |
- 0.939 |
- 0.988 |
- 0.988 |
- 0.986 |
- 0.981 |
- 0.972 |
- 0.989 |
- 0.991 |
- 0.991 |
- 0.983 |
- 0.986 |
- 0.974 |
- 0.983 |
- 0.984 |
- 0.965 |
- 0.991 |
- 1 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.986 |
- 0.986 |
- 0.98 |
- 0.98 |
- 0.989 |
- 0.982 |
- 0.972 |
- 0.981 |
- 0.977 |
- 0.986 |
- 0.982 |
- 0.971 |
- 0.98 |
- 0.984 |
- 0.988 |
- 0.981 |
- 0.987 |
- 0.987 |
- 0.984 |
- 0.955 |
- 0.972 |
- 0.981 |
- 0.968 |
- 0.985 |
- 0.976 |
- 0.985 |
- 0.983 |
- 0.987 |
- 0.987 |
- 0.984 |
- 0.976 |
- 0.983 |
- 0.967 |
- 0.987 |
- 0.991 |
- 0.989 |
- 0.971 |
- 0.983 |
- 0.988 |
- 0.988 |
- 0.984 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.98 |
- 0.985 |
- 0.986 |
- 0.987 |
- 0.988 |
- 0.988 |
- 0.931 |
- 0.988 |
- 0.984 |
- 0.988 |
- 0.99 |
- 0.987 |
- 0.939 |
- 0.97 |
- 0.94 |
- |
- 0.886 |
- 0.98 |
-
-
- | Liver |
- 630 |
- F |
- 119 |
- 111314.10 |
- HF |
- BXD29 |
- H1037 |
- 0.97 |
- 0.934 |
- 0.932 |
- 0.972 |
- 0.964 |
- 0.973 |
- 0.97 |
- 0.983 |
- 0.914 |
- 0.971 |
- 0.957 |
- 0.978 |
- 0.971 |
- 0.977 |
- 0.97 |
- 0.969 |
- 0.983 |
- 0.972 |
- 0.975 |
- 0.973 |
- 0.968 |
- 0.974 |
- 0.973 |
- 0.975 |
- 0.983 |
- 0.975 |
- 0.974 |
- 0.979 |
- 0.974 |
- 0.971 |
- 0.976 |
- 0.975 |
- 0.934 |
- 0.978 |
- 0.983 |
- 0.978 |
- 0.956 |
- 0.974 |
- 0.983 |
- 0.979 |
- 0.978 |
- 0.972 |
- 0.976 |
- 0.972 |
- 0.981 |
- 0.956 |
- 0.956 |
- 0.97 |
- 0.968 |
- 0.965 |
- 0.979 |
- 0.973 |
- 0.98 |
- 0.967 |
- 0.975 |
- 0.971 |
- 0.976 |
- 0.973 |
- 0.979 |
- 0.977 |
- 0.958 |
- 0.943 |
- 0.98 |
- 0.889 |
- 0.968 |
- 0.968 |
- 0.977 |
- 0.976 |
- 0.978 |
- 0.96 |
- 0.977 |
- 0.962 |
- 0.972 |
- 0.97 |
- 0.981 |
- 0.977 |
- 0.98 |
- 0.968 |
- 0.979 |
- 0.98 |
- 0.968 |
- 0.966 |
- 0.955 |
- 0.97 |
- 0.976 |
- 0.977 |
- 0.976 |
- 0.979 |
- 1 |
- 0.97 |
- 0.973 |
- 0.976 |
- 0.979 |
- 0.983 |
- 0.983 |
- 0.977 |
- 0.972 |
- 0.98 |
- 0.977 |
- 0.979 |
- 0.968 |
- 0.974 |
- 0.974 |
- 0.973 |
- 0.968 |
- 0.973 |
- 0.979 |
- 0.972 |
- 0.968 |
- 0.978 |
- 0.933 |
- 0.981 |
- 0.982 |
- 0.973 |
- 0.97 |
- 0.977 |
- 0.973 |
- 0.964 |
- 0.974 |
- 0.97 |
- 0.972 |
- 0.96 |
- 0.972 |
- 0.963 |
- 0.979 |
- 0.979 |
- 0.974 |
- 0.98 |
- 0.978 |
- 0.98 |
- 0.979 |
- 0.978 |
- 0.972 |
- 0.975 |
- 0.965 |
- 0.965 |
- 0.962 |
- 0.971 |
- 0.98 |
- 0.968 |
- 0.977 |
- 0.922 |
- 0.967 |
- 0.964 |
- 0.976 |
- 0.974 |
- 0.978 |
- 0.962 |
- 0.969 |
- 0.96 |
- |
- 0.889 |
- 0.97 |
-
-
- | Liver |
- 200 |
- F |
- 261 |
- 042015.20 |
- HF |
- BXD32 |
- H2030 |
- 0.985 |
- 0.927 |
- 0.928 |
- 0.981 |
- 0.975 |
- 0.984 |
- 0.984 |
- 0.965 |
- 0.887 |
- 0.981 |
- 0.97 |
- 0.986 |
- 0.971 |
- 0.977 |
- 0.973 |
- 0.988 |
- 0.969 |
- 0.972 |
- 0.979 |
- 0.978 |
- 0.984 |
- 0.987 |
- 0.982 |
- 0.984 |
- 0.978 |
- 0.971 |
- 0.971 |
- 0.979 |
- 0.981 |
- 0.986 |
- 0.979 |
- 0.986 |
- 0.941 |
- 0.971 |
- 0.977 |
- 0.974 |
- 0.937 |
- 0.984 |
- 0.978 |
- 0.982 |
- 0.986 |
- 0.977 |
- 0.975 |
- 0.983 |
- 0.98 |
- 0.948 |
- 0.976 |
- 0.977 |
- 0.984 |
- 0.979 |
- 0.984 |
- 0.96 |
- 0.974 |
- 0.972 |
- 0.981 |
- 0.986 |
- 0.976 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.973 |
- 0.962 |
- 0.98 |
- 0.896 |
- 0.976 |
- 0.97 |
- 0.969 |
- 0.98 |
- 0.966 |
- 0.945 |
- 0.979 |
- 0.942 |
- 0.981 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.968 |
- 0.985 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.983 |
- 0.973 |
- 0.979 |
- 0.987 |
- 0.961 |
- 0.982 |
- 0.983 |
- 0.97 |
- 1 |
- 0.983 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.973 |
- 0.975 |
- 0.976 |
- 0.98 |
- 0.987 |
- 0.97 |
- 0.976 |
- 0.976 |
- 0.979 |
- 0.976 |
- 0.984 |
- 0.975 |
- 0.983 |
- 0.943 |
- 0.97 |
- 0.983 |
- 0.97 |
- 0.981 |
- 0.969 |
- 0.982 |
- 0.977 |
- 0.988 |
- 0.982 |
- 0.981 |
- 0.973 |
- 0.985 |
- 0.967 |
- 0.98 |
- 0.985 |
- 0.987 |
- 0.969 |
- 0.981 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.984 |
- 0.927 |
- 0.982 |
- 0.974 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.942 |
- 0.975 |
- 0.946 |
- |
- 0.887 |
- 0.97 |
-
-
- | Liver |
- 539 |
- F |
- 318 |
- 101014.02 |
- HF |
- BXD32 |
- H1137 |
- 0.982 |
- 0.923 |
- 0.925 |
- 0.98 |
- 0.968 |
- 0.98 |
- 0.977 |
- 0.96 |
- 0.888 |
- 0.977 |
- 0.97 |
- 0.978 |
- 0.974 |
- 0.978 |
- 0.964 |
- 0.98 |
- 0.975 |
- 0.969 |
- 0.986 |
- 0.98 |
- 0.975 |
- 0.981 |
- 0.978 |
- 0.98 |
- 0.973 |
- 0.966 |
- 0.967 |
- 0.968 |
- 0.981 |
- 0.978 |
- 0.979 |
- 0.978 |
- 0.947 |
- 0.974 |
- 0.982 |
- 0.973 |
- 0.926 |
- 0.977 |
- 0.976 |
- 0.982 |
- 0.983 |
- 0.984 |
- 0.981 |
- 0.982 |
- 0.976 |
- 0.936 |
- 0.971 |
- 0.975 |
- 0.978 |
- 0.97 |
- 0.982 |
- 0.954 |
- 0.972 |
- 0.971 |
- 0.981 |
- 0.978 |
- 0.971 |
- 0.983 |
- 0.985 |
- 0.978 |
- 0.971 |
- 0.964 |
- 0.975 |
- 0.896 |
- 0.979 |
- 0.978 |
- 0.973 |
- 0.981 |
- 0.96 |
- 0.932 |
- 0.972 |
- 0.932 |
- 0.979 |
- 0.977 |
- 0.976 |
- 0.978 |
- 0.972 |
- 0.981 |
- 0.985 |
- 0.987 |
- 0.974 |
- 0.981 |
- 0.971 |
- 0.981 |
- 0.979 |
- 0.971 |
- 0.979 |
- 0.982 |
- 0.973 |
- 0.983 |
- 1 |
- 0.987 |
- 0.986 |
- 0.98 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.966 |
- 0.975 |
- 0.97 |
- 0.98 |
- 0.976 |
- 0.968 |
- 0.97 |
- 0.975 |
- 0.979 |
- 0.985 |
- 0.985 |
- 0.98 |
- 0.979 |
- 0.946 |
- 0.968 |
- 0.98 |
- 0.966 |
- 0.972 |
- 0.973 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.97 |
- 0.977 |
- 0.962 |
- 0.977 |
- 0.983 |
- 0.982 |
- 0.967 |
- 0.983 |
- 0.979 |
- 0.986 |
- 0.979 |
- 0.981 |
- 0.983 |
- 0.973 |
- 0.976 |
- 0.982 |
- 0.975 |
- 0.98 |
- 0.979 |
- 0.977 |
- 0.928 |
- 0.982 |
- 0.976 |
- 0.977 |
- 0.982 |
- 0.977 |
- 0.932 |
- 0.978 |
- 0.939 |
- |
- 0.888 |
- 0.97 |
-
-
- | Liver |
- 197 |
- F |
- 283 |
- 101513.04 |
- HF |
- BXD34 |
- H1056 |
- 0.984 |
- 0.943 |
- 0.945 |
- 0.986 |
- 0.977 |
- 0.986 |
- 0.978 |
- 0.965 |
- 0.908 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.979 |
- 0.982 |
- 0.973 |
- 0.983 |
- 0.979 |
- 0.968 |
- 0.997 |
- 0.985 |
- 0.976 |
- 0.984 |
- 0.98 |
- 0.984 |
- 0.98 |
- 0.974 |
- 0.975 |
- 0.975 |
- 0.987 |
- 0.981 |
- 0.982 |
- 0.98 |
- 0.959 |
- 0.973 |
- 0.982 |
- 0.983 |
- 0.939 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.983 |
- 0.982 |
- 0.98 |
- 0.984 |
- 0.979 |
- 0.948 |
- 0.977 |
- 0.984 |
- 0.981 |
- 0.976 |
- 0.986 |
- 0.962 |
- 0.979 |
- 0.978 |
- 0.984 |
- 0.981 |
- 0.978 |
- 0.978 |
- 0.989 |
- 0.98 |
- 0.976 |
- 0.973 |
- 0.982 |
- 0.916 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.984 |
- 0.968 |
- 0.941 |
- 0.978 |
- 0.942 |
- 0.984 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.989 |
- 0.989 |
- 0.976 |
- 0.984 |
- 0.977 |
- 0.982 |
- 0.981 |
- 0.977 |
- 0.982 |
- 0.986 |
- 0.976 |
- 0.979 |
- 0.987 |
- 1 |
- 0.997 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.974 |
- 0.985 |
- 0.977 |
- 0.986 |
- 0.981 |
- 0.978 |
- 0.978 |
- 0.983 |
- 0.981 |
- 0.981 |
- 0.985 |
- 0.985 |
- 0.987 |
- 0.956 |
- 0.971 |
- 0.981 |
- 0.971 |
- 0.977 |
- 0.983 |
- 0.981 |
- 0.984 |
- 0.981 |
- 0.981 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.971 |
- 0.984 |
- 0.987 |
- 0.984 |
- 0.973 |
- 0.984 |
- 0.985 |
- 0.986 |
- 0.987 |
- 0.986 |
- 0.979 |
- 0.976 |
- 0.983 |
- 0.987 |
- 0.978 |
- 0.985 |
- 0.984 |
- 0.981 |
- 0.942 |
- 0.983 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.978 |
- 0.942 |
- 0.978 |
- 0.947 |
- |
- 0.908 |
- 0.98 |
-
-
- | Liver |
- 537 |
- F |
- 292 |
- 101014.05 |
- HF |
- BXD34 |
- H1052 |
- 0.983 |
- 0.946 |
- 0.948 |
- 0.985 |
- 0.977 |
- 0.987 |
- 0.978 |
- 0.969 |
- 0.913 |
- 0.979 |
- 0.977 |
- 0.983 |
- 0.979 |
- 0.982 |
- 0.974 |
- 0.983 |
- 0.981 |
- 0.972 |
- 0.997 |
- 0.985 |
- 0.977 |
- 0.983 |
- 0.98 |
- 0.984 |
- 0.981 |
- 0.977 |
- 0.977 |
- 0.977 |
- 0.987 |
- 0.981 |
- 0.981 |
- 0.981 |
- 0.958 |
- 0.974 |
- 0.983 |
- 0.984 |
- 0.944 |
- 0.981 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.98 |
- 0.952 |
- 0.976 |
- 0.984 |
- 0.98 |
- 0.976 |
- 0.986 |
- 0.965 |
- 0.981 |
- 0.979 |
- 0.983 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.989 |
- 0.981 |
- 0.974 |
- 0.971 |
- 0.983 |
- 0.916 |
- 0.979 |
- 0.978 |
- 0.984 |
- 0.984 |
- 0.971 |
- 0.946 |
- 0.979 |
- 0.947 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.982 |
- 0.989 |
- 0.989 |
- 0.977 |
- 0.983 |
- 0.977 |
- 0.982 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.986 |
- 0.979 |
- 0.98 |
- 0.986 |
- 0.997 |
- 1 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.985 |
- 0.976 |
- 0.986 |
- 0.979 |
- 0.985 |
- 0.981 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.988 |
- 0.955 |
- 0.972 |
- 0.981 |
- 0.974 |
- 0.977 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.981 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.972 |
- 0.985 |
- 0.987 |
- 0.984 |
- 0.976 |
- 0.984 |
- 0.986 |
- 0.986 |
- 0.988 |
- 0.985 |
- 0.979 |
- 0.975 |
- 0.983 |
- 0.985 |
- 0.978 |
- 0.986 |
- 0.982 |
- 0.981 |
- 0.942 |
- 0.982 |
- 0.982 |
- 0.983 |
- 0.984 |
- 0.979 |
- 0.947 |
- 0.979 |
- 0.953 |
- |
- 0.913 |
- 0.98 |
-
-
- | Liver |
- 350 |
- F |
- 129 |
- 121214.22 |
- HF |
- BXD39 |
- H1474 |
- 0.979 |
- 0.941 |
- 0.941 |
- 0.981 |
- 0.971 |
- 0.981 |
- 0.975 |
- 0.981 |
- 0.911 |
- 0.974 |
- 0.968 |
- 0.982 |
- 0.969 |
- 0.975 |
- 0.973 |
- 0.976 |
- 0.981 |
- 0.967 |
- 0.981 |
- 0.984 |
- 0.979 |
- 0.982 |
- 0.977 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.977 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.978 |
- 0.943 |
- 0.98 |
- 0.984 |
- 0.981 |
- 0.953 |
- 0.984 |
- 0.989 |
- 0.989 |
- 0.981 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.979 |
- 0.954 |
- 0.966 |
- 0.974 |
- 0.98 |
- 0.978 |
- 0.982 |
- 0.973 |
- 0.981 |
- 0.973 |
- 0.981 |
- 0.979 |
- 0.981 |
- 0.977 |
- 0.985 |
- 0.984 |
- 0.966 |
- 0.958 |
- 0.981 |
- 0.9 |
- 0.97 |
- 0.971 |
- 0.976 |
- 0.978 |
- 0.97 |
- 0.952 |
- 0.98 |
- 0.951 |
- 0.978 |
- 0.975 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.977 |
- 0.983 |
- 0.983 |
- 0.98 |
- 0.978 |
- 0.964 |
- 0.973 |
- 0.981 |
- 0.972 |
- 0.978 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.984 |
- 1 |
- 0.997 |
- 0.976 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.977 |
- 0.986 |
- 0.977 |
- 0.976 |
- 0.973 |
- 0.978 |
- 0.983 |
- 0.979 |
- 0.973 |
- 0.984 |
- 0.936 |
- 0.984 |
- 0.99 |
- 0.976 |
- 0.974 |
- 0.976 |
- 0.98 |
- 0.972 |
- 0.979 |
- 0.974 |
- 0.973 |
- 0.969 |
- 0.976 |
- 0.966 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.98 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.97 |
- 0.973 |
- 0.975 |
- 0.975 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.926 |
- 0.979 |
- 0.973 |
- 0.981 |
- 0.981 |
- 0.98 |
- 0.951 |
- 0.971 |
- 0.949 |
- |
- 0.9 |
- 0.98 |
-
-
- | Liver |
- 350 |
- F |
- 204 |
- 121214.21 |
- HF |
- BXD39 |
- H1473 |
- 0.979 |
- 0.94 |
- 0.941 |
- 0.981 |
- 0.971 |
- 0.98 |
- 0.974 |
- 0.981 |
- 0.911 |
- 0.974 |
- 0.967 |
- 0.981 |
- 0.968 |
- 0.975 |
- 0.972 |
- 0.975 |
- 0.981 |
- 0.965 |
- 0.981 |
- 0.984 |
- 0.978 |
- 0.981 |
- 0.976 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.976 |
- 0.984 |
- 0.982 |
- 0.978 |
- 0.979 |
- 0.977 |
- 0.943 |
- 0.98 |
- 0.984 |
- 0.98 |
- 0.953 |
- 0.983 |
- 0.988 |
- 0.989 |
- 0.981 |
- 0.979 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.953 |
- 0.965 |
- 0.973 |
- 0.98 |
- 0.977 |
- 0.981 |
- 0.972 |
- 0.981 |
- 0.974 |
- 0.98 |
- 0.978 |
- 0.98 |
- 0.976 |
- 0.984 |
- 0.983 |
- 0.966 |
- 0.958 |
- 0.98 |
- 0.9 |
- 0.97 |
- 0.97 |
- 0.976 |
- 0.977 |
- 0.969 |
- 0.952 |
- 0.98 |
- 0.95 |
- 0.977 |
- 0.974 |
- 0.978 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.977 |
- 0.964 |
- 0.972 |
- 0.98 |
- 0.971 |
- 0.977 |
- 0.98 |
- 0.983 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.983 |
- 0.997 |
- 1 |
- 0.975 |
- 0.984 |
- 0.98 |
- 0.979 |
- 0.981 |
- 0.976 |
- 0.985 |
- 0.977 |
- 0.976 |
- 0.973 |
- 0.977 |
- 0.984 |
- 0.978 |
- 0.973 |
- 0.984 |
- 0.935 |
- 0.984 |
- 0.989 |
- 0.975 |
- 0.973 |
- 0.976 |
- 0.98 |
- 0.972 |
- 0.978 |
- 0.973 |
- 0.972 |
- 0.968 |
- 0.975 |
- 0.966 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.986 |
- 0.985 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.97 |
- 0.972 |
- 0.974 |
- 0.974 |
- 0.98 |
- 0.977 |
- 0.982 |
- 0.925 |
- 0.979 |
- 0.972 |
- 0.98 |
- 0.98 |
- 0.978 |
- 0.95 |
- 0.971 |
- 0.948 |
- |
- 0.9 |
- 0.97 |
-
-
- | Liver |
- 291 |
- F |
- 280 |
- 111314.05 |
- HF |
- BXD40 |
- H1488 |
- 0.988 |
- 0.933 |
- 0.934 |
- 0.986 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.964 |
- 0.896 |
- 0.985 |
- 0.974 |
- 0.985 |
- 0.985 |
- 0.987 |
- 0.974 |
- 0.979 |
- 0.973 |
- 0.968 |
- 0.984 |
- 0.981 |
- 0.976 |
- 0.989 |
- 0.991 |
- 0.991 |
- 0.985 |
- 0.976 |
- 0.976 |
- 0.974 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.985 |
- 0.952 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.938 |
- 0.982 |
- 0.978 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.978 |
- 0.987 |
- 0.985 |
- 0.95 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.978 |
- 0.987 |
- 0.963 |
- 0.98 |
- 0.979 |
- 0.986 |
- 0.984 |
- 0.979 |
- 0.976 |
- 0.985 |
- 0.979 |
- 0.979 |
- 0.967 |
- 0.986 |
- 0.906 |
- 0.984 |
- 0.983 |
- 0.981 |
- 0.986 |
- 0.973 |
- 0.947 |
- 0.982 |
- 0.948 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.979 |
- 0.973 |
- 0.987 |
- 0.991 |
- 0.99 |
- 0.982 |
- 0.985 |
- 0.977 |
- 0.983 |
- 0.987 |
- 0.971 |
- 0.988 |
- 0.989 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.976 |
- 0.975 |
- 1 |
- 0.986 |
- 0.974 |
- 0.983 |
- 0.978 |
- 0.985 |
- 0.98 |
- 0.978 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.978 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.957 |
- 0.97 |
- 0.978 |
- 0.97 |
- 0.988 |
- 0.981 |
- 0.983 |
- 0.985 |
- 0.986 |
- 0.988 |
- 0.986 |
- 0.976 |
- 0.984 |
- 0.972 |
- 0.986 |
- 0.988 |
- 0.984 |
- 0.972 |
- 0.978 |
- 0.985 |
- 0.982 |
- 0.983 |
- 0.986 |
- 0.976 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.986 |
- 0.988 |
- 0.983 |
- 0.984 |
- 0.936 |
- 0.983 |
- 0.982 |
- 0.988 |
- 0.987 |
- 0.982 |
- 0.948 |
- 0.974 |
- 0.951 |
- |
- 0.896 |
- 0.98 |
-
-
- | Liver |
- 358 |
- F |
- 202 |
- 121214.13 |
- HF |
- BXD40 |
- H1593 |
- 0.984 |
- 0.942 |
- 0.945 |
- 0.984 |
- 0.976 |
- 0.983 |
- 0.977 |
- 0.965 |
- 0.904 |
- 0.977 |
- 0.979 |
- 0.983 |
- 0.975 |
- 0.978 |
- 0.974 |
- 0.979 |
- 0.973 |
- 0.965 |
- 0.985 |
- 0.984 |
- 0.974 |
- 0.986 |
- 0.982 |
- 0.983 |
- 0.976 |
- 0.974 |
- 0.975 |
- 0.978 |
- 0.985 |
- 0.98 |
- 0.979 |
- 0.978 |
- 0.959 |
- 0.972 |
- 0.979 |
- 0.98 |
- 0.937 |
- 0.983 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.985 |
- 0.978 |
- 0.944 |
- 0.972 |
- 0.976 |
- 0.983 |
- 0.978 |
- 0.984 |
- 0.96 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.98 |
- 0.978 |
- 0.975 |
- 0.984 |
- 0.979 |
- 0.974 |
- 0.973 |
- 0.981 |
- 0.911 |
- 0.977 |
- 0.975 |
- 0.981 |
- 0.982 |
- 0.963 |
- 0.94 |
- 0.98 |
- 0.939 |
- 0.984 |
- 0.977 |
- 0.973 |
- 0.979 |
- 0.975 |
- 0.984 |
- 0.987 |
- 0.987 |
- 0.981 |
- 0.985 |
- 0.975 |
- 0.98 |
- 0.984 |
- 0.972 |
- 0.98 |
- 0.982 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.984 |
- 0.986 |
- 1 |
- 0.971 |
- 0.98 |
- 0.975 |
- 0.985 |
- 0.986 |
- 0.976 |
- 0.975 |
- 0.981 |
- 0.978 |
- 0.982 |
- 0.986 |
- 0.981 |
- 0.984 |
- 0.95 |
- 0.97 |
- 0.982 |
- 0.969 |
- 0.977 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.976 |
- 0.974 |
- 0.976 |
- 0.969 |
- 0.983 |
- 0.984 |
- 0.983 |
- 0.973 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.984 |
- 1 |
- 0.978 |
- 0.976 |
- 0.981 |
- 0.987 |
- 0.977 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.938 |
- 0.986 |
- 0.983 |
- 0.985 |
- 0.984 |
- 0.974 |
- 0.939 |
- 0.977 |
- 0.941 |
- |
- 0.904 |
- 0.98 |
-
-
- | Liver |
- 240 |
- F |
- 258 |
- 042015.10 |
- HF |
- BXD44 |
- H1825 |
- 0.971 |
- 0.941 |
- 0.94 |
- 0.972 |
- 0.967 |
- 0.971 |
- 0.969 |
- 0.981 |
- 0.919 |
- 0.969 |
- 0.953 |
- 0.981 |
- 0.961 |
- 0.969 |
- 0.972 |
- 0.968 |
- 0.977 |
- 0.973 |
- 0.972 |
- 0.971 |
- 0.966 |
- 0.975 |
- 0.972 |
- 0.979 |
- 0.989 |
- 0.981 |
- 0.981 |
- 0.985 |
- 0.974 |
- 0.972 |
- 0.97 |
- 0.973 |
- 0.928 |
- 0.971 |
- 0.98 |
- 0.981 |
- 0.974 |
- 0.974 |
- 0.983 |
- 0.977 |
- 0.974 |
- 0.964 |
- 0.968 |
- 0.968 |
- 0.979 |
- 0.966 |
- 0.957 |
- 0.965 |
- 0.971 |
- 0.977 |
- 0.974 |
- 0.985 |
- 0.986 |
- 0.964 |
- 0.972 |
- 0.972 |
- 0.985 |
- 0.964 |
- 0.977 |
- 0.976 |
- 0.958 |
- 0.942 |
- 0.981 |
- 0.888 |
- 0.962 |
- 0.96 |
- 0.976 |
- 0.972 |
- 0.983 |
- 0.975 |
- 0.982 |
- 0.973 |
- 0.966 |
- 0.969 |
- 0.976 |
- 0.976 |
- 0.98 |
- 0.967 |
- 0.974 |
- 0.975 |
- 0.972 |
- 0.966 |
- 0.955 |
- 0.961 |
- 0.978 |
- 0.972 |
- 0.975 |
- 0.972 |
- 0.98 |
- 0.973 |
- 0.966 |
- 0.974 |
- 0.976 |
- 0.981 |
- 0.98 |
- 0.974 |
- 0.971 |
- 1 |
- 0.981 |
- 0.997 |
- 0.967 |
- 0.978 |
- 0.976 |
- 0.975 |
- 0.961 |
- 0.967 |
- 0.969 |
- 0.969 |
- 0.964 |
- 0.98 |
- 0.928 |
- 0.976 |
- 0.979 |
- 0.966 |
- 0.974 |
- 0.976 |
- 0.971 |
- 0.962 |
- 0.971 |
- 0.967 |
- 0.97 |
- 0.959 |
- 0.974 |
- 0.967 |
- 0.98 |
- 0.977 |
- 0.973 |
- 0.986 |
- 0.974 |
- 0.981 |
- 0.971 |
- 0.98 |
- 0.971 |
- 0.971 |
- 0.965 |
- 0.961 |
- 0.961 |
- 0.97 |
- 0.978 |
- 0.966 |
- 0.976 |
- 0.915 |
- 0.967 |
- 0.959 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.973 |
- 0.971 |
- |
- 0.888 |
- 0.97 |
-
-
- | Liver |
- 379 |
- F |
- 158 |
- 012615.12 |
- HF |
- BXD44 |
- H1501 |
- 0.978 |
- 0.95 |
- 0.952 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.966 |
- 0.919 |
- 0.98 |
- 0.971 |
- 0.982 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.976 |
- 0.968 |
- 0.984 |
- 0.978 |
- 0.97 |
- 0.978 |
- 0.98 |
- 0.984 |
- 0.983 |
- 0.978 |
- 0.978 |
- 0.976 |
- 0.982 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.956 |
- 0.975 |
- 0.976 |
- 0.982 |
- 0.953 |
- 0.978 |
- 0.979 |
- 0.977 |
- 0.98 |
- 0.976 |
- 0.975 |
- 0.979 |
- 0.978 |
- 0.959 |
- 0.974 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.97 |
- 0.98 |
- 0.978 |
- 0.981 |
- 0.978 |
- 0.978 |
- 0.969 |
- 0.981 |
- 0.978 |
- 0.976 |
- 0.967 |
- 0.981 |
- 0.915 |
- 0.974 |
- 0.978 |
- 0.987 |
- 0.977 |
- 0.975 |
- 0.955 |
- 0.979 |
- 0.958 |
- 0.979 |
- 0.979 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.976 |
- 0.98 |
- 0.974 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.977 |
- 0.981 |
- 0.977 |
- 0.975 |
- 0.975 |
- 0.985 |
- 0.986 |
- 0.98 |
- 0.979 |
- 0.983 |
- 0.98 |
- 0.981 |
- 1 |
- 0.983 |
- 0.98 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.973 |
- 0.977 |
- 0.977 |
- 0.985 |
- 0.957 |
- 0.974 |
- 0.977 |
- 0.973 |
- 0.981 |
- 0.987 |
- 0.979 |
- 0.981 |
- 0.974 |
- 0.981 |
- 0.981 |
- 0.978 |
- 0.978 |
- 0.982 |
- 0.984 |
- 0.98 |
- 0.978 |
- 0.977 |
- 0.978 |
- 0.983 |
- 0.976 |
- 0.985 |
- 0.98 |
- 0.974 |
- 0.977 |
- 0.976 |
- 0.979 |
- 0.981 |
- 0.986 |
- 0.982 |
- 0.981 |
- 0.939 |
- 0.98 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.976 |
- 0.958 |
- 0.975 |
- 0.96 |
- |
- 0.915 |
- 0.98 |
-
-
- | Liver |
- 715 |
- F |
- 144 |
- 102414.12 |
- HF |
- BXD44 |
- H1687 |
- 0.976 |
- 0.939 |
- 0.94 |
- 0.976 |
- 0.97 |
- 0.974 |
- 0.972 |
- 0.978 |
- 0.914 |
- 0.972 |
- 0.958 |
- 0.984 |
- 0.965 |
- 0.973 |
- 0.974 |
- 0.972 |
- 0.976 |
- 0.972 |
- 0.976 |
- 0.975 |
- 0.969 |
- 0.979 |
- 0.976 |
- 0.983 |
- 0.99 |
- 0.981 |
- 0.981 |
- 0.985 |
- 0.977 |
- 0.976 |
- 0.975 |
- 0.976 |
- 0.932 |
- 0.972 |
- 0.983 |
- 0.982 |
- 0.969 |
- 0.977 |
- 0.985 |
- 0.98 |
- 0.976 |
- 0.968 |
- 0.972 |
- 0.973 |
- 0.981 |
- 0.963 |
- 0.962 |
- 0.967 |
- 0.976 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.987 |
- 0.966 |
- 0.976 |
- 0.976 |
- 0.985 |
- 0.967 |
- 0.98 |
- 0.978 |
- 0.963 |
- 0.947 |
- 0.983 |
- 0.89 |
- 0.967 |
- 0.966 |
- 0.978 |
- 0.976 |
- 0.982 |
- 0.972 |
- 0.984 |
- 0.97 |
- 0.97 |
- 0.972 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.973 |
- 0.978 |
- 0.979 |
- 0.974 |
- 0.971 |
- 0.96 |
- 0.965 |
- 0.98 |
- 0.972 |
- 0.979 |
- 0.977 |
- 0.979 |
- 0.976 |
- 0.97 |
- 0.977 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.978 |
- 0.975 |
- 0.997 |
- 0.983 |
- 1 |
- 0.972 |
- 0.981 |
- 0.976 |
- 0.977 |
- 0.965 |
- 0.972 |
- 0.971 |
- 0.974 |
- 0.97 |
- 0.982 |
- 0.932 |
- 0.976 |
- 0.981 |
- 0.966 |
- 0.977 |
- 0.978 |
- 0.975 |
- 0.967 |
- 0.975 |
- 0.972 |
- 0.973 |
- 0.962 |
- 0.977 |
- 0.969 |
- 0.983 |
- 0.98 |
- 0.976 |
- 0.985 |
- 0.976 |
- 0.983 |
- 0.975 |
- 0.982 |
- 0.975 |
- 0.975 |
- 0.969 |
- 0.965 |
- 0.968 |
- 0.974 |
- 0.98 |
- 0.972 |
- 0.98 |
- 0.917 |
- 0.972 |
- 0.965 |
- 0.976 |
- 0.977 |
- 0.975 |
- 0.97 |
- 0.976 |
- 0.967 |
- |
- 0.89 |
- 0.97 |
-
-
- | Liver |
- 503 |
- F |
- 303 |
- 121515.15 |
- HF |
- BXD45 |
- H1940 |
- 0.987 |
- 0.944 |
- 0.946 |
- 0.988 |
- 0.982 |
- 0.989 |
- 0.98 |
- 0.958 |
- 0.905 |
- 0.982 |
- 0.985 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.974 |
- 0.983 |
- 0.97 |
- 0.959 |
- 0.986 |
- 0.985 |
- 0.979 |
- 0.985 |
- 0.981 |
- 0.985 |
- 0.974 |
- 0.977 |
- 0.978 |
- 0.97 |
- 0.989 |
- 0.985 |
- 0.982 |
- 0.983 |
- 0.963 |
- 0.967 |
- 0.976 |
- 0.98 |
- 0.929 |
- 0.98 |
- 0.973 |
- 0.975 |
- 0.983 |
- 0.982 |
- 0.976 |
- 0.985 |
- 0.978 |
- 0.946 |
- 0.977 |
- 0.98 |
- 0.982 |
- 0.978 |
- 0.986 |
- 0.954 |
- 0.977 |
- 0.981 |
- 0.984 |
- 0.985 |
- 0.977 |
- 0.974 |
- 0.986 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.977 |
- 0.918 |
- 0.982 |
- 0.979 |
- 0.978 |
- 0.983 |
- 0.965 |
- 0.935 |
- 0.977 |
- 0.931 |
- 0.989 |
- 0.98 |
- 0.974 |
- 0.977 |
- 0.968 |
- 0.986 |
- 0.99 |
- 0.988 |
- 0.979 |
- 0.986 |
- 0.983 |
- 0.984 |
- 0.983 |
- 0.963 |
- 0.983 |
- 0.986 |
- 0.968 |
- 0.98 |
- 0.98 |
- 0.986 |
- 0.985 |
- 0.977 |
- 0.976 |
- 0.985 |
- 0.985 |
- 0.967 |
- 0.98 |
- 0.972 |
- 1 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.988 |
- 0.982 |
- 0.976 |
- 0.984 |
- 0.982 |
- 0.985 |
- 0.958 |
- 0.961 |
- 0.974 |
- 0.967 |
- 0.978 |
- 0.978 |
- 0.978 |
- 0.986 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.973 |
- 0.98 |
- 0.986 |
- 0.986 |
- 0.968 |
- 0.982 |
- 0.983 |
- 0.982 |
- 0.985 |
- 0.985 |
- 0.972 |
- 0.978 |
- 0.989 |
- 0.986 |
- 0.977 |
- 0.982 |
- 0.986 |
- 0.981 |
- 0.948 |
- 0.981 |
- 0.985 |
- 0.988 |
- 0.984 |
- 0.976 |
- 0.931 |
- 0.969 |
- 0.941 |
- |
- 0.905 |
- 0.98 |
-
-
- | Liver |
- 189 |
- F |
- 263 |
- 042015.24 |
- HF |
- BXD48 |
- H2046 |
- 0.983 |
- 0.937 |
- 0.938 |
- 0.983 |
- 0.977 |
- 0.982 |
- 0.982 |
- 0.972 |
- 0.899 |
- 0.978 |
- 0.973 |
- 0.986 |
- 0.973 |
- 0.976 |
- 0.978 |
- 0.981 |
- 0.971 |
- 0.969 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.984 |
- 0.981 |
- 0.983 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.988 |
- 0.988 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.946 |
- 0.973 |
- 0.979 |
- 0.98 |
- 0.944 |
- 0.987 |
- 0.984 |
- 0.987 |
- 0.986 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.982 |
- 0.953 |
- 0.973 |
- 0.975 |
- 0.986 |
- 0.983 |
- 0.984 |
- 0.968 |
- 0.98 |
- 0.972 |
- 0.981 |
- 0.982 |
- 0.982 |
- 0.978 |
- 0.983 |
- 0.982 |
- 0.971 |
- 0.961 |
- 0.983 |
- 0.899 |
- 0.976 |
- 0.972 |
- 0.977 |
- 0.98 |
- 0.97 |
- 0.955 |
- 0.983 |
- 0.95 |
- 0.984 |
- 0.982 |
- 0.98 |
- 0.982 |
- 0.972 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.986 |
- 0.981 |
- 0.97 |
- 0.978 |
- 0.987 |
- 0.966 |
- 0.982 |
- 0.982 |
- 0.974 |
- 0.987 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.985 |
- 0.98 |
- 0.986 |
- 0.978 |
- 0.979 |
- 0.981 |
- 0.981 |
- 1 |
- 0.976 |
- 0.979 |
- 0.981 |
- 0.981 |
- 0.976 |
- 0.985 |
- 0.975 |
- 0.983 |
- 0.944 |
- 0.975 |
- 0.986 |
- 0.973 |
- 0.98 |
- 0.977 |
- 0.984 |
- 0.977 |
- 0.984 |
- 0.979 |
- 0.977 |
- 0.969 |
- 0.98 |
- 0.969 |
- 0.985 |
- 0.984 |
- 0.985 |
- 0.976 |
- 0.979 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.986 |
- 0.981 |
- 0.976 |
- 0.975 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.981 |
- 0.986 |
- 0.928 |
- 0.983 |
- 0.979 |
- 0.987 |
- 0.985 |
- 0.981 |
- 0.95 |
- 0.975 |
- 0.948 |
- |
- 0.899 |
- 0.98 |
-
-
- | Liver |
- 595 |
- F |
- 238 |
- 042915.13 |
- HF |
- BXD48 |
- H1377 |
- 0.97 |
- 0.96 |
- 0.96 |
- 0.974 |
- 0.978 |
- 0.976 |
- 0.97 |
- 0.97 |
- 0.932 |
- 0.976 |
- 0.97 |
- 0.97 |
- 0.969 |
- 0.972 |
- 0.976 |
- 0.967 |
- 0.978 |
- 0.966 |
- 0.976 |
- 0.973 |
- 0.96 |
- 0.971 |
- 0.969 |
- 0.974 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.978 |
- 0.982 |
- 0.969 |
- 0.965 |
- 0.974 |
- 0.952 |
- 0.969 |
- 0.968 |
- 0.983 |
- 0.962 |
- 0.968 |
- 0.973 |
- 0.968 |
- 0.973 |
- 0.969 |
- 0.968 |
- 0.971 |
- 0.973 |
- 0.96 |
- 0.968 |
- 0.974 |
- 0.966 |
- 0.973 |
- 0.971 |
- 0.966 |
- 0.98 |
- 0.977 |
- 0.971 |
- 0.969 |
- 0.98 |
- 0.959 |
- 0.976 |
- 0.977 |
- 0.966 |
- 0.962 |
- 0.972 |
- 0.916 |
- 0.962 |
- 0.964 |
- 0.984 |
- 0.971 |
- 0.978 |
- 0.963 |
- 0.98 |
- 0.955 |
- 0.971 |
- 0.97 |
- 0.964 |
- 0.977 |
- 0.977 |
- 0.97 |
- 0.977 |
- 0.974 |
- 0.974 |
- 0.975 |
- 0.973 |
- 0.969 |
- 0.979 |
- 0.973 |
- 0.974 |
- 0.971 |
- 0.974 |
- 0.97 |
- 0.968 |
- 0.978 |
- 0.98 |
- 0.977 |
- 0.977 |
- 0.978 |
- 0.976 |
- 0.976 |
- 0.981 |
- 0.976 |
- 0.977 |
- 0.976 |
- 1 |
- 0.978 |
- 0.976 |
- 0.963 |
- 0.97 |
- 0.966 |
- 0.963 |
- 0.983 |
- 0.947 |
- 0.967 |
- 0.968 |
- 0.971 |
- 0.976 |
- 0.984 |
- 0.965 |
- 0.976 |
- 0.97 |
- 0.976 |
- 0.977 |
- 0.975 |
- 0.975 |
- 0.979 |
- 0.977 |
- 0.971 |
- 0.969 |
- 0.978 |
- 0.971 |
- 0.977 |
- 0.967 |
- 0.983 |
- 0.976 |
- 0.961 |
- 0.969 |
- 0.975 |
- 0.97 |
- 0.97 |
- 0.98 |
- 0.966 |
- 0.971 |
- 0.939 |
- 0.968 |
- 0.968 |
- 0.976 |
- 0.969 |
- 0.962 |
- 0.955 |
- 0.97 |
- 0.966 |
- |
- 0.916 |
- 0.97 |
-
-
- | Liver |
- 233 |
- F |
- 239 |
- 051112.04 |
- HF |
- BXD48a |
- H0210 |
- 0.979 |
- 0.941 |
- 0.941 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.968 |
- 0.91 |
- 0.977 |
- 0.97 |
- 0.978 |
- 0.976 |
- 0.976 |
- 0.972 |
- 0.976 |
- 0.971 |
- 0.964 |
- 0.977 |
- 0.976 |
- 0.974 |
- 0.979 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.977 |
- 0.977 |
- 0.978 |
- 0.984 |
- 0.978 |
- 0.978 |
- 0.981 |
- 0.945 |
- 0.972 |
- 0.975 |
- 0.979 |
- 0.95 |
- 0.978 |
- 0.977 |
- 0.973 |
- 0.976 |
- 0.973 |
- 0.973 |
- 0.978 |
- 0.978 |
- 0.96 |
- 0.975 |
- 0.977 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.97 |
- 0.977 |
- 0.976 |
- 0.981 |
- 0.978 |
- 0.977 |
- 0.969 |
- 0.98 |
- 0.975 |
- 0.973 |
- 0.957 |
- 0.98 |
- 0.904 |
- 0.972 |
- 0.973 |
- 0.975 |
- 0.976 |
- 0.971 |
- 0.952 |
- 0.976 |
- 0.953 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.975 |
- 0.971 |
- 0.981 |
- 0.982 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.97 |
- 0.974 |
- 0.979 |
- 0.964 |
- 0.978 |
- 0.98 |
- 0.973 |
- 0.976 |
- 0.97 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.976 |
- 0.98 |
- 0.975 |
- 0.975 |
- 0.98 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.978 |
- 1 |
- 0.982 |
- 0.977 |
- 0.968 |
- 0.974 |
- 0.973 |
- 0.982 |
- 0.951 |
- 0.971 |
- 0.974 |
- 0.97 |
- 0.983 |
- 0.975 |
- 0.977 |
- 0.973 |
- 0.976 |
- 0.977 |
- 0.979 |
- 0.974 |
- 0.977 |
- 0.97 |
- 0.984 |
- 0.98 |
- 0.979 |
- 0.974 |
- 0.977 |
- 0.982 |
- 0.976 |
- 0.982 |
- 0.975 |
- 0.969 |
- 0.977 |
- 0.974 |
- 0.974 |
- 0.982 |
- 0.981 |
- 0.978 |
- 0.981 |
- 0.933 |
- 0.975 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.979 |
- 0.953 |
- 0.967 |
- 0.957 |
- |
- 0.904 |
- 0.97 |
-
-
- | Liver |
- 543 |
- F |
- 287 |
- 062013.06 |
- HF |
- BXD48a |
- H0699 |
- 0.982 |
- 0.943 |
- 0.944 |
- 0.986 |
- 0.985 |
- 0.988 |
- 0.981 |
- 0.956 |
- 0.907 |
- 0.979 |
- 0.984 |
- 0.977 |
- 0.985 |
- 0.979 |
- 0.975 |
- 0.98 |
- 0.965 |
- 0.956 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.969 |
- 0.972 |
- 0.972 |
- 0.969 |
- 0.989 |
- 0.982 |
- 0.981 |
- 0.982 |
- 0.965 |
- 0.966 |
- 0.97 |
- 0.978 |
- 0.928 |
- 0.978 |
- 0.971 |
- 0.971 |
- 0.98 |
- 0.981 |
- 0.97 |
- 0.984 |
- 0.979 |
- 0.949 |
- 0.979 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.983 |
- 0.951 |
- 0.971 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.97 |
- 0.974 |
- 0.981 |
- 0.972 |
- 0.979 |
- 0.971 |
- 0.974 |
- 0.919 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.979 |
- 0.96 |
- 0.931 |
- 0.973 |
- 0.93 |
- 0.987 |
- 0.981 |
- 0.979 |
- 0.972 |
- 0.964 |
- 0.984 |
- 0.987 |
- 0.985 |
- 0.979 |
- 0.984 |
- 0.983 |
- 0.983 |
- 0.979 |
- 0.963 |
- 0.978 |
- 0.984 |
- 0.968 |
- 0.976 |
- 0.975 |
- 0.983 |
- 0.982 |
- 0.973 |
- 0.973 |
- 0.983 |
- 0.981 |
- 0.961 |
- 0.98 |
- 0.965 |
- 0.988 |
- 0.981 |
- 0.976 |
- 0.982 |
- 1 |
- 0.981 |
- 0.969 |
- 0.979 |
- 0.976 |
- 0.981 |
- 0.965 |
- 0.959 |
- 0.97 |
- 0.974 |
- 0.978 |
- 0.976 |
- 0.975 |
- 0.984 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.983 |
- 0.978 |
- 0.972 |
- 0.979 |
- 0.983 |
- 0.983 |
- 0.964 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.966 |
- 0.976 |
- 0.986 |
- 0.982 |
- 0.978 |
- 0.981 |
- 0.985 |
- 0.978 |
- 0.952 |
- 0.98 |
- 0.985 |
- 0.986 |
- 0.984 |
- 0.98 |
- 0.93 |
- 0.963 |
- 0.943 |
- |
- 0.907 |
- 0.97 |
-
-
- | Liver |
- 713 |
- F |
- 143 |
- 010614.07 |
- HF |
- BXD53 |
- H0833 |
- 0.99 |
- 0.915 |
- 0.917 |
- 0.988 |
- 0.978 |
- 0.983 |
- 0.988 |
- 0.963 |
- 0.878 |
- 0.981 |
- 0.97 |
- 0.984 |
- 0.979 |
- 0.982 |
- 0.968 |
- 0.979 |
- 0.969 |
- 0.955 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.987 |
- 0.987 |
- 0.985 |
- 0.977 |
- 0.969 |
- 0.97 |
- 0.971 |
- 0.985 |
- 0.984 |
- 0.997 |
- 0.984 |
- 0.943 |
- 0.976 |
- 0.985 |
- 0.972 |
- 0.927 |
- 0.987 |
- 0.982 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.987 |
- 0.981 |
- 0.943 |
- 0.976 |
- 0.977 |
- 0.985 |
- 0.978 |
- 0.987 |
- 0.96 |
- 0.972 |
- 0.974 |
- 0.988 |
- 0.984 |
- 0.972 |
- 0.981 |
- 0.985 |
- 0.979 |
- 0.975 |
- 0.961 |
- 0.982 |
- 0.894 |
- 0.983 |
- 0.984 |
- 0.97 |
- 0.983 |
- 0.961 |
- 0.934 |
- 0.976 |
- 0.936 |
- 0.989 |
- 0.988 |
- 0.988 |
- 0.979 |
- 0.967 |
- 0.988 |
- 0.987 |
- 0.989 |
- 0.98 |
- 0.982 |
- 0.968 |
- 0.982 |
- 0.979 |
- 0.961 |
- 0.982 |
- 0.988 |
- 0.973 |
- 0.979 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.978 |
- 0.977 |
- 0.982 |
- 0.978 |
- 0.967 |
- 0.977 |
- 0.972 |
- 0.982 |
- 0.981 |
- 0.963 |
- 0.977 |
- 0.981 |
- 1 |
- 0.978 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.947 |
- 0.972 |
- 0.982 |
- 0.968 |
- 0.981 |
- 0.97 |
- 0.986 |
- 0.978 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.969 |
- 0.98 |
- 0.962 |
- 0.983 |
- 0.987 |
- 0.986 |
- 0.965 |
- 0.982 |
- 0.983 |
- 0.987 |
- 0.981 |
- 0.978 |
- 0.982 |
- 0.981 |
- 0.976 |
- 0.981 |
- 0.984 |
- 0.981 |
- 0.988 |
- 0.986 |
- 0.923 |
- 0.985 |
- 0.983 |
- 0.986 |
- 0.988 |
- 0.988 |
- 0.936 |
- 0.963 |
- 0.931 |
- |
- 0.878 |
- 0.97 |
-
-
- | Liver |
- 188 |
- F |
- 128 |
- 111414.03 |
- HF |
- BXD61 |
- H1922 |
- 0.98 |
- 0.922 |
- 0.924 |
- 0.98 |
- 0.967 |
- 0.975 |
- 0.976 |
- 0.97 |
- 0.891 |
- 0.978 |
- 0.968 |
- 0.976 |
- 0.973 |
- 0.978 |
- 0.963 |
- 0.969 |
- 0.978 |
- 0.96 |
- 0.98 |
- 0.98 |
- 0.967 |
- 0.98 |
- 0.977 |
- 0.979 |
- 0.975 |
- 0.971 |
- 0.972 |
- 0.972 |
- 0.981 |
- 0.975 |
- 0.979 |
- 0.974 |
- 0.944 |
- 0.986 |
- 0.987 |
- 0.975 |
- 0.938 |
- 0.98 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.987 |
- 0.982 |
- 0.977 |
- 0.939 |
- 0.97 |
- 0.976 |
- 0.977 |
- 0.969 |
- 0.979 |
- 0.961 |
- 0.978 |
- 0.974 |
- 0.979 |
- 0.975 |
- 0.975 |
- 0.976 |
- 0.983 |
- 0.983 |
- 0.963 |
- 0.959 |
- 0.975 |
- 0.892 |
- 0.977 |
- 0.977 |
- 0.973 |
- 0.982 |
- 0.964 |
- 0.943 |
- 0.977 |
- 0.939 |
- 0.979 |
- 0.976 |
- 0.973 |
- 0.983 |
- 0.978 |
- 0.979 |
- 0.982 |
- 0.983 |
- 0.977 |
- 0.978 |
- 0.963 |
- 0.977 |
- 0.98 |
- 0.968 |
- 0.982 |
- 0.981 |
- 0.979 |
- 0.976 |
- 0.985 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.984 |
- 0.978 |
- 0.982 |
- 0.969 |
- 0.973 |
- 0.971 |
- 0.976 |
- 0.976 |
- 0.97 |
- 0.968 |
- 0.969 |
- 0.978 |
- 1 |
- 0.986 |
- 0.979 |
- 0.979 |
- 0.938 |
- 0.978 |
- 0.983 |
- 0.966 |
- 0.971 |
- 0.973 |
- 0.978 |
- 0.973 |
- 0.981 |
- 0.979 |
- 0.972 |
- 0.964 |
- 0.97 |
- 0.958 |
- 0.978 |
- 0.98 |
- 0.977 |
- 0.974 |
- 0.98 |
- 0.98 |
- 0.984 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.97 |
- 0.968 |
- 0.975 |
- 0.972 |
- 0.981 |
- 0.975 |
- 0.979 |
- 0.92 |
- 0.981 |
- 0.973 |
- 0.977 |
- 0.976 |
- 0.972 |
- 0.939 |
- 0.97 |
- 0.934 |
- |
- 0.891 |
- 0.97 |
-
-
- | Liver |
- 188 |
- F |
- 323 |
- 111414.04 |
- HF |
- BXD61 |
- H1722 |
- 0.988 |
- 0.922 |
- 0.924 |
- 0.986 |
- 0.974 |
- 0.983 |
- 0.984 |
- 0.96 |
- 0.882 |
- 0.981 |
- 0.976 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.967 |
- 0.98 |
- 0.969 |
- 0.964 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.987 |
- 0.983 |
- 0.986 |
- 0.977 |
- 0.971 |
- 0.972 |
- 0.974 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.95 |
- 0.978 |
- 0.985 |
- 0.976 |
- 0.925 |
- 0.986 |
- 0.978 |
- 0.986 |
- 0.989 |
- 0.985 |
- 0.984 |
- 0.989 |
- 0.982 |
- 0.937 |
- 0.976 |
- 0.978 |
- 0.986 |
- 0.976 |
- 0.986 |
- 0.956 |
- 0.976 |
- 0.972 |
- 0.983 |
- 0.982 |
- 0.977 |
- 0.98 |
- 0.986 |
- 0.98 |
- 0.97 |
- 0.965 |
- 0.983 |
- 0.896 |
- 0.984 |
- 0.979 |
- 0.976 |
- 0.986 |
- 0.962 |
- 0.938 |
- 0.979 |
- 0.936 |
- 0.987 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.968 |
- 0.988 |
- 0.99 |
- 0.99 |
- 0.983 |
- 0.985 |
- 0.973 |
- 0.984 |
- 0.987 |
- 0.965 |
- 0.987 |
- 0.987 |
- 0.972 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.986 |
- 0.969 |
- 0.977 |
- 0.974 |
- 0.984 |
- 0.985 |
- 0.966 |
- 0.974 |
- 0.979 |
- 0.984 |
- 0.986 |
- 1 |
- 0.988 |
- 0.981 |
- 0.952 |
- 0.969 |
- 0.984 |
- 0.966 |
- 0.978 |
- 0.976 |
- 0.987 |
- 0.982 |
- 0.989 |
- 0.986 |
- 0.98 |
- 0.97 |
- 0.98 |
- 0.962 |
- 0.981 |
- 0.986 |
- 0.984 |
- 0.969 |
- 0.978 |
- 0.982 |
- 0.986 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.979 |
- 0.977 |
- 0.986 |
- 0.98 |
- 0.982 |
- 0.986 |
- 0.984 |
- 0.929 |
- 0.988 |
- 0.985 |
- 0.988 |
- 0.986 |
- 0.979 |
- 0.936 |
- 0.976 |
- 0.933 |
- |
- 0.882 |
- 0.98 |
-
-
- | Liver |
- 524 |
- F |
- 316 |
- 121515.25 |
- HF |
- BXD61 |
- H1843 |
- 0.987 |
- 0.92 |
- 0.924 |
- 0.983 |
- 0.972 |
- 0.979 |
- 0.978 |
- 0.95 |
- 0.88 |
- 0.976 |
- 0.972 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.963 |
- 0.978 |
- 0.966 |
- 0.952 |
- 0.985 |
- 0.981 |
- 0.972 |
- 0.984 |
- 0.981 |
- 0.984 |
- 0.975 |
- 0.96 |
- 0.961 |
- 0.964 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.978 |
- 0.951 |
- 0.968 |
- 0.982 |
- 0.97 |
- 0.919 |
- 0.978 |
- 0.974 |
- 0.98 |
- 0.98 |
- 0.976 |
- 0.979 |
- 0.98 |
- 0.972 |
- 0.929 |
- 0.97 |
- 0.973 |
- 0.981 |
- 0.971 |
- 0.982 |
- 0.95 |
- 0.969 |
- 0.972 |
- 0.985 |
- 0.98 |
- 0.969 |
- 0.971 |
- 0.985 |
- 0.972 |
- 0.975 |
- 0.965 |
- 0.982 |
- 0.9 |
- 0.983 |
- 0.983 |
- 0.972 |
- 0.985 |
- 0.958 |
- 0.925 |
- 0.97 |
- 0.931 |
- 0.982 |
- 0.978 |
- 0.974 |
- 0.972 |
- 0.963 |
- 0.985 |
- 0.988 |
- 0.989 |
- 0.972 |
- 0.982 |
- 0.972 |
- 0.978 |
- 0.974 |
- 0.963 |
- 0.979 |
- 0.987 |
- 0.968 |
- 0.975 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.973 |
- 0.973 |
- 0.984 |
- 0.981 |
- 0.964 |
- 0.977 |
- 0.97 |
- 0.982 |
- 0.975 |
- 0.963 |
- 0.973 |
- 0.976 |
- 0.984 |
- 0.979 |
- 0.988 |
- 1 |
- 0.981 |
- 0.956 |
- 0.962 |
- 0.976 |
- 0.955 |
- 0.978 |
- 0.972 |
- 0.984 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.978 |
- 0.969 |
- 0.977 |
- 0.96 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.96 |
- 0.979 |
- 0.982 |
- 0.986 |
- 0.981 |
- 0.981 |
- 0.977 |
- 0.98 |
- 0.976 |
- 0.987 |
- 0.98 |
- 0.978 |
- 0.988 |
- 0.984 |
- 0.932 |
- 0.983 |
- 0.985 |
- 0.982 |
- 0.984 |
- 0.975 |
- 0.931 |
- 0.969 |
- 0.924 |
- |
- 0.88 |
- 0.97 |
-
-
- | Liver |
- 488 |
- F |
- 242 |
- 042915.19 |
- HF |
- BXD62 |
- H1434 |
- 0.984 |
- 0.948 |
- 0.949 |
- 0.986 |
- 0.98 |
- 0.985 |
- 0.98 |
- 0.972 |
- 0.916 |
- 0.981 |
- 0.977 |
- 0.984 |
- 0.976 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.978 |
- 0.967 |
- 0.986 |
- 0.983 |
- 0.977 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.986 |
- 0.983 |
- 0.981 |
- 0.983 |
- 0.957 |
- 0.973 |
- 0.98 |
- 0.986 |
- 0.955 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.982 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.979 |
- 0.956 |
- 0.975 |
- 0.98 |
- 0.98 |
- 0.979 |
- 0.984 |
- 0.967 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.975 |
- 0.987 |
- 0.983 |
- 0.975 |
- 0.969 |
- 0.982 |
- 0.915 |
- 0.974 |
- 0.975 |
- 0.981 |
- 0.982 |
- 0.975 |
- 0.953 |
- 0.981 |
- 0.949 |
- 0.984 |
- 0.98 |
- 0.977 |
- 0.983 |
- 0.976 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.981 |
- 0.984 |
- 0.978 |
- 0.978 |
- 0.983 |
- 0.973 |
- 0.981 |
- 0.984 |
- 0.978 |
- 0.983 |
- 0.979 |
- 0.987 |
- 0.988 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.981 |
- 0.979 |
- 0.981 |
- 0.981 |
- 1 |
- 0.956 |
- 0.973 |
- 0.982 |
- 0.974 |
- 0.98 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.98 |
- 0.984 |
- 0.975 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.977 |
- 0.985 |
- 0.986 |
- 0.983 |
- 1 |
- 0.984 |
- 0.977 |
- 0.977 |
- 0.982 |
- 0.983 |
- 0.978 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.94 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.986 |
- 0.978 |
- 0.949 |
- 0.974 |
- 0.955 |
- |
- 0.915 |
- 0.98 |
-
-
- | Liver |
- 548 |
- F |
- 302 |
- 082214.10 |
- HF |
- BXD62 |
- H1315 |
- 0.951 |
- 0.932 |
- 0.934 |
- 0.952 |
- 0.96 |
- 0.959 |
- 0.951 |
- 0.914 |
- 0.896 |
- 0.953 |
- 0.96 |
- 0.947 |
- 0.964 |
- 0.956 |
- 0.948 |
- 0.952 |
- 0.928 |
- 0.926 |
- 0.956 |
- 0.952 |
- 0.947 |
- 0.949 |
- 0.953 |
- 0.953 |
- 0.938 |
- 0.938 |
- 0.939 |
- 0.929 |
- 0.957 |
- 0.954 |
- 0.947 |
- 0.95 |
- 0.97 |
- 0.932 |
- 0.932 |
- 0.948 |
- 0.902 |
- 0.947 |
- 0.934 |
- 0.938 |
- 0.947 |
- 0.949 |
- 0.939 |
- 0.952 |
- 0.942 |
- 0.921 |
- 0.959 |
- 0.964 |
- 0.947 |
- 0.948 |
- 0.95 |
- 0.917 |
- 0.939 |
- 0.961 |
- 0.953 |
- 0.954 |
- 0.937 |
- 0.936 |
- 0.949 |
- 0.94 |
- 0.963 |
- 0.956 |
- 0.942 |
- 0.926 |
- 0.952 |
- 0.954 |
- 0.952 |
- 0.956 |
- 0.934 |
- 0.898 |
- 0.946 |
- 0.903 |
- 0.959 |
- 0.951 |
- 0.942 |
- 0.94 |
- 0.931 |
- 0.957 |
- 0.959 |
- 0.956 |
- 0.95 |
- 0.958 |
- 0.968 |
- 0.954 |
- 0.945 |
- 0.944 |
- 0.95 |
- 0.955 |
- 0.933 |
- 0.943 |
- 0.946 |
- 0.956 |
- 0.955 |
- 0.936 |
- 0.935 |
- 0.957 |
- 0.95 |
- 0.928 |
- 0.957 |
- 0.932 |
- 0.958 |
- 0.944 |
- 0.947 |
- 0.951 |
- 0.965 |
- 0.947 |
- 0.938 |
- 0.952 |
- 0.956 |
- 0.956 |
- 1 |
- 0.924 |
- 0.936 |
- 0.947 |
- 0.952 |
- 0.952 |
- 0.944 |
- 0.964 |
- 0.948 |
- 0.958 |
- 0.958 |
- 0.969 |
- 0.952 |
- 0.958 |
- 0.952 |
- 0.953 |
- 0.951 |
- 0.928 |
- 0.941 |
- 0.95 |
- 0.946 |
- 0.956 |
- 0.95 |
- 0.932 |
- 0.953 |
- 0.958 |
- 0.961 |
- 0.951 |
- 0.95 |
- 0.963 |
- 0.948 |
- 0.954 |
- 0.953 |
- 0.969 |
- 0.957 |
- 0.955 |
- 0.944 |
- 0.903 |
- 0.935 |
- 0.913 |
- |
- 0.896 |
- 0.95 |
-
-
- | Liver |
- 186 |
- F |
- 125 |
- 111414.09 |
- HF |
- BXD63 |
- H1715 |
- 0.972 |
- 0.922 |
- 0.922 |
- 0.969 |
- 0.965 |
- 0.966 |
- 0.974 |
- 0.979 |
- 0.895 |
- 0.97 |
- 0.95 |
- 0.976 |
- 0.959 |
- 0.968 |
- 0.961 |
- 0.963 |
- 0.979 |
- 0.961 |
- 0.969 |
- 0.968 |
- 0.96 |
- 0.973 |
- 0.974 |
- 0.973 |
- 0.977 |
- 0.975 |
- 0.975 |
- 0.976 |
- 0.971 |
- 0.97 |
- 0.975 |
- 0.967 |
- 0.922 |
- 0.986 |
- 0.98 |
- 0.972 |
- 0.955 |
- 0.983 |
- 0.989 |
- 0.986 |
- 0.972 |
- 0.971 |
- 0.98 |
- 0.974 |
- 0.975 |
- 0.952 |
- 0.964 |
- 0.97 |
- 0.974 |
- 0.971 |
- 0.972 |
- 0.976 |
- 0.976 |
- 0.967 |
- 0.974 |
- 0.97 |
- 0.974 |
- 0.967 |
- 0.975 |
- 0.984 |
- 0.957 |
- 0.94 |
- 0.976 |
- 0.88 |
- 0.964 |
- 0.967 |
- 0.968 |
- 0.969 |
- 0.969 |
- 0.957 |
- 0.976 |
- 0.958 |
- 0.967 |
- 0.974 |
- 0.977 |
- 0.984 |
- 0.982 |
- 0.972 |
- 0.972 |
- 0.975 |
- 0.975 |
- 0.964 |
- 0.947 |
- 0.962 |
- 0.973 |
- 0.964 |
- 0.973 |
- 0.972 |
- 0.981 |
- 0.97 |
- 0.968 |
- 0.971 |
- 0.972 |
- 0.984 |
- 0.984 |
- 0.97 |
- 0.97 |
- 0.976 |
- 0.974 |
- 0.976 |
- 0.961 |
- 0.975 |
- 0.967 |
- 0.971 |
- 0.959 |
- 0.972 |
- 0.978 |
- 0.969 |
- 0.962 |
- 0.973 |
- 0.924 |
- 1 |
- 0.988 |
- 0.973 |
- 0.973 |
- 0.968 |
- 0.978 |
- 0.958 |
- 0.969 |
- 0.968 |
- 0.967 |
- 0.955 |
- 0.967 |
- 0.956 |
- 0.98 |
- 0.975 |
- 0.97 |
- 0.979 |
- 0.974 |
- 0.979 |
- 0.973 |
- 0.973 |
- 0.97 |
- 0.98 |
- 0.967 |
- 0.954 |
- 0.961 |
- 0.975 |
- 0.977 |
- 0.967 |
- 0.978 |
- 0.901 |
- 0.972 |
- 0.962 |
- 0.971 |
- 0.971 |
- 0.976 |
- 0.958 |
- 0.964 |
- 0.946 |
- |
- 0.88 |
- 0.97 |
-
-
- | Liver |
- 344 |
- F |
- 123 |
- 121214.26 |
- HF |
- BXD63 |
- H1416 |
- 0.982 |
- 0.925 |
- 0.926 |
- 0.98 |
- 0.967 |
- 0.977 |
- 0.979 |
- 0.977 |
- 0.892 |
- 0.975 |
- 0.963 |
- 0.983 |
- 0.967 |
- 0.976 |
- 0.967 |
- 0.975 |
- 0.977 |
- 0.967 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.983 |
- 0.979 |
- 0.981 |
- 0.981 |
- 0.973 |
- 0.974 |
- 0.982 |
- 0.98 |
- 0.979 |
- 0.983 |
- 0.979 |
- 0.935 |
- 0.98 |
- 0.986 |
- 0.976 |
- 0.944 |
- 0.99 |
- 0.991 |
- 0.996 |
- 0.984 |
- 0.979 |
- 0.982 |
- 0.981 |
- 0.981 |
- 0.946 |
- 0.967 |
- 0.974 |
- 0.982 |
- 0.976 |
- 0.983 |
- 0.97 |
- 0.978 |
- 0.968 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.963 |
- 0.951 |
- 0.984 |
- 0.889 |
- 0.973 |
- 0.972 |
- 0.973 |
- 0.98 |
- 0.968 |
- 0.951 |
- 0.979 |
- 0.949 |
- 0.979 |
- 0.979 |
- 0.982 |
- 0.984 |
- 0.978 |
- 0.98 |
- 0.983 |
- 0.985 |
- 0.981 |
- 0.976 |
- 0.959 |
- 0.974 |
- 0.982 |
- 0.968 |
- 0.98 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.99 |
- 0.989 |
- 0.978 |
- 0.982 |
- 0.979 |
- 0.977 |
- 0.981 |
- 0.974 |
- 0.986 |
- 0.968 |
- 0.974 |
- 0.97 |
- 0.982 |
- 0.983 |
- 0.984 |
- 0.976 |
- 0.982 |
- 0.936 |
- 0.988 |
- 1 |
- 0.976 |
- 0.974 |
- 0.973 |
- 0.985 |
- 0.971 |
- 0.982 |
- 0.975 |
- 0.976 |
- 0.963 |
- 0.978 |
- 0.961 |
- 0.985 |
- 0.985 |
- 0.982 |
- 0.977 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.982 |
- 0.982 |
- 0.986 |
- 0.973 |
- 0.968 |
- 0.975 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.984 |
- 0.917 |
- 0.981 |
- 0.975 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.949 |
- 0.972 |
- 0.943 |
- |
- 0.889 |
- 0.97 |
-
-
- | Liver |
- 752 |
- F |
- 135 |
- 102616.17 |
- HF |
- BXD63 |
- H2091 |
- 0.964 |
- 0.943 |
- 0.942 |
- 0.969 |
- 0.971 |
- 0.975 |
- 0.969 |
- 0.972 |
- 0.922 |
- 0.965 |
- 0.966 |
- 0.97 |
- 0.964 |
- 0.96 |
- 0.972 |
- 0.968 |
- 0.969 |
- 0.967 |
- 0.97 |
- 0.968 |
- 0.971 |
- 0.966 |
- 0.968 |
- 0.968 |
- 0.966 |
- 0.972 |
- 0.972 |
- 0.971 |
- 0.972 |
- 0.97 |
- 0.97 |
- 0.969 |
- 0.947 |
- 0.97 |
- 0.966 |
- 0.977 |
- 0.949 |
- 0.975 |
- 0.976 |
- 0.973 |
- 0.97 |
- 0.97 |
- 0.963 |
- 0.972 |
- 0.973 |
- 0.961 |
- 0.965 |
- 0.973 |
- 0.969 |
- 0.97 |
- 0.971 |
- 0.963 |
- 0.971 |
- 0.97 |
- 0.97 |
- 0.97 |
- 0.969 |
- 0.968 |
- 0.969 |
- 0.972 |
- 0.963 |
- 0.95 |
- 0.967 |
- 0.905 |
- 0.958 |
- 0.961 |
- 0.971 |
- 0.966 |
- 0.964 |
- 0.946 |
- 0.973 |
- 0.945 |
- 0.972 |
- 0.969 |
- 0.975 |
- 0.972 |
- 0.97 |
- 0.968 |
- 0.974 |
- 0.973 |
- 0.972 |
- 0.967 |
- 0.966 |
- 0.966 |
- 0.971 |
- 0.965 |
- 0.966 |
- 0.968 |
- 0.973 |
- 0.97 |
- 0.966 |
- 0.971 |
- 0.974 |
- 0.976 |
- 0.975 |
- 0.97 |
- 0.969 |
- 0.966 |
- 0.973 |
- 0.966 |
- 0.967 |
- 0.973 |
- 0.971 |
- 0.97 |
- 0.974 |
- 0.968 |
- 0.966 |
- 0.966 |
- 0.955 |
- 0.974 |
- 0.947 |
- 0.973 |
- 0.976 |
- 1 |
- 0.966 |
- 0.971 |
- 0.964 |
- 0.967 |
- 0.968 |
- 0.969 |
- 0.967 |
- 0.97 |
- 0.968 |
- 0.969 |
- 0.974 |
- 0.972 |
- 0.971 |
- 0.971 |
- 0.971 |
- 0.974 |
- 0.971 |
- 0.974 |
- 0.969 |
- 0.967 |
- 0.962 |
- 0.971 |
- 0.963 |
- 0.968 |
- 0.973 |
- 0.968 |
- 0.97 |
- 0.936 |
- 0.968 |
- 0.967 |
- 0.973 |
- 0.971 |
- 0.976 |
- 0.945 |
- 0.961 |
- 0.959 |
- |
- 0.905 |
- 0.97 |
-
-
- | Liver |
- 230 |
- F |
- 265 |
- 051012.01 |
- HF |
- BXD65 |
- H0458 |
- 0.986 |
- 0.927 |
- 0.929 |
- 0.981 |
- 0.987 |
- 0.979 |
- 0.988 |
- 0.962 |
- 0.889 |
- 0.983 |
- 0.967 |
- 0.982 |
- 0.977 |
- 0.982 |
- 0.974 |
- 0.975 |
- 0.967 |
- 0.962 |
- 0.976 |
- 0.975 |
- 0.971 |
- 0.984 |
- 0.989 |
- 0.988 |
- 0.981 |
- 0.973 |
- 0.974 |
- 0.973 |
- 0.981 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.941 |
- 0.976 |
- 0.978 |
- 0.975 |
- 0.944 |
- 0.982 |
- 0.978 |
- 0.976 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.98 |
- 0.953 |
- 0.982 |
- 0.977 |
- 0.982 |
- 0.983 |
- 0.98 |
- 0.967 |
- 0.976 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.976 |
- 0.97 |
- 0.98 |
- 0.977 |
- 0.98 |
- 0.961 |
- 0.982 |
- 0.895 |
- 0.978 |
- 0.98 |
- 0.976 |
- 0.979 |
- 0.97 |
- 0.949 |
- 0.981 |
- 0.953 |
- 0.98 |
- 0.988 |
- 0.982 |
- 0.977 |
- 0.971 |
- 0.988 |
- 0.983 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.973 |
- 0.975 |
- 0.983 |
- 0.962 |
- 0.984 |
- 0.985 |
- 0.97 |
- 0.981 |
- 0.972 |
- 0.977 |
- 0.977 |
- 0.974 |
- 0.973 |
- 0.988 |
- 0.977 |
- 0.974 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.978 |
- 0.981 |
- 0.971 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.952 |
- 0.973 |
- 0.974 |
- 0.966 |
- 1 |
- 0.976 |
- 0.986 |
- 0.981 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.973 |
- 0.983 |
- 0.971 |
- 0.987 |
- 0.984 |
- 0.98 |
- 0.971 |
- 0.975 |
- 0.984 |
- 0.977 |
- 0.98 |
- 0.977 |
- 0.975 |
- 0.988 |
- 0.973 |
- 0.979 |
- 0.991 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.923 |
- 0.981 |
- 0.978 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.953 |
- 0.969 |
- 0.949 |
- |
- 0.889 |
- 0.97 |
-
-
- | Liver |
- 541 |
- F |
- 212 |
- 121615.06 |
- HF |
- BXD65 |
- H1784 |
- 0.972 |
- 0.955 |
- 0.956 |
- 0.975 |
- 0.972 |
- 0.977 |
- 0.97 |
- 0.968 |
- 0.925 |
- 0.975 |
- 0.97 |
- 0.976 |
- 0.974 |
- 0.973 |
- 0.975 |
- 0.969 |
- 0.977 |
- 0.973 |
- 0.982 |
- 0.975 |
- 0.964 |
- 0.972 |
- 0.974 |
- 0.976 |
- 0.978 |
- 0.979 |
- 0.979 |
- 0.977 |
- 0.98 |
- 0.97 |
- 0.973 |
- 0.97 |
- 0.958 |
- 0.971 |
- 0.974 |
- 0.983 |
- 0.952 |
- 0.972 |
- 0.975 |
- 0.973 |
- 0.981 |
- 0.977 |
- 0.974 |
- 0.978 |
- 0.978 |
- 0.959 |
- 0.964 |
- 0.973 |
- 0.971 |
- 0.971 |
- 0.976 |
- 0.968 |
- 0.982 |
- 0.972 |
- 0.974 |
- 0.97 |
- 0.98 |
- 0.965 |
- 0.978 |
- 0.974 |
- 0.965 |
- 0.967 |
- 0.979 |
- 0.917 |
- 0.971 |
- 0.971 |
- 1 |
- 0.976 |
- 0.975 |
- 0.959 |
- 0.978 |
- 0.957 |
- 0.977 |
- 0.97 |
- 0.972 |
- 0.974 |
- 0.976 |
- 0.973 |
- 0.983 |
- 0.982 |
- 0.97 |
- 0.976 |
- 0.969 |
- 0.975 |
- 0.98 |
- 0.985 |
- 0.976 |
- 0.976 |
- 0.977 |
- 0.969 |
- 0.973 |
- 0.983 |
- 0.984 |
- 0.976 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.976 |
- 0.987 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.984 |
- 0.975 |
- 0.976 |
- 0.97 |
- 0.973 |
- 0.976 |
- 0.972 |
- 0.981 |
- 0.952 |
- 0.968 |
- 0.973 |
- 0.971 |
- 0.976 |
- 1 |
- 0.975 |
- 0.983 |
- 0.975 |
- 0.978 |
- 0.974 |
- 0.971 |
- 0.971 |
- 0.98 |
- 0.979 |
- 0.976 |
- 0.972 |
- 0.978 |
- 0.973 |
- 0.98 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.966 |
- 0.97 |
- 0.975 |
- 0.974 |
- 0.973 |
- 0.987 |
- 0.974 |
- 0.974 |
- 0.941 |
- 0.973 |
- 0.975 |
- 0.978 |
- 0.974 |
- 0.968 |
- 0.957 |
- 0.979 |
- 0.963 |
- |
- 0.917 |
- 0.97 |
-
-
- | Liver |
- 174 |
- F |
- 315 |
- 102414.18 |
- HF |
- BXD65b |
- H1713 |
- 0.987 |
- 0.92 |
- 0.922 |
- 0.982 |
- 0.974 |
- 0.978 |
- 0.985 |
- 0.964 |
- 0.88 |
- 0.98 |
- 0.968 |
- 0.985 |
- 0.974 |
- 0.98 |
- 0.964 |
- 0.978 |
- 0.97 |
- 0.962 |
- 0.981 |
- 0.977 |
- 0.974 |
- 0.986 |
- 0.984 |
- 0.984 |
- 0.977 |
- 0.969 |
- 0.97 |
- 0.975 |
- 0.98 |
- 0.981 |
- 0.987 |
- 0.98 |
- 0.938 |
- 0.979 |
- 0.984 |
- 0.973 |
- 0.931 |
- 0.986 |
- 0.984 |
- 0.987 |
- 0.986 |
- 0.982 |
- 0.987 |
- 0.987 |
- 0.978 |
- 0.94 |
- 0.973 |
- 0.973 |
- 0.987 |
- 0.977 |
- 0.982 |
- 0.963 |
- 0.972 |
- 0.97 |
- 0.986 |
- 0.981 |
- 0.973 |
- 0.977 |
- 0.984 |
- 0.98 |
- 0.971 |
- 0.959 |
- 0.985 |
- 0.889 |
- 0.981 |
- 0.98 |
- 0.975 |
- 0.979 |
- 0.962 |
- 0.941 |
- 0.975 |
- 0.946 |
- 0.981 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.969 |
- 0.988 |
- 0.985 |
- 0.989 |
- 0.979 |
- 0.981 |
- 0.967 |
- 0.978 |
- 0.981 |
- 0.964 |
- 0.981 |
- 0.985 |
- 0.973 |
- 0.982 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.971 |
- 0.979 |
- 0.975 |
- 0.978 |
- 0.984 |
- 0.965 |
- 0.977 |
- 0.975 |
- 0.986 |
- 0.978 |
- 0.987 |
- 0.984 |
- 0.98 |
- 0.944 |
- 0.978 |
- 0.985 |
- 0.964 |
- 0.986 |
- 0.975 |
- 1 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.978 |
- 0.965 |
- 0.979 |
- 0.961 |
- 0.987 |
- 0.986 |
- 0.983 |
- 0.969 |
- 0.982 |
- 0.984 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.97 |
- 0.982 |
- 0.987 |
- 0.983 |
- 0.987 |
- 0.989 |
- 0.919 |
- 0.985 |
- 0.983 |
- 0.984 |
- 0.988 |
- 0.983 |
- 0.946 |
- 0.974 |
- 0.933 |
- |
- 0.88 |
- 0.97 |
-
-
- | Liver |
- 527 |
- F |
- 321 |
- 121615.11 |
- HF |
- BXD65b |
- H1790 |
- 0.984 |
- 0.935 |
- 0.938 |
- 0.983 |
- 0.98 |
- 0.984 |
- 0.981 |
- 0.95 |
- 0.895 |
- 0.981 |
- 0.978 |
- 0.976 |
- 0.979 |
- 0.981 |
- 0.973 |
- 0.975 |
- 0.962 |
- 0.957 |
- 0.984 |
- 0.979 |
- 0.973 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.97 |
- 0.966 |
- 0.966 |
- 0.963 |
- 0.984 |
- 0.98 |
- 0.978 |
- 0.979 |
- 0.965 |
- 0.965 |
- 0.97 |
- 0.972 |
- 0.923 |
- 0.976 |
- 0.968 |
- 0.973 |
- 0.983 |
- 0.984 |
- 0.974 |
- 0.984 |
- 0.974 |
- 0.939 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.974 |
- 0.98 |
- 0.947 |
- 0.968 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.972 |
- 0.972 |
- 0.98 |
- 0.973 |
- 0.978 |
- 0.98 |
- 0.972 |
- 0.92 |
- 0.978 |
- 0.978 |
- 0.983 |
- 0.98 |
- 0.959 |
- 0.931 |
- 0.974 |
- 0.926 |
- 0.985 |
- 0.981 |
- 0.97 |
- 0.973 |
- 0.961 |
- 0.986 |
- 0.985 |
- 0.985 |
- 0.979 |
- 0.989 |
- 0.984 |
- 0.981 |
- 0.981 |
- 0.969 |
- 0.98 |
- 0.983 |
- 0.964 |
- 0.977 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.972 |
- 0.972 |
- 0.985 |
- 0.983 |
- 0.962 |
- 0.981 |
- 0.967 |
- 0.986 |
- 0.977 |
- 0.976 |
- 0.973 |
- 0.984 |
- 0.978 |
- 0.973 |
- 0.982 |
- 0.98 |
- 0.982 |
- 0.964 |
- 0.958 |
- 0.971 |
- 0.967 |
- 0.981 |
- 0.983 |
- 0.978 |
- 1 |
- 0.98 |
- 0.986 |
- 0.981 |
- 0.981 |
- 0.98 |
- 0.976 |
- 0.976 |
- 0.981 |
- 0.979 |
- 0.959 |
- 0.975 |
- 0.976 |
- 0.978 |
- 0.982 |
- 0.983 |
- 0.969 |
- 0.978 |
- 0.984 |
- 0.986 |
- 0.978 |
- 0.98 |
- 0.984 |
- 0.976 |
- 0.944 |
- 0.982 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.973 |
- 0.926 |
- 0.968 |
- 0.935 |
- |
- 0.895 |
- 0.97 |
-
-
- | Liver |
- 184 |
- F |
- 262 |
- 042415.05 |
- HF |
- BXD66 |
- H2124 |
- 0.986 |
- 0.923 |
- 0.923 |
- 0.985 |
- 0.975 |
- 0.985 |
- 0.983 |
- 0.966 |
- 0.885 |
- 0.983 |
- 0.973 |
- 0.984 |
- 0.978 |
- 0.981 |
- 0.969 |
- 0.981 |
- 0.968 |
- 0.97 |
- 0.98 |
- 0.981 |
- 0.984 |
- 0.988 |
- 0.984 |
- 0.987 |
- 0.98 |
- 0.974 |
- 0.974 |
- 0.976 |
- 0.984 |
- 0.985 |
- 0.982 |
- 0.987 |
- 0.946 |
- 0.974 |
- 0.982 |
- 0.976 |
- 0.932 |
- 0.984 |
- 0.976 |
- 0.981 |
- 0.988 |
- 0.983 |
- 0.978 |
- 0.988 |
- 0.989 |
- 0.948 |
- 0.973 |
- 0.978 |
- 0.981 |
- 0.975 |
- 0.987 |
- 0.958 |
- 0.977 |
- 0.973 |
- 0.981 |
- 0.985 |
- 0.977 |
- 0.981 |
- 0.985 |
- 0.979 |
- 0.969 |
- 0.961 |
- 0.982 |
- 0.894 |
- 0.981 |
- 0.974 |
- 0.975 |
- 0.985 |
- 0.965 |
- 0.941 |
- 0.98 |
- 0.938 |
- 0.985 |
- 0.983 |
- 0.981 |
- 0.979 |
- 0.969 |
- 0.984 |
- 0.988 |
- 0.988 |
- 0.985 |
- 0.984 |
- 0.972 |
- 0.985 |
- 0.99 |
- 0.964 |
- 0.986 |
- 0.987 |
- 0.974 |
- 0.988 |
- 0.983 |
- 0.981 |
- 0.981 |
- 0.979 |
- 0.978 |
- 0.986 |
- 0.983 |
- 0.971 |
- 0.974 |
- 0.975 |
- 0.983 |
- 0.984 |
- 0.97 |
- 0.976 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.989 |
- 0.978 |
- 0.98 |
- 0.948 |
- 0.969 |
- 0.982 |
- 0.968 |
- 0.979 |
- 0.975 |
- 0.981 |
- 0.98 |
- 1 |
- 0.99 |
- 0.98 |
- 0.971 |
- 0.982 |
- 0.964 |
- 0.98 |
- 0.987 |
- 0.985 |
- 0.969 |
- 0.978 |
- 0.983 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.977 |
- 0.977 |
- 0.977 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.979 |
- 0.982 |
- 0.928 |
- 0.984 |
- 0.979 |
- 0.989 |
- 0.985 |
- 0.982 |
- 0.938 |
- 0.973 |
- 0.943 |
- |
- 0.885 |
- 0.98 |
-
-
- | Liver |
- 367 |
- F |
- 122 |
- 121214.04 |
- HF |
- BXD66 |
- H1560 |
- 0.986 |
- 0.927 |
- 0.93 |
- 0.983 |
- 0.984 |
- 0.983 |
- 0.988 |
- 0.958 |
- 0.889 |
- 0.987 |
- 0.975 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.971 |
- 0.976 |
- 0.966 |
- 0.964 |
- 0.981 |
- 0.979 |
- 0.975 |
- 0.983 |
- 0.987 |
- 0.987 |
- 0.977 |
- 0.973 |
- 0.974 |
- 0.969 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.953 |
- 0.976 |
- 0.977 |
- 0.975 |
- 0.934 |
- 0.981 |
- 0.973 |
- 0.976 |
- 0.984 |
- 0.985 |
- 0.978 |
- 0.987 |
- 0.985 |
- 0.949 |
- 0.984 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.982 |
- 0.957 |
- 0.975 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.975 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.979 |
- 0.968 |
- 0.977 |
- 0.902 |
- 0.981 |
- 0.98 |
- 0.978 |
- 0.982 |
- 0.965 |
- 0.942 |
- 0.981 |
- 0.938 |
- 0.984 |
- 0.988 |
- 0.978 |
- 0.98 |
- 0.969 |
- 0.989 |
- 0.986 |
- 0.988 |
- 0.985 |
- 0.988 |
- 0.978 |
- 0.984 |
- 0.987 |
- 0.966 |
- 0.986 |
- 0.987 |
- 0.97 |
- 0.982 |
- 0.982 |
- 0.981 |
- 0.981 |
- 0.974 |
- 0.973 |
- 0.988 |
- 0.981 |
- 0.967 |
- 0.981 |
- 0.972 |
- 0.983 |
- 0.979 |
- 0.976 |
- 0.977 |
- 0.983 |
- 0.982 |
- 0.979 |
- 0.986 |
- 0.978 |
- 0.98 |
- 0.958 |
- 0.968 |
- 0.975 |
- 0.969 |
- 0.985 |
- 0.978 |
- 0.981 |
- 0.986 |
- 0.99 |
- 1 |
- 0.985 |
- 0.977 |
- 0.982 |
- 0.972 |
- 0.982 |
- 0.984 |
- 0.981 |
- 0.968 |
- 0.975 |
- 0.981 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.974 |
- 0.983 |
- 0.978 |
- 0.983 |
- 0.984 |
- 0.986 |
- 0.983 |
- 0.982 |
- 0.932 |
- 0.987 |
- 0.982 |
- 0.986 |
- 0.985 |
- 0.979 |
- 0.938 |
- 0.972 |
- 0.944 |
- |
- 0.889 |
- 0.98 |
-
-
- | Liver |
- 201 |
- F |
- 59 |
- 101613.08 |
- HF |
- BXD68 |
- H1071 |
- 0.986 |
- 0.93 |
- 0.931 |
- 0.983 |
- 0.982 |
- 0.982 |
- 0.988 |
- 0.958 |
- 0.894 |
- 0.985 |
- 0.972 |
- 0.979 |
- 0.979 |
- 0.984 |
- 0.971 |
- 0.977 |
- 0.971 |
- 0.961 |
- 0.984 |
- 0.976 |
- 0.973 |
- 0.982 |
- 0.983 |
- 0.986 |
- 0.98 |
- 0.969 |
- 0.969 |
- 0.969 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.985 |
- 0.949 |
- 0.971 |
- 0.975 |
- 0.976 |
- 0.938 |
- 0.979 |
- 0.975 |
- 0.976 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.98 |
- 0.977 |
- 0.946 |
- 0.986 |
- 0.984 |
- 0.977 |
- 0.977 |
- 0.982 |
- 0.957 |
- 0.972 |
- 0.98 |
- 0.983 |
- 0.981 |
- 0.975 |
- 0.973 |
- 0.982 |
- 0.979 |
- 0.977 |
- 0.964 |
- 0.981 |
- 0.906 |
- 0.976 |
- 0.976 |
- 0.974 |
- 0.982 |
- 0.968 |
- 0.943 |
- 0.978 |
- 0.94 |
- 0.983 |
- 0.988 |
- 0.978 |
- 0.979 |
- 0.967 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.976 |
- 0.98 |
- 0.982 |
- 0.965 |
- 0.983 |
- 0.984 |
- 0.972 |
- 0.981 |
- 0.977 |
- 0.985 |
- 0.985 |
- 0.973 |
- 0.972 |
- 0.986 |
- 0.976 |
- 0.97 |
- 0.981 |
- 0.973 |
- 0.981 |
- 0.977 |
- 0.977 |
- 0.979 |
- 0.981 |
- 0.98 |
- 0.972 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.958 |
- 0.967 |
- 0.976 |
- 0.967 |
- 0.983 |
- 0.974 |
- 0.978 |
- 0.981 |
- 0.98 |
- 0.985 |
- 1 |
- 0.981 |
- 0.988 |
- 0.972 |
- 0.982 |
- 0.981 |
- 0.98 |
- 0.968 |
- 0.977 |
- 0.98 |
- 0.978 |
- 0.983 |
- 0.976 |
- 0.971 |
- 0.985 |
- 0.979 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.935 |
- 0.983 |
- 0.978 |
- 0.985 |
- 0.985 |
- 0.978 |
- 0.94 |
- 0.968 |
- 0.947 |
- |
- 0.894 |
- 0.97 |
-
-
- | Liver |
- 545 |
- F |
- 71 |
- 082214.08 |
- HF |
- BXD68 |
- H1290 |
- 0.975 |
- 0.95 |
- 0.951 |
- 0.976 |
- 0.982 |
- 0.985 |
- 0.973 |
- 0.948 |
- 0.919 |
- 0.976 |
- 0.98 |
- 0.971 |
- 0.976 |
- 0.974 |
- 0.977 |
- 0.977 |
- 0.963 |
- 0.951 |
- 0.982 |
- 0.976 |
- 0.969 |
- 0.973 |
- 0.973 |
- 0.975 |
- 0.964 |
- 0.967 |
- 0.968 |
- 0.959 |
- 0.979 |
- 0.978 |
- 0.969 |
- 0.977 |
- 0.971 |
- 0.961 |
- 0.961 |
- 0.975 |
- 0.935 |
- 0.97 |
- 0.963 |
- 0.963 |
- 0.97 |
- 0.972 |
- 0.964 |
- 0.975 |
- 0.967 |
- 0.949 |
- 0.982 |
- 0.986 |
- 0.971 |
- 0.973 |
- 0.974 |
- 0.948 |
- 0.967 |
- 0.983 |
- 0.975 |
- 0.978 |
- 0.966 |
- 0.964 |
- 0.977 |
- 0.97 |
- 0.98 |
- 0.976 |
- 0.964 |
- 0.937 |
- 0.969 |
- 0.971 |
- 0.971 |
- 0.973 |
- 0.961 |
- 0.929 |
- 0.972 |
- 0.928 |
- 0.978 |
- 0.973 |
- 0.966 |
- 0.97 |
- 0.963 |
- 0.978 |
- 0.979 |
- 0.976 |
- 0.975 |
- 0.979 |
- 0.985 |
- 0.974 |
- 0.972 |
- 0.962 |
- 0.972 |
- 0.976 |
- 0.96 |
- 0.973 |
- 0.97 |
- 0.982 |
- 0.982 |
- 0.969 |
- 0.968 |
- 0.976 |
- 0.974 |
- 0.959 |
- 0.978 |
- 0.962 |
- 0.982 |
- 0.969 |
- 0.975 |
- 0.974 |
- 0.983 |
- 0.969 |
- 0.964 |
- 0.97 |
- 0.969 |
- 0.98 |
- 0.969 |
- 0.955 |
- 0.963 |
- 0.97 |
- 0.973 |
- 0.971 |
- 0.965 |
- 0.981 |
- 0.971 |
- 0.977 |
- 0.981 |
- 1 |
- 0.976 |
- 0.978 |
- 0.973 |
- 0.975 |
- 0.976 |
- 0.959 |
- 0.972 |
- 0.974 |
- 0.969 |
- 0.98 |
- 0.974 |
- 0.962 |
- 0.971 |
- 0.984 |
- 0.98 |
- 0.971 |
- 0.973 |
- 0.976 |
- 0.97 |
- 0.959 |
- 0.974 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.968 |
- 0.928 |
- 0.958 |
- 0.944 |
- |
- 0.919 |
- 0.97 |
-
-
- | Liver |
- 210 |
- F |
- 58 |
- 101613.09 |
- HF |
- BXD69 |
- H1087 |
- 0.985 |
- 0.927 |
- 0.928 |
- 0.983 |
- 0.979 |
- 0.982 |
- 0.985 |
- 0.962 |
- 0.892 |
- 0.982 |
- 0.971 |
- 0.98 |
- 0.973 |
- 0.982 |
- 0.971 |
- 0.98 |
- 0.968 |
- 0.964 |
- 0.979 |
- 0.976 |
- 0.978 |
- 0.985 |
- 0.981 |
- 0.985 |
- 0.981 |
- 0.969 |
- 0.969 |
- 0.971 |
- 0.979 |
- 0.984 |
- 0.98 |
- 0.988 |
- 0.944 |
- 0.967 |
- 0.976 |
- 0.974 |
- 0.938 |
- 0.979 |
- 0.976 |
- 0.978 |
- 0.98 |
- 0.973 |
- 0.972 |
- 0.979 |
- 0.978 |
- 0.945 |
- 0.977 |
- 0.978 |
- 0.982 |
- 0.982 |
- 0.982 |
- 0.957 |
- 0.972 |
- 0.976 |
- 0.981 |
- 0.984 |
- 0.975 |
- 0.974 |
- 0.982 |
- 0.979 |
- 0.974 |
- 0.959 |
- 0.979 |
- 0.899 |
- 0.972 |
- 0.971 |
- 0.971 |
- 0.98 |
- 0.968 |
- 0.945 |
- 0.978 |
- 0.941 |
- 0.981 |
- 0.985 |
- 0.979 |
- 0.979 |
- 0.965 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.983 |
- 0.977 |
- 0.978 |
- 0.983 |
- 0.961 |
- 0.981 |
- 0.983 |
- 0.972 |
- 0.985 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.976 |
- 0.975 |
- 0.984 |
- 0.976 |
- 0.974 |
- 0.978 |
- 0.977 |
- 0.981 |
- 0.98 |
- 0.975 |
- 0.977 |
- 0.978 |
- 0.98 |
- 0.97 |
- 0.98 |
- 0.977 |
- 0.984 |
- 0.952 |
- 0.967 |
- 0.978 |
- 0.968 |
- 0.983 |
- 0.971 |
- 0.979 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.988 |
- 0.976 |
- 1 |
- 0.975 |
- 0.983 |
- 0.984 |
- 0.983 |
- 0.967 |
- 0.978 |
- 0.981 |
- 0.98 |
- 0.984 |
- 0.976 |
- 0.973 |
- 0.98 |
- 0.978 |
- 0.98 |
- 0.981 |
- 0.976 |
- 0.981 |
- 0.981 |
- 0.931 |
- 0.979 |
- 0.978 |
- 0.985 |
- 0.987 |
- 0.981 |
- 0.941 |
- 0.968 |
- 0.947 |
- |
- 0.892 |
- 0.97 |
-
-
- | Liver |
- 528 |
- F |
- 109 |
- 121214.23 |
- HF |
- BXD69 |
- H1328 |
- 0.965 |
- 0.957 |
- 0.957 |
- 0.966 |
- 0.975 |
- 0.973 |
- 0.966 |
- 0.955 |
- 0.926 |
- 0.97 |
- 0.965 |
- 0.968 |
- 0.967 |
- 0.965 |
- 0.977 |
- 0.966 |
- 0.962 |
- 0.959 |
- 0.969 |
- 0.966 |
- 0.959 |
- 0.965 |
- 0.969 |
- 0.969 |
- 0.967 |
- 0.969 |
- 0.969 |
- 0.963 |
- 0.972 |
- 0.97 |
- 0.964 |
- 0.968 |
- 0.96 |
- 0.959 |
- 0.957 |
- 0.971 |
- 0.949 |
- 0.963 |
- 0.963 |
- 0.96 |
- 0.968 |
- 0.964 |
- 0.957 |
- 0.966 |
- 0.966 |
- 0.959 |
- 0.967 |
- 0.971 |
- 0.968 |
- 0.976 |
- 0.967 |
- 0.958 |
- 0.971 |
- 0.975 |
- 0.969 |
- 0.97 |
- 0.969 |
- 0.954 |
- 0.968 |
- 0.967 |
- 0.972 |
- 0.962 |
- 0.964 |
- 0.926 |
- 0.958 |
- 0.963 |
- 0.98 |
- 0.966 |
- 0.968 |
- 0.949 |
- 0.972 |
- 0.945 |
- 0.968 |
- 0.966 |
- 0.963 |
- 0.967 |
- 0.963 |
- 0.969 |
- 0.973 |
- 0.971 |
- 0.969 |
- 0.972 |
- 0.972 |
- 0.965 |
- 0.97 |
- 0.972 |
- 0.964 |
- 0.967 |
- 0.963 |
- 0.967 |
- 0.962 |
- 0.971 |
- 0.972 |
- 0.966 |
- 0.966 |
- 0.972 |
- 0.969 |
- 0.967 |
- 0.982 |
- 0.969 |
- 0.973 |
- 0.969 |
- 0.979 |
- 0.97 |
- 0.972 |
- 0.962 |
- 0.958 |
- 0.962 |
- 0.96 |
- 0.975 |
- 0.958 |
- 0.956 |
- 0.961 |
- 0.969 |
- 0.971 |
- 0.98 |
- 0.961 |
- 0.976 |
- 0.964 |
- 0.972 |
- 0.972 |
- 0.978 |
- 0.975 |
- 1 |
- 0.971 |
- 0.968 |
- 0.969 |
- 0.966 |
- 0.966 |
- 0.972 |
- 0.96 |
- 0.975 |
- 0.969 |
- 0.957 |
- 0.967 |
- 0.972 |
- 0.968 |
- 0.969 |
- 0.972 |
- 0.968 |
- 0.968 |
- 0.947 |
- 0.966 |
- 0.968 |
- 0.972 |
- 0.968 |
- 0.963 |
- 0.945 |
- 0.963 |
- 0.958 |
- |
- 0.926 |
- 0.97 |
-
-
- | Liver |
- 239 |
- F |
- 266 |
- 051012.08 |
- HF |
- BXD70 |
- H0188 |
- 0.986 |
- 0.936 |
- 0.938 |
- 0.984 |
- 0.982 |
- 0.981 |
- 0.985 |
- 0.974 |
- 0.901 |
- 0.979 |
- 0.971 |
- 0.986 |
- 0.977 |
- 0.981 |
- 0.973 |
- 0.978 |
- 0.977 |
- 0.968 |
- 0.983 |
- 0.981 |
- 0.976 |
- 0.985 |
- 0.987 |
- 0.987 |
- 0.984 |
- 0.978 |
- 0.979 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.985 |
- 0.982 |
- 0.946 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.951 |
- 0.987 |
- 0.988 |
- 0.986 |
- 0.981 |
- 0.979 |
- 0.98 |
- 0.984 |
- 0.984 |
- 0.955 |
- 0.977 |
- 0.98 |
- 0.986 |
- 0.984 |
- 0.988 |
- 0.978 |
- 0.983 |
- 0.978 |
- 0.989 |
- 0.983 |
- 0.982 |
- 0.973 |
- 0.985 |
- 0.984 |
- 0.976 |
- 0.96 |
- 0.987 |
- 0.898 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.983 |
- 0.972 |
- 0.954 |
- 0.985 |
- 0.954 |
- 0.982 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.988 |
- 0.989 |
- 0.982 |
- 0.981 |
- 0.97 |
- 0.976 |
- 0.983 |
- 0.97 |
- 0.984 |
- 0.987 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.984 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.986 |
- 0.983 |
- 0.98 |
- 0.984 |
- 0.983 |
- 0.98 |
- 0.985 |
- 0.977 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.978 |
- 0.981 |
- 0.981 |
- 0.985 |
- 0.952 |
- 0.98 |
- 0.985 |
- 0.974 |
- 0.987 |
- 0.979 |
- 0.987 |
- 0.976 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.973 |
- 0.983 |
- 0.971 |
- 1 |
- 0.992 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.99 |
- 0.985 |
- 0.985 |
- 0.983 |
- 0.98 |
- 0.983 |
- 0.976 |
- 0.98 |
- 0.987 |
- 0.987 |
- 0.986 |
- 0.99 |
- 0.929 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.987 |
- 0.985 |
- 0.954 |
- 0.976 |
- 0.952 |
- |
- 0.898 |
- 0.98 |
-
-
- | Liver |
- 578 |
- F |
- 294 |
- 121615.14 |
- HF |
- BXD70 |
- H1728 |
- 0.989 |
- 0.929 |
- 0.93 |
- 0.988 |
- 0.98 |
- 0.987 |
- 0.985 |
- 0.969 |
- 0.892 |
- 0.981 |
- 0.974 |
- 0.989 |
- 0.982 |
- 0.985 |
- 0.973 |
- 0.985 |
- 0.973 |
- 0.969 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.99 |
- 0.989 |
- 0.99 |
- 0.984 |
- 0.976 |
- 0.976 |
- 0.978 |
- 0.986 |
- 0.989 |
- 0.988 |
- 0.987 |
- 0.949 |
- 0.976 |
- 0.986 |
- 0.979 |
- 0.938 |
- 0.988 |
- 0.985 |
- 0.985 |
- 0.985 |
- 0.983 |
- 0.98 |
- 0.987 |
- 0.986 |
- 0.95 |
- 0.976 |
- 0.981 |
- 0.987 |
- 0.98 |
- 0.994 |
- 0.969 |
- 0.981 |
- 0.978 |
- 0.989 |
- 0.989 |
- 0.978 |
- 0.982 |
- 0.99 |
- 0.982 |
- 0.977 |
- 0.963 |
- 0.986 |
- 0.9 |
- 0.983 |
- 0.98 |
- 0.976 |
- 0.988 |
- 0.97 |
- 0.943 |
- 0.983 |
- 0.945 |
- 0.986 |
- 0.985 |
- 0.988 |
- 0.982 |
- 0.976 |
- 0.987 |
- 0.992 |
- 0.992 |
- 0.982 |
- 0.984 |
- 0.973 |
- 0.981 |
- 0.985 |
- 0.968 |
- 0.986 |
- 0.991 |
- 0.979 |
- 0.985 |
- 0.983 |
- 0.987 |
- 0.987 |
- 0.983 |
- 0.982 |
- 0.988 |
- 0.984 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.986 |
- 0.984 |
- 0.971 |
- 0.98 |
- 0.983 |
- 0.987 |
- 0.98 |
- 0.986 |
- 0.984 |
- 0.985 |
- 0.953 |
- 0.975 |
- 0.985 |
- 0.972 |
- 0.984 |
- 0.976 |
- 0.986 |
- 0.981 |
- 0.987 |
- 0.984 |
- 0.981 |
- 0.975 |
- 0.984 |
- 0.968 |
- 0.992 |
- 1 |
- 0.99 |
- 0.973 |
- 0.985 |
- 0.99 |
- 0.988 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.984 |
- 0.986 |
- 0.988 |
- 0.989 |
- 0.933 |
- 0.985 |
- 0.984 |
- 0.988 |
- 0.991 |
- 0.989 |
- 0.945 |
- 0.974 |
- 0.945 |
- |
- 0.892 |
- 0.98 |
-
-
- | Liver |
- 206 |
- F |
- 224 |
- 042015.18 |
- HF |
- BXD73 |
- H2071 |
- 0.988 |
- 0.93 |
- 0.931 |
- 0.987 |
- 0.979 |
- 0.989 |
- 0.982 |
- 0.965 |
- 0.892 |
- 0.98 |
- 0.975 |
- 0.987 |
- 0.98 |
- 0.982 |
- 0.975 |
- 0.987 |
- 0.97 |
- 0.964 |
- 0.984 |
- 0.985 |
- 0.986 |
- 0.989 |
- 0.985 |
- 0.987 |
- 0.978 |
- 0.971 |
- 0.971 |
- 0.976 |
- 0.985 |
- 0.991 |
- 0.985 |
- 0.987 |
- 0.951 |
- 0.971 |
- 0.98 |
- 0.976 |
- 0.934 |
- 0.985 |
- 0.98 |
- 0.983 |
- 0.985 |
- 0.981 |
- 0.977 |
- 0.985 |
- 0.982 |
- 0.948 |
- 0.975 |
- 0.979 |
- 0.987 |
- 0.98 |
- 0.99 |
- 0.961 |
- 0.979 |
- 0.98 |
- 0.991 |
- 0.991 |
- 0.975 |
- 0.983 |
- 0.99 |
- 0.979 |
- 0.98 |
- 0.965 |
- 0.982 |
- 0.903 |
- 0.982 |
- 0.979 |
- 0.972 |
- 0.985 |
- 0.965 |
- 0.935 |
- 0.977 |
- 0.937 |
- 0.986 |
- 0.982 |
- 0.983 |
- 0.979 |
- 0.969 |
- 0.986 |
- 0.988 |
- 0.988 |
- 0.982 |
- 0.984 |
- 0.975 |
- 0.982 |
- 0.982 |
- 0.964 |
- 0.982 |
- 0.989 |
- 0.974 |
- 0.987 |
- 0.982 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.981 |
- 0.984 |
- 0.983 |
- 0.973 |
- 0.978 |
- 0.976 |
- 0.986 |
- 0.985 |
- 0.969 |
- 0.979 |
- 0.983 |
- 0.986 |
- 0.977 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.951 |
- 0.97 |
- 0.982 |
- 0.971 |
- 0.98 |
- 0.972 |
- 0.983 |
- 0.979 |
- 0.985 |
- 0.981 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.969 |
- 0.985 |
- 0.99 |
- 1 |
- 0.972 |
- 0.989 |
- 0.99 |
- 0.986 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.98 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.986 |
- 0.988 |
- 0.936 |
- 0.984 |
- 0.98 |
- 0.989 |
- 0.988 |
- 0.987 |
- 0.937 |
- 0.969 |
- 0.94 |
- |
- 0.892 |
- 0.98 |
-
-
- | Liver |
- 361 |
- F |
- 196 |
- 121214.11 |
- HF |
- BXD73 |
- H1447 |
- 0.968 |
- 0.945 |
- 0.945 |
- 0.97 |
- 0.969 |
- 0.97 |
- 0.968 |
- 0.982 |
- 0.926 |
- 0.967 |
- 0.958 |
- 0.975 |
- 0.963 |
- 0.966 |
- 0.97 |
- 0.963 |
- 0.982 |
- 0.97 |
- 0.971 |
- 0.97 |
- 0.958 |
- 0.969 |
- 0.971 |
- 0.973 |
- 0.98 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.976 |
- 0.97 |
- 0.969 |
- 0.968 |
- 0.932 |
- 0.978 |
- 0.979 |
- 0.985 |
- 0.975 |
- 0.975 |
- 0.983 |
- 0.976 |
- 0.971 |
- 0.968 |
- 0.973 |
- 0.972 |
- 0.978 |
- 0.967 |
- 0.961 |
- 0.968 |
- 0.972 |
- 0.977 |
- 0.971 |
- 0.987 |
- 0.992 |
- 0.972 |
- 0.976 |
- 0.97 |
- 0.984 |
- 0.961 |
- 0.976 |
- 0.98 |
- 0.956 |
- 0.944 |
- 0.977 |
- 0.891 |
- 0.962 |
- 0.963 |
- 0.978 |
- 0.97 |
- 0.979 |
- 0.974 |
- 0.982 |
- 0.97 |
- 0.967 |
- 0.968 |
- 0.973 |
- 0.98 |
- 0.987 |
- 0.968 |
- 0.973 |
- 0.973 |
- 0.971 |
- 0.965 |
- 0.954 |
- 0.963 |
- 0.978 |
- 0.971 |
- 0.974 |
- 0.971 |
- 0.98 |
- 0.969 |
- 0.967 |
- 0.973 |
- 0.976 |
- 0.98 |
- 0.98 |
- 0.972 |
- 0.973 |
- 0.986 |
- 0.977 |
- 0.985 |
- 0.968 |
- 0.976 |
- 0.978 |
- 0.974 |
- 0.964 |
- 0.965 |
- 0.974 |
- 0.969 |
- 0.96 |
- 0.977 |
- 0.928 |
- 0.979 |
- 0.977 |
- 0.971 |
- 0.971 |
- 0.978 |
- 0.969 |
- 0.959 |
- 0.969 |
- 0.968 |
- 0.968 |
- 0.959 |
- 0.967 |
- 0.966 |
- 0.98 |
- 0.973 |
- 0.972 |
- 1 |
- 0.976 |
- 0.984 |
- 0.971 |
- 0.977 |
- 0.973 |
- 0.97 |
- 0.965 |
- 0.962 |
- 0.962 |
- 0.969 |
- 0.983 |
- 0.964 |
- 0.974 |
- 0.917 |
- 0.969 |
- 0.96 |
- 0.97 |
- 0.966 |
- 0.967 |
- 0.97 |
- 0.973 |
- 0.97 |
- |
- 0.891 |
- 0.97 |
-
-
- | Liver |
- 237 |
- F |
- 97 |
- 051112.14 |
- HF |
- BXD73b |
- H0183 |
- 0.982 |
- 0.935 |
- 0.936 |
- 0.983 |
- 0.974 |
- 0.984 |
- 0.976 |
- 0.97 |
- 0.904 |
- 0.975 |
- 0.971 |
- 0.982 |
- 0.974 |
- 0.978 |
- 0.971 |
- 0.981 |
- 0.978 |
- 0.964 |
- 0.983 |
- 0.983 |
- 0.977 |
- 0.983 |
- 0.979 |
- 0.98 |
- 0.976 |
- 0.971 |
- 0.971 |
- 0.975 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.982 |
- 0.947 |
- 0.974 |
- 0.982 |
- 0.979 |
- 0.942 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.98 |
- 0.979 |
- 0.979 |
- 0.978 |
- 0.976 |
- 0.948 |
- 0.968 |
- 0.974 |
- 0.981 |
- 0.975 |
- 0.984 |
- 0.964 |
- 0.979 |
- 0.978 |
- 0.99 |
- 0.985 |
- 0.974 |
- 0.981 |
- 0.988 |
- 0.979 |
- 0.973 |
- 0.963 |
- 0.979 |
- 0.903 |
- 0.976 |
- 0.976 |
- 0.973 |
- 0.979 |
- 0.964 |
- 0.939 |
- 0.974 |
- 0.942 |
- 0.98 |
- 0.976 |
- 0.98 |
- 0.979 |
- 0.975 |
- 0.981 |
- 0.984 |
- 0.985 |
- 0.974 |
- 0.979 |
- 0.969 |
- 0.977 |
- 0.976 |
- 0.969 |
- 0.975 |
- 0.983 |
- 0.978 |
- 0.981 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.986 |
- 0.986 |
- 0.978 |
- 0.982 |
- 0.974 |
- 0.978 |
- 0.976 |
- 0.982 |
- 0.979 |
- 0.971 |
- 0.977 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.978 |
- 0.979 |
- 0.985 |
- 0.941 |
- 0.974 |
- 0.982 |
- 0.971 |
- 0.975 |
- 0.973 |
- 0.982 |
- 0.975 |
- 0.978 |
- 0.975 |
- 0.977 |
- 0.972 |
- 0.978 |
- 0.966 |
- 0.983 |
- 0.985 |
- 0.989 |
- 0.976 |
- 1 |
- 0.988 |
- 0.987 |
- 0.985 |
- 0.982 |
- 0.981 |
- 0.975 |
- 0.978 |
- 0.979 |
- 0.978 |
- 0.981 |
- 0.982 |
- 0.984 |
- 0.932 |
- 0.979 |
- 0.975 |
- 0.982 |
- 0.984 |
- 0.982 |
- 0.942 |
- 0.971 |
- 0.943 |
- |
- 0.903 |
- 0.97 |
-
-
- | Liver |
- 474 |
- F |
- 256 |
- 050115.12 |
- HF |
- BXD73b |
- H1545 |
- 0.986 |
- 0.939 |
- 0.94 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.974 |
- 0.906 |
- 0.979 |
- 0.972 |
- 0.988 |
- 0.979 |
- 0.983 |
- 0.976 |
- 0.982 |
- 0.978 |
- 0.969 |
- 0.984 |
- 0.984 |
- 0.977 |
- 0.986 |
- 0.986 |
- 0.988 |
- 0.985 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.986 |
- 0.99 |
- 0.984 |
- 0.984 |
- 0.949 |
- 0.978 |
- 0.985 |
- 0.984 |
- 0.951 |
- 0.986 |
- 0.987 |
- 0.985 |
- 0.983 |
- 0.979 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.958 |
- 0.974 |
- 0.98 |
- 0.987 |
- 0.984 |
- 0.988 |
- 0.974 |
- 0.988 |
- 0.983 |
- 0.992 |
- 0.99 |
- 0.982 |
- 0.976 |
- 0.99 |
- 0.984 |
- 0.977 |
- 0.962 |
- 0.987 |
- 0.904 |
- 0.98 |
- 0.979 |
- 0.98 |
- 0.985 |
- 0.974 |
- 0.952 |
- 0.984 |
- 0.954 |
- 0.982 |
- 0.982 |
- 0.985 |
- 0.984 |
- 0.982 |
- 0.985 |
- 0.989 |
- 0.989 |
- 0.982 |
- 0.981 |
- 0.971 |
- 0.977 |
- 0.984 |
- 0.971 |
- 0.984 |
- 0.988 |
- 0.98 |
- 0.982 |
- 0.979 |
- 0.985 |
- 0.986 |
- 0.985 |
- 0.985 |
- 0.985 |
- 0.985 |
- 0.981 |
- 0.983 |
- 0.983 |
- 0.983 |
- 0.985 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.983 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.986 |
- 0.95 |
- 0.979 |
- 0.984 |
- 0.974 |
- 0.984 |
- 0.98 |
- 0.984 |
- 0.976 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.974 |
- 0.981 |
- 0.972 |
- 0.99 |
- 0.99 |
- 0.99 |
- 0.984 |
- 0.988 |
- 1 |
- 0.985 |
- 0.986 |
- 0.985 |
- 0.982 |
- 0.981 |
- 0.978 |
- 0.98 |
- 0.985 |
- 0.988 |
- 0.984 |
- 0.989 |
- 0.933 |
- 0.983 |
- 0.979 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.954 |
- 0.975 |
- 0.953 |
- |
- 0.904 |
- 0.98 |
-
-
- | Liver |
- 511 |
- F |
- 319 |
- 121615.19 |
- HF |
- BXD77 |
- H1866 |
- 0.986 |
- 0.922 |
- 0.924 |
- 0.986 |
- 0.973 |
- 0.983 |
- 0.981 |
- 0.968 |
- 0.889 |
- 0.977 |
- 0.971 |
- 0.982 |
- 0.977 |
- 0.983 |
- 0.967 |
- 0.978 |
- 0.975 |
- 0.962 |
- 0.985 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.978 |
- 0.969 |
- 0.969 |
- 0.974 |
- 0.985 |
- 0.982 |
- 0.987 |
- 0.982 |
- 0.944 |
- 0.975 |
- 0.988 |
- 0.976 |
- 0.932 |
- 0.984 |
- 0.984 |
- 0.987 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.983 |
- 0.981 |
- 0.941 |
- 0.97 |
- 0.977 |
- 0.982 |
- 0.975 |
- 0.986 |
- 0.962 |
- 0.975 |
- 0.973 |
- 0.987 |
- 0.982 |
- 0.979 |
- 0.981 |
- 0.987 |
- 0.98 |
- 0.972 |
- 0.96 |
- 0.981 |
- 0.895 |
- 0.98 |
- 0.981 |
- 0.972 |
- 0.985 |
- 0.963 |
- 0.937 |
- 0.976 |
- 0.936 |
- 0.984 |
- 0.981 |
- 0.984 |
- 0.98 |
- 0.973 |
- 0.984 |
- 0.988 |
- 0.989 |
- 0.977 |
- 0.982 |
- 0.969 |
- 0.979 |
- 0.979 |
- 0.967 |
- 0.983 |
- 0.988 |
- 0.979 |
- 0.98 |
- 0.986 |
- 0.986 |
- 0.986 |
- 0.984 |
- 0.983 |
- 0.982 |
- 0.982 |
- 0.971 |
- 0.976 |
- 0.975 |
- 0.982 |
- 0.98 |
- 0.967 |
- 0.976 |
- 0.98 |
- 0.987 |
- 0.984 |
- 0.986 |
- 0.986 |
- 0.983 |
- 0.946 |
- 0.973 |
- 0.986 |
- 0.971 |
- 0.977 |
- 0.972 |
- 0.984 |
- 0.978 |
- 0.982 |
- 0.979 |
- 0.978 |
- 0.969 |
- 0.98 |
- 0.96 |
- 0.985 |
- 0.988 |
- 0.986 |
- 0.971 |
- 0.987 |
- 0.985 |
- 1 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.977 |
- 0.977 |
- 0.981 |
- 0.98 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.928 |
- 0.983 |
- 0.981 |
- 0.982 |
- 0.985 |
- 0.985 |
- 0.936 |
- 0.971 |
- 0.937 |
- |
- 0.889 |
- 0.98 |
-
-
- | Liver |
- 571 |
- F |
- 24 |
- 061913.18 |
- HF |
- BXD79 |
- H0583 |
- 0.984 |
- 0.948 |
- 0.949 |
- 0.986 |
- 0.98 |
- 0.985 |
- 0.98 |
- 0.972 |
- 0.916 |
- 0.981 |
- 0.977 |
- 0.984 |
- 0.976 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.978 |
- 0.967 |
- 0.986 |
- 0.983 |
- 0.977 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.981 |
- 0.977 |
- 0.978 |
- 0.978 |
- 0.986 |
- 0.983 |
- 0.981 |
- 0.983 |
- 0.957 |
- 0.973 |
- 0.98 |
- 0.986 |
- 0.955 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.982 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.979 |
- 0.956 |
- 0.975 |
- 0.98 |
- 0.98 |
- 0.979 |
- 0.984 |
- 0.967 |
- 0.981 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.975 |
- 0.987 |
- 0.983 |
- 0.975 |
- 0.969 |
- 0.982 |
- 0.915 |
- 0.974 |
- 0.975 |
- 0.981 |
- 0.982 |
- 0.975 |
- 0.953 |
- 0.981 |
- 0.949 |
- 0.984 |
- 0.98 |
- 0.977 |
- 0.983 |
- 0.976 |
- 0.984 |
- 0.988 |
- 0.987 |
- 0.981 |
- 0.984 |
- 0.978 |
- 0.978 |
- 0.983 |
- 0.973 |
- 0.981 |
- 0.984 |
- 0.978 |
- 0.983 |
- 0.979 |
- 0.987 |
- 0.988 |
- 0.984 |
- 0.984 |
- 0.983 |
- 0.984 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.985 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.981 |
- 0.981 |
- 0.979 |
- 0.981 |
- 0.981 |
- 1 |
- 0.956 |
- 0.973 |
- 0.982 |
- 0.974 |
- 0.98 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.983 |
- 0.98 |
- 0.984 |
- 0.975 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.977 |
- 0.985 |
- 0.986 |
- 0.983 |
- 1 |
- 0.984 |
- 0.977 |
- 0.977 |
- 0.982 |
- 0.983 |
- 0.978 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.94 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.986 |
- 0.978 |
- 0.949 |
- 0.974 |
- 0.955 |
- |
- 0.915 |
- 0.98 |
-
-
- | Liver |
- 241 |
- F |
- 2 |
- 051012.14 |
- HF |
- BXD87 |
- H0243 |
- 0.984 |
- 0.942 |
- 0.945 |
- 0.984 |
- 0.976 |
- 0.983 |
- 0.977 |
- 0.965 |
- 0.904 |
- 0.977 |
- 0.979 |
- 0.983 |
- 0.975 |
- 0.978 |
- 0.974 |
- 0.979 |
- 0.973 |
- 0.965 |
- 0.985 |
- 0.984 |
- 0.974 |
- 0.986 |
- 0.982 |
- 0.983 |
- 0.976 |
- 0.974 |
- 0.975 |
- 0.978 |
- 0.985 |
- 0.98 |
- 0.979 |
- 0.978 |
- 0.959 |
- 0.972 |
- 0.979 |
- 0.98 |
- 0.937 |
- 0.983 |
- 0.981 |
- 0.985 |
- 0.984 |
- 0.983 |
- 0.979 |
- 0.985 |
- 0.978 |
- 0.944 |
- 0.972 |
- 0.976 |
- 0.983 |
- 0.978 |
- 0.984 |
- 0.96 |
- 0.98 |
- 0.976 |
- 0.983 |
- 0.98 |
- 0.978 |
- 0.975 |
- 0.984 |
- 0.979 |
- 0.974 |
- 0.973 |
- 0.981 |
- 0.911 |
- 0.977 |
- 0.975 |
- 0.981 |
- 0.982 |
- 0.963 |
- 0.94 |
- 0.98 |
- 0.939 |
- 0.984 |
- 0.977 |
- 0.973 |
- 0.979 |
- 0.975 |
- 0.984 |
- 0.987 |
- 0.987 |
- 0.981 |
- 0.985 |
- 0.975 |
- 0.98 |
- 0.984 |
- 0.972 |
- 0.98 |
- 0.982 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.986 |
- 0.985 |
- 0.984 |
- 0.984 |
- 0.986 |
- 1 |
- 0.971 |
- 0.98 |
- 0.975 |
- 0.985 |
- 0.986 |
- 0.976 |
- 0.975 |
- 0.981 |
- 0.978 |
- 0.982 |
- 0.986 |
- 0.981 |
- 0.984 |
- 0.95 |
- 0.97 |
- 0.982 |
- 0.969 |
- 0.977 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.976 |
- 0.974 |
- 0.976 |
- 0.969 |
- 0.983 |
- 0.984 |
- 0.983 |
- 0.973 |
- 0.982 |
- 0.985 |
- 0.982 |
- 0.984 |
- 1 |
- 0.978 |
- 0.976 |
- 0.981 |
- 0.987 |
- 0.977 |
- 0.985 |
- 0.983 |
- 0.982 |
- 0.938 |
- 0.986 |
- 0.983 |
- 0.985 |
- 0.984 |
- 0.974 |
- 0.939 |
- 0.977 |
- 0.941 |
- |
- 0.904 |
- 0.98 |
-
-
- | Liver |
- 512 |
- F |
- 326 |
- 121615.21 |
- HF |
- BXD87 |
- H1945 |
- 0.982 |
- 0.915 |
- 0.917 |
- 0.976 |
- 0.968 |
- 0.976 |
- 0.977 |
- 0.965 |
- 0.879 |
- 0.974 |
- 0.959 |
- 0.984 |
- 0.967 |
- 0.975 |
- 0.968 |
- 0.979 |
- 0.974 |
- 0.963 |
- 0.979 |
- 0.976 |
- 0.971 |
- 0.983 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.968 |
- 0.969 |
- 0.975 |
- 0.976 |
- 0.98 |
- 0.982 |
- 0.973 |
- 0.933 |
- 0.978 |
- 0.984 |
- 0.971 |
- 0.935 |
- 0.983 |
- 0.983 |
- 0.987 |
- 0.981 |
- 0.98 |
- 0.982 |
- 0.98 |
- 0.975 |
- 0.941 |
- 0.969 |
- 0.97 |
- 0.985 |
- 0.974 |
- 0.981 |
- 0.965 |
- 0.974 |
- 0.969 |
- 0.982 |
- 0.98 |
- 0.975 |
- 0.982 |
- 0.985 |
- 0.98 |
- 0.973 |
- 0.957 |
- 0.978 |
- 0.883 |
- 0.979 |
- 0.979 |
- 0.966 |
- 0.977 |
- 0.966 |
- 0.94 |
- 0.975 |
- 0.945 |
- 0.976 |
- 0.977 |
- 0.979 |
- 0.98 |
- 0.973 |
- 0.981 |
- 0.979 |
- 0.983 |
- 0.975 |
- 0.974 |
- 0.961 |
- 0.971 |
- 0.977 |
- 0.964 |
- 0.978 |
- 0.98 |
- 0.975 |
- 0.982 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.982 |
- 0.982 |
- 0.976 |
- 0.978 |
- 0.971 |
- 0.974 |
- 0.975 |
- 0.972 |
- 0.981 |
- 0.961 |
- 0.969 |
- 0.966 |
- 0.982 |
- 0.982 |
- 0.981 |
- 0.977 |
- 0.977 |
- 0.932 |
- 0.98 |
- 0.986 |
- 0.967 |
- 0.975 |
- 0.966 |
- 0.984 |
- 0.969 |
- 0.977 |
- 0.974 |
- 0.971 |
- 0.962 |
- 0.973 |
- 0.957 |
- 0.98 |
- 0.983 |
- 0.982 |
- 0.97 |
- 0.981 |
- 0.982 |
- 0.983 |
- 0.977 |
- 0.978 |
- 1 |
- 0.974 |
- 0.967 |
- 0.974 |
- 0.98 |
- 0.979 |
- 0.977 |
- 0.984 |
- 0.911 |
- 0.98 |
- 0.971 |
- 0.976 |
- 0.98 |
- 0.981 |
- 0.945 |
- 0.972 |
- 0.933 |
- |
- 0.879 |
- 0.97 |
-
-
- | Liver |
- 243 |
- F |
- 267 |
- 051112.01 |
- HF |
- BXD89 |
- H0176 |
- 0.986 |
- 0.921 |
- 0.923 |
- 0.982 |
- 0.983 |
- 0.978 |
- 0.987 |
- 0.954 |
- 0.88 |
- 0.981 |
- 0.966 |
- 0.979 |
- 0.977 |
- 0.981 |
- 0.967 |
- 0.973 |
- 0.965 |
- 0.956 |
- 0.975 |
- 0.974 |
- 0.969 |
- 0.983 |
- 0.986 |
- 0.985 |
- 0.976 |
- 0.966 |
- 0.967 |
- 0.968 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.98 |
- 0.941 |
- 0.972 |
- 0.974 |
- 0.97 |
- 0.932 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.979 |
- 0.975 |
- 0.976 |
- 0.981 |
- 0.975 |
- 0.944 |
- 0.982 |
- 0.975 |
- 0.982 |
- 0.978 |
- 0.98 |
- 0.96 |
- 0.971 |
- 0.978 |
- 0.986 |
- 0.981 |
- 0.973 |
- 0.97 |
- 0.978 |
- 0.976 |
- 0.98 |
- 0.966 |
- 0.98 |
- 0.896 |
- 0.98 |
- 0.981 |
- 0.97 |
- 0.98 |
- 0.962 |
- 0.938 |
- 0.976 |
- 0.941 |
- 0.98 |
- 0.987 |
- 0.978 |
- 0.976 |
- 0.965 |
- 0.988 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.981 |
- 0.971 |
- 0.975 |
- 0.979 |
- 0.958 |
- 0.981 |
- 0.983 |
- 0.965 |
- 0.979 |
- 0.973 |
- 0.976 |
- 0.975 |
- 0.97 |
- 0.97 |
- 0.985 |
- 0.976 |
- 0.965 |
- 0.977 |
- 0.969 |
- 0.978 |
- 0.976 |
- 0.969 |
- 0.977 |
- 0.976 |
- 0.981 |
- 0.97 |
- 0.979 |
- 0.98 |
- 0.977 |
- 0.953 |
- 0.967 |
- 0.973 |
- 0.962 |
- 0.988 |
- 0.97 |
- 0.983 |
- 0.978 |
- 0.977 |
- 0.983 |
- 0.985 |
- 0.971 |
- 0.98 |
- 0.967 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.965 |
- 0.975 |
- 0.981 |
- 0.977 |
- 0.977 |
- 0.976 |
- 0.974 |
- 1 |
- 0.977 |
- 0.98 |
- 0.988 |
- 0.982 |
- 0.982 |
- 0.986 |
- 0.926 |
- 0.984 |
- 0.976 |
- 0.983 |
- 0.982 |
- 0.978 |
- 0.941 |
- 0.967 |
- 0.939 |
- |
- 0.88 |
- 0.97 |
-
-
- | Liver |
- 539 |
- F |
- 282 |
- 101014.04 |
- HF |
- BXD89 |
- H1321 |
- 0.98 |
- 0.946 |
- 0.948 |
- 0.984 |
- 0.981 |
- 0.988 |
- 0.975 |
- 0.955 |
- 0.918 |
- 0.977 |
- 0.983 |
- 0.975 |
- 0.978 |
- 0.976 |
- 0.975 |
- 0.982 |
- 0.969 |
- 0.958 |
- 0.982 |
- 0.98 |
- 0.976 |
- 0.979 |
- 0.976 |
- 0.979 |
- 0.968 |
- 0.97 |
- 0.97 |
- 0.966 |
- 0.983 |
- 0.98 |
- 0.976 |
- 0.98 |
- 0.966 |
- 0.96 |
- 0.969 |
- 0.978 |
- 0.928 |
- 0.973 |
- 0.968 |
- 0.969 |
- 0.978 |
- 0.976 |
- 0.968 |
- 0.979 |
- 0.973 |
- 0.947 |
- 0.974 |
- 0.977 |
- 0.975 |
- 0.972 |
- 0.982 |
- 0.948 |
- 0.971 |
- 0.978 |
- 0.978 |
- 0.98 |
- 0.972 |
- 0.971 |
- 0.981 |
- 0.971 |
- 0.977 |
- 0.98 |
- 0.972 |
- 0.927 |
- 0.977 |
- 0.975 |
- 0.975 |
- 0.979 |
- 0.962 |
- 0.929 |
- 0.972 |
- 0.927 |
- 0.985 |
- 0.975 |
- 0.971 |
- 0.971 |
- 0.964 |
- 0.98 |
- 0.985 |
- 0.982 |
- 0.974 |
- 0.983 |
- 0.985 |
- 0.98 |
- 0.977 |
- 0.963 |
- 0.975 |
- 0.98 |
- 0.965 |
- 0.976 |
- 0.976 |
- 0.983 |
- 0.983 |
- 0.973 |
- 0.972 |
- 0.981 |
- 0.981 |
- 0.961 |
- 0.976 |
- 0.965 |
- 0.989 |
- 0.975 |
- 0.975 |
- 0.974 |
- 0.986 |
- 0.976 |
- 0.968 |
- 0.977 |
- 0.976 |
- 0.982 |
- 0.958 |
- 0.954 |
- 0.968 |
- 0.971 |
- 0.973 |
- 0.975 |
- 0.97 |
- 0.984 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.984 |
- 0.978 |
- 0.972 |
- 0.976 |
- 0.981 |
- 0.982 |
- 0.962 |
- 0.978 |
- 0.978 |
- 0.977 |
- 0.982 |
- 0.981 |
- 0.967 |
- 0.977 |
- 1 |
- 0.983 |
- 0.973 |
- 0.979 |
- 0.98 |
- 0.976 |
- 0.96 |
- 0.977 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.973 |
- 0.927 |
- 0.966 |
- 0.944 |
- |
- 0.918 |
- 0.97 |
-
-
- | Liver |
- 548 |
- F |
- 312 |
- 082214.09 |
- HF |
- BXD9 |
- H1009 |
- 0.987 |
- 0.932 |
- 0.936 |
- 0.985 |
- 0.979 |
- 0.984 |
- 0.981 |
- 0.949 |
- 0.889 |
- 0.98 |
- 0.979 |
- 0.98 |
- 0.979 |
- 0.982 |
- 0.968 |
- 0.98 |
- 0.964 |
- 0.956 |
- 0.987 |
- 0.982 |
- 0.976 |
- 0.985 |
- 0.982 |
- 0.983 |
- 0.97 |
- 0.965 |
- 0.966 |
- 0.966 |
- 0.985 |
- 0.982 |
- 0.98 |
- 0.98 |
- 0.961 |
- 0.966 |
- 0.974 |
- 0.973 |
- 0.922 |
- 0.981 |
- 0.973 |
- 0.978 |
- 0.98 |
- 0.98 |
- 0.977 |
- 0.984 |
- 0.972 |
- 0.936 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.977 |
- 0.981 |
- 0.949 |
- 0.969 |
- 0.978 |
- 0.983 |
- 0.982 |
- 0.97 |
- 0.972 |
- 0.983 |
- 0.975 |
- 0.979 |
- 0.976 |
- 0.98 |
- 0.918 |
- 0.979 |
- 0.979 |
- 0.974 |
- 0.981 |
- 0.955 |
- 0.926 |
- 0.973 |
- 0.927 |
- 0.985 |
- 0.981 |
- 0.972 |
- 0.975 |
- 0.963 |
- 0.988 |
- 0.987 |
- 0.987 |
- 0.979 |
- 0.987 |
- 0.981 |
- 0.982 |
- 0.979 |
- 0.964 |
- 0.98 |
- 0.985 |
- 0.962 |
- 0.98 |
- 0.982 |
- 0.987 |
- 0.985 |
- 0.975 |
- 0.974 |
- 0.984 |
- 0.987 |
- 0.961 |
- 0.979 |
- 0.968 |
- 0.986 |
- 0.979 |
- 0.97 |
- 0.974 |
- 0.982 |
- 0.981 |
- 0.975 |
- 0.986 |
- 0.987 |
- 0.983 |
- 0.961 |
- 0.961 |
- 0.975 |
- 0.963 |
- 0.979 |
- 0.974 |
- 0.982 |
- 0.986 |
- 0.981 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.968 |
- 0.98 |
- 0.983 |
- 0.983 |
- 0.962 |
- 0.979 |
- 0.98 |
- 0.981 |
- 0.983 |
- 0.987 |
- 0.974 |
- 0.98 |
- 0.983 |
- 1 |
- 0.979 |
- 0.979 |
- 0.987 |
- 0.98 |
- 0.941 |
- 0.987 |
- 0.987 |
- 0.984 |
- 0.985 |
- 0.975 |
- 0.927 |
- 0.971 |
- 0.93 |
- |
- 0.889 |
- 0.97 |
-
-
- | Liver |
- 218 |
- F |
- 297 |
- 101613.19 |
- HF |
- BXD90 |
- H1093 |
- 0.985 |
- 0.922 |
- 0.924 |
- 0.98 |
- 0.985 |
- 0.979 |
- 0.988 |
- 0.961 |
- 0.884 |
- 0.981 |
- 0.965 |
- 0.982 |
- 0.977 |
- 0.981 |
- 0.973 |
- 0.976 |
- 0.967 |
- 0.962 |
- 0.977 |
- 0.975 |
- 0.972 |
- 0.983 |
- 0.988 |
- 0.986 |
- 0.979 |
- 0.97 |
- 0.97 |
- 0.972 |
- 0.98 |
- 0.983 |
- 0.985 |
- 0.981 |
- 0.94 |
- 0.977 |
- 0.978 |
- 0.972 |
- 0.937 |
- 0.983 |
- 0.979 |
- 0.979 |
- 0.98 |
- 0.978 |
- 0.978 |
- 0.983 |
- 0.979 |
- 0.95 |
- 0.98 |
- 0.976 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.965 |
- 0.973 |
- 0.977 |
- 0.987 |
- 0.983 |
- 0.974 |
- 0.973 |
- 0.981 |
- 0.979 |
- 0.981 |
- 0.96 |
- 0.981 |
- 0.892 |
- 0.982 |
- 0.985 |
- 0.973 |
- 0.98 |
- 0.966 |
- 0.943 |
- 0.977 |
- 0.948 |
- 0.98 |
- 0.988 |
- 0.984 |
- 0.979 |
- 0.969 |
- 0.988 |
- 0.983 |
- 0.987 |
- 0.983 |
- 0.982 |
- 0.971 |
- 0.976 |
- 0.98 |
- 0.963 |
- 0.981 |
- 0.986 |
- 0.971 |
- 0.981 |
- 0.975 |
- 0.978 |
- 0.978 |
- 0.975 |
- 0.974 |
- 0.986 |
- 0.977 |
- 0.97 |
- 0.981 |
- 0.974 |
- 0.977 |
- 0.981 |
- 0.97 |
- 0.982 |
- 0.978 |
- 0.984 |
- 0.972 |
- 0.98 |
- 0.98 |
- 0.978 |
- 0.951 |
- 0.975 |
- 0.978 |
- 0.968 |
- 0.991 |
- 0.973 |
- 0.987 |
- 0.978 |
- 0.98 |
- 0.984 |
- 0.982 |
- 0.971 |
- 0.981 |
- 0.969 |
- 0.987 |
- 0.984 |
- 0.983 |
- 0.969 |
- 0.978 |
- 0.985 |
- 0.98 |
- 0.978 |
- 0.977 |
- 0.98 |
- 0.988 |
- 0.973 |
- 0.979 |
- 1 |
- 0.987 |
- 0.985 |
- 0.988 |
- 0.923 |
- 0.983 |
- 0.979 |
- 0.983 |
- 0.985 |
- 0.985 |
- 0.948 |
- 0.97 |
- 0.944 |
- |
- 0.884 |
- 0.97 |
-
-
- | Liver |
- 570 |
- F |
- 274 |
- 062013.03 |
- HF |
- BXD90 |
- H0736 |
- 0.983 |
- 0.941 |
- 0.943 |
- 0.983 |
- 0.983 |
- 0.983 |
- 0.982 |
- 0.973 |
- 0.91 |
- 0.982 |
- 0.972 |
- 0.984 |
- 0.981 |
- 0.981 |
- 0.977 |
- 0.976 |
- 0.981 |
- 0.974 |
- 0.984 |
- 0.982 |
- 0.97 |
- 0.982 |
- 0.987 |
- 0.986 |
- 0.983 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.983 |
- 0.978 |
- 0.951 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.953 |
- 0.983 |
- 0.983 |
- 0.979 |
- 0.983 |
- 0.984 |
- 0.982 |
- 0.986 |
- 0.985 |
- 0.961 |
- 0.977 |
- 0.978 |
- 0.982 |
- 0.981 |
- 0.984 |
- 0.975 |
- 0.987 |
- 0.981 |
- 0.986 |
- 0.981 |
- 0.984 |
- 0.974 |
- 0.985 |
- 0.983 |
- 0.976 |
- 0.968 |
- 0.983 |
- 0.902 |
- 0.984 |
- 0.986 |
- 0.987 |
- 0.982 |
- 0.976 |
- 0.957 |
- 0.984 |
- 0.959 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.983 |
- 0.984 |
- 0.985 |
- 0.987 |
- 0.988 |
- 0.98 |
- 0.981 |
- 0.971 |
- 0.98 |
- 0.985 |
- 0.976 |
- 0.985 |
- 0.987 |
- 0.98 |
- 0.977 |
- 0.98 |
- 0.985 |
- 0.986 |
- 0.98 |
- 0.98 |
- 0.988 |
- 0.985 |
- 0.978 |
- 0.986 |
- 0.98 |
- 0.982 |
- 0.982 |
- 0.98 |
- 0.981 |
- 0.981 |
- 0.981 |
- 0.981 |
- 0.982 |
- 0.978 |
- 0.983 |
- 0.95 |
- 0.977 |
- 0.979 |
- 0.973 |
- 0.985 |
- 0.987 |
- 0.983 |
- 0.98 |
- 0.982 |
- 0.986 |
- 0.979 |
- 0.973 |
- 0.976 |
- 0.972 |
- 0.987 |
- 0.986 |
- 0.981 |
- 0.983 |
- 0.981 |
- 0.988 |
- 0.981 |
- 0.983 |
- 0.985 |
- 0.979 |
- 0.982 |
- 0.979 |
- 0.979 |
- 0.987 |
- 1 |
- 0.982 |
- 0.986 |
- 0.931 |
- 0.983 |
- 0.979 |
- 0.983 |
- 0.983 |
- 0.98 |
- 0.959 |
- 0.981 |
- 0.96 |
- |
- 0.902 |
- 0.98 |
-
-
- | Liver |
- 562 |
- F |
- 325 |
- 062013.19 |
- HF |
- BXD91 |
- H0881 |
- 0.988 |
- 0.928 |
- 0.931 |
- 0.986 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.955 |
- 0.888 |
- 0.979 |
- 0.977 |
- 0.983 |
- 0.982 |
- 0.983 |
- 0.97 |
- 0.98 |
- 0.964 |
- 0.954 |
- 0.984 |
- 0.983 |
- 0.98 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.973 |
- 0.967 |
- 0.968 |
- 0.969 |
- 0.984 |
- 0.985 |
- 0.988 |
- 0.982 |
- 0.957 |
- 0.97 |
- 0.978 |
- 0.973 |
- 0.925 |
- 0.984 |
- 0.978 |
- 0.982 |
- 0.981 |
- 0.982 |
- 0.978 |
- 0.985 |
- 0.976 |
- 0.94 |
- 0.978 |
- 0.978 |
- 0.986 |
- 0.98 |
- 0.984 |
- 0.955 |
- 0.971 |
- 0.978 |
- 0.988 |
- 0.985 |
- 0.97 |
- 0.975 |
- 0.984 |
- 0.976 |
- 0.98 |
- 0.97 |
- 0.98 |
- 0.907 |
- 0.981 |
- 0.983 |
- 0.974 |
- 0.982 |
- 0.958 |
- 0.929 |
- 0.974 |
- 0.933 |
- 0.987 |
- 0.984 |
- 0.98 |
- 0.976 |
- 0.965 |
- 0.99 |
- 0.989 |
- 0.99 |
- 0.979 |
- 0.986 |
- 0.978 |
- 0.981 |
- 0.978 |
- 0.964 |
- 0.981 |
- 0.988 |
- 0.968 |
- 0.978 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.978 |
- 0.977 |
- 0.983 |
- 0.983 |
- 0.966 |
- 0.982 |
- 0.972 |
- 0.986 |
- 0.981 |
- 0.966 |
- 0.978 |
- 0.985 |
- 0.988 |
- 0.975 |
- 0.986 |
- 0.988 |
- 0.982 |
- 0.963 |
- 0.967 |
- 0.979 |
- 0.968 |
- 0.982 |
- 0.974 |
- 0.987 |
- 0.984 |
- 0.979 |
- 0.983 |
- 0.98 |
- 0.976 |
- 0.981 |
- 0.968 |
- 0.986 |
- 0.988 |
- 0.986 |
- 0.964 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.982 |
- 0.983 |
- 0.977 |
- 0.982 |
- 0.98 |
- 0.987 |
- 0.985 |
- 0.982 |
- 1 |
- 0.988 |
- 0.938 |
- 0.987 |
- 0.991 |
- 0.987 |
- 0.99 |
- 0.984 |
- 0.933 |
- 0.967 |
- 0.931 |
- |
- 0.888 |
- 0.98 |
-
-
- | Liver |
- 213 |
- F |
- 288 |
- 101613.21 |
- HF |
- BXD95 |
- H1275 |
- 0.988 |
- 0.929 |
- 0.931 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.985 |
- 0.97 |
- 0.892 |
- 0.98 |
- 0.968 |
- 0.988 |
- 0.977 |
- 0.982 |
- 0.972 |
- 0.981 |
- 0.973 |
- 0.965 |
- 0.98 |
- 0.981 |
- 0.979 |
- 0.988 |
- 0.987 |
- 0.986 |
- 0.981 |
- 0.975 |
- 0.975 |
- 0.98 |
- 0.983 |
- 0.985 |
- 0.987 |
- 0.983 |
- 0.943 |
- 0.98 |
- 0.985 |
- 0.977 |
- 0.944 |
- 0.987 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.979 |
- 0.981 |
- 0.984 |
- 0.982 |
- 0.954 |
- 0.976 |
- 0.977 |
- 0.988 |
- 0.982 |
- 0.986 |
- 0.97 |
- 0.978 |
- 0.977 |
- 0.989 |
- 0.985 |
- 0.979 |
- 0.978 |
- 0.986 |
- 0.982 |
- 0.977 |
- 0.962 |
- 0.986 |
- 0.897 |
- 0.982 |
- 0.98 |
- 0.974 |
- 0.986 |
- 0.97 |
- 0.946 |
- 0.981 |
- 0.951 |
- 0.983 |
- 0.985 |
- 0.985 |
- 0.982 |
- 0.974 |
- 0.987 |
- 0.987 |
- 0.988 |
- 0.982 |
- 0.981 |
- 0.969 |
- 0.977 |
- 0.982 |
- 0.965 |
- 0.983 |
- 0.988 |
- 0.977 |
- 0.984 |
- 0.977 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.982 |
- 0.976 |
- 0.981 |
- 0.98 |
- 0.981 |
- 0.986 |
- 0.971 |
- 0.981 |
- 0.978 |
- 0.986 |
- 0.979 |
- 0.984 |
- 0.984 |
- 0.984 |
- 0.948 |
- 0.978 |
- 0.984 |
- 0.97 |
- 0.985 |
- 0.974 |
- 0.989 |
- 0.976 |
- 0.982 |
- 0.982 |
- 0.981 |
- 0.97 |
- 0.981 |
- 0.968 |
- 0.99 |
- 0.989 |
- 0.988 |
- 0.974 |
- 0.984 |
- 0.989 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.984 |
- 0.986 |
- 0.976 |
- 0.98 |
- 0.988 |
- 0.986 |
- 0.988 |
- 1 |
- 0.929 |
- 0.985 |
- 0.98 |
- 0.987 |
- 0.988 |
- 0.987 |
- 0.951 |
- 0.972 |
- 0.944 |
- |
- 0.892 |
- 0.98 |
-
-
- | Liver |
- 550 |
- F |
- 236 |
- 102414.20 |
- HF |
- BXD95 |
- H1273 |
- 0.925 |
- 0.95 |
- 0.95 |
- 0.935 |
- 0.941 |
- 0.951 |
- 0.921 |
- 0.908 |
- 0.939 |
- 0.932 |
- 0.955 |
- 0.928 |
- 0.944 |
- 0.932 |
- 0.942 |
- 0.942 |
- 0.921 |
- 0.914 |
- 0.94 |
- 0.938 |
- 0.932 |
- 0.928 |
- 0.926 |
- 0.929 |
- 0.919 |
- 0.928 |
- 0.928 |
- 0.92 |
- 0.941 |
- 0.933 |
- 0.924 |
- 0.934 |
- 0.964 |
- 0.909 |
- 0.913 |
- 0.938 |
- 0.893 |
- 0.922 |
- 0.916 |
- 0.917 |
- 0.932 |
- 0.927 |
- 0.916 |
- 0.929 |
- 0.924 |
- 0.917 |
- 0.929 |
- 0.942 |
- 0.924 |
- 0.924 |
- 0.934 |
- 0.899 |
- 0.927 |
- 0.942 |
- 0.93 |
- 0.933 |
- 0.924 |
- 0.919 |
- 0.934 |
- 0.918 |
- 0.941 |
- 0.947 |
- 0.923 |
- 0.952 |
- 0.93 |
- 0.929 |
- 0.941 |
- 0.937 |
- 0.925 |
- 0.886 |
- 0.925 |
- 0.89 |
- 0.941 |
- 0.921 |
- 0.922 |
- 0.918 |
- 0.916 |
- 0.929 |
- 0.942 |
- 0.935 |
- 0.926 |
- 0.94 |
- 0.96 |
- 0.938 |
- 0.928 |
- 0.933 |
- 0.924 |
- 0.931 |
- 0.922 |
- 0.927 |
- 0.928 |
- 0.942 |
- 0.942 |
- 0.926 |
- 0.925 |
- 0.936 |
- 0.938 |
- 0.915 |
- 0.939 |
- 0.917 |
- 0.948 |
- 0.928 |
- 0.939 |
- 0.933 |
- 0.952 |
- 0.923 |
- 0.92 |
- 0.929 |
- 0.932 |
- 0.94 |
- 0.954 |
- 0.901 |
- 0.917 |
- 0.936 |
- 0.923 |
- 0.941 |
- 0.919 |
- 0.944 |
- 0.928 |
- 0.932 |
- 0.935 |
- 0.959 |
- 0.931 |
- 0.947 |
- 0.929 |
- 0.933 |
- 0.936 |
- 0.917 |
- 0.932 |
- 0.933 |
- 0.928 |
- 0.94 |
- 0.938 |
- 0.911 |
- 0.926 |
- 0.96 |
- 0.941 |
- 0.923 |
- 0.931 |
- 0.938 |
- 0.929 |
- 1 |
- 0.926 |
- 0.945 |
- 0.939 |
- 0.933 |
- 0.923 |
- 0.89 |
- 0.918 |
- 0.913 |
- |
- 0.886 |
- 0.93 |
-
-
- | Liver |
- 182 |
- F |
- 305 |
- 050914.05 |
- HF |
- BXD99 |
- H1355 |
- 0.99 |
- 0.922 |
- 0.924 |
- 0.985 |
- 0.98 |
- 0.981 |
- 0.988 |
- 0.958 |
- 0.88 |
- 0.982 |
- 0.973 |
- 0.982 |
- 0.978 |
- 0.981 |
- 0.968 |
- 0.976 |
- 0.967 |
- 0.957 |
- 0.983 |
- 0.982 |
- 0.975 |
- 0.986 |
- 0.987 |
- 0.986 |
- 0.974 |
- 0.97 |
- 0.971 |
- 0.972 |
- 0.985 |
- 0.984 |
- 0.985 |
- 0.98 |
- 0.948 |
- 0.977 |
- 0.98 |
- 0.974 |
- 0.931 |
- 0.988 |
- 0.979 |
- 0.984 |
- 0.982 |
- 0.985 |
- 0.981 |
- 0.988 |
- 0.979 |
- 0.94 |
- 0.985 |
- 0.982 |
- 0.987 |
- 0.983 |
- 0.984 |
- 0.96 |
- 0.974 |
- 0.979 |
- 0.986 |
- 0.984 |
- 0.974 |
- 0.976 |
- 0.983 |
- 0.983 |
- 0.978 |
- 0.968 |
- 0.979 |
- 0.899 |
- 0.979 |
- 0.981 |
- 0.973 |
- 0.983 |
- 0.958 |
- 0.936 |
- 0.983 |
- 0.932 |
- 0.986 |
- 0.988 |
- 0.979 |
- 0.983 |
- 0.97 |
- 0.991 |
- 0.985 |
- 0.988 |
- 0.986 |
- 0.987 |
- 0.972 |
- 0.982 |
- 0.983 |
- 0.961 |
- 0.985 |
- 0.988 |
- 0.967 |
- 0.982 |
- 0.982 |
- 0.983 |
- 0.982 |
- 0.979 |
- 0.979 |
- 0.983 |
- 0.986 |
- 0.967 |
- 0.98 |
- 0.972 |
- 0.981 |
- 0.983 |
- 0.968 |
- 0.975 |
- 0.98 |
- 0.985 |
- 0.981 |
- 0.988 |
- 0.983 |
- 0.981 |
- 0.953 |
- 0.972 |
- 0.981 |
- 0.968 |
- 0.981 |
- 0.973 |
- 0.985 |
- 0.982 |
- 0.984 |
- 0.987 |
- 0.983 |
- 0.974 |
- 0.979 |
- 0.966 |
- 0.985 |
- 0.985 |
- 0.984 |
- 0.969 |
- 0.979 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.986 |
- 0.98 |
- 0.984 |
- 0.977 |
- 0.987 |
- 0.983 |
- 0.983 |
- 0.987 |
- 0.985 |
- 0.926 |
- 1 |
- 0.984 |
- 0.984 |
- 0.986 |
- 0.981 |
- 0.932 |
- 0.97 |
- 0.933 |
- |
- 0.88 |
- 0.98 |
-
-
- | Liver |
- 544 |
- F |
- 309 |
- 062013.09 |
- HF |
- C57BL/6J |
- H0514 |
- 0.984 |
- 0.933 |
- 0.936 |
- 0.983 |
- 0.978 |
- 0.982 |
- 0.981 |
- 0.949 |
- 0.894 |
- 0.979 |
- 0.982 |
- 0.977 |
- 0.98 |
- 0.98 |
- 0.967 |
- 0.977 |
- 0.961 |
- 0.952 |
- 0.984 |
- 0.979 |
- 0.975 |
- 0.981 |
- 0.98 |
- 0.98 |
- 0.968 |
- 0.967 |
- 0.968 |
- 0.964 |
- 0.983 |
- 0.98 |
- 0.983 |
- 0.977 |
- 0.964 |
- 0.965 |
- 0.972 |
- 0.972 |
- 0.919 |
- 0.981 |
- 0.972 |
- 0.978 |
- 0.978 |
- 0.979 |
- 0.975 |
- 0.984 |
- 0.972 |
- 0.934 |
- 0.976 |
- 0.979 |
- 0.98 |
- 0.974 |
- 0.98 |
- 0.947 |
- 0.968 |
- 0.975 |
- 0.981 |
- 0.98 |
- 0.967 |
- 0.969 |
- 0.98 |
- 0.97 |
- 0.975 |
- 0.971 |
- 0.976 |
- 0.915 |
- 0.977 |
- 0.978 |
- 0.975 |
- 0.979 |
- 0.955 |
- 0.927 |
- 0.971 |
- 0.93 |
- 0.989 |
- 0.981 |
- 0.974 |
- 0.97 |
- 0.959 |
- 0.986 |
- 0.988 |
- 0.989 |
- 0.978 |
- 0.986 |
- 0.981 |
- 0.983 |
- 0.977 |
- 0.963 |
- 0.979 |
- 0.984 |
- 0.964 |
- 0.974 |
- 0.976 |
- 0.984 |
- 0.982 |
- 0.973 |
- 0.972 |
- 0.982 |
- 0.983 |
- 0.959 |
- 0.979 |
- 0.965 |
- 0.985 |
- 0.979 |
- 0.968 |
- 0.975 |
- 0.985 |
- 0.983 |
- 0.973 |
- 0.985 |
- 0.985 |
- 0.981 |
- 0.969 |
- 0.962 |
- 0.975 |
- 0.967 |
- 0.978 |
- 0.975 |
- 0.983 |
- 0.985 |
- 0.979 |
- 0.982 |
- 0.978 |
- 0.977 |
- 0.978 |
- 0.968 |
- 0.982 |
- 0.984 |
- 0.98 |
- 0.96 |
- 0.975 |
- 0.979 |
- 0.981 |
- 0.981 |
- 0.983 |
- 0.971 |
- 0.976 |
- 0.98 |
- 0.987 |
- 0.979 |
- 0.979 |
- 0.991 |
- 0.98 |
- 0.945 |
- 0.984 |
- 1 |
- 0.986 |
- 0.986 |
- 0.976 |
- 0.93 |
- 0.965 |
- 0.926 |
- |
- 0.894 |
- 0.97 |
-
-
- | Liver |
- 182 |
- F |
- 235 |
- 102414.06 |
- HF |
- C57BL/6J |
- H1681 |
- 0.988 |
- 0.934 |
- 0.935 |
- 0.989 |
- 0.982 |
- 0.988 |
- 0.987 |
- 0.966 |
- 0.895 |
- 0.985 |
- 0.977 |
- 0.987 |
- 0.984 |
- 0.985 |
- 0.976 |
- 0.983 |
- 0.968 |
- 0.965 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.989 |
- 0.987 |
- 0.988 |
- 0.981 |
- 0.976 |
- 0.975 |
- 0.978 |
- 0.987 |
- 0.987 |
- 0.986 |
- 0.989 |
- 0.953 |
- 0.974 |
- 0.98 |
- 0.979 |
- 0.936 |
- 0.986 |
- 0.98 |
- 0.982 |
- 0.989 |
- 0.982 |
- 0.978 |
- 0.988 |
- 0.984 |
- 0.951 |
- 0.978 |
- 0.981 |
- 0.984 |
- 0.979 |
- 0.989 |
- 0.961 |
- 0.978 |
- 0.978 |
- 0.986 |
- 0.987 |
- 0.978 |
- 0.981 |
- 0.986 |
- 0.978 |
- 0.976 |
- 0.966 |
- 0.986 |
- 0.906 |
- 0.982 |
- 0.977 |
- 0.978 |
- 0.986 |
- 0.969 |
- 0.944 |
- 0.981 |
- 0.944 |
- 0.993 |
- 0.987 |
- 0.983 |
- 0.978 |
- 0.966 |
- 0.988 |
- 0.991 |
- 0.989 |
- 0.986 |
- 0.986 |
- 0.977 |
- 0.985 |
- 0.988 |
- 0.966 |
- 0.986 |
- 0.988 |
- 0.976 |
- 0.986 |
- 0.977 |
- 0.983 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.988 |
- 0.985 |
- 0.973 |
- 0.981 |
- 0.976 |
- 0.988 |
- 0.987 |
- 0.976 |
- 0.982 |
- 0.986 |
- 0.986 |
- 0.977 |
- 0.988 |
- 0.982 |
- 0.986 |
- 0.957 |
- 0.971 |
- 0.982 |
- 0.973 |
- 0.984 |
- 0.978 |
- 0.984 |
- 0.984 |
- 0.989 |
- 0.986 |
- 0.985 |
- 0.977 |
- 0.985 |
- 0.972 |
- 0.985 |
- 0.988 |
- 0.989 |
- 0.97 |
- 0.982 |
- 0.986 |
- 0.982 |
- 0.986 |
- 0.985 |
- 0.976 |
- 0.983 |
- 0.982 |
- 0.984 |
- 0.983 |
- 0.983 |
- 0.987 |
- 0.987 |
- 0.939 |
- 0.984 |
- 0.986 |
- 1 |
- 0.989 |
- 0.985 |
- 0.944 |
- 0.969 |
- 0.943 |
- |
- 0.895 |
- 0.98 |
-
-
- | Liver |
- 214 |
- F |
- 301 |
- 101713.20 |
- HF |
- D2B6F1 |
- H1150 |
- 0.99 |
- 0.927 |
- 0.928 |
- 0.988 |
- 0.98 |
- 0.985 |
- 0.989 |
- 0.963 |
- 0.889 |
- 0.983 |
- 0.975 |
- 0.986 |
- 0.979 |
- 0.983 |
- 0.973 |
- 0.984 |
- 0.969 |
- 0.966 |
- 0.984 |
- 0.983 |
- 0.985 |
- 0.988 |
- 0.987 |
- 0.987 |
- 0.979 |
- 0.971 |
- 0.971 |
- 0.973 |
- 0.984 |
- 0.987 |
- 0.988 |
- 0.987 |
- 0.95 |
- 0.972 |
- 0.981 |
- 0.976 |
- 0.932 |
- 0.986 |
- 0.981 |
- 0.984 |
- 0.984 |
- 0.982 |
- 0.977 |
- 0.986 |
- 0.981 |
- 0.945 |
- 0.979 |
- 0.979 |
- 0.984 |
- 0.98 |
- 0.988 |
- 0.959 |
- 0.973 |
- 0.975 |
- 0.987 |
- 0.987 |
- 0.974 |
- 0.983 |
- 0.986 |
- 0.979 |
- 0.978 |
- 0.967 |
- 0.984 |
- 0.901 |
- 0.98 |
- 0.979 |
- 0.974 |
- 0.984 |
- 0.964 |
- 0.938 |
- 0.978 |
- 0.941 |
- 0.988 |
- 0.989 |
- 0.987 |
- 0.979 |
- 0.967 |
- 0.991 |
- 0.99 |
- 0.992 |
- 0.982 |
- 0.986 |
- 0.977 |
- 0.983 |
- 0.983 |
- 0.966 |
- 0.983 |
- 0.99 |
- 0.974 |
- 0.986 |
- 0.982 |
- 0.984 |
- 0.984 |
- 0.981 |
- 0.98 |
- 0.987 |
- 0.984 |
- 0.973 |
- 0.982 |
- 0.977 |
- 0.984 |
- 0.985 |
- 0.969 |
- 0.98 |
- 0.984 |
- 0.988 |
- 0.976 |
- 0.986 |
- 0.984 |
- 0.986 |
- 0.955 |
- 0.971 |
- 0.983 |
- 0.971 |
- 0.984 |
- 0.974 |
- 0.988 |
- 0.983 |
- 0.985 |
- 0.985 |
- 0.985 |
- 0.976 |
- 0.987 |
- 0.968 |
- 0.987 |
- 0.991 |
- 0.988 |
- 0.966 |
- 0.984 |
- 0.985 |
- 0.985 |
- 0.986 |
- 0.984 |
- 0.98 |
- 0.982 |
- 0.981 |
- 0.985 |
- 0.985 |
- 0.983 |
- 0.99 |
- 0.988 |
- 0.933 |
- 0.986 |
- 0.986 |
- 0.989 |
- 1 |
- 0.989 |
- 0.941 |
- 0.972 |
- 0.941 |
- |
- 0.889 |
- 0.98 |
-
-
- | Liver |
- 540 |
- F |
- 291 |
- 062013.13 |
- HF |
- D2B6F1 |
- H0642 |
- 0.984 |
- 0.917 |
- 0.917 |
- 0.982 |
- 0.976 |
- 0.983 |
- 0.986 |
- 0.97 |
- 0.882 |
- 0.976 |
- 0.963 |
- 0.985 |
- 0.975 |
- 0.978 |
- 0.97 |
- 0.98 |
- 0.967 |
- 0.965 |
- 0.977 |
- 0.978 |
- 0.986 |
- 0.985 |
- 0.987 |
- 0.983 |
- 0.978 |
- 0.97 |
- 0.969 |
- 0.974 |
- 0.979 |
- 0.985 |
- 0.989 |
- 0.985 |
- 0.935 |
- 0.975 |
- 0.982 |
- 0.971 |
- 0.935 |
- 0.986 |
- 0.983 |
- 0.981 |
- 0.98 |
- 0.979 |
- 0.974 |
- 0.983 |
- 0.985 |
- 0.953 |
- 0.973 |
- 0.976 |
- 0.983 |
- 0.978 |
- 0.986 |
- 0.965 |
- 0.971 |
- 0.971 |
- 0.985 |
- 0.985 |
- 0.972 |
- 0.984 |
- 0.983 |
- 0.977 |
- 0.974 |
- 0.951 |
- 0.981 |
- 0.888 |
- 0.976 |
- 0.976 |
- 0.968 |
- 0.981 |
- 0.963 |
- 0.938 |
- 0.976 |
- 0.943 |
- 0.983 |
- 0.986 |
- 0.994 |
- 0.977 |
- 0.968 |
- 0.984 |
- 0.984 |
- 0.987 |
- 0.98 |
- 0.978 |
- 0.965 |
- 0.976 |
- 0.979 |
- 0.961 |
- 0.98 |
- 0.987 |
- 0.978 |
- 0.983 |
- 0.977 |
- 0.978 |
- 0.979 |
- 0.98 |
- 0.978 |
- 0.982 |
- 0.974 |
- 0.973 |
- 0.976 |
- 0.975 |
- 0.976 |
- 0.981 |
- 0.962 |
- 0.979 |
- 0.98 |
- 0.988 |
- 0.972 |
- 0.979 |
- 0.975 |
- 0.978 |
- 0.944 |
- 0.976 |
- 0.983 |
- 0.976 |
- 0.981 |
- 0.968 |
- 0.983 |
- 0.973 |
- 0.982 |
- 0.979 |
- 0.978 |
- 0.968 |
- 0.981 |
- 0.963 |
- 0.985 |
- 0.989 |
- 0.987 |
- 0.967 |
- 0.982 |
- 0.984 |
- 0.985 |
- 0.978 |
- 0.974 |
- 0.981 |
- 0.978 |
- 0.973 |
- 0.975 |
- 0.985 |
- 0.98 |
- 0.984 |
- 0.987 |
- 0.923 |
- 0.981 |
- 0.976 |
- 0.985 |
- 0.989 |
- 1 |
- 0.943 |
- 0.964 |
- 0.945 |
- |
- 0.882 |
- 0.97 |
-
-
- | Liver |
- 212 |
- F |
- 16 |
- 101713.11 |
- HF |
- DBA/2J |
- H1144 |
- 0.935 |
- 0.931 |
- 0.929 |
- 0.935 |
- 0.942 |
- 0.94 |
- 0.938 |
- 0.964 |
- 0.922 |
- 0.943 |
- 0.922 |
- 0.954 |
- 0.934 |
- 0.938 |
- 0.952 |
- 0.937 |
- 0.958 |
- 0.962 |
- 0.939 |
- 0.935 |
- 0.928 |
- 0.941 |
- 0.945 |
- 0.946 |
- 0.964 |
- 0.967 |
- 0.967 |
- 0.969 |
- 0.943 |
- 0.938 |
- 0.941 |
- 0.94 |
- 0.9 |
- 0.953 |
- 0.954 |
- 0.961 |
- 0.976 |
- 0.944 |
- 0.96 |
- 0.945 |
- 0.946 |
- 0.934 |
- 0.944 |
- 0.939 |
- 0.954 |
- 0.96 |
- 0.927 |
- 0.935 |
- 0.942 |
- 0.95 |
- 0.941 |
- 0.976 |
- 0.967 |
- 0.935 |
- 0.943 |
- 0.938 |
- 0.961 |
- 0.935 |
- 0.945 |
- 0.946 |
- 0.932 |
- 0.911 |
- 0.959 |
- 0.863 |
- 0.935 |
- 0.935 |
- 0.957 |
- 0.94 |
- 0.974 |
- 0.976 |
- 0.958 |
- 1 |
- 0.936 |
- 0.938 |
- 0.952 |
- 0.946 |
- 0.96 |
- 0.935 |
- 0.942 |
- 0.944 |
- 0.94 |
- 0.93 |
- 0.923 |
- 0.931 |
- 0.95 |
- 0.955 |
- 0.945 |
- 0.939 |
- 0.962 |
- 0.942 |
- 0.932 |
- 0.942 |
- 0.947 |
- 0.951 |
- 0.95 |
- 0.948 |
- 0.939 |
- 0.973 |
- 0.958 |
- 0.97 |
- 0.931 |
- 0.95 |
- 0.955 |
- 0.953 |
- 0.93 |
- 0.936 |
- 0.939 |
- 0.936 |
- 0.931 |
- 0.949 |
- 0.903 |
- 0.958 |
- 0.949 |
- 0.945 |
- 0.953 |
- 0.957 |
- 0.946 |
- 0.926 |
- 0.938 |
- 0.938 |
- 0.94 |
- 0.928 |
- 0.941 |
- 0.945 |
- 0.954 |
- 0.945 |
- 0.937 |
- 0.97 |
- 0.942 |
- 0.954 |
- 0.936 |
- 0.949 |
- 0.939 |
- 0.945 |
- 0.941 |
- 0.927 |
- 0.927 |
- 0.948 |
- 0.959 |
- 0.933 |
- 0.951 |
- 0.89 |
- 0.932 |
- 0.93 |
- 0.944 |
- 0.941 |
- 0.943 |
- 1 |
- 0.957 |
- 0.968 |
- |
- 0.863 |
- 0.94 |
-
-
- | Liver |
- 544 |
- M |
- 181 |
- 091914.07 |
- HF |
- DBA/2J |
- H1140 |
- 0.969 |
- 0.935 |
- 0.937 |
- 0.967 |
- 0.961 |
- 0.969 |
- 0.966 |
- 0.964 |
- 0.903 |
- 0.968 |
- 0.96 |
- 0.977 |
- 0.961 |
- 0.966 |
- 0.964 |
- 0.97 |
- 0.973 |
- 0.99 |
- 0.977 |
- 0.968 |
- 0.96 |
- 0.971 |
- 0.968 |
- 0.973 |
- 0.977 |
- 0.971 |
- 0.972 |
- 0.977 |
- 0.971 |
- 0.966 |
- 0.966 |
- 0.965 |
- 0.94 |
- 0.965 |
- 0.974 |
- 0.977 |
- 0.944 |
- 0.97 |
- 0.975 |
- 0.973 |
- 0.977 |
- 0.969 |
- 0.969 |
- 0.971 |
- 0.972 |
- 0.946 |
- 0.958 |
- 0.962 |
- 0.972 |
- 0.968 |
- 0.972 |
- 0.965 |
- 0.977 |
- 0.959 |
- 0.97 |
- 0.966 |
- 0.977 |
- 0.969 |
- 0.974 |
- 0.973 |
- 0.959 |
- 0.957 |
- 0.977 |
- 0.888 |
- 0.967 |
- 0.963 |
- 0.979 |
- 0.97 |
- 0.969 |
- 0.954 |
- 0.974 |
- 0.957 |
- 0.966 |
- 0.966 |
- 0.968 |
- 0.973 |
- 0.974 |
- 0.969 |
- 0.976 |
- 0.978 |
- 0.965 |
- 0.969 |
- 0.96 |
- 0.968 |
- 0.978 |
- 0.976 |
- 0.971 |
- 0.97 |
- 0.969 |
- 0.975 |
- 0.978 |
- 0.978 |
- 0.979 |
- 0.971 |
- 0.971 |
- 0.974 |
- 0.977 |
- 0.973 |
- 0.975 |
- 0.976 |
- 0.969 |
- 0.975 |
- 0.97 |
- 0.967 |
- 0.963 |
- 0.963 |
- 0.97 |
- 0.976 |
- 0.969 |
- 0.974 |
- 0.935 |
- 0.964 |
- 0.972 |
- 0.961 |
- 0.969 |
- 0.979 |
- 0.974 |
- 0.968 |
- 0.973 |
- 0.972 |
- 0.968 |
- 0.958 |
- 0.968 |
- 0.963 |
- 0.976 |
- 0.974 |
- 0.969 |
- 0.973 |
- 0.971 |
- 0.975 |
- 0.971 |
- 0.974 |
- 0.977 |
- 0.972 |
- 0.967 |
- 0.966 |
- 0.971 |
- 0.97 |
- 0.981 |
- 0.967 |
- 0.972 |
- 0.918 |
- 0.97 |
- 0.965 |
- 0.969 |
- 0.972 |
- 0.964 |
- 0.957 |
- 1 |
- 0.957 |
- |
- 0.888 |
- 0.97 |
-
-
- | Liver |
- 549 |
- F |
- 190 |
- 091914.05 |
- HF |
- DBA/2J |
- H1142 |
- 0.932 |
- 0.949 |
- 0.946 |
- 0.938 |
- 0.948 |
- 0.949 |
- 0.94 |
- 0.965 |
- 0.941 |
- 0.94 |
- 0.932 |
- 0.949 |
- 0.938 |
- 0.935 |
- 0.957 |
- 0.942 |
- 0.959 |
- 0.972 |
- 0.944 |
- 0.938 |
- 0.94 |
- 0.938 |
- 0.942 |
- 0.945 |
- 0.96 |
- 0.968 |
- 0.967 |
- 0.963 |
- 0.948 |
- 0.94 |
- 0.936 |
- 0.947 |
- 0.915 |
- 0.944 |
- 0.947 |
- 0.967 |
- 0.975 |
- 0.938 |
- 0.951 |
- 0.937 |
- 0.942 |
- 0.935 |
- 0.932 |
- 0.939 |
- 0.957 |
- 0.973 |
- 0.933 |
- 0.942 |
- 0.935 |
- 0.952 |
- 0.943 |
- 0.969 |
- 0.968 |
- 0.943 |
- 0.941 |
- 0.94 |
- 0.963 |
- 0.934 |
- 0.945 |
- 0.949 |
- 0.934 |
- 0.919 |
- 0.952 |
- 0.883 |
- 0.929 |
- 0.929 |
- 0.963 |
- 0.941 |
- 0.971 |
- 0.972 |
- 0.959 |
- 0.968 |
- 0.935 |
- 0.94 |
- 0.953 |
- 0.949 |
- 0.963 |
- 0.934 |
- 0.948 |
- 0.946 |
- 0.942 |
- 0.935 |
- 0.938 |
- 0.936 |
- 0.954 |
- 0.958 |
- 0.943 |
- 0.94 |
- 0.96 |
- 0.946 |
- 0.939 |
- 0.947 |
- 0.953 |
- 0.949 |
- 0.948 |
- 0.951 |
- 0.941 |
- 0.971 |
- 0.96 |
- 0.967 |
- 0.941 |
- 0.948 |
- 0.966 |
- 0.957 |
- 0.943 |
- 0.931 |
- 0.934 |
- 0.933 |
- 0.924 |
- 0.955 |
- 0.913 |
- 0.946 |
- 0.943 |
- 0.959 |
- 0.949 |
- 0.963 |
- 0.933 |
- 0.935 |
- 0.943 |
- 0.944 |
- 0.947 |
- 0.944 |
- 0.947 |
- 0.958 |
- 0.952 |
- 0.945 |
- 0.94 |
- 0.97 |
- 0.943 |
- 0.953 |
- 0.937 |
- 0.955 |
- 0.941 |
- 0.933 |
- 0.939 |
- 0.944 |
- 0.93 |
- 0.944 |
- 0.96 |
- 0.931 |
- 0.944 |
- 0.913 |
- 0.933 |
- 0.926 |
- 0.943 |
- 0.941 |
- 0.945 |
- 0.968 |
- 0.957 |
- 1 |
- |
- 0.883 |
- 0.95 |
-
-
- | |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
- |
-
-
- | |
- |
- |
- |
- |
- |
- |
- Min |
- 0.877 |
- 0.914 |
- 0.914 |
- 0.894 |
- 0.907 |
- 0.913 |
- 0.877 |
- 0.879 |
- 0.877 |
- 0.894 |
- 0.917 |
- 0.897 |
- 0.897 |
- 0.887 |
- 0.919 |
- 0.902 |
- 0.896 |
- 0.88 |
- 0.905 |
- 0.903 |
- 0.885 |
- 0.886 |
- 0.884 |
- 0.889 |
- 0.89 |
- 0.903 |
- 0.904 |
- 0.89 |
- 0.907 |
- 0.891 |
- 0.883 |
- 0.894 |
- 0.9 |
- 0.884 |
- 0.883 |
- 0.91 |
- 0.875 |
- 0.884 |
- 0.89 |
- 0.888 |
- 0.893 |
- 0.888 |
- 0.888 |
- 0.887 |
- 0.889 |
- 0.9 |
- 0.883 |
- 0.903 |
- 0.884 |
- 0.9 |
- 0.893 |
- 0.877 |
- 0.901 |
- 0.91 |
- 0.892 |
- 0.891 |
- 0.898 |
- 0.878 |
- 0.901 |
- 0.896 |
- 0.894 |
- 0.901 |
- 0.893 |
- 0.863 |
- 0.882 |
- 0.884 |
- 0.917 |
- 0.893 |
- 0.899 |
- 0.863 |
- 0.901 |
- 0.863 |
- 0.894 |
- 0.877 |
- 0.889 |
- 0.896 |
- 0.895 |
- 0.881 |
- 0.901 |
- 0.895 |
- 0.89 |
- 0.892 |
- 0.917 |
- 0.892 |
- 0.897 |
- 0.912 |
- 0.887 |
- 0.886 |
- 0.889 |
- 0.887 |
- 0.888 |
- 0.908 |
- 0.913 |
- 0.9 |
- 0.9 |
- 0.896 |
- 0.904 |
- 0.888 |
- 0.915 |
- 0.89 |
- 0.905 |
- 0.899 |
- 0.916 |
- 0.904 |
- 0.907 |
- 0.878 |
- 0.891 |
- 0.882 |
- 0.88 |
- 0.915 |
- 0.896 |
- 0.88 |
- 0.889 |
- 0.905 |
- 0.889 |
- 0.917 |
- 0.88 |
- 0.895 |
- 0.885 |
- 0.889 |
- 0.894 |
- 0.919 |
- 0.892 |
- 0.926 |
- 0.898 |
- 0.892 |
- 0.892 |
- 0.891 |
- 0.903 |
- 0.904 |
- 0.889 |
- 0.915 |
- 0.904 |
- 0.879 |
- 0.88 |
- 0.918 |
- 0.889 |
- 0.884 |
- 0.902 |
- 0.888 |
- 0.892 |
- 0.886 |
- 0.88 |
- 0.894 |
- 0.895 |
- 0.889 |
- 0.882 |
- 0.863 |
- 0.888 |
- 0.883 |
- |
- min |
- average |
-
-
- | |
- |
- |
- |
- |
- |
- |
- Average |
- 0.97756 |
- 0.93466 |
- 0.93572 |
- 0.977506667 |
- 0.973973333 |
- 0.977946667 |
- 0.975493333 |
- 0.963486667 |
- 0.90262 |
- 0.97514 |
- 0.968173333 |
- 0.97762 |
- 0.972413333 |
- 0.974673333 |
- 0.969886667 |
- 0.973686667 |
- 0.969613333 |
- 0.961593333 |
- 0.976486667 |
- 0.975906667 |
- 0.96964 |
- 0.97762 |
- 0.976953333 |
- 0.978366667 |
- 0.974806667 |
- 0.972206667 |
- 0.972566667 |
- 0.972233333 |
- 0.97908 |
- 0.97666 |
- 0.97576 |
- 0.97558 |
- 0.946613333 |
- 0.9703 |
- 0.97476 |
- 0.97526 |
- 0.941373333 |
- 0.97684 |
- 0.975266667 |
- 0.9745 |
- 0.976933333 |
- 0.974533333 |
- 0.9729 |
- 0.977533333 |
- 0.975493333 |
- 0.9497 |
- 0.9698 |
- 0.973826667 |
- 0.975773333 |
- 0.973746667 |
- 0.97796 |
- 0.962326667 |
- 0.975153333 |
- 0.9728 |
- 0.977426667 |
- 0.97666 |
- 0.974006667 |
- 0.969673333 |
- 0.978873333 |
- 0.975313333 |
- 0.968826667 |
- 0.959866667 |
- 0.975613333 |
- 0.90348 |
- 0.972453333 |
- 0.971593333 |
- 0.973173333 |
- 0.97614 |
- 0.966853333 |
- 0.945306667 |
- 0.975946667 |
- 0.94446 |
- 0.97698 |
- 0.975493333 |
- 0.974506667 |
- 0.975313333 |
- 0.970326667 |
- 0.9773 |
- 0.979746667 |
- 0.979673333 |
- 0.97476 |
- 0.975386667 |
- 0.967573333 |
- 0.9728 |
- 0.977166667 |
- 0.96468 |
- 0.976573333 |
- 0.97796 |
- 0.970653333 |
- 0.974686667 |
- 0.972506667 |
- 0.977466667 |
- 0.977986667 |
- 0.975166667 |
- 0.974586667 |
- 0.977833333 |
- 0.976026667 |
- 0.970193333 |
- 0.976033333 |
- 0.972746667 |
- 0.9761 |
- 0.976293333 |
- 0.970913333 |
- 0.973486667 |
- 0.974113333 |
- 0.974686667 |
- 0.97198 |
- 0.975646667 |
- 0.97186 |
- 0.97794 |
- 0.946553333 |
- 0.967726667 |
- 0.97422 |
- 0.966993333 |
- 0.974926667 |
- 0.973173333 |
- 0.974446667 |
- 0.97308 |
- 0.975346667 |
- 0.975633333 |
- 0.97448 |
- 0.969666667 |
- 0.9739 |
- 0.96608 |
- 0.978153333 |
- 0.97868 |
- 0.976826667 |
- 0.969986667 |
- 0.97468 |
- 0.97894 |
- 0.97516 |
- 0.97794 |
- 0.976026667 |
- 0.971426667 |
- 0.972306667 |
- 0.972466667 |
- 0.973773333 |
- 0.97452 |
- 0.978466667 |
- 0.975233333 |
- 0.977166667 |
- 0.930506667 |
- 0.975353333 |
- 0.9727 |
- 0.978113333 |
- 0.9772 |
- 0.973826667 |
- 0.94446 |
- 0.967473333 |
- 0.946173333 |
- |
- 0.90262 |
- 0.970757511 |
-
-
-
diff --git a/general/datasets/UTHSC_BXD_Harv_Liv_1019/specifics.rtf b/general/datasets/UTHSC_BXD_Harv_Liv_1019/specifics.rtf
deleted file mode 100644
index 402ed9c..0000000
--- a/general/datasets/UTHSC_BXD_Harv_Liv_1019/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-TPM Log2
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_Harv_Liv_1019/summary.rtf b/general/datasets/UTHSC_BXD_Harv_Liv_1019/summary.rtf
deleted file mode 100644
index 153d98d..0000000
--- a/general/datasets/UTHSC_BXD_Harv_Liv_1019/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In working progress...
diff --git a/general/datasets/UTHSC_BXD_Harv_Liv_TPM_log2_1019/specifics.rtf b/general/datasets/UTHSC_BXD_Harv_Liv_TPM_log2_1019/specifics.rtf
deleted file mode 100644
index a316cd4..0000000
--- a/general/datasets/UTHSC_BXD_Harv_Liv_TPM_log2_1019/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-UTHSC BXD Liver RNA-Seq Avg (Oct19) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_Harv_Liv_TPM_log2_1019/summary.rtf b/general/datasets/UTHSC_BXD_Harv_Liv_TPM_log2_1019/summary.rtf
deleted file mode 100644
index 3ef9ac2..0000000
--- a/general/datasets/UTHSC_BXD_Harv_Liv_TPM_log2_1019/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-UTHSC BXD Liver RNA-Seq Avg (Oct19) TPM Log2
diff --git a/general/datasets/UTHSC_BXD_Hip_PostD7CtrlBS_1121/specifics.rtf b/general/datasets/UTHSC_BXD_Hip_PostD7CtrlBS_1121/specifics.rtf
deleted file mode 100644
index 2a8ed1d..0000000
--- a/general/datasets/UTHSC_BXD_Hip_PostD7CtrlBS_1121/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-BXD Hippocampus Postnatal Day 7 Control Both Sexes
diff --git a/general/datasets/UTHSC_BXD_Hip_PostD7CtrlBS_1121/summary.rtf b/general/datasets/UTHSC_BXD_Hip_PostD7CtrlBS_1121/summary.rtf
deleted file mode 100644
index 739e3b7..0000000
--- a/general/datasets/UTHSC_BXD_Hip_PostD7CtrlBS_1121/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Affymetrix Genechip Mouse Clariom S was used to examine gene expression (Affymetrix, California, United States). Two hundred nanograms of DNased total RNA was amplified, labeled, and fragmented using Ambion Whole Transcript (WT) Expression Kit according to manufacturer’s protocol (Thermo Fisher Scientific, Santa Clara, California United States). Briefly, samples are hybridized overnight according to manufacturer’s protocols; samples are then washed and stained on Affymetrix GeneChip Fluidics Station 450 (Affymetrix, California, United States). Samples were then scanned using the GeneChip Scanner 3000 (Applied Biosystems, California, United States). Data was normalized and analyzed for quality control in Affymetrix Expression Console Software using RMA-sketch normalization (Affymetrix, California, United States). After normalization and quality control, a total number of 22,203 probe sets were used for subsequent data analysis. A total of 128 samples were used—4 samples per treatment (control, ethanol), sex (male, female), and strain (B6, D2, BXD2, BXD48a, BXD60, BXD71, BXD73, BXD100).
diff --git a/general/datasets/UTHSC_BXD_Hip_PostD7EtohBS_1121/specifics.rtf b/general/datasets/UTHSC_BXD_Hip_PostD7EtohBS_1121/specifics.rtf
deleted file mode 100644
index ebc4e0d..0000000
--- a/general/datasets/UTHSC_BXD_Hip_PostD7EtohBS_1121/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-BXD Hippocampus Postnatal Day 7 Ethanol Both Sexes
diff --git a/general/datasets/UTHSC_BXD_Hip_PostD7EtohBS_1121/summary.rtf b/general/datasets/UTHSC_BXD_Hip_PostD7EtohBS_1121/summary.rtf
deleted file mode 100644
index 739e3b7..0000000
--- a/general/datasets/UTHSC_BXD_Hip_PostD7EtohBS_1121/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Affymetrix Genechip Mouse Clariom S was used to examine gene expression (Affymetrix, California, United States). Two hundred nanograms of DNased total RNA was amplified, labeled, and fragmented using Ambion Whole Transcript (WT) Expression Kit according to manufacturer’s protocol (Thermo Fisher Scientific, Santa Clara, California United States). Briefly, samples are hybridized overnight according to manufacturer’s protocols; samples are then washed and stained on Affymetrix GeneChip Fluidics Station 450 (Affymetrix, California, United States). Samples were then scanned using the GeneChip Scanner 3000 (Applied Biosystems, California, United States). Data was normalized and analyzed for quality control in Affymetrix Expression Console Software using RMA-sketch normalization (Affymetrix, California, United States). After normalization and quality control, a total number of 22,203 probe sets were used for subsequent data analysis. A total of 128 samples were used—4 samples per treatment (control, ethanol), sex (male, female), and strain (B6, D2, BXD2, BXD48a, BXD60, BXD71, BXD73, BXD100).
diff --git a/general/datasets/UTHSC_BXD_Hip_miRNASeq0214/specifics.rtf b/general/datasets/UTHSC_BXD_Hip_miRNASeq0214/specifics.rtf
deleted file mode 100644
index 280762b..0000000
--- a/general/datasets/UTHSC_BXD_Hip_miRNASeq0214/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NA
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_Hip_miRNASeq0214/summary.rtf b/general/datasets/UTHSC_BXD_Hip_miRNASeq0214/summary.rtf
deleted file mode 100644
index 1a4d656..0000000
--- a/general/datasets/UTHSC_BXD_Hip_miRNASeq0214/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This group of datasets is confidential
diff --git a/general/datasets/UTHSC_BXD_LivCDNAm_1119/experiment-design.rtf b/general/datasets/UTHSC_BXD_LivCDNAm_1119/experiment-design.rtf
deleted file mode 100644
index 5c63e07..0000000
--- a/general/datasets/UTHSC_BXD_LivCDNAm_1119/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Aging
diff --git a/general/datasets/UTHSC_BXD_LivCDNAm_1119/platform.rtf b/general/datasets/UTHSC_BXD_LivCDNAm_1119/platform.rtf
deleted file mode 100644
index 01ea9ea..0000000
--- a/general/datasets/UTHSC_BXD_LivCDNAm_1119/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Pan-Mammalian DNAm Infinium array; this is a custom array
diff --git a/general/datasets/UTHSC_BXD_LivCDNAm_1119/processing.rtf b/general/datasets/UTHSC_BXD_LivCDNAm_1119/processing.rtf
deleted file mode 100644
index 5dc0f7f..0000000
--- a/general/datasets/UTHSC_BXD_LivCDNAm_1119/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Beta-values after normalization
diff --git a/general/datasets/UTHSC_BXD_LivCDNAm_1119/specifics.rtf b/general/datasets/UTHSC_BXD_LivCDNAm_1119/specifics.rtf
deleted file mode 100644
index cf79575..0000000
--- a/general/datasets/UTHSC_BXD_LivCDNAm_1119/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NIA-UTHSC BXD Liver CD DNAm (Nov20) Sesame
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_LivCDNAm_1119/summary.rtf b/general/datasets/UTHSC_BXD_LivCDNAm_1119/summary.rtf
deleted file mode 100644
index 0961144..0000000
--- a/general/datasets/UTHSC_BXD_LivCDNAm_1119/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DNA from liver tissue profiled on the Illumina Pan-Mammalian Infinium microarray. This array was designed and developed by Steve Horvath at UCLA. Array hybridization, initial data QC, and normalization done at UCLA.
diff --git a/general/datasets/UTHSC_BXD_LivDNAm_1119/experiment-design.rtf b/general/datasets/UTHSC_BXD_LivDNAm_1119/experiment-design.rtf
deleted file mode 100644
index 5c63e07..0000000
--- a/general/datasets/UTHSC_BXD_LivDNAm_1119/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Aging
diff --git a/general/datasets/UTHSC_BXD_LivDNAm_1119/platform.rtf b/general/datasets/UTHSC_BXD_LivDNAm_1119/platform.rtf
deleted file mode 100644
index 01ea9ea..0000000
--- a/general/datasets/UTHSC_BXD_LivDNAm_1119/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Pan-Mammalian DNAm Infinium array; this is a custom array
diff --git a/general/datasets/UTHSC_BXD_LivDNAm_1119/processing.rtf b/general/datasets/UTHSC_BXD_LivDNAm_1119/processing.rtf
deleted file mode 100644
index 5dc0f7f..0000000
--- a/general/datasets/UTHSC_BXD_LivDNAm_1119/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Beta-values after normalization
diff --git a/general/datasets/UTHSC_BXD_LivDNAm_1119/specifics.rtf b/general/datasets/UTHSC_BXD_LivDNAm_1119/specifics.rtf
deleted file mode 100644
index 06c93b7..0000000
--- a/general/datasets/UTHSC_BXD_LivDNAm_1119/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NIA-UTHSC BXD Liver CD-HFD DNAm (Nov20) Sesame
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_LivDNAm_1119/summary.rtf b/general/datasets/UTHSC_BXD_LivDNAm_1119/summary.rtf
deleted file mode 100644
index 0961144..0000000
--- a/general/datasets/UTHSC_BXD_LivDNAm_1119/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DNA from liver tissue profiled on the Illumina Pan-Mammalian Infinium microarray. This array was designed and developed by Steve Horvath at UCLA. Array hybridization, initial data QC, and normalization done at UCLA.
diff --git a/general/datasets/UTHSC_BXD_LivHFDNAm_1119/experiment-design.rtf b/general/datasets/UTHSC_BXD_LivHFDNAm_1119/experiment-design.rtf
deleted file mode 100644
index 5c63e07..0000000
--- a/general/datasets/UTHSC_BXD_LivHFDNAm_1119/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Aging
diff --git a/general/datasets/UTHSC_BXD_LivHFDNAm_1119/platform.rtf b/general/datasets/UTHSC_BXD_LivHFDNAm_1119/platform.rtf
deleted file mode 100644
index 01ea9ea..0000000
--- a/general/datasets/UTHSC_BXD_LivHFDNAm_1119/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Pan-Mammalian DNAm Infinium array; this is a custom array
diff --git a/general/datasets/UTHSC_BXD_LivHFDNAm_1119/processing.rtf b/general/datasets/UTHSC_BXD_LivHFDNAm_1119/processing.rtf
deleted file mode 100644
index 5dc0f7f..0000000
--- a/general/datasets/UTHSC_BXD_LivHFDNAm_1119/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Beta-values after normalization
diff --git a/general/datasets/UTHSC_BXD_LivHFDNAm_1119/specifics.rtf b/general/datasets/UTHSC_BXD_LivHFDNAm_1119/specifics.rtf
deleted file mode 100644
index b8b1955..0000000
--- a/general/datasets/UTHSC_BXD_LivHFDNAm_1119/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-NIA-UTHSC BXD Liver HFD DNAm (Nov20) Sesame
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_LivHFDNAm_1119/summary.rtf b/general/datasets/UTHSC_BXD_LivHFDNAm_1119/summary.rtf
deleted file mode 100644
index 0961144..0000000
--- a/general/datasets/UTHSC_BXD_LivHFDNAm_1119/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-DNA from liver tissue profiled on the Illumina Pan-Mammalian Infinium microarray. This array was designed and developed by Steve Horvath at UCLA. Array hybridization, initial data QC, and normalization done at UCLA.
diff --git a/general/datasets/UTHSC_BXD_Liv_0818/specifics.rtf b/general/datasets/UTHSC_BXD_Liv_0818/specifics.rtf
deleted file mode 100644
index 342d36e..0000000
--- a/general/datasets/UTHSC_BXD_Liv_0818/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-2nd set
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_Liv_0818/summary.rtf b/general/datasets/UTHSC_BXD_Liv_0818/summary.rtf
deleted file mode 100644
index 790afd7..0000000
--- a/general/datasets/UTHSC_BXD_Liv_0818/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In working progress
diff --git a/general/datasets/UTHSC_BXD_Liv_0917/specifics.rtf b/general/datasets/UTHSC_BXD_Liv_0917/specifics.rtf
deleted file mode 100644
index 0b70afe..0000000
--- a/general/datasets/UTHSC_BXD_Liv_0917/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Gene Level
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_Liv_0917/summary.rtf b/general/datasets/UTHSC_BXD_Liv_0917/summary.rtf
deleted file mode 100644
index 790afd7..0000000
--- a/general/datasets/UTHSC_BXD_Liv_0917/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In working progress
diff --git a/general/datasets/UTHSC_BXD_MamGland_ca_0322/specifics.rtf b/general/datasets/UTHSC_BXD_MamGland_ca_0322/specifics.rtf
deleted file mode 100644
index 81e1218..0000000
--- a/general/datasets/UTHSC_BXD_MamGland_ca_0322/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-UTHSC BXD Triple Negative Breast Cancer Model RNA-Seq (Mar22) Count All Samples
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_MamGland_ca_0322/summary.rtf b/general/datasets/UTHSC_BXD_MamGland_ca_0322/summary.rtf
deleted file mode 100644
index 4e4269c..0000000
--- a/general/datasets/UTHSC_BXD_MamGland_ca_0322/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is currently unpublished. Please refer to the contact information above if you want to use this data.
diff --git a/general/datasets/UTHSC_BXD_MamGland_cpmNtum_0322/specifics.rtf b/general/datasets/UTHSC_BXD_MamGland_cpmNtum_0322/specifics.rtf
deleted file mode 100644
index 4d79eab..0000000
--- a/general/datasets/UTHSC_BXD_MamGland_cpmNtum_0322/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-UTHSC BXD Triple Negative Breast Cancer Model RNA-Seq (Mar22) CPM Norm Tumor Only
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_MamGland_cpmNtum_0322/summary.rtf b/general/datasets/UTHSC_BXD_MamGland_cpmNtum_0322/summary.rtf
deleted file mode 100644
index 4e4269c..0000000
--- a/general/datasets/UTHSC_BXD_MamGland_cpmNtum_0322/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is currently unpublished. Please refer to the contact information above if you want to use this data.
diff --git a/general/datasets/UTHSC_BXD_MamGland_cpm_0322/specifics.rtf b/general/datasets/UTHSC_BXD_MamGland_cpm_0322/specifics.rtf
deleted file mode 100644
index 3b28a0d..0000000
--- a/general/datasets/UTHSC_BXD_MamGland_cpm_0322/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-UTHSC BXD Triple Negative Breast Cancer Model RNA-Seq (Mar22) CPM Norm All Samples
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_MamGland_cpm_0322/summary.rtf b/general/datasets/UTHSC_BXD_MamGland_cpm_0322/summary.rtf
deleted file mode 100644
index 4e4269c..0000000
--- a/general/datasets/UTHSC_BXD_MamGland_cpm_0322/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is currently unpublished. Please refer to the contact information above if you want to use this data.
diff --git a/general/datasets/UTHSC_BXD_MamGland_tum_0322/specifics.rtf b/general/datasets/UTHSC_BXD_MamGland_tum_0322/specifics.rtf
deleted file mode 100644
index bc15cdf..0000000
--- a/general/datasets/UTHSC_BXD_MamGland_tum_0322/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-UTHSC BXD Triple Negative Breast Cancer Model RNA-Seq (Mar22) Counts Tumor Only
\ No newline at end of file
diff --git a/general/datasets/UTHSC_BXD_MamGland_tum_0322/summary.rtf b/general/datasets/UTHSC_BXD_MamGland_tum_0322/summary.rtf
deleted file mode 100644
index 4e4269c..0000000
--- a/general/datasets/UTHSC_BXD_MamGland_tum_0322/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset is currently unpublished. Please refer to the contact information above if you want to use this data.
diff --git a/general/datasets/UTHSC_BXD_WB_RNASeqtrim1112/cases.rtf b/general/datasets/UTHSC_BXD_WB_RNASeqtrim1112/cases.rtf
deleted file mode 100644
index 2f0fdc0..0000000
--- a/general/datasets/UTHSC_BXD_WB_RNASeqtrim1112/cases.rtf
+++ /dev/null
@@ -1,245 +0,0 @@
-
-
-
-
-
-
-
-
- | Index |
- Original Strain |
- Corrected Strain |
- Sex |
- Age |
-
-
- | 1 |
- BXD13_batch2 |
- BXD18 |
- M |
- 67 |
-
-
- | 2 |
- BXD15_batch2 |
- BXD15 |
- F |
- 62 |
-
-
- | 3 |
- BXD18_batch2 |
- BXD19 |
- F |
- 65 |
-
-
- | 4 |
- BXD24_batch2 |
- BXD24 |
- F |
- 63 |
-
-
- | 5 |
- BXD36_batch2 |
- BXD45 removed |
- M |
- 67 |
-
-
- | 6 |
- BXD39_batch2 |
- BXD39 |
- F |
- 60 |
-
-
- | 7 |
- BXD42_batch2 |
- BXD43 |
- F |
- 67 |
-
-
- | 8 |
- BXD43_batch2 |
- BXD42 |
- F |
- 60 |
-
-
- | 9 |
- BXD45_batch2 |
- BXD45 |
- F |
- 60 |
-
-
- | 10 |
- BXD50_batch2 |
- BXD50 |
- F |
- 57 |
-
-
- | 11 |
- BXD51_batch2 |
- BXD55 |
- F |
- 59 |
-
-
- | 12 |
- BXD55_batch2 |
- BXD51 |
- F |
- 61 |
-
-
- | 13 |
- BXD56_batch2 |
- BXD56 |
- F |
- 67 |
-
-
- | 14 |
- BXD6_batch2 |
- BXD6 |
- F |
- 59 |
-
-
- | 15 |
- BXD8_batch2 |
- BXD9 |
- F |
- 62 |
-
-
- | 16 |
- BXD9_batch2 |
- BXD8 |
- M |
- 70 |
-
-
- | 17 |
- BXD14_batch3 |
- BXD40 |
- F |
- 76 |
-
-
- | 18 |
- BXD16_batch3 |
- BXD19 |
- M |
- 74 |
-
-
- | 19 |
- BXD32_batch3 |
- BXD32 |
- M |
- 54 |
-
-
- | 20 |
- BXD38_batch3 |
- BXD38 |
- F |
- 102 |
-
-
- | 21 |
- BXD40_batch3 |
- BXD14 |
- M |
- 81 |
-
-
- | 22 |
- BXD48_batch3 |
- BXD48 |
- M |
- 68 |
-
-
- | 23 |
- BXD60_batch3 |
- BXD60 |
- F |
- 64 |
-
-
- | 24 |
- BXD66_batch3 |
- BXD66 |
- M |
- 61 |
-
-
- | 25 |
- BXD69_batch3 |
- BXD69 |
- F |
- 66 |
-
-
- | 26 |
- BXD70_batch3 |
- BXD70 |
- M |
- 72 |
-
-
- | 27 |
- BXD29m_batch4 |
- BXD1 |
- F |
- 60 |
-
-
- | 28 |
- BXD29n_batch4 |
- BXD29 |
- F |
- 344 |
-
-
- | 29 |
- BXD34_batch4 |
- BXD34 |
- F |
- 108 |
-
-
- | 30 |
- BXD49_batch4 |
- BXD49 |
- M |
- 76 |
-
-
- | 31 |
- BXD65_batch4 |
- BXD29 |
- F |
- 58 |
-
-
- | 32 |
- BXD22_batch6 |
- BXD22 |
- F |
- 67 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_BXD_WB_RNASeqtrim1112/notes.rtf b/general/datasets/UTHSC_BXD_WB_RNASeqtrim1112/notes.rtf
deleted file mode 100644
index c16bd50..0000000
--- a/general/datasets/UTHSC_BXD_WB_RNASeqtrim1112/notes.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-RNA sequencing for BXD strains on SOLiD by David Li.
-All Bam files alignment done by Xusheng Wang
-Aligned files were uploaded to Partek Genomic Suite 6.5 (version 6.10.0810) and processed by K Mozhui
-Normalization: RPKM (reads per kilobase per million mapped reads)
-Batch effect due to low exonic reads for batch 2
-
-Revision 1.6 Untrimmed (current) LRS=(23 999) ->350 records
-Max LRS = 102.6 Record Id:uthsc_nr_015498, Gene Symbol:1500004A13Rik **Note: 1 sample BXD45 and BXD34 removed. BXD41 switched to BXD1 as a second posible candidate.
-
-Revision 1.5 Untrimmed LRS=(23 999) ->268 records
-Max LRS = 80.0 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1 **Note: 1 sample BXD45 removed. BXD41 switched to BXD1 as a second posible candidate.
-
-Revision 1.4 Untrimmed LRS=(23 999) ->246 records
-Max LRS = 80.0 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1 **Note: 1 sample BXD45 removed and keep BXD41
-
-Revision 1.3 Untrimmed LRS=(23 999) ->233 records
-Max LRS = 80.7 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1
-
-Revision 1.2 Untrimmed LRS=(23 999) ->190 records
-Max LRS = 56.9 Record Id:uthsc_nr_003513, Gene Symbol:Neat1
-
-Revision 1 Untrimmed LRS=(23 999) ->126 records
-Max LRS = 35.3 Record Id:uthsc_nm_001113412, Gene Symbol:Fggy
diff --git a/general/datasets/UTHSC_BXD_WB_RNASeqtrim1112/summary.rtf b/general/datasets/UTHSC_BXD_WB_RNASeqtrim1112/summary.rtf
deleted file mode 100644
index 82080d4..0000000
--- a/general/datasets/UTHSC_BXD_WB_RNASeqtrim1112/summary.rtf
+++ /dev/null
@@ -1,4 +0,0 @@
-
- - UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Untrimmed
- - UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Trimmed dataset have been re-normalized by forcing values down to zero at level of individual mRNA seq assay.
-
diff --git a/general/datasets/UTHSC_BXD_WB_RNASeqtrim1_1112/cases.rtf b/general/datasets/UTHSC_BXD_WB_RNASeqtrim1_1112/cases.rtf
deleted file mode 100644
index 2f0fdc0..0000000
--- a/general/datasets/UTHSC_BXD_WB_RNASeqtrim1_1112/cases.rtf
+++ /dev/null
@@ -1,245 +0,0 @@
-
-
-
-
-
-
-
-
- | Index |
- Original Strain |
- Corrected Strain |
- Sex |
- Age |
-
-
- | 1 |
- BXD13_batch2 |
- BXD18 |
- M |
- 67 |
-
-
- | 2 |
- BXD15_batch2 |
- BXD15 |
- F |
- 62 |
-
-
- | 3 |
- BXD18_batch2 |
- BXD19 |
- F |
- 65 |
-
-
- | 4 |
- BXD24_batch2 |
- BXD24 |
- F |
- 63 |
-
-
- | 5 |
- BXD36_batch2 |
- BXD45 removed |
- M |
- 67 |
-
-
- | 6 |
- BXD39_batch2 |
- BXD39 |
- F |
- 60 |
-
-
- | 7 |
- BXD42_batch2 |
- BXD43 |
- F |
- 67 |
-
-
- | 8 |
- BXD43_batch2 |
- BXD42 |
- F |
- 60 |
-
-
- | 9 |
- BXD45_batch2 |
- BXD45 |
- F |
- 60 |
-
-
- | 10 |
- BXD50_batch2 |
- BXD50 |
- F |
- 57 |
-
-
- | 11 |
- BXD51_batch2 |
- BXD55 |
- F |
- 59 |
-
-
- | 12 |
- BXD55_batch2 |
- BXD51 |
- F |
- 61 |
-
-
- | 13 |
- BXD56_batch2 |
- BXD56 |
- F |
- 67 |
-
-
- | 14 |
- BXD6_batch2 |
- BXD6 |
- F |
- 59 |
-
-
- | 15 |
- BXD8_batch2 |
- BXD9 |
- F |
- 62 |
-
-
- | 16 |
- BXD9_batch2 |
- BXD8 |
- M |
- 70 |
-
-
- | 17 |
- BXD14_batch3 |
- BXD40 |
- F |
- 76 |
-
-
- | 18 |
- BXD16_batch3 |
- BXD19 |
- M |
- 74 |
-
-
- | 19 |
- BXD32_batch3 |
- BXD32 |
- M |
- 54 |
-
-
- | 20 |
- BXD38_batch3 |
- BXD38 |
- F |
- 102 |
-
-
- | 21 |
- BXD40_batch3 |
- BXD14 |
- M |
- 81 |
-
-
- | 22 |
- BXD48_batch3 |
- BXD48 |
- M |
- 68 |
-
-
- | 23 |
- BXD60_batch3 |
- BXD60 |
- F |
- 64 |
-
-
- | 24 |
- BXD66_batch3 |
- BXD66 |
- M |
- 61 |
-
-
- | 25 |
- BXD69_batch3 |
- BXD69 |
- F |
- 66 |
-
-
- | 26 |
- BXD70_batch3 |
- BXD70 |
- M |
- 72 |
-
-
- | 27 |
- BXD29m_batch4 |
- BXD1 |
- F |
- 60 |
-
-
- | 28 |
- BXD29n_batch4 |
- BXD29 |
- F |
- 344 |
-
-
- | 29 |
- BXD34_batch4 |
- BXD34 |
- F |
- 108 |
-
-
- | 30 |
- BXD49_batch4 |
- BXD49 |
- M |
- 76 |
-
-
- | 31 |
- BXD65_batch4 |
- BXD29 |
- F |
- 58 |
-
-
- | 32 |
- BXD22_batch6 |
- BXD22 |
- F |
- 67 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_BXD_WB_RNASeqtrim1_1112/notes.rtf b/general/datasets/UTHSC_BXD_WB_RNASeqtrim1_1112/notes.rtf
deleted file mode 100644
index c16bd50..0000000
--- a/general/datasets/UTHSC_BXD_WB_RNASeqtrim1_1112/notes.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-RNA sequencing for BXD strains on SOLiD by David Li.
-All Bam files alignment done by Xusheng Wang
-Aligned files were uploaded to Partek Genomic Suite 6.5 (version 6.10.0810) and processed by K Mozhui
-Normalization: RPKM (reads per kilobase per million mapped reads)
-Batch effect due to low exonic reads for batch 2
-
-Revision 1.6 Untrimmed (current) LRS=(23 999) ->350 records
-Max LRS = 102.6 Record Id:uthsc_nr_015498, Gene Symbol:1500004A13Rik **Note: 1 sample BXD45 and BXD34 removed. BXD41 switched to BXD1 as a second posible candidate.
-
-Revision 1.5 Untrimmed LRS=(23 999) ->268 records
-Max LRS = 80.0 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1 **Note: 1 sample BXD45 removed. BXD41 switched to BXD1 as a second posible candidate.
-
-Revision 1.4 Untrimmed LRS=(23 999) ->246 records
-Max LRS = 80.0 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1 **Note: 1 sample BXD45 removed and keep BXD41
-
-Revision 1.3 Untrimmed LRS=(23 999) ->233 records
-Max LRS = 80.7 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1
-
-Revision 1.2 Untrimmed LRS=(23 999) ->190 records
-Max LRS = 56.9 Record Id:uthsc_nr_003513, Gene Symbol:Neat1
-
-Revision 1 Untrimmed LRS=(23 999) ->126 records
-Max LRS = 35.3 Record Id:uthsc_nm_001113412, Gene Symbol:Fggy
diff --git a/general/datasets/UTHSC_BXD_WB_RNASeqtrim1_1112/summary.rtf b/general/datasets/UTHSC_BXD_WB_RNASeqtrim1_1112/summary.rtf
deleted file mode 100644
index 82080d4..0000000
--- a/general/datasets/UTHSC_BXD_WB_RNASeqtrim1_1112/summary.rtf
+++ /dev/null
@@ -1,4 +0,0 @@
-
- - UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Untrimmed
- - UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Trimmed dataset have been re-normalized by forcing values down to zero at level of individual mRNA seq assay.
-
diff --git a/general/datasets/UTHSC_BXD_Young_Adult_Eye_RNAseq_TPM_Log/experiment-design.rtf b/general/datasets/UTHSC_BXD_Young_Adult_Eye_RNAseq_TPM_Log/experiment-design.rtf
deleted file mode 100644
index 2f8cedc..0000000
--- a/general/datasets/UTHSC_BXD_Young_Adult_Eye_RNAseq_TPM_Log/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Total RNA was extracted using Trizol® reagent (Invitrogen, Grand Island, NY, USA) according to the manufacturer’s instructions. Approximately 30 mg of PFC tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been treated with DNase to avoid DNA contamination, and verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/UTHSC_BXD_Young_Adult_Eye_RNAseq_TPM_Log/processing.rtf b/general/datasets/UTHSC_BXD_Young_Adult_Eye_RNAseq_TPM_Log/processing.rtf
deleted file mode 100644
index 8e460ff..0000000
--- a/general/datasets/UTHSC_BXD_Young_Adult_Eye_RNAseq_TPM_Log/processing.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-Generation of RNA-seq data
-
-1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
-
-
-
-Read mapping and normalization
-
-Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/UTHSC_BXD_Young_Adult_Eye_RNAseq_TPM_Log/specifics.rtf b/general/datasets/UTHSC_BXD_Young_Adult_Eye_RNAseq_TPM_Log/specifics.rtf
deleted file mode 100644
index 7e44a00..0000000
--- a/general/datasets/UTHSC_BXD_Young_Adult_Eye_RNAseq_TPM_Log/specifics.rtf
+++ /dev/null
@@ -1,3644 +0,0 @@
-BXD Eye (2~6 Month) RNA-Seq (Oct30) TPM Log2
-
-The table of samples that are finally used for this study.
-
-
-
-
- |
- Index
- |
-
- RNA ID
- |
-
- case ID
- |
-
- DA_corrected_strain
- |
-
- Fuyi_corrected_Sex
- |
-
- Age (day)
- |
-
- Tissue
- |
-
-
- |
- 1
- |
-
- E508
- |
-
- *060619.13
- |
-
- BXD170
- |
-
- Female
- |
-
- 76
- |
-
- Eyeball
- |
-
-
- |
- 2
- |
-
- E509
- |
-
- *060619.14
- |
-
- BXD170
- |
-
- Male
- |
-
- 76
- |
-
- Eyeball
- |
-
-
- |
- 3
- |
-
- E510
- |
-
- *060619.16
- |
-
- BXD194
- |
-
- Female
- |
-
- 94
- |
-
- Eyeball
- |
-
-
- |
- 4
- |
-
- E511
- |
-
- *060619.17
- |
-
- BXD194
- |
-
- Male
- |
-
- 94
- |
-
- Eyeball
- |
-
-
- |
- 5
- |
-
- E512
- |
-
- *060619.19
- |
-
- BXD213
- |
-
- Female
- |
-
- 78
- |
-
- Eyeball
- |
-
-
- |
- 6
- |
-
- E513
- |
-
- *060619.20
- |
-
- BXD213
- |
-
- Male
- |
-
- 78
- |
-
- Eyeball
- |
-
-
- |
- 7
- |
-
- E514
- |
-
- *060619.22
- |
-
- BXD214
- |
-
- Female
- |
-
- 107
- |
-
- Eyeball
- |
-
-
- |
- 8
- |
-
- E515
- |
-
- *060619.23
- |
-
- BXD214
- |
-
- Male
- |
-
- 107
- |
-
- Eyeball
- |
-
-
- |
- 9
- |
-
- E516
- |
-
- *060619.02
- |
-
- BXD125
- |
-
- Female
- |
-
- 100
- |
-
- Eyeball
- |
-
-
- |
- 10
- |
-
- E517
- |
-
- *060619.03
- |
-
- BXD125
- |
-
- Male
- |
-
- 100
- |
-
- Eyeball
- |
-
-
- |
- 11
- |
-
- E518
- |
-
- *060619.05
- |
-
- BXD151
- |
-
- Female
- |
-
- 97
- |
-
- Eyeball
- |
-
-
- |
- 12
- |
-
- E519
- |
-
- *060619.06
- |
-
- BXD151
- |
-
- Male
- |
-
- 97
- |
-
- Eyeball
- |
-
-
- |
- 13
- |
-
- E520
- |
-
- *060619.08
- |
-
- BXD154
- |
-
- Female
- |
-
- 102
- |
-
- Eyeball
- |
-
-
- |
- 14
- |
-
- E521
- |
-
- *060619.09
- |
-
- BXD154
- |
-
- Male
- |
-
- 102
- |
-
- Eyeball
- |
-
-
- |
- 15
- |
-
- E522
- |
-
- *060519.06
- |
-
- BXD27
- |
-
- Female
- |
-
- 94
- |
-
- Eyeball
- |
-
-
- |
- 16
- |
-
- E523
- |
-
- *060519.07
- |
-
- BXD27
- |
-
- Female
- |
-
- 94
- |
-
- Eyeball
- |
-
-
- |
- 17
- |
-
- E524
- |
-
- *060519.09
- |
-
- BXD60
- |
-
- Female
- |
-
- 82
- |
-
- Eyeball
- |
-
-
- |
- 18
- |
-
- E525
- |
-
- *060519.10
- |
-
- BXD60
- |
-
- Male
- |
-
- 82
- |
-
- Eyeball
- |
-
-
- |
- 19
- |
-
- E526
- |
-
- *060519.11
- |
-
- BXD66
- |
-
- Female
- |
-
- 104
- |
-
- Eyeball
- |
-
-
- |
- 20
- |
-
- E527
- |
-
- *060519.12
- |
-
- BXD66
- |
-
- Male
- |
-
- 104
- |
-
- Eyeball
- |
-
-
- |
- 21
- |
-
- E528
- |
-
- *060519.13
- |
-
- BXD68
- |
-
- Female
- |
-
- 91
- |
-
- Eyeball
- |
-
-
- |
- 22
- |
-
- E529
- |
-
- *060519.16
- |
-
- BXD73a
- |
-
- Female
- |
-
- 134
- |
-
- Eyeball
- |
-
-
- |
- 23
- |
-
- E530
- |
-
- *060519.15
- |
-
- BXD68
- |
-
- Male
- |
-
- 91
- |
-
- Eyeball
- |
-
-
- |
- 24
- |
-
- E531
- |
-
- *060519.19
- |
-
- BXD78
- |
-
- Female
- |
-
- 107
- |
-
- Eyeball
- |
-
-
- |
- 25
- |
-
- E532
- |
-
- *060519.21
- |
-
- BXD79
- |
-
- Female
- |
-
- 108
- |
-
- Eyeball
- |
-
-
- |
- 26
- |
-
- E533
- |
-
- *060519.20
- |
-
- BXD78
- |
-
- Male
- |
-
- 107
- |
-
- Eyeball
- |
-
-
- |
- 27
- |
-
- E534
- |
-
- *060519.23
- |
-
- BXD79
- |
-
- Male
- |
-
- 108
- |
-
- Eyeball
- |
-
-
- |
- 28
- |
-
- E535
- |
-
- *060519.24
- |
-
- BXD124
- |
-
- Female
- |
-
- 95
- |
-
- Eyeball
- |
-
-
- |
- 29
- |
-
- E536
- |
-
- *060519.26
- |
-
- BXD124
- |
-
- Male
- |
-
- 95
- |
-
- Eyeball
- |
-
-
- |
- 30
- |
-
- E537
- |
-
- *051119.05
- |
-
- BXD216
- |
-
- Female
- |
-
- 60
- |
-
- Eyeball
- |
-
-
- |
- 31
- |
-
- E538
- |
-
- *051119.06
- |
-
- BXD216
- |
-
- Male
- |
-
- 60
- |
-
- Eyeball
- |
-
-
- |
- 32
- |
-
- E539
- |
-
- 42415.13
- |
-
- BXD100
- |
-
- Female
- |
-
- 176
- |
-
- Eyeball
- |
-
-
- |
- 33
- |
-
- E550
- |
-
- *061119.09
- |
-
- DBA/2J
- |
-
- Male
- |
-
- 172
- |
-
- Eyeball
- |
-
-
- |
- 34
- |
-
- E597
- |
-
- *050118.27
- |
-
- DBA/2J
- |
-
- Female
- |
-
- 167
- |
-
- Eyeball
- |
-
-
- |
- 35
- |
-
- E598
- |
-
- *050118.28
- |
-
- DBA/2J
- |
-
- Female
- |
-
- 167
- |
-
- Eyeball
- |
-
-
- |
- 36
- |
-
- E599
- |
-
- *050118.29
- |
-
- DBA/2J
- |
-
- Male
- |
-
- 167
- |
-
- Eyeball
- |
-
-
- |
- 37
- |
-
- E619
- |
-
- *012420.07
- |
-
- BXD75
- |
-
- Female
- |
-
- 95
- |
-
- Eyeball
- |
-
-
- |
- 38
- |
-
- E622
- |
-
- *012420.50
- |
-
- BXD197
- |
-
- Female
- |
-
- 128
- |
-
- Eyeball
- |
-
-
- |
- 39
- |
-
- E624
- |
-
- *110918.11
- |
-
- BXD32
- |
-
- Female
- |
-
- 153
- |
-
- Eyeball
- |
-
-
- |
- 40
- |
-
- E660
- |
-
- *100819.150
- |
-
- BXD199
- |
-
- Female
- |
-
- 116
- |
-
- Eyeball
- |
-
-
- |
- 41
- |
-
- E661
- |
-
- *100819.151
- |
-
- BXD199
- |
-
- Male
- |
-
- 117
- |
-
- Eyeball
- |
-
-
- |
- 42
- |
-
- E673
- |
-
- *052920.03
- |
-
- C57BL/6J
- |
-
- Female
- |
-
- 121
- |
-
- Eyeball
- |
-
-
- |
- 43
- |
-
- E681
- |
-
- *052920.04
- |
-
- BXD73a
- |
-
- Female
- |
-
- 180
- |
-
- Eyeball
- |
-
-
- |
- 44
- |
-
- E683
- |
-
- *052920.07
- |
-
- BXD9
- |
-
- Female
- |
-
- 185
- |
-
- Eyeball
- |
-
-
- |
- 45
- |
-
- E684
- |
-
- *052920.08
- |
-
- BXD9
- |
-
- Male
- |
-
- 186
- |
-
- Eyeball
- |
-
-
- |
- 46
- |
-
- E691
- |
-
- *072120.06
- |
-
- BXD83
- |
-
- Female
- |
-
- 132
- |
-
- Eyeball
- |
-
-
- |
- 47
- |
-
- E692
- |
-
- *072120.07
- |
-
- BXD83
- |
-
- Male
- |
-
- 132
- |
-
- Eyeball
- |
-
-
- |
- 48
- |
-
- E693
- |
-
- *072120.08
- |
-
- BXD122
- |
-
- Female
- |
-
- 73
- |
-
- Eyeball
- |
-
-
- |
- 49
- |
-
- E695
- |
-
- *072120.11
- |
-
- BXD178
- |
-
- Female
- |
-
- 172
- |
-
- Eyeball
- |
-
-
- |
- 50
- |
-
- E696
- |
-
- *072120.10
- |
-
- BXD178
- |
-
- Female
- |
-
- 172
- |
-
- Eyeball
- |
-
-
- |
- 51
- |
-
- E697
- |
-
- *072120.12
- |
-
- BXD1
- |
-
- Female
- |
-
- 133
- |
-
- Eyeball
- |
-
-
- |
- 52
- |
-
- E698
- |
-
- *072120.13
- |
-
- BXD1
- |
-
- Male
- |
-
- 133
- |
-
- Eyeball
- |
-
-
- |
- 53
- |
-
- E700
- |
-
- *072120.15
- |
-
- BXD40
- |
-
- Female
- |
-
- 118
- |
-
- Eyeball
- |
-
-
- |
- 54
- |
-
- E701
- |
-
- *072120.16
- |
-
- BXD40
- |
-
- Female
- |
-
- 118
- |
-
- Eyeball
- |
-
-
- |
- 55
- |
-
- E702
- |
-
- *072120.17
- |
-
- BXD43
- |
-
- Female
- |
-
- 102
- |
-
- Eyeball
- |
-
-
- |
- 56
- |
-
- E703
- |
-
- *072120.18
- |
-
- BXD43
- |
-
- Male
- |
-
- 102
- |
-
- Eyeball
- |
-
-
- |
- 57
- |
-
- E704
- |
-
- *072120.20
- |
-
- BXD51
- |
-
- Male
- |
-
- 135
- |
-
- Eyeball
- |
-
-
- |
- 58
- |
-
- E705
- |
-
- *072120.19
- |
-
- BXD51
- |
-
- Female
- |
-
- 135
- |
-
- Eyeball
- |
-
-
- |
- 59
- |
-
- E707
- |
-
- *072120.22
- |
-
- BXD113
- |
-
- Female
- |
-
- 180
- |
-
- Eyeball
- |
-
-
- |
- 60
- |
-
- E708
- |
-
- *072120.23
- |
-
- BXD113
- |
-
- Male
- |
-
- 180
- |
-
- Eyeball
- |
-
-
- |
- 61
- |
-
- E710
- |
-
- *072120.25
- |
-
- BXD150
- |
-
- Female
- |
-
- 173
- |
-
- Eyeball
- |
-
-
- |
- 62
- |
-
- E711
- |
-
- *072120.26
- |
-
- BXD150
- |
-
- Male
- |
-
- 173
- |
-
- Eyeball
- |
-
-
- |
- 63
- |
-
- E714
- |
-
- *072120.29
- |
-
- BXD160
- |
-
- Female
- |
-
- 144
- |
-
- Eyeball
- |
-
-
- |
- 64
- |
-
- E715
- |
-
- *072120.30
- |
-
- BXD160
- |
-
- Male
- |
-
- 144
- |
-
- Eyeball
- |
-
-
- |
- 65
- |
-
- E716
- |
-
- *072120.31
- |
-
- BXD161
- |
-
- Female
- |
-
- 71
- |
-
- Eyeball
- |
-
-
- |
- 66
- |
-
- E717
- |
-
- *072120.32
- |
-
- BXD161
- |
-
- Male
- |
-
- 71
- |
-
- Eyeball
- |
-
-
- |
- 67
- |
-
- E719
- |
-
- *072120.34
- |
-
- BXD197
- |
-
- Male
- |
-
- 153
- |
-
- Eyeball
- |
-
-
- |
- 68
- |
-
- E720
- |
-
- *072120.35
- |
-
- DBA/2J-Gpnmb
- |
-
- Female
- |
-
- 97
- |
-
- Eyeball
- |
-
-
- |
- 69
- |
-
- E721
- |
-
- *072120.36
- |
-
- DBA/2J-Gpnmb
- |
-
- Male
- |
-
- 97
- |
-
- Eyeball
- |
-
-
- |
- 70
- |
-
- E724
- |
-
- *072120.39
- |
-
- BXD11
- |
-
- Female
- |
-
- 131
- |
-
- Eyeball
- |
-
-
- |
- 71
- |
-
- E725
- |
-
- *072120.40
- |
-
- BXD11
- |
-
- Male
- |
-
- 131
- |
-
- Eyeball
- |
-
-
- |
- 72
- |
-
- E729
- |
-
- *072120.44
- |
-
- BXD34
- |
-
- Female
- |
-
- 166
- |
-
- Eyeball
- |
-
-
- |
- 73
- |
-
- E730
- |
-
- *072120.45
- |
-
- BXD34
- |
-
- Female
- |
-
- 166
- |
-
- Eyeball
- |
-
-
- |
- 74
- |
-
- E731
- |
-
- *072120.46
- |
-
- BXD50
- |
-
- Female
- |
-
- 177
- |
-
- Eyeball
- |
-
-
- |
- 75
- |
-
- E732
- |
-
- *072120.47
- |
-
- BXD50
- |
-
- Male
- |
-
- 177
- |
-
- Eyeball
- |
-
-
- |
- 76
- |
-
- E736
- |
-
- *072120.51
- |
-
- BXD180
- |
-
- Female
- |
-
- 92
- |
-
- Eyeball
- |
-
-
- |
- 77
- |
-
- E743
- |
-
- *072120.58
- |
-
- BXD191
- |
-
- Female
- |
-
- 134
- |
-
- Eyeball
- |
-
-
- |
- 78
- |
-
- E744
- |
-
- *072120.59
- |
-
- BXD191
- |
-
- Male
- |
-
- 134
- |
-
- Eyeball
- |
-
-
- |
- 79
- |
-
- E747
- |
-
- *072120.62
- |
-
- B6D2F1
- |
-
- Female
- |
-
- 129
- |
-
- Eyeball
- |
-
-
- |
- 80
- |
-
- E748
- |
-
- *072120.63
- |
-
- B6D2F1
- |
-
- Male
- |
-
- 125
- |
-
- Eyeball
- |
-
-
- |
- 81
- |
-
- E751
- |
-
- *072120.66
- |
-
- BXD2
- |
-
- Female
- |
-
- 115
- |
-
- Eyeball
- |
-
-
- |
- 82
- |
-
- E752
- |
-
- *072120.67
- |
-
- BXD2
- |
-
- Male
- |
-
- 115
- |
-
- Eyeball
- |
-
-
- |
- 83
- |
-
- E755
- |
-
- *072120.74
- |
-
- BXD187
- |
-
- Female
- |
-
- 133
- |
-
- Eyeball
- |
-
-
- |
- 84
- |
-
- E756
- |
-
- *072120.75
- |
-
- BXD187
- |
-
- Male
- |
-
- 133
- |
-
- Eyeball
- |
-
-
- |
- 85
- |
-
- E757
- |
-
- *072120.71
- |
-
- BXD169
- |
-
- Male
- |
-
- 136
- |
-
- Eyeball
- |
-
-
- |
- 86
- |
-
- E758
- |
-
- *072120.70
- |
-
- BXD169
- |
-
- Female
- |
-
- 136
- |
-
- Eyeball
- |
-
-
- |
- 87
- |
-
- E761
- |
-
- *081420.01
- |
-
- BXD128a
- |
-
- Female
- |
-
- 144
- |
-
- Eyeball
- |
-
-
- |
- 88
- |
-
- E762
- |
-
- *081420.02
- |
-
- BXD128a
- |
-
- Male
- |
-
- 144
- |
-
- Eyeball
- |
-
-
- |
- 89
- |
-
- E763
- |
-
- *081420.03
- |
-
- BXD48a
- |
-
- Female
- |
-
- 71
- |
-
- Eyeball
- |
-
-
- |
- 90
- |
-
- E764
- |
-
- *081420.04
- |
-
- BXD48a
- |
-
- Male
- |
-
- 71
- |
-
- Eyeball
- |
-
-
- |
- 91
- |
-
- E316
- |
-
- *012420.49
- |
-
- BXD190
- |
-
- Male
- |
-
- 148
- |
-
- Eyeball
- |
-
-
- |
- 92
- |
-
- E317
- |
-
- *012420.14
- |
-
- BXD87
- |
-
- Male
- |
-
- 120
- |
-
- Eyeball
- |
-
-
- |
- 93
- |
-
- E319
- |
-
- *012420.45
- |
-
- BXD180
- |
-
- Male
- |
-
- 109
- |
-
- Eyeball
- |
-
-
- |
- 94
- |
-
- E321
- |
-
- *012420.34
- |
-
- BXD152
- |
-
- Female
- |
-
- 131
- |
-
- Eyeball
- |
-
-
- |
- 95
- |
-
- E322
- |
-
- *012420.36
- |
-
- BXD152
- |
-
- Male
- |
-
- 131
- |
-
- Eyeball
- |
-
-
- |
- 96
- |
-
- E323
- |
-
- *012420.13
- |
-
- BXD87
- |
-
- Female
- |
-
- 120
- |
-
- Eyeball
- |
-
-
- |
- 97
- |
-
- E325
- |
-
- *012420.48
- |
-
- BXD190
- |
-
- Female
- |
-
- 148
- |
-
- Eyeball
- |
-
-
- |
- 98
- |
-
- E326
- |
-
- *012420.09
- |
-
- BXD75
- |
-
- Male
- |
-
- 95
- |
-
- Eyeball
- |
-
-
- |
- 99
- |
-
- E336
- |
-
- *110918.13
- |
-
- BXD32
- |
-
- Male
- |
-
- 153
- |
-
- Eyeball
- |
-
-
- |
- 100
- |
-
- E338
- |
-
- *110918.36
- |
-
- BXD71
- |
-
- Male
- |
-
- 174
- |
-
- Eyeball
- |
-
-
- |
- 101
- |
-
- E339
- |
-
- *110918.35
- |
-
- BXD71
- |
-
- Female
- |
-
- 174
- |
-
- Eyeball
- |
-
-
- |
- 102
- |
-
- E401
- |
-
- *100819.01
- |
-
- C57BL/6J
- |
-
- Female
- |
-
- 110
- |
-
- Eyeball
- |
-
-
- |
- 103
- |
-
- E402
- |
-
- *100819.02
- |
-
- C57BL/6J
- |
-
- Female
- |
-
- 110
- |
-
- Eyeball
- |
-
-
- |
- 104
- |
-
- E403
- |
-
- *100819.03
- |
-
- C57BL/6J
- |
-
- Male
- |
-
- 110
- |
-
- Eyeball
- |
-
-
- |
- 105
- |
-
- E410
- |
-
- *100819.14
- |
-
- BXD15
- |
-
- Female
- |
-
- 94
- |
-
- Eyeball
- |
-
-
- |
- 106
- |
-
- E411
- |
-
- *100819.15
- |
-
- BXD15
- |
-
- Female
- |
-
- 94
- |
-
- Eyeball
- |
-
-
- |
- 107
- |
-
- E412
- |
-
- *100819.28
- |
-
- BXD29
- |
-
- Female
- |
-
- 68
- |
-
- Eyeball
- |
-
-
- |
- 108
- |
-
- E413
- |
-
- *100819.29
- |
-
- BXD29
- |
-
- Male
- |
-
- 68
- |
-
- Eyeball
- |
-
-
- |
- 109
- |
-
- E420
- |
-
- *100819.44
- |
-
- BXD44
- |
-
- Female
- |
-
- 152
- |
-
- Eyeball
- |
-
-
- |
- 110
- |
-
- E421
- |
-
- *100819.45
- |
-
- BXD44
- |
-
- Male
- |
-
- 152
- |
-
- Eyeball
- |
-
-
- |
- 111
- |
-
- E424
- |
-
- *100819.55
- |
-
- BXD61
- |
-
- Female
- |
-
- 120
- |
-
- Eyeball
- |
-
-
- |
- 112
- |
-
- E425
- |
-
- *100819.56
- |
-
- BXD61
- |
-
- Male
- |
-
- 120
- |
-
- Eyeball
- |
-
-
- |
- 113
- |
-
- E426
- |
-
- *100819.58
- |
-
- BXD62
- |
-
- Female
- |
-
- 99
- |
-
- Eyeball
- |
-
-
- |
- 114
- |
-
- E427
- |
-
- *100819.59
- |
-
- BXD62
- |
-
- Male
- |
-
- 99
- |
-
- Eyeball
- |
-
-
- |
- 115
- |
-
- E428
- |
-
- *100819.63
- |
-
- BXD65
- |
-
- Female
- |
-
- 121
- |
-
- Eyeball
- |
-
-
- |
- 116
- |
-
- E429
- |
-
- *100819.64
- |
-
- BXD65
- |
-
- Male
- |
-
- 121
- |
-
- Eyeball
- |
-
-
- |
- 117
- |
-
- E432
- |
-
- *100819.74
- |
-
- BXD73
- |
-
- Female
- |
-
- 154
- |
-
- Eyeball
- |
-
-
- |
- 118
- |
-
- E433
- |
-
- *100819.75
- |
-
- BXD73
- |
-
- Male
- |
-
- 154
- |
-
- Eyeball
- |
-
-
- |
- 119
- |
-
- E434
- |
-
- *100819.77
- |
-
- BXD73b
- |
-
- Female
- |
-
- 153
- |
-
- Eyeball
- |
-
-
- |
- 120
- |
-
- E435
- |
-
- *100819.78
- |
-
- BXD73b
- |
-
- Male
- |
-
- 153
- |
-
- Eyeball
- |
-
-
- |
- 121
- |
-
- E436
- |
-
- *100819.79
- |
-
- BXD75
- |
-
- Female
- |
-
- 93
- |
-
- Eyeball
- |
-
-
- |
- 122
- |
-
- E437
- |
-
- *100819.80
- |
-
- BXD75
- |
-
- Male
- |
-
- 93
- |
-
- Eyeball
- |
-
-
- |
- 123
- |
-
- E438
- |
-
- *100819.86
- |
-
- BXD86
- |
-
- Female
- |
-
- 75
- |
-
- Eyeball
- |
-
-
- |
- 124
- |
-
- E439
- |
-
- *100819.87
- |
-
- BXD86
- |
-
- Male
- |
-
- 75
- |
-
- Eyeball
- |
-
-
- |
- 125
- |
-
- E440
- |
-
- *100819.90
- |
-
- BXD89
- |
-
- Female
- |
-
- 112
- |
-
- Eyeball
- |
-
-
- |
- 126
- |
-
- E441
- |
-
- *100819.91
- |
-
- BXD89
- |
-
- Male
- |
-
- 112
- |
-
- Eyeball
- |
-
-
- |
- 127
- |
-
- E442
- |
-
- *100819.92
- |
-
- BXD90
- |
-
- Female
- |
-
- 123
- |
-
- Eyeball
- |
-
-
- |
- 128
- |
-
- E443
- |
-
- *100819.93
- |
-
- BXD90
- |
-
- Male
- |
-
- 123
- |
-
- Eyeball
- |
-
-
- |
- 129
- |
-
- E444
- |
-
- *100819.95
- |
-
- BXD101
- |
-
- Female
- |
-
- 118
- |
-
- Eyeball
- |
-
-
- |
- 130
- |
-
- E445
- |
-
- *100819.96
- |
-
- BXD101
- |
-
- Male
- |
-
- 118
- |
-
- Eyeball
- |
-
-
- |
- 131
- |
-
- E446
- |
-
- *100819.98
- |
-
- BXD102
- |
-
- Female
- |
-
- 121
- |
-
- Eyeball
- |
-
-
- |
- 132
- |
-
- E447
- |
-
- *100819.99
- |
-
- BXD102
- |
-
- Male
- |
-
- 121
- |
-
- Eyeball
- |
-
-
- |
- 133
- |
-
- E457
- |
-
- *100819.122
- |
-
- BXD155
- |
-
- Female
- |
-
- 86
- |
-
- Eyeball
- |
-
-
- |
- 134
- |
-
- E458
- |
-
- *100819.123
- |
-
- BXD155
- |
-
- Male
- |
-
- 86
- |
-
- Eyeball
- |
-
-
- |
- 135
- |
-
- E461
- |
-
- *052220.38
- |
-
- BXD84
- |
-
- Female
- |
-
- 133
- |
-
- Eyeball
- |
-
-
- |
- 136
- |
-
- E462
- |
-
- *052220.47
- |
-
- BXD195
- |
-
- Male
- |
-
- 93
- |
-
- Eyeball
- |
-
-
- |
- 137
- |
-
- E463
- |
-
- *052220.46
- |
-
- BXD195
- |
-
- Female
- |
-
- 93
- |
-
- Eyeball
- |
-
-
- |
- 138
- |
-
- E464
- |
-
- *052220.39
- |
-
- BXD84
- |
-
- Male
- |
-
- 133
- |
-
- Eyeball
- |
-
-
- |
- 139
- |
-
- E465
- |
-
- *052220.42
- |
-
- BXD31
- |
-
- Female
- |
-
- 111
- |
-
- Eyeball
- |
-
-
- |
- 140
- |
-
- E466
- |
-
- *052220.43
- |
-
- BXD31
- |
-
- Male
- |
-
- 111
- |
-
- Eyeball
- |
-
-
- |
- 141
- |
-
- E467
- |
-
- *052220.26
- |
-
- BXD24
- |
-
- Female
- |
-
- 155
- |
-
- Eyeball
- |
-
-
- |
- 142
- |
-
- E468
- |
-
- *052220.27
- |
-
- BXD24
- |
-
- Male
- |
-
- 155
- |
-
- Eyeball
- |
-
-
- |
- 143
- |
-
- E469
- |
-
- *052220.49
- |
-
- BXD218
- |
-
- Male
- |
-
- 109
- |
-
- Eyeball
- |
-
-
- |
- 144
- |
-
- E470
- |
-
- *052220.36
- |
-
- BXD65b
- |
-
- Female
- |
-
- 110
- |
-
- Eyeball
- |
-
-
- |
- 145
- |
-
- E471
- |
-
- *052220.40
- |
-
- BXD202
- |
-
- Female
- |
-
- 92
- |
-
- Eyeball
- |
-
-
- |
- 146
- |
-
- E472
- |
-
- *052220.45
- |
-
- BXD122
- |
-
- Male
- |
-
- 87
- |
-
- Eyeball
- |
-
-
- |
- 147
- |
-
- E474
- |
-
- *052220.41
- |
-
- BXD202
- |
-
- Male
- |
-
- 92
- |
-
- Eyeball
- |
-
-
- |
- 148
- |
-
- E475
- |
-
- *052220.37
- |
-
- BXD65b
- |
-
- Male
- |
-
- 110
- |
-
- Eyeball
- |
-
-
- |
- 149
- |
-
- E476
- |
-
- *052220.33
- |
-
- BXD171
- |
-
- Male
- |
-
- 74
- |
-
- Eyeball
- |
-
-
- |
- 150
- |
-
- E477
- |
-
- *052220.34
- |
-
- BXD123
- |
-
- Female
- |
-
- 127
- |
-
- Eyeball
- |
-
-
- |
- 151
- |
-
- E479
- |
-
- *052220.32
- |
-
- BXD171
- |
-
- Female
- |
-
- 74
- |
-
- Eyeball
- |
-
-
- |
- 152
- |
-
- E480
- |
-
- *052220.35
- |
-
- BXD123
- |
-
- Male
- |
-
- 127
- |
-
- Eyeball
- |
-
-
- |
- 153
- |
-
- E481
- |
-
- *052220.30
- |
-
- BXD172
- |
-
- Female
- |
-
- 104
- |
-
- Eyeball
- |
-
-
- |
- 154
- |
-
- E491
- |
-
- *052220.28
- |
-
- BXD70
- |
-
- Female
- |
-
- 118
- |
-
- Eyeball
- |
-
-
- |
- 155
- |
-
- E492
- |
-
- *052220.29
- |
-
- BXD70
- |
-
- Male
- |
-
- 118
- |
-
- Eyeball
- |
-
-
- |
- 156
- |
-
- E505
- |
-
- *052220.31
- |
-
- BXD172
- |
-
- Male
- |
-
- 104
- |
-
- Eyeball
- |
-
-
- |
- 157
- |
-
- E507
- |
-
- *052220.48
- |
-
- BXD218
- |
-
- Female
- |
-
- 109
- |
-
- Eyeball
- |
-
-
-
-
-
diff --git a/general/datasets/UTHSC_BXD_Young_Adult_Eye_RNAseq_TPM_Log/tissue.rtf b/general/datasets/UTHSC_BXD_Young_Adult_Eye_RNAseq_TPM_Log/tissue.rtf
deleted file mode 100644
index bbfb410..0000000
--- a/general/datasets/UTHSC_BXD_Young_Adult_Eye_RNAseq_TPM_Log/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The animals were sacrificed under saturated isoflurane. Eyeballs from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/UTHSC_EMSR_All_AffyMTA1_Mar17/specifics.rtf b/general/datasets/UTHSC_EMSR_All_AffyMTA1_Mar17/specifics.rtf
deleted file mode 100644
index 4f2baa1..0000000
--- a/general/datasets/UTHSC_EMSR_All_AffyMTA1_Mar17/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-All Treatments
\ No newline at end of file
diff --git a/general/datasets/UTHSC_EMSR_All_AffyMTA1_Mar17/summary.rtf b/general/datasets/UTHSC_EMSR_All_AffyMTA1_Mar17/summary.rtf
deleted file mode 100644
index e320185..0000000
--- a/general/datasets/UTHSC_EMSR_All_AffyMTA1_Mar17/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Info File in progress.
diff --git a/general/datasets/UTHSC_EMSR_EtSt_AffyMTA1_Mar17/specifics.rtf b/general/datasets/UTHSC_EMSR_EtSt_AffyMTA1_Mar17/specifics.rtf
deleted file mode 100644
index 1c7602b..0000000
--- a/general/datasets/UTHSC_EMSR_EtSt_AffyMTA1_Mar17/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Ethanol-Stress Treatment
\ No newline at end of file
diff --git a/general/datasets/UTHSC_EMSR_EtSt_AffyMTA1_Mar17/summary.rtf b/general/datasets/UTHSC_EMSR_EtSt_AffyMTA1_Mar17/summary.rtf
deleted file mode 100644
index e320185..0000000
--- a/general/datasets/UTHSC_EMSR_EtSt_AffyMTA1_Mar17/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Info File in progress.
diff --git a/general/datasets/UTHSC_EMSR_Et_AffyMTA1_Mar17/specifics.rtf b/general/datasets/UTHSC_EMSR_Et_AffyMTA1_Mar17/specifics.rtf
deleted file mode 100644
index 971c8e2..0000000
--- a/general/datasets/UTHSC_EMSR_Et_AffyMTA1_Mar17/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Ethanol Treatment
\ No newline at end of file
diff --git a/general/datasets/UTHSC_EMSR_Et_AffyMTA1_Mar17/summary.rtf b/general/datasets/UTHSC_EMSR_Et_AffyMTA1_Mar17/summary.rtf
deleted file mode 100644
index e320185..0000000
--- a/general/datasets/UTHSC_EMSR_Et_AffyMTA1_Mar17/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Info File in progress.
diff --git a/general/datasets/UTHSC_EMSR_Sal_AffyMTA1_Mar17/specifics.rtf b/general/datasets/UTHSC_EMSR_Sal_AffyMTA1_Mar17/specifics.rtf
deleted file mode 100644
index 84f5f30..0000000
--- a/general/datasets/UTHSC_EMSR_Sal_AffyMTA1_Mar17/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Saline Treatment
\ No newline at end of file
diff --git a/general/datasets/UTHSC_EMSR_Sal_AffyMTA1_Mar17/summary.rtf b/general/datasets/UTHSC_EMSR_Sal_AffyMTA1_Mar17/summary.rtf
deleted file mode 100644
index e320185..0000000
--- a/general/datasets/UTHSC_EMSR_Sal_AffyMTA1_Mar17/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Info File in progress.
diff --git a/general/datasets/UTHSC_EMSR_St_AffyMTA1_Mar17/specifics.rtf b/general/datasets/UTHSC_EMSR_St_AffyMTA1_Mar17/specifics.rtf
deleted file mode 100644
index 78e1f39..0000000
--- a/general/datasets/UTHSC_EMSR_St_AffyMTA1_Mar17/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Stress Treatment
\ No newline at end of file
diff --git a/general/datasets/UTHSC_EMSR_St_AffyMTA1_Mar17/summary.rtf b/general/datasets/UTHSC_EMSR_St_AffyMTA1_Mar17/summary.rtf
deleted file mode 100644
index e320185..0000000
--- a/general/datasets/UTHSC_EMSR_St_AffyMTA1_Mar17/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Info File in progress.
diff --git a/general/datasets/UTHSC_GutExL_0414/cases.rtf b/general/datasets/UTHSC_GutExL_0414/cases.rtf
deleted file mode 100644
index e3e9e26..0000000
--- a/general/datasets/UTHSC_GutExL_0414/cases.rtf
+++ /dev/null
@@ -1,1696 +0,0 @@
-
-
-
-
-
-
-
-
- | Index |
- CaseID |
- Strain |
- Sex |
- Coat Color |
- Date of Birth |
- Generation |
- Sacrifice Date |
- Age |
- RNA
- conc.(ug/ul) |
- RNA Purity
- 260/280 |
- RNA Integrity Number RIN |
- Run Chip |
- Notes |
-
-
- | 1 |
- 081910.14 |
- B6D2F1 |
- M |
- black |
- 06/10/2010 |
- |
- 08/18/2010 |
- 69 |
- 0.5 |
- 2.00 |
- 8.40 |
- y |
- |
-
-
- | 2 |
- 081910.17 |
- B6D2F1 |
- M |
- black |
- 06/10/2010 |
- |
- 08/18/2010 |
- 69 |
- 0.9 |
- 2.00 |
- 8.60 |
- |
- |
-
-
- | 3 |
- 081910.18 |
- B6D2F1 |
- F |
- black |
- 06/10/2010 |
- |
- 08/18/2010 |
- 69 |
- 0.3 |
- 1.80 |
- 9.30 |
- y |
- |
-
-
- | 4 |
- 081910.09 |
- D2B6F1 |
- F |
- black |
- 06/02/2010 |
- |
- 08/18/2010 |
- 77 |
- 0.7 |
- 2.00 |
- 9.00 |
- y |
- |
-
-
- | 5 |
- 081910.23 |
- D2B6F1 |
- M |
- black |
- 06/02/2010 |
- |
- 08/18/2010 |
- 77 |
- 10.2 |
- 2.02 |
- 8.50 |
- y |
- |
-
-
- | 6 |
- 081910.12 |
- C57BL/6J |
- F |
- black |
- 06/02/2010 |
- |
- 08/18/2010 |
- 77 |
- 0.6 |
- 1.90 |
- n/a |
- y |
- |
-
-
- | 7 |
- 081910.25 |
- C57BL/6J |
- M |
- black |
- 06/02/2010 |
- |
- 08/18/2010 |
- 77 |
- 3.4 |
- 2.03 |
- |
- y |
- |
-
-
- | 8 |
- 081910.39 |
- C57BL/6J |
- F |
- black |
- 06/02/2010 |
- |
- 08/18/2010 |
- 77 |
- 2.30 |
- 1.99 |
- 8.50 |
- y |
- |
-
-
- | 9 |
- 081910.41 |
- C57BL/6J |
- M |
- black |
- 06/18/2010 |
- |
- 08/18/2010 |
- 61 |
- 2.20 |
- 2.02 |
- 8.60 |
- y |
- |
-
-
- | 10 |
- 081910.29 |
- DBA/2J |
- F |
- dilute brown DBA |
- 06/02/2010 |
- |
- 08/18/2010 |
- 77 |
- 2.9 |
- 2.03 |
- 8.50 |
- y |
- need one more female |
-
-
- | 11 |
- 081910.31 |
- DBA/2J |
- M |
- dilute brown DBA |
- 06/11/2010 |
- |
- 08/18/2010 |
- 68 |
- 8.6 |
- 2.06 |
- 8.00 |
- y |
- |
-
-
- | 12 |
- 081910.43 |
- DBA/2J |
- M |
- dilute brown DBA |
- 05/06/2010 |
- |
- 08/18/2010 |
- 104 |
- 2.30 |
- 2.01 |
- 9.30 |
- y |
- |
-
-
- | 13 |
- 081810.08 |
- BXD1 |
- M |
- dilute brown DBA |
- 05/24/2010 |
- 142 |
- 08/17/2010 |
- 85 |
- 0.6 |
- 1.92 |
- 8.50 |
- y |
- |
-
-
- | 14 |
- 081810.13 |
- BXD1 |
- F |
- dilute brown DBA |
- 06/07/2010 |
- 139 |
- 08/17/2010 |
- 71 |
- 0.7 |
- |
- 9.00 |
- y |
- |
-
-
- | 15 |
- 081710.91 |
- BXD11 |
- M |
- black |
- 06/02/2010 |
- 137 |
- 08/17/2010 |
- 76 |
- 0.7 |
- 1.93 |
- 8.20 |
- y |
- |
-
-
- | 16 |
- 081710.97 |
- BXD11 |
- F |
- black |
- 05/22/2010 |
- 136 |
- 08/17/2010 |
- 87 |
- 1.0 |
- 1.95 |
- 8.90 |
- y |
- |
-
-
- | 17 |
- 081810.23 |
- BXD12 |
- M |
- gray |
- 06/01/2010 |
- 122 |
- 08/17/2010 |
- 77 |
- 0.9 |
- 2.00 |
- 8.00 |
- y |
- |
-
-
- | 18 |
- 081810.44 |
- BXD12 |
- F |
- gray |
- 06/01/2010 |
- 122 |
- 08/18/2010 |
- 78 |
- 0.8 |
- 1.93 |
- 8.30 |
- y |
- |
-
-
- | 19 |
- 081810.33 |
- BXD14 |
- F |
- black |
- 05/29/2010 |
- 142 |
- 08/17/2010 |
- 80 |
- 1.2 |
- 1.97 |
- 8.10 |
- y |
- |
-
-
- | 20 |
- 081810.52 |
- BXD14 |
- M |
- black |
- 05/29/2010 |
- 142 |
- 08/18/2010 |
- 81 |
- 0.4 |
- 1.90 |
- 9.00 |
- y |
- |
-
-
- | 21 |
- 081810.19 |
- BXD24 |
- F |
- brown |
- 05/24/2010 |
- 90 |
- 08/17/2010 |
- 85 |
- 0.3 |
- 1.90 |
- 9.10 |
- y |
- This strain comes from UTHSC colony since 2008. So they are probably blind. |
-
-
- | 22 |
- 081810.42 |
- BXD24 |
- M |
- brown |
- 05/24/2010 |
- 90 |
- 08/17/2010 |
- 85 |
- 0.7 |
- 2.00 |
- 8.50 |
- y |
- This strain comes from UTHSC colony since 2008. So they are probably blind. |
-
-
- | 23 |
- 081710.99 |
- BXD27 |
- M |
- dilute brown DBA |
- 06/05/2010 |
- 162 |
- 08/17/2010 |
- 73 |
- 1.3 |
- 1.95 |
- 8.40 |
- y |
- need one more female |
-
-
- | 24 |
- 081810.04 |
- BXD29 |
- M |
- gray |
- 06/07/2010 |
- 25 |
- 08/17/2010 |
- 71 |
- 0.5 |
- 1.91 |
- 8.40 |
- y |
- |
-
-
- | 25 |
- 081810.10 |
- BXD29 |
- F |
- gray |
- 06/07/2010 |
- 25 |
- 08/17/2010 |
- 71 |
- 0.6 |
- 1.97 |
- 8.70 |
- y |
- |
-
-
- | 26 |
- 081810.18 |
- BXD31 |
- M |
- black |
- 06/05/2010 |
- 130 |
- 08/17/2010 |
- 73 |
- 0.5 |
- 1.88 |
- 8.70 |
- y |
- |
-
-
- | 27 |
- 081810.40 |
- BXD31 |
- F |
- black |
- 06/05/2010 |
- 130 |
- 08/17/2010 |
- 73 |
- 1.1 |
- 2.00 |
- 7.00 |
- y |
- |
-
-
- | 28 |
- 081610.76 |
- BXD32 |
- F |
- black |
- 05/29/2010 |
- 116 |
- 08/18/2010 |
- 81 |
- 3.8 |
- 2.05 |
- 9.10 |
- y |
- need one more male |
-
-
- | 29 |
- 081810.26 |
- BXD34 |
- M |
- black |
- 06/02/2010 |
- 63 |
- 08/17/2010 |
- 76 |
- 1.3 |
- 1.98 |
- 8.20 |
- y |
- |
-
-
- | 30 |
- 081810.29 |
- BXD34 |
- M |
- black |
- 06/02/2010 |
- 63 |
- 08/17/2010 |
- 76 |
- 0.7 |
- 1.93 |
- 8.50 |
- |
- |
-
-
- | 31 |
- 081810.46 |
- BXD34 |
- F |
- black |
- 06/02/2010 |
- 63 |
- 08/18/2010 |
- 77 |
- 1.0 |
- 2.00 |
- 7.10 |
- y |
- |
-
-
- | 32 |
- 081810.36 |
- BXD39 |
- M |
- gray |
- 05/31/2010 |
- 68 |
- 08/17/2010 |
- 78 |
- 0.6 |
- 1.94 |
- 8.20 |
- y |
- |
-
-
- | 33 |
- 081810.55 |
- BXD39 |
- F |
- gray |
- 05/31/2010 |
- 68 |
- 08/18/2010 |
- 79 |
- 0.8 |
- 1.96 |
- 8.40 |
- y |
- |
-
-
- | 34 |
- 081910.03 |
- BXD40 |
- F |
- gray |
- 05/25/2010 |
- 58 |
- 08/18/2010 |
- 85 |
- 1.2 |
- 2.00 |
- 8.80 |
- y |
- |
-
-
- | 35 |
- 081910.06 |
- BXD40 |
- M |
- gray |
- 05/25/2010 |
- 58 |
- 08/18/2010 |
- 85 |
- 0.7 |
- 1.90 |
- 8.80 |
- y |
- |
-
-
- | 36 |
- 081810.31 |
- BXD42 |
- F |
- black |
- 05/23/2010 |
- 64 |
- 08/17/2010 |
- 86 |
- 0.9 |
- 1.95 |
- 8.30 |
- y |
- |
-
-
- | 37 |
- 081810.48 |
- BXD42 |
- M |
- black |
- 05/23/2010 |
- 64 |
- 08/18/2010 |
- 87 |
- 0.8 |
- 1.93 |
- 8.90 |
- y |
- |
-
-
- | 38 |
- 081710.47 |
- BXD43 |
- M |
- black |
- 05/28/2010 |
- 44 |
- 08/17/2010 |
- 81 |
- 1.2 |
- 1.95 |
- 8.10 |
- y |
- |
-
-
- | 39 |
- 081710.48 |
- BXD43 |
- F |
- black |
- 05/28/2010 |
- 44 |
- 08/17/2010 |
- 81 |
- 1.7 |
- 1.96 |
- 8.90 |
- y |
- |
-
-
- | 40 |
- 081710.49 |
- BXD43 |
- F |
- black |
- 05/28/2010 |
- 44 |
- 08/17/2010 |
- 81 |
- 1.2 |
- 1.95 |
- 8.50 |
- |
- |
-
-
- | 41 |
- 081710.23 |
- BXD44 |
- F |
- brown |
- 05/26/2010 |
- 41 |
- 08/17/2010 |
- 83 |
- 1.1 |
- 1.96 |
- 8.30 |
- y |
- |
-
-
- | 42 |
- 081710.24 |
- BXD44 |
- F |
- brown |
- 05/26/2010 |
- 41 |
- 08/17/2010 |
- 83 |
- 0.9 |
- 1.92 |
- 8.70 |
- |
- |
-
-
- | 43 |
- 081710.30 |
- BXD44 |
- M |
- dilute brown DBA |
- 05/26/2010 |
- 41 |
- 08/17/2010 |
- 83 |
- 1.3 |
- 1.97 |
- 8.20 |
- y |
- |
-
-
- | 44 |
- 081710.31 |
- BXD44 |
- M |
- dilute brown DBA |
- 05/26/2010 |
- 41 |
- 08/17/2010 |
- 83 |
- 1.6 |
- 1.98 |
- 8.30 |
- |
- |
-
-
- | 45 |
- 081710.32 |
- BXD44 |
- M |
- dilute brown DBA |
- 05/26/2010 |
- 41 |
- 08/17/2010 |
- 83 |
- 0.8 |
- 1.95 |
- 8.80 |
- |
- |
-
-
- | 46 |
- 081710.51 |
- BXD45 |
- M |
- dilute brown DBA |
- 06/01/2010 |
- 39 |
- 08/17/2010 |
- 77 |
- 1.2 |
- 1.94 |
- 7.80 |
- y |
- |
-
-
- | 47 |
- 081710.54 |
- BXD45 |
- F |
- dilute brown DBA |
- 06/01/2010 |
- 39 |
- 08/17/2010 |
- 77 |
- 1.0 |
- 1.94 |
- 7.30 |
- y |
- |
-
-
- | 48 |
- 081610.14 |
- BXD48 |
- F |
- black |
- 06/03/2010 |
- 40 |
- 08/18/2010 |
- 76 |
- 2.2 |
- 2.01 |
- 9.50 |
- y |
- |
-
-
- | 49 |
- 081610.17 |
- BXD48 |
- M |
- black |
- 06/03/2010 |
- 40 |
- 08/18/2010 |
- 76 |
- 3.3 |
- 2.05 |
- 8.20 |
- y |
- |
-
-
- | 50 |
- 081710.29 |
- BXD49 |
- M |
- gray |
- 05/25/2010 |
- 49 |
- 08/17/2010 |
- 84 |
- 1.6 |
- 1.97 |
- 7.10 |
- y |
- |
-
-
- | 51 |
- 081710.34 |
- BXD49 |
- F |
- gray |
- 05/25/2010 |
- 24 |
- 08/17/2010 |
- 84 |
- 1.0 |
- 1.95 |
- 8.50 |
- y |
- |
-
-
- | 52 |
- 081610.29 |
- BXD50 |
- F |
- black |
- 06/02/2010 |
- 35 |
- 08/18/2010 |
- 77 |
- 3.3 |
- 2.05 |
- 8.40 |
- y |
- |
-
-
- | 53 |
- 081610.32 |
- BXD50 |
- M |
- black |
- 06/02/2010 |
- 35 |
- 08/18/2010 |
- 77 |
- 9.1 |
- 2.03 |
- 8.40 |
- y |
- |
-
-
- | 54 |
- 081610.36 |
- BXD56 |
- M |
- black |
- 06/02/2010 |
- 34 |
- 08/18/2010 |
- 77 |
- 1.9 |
- 2.02 |
- 9.60 |
- y |
- |
-
-
- | 55 |
- 081610.77 |
- BXD56 |
- F |
- black |
- 05/26/2010 |
- 34 |
- 08/18/2010 |
- 84 |
- 3.4 |
- 2.05 |
- 8.20 |
- y |
- |
-
-
- | 56 |
- 081610.80 |
- BXD56 |
- F |
- black |
- 05/26/2010 |
- 33 |
- 08/18/2010 |
- 84 |
- 3.2 |
- 2.05 |
- 8.50 |
- |
- |
-
-
- | 57 |
- 081710.67 |
- BXD60 |
- M |
- brown |
- 06/08/2010 |
- 43 |
- 08/17/2010 |
- 70 |
- 0.9 |
- 1.91 |
- 8.40 |
- y |
- need one more female |
-
-
- | 58 |
- 081810.83 |
- BXD62 |
- M |
- brown |
- 05/27/2010 |
- 41 |
- 08/18/2010 |
- 83 |
- 0.5 |
- 1.95 |
- 8.10 |
- y |
- need one more female |
-
-
- | 59 |
- 081610.22 |
- BXD63 |
- M |
- dilute brown DBA |
- 06/02/2010 |
- 31 |
- 08/18/2010 |
- 77 |
- 6.9 |
- 2.07 |
- 8.50 |
- y |
- |
-
-
- | 60 |
- 081610.25 |
- BXD63 |
- F |
- dilute brown DBA |
- 06/02/2010 |
- 31 |
- 08/18/2010 |
- 77 |
- 2.2 |
- 2.00 |
- 8.70 |
- y |
- |
-
-
- | 61 |
- 081610.03 |
- BXD65 |
- M |
- brown |
- 05/26/2010 |
- 32 |
- 08/18/2010 |
- 84 |
- 11.2 |
- 2.03 |
- 8.70 |
- y |
- |
-
-
- | 62 |
- 081610.11 |
- BXD65 |
- F |
- brown |
- 05/26/2010 |
- 32 |
- 08/18/2010 |
- 84 |
- 3.1 |
- 2.03 |
- 9.10 |
- y |
- |
-
-
- | 63 |
- 081610.96 |
- BXD68 |
- F |
- brown |
- 06/03/2010 |
- 33 |
- 08/18/2010 |
- 76 |
- 4.0 |
- 2.03 |
- 8.20 |
- y |
- |
-
-
- | 64 |
- 081610.99 |
- BXD68 |
- M |
- brown |
- 06/03/2010 |
- 33 |
- 08/18/2010 |
- 76 |
- 3.4 |
- 2.09 |
- 7.80 |
- y |
- |
-
-
- | 65 |
- 081710.71 |
- BXD69 |
- M |
- dilute brown DBA |
- 05/29/2010 |
- 41 |
- 08/17/2010 |
- 80 |
- 1.3 |
- 1.96 |
- 7.90 |
- y |
- |
-
-
- | 66 |
- 081710.78 |
- BXD69 |
- F |
- dilute brown DBA |
- 06/09/2010 |
- 42 |
- 08/17/2010 |
- 69 |
- 0.8 |
- 1.90 |
- 8.50 |
- y |
- |
-
-
- | 67 |
- 081610.85 |
- BXD70 |
- M |
- dilute brown DBA |
- 06/03/2010 |
- 36 |
- 08/18/2010 |
- 76 |
- 4.6 |
- 1.99 |
- 9.40 |
- y |
- |
-
-
- | 68 |
- 081610.92 |
- BXD70 |
- F |
- dilute brown DBA |
- 06/03/2010 |
- 36 |
- 08/18/2010 |
- 76 |
- 3.1 |
- 2.07 |
- 8.50 |
- y |
- |
-
-
- | 69 |
- 081910.33 |
- BXD71 |
- F |
- dilute brown DBA |
- 06/03/2010 |
- 35 |
- 08/18/2010 |
- 76 |
- 2.8 |
- 2.05 |
- 8.00 |
- y |
- |
-
-
- | 70 |
- 081910.38 |
- BXD71 |
- M |
- dilute brown DBA |
- 06/03/2010 |
- 35 |
- 08/18/2010 |
- 76 |
- 4.6 |
- 2.02 |
- 8.30 |
- y |
- |
-
-
- | 71 |
- 081710.81 |
- BXD73 |
- F |
- dilute brown DBA |
- 05/26/2010 |
- 44 |
- 08/17/2010 |
- 83 |
- 0.8 |
- 1.90 |
- 8.60 |
- y |
- |
-
-
- | 72 |
- 081710.83 |
- BXD73 |
- M |
- dilute brown DBA |
- 05/26/2010 |
- 41 |
- 08/17/2010 |
- 83 |
- 0.8 |
- 1.91 |
- 8.40 |
- y |
- |
-
-
- | 73 |
- 081810.58 |
- BXD75 |
- M |
- dilute brown DBA |
- 06/03/2010 |
- 39 |
- 08/18/2010 |
- 76 |
- 0.8 |
- 1.95 |
- 8.70 |
- y |
- |
-
-
- | 74 |
- 081810.73 |
- BXD75 |
- F |
- dilute brown DBA |
- 06/03/2010 |
- 39 |
- 08/18/2010 |
- 76 |
- 0.7 |
- 1.92 |
- 9.30 |
- y |
- |
-
-
- | 75 |
- 081710.06 |
- BXD79 |
- F |
- gray |
- 05/23/2010 |
- 24 |
- 08/18/2010 |
- 87 |
- 2.9 |
- 2.04 |
- 8.60 |
- y |
- |
-
-
- | 76 |
- 081710.08 |
- BXD79 |
- M |
- gray |
- 05/23/2010 |
- 24 |
- 08/18/2010 |
- 87 |
- 2.1 |
- 2.01 |
- 9.40 |
- y |
- |
-
-
- | 77 |
- 081710.87 |
- BXD80 |
- F |
- dilute brown DBA |
- 06/05/2010 |
- 33 |
- 08/17/2010 |
- 73 |
- 1.2 |
- 1.95 |
- 8.20 |
- y |
- |
-
-
- | 78 |
- 081710.88 |
- BXD80 |
- M |
- dilute brown DBA |
- 06/05/2010 |
- 33 |
- 08/17/2010 |
- 73 |
- 0.8 |
- 1.91 |
- 8.00 |
- y |
- |
-
-
- | 79 |
- 081610.64 |
- BXD83 |
- M |
- dilute brown DBA |
- 05/29/2010 |
- 32 |
- 08/18/2010 |
- 81 |
- 2.5 |
- 2.04 |
- 8.50 |
- y |
- |
-
-
- | 80 |
- 081610.69 |
- BXD83 |
- F |
- dilute brown DBA |
- 05/29/2010 |
- 32 |
- 08/18/2010 |
- 81 |
- 2.7 |
- 2.05 |
- 8.20 |
- y |
- |
-
-
- | 81 |
- 081810.80 |
- BXD84 |
- F |
- dilute brown DBA |
- 06/03/2010 |
- 31 |
- 08/18/2010 |
- 76 |
- 0.9 |
- 1.96 |
- 8.80 |
- y |
- need one more male |
-
-
- | 82 |
- 081710.10 |
- BXD85 |
- F |
- dilute brown DBA |
- 06/05/2010 |
- 40 |
- 08/18/2010 |
- 74 |
- 3.7 |
- 2.04 |
- 7.90 |
- y |
- |
-
-
- | 83 |
- 081710.13 |
- BXD85 |
- M |
- dilute brown DBA |
- 06/05/2010 |
- 40 |
- 08/18/2010 |
- 74 |
- 2.9 |
- 2.06 |
- 8.40 |
- y |
- |
-
-
- | 84 |
- 081610.60 |
- BXD87 |
- M |
- black |
- 05/27/2010 |
- 35 |
- 08/18/2010 |
- 83 |
- 3.4 |
- 2.04 |
- 8.30 |
- y |
- |
-
-
- | 85 |
- 081610.63 |
- BXD87 |
- F |
- black |
- 05/27/2010 |
- 35 |
- 08/18/2010 |
- 83 |
- 3.1 |
- 2.05 |
- 8.40 |
- y |
- |
-
-
- | 86 |
- 081610.40 |
- BXD89 |
- M |
- dilute brown DBA |
- 05/28/2010 |
- 36 |
- 08/18/2010 |
- 82 |
- 2.6 |
- 2.05 |
- 8.50 |
- y |
- need one more female |
-
-
- | 87 |
- 081610.53 |
- BXD90 |
- F |
- dilute brown DBA |
- 05/28/2010 |
- 39 |
- 08/18/2010 |
- 82 |
- 9.1 |
- 2.06 |
- 8.60 |
- y |
- |
-
-
- | 88 |
- 081610.57 |
- BXD90 |
- M |
- dilute brown DBA |
- 05/28/2010 |
- 39 |
- 08/18/2010 |
- 82 |
- 2.1 |
- 2.02 |
- 9.40 |
- y |
- |
-
-
- | 89 |
- 081610.87 |
- BXD92A |
- F |
- brown |
- 05/24/2010 |
- 42 |
- 08/18/2010 |
- 86 |
- 2.6 |
- 2.05 |
- 8.60 |
- y |
- |
-
-
- | 90 |
- 081610.93 |
- BXD92A |
- M |
- brown |
- 05/21/2010 |
- 42 |
- 08/18/2010 |
- 89 |
- 8.5 |
- 2.07 |
- 8.80 |
- y |
- |
-
-
- | 91 |
- 081910.32 |
- BXD95 |
- M |
- dilute brown DBA |
- 06/03/2010 |
- 25 |
- 08/18/2010 |
- 76 |
- 2.7 |
- 2.05 |
- 9.20 |
- y |
- |
-
-
- | 92 |
- 081610.81 |
- BXD95 |
- F |
- dilute brown DBA |
- 06/03/2010 |
- 25 |
- 08/18/2010 |
- 76 |
- 3.2 |
- 2.07 |
- 8.70 |
- y |
- |
-
-
- | 93 |
- 081610.84 |
- BXD95 |
- M |
- dilute brown DBA |
- 06/03/2010 |
- 25 |
- 08/18/2010 |
- 76 |
- 13.3 |
- 1.97 |
- 7.70 |
- |
- |
-
-
- | 94 |
- 081610.47 |
- BXD97 |
- F |
- brown |
- 06/08/2010 |
- 35 |
- 08/18/2010 |
- 71 |
- 2.3 |
- 2.00 |
- 9.10 |
- y |
- need one more male |
-
-
- | 95 |
- 081610.06 |
- BXD99 |
- F |
- dilute brown DBA |
- 06/02/2010 |
- 28 |
- 08/18/2010 |
- 77 |
- 4.2 |
- 2.01 |
- 9.00 |
- y |
- |
-
-
- | 96 |
- 081610.20 |
- BXD99 |
- M |
- dilute brown DBA |
- 06/02/2010 |
- 28 |
- 08/18/2010 |
- 77 |
- 2.2 |
- 2.00 |
- 8.90 |
- y |
- |
-
-
- | 97 |
- 081810.63 |
- BXD100 |
- M |
- black |
- 05/27/2010 |
- 30 |
- 08/18/2010 |
- 83 |
- 0.7 |
- 1.90 |
- 8.60 |
- y |
- |
-
-
- | 98 |
- 081810.75 |
- BXD100 |
- F |
- black |
- 05/27/2010 |
- 30 |
- 08/18/2010 |
- 83 |
- 0.9 |
- 1.95 |
- 8.10 |
- y |
- |
-
-
- | 99 |
- 081710.14 |
- BXD101 |
- M |
- gray |
- 05/21/2010 |
- 27 |
- 08/18/2010 |
- 89 |
- 2.9 |
- 2.05 |
- 8.90 |
- y |
- |
-
-
- | 100 |
- 081710.19 |
- BXD101 |
- F |
- gray |
- 05/21/2010 |
- 27 |
- 08/18/2010 |
- 89 |
- 3.2 |
- 2.06 |
- 8.30 |
- y |
- |
-
-
- | 101 |
- 081710.41 |
- BXD102 |
- F |
- brown |
- 05/21/2010 |
- 25 |
- 08/17/2010 |
- 88 |
- 1.5 |
- 1.95 |
- 7.70 |
- y |
- |
-
-
- | 102 |
- 081710.45 |
- BXD102 |
- M |
- brown |
- 05/21/2010 |
- 25 |
- 08/17/2010 |
- 88 |
- 1.2 |
- 1.97 |
- 7.70 |
- y |
- |
-
-
- | 103 |
- 081710.58 |
- BXD103 |
- M |
- dilute brown DBA |
- 05/31/2010 |
- 21 |
- 08/17/2010 |
- 78 |
- 1.1 |
- 1.94 |
- 8.40 |
- y |
- |
-
-
- | 104 |
- 081710.62 |
- BXD103 |
- F |
- dilute brown DBA |
- 05/31/2010 |
- 21 |
- 08/17/2010 |
- 78 |
- 0.6 |
- 1.91 |
- 8.40 |
- y |
- |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_GutExL_0414/platform.rtf b/general/datasets/UTHSC_GutExL_0414/platform.rtf
deleted file mode 100644
index 79244c6..0000000
--- a/general/datasets/UTHSC_GutExL_0414/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version]
diff --git a/general/datasets/UTHSC_GutExL_0414/processing.rtf b/general/datasets/UTHSC_GutExL_0414/processing.rtf
deleted file mode 100644
index ebfa292..0000000
--- a/general/datasets/UTHSC_GutExL_0414/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset includes Gene and Exon level RMA normalization.
diff --git a/general/datasets/UTHSC_GutExL_0414/specifics.rtf b/general/datasets/UTHSC_GutExL_0414/specifics.rtf
deleted file mode 100644
index 2400c03..0000000
--- a/general/datasets/UTHSC_GutExL_0414/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Exon Level
diff --git a/general/datasets/UTHSC_GutExL_0414/tissue.rtf b/general/datasets/UTHSC_GutExL_0414/tissue.rtf
deleted file mode 100644
index 5653e30..0000000
--- a/general/datasets/UTHSC_GutExL_0414/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Approximately two equal-sized segments of the small intestine were pooled per animal: one taken from the proximal jejunum and one from the distal ileum. We did generate a second data set (not in GeneNetwork) for different segments of the the GI tract from stomach to distal colon for C57BL/6J and DBA/2J parental strains. These additional data are available upon request from Drs. Dennis Black and Lu Lu.
diff --git a/general/datasets/UTHSC_GutGL_0414/cases.rtf b/general/datasets/UTHSC_GutGL_0414/cases.rtf
deleted file mode 100644
index e3e9e26..0000000
--- a/general/datasets/UTHSC_GutGL_0414/cases.rtf
+++ /dev/null
@@ -1,1696 +0,0 @@
-
-
-
-
-
-
-
-
- | Index |
- CaseID |
- Strain |
- Sex |
- Coat Color |
- Date of Birth |
- Generation |
- Sacrifice Date |
- Age |
- RNA
- conc.(ug/ul) |
- RNA Purity
- 260/280 |
- RNA Integrity Number RIN |
- Run Chip |
- Notes |
-
-
- | 1 |
- 081910.14 |
- B6D2F1 |
- M |
- black |
- 06/10/2010 |
- |
- 08/18/2010 |
- 69 |
- 0.5 |
- 2.00 |
- 8.40 |
- y |
- |
-
-
- | 2 |
- 081910.17 |
- B6D2F1 |
- M |
- black |
- 06/10/2010 |
- |
- 08/18/2010 |
- 69 |
- 0.9 |
- 2.00 |
- 8.60 |
- |
- |
-
-
- | 3 |
- 081910.18 |
- B6D2F1 |
- F |
- black |
- 06/10/2010 |
- |
- 08/18/2010 |
- 69 |
- 0.3 |
- 1.80 |
- 9.30 |
- y |
- |
-
-
- | 4 |
- 081910.09 |
- D2B6F1 |
- F |
- black |
- 06/02/2010 |
- |
- 08/18/2010 |
- 77 |
- 0.7 |
- 2.00 |
- 9.00 |
- y |
- |
-
-
- | 5 |
- 081910.23 |
- D2B6F1 |
- M |
- black |
- 06/02/2010 |
- |
- 08/18/2010 |
- 77 |
- 10.2 |
- 2.02 |
- 8.50 |
- y |
- |
-
-
- | 6 |
- 081910.12 |
- C57BL/6J |
- F |
- black |
- 06/02/2010 |
- |
- 08/18/2010 |
- 77 |
- 0.6 |
- 1.90 |
- n/a |
- y |
- |
-
-
- | 7 |
- 081910.25 |
- C57BL/6J |
- M |
- black |
- 06/02/2010 |
- |
- 08/18/2010 |
- 77 |
- 3.4 |
- 2.03 |
- |
- y |
- |
-
-
- | 8 |
- 081910.39 |
- C57BL/6J |
- F |
- black |
- 06/02/2010 |
- |
- 08/18/2010 |
- 77 |
- 2.30 |
- 1.99 |
- 8.50 |
- y |
- |
-
-
- | 9 |
- 081910.41 |
- C57BL/6J |
- M |
- black |
- 06/18/2010 |
- |
- 08/18/2010 |
- 61 |
- 2.20 |
- 2.02 |
- 8.60 |
- y |
- |
-
-
- | 10 |
- 081910.29 |
- DBA/2J |
- F |
- dilute brown DBA |
- 06/02/2010 |
- |
- 08/18/2010 |
- 77 |
- 2.9 |
- 2.03 |
- 8.50 |
- y |
- need one more female |
-
-
- | 11 |
- 081910.31 |
- DBA/2J |
- M |
- dilute brown DBA |
- 06/11/2010 |
- |
- 08/18/2010 |
- 68 |
- 8.6 |
- 2.06 |
- 8.00 |
- y |
- |
-
-
- | 12 |
- 081910.43 |
- DBA/2J |
- M |
- dilute brown DBA |
- 05/06/2010 |
- |
- 08/18/2010 |
- 104 |
- 2.30 |
- 2.01 |
- 9.30 |
- y |
- |
-
-
- | 13 |
- 081810.08 |
- BXD1 |
- M |
- dilute brown DBA |
- 05/24/2010 |
- 142 |
- 08/17/2010 |
- 85 |
- 0.6 |
- 1.92 |
- 8.50 |
- y |
- |
-
-
- | 14 |
- 081810.13 |
- BXD1 |
- F |
- dilute brown DBA |
- 06/07/2010 |
- 139 |
- 08/17/2010 |
- 71 |
- 0.7 |
- |
- 9.00 |
- y |
- |
-
-
- | 15 |
- 081710.91 |
- BXD11 |
- M |
- black |
- 06/02/2010 |
- 137 |
- 08/17/2010 |
- 76 |
- 0.7 |
- 1.93 |
- 8.20 |
- y |
- |
-
-
- | 16 |
- 081710.97 |
- BXD11 |
- F |
- black |
- 05/22/2010 |
- 136 |
- 08/17/2010 |
- 87 |
- 1.0 |
- 1.95 |
- 8.90 |
- y |
- |
-
-
- | 17 |
- 081810.23 |
- BXD12 |
- M |
- gray |
- 06/01/2010 |
- 122 |
- 08/17/2010 |
- 77 |
- 0.9 |
- 2.00 |
- 8.00 |
- y |
- |
-
-
- | 18 |
- 081810.44 |
- BXD12 |
- F |
- gray |
- 06/01/2010 |
- 122 |
- 08/18/2010 |
- 78 |
- 0.8 |
- 1.93 |
- 8.30 |
- y |
- |
-
-
- | 19 |
- 081810.33 |
- BXD14 |
- F |
- black |
- 05/29/2010 |
- 142 |
- 08/17/2010 |
- 80 |
- 1.2 |
- 1.97 |
- 8.10 |
- y |
- |
-
-
- | 20 |
- 081810.52 |
- BXD14 |
- M |
- black |
- 05/29/2010 |
- 142 |
- 08/18/2010 |
- 81 |
- 0.4 |
- 1.90 |
- 9.00 |
- y |
- |
-
-
- | 21 |
- 081810.19 |
- BXD24 |
- F |
- brown |
- 05/24/2010 |
- 90 |
- 08/17/2010 |
- 85 |
- 0.3 |
- 1.90 |
- 9.10 |
- y |
- This strain comes from UTHSC colony since 2008. So they are probably blind. |
-
-
- | 22 |
- 081810.42 |
- BXD24 |
- M |
- brown |
- 05/24/2010 |
- 90 |
- 08/17/2010 |
- 85 |
- 0.7 |
- 2.00 |
- 8.50 |
- y |
- This strain comes from UTHSC colony since 2008. So they are probably blind. |
-
-
- | 23 |
- 081710.99 |
- BXD27 |
- M |
- dilute brown DBA |
- 06/05/2010 |
- 162 |
- 08/17/2010 |
- 73 |
- 1.3 |
- 1.95 |
- 8.40 |
- y |
- need one more female |
-
-
- | 24 |
- 081810.04 |
- BXD29 |
- M |
- gray |
- 06/07/2010 |
- 25 |
- 08/17/2010 |
- 71 |
- 0.5 |
- 1.91 |
- 8.40 |
- y |
- |
-
-
- | 25 |
- 081810.10 |
- BXD29 |
- F |
- gray |
- 06/07/2010 |
- 25 |
- 08/17/2010 |
- 71 |
- 0.6 |
- 1.97 |
- 8.70 |
- y |
- |
-
-
- | 26 |
- 081810.18 |
- BXD31 |
- M |
- black |
- 06/05/2010 |
- 130 |
- 08/17/2010 |
- 73 |
- 0.5 |
- 1.88 |
- 8.70 |
- y |
- |
-
-
- | 27 |
- 081810.40 |
- BXD31 |
- F |
- black |
- 06/05/2010 |
- 130 |
- 08/17/2010 |
- 73 |
- 1.1 |
- 2.00 |
- 7.00 |
- y |
- |
-
-
- | 28 |
- 081610.76 |
- BXD32 |
- F |
- black |
- 05/29/2010 |
- 116 |
- 08/18/2010 |
- 81 |
- 3.8 |
- 2.05 |
- 9.10 |
- y |
- need one more male |
-
-
- | 29 |
- 081810.26 |
- BXD34 |
- M |
- black |
- 06/02/2010 |
- 63 |
- 08/17/2010 |
- 76 |
- 1.3 |
- 1.98 |
- 8.20 |
- y |
- |
-
-
- | 30 |
- 081810.29 |
- BXD34 |
- M |
- black |
- 06/02/2010 |
- 63 |
- 08/17/2010 |
- 76 |
- 0.7 |
- 1.93 |
- 8.50 |
- |
- |
-
-
- | 31 |
- 081810.46 |
- BXD34 |
- F |
- black |
- 06/02/2010 |
- 63 |
- 08/18/2010 |
- 77 |
- 1.0 |
- 2.00 |
- 7.10 |
- y |
- |
-
-
- | 32 |
- 081810.36 |
- BXD39 |
- M |
- gray |
- 05/31/2010 |
- 68 |
- 08/17/2010 |
- 78 |
- 0.6 |
- 1.94 |
- 8.20 |
- y |
- |
-
-
- | 33 |
- 081810.55 |
- BXD39 |
- F |
- gray |
- 05/31/2010 |
- 68 |
- 08/18/2010 |
- 79 |
- 0.8 |
- 1.96 |
- 8.40 |
- y |
- |
-
-
- | 34 |
- 081910.03 |
- BXD40 |
- F |
- gray |
- 05/25/2010 |
- 58 |
- 08/18/2010 |
- 85 |
- 1.2 |
- 2.00 |
- 8.80 |
- y |
- |
-
-
- | 35 |
- 081910.06 |
- BXD40 |
- M |
- gray |
- 05/25/2010 |
- 58 |
- 08/18/2010 |
- 85 |
- 0.7 |
- 1.90 |
- 8.80 |
- y |
- |
-
-
- | 36 |
- 081810.31 |
- BXD42 |
- F |
- black |
- 05/23/2010 |
- 64 |
- 08/17/2010 |
- 86 |
- 0.9 |
- 1.95 |
- 8.30 |
- y |
- |
-
-
- | 37 |
- 081810.48 |
- BXD42 |
- M |
- black |
- 05/23/2010 |
- 64 |
- 08/18/2010 |
- 87 |
- 0.8 |
- 1.93 |
- 8.90 |
- y |
- |
-
-
- | 38 |
- 081710.47 |
- BXD43 |
- M |
- black |
- 05/28/2010 |
- 44 |
- 08/17/2010 |
- 81 |
- 1.2 |
- 1.95 |
- 8.10 |
- y |
- |
-
-
- | 39 |
- 081710.48 |
- BXD43 |
- F |
- black |
- 05/28/2010 |
- 44 |
- 08/17/2010 |
- 81 |
- 1.7 |
- 1.96 |
- 8.90 |
- y |
- |
-
-
- | 40 |
- 081710.49 |
- BXD43 |
- F |
- black |
- 05/28/2010 |
- 44 |
- 08/17/2010 |
- 81 |
- 1.2 |
- 1.95 |
- 8.50 |
- |
- |
-
-
- | 41 |
- 081710.23 |
- BXD44 |
- F |
- brown |
- 05/26/2010 |
- 41 |
- 08/17/2010 |
- 83 |
- 1.1 |
- 1.96 |
- 8.30 |
- y |
- |
-
-
- | 42 |
- 081710.24 |
- BXD44 |
- F |
- brown |
- 05/26/2010 |
- 41 |
- 08/17/2010 |
- 83 |
- 0.9 |
- 1.92 |
- 8.70 |
- |
- |
-
-
- | 43 |
- 081710.30 |
- BXD44 |
- M |
- dilute brown DBA |
- 05/26/2010 |
- 41 |
- 08/17/2010 |
- 83 |
- 1.3 |
- 1.97 |
- 8.20 |
- y |
- |
-
-
- | 44 |
- 081710.31 |
- BXD44 |
- M |
- dilute brown DBA |
- 05/26/2010 |
- 41 |
- 08/17/2010 |
- 83 |
- 1.6 |
- 1.98 |
- 8.30 |
- |
- |
-
-
- | 45 |
- 081710.32 |
- BXD44 |
- M |
- dilute brown DBA |
- 05/26/2010 |
- 41 |
- 08/17/2010 |
- 83 |
- 0.8 |
- 1.95 |
- 8.80 |
- |
- |
-
-
- | 46 |
- 081710.51 |
- BXD45 |
- M |
- dilute brown DBA |
- 06/01/2010 |
- 39 |
- 08/17/2010 |
- 77 |
- 1.2 |
- 1.94 |
- 7.80 |
- y |
- |
-
-
- | 47 |
- 081710.54 |
- BXD45 |
- F |
- dilute brown DBA |
- 06/01/2010 |
- 39 |
- 08/17/2010 |
- 77 |
- 1.0 |
- 1.94 |
- 7.30 |
- y |
- |
-
-
- | 48 |
- 081610.14 |
- BXD48 |
- F |
- black |
- 06/03/2010 |
- 40 |
- 08/18/2010 |
- 76 |
- 2.2 |
- 2.01 |
- 9.50 |
- y |
- |
-
-
- | 49 |
- 081610.17 |
- BXD48 |
- M |
- black |
- 06/03/2010 |
- 40 |
- 08/18/2010 |
- 76 |
- 3.3 |
- 2.05 |
- 8.20 |
- y |
- |
-
-
- | 50 |
- 081710.29 |
- BXD49 |
- M |
- gray |
- 05/25/2010 |
- 49 |
- 08/17/2010 |
- 84 |
- 1.6 |
- 1.97 |
- 7.10 |
- y |
- |
-
-
- | 51 |
- 081710.34 |
- BXD49 |
- F |
- gray |
- 05/25/2010 |
- 24 |
- 08/17/2010 |
- 84 |
- 1.0 |
- 1.95 |
- 8.50 |
- y |
- |
-
-
- | 52 |
- 081610.29 |
- BXD50 |
- F |
- black |
- 06/02/2010 |
- 35 |
- 08/18/2010 |
- 77 |
- 3.3 |
- 2.05 |
- 8.40 |
- y |
- |
-
-
- | 53 |
- 081610.32 |
- BXD50 |
- M |
- black |
- 06/02/2010 |
- 35 |
- 08/18/2010 |
- 77 |
- 9.1 |
- 2.03 |
- 8.40 |
- y |
- |
-
-
- | 54 |
- 081610.36 |
- BXD56 |
- M |
- black |
- 06/02/2010 |
- 34 |
- 08/18/2010 |
- 77 |
- 1.9 |
- 2.02 |
- 9.60 |
- y |
- |
-
-
- | 55 |
- 081610.77 |
- BXD56 |
- F |
- black |
- 05/26/2010 |
- 34 |
- 08/18/2010 |
- 84 |
- 3.4 |
- 2.05 |
- 8.20 |
- y |
- |
-
-
- | 56 |
- 081610.80 |
- BXD56 |
- F |
- black |
- 05/26/2010 |
- 33 |
- 08/18/2010 |
- 84 |
- 3.2 |
- 2.05 |
- 8.50 |
- |
- |
-
-
- | 57 |
- 081710.67 |
- BXD60 |
- M |
- brown |
- 06/08/2010 |
- 43 |
- 08/17/2010 |
- 70 |
- 0.9 |
- 1.91 |
- 8.40 |
- y |
- need one more female |
-
-
- | 58 |
- 081810.83 |
- BXD62 |
- M |
- brown |
- 05/27/2010 |
- 41 |
- 08/18/2010 |
- 83 |
- 0.5 |
- 1.95 |
- 8.10 |
- y |
- need one more female |
-
-
- | 59 |
- 081610.22 |
- BXD63 |
- M |
- dilute brown DBA |
- 06/02/2010 |
- 31 |
- 08/18/2010 |
- 77 |
- 6.9 |
- 2.07 |
- 8.50 |
- y |
- |
-
-
- | 60 |
- 081610.25 |
- BXD63 |
- F |
- dilute brown DBA |
- 06/02/2010 |
- 31 |
- 08/18/2010 |
- 77 |
- 2.2 |
- 2.00 |
- 8.70 |
- y |
- |
-
-
- | 61 |
- 081610.03 |
- BXD65 |
- M |
- brown |
- 05/26/2010 |
- 32 |
- 08/18/2010 |
- 84 |
- 11.2 |
- 2.03 |
- 8.70 |
- y |
- |
-
-
- | 62 |
- 081610.11 |
- BXD65 |
- F |
- brown |
- 05/26/2010 |
- 32 |
- 08/18/2010 |
- 84 |
- 3.1 |
- 2.03 |
- 9.10 |
- y |
- |
-
-
- | 63 |
- 081610.96 |
- BXD68 |
- F |
- brown |
- 06/03/2010 |
- 33 |
- 08/18/2010 |
- 76 |
- 4.0 |
- 2.03 |
- 8.20 |
- y |
- |
-
-
- | 64 |
- 081610.99 |
- BXD68 |
- M |
- brown |
- 06/03/2010 |
- 33 |
- 08/18/2010 |
- 76 |
- 3.4 |
- 2.09 |
- 7.80 |
- y |
- |
-
-
- | 65 |
- 081710.71 |
- BXD69 |
- M |
- dilute brown DBA |
- 05/29/2010 |
- 41 |
- 08/17/2010 |
- 80 |
- 1.3 |
- 1.96 |
- 7.90 |
- y |
- |
-
-
- | 66 |
- 081710.78 |
- BXD69 |
- F |
- dilute brown DBA |
- 06/09/2010 |
- 42 |
- 08/17/2010 |
- 69 |
- 0.8 |
- 1.90 |
- 8.50 |
- y |
- |
-
-
- | 67 |
- 081610.85 |
- BXD70 |
- M |
- dilute brown DBA |
- 06/03/2010 |
- 36 |
- 08/18/2010 |
- 76 |
- 4.6 |
- 1.99 |
- 9.40 |
- y |
- |
-
-
- | 68 |
- 081610.92 |
- BXD70 |
- F |
- dilute brown DBA |
- 06/03/2010 |
- 36 |
- 08/18/2010 |
- 76 |
- 3.1 |
- 2.07 |
- 8.50 |
- y |
- |
-
-
- | 69 |
- 081910.33 |
- BXD71 |
- F |
- dilute brown DBA |
- 06/03/2010 |
- 35 |
- 08/18/2010 |
- 76 |
- 2.8 |
- 2.05 |
- 8.00 |
- y |
- |
-
-
- | 70 |
- 081910.38 |
- BXD71 |
- M |
- dilute brown DBA |
- 06/03/2010 |
- 35 |
- 08/18/2010 |
- 76 |
- 4.6 |
- 2.02 |
- 8.30 |
- y |
- |
-
-
- | 71 |
- 081710.81 |
- BXD73 |
- F |
- dilute brown DBA |
- 05/26/2010 |
- 44 |
- 08/17/2010 |
- 83 |
- 0.8 |
- 1.90 |
- 8.60 |
- y |
- |
-
-
- | 72 |
- 081710.83 |
- BXD73 |
- M |
- dilute brown DBA |
- 05/26/2010 |
- 41 |
- 08/17/2010 |
- 83 |
- 0.8 |
- 1.91 |
- 8.40 |
- y |
- |
-
-
- | 73 |
- 081810.58 |
- BXD75 |
- M |
- dilute brown DBA |
- 06/03/2010 |
- 39 |
- 08/18/2010 |
- 76 |
- 0.8 |
- 1.95 |
- 8.70 |
- y |
- |
-
-
- | 74 |
- 081810.73 |
- BXD75 |
- F |
- dilute brown DBA |
- 06/03/2010 |
- 39 |
- 08/18/2010 |
- 76 |
- 0.7 |
- 1.92 |
- 9.30 |
- y |
- |
-
-
- | 75 |
- 081710.06 |
- BXD79 |
- F |
- gray |
- 05/23/2010 |
- 24 |
- 08/18/2010 |
- 87 |
- 2.9 |
- 2.04 |
- 8.60 |
- y |
- |
-
-
- | 76 |
- 081710.08 |
- BXD79 |
- M |
- gray |
- 05/23/2010 |
- 24 |
- 08/18/2010 |
- 87 |
- 2.1 |
- 2.01 |
- 9.40 |
- y |
- |
-
-
- | 77 |
- 081710.87 |
- BXD80 |
- F |
- dilute brown DBA |
- 06/05/2010 |
- 33 |
- 08/17/2010 |
- 73 |
- 1.2 |
- 1.95 |
- 8.20 |
- y |
- |
-
-
- | 78 |
- 081710.88 |
- BXD80 |
- M |
- dilute brown DBA |
- 06/05/2010 |
- 33 |
- 08/17/2010 |
- 73 |
- 0.8 |
- 1.91 |
- 8.00 |
- y |
- |
-
-
- | 79 |
- 081610.64 |
- BXD83 |
- M |
- dilute brown DBA |
- 05/29/2010 |
- 32 |
- 08/18/2010 |
- 81 |
- 2.5 |
- 2.04 |
- 8.50 |
- y |
- |
-
-
- | 80 |
- 081610.69 |
- BXD83 |
- F |
- dilute brown DBA |
- 05/29/2010 |
- 32 |
- 08/18/2010 |
- 81 |
- 2.7 |
- 2.05 |
- 8.20 |
- y |
- |
-
-
- | 81 |
- 081810.80 |
- BXD84 |
- F |
- dilute brown DBA |
- 06/03/2010 |
- 31 |
- 08/18/2010 |
- 76 |
- 0.9 |
- 1.96 |
- 8.80 |
- y |
- need one more male |
-
-
- | 82 |
- 081710.10 |
- BXD85 |
- F |
- dilute brown DBA |
- 06/05/2010 |
- 40 |
- 08/18/2010 |
- 74 |
- 3.7 |
- 2.04 |
- 7.90 |
- y |
- |
-
-
- | 83 |
- 081710.13 |
- BXD85 |
- M |
- dilute brown DBA |
- 06/05/2010 |
- 40 |
- 08/18/2010 |
- 74 |
- 2.9 |
- 2.06 |
- 8.40 |
- y |
- |
-
-
- | 84 |
- 081610.60 |
- BXD87 |
- M |
- black |
- 05/27/2010 |
- 35 |
- 08/18/2010 |
- 83 |
- 3.4 |
- 2.04 |
- 8.30 |
- y |
- |
-
-
- | 85 |
- 081610.63 |
- BXD87 |
- F |
- black |
- 05/27/2010 |
- 35 |
- 08/18/2010 |
- 83 |
- 3.1 |
- 2.05 |
- 8.40 |
- y |
- |
-
-
- | 86 |
- 081610.40 |
- BXD89 |
- M |
- dilute brown DBA |
- 05/28/2010 |
- 36 |
- 08/18/2010 |
- 82 |
- 2.6 |
- 2.05 |
- 8.50 |
- y |
- need one more female |
-
-
- | 87 |
- 081610.53 |
- BXD90 |
- F |
- dilute brown DBA |
- 05/28/2010 |
- 39 |
- 08/18/2010 |
- 82 |
- 9.1 |
- 2.06 |
- 8.60 |
- y |
- |
-
-
- | 88 |
- 081610.57 |
- BXD90 |
- M |
- dilute brown DBA |
- 05/28/2010 |
- 39 |
- 08/18/2010 |
- 82 |
- 2.1 |
- 2.02 |
- 9.40 |
- y |
- |
-
-
- | 89 |
- 081610.87 |
- BXD92A |
- F |
- brown |
- 05/24/2010 |
- 42 |
- 08/18/2010 |
- 86 |
- 2.6 |
- 2.05 |
- 8.60 |
- y |
- |
-
-
- | 90 |
- 081610.93 |
- BXD92A |
- M |
- brown |
- 05/21/2010 |
- 42 |
- 08/18/2010 |
- 89 |
- 8.5 |
- 2.07 |
- 8.80 |
- y |
- |
-
-
- | 91 |
- 081910.32 |
- BXD95 |
- M |
- dilute brown DBA |
- 06/03/2010 |
- 25 |
- 08/18/2010 |
- 76 |
- 2.7 |
- 2.05 |
- 9.20 |
- y |
- |
-
-
- | 92 |
- 081610.81 |
- BXD95 |
- F |
- dilute brown DBA |
- 06/03/2010 |
- 25 |
- 08/18/2010 |
- 76 |
- 3.2 |
- 2.07 |
- 8.70 |
- y |
- |
-
-
- | 93 |
- 081610.84 |
- BXD95 |
- M |
- dilute brown DBA |
- 06/03/2010 |
- 25 |
- 08/18/2010 |
- 76 |
- 13.3 |
- 1.97 |
- 7.70 |
- |
- |
-
-
- | 94 |
- 081610.47 |
- BXD97 |
- F |
- brown |
- 06/08/2010 |
- 35 |
- 08/18/2010 |
- 71 |
- 2.3 |
- 2.00 |
- 9.10 |
- y |
- need one more male |
-
-
- | 95 |
- 081610.06 |
- BXD99 |
- F |
- dilute brown DBA |
- 06/02/2010 |
- 28 |
- 08/18/2010 |
- 77 |
- 4.2 |
- 2.01 |
- 9.00 |
- y |
- |
-
-
- | 96 |
- 081610.20 |
- BXD99 |
- M |
- dilute brown DBA |
- 06/02/2010 |
- 28 |
- 08/18/2010 |
- 77 |
- 2.2 |
- 2.00 |
- 8.90 |
- y |
- |
-
-
- | 97 |
- 081810.63 |
- BXD100 |
- M |
- black |
- 05/27/2010 |
- 30 |
- 08/18/2010 |
- 83 |
- 0.7 |
- 1.90 |
- 8.60 |
- y |
- |
-
-
- | 98 |
- 081810.75 |
- BXD100 |
- F |
- black |
- 05/27/2010 |
- 30 |
- 08/18/2010 |
- 83 |
- 0.9 |
- 1.95 |
- 8.10 |
- y |
- |
-
-
- | 99 |
- 081710.14 |
- BXD101 |
- M |
- gray |
- 05/21/2010 |
- 27 |
- 08/18/2010 |
- 89 |
- 2.9 |
- 2.05 |
- 8.90 |
- y |
- |
-
-
- | 100 |
- 081710.19 |
- BXD101 |
- F |
- gray |
- 05/21/2010 |
- 27 |
- 08/18/2010 |
- 89 |
- 3.2 |
- 2.06 |
- 8.30 |
- y |
- |
-
-
- | 101 |
- 081710.41 |
- BXD102 |
- F |
- brown |
- 05/21/2010 |
- 25 |
- 08/17/2010 |
- 88 |
- 1.5 |
- 1.95 |
- 7.70 |
- y |
- |
-
-
- | 102 |
- 081710.45 |
- BXD102 |
- M |
- brown |
- 05/21/2010 |
- 25 |
- 08/17/2010 |
- 88 |
- 1.2 |
- 1.97 |
- 7.70 |
- y |
- |
-
-
- | 103 |
- 081710.58 |
- BXD103 |
- M |
- dilute brown DBA |
- 05/31/2010 |
- 21 |
- 08/17/2010 |
- 78 |
- 1.1 |
- 1.94 |
- 8.40 |
- y |
- |
-
-
- | 104 |
- 081710.62 |
- BXD103 |
- F |
- dilute brown DBA |
- 05/31/2010 |
- 21 |
- 08/17/2010 |
- 78 |
- 0.6 |
- 1.91 |
- 8.40 |
- y |
- |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_GutGL_0414/platform.rtf b/general/datasets/UTHSC_GutGL_0414/platform.rtf
deleted file mode 100644
index 79244c6..0000000
--- a/general/datasets/UTHSC_GutGL_0414/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version]
diff --git a/general/datasets/UTHSC_GutGL_0414/processing.rtf b/general/datasets/UTHSC_GutGL_0414/processing.rtf
deleted file mode 100644
index ebfa292..0000000
--- a/general/datasets/UTHSC_GutGL_0414/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This dataset includes Gene and Exon level RMA normalization.
diff --git a/general/datasets/UTHSC_GutGL_0414/specifics.rtf b/general/datasets/UTHSC_GutGL_0414/specifics.rtf
deleted file mode 100644
index d877bcf..0000000
--- a/general/datasets/UTHSC_GutGL_0414/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Gene Level
diff --git a/general/datasets/UTHSC_GutGL_0414/tissue.rtf b/general/datasets/UTHSC_GutGL_0414/tissue.rtf
deleted file mode 100644
index 5653e30..0000000
--- a/general/datasets/UTHSC_GutGL_0414/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Approximately two equal-sized segments of the small intestine were pooled per animal: one taken from the proximal jejunum and one from the distal ileum. We did generate a second data set (not in GeneNetwork) for different segments of the the GI tract from stomach to distal colon for C57BL/6J and DBA/2J parental strains. These additional data are available upon request from Drs. Dennis Black and Lu Lu.
diff --git a/general/datasets/UTHSC_HuIslets_Mar17/platform.rtf b/general/datasets/UTHSC_HuIslets_Mar17/platform.rtf
deleted file mode 100644
index 10c6122..0000000
--- a/general/datasets/UTHSC_HuIslets_Mar17/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Affymetrix Human Gene 2.0 ST Array
diff --git a/general/datasets/UTHSC_HuIslets_Mar17/summary.rtf b/general/datasets/UTHSC_HuIslets_Mar17/summary.rtf
deleted file mode 100644
index e59b6f7..0000000
--- a/general/datasets/UTHSC_HuIslets_Mar17/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Info file in progress...
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0216/notes.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0216/notes.rtf
deleted file mode 100644
index 35247b6..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0216/notes.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Hippocampus 5 Conditions
-Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
-Batch and Outlier Analysis on Partek Genomic Suite 6.6
-ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
-K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
-Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
-Number of samples = 284
-Number of probes = 46643
-
-
- - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
- - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
- - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
- - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
- ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
- - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
- ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
- - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
-
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0216/summary.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0216/summary.rtf
deleted file mode 100644
index 5aeb69c..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0216/summary.rtf
+++ /dev/null
@@ -1,39 +0,0 @@
-This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
-
-For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
-
-Restraint Stress Protocol
-
-
- - Weigh animals all animals to be tested and record body weight.
- - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
- - Place animals in immobilization tubes for 15 minutes.
- - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
- - Place each animal into zero-maze for 10 minutes.
- - Return animal to home cage.
- - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
-
-
-Ethanol and saline injections
-Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
-
-"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
-
-Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
-
-Quality Control Data
-Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
-
-
- - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
- - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
- - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
- - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
- - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
-
-
-Entered by Arthur Centeno, September 20, 2010.
-
-Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
-
-Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0217/notes.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0217/notes.rtf
deleted file mode 100644
index 35247b6..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0217/notes.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Hippocampus 5 Conditions
-Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
-Batch and Outlier Analysis on Partek Genomic Suite 6.6
-ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
-K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
-Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
-Number of samples = 284
-Number of probes = 46643
-
-
- - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
- - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
- - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
- - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
- ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
- - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
- ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
- - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
-
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0217/specifics.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0217/specifics.rtf
deleted file mode 100644
index 340fc0e..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0217/specifics.rtf
+++ /dev/null
@@ -1,392 +0,0 @@
-NOE = No restraint stress and given an ethanol injection prior to sacrifice.
-
-
-
-
-
-
-
-
-
- | Index |
- Array ID |
- Condition |
- Strain |
- Sex |
- Age |
-
-
- | 1 |
- 4060001078_D |
- NOE |
- BXD34 |
- F |
- 75 |
-
-
- | 2 |
- 4060001088_A |
- NOE |
- BXD43 |
- F |
- 67 |
-
-
- | 3 |
- 4207851040_C |
- NOE |
- BXD43 |
- F |
- 65 |
-
-
- | 4 |
- 4207851040_D |
- NOE |
- BXD45 |
- F |
- 71 |
-
-
- | 5 |
- 4207851041_C |
- NOE |
- BXD45 |
- M |
- 68 |
-
-
- | 6 |
- 4068846016_D |
- NOE |
- BXD51 |
- F |
- 73 |
-
-
- | 7 |
- 4207851035_D |
- NOE |
- BXD51 |
- M |
- 85 |
-
-
- | 8 |
- 4060001003_C |
- NOE |
- BXD55 |
- F |
- 79 |
-
-
- | 9 |
- 4068846016_C |
- NOE |
- BXD55 |
- M |
- 68 |
-
-
- | 10 |
- 4060001071_A |
- NOE |
- BXD60 |
- F |
- 76 |
-
-
- | 11 |
- 4068846016_A |
- NOE |
- BXD60 |
- M |
- 67 |
-
-
- | 12 |
- 4060001003_D |
- NOE |
- BXD61 |
- M |
- 67 |
-
-
- | 13 |
- 4207851041_A |
- NOE |
- BXD61 |
- F |
- 70 |
-
-
- | 14 |
- 4060001075_F |
- NOE |
- BXD62 |
- M |
- 68 |
-
-
- | 15 |
- 4207851041_B |
- NOE |
- BXD62 |
- F |
- 67 |
-
-
- | 16 |
- 4207851035_A |
- NOE |
- BXD66 |
- F |
- 73 |
-
-
- | 17 |
- 4256265071_C |
- NOE |
- BXD66 |
- M |
- 63 |
-
-
- | 18 |
- 4207851035_B |
- NOE |
- BXD68 |
- M |
- 66 |
-
-
- | 19 |
- 4256265026_E |
- NOE |
- BXD68 |
- F |
- 67 |
-
-
- | 20 |
- 4060001010_F |
- NOE |
- BXD70 |
- M |
- 87 |
-
-
- | 21 |
- 4207851045_B |
- NOE |
- BXD70 |
- F |
- 69 |
-
-
- | 22 |
- 4256265057_A |
- NOE |
- BXD71 |
- F |
- 76 |
-
-
- | 23 |
- 4256265087_C |
- NOE |
- BXD71 |
- M |
- 75 |
-
-
- | 24 |
- 4256265042_B |
- NOE |
- BXD73 |
- F |
- 66 |
-
-
- | 25 |
- 4060001010_E |
- NOE |
- BXD75 |
- F |
- 70 |
-
-
- | 26 |
- 4256265042_C |
- NOE |
- BXD75 |
- M |
- 69 |
-
-
- | 27 |
- 4060001083_A |
- NOE |
- BXD83 |
- M |
- 69 |
-
-
- | 28 |
- 4256265071_D |
- NOE |
- BXD83 |
- F |
- 80 |
-
-
- | 29 |
- 4256265045_C |
- NOE |
- BXD84 |
- F |
- 68 |
-
-
- | 30 |
- 4207851058_A |
- NOE |
- BXD87 |
- F |
- 63 |
-
-
- | 31 |
- 4256265080_C |
- NOE |
- BXD87 |
- M |
- 65 |
-
-
- | 32 |
- 4207851058_B |
- NOE |
- BXD89 |
- M |
- 68 |
-
-
- | 33 |
- 4256265024_A |
- NOE |
- BXD89 |
- F |
- 71 |
-
-
- | 34 |
- 4256265024_B |
- NOE |
- BXD90 |
- F |
- 68 |
-
-
- | 35 |
- 4256265052_A |
- NOE |
- BXD90 |
- M |
- 74 |
-
-
- | 36 |
- 4256265023_A |
- NOE |
- BXD96 |
- M |
- 68 |
-
-
- | 37 |
- 4256265023_F |
- NOE |
- BXD96 |
- F |
- 68 |
-
-
- | 38 |
- 4256265044_A |
- NOE |
- BXD96 |
- M |
- 68 |
-
-
- | 39 |
- 4068846017_B |
- NOE |
- BXD97 |
- M |
- 67 |
-
-
- | 40 |
- 4068846017_A |
- NOE |
- BXD98 |
- F |
- 74 |
-
-
- | 41 |
- 4207851052_F |
- NOE |
- BXD98 |
- M |
- 71 |
-
-
- | 42 |
- 4068846021_F |
- NOE |
- BXD99 |
- M |
- 70 |
-
-
- | 43 |
- 4060001088_E |
- NOE |
- BXD100 |
- F |
- 61 |
-
-
- | 44 |
- 4060001088_D |
- NOE |
- BXD101 |
- M |
- 71 |
-
-
- | 45 |
- 4060001030_D |
- NOE |
- DBA/2J |
- F |
- 79 |
-
-
- | 46 |
- 4256265069_F |
- NOE |
- DBA/2J |
- F |
- 79 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0217/summary.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0217/summary.rtf
deleted file mode 100644
index 5aeb69c..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_NOEb_0217/summary.rtf
+++ /dev/null
@@ -1,39 +0,0 @@
-This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
-
-For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
-
-Restraint Stress Protocol
-
-
- - Weigh animals all animals to be tested and record body weight.
- - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
- - Place animals in immobilization tubes for 15 minutes.
- - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
- - Place each animal into zero-maze for 10 minutes.
- - Return animal to home cage.
- - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
-
-
-Ethanol and saline injections
-Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
-
-"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
-
-Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
-
-Quality Control Data
-Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
-
-
- - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
- - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
- - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
- - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
- - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
-
-
-Entered by Arthur Centeno, September 20, 2010.
-
-Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
-
-Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_NOSb_0217/notes.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_NOSb_0217/notes.rtf
deleted file mode 100644
index 35247b6..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_NOSb_0217/notes.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Hippocampus 5 Conditions
-Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
-Batch and Outlier Analysis on Partek Genomic Suite 6.6
-ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
-K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
-Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
-Number of samples = 284
-Number of probes = 46643
-
-
- - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
- - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
- - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
- - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
- ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
- - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
- ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
- - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
-
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_NOSb_0217/specifics.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_NOSb_0217/specifics.rtf
deleted file mode 100644
index e60e427..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_NOSb_0217/specifics.rtf
+++ /dev/null
@@ -1,408 +0,0 @@
-NOS = No restraint stress and given only saline injections prior to sacrifice.
-
-
-
-
-
-
-
-
-
- | Index |
- Array ID |
- Condition |
- Strain |
- Sex |
- Age |
-
-
- | 1 |
- 4207851040_B |
- NOS |
- BXD34 |
- M |
- 67 |
-
-
- | 2 |
- 4207851045_E |
- NOS |
- BXD43 |
- F |
- 75 |
-
-
- | 3 |
- 4256265009_D |
- NOS |
- BXD43 |
- M |
- 64 |
-
-
- | 4 |
- 4060001010_A |
- NOS |
- BXD45 |
- F |
- 81 |
-
-
- | 5 |
- 4068846016_E |
- NOS |
- BXD45 |
- M |
- 65 |
-
-
- | 6 |
- 4060001011_A |
- NOS |
- BXD51 |
- F |
- 85 |
-
-
- | 7 |
- 4060001082_B |
- NOS |
- BXD51 |
- M |
- 75 |
-
-
- | 8 |
- 4060001082_F |
- NOS |
- BXD55 |
- F |
- 62 |
-
-
- | 9 |
- 4256265070_B |
- NOS |
- BXD55 |
- M |
- 76 |
-
-
- | 10 |
- 4207851041_F |
- NOS |
- BXD60 |
- F |
- 76 |
-
-
- | 11 |
- 4256265071_B |
- NOS |
- BXD60 |
- M |
- 77 |
-
-
- | 12 |
- 4060001069_A |
- NOS |
- BXD61 |
- F |
- 78 |
-
-
- | 13 |
- 4207851051_C |
- NOS |
- BXD61 |
- M |
- 78 |
-
-
- | 14 |
- 4207851053_D |
- NOS |
- BXD62 |
- F |
- 67 |
-
-
- | 15 |
- 4256265043_A |
- NOS |
- BXD62 |
- M |
- 68 |
-
-
- | 16 |
- 4207851051_E |
- NOS |
- BXD66 |
- M |
- 63 |
-
-
- | 17 |
- 4256265074_C |
- NOS |
- BXD66 |
- F |
- 69 |
-
-
- | 18 |
- 4207851038_B |
- NOS |
- BXD68 |
- F |
- 69 |
-
-
- | 19 |
- 4256265044_C |
- NOS |
- BXD68 |
- M |
- 66 |
-
-
- | 20 |
- 4256265070_A |
- NOS |
- BXD70 |
- F |
- 61 |
-
-
- | 21 |
- 4256265083_D |
- NOS |
- BXD70 |
- M |
- 67 |
-
-
- | 22 |
- 4060001096_B |
- NOS |
- BXD71 |
- M |
- 83 |
-
-
- | 23 |
- 4256265071_A |
- NOS |
- BXD71 |
- F |
- 0 |
-
-
- | 24 |
- 4256265057_E |
- NOS |
- BXD73 |
- F |
- 66 |
-
-
- | 25 |
- 4256265074_A |
- NOS |
- BXD73 |
- M |
- 69 |
-
-
- | 26 |
- 4060001078_B |
- NOS |
- BXD75 |
- M |
- 70 |
-
-
- | 27 |
- 4207851058_E |
- NOS |
- BXD75 |
- F |
- 68 |
-
-
- | 28 |
- 4207851051_A |
- NOS |
- BXD83 |
- M |
- 67 |
-
-
- | 29 |
- 4256265023_B |
- NOS |
- BXD83 |
- F |
- 70 |
-
-
- | 30 |
- 4256265083_C |
- NOS |
- BXD84 |
- M |
- 69 |
-
-
- | 31 |
- 4256265085_F |
- NOS |
- BXD84 |
- M |
- 67 |
-
-
- | 32 |
- 4207851045_F |
- NOS |
- BXD87 |
- M |
- 68 |
-
-
- | 33 |
- 4068846021_B |
- NOS |
- BXD89 |
- F |
- 69 |
-
-
- | 34 |
- 4256265073_F |
- NOS |
- BXD89 |
- M |
- 69 |
-
-
- | 35 |
- 4256265080_E |
- NOS |
- BXD90 |
- M |
- 73 |
-
-
- | 36 |
- 4256265085_E |
- NOS |
- BXD90 |
- F |
- 73 |
-
-
- | 37 |
- 4060001010_B |
- NOS |
- BXD96 |
- M |
- 68 |
-
-
- | 38 |
- 4060001071_D |
- NOS |
- BXD96 |
- F |
- 69 |
-
-
- | 39 |
- 4207851052_C |
- NOS |
- BXD96 |
- M |
- 69 |
-
-
- | 40 |
- 4060001011_B |
- NOS |
- BXD97 |
- M |
- 68 |
-
-
- | 41 |
- 4060001082_A |
- NOS |
- BXD98 |
- F |
- 72 |
-
-
- | 42 |
- 4256265058_F |
- NOS |
- BXD98 |
- M |
- 70 |
-
-
- | 43 |
- 4256265051_F |
- NOS |
- BXD99 |
- M |
- 70 |
-
-
- | 44 |
- 4060001075_E |
- NOS |
- BXD100 |
- F |
- 63 |
-
-
- | 45 |
- 4207851035_E |
- NOS |
- BXD100 |
- M |
- 72 |
-
-
- | 46 |
- 4060001075_D |
- NOS |
- BXD101 |
- M |
- 78 |
-
-
- | 47 |
- 4060001030_F |
- NOS |
- DBA/2J |
- M |
- 63 |
-
-
- | 48 |
- 4060001012_B |
- NOS |
- DBA/2J |
- F |
- 81 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_NOSb_0217/summary.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_NOSb_0217/summary.rtf
deleted file mode 100644
index 5aeb69c..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_NOSb_0217/summary.rtf
+++ /dev/null
@@ -1,39 +0,0 @@
-This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
-
-For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
-
-Restraint Stress Protocol
-
-
- - Weigh animals all animals to be tested and record body weight.
- - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
- - Place animals in immobilization tubes for 15 minutes.
- - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
- - Place each animal into zero-maze for 10 minutes.
- - Return animal to home cage.
- - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
-
-
-Ethanol and saline injections
-Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
-
-"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
-
-Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
-
-Quality Control Data
-Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
-
-
- - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
- - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
- - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
- - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
- - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
-
-
-Entered by Arthur Centeno, September 20, 2010.
-
-Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
-
-Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0216/notes.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0216/notes.rtf
deleted file mode 100644
index 35247b6..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0216/notes.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Hippocampus 5 Conditions
-Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
-Batch and Outlier Analysis on Partek Genomic Suite 6.6
-ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
-K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
-Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
-Number of samples = 284
-Number of probes = 46643
-
-
- - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
- - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
- - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
- - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
- ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
- - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
- ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
- - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
-
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0216/summary.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0216/summary.rtf
deleted file mode 100644
index 5aeb69c..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0216/summary.rtf
+++ /dev/null
@@ -1,39 +0,0 @@
-This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
-
-For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
-
-Restraint Stress Protocol
-
-
- - Weigh animals all animals to be tested and record body weight.
- - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
- - Place animals in immobilization tubes for 15 minutes.
- - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
- - Place each animal into zero-maze for 10 minutes.
- - Return animal to home cage.
- - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
-
-
-Ethanol and saline injections
-Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
-
-"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
-
-Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
-
-Quality Control Data
-Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
-
-
- - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
- - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
- - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
- - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
- - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
-
-
-Entered by Arthur Centeno, September 20, 2010.
-
-Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
-
-Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0217/notes.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0217/notes.rtf
deleted file mode 100644
index 35247b6..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0217/notes.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Hippocampus 5 Conditions
-Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
-Batch and Outlier Analysis on Partek Genomic Suite 6.6
-ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
-K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
-Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
-Number of samples = 284
-Number of probes = 46643
-
-
- - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
- - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
- - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
- - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
- ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
- - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
- ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
- - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
-
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0217/specifics.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0217/specifics.rtf
deleted file mode 100644
index 01586d5..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0217/specifics.rtf
+++ /dev/null
@@ -1,408 +0,0 @@
-RSE = Restraint stress followed by an ethanol injection.
-
-
-
-
-
-
-
-
-
- | Index |
- Array ID |
- Condition |
- Strain |
- Sex |
- Age |
-
-
- | 1 |
- 4060001088_B |
- RSE |
- BXD34 |
- M |
- 71 |
-
-
- | 2 |
- 4256265042_E |
- RSE |
- BXD43 |
- M |
- 72 |
-
-
- | 3 |
- 4256265052_B |
- RSE |
- BXD43 |
- F |
- 73 |
-
-
- | 4 |
- 4256265051_A |
- RSE |
- BXD45 |
- F |
- 60 |
-
-
- | 5 |
- 4256265070_F |
- RSE |
- BXD45 |
- M |
- 67 |
-
-
- | 6 |
- 4207851041_D |
- RSE |
- BXD51 |
- F |
- 66 |
-
-
- | 7 |
- 4207851058_C |
- RSE |
- BXD51 |
- M |
- 85 |
-
-
- | 8 |
- 4207851035_F |
- RSE |
- BXD55 |
- M |
- 62 |
-
-
- | 9 |
- 4207851041_E |
- RSE |
- BXD55 |
- M |
- 62 |
-
-
- | 10 |
- 4060001082_D |
- RSE |
- BXD60 |
- F |
- 76 |
-
-
- | 11 |
- 4256265043_D |
- RSE |
- BXD60 |
- M |
- 67 |
-
-
- | 12 |
- 4256265043_E |
- RSE |
- BXD61 |
- F |
- 70 |
-
-
- | 13 |
- 4256265087_E |
- RSE |
- BXD61 |
- M |
- 70 |
-
-
- | 14 |
- 4060001010_C |
- RSE |
- BXD62 |
- F |
- 69 |
-
-
- | 15 |
- 4207851027_A |
- RSE |
- BXD62 |
- M |
- 67 |
-
-
- | 16 |
- 4207851027_C |
- RSE |
- BXD66 |
- M |
- 74 |
-
-
- | 17 |
- 4060001011_C |
- RSE |
- BXD66 |
- F |
- 79 |
-
-
- | 18 |
- 4207851049_D |
- RSE |
- BXD68 |
- F |
- 73 |
-
-
- | 19 |
- 4256265071_F |
- RSE |
- BXD68 |
- M |
- 62 |
-
-
- | 20 |
- 4060001011_D |
- RSE |
- BXD70 |
- M |
- 82 |
-
-
- | 21 |
- 4256265044_D |
- RSE |
- BXD70 |
- F |
- 69 |
-
-
- | 22 |
- 4060001078_F |
- RSE |
- BXD71 |
- M |
- 70 |
-
-
- | 23 |
- 4207851027_D |
- RSE |
- BXD71 |
- F |
- 76 |
-
-
- | 24 |
- 4060001075_A |
- RSE |
- BXD73 |
- M |
- 69 |
-
-
- | 25 |
- 4256265073_C |
- RSE |
- BXD73 |
- F |
- 68 |
-
-
- | 26 |
- 4256265063_A |
- RSE |
- BXD75 |
- F |
- 66 |
-
-
- | 27 |
- 4256265083_F |
- RSE |
- BXD75 |
- M |
- 69 |
-
-
- | 28 |
- 4256265083_E |
- RSE |
- BXD83 |
- F |
- 87 |
-
-
- | 29 |
- 4256265085_B |
- RSE |
- BXD83 |
- M |
- 73 |
-
-
- | 30 |
- 4256265071_E |
- RSE |
- BXD84 |
- F |
- 51 |
-
-
- | 31 |
- 4256265086_D |
- RSE |
- BXD84 |
- M |
- 68 |
-
-
- | 32 |
- 4256265085_A |
- RSE |
- BXD87 |
- F |
- 64 |
-
-
- | 33 |
- 4256265086_E |
- RSE |
- BXD87 |
- M |
- 69 |
-
-
- | 34 |
- 4256265026_A |
- RSE |
- BXD89 |
- F |
- 74 |
-
-
- | 35 |
- 4256265057_D |
- RSE |
- BXD89 |
- M |
- 68 |
-
-
- | 36 |
- 4060001075_B |
- RSE |
- BXD90 |
- F |
- 72 |
-
-
- | 37 |
- 4256265086_F |
- RSE |
- BXD90 |
- M |
- 70 |
-
-
- | 38 |
- 4207851014_E |
- RSE |
- BXD96 |
- F |
- 67 |
-
-
- | 39 |
- 4256265063_D |
- RSE |
- BXD96 |
- M |
- 64 |
-
-
- | 40 |
- 4060001096_C |
- RSE |
- BXD97 |
- M |
- 65 |
-
-
- | 41 |
- 4256265062_D |
- RSE |
- BXD97 |
- M |
- 65 |
-
-
- | 42 |
- 4256265023_E |
- RSE |
- BXD98 |
- M |
- 75 |
-
-
- | 43 |
- 4256265063_F |
- RSE |
- BXD98 |
- M |
- 71 |
-
-
- | 44 |
- 4256265058_A |
- RSE |
- BXD99 |
- M |
- 76 |
-
-
- | 45 |
- 4256265026_B |
- RSE |
- BXD100 |
- M |
- 95 |
-
-
- | 46 |
- 4207851040_A |
- RSE |
- BXD101 |
- F |
- 69 |
-
-
- | 47 |
- 4060001031_F |
- RSE |
- DBA/2J |
- M |
- 76 |
-
-
- | 48 |
- 4256265069_C |
- RSE |
- DBA/2J |
- F |
- 86 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0217/summary.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0217/summary.rtf
deleted file mode 100644
index 5aeb69c..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_RSEb_0217/summary.rtf
+++ /dev/null
@@ -1,39 +0,0 @@
-This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
-
-For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
-
-Restraint Stress Protocol
-
-
- - Weigh animals all animals to be tested and record body weight.
- - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
- - Place animals in immobilization tubes for 15 minutes.
- - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
- - Place each animal into zero-maze for 10 minutes.
- - Return animal to home cage.
- - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
-
-
-Ethanol and saline injections
-Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
-
-"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
-
-Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
-
-Quality Control Data
-Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
-
-
- - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
- - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
- - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
- - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
- - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
-
-
-Entered by Arthur Centeno, September 20, 2010.
-
-Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
-
-Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0216/notes.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0216/notes.rtf
deleted file mode 100644
index 35247b6..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0216/notes.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Hippocampus 5 Conditions
-Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
-Batch and Outlier Analysis on Partek Genomic Suite 6.6
-ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
-K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
-Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
-Number of samples = 284
-Number of probes = 46643
-
-
- - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
- - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
- - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
- - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
- ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
- - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
- ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
- - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
-
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0216/summary.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0216/summary.rtf
deleted file mode 100644
index 5aeb69c..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0216/summary.rtf
+++ /dev/null
@@ -1,39 +0,0 @@
-This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
-
-For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
-
-Restraint Stress Protocol
-
-
- - Weigh animals all animals to be tested and record body weight.
- - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
- - Place animals in immobilization tubes for 15 minutes.
- - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
- - Place each animal into zero-maze for 10 minutes.
- - Return animal to home cage.
- - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
-
-
-Ethanol and saline injections
-Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
-
-"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
-
-Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
-
-Quality Control Data
-Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
-
-
- - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
- - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
- - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
- - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
- - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
-
-
-Entered by Arthur Centeno, September 20, 2010.
-
-Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
-
-Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0217/notes.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0217/notes.rtf
deleted file mode 100644
index 35247b6..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0217/notes.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Hippocampus 5 Conditions
-Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
-Batch and Outlier Analysis on Partek Genomic Suite 6.6
-ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
-K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
-Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
-Number of samples = 284
-Number of probes = 46643
-
-
- - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
- - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
- - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
- - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
- ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
- - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
- ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
- - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
-
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0217/specifics.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0217/specifics.rtf
deleted file mode 100644
index 6036ccb..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0217/specifics.rtf
+++ /dev/null
@@ -1,400 +0,0 @@
-RSS = short restraint stress (1 episode) followed by a saline injection.
-
-
-
-
-
-
-
-
-
- | Index |
- Array ID |
- Condition |
- Strain |
- Sex |
- Age |
-
-
- | 1 |
- 4207851045_D |
- RSS |
- BXD34 |
- M |
- 71 |
-
-
- | 2 |
- 4060001083_B |
- RSS |
- BXD43 |
- M |
- 72 |
-
-
- | 3 |
- 4068846017_C |
- RSS |
- BXD43 |
- F |
- 73 |
-
-
- | 4 |
- 4060001083_F |
- RSS |
- BXD45 |
- F |
- 67 |
-
-
- | 5 |
- 4256265070_D |
- RSS |
- BXD45 |
- M |
- 79 |
-
-
- | 6 |
- 4060001096_F |
- RSS |
- BXD51 |
- M |
- 75 |
-
-
- | 7 |
- 4256265045_E |
- RSS |
- BXD51 |
- F |
- 88 |
-
-
- | 8 |
- 4256265043_B |
- RSS |
- BXD55 |
- F |
- 67 |
-
-
- | 9 |
- 4256265024_D |
- RSS |
- BXD60 |
- M |
- 76 |
-
-
- | 10 |
- 4256265045_F |
- RSS |
- BXD60 |
- F |
- 72 |
-
-
- | 11 |
- 4207851058_D |
- RSS |
- BXD61 |
- F |
- 70 |
-
-
- | 12 |
- 4256265083_B |
- RSS |
- BXD61 |
- M |
- 82 |
-
-
- | 13 |
- 4068846017_E |
- RSS |
- BXD62 |
- F |
- 61 |
-
-
- | 14 |
- 4256265080_F |
- RSS |
- BXD62 |
- M |
- 67 |
-
-
- | 15 |
- 4207851052_A |
- RSS |
- BXD66 |
- M |
- 74 |
-
-
- | 16 |
- 4256265044_B |
- RSS |
- BXD66 |
- F |
- 69 |
-
-
- | 17 |
- 4060001003_E |
- RSS |
- BXD68 |
- F |
- 77 |
-
-
- | 18 |
- 4060001075_C |
- RSS |
- BXD68 |
- M |
- 64 |
-
-
- | 19 |
- 4068846021_E |
- RSS |
- BXD70 |
- M |
- 68 |
-
-
- | 20 |
- 4207851038_C |
- RSS |
- BXD70 |
- F |
- 69 |
-
-
- | 21 |
- 4060001003_F |
- RSS |
- BXD71 |
- M |
- 78 |
-
-
- | 22 |
- 4060001011_E |
- RSS |
- BXD71 |
- F |
- 76 |
-
-
- | 23 |
- 4207851014_A |
- RSS |
- BXD73 |
- F |
- 68 |
-
-
- | 24 |
- 4207851014_D |
- RSS |
- BXD73 |
- M |
- 67 |
-
-
- | 25 |
- 4051964017_A |
- RSS |
- BXD75 |
- F |
- 73 |
-
-
- | 26 |
- 4256265058_B |
- RSS |
- BXD75 |
- F |
- 69 |
-
-
- | 27 |
- 4256265058_C |
- RSS |
- BXD83 |
- F |
- 75 |
-
-
- | 28 |
- 4256265074_F |
- RSS |
- BXD83 |
- M |
- 69 |
-
-
- | 29 |
- 4256265062_B |
- RSS |
- BXD84 |
- F |
- 73 |
-
-
- | 30 |
- 4256265086_B |
- RSS |
- BXD84 |
- M |
- 69 |
-
-
- | 31 |
- 4207851051_F |
- RSS |
- BXD87 |
- M |
- 69 |
-
-
- | 32 |
- 4256265083_A |
- RSS |
- BXD89 |
- F |
- 59 |
-
-
- | 33 |
- 4256265073_A |
- RSS |
- BXD90 |
- F |
- 68 |
-
-
- | 34 |
- 4256265087_F |
- RSS |
- BXD90 |
- M |
- 68 |
-
-
- | 35 |
- 4207851051_B |
- RSS |
- BXD96 |
- M |
- 69 |
-
-
- | 36 |
- 4256265085_C |
- RSS |
- BXD96 |
- F |
- 76 |
-
-
- | 37 |
- 4060001079_F |
- RSS |
- BXD97 |
- F |
- 65 |
-
-
- | 38 |
- 4256265080_A |
- RSS |
- BXD97 |
- M |
- 70 |
-
-
- | 39 |
- 4060001011_F |
- RSS |
- BXD98 |
- M |
- 72 |
-
-
- | 40 |
- 4256265086_A |
- RSS |
- BXD98 |
- F |
- 72 |
-
-
- | 41 |
- 4207851014_C |
- RSS |
- BXD99 |
- M |
- 73 |
-
-
- | 42 |
- 4256265086_C |
- RSS |
- BXD99 |
- F |
- 86 |
-
-
- | 43 |
- 4060001068_F |
- RSS |
- BXD100 |
- M |
- 79 |
-
-
- | 44 |
- 4207851051_D |
- RSS |
- BXD100 |
- F |
- 68 |
-
-
- | 45 |
- 4207851045_C |
- RSS |
- BXD101 |
- F |
- 66 |
-
-
- | 46 |
- 4060001012_F |
- RSS |
- DBA/2J |
- F |
- 70 |
-
-
- | 47 |
- 4060001031_D |
- RSS |
- DBA/2J |
- F |
- 70 |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0217/summary.rtf b/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0217/summary.rtf
deleted file mode 100644
index 5aeb69c..0000000
--- a/general/datasets/UTHSC_ILM_BXD_hipp_RSSb_0217/summary.rtf
+++ /dev/null
@@ -1,39 +0,0 @@
-This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
-
-For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
-
-Restraint Stress Protocol
-
-
- - Weigh animals all animals to be tested and record body weight.
- - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
- - Place animals in immobilization tubes for 15 minutes.
- - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
- - Place each animal into zero-maze for 10 minutes.
- - Return animal to home cage.
- - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
-
-
-Ethanol and saline injections
-Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
-
-"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
-
-Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
-
-Quality Control Data
-Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
-
-
- - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
- - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
- - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
- - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
- - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
-
-
-Entered by Arthur Centeno, September 20, 2010.
-
-Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
-
-Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/UTHSC_Neut_1014/experiment-design.rtf b/general/datasets/UTHSC_Neut_1014/experiment-design.rtf
deleted file mode 100644
index eed4905..0000000
--- a/general/datasets/UTHSC_Neut_1014/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Normal young adults of either sex between 40 and 100 days of age.
diff --git a/general/datasets/UTHSC_Neut_1014/summary.rtf b/general/datasets/UTHSC_Neut_1014/summary.rtf
deleted file mode 100644
index edd0ac2..0000000
--- a/general/datasets/UTHSC_Neut_1014/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The data set represents gene expression data from peritoneal neutrophils. Cells were collected four hours after injection of sterile thioglycollate. Purity was assessed by cytospin and nuclear morphology. Usually 4 to 6 animals were used to generate sufficient material for RNA expression analysis.
diff --git a/general/datasets/UTHSC_Neut_EL_1014/experiment-design.rtf b/general/datasets/UTHSC_Neut_EL_1014/experiment-design.rtf
deleted file mode 100644
index eed4905..0000000
--- a/general/datasets/UTHSC_Neut_EL_1014/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Normal young adults of either sex between 40 and 100 days of age.
diff --git a/general/datasets/UTHSC_Neut_EL_1014/summary.rtf b/general/datasets/UTHSC_Neut_EL_1014/summary.rtf
deleted file mode 100644
index edd0ac2..0000000
--- a/general/datasets/UTHSC_Neut_EL_1014/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The data set represents gene expression data from peritoneal neutrophils. Cells were collected four hours after injection of sterile thioglycollate. Purity was assessed by cytospin and nuclear morphology. Usually 4 to 6 animals were used to generate sufficient material for RNA expression analysis.
diff --git a/general/datasets/UTHSC_SPL_RMAEx_1210/cases.rtf b/general/datasets/UTHSC_SPL_RMAEx_1210/cases.rtf
deleted file mode 100644
index 7fa108f..0000000
--- a/general/datasets/UTHSC_SPL_RMAEx_1210/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Cases. A total of 111 strains, including 81 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1), and 26 other common inbred strains were quantified. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by Lu Lu and colleagues. Samples were pooled by sex and usually include at least two cases per sex and strain.
-
-Sex Balance. XX strains have matched male and female samples. XX strains have male only samples (BXDX, XX, XX, XXX and XXX). XX strains have only female samples (BXDXX, XX, and XX.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/UTHSC_SPL_RMAEx_1210/experiment-design.rtf b/general/datasets/UTHSC_SPL_RMAEx_1210/experiment-design.rtf
deleted file mode 100644
index a0aeba6..0000000
--- a/general/datasets/UTHSC_SPL_RMAEx_1210/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA Processing. Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
-
-Array Processing: All arrays were processed by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. The spleen was dissected by both Dr. Lu Lu and colleagues and Dr. Abdeltawab and colleagues. All arrays were run together (interleaved) as a single large batch.
diff --git a/general/datasets/UTHSC_SPL_RMAEx_1210/notes.rtf b/general/datasets/UTHSC_SPL_RMAEx_1210/notes.rtf
deleted file mode 100644
index c7bb873..0000000
--- a/general/datasets/UTHSC_SPL_RMAEx_1210/notes.rtf
+++ /dev/null
@@ -1,4 +0,0 @@
-Data Status and Use. This is a provisional release that will soon be replaced by a final corrected data set. In the interim this data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
-This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
-
-Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/UTHSC_SPL_RMAEx_1210/processing.rtf b/general/datasets/UTHSC_SPL_RMAEx_1210/processing.rtf
deleted file mode 100644
index deaf264..0000000
--- a/general/datasets/UTHSC_SPL_RMAEx_1210/processing.rtf
+++ /dev/null
@@ -1,1932 +0,0 @@
-Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
-
-Batch Effects. This data set required some correction for batch effects and the data in this initial release incorporate any additional corrections. There are several additional confounder-like factors that should be considered:
-
-
- - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
- - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest probe sets in this spleen data set accounts of XX% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the spleen data set can be mapped as a trait.
-
-
-Data Release. This data set was first uploaded into GeneNetwork by Arthur Centeno, October 11, 2010 and made accessible without a password to all users on November 1, 2010. The initial data release had numerous strain identification errors that have now largely been fixed. Based on an analysis of the top 20 Mendelian loci, the following 21 strains were likely to have been incorrectly identified or assigned in the current release:
-
-
- - BXD8, e.g., Probe set 10450161, 1036098. 10338684
- - BXD13, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10342568,
- - BXD21 (may be ok, only one probe set 10338684 is problematic)
- - BXD23 (may be ok, only two probe sets 10421128, 10419465 is problematic)
- - BXD36 (may be ok, only one probe set 10421128 is problematic)
- - BXD40, e.g., Probe set 10341070
- - BXD43, e.g., Probe set 10450161, 1036098, 10338684
- - BXD48, e.g., Probe set 1036098, 10402390, 10514896, 10592493, 10357381, 10342568, 10571444, 10419465
- - BXD62, e.g., Probe set 1036098, 1036098, 10402390, 10514896, 10592493, 10421128, 10571444
- - BXD68 (may be ok, only one probe set 10338684 is problematic)
- - BXD69, e.g., Probe set 10450161
- - BXD73, e.g., Probe set 10341070, 1036098, 10402390, 10514896, 10587633, 10342568, 10421128
- - BXD74, e.g., Probe set 10402390
- - BXD80, e.g., Probe set 10341070, 1036098, 10592493, 10400109, 10338684, 10342568, 10421128, 10419465
- - BXD83, e.g., Probe set 10450161, 10338684
- - BXD87 (may be ok, only one probe set 10421128 is problematic)
- - BXD89, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10357381, 10419465
- - BXD93, e.g., Probe set 10402390, 10357381
- - BALB/cByJ, e.g., Probe set 10388042, 1036098, 10587633, 10357381, 10342568, 10421128
- - LP/J, e.g., Probe set 10592493
- - DBA/2J, e.g., Probe set 10592493
-
-
-Data Evaluation Summary
-
-
- - Before correction: eQLTs with LOD >10 (LRS>46.1): n = 638
- - After strain assignment correction: eQLTs with LOD >10 (LRS>46.1): n = 820
- - Before correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 237.9
- - After correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 278.1
- - Lowest mean value: Trait ID 10344361, mean = 3.998
- - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
- - Greatest sex difference: Trait ID: 10606178 (Xist)
- - Great variation within and among strains: Trait ID 10454192 (Ttr
-
Table 1 (please confirm that these assignments are after correction)
-
-
-
-
-
-
-
-
-
- | Index |
- Array ID |
- Phase |
- Strain |
- Age |
- Sex |
-
-
- | 1 |
- R5583S |
- 1 |
- 129P3/J |
- 65 |
- F |
-
-
- | 2 |
- R5584S |
- 1 |
- 129P3/J |
- 66 |
- M |
-
-
- | 3 |
- R5585S |
- 1 |
- 129S1/SvImJ |
- 66 |
- F |
-
-
- | 4 |
- R5586S |
- 1 |
- 129S1/SvImJ |
- 66 |
- M |
-
-
- | 5 |
- R5587S |
- 1 |
- 129X1/SvJ |
- 65 |
- F |
-
-
- | 6 |
- R5588S |
- 1 |
- 129X1/SvJ |
- 66 |
- M |
-
-
- | 7 |
- R6348S |
- 3 |
- B6D2F1 |
- 67 |
- F |
-
-
- | 8 |
- R6347S |
- 3 |
- B6D2F1 |
- 62 |
- F |
-
-
- | 9 |
- R5590S |
- 1 |
- B6D2F1 |
- 79 |
- M |
-
-
- | 10 |
- R5662S |
- 1 |
- BALB/cByJ |
- 59 |
- F |
-
-
- | 11 |
- R5664S |
- 1 |
- BALB/cByJ |
- 59 |
- M |
-
-
- | 12 |
- R5591S |
- 1 |
- BALB/cJ |
- 51 |
- F |
-
-
- | 13 |
- R5592S |
- 1 |
- BALB/cJ |
- 51 |
- M |
-
-
- | 14 |
- R6154S |
- 2 |
- BTBR T+ tf/J |
- 60 |
- F |
-
-
- | 15 |
- R6516S |
- 3 |
- BXD1 |
- 82 |
- F |
-
-
- | 16 |
- R6584S |
- 3 |
- BXD1 |
- 95 |
- M |
-
-
- | 17 |
- R5759S |
- 1 |
- BXD2 |
- N/A |
- F |
-
-
- | 18 |
- R5837S |
- 1 |
- BXD2 |
- 106 |
- M |
-
-
- | 19 |
- R5874S |
- 2 |
- BXD5 |
- 86 |
- F |
-
-
- | 20 |
- R6554S |
- 3 |
- BXD5 |
- 60 |
- M |
-
-
- | 21 |
- R6359S |
- 3 |
- BXD6 |
- 72 |
- F |
-
-
- | 22 |
- R5777S |
- 1 |
- BXD6 |
- 149 |
- M |
-
-
- | 23 |
- R6364S |
- 3 |
- BXD8 |
- 76 |
- F |
-
-
- | 24 |
- R5637S |
- 1 |
- BXD8 |
- 71 |
- F |
-
-
- | 25 |
- R6365S |
- 3 |
- BXD8 |
- 76 |
- M |
-
-
- | 26 |
- R5746S |
- 1 |
- BXD9 |
- 70 |
- F |
-
-
- | 27 |
- R5981S |
- 2 |
- BXD9 |
- 67 |
- M |
-
-
- | 28 |
- R5980S |
- 2 |
- BXD9 |
- 67 |
- M |
-
-
- | 29 |
- R6182S |
- 2 |
- BXD11 |
- 84 |
- F |
-
-
- | 30 |
- R6486S |
- 3 |
- BXD11 |
- 58 |
- M |
-
-
- | 31 |
- R6711S2 |
- 4 |
- BXD12 |
- 71 |
- F |
-
-
- | 32 |
- R6608S |
- 3 |
- BXD12 |
- 48 |
- F |
-
-
- | 33 |
- R5885S |
- 2 |
- BXD12 |
- 44 |
- M |
-
-
- | 34 |
- R5755S |
- 1 |
- BXD13 |
- 160 |
- F |
-
-
- | 35 |
- R5887S |
- 2 |
- BXD13 |
- 53 |
- M |
-
-
- | 36 |
- R6180S |
- 2 |
- BXD14 |
- 70 |
- F |
-
-
- | 37 |
- R5669S |
- 1 |
- BXD14 |
- 91 |
- M |
-
-
- | 38 |
- R6456S |
- 3 |
- BXD15 |
- 60 |
- F |
-
-
- | 39 |
- R6622S |
- 3 |
- BXD15 |
- 60 |
- F |
-
-
- | 40 |
- R6626S |
- 3 |
- BXD15 |
- 60 |
- M |
-
-
- | 41 |
- R6181S |
- 2 |
- BXD16 |
- 74 |
- F |
-
-
- | 42 |
- R6515S |
- 3 |
- BXD16 |
- 64 |
- M |
-
-
- | 43 |
- R5673S |
- 1 |
- BXD18 |
- 80 |
- F |
-
-
- | 44 |
- R5674S |
- 1 |
- BXD18 |
- 65 |
- M |
-
-
- | 45 |
- R6553S |
- 3 |
- BXD19 |
- 158 |
- F |
-
-
- | 46 |
- R6551S |
- 3 |
- BXD19 |
- 60 |
- M |
-
-
- | 47 |
- R6643S4 |
- 4 |
- BXD20 |
- 59 |
- F |
-
-
- | 48 |
- R6595S |
- 3 |
- BXD20 |
- 60 |
- M |
-
-
- | 49 |
- R5735S |
- 1 |
- BXD21 |
- 64 |
- F |
-
-
- | 50 |
- R5892S |
- 2 |
- BXD21 |
- 99 |
- M |
-
-
- | 51 |
- R5896S |
- 2 |
- BXD22 |
- 60 |
- F |
-
-
- | 52 |
- R6414S |
- 3 |
- BXD22 |
- 73 |
- M |
-
-
- | 53 |
- R6550S |
- 3 |
- BXD23 |
- 74 |
- F |
-
-
- | 54 |
- R6586S |
- 3 |
- BXD23 |
- 102 |
- F |
-
-
- | 55 |
- R5630S |
- 1 |
- BXD24 |
- 71 |
- F |
-
-
- | 56 |
- R6356S |
- 3 |
- BXD24 |
- 57 |
- M |
-
-
- | 57 |
- R6162S |
- 2 |
- BXD25 |
- 67 |
- F |
-
-
- | 58 |
- R6625S |
- 3 |
- BXD25 |
- 67 |
- F |
-
-
- | 59 |
- R6642S4 |
- 4 |
- BXD25 |
- 58 |
- M |
-
-
- | 60 |
- R5761S |
- 1 |
- BXD27 |
- N/A |
- F |
-
-
- | 61 |
- R5763S |
- 1 |
- BXD27 |
- 90 |
- M |
-
-
- | 62 |
- R6621S |
- 3 |
- BXD28 |
- 113 |
- F |
-
-
- | 63 |
- R6548S |
- 3 |
- BXD28 |
- 60 |
- M |
-
-
- | 64 |
- R6547S |
- 3 |
- BXD29 |
- 60 |
- F |
-
-
- | 65 |
- R6453S |
- 3 |
- BXD31 |
- 48 |
- F |
-
-
- | 66 |
- R6452S |
- 3 |
- BXD31 |
- 48 |
- M |
-
-
- | 67 |
- R6583S |
- 3 |
- BXD32 |
- 60 |
- F |
-
-
- | 68 |
- R5765S |
- 1 |
- BXD32 |
- 71 |
- M |
-
-
- | 69 |
- R5689S |
- 1 |
- BXD33 |
- 65 |
- F |
-
-
- | 70 |
- R6450S |
- 3 |
- BXD33 |
- 55 |
- M |
-
-
- | 71 |
- R5767S |
- 1 |
- BXD34 |
- 72 |
- F |
-
-
- | 72 |
- R5900S |
- 2 |
- BXD34 |
- 70 |
- M |
-
-
- | 73 |
- R6588S |
- 3 |
- BXD36 |
- 61 |
- F |
-
-
- | 74 |
- R6490S |
- 3 |
- BXD36 |
- 63 |
- M |
-
-
- | 75 |
- R6417S |
- 3 |
- BXD38 |
- 64 |
- F |
-
-
- | 76 |
- R6439S |
- 3 |
- BXD38 |
- 72 |
- M |
-
-
- | 77 |
- R5769S |
- 1 |
- BXD39 |
- N/A |
- F |
-
-
- | 78 |
- R5771S |
- 1 |
- BXD39 |
- 74 |
- M |
-
-
- | 79 |
- R5773S |
- 1 |
- BXD40 |
- N/A |
- F |
-
-
- | 80 |
- R5775S |
- 1 |
- BXD40 |
- N/A |
- M |
-
-
- | 81 |
- R6494S |
- 3 |
- BXD41 |
- 72 |
- F |
-
-
- | 82 |
- R5910S |
- 2 |
- BXD42 |
- 79 |
- F |
-
-
- | 83 |
- R6493S |
- 3 |
- BXD42 |
- 69 |
- M |
-
-
- | 84 |
- R6341S |
- 3 |
- BXD43 |
- 59 |
- F |
-
-
- | 85 |
- R6401S |
- 3 |
- BXD43 |
- 99 |
- M |
-
-
- | 86 |
- R5916S |
- 2 |
- BXD43 |
- 79 |
- M |
-
-
- | 87 |
- R5839S |
- 1 |
- BXD44 |
- 141 |
- F |
-
-
- | 88 |
- R5779S |
- 1 |
- BXD44 |
- 124 |
- M |
-
-
- | 89 |
- R6405S |
- 3 |
- BXD45 |
- 58 |
- F |
-
-
- | 90 |
- R6610S |
- 3 |
- BXD45 |
- 55 |
- M |
-
-
- | 91 |
- R5922S |
- 2 |
- BXD48 |
- 64 |
- F |
-
-
- | 92 |
- R5925S |
- 2 |
- BXD48 |
- 60 |
- M |
-
-
- | 93 |
- R6719S1 |
- 4 |
- BXD49 |
- 58 |
- F |
-
-
- | 94 |
- R6485S |
- 3 |
- BXD49 |
- 79 |
- M |
-
-
- | 95 |
- R5781S |
- 1 |
- BXD50 |
- 61 |
- F |
-
-
- | 96 |
- R6464S |
- 3 |
- BXD51 |
- 65 |
- F |
-
-
- | 97 |
- R6585S |
- 3 |
- BXD51 |
- 63 |
- M |
-
-
- | 98 |
- R6500S |
- 3 |
- BXD55 |
- 58 |
- F |
-
-
- | 99 |
- R5938S |
- 2 |
- BXD55 |
- 93 |
- M |
-
-
- | 100 |
- R6504S |
- 3 |
- BXD56 |
- 58 |
- F |
-
-
- | 101 |
- R6503S |
- 3 |
- BXD56 |
- 58 |
- M |
-
-
- | 102 |
- R5783S |
- 1 |
- BXD60 |
- 111 |
- F |
-
-
- | 103 |
- R5784S |
- 1 |
- BXD60 |
- 85 |
- M |
-
-
- | 104 |
- R5786S |
- 1 |
- BXD61 |
- 86 |
- F |
-
-
- | 105 |
- R6449S |
- 3 |
- BXD61 |
- 65 |
- M |
-
-
- | 106 |
- R6716S1 |
- 4 |
- BXD62 |
- 54 |
- F |
-
-
- | 107 |
- R5790S |
- 1 |
- BXD62 |
- 115 |
- M |
-
-
- | 108 |
- R6519S |
- 3 |
- BXD63 |
- 54 |
- F |
-
-
- | 109 |
- R6717S1 |
- 4 |
- BXD63 |
- 70 |
- M |
-
-
- | 110 |
- R5792S |
- 1 |
- BXD64 |
- 167 |
- F |
-
-
- | 111 |
- R6641S4 |
- 4 |
- BXD64 |
- 68 |
- M |
-
-
- | 112 |
- R6630S |
- 3 |
- BXD64 |
- 68 |
- M |
-
-
- | 113 |
- R6477S |
- 3 |
- BXD65 |
- 58 |
- F |
-
-
- | 114 |
- R6628S |
- 3 |
- BXD65 |
- 70 |
- M |
-
-
- | 115 |
- R6511S |
- 3 |
- BXD66 |
- 70 |
- F |
-
-
- | 116 |
- R6448S |
- 3 |
- BXD66 |
- 61 |
- M |
-
-
- | 117 |
- R5794S |
- 1 |
- BXD66 |
- 144 |
- M |
-
-
- | 118 |
- R6502S |
- 3 |
- BXD67 |
- 66 |
- F |
-
-
- | 119 |
- R6545S |
- 3 |
- BXD67 |
- 61 |
- M |
-
-
- | 120 |
- R6337S |
- 3 |
- BXD68 |
- 56 |
- F |
-
-
- | 121 |
- R6594S |
- 3 |
- BXD68 |
- 64 |
- M |
-
-
- | 122 |
- R5796S |
- 1 |
- BXD69 |
- 85 |
- F |
-
-
- | 123 |
- R5798S |
- 1 |
- BXD69 |
- 98 |
- M |
-
-
- | 124 |
- R6402S |
- 3 |
- BXD70 |
- 93 |
- F |
-
-
- | 125 |
- R5841S |
- 1 |
- BXD70 |
- 121 |
- F |
-
-
- | 126 |
- R6592S |
- 3 |
- BXD70 |
- 59 |
- M |
-
-
- | 127 |
- R6328S |
- 3 |
- BXD71 |
- 87 |
- F |
-
-
- | 128 |
- R5967S |
- 2 |
- BXD71 |
- 64 |
- M |
-
-
- | 129 |
- R5969S |
- 2 |
- BXD73 |
- 64 |
- F |
-
-
- | 130 |
- R5800S |
- 1 |
- BXD73 |
- 120 |
- M |
-
-
- | 131 |
- R6646S |
- 3 |
- BXD74 |
- 40 |
- F |
-
-
- | 132 |
- R6524S |
- 3 |
- BXD74 |
- 72 |
- M |
-
-
- | 133 |
- R6445S |
- 3 |
- BXD75 |
- 85 |
- F |
-
-
- | 134 |
- R5843S |
- 1 |
- BXD75 |
- 103 |
- F |
-
-
- | 135 |
- R5845S |
- 1 |
- BXD75 |
- 103 |
- M |
-
-
- | 136 |
- R6604S |
- 3 |
- BXD77 |
- 64 |
- F |
-
-
- | 137 |
- R6513S |
- 3 |
- BXD77 |
- 72 |
- M |
-
-
- | 138 |
- R6582S |
- 3 |
- BXD78 |
- 144 |
- F |
-
-
- | 139 |
- R6563S |
- 3 |
- BXD78 |
- 95 |
- M |
-
-
- | 140 |
- R6645S4 |
- 4 |
- BXD79 |
- 66 |
- F |
-
-
- | 141 |
- R5806S |
- 1 |
- BXD79 |
- 78 |
- M |
-
-
- | 142 |
- R5847S |
- 1 |
- BXD80 |
- 89 |
- F |
-
-
- | 143 |
- R5852S |
- 1 |
- BXD80 |
- 79 |
- M |
-
-
- | 144 |
- R6562S |
- 3 |
- BXD81 |
- 99 |
- F |
-
-
- | 145 |
- R6468S |
- 3 |
- BXD81 |
- 65 |
- M |
-
-
- | 146 |
- R6560S |
- 3 |
- BXD82 |
- 85 |
- F |
-
-
- | 147 |
- R6512S |
- 3 |
- BXD83 |
- 68 |
- F |
-
-
- | 148 |
- R5810S |
- 1 |
- BXD83 |
- 139 |
- M |
-
-
- | 149 |
- R6510S |
- 3 |
- BXD84 |
- 87 |
- F |
-
-
- | 150 |
- R5970S |
- 2 |
- BXD84 |
- 107 |
- F |
-
-
- | 151 |
- R6603S |
- 3 |
- BXD84 |
- 99 |
- M |
-
-
- | 152 |
- R6517S |
- 3 |
- BXD85 |
- 58 |
- F |
-
-
- | 153 |
- R6718S1 |
- 4 |
- BXD85 |
- 86 |
- M |
-
-
- | 154 |
- R5812S |
- 1 |
- BXD86 |
- 61 |
- F |
-
-
- | 155 |
- R5814S |
- 1 |
- BXD86 |
- 59 |
- M |
-
-
- | 156 |
- R5816S |
- 1 |
- BXD87 |
- 112 |
- F |
-
-
- | 157 |
- R6488S |
- 3 |
- BXD87 |
- 137 |
- M |
-
-
- | 158 |
- R6580S |
- 3 |
- BXD88 |
- 125 |
- F |
-
-
- | 159 |
- R5977S |
- 2 |
- BXD89 |
- 68 |
- F |
-
-
- | 160 |
- R5979S |
- 2 |
- BXD89 |
- 79 |
- M |
-
-
- | 161 |
- R5978S |
- 2 |
- BXD89 |
- 79 |
- M |
-
-
- | 162 |
- R5818S |
- 1 |
- BXD90 |
- 106 |
- F |
-
-
- | 163 |
- R5820S |
- 1 |
- BXD90 |
- 131 |
- M |
-
-
- | 164 |
- R6343S |
- 3 |
- BXD92 |
- 62 |
- F |
-
-
- | 165 |
- R5984S |
- 2 |
- BXD92 |
- 55 |
- M |
-
-
- | 166 |
- R6581S |
- 3 |
- BXD93 |
- 173 |
- M |
-
-
- | 167 |
- R6557S |
- 3 |
- BXD93 |
- 126 |
- M |
-
-
- | 168 |
- R6509S |
- 3 |
- BXD95 |
- 59 |
- F |
-
-
- | 169 |
- R5822S |
- 1 |
- BXD95 |
- 89 |
- M |
-
-
- | 170 |
- R6640S4 |
- 4 |
- BXD96 |
- 70 |
- F |
-
-
- | 171 |
- R6514S |
- 3 |
- BXD96 |
- 64 |
- M |
-
-
- | 172 |
- R6506S |
- 3 |
- BXD97 |
- 78 |
- F |
-
-
- | 173 |
- R5849S |
- 1 |
- BXD97 |
- 130 |
- F |
-
-
- | 174 |
- R6591S |
- 3 |
- BXD97 |
- 122 |
- M |
-
-
- | 175 |
- R5990S |
- 2 |
- BXD98 |
- 65 |
- F |
-
-
- | 176 |
- R6596S |
- 3 |
- BXD98 |
- 67 |
- M |
-
-
- | 177 |
- R5993S |
- 2 |
- BXD99 |
- 74 |
- F |
-
-
- | 178 |
- R5995S |
- 2 |
- BXD99 |
- 50 |
- M |
-
-
- | 179 |
- R6607S |
- 3 |
- BXD100 |
- 75 |
- F |
-
-
- | 180 |
- R6411S |
- 3 |
- BXD100 |
- 104 |
- M |
-
-
- | 181 |
- R6508S |
- 3 |
- BXD101 |
- 59 |
- F |
-
-
- | 182 |
- R5593S |
- 1 |
- BXD101 |
- 59 |
- M |
-
-
- | 183 |
- R6523S |
- 3 |
- BXD102 |
- 60 |
- F |
-
-
- | 184 |
- R6466S |
- 3 |
- BXD102 |
- 50 |
- M |
-
-
- | 185 |
- R6404S |
- 3 |
- BXD103 |
- 72 |
- F |
-
-
- | 186 |
- R6609S |
- 3 |
- BXD103 |
- 57 |
- M |
-
-
- | 187 |
- R6555S |
- 3 |
- C57BL/10J |
- 73 |
- M |
-
-
- | 188 |
- R5596S |
- 1 |
- C57BL/10J |
- 73 |
- M |
-
-
- | 189 |
- R5597S |
- 1 |
- C57BL/6ByJ |
- 51 |
- F |
-
-
- | 190 |
- R5598S |
- 1 |
- C57BL/6ByJ |
- 69 |
- M |
-
-
- | 191 |
- R5600S |
- 1 |
- C57BL/6J |
- 79 |
- F |
-
-
- | 192 |
- R5599S |
- 1 |
- C57BL/6J |
- 60 |
- F |
-
-
- | 193 |
- R6451S |
- 3 |
- C57BL/6J |
- 77 |
- M |
-
-
- | 194 |
- R6410S |
- 3 |
- C57BL/6J |
- 85 |
- M |
-
-
- | 195 |
- R5603S |
- 1 |
- C57BLKS/J |
- 66 |
- F |
-
-
- | 196 |
- R5604S |
- 1 |
- C57BLKS/J |
- 66 |
- M |
-
-
- | 197 |
- R5996S |
- 2 |
- CBA/CaJ |
- 66 |
- F |
-
-
- | 198 |
- R6349S |
- 3 |
- CBA/CaJ |
- 66 |
- M |
-
-
- | 199 |
- R6458S |
- 3 |
- D2B6F1 |
- 64 |
- F |
-
-
- | 200 |
- R6353S |
- 3 |
- D2B6F1 |
- 60 |
- M |
-
-
- | 201 |
- R5605S |
- 1 |
- DBA/2J |
- 79 |
- F |
-
-
- | 202 |
- R6446S |
- 3 |
- DBA/2J |
- 83 |
- M |
-
-
- | 203 |
- R6597S |
- 3 |
- FVB/NJ |
- 60 |
- F |
-
-
- | 204 |
- R5643S |
- 1 |
- FVB/NJ |
- 60 |
- F |
-
-
- | 205 |
- R6598S |
- 3 |
- FVB/NJ |
- 60 |
- M |
-
-
- | 206 |
- R5606S |
- 1 |
- ILS |
- 74 |
- F |
-
-
- | 207 |
- R5607S |
- 1 |
- ILS |
- 74 |
- M |
-
-
- | 208 |
- R5610S |
- 1 |
- ISS |
- 97 |
- M |
-
-
- | 209 |
- R6627S |
- 3 |
- KK/HlJ |
- 64 |
- F |
-
-
- | 210 |
- R6444S |
- 3 |
- KK/HlJ |
- 65 |
- M |
-
-
- | 211 |
- R5702S |
- 1 |
- KK/HlJ |
- 61 |
- M |
-
-
- | 212 |
- R5613S |
- 1 |
- LG/J |
- 63 |
- F |
-
-
- | 213 |
- R5704S |
- 1 |
- LG/J |
- 65 |
- M |
-
-
- | 214 |
- R5614S |
- 1 |
- LP/J |
- 65 |
- F |
-
-
- | 215 |
- R5615S |
- 1 |
- LP/J |
- 65 |
- M |
-
-
- | 216 |
- R6599S |
- 3 |
- MOLF/EiJ |
- 60 |
- F |
-
-
- | 217 |
- R6606S |
- 3 |
- MOLF/EiJ |
- 60 |
- M |
-
-
- | 218 |
- R6544S |
- 3 |
- NOD/LtJ |
- 77 |
- F |
-
-
- | 219 |
- R5709S |
- 1 |
- NOD/LtJ |
- 58 |
- M |
-
-
- | 220 |
- R6601S |
- 3 |
- NZB/BlNJ |
- 61 |
- F |
-
-
- | 221 |
- R5711S |
- 1 |
- NZB/BlNJ |
- 61 |
- F |
-
-
- | 222 |
- R6427S |
- 3 |
- NZB/BlNJ |
- 58 |
- M |
-
-
- | 223 |
- R6150S |
- 2 |
- NZO/HlLtJ |
- 71 |
- F |
-
-
- | 224 |
- R6155S |
- 2 |
- NZW/LacJ |
- 65 |
- F |
-
-
- | 225 |
- R5654S |
- 1 |
- NZW/LacJ |
- 60 |
- M |
-
-
- | 226 |
- R5721S |
- 1 |
- PL/J |
- 59 |
- M |
-
-
- | 227 |
- R5616S |
- 1 |
- PWD/PhJ |
- 60 |
- M |
-
-
- | 228 |
- R5725S |
- 1 |
- PWK/PhJ |
- 121 |
- M |
-
-
- | 229 |
- R6174S |
- 2 |
- SJL/J |
- 63 |
- F |
-
-
- | 230 |
- R6350S |
- 3 |
- SJL/J |
- 65 |
- M |
-
-
- | 231 |
- R6419S |
- 3 |
- WSB/EiJ |
- 60 |
- F |
-
-
- | 232 |
- R5620S |
- 1 |
- WSB/EiJ |
- 60 |
- M |
-
-
-
-
- |
-
-
-
-
-
-
-
-
-
diff --git a/general/datasets/UTHSC_SPL_RMAEx_1210/summary.rtf b/general/datasets/UTHSC_SPL_RMAEx_1210/summary.rtf
deleted file mode 100644
index d9478f8..0000000
--- a/general/datasets/UTHSC_SPL_RMAEx_1210/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-This is a near final release of a spleen gene expression data set generated by a DOD-funded consortium (Byrne, Kotb, Williams, and Lu). Please contact Lu Lu or Robert Williams regarding status of this data set. The initial data enterted in 2010 had many errors described below. The data set is much improved and has no known errors of strain assignment.
-
-Animals were generated at UTHSC by Lu Lu and colleagues. The spleen of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/UTHSC_SPLs1_RMA_1210/cases.rtf b/general/datasets/UTHSC_SPLs1_RMA_1210/cases.rtf
deleted file mode 100644
index 7fa108f..0000000
--- a/general/datasets/UTHSC_SPLs1_RMA_1210/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Cases. A total of 111 strains, including 81 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1), and 26 other common inbred strains were quantified. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by Lu Lu and colleagues. Samples were pooled by sex and usually include at least two cases per sex and strain.
-
-Sex Balance. XX strains have matched male and female samples. XX strains have male only samples (BXDX, XX, XX, XXX and XXX). XX strains have only female samples (BXDXX, XX, and XX.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/UTHSC_SPLs1_RMA_1210/experiment-design.rtf b/general/datasets/UTHSC_SPLs1_RMA_1210/experiment-design.rtf
deleted file mode 100644
index a0aeba6..0000000
--- a/general/datasets/UTHSC_SPLs1_RMA_1210/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA Processing. Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
-
-Array Processing: All arrays were processed by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. The spleen was dissected by both Dr. Lu Lu and colleagues and Dr. Abdeltawab and colleagues. All arrays were run together (interleaved) as a single large batch.
diff --git a/general/datasets/UTHSC_SPLs1_RMA_1210/notes.rtf b/general/datasets/UTHSC_SPLs1_RMA_1210/notes.rtf
deleted file mode 100644
index c7bb873..0000000
--- a/general/datasets/UTHSC_SPLs1_RMA_1210/notes.rtf
+++ /dev/null
@@ -1,4 +0,0 @@
-Data Status and Use. This is a provisional release that will soon be replaced by a final corrected data set. In the interim this data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
-This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
-
-Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/UTHSC_SPLs1_RMA_1210/processing.rtf b/general/datasets/UTHSC_SPLs1_RMA_1210/processing.rtf
deleted file mode 100644
index deaf264..0000000
--- a/general/datasets/UTHSC_SPLs1_RMA_1210/processing.rtf
+++ /dev/null
@@ -1,1932 +0,0 @@
-Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
-
-Batch Effects. This data set required some correction for batch effects and the data in this initial release incorporate any additional corrections. There are several additional confounder-like factors that should be considered:
-
-
- - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
- - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest probe sets in this spleen data set accounts of XX% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the spleen data set can be mapped as a trait.
-
-
-Data Release. This data set was first uploaded into GeneNetwork by Arthur Centeno, October 11, 2010 and made accessible without a password to all users on November 1, 2010. The initial data release had numerous strain identification errors that have now largely been fixed. Based on an analysis of the top 20 Mendelian loci, the following 21 strains were likely to have been incorrectly identified or assigned in the current release:
-
-
- - BXD8, e.g., Probe set 10450161, 1036098. 10338684
- - BXD13, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10342568,
- - BXD21 (may be ok, only one probe set 10338684 is problematic)
- - BXD23 (may be ok, only two probe sets 10421128, 10419465 is problematic)
- - BXD36 (may be ok, only one probe set 10421128 is problematic)
- - BXD40, e.g., Probe set 10341070
- - BXD43, e.g., Probe set 10450161, 1036098, 10338684
- - BXD48, e.g., Probe set 1036098, 10402390, 10514896, 10592493, 10357381, 10342568, 10571444, 10419465
- - BXD62, e.g., Probe set 1036098, 1036098, 10402390, 10514896, 10592493, 10421128, 10571444
- - BXD68 (may be ok, only one probe set 10338684 is problematic)
- - BXD69, e.g., Probe set 10450161
- - BXD73, e.g., Probe set 10341070, 1036098, 10402390, 10514896, 10587633, 10342568, 10421128
- - BXD74, e.g., Probe set 10402390
- - BXD80, e.g., Probe set 10341070, 1036098, 10592493, 10400109, 10338684, 10342568, 10421128, 10419465
- - BXD83, e.g., Probe set 10450161, 10338684
- - BXD87 (may be ok, only one probe set 10421128 is problematic)
- - BXD89, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10357381, 10419465
- - BXD93, e.g., Probe set 10402390, 10357381
- - BALB/cByJ, e.g., Probe set 10388042, 1036098, 10587633, 10357381, 10342568, 10421128
- - LP/J, e.g., Probe set 10592493
- - DBA/2J, e.g., Probe set 10592493
-
-
-Data Evaluation Summary
-
-
- - Before correction: eQLTs with LOD >10 (LRS>46.1): n = 638
- - After strain assignment correction: eQLTs with LOD >10 (LRS>46.1): n = 820
- - Before correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 237.9
- - After correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 278.1
- - Lowest mean value: Trait ID 10344361, mean = 3.998
- - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
- - Greatest sex difference: Trait ID: 10606178 (Xist)
- - Great variation within and among strains: Trait ID 10454192 (Ttr
-
Table 1 (please confirm that these assignments are after correction)
-
-
-
-
-
-
-
-
-
- | Index |
- Array ID |
- Phase |
- Strain |
- Age |
- Sex |
-
-
- | 1 |
- R5583S |
- 1 |
- 129P3/J |
- 65 |
- F |
-
-
- | 2 |
- R5584S |
- 1 |
- 129P3/J |
- 66 |
- M |
-
-
- | 3 |
- R5585S |
- 1 |
- 129S1/SvImJ |
- 66 |
- F |
-
-
- | 4 |
- R5586S |
- 1 |
- 129S1/SvImJ |
- 66 |
- M |
-
-
- | 5 |
- R5587S |
- 1 |
- 129X1/SvJ |
- 65 |
- F |
-
-
- | 6 |
- R5588S |
- 1 |
- 129X1/SvJ |
- 66 |
- M |
-
-
- | 7 |
- R6348S |
- 3 |
- B6D2F1 |
- 67 |
- F |
-
-
- | 8 |
- R6347S |
- 3 |
- B6D2F1 |
- 62 |
- F |
-
-
- | 9 |
- R5590S |
- 1 |
- B6D2F1 |
- 79 |
- M |
-
-
- | 10 |
- R5662S |
- 1 |
- BALB/cByJ |
- 59 |
- F |
-
-
- | 11 |
- R5664S |
- 1 |
- BALB/cByJ |
- 59 |
- M |
-
-
- | 12 |
- R5591S |
- 1 |
- BALB/cJ |
- 51 |
- F |
-
-
- | 13 |
- R5592S |
- 1 |
- BALB/cJ |
- 51 |
- M |
-
-
- | 14 |
- R6154S |
- 2 |
- BTBR T+ tf/J |
- 60 |
- F |
-
-
- | 15 |
- R6516S |
- 3 |
- BXD1 |
- 82 |
- F |
-
-
- | 16 |
- R6584S |
- 3 |
- BXD1 |
- 95 |
- M |
-
-
- | 17 |
- R5759S |
- 1 |
- BXD2 |
- N/A |
- F |
-
-
- | 18 |
- R5837S |
- 1 |
- BXD2 |
- 106 |
- M |
-
-
- | 19 |
- R5874S |
- 2 |
- BXD5 |
- 86 |
- F |
-
-
- | 20 |
- R6554S |
- 3 |
- BXD5 |
- 60 |
- M |
-
-
- | 21 |
- R6359S |
- 3 |
- BXD6 |
- 72 |
- F |
-
-
- | 22 |
- R5777S |
- 1 |
- BXD6 |
- 149 |
- M |
-
-
- | 23 |
- R6364S |
- 3 |
- BXD8 |
- 76 |
- F |
-
-
- | 24 |
- R5637S |
- 1 |
- BXD8 |
- 71 |
- F |
-
-
- | 25 |
- R6365S |
- 3 |
- BXD8 |
- 76 |
- M |
-
-
- | 26 |
- R5746S |
- 1 |
- BXD9 |
- 70 |
- F |
-
-
- | 27 |
- R5981S |
- 2 |
- BXD9 |
- 67 |
- M |
-
-
- | 28 |
- R5980S |
- 2 |
- BXD9 |
- 67 |
- M |
-
-
- | 29 |
- R6182S |
- 2 |
- BXD11 |
- 84 |
- F |
-
-
- | 30 |
- R6486S |
- 3 |
- BXD11 |
- 58 |
- M |
-
-
- | 31 |
- R6711S2 |
- 4 |
- BXD12 |
- 71 |
- F |
-
-
- | 32 |
- R6608S |
- 3 |
- BXD12 |
- 48 |
- F |
-
-
- | 33 |
- R5885S |
- 2 |
- BXD12 |
- 44 |
- M |
-
-
- | 34 |
- R5755S |
- 1 |
- BXD13 |
- 160 |
- F |
-
-
- | 35 |
- R5887S |
- 2 |
- BXD13 |
- 53 |
- M |
-
-
- | 36 |
- R6180S |
- 2 |
- BXD14 |
- 70 |
- F |
-
-
- | 37 |
- R5669S |
- 1 |
- BXD14 |
- 91 |
- M |
-
-
- | 38 |
- R6456S |
- 3 |
- BXD15 |
- 60 |
- F |
-
-
- | 39 |
- R6622S |
- 3 |
- BXD15 |
- 60 |
- F |
-
-
- | 40 |
- R6626S |
- 3 |
- BXD15 |
- 60 |
- M |
-
-
- | 41 |
- R6181S |
- 2 |
- BXD16 |
- 74 |
- F |
-
-
- | 42 |
- R6515S |
- 3 |
- BXD16 |
- 64 |
- M |
-
-
- | 43 |
- R5673S |
- 1 |
- BXD18 |
- 80 |
- F |
-
-
- | 44 |
- R5674S |
- 1 |
- BXD18 |
- 65 |
- M |
-
-
- | 45 |
- R6553S |
- 3 |
- BXD19 |
- 158 |
- F |
-
-
- | 46 |
- R6551S |
- 3 |
- BXD19 |
- 60 |
- M |
-
-
- | 47 |
- R6643S4 |
- 4 |
- BXD20 |
- 59 |
- F |
-
-
- | 48 |
- R6595S |
- 3 |
- BXD20 |
- 60 |
- M |
-
-
- | 49 |
- R5735S |
- 1 |
- BXD21 |
- 64 |
- F |
-
-
- | 50 |
- R5892S |
- 2 |
- BXD21 |
- 99 |
- M |
-
-
- | 51 |
- R5896S |
- 2 |
- BXD22 |
- 60 |
- F |
-
-
- | 52 |
- R6414S |
- 3 |
- BXD22 |
- 73 |
- M |
-
-
- | 53 |
- R6550S |
- 3 |
- BXD23 |
- 74 |
- F |
-
-
- | 54 |
- R6586S |
- 3 |
- BXD23 |
- 102 |
- F |
-
-
- | 55 |
- R5630S |
- 1 |
- BXD24 |
- 71 |
- F |
-
-
- | 56 |
- R6356S |
- 3 |
- BXD24 |
- 57 |
- M |
-
-
- | 57 |
- R6162S |
- 2 |
- BXD25 |
- 67 |
- F |
-
-
- | 58 |
- R6625S |
- 3 |
- BXD25 |
- 67 |
- F |
-
-
- | 59 |
- R6642S4 |
- 4 |
- BXD25 |
- 58 |
- M |
-
-
- | 60 |
- R5761S |
- 1 |
- BXD27 |
- N/A |
- F |
-
-
- | 61 |
- R5763S |
- 1 |
- BXD27 |
- 90 |
- M |
-
-
- | 62 |
- R6621S |
- 3 |
- BXD28 |
- 113 |
- F |
-
-
- | 63 |
- R6548S |
- 3 |
- BXD28 |
- 60 |
- M |
-
-
- | 64 |
- R6547S |
- 3 |
- BXD29 |
- 60 |
- F |
-
-
- | 65 |
- R6453S |
- 3 |
- BXD31 |
- 48 |
- F |
-
-
- | 66 |
- R6452S |
- 3 |
- BXD31 |
- 48 |
- M |
-
-
- | 67 |
- R6583S |
- 3 |
- BXD32 |
- 60 |
- F |
-
-
- | 68 |
- R5765S |
- 1 |
- BXD32 |
- 71 |
- M |
-
-
- | 69 |
- R5689S |
- 1 |
- BXD33 |
- 65 |
- F |
-
-
- | 70 |
- R6450S |
- 3 |
- BXD33 |
- 55 |
- M |
-
-
- | 71 |
- R5767S |
- 1 |
- BXD34 |
- 72 |
- F |
-
-
- | 72 |
- R5900S |
- 2 |
- BXD34 |
- 70 |
- M |
-
-
- | 73 |
- R6588S |
- 3 |
- BXD36 |
- 61 |
- F |
-
-
- | 74 |
- R6490S |
- 3 |
- BXD36 |
- 63 |
- M |
-
-
- | 75 |
- R6417S |
- 3 |
- BXD38 |
- 64 |
- F |
-
-
- | 76 |
- R6439S |
- 3 |
- BXD38 |
- 72 |
- M |
-
-
- | 77 |
- R5769S |
- 1 |
- BXD39 |
- N/A |
- F |
-
-
- | 78 |
- R5771S |
- 1 |
- BXD39 |
- 74 |
- M |
-
-
- | 79 |
- R5773S |
- 1 |
- BXD40 |
- N/A |
- F |
-
-
- | 80 |
- R5775S |
- 1 |
- BXD40 |
- N/A |
- M |
-
-
- | 81 |
- R6494S |
- 3 |
- BXD41 |
- 72 |
- F |
-
-
- | 82 |
- R5910S |
- 2 |
- BXD42 |
- 79 |
- F |
-
-
- | 83 |
- R6493S |
- 3 |
- BXD42 |
- 69 |
- M |
-
-
- | 84 |
- R6341S |
- 3 |
- BXD43 |
- 59 |
- F |
-
-
- | 85 |
- R6401S |
- 3 |
- BXD43 |
- 99 |
- M |
-
-
- | 86 |
- R5916S |
- 2 |
- BXD43 |
- 79 |
- M |
-
-
- | 87 |
- R5839S |
- 1 |
- BXD44 |
- 141 |
- F |
-
-
- | 88 |
- R5779S |
- 1 |
- BXD44 |
- 124 |
- M |
-
-
- | 89 |
- R6405S |
- 3 |
- BXD45 |
- 58 |
- F |
-
-
- | 90 |
- R6610S |
- 3 |
- BXD45 |
- 55 |
- M |
-
-
- | 91 |
- R5922S |
- 2 |
- BXD48 |
- 64 |
- F |
-
-
- | 92 |
- R5925S |
- 2 |
- BXD48 |
- 60 |
- M |
-
-
- | 93 |
- R6719S1 |
- 4 |
- BXD49 |
- 58 |
- F |
-
-
- | 94 |
- R6485S |
- 3 |
- BXD49 |
- 79 |
- M |
-
-
- | 95 |
- R5781S |
- 1 |
- BXD50 |
- 61 |
- F |
-
-
- | 96 |
- R6464S |
- 3 |
- BXD51 |
- 65 |
- F |
-
-
- | 97 |
- R6585S |
- 3 |
- BXD51 |
- 63 |
- M |
-
-
- | 98 |
- R6500S |
- 3 |
- BXD55 |
- 58 |
- F |
-
-
- | 99 |
- R5938S |
- 2 |
- BXD55 |
- 93 |
- M |
-
-
- | 100 |
- R6504S |
- 3 |
- BXD56 |
- 58 |
- F |
-
-
- | 101 |
- R6503S |
- 3 |
- BXD56 |
- 58 |
- M |
-
-
- | 102 |
- R5783S |
- 1 |
- BXD60 |
- 111 |
- F |
-
-
- | 103 |
- R5784S |
- 1 |
- BXD60 |
- 85 |
- M |
-
-
- | 104 |
- R5786S |
- 1 |
- BXD61 |
- 86 |
- F |
-
-
- | 105 |
- R6449S |
- 3 |
- BXD61 |
- 65 |
- M |
-
-
- | 106 |
- R6716S1 |
- 4 |
- BXD62 |
- 54 |
- F |
-
-
- | 107 |
- R5790S |
- 1 |
- BXD62 |
- 115 |
- M |
-
-
- | 108 |
- R6519S |
- 3 |
- BXD63 |
- 54 |
- F |
-
-
- | 109 |
- R6717S1 |
- 4 |
- BXD63 |
- 70 |
- M |
-
-
- | 110 |
- R5792S |
- 1 |
- BXD64 |
- 167 |
- F |
-
-
- | 111 |
- R6641S4 |
- 4 |
- BXD64 |
- 68 |
- M |
-
-
- | 112 |
- R6630S |
- 3 |
- BXD64 |
- 68 |
- M |
-
-
- | 113 |
- R6477S |
- 3 |
- BXD65 |
- 58 |
- F |
-
-
- | 114 |
- R6628S |
- 3 |
- BXD65 |
- 70 |
- M |
-
-
- | 115 |
- R6511S |
- 3 |
- BXD66 |
- 70 |
- F |
-
-
- | 116 |
- R6448S |
- 3 |
- BXD66 |
- 61 |
- M |
-
-
- | 117 |
- R5794S |
- 1 |
- BXD66 |
- 144 |
- M |
-
-
- | 118 |
- R6502S |
- 3 |
- BXD67 |
- 66 |
- F |
-
-
- | 119 |
- R6545S |
- 3 |
- BXD67 |
- 61 |
- M |
-
-
- | 120 |
- R6337S |
- 3 |
- BXD68 |
- 56 |
- F |
-
-
- | 121 |
- R6594S |
- 3 |
- BXD68 |
- 64 |
- M |
-
-
- | 122 |
- R5796S |
- 1 |
- BXD69 |
- 85 |
- F |
-
-
- | 123 |
- R5798S |
- 1 |
- BXD69 |
- 98 |
- M |
-
-
- | 124 |
- R6402S |
- 3 |
- BXD70 |
- 93 |
- F |
-
-
- | 125 |
- R5841S |
- 1 |
- BXD70 |
- 121 |
- F |
-
-
- | 126 |
- R6592S |
- 3 |
- BXD70 |
- 59 |
- M |
-
-
- | 127 |
- R6328S |
- 3 |
- BXD71 |
- 87 |
- F |
-
-
- | 128 |
- R5967S |
- 2 |
- BXD71 |
- 64 |
- M |
-
-
- | 129 |
- R5969S |
- 2 |
- BXD73 |
- 64 |
- F |
-
-
- | 130 |
- R5800S |
- 1 |
- BXD73 |
- 120 |
- M |
-
-
- | 131 |
- R6646S |
- 3 |
- BXD74 |
- 40 |
- F |
-
-
- | 132 |
- R6524S |
- 3 |
- BXD74 |
- 72 |
- M |
-
-
- | 133 |
- R6445S |
- 3 |
- BXD75 |
- 85 |
- F |
-
-
- | 134 |
- R5843S |
- 1 |
- BXD75 |
- 103 |
- F |
-
-
- | 135 |
- R5845S |
- 1 |
- BXD75 |
- 103 |
- M |
-
-
- | 136 |
- R6604S |
- 3 |
- BXD77 |
- 64 |
- F |
-
-
- | 137 |
- R6513S |
- 3 |
- BXD77 |
- 72 |
- M |
-
-
- | 138 |
- R6582S |
- 3 |
- BXD78 |
- 144 |
- F |
-
-
- | 139 |
- R6563S |
- 3 |
- BXD78 |
- 95 |
- M |
-
-
- | 140 |
- R6645S4 |
- 4 |
- BXD79 |
- 66 |
- F |
-
-
- | 141 |
- R5806S |
- 1 |
- BXD79 |
- 78 |
- M |
-
-
- | 142 |
- R5847S |
- 1 |
- BXD80 |
- 89 |
- F |
-
-
- | 143 |
- R5852S |
- 1 |
- BXD80 |
- 79 |
- M |
-
-
- | 144 |
- R6562S |
- 3 |
- BXD81 |
- 99 |
- F |
-
-
- | 145 |
- R6468S |
- 3 |
- BXD81 |
- 65 |
- M |
-
-
- | 146 |
- R6560S |
- 3 |
- BXD82 |
- 85 |
- F |
-
-
- | 147 |
- R6512S |
- 3 |
- BXD83 |
- 68 |
- F |
-
-
- | 148 |
- R5810S |
- 1 |
- BXD83 |
- 139 |
- M |
-
-
- | 149 |
- R6510S |
- 3 |
- BXD84 |
- 87 |
- F |
-
-
- | 150 |
- R5970S |
- 2 |
- BXD84 |
- 107 |
- F |
-
-
- | 151 |
- R6603S |
- 3 |
- BXD84 |
- 99 |
- M |
-
-
- | 152 |
- R6517S |
- 3 |
- BXD85 |
- 58 |
- F |
-
-
- | 153 |
- R6718S1 |
- 4 |
- BXD85 |
- 86 |
- M |
-
-
- | 154 |
- R5812S |
- 1 |
- BXD86 |
- 61 |
- F |
-
-
- | 155 |
- R5814S |
- 1 |
- BXD86 |
- 59 |
- M |
-
-
- | 156 |
- R5816S |
- 1 |
- BXD87 |
- 112 |
- F |
-
-
- | 157 |
- R6488S |
- 3 |
- BXD87 |
- 137 |
- M |
-
-
- | 158 |
- R6580S |
- 3 |
- BXD88 |
- 125 |
- F |
-
-
- | 159 |
- R5977S |
- 2 |
- BXD89 |
- 68 |
- F |
-
-
- | 160 |
- R5979S |
- 2 |
- BXD89 |
- 79 |
- M |
-
-
- | 161 |
- R5978S |
- 2 |
- BXD89 |
- 79 |
- M |
-
-
- | 162 |
- R5818S |
- 1 |
- BXD90 |
- 106 |
- F |
-
-
- | 163 |
- R5820S |
- 1 |
- BXD90 |
- 131 |
- M |
-
-
- | 164 |
- R6343S |
- 3 |
- BXD92 |
- 62 |
- F |
-
-
- | 165 |
- R5984S |
- 2 |
- BXD92 |
- 55 |
- M |
-
-
- | 166 |
- R6581S |
- 3 |
- BXD93 |
- 173 |
- M |
-
-
- | 167 |
- R6557S |
- 3 |
- BXD93 |
- 126 |
- M |
-
-
- | 168 |
- R6509S |
- 3 |
- BXD95 |
- 59 |
- F |
-
-
- | 169 |
- R5822S |
- 1 |
- BXD95 |
- 89 |
- M |
-
-
- | 170 |
- R6640S4 |
- 4 |
- BXD96 |
- 70 |
- F |
-
-
- | 171 |
- R6514S |
- 3 |
- BXD96 |
- 64 |
- M |
-
-
- | 172 |
- R6506S |
- 3 |
- BXD97 |
- 78 |
- F |
-
-
- | 173 |
- R5849S |
- 1 |
- BXD97 |
- 130 |
- F |
-
-
- | 174 |
- R6591S |
- 3 |
- BXD97 |
- 122 |
- M |
-
-
- | 175 |
- R5990S |
- 2 |
- BXD98 |
- 65 |
- F |
-
-
- | 176 |
- R6596S |
- 3 |
- BXD98 |
- 67 |
- M |
-
-
- | 177 |
- R5993S |
- 2 |
- BXD99 |
- 74 |
- F |
-
-
- | 178 |
- R5995S |
- 2 |
- BXD99 |
- 50 |
- M |
-
-
- | 179 |
- R6607S |
- 3 |
- BXD100 |
- 75 |
- F |
-
-
- | 180 |
- R6411S |
- 3 |
- BXD100 |
- 104 |
- M |
-
-
- | 181 |
- R6508S |
- 3 |
- BXD101 |
- 59 |
- F |
-
-
- | 182 |
- R5593S |
- 1 |
- BXD101 |
- 59 |
- M |
-
-
- | 183 |
- R6523S |
- 3 |
- BXD102 |
- 60 |
- F |
-
-
- | 184 |
- R6466S |
- 3 |
- BXD102 |
- 50 |
- M |
-
-
- | 185 |
- R6404S |
- 3 |
- BXD103 |
- 72 |
- F |
-
-
- | 186 |
- R6609S |
- 3 |
- BXD103 |
- 57 |
- M |
-
-
- | 187 |
- R6555S |
- 3 |
- C57BL/10J |
- 73 |
- M |
-
-
- | 188 |
- R5596S |
- 1 |
- C57BL/10J |
- 73 |
- M |
-
-
- | 189 |
- R5597S |
- 1 |
- C57BL/6ByJ |
- 51 |
- F |
-
-
- | 190 |
- R5598S |
- 1 |
- C57BL/6ByJ |
- 69 |
- M |
-
-
- | 191 |
- R5600S |
- 1 |
- C57BL/6J |
- 79 |
- F |
-
-
- | 192 |
- R5599S |
- 1 |
- C57BL/6J |
- 60 |
- F |
-
-
- | 193 |
- R6451S |
- 3 |
- C57BL/6J |
- 77 |
- M |
-
-
- | 194 |
- R6410S |
- 3 |
- C57BL/6J |
- 85 |
- M |
-
-
- | 195 |
- R5603S |
- 1 |
- C57BLKS/J |
- 66 |
- F |
-
-
- | 196 |
- R5604S |
- 1 |
- C57BLKS/J |
- 66 |
- M |
-
-
- | 197 |
- R5996S |
- 2 |
- CBA/CaJ |
- 66 |
- F |
-
-
- | 198 |
- R6349S |
- 3 |
- CBA/CaJ |
- 66 |
- M |
-
-
- | 199 |
- R6458S |
- 3 |
- D2B6F1 |
- 64 |
- F |
-
-
- | 200 |
- R6353S |
- 3 |
- D2B6F1 |
- 60 |
- M |
-
-
- | 201 |
- R5605S |
- 1 |
- DBA/2J |
- 79 |
- F |
-
-
- | 202 |
- R6446S |
- 3 |
- DBA/2J |
- 83 |
- M |
-
-
- | 203 |
- R6597S |
- 3 |
- FVB/NJ |
- 60 |
- F |
-
-
- | 204 |
- R5643S |
- 1 |
- FVB/NJ |
- 60 |
- F |
-
-
- | 205 |
- R6598S |
- 3 |
- FVB/NJ |
- 60 |
- M |
-
-
- | 206 |
- R5606S |
- 1 |
- ILS |
- 74 |
- F |
-
-
- | 207 |
- R5607S |
- 1 |
- ILS |
- 74 |
- M |
-
-
- | 208 |
- R5610S |
- 1 |
- ISS |
- 97 |
- M |
-
-
- | 209 |
- R6627S |
- 3 |
- KK/HlJ |
- 64 |
- F |
-
-
- | 210 |
- R6444S |
- 3 |
- KK/HlJ |
- 65 |
- M |
-
-
- | 211 |
- R5702S |
- 1 |
- KK/HlJ |
- 61 |
- M |
-
-
- | 212 |
- R5613S |
- 1 |
- LG/J |
- 63 |
- F |
-
-
- | 213 |
- R5704S |
- 1 |
- LG/J |
- 65 |
- M |
-
-
- | 214 |
- R5614S |
- 1 |
- LP/J |
- 65 |
- F |
-
-
- | 215 |
- R5615S |
- 1 |
- LP/J |
- 65 |
- M |
-
-
- | 216 |
- R6599S |
- 3 |
- MOLF/EiJ |
- 60 |
- F |
-
-
- | 217 |
- R6606S |
- 3 |
- MOLF/EiJ |
- 60 |
- M |
-
-
- | 218 |
- R6544S |
- 3 |
- NOD/LtJ |
- 77 |
- F |
-
-
- | 219 |
- R5709S |
- 1 |
- NOD/LtJ |
- 58 |
- M |
-
-
- | 220 |
- R6601S |
- 3 |
- NZB/BlNJ |
- 61 |
- F |
-
-
- | 221 |
- R5711S |
- 1 |
- NZB/BlNJ |
- 61 |
- F |
-
-
- | 222 |
- R6427S |
- 3 |
- NZB/BlNJ |
- 58 |
- M |
-
-
- | 223 |
- R6150S |
- 2 |
- NZO/HlLtJ |
- 71 |
- F |
-
-
- | 224 |
- R6155S |
- 2 |
- NZW/LacJ |
- 65 |
- F |
-
-
- | 225 |
- R5654S |
- 1 |
- NZW/LacJ |
- 60 |
- M |
-
-
- | 226 |
- R5721S |
- 1 |
- PL/J |
- 59 |
- M |
-
-
- | 227 |
- R5616S |
- 1 |
- PWD/PhJ |
- 60 |
- M |
-
-
- | 228 |
- R5725S |
- 1 |
- PWK/PhJ |
- 121 |
- M |
-
-
- | 229 |
- R6174S |
- 2 |
- SJL/J |
- 63 |
- F |
-
-
- | 230 |
- R6350S |
- 3 |
- SJL/J |
- 65 |
- M |
-
-
- | 231 |
- R6419S |
- 3 |
- WSB/EiJ |
- 60 |
- F |
-
-
- | 232 |
- R5620S |
- 1 |
- WSB/EiJ |
- 60 |
- M |
-
-
-
-
- |
-
-
-
-
-
-
-
-
-
diff --git a/general/datasets/UTHSC_SPLs1_RMA_1210/summary.rtf b/general/datasets/UTHSC_SPLs1_RMA_1210/summary.rtf
deleted file mode 100644
index d9478f8..0000000
--- a/general/datasets/UTHSC_SPLs1_RMA_1210/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-This is a near final release of a spleen gene expression data set generated by a DOD-funded consortium (Byrne, Kotb, Williams, and Lu). Please contact Lu Lu or Robert Williams regarding status of this data set. The initial data enterted in 2010 had many errors described below. The data set is much improved and has no known errors of strain assignment.
-
-Animals were generated at UTHSC by Lu Lu and colleagues. The spleen of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/UTHSC_SPLs2_RMA_1210/cases.rtf b/general/datasets/UTHSC_SPLs2_RMA_1210/cases.rtf
deleted file mode 100644
index 7fa108f..0000000
--- a/general/datasets/UTHSC_SPLs2_RMA_1210/cases.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Cases. A total of 111 strains, including 81 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1), and 26 other common inbred strains were quantified. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by Lu Lu and colleagues. Samples were pooled by sex and usually include at least two cases per sex and strain.
-
-Sex Balance. XX strains have matched male and female samples. XX strains have male only samples (BXDX, XX, XX, XXX and XXX). XX strains have only female samples (BXDXX, XX, and XX.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/UTHSC_SPLs2_RMA_1210/experiment-design.rtf b/general/datasets/UTHSC_SPLs2_RMA_1210/experiment-design.rtf
deleted file mode 100644
index a0aeba6..0000000
--- a/general/datasets/UTHSC_SPLs2_RMA_1210/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-RNA Processing. Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
-
-Array Processing: All arrays were processed by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. The spleen was dissected by both Dr. Lu Lu and colleagues and Dr. Abdeltawab and colleagues. All arrays were run together (interleaved) as a single large batch.
diff --git a/general/datasets/UTHSC_SPLs2_RMA_1210/notes.rtf b/general/datasets/UTHSC_SPLs2_RMA_1210/notes.rtf
deleted file mode 100644
index c7bb873..0000000
--- a/general/datasets/UTHSC_SPLs2_RMA_1210/notes.rtf
+++ /dev/null
@@ -1,4 +0,0 @@
-Data Status and Use. This is a provisional release that will soon be replaced by a final corrected data set. In the interim this data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
-This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
-
-Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/UTHSC_SPLs2_RMA_1210/processing.rtf b/general/datasets/UTHSC_SPLs2_RMA_1210/processing.rtf
deleted file mode 100644
index deaf264..0000000
--- a/general/datasets/UTHSC_SPLs2_RMA_1210/processing.rtf
+++ /dev/null
@@ -1,1932 +0,0 @@
-Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
-
-Batch Effects. This data set required some correction for batch effects and the data in this initial release incorporate any additional corrections. There are several additional confounder-like factors that should be considered:
-
-
- - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
- - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest probe sets in this spleen data set accounts of XX% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the spleen data set can be mapped as a trait.
-
-
-Data Release. This data set was first uploaded into GeneNetwork by Arthur Centeno, October 11, 2010 and made accessible without a password to all users on November 1, 2010. The initial data release had numerous strain identification errors that have now largely been fixed. Based on an analysis of the top 20 Mendelian loci, the following 21 strains were likely to have been incorrectly identified or assigned in the current release:
-
-
- - BXD8, e.g., Probe set 10450161, 1036098. 10338684
- - BXD13, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10342568,
- - BXD21 (may be ok, only one probe set 10338684 is problematic)
- - BXD23 (may be ok, only two probe sets 10421128, 10419465 is problematic)
- - BXD36 (may be ok, only one probe set 10421128 is problematic)
- - BXD40, e.g., Probe set 10341070
- - BXD43, e.g., Probe set 10450161, 1036098, 10338684
- - BXD48, e.g., Probe set 1036098, 10402390, 10514896, 10592493, 10357381, 10342568, 10571444, 10419465
- - BXD62, e.g., Probe set 1036098, 1036098, 10402390, 10514896, 10592493, 10421128, 10571444
- - BXD68 (may be ok, only one probe set 10338684 is problematic)
- - BXD69, e.g., Probe set 10450161
- - BXD73, e.g., Probe set 10341070, 1036098, 10402390, 10514896, 10587633, 10342568, 10421128
- - BXD74, e.g., Probe set 10402390
- - BXD80, e.g., Probe set 10341070, 1036098, 10592493, 10400109, 10338684, 10342568, 10421128, 10419465
- - BXD83, e.g., Probe set 10450161, 10338684
- - BXD87 (may be ok, only one probe set 10421128 is problematic)
- - BXD89, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10357381, 10419465
- - BXD93, e.g., Probe set 10402390, 10357381
- - BALB/cByJ, e.g., Probe set 10388042, 1036098, 10587633, 10357381, 10342568, 10421128
- - LP/J, e.g., Probe set 10592493
- - DBA/2J, e.g., Probe set 10592493
-
-
-Data Evaluation Summary
-
-
- - Before correction: eQLTs with LOD >10 (LRS>46.1): n = 638
- - After strain assignment correction: eQLTs with LOD >10 (LRS>46.1): n = 820
- - Before correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 237.9
- - After correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 278.1
- - Lowest mean value: Trait ID 10344361, mean = 3.998
- - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
- - Greatest sex difference: Trait ID: 10606178 (Xist)
- - Great variation within and among strains: Trait ID 10454192 (Ttr
-
Table 1 (please confirm that these assignments are after correction)
-
-
-
-
-
-
-
-
-
- | Index |
- Array ID |
- Phase |
- Strain |
- Age |
- Sex |
-
-
- | 1 |
- R5583S |
- 1 |
- 129P3/J |
- 65 |
- F |
-
-
- | 2 |
- R5584S |
- 1 |
- 129P3/J |
- 66 |
- M |
-
-
- | 3 |
- R5585S |
- 1 |
- 129S1/SvImJ |
- 66 |
- F |
-
-
- | 4 |
- R5586S |
- 1 |
- 129S1/SvImJ |
- 66 |
- M |
-
-
- | 5 |
- R5587S |
- 1 |
- 129X1/SvJ |
- 65 |
- F |
-
-
- | 6 |
- R5588S |
- 1 |
- 129X1/SvJ |
- 66 |
- M |
-
-
- | 7 |
- R6348S |
- 3 |
- B6D2F1 |
- 67 |
- F |
-
-
- | 8 |
- R6347S |
- 3 |
- B6D2F1 |
- 62 |
- F |
-
-
- | 9 |
- R5590S |
- 1 |
- B6D2F1 |
- 79 |
- M |
-
-
- | 10 |
- R5662S |
- 1 |
- BALB/cByJ |
- 59 |
- F |
-
-
- | 11 |
- R5664S |
- 1 |
- BALB/cByJ |
- 59 |
- M |
-
-
- | 12 |
- R5591S |
- 1 |
- BALB/cJ |
- 51 |
- F |
-
-
- | 13 |
- R5592S |
- 1 |
- BALB/cJ |
- 51 |
- M |
-
-
- | 14 |
- R6154S |
- 2 |
- BTBR T+ tf/J |
- 60 |
- F |
-
-
- | 15 |
- R6516S |
- 3 |
- BXD1 |
- 82 |
- F |
-
-
- | 16 |
- R6584S |
- 3 |
- BXD1 |
- 95 |
- M |
-
-
- | 17 |
- R5759S |
- 1 |
- BXD2 |
- N/A |
- F |
-
-
- | 18 |
- R5837S |
- 1 |
- BXD2 |
- 106 |
- M |
-
-
- | 19 |
- R5874S |
- 2 |
- BXD5 |
- 86 |
- F |
-
-
- | 20 |
- R6554S |
- 3 |
- BXD5 |
- 60 |
- M |
-
-
- | 21 |
- R6359S |
- 3 |
- BXD6 |
- 72 |
- F |
-
-
- | 22 |
- R5777S |
- 1 |
- BXD6 |
- 149 |
- M |
-
-
- | 23 |
- R6364S |
- 3 |
- BXD8 |
- 76 |
- F |
-
-
- | 24 |
- R5637S |
- 1 |
- BXD8 |
- 71 |
- F |
-
-
- | 25 |
- R6365S |
- 3 |
- BXD8 |
- 76 |
- M |
-
-
- | 26 |
- R5746S |
- 1 |
- BXD9 |
- 70 |
- F |
-
-
- | 27 |
- R5981S |
- 2 |
- BXD9 |
- 67 |
- M |
-
-
- | 28 |
- R5980S |
- 2 |
- BXD9 |
- 67 |
- M |
-
-
- | 29 |
- R6182S |
- 2 |
- BXD11 |
- 84 |
- F |
-
-
- | 30 |
- R6486S |
- 3 |
- BXD11 |
- 58 |
- M |
-
-
- | 31 |
- R6711S2 |
- 4 |
- BXD12 |
- 71 |
- F |
-
-
- | 32 |
- R6608S |
- 3 |
- BXD12 |
- 48 |
- F |
-
-
- | 33 |
- R5885S |
- 2 |
- BXD12 |
- 44 |
- M |
-
-
- | 34 |
- R5755S |
- 1 |
- BXD13 |
- 160 |
- F |
-
-
- | 35 |
- R5887S |
- 2 |
- BXD13 |
- 53 |
- M |
-
-
- | 36 |
- R6180S |
- 2 |
- BXD14 |
- 70 |
- F |
-
-
- | 37 |
- R5669S |
- 1 |
- BXD14 |
- 91 |
- M |
-
-
- | 38 |
- R6456S |
- 3 |
- BXD15 |
- 60 |
- F |
-
-
- | 39 |
- R6622S |
- 3 |
- BXD15 |
- 60 |
- F |
-
-
- | 40 |
- R6626S |
- 3 |
- BXD15 |
- 60 |
- M |
-
-
- | 41 |
- R6181S |
- 2 |
- BXD16 |
- 74 |
- F |
-
-
- | 42 |
- R6515S |
- 3 |
- BXD16 |
- 64 |
- M |
-
-
- | 43 |
- R5673S |
- 1 |
- BXD18 |
- 80 |
- F |
-
-
- | 44 |
- R5674S |
- 1 |
- BXD18 |
- 65 |
- M |
-
-
- | 45 |
- R6553S |
- 3 |
- BXD19 |
- 158 |
- F |
-
-
- | 46 |
- R6551S |
- 3 |
- BXD19 |
- 60 |
- M |
-
-
- | 47 |
- R6643S4 |
- 4 |
- BXD20 |
- 59 |
- F |
-
-
- | 48 |
- R6595S |
- 3 |
- BXD20 |
- 60 |
- M |
-
-
- | 49 |
- R5735S |
- 1 |
- BXD21 |
- 64 |
- F |
-
-
- | 50 |
- R5892S |
- 2 |
- BXD21 |
- 99 |
- M |
-
-
- | 51 |
- R5896S |
- 2 |
- BXD22 |
- 60 |
- F |
-
-
- | 52 |
- R6414S |
- 3 |
- BXD22 |
- 73 |
- M |
-
-
- | 53 |
- R6550S |
- 3 |
- BXD23 |
- 74 |
- F |
-
-
- | 54 |
- R6586S |
- 3 |
- BXD23 |
- 102 |
- F |
-
-
- | 55 |
- R5630S |
- 1 |
- BXD24 |
- 71 |
- F |
-
-
- | 56 |
- R6356S |
- 3 |
- BXD24 |
- 57 |
- M |
-
-
- | 57 |
- R6162S |
- 2 |
- BXD25 |
- 67 |
- F |
-
-
- | 58 |
- R6625S |
- 3 |
- BXD25 |
- 67 |
- F |
-
-
- | 59 |
- R6642S4 |
- 4 |
- BXD25 |
- 58 |
- M |
-
-
- | 60 |
- R5761S |
- 1 |
- BXD27 |
- N/A |
- F |
-
-
- | 61 |
- R5763S |
- 1 |
- BXD27 |
- 90 |
- M |
-
-
- | 62 |
- R6621S |
- 3 |
- BXD28 |
- 113 |
- F |
-
-
- | 63 |
- R6548S |
- 3 |
- BXD28 |
- 60 |
- M |
-
-
- | 64 |
- R6547S |
- 3 |
- BXD29 |
- 60 |
- F |
-
-
- | 65 |
- R6453S |
- 3 |
- BXD31 |
- 48 |
- F |
-
-
- | 66 |
- R6452S |
- 3 |
- BXD31 |
- 48 |
- M |
-
-
- | 67 |
- R6583S |
- 3 |
- BXD32 |
- 60 |
- F |
-
-
- | 68 |
- R5765S |
- 1 |
- BXD32 |
- 71 |
- M |
-
-
- | 69 |
- R5689S |
- 1 |
- BXD33 |
- 65 |
- F |
-
-
- | 70 |
- R6450S |
- 3 |
- BXD33 |
- 55 |
- M |
-
-
- | 71 |
- R5767S |
- 1 |
- BXD34 |
- 72 |
- F |
-
-
- | 72 |
- R5900S |
- 2 |
- BXD34 |
- 70 |
- M |
-
-
- | 73 |
- R6588S |
- 3 |
- BXD36 |
- 61 |
- F |
-
-
- | 74 |
- R6490S |
- 3 |
- BXD36 |
- 63 |
- M |
-
-
- | 75 |
- R6417S |
- 3 |
- BXD38 |
- 64 |
- F |
-
-
- | 76 |
- R6439S |
- 3 |
- BXD38 |
- 72 |
- M |
-
-
- | 77 |
- R5769S |
- 1 |
- BXD39 |
- N/A |
- F |
-
-
- | 78 |
- R5771S |
- 1 |
- BXD39 |
- 74 |
- M |
-
-
- | 79 |
- R5773S |
- 1 |
- BXD40 |
- N/A |
- F |
-
-
- | 80 |
- R5775S |
- 1 |
- BXD40 |
- N/A |
- M |
-
-
- | 81 |
- R6494S |
- 3 |
- BXD41 |
- 72 |
- F |
-
-
- | 82 |
- R5910S |
- 2 |
- BXD42 |
- 79 |
- F |
-
-
- | 83 |
- R6493S |
- 3 |
- BXD42 |
- 69 |
- M |
-
-
- | 84 |
- R6341S |
- 3 |
- BXD43 |
- 59 |
- F |
-
-
- | 85 |
- R6401S |
- 3 |
- BXD43 |
- 99 |
- M |
-
-
- | 86 |
- R5916S |
- 2 |
- BXD43 |
- 79 |
- M |
-
-
- | 87 |
- R5839S |
- 1 |
- BXD44 |
- 141 |
- F |
-
-
- | 88 |
- R5779S |
- 1 |
- BXD44 |
- 124 |
- M |
-
-
- | 89 |
- R6405S |
- 3 |
- BXD45 |
- 58 |
- F |
-
-
- | 90 |
- R6610S |
- 3 |
- BXD45 |
- 55 |
- M |
-
-
- | 91 |
- R5922S |
- 2 |
- BXD48 |
- 64 |
- F |
-
-
- | 92 |
- R5925S |
- 2 |
- BXD48 |
- 60 |
- M |
-
-
- | 93 |
- R6719S1 |
- 4 |
- BXD49 |
- 58 |
- F |
-
-
- | 94 |
- R6485S |
- 3 |
- BXD49 |
- 79 |
- M |
-
-
- | 95 |
- R5781S |
- 1 |
- BXD50 |
- 61 |
- F |
-
-
- | 96 |
- R6464S |
- 3 |
- BXD51 |
- 65 |
- F |
-
-
- | 97 |
- R6585S |
- 3 |
- BXD51 |
- 63 |
- M |
-
-
- | 98 |
- R6500S |
- 3 |
- BXD55 |
- 58 |
- F |
-
-
- | 99 |
- R5938S |
- 2 |
- BXD55 |
- 93 |
- M |
-
-
- | 100 |
- R6504S |
- 3 |
- BXD56 |
- 58 |
- F |
-
-
- | 101 |
- R6503S |
- 3 |
- BXD56 |
- 58 |
- M |
-
-
- | 102 |
- R5783S |
- 1 |
- BXD60 |
- 111 |
- F |
-
-
- | 103 |
- R5784S |
- 1 |
- BXD60 |
- 85 |
- M |
-
-
- | 104 |
- R5786S |
- 1 |
- BXD61 |
- 86 |
- F |
-
-
- | 105 |
- R6449S |
- 3 |
- BXD61 |
- 65 |
- M |
-
-
- | 106 |
- R6716S1 |
- 4 |
- BXD62 |
- 54 |
- F |
-
-
- | 107 |
- R5790S |
- 1 |
- BXD62 |
- 115 |
- M |
-
-
- | 108 |
- R6519S |
- 3 |
- BXD63 |
- 54 |
- F |
-
-
- | 109 |
- R6717S1 |
- 4 |
- BXD63 |
- 70 |
- M |
-
-
- | 110 |
- R5792S |
- 1 |
- BXD64 |
- 167 |
- F |
-
-
- | 111 |
- R6641S4 |
- 4 |
- BXD64 |
- 68 |
- M |
-
-
- | 112 |
- R6630S |
- 3 |
- BXD64 |
- 68 |
- M |
-
-
- | 113 |
- R6477S |
- 3 |
- BXD65 |
- 58 |
- F |
-
-
- | 114 |
- R6628S |
- 3 |
- BXD65 |
- 70 |
- M |
-
-
- | 115 |
- R6511S |
- 3 |
- BXD66 |
- 70 |
- F |
-
-
- | 116 |
- R6448S |
- 3 |
- BXD66 |
- 61 |
- M |
-
-
- | 117 |
- R5794S |
- 1 |
- BXD66 |
- 144 |
- M |
-
-
- | 118 |
- R6502S |
- 3 |
- BXD67 |
- 66 |
- F |
-
-
- | 119 |
- R6545S |
- 3 |
- BXD67 |
- 61 |
- M |
-
-
- | 120 |
- R6337S |
- 3 |
- BXD68 |
- 56 |
- F |
-
-
- | 121 |
- R6594S |
- 3 |
- BXD68 |
- 64 |
- M |
-
-
- | 122 |
- R5796S |
- 1 |
- BXD69 |
- 85 |
- F |
-
-
- | 123 |
- R5798S |
- 1 |
- BXD69 |
- 98 |
- M |
-
-
- | 124 |
- R6402S |
- 3 |
- BXD70 |
- 93 |
- F |
-
-
- | 125 |
- R5841S |
- 1 |
- BXD70 |
- 121 |
- F |
-
-
- | 126 |
- R6592S |
- 3 |
- BXD70 |
- 59 |
- M |
-
-
- | 127 |
- R6328S |
- 3 |
- BXD71 |
- 87 |
- F |
-
-
- | 128 |
- R5967S |
- 2 |
- BXD71 |
- 64 |
- M |
-
-
- | 129 |
- R5969S |
- 2 |
- BXD73 |
- 64 |
- F |
-
-
- | 130 |
- R5800S |
- 1 |
- BXD73 |
- 120 |
- M |
-
-
- | 131 |
- R6646S |
- 3 |
- BXD74 |
- 40 |
- F |
-
-
- | 132 |
- R6524S |
- 3 |
- BXD74 |
- 72 |
- M |
-
-
- | 133 |
- R6445S |
- 3 |
- BXD75 |
- 85 |
- F |
-
-
- | 134 |
- R5843S |
- 1 |
- BXD75 |
- 103 |
- F |
-
-
- | 135 |
- R5845S |
- 1 |
- BXD75 |
- 103 |
- M |
-
-
- | 136 |
- R6604S |
- 3 |
- BXD77 |
- 64 |
- F |
-
-
- | 137 |
- R6513S |
- 3 |
- BXD77 |
- 72 |
- M |
-
-
- | 138 |
- R6582S |
- 3 |
- BXD78 |
- 144 |
- F |
-
-
- | 139 |
- R6563S |
- 3 |
- BXD78 |
- 95 |
- M |
-
-
- | 140 |
- R6645S4 |
- 4 |
- BXD79 |
- 66 |
- F |
-
-
- | 141 |
- R5806S |
- 1 |
- BXD79 |
- 78 |
- M |
-
-
- | 142 |
- R5847S |
- 1 |
- BXD80 |
- 89 |
- F |
-
-
- | 143 |
- R5852S |
- 1 |
- BXD80 |
- 79 |
- M |
-
-
- | 144 |
- R6562S |
- 3 |
- BXD81 |
- 99 |
- F |
-
-
- | 145 |
- R6468S |
- 3 |
- BXD81 |
- 65 |
- M |
-
-
- | 146 |
- R6560S |
- 3 |
- BXD82 |
- 85 |
- F |
-
-
- | 147 |
- R6512S |
- 3 |
- BXD83 |
- 68 |
- F |
-
-
- | 148 |
- R5810S |
- 1 |
- BXD83 |
- 139 |
- M |
-
-
- | 149 |
- R6510S |
- 3 |
- BXD84 |
- 87 |
- F |
-
-
- | 150 |
- R5970S |
- 2 |
- BXD84 |
- 107 |
- F |
-
-
- | 151 |
- R6603S |
- 3 |
- BXD84 |
- 99 |
- M |
-
-
- | 152 |
- R6517S |
- 3 |
- BXD85 |
- 58 |
- F |
-
-
- | 153 |
- R6718S1 |
- 4 |
- BXD85 |
- 86 |
- M |
-
-
- | 154 |
- R5812S |
- 1 |
- BXD86 |
- 61 |
- F |
-
-
- | 155 |
- R5814S |
- 1 |
- BXD86 |
- 59 |
- M |
-
-
- | 156 |
- R5816S |
- 1 |
- BXD87 |
- 112 |
- F |
-
-
- | 157 |
- R6488S |
- 3 |
- BXD87 |
- 137 |
- M |
-
-
- | 158 |
- R6580S |
- 3 |
- BXD88 |
- 125 |
- F |
-
-
- | 159 |
- R5977S |
- 2 |
- BXD89 |
- 68 |
- F |
-
-
- | 160 |
- R5979S |
- 2 |
- BXD89 |
- 79 |
- M |
-
-
- | 161 |
- R5978S |
- 2 |
- BXD89 |
- 79 |
- M |
-
-
- | 162 |
- R5818S |
- 1 |
- BXD90 |
- 106 |
- F |
-
-
- | 163 |
- R5820S |
- 1 |
- BXD90 |
- 131 |
- M |
-
-
- | 164 |
- R6343S |
- 3 |
- BXD92 |
- 62 |
- F |
-
-
- | 165 |
- R5984S |
- 2 |
- BXD92 |
- 55 |
- M |
-
-
- | 166 |
- R6581S |
- 3 |
- BXD93 |
- 173 |
- M |
-
-
- | 167 |
- R6557S |
- 3 |
- BXD93 |
- 126 |
- M |
-
-
- | 168 |
- R6509S |
- 3 |
- BXD95 |
- 59 |
- F |
-
-
- | 169 |
- R5822S |
- 1 |
- BXD95 |
- 89 |
- M |
-
-
- | 170 |
- R6640S4 |
- 4 |
- BXD96 |
- 70 |
- F |
-
-
- | 171 |
- R6514S |
- 3 |
- BXD96 |
- 64 |
- M |
-
-
- | 172 |
- R6506S |
- 3 |
- BXD97 |
- 78 |
- F |
-
-
- | 173 |
- R5849S |
- 1 |
- BXD97 |
- 130 |
- F |
-
-
- | 174 |
- R6591S |
- 3 |
- BXD97 |
- 122 |
- M |
-
-
- | 175 |
- R5990S |
- 2 |
- BXD98 |
- 65 |
- F |
-
-
- | 176 |
- R6596S |
- 3 |
- BXD98 |
- 67 |
- M |
-
-
- | 177 |
- R5993S |
- 2 |
- BXD99 |
- 74 |
- F |
-
-
- | 178 |
- R5995S |
- 2 |
- BXD99 |
- 50 |
- M |
-
-
- | 179 |
- R6607S |
- 3 |
- BXD100 |
- 75 |
- F |
-
-
- | 180 |
- R6411S |
- 3 |
- BXD100 |
- 104 |
- M |
-
-
- | 181 |
- R6508S |
- 3 |
- BXD101 |
- 59 |
- F |
-
-
- | 182 |
- R5593S |
- 1 |
- BXD101 |
- 59 |
- M |
-
-
- | 183 |
- R6523S |
- 3 |
- BXD102 |
- 60 |
- F |
-
-
- | 184 |
- R6466S |
- 3 |
- BXD102 |
- 50 |
- M |
-
-
- | 185 |
- R6404S |
- 3 |
- BXD103 |
- 72 |
- F |
-
-
- | 186 |
- R6609S |
- 3 |
- BXD103 |
- 57 |
- M |
-
-
- | 187 |
- R6555S |
- 3 |
- C57BL/10J |
- 73 |
- M |
-
-
- | 188 |
- R5596S |
- 1 |
- C57BL/10J |
- 73 |
- M |
-
-
- | 189 |
- R5597S |
- 1 |
- C57BL/6ByJ |
- 51 |
- F |
-
-
- | 190 |
- R5598S |
- 1 |
- C57BL/6ByJ |
- 69 |
- M |
-
-
- | 191 |
- R5600S |
- 1 |
- C57BL/6J |
- 79 |
- F |
-
-
- | 192 |
- R5599S |
- 1 |
- C57BL/6J |
- 60 |
- F |
-
-
- | 193 |
- R6451S |
- 3 |
- C57BL/6J |
- 77 |
- M |
-
-
- | 194 |
- R6410S |
- 3 |
- C57BL/6J |
- 85 |
- M |
-
-
- | 195 |
- R5603S |
- 1 |
- C57BLKS/J |
- 66 |
- F |
-
-
- | 196 |
- R5604S |
- 1 |
- C57BLKS/J |
- 66 |
- M |
-
-
- | 197 |
- R5996S |
- 2 |
- CBA/CaJ |
- 66 |
- F |
-
-
- | 198 |
- R6349S |
- 3 |
- CBA/CaJ |
- 66 |
- M |
-
-
- | 199 |
- R6458S |
- 3 |
- D2B6F1 |
- 64 |
- F |
-
-
- | 200 |
- R6353S |
- 3 |
- D2B6F1 |
- 60 |
- M |
-
-
- | 201 |
- R5605S |
- 1 |
- DBA/2J |
- 79 |
- F |
-
-
- | 202 |
- R6446S |
- 3 |
- DBA/2J |
- 83 |
- M |
-
-
- | 203 |
- R6597S |
- 3 |
- FVB/NJ |
- 60 |
- F |
-
-
- | 204 |
- R5643S |
- 1 |
- FVB/NJ |
- 60 |
- F |
-
-
- | 205 |
- R6598S |
- 3 |
- FVB/NJ |
- 60 |
- M |
-
-
- | 206 |
- R5606S |
- 1 |
- ILS |
- 74 |
- F |
-
-
- | 207 |
- R5607S |
- 1 |
- ILS |
- 74 |
- M |
-
-
- | 208 |
- R5610S |
- 1 |
- ISS |
- 97 |
- M |
-
-
- | 209 |
- R6627S |
- 3 |
- KK/HlJ |
- 64 |
- F |
-
-
- | 210 |
- R6444S |
- 3 |
- KK/HlJ |
- 65 |
- M |
-
-
- | 211 |
- R5702S |
- 1 |
- KK/HlJ |
- 61 |
- M |
-
-
- | 212 |
- R5613S |
- 1 |
- LG/J |
- 63 |
- F |
-
-
- | 213 |
- R5704S |
- 1 |
- LG/J |
- 65 |
- M |
-
-
- | 214 |
- R5614S |
- 1 |
- LP/J |
- 65 |
- F |
-
-
- | 215 |
- R5615S |
- 1 |
- LP/J |
- 65 |
- M |
-
-
- | 216 |
- R6599S |
- 3 |
- MOLF/EiJ |
- 60 |
- F |
-
-
- | 217 |
- R6606S |
- 3 |
- MOLF/EiJ |
- 60 |
- M |
-
-
- | 218 |
- R6544S |
- 3 |
- NOD/LtJ |
- 77 |
- F |
-
-
- | 219 |
- R5709S |
- 1 |
- NOD/LtJ |
- 58 |
- M |
-
-
- | 220 |
- R6601S |
- 3 |
- NZB/BlNJ |
- 61 |
- F |
-
-
- | 221 |
- R5711S |
- 1 |
- NZB/BlNJ |
- 61 |
- F |
-
-
- | 222 |
- R6427S |
- 3 |
- NZB/BlNJ |
- 58 |
- M |
-
-
- | 223 |
- R6150S |
- 2 |
- NZO/HlLtJ |
- 71 |
- F |
-
-
- | 224 |
- R6155S |
- 2 |
- NZW/LacJ |
- 65 |
- F |
-
-
- | 225 |
- R5654S |
- 1 |
- NZW/LacJ |
- 60 |
- M |
-
-
- | 226 |
- R5721S |
- 1 |
- PL/J |
- 59 |
- M |
-
-
- | 227 |
- R5616S |
- 1 |
- PWD/PhJ |
- 60 |
- M |
-
-
- | 228 |
- R5725S |
- 1 |
- PWK/PhJ |
- 121 |
- M |
-
-
- | 229 |
- R6174S |
- 2 |
- SJL/J |
- 63 |
- F |
-
-
- | 230 |
- R6350S |
- 3 |
- SJL/J |
- 65 |
- M |
-
-
- | 231 |
- R6419S |
- 3 |
- WSB/EiJ |
- 60 |
- F |
-
-
- | 232 |
- R5620S |
- 1 |
- WSB/EiJ |
- 60 |
- M |
-
-
-
-
- |
-
-
-
-
-
-
-
-
-
diff --git a/general/datasets/UTHSC_SPLs2_RMA_1210/summary.rtf b/general/datasets/UTHSC_SPLs2_RMA_1210/summary.rtf
deleted file mode 100644
index d9478f8..0000000
--- a/general/datasets/UTHSC_SPLs2_RMA_1210/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-This is a near final release of a spleen gene expression data set generated by a DOD-funded consortium (Byrne, Kotb, Williams, and Lu). Please contact Lu Lu or Robert Williams regarding status of this data set. The initial data enterted in 2010 had many errors described below. The data set is much improved and has no known errors of strain assignment.
-
-Animals were generated at UTHSC by Lu Lu and colleagues. The spleen of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/acknowledgment.rtf b/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/acknowledgment.rtf
deleted file mode 100644
index 1853348..0000000
--- a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We thank Varigenix and Charle River Laboratory for their donation of BXD cyropreserved hepatcytes. We thank Jesse Ingels for preparing RNA samples. We thank Lorne Rose and the UTHSC Molecular Resource Center for processing RNA samples and generating array data. We thank Arthur Centeno for data entry. We thank the UTHSC CITG and the UT-ORNL Governor's chair for support of microarray analysis.
diff --git a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/cases.rtf b/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/cases.rtf
deleted file mode 100644
index e06c56f..0000000
--- a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/cases.rtf
+++ /dev/null
@@ -1,266 +0,0 @@
-
-
-
- | Sample ID |
- Varigenix Strain |
- Sex |
- RNA Concentrations
- ng/ul |
- 260/280 |
- 260/230 |
- Agilent
- Concentration(ng/ul) |
- RIN |
-
-
- | V1 |
- BXD32 |
- M |
- 1414.8 |
- 2.09 |
- 2.21 |
- 3,062 |
- 9.3 |
-
-
- | V2 |
- BXD1 |
- M |
- 1608.9 |
- 2.11 |
- 2.24 |
- 3,102 |
- 9.3 |
-
-
- | V3 |
- BXD5 |
- M |
- 1263.91 |
- 2.1 |
- 2.09 |
- 2,460 |
- 8.5 |
-
-
- | V4 |
- BXD31 |
- M |
- 1793.95 |
- 2.1 |
- 2.22 |
- 3,387 |
- 8.5 |
-
-
- | V5 |
- BXD8 |
- M |
- 1193.21 |
- 2.1 |
- 2.17 |
- 2,293 |
- 9.3 |
-
-
- | V6 |
- BXD18 |
- M |
- 1041.05 |
- 2.13 |
- 2.17 |
- 2,115 |
- 9.2 |
-
-
- | V7 |
- BXD42 |
- M |
- 398.28 |
- 1.99 |
- 2.28 |
- 1,519 |
- 8.3 |
-
-
- | V8 |
- BXD29 |
- M |
- 477.37 |
- 2.02 |
- 2.24 |
- 1,301 |
- 8.1 |
-
-
- | V9 |
- BXD21 |
- M |
- 414.6 |
- 2 |
- 2.27 |
- 1,174 |
- 8.3 |
-
-
- | V10 |
- BXD27 |
- M |
- 438.61 |
- 2.02 |
- 2.27 |
- 1,100 |
- 8.1 |
-
-
- | V11 |
- BXD16 |
- M |
- 436.21 |
- 2.01 |
- 2.27 |
- 868 |
- 8.5 |
-
-
- | V12 |
- BXD19 |
- M |
- 489.12 |
- 2.01 |
- 2.26 |
- 1,277 |
- 8 |
-
-
- | V13 |
- BXD22 |
- M |
- 1032.89 |
- 2.09 |
- 2.22 |
- 2,060 |
- 7.8 |
-
-
- | V14 |
- BXD38 |
- M |
- 510.24 |
- 2.01 |
- 2.22 |
- 1,213 |
- 8 |
-
-
- | V15 |
- BXD34 |
- M |
- 1021.26 |
- 2.09 |
- 2.24 |
- 1,514 |
- 8.2 |
-
-
- | V16 |
- BXD20 |
- M |
- 330.85 |
- 2 |
- 2.27 |
- 901 |
- 8.1 |
-
-
- | V17 |
- BXD15 |
- M |
- 1220.54 |
- 2.1 |
- 2.21 |
- 1,909 |
- 8.1 |
-
-
- | V18 |
- BXD6 |
- M |
- 1001.04 |
- 2.09 |
- 2.2 |
- 1,523 |
- 8.3 |
-
-
- | V19 |
- BXD13 |
- M |
- 1241.88 |
- 2.1 |
- 2.21 |
- 1,770 |
- 8.2 |
-
-
- | V20 |
- BXD40 |
- M |
- 1032.04 |
- 2.08 |
- 2.22 |
- 1,985 |
- 8.2 |
-
-
- | V21 |
- BXD14 |
- M |
- 881.62 |
- 2.11 |
- 2.19 |
- 481 |
- 8.7 |
-
-
- | V22 |
- BXD2 |
- M |
- 1069.09 |
- 2.08 |
- 2.22 |
- 1,536 |
- 8.2 |
-
-
- | V23 |
- BXD28 |
- M |
- 452.6 |
- 2 |
- 2.26 |
- 2,567 |
- 7.9 |
-
-
- | V24 |
- BXD11 |
- M |
- 930.72 |
- 2.07 |
- 2.21 |
- 999 |
- 8.5 |
-
-
- | V25 |
- BXD39 |
- M |
- 1177.27 |
- 2.07 |
- 2.23 |
- 838 |
- 8.7 |
-
-
-
diff --git a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/experiment-design.rtf b/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/experiment-design.rtf
deleted file mode 100644
index 323648a..0000000
--- a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Control hepatocyte mRNA expression data prior to any treatment for young adult male BXD strains. This is esssentially the mRNA state of frozen hepatocytes.
-
-
diff --git a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/platform.rtf b/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/platform.rtf
deleted file mode 100644
index 61c48c5..0000000
--- a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Affy Mouse Gene 1.0 ST (GPL6246)
diff --git a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/processing.rtf b/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/processing.rtf
deleted file mode 100644
index 662571f..0000000
--- a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Standard 2z+8 of log2 data. RMA data were log2 transformed (adding an olffset of 1 to avoid negative values). Variance was stablized (i.e. each array was converted to a set of Z scores). Z scores were then multipled by 2. Mean Z was then shifted from 0 to to 8 units per array.
diff --git a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/summary.rtf b/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/summary.rtf
deleted file mode 100644
index 8e4cabf..0000000
--- a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-mRNA levels in cryopreserved BXD strain hepatotcytes (males at 60 days of age) immediately after thawing to 4 deg C. This is the "frozen state" mRNA status.
diff --git a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/tissue.rtf b/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/tissue.rtf
deleted file mode 100644
index 94ad98a..0000000
--- a/general/datasets/UTHSC_VGX_MmBXDHepatocytesRMA1014/tissue.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-
-
-Hepatocytes prepared by Rob Kaiser at CRL Piedmont in Spring of 2011. Held in liquid nitrogen (vapor phase) until use Fall 2014 at UTHSC.
-
-One vial of hepatocytes in 1 ml of freeze media was wiped with 70% ETOH, quick thawed by swift agitation in a 37 degree C water bath until a small amount of ice remained in the vial. Contents of the vial were removed with a sterile 1000 ul pipette tip and added to a 5 ml sterile polypropylene tube on ice containing 3 ml of ice-cold sterile 1x PBS. sitting in ice. One ml of sterile ice-cold 1x PBS was added to the original vial to remove any remaining cells and added to the 5 ml tube on ice. This process was quickly repeated with three more vials of cells. Four 5 ml tubes were centrifuged at 8,000 rpm at 4 degrees C for 4 minutes to pellet hepatocytes. PBS diluted freeze media was completely removed from the cell pellet. Entire process for sets of vials took about 7 minutes until RNA lysis buffer was added.
-
-The QIAgen AllPrep DNA/RNA mini kit was used in conjunction with the QIAcube for purification of DNA and RNA from the hepatocytes. 600 ul of kit lysis buffer was added to pelleted cells, along with one 5 mm sterile stainless steel bead and cells were completely disrupted using the TissueLyser. The QIAcube protocol was used first for DNA extraction (held at -80 deg C for future use) and the flow-through containing total RNA was then used for the second purification.
-
-Any residual DNA was removed from the RNA before Agilent quantification of concentration and RIN, using the QIAgen DNase I reagent, followed by ethanol precipitation and resuspension of DNA-free total RNA in 50 ul RNAse free water.
diff --git a/general/datasets/UTHSC_mm10_B6D2_Ret_miRNA_1116/experiment-design.rtf b/general/datasets/UTHSC_mm10_B6D2_Ret_miRNA_1116/experiment-design.rtf
deleted file mode 100644
index ad9776a..0000000
--- a/general/datasets/UTHSC_mm10_B6D2_Ret_miRNA_1116/experiment-design.rtf
+++ /dev/null
@@ -1,980 +0,0 @@
-
-
-
-
-
-
-
-
- | Index |
- Sample ID |
- Case ID |
- Strain |
- Sex |
- DOB |
- Sac date |
- Age group |
- Age (days) |
- Age (month) |
- EarTag Number |
- Tube ID |
- Agilent RNA concentration (ng/ul) |
- RIN |
- Nanodrop RNA concentration (ng/ul) |
- 260/280 |
- 260/230 |
- Batch ID |
- Notes |
-
-
- | 1 |
- B6.01 |
- 071515.08 |
- C57BL/6J |
- M |
- 06/15/15 |
- 07/15/15 |
- 1~2 |
- 30 |
- 1.0 |
- |
- R11 |
- 173 |
- 10.00 |
- 181.22 |
- 2.09 |
- 2.12 |
- 2 |
- best |
-
-
- | 2 |
- B6.02 |
- 071515.09 |
- C57BL/6J |
- M |
- 06/15/15 |
- 07/15/15 |
- 1~2 |
- 30 |
- 1.0 |
- |
- R12 |
- 121 |
- N/A |
- 148.52 |
- 2.10 |
- 1.69 |
- 2 |
- best |
-
-
- | 3 |
- B6.03 |
- 052314.01 |
- C57BL/6J |
- F |
- 03/23/14 |
- 05/23/14 |
- 2~4 |
- 61 |
- 2.0 |
- |
- Ret 32 |
- 68 |
- 10.0 |
- 48.53 |
- 2.02 |
- 1.93 |
- 1 |
- |
-
-
- | 4 |
- B6.04 |
- 062514.01 |
- C57BL/6J |
- M |
- 04/10/14 |
- 06/25/14 |
- 2~4 |
- 76 |
- 2.5 |
- |
- Ret 21 |
- 81 |
- 9.0 |
- 168.7 |
- 2.06 |
- 1.97 |
- 1 |
- |
-
-
- | 5 |
- B6.05 |
- 040816.03 |
- C57BL/6J |
- M |
- 02/04/16 |
- 04/08/16 |
- 2~4 |
- 64 |
- 2.1 |
- |
- R74 |
- 385 |
- 10.00 |
- 448.16 |
- 1.98 |
- 2.12 |
- 2 |
- |
-
-
- | 6 |
- B6.06 |
- 040816.04 |
- C57BL/6J |
- M |
- 02/04/16 |
- 04/08/16 |
- 2~4 |
- 64 |
- 2.1 |
- |
- R75 |
- 226 |
- 8.70 |
- 167.31 |
- 2.04 |
- 2.13 |
- 2 |
- |
-
-
- | 7 |
- B6.07 |
- 041014.19 |
- C57BL/6J |
- F |
- 10/20/13 |
- 04/10/14 |
- 5~7 |
- 172 |
- 5.7 |
- |
- Ret 10 |
- 22 |
- 10.0 |
- 36.97 |
- 2.22 |
- 0.051 |
- 1 |
- |
-
-
- | 8 |
- B6.08 |
- 101813.27 |
- C57BL/6J |
- M |
- 05/06/13 |
- 10/18/13 |
- 5~7 |
- 165 |
- 5.5 |
- |
- Ret 7 |
- 38 |
- 10.0 |
- 54.47 |
- 2.08 |
- 0.094 |
- 1 |
- |
-
-
- | 9 |
- B6.09 |
- 050214.03 |
- C57BL/6J |
- F |
- 08/14/13 |
- 05/02/14 |
- 7~9 |
- 261 |
- 8.7 |
- |
- Ret 27 |
- 20 |
- 10.0 |
- 54.45 |
- 2.11 |
- 1.14 |
- 1 |
- |
-
-
- | 10 |
- B6.10 |
- 041014.24 |
- C57BL/6J |
- M |
- 09/02/13 |
- 04/10/14 |
- 7~9 |
- 220 |
- 7.3 |
- |
- Ret 12 |
- 38 |
- 9.50 |
- 58.97 |
- 2.08 |
- 2.14 |
- 1 |
- |
-
-
- | 11 |
- B6.11 |
- 101813.17 |
- C57BL/6J |
- F |
- 12/07/12 |
- 10/18/13 |
- 10~12 |
- 315 |
- 10.5 |
- |
- Ret 2 |
- 59 |
- 9.40 |
- 83.86 |
- 2.17 |
- 1.87 |
- 1 |
- |
-
-
- | 12 |
- B6.12 |
- 052116.01 |
- C57BL/6J |
- M |
- 05/19/15 |
- 05/22/16 |
- 10~12 |
- 369 |
- 12.3 |
- |
- R102 |
- 293 |
- 8.30 |
- 179.69 |
- 2.06 |
- 2.11 |
- 2 |
- |
-
-
- | 13 |
- B6.13 |
- 052116.02 |
- C57BL/6J |
- M |
- 05/19/15 |
- 05/22/16 |
- 10~12 |
- 369 |
- 12.3 |
- |
- R103 |
- 255 |
- 8.40 |
- 194.24 |
- 2.04 |
- 1.82 |
- 2 |
- |
-
-
- | 14 |
- B6.14 |
- 042114.19 |
- C57BL/6J |
- F |
- 03/11/13 |
- 04/21/14 |
- 13~15 |
- 406 |
- 13.5 |
- 1252 |
- Ret 26 |
- 28 |
- 10.0 |
- 39.95 |
- 2.22 |
- 1.71 |
- 1 |
- |
-
-
- | 15 |
- B6.15 |
- 050214.07 |
- C57BL/6J |
- M |
- 03/20/13 |
- 05/02/14 |
- 13~15 |
- 408 |
- 13.6 |
- |
- Ret 28 |
- 30 |
- 10.0 |
- 51.81 |
- 2.06 |
- 2.07 |
- 1 |
- |
-
-
- | 16 |
- B6.16 |
- 041714.02 |
- C57BL/6J |
- M |
- 09/18/12 |
- 04/17/14 |
- 19~21 |
- 576 |
- 19.2 |
- 1117 |
- Ret 17 |
- 25 |
- 10.0 |
- 51.55 |
- 2.13 |
- 1.13 |
- 1 |
- |
-
-
- | 17 |
- B6.17 |
- 041714.03 |
- C57BL/6J |
- M |
- 09/18/12 |
- 04/17/14 |
- 19~21 |
- 576 |
- 19.2 |
- 1116 |
- Ret 18 |
- 28 |
- 10.0 |
- 65.11 |
- 2.01 |
- 2.16 |
- 1 |
- |
-
-
- | 18 |
- D2.01 |
- 030116.02 |
- DBA/2J |
- M |
- 01/29/16 |
- 03/01/16 |
- 1~2 |
- 32 |
- 1.1 |
- |
- R63 |
- 107 |
- 8.80 |
- 119.02 |
- 2.05 |
- 1.79 |
- 2 |
- |
-
-
- | 19 |
- D2.02 |
- 030116.04 |
- DBA/2J |
- M |
- 01/29/16 |
- 03/01/16 |
- 1~2 |
- 32 |
- 1.1 |
- |
- R65 |
- 202 |
- 9.10 |
- 250.38 |
- 2.03 |
- 1.67 |
- 2 |
- |
-
-
- | 20 |
- D2.03 |
- 062714.02 |
- DBA/2J |
- F |
- 03/23/14 |
- 06/27/14 |
- 2~4 |
- 104 |
- 3.5 |
- |
- Ret 20a |
- |
- |
- 189.3 |
- 1.95 |
- 1.81 |
- 1 |
- No Agilent as of 6/27/2014 |
-
-
- | 21 |
- D2.04 |
- 062714.01 |
- DBA/2J |
- M |
- 03/19/14 |
- 06/27/14 |
- 2~4 |
- 100 |
- 3.3 |
- |
- Ret 19a |
- |
- |
- 154 |
- 2.05 |
- 1.89 |
- 1 |
- No Agilent as of 6/27/2014 |
-
-
- | 22 |
- D2.05 |
- 032316.03 |
- DBA/2J |
- M |
- 01/23/16 |
- 03/23/16 |
- 2~4 |
- 60 |
- 2.0 |
- |
- R70 |
- 99 |
- 9.30 |
- 99.17 |
- 2.04 |
- 1.63 |
- 2 |
- |
-
-
- | 23 |
- D2.06 |
- 032316.04 |
- DBA/2J |
- M |
- 01/23/16 |
- 03/23/16 |
- 2~4 |
- 60 |
- 2.0 |
- |
- R71 |
- 205 |
- 9.10 |
- 124.33 |
- 2.03 |
- 1.24 |
- 2 |
- |
-
-
- | 24 |
- D2.07 |
- 050214.11 |
- DBA/2J |
- F |
- 12/07/13 |
- 05/02/14 |
- 5~7 |
- 146 |
- 4.9 |
- |
- Ret 29 |
- 100 |
- 10.0 |
- 86.47 |
- 2.14 |
- 1.9 |
- 1 |
- |
-
-
- | 25 |
- D2.08 |
- 101813.08 |
- DBA/2J |
- M |
- 03/21/13 |
- 10/18/13 |
- 5~7 |
- 211 |
- 7.0 |
- |
- Ret 1 |
- 52 |
- 9.9 |
- 86.98 |
- 2.11 |
- 2.12 |
- 1 |
- |
-
-
- | 26 |
- D2.09 |
- 041014.23 |
- DBA/2J |
- F |
- 08/24/13 |
- 04/10/14 |
- 7~9 |
- 229 |
- 7.6 |
- |
- Ret 11 |
- 21 |
- 9.9 |
- 44.39 |
- 2.17 |
- 1.15 |
- 1 |
- |
-
-
- | 27 |
- D2.10 |
- 050214.15 |
- DBA/2J |
- F |
- 07/27/13 |
- 05/02/14 |
- 7~9 |
- 279 |
- 9.3 |
- |
- Ret 30 |
- 37 |
- 10.0 |
- 43.57 |
- 2.13 |
- 2.04 |
- 1 |
- |
-
-
- | 28 |
- D2.11 |
- 101813.23 |
- DBA/2J |
- F |
- 11/29/12 |
- 10/18/13 |
- 10~12 |
- 323 |
- 10.8 |
- |
- Ret 6 |
- 77 |
- 9.7 |
- 105.02 |
- 2.06 |
- 2.14 |
- 1 |
- |
-
-
- | 29 |
- D2.12 |
- 101813.19 |
- DBA/2J |
- M |
- 12/08/12 |
- 10/18/13 |
- 10~12 |
- 314 |
- 10.5 |
- |
- Ret 3 |
- 46 |
- 9.9 |
- 65.7 |
- 2.13 |
- 1.71 |
- 1 |
- |
-
-
- | 30 |
- D2.13 |
- 042114.18 |
- DBA/2J |
- F |
- 03/19/13 |
- 04/21/14 |
- 13~15 |
- 398 |
- 13.3 |
- 1148 |
- Ret 25 |
- 26 |
- 9.9 |
- 65.53 |
- 2.17 |
- 2.43 |
- 1 |
- |
-
-
- | 31 |
- D2.14 |
- 042114.17 |
- DBA/2J |
- M |
- 03/19/13 |
- 04/21/14 |
- 13~15 |
- 398 |
- 13.3 |
- 1130 |
- Ret 24 |
- 40 |
- 9.4 |
- 36.98 |
- 2.07 |
- 0.8 |
- 1 |
- |
-
-
- | 32 |
- D2.15 |
- 041014.06 |
- DBA/2J |
- M |
- 9/6/2012 |
- 04/10/14 |
- 19~21 |
- 581 |
- 19.4 |
- 1123 |
- Ret 8 |
- 35 |
- 9.9 |
- 52.99 |
- 2.12 |
- 0.091 |
- 1 |
- |
-
-
- | 33 |
- D2.16 |
- 041014.07 |
- DBA/2J |
- F |
- 9/6/2012 |
- 04/10/14 |
- 19~21 |
- 581 |
- 19.4 |
- 1124 |
- Ret 9 |
- 30 |
- 9.5 |
- 52.44 |
- 2.19 |
- 0.08 |
- 1 |
- |
-
-
- | 34 |
- D2GP.01 |
- 041416.15 |
- DBA-Gpmnb(wp) |
- F |
- 03/15/16 |
- 04/14/16 |
- 1~2 |
- 30 |
- 1.0 |
- |
- R92 |
- 334 |
- 9.10 |
- 135.79 |
- 1.87 |
- 2.23 |
- 2 |
- |
-
-
- | 35 |
- D2GP.02 |
- 120715.02 |
- DBA-Gpmnb(wp) |
- M |
- 11/05/15 |
- 12/07/15 |
- 1~2 |
- 32 |
- 1.1 |
- |
- R31 |
- 85 |
- 9.20 |
- 106.06 |
- 2.04 |
- 2.06 |
- 2 |
- |
-
-
- | 36 |
- D2GP.03 |
- 041416.04 |
- DBA-Gpmnb(wp) |
- F |
- 02/02/16 |
- 04/14/16 |
- 2~4 |
- 72 |
- 2.4 |
- |
- R81 |
- 112 |
- 9.40 |
- 94.79 |
- 1.94 |
- 2.19 |
- 2 |
- |
-
-
- | 37 |
- D2GP.04 |
- 120815.04 |
- DBA-Gpmnb(wp) |
- M |
- 10/08/15 |
- 12/08/15 |
- 2~4 |
- 61 |
- 2.0 |
- |
- R39 |
- 89 |
- N/A |
- 118.84 |
- 2.05 |
- 1.97 |
- 2 |
- |
-
-
- | 38 |
- D2GP.05 |
- 101813.21 |
- DBA-Gpmnb(wp) |
- F |
- 04/09/13 |
- 10/18/13 |
- 5~7 |
- 192 |
- 6.4 |
- |
- Ret 4 |
- 53 |
- 9.9 |
- 74.13 |
- 2.14 |
- 2.28 |
- 1 |
- |
-
-
- | 39 |
- D2GP.06 |
- 101813.22 |
- DBA-Gpmnb(wp) |
- M |
- 04/09/13 |
- 10/18/13 |
- 5~7 |
- 192 |
- 6.4 |
- |
- Ret 5 |
- 54 |
- 10.0 |
- 81.32 |
- 2.1 |
- 2.19 |
- 1 |
- |
-
-
- | 40 |
- D2GP.07 |
- 041014.27 |
- DBA-Gpmnb(wp) |
- F |
- 08/29/13 |
- 04/10/14 |
- 7~9 |
- 224 |
- 7.5 |
- |
- Ret 15 |
- 14 |
- 10.0 |
- 37.03 |
- 2.06 |
- 1.44 |
- 1 |
- |
-
-
- | 41 |
- D2GP.08 |
- 041014.28 |
- DBA-Gpmnb(wp) |
- M |
- 08/29/13 |
- 04/10/14 |
- 7~9 |
- 224 |
- 7.5 |
- |
- Ret 16 |
- 29 |
- 9.9 |
- 63.83 |
- 2.03 |
- 2.08 |
- 1 |
- |
-
-
- | 42 |
- D2GP.09 |
- 041014.25 |
- DBA-Gpmnb(wp) |
- F |
- 06/12/13 |
- 04/10/14 |
- 10~12 |
- 302 |
- 10.1 |
- |
- Ret 13 |
- 31 |
- 9.8 |
- 60.73 |
- 2.07 |
- 2.12 |
- 1 |
- |
-
-
- | 43 |
- D2GP.10 |
- 041014.26 |
- DBA-Gpmnb(wp) |
- M |
- 06/12/13 |
- 04/10/14 |
- 10~12 |
- 302 |
- 10.1 |
- |
- Ret 14 |
- 24 |
- 10.0 |
- 65.1 |
- 2.06 |
- 1.09 |
- 1 |
- |
-
-
- | 44 |
- D2GP.11 |
- 042114.08 |
- DBA-Gpmnb(wp) |
- F |
- 01/14/13 |
- 04/21/14 |
- 13~15 |
- 462 |
- 15.4 |
- 1021 |
- Ret 22 |
- 87 |
- 9.0 |
- 150.69 |
- 2.09 |
- 2.02 |
- 1 |
- |
-
-
- | 45 |
- D2GP.12 |
- 042114.09 |
- DBA-Gpmnb(wp) |
- F |
- 01/14/13 |
- 04/21/14 |
- 13~15 |
- 462 |
- 15.4 |
- 1022 |
- Ret 23 |
- 18 |
- 10.0 |
- 44.16 |
- 2.11 |
- 0.069 |
- 1 |
- |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_mm10_B6D2_Ret_miRNA_1116/specifics.rtf b/general/datasets/UTHSC_mm10_B6D2_Ret_miRNA_1116/specifics.rtf
deleted file mode 100644
index 69b4147..0000000
--- a/general/datasets/UTHSC_mm10_B6D2_Ret_miRNA_1116/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-micro RNA
\ No newline at end of file
diff --git a/general/datasets/UTHSC_mm10_B6D2_Ret_miRNA_1116/summary.rtf b/general/datasets/UTHSC_mm10_B6D2_Ret_miRNA_1116/summary.rtf
deleted file mode 100644
index 1d95169..0000000
--- a/general/datasets/UTHSC_mm10_B6D2_Ret_miRNA_1116/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-This is a microRNA data set generated using the Affymetrix Genechip miRNA 4.0 array (see http://media.affymetrix.com/support/technical/datasheets/miRNA_4-0_and_4-1_datasheet.pdf).
-
-The data set provides 3222 estimates of expression (mainly for mi-RNAs) for 45 retinas from C57BL/6J (B6 cases B6.01 to B6.17), DBA/2J (cases D2.01 to D2.16), and DBA/2J with a wildtype Gpnmb allele (D2GP.01 to D2GP.12). Cases range in age from 30 to 576 days and include both sexes.
-
-We are using this data set in combination with the conventional Mouse Gene 1.0ST array to study normal and glaucomatous changes in gene expression as a function of age.
-
-Please contact Lu Lu (lulu@uthsc.edu), Robert W. Williams (rwilliams@uthsc.edu), or Junming Yue (jyue@uthsc.edu).
-
-Supported in part by Research to Prevent Blindness.
diff --git a/general/datasets/UTHSC_mm9_B6D2_RetEx_0916/cases.rtf b/general/datasets/UTHSC_mm9_B6D2_RetEx_0916/cases.rtf
deleted file mode 100644
index ad9776a..0000000
--- a/general/datasets/UTHSC_mm9_B6D2_RetEx_0916/cases.rtf
+++ /dev/null
@@ -1,980 +0,0 @@
-
-
-
-
-
-
-
-
- | Index |
- Sample ID |
- Case ID |
- Strain |
- Sex |
- DOB |
- Sac date |
- Age group |
- Age (days) |
- Age (month) |
- EarTag Number |
- Tube ID |
- Agilent RNA concentration (ng/ul) |
- RIN |
- Nanodrop RNA concentration (ng/ul) |
- 260/280 |
- 260/230 |
- Batch ID |
- Notes |
-
-
- | 1 |
- B6.01 |
- 071515.08 |
- C57BL/6J |
- M |
- 06/15/15 |
- 07/15/15 |
- 1~2 |
- 30 |
- 1.0 |
- |
- R11 |
- 173 |
- 10.00 |
- 181.22 |
- 2.09 |
- 2.12 |
- 2 |
- best |
-
-
- | 2 |
- B6.02 |
- 071515.09 |
- C57BL/6J |
- M |
- 06/15/15 |
- 07/15/15 |
- 1~2 |
- 30 |
- 1.0 |
- |
- R12 |
- 121 |
- N/A |
- 148.52 |
- 2.10 |
- 1.69 |
- 2 |
- best |
-
-
- | 3 |
- B6.03 |
- 052314.01 |
- C57BL/6J |
- F |
- 03/23/14 |
- 05/23/14 |
- 2~4 |
- 61 |
- 2.0 |
- |
- Ret 32 |
- 68 |
- 10.0 |
- 48.53 |
- 2.02 |
- 1.93 |
- 1 |
- |
-
-
- | 4 |
- B6.04 |
- 062514.01 |
- C57BL/6J |
- M |
- 04/10/14 |
- 06/25/14 |
- 2~4 |
- 76 |
- 2.5 |
- |
- Ret 21 |
- 81 |
- 9.0 |
- 168.7 |
- 2.06 |
- 1.97 |
- 1 |
- |
-
-
- | 5 |
- B6.05 |
- 040816.03 |
- C57BL/6J |
- M |
- 02/04/16 |
- 04/08/16 |
- 2~4 |
- 64 |
- 2.1 |
- |
- R74 |
- 385 |
- 10.00 |
- 448.16 |
- 1.98 |
- 2.12 |
- 2 |
- |
-
-
- | 6 |
- B6.06 |
- 040816.04 |
- C57BL/6J |
- M |
- 02/04/16 |
- 04/08/16 |
- 2~4 |
- 64 |
- 2.1 |
- |
- R75 |
- 226 |
- 8.70 |
- 167.31 |
- 2.04 |
- 2.13 |
- 2 |
- |
-
-
- | 7 |
- B6.07 |
- 041014.19 |
- C57BL/6J |
- F |
- 10/20/13 |
- 04/10/14 |
- 5~7 |
- 172 |
- 5.7 |
- |
- Ret 10 |
- 22 |
- 10.0 |
- 36.97 |
- 2.22 |
- 0.051 |
- 1 |
- |
-
-
- | 8 |
- B6.08 |
- 101813.27 |
- C57BL/6J |
- M |
- 05/06/13 |
- 10/18/13 |
- 5~7 |
- 165 |
- 5.5 |
- |
- Ret 7 |
- 38 |
- 10.0 |
- 54.47 |
- 2.08 |
- 0.094 |
- 1 |
- |
-
-
- | 9 |
- B6.09 |
- 050214.03 |
- C57BL/6J |
- F |
- 08/14/13 |
- 05/02/14 |
- 7~9 |
- 261 |
- 8.7 |
- |
- Ret 27 |
- 20 |
- 10.0 |
- 54.45 |
- 2.11 |
- 1.14 |
- 1 |
- |
-
-
- | 10 |
- B6.10 |
- 041014.24 |
- C57BL/6J |
- M |
- 09/02/13 |
- 04/10/14 |
- 7~9 |
- 220 |
- 7.3 |
- |
- Ret 12 |
- 38 |
- 9.50 |
- 58.97 |
- 2.08 |
- 2.14 |
- 1 |
- |
-
-
- | 11 |
- B6.11 |
- 101813.17 |
- C57BL/6J |
- F |
- 12/07/12 |
- 10/18/13 |
- 10~12 |
- 315 |
- 10.5 |
- |
- Ret 2 |
- 59 |
- 9.40 |
- 83.86 |
- 2.17 |
- 1.87 |
- 1 |
- |
-
-
- | 12 |
- B6.12 |
- 052116.01 |
- C57BL/6J |
- M |
- 05/19/15 |
- 05/22/16 |
- 10~12 |
- 369 |
- 12.3 |
- |
- R102 |
- 293 |
- 8.30 |
- 179.69 |
- 2.06 |
- 2.11 |
- 2 |
- |
-
-
- | 13 |
- B6.13 |
- 052116.02 |
- C57BL/6J |
- M |
- 05/19/15 |
- 05/22/16 |
- 10~12 |
- 369 |
- 12.3 |
- |
- R103 |
- 255 |
- 8.40 |
- 194.24 |
- 2.04 |
- 1.82 |
- 2 |
- |
-
-
- | 14 |
- B6.14 |
- 042114.19 |
- C57BL/6J |
- F |
- 03/11/13 |
- 04/21/14 |
- 13~15 |
- 406 |
- 13.5 |
- 1252 |
- Ret 26 |
- 28 |
- 10.0 |
- 39.95 |
- 2.22 |
- 1.71 |
- 1 |
- |
-
-
- | 15 |
- B6.15 |
- 050214.07 |
- C57BL/6J |
- M |
- 03/20/13 |
- 05/02/14 |
- 13~15 |
- 408 |
- 13.6 |
- |
- Ret 28 |
- 30 |
- 10.0 |
- 51.81 |
- 2.06 |
- 2.07 |
- 1 |
- |
-
-
- | 16 |
- B6.16 |
- 041714.02 |
- C57BL/6J |
- M |
- 09/18/12 |
- 04/17/14 |
- 19~21 |
- 576 |
- 19.2 |
- 1117 |
- Ret 17 |
- 25 |
- 10.0 |
- 51.55 |
- 2.13 |
- 1.13 |
- 1 |
- |
-
-
- | 17 |
- B6.17 |
- 041714.03 |
- C57BL/6J |
- M |
- 09/18/12 |
- 04/17/14 |
- 19~21 |
- 576 |
- 19.2 |
- 1116 |
- Ret 18 |
- 28 |
- 10.0 |
- 65.11 |
- 2.01 |
- 2.16 |
- 1 |
- |
-
-
- | 18 |
- D2.01 |
- 030116.02 |
- DBA/2J |
- M |
- 01/29/16 |
- 03/01/16 |
- 1~2 |
- 32 |
- 1.1 |
- |
- R63 |
- 107 |
- 8.80 |
- 119.02 |
- 2.05 |
- 1.79 |
- 2 |
- |
-
-
- | 19 |
- D2.02 |
- 030116.04 |
- DBA/2J |
- M |
- 01/29/16 |
- 03/01/16 |
- 1~2 |
- 32 |
- 1.1 |
- |
- R65 |
- 202 |
- 9.10 |
- 250.38 |
- 2.03 |
- 1.67 |
- 2 |
- |
-
-
- | 20 |
- D2.03 |
- 062714.02 |
- DBA/2J |
- F |
- 03/23/14 |
- 06/27/14 |
- 2~4 |
- 104 |
- 3.5 |
- |
- Ret 20a |
- |
- |
- 189.3 |
- 1.95 |
- 1.81 |
- 1 |
- No Agilent as of 6/27/2014 |
-
-
- | 21 |
- D2.04 |
- 062714.01 |
- DBA/2J |
- M |
- 03/19/14 |
- 06/27/14 |
- 2~4 |
- 100 |
- 3.3 |
- |
- Ret 19a |
- |
- |
- 154 |
- 2.05 |
- 1.89 |
- 1 |
- No Agilent as of 6/27/2014 |
-
-
- | 22 |
- D2.05 |
- 032316.03 |
- DBA/2J |
- M |
- 01/23/16 |
- 03/23/16 |
- 2~4 |
- 60 |
- 2.0 |
- |
- R70 |
- 99 |
- 9.30 |
- 99.17 |
- 2.04 |
- 1.63 |
- 2 |
- |
-
-
- | 23 |
- D2.06 |
- 032316.04 |
- DBA/2J |
- M |
- 01/23/16 |
- 03/23/16 |
- 2~4 |
- 60 |
- 2.0 |
- |
- R71 |
- 205 |
- 9.10 |
- 124.33 |
- 2.03 |
- 1.24 |
- 2 |
- |
-
-
- | 24 |
- D2.07 |
- 050214.11 |
- DBA/2J |
- F |
- 12/07/13 |
- 05/02/14 |
- 5~7 |
- 146 |
- 4.9 |
- |
- Ret 29 |
- 100 |
- 10.0 |
- 86.47 |
- 2.14 |
- 1.9 |
- 1 |
- |
-
-
- | 25 |
- D2.08 |
- 101813.08 |
- DBA/2J |
- M |
- 03/21/13 |
- 10/18/13 |
- 5~7 |
- 211 |
- 7.0 |
- |
- Ret 1 |
- 52 |
- 9.9 |
- 86.98 |
- 2.11 |
- 2.12 |
- 1 |
- |
-
-
- | 26 |
- D2.09 |
- 041014.23 |
- DBA/2J |
- F |
- 08/24/13 |
- 04/10/14 |
- 7~9 |
- 229 |
- 7.6 |
- |
- Ret 11 |
- 21 |
- 9.9 |
- 44.39 |
- 2.17 |
- 1.15 |
- 1 |
- |
-
-
- | 27 |
- D2.10 |
- 050214.15 |
- DBA/2J |
- F |
- 07/27/13 |
- 05/02/14 |
- 7~9 |
- 279 |
- 9.3 |
- |
- Ret 30 |
- 37 |
- 10.0 |
- 43.57 |
- 2.13 |
- 2.04 |
- 1 |
- |
-
-
- | 28 |
- D2.11 |
- 101813.23 |
- DBA/2J |
- F |
- 11/29/12 |
- 10/18/13 |
- 10~12 |
- 323 |
- 10.8 |
- |
- Ret 6 |
- 77 |
- 9.7 |
- 105.02 |
- 2.06 |
- 2.14 |
- 1 |
- |
-
-
- | 29 |
- D2.12 |
- 101813.19 |
- DBA/2J |
- M |
- 12/08/12 |
- 10/18/13 |
- 10~12 |
- 314 |
- 10.5 |
- |
- Ret 3 |
- 46 |
- 9.9 |
- 65.7 |
- 2.13 |
- 1.71 |
- 1 |
- |
-
-
- | 30 |
- D2.13 |
- 042114.18 |
- DBA/2J |
- F |
- 03/19/13 |
- 04/21/14 |
- 13~15 |
- 398 |
- 13.3 |
- 1148 |
- Ret 25 |
- 26 |
- 9.9 |
- 65.53 |
- 2.17 |
- 2.43 |
- 1 |
- |
-
-
- | 31 |
- D2.14 |
- 042114.17 |
- DBA/2J |
- M |
- 03/19/13 |
- 04/21/14 |
- 13~15 |
- 398 |
- 13.3 |
- 1130 |
- Ret 24 |
- 40 |
- 9.4 |
- 36.98 |
- 2.07 |
- 0.8 |
- 1 |
- |
-
-
- | 32 |
- D2.15 |
- 041014.06 |
- DBA/2J |
- M |
- 9/6/2012 |
- 04/10/14 |
- 19~21 |
- 581 |
- 19.4 |
- 1123 |
- Ret 8 |
- 35 |
- 9.9 |
- 52.99 |
- 2.12 |
- 0.091 |
- 1 |
- |
-
-
- | 33 |
- D2.16 |
- 041014.07 |
- DBA/2J |
- F |
- 9/6/2012 |
- 04/10/14 |
- 19~21 |
- 581 |
- 19.4 |
- 1124 |
- Ret 9 |
- 30 |
- 9.5 |
- 52.44 |
- 2.19 |
- 0.08 |
- 1 |
- |
-
-
- | 34 |
- D2GP.01 |
- 041416.15 |
- DBA-Gpmnb(wp) |
- F |
- 03/15/16 |
- 04/14/16 |
- 1~2 |
- 30 |
- 1.0 |
- |
- R92 |
- 334 |
- 9.10 |
- 135.79 |
- 1.87 |
- 2.23 |
- 2 |
- |
-
-
- | 35 |
- D2GP.02 |
- 120715.02 |
- DBA-Gpmnb(wp) |
- M |
- 11/05/15 |
- 12/07/15 |
- 1~2 |
- 32 |
- 1.1 |
- |
- R31 |
- 85 |
- 9.20 |
- 106.06 |
- 2.04 |
- 2.06 |
- 2 |
- |
-
-
- | 36 |
- D2GP.03 |
- 041416.04 |
- DBA-Gpmnb(wp) |
- F |
- 02/02/16 |
- 04/14/16 |
- 2~4 |
- 72 |
- 2.4 |
- |
- R81 |
- 112 |
- 9.40 |
- 94.79 |
- 1.94 |
- 2.19 |
- 2 |
- |
-
-
- | 37 |
- D2GP.04 |
- 120815.04 |
- DBA-Gpmnb(wp) |
- M |
- 10/08/15 |
- 12/08/15 |
- 2~4 |
- 61 |
- 2.0 |
- |
- R39 |
- 89 |
- N/A |
- 118.84 |
- 2.05 |
- 1.97 |
- 2 |
- |
-
-
- | 38 |
- D2GP.05 |
- 101813.21 |
- DBA-Gpmnb(wp) |
- F |
- 04/09/13 |
- 10/18/13 |
- 5~7 |
- 192 |
- 6.4 |
- |
- Ret 4 |
- 53 |
- 9.9 |
- 74.13 |
- 2.14 |
- 2.28 |
- 1 |
- |
-
-
- | 39 |
- D2GP.06 |
- 101813.22 |
- DBA-Gpmnb(wp) |
- M |
- 04/09/13 |
- 10/18/13 |
- 5~7 |
- 192 |
- 6.4 |
- |
- Ret 5 |
- 54 |
- 10.0 |
- 81.32 |
- 2.1 |
- 2.19 |
- 1 |
- |
-
-
- | 40 |
- D2GP.07 |
- 041014.27 |
- DBA-Gpmnb(wp) |
- F |
- 08/29/13 |
- 04/10/14 |
- 7~9 |
- 224 |
- 7.5 |
- |
- Ret 15 |
- 14 |
- 10.0 |
- 37.03 |
- 2.06 |
- 1.44 |
- 1 |
- |
-
-
- | 41 |
- D2GP.08 |
- 041014.28 |
- DBA-Gpmnb(wp) |
- M |
- 08/29/13 |
- 04/10/14 |
- 7~9 |
- 224 |
- 7.5 |
- |
- Ret 16 |
- 29 |
- 9.9 |
- 63.83 |
- 2.03 |
- 2.08 |
- 1 |
- |
-
-
- | 42 |
- D2GP.09 |
- 041014.25 |
- DBA-Gpmnb(wp) |
- F |
- 06/12/13 |
- 04/10/14 |
- 10~12 |
- 302 |
- 10.1 |
- |
- Ret 13 |
- 31 |
- 9.8 |
- 60.73 |
- 2.07 |
- 2.12 |
- 1 |
- |
-
-
- | 43 |
- D2GP.10 |
- 041014.26 |
- DBA-Gpmnb(wp) |
- M |
- 06/12/13 |
- 04/10/14 |
- 10~12 |
- 302 |
- 10.1 |
- |
- Ret 14 |
- 24 |
- 10.0 |
- 65.1 |
- 2.06 |
- 1.09 |
- 1 |
- |
-
-
- | 44 |
- D2GP.11 |
- 042114.08 |
- DBA-Gpmnb(wp) |
- F |
- 01/14/13 |
- 04/21/14 |
- 13~15 |
- 462 |
- 15.4 |
- 1021 |
- Ret 22 |
- 87 |
- 9.0 |
- 150.69 |
- 2.09 |
- 2.02 |
- 1 |
- |
-
-
- | 45 |
- D2GP.12 |
- 042114.09 |
- DBA-Gpmnb(wp) |
- F |
- 01/14/13 |
- 04/21/14 |
- 13~15 |
- 462 |
- 15.4 |
- 1022 |
- Ret 23 |
- 18 |
- 10.0 |
- 44.16 |
- 2.11 |
- 0.069 |
- 1 |
- |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_mm9_B6D2_RetEx_0916/specifics.rtf b/general/datasets/UTHSC_mm9_B6D2_RetEx_0916/specifics.rtf
deleted file mode 100644
index 7c1a914..0000000
--- a/general/datasets/UTHSC_mm9_B6D2_RetEx_0916/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Exon Level
\ No newline at end of file
diff --git a/general/datasets/UTHSC_mm9_B6D2_RetEx_0916/summary.rtf b/general/datasets/UTHSC_mm9_B6D2_RetEx_0916/summary.rtf
deleted file mode 100644
index de58298..0000000
--- a/general/datasets/UTHSC_mm9_B6D2_RetEx_0916/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-This is an array data set generated using the Affymetrix Genechip Mouse 1.0 ST array. Please see the companion microRNA (miRNA) data set.
-
-All of these data sets provides estimates of expression for 45 retinas from C57BL/6J (B6 cases B6.01 to B6.17), DBA/2J (cases D2.01 to D2.16), and DBA/2J with a wildtype Gpnmb allele (D2GP.01 to D2GP.12). Cases range in age from 30 to 576 days and include both sexes.
-
-We are using these data in combination with the micro RNA array 4.0 to study normal and glaucomatous changes in gene expression as a function of age.
-
-Please contact Lu Lu (lulu@uthsc.edu), Robert W. Williams (rwilliams@uthsc.edu), or Junming Yue (jyue@uthsc.edu).
-
-Supported in part by Research to Prevent Blindness.
diff --git a/general/datasets/UTHSC_mm9_B6D2_Ret_0916/cases.rtf b/general/datasets/UTHSC_mm9_B6D2_Ret_0916/cases.rtf
deleted file mode 100644
index ad9776a..0000000
--- a/general/datasets/UTHSC_mm9_B6D2_Ret_0916/cases.rtf
+++ /dev/null
@@ -1,980 +0,0 @@
-
-
-
-
-
-
-
-
- | Index |
- Sample ID |
- Case ID |
- Strain |
- Sex |
- DOB |
- Sac date |
- Age group |
- Age (days) |
- Age (month) |
- EarTag Number |
- Tube ID |
- Agilent RNA concentration (ng/ul) |
- RIN |
- Nanodrop RNA concentration (ng/ul) |
- 260/280 |
- 260/230 |
- Batch ID |
- Notes |
-
-
- | 1 |
- B6.01 |
- 071515.08 |
- C57BL/6J |
- M |
- 06/15/15 |
- 07/15/15 |
- 1~2 |
- 30 |
- 1.0 |
- |
- R11 |
- 173 |
- 10.00 |
- 181.22 |
- 2.09 |
- 2.12 |
- 2 |
- best |
-
-
- | 2 |
- B6.02 |
- 071515.09 |
- C57BL/6J |
- M |
- 06/15/15 |
- 07/15/15 |
- 1~2 |
- 30 |
- 1.0 |
- |
- R12 |
- 121 |
- N/A |
- 148.52 |
- 2.10 |
- 1.69 |
- 2 |
- best |
-
-
- | 3 |
- B6.03 |
- 052314.01 |
- C57BL/6J |
- F |
- 03/23/14 |
- 05/23/14 |
- 2~4 |
- 61 |
- 2.0 |
- |
- Ret 32 |
- 68 |
- 10.0 |
- 48.53 |
- 2.02 |
- 1.93 |
- 1 |
- |
-
-
- | 4 |
- B6.04 |
- 062514.01 |
- C57BL/6J |
- M |
- 04/10/14 |
- 06/25/14 |
- 2~4 |
- 76 |
- 2.5 |
- |
- Ret 21 |
- 81 |
- 9.0 |
- 168.7 |
- 2.06 |
- 1.97 |
- 1 |
- |
-
-
- | 5 |
- B6.05 |
- 040816.03 |
- C57BL/6J |
- M |
- 02/04/16 |
- 04/08/16 |
- 2~4 |
- 64 |
- 2.1 |
- |
- R74 |
- 385 |
- 10.00 |
- 448.16 |
- 1.98 |
- 2.12 |
- 2 |
- |
-
-
- | 6 |
- B6.06 |
- 040816.04 |
- C57BL/6J |
- M |
- 02/04/16 |
- 04/08/16 |
- 2~4 |
- 64 |
- 2.1 |
- |
- R75 |
- 226 |
- 8.70 |
- 167.31 |
- 2.04 |
- 2.13 |
- 2 |
- |
-
-
- | 7 |
- B6.07 |
- 041014.19 |
- C57BL/6J |
- F |
- 10/20/13 |
- 04/10/14 |
- 5~7 |
- 172 |
- 5.7 |
- |
- Ret 10 |
- 22 |
- 10.0 |
- 36.97 |
- 2.22 |
- 0.051 |
- 1 |
- |
-
-
- | 8 |
- B6.08 |
- 101813.27 |
- C57BL/6J |
- M |
- 05/06/13 |
- 10/18/13 |
- 5~7 |
- 165 |
- 5.5 |
- |
- Ret 7 |
- 38 |
- 10.0 |
- 54.47 |
- 2.08 |
- 0.094 |
- 1 |
- |
-
-
- | 9 |
- B6.09 |
- 050214.03 |
- C57BL/6J |
- F |
- 08/14/13 |
- 05/02/14 |
- 7~9 |
- 261 |
- 8.7 |
- |
- Ret 27 |
- 20 |
- 10.0 |
- 54.45 |
- 2.11 |
- 1.14 |
- 1 |
- |
-
-
- | 10 |
- B6.10 |
- 041014.24 |
- C57BL/6J |
- M |
- 09/02/13 |
- 04/10/14 |
- 7~9 |
- 220 |
- 7.3 |
- |
- Ret 12 |
- 38 |
- 9.50 |
- 58.97 |
- 2.08 |
- 2.14 |
- 1 |
- |
-
-
- | 11 |
- B6.11 |
- 101813.17 |
- C57BL/6J |
- F |
- 12/07/12 |
- 10/18/13 |
- 10~12 |
- 315 |
- 10.5 |
- |
- Ret 2 |
- 59 |
- 9.40 |
- 83.86 |
- 2.17 |
- 1.87 |
- 1 |
- |
-
-
- | 12 |
- B6.12 |
- 052116.01 |
- C57BL/6J |
- M |
- 05/19/15 |
- 05/22/16 |
- 10~12 |
- 369 |
- 12.3 |
- |
- R102 |
- 293 |
- 8.30 |
- 179.69 |
- 2.06 |
- 2.11 |
- 2 |
- |
-
-
- | 13 |
- B6.13 |
- 052116.02 |
- C57BL/6J |
- M |
- 05/19/15 |
- 05/22/16 |
- 10~12 |
- 369 |
- 12.3 |
- |
- R103 |
- 255 |
- 8.40 |
- 194.24 |
- 2.04 |
- 1.82 |
- 2 |
- |
-
-
- | 14 |
- B6.14 |
- 042114.19 |
- C57BL/6J |
- F |
- 03/11/13 |
- 04/21/14 |
- 13~15 |
- 406 |
- 13.5 |
- 1252 |
- Ret 26 |
- 28 |
- 10.0 |
- 39.95 |
- 2.22 |
- 1.71 |
- 1 |
- |
-
-
- | 15 |
- B6.15 |
- 050214.07 |
- C57BL/6J |
- M |
- 03/20/13 |
- 05/02/14 |
- 13~15 |
- 408 |
- 13.6 |
- |
- Ret 28 |
- 30 |
- 10.0 |
- 51.81 |
- 2.06 |
- 2.07 |
- 1 |
- |
-
-
- | 16 |
- B6.16 |
- 041714.02 |
- C57BL/6J |
- M |
- 09/18/12 |
- 04/17/14 |
- 19~21 |
- 576 |
- 19.2 |
- 1117 |
- Ret 17 |
- 25 |
- 10.0 |
- 51.55 |
- 2.13 |
- 1.13 |
- 1 |
- |
-
-
- | 17 |
- B6.17 |
- 041714.03 |
- C57BL/6J |
- M |
- 09/18/12 |
- 04/17/14 |
- 19~21 |
- 576 |
- 19.2 |
- 1116 |
- Ret 18 |
- 28 |
- 10.0 |
- 65.11 |
- 2.01 |
- 2.16 |
- 1 |
- |
-
-
- | 18 |
- D2.01 |
- 030116.02 |
- DBA/2J |
- M |
- 01/29/16 |
- 03/01/16 |
- 1~2 |
- 32 |
- 1.1 |
- |
- R63 |
- 107 |
- 8.80 |
- 119.02 |
- 2.05 |
- 1.79 |
- 2 |
- |
-
-
- | 19 |
- D2.02 |
- 030116.04 |
- DBA/2J |
- M |
- 01/29/16 |
- 03/01/16 |
- 1~2 |
- 32 |
- 1.1 |
- |
- R65 |
- 202 |
- 9.10 |
- 250.38 |
- 2.03 |
- 1.67 |
- 2 |
- |
-
-
- | 20 |
- D2.03 |
- 062714.02 |
- DBA/2J |
- F |
- 03/23/14 |
- 06/27/14 |
- 2~4 |
- 104 |
- 3.5 |
- |
- Ret 20a |
- |
- |
- 189.3 |
- 1.95 |
- 1.81 |
- 1 |
- No Agilent as of 6/27/2014 |
-
-
- | 21 |
- D2.04 |
- 062714.01 |
- DBA/2J |
- M |
- 03/19/14 |
- 06/27/14 |
- 2~4 |
- 100 |
- 3.3 |
- |
- Ret 19a |
- |
- |
- 154 |
- 2.05 |
- 1.89 |
- 1 |
- No Agilent as of 6/27/2014 |
-
-
- | 22 |
- D2.05 |
- 032316.03 |
- DBA/2J |
- M |
- 01/23/16 |
- 03/23/16 |
- 2~4 |
- 60 |
- 2.0 |
- |
- R70 |
- 99 |
- 9.30 |
- 99.17 |
- 2.04 |
- 1.63 |
- 2 |
- |
-
-
- | 23 |
- D2.06 |
- 032316.04 |
- DBA/2J |
- M |
- 01/23/16 |
- 03/23/16 |
- 2~4 |
- 60 |
- 2.0 |
- |
- R71 |
- 205 |
- 9.10 |
- 124.33 |
- 2.03 |
- 1.24 |
- 2 |
- |
-
-
- | 24 |
- D2.07 |
- 050214.11 |
- DBA/2J |
- F |
- 12/07/13 |
- 05/02/14 |
- 5~7 |
- 146 |
- 4.9 |
- |
- Ret 29 |
- 100 |
- 10.0 |
- 86.47 |
- 2.14 |
- 1.9 |
- 1 |
- |
-
-
- | 25 |
- D2.08 |
- 101813.08 |
- DBA/2J |
- M |
- 03/21/13 |
- 10/18/13 |
- 5~7 |
- 211 |
- 7.0 |
- |
- Ret 1 |
- 52 |
- 9.9 |
- 86.98 |
- 2.11 |
- 2.12 |
- 1 |
- |
-
-
- | 26 |
- D2.09 |
- 041014.23 |
- DBA/2J |
- F |
- 08/24/13 |
- 04/10/14 |
- 7~9 |
- 229 |
- 7.6 |
- |
- Ret 11 |
- 21 |
- 9.9 |
- 44.39 |
- 2.17 |
- 1.15 |
- 1 |
- |
-
-
- | 27 |
- D2.10 |
- 050214.15 |
- DBA/2J |
- F |
- 07/27/13 |
- 05/02/14 |
- 7~9 |
- 279 |
- 9.3 |
- |
- Ret 30 |
- 37 |
- 10.0 |
- 43.57 |
- 2.13 |
- 2.04 |
- 1 |
- |
-
-
- | 28 |
- D2.11 |
- 101813.23 |
- DBA/2J |
- F |
- 11/29/12 |
- 10/18/13 |
- 10~12 |
- 323 |
- 10.8 |
- |
- Ret 6 |
- 77 |
- 9.7 |
- 105.02 |
- 2.06 |
- 2.14 |
- 1 |
- |
-
-
- | 29 |
- D2.12 |
- 101813.19 |
- DBA/2J |
- M |
- 12/08/12 |
- 10/18/13 |
- 10~12 |
- 314 |
- 10.5 |
- |
- Ret 3 |
- 46 |
- 9.9 |
- 65.7 |
- 2.13 |
- 1.71 |
- 1 |
- |
-
-
- | 30 |
- D2.13 |
- 042114.18 |
- DBA/2J |
- F |
- 03/19/13 |
- 04/21/14 |
- 13~15 |
- 398 |
- 13.3 |
- 1148 |
- Ret 25 |
- 26 |
- 9.9 |
- 65.53 |
- 2.17 |
- 2.43 |
- 1 |
- |
-
-
- | 31 |
- D2.14 |
- 042114.17 |
- DBA/2J |
- M |
- 03/19/13 |
- 04/21/14 |
- 13~15 |
- 398 |
- 13.3 |
- 1130 |
- Ret 24 |
- 40 |
- 9.4 |
- 36.98 |
- 2.07 |
- 0.8 |
- 1 |
- |
-
-
- | 32 |
- D2.15 |
- 041014.06 |
- DBA/2J |
- M |
- 9/6/2012 |
- 04/10/14 |
- 19~21 |
- 581 |
- 19.4 |
- 1123 |
- Ret 8 |
- 35 |
- 9.9 |
- 52.99 |
- 2.12 |
- 0.091 |
- 1 |
- |
-
-
- | 33 |
- D2.16 |
- 041014.07 |
- DBA/2J |
- F |
- 9/6/2012 |
- 04/10/14 |
- 19~21 |
- 581 |
- 19.4 |
- 1124 |
- Ret 9 |
- 30 |
- 9.5 |
- 52.44 |
- 2.19 |
- 0.08 |
- 1 |
- |
-
-
- | 34 |
- D2GP.01 |
- 041416.15 |
- DBA-Gpmnb(wp) |
- F |
- 03/15/16 |
- 04/14/16 |
- 1~2 |
- 30 |
- 1.0 |
- |
- R92 |
- 334 |
- 9.10 |
- 135.79 |
- 1.87 |
- 2.23 |
- 2 |
- |
-
-
- | 35 |
- D2GP.02 |
- 120715.02 |
- DBA-Gpmnb(wp) |
- M |
- 11/05/15 |
- 12/07/15 |
- 1~2 |
- 32 |
- 1.1 |
- |
- R31 |
- 85 |
- 9.20 |
- 106.06 |
- 2.04 |
- 2.06 |
- 2 |
- |
-
-
- | 36 |
- D2GP.03 |
- 041416.04 |
- DBA-Gpmnb(wp) |
- F |
- 02/02/16 |
- 04/14/16 |
- 2~4 |
- 72 |
- 2.4 |
- |
- R81 |
- 112 |
- 9.40 |
- 94.79 |
- 1.94 |
- 2.19 |
- 2 |
- |
-
-
- | 37 |
- D2GP.04 |
- 120815.04 |
- DBA-Gpmnb(wp) |
- M |
- 10/08/15 |
- 12/08/15 |
- 2~4 |
- 61 |
- 2.0 |
- |
- R39 |
- 89 |
- N/A |
- 118.84 |
- 2.05 |
- 1.97 |
- 2 |
- |
-
-
- | 38 |
- D2GP.05 |
- 101813.21 |
- DBA-Gpmnb(wp) |
- F |
- 04/09/13 |
- 10/18/13 |
- 5~7 |
- 192 |
- 6.4 |
- |
- Ret 4 |
- 53 |
- 9.9 |
- 74.13 |
- 2.14 |
- 2.28 |
- 1 |
- |
-
-
- | 39 |
- D2GP.06 |
- 101813.22 |
- DBA-Gpmnb(wp) |
- M |
- 04/09/13 |
- 10/18/13 |
- 5~7 |
- 192 |
- 6.4 |
- |
- Ret 5 |
- 54 |
- 10.0 |
- 81.32 |
- 2.1 |
- 2.19 |
- 1 |
- |
-
-
- | 40 |
- D2GP.07 |
- 041014.27 |
- DBA-Gpmnb(wp) |
- F |
- 08/29/13 |
- 04/10/14 |
- 7~9 |
- 224 |
- 7.5 |
- |
- Ret 15 |
- 14 |
- 10.0 |
- 37.03 |
- 2.06 |
- 1.44 |
- 1 |
- |
-
-
- | 41 |
- D2GP.08 |
- 041014.28 |
- DBA-Gpmnb(wp) |
- M |
- 08/29/13 |
- 04/10/14 |
- 7~9 |
- 224 |
- 7.5 |
- |
- Ret 16 |
- 29 |
- 9.9 |
- 63.83 |
- 2.03 |
- 2.08 |
- 1 |
- |
-
-
- | 42 |
- D2GP.09 |
- 041014.25 |
- DBA-Gpmnb(wp) |
- F |
- 06/12/13 |
- 04/10/14 |
- 10~12 |
- 302 |
- 10.1 |
- |
- Ret 13 |
- 31 |
- 9.8 |
- 60.73 |
- 2.07 |
- 2.12 |
- 1 |
- |
-
-
- | 43 |
- D2GP.10 |
- 041014.26 |
- DBA-Gpmnb(wp) |
- M |
- 06/12/13 |
- 04/10/14 |
- 10~12 |
- 302 |
- 10.1 |
- |
- Ret 14 |
- 24 |
- 10.0 |
- 65.1 |
- 2.06 |
- 1.09 |
- 1 |
- |
-
-
- | 44 |
- D2GP.11 |
- 042114.08 |
- DBA-Gpmnb(wp) |
- F |
- 01/14/13 |
- 04/21/14 |
- 13~15 |
- 462 |
- 15.4 |
- 1021 |
- Ret 22 |
- 87 |
- 9.0 |
- 150.69 |
- 2.09 |
- 2.02 |
- 1 |
- |
-
-
- | 45 |
- D2GP.12 |
- 042114.09 |
- DBA-Gpmnb(wp) |
- F |
- 01/14/13 |
- 04/21/14 |
- 13~15 |
- 462 |
- 15.4 |
- 1022 |
- Ret 23 |
- 18 |
- 10.0 |
- 44.16 |
- 2.11 |
- 0.069 |
- 1 |
- |
-
-
-
- |
-
-
-
-
diff --git a/general/datasets/UTHSC_mm9_B6D2_Ret_0916/summary.rtf b/general/datasets/UTHSC_mm9_B6D2_Ret_0916/summary.rtf
deleted file mode 100644
index de58298..0000000
--- a/general/datasets/UTHSC_mm9_B6D2_Ret_0916/summary.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-This is an array data set generated using the Affymetrix Genechip Mouse 1.0 ST array. Please see the companion microRNA (miRNA) data set.
-
-All of these data sets provides estimates of expression for 45 retinas from C57BL/6J (B6 cases B6.01 to B6.17), DBA/2J (cases D2.01 to D2.16), and DBA/2J with a wildtype Gpnmb allele (D2GP.01 to D2GP.12). Cases range in age from 30 to 576 days and include both sexes.
-
-We are using these data in combination with the micro RNA array 4.0 to study normal and glaucomatous changes in gene expression as a function of age.
-
-Please contact Lu Lu (lulu@uthsc.edu), Robert W. Williams (rwilliams@uthsc.edu), or Junming Yue (jyue@uthsc.edu).
-
-Supported in part by Research to Prevent Blindness.
diff --git a/general/datasets/UT_ILM_BXD_hipp_NOE_1112/notes.rtf b/general/datasets/UT_ILM_BXD_hipp_NOE_1112/notes.rtf
deleted file mode 100644
index 35247b6..0000000
--- a/general/datasets/UT_ILM_BXD_hipp_NOE_1112/notes.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Hippocampus 5 Conditions
-Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
-Batch and Outlier Analysis on Partek Genomic Suite 6.6
-ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
-K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
-Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
-Number of samples = 284
-Number of probes = 46643
-
-
- - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
- - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
- - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
- - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
- ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
- - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
- ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
- - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
-
diff --git a/general/datasets/UT_ILM_BXD_hipp_NOE_1112/summary.rtf b/general/datasets/UT_ILM_BXD_hipp_NOE_1112/summary.rtf
deleted file mode 100644
index 5aeb69c..0000000
--- a/general/datasets/UT_ILM_BXD_hipp_NOE_1112/summary.rtf
+++ /dev/null
@@ -1,39 +0,0 @@
-This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
-
-For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
-
-Restraint Stress Protocol
-
-
- - Weigh animals all animals to be tested and record body weight.
- - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
- - Place animals in immobilization tubes for 15 minutes.
- - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
- - Place each animal into zero-maze for 10 minutes.
- - Return animal to home cage.
- - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
-
-
-Ethanol and saline injections
-Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
-
-"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
-
-Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
-
-Quality Control Data
-Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
-
-
- - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
- - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
- - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
- - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
- - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
-
-
-Entered by Arthur Centeno, September 20, 2010.
-
-Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
-
-Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/UT_ILM_BXD_hipp_RSS_1112/notes.rtf b/general/datasets/UT_ILM_BXD_hipp_RSS_1112/notes.rtf
deleted file mode 100644
index 35247b6..0000000
--- a/general/datasets/UT_ILM_BXD_hipp_RSS_1112/notes.rtf
+++ /dev/null
@@ -1,23 +0,0 @@
-Hippocampus 5 Conditions
-Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
-Batch and Outlier Analysis on Partek Genomic Suite 6.6
-ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
-K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
-Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
-Number of samples = 284
-Number of probes = 46643
-
-
- - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
- - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
- - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
- ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
- - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
- ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
- - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
- ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
- - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
- ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
-
diff --git a/general/datasets/UT_ILM_BXD_hipp_RSS_1112/summary.rtf b/general/datasets/UT_ILM_BXD_hipp_RSS_1112/summary.rtf
deleted file mode 100644
index 5aeb69c..0000000
--- a/general/datasets/UT_ILM_BXD_hipp_RSS_1112/summary.rtf
+++ /dev/null
@@ -1,39 +0,0 @@
-This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
-
-For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
-
-Restraint Stress Protocol
-
-
- - Weigh animals all animals to be tested and record body weight.
- - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
- - Place animals in immobilization tubes for 15 minutes.
- - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
- - Place each animal into zero-maze for 10 minutes.
- - Return animal to home cage.
- - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
-
-
-Ethanol and saline injections
-Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
-
-"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
-
-Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
-
-Quality Control Data
-Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
-
-
- - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
- - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
- - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
- - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
- - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
-
-
-Entered by Arthur Centeno, September 20, 2010.
-
-Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
-
-Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/UT_VGX_HEL1014/acknowledgment.rtf b/general/datasets/UT_VGX_HEL1014/acknowledgment.rtf
deleted file mode 100644
index 1853348..0000000
--- a/general/datasets/UT_VGX_HEL1014/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We thank Varigenix and Charle River Laboratory for their donation of BXD cyropreserved hepatcytes. We thank Jesse Ingels for preparing RNA samples. We thank Lorne Rose and the UTHSC Molecular Resource Center for processing RNA samples and generating array data. We thank Arthur Centeno for data entry. We thank the UTHSC CITG and the UT-ORNL Governor's chair for support of microarray analysis.
diff --git a/general/datasets/UT_VGX_HEL1014/cases.rtf b/general/datasets/UT_VGX_HEL1014/cases.rtf
deleted file mode 100644
index e06c56f..0000000
--- a/general/datasets/UT_VGX_HEL1014/cases.rtf
+++ /dev/null
@@ -1,266 +0,0 @@
-
-
-
- | Sample ID |
- Varigenix Strain |
- Sex |
- RNA Concentrations
- ng/ul |
- 260/280 |
- 260/230 |
- Agilent
- Concentration(ng/ul) |
- RIN |
-
-
- | V1 |
- BXD32 |
- M |
- 1414.8 |
- 2.09 |
- 2.21 |
- 3,062 |
- 9.3 |
-
-
- | V2 |
- BXD1 |
- M |
- 1608.9 |
- 2.11 |
- 2.24 |
- 3,102 |
- 9.3 |
-
-
- | V3 |
- BXD5 |
- M |
- 1263.91 |
- 2.1 |
- 2.09 |
- 2,460 |
- 8.5 |
-
-
- | V4 |
- BXD31 |
- M |
- 1793.95 |
- 2.1 |
- 2.22 |
- 3,387 |
- 8.5 |
-
-
- | V5 |
- BXD8 |
- M |
- 1193.21 |
- 2.1 |
- 2.17 |
- 2,293 |
- 9.3 |
-
-
- | V6 |
- BXD18 |
- M |
- 1041.05 |
- 2.13 |
- 2.17 |
- 2,115 |
- 9.2 |
-
-
- | V7 |
- BXD42 |
- M |
- 398.28 |
- 1.99 |
- 2.28 |
- 1,519 |
- 8.3 |
-
-
- | V8 |
- BXD29 |
- M |
- 477.37 |
- 2.02 |
- 2.24 |
- 1,301 |
- 8.1 |
-
-
- | V9 |
- BXD21 |
- M |
- 414.6 |
- 2 |
- 2.27 |
- 1,174 |
- 8.3 |
-
-
- | V10 |
- BXD27 |
- M |
- 438.61 |
- 2.02 |
- 2.27 |
- 1,100 |
- 8.1 |
-
-
- | V11 |
- BXD16 |
- M |
- 436.21 |
- 2.01 |
- 2.27 |
- 868 |
- 8.5 |
-
-
- | V12 |
- BXD19 |
- M |
- 489.12 |
- 2.01 |
- 2.26 |
- 1,277 |
- 8 |
-
-
- | V13 |
- BXD22 |
- M |
- 1032.89 |
- 2.09 |
- 2.22 |
- 2,060 |
- 7.8 |
-
-
- | V14 |
- BXD38 |
- M |
- 510.24 |
- 2.01 |
- 2.22 |
- 1,213 |
- 8 |
-
-
- | V15 |
- BXD34 |
- M |
- 1021.26 |
- 2.09 |
- 2.24 |
- 1,514 |
- 8.2 |
-
-
- | V16 |
- BXD20 |
- M |
- 330.85 |
- 2 |
- 2.27 |
- 901 |
- 8.1 |
-
-
- | V17 |
- BXD15 |
- M |
- 1220.54 |
- 2.1 |
- 2.21 |
- 1,909 |
- 8.1 |
-
-
- | V18 |
- BXD6 |
- M |
- 1001.04 |
- 2.09 |
- 2.2 |
- 1,523 |
- 8.3 |
-
-
- | V19 |
- BXD13 |
- M |
- 1241.88 |
- 2.1 |
- 2.21 |
- 1,770 |
- 8.2 |
-
-
- | V20 |
- BXD40 |
- M |
- 1032.04 |
- 2.08 |
- 2.22 |
- 1,985 |
- 8.2 |
-
-
- | V21 |
- BXD14 |
- M |
- 881.62 |
- 2.11 |
- 2.19 |
- 481 |
- 8.7 |
-
-
- | V22 |
- BXD2 |
- M |
- 1069.09 |
- 2.08 |
- 2.22 |
- 1,536 |
- 8.2 |
-
-
- | V23 |
- BXD28 |
- M |
- 452.6 |
- 2 |
- 2.26 |
- 2,567 |
- 7.9 |
-
-
- | V24 |
- BXD11 |
- M |
- 930.72 |
- 2.07 |
- 2.21 |
- 999 |
- 8.5 |
-
-
- | V25 |
- BXD39 |
- M |
- 1177.27 |
- 2.07 |
- 2.23 |
- 838 |
- 8.7 |
-
-
-
diff --git a/general/datasets/UT_VGX_HEL1014/experiment-design.rtf b/general/datasets/UT_VGX_HEL1014/experiment-design.rtf
deleted file mode 100644
index 323648a..0000000
--- a/general/datasets/UT_VGX_HEL1014/experiment-design.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Control hepatocyte mRNA expression data prior to any treatment for young adult male BXD strains. This is esssentially the mRNA state of frozen hepatocytes.
-
-
diff --git a/general/datasets/UT_VGX_HEL1014/platform.rtf b/general/datasets/UT_VGX_HEL1014/platform.rtf
deleted file mode 100644
index 61c48c5..0000000
--- a/general/datasets/UT_VGX_HEL1014/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Affy Mouse Gene 1.0 ST (GPL6246)
diff --git a/general/datasets/UT_VGX_HEL1014/processing.rtf b/general/datasets/UT_VGX_HEL1014/processing.rtf
deleted file mode 100644
index 662571f..0000000
--- a/general/datasets/UT_VGX_HEL1014/processing.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Standard 2z+8 of log2 data. RMA data were log2 transformed (adding an olffset of 1 to avoid negative values). Variance was stablized (i.e. each array was converted to a set of Z scores). Z scores were then multipled by 2. Mean Z was then shifted from 0 to to 8 units per array.
diff --git a/general/datasets/UT_VGX_HEL1014/summary.rtf b/general/datasets/UT_VGX_HEL1014/summary.rtf
deleted file mode 100644
index 8e4cabf..0000000
--- a/general/datasets/UT_VGX_HEL1014/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-mRNA levels in cryopreserved BXD strain hepatotcytes (males at 60 days of age) immediately after thawing to 4 deg C. This is the "frozen state" mRNA status.
diff --git a/general/datasets/UT_VGX_HEL1014/tissue.rtf b/general/datasets/UT_VGX_HEL1014/tissue.rtf
deleted file mode 100644
index 94ad98a..0000000
--- a/general/datasets/UT_VGX_HEL1014/tissue.rtf
+++ /dev/null
@@ -1,9 +0,0 @@
-
-
-Hepatocytes prepared by Rob Kaiser at CRL Piedmont in Spring of 2011. Held in liquid nitrogen (vapor phase) until use Fall 2014 at UTHSC.
-
-One vial of hepatocytes in 1 ml of freeze media was wiped with 70% ETOH, quick thawed by swift agitation in a 37 degree C water bath until a small amount of ice remained in the vial. Contents of the vial were removed with a sterile 1000 ul pipette tip and added to a 5 ml sterile polypropylene tube on ice containing 3 ml of ice-cold sterile 1x PBS. sitting in ice. One ml of sterile ice-cold 1x PBS was added to the original vial to remove any remaining cells and added to the 5 ml tube on ice. This process was quickly repeated with three more vials of cells. Four 5 ml tubes were centrifuged at 8,000 rpm at 4 degrees C for 4 minutes to pellet hepatocytes. PBS diluted freeze media was completely removed from the cell pellet. Entire process for sets of vials took about 7 minutes until RNA lysis buffer was added.
-
-The QIAgen AllPrep DNA/RNA mini kit was used in conjunction with the QIAcube for purification of DNA and RNA from the hepatocytes. 600 ul of kit lysis buffer was added to pelleted cells, along with one 5 mm sterile stainless steel bead and cells were completely disrupted using the TissueLyser. The QIAcube protocol was used first for DNA extraction (held at -80 deg C for future use) and the flow-through containing total RNA was then used for the second purification.
-
-Any residual DNA was removed from the RNA before Agilent quantification of concentration and RIN, using the QIAgen DNase I reagent, followed by ethanol precipitation and resuspension of DNA-free total RNA in 50 ul RNAse free water.
diff --git a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/acknowledgment.rtf b/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/acknowledgment.rtf
deleted file mode 100644
index 2349291..0000000
--- a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We thank Drs. David L. Bronson and Louaine L. Spriggs for their excellent editing of this manuscript.
diff --git a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/cases.rtf b/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/cases.rtf
deleted file mode 100644
index a9015ee..0000000
--- a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Animal Care and Use Committee of both the Seton Hall University and University of Virginia approved this study. Adult male HIV-1Tg rats and F344 background control rats (n = 12 per group) were purchased from Harlan Inc. (Indianapolis, IN). All rats were double housed in standard plastic cages and maintained in a temperature-controlled environment with a 12 h light/dark cycle and fed a standard rat diet and water ad libitum. The animals were monitored daily, and their cage bedding was changed twice a week. All animals were participants in a previously reported behavioral study [31]. All experimental procedures were conducted during the light cycle in accordance with the Animal Care and Use Committees of both participating institutions.
diff --git a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/experiment-design.rtf b/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/experiment-design.rtf
deleted file mode 100644
index a31cc4a..0000000
--- a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-144 RNA samples (2 strains, 2 treatments, 3 regions, and 12 animals per group) were analyzed.
diff --git a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/notes.rtf b/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/notes.rtf
deleted file mode 100644
index da785f4..0000000
--- a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/notes.rtf
+++ /dev/null
@@ -1 +0,0 @@
-https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0059582
diff --git a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/platform.rtf b/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/platform.rtf
deleted file mode 100644
index d55c8e4..0000000
--- a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GPL14844Illumina HiSeq 2000 (Rattus norvegicus)
diff --git a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/processing.rtf b/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/processing.rtf
deleted file mode 100644
index b0cb37b..0000000
--- a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The extraction of 50-bp length paired-end reads was achieved using CASAVA (Illumina Pipeline v1.38). For each sample, reads with a quality score of ≥Q30 that passed filtering were used to generate a complete FASTQ file, which was then mapped to UCSC Rat reference [build Rn4] (ftp://ftp.cbcb.umd.edu/pub/data/bowtie_indexes/rn4.ebwt.zip) using TopHat with the default parameter setting of 40 alignments per read and up to 2 mismatches per alignment. The sequence alignment files (BAM) were analyzed using RSeQC package [36] for quality control analysis, which includes the mRNA fragment insert size, base quality distribution, reads mapping distribution, and splicing distribution analysis.
-
-
-
-The resulting aligned reads were then analyzed with Cufflinks suite (http://cufflinks.cbcb.umd.edu) [37], which assembles the aligned reads into transcripts and measures their relative abundance. The expression of each transcript was quantified as the number of reads mapping to a gene divided by the gene length in kilobases and the total number of mapped reads in millions, which is called fragments per kilobase of exon per million fragments mapped (FPKM). All the junctions identified by Cufflink were compared on the basis of the junction and splicing site provided by reference transcript annotation GTF files to identify known and novel junctions. Then, Cuffcompare merged all the transcripts from different samples to a final transcript annotation GTF file, reported changes in the relative abundance of transcripts sharing a common transcription start site, and indicated the relative abundance of the primary transcripts of each gene crossing all the samples.
diff --git a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/specifics.rtf b/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/specifics.rtf
deleted file mode 100644
index 421629b..0000000
--- a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Hippocampus. rlog normalization
\ No newline at end of file
diff --git a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/summary.rtf b/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/summary.rtf
deleted file mode 100644
index 7bfa259..0000000
--- a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Purpose: The study was designed to determine expression differences in brain regions of F344 and HIV-1 Transgenic rats by using RNA-sq analysis. Methods: 144 RNA samples (2 strains, 2 treatments, 3 regions, and 12 animals per group) were analyzed. Following deep-sequencing analysis of 50-bp paired-end reads of RNA-Seq, we used Bowtie/Tophat/Cufflinks suites to align these reads into transcripts based on the Rn4 rat reference genome and to measure the relative abundance of each transcript. MATLAB was used to conduct all statistical analysis. qRT–PCR validation was performed using TaqMan and SYBR Green assays fo soem representative genes. Results: Statistical and bioinformatic analyses on each brain region in the two strains revealed that immune response- and neurotransmission-related pathways were altered in the HIV-1Tg rats, with brain region differences. Other neuronal survival-related pathways, including those encoding myelin proteins, growth factors, and translation regulators, were altered in the HIV-1Tg rats in a brain region-dependent manner. After nicotine expousure, 20% of the altered genes in the HIV-1Tg rat were affected by nicotine in each brain region, with the expression of most restored. Analysis of the restored genes showed distinct pathways corrected by nicotine in different brain regions of HIV-1Tg rats.
-
-Conclusions: The abnormal gene expression pattern discovered in HIV-1Tg rats suggest mechanisms underlying the deficits in learning and memory and vulnerability to drug addiction and other psychiatric disorders observed in HIV positive patients. The gene expression pattern in the HIV-1Tg rats after nicotine exposure indicate that cholinergic modulators such as nicotine may have beneficial effects on HIV-1-induced neurologic deficits.
diff --git a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/tissue.rtf b/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/tissue.rtf
deleted file mode 100644
index b65b5d6..0000000
--- a/general/datasets/UVA_HIV_1Tg_Hip_rlog_0720/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Using a rat brain matrix, slices of approximately 1 mm were taken from each brain, and the slices that contained the PFC, HIP, and dorsal STR were identified according to a rat brain atlas [35]. Tissues from specific regions of interest were collected bilaterally from each brain using a 3.00-mm Harris Micro-Punch (GE Healthcare Life Sciences, Piscataway, NJ, USA) and stored at −80°C until use.
diff --git a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/acknowledgment.rtf b/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/acknowledgment.rtf
deleted file mode 100644
index 2349291..0000000
--- a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We thank Drs. David L. Bronson and Louaine L. Spriggs for their excellent editing of this manuscript.
diff --git a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/cases.rtf b/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/cases.rtf
deleted file mode 100644
index a9015ee..0000000
--- a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Animal Care and Use Committee of both the Seton Hall University and University of Virginia approved this study. Adult male HIV-1Tg rats and F344 background control rats (n = 12 per group) were purchased from Harlan Inc. (Indianapolis, IN). All rats were double housed in standard plastic cages and maintained in a temperature-controlled environment with a 12 h light/dark cycle and fed a standard rat diet and water ad libitum. The animals were monitored daily, and their cage bedding was changed twice a week. All animals were participants in a previously reported behavioral study [31]. All experimental procedures were conducted during the light cycle in accordance with the Animal Care and Use Committees of both participating institutions.
diff --git a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/experiment-design.rtf b/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/experiment-design.rtf
deleted file mode 100644
index a31cc4a..0000000
--- a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-144 RNA samples (2 strains, 2 treatments, 3 regions, and 12 animals per group) were analyzed.
diff --git a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/notes.rtf b/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/notes.rtf
deleted file mode 100644
index da785f4..0000000
--- a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/notes.rtf
+++ /dev/null
@@ -1 +0,0 @@
-https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0059582
diff --git a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/platform.rtf b/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/platform.rtf
deleted file mode 100644
index d55c8e4..0000000
--- a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GPL14844Illumina HiSeq 2000 (Rattus norvegicus)
diff --git a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/processing.rtf b/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/processing.rtf
deleted file mode 100644
index b0cb37b..0000000
--- a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The extraction of 50-bp length paired-end reads was achieved using CASAVA (Illumina Pipeline v1.38). For each sample, reads with a quality score of ≥Q30 that passed filtering were used to generate a complete FASTQ file, which was then mapped to UCSC Rat reference [build Rn4] (ftp://ftp.cbcb.umd.edu/pub/data/bowtie_indexes/rn4.ebwt.zip) using TopHat with the default parameter setting of 40 alignments per read and up to 2 mismatches per alignment. The sequence alignment files (BAM) were analyzed using RSeQC package [36] for quality control analysis, which includes the mRNA fragment insert size, base quality distribution, reads mapping distribution, and splicing distribution analysis.
-
-
-
-The resulting aligned reads were then analyzed with Cufflinks suite (http://cufflinks.cbcb.umd.edu) [37], which assembles the aligned reads into transcripts and measures their relative abundance. The expression of each transcript was quantified as the number of reads mapping to a gene divided by the gene length in kilobases and the total number of mapped reads in millions, which is called fragments per kilobase of exon per million fragments mapped (FPKM). All the junctions identified by Cufflink were compared on the basis of the junction and splicing site provided by reference transcript annotation GTF files to identify known and novel junctions. Then, Cuffcompare merged all the transcripts from different samples to a final transcript annotation GTF file, reported changes in the relative abundance of transcripts sharing a common transcription start site, and indicated the relative abundance of the primary transcripts of each gene crossing all the samples.
diff --git a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/specifics.rtf b/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/specifics.rtf
deleted file mode 100644
index d27a33b..0000000
--- a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Prefrontal Cortex. rlog normalization
\ No newline at end of file
diff --git a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/summary.rtf b/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/summary.rtf
deleted file mode 100644
index 7bfa259..0000000
--- a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Purpose: The study was designed to determine expression differences in brain regions of F344 and HIV-1 Transgenic rats by using RNA-sq analysis. Methods: 144 RNA samples (2 strains, 2 treatments, 3 regions, and 12 animals per group) were analyzed. Following deep-sequencing analysis of 50-bp paired-end reads of RNA-Seq, we used Bowtie/Tophat/Cufflinks suites to align these reads into transcripts based on the Rn4 rat reference genome and to measure the relative abundance of each transcript. MATLAB was used to conduct all statistical analysis. qRT–PCR validation was performed using TaqMan and SYBR Green assays fo soem representative genes. Results: Statistical and bioinformatic analyses on each brain region in the two strains revealed that immune response- and neurotransmission-related pathways were altered in the HIV-1Tg rats, with brain region differences. Other neuronal survival-related pathways, including those encoding myelin proteins, growth factors, and translation regulators, were altered in the HIV-1Tg rats in a brain region-dependent manner. After nicotine expousure, 20% of the altered genes in the HIV-1Tg rat were affected by nicotine in each brain region, with the expression of most restored. Analysis of the restored genes showed distinct pathways corrected by nicotine in different brain regions of HIV-1Tg rats.
-
-Conclusions: The abnormal gene expression pattern discovered in HIV-1Tg rats suggest mechanisms underlying the deficits in learning and memory and vulnerability to drug addiction and other psychiatric disorders observed in HIV positive patients. The gene expression pattern in the HIV-1Tg rats after nicotine exposure indicate that cholinergic modulators such as nicotine may have beneficial effects on HIV-1-induced neurologic deficits.
diff --git a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/tissue.rtf b/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/tissue.rtf
deleted file mode 100644
index b65b5d6..0000000
--- a/general/datasets/UVA_HIV_1Tg_PFC_rlog_0720/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Using a rat brain matrix, slices of approximately 1 mm were taken from each brain, and the slices that contained the PFC, HIP, and dorsal STR were identified according to a rat brain atlas [35]. Tissues from specific regions of interest were collected bilaterally from each brain using a 3.00-mm Harris Micro-Punch (GE Healthcare Life Sciences, Piscataway, NJ, USA) and stored at −80°C until use.
diff --git a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/acknowledgment.rtf b/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/acknowledgment.rtf
deleted file mode 100644
index 2349291..0000000
--- a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-We thank Drs. David L. Bronson and Louaine L. Spriggs for their excellent editing of this manuscript.
diff --git a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/cases.rtf b/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/cases.rtf
deleted file mode 100644
index a9015ee..0000000
--- a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-The Animal Care and Use Committee of both the Seton Hall University and University of Virginia approved this study. Adult male HIV-1Tg rats and F344 background control rats (n = 12 per group) were purchased from Harlan Inc. (Indianapolis, IN). All rats were double housed in standard plastic cages and maintained in a temperature-controlled environment with a 12 h light/dark cycle and fed a standard rat diet and water ad libitum. The animals were monitored daily, and their cage bedding was changed twice a week. All animals were participants in a previously reported behavioral study [31]. All experimental procedures were conducted during the light cycle in accordance with the Animal Care and Use Committees of both participating institutions.
diff --git a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/experiment-design.rtf b/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/experiment-design.rtf
deleted file mode 100644
index a31cc4a..0000000
--- a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-144 RNA samples (2 strains, 2 treatments, 3 regions, and 12 animals per group) were analyzed.
diff --git a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/notes.rtf b/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/notes.rtf
deleted file mode 100644
index da785f4..0000000
--- a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/notes.rtf
+++ /dev/null
@@ -1 +0,0 @@
-https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0059582
diff --git a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/platform.rtf b/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/platform.rtf
deleted file mode 100644
index d55c8e4..0000000
--- a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-GPL14844Illumina HiSeq 2000 (Rattus norvegicus)
diff --git a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/processing.rtf b/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/processing.rtf
deleted file mode 100644
index b0cb37b..0000000
--- a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/processing.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-The extraction of 50-bp length paired-end reads was achieved using CASAVA (Illumina Pipeline v1.38). For each sample, reads with a quality score of ≥Q30 that passed filtering were used to generate a complete FASTQ file, which was then mapped to UCSC Rat reference [build Rn4] (ftp://ftp.cbcb.umd.edu/pub/data/bowtie_indexes/rn4.ebwt.zip) using TopHat with the default parameter setting of 40 alignments per read and up to 2 mismatches per alignment. The sequence alignment files (BAM) were analyzed using RSeQC package [36] for quality control analysis, which includes the mRNA fragment insert size, base quality distribution, reads mapping distribution, and splicing distribution analysis.
-
-
-
-The resulting aligned reads were then analyzed with Cufflinks suite (http://cufflinks.cbcb.umd.edu) [37], which assembles the aligned reads into transcripts and measures their relative abundance. The expression of each transcript was quantified as the number of reads mapping to a gene divided by the gene length in kilobases and the total number of mapped reads in millions, which is called fragments per kilobase of exon per million fragments mapped (FPKM). All the junctions identified by Cufflink were compared on the basis of the junction and splicing site provided by reference transcript annotation GTF files to identify known and novel junctions. Then, Cuffcompare merged all the transcripts from different samples to a final transcript annotation GTF file, reported changes in the relative abundance of transcripts sharing a common transcription start site, and indicated the relative abundance of the primary transcripts of each gene crossing all the samples.
diff --git a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/specifics.rtf b/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/specifics.rtf
deleted file mode 100644
index 2a10692..0000000
--- a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/specifics.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Striatum. rlog normalization
\ No newline at end of file
diff --git a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/summary.rtf b/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/summary.rtf
deleted file mode 100644
index 7bfa259..0000000
--- a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/summary.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Purpose: The study was designed to determine expression differences in brain regions of F344 and HIV-1 Transgenic rats by using RNA-sq analysis. Methods: 144 RNA samples (2 strains, 2 treatments, 3 regions, and 12 animals per group) were analyzed. Following deep-sequencing analysis of 50-bp paired-end reads of RNA-Seq, we used Bowtie/Tophat/Cufflinks suites to align these reads into transcripts based on the Rn4 rat reference genome and to measure the relative abundance of each transcript. MATLAB was used to conduct all statistical analysis. qRT–PCR validation was performed using TaqMan and SYBR Green assays fo soem representative genes. Results: Statistical and bioinformatic analyses on each brain region in the two strains revealed that immune response- and neurotransmission-related pathways were altered in the HIV-1Tg rats, with brain region differences. Other neuronal survival-related pathways, including those encoding myelin proteins, growth factors, and translation regulators, were altered in the HIV-1Tg rats in a brain region-dependent manner. After nicotine expousure, 20% of the altered genes in the HIV-1Tg rat were affected by nicotine in each brain region, with the expression of most restored. Analysis of the restored genes showed distinct pathways corrected by nicotine in different brain regions of HIV-1Tg rats.
-
-Conclusions: The abnormal gene expression pattern discovered in HIV-1Tg rats suggest mechanisms underlying the deficits in learning and memory and vulnerability to drug addiction and other psychiatric disorders observed in HIV positive patients. The gene expression pattern in the HIV-1Tg rats after nicotine exposure indicate that cholinergic modulators such as nicotine may have beneficial effects on HIV-1-induced neurologic deficits.
diff --git a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/tissue.rtf b/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/tissue.rtf
deleted file mode 100644
index b65b5d6..0000000
--- a/general/datasets/UVA_HIV_1Tg_Str_rlog_0720/tissue.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Using a rat brain matrix, slices of approximately 1 mm were taken from each brain, and the slices that contained the PFC, HIP, and dorsal STR were identified according to a rat brain atlas [35]. Tissues from specific regions of interest were collected bilaterally from each brain using a 3.00-mm Harris Micro-Punch (GE Healthcare Life Sciences, Piscataway, NJ, USA) and stored at −80°C until use.
diff --git a/general/datasets/Uab_droswb_lc_rma_1009/citation.rtf b/general/datasets/Uab_droswb_lc_rma_1009/citation.rtf
new file mode 100644
index 0000000..db3c29c
--- /dev/null
+++ b/general/datasets/Uab_droswb_lc_rma_1009/citation.rtf
@@ -0,0 +1 @@
+Ruden DM, et al. Genetical toxicogenomics in Drosophila identifies master-modulatory loci that are regulated by developmental exposure to lead, Neurotoxicology (2009), doi:10.1016/j.neuro.2009.08.011
diff --git a/general/datasets/Uab_droswb_lc_rma_1009/contributors.rtf b/general/datasets/Uab_droswb_lc_rma_1009/contributors.rtf
new file mode 100644
index 0000000..f78c41d
--- /dev/null
+++ b/general/datasets/Uab_droswb_lc_rma_1009/contributors.rtf
@@ -0,0 +1 @@
+Douglas M. Ruden a,*, Lang Chen b, Debra Possidente c, Bernard Possidente d, Parsa Rasouli a, Luan Wanga, Xiangyi Lu a, Mark D. Garfinkel e, Helmut V.B. Hirsch d, Grier P. Page f a Institute of Environmental Health Sciences, Wayne State University, Detroit, MI, United States b Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States c Department of Biological Sciences, University at Albany, SUNY, Albany, NY, United States d Department of Biology, Skidmore College, Saratoga Springs, NY, United States e Department of Environmental Health Sciences, University of Alabama at Birmingham, Birmingham, AL, United States f Statistics and Epidemiology Unit, RTI International, Atlanta, GA, United States
diff --git a/general/datasets/Uab_droswb_lc_rma_1009/platform.rtf b/general/datasets/Uab_droswb_lc_rma_1009/platform.rtf
new file mode 100644
index 0000000..2a01b87
--- /dev/null
+++ b/general/datasets/Uab_droswb_lc_rma_1009/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Drosophila Genome 2.0 Array GEO_GPL1322
diff --git a/general/datasets/Uab_droswb_lc_rma_1009/summary.rtf b/general/datasets/Uab_droswb_lc_rma_1009/summary.rtf
new file mode 100644
index 0000000..ef884bc
--- /dev/null
+++ b/general/datasets/Uab_droswb_lc_rma_1009/summary.rtf
@@ -0,0 +1 @@
+The genetics of gene expression in recombinant inbred lines (RILs) can be mapped as expression quantitative trait loci (eQTLs). So-called "genetical genomics" studies have identified locally acting eQTLs (cis-eQTLs) for genes that show differences in steady-state RNA levels. These studies have also identified distantly acting master-modulatory trans-eQTLs that regulate tens or hundreds of transcripts (hotspots or transbands). We expand on these studies by performing genetical genomics experiments in two environments in order to identify trans-eQTL thatmight be regulated by developmental exposure to the neurotoxin lead. Flies from each of 75 RIL were raised from eggs to adults on either control food (made with 250 mM sodium acetate), or lead-treated food (made with 250 mM lead acetate, PbAc). RNA expression analyses of whole adult male flies (5–10 days old) were performed with Affymetrix DrosII whole genome arrays (18,952 probesets). Among the 1389 genes with cis-eQTL, there were 405 genes unique to control flies and 544 genes unique to lead-treated ones (440 genes had the same cis-eQTLs in both samples). There are 2396 genes with trans-eQTL which mapped to 12major transbands with greater than 95 genes. Permutation analyses of the strain labels but not the expression data suggests that the total number of eQTL and the number of transbands are more important criteria for validation than the size of the transband. Two transbands, one located on the 2nd chromosome and one on the 3rd chromosome, co-regulate 33 lead-induced genes, many of which are involved in neurodevelopmental processes. For these 33 genes, rather than allelic variation at one locus exerting differential effects in two environments, we found that variation at two different loci are required for optimal effects on lead-induced expression.
diff --git a/general/datasets/Uab_droswb_le_rma_1009/citation.rtf b/general/datasets/Uab_droswb_le_rma_1009/citation.rtf
new file mode 100644
index 0000000..db3c29c
--- /dev/null
+++ b/general/datasets/Uab_droswb_le_rma_1009/citation.rtf
@@ -0,0 +1 @@
+Ruden DM, et al. Genetical toxicogenomics in Drosophila identifies master-modulatory loci that are regulated by developmental exposure to lead, Neurotoxicology (2009), doi:10.1016/j.neuro.2009.08.011
diff --git a/general/datasets/Uab_droswb_le_rma_1009/contributors.rtf b/general/datasets/Uab_droswb_le_rma_1009/contributors.rtf
new file mode 100644
index 0000000..f78c41d
--- /dev/null
+++ b/general/datasets/Uab_droswb_le_rma_1009/contributors.rtf
@@ -0,0 +1 @@
+Douglas M. Ruden a,*, Lang Chen b, Debra Possidente c, Bernard Possidente d, Parsa Rasouli a, Luan Wanga, Xiangyi Lu a, Mark D. Garfinkel e, Helmut V.B. Hirsch d, Grier P. Page f a Institute of Environmental Health Sciences, Wayne State University, Detroit, MI, United States b Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States c Department of Biological Sciences, University at Albany, SUNY, Albany, NY, United States d Department of Biology, Skidmore College, Saratoga Springs, NY, United States e Department of Environmental Health Sciences, University of Alabama at Birmingham, Birmingham, AL, United States f Statistics and Epidemiology Unit, RTI International, Atlanta, GA, United States
diff --git a/general/datasets/Uab_droswb_le_rma_1009/platform.rtf b/general/datasets/Uab_droswb_le_rma_1009/platform.rtf
new file mode 100644
index 0000000..2a01b87
--- /dev/null
+++ b/general/datasets/Uab_droswb_le_rma_1009/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Drosophila Genome 2.0 Array GEO_GPL1322
diff --git a/general/datasets/Uab_droswb_le_rma_1009/summary.rtf b/general/datasets/Uab_droswb_le_rma_1009/summary.rtf
new file mode 100644
index 0000000..ef884bc
--- /dev/null
+++ b/general/datasets/Uab_droswb_le_rma_1009/summary.rtf
@@ -0,0 +1 @@
+The genetics of gene expression in recombinant inbred lines (RILs) can be mapped as expression quantitative trait loci (eQTLs). So-called "genetical genomics" studies have identified locally acting eQTLs (cis-eQTLs) for genes that show differences in steady-state RNA levels. These studies have also identified distantly acting master-modulatory trans-eQTLs that regulate tens or hundreds of transcripts (hotspots or transbands). We expand on these studies by performing genetical genomics experiments in two environments in order to identify trans-eQTL thatmight be regulated by developmental exposure to the neurotoxin lead. Flies from each of 75 RIL were raised from eggs to adults on either control food (made with 250 mM sodium acetate), or lead-treated food (made with 250 mM lead acetate, PbAc). RNA expression analyses of whole adult male flies (5–10 days old) were performed with Affymetrix DrosII whole genome arrays (18,952 probesets). Among the 1389 genes with cis-eQTL, there were 405 genes unique to control flies and 544 genes unique to lead-treated ones (440 genes had the same cis-eQTLs in both samples). There are 2396 genes with trans-eQTL which mapped to 12major transbands with greater than 95 genes. Permutation analyses of the strain labels but not the expression data suggests that the total number of eQTL and the number of transbands are more important criteria for validation than the size of the transband. Two transbands, one located on the 2nd chromosome and one on the 3rd chromosome, co-regulate 33 lead-induced genes, many of which are involved in neurodevelopmental processes. For these 33 genes, rather than allelic variation at one locus exerting differential effects in two environments, we found that variation at two different loci are required for optimal effects on lead-induced expression.
diff --git a/general/datasets/Ubc_gse23529hlt0613/citation.rtf b/general/datasets/Ubc_gse23529hlt0613/citation.rtf
new file mode 100644
index 0000000..2aafa46
--- /dev/null
+++ b/general/datasets/Ubc_gse23529hlt0613/citation.rtf
@@ -0,0 +1 @@
+Bossé Y, Postma DS, Sin DD, Lamontagne M et al. Molecular signature of smoking in human lung tissues. Cancer Res 2012 Aug 1;72(15):3753-63. PMID: 22659451
diff --git a/general/datasets/Ubc_gse23529hlt0613/contributors.rtf b/general/datasets/Ubc_gse23529hlt0613/contributors.rtf
new file mode 100644
index 0000000..a22a4a5
--- /dev/null
+++ b/general/datasets/Ubc_gse23529hlt0613/contributors.rtf
@@ -0,0 +1 @@
+Bossé Y, Laviolette M
diff --git a/general/datasets/Ubc_gse23529hlt0613/summary.rtf b/general/datasets/Ubc_gse23529hlt0613/summary.rtf
new file mode 100644
index 0000000..9cb9538
--- /dev/null
+++ b/general/datasets/Ubc_gse23529hlt0613/summary.rtf
@@ -0,0 +1,15 @@
+This SuperSeries is composed of the following SubSeries:
+
+
+
+
+ | GSE23352 Whole-genome gene expression profiles of non-tumorous human lung tissues: Laval set |
+
+
+ | GSE23529 Whole-genome gene expression profiles of non-tumorous human lung tissues: UBC set |
+
+
+ | GSE23545 Whole-genome gene expression profiles of non-tumorous human lung tissues: GRNG set |
+
+
+
diff --git a/general/datasets/Ucamc_lxsbretoh_rna_seq_0216/citation.rtf b/general/datasets/Ucamc_lxsbretoh_rna_seq_0216/citation.rtf
new file mode 100644
index 0000000..574c7ce
--- /dev/null
+++ b/general/datasets/Ucamc_lxsbretoh_rna_seq_0216/citation.rtf
@@ -0,0 +1,6 @@
+Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31:166-169.
+Bennett B, Larson C, Richmond PA, Odell AT, Saba LM, Tabakoff B, Dowell R, Radcliffe RA (2015) Quantitative Trait Locus Mapping of Acute Functional Tolerance in the LXS Recombinant Inbred Strains. Alcoholism: Clinical and Experimental Research 39:611-620. Darlington TM, Ehringer MA, Larson C, Phang TL, Radcliffe RA (2013) Transcriptome analysis of Inbred Long Sleep and Inbred Short Sleep mice. Genes Brain Behav 12:263-274.
+Radcliffe RA, Floyd KL, Lee MJ (2006) Rapid ethanol tolerance mediated by adaptations in acute tolerance in inbred mouse strains. Pharmacol Biochem Behav 84:524-534.
+Radcliffe RA, Larson C, Bennett B (2013) Genetic studies of acute tolerance, rapid tolerance, and drinking in the dark in the LXS recombinant inbred strains. Alcohol Clin Exp Res 37:2019-2028.
+Saba LM, Bennett B, Hoffman PL, Barcomb K, Ishii T, Kechris K, Tabakoff B (2011) A systems genetic analysis of alcohol drinking by mice, rats and men: influence of brain GABAergic transmission. Neuropharmacology 60:1269-1280.
+Trapnell C, Pachter L, Salzberg SL (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25:1105-1111.
diff --git a/general/datasets/Ucamc_lxsbretoh_rna_seq_0216/specifics.rtf b/general/datasets/Ucamc_lxsbretoh_rna_seq_0216/specifics.rtf
new file mode 100644
index 0000000..ecd3498
--- /dev/null
+++ b/general/datasets/Ucamc_lxsbretoh_rna_seq_0216/specifics.rtf
@@ -0,0 +1,5 @@
+Summary: RNA-seq in the LXS RI Panel Following an Intraperitoneal Injection of Ethanol
+
+RNA-seq-derived gene expression was determined from the LXS recombinant inbred strains and the two parental strains (ILS/Ibg and ISS/Ibg) that had been treated with 5 g/kg ethanol (20% v/v in normal saline, ip) 8 hours before being sacrificed. (This is a companion to a similar dataset in which the same strains were treated with normal saline [ip] and sacrificed at 8 hours). Breeders were obtained from the Jackson Laboratory and experimental mice were bred in-house at the University of Colorado Anschutz Medical Campus. All samples were from whole brain (minus cerebellum and olfactory bulbs) of male mice at an average age of 80 days (SEM: +/- 0.4; range: 56-106; median: 81). The rationale for the dosing and the implicit overall rationale for this experiment can be found in Radcliffe et al. (2006); Radcliffe et al. (2013); Darlington et al. (2013); and Bennett et al. (2015).
+
+A total of 396 mice representing 44 LXS RI strains and the ILS and ISS were used. Following total RNA isolation, an equal amount of RNA from three mice of each strain was quantitatively pooled and then the samples were enriched for poly-A RNA using the Dynabeads mRNA Purification kit (Invitrogen) as directed by the manufacturer. Paired-end (2x100, expected size of 300 bp), strand-specific, cluster-ready libraries were prepared from the poly-A enriched RNA using the ScriptSeq RNA-Seq Library Preparation Kit v2 (Illumina). Three libraries per strain were prepared, 132 in total. Due to poor quality or other technical difficulties, 5 libraries were eliminated leaving a total of 44 strains (including ILS and ISS) comprised of 40 strains with n=3, 3 strains with n=2 and 1 strains with n=1. Tophat (Trapnell et al., 2009) was used to map reads to RI-specific genomes; i.e., the ILS and ISS were sequenced (see Bennett et al., 2015) and with the use of genotype data from the LXS (see Saba et al., 2011), a genome was created for each RI strain. Mapped reads were then quantified at the gene level using HTSeq (Anders et al., 2015) with Ensembl full gene annotations and then converted to FPKM using the formula FPKM=fragments/kb exon/million mapped reads/2 (note that this assumes that both reads of a pair were successfully mapped; for a small percentage of the reads this was not the case and these were treated separately and added in). FPKM values were converted to log2 (FPKM+1) which gives a value of 0 for FPKM=0, 1 for FPKM=1, 2 for FPKM=3, 3 for FPKM=7, 4 for FPKM=15, and so on.
diff --git a/general/datasets/Ucamc_lxsbrsal_rna_seq_0216/citation.rtf b/general/datasets/Ucamc_lxsbrsal_rna_seq_0216/citation.rtf
new file mode 100644
index 0000000..574c7ce
--- /dev/null
+++ b/general/datasets/Ucamc_lxsbrsal_rna_seq_0216/citation.rtf
@@ -0,0 +1,6 @@
+Anders S, Pyl PT, Huber W (2015) HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics 31:166-169.
+Bennett B, Larson C, Richmond PA, Odell AT, Saba LM, Tabakoff B, Dowell R, Radcliffe RA (2015) Quantitative Trait Locus Mapping of Acute Functional Tolerance in the LXS Recombinant Inbred Strains. Alcoholism: Clinical and Experimental Research 39:611-620. Darlington TM, Ehringer MA, Larson C, Phang TL, Radcliffe RA (2013) Transcriptome analysis of Inbred Long Sleep and Inbred Short Sleep mice. Genes Brain Behav 12:263-274.
+Radcliffe RA, Floyd KL, Lee MJ (2006) Rapid ethanol tolerance mediated by adaptations in acute tolerance in inbred mouse strains. Pharmacol Biochem Behav 84:524-534.
+Radcliffe RA, Larson C, Bennett B (2013) Genetic studies of acute tolerance, rapid tolerance, and drinking in the dark in the LXS recombinant inbred strains. Alcohol Clin Exp Res 37:2019-2028.
+Saba LM, Bennett B, Hoffman PL, Barcomb K, Ishii T, Kechris K, Tabakoff B (2011) A systems genetic analysis of alcohol drinking by mice, rats and men: influence of brain GABAergic transmission. Neuropharmacology 60:1269-1280.
+Trapnell C, Pachter L, Salzberg SL (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25:1105-1111.
diff --git a/general/datasets/Ucamc_lxsbrsal_rna_seq_0216/specifics.rtf b/general/datasets/Ucamc_lxsbrsal_rna_seq_0216/specifics.rtf
new file mode 100644
index 0000000..89ef78d
--- /dev/null
+++ b/general/datasets/Ucamc_lxsbrsal_rna_seq_0216/specifics.rtf
@@ -0,0 +1,5 @@
+Summary: RNA-seq in the LXS RI Panel Following an Intraperitoneal Injection of Saline
+
+RNA-seq-derived gene expression was determined from the LXS recombinant inbred strains and the two parental strains (ILS/Ibg and ISS/Ibg) that had been treated with normal saline (ip) 8 hours before being sacrificed. (This is a companion to a similar dataset in which the same strains were treated with 5 g/kg ethanol [20% v/v in normal saline, ip] and sacrificed at 8 hours). Breeders were obtained from the Jackson Laboratory and experimental mice were bred in-house at the University of Colorado Anschutz Medical Campus. All samples were from whole brain (minus cerebellum and olfactory bulbs) of male mice at an average age of 80 days (SEM: +/- 0.3; range: 58-106; median: 82). The rationale for the dosing and the implicit overall rationale for this experiment can be found in Radcliffe et al. (2006); Radcliffe et al. (2013); Darlington et al. (2013); and Bennett et al. (2015).
+
+A total of 396 mice representing 43 LXS RI strains and the ILS and ISS were used. Following total RNA isolation, an equal amount of RNA from three mice of each strain was quantitatively pooled and then the samples were enriched for poly-A RNA using the Dynabeads mRNA Purification kit (Invitrogen) as directed by the manufacturer. Paired-end (2x100, expected size of 300 bp), strand-specific, cluster-ready libraries were prepared from the poly-A enriched RNA using the ScriptSeq RNA-Seq Library Preparation Kit v2 (Illumina). Three libraries per strain were prepared, 132 in total. Due to poor quality or other technical difficulties, 9 libraries were eliminated leaving a total of 41 strains (including ILS and ISS) comprised of 36 strains with n=3, 3 strains with n=2 and 2 strains with n=1. Tophat (Trapnell et al., 2009) was used to map reads to RI-specific genomes; i.e., the ILS and ISS were sequenced (see Bennett et al., 2015) and with the use of genotype data from the LXS (see Saba et al., 2011), a genome was created for each RI strain. Mapped reads were then quantified at the gene level using HTSeq (Anders et al., 2015) with Ensembl full gene annotations and then converted to FPKM using the formula FPKM=fragments/kb exon/million mapped reads/2 (note that this assumes that both reads of a pair were successfully mapped; for a small percentage of the reads this was not the case and these were treated separately and added in). FPKM values were converted to log2 (FPKM+1) which gives a value of 0 for FPKM=0, 1 for FPKM=1, 2 for FPKM=3, 3 for FPKM=7, 4 for FPKM=15, and so on.
diff --git a/general/datasets/Uci_ec_0913/citation.rtf b/general/datasets/Uci_ec_0913/citation.rtf
new file mode 100644
index 0000000..f3ba04a
--- /dev/null
+++ b/general/datasets/Uci_ec_0913/citation.rtf
@@ -0,0 +1 @@
+Berchtold NC, Cribbs DH, Coleman PD, Rogers J et al. Gene expression changes in the course of normal brain aging are sexually dimorphic. Proc Natl Acad Sci U S A 2008 Oct 7;105(40):15605-10. PMID: 18832152
diff --git a/general/datasets/Uci_ec_0913/contributors.rtf b/general/datasets/Uci_ec_0913/contributors.rtf
new file mode 100644
index 0000000..fd462e2
--- /dev/null
+++ b/general/datasets/Uci_ec_0913/contributors.rtf
@@ -0,0 +1 @@
+Berchtold NC, Cribbs DH, Coleman PD, Rogers J, Head E, Kim R, Beach T, Miller C, Troncoso J, Trojanowski JQ, Zielke HR, Cotman CW
diff --git a/general/datasets/Uci_ec_0913/experiment-design.rtf b/general/datasets/Uci_ec_0913/experiment-design.rtf
new file mode 100644
index 0000000..f6a3038
--- /dev/null
+++ b/general/datasets/Uci_ec_0913/experiment-design.rtf
@@ -0,0 +1 @@
+Postmortem brain tissue was collected from ADRC brain banks. Cases were preferentially selected where 3 or more brain regions were available.
diff --git a/general/datasets/Uci_ec_0913/summary.rtf b/general/datasets/Uci_ec_0913/summary.rtf
new file mode 100644
index 0000000..fea08e6
--- /dev/null
+++ b/general/datasets/Uci_ec_0913/summary.rtf
@@ -0,0 +1 @@
+Gene expression profiles were assessed in the hippocampus (HC), entorhinal cortex (EC), superior frontal gyrus (SG), and postcentral gyrus (PCG) across the lifespan of 63 cognitively intact individuals from 20-99 years old. New perspectives on the global gene changes that are associated with brain aging emerged, revealing two overarching concepts. First, different regions of the forebrain exhibited substantially different gene profile changes with age. For example, comparing equally powered groups, 5,029 probe sets were significantly altered with age (20-59 vs. 60-99) in the superior frontal gyrus, compared with 1,110 in the entorhinal cortex. Prominent change occurred in the 6th-7th decades across cortical regions, suggesting that this period is a critical transition point in brain aging, particularly in males. Second, clear gender differences in brain aging were evident across the lifespan, suggesting that the brain undergoes sexually dimorphic changes in gene expression not only in development but also in later life. Globally across all brain regions, males showed more gene change than females. Further, Gene Ontology analysis revealed that different categories of genes were predominantly affected in males vs. females. Notably, the male brain was characterized by global decreased catabolic and anabolic capacity with aging, with downregulated genes heavily enriched in energy production and protein synthesis/transport categories. Increased immune activation was a prominent feature of aging in both sexes, with more widespread activation in the female brain. These data open new opportunities to explore age-dependent changes in gene expression that set the balance between neurodegeneration and compensatory mechanisms in the brain, and suggest that this balance is set differently in males and females, an intriguing and novel idea. HgU133plus2.0 microarray chips were used to profile gene expression in 4 brain regions of cognitively intact humans, across the adult lifespan (ages 20-99).
diff --git a/general/datasets/Uci_hc_0913/citation.rtf b/general/datasets/Uci_hc_0913/citation.rtf
new file mode 100644
index 0000000..f3ba04a
--- /dev/null
+++ b/general/datasets/Uci_hc_0913/citation.rtf
@@ -0,0 +1 @@
+Berchtold NC, Cribbs DH, Coleman PD, Rogers J et al. Gene expression changes in the course of normal brain aging are sexually dimorphic. Proc Natl Acad Sci U S A 2008 Oct 7;105(40):15605-10. PMID: 18832152
diff --git a/general/datasets/Uci_hc_0913/contributors.rtf b/general/datasets/Uci_hc_0913/contributors.rtf
new file mode 100644
index 0000000..fd462e2
--- /dev/null
+++ b/general/datasets/Uci_hc_0913/contributors.rtf
@@ -0,0 +1 @@
+Berchtold NC, Cribbs DH, Coleman PD, Rogers J, Head E, Kim R, Beach T, Miller C, Troncoso J, Trojanowski JQ, Zielke HR, Cotman CW
diff --git a/general/datasets/Uci_hc_0913/experiment-design.rtf b/general/datasets/Uci_hc_0913/experiment-design.rtf
new file mode 100644
index 0000000..f6a3038
--- /dev/null
+++ b/general/datasets/Uci_hc_0913/experiment-design.rtf
@@ -0,0 +1 @@
+Postmortem brain tissue was collected from ADRC brain banks. Cases were preferentially selected where 3 or more brain regions were available.
diff --git a/general/datasets/Uci_hc_0913/summary.rtf b/general/datasets/Uci_hc_0913/summary.rtf
new file mode 100644
index 0000000..fea08e6
--- /dev/null
+++ b/general/datasets/Uci_hc_0913/summary.rtf
@@ -0,0 +1 @@
+Gene expression profiles were assessed in the hippocampus (HC), entorhinal cortex (EC), superior frontal gyrus (SG), and postcentral gyrus (PCG) across the lifespan of 63 cognitively intact individuals from 20-99 years old. New perspectives on the global gene changes that are associated with brain aging emerged, revealing two overarching concepts. First, different regions of the forebrain exhibited substantially different gene profile changes with age. For example, comparing equally powered groups, 5,029 probe sets were significantly altered with age (20-59 vs. 60-99) in the superior frontal gyrus, compared with 1,110 in the entorhinal cortex. Prominent change occurred in the 6th-7th decades across cortical regions, suggesting that this period is a critical transition point in brain aging, particularly in males. Second, clear gender differences in brain aging were evident across the lifespan, suggesting that the brain undergoes sexually dimorphic changes in gene expression not only in development but also in later life. Globally across all brain regions, males showed more gene change than females. Further, Gene Ontology analysis revealed that different categories of genes were predominantly affected in males vs. females. Notably, the male brain was characterized by global decreased catabolic and anabolic capacity with aging, with downregulated genes heavily enriched in energy production and protein synthesis/transport categories. Increased immune activation was a prominent feature of aging in both sexes, with more widespread activation in the female brain. These data open new opportunities to explore age-dependent changes in gene expression that set the balance between neurodegeneration and compensatory mechanisms in the brain, and suggest that this balance is set differently in males and females, an intriguing and novel idea. HgU133plus2.0 microarray chips were used to profile gene expression in 4 brain regions of cognitively intact humans, across the adult lifespan (ages 20-99).
diff --git a/general/datasets/Uci_pcg_0913/citation.rtf b/general/datasets/Uci_pcg_0913/citation.rtf
new file mode 100644
index 0000000..f3ba04a
--- /dev/null
+++ b/general/datasets/Uci_pcg_0913/citation.rtf
@@ -0,0 +1 @@
+Berchtold NC, Cribbs DH, Coleman PD, Rogers J et al. Gene expression changes in the course of normal brain aging are sexually dimorphic. Proc Natl Acad Sci U S A 2008 Oct 7;105(40):15605-10. PMID: 18832152
diff --git a/general/datasets/Uci_pcg_0913/contributors.rtf b/general/datasets/Uci_pcg_0913/contributors.rtf
new file mode 100644
index 0000000..fd462e2
--- /dev/null
+++ b/general/datasets/Uci_pcg_0913/contributors.rtf
@@ -0,0 +1 @@
+Berchtold NC, Cribbs DH, Coleman PD, Rogers J, Head E, Kim R, Beach T, Miller C, Troncoso J, Trojanowski JQ, Zielke HR, Cotman CW
diff --git a/general/datasets/Uci_pcg_0913/experiment-design.rtf b/general/datasets/Uci_pcg_0913/experiment-design.rtf
new file mode 100644
index 0000000..f6a3038
--- /dev/null
+++ b/general/datasets/Uci_pcg_0913/experiment-design.rtf
@@ -0,0 +1 @@
+Postmortem brain tissue was collected from ADRC brain banks. Cases were preferentially selected where 3 or more brain regions were available.
diff --git a/general/datasets/Uci_pcg_0913/summary.rtf b/general/datasets/Uci_pcg_0913/summary.rtf
new file mode 100644
index 0000000..fea08e6
--- /dev/null
+++ b/general/datasets/Uci_pcg_0913/summary.rtf
@@ -0,0 +1 @@
+Gene expression profiles were assessed in the hippocampus (HC), entorhinal cortex (EC), superior frontal gyrus (SG), and postcentral gyrus (PCG) across the lifespan of 63 cognitively intact individuals from 20-99 years old. New perspectives on the global gene changes that are associated with brain aging emerged, revealing two overarching concepts. First, different regions of the forebrain exhibited substantially different gene profile changes with age. For example, comparing equally powered groups, 5,029 probe sets were significantly altered with age (20-59 vs. 60-99) in the superior frontal gyrus, compared with 1,110 in the entorhinal cortex. Prominent change occurred in the 6th-7th decades across cortical regions, suggesting that this period is a critical transition point in brain aging, particularly in males. Second, clear gender differences in brain aging were evident across the lifespan, suggesting that the brain undergoes sexually dimorphic changes in gene expression not only in development but also in later life. Globally across all brain regions, males showed more gene change than females. Further, Gene Ontology analysis revealed that different categories of genes were predominantly affected in males vs. females. Notably, the male brain was characterized by global decreased catabolic and anabolic capacity with aging, with downregulated genes heavily enriched in energy production and protein synthesis/transport categories. Increased immune activation was a prominent feature of aging in both sexes, with more widespread activation in the female brain. These data open new opportunities to explore age-dependent changes in gene expression that set the balance between neurodegeneration and compensatory mechanisms in the brain, and suggest that this balance is set differently in males and females, an intriguing and novel idea. HgU133plus2.0 microarray chips were used to profile gene expression in 4 brain regions of cognitively intact humans, across the adult lifespan (ages 20-99).
diff --git a/general/datasets/Uci_sg_0913/citation.rtf b/general/datasets/Uci_sg_0913/citation.rtf
new file mode 100644
index 0000000..f3ba04a
--- /dev/null
+++ b/general/datasets/Uci_sg_0913/citation.rtf
@@ -0,0 +1 @@
+Berchtold NC, Cribbs DH, Coleman PD, Rogers J et al. Gene expression changes in the course of normal brain aging are sexually dimorphic. Proc Natl Acad Sci U S A 2008 Oct 7;105(40):15605-10. PMID: 18832152
diff --git a/general/datasets/Uci_sg_0913/contributors.rtf b/general/datasets/Uci_sg_0913/contributors.rtf
new file mode 100644
index 0000000..fd462e2
--- /dev/null
+++ b/general/datasets/Uci_sg_0913/contributors.rtf
@@ -0,0 +1 @@
+Berchtold NC, Cribbs DH, Coleman PD, Rogers J, Head E, Kim R, Beach T, Miller C, Troncoso J, Trojanowski JQ, Zielke HR, Cotman CW
diff --git a/general/datasets/Uci_sg_0913/experiment-design.rtf b/general/datasets/Uci_sg_0913/experiment-design.rtf
new file mode 100644
index 0000000..f6a3038
--- /dev/null
+++ b/general/datasets/Uci_sg_0913/experiment-design.rtf
@@ -0,0 +1 @@
+Postmortem brain tissue was collected from ADRC brain banks. Cases were preferentially selected where 3 or more brain regions were available.
diff --git a/general/datasets/Uci_sg_0913/summary.rtf b/general/datasets/Uci_sg_0913/summary.rtf
new file mode 100644
index 0000000..fea08e6
--- /dev/null
+++ b/general/datasets/Uci_sg_0913/summary.rtf
@@ -0,0 +1 @@
+Gene expression profiles were assessed in the hippocampus (HC), entorhinal cortex (EC), superior frontal gyrus (SG), and postcentral gyrus (PCG) across the lifespan of 63 cognitively intact individuals from 20-99 years old. New perspectives on the global gene changes that are associated with brain aging emerged, revealing two overarching concepts. First, different regions of the forebrain exhibited substantially different gene profile changes with age. For example, comparing equally powered groups, 5,029 probe sets were significantly altered with age (20-59 vs. 60-99) in the superior frontal gyrus, compared with 1,110 in the entorhinal cortex. Prominent change occurred in the 6th-7th decades across cortical regions, suggesting that this period is a critical transition point in brain aging, particularly in males. Second, clear gender differences in brain aging were evident across the lifespan, suggesting that the brain undergoes sexually dimorphic changes in gene expression not only in development but also in later life. Globally across all brain regions, males showed more gene change than females. Further, Gene Ontology analysis revealed that different categories of genes were predominantly affected in males vs. females. Notably, the male brain was characterized by global decreased catabolic and anabolic capacity with aging, with downregulated genes heavily enriched in energy production and protein synthesis/transport categories. Increased immune activation was a prominent feature of aging in both sexes, with more widespread activation in the female brain. These data open new opportunities to explore age-dependent changes in gene expression that set the balance between neurodegeneration and compensatory mechanisms in the brain, and suggest that this balance is set differently in males and females, an intriguing and novel idea. HgU133plus2.0 microarray chips were used to profile gene expression in 4 brain regions of cognitively intact humans, across the adult lifespan (ages 20-99).
diff --git a/general/datasets/Ucla_axb_bxa_aor_jan16/citation.rtf b/general/datasets/Ucla_axb_bxa_aor_jan16/citation.rtf
new file mode 100644
index 0000000..6d383f0
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_aor_jan16/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Bennett BJ, Davis RC, Civelek M, Orozco L et al. Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains. PLoS Genet 2015 Dec 22;11(12):e1005711. PMID: 26694027
+
diff --git a/general/datasets/Ucla_axb_bxa_aor_jan16/contributors.rtf b/general/datasets/Ucla_axb_bxa_aor_jan16/contributors.rtf
new file mode 100644
index 0000000..8450813
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_aor_jan16/contributors.rtf
@@ -0,0 +1 @@
+Lusis AJ, Bennett B, Davis R
diff --git a/general/datasets/Ucla_axb_bxa_aor_jan16/experiment-design.rtf b/general/datasets/Ucla_axb_bxa_aor_jan16/experiment-design.rtf
new file mode 100644
index 0000000..1113b37
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_aor_jan16/experiment-design.rtf
@@ -0,0 +1 @@
+GWAS for expression in aortas of F1 offspring of inbred strains crossed with C57BL/6J carrying ApoE-Leiden and CETP transgenes fed chow diet for 8 weeks followed by Western diet for 16 weeks
diff --git a/general/datasets/Ucla_axb_bxa_aor_jan16/platform.rtf b/general/datasets/Ucla_axb_bxa_aor_jan16/platform.rtf
new file mode 100644
index 0000000..41439e8
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_aor_jan16/platform.rtf
@@ -0,0 +1 @@
+GPL11180 HT_MG-430_PM] Affymetrix HT MG-430 PM Array Plate
diff --git a/general/datasets/Ucla_axb_bxa_aor_jan16/specifics.rtf b/general/datasets/Ucla_axb_bxa_aor_jan16/specifics.rtf
new file mode 100644
index 0000000..8cdd2b9
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_aor_jan16/specifics.rtf
@@ -0,0 +1 @@
+Group AXB/BXA
\ No newline at end of file
diff --git a/general/datasets/Ucla_axb_bxa_aor_jan16/summary.rtf b/general/datasets/Ucla_axb_bxa_aor_jan16/summary.rtf
new file mode 100644
index 0000000..59e49a1
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_aor_jan16/summary.rtf
@@ -0,0 +1 @@
+Identify genes in the aorta whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. 104 of these strains were bred onto a C57BL/6J background carrying transgenes for both ApoE-Leiden and cholesteryl ester transfer protein (CETP). The RMA values of genes were used for genome wide association as described in Davis et al PLOS Genetics 2015. These data are used to identify candidate genes at loci associated with atherosclerotic lesion size.
diff --git a/general/datasets/Ucla_axb_bxa_femur_0113_rsn/experiment-type.rtf b/general/datasets/Ucla_axb_bxa_femur_0113_rsn/experiment-type.rtf
new file mode 100644
index 0000000..c29a175
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_femur_0113_rsn/experiment-type.rtf
@@ -0,0 +1 @@
+RNA from cortical bone (femoral diaphysis free of marrow) were profiled from 99 Hybrid Mouse Diversity Panel strains were profiled. Sixteen-week old male mice were used in this study. A total of 1-3 mice per strain were arrayed.
\ No newline at end of file
diff --git a/general/datasets/Ucla_axb_bxa_femur_0113_rsn/summary.rtf b/general/datasets/Ucla_axb_bxa_femur_0113_rsn/summary.rtf
new file mode 100644
index 0000000..aaa3dd1
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_femur_0113_rsn/summary.rtf
@@ -0,0 +1,15 @@
+Summary of DatasetId 163, Name: UCLA GSE27483 AXB/BXA Bone Femur ILM Mouse WG-6 v1, v1.1 (Jan13)
+
+J Bone Miner Res. 2009 Jan;24(1):105-16. doi: 10.1359/jbmr.080908.
+
+An integrative genetics approach to identify candidate genes regulating BMD: combining linkage, gene expression, and association
+
+Farber CR, van Nas A, Ghazalpour A, Aten JE, Doss S, Sos B, Schadt EE, Ingram-Drake L, Davis RC, Horvath S, Smith DJ, Drake TA, Lusis AJ
+
+Abstract
+
+Numerous quantitative trait loci (QTLs) affecting bone traits have been identified in the mouse; however, few of the underlying genes have been discovered. To improve the process of transitioning from QTL to gene, we describe an integrative genetics approach, which combines linkage analysis, expression QTL (eQTL) mapping, causality modeling, and genetic association in outbred mice. In C57BL/6J x C3H/HeJ (BXH) F(2) mice, nine QTLs regulating femoral BMD were identified. To select candidate genes from within each QTL region, microarray gene expression profiles from individual F(2) mice were used to identify 148 genes whose expression was correlated with BMD and regulated by local eQTLs. Many of the genes that were the most highly correlated with BMD have been previously shown to modulate bonemass or skeletal development. Candidates were further prioritized by determining whether their expression was predicted to underlie variation in BMD. Using network edge orienting (NEO), a causality modeling algorithm, 18 of the 148 candidates were predicted to be causally related to differences in BMD. To fine-map QTLs, markers in outbred MF1 mice were tested for association with BMD. Three chromosome 11 SNPs were identified that were associated with BMD within the Bmd11 QTL. Finally, our approach provides strong support for Wnt9a, Rasd1, or both underlying Bmd11. Integration of multiple genetic and genomic data sets can substantially improve the efficiency of QTL fine-mapping and candidate gene identification.
+
+
+ - PMID:18767929, PMCID: PMC2661539, DOI:10.1359/jbmr.080908
+
diff --git a/general/datasets/Ucla_axb_bxa_liv_jan16/citation.rtf b/general/datasets/Ucla_axb_bxa_liv_jan16/citation.rtf
new file mode 100644
index 0000000..6d383f0
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_liv_jan16/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Bennett BJ, Davis RC, Civelek M, Orozco L et al. Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains. PLoS Genet 2015 Dec 22;11(12):e1005711. PMID: 26694027
+
diff --git a/general/datasets/Ucla_axb_bxa_liv_jan16/contributors.rtf b/general/datasets/Ucla_axb_bxa_liv_jan16/contributors.rtf
new file mode 100644
index 0000000..8450813
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_liv_jan16/contributors.rtf
@@ -0,0 +1 @@
+Lusis AJ, Bennett B, Davis R
diff --git a/general/datasets/Ucla_axb_bxa_liv_jan16/experiment-design.rtf b/general/datasets/Ucla_axb_bxa_liv_jan16/experiment-design.rtf
new file mode 100644
index 0000000..715a1a3
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_liv_jan16/experiment-design.rtf
@@ -0,0 +1 @@
+GWAS for expression in livers of F1 offspring of inbred strains crossed with C57BL/6J carrying ApoE-Leiden and CETP transgenes fed chow diet for 8 weeks followed by Western diet for 16 weeks
diff --git a/general/datasets/Ucla_axb_bxa_liv_jan16/platform.rtf b/general/datasets/Ucla_axb_bxa_liv_jan16/platform.rtf
new file mode 100644
index 0000000..7659aeb
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_liv_jan16/platform.rtf
@@ -0,0 +1 @@
+GPL11180 HT_MG-430_PM] Affymetrix HT MG-430 PM Array Plate
diff --git a/general/datasets/Ucla_axb_bxa_liv_jan16/specifics.rtf b/general/datasets/Ucla_axb_bxa_liv_jan16/specifics.rtf
new file mode 100644
index 0000000..8cdd2b9
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_liv_jan16/specifics.rtf
@@ -0,0 +1 @@
+Group AXB/BXA
\ No newline at end of file
diff --git a/general/datasets/Ucla_axb_bxa_liv_jan16/summary.rtf b/general/datasets/Ucla_axb_bxa_liv_jan16/summary.rtf
new file mode 100644
index 0000000..9ffc1be
--- /dev/null
+++ b/general/datasets/Ucla_axb_bxa_liv_jan16/summary.rtf
@@ -0,0 +1 @@
+Identify genes in the liver whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. 104 of these strains were bred onto a C57BL/6J background carrying transgenes for both ApoE-Leiden and cholesteryl ester transfer protein (CETP). The RMA values of genes were used for genome wide association as described in Davis et al PLOS Genetics 2015. These data are used to identify candidate genes at loci associated with atherosclerotic lesion size.
diff --git a/general/datasets/Ucla_bdf2_liver_1999/citation.rtf b/general/datasets/Ucla_bdf2_liver_1999/citation.rtf
new file mode 100644
index 0000000..0f615b3
--- /dev/null
+++ b/general/datasets/Ucla_bdf2_liver_1999/citation.rtf
@@ -0,0 +1,8 @@
+
+ - Wang S, Yehya N, Schadt EE, Wang H et al. Genetic and genomic analysis of a fat mass trait with complex inheritance reveals marked sex specificity. PLoS Genet 2006 Feb;2(2):e15. PMID: 16462940
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - Ghazalpour A, Doss S, Zhang B, Wang S et al. Integrating genetic and network analysis to characterize genes related to mouse weight. PLoS Genet 2006 Aug 18;2(8):e130. PMID: 16934000
+ - Chen Y, Zhu J, Lum PY, Yang X et al. Variations in DNA elucidate molecular networks that cause disease. Nature 2008 Mar 27;452(7186):429-35. PMID: 18344982
+ - Wu S, Mar-Heyming R, Dugum EZ, Kolaitis NA et al. Upstream transcription factor 1 influences plasma lipid and metabolic traits in mice. Hum Mol Genet2010 Feb 15;19(4):597-608. PMID: 19995791
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bdf2_liver_1999/experiment-design.rtf b/general/datasets/Ucla_bdf2_liver_1999/experiment-design.rtf
new file mode 100644
index 0000000..592d9aa
--- /dev/null
+++ b/general/datasets/Ucla_bdf2_liver_1999/experiment-design.rtf
@@ -0,0 +1 @@
+Livers from 311 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bdf2_liver_1999/summary.rtf b/general/datasets/Ucla_bdf2_liver_1999/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bdf2_liver_1999/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhf2_adipose_0605/citation.rtf b/general/datasets/Ucla_bhf2_adipose_0605/citation.rtf
new file mode 100644
index 0000000..879b304
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_0605/citation.rtf
@@ -0,0 +1,5 @@
+
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - Chen Y, Zhu J, Lum PY, Yang X et al. Variations in DNA elucidate molecular networks that cause disease. Nature 2008 Mar 27;452(7186):429-35. PMID: 18344982
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhf2_adipose_0605/contributors.rtf b/general/datasets/Ucla_bhf2_adipose_0605/contributors.rtf
new file mode 100644
index 0000000..b570034
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_0605/contributors.rtf
@@ -0,0 +1 @@
+Yang X, Schadt EE, Wang S, Wang H, Arnold AP, Ingram-Drake L, Drake TA, Lusis AJ
diff --git a/general/datasets/Ucla_bhf2_adipose_0605/experiment-design.rtf b/general/datasets/Ucla_bhf2_adipose_0605/experiment-design.rtf
new file mode 100644
index 0000000..54a15e7
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_0605/experiment-design.rtf
@@ -0,0 +1 @@
+Adipose from 295 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhf2_adipose_0605/summary.rtf b/general/datasets/Ucla_bhf2_adipose_0605/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_0605/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhf2_adipose_female/citation.rtf b/general/datasets/Ucla_bhf2_adipose_female/citation.rtf
new file mode 100644
index 0000000..879b304
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_female/citation.rtf
@@ -0,0 +1,5 @@
+
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - Chen Y, Zhu J, Lum PY, Yang X et al. Variations in DNA elucidate molecular networks that cause disease. Nature 2008 Mar 27;452(7186):429-35. PMID: 18344982
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhf2_adipose_female/contributors.rtf b/general/datasets/Ucla_bhf2_adipose_female/contributors.rtf
new file mode 100644
index 0000000..b570034
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_female/contributors.rtf
@@ -0,0 +1 @@
+Yang X, Schadt EE, Wang S, Wang H, Arnold AP, Ingram-Drake L, Drake TA, Lusis AJ
diff --git a/general/datasets/Ucla_bhf2_adipose_female/experiment-design.rtf b/general/datasets/Ucla_bhf2_adipose_female/experiment-design.rtf
new file mode 100644
index 0000000..54a15e7
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_female/experiment-design.rtf
@@ -0,0 +1 @@
+Adipose from 295 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhf2_adipose_female/specifics.rtf b/general/datasets/Ucla_bhf2_adipose_female/specifics.rtf
new file mode 100644
index 0000000..3a8cf6f
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_female/specifics.rtf
@@ -0,0 +1 @@
+Females only
diff --git a/general/datasets/Ucla_bhf2_adipose_female/summary.rtf b/general/datasets/Ucla_bhf2_adipose_female/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_female/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhf2_adipose_male/citation.rtf b/general/datasets/Ucla_bhf2_adipose_male/citation.rtf
new file mode 100644
index 0000000..879b304
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_male/citation.rtf
@@ -0,0 +1,5 @@
+
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - Chen Y, Zhu J, Lum PY, Yang X et al. Variations in DNA elucidate molecular networks that cause disease. Nature 2008 Mar 27;452(7186):429-35. PMID: 18344982
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhf2_adipose_male/contributors.rtf b/general/datasets/Ucla_bhf2_adipose_male/contributors.rtf
new file mode 100644
index 0000000..b570034
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_male/contributors.rtf
@@ -0,0 +1 @@
+Yang X, Schadt EE, Wang S, Wang H, Arnold AP, Ingram-Drake L, Drake TA, Lusis AJ
diff --git a/general/datasets/Ucla_bhf2_adipose_male/experiment-design.rtf b/general/datasets/Ucla_bhf2_adipose_male/experiment-design.rtf
new file mode 100644
index 0000000..54a15e7
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_male/experiment-design.rtf
@@ -0,0 +1 @@
+Adipose from 295 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhf2_adipose_male/specifics.rtf b/general/datasets/Ucla_bhf2_adipose_male/specifics.rtf
new file mode 100644
index 0000000..6b7200b
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_male/specifics.rtf
@@ -0,0 +1 @@
+Males only
diff --git a/general/datasets/Ucla_bhf2_adipose_male/summary.rtf b/general/datasets/Ucla_bhf2_adipose_male/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_adipose_male/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhf2_brain_0605/citation.rtf b/general/datasets/Ucla_bhf2_brain_0605/citation.rtf
new file mode 100644
index 0000000..fdcaa84
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_0605/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhf2_brain_0605/contributors.rtf b/general/datasets/Ucla_bhf2_brain_0605/contributors.rtf
new file mode 100644
index 0000000..b570034
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_0605/contributors.rtf
@@ -0,0 +1 @@
+Yang X, Schadt EE, Wang S, Wang H, Arnold AP, Ingram-Drake L, Drake TA, Lusis AJ
diff --git a/general/datasets/Ucla_bhf2_brain_0605/experiment-design.rtf b/general/datasets/Ucla_bhf2_brain_0605/experiment-design.rtf
new file mode 100644
index 0000000..171d4d8
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_0605/experiment-design.rtf
@@ -0,0 +1 @@
+Brain from 249 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhf2_brain_0605/summary.rtf b/general/datasets/Ucla_bhf2_brain_0605/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_0605/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhf2_brain_female/citation.rtf b/general/datasets/Ucla_bhf2_brain_female/citation.rtf
new file mode 100644
index 0000000..fdcaa84
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_female/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhf2_brain_female/contributors.rtf b/general/datasets/Ucla_bhf2_brain_female/contributors.rtf
new file mode 100644
index 0000000..b570034
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_female/contributors.rtf
@@ -0,0 +1 @@
+Yang X, Schadt EE, Wang S, Wang H, Arnold AP, Ingram-Drake L, Drake TA, Lusis AJ
diff --git a/general/datasets/Ucla_bhf2_brain_female/experiment-design.rtf b/general/datasets/Ucla_bhf2_brain_female/experiment-design.rtf
new file mode 100644
index 0000000..171d4d8
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_female/experiment-design.rtf
@@ -0,0 +1 @@
+Brain from 249 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhf2_brain_female/specifics.rtf b/general/datasets/Ucla_bhf2_brain_female/specifics.rtf
new file mode 100644
index 0000000..3a8cf6f
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_female/specifics.rtf
@@ -0,0 +1 @@
+Females only
diff --git a/general/datasets/Ucla_bhf2_brain_female/summary.rtf b/general/datasets/Ucla_bhf2_brain_female/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_female/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhf2_brain_male/citation.rtf b/general/datasets/Ucla_bhf2_brain_male/citation.rtf
new file mode 100644
index 0000000..fdcaa84
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_male/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhf2_brain_male/contributors.rtf b/general/datasets/Ucla_bhf2_brain_male/contributors.rtf
new file mode 100644
index 0000000..b570034
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_male/contributors.rtf
@@ -0,0 +1 @@
+Yang X, Schadt EE, Wang S, Wang H, Arnold AP, Ingram-Drake L, Drake TA, Lusis AJ
diff --git a/general/datasets/Ucla_bhf2_brain_male/experiment-design.rtf b/general/datasets/Ucla_bhf2_brain_male/experiment-design.rtf
new file mode 100644
index 0000000..171d4d8
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_male/experiment-design.rtf
@@ -0,0 +1 @@
+Brain from 249 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhf2_brain_male/specifics.rtf b/general/datasets/Ucla_bhf2_brain_male/specifics.rtf
new file mode 100644
index 0000000..6b7200b
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_male/specifics.rtf
@@ -0,0 +1 @@
+Males only
diff --git a/general/datasets/Ucla_bhf2_brain_male/summary.rtf b/general/datasets/Ucla_bhf2_brain_male/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_brain_male/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhf2_liver_0605/citation.rtf b/general/datasets/Ucla_bhf2_liver_0605/citation.rtf
new file mode 100644
index 0000000..0f615b3
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_liver_0605/citation.rtf
@@ -0,0 +1,8 @@
+
+ - Wang S, Yehya N, Schadt EE, Wang H et al. Genetic and genomic analysis of a fat mass trait with complex inheritance reveals marked sex specificity. PLoS Genet 2006 Feb;2(2):e15. PMID: 16462940
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - Ghazalpour A, Doss S, Zhang B, Wang S et al. Integrating genetic and network analysis to characterize genes related to mouse weight. PLoS Genet 2006 Aug 18;2(8):e130. PMID: 16934000
+ - Chen Y, Zhu J, Lum PY, Yang X et al. Variations in DNA elucidate molecular networks that cause disease. Nature 2008 Mar 27;452(7186):429-35. PMID: 18344982
+ - Wu S, Mar-Heyming R, Dugum EZ, Kolaitis NA et al. Upstream transcription factor 1 influences plasma lipid and metabolic traits in mice. Hum Mol Genet2010 Feb 15;19(4):597-608. PMID: 19995791
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhf2_liver_0605/experiment-design.rtf b/general/datasets/Ucla_bhf2_liver_0605/experiment-design.rtf
new file mode 100644
index 0000000..592d9aa
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_liver_0605/experiment-design.rtf
@@ -0,0 +1 @@
+Livers from 311 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhf2_liver_0605/summary.rtf b/general/datasets/Ucla_bhf2_liver_0605/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_liver_0605/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhf2_liver_female/citation.rtf b/general/datasets/Ucla_bhf2_liver_female/citation.rtf
new file mode 100644
index 0000000..0f615b3
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_liver_female/citation.rtf
@@ -0,0 +1,8 @@
+
+ - Wang S, Yehya N, Schadt EE, Wang H et al. Genetic and genomic analysis of a fat mass trait with complex inheritance reveals marked sex specificity. PLoS Genet 2006 Feb;2(2):e15. PMID: 16462940
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - Ghazalpour A, Doss S, Zhang B, Wang S et al. Integrating genetic and network analysis to characterize genes related to mouse weight. PLoS Genet 2006 Aug 18;2(8):e130. PMID: 16934000
+ - Chen Y, Zhu J, Lum PY, Yang X et al. Variations in DNA elucidate molecular networks that cause disease. Nature 2008 Mar 27;452(7186):429-35. PMID: 18344982
+ - Wu S, Mar-Heyming R, Dugum EZ, Kolaitis NA et al. Upstream transcription factor 1 influences plasma lipid and metabolic traits in mice. Hum Mol Genet2010 Feb 15;19(4):597-608. PMID: 19995791
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhf2_liver_female/experiment-design.rtf b/general/datasets/Ucla_bhf2_liver_female/experiment-design.rtf
new file mode 100644
index 0000000..592d9aa
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_liver_female/experiment-design.rtf
@@ -0,0 +1 @@
+Livers from 311 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhf2_liver_female/specifics.rtf b/general/datasets/Ucla_bhf2_liver_female/specifics.rtf
new file mode 100644
index 0000000..3a8cf6f
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_liver_female/specifics.rtf
@@ -0,0 +1 @@
+Females only
diff --git a/general/datasets/Ucla_bhf2_liver_female/summary.rtf b/general/datasets/Ucla_bhf2_liver_female/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_liver_female/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhf2_liver_male/citation.rtf b/general/datasets/Ucla_bhf2_liver_male/citation.rtf
new file mode 100644
index 0000000..0f615b3
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_liver_male/citation.rtf
@@ -0,0 +1,8 @@
+
+ - Wang S, Yehya N, Schadt EE, Wang H et al. Genetic and genomic analysis of a fat mass trait with complex inheritance reveals marked sex specificity. PLoS Genet 2006 Feb;2(2):e15. PMID: 16462940
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - Ghazalpour A, Doss S, Zhang B, Wang S et al. Integrating genetic and network analysis to characterize genes related to mouse weight. PLoS Genet 2006 Aug 18;2(8):e130. PMID: 16934000
+ - Chen Y, Zhu J, Lum PY, Yang X et al. Variations in DNA elucidate molecular networks that cause disease. Nature 2008 Mar 27;452(7186):429-35. PMID: 18344982
+ - Wu S, Mar-Heyming R, Dugum EZ, Kolaitis NA et al. Upstream transcription factor 1 influences plasma lipid and metabolic traits in mice. Hum Mol Genet2010 Feb 15;19(4):597-608. PMID: 19995791
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhf2_liver_male/experiment-design.rtf b/general/datasets/Ucla_bhf2_liver_male/experiment-design.rtf
new file mode 100644
index 0000000..592d9aa
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_liver_male/experiment-design.rtf
@@ -0,0 +1 @@
+Livers from 311 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhf2_liver_male/specifics.rtf b/general/datasets/Ucla_bhf2_liver_male/specifics.rtf
new file mode 100644
index 0000000..6b7200b
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_liver_male/specifics.rtf
@@ -0,0 +1 @@
+Males only
diff --git a/general/datasets/Ucla_bhf2_liver_male/summary.rtf b/general/datasets/Ucla_bhf2_liver_male/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_liver_male/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhf2_muscle_0605/citation.rtf b/general/datasets/Ucla_bhf2_muscle_0605/citation.rtf
new file mode 100644
index 0000000..fdcaa84
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_0605/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhf2_muscle_0605/contributors.rtf b/general/datasets/Ucla_bhf2_muscle_0605/contributors.rtf
new file mode 100644
index 0000000..b570034
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_0605/contributors.rtf
@@ -0,0 +1 @@
+Yang X, Schadt EE, Wang S, Wang H, Arnold AP, Ingram-Drake L, Drake TA, Lusis AJ
diff --git a/general/datasets/Ucla_bhf2_muscle_0605/experiment-design.rtf b/general/datasets/Ucla_bhf2_muscle_0605/experiment-design.rtf
new file mode 100644
index 0000000..fda46c2
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_0605/experiment-design.rtf
@@ -0,0 +1 @@
+Muscle from 319 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhf2_muscle_0605/summary.rtf b/general/datasets/Ucla_bhf2_muscle_0605/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_0605/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhf2_muscle_female/citation.rtf b/general/datasets/Ucla_bhf2_muscle_female/citation.rtf
new file mode 100644
index 0000000..fdcaa84
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_female/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhf2_muscle_female/contributors.rtf b/general/datasets/Ucla_bhf2_muscle_female/contributors.rtf
new file mode 100644
index 0000000..b570034
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_female/contributors.rtf
@@ -0,0 +1 @@
+Yang X, Schadt EE, Wang S, Wang H, Arnold AP, Ingram-Drake L, Drake TA, Lusis AJ
diff --git a/general/datasets/Ucla_bhf2_muscle_female/experiment-design.rtf b/general/datasets/Ucla_bhf2_muscle_female/experiment-design.rtf
new file mode 100644
index 0000000..fda46c2
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_female/experiment-design.rtf
@@ -0,0 +1 @@
+Muscle from 319 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhf2_muscle_female/specifics.rtf b/general/datasets/Ucla_bhf2_muscle_female/specifics.rtf
new file mode 100644
index 0000000..3a8cf6f
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_female/specifics.rtf
@@ -0,0 +1 @@
+Females only
diff --git a/general/datasets/Ucla_bhf2_muscle_female/summary.rtf b/general/datasets/Ucla_bhf2_muscle_female/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_female/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhf2_muscle_male/citation.rtf b/general/datasets/Ucla_bhf2_muscle_male/citation.rtf
new file mode 100644
index 0000000..fdcaa84
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_male/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Yang X, Schadt EE, Wang S, Wang H et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res 2006 Aug;16(8):995-1004. PMID: 16825664
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhf2_muscle_male/contributors.rtf b/general/datasets/Ucla_bhf2_muscle_male/contributors.rtf
new file mode 100644
index 0000000..b570034
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_male/contributors.rtf
@@ -0,0 +1 @@
+Yang X, Schadt EE, Wang S, Wang H, Arnold AP, Ingram-Drake L, Drake TA, Lusis AJ
diff --git a/general/datasets/Ucla_bhf2_muscle_male/experiment-design.rtf b/general/datasets/Ucla_bhf2_muscle_male/experiment-design.rtf
new file mode 100644
index 0000000..fda46c2
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_male/experiment-design.rtf
@@ -0,0 +1 @@
+Muscle from 319 F2 female and male mice (animals fed a high fat "Western" diet from 8-24 weeks of age.) derived from C57BL/6J and C3H/HeJ parental strains with both on ApoE null backgrounds. All samples were compared to a common pool created from equal portions of RNA from each of the samples. Keywords=Genetics of Gene Expression Keywords=C57BL/6J Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhf2_muscle_male/specifics.rtf b/general/datasets/Ucla_bhf2_muscle_male/specifics.rtf
new file mode 100644
index 0000000..6b7200b
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_male/specifics.rtf
@@ -0,0 +1 @@
+Males only
diff --git a/general/datasets/Ucla_bhf2_muscle_male/summary.rtf b/general/datasets/Ucla_bhf2_muscle_male/summary.rtf
new file mode 100644
index 0000000..c5cf6bd
--- /dev/null
+++ b/general/datasets/Ucla_bhf2_muscle_male/summary.rtf
@@ -0,0 +1 @@
+The (C57BL/6J X C3H/HeJ)F2 intercross consists of 334 animals of both sexes. All are ApoE null and received a high fat Western diet from 8-24 weeks of age.
diff --git a/general/datasets/Ucla_bhhbf2_adipose_2005/citation.rtf b/general/datasets/Ucla_bhhbf2_adipose_2005/citation.rtf
new file mode 100644
index 0000000..b80d79e
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_2005/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Orozco LD, Cokus SJ, Ghazalpour A, Ingram-Drake L et al. Copy number variation influences gene expression and metabolic traits in mice. Hum Mol Genet 2009 Nov 1;18(21):4118-29. PMID: 19648292
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhhbf2_adipose_2005/contributors.rtf b/general/datasets/Ucla_bhhbf2_adipose_2005/contributors.rtf
new file mode 100644
index 0000000..66e613d
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_2005/contributors.rtf
@@ -0,0 +1 @@
+Lusis AJ, Schadt EE
diff --git a/general/datasets/Ucla_bhhbf2_adipose_2005/experiment-design.rtf b/general/datasets/Ucla_bhhbf2_adipose_2005/experiment-design.rtf
new file mode 100644
index 0000000..6df1de9
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_2005/experiment-design.rtf
@@ -0,0 +1 @@
+Adipose from 295 F2 female and male mice were generated by intercrossing F1 mice. Mice were fed chow diet containing 4% fat (Ralston-Purina Co., St. Louis, MO) until 8 weeks of age and then were placed on a high-fat "Western" diet containing 42% fat and 0.15% cholesterol (Teklad 88137, Harlan Teklad, Madison WI) for 12 weeks. At 20 weeks mice were sacrificed, after a 12-hour fast adipose tissues were dissected and flash frozen in LN2 and stored at -80°C. Keywords=Genetics of Gene Expression Keywords Keywords=C57B1/J6 Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhhbf2_adipose_2005/summary.rtf b/general/datasets/Ucla_bhhbf2_adipose_2005/summary.rtf
new file mode 100644
index 0000000..e7144bf
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_2005/summary.rtf
@@ -0,0 +1 @@
+The purpose of this experiment was to determine the expression traits in animals from F2 intercross of inbred strains C57BL/6J, C3H/HeJ. (N=309, 164 males and 145 females).
diff --git a/general/datasets/Ucla_bhhbf2_adipose_female/citation.rtf b/general/datasets/Ucla_bhhbf2_adipose_female/citation.rtf
new file mode 100644
index 0000000..b80d79e
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_female/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Orozco LD, Cokus SJ, Ghazalpour A, Ingram-Drake L et al. Copy number variation influences gene expression and metabolic traits in mice. Hum Mol Genet 2009 Nov 1;18(21):4118-29. PMID: 19648292
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhhbf2_adipose_female/contributors.rtf b/general/datasets/Ucla_bhhbf2_adipose_female/contributors.rtf
new file mode 100644
index 0000000..66e613d
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_female/contributors.rtf
@@ -0,0 +1 @@
+Lusis AJ, Schadt EE
diff --git a/general/datasets/Ucla_bhhbf2_adipose_female/experiment-design.rtf b/general/datasets/Ucla_bhhbf2_adipose_female/experiment-design.rtf
new file mode 100644
index 0000000..6df1de9
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_female/experiment-design.rtf
@@ -0,0 +1 @@
+Adipose from 295 F2 female and male mice were generated by intercrossing F1 mice. Mice were fed chow diet containing 4% fat (Ralston-Purina Co., St. Louis, MO) until 8 weeks of age and then were placed on a high-fat "Western" diet containing 42% fat and 0.15% cholesterol (Teklad 88137, Harlan Teklad, Madison WI) for 12 weeks. At 20 weeks mice were sacrificed, after a 12-hour fast adipose tissues were dissected and flash frozen in LN2 and stored at -80°C. Keywords=Genetics of Gene Expression Keywords Keywords=C57B1/J6 Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhhbf2_adipose_female/specifics.rtf b/general/datasets/Ucla_bhhbf2_adipose_female/specifics.rtf
new file mode 100644
index 0000000..3a8cf6f
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_female/specifics.rtf
@@ -0,0 +1 @@
+Females only
diff --git a/general/datasets/Ucla_bhhbf2_adipose_female/summary.rtf b/general/datasets/Ucla_bhhbf2_adipose_female/summary.rtf
new file mode 100644
index 0000000..e7144bf
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_female/summary.rtf
@@ -0,0 +1 @@
+The purpose of this experiment was to determine the expression traits in animals from F2 intercross of inbred strains C57BL/6J, C3H/HeJ. (N=309, 164 males and 145 females).
diff --git a/general/datasets/Ucla_bhhbf2_adipose_male/citation.rtf b/general/datasets/Ucla_bhhbf2_adipose_male/citation.rtf
new file mode 100644
index 0000000..b80d79e
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_male/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Orozco LD, Cokus SJ, Ghazalpour A, Ingram-Drake L et al. Copy number variation influences gene expression and metabolic traits in mice. Hum Mol Genet 2009 Nov 1;18(21):4118-29. PMID: 19648292
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhhbf2_adipose_male/contributors.rtf b/general/datasets/Ucla_bhhbf2_adipose_male/contributors.rtf
new file mode 100644
index 0000000..66e613d
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_male/contributors.rtf
@@ -0,0 +1 @@
+Lusis AJ, Schadt EE
diff --git a/general/datasets/Ucla_bhhbf2_adipose_male/experiment-design.rtf b/general/datasets/Ucla_bhhbf2_adipose_male/experiment-design.rtf
new file mode 100644
index 0000000..6df1de9
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_male/experiment-design.rtf
@@ -0,0 +1 @@
+Adipose from 295 F2 female and male mice were generated by intercrossing F1 mice. Mice were fed chow diet containing 4% fat (Ralston-Purina Co., St. Louis, MO) until 8 weeks of age and then were placed on a high-fat "Western" diet containing 42% fat and 0.15% cholesterol (Teklad 88137, Harlan Teklad, Madison WI) for 12 weeks. At 20 weeks mice were sacrificed, after a 12-hour fast adipose tissues were dissected and flash frozen in LN2 and stored at -80°C. Keywords=Genetics of Gene Expression Keywords Keywords=C57B1/J6 Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhhbf2_adipose_male/specifics.rtf b/general/datasets/Ucla_bhhbf2_adipose_male/specifics.rtf
new file mode 100644
index 0000000..6b7200b
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_male/specifics.rtf
@@ -0,0 +1 @@
+Males only
diff --git a/general/datasets/Ucla_bhhbf2_adipose_male/summary.rtf b/general/datasets/Ucla_bhhbf2_adipose_male/summary.rtf
new file mode 100644
index 0000000..e7144bf
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_adipose_male/summary.rtf
@@ -0,0 +1 @@
+The purpose of this experiment was to determine the expression traits in animals from F2 intercross of inbred strains C57BL/6J, C3H/HeJ. (N=309, 164 males and 145 females).
diff --git a/general/datasets/Ucla_bhhbf2_brain_2005/citation.rtf b/general/datasets/Ucla_bhhbf2_brain_2005/citation.rtf
new file mode 100644
index 0000000..b80d79e
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_brain_2005/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Orozco LD, Cokus SJ, Ghazalpour A, Ingram-Drake L et al. Copy number variation influences gene expression and metabolic traits in mice. Hum Mol Genet 2009 Nov 1;18(21):4118-29. PMID: 19648292
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhhbf2_brain_2005/experiment-design.rtf b/general/datasets/Ucla_bhhbf2_brain_2005/experiment-design.rtf
new file mode 100644
index 0000000..b1ce841
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_brain_2005/experiment-design.rtf
@@ -0,0 +1 @@
+Brain from 292 F2 female and male mice were generated by intercrossing F1 mice. Mice were fed chow diet containing 4% fat (Ralston-Purina Co., St. Louis, MO) until 8 weeks of age and then were placed on a high-fat "Western" diet containing 42% fat and 0.15%cholesterol (Teklad 88137, Harlan Teklad, Madison WI) for 12 weeks. At 20 weeks mice were sacrificed, after a 12-hour fast Brain tissues were dissected and flash frozen in LN2 and stored at -80°C.
diff --git a/general/datasets/Ucla_bhhbf2_brain_2005/summary.rtf b/general/datasets/Ucla_bhhbf2_brain_2005/summary.rtf
new file mode 100644
index 0000000..e7144bf
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_brain_2005/summary.rtf
@@ -0,0 +1 @@
+The purpose of this experiment was to determine the expression traits in animals from F2 intercross of inbred strains C57BL/6J, C3H/HeJ. (N=309, 164 males and 145 females).
diff --git a/general/datasets/Ucla_bhhbf2_brain_female/citation.rtf b/general/datasets/Ucla_bhhbf2_brain_female/citation.rtf
new file mode 100644
index 0000000..b80d79e
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_brain_female/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Orozco LD, Cokus SJ, Ghazalpour A, Ingram-Drake L et al. Copy number variation influences gene expression and metabolic traits in mice. Hum Mol Genet 2009 Nov 1;18(21):4118-29. PMID: 19648292
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhhbf2_brain_female/experiment-design.rtf b/general/datasets/Ucla_bhhbf2_brain_female/experiment-design.rtf
new file mode 100644
index 0000000..b1ce841
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_brain_female/experiment-design.rtf
@@ -0,0 +1 @@
+Brain from 292 F2 female and male mice were generated by intercrossing F1 mice. Mice were fed chow diet containing 4% fat (Ralston-Purina Co., St. Louis, MO) until 8 weeks of age and then were placed on a high-fat "Western" diet containing 42% fat and 0.15%cholesterol (Teklad 88137, Harlan Teklad, Madison WI) for 12 weeks. At 20 weeks mice were sacrificed, after a 12-hour fast Brain tissues were dissected and flash frozen in LN2 and stored at -80°C.
diff --git a/general/datasets/Ucla_bhhbf2_brain_female/specifics.rtf b/general/datasets/Ucla_bhhbf2_brain_female/specifics.rtf
new file mode 100644
index 0000000..3a8cf6f
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_brain_female/specifics.rtf
@@ -0,0 +1 @@
+Females only
diff --git a/general/datasets/Ucla_bhhbf2_brain_female/summary.rtf b/general/datasets/Ucla_bhhbf2_brain_female/summary.rtf
new file mode 100644
index 0000000..e7144bf
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_brain_female/summary.rtf
@@ -0,0 +1 @@
+The purpose of this experiment was to determine the expression traits in animals from F2 intercross of inbred strains C57BL/6J, C3H/HeJ. (N=309, 164 males and 145 females).
diff --git a/general/datasets/Ucla_bhhbf2_brain_male/citation.rtf b/general/datasets/Ucla_bhhbf2_brain_male/citation.rtf
new file mode 100644
index 0000000..b80d79e
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_brain_male/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Orozco LD, Cokus SJ, Ghazalpour A, Ingram-Drake L et al. Copy number variation influences gene expression and metabolic traits in mice. Hum Mol Genet 2009 Nov 1;18(21):4118-29. PMID: 19648292
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhhbf2_brain_male/experiment-design.rtf b/general/datasets/Ucla_bhhbf2_brain_male/experiment-design.rtf
new file mode 100644
index 0000000..b1ce841
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_brain_male/experiment-design.rtf
@@ -0,0 +1 @@
+Brain from 292 F2 female and male mice were generated by intercrossing F1 mice. Mice were fed chow diet containing 4% fat (Ralston-Purina Co., St. Louis, MO) until 8 weeks of age and then were placed on a high-fat "Western" diet containing 42% fat and 0.15%cholesterol (Teklad 88137, Harlan Teklad, Madison WI) for 12 weeks. At 20 weeks mice were sacrificed, after a 12-hour fast Brain tissues were dissected and flash frozen in LN2 and stored at -80°C.
diff --git a/general/datasets/Ucla_bhhbf2_brain_male/specifics.rtf b/general/datasets/Ucla_bhhbf2_brain_male/specifics.rtf
new file mode 100644
index 0000000..6b7200b
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_brain_male/specifics.rtf
@@ -0,0 +1 @@
+Males only
diff --git a/general/datasets/Ucla_bhhbf2_brain_male/summary.rtf b/general/datasets/Ucla_bhhbf2_brain_male/summary.rtf
new file mode 100644
index 0000000..e7144bf
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_brain_male/summary.rtf
@@ -0,0 +1 @@
+The purpose of this experiment was to determine the expression traits in animals from F2 intercross of inbred strains C57BL/6J, C3H/HeJ. (N=309, 164 males and 145 females).
diff --git a/general/datasets/Ucla_bhhbf2_liver_2005/citation.rtf b/general/datasets/Ucla_bhhbf2_liver_2005/citation.rtf
new file mode 100644
index 0000000..b80d79e
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_liver_2005/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Orozco LD, Cokus SJ, Ghazalpour A, Ingram-Drake L et al. Copy number variation influences gene expression and metabolic traits in mice. Hum Mol Genet 2009 Nov 1;18(21):4118-29. PMID: 19648292
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhhbf2_liver_2005/experiment-design.rtf b/general/datasets/Ucla_bhhbf2_liver_2005/experiment-design.rtf
new file mode 100644
index 0000000..dad76ff
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_liver_2005/experiment-design.rtf
@@ -0,0 +1 @@
+Liver from 302 F2 female and male mice were generated by intercrossing F1 mice. Mice were fed chow diet containing 4% fat (Ralston-Purina Co., St. Louis, MO) until 8 weeks of age and then were placed on a high-fat "Western" diet containing 42% fat and 0.15% cholesterol (Teklad 88137, Harlan Teklad, Madison WI) for 12 weeks. At 20 weeks mice were sacrificed, after a 12-hour fast liver tissues were dissected and flash frozen in LN2 and stored at -80°C. Keywords=Genetics of Gene Expression Keywords Keywords=C57B1/J6 Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhhbf2_liver_2005/summary.rtf b/general/datasets/Ucla_bhhbf2_liver_2005/summary.rtf
new file mode 100644
index 0000000..e7144bf
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_liver_2005/summary.rtf
@@ -0,0 +1 @@
+The purpose of this experiment was to determine the expression traits in animals from F2 intercross of inbred strains C57BL/6J, C3H/HeJ. (N=309, 164 males and 145 females).
diff --git a/general/datasets/Ucla_bhhbf2_liver_female/citation.rtf b/general/datasets/Ucla_bhhbf2_liver_female/citation.rtf
new file mode 100644
index 0000000..b80d79e
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_liver_female/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Orozco LD, Cokus SJ, Ghazalpour A, Ingram-Drake L et al. Copy number variation influences gene expression and metabolic traits in mice. Hum Mol Genet 2009 Nov 1;18(21):4118-29. PMID: 19648292
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhhbf2_liver_female/experiment-design.rtf b/general/datasets/Ucla_bhhbf2_liver_female/experiment-design.rtf
new file mode 100644
index 0000000..dad76ff
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_liver_female/experiment-design.rtf
@@ -0,0 +1 @@
+Liver from 302 F2 female and male mice were generated by intercrossing F1 mice. Mice were fed chow diet containing 4% fat (Ralston-Purina Co., St. Louis, MO) until 8 weeks of age and then were placed on a high-fat "Western" diet containing 42% fat and 0.15% cholesterol (Teklad 88137, Harlan Teklad, Madison WI) for 12 weeks. At 20 weeks mice were sacrificed, after a 12-hour fast liver tissues were dissected and flash frozen in LN2 and stored at -80°C. Keywords=Genetics of Gene Expression Keywords Keywords=C57B1/J6 Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhhbf2_liver_female/specifics.rtf b/general/datasets/Ucla_bhhbf2_liver_female/specifics.rtf
new file mode 100644
index 0000000..3a8cf6f
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_liver_female/specifics.rtf
@@ -0,0 +1 @@
+Females only
diff --git a/general/datasets/Ucla_bhhbf2_liver_female/summary.rtf b/general/datasets/Ucla_bhhbf2_liver_female/summary.rtf
new file mode 100644
index 0000000..e7144bf
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_liver_female/summary.rtf
@@ -0,0 +1 @@
+The purpose of this experiment was to determine the expression traits in animals from F2 intercross of inbred strains C57BL/6J, C3H/HeJ. (N=309, 164 males and 145 females).
diff --git a/general/datasets/Ucla_bhhbf2_liver_male/citation.rtf b/general/datasets/Ucla_bhhbf2_liver_male/citation.rtf
new file mode 100644
index 0000000..b80d79e
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_liver_male/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Orozco LD, Cokus SJ, Ghazalpour A, Ingram-Drake L et al. Copy number variation influences gene expression and metabolic traits in mice. Hum Mol Genet 2009 Nov 1;18(21):4118-29. PMID: 19648292
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhhbf2_liver_male/experiment-design.rtf b/general/datasets/Ucla_bhhbf2_liver_male/experiment-design.rtf
new file mode 100644
index 0000000..dad76ff
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_liver_male/experiment-design.rtf
@@ -0,0 +1 @@
+Liver from 302 F2 female and male mice were generated by intercrossing F1 mice. Mice were fed chow diet containing 4% fat (Ralston-Purina Co., St. Louis, MO) until 8 weeks of age and then were placed on a high-fat "Western" diet containing 42% fat and 0.15% cholesterol (Teklad 88137, Harlan Teklad, Madison WI) for 12 weeks. At 20 weeks mice were sacrificed, after a 12-hour fast liver tissues were dissected and flash frozen in LN2 and stored at -80°C. Keywords=Genetics of Gene Expression Keywords Keywords=C57B1/J6 Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhhbf2_liver_male/specifics.rtf b/general/datasets/Ucla_bhhbf2_liver_male/specifics.rtf
new file mode 100644
index 0000000..6b7200b
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_liver_male/specifics.rtf
@@ -0,0 +1 @@
+Males only
diff --git a/general/datasets/Ucla_bhhbf2_liver_male/summary.rtf b/general/datasets/Ucla_bhhbf2_liver_male/summary.rtf
new file mode 100644
index 0000000..e7144bf
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_liver_male/summary.rtf
@@ -0,0 +1 @@
+The purpose of this experiment was to determine the expression traits in animals from F2 intercross of inbred strains C57BL/6J, C3H/HeJ. (N=309, 164 males and 145 females).
diff --git a/general/datasets/Ucla_bhhbf2_muscle_2005/citation.rtf b/general/datasets/Ucla_bhhbf2_muscle_2005/citation.rtf
new file mode 100644
index 0000000..b80d79e
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_muscle_2005/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Orozco LD, Cokus SJ, Ghazalpour A, Ingram-Drake L et al. Copy number variation influences gene expression and metabolic traits in mice. Hum Mol Genet 2009 Nov 1;18(21):4118-29. PMID: 19648292
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhhbf2_muscle_2005/experiment-design.rtf b/general/datasets/Ucla_bhhbf2_muscle_2005/experiment-design.rtf
new file mode 100644
index 0000000..fa6a257
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_muscle_2005/experiment-design.rtf
@@ -0,0 +1 @@
+Muscle from 285 F2 female and male mice were generated by intercrossing F1 mice. Mice were fed chow diet containing 4% fat (Ralston-Purina Co., St. Louis, MO) until 8 weeks of age and then were placed on a high-fat "Western" diet containing 42% fat and 0.15% cholesterol (Teklad 88137, Harlan Teklad, Madison WI) for 12 weeks. At 20 weeks mice were sacrificed, after a 12-hour fast Muscle tissues were dissected and flash frozen in LN2 and stored at -80°C. Keywords=Genetics of Gene Expression Keywords Keywords=C57B1/J6 Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhhbf2_muscle_2005/summary.rtf b/general/datasets/Ucla_bhhbf2_muscle_2005/summary.rtf
new file mode 100644
index 0000000..e7144bf
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_muscle_2005/summary.rtf
@@ -0,0 +1 @@
+The purpose of this experiment was to determine the expression traits in animals from F2 intercross of inbred strains C57BL/6J, C3H/HeJ. (N=309, 164 males and 145 females).
diff --git a/general/datasets/Ucla_bhhbf2_muscle_female/citation.rtf b/general/datasets/Ucla_bhhbf2_muscle_female/citation.rtf
new file mode 100644
index 0000000..b80d79e
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_muscle_female/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Orozco LD, Cokus SJ, Ghazalpour A, Ingram-Drake L et al. Copy number variation influences gene expression and metabolic traits in mice. Hum Mol Genet 2009 Nov 1;18(21):4118-29. PMID: 19648292
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhhbf2_muscle_female/experiment-design.rtf b/general/datasets/Ucla_bhhbf2_muscle_female/experiment-design.rtf
new file mode 100644
index 0000000..fa6a257
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_muscle_female/experiment-design.rtf
@@ -0,0 +1 @@
+Muscle from 285 F2 female and male mice were generated by intercrossing F1 mice. Mice were fed chow diet containing 4% fat (Ralston-Purina Co., St. Louis, MO) until 8 weeks of age and then were placed on a high-fat "Western" diet containing 42% fat and 0.15% cholesterol (Teklad 88137, Harlan Teklad, Madison WI) for 12 weeks. At 20 weeks mice were sacrificed, after a 12-hour fast Muscle tissues were dissected and flash frozen in LN2 and stored at -80°C. Keywords=Genetics of Gene Expression Keywords Keywords=C57B1/J6 Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhhbf2_muscle_female/specifics.rtf b/general/datasets/Ucla_bhhbf2_muscle_female/specifics.rtf
new file mode 100644
index 0000000..3a8cf6f
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_muscle_female/specifics.rtf
@@ -0,0 +1 @@
+Females only
diff --git a/general/datasets/Ucla_bhhbf2_muscle_female/summary.rtf b/general/datasets/Ucla_bhhbf2_muscle_female/summary.rtf
new file mode 100644
index 0000000..e7144bf
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_muscle_female/summary.rtf
@@ -0,0 +1 @@
+The purpose of this experiment was to determine the expression traits in animals from F2 intercross of inbred strains C57BL/6J, C3H/HeJ. (N=309, 164 males and 145 females).
diff --git a/general/datasets/Ucla_bhhbf2_muscle_male/citation.rtf b/general/datasets/Ucla_bhhbf2_muscle_male/citation.rtf
new file mode 100644
index 0000000..b80d79e
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_muscle_male/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Orozco LD, Cokus SJ, Ghazalpour A, Ingram-Drake L et al. Copy number variation influences gene expression and metabolic traits in mice. Hum Mol Genet 2009 Nov 1;18(21):4118-29. PMID: 19648292
+ - van Nas A, Ingram-Drake L, Sinsheimer JS, Wang SS et al. Expression quantitative trait loci: replication, tissue- and sex-specificity in mice. Genetics2010 Jul;185(3):1059-68. PMID: 20439777
+
diff --git a/general/datasets/Ucla_bhhbf2_muscle_male/experiment-design.rtf b/general/datasets/Ucla_bhhbf2_muscle_male/experiment-design.rtf
new file mode 100644
index 0000000..fa6a257
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_muscle_male/experiment-design.rtf
@@ -0,0 +1 @@
+Muscle from 285 F2 female and male mice were generated by intercrossing F1 mice. Mice were fed chow diet containing 4% fat (Ralston-Purina Co., St. Louis, MO) until 8 weeks of age and then were placed on a high-fat "Western" diet containing 42% fat and 0.15% cholesterol (Teklad 88137, Harlan Teklad, Madison WI) for 12 weeks. At 20 weeks mice were sacrificed, after a 12-hour fast Muscle tissues were dissected and flash frozen in LN2 and stored at -80°C. Keywords=Genetics of Gene Expression Keywords Keywords=C57B1/J6 Keywords=C3H/HeJ
diff --git a/general/datasets/Ucla_bhhbf2_muscle_male/specifics.rtf b/general/datasets/Ucla_bhhbf2_muscle_male/specifics.rtf
new file mode 100644
index 0000000..6b7200b
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_muscle_male/specifics.rtf
@@ -0,0 +1 @@
+Males only
diff --git a/general/datasets/Ucla_bhhbf2_muscle_male/summary.rtf b/general/datasets/Ucla_bhhbf2_muscle_male/summary.rtf
new file mode 100644
index 0000000..e7144bf
--- /dev/null
+++ b/general/datasets/Ucla_bhhbf2_muscle_male/summary.rtf
@@ -0,0 +1 @@
+The purpose of this experiment was to determine the expression traits in animals from F2 intercross of inbred strains C57BL/6J, C3H/HeJ. (N=309, 164 males and 145 females).
diff --git a/general/datasets/Ucla_bxd_aor_jan16/citation.rtf b/general/datasets/Ucla_bxd_aor_jan16/citation.rtf
new file mode 100644
index 0000000..6d383f0
--- /dev/null
+++ b/general/datasets/Ucla_bxd_aor_jan16/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Bennett BJ, Davis RC, Civelek M, Orozco L et al. Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains. PLoS Genet 2015 Dec 22;11(12):e1005711. PMID: 26694027
+
diff --git a/general/datasets/Ucla_bxd_aor_jan16/contributors.rtf b/general/datasets/Ucla_bxd_aor_jan16/contributors.rtf
new file mode 100644
index 0000000..8450813
--- /dev/null
+++ b/general/datasets/Ucla_bxd_aor_jan16/contributors.rtf
@@ -0,0 +1 @@
+Lusis AJ, Bennett B, Davis R
diff --git a/general/datasets/Ucla_bxd_aor_jan16/experiment-design.rtf b/general/datasets/Ucla_bxd_aor_jan16/experiment-design.rtf
new file mode 100644
index 0000000..1113b37
--- /dev/null
+++ b/general/datasets/Ucla_bxd_aor_jan16/experiment-design.rtf
@@ -0,0 +1 @@
+GWAS for expression in aortas of F1 offspring of inbred strains crossed with C57BL/6J carrying ApoE-Leiden and CETP transgenes fed chow diet for 8 weeks followed by Western diet for 16 weeks
diff --git a/general/datasets/Ucla_bxd_aor_jan16/platform.rtf b/general/datasets/Ucla_bxd_aor_jan16/platform.rtf
new file mode 100644
index 0000000..41439e8
--- /dev/null
+++ b/general/datasets/Ucla_bxd_aor_jan16/platform.rtf
@@ -0,0 +1 @@
+GPL11180 HT_MG-430_PM] Affymetrix HT MG-430 PM Array Plate
diff --git a/general/datasets/Ucla_bxd_aor_jan16/specifics.rtf b/general/datasets/Ucla_bxd_aor_jan16/specifics.rtf
new file mode 100644
index 0000000..3864d15
--- /dev/null
+++ b/general/datasets/Ucla_bxd_aor_jan16/specifics.rtf
@@ -0,0 +1 @@
+Group BXD
\ No newline at end of file
diff --git a/general/datasets/Ucla_bxd_aor_jan16/summary.rtf b/general/datasets/Ucla_bxd_aor_jan16/summary.rtf
new file mode 100644
index 0000000..59e49a1
--- /dev/null
+++ b/general/datasets/Ucla_bxd_aor_jan16/summary.rtf
@@ -0,0 +1 @@
+Identify genes in the aorta whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. 104 of these strains were bred onto a C57BL/6J background carrying transgenes for both ApoE-Leiden and cholesteryl ester transfer protein (CETP). The RMA values of genes were used for genome wide association as described in Davis et al PLOS Genetics 2015. These data are used to identify candidate genes at loci associated with atherosclerotic lesion size.
diff --git a/general/datasets/Ucla_bxd_cartilage/experiment-design.rtf b/general/datasets/Ucla_bxd_cartilage/experiment-design.rtf
new file mode 100644
index 0000000..93735b8
--- /dev/null
+++ b/general/datasets/Ucla_bxd_cartilage/experiment-design.rtf
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+ -
+ -
+
diff --git a/general/datasets/Ucla_bxd_cartilage/summary.rtf b/general/datasets/Ucla_bxd_cartilage/summary.rtf
new file mode 100644
index 0000000..fbd364b
--- /dev/null
+++ b/general/datasets/Ucla_bxd_cartilage/summary.rtf
@@ -0,0 +1,11 @@
+Summary of DatasetId 59, Name: UCLA BXD and BXH Cartilage
+
+​J Bone Miner Res. 2011 Apr;26(4):747-60. doi: 10.1002/jbmr.271.
+
+Systems genetics analysis of mouse chondrocyte differentiation.
+
+Suwanwela J, Farber CR, Haung BL, Song B, Pan C, Lyons KM, Lusis AJ
+
+One of the goals of systems genetics is the reconstruction of gene networks that underlie key processes in development and disease. To identify cartilage gene networks that play an important role in bone development, we used a systems genetics approach that integrated microarray gene expression profiles from cartilage and bone phenotypic data from two sets of recombinant inbred strains. Microarray profiles generated from isolated chondrocytes were used to generate weighted gene coexpression networks. This analysis resulted in the identification of subnetworks (modules) of coexpressed genes that then were examined for relationships with bone geometry and density. One module exhibited significant correlation with femur length (r = 0.416), anteroposterior diameter (r = 0.418), mediolateral diameter (r = 0.576), and bone mineral density (r = 0.475). Highly connected genes (n = 28) from this and other modules were tested in vitro using prechondrocyte ATDC5 cells and RNA interference. Five of the 28 genes were found to play a role in chondrocyte differentiation. Two of these, Hspd1 and Cdkn1a, were known previously to function in chondrocyte development, whereas the other three, Bhlhb9, Cugbp1, and Spcs3, are novel genes. Our integrative analysis provided a systems-level view of cartilage development and identified genes that may be involved in bone development.
+
+PMID:20954177, PMCID:PMC3179327, DOI:10.1002/jbmr.271
diff --git a/general/datasets/Ucla_bxd_femur_0113_rsn/acknowledgment.rtf b/general/datasets/Ucla_bxd_femur_0113_rsn/acknowledgment.rtf
new file mode 100644
index 0000000..841713a
--- /dev/null
+++ b/general/datasets/Ucla_bxd_femur_0113_rsn/acknowledgment.rtf
@@ -0,0 +1 @@
+Calabrese G, Bennett BJ, Orozco L, Kang HM, Eskin E, Dombret C, De Backer O, Lusis AJ, Farber CR.
diff --git a/general/datasets/Ucla_bxd_femur_0113_rsn/citation.rtf b/general/datasets/Ucla_bxd_femur_0113_rsn/citation.rtf
new file mode 100644
index 0000000..a3b7aa6
--- /dev/null
+++ b/general/datasets/Ucla_bxd_femur_0113_rsn/citation.rtf
@@ -0,0 +1 @@
+Farber CR, Bennett BJ, Orozco L, Zou W et al. Mouse genome-wide association and systems genetics identify Asxl2 as a regulator of bone mineral density and osteoclastogenesis. PLoS Genet 2011 Apr;7(4):e1002038. PMID: 21490954 Calabrese G, Bennett BJ, Orozco L, Kang HM et al. Systems genetic analysis of osteoblast-lineage cells. PLoS Genet 2012 Dec;8(12):e1003150. PMID: 23300464.
diff --git a/general/datasets/Ucla_bxd_femur_0113_rsn/experiment-design.rtf b/general/datasets/Ucla_bxd_femur_0113_rsn/experiment-design.rtf
new file mode 100644
index 0000000..6a72392
--- /dev/null
+++ b/general/datasets/Ucla_bxd_femur_0113_rsn/experiment-design.rtf
@@ -0,0 +1 @@
+RNA from cortical bone (femoral diaphysis free of marrow) were profiled from 99 Hybrid Mouse Diversity Panel strains were profiled. Sixteen-week old male mice were used in this study. A total of 1-3 mice per strain were arrayed.
diff --git a/general/datasets/Ucla_bxd_femur_0113_rsn/experiment-type.rtf b/general/datasets/Ucla_bxd_femur_0113_rsn/experiment-type.rtf
new file mode 100644
index 0000000..c29a175
--- /dev/null
+++ b/general/datasets/Ucla_bxd_femur_0113_rsn/experiment-type.rtf
@@ -0,0 +1 @@
+RNA from cortical bone (femoral diaphysis free of marrow) were profiled from 99 Hybrid Mouse Diversity Panel strains were profiled. Sixteen-week old male mice were used in this study. A total of 1-3 mice per strain were arrayed.
\ No newline at end of file
diff --git a/general/datasets/Ucla_bxd_femur_0113_rsn/platform.rtf b/general/datasets/Ucla_bxd_femur_0113_rsn/platform.rtf
new file mode 100644
index 0000000..578985c
--- /dev/null
+++ b/general/datasets/Ucla_bxd_femur_0113_rsn/platform.rtf
@@ -0,0 +1 @@
+Illumina mouse-6 v1.1 expression beadchip
diff --git a/general/datasets/Ucla_bxd_femur_0113_rsn/processing.rtf b/general/datasets/Ucla_bxd_femur_0113_rsn/processing.rtf
new file mode 100644
index 0000000..9f66d05
--- /dev/null
+++ b/general/datasets/Ucla_bxd_femur_0113_rsn/processing.rtf
@@ -0,0 +1 @@
+The expression values were transformed using the Variance Stabilizing Transformation (VST), and normalized with the Robust Spline Normalization (RSN) algorithm using the LumiR R package. After normalization, the ComBat software was used to adjust for batch effects using an empirical Bayes method.
diff --git a/general/datasets/Ucla_bxd_femur_0113_rsn/summary.rtf b/general/datasets/Ucla_bxd_femur_0113_rsn/summary.rtf
new file mode 100644
index 0000000..df75fa6
--- /dev/null
+++ b/general/datasets/Ucla_bxd_femur_0113_rsn/summary.rtf
@@ -0,0 +1 @@
+Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis was used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal and femoral BMD revealed four significant associations (-log10P > 5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12 and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism though which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression gene module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cell of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.
diff --git a/general/datasets/Ucla_bxd_liv_jan16/citation.rtf b/general/datasets/Ucla_bxd_liv_jan16/citation.rtf
new file mode 100644
index 0000000..6d383f0
--- /dev/null
+++ b/general/datasets/Ucla_bxd_liv_jan16/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Bennett BJ, Davis RC, Civelek M, Orozco L et al. Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains. PLoS Genet 2015 Dec 22;11(12):e1005711. PMID: 26694027
+
diff --git a/general/datasets/Ucla_bxd_liv_jan16/contributors.rtf b/general/datasets/Ucla_bxd_liv_jan16/contributors.rtf
new file mode 100644
index 0000000..8450813
--- /dev/null
+++ b/general/datasets/Ucla_bxd_liv_jan16/contributors.rtf
@@ -0,0 +1 @@
+Lusis AJ, Bennett B, Davis R
diff --git a/general/datasets/Ucla_bxd_liv_jan16/experiment-design.rtf b/general/datasets/Ucla_bxd_liv_jan16/experiment-design.rtf
new file mode 100644
index 0000000..715a1a3
--- /dev/null
+++ b/general/datasets/Ucla_bxd_liv_jan16/experiment-design.rtf
@@ -0,0 +1 @@
+GWAS for expression in livers of F1 offspring of inbred strains crossed with C57BL/6J carrying ApoE-Leiden and CETP transgenes fed chow diet for 8 weeks followed by Western diet for 16 weeks
diff --git a/general/datasets/Ucla_bxd_liv_jan16/platform.rtf b/general/datasets/Ucla_bxd_liv_jan16/platform.rtf
new file mode 100644
index 0000000..7659aeb
--- /dev/null
+++ b/general/datasets/Ucla_bxd_liv_jan16/platform.rtf
@@ -0,0 +1 @@
+GPL11180 HT_MG-430_PM] Affymetrix HT MG-430 PM Array Plate
diff --git a/general/datasets/Ucla_bxd_liv_jan16/summary.rtf b/general/datasets/Ucla_bxd_liv_jan16/summary.rtf
new file mode 100644
index 0000000..9ffc1be
--- /dev/null
+++ b/general/datasets/Ucla_bxd_liv_jan16/summary.rtf
@@ -0,0 +1 @@
+Identify genes in the liver whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. 104 of these strains were bred onto a C57BL/6J background carrying transgenes for both ApoE-Leiden and cholesteryl ester transfer protein (CETP). The RMA values of genes were used for genome wide association as described in Davis et al PLOS Genetics 2015. These data are used to identify candidate genes at loci associated with atherosclerotic lesion size.
diff --git a/general/datasets/Ucla_bxd_on_femur_0113_rsn/acknowledgment.rtf b/general/datasets/Ucla_bxd_on_femur_0113_rsn/acknowledgment.rtf
new file mode 100644
index 0000000..841713a
--- /dev/null
+++ b/general/datasets/Ucla_bxd_on_femur_0113_rsn/acknowledgment.rtf
@@ -0,0 +1 @@
+Calabrese G, Bennett BJ, Orozco L, Kang HM, Eskin E, Dombret C, De Backer O, Lusis AJ, Farber CR.
diff --git a/general/datasets/Ucla_bxd_on_femur_0113_rsn/citation.rtf b/general/datasets/Ucla_bxd_on_femur_0113_rsn/citation.rtf
new file mode 100644
index 0000000..a3b7aa6
--- /dev/null
+++ b/general/datasets/Ucla_bxd_on_femur_0113_rsn/citation.rtf
@@ -0,0 +1 @@
+Farber CR, Bennett BJ, Orozco L, Zou W et al. Mouse genome-wide association and systems genetics identify Asxl2 as a regulator of bone mineral density and osteoclastogenesis. PLoS Genet 2011 Apr;7(4):e1002038. PMID: 21490954 Calabrese G, Bennett BJ, Orozco L, Kang HM et al. Systems genetic analysis of osteoblast-lineage cells. PLoS Genet 2012 Dec;8(12):e1003150. PMID: 23300464.
diff --git a/general/datasets/Ucla_bxd_on_femur_0113_rsn/experiment-design.rtf b/general/datasets/Ucla_bxd_on_femur_0113_rsn/experiment-design.rtf
new file mode 100644
index 0000000..6a72392
--- /dev/null
+++ b/general/datasets/Ucla_bxd_on_femur_0113_rsn/experiment-design.rtf
@@ -0,0 +1 @@
+RNA from cortical bone (femoral diaphysis free of marrow) were profiled from 99 Hybrid Mouse Diversity Panel strains were profiled. Sixteen-week old male mice were used in this study. A total of 1-3 mice per strain were arrayed.
diff --git a/general/datasets/Ucla_bxd_on_femur_0113_rsn/experiment-type.rtf b/general/datasets/Ucla_bxd_on_femur_0113_rsn/experiment-type.rtf
new file mode 100644
index 0000000..c29a175
--- /dev/null
+++ b/general/datasets/Ucla_bxd_on_femur_0113_rsn/experiment-type.rtf
@@ -0,0 +1 @@
+RNA from cortical bone (femoral diaphysis free of marrow) were profiled from 99 Hybrid Mouse Diversity Panel strains were profiled. Sixteen-week old male mice were used in this study. A total of 1-3 mice per strain were arrayed.
\ No newline at end of file
diff --git a/general/datasets/Ucla_bxd_on_femur_0113_rsn/platform.rtf b/general/datasets/Ucla_bxd_on_femur_0113_rsn/platform.rtf
new file mode 100644
index 0000000..578985c
--- /dev/null
+++ b/general/datasets/Ucla_bxd_on_femur_0113_rsn/platform.rtf
@@ -0,0 +1 @@
+Illumina mouse-6 v1.1 expression beadchip
diff --git a/general/datasets/Ucla_bxd_on_femur_0113_rsn/processing.rtf b/general/datasets/Ucla_bxd_on_femur_0113_rsn/processing.rtf
new file mode 100644
index 0000000..9f66d05
--- /dev/null
+++ b/general/datasets/Ucla_bxd_on_femur_0113_rsn/processing.rtf
@@ -0,0 +1 @@
+The expression values were transformed using the Variance Stabilizing Transformation (VST), and normalized with the Robust Spline Normalization (RSN) algorithm using the LumiR R package. After normalization, the ComBat software was used to adjust for batch effects using an empirical Bayes method.
diff --git a/general/datasets/Ucla_bxd_on_femur_0113_rsn/summary.rtf b/general/datasets/Ucla_bxd_on_femur_0113_rsn/summary.rtf
new file mode 100644
index 0000000..df75fa6
--- /dev/null
+++ b/general/datasets/Ucla_bxd_on_femur_0113_rsn/summary.rtf
@@ -0,0 +1 @@
+Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis was used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal and femoral BMD revealed four significant associations (-log10P > 5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12 and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism though which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression gene module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cell of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.
diff --git a/general/datasets/Ucla_bxdbxh_cartilage/experiment-design.rtf b/general/datasets/Ucla_bxdbxh_cartilage/experiment-design.rtf
new file mode 100644
index 0000000..93735b8
--- /dev/null
+++ b/general/datasets/Ucla_bxdbxh_cartilage/experiment-design.rtf
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+ -
+ -
+
diff --git a/general/datasets/Ucla_bxdbxh_cartilage/summary.rtf b/general/datasets/Ucla_bxdbxh_cartilage/summary.rtf
new file mode 100644
index 0000000..fbd364b
--- /dev/null
+++ b/general/datasets/Ucla_bxdbxh_cartilage/summary.rtf
@@ -0,0 +1,11 @@
+Summary of DatasetId 59, Name: UCLA BXD and BXH Cartilage
+
+​J Bone Miner Res. 2011 Apr;26(4):747-60. doi: 10.1002/jbmr.271.
+
+Systems genetics analysis of mouse chondrocyte differentiation.
+
+Suwanwela J, Farber CR, Haung BL, Song B, Pan C, Lyons KM, Lusis AJ
+
+One of the goals of systems genetics is the reconstruction of gene networks that underlie key processes in development and disease. To identify cartilage gene networks that play an important role in bone development, we used a systems genetics approach that integrated microarray gene expression profiles from cartilage and bone phenotypic data from two sets of recombinant inbred strains. Microarray profiles generated from isolated chondrocytes were used to generate weighted gene coexpression networks. This analysis resulted in the identification of subnetworks (modules) of coexpressed genes that then were examined for relationships with bone geometry and density. One module exhibited significant correlation with femur length (r = 0.416), anteroposterior diameter (r = 0.418), mediolateral diameter (r = 0.576), and bone mineral density (r = 0.475). Highly connected genes (n = 28) from this and other modules were tested in vitro using prechondrocyte ATDC5 cells and RNA interference. Five of the 28 genes were found to play a role in chondrocyte differentiation. Two of these, Hspd1 and Cdkn1a, were known previously to function in chondrocyte development, whereas the other three, Bhlhb9, Cugbp1, and Spcs3, are novel genes. Our integrative analysis provided a systems-level view of cartilage development and identified genes that may be involved in bone development.
+
+PMID:20954177, PMCID:PMC3179327, DOI:10.1002/jbmr.271
diff --git a/general/datasets/Ucla_bxdbxh_cartilage_v2/experiment-design.rtf b/general/datasets/Ucla_bxdbxh_cartilage_v2/experiment-design.rtf
new file mode 100644
index 0000000..93735b8
--- /dev/null
+++ b/general/datasets/Ucla_bxdbxh_cartilage_v2/experiment-design.rtf
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+ -
+ -
+
diff --git a/general/datasets/Ucla_bxdbxh_cartilage_v2/summary.rtf b/general/datasets/Ucla_bxdbxh_cartilage_v2/summary.rtf
new file mode 100644
index 0000000..fbd364b
--- /dev/null
+++ b/general/datasets/Ucla_bxdbxh_cartilage_v2/summary.rtf
@@ -0,0 +1,11 @@
+Summary of DatasetId 59, Name: UCLA BXD and BXH Cartilage
+
+​J Bone Miner Res. 2011 Apr;26(4):747-60. doi: 10.1002/jbmr.271.
+
+Systems genetics analysis of mouse chondrocyte differentiation.
+
+Suwanwela J, Farber CR, Haung BL, Song B, Pan C, Lyons KM, Lusis AJ
+
+One of the goals of systems genetics is the reconstruction of gene networks that underlie key processes in development and disease. To identify cartilage gene networks that play an important role in bone development, we used a systems genetics approach that integrated microarray gene expression profiles from cartilage and bone phenotypic data from two sets of recombinant inbred strains. Microarray profiles generated from isolated chondrocytes were used to generate weighted gene coexpression networks. This analysis resulted in the identification of subnetworks (modules) of coexpressed genes that then were examined for relationships with bone geometry and density. One module exhibited significant correlation with femur length (r = 0.416), anteroposterior diameter (r = 0.418), mediolateral diameter (r = 0.576), and bone mineral density (r = 0.475). Highly connected genes (n = 28) from this and other modules were tested in vitro using prechondrocyte ATDC5 cells and RNA interference. Five of the 28 genes were found to play a role in chondrocyte differentiation. Two of these, Hspd1 and Cdkn1a, were known previously to function in chondrocyte development, whereas the other three, Bhlhb9, Cugbp1, and Spcs3, are novel genes. Our integrative analysis provided a systems-level view of cartilage development and identified genes that may be involved in bone development.
+
+PMID:20954177, PMCID:PMC3179327, DOI:10.1002/jbmr.271
diff --git a/general/datasets/Ucla_bxh_cartilage/experiment-design.rtf b/general/datasets/Ucla_bxh_cartilage/experiment-design.rtf
new file mode 100644
index 0000000..93735b8
--- /dev/null
+++ b/general/datasets/Ucla_bxh_cartilage/experiment-design.rtf
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+ -
+ -
+
diff --git a/general/datasets/Ucla_bxh_cartilage/summary.rtf b/general/datasets/Ucla_bxh_cartilage/summary.rtf
new file mode 100644
index 0000000..fbd364b
--- /dev/null
+++ b/general/datasets/Ucla_bxh_cartilage/summary.rtf
@@ -0,0 +1,11 @@
+Summary of DatasetId 59, Name: UCLA BXD and BXH Cartilage
+
+​J Bone Miner Res. 2011 Apr;26(4):747-60. doi: 10.1002/jbmr.271.
+
+Systems genetics analysis of mouse chondrocyte differentiation.
+
+Suwanwela J, Farber CR, Haung BL, Song B, Pan C, Lyons KM, Lusis AJ
+
+One of the goals of systems genetics is the reconstruction of gene networks that underlie key processes in development and disease. To identify cartilage gene networks that play an important role in bone development, we used a systems genetics approach that integrated microarray gene expression profiles from cartilage and bone phenotypic data from two sets of recombinant inbred strains. Microarray profiles generated from isolated chondrocytes were used to generate weighted gene coexpression networks. This analysis resulted in the identification of subnetworks (modules) of coexpressed genes that then were examined for relationships with bone geometry and density. One module exhibited significant correlation with femur length (r = 0.416), anteroposterior diameter (r = 0.418), mediolateral diameter (r = 0.576), and bone mineral density (r = 0.475). Highly connected genes (n = 28) from this and other modules were tested in vitro using prechondrocyte ATDC5 cells and RNA interference. Five of the 28 genes were found to play a role in chondrocyte differentiation. Two of these, Hspd1 and Cdkn1a, were known previously to function in chondrocyte development, whereas the other three, Bhlhb9, Cugbp1, and Spcs3, are novel genes. Our integrative analysis provided a systems-level view of cartilage development and identified genes that may be involved in bone development.
+
+PMID:20954177, PMCID:PMC3179327, DOI:10.1002/jbmr.271
diff --git a/general/datasets/Ucla_bxh_femur_0113_rsn/experiment-type.rtf b/general/datasets/Ucla_bxh_femur_0113_rsn/experiment-type.rtf
new file mode 100644
index 0000000..c29a175
--- /dev/null
+++ b/general/datasets/Ucla_bxh_femur_0113_rsn/experiment-type.rtf
@@ -0,0 +1 @@
+RNA from cortical bone (femoral diaphysis free of marrow) were profiled from 99 Hybrid Mouse Diversity Panel strains were profiled. Sixteen-week old male mice were used in this study. A total of 1-3 mice per strain were arrayed.
\ No newline at end of file
diff --git a/general/datasets/Ucla_bxh_femur_0113_rsn/summary.rtf b/general/datasets/Ucla_bxh_femur_0113_rsn/summary.rtf
new file mode 100644
index 0000000..b5cf311
--- /dev/null
+++ b/general/datasets/Ucla_bxh_femur_0113_rsn/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 164, Name: UCLA GSE27483 BXH Bone Femur ILM Mouse WG-6 v1, v1.1 (Jan13)
\ No newline at end of file
diff --git a/general/datasets/Ucla_bxhbxd_cartilage/experiment-design.rtf b/general/datasets/Ucla_bxhbxd_cartilage/experiment-design.rtf
new file mode 100644
index 0000000..93735b8
--- /dev/null
+++ b/general/datasets/Ucla_bxhbxd_cartilage/experiment-design.rtf
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+ -
+ -
+
diff --git a/general/datasets/Ucla_bxhbxd_cartilage/summary.rtf b/general/datasets/Ucla_bxhbxd_cartilage/summary.rtf
new file mode 100644
index 0000000..fbd364b
--- /dev/null
+++ b/general/datasets/Ucla_bxhbxd_cartilage/summary.rtf
@@ -0,0 +1,11 @@
+Summary of DatasetId 59, Name: UCLA BXD and BXH Cartilage
+
+​J Bone Miner Res. 2011 Apr;26(4):747-60. doi: 10.1002/jbmr.271.
+
+Systems genetics analysis of mouse chondrocyte differentiation.
+
+Suwanwela J, Farber CR, Haung BL, Song B, Pan C, Lyons KM, Lusis AJ
+
+One of the goals of systems genetics is the reconstruction of gene networks that underlie key processes in development and disease. To identify cartilage gene networks that play an important role in bone development, we used a systems genetics approach that integrated microarray gene expression profiles from cartilage and bone phenotypic data from two sets of recombinant inbred strains. Microarray profiles generated from isolated chondrocytes were used to generate weighted gene coexpression networks. This analysis resulted in the identification of subnetworks (modules) of coexpressed genes that then were examined for relationships with bone geometry and density. One module exhibited significant correlation with femur length (r = 0.416), anteroposterior diameter (r = 0.418), mediolateral diameter (r = 0.576), and bone mineral density (r = 0.475). Highly connected genes (n = 28) from this and other modules were tested in vitro using prechondrocyte ATDC5 cells and RNA interference. Five of the 28 genes were found to play a role in chondrocyte differentiation. Two of these, Hspd1 and Cdkn1a, were known previously to function in chondrocyte development, whereas the other three, Bhlhb9, Cugbp1, and Spcs3, are novel genes. Our integrative analysis provided a systems-level view of cartilage development and identified genes that may be involved in bone development.
+
+PMID:20954177, PMCID:PMC3179327, DOI:10.1002/jbmr.271
diff --git a/general/datasets/Ucla_bxhbxd_cartilage_v2/experiment-design.rtf b/general/datasets/Ucla_bxhbxd_cartilage_v2/experiment-design.rtf
new file mode 100644
index 0000000..93735b8
--- /dev/null
+++ b/general/datasets/Ucla_bxhbxd_cartilage_v2/experiment-design.rtf
@@ -0,0 +1,10 @@
+
+
+
+
+
+
+
+ -
+ -
+
diff --git a/general/datasets/Ucla_bxhbxd_cartilage_v2/summary.rtf b/general/datasets/Ucla_bxhbxd_cartilage_v2/summary.rtf
new file mode 100644
index 0000000..fbd364b
--- /dev/null
+++ b/general/datasets/Ucla_bxhbxd_cartilage_v2/summary.rtf
@@ -0,0 +1,11 @@
+Summary of DatasetId 59, Name: UCLA BXD and BXH Cartilage
+
+​J Bone Miner Res. 2011 Apr;26(4):747-60. doi: 10.1002/jbmr.271.
+
+Systems genetics analysis of mouse chondrocyte differentiation.
+
+Suwanwela J, Farber CR, Haung BL, Song B, Pan C, Lyons KM, Lusis AJ
+
+One of the goals of systems genetics is the reconstruction of gene networks that underlie key processes in development and disease. To identify cartilage gene networks that play an important role in bone development, we used a systems genetics approach that integrated microarray gene expression profiles from cartilage and bone phenotypic data from two sets of recombinant inbred strains. Microarray profiles generated from isolated chondrocytes were used to generate weighted gene coexpression networks. This analysis resulted in the identification of subnetworks (modules) of coexpressed genes that then were examined for relationships with bone geometry and density. One module exhibited significant correlation with femur length (r = 0.416), anteroposterior diameter (r = 0.418), mediolateral diameter (r = 0.576), and bone mineral density (r = 0.475). Highly connected genes (n = 28) from this and other modules were tested in vitro using prechondrocyte ATDC5 cells and RNA interference. Five of the 28 genes were found to play a role in chondrocyte differentiation. Two of these, Hspd1 and Cdkn1a, were known previously to function in chondrocyte development, whereas the other three, Bhlhb9, Cugbp1, and Spcs3, are novel genes. Our integrative analysis provided a systems-level view of cartilage development and identified genes that may be involved in bone development.
+
+PMID:20954177, PMCID:PMC3179327, DOI:10.1002/jbmr.271
diff --git a/general/datasets/Ucla_ctb6b6ctf2_adipose_2005/summary.rtf b/general/datasets/Ucla_ctb6b6ctf2_adipose_2005/summary.rtf
new file mode 100644
index 0000000..5cbfe56
--- /dev/null
+++ b/general/datasets/Ucla_ctb6b6ctf2_adipose_2005/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 51, Name: UCLA CTB6B6CTF2 Adipose mlratio
diff --git a/general/datasets/Ucla_ctb6b6ctf2_adipose_female/summary.rtf b/general/datasets/Ucla_ctb6b6ctf2_adipose_female/summary.rtf
new file mode 100644
index 0000000..5cbfe56
--- /dev/null
+++ b/general/datasets/Ucla_ctb6b6ctf2_adipose_female/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 51, Name: UCLA CTB6B6CTF2 Adipose mlratio
diff --git a/general/datasets/Ucla_ctb6b6ctf2_adipose_male/summary.rtf b/general/datasets/Ucla_ctb6b6ctf2_adipose_male/summary.rtf
new file mode 100644
index 0000000..5cbfe56
--- /dev/null
+++ b/general/datasets/Ucla_ctb6b6ctf2_adipose_male/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 51, Name: UCLA CTB6B6CTF2 Adipose mlratio
diff --git a/general/datasets/Ucla_ctb6b6ctf2_brain_2005/summary.rtf b/general/datasets/Ucla_ctb6b6ctf2_brain_2005/summary.rtf
new file mode 100644
index 0000000..9d8eb19
--- /dev/null
+++ b/general/datasets/Ucla_ctb6b6ctf2_brain_2005/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 52, Name: UCLA CTB6/B6CTF2 Brain (2005) mlratio
\ No newline at end of file
diff --git a/general/datasets/Ucla_ctb6b6ctf2_brain_female/summary.rtf b/general/datasets/Ucla_ctb6b6ctf2_brain_female/summary.rtf
new file mode 100644
index 0000000..9d8eb19
--- /dev/null
+++ b/general/datasets/Ucla_ctb6b6ctf2_brain_female/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 52, Name: UCLA CTB6/B6CTF2 Brain (2005) mlratio
\ No newline at end of file
diff --git a/general/datasets/Ucla_ctb6b6ctf2_brain_male/summary.rtf b/general/datasets/Ucla_ctb6b6ctf2_brain_male/summary.rtf
new file mode 100644
index 0000000..9d8eb19
--- /dev/null
+++ b/general/datasets/Ucla_ctb6b6ctf2_brain_male/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 52, Name: UCLA CTB6/B6CTF2 Brain (2005) mlratio
\ No newline at end of file
diff --git a/general/datasets/Ucla_ctb6b6ctf2_liver_2005/summary.rtf b/general/datasets/Ucla_ctb6b6ctf2_liver_2005/summary.rtf
new file mode 100644
index 0000000..fdd0e9f
--- /dev/null
+++ b/general/datasets/Ucla_ctb6b6ctf2_liver_2005/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 53, Name: UCLA CTB6B6CTF2 Liver Female mlratio **
\ No newline at end of file
diff --git a/general/datasets/Ucla_ctb6b6ctf2_liver_female/summary.rtf b/general/datasets/Ucla_ctb6b6ctf2_liver_female/summary.rtf
new file mode 100644
index 0000000..fdd0e9f
--- /dev/null
+++ b/general/datasets/Ucla_ctb6b6ctf2_liver_female/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 53, Name: UCLA CTB6B6CTF2 Liver Female mlratio **
\ No newline at end of file
diff --git a/general/datasets/Ucla_ctb6b6ctf2_liver_male/summary.rtf b/general/datasets/Ucla_ctb6b6ctf2_liver_male/summary.rtf
new file mode 100644
index 0000000..fdd0e9f
--- /dev/null
+++ b/general/datasets/Ucla_ctb6b6ctf2_liver_male/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 53, Name: UCLA CTB6B6CTF2 Liver Female mlratio **
\ No newline at end of file
diff --git a/general/datasets/Ucla_ctb6b6ctf2_muscle_2005/summary.rtf b/general/datasets/Ucla_ctb6b6ctf2_muscle_2005/summary.rtf
new file mode 100644
index 0000000..f1e6b81
--- /dev/null
+++ b/general/datasets/Ucla_ctb6b6ctf2_muscle_2005/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 54, Name: UCLA CTB6B6CTF2 Muscle Female mlratio **
diff --git a/general/datasets/Ucla_ctb6b6ctf2_muscle_female/summary.rtf b/general/datasets/Ucla_ctb6b6ctf2_muscle_female/summary.rtf
new file mode 100644
index 0000000..f1e6b81
--- /dev/null
+++ b/general/datasets/Ucla_ctb6b6ctf2_muscle_female/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 54, Name: UCLA CTB6B6CTF2 Muscle Female mlratio **
diff --git a/general/datasets/Ucla_ctb6b6ctf2_muscle_male/summary.rtf b/general/datasets/Ucla_ctb6b6ctf2_muscle_male/summary.rtf
new file mode 100644
index 0000000..f1e6b81
--- /dev/null
+++ b/general/datasets/Ucla_ctb6b6ctf2_muscle_male/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 54, Name: UCLA CTB6B6CTF2 Muscle Female mlratio **
diff --git a/general/datasets/Ucla_cxb_aor_jan16/citation.rtf b/general/datasets/Ucla_cxb_aor_jan16/citation.rtf
new file mode 100644
index 0000000..6d383f0
--- /dev/null
+++ b/general/datasets/Ucla_cxb_aor_jan16/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Bennett BJ, Davis RC, Civelek M, Orozco L et al. Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains. PLoS Genet 2015 Dec 22;11(12):e1005711. PMID: 26694027
+
diff --git a/general/datasets/Ucla_cxb_aor_jan16/contributors.rtf b/general/datasets/Ucla_cxb_aor_jan16/contributors.rtf
new file mode 100644
index 0000000..8450813
--- /dev/null
+++ b/general/datasets/Ucla_cxb_aor_jan16/contributors.rtf
@@ -0,0 +1 @@
+Lusis AJ, Bennett B, Davis R
diff --git a/general/datasets/Ucla_cxb_aor_jan16/experiment-design.rtf b/general/datasets/Ucla_cxb_aor_jan16/experiment-design.rtf
new file mode 100644
index 0000000..1113b37
--- /dev/null
+++ b/general/datasets/Ucla_cxb_aor_jan16/experiment-design.rtf
@@ -0,0 +1 @@
+GWAS for expression in aortas of F1 offspring of inbred strains crossed with C57BL/6J carrying ApoE-Leiden and CETP transgenes fed chow diet for 8 weeks followed by Western diet for 16 weeks
diff --git a/general/datasets/Ucla_cxb_aor_jan16/platform.rtf b/general/datasets/Ucla_cxb_aor_jan16/platform.rtf
new file mode 100644
index 0000000..41439e8
--- /dev/null
+++ b/general/datasets/Ucla_cxb_aor_jan16/platform.rtf
@@ -0,0 +1 @@
+GPL11180 HT_MG-430_PM] Affymetrix HT MG-430 PM Array Plate
diff --git a/general/datasets/Ucla_cxb_aor_jan16/specifics.rtf b/general/datasets/Ucla_cxb_aor_jan16/specifics.rtf
new file mode 100644
index 0000000..20dd05b
--- /dev/null
+++ b/general/datasets/Ucla_cxb_aor_jan16/specifics.rtf
@@ -0,0 +1 @@
+Group CXB
\ No newline at end of file
diff --git a/general/datasets/Ucla_cxb_aor_jan16/summary.rtf b/general/datasets/Ucla_cxb_aor_jan16/summary.rtf
new file mode 100644
index 0000000..59e49a1
--- /dev/null
+++ b/general/datasets/Ucla_cxb_aor_jan16/summary.rtf
@@ -0,0 +1 @@
+Identify genes in the aorta whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. 104 of these strains were bred onto a C57BL/6J background carrying transgenes for both ApoE-Leiden and cholesteryl ester transfer protein (CETP). The RMA values of genes were used for genome wide association as described in Davis et al PLOS Genetics 2015. These data are used to identify candidate genes at loci associated with atherosclerotic lesion size.
diff --git a/general/datasets/Ucla_cxb_liv_jan16/citation.rtf b/general/datasets/Ucla_cxb_liv_jan16/citation.rtf
new file mode 100644
index 0000000..6d383f0
--- /dev/null
+++ b/general/datasets/Ucla_cxb_liv_jan16/citation.rtf
@@ -0,0 +1,3 @@
+
+ - Bennett BJ, Davis RC, Civelek M, Orozco L et al. Genetic Architecture of Atherosclerosis in Mice: A Systems Genetics Analysis of Common Inbred Strains. PLoS Genet 2015 Dec 22;11(12):e1005711. PMID: 26694027
+
diff --git a/general/datasets/Ucla_cxb_liv_jan16/contributors.rtf b/general/datasets/Ucla_cxb_liv_jan16/contributors.rtf
new file mode 100644
index 0000000..8450813
--- /dev/null
+++ b/general/datasets/Ucla_cxb_liv_jan16/contributors.rtf
@@ -0,0 +1 @@
+Lusis AJ, Bennett B, Davis R
diff --git a/general/datasets/Ucla_cxb_liv_jan16/experiment-design.rtf b/general/datasets/Ucla_cxb_liv_jan16/experiment-design.rtf
new file mode 100644
index 0000000..715a1a3
--- /dev/null
+++ b/general/datasets/Ucla_cxb_liv_jan16/experiment-design.rtf
@@ -0,0 +1 @@
+GWAS for expression in livers of F1 offspring of inbred strains crossed with C57BL/6J carrying ApoE-Leiden and CETP transgenes fed chow diet for 8 weeks followed by Western diet for 16 weeks
diff --git a/general/datasets/Ucla_cxb_liv_jan16/platform.rtf b/general/datasets/Ucla_cxb_liv_jan16/platform.rtf
new file mode 100644
index 0000000..7659aeb
--- /dev/null
+++ b/general/datasets/Ucla_cxb_liv_jan16/platform.rtf
@@ -0,0 +1 @@
+GPL11180 HT_MG-430_PM] Affymetrix HT MG-430 PM Array Plate
diff --git a/general/datasets/Ucla_cxb_liv_jan16/specifics.rtf b/general/datasets/Ucla_cxb_liv_jan16/specifics.rtf
new file mode 100644
index 0000000..20dd05b
--- /dev/null
+++ b/general/datasets/Ucla_cxb_liv_jan16/specifics.rtf
@@ -0,0 +1 @@
+Group CXB
\ No newline at end of file
diff --git a/general/datasets/Ucla_cxb_liv_jan16/summary.rtf b/general/datasets/Ucla_cxb_liv_jan16/summary.rtf
new file mode 100644
index 0000000..9ffc1be
--- /dev/null
+++ b/general/datasets/Ucla_cxb_liv_jan16/summary.rtf
@@ -0,0 +1 @@
+Identify genes in the liver whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. 104 of these strains were bred onto a C57BL/6J background carrying transgenes for both ApoE-Leiden and cholesteryl ester transfer protein (CETP). The RMA values of genes were used for genome wide association as described in Davis et al PLOS Genetics 2015. These data are used to identify candidate genes at loci associated with atherosclerotic lesion size.
diff --git a/general/datasets/Ucla_mdp_femur_0113_rsn/acknowledgment.rtf b/general/datasets/Ucla_mdp_femur_0113_rsn/acknowledgment.rtf
new file mode 100644
index 0000000..841713a
--- /dev/null
+++ b/general/datasets/Ucla_mdp_femur_0113_rsn/acknowledgment.rtf
@@ -0,0 +1 @@
+Calabrese G, Bennett BJ, Orozco L, Kang HM, Eskin E, Dombret C, De Backer O, Lusis AJ, Farber CR.
diff --git a/general/datasets/Ucla_mdp_femur_0113_rsn/citation.rtf b/general/datasets/Ucla_mdp_femur_0113_rsn/citation.rtf
new file mode 100644
index 0000000..a3b7aa6
--- /dev/null
+++ b/general/datasets/Ucla_mdp_femur_0113_rsn/citation.rtf
@@ -0,0 +1 @@
+Farber CR, Bennett BJ, Orozco L, Zou W et al. Mouse genome-wide association and systems genetics identify Asxl2 as a regulator of bone mineral density and osteoclastogenesis. PLoS Genet 2011 Apr;7(4):e1002038. PMID: 21490954 Calabrese G, Bennett BJ, Orozco L, Kang HM et al. Systems genetic analysis of osteoblast-lineage cells. PLoS Genet 2012 Dec;8(12):e1003150. PMID: 23300464.
diff --git a/general/datasets/Ucla_mdp_femur_0113_rsn/experiment-design.rtf b/general/datasets/Ucla_mdp_femur_0113_rsn/experiment-design.rtf
new file mode 100644
index 0000000..6a72392
--- /dev/null
+++ b/general/datasets/Ucla_mdp_femur_0113_rsn/experiment-design.rtf
@@ -0,0 +1 @@
+RNA from cortical bone (femoral diaphysis free of marrow) were profiled from 99 Hybrid Mouse Diversity Panel strains were profiled. Sixteen-week old male mice were used in this study. A total of 1-3 mice per strain were arrayed.
diff --git a/general/datasets/Ucla_mdp_femur_0113_rsn/experiment-type.rtf b/general/datasets/Ucla_mdp_femur_0113_rsn/experiment-type.rtf
new file mode 100644
index 0000000..c29a175
--- /dev/null
+++ b/general/datasets/Ucla_mdp_femur_0113_rsn/experiment-type.rtf
@@ -0,0 +1 @@
+RNA from cortical bone (femoral diaphysis free of marrow) were profiled from 99 Hybrid Mouse Diversity Panel strains were profiled. Sixteen-week old male mice were used in this study. A total of 1-3 mice per strain were arrayed.
\ No newline at end of file
diff --git a/general/datasets/Ucla_mdp_femur_0113_rsn/platform.rtf b/general/datasets/Ucla_mdp_femur_0113_rsn/platform.rtf
new file mode 100644
index 0000000..578985c
--- /dev/null
+++ b/general/datasets/Ucla_mdp_femur_0113_rsn/platform.rtf
@@ -0,0 +1 @@
+Illumina mouse-6 v1.1 expression beadchip
diff --git a/general/datasets/Ucla_mdp_femur_0113_rsn/processing.rtf b/general/datasets/Ucla_mdp_femur_0113_rsn/processing.rtf
new file mode 100644
index 0000000..9f66d05
--- /dev/null
+++ b/general/datasets/Ucla_mdp_femur_0113_rsn/processing.rtf
@@ -0,0 +1 @@
+The expression values were transformed using the Variance Stabilizing Transformation (VST), and normalized with the Robust Spline Normalization (RSN) algorithm using the LumiR R package. After normalization, the ComBat software was used to adjust for batch effects using an empirical Bayes method.
diff --git a/general/datasets/Ucla_mdp_femur_0113_rsn/summary.rtf b/general/datasets/Ucla_mdp_femur_0113_rsn/summary.rtf
new file mode 100644
index 0000000..df75fa6
--- /dev/null
+++ b/general/datasets/Ucla_mdp_femur_0113_rsn/summary.rtf
@@ -0,0 +1 @@
+Significant advances have been made in the discovery of genes affecting bone mineral density (BMD); however, our understanding of its genetic basis remains incomplete. In the current study, genome-wide association (GWA) and co-expression network analysis was used in the recently described Hybrid Mouse Diversity Panel (HMDP) to identify and functionally characterize novel BMD genes. In the HMDP, a GWA of total body, spinal and femoral BMD revealed four significant associations (-log10P > 5.39) affecting at least one BMD trait on chromosomes (Chrs.) 7, 11, 12 and 17. The associations implicated a total of 163 genes with each association harboring between 14 and 112 genes. This list was reduced to 26 functional candidates by identifying those genes that were regulated by local eQTL in bone or harbored potentially functional non-synonymous (NS) SNPs. This analysis revealed that the most significant BMD SNP on Chr. 12 was a NS SNP in the additional sex combs like-2 (Asxl2) gene that was predicted to be functional. The involvement of Asxl2 in the regulation of bone mass was confirmed by the observation that Asxl2 knockout mice had reduced BMD. To begin to unravel the mechanism though which Asxl2 influenced BMD, a gene co-expression network was created using cortical bone gene expression microarray data from the HMDP strains. Asxl2 was identified as a member of a co-expression gene module enriched for genes involved in the differentiation of myeloid cells. In bone, osteoclasts are bone-resorbing cell of myeloid origin, suggesting that Asxl2 may play a role in osteoclast differentiation. In agreement, the knockdown of Asxl2 in bone marrow macrophages impaired their ability to form osteoclasts. This study identifies a new regulator of BMD and osteoclastogenesis and highlights the power of GWA and systems genetics in the mouse for dissecting complex genetic traits.
diff --git a/general/datasets/Uconn_rgc_rseq_log2_0918/specifics.rtf b/general/datasets/Uconn_rgc_rseq_log2_0918/specifics.rtf
new file mode 100644
index 0000000..843d470
--- /dev/null
+++ b/general/datasets/Uconn_rgc_rseq_log2_0918/specifics.rtf
@@ -0,0 +1 @@
+Log2
\ No newline at end of file
diff --git a/general/datasets/Uconn_rgc_rseq_log2_0918/summary.rtf b/general/datasets/Uconn_rgc_rseq_log2_0918/summary.rtf
new file mode 100644
index 0000000..aab94b8
--- /dev/null
+++ b/general/datasets/Uconn_rgc_rseq_log2_0918/summary.rtf
@@ -0,0 +1,3 @@
+Retinal ganglion cells (RGCs) convey the major output of information collected from the eye to the brain. Thirty subtypes of RGCs have been identified to date. Here, we analyze 6225 RGCs (average of 5000 genes per cell) from right and left eyes by single-cell RNA-seq and classify them into 40 subtypes using clustering algorithms. We identify additional subtypes and markers, as well as transcription factors predicted to cooperate in specifying RGC subtypes. Zic1, a marker of the right eye-enriched subtype, is validated by immunostaining in situ. Runx1 and Fst, the markers of other subtypes, are validated in purified RGCs by fluorescent in situ hybridization (FISH) and immunostaining. We show the extent of gene expression variability needed for subtype segregation, and we show a hierarchy in diversification from a cell-type population to subtypes. Finally, we present a website for comparing the gene expression of RGC subtypes.
+
+https://www.nature.com/articles/s41467-018-05134-3
diff --git a/general/datasets/Uconn_rgc_rseq_r_0918/specifics.rtf b/general/datasets/Uconn_rgc_rseq_r_0918/specifics.rtf
new file mode 100644
index 0000000..8c82808
--- /dev/null
+++ b/general/datasets/Uconn_rgc_rseq_r_0918/specifics.rtf
@@ -0,0 +1 @@
+Raw data
\ No newline at end of file
diff --git a/general/datasets/Uconn_rgc_rseq_r_0918/summary.rtf b/general/datasets/Uconn_rgc_rseq_r_0918/summary.rtf
new file mode 100644
index 0000000..aab94b8
--- /dev/null
+++ b/general/datasets/Uconn_rgc_rseq_r_0918/summary.rtf
@@ -0,0 +1,3 @@
+Retinal ganglion cells (RGCs) convey the major output of information collected from the eye to the brain. Thirty subtypes of RGCs have been identified to date. Here, we analyze 6225 RGCs (average of 5000 genes per cell) from right and left eyes by single-cell RNA-seq and classify them into 40 subtypes using clustering algorithms. We identify additional subtypes and markers, as well as transcription factors predicted to cooperate in specifying RGC subtypes. Zic1, a marker of the right eye-enriched subtype, is validated by immunostaining in situ. Runx1 and Fst, the markers of other subtypes, are validated in purified RGCs by fluorescent in situ hybridization (FISH) and immunostaining. We show the extent of gene expression variability needed for subtype segregation, and we show a hierarchy in diversification from a cell-type population to subtypes. Finally, we present a website for comparing the gene expression of RGC subtypes.
+
+https://www.nature.com/articles/s41467-018-05134-3
diff --git a/general/datasets/Uconn_rgc_rseq_s_0918/specifics.rtf b/general/datasets/Uconn_rgc_rseq_s_0918/specifics.rtf
new file mode 100644
index 0000000..394e70a
--- /dev/null
+++ b/general/datasets/Uconn_rgc_rseq_s_0918/specifics.rtf
@@ -0,0 +1 @@
+Siamak normalization mapped to our DB
\ No newline at end of file
diff --git a/general/datasets/Uconn_rgc_rseq_s_0918/summary.rtf b/general/datasets/Uconn_rgc_rseq_s_0918/summary.rtf
new file mode 100644
index 0000000..aab94b8
--- /dev/null
+++ b/general/datasets/Uconn_rgc_rseq_s_0918/summary.rtf
@@ -0,0 +1,3 @@
+Retinal ganglion cells (RGCs) convey the major output of information collected from the eye to the brain. Thirty subtypes of RGCs have been identified to date. Here, we analyze 6225 RGCs (average of 5000 genes per cell) from right and left eyes by single-cell RNA-seq and classify them into 40 subtypes using clustering algorithms. We identify additional subtypes and markers, as well as transcription factors predicted to cooperate in specifying RGC subtypes. Zic1, a marker of the right eye-enriched subtype, is validated by immunostaining in situ. Runx1 and Fst, the markers of other subtypes, are validated in purified RGCs by fluorescent in situ hybridization (FISH) and immunostaining. We show the extent of gene expression variability needed for subtype segregation, and we show a hierarchy in diversification from a cell-type population to subtypes. Finally, we present a website for comparing the gene expression of RGC subtypes.
+
+https://www.nature.com/articles/s41467-018-05134-3
diff --git a/general/datasets/Ucsd_ail_hip_rna_seq_0418/citation.rtf b/general/datasets/Ucsd_ail_hip_rna_seq_0418/citation.rtf
new file mode 100644
index 0000000..d31add6
--- /dev/null
+++ b/general/datasets/Ucsd_ail_hip_rna_seq_0418/citation.rtf
@@ -0,0 +1 @@
+Genome wide association study of behavioral, physiological and gene expression traits in a multigenerational mouse intercross
diff --git a/general/datasets/Ucsd_ail_hip_rna_seq_0418/contributors.rtf b/general/datasets/Ucsd_ail_hip_rna_seq_0418/contributors.rtf
new file mode 100644
index 0000000..77f2c40
--- /dev/null
+++ b/general/datasets/Ucsd_ail_hip_rna_seq_0418/contributors.rtf
@@ -0,0 +1 @@
+Natalia M. Gonzales, Jungkyun Seo, Ana Isabel Hernandez-Cordero, Celine L. St. Pierre, Jennifer S. Gregory, Margaret G. Distler, Mark Abney, Stefan Canzar, Arimantas Lionikas, Abraham A. Palmer
diff --git a/general/datasets/Ucsd_ail_hip_rna_seq_0418/specifics.rtf b/general/datasets/Ucsd_ail_hip_rna_seq_0418/specifics.rtf
new file mode 100644
index 0000000..f3a4dfd
--- /dev/null
+++ b/general/datasets/Ucsd_ail_hip_rna_seq_0418/specifics.rtf
@@ -0,0 +1 @@
+Hippocampus
\ No newline at end of file
diff --git a/general/datasets/Ucsd_ail_hip_rna_seq_0418/summary.rtf b/general/datasets/Ucsd_ail_hip_rna_seq_0418/summary.rtf
new file mode 100644
index 0000000..37e2d16
--- /dev/null
+++ b/general/datasets/Ucsd_ail_hip_rna_seq_0418/summary.rtf
@@ -0,0 +1 @@
+Genome wide association analyses (GWAS) in model organisms have numerous advantages compared to human GWAS, including the ability to use populations with well-defined genetic diversity, the ability to collect tissue for gene expression analysis and the ability to perform experimental manipulations. We examined behavioral, physiological, and gene expression traits in 1,063 male and female mice from a 50-generation intercross between two inbred strains (LG/J and SM/J). We used genotyping by sequencing in conjunction with whole genome sequence data from the two founder strains to obtain genotypes at 4.3 million SNPs. As expected, all alleles were common (mean MAF=0.35) and linkage disequilibrium degraded rapidly, providing excellent power and sub-megabase mapping precision. We identified 126 genome-wide significant loci for 50 traits and integrated this information with 7,081 cis-eQTLs and 1,476 trans-eQTLs identified in hippocampus, striatum and prefrontal cortex. We replicated several loci that were identified using an earlier generation of this intercross, including an association between locomotor activity and a locus containing a single gene, Csmd1. We also showed that Csmd1 mutant mice recapitulated the locomotor phenotype. Our results demonstrate the utility of this population, identify numerous novel associations, and provide examples of replication in an independent cohort, which is customary in human genetics, and replication by experimental manipulation, which is a unique advantage of model organisms.
diff --git a/general/datasets/Ucsd_ail_hip_rna_seq_log2_0418/citation.rtf b/general/datasets/Ucsd_ail_hip_rna_seq_log2_0418/citation.rtf
new file mode 100644
index 0000000..d31add6
--- /dev/null
+++ b/general/datasets/Ucsd_ail_hip_rna_seq_log2_0418/citation.rtf
@@ -0,0 +1 @@
+Genome wide association study of behavioral, physiological and gene expression traits in a multigenerational mouse intercross
diff --git a/general/datasets/Ucsd_ail_hip_rna_seq_log2_0418/contributors.rtf b/general/datasets/Ucsd_ail_hip_rna_seq_log2_0418/contributors.rtf
new file mode 100644
index 0000000..77f2c40
--- /dev/null
+++ b/general/datasets/Ucsd_ail_hip_rna_seq_log2_0418/contributors.rtf
@@ -0,0 +1 @@
+Natalia M. Gonzales, Jungkyun Seo, Ana Isabel Hernandez-Cordero, Celine L. St. Pierre, Jennifer S. Gregory, Margaret G. Distler, Mark Abney, Stefan Canzar, Arimantas Lionikas, Abraham A. Palmer
diff --git a/general/datasets/Ucsd_ail_hip_rna_seq_log2_0418/specifics.rtf b/general/datasets/Ucsd_ail_hip_rna_seq_log2_0418/specifics.rtf
new file mode 100644
index 0000000..843d470
--- /dev/null
+++ b/general/datasets/Ucsd_ail_hip_rna_seq_log2_0418/specifics.rtf
@@ -0,0 +1 @@
+Log2
\ No newline at end of file
diff --git a/general/datasets/Ucsd_ail_hip_rna_seq_log2_0418/summary.rtf b/general/datasets/Ucsd_ail_hip_rna_seq_log2_0418/summary.rtf
new file mode 100644
index 0000000..37e2d16
--- /dev/null
+++ b/general/datasets/Ucsd_ail_hip_rna_seq_log2_0418/summary.rtf
@@ -0,0 +1 @@
+Genome wide association analyses (GWAS) in model organisms have numerous advantages compared to human GWAS, including the ability to use populations with well-defined genetic diversity, the ability to collect tissue for gene expression analysis and the ability to perform experimental manipulations. We examined behavioral, physiological, and gene expression traits in 1,063 male and female mice from a 50-generation intercross between two inbred strains (LG/J and SM/J). We used genotyping by sequencing in conjunction with whole genome sequence data from the two founder strains to obtain genotypes at 4.3 million SNPs. As expected, all alleles were common (mean MAF=0.35) and linkage disequilibrium degraded rapidly, providing excellent power and sub-megabase mapping precision. We identified 126 genome-wide significant loci for 50 traits and integrated this information with 7,081 cis-eQTLs and 1,476 trans-eQTLs identified in hippocampus, striatum and prefrontal cortex. We replicated several loci that were identified using an earlier generation of this intercross, including an association between locomotor activity and a locus containing a single gene, Csmd1. We also showed that Csmd1 mutant mice recapitulated the locomotor phenotype. Our results demonstrate the utility of this population, identify numerous novel associations, and provide examples of replication in an independent cohort, which is customary in human genetics, and replication by experimental manipulation, which is a unique advantage of model organisms.
diff --git a/general/datasets/Ucsd_ail_pfc_rna_seq_0418/citation.rtf b/general/datasets/Ucsd_ail_pfc_rna_seq_0418/citation.rtf
new file mode 100644
index 0000000..d31add6
--- /dev/null
+++ b/general/datasets/Ucsd_ail_pfc_rna_seq_0418/citation.rtf
@@ -0,0 +1 @@
+Genome wide association study of behavioral, physiological and gene expression traits in a multigenerational mouse intercross
diff --git a/general/datasets/Ucsd_ail_pfc_rna_seq_0418/contributors.rtf b/general/datasets/Ucsd_ail_pfc_rna_seq_0418/contributors.rtf
new file mode 100644
index 0000000..77f2c40
--- /dev/null
+++ b/general/datasets/Ucsd_ail_pfc_rna_seq_0418/contributors.rtf
@@ -0,0 +1 @@
+Natalia M. Gonzales, Jungkyun Seo, Ana Isabel Hernandez-Cordero, Celine L. St. Pierre, Jennifer S. Gregory, Margaret G. Distler, Mark Abney, Stefan Canzar, Arimantas Lionikas, Abraham A. Palmer
diff --git a/general/datasets/Ucsd_ail_pfc_rna_seq_0418/specifics.rtf b/general/datasets/Ucsd_ail_pfc_rna_seq_0418/specifics.rtf
new file mode 100644
index 0000000..30656c6
--- /dev/null
+++ b/general/datasets/Ucsd_ail_pfc_rna_seq_0418/specifics.rtf
@@ -0,0 +1 @@
+Prefrontal Cortex
\ No newline at end of file
diff --git a/general/datasets/Ucsd_ail_pfc_rna_seq_0418/summary.rtf b/general/datasets/Ucsd_ail_pfc_rna_seq_0418/summary.rtf
new file mode 100644
index 0000000..37e2d16
--- /dev/null
+++ b/general/datasets/Ucsd_ail_pfc_rna_seq_0418/summary.rtf
@@ -0,0 +1 @@
+Genome wide association analyses (GWAS) in model organisms have numerous advantages compared to human GWAS, including the ability to use populations with well-defined genetic diversity, the ability to collect tissue for gene expression analysis and the ability to perform experimental manipulations. We examined behavioral, physiological, and gene expression traits in 1,063 male and female mice from a 50-generation intercross between two inbred strains (LG/J and SM/J). We used genotyping by sequencing in conjunction with whole genome sequence data from the two founder strains to obtain genotypes at 4.3 million SNPs. As expected, all alleles were common (mean MAF=0.35) and linkage disequilibrium degraded rapidly, providing excellent power and sub-megabase mapping precision. We identified 126 genome-wide significant loci for 50 traits and integrated this information with 7,081 cis-eQTLs and 1,476 trans-eQTLs identified in hippocampus, striatum and prefrontal cortex. We replicated several loci that were identified using an earlier generation of this intercross, including an association between locomotor activity and a locus containing a single gene, Csmd1. We also showed that Csmd1 mutant mice recapitulated the locomotor phenotype. Our results demonstrate the utility of this population, identify numerous novel associations, and provide examples of replication in an independent cohort, which is customary in human genetics, and replication by experimental manipulation, which is a unique advantage of model organisms.
diff --git a/general/datasets/Ucsd_ail_pfc_rna_seq_log2_0418/citation.rtf b/general/datasets/Ucsd_ail_pfc_rna_seq_log2_0418/citation.rtf
new file mode 100644
index 0000000..d31add6
--- /dev/null
+++ b/general/datasets/Ucsd_ail_pfc_rna_seq_log2_0418/citation.rtf
@@ -0,0 +1 @@
+Genome wide association study of behavioral, physiological and gene expression traits in a multigenerational mouse intercross
diff --git a/general/datasets/Ucsd_ail_pfc_rna_seq_log2_0418/contributors.rtf b/general/datasets/Ucsd_ail_pfc_rna_seq_log2_0418/contributors.rtf
new file mode 100644
index 0000000..77f2c40
--- /dev/null
+++ b/general/datasets/Ucsd_ail_pfc_rna_seq_log2_0418/contributors.rtf
@@ -0,0 +1 @@
+Natalia M. Gonzales, Jungkyun Seo, Ana Isabel Hernandez-Cordero, Celine L. St. Pierre, Jennifer S. Gregory, Margaret G. Distler, Mark Abney, Stefan Canzar, Arimantas Lionikas, Abraham A. Palmer
diff --git a/general/datasets/Ucsd_ail_pfc_rna_seq_log2_0418/specifics.rtf b/general/datasets/Ucsd_ail_pfc_rna_seq_log2_0418/specifics.rtf
new file mode 100644
index 0000000..843d470
--- /dev/null
+++ b/general/datasets/Ucsd_ail_pfc_rna_seq_log2_0418/specifics.rtf
@@ -0,0 +1 @@
+Log2
\ No newline at end of file
diff --git a/general/datasets/Ucsd_ail_pfc_rna_seq_log2_0418/summary.rtf b/general/datasets/Ucsd_ail_pfc_rna_seq_log2_0418/summary.rtf
new file mode 100644
index 0000000..37e2d16
--- /dev/null
+++ b/general/datasets/Ucsd_ail_pfc_rna_seq_log2_0418/summary.rtf
@@ -0,0 +1 @@
+Genome wide association analyses (GWAS) in model organisms have numerous advantages compared to human GWAS, including the ability to use populations with well-defined genetic diversity, the ability to collect tissue for gene expression analysis and the ability to perform experimental manipulations. We examined behavioral, physiological, and gene expression traits in 1,063 male and female mice from a 50-generation intercross between two inbred strains (LG/J and SM/J). We used genotyping by sequencing in conjunction with whole genome sequence data from the two founder strains to obtain genotypes at 4.3 million SNPs. As expected, all alleles were common (mean MAF=0.35) and linkage disequilibrium degraded rapidly, providing excellent power and sub-megabase mapping precision. We identified 126 genome-wide significant loci for 50 traits and integrated this information with 7,081 cis-eQTLs and 1,476 trans-eQTLs identified in hippocampus, striatum and prefrontal cortex. We replicated several loci that were identified using an earlier generation of this intercross, including an association between locomotor activity and a locus containing a single gene, Csmd1. We also showed that Csmd1 mutant mice recapitulated the locomotor phenotype. Our results demonstrate the utility of this population, identify numerous novel associations, and provide examples of replication in an independent cohort, which is customary in human genetics, and replication by experimental manipulation, which is a unique advantage of model organisms.
diff --git a/general/datasets/Ucsd_ail_str_rna_seq_0418/citation.rtf b/general/datasets/Ucsd_ail_str_rna_seq_0418/citation.rtf
new file mode 100644
index 0000000..d31add6
--- /dev/null
+++ b/general/datasets/Ucsd_ail_str_rna_seq_0418/citation.rtf
@@ -0,0 +1 @@
+Genome wide association study of behavioral, physiological and gene expression traits in a multigenerational mouse intercross
diff --git a/general/datasets/Ucsd_ail_str_rna_seq_0418/contributors.rtf b/general/datasets/Ucsd_ail_str_rna_seq_0418/contributors.rtf
new file mode 100644
index 0000000..77f2c40
--- /dev/null
+++ b/general/datasets/Ucsd_ail_str_rna_seq_0418/contributors.rtf
@@ -0,0 +1 @@
+Natalia M. Gonzales, Jungkyun Seo, Ana Isabel Hernandez-Cordero, Celine L. St. Pierre, Jennifer S. Gregory, Margaret G. Distler, Mark Abney, Stefan Canzar, Arimantas Lionikas, Abraham A. Palmer
diff --git a/general/datasets/Ucsd_ail_str_rna_seq_0418/specifics.rtf b/general/datasets/Ucsd_ail_str_rna_seq_0418/specifics.rtf
new file mode 100644
index 0000000..fe51d98
--- /dev/null
+++ b/general/datasets/Ucsd_ail_str_rna_seq_0418/specifics.rtf
@@ -0,0 +1 @@
+Striatum
\ No newline at end of file
diff --git a/general/datasets/Ucsd_ail_str_rna_seq_0418/summary.rtf b/general/datasets/Ucsd_ail_str_rna_seq_0418/summary.rtf
new file mode 100644
index 0000000..37e2d16
--- /dev/null
+++ b/general/datasets/Ucsd_ail_str_rna_seq_0418/summary.rtf
@@ -0,0 +1 @@
+Genome wide association analyses (GWAS) in model organisms have numerous advantages compared to human GWAS, including the ability to use populations with well-defined genetic diversity, the ability to collect tissue for gene expression analysis and the ability to perform experimental manipulations. We examined behavioral, physiological, and gene expression traits in 1,063 male and female mice from a 50-generation intercross between two inbred strains (LG/J and SM/J). We used genotyping by sequencing in conjunction with whole genome sequence data from the two founder strains to obtain genotypes at 4.3 million SNPs. As expected, all alleles were common (mean MAF=0.35) and linkage disequilibrium degraded rapidly, providing excellent power and sub-megabase mapping precision. We identified 126 genome-wide significant loci for 50 traits and integrated this information with 7,081 cis-eQTLs and 1,476 trans-eQTLs identified in hippocampus, striatum and prefrontal cortex. We replicated several loci that were identified using an earlier generation of this intercross, including an association between locomotor activity and a locus containing a single gene, Csmd1. We also showed that Csmd1 mutant mice recapitulated the locomotor phenotype. Our results demonstrate the utility of this population, identify numerous novel associations, and provide examples of replication in an independent cohort, which is customary in human genetics, and replication by experimental manipulation, which is a unique advantage of model organisms.
diff --git a/general/datasets/Ucsd_ail_str_rna_seq_log2_0418/citation.rtf b/general/datasets/Ucsd_ail_str_rna_seq_log2_0418/citation.rtf
new file mode 100644
index 0000000..d31add6
--- /dev/null
+++ b/general/datasets/Ucsd_ail_str_rna_seq_log2_0418/citation.rtf
@@ -0,0 +1 @@
+Genome wide association study of behavioral, physiological and gene expression traits in a multigenerational mouse intercross
diff --git a/general/datasets/Ucsd_ail_str_rna_seq_log2_0418/contributors.rtf b/general/datasets/Ucsd_ail_str_rna_seq_log2_0418/contributors.rtf
new file mode 100644
index 0000000..77f2c40
--- /dev/null
+++ b/general/datasets/Ucsd_ail_str_rna_seq_log2_0418/contributors.rtf
@@ -0,0 +1 @@
+Natalia M. Gonzales, Jungkyun Seo, Ana Isabel Hernandez-Cordero, Celine L. St. Pierre, Jennifer S. Gregory, Margaret G. Distler, Mark Abney, Stefan Canzar, Arimantas Lionikas, Abraham A. Palmer
diff --git a/general/datasets/Ucsd_ail_str_rna_seq_log2_0418/specifics.rtf b/general/datasets/Ucsd_ail_str_rna_seq_log2_0418/specifics.rtf
new file mode 100644
index 0000000..843d470
--- /dev/null
+++ b/general/datasets/Ucsd_ail_str_rna_seq_log2_0418/specifics.rtf
@@ -0,0 +1 @@
+Log2
\ No newline at end of file
diff --git a/general/datasets/Ucsd_ail_str_rna_seq_log2_0418/summary.rtf b/general/datasets/Ucsd_ail_str_rna_seq_log2_0418/summary.rtf
new file mode 100644
index 0000000..37e2d16
--- /dev/null
+++ b/general/datasets/Ucsd_ail_str_rna_seq_log2_0418/summary.rtf
@@ -0,0 +1 @@
+Genome wide association analyses (GWAS) in model organisms have numerous advantages compared to human GWAS, including the ability to use populations with well-defined genetic diversity, the ability to collect tissue for gene expression analysis and the ability to perform experimental manipulations. We examined behavioral, physiological, and gene expression traits in 1,063 male and female mice from a 50-generation intercross between two inbred strains (LG/J and SM/J). We used genotyping by sequencing in conjunction with whole genome sequence data from the two founder strains to obtain genotypes at 4.3 million SNPs. As expected, all alleles were common (mean MAF=0.35) and linkage disequilibrium degraded rapidly, providing excellent power and sub-megabase mapping precision. We identified 126 genome-wide significant loci for 50 traits and integrated this information with 7,081 cis-eQTLs and 1,476 trans-eQTLs identified in hippocampus, striatum and prefrontal cortex. We replicated several loci that were identified using an earlier generation of this intercross, including an association between locomotor activity and a locus containing a single gene, Csmd1. We also showed that Csmd1 mutant mice recapitulated the locomotor phenotype. Our results demonstrate the utility of this population, identify numerous novel associations, and provide examples of replication in an independent cohort, which is customary in human genetics, and replication by experimental manipulation, which is a unique advantage of model organisms.
diff --git a/general/datasets/Ucsd_cfw_hip_rna_seq_0117/acknowledgment.rtf b/general/datasets/Ucsd_cfw_hip_rna_seq_0117/acknowledgment.rtf
new file mode 100644
index 0000000..24f8c40
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_hip_rna_seq_0117/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors wish to acknowledge technical assistance from: D. Godfrey, S. Lionikaite, V. Lionikaite, A.S. Lionikiene and J. Zekos as well as technical and intellectual input from M. Abney, J. Borevitz, K. Broman, N. Cai, R. Cheng, N. Cox, R. Davies, J. Flint, L. Goodstadt, P. Grabowski, B. Harr, E. Leffler, R. Mott, J. Nicod, J. Novembre, A. Price, M. Stephens, D. Weeks and X. Zhou. This project was funded by NIH R01GM097737 and P50DA037844 (A.A.P.), NIH T32DA07255 (C.C.P.), NIH T32GM07197 (N.M.G.), NIH R01AR056280 (D.A.B.), NIH R01AR060234 (C.L.A.-B.), the Fellowship from the Human Frontiers Science Program (P.C.) and the Howard Hughes Medical Institute (J.K.P.).
diff --git a/general/datasets/Ucsd_cfw_hip_rna_seq_0117/cases.rtf b/general/datasets/Ucsd_cfw_hip_rna_seq_0117/cases.rtf
new file mode 100644
index 0000000..97eed8a
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_hip_rna_seq_0117/cases.rtf
@@ -0,0 +1,3 @@
+Phenotype, genotype and RNA-seq gene expression data is available at
+
+http://datadryad.org/resource/doi:10.5061/dryad.2rs41
diff --git a/general/datasets/Ucsd_cfw_hip_rna_seq_0117/contributors.rtf b/general/datasets/Ucsd_cfw_hip_rna_seq_0117/contributors.rtf
new file mode 100644
index 0000000..24e5cd6
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_hip_rna_seq_0117/contributors.rtf
@@ -0,0 +1 @@
+A.A.P. conceived the study. C.C.P. and A.A.P. supervised the project. S.G. and P.C. designed and implemented the statistical and bioinformatics analyses with contributions from C.C.P., J.K.P. and A.A.P. N.M.G. designed and executed the RNA-seq and GBS protocols with assistance from E.A. and J.D. C.C.P. performed the behavioral phenotyping with assistance from E.L. and Y.J.P. A.L. performed the muscle and bone phenotyping with input from D.A.B. C.L.A.-B. performed the BMD phenotyping. C.C.P., S.G., P.C. and A.A.P. wrote the manuscript, with input from all co-authors.
diff --git a/general/datasets/Ucsd_cfw_hip_rna_seq_0117/processing.rtf b/general/datasets/Ucsd_cfw_hip_rna_seq_0117/processing.rtf
new file mode 100644
index 0000000..9c368fa
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_hip_rna_seq_0117/processing.rtf
@@ -0,0 +1 @@
+FPKM data were quantitle normalized for each ENSEMBL gene (mRNA) model (Identifiers such as ENSMUSG00000093778). Every gene/mRNA therefore has a mean expression value of 0 and a perfectly normal distribution, even if the original distribution was bimodal. The QQ plots is GN will be straight lines. There is no data at all on expression level in this original data set downloaded from http://dx.doi.org/10.5061/dryad.2rs41
diff --git a/general/datasets/Ucsd_cfw_hip_rna_seq_0117/specifics.rtf b/general/datasets/Ucsd_cfw_hip_rna_seq_0117/specifics.rtf
new file mode 100644
index 0000000..780e837
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_hip_rna_seq_0117/specifics.rtf
@@ -0,0 +1 @@
+Hippocampus
quantitle normalized
\ No newline at end of file
diff --git a/general/datasets/Ucsd_cfw_hip_rna_seq_0117/summary.rtf b/general/datasets/Ucsd_cfw_hip_rna_seq_0117/summary.rtf
new file mode 100644
index 0000000..0639fe7
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_hip_rna_seq_0117/summary.rtf
@@ -0,0 +1 @@
+Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice. Full article available here.
diff --git a/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/acknowledgment.rtf b/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/acknowledgment.rtf
new file mode 100644
index 0000000..24f8c40
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors wish to acknowledge technical assistance from: D. Godfrey, S. Lionikaite, V. Lionikaite, A.S. Lionikiene and J. Zekos as well as technical and intellectual input from M. Abney, J. Borevitz, K. Broman, N. Cai, R. Cheng, N. Cox, R. Davies, J. Flint, L. Goodstadt, P. Grabowski, B. Harr, E. Leffler, R. Mott, J. Nicod, J. Novembre, A. Price, M. Stephens, D. Weeks and X. Zhou. This project was funded by NIH R01GM097737 and P50DA037844 (A.A.P.), NIH T32DA07255 (C.C.P.), NIH T32GM07197 (N.M.G.), NIH R01AR056280 (D.A.B.), NIH R01AR060234 (C.L.A.-B.), the Fellowship from the Human Frontiers Science Program (P.C.) and the Howard Hughes Medical Institute (J.K.P.).
diff --git a/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/cases.rtf b/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/cases.rtf
new file mode 100644
index 0000000..97eed8a
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/cases.rtf
@@ -0,0 +1,3 @@
+Phenotype, genotype and RNA-seq gene expression data is available at
+
+http://datadryad.org/resource/doi:10.5061/dryad.2rs41
diff --git a/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/contributors.rtf b/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/contributors.rtf
new file mode 100644
index 0000000..24e5cd6
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/contributors.rtf
@@ -0,0 +1 @@
+A.A.P. conceived the study. C.C.P. and A.A.P. supervised the project. S.G. and P.C. designed and implemented the statistical and bioinformatics analyses with contributions from C.C.P., J.K.P. and A.A.P. N.M.G. designed and executed the RNA-seq and GBS protocols with assistance from E.A. and J.D. C.C.P. performed the behavioral phenotyping with assistance from E.L. and Y.J.P. A.L. performed the muscle and bone phenotyping with input from D.A.B. C.L.A.-B. performed the BMD phenotyping. C.C.P., S.G., P.C. and A.A.P. wrote the manuscript, with input from all co-authors.
diff --git a/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/processing.rtf b/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/processing.rtf
new file mode 100644
index 0000000..9c368fa
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/processing.rtf
@@ -0,0 +1 @@
+FPKM data were quantitle normalized for each ENSEMBL gene (mRNA) model (Identifiers such as ENSMUSG00000093778). Every gene/mRNA therefore has a mean expression value of 0 and a perfectly normal distribution, even if the original distribution was bimodal. The QQ plots is GN will be straight lines. There is no data at all on expression level in this original data set downloaded from http://dx.doi.org/10.5061/dryad.2rs41
diff --git a/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/specifics.rtf b/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/specifics.rtf
new file mode 100644
index 0000000..0ef5311
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/specifics.rtf
@@ -0,0 +1,5 @@
+Notes: We took the raw fpkm values provided by Apurva from file GN811-UCSD_CFW_RNA-Seq_HIP_raw_FPKM.txt.zip (11M) and transformed to log2 Z-scored. (GN811-UCSD_CFW_RNA-Seq_HIP_log2_ZScore.txt.zip (4.0M))
+
+RNA-Seq Log2 Z-score
+
+In general, the array data that we put in GeneNetwork has been logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having a standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/summary.rtf b/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/summary.rtf
new file mode 100644
index 0000000..0639fe7
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_hip_rna_seq_log2_0117/summary.rtf
@@ -0,0 +1 @@
+Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice. Full article available here.
diff --git a/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/acknowledgment.rtf b/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/acknowledgment.rtf
new file mode 100644
index 0000000..24f8c40
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors wish to acknowledge technical assistance from: D. Godfrey, S. Lionikaite, V. Lionikaite, A.S. Lionikiene and J. Zekos as well as technical and intellectual input from M. Abney, J. Borevitz, K. Broman, N. Cai, R. Cheng, N. Cox, R. Davies, J. Flint, L. Goodstadt, P. Grabowski, B. Harr, E. Leffler, R. Mott, J. Nicod, J. Novembre, A. Price, M. Stephens, D. Weeks and X. Zhou. This project was funded by NIH R01GM097737 and P50DA037844 (A.A.P.), NIH T32DA07255 (C.C.P.), NIH T32GM07197 (N.M.G.), NIH R01AR056280 (D.A.B.), NIH R01AR060234 (C.L.A.-B.), the Fellowship from the Human Frontiers Science Program (P.C.) and the Howard Hughes Medical Institute (J.K.P.).
diff --git a/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/cases.rtf b/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/cases.rtf
new file mode 100644
index 0000000..97eed8a
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/cases.rtf
@@ -0,0 +1,3 @@
+Phenotype, genotype and RNA-seq gene expression data is available at
+
+http://datadryad.org/resource/doi:10.5061/dryad.2rs41
diff --git a/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/contributors.rtf b/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/contributors.rtf
new file mode 100644
index 0000000..24e5cd6
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/contributors.rtf
@@ -0,0 +1 @@
+A.A.P. conceived the study. C.C.P. and A.A.P. supervised the project. S.G. and P.C. designed and implemented the statistical and bioinformatics analyses with contributions from C.C.P., J.K.P. and A.A.P. N.M.G. designed and executed the RNA-seq and GBS protocols with assistance from E.A. and J.D. C.C.P. performed the behavioral phenotyping with assistance from E.L. and Y.J.P. A.L. performed the muscle and bone phenotyping with input from D.A.B. C.L.A.-B. performed the BMD phenotyping. C.C.P., S.G., P.C. and A.A.P. wrote the manuscript, with input from all co-authors.
diff --git a/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/processing.rtf b/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/processing.rtf
new file mode 100644
index 0000000..9c368fa
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/processing.rtf
@@ -0,0 +1 @@
+FPKM data were quantitle normalized for each ENSEMBL gene (mRNA) model (Identifiers such as ENSMUSG00000093778). Every gene/mRNA therefore has a mean expression value of 0 and a perfectly normal distribution, even if the original distribution was bimodal. The QQ plots is GN will be straight lines. There is no data at all on expression level in this original data set downloaded from http://dx.doi.org/10.5061/dryad.2rs41
diff --git a/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/specifics.rtf b/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/specifics.rtf
new file mode 100644
index 0000000..30656c6
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/specifics.rtf
@@ -0,0 +1 @@
+Prefrontal Cortex
\ No newline at end of file
diff --git a/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/summary.rtf b/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/summary.rtf
new file mode 100644
index 0000000..0639fe7
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_pfc_rna_seq_0117/summary.rtf
@@ -0,0 +1 @@
+Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice. Full article available here.
diff --git a/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/acknowledgment.rtf b/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/acknowledgment.rtf
new file mode 100644
index 0000000..24f8c40
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors wish to acknowledge technical assistance from: D. Godfrey, S. Lionikaite, V. Lionikaite, A.S. Lionikiene and J. Zekos as well as technical and intellectual input from M. Abney, J. Borevitz, K. Broman, N. Cai, R. Cheng, N. Cox, R. Davies, J. Flint, L. Goodstadt, P. Grabowski, B. Harr, E. Leffler, R. Mott, J. Nicod, J. Novembre, A. Price, M. Stephens, D. Weeks and X. Zhou. This project was funded by NIH R01GM097737 and P50DA037844 (A.A.P.), NIH T32DA07255 (C.C.P.), NIH T32GM07197 (N.M.G.), NIH R01AR056280 (D.A.B.), NIH R01AR060234 (C.L.A.-B.), the Fellowship from the Human Frontiers Science Program (P.C.) and the Howard Hughes Medical Institute (J.K.P.).
diff --git a/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/cases.rtf b/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/cases.rtf
new file mode 100644
index 0000000..97eed8a
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/cases.rtf
@@ -0,0 +1,3 @@
+Phenotype, genotype and RNA-seq gene expression data is available at
+
+http://datadryad.org/resource/doi:10.5061/dryad.2rs41
diff --git a/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/contributors.rtf b/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/contributors.rtf
new file mode 100644
index 0000000..24e5cd6
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/contributors.rtf
@@ -0,0 +1 @@
+A.A.P. conceived the study. C.C.P. and A.A.P. supervised the project. S.G. and P.C. designed and implemented the statistical and bioinformatics analyses with contributions from C.C.P., J.K.P. and A.A.P. N.M.G. designed and executed the RNA-seq and GBS protocols with assistance from E.A. and J.D. C.C.P. performed the behavioral phenotyping with assistance from E.L. and Y.J.P. A.L. performed the muscle and bone phenotyping with input from D.A.B. C.L.A.-B. performed the BMD phenotyping. C.C.P., S.G., P.C. and A.A.P. wrote the manuscript, with input from all co-authors.
diff --git a/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/processing.rtf b/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/processing.rtf
new file mode 100644
index 0000000..9c368fa
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/processing.rtf
@@ -0,0 +1 @@
+FPKM data were quantitle normalized for each ENSEMBL gene (mRNA) model (Identifiers such as ENSMUSG00000093778). Every gene/mRNA therefore has a mean expression value of 0 and a perfectly normal distribution, even if the original distribution was bimodal. The QQ plots is GN will be straight lines. There is no data at all on expression level in this original data set downloaded from http://dx.doi.org/10.5061/dryad.2rs41
diff --git a/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/specifics.rtf b/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/specifics.rtf
new file mode 100644
index 0000000..6077f41
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/specifics.rtf
@@ -0,0 +1,3 @@
+RNA-Seq Log2 Z-score
+
+In general, the array data that we put in GeneNetwork has been logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/summary.rtf b/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/summary.rtf
new file mode 100644
index 0000000..0639fe7
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_pfc_rna_seq_log2_0117/summary.rtf
@@ -0,0 +1 @@
+Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice. Full article available here.
diff --git a/general/datasets/Ucsd_cfw_spl_rna_seq_0117/acknowledgment.rtf b/general/datasets/Ucsd_cfw_spl_rna_seq_0117/acknowledgment.rtf
new file mode 100644
index 0000000..24f8c40
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_spl_rna_seq_0117/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors wish to acknowledge technical assistance from: D. Godfrey, S. Lionikaite, V. Lionikaite, A.S. Lionikiene and J. Zekos as well as technical and intellectual input from M. Abney, J. Borevitz, K. Broman, N. Cai, R. Cheng, N. Cox, R. Davies, J. Flint, L. Goodstadt, P. Grabowski, B. Harr, E. Leffler, R. Mott, J. Nicod, J. Novembre, A. Price, M. Stephens, D. Weeks and X. Zhou. This project was funded by NIH R01GM097737 and P50DA037844 (A.A.P.), NIH T32DA07255 (C.C.P.), NIH T32GM07197 (N.M.G.), NIH R01AR056280 (D.A.B.), NIH R01AR060234 (C.L.A.-B.), the Fellowship from the Human Frontiers Science Program (P.C.) and the Howard Hughes Medical Institute (J.K.P.).
diff --git a/general/datasets/Ucsd_cfw_spl_rna_seq_0117/cases.rtf b/general/datasets/Ucsd_cfw_spl_rna_seq_0117/cases.rtf
new file mode 100644
index 0000000..97eed8a
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_spl_rna_seq_0117/cases.rtf
@@ -0,0 +1,3 @@
+Phenotype, genotype and RNA-seq gene expression data is available at
+
+http://datadryad.org/resource/doi:10.5061/dryad.2rs41
diff --git a/general/datasets/Ucsd_cfw_spl_rna_seq_0117/contributors.rtf b/general/datasets/Ucsd_cfw_spl_rna_seq_0117/contributors.rtf
new file mode 100644
index 0000000..24e5cd6
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_spl_rna_seq_0117/contributors.rtf
@@ -0,0 +1 @@
+A.A.P. conceived the study. C.C.P. and A.A.P. supervised the project. S.G. and P.C. designed and implemented the statistical and bioinformatics analyses with contributions from C.C.P., J.K.P. and A.A.P. N.M.G. designed and executed the RNA-seq and GBS protocols with assistance from E.A. and J.D. C.C.P. performed the behavioral phenotyping with assistance from E.L. and Y.J.P. A.L. performed the muscle and bone phenotyping with input from D.A.B. C.L.A.-B. performed the BMD phenotyping. C.C.P., S.G., P.C. and A.A.P. wrote the manuscript, with input from all co-authors.
diff --git a/general/datasets/Ucsd_cfw_spl_rna_seq_0117/processing.rtf b/general/datasets/Ucsd_cfw_spl_rna_seq_0117/processing.rtf
new file mode 100644
index 0000000..9c368fa
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_spl_rna_seq_0117/processing.rtf
@@ -0,0 +1 @@
+FPKM data were quantitle normalized for each ENSEMBL gene (mRNA) model (Identifiers such as ENSMUSG00000093778). Every gene/mRNA therefore has a mean expression value of 0 and a perfectly normal distribution, even if the original distribution was bimodal. The QQ plots is GN will be straight lines. There is no data at all on expression level in this original data set downloaded from http://dx.doi.org/10.5061/dryad.2rs41
diff --git a/general/datasets/Ucsd_cfw_spl_rna_seq_0117/specifics.rtf b/general/datasets/Ucsd_cfw_spl_rna_seq_0117/specifics.rtf
new file mode 100644
index 0000000..0e70b6c
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_spl_rna_seq_0117/specifics.rtf
@@ -0,0 +1 @@
+Striatum
diff --git a/general/datasets/Ucsd_cfw_spl_rna_seq_0117/summary.rtf b/general/datasets/Ucsd_cfw_spl_rna_seq_0117/summary.rtf
new file mode 100644
index 0000000..0639fe7
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_spl_rna_seq_0117/summary.rtf
@@ -0,0 +1 @@
+Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice. Full article available here.
diff --git a/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/acknowledgment.rtf b/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/acknowledgment.rtf
new file mode 100644
index 0000000..24f8c40
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/acknowledgment.rtf
@@ -0,0 +1 @@
+The authors wish to acknowledge technical assistance from: D. Godfrey, S. Lionikaite, V. Lionikaite, A.S. Lionikiene and J. Zekos as well as technical and intellectual input from M. Abney, J. Borevitz, K. Broman, N. Cai, R. Cheng, N. Cox, R. Davies, J. Flint, L. Goodstadt, P. Grabowski, B. Harr, E. Leffler, R. Mott, J. Nicod, J. Novembre, A. Price, M. Stephens, D. Weeks and X. Zhou. This project was funded by NIH R01GM097737 and P50DA037844 (A.A.P.), NIH T32DA07255 (C.C.P.), NIH T32GM07197 (N.M.G.), NIH R01AR056280 (D.A.B.), NIH R01AR060234 (C.L.A.-B.), the Fellowship from the Human Frontiers Science Program (P.C.) and the Howard Hughes Medical Institute (J.K.P.).
diff --git a/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/cases.rtf b/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/cases.rtf
new file mode 100644
index 0000000..97eed8a
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/cases.rtf
@@ -0,0 +1,3 @@
+Phenotype, genotype and RNA-seq gene expression data is available at
+
+http://datadryad.org/resource/doi:10.5061/dryad.2rs41
diff --git a/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/contributors.rtf b/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/contributors.rtf
new file mode 100644
index 0000000..24e5cd6
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/contributors.rtf
@@ -0,0 +1 @@
+A.A.P. conceived the study. C.C.P. and A.A.P. supervised the project. S.G. and P.C. designed and implemented the statistical and bioinformatics analyses with contributions from C.C.P., J.K.P. and A.A.P. N.M.G. designed and executed the RNA-seq and GBS protocols with assistance from E.A. and J.D. C.C.P. performed the behavioral phenotyping with assistance from E.L. and Y.J.P. A.L. performed the muscle and bone phenotyping with input from D.A.B. C.L.A.-B. performed the BMD phenotyping. C.C.P., S.G., P.C. and A.A.P. wrote the manuscript, with input from all co-authors.
diff --git a/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/processing.rtf b/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/processing.rtf
new file mode 100644
index 0000000..9c368fa
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/processing.rtf
@@ -0,0 +1 @@
+FPKM data were quantitle normalized for each ENSEMBL gene (mRNA) model (Identifiers such as ENSMUSG00000093778). Every gene/mRNA therefore has a mean expression value of 0 and a perfectly normal distribution, even if the original distribution was bimodal. The QQ plots is GN will be straight lines. There is no data at all on expression level in this original data set downloaded from http://dx.doi.org/10.5061/dryad.2rs41
diff --git a/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/specifics.rtf b/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/specifics.rtf
new file mode 100644
index 0000000..6077f41
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/specifics.rtf
@@ -0,0 +1,3 @@
+RNA-Seq Log2 Z-score
+
+In general, the array data that we put in GeneNetwork has been logged and then z normalized, but instead of leaving the mean at 0 and the standard deviation of 1 unit, we shift up to a mean of 8 units and increase the spread by having an standard deviation of 2 units (what we call 2Z + 8 normalized data). This removes negative values from the tables.
diff --git a/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/summary.rtf b/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/summary.rtf
new file mode 100644
index 0000000..0639fe7
--- /dev/null
+++ b/general/datasets/Ucsd_cfw_str_rna_seq_log2_0117/summary.rtf
@@ -0,0 +1 @@
+Although mice are the most widely used mammalian model organism, genetic studies have suffered from limited mapping resolution due to extensive linkage disequilibrium (LD) that is characteristic of crosses among inbred strains. Carworth Farms White (CFW) mice are a commercially available outbred mouse population that exhibit rapid LD decay in comparison to other available mouse populations. We performed a genome-wide association study (GWAS) of behavioral, physiological and gene expression phenotypes using 1,200 male CFW mice. We used genotyping by sequencing (GBS) to obtain genotypes at 92,734 SNPs. We also measured gene expression using RNA sequencing in three brain regions. Our study identified numerous behavioral, physiological and expression quantitative trait loci (QTLs). We integrated the behavioral QTL and eQTL results to implicate specific genes, including Azi2 in sensitivity to methamphetamine and Zmynd11 in anxiety-like behavior. The combination of CFW mice, GBS and RNA sequencing constitutes a powerful approach to GWAS in mice. Full article available here.
diff --git a/general/datasets/Ufl_mdp_hipp0814/summary.rtf b/general/datasets/Ufl_mdp_hipp0814/summary.rtf
new file mode 100644
index 0000000..5bf7963
--- /dev/null
+++ b/general/datasets/Ufl_mdp_hipp0814/summary.rtf
@@ -0,0 +1 @@
+Information regarding of this data set will become available soon
diff --git a/general/datasets/Uiowa_eye_rma_0906/summary.rtf b/general/datasets/Uiowa_eye_rma_0906/summary.rtf
new file mode 100644
index 0000000..7815ecc
--- /dev/null
+++ b/general/datasets/Uiowa_eye_rma_0906/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 73, Name: UIOWA Eye mRNA RAE230v2 (Sep06)
\ No newline at end of file
diff --git a/general/datasets/Umcg_0907_eryth/summary.rtf b/general/datasets/Umcg_0907_eryth/summary.rtf
new file mode 100644
index 0000000..9afd234
--- /dev/null
+++ b/general/datasets/Umcg_0907_eryth/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 38, Name: UMCG Myeloid Cells ILM6v1.1 (Apr09)
\ No newline at end of file
diff --git a/general/datasets/Umcg_0907_eryth_ori/summary.rtf b/general/datasets/Umcg_0907_eryth_ori/summary.rtf
new file mode 100644
index 0000000..9afd234
--- /dev/null
+++ b/general/datasets/Umcg_0907_eryth_ori/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 38, Name: UMCG Myeloid Cells ILM6v1.1 (Apr09)
\ No newline at end of file
diff --git a/general/datasets/Umcg_0907_hemastem/summary.rtf b/general/datasets/Umcg_0907_hemastem/summary.rtf
new file mode 100644
index 0000000..9afd234
--- /dev/null
+++ b/general/datasets/Umcg_0907_hemastem/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 38, Name: UMCG Myeloid Cells ILM6v1.1 (Apr09)
\ No newline at end of file
diff --git a/general/datasets/Umcg_0907_hemastem_ori/summary.rtf b/general/datasets/Umcg_0907_hemastem_ori/summary.rtf
new file mode 100644
index 0000000..9afd234
--- /dev/null
+++ b/general/datasets/Umcg_0907_hemastem_ori/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 38, Name: UMCG Myeloid Cells ILM6v1.1 (Apr09)
\ No newline at end of file
diff --git a/general/datasets/Umcg_0907_myeloid/summary.rtf b/general/datasets/Umcg_0907_myeloid/summary.rtf
new file mode 100644
index 0000000..9afd234
--- /dev/null
+++ b/general/datasets/Umcg_0907_myeloid/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 38, Name: UMCG Myeloid Cells ILM6v1.1 (Apr09)
\ No newline at end of file
diff --git a/general/datasets/Umcg_0907_myeloid_ori/summary.rtf b/general/datasets/Umcg_0907_myeloid_ori/summary.rtf
new file mode 100644
index 0000000..9afd234
--- /dev/null
+++ b/general/datasets/Umcg_0907_myeloid_ori/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 38, Name: UMCG Myeloid Cells ILM6v1.1 (Apr09)
\ No newline at end of file
diff --git a/general/datasets/Umcg_0907_pro/summary.rtf b/general/datasets/Umcg_0907_pro/summary.rtf
new file mode 100644
index 0000000..9afd234
--- /dev/null
+++ b/general/datasets/Umcg_0907_pro/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 38, Name: UMCG Myeloid Cells ILM6v1.1 (Apr09)
\ No newline at end of file
diff --git a/general/datasets/Umcg_0907_pro_ori/summary.rtf b/general/datasets/Umcg_0907_pro_ori/summary.rtf
new file mode 100644
index 0000000..9afd234
--- /dev/null
+++ b/general/datasets/Umcg_0907_pro_ori/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 38, Name: UMCG Myeloid Cells ILM6v1.1 (Apr09)
\ No newline at end of file
diff --git a/general/datasets/Umutaffyexon_0209_rma/acknowledgment.rtf b/general/datasets/Umutaffyexon_0209_rma/acknowledgment.rtf
new file mode 100644
index 0000000..9f0655d
--- /dev/null
+++ b/general/datasets/Umutaffyexon_0209_rma/acknowledgment.rtf
@@ -0,0 +1 @@
+We thank Affymetrix Inc. for their generous support of this project and array data set.
diff --git a/general/datasets/Umutaffyexon_0209_rma/cases.rtf b/general/datasets/Umutaffyexon_0209_rma/cases.rtf
new file mode 100644
index 0000000..35ae421
--- /dev/null
+++ b/general/datasets/Umutaffyexon_0209_rma/cases.rtf
@@ -0,0 +1,1182 @@
+
+
+
+
+
+
+
+ | Index |
+ Original CEL |
+ Tube ID |
+ Strain |
+ Age |
+ Sex |
+ Source |
+
+
+ | 1 |
+ JR3551H.CEL |
+ jr3551h |
+ C57BL/6J |
+ 60 |
+ F |
+ UTM RW |
+
+
+ | 2 |
+ JR3552H.CEL |
+ jr3552hre |
+ C57BL/6J |
+ 60 |
+ F |
+ UTM RW |
+
+
+ | 3 |
+ R0572H.CEL |
+ r0572h |
+ C57BL/6J |
+ 69 |
+ F |
+ |
+
+
+ | 4 |
+ R2137H.CEL |
+ r2137h |
+ C57BL/6J |
+ 55 |
+ F |
+ JAX |
+
+
+ | 5 |
+ R3552H.CEL |
+ r3552h |
+ C57BL/6J |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 6 |
+ JR3549H.CEL |
+ jr3549h |
+ C57BL/6J |
+ 60 |
+ M |
+ UTM RW |
+
+
+ | 7 |
+ JR3550H.CEL |
+ jr3550hre |
+ C57BL/6J |
+ 60 |
+ M |
+ UTM RW |
+
+
+ | 8 |
+ R0574H.CEL |
+ r0574h |
+ C57BL/6J |
+ 69 |
+ M |
+ |
+
+
+ | 9 |
+ R2136H.CEL |
+ r2136h |
+ C57BL/6J |
+ 55 |
+ M |
+ JAX |
+
+
+ | 10 |
+ R3549H.CEL |
+ r3549h |
+ C57BL/6J |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 11 |
+ JR3557H.CEL |
+ jr3557h |
+ DBA/2J |
+ 60 |
+ F |
+ UTM RW |
+
+
+ | 12 |
+ JR3558H.CEL |
+ jr3558hre |
+ DBA/2J |
+ 60 |
+ F |
+ UTM RW |
+
+
+ | 13 |
+ R3558H.CEL |
+ r3558h |
+ DBA/2J |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 14 |
+ JR3555H.CEL |
+ jr3555h |
+ DBA/2J |
+ 60 |
+ M |
+ UTM RW |
+
+
+ | 15 |
+ JR3556H.CEL |
+ jr3556h |
+ DBA/2J |
+ 60 |
+ M |
+ UTM RW |
+
+
+ | 16 |
+ R3555H.CEL |
+ r3555h |
+ DBA/2J |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 17 |
+ R3497H.CEL |
+ r3497h |
+ B6D2F1 |
+ 58 |
+ F |
+ Glenn |
+
+
+ | 18 |
+ R3500H.CEL |
+ r3500h |
+ B6D2F1 |
+ 58 |
+ M |
+ Glenn |
+
+
+ | 19 |
+ R1374H.CEL |
+ r1374h |
+ D2B6F1 |
+ 58 |
+ F |
+ UTM RW |
+
+
+ | 20 |
+ R1382H.CEL |
+ r1382h |
+ D2B6F1 |
+ 59 |
+ M |
+ UTM RW |
+
+
+ | 21 |
+ R3532H.CEL |
+ r3532h |
+ 129S1/SvImJ |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 22 |
+ R3512H.CEL |
+ r3512h |
+ 129S1/SvImJ |
+ 59 |
+ M |
+ Glenn |
+
+
+ | 23 |
+ R3520H.CEL |
+ r3520h |
+ A/J |
+ 59 |
+ F |
+ Glenn |
+
+
+ | 24 |
+ R3523H.CEL |
+ r3523h |
+ A/J |
+ 59 |
+ M |
+ Glenn |
+
+
+ | 25 |
+ R3514H.CEL |
+ r3514h |
+ AKR/J |
+ 59 |
+ F |
+ Glenn |
+
+
+ | 26 |
+ R3515H.CEL |
+ r3515h |
+ AKR/J |
+ 59 |
+ M |
+ Glenn |
+
+
+ | 27 |
+ R3508H.CEL |
+ r3508h |
+ BALB/cByJ |
+ 59 |
+ F |
+ Glenn |
+
+
+ | 28 |
+ R3505H.CEL |
+ r3505h |
+ BALB/cByJ |
+ 59 |
+ M |
+ Glenn |
+
+
+ | 29 |
+ R3524H.CEL |
+ r3524h |
+ BTBR T+ tf/J |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 30 |
+ R3509H.CEL |
+ r3509h |
+ BTBR T+ tf/J |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 31 |
+ R1542H.CEL |
+ r1542h |
+ BXD1 |
+ 59 |
+ F |
+ Glenn |
+
+
+ | 32 |
+ R1520H.CEL |
+ r1520h |
+ BXD2 |
+ 56 |
+ F |
+ Glenn |
+
+
+ | 33 |
+ R1694H.CEL |
+ r1694h |
+ BXD5 |
+ 58 |
+ M |
+ Glenn |
+
+
+ | 34 |
+ R3454H.CEL |
+ r3454h |
+ BXD6 |
+ 58 |
+ M |
+ Glenn |
+
+
+ | 35 |
+ R3457H.CEL |
+ r3457h |
+ BXD8 |
+ 61 |
+ F |
+ Glenn |
+
+
+ | 36 |
+ R3455H.CEL |
+ r3455h |
+ BXD9 |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 37 |
+ R3462H.CEL |
+ r3462h |
+ BXD11 |
+ 59 |
+ M |
+ Glenn |
+
+
+ | 38 |
+ R3464H.CEL |
+ r3464h |
+ BXD12 |
+ 59 |
+ F |
+ Glenn |
+
+
+ | 39 |
+ R2315H.CEL |
+ r2315h |
+ BXD13 |
+ 84 |
+ M |
+ UTM RW |
+
+
+ | 40 |
+ R3480H.CEL |
+ r3480h |
+ BXD14 |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 41 |
+ R3478H.CEL |
+ r3478h |
+ BXD15 |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 42 |
+ R3482H.CEL |
+ r3482h |
+ BXD16 |
+ 59 |
+ F |
+ Glenn |
+
+
+ | 43 |
+ R3488H.CEL |
+ r3488h |
+ BXD18 |
+ 59 |
+ M |
+ Glenn |
+
+
+ | 44 |
+ R3471H.CEL |
+ r3471h |
+ BXD19 |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 45 |
+ R2506H.CEL |
+ r2506h |
+ BXD20 |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 46 |
+ R3490H.CEL |
+ r3490h |
+ BXD21 |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 47 |
+ R3492H.CEL |
+ r3492h |
+ BXD22 |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 48 |
+ R3486H.CEL |
+ r3486h |
+ BXD23 |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 49 |
+ R1547H.CEL |
+ r1547h |
+ BXD24 |
+ 59 |
+ M |
+ Glenn |
+
+
+ | 50 |
+ R2892H.CEL |
+ r2892h |
+ BXD25 |
+ 67 |
+ F |
+ UTM RW |
+
+
+ | 51 |
+ R3485H.CEL |
+ r3485h |
+ BXD27 |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 52 |
+ R3477H.CEL |
+ r3477h |
+ BXD28 |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 53 |
+ R3475H.CEL |
+ r3475h |
+ BXD29 |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 54 |
+ R3456H.CEL |
+ r3456h |
+ BXD31 |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 55 |
+ R3570H.CEL |
+ r3570h |
+ BXD32 |
+ 66 |
+ F |
+ |
+
+
+ | 56 |
+ R3571H.CEL |
+ r3571h |
+ BXD32 |
+ 58 |
+ M |
+ |
+
+
+ | 57 |
+ R3467H.CEL |
+ r3467h |
+ BXD33 |
+ 59 |
+ M |
+ Glenn |
+
+
+ | 58 |
+ R3466H.CEL |
+ r3466h |
+ BXD34 |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 59 |
+ R3463H.CEL |
+ r3463h |
+ BXD36 |
+ 61 |
+ F |
+ Glenn |
+
+
+ | 60 |
+ R3458H.CEL |
+ r3458h |
+ BXD38 |
+ 55 |
+ M |
+ Glenn |
+
+
+ | 61 |
+ JR4433H.CEL |
+ jr4433sa |
+ BXD39 |
+ 63 |
+ F |
+ UTM RW |
+
+
+ | 62 |
+ R1535H.CEL |
+ r1535h |
+ BXD39 |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 63 |
+ R3459H.CEL |
+ r3459h |
+ BXD40 |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 64 |
+ R1541H.CEL |
+ r1541h |
+ BXD42 |
+ 58 |
+ F |
+ Glenn |
+
+
+ | 65 |
+ R1279H.CEL |
+ r1279h |
+ BXD43 |
+ 57 |
+ M |
+ UTM RW |
+
+
+ | 66 |
+ R1472H.CEL |
+ r1472h |
+ BXD45 |
+ 65 |
+ M |
+ UTM RW |
+
+
+ | 67 |
+ R1586H.CEL |
+ r1586h |
+ BXD48 |
+ 59 |
+ F |
+ UTM RW |
+
+
+ | 68 |
+ R2936H.CEL |
+ r2936h |
+ BXD50 |
+ 61 |
+ F |
+ UTM RW |
+
+
+ | 69 |
+ R1313H.CEL |
+ r1313h |
+ BXD51 |
+ 62 |
+ M |
+ UTM RW |
+
+
+ | 70 |
+ JR2680H.CEL |
+ jr2680h |
+ BXD55 |
+ 65 |
+ M |
+ UTM RW |
+
+
+ | 71 |
+ R1340H.CEL |
+ r1340h |
+ BXD60 |
+ 64 |
+ F |
+ UTM RW |
+
+
+ | 72 |
+ R1856H.CEL |
+ r1856h |
+ BXD61 |
+ 94 |
+ M |
+ UTM RW |
+
+
+ | 73 |
+ R1317H.CEL |
+ r1317h |
+ BXD62 |
+ 59 |
+ F |
+ UTM RW |
+
+
+ | 74 |
+ R1945H.CEL |
+ r1945h |
+ BXD63 |
+ 107 |
+ F |
+ UTM RW |
+
+
+ | 75 |
+ R2615H.CEL |
+ r2615h |
+ BXD64 |
+ 68 |
+ F |
+ UTM RW |
+
+
+ | 76 |
+ R3567H.CEL |
+ r3567h |
+ BXD65 |
+ 60 |
+ F |
+ UTRW |
+
+
+ | 77 |
+ R1949H.CEL |
+ r1949h |
+ BXD66 |
+ 96 |
+ M |
+ UTM RW |
+
+
+ | 78 |
+ R2060H.CEL |
+ r2060h |
+ BXD67 |
+ 54 |
+ F |
+ UTM RW |
+
+
+ | 79 |
+ R2902H.CEL |
+ r2902h |
+ BXD68 |
+ 57 |
+ M |
+ UTM RW |
+
+
+ | 80 |
+ R1466H.CEL |
+ r1466h |
+ BXD69 |
+ 59 |
+ F |
+ UTM RW |
+
+
+ | 81 |
+ R2063H.CEL |
+ r2063h |
+ BXD70 |
+ 55 |
+ M |
+ UTM RW |
+
+
+ | 82 |
+ R1269H.CEL |
+ r1269h |
+ BXD73 |
+ 72 |
+ M |
+ UTM RW |
+
+
+ | 83 |
+ JR2316H.CEL |
+ jr2316hre |
+ BXD74 |
+ 193 |
+ M |
+ UTM RW |
+
+
+ | 84 |
+ R1871H.CEL |
+ r1871h |
+ BXD75 |
+ 61 |
+ F |
+ UTM RW |
+
+
+ | 85 |
+ JR1948H.CEL |
+ jr1948h |
+ BXD76 |
+ 81 |
+ F |
+ UTM RW |
+
+
+ | 86 |
+ R1427H.CEL |
+ r1427h |
+ BXD77 |
+ 61 |
+ M |
+ UTM RW |
+
+
+ | 87 |
+ JR4434H.CEL |
+ jr4434sare |
+ BXD79 |
+ 63 |
+ F |
+ UTM RW |
+
+
+ | 88 |
+ R3568H.CEL |
+ r3568h |
+ BXD80 |
+ 66 |
+ M |
+ UTRW |
+
+
+ | 89 |
+ R2959H.CEL |
+ r2959h |
+ BXD83 |
+ 58 |
+ F |
+ UTM RW |
+
+
+ | 90 |
+ R2898H.CEL |
+ r2898h |
+ BXD84 |
+ 67 |
+ M |
+ UTM RW |
+
+
+ | 91 |
+ R3566H.CEL |
+ r3566h |
+ BXD85 |
+ 65 |
+ M |
+ UTRW |
+
+
+ | 92 |
+ R1556H.CEL |
+ r1556h |
+ BXD86 |
+ 57 |
+ F |
+ UTM RW |
+
+
+ | 93 |
+ R1710H.CEL |
+ r1710h |
+ BXD87 |
+ 84 |
+ M |
+ UTM RW |
+
+
+ | 94 |
+ JR4079H.CEL |
+ jr4079hre |
+ BXD89 |
+ 63 |
+ M |
+ UTM RW |
+
+
+ | 95 |
+ R2058H.CEL |
+ r2058h |
+ BXD90 |
+ 61 |
+ F |
+ UTM RW |
+
+
+ | 96 |
+ R1284H.CEL |
+ r1284h |
+ BXD92 |
+ 58 |
+ M |
+ UTM RW |
+
+
+ | 97 |
+ JR2057H.CEL |
+ jr2057h |
+ BXD93 |
+ 92 |
+ F |
+ UTM RW |
+
+
+ | 98 |
+ JR2313H.CEL |
+ jr2313h-re |
+ BXD94 |
+ 59 |
+ F |
+ UTM RW |
+
+
+ | 99 |
+ R1915H.CEL |
+ r1915h |
+ BXD96 |
+ 65 |
+ F |
+ UTM RW |
+
+
+ | 100 |
+ R2648H.CEL |
+ r2648h |
+ BXD97 |
+ 74 |
+ F |
+ UTM RW |
+
+
+ | 101 |
+ R1942H.CEL |
+ r1942h |
+ BXD98 |
+ 62 |
+ F |
+ UTM RW |
+
+
+ | 102 |
+ R1369H.CEL |
+ r1369h |
+ BXD99 |
+ 76 |
+ M |
+ UMemphis |
+
+
+ | 103 |
+ R2889H.CEL |
+ r2889h |
+ BXSB/MpJ |
+ 61 |
+ F |
+ Glenn |
+
+
+ | 104 |
+ R2887H.CEL |
+ r2887h |
+ BXSB/MpJ |
+ 61 |
+ M |
+ Glenn |
+
+
+ | 105 |
+ R3501H.CEL |
+ r3501h |
+ C3H/HeJ |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 106 |
+ R3504H.CEL |
+ r3504h |
+ C3H/HeJ |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 107 |
+ R3564H.CEL |
+ r3564h |
+ CAST/EiJ |
+ 57 |
+ F |
+ Glenn |
+
+
+ | 108 |
+ R3565H.CEL |
+ r3565h |
+ CAST/EiJ |
+ 61 |
+ M |
+ Glenn |
+
+
+ | 109 |
+ R3493H.CEL |
+ r3493h |
+ FVB/NJ |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 110 |
+ R3496H.CEL |
+ r3496h |
+ FVB/NJ |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 111 |
+ JR1683H.CEL |
+ jr1683h |
+ KK/HlJ |
+ 72 |
+ F |
+ UTM RW |
+
+
+ | 112 |
+ JR3542H.CEL |
+ jr3542hre |
+ KK/HlJ |
+ 61 |
+ M |
+ UTM RW |
+
+
+ | 113 |
+ JR2046H.CEL |
+ jr2046hre |
+ LG/J |
+ 63 |
+ F |
+ UTM RW |
+
+
+ | 114 |
+ JR2047H.CEL |
+ jr2047h |
+ LG/J |
+ 63 |
+ M |
+ UTM RW |
+
+
+ | 115 |
+ R3541H.CEL |
+ r3541h |
+ MOLF/EiJ |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 116 |
+ R3553H.CEL |
+ r3553h |
+ MOLF/EiJ |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 117 |
+ R3516H.CEL |
+ r3516h |
+ NOD/LtJ |
+ 58 |
+ F |
+ Glenn |
+
+
+ | 118 |
+ R3519H.CEL |
+ r3519h |
+ NOD/LtJ |
+ 58 |
+ M |
+ Glenn |
+
+
+ | 119 |
+ R3554H.CEL |
+ r3554h |
+ NZB/BlNJ |
+ 61 |
+ F |
+ Glenn |
+
+
+ | 120 |
+ R3513H.CEL |
+ r3513h |
+ NZB/BlNJ |
+ 58 |
+ M |
+ Glenn |
+
+
+ | 121 |
+ R3539H.CEL |
+ r3539h |
+ NZO/HlLtJ |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 122 |
+ R3536H.CEL |
+ r3536h |
+ NZO/HlLtJ |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 123 |
+ R3540H.CEL |
+ r3540h |
+ NZW/LacJ |
+ 65 |
+ F |
+ Glenn |
+
+
+ | 124 |
+ R3535H.CEL |
+ r3535h |
+ NZW/LacJ |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 125 |
+ R3527H.CEL |
+ r3527h |
+ PWD/PhJ |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 126 |
+ R3526H.CEL |
+ r3526h |
+ PWD/PhJ |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 127 |
+ R3531H.CEL |
+ r3531h |
+ PWK/PhJ |
+ 60 |
+ M |
+ Glenn |
+
+
+ | 128 |
+ R3561H.CEL |
+ r3561h |
+ WSB/EiJ |
+ 60 |
+ F |
+ Glenn |
+
+
+ | 129 |
+ R3525H.CEL |
+ r3525h |
+ WSB/EiJ |
+ 60 |
+ M |
+ Glenn |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Umutaffyexon_0209_rma/experiment-type.rtf b/general/datasets/Umutaffyexon_0209_rma/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Umutaffyexon_0209_rma/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Umutaffyexon_0209_rma/processing.rtf b/general/datasets/Umutaffyexon_0209_rma/processing.rtf
new file mode 100644
index 0000000..6e4dc8e
--- /dev/null
+++ b/general/datasets/Umutaffyexon_0209_rma/processing.rtf
@@ -0,0 +1,9 @@
+The following steps were applied to refine the data by M. Jagalur in RWW lab:
+
+
+ - Strain correction: In this step the strong probe level cis-QTLs were identified and using an expectation maximization (EM)-like method, the genotypes of each marker was re-assigned. This set of reassigned markers was compared to existing list genotypes of BXD strains and the maximal match was identified as the correct strain.
+ - Sex correction: In this step probes that are highly correlated to sex were identified and using an EM-like method we detected and corrected the sex of single array data sets.
+ - Data exclusion criteria: In this step individual arrays were evaluated. Arrays were systematically excluded from the data set (drop one out) and the number of cis-QTLs was recomputed. If excluding an array resulted in s significantly higher number of cis-QTLs then that array was considered to be of poor quality and was excluded from the final data set This step was repeated across all arrays in multiple cycles until there was no improvement in number of cis-QTLs.
+ - Tissue correction: In this step probes that are highly correlated to tissue type were identified and EM-like method was used to identify correct tissue.
+ - Noise Removal: A noise component was calculated using the expression of "unhybridized"probes (those with the lowest signal) and was removed from the data.
+
diff --git a/general/datasets/Umutaffyexon_0209_rma/summary.rtf b/general/datasets/Umutaffyexon_0209_rma/summary.rtf
new file mode 100644
index 0000000..a1fe16a
--- /dev/null
+++ b/general/datasets/Umutaffyexon_0209_rma/summary.rtf
@@ -0,0 +1,3 @@
+Data generated by RW Williams, Lu Lu, Manjunatha Jagalur, and David Kulp. All arrays run at the VA Medical Center, Memphis, by Yan Jiao.
+
+Data entered by Arthur Centeno and Manju Jagalur, Feb 27, 2009. This data set modified data for two BXD strains. Data were added for BXD79 that had been incorrectly included as a striatum sample (this data set was therefore deleted from the Exon 1.0ST striatum data set). We also changed data for BXD39. As expected, this addition and correction improved QTL mapping values. For example, for Kcnj9 probe set 4519178 the LRS values increased from 103.3 in the Aug08 data to 115.7 for these Feb09 data. Rob is concerned about the high error term of BXD39.
diff --git a/general/datasets/Umutaffyexon_0209_rma_mdp/experiment-type.rtf b/general/datasets/Umutaffyexon_0209_rma_mdp/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Umutaffyexon_0209_rma_mdp/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Umutaffyexon_0209_rma_mdp/summary.rtf b/general/datasets/Umutaffyexon_0209_rma_mdp/summary.rtf
new file mode 100644
index 0000000..afe9391
--- /dev/null
+++ b/general/datasets/Umutaffyexon_0209_rma_mdp/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 98, Name: UMUTAffy Hippocampus Exon (Feb09)
\ No newline at end of file
diff --git a/general/datasets/Und_nida_hxb_bxh_indbp_log2z8_0321/cases.rtf b/general/datasets/Und_nida_hxb_bxh_indbp_log2z8_0321/cases.rtf
new file mode 100644
index 0000000..ce39718
--- /dev/null
+++ b/general/datasets/Und_nida_hxb_bxh_indbp_log2z8_0321/cases.rtf
@@ -0,0 +1,1075 @@
+
+
+
+ |
+ Index
+ |
+
+ Strain
+ |
+
+ Sex
+ |
+
+ TMT Batch
+ |
+
+ TMT Channel
+ |
+
+
+ |
+ 1
+ |
+
+ SHR
+ |
+
+ M
+ |
+
+ 1
+ |
+
+ sig127C
+ |
+
+
+ |
+ 2
+ |
+
+ SHR
+ |
+
+ F
+ |
+
+ 1
+ |
+
+ sig128N
+ |
+
+
+ |
+ 3
+ |
+
+ BN.Lx
+ |
+
+ M
+ |
+
+ 1
+ |
+
+ sig129C
+ |
+
+
+ |
+ 4
+ |
+
+ BN.Lx
+ |
+
+ F
+ |
+
+ 1
+ |
+
+ sig131N
+ |
+
+
+ |
+ 5
+ |
+
+ HXB18
+ |
+
+ F
+ |
+
+ 1
+ |
+
+ sig126
+ |
+
+
+ |
+ 6
+ |
+
+ HXB18
+ |
+
+ M
+ |
+
+ 1
+ |
+
+ sig127N
+ |
+
+
+ |
+ 7
+ |
+
+ BXH3
+ |
+
+ M
+ |
+
+ 1
+ |
+
+ sig131C
+ |
+
+
+ |
+ 8
+ |
+
+ BXH3
+ |
+
+ F
+ |
+
+ 1
+ |
+
+ sig132N
+ |
+
+
+ |
+ 9
+ |
+
+ BXH12
+ |
+
+ M
+ |
+
+ 1
+ |
+
+ sig132C
+ |
+
+
+ |
+ 10
+ |
+
+ BXH12
+ |
+
+ F
+ |
+
+ 1
+ |
+
+ sig133N
+ |
+
+
+ |
+ 11
+ |
+
+ BXH13
+ |
+
+ M
+ |
+
+ 1
+ |
+
+ sig133C
+ |
+
+
+ |
+ 12
+ |
+
+ BXH13
+ |
+
+ F
+ |
+
+ 1
+ |
+
+ sig134N
+ |
+
+
+ |
+ 13
+ |
+
+ BXH6
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig127N
+ |
+
+
+ |
+ 14
+ |
+
+ BXH6
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig127C
+ |
+
+
+ |
+ 15
+ |
+
+ BXH8
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig128N
+ |
+
+
+ |
+ 16
+ |
+
+ BXH8
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig128C
+ |
+
+
+ |
+ 17
+ |
+
+ HXB1
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig129N
+ |
+
+
+ |
+ 18
+ |
+
+ HXB1
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig129C
+ |
+
+
+ |
+ 19
+ |
+
+ HXB10
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig130N
+ |
+
+
+ |
+ 20
+ |
+
+ HXB10
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig130C
+ |
+
+
+ |
+ 21
+ |
+
+ HXB13
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig131N
+ |
+
+
+ |
+ 22
+ |
+
+ HXB13
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig131C
+ |
+
+
+ |
+ 23
+ |
+
+ HXB15
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig132N
+ |
+
+
+ |
+ 24
+ |
+
+ HXB15
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig132C
+ |
+
+
+ |
+ 25
+ |
+
+ HXB17
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig133N
+ |
+
+
+ |
+ 26
+ |
+
+ HXB17
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig133C
+ |
+
+
+ |
+ 27
+ |
+
+ HXB4
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig134N
+ |
+
+
+ |
+ 28
+ |
+
+ HXB4
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig127N
+ |
+
+
+ |
+ 29
+ |
+
+ HXB2
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig127C
+ |
+
+
+ |
+ 30
+ |
+
+ HXB2
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig128N
+ |
+
+
+ |
+ 31
+ |
+
+ HXB20
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig128C
+ |
+
+
+ |
+ 32
+ |
+
+ HXB20
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig129N
+ |
+
+
+ |
+ 33
+ |
+
+ HXB22
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig129C
+ |
+
+
+ |
+ 34
+ |
+
+ HXB22
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig130N
+ |
+
+
+ |
+ 35
+ |
+
+ HXB29
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig130C
+ |
+
+
+ |
+ 36
+ |
+
+ HXB29
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig131N
+ |
+
+
+ |
+ 37
+ |
+
+ HXB3
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig131C
+ |
+
+
+ |
+ 38
+ |
+
+ HXB3
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig132N
+ |
+
+
+ |
+ 39
+ |
+
+ HXB31
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig132C
+ |
+
+
+ |
+ 40
+ |
+
+ HXB31
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig133N
+ |
+
+
+ |
+ 41
+ |
+
+ HXB7
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig133C
+ |
+
+
+ |
+ 42
+ |
+
+ HXB7
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig134N
+ |
+
+
+ |
+ 43
+ |
+
+ BXH5
+ |
+
+ F
+ |
+
+ 4
+ |
+
+ sig126
+ |
+
+
+ |
+ 44
+ |
+
+ BXH5
+ |
+
+ M
+ |
+
+ 4
+ |
+
+ sig127N
+ |
+
+
+ |
+ 45
+ |
+
+ BXH9
+ |
+
+ F
+ |
+
+ 4
+ |
+
+ sig127C
+ |
+
+
+ |
+ 46
+ |
+
+ BXH9
+ |
+
+ M
+ |
+
+ 4
+ |
+
+ sig128N
+ |
+
+
+ |
+ 47
+ |
+
+ BXH10
+ |
+
+ F
+ |
+
+ 4
+ |
+
+ sig128C
+ |
+
+
+ |
+ 48
+ |
+
+ BXH10
+ |
+
+ M
+ |
+
+ 4
+ |
+
+ sig129N
+ |
+
+
+ |
+ 49
+ |
+
+ BXH11
+ |
+
+ F
+ |
+
+ 4
+ |
+
+ sig129C
+ |
+
+
+ |
+ 50
+ |
+
+ BXH11
+ |
+
+ M
+ |
+
+ 4
+ |
+
+ sig130N
+ |
+
+
+ |
+ 51
+ |
+
+ HXB5
+ |
+
+ F
+ |
+
+ 4
+ |
+
+ sig130C
+ |
+
+
+ |
+ 52
+ |
+
+ HXB5
+ |
+
+ M
+ |
+
+ 4
+ |
+
+ sig131N
+ |
+
+
+ |
+ 53
+ |
+
+ HXB21
+ |
+
+ F
+ |
+
+ 5
+ |
+
+ sig126
+ |
+
+
+ |
+ 54
+ |
+
+ HXB21
+ |
+
+ M
+ |
+
+ 5
+ |
+
+ sig127N
+ |
+
+
+ |
+ 55
+ |
+
+ HXB23
+ |
+
+ F
+ |
+
+ 5
+ |
+
+ sig127C
+ |
+
+
+ |
+ 56
+ |
+
+ HXB23
+ |
+
+ M
+ |
+
+ 5
+ |
+
+ sig128N
+ |
+
+
+ |
+ 57
+ |
+
+ HXB24
+ |
+
+ F
+ |
+
+ 5
+ |
+
+ sig128C
+ |
+
+
+ |
+ 58
+ |
+
+ HXB24
+ |
+
+ M
+ |
+
+ 5
+ |
+
+ sig129N
+ |
+
+
+ |
+ 59
+ |
+
+ HXB25
+ |
+
+ F
+ |
+
+ 5
+ |
+
+ sig129C
+ |
+
+
+ |
+ 60
+ |
+
+ HXB25
+ |
+
+ M
+ |
+
+ 5
+ |
+
+ sig130N
+ |
+
+
+ |
+ 61
+ |
+
+ HXB27
+ |
+
+ F
+ |
+
+ 5
+ |
+
+ sig130C
+ |
+
+
+ |
+ 62
+ |
+
+ HXB27
+ |
+
+ M
+ |
+
+ 5
+ |
+
+ sig131N
+ |
+
+
+
diff --git a/general/datasets/Und_nida_hxb_bxh_indbp_log2z8_0321/processing.rtf b/general/datasets/Und_nida_hxb_bxh_indbp_log2z8_0321/processing.rtf
new file mode 100644
index 0000000..c05f172
--- /dev/null
+++ b/general/datasets/Und_nida_hxb_bxh_indbp_log2z8_0321/processing.rtf
@@ -0,0 +1,5 @@
+Sample processing protocol: The proteomic data were generated with 3 batches of 16-plex and 2 batches of 11-plex TMT experiments. The rat brain samples from 31 HXB/BXH strains with replicates (i.e., male and female) were lysed, digested, and labeled with either 11 or 16 different TMT tags. The TMT-labeled peptides were pooled with an equal amount of each and fractionated into 42 fractions in a concatenated fashion on an RP-HPLC column (4.6 mm x 250 mm) under basic pH conditions. each fraction was run sequentially on a column (75 μm x 20 cm for the whole proteome, 50 μm x ∼30 cm for phosphoproteome, 1.9 μm C18 resin from Dr. Maisch GmbH, 65°C to reduce backpressure) interfaced with a Q Exactive HF Orbitrap or Fusion MS (Thermo Fisher). Peptides were eluted by a 2-3 hr gradient (buffer A: 0.2% formic acid, 5% DMSO; buffer B: buffer A plus 65% acetonitrile). MS settings included the MS1 scan (410-1600 m/z, 60,000 or 120,000 resolution, 1 × 106 AGC and 50 ms maximal ion time) and 20 data-dependent MS2 scans (fixed first mass of 120 m/z, 60,000 resolution, 1 × 105 AGC, 100-150 ms maximal ion time, HCD, 35%–38% normalized collision energy, ∼1.0 m/z isolation window).
+
+Data processing protocol: The MS/MS raw files are processed using the JUMP searching engine against the UniProt mouse database. Searches were performed using 8 ppm mass tolerance for precursor ions due to JUMP’s auto mass correction function and 15 ppm for fragment ions, allowing up to two missed trypsin cleavage sites. TMT tags on lysine residues and peptide N termini (+229.162932 Da) were used for static modifications and the dynamic modifications include oxidation of methionine residues (+15.99492 Da). The assigned peptides are filtered by minimal peptide length, maximum miscleavages, mass-to-charge accuracy and matching scores. The peptides are then divided into groups according to peptide length, trypticity, modification, miscleavage, and charge and then further filtered by matching scores to reduce protein or phosphopeptide FDR to below 1%. Proteins or phosphopeptides were quantified by summing reporter ion counts across all matched PSMs using our in-house software.
+
+Protein quantification: We first extracted the TMT reporter ion intensities of each PSM and corrected the raw intensities based on the isotopic distribution of each labeling reagent. We discarded PSMs with low intensities (i.e., the minimum intensity of 1,000 and the median intensity of 5,000). After normalizing abundance with the trimmed median intensity of all PSMs, we calculated the mean-centered intensities across samples (e.g., relative intensities between each sample and the mean) and summarized protein relative intensities by averaging related PSMs. Finally, we derived protein absolute intensities by multiplying the relative intensities by the grand mean of the three most highly abundant PSMs. We first used the internal standard to normalize 3 batches of 16-plex experiments and 2 batches of 11-plex experiments. We then used the LIMMA batch removal function to normalize all five batches of TMT experiments.
diff --git a/general/datasets/Und_nida_hxb_bxh_indbp_log2z8_0321/specifics.rtf b/general/datasets/Und_nida_hxb_bxh_indbp_log2z8_0321/specifics.rtf
new file mode 100644
index 0000000..2fa1f25
--- /dev/null
+++ b/general/datasets/Und_nida_hxb_bxh_indbp_log2z8_0321/specifics.rtf
@@ -0,0 +1 @@
+Brain Proteome Individual (protein level)
\ No newline at end of file
diff --git a/general/datasets/Und_nida_hxb_bxh_indbp_log2z8_0321/summary.rtf b/general/datasets/Und_nida_hxb_bxh_indbp_log2z8_0321/summary.rtf
new file mode 100644
index 0000000..94c8e6e
--- /dev/null
+++ b/general/datasets/Und_nida_hxb_bxh_indbp_log2z8_0321/summary.rtf
@@ -0,0 +1,3 @@
+Brain proteome data. Deep proteome data were generated using whole brain tissue from both parents and 29 members of the HXB family, one male and one female per strain. Proteins in these samples were identified and quantified using the tandem-mass-tag (TMT) labeling strategy coupled with two-dimensional liquid chromatography-tandem mass spectrometry (LC/LC-MS/MS).
+
+This rat whole brain proteome data provide protein expression of 31 HXB/BXH strains, including 29 RI strains, and two parental strains, SHR/OlaIpcv and BN-Lx/Cub. A total of 8,124 proteins were quantified across all 31 strains.
diff --git a/general/datasets/Und_nida_hxb_bxh_indbpep_log2z8_0321/cases.rtf b/general/datasets/Und_nida_hxb_bxh_indbpep_log2z8_0321/cases.rtf
new file mode 100644
index 0000000..ce39718
--- /dev/null
+++ b/general/datasets/Und_nida_hxb_bxh_indbpep_log2z8_0321/cases.rtf
@@ -0,0 +1,1075 @@
+
+
+
+ |
+ Index
+ |
+
+ Strain
+ |
+
+ Sex
+ |
+
+ TMT Batch
+ |
+
+ TMT Channel
+ |
+
+
+ |
+ 1
+ |
+
+ SHR
+ |
+
+ M
+ |
+
+ 1
+ |
+
+ sig127C
+ |
+
+
+ |
+ 2
+ |
+
+ SHR
+ |
+
+ F
+ |
+
+ 1
+ |
+
+ sig128N
+ |
+
+
+ |
+ 3
+ |
+
+ BN.Lx
+ |
+
+ M
+ |
+
+ 1
+ |
+
+ sig129C
+ |
+
+
+ |
+ 4
+ |
+
+ BN.Lx
+ |
+
+ F
+ |
+
+ 1
+ |
+
+ sig131N
+ |
+
+
+ |
+ 5
+ |
+
+ HXB18
+ |
+
+ F
+ |
+
+ 1
+ |
+
+ sig126
+ |
+
+
+ |
+ 6
+ |
+
+ HXB18
+ |
+
+ M
+ |
+
+ 1
+ |
+
+ sig127N
+ |
+
+
+ |
+ 7
+ |
+
+ BXH3
+ |
+
+ M
+ |
+
+ 1
+ |
+
+ sig131C
+ |
+
+
+ |
+ 8
+ |
+
+ BXH3
+ |
+
+ F
+ |
+
+ 1
+ |
+
+ sig132N
+ |
+
+
+ |
+ 9
+ |
+
+ BXH12
+ |
+
+ M
+ |
+
+ 1
+ |
+
+ sig132C
+ |
+
+
+ |
+ 10
+ |
+
+ BXH12
+ |
+
+ F
+ |
+
+ 1
+ |
+
+ sig133N
+ |
+
+
+ |
+ 11
+ |
+
+ BXH13
+ |
+
+ M
+ |
+
+ 1
+ |
+
+ sig133C
+ |
+
+
+ |
+ 12
+ |
+
+ BXH13
+ |
+
+ F
+ |
+
+ 1
+ |
+
+ sig134N
+ |
+
+
+ |
+ 13
+ |
+
+ BXH6
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig127N
+ |
+
+
+ |
+ 14
+ |
+
+ BXH6
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig127C
+ |
+
+
+ |
+ 15
+ |
+
+ BXH8
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig128N
+ |
+
+
+ |
+ 16
+ |
+
+ BXH8
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig128C
+ |
+
+
+ |
+ 17
+ |
+
+ HXB1
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig129N
+ |
+
+
+ |
+ 18
+ |
+
+ HXB1
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig129C
+ |
+
+
+ |
+ 19
+ |
+
+ HXB10
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig130N
+ |
+
+
+ |
+ 20
+ |
+
+ HXB10
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig130C
+ |
+
+
+ |
+ 21
+ |
+
+ HXB13
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig131N
+ |
+
+
+ |
+ 22
+ |
+
+ HXB13
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig131C
+ |
+
+
+ |
+ 23
+ |
+
+ HXB15
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig132N
+ |
+
+
+ |
+ 24
+ |
+
+ HXB15
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig132C
+ |
+
+
+ |
+ 25
+ |
+
+ HXB17
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig133N
+ |
+
+
+ |
+ 26
+ |
+
+ HXB17
+ |
+
+ F
+ |
+
+ 2
+ |
+
+ sig133C
+ |
+
+
+ |
+ 27
+ |
+
+ HXB4
+ |
+
+ M
+ |
+
+ 2
+ |
+
+ sig134N
+ |
+
+
+ |
+ 28
+ |
+
+ HXB4
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig127N
+ |
+
+
+ |
+ 29
+ |
+
+ HXB2
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig127C
+ |
+
+
+ |
+ 30
+ |
+
+ HXB2
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig128N
+ |
+
+
+ |
+ 31
+ |
+
+ HXB20
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig128C
+ |
+
+
+ |
+ 32
+ |
+
+ HXB20
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig129N
+ |
+
+
+ |
+ 33
+ |
+
+ HXB22
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig129C
+ |
+
+
+ |
+ 34
+ |
+
+ HXB22
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig130N
+ |
+
+
+ |
+ 35
+ |
+
+ HXB29
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig130C
+ |
+
+
+ |
+ 36
+ |
+
+ HXB29
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig131N
+ |
+
+
+ |
+ 37
+ |
+
+ HXB3
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig131C
+ |
+
+
+ |
+ 38
+ |
+
+ HXB3
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig132N
+ |
+
+
+ |
+ 39
+ |
+
+ HXB31
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig132C
+ |
+
+
+ |
+ 40
+ |
+
+ HXB31
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig133N
+ |
+
+
+ |
+ 41
+ |
+
+ HXB7
+ |
+
+ M
+ |
+
+ 3
+ |
+
+ sig133C
+ |
+
+
+ |
+ 42
+ |
+
+ HXB7
+ |
+
+ F
+ |
+
+ 3
+ |
+
+ sig134N
+ |
+
+
+ |
+ 43
+ |
+
+ BXH5
+ |
+
+ F
+ |
+
+ 4
+ |
+
+ sig126
+ |
+
+
+ |
+ 44
+ |
+
+ BXH5
+ |
+
+ M
+ |
+
+ 4
+ |
+
+ sig127N
+ |
+
+
+ |
+ 45
+ |
+
+ BXH9
+ |
+
+ F
+ |
+
+ 4
+ |
+
+ sig127C
+ |
+
+
+ |
+ 46
+ |
+
+ BXH9
+ |
+
+ M
+ |
+
+ 4
+ |
+
+ sig128N
+ |
+
+
+ |
+ 47
+ |
+
+ BXH10
+ |
+
+ F
+ |
+
+ 4
+ |
+
+ sig128C
+ |
+
+
+ |
+ 48
+ |
+
+ BXH10
+ |
+
+ M
+ |
+
+ 4
+ |
+
+ sig129N
+ |
+
+
+ |
+ 49
+ |
+
+ BXH11
+ |
+
+ F
+ |
+
+ 4
+ |
+
+ sig129C
+ |
+
+
+ |
+ 50
+ |
+
+ BXH11
+ |
+
+ M
+ |
+
+ 4
+ |
+
+ sig130N
+ |
+
+
+ |
+ 51
+ |
+
+ HXB5
+ |
+
+ F
+ |
+
+ 4
+ |
+
+ sig130C
+ |
+
+
+ |
+ 52
+ |
+
+ HXB5
+ |
+
+ M
+ |
+
+ 4
+ |
+
+ sig131N
+ |
+
+
+ |
+ 53
+ |
+
+ HXB21
+ |
+
+ F
+ |
+
+ 5
+ |
+
+ sig126
+ |
+
+
+ |
+ 54
+ |
+
+ HXB21
+ |
+
+ M
+ |
+
+ 5
+ |
+
+ sig127N
+ |
+
+
+ |
+ 55
+ |
+
+ HXB23
+ |
+
+ F
+ |
+
+ 5
+ |
+
+ sig127C
+ |
+
+
+ |
+ 56
+ |
+
+ HXB23
+ |
+
+ M
+ |
+
+ 5
+ |
+
+ sig128N
+ |
+
+
+ |
+ 57
+ |
+
+ HXB24
+ |
+
+ F
+ |
+
+ 5
+ |
+
+ sig128C
+ |
+
+
+ |
+ 58
+ |
+
+ HXB24
+ |
+
+ M
+ |
+
+ 5
+ |
+
+ sig129N
+ |
+
+
+ |
+ 59
+ |
+
+ HXB25
+ |
+
+ F
+ |
+
+ 5
+ |
+
+ sig129C
+ |
+
+
+ |
+ 60
+ |
+
+ HXB25
+ |
+
+ M
+ |
+
+ 5
+ |
+
+ sig130N
+ |
+
+
+ |
+ 61
+ |
+
+ HXB27
+ |
+
+ F
+ |
+
+ 5
+ |
+
+ sig130C
+ |
+
+
+ |
+ 62
+ |
+
+ HXB27
+ |
+
+ M
+ |
+
+ 5
+ |
+
+ sig131N
+ |
+
+
+
diff --git a/general/datasets/Und_nida_hxb_bxh_indbpep_log2z8_0321/processing.rtf b/general/datasets/Und_nida_hxb_bxh_indbpep_log2z8_0321/processing.rtf
new file mode 100644
index 0000000..c05f172
--- /dev/null
+++ b/general/datasets/Und_nida_hxb_bxh_indbpep_log2z8_0321/processing.rtf
@@ -0,0 +1,5 @@
+Sample processing protocol: The proteomic data were generated with 3 batches of 16-plex and 2 batches of 11-plex TMT experiments. The rat brain samples from 31 HXB/BXH strains with replicates (i.e., male and female) were lysed, digested, and labeled with either 11 or 16 different TMT tags. The TMT-labeled peptides were pooled with an equal amount of each and fractionated into 42 fractions in a concatenated fashion on an RP-HPLC column (4.6 mm x 250 mm) under basic pH conditions. each fraction was run sequentially on a column (75 μm x 20 cm for the whole proteome, 50 μm x ∼30 cm for phosphoproteome, 1.9 μm C18 resin from Dr. Maisch GmbH, 65°C to reduce backpressure) interfaced with a Q Exactive HF Orbitrap or Fusion MS (Thermo Fisher). Peptides were eluted by a 2-3 hr gradient (buffer A: 0.2% formic acid, 5% DMSO; buffer B: buffer A plus 65% acetonitrile). MS settings included the MS1 scan (410-1600 m/z, 60,000 or 120,000 resolution, 1 × 106 AGC and 50 ms maximal ion time) and 20 data-dependent MS2 scans (fixed first mass of 120 m/z, 60,000 resolution, 1 × 105 AGC, 100-150 ms maximal ion time, HCD, 35%–38% normalized collision energy, ∼1.0 m/z isolation window).
+
+Data processing protocol: The MS/MS raw files are processed using the JUMP searching engine against the UniProt mouse database. Searches were performed using 8 ppm mass tolerance for precursor ions due to JUMP’s auto mass correction function and 15 ppm for fragment ions, allowing up to two missed trypsin cleavage sites. TMT tags on lysine residues and peptide N termini (+229.162932 Da) were used for static modifications and the dynamic modifications include oxidation of methionine residues (+15.99492 Da). The assigned peptides are filtered by minimal peptide length, maximum miscleavages, mass-to-charge accuracy and matching scores. The peptides are then divided into groups according to peptide length, trypticity, modification, miscleavage, and charge and then further filtered by matching scores to reduce protein or phosphopeptide FDR to below 1%. Proteins or phosphopeptides were quantified by summing reporter ion counts across all matched PSMs using our in-house software.
+
+Protein quantification: We first extracted the TMT reporter ion intensities of each PSM and corrected the raw intensities based on the isotopic distribution of each labeling reagent. We discarded PSMs with low intensities (i.e., the minimum intensity of 1,000 and the median intensity of 5,000). After normalizing abundance with the trimmed median intensity of all PSMs, we calculated the mean-centered intensities across samples (e.g., relative intensities between each sample and the mean) and summarized protein relative intensities by averaging related PSMs. Finally, we derived protein absolute intensities by multiplying the relative intensities by the grand mean of the three most highly abundant PSMs. We first used the internal standard to normalize 3 batches of 16-plex experiments and 2 batches of 11-plex experiments. We then used the LIMMA batch removal function to normalize all five batches of TMT experiments.
diff --git a/general/datasets/Und_nida_hxb_bxh_indbpep_log2z8_0321/specifics.rtf b/general/datasets/Und_nida_hxb_bxh_indbpep_log2z8_0321/specifics.rtf
new file mode 100644
index 0000000..f255583
--- /dev/null
+++ b/general/datasets/Und_nida_hxb_bxh_indbpep_log2z8_0321/specifics.rtf
@@ -0,0 +1 @@
+UND NIDA Brain Proteome Individual (peptide-level) log2z+8 (Mar21)
\ No newline at end of file
diff --git a/general/datasets/Und_nida_hxb_bxh_indbpep_log2z8_0321/summary.rtf b/general/datasets/Und_nida_hxb_bxh_indbpep_log2z8_0321/summary.rtf
new file mode 100644
index 0000000..94c8e6e
--- /dev/null
+++ b/general/datasets/Und_nida_hxb_bxh_indbpep_log2z8_0321/summary.rtf
@@ -0,0 +1,3 @@
+Brain proteome data. Deep proteome data were generated using whole brain tissue from both parents and 29 members of the HXB family, one male and one female per strain. Proteins in these samples were identified and quantified using the tandem-mass-tag (TMT) labeling strategy coupled with two-dimensional liquid chromatography-tandem mass spectrometry (LC/LC-MS/MS).
+
+This rat whole brain proteome data provide protein expression of 31 HXB/BXH strains, including 29 RI strains, and two parental strains, SHR/OlaIpcv and BN-Lx/Cub. A total of 8,124 proteins were quantified across all 31 strains.
diff --git a/general/datasets/Ut_ceph_rankinv0909/acknowledgment.rtf b/general/datasets/Ut_ceph_rankinv0909/acknowledgment.rtf
new file mode 100644
index 0000000..7d66250
--- /dev/null
+++ b/general/datasets/Ut_ceph_rankinv0909/acknowledgment.rtf
@@ -0,0 +1 @@
+Financial support for this project was provided by Dr. Barrett Haik and the Hamilton Eye Institute, by NIH grant support to Malak Kotb, Robert W. Williams, Rita G. Kasal and colleagues, and by the UT Center for Integrative and Translational Genomics.
diff --git a/general/datasets/Ut_ceph_rankinv0909/cases.rtf b/general/datasets/Ut_ceph_rankinv0909/cases.rtf
new file mode 100644
index 0000000..f4f6663
--- /dev/null
+++ b/general/datasets/Ut_ceph_rankinv0909/cases.rtf
@@ -0,0 +1,2009 @@
+About the CEPH/UTAH families used to generate this data set:
+
+The CEPH/UTAH families used in this data set are part of CEPH repository linkage families of National Institute of General Medical Sciences (NIGMS) human genetic cell repository. These are immortalized human B-lymphocytes (EBV-transformed) from Caucasian donors of UTAH/Mormon ethnicity. The CEPH/UTAH families contain 48 families; the present data set includes 14 of these families with available DNA/genotypes for each member of these pedigrees. There are five families common with the published Monks et al (2004), namely families: 1346, 1362, 1418, 1421, and 1424.
+
+
+
+
+
+
+
+
+ | Index |
+ Repository
+ Number |
+ Case ID |
+ Gender |
+ Family ID |
+ Family Member ID |
+ Sentrix ID |
+ Sentrix
+ Position |
+ Batch ID |
+
+
+ | 1 |
+ GM07038 |
+ 1333001 |
+ Male |
+ 1333 |
+ 1 |
+ 4256249060 |
+ A |
+ 5 |
+
+
+ | 2 |
+ GM06987 |
+ 1333002 |
+ Female |
+ 1333 |
+ 2 |
+ 4158260019 |
+ B |
+ 4 |
+
+
+ | 3 |
+ GM07004 |
+ 1333003 |
+ Male |
+ 1333 |
+ 3 |
+ 4256249103 |
+ A |
+ 7 |
+
+
+ | 4 |
+ GM07052 |
+ 1333004 |
+ Male |
+ 1333 |
+ 4 |
+ 4256249051 |
+ A |
+ 6 |
+
+
+ | 5 |
+ GM06982 |
+ 1333005 |
+ Male |
+ 1333 |
+ 5 |
+ 4158260009 |
+ F |
+ 3 |
+
+
+ | 6 |
+ GM07011 |
+ 1333006 |
+ Female |
+ 1333 |
+ 6 |
+ 4158260012 |
+ C |
+ 3 |
+
+
+ | 7 |
+ GM07009 |
+ 1333007 |
+ Male |
+ 1333 |
+ 7 |
+ 4256249101 |
+ F |
+ 6 |
+
+
+ | 8 |
+ GM07678 |
+ 1333008 |
+ Male |
+ 1333 |
+ 8 |
+ 4158260005 |
+ B |
+ 4 |
+
+
+ | 9 |
+ GM07026 |
+ 1333009 |
+ Male |
+ 1333 |
+ 9 |
+ 4158260026 |
+ C |
+ 3 |
+
+
+ | 10 |
+ GM07679 |
+ 1333010 |
+ Male |
+ 1333 |
+ 10 |
+ 4158260030 |
+ C |
+ 3 |
+
+
+ | 11 |
+ GM07049 |
+ 1333011 |
+ Male |
+ 1333 |
+ 11 |
+ 4256249059 |
+ A |
+ 5 |
+
+
+ | 12 |
+ GM07002 |
+ 1333012 |
+ Female |
+ 1333 |
+ 12 |
+ 4158260001 |
+ B |
+ 4 |
+
+
+ | 13 |
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+ GM12770 |
+ 1451005 |
+ Female |
+ 1451 |
+ 5 |
+ 4158260005 |
+ A |
+ 4 |
+
+
+ | 150 |
+ GM12771 |
+ 1451006 |
+ Male |
+ 1451 |
+ 6 |
+ 4256249047 |
+ E |
+ 6 |
+
+
+ | 151 |
+ GM12772 |
+ 1451007 |
+ Female |
+ 1451 |
+ 7 |
+ 4158260019 |
+ A |
+ 4 |
+
+
+ | 152 |
+ GM12773 |
+ 1451008 |
+ Female |
+ 1451 |
+ 8 |
+ 4158260002 |
+ B |
+ 4 |
+
+
+ | 153 |
+ GM12848 |
+ 1451009 |
+ Female |
+ 1451 |
+ 9 |
+ 4256249051 |
+ D |
+ 6 |
+
+
+ | 154 |
+ GM12774 |
+ 1451010 |
+ Male |
+ 1451 |
+ 10 |
+ 4158260030 |
+ F |
+ 3 |
+
+
+ | 155 |
+ GM12776 |
+ 1451012 |
+ Female |
+ 1451 |
+ 12 |
+ 4256249099 |
+ E |
+ 7 |
+
+
+ | 156 |
+ GM12777 |
+ 1451013 |
+ Male |
+ 1451 |
+ 13 |
+ 4256249060 |
+ D |
+ 5 |
+
+
+ | 157 |
+ GM12801 |
+ 1454001 |
+ Male |
+ 1454 |
+ 1 |
+ 4256249103 |
+ C |
+ 7 |
+
+
+ | 158 |
+ GM12803 |
+ 1454003 |
+ Female |
+ 1454 |
+ 3 |
+ 4158260019 |
+ C |
+ 4 |
+
+
+ | 159 |
+ GM12804 |
+ 1454004 |
+ Female |
+ 1454 |
+ 4 |
+ 4256249101 |
+ D |
+ 6 |
+
+
+ | 160 |
+ GM12805 |
+ 1454005 |
+ Male |
+ 1454 |
+ 5 |
+ 4256249095 |
+ F |
+ 7 |
+
+
+ | 161 |
+ GM12806 |
+ 1454006 |
+ Male |
+ 1454 |
+ 6 |
+ 4256249098 |
+ E |
+ 7 |
+
+
+ | 162 |
+ GM12808 |
+ 1454008 |
+ Female |
+ 1454 |
+ 8 |
+ 4256249099 |
+ C |
+ 7 |
+
+
+ | 163 |
+ GM12809 |
+ 1454009 |
+ Female |
+ 1454 |
+ 9 |
+ 4256249051 |
+ E |
+ 6 |
+
+
+ | 164 |
+ GM12810 |
+ 1454010 |
+ Male |
+ 1454 |
+ 10 |
+ 4256249104 |
+ A |
+ 7 |
+
+
+ | 165 |
+ GM12811 |
+ 1454011 |
+ Male |
+ 1454 |
+ 11 |
+ 4256249044 |
+ B |
+ 7 |
+
+
+ | 166 |
+ GM12812 |
+ 1454012 |
+ Male |
+ 1454 |
+ 12 |
+ 4256249042 |
+ F |
+ 6 |
+
+
+ | 167 |
+ GM12813 |
+ 1454013 |
+ Female |
+ 1454 |
+ 13 |
+ 4256249094 |
+ E |
+ 6 |
+
+
+ | 168 |
+ GM12814 |
+ 1454014 |
+ Male |
+ 1454 |
+ 14 |
+ 4256249096 |
+ D |
+ 7 |
+
+
+ | 169 |
+ GM12815 |
+ 1454015 |
+ Female |
+ 1454 |
+ 15 |
+ 4256249041 |
+ E |
+ 6 |
+
+
+ | 170 |
+ GM12816 |
+ 1454016 |
+ Male |
+ 1454 |
+ 16 |
+ 4256249047 |
+ F |
+ 6 |
+
+
+ | 171 |
+ GM12817 |
+ 1456001 |
+ Male |
+ 1456 |
+ 1 |
+ 4256249051 |
+ F |
+ 6 |
+
+
+ | 172 |
+ GM12818 |
+ 1456002 |
+ Female |
+ 1456 |
+ 2 |
+ 4256249101 |
+ E |
+ 6 |
+
+
+ | 173 |
+ GM12819 |
+ 1456003 |
+ Male |
+ 1456 |
+ 3 |
+ 4256249095 |
+ B |
+ 7 |
+
+
+ | 174 |
+ GM12821 |
+ 1456005 |
+ Female |
+ 1456 |
+ 5 |
+ 4256249044 |
+ C |
+ 7 |
+
+
+ | 175 |
+ GM12822 |
+ 1456006 |
+ Male |
+ 1456 |
+ 6 |
+ 4256249094 |
+ F |
+ 6 |
+
+
+ | 176 |
+ GM12823 |
+ 1456007 |
+ Male |
+ 1456 |
+ 7 |
+ 4256249096 |
+ B |
+ 7 |
+
+
+ | 177 |
+ GM12824 |
+ 1456008 |
+ Female |
+ 1456 |
+ 8 |
+ 4256249104 |
+ D |
+ 7 |
+
+
+ | 178 |
+ GM12825 |
+ 1456009 |
+ Male |
+ 1456 |
+ 9 |
+ 4158260026 |
+ B |
+ 3 |
+
+
+ | 179 |
+ GM12826 |
+ 1456010 |
+ Female |
+ 1456 |
+ 10 |
+ 4256249041 |
+ F |
+ 6 |
+
+
+ | 180 |
+ GM12828 |
+ 1456012 |
+ Female |
+ 1456 |
+ 12 |
+ 4256249099 |
+ F |
+ 7 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Ut_ceph_rankinv0909/contributors.rtf b/general/datasets/Ut_ceph_rankinv0909/contributors.rtf
new file mode 100644
index 0000000..507f2f7
--- /dev/null
+++ b/general/datasets/Ut_ceph_rankinv0909/contributors.rtf
@@ -0,0 +1,3 @@
+Eldon Geisert, Barrett Haik, Malak Kotb, Lu Lu, Roel Ophoff, Robert Williams.
+
+NIGMS Human Genetic Cell Repository
diff --git a/general/datasets/Ut_ceph_rankinv0909/experiment-design.rtf b/general/datasets/Ut_ceph_rankinv0909/experiment-design.rtf
new file mode 100644
index 0000000..d525b2e
--- /dev/null
+++ b/general/datasets/Ut_ceph_rankinv0909/experiment-design.rtf
@@ -0,0 +1,13 @@
+Experimental Design and Batch Structure:
+
+This data set consists of arrays processed in seven groups. Groups consisted of 2, 3, 4, 4, 3, 6, and then 8 beadchips at a time, batch IDs are indicated in table 1. Samples from same family were scattered among array groups, with samples from six different families were run on one chip. This was done to ensure balance and to minimize batch effects and group-by-family statistical confounds in normalization. This was done with the exception of the first two chips, which were run with 3 generations of the same family on one chip. A single operator, Yan Jiao, processed all arrays using illumina protocol for hybridization, washing and scanning. All samples in a group were labeled on one day, hybridization station accommodates up to 24 samples, or 4 beadchips. Chips were scanned using BeadArray Reader in sets of three.
+
+About the processing of cell lines:
+
+CEPH/UTAH families cell lines were purchased from Coriell repository of cell lines part of NIGMS. Upon arrival from the Coriell institute, we incubated the cell lines in 25ml flasks upright overnight at 37 ºC humidified incubator, with 5% carbon dioxide. We maintained the cells at a density of 5 X 105 cells/ml. The composition of the media used was RPMI-1640, 15% fetal bovine serum (FBS) and 2mM L-Glutamine; all FBS used was from the same lot. At 48 hours or when cell counts were ≥ 8 x 106 cells total, we harvested the cells and tested each cell line for mycoplasma contamination using e-Myco Mycoplasma PCR detection kit (iNtRON Biotechnology) according to manufacturer protocol. Cell lysates free of mycoplasma were used for RNA extraction as detailed below. We froze duplicates of each cell line at a concentration of ~2–6 x106 cells/ml according to standard procedures and stored in liquid nitrogen.
+
+About RNA processing:
+
+Two hundred and five cell lines were used for isolation of RNA. Ms. Sarah Rowe Hasty performed initial RNA isolation, purification and re-precipitation from 205 cell lines in Dr. Malak Kotb laboratory at VAMC. After initial RNA isolation, Ms. Nourtan Abdeltawab treated all samples for removal of contaminating DNA, along with further purification and re-precipitation of all samples. RNA samples that passed quality control were used to generate cRNA samples, those that didn't pass QC were re-extracted as we had duplicates of all cell lines lysates. RNA Extraction details: We used Qiagen RNeasy Mini purification of total RNA from tissues and cells spin protocol. RNA was isolated from 7.5 X 105 cells in duplicates. We froze cell lysates in RLT buffer and ß-mercaptoethanol at -80 ºC in 96 well plates until processed at a later time. We thawed samples, one 96 well plate at a time, and proceeded with RNA isolation steps and resuspended the pellets in RNase-free water. We then treated RNA to remove any DNA contamination using DNase digestion with RNase-free DNase kit (Qiagen) according to manufacturer protocol. RNA was finally purified by re-precipitation using ethanol precipitation using Purescript RNA purification kit (Gentra). Final purified RNA was resuspended in RNase-free water. RNA quality control: RNA samples were checked for RNA purity and integrity. RNA purity was evaluated using the 260/280 and 260/230 absorbance ratios. We used RNA samples with 260/280 ratio values ≥ 1.8 and 260/230 of ≥1.7. In cases were RNA samples did not meet these ratios, the RNA was purified by re-precipitation as above. RNA integrity was assessed using 1% RNA denaturing agrose gels. We required clear sharp bands of 18S and 28S rRNA for all samples compared to a control RNA sample to ensure intactness of rRNA.
+
+All RNA samples were processed by Yan Jiao at Dr. Weikuan Gu’s microarray core facility at VA medical center, Memphis, TN. We used only RNA samples that passed quality control as detailed above and of concentration ≥ 50ng/ul for cRNA synthesis using Illumina TotalPrep RNA amplification kit (Ambion) according to manufacturer protocol. The basic outline of the procedure involves reverse transcription of RNA to synthesize cDNA using oligo (dT) primer, followed by in vitro transcription of purified dsDNA to synthesize amplified biotinylated cRNA (aRNA). We evaluated purified labeled cRNA using same methods as mentioned above for RNA samples. cRNA samples of good quality (passing QC), were then used to hybridize to Illumina Human-6WG v2.0 according to Illumina standard protocols.
diff --git a/general/datasets/Ut_ceph_rankinv0909/experiment-type.rtf b/general/datasets/Ut_ceph_rankinv0909/experiment-type.rtf
new file mode 100644
index 0000000..0ef1518
--- /dev/null
+++ b/general/datasets/Ut_ceph_rankinv0909/experiment-type.rtf
@@ -0,0 +1,6 @@
+Experimental Design and Batch Structure:
+This data set consists of arrays processed in seven groups. Groups consisted of 2, 3, 4, 4, 3, 6, and then 8 beadchips at a time, batch IDs are indicated in table 1. Samples from same family were scattered among array groups, with samples from six different families were run on one chip. This was done to ensure balance and to minimize batch effects and group-by-family statistical confounds in normalization. This was done with the exception of the first two chips, which were run with 3 generations of the same family on one chip. A single operator, Yan Jiao, processed all arrays using illumina protocol for hybridization, washing and scanning. All samples in a group were labeled on one day, hybridization station accommodates up to 24 samples, or 4 beadchips. Chips were scanned using BeadArray Reader in sets of three.
+About the processing of cell lines:
+CEPH/UTAH families cell lines were purchased from Coriell repository of cell lines part of NIGMS. Upon arrival from the Coriell institute, we incubated the cell lines in 25ml flasks upright overnight at 37 ºC humidified incubator, with 5% carbon dioxide. We maintained the cells at a density of 5 X 105 cells/ml. The composition of the media used was RPMI-1640, 15% fetal bovine serum (FBS) and 2mM L-Glutamine; all FBS used was from the same lot. At 48 hours or when cell counts were ≥ 8 x 106 cells total, we harvested the cells and tested each cell line for mycoplasma contamination using e-Myco Mycoplasma PCR detection kit (iNtRON Biotechnology) according to manufacturer protocol. Cell lysates free of mycoplasma were used for RNA extraction as detailed below. We froze duplicates of each cell line at a concentration of ~2–6 x106 cells/ml according to standard procedures and stored in liquid nitrogen.
+About RNA processing:
+Two hundred and five cell lines were used for isolation of RNA. Ms. Sarah Rowe Hasty performed initial RNA isolation, purification and re-precipitation from 205 cell lines in Dr. Malak Kotb laboratory at VAMC. After initial RNA isolation, Ms. Nourtan Abdeltawab treated all samples for removal of contaminating DNA, along with further purification and re-precipitation of all samples. RNA samples that passed quality control were used to generate cRNA samples, those that didn't pass QC were re-extracted as we had duplicates of all cell lines lysates. RNA Extraction details: We used Qiagen RNeasy Mini purification of total RNA from tissues and cells spin protocol. RNA was isolated from 7.5 X 105 cells in duplicates. We froze cell lysates in RLT buffer and ß-mercaptoethanol at -80 ºC in 96 well plates until processed at a later time. We thawed samples, one 96 well plate at a time, and proceeded with RNA isolation steps and resuspended the pellets in RNase-free water. We then treated RNA to remove any DNA contamination using DNase digestion with RNase-free DNase kit (Qiagen) according to manufacturer protocol. RNA was finally purified by re-precipitation using ethanol precipitation using Purescript RNA purification kit (Gentra). Final purified RNA was resuspended in RNase-free water. RNA quality control: RNA samples were checked for RNA purity and integrity. RNA purity was evaluated using the 260/280 and 260/230 absorbance ratios. We used RNA samples with 260/280 ratio values ≥ 1.8 and 260/230 of ≥1.7. In cases were RNA samples did not meet these ratios, the RNA was purified by re-precipitation as above. RNA integrity was assessed using 1% RNA denaturing agrose gels. We required clear sharp bands of 18S and 28S rRNA for all samples compared to a control RNA sample to ensure intactness of rRNA.
\ No newline at end of file
diff --git a/general/datasets/Ut_ceph_rankinv0909/platform.rtf b/general/datasets/Ut_ceph_rankinv0909/platform.rtf
new file mode 100644
index 0000000..a7a8769
--- /dev/null
+++ b/general/datasets/Ut_ceph_rankinv0909/platform.rtf
@@ -0,0 +1 @@
+Illumina HumanGW-6 v2.0 BeadChip: The Human-6 v2 beadchip simultaneously assays six samples, therefore, known as ‘array of arrays’. Each chip has ~1.8 million beads, beads have several hundred thousands copies of optimized 50-mer gene-specific probes. These probes cover more than 48,000 transcripts per sample, targeting genes and known alternative splice variants from the RefSeq database release 17 and UniGene build 188.
diff --git a/general/datasets/Ut_ceph_rankinv0909/processing.rtf b/general/datasets/Ut_ceph_rankinv0909/processing.rtf
new file mode 100644
index 0000000..d144cac
--- /dev/null
+++ b/general/datasets/Ut_ceph_rankinv0909/processing.rtf
@@ -0,0 +1,3 @@
+About array data processing and analysis:
+
+RNA samples (n = 180) were processed using a total of 30 Illumina HumanWG-6 BeadChips, each beadchip analyses six samples covering 48,000 transcripts per sample. All chips passed quality control and error checking. This data set was extracted and processed using the Bead Studio 3. We applied Rank-invariant normalization to all the samples and the resulting expression values along with gene ID were exported in GeneSpring format. Dr. Rita Kansal performed the normalization steps.
diff --git a/general/datasets/Ut_ceph_rankinv0909/summary.rtf b/general/datasets/Ut_ceph_rankinv0909/summary.rtf
new file mode 100644
index 0000000..4394cb5
--- /dev/null
+++ b/general/datasets/Ut_ceph_rankinv0909/summary.rtf
@@ -0,0 +1,7 @@
+The Illumina Human Whole Genome 6 v2.0 Rank Invariant data for CEPH lymphoblastoid cell lines obtained from the Coriell Institute for Medical Research. All cell lines were processed in Memphis in the UTHSC laboratory of Dr. Malak Kotb (2007-2009), by Dr. Rita G. Kasal, Nourtan Abdeltawab, and colleagues.
+
+Selection of CEPH families and members was done by Dr. Roel Ophoff (Utrecht and UCLA).
+
+Array data were generated at microarray core facility in laboratory of Dr. Weikuan Gu at VA medical center, Memphis, TN.
+
+Analysis by Mark Reimers, Stephanie Santorico, and Roel Ophoff
diff --git a/general/datasets/Ut_hippratex_rma_0709/acknowledgment.rtf b/general/datasets/Ut_hippratex_rma_0709/acknowledgment.rtf
new file mode 100644
index 0000000..ded4315
--- /dev/null
+++ b/general/datasets/Ut_hippratex_rma_0709/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with NIAAA grants U01AA13499 to Robert W. Williams and a grant to Gerd Kempermann, Genomics of Regeneration in the Central Nervous System, Center for Regenerative Therapies, Dresden.
diff --git a/general/datasets/Ut_hippratex_rma_0709/cases.rtf b/general/datasets/Ut_hippratex_rma_0709/cases.rtf
new file mode 100644
index 0000000..85b4b4b
--- /dev/null
+++ b/general/datasets/Ut_hippratex_rma_0709/cases.rtf
@@ -0,0 +1,1392 @@
+
+
+
+
+
+
+
+ | Index |
+ run order |
+ case ID |
+ strain |
+ RNA ID |
+ Tube ID |
+ tissue |
+ out ID |
+ BORN |
+ SEX |
+ age |
+ from |
+ Extracted |
+ RIN |
+ 260:280 |
+ 260:230 |
+ ng/ul |
+ 8ug |
+
+
+ | 1 |
+ 1 |
+ 100908.03 |
+ BN.Lx |
+ R5448H |
+ R5448H1 |
+ hippo |
+ BN.Lx |
+ 12/25/10 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/14/13 |
+ |
+ 2.03 |
+ 2.2 |
+ 1042.14 |
+ 8 |
+
+
+ | 2 |
+ 16 |
+ 100908.02 |
+ BN.Lx |
+ R5446H |
+ R5446H1 |
+ hippo |
+ BN.Lx |
+ 12/25/10 |
+ male 2 |
+ 6 weeks |
+ Pravence's lab |
+ 3/14/13 |
+ |
+ 2.02 |
+ 2.24 |
+ 392.64 |
+ 20 |
+
+
+ | 3 |
+ 57 |
+ 100908.04 |
+ BN.Lx |
+ R5450H |
+ R5450H1 |
+ hippo |
+ BN.Lx |
+ 12/25/10 |
+ female 2 |
+ 6 weeks |
+ Pravence's lab |
+ 3/14/13 |
+ |
+ 2.06 |
+ 2.18 |
+ 1233.45 |
+ 6 |
+
+
+ | 4 |
+ 68 |
+ 100908.01 |
+ BN.Lx |
+ R5444H |
+ R5444H1 |
+ hippo |
+ BN.Lx |
+ 12/25/10 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/14/13 |
+ |
+ 2.05 |
+ 2.05 |
+ 640.56 |
+ 12 |
+
+
+ | 5 |
+ 3 |
+ 101308.03 |
+ BXH10 |
+ R5390H |
+ R5390H1 |
+ hippo |
+ RI 10C |
+ 6/8/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/4/13 |
+ |
+ 1.97 |
+ 2.26 |
+ 444.35 |
+ 18 |
+
+
+ | 6 |
+ 66 |
+ 101308.01 |
+ BXH10 |
+ R5386H |
+ R5386H1 |
+ hippo |
+ RI 10C |
+ 2/6/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/4/13 |
+ |
+ 2.04 |
+ 2.25 |
+ 746.6 |
+ 11 |
+
+
+ | 7 |
+ 5 |
+ 110608.19 |
+ BXH11 |
+ R5380H |
+ R5380H1 |
+ hippo |
+ RI 11C |
+ 5/25/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/4/13 |
+ |
+ 1.97 |
+ 2.35 |
+ 269.58 |
+ 30 |
+
+
+ | 8 |
+ 64 |
+ 110608.17 |
+ BXH11 |
+ R5378H |
+ R5378H1 |
+ hippo |
+ RI 11C |
+ 5/25/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/4/13 |
+ |
+ 2.04 |
+ 2.28 |
+ 811.02 |
+ 10 |
+
+
+ | 9 |
+ 7 |
+ 110608.23 |
+ BXH12 |
+ R5384H |
+ R5384H1 |
+ hippo |
+ RI 12C |
+ 3/26/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/4/13 |
+ |
+ 2.06 |
+ 2.28 |
+ 923.13 |
+ 9 |
+
+
+ | 10 |
+ 62 |
+ 110608.21 |
+ BXH12 |
+ R5382H |
+ R5382H1 |
+ hippo |
+ RI 12C |
+ 3/26/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/4/13 |
+ |
+ 1.96 |
+ 2.33 |
+ 260.39 |
+ 31 |
+
+
+ | 11 |
+ 9 |
+ 101508.19 |
+ BXH13 |
+ R5438H |
+ R5438H1 |
+ hippo |
+ RI 13C |
+ 4/20/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/10/13 |
+ |
+ 1.98 |
+ 2.33 |
+ 274.04 |
+ 29 |
+
+
+ | 12 |
+ 60 |
+ 101508.17 |
+ BXH13 |
+ R5436H |
+ R5436H1 |
+ hippo |
+ RI 13C |
+ 4/20/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/10/13 |
+ |
+ 1.98 |
+ 2.26 |
+ 334.92 |
+ 24 |
+
+
+ | 13 |
+ 11 |
+ 110608.27 |
+ BXH2 |
+ R5462H |
+ R5462H1 |
+ hippo |
+ RI 2C |
+ 4/1/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/14/13 |
+ |
+ 2.06 |
+ 2.3 |
+ 1050.29 |
+ 8 |
+
+
+ | 14 |
+ 58 |
+ 110608.25 |
+ BXH2 |
+ R5464H |
+ R5464H1 |
+ hippo |
+ RI 2C |
+ 4/1/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/14/13 |
+ |
+ 2.04 |
+ 2.29 |
+ 804.77 |
+ 10 |
+
+
+ | 15 |
+ 56 |
+ 100908.05 |
+ BXH3 |
+ R5452H |
+ R5452H1 |
+ hippo |
+ RI 3C |
+ 1/14/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/5/13 |
+ |
+ 1.97 |
+ 2.36 |
+ 306.01 |
+ 26 |
+
+
+ | 16 |
+ 59 |
+ 100908.08 |
+ BXH3 |
+ R5394H |
+ R5394H1 |
+ hippo |
+ RI 3C |
+ 1/14/11 |
+ female 2 |
+ 6 weeks |
+ Pravence's lab |
+ 3/5/13 |
+ |
+ 1.97 |
+ 2.28 |
+ 409.78 |
+ 20 |
+
+
+ | 17 |
+ 13 |
+ 110608.31 |
+ BXH5 |
+ R5368H |
+ R5368H1 |
+ hippo |
+ RI 5C |
+ 4/1/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/3/13 |
+ |
+ 2.07 |
+ 2.3 |
+ 1235.02 |
+ 6 |
+
+
+ | 18 |
+ 54 |
+ 110608.29 |
+ BXH5 |
+ R5366H |
+ R5366H1 |
+ hippo |
+ RI 5C |
+ 4/1/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/3/13 |
+ |
+ 2.04 |
+ 2.28 |
+ 905 |
+ 9 |
+
+
+ | 19 |
+ 15 |
+ 110608.11 |
+ BXH6 |
+ R5372H |
+ R5372H1 |
+ hippo |
+ RI 6C |
+ 6/4/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/3/13 |
+ |
+ 2.05 |
+ 1.95 |
+ 692.63 |
+ 12 |
+
+
+ | 20 |
+ 52 |
+ 110608.09 |
+ BXH6 |
+ R5370H |
+ R5370H1 |
+ hippo |
+ RI 6C |
+ 6/4/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/3/13 |
+ 8.1 |
+ 2.06 |
+ 2.08 |
+ 954.85 |
+ 8 |
+
+
+ | 21 |
+ 17 |
+ 112008.07 |
+ BXH8 |
+ R5360H |
+ R5360H1 |
+ hippo |
+ RI 8C |
+ 4/17/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 2/28/13 |
+ 9.1 |
+ 2.07 |
+ 2.27 |
+ 1127.86 |
+ 7 |
+
+
+ | 22 |
+ 50 |
+ 112008.05 |
+ BXH8 |
+ R5358H |
+ R5358H1 |
+ hippo |
+ RI 8C |
+ 4/17/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 2/28/13 |
+ 9.1 |
+ 2.08 |
+ 2.2 |
+ 682.5 |
+ 12 |
+
+
+ | 23 |
+ 19 |
+ 110608.15 |
+ BXH9 |
+ R5376H |
+ R5376H1 |
+ hippo |
+ RI 9C |
+ 6/16/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/3/13 |
+ 9.5 |
+ 2.08 |
+ 2.24 |
+ 736.93 |
+ 11 |
+
+
+ | 24 |
+ 48 |
+ 110608.13 |
+ BXH9 |
+ R5374H |
+ R5374H1 |
+ hippo |
+ RI 9C |
+ 6/16/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/3/13 |
+ 8.9 |
+ 1.98 |
+ 2.25 |
+ 434.51 |
+ 18 |
+
+
+ | 25 |
+ 21 |
+ 110608.03 |
+ HXB1 |
+ R5422H |
+ R5422H1 |
+ hippo |
+ RI 1 |
+ 3/13/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/10/13 |
+ |
+ 1.99 |
+ 2.22 |
+ 401.83 |
+ 20 |
+
+
+ | 26 |
+ 46 |
+ 110608.01 |
+ HXB1 |
+ R5420H |
+ R5420H1 |
+ hippo |
+ RI 1 |
+ 3/13/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/10/13 |
+ |
+ 1.97 |
+ 2.29 |
+ 351.01 |
+ 23 |
+
+
+ | 27 |
+ 23 |
+ 112008.51 |
+ HXB10 |
+ R5470H |
+ R5470H1 |
+ hippo |
+ RI 10 |
+ 3/30/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/17/13 |
+ |
+ 2.04 |
+ 2.26 |
+ 743.27 |
+ 11 |
+
+
+ | 28 |
+ 44 |
+ 112008.49 |
+ HXB10 |
+ R5472H |
+ R5472H1 |
+ hippo |
+ RI 10 |
+ 3/30/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/17/13 |
+ |
+ 2.05 |
+ 2.21 |
+ 958.07 |
+ 8 |
+
+
+ | 29 |
+ 25 |
+ 112008.55 |
+ HXB13 |
+ R5352H |
+ R5352H1 |
+ hippo |
+ RI 13 |
+ 3/3/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 2/28/13 |
+ |
+ 2.06 |
+ 2.13 |
+ 306.01 |
+ 26 |
+
+
+ | 30 |
+ 42 |
+ 112008.53 |
+ HXB13 |
+ R5350H |
+ R5350H1 |
+ hippo |
+ RI 13 |
+ 3/3/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 2/28/13 |
+ 9.1 |
+ 2.09 |
+ 2.24 |
+ 965.01 |
+ 8 |
+
+
+ | 31 |
+ 27 |
+ 112008.11 |
+ HXB15 |
+ R5414H |
+ R5414H1 |
+ hippo |
+ RI 15 |
+ 1/22/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/6/13 |
+ 8.7 |
+ 2.03 |
+ 2.31 |
+ 788.08 |
+ 10 |
+
+
+ | 32 |
+ 40 |
+ 112008.09 |
+ HXB15 |
+ R5412H |
+ R5412H1 |
+ hippo |
+ RI 15 |
+ 1/22/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/6/13 |
+ |
+ 2.05 |
+ 2.3 |
+ 1041.66 |
+ 8 |
+
+
+ | 33 |
+ 29 |
+ 112008.47 |
+ HXB17 |
+ R5474H |
+ R5474H1 |
+ hippo |
+ RI 17 |
+ 4/13/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/17/13 |
+ |
+ 2.03 |
+ 2.28 |
+ 758.42 |
+ 11 |
+
+
+ | 34 |
+ 38 |
+ 112008.45 |
+ HXB17 |
+ R5476H |
+ R5476H1 |
+ hippo |
+ RI 17 |
+ 4/13/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/17/13 |
+ |
+ 2.05 |
+ 2.27 |
+ 1112.55 |
+ 7 |
+
+
+ | 35 |
+ 14 |
+ 112008.22 |
+ HXB18 |
+ R5409H |
+ R5409H1 |
+ hippo |
+ RI 18 |
+ 2/2/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/6/13 |
+ |
+ 2.06 |
+ 2.27 |
+ 1281.26 |
+ 6 |
+
+
+ | 36 |
+ 31 |
+ 112008.23 |
+ HXB18 |
+ R5410H |
+ R5410H1 |
+ hippo |
+ RI 18 |
+ 2/2/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/6/13 |
+ 8.9 |
+ 1.98 |
+ 2.29 |
+ 356.56 |
+ 22 |
+
+
+ | 37 |
+ 36 |
+ 112008.13 |
+ HXB2 |
+ R5416H |
+ R5416H1 |
+ hippo |
+ RI 2 |
+ 1/10/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/6/13 |
+ 8.2 |
+ 2.06 |
+ 2.3 |
+ 1471.72 |
+ 5 |
+
+
+ | 38 |
+ 67 |
+ 112008.15 |
+ HXB2 |
+ R5418H |
+ R5418H1 |
+ hippo |
+ RI 2 |
+ 1/10/11 |
+ female1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/6/13 |
+ |
+ 2.01 |
+ 2.29 |
+ 690.65 |
+ 12 |
+
+
+ | 39 |
+ 33 |
+ 112008.19 |
+ HXB20 |
+ R5406H |
+ R5406H1 |
+ hippo |
+ RI 20 |
+ 5/24/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/6/13 |
+ |
+ 2.07 |
+ 2.24 |
+ 1386.52 |
+ 6 |
+
+
+ | 40 |
+ 34 |
+ 112008.17 |
+ HXB20 |
+ R5404H |
+ R5404H1 |
+ hippo |
+ RI 20 |
+ 2/16/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/6/13 |
+ 8.6 |
+ 2.05 |
+ 2.26 |
+ 1072.81 |
+ 7 |
+
+
+ | 41 |
+ 12 |
+ 101508.02 |
+ HXB21 |
+ R5458H |
+ R5458H1 |
+ hippo |
+ RI 21 |
+ 2/3/11 |
+ male 2 |
+ 6 weeks |
+ Pravence's lab |
+ 3/14/13 |
+ |
+ 2 |
+ 2.23 |
+ 791.4 |
+ 10 |
+
+
+ | 42 |
+ 35 |
+ 101508.04 |
+ HXB21 |
+ R5460H |
+ R5460H1 |
+ hippo |
+ RI 21 |
+ 2/3/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/14/13 |
+ |
+ 1.97 |
+ 2.29 |
+ 413.19 |
+ 19 |
+
+
+ | 43 |
+ 32 |
+ 112008.33 |
+ HXB22 |
+ R5484H |
+ R5484H1 |
+ hippo |
+ RI 22 |
+ 4/5/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/18/13 |
+ |
+ 2.08 |
+ 2.16 |
+ 755.61 |
+ 11 |
+
+
+ | 44 |
+ 37 |
+ 112008.35 |
+ HXB22 |
+ R5482H |
+ R5482H1 |
+ hippo |
+ RI 22 |
+ 4/5/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/18/13 |
+ |
+ 2.02 |
+ 2.3 |
+ 978.86 |
+ 8 |
+
+
+ | 45 |
+ 10 |
+ 101508.06 |
+ HXB23 |
+ R5454H |
+ R5454H1 |
+ hippo |
+ RI 23 |
+ 3/15/11 |
+ male 2 |
+ 6 weeks |
+ Pravence's lab |
+ 3/14/13 |
+ |
+ 2.05 |
+ 2.3 |
+ 1052.18 |
+ 8 |
+
+
+ | 46 |
+ 61 |
+ 101508.08 |
+ HXB23 |
+ R5456H |
+ R5456H1 |
+ hippo |
+ RI 23 |
+ 3/15/11 |
+ female 2 |
+ 6 weeks |
+ Pravence's lab |
+ 3/14/13 |
+ |
+ 2.06 |
+ 2.27 |
+ 1281.26 |
+ 6 |
+
+
+ | 47 |
+ 30 |
+ 100908.09 |
+ HXB24 |
+ R5396H |
+ R5396H1 |
+ hippo |
+ RI 24 |
+ 2/6/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/5/13 |
+ 8.4 |
+ 2.08 |
+ 1.74 |
+ 764.68 |
+ 10 |
+
+
+ | 48 |
+ 39 |
+ 100908.11 |
+ HXB24 |
+ R5400H |
+ R5400H1 |
+ hippo |
+ RI 24 |
+ 2/15/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/5/13 |
+ 8.8 |
+ 2.04 |
+ 2.26 |
+ 906.15 |
+ 9 |
+
+
+ | 49 |
+ 28 |
+ 101508.09 |
+ HXB25 |
+ R5428H |
+ R5428H1 |
+ hippo |
+ RI 25 |
+ 3/1/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/10/13 |
+ 8.5 |
+ 2.05 |
+ 2.3 |
+ 966.92 |
+ 8 |
+
+
+ | 50 |
+ 41 |
+ 101508.11 |
+ HXB25 |
+ R5430H |
+ R5430H1 |
+ hippo |
+ RI 25 |
+ 3/1/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/10/13 |
+ |
+ 2.03 |
+ 2.3 |
+ 811.64 |
+ 10 |
+
+
+ | 51 |
+ 8 |
+ 101508.22 |
+ HXB27 |
+ R5441H |
+ R5441H1 |
+ hippo |
+ RI 27 |
+ 4/19/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/10/13 |
+ |
+ 2.02 |
+ 2.24 |
+ 428.61 |
+ 19 |
+
+
+ | 52 |
+ 43 |
+ 101508.23 |
+ HXB27 |
+ R5442H |
+ R5442H1 |
+ hippo |
+ RI 27 |
+ 4/19/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/10/13 |
+ |
+ 2.02 |
+ 2.27 |
+ 767.32 |
+ 10 |
+
+
+ | 53 |
+ 6 |
+ 112008.26 |
+ HXB29 |
+ R5364H |
+ R5364H1 |
+ hippo |
+ RI 29 |
+ 2/13/11 |
+ male 2 |
+ 6 weeks |
+ Pravence's lab |
+ 3/3/13 |
+ |
+ 2.06 |
+ 2.29 |
+ 961 |
+ 8 |
+
+
+ | 54 |
+ 63 |
+ 112008.28 |
+ HXB29 |
+ R5362H |
+ R5362H1 |
+ hippo |
+ RI 29 |
+ 2/13/11 |
+ female 2 |
+ 6 weeks |
+ Pravence's lab |
+ 3/3/13 |
+ 8.8 |
+ 2.07 |
+ 2.26 |
+ 830.15 |
+ 10 |
+
+
+ | 55 |
+ 26 |
+ 112008.37 |
+ HXB3 |
+ R5480H |
+ R5480H1 |
+ hippo |
+ RI 3 |
+ 3/16/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/18/13 |
+ 8.7 |
+ 2.05 |
+ 2.26 |
+ 1169.97 |
+ 7 |
+
+
+ | 56 |
+ 45 |
+ 112008.39 |
+ HXB3 |
+ R5478H |
+ R5478H1 |
+ hippo |
+ RI 3 |
+ 3/16/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/18/13 |
+ |
+ 2.01 |
+ 2.18 |
+ 864.52 |
+ 9 |
+
+
+ | 57 |
+ 4 |
+ 112008.30 |
+ HXB31 |
+ R5347H |
+ R5347H1 |
+ hippo |
+ RI 31 |
+ 3/27/11 |
+ male 2 |
+ 6 weeks |
+ Pravence's lab |
+ 2/28/13 |
+ |
+ 2.1 |
+ 2.29 |
+ 881.39 |
+ 9 |
+
+
+ | 58 |
+ 47 |
+ 112008.31 |
+ HXB31 |
+ R5348H |
+ R5348H1 |
+ hippo |
+ RI 31 |
+ 3/27/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 2/28/13 |
+ |
+ 1.96 |
+ 2.37 |
+ 194.23 |
+ 41 |
+
+
+ | 59 |
+ 24 |
+ 101508.13 |
+ HXB4 |
+ R5432H |
+ R5432H1 |
+ hippo |
+ RI 4 |
+ 2/25/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/10/13 |
+ 8.4 |
+ 2.06 |
+ 2.29 |
+ 1345.87 |
+ 6 |
+
+
+ | 60 |
+ 49 |
+ 101508.15 |
+ HXB4 |
+ R5434H |
+ R5434H1 |
+ hippo |
+ RI 4 |
+ 2/25/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/10/13 |
+ |
+ 2.05 |
+ 2.21 |
+ 663.4 |
+ 12 |
+
+
+ | 61 |
+ 22 |
+ 112008.41 |
+ HXB5 |
+ R5468H |
+ R5468H1 |
+ hippo |
+ RI 5 |
+ 4/20/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/17/13 |
+ |
+ 2.05 |
+ 2.26 |
+ 961.62 |
+ 8 |
+
+
+ | 62 |
+ 51 |
+ 112008.43 |
+ HXB5 |
+ R5466H |
+ R5466H1 |
+ hippo |
+ RI 5 |
+ 4/20/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/17/13 |
+ |
+ 1.99 |
+ 2.32 |
+ 349.47 |
+ 23 |
+
+
+ | 63 |
+ 20 |
+ 110608.05 |
+ HXB7 |
+ R5424H |
+ R5424H1 |
+ hippo |
+ RI 7 |
+ 1/19/11 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/10/13 |
+ 8.5 |
+ 2.04 |
+ 2.29 |
+ 911.71 |
+ 9 |
+
+
+ | 64 |
+ 53 |
+ 110608.07 |
+ HXB7 |
+ R5426H |
+ R5426H1 |
+ hippo |
+ RI 7 |
+ 3/28/11 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 3/10/13 |
+ |
+ 1.97 |
+ 2.28 |
+ 423.45 |
+ 19 |
+
+
+ | 65 |
+ 2 |
+ 112008.02 |
+ SHR |
+ R5355H |
+ R5355H1 |
+ hippo |
+ SHR |
+ 12/25/10 |
+ male 2 |
+ 6 weeks |
+ Pravence's lab |
+ 2/28/13 |
+ |
+ 2.08 |
+ 2.24 |
+ 684.67 |
+ 12 |
+
+
+ | 66 |
+ 18 |
+ 112008.01 |
+ SHR |
+ R5354H |
+ R5354H1 |
+ hippo |
+ SHR |
+ 12/25/10 |
+ male 1 |
+ 6 weeks |
+ Pravence's lab |
+ 2/28/13 |
+ |
+ 2.07 |
+ 2.29 |
+ 728.58 |
+ 11 |
+
+
+ | 67 |
+ 55 |
+ 112008.03 |
+ SHR |
+ R5356H |
+ R5356H1 |
+ hippo |
+ SHR |
+ 12/25/10 |
+ female 1 |
+ 6 weeks |
+ Pravence's lab |
+ 2/28/13 |
+ |
+ 1.97 |
+ 2.36 |
+ 265.66 |
+ 30 |
+
+
+ | 68 |
+ 65 |
+ 112008.04 |
+ SHR |
+ R5357H |
+ R5357H1 |
+ hippo |
+ SHR |
+ 12/25/10 |
+ female 2 |
+ 6 weeks |
+ Pravence's lab |
+ 2/28/13 |
+ |
+ 2.05 |
+ 2.29 |
+ 967.24 |
+ 8 |
+
+
+
+ |
+
+
+
diff --git a/general/datasets/Ut_hippratex_rma_0709/summary.rtf b/general/datasets/Ut_hippratex_rma_0709/summary.rtf
new file mode 100644
index 0000000..8ea4a28
--- /dev/null
+++ b/general/datasets/Ut_hippratex_rma_0709/summary.rtf
@@ -0,0 +1 @@
+The HXB/BXH data provides estimates of Hippocampus mRNA expression. Affymetrix Rat Exon 1.0ST microarrays were used for hybridization using standard procedures. Total of 68 samples come from 30 BXH/HXB strain (one male and one female) and 2 parental strains (two males and two females).
diff --git a/general/datasets/Ut_ilm_bxd_hipp_5t_1112/notes.rtf b/general/datasets/Ut_ilm_bxd_hipp_5t_1112/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_5t_1112/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Ut_ilm_bxd_hipp_5t_1112/summary.rtf b/general/datasets/Ut_ilm_bxd_hipp_5t_1112/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_5t_1112/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Ut_ilm_bxd_hipp_noe_0909/notes.rtf b/general/datasets/Ut_ilm_bxd_hipp_noe_0909/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_noe_0909/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Ut_ilm_bxd_hipp_noe_0909/summary.rtf b/general/datasets/Ut_ilm_bxd_hipp_noe_0909/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_noe_0909/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Ut_ilm_bxd_hipp_noe_1112/notes.rtf b/general/datasets/Ut_ilm_bxd_hipp_noe_1112/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_noe_1112/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Ut_ilm_bxd_hipp_noe_1112/summary.rtf b/general/datasets/Ut_ilm_bxd_hipp_noe_1112/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_noe_1112/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Ut_ilm_bxd_hipp_non_0909/experiment-type.rtf b/general/datasets/Ut_ilm_bxd_hipp_non_0909/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_non_0909/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Ut_ilm_bxd_hipp_non_0909/notes.rtf b/general/datasets/Ut_ilm_bxd_hipp_non_0909/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_non_0909/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Ut_ilm_bxd_hipp_non_0909/summary.rtf b/general/datasets/Ut_ilm_bxd_hipp_non_0909/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_non_0909/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Ut_ilm_bxd_hipp_non_1112/notes.rtf b/general/datasets/Ut_ilm_bxd_hipp_non_1112/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_non_1112/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Ut_ilm_bxd_hipp_non_1112/summary.rtf b/general/datasets/Ut_ilm_bxd_hipp_non_1112/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_non_1112/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Ut_ilm_bxd_hipp_nos_0909/notes.rtf b/general/datasets/Ut_ilm_bxd_hipp_nos_0909/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_nos_0909/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Ut_ilm_bxd_hipp_nos_0909/summary.rtf b/general/datasets/Ut_ilm_bxd_hipp_nos_0909/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_nos_0909/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Ut_ilm_bxd_hipp_nos_1112/notes.rtf b/general/datasets/Ut_ilm_bxd_hipp_nos_1112/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_nos_1112/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Ut_ilm_bxd_hipp_nos_1112/summary.rtf b/general/datasets/Ut_ilm_bxd_hipp_nos_1112/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_nos_1112/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Ut_ilm_bxd_hipp_rse_0909/notes.rtf b/general/datasets/Ut_ilm_bxd_hipp_rse_0909/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_rse_0909/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Ut_ilm_bxd_hipp_rse_0909/summary.rtf b/general/datasets/Ut_ilm_bxd_hipp_rse_0909/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_rse_0909/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Ut_ilm_bxd_hipp_rse_1112/notes.rtf b/general/datasets/Ut_ilm_bxd_hipp_rse_1112/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_rse_1112/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Ut_ilm_bxd_hipp_rse_1112/summary.rtf b/general/datasets/Ut_ilm_bxd_hipp_rse_1112/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_rse_1112/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Ut_ilm_bxd_hipp_rss_0909/notes.rtf b/general/datasets/Ut_ilm_bxd_hipp_rss_0909/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_rss_0909/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Ut_ilm_bxd_hipp_rss_0909/summary.rtf b/general/datasets/Ut_ilm_bxd_hipp_rss_0909/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_rss_0909/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Ut_ilm_bxd_hipp_rss_1112/notes.rtf b/general/datasets/Ut_ilm_bxd_hipp_rss_1112/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_rss_1112/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Ut_ilm_bxd_hipp_rss_1112/summary.rtf b/general/datasets/Ut_ilm_bxd_hipp_rss_1112/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Ut_ilm_bxd_hipp_rss_1112/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Ut_vgx_hel1014/acknowledgment.rtf b/general/datasets/Ut_vgx_hel1014/acknowledgment.rtf
new file mode 100644
index 0000000..1853348
--- /dev/null
+++ b/general/datasets/Ut_vgx_hel1014/acknowledgment.rtf
@@ -0,0 +1 @@
+We thank Varigenix and Charle River Laboratory for their donation of BXD cyropreserved hepatcytes. We thank Jesse Ingels for preparing RNA samples. We thank Lorne Rose and the UTHSC Molecular Resource Center for processing RNA samples and generating array data. We thank Arthur Centeno for data entry. We thank the UTHSC CITG and the UT-ORNL Governor's chair for support of microarray analysis.
diff --git a/general/datasets/Ut_vgx_hel1014/cases.rtf b/general/datasets/Ut_vgx_hel1014/cases.rtf
new file mode 100644
index 0000000..e06c56f
--- /dev/null
+++ b/general/datasets/Ut_vgx_hel1014/cases.rtf
@@ -0,0 +1,266 @@
+
+
+
+ | Sample ID |
+ Varigenix Strain |
+ Sex |
+ RNA Concentrations
+ ng/ul |
+ 260/280 |
+ 260/230 |
+ Agilent
+ Concentration(ng/ul) |
+ RIN |
+
+
+ | V1 |
+ BXD32 |
+ M |
+ 1414.8 |
+ 2.09 |
+ 2.21 |
+ 3,062 |
+ 9.3 |
+
+
+ | V2 |
+ BXD1 |
+ M |
+ 1608.9 |
+ 2.11 |
+ 2.24 |
+ 3,102 |
+ 9.3 |
+
+
+ | V3 |
+ BXD5 |
+ M |
+ 1263.91 |
+ 2.1 |
+ 2.09 |
+ 2,460 |
+ 8.5 |
+
+
+ | V4 |
+ BXD31 |
+ M |
+ 1793.95 |
+ 2.1 |
+ 2.22 |
+ 3,387 |
+ 8.5 |
+
+
+ | V5 |
+ BXD8 |
+ M |
+ 1193.21 |
+ 2.1 |
+ 2.17 |
+ 2,293 |
+ 9.3 |
+
+
+ | V6 |
+ BXD18 |
+ M |
+ 1041.05 |
+ 2.13 |
+ 2.17 |
+ 2,115 |
+ 9.2 |
+
+
+ | V7 |
+ BXD42 |
+ M |
+ 398.28 |
+ 1.99 |
+ 2.28 |
+ 1,519 |
+ 8.3 |
+
+
+ | V8 |
+ BXD29 |
+ M |
+ 477.37 |
+ 2.02 |
+ 2.24 |
+ 1,301 |
+ 8.1 |
+
+
+ | V9 |
+ BXD21 |
+ M |
+ 414.6 |
+ 2 |
+ 2.27 |
+ 1,174 |
+ 8.3 |
+
+
+ | V10 |
+ BXD27 |
+ M |
+ 438.61 |
+ 2.02 |
+ 2.27 |
+ 1,100 |
+ 8.1 |
+
+
+ | V11 |
+ BXD16 |
+ M |
+ 436.21 |
+ 2.01 |
+ 2.27 |
+ 868 |
+ 8.5 |
+
+
+ | V12 |
+ BXD19 |
+ M |
+ 489.12 |
+ 2.01 |
+ 2.26 |
+ 1,277 |
+ 8 |
+
+
+ | V13 |
+ BXD22 |
+ M |
+ 1032.89 |
+ 2.09 |
+ 2.22 |
+ 2,060 |
+ 7.8 |
+
+
+ | V14 |
+ BXD38 |
+ M |
+ 510.24 |
+ 2.01 |
+ 2.22 |
+ 1,213 |
+ 8 |
+
+
+ | V15 |
+ BXD34 |
+ M |
+ 1021.26 |
+ 2.09 |
+ 2.24 |
+ 1,514 |
+ 8.2 |
+
+
+ | V16 |
+ BXD20 |
+ M |
+ 330.85 |
+ 2 |
+ 2.27 |
+ 901 |
+ 8.1 |
+
+
+ | V17 |
+ BXD15 |
+ M |
+ 1220.54 |
+ 2.1 |
+ 2.21 |
+ 1,909 |
+ 8.1 |
+
+
+ | V18 |
+ BXD6 |
+ M |
+ 1001.04 |
+ 2.09 |
+ 2.2 |
+ 1,523 |
+ 8.3 |
+
+
+ | V19 |
+ BXD13 |
+ M |
+ 1241.88 |
+ 2.1 |
+ 2.21 |
+ 1,770 |
+ 8.2 |
+
+
+ | V20 |
+ BXD40 |
+ M |
+ 1032.04 |
+ 2.08 |
+ 2.22 |
+ 1,985 |
+ 8.2 |
+
+
+ | V21 |
+ BXD14 |
+ M |
+ 881.62 |
+ 2.11 |
+ 2.19 |
+ 481 |
+ 8.7 |
+
+
+ | V22 |
+ BXD2 |
+ M |
+ 1069.09 |
+ 2.08 |
+ 2.22 |
+ 1,536 |
+ 8.2 |
+
+
+ | V23 |
+ BXD28 |
+ M |
+ 452.6 |
+ 2 |
+ 2.26 |
+ 2,567 |
+ 7.9 |
+
+
+ | V24 |
+ BXD11 |
+ M |
+ 930.72 |
+ 2.07 |
+ 2.21 |
+ 999 |
+ 8.5 |
+
+
+ | V25 |
+ BXD39 |
+ M |
+ 1177.27 |
+ 2.07 |
+ 2.23 |
+ 838 |
+ 8.7 |
+
+
+
diff --git a/general/datasets/Ut_vgx_hel1014/citation.rtf b/general/datasets/Ut_vgx_hel1014/citation.rtf
new file mode 100644
index 0000000..09eb6d1
--- /dev/null
+++ b/general/datasets/Ut_vgx_hel1014/citation.rtf
@@ -0,0 +1 @@
+In progress.
diff --git a/general/datasets/Ut_vgx_hel1014/contributors.rtf b/general/datasets/Ut_vgx_hel1014/contributors.rtf
new file mode 100644
index 0000000..bfa5fbf
--- /dev/null
+++ b/general/datasets/Ut_vgx_hel1014/contributors.rtf
@@ -0,0 +1 @@
+Robert W. Williams, Roberrt E. Scott and colleagues. Cells were donated to Williams group by Varigenix Inc. and CRL Inc.
diff --git a/general/datasets/Ut_vgx_hel1014/experiment-design.rtf b/general/datasets/Ut_vgx_hel1014/experiment-design.rtf
new file mode 100644
index 0000000..323648a
--- /dev/null
+++ b/general/datasets/Ut_vgx_hel1014/experiment-design.rtf
@@ -0,0 +1,3 @@
+Control hepatocyte mRNA expression data prior to any treatment for young adult male BXD strains. This is esssentially the mRNA state of frozen hepatocytes.
+
+
diff --git a/general/datasets/Ut_vgx_hel1014/platform.rtf b/general/datasets/Ut_vgx_hel1014/platform.rtf
new file mode 100644
index 0000000..61c48c5
--- /dev/null
+++ b/general/datasets/Ut_vgx_hel1014/platform.rtf
@@ -0,0 +1 @@
+Affy Mouse Gene 1.0 ST (GPL6246)
diff --git a/general/datasets/Ut_vgx_hel1014/processing.rtf b/general/datasets/Ut_vgx_hel1014/processing.rtf
new file mode 100644
index 0000000..662571f
--- /dev/null
+++ b/general/datasets/Ut_vgx_hel1014/processing.rtf
@@ -0,0 +1 @@
+Standard 2z+8 of log2 data. RMA data were log2 transformed (adding an olffset of 1 to avoid negative values). Variance was stablized (i.e. each array was converted to a set of Z scores). Z scores were then multipled by 2. Mean Z was then shifted from 0 to to 8 units per array.
diff --git a/general/datasets/Ut_vgx_hel1014/summary.rtf b/general/datasets/Ut_vgx_hel1014/summary.rtf
new file mode 100644
index 0000000..8e4cabf
--- /dev/null
+++ b/general/datasets/Ut_vgx_hel1014/summary.rtf
@@ -0,0 +1 @@
+mRNA levels in cryopreserved BXD strain hepatotcytes (males at 60 days of age) immediately after thawing to 4 deg C. This is the "frozen state" mRNA status.
diff --git a/general/datasets/Ut_vgx_hel1014/tissue.rtf b/general/datasets/Ut_vgx_hel1014/tissue.rtf
new file mode 100644
index 0000000..94ad98a
--- /dev/null
+++ b/general/datasets/Ut_vgx_hel1014/tissue.rtf
@@ -0,0 +1,9 @@
+
+
+Hepatocytes prepared by Rob Kaiser at CRL Piedmont in Spring of 2011. Held in liquid nitrogen (vapor phase) until use Fall 2014 at UTHSC.
+
+One vial of hepatocytes in 1 ml of freeze media was wiped with 70% ETOH, quick thawed by swift agitation in a 37 degree C water bath until a small amount of ice remained in the vial. Contents of the vial were removed with a sterile 1000 ul pipette tip and added to a 5 ml sterile polypropylene tube on ice containing 3 ml of ice-cold sterile 1x PBS. sitting in ice. One ml of sterile ice-cold 1x PBS was added to the original vial to remove any remaining cells and added to the 5 ml tube on ice. This process was quickly repeated with three more vials of cells. Four 5 ml tubes were centrifuged at 8,000 rpm at 4 degrees C for 4 minutes to pellet hepatocytes. PBS diluted freeze media was completely removed from the cell pellet. Entire process for sets of vials took about 7 minutes until RNA lysis buffer was added.
+
+The QIAgen AllPrep DNA/RNA mini kit was used in conjunction with the QIAcube for purification of DNA and RNA from the hepatocytes. 600 ul of kit lysis buffer was added to pelleted cells, along with one 5 mm sterile stainless steel bead and cells were completely disrupted using the TissueLyser. The QIAcube protocol was used first for DNA extraction (held at -80 deg C for future use) and the flow-through containing total RNA was then used for the second purification.
+
+Any residual DNA was removed from the RNA before Agilent quantification of concentration and RIN, using the QIAgen DNase I reagent, followed by ethanol precipitation and resuspension of DNA-free total RNA in 50 ul RNAse free water.
diff --git a/general/datasets/Uthsc_1107_rankinv/summary.rtf b/general/datasets/Uthsc_1107_rankinv/summary.rtf
new file mode 100644
index 0000000..cc6ac0f
--- /dev/null
+++ b/general/datasets/Uthsc_1107_rankinv/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 42, Name: HQF BXD Striatum ILM6.1 (Dec10)
\ No newline at end of file
diff --git a/general/datasets/Uthsc_b6d2ri_h_0912/summary.rtf b/general/datasets/Uthsc_b6d2ri_h_0912/summary.rtf
new file mode 100644
index 0000000..a0fc73e
--- /dev/null
+++ b/general/datasets/Uthsc_b6d2ri_h_0912/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 155, Name: UTHSC B6D2RI Aged Hippocampus Affy Mouse Gene 1.0 ST (Sep12)
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_aged_eye_rnaseq_tpm_log2_1120/experiment-design.rtf b/general/datasets/Uthsc_bxd_aged_eye_rnaseq_tpm_log2_1120/experiment-design.rtf
new file mode 100644
index 0000000..2f8cedc
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_aged_eye_rnaseq_tpm_log2_1120/experiment-design.rtf
@@ -0,0 +1 @@
+Total RNA was extracted using Trizol® reagent (Invitrogen, Grand Island, NY, USA) according to the manufacturer’s instructions. Approximately 30 mg of PFC tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been treated with DNase to avoid DNA contamination, and verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/Uthsc_bxd_aged_eye_rnaseq_tpm_log2_1120/processing.rtf b/general/datasets/Uthsc_bxd_aged_eye_rnaseq_tpm_log2_1120/processing.rtf
new file mode 100644
index 0000000..8e460ff
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_aged_eye_rnaseq_tpm_log2_1120/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/Uthsc_bxd_aged_eye_rnaseq_tpm_log2_1120/specifics.rtf b/general/datasets/Uthsc_bxd_aged_eye_rnaseq_tpm_log2_1120/specifics.rtf
new file mode 100644
index 0000000..4d2bd9f
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_aged_eye_rnaseq_tpm_log2_1120/specifics.rtf
@@ -0,0 +1,4332 @@
+BXD Eye (12~18 Month) RNA-Seq (Oct30) TPM Log2
+
+The table of samples that are finally used for this study.
+
+
+
+
+ |
+ Index
+ |
+
+ RNA ID
+ |
+
+ case ID
+ |
+
+ DA_corrected_strain
+ |
+
+ Corrected Sex
+ |
+
+ AgeAtDeath days
+ |
+
+ Tissue
+ |
+
+
+ |
+ 1
+ |
+
+ E18
+ |
+
+ 050115.16
+ |
+
+ BXD75
+ |
+
+ Female
+ |
+
+ 460
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 2
+ |
+
+ E19
+ |
+
+ 050115.17
+ |
+
+ BXD75
+ |
+
+ Female
+ |
+
+ 460
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 3
+ |
+
+ E21
+ |
+
+ 042715.10
+ |
+
+ D2B6F1
+ |
+
+ Female
+ |
+
+ 500
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 4
+ |
+
+ E22
+ |
+
+ 050115.19
+ |
+
+ BXD79
+ |
+
+ Female
+ |
+
+ 468
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 5
+ |
+
+ E31
+ |
+
+ 121515.13
+ |
+
+ BXD45
+ |
+
+ Female
+ |
+
+ 507
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 6
+ |
+
+ E33
+ |
+
+ 012615.10
+ |
+
+ BXD45
+ |
+
+ Female
+ |
+
+ 384
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 7
+ |
+
+ E34
+ |
+
+ 012615.04
+ |
+
+ BXD62
+ |
+
+ Female
+ |
+
+ 376
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 8
+ |
+
+ E40
+ |
+
+ 021213.21
+ |
+
+ BXD79
+ |
+
+ Female
+ |
+
+ 378
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 9
+ |
+
+ E49
+ |
+
+ 021213.13
+ |
+
+ BXD60
+ |
+
+ Female
+ |
+
+ 530
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 10
+ |
+
+ E60
+ |
+
+ 101713.01
+ |
+
+ BXD60
+ |
+
+ Female
+ |
+
+ 374
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 11
+ |
+
+ E62
+ |
+
+ 090612.07
+ |
+
+ BXD73b
+ |
+
+ Female
+ |
+
+ 377
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 12
+ |
+
+ E63
+ |
+
+ 090612.08
+ |
+
+ BXD73b
+ |
+
+ Female
+ |
+
+ 377
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 13
+ |
+
+ E65
+ |
+
+ 050912.04
+ |
+
+ BXD34
+ |
+
+ Female
+ |
+
+ 419
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 14
+ |
+
+ E67
+ |
+
+ 42214.08
+ |
+
+ BXD40
+ |
+
+ Female
+ |
+
+ 362
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 15
+ |
+
+ E72
+ |
+
+ 42214.04
+ |
+
+ BXD24
+ |
+
+ Female
+ |
+
+ 377
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 16
+ |
+
+ E75
+ |
+
+ 42214.03
+ |
+
+ BXD24
+ |
+
+ Female
+ |
+
+ 377
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 17
+ |
+
+ E78
+ |
+
+ 42314.1
+ |
+
+ B6D2F1
+ |
+
+ Male
+ |
+
+ 364
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 18
+ |
+
+ E82
+ |
+
+ 121615.05
+ |
+
+ BXD62
+ |
+
+ Female
+ |
+
+ 525
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 19
+ |
+
+ E87
+ |
+
+ 101014.10
+ |
+
+ BXD95
+ |
+
+ Female
+ |
+
+ 536
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 20
+ |
+
+ E89
+ |
+
+ 121615.22
+ |
+
+ BXD89
+ |
+
+ Female
+ |
+
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ Eyeball
+ |
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+ |
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+ |
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+ |
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+ *052220.21
+ |
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+ BXD73a
+ |
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+ Female
+ |
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+ 408
+ |
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+ Eyeball
+ |
+
+
+ |
+ 124
+ |
+
+ E502
+ |
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+ |
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+ BXD11
+ |
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+ Male
+ |
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+ 379
+ |
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+ Eyeball
+ |
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+
+ |
+ 125
+ |
+
+ E503
+ |
+
+ *052220.22
+ |
+
+ DBA/2J-Gpnmb
+ |
+
+ Female
+ |
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+ 439
+ |
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+ Eyeball
+ |
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+
+ |
+ 126
+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ 478
+ |
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+ Eyeball
+ |
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+
+ |
+ 128
+ |
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+ E542
+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+
+ |
+ 129
+ |
+
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+ |
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+ |
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+ BXD29
+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ 364
+ |
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+ Eyeball
+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ Eyeball
+ |
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+ |
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+ |
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+ |
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+ |
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+ Male
+ |
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+ |
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+ |
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+
+ |
+ 133
+ |
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+ |
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+ |
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+ |
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+ Female
+ |
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+ |
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+ Eyeball
+ |
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+
+ |
+ 134
+ |
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+ |
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+ |
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+ DBA/2J
+ |
+
+ Male
+ |
+
+ 392
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 135
+ |
+
+ E554
+ |
+
+ *061119.15
+ |
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+ DBA/2J
+ |
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+ Male
+ |
+
+ 392
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 136
+ |
+
+ E556
+ |
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+ |
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+ DBA/2J
+ |
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+ |
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+ |
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+ |
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+
+ |
+ 137
+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ Male
+ |
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+ 381
+ |
+
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+ |
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+ |
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+ |
+
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+ |
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+ |
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+ |
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+ Male
+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ 459
+ |
+
+ Eyeball
+ |
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+
+ |
+ 146
+ |
+
+ E591
+ |
+
+ *061319.04
+ |
+
+ BXD48
+ |
+
+ Female
+ |
+
+ 425
+ |
+
+ Eyeball
+ |
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+
+ |
+ 147
+ |
+
+ E592
+ |
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+ *061319.05
+ |
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+ BXD48
+ |
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+ |
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+ |
+
+ Eyeball
+ |
+
+
+ |
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+ |
+
+ E593
+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
+
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+ |
+
+ Eyeball
+ |
+
+
+ |
+ 152
+ |
+
+ E605
+ |
+
+ *013020.54
+ |
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+ BXD102
+ |
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+ |
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+ |
+
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+ |
+
+
+ |
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+ |
+
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+ |
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+ |
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+ |
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+ Male
+ |
+
+ 366
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 154
+ |
+
+ E625
+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+
+ |
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+ |
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+ |
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+ |
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+ |
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+
+ |
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+ |
+
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+ |
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+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
+
+ |
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+ |
+
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+ |
+
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+ |
+
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+ |
+
+ Female
+ |
+
+ 378
+ |
+
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+ |
+
+
+ |
+ 159
+ |
+
+ E639
+ |
+
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+ |
+
+ BXD90
+ |
+
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+ |
+
+ 378
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 160
+ |
+
+ E662
+ |
+
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+ |
+
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+ |
+
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+ |
+
+ 410
+ |
+
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+ |
+
+
+ |
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+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
+
+ |
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+ |
+
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+ |
+
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+ |
+
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+ |
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+ |
+
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+ |
+
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+ |
+
+
+ |
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+ |
+
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+ |
+
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+ |
+
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+ |
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+ |
+
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+ |
+
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+ |
+
+
+ |
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+ |
+
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+ |
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+ |
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+
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+
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+ |
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+
+ |
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+ |
+
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+ |
+
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
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+ |
+
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+ |
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+
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+ |
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+ |
+
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+ |
+
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+ |
+
+
+ |
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+ |
+
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+ |
+
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+ |
+
+ DBA/2J-Gpnmb
+ |
+
+ Female
+ |
+
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+ |
+
+ Eyeball
+ |
+
+
+ |
+ 169
+ |
+
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+ |
+
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+ |
+
+ DBA/2J-Gpnmb
+ |
+
+ Female
+ |
+
+ 458
+ |
+
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+ |
+
+
+ |
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+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
+ Eyeball
+ |
+
+
+ |
+ 171
+ |
+
+ E682
+ |
+
+ *052920.02
+ |
+
+ C57BL/6J
+ |
+
+ Female
+ |
+
+ 433
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 172
+ |
+
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+ |
+
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+ |
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+ |
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+ |
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+ |
+
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+ |
+
+
+ |
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+ |
+
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+ |
+
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+ |
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+ |
+
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+
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+ |
+
+
+ |
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+ |
+
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+ |
+
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+ |
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+ |
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+ |
+
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+ |
+
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+ |
+
+
+ |
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+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
+
+ |
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+ |
+
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+ |
+
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+ |
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+ |
+
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+ |
+
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+ |
+
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+ |
+
+
+ |
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+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
+ Eyeball
+ |
+
+
+ |
+ 178
+ |
+
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+ |
+
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+ |
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+ |
+
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+ |
+
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+ |
+
+ Eyeball
+ |
+
+
+ |
+ 179
+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
+ 387
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 180
+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
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+ |
+
+ Eyeball
+ |
+
+
+ |
+ 181
+ |
+
+ E746
+ |
+
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+ |
+
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+ |
+
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+ |
+
+ 457
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 182
+ |
+
+ E749
+ |
+
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+ |
+
+ BXD2
+ |
+
+ Female
+ |
+
+ 399
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 183
+ |
+
+ E750
+ |
+
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+ |
+
+ BXD2
+ |
+
+ Male
+ |
+
+ 399
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 184
+ |
+
+ E753
+ |
+
+ *072120.68
+ |
+
+ BXD169
+ |
+
+ Female
+ |
+
+ 441
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 185
+ |
+
+ E754
+ |
+
+ *072120.69
+ |
+
+ BXD169
+ |
+
+ Male
+ |
+
+ 441
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 186
+ |
+
+ E759
+ |
+
+ *072120.72
+ |
+
+ BXD187
+ |
+
+ Female
+ |
+
+ 354
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 187
+ |
+
+ E760
+ |
+
+ *072120.73
+ |
+
+ BXD187
+ |
+
+ Male
+ |
+
+ 354
+ |
+
+ Eyeball
+ |
+
+
+
diff --git a/general/datasets/Uthsc_bxd_aged_eye_rnaseq_tpm_log2_1120/tissue.rtf b/general/datasets/Uthsc_bxd_aged_eye_rnaseq_tpm_log2_1120/tissue.rtf
new file mode 100644
index 0000000..bbfb410
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_aged_eye_rnaseq_tpm_log2_1120/tissue.rtf
@@ -0,0 +1 @@
+The animals were sacrificed under saturated isoflurane. Eyeballs from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Uthsc_bxd_agehipp0515/cases.rtf b/general/datasets/Uthsc_bxd_agehipp0515/cases.rtf
new file mode 100644
index 0000000..2b37c95
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_agehipp0515/cases.rtf
@@ -0,0 +1,1258 @@
+The study includes 137 mice (11~25 months old) from 73 strains (B6, D2, DBF1, and 70 BXD strains). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+The table of samples that are finally used for this study:
+
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Sex |
+ RNA ID |
+ Age |
+ Phase |
+ Tissue |
+
+
+ | 1 |
+ BXD1 |
+ F |
+ R7281H |
+ 448 |
+ II |
+ Hippocampus |
+
+
+ | 2 |
+ BXD1 |
+ M |
+ R7276H |
+ 323 |
+ II |
+ Hippocampus |
+
+
+ | 3 |
+ BXD2 |
+ M |
+ R7261H |
+ 394 |
+ I |
+ Hippocampus |
+
+
+ | 4 |
+ BXD2 |
+ F |
+ R7256H |
+ 456 |
+ I |
+ Hippocampus |
+
+
+ | 5 |
+ BXD6 |
+ M |
+ R7223H |
+ 526 |
+ I |
+ Hippocampus |
+
+
+ | 6 |
+ BXD8 |
+ M |
+ R7203H |
+ 471 |
+ I |
+ Hippocampus |
+
+
+ | 7 |
+ BXD8 |
+ F |
+ R7200H |
+ 460 |
+ I |
+ Hippocampus |
+
+
+ | 8 |
+ BXD8 |
+ F |
+ R7198H |
+ 433 |
+ I |
+ Hippocampus |
+
+
+ | 9 |
+ BXD9 |
+ F |
+ R7294H |
+ 456 |
+ II |
+ Hippocampus |
+
+
+ | 10 |
+ BXD11 |
+ M |
+ R7300H |
+ 457 |
+ II |
+ Hippocampus |
+
+
+ | 11 |
+ BXD11 |
+ F |
+ R7227H |
+ 536 |
+ I |
+ Hippocampus |
+
+
+ | 12 |
+ BXD12 |
+ F |
+ R7183H |
+ 506 |
+ I |
+ Hippocampus |
+
+
+ | 13 |
+ BXD12 |
+ F |
+ R7233H |
+ 561 |
+ I |
+ Hippocampus |
+
+
+ | 14 |
+ BXD12 |
+ M |
+ R7234H |
+ 606 |
+ I |
+ Hippocampus |
+
+
+ | 15 |
+ BXD14 |
+ F |
+ R7238H |
+ 605 |
+ I |
+ Hippocampus |
+
+
+ | 16 |
+ BXD14 |
+ M |
+ R7235H |
+ 605 |
+ I |
+ Hippocampus |
+
+
+ | 17 |
+ BXD16 |
+ F |
+ R7236H |
+ 561 |
+ I |
+ Hippocampus |
+
+
+ | 18 |
+ BXD16 |
+ M |
+ R7239H |
+ 475 |
+ I |
+ Hippocampus |
+
+
+ | 19 |
+ BXD18 |
+ F |
+ R7229H |
+ 493 |
+ I |
+ Hippocampus |
+
+
+ | 20 |
+ BXD19 |
+ F |
+ R7267H |
+ 551 |
+ I |
+ Hippocampus |
+
+
+ | 21 |
+ BXD19 |
+ M |
+ R7268H |
+ 492 |
+ I |
+ Hippocampus |
+
+
+ | 22 |
+ BXD20 |
+ M |
+ R7232H |
+ 506 |
+ I |
+ Hippocampus |
+
+
+ | 23 |
+ BXD20 |
+ M |
+ R7263H |
+ 489 |
+ I |
+ Hippocampus |
+
+
+ | 24 |
+ BXD21 |
+ F |
+ R7230H |
+ 537 |
+ I |
+ Hippocampus |
+
+
+ | 25 |
+ BXD22 |
+ F |
+ R7260H |
+ 502 |
+ I |
+ Hippocampus |
+
+
+ | 26 |
+ BXD22 |
+ M |
+ R7262H |
+ 596 |
+ I |
+ Hippocampus |
+
+
+ | 27 |
+ BXD23 |
+ F |
+ R7258H |
+ 502 |
+ I |
+ Hippocampus |
+
+
+ | 28 |
+ BXD23 |
+ M |
+ R7257H |
+ 462 |
+ I |
+ Hippocampus |
+
+
+ | 29 |
+ BXD24 |
+ M |
+ R7231H |
+ 470 |
+ I |
+ Hippocampus |
+
+
+ | 30 |
+ BXD24 |
+ F |
+ R7228H |
+ 415 |
+ I |
+ Hippocampus |
+
+
+ | 31 |
+ BXD24 |
+ F |
+ R7255H |
+ 456 |
+ I |
+ Hippocampus |
+
+
+ | 32 |
+ BXD25 |
+ F |
+ R7252H |
+ 454 |
+ I |
+ Hippocampus |
+
+
+ | 33 |
+ BXD27 |
+ F |
+ R7286H |
+ 472 |
+ II |
+ Hippocampus |
+
+
+ | 34 |
+ BXD27 |
+ F |
+ R7170H |
+ 472 |
+ I |
+ Hippocampus |
+
+
+ | 35 |
+ BXD28 |
+ M |
+ R7254H |
+ 493 |
+ I |
+ Hippocampus |
+
+
+ | 36 |
+ BXD28 |
+ F |
+ R7251H |
+ 543 |
+ I |
+ Hippocampus |
+
+
+ | 37 |
+ BXD29 |
+ F |
+ R7259H |
+ 483 |
+ I |
+ Hippocampus |
+
+
+ | 38 |
+ BXD33 |
+ M |
+ R7253H |
+ 464 |
+ I |
+ Hippocampus |
+
+
+ | 39 |
+ BXD33 |
+ F |
+ R7174H |
+ 471 |
+ I |
+ Hippocampus |
+
+
+ | 40 |
+ BXD33 |
+ F |
+ R7244H |
+ 448 |
+ I |
+ Hippocampus |
+
+
+ | 41 |
+ BXD33 |
+ M |
+ R7270H |
+ 662 |
+ I |
+ Hippocampus |
+
+
+ | 42 |
+ BXD38 |
+ F |
+ R7242H |
+ 464 |
+ I |
+ Hippocampus |
+
+
+ | 43 |
+ BXD38 |
+ M |
+ R7247H |
+ 446 |
+ I |
+ Hippocampus |
+
+
+ | 44 |
+ BXD39 |
+ M |
+ R7250H |
+ 536 |
+ I |
+ Hippocampus |
+
+
+ | 45 |
+ BXD39 |
+ F |
+ R7173H |
+ 500 |
+ I |
+ Hippocampus |
+
+
+ | 46 |
+ BXD39 |
+ M |
+ R7175H |
+ 500 |
+ I |
+ Hippocampus |
+
+
+ | 47 |
+ BXD40 |
+ F |
+ R7288H |
+ 451 |
+ II |
+ Hippocampus |
+
+
+ | 48 |
+ BXD40 |
+ M |
+ R7210H |
+ 470 |
+ I |
+ Hippocampus |
+
+
+ | 49 |
+ BXD40 |
+ M |
+ R7197H |
+ 614 |
+ I |
+ Hippocampus |
+
+
+ | 50 |
+ BXD42 |
+ F |
+ R7280H |
+ 518 |
+ II |
+ Hippocampus |
+
+
+ | 51 |
+ BXD42 |
+ M |
+ R7246H |
+ 446 |
+ I |
+ Hippocampus |
+
+
+ | 52 |
+ BXD42 |
+ F |
+ R7266H |
+ 486 |
+ I |
+ Hippocampus |
+
+
+ | 53 |
+ BXD43 |
+ F |
+ R7249H |
+ 454 |
+ I |
+ Hippocampus |
+
+
+ | 54 |
+ BXD43 |
+ M |
+ R7248H |
+ 462 |
+ I |
+ Hippocampus |
+
+
+ | 55 |
+ BXD44 |
+ M |
+ R7241H |
+ 415 |
+ I |
+ Hippocampus |
+
+
+ | 56 |
+ BXD44 |
+ M |
+ R7279H |
+ 419 |
+ II |
+ Hippocampus |
+
+
+ | 57 |
+ BXD44 |
+ F |
+ R7243H |
+ 438 |
+ I |
+ Hippocampus |
+
+
+ | 58 |
+ BXD45 |
+ F |
+ R7176H |
+ 451 |
+ I |
+ Hippocampus |
+
+
+ | 59 |
+ BXD48 |
+ F |
+ R7245H |
+ 499 |
+ I |
+ Hippocampus |
+
+
+ | 60 |
+ BXD48 |
+ M |
+ R7220H |
+ 526 |
+ I |
+ Hippocampus |
+
+
+ | 61 |
+ BXD48a |
+ F |
+ R7299H |
+ 479 |
+ II |
+ Hippocampus |
+
+
+ | 62 |
+ BXD48a |
+ M |
+ R7297H |
+ 479 |
+ II |
+ Hippocampus |
+
+
+ | 63 |
+ BXD50 |
+ F |
+ R7224H |
+ 530 |
+ I |
+ Hippocampus |
+
+
+ | 64 |
+ BXD50 |
+ M |
+ R7221H |
+ 530 |
+ I |
+ Hippocampus |
+
+
+ | 65 |
+ BXD51 |
+ F |
+ R7177H |
+ 487 |
+ I |
+ Hippocampus |
+
+
+ | 66 |
+ BXD51 |
+ M |
+ R7290H |
+ 407 |
+ II |
+ Hippocampus |
+
+
+ | 67 |
+ BXD55 |
+ M |
+ R7222H |
+ 528 |
+ I |
+ Hippocampus |
+
+
+ | 68 |
+ BXD55 |
+ F |
+ R7225H |
+ 587 |
+ I |
+ Hippocampus |
+
+
+ | 69 |
+ BXD56 |
+ M |
+ R7178H |
+ 501 |
+ I |
+ Hippocampus |
+
+
+ | 70 |
+ BXD62 |
+ M |
+ R7291H |
+ 439 |
+ II |
+ Hippocampus |
+
+
+ | 71 |
+ BXD63 |
+ M |
+ R7218H |
+ 438 |
+ I |
+ Hippocampus |
+
+
+ | 72 |
+ BXD63 |
+ F |
+ R7215H |
+ 475 |
+ I |
+ Hippocampus |
+
+
+ | 73 |
+ BXD64 |
+ M |
+ R7219H |
+ 528 |
+ I |
+ Hippocampus |
+
+
+ | 74 |
+ BXD64 |
+ F |
+ R7216H |
+ 587 |
+ I |
+ Hippocampus |
+
+
+ | 75 |
+ BXD65 |
+ F |
+ R7217H |
+ 425 |
+ I |
+ Hippocampus |
+
+
+ | 76 |
+ BXD65a |
+ F |
+ R7273H |
+ 389 |
+ II |
+ Hippocampus |
+
+
+ | 77 |
+ BXD65a |
+ M |
+ R7277H |
+ 715 |
+ II |
+ Hippocampus |
+
+
+ | 78 |
+ BXD65b |
+ M |
+ R7271H |
+ 483 |
+ II |
+ Hippocampus |
+
+
+ | 79 |
+ BXD66 |
+ M |
+ R7214H |
+ 463 |
+ I |
+ Hippocampus |
+
+
+ | 80 |
+ BXD66 |
+ F |
+ R7302H |
+ 446 |
+ III |
+ Hippocampus |
+
+
+ | 81 |
+ BXD67 |
+ F |
+ R7240H |
+ 499 |
+ I |
+ Hippocampus |
+
+
+ | 82 |
+ BXD67 |
+ M |
+ R7213H |
+ 425 |
+ I |
+ Hippocampus |
+
+
+ | 83 |
+ BXD67 |
+ F |
+ R7278H |
+ 415 |
+ II |
+ Hippocampus |
+
+
+ | 84 |
+ BXD68 |
+ M |
+ R7212H |
+ 421 |
+ I |
+ Hippocampus |
+
+
+ | 85 |
+ BXD68 |
+ F |
+ R7211H |
+ 415 |
+ I |
+ Hippocampus |
+
+
+ | 86 |
+ BXD69 |
+ F |
+ R7305H |
+ 504 |
+ III |
+ Hippocampus |
+
+
+ | 87 |
+ BXD70 |
+ F |
+ R7207H |
+ 458 |
+ I |
+ Hippocampus |
+
+
+ | 88 |
+ BXD70 |
+ M |
+ R7204H |
+ 460 |
+ I |
+ Hippocampus |
+
+
+ | 89 |
+ BXD71 |
+ M |
+ R7205H |
+ 471 |
+ I |
+ Hippocampus |
+
+
+ | 90 |
+ BXD71 |
+ F |
+ R7208H |
+ 474 |
+ I |
+ Hippocampus |
+
+
+ | 91 |
+ BXD73 |
+ F |
+ R7209H |
+ 470 |
+ I |
+ Hippocampus |
+
+
+ | 92 |
+ BXD73 |
+ M |
+ R7206H |
+ 464 |
+ I |
+ Hippocampus |
+
+
+ | 93 |
+ BXD73a |
+ F |
+ R7181H |
+ 443 |
+ I |
+ Hippocampus |
+
+
+ | 94 |
+ BXD73a |
+ M |
+ R7182H |
+ 614 |
+ I |
+ Hippocampus |
+
+
+ | 95 |
+ BXD76 |
+ M |
+ R7179H |
+ 579 |
+ I |
+ Hippocampus |
+
+
+ | 96 |
+ BXD76 |
+ F |
+ R7188H |
+ 408 |
+ I |
+ Hippocampus |
+
+
+ | 97 |
+ BXD76 |
+ M |
+ R7187H |
+ 564 |
+ I |
+ Hippocampus |
+
+
+ | 98 |
+ BXD77 |
+ M |
+ R7292H |
+ 347 |
+ II |
+ Hippocampus |
+
+
+ | 99 |
+ BXD77 |
+ F |
+ R7201H |
+ 454 |
+ I |
+ Hippocampus |
+
+
+ | 100 |
+ BXD79 |
+ M |
+ R7202H |
+ 485 |
+ I |
+ Hippocampus |
+
+
+ | 101 |
+ BXD79 |
+ F |
+ R7199H |
+ 515 |
+ I |
+ Hippocampus |
+
+
+ | 102 |
+ BXD79 |
+ M |
+ R7298H |
+ 704 |
+ II |
+ Hippocampus |
+
+
+ | 103 |
+ BXD81 |
+ M |
+ R7196H |
+ 515 |
+ I |
+ Hippocampus |
+
+
+ | 104 |
+ BXD81 |
+ F |
+ R7190H |
+ 458 |
+ I |
+ Hippocampus |
+
+
+ | 105 |
+ BXD83 |
+ M |
+ R7184H |
+ 441 |
+ I |
+ Hippocampus |
+
+
+ | 106 |
+ BXD84 |
+ M |
+ R7195H |
+ 474 |
+ I |
+ Hippocampus |
+
+
+ | 107 |
+ BXD84 |
+ M |
+ R7296H |
+ 484 |
+ II |
+ Hippocampus |
+
+
+ | 108 |
+ BXD84 |
+ F |
+ R7192H |
+ 522 |
+ I |
+ Hippocampus |
+
+
+ | 109 |
+ BXD85 |
+ M |
+ R7272H |
+ 425 |
+ II |
+ Hippocampus |
+
+
+ | 110 |
+ BXD85 |
+ F |
+ R7193H |
+ 506 |
+ I |
+ Hippocampus |
+
+
+ | 111 |
+ BXD86 |
+ M |
+ R7191H |
+ 425 |
+ I |
+ Hippocampus |
+
+
+ | 112 |
+ BXD87 |
+ F |
+ R7194H |
+ 425 |
+ I |
+ Hippocampus |
+
+
+ | 113 |
+ BXD87 |
+ M |
+ R7303H |
+ 478 |
+ III |
+ Hippocampus |
+
+
+ | 114 |
+ BXD87 |
+ M |
+ R7186H |
+ 442 |
+ I |
+ Hippocampus |
+
+
+ | 115 |
+ BXD89 |
+ F |
+ R7295H |
+ 446 |
+ II |
+ Hippocampus |
+
+
+ | 116 |
+ BXD90 |
+ M |
+ R7287H |
+ 434 |
+ II |
+ Hippocampus |
+
+
+ | 117 |
+ BXD90 |
+ M |
+ R7293H |
+ 558 |
+ II |
+ Hippocampus |
+
+
+ | 118 |
+ BXD95 |
+ F |
+ R7180H |
+ 467 |
+ I |
+ Hippocampus |
+
+
+ | 119 |
+ BXD95 |
+ M |
+ R7169H |
+ 467 |
+ I |
+ Hippocampus |
+
+
+ | 120 |
+ BXD98 |
+ M |
+ R7237H |
+ 605 |
+ I |
+ Hippocampus |
+
+
+ | 121 |
+ BXD98 |
+ F |
+ R7171H |
+ 639 |
+ I |
+ Hippocampus |
+
+
+ | 122 |
+ BXD98 |
+ F |
+ R7275H |
+ 488 |
+ II |
+ Hippocampus |
+
+
+ | 123 |
+ BXD99 |
+ M |
+ R7189H |
+ 524 |
+ I |
+ Hippocampus |
+
+
+ | 124 |
+ BXD99 |
+ F |
+ R7172H |
+ 471 |
+ I |
+ Hippocampus |
+
+
+ | 125 |
+ BXD100 |
+ F |
+ R7282H |
+ 463 |
+ II |
+ Hippocampus |
+
+
+ | 126 |
+ BXD100 |
+ M |
+ R7283H |
+ 507 |
+ II |
+ Hippocampus |
+
+
+ | 127 |
+ BXD100 |
+ M |
+ R7274H |
+ 577 |
+ II |
+ Hippocampus |
+
+
+ | 128 |
+ BXD100 |
+ F |
+ R7226H |
+ 464 |
+ I |
+ Hippocampus |
+
+
+ | 129 |
+ BXD101 |
+ F |
+ R7284H |
+ 490 |
+ II |
+ Hippocampus |
+
+
+ | 130 |
+ BXD101 |
+ M |
+ R7285H |
+ 408 |
+ II |
+ Hippocampus |
+
+
+ | 131 |
+ C57BL/6J |
+ M |
+ R7264H |
+ 489 |
+ I |
+ Hippocampus |
+
+
+ | 132 |
+ C57BL/6J |
+ M |
+ R7289H |
+ 756 |
+ II |
+ Hippocampus |
+
+
+ | 133 |
+ D2B6F1 |
+ M |
+ R7265H |
+ 492 |
+ I |
+ Hippocampus |
+
+
+ | 134 |
+ D2B6F1 |
+ F |
+ R7304H |
+ 495 |
+ III |
+ Hippocampus |
+
+
+ | 135 |
+ DBA/2J |
+ F |
+ R7185H |
+ 433 |
+ I |
+ Hippocampus |
+
+
+ | 136 |
+ DBA/2J |
+ M |
+ R7269H |
+ 367 |
+ I |
+ Hippocampus |
+
+
+ | 137 |
+ DBA/2J |
+ F |
+ R7301H |
+ 566 |
+ III |
+ Hippocampus |
+
+
+
diff --git a/general/datasets/Uthsc_bxd_agehipp0515/experiment-design.rtf b/general/datasets/Uthsc_bxd_agehipp0515/experiment-design.rtf
new file mode 100644
index 0000000..d6b2d5b
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_agehipp0515/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Extraction
+
+RNA was extracted using the RNeasy mini kit (Qiagen, Valencia, CA, USA) according to the manufactures’ procedure. 2100 BioAnalyzer (Agilent Technologies) was used to evaluate RNA integrity and quality. Samples with RNA Integrity Numbers (RIN values) > 8.0 were run on Affy MoGene1.0 ST at the UTHSC
diff --git a/general/datasets/Uthsc_bxd_agehipp0515/processing.rtf b/general/datasets/Uthsc_bxd_agehipp0515/processing.rtf
new file mode 100644
index 0000000..e951515
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_agehipp0515/processing.rtf
@@ -0,0 +1,3 @@
+About data processing:
+
+Raw microarray data were normalized using the Robust Multichip Array (RMA) method. The expression data were then re-normalized using a modified Z score.
diff --git a/general/datasets/Uthsc_bxd_agehipp0515/specifics.rtf b/general/datasets/Uthsc_bxd_agehipp0515/specifics.rtf
new file mode 100644
index 0000000..3d4ba9a
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_agehipp0515/specifics.rtf
@@ -0,0 +1 @@
+UTHSC BXD Aged Hippocampus Affy MoGene1.0 ST (May15) RMA Gene Level **
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_agehipp0515/tissue.rtf b/general/datasets/Uthsc_bxd_agehipp0515/tissue.rtf
new file mode 100644
index 0000000..3166717
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_agehipp0515/tissue.rtf
@@ -0,0 +1,3 @@
+Tissue Harvest
+
+The animals were sacrificed under saturated isoflurane. Hippocampus from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Uthsc_bxd_all_ages_eye_rnaseq_tpm_log/experiment-design.rtf b/general/datasets/Uthsc_bxd_all_ages_eye_rnaseq_tpm_log/experiment-design.rtf
new file mode 100644
index 0000000..2f8cedc
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_all_ages_eye_rnaseq_tpm_log/experiment-design.rtf
@@ -0,0 +1 @@
+Total RNA was extracted using Trizol® reagent (Invitrogen, Grand Island, NY, USA) according to the manufacturer’s instructions. Approximately 30 mg of PFC tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been treated with DNase to avoid DNA contamination, and verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/Uthsc_bxd_all_ages_eye_rnaseq_tpm_log/processing.rtf b/general/datasets/Uthsc_bxd_all_ages_eye_rnaseq_tpm_log/processing.rtf
new file mode 100644
index 0000000..8e460ff
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_all_ages_eye_rnaseq_tpm_log/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/Uthsc_bxd_all_ages_eye_rnaseq_tpm_log/specifics.rtf b/general/datasets/Uthsc_bxd_all_ages_eye_rnaseq_tpm_log/specifics.rtf
new file mode 100644
index 0000000..8b003fb
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_all_ages_eye_rnaseq_tpm_log/specifics.rtf
@@ -0,0 +1 @@
+UTHSC BXD All Ages Eye RNA-Seq (Nov20) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_all_ages_eye_rnaseq_tpm_log/tissue.rtf b/general/datasets/Uthsc_bxd_all_ages_eye_rnaseq_tpm_log/tissue.rtf
new file mode 100644
index 0000000..bbfb410
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_all_ages_eye_rnaseq_tpm_log/tissue.rtf
@@ -0,0 +1 @@
+The animals were sacrificed under saturated isoflurane. Eyeballs from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Uthsc_bxd_h_0912/cases.rtf b/general/datasets/Uthsc_bxd_h_0912/cases.rtf
new file mode 100644
index 0000000..2b37c95
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_h_0912/cases.rtf
@@ -0,0 +1,1258 @@
+The study includes 137 mice (11~25 months old) from 73 strains (B6, D2, DBF1, and 70 BXD strains). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+The table of samples that are finally used for this study:
+
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Sex |
+ RNA ID |
+ Age |
+ Phase |
+ Tissue |
+
+
+ | 1 |
+ BXD1 |
+ F |
+ R7281H |
+ 448 |
+ II |
+ Hippocampus |
+
+
+ | 2 |
+ BXD1 |
+ M |
+ R7276H |
+ 323 |
+ II |
+ Hippocampus |
+
+
+ | 3 |
+ BXD2 |
+ M |
+ R7261H |
+ 394 |
+ I |
+ Hippocampus |
+
+
+ | 4 |
+ BXD2 |
+ F |
+ R7256H |
+ 456 |
+ I |
+ Hippocampus |
+
+
+ | 5 |
+ BXD6 |
+ M |
+ R7223H |
+ 526 |
+ I |
+ Hippocampus |
+
+
+ | 6 |
+ BXD8 |
+ M |
+ R7203H |
+ 471 |
+ I |
+ Hippocampus |
+
+
+ | 7 |
+ BXD8 |
+ F |
+ R7200H |
+ 460 |
+ I |
+ Hippocampus |
+
+
+ | 8 |
+ BXD8 |
+ F |
+ R7198H |
+ 433 |
+ I |
+ Hippocampus |
+
+
+ | 9 |
+ BXD9 |
+ F |
+ R7294H |
+ 456 |
+ II |
+ Hippocampus |
+
+
+ | 10 |
+ BXD11 |
+ M |
+ R7300H |
+ 457 |
+ II |
+ Hippocampus |
+
+
+ | 11 |
+ BXD11 |
+ F |
+ R7227H |
+ 536 |
+ I |
+ Hippocampus |
+
+
+ | 12 |
+ BXD12 |
+ F |
+ R7183H |
+ 506 |
+ I |
+ Hippocampus |
+
+
+ | 13 |
+ BXD12 |
+ F |
+ R7233H |
+ 561 |
+ I |
+ Hippocampus |
+
+
+ | 14 |
+ BXD12 |
+ M |
+ R7234H |
+ 606 |
+ I |
+ Hippocampus |
+
+
+ | 15 |
+ BXD14 |
+ F |
+ R7238H |
+ 605 |
+ I |
+ Hippocampus |
+
+
+ | 16 |
+ BXD14 |
+ M |
+ R7235H |
+ 605 |
+ I |
+ Hippocampus |
+
+
+ | 17 |
+ BXD16 |
+ F |
+ R7236H |
+ 561 |
+ I |
+ Hippocampus |
+
+
+ | 18 |
+ BXD16 |
+ M |
+ R7239H |
+ 475 |
+ I |
+ Hippocampus |
+
+
+ | 19 |
+ BXD18 |
+ F |
+ R7229H |
+ 493 |
+ I |
+ Hippocampus |
+
+
+ | 20 |
+ BXD19 |
+ F |
+ R7267H |
+ 551 |
+ I |
+ Hippocampus |
+
+
+ | 21 |
+ BXD19 |
+ M |
+ R7268H |
+ 492 |
+ I |
+ Hippocampus |
+
+
+ | 22 |
+ BXD20 |
+ M |
+ R7232H |
+ 506 |
+ I |
+ Hippocampus |
+
+
+ | 23 |
+ BXD20 |
+ M |
+ R7263H |
+ 489 |
+ I |
+ Hippocampus |
+
+
+ | 24 |
+ BXD21 |
+ F |
+ R7230H |
+ 537 |
+ I |
+ Hippocampus |
+
+
+ | 25 |
+ BXD22 |
+ F |
+ R7260H |
+ 502 |
+ I |
+ Hippocampus |
+
+
+ | 26 |
+ BXD22 |
+ M |
+ R7262H |
+ 596 |
+ I |
+ Hippocampus |
+
+
+ | 27 |
+ BXD23 |
+ F |
+ R7258H |
+ 502 |
+ I |
+ Hippocampus |
+
+
+ | 28 |
+ BXD23 |
+ M |
+ R7257H |
+ 462 |
+ I |
+ Hippocampus |
+
+
+ | 29 |
+ BXD24 |
+ M |
+ R7231H |
+ 470 |
+ I |
+ Hippocampus |
+
+
+ | 30 |
+ BXD24 |
+ F |
+ R7228H |
+ 415 |
+ I |
+ Hippocampus |
+
+
+ | 31 |
+ BXD24 |
+ F |
+ R7255H |
+ 456 |
+ I |
+ Hippocampus |
+
+
+ | 32 |
+ BXD25 |
+ F |
+ R7252H |
+ 454 |
+ I |
+ Hippocampus |
+
+
+ | 33 |
+ BXD27 |
+ F |
+ R7286H |
+ 472 |
+ II |
+ Hippocampus |
+
+
+ | 34 |
+ BXD27 |
+ F |
+ R7170H |
+ 472 |
+ I |
+ Hippocampus |
+
+
+ | 35 |
+ BXD28 |
+ M |
+ R7254H |
+ 493 |
+ I |
+ Hippocampus |
+
+
+ | 36 |
+ BXD28 |
+ F |
+ R7251H |
+ 543 |
+ I |
+ Hippocampus |
+
+
+ | 37 |
+ BXD29 |
+ F |
+ R7259H |
+ 483 |
+ I |
+ Hippocampus |
+
+
+ | 38 |
+ BXD33 |
+ M |
+ R7253H |
+ 464 |
+ I |
+ Hippocampus |
+
+
+ | 39 |
+ BXD33 |
+ F |
+ R7174H |
+ 471 |
+ I |
+ Hippocampus |
+
+
+ | 40 |
+ BXD33 |
+ F |
+ R7244H |
+ 448 |
+ I |
+ Hippocampus |
+
+
+ | 41 |
+ BXD33 |
+ M |
+ R7270H |
+ 662 |
+ I |
+ Hippocampus |
+
+
+ | 42 |
+ BXD38 |
+ F |
+ R7242H |
+ 464 |
+ I |
+ Hippocampus |
+
+
+ | 43 |
+ BXD38 |
+ M |
+ R7247H |
+ 446 |
+ I |
+ Hippocampus |
+
+
+ | 44 |
+ BXD39 |
+ M |
+ R7250H |
+ 536 |
+ I |
+ Hippocampus |
+
+
+ | 45 |
+ BXD39 |
+ F |
+ R7173H |
+ 500 |
+ I |
+ Hippocampus |
+
+
+ | 46 |
+ BXD39 |
+ M |
+ R7175H |
+ 500 |
+ I |
+ Hippocampus |
+
+
+ | 47 |
+ BXD40 |
+ F |
+ R7288H |
+ 451 |
+ II |
+ Hippocampus |
+
+
+ | 48 |
+ BXD40 |
+ M |
+ R7210H |
+ 470 |
+ I |
+ Hippocampus |
+
+
+ | 49 |
+ BXD40 |
+ M |
+ R7197H |
+ 614 |
+ I |
+ Hippocampus |
+
+
+ | 50 |
+ BXD42 |
+ F |
+ R7280H |
+ 518 |
+ II |
+ Hippocampus |
+
+
+ | 51 |
+ BXD42 |
+ M |
+ R7246H |
+ 446 |
+ I |
+ Hippocampus |
+
+
+ | 52 |
+ BXD42 |
+ F |
+ R7266H |
+ 486 |
+ I |
+ Hippocampus |
+
+
+ | 53 |
+ BXD43 |
+ F |
+ R7249H |
+ 454 |
+ I |
+ Hippocampus |
+
+
+ | 54 |
+ BXD43 |
+ M |
+ R7248H |
+ 462 |
+ I |
+ Hippocampus |
+
+
+ | 55 |
+ BXD44 |
+ M |
+ R7241H |
+ 415 |
+ I |
+ Hippocampus |
+
+
+ | 56 |
+ BXD44 |
+ M |
+ R7279H |
+ 419 |
+ II |
+ Hippocampus |
+
+
+ | 57 |
+ BXD44 |
+ F |
+ R7243H |
+ 438 |
+ I |
+ Hippocampus |
+
+
+ | 58 |
+ BXD45 |
+ F |
+ R7176H |
+ 451 |
+ I |
+ Hippocampus |
+
+
+ | 59 |
+ BXD48 |
+ F |
+ R7245H |
+ 499 |
+ I |
+ Hippocampus |
+
+
+ | 60 |
+ BXD48 |
+ M |
+ R7220H |
+ 526 |
+ I |
+ Hippocampus |
+
+
+ | 61 |
+ BXD48a |
+ F |
+ R7299H |
+ 479 |
+ II |
+ Hippocampus |
+
+
+ | 62 |
+ BXD48a |
+ M |
+ R7297H |
+ 479 |
+ II |
+ Hippocampus |
+
+
+ | 63 |
+ BXD50 |
+ F |
+ R7224H |
+ 530 |
+ I |
+ Hippocampus |
+
+
+ | 64 |
+ BXD50 |
+ M |
+ R7221H |
+ 530 |
+ I |
+ Hippocampus |
+
+
+ | 65 |
+ BXD51 |
+ F |
+ R7177H |
+ 487 |
+ I |
+ Hippocampus |
+
+
+ | 66 |
+ BXD51 |
+ M |
+ R7290H |
+ 407 |
+ II |
+ Hippocampus |
+
+
+ | 67 |
+ BXD55 |
+ M |
+ R7222H |
+ 528 |
+ I |
+ Hippocampus |
+
+
+ | 68 |
+ BXD55 |
+ F |
+ R7225H |
+ 587 |
+ I |
+ Hippocampus |
+
+
+ | 69 |
+ BXD56 |
+ M |
+ R7178H |
+ 501 |
+ I |
+ Hippocampus |
+
+
+ | 70 |
+ BXD62 |
+ M |
+ R7291H |
+ 439 |
+ II |
+ Hippocampus |
+
+
+ | 71 |
+ BXD63 |
+ M |
+ R7218H |
+ 438 |
+ I |
+ Hippocampus |
+
+
+ | 72 |
+ BXD63 |
+ F |
+ R7215H |
+ 475 |
+ I |
+ Hippocampus |
+
+
+ | 73 |
+ BXD64 |
+ M |
+ R7219H |
+ 528 |
+ I |
+ Hippocampus |
+
+
+ | 74 |
+ BXD64 |
+ F |
+ R7216H |
+ 587 |
+ I |
+ Hippocampus |
+
+
+ | 75 |
+ BXD65 |
+ F |
+ R7217H |
+ 425 |
+ I |
+ Hippocampus |
+
+
+ | 76 |
+ BXD65a |
+ F |
+ R7273H |
+ 389 |
+ II |
+ Hippocampus |
+
+
+ | 77 |
+ BXD65a |
+ M |
+ R7277H |
+ 715 |
+ II |
+ Hippocampus |
+
+
+ | 78 |
+ BXD65b |
+ M |
+ R7271H |
+ 483 |
+ II |
+ Hippocampus |
+
+
+ | 79 |
+ BXD66 |
+ M |
+ R7214H |
+ 463 |
+ I |
+ Hippocampus |
+
+
+ | 80 |
+ BXD66 |
+ F |
+ R7302H |
+ 446 |
+ III |
+ Hippocampus |
+
+
+ | 81 |
+ BXD67 |
+ F |
+ R7240H |
+ 499 |
+ I |
+ Hippocampus |
+
+
+ | 82 |
+ BXD67 |
+ M |
+ R7213H |
+ 425 |
+ I |
+ Hippocampus |
+
+
+ | 83 |
+ BXD67 |
+ F |
+ R7278H |
+ 415 |
+ II |
+ Hippocampus |
+
+
+ | 84 |
+ BXD68 |
+ M |
+ R7212H |
+ 421 |
+ I |
+ Hippocampus |
+
+
+ | 85 |
+ BXD68 |
+ F |
+ R7211H |
+ 415 |
+ I |
+ Hippocampus |
+
+
+ | 86 |
+ BXD69 |
+ F |
+ R7305H |
+ 504 |
+ III |
+ Hippocampus |
+
+
+ | 87 |
+ BXD70 |
+ F |
+ R7207H |
+ 458 |
+ I |
+ Hippocampus |
+
+
+ | 88 |
+ BXD70 |
+ M |
+ R7204H |
+ 460 |
+ I |
+ Hippocampus |
+
+
+ | 89 |
+ BXD71 |
+ M |
+ R7205H |
+ 471 |
+ I |
+ Hippocampus |
+
+
+ | 90 |
+ BXD71 |
+ F |
+ R7208H |
+ 474 |
+ I |
+ Hippocampus |
+
+
+ | 91 |
+ BXD73 |
+ F |
+ R7209H |
+ 470 |
+ I |
+ Hippocampus |
+
+
+ | 92 |
+ BXD73 |
+ M |
+ R7206H |
+ 464 |
+ I |
+ Hippocampus |
+
+
+ | 93 |
+ BXD73a |
+ F |
+ R7181H |
+ 443 |
+ I |
+ Hippocampus |
+
+
+ | 94 |
+ BXD73a |
+ M |
+ R7182H |
+ 614 |
+ I |
+ Hippocampus |
+
+
+ | 95 |
+ BXD76 |
+ M |
+ R7179H |
+ 579 |
+ I |
+ Hippocampus |
+
+
+ | 96 |
+ BXD76 |
+ F |
+ R7188H |
+ 408 |
+ I |
+ Hippocampus |
+
+
+ | 97 |
+ BXD76 |
+ M |
+ R7187H |
+ 564 |
+ I |
+ Hippocampus |
+
+
+ | 98 |
+ BXD77 |
+ M |
+ R7292H |
+ 347 |
+ II |
+ Hippocampus |
+
+
+ | 99 |
+ BXD77 |
+ F |
+ R7201H |
+ 454 |
+ I |
+ Hippocampus |
+
+
+ | 100 |
+ BXD79 |
+ M |
+ R7202H |
+ 485 |
+ I |
+ Hippocampus |
+
+
+ | 101 |
+ BXD79 |
+ F |
+ R7199H |
+ 515 |
+ I |
+ Hippocampus |
+
+
+ | 102 |
+ BXD79 |
+ M |
+ R7298H |
+ 704 |
+ II |
+ Hippocampus |
+
+
+ | 103 |
+ BXD81 |
+ M |
+ R7196H |
+ 515 |
+ I |
+ Hippocampus |
+
+
+ | 104 |
+ BXD81 |
+ F |
+ R7190H |
+ 458 |
+ I |
+ Hippocampus |
+
+
+ | 105 |
+ BXD83 |
+ M |
+ R7184H |
+ 441 |
+ I |
+ Hippocampus |
+
+
+ | 106 |
+ BXD84 |
+ M |
+ R7195H |
+ 474 |
+ I |
+ Hippocampus |
+
+
+ | 107 |
+ BXD84 |
+ M |
+ R7296H |
+ 484 |
+ II |
+ Hippocampus |
+
+
+ | 108 |
+ BXD84 |
+ F |
+ R7192H |
+ 522 |
+ I |
+ Hippocampus |
+
+
+ | 109 |
+ BXD85 |
+ M |
+ R7272H |
+ 425 |
+ II |
+ Hippocampus |
+
+
+ | 110 |
+ BXD85 |
+ F |
+ R7193H |
+ 506 |
+ I |
+ Hippocampus |
+
+
+ | 111 |
+ BXD86 |
+ M |
+ R7191H |
+ 425 |
+ I |
+ Hippocampus |
+
+
+ | 112 |
+ BXD87 |
+ F |
+ R7194H |
+ 425 |
+ I |
+ Hippocampus |
+
+
+ | 113 |
+ BXD87 |
+ M |
+ R7303H |
+ 478 |
+ III |
+ Hippocampus |
+
+
+ | 114 |
+ BXD87 |
+ M |
+ R7186H |
+ 442 |
+ I |
+ Hippocampus |
+
+
+ | 115 |
+ BXD89 |
+ F |
+ R7295H |
+ 446 |
+ II |
+ Hippocampus |
+
+
+ | 116 |
+ BXD90 |
+ M |
+ R7287H |
+ 434 |
+ II |
+ Hippocampus |
+
+
+ | 117 |
+ BXD90 |
+ M |
+ R7293H |
+ 558 |
+ II |
+ Hippocampus |
+
+
+ | 118 |
+ BXD95 |
+ F |
+ R7180H |
+ 467 |
+ I |
+ Hippocampus |
+
+
+ | 119 |
+ BXD95 |
+ M |
+ R7169H |
+ 467 |
+ I |
+ Hippocampus |
+
+
+ | 120 |
+ BXD98 |
+ M |
+ R7237H |
+ 605 |
+ I |
+ Hippocampus |
+
+
+ | 121 |
+ BXD98 |
+ F |
+ R7171H |
+ 639 |
+ I |
+ Hippocampus |
+
+
+ | 122 |
+ BXD98 |
+ F |
+ R7275H |
+ 488 |
+ II |
+ Hippocampus |
+
+
+ | 123 |
+ BXD99 |
+ M |
+ R7189H |
+ 524 |
+ I |
+ Hippocampus |
+
+
+ | 124 |
+ BXD99 |
+ F |
+ R7172H |
+ 471 |
+ I |
+ Hippocampus |
+
+
+ | 125 |
+ BXD100 |
+ F |
+ R7282H |
+ 463 |
+ II |
+ Hippocampus |
+
+
+ | 126 |
+ BXD100 |
+ M |
+ R7283H |
+ 507 |
+ II |
+ Hippocampus |
+
+
+ | 127 |
+ BXD100 |
+ M |
+ R7274H |
+ 577 |
+ II |
+ Hippocampus |
+
+
+ | 128 |
+ BXD100 |
+ F |
+ R7226H |
+ 464 |
+ I |
+ Hippocampus |
+
+
+ | 129 |
+ BXD101 |
+ F |
+ R7284H |
+ 490 |
+ II |
+ Hippocampus |
+
+
+ | 130 |
+ BXD101 |
+ M |
+ R7285H |
+ 408 |
+ II |
+ Hippocampus |
+
+
+ | 131 |
+ C57BL/6J |
+ M |
+ R7264H |
+ 489 |
+ I |
+ Hippocampus |
+
+
+ | 132 |
+ C57BL/6J |
+ M |
+ R7289H |
+ 756 |
+ II |
+ Hippocampus |
+
+
+ | 133 |
+ D2B6F1 |
+ M |
+ R7265H |
+ 492 |
+ I |
+ Hippocampus |
+
+
+ | 134 |
+ D2B6F1 |
+ F |
+ R7304H |
+ 495 |
+ III |
+ Hippocampus |
+
+
+ | 135 |
+ DBA/2J |
+ F |
+ R7185H |
+ 433 |
+ I |
+ Hippocampus |
+
+
+ | 136 |
+ DBA/2J |
+ M |
+ R7269H |
+ 367 |
+ I |
+ Hippocampus |
+
+
+ | 137 |
+ DBA/2J |
+ F |
+ R7301H |
+ 566 |
+ III |
+ Hippocampus |
+
+
+
diff --git a/general/datasets/Uthsc_bxd_h_0912/experiment-design.rtf b/general/datasets/Uthsc_bxd_h_0912/experiment-design.rtf
new file mode 100644
index 0000000..d6b2d5b
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_h_0912/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Extraction
+
+RNA was extracted using the RNeasy mini kit (Qiagen, Valencia, CA, USA) according to the manufactures’ procedure. 2100 BioAnalyzer (Agilent Technologies) was used to evaluate RNA integrity and quality. Samples with RNA Integrity Numbers (RIN values) > 8.0 were run on Affy MoGene1.0 ST at the UTHSC
diff --git a/general/datasets/Uthsc_bxd_h_0912/processing.rtf b/general/datasets/Uthsc_bxd_h_0912/processing.rtf
new file mode 100644
index 0000000..e951515
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_h_0912/processing.rtf
@@ -0,0 +1,3 @@
+About data processing:
+
+Raw microarray data were normalized using the Robust Multichip Array (RMA) method. The expression data were then re-normalized using a modified Z score.
diff --git a/general/datasets/Uthsc_bxd_h_0912/specifics.rtf b/general/datasets/Uthsc_bxd_h_0912/specifics.rtf
new file mode 100644
index 0000000..0888a16
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_h_0912/specifics.rtf
@@ -0,0 +1 @@
+Exon Level Data
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_h_0912/tissue.rtf b/general/datasets/Uthsc_bxd_h_0912/tissue.rtf
new file mode 100644
index 0000000..3166717
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_h_0912/tissue.rtf
@@ -0,0 +1,3 @@
+Tissue Harvest
+
+The animals were sacrificed under saturated isoflurane. Hippocampus from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Uthsc_bxd_harev3_0912/cases.rtf b/general/datasets/Uthsc_bxd_harev3_0912/cases.rtf
new file mode 100644
index 0000000..2b37c95
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harev3_0912/cases.rtf
@@ -0,0 +1,1258 @@
+The study includes 137 mice (11~25 months old) from 73 strains (B6, D2, DBF1, and 70 BXD strains). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+The table of samples that are finally used for this study:
+
+
+
+
+
+
+
+
+
+
+
+
+ | Index |
+ Strain |
+ Sex |
+ RNA ID |
+ Age |
+ Phase |
+ Tissue |
+
+
+ | 1 |
+ BXD1 |
+ F |
+ R7281H |
+ 448 |
+ II |
+ Hippocampus |
+
+
+ | 2 |
+ BXD1 |
+ M |
+ R7276H |
+ 323 |
+ II |
+ Hippocampus |
+
+
+ | 3 |
+ BXD2 |
+ M |
+ R7261H |
+ 394 |
+ I |
+ Hippocampus |
+
+
+ | 4 |
+ BXD2 |
+ F |
+ R7256H |
+ 456 |
+ I |
+ Hippocampus |
+
+
+ | 5 |
+ BXD6 |
+ M |
+ R7223H |
+ 526 |
+ I |
+ Hippocampus |
+
+
+ | 6 |
+ BXD8 |
+ M |
+ R7203H |
+ 471 |
+ I |
+ Hippocampus |
+
+
+ | 7 |
+ BXD8 |
+ F |
+ R7200H |
+ 460 |
+ I |
+ Hippocampus |
+
+
+ | 8 |
+ BXD8 |
+ F |
+ R7198H |
+ 433 |
+ I |
+ Hippocampus |
+
+
+ | 9 |
+ BXD9 |
+ F |
+ R7294H |
+ 456 |
+ II |
+ Hippocampus |
+
+
+ | 10 |
+ BXD11 |
+ M |
+ R7300H |
+ 457 |
+ II |
+ Hippocampus |
+
+
+ | 11 |
+ BXD11 |
+ F |
+ R7227H |
+ 536 |
+ I |
+ Hippocampus |
+
+
+ | 12 |
+ BXD12 |
+ F |
+ R7183H |
+ 506 |
+ I |
+ Hippocampus |
+
+
+ | 13 |
+ BXD12 |
+ F |
+ R7233H |
+ 561 |
+ I |
+ Hippocampus |
+
+
+ | 14 |
+ BXD12 |
+ M |
+ R7234H |
+ 606 |
+ I |
+ Hippocampus |
+
+
+ | 15 |
+ BXD14 |
+ F |
+ R7238H |
+ 605 |
+ I |
+ Hippocampus |
+
+
+ | 16 |
+ BXD14 |
+ M |
+ R7235H |
+ 605 |
+ I |
+ Hippocampus |
+
+
+ | 17 |
+ BXD16 |
+ F |
+ R7236H |
+ 561 |
+ I |
+ Hippocampus |
+
+
+ | 18 |
+ BXD16 |
+ M |
+ R7239H |
+ 475 |
+ I |
+ Hippocampus |
+
+
+ | 19 |
+ BXD18 |
+ F |
+ R7229H |
+ 493 |
+ I |
+ Hippocampus |
+
+
+ | 20 |
+ BXD19 |
+ F |
+ R7267H |
+ 551 |
+ I |
+ Hippocampus |
+
+
+ | 21 |
+ BXD19 |
+ M |
+ R7268H |
+ 492 |
+ I |
+ Hippocampus |
+
+
+ | 22 |
+ BXD20 |
+ M |
+ R7232H |
+ 506 |
+ I |
+ Hippocampus |
+
+
+ | 23 |
+ BXD20 |
+ M |
+ R7263H |
+ 489 |
+ I |
+ Hippocampus |
+
+
+ | 24 |
+ BXD21 |
+ F |
+ R7230H |
+ 537 |
+ I |
+ Hippocampus |
+
+
+ | 25 |
+ BXD22 |
+ F |
+ R7260H |
+ 502 |
+ I |
+ Hippocampus |
+
+
+ | 26 |
+ BXD22 |
+ M |
+ R7262H |
+ 596 |
+ I |
+ Hippocampus |
+
+
+ | 27 |
+ BXD23 |
+ F |
+ R7258H |
+ 502 |
+ I |
+ Hippocampus |
+
+
+ | 28 |
+ BXD23 |
+ M |
+ R7257H |
+ 462 |
+ I |
+ Hippocampus |
+
+
+ | 29 |
+ BXD24 |
+ M |
+ R7231H |
+ 470 |
+ I |
+ Hippocampus |
+
+
+ | 30 |
+ BXD24 |
+ F |
+ R7228H |
+ 415 |
+ I |
+ Hippocampus |
+
+
+ | 31 |
+ BXD24 |
+ F |
+ R7255H |
+ 456 |
+ I |
+ Hippocampus |
+
+
+ | 32 |
+ BXD25 |
+ F |
+ R7252H |
+ 454 |
+ I |
+ Hippocampus |
+
+
+ | 33 |
+ BXD27 |
+ F |
+ R7286H |
+ 472 |
+ II |
+ Hippocampus |
+
+
+ | 34 |
+ BXD27 |
+ F |
+ R7170H |
+ 472 |
+ I |
+ Hippocampus |
+
+
+ | 35 |
+ BXD28 |
+ M |
+ R7254H |
+ 493 |
+ I |
+ Hippocampus |
+
+
+ | 36 |
+ BXD28 |
+ F |
+ R7251H |
+ 543 |
+ I |
+ Hippocampus |
+
+
+ | 37 |
+ BXD29 |
+ F |
+ R7259H |
+ 483 |
+ I |
+ Hippocampus |
+
+
+ | 38 |
+ BXD33 |
+ M |
+ R7253H |
+ 464 |
+ I |
+ Hippocampus |
+
+
+ | 39 |
+ BXD33 |
+ F |
+ R7174H |
+ 471 |
+ I |
+ Hippocampus |
+
+
+ | 40 |
+ BXD33 |
+ F |
+ R7244H |
+ 448 |
+ I |
+ Hippocampus |
+
+
+ | 41 |
+ BXD33 |
+ M |
+ R7270H |
+ 662 |
+ I |
+ Hippocampus |
+
+
+ | 42 |
+ BXD38 |
+ F |
+ R7242H |
+ 464 |
+ I |
+ Hippocampus |
+
+
+ | 43 |
+ BXD38 |
+ M |
+ R7247H |
+ 446 |
+ I |
+ Hippocampus |
+
+
+ | 44 |
+ BXD39 |
+ M |
+ R7250H |
+ 536 |
+ I |
+ Hippocampus |
+
+
+ | 45 |
+ BXD39 |
+ F |
+ R7173H |
+ 500 |
+ I |
+ Hippocampus |
+
+
+ | 46 |
+ BXD39 |
+ M |
+ R7175H |
+ 500 |
+ I |
+ Hippocampus |
+
+
+ | 47 |
+ BXD40 |
+ F |
+ R7288H |
+ 451 |
+ II |
+ Hippocampus |
+
+
+ | 48 |
+ BXD40 |
+ M |
+ R7210H |
+ 470 |
+ I |
+ Hippocampus |
+
+
+ | 49 |
+ BXD40 |
+ M |
+ R7197H |
+ 614 |
+ I |
+ Hippocampus |
+
+
+ | 50 |
+ BXD42 |
+ F |
+ R7280H |
+ 518 |
+ II |
+ Hippocampus |
+
+
+ | 51 |
+ BXD42 |
+ M |
+ R7246H |
+ 446 |
+ I |
+ Hippocampus |
+
+
+ | 52 |
+ BXD42 |
+ F |
+ R7266H |
+ 486 |
+ I |
+ Hippocampus |
+
+
+ | 53 |
+ BXD43 |
+ F |
+ R7249H |
+ 454 |
+ I |
+ Hippocampus |
+
+
+ | 54 |
+ BXD43 |
+ M |
+ R7248H |
+ 462 |
+ I |
+ Hippocampus |
+
+
+ | 55 |
+ BXD44 |
+ M |
+ R7241H |
+ 415 |
+ I |
+ Hippocampus |
+
+
+ | 56 |
+ BXD44 |
+ M |
+ R7279H |
+ 419 |
+ II |
+ Hippocampus |
+
+
+ | 57 |
+ BXD44 |
+ F |
+ R7243H |
+ 438 |
+ I |
+ Hippocampus |
+
+
+ | 58 |
+ BXD45 |
+ F |
+ R7176H |
+ 451 |
+ I |
+ Hippocampus |
+
+
+ | 59 |
+ BXD48 |
+ F |
+ R7245H |
+ 499 |
+ I |
+ Hippocampus |
+
+
+ | 60 |
+ BXD48 |
+ M |
+ R7220H |
+ 526 |
+ I |
+ Hippocampus |
+
+
+ | 61 |
+ BXD48a |
+ F |
+ R7299H |
+ 479 |
+ II |
+ Hippocampus |
+
+
+ | 62 |
+ BXD48a |
+ M |
+ R7297H |
+ 479 |
+ II |
+ Hippocampus |
+
+
+ | 63 |
+ BXD50 |
+ F |
+ R7224H |
+ 530 |
+ I |
+ Hippocampus |
+
+
+ | 64 |
+ BXD50 |
+ M |
+ R7221H |
+ 530 |
+ I |
+ Hippocampus |
+
+
+ | 65 |
+ BXD51 |
+ F |
+ R7177H |
+ 487 |
+ I |
+ Hippocampus |
+
+
+ | 66 |
+ BXD51 |
+ M |
+ R7290H |
+ 407 |
+ II |
+ Hippocampus |
+
+
+ | 67 |
+ BXD55 |
+ M |
+ R7222H |
+ 528 |
+ I |
+ Hippocampus |
+
+
+ | 68 |
+ BXD55 |
+ F |
+ R7225H |
+ 587 |
+ I |
+ Hippocampus |
+
+
+ | 69 |
+ BXD56 |
+ M |
+ R7178H |
+ 501 |
+ I |
+ Hippocampus |
+
+
+ | 70 |
+ BXD62 |
+ M |
+ R7291H |
+ 439 |
+ II |
+ Hippocampus |
+
+
+ | 71 |
+ BXD63 |
+ M |
+ R7218H |
+ 438 |
+ I |
+ Hippocampus |
+
+
+ | 72 |
+ BXD63 |
+ F |
+ R7215H |
+ 475 |
+ I |
+ Hippocampus |
+
+
+ | 73 |
+ BXD64 |
+ M |
+ R7219H |
+ 528 |
+ I |
+ Hippocampus |
+
+
+ | 74 |
+ BXD64 |
+ F |
+ R7216H |
+ 587 |
+ I |
+ Hippocampus |
+
+
+ | 75 |
+ BXD65 |
+ F |
+ R7217H |
+ 425 |
+ I |
+ Hippocampus |
+
+
+ | 76 |
+ BXD65a |
+ F |
+ R7273H |
+ 389 |
+ II |
+ Hippocampus |
+
+
+ | 77 |
+ BXD65a |
+ M |
+ R7277H |
+ 715 |
+ II |
+ Hippocampus |
+
+
+ | 78 |
+ BXD65b |
+ M |
+ R7271H |
+ 483 |
+ II |
+ Hippocampus |
+
+
+ | 79 |
+ BXD66 |
+ M |
+ R7214H |
+ 463 |
+ I |
+ Hippocampus |
+
+
+ | 80 |
+ BXD66 |
+ F |
+ R7302H |
+ 446 |
+ III |
+ Hippocampus |
+
+
+ | 81 |
+ BXD67 |
+ F |
+ R7240H |
+ 499 |
+ I |
+ Hippocampus |
+
+
+ | 82 |
+ BXD67 |
+ M |
+ R7213H |
+ 425 |
+ I |
+ Hippocampus |
+
+
+ | 83 |
+ BXD67 |
+ F |
+ R7278H |
+ 415 |
+ II |
+ Hippocampus |
+
+
+ | 84 |
+ BXD68 |
+ M |
+ R7212H |
+ 421 |
+ I |
+ Hippocampus |
+
+
+ | 85 |
+ BXD68 |
+ F |
+ R7211H |
+ 415 |
+ I |
+ Hippocampus |
+
+
+ | 86 |
+ BXD69 |
+ F |
+ R7305H |
+ 504 |
+ III |
+ Hippocampus |
+
+
+ | 87 |
+ BXD70 |
+ F |
+ R7207H |
+ 458 |
+ I |
+ Hippocampus |
+
+
+ | 88 |
+ BXD70 |
+ M |
+ R7204H |
+ 460 |
+ I |
+ Hippocampus |
+
+
+ | 89 |
+ BXD71 |
+ M |
+ R7205H |
+ 471 |
+ I |
+ Hippocampus |
+
+
+ | 90 |
+ BXD71 |
+ F |
+ R7208H |
+ 474 |
+ I |
+ Hippocampus |
+
+
+ | 91 |
+ BXD73 |
+ F |
+ R7209H |
+ 470 |
+ I |
+ Hippocampus |
+
+
+ | 92 |
+ BXD73 |
+ M |
+ R7206H |
+ 464 |
+ I |
+ Hippocampus |
+
+
+ | 93 |
+ BXD73a |
+ F |
+ R7181H |
+ 443 |
+ I |
+ Hippocampus |
+
+
+ | 94 |
+ BXD73a |
+ M |
+ R7182H |
+ 614 |
+ I |
+ Hippocampus |
+
+
+ | 95 |
+ BXD76 |
+ M |
+ R7179H |
+ 579 |
+ I |
+ Hippocampus |
+
+
+ | 96 |
+ BXD76 |
+ F |
+ R7188H |
+ 408 |
+ I |
+ Hippocampus |
+
+
+ | 97 |
+ BXD76 |
+ M |
+ R7187H |
+ 564 |
+ I |
+ Hippocampus |
+
+
+ | 98 |
+ BXD77 |
+ M |
+ R7292H |
+ 347 |
+ II |
+ Hippocampus |
+
+
+ | 99 |
+ BXD77 |
+ F |
+ R7201H |
+ 454 |
+ I |
+ Hippocampus |
+
+
+ | 100 |
+ BXD79 |
+ M |
+ R7202H |
+ 485 |
+ I |
+ Hippocampus |
+
+
+ | 101 |
+ BXD79 |
+ F |
+ R7199H |
+ 515 |
+ I |
+ Hippocampus |
+
+
+ | 102 |
+ BXD79 |
+ M |
+ R7298H |
+ 704 |
+ II |
+ Hippocampus |
+
+
+ | 103 |
+ BXD81 |
+ M |
+ R7196H |
+ 515 |
+ I |
+ Hippocampus |
+
+
+ | 104 |
+ BXD81 |
+ F |
+ R7190H |
+ 458 |
+ I |
+ Hippocampus |
+
+
+ | 105 |
+ BXD83 |
+ M |
+ R7184H |
+ 441 |
+ I |
+ Hippocampus |
+
+
+ | 106 |
+ BXD84 |
+ M |
+ R7195H |
+ 474 |
+ I |
+ Hippocampus |
+
+
+ | 107 |
+ BXD84 |
+ M |
+ R7296H |
+ 484 |
+ II |
+ Hippocampus |
+
+
+ | 108 |
+ BXD84 |
+ F |
+ R7192H |
+ 522 |
+ I |
+ Hippocampus |
+
+
+ | 109 |
+ BXD85 |
+ M |
+ R7272H |
+ 425 |
+ II |
+ Hippocampus |
+
+
+ | 110 |
+ BXD85 |
+ F |
+ R7193H |
+ 506 |
+ I |
+ Hippocampus |
+
+
+ | 111 |
+ BXD86 |
+ M |
+ R7191H |
+ 425 |
+ I |
+ Hippocampus |
+
+
+ | 112 |
+ BXD87 |
+ F |
+ R7194H |
+ 425 |
+ I |
+ Hippocampus |
+
+
+ | 113 |
+ BXD87 |
+ M |
+ R7303H |
+ 478 |
+ III |
+ Hippocampus |
+
+
+ | 114 |
+ BXD87 |
+ M |
+ R7186H |
+ 442 |
+ I |
+ Hippocampus |
+
+
+ | 115 |
+ BXD89 |
+ F |
+ R7295H |
+ 446 |
+ II |
+ Hippocampus |
+
+
+ | 116 |
+ BXD90 |
+ M |
+ R7287H |
+ 434 |
+ II |
+ Hippocampus |
+
+
+ | 117 |
+ BXD90 |
+ M |
+ R7293H |
+ 558 |
+ II |
+ Hippocampus |
+
+
+ | 118 |
+ BXD95 |
+ F |
+ R7180H |
+ 467 |
+ I |
+ Hippocampus |
+
+
+ | 119 |
+ BXD95 |
+ M |
+ R7169H |
+ 467 |
+ I |
+ Hippocampus |
+
+
+ | 120 |
+ BXD98 |
+ M |
+ R7237H |
+ 605 |
+ I |
+ Hippocampus |
+
+
+ | 121 |
+ BXD98 |
+ F |
+ R7171H |
+ 639 |
+ I |
+ Hippocampus |
+
+
+ | 122 |
+ BXD98 |
+ F |
+ R7275H |
+ 488 |
+ II |
+ Hippocampus |
+
+
+ | 123 |
+ BXD99 |
+ M |
+ R7189H |
+ 524 |
+ I |
+ Hippocampus |
+
+
+ | 124 |
+ BXD99 |
+ F |
+ R7172H |
+ 471 |
+ I |
+ Hippocampus |
+
+
+ | 125 |
+ BXD100 |
+ F |
+ R7282H |
+ 463 |
+ II |
+ Hippocampus |
+
+
+ | 126 |
+ BXD100 |
+ M |
+ R7283H |
+ 507 |
+ II |
+ Hippocampus |
+
+
+ | 127 |
+ BXD100 |
+ M |
+ R7274H |
+ 577 |
+ II |
+ Hippocampus |
+
+
+ | 128 |
+ BXD100 |
+ F |
+ R7226H |
+ 464 |
+ I |
+ Hippocampus |
+
+
+ | 129 |
+ BXD101 |
+ F |
+ R7284H |
+ 490 |
+ II |
+ Hippocampus |
+
+
+ | 130 |
+ BXD101 |
+ M |
+ R7285H |
+ 408 |
+ II |
+ Hippocampus |
+
+
+ | 131 |
+ C57BL/6J |
+ M |
+ R7264H |
+ 489 |
+ I |
+ Hippocampus |
+
+
+ | 132 |
+ C57BL/6J |
+ M |
+ R7289H |
+ 756 |
+ II |
+ Hippocampus |
+
+
+ | 133 |
+ D2B6F1 |
+ M |
+ R7265H |
+ 492 |
+ I |
+ Hippocampus |
+
+
+ | 134 |
+ D2B6F1 |
+ F |
+ R7304H |
+ 495 |
+ III |
+ Hippocampus |
+
+
+ | 135 |
+ DBA/2J |
+ F |
+ R7185H |
+ 433 |
+ I |
+ Hippocampus |
+
+
+ | 136 |
+ DBA/2J |
+ M |
+ R7269H |
+ 367 |
+ I |
+ Hippocampus |
+
+
+ | 137 |
+ DBA/2J |
+ F |
+ R7301H |
+ 566 |
+ III |
+ Hippocampus |
+
+
+
diff --git a/general/datasets/Uthsc_bxd_harev3_0912/experiment-design.rtf b/general/datasets/Uthsc_bxd_harev3_0912/experiment-design.rtf
new file mode 100644
index 0000000..d6b2d5b
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harev3_0912/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Extraction
+
+RNA was extracted using the RNeasy mini kit (Qiagen, Valencia, CA, USA) according to the manufactures’ procedure. 2100 BioAnalyzer (Agilent Technologies) was used to evaluate RNA integrity and quality. Samples with RNA Integrity Numbers (RIN values) > 8.0 were run on Affy MoGene1.0 ST at the UTHSC
diff --git a/general/datasets/Uthsc_bxd_harev3_0912/processing.rtf b/general/datasets/Uthsc_bxd_harev3_0912/processing.rtf
new file mode 100644
index 0000000..e951515
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harev3_0912/processing.rtf
@@ -0,0 +1,3 @@
+About data processing:
+
+Raw microarray data were normalized using the Robust Multichip Array (RMA) method. The expression data were then re-normalized using a modified Z score.
diff --git a/general/datasets/Uthsc_bxd_harev3_0912/tissue.rtf b/general/datasets/Uthsc_bxd_harev3_0912/tissue.rtf
new file mode 100644
index 0000000..3166717
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harev3_0912/tissue.rtf
@@ -0,0 +1,3 @@
+Tissue Harvest
+
+The animals were sacrificed under saturated isoflurane. Hippocampus from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Uthsc_bxd_harv_liv_0118/cases.rtf b/general/datasets/Uthsc_bxd_harv_liv_0118/cases.rtf
new file mode 100644
index 0000000..18fdd1d
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harv_liv_0118/cases.rtf
@@ -0,0 +1,1371 @@
+
+
+
+
+
+
+
+
+
+
+
+ | CaseID |
+ Strain |
+ Diet |
+ Sex |
+ Age |
+ EarTag Current |
+ GN-SampleID |
+
+
+ | 062013.09 |
+ C57BL/6J |
+ HF |
+ F |
+ 544 |
+ 514 |
+ H0514 |
+
+
+ | 091914.09 |
+ C57BL/6J |
+ CD |
+ F |
+ 537 |
+ 1103 |
+ H1103 |
+
+
+ | 012615.26 |
+ C57BL/6J |
+ CD |
+ M |
+ 361 |
+ 1590 |
+ H1590 |
+
+
+ | 102414.06 |
+ C57BL/6J |
+ HF |
+ F |
+ 182 |
+ 1681 |
+ H1681 |
+
+
+ | 062013.12 |
+ D2B6F1 |
+ CD |
+ F |
+ 545 |
+ 646 |
+ H0646 |
+
+
+ | 062013.13 |
+ D2B6F1 |
+ HF |
+ F |
+ 540 |
+ 642 |
+ H0642 |
+
+
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+ | 101713.11 |
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+ | 012615.12 |
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+
+ | 042015.07 |
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+ | 042015.10 |
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+ | 121515.12 |
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+
+ | 121515.15 |
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+
+ | 012615.11 |
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+
+ | 042915.13 |
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+ | 121515.18 |
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+
+ | 042015.24 |
+ BXD48 |
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+ | 042015.27 |
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+
+ | 062013.06 |
+ BXD48a |
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+ H0699 |
+
+
+ | 051112.05 |
+ BXD48a |
+ CD |
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+
+
+ | 051112.04 |
+ BXD48a |
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+
+
+ | 010614.07 |
+ BXD53 |
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+
+
+ | 062013.16 |
+ BXD53 |
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+
+ | 021213.14 |
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+
+
+ | 050912.08 |
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+
+ | 121515.23 |
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+
+ | 121515.25 |
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+
+ | 111414.02 |
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+
+ | 111414.03 |
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+
+ | 111414.04 |
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+
+ | 082214.10 |
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+
+ | 042915.19 |
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+
+ | 121214.20 |
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+
+ | 042015.05 |
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+
+ | 102616.17 |
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+
+
+ | 083016.03 |
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+
+
+ | 121214.24 |
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+
+
+ | 121214.26 |
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+ HF |
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+ 1416 |
+ H1416 |
+
+
+ | 090412.08 |
+ BXD63 |
+ CD |
+ F |
+ 218 |
+ 818 |
+ H0818 |
+
+
+ | 111414.09 |
+ BXD63 |
+ HF |
+ F |
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+ 1715 |
+ H1715 |
+
+
+ | 121615.09 |
+ BXD65 |
+ CD |
+ F |
+ 541 |
+ 1787 |
+ H1787 |
+
+
+ | 121615.06 |
+ BXD65 |
+ HF |
+ F |
+ 541 |
+ 1784 |
+ H1784 |
+
+
+ | 051012.01 |
+ BXD65 |
+ HF |
+ F |
+ 230 |
+ 458 |
+ H0458 |
+
+
+ | 042015.13 |
+ BXD65 |
+ CD |
+ F |
+ 222 |
+ 2098 |
+ H2098 |
+
+
+ | 121615.12 |
+ BXD65b |
+ CD |
+ F |
+ 527 |
+ 1793 |
+ H1793 |
+
+
+ | 121615.11 |
+ BXD65b |
+ HF |
+ F |
+ 527 |
+ 1790 |
+ H1790 |
+
+
+ | 111414.05 |
+ BXD65b |
+ CD |
+ F |
+ 187 |
+ 1766 |
+ H1766 |
+
+
+ | 102414.18 |
+ BXD65b |
+ HF |
+ F |
+ 174 |
+ 1713 |
+ H1713 |
+
+
+ | 121214.04 |
+ BXD66 |
+ HF |
+ F |
+ 367 |
+ 1560 |
+ H1560 |
+
+
+ | 121214.19 |
+ BXD66 |
+ CD |
+ F |
+ 354 |
+ 1558 |
+ H1558 |
+
+
+ | 042415.08 |
+ BXD66 |
+ CD |
+ F |
+ 184 |
+ 2128 |
+ H2128 |
+
+
+ | 042415.05 |
+ BXD66 |
+ HF |
+ F |
+ 184 |
+ 2124 |
+ H2124 |
+
+
+ | 082214.02 |
+ BXD68 |
+ CD |
+ F |
+ 545 |
+ 1080 |
+ H1080 |
+
+
+ | 082214.08 |
+ BXD68 |
+ HF |
+ F |
+ 545 |
+ 1290 |
+ H1290 |
+
+
+ | 101613.05 |
+ BXD68 |
+ CD |
+ F |
+ 201 |
+ 1068 |
+ H1068 |
+
+
+ | 101613.08 |
+ BXD68 |
+ HF |
+ F |
+ 201 |
+ 1071 |
+ H1071 |
+
+
+ | 061913.13 |
+ BXD69 |
+ CD |
+ F |
+ 558 |
+ 591 |
+ H0591 |
+
+
+ | 121214.23 |
+ BXD69 |
+ HF |
+ F |
+ 528 |
+ 1328 |
+ H1328 |
+
+
+ | 101613.09 |
+ BXD69 |
+ HF |
+ F |
+ 210 |
+ 1087 |
+ H1087 |
+
+
+ | 042415.23 |
+ BXD69 |
+ CD |
+ F |
+ 157 |
+ 2142 |
+ H2142 |
+
+
+ | 121615.14 |
+ BXD70 |
+ HF |
+ F |
+ 578 |
+ 1728 |
+ H1728 |
+
+
+ | 121214.16 |
+ BXD70 |
+ CD |
+ F |
+ 357 |
+ 1512 |
+ H1512 |
+
+
+ | 050115.06 |
+ BXD70 |
+ CD |
+ F |
+ 261 |
+ 1855 |
+ H1855 |
+
+
+ | 051012.08 |
+ BXD70 |
+ HF |
+ F |
+ 239 |
+ 188 |
+ H0188 |
+
+
+ | 121615.17 |
+ BXD73 |
+ CD |
+ F |
+ 539 |
+ 1906 |
+ H1906 |
+
+
+ | 121214.10 |
+ BXD73 |
+ CD |
+ F |
+ 361 |
+ 1451 |
+ H1451 |
+
+
+ | 121214.11 |
+ BXD73 |
+ HF |
+ F |
+ 361 |
+ 1447 |
+ H1447 |
+
+
+ | 042015.18 |
+ BXD73 |
+ HF |
+ F |
+ 206 |
+ 2071 |
+ H2071 |
+
+
+ | 050115.15 |
+ BXD73b |
+ CD |
+ F |
+ 497 |
+ 1466 |
+ H1466 |
+
+
+ | 050115.12 |
+ BXD73b |
+ HF |
+ F |
+ 474 |
+ 1545 |
+ H1545 |
+
+
+ | 051112.12 |
+ BXD73b |
+ CD |
+ F |
+ 238 |
+ 184 |
+ H0184 |
+
+
+ | 051112.14 |
+ BXD73b |
+ HF |
+ F |
+ 237 |
+ 183 |
+ H0183 |
+
+
+ | 121615.19 |
+ BXD77 |
+ HF |
+ F |
+ 511 |
+ 1866 |
+ H1866 |
+
+
+ | 050115.17 |
+ BXD77 |
+ CD |
+ F |
+ 460 |
+ 1398 |
+ H1398 |
+
+
+ | 061913.18 |
+ BXD79 |
+ HF |
+ F |
+ 571 |
+ 583 |
+ H0583 |
+
+
+ | 050115.19 |
+ BXD79 |
+ CD |
+ F |
+ 468 |
+ 1555 |
+ H1555 |
+
+
+ | 090412.10 |
+ BXD79 |
+ CD |
+ F |
+ 217 |
+ 825 |
+ H0825 |
+
+
+ | 061913.19 |
+ BXD87 |
+ CD |
+ F |
+ 581 |
+ 296 |
+ H0296 |
+
+
+ | 121615.21 |
+ BXD87 |
+ HF |
+ F |
+ 512 |
+ 1945 |
+ H1945 |
+
+
+ | 051012.14 |
+ BXD87 |
+ HF |
+ F |
+ 241 |
+ 243 |
+ H0243 |
+
+
+ | 090612.10 |
+ BXD87 |
+ CD |
+ F |
+ 200 |
+ 550 |
+ H0550 |
+
+
+ | 101014.04 |
+ BXD89 |
+ HF |
+ F |
+ 539 |
+ 1321 |
+ H1321 |
+
+
+ | 051112.01 |
+ BXD89 |
+ HF |
+ F |
+ 243 |
+ 176 |
+ H0176 |
+
+
+ | 090612.14 |
+ BXD89 |
+ CD |
+ F |
+ 193 |
+ 555 |
+ H0555 |
+
+
+ | 062013.03 |
+ BXD90 |
+ HF |
+ F |
+ 570 |
+ 736 |
+ H0736 |
+
+
+ | 062013.02 |
+ BXD90 |
+ CD |
+ F |
+ 549 |
+ 756 |
+ H0756 |
+
+
+ | 101613.19 |
+ BXD90 |
+ HF |
+ F |
+ 218 |
+ 1093 |
+ H1093 |
+
+
+ | 102414.03 |
+ BXD90 |
+ CD |
+ F |
+ 188 |
+ 1702 |
+ H1702 |
+
+
+ | 062013.17 |
+ BXD91 |
+ CD |
+ F |
+ 562 |
+ 883 |
+ H0883 |
+
+
+ | 062013.19 |
+ BXD91 |
+ HF |
+ F |
+ 562 |
+ 881 |
+ H0881 |
+
+
+ | 102414.20 |
+ BXD95 |
+ HF |
+ F |
+ 550 |
+ 1273 |
+ H1273 |
+
+
+ | 101014.10 |
+ BXD95 |
+ CD |
+ F |
+ 536 |
+ 1742 |
+ H1742 |
+
+
+ | 101613.21 |
+ BXD95 |
+ HF |
+ F |
+ 213 |
+ 1275 |
+ H1275 |
+
+
+ | 012615.17 |
+ BXD98 |
+ CD |
+ F |
+ 384 |
+ 1769 |
+ H1769 |
+
+
+ | 012615.16 |
+ BXD98 |
+ CD |
+ F |
+ 384 |
+ 1524 |
+ H1524 |
+
+
+ | 111414.14 |
+ BXD99 |
+ CD |
+ F |
+ 535 |
+ 1354 |
+ H1354 |
+
+
+ | 050914.05 |
+ BXD99 |
+ HF |
+ F |
+ 182 |
+ 1355 |
+ H1355 |
+
+
+ | 111314.15 |
+ BXD100 |
+ CD |
+ F |
+ 567 |
+ 1190 |
+ H1190 |
+
+
+ | 050914.04 |
+ BXD100 |
+ HF |
+ F |
+ 537 |
+ 1187 |
+ H1187 |
+
+
+ | 051112.07 |
+ BXD100 |
+ CD |
+ F |
+ 223 |
+ 247 |
+ H0247 |
+
+
+ | 051112.08 |
+ BXD100 |
+ CD |
+ F |
+ 223 |
+ 248 |
+ H0248 |
+
+
+ | 042415.12 |
+ BXD100 |
+ HF |
+ F |
+ 176 |
+ 2085 |
+ H2085 |
+
+
+ | 102616.20 |
+ BXD101 |
+ CD |
+ F |
+ 756 |
+ 2114 |
+ H2114 |
+
+
+ | 042715.19 |
+ BXD101 |
+ HF |
+ F |
+ 493 |
+ 1422 |
+ H1422 |
+
+
+ | 111414.20 |
+ BXD101 |
+ CD |
+ F |
+ 349 |
+ 1425 |
+ H1425 |
+
+
+ | 051112.09 |
+ BXD101 |
+ CD |
+ F |
+ 223 |
+ 468 |
+ H0468 |
+
+
+ | 042915.01 |
+ BXD102 |
+ CD |
+ F |
+ 501 |
+ 1499 |
+ H1499 |
+
+
+ | 121214.07 |
+ BXD102 |
+ HF |
+ F |
+ 366 |
+ 1498 |
+ H1498 |
+
+
+ | 053014.01 |
+ BXD102 |
+ CD |
+ F |
+ 183 |
+ 1363 |
+ H1363 |
+
+
+ | 052814.04 |
+ BXD102 |
+ HF |
+ F |
+ 183 |
+ 1361 |
+ H1361 |
+
+
+
diff --git a/general/datasets/Uthsc_bxd_harv_liv_0118/processing.rtf b/general/datasets/Uthsc_bxd_harv_liv_0118/processing.rtf
new file mode 100644
index 0000000..4504c49
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harv_liv_0118/processing.rtf
@@ -0,0 +1,26883 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | 150 UTHSC Aging Liver RNA Selected for Novogene Submission |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+
+
+ | All Samples approximately 110ng/ul with a total of approximately 3ug RNA |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
+ |
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+ | File last updated by A.Centeno 1-3-18 |
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+ | Pearson Product-Moment Correlation |
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+ | No Selector |
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+ |
+ |
+ |
+
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+ | Tissue |
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+ 0.972466667 |
+ 0.973773333 |
+ 0.97452 |
+ 0.978466667 |
+ 0.975233333 |
+ 0.977166667 |
+ 0.930506667 |
+ 0.975353333 |
+ 0.9727 |
+ 0.978113333 |
+ 0.9772 |
+ 0.973826667 |
+ 0.94446 |
+ 0.967473333 |
+ 0.946173333 |
+ |
+ 0.90262 |
+ 0.970757511 |
+
+
+
diff --git a/general/datasets/Uthsc_bxd_harv_liv_0118/specifics.rtf b/general/datasets/Uthsc_bxd_harv_liv_0118/specifics.rtf
new file mode 100644
index 0000000..e492142
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harv_liv_0118/specifics.rtf
@@ -0,0 +1 @@
+RNA-Seq Log2
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_harv_liv_0118/summary.rtf b/general/datasets/Uthsc_bxd_harv_liv_0118/summary.rtf
new file mode 100644
index 0000000..153d98d
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harv_liv_0118/summary.rtf
@@ -0,0 +1 @@
+In working progress...
diff --git a/general/datasets/Uthsc_bxd_harv_liv_1019/cases.rtf b/general/datasets/Uthsc_bxd_harv_liv_1019/cases.rtf
new file mode 100644
index 0000000..18fdd1d
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harv_liv_1019/cases.rtf
@@ -0,0 +1,1371 @@
+
+
+
+
+
+
+
+
+
+
+
+ | CaseID |
+ Strain |
+ Diet |
+ Sex |
+ Age |
+ EarTag Current |
+ GN-SampleID |
+
+
+ | 062013.09 |
+ C57BL/6J |
+ HF |
+ F |
+ 544 |
+ 514 |
+ H0514 |
+
+
+ | 091914.09 |
+ C57BL/6J |
+ CD |
+ F |
+ 537 |
+ 1103 |
+ H1103 |
+
+
+ | 012615.26 |
+ C57BL/6J |
+ CD |
+ M |
+ 361 |
+ 1590 |
+ H1590 |
+
+
+ | 102414.06 |
+ C57BL/6J |
+ HF |
+ F |
+ 182 |
+ 1681 |
+ H1681 |
+
+
+ | 062013.12 |
+ D2B6F1 |
+ CD |
+ F |
+ 545 |
+ 646 |
+ H0646 |
+
+
+ | 062013.13 |
+ D2B6F1 |
+ HF |
+ F |
+ 540 |
+ 642 |
+ H0642 |
+
+
+ | 101713.20 |
+ D2B6F1 |
+ HF |
+ F |
+ 214 |
+ 1150 |
+ H1150 |
+
+
+ | 101713.18 |
+ D2B6F1 |
+ CD |
+ F |
+ 210 |
+ 1154 |
+ H1154 |
+
+
+ | 083016.07 |
+ DBA/2J |
+ CD |
+ F |
+ 764 |
+ 1818 |
+ H1818 |
+
+
+ | 091914.05 |
+ DBA/2J |
+ HF |
+ F |
+ 549 |
+ 1142 |
+ H1142 |
+
+
+ | 091914.07 |
+ DBA/2J |
+ HF |
+ M |
+ 544 |
+ 1140 |
+ H1140 |
+
+
+ | 101713.10 |
+ DBA/2J |
+ CD |
+ F |
+ 212 |
+ 1147 |
+ H1147 |
+
+
+ | 101713.11 |
+ DBA/2J |
+ HF |
+ F |
+ 212 |
+ 1144 |
+ H1144 |
+
+
+ | 121214.29 |
+ B6D2F1 |
+ CD |
+ F |
+ 640 |
+ 1227 |
+ H1227 |
+
+
+ | 012615.07 |
+ B6D2F1 |
+ CD |
+ F |
+ 552 |
+ 1569 |
+ H1569 |
+
+
+ | 102616.04 |
+ B6D2F1 |
+ HF |
+ F |
+ 547 |
+ 2288 |
+ H2288 |
+
+
+ | 102616.05 |
+ B6D2F1 |
+ HF |
+ F |
+ 547 |
+ 2290 |
+ H2290 |
+
+
+ | 101713.13 |
+ B6D2F1 |
+ CD |
+ F |
+ 216 |
+ 1223 |
+ H1223 |
+
+
+ | 101713.15 |
+ B6D2F1 |
+ HF |
+ F |
+ 216 |
+ 1302 |
+ H1302 |
+
+
+ | 082214.11 |
+ BXD9 |
+ CD |
+ F |
+ 548 |
+ 1006 |
+ H1006 |
+
+
+ | 082214.09 |
+ BXD9 |
+ HF |
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+ 1009 |
+ H1009 |
+
+
+ | 102616.12 |
+ BXD9 |
+ CD |
+ F |
+ 245 |
+ 2577 |
+ H2577 |
+
+
+ | 083016.08 |
+ BXD24 |
+ HF |
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+ 688 |
+ 2259 |
+ H2259 |
+
+
+ | 012615.19 |
+ BXD24 |
+ CD |
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+ 205 |
+ 1792 |
+ H1792 |
+
+
+ | 012615.08 |
+ BXD29 |
+ CD |
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+ 724 |
+ 1044 |
+ H1044 |
+
+
+ | 111314.10 |
+ BXD29 |
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+ 1037 |
+ H1037 |
+
+
+ | 061913.04 |
+ BXD29 |
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+ 669 |
+ H0669 |
+
+
+ | 111314.11 |
+ BXD29 |
+ CD |
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+ 1040 |
+ H1040 |
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+
+ | 061913.01 |
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+ 742 |
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+ | 121515.05 |
+ BXD29 |
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+ 2349 |
+ H2349 |
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+
+ | 101014.02 |
+ BXD32 |
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+ 1137 |
+ H1137 |
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+
+ | 083016.01 |
+ BXD32 |
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+
+ | 042015.22 |
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+ 2034 |
+ H2034 |
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+
+ | 042015.20 |
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+ HF |
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+ 2030 |
+ H2030 |
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+ | 101513.05 |
+ BXD34 |
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+ 765 |
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+
+ | 042015.07 |
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+ 1822 |
+ H1822 |
+
+
+ | 042015.10 |
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+ | 121515.12 |
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+ | 121515.15 |
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+
+ | 012615.11 |
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+ CD |
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+ 1762 |
+ H1762 |
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+
+ | 042915.13 |
+ BXD48 |
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+ 1377 |
+ H1377 |
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+
+ | 121515.18 |
+ BXD48 |
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+ 1835 |
+ H1835 |
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+
+ | 042015.24 |
+ BXD48 |
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+ 189 |
+ 2046 |
+ H2046 |
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+
+ | 042015.27 |
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+
+
+ | 062013.06 |
+ BXD48a |
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+ 699 |
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+
+ | 051112.05 |
+ BXD48a |
+ CD |
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+ 233 |
+ 209 |
+ H0209 |
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+
+ | 051112.04 |
+ BXD48a |
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+ 210 |
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+
+ | 010614.07 |
+ BXD53 |
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+ 833 |
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+
+ | 062013.16 |
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+ 848 |
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+
+ | 021213.14 |
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+ 171 |
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+
+ | 050912.08 |
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+ 1841 |
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+ | 121515.25 |
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+ 1843 |
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+ | 111414.02 |
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+ 1770 |
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+ | 111414.03 |
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+ 1722 |
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+
+ | 082214.10 |
+ BXD62 |
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+ 1315 |
+ H1315 |
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+
+ | 042915.19 |
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+ 1434 |
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+
+ | 121214.20 |
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+ 1436 |
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+ | 042015.05 |
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+ 1847 |
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+
+ | 102616.17 |
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+ | 083016.03 |
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+ 1872 |
+ H1872 |
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+ | 121214.24 |
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+ 1414 |
+ H1414 |
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+ | 121214.26 |
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+ | 090412.08 |
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+ | 111414.09 |
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+ | 121615.09 |
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+ | 121615.06 |
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+ | 051012.01 |
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+ 458 |
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+ | 042015.13 |
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+ | 121615.12 |
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+ | 121615.11 |
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+ | 042415.05 |
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+ | 082214.02 |
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+ H1080 |
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+ | 051012.08 |
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+ | 121615.17 |
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+ | 050115.17 |
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+ | 061913.19 |
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+ 296 |
+ H0296 |
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+ | 121615.21 |
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+ 1945 |
+ H1945 |
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+ | 051012.14 |
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+ 243 |
+ H0243 |
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+ | 090612.10 |
+ BXD87 |
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+ 550 |
+ H0550 |
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+
+ | 101014.04 |
+ BXD89 |
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+ | 051112.01 |
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+ 176 |
+ H0176 |
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+ | 090612.14 |
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+ 555 |
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+
+ | 062013.03 |
+ BXD90 |
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+ 736 |
+ H0736 |
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+
+ | 062013.02 |
+ BXD90 |
+ CD |
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+ 756 |
+ H0756 |
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+
+ | 101613.19 |
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+ 1093 |
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+
+ | 102414.03 |
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+ H1702 |
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+
+ | 062013.17 |
+ BXD91 |
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+ 562 |
+ 883 |
+ H0883 |
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+
+ | 062013.19 |
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+ | 102414.20 |
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+ | 101014.10 |
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+
+ | 101613.21 |
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+ | 012615.17 |
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+ | 012615.16 |
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+ | 111414.14 |
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+ | 050914.05 |
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+ | 111314.15 |
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+ | 051112.07 |
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+
+ | 102616.20 |
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+
+ | 042715.19 |
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+ 1422 |
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+ | 111414.20 |
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+ | 051112.09 |
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+ 468 |
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+
+ | 042915.01 |
+ BXD102 |
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+ 1499 |
+ H1499 |
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+
+ | 121214.07 |
+ BXD102 |
+ HF |
+ F |
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+ | 053014.01 |
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diff --git a/general/datasets/Uthsc_bxd_harv_liv_1019/processing.rtf b/general/datasets/Uthsc_bxd_harv_liv_1019/processing.rtf
new file mode 100644
index 0000000..4504c49
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harv_liv_1019/processing.rtf
@@ -0,0 +1,26883 @@
+
+
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+ | 150 UTHSC Aging Liver RNA Selected for Novogene Submission |
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+ | All Samples approximately 110ng/ul with a total of approximately 3ug RNA |
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+ | File last updated by A.Centeno 1-3-18 |
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+ | Pearson Product-Moment Correlation |
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+ HF |
+ |
+ |
+ |
+
+
+ | |
+ |
+ |
+ |
+ |
+ |
+ |
+ Strain |
+ B6D2F1 |
+ B6D2F1 |
+ B6D2F1 |
+ BXD100 |
+ BXD100 |
+ BXD100 |
+ BXD101 |
+ BXD101 |
+ BXD101 |
+ BXD102 |
+ BXD102 |
+ BXD24 |
+ BXD29 |
+ BXD29 |
+ BXD29 |
+ BXD32 |
+ BXD32 |
+ BXD34 |
+ BXD34 |
+ BXD39 |
+ BXD39 |
+ BXD40 |
+ BXD40 |
+ BXD44 |
+ BXD44 |
+ BXD45 |
+ BXD45 |
+ BXD48 |
+ BXD48 |
+ BXD48a |
+ BXD53 |
+ BXD60 |
+ BXD60 |
+ BXD61 |
+ BXD61 |
+ BXD62 |
+ BXD62 |
+ BXD63 |
+ BXD63 |
+ BXD63 |
+ BXD65 |
+ BXD65 |
+ BXD65b |
+ BXD65b |
+ BXD66 |
+ BXD66 |
+ BXD68 |
+ BXD68 |
+ BXD69 |
+ BXD69 |
+ BXD70 |
+ BXD70 |
+ BXD73 |
+ BXD73 |
+ BXD73b |
+ BXD73b |
+ BXD77 |
+ BXD79 |
+ BXD79 |
+ BXD87 |
+ BXD87 |
+ BXD89 |
+ BXD9 |
+ BXD9 |
+ BXD90 |
+ BXD90 |
+ BXD91 |
+ BXD95 |
+ BXD98 |
+ BXD98 |
+ BXD99 |
+ C57BL/6J |
+ C57BL/6J |
+ D2B6F1 |
+ D2B6F1 |
+ DBA/2J |
+ DBA/2J |
+ B6D2F1 |
+ B6D2F1 |
+ B6D2F1 |
+ BXD100 |
+ BXD100 |
+ BXD101 |
+ BXD102 |
+ BXD102 |
+ BXD24 |
+ BXD29 |
+ BXD29 |
+ BXD29 |
+ BXD32 |
+ BXD32 |
+ BXD34 |
+ BXD34 |
+ BXD39 |
+ BXD39 |
+ BXD40 |
+ BXD40 |
+ BXD44 |
+ BXD44 |
+ BXD44 |
+ BXD45 |
+ BXD48 |
+ BXD48 |
+ BXD48a |
+ BXD48a |
+ BXD53 |
+ BXD61 |
+ BXD61 |
+ BXD61 |
+ BXD62 |
+ BXD62 |
+ BXD63 |
+ BXD63 |
+ BXD63 |
+ BXD65 |
+ BXD65 |
+ BXD65b |
+ BXD65b |
+ BXD66 |
+ BXD66 |
+ BXD68 |
+ BXD68 |
+ BXD69 |
+ BXD69 |
+ BXD70 |
+ BXD70 |
+ BXD73 |
+ BXD73 |
+ BXD73b |
+ BXD73b |
+ BXD77 |
+ BXD79 |
+ BXD87 |
+ BXD87 |
+ BXD89 |
+ BXD89 |
+ BXD9 |
+ BXD90 |
+ BXD90 |
+ BXD91 |
+ BXD95 |
+ BXD95 |
+ BXD99 |
+ C57BL/6J |
+ C57BL/6J |
+ D2B6F1 |
+ D2B6F1 |
+ DBA/2J |
+ DBA/2J |
+ DBA/2J |
+ |
+ |
+ |
+
+
+ | Tissue |
+ Age |
+ Sex |
+ JI-ID |
+ CaseID |
+ Diet |
+ Strain |
+ EarTag |
+ H1223 |
+ H1569 |
+ H1227 |
+ H0247 |
+ H0248 |
+ H1190 |
+ H0468 |
+ H1425 |
+ H2114 |
+ H1363 |
+ H1499 |
+ H1792 |
+ H0742 |
+ H1040 |
+ H1044 |
+ H2034 |
+ H2494 |
+ H1054 |
+ H0765 |
+ H1322 |
+ H0673 |
+ H1691 |
+ H0680 |
+ H1822 |
+ H1505 |
+ H1762 |
+ H1826 |
+ H2054 |
+ H1835 |
+ H0209 |
+ H0848 |
+ H0235 |
+ H0171 |
+ H1770 |
+ H1841 |
+ H1847 |
+ H1436 |
+ H0818 |
+ H1414 |
+ H1872 |
+ H2098 |
+ H1787 |
+ H1766 |
+ H1793 |
+ H2128 |
+ H1558 |
+ H1068 |
+ H1080 |
+ H2142 |
+ H0591 |
+ H1855 |
+ H1512 |
+ H1451 |
+ H1906 |
+ H0184 |
+ H1466 |
+ H1398 |
+ H0825 |
+ H1555 |
+ H0550 |
+ H0296 |
+ H0555 |
+ H2577 |
+ H1006 |
+ H1702 |
+ H0756 |
+ H0883 |
+ H1742 |
+ H1769 |
+ H1524 |
+ H1354 |
+ H1590 |
+ H1103 |
+ H1154 |
+ H0646 |
+ H1147 |
+ H1818 |
+ H1302 |
+ H2288 |
+ H2290 |
+ H2085 |
+ H1187 |
+ H1422 |
+ H1361 |
+ H1498 |
+ H2259 |
+ H2349 |
+ H0669 |
+ H1037 |
+ H2030 |
+ H1137 |
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+ H1052 |
+ H1474 |
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+ H1488 |
+ H1593 |
+ H1825 |
+ H1501 |
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+ H1940 |
+ H2046 |
+ H1377 |
+ H0210 |
+ H0699 |
+ H0833 |
+ H1922 |
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+ H1843 |
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+ H1416 |
+ H2091 |
+ H0458 |
+ H1784 |
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+ H1790 |
+ H2124 |
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+ H1328 |
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+ H1728 |
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+ H1150 |
+ H0642 |
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+ H1140 |
+ H1142 |
+ |
+ min |
+ Average |
+
+
+ | Liver |
+ 216 |
+ F |
+ 307 |
+ 101713.13 |
+ CD |
+ B6D2F1 |
+ H1223 |
+ 1 |
+ 0.919 |
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+ |
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+
+ | Liver |
+ 552 |
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+ |
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+
+
+ | Liver |
+ 640 |
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+
+ | Liver |
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+ 0.97666 |
+ 0.97576 |
+ 0.97558 |
+ 0.946613333 |
+ 0.9703 |
+ 0.97476 |
+ 0.97526 |
+ 0.941373333 |
+ 0.97684 |
+ 0.975266667 |
+ 0.9745 |
+ 0.976933333 |
+ 0.974533333 |
+ 0.9729 |
+ 0.977533333 |
+ 0.975493333 |
+ 0.9497 |
+ 0.9698 |
+ 0.973826667 |
+ 0.975773333 |
+ 0.973746667 |
+ 0.97796 |
+ 0.962326667 |
+ 0.975153333 |
+ 0.9728 |
+ 0.977426667 |
+ 0.97666 |
+ 0.974006667 |
+ 0.969673333 |
+ 0.978873333 |
+ 0.975313333 |
+ 0.968826667 |
+ 0.959866667 |
+ 0.975613333 |
+ 0.90348 |
+ 0.972453333 |
+ 0.971593333 |
+ 0.973173333 |
+ 0.97614 |
+ 0.966853333 |
+ 0.945306667 |
+ 0.975946667 |
+ 0.94446 |
+ 0.97698 |
+ 0.975493333 |
+ 0.974506667 |
+ 0.975313333 |
+ 0.970326667 |
+ 0.9773 |
+ 0.979746667 |
+ 0.979673333 |
+ 0.97476 |
+ 0.975386667 |
+ 0.967573333 |
+ 0.9728 |
+ 0.977166667 |
+ 0.96468 |
+ 0.976573333 |
+ 0.97796 |
+ 0.970653333 |
+ 0.974686667 |
+ 0.972506667 |
+ 0.977466667 |
+ 0.977986667 |
+ 0.975166667 |
+ 0.974586667 |
+ 0.977833333 |
+ 0.976026667 |
+ 0.970193333 |
+ 0.976033333 |
+ 0.972746667 |
+ 0.9761 |
+ 0.976293333 |
+ 0.970913333 |
+ 0.973486667 |
+ 0.974113333 |
+ 0.974686667 |
+ 0.97198 |
+ 0.975646667 |
+ 0.97186 |
+ 0.97794 |
+ 0.946553333 |
+ 0.967726667 |
+ 0.97422 |
+ 0.966993333 |
+ 0.974926667 |
+ 0.973173333 |
+ 0.974446667 |
+ 0.97308 |
+ 0.975346667 |
+ 0.975633333 |
+ 0.97448 |
+ 0.969666667 |
+ 0.9739 |
+ 0.96608 |
+ 0.978153333 |
+ 0.97868 |
+ 0.976826667 |
+ 0.969986667 |
+ 0.97468 |
+ 0.97894 |
+ 0.97516 |
+ 0.97794 |
+ 0.976026667 |
+ 0.971426667 |
+ 0.972306667 |
+ 0.972466667 |
+ 0.973773333 |
+ 0.97452 |
+ 0.978466667 |
+ 0.975233333 |
+ 0.977166667 |
+ 0.930506667 |
+ 0.975353333 |
+ 0.9727 |
+ 0.978113333 |
+ 0.9772 |
+ 0.973826667 |
+ 0.94446 |
+ 0.967473333 |
+ 0.946173333 |
+ |
+ 0.90262 |
+ 0.970757511 |
+
+
+
diff --git a/general/datasets/Uthsc_bxd_harv_liv_1019/specifics.rtf b/general/datasets/Uthsc_bxd_harv_liv_1019/specifics.rtf
new file mode 100644
index 0000000..402ed9c
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harv_liv_1019/specifics.rtf
@@ -0,0 +1 @@
+TPM Log2
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_harv_liv_1019/summary.rtf b/general/datasets/Uthsc_bxd_harv_liv_1019/summary.rtf
new file mode 100644
index 0000000..153d98d
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harv_liv_1019/summary.rtf
@@ -0,0 +1 @@
+In working progress...
diff --git a/general/datasets/Uthsc_bxd_harv_liv_tpm_log2_1019/specifics.rtf b/general/datasets/Uthsc_bxd_harv_liv_tpm_log2_1019/specifics.rtf
new file mode 100644
index 0000000..a316cd4
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harv_liv_tpm_log2_1019/specifics.rtf
@@ -0,0 +1 @@
+UTHSC BXD Liver RNA-Seq Avg (Oct19) TPM Log2
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_harv_liv_tpm_log2_1019/summary.rtf b/general/datasets/Uthsc_bxd_harv_liv_tpm_log2_1019/summary.rtf
new file mode 100644
index 0000000..3ef9ac2
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_harv_liv_tpm_log2_1019/summary.rtf
@@ -0,0 +1 @@
+UTHSC BXD Liver RNA-Seq Avg (Oct19) TPM Log2
diff --git a/general/datasets/Uthsc_bxd_hip_mirnaseq0214/specifics.rtf b/general/datasets/Uthsc_bxd_hip_mirnaseq0214/specifics.rtf
new file mode 100644
index 0000000..280762b
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_hip_mirnaseq0214/specifics.rtf
@@ -0,0 +1 @@
+NA
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_hip_mirnaseq0214/summary.rtf b/general/datasets/Uthsc_bxd_hip_mirnaseq0214/summary.rtf
new file mode 100644
index 0000000..1a4d656
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_hip_mirnaseq0214/summary.rtf
@@ -0,0 +1 @@
+This group of datasets is confidential
diff --git a/general/datasets/Uthsc_bxd_hip_postd7ctrlbs_1121/specifics.rtf b/general/datasets/Uthsc_bxd_hip_postd7ctrlbs_1121/specifics.rtf
new file mode 100644
index 0000000..2a8ed1d
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_hip_postd7ctrlbs_1121/specifics.rtf
@@ -0,0 +1 @@
+BXD Hippocampus Postnatal Day 7 Control Both Sexes
diff --git a/general/datasets/Uthsc_bxd_hip_postd7ctrlbs_1121/summary.rtf b/general/datasets/Uthsc_bxd_hip_postd7ctrlbs_1121/summary.rtf
new file mode 100644
index 0000000..739e3b7
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_hip_postd7ctrlbs_1121/summary.rtf
@@ -0,0 +1 @@
+The Affymetrix Genechip Mouse Clariom S was used to examine gene expression (Affymetrix, California, United States). Two hundred nanograms of DNased total RNA was amplified, labeled, and fragmented using Ambion Whole Transcript (WT) Expression Kit according to manufacturer’s protocol (Thermo Fisher Scientific, Santa Clara, California United States). Briefly, samples are hybridized overnight according to manufacturer’s protocols; samples are then washed and stained on Affymetrix GeneChip Fluidics Station 450 (Affymetrix, California, United States). Samples were then scanned using the GeneChip Scanner 3000 (Applied Biosystems, California, United States). Data was normalized and analyzed for quality control in Affymetrix Expression Console Software using RMA-sketch normalization (Affymetrix, California, United States). After normalization and quality control, a total number of 22,203 probe sets were used for subsequent data analysis. A total of 128 samples were used—4 samples per treatment (control, ethanol), sex (male, female), and strain (B6, D2, BXD2, BXD48a, BXD60, BXD71, BXD73, BXD100).
diff --git a/general/datasets/Uthsc_bxd_hip_postd7etohbs_1121/specifics.rtf b/general/datasets/Uthsc_bxd_hip_postd7etohbs_1121/specifics.rtf
new file mode 100644
index 0000000..ebc4e0d
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_hip_postd7etohbs_1121/specifics.rtf
@@ -0,0 +1 @@
+BXD Hippocampus Postnatal Day 7 Ethanol Both Sexes
diff --git a/general/datasets/Uthsc_bxd_hip_postd7etohbs_1121/summary.rtf b/general/datasets/Uthsc_bxd_hip_postd7etohbs_1121/summary.rtf
new file mode 100644
index 0000000..739e3b7
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_hip_postd7etohbs_1121/summary.rtf
@@ -0,0 +1 @@
+The Affymetrix Genechip Mouse Clariom S was used to examine gene expression (Affymetrix, California, United States). Two hundred nanograms of DNased total RNA was amplified, labeled, and fragmented using Ambion Whole Transcript (WT) Expression Kit according to manufacturer’s protocol (Thermo Fisher Scientific, Santa Clara, California United States). Briefly, samples are hybridized overnight according to manufacturer’s protocols; samples are then washed and stained on Affymetrix GeneChip Fluidics Station 450 (Affymetrix, California, United States). Samples were then scanned using the GeneChip Scanner 3000 (Applied Biosystems, California, United States). Data was normalized and analyzed for quality control in Affymetrix Expression Console Software using RMA-sketch normalization (Affymetrix, California, United States). After normalization and quality control, a total number of 22,203 probe sets were used for subsequent data analysis. A total of 128 samples were used—4 samples per treatment (control, ethanol), sex (male, female), and strain (B6, D2, BXD2, BXD48a, BXD60, BXD71, BXD73, BXD100).
diff --git a/general/datasets/Uthsc_bxd_liv_0818/specifics.rtf b/general/datasets/Uthsc_bxd_liv_0818/specifics.rtf
new file mode 100644
index 0000000..342d36e
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_liv_0818/specifics.rtf
@@ -0,0 +1 @@
+2nd set
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_liv_0818/summary.rtf b/general/datasets/Uthsc_bxd_liv_0818/summary.rtf
new file mode 100644
index 0000000..790afd7
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_liv_0818/summary.rtf
@@ -0,0 +1 @@
+In working progress
diff --git a/general/datasets/Uthsc_bxd_liv_0917/specifics.rtf b/general/datasets/Uthsc_bxd_liv_0917/specifics.rtf
new file mode 100644
index 0000000..0b70afe
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_liv_0917/specifics.rtf
@@ -0,0 +1 @@
+Gene Level
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_liv_0917/summary.rtf b/general/datasets/Uthsc_bxd_liv_0917/summary.rtf
new file mode 100644
index 0000000..790afd7
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_liv_0917/summary.rtf
@@ -0,0 +1 @@
+In working progress
diff --git a/general/datasets/Uthsc_bxd_livcdnam_1119/experiment-design.rtf b/general/datasets/Uthsc_bxd_livcdnam_1119/experiment-design.rtf
new file mode 100644
index 0000000..5c63e07
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livcdnam_1119/experiment-design.rtf
@@ -0,0 +1 @@
+Aging
diff --git a/general/datasets/Uthsc_bxd_livcdnam_1119/platform.rtf b/general/datasets/Uthsc_bxd_livcdnam_1119/platform.rtf
new file mode 100644
index 0000000..01ea9ea
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livcdnam_1119/platform.rtf
@@ -0,0 +1 @@
+Pan-Mammalian DNAm Infinium array; this is a custom array
diff --git a/general/datasets/Uthsc_bxd_livcdnam_1119/processing.rtf b/general/datasets/Uthsc_bxd_livcdnam_1119/processing.rtf
new file mode 100644
index 0000000..5dc0f7f
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livcdnam_1119/processing.rtf
@@ -0,0 +1 @@
+Beta-values after normalization
diff --git a/general/datasets/Uthsc_bxd_livcdnam_1119/specifics.rtf b/general/datasets/Uthsc_bxd_livcdnam_1119/specifics.rtf
new file mode 100644
index 0000000..cf79575
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livcdnam_1119/specifics.rtf
@@ -0,0 +1 @@
+NIA-UTHSC BXD Liver CD DNAm (Nov20) Sesame
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_livcdnam_1119/summary.rtf b/general/datasets/Uthsc_bxd_livcdnam_1119/summary.rtf
new file mode 100644
index 0000000..0961144
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livcdnam_1119/summary.rtf
@@ -0,0 +1 @@
+DNA from liver tissue profiled on the Illumina Pan-Mammalian Infinium microarray. This array was designed and developed by Steve Horvath at UCLA. Array hybridization, initial data QC, and normalization done at UCLA.
diff --git a/general/datasets/Uthsc_bxd_livdnam_1119/experiment-design.rtf b/general/datasets/Uthsc_bxd_livdnam_1119/experiment-design.rtf
new file mode 100644
index 0000000..5c63e07
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livdnam_1119/experiment-design.rtf
@@ -0,0 +1 @@
+Aging
diff --git a/general/datasets/Uthsc_bxd_livdnam_1119/platform.rtf b/general/datasets/Uthsc_bxd_livdnam_1119/platform.rtf
new file mode 100644
index 0000000..01ea9ea
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livdnam_1119/platform.rtf
@@ -0,0 +1 @@
+Pan-Mammalian DNAm Infinium array; this is a custom array
diff --git a/general/datasets/Uthsc_bxd_livdnam_1119/processing.rtf b/general/datasets/Uthsc_bxd_livdnam_1119/processing.rtf
new file mode 100644
index 0000000..5dc0f7f
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livdnam_1119/processing.rtf
@@ -0,0 +1 @@
+Beta-values after normalization
diff --git a/general/datasets/Uthsc_bxd_livdnam_1119/specifics.rtf b/general/datasets/Uthsc_bxd_livdnam_1119/specifics.rtf
new file mode 100644
index 0000000..06c93b7
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livdnam_1119/specifics.rtf
@@ -0,0 +1 @@
+NIA-UTHSC BXD Liver CD-HFD DNAm (Nov20) Sesame
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_livdnam_1119/summary.rtf b/general/datasets/Uthsc_bxd_livdnam_1119/summary.rtf
new file mode 100644
index 0000000..0961144
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livdnam_1119/summary.rtf
@@ -0,0 +1 @@
+DNA from liver tissue profiled on the Illumina Pan-Mammalian Infinium microarray. This array was designed and developed by Steve Horvath at UCLA. Array hybridization, initial data QC, and normalization done at UCLA.
diff --git a/general/datasets/Uthsc_bxd_livhfdnam_1119/experiment-design.rtf b/general/datasets/Uthsc_bxd_livhfdnam_1119/experiment-design.rtf
new file mode 100644
index 0000000..5c63e07
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livhfdnam_1119/experiment-design.rtf
@@ -0,0 +1 @@
+Aging
diff --git a/general/datasets/Uthsc_bxd_livhfdnam_1119/platform.rtf b/general/datasets/Uthsc_bxd_livhfdnam_1119/platform.rtf
new file mode 100644
index 0000000..01ea9ea
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livhfdnam_1119/platform.rtf
@@ -0,0 +1 @@
+Pan-Mammalian DNAm Infinium array; this is a custom array
diff --git a/general/datasets/Uthsc_bxd_livhfdnam_1119/processing.rtf b/general/datasets/Uthsc_bxd_livhfdnam_1119/processing.rtf
new file mode 100644
index 0000000..5dc0f7f
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livhfdnam_1119/processing.rtf
@@ -0,0 +1 @@
+Beta-values after normalization
diff --git a/general/datasets/Uthsc_bxd_livhfdnam_1119/specifics.rtf b/general/datasets/Uthsc_bxd_livhfdnam_1119/specifics.rtf
new file mode 100644
index 0000000..b8b1955
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livhfdnam_1119/specifics.rtf
@@ -0,0 +1 @@
+NIA-UTHSC BXD Liver HFD DNAm (Nov20) Sesame
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_livhfdnam_1119/summary.rtf b/general/datasets/Uthsc_bxd_livhfdnam_1119/summary.rtf
new file mode 100644
index 0000000..0961144
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_livhfdnam_1119/summary.rtf
@@ -0,0 +1 @@
+DNA from liver tissue profiled on the Illumina Pan-Mammalian Infinium microarray. This array was designed and developed by Steve Horvath at UCLA. Array hybridization, initial data QC, and normalization done at UCLA.
diff --git a/general/datasets/Uthsc_bxd_mamgland_ca_0322/specifics.rtf b/general/datasets/Uthsc_bxd_mamgland_ca_0322/specifics.rtf
new file mode 100644
index 0000000..81e1218
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_mamgland_ca_0322/specifics.rtf
@@ -0,0 +1 @@
+UTHSC BXD Triple Negative Breast Cancer Model RNA-Seq (Mar22) Count All Samples
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_mamgland_ca_0322/summary.rtf b/general/datasets/Uthsc_bxd_mamgland_ca_0322/summary.rtf
new file mode 100644
index 0000000..4e4269c
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_mamgland_ca_0322/summary.rtf
@@ -0,0 +1 @@
+This dataset is currently unpublished. Please refer to the contact information above if you want to use this data.
diff --git a/general/datasets/Uthsc_bxd_mamgland_cpm_0322/specifics.rtf b/general/datasets/Uthsc_bxd_mamgland_cpm_0322/specifics.rtf
new file mode 100644
index 0000000..3b28a0d
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_mamgland_cpm_0322/specifics.rtf
@@ -0,0 +1 @@
+UTHSC BXD Triple Negative Breast Cancer Model RNA-Seq (Mar22) CPM Norm All Samples
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_mamgland_cpm_0322/summary.rtf b/general/datasets/Uthsc_bxd_mamgland_cpm_0322/summary.rtf
new file mode 100644
index 0000000..4e4269c
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_mamgland_cpm_0322/summary.rtf
@@ -0,0 +1 @@
+This dataset is currently unpublished. Please refer to the contact information above if you want to use this data.
diff --git a/general/datasets/Uthsc_bxd_mamgland_cpmntum_0322/specifics.rtf b/general/datasets/Uthsc_bxd_mamgland_cpmntum_0322/specifics.rtf
new file mode 100644
index 0000000..4d79eab
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_mamgland_cpmntum_0322/specifics.rtf
@@ -0,0 +1 @@
+UTHSC BXD Triple Negative Breast Cancer Model RNA-Seq (Mar22) CPM Norm Tumor Only
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_mamgland_cpmntum_0322/summary.rtf b/general/datasets/Uthsc_bxd_mamgland_cpmntum_0322/summary.rtf
new file mode 100644
index 0000000..4e4269c
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_mamgland_cpmntum_0322/summary.rtf
@@ -0,0 +1 @@
+This dataset is currently unpublished. Please refer to the contact information above if you want to use this data.
diff --git a/general/datasets/Uthsc_bxd_mamgland_tum_0322/specifics.rtf b/general/datasets/Uthsc_bxd_mamgland_tum_0322/specifics.rtf
new file mode 100644
index 0000000..bc15cdf
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_mamgland_tum_0322/specifics.rtf
@@ -0,0 +1 @@
+UTHSC BXD Triple Negative Breast Cancer Model RNA-Seq (Mar22) Counts Tumor Only
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_mamgland_tum_0322/summary.rtf b/general/datasets/Uthsc_bxd_mamgland_tum_0322/summary.rtf
new file mode 100644
index 0000000..4e4269c
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_mamgland_tum_0322/summary.rtf
@@ -0,0 +1 @@
+This dataset is currently unpublished. Please refer to the contact information above if you want to use this data.
diff --git a/general/datasets/Uthsc_bxd_wb_rnaseq1112/cases.rtf b/general/datasets/Uthsc_bxd_wb_rnaseq1112/cases.rtf
new file mode 100644
index 0000000..2f0fdc0
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_wb_rnaseq1112/cases.rtf
@@ -0,0 +1,245 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Original Strain |
+ Corrected Strain |
+ Sex |
+ Age |
+
+
+ | 1 |
+ BXD13_batch2 |
+ BXD18 |
+ M |
+ 67 |
+
+
+ | 2 |
+ BXD15_batch2 |
+ BXD15 |
+ F |
+ 62 |
+
+
+ | 3 |
+ BXD18_batch2 |
+ BXD19 |
+ F |
+ 65 |
+
+
+ | 4 |
+ BXD24_batch2 |
+ BXD24 |
+ F |
+ 63 |
+
+
+ | 5 |
+ BXD36_batch2 |
+ BXD45 removed |
+ M |
+ 67 |
+
+
+ | 6 |
+ BXD39_batch2 |
+ BXD39 |
+ F |
+ 60 |
+
+
+ | 7 |
+ BXD42_batch2 |
+ BXD43 |
+ F |
+ 67 |
+
+
+ | 8 |
+ BXD43_batch2 |
+ BXD42 |
+ F |
+ 60 |
+
+
+ | 9 |
+ BXD45_batch2 |
+ BXD45 |
+ F |
+ 60 |
+
+
+ | 10 |
+ BXD50_batch2 |
+ BXD50 |
+ F |
+ 57 |
+
+
+ | 11 |
+ BXD51_batch2 |
+ BXD55 |
+ F |
+ 59 |
+
+
+ | 12 |
+ BXD55_batch2 |
+ BXD51 |
+ F |
+ 61 |
+
+
+ | 13 |
+ BXD56_batch2 |
+ BXD56 |
+ F |
+ 67 |
+
+
+ | 14 |
+ BXD6_batch2 |
+ BXD6 |
+ F |
+ 59 |
+
+
+ | 15 |
+ BXD8_batch2 |
+ BXD9 |
+ F |
+ 62 |
+
+
+ | 16 |
+ BXD9_batch2 |
+ BXD8 |
+ M |
+ 70 |
+
+
+ | 17 |
+ BXD14_batch3 |
+ BXD40 |
+ F |
+ 76 |
+
+
+ | 18 |
+ BXD16_batch3 |
+ BXD19 |
+ M |
+ 74 |
+
+
+ | 19 |
+ BXD32_batch3 |
+ BXD32 |
+ M |
+ 54 |
+
+
+ | 20 |
+ BXD38_batch3 |
+ BXD38 |
+ F |
+ 102 |
+
+
+ | 21 |
+ BXD40_batch3 |
+ BXD14 |
+ M |
+ 81 |
+
+
+ | 22 |
+ BXD48_batch3 |
+ BXD48 |
+ M |
+ 68 |
+
+
+ | 23 |
+ BXD60_batch3 |
+ BXD60 |
+ F |
+ 64 |
+
+
+ | 24 |
+ BXD66_batch3 |
+ BXD66 |
+ M |
+ 61 |
+
+
+ | 25 |
+ BXD69_batch3 |
+ BXD69 |
+ F |
+ 66 |
+
+
+ | 26 |
+ BXD70_batch3 |
+ BXD70 |
+ M |
+ 72 |
+
+
+ | 27 |
+ BXD29m_batch4 |
+ BXD1 |
+ F |
+ 60 |
+
+
+ | 28 |
+ BXD29n_batch4 |
+ BXD29 |
+ F |
+ 344 |
+
+
+ | 29 |
+ BXD34_batch4 |
+ BXD34 |
+ F |
+ 108 |
+
+
+ | 30 |
+ BXD49_batch4 |
+ BXD49 |
+ M |
+ 76 |
+
+
+ | 31 |
+ BXD65_batch4 |
+ BXD29 |
+ F |
+ 58 |
+
+
+ | 32 |
+ BXD22_batch6 |
+ BXD22 |
+ F |
+ 67 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_bxd_wb_rnaseq1112/notes.rtf b/general/datasets/Uthsc_bxd_wb_rnaseq1112/notes.rtf
new file mode 100644
index 0000000..c16bd50
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_wb_rnaseq1112/notes.rtf
@@ -0,0 +1,23 @@
+RNA sequencing for BXD strains on SOLiD by David Li.
+All Bam files alignment done by Xusheng Wang
+Aligned files were uploaded to Partek Genomic Suite 6.5 (version 6.10.0810) and processed by K Mozhui
+Normalization: RPKM (reads per kilobase per million mapped reads)
+Batch effect due to low exonic reads for batch 2
+
+Revision 1.6 Untrimmed (current) LRS=(23 999) ->350 records
+Max LRS = 102.6 Record Id:uthsc_nr_015498, Gene Symbol:1500004A13Rik **Note: 1 sample BXD45 and BXD34 removed. BXD41 switched to BXD1 as a second posible candidate.
+
+Revision 1.5 Untrimmed LRS=(23 999) ->268 records
+Max LRS = 80.0 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1 **Note: 1 sample BXD45 removed. BXD41 switched to BXD1 as a second posible candidate.
+
+Revision 1.4 Untrimmed LRS=(23 999) ->246 records
+Max LRS = 80.0 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1 **Note: 1 sample BXD45 removed and keep BXD41
+
+Revision 1.3 Untrimmed LRS=(23 999) ->233 records
+Max LRS = 80.7 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1
+
+Revision 1.2 Untrimmed LRS=(23 999) ->190 records
+Max LRS = 56.9 Record Id:uthsc_nr_003513, Gene Symbol:Neat1
+
+Revision 1 Untrimmed LRS=(23 999) ->126 records
+Max LRS = 35.3 Record Id:uthsc_nm_001113412, Gene Symbol:Fggy
diff --git a/general/datasets/Uthsc_bxd_wb_rnaseq1112/specifics.rtf b/general/datasets/Uthsc_bxd_wb_rnaseq1112/specifics.rtf
new file mode 100644
index 0000000..8e3eb6f
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_wb_rnaseq1112/specifics.rtf
@@ -0,0 +1 @@
+Note: March 2019: now actually 449 transcripts/genes with LRS > 23 and peak LRS is still 102.6.
diff --git a/general/datasets/Uthsc_bxd_wb_rnaseq1112/summary.rtf b/general/datasets/Uthsc_bxd_wb_rnaseq1112/summary.rtf
new file mode 100644
index 0000000..82080d4
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_wb_rnaseq1112/summary.rtf
@@ -0,0 +1,4 @@
+
+ - UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Untrimmed
+ - UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Trimmed dataset have been re-normalized by forcing values down to zero at level of individual mRNA seq assay.
+
diff --git a/general/datasets/Uthsc_bxd_wb_rnaseqex1112/specifics.rtf b/general/datasets/Uthsc_bxd_wb_rnaseqex1112/specifics.rtf
new file mode 100644
index 0000000..7c1a914
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_wb_rnaseqex1112/specifics.rtf
@@ -0,0 +1 @@
+Exon Level
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxd_wb_rnaseqex1112/summary.rtf b/general/datasets/Uthsc_bxd_wb_rnaseqex1112/summary.rtf
new file mode 100644
index 0000000..0ffc063
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_wb_rnaseqex1112/summary.rtf
@@ -0,0 +1 @@
+UTHSC Mouse BXD Whole Brain RNA Sequence Exon Level (Nov12) RPKM
diff --git a/general/datasets/Uthsc_bxd_wb_rnaseqtrim1112/cases.rtf b/general/datasets/Uthsc_bxd_wb_rnaseqtrim1112/cases.rtf
new file mode 100644
index 0000000..2f0fdc0
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_wb_rnaseqtrim1112/cases.rtf
@@ -0,0 +1,245 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Original Strain |
+ Corrected Strain |
+ Sex |
+ Age |
+
+
+ | 1 |
+ BXD13_batch2 |
+ BXD18 |
+ M |
+ 67 |
+
+
+ | 2 |
+ BXD15_batch2 |
+ BXD15 |
+ F |
+ 62 |
+
+
+ | 3 |
+ BXD18_batch2 |
+ BXD19 |
+ F |
+ 65 |
+
+
+ | 4 |
+ BXD24_batch2 |
+ BXD24 |
+ F |
+ 63 |
+
+
+ | 5 |
+ BXD36_batch2 |
+ BXD45 removed |
+ M |
+ 67 |
+
+
+ | 6 |
+ BXD39_batch2 |
+ BXD39 |
+ F |
+ 60 |
+
+
+ | 7 |
+ BXD42_batch2 |
+ BXD43 |
+ F |
+ 67 |
+
+
+ | 8 |
+ BXD43_batch2 |
+ BXD42 |
+ F |
+ 60 |
+
+
+ | 9 |
+ BXD45_batch2 |
+ BXD45 |
+ F |
+ 60 |
+
+
+ | 10 |
+ BXD50_batch2 |
+ BXD50 |
+ F |
+ 57 |
+
+
+ | 11 |
+ BXD51_batch2 |
+ BXD55 |
+ F |
+ 59 |
+
+
+ | 12 |
+ BXD55_batch2 |
+ BXD51 |
+ F |
+ 61 |
+
+
+ | 13 |
+ BXD56_batch2 |
+ BXD56 |
+ F |
+ 67 |
+
+
+ | 14 |
+ BXD6_batch2 |
+ BXD6 |
+ F |
+ 59 |
+
+
+ | 15 |
+ BXD8_batch2 |
+ BXD9 |
+ F |
+ 62 |
+
+
+ | 16 |
+ BXD9_batch2 |
+ BXD8 |
+ M |
+ 70 |
+
+
+ | 17 |
+ BXD14_batch3 |
+ BXD40 |
+ F |
+ 76 |
+
+
+ | 18 |
+ BXD16_batch3 |
+ BXD19 |
+ M |
+ 74 |
+
+
+ | 19 |
+ BXD32_batch3 |
+ BXD32 |
+ M |
+ 54 |
+
+
+ | 20 |
+ BXD38_batch3 |
+ BXD38 |
+ F |
+ 102 |
+
+
+ | 21 |
+ BXD40_batch3 |
+ BXD14 |
+ M |
+ 81 |
+
+
+ | 22 |
+ BXD48_batch3 |
+ BXD48 |
+ M |
+ 68 |
+
+
+ | 23 |
+ BXD60_batch3 |
+ BXD60 |
+ F |
+ 64 |
+
+
+ | 24 |
+ BXD66_batch3 |
+ BXD66 |
+ M |
+ 61 |
+
+
+ | 25 |
+ BXD69_batch3 |
+ BXD69 |
+ F |
+ 66 |
+
+
+ | 26 |
+ BXD70_batch3 |
+ BXD70 |
+ M |
+ 72 |
+
+
+ | 27 |
+ BXD29m_batch4 |
+ BXD1 |
+ F |
+ 60 |
+
+
+ | 28 |
+ BXD29n_batch4 |
+ BXD29 |
+ F |
+ 344 |
+
+
+ | 29 |
+ BXD34_batch4 |
+ BXD34 |
+ F |
+ 108 |
+
+
+ | 30 |
+ BXD49_batch4 |
+ BXD49 |
+ M |
+ 76 |
+
+
+ | 31 |
+ BXD65_batch4 |
+ BXD29 |
+ F |
+ 58 |
+
+
+ | 32 |
+ BXD22_batch6 |
+ BXD22 |
+ F |
+ 67 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_bxd_wb_rnaseqtrim1112/notes.rtf b/general/datasets/Uthsc_bxd_wb_rnaseqtrim1112/notes.rtf
new file mode 100644
index 0000000..c16bd50
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_wb_rnaseqtrim1112/notes.rtf
@@ -0,0 +1,23 @@
+RNA sequencing for BXD strains on SOLiD by David Li.
+All Bam files alignment done by Xusheng Wang
+Aligned files were uploaded to Partek Genomic Suite 6.5 (version 6.10.0810) and processed by K Mozhui
+Normalization: RPKM (reads per kilobase per million mapped reads)
+Batch effect due to low exonic reads for batch 2
+
+Revision 1.6 Untrimmed (current) LRS=(23 999) ->350 records
+Max LRS = 102.6 Record Id:uthsc_nr_015498, Gene Symbol:1500004A13Rik **Note: 1 sample BXD45 and BXD34 removed. BXD41 switched to BXD1 as a second posible candidate.
+
+Revision 1.5 Untrimmed LRS=(23 999) ->268 records
+Max LRS = 80.0 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1 **Note: 1 sample BXD45 removed. BXD41 switched to BXD1 as a second posible candidate.
+
+Revision 1.4 Untrimmed LRS=(23 999) ->246 records
+Max LRS = 80.0 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1 **Note: 1 sample BXD45 removed and keep BXD41
+
+Revision 1.3 Untrimmed LRS=(23 999) ->233 records
+Max LRS = 80.7 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1
+
+Revision 1.2 Untrimmed LRS=(23 999) ->190 records
+Max LRS = 56.9 Record Id:uthsc_nr_003513, Gene Symbol:Neat1
+
+Revision 1 Untrimmed LRS=(23 999) ->126 records
+Max LRS = 35.3 Record Id:uthsc_nm_001113412, Gene Symbol:Fggy
diff --git a/general/datasets/Uthsc_bxd_wb_rnaseqtrim1112/summary.rtf b/general/datasets/Uthsc_bxd_wb_rnaseqtrim1112/summary.rtf
new file mode 100644
index 0000000..82080d4
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_wb_rnaseqtrim1112/summary.rtf
@@ -0,0 +1,4 @@
+
+ - UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Untrimmed
+ - UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Trimmed dataset have been re-normalized by forcing values down to zero at level of individual mRNA seq assay.
+
diff --git a/general/datasets/Uthsc_bxd_wb_rnaseqtrim1_1112/cases.rtf b/general/datasets/Uthsc_bxd_wb_rnaseqtrim1_1112/cases.rtf
new file mode 100644
index 0000000..2f0fdc0
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_wb_rnaseqtrim1_1112/cases.rtf
@@ -0,0 +1,245 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Original Strain |
+ Corrected Strain |
+ Sex |
+ Age |
+
+
+ | 1 |
+ BXD13_batch2 |
+ BXD18 |
+ M |
+ 67 |
+
+
+ | 2 |
+ BXD15_batch2 |
+ BXD15 |
+ F |
+ 62 |
+
+
+ | 3 |
+ BXD18_batch2 |
+ BXD19 |
+ F |
+ 65 |
+
+
+ | 4 |
+ BXD24_batch2 |
+ BXD24 |
+ F |
+ 63 |
+
+
+ | 5 |
+ BXD36_batch2 |
+ BXD45 removed |
+ M |
+ 67 |
+
+
+ | 6 |
+ BXD39_batch2 |
+ BXD39 |
+ F |
+ 60 |
+
+
+ | 7 |
+ BXD42_batch2 |
+ BXD43 |
+ F |
+ 67 |
+
+
+ | 8 |
+ BXD43_batch2 |
+ BXD42 |
+ F |
+ 60 |
+
+
+ | 9 |
+ BXD45_batch2 |
+ BXD45 |
+ F |
+ 60 |
+
+
+ | 10 |
+ BXD50_batch2 |
+ BXD50 |
+ F |
+ 57 |
+
+
+ | 11 |
+ BXD51_batch2 |
+ BXD55 |
+ F |
+ 59 |
+
+
+ | 12 |
+ BXD55_batch2 |
+ BXD51 |
+ F |
+ 61 |
+
+
+ | 13 |
+ BXD56_batch2 |
+ BXD56 |
+ F |
+ 67 |
+
+
+ | 14 |
+ BXD6_batch2 |
+ BXD6 |
+ F |
+ 59 |
+
+
+ | 15 |
+ BXD8_batch2 |
+ BXD9 |
+ F |
+ 62 |
+
+
+ | 16 |
+ BXD9_batch2 |
+ BXD8 |
+ M |
+ 70 |
+
+
+ | 17 |
+ BXD14_batch3 |
+ BXD40 |
+ F |
+ 76 |
+
+
+ | 18 |
+ BXD16_batch3 |
+ BXD19 |
+ M |
+ 74 |
+
+
+ | 19 |
+ BXD32_batch3 |
+ BXD32 |
+ M |
+ 54 |
+
+
+ | 20 |
+ BXD38_batch3 |
+ BXD38 |
+ F |
+ 102 |
+
+
+ | 21 |
+ BXD40_batch3 |
+ BXD14 |
+ M |
+ 81 |
+
+
+ | 22 |
+ BXD48_batch3 |
+ BXD48 |
+ M |
+ 68 |
+
+
+ | 23 |
+ BXD60_batch3 |
+ BXD60 |
+ F |
+ 64 |
+
+
+ | 24 |
+ BXD66_batch3 |
+ BXD66 |
+ M |
+ 61 |
+
+
+ | 25 |
+ BXD69_batch3 |
+ BXD69 |
+ F |
+ 66 |
+
+
+ | 26 |
+ BXD70_batch3 |
+ BXD70 |
+ M |
+ 72 |
+
+
+ | 27 |
+ BXD29m_batch4 |
+ BXD1 |
+ F |
+ 60 |
+
+
+ | 28 |
+ BXD29n_batch4 |
+ BXD29 |
+ F |
+ 344 |
+
+
+ | 29 |
+ BXD34_batch4 |
+ BXD34 |
+ F |
+ 108 |
+
+
+ | 30 |
+ BXD49_batch4 |
+ BXD49 |
+ M |
+ 76 |
+
+
+ | 31 |
+ BXD65_batch4 |
+ BXD29 |
+ F |
+ 58 |
+
+
+ | 32 |
+ BXD22_batch6 |
+ BXD22 |
+ F |
+ 67 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_bxd_wb_rnaseqtrim1_1112/notes.rtf b/general/datasets/Uthsc_bxd_wb_rnaseqtrim1_1112/notes.rtf
new file mode 100644
index 0000000..c16bd50
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_wb_rnaseqtrim1_1112/notes.rtf
@@ -0,0 +1,23 @@
+RNA sequencing for BXD strains on SOLiD by David Li.
+All Bam files alignment done by Xusheng Wang
+Aligned files were uploaded to Partek Genomic Suite 6.5 (version 6.10.0810) and processed by K Mozhui
+Normalization: RPKM (reads per kilobase per million mapped reads)
+Batch effect due to low exonic reads for batch 2
+
+Revision 1.6 Untrimmed (current) LRS=(23 999) ->350 records
+Max LRS = 102.6 Record Id:uthsc_nr_015498, Gene Symbol:1500004A13Rik **Note: 1 sample BXD45 and BXD34 removed. BXD41 switched to BXD1 as a second posible candidate.
+
+Revision 1.5 Untrimmed LRS=(23 999) ->268 records
+Max LRS = 80.0 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1 **Note: 1 sample BXD45 removed. BXD41 switched to BXD1 as a second posible candidate.
+
+Revision 1.4 Untrimmed LRS=(23 999) ->246 records
+Max LRS = 80.0 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1 **Note: 1 sample BXD45 removed and keep BXD41
+
+Revision 1.3 Untrimmed LRS=(23 999) ->233 records
+Max LRS = 80.7 Record Id:uthsc_nm_001039533, Gene Symbol:Pdxdc1
+
+Revision 1.2 Untrimmed LRS=(23 999) ->190 records
+Max LRS = 56.9 Record Id:uthsc_nr_003513, Gene Symbol:Neat1
+
+Revision 1 Untrimmed LRS=(23 999) ->126 records
+Max LRS = 35.3 Record Id:uthsc_nm_001113412, Gene Symbol:Fggy
diff --git a/general/datasets/Uthsc_bxd_wb_rnaseqtrim1_1112/summary.rtf b/general/datasets/Uthsc_bxd_wb_rnaseqtrim1_1112/summary.rtf
new file mode 100644
index 0000000..82080d4
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_wb_rnaseqtrim1_1112/summary.rtf
@@ -0,0 +1,4 @@
+
+ - UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Untrimmed
+ - UTHSC Mouse BXD Whole Brain RNA Sequence (Nov12) RPKM Trimmed dataset have been re-normalized by forcing values down to zero at level of individual mRNA seq assay.
+
diff --git a/general/datasets/Uthsc_bxd_young_adult_eye_rnaseq_tpm_log/experiment-design.rtf b/general/datasets/Uthsc_bxd_young_adult_eye_rnaseq_tpm_log/experiment-design.rtf
new file mode 100644
index 0000000..2f8cedc
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_young_adult_eye_rnaseq_tpm_log/experiment-design.rtf
@@ -0,0 +1 @@
+Total RNA was extracted using Trizol® reagent (Invitrogen, Grand Island, NY, USA) according to the manufacturer’s instructions. Approximately 30 mg of PFC tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been treated with DNase to avoid DNA contamination, and verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 8.0 were used for library preparation
diff --git a/general/datasets/Uthsc_bxd_young_adult_eye_rnaseq_tpm_log/processing.rtf b/general/datasets/Uthsc_bxd_young_adult_eye_rnaseq_tpm_log/processing.rtf
new file mode 100644
index 0000000..8e460ff
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_young_adult_eye_rnaseq_tpm_log/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (GRCm38) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Indices of the reference genome were built using STAR v2.5.0a and paired-end reads were aligned to the reference genome. STAR used the method of Maximal Mappable Prefix which can generate a precise mapping result for junction reads. FeatureCount v0.6.1 was used to count the number of read mapped to each gene. Transcripts Per Million (TPM) was calculated for each gene based on the length of the gene and reads mapped to that gene. In this normalization, the sum of all TPMs (genes-level) are equal to 1,000,000. The TPM was further rescaled to log2(TPM+1).
diff --git a/general/datasets/Uthsc_bxd_young_adult_eye_rnaseq_tpm_log/specifics.rtf b/general/datasets/Uthsc_bxd_young_adult_eye_rnaseq_tpm_log/specifics.rtf
new file mode 100644
index 0000000..7e44a00
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_young_adult_eye_rnaseq_tpm_log/specifics.rtf
@@ -0,0 +1,3644 @@
+BXD Eye (2~6 Month) RNA-Seq (Oct30) TPM Log2
+
+The table of samples that are finally used for this study.
+
+
+
+
+ |
+ Index
+ |
+
+ RNA ID
+ |
+
+ case ID
+ |
+
+ DA_corrected_strain
+ |
+
+ Fuyi_corrected_Sex
+ |
+
+ Age (day)
+ |
+
+ Tissue
+ |
+
+
+ |
+ 1
+ |
+
+ E508
+ |
+
+ *060619.13
+ |
+
+ BXD170
+ |
+
+ Female
+ |
+
+ 76
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 2
+ |
+
+ E509
+ |
+
+ *060619.14
+ |
+
+ BXD170
+ |
+
+ Male
+ |
+
+ 76
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 3
+ |
+
+ E510
+ |
+
+ *060619.16
+ |
+
+ BXD194
+ |
+
+ Female
+ |
+
+ 94
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 4
+ |
+
+ E511
+ |
+
+ *060619.17
+ |
+
+ BXD194
+ |
+
+ Male
+ |
+
+ 94
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 5
+ |
+
+ E512
+ |
+
+ *060619.19
+ |
+
+ BXD213
+ |
+
+ Female
+ |
+
+ 78
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 6
+ |
+
+ E513
+ |
+
+ *060619.20
+ |
+
+ BXD213
+ |
+
+ Male
+ |
+
+ 78
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 7
+ |
+
+ E514
+ |
+
+ *060619.22
+ |
+
+ BXD214
+ |
+
+ Female
+ |
+
+ 107
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 8
+ |
+
+ E515
+ |
+
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+ *012420.36
+ |
+
+ BXD152
+ |
+
+ Male
+ |
+
+ 131
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 96
+ |
+
+ E323
+ |
+
+ *012420.13
+ |
+
+ BXD87
+ |
+
+ Female
+ |
+
+ 120
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 97
+ |
+
+ E325
+ |
+
+ *012420.48
+ |
+
+ BXD190
+ |
+
+ Female
+ |
+
+ 148
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 98
+ |
+
+ E326
+ |
+
+ *012420.09
+ |
+
+ BXD75
+ |
+
+ Male
+ |
+
+ 95
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 99
+ |
+
+ E336
+ |
+
+ *110918.13
+ |
+
+ BXD32
+ |
+
+ Male
+ |
+
+ 153
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 100
+ |
+
+ E338
+ |
+
+ *110918.36
+ |
+
+ BXD71
+ |
+
+ Male
+ |
+
+ 174
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 101
+ |
+
+ E339
+ |
+
+ *110918.35
+ |
+
+ BXD71
+ |
+
+ Female
+ |
+
+ 174
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 102
+ |
+
+ E401
+ |
+
+ *100819.01
+ |
+
+ C57BL/6J
+ |
+
+ Female
+ |
+
+ 110
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 103
+ |
+
+ E402
+ |
+
+ *100819.02
+ |
+
+ C57BL/6J
+ |
+
+ Female
+ |
+
+ 110
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 104
+ |
+
+ E403
+ |
+
+ *100819.03
+ |
+
+ C57BL/6J
+ |
+
+ Male
+ |
+
+ 110
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 105
+ |
+
+ E410
+ |
+
+ *100819.14
+ |
+
+ BXD15
+ |
+
+ Female
+ |
+
+ 94
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 106
+ |
+
+ E411
+ |
+
+ *100819.15
+ |
+
+ BXD15
+ |
+
+ Female
+ |
+
+ 94
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 107
+ |
+
+ E412
+ |
+
+ *100819.28
+ |
+
+ BXD29
+ |
+
+ Female
+ |
+
+ 68
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 108
+ |
+
+ E413
+ |
+
+ *100819.29
+ |
+
+ BXD29
+ |
+
+ Male
+ |
+
+ 68
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 109
+ |
+
+ E420
+ |
+
+ *100819.44
+ |
+
+ BXD44
+ |
+
+ Female
+ |
+
+ 152
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 110
+ |
+
+ E421
+ |
+
+ *100819.45
+ |
+
+ BXD44
+ |
+
+ Male
+ |
+
+ 152
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 111
+ |
+
+ E424
+ |
+
+ *100819.55
+ |
+
+ BXD61
+ |
+
+ Female
+ |
+
+ 120
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 112
+ |
+
+ E425
+ |
+
+ *100819.56
+ |
+
+ BXD61
+ |
+
+ Male
+ |
+
+ 120
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 113
+ |
+
+ E426
+ |
+
+ *100819.58
+ |
+
+ BXD62
+ |
+
+ Female
+ |
+
+ 99
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 114
+ |
+
+ E427
+ |
+
+ *100819.59
+ |
+
+ BXD62
+ |
+
+ Male
+ |
+
+ 99
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 115
+ |
+
+ E428
+ |
+
+ *100819.63
+ |
+
+ BXD65
+ |
+
+ Female
+ |
+
+ 121
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 116
+ |
+
+ E429
+ |
+
+ *100819.64
+ |
+
+ BXD65
+ |
+
+ Male
+ |
+
+ 121
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 117
+ |
+
+ E432
+ |
+
+ *100819.74
+ |
+
+ BXD73
+ |
+
+ Female
+ |
+
+ 154
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 118
+ |
+
+ E433
+ |
+
+ *100819.75
+ |
+
+ BXD73
+ |
+
+ Male
+ |
+
+ 154
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 119
+ |
+
+ E434
+ |
+
+ *100819.77
+ |
+
+ BXD73b
+ |
+
+ Female
+ |
+
+ 153
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 120
+ |
+
+ E435
+ |
+
+ *100819.78
+ |
+
+ BXD73b
+ |
+
+ Male
+ |
+
+ 153
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 121
+ |
+
+ E436
+ |
+
+ *100819.79
+ |
+
+ BXD75
+ |
+
+ Female
+ |
+
+ 93
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 122
+ |
+
+ E437
+ |
+
+ *100819.80
+ |
+
+ BXD75
+ |
+
+ Male
+ |
+
+ 93
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 123
+ |
+
+ E438
+ |
+
+ *100819.86
+ |
+
+ BXD86
+ |
+
+ Female
+ |
+
+ 75
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 124
+ |
+
+ E439
+ |
+
+ *100819.87
+ |
+
+ BXD86
+ |
+
+ Male
+ |
+
+ 75
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 125
+ |
+
+ E440
+ |
+
+ *100819.90
+ |
+
+ BXD89
+ |
+
+ Female
+ |
+
+ 112
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 126
+ |
+
+ E441
+ |
+
+ *100819.91
+ |
+
+ BXD89
+ |
+
+ Male
+ |
+
+ 112
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 127
+ |
+
+ E442
+ |
+
+ *100819.92
+ |
+
+ BXD90
+ |
+
+ Female
+ |
+
+ 123
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 128
+ |
+
+ E443
+ |
+
+ *100819.93
+ |
+
+ BXD90
+ |
+
+ Male
+ |
+
+ 123
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 129
+ |
+
+ E444
+ |
+
+ *100819.95
+ |
+
+ BXD101
+ |
+
+ Female
+ |
+
+ 118
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 130
+ |
+
+ E445
+ |
+
+ *100819.96
+ |
+
+ BXD101
+ |
+
+ Male
+ |
+
+ 118
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 131
+ |
+
+ E446
+ |
+
+ *100819.98
+ |
+
+ BXD102
+ |
+
+ Female
+ |
+
+ 121
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 132
+ |
+
+ E447
+ |
+
+ *100819.99
+ |
+
+ BXD102
+ |
+
+ Male
+ |
+
+ 121
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 133
+ |
+
+ E457
+ |
+
+ *100819.122
+ |
+
+ BXD155
+ |
+
+ Female
+ |
+
+ 86
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 134
+ |
+
+ E458
+ |
+
+ *100819.123
+ |
+
+ BXD155
+ |
+
+ Male
+ |
+
+ 86
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 135
+ |
+
+ E461
+ |
+
+ *052220.38
+ |
+
+ BXD84
+ |
+
+ Female
+ |
+
+ 133
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 136
+ |
+
+ E462
+ |
+
+ *052220.47
+ |
+
+ BXD195
+ |
+
+ Male
+ |
+
+ 93
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 137
+ |
+
+ E463
+ |
+
+ *052220.46
+ |
+
+ BXD195
+ |
+
+ Female
+ |
+
+ 93
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 138
+ |
+
+ E464
+ |
+
+ *052220.39
+ |
+
+ BXD84
+ |
+
+ Male
+ |
+
+ 133
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 139
+ |
+
+ E465
+ |
+
+ *052220.42
+ |
+
+ BXD31
+ |
+
+ Female
+ |
+
+ 111
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 140
+ |
+
+ E466
+ |
+
+ *052220.43
+ |
+
+ BXD31
+ |
+
+ Male
+ |
+
+ 111
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 141
+ |
+
+ E467
+ |
+
+ *052220.26
+ |
+
+ BXD24
+ |
+
+ Female
+ |
+
+ 155
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 142
+ |
+
+ E468
+ |
+
+ *052220.27
+ |
+
+ BXD24
+ |
+
+ Male
+ |
+
+ 155
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 143
+ |
+
+ E469
+ |
+
+ *052220.49
+ |
+
+ BXD218
+ |
+
+ Male
+ |
+
+ 109
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 144
+ |
+
+ E470
+ |
+
+ *052220.36
+ |
+
+ BXD65b
+ |
+
+ Female
+ |
+
+ 110
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 145
+ |
+
+ E471
+ |
+
+ *052220.40
+ |
+
+ BXD202
+ |
+
+ Female
+ |
+
+ 92
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 146
+ |
+
+ E472
+ |
+
+ *052220.45
+ |
+
+ BXD122
+ |
+
+ Male
+ |
+
+ 87
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 147
+ |
+
+ E474
+ |
+
+ *052220.41
+ |
+
+ BXD202
+ |
+
+ Male
+ |
+
+ 92
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 148
+ |
+
+ E475
+ |
+
+ *052220.37
+ |
+
+ BXD65b
+ |
+
+ Male
+ |
+
+ 110
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 149
+ |
+
+ E476
+ |
+
+ *052220.33
+ |
+
+ BXD171
+ |
+
+ Male
+ |
+
+ 74
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 150
+ |
+
+ E477
+ |
+
+ *052220.34
+ |
+
+ BXD123
+ |
+
+ Female
+ |
+
+ 127
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 151
+ |
+
+ E479
+ |
+
+ *052220.32
+ |
+
+ BXD171
+ |
+
+ Female
+ |
+
+ 74
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 152
+ |
+
+ E480
+ |
+
+ *052220.35
+ |
+
+ BXD123
+ |
+
+ Male
+ |
+
+ 127
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 153
+ |
+
+ E481
+ |
+
+ *052220.30
+ |
+
+ BXD172
+ |
+
+ Female
+ |
+
+ 104
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 154
+ |
+
+ E491
+ |
+
+ *052220.28
+ |
+
+ BXD70
+ |
+
+ Female
+ |
+
+ 118
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 155
+ |
+
+ E492
+ |
+
+ *052220.29
+ |
+
+ BXD70
+ |
+
+ Male
+ |
+
+ 118
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 156
+ |
+
+ E505
+ |
+
+ *052220.31
+ |
+
+ BXD172
+ |
+
+ Male
+ |
+
+ 104
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 157
+ |
+
+ E507
+ |
+
+ *052220.48
+ |
+
+ BXD218
+ |
+
+ Female
+ |
+
+ 109
+ |
+
+ Eyeball
+ |
+
+
+
+
+
diff --git a/general/datasets/Uthsc_bxd_young_adult_eye_rnaseq_tpm_log/tissue.rtf b/general/datasets/Uthsc_bxd_young_adult_eye_rnaseq_tpm_log/tissue.rtf
new file mode 100644
index 0000000..bbfb410
--- /dev/null
+++ b/general/datasets/Uthsc_bxd_young_adult_eye_rnaseq_tpm_log/tissue.rtf
@@ -0,0 +1 @@
+The animals were sacrificed under saturated isoflurane. Eyeballs from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Uthsc_bxdaged_0615/cases.rtf b/general/datasets/Uthsc_bxdaged_0615/cases.rtf
new file mode 100644
index 0000000..fba3fbb
--- /dev/null
+++ b/general/datasets/Uthsc_bxdaged_0615/cases.rtf
@@ -0,0 +1,1894 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Sample |
+ Strain |
+ Sex |
+ Age |
+ Batch |
+
+
+ | 1 |
+ R7264H |
+ C57BL/6J_1 |
+ M |
+ 489 |
+ 1 |
+
+
+ | 2 |
+ 052008.03 |
+ C57BL/6J_2 |
+ F |
+ 650 |
+ 2 |
+
+
+ | 3 |
+ R7289H |
+ C57BL/6J_3 |
+ M |
+ 756 |
+ 1 |
+
+
+ | 4 |
+ 052008.01 |
+ C57BL/6J_4 |
+ M |
+ 756 |
+ 2 |
+
+
+ | 5 |
+ R7269H |
+ DBA/2J_1 |
+ M |
+ 367 |
+ 1 |
+
+
+ | 6 |
+ R7185H |
+ DBA/2J_2 |
+ F |
+ 433 |
+ 1 |
+
+
+ | 7 |
+ R7301H |
+ DBA/2J_3 |
+ F |
+ 566 |
+ 1 |
+
+
+ | 8 |
+ R7265H |
+ D2B6F1_1 |
+ M |
+ 492 |
+ 1 |
+
+
+ | 9 |
+ R7304H |
+ D2B6F1_2 |
+ F |
+ 495 |
+ 1 |
+
+
+ | 10 |
+ R7276H |
+ BXD1_1 |
+ M |
+ 323 |
+ 1 |
+
+
+ | 11 |
+ R7281H |
+ BXD1_2 |
+ F |
+ 448 |
+ 1 |
+
+
+ | 12 |
+ 051209.20 |
+ BXD1_3 |
+ F |
+ 477 |
+ 2 |
+
+
+ | 13 |
+ R7261H |
+ BXD2_1 |
+ M |
+ 394 |
+ 1 |
+
+
+ | 14 |
+ R7256H |
+ BXD2_2 |
+ F |
+ 456 |
+ 1 |
+
+
+ | 15 |
+ 022807.04 |
+ BXD2_3 |
+ M |
+ 483 |
+ 2 |
+
+
+ | 16 |
+ 042909.46 |
+ BXD2_4 |
+ M |
+ 609 |
+ 2 |
+
+
+ | 17 |
+ 042909.47 |
+ BXD2_5 |
+ F |
+ 609 |
+ 2 |
+
+
+ | 18 |
+ R7223H |
+ BXD6_1 |
+ M |
+ 526 |
+ 1 |
+
+
+ | 19 |
+ R7198H |
+ BXD8_1 |
+ F |
+ 433 |
+ 1 |
+
+
+ | 20 |
+ R7200H |
+ BXD8_2 |
+ F |
+ 460 |
+ 1 |
+
+
+ | 21 |
+ R7203H |
+ BXD8_3 |
+ M |
+ 471 |
+ 1 |
+
+
+ | 22 |
+ R7294H |
+ BXD9_1 |
+ F |
+ 456 |
+ 1 |
+
+
+ | 23 |
+ 052008.17 |
+ BXD9_2 |
+ M |
+ 631 |
+ 2 |
+
+
+ | 24 |
+ 052008.18 |
+ BXD9_3 |
+ M |
+ 631 |
+ 2 |
+
+
+ | 25 |
+ R7300H |
+ BXD11_1 |
+ M |
+ 457 |
+ 1 |
+
+
+ | 26 |
+ R7227H |
+ BXD11_2 |
+ F |
+ 536 |
+ 1 |
+
+
+ | 27 |
+ 021113.01 |
+ BXD11_3 |
+ F |
+ 741 |
+ 2 |
+
+
+ | 28 |
+ 021113.02 |
+ BXD11_4 |
+ F |
+ 741 |
+ 2 |
+
+
+ | 29 |
+ R7183H |
+ BXD12_1 |
+ F |
+ 506 |
+ 1 |
+
+
+ | 30 |
+ R7233H |
+ BXD12_2 |
+ F |
+ 561 |
+ 1 |
+
+
+ | 31 |
+ R7234H |
+ BXD12_3 |
+ M |
+ 606 |
+ 1 |
+
+
+ | 32 |
+ 020409.01 |
+ BXD12_4 |
+ F |
+ 850 |
+ 2 |
+
+
+ | 33 |
+ 020409.03 |
+ BXD12_5 |
+ M |
+ 850 |
+ 2 |
+
+
+ | 34 |
+ R7238H |
+ BXD14_1 |
+ F |
+ 605 |
+ 1 |
+
+
+ | 35 |
+ R7235H |
+ BXD14_2 |
+ M |
+ 605 |
+ 1 |
+
+
+ | 36 |
+ 022807.11 |
+ BXD16_1 |
+ F |
+ 455 |
+ 2 |
+
+
+ | 37 |
+ R7239H |
+ BXD16_2 |
+ M |
+ 475 |
+ 1 |
+
+
+ | 38 |
+ R7236H |
+ BXD16_3 |
+ F |
+ 561 |
+ 1 |
+
+
+ | 39 |
+ R7229H |
+ BXD18_1 |
+ F |
+ 493 |
+ 1 |
+
+
+ | 40 |
+ 020409.28 |
+ BXD18_2 |
+ F |
+ 548 |
+ 2 |
+
+
+ | 41 |
+ R7268H |
+ BXD19_1 |
+ M |
+ 492 |
+ 1 |
+
+
+ | 42 |
+ R7267H |
+ BXD19_2 |
+ F |
+ 551 |
+ 1 |
+
+
+ | 43 |
+ R7263H |
+ BXD20_1 |
+ M |
+ 489 |
+ 1 |
+
+
+ | 44 |
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+ BXD100_1 |
+ F |
+ 463 |
+ 1 |
+
+
+ | 228 |
+ R7283H |
+ BXD100_2 |
+ M |
+ 507 |
+ 1 |
+
+
+ | 229 |
+ R7274H |
+ BXD100_3 |
+ M |
+ 577 |
+ 1 |
+
+
+ | 230 |
+ R7226H |
+ BXD100_4 |
+ F |
+ 464 |
+ 1 |
+
+
+ | 231 |
+ 051209.62 |
+ BXD100_5 |
+ M |
+ 577 |
+ 2 |
+
+
+ | 232 |
+ R7284H |
+ BXD101_1 |
+ F |
+ 490 |
+ 1 |
+
+
+ | 233 |
+ R7285H |
+ BXD101_2 |
+ M |
+ 408 |
+ 1 |
+
+
+ | 234 |
+ 051112.10 |
+ BXD101_3 |
+ F |
+ 223 |
+ 2 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_bxdaged_0615/specifics.rtf b/general/datasets/Uthsc_bxdaged_0615/specifics.rtf
new file mode 100644
index 0000000..d877bcf
--- /dev/null
+++ b/general/datasets/Uthsc_bxdaged_0615/specifics.rtf
@@ -0,0 +1 @@
+Gene Level
diff --git a/general/datasets/Uthsc_bxdaged_0615/summary.rtf b/general/datasets/Uthsc_bxdaged_0615/summary.rtf
new file mode 100644
index 0000000..73a0125
--- /dev/null
+++ b/general/datasets/Uthsc_bxdaged_0615/summary.rtf
@@ -0,0 +1 @@
+This dataset is now public.
diff --git a/general/datasets/Uthsc_bxdagedex_1116/cases.rtf b/general/datasets/Uthsc_bxdagedex_1116/cases.rtf
new file mode 100644
index 0000000..fba3fbb
--- /dev/null
+++ b/general/datasets/Uthsc_bxdagedex_1116/cases.rtf
@@ -0,0 +1,1894 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Sample |
+ Strain |
+ Sex |
+ Age |
+ Batch |
+
+
+ | 1 |
+ R7264H |
+ C57BL/6J_1 |
+ M |
+ 489 |
+ 1 |
+
+
+ | 2 |
+ 052008.03 |
+ C57BL/6J_2 |
+ F |
+ 650 |
+ 2 |
+
+
+ | 3 |
+ R7289H |
+ C57BL/6J_3 |
+ M |
+ 756 |
+ 1 |
+
+
+ | 4 |
+ 052008.01 |
+ C57BL/6J_4 |
+ M |
+ 756 |
+ 2 |
+
+
+ | 5 |
+ R7269H |
+ DBA/2J_1 |
+ M |
+ 367 |
+ 1 |
+
+
+ | 6 |
+ R7185H |
+ DBA/2J_2 |
+ F |
+ 433 |
+ 1 |
+
+
+ | 7 |
+ R7301H |
+ DBA/2J_3 |
+ F |
+ 566 |
+ 1 |
+
+
+ | 8 |
+ R7265H |
+ D2B6F1_1 |
+ M |
+ 492 |
+ 1 |
+
+
+ | 9 |
+ R7304H |
+ D2B6F1_2 |
+ F |
+ 495 |
+ 1 |
+
+
+ | 10 |
+ R7276H |
+ BXD1_1 |
+ M |
+ 323 |
+ 1 |
+
+
+ | 11 |
+ R7281H |
+ BXD1_2 |
+ F |
+ 448 |
+ 1 |
+
+
+ | 12 |
+ 051209.20 |
+ BXD1_3 |
+ F |
+ 477 |
+ 2 |
+
+
+ | 13 |
+ R7261H |
+ BXD2_1 |
+ M |
+ 394 |
+ 1 |
+
+
+ | 14 |
+ R7256H |
+ BXD2_2 |
+ F |
+ 456 |
+ 1 |
+
+
+ | 15 |
+ 022807.04 |
+ BXD2_3 |
+ M |
+ 483 |
+ 2 |
+
+
+ | 16 |
+ 042909.46 |
+ BXD2_4 |
+ M |
+ 609 |
+ 2 |
+
+
+ | 17 |
+ 042909.47 |
+ BXD2_5 |
+ F |
+ 609 |
+ 2 |
+
+
+ | 18 |
+ R7223H |
+ BXD6_1 |
+ M |
+ 526 |
+ 1 |
+
+
+ | 19 |
+ R7198H |
+ BXD8_1 |
+ F |
+ 433 |
+ 1 |
+
+
+ | 20 |
+ R7200H |
+ BXD8_2 |
+ F |
+ 460 |
+ 1 |
+
+
+ | 21 |
+ R7203H |
+ BXD8_3 |
+ M |
+ 471 |
+ 1 |
+
+
+ | 22 |
+ R7294H |
+ BXD9_1 |
+ F |
+ 456 |
+ 1 |
+
+
+ | 23 |
+ 052008.17 |
+ BXD9_2 |
+ M |
+ 631 |
+ 2 |
+
+
+ | 24 |
+ 052008.18 |
+ BXD9_3 |
+ M |
+ 631 |
+ 2 |
+
+
+ | 25 |
+ R7300H |
+ BXD11_1 |
+ M |
+ 457 |
+ 1 |
+
+
+ | 26 |
+ R7227H |
+ BXD11_2 |
+ F |
+ 536 |
+ 1 |
+
+
+ | 27 |
+ 021113.01 |
+ BXD11_3 |
+ F |
+ 741 |
+ 2 |
+
+
+ | 28 |
+ 021113.02 |
+ BXD11_4 |
+ F |
+ 741 |
+ 2 |
+
+
+ | 29 |
+ R7183H |
+ BXD12_1 |
+ F |
+ 506 |
+ 1 |
+
+
+ | 30 |
+ R7233H |
+ BXD12_2 |
+ F |
+ 561 |
+ 1 |
+
+
+ | 31 |
+ R7234H |
+ BXD12_3 |
+ M |
+ 606 |
+ 1 |
+
+
+ | 32 |
+ 020409.01 |
+ BXD12_4 |
+ F |
+ 850 |
+ 2 |
+
+
+ | 33 |
+ 020409.03 |
+ BXD12_5 |
+ M |
+ 850 |
+ 2 |
+
+
+ | 34 |
+ R7238H |
+ BXD14_1 |
+ F |
+ 605 |
+ 1 |
+
+
+ | 35 |
+ R7235H |
+ BXD14_2 |
+ M |
+ 605 |
+ 1 |
+
+
+ | 36 |
+ 022807.11 |
+ BXD16_1 |
+ F |
+ 455 |
+ 2 |
+
+
+ | 37 |
+ R7239H |
+ BXD16_2 |
+ M |
+ 475 |
+ 1 |
+
+
+ | 38 |
+ R7236H |
+ BXD16_3 |
+ F |
+ 561 |
+ 1 |
+
+
+ | 39 |
+ R7229H |
+ BXD18_1 |
+ F |
+ 493 |
+ 1 |
+
+
+ | 40 |
+ 020409.28 |
+ BXD18_2 |
+ F |
+ 548 |
+ 2 |
+
+
+ | 41 |
+ R7268H |
+ BXD19_1 |
+ M |
+ 492 |
+ 1 |
+
+
+ | 42 |
+ R7267H |
+ BXD19_2 |
+ F |
+ 551 |
+ 1 |
+
+
+ | 43 |
+ R7263H |
+ BXD20_1 |
+ M |
+ 489 |
+ 1 |
+
+
+ | 44 |
+ R7232H |
+ BXD20_2 |
+ M |
+ 506 |
+ 1 |
+
+
+ | 45 |
+ R7230H |
+ BXD21_1 |
+ F |
+ 537 |
+ 1 |
+
+
+ | 46 |
+ R7260H |
+ BXD22_1 |
+ F |
+ 502 |
+ 1 |
+
+
+ | 47 |
+ R7262H |
+ BXD22_2 |
+ M |
+ 596 |
+ 1 |
+
+
+ | 48 |
+ 020409.08 |
+ BXD22_3 |
+ F |
+ 675 |
+ 2 |
+
+
+ | 49 |
+ R7257H |
+ BXD23_1 |
+ M |
+ 462 |
+ 1 |
+
+
+ | 50 |
+ R7258H |
+ BXD23_2 |
+ F |
+ 502 |
+ 1 |
+
+
+ | 51 |
+ 020107.15 |
+ BXD23_3 |
+ M |
+ 512 |
+ 2 |
+
+
+ | 52 |
+ R7228H |
+ BXD24_1 |
+ F |
+ 415 |
+ 1 |
+
+
+ | 53 |
+ R7255H |
+ BXD24_2 |
+ F |
+ 456 |
+ 1 |
+
+
+ | 54 |
+ R7231H |
+ BXD24_3 |
+ M |
+ 470 |
+ 1 |
+
+
+ | 55 |
+ 020409.21 |
+ BXD24_4 |
+ F |
+ 636 |
+ 2 |
+
+
+ | 56 |
+ 020409.29 |
+ BXD24_5 |
+ F |
+ 639 |
+ 2 |
+
+
+ | 57 |
+ 052008.36 |
+ BXD25_1 |
+ F |
+ 430 |
+ 2 |
+
+
+ | 58 |
+ R7252H |
+ BXD25_2 |
+ F |
+ 454 |
+ 1 |
+
+
+ | 59 |
+ 052008.115 |
+ BXD25_3 |
+ M |
+ 709 |
+ 2 |
+
+
+ | 60 |
+ R7286H |
+ BXD27_1 |
+ F |
+ 472 |
+ 1 |
+
+
+ | 61 |
+ R7170H |
+ BXD27_2 |
+ F |
+ 472 |
+ 1 |
+
+
+ | 62 |
+ R7254H |
+ BXD28_1 |
+ M |
+ 493 |
+ 1 |
+
+
+ | 63 |
+ R7251H |
+ BXD28_2 |
+ F |
+ 543 |
+ 1 |
+
+
+ | 64 |
+ 020107.18 |
+ BXD28_3 |
+ M |
+ 605 |
+ 2 |
+
+
+ | 65 |
+ R7259H |
+ BXD29_1 |
+ F |
+ 483 |
+ 1 |
+
+
+ | 66 |
+ 040109.92 |
+ BXD31_1 |
+ F |
+ 445 |
+ 2 |
+
+
+ | 67 |
+ 031407.18 |
+ BXD31_2 |
+ F |
+ 467 |
+ 2 |
+
+
+ | 68 |
+ 020409.31 |
+ BXD31_3 |
+ F |
+ 648 |
+ 2 |
+
+
+ | 69 |
+ 042909.71 |
+ BXD32_1 |
+ M |
+ 566 |
+ 2 |
+
+
+ | 70 |
+ R7244H |
+ BXD33_1 |
+ F |
+ 448 |
+ 1 |
+
+
+ | 71 |
+ R7253H |
+ BXD33_2 |
+ M |
+ 464 |
+ 1 |
+
+
+ | 72 |
+ R7174H |
+ BXD33_3 |
+ F |
+ 471 |
+ 1 |
+
+
+ | 73 |
+ R7270H |
+ BXD33_4 |
+ M |
+ 662 |
+ 1 |
+
+
+ | 74 |
+ 040109.79 |
+ BXD33_5 |
+ F |
+ 683 |
+ 2 |
+
+
+ | 75 |
+ 050609.35 |
+ BXD34_1 |
+ F |
+ 414 |
+ 2 |
+
+
+ | 76 |
+ 052008.51 |
+ BXD34_2 |
+ F |
+ 549 |
+ 2 |
+
+
+ | 77 |
+ 101513.06 |
+ BXD34_3 |
+ F |
+ 554 |
+ 2 |
+
+
+ | 78 |
+ 101513.07 |
+ BXD34_4 |
+ F |
+ 748 |
+ 2 |
+
+
+ | 79 |
+ R7247H |
+ BXD38_1 |
+ M |
+ 446 |
+ 1 |
+
+
+ | 80 |
+ R7242H |
+ BXD38_3 |
+ F |
+ 464 |
+ 1 |
+
+
+ | 81 |
+ 020107.25 |
+ BXD38_4 |
+ M |
+ 530 |
+ 2 |
+
+
+ | 82 |
+ R7173H |
+ BXD39_1 |
+ F |
+ 500 |
+ 1 |
+
+
+ | 83 |
+ R7175H |
+ BXD39_2 |
+ M |
+ 500 |
+ 1 |
+
+
+ | 84 |
+ R7250H |
+ BXD39_3 |
+ M |
+ 536 |
+ 1 |
+
+
+ | 85 |
+ 020409.19 |
+ BXD39_4 |
+ F |
+ 661 |
+ 2 |
+
+
+ | 86 |
+ R7288H |
+ BXD40_1 |
+ F |
+ 451 |
+ 1 |
+
+
+ | 87 |
+ 051209.56 |
+ BXD40_2 |
+ F |
+ 451 |
+ 2 |
+
+
+ | 88 |
+ R7210H |
+ BXD40_3 |
+ M |
+ 470 |
+ 1 |
+
+
+ | 89 |
+ R7197H |
+ BXD40_4 |
+ M |
+ 614 |
+ 1 |
+
+
+ | 90 |
+ 042909.19 |
+ BXD40_5 |
+ F |
+ 633 |
+ 2 |
+
+
+ | 91 |
+ 020409.73 |
+ BXD40_6 |
+ F |
+ 728 |
+ 2 |
+
+
+ | 92 |
+ R7246H |
+ BXD42_1 |
+ M |
+ 446 |
+ 1 |
+
+
+ | 93 |
+ R7266H |
+ BXD42_2 |
+ F |
+ 486 |
+ 1 |
+
+
+ | 94 |
+ R7280H |
+ BXD42_3 |
+ F |
+ 518 |
+ 1 |
+
+
+ | 95 |
+ R7249H |
+ BXD43_1 |
+ F |
+ 454 |
+ 1 |
+
+
+ | 96 |
+ R7248H |
+ BXD43_2 |
+ M |
+ 462 |
+ 1 |
+
+
+ | 97 |
+ 050609.76 |
+ BXD43_3 |
+ M |
+ 616 |
+ 2 |
+
+
+ | 98 |
+ R7241H |
+ BXD44_1 |
+ M |
+ 415 |
+ 1 |
+
+
+ | 99 |
+ R7279H |
+ BXD44_2 |
+ M |
+ 419 |
+ 1 |
+
+
+ | 100 |
+ R7243H |
+ BXD44_3 |
+ F |
+ 438 |
+ 1 |
+
+
+ | 101 |
+ 042607.13 |
+ BXD44_4 |
+ F |
+ 564 |
+ 2 |
+
+
+ | 102 |
+ 042607.14 |
+ BXD44_5 |
+ F |
+ 564 |
+ 2 |
+
+
+ | 103 |
+ R7176H |
+ BXD45_1 |
+ F |
+ 451 |
+ 1 |
+
+
+ | 104 |
+ 040109.88 |
+ BXD45_2 |
+ M |
+ 631 |
+ 2 |
+
+
+ | 105 |
+ R7245H |
+ BXD48_1 |
+ F |
+ 499 |
+ 1 |
+
+
+ | 106 |
+ R7220H |
+ BXD48_2 |
+ M |
+ 526 |
+ 1 |
+
+
+ | 107 |
+ 051209.29 |
+ BXD48_3 |
+ M |
+ 740 |
+ 2 |
+
+
+ | 108 |
+ 101513.10 |
+ BXD48_4 |
+ F |
+ 740 |
+ 2 |
+
+
+ | 109 |
+ R7299H |
+ BXD48a_1 |
+ F |
+ 479 |
+ 1 |
+
+
+ | 110 |
+ R7297H |
+ BXD48a_2 |
+ M |
+ 479 |
+ 1 |
+
+
+ | 111 |
+ 051209.01 |
+ BXD48a_3 |
+ F |
+ 479 |
+ 2 |
+
+
+ | 112 |
+ 051209.03 |
+ BXD48a_4 |
+ M |
+ 479 |
+ 2 |
+
+
+ | 113 |
+ 051209.52 |
+ BXD48a_5 |
+ F |
+ 608 |
+ 2 |
+
+
+ | 114 |
+ 051209.65 |
+ BXD48a_6 |
+ M |
+ 748 |
+ 2 |
+
+
+ | 115 |
+ R7224H |
+ BXD50_1 |
+ F |
+ 530 |
+ 1 |
+
+
+ | 116 |
+ R7221H |
+ BXD50_2 |
+ M |
+ 530 |
+ 1 |
+
+
+ | 117 |
+ 050609.04 |
+ BXD50_3 |
+ F |
+ 778 |
+ 2 |
+
+
+ | 118 |
+ R7177H |
+ BXD51_1 |
+ F |
+ 487 |
+ 1 |
+
+
+ | 119 |
+ R7290H |
+ BXD51_2 |
+ M |
+ 407 |
+ 1 |
+
+
+ | 120 |
+ 041709.11 |
+ BXD51_3 |
+ M |
+ 621 |
+ 2 |
+
+
+ | 121 |
+ R7222H |
+ BXD55_1 |
+ M |
+ 528 |
+ 1 |
+
+
+ | 122 |
+ R7225H |
+ BXD55_2 |
+ F |
+ 587 |
+ 1 |
+
+
+ | 123 |
+ 052008.134 |
+ BXD55_3 |
+ F |
+ 778 |
+ 2 |
+
+
+ | 124 |
+ 052008.135 |
+ BXD55_4 |
+ F |
+ 766 |
+ 2 |
+
+
+ | 125 |
+ R7178H |
+ BXD56_1 |
+ M |
+ 501 |
+ 1 |
+
+
+ | 126 |
+ 051209.66 |
+ BXD56_2 |
+ M |
+ 694 |
+ 2 |
+
+
+ | 127 |
+ 052008.139 |
+ BXD56_3 |
+ F |
+ 734 |
+ 2 |
+
+
+ | 128 |
+ 042909.52 |
+ BXD60_1 |
+ M |
+ 457 |
+ 2 |
+
+
+ | 129 |
+ 101513.14 |
+ BXD60_2 |
+ F |
+ 759 |
+ 2 |
+
+
+ | 130 |
+ 052008.63 |
+ BXD61_1 |
+ M |
+ 650 |
+ 2 |
+
+
+ | 131 |
+ 020409.14 |
+ BXD61_2 |
+ F |
+ 702 |
+ 2 |
+
+
+ | 132 |
+ 121214.20 |
+ BXD62_1 |
+ F |
+ 353 |
+ 2 |
+
+
+ | 133 |
+ R7291H |
+ BXD62_2 |
+ M |
+ 439 |
+ 1 |
+
+
+ | 134 |
+ 040109.91 |
+ BXD62_3 |
+ F |
+ 699 |
+ 2 |
+
+
+ | 135 |
+ R7218H |
+ BXD63_1 |
+ M |
+ 438 |
+ 1 |
+
+
+ | 136 |
+ R7215H |
+ BXD63_2 |
+ F |
+ 475 |
+ 1 |
+
+
+ | 137 |
+ 050609.28 |
+ BXD63_3 |
+ M |
+ 972 |
+ 2 |
+
+
+ | 138 |
+ R7219H |
+ BXD64_1 |
+ M |
+ 528 |
+ 1 |
+
+
+ | 139 |
+ R7216H |
+ BXD64_2 |
+ F |
+ 587 |
+ 1 |
+
+
+ | 140 |
+ R7217H |
+ BXD65_1 |
+ F |
+ 425 |
+ 1 |
+
+
+ | 141 |
+ 050609.39 |
+ BXD65_2 |
+ M |
+ 601 |
+ 2 |
+
+
+ | 142 |
+ 052008.67 |
+ BXD65_3 |
+ F |
+ 808 |
+ 2 |
+
+
+ | 143 |
+ R7273H |
+ BXD65a_1 |
+ F |
+ 389 |
+ 1 |
+
+
+ | 144 |
+ R7277H |
+ BXD65a_2 |
+ M |
+ 715 |
+ 1 |
+
+
+ | 145 |
+ 061407.15 |
+ BXD65a_3 |
+ F |
+ 536 |
+ 2 |
+
+
+ | 146 |
+ 061407.16 |
+ BXD65a_4 |
+ F |
+ 536 |
+ 2 |
+
+
+ | 147 |
+ R7271H |
+ BXD65b_1 |
+ M |
+ 483 |
+ 1 |
+
+
+ | 148 |
+ R7302H |
+ BXD66_1 |
+ F |
+ 446 |
+ 1 |
+
+
+ | 149 |
+ R7214H |
+ BXD66_2 |
+ M |
+ 463 |
+ 1 |
+
+
+ | 150 |
+ 042507.19 |
+ BXD66_3 |
+ M |
+ 557 |
+ 2 |
+
+
+ | 151 |
+ 042507.20 |
+ BXD66_4 |
+ F |
+ 557 |
+ 2 |
+
+
+ | 152 |
+ R7278H |
+ BXD67_1 |
+ F |
+ 415 |
+ 1 |
+
+
+ | 153 |
+ R7213H |
+ BXD67_2 |
+ M |
+ 425 |
+ 1 |
+
+
+ | 154 |
+ R7240H |
+ BXD67_3 |
+ F |
+ 499 |
+ 1 |
+
+
+ | 155 |
+ 042607.11 |
+ BXD67_4 |
+ F |
+ 606 |
+ 2 |
+
+
+ | 156 |
+ 052008.71 |
+ BXD67_5 |
+ F |
+ 649 |
+ 2 |
+
+
+ | 157 |
+ R7211H |
+ BXD68_1 |
+ F |
+ 415 |
+ 1 |
+
+
+ | 158 |
+ R7212H |
+ BXD68_2 |
+ M |
+ 421 |
+ 1 |
+
+
+ | 159 |
+ 042607.27 |
+ BXD68_3 |
+ F |
+ 623 |
+ 2 |
+
+
+ | 160 |
+ 042607.28 |
+ BXD68_4 |
+ F |
+ 623 |
+ 2 |
+
+
+ | 161 |
+ R7305H |
+ BXD69_1 |
+ F |
+ 504 |
+ 1 |
+
+
+ | 162 |
+ 061913.13 |
+ BXD69_2 |
+ F |
+ 558 |
+ 2 |
+
+
+ | 163 |
+ 112707.08 |
+ BXD69_3 |
+ F |
+ 602 |
+ 2 |
+
+
+ | 164 |
+ R7207H |
+ BXD70_1 |
+ F |
+ 458 |
+ 1 |
+
+
+ | 165 |
+ R7204H |
+ BXD70_2 |
+ M |
+ 460 |
+ 1 |
+
+
+ | 166 |
+ 042909.28 |
+ BXD70_3 |
+ F |
+ 761 |
+ 2 |
+
+
+ | 167 |
+ 042909.29 |
+ BXD70_4 |
+ F |
+ 761 |
+ 2 |
+
+
+ | 168 |
+ R7205H |
+ BXD71_1 |
+ M |
+ 471 |
+ 1 |
+
+
+ | 169 |
+ R7208H |
+ BXD71_2 |
+ F |
+ 474 |
+ 1 |
+
+
+ | 170 |
+ 020409.11 |
+ BXD71_3 |
+ F |
+ 701 |
+ 2 |
+
+
+ | 171 |
+ 020409.49 |
+ BXD71_4 |
+ F |
+ 582 |
+ 2 |
+
+
+ | 172 |
+ R7209H |
+ BXD73_1 |
+ F |
+ 470 |
+ 1 |
+
+
+ | 173 |
+ R7206H |
+ BXD73_2 |
+ M |
+ 464 |
+ 1 |
+
+
+ | 174 |
+ 011007.16 |
+ BXD73_3 |
+ F |
+ 544 |
+ 2 |
+
+
+ | 175 |
+ 052008.81 |
+ BXD73_4 |
+ F |
+ 642 |
+ 2 |
+
+
+ | 176 |
+ R7181H |
+ BXD73a_1 |
+ F |
+ 443 |
+ 1 |
+
+
+ | 177 |
+ 061407.18 |
+ BXD73a_2 |
+ F |
+ 443 |
+ 2 |
+
+
+ | 178 |
+ R7182H |
+ BXD73a_3 |
+ M |
+ 614 |
+ 1 |
+
+
+ | 179 |
+ 052008.86 |
+ BXD73a_4 |
+ M |
+ 710 |
+ 2 |
+
+
+ | 180 |
+ 031407.10 |
+ BXD74_1 |
+ M |
+ 804 |
+ 2 |
+
+
+ | 181 |
+ 011107.08 |
+ BXD75_1 |
+ F |
+ 535 |
+ 2 |
+
+
+ | 182 |
+ R7188H |
+ BXD76_1 |
+ F |
+ 408 |
+ 1 |
+
+
+ | 183 |
+ R7187H |
+ BXD76_2 |
+ M |
+ 564 |
+ 1 |
+
+
+ | 184 |
+ R7179H |
+ BXD76_3 |
+ M |
+ 579 |
+ 1 |
+
+
+ | 185 |
+ R7292HR |
+ BXD77_1 |
+ M |
+ 347 |
+ 1 |
+
+
+ | 186 |
+ R7201H |
+ BXD77_2 |
+ F |
+ 454 |
+ 1 |
+
+
+ | 187 |
+ 052008.83 |
+ BXD77_3 |
+ F |
+ 659 |
+ 2 |
+
+
+ | 188 |
+ R7202H |
+ BXD79_1 |
+ M |
+ 485 |
+ 1 |
+
+
+ | 189 |
+ R7199H |
+ BXD79_2 |
+ F |
+ 515 |
+ 1 |
+
+
+ | 190 |
+ R7298H |
+ BXD79_3 |
+ M |
+ 704 |
+ 1 |
+
+
+ | 191 |
+ 050609.25 |
+ BXD81_1 |
+ F |
+ 434 |
+ 2 |
+
+
+ | 192 |
+ R7190H |
+ BXD81_2 |
+ F |
+ 458 |
+ 1 |
+
+
+ | 193 |
+ R7196H |
+ BXD81_3 |
+ M |
+ 515 |
+ 1 |
+
+
+ | 194 |
+ R7184H |
+ BXD83_1 |
+ M |
+ 441 |
+ 1 |
+
+
+ | 195 |
+ 061307.30 |
+ BXD83_2 |
+ F |
+ 612 |
+ 2 |
+
+
+ | 196 |
+ 121907.10 |
+ BXD83_3 |
+ M |
+ 617 |
+ 2 |
+
+
+ | 197 |
+ R7195H |
+ BXD84_1 |
+ M |
+ 474 |
+ 1 |
+
+
+ | 198 |
+ R7296H |
+ BXD84_2 |
+ M |
+ 484 |
+ 1 |
+
+
+ | 199 |
+ R7192H |
+ BXD84_3 |
+ F |
+ 522 |
+ 1 |
+
+
+ | 200 |
+ 020409.80 |
+ BXD84_4 |
+ F |
+ 564 |
+ 2 |
+
+
+ | 201 |
+ 112707.12 |
+ BXD84_5 |
+ F |
+ 592 |
+ 2 |
+
+
+ | 202 |
+ R7272H |
+ BXD85_1 |
+ M |
+ 425 |
+ 1 |
+
+
+ | 203 |
+ R7193H |
+ BXD85_2 |
+ F |
+ 506 |
+ 1 |
+
+
+ | 204 |
+ 020409.12 |
+ BXD85_3 |
+ F |
+ 702 |
+ 2 |
+
+
+ | 205 |
+ 020409.13 |
+ BXD85_4 |
+ F |
+ 702 |
+ 2 |
+
+
+ | 206 |
+ R7191H |
+ BXD86_1 |
+ M |
+ 425 |
+ 1 |
+
+
+ | 207 |
+ 020409.35 |
+ BXD86_2 |
+ F |
+ 613 |
+ 2 |
+
+
+ | 208 |
+ 020409.36 |
+ BXD86_3 |
+ F |
+ 613 |
+ 2 |
+
+
+ | 209 |
+ R7194H |
+ BXD87_1 |
+ F |
+ 425 |
+ 1 |
+
+
+ | 210 |
+ R7303HR |
+ BXD87_2 |
+ M |
+ 478 |
+ 1 |
+
+
+ | 211 |
+ R7186H |
+ BXD87_3 |
+ M |
+ 442 |
+ 1 |
+
+
+ | 212 |
+ 052008.97 |
+ BXD87_4 |
+ F |
+ 666 |
+ 2 |
+
+
+ | 213 |
+ 052008.98 |
+ BXD87_5 |
+ M |
+ 666 |
+ 2 |
+
+
+ | 214 |
+ R7295H |
+ BXD89_1 |
+ F |
+ 446 |
+ 1 |
+
+
+ | 215 |
+ 052008.100 |
+ BXD89_2 |
+ M |
+ 616 |
+ 2 |
+
+
+ | 216 |
+ R7287H |
+ BXD90_1 |
+ M |
+ 434 |
+ 1 |
+
+
+ | 217 |
+ R7293H |
+ BXD90_2 |
+ M |
+ 558 |
+ 1 |
+
+
+ | 218 |
+ 052008.105 |
+ BXD90_3 |
+ F |
+ 452 |
+ 2 |
+
+
+ | 219 |
+ R7180H |
+ BXD95_1 |
+ F |
+ 467 |
+ 1 |
+
+
+ | 220 |
+ R7169H |
+ BXD95_2 |
+ M |
+ 467 |
+ 1 |
+
+
+ | 221 |
+ 100914.09 |
+ BXD95_3 |
+ F |
+ 536 |
+ 2 |
+
+
+ | 222 |
+ R7237H |
+ BXD98_1 |
+ M |
+ 605 |
+ 1 |
+
+
+ | 223 |
+ R7171H |
+ BXD98_2 |
+ F |
+ 639 |
+ 1 |
+
+
+ | 224 |
+ R7275H |
+ BXD98_3 |
+ F |
+ 488 |
+ 1 |
+
+
+ | 225 |
+ R7189H |
+ BXD99_1 |
+ M |
+ 524 |
+ 1 |
+
+
+ | 226 |
+ R7172H |
+ BXD99_2 |
+ F |
+ 471 |
+ 1 |
+
+
+ | 227 |
+ R7282H |
+ BXD100_1 |
+ F |
+ 463 |
+ 1 |
+
+
+ | 228 |
+ R7283H |
+ BXD100_2 |
+ M |
+ 507 |
+ 1 |
+
+
+ | 229 |
+ R7274H |
+ BXD100_3 |
+ M |
+ 577 |
+ 1 |
+
+
+ | 230 |
+ R7226H |
+ BXD100_4 |
+ F |
+ 464 |
+ 1 |
+
+
+ | 231 |
+ 051209.62 |
+ BXD100_5 |
+ M |
+ 577 |
+ 2 |
+
+
+ | 232 |
+ R7284H |
+ BXD101_1 |
+ F |
+ 490 |
+ 1 |
+
+
+ | 233 |
+ R7285H |
+ BXD101_2 |
+ M |
+ 408 |
+ 1 |
+
+
+ | 234 |
+ 051112.10 |
+ BXD101_3 |
+ F |
+ 223 |
+ 2 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_bxdagedex_1116/specifics.rtf b/general/datasets/Uthsc_bxdagedex_1116/specifics.rtf
new file mode 100644
index 0000000..7c1a914
--- /dev/null
+++ b/general/datasets/Uthsc_bxdagedex_1116/specifics.rtf
@@ -0,0 +1 @@
+Exon Level
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxdagedex_1116/summary.rtf b/general/datasets/Uthsc_bxdagedex_1116/summary.rtf
new file mode 100644
index 0000000..73a0125
--- /dev/null
+++ b/general/datasets/Uthsc_bxdagedex_1116/summary.rtf
@@ -0,0 +1 @@
+This dataset is now public.
diff --git a/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/cases.rtf b/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/cases.rtf
new file mode 100644
index 0000000..9fbf83b
--- /dev/null
+++ b/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/cases.rtf
@@ -0,0 +1,4336 @@
+The study included 187 mice (12~18 month) from B6, D2, D2-Gpmnb, B6D2F1, D2B6F1, and 87 advanced intercross BXD strains (about 2 mice per strain). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+
+
+The table of samples that are finally used for this study.
+
+
+
+
+ |
+ Index
+ |
+
+ RNA ID
+ |
+
+ case ID
+ |
+
+ DA_corrected_strain
+ |
+
+ Corrected Sex
+ |
+
+ AgeAtDeath days
+ |
+
+ Tissue
+ |
+
+
+ |
+ 1
+ |
+
+ E18
+ |
+
+ 050115.16
+ |
+
+ BXD75
+ |
+
+ Female
+ |
+
+ 460
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 2
+ |
+
+ E19
+ |
+
+ 050115.17
+ |
+
+ BXD75
+ |
+
+ Female
+ |
+
+ 460
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 3
+ |
+
+ E21
+ |
+
+ 042715.10
+ |
+
+ D2B6F1
+ |
+
+ Female
+ |
+
+ 500
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 4
+ |
+
+ E22
+ |
+
+ 050115.19
+ |
+
+ BXD79
+ |
+
+ Female
+ |
+
+ 468
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 5
+ |
+
+ E31
+ |
+
+ 121515.13
+ |
+
+ BXD45
+ |
+
+ Female
+ |
+
+ 507
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 6
+ |
+
+ E33
+ |
+
+ 012615.10
+ |
+
+ BXD45
+ |
+
+ Female
+ |
+
+ 384
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 7
+ |
+
+ E34
+ |
+
+ 012615.04
+ |
+
+ BXD62
+ |
+
+ Female
+ |
+
+ 376
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 8
+ |
+
+ E40
+ |
+
+ 021213.21
+ |
+
+ BXD79
+ |
+
+ Female
+ |
+
+ 378
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 9
+ |
+
+ E49
+ |
+
+ 021213.13
+ |
+
+ BXD60
+ |
+
+ Female
+ |
+
+ 530
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 10
+ |
+
+ E60
+ |
+
+ 101713.01
+ |
+
+ BXD60
+ |
+
+ Female
+ |
+
+ 374
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 11
+ |
+
+ E62
+ |
+
+ 090612.07
+ |
+
+ BXD73b
+ |
+
+ Female
+ |
+
+ 377
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 12
+ |
+
+ E63
+ |
+
+ 090612.08
+ |
+
+ BXD73b
+ |
+
+ Female
+ |
+
+ 377
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 13
+ |
+
+ E65
+ |
+
+ 050912.04
+ |
+
+ BXD34
+ |
+
+ Female
+ |
+
+ 419
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 14
+ |
+
+ E67
+ |
+
+ 42214.08
+ |
+
+ BXD40
+ |
+
+ Female
+ |
+
+ 362
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 15
+ |
+
+ E72
+ |
+
+ 42214.04
+ |
+
+ BXD24
+ |
+
+ Female
+ |
+
+ 377
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 16
+ |
+
+ E75
+ |
+
+ 42214.03
+ |
+
+ BXD24
+ |
+
+ Female
+ |
+
+ 377
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 17
+ |
+
+ E78
+ |
+
+ 42314.1
+ |
+
+ B6D2F1
+ |
+
+ Male
+ |
+
+ 364
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 18
+ |
+
+ E82
+ |
+
+ 121615.05
+ |
+
+ BXD62
+ |
+
+ Female
+ |
+
+ 525
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 19
+ |
+
+ E87
+ |
+
+ 101014.10
+ |
+
+ BXD95
+ |
+
+ Female
+ |
+
+ 536
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 20
+ |
+
+ E89
+ |
+
+ 121615.22
+ |
+
+ BXD89
+ |
+
+ Female
+ |
+
+ 444
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 21
+ |
+
+ E90
+ |
+
+ 101014.09
+ |
+
+ BXD95
+ |
+
+ Female
+ |
+
+ 536
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 22
+ |
+
+ E99
+ |
+
+ 121214.15
+ |
+
+ BXD70
+ |
+
+ Female
+ |
+
+ 357
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 23
+ |
+
+ E100
+ |
+
+ 121214.16
+ |
+
+ BXD70
+ |
+
+ Female
+ |
+
+ 357
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 24
+ |
+
+ E124
+ |
+
+ 042214.18
+ |
+
+ D2B6F1
+ |
+
+ Male
+ |
+
+ 397
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 25
+ |
+
+ E152
+ |
+
+ 050912.04
+ |
+
+ BXD48a
+ |
+
+ Female
+ |
+
+ 419
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 26
+ |
+
+ E158
+ |
+
+ 101713.02
+ |
+
+ BXD100
+ |
+
+ Female
+ |
+
+ 374
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 27
+ |
+
+ E224
+ |
+
+ 021313.26
+ |
+
+ BXD84
+ |
+
+ Female
+ |
+
+ 385
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 28
+ |
+
+ E264
+ |
+
+ *050318.12
+ |
+
+ BXD69
+ |
+
+ Male
+ |
+
+ 387
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 29
+ |
+
+ E288
+ |
+
+ *110918.106
+ |
+
+ BXD211
+ |
+
+ Male
+ |
+
+ 404
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 30
+ |
+
+ E289
+ |
+
+ *110918.105
+ |
+
+ BXD211
+ |
+
+ Female
+ |
+
+ 404
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 31
+ |
+
+ E290
+ |
+
+ *100218.04
+ |
+
+ BXD44
+ |
+
+ Female
+ |
+
+ 530
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 32
+ |
+
+ E291
+ |
+
+ *100218.05
+ |
+
+ BXD44
+ |
+
+ Male
+ |
+
+ 530
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 33
+ |
+
+ E292
+ |
+
+ *100218.18
+ |
+
+ BXD68
+ |
+
+ Female
+ |
+
+ 516
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 34
+ |
+
+ E293
+ |
+
+ *100218.20
+ |
+
+ BXD68
+ |
+
+ Male
+ |
+
+ 516
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 35
+ |
+
+ E294
+ |
+
+ *100218.36
+ |
+
+ BXD84
+ |
+
+ Female
+ |
+
+ 516
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 36
+ |
+
+ E298
+ |
+
+ *100218.73
+ |
+
+ BXD184
+ |
+
+ Female
+ |
+
+ 512
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 37
+ |
+
+ E299
+ |
+
+ *100218.74
+ |
+
+ BXD184
+ |
+
+ Male
+ |
+
+ 512
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 38
+ |
+
+ E303
+ |
+
+ AGE061218.98
+ |
+
+ BXD177
+ |
+
+ Female
+ |
+
+ 364
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 39
+ |
+
+ E304
+ |
+
+ AGE061218.108
+ |
+
+ BXD195
+ |
+
+ Male
+ |
+
+ 386
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 40
+ |
+
+ E306
+ |
+
+ AGE061218.107
+ |
+
+ BXD195
+ |
+
+ Female
+ |
+
+ 386
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 41
+ |
+
+ E308
+ |
+
+ AGE061218.99
+ |
+
+ BXD177
+ |
+
+ Male
+ |
+
+ 364
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 42
+ |
+
+ E310
+ |
+
+ AGE061218.90
+ |
+
+ BXD168
+ |
+
+ Male
+ |
+
+ 538
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 43
+ |
+
+ E311
+ |
+
+ AGE061218.85
+ |
+
+ BXD160
+ |
+
+ Male
+ |
+
+ 390
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 44
+ |
+
+ E312
+ |
+
+ AGE061218.71
+ |
+
+ BXD150
+ |
+
+ Male
+ |
+
+ 398
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 45
+ |
+
+ E313
+ |
+
+ AGE061218.22
+ |
+
+ BXD34
+ |
+
+ Male
+ |
+
+ 369
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 46
+ |
+
+ E314
+ |
+
+ AGE061218.21
+ |
+
+ BXD34
+ |
+
+ Female
+ |
+
+ 369
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 47
+ |
+
+ E331
+ |
+
+ *110918.07
+ |
+
+ BXD28
+ |
+
+ Male
+ |
+
+ 366
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 48
+ |
+
+ E334
+ |
+
+ *110918.02
+ |
+
+ BXD18
+ |
+
+ Male
+ |
+
+ 452
+ |
+
+ Eyeball
+ |
+
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+ E556
+ |
+
+ *061119.22
+ |
+
+ DBA/2J
+ |
+
+ Male
+ |
+
+ 380
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 137
+ |
+
+ E561
+ |
+
+ *061219.12
+ |
+
+ BXD27
+ |
+
+ Female
+ |
+
+ 494
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 138
+ |
+
+ E564
+ |
+
+ *061219.14
+ |
+
+ BXD27
+ |
+
+ Male
+ |
+
+ 494
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 139
+ |
+
+ E565
+ |
+
+ *060419.04
+ |
+
+ BXD32
+ |
+
+ Female
+ |
+
+ 425
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 140
+ |
+
+ E566
+ |
+
+ *060419.05
+ |
+
+ BXD32
+ |
+
+ Male
+ |
+
+ 425
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 141
+ |
+
+ E567
+ |
+
+ *070919.01
+ |
+
+ BXD86
+ |
+
+ Female
+ |
+
+ 381
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 142
+ |
+
+ E569
+ |
+
+ *070919.03
+ |
+
+ BXD86
+ |
+
+ Male
+ |
+
+ 381
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 143
+ |
+
+ E576
+ |
+
+ *072519.11
+ |
+
+ BXD191
+ |
+
+ Male
+ |
+
+ 477
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 144
+ |
+
+ E577
+ |
+
+ *072519.09
+ |
+
+ BXD190
+ |
+
+ Male
+ |
+
+ 434
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 145
+ |
+
+ E582
+ |
+
+ *073019.16
+ |
+
+ BXD216
+ |
+
+ Male
+ |
+
+ 459
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 146
+ |
+
+ E591
+ |
+
+ *061319.04
+ |
+
+ BXD48
+ |
+
+ Female
+ |
+
+ 425
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 147
+ |
+
+ E592
+ |
+
+ *061319.05
+ |
+
+ BXD48
+ |
+
+ Male
+ |
+
+ 425
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 148
+ |
+
+ E593
+ |
+
+ *061319.21
+ |
+
+ BXD61
+ |
+
+ Male
+ |
+
+ 459
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 149
+ |
+
+ E600
+ |
+
+ *050318.10
+ |
+
+ BXD69
+ |
+
+ Female
+ |
+
+ 387
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 150
+ |
+
+ E601
+ |
+
+ *013020.53
+ |
+
+ BXD102
+ |
+
+ Male
+ |
+
+ 416
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 151
+ |
+
+ E603
+ |
+
+ *013020.25
+ |
+
+ BXD65b
+ |
+
+ Male
+ |
+
+ 505
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 152
+ |
+
+ E605
+ |
+
+ *013020.54
+ |
+
+ BXD102
+ |
+
+ Female
+ |
+
+ 416
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 153
+ |
+
+ E620
+ |
+
+ *012420.26
+ |
+
+ BXD128a
+ |
+
+ Male
+ |
+
+ 366
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 154
+ |
+
+ E625
+ |
+
+ *110918.54
+ |
+
+ BXD101
+ |
+
+ Male
+ |
+
+ 361
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 155
+ |
+
+ E626
+ |
+
+ *110918.53
+ |
+
+ BXD101
+ |
+
+ Female
+ |
+
+ 361
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 156
+ |
+
+ E631
+ |
+
+ *083019.14
+ |
+
+ BXD16
+ |
+
+ Female
+ |
+
+ 363
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 157
+ |
+
+ E635
+ |
+
+ *083019.35
+ |
+
+ BXD61
+ |
+
+ Male
+ |
+
+ 364
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 158
+ |
+
+ E638
+ |
+
+ *083019.60
+ |
+
+ BXD90
+ |
+
+ Female
+ |
+
+ 378
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 159
+ |
+
+ E639
+ |
+
+ *083019.62
+ |
+
+ BXD90
+ |
+
+ Male
+ |
+
+ 378
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 160
+ |
+
+ E662
+ |
+
+ *100819.153
+ |
+
+ BXD202
+ |
+
+ Male
+ |
+
+ 410
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 161
+ |
+
+ E663
+ |
+
+ *100819.157
+ |
+
+ BXD205
+ |
+
+ Female
+ |
+
+ 371
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 162
+ |
+
+ E664
+ |
+
+ *100819.158
+ |
+
+ BXD205
+ |
+
+ Male
+ |
+
+ 372
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 163
+ |
+
+ E665
+ |
+
+ *100819.163
+ |
+
+ BXD213
+ |
+
+ Female
+ |
+
+ 396
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 164
+ |
+
+ E666
+ |
+
+ *100819.164
+ |
+
+ BXD213
+ |
+
+ Male
+ |
+
+ 397
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 165
+ |
+
+ E667
+ |
+
+ *100819.168
+ |
+
+ BXD223
+ |
+
+ Female
+ |
+
+ 419
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 166
+ |
+
+ E668
+ |
+
+ *100819.169
+ |
+
+ BXD223
+ |
+
+ Male
+ |
+
+ 420
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 167
+ |
+
+ E672
+ |
+
+ *052920.10
+ |
+
+ BXD83
+ |
+
+ Male
+ |
+
+ 380
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 168
+ |
+
+ E675
+ |
+
+ *052920.13
+ |
+
+ DBA/2J-Gpnmb
+ |
+
+ Female
+ |
+
+ 452
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 169
+ |
+
+ E679
+ |
+
+ *052920.12
+ |
+
+ DBA/2J-Gpnmb
+ |
+
+ Female
+ |
+
+ 458
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 170
+ |
+
+ E680
+ |
+
+ *052920.01
+ |
+
+ BXD43
+ |
+
+ Female
+ |
+
+ 465
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 171
+ |
+
+ E682
+ |
+
+ *052920.02
+ |
+
+ C57BL/6J
+ |
+
+ Female
+ |
+
+ 433
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 172
+ |
+
+ E685
+ |
+
+ *052920.09
+ |
+
+ BXD83
+ |
+
+ Female
+ |
+
+ 379
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 173
+ |
+
+ E699
+ |
+
+ *072120.14
+ |
+
+ BXD40
+ |
+
+ Male
+ |
+
+ 458
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 174
+ |
+
+ E709
+ |
+
+ *072120.24
+ |
+
+ BXD150
+ |
+
+ Female
+ |
+
+ 433
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 175
+ |
+
+ E712
+ |
+
+ *072120.27
+ |
+
+ BXD160
+ |
+
+ Female
+ |
+
+ 367
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 176
+ |
+
+ E726
+ |
+
+ *072120.41
+ |
+
+ BXD16
+ |
+
+ Female
+ |
+
+ 367
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 177
+ |
+
+ E733
+ |
+
+ *072120.48
+ |
+
+ BXD60
+ |
+
+ Female
+ |
+
+ 558
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 178
+ |
+
+ E735
+ |
+
+ *072120.50
+ |
+
+ BXD180
+ |
+
+ Male
+ |
+
+ 473
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 179
+ |
+
+ E738
+ |
+
+ *072120.53
+ |
+
+ BXD128a
+ |
+
+ Female
+ |
+
+ 387
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 180
+ |
+
+ E745
+ |
+
+ *072120.60
+ |
+
+ BXD199
+ |
+
+ Female
+ |
+
+ 457
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 181
+ |
+
+ E746
+ |
+
+ *072120.61
+ |
+
+ BXD199
+ |
+
+ Male
+ |
+
+ 457
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 182
+ |
+
+ E749
+ |
+
+ *072120.64
+ |
+
+ BXD2
+ |
+
+ Female
+ |
+
+ 399
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 183
+ |
+
+ E750
+ |
+
+ *072120.65
+ |
+
+ BXD2
+ |
+
+ Male
+ |
+
+ 399
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 184
+ |
+
+ E753
+ |
+
+ *072120.68
+ |
+
+ BXD169
+ |
+
+ Female
+ |
+
+ 441
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 185
+ |
+
+ E754
+ |
+
+ *072120.69
+ |
+
+ BXD169
+ |
+
+ Male
+ |
+
+ 441
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 186
+ |
+
+ E759
+ |
+
+ *072120.72
+ |
+
+ BXD187
+ |
+
+ Female
+ |
+
+ 354
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 187
+ |
+
+ E760
+ |
+
+ *072120.73
+ |
+
+ BXD187
+ |
+
+ Male
+ |
+
+ 354
+ |
+
+ Eyeball
+ |
+
+
+
+
+
diff --git a/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/experiment-design.rtf b/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/experiment-design.rtf
new file mode 100644
index 0000000..e7afcee
--- /dev/null
+++ b/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Extraction
+
+Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. according to the manufacturer’s instructions. Approximately 30 mg of PFC tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 7.0 were used for library preparation
diff --git a/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/notes.rtf b/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/notes.rtf
new file mode 100644
index 0000000..d622df7
--- /dev/null
+++ b/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/notes.rtf
@@ -0,0 +1 @@
+UTHSC BXD Young Aged Eye RNA-Seq (Apr22) DESeq2 rlog2
diff --git a/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/processing.rtf b/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/processing.rtf
new file mode 100644
index 0000000..7ddb89f
--- /dev/null
+++ b/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (mm11 Mus_musculus.GRCm39, release 104) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Rows with no gene symbol name were deleted. Indices of the reference genome were built using STAR version 2.5.2b and paired-end reads were aligned to the reference genome. FeatureCount from package RsubRead, version 1.32.4, was used to count the number of read mapped to each gene. Raw counts were then normalized and log2 transformed using function rlogTransformation from the DESeq2 package (version 1.16.1) and an increment was added to the normalized values to make all values positive.
diff --git a/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/specifics.rtf b/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/specifics.rtf
new file mode 100644
index 0000000..2e5de4e
--- /dev/null
+++ b/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/specifics.rtf
@@ -0,0 +1 @@
+UTHSC BXD Old Aged Eye RNA-Seq (Apr22) DESeq2 rlog2
\ No newline at end of file
diff --git a/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/tissue.rtf b/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/tissue.rtf
new file mode 100644
index 0000000..126ab9f
--- /dev/null
+++ b/general/datasets/Uthsc_bxdoldeyernaseq_deseq2_rlog2_0422/tissue.rtf
@@ -0,0 +1,3 @@
+Tissue Harvest
+
+The animals were sacrificed under saturated isoflurane. Eyeballs from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/cases.rtf b/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/cases.rtf
new file mode 100644
index 0000000..9fbf83b
--- /dev/null
+++ b/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/cases.rtf
@@ -0,0 +1,4336 @@
+The study included 187 mice (12~18 month) from B6, D2, D2-Gpmnb, B6D2F1, D2B6F1, and 87 advanced intercross BXD strains (about 2 mice per strain). All procedures were approved by the UTHSC Institutional Animal Care and Use Committee.
+
+
+
+The table of samples that are finally used for this study.
+
+
+
+
+ |
+ Index
+ |
+
+ RNA ID
+ |
+
+ case ID
+ |
+
+ DA_corrected_strain
+ |
+
+ Corrected Sex
+ |
+
+ AgeAtDeath days
+ |
+
+ Tissue
+ |
+
+
+ |
+ 1
+ |
+
+ E18
+ |
+
+ 050115.16
+ |
+
+ BXD75
+ |
+
+ Female
+ |
+
+ 460
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 2
+ |
+
+ E19
+ |
+
+ 050115.17
+ |
+
+ BXD75
+ |
+
+ Female
+ |
+
+ 460
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 3
+ |
+
+ E21
+ |
+
+ 042715.10
+ |
+
+ D2B6F1
+ |
+
+ Female
+ |
+
+ 500
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 4
+ |
+
+ E22
+ |
+
+ 050115.19
+ |
+
+ BXD79
+ |
+
+ Female
+ |
+
+ 468
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 5
+ |
+
+ E31
+ |
+
+ 121515.13
+ |
+
+ BXD45
+ |
+
+ Female
+ |
+
+ 507
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 6
+ |
+
+ E33
+ |
+
+ 012615.10
+ |
+
+ BXD45
+ |
+
+ Female
+ |
+
+ 384
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 7
+ |
+
+ E34
+ |
+
+ 012615.04
+ |
+
+ BXD62
+ |
+
+ Female
+ |
+
+ 376
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 8
+ |
+
+ E40
+ |
+
+ 021213.21
+ |
+
+ BXD79
+ |
+
+ Female
+ |
+
+ 378
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 9
+ |
+
+ E49
+ |
+
+ 021213.13
+ |
+
+ BXD60
+ |
+
+ Female
+ |
+
+ 530
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 10
+ |
+
+ E60
+ |
+
+ 101713.01
+ |
+
+ BXD60
+ |
+
+ Female
+ |
+
+ 374
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 11
+ |
+
+ E62
+ |
+
+ 090612.07
+ |
+
+ BXD73b
+ |
+
+ Female
+ |
+
+ 377
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 12
+ |
+
+ E63
+ |
+
+ 090612.08
+ |
+
+ BXD73b
+ |
+
+ Female
+ |
+
+ 377
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 13
+ |
+
+ E65
+ |
+
+ 050912.04
+ |
+
+ BXD34
+ |
+
+ Female
+ |
+
+ 419
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 14
+ |
+
+ E67
+ |
+
+ 42214.08
+ |
+
+ BXD40
+ |
+
+ Female
+ |
+
+ 362
+ |
+
+ Eyeball
+ |
+
+
+ |
+ 15
+ |
+
+ E72
+ |
+
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diff --git a/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/experiment-design.rtf b/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/experiment-design.rtf
new file mode 100644
index 0000000..e7afcee
--- /dev/null
+++ b/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Extraction
+
+Total RNA was extracted using MIRNEASY MINI KIT (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. according to the manufacturer’s instructions. Approximately 30 mg of PFC tissue was added into a 2 ml tube containing 700ul QIAzol Lysis Reagent and one 5 mm stainless steel bead (Qiagen, Hilden, Germany). The tissue was homogenized for 2 minutes in a Tissue Lyser II (Qiagen, Hilden, Germany) with a speed frequency of 30 r followed by incubating for 5 minutes.140 µl chloroform was added into the homogenate, shaken vigorously for 15 seconds, and centrifuged for 15 minutes at 12,000 x g at 4 ℃. 280 µl upper aqueous was then transferred into a new collection tube containing 500 µl 100% ethanol. The mixture was loaded into a RNeasy miniâ€spin column (Qiagen, Valencia, CA, USA), once with Buffer RWT and twice with Buffer RPE purification. All RNA had been verified by Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA with OD260/280 > 1.8 and RIN > 7.0 were used for library preparation
diff --git a/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/notes.rtf b/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/notes.rtf
new file mode 100644
index 0000000..d622df7
--- /dev/null
+++ b/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/notes.rtf
@@ -0,0 +1 @@
+UTHSC BXD Young Aged Eye RNA-Seq (Apr22) DESeq2 rlog2
diff --git a/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/processing.rtf b/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/processing.rtf
new file mode 100644
index 0000000..7ddb89f
--- /dev/null
+++ b/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/processing.rtf
@@ -0,0 +1,9 @@
+Generation of RNA-seq data
+
+1 µg of RNA was used for cDNA library construction at Novogene using an NEBNext® Ultra RNA Library Prep Kit for Illumina® (cat# E7420S, New England Biolabs, Ipswich, MA, USA) according to the manufacturer’s protocol. Briefly, mRNA was enriched using oligo(dT) beads followed by two rounds of purification and fragmented randomly by adding fragmentation buffer. The first strand cDNA was synthesized using random hexamers primer, after which a custom second-strand synthesis buffer (Illumina, San Diego, CA, USA), dNTPs, RNase H and DNA polymerase I were added to generate the second strand (ds cDNA). After a series of terminal repair, poly-adenylation, and sequencing adaptor ligation, the double-stranded cDNA library was completed following size selection and PCR enrichment. The resulting 250-350 bp insert libraries were quantified using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR. Size distribution was analyzed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). Qualified libraries were sequenced on an Illumina Novaseq Platform (Illumina, San Diego, CA, USA) using a paired-end 150 run (2×150 bases). An average of 40 million raw reads were generated from each library.
+
+
+
+Read mapping and normalization
+
+Mus musculus (mouse) reference genome (mm11 Mus_musculus.GRCm39, release 104) and gene model annotation files were downloaded from the Ensembl genome browser (https://useast.ensembl.org/). Rows with no gene symbol name were deleted. Indices of the reference genome were built using STAR version 2.5.2b and paired-end reads were aligned to the reference genome. FeatureCount from package RsubRead, version 1.32.4, was used to count the number of read mapped to each gene. Raw counts were then normalized and log2 transformed using function rlogTransformation from the DESeq2 package (version 1.16.1) and an increment was added to the normalized values to make all values positive.
diff --git a/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/tissue.rtf b/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/tissue.rtf
new file mode 100644
index 0000000..126ab9f
--- /dev/null
+++ b/general/datasets/Uthsc_bxdygeyernaseq_deseq2_rlog2_0422/tissue.rtf
@@ -0,0 +1,3 @@
+Tissue Harvest
+
+The animals were sacrificed under saturated isoflurane. Eyeballs from the animals were dissected and stored at −80°C until RNA extraction.
diff --git a/general/datasets/Uthsc_emsr_all_affymta1_mar17/specifics.rtf b/general/datasets/Uthsc_emsr_all_affymta1_mar17/specifics.rtf
new file mode 100644
index 0000000..4f2baa1
--- /dev/null
+++ b/general/datasets/Uthsc_emsr_all_affymta1_mar17/specifics.rtf
@@ -0,0 +1 @@
+All Treatments
\ No newline at end of file
diff --git a/general/datasets/Uthsc_emsr_all_affymta1_mar17/summary.rtf b/general/datasets/Uthsc_emsr_all_affymta1_mar17/summary.rtf
new file mode 100644
index 0000000..e320185
--- /dev/null
+++ b/general/datasets/Uthsc_emsr_all_affymta1_mar17/summary.rtf
@@ -0,0 +1 @@
+Info File in progress.
diff --git a/general/datasets/Uthsc_emsr_et_affymta1_mar17/specifics.rtf b/general/datasets/Uthsc_emsr_et_affymta1_mar17/specifics.rtf
new file mode 100644
index 0000000..971c8e2
--- /dev/null
+++ b/general/datasets/Uthsc_emsr_et_affymta1_mar17/specifics.rtf
@@ -0,0 +1 @@
+Ethanol Treatment
\ No newline at end of file
diff --git a/general/datasets/Uthsc_emsr_et_affymta1_mar17/summary.rtf b/general/datasets/Uthsc_emsr_et_affymta1_mar17/summary.rtf
new file mode 100644
index 0000000..e320185
--- /dev/null
+++ b/general/datasets/Uthsc_emsr_et_affymta1_mar17/summary.rtf
@@ -0,0 +1 @@
+Info File in progress.
diff --git a/general/datasets/Uthsc_emsr_etst_affymta1_mar17/specifics.rtf b/general/datasets/Uthsc_emsr_etst_affymta1_mar17/specifics.rtf
new file mode 100644
index 0000000..1c7602b
--- /dev/null
+++ b/general/datasets/Uthsc_emsr_etst_affymta1_mar17/specifics.rtf
@@ -0,0 +1 @@
+Ethanol-Stress Treatment
\ No newline at end of file
diff --git a/general/datasets/Uthsc_emsr_etst_affymta1_mar17/summary.rtf b/general/datasets/Uthsc_emsr_etst_affymta1_mar17/summary.rtf
new file mode 100644
index 0000000..e320185
--- /dev/null
+++ b/general/datasets/Uthsc_emsr_etst_affymta1_mar17/summary.rtf
@@ -0,0 +1 @@
+Info File in progress.
diff --git a/general/datasets/Uthsc_emsr_sal_affymta1_mar17/specifics.rtf b/general/datasets/Uthsc_emsr_sal_affymta1_mar17/specifics.rtf
new file mode 100644
index 0000000..84f5f30
--- /dev/null
+++ b/general/datasets/Uthsc_emsr_sal_affymta1_mar17/specifics.rtf
@@ -0,0 +1 @@
+Saline Treatment
\ No newline at end of file
diff --git a/general/datasets/Uthsc_emsr_sal_affymta1_mar17/summary.rtf b/general/datasets/Uthsc_emsr_sal_affymta1_mar17/summary.rtf
new file mode 100644
index 0000000..e320185
--- /dev/null
+++ b/general/datasets/Uthsc_emsr_sal_affymta1_mar17/summary.rtf
@@ -0,0 +1 @@
+Info File in progress.
diff --git a/general/datasets/Uthsc_emsr_st_affymta1_mar17/specifics.rtf b/general/datasets/Uthsc_emsr_st_affymta1_mar17/specifics.rtf
new file mode 100644
index 0000000..78e1f39
--- /dev/null
+++ b/general/datasets/Uthsc_emsr_st_affymta1_mar17/specifics.rtf
@@ -0,0 +1 @@
+Stress Treatment
\ No newline at end of file
diff --git a/general/datasets/Uthsc_emsr_st_affymta1_mar17/summary.rtf b/general/datasets/Uthsc_emsr_st_affymta1_mar17/summary.rtf
new file mode 100644
index 0000000..e320185
--- /dev/null
+++ b/general/datasets/Uthsc_emsr_st_affymta1_mar17/summary.rtf
@@ -0,0 +1 @@
+Info File in progress.
diff --git a/general/datasets/Uthsc_gutexl_0414/cases.rtf b/general/datasets/Uthsc_gutexl_0414/cases.rtf
new file mode 100644
index 0000000..e3e9e26
--- /dev/null
+++ b/general/datasets/Uthsc_gutexl_0414/cases.rtf
@@ -0,0 +1,1696 @@
+
+
+
+
+
+
+
+
+ | Index |
+ CaseID |
+ Strain |
+ Sex |
+ Coat Color |
+ Date of Birth |
+ Generation |
+ Sacrifice Date |
+ Age |
+ RNA
+ conc.(ug/ul) |
+ RNA Purity
+ 260/280 |
+ RNA Integrity Number RIN |
+ Run Chip |
+ Notes |
+
+
+ | 1 |
+ 081910.14 |
+ B6D2F1 |
+ M |
+ black |
+ 06/10/2010 |
+ |
+ 08/18/2010 |
+ 69 |
+ 0.5 |
+ 2.00 |
+ 8.40 |
+ y |
+ |
+
+
+ | 2 |
+ 081910.17 |
+ B6D2F1 |
+ M |
+ black |
+ 06/10/2010 |
+ |
+ 08/18/2010 |
+ 69 |
+ 0.9 |
+ 2.00 |
+ 8.60 |
+ |
+ |
+
+
+ | 3 |
+ 081910.18 |
+ B6D2F1 |
+ F |
+ black |
+ 06/10/2010 |
+ |
+ 08/18/2010 |
+ 69 |
+ 0.3 |
+ 1.80 |
+ 9.30 |
+ y |
+ |
+
+
+ | 4 |
+ 081910.09 |
+ D2B6F1 |
+ F |
+ black |
+ 06/02/2010 |
+ |
+ 08/18/2010 |
+ 77 |
+ 0.7 |
+ 2.00 |
+ 9.00 |
+ y |
+ |
+
+
+ | 5 |
+ 081910.23 |
+ D2B6F1 |
+ M |
+ black |
+ 06/02/2010 |
+ |
+ 08/18/2010 |
+ 77 |
+ 10.2 |
+ 2.02 |
+ 8.50 |
+ y |
+ |
+
+
+ | 6 |
+ 081910.12 |
+ C57BL/6J |
+ F |
+ black |
+ 06/02/2010 |
+ |
+ 08/18/2010 |
+ 77 |
+ 0.6 |
+ 1.90 |
+ n/a |
+ y |
+ |
+
+
+ | 7 |
+ 081910.25 |
+ C57BL/6J |
+ M |
+ black |
+ 06/02/2010 |
+ |
+ 08/18/2010 |
+ 77 |
+ 3.4 |
+ 2.03 |
+ |
+ y |
+ |
+
+
+ | 8 |
+ 081910.39 |
+ C57BL/6J |
+ F |
+ black |
+ 06/02/2010 |
+ |
+ 08/18/2010 |
+ 77 |
+ 2.30 |
+ 1.99 |
+ 8.50 |
+ y |
+ |
+
+
+ | 9 |
+ 081910.41 |
+ C57BL/6J |
+ M |
+ black |
+ 06/18/2010 |
+ |
+ 08/18/2010 |
+ 61 |
+ 2.20 |
+ 2.02 |
+ 8.60 |
+ y |
+ |
+
+
+ | 10 |
+ 081910.29 |
+ DBA/2J |
+ F |
+ dilute brown DBA |
+ 06/02/2010 |
+ |
+ 08/18/2010 |
+ 77 |
+ 2.9 |
+ 2.03 |
+ 8.50 |
+ y |
+ need one more female |
+
+
+ | 11 |
+ 081910.31 |
+ DBA/2J |
+ M |
+ dilute brown DBA |
+ 06/11/2010 |
+ |
+ 08/18/2010 |
+ 68 |
+ 8.6 |
+ 2.06 |
+ 8.00 |
+ y |
+ |
+
+
+ | 12 |
+ 081910.43 |
+ DBA/2J |
+ M |
+ dilute brown DBA |
+ 05/06/2010 |
+ |
+ 08/18/2010 |
+ 104 |
+ 2.30 |
+ 2.01 |
+ 9.30 |
+ y |
+ |
+
+
+ | 13 |
+ 081810.08 |
+ BXD1 |
+ M |
+ dilute brown DBA |
+ 05/24/2010 |
+ 142 |
+ 08/17/2010 |
+ 85 |
+ 0.6 |
+ 1.92 |
+ 8.50 |
+ y |
+ |
+
+
+ | 14 |
+ 081810.13 |
+ BXD1 |
+ F |
+ dilute brown DBA |
+ 06/07/2010 |
+ 139 |
+ 08/17/2010 |
+ 71 |
+ 0.7 |
+ |
+ 9.00 |
+ y |
+ |
+
+
+ | 15 |
+ 081710.91 |
+ BXD11 |
+ M |
+ black |
+ 06/02/2010 |
+ 137 |
+ 08/17/2010 |
+ 76 |
+ 0.7 |
+ 1.93 |
+ 8.20 |
+ y |
+ |
+
+
+ | 16 |
+ 081710.97 |
+ BXD11 |
+ F |
+ black |
+ 05/22/2010 |
+ 136 |
+ 08/17/2010 |
+ 87 |
+ 1.0 |
+ 1.95 |
+ 8.90 |
+ y |
+ |
+
+
+ | 17 |
+ 081810.23 |
+ BXD12 |
+ M |
+ gray |
+ 06/01/2010 |
+ 122 |
+ 08/17/2010 |
+ 77 |
+ 0.9 |
+ 2.00 |
+ 8.00 |
+ y |
+ |
+
+
+ | 18 |
+ 081810.44 |
+ BXD12 |
+ F |
+ gray |
+ 06/01/2010 |
+ 122 |
+ 08/18/2010 |
+ 78 |
+ 0.8 |
+ 1.93 |
+ 8.30 |
+ y |
+ |
+
+
+ | 19 |
+ 081810.33 |
+ BXD14 |
+ F |
+ black |
+ 05/29/2010 |
+ 142 |
+ 08/17/2010 |
+ 80 |
+ 1.2 |
+ 1.97 |
+ 8.10 |
+ y |
+ |
+
+
+ | 20 |
+ 081810.52 |
+ BXD14 |
+ M |
+ black |
+ 05/29/2010 |
+ 142 |
+ 08/18/2010 |
+ 81 |
+ 0.4 |
+ 1.90 |
+ 9.00 |
+ y |
+ |
+
+
+ | 21 |
+ 081810.19 |
+ BXD24 |
+ F |
+ brown |
+ 05/24/2010 |
+ 90 |
+ 08/17/2010 |
+ 85 |
+ 0.3 |
+ 1.90 |
+ 9.10 |
+ y |
+ This strain comes from UTHSC colony since 2008. So they are probably blind. |
+
+
+ | 22 |
+ 081810.42 |
+ BXD24 |
+ M |
+ brown |
+ 05/24/2010 |
+ 90 |
+ 08/17/2010 |
+ 85 |
+ 0.7 |
+ 2.00 |
+ 8.50 |
+ y |
+ This strain comes from UTHSC colony since 2008. So they are probably blind. |
+
+
+ | 23 |
+ 081710.99 |
+ BXD27 |
+ M |
+ dilute brown DBA |
+ 06/05/2010 |
+ 162 |
+ 08/17/2010 |
+ 73 |
+ 1.3 |
+ 1.95 |
+ 8.40 |
+ y |
+ need one more female |
+
+
+ | 24 |
+ 081810.04 |
+ BXD29 |
+ M |
+ gray |
+ 06/07/2010 |
+ 25 |
+ 08/17/2010 |
+ 71 |
+ 0.5 |
+ 1.91 |
+ 8.40 |
+ y |
+ |
+
+
+ | 25 |
+ 081810.10 |
+ BXD29 |
+ F |
+ gray |
+ 06/07/2010 |
+ 25 |
+ 08/17/2010 |
+ 71 |
+ 0.6 |
+ 1.97 |
+ 8.70 |
+ y |
+ |
+
+
+ | 26 |
+ 081810.18 |
+ BXD31 |
+ M |
+ black |
+ 06/05/2010 |
+ 130 |
+ 08/17/2010 |
+ 73 |
+ 0.5 |
+ 1.88 |
+ 8.70 |
+ y |
+ |
+
+
+ | 27 |
+ 081810.40 |
+ BXD31 |
+ F |
+ black |
+ 06/05/2010 |
+ 130 |
+ 08/17/2010 |
+ 73 |
+ 1.1 |
+ 2.00 |
+ 7.00 |
+ y |
+ |
+
+
+ | 28 |
+ 081610.76 |
+ BXD32 |
+ F |
+ black |
+ 05/29/2010 |
+ 116 |
+ 08/18/2010 |
+ 81 |
+ 3.8 |
+ 2.05 |
+ 9.10 |
+ y |
+ need one more male |
+
+
+ | 29 |
+ 081810.26 |
+ BXD34 |
+ M |
+ black |
+ 06/02/2010 |
+ 63 |
+ 08/17/2010 |
+ 76 |
+ 1.3 |
+ 1.98 |
+ 8.20 |
+ y |
+ |
+
+
+ | 30 |
+ 081810.29 |
+ BXD34 |
+ M |
+ black |
+ 06/02/2010 |
+ 63 |
+ 08/17/2010 |
+ 76 |
+ 0.7 |
+ 1.93 |
+ 8.50 |
+ |
+ |
+
+
+ | 31 |
+ 081810.46 |
+ BXD34 |
+ F |
+ black |
+ 06/02/2010 |
+ 63 |
+ 08/18/2010 |
+ 77 |
+ 1.0 |
+ 2.00 |
+ 7.10 |
+ y |
+ |
+
+
+ | 32 |
+ 081810.36 |
+ BXD39 |
+ M |
+ gray |
+ 05/31/2010 |
+ 68 |
+ 08/17/2010 |
+ 78 |
+ 0.6 |
+ 1.94 |
+ 8.20 |
+ y |
+ |
+
+
+ | 33 |
+ 081810.55 |
+ BXD39 |
+ F |
+ gray |
+ 05/31/2010 |
+ 68 |
+ 08/18/2010 |
+ 79 |
+ 0.8 |
+ 1.96 |
+ 8.40 |
+ y |
+ |
+
+
+ | 34 |
+ 081910.03 |
+ BXD40 |
+ F |
+ gray |
+ 05/25/2010 |
+ 58 |
+ 08/18/2010 |
+ 85 |
+ 1.2 |
+ 2.00 |
+ 8.80 |
+ y |
+ |
+
+
+ | 35 |
+ 081910.06 |
+ BXD40 |
+ M |
+ gray |
+ 05/25/2010 |
+ 58 |
+ 08/18/2010 |
+ 85 |
+ 0.7 |
+ 1.90 |
+ 8.80 |
+ y |
+ |
+
+
+ | 36 |
+ 081810.31 |
+ BXD42 |
+ F |
+ black |
+ 05/23/2010 |
+ 64 |
+ 08/17/2010 |
+ 86 |
+ 0.9 |
+ 1.95 |
+ 8.30 |
+ y |
+ |
+
+
+ | 37 |
+ 081810.48 |
+ BXD42 |
+ M |
+ black |
+ 05/23/2010 |
+ 64 |
+ 08/18/2010 |
+ 87 |
+ 0.8 |
+ 1.93 |
+ 8.90 |
+ y |
+ |
+
+
+ | 38 |
+ 081710.47 |
+ BXD43 |
+ M |
+ black |
+ 05/28/2010 |
+ 44 |
+ 08/17/2010 |
+ 81 |
+ 1.2 |
+ 1.95 |
+ 8.10 |
+ y |
+ |
+
+
+ | 39 |
+ 081710.48 |
+ BXD43 |
+ F |
+ black |
+ 05/28/2010 |
+ 44 |
+ 08/17/2010 |
+ 81 |
+ 1.7 |
+ 1.96 |
+ 8.90 |
+ y |
+ |
+
+
+ | 40 |
+ 081710.49 |
+ BXD43 |
+ F |
+ black |
+ 05/28/2010 |
+ 44 |
+ 08/17/2010 |
+ 81 |
+ 1.2 |
+ 1.95 |
+ 8.50 |
+ |
+ |
+
+
+ | 41 |
+ 081710.23 |
+ BXD44 |
+ F |
+ brown |
+ 05/26/2010 |
+ 41 |
+ 08/17/2010 |
+ 83 |
+ 1.1 |
+ 1.96 |
+ 8.30 |
+ y |
+ |
+
+
+ | 42 |
+ 081710.24 |
+ BXD44 |
+ F |
+ brown |
+ 05/26/2010 |
+ 41 |
+ 08/17/2010 |
+ 83 |
+ 0.9 |
+ 1.92 |
+ 8.70 |
+ |
+ |
+
+
+ | 43 |
+ 081710.30 |
+ BXD44 |
+ M |
+ dilute brown DBA |
+ 05/26/2010 |
+ 41 |
+ 08/17/2010 |
+ 83 |
+ 1.3 |
+ 1.97 |
+ 8.20 |
+ y |
+ |
+
+
+ | 44 |
+ 081710.31 |
+ BXD44 |
+ M |
+ dilute brown DBA |
+ 05/26/2010 |
+ 41 |
+ 08/17/2010 |
+ 83 |
+ 1.6 |
+ 1.98 |
+ 8.30 |
+ |
+ |
+
+
+ | 45 |
+ 081710.32 |
+ BXD44 |
+ M |
+ dilute brown DBA |
+ 05/26/2010 |
+ 41 |
+ 08/17/2010 |
+ 83 |
+ 0.8 |
+ 1.95 |
+ 8.80 |
+ |
+ |
+
+
+ | 46 |
+ 081710.51 |
+ BXD45 |
+ M |
+ dilute brown DBA |
+ 06/01/2010 |
+ 39 |
+ 08/17/2010 |
+ 77 |
+ 1.2 |
+ 1.94 |
+ 7.80 |
+ y |
+ |
+
+
+ | 47 |
+ 081710.54 |
+ BXD45 |
+ F |
+ dilute brown DBA |
+ 06/01/2010 |
+ 39 |
+ 08/17/2010 |
+ 77 |
+ 1.0 |
+ 1.94 |
+ 7.30 |
+ y |
+ |
+
+
+ | 48 |
+ 081610.14 |
+ BXD48 |
+ F |
+ black |
+ 06/03/2010 |
+ 40 |
+ 08/18/2010 |
+ 76 |
+ 2.2 |
+ 2.01 |
+ 9.50 |
+ y |
+ |
+
+
+ | 49 |
+ 081610.17 |
+ BXD48 |
+ M |
+ black |
+ 06/03/2010 |
+ 40 |
+ 08/18/2010 |
+ 76 |
+ 3.3 |
+ 2.05 |
+ 8.20 |
+ y |
+ |
+
+
+ | 50 |
+ 081710.29 |
+ BXD49 |
+ M |
+ gray |
+ 05/25/2010 |
+ 49 |
+ 08/17/2010 |
+ 84 |
+ 1.6 |
+ 1.97 |
+ 7.10 |
+ y |
+ |
+
+
+ | 51 |
+ 081710.34 |
+ BXD49 |
+ F |
+ gray |
+ 05/25/2010 |
+ 24 |
+ 08/17/2010 |
+ 84 |
+ 1.0 |
+ 1.95 |
+ 8.50 |
+ y |
+ |
+
+
+ | 52 |
+ 081610.29 |
+ BXD50 |
+ F |
+ black |
+ 06/02/2010 |
+ 35 |
+ 08/18/2010 |
+ 77 |
+ 3.3 |
+ 2.05 |
+ 8.40 |
+ y |
+ |
+
+
+ | 53 |
+ 081610.32 |
+ BXD50 |
+ M |
+ black |
+ 06/02/2010 |
+ 35 |
+ 08/18/2010 |
+ 77 |
+ 9.1 |
+ 2.03 |
+ 8.40 |
+ y |
+ |
+
+
+ | 54 |
+ 081610.36 |
+ BXD56 |
+ M |
+ black |
+ 06/02/2010 |
+ 34 |
+ 08/18/2010 |
+ 77 |
+ 1.9 |
+ 2.02 |
+ 9.60 |
+ y |
+ |
+
+
+ | 55 |
+ 081610.77 |
+ BXD56 |
+ F |
+ black |
+ 05/26/2010 |
+ 34 |
+ 08/18/2010 |
+ 84 |
+ 3.4 |
+ 2.05 |
+ 8.20 |
+ y |
+ |
+
+
+ | 56 |
+ 081610.80 |
+ BXD56 |
+ F |
+ black |
+ 05/26/2010 |
+ 33 |
+ 08/18/2010 |
+ 84 |
+ 3.2 |
+ 2.05 |
+ 8.50 |
+ |
+ |
+
+
+ | 57 |
+ 081710.67 |
+ BXD60 |
+ M |
+ brown |
+ 06/08/2010 |
+ 43 |
+ 08/17/2010 |
+ 70 |
+ 0.9 |
+ 1.91 |
+ 8.40 |
+ y |
+ need one more female |
+
+
+ | 58 |
+ 081810.83 |
+ BXD62 |
+ M |
+ brown |
+ 05/27/2010 |
+ 41 |
+ 08/18/2010 |
+ 83 |
+ 0.5 |
+ 1.95 |
+ 8.10 |
+ y |
+ need one more female |
+
+
+ | 59 |
+ 081610.22 |
+ BXD63 |
+ M |
+ dilute brown DBA |
+ 06/02/2010 |
+ 31 |
+ 08/18/2010 |
+ 77 |
+ 6.9 |
+ 2.07 |
+ 8.50 |
+ y |
+ |
+
+
+ | 60 |
+ 081610.25 |
+ BXD63 |
+ F |
+ dilute brown DBA |
+ 06/02/2010 |
+ 31 |
+ 08/18/2010 |
+ 77 |
+ 2.2 |
+ 2.00 |
+ 8.70 |
+ y |
+ |
+
+
+ | 61 |
+ 081610.03 |
+ BXD65 |
+ M |
+ brown |
+ 05/26/2010 |
+ 32 |
+ 08/18/2010 |
+ 84 |
+ 11.2 |
+ 2.03 |
+ 8.70 |
+ y |
+ |
+
+
+ | 62 |
+ 081610.11 |
+ BXD65 |
+ F |
+ brown |
+ 05/26/2010 |
+ 32 |
+ 08/18/2010 |
+ 84 |
+ 3.1 |
+ 2.03 |
+ 9.10 |
+ y |
+ |
+
+
+ | 63 |
+ 081610.96 |
+ BXD68 |
+ F |
+ brown |
+ 06/03/2010 |
+ 33 |
+ 08/18/2010 |
+ 76 |
+ 4.0 |
+ 2.03 |
+ 8.20 |
+ y |
+ |
+
+
+ | 64 |
+ 081610.99 |
+ BXD68 |
+ M |
+ brown |
+ 06/03/2010 |
+ 33 |
+ 08/18/2010 |
+ 76 |
+ 3.4 |
+ 2.09 |
+ 7.80 |
+ y |
+ |
+
+
+ | 65 |
+ 081710.71 |
+ BXD69 |
+ M |
+ dilute brown DBA |
+ 05/29/2010 |
+ 41 |
+ 08/17/2010 |
+ 80 |
+ 1.3 |
+ 1.96 |
+ 7.90 |
+ y |
+ |
+
+
+ | 66 |
+ 081710.78 |
+ BXD69 |
+ F |
+ dilute brown DBA |
+ 06/09/2010 |
+ 42 |
+ 08/17/2010 |
+ 69 |
+ 0.8 |
+ 1.90 |
+ 8.50 |
+ y |
+ |
+
+
+ | 67 |
+ 081610.85 |
+ BXD70 |
+ M |
+ dilute brown DBA |
+ 06/03/2010 |
+ 36 |
+ 08/18/2010 |
+ 76 |
+ 4.6 |
+ 1.99 |
+ 9.40 |
+ y |
+ |
+
+
+ | 68 |
+ 081610.92 |
+ BXD70 |
+ F |
+ dilute brown DBA |
+ 06/03/2010 |
+ 36 |
+ 08/18/2010 |
+ 76 |
+ 3.1 |
+ 2.07 |
+ 8.50 |
+ y |
+ |
+
+
+ | 69 |
+ 081910.33 |
+ BXD71 |
+ F |
+ dilute brown DBA |
+ 06/03/2010 |
+ 35 |
+ 08/18/2010 |
+ 76 |
+ 2.8 |
+ 2.05 |
+ 8.00 |
+ y |
+ |
+
+
+ | 70 |
+ 081910.38 |
+ BXD71 |
+ M |
+ dilute brown DBA |
+ 06/03/2010 |
+ 35 |
+ 08/18/2010 |
+ 76 |
+ 4.6 |
+ 2.02 |
+ 8.30 |
+ y |
+ |
+
+
+ | 71 |
+ 081710.81 |
+ BXD73 |
+ F |
+ dilute brown DBA |
+ 05/26/2010 |
+ 44 |
+ 08/17/2010 |
+ 83 |
+ 0.8 |
+ 1.90 |
+ 8.60 |
+ y |
+ |
+
+
+ | 72 |
+ 081710.83 |
+ BXD73 |
+ M |
+ dilute brown DBA |
+ 05/26/2010 |
+ 41 |
+ 08/17/2010 |
+ 83 |
+ 0.8 |
+ 1.91 |
+ 8.40 |
+ y |
+ |
+
+
+ | 73 |
+ 081810.58 |
+ BXD75 |
+ M |
+ dilute brown DBA |
+ 06/03/2010 |
+ 39 |
+ 08/18/2010 |
+ 76 |
+ 0.8 |
+ 1.95 |
+ 8.70 |
+ y |
+ |
+
+
+ | 74 |
+ 081810.73 |
+ BXD75 |
+ F |
+ dilute brown DBA |
+ 06/03/2010 |
+ 39 |
+ 08/18/2010 |
+ 76 |
+ 0.7 |
+ 1.92 |
+ 9.30 |
+ y |
+ |
+
+
+ | 75 |
+ 081710.06 |
+ BXD79 |
+ F |
+ gray |
+ 05/23/2010 |
+ 24 |
+ 08/18/2010 |
+ 87 |
+ 2.9 |
+ 2.04 |
+ 8.60 |
+ y |
+ |
+
+
+ | 76 |
+ 081710.08 |
+ BXD79 |
+ M |
+ gray |
+ 05/23/2010 |
+ 24 |
+ 08/18/2010 |
+ 87 |
+ 2.1 |
+ 2.01 |
+ 9.40 |
+ y |
+ |
+
+
+ | 77 |
+ 081710.87 |
+ BXD80 |
+ F |
+ dilute brown DBA |
+ 06/05/2010 |
+ 33 |
+ 08/17/2010 |
+ 73 |
+ 1.2 |
+ 1.95 |
+ 8.20 |
+ y |
+ |
+
+
+ | 78 |
+ 081710.88 |
+ BXD80 |
+ M |
+ dilute brown DBA |
+ 06/05/2010 |
+ 33 |
+ 08/17/2010 |
+ 73 |
+ 0.8 |
+ 1.91 |
+ 8.00 |
+ y |
+ |
+
+
+ | 79 |
+ 081610.64 |
+ BXD83 |
+ M |
+ dilute brown DBA |
+ 05/29/2010 |
+ 32 |
+ 08/18/2010 |
+ 81 |
+ 2.5 |
+ 2.04 |
+ 8.50 |
+ y |
+ |
+
+
+ | 80 |
+ 081610.69 |
+ BXD83 |
+ F |
+ dilute brown DBA |
+ 05/29/2010 |
+ 32 |
+ 08/18/2010 |
+ 81 |
+ 2.7 |
+ 2.05 |
+ 8.20 |
+ y |
+ |
+
+
+ | 81 |
+ 081810.80 |
+ BXD84 |
+ F |
+ dilute brown DBA |
+ 06/03/2010 |
+ 31 |
+ 08/18/2010 |
+ 76 |
+ 0.9 |
+ 1.96 |
+ 8.80 |
+ y |
+ need one more male |
+
+
+ | 82 |
+ 081710.10 |
+ BXD85 |
+ F |
+ dilute brown DBA |
+ 06/05/2010 |
+ 40 |
+ 08/18/2010 |
+ 74 |
+ 3.7 |
+ 2.04 |
+ 7.90 |
+ y |
+ |
+
+
+ | 83 |
+ 081710.13 |
+ BXD85 |
+ M |
+ dilute brown DBA |
+ 06/05/2010 |
+ 40 |
+ 08/18/2010 |
+ 74 |
+ 2.9 |
+ 2.06 |
+ 8.40 |
+ y |
+ |
+
+
+ | 84 |
+ 081610.60 |
+ BXD87 |
+ M |
+ black |
+ 05/27/2010 |
+ 35 |
+ 08/18/2010 |
+ 83 |
+ 3.4 |
+ 2.04 |
+ 8.30 |
+ y |
+ |
+
+
+ | 85 |
+ 081610.63 |
+ BXD87 |
+ F |
+ black |
+ 05/27/2010 |
+ 35 |
+ 08/18/2010 |
+ 83 |
+ 3.1 |
+ 2.05 |
+ 8.40 |
+ y |
+ |
+
+
+ | 86 |
+ 081610.40 |
+ BXD89 |
+ M |
+ dilute brown DBA |
+ 05/28/2010 |
+ 36 |
+ 08/18/2010 |
+ 82 |
+ 2.6 |
+ 2.05 |
+ 8.50 |
+ y |
+ need one more female |
+
+
+ | 87 |
+ 081610.53 |
+ BXD90 |
+ F |
+ dilute brown DBA |
+ 05/28/2010 |
+ 39 |
+ 08/18/2010 |
+ 82 |
+ 9.1 |
+ 2.06 |
+ 8.60 |
+ y |
+ |
+
+
+ | 88 |
+ 081610.57 |
+ BXD90 |
+ M |
+ dilute brown DBA |
+ 05/28/2010 |
+ 39 |
+ 08/18/2010 |
+ 82 |
+ 2.1 |
+ 2.02 |
+ 9.40 |
+ y |
+ |
+
+
+ | 89 |
+ 081610.87 |
+ BXD92A |
+ F |
+ brown |
+ 05/24/2010 |
+ 42 |
+ 08/18/2010 |
+ 86 |
+ 2.6 |
+ 2.05 |
+ 8.60 |
+ y |
+ |
+
+
+ | 90 |
+ 081610.93 |
+ BXD92A |
+ M |
+ brown |
+ 05/21/2010 |
+ 42 |
+ 08/18/2010 |
+ 89 |
+ 8.5 |
+ 2.07 |
+ 8.80 |
+ y |
+ |
+
+
+ | 91 |
+ 081910.32 |
+ BXD95 |
+ M |
+ dilute brown DBA |
+ 06/03/2010 |
+ 25 |
+ 08/18/2010 |
+ 76 |
+ 2.7 |
+ 2.05 |
+ 9.20 |
+ y |
+ |
+
+
+ | 92 |
+ 081610.81 |
+ BXD95 |
+ F |
+ dilute brown DBA |
+ 06/03/2010 |
+ 25 |
+ 08/18/2010 |
+ 76 |
+ 3.2 |
+ 2.07 |
+ 8.70 |
+ y |
+ |
+
+
+ | 93 |
+ 081610.84 |
+ BXD95 |
+ M |
+ dilute brown DBA |
+ 06/03/2010 |
+ 25 |
+ 08/18/2010 |
+ 76 |
+ 13.3 |
+ 1.97 |
+ 7.70 |
+ |
+ |
+
+
+ | 94 |
+ 081610.47 |
+ BXD97 |
+ F |
+ brown |
+ 06/08/2010 |
+ 35 |
+ 08/18/2010 |
+ 71 |
+ 2.3 |
+ 2.00 |
+ 9.10 |
+ y |
+ need one more male |
+
+
+ | 95 |
+ 081610.06 |
+ BXD99 |
+ F |
+ dilute brown DBA |
+ 06/02/2010 |
+ 28 |
+ 08/18/2010 |
+ 77 |
+ 4.2 |
+ 2.01 |
+ 9.00 |
+ y |
+ |
+
+
+ | 96 |
+ 081610.20 |
+ BXD99 |
+ M |
+ dilute brown DBA |
+ 06/02/2010 |
+ 28 |
+ 08/18/2010 |
+ 77 |
+ 2.2 |
+ 2.00 |
+ 8.90 |
+ y |
+ |
+
+
+ | 97 |
+ 081810.63 |
+ BXD100 |
+ M |
+ black |
+ 05/27/2010 |
+ 30 |
+ 08/18/2010 |
+ 83 |
+ 0.7 |
+ 1.90 |
+ 8.60 |
+ y |
+ |
+
+
+ | 98 |
+ 081810.75 |
+ BXD100 |
+ F |
+ black |
+ 05/27/2010 |
+ 30 |
+ 08/18/2010 |
+ 83 |
+ 0.9 |
+ 1.95 |
+ 8.10 |
+ y |
+ |
+
+
+ | 99 |
+ 081710.14 |
+ BXD101 |
+ M |
+ gray |
+ 05/21/2010 |
+ 27 |
+ 08/18/2010 |
+ 89 |
+ 2.9 |
+ 2.05 |
+ 8.90 |
+ y |
+ |
+
+
+ | 100 |
+ 081710.19 |
+ BXD101 |
+ F |
+ gray |
+ 05/21/2010 |
+ 27 |
+ 08/18/2010 |
+ 89 |
+ 3.2 |
+ 2.06 |
+ 8.30 |
+ y |
+ |
+
+
+ | 101 |
+ 081710.41 |
+ BXD102 |
+ F |
+ brown |
+ 05/21/2010 |
+ 25 |
+ 08/17/2010 |
+ 88 |
+ 1.5 |
+ 1.95 |
+ 7.70 |
+ y |
+ |
+
+
+ | 102 |
+ 081710.45 |
+ BXD102 |
+ M |
+ brown |
+ 05/21/2010 |
+ 25 |
+ 08/17/2010 |
+ 88 |
+ 1.2 |
+ 1.97 |
+ 7.70 |
+ y |
+ |
+
+
+ | 103 |
+ 081710.58 |
+ BXD103 |
+ M |
+ dilute brown DBA |
+ 05/31/2010 |
+ 21 |
+ 08/17/2010 |
+ 78 |
+ 1.1 |
+ 1.94 |
+ 8.40 |
+ y |
+ |
+
+
+ | 104 |
+ 081710.62 |
+ BXD103 |
+ F |
+ dilute brown DBA |
+ 05/31/2010 |
+ 21 |
+ 08/17/2010 |
+ 78 |
+ 0.6 |
+ 1.91 |
+ 8.40 |
+ y |
+ |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_gutexl_0414/platform.rtf b/general/datasets/Uthsc_gutexl_0414/platform.rtf
new file mode 100644
index 0000000..79244c6
--- /dev/null
+++ b/general/datasets/Uthsc_gutexl_0414/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version]
diff --git a/general/datasets/Uthsc_gutexl_0414/processing.rtf b/general/datasets/Uthsc_gutexl_0414/processing.rtf
new file mode 100644
index 0000000..ebfa292
--- /dev/null
+++ b/general/datasets/Uthsc_gutexl_0414/processing.rtf
@@ -0,0 +1 @@
+This dataset includes Gene and Exon level RMA normalization.
diff --git a/general/datasets/Uthsc_gutexl_0414/specifics.rtf b/general/datasets/Uthsc_gutexl_0414/specifics.rtf
new file mode 100644
index 0000000..2400c03
--- /dev/null
+++ b/general/datasets/Uthsc_gutexl_0414/specifics.rtf
@@ -0,0 +1 @@
+Exon Level
diff --git a/general/datasets/Uthsc_gutexl_0414/tissue.rtf b/general/datasets/Uthsc_gutexl_0414/tissue.rtf
new file mode 100644
index 0000000..5653e30
--- /dev/null
+++ b/general/datasets/Uthsc_gutexl_0414/tissue.rtf
@@ -0,0 +1 @@
+Approximately two equal-sized segments of the small intestine were pooled per animal: one taken from the proximal jejunum and one from the distal ileum. We did generate a second data set (not in GeneNetwork) for different segments of the the GI tract from stomach to distal colon for C57BL/6J and DBA/2J parental strains. These additional data are available upon request from Drs. Dennis Black and Lu Lu.
diff --git a/general/datasets/Uthsc_gutgl_0414/cases.rtf b/general/datasets/Uthsc_gutgl_0414/cases.rtf
new file mode 100644
index 0000000..e3e9e26
--- /dev/null
+++ b/general/datasets/Uthsc_gutgl_0414/cases.rtf
@@ -0,0 +1,1696 @@
+
+
+
+
+
+
+
+
+ | Index |
+ CaseID |
+ Strain |
+ Sex |
+ Coat Color |
+ Date of Birth |
+ Generation |
+ Sacrifice Date |
+ Age |
+ RNA
+ conc.(ug/ul) |
+ RNA Purity
+ 260/280 |
+ RNA Integrity Number RIN |
+ Run Chip |
+ Notes |
+
+
+ | 1 |
+ 081910.14 |
+ B6D2F1 |
+ M |
+ black |
+ 06/10/2010 |
+ |
+ 08/18/2010 |
+ 69 |
+ 0.5 |
+ 2.00 |
+ 8.40 |
+ y |
+ |
+
+
+ | 2 |
+ 081910.17 |
+ B6D2F1 |
+ M |
+ black |
+ 06/10/2010 |
+ |
+ 08/18/2010 |
+ 69 |
+ 0.9 |
+ 2.00 |
+ 8.60 |
+ |
+ |
+
+
+ | 3 |
+ 081910.18 |
+ B6D2F1 |
+ F |
+ black |
+ 06/10/2010 |
+ |
+ 08/18/2010 |
+ 69 |
+ 0.3 |
+ 1.80 |
+ 9.30 |
+ y |
+ |
+
+
+ | 4 |
+ 081910.09 |
+ D2B6F1 |
+ F |
+ black |
+ 06/02/2010 |
+ |
+ 08/18/2010 |
+ 77 |
+ 0.7 |
+ 2.00 |
+ 9.00 |
+ y |
+ |
+
+
+ | 5 |
+ 081910.23 |
+ D2B6F1 |
+ M |
+ black |
+ 06/02/2010 |
+ |
+ 08/18/2010 |
+ 77 |
+ 10.2 |
+ 2.02 |
+ 8.50 |
+ y |
+ |
+
+
+ | 6 |
+ 081910.12 |
+ C57BL/6J |
+ F |
+ black |
+ 06/02/2010 |
+ |
+ 08/18/2010 |
+ 77 |
+ 0.6 |
+ 1.90 |
+ n/a |
+ y |
+ |
+
+
+ | 7 |
+ 081910.25 |
+ C57BL/6J |
+ M |
+ black |
+ 06/02/2010 |
+ |
+ 08/18/2010 |
+ 77 |
+ 3.4 |
+ 2.03 |
+ |
+ y |
+ |
+
+
+ | 8 |
+ 081910.39 |
+ C57BL/6J |
+ F |
+ black |
+ 06/02/2010 |
+ |
+ 08/18/2010 |
+ 77 |
+ 2.30 |
+ 1.99 |
+ 8.50 |
+ y |
+ |
+
+
+ | 9 |
+ 081910.41 |
+ C57BL/6J |
+ M |
+ black |
+ 06/18/2010 |
+ |
+ 08/18/2010 |
+ 61 |
+ 2.20 |
+ 2.02 |
+ 8.60 |
+ y |
+ |
+
+
+ | 10 |
+ 081910.29 |
+ DBA/2J |
+ F |
+ dilute brown DBA |
+ 06/02/2010 |
+ |
+ 08/18/2010 |
+ 77 |
+ 2.9 |
+ 2.03 |
+ 8.50 |
+ y |
+ need one more female |
+
+
+ | 11 |
+ 081910.31 |
+ DBA/2J |
+ M |
+ dilute brown DBA |
+ 06/11/2010 |
+ |
+ 08/18/2010 |
+ 68 |
+ 8.6 |
+ 2.06 |
+ 8.00 |
+ y |
+ |
+
+
+ | 12 |
+ 081910.43 |
+ DBA/2J |
+ M |
+ dilute brown DBA |
+ 05/06/2010 |
+ |
+ 08/18/2010 |
+ 104 |
+ 2.30 |
+ 2.01 |
+ 9.30 |
+ y |
+ |
+
+
+ | 13 |
+ 081810.08 |
+ BXD1 |
+ M |
+ dilute brown DBA |
+ 05/24/2010 |
+ 142 |
+ 08/17/2010 |
+ 85 |
+ 0.6 |
+ 1.92 |
+ 8.50 |
+ y |
+ |
+
+
+ | 14 |
+ 081810.13 |
+ BXD1 |
+ F |
+ dilute brown DBA |
+ 06/07/2010 |
+ 139 |
+ 08/17/2010 |
+ 71 |
+ 0.7 |
+ |
+ 9.00 |
+ y |
+ |
+
+
+ | 15 |
+ 081710.91 |
+ BXD11 |
+ M |
+ black |
+ 06/02/2010 |
+ 137 |
+ 08/17/2010 |
+ 76 |
+ 0.7 |
+ 1.93 |
+ 8.20 |
+ y |
+ |
+
+
+ | 16 |
+ 081710.97 |
+ BXD11 |
+ F |
+ black |
+ 05/22/2010 |
+ 136 |
+ 08/17/2010 |
+ 87 |
+ 1.0 |
+ 1.95 |
+ 8.90 |
+ y |
+ |
+
+
+ | 17 |
+ 081810.23 |
+ BXD12 |
+ M |
+ gray |
+ 06/01/2010 |
+ 122 |
+ 08/17/2010 |
+ 77 |
+ 0.9 |
+ 2.00 |
+ 8.00 |
+ y |
+ |
+
+
+ | 18 |
+ 081810.44 |
+ BXD12 |
+ F |
+ gray |
+ 06/01/2010 |
+ 122 |
+ 08/18/2010 |
+ 78 |
+ 0.8 |
+ 1.93 |
+ 8.30 |
+ y |
+ |
+
+
+ | 19 |
+ 081810.33 |
+ BXD14 |
+ F |
+ black |
+ 05/29/2010 |
+ 142 |
+ 08/17/2010 |
+ 80 |
+ 1.2 |
+ 1.97 |
+ 8.10 |
+ y |
+ |
+
+
+ | 20 |
+ 081810.52 |
+ BXD14 |
+ M |
+ black |
+ 05/29/2010 |
+ 142 |
+ 08/18/2010 |
+ 81 |
+ 0.4 |
+ 1.90 |
+ 9.00 |
+ y |
+ |
+
+
+ | 21 |
+ 081810.19 |
+ BXD24 |
+ F |
+ brown |
+ 05/24/2010 |
+ 90 |
+ 08/17/2010 |
+ 85 |
+ 0.3 |
+ 1.90 |
+ 9.10 |
+ y |
+ This strain comes from UTHSC colony since 2008. So they are probably blind. |
+
+
+ | 22 |
+ 081810.42 |
+ BXD24 |
+ M |
+ brown |
+ 05/24/2010 |
+ 90 |
+ 08/17/2010 |
+ 85 |
+ 0.7 |
+ 2.00 |
+ 8.50 |
+ y |
+ This strain comes from UTHSC colony since 2008. So they are probably blind. |
+
+
+ | 23 |
+ 081710.99 |
+ BXD27 |
+ M |
+ dilute brown DBA |
+ 06/05/2010 |
+ 162 |
+ 08/17/2010 |
+ 73 |
+ 1.3 |
+ 1.95 |
+ 8.40 |
+ y |
+ need one more female |
+
+
+ | 24 |
+ 081810.04 |
+ BXD29 |
+ M |
+ gray |
+ 06/07/2010 |
+ 25 |
+ 08/17/2010 |
+ 71 |
+ 0.5 |
+ 1.91 |
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+ |
+
+
+ | 25 |
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+ |
+
+
+ | 26 |
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+ |
+
+
+ | 27 |
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+ y |
+ |
+
+
+ | 28 |
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+ y |
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+
+
+ | 29 |
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+ |
+
+
+ | 30 |
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+ |
+ |
+
+
+ | 31 |
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+ 1.0 |
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+ y |
+ |
+
+
+ | 32 |
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+ 0.6 |
+ 1.94 |
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+ y |
+ |
+
+
+ | 33 |
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+ y |
+ |
+
+
+ | 34 |
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+ 1.2 |
+ 2.00 |
+ 8.80 |
+ y |
+ |
+
+
+ | 35 |
+ 081910.06 |
+ BXD40 |
+ M |
+ gray |
+ 05/25/2010 |
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+ 08/18/2010 |
+ 85 |
+ 0.7 |
+ 1.90 |
+ 8.80 |
+ y |
+ |
+
+
+ | 36 |
+ 081810.31 |
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+ black |
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+ 0.9 |
+ 1.95 |
+ 8.30 |
+ y |
+ |
+
+
+ | 37 |
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+ 1.93 |
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+ y |
+ |
+
+
+ | 38 |
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+ 1.2 |
+ 1.95 |
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+ y |
+ |
+
+
+ | 39 |
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+ y |
+ |
+
+
+ | 40 |
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+ 1.95 |
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+ |
+ |
+
+
+ | 41 |
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+ |
+
+
+ | 42 |
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+ |
+ |
+
+
+ | 43 |
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+ 8.20 |
+ y |
+ |
+
+
+ | 44 |
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+ 83 |
+ 1.6 |
+ 1.98 |
+ 8.30 |
+ |
+ |
+
+
+ | 45 |
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+ 83 |
+ 0.8 |
+ 1.95 |
+ 8.80 |
+ |
+ |
+
+
+ | 46 |
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+ BXD45 |
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+ 77 |
+ 1.2 |
+ 1.94 |
+ 7.80 |
+ y |
+ |
+
+
+ | 47 |
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+ 77 |
+ 1.0 |
+ 1.94 |
+ 7.30 |
+ y |
+ |
+
+
+ | 48 |
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+ 2.2 |
+ 2.01 |
+ 9.50 |
+ y |
+ |
+
+
+ | 49 |
+ 081610.17 |
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+ black |
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+ 3.3 |
+ 2.05 |
+ 8.20 |
+ y |
+ |
+
+
+ | 50 |
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+ gray |
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+ 1.6 |
+ 1.97 |
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+ y |
+ |
+
+
+ | 51 |
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+ 1.0 |
+ 1.95 |
+ 8.50 |
+ y |
+ |
+
+
+ | 52 |
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+ 77 |
+ 3.3 |
+ 2.05 |
+ 8.40 |
+ y |
+ |
+
+
+ | 53 |
+ 081610.32 |
+ BXD50 |
+ M |
+ black |
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+ 77 |
+ 9.1 |
+ 2.03 |
+ 8.40 |
+ y |
+ |
+
+
+ | 54 |
+ 081610.36 |
+ BXD56 |
+ M |
+ black |
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+ 08/18/2010 |
+ 77 |
+ 1.9 |
+ 2.02 |
+ 9.60 |
+ y |
+ |
+
+
+ | 55 |
+ 081610.77 |
+ BXD56 |
+ F |
+ black |
+ 05/26/2010 |
+ 34 |
+ 08/18/2010 |
+ 84 |
+ 3.4 |
+ 2.05 |
+ 8.20 |
+ y |
+ |
+
+
+ | 56 |
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+ BXD56 |
+ F |
+ black |
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+ 33 |
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+ 84 |
+ 3.2 |
+ 2.05 |
+ 8.50 |
+ |
+ |
+
+
+ | 57 |
+ 081710.67 |
+ BXD60 |
+ M |
+ brown |
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+ 43 |
+ 08/17/2010 |
+ 70 |
+ 0.9 |
+ 1.91 |
+ 8.40 |
+ y |
+ need one more female |
+
+
+ | 58 |
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+ BXD62 |
+ M |
+ brown |
+ 05/27/2010 |
+ 41 |
+ 08/18/2010 |
+ 83 |
+ 0.5 |
+ 1.95 |
+ 8.10 |
+ y |
+ need one more female |
+
+
+ | 59 |
+ 081610.22 |
+ BXD63 |
+ M |
+ dilute brown DBA |
+ 06/02/2010 |
+ 31 |
+ 08/18/2010 |
+ 77 |
+ 6.9 |
+ 2.07 |
+ 8.50 |
+ y |
+ |
+
+
+ | 60 |
+ 081610.25 |
+ BXD63 |
+ F |
+ dilute brown DBA |
+ 06/02/2010 |
+ 31 |
+ 08/18/2010 |
+ 77 |
+ 2.2 |
+ 2.00 |
+ 8.70 |
+ y |
+ |
+
+
+ | 61 |
+ 081610.03 |
+ BXD65 |
+ M |
+ brown |
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+ 32 |
+ 08/18/2010 |
+ 84 |
+ 11.2 |
+ 2.03 |
+ 8.70 |
+ y |
+ |
+
+
+ | 62 |
+ 081610.11 |
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+ F |
+ brown |
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+ 32 |
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+ 84 |
+ 3.1 |
+ 2.03 |
+ 9.10 |
+ y |
+ |
+
+
+ | 63 |
+ 081610.96 |
+ BXD68 |
+ F |
+ brown |
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+ 33 |
+ 08/18/2010 |
+ 76 |
+ 4.0 |
+ 2.03 |
+ 8.20 |
+ y |
+ |
+
+
+ | 64 |
+ 081610.99 |
+ BXD68 |
+ M |
+ brown |
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+ 33 |
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+ 76 |
+ 3.4 |
+ 2.09 |
+ 7.80 |
+ y |
+ |
+
+
+ | 65 |
+ 081710.71 |
+ BXD69 |
+ M |
+ dilute brown DBA |
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+ 41 |
+ 08/17/2010 |
+ 80 |
+ 1.3 |
+ 1.96 |
+ 7.90 |
+ y |
+ |
+
+
+ | 66 |
+ 081710.78 |
+ BXD69 |
+ F |
+ dilute brown DBA |
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+ 42 |
+ 08/17/2010 |
+ 69 |
+ 0.8 |
+ 1.90 |
+ 8.50 |
+ y |
+ |
+
+
+ | 67 |
+ 081610.85 |
+ BXD70 |
+ M |
+ dilute brown DBA |
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+ 36 |
+ 08/18/2010 |
+ 76 |
+ 4.6 |
+ 1.99 |
+ 9.40 |
+ y |
+ |
+
+
+ | 68 |
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+ BXD70 |
+ F |
+ dilute brown DBA |
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+ 36 |
+ 08/18/2010 |
+ 76 |
+ 3.1 |
+ 2.07 |
+ 8.50 |
+ y |
+ |
+
+
+ | 69 |
+ 081910.33 |
+ BXD71 |
+ F |
+ dilute brown DBA |
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+ 35 |
+ 08/18/2010 |
+ 76 |
+ 2.8 |
+ 2.05 |
+ 8.00 |
+ y |
+ |
+
+
+ | 70 |
+ 081910.38 |
+ BXD71 |
+ M |
+ dilute brown DBA |
+ 06/03/2010 |
+ 35 |
+ 08/18/2010 |
+ 76 |
+ 4.6 |
+ 2.02 |
+ 8.30 |
+ y |
+ |
+
+
+ | 71 |
+ 081710.81 |
+ BXD73 |
+ F |
+ dilute brown DBA |
+ 05/26/2010 |
+ 44 |
+ 08/17/2010 |
+ 83 |
+ 0.8 |
+ 1.90 |
+ 8.60 |
+ y |
+ |
+
+
+ | 72 |
+ 081710.83 |
+ BXD73 |
+ M |
+ dilute brown DBA |
+ 05/26/2010 |
+ 41 |
+ 08/17/2010 |
+ 83 |
+ 0.8 |
+ 1.91 |
+ 8.40 |
+ y |
+ |
+
+
+ | 73 |
+ 081810.58 |
+ BXD75 |
+ M |
+ dilute brown DBA |
+ 06/03/2010 |
+ 39 |
+ 08/18/2010 |
+ 76 |
+ 0.8 |
+ 1.95 |
+ 8.70 |
+ y |
+ |
+
+
+ | 74 |
+ 081810.73 |
+ BXD75 |
+ F |
+ dilute brown DBA |
+ 06/03/2010 |
+ 39 |
+ 08/18/2010 |
+ 76 |
+ 0.7 |
+ 1.92 |
+ 9.30 |
+ y |
+ |
+
+
+ | 75 |
+ 081710.06 |
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+ F |
+ gray |
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+ 87 |
+ 2.9 |
+ 2.04 |
+ 8.60 |
+ y |
+ |
+
+
+ | 76 |
+ 081710.08 |
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+ M |
+ gray |
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+ 87 |
+ 2.1 |
+ 2.01 |
+ 9.40 |
+ y |
+ |
+
+
+ | 77 |
+ 081710.87 |
+ BXD80 |
+ F |
+ dilute brown DBA |
+ 06/05/2010 |
+ 33 |
+ 08/17/2010 |
+ 73 |
+ 1.2 |
+ 1.95 |
+ 8.20 |
+ y |
+ |
+
+
+ | 78 |
+ 081710.88 |
+ BXD80 |
+ M |
+ dilute brown DBA |
+ 06/05/2010 |
+ 33 |
+ 08/17/2010 |
+ 73 |
+ 0.8 |
+ 1.91 |
+ 8.00 |
+ y |
+ |
+
+
+ | 79 |
+ 081610.64 |
+ BXD83 |
+ M |
+ dilute brown DBA |
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+ 32 |
+ 08/18/2010 |
+ 81 |
+ 2.5 |
+ 2.04 |
+ 8.50 |
+ y |
+ |
+
+
+ | 80 |
+ 081610.69 |
+ BXD83 |
+ F |
+ dilute brown DBA |
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+ 32 |
+ 08/18/2010 |
+ 81 |
+ 2.7 |
+ 2.05 |
+ 8.20 |
+ y |
+ |
+
+
+ | 81 |
+ 081810.80 |
+ BXD84 |
+ F |
+ dilute brown DBA |
+ 06/03/2010 |
+ 31 |
+ 08/18/2010 |
+ 76 |
+ 0.9 |
+ 1.96 |
+ 8.80 |
+ y |
+ need one more male |
+
+
+ | 82 |
+ 081710.10 |
+ BXD85 |
+ F |
+ dilute brown DBA |
+ 06/05/2010 |
+ 40 |
+ 08/18/2010 |
+ 74 |
+ 3.7 |
+ 2.04 |
+ 7.90 |
+ y |
+ |
+
+
+ | 83 |
+ 081710.13 |
+ BXD85 |
+ M |
+ dilute brown DBA |
+ 06/05/2010 |
+ 40 |
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+ 74 |
+ 2.9 |
+ 2.06 |
+ 8.40 |
+ y |
+ |
+
+
+ | 84 |
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+ BXD87 |
+ M |
+ black |
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+ 83 |
+ 3.4 |
+ 2.04 |
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+ y |
+ |
+
+
+ | 85 |
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+ black |
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+ 83 |
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+ 2.05 |
+ 8.40 |
+ y |
+ |
+
+
+ | 86 |
+ 081610.40 |
+ BXD89 |
+ M |
+ dilute brown DBA |
+ 05/28/2010 |
+ 36 |
+ 08/18/2010 |
+ 82 |
+ 2.6 |
+ 2.05 |
+ 8.50 |
+ y |
+ need one more female |
+
+
+ | 87 |
+ 081610.53 |
+ BXD90 |
+ F |
+ dilute brown DBA |
+ 05/28/2010 |
+ 39 |
+ 08/18/2010 |
+ 82 |
+ 9.1 |
+ 2.06 |
+ 8.60 |
+ y |
+ |
+
+
+ | 88 |
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+ BXD90 |
+ M |
+ dilute brown DBA |
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+ 39 |
+ 08/18/2010 |
+ 82 |
+ 2.1 |
+ 2.02 |
+ 9.40 |
+ y |
+ |
+
+
+ | 89 |
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+ BXD92A |
+ F |
+ brown |
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+ 42 |
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+ 86 |
+ 2.6 |
+ 2.05 |
+ 8.60 |
+ y |
+ |
+
+
+ | 90 |
+ 081610.93 |
+ BXD92A |
+ M |
+ brown |
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+ 42 |
+ 08/18/2010 |
+ 89 |
+ 8.5 |
+ 2.07 |
+ 8.80 |
+ y |
+ |
+
+
+ | 91 |
+ 081910.32 |
+ BXD95 |
+ M |
+ dilute brown DBA |
+ 06/03/2010 |
+ 25 |
+ 08/18/2010 |
+ 76 |
+ 2.7 |
+ 2.05 |
+ 9.20 |
+ y |
+ |
+
+
+ | 92 |
+ 081610.81 |
+ BXD95 |
+ F |
+ dilute brown DBA |
+ 06/03/2010 |
+ 25 |
+ 08/18/2010 |
+ 76 |
+ 3.2 |
+ 2.07 |
+ 8.70 |
+ y |
+ |
+
+
+ | 93 |
+ 081610.84 |
+ BXD95 |
+ M |
+ dilute brown DBA |
+ 06/03/2010 |
+ 25 |
+ 08/18/2010 |
+ 76 |
+ 13.3 |
+ 1.97 |
+ 7.70 |
+ |
+ |
+
+
+ | 94 |
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+ BXD97 |
+ F |
+ brown |
+ 06/08/2010 |
+ 35 |
+ 08/18/2010 |
+ 71 |
+ 2.3 |
+ 2.00 |
+ 9.10 |
+ y |
+ need one more male |
+
+
+ | 95 |
+ 081610.06 |
+ BXD99 |
+ F |
+ dilute brown DBA |
+ 06/02/2010 |
+ 28 |
+ 08/18/2010 |
+ 77 |
+ 4.2 |
+ 2.01 |
+ 9.00 |
+ y |
+ |
+
+
+ | 96 |
+ 081610.20 |
+ BXD99 |
+ M |
+ dilute brown DBA |
+ 06/02/2010 |
+ 28 |
+ 08/18/2010 |
+ 77 |
+ 2.2 |
+ 2.00 |
+ 8.90 |
+ y |
+ |
+
+
+ | 97 |
+ 081810.63 |
+ BXD100 |
+ M |
+ black |
+ 05/27/2010 |
+ 30 |
+ 08/18/2010 |
+ 83 |
+ 0.7 |
+ 1.90 |
+ 8.60 |
+ y |
+ |
+
+
+ | 98 |
+ 081810.75 |
+ BXD100 |
+ F |
+ black |
+ 05/27/2010 |
+ 30 |
+ 08/18/2010 |
+ 83 |
+ 0.9 |
+ 1.95 |
+ 8.10 |
+ y |
+ |
+
+
+ | 99 |
+ 081710.14 |
+ BXD101 |
+ M |
+ gray |
+ 05/21/2010 |
+ 27 |
+ 08/18/2010 |
+ 89 |
+ 2.9 |
+ 2.05 |
+ 8.90 |
+ y |
+ |
+
+
+ | 100 |
+ 081710.19 |
+ BXD101 |
+ F |
+ gray |
+ 05/21/2010 |
+ 27 |
+ 08/18/2010 |
+ 89 |
+ 3.2 |
+ 2.06 |
+ 8.30 |
+ y |
+ |
+
+
+ | 101 |
+ 081710.41 |
+ BXD102 |
+ F |
+ brown |
+ 05/21/2010 |
+ 25 |
+ 08/17/2010 |
+ 88 |
+ 1.5 |
+ 1.95 |
+ 7.70 |
+ y |
+ |
+
+
+ | 102 |
+ 081710.45 |
+ BXD102 |
+ M |
+ brown |
+ 05/21/2010 |
+ 25 |
+ 08/17/2010 |
+ 88 |
+ 1.2 |
+ 1.97 |
+ 7.70 |
+ y |
+ |
+
+
+ | 103 |
+ 081710.58 |
+ BXD103 |
+ M |
+ dilute brown DBA |
+ 05/31/2010 |
+ 21 |
+ 08/17/2010 |
+ 78 |
+ 1.1 |
+ 1.94 |
+ 8.40 |
+ y |
+ |
+
+
+ | 104 |
+ 081710.62 |
+ BXD103 |
+ F |
+ dilute brown DBA |
+ 05/31/2010 |
+ 21 |
+ 08/17/2010 |
+ 78 |
+ 0.6 |
+ 1.91 |
+ 8.40 |
+ y |
+ |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_gutgl_0414/platform.rtf b/general/datasets/Uthsc_gutgl_0414/platform.rtf
new file mode 100644
index 0000000..79244c6
--- /dev/null
+++ b/general/datasets/Uthsc_gutgl_0414/platform.rtf
@@ -0,0 +1 @@
+[MoGene-1_0-st] Affymetrix Mouse Gene 1.0 ST Array [transcript (gene) version]
diff --git a/general/datasets/Uthsc_gutgl_0414/processing.rtf b/general/datasets/Uthsc_gutgl_0414/processing.rtf
new file mode 100644
index 0000000..ebfa292
--- /dev/null
+++ b/general/datasets/Uthsc_gutgl_0414/processing.rtf
@@ -0,0 +1 @@
+This dataset includes Gene and Exon level RMA normalization.
diff --git a/general/datasets/Uthsc_gutgl_0414/specifics.rtf b/general/datasets/Uthsc_gutgl_0414/specifics.rtf
new file mode 100644
index 0000000..d877bcf
--- /dev/null
+++ b/general/datasets/Uthsc_gutgl_0414/specifics.rtf
@@ -0,0 +1 @@
+Gene Level
diff --git a/general/datasets/Uthsc_gutgl_0414/tissue.rtf b/general/datasets/Uthsc_gutgl_0414/tissue.rtf
new file mode 100644
index 0000000..5653e30
--- /dev/null
+++ b/general/datasets/Uthsc_gutgl_0414/tissue.rtf
@@ -0,0 +1 @@
+Approximately two equal-sized segments of the small intestine were pooled per animal: one taken from the proximal jejunum and one from the distal ileum. We did generate a second data set (not in GeneNetwork) for different segments of the the GI tract from stomach to distal colon for C57BL/6J and DBA/2J parental strains. These additional data are available upon request from Drs. Dennis Black and Lu Lu.
diff --git a/general/datasets/Uthsc_huislets_mar17/platform.rtf b/general/datasets/Uthsc_huislets_mar17/platform.rtf
new file mode 100644
index 0000000..10c6122
--- /dev/null
+++ b/general/datasets/Uthsc_huislets_mar17/platform.rtf
@@ -0,0 +1 @@
+Affymetrix Human Gene 2.0 ST Array
diff --git a/general/datasets/Uthsc_huislets_mar17/summary.rtf b/general/datasets/Uthsc_huislets_mar17/summary.rtf
new file mode 100644
index 0000000..e59b6f7
--- /dev/null
+++ b/general/datasets/Uthsc_huislets_mar17/summary.rtf
@@ -0,0 +1 @@
+Info file in progress...
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0216/notes.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0216/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0216/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0216/summary.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0216/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0216/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0217/notes.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0217/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0217/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0217/specifics.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0217/specifics.rtf
new file mode 100644
index 0000000..340fc0e
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0217/specifics.rtf
@@ -0,0 +1,392 @@
+NOE = No restraint stress and given an ethanol injection prior to sacrifice.
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Condition |
+ Strain |
+ Sex |
+ Age |
+
+
+ | 1 |
+ 4060001078_D |
+ NOE |
+ BXD34 |
+ F |
+ 75 |
+
+
+ | 2 |
+ 4060001088_A |
+ NOE |
+ BXD43 |
+ F |
+ 67 |
+
+
+ | 3 |
+ 4207851040_C |
+ NOE |
+ BXD43 |
+ F |
+ 65 |
+
+
+ | 4 |
+ 4207851040_D |
+ NOE |
+ BXD45 |
+ F |
+ 71 |
+
+
+ | 5 |
+ 4207851041_C |
+ NOE |
+ BXD45 |
+ M |
+ 68 |
+
+
+ | 6 |
+ 4068846016_D |
+ NOE |
+ BXD51 |
+ F |
+ 73 |
+
+
+ | 7 |
+ 4207851035_D |
+ NOE |
+ BXD51 |
+ M |
+ 85 |
+
+
+ | 8 |
+ 4060001003_C |
+ NOE |
+ BXD55 |
+ F |
+ 79 |
+
+
+ | 9 |
+ 4068846016_C |
+ NOE |
+ BXD55 |
+ M |
+ 68 |
+
+
+ | 10 |
+ 4060001071_A |
+ NOE |
+ BXD60 |
+ F |
+ 76 |
+
+
+ | 11 |
+ 4068846016_A |
+ NOE |
+ BXD60 |
+ M |
+ 67 |
+
+
+ | 12 |
+ 4060001003_D |
+ NOE |
+ BXD61 |
+ M |
+ 67 |
+
+
+ | 13 |
+ 4207851041_A |
+ NOE |
+ BXD61 |
+ F |
+ 70 |
+
+
+ | 14 |
+ 4060001075_F |
+ NOE |
+ BXD62 |
+ M |
+ 68 |
+
+
+ | 15 |
+ 4207851041_B |
+ NOE |
+ BXD62 |
+ F |
+ 67 |
+
+
+ | 16 |
+ 4207851035_A |
+ NOE |
+ BXD66 |
+ F |
+ 73 |
+
+
+ | 17 |
+ 4256265071_C |
+ NOE |
+ BXD66 |
+ M |
+ 63 |
+
+
+ | 18 |
+ 4207851035_B |
+ NOE |
+ BXD68 |
+ M |
+ 66 |
+
+
+ | 19 |
+ 4256265026_E |
+ NOE |
+ BXD68 |
+ F |
+ 67 |
+
+
+ | 20 |
+ 4060001010_F |
+ NOE |
+ BXD70 |
+ M |
+ 87 |
+
+
+ | 21 |
+ 4207851045_B |
+ NOE |
+ BXD70 |
+ F |
+ 69 |
+
+
+ | 22 |
+ 4256265057_A |
+ NOE |
+ BXD71 |
+ F |
+ 76 |
+
+
+ | 23 |
+ 4256265087_C |
+ NOE |
+ BXD71 |
+ M |
+ 75 |
+
+
+ | 24 |
+ 4256265042_B |
+ NOE |
+ BXD73 |
+ F |
+ 66 |
+
+
+ | 25 |
+ 4060001010_E |
+ NOE |
+ BXD75 |
+ F |
+ 70 |
+
+
+ | 26 |
+ 4256265042_C |
+ NOE |
+ BXD75 |
+ M |
+ 69 |
+
+
+ | 27 |
+ 4060001083_A |
+ NOE |
+ BXD83 |
+ M |
+ 69 |
+
+
+ | 28 |
+ 4256265071_D |
+ NOE |
+ BXD83 |
+ F |
+ 80 |
+
+
+ | 29 |
+ 4256265045_C |
+ NOE |
+ BXD84 |
+ F |
+ 68 |
+
+
+ | 30 |
+ 4207851058_A |
+ NOE |
+ BXD87 |
+ F |
+ 63 |
+
+
+ | 31 |
+ 4256265080_C |
+ NOE |
+ BXD87 |
+ M |
+ 65 |
+
+
+ | 32 |
+ 4207851058_B |
+ NOE |
+ BXD89 |
+ M |
+ 68 |
+
+
+ | 33 |
+ 4256265024_A |
+ NOE |
+ BXD89 |
+ F |
+ 71 |
+
+
+ | 34 |
+ 4256265024_B |
+ NOE |
+ BXD90 |
+ F |
+ 68 |
+
+
+ | 35 |
+ 4256265052_A |
+ NOE |
+ BXD90 |
+ M |
+ 74 |
+
+
+ | 36 |
+ 4256265023_A |
+ NOE |
+ BXD96 |
+ M |
+ 68 |
+
+
+ | 37 |
+ 4256265023_F |
+ NOE |
+ BXD96 |
+ F |
+ 68 |
+
+
+ | 38 |
+ 4256265044_A |
+ NOE |
+ BXD96 |
+ M |
+ 68 |
+
+
+ | 39 |
+ 4068846017_B |
+ NOE |
+ BXD97 |
+ M |
+ 67 |
+
+
+ | 40 |
+ 4068846017_A |
+ NOE |
+ BXD98 |
+ F |
+ 74 |
+
+
+ | 41 |
+ 4207851052_F |
+ NOE |
+ BXD98 |
+ M |
+ 71 |
+
+
+ | 42 |
+ 4068846021_F |
+ NOE |
+ BXD99 |
+ M |
+ 70 |
+
+
+ | 43 |
+ 4060001088_E |
+ NOE |
+ BXD100 |
+ F |
+ 61 |
+
+
+ | 44 |
+ 4060001088_D |
+ NOE |
+ BXD101 |
+ M |
+ 71 |
+
+
+ | 45 |
+ 4060001030_D |
+ NOE |
+ DBA/2J |
+ F |
+ 79 |
+
+
+ | 46 |
+ 4256265069_F |
+ NOE |
+ DBA/2J |
+ F |
+ 79 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0217/summary.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0217/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_noeb_0217/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_nosb_0217/notes.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_nosb_0217/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_nosb_0217/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_nosb_0217/specifics.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_nosb_0217/specifics.rtf
new file mode 100644
index 0000000..e60e427
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_nosb_0217/specifics.rtf
@@ -0,0 +1,408 @@
+NOS = No restraint stress and given only saline injections prior to sacrifice.
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Condition |
+ Strain |
+ Sex |
+ Age |
+
+
+ | 1 |
+ 4207851040_B |
+ NOS |
+ BXD34 |
+ M |
+ 67 |
+
+
+ | 2 |
+ 4207851045_E |
+ NOS |
+ BXD43 |
+ F |
+ 75 |
+
+
+ | 3 |
+ 4256265009_D |
+ NOS |
+ BXD43 |
+ M |
+ 64 |
+
+
+ | 4 |
+ 4060001010_A |
+ NOS |
+ BXD45 |
+ F |
+ 81 |
+
+
+ | 5 |
+ 4068846016_E |
+ NOS |
+ BXD45 |
+ M |
+ 65 |
+
+
+ | 6 |
+ 4060001011_A |
+ NOS |
+ BXD51 |
+ F |
+ 85 |
+
+
+ | 7 |
+ 4060001082_B |
+ NOS |
+ BXD51 |
+ M |
+ 75 |
+
+
+ | 8 |
+ 4060001082_F |
+ NOS |
+ BXD55 |
+ F |
+ 62 |
+
+
+ | 9 |
+ 4256265070_B |
+ NOS |
+ BXD55 |
+ M |
+ 76 |
+
+
+ | 10 |
+ 4207851041_F |
+ NOS |
+ BXD60 |
+ F |
+ 76 |
+
+
+ | 11 |
+ 4256265071_B |
+ NOS |
+ BXD60 |
+ M |
+ 77 |
+
+
+ | 12 |
+ 4060001069_A |
+ NOS |
+ BXD61 |
+ F |
+ 78 |
+
+
+ | 13 |
+ 4207851051_C |
+ NOS |
+ BXD61 |
+ M |
+ 78 |
+
+
+ | 14 |
+ 4207851053_D |
+ NOS |
+ BXD62 |
+ F |
+ 67 |
+
+
+ | 15 |
+ 4256265043_A |
+ NOS |
+ BXD62 |
+ M |
+ 68 |
+
+
+ | 16 |
+ 4207851051_E |
+ NOS |
+ BXD66 |
+ M |
+ 63 |
+
+
+ | 17 |
+ 4256265074_C |
+ NOS |
+ BXD66 |
+ F |
+ 69 |
+
+
+ | 18 |
+ 4207851038_B |
+ NOS |
+ BXD68 |
+ F |
+ 69 |
+
+
+ | 19 |
+ 4256265044_C |
+ NOS |
+ BXD68 |
+ M |
+ 66 |
+
+
+ | 20 |
+ 4256265070_A |
+ NOS |
+ BXD70 |
+ F |
+ 61 |
+
+
+ | 21 |
+ 4256265083_D |
+ NOS |
+ BXD70 |
+ M |
+ 67 |
+
+
+ | 22 |
+ 4060001096_B |
+ NOS |
+ BXD71 |
+ M |
+ 83 |
+
+
+ | 23 |
+ 4256265071_A |
+ NOS |
+ BXD71 |
+ F |
+ 0 |
+
+
+ | 24 |
+ 4256265057_E |
+ NOS |
+ BXD73 |
+ F |
+ 66 |
+
+
+ | 25 |
+ 4256265074_A |
+ NOS |
+ BXD73 |
+ M |
+ 69 |
+
+
+ | 26 |
+ 4060001078_B |
+ NOS |
+ BXD75 |
+ M |
+ 70 |
+
+
+ | 27 |
+ 4207851058_E |
+ NOS |
+ BXD75 |
+ F |
+ 68 |
+
+
+ | 28 |
+ 4207851051_A |
+ NOS |
+ BXD83 |
+ M |
+ 67 |
+
+
+ | 29 |
+ 4256265023_B |
+ NOS |
+ BXD83 |
+ F |
+ 70 |
+
+
+ | 30 |
+ 4256265083_C |
+ NOS |
+ BXD84 |
+ M |
+ 69 |
+
+
+ | 31 |
+ 4256265085_F |
+ NOS |
+ BXD84 |
+ M |
+ 67 |
+
+
+ | 32 |
+ 4207851045_F |
+ NOS |
+ BXD87 |
+ M |
+ 68 |
+
+
+ | 33 |
+ 4068846021_B |
+ NOS |
+ BXD89 |
+ F |
+ 69 |
+
+
+ | 34 |
+ 4256265073_F |
+ NOS |
+ BXD89 |
+ M |
+ 69 |
+
+
+ | 35 |
+ 4256265080_E |
+ NOS |
+ BXD90 |
+ M |
+ 73 |
+
+
+ | 36 |
+ 4256265085_E |
+ NOS |
+ BXD90 |
+ F |
+ 73 |
+
+
+ | 37 |
+ 4060001010_B |
+ NOS |
+ BXD96 |
+ M |
+ 68 |
+
+
+ | 38 |
+ 4060001071_D |
+ NOS |
+ BXD96 |
+ F |
+ 69 |
+
+
+ | 39 |
+ 4207851052_C |
+ NOS |
+ BXD96 |
+ M |
+ 69 |
+
+
+ | 40 |
+ 4060001011_B |
+ NOS |
+ BXD97 |
+ M |
+ 68 |
+
+
+ | 41 |
+ 4060001082_A |
+ NOS |
+ BXD98 |
+ F |
+ 72 |
+
+
+ | 42 |
+ 4256265058_F |
+ NOS |
+ BXD98 |
+ M |
+ 70 |
+
+
+ | 43 |
+ 4256265051_F |
+ NOS |
+ BXD99 |
+ M |
+ 70 |
+
+
+ | 44 |
+ 4060001075_E |
+ NOS |
+ BXD100 |
+ F |
+ 63 |
+
+
+ | 45 |
+ 4207851035_E |
+ NOS |
+ BXD100 |
+ M |
+ 72 |
+
+
+ | 46 |
+ 4060001075_D |
+ NOS |
+ BXD101 |
+ M |
+ 78 |
+
+
+ | 47 |
+ 4060001030_F |
+ NOS |
+ DBA/2J |
+ M |
+ 63 |
+
+
+ | 48 |
+ 4060001012_B |
+ NOS |
+ DBA/2J |
+ F |
+ 81 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_nosb_0217/summary.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_nosb_0217/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_nosb_0217/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0216/notes.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0216/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0216/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0216/summary.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0216/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0216/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0217/notes.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0217/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0217/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0217/specifics.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0217/specifics.rtf
new file mode 100644
index 0000000..01586d5
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0217/specifics.rtf
@@ -0,0 +1,408 @@
+RSE = Restraint stress followed by an ethanol injection.
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Condition |
+ Strain |
+ Sex |
+ Age |
+
+
+ | 1 |
+ 4060001088_B |
+ RSE |
+ BXD34 |
+ M |
+ 71 |
+
+
+ | 2 |
+ 4256265042_E |
+ RSE |
+ BXD43 |
+ M |
+ 72 |
+
+
+ | 3 |
+ 4256265052_B |
+ RSE |
+ BXD43 |
+ F |
+ 73 |
+
+
+ | 4 |
+ 4256265051_A |
+ RSE |
+ BXD45 |
+ F |
+ 60 |
+
+
+ | 5 |
+ 4256265070_F |
+ RSE |
+ BXD45 |
+ M |
+ 67 |
+
+
+ | 6 |
+ 4207851041_D |
+ RSE |
+ BXD51 |
+ F |
+ 66 |
+
+
+ | 7 |
+ 4207851058_C |
+ RSE |
+ BXD51 |
+ M |
+ 85 |
+
+
+ | 8 |
+ 4207851035_F |
+ RSE |
+ BXD55 |
+ M |
+ 62 |
+
+
+ | 9 |
+ 4207851041_E |
+ RSE |
+ BXD55 |
+ M |
+ 62 |
+
+
+ | 10 |
+ 4060001082_D |
+ RSE |
+ BXD60 |
+ F |
+ 76 |
+
+
+ | 11 |
+ 4256265043_D |
+ RSE |
+ BXD60 |
+ M |
+ 67 |
+
+
+ | 12 |
+ 4256265043_E |
+ RSE |
+ BXD61 |
+ F |
+ 70 |
+
+
+ | 13 |
+ 4256265087_E |
+ RSE |
+ BXD61 |
+ M |
+ 70 |
+
+
+ | 14 |
+ 4060001010_C |
+ RSE |
+ BXD62 |
+ F |
+ 69 |
+
+
+ | 15 |
+ 4207851027_A |
+ RSE |
+ BXD62 |
+ M |
+ 67 |
+
+
+ | 16 |
+ 4207851027_C |
+ RSE |
+ BXD66 |
+ M |
+ 74 |
+
+
+ | 17 |
+ 4060001011_C |
+ RSE |
+ BXD66 |
+ F |
+ 79 |
+
+
+ | 18 |
+ 4207851049_D |
+ RSE |
+ BXD68 |
+ F |
+ 73 |
+
+
+ | 19 |
+ 4256265071_F |
+ RSE |
+ BXD68 |
+ M |
+ 62 |
+
+
+ | 20 |
+ 4060001011_D |
+ RSE |
+ BXD70 |
+ M |
+ 82 |
+
+
+ | 21 |
+ 4256265044_D |
+ RSE |
+ BXD70 |
+ F |
+ 69 |
+
+
+ | 22 |
+ 4060001078_F |
+ RSE |
+ BXD71 |
+ M |
+ 70 |
+
+
+ | 23 |
+ 4207851027_D |
+ RSE |
+ BXD71 |
+ F |
+ 76 |
+
+
+ | 24 |
+ 4060001075_A |
+ RSE |
+ BXD73 |
+ M |
+ 69 |
+
+
+ | 25 |
+ 4256265073_C |
+ RSE |
+ BXD73 |
+ F |
+ 68 |
+
+
+ | 26 |
+ 4256265063_A |
+ RSE |
+ BXD75 |
+ F |
+ 66 |
+
+
+ | 27 |
+ 4256265083_F |
+ RSE |
+ BXD75 |
+ M |
+ 69 |
+
+
+ | 28 |
+ 4256265083_E |
+ RSE |
+ BXD83 |
+ F |
+ 87 |
+
+
+ | 29 |
+ 4256265085_B |
+ RSE |
+ BXD83 |
+ M |
+ 73 |
+
+
+ | 30 |
+ 4256265071_E |
+ RSE |
+ BXD84 |
+ F |
+ 51 |
+
+
+ | 31 |
+ 4256265086_D |
+ RSE |
+ BXD84 |
+ M |
+ 68 |
+
+
+ | 32 |
+ 4256265085_A |
+ RSE |
+ BXD87 |
+ F |
+ 64 |
+
+
+ | 33 |
+ 4256265086_E |
+ RSE |
+ BXD87 |
+ M |
+ 69 |
+
+
+ | 34 |
+ 4256265026_A |
+ RSE |
+ BXD89 |
+ F |
+ 74 |
+
+
+ | 35 |
+ 4256265057_D |
+ RSE |
+ BXD89 |
+ M |
+ 68 |
+
+
+ | 36 |
+ 4060001075_B |
+ RSE |
+ BXD90 |
+ F |
+ 72 |
+
+
+ | 37 |
+ 4256265086_F |
+ RSE |
+ BXD90 |
+ M |
+ 70 |
+
+
+ | 38 |
+ 4207851014_E |
+ RSE |
+ BXD96 |
+ F |
+ 67 |
+
+
+ | 39 |
+ 4256265063_D |
+ RSE |
+ BXD96 |
+ M |
+ 64 |
+
+
+ | 40 |
+ 4060001096_C |
+ RSE |
+ BXD97 |
+ M |
+ 65 |
+
+
+ | 41 |
+ 4256265062_D |
+ RSE |
+ BXD97 |
+ M |
+ 65 |
+
+
+ | 42 |
+ 4256265023_E |
+ RSE |
+ BXD98 |
+ M |
+ 75 |
+
+
+ | 43 |
+ 4256265063_F |
+ RSE |
+ BXD98 |
+ M |
+ 71 |
+
+
+ | 44 |
+ 4256265058_A |
+ RSE |
+ BXD99 |
+ M |
+ 76 |
+
+
+ | 45 |
+ 4256265026_B |
+ RSE |
+ BXD100 |
+ M |
+ 95 |
+
+
+ | 46 |
+ 4207851040_A |
+ RSE |
+ BXD101 |
+ F |
+ 69 |
+
+
+ | 47 |
+ 4060001031_F |
+ RSE |
+ DBA/2J |
+ M |
+ 76 |
+
+
+ | 48 |
+ 4256265069_C |
+ RSE |
+ DBA/2J |
+ F |
+ 86 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0217/summary.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0217/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_rseb_0217/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0216/notes.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0216/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0216/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0216/summary.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0216/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0216/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0217/notes.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0217/notes.rtf
new file mode 100644
index 0000000..35247b6
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0217/notes.rtf
@@ -0,0 +1,23 @@
+Hippocampus 5 Conditions
+Illumina Rank Invariant Normalized; Log2 Transformed and Z-Scored
+Batch and Outlier Analysis on Partek Genomic Suite 6.6
+ANOVA Done with batch (BATCH 1 AND 2); Batch effect removed
+K MOZHUI (KMOZHUI@UTHSC.EDU) 12-Nov-12
+Outliers removed are: 4060001003_A, 4060001010_D, 4060001012_A, 4060001012_C, 4060001012_E, AND 4060001078_A
+Number of samples = 284
+Number of probes = 46643
+
+
+ - UTHSC Hippocampus Illumina v6.1 5Trt (Nov12) RankInv LRS=(46 999)-> 1331
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=192
+ - UTHSC Hippocampus Illumina v6.1 NON (Nov12) RankInv LRS=(46 999)-> 219
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=97.8
+ - UTHSC Hippocampus Illumina v6.1 NOS (Nov12) RankInv LRS=(46 999)-> 404
+ ProbeSetID:ILM3440048 Gene:Cdkl2 Max LRS=106.6
+ - UTHSC Hippocampus Illumina v6.1 NOE (Nov12) RankInv LRS=(46 999)-> 509
+ ProbeSetID:ILM5270066 Gene:MGC67181 Max LRS=151
+ - UTHSC Hippocampus Illumina v6.1 RSS (Nov12) RankInv LRS=(46 999)-> 415
+ ProbeSetID:ILM5720687 Gene:Abhd16a Max LRS=121.7
+ - UTHSC Hippocampus Illumina v6.1 RSE (Nov12) RankInv LRS=(46 999)-> 421
+ ProbeSetID:ILM6350725 Gene:C14orf119 Max LRS=144.1
+
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0217/specifics.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0217/specifics.rtf
new file mode 100644
index 0000000..6036ccb
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0217/specifics.rtf
@@ -0,0 +1,400 @@
+RSS = short restraint stress (1 episode) followed by a saline injection.
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Condition |
+ Strain |
+ Sex |
+ Age |
+
+
+ | 1 |
+ 4207851045_D |
+ RSS |
+ BXD34 |
+ M |
+ 71 |
+
+
+ | 2 |
+ 4060001083_B |
+ RSS |
+ BXD43 |
+ M |
+ 72 |
+
+
+ | 3 |
+ 4068846017_C |
+ RSS |
+ BXD43 |
+ F |
+ 73 |
+
+
+ | 4 |
+ 4060001083_F |
+ RSS |
+ BXD45 |
+ F |
+ 67 |
+
+
+ | 5 |
+ 4256265070_D |
+ RSS |
+ BXD45 |
+ M |
+ 79 |
+
+
+ | 6 |
+ 4060001096_F |
+ RSS |
+ BXD51 |
+ M |
+ 75 |
+
+
+ | 7 |
+ 4256265045_E |
+ RSS |
+ BXD51 |
+ F |
+ 88 |
+
+
+ | 8 |
+ 4256265043_B |
+ RSS |
+ BXD55 |
+ F |
+ 67 |
+
+
+ | 9 |
+ 4256265024_D |
+ RSS |
+ BXD60 |
+ M |
+ 76 |
+
+
+ | 10 |
+ 4256265045_F |
+ RSS |
+ BXD60 |
+ F |
+ 72 |
+
+
+ | 11 |
+ 4207851058_D |
+ RSS |
+ BXD61 |
+ F |
+ 70 |
+
+
+ | 12 |
+ 4256265083_B |
+ RSS |
+ BXD61 |
+ M |
+ 82 |
+
+
+ | 13 |
+ 4068846017_E |
+ RSS |
+ BXD62 |
+ F |
+ 61 |
+
+
+ | 14 |
+ 4256265080_F |
+ RSS |
+ BXD62 |
+ M |
+ 67 |
+
+
+ | 15 |
+ 4207851052_A |
+ RSS |
+ BXD66 |
+ M |
+ 74 |
+
+
+ | 16 |
+ 4256265044_B |
+ RSS |
+ BXD66 |
+ F |
+ 69 |
+
+
+ | 17 |
+ 4060001003_E |
+ RSS |
+ BXD68 |
+ F |
+ 77 |
+
+
+ | 18 |
+ 4060001075_C |
+ RSS |
+ BXD68 |
+ M |
+ 64 |
+
+
+ | 19 |
+ 4068846021_E |
+ RSS |
+ BXD70 |
+ M |
+ 68 |
+
+
+ | 20 |
+ 4207851038_C |
+ RSS |
+ BXD70 |
+ F |
+ 69 |
+
+
+ | 21 |
+ 4060001003_F |
+ RSS |
+ BXD71 |
+ M |
+ 78 |
+
+
+ | 22 |
+ 4060001011_E |
+ RSS |
+ BXD71 |
+ F |
+ 76 |
+
+
+ | 23 |
+ 4207851014_A |
+ RSS |
+ BXD73 |
+ F |
+ 68 |
+
+
+ | 24 |
+ 4207851014_D |
+ RSS |
+ BXD73 |
+ M |
+ 67 |
+
+
+ | 25 |
+ 4051964017_A |
+ RSS |
+ BXD75 |
+ F |
+ 73 |
+
+
+ | 26 |
+ 4256265058_B |
+ RSS |
+ BXD75 |
+ F |
+ 69 |
+
+
+ | 27 |
+ 4256265058_C |
+ RSS |
+ BXD83 |
+ F |
+ 75 |
+
+
+ | 28 |
+ 4256265074_F |
+ RSS |
+ BXD83 |
+ M |
+ 69 |
+
+
+ | 29 |
+ 4256265062_B |
+ RSS |
+ BXD84 |
+ F |
+ 73 |
+
+
+ | 30 |
+ 4256265086_B |
+ RSS |
+ BXD84 |
+ M |
+ 69 |
+
+
+ | 31 |
+ 4207851051_F |
+ RSS |
+ BXD87 |
+ M |
+ 69 |
+
+
+ | 32 |
+ 4256265083_A |
+ RSS |
+ BXD89 |
+ F |
+ 59 |
+
+
+ | 33 |
+ 4256265073_A |
+ RSS |
+ BXD90 |
+ F |
+ 68 |
+
+
+ | 34 |
+ 4256265087_F |
+ RSS |
+ BXD90 |
+ M |
+ 68 |
+
+
+ | 35 |
+ 4207851051_B |
+ RSS |
+ BXD96 |
+ M |
+ 69 |
+
+
+ | 36 |
+ 4256265085_C |
+ RSS |
+ BXD96 |
+ F |
+ 76 |
+
+
+ | 37 |
+ 4060001079_F |
+ RSS |
+ BXD97 |
+ F |
+ 65 |
+
+
+ | 38 |
+ 4256265080_A |
+ RSS |
+ BXD97 |
+ M |
+ 70 |
+
+
+ | 39 |
+ 4060001011_F |
+ RSS |
+ BXD98 |
+ M |
+ 72 |
+
+
+ | 40 |
+ 4256265086_A |
+ RSS |
+ BXD98 |
+ F |
+ 72 |
+
+
+ | 41 |
+ 4207851014_C |
+ RSS |
+ BXD99 |
+ M |
+ 73 |
+
+
+ | 42 |
+ 4256265086_C |
+ RSS |
+ BXD99 |
+ F |
+ 86 |
+
+
+ | 43 |
+ 4060001068_F |
+ RSS |
+ BXD100 |
+ M |
+ 79 |
+
+
+ | 44 |
+ 4207851051_D |
+ RSS |
+ BXD100 |
+ F |
+ 68 |
+
+
+ | 45 |
+ 4207851045_C |
+ RSS |
+ BXD101 |
+ F |
+ 66 |
+
+
+ | 46 |
+ 4060001012_F |
+ RSS |
+ DBA/2J |
+ F |
+ 70 |
+
+
+ | 47 |
+ 4060001031_D |
+ RSS |
+ DBA/2J |
+ F |
+ 70 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0217/summary.rtf b/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0217/summary.rtf
new file mode 100644
index 0000000..5aeb69c
--- /dev/null
+++ b/general/datasets/Uthsc_ilm_bxd_hipp_rssb_0217/summary.rtf
@@ -0,0 +1,39 @@
+This is untreated control "Base" group gene expression data for the hippocampus of BXD strains of mice (n = 27 strains and n = 35 animals). These data NON data are useful as baseline for comparison with NOS, NOE, RSS, and RSE data sets. NON = NON = No stress and no saline control injection; NOS = No restraint stress and given only saline injections prior to sacrifice; NOE = No restraint stress and given an ethanol injection prior to sacrifice; RSS = short restraint stress (1 episode) followed by a saline injection; and finally, RSE = Restraint stress followed by an ethanol injection.
+
+For more details on the precise experimental paradigm, please see Ziebarth et al 2010 or the original paper that used this paradigm by Kerns RT, Ravindranathan A, Hassan S, Cage MP, York T, Williams RW, Miles MF (2005) Ethanol-responsive brain region expression networks: implications for behavioral responses to acute ethanol in DBA/2J versus C57BL/6J mice. Journal of Neuroscience 25: 2255-2266.
+
+Restraint Stress Protocol
+
+
+ - Weigh animals all animals to be tested and record body weight.
+ - Bring animals into testing area at least one hour prior to testing. 9 a.m. The following steps will be done for three animals (in parallel) because we have three zero-mazes.
+ - Place animals in immobilization tubes for 15 minutes.
+ - Inject animals IP with saline OR ethanol* and return to home cages for 5 minutes. (Remember to counterbalance groups. All animals in one cage should not be assigned to same group).
+ - Place each animal into zero-maze for 10 minutes.
+ - Return animal to home cage.
+ - Exactly 4 hours after injection, kill animals and remove brains to RNAlater solution. Animals should be killed by rapid decapitation with scissors so that trunk blood can be collected at the same time for corticosteroid analysis.
+
+
+Ethanol and saline injections
+Ethanol will be mixed with saline : 12.5% v/v. 100 ml of solution = 87.5 ml of saline and 12.5 ml of ethanol. Animals receive an injection of 1.8 g/kg. Multiply animals’ body weight by 0.018 to get injection volume (i.e. 25 g mouse X .018 mL/g = 0.45mL injection volume).
+
+"Adult mice were housed three to five to a cage with ad libitum access to standard rodent chow (Harlan Teklad, Madison, WI) and water in a 12 h dark/light cycle. All injections were intraperitoneal. Mice were given a saline injection once daily for 5 d to habituate them to the injection process. On day 6, mice received either an injection of saline or 20% ethanol in saline."
+
+Data Quality: All five data have been error checked. Strain and sex assignments were verified and are correct. This was determined by analysis of approximately 20 "test Mendelian" probes such as that for Thumpd1 (ILM751048). These probes have very high LRS values and the expected strain distribution pattern given their chromosomal location. Expression of genes on X and Y chromosomes (such as Xist) were used to confirm sex.
+
+Quality Control Data
+Total cis eQTLs with LRS > 23 within 5 Mb, maximum cis eQTL LRS value and probe
+
+
+ - NON: 669 (n=27 BXDs), 86.5 for B3galt6 (ILM50195)
+ - NOS: 844 (n=28 BXDs), 100.2 for Telo2 (ILM4850047)
+ - NOE: 1186 (n=35 BXDs), 101.9 for Mela-associated pseudogene (ILM4850047)
+ - RSS: 725 (n=27 BXDs), 82.8 for Gpr116 (ILM105390524)
+ - RSE: 915 (n=29 BXDs), 100.6 for Casp9 (ILM60577)
+
+
+Entered by Arthur Centeno, September 20, 2010.
+
+Array data sets all generated by Dr. Lu Lu (2008 - 2009) at the University of Tennessee Health Science Center, Memphis.
+
+Corresponding anxiety and ethanol response phenotypes generated by Dr. Melloni Cook and colleagues at the University of Memphis.
diff --git a/general/datasets/Uthsc_mm10_b6d2_ret_mirna_1116/experiment-design.rtf b/general/datasets/Uthsc_mm10_b6d2_ret_mirna_1116/experiment-design.rtf
new file mode 100644
index 0000000..ad9776a
--- /dev/null
+++ b/general/datasets/Uthsc_mm10_b6d2_ret_mirna_1116/experiment-design.rtf
@@ -0,0 +1,980 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Case ID |
+ Strain |
+ Sex |
+ DOB |
+ Sac date |
+ Age group |
+ Age (days) |
+ Age (month) |
+ EarTag Number |
+ Tube ID |
+ Agilent RNA concentration (ng/ul) |
+ RIN |
+ Nanodrop RNA concentration (ng/ul) |
+ 260/280 |
+ 260/230 |
+ Batch ID |
+ Notes |
+
+
+ | 1 |
+ B6.01 |
+ 071515.08 |
+ C57BL/6J |
+ M |
+ 06/15/15 |
+ 07/15/15 |
+ 1~2 |
+ 30 |
+ 1.0 |
+ |
+ R11 |
+ 173 |
+ 10.00 |
+ 181.22 |
+ 2.09 |
+ 2.12 |
+ 2 |
+ best |
+
+
+ | 2 |
+ B6.02 |
+ 071515.09 |
+ C57BL/6J |
+ M |
+ 06/15/15 |
+ 07/15/15 |
+ 1~2 |
+ 30 |
+ 1.0 |
+ |
+ R12 |
+ 121 |
+ N/A |
+ 148.52 |
+ 2.10 |
+ 1.69 |
+ 2 |
+ best |
+
+
+ | 3 |
+ B6.03 |
+ 052314.01 |
+ C57BL/6J |
+ F |
+ 03/23/14 |
+ 05/23/14 |
+ 2~4 |
+ 61 |
+ 2.0 |
+ |
+ Ret 32 |
+ 68 |
+ 10.0 |
+ 48.53 |
+ 2.02 |
+ 1.93 |
+ 1 |
+ |
+
+
+ | 4 |
+ B6.04 |
+ 062514.01 |
+ C57BL/6J |
+ M |
+ 04/10/14 |
+ 06/25/14 |
+ 2~4 |
+ 76 |
+ 2.5 |
+ |
+ Ret 21 |
+ 81 |
+ 9.0 |
+ 168.7 |
+ 2.06 |
+ 1.97 |
+ 1 |
+ |
+
+
+ | 5 |
+ B6.05 |
+ 040816.03 |
+ C57BL/6J |
+ M |
+ 02/04/16 |
+ 04/08/16 |
+ 2~4 |
+ 64 |
+ 2.1 |
+ |
+ R74 |
+ 385 |
+ 10.00 |
+ 448.16 |
+ 1.98 |
+ 2.12 |
+ 2 |
+ |
+
+
+ | 6 |
+ B6.06 |
+ 040816.04 |
+ C57BL/6J |
+ M |
+ 02/04/16 |
+ 04/08/16 |
+ 2~4 |
+ 64 |
+ 2.1 |
+ |
+ R75 |
+ 226 |
+ 8.70 |
+ 167.31 |
+ 2.04 |
+ 2.13 |
+ 2 |
+ |
+
+
+ | 7 |
+ B6.07 |
+ 041014.19 |
+ C57BL/6J |
+ F |
+ 10/20/13 |
+ 04/10/14 |
+ 5~7 |
+ 172 |
+ 5.7 |
+ |
+ Ret 10 |
+ 22 |
+ 10.0 |
+ 36.97 |
+ 2.22 |
+ 0.051 |
+ 1 |
+ |
+
+
+ | 8 |
+ B6.08 |
+ 101813.27 |
+ C57BL/6J |
+ M |
+ 05/06/13 |
+ 10/18/13 |
+ 5~7 |
+ 165 |
+ 5.5 |
+ |
+ Ret 7 |
+ 38 |
+ 10.0 |
+ 54.47 |
+ 2.08 |
+ 0.094 |
+ 1 |
+ |
+
+
+ | 9 |
+ B6.09 |
+ 050214.03 |
+ C57BL/6J |
+ F |
+ 08/14/13 |
+ 05/02/14 |
+ 7~9 |
+ 261 |
+ 8.7 |
+ |
+ Ret 27 |
+ 20 |
+ 10.0 |
+ 54.45 |
+ 2.11 |
+ 1.14 |
+ 1 |
+ |
+
+
+ | 10 |
+ B6.10 |
+ 041014.24 |
+ C57BL/6J |
+ M |
+ 09/02/13 |
+ 04/10/14 |
+ 7~9 |
+ 220 |
+ 7.3 |
+ |
+ Ret 12 |
+ 38 |
+ 9.50 |
+ 58.97 |
+ 2.08 |
+ 2.14 |
+ 1 |
+ |
+
+
+ | 11 |
+ B6.11 |
+ 101813.17 |
+ C57BL/6J |
+ F |
+ 12/07/12 |
+ 10/18/13 |
+ 10~12 |
+ 315 |
+ 10.5 |
+ |
+ Ret 2 |
+ 59 |
+ 9.40 |
+ 83.86 |
+ 2.17 |
+ 1.87 |
+ 1 |
+ |
+
+
+ | 12 |
+ B6.12 |
+ 052116.01 |
+ C57BL/6J |
+ M |
+ 05/19/15 |
+ 05/22/16 |
+ 10~12 |
+ 369 |
+ 12.3 |
+ |
+ R102 |
+ 293 |
+ 8.30 |
+ 179.69 |
+ 2.06 |
+ 2.11 |
+ 2 |
+ |
+
+
+ | 13 |
+ B6.13 |
+ 052116.02 |
+ C57BL/6J |
+ M |
+ 05/19/15 |
+ 05/22/16 |
+ 10~12 |
+ 369 |
+ 12.3 |
+ |
+ R103 |
+ 255 |
+ 8.40 |
+ 194.24 |
+ 2.04 |
+ 1.82 |
+ 2 |
+ |
+
+
+ | 14 |
+ B6.14 |
+ 042114.19 |
+ C57BL/6J |
+ F |
+ 03/11/13 |
+ 04/21/14 |
+ 13~15 |
+ 406 |
+ 13.5 |
+ 1252 |
+ Ret 26 |
+ 28 |
+ 10.0 |
+ 39.95 |
+ 2.22 |
+ 1.71 |
+ 1 |
+ |
+
+
+ | 15 |
+ B6.15 |
+ 050214.07 |
+ C57BL/6J |
+ M |
+ 03/20/13 |
+ 05/02/14 |
+ 13~15 |
+ 408 |
+ 13.6 |
+ |
+ Ret 28 |
+ 30 |
+ 10.0 |
+ 51.81 |
+ 2.06 |
+ 2.07 |
+ 1 |
+ |
+
+
+ | 16 |
+ B6.16 |
+ 041714.02 |
+ C57BL/6J |
+ M |
+ 09/18/12 |
+ 04/17/14 |
+ 19~21 |
+ 576 |
+ 19.2 |
+ 1117 |
+ Ret 17 |
+ 25 |
+ 10.0 |
+ 51.55 |
+ 2.13 |
+ 1.13 |
+ 1 |
+ |
+
+
+ | 17 |
+ B6.17 |
+ 041714.03 |
+ C57BL/6J |
+ M |
+ 09/18/12 |
+ 04/17/14 |
+ 19~21 |
+ 576 |
+ 19.2 |
+ 1116 |
+ Ret 18 |
+ 28 |
+ 10.0 |
+ 65.11 |
+ 2.01 |
+ 2.16 |
+ 1 |
+ |
+
+
+ | 18 |
+ D2.01 |
+ 030116.02 |
+ DBA/2J |
+ M |
+ 01/29/16 |
+ 03/01/16 |
+ 1~2 |
+ 32 |
+ 1.1 |
+ |
+ R63 |
+ 107 |
+ 8.80 |
+ 119.02 |
+ 2.05 |
+ 1.79 |
+ 2 |
+ |
+
+
+ | 19 |
+ D2.02 |
+ 030116.04 |
+ DBA/2J |
+ M |
+ 01/29/16 |
+ 03/01/16 |
+ 1~2 |
+ 32 |
+ 1.1 |
+ |
+ R65 |
+ 202 |
+ 9.10 |
+ 250.38 |
+ 2.03 |
+ 1.67 |
+ 2 |
+ |
+
+
+ | 20 |
+ D2.03 |
+ 062714.02 |
+ DBA/2J |
+ F |
+ 03/23/14 |
+ 06/27/14 |
+ 2~4 |
+ 104 |
+ 3.5 |
+ |
+ Ret 20a |
+ |
+ |
+ 189.3 |
+ 1.95 |
+ 1.81 |
+ 1 |
+ No Agilent as of 6/27/2014 |
+
+
+ | 21 |
+ D2.04 |
+ 062714.01 |
+ DBA/2J |
+ M |
+ 03/19/14 |
+ 06/27/14 |
+ 2~4 |
+ 100 |
+ 3.3 |
+ |
+ Ret 19a |
+ |
+ |
+ 154 |
+ 2.05 |
+ 1.89 |
+ 1 |
+ No Agilent as of 6/27/2014 |
+
+
+ | 22 |
+ D2.05 |
+ 032316.03 |
+ DBA/2J |
+ M |
+ 01/23/16 |
+ 03/23/16 |
+ 2~4 |
+ 60 |
+ 2.0 |
+ |
+ R70 |
+ 99 |
+ 9.30 |
+ 99.17 |
+ 2.04 |
+ 1.63 |
+ 2 |
+ |
+
+
+ | 23 |
+ D2.06 |
+ 032316.04 |
+ DBA/2J |
+ M |
+ 01/23/16 |
+ 03/23/16 |
+ 2~4 |
+ 60 |
+ 2.0 |
+ |
+ R71 |
+ 205 |
+ 9.10 |
+ 124.33 |
+ 2.03 |
+ 1.24 |
+ 2 |
+ |
+
+
+ | 24 |
+ D2.07 |
+ 050214.11 |
+ DBA/2J |
+ F |
+ 12/07/13 |
+ 05/02/14 |
+ 5~7 |
+ 146 |
+ 4.9 |
+ |
+ Ret 29 |
+ 100 |
+ 10.0 |
+ 86.47 |
+ 2.14 |
+ 1.9 |
+ 1 |
+ |
+
+
+ | 25 |
+ D2.08 |
+ 101813.08 |
+ DBA/2J |
+ M |
+ 03/21/13 |
+ 10/18/13 |
+ 5~7 |
+ 211 |
+ 7.0 |
+ |
+ Ret 1 |
+ 52 |
+ 9.9 |
+ 86.98 |
+ 2.11 |
+ 2.12 |
+ 1 |
+ |
+
+
+ | 26 |
+ D2.09 |
+ 041014.23 |
+ DBA/2J |
+ F |
+ 08/24/13 |
+ 04/10/14 |
+ 7~9 |
+ 229 |
+ 7.6 |
+ |
+ Ret 11 |
+ 21 |
+ 9.9 |
+ 44.39 |
+ 2.17 |
+ 1.15 |
+ 1 |
+ |
+
+
+ | 27 |
+ D2.10 |
+ 050214.15 |
+ DBA/2J |
+ F |
+ 07/27/13 |
+ 05/02/14 |
+ 7~9 |
+ 279 |
+ 9.3 |
+ |
+ Ret 30 |
+ 37 |
+ 10.0 |
+ 43.57 |
+ 2.13 |
+ 2.04 |
+ 1 |
+ |
+
+
+ | 28 |
+ D2.11 |
+ 101813.23 |
+ DBA/2J |
+ F |
+ 11/29/12 |
+ 10/18/13 |
+ 10~12 |
+ 323 |
+ 10.8 |
+ |
+ Ret 6 |
+ 77 |
+ 9.7 |
+ 105.02 |
+ 2.06 |
+ 2.14 |
+ 1 |
+ |
+
+
+ | 29 |
+ D2.12 |
+ 101813.19 |
+ DBA/2J |
+ M |
+ 12/08/12 |
+ 10/18/13 |
+ 10~12 |
+ 314 |
+ 10.5 |
+ |
+ Ret 3 |
+ 46 |
+ 9.9 |
+ 65.7 |
+ 2.13 |
+ 1.71 |
+ 1 |
+ |
+
+
+ | 30 |
+ D2.13 |
+ 042114.18 |
+ DBA/2J |
+ F |
+ 03/19/13 |
+ 04/21/14 |
+ 13~15 |
+ 398 |
+ 13.3 |
+ 1148 |
+ Ret 25 |
+ 26 |
+ 9.9 |
+ 65.53 |
+ 2.17 |
+ 2.43 |
+ 1 |
+ |
+
+
+ | 31 |
+ D2.14 |
+ 042114.17 |
+ DBA/2J |
+ M |
+ 03/19/13 |
+ 04/21/14 |
+ 13~15 |
+ 398 |
+ 13.3 |
+ 1130 |
+ Ret 24 |
+ 40 |
+ 9.4 |
+ 36.98 |
+ 2.07 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 32 |
+ D2.15 |
+ 041014.06 |
+ DBA/2J |
+ M |
+ 9/6/2012 |
+ 04/10/14 |
+ 19~21 |
+ 581 |
+ 19.4 |
+ 1123 |
+ Ret 8 |
+ 35 |
+ 9.9 |
+ 52.99 |
+ 2.12 |
+ 0.091 |
+ 1 |
+ |
+
+
+ | 33 |
+ D2.16 |
+ 041014.07 |
+ DBA/2J |
+ F |
+ 9/6/2012 |
+ 04/10/14 |
+ 19~21 |
+ 581 |
+ 19.4 |
+ 1124 |
+ Ret 9 |
+ 30 |
+ 9.5 |
+ 52.44 |
+ 2.19 |
+ 0.08 |
+ 1 |
+ |
+
+
+ | 34 |
+ D2GP.01 |
+ 041416.15 |
+ DBA-Gpmnb(wp) |
+ F |
+ 03/15/16 |
+ 04/14/16 |
+ 1~2 |
+ 30 |
+ 1.0 |
+ |
+ R92 |
+ 334 |
+ 9.10 |
+ 135.79 |
+ 1.87 |
+ 2.23 |
+ 2 |
+ |
+
+
+ | 35 |
+ D2GP.02 |
+ 120715.02 |
+ DBA-Gpmnb(wp) |
+ M |
+ 11/05/15 |
+ 12/07/15 |
+ 1~2 |
+ 32 |
+ 1.1 |
+ |
+ R31 |
+ 85 |
+ 9.20 |
+ 106.06 |
+ 2.04 |
+ 2.06 |
+ 2 |
+ |
+
+
+ | 36 |
+ D2GP.03 |
+ 041416.04 |
+ DBA-Gpmnb(wp) |
+ F |
+ 02/02/16 |
+ 04/14/16 |
+ 2~4 |
+ 72 |
+ 2.4 |
+ |
+ R81 |
+ 112 |
+ 9.40 |
+ 94.79 |
+ 1.94 |
+ 2.19 |
+ 2 |
+ |
+
+
+ | 37 |
+ D2GP.04 |
+ 120815.04 |
+ DBA-Gpmnb(wp) |
+ M |
+ 10/08/15 |
+ 12/08/15 |
+ 2~4 |
+ 61 |
+ 2.0 |
+ |
+ R39 |
+ 89 |
+ N/A |
+ 118.84 |
+ 2.05 |
+ 1.97 |
+ 2 |
+ |
+
+
+ | 38 |
+ D2GP.05 |
+ 101813.21 |
+ DBA-Gpmnb(wp) |
+ F |
+ 04/09/13 |
+ 10/18/13 |
+ 5~7 |
+ 192 |
+ 6.4 |
+ |
+ Ret 4 |
+ 53 |
+ 9.9 |
+ 74.13 |
+ 2.14 |
+ 2.28 |
+ 1 |
+ |
+
+
+ | 39 |
+ D2GP.06 |
+ 101813.22 |
+ DBA-Gpmnb(wp) |
+ M |
+ 04/09/13 |
+ 10/18/13 |
+ 5~7 |
+ 192 |
+ 6.4 |
+ |
+ Ret 5 |
+ 54 |
+ 10.0 |
+ 81.32 |
+ 2.1 |
+ 2.19 |
+ 1 |
+ |
+
+
+ | 40 |
+ D2GP.07 |
+ 041014.27 |
+ DBA-Gpmnb(wp) |
+ F |
+ 08/29/13 |
+ 04/10/14 |
+ 7~9 |
+ 224 |
+ 7.5 |
+ |
+ Ret 15 |
+ 14 |
+ 10.0 |
+ 37.03 |
+ 2.06 |
+ 1.44 |
+ 1 |
+ |
+
+
+ | 41 |
+ D2GP.08 |
+ 041014.28 |
+ DBA-Gpmnb(wp) |
+ M |
+ 08/29/13 |
+ 04/10/14 |
+ 7~9 |
+ 224 |
+ 7.5 |
+ |
+ Ret 16 |
+ 29 |
+ 9.9 |
+ 63.83 |
+ 2.03 |
+ 2.08 |
+ 1 |
+ |
+
+
+ | 42 |
+ D2GP.09 |
+ 041014.25 |
+ DBA-Gpmnb(wp) |
+ F |
+ 06/12/13 |
+ 04/10/14 |
+ 10~12 |
+ 302 |
+ 10.1 |
+ |
+ Ret 13 |
+ 31 |
+ 9.8 |
+ 60.73 |
+ 2.07 |
+ 2.12 |
+ 1 |
+ |
+
+
+ | 43 |
+ D2GP.10 |
+ 041014.26 |
+ DBA-Gpmnb(wp) |
+ M |
+ 06/12/13 |
+ 04/10/14 |
+ 10~12 |
+ 302 |
+ 10.1 |
+ |
+ Ret 14 |
+ 24 |
+ 10.0 |
+ 65.1 |
+ 2.06 |
+ 1.09 |
+ 1 |
+ |
+
+
+ | 44 |
+ D2GP.11 |
+ 042114.08 |
+ DBA-Gpmnb(wp) |
+ F |
+ 01/14/13 |
+ 04/21/14 |
+ 13~15 |
+ 462 |
+ 15.4 |
+ 1021 |
+ Ret 22 |
+ 87 |
+ 9.0 |
+ 150.69 |
+ 2.09 |
+ 2.02 |
+ 1 |
+ |
+
+
+ | 45 |
+ D2GP.12 |
+ 042114.09 |
+ DBA-Gpmnb(wp) |
+ F |
+ 01/14/13 |
+ 04/21/14 |
+ 13~15 |
+ 462 |
+ 15.4 |
+ 1022 |
+ Ret 23 |
+ 18 |
+ 10.0 |
+ 44.16 |
+ 2.11 |
+ 0.069 |
+ 1 |
+ |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_mm10_b6d2_ret_mirna_1116/specifics.rtf b/general/datasets/Uthsc_mm10_b6d2_ret_mirna_1116/specifics.rtf
new file mode 100644
index 0000000..69b4147
--- /dev/null
+++ b/general/datasets/Uthsc_mm10_b6d2_ret_mirna_1116/specifics.rtf
@@ -0,0 +1 @@
+micro RNA
\ No newline at end of file
diff --git a/general/datasets/Uthsc_mm10_b6d2_ret_mirna_1116/summary.rtf b/general/datasets/Uthsc_mm10_b6d2_ret_mirna_1116/summary.rtf
new file mode 100644
index 0000000..1d95169
--- /dev/null
+++ b/general/datasets/Uthsc_mm10_b6d2_ret_mirna_1116/summary.rtf
@@ -0,0 +1,9 @@
+This is a microRNA data set generated using the Affymetrix Genechip miRNA 4.0 array (see http://media.affymetrix.com/support/technical/datasheets/miRNA_4-0_and_4-1_datasheet.pdf).
+
+The data set provides 3222 estimates of expression (mainly for mi-RNAs) for 45 retinas from C57BL/6J (B6 cases B6.01 to B6.17), DBA/2J (cases D2.01 to D2.16), and DBA/2J with a wildtype Gpnmb allele (D2GP.01 to D2GP.12). Cases range in age from 30 to 576 days and include both sexes.
+
+We are using this data set in combination with the conventional Mouse Gene 1.0ST array to study normal and glaucomatous changes in gene expression as a function of age.
+
+Please contact Lu Lu (lulu@uthsc.edu), Robert W. Williams (rwilliams@uthsc.edu), or Junming Yue (jyue@uthsc.edu).
+
+Supported in part by Research to Prevent Blindness.
diff --git a/general/datasets/Uthsc_mm9_b6d2_ret_0916/cases.rtf b/general/datasets/Uthsc_mm9_b6d2_ret_0916/cases.rtf
new file mode 100644
index 0000000..ad9776a
--- /dev/null
+++ b/general/datasets/Uthsc_mm9_b6d2_ret_0916/cases.rtf
@@ -0,0 +1,980 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Case ID |
+ Strain |
+ Sex |
+ DOB |
+ Sac date |
+ Age group |
+ Age (days) |
+ Age (month) |
+ EarTag Number |
+ Tube ID |
+ Agilent RNA concentration (ng/ul) |
+ RIN |
+ Nanodrop RNA concentration (ng/ul) |
+ 260/280 |
+ 260/230 |
+ Batch ID |
+ Notes |
+
+
+ | 1 |
+ B6.01 |
+ 071515.08 |
+ C57BL/6J |
+ M |
+ 06/15/15 |
+ 07/15/15 |
+ 1~2 |
+ 30 |
+ 1.0 |
+ |
+ R11 |
+ 173 |
+ 10.00 |
+ 181.22 |
+ 2.09 |
+ 2.12 |
+ 2 |
+ best |
+
+
+ | 2 |
+ B6.02 |
+ 071515.09 |
+ C57BL/6J |
+ M |
+ 06/15/15 |
+ 07/15/15 |
+ 1~2 |
+ 30 |
+ 1.0 |
+ |
+ R12 |
+ 121 |
+ N/A |
+ 148.52 |
+ 2.10 |
+ 1.69 |
+ 2 |
+ best |
+
+
+ | 3 |
+ B6.03 |
+ 052314.01 |
+ C57BL/6J |
+ F |
+ 03/23/14 |
+ 05/23/14 |
+ 2~4 |
+ 61 |
+ 2.0 |
+ |
+ Ret 32 |
+ 68 |
+ 10.0 |
+ 48.53 |
+ 2.02 |
+ 1.93 |
+ 1 |
+ |
+
+
+ | 4 |
+ B6.04 |
+ 062514.01 |
+ C57BL/6J |
+ M |
+ 04/10/14 |
+ 06/25/14 |
+ 2~4 |
+ 76 |
+ 2.5 |
+ |
+ Ret 21 |
+ 81 |
+ 9.0 |
+ 168.7 |
+ 2.06 |
+ 1.97 |
+ 1 |
+ |
+
+
+ | 5 |
+ B6.05 |
+ 040816.03 |
+ C57BL/6J |
+ M |
+ 02/04/16 |
+ 04/08/16 |
+ 2~4 |
+ 64 |
+ 2.1 |
+ |
+ R74 |
+ 385 |
+ 10.00 |
+ 448.16 |
+ 1.98 |
+ 2.12 |
+ 2 |
+ |
+
+
+ | 6 |
+ B6.06 |
+ 040816.04 |
+ C57BL/6J |
+ M |
+ 02/04/16 |
+ 04/08/16 |
+ 2~4 |
+ 64 |
+ 2.1 |
+ |
+ R75 |
+ 226 |
+ 8.70 |
+ 167.31 |
+ 2.04 |
+ 2.13 |
+ 2 |
+ |
+
+
+ | 7 |
+ B6.07 |
+ 041014.19 |
+ C57BL/6J |
+ F |
+ 10/20/13 |
+ 04/10/14 |
+ 5~7 |
+ 172 |
+ 5.7 |
+ |
+ Ret 10 |
+ 22 |
+ 10.0 |
+ 36.97 |
+ 2.22 |
+ 0.051 |
+ 1 |
+ |
+
+
+ | 8 |
+ B6.08 |
+ 101813.27 |
+ C57BL/6J |
+ M |
+ 05/06/13 |
+ 10/18/13 |
+ 5~7 |
+ 165 |
+ 5.5 |
+ |
+ Ret 7 |
+ 38 |
+ 10.0 |
+ 54.47 |
+ 2.08 |
+ 0.094 |
+ 1 |
+ |
+
+
+ | 9 |
+ B6.09 |
+ 050214.03 |
+ C57BL/6J |
+ F |
+ 08/14/13 |
+ 05/02/14 |
+ 7~9 |
+ 261 |
+ 8.7 |
+ |
+ Ret 27 |
+ 20 |
+ 10.0 |
+ 54.45 |
+ 2.11 |
+ 1.14 |
+ 1 |
+ |
+
+
+ | 10 |
+ B6.10 |
+ 041014.24 |
+ C57BL/6J |
+ M |
+ 09/02/13 |
+ 04/10/14 |
+ 7~9 |
+ 220 |
+ 7.3 |
+ |
+ Ret 12 |
+ 38 |
+ 9.50 |
+ 58.97 |
+ 2.08 |
+ 2.14 |
+ 1 |
+ |
+
+
+ | 11 |
+ B6.11 |
+ 101813.17 |
+ C57BL/6J |
+ F |
+ 12/07/12 |
+ 10/18/13 |
+ 10~12 |
+ 315 |
+ 10.5 |
+ |
+ Ret 2 |
+ 59 |
+ 9.40 |
+ 83.86 |
+ 2.17 |
+ 1.87 |
+ 1 |
+ |
+
+
+ | 12 |
+ B6.12 |
+ 052116.01 |
+ C57BL/6J |
+ M |
+ 05/19/15 |
+ 05/22/16 |
+ 10~12 |
+ 369 |
+ 12.3 |
+ |
+ R102 |
+ 293 |
+ 8.30 |
+ 179.69 |
+ 2.06 |
+ 2.11 |
+ 2 |
+ |
+
+
+ | 13 |
+ B6.13 |
+ 052116.02 |
+ C57BL/6J |
+ M |
+ 05/19/15 |
+ 05/22/16 |
+ 10~12 |
+ 369 |
+ 12.3 |
+ |
+ R103 |
+ 255 |
+ 8.40 |
+ 194.24 |
+ 2.04 |
+ 1.82 |
+ 2 |
+ |
+
+
+ | 14 |
+ B6.14 |
+ 042114.19 |
+ C57BL/6J |
+ F |
+ 03/11/13 |
+ 04/21/14 |
+ 13~15 |
+ 406 |
+ 13.5 |
+ 1252 |
+ Ret 26 |
+ 28 |
+ 10.0 |
+ 39.95 |
+ 2.22 |
+ 1.71 |
+ 1 |
+ |
+
+
+ | 15 |
+ B6.15 |
+ 050214.07 |
+ C57BL/6J |
+ M |
+ 03/20/13 |
+ 05/02/14 |
+ 13~15 |
+ 408 |
+ 13.6 |
+ |
+ Ret 28 |
+ 30 |
+ 10.0 |
+ 51.81 |
+ 2.06 |
+ 2.07 |
+ 1 |
+ |
+
+
+ | 16 |
+ B6.16 |
+ 041714.02 |
+ C57BL/6J |
+ M |
+ 09/18/12 |
+ 04/17/14 |
+ 19~21 |
+ 576 |
+ 19.2 |
+ 1117 |
+ Ret 17 |
+ 25 |
+ 10.0 |
+ 51.55 |
+ 2.13 |
+ 1.13 |
+ 1 |
+ |
+
+
+ | 17 |
+ B6.17 |
+ 041714.03 |
+ C57BL/6J |
+ M |
+ 09/18/12 |
+ 04/17/14 |
+ 19~21 |
+ 576 |
+ 19.2 |
+ 1116 |
+ Ret 18 |
+ 28 |
+ 10.0 |
+ 65.11 |
+ 2.01 |
+ 2.16 |
+ 1 |
+ |
+
+
+ | 18 |
+ D2.01 |
+ 030116.02 |
+ DBA/2J |
+ M |
+ 01/29/16 |
+ 03/01/16 |
+ 1~2 |
+ 32 |
+ 1.1 |
+ |
+ R63 |
+ 107 |
+ 8.80 |
+ 119.02 |
+ 2.05 |
+ 1.79 |
+ 2 |
+ |
+
+
+ | 19 |
+ D2.02 |
+ 030116.04 |
+ DBA/2J |
+ M |
+ 01/29/16 |
+ 03/01/16 |
+ 1~2 |
+ 32 |
+ 1.1 |
+ |
+ R65 |
+ 202 |
+ 9.10 |
+ 250.38 |
+ 2.03 |
+ 1.67 |
+ 2 |
+ |
+
+
+ | 20 |
+ D2.03 |
+ 062714.02 |
+ DBA/2J |
+ F |
+ 03/23/14 |
+ 06/27/14 |
+ 2~4 |
+ 104 |
+ 3.5 |
+ |
+ Ret 20a |
+ |
+ |
+ 189.3 |
+ 1.95 |
+ 1.81 |
+ 1 |
+ No Agilent as of 6/27/2014 |
+
+
+ | 21 |
+ D2.04 |
+ 062714.01 |
+ DBA/2J |
+ M |
+ 03/19/14 |
+ 06/27/14 |
+ 2~4 |
+ 100 |
+ 3.3 |
+ |
+ Ret 19a |
+ |
+ |
+ 154 |
+ 2.05 |
+ 1.89 |
+ 1 |
+ No Agilent as of 6/27/2014 |
+
+
+ | 22 |
+ D2.05 |
+ 032316.03 |
+ DBA/2J |
+ M |
+ 01/23/16 |
+ 03/23/16 |
+ 2~4 |
+ 60 |
+ 2.0 |
+ |
+ R70 |
+ 99 |
+ 9.30 |
+ 99.17 |
+ 2.04 |
+ 1.63 |
+ 2 |
+ |
+
+
+ | 23 |
+ D2.06 |
+ 032316.04 |
+ DBA/2J |
+ M |
+ 01/23/16 |
+ 03/23/16 |
+ 2~4 |
+ 60 |
+ 2.0 |
+ |
+ R71 |
+ 205 |
+ 9.10 |
+ 124.33 |
+ 2.03 |
+ 1.24 |
+ 2 |
+ |
+
+
+ | 24 |
+ D2.07 |
+ 050214.11 |
+ DBA/2J |
+ F |
+ 12/07/13 |
+ 05/02/14 |
+ 5~7 |
+ 146 |
+ 4.9 |
+ |
+ Ret 29 |
+ 100 |
+ 10.0 |
+ 86.47 |
+ 2.14 |
+ 1.9 |
+ 1 |
+ |
+
+
+ | 25 |
+ D2.08 |
+ 101813.08 |
+ DBA/2J |
+ M |
+ 03/21/13 |
+ 10/18/13 |
+ 5~7 |
+ 211 |
+ 7.0 |
+ |
+ Ret 1 |
+ 52 |
+ 9.9 |
+ 86.98 |
+ 2.11 |
+ 2.12 |
+ 1 |
+ |
+
+
+ | 26 |
+ D2.09 |
+ 041014.23 |
+ DBA/2J |
+ F |
+ 08/24/13 |
+ 04/10/14 |
+ 7~9 |
+ 229 |
+ 7.6 |
+ |
+ Ret 11 |
+ 21 |
+ 9.9 |
+ 44.39 |
+ 2.17 |
+ 1.15 |
+ 1 |
+ |
+
+
+ | 27 |
+ D2.10 |
+ 050214.15 |
+ DBA/2J |
+ F |
+ 07/27/13 |
+ 05/02/14 |
+ 7~9 |
+ 279 |
+ 9.3 |
+ |
+ Ret 30 |
+ 37 |
+ 10.0 |
+ 43.57 |
+ 2.13 |
+ 2.04 |
+ 1 |
+ |
+
+
+ | 28 |
+ D2.11 |
+ 101813.23 |
+ DBA/2J |
+ F |
+ 11/29/12 |
+ 10/18/13 |
+ 10~12 |
+ 323 |
+ 10.8 |
+ |
+ Ret 6 |
+ 77 |
+ 9.7 |
+ 105.02 |
+ 2.06 |
+ 2.14 |
+ 1 |
+ |
+
+
+ | 29 |
+ D2.12 |
+ 101813.19 |
+ DBA/2J |
+ M |
+ 12/08/12 |
+ 10/18/13 |
+ 10~12 |
+ 314 |
+ 10.5 |
+ |
+ Ret 3 |
+ 46 |
+ 9.9 |
+ 65.7 |
+ 2.13 |
+ 1.71 |
+ 1 |
+ |
+
+
+ | 30 |
+ D2.13 |
+ 042114.18 |
+ DBA/2J |
+ F |
+ 03/19/13 |
+ 04/21/14 |
+ 13~15 |
+ 398 |
+ 13.3 |
+ 1148 |
+ Ret 25 |
+ 26 |
+ 9.9 |
+ 65.53 |
+ 2.17 |
+ 2.43 |
+ 1 |
+ |
+
+
+ | 31 |
+ D2.14 |
+ 042114.17 |
+ DBA/2J |
+ M |
+ 03/19/13 |
+ 04/21/14 |
+ 13~15 |
+ 398 |
+ 13.3 |
+ 1130 |
+ Ret 24 |
+ 40 |
+ 9.4 |
+ 36.98 |
+ 2.07 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 32 |
+ D2.15 |
+ 041014.06 |
+ DBA/2J |
+ M |
+ 9/6/2012 |
+ 04/10/14 |
+ 19~21 |
+ 581 |
+ 19.4 |
+ 1123 |
+ Ret 8 |
+ 35 |
+ 9.9 |
+ 52.99 |
+ 2.12 |
+ 0.091 |
+ 1 |
+ |
+
+
+ | 33 |
+ D2.16 |
+ 041014.07 |
+ DBA/2J |
+ F |
+ 9/6/2012 |
+ 04/10/14 |
+ 19~21 |
+ 581 |
+ 19.4 |
+ 1124 |
+ Ret 9 |
+ 30 |
+ 9.5 |
+ 52.44 |
+ 2.19 |
+ 0.08 |
+ 1 |
+ |
+
+
+ | 34 |
+ D2GP.01 |
+ 041416.15 |
+ DBA-Gpmnb(wp) |
+ F |
+ 03/15/16 |
+ 04/14/16 |
+ 1~2 |
+ 30 |
+ 1.0 |
+ |
+ R92 |
+ 334 |
+ 9.10 |
+ 135.79 |
+ 1.87 |
+ 2.23 |
+ 2 |
+ |
+
+
+ | 35 |
+ D2GP.02 |
+ 120715.02 |
+ DBA-Gpmnb(wp) |
+ M |
+ 11/05/15 |
+ 12/07/15 |
+ 1~2 |
+ 32 |
+ 1.1 |
+ |
+ R31 |
+ 85 |
+ 9.20 |
+ 106.06 |
+ 2.04 |
+ 2.06 |
+ 2 |
+ |
+
+
+ | 36 |
+ D2GP.03 |
+ 041416.04 |
+ DBA-Gpmnb(wp) |
+ F |
+ 02/02/16 |
+ 04/14/16 |
+ 2~4 |
+ 72 |
+ 2.4 |
+ |
+ R81 |
+ 112 |
+ 9.40 |
+ 94.79 |
+ 1.94 |
+ 2.19 |
+ 2 |
+ |
+
+
+ | 37 |
+ D2GP.04 |
+ 120815.04 |
+ DBA-Gpmnb(wp) |
+ M |
+ 10/08/15 |
+ 12/08/15 |
+ 2~4 |
+ 61 |
+ 2.0 |
+ |
+ R39 |
+ 89 |
+ N/A |
+ 118.84 |
+ 2.05 |
+ 1.97 |
+ 2 |
+ |
+
+
+ | 38 |
+ D2GP.05 |
+ 101813.21 |
+ DBA-Gpmnb(wp) |
+ F |
+ 04/09/13 |
+ 10/18/13 |
+ 5~7 |
+ 192 |
+ 6.4 |
+ |
+ Ret 4 |
+ 53 |
+ 9.9 |
+ 74.13 |
+ 2.14 |
+ 2.28 |
+ 1 |
+ |
+
+
+ | 39 |
+ D2GP.06 |
+ 101813.22 |
+ DBA-Gpmnb(wp) |
+ M |
+ 04/09/13 |
+ 10/18/13 |
+ 5~7 |
+ 192 |
+ 6.4 |
+ |
+ Ret 5 |
+ 54 |
+ 10.0 |
+ 81.32 |
+ 2.1 |
+ 2.19 |
+ 1 |
+ |
+
+
+ | 40 |
+ D2GP.07 |
+ 041014.27 |
+ DBA-Gpmnb(wp) |
+ F |
+ 08/29/13 |
+ 04/10/14 |
+ 7~9 |
+ 224 |
+ 7.5 |
+ |
+ Ret 15 |
+ 14 |
+ 10.0 |
+ 37.03 |
+ 2.06 |
+ 1.44 |
+ 1 |
+ |
+
+
+ | 41 |
+ D2GP.08 |
+ 041014.28 |
+ DBA-Gpmnb(wp) |
+ M |
+ 08/29/13 |
+ 04/10/14 |
+ 7~9 |
+ 224 |
+ 7.5 |
+ |
+ Ret 16 |
+ 29 |
+ 9.9 |
+ 63.83 |
+ 2.03 |
+ 2.08 |
+ 1 |
+ |
+
+
+ | 42 |
+ D2GP.09 |
+ 041014.25 |
+ DBA-Gpmnb(wp) |
+ F |
+ 06/12/13 |
+ 04/10/14 |
+ 10~12 |
+ 302 |
+ 10.1 |
+ |
+ Ret 13 |
+ 31 |
+ 9.8 |
+ 60.73 |
+ 2.07 |
+ 2.12 |
+ 1 |
+ |
+
+
+ | 43 |
+ D2GP.10 |
+ 041014.26 |
+ DBA-Gpmnb(wp) |
+ M |
+ 06/12/13 |
+ 04/10/14 |
+ 10~12 |
+ 302 |
+ 10.1 |
+ |
+ Ret 14 |
+ 24 |
+ 10.0 |
+ 65.1 |
+ 2.06 |
+ 1.09 |
+ 1 |
+ |
+
+
+ | 44 |
+ D2GP.11 |
+ 042114.08 |
+ DBA-Gpmnb(wp) |
+ F |
+ 01/14/13 |
+ 04/21/14 |
+ 13~15 |
+ 462 |
+ 15.4 |
+ 1021 |
+ Ret 22 |
+ 87 |
+ 9.0 |
+ 150.69 |
+ 2.09 |
+ 2.02 |
+ 1 |
+ |
+
+
+ | 45 |
+ D2GP.12 |
+ 042114.09 |
+ DBA-Gpmnb(wp) |
+ F |
+ 01/14/13 |
+ 04/21/14 |
+ 13~15 |
+ 462 |
+ 15.4 |
+ 1022 |
+ Ret 23 |
+ 18 |
+ 10.0 |
+ 44.16 |
+ 2.11 |
+ 0.069 |
+ 1 |
+ |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_mm9_b6d2_ret_0916/summary.rtf b/general/datasets/Uthsc_mm9_b6d2_ret_0916/summary.rtf
new file mode 100644
index 0000000..de58298
--- /dev/null
+++ b/general/datasets/Uthsc_mm9_b6d2_ret_0916/summary.rtf
@@ -0,0 +1,9 @@
+This is an array data set generated using the Affymetrix Genechip Mouse 1.0 ST array. Please see the companion microRNA (miRNA) data set.
+
+All of these data sets provides estimates of expression for 45 retinas from C57BL/6J (B6 cases B6.01 to B6.17), DBA/2J (cases D2.01 to D2.16), and DBA/2J with a wildtype Gpnmb allele (D2GP.01 to D2GP.12). Cases range in age from 30 to 576 days and include both sexes.
+
+We are using these data in combination with the micro RNA array 4.0 to study normal and glaucomatous changes in gene expression as a function of age.
+
+Please contact Lu Lu (lulu@uthsc.edu), Robert W. Williams (rwilliams@uthsc.edu), or Junming Yue (jyue@uthsc.edu).
+
+Supported in part by Research to Prevent Blindness.
diff --git a/general/datasets/Uthsc_mm9_b6d2_retex_0916/cases.rtf b/general/datasets/Uthsc_mm9_b6d2_retex_0916/cases.rtf
new file mode 100644
index 0000000..ad9776a
--- /dev/null
+++ b/general/datasets/Uthsc_mm9_b6d2_retex_0916/cases.rtf
@@ -0,0 +1,980 @@
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Case ID |
+ Strain |
+ Sex |
+ DOB |
+ Sac date |
+ Age group |
+ Age (days) |
+ Age (month) |
+ EarTag Number |
+ Tube ID |
+ Agilent RNA concentration (ng/ul) |
+ RIN |
+ Nanodrop RNA concentration (ng/ul) |
+ 260/280 |
+ 260/230 |
+ Batch ID |
+ Notes |
+
+
+ | 1 |
+ B6.01 |
+ 071515.08 |
+ C57BL/6J |
+ M |
+ 06/15/15 |
+ 07/15/15 |
+ 1~2 |
+ 30 |
+ 1.0 |
+ |
+ R11 |
+ 173 |
+ 10.00 |
+ 181.22 |
+ 2.09 |
+ 2.12 |
+ 2 |
+ best |
+
+
+ | 2 |
+ B6.02 |
+ 071515.09 |
+ C57BL/6J |
+ M |
+ 06/15/15 |
+ 07/15/15 |
+ 1~2 |
+ 30 |
+ 1.0 |
+ |
+ R12 |
+ 121 |
+ N/A |
+ 148.52 |
+ 2.10 |
+ 1.69 |
+ 2 |
+ best |
+
+
+ | 3 |
+ B6.03 |
+ 052314.01 |
+ C57BL/6J |
+ F |
+ 03/23/14 |
+ 05/23/14 |
+ 2~4 |
+ 61 |
+ 2.0 |
+ |
+ Ret 32 |
+ 68 |
+ 10.0 |
+ 48.53 |
+ 2.02 |
+ 1.93 |
+ 1 |
+ |
+
+
+ | 4 |
+ B6.04 |
+ 062514.01 |
+ C57BL/6J |
+ M |
+ 04/10/14 |
+ 06/25/14 |
+ 2~4 |
+ 76 |
+ 2.5 |
+ |
+ Ret 21 |
+ 81 |
+ 9.0 |
+ 168.7 |
+ 2.06 |
+ 1.97 |
+ 1 |
+ |
+
+
+ | 5 |
+ B6.05 |
+ 040816.03 |
+ C57BL/6J |
+ M |
+ 02/04/16 |
+ 04/08/16 |
+ 2~4 |
+ 64 |
+ 2.1 |
+ |
+ R74 |
+ 385 |
+ 10.00 |
+ 448.16 |
+ 1.98 |
+ 2.12 |
+ 2 |
+ |
+
+
+ | 6 |
+ B6.06 |
+ 040816.04 |
+ C57BL/6J |
+ M |
+ 02/04/16 |
+ 04/08/16 |
+ 2~4 |
+ 64 |
+ 2.1 |
+ |
+ R75 |
+ 226 |
+ 8.70 |
+ 167.31 |
+ 2.04 |
+ 2.13 |
+ 2 |
+ |
+
+
+ | 7 |
+ B6.07 |
+ 041014.19 |
+ C57BL/6J |
+ F |
+ 10/20/13 |
+ 04/10/14 |
+ 5~7 |
+ 172 |
+ 5.7 |
+ |
+ Ret 10 |
+ 22 |
+ 10.0 |
+ 36.97 |
+ 2.22 |
+ 0.051 |
+ 1 |
+ |
+
+
+ | 8 |
+ B6.08 |
+ 101813.27 |
+ C57BL/6J |
+ M |
+ 05/06/13 |
+ 10/18/13 |
+ 5~7 |
+ 165 |
+ 5.5 |
+ |
+ Ret 7 |
+ 38 |
+ 10.0 |
+ 54.47 |
+ 2.08 |
+ 0.094 |
+ 1 |
+ |
+
+
+ | 9 |
+ B6.09 |
+ 050214.03 |
+ C57BL/6J |
+ F |
+ 08/14/13 |
+ 05/02/14 |
+ 7~9 |
+ 261 |
+ 8.7 |
+ |
+ Ret 27 |
+ 20 |
+ 10.0 |
+ 54.45 |
+ 2.11 |
+ 1.14 |
+ 1 |
+ |
+
+
+ | 10 |
+ B6.10 |
+ 041014.24 |
+ C57BL/6J |
+ M |
+ 09/02/13 |
+ 04/10/14 |
+ 7~9 |
+ 220 |
+ 7.3 |
+ |
+ Ret 12 |
+ 38 |
+ 9.50 |
+ 58.97 |
+ 2.08 |
+ 2.14 |
+ 1 |
+ |
+
+
+ | 11 |
+ B6.11 |
+ 101813.17 |
+ C57BL/6J |
+ F |
+ 12/07/12 |
+ 10/18/13 |
+ 10~12 |
+ 315 |
+ 10.5 |
+ |
+ Ret 2 |
+ 59 |
+ 9.40 |
+ 83.86 |
+ 2.17 |
+ 1.87 |
+ 1 |
+ |
+
+
+ | 12 |
+ B6.12 |
+ 052116.01 |
+ C57BL/6J |
+ M |
+ 05/19/15 |
+ 05/22/16 |
+ 10~12 |
+ 369 |
+ 12.3 |
+ |
+ R102 |
+ 293 |
+ 8.30 |
+ 179.69 |
+ 2.06 |
+ 2.11 |
+ 2 |
+ |
+
+
+ | 13 |
+ B6.13 |
+ 052116.02 |
+ C57BL/6J |
+ M |
+ 05/19/15 |
+ 05/22/16 |
+ 10~12 |
+ 369 |
+ 12.3 |
+ |
+ R103 |
+ 255 |
+ 8.40 |
+ 194.24 |
+ 2.04 |
+ 1.82 |
+ 2 |
+ |
+
+
+ | 14 |
+ B6.14 |
+ 042114.19 |
+ C57BL/6J |
+ F |
+ 03/11/13 |
+ 04/21/14 |
+ 13~15 |
+ 406 |
+ 13.5 |
+ 1252 |
+ Ret 26 |
+ 28 |
+ 10.0 |
+ 39.95 |
+ 2.22 |
+ 1.71 |
+ 1 |
+ |
+
+
+ | 15 |
+ B6.15 |
+ 050214.07 |
+ C57BL/6J |
+ M |
+ 03/20/13 |
+ 05/02/14 |
+ 13~15 |
+ 408 |
+ 13.6 |
+ |
+ Ret 28 |
+ 30 |
+ 10.0 |
+ 51.81 |
+ 2.06 |
+ 2.07 |
+ 1 |
+ |
+
+
+ | 16 |
+ B6.16 |
+ 041714.02 |
+ C57BL/6J |
+ M |
+ 09/18/12 |
+ 04/17/14 |
+ 19~21 |
+ 576 |
+ 19.2 |
+ 1117 |
+ Ret 17 |
+ 25 |
+ 10.0 |
+ 51.55 |
+ 2.13 |
+ 1.13 |
+ 1 |
+ |
+
+
+ | 17 |
+ B6.17 |
+ 041714.03 |
+ C57BL/6J |
+ M |
+ 09/18/12 |
+ 04/17/14 |
+ 19~21 |
+ 576 |
+ 19.2 |
+ 1116 |
+ Ret 18 |
+ 28 |
+ 10.0 |
+ 65.11 |
+ 2.01 |
+ 2.16 |
+ 1 |
+ |
+
+
+ | 18 |
+ D2.01 |
+ 030116.02 |
+ DBA/2J |
+ M |
+ 01/29/16 |
+ 03/01/16 |
+ 1~2 |
+ 32 |
+ 1.1 |
+ |
+ R63 |
+ 107 |
+ 8.80 |
+ 119.02 |
+ 2.05 |
+ 1.79 |
+ 2 |
+ |
+
+
+ | 19 |
+ D2.02 |
+ 030116.04 |
+ DBA/2J |
+ M |
+ 01/29/16 |
+ 03/01/16 |
+ 1~2 |
+ 32 |
+ 1.1 |
+ |
+ R65 |
+ 202 |
+ 9.10 |
+ 250.38 |
+ 2.03 |
+ 1.67 |
+ 2 |
+ |
+
+
+ | 20 |
+ D2.03 |
+ 062714.02 |
+ DBA/2J |
+ F |
+ 03/23/14 |
+ 06/27/14 |
+ 2~4 |
+ 104 |
+ 3.5 |
+ |
+ Ret 20a |
+ |
+ |
+ 189.3 |
+ 1.95 |
+ 1.81 |
+ 1 |
+ No Agilent as of 6/27/2014 |
+
+
+ | 21 |
+ D2.04 |
+ 062714.01 |
+ DBA/2J |
+ M |
+ 03/19/14 |
+ 06/27/14 |
+ 2~4 |
+ 100 |
+ 3.3 |
+ |
+ Ret 19a |
+ |
+ |
+ 154 |
+ 2.05 |
+ 1.89 |
+ 1 |
+ No Agilent as of 6/27/2014 |
+
+
+ | 22 |
+ D2.05 |
+ 032316.03 |
+ DBA/2J |
+ M |
+ 01/23/16 |
+ 03/23/16 |
+ 2~4 |
+ 60 |
+ 2.0 |
+ |
+ R70 |
+ 99 |
+ 9.30 |
+ 99.17 |
+ 2.04 |
+ 1.63 |
+ 2 |
+ |
+
+
+ | 23 |
+ D2.06 |
+ 032316.04 |
+ DBA/2J |
+ M |
+ 01/23/16 |
+ 03/23/16 |
+ 2~4 |
+ 60 |
+ 2.0 |
+ |
+ R71 |
+ 205 |
+ 9.10 |
+ 124.33 |
+ 2.03 |
+ 1.24 |
+ 2 |
+ |
+
+
+ | 24 |
+ D2.07 |
+ 050214.11 |
+ DBA/2J |
+ F |
+ 12/07/13 |
+ 05/02/14 |
+ 5~7 |
+ 146 |
+ 4.9 |
+ |
+ Ret 29 |
+ 100 |
+ 10.0 |
+ 86.47 |
+ 2.14 |
+ 1.9 |
+ 1 |
+ |
+
+
+ | 25 |
+ D2.08 |
+ 101813.08 |
+ DBA/2J |
+ M |
+ 03/21/13 |
+ 10/18/13 |
+ 5~7 |
+ 211 |
+ 7.0 |
+ |
+ Ret 1 |
+ 52 |
+ 9.9 |
+ 86.98 |
+ 2.11 |
+ 2.12 |
+ 1 |
+ |
+
+
+ | 26 |
+ D2.09 |
+ 041014.23 |
+ DBA/2J |
+ F |
+ 08/24/13 |
+ 04/10/14 |
+ 7~9 |
+ 229 |
+ 7.6 |
+ |
+ Ret 11 |
+ 21 |
+ 9.9 |
+ 44.39 |
+ 2.17 |
+ 1.15 |
+ 1 |
+ |
+
+
+ | 27 |
+ D2.10 |
+ 050214.15 |
+ DBA/2J |
+ F |
+ 07/27/13 |
+ 05/02/14 |
+ 7~9 |
+ 279 |
+ 9.3 |
+ |
+ Ret 30 |
+ 37 |
+ 10.0 |
+ 43.57 |
+ 2.13 |
+ 2.04 |
+ 1 |
+ |
+
+
+ | 28 |
+ D2.11 |
+ 101813.23 |
+ DBA/2J |
+ F |
+ 11/29/12 |
+ 10/18/13 |
+ 10~12 |
+ 323 |
+ 10.8 |
+ |
+ Ret 6 |
+ 77 |
+ 9.7 |
+ 105.02 |
+ 2.06 |
+ 2.14 |
+ 1 |
+ |
+
+
+ | 29 |
+ D2.12 |
+ 101813.19 |
+ DBA/2J |
+ M |
+ 12/08/12 |
+ 10/18/13 |
+ 10~12 |
+ 314 |
+ 10.5 |
+ |
+ Ret 3 |
+ 46 |
+ 9.9 |
+ 65.7 |
+ 2.13 |
+ 1.71 |
+ 1 |
+ |
+
+
+ | 30 |
+ D2.13 |
+ 042114.18 |
+ DBA/2J |
+ F |
+ 03/19/13 |
+ 04/21/14 |
+ 13~15 |
+ 398 |
+ 13.3 |
+ 1148 |
+ Ret 25 |
+ 26 |
+ 9.9 |
+ 65.53 |
+ 2.17 |
+ 2.43 |
+ 1 |
+ |
+
+
+ | 31 |
+ D2.14 |
+ 042114.17 |
+ DBA/2J |
+ M |
+ 03/19/13 |
+ 04/21/14 |
+ 13~15 |
+ 398 |
+ 13.3 |
+ 1130 |
+ Ret 24 |
+ 40 |
+ 9.4 |
+ 36.98 |
+ 2.07 |
+ 0.8 |
+ 1 |
+ |
+
+
+ | 32 |
+ D2.15 |
+ 041014.06 |
+ DBA/2J |
+ M |
+ 9/6/2012 |
+ 04/10/14 |
+ 19~21 |
+ 581 |
+ 19.4 |
+ 1123 |
+ Ret 8 |
+ 35 |
+ 9.9 |
+ 52.99 |
+ 2.12 |
+ 0.091 |
+ 1 |
+ |
+
+
+ | 33 |
+ D2.16 |
+ 041014.07 |
+ DBA/2J |
+ F |
+ 9/6/2012 |
+ 04/10/14 |
+ 19~21 |
+ 581 |
+ 19.4 |
+ 1124 |
+ Ret 9 |
+ 30 |
+ 9.5 |
+ 52.44 |
+ 2.19 |
+ 0.08 |
+ 1 |
+ |
+
+
+ | 34 |
+ D2GP.01 |
+ 041416.15 |
+ DBA-Gpmnb(wp) |
+ F |
+ 03/15/16 |
+ 04/14/16 |
+ 1~2 |
+ 30 |
+ 1.0 |
+ |
+ R92 |
+ 334 |
+ 9.10 |
+ 135.79 |
+ 1.87 |
+ 2.23 |
+ 2 |
+ |
+
+
+ | 35 |
+ D2GP.02 |
+ 120715.02 |
+ DBA-Gpmnb(wp) |
+ M |
+ 11/05/15 |
+ 12/07/15 |
+ 1~2 |
+ 32 |
+ 1.1 |
+ |
+ R31 |
+ 85 |
+ 9.20 |
+ 106.06 |
+ 2.04 |
+ 2.06 |
+ 2 |
+ |
+
+
+ | 36 |
+ D2GP.03 |
+ 041416.04 |
+ DBA-Gpmnb(wp) |
+ F |
+ 02/02/16 |
+ 04/14/16 |
+ 2~4 |
+ 72 |
+ 2.4 |
+ |
+ R81 |
+ 112 |
+ 9.40 |
+ 94.79 |
+ 1.94 |
+ 2.19 |
+ 2 |
+ |
+
+
+ | 37 |
+ D2GP.04 |
+ 120815.04 |
+ DBA-Gpmnb(wp) |
+ M |
+ 10/08/15 |
+ 12/08/15 |
+ 2~4 |
+ 61 |
+ 2.0 |
+ |
+ R39 |
+ 89 |
+ N/A |
+ 118.84 |
+ 2.05 |
+ 1.97 |
+ 2 |
+ |
+
+
+ | 38 |
+ D2GP.05 |
+ 101813.21 |
+ DBA-Gpmnb(wp) |
+ F |
+ 04/09/13 |
+ 10/18/13 |
+ 5~7 |
+ 192 |
+ 6.4 |
+ |
+ Ret 4 |
+ 53 |
+ 9.9 |
+ 74.13 |
+ 2.14 |
+ 2.28 |
+ 1 |
+ |
+
+
+ | 39 |
+ D2GP.06 |
+ 101813.22 |
+ DBA-Gpmnb(wp) |
+ M |
+ 04/09/13 |
+ 10/18/13 |
+ 5~7 |
+ 192 |
+ 6.4 |
+ |
+ Ret 5 |
+ 54 |
+ 10.0 |
+ 81.32 |
+ 2.1 |
+ 2.19 |
+ 1 |
+ |
+
+
+ | 40 |
+ D2GP.07 |
+ 041014.27 |
+ DBA-Gpmnb(wp) |
+ F |
+ 08/29/13 |
+ 04/10/14 |
+ 7~9 |
+ 224 |
+ 7.5 |
+ |
+ Ret 15 |
+ 14 |
+ 10.0 |
+ 37.03 |
+ 2.06 |
+ 1.44 |
+ 1 |
+ |
+
+
+ | 41 |
+ D2GP.08 |
+ 041014.28 |
+ DBA-Gpmnb(wp) |
+ M |
+ 08/29/13 |
+ 04/10/14 |
+ 7~9 |
+ 224 |
+ 7.5 |
+ |
+ Ret 16 |
+ 29 |
+ 9.9 |
+ 63.83 |
+ 2.03 |
+ 2.08 |
+ 1 |
+ |
+
+
+ | 42 |
+ D2GP.09 |
+ 041014.25 |
+ DBA-Gpmnb(wp) |
+ F |
+ 06/12/13 |
+ 04/10/14 |
+ 10~12 |
+ 302 |
+ 10.1 |
+ |
+ Ret 13 |
+ 31 |
+ 9.8 |
+ 60.73 |
+ 2.07 |
+ 2.12 |
+ 1 |
+ |
+
+
+ | 43 |
+ D2GP.10 |
+ 041014.26 |
+ DBA-Gpmnb(wp) |
+ M |
+ 06/12/13 |
+ 04/10/14 |
+ 10~12 |
+ 302 |
+ 10.1 |
+ |
+ Ret 14 |
+ 24 |
+ 10.0 |
+ 65.1 |
+ 2.06 |
+ 1.09 |
+ 1 |
+ |
+
+
+ | 44 |
+ D2GP.11 |
+ 042114.08 |
+ DBA-Gpmnb(wp) |
+ F |
+ 01/14/13 |
+ 04/21/14 |
+ 13~15 |
+ 462 |
+ 15.4 |
+ 1021 |
+ Ret 22 |
+ 87 |
+ 9.0 |
+ 150.69 |
+ 2.09 |
+ 2.02 |
+ 1 |
+ |
+
+
+ | 45 |
+ D2GP.12 |
+ 042114.09 |
+ DBA-Gpmnb(wp) |
+ F |
+ 01/14/13 |
+ 04/21/14 |
+ 13~15 |
+ 462 |
+ 15.4 |
+ 1022 |
+ Ret 23 |
+ 18 |
+ 10.0 |
+ 44.16 |
+ 2.11 |
+ 0.069 |
+ 1 |
+ |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Uthsc_mm9_b6d2_retex_0916/specifics.rtf b/general/datasets/Uthsc_mm9_b6d2_retex_0916/specifics.rtf
new file mode 100644
index 0000000..7c1a914
--- /dev/null
+++ b/general/datasets/Uthsc_mm9_b6d2_retex_0916/specifics.rtf
@@ -0,0 +1 @@
+Exon Level
\ No newline at end of file
diff --git a/general/datasets/Uthsc_mm9_b6d2_retex_0916/summary.rtf b/general/datasets/Uthsc_mm9_b6d2_retex_0916/summary.rtf
new file mode 100644
index 0000000..de58298
--- /dev/null
+++ b/general/datasets/Uthsc_mm9_b6d2_retex_0916/summary.rtf
@@ -0,0 +1,9 @@
+This is an array data set generated using the Affymetrix Genechip Mouse 1.0 ST array. Please see the companion microRNA (miRNA) data set.
+
+All of these data sets provides estimates of expression for 45 retinas from C57BL/6J (B6 cases B6.01 to B6.17), DBA/2J (cases D2.01 to D2.16), and DBA/2J with a wildtype Gpnmb allele (D2GP.01 to D2GP.12). Cases range in age from 30 to 576 days and include both sexes.
+
+We are using these data in combination with the micro RNA array 4.0 to study normal and glaucomatous changes in gene expression as a function of age.
+
+Please contact Lu Lu (lulu@uthsc.edu), Robert W. Williams (rwilliams@uthsc.edu), or Junming Yue (jyue@uthsc.edu).
+
+Supported in part by Research to Prevent Blindness.
diff --git a/general/datasets/Uthsc_neut_1014/experiment-design.rtf b/general/datasets/Uthsc_neut_1014/experiment-design.rtf
new file mode 100644
index 0000000..eed4905
--- /dev/null
+++ b/general/datasets/Uthsc_neut_1014/experiment-design.rtf
@@ -0,0 +1 @@
+Normal young adults of either sex between 40 and 100 days of age.
diff --git a/general/datasets/Uthsc_neut_1014/summary.rtf b/general/datasets/Uthsc_neut_1014/summary.rtf
new file mode 100644
index 0000000..edd0ac2
--- /dev/null
+++ b/general/datasets/Uthsc_neut_1014/summary.rtf
@@ -0,0 +1 @@
+The data set represents gene expression data from peritoneal neutrophils. Cells were collected four hours after injection of sterile thioglycollate. Purity was assessed by cytospin and nuclear morphology. Usually 4 to 6 animals were used to generate sufficient material for RNA expression analysis.
diff --git a/general/datasets/Uthsc_neut_el_1014/experiment-design.rtf b/general/datasets/Uthsc_neut_el_1014/experiment-design.rtf
new file mode 100644
index 0000000..eed4905
--- /dev/null
+++ b/general/datasets/Uthsc_neut_el_1014/experiment-design.rtf
@@ -0,0 +1 @@
+Normal young adults of either sex between 40 and 100 days of age.
diff --git a/general/datasets/Uthsc_neut_el_1014/summary.rtf b/general/datasets/Uthsc_neut_el_1014/summary.rtf
new file mode 100644
index 0000000..edd0ac2
--- /dev/null
+++ b/general/datasets/Uthsc_neut_el_1014/summary.rtf
@@ -0,0 +1 @@
+The data set represents gene expression data from peritoneal neutrophils. Cells were collected four hours after injection of sterile thioglycollate. Purity was assessed by cytospin and nuclear morphology. Usually 4 to 6 animals were used to generate sufficient material for RNA expression analysis.
diff --git a/general/datasets/Uthsc_spl_rma_1010/cases.rtf b/general/datasets/Uthsc_spl_rma_1010/cases.rtf
new file mode 100644
index 0000000..7fa108f
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1010/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 111 strains, including 81 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1), and 26 other common inbred strains were quantified. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by Lu Lu and colleagues. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. XX strains have matched male and female samples. XX strains have male only samples (BXDX, XX, XX, XXX and XXX). XX strains have only female samples (BXDXX, XX, and XX.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/Uthsc_spl_rma_1010/experiment-design.rtf b/general/datasets/Uthsc_spl_rma_1010/experiment-design.rtf
new file mode 100644
index 0000000..a0aeba6
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1010/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Processing. Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+Array Processing: All arrays were processed by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. The spleen was dissected by both Dr. Lu Lu and colleagues and Dr. Abdeltawab and colleagues. All arrays were run together (interleaved) as a single large batch.
diff --git a/general/datasets/Uthsc_spl_rma_1010/notes.rtf b/general/datasets/Uthsc_spl_rma_1010/notes.rtf
new file mode 100644
index 0000000..c7bb873
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1010/notes.rtf
@@ -0,0 +1,4 @@
+Data Status and Use. This is a provisional release that will soon be replaced by a final corrected data set. In the interim this data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/Uthsc_spl_rma_1010/processing.rtf b/general/datasets/Uthsc_spl_rma_1010/processing.rtf
new file mode 100644
index 0000000..deaf264
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1010/processing.rtf
@@ -0,0 +1,1932 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required some correction for batch effects and the data in this initial release incorporate any additional corrections. There are several additional confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest probe sets in this spleen data set accounts of XX% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the spleen data set can be mapped as a trait.
+
+
+Data Release. This data set was first uploaded into GeneNetwork by Arthur Centeno, October 11, 2010 and made accessible without a password to all users on November 1, 2010. The initial data release had numerous strain identification errors that have now largely been fixed. Based on an analysis of the top 20 Mendelian loci, the following 21 strains were likely to have been incorrectly identified or assigned in the current release:
+
+
+ - BXD8, e.g., Probe set 10450161, 1036098. 10338684
+ - BXD13, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10342568,
+ - BXD21 (may be ok, only one probe set 10338684 is problematic)
+ - BXD23 (may be ok, only two probe sets 10421128, 10419465 is problematic)
+ - BXD36 (may be ok, only one probe set 10421128 is problematic)
+ - BXD40, e.g., Probe set 10341070
+ - BXD43, e.g., Probe set 10450161, 1036098, 10338684
+ - BXD48, e.g., Probe set 1036098, 10402390, 10514896, 10592493, 10357381, 10342568, 10571444, 10419465
+ - BXD62, e.g., Probe set 1036098, 1036098, 10402390, 10514896, 10592493, 10421128, 10571444
+ - BXD68 (may be ok, only one probe set 10338684 is problematic)
+ - BXD69, e.g., Probe set 10450161
+ - BXD73, e.g., Probe set 10341070, 1036098, 10402390, 10514896, 10587633, 10342568, 10421128
+ - BXD74, e.g., Probe set 10402390
+ - BXD80, e.g., Probe set 10341070, 1036098, 10592493, 10400109, 10338684, 10342568, 10421128, 10419465
+ - BXD83, e.g., Probe set 10450161, 10338684
+ - BXD87 (may be ok, only one probe set 10421128 is problematic)
+ - BXD89, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10357381, 10419465
+ - BXD93, e.g., Probe set 10402390, 10357381
+ - BALB/cByJ, e.g., Probe set 10388042, 1036098, 10587633, 10357381, 10342568, 10421128
+ - LP/J, e.g., Probe set 10592493
+ - DBA/2J, e.g., Probe set 10592493
+
+
+Data Evaluation Summary
+
+
+ - Before correction: eQLTs with LOD >10 (LRS>46.1): n = 638
+ - After strain assignment correction: eQLTs with LOD >10 (LRS>46.1): n = 820
+ - Before correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 237.9
+ - After correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 278.1
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
Table 1 (please confirm that these assignments are after correction)
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Phase |
+ Strain |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R5583S |
+ 1 |
+ 129P3/J |
+ 65 |
+ F |
+
+
+ | 2 |
+ R5584S |
+ 1 |
+ 129P3/J |
+ 66 |
+ M |
+
+
+ | 3 |
+ R5585S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+
+
+ | 4 |
+ R5586S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+
+
+ | 5 |
+ R5587S |
+ 1 |
+ 129X1/SvJ |
+ 65 |
+ F |
+
+
+ | 6 |
+ R5588S |
+ 1 |
+ 129X1/SvJ |
+ 66 |
+ M |
+
+
+ | 7 |
+ R6348S |
+ 3 |
+ B6D2F1 |
+ 67 |
+ F |
+
+
+ | 8 |
+ R6347S |
+ 3 |
+ B6D2F1 |
+ 62 |
+ F |
+
+
+ | 9 |
+ R5590S |
+ 1 |
+ B6D2F1 |
+ 79 |
+ M |
+
+
+ | 10 |
+ R5662S |
+ 1 |
+ BALB/cByJ |
+ 59 |
+ F |
+
+
+ | 11 |
+ R5664S |
+ 1 |
+ BALB/cByJ |
+ 59 |
+ M |
+
+
+ | 12 |
+ R5591S |
+ 1 |
+ BALB/cJ |
+ 51 |
+ F |
+
+
+ | 13 |
+ R5592S |
+ 1 |
+ BALB/cJ |
+ 51 |
+ M |
+
+
+ | 14 |
+ R6154S |
+ 2 |
+ BTBR T+ tf/J |
+ 60 |
+ F |
+
+
+ | 15 |
+ R6516S |
+ 3 |
+ BXD1 |
+ 82 |
+ F |
+
+
+ | 16 |
+ R6584S |
+ 3 |
+ BXD1 |
+ 95 |
+ M |
+
+
+ | 17 |
+ R5759S |
+ 1 |
+ BXD2 |
+ N/A |
+ F |
+
+
+ | 18 |
+ R5837S |
+ 1 |
+ BXD2 |
+ 106 |
+ M |
+
+
+ | 19 |
+ R5874S |
+ 2 |
+ BXD5 |
+ 86 |
+ F |
+
+
+ | 20 |
+ R6554S |
+ 3 |
+ BXD5 |
+ 60 |
+ M |
+
+
+ | 21 |
+ R6359S |
+ 3 |
+ BXD6 |
+ 72 |
+ F |
+
+
+ | 22 |
+ R5777S |
+ 1 |
+ BXD6 |
+ 149 |
+ M |
+
+
+ | 23 |
+ R6364S |
+ 3 |
+ BXD8 |
+ 76 |
+ F |
+
+
+ | 24 |
+ R5637S |
+ 1 |
+ BXD8 |
+ 71 |
+ F |
+
+
+ | 25 |
+ R6365S |
+ 3 |
+ BXD8 |
+ 76 |
+ M |
+
+
+ | 26 |
+ R5746S |
+ 1 |
+ BXD9 |
+ 70 |
+ F |
+
+
+ | 27 |
+ R5981S |
+ 2 |
+ BXD9 |
+ 67 |
+ M |
+
+
+ | 28 |
+ R5980S |
+ 2 |
+ BXD9 |
+ 67 |
+ M |
+
+
+ | 29 |
+ R6182S |
+ 2 |
+ BXD11 |
+ 84 |
+ F |
+
+
+ | 30 |
+ R6486S |
+ 3 |
+ BXD11 |
+ 58 |
+ M |
+
+
+ | 31 |
+ R6711S2 |
+ 4 |
+ BXD12 |
+ 71 |
+ F |
+
+
+ | 32 |
+ R6608S |
+ 3 |
+ BXD12 |
+ 48 |
+ F |
+
+
+ | 33 |
+ R5885S |
+ 2 |
+ BXD12 |
+ 44 |
+ M |
+
+
+ | 34 |
+ R5755S |
+ 1 |
+ BXD13 |
+ 160 |
+ F |
+
+
+ | 35 |
+ R5887S |
+ 2 |
+ BXD13 |
+ 53 |
+ M |
+
+
+ | 36 |
+ R6180S |
+ 2 |
+ BXD14 |
+ 70 |
+ F |
+
+
+ | 37 |
+ R5669S |
+ 1 |
+ BXD14 |
+ 91 |
+ M |
+
+
+ | 38 |
+ R6456S |
+ 3 |
+ BXD15 |
+ 60 |
+ F |
+
+
+ | 39 |
+ R6622S |
+ 3 |
+ BXD15 |
+ 60 |
+ F |
+
+
+ | 40 |
+ R6626S |
+ 3 |
+ BXD15 |
+ 60 |
+ M |
+
+
+ | 41 |
+ R6181S |
+ 2 |
+ BXD16 |
+ 74 |
+ F |
+
+
+ | 42 |
+ R6515S |
+ 3 |
+ BXD16 |
+ 64 |
+ M |
+
+
+ | 43 |
+ R5673S |
+ 1 |
+ BXD18 |
+ 80 |
+ F |
+
+
+ | 44 |
+ R5674S |
+ 1 |
+ BXD18 |
+ 65 |
+ M |
+
+
+ | 45 |
+ R6553S |
+ 3 |
+ BXD19 |
+ 158 |
+ F |
+
+
+ | 46 |
+ R6551S |
+ 3 |
+ BXD19 |
+ 60 |
+ M |
+
+
+ | 47 |
+ R6643S4 |
+ 4 |
+ BXD20 |
+ 59 |
+ F |
+
+
+ | 48 |
+ R6595S |
+ 3 |
+ BXD20 |
+ 60 |
+ M |
+
+
+ | 49 |
+ R5735S |
+ 1 |
+ BXD21 |
+ 64 |
+ F |
+
+
+ | 50 |
+ R5892S |
+ 2 |
+ BXD21 |
+ 99 |
+ M |
+
+
+ | 51 |
+ R5896S |
+ 2 |
+ BXD22 |
+ 60 |
+ F |
+
+
+ | 52 |
+ R6414S |
+ 3 |
+ BXD22 |
+ 73 |
+ M |
+
+
+ | 53 |
+ R6550S |
+ 3 |
+ BXD23 |
+ 74 |
+ F |
+
+
+ | 54 |
+ R6586S |
+ 3 |
+ BXD23 |
+ 102 |
+ F |
+
+
+ | 55 |
+ R5630S |
+ 1 |
+ BXD24 |
+ 71 |
+ F |
+
+
+ | 56 |
+ R6356S |
+ 3 |
+ BXD24 |
+ 57 |
+ M |
+
+
+ | 57 |
+ R6162S |
+ 2 |
+ BXD25 |
+ 67 |
+ F |
+
+
+ | 58 |
+ R6625S |
+ 3 |
+ BXD25 |
+ 67 |
+ F |
+
+
+ | 59 |
+ R6642S4 |
+ 4 |
+ BXD25 |
+ 58 |
+ M |
+
+
+ | 60 |
+ R5761S |
+ 1 |
+ BXD27 |
+ N/A |
+ F |
+
+
+ | 61 |
+ R5763S |
+ 1 |
+ BXD27 |
+ 90 |
+ M |
+
+
+ | 62 |
+ R6621S |
+ 3 |
+ BXD28 |
+ 113 |
+ F |
+
+
+ | 63 |
+ R6548S |
+ 3 |
+ BXD28 |
+ 60 |
+ M |
+
+
+ | 64 |
+ R6547S |
+ 3 |
+ BXD29 |
+ 60 |
+ F |
+
+
+ | 65 |
+ R6453S |
+ 3 |
+ BXD31 |
+ 48 |
+ F |
+
+
+ | 66 |
+ R6452S |
+ 3 |
+ BXD31 |
+ 48 |
+ M |
+
+
+ | 67 |
+ R6583S |
+ 3 |
+ BXD32 |
+ 60 |
+ F |
+
+
+ | 68 |
+ R5765S |
+ 1 |
+ BXD32 |
+ 71 |
+ M |
+
+
+ | 69 |
+ R5689S |
+ 1 |
+ BXD33 |
+ 65 |
+ F |
+
+
+ | 70 |
+ R6450S |
+ 3 |
+ BXD33 |
+ 55 |
+ M |
+
+
+ | 71 |
+ R5767S |
+ 1 |
+ BXD34 |
+ 72 |
+ F |
+
+
+ | 72 |
+ R5900S |
+ 2 |
+ BXD34 |
+ 70 |
+ M |
+
+
+ | 73 |
+ R6588S |
+ 3 |
+ BXD36 |
+ 61 |
+ F |
+
+
+ | 74 |
+ R6490S |
+ 3 |
+ BXD36 |
+ 63 |
+ M |
+
+
+ | 75 |
+ R6417S |
+ 3 |
+ BXD38 |
+ 64 |
+ F |
+
+
+ | 76 |
+ R6439S |
+ 3 |
+ BXD38 |
+ 72 |
+ M |
+
+
+ | 77 |
+ R5769S |
+ 1 |
+ BXD39 |
+ N/A |
+ F |
+
+
+ | 78 |
+ R5771S |
+ 1 |
+ BXD39 |
+ 74 |
+ M |
+
+
+ | 79 |
+ R5773S |
+ 1 |
+ BXD40 |
+ N/A |
+ F |
+
+
+ | 80 |
+ R5775S |
+ 1 |
+ BXD40 |
+ N/A |
+ M |
+
+
+ | 81 |
+ R6494S |
+ 3 |
+ BXD41 |
+ 72 |
+ F |
+
+
+ | 82 |
+ R5910S |
+ 2 |
+ BXD42 |
+ 79 |
+ F |
+
+
+ | 83 |
+ R6493S |
+ 3 |
+ BXD42 |
+ 69 |
+ M |
+
+
+ | 84 |
+ R6341S |
+ 3 |
+ BXD43 |
+ 59 |
+ F |
+
+
+ | 85 |
+ R6401S |
+ 3 |
+ BXD43 |
+ 99 |
+ M |
+
+
+ | 86 |
+ R5916S |
+ 2 |
+ BXD43 |
+ 79 |
+ M |
+
+
+ | 87 |
+ R5839S |
+ 1 |
+ BXD44 |
+ 141 |
+ F |
+
+
+ | 88 |
+ R5779S |
+ 1 |
+ BXD44 |
+ 124 |
+ M |
+
+
+ | 89 |
+ R6405S |
+ 3 |
+ BXD45 |
+ 58 |
+ F |
+
+
+ | 90 |
+ R6610S |
+ 3 |
+ BXD45 |
+ 55 |
+ M |
+
+
+ | 91 |
+ R5922S |
+ 2 |
+ BXD48 |
+ 64 |
+ F |
+
+
+ | 92 |
+ R5925S |
+ 2 |
+ BXD48 |
+ 60 |
+ M |
+
+
+ | 93 |
+ R6719S1 |
+ 4 |
+ BXD49 |
+ 58 |
+ F |
+
+
+ | 94 |
+ R6485S |
+ 3 |
+ BXD49 |
+ 79 |
+ M |
+
+
+ | 95 |
+ R5781S |
+ 1 |
+ BXD50 |
+ 61 |
+ F |
+
+
+ | 96 |
+ R6464S |
+ 3 |
+ BXD51 |
+ 65 |
+ F |
+
+
+ | 97 |
+ R6585S |
+ 3 |
+ BXD51 |
+ 63 |
+ M |
+
+
+ | 98 |
+ R6500S |
+ 3 |
+ BXD55 |
+ 58 |
+ F |
+
+
+ | 99 |
+ R5938S |
+ 2 |
+ BXD55 |
+ 93 |
+ M |
+
+
+ | 100 |
+ R6504S |
+ 3 |
+ BXD56 |
+ 58 |
+ F |
+
+
+ | 101 |
+ R6503S |
+ 3 |
+ BXD56 |
+ 58 |
+ M |
+
+
+ | 102 |
+ R5783S |
+ 1 |
+ BXD60 |
+ 111 |
+ F |
+
+
+ | 103 |
+ R5784S |
+ 1 |
+ BXD60 |
+ 85 |
+ M |
+
+
+ | 104 |
+ R5786S |
+ 1 |
+ BXD61 |
+ 86 |
+ F |
+
+
+ | 105 |
+ R6449S |
+ 3 |
+ BXD61 |
+ 65 |
+ M |
+
+
+ | 106 |
+ R6716S1 |
+ 4 |
+ BXD62 |
+ 54 |
+ F |
+
+
+ | 107 |
+ R5790S |
+ 1 |
+ BXD62 |
+ 115 |
+ M |
+
+
+ | 108 |
+ R6519S |
+ 3 |
+ BXD63 |
+ 54 |
+ F |
+
+
+ | 109 |
+ R6717S1 |
+ 4 |
+ BXD63 |
+ 70 |
+ M |
+
+
+ | 110 |
+ R5792S |
+ 1 |
+ BXD64 |
+ 167 |
+ F |
+
+
+ | 111 |
+ R6641S4 |
+ 4 |
+ BXD64 |
+ 68 |
+ M |
+
+
+ | 112 |
+ R6630S |
+ 3 |
+ BXD64 |
+ 68 |
+ M |
+
+
+ | 113 |
+ R6477S |
+ 3 |
+ BXD65 |
+ 58 |
+ F |
+
+
+ | 114 |
+ R6628S |
+ 3 |
+ BXD65 |
+ 70 |
+ M |
+
+
+ | 115 |
+ R6511S |
+ 3 |
+ BXD66 |
+ 70 |
+ F |
+
+
+ | 116 |
+ R6448S |
+ 3 |
+ BXD66 |
+ 61 |
+ M |
+
+
+ | 117 |
+ R5794S |
+ 1 |
+ BXD66 |
+ 144 |
+ M |
+
+
+ | 118 |
+ R6502S |
+ 3 |
+ BXD67 |
+ 66 |
+ F |
+
+
+ | 119 |
+ R6545S |
+ 3 |
+ BXD67 |
+ 61 |
+ M |
+
+
+ | 120 |
+ R6337S |
+ 3 |
+ BXD68 |
+ 56 |
+ F |
+
+
+ | 121 |
+ R6594S |
+ 3 |
+ BXD68 |
+ 64 |
+ M |
+
+
+ | 122 |
+ R5796S |
+ 1 |
+ BXD69 |
+ 85 |
+ F |
+
+
+ | 123 |
+ R5798S |
+ 1 |
+ BXD69 |
+ 98 |
+ M |
+
+
+ | 124 |
+ R6402S |
+ 3 |
+ BXD70 |
+ 93 |
+ F |
+
+
+ | 125 |
+ R5841S |
+ 1 |
+ BXD70 |
+ 121 |
+ F |
+
+
+ | 126 |
+ R6592S |
+ 3 |
+ BXD70 |
+ 59 |
+ M |
+
+
+ | 127 |
+ R6328S |
+ 3 |
+ BXD71 |
+ 87 |
+ F |
+
+
+ | 128 |
+ R5967S |
+ 2 |
+ BXD71 |
+ 64 |
+ M |
+
+
+ | 129 |
+ R5969S |
+ 2 |
+ BXD73 |
+ 64 |
+ F |
+
+
+ | 130 |
+ R5800S |
+ 1 |
+ BXD73 |
+ 120 |
+ M |
+
+
+ | 131 |
+ R6646S |
+ 3 |
+ BXD74 |
+ 40 |
+ F |
+
+
+ | 132 |
+ R6524S |
+ 3 |
+ BXD74 |
+ 72 |
+ M |
+
+
+ | 133 |
+ R6445S |
+ 3 |
+ BXD75 |
+ 85 |
+ F |
+
+
+ | 134 |
+ R5843S |
+ 1 |
+ BXD75 |
+ 103 |
+ F |
+
+
+ | 135 |
+ R5845S |
+ 1 |
+ BXD75 |
+ 103 |
+ M |
+
+
+ | 136 |
+ R6604S |
+ 3 |
+ BXD77 |
+ 64 |
+ F |
+
+
+ | 137 |
+ R6513S |
+ 3 |
+ BXD77 |
+ 72 |
+ M |
+
+
+ | 138 |
+ R6582S |
+ 3 |
+ BXD78 |
+ 144 |
+ F |
+
+
+ | 139 |
+ R6563S |
+ 3 |
+ BXD78 |
+ 95 |
+ M |
+
+
+ | 140 |
+ R6645S4 |
+ 4 |
+ BXD79 |
+ 66 |
+ F |
+
+
+ | 141 |
+ R5806S |
+ 1 |
+ BXD79 |
+ 78 |
+ M |
+
+
+ | 142 |
+ R5847S |
+ 1 |
+ BXD80 |
+ 89 |
+ F |
+
+
+ | 143 |
+ R5852S |
+ 1 |
+ BXD80 |
+ 79 |
+ M |
+
+
+ | 144 |
+ R6562S |
+ 3 |
+ BXD81 |
+ 99 |
+ F |
+
+
+ | 145 |
+ R6468S |
+ 3 |
+ BXD81 |
+ 65 |
+ M |
+
+
+ | 146 |
+ R6560S |
+ 3 |
+ BXD82 |
+ 85 |
+ F |
+
+
+ | 147 |
+ R6512S |
+ 3 |
+ BXD83 |
+ 68 |
+ F |
+
+
+ | 148 |
+ R5810S |
+ 1 |
+ BXD83 |
+ 139 |
+ M |
+
+
+ | 149 |
+ R6510S |
+ 3 |
+ BXD84 |
+ 87 |
+ F |
+
+
+ | 150 |
+ R5970S |
+ 2 |
+ BXD84 |
+ 107 |
+ F |
+
+
+ | 151 |
+ R6603S |
+ 3 |
+ BXD84 |
+ 99 |
+ M |
+
+
+ | 152 |
+ R6517S |
+ 3 |
+ BXD85 |
+ 58 |
+ F |
+
+
+ | 153 |
+ R6718S1 |
+ 4 |
+ BXD85 |
+ 86 |
+ M |
+
+
+ | 154 |
+ R5812S |
+ 1 |
+ BXD86 |
+ 61 |
+ F |
+
+
+ | 155 |
+ R5814S |
+ 1 |
+ BXD86 |
+ 59 |
+ M |
+
+
+ | 156 |
+ R5816S |
+ 1 |
+ BXD87 |
+ 112 |
+ F |
+
+
+ | 157 |
+ R6488S |
+ 3 |
+ BXD87 |
+ 137 |
+ M |
+
+
+ | 158 |
+ R6580S |
+ 3 |
+ BXD88 |
+ 125 |
+ F |
+
+
+ | 159 |
+ R5977S |
+ 2 |
+ BXD89 |
+ 68 |
+ F |
+
+
+ | 160 |
+ R5979S |
+ 2 |
+ BXD89 |
+ 79 |
+ M |
+
+
+ | 161 |
+ R5978S |
+ 2 |
+ BXD89 |
+ 79 |
+ M |
+
+
+ | 162 |
+ R5818S |
+ 1 |
+ BXD90 |
+ 106 |
+ F |
+
+
+ | 163 |
+ R5820S |
+ 1 |
+ BXD90 |
+ 131 |
+ M |
+
+
+ | 164 |
+ R6343S |
+ 3 |
+ BXD92 |
+ 62 |
+ F |
+
+
+ | 165 |
+ R5984S |
+ 2 |
+ BXD92 |
+ 55 |
+ M |
+
+
+ | 166 |
+ R6581S |
+ 3 |
+ BXD93 |
+ 173 |
+ M |
+
+
+ | 167 |
+ R6557S |
+ 3 |
+ BXD93 |
+ 126 |
+ M |
+
+
+ | 168 |
+ R6509S |
+ 3 |
+ BXD95 |
+ 59 |
+ F |
+
+
+ | 169 |
+ R5822S |
+ 1 |
+ BXD95 |
+ 89 |
+ M |
+
+
+ | 170 |
+ R6640S4 |
+ 4 |
+ BXD96 |
+ 70 |
+ F |
+
+
+ | 171 |
+ R6514S |
+ 3 |
+ BXD96 |
+ 64 |
+ M |
+
+
+ | 172 |
+ R6506S |
+ 3 |
+ BXD97 |
+ 78 |
+ F |
+
+
+ | 173 |
+ R5849S |
+ 1 |
+ BXD97 |
+ 130 |
+ F |
+
+
+ | 174 |
+ R6591S |
+ 3 |
+ BXD97 |
+ 122 |
+ M |
+
+
+ | 175 |
+ R5990S |
+ 2 |
+ BXD98 |
+ 65 |
+ F |
+
+
+ | 176 |
+ R6596S |
+ 3 |
+ BXD98 |
+ 67 |
+ M |
+
+
+ | 177 |
+ R5993S |
+ 2 |
+ BXD99 |
+ 74 |
+ F |
+
+
+ | 178 |
+ R5995S |
+ 2 |
+ BXD99 |
+ 50 |
+ M |
+
+
+ | 179 |
+ R6607S |
+ 3 |
+ BXD100 |
+ 75 |
+ F |
+
+
+ | 180 |
+ R6411S |
+ 3 |
+ BXD100 |
+ 104 |
+ M |
+
+
+ | 181 |
+ R6508S |
+ 3 |
+ BXD101 |
+ 59 |
+ F |
+
+
+ | 182 |
+ R5593S |
+ 1 |
+ BXD101 |
+ 59 |
+ M |
+
+
+ | 183 |
+ R6523S |
+ 3 |
+ BXD102 |
+ 60 |
+ F |
+
+
+ | 184 |
+ R6466S |
+ 3 |
+ BXD102 |
+ 50 |
+ M |
+
+
+ | 185 |
+ R6404S |
+ 3 |
+ BXD103 |
+ 72 |
+ F |
+
+
+ | 186 |
+ R6609S |
+ 3 |
+ BXD103 |
+ 57 |
+ M |
+
+
+ | 187 |
+ R6555S |
+ 3 |
+ C57BL/10J |
+ 73 |
+ M |
+
+
+ | 188 |
+ R5596S |
+ 1 |
+ C57BL/10J |
+ 73 |
+ M |
+
+
+ | 189 |
+ R5597S |
+ 1 |
+ C57BL/6ByJ |
+ 51 |
+ F |
+
+
+ | 190 |
+ R5598S |
+ 1 |
+ C57BL/6ByJ |
+ 69 |
+ M |
+
+
+ | 191 |
+ R5600S |
+ 1 |
+ C57BL/6J |
+ 79 |
+ F |
+
+
+ | 192 |
+ R5599S |
+ 1 |
+ C57BL/6J |
+ 60 |
+ F |
+
+
+ | 193 |
+ R6451S |
+ 3 |
+ C57BL/6J |
+ 77 |
+ M |
+
+
+ | 194 |
+ R6410S |
+ 3 |
+ C57BL/6J |
+ 85 |
+ M |
+
+
+ | 195 |
+ R5603S |
+ 1 |
+ C57BLKS/J |
+ 66 |
+ F |
+
+
+ | 196 |
+ R5604S |
+ 1 |
+ C57BLKS/J |
+ 66 |
+ M |
+
+
+ | 197 |
+ R5996S |
+ 2 |
+ CBA/CaJ |
+ 66 |
+ F |
+
+
+ | 198 |
+ R6349S |
+ 3 |
+ CBA/CaJ |
+ 66 |
+ M |
+
+
+ | 199 |
+ R6458S |
+ 3 |
+ D2B6F1 |
+ 64 |
+ F |
+
+
+ | 200 |
+ R6353S |
+ 3 |
+ D2B6F1 |
+ 60 |
+ M |
+
+
+ | 201 |
+ R5605S |
+ 1 |
+ DBA/2J |
+ 79 |
+ F |
+
+
+ | 202 |
+ R6446S |
+ 3 |
+ DBA/2J |
+ 83 |
+ M |
+
+
+ | 203 |
+ R6597S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 204 |
+ R5643S |
+ 1 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 205 |
+ R6598S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ M |
+
+
+ | 206 |
+ R5606S |
+ 1 |
+ ILS |
+ 74 |
+ F |
+
+
+ | 207 |
+ R5607S |
+ 1 |
+ ILS |
+ 74 |
+ M |
+
+
+ | 208 |
+ R5610S |
+ 1 |
+ ISS |
+ 97 |
+ M |
+
+
+ | 209 |
+ R6627S |
+ 3 |
+ KK/HlJ |
+ 64 |
+ F |
+
+
+ | 210 |
+ R6444S |
+ 3 |
+ KK/HlJ |
+ 65 |
+ M |
+
+
+ | 211 |
+ R5702S |
+ 1 |
+ KK/HlJ |
+ 61 |
+ M |
+
+
+ | 212 |
+ R5613S |
+ 1 |
+ LG/J |
+ 63 |
+ F |
+
+
+ | 213 |
+ R5704S |
+ 1 |
+ LG/J |
+ 65 |
+ M |
+
+
+ | 214 |
+ R5614S |
+ 1 |
+ LP/J |
+ 65 |
+ F |
+
+
+ | 215 |
+ R5615S |
+ 1 |
+ LP/J |
+ 65 |
+ M |
+
+
+ | 216 |
+ R6599S |
+ 3 |
+ MOLF/EiJ |
+ 60 |
+ F |
+
+
+ | 217 |
+ R6606S |
+ 3 |
+ MOLF/EiJ |
+ 60 |
+ M |
+
+
+ | 218 |
+ R6544S |
+ 3 |
+ NOD/LtJ |
+ 77 |
+ F |
+
+
+ | 219 |
+ R5709S |
+ 1 |
+ NOD/LtJ |
+ 58 |
+ M |
+
+
+ | 220 |
+ R6601S |
+ 3 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 221 |
+ R5711S |
+ 1 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 222 |
+ R6427S |
+ 3 |
+ NZB/BlNJ |
+ 58 |
+ M |
+
+
+ | 223 |
+ R6150S |
+ 2 |
+ NZO/HlLtJ |
+ 71 |
+ F |
+
+
+ | 224 |
+ R6155S |
+ 2 |
+ NZW/LacJ |
+ 65 |
+ F |
+
+
+ | 225 |
+ R5654S |
+ 1 |
+ NZW/LacJ |
+ 60 |
+ M |
+
+
+ | 226 |
+ R5721S |
+ 1 |
+ PL/J |
+ 59 |
+ M |
+
+
+ | 227 |
+ R5616S |
+ 1 |
+ PWD/PhJ |
+ 60 |
+ M |
+
+
+ | 228 |
+ R5725S |
+ 1 |
+ PWK/PhJ |
+ 121 |
+ M |
+
+
+ | 229 |
+ R6174S |
+ 2 |
+ SJL/J |
+ 63 |
+ F |
+
+
+ | 230 |
+ R6350S |
+ 3 |
+ SJL/J |
+ 65 |
+ M |
+
+
+ | 231 |
+ R6419S |
+ 3 |
+ WSB/EiJ |
+ 60 |
+ F |
+
+
+ | 232 |
+ R5620S |
+ 1 |
+ WSB/EiJ |
+ 60 |
+ M |
+
+
+
+
+ |
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/Uthsc_spl_rma_1010/summary.rtf b/general/datasets/Uthsc_spl_rma_1010/summary.rtf
new file mode 100644
index 0000000..d9478f8
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1010/summary.rtf
@@ -0,0 +1,3 @@
+This is a near final release of a spleen gene expression data set generated by a DOD-funded consortium (Byrne, Kotb, Williams, and Lu). Please contact Lu Lu or Robert Williams regarding status of this data set. The initial data enterted in 2010 had many errors described below. The data set is much improved and has no known errors of strain assignment.
+
+Animals were generated at UTHSC by Lu Lu and colleagues. The spleen of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/Uthsc_spl_rma_1210/cases.rtf b/general/datasets/Uthsc_spl_rma_1210/cases.rtf
new file mode 100644
index 0000000..7fa108f
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 111 strains, including 81 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1), and 26 other common inbred strains were quantified. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by Lu Lu and colleagues. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. XX strains have matched male and female samples. XX strains have male only samples (BXDX, XX, XX, XXX and XXX). XX strains have only female samples (BXDXX, XX, and XX.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/Uthsc_spl_rma_1210/experiment-design.rtf b/general/datasets/Uthsc_spl_rma_1210/experiment-design.rtf
new file mode 100644
index 0000000..a0aeba6
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Processing. Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+Array Processing: All arrays were processed by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. The spleen was dissected by both Dr. Lu Lu and colleagues and Dr. Abdeltawab and colleagues. All arrays were run together (interleaved) as a single large batch.
diff --git a/general/datasets/Uthsc_spl_rma_1210/notes.rtf b/general/datasets/Uthsc_spl_rma_1210/notes.rtf
new file mode 100644
index 0000000..c7bb873
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210/notes.rtf
@@ -0,0 +1,4 @@
+Data Status and Use. This is a provisional release that will soon be replaced by a final corrected data set. In the interim this data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/Uthsc_spl_rma_1210/processing.rtf b/general/datasets/Uthsc_spl_rma_1210/processing.rtf
new file mode 100644
index 0000000..deaf264
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210/processing.rtf
@@ -0,0 +1,1932 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required some correction for batch effects and the data in this initial release incorporate any additional corrections. There are several additional confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest probe sets in this spleen data set accounts of XX% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the spleen data set can be mapped as a trait.
+
+
+Data Release. This data set was first uploaded into GeneNetwork by Arthur Centeno, October 11, 2010 and made accessible without a password to all users on November 1, 2010. The initial data release had numerous strain identification errors that have now largely been fixed. Based on an analysis of the top 20 Mendelian loci, the following 21 strains were likely to have been incorrectly identified or assigned in the current release:
+
+
+ - BXD8, e.g., Probe set 10450161, 1036098. 10338684
+ - BXD13, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10342568,
+ - BXD21 (may be ok, only one probe set 10338684 is problematic)
+ - BXD23 (may be ok, only two probe sets 10421128, 10419465 is problematic)
+ - BXD36 (may be ok, only one probe set 10421128 is problematic)
+ - BXD40, e.g., Probe set 10341070
+ - BXD43, e.g., Probe set 10450161, 1036098, 10338684
+ - BXD48, e.g., Probe set 1036098, 10402390, 10514896, 10592493, 10357381, 10342568, 10571444, 10419465
+ - BXD62, e.g., Probe set 1036098, 1036098, 10402390, 10514896, 10592493, 10421128, 10571444
+ - BXD68 (may be ok, only one probe set 10338684 is problematic)
+ - BXD69, e.g., Probe set 10450161
+ - BXD73, e.g., Probe set 10341070, 1036098, 10402390, 10514896, 10587633, 10342568, 10421128
+ - BXD74, e.g., Probe set 10402390
+ - BXD80, e.g., Probe set 10341070, 1036098, 10592493, 10400109, 10338684, 10342568, 10421128, 10419465
+ - BXD83, e.g., Probe set 10450161, 10338684
+ - BXD87 (may be ok, only one probe set 10421128 is problematic)
+ - BXD89, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10357381, 10419465
+ - BXD93, e.g., Probe set 10402390, 10357381
+ - BALB/cByJ, e.g., Probe set 10388042, 1036098, 10587633, 10357381, 10342568, 10421128
+ - LP/J, e.g., Probe set 10592493
+ - DBA/2J, e.g., Probe set 10592493
+
+
+Data Evaluation Summary
+
+
+ - Before correction: eQLTs with LOD >10 (LRS>46.1): n = 638
+ - After strain assignment correction: eQLTs with LOD >10 (LRS>46.1): n = 820
+ - Before correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 237.9
+ - After correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 278.1
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
Table 1 (please confirm that these assignments are after correction)
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Phase |
+ Strain |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R5583S |
+ 1 |
+ 129P3/J |
+ 65 |
+ F |
+
+
+ | 2 |
+ R5584S |
+ 1 |
+ 129P3/J |
+ 66 |
+ M |
+
+
+ | 3 |
+ R5585S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+
+
+ | 4 |
+ R5586S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+
+
+ | 5 |
+ R5587S |
+ 1 |
+ 129X1/SvJ |
+ 65 |
+ F |
+
+
+ | 6 |
+ R5588S |
+ 1 |
+ 129X1/SvJ |
+ 66 |
+ M |
+
+
+ | 7 |
+ R6348S |
+ 3 |
+ B6D2F1 |
+ 67 |
+ F |
+
+
+ | 8 |
+ R6347S |
+ 3 |
+ B6D2F1 |
+ 62 |
+ F |
+
+
+ | 9 |
+ R5590S |
+ 1 |
+ B6D2F1 |
+ 79 |
+ M |
+
+
+ | 10 |
+ R5662S |
+ 1 |
+ BALB/cByJ |
+ 59 |
+ F |
+
+
+ | 11 |
+ R5664S |
+ 1 |
+ BALB/cByJ |
+ 59 |
+ M |
+
+
+ | 12 |
+ R5591S |
+ 1 |
+ BALB/cJ |
+ 51 |
+ F |
+
+
+ | 13 |
+ R5592S |
+ 1 |
+ BALB/cJ |
+ 51 |
+ M |
+
+
+ | 14 |
+ R6154S |
+ 2 |
+ BTBR T+ tf/J |
+ 60 |
+ F |
+
+
+ | 15 |
+ R6516S |
+ 3 |
+ BXD1 |
+ 82 |
+ F |
+
+
+ | 16 |
+ R6584S |
+ 3 |
+ BXD1 |
+ 95 |
+ M |
+
+
+ | 17 |
+ R5759S |
+ 1 |
+ BXD2 |
+ N/A |
+ F |
+
+
+ | 18 |
+ R5837S |
+ 1 |
+ BXD2 |
+ 106 |
+ M |
+
+
+ | 19 |
+ R5874S |
+ 2 |
+ BXD5 |
+ 86 |
+ F |
+
+
+ | 20 |
+ R6554S |
+ 3 |
+ BXD5 |
+ 60 |
+ M |
+
+
+ | 21 |
+ R6359S |
+ 3 |
+ BXD6 |
+ 72 |
+ F |
+
+
+ | 22 |
+ R5777S |
+ 1 |
+ BXD6 |
+ 149 |
+ M |
+
+
+ | 23 |
+ R6364S |
+ 3 |
+ BXD8 |
+ 76 |
+ F |
+
+
+ | 24 |
+ R5637S |
+ 1 |
+ BXD8 |
+ 71 |
+ F |
+
+
+ | 25 |
+ R6365S |
+ 3 |
+ BXD8 |
+ 76 |
+ M |
+
+
+ | 26 |
+ R5746S |
+ 1 |
+ BXD9 |
+ 70 |
+ F |
+
+
+ | 27 |
+ R5981S |
+ 2 |
+ BXD9 |
+ 67 |
+ M |
+
+
+ | 28 |
+ R5980S |
+ 2 |
+ BXD9 |
+ 67 |
+ M |
+
+
+ | 29 |
+ R6182S |
+ 2 |
+ BXD11 |
+ 84 |
+ F |
+
+
+ | 30 |
+ R6486S |
+ 3 |
+ BXD11 |
+ 58 |
+ M |
+
+
+ | 31 |
+ R6711S2 |
+ 4 |
+ BXD12 |
+ 71 |
+ F |
+
+
+ | 32 |
+ R6608S |
+ 3 |
+ BXD12 |
+ 48 |
+ F |
+
+
+ | 33 |
+ R5885S |
+ 2 |
+ BXD12 |
+ 44 |
+ M |
+
+
+ | 34 |
+ R5755S |
+ 1 |
+ BXD13 |
+ 160 |
+ F |
+
+
+ | 35 |
+ R5887S |
+ 2 |
+ BXD13 |
+ 53 |
+ M |
+
+
+ | 36 |
+ R6180S |
+ 2 |
+ BXD14 |
+ 70 |
+ F |
+
+
+ | 37 |
+ R5669S |
+ 1 |
+ BXD14 |
+ 91 |
+ M |
+
+
+ | 38 |
+ R6456S |
+ 3 |
+ BXD15 |
+ 60 |
+ F |
+
+
+ | 39 |
+ R6622S |
+ 3 |
+ BXD15 |
+ 60 |
+ F |
+
+
+ | 40 |
+ R6626S |
+ 3 |
+ BXD15 |
+ 60 |
+ M |
+
+
+ | 41 |
+ R6181S |
+ 2 |
+ BXD16 |
+ 74 |
+ F |
+
+
+ | 42 |
+ R6515S |
+ 3 |
+ BXD16 |
+ 64 |
+ M |
+
+
+ | 43 |
+ R5673S |
+ 1 |
+ BXD18 |
+ 80 |
+ F |
+
+
+ | 44 |
+ R5674S |
+ 1 |
+ BXD18 |
+ 65 |
+ M |
+
+
+ | 45 |
+ R6553S |
+ 3 |
+ BXD19 |
+ 158 |
+ F |
+
+
+ | 46 |
+ R6551S |
+ 3 |
+ BXD19 |
+ 60 |
+ M |
+
+
+ | 47 |
+ R6643S4 |
+ 4 |
+ BXD20 |
+ 59 |
+ F |
+
+
+ | 48 |
+ R6595S |
+ 3 |
+ BXD20 |
+ 60 |
+ M |
+
+
+ | 49 |
+ R5735S |
+ 1 |
+ BXD21 |
+ 64 |
+ F |
+
+
+ | 50 |
+ R5892S |
+ 2 |
+ BXD21 |
+ 99 |
+ M |
+
+
+ | 51 |
+ R5896S |
+ 2 |
+ BXD22 |
+ 60 |
+ F |
+
+
+ | 52 |
+ R6414S |
+ 3 |
+ BXD22 |
+ 73 |
+ M |
+
+
+ | 53 |
+ R6550S |
+ 3 |
+ BXD23 |
+ 74 |
+ F |
+
+
+ | 54 |
+ R6586S |
+ 3 |
+ BXD23 |
+ 102 |
+ F |
+
+
+ | 55 |
+ R5630S |
+ 1 |
+ BXD24 |
+ 71 |
+ F |
+
+
+ | 56 |
+ R6356S |
+ 3 |
+ BXD24 |
+ 57 |
+ M |
+
+
+ | 57 |
+ R6162S |
+ 2 |
+ BXD25 |
+ 67 |
+ F |
+
+
+ | 58 |
+ R6625S |
+ 3 |
+ BXD25 |
+ 67 |
+ F |
+
+
+ | 59 |
+ R6642S4 |
+ 4 |
+ BXD25 |
+ 58 |
+ M |
+
+
+ | 60 |
+ R5761S |
+ 1 |
+ BXD27 |
+ N/A |
+ F |
+
+
+ | 61 |
+ R5763S |
+ 1 |
+ BXD27 |
+ 90 |
+ M |
+
+
+ | 62 |
+ R6621S |
+ 3 |
+ BXD28 |
+ 113 |
+ F |
+
+
+ | 63 |
+ R6548S |
+ 3 |
+ BXD28 |
+ 60 |
+ M |
+
+
+ | 64 |
+ R6547S |
+ 3 |
+ BXD29 |
+ 60 |
+ F |
+
+
+ | 65 |
+ R6453S |
+ 3 |
+ BXD31 |
+ 48 |
+ F |
+
+
+ | 66 |
+ R6452S |
+ 3 |
+ BXD31 |
+ 48 |
+ M |
+
+
+ | 67 |
+ R6583S |
+ 3 |
+ BXD32 |
+ 60 |
+ F |
+
+
+ | 68 |
+ R5765S |
+ 1 |
+ BXD32 |
+ 71 |
+ M |
+
+
+ | 69 |
+ R5689S |
+ 1 |
+ BXD33 |
+ 65 |
+ F |
+
+
+ | 70 |
+ R6450S |
+ 3 |
+ BXD33 |
+ 55 |
+ M |
+
+
+ | 71 |
+ R5767S |
+ 1 |
+ BXD34 |
+ 72 |
+ F |
+
+
+ | 72 |
+ R5900S |
+ 2 |
+ BXD34 |
+ 70 |
+ M |
+
+
+ | 73 |
+ R6588S |
+ 3 |
+ BXD36 |
+ 61 |
+ F |
+
+
+ | 74 |
+ R6490S |
+ 3 |
+ BXD36 |
+ 63 |
+ M |
+
+
+ | 75 |
+ R6417S |
+ 3 |
+ BXD38 |
+ 64 |
+ F |
+
+
+ | 76 |
+ R6439S |
+ 3 |
+ BXD38 |
+ 72 |
+ M |
+
+
+ | 77 |
+ R5769S |
+ 1 |
+ BXD39 |
+ N/A |
+ F |
+
+
+ | 78 |
+ R5771S |
+ 1 |
+ BXD39 |
+ 74 |
+ M |
+
+
+ | 79 |
+ R5773S |
+ 1 |
+ BXD40 |
+ N/A |
+ F |
+
+
+ | 80 |
+ R5775S |
+ 1 |
+ BXD40 |
+ N/A |
+ M |
+
+
+ | 81 |
+ R6494S |
+ 3 |
+ BXD41 |
+ 72 |
+ F |
+
+
+ | 82 |
+ R5910S |
+ 2 |
+ BXD42 |
+ 79 |
+ F |
+
+
+ | 83 |
+ R6493S |
+ 3 |
+ BXD42 |
+ 69 |
+ M |
+
+
+ | 84 |
+ R6341S |
+ 3 |
+ BXD43 |
+ 59 |
+ F |
+
+
+ | 85 |
+ R6401S |
+ 3 |
+ BXD43 |
+ 99 |
+ M |
+
+
+ | 86 |
+ R5916S |
+ 2 |
+ BXD43 |
+ 79 |
+ M |
+
+
+ | 87 |
+ R5839S |
+ 1 |
+ BXD44 |
+ 141 |
+ F |
+
+
+ | 88 |
+ R5779S |
+ 1 |
+ BXD44 |
+ 124 |
+ M |
+
+
+ | 89 |
+ R6405S |
+ 3 |
+ BXD45 |
+ 58 |
+ F |
+
+
+ | 90 |
+ R6610S |
+ 3 |
+ BXD45 |
+ 55 |
+ M |
+
+
+ | 91 |
+ R5922S |
+ 2 |
+ BXD48 |
+ 64 |
+ F |
+
+
+ | 92 |
+ R5925S |
+ 2 |
+ BXD48 |
+ 60 |
+ M |
+
+
+ | 93 |
+ R6719S1 |
+ 4 |
+ BXD49 |
+ 58 |
+ F |
+
+
+ | 94 |
+ R6485S |
+ 3 |
+ BXD49 |
+ 79 |
+ M |
+
+
+ | 95 |
+ R5781S |
+ 1 |
+ BXD50 |
+ 61 |
+ F |
+
+
+ | 96 |
+ R6464S |
+ 3 |
+ BXD51 |
+ 65 |
+ F |
+
+
+ | 97 |
+ R6585S |
+ 3 |
+ BXD51 |
+ 63 |
+ M |
+
+
+ | 98 |
+ R6500S |
+ 3 |
+ BXD55 |
+ 58 |
+ F |
+
+
+ | 99 |
+ R5938S |
+ 2 |
+ BXD55 |
+ 93 |
+ M |
+
+
+ | 100 |
+ R6504S |
+ 3 |
+ BXD56 |
+ 58 |
+ F |
+
+
+ | 101 |
+ R6503S |
+ 3 |
+ BXD56 |
+ 58 |
+ M |
+
+
+ | 102 |
+ R5783S |
+ 1 |
+ BXD60 |
+ 111 |
+ F |
+
+
+ | 103 |
+ R5784S |
+ 1 |
+ BXD60 |
+ 85 |
+ M |
+
+
+ | 104 |
+ R5786S |
+ 1 |
+ BXD61 |
+ 86 |
+ F |
+
+
+ | 105 |
+ R6449S |
+ 3 |
+ BXD61 |
+ 65 |
+ M |
+
+
+ | 106 |
+ R6716S1 |
+ 4 |
+ BXD62 |
+ 54 |
+ F |
+
+
+ | 107 |
+ R5790S |
+ 1 |
+ BXD62 |
+ 115 |
+ M |
+
+
+ | 108 |
+ R6519S |
+ 3 |
+ BXD63 |
+ 54 |
+ F |
+
+
+ | 109 |
+ R6717S1 |
+ 4 |
+ BXD63 |
+ 70 |
+ M |
+
+
+ | 110 |
+ R5792S |
+ 1 |
+ BXD64 |
+ 167 |
+ F |
+
+
+ | 111 |
+ R6641S4 |
+ 4 |
+ BXD64 |
+ 68 |
+ M |
+
+
+ | 112 |
+ R6630S |
+ 3 |
+ BXD64 |
+ 68 |
+ M |
+
+
+ | 113 |
+ R6477S |
+ 3 |
+ BXD65 |
+ 58 |
+ F |
+
+
+ | 114 |
+ R6628S |
+ 3 |
+ BXD65 |
+ 70 |
+ M |
+
+
+ | 115 |
+ R6511S |
+ 3 |
+ BXD66 |
+ 70 |
+ F |
+
+
+ | 116 |
+ R6448S |
+ 3 |
+ BXD66 |
+ 61 |
+ M |
+
+
+ | 117 |
+ R5794S |
+ 1 |
+ BXD66 |
+ 144 |
+ M |
+
+
+ | 118 |
+ R6502S |
+ 3 |
+ BXD67 |
+ 66 |
+ F |
+
+
+ | 119 |
+ R6545S |
+ 3 |
+ BXD67 |
+ 61 |
+ M |
+
+
+ | 120 |
+ R6337S |
+ 3 |
+ BXD68 |
+ 56 |
+ F |
+
+
+ | 121 |
+ R6594S |
+ 3 |
+ BXD68 |
+ 64 |
+ M |
+
+
+ | 122 |
+ R5796S |
+ 1 |
+ BXD69 |
+ 85 |
+ F |
+
+
+ | 123 |
+ R5798S |
+ 1 |
+ BXD69 |
+ 98 |
+ M |
+
+
+ | 124 |
+ R6402S |
+ 3 |
+ BXD70 |
+ 93 |
+ F |
+
+
+ | 125 |
+ R5841S |
+ 1 |
+ BXD70 |
+ 121 |
+ F |
+
+
+ | 126 |
+ R6592S |
+ 3 |
+ BXD70 |
+ 59 |
+ M |
+
+
+ | 127 |
+ R6328S |
+ 3 |
+ BXD71 |
+ 87 |
+ F |
+
+
+ | 128 |
+ R5967S |
+ 2 |
+ BXD71 |
+ 64 |
+ M |
+
+
+ | 129 |
+ R5969S |
+ 2 |
+ BXD73 |
+ 64 |
+ F |
+
+
+ | 130 |
+ R5800S |
+ 1 |
+ BXD73 |
+ 120 |
+ M |
+
+
+ | 131 |
+ R6646S |
+ 3 |
+ BXD74 |
+ 40 |
+ F |
+
+
+ | 132 |
+ R6524S |
+ 3 |
+ BXD74 |
+ 72 |
+ M |
+
+
+ | 133 |
+ R6445S |
+ 3 |
+ BXD75 |
+ 85 |
+ F |
+
+
+ | 134 |
+ R5843S |
+ 1 |
+ BXD75 |
+ 103 |
+ F |
+
+
+ | 135 |
+ R5845S |
+ 1 |
+ BXD75 |
+ 103 |
+ M |
+
+
+ | 136 |
+ R6604S |
+ 3 |
+ BXD77 |
+ 64 |
+ F |
+
+
+ | 137 |
+ R6513S |
+ 3 |
+ BXD77 |
+ 72 |
+ M |
+
+
+ | 138 |
+ R6582S |
+ 3 |
+ BXD78 |
+ 144 |
+ F |
+
+
+ | 139 |
+ R6563S |
+ 3 |
+ BXD78 |
+ 95 |
+ M |
+
+
+ | 140 |
+ R6645S4 |
+ 4 |
+ BXD79 |
+ 66 |
+ F |
+
+
+ | 141 |
+ R5806S |
+ 1 |
+ BXD79 |
+ 78 |
+ M |
+
+
+ | 142 |
+ R5847S |
+ 1 |
+ BXD80 |
+ 89 |
+ F |
+
+
+ | 143 |
+ R5852S |
+ 1 |
+ BXD80 |
+ 79 |
+ M |
+
+
+ | 144 |
+ R6562S |
+ 3 |
+ BXD81 |
+ 99 |
+ F |
+
+
+ | 145 |
+ R6468S |
+ 3 |
+ BXD81 |
+ 65 |
+ M |
+
+
+ | 146 |
+ R6560S |
+ 3 |
+ BXD82 |
+ 85 |
+ F |
+
+
+ | 147 |
+ R6512S |
+ 3 |
+ BXD83 |
+ 68 |
+ F |
+
+
+ | 148 |
+ R5810S |
+ 1 |
+ BXD83 |
+ 139 |
+ M |
+
+
+ | 149 |
+ R6510S |
+ 3 |
+ BXD84 |
+ 87 |
+ F |
+
+
+ | 150 |
+ R5970S |
+ 2 |
+ BXD84 |
+ 107 |
+ F |
+
+
+ | 151 |
+ R6603S |
+ 3 |
+ BXD84 |
+ 99 |
+ M |
+
+
+ | 152 |
+ R6517S |
+ 3 |
+ BXD85 |
+ 58 |
+ F |
+
+
+ | 153 |
+ R6718S1 |
+ 4 |
+ BXD85 |
+ 86 |
+ M |
+
+
+ | 154 |
+ R5812S |
+ 1 |
+ BXD86 |
+ 61 |
+ F |
+
+
+ | 155 |
+ R5814S |
+ 1 |
+ BXD86 |
+ 59 |
+ M |
+
+
+ | 156 |
+ R5816S |
+ 1 |
+ BXD87 |
+ 112 |
+ F |
+
+
+ | 157 |
+ R6488S |
+ 3 |
+ BXD87 |
+ 137 |
+ M |
+
+
+ | 158 |
+ R6580S |
+ 3 |
+ BXD88 |
+ 125 |
+ F |
+
+
+ | 159 |
+ R5977S |
+ 2 |
+ BXD89 |
+ 68 |
+ F |
+
+
+ | 160 |
+ R5979S |
+ 2 |
+ BXD89 |
+ 79 |
+ M |
+
+
+ | 161 |
+ R5978S |
+ 2 |
+ BXD89 |
+ 79 |
+ M |
+
+
+ | 162 |
+ R5818S |
+ 1 |
+ BXD90 |
+ 106 |
+ F |
+
+
+ | 163 |
+ R5820S |
+ 1 |
+ BXD90 |
+ 131 |
+ M |
+
+
+ | 164 |
+ R6343S |
+ 3 |
+ BXD92 |
+ 62 |
+ F |
+
+
+ | 165 |
+ R5984S |
+ 2 |
+ BXD92 |
+ 55 |
+ M |
+
+
+ | 166 |
+ R6581S |
+ 3 |
+ BXD93 |
+ 173 |
+ M |
+
+
+ | 167 |
+ R6557S |
+ 3 |
+ BXD93 |
+ 126 |
+ M |
+
+
+ | 168 |
+ R6509S |
+ 3 |
+ BXD95 |
+ 59 |
+ F |
+
+
+ | 169 |
+ R5822S |
+ 1 |
+ BXD95 |
+ 89 |
+ M |
+
+
+ | 170 |
+ R6640S4 |
+ 4 |
+ BXD96 |
+ 70 |
+ F |
+
+
+ | 171 |
+ R6514S |
+ 3 |
+ BXD96 |
+ 64 |
+ M |
+
+
+ | 172 |
+ R6506S |
+ 3 |
+ BXD97 |
+ 78 |
+ F |
+
+
+ | 173 |
+ R5849S |
+ 1 |
+ BXD97 |
+ 130 |
+ F |
+
+
+ | 174 |
+ R6591S |
+ 3 |
+ BXD97 |
+ 122 |
+ M |
+
+
+ | 175 |
+ R5990S |
+ 2 |
+ BXD98 |
+ 65 |
+ F |
+
+
+ | 176 |
+ R6596S |
+ 3 |
+ BXD98 |
+ 67 |
+ M |
+
+
+ | 177 |
+ R5993S |
+ 2 |
+ BXD99 |
+ 74 |
+ F |
+
+
+ | 178 |
+ R5995S |
+ 2 |
+ BXD99 |
+ 50 |
+ M |
+
+
+ | 179 |
+ R6607S |
+ 3 |
+ BXD100 |
+ 75 |
+ F |
+
+
+ | 180 |
+ R6411S |
+ 3 |
+ BXD100 |
+ 104 |
+ M |
+
+
+ | 181 |
+ R6508S |
+ 3 |
+ BXD101 |
+ 59 |
+ F |
+
+
+ | 182 |
+ R5593S |
+ 1 |
+ BXD101 |
+ 59 |
+ M |
+
+
+ | 183 |
+ R6523S |
+ 3 |
+ BXD102 |
+ 60 |
+ F |
+
+
+ | 184 |
+ R6466S |
+ 3 |
+ BXD102 |
+ 50 |
+ M |
+
+
+ | 185 |
+ R6404S |
+ 3 |
+ BXD103 |
+ 72 |
+ F |
+
+
+ | 186 |
+ R6609S |
+ 3 |
+ BXD103 |
+ 57 |
+ M |
+
+
+ | 187 |
+ R6555S |
+ 3 |
+ C57BL/10J |
+ 73 |
+ M |
+
+
+ | 188 |
+ R5596S |
+ 1 |
+ C57BL/10J |
+ 73 |
+ M |
+
+
+ | 189 |
+ R5597S |
+ 1 |
+ C57BL/6ByJ |
+ 51 |
+ F |
+
+
+ | 190 |
+ R5598S |
+ 1 |
+ C57BL/6ByJ |
+ 69 |
+ M |
+
+
+ | 191 |
+ R5600S |
+ 1 |
+ C57BL/6J |
+ 79 |
+ F |
+
+
+ | 192 |
+ R5599S |
+ 1 |
+ C57BL/6J |
+ 60 |
+ F |
+
+
+ | 193 |
+ R6451S |
+ 3 |
+ C57BL/6J |
+ 77 |
+ M |
+
+
+ | 194 |
+ R6410S |
+ 3 |
+ C57BL/6J |
+ 85 |
+ M |
+
+
+ | 195 |
+ R5603S |
+ 1 |
+ C57BLKS/J |
+ 66 |
+ F |
+
+
+ | 196 |
+ R5604S |
+ 1 |
+ C57BLKS/J |
+ 66 |
+ M |
+
+
+ | 197 |
+ R5996S |
+ 2 |
+ CBA/CaJ |
+ 66 |
+ F |
+
+
+ | 198 |
+ R6349S |
+ 3 |
+ CBA/CaJ |
+ 66 |
+ M |
+
+
+ | 199 |
+ R6458S |
+ 3 |
+ D2B6F1 |
+ 64 |
+ F |
+
+
+ | 200 |
+ R6353S |
+ 3 |
+ D2B6F1 |
+ 60 |
+ M |
+
+
+ | 201 |
+ R5605S |
+ 1 |
+ DBA/2J |
+ 79 |
+ F |
+
+
+ | 202 |
+ R6446S |
+ 3 |
+ DBA/2J |
+ 83 |
+ M |
+
+
+ | 203 |
+ R6597S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 204 |
+ R5643S |
+ 1 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 205 |
+ R6598S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ M |
+
+
+ | 206 |
+ R5606S |
+ 1 |
+ ILS |
+ 74 |
+ F |
+
+
+ | 207 |
+ R5607S |
+ 1 |
+ ILS |
+ 74 |
+ M |
+
+
+ | 208 |
+ R5610S |
+ 1 |
+ ISS |
+ 97 |
+ M |
+
+
+ | 209 |
+ R6627S |
+ 3 |
+ KK/HlJ |
+ 64 |
+ F |
+
+
+ | 210 |
+ R6444S |
+ 3 |
+ KK/HlJ |
+ 65 |
+ M |
+
+
+ | 211 |
+ R5702S |
+ 1 |
+ KK/HlJ |
+ 61 |
+ M |
+
+
+ | 212 |
+ R5613S |
+ 1 |
+ LG/J |
+ 63 |
+ F |
+
+
+ | 213 |
+ R5704S |
+ 1 |
+ LG/J |
+ 65 |
+ M |
+
+
+ | 214 |
+ R5614S |
+ 1 |
+ LP/J |
+ 65 |
+ F |
+
+
+ | 215 |
+ R5615S |
+ 1 |
+ LP/J |
+ 65 |
+ M |
+
+
+ | 216 |
+ R6599S |
+ 3 |
+ MOLF/EiJ |
+ 60 |
+ F |
+
+
+ | 217 |
+ R6606S |
+ 3 |
+ MOLF/EiJ |
+ 60 |
+ M |
+
+
+ | 218 |
+ R6544S |
+ 3 |
+ NOD/LtJ |
+ 77 |
+ F |
+
+
+ | 219 |
+ R5709S |
+ 1 |
+ NOD/LtJ |
+ 58 |
+ M |
+
+
+ | 220 |
+ R6601S |
+ 3 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 221 |
+ R5711S |
+ 1 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 222 |
+ R6427S |
+ 3 |
+ NZB/BlNJ |
+ 58 |
+ M |
+
+
+ | 223 |
+ R6150S |
+ 2 |
+ NZO/HlLtJ |
+ 71 |
+ F |
+
+
+ | 224 |
+ R6155S |
+ 2 |
+ NZW/LacJ |
+ 65 |
+ F |
+
+
+ | 225 |
+ R5654S |
+ 1 |
+ NZW/LacJ |
+ 60 |
+ M |
+
+
+ | 226 |
+ R5721S |
+ 1 |
+ PL/J |
+ 59 |
+ M |
+
+
+ | 227 |
+ R5616S |
+ 1 |
+ PWD/PhJ |
+ 60 |
+ M |
+
+
+ | 228 |
+ R5725S |
+ 1 |
+ PWK/PhJ |
+ 121 |
+ M |
+
+
+ | 229 |
+ R6174S |
+ 2 |
+ SJL/J |
+ 63 |
+ F |
+
+
+ | 230 |
+ R6350S |
+ 3 |
+ SJL/J |
+ 65 |
+ M |
+
+
+ | 231 |
+ R6419S |
+ 3 |
+ WSB/EiJ |
+ 60 |
+ F |
+
+
+ | 232 |
+ R5620S |
+ 1 |
+ WSB/EiJ |
+ 60 |
+ M |
+
+
+
+
+ |
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/Uthsc_spl_rma_1210/summary.rtf b/general/datasets/Uthsc_spl_rma_1210/summary.rtf
new file mode 100644
index 0000000..d9478f8
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210/summary.rtf
@@ -0,0 +1,3 @@
+This is a near final release of a spleen gene expression data set generated by a DOD-funded consortium (Byrne, Kotb, Williams, and Lu). Please contact Lu Lu or Robert Williams regarding status of this data set. The initial data enterted in 2010 had many errors described below. The data set is much improved and has no known errors of strain assignment.
+
+Animals were generated at UTHSC by Lu Lu and colleagues. The spleen of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/Uthsc_spl_rma_1210f/cases.rtf b/general/datasets/Uthsc_spl_rma_1210f/cases.rtf
new file mode 100644
index 0000000..7fa108f
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210f/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 111 strains, including 81 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1), and 26 other common inbred strains were quantified. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by Lu Lu and colleagues. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. XX strains have matched male and female samples. XX strains have male only samples (BXDX, XX, XX, XXX and XXX). XX strains have only female samples (BXDXX, XX, and XX.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/Uthsc_spl_rma_1210f/experiment-design.rtf b/general/datasets/Uthsc_spl_rma_1210f/experiment-design.rtf
new file mode 100644
index 0000000..a0aeba6
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210f/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Processing. Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+Array Processing: All arrays were processed by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. The spleen was dissected by both Dr. Lu Lu and colleagues and Dr. Abdeltawab and colleagues. All arrays were run together (interleaved) as a single large batch.
diff --git a/general/datasets/Uthsc_spl_rma_1210f/experiment-type.rtf b/general/datasets/Uthsc_spl_rma_1210f/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210f/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Uthsc_spl_rma_1210f/notes.rtf b/general/datasets/Uthsc_spl_rma_1210f/notes.rtf
new file mode 100644
index 0000000..c7bb873
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210f/notes.rtf
@@ -0,0 +1,4 @@
+Data Status and Use. This is a provisional release that will soon be replaced by a final corrected data set. In the interim this data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/Uthsc_spl_rma_1210f/processing.rtf b/general/datasets/Uthsc_spl_rma_1210f/processing.rtf
new file mode 100644
index 0000000..deaf264
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210f/processing.rtf
@@ -0,0 +1,1932 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required some correction for batch effects and the data in this initial release incorporate any additional corrections. There are several additional confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest probe sets in this spleen data set accounts of XX% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the spleen data set can be mapped as a trait.
+
+
+Data Release. This data set was first uploaded into GeneNetwork by Arthur Centeno, October 11, 2010 and made accessible without a password to all users on November 1, 2010. The initial data release had numerous strain identification errors that have now largely been fixed. Based on an analysis of the top 20 Mendelian loci, the following 21 strains were likely to have been incorrectly identified or assigned in the current release:
+
+
+ - BXD8, e.g., Probe set 10450161, 1036098. 10338684
+ - BXD13, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10342568,
+ - BXD21 (may be ok, only one probe set 10338684 is problematic)
+ - BXD23 (may be ok, only two probe sets 10421128, 10419465 is problematic)
+ - BXD36 (may be ok, only one probe set 10421128 is problematic)
+ - BXD40, e.g., Probe set 10341070
+ - BXD43, e.g., Probe set 10450161, 1036098, 10338684
+ - BXD48, e.g., Probe set 1036098, 10402390, 10514896, 10592493, 10357381, 10342568, 10571444, 10419465
+ - BXD62, e.g., Probe set 1036098, 1036098, 10402390, 10514896, 10592493, 10421128, 10571444
+ - BXD68 (may be ok, only one probe set 10338684 is problematic)
+ - BXD69, e.g., Probe set 10450161
+ - BXD73, e.g., Probe set 10341070, 1036098, 10402390, 10514896, 10587633, 10342568, 10421128
+ - BXD74, e.g., Probe set 10402390
+ - BXD80, e.g., Probe set 10341070, 1036098, 10592493, 10400109, 10338684, 10342568, 10421128, 10419465
+ - BXD83, e.g., Probe set 10450161, 10338684
+ - BXD87 (may be ok, only one probe set 10421128 is problematic)
+ - BXD89, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10357381, 10419465
+ - BXD93, e.g., Probe set 10402390, 10357381
+ - BALB/cByJ, e.g., Probe set 10388042, 1036098, 10587633, 10357381, 10342568, 10421128
+ - LP/J, e.g., Probe set 10592493
+ - DBA/2J, e.g., Probe set 10592493
+
+
+Data Evaluation Summary
+
+
+ - Before correction: eQLTs with LOD >10 (LRS>46.1): n = 638
+ - After strain assignment correction: eQLTs with LOD >10 (LRS>46.1): n = 820
+ - Before correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 237.9
+ - After correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 278.1
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
Table 1 (please confirm that these assignments are after correction)
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Phase |
+ Strain |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R5583S |
+ 1 |
+ 129P3/J |
+ 65 |
+ F |
+
+
+ | 2 |
+ R5584S |
+ 1 |
+ 129P3/J |
+ 66 |
+ M |
+
+
+ | 3 |
+ R5585S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+
+
+ | 4 |
+ R5586S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+
+
+ | 5 |
+ R5587S |
+ 1 |
+ 129X1/SvJ |
+ 65 |
+ F |
+
+
+ | 6 |
+ R5588S |
+ 1 |
+ 129X1/SvJ |
+ 66 |
+ M |
+
+
+ | 7 |
+ R6348S |
+ 3 |
+ B6D2F1 |
+ 67 |
+ F |
+
+
+ | 8 |
+ R6347S |
+ 3 |
+ B6D2F1 |
+ 62 |
+ F |
+
+
+ | 9 |
+ R5590S |
+ 1 |
+ B6D2F1 |
+ 79 |
+ M |
+
+
+ | 10 |
+ R5662S |
+ 1 |
+ BALB/cByJ |
+ 59 |
+ F |
+
+
+ | 11 |
+ R5664S |
+ 1 |
+ BALB/cByJ |
+ 59 |
+ M |
+
+
+ | 12 |
+ R5591S |
+ 1 |
+ BALB/cJ |
+ 51 |
+ F |
+
+
+ | 13 |
+ R5592S |
+ 1 |
+ BALB/cJ |
+ 51 |
+ M |
+
+
+ | 14 |
+ R6154S |
+ 2 |
+ BTBR T+ tf/J |
+ 60 |
+ F |
+
+
+ | 15 |
+ R6516S |
+ 3 |
+ BXD1 |
+ 82 |
+ F |
+
+
+ | 16 |
+ R6584S |
+ 3 |
+ BXD1 |
+ 95 |
+ M |
+
+
+ | 17 |
+ R5759S |
+ 1 |
+ BXD2 |
+ N/A |
+ F |
+
+
+ | 18 |
+ R5837S |
+ 1 |
+ BXD2 |
+ 106 |
+ M |
+
+
+ | 19 |
+ R5874S |
+ 2 |
+ BXD5 |
+ 86 |
+ F |
+
+
+ | 20 |
+ R6554S |
+ 3 |
+ BXD5 |
+ 60 |
+ M |
+
+
+ | 21 |
+ R6359S |
+ 3 |
+ BXD6 |
+ 72 |
+ F |
+
+
+ | 22 |
+ R5777S |
+ 1 |
+ BXD6 |
+ 149 |
+ M |
+
+
+ | 23 |
+ R6364S |
+ 3 |
+ BXD8 |
+ 76 |
+ F |
+
+
+ | 24 |
+ R5637S |
+ 1 |
+ BXD8 |
+ 71 |
+ F |
+
+
+ | 25 |
+ R6365S |
+ 3 |
+ BXD8 |
+ 76 |
+ M |
+
+
+ | 26 |
+ R5746S |
+ 1 |
+ BXD9 |
+ 70 |
+ F |
+
+
+ | 27 |
+ R5981S |
+ 2 |
+ BXD9 |
+ 67 |
+ M |
+
+
+ | 28 |
+ R5980S |
+ 2 |
+ BXD9 |
+ 67 |
+ M |
+
+
+ | 29 |
+ R6182S |
+ 2 |
+ BXD11 |
+ 84 |
+ F |
+
+
+ | 30 |
+ R6486S |
+ 3 |
+ BXD11 |
+ 58 |
+ M |
+
+
+ | 31 |
+ R6711S2 |
+ 4 |
+ BXD12 |
+ 71 |
+ F |
+
+
+ | 32 |
+ R6608S |
+ 3 |
+ BXD12 |
+ 48 |
+ F |
+
+
+ | 33 |
+ R5885S |
+ 2 |
+ BXD12 |
+ 44 |
+ M |
+
+
+ | 34 |
+ R5755S |
+ 1 |
+ BXD13 |
+ 160 |
+ F |
+
+
+ | 35 |
+ R5887S |
+ 2 |
+ BXD13 |
+ 53 |
+ M |
+
+
+ | 36 |
+ R6180S |
+ 2 |
+ BXD14 |
+ 70 |
+ F |
+
+
+ | 37 |
+ R5669S |
+ 1 |
+ BXD14 |
+ 91 |
+ M |
+
+
+ | 38 |
+ R6456S |
+ 3 |
+ BXD15 |
+ 60 |
+ F |
+
+
+ | 39 |
+ R6622S |
+ 3 |
+ BXD15 |
+ 60 |
+ F |
+
+
+ | 40 |
+ R6626S |
+ 3 |
+ BXD15 |
+ 60 |
+ M |
+
+
+ | 41 |
+ R6181S |
+ 2 |
+ BXD16 |
+ 74 |
+ F |
+
+
+ | 42 |
+ R6515S |
+ 3 |
+ BXD16 |
+ 64 |
+ M |
+
+
+ | 43 |
+ R5673S |
+ 1 |
+ BXD18 |
+ 80 |
+ F |
+
+
+ | 44 |
+ R5674S |
+ 1 |
+ BXD18 |
+ 65 |
+ M |
+
+
+ | 45 |
+ R6553S |
+ 3 |
+ BXD19 |
+ 158 |
+ F |
+
+
+ | 46 |
+ R6551S |
+ 3 |
+ BXD19 |
+ 60 |
+ M |
+
+
+ | 47 |
+ R6643S4 |
+ 4 |
+ BXD20 |
+ 59 |
+ F |
+
+
+ | 48 |
+ R6595S |
+ 3 |
+ BXD20 |
+ 60 |
+ M |
+
+
+ | 49 |
+ R5735S |
+ 1 |
+ BXD21 |
+ 64 |
+ F |
+
+
+ | 50 |
+ R5892S |
+ 2 |
+ BXD21 |
+ 99 |
+ M |
+
+
+ | 51 |
+ R5896S |
+ 2 |
+ BXD22 |
+ 60 |
+ F |
+
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+ | 52 |
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+ 3 |
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+ | 53 |
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+ 3 |
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+ 74 |
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+ | 54 |
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+ 3 |
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+ | 55 |
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+ 1 |
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+ | 56 |
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+ 3 |
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+ | 57 |
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+ 2 |
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+ | 58 |
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+ 3 |
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+ | 59 |
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+ 4 |
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+ 58 |
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+
+ | 60 |
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+ 1 |
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+
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+ 1 |
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+ 90 |
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+ | 62 |
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+ 3 |
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+ 3 |
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+ 1 |
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+ 1 |
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+ 3 |
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+ 55 |
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+ 1 |
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+ 2 |
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+ 1 |
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+ 1 |
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+ 74 |
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+
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+ 1 |
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+
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+ 1 |
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+
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+ 3 |
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+ 72 |
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+
+ | 82 |
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+ 2 |
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+ 3 |
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+ 2 |
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+ 1 |
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+ 1 |
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+ 3 |
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+ 2 |
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+ 2 |
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+ 60 |
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+ 4 |
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+ 58 |
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+
+
+ | 94 |
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+ 3 |
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+ 79 |
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+
+
+ | 95 |
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+ 1 |
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+
+ | 96 |
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+ 3 |
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+ 65 |
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+
+ | 97 |
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+ 3 |
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+ 63 |
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+
+
+ | 98 |
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+ 3 |
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+ 58 |
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+
+
+ | 99 |
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+ 2 |
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+
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+ 3 |
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+
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+ 3 |
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+ 58 |
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+
+
+ | 102 |
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+ 1 |
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+ 111 |
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+
+
+ | 103 |
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+ 1 |
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+ 85 |
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+
+ | 104 |
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+ 1 |
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+ 86 |
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+
+ | 105 |
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+ 3 |
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+ 65 |
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+
+ | 106 |
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+ 4 |
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+ 54 |
+ F |
+
+
+ | 107 |
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+ 1 |
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+ 115 |
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+
+
+ | 108 |
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+ 3 |
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+ 54 |
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+
+
+ | 109 |
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+ 4 |
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+ 70 |
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+
+
+ | 110 |
+ R5792S |
+ 1 |
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+ 167 |
+ F |
+
+
+ | 111 |
+ R6641S4 |
+ 4 |
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+ 68 |
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+
+ | 112 |
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+ 3 |
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+
+ | 113 |
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+
+ | 114 |
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+ 3 |
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+
+ | 115 |
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+ 3 |
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+
+
+ | 116 |
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+ 3 |
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+ 61 |
+ M |
+
+
+ | 117 |
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+ 1 |
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+ 144 |
+ M |
+
+
+ | 118 |
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+ 3 |
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+ 66 |
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+
+
+ | 119 |
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+ 3 |
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+
+ | 120 |
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+ 3 |
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+
+
+ | 121 |
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+ 3 |
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+
+
+ | 122 |
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+ 1 |
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+ 85 |
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+
+
+ | 123 |
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+ 1 |
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+ 98 |
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+
+
+ | 124 |
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+ 3 |
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+ 93 |
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+
+
+ | 125 |
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+ 1 |
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+
+
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+
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+
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+ 1 |
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+
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+ 1 |
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+
+ | 137 |
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+ 1 |
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+ 1 |
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+ 3 |
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+
+ | 168 |
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+ 3 |
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+ | 169 |
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+ 1 |
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+
+ | 170 |
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+
+ | 171 |
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+
+ | 172 |
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+ 3 |
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+
+
+ | 173 |
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+ 1 |
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+
+
+ | 174 |
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+ 3 |
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+
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+ 2 |
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+ 2 |
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+
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+
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+
+
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+ 3 |
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+
+ | 182 |
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+ 1 |
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+
+
+ | 183 |
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+ 3 |
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+
+ | 184 |
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+ 3 |
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+
+
+ | 185 |
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+ 3 |
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+
+
+ | 186 |
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+ 3 |
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+ 57 |
+ M |
+
+
+ | 187 |
+ R6555S |
+ 3 |
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+ 73 |
+ M |
+
+
+ | 188 |
+ R5596S |
+ 1 |
+ C57BL/10J |
+ 73 |
+ M |
+
+
+ | 189 |
+ R5597S |
+ 1 |
+ C57BL/6ByJ |
+ 51 |
+ F |
+
+
+ | 190 |
+ R5598S |
+ 1 |
+ C57BL/6ByJ |
+ 69 |
+ M |
+
+
+ | 191 |
+ R5600S |
+ 1 |
+ C57BL/6J |
+ 79 |
+ F |
+
+
+ | 192 |
+ R5599S |
+ 1 |
+ C57BL/6J |
+ 60 |
+ F |
+
+
+ | 193 |
+ R6451S |
+ 3 |
+ C57BL/6J |
+ 77 |
+ M |
+
+
+ | 194 |
+ R6410S |
+ 3 |
+ C57BL/6J |
+ 85 |
+ M |
+
+
+ | 195 |
+ R5603S |
+ 1 |
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+ 66 |
+ F |
+
+
+ | 196 |
+ R5604S |
+ 1 |
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+ 66 |
+ M |
+
+
+ | 197 |
+ R5996S |
+ 2 |
+ CBA/CaJ |
+ 66 |
+ F |
+
+
+ | 198 |
+ R6349S |
+ 3 |
+ CBA/CaJ |
+ 66 |
+ M |
+
+
+ | 199 |
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+ 3 |
+ D2B6F1 |
+ 64 |
+ F |
+
+
+ | 200 |
+ R6353S |
+ 3 |
+ D2B6F1 |
+ 60 |
+ M |
+
+
+ | 201 |
+ R5605S |
+ 1 |
+ DBA/2J |
+ 79 |
+ F |
+
+
+ | 202 |
+ R6446S |
+ 3 |
+ DBA/2J |
+ 83 |
+ M |
+
+
+ | 203 |
+ R6597S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 204 |
+ R5643S |
+ 1 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 205 |
+ R6598S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ M |
+
+
+ | 206 |
+ R5606S |
+ 1 |
+ ILS |
+ 74 |
+ F |
+
+
+ | 207 |
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+ 1 |
+ ILS |
+ 74 |
+ M |
+
+
+ | 208 |
+ R5610S |
+ 1 |
+ ISS |
+ 97 |
+ M |
+
+
+ | 209 |
+ R6627S |
+ 3 |
+ KK/HlJ |
+ 64 |
+ F |
+
+
+ | 210 |
+ R6444S |
+ 3 |
+ KK/HlJ |
+ 65 |
+ M |
+
+
+ | 211 |
+ R5702S |
+ 1 |
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+ 61 |
+ M |
+
+
+ | 212 |
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+ 1 |
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+ 63 |
+ F |
+
+
+ | 213 |
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+ 1 |
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+ 65 |
+ M |
+
+
+ | 214 |
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+ 1 |
+ LP/J |
+ 65 |
+ F |
+
+
+ | 215 |
+ R5615S |
+ 1 |
+ LP/J |
+ 65 |
+ M |
+
+
+ | 216 |
+ R6599S |
+ 3 |
+ MOLF/EiJ |
+ 60 |
+ F |
+
+
+ | 217 |
+ R6606S |
+ 3 |
+ MOLF/EiJ |
+ 60 |
+ M |
+
+
+ | 218 |
+ R6544S |
+ 3 |
+ NOD/LtJ |
+ 77 |
+ F |
+
+
+ | 219 |
+ R5709S |
+ 1 |
+ NOD/LtJ |
+ 58 |
+ M |
+
+
+ | 220 |
+ R6601S |
+ 3 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 221 |
+ R5711S |
+ 1 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 222 |
+ R6427S |
+ 3 |
+ NZB/BlNJ |
+ 58 |
+ M |
+
+
+ | 223 |
+ R6150S |
+ 2 |
+ NZO/HlLtJ |
+ 71 |
+ F |
+
+
+ | 224 |
+ R6155S |
+ 2 |
+ NZW/LacJ |
+ 65 |
+ F |
+
+
+ | 225 |
+ R5654S |
+ 1 |
+ NZW/LacJ |
+ 60 |
+ M |
+
+
+ | 226 |
+ R5721S |
+ 1 |
+ PL/J |
+ 59 |
+ M |
+
+
+ | 227 |
+ R5616S |
+ 1 |
+ PWD/PhJ |
+ 60 |
+ M |
+
+
+ | 228 |
+ R5725S |
+ 1 |
+ PWK/PhJ |
+ 121 |
+ M |
+
+
+ | 229 |
+ R6174S |
+ 2 |
+ SJL/J |
+ 63 |
+ F |
+
+
+ | 230 |
+ R6350S |
+ 3 |
+ SJL/J |
+ 65 |
+ M |
+
+
+ | 231 |
+ R6419S |
+ 3 |
+ WSB/EiJ |
+ 60 |
+ F |
+
+
+ | 232 |
+ R5620S |
+ 1 |
+ WSB/EiJ |
+ 60 |
+ M |
+
+
+
+
+ |
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/Uthsc_spl_rma_1210f/summary.rtf b/general/datasets/Uthsc_spl_rma_1210f/summary.rtf
new file mode 100644
index 0000000..d9478f8
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210f/summary.rtf
@@ -0,0 +1,3 @@
+This is a near final release of a spleen gene expression data set generated by a DOD-funded consortium (Byrne, Kotb, Williams, and Lu). Please contact Lu Lu or Robert Williams regarding status of this data set. The initial data enterted in 2010 had many errors described below. The data set is much improved and has no known errors of strain assignment.
+
+Animals were generated at UTHSC by Lu Lu and colleagues. The spleen of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/Uthsc_spl_rma_1210m/cases.rtf b/general/datasets/Uthsc_spl_rma_1210m/cases.rtf
new file mode 100644
index 0000000..7fa108f
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210m/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 111 strains, including 81 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1), and 26 other common inbred strains were quantified. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by Lu Lu and colleagues. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. XX strains have matched male and female samples. XX strains have male only samples (BXDX, XX, XX, XXX and XXX). XX strains have only female samples (BXDXX, XX, and XX.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/Uthsc_spl_rma_1210m/experiment-design.rtf b/general/datasets/Uthsc_spl_rma_1210m/experiment-design.rtf
new file mode 100644
index 0000000..a0aeba6
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210m/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Processing. Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+Array Processing: All arrays were processed by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. The spleen was dissected by both Dr. Lu Lu and colleagues and Dr. Abdeltawab and colleagues. All arrays were run together (interleaved) as a single large batch.
diff --git a/general/datasets/Uthsc_spl_rma_1210m/experiment-type.rtf b/general/datasets/Uthsc_spl_rma_1210m/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210m/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Uthsc_spl_rma_1210m/notes.rtf b/general/datasets/Uthsc_spl_rma_1210m/notes.rtf
new file mode 100644
index 0000000..c7bb873
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210m/notes.rtf
@@ -0,0 +1,4 @@
+Data Status and Use. This is a provisional release that will soon be replaced by a final corrected data set. In the interim this data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/Uthsc_spl_rma_1210m/processing.rtf b/general/datasets/Uthsc_spl_rma_1210m/processing.rtf
new file mode 100644
index 0000000..deaf264
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210m/processing.rtf
@@ -0,0 +1,1932 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required some correction for batch effects and the data in this initial release incorporate any additional corrections. There are several additional confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest probe sets in this spleen data set accounts of XX% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the spleen data set can be mapped as a trait.
+
+
+Data Release. This data set was first uploaded into GeneNetwork by Arthur Centeno, October 11, 2010 and made accessible without a password to all users on November 1, 2010. The initial data release had numerous strain identification errors that have now largely been fixed. Based on an analysis of the top 20 Mendelian loci, the following 21 strains were likely to have been incorrectly identified or assigned in the current release:
+
+
+ - BXD8, e.g., Probe set 10450161, 1036098. 10338684
+ - BXD13, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10342568,
+ - BXD21 (may be ok, only one probe set 10338684 is problematic)
+ - BXD23 (may be ok, only two probe sets 10421128, 10419465 is problematic)
+ - BXD36 (may be ok, only one probe set 10421128 is problematic)
+ - BXD40, e.g., Probe set 10341070
+ - BXD43, e.g., Probe set 10450161, 1036098, 10338684
+ - BXD48, e.g., Probe set 1036098, 10402390, 10514896, 10592493, 10357381, 10342568, 10571444, 10419465
+ - BXD62, e.g., Probe set 1036098, 1036098, 10402390, 10514896, 10592493, 10421128, 10571444
+ - BXD68 (may be ok, only one probe set 10338684 is problematic)
+ - BXD69, e.g., Probe set 10450161
+ - BXD73, e.g., Probe set 10341070, 1036098, 10402390, 10514896, 10587633, 10342568, 10421128
+ - BXD74, e.g., Probe set 10402390
+ - BXD80, e.g., Probe set 10341070, 1036098, 10592493, 10400109, 10338684, 10342568, 10421128, 10419465
+ - BXD83, e.g., Probe set 10450161, 10338684
+ - BXD87 (may be ok, only one probe set 10421128 is problematic)
+ - BXD89, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10357381, 10419465
+ - BXD93, e.g., Probe set 10402390, 10357381
+ - BALB/cByJ, e.g., Probe set 10388042, 1036098, 10587633, 10357381, 10342568, 10421128
+ - LP/J, e.g., Probe set 10592493
+ - DBA/2J, e.g., Probe set 10592493
+
+
+Data Evaluation Summary
+
+
+ - Before correction: eQLTs with LOD >10 (LRS>46.1): n = 638
+ - After strain assignment correction: eQLTs with LOD >10 (LRS>46.1): n = 820
+ - Before correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 237.9
+ - After correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 278.1
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
Table 1 (please confirm that these assignments are after correction)
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Phase |
+ Strain |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R5583S |
+ 1 |
+ 129P3/J |
+ 65 |
+ F |
+
+
+ | 2 |
+ R5584S |
+ 1 |
+ 129P3/J |
+ 66 |
+ M |
+
+
+ | 3 |
+ R5585S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+
+
+ | 4 |
+ R5586S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+
+
+ | 5 |
+ R5587S |
+ 1 |
+ 129X1/SvJ |
+ 65 |
+ F |
+
+
+ | 6 |
+ R5588S |
+ 1 |
+ 129X1/SvJ |
+ 66 |
+ M |
+
+
+ | 7 |
+ R6348S |
+ 3 |
+ B6D2F1 |
+ 67 |
+ F |
+
+
+ | 8 |
+ R6347S |
+ 3 |
+ B6D2F1 |
+ 62 |
+ F |
+
+
+ | 9 |
+ R5590S |
+ 1 |
+ B6D2F1 |
+ 79 |
+ M |
+
+
+ | 10 |
+ R5662S |
+ 1 |
+ BALB/cByJ |
+ 59 |
+ F |
+
+
+ | 11 |
+ R5664S |
+ 1 |
+ BALB/cByJ |
+ 59 |
+ M |
+
+
+ | 12 |
+ R5591S |
+ 1 |
+ BALB/cJ |
+ 51 |
+ F |
+
+
+ | 13 |
+ R5592S |
+ 1 |
+ BALB/cJ |
+ 51 |
+ M |
+
+
+ | 14 |
+ R6154S |
+ 2 |
+ BTBR T+ tf/J |
+ 60 |
+ F |
+
+
+ | 15 |
+ R6516S |
+ 3 |
+ BXD1 |
+ 82 |
+ F |
+
+
+ | 16 |
+ R6584S |
+ 3 |
+ BXD1 |
+ 95 |
+ M |
+
+
+ | 17 |
+ R5759S |
+ 1 |
+ BXD2 |
+ N/A |
+ F |
+
+
+ | 18 |
+ R5837S |
+ 1 |
+ BXD2 |
+ 106 |
+ M |
+
+
+ | 19 |
+ R5874S |
+ 2 |
+ BXD5 |
+ 86 |
+ F |
+
+
+ | 20 |
+ R6554S |
+ 3 |
+ BXD5 |
+ 60 |
+ M |
+
+
+ | 21 |
+ R6359S |
+ 3 |
+ BXD6 |
+ 72 |
+ F |
+
+
+ | 22 |
+ R5777S |
+ 1 |
+ BXD6 |
+ 149 |
+ M |
+
+
+ | 23 |
+ R6364S |
+ 3 |
+ BXD8 |
+ 76 |
+ F |
+
+
+ | 24 |
+ R5637S |
+ 1 |
+ BXD8 |
+ 71 |
+ F |
+
+
+ | 25 |
+ R6365S |
+ 3 |
+ BXD8 |
+ 76 |
+ M |
+
+
+ | 26 |
+ R5746S |
+ 1 |
+ BXD9 |
+ 70 |
+ F |
+
+
+ | 27 |
+ R5981S |
+ 2 |
+ BXD9 |
+ 67 |
+ M |
+
+
+ | 28 |
+ R5980S |
+ 2 |
+ BXD9 |
+ 67 |
+ M |
+
+
+ | 29 |
+ R6182S |
+ 2 |
+ BXD11 |
+ 84 |
+ F |
+
+
+ | 30 |
+ R6486S |
+ 3 |
+ BXD11 |
+ 58 |
+ M |
+
+
+ | 31 |
+ R6711S2 |
+ 4 |
+ BXD12 |
+ 71 |
+ F |
+
+
+ | 32 |
+ R6608S |
+ 3 |
+ BXD12 |
+ 48 |
+ F |
+
+
+ | 33 |
+ R5885S |
+ 2 |
+ BXD12 |
+ 44 |
+ M |
+
+
+ | 34 |
+ R5755S |
+ 1 |
+ BXD13 |
+ 160 |
+ F |
+
+
+ | 35 |
+ R5887S |
+ 2 |
+ BXD13 |
+ 53 |
+ M |
+
+
+ | 36 |
+ R6180S |
+ 2 |
+ BXD14 |
+ 70 |
+ F |
+
+
+ | 37 |
+ R5669S |
+ 1 |
+ BXD14 |
+ 91 |
+ M |
+
+
+ | 38 |
+ R6456S |
+ 3 |
+ BXD15 |
+ 60 |
+ F |
+
+
+ | 39 |
+ R6622S |
+ 3 |
+ BXD15 |
+ 60 |
+ F |
+
+
+ | 40 |
+ R6626S |
+ 3 |
+ BXD15 |
+ 60 |
+ M |
+
+
+ | 41 |
+ R6181S |
+ 2 |
+ BXD16 |
+ 74 |
+ F |
+
+
+ | 42 |
+ R6515S |
+ 3 |
+ BXD16 |
+ 64 |
+ M |
+
+
+ | 43 |
+ R5673S |
+ 1 |
+ BXD18 |
+ 80 |
+ F |
+
+
+ | 44 |
+ R5674S |
+ 1 |
+ BXD18 |
+ 65 |
+ M |
+
+
+ | 45 |
+ R6553S |
+ 3 |
+ BXD19 |
+ 158 |
+ F |
+
+
+ | 46 |
+ R6551S |
+ 3 |
+ BXD19 |
+ 60 |
+ M |
+
+
+ | 47 |
+ R6643S4 |
+ 4 |
+ BXD20 |
+ 59 |
+ F |
+
+
+ | 48 |
+ R6595S |
+ 3 |
+ BXD20 |
+ 60 |
+ M |
+
+
+ | 49 |
+ R5735S |
+ 1 |
+ BXD21 |
+ 64 |
+ F |
+
+
+ | 50 |
+ R5892S |
+ 2 |
+ BXD21 |
+ 99 |
+ M |
+
+
+ | 51 |
+ R5896S |
+ 2 |
+ BXD22 |
+ 60 |
+ F |
+
+
+ | 52 |
+ R6414S |
+ 3 |
+ BXD22 |
+ 73 |
+ M |
+
+
+ | 53 |
+ R6550S |
+ 3 |
+ BXD23 |
+ 74 |
+ F |
+
+
+ | 54 |
+ R6586S |
+ 3 |
+ BXD23 |
+ 102 |
+ F |
+
+
+ | 55 |
+ R5630S |
+ 1 |
+ BXD24 |
+ 71 |
+ F |
+
+
+ | 56 |
+ R6356S |
+ 3 |
+ BXD24 |
+ 57 |
+ M |
+
+
+ | 57 |
+ R6162S |
+ 2 |
+ BXD25 |
+ 67 |
+ F |
+
+
+ | 58 |
+ R6625S |
+ 3 |
+ BXD25 |
+ 67 |
+ F |
+
+
+ | 59 |
+ R6642S4 |
+ 4 |
+ BXD25 |
+ 58 |
+ M |
+
+
+ | 60 |
+ R5761S |
+ 1 |
+ BXD27 |
+ N/A |
+ F |
+
+
+ | 61 |
+ R5763S |
+ 1 |
+ BXD27 |
+ 90 |
+ M |
+
+
+ | 62 |
+ R6621S |
+ 3 |
+ BXD28 |
+ 113 |
+ F |
+
+
+ | 63 |
+ R6548S |
+ 3 |
+ BXD28 |
+ 60 |
+ M |
+
+
+ | 64 |
+ R6547S |
+ 3 |
+ BXD29 |
+ 60 |
+ F |
+
+
+ | 65 |
+ R6453S |
+ 3 |
+ BXD31 |
+ 48 |
+ F |
+
+
+ | 66 |
+ R6452S |
+ 3 |
+ BXD31 |
+ 48 |
+ M |
+
+
+ | 67 |
+ R6583S |
+ 3 |
+ BXD32 |
+ 60 |
+ F |
+
+
+ | 68 |
+ R5765S |
+ 1 |
+ BXD32 |
+ 71 |
+ M |
+
+
+ | 69 |
+ R5689S |
+ 1 |
+ BXD33 |
+ 65 |
+ F |
+
+
+ | 70 |
+ R6450S |
+ 3 |
+ BXD33 |
+ 55 |
+ M |
+
+
+ | 71 |
+ R5767S |
+ 1 |
+ BXD34 |
+ 72 |
+ F |
+
+
+ | 72 |
+ R5900S |
+ 2 |
+ BXD34 |
+ 70 |
+ M |
+
+
+ | 73 |
+ R6588S |
+ 3 |
+ BXD36 |
+ 61 |
+ F |
+
+
+ | 74 |
+ R6490S |
+ 3 |
+ BXD36 |
+ 63 |
+ M |
+
+
+ | 75 |
+ R6417S |
+ 3 |
+ BXD38 |
+ 64 |
+ F |
+
+
+ | 76 |
+ R6439S |
+ 3 |
+ BXD38 |
+ 72 |
+ M |
+
+
+ | 77 |
+ R5769S |
+ 1 |
+ BXD39 |
+ N/A |
+ F |
+
+
+ | 78 |
+ R5771S |
+ 1 |
+ BXD39 |
+ 74 |
+ M |
+
+
+ | 79 |
+ R5773S |
+ 1 |
+ BXD40 |
+ N/A |
+ F |
+
+
+ | 80 |
+ R5775S |
+ 1 |
+ BXD40 |
+ N/A |
+ M |
+
+
+ | 81 |
+ R6494S |
+ 3 |
+ BXD41 |
+ 72 |
+ F |
+
+
+ | 82 |
+ R5910S |
+ 2 |
+ BXD42 |
+ 79 |
+ F |
+
+
+ | 83 |
+ R6493S |
+ 3 |
+ BXD42 |
+ 69 |
+ M |
+
+
+ | 84 |
+ R6341S |
+ 3 |
+ BXD43 |
+ 59 |
+ F |
+
+
+ | 85 |
+ R6401S |
+ 3 |
+ BXD43 |
+ 99 |
+ M |
+
+
+ | 86 |
+ R5916S |
+ 2 |
+ BXD43 |
+ 79 |
+ M |
+
+
+ | 87 |
+ R5839S |
+ 1 |
+ BXD44 |
+ 141 |
+ F |
+
+
+ | 88 |
+ R5779S |
+ 1 |
+ BXD44 |
+ 124 |
+ M |
+
+
+ | 89 |
+ R6405S |
+ 3 |
+ BXD45 |
+ 58 |
+ F |
+
+
+ | 90 |
+ R6610S |
+ 3 |
+ BXD45 |
+ 55 |
+ M |
+
+
+ | 91 |
+ R5922S |
+ 2 |
+ BXD48 |
+ 64 |
+ F |
+
+
+ | 92 |
+ R5925S |
+ 2 |
+ BXD48 |
+ 60 |
+ M |
+
+
+ | 93 |
+ R6719S1 |
+ 4 |
+ BXD49 |
+ 58 |
+ F |
+
+
+ | 94 |
+ R6485S |
+ 3 |
+ BXD49 |
+ 79 |
+ M |
+
+
+ | 95 |
+ R5781S |
+ 1 |
+ BXD50 |
+ 61 |
+ F |
+
+
+ | 96 |
+ R6464S |
+ 3 |
+ BXD51 |
+ 65 |
+ F |
+
+
+ | 97 |
+ R6585S |
+ 3 |
+ BXD51 |
+ 63 |
+ M |
+
+
+ | 98 |
+ R6500S |
+ 3 |
+ BXD55 |
+ 58 |
+ F |
+
+
+ | 99 |
+ R5938S |
+ 2 |
+ BXD55 |
+ 93 |
+ M |
+
+
+ | 100 |
+ R6504S |
+ 3 |
+ BXD56 |
+ 58 |
+ F |
+
+
+ | 101 |
+ R6503S |
+ 3 |
+ BXD56 |
+ 58 |
+ M |
+
+
+ | 102 |
+ R5783S |
+ 1 |
+ BXD60 |
+ 111 |
+ F |
+
+
+ | 103 |
+ R5784S |
+ 1 |
+ BXD60 |
+ 85 |
+ M |
+
+
+ | 104 |
+ R5786S |
+ 1 |
+ BXD61 |
+ 86 |
+ F |
+
+
+ | 105 |
+ R6449S |
+ 3 |
+ BXD61 |
+ 65 |
+ M |
+
+
+ | 106 |
+ R6716S1 |
+ 4 |
+ BXD62 |
+ 54 |
+ F |
+
+
+ | 107 |
+ R5790S |
+ 1 |
+ BXD62 |
+ 115 |
+ M |
+
+
+ | 108 |
+ R6519S |
+ 3 |
+ BXD63 |
+ 54 |
+ F |
+
+
+ | 109 |
+ R6717S1 |
+ 4 |
+ BXD63 |
+ 70 |
+ M |
+
+
+ | 110 |
+ R5792S |
+ 1 |
+ BXD64 |
+ 167 |
+ F |
+
+
+ | 111 |
+ R6641S4 |
+ 4 |
+ BXD64 |
+ 68 |
+ M |
+
+
+ | 112 |
+ R6630S |
+ 3 |
+ BXD64 |
+ 68 |
+ M |
+
+
+ | 113 |
+ R6477S |
+ 3 |
+ BXD65 |
+ 58 |
+ F |
+
+
+ | 114 |
+ R6628S |
+ 3 |
+ BXD65 |
+ 70 |
+ M |
+
+
+ | 115 |
+ R6511S |
+ 3 |
+ BXD66 |
+ 70 |
+ F |
+
+
+ | 116 |
+ R6448S |
+ 3 |
+ BXD66 |
+ 61 |
+ M |
+
+
+ | 117 |
+ R5794S |
+ 1 |
+ BXD66 |
+ 144 |
+ M |
+
+
+ | 118 |
+ R6502S |
+ 3 |
+ BXD67 |
+ 66 |
+ F |
+
+
+ | 119 |
+ R6545S |
+ 3 |
+ BXD67 |
+ 61 |
+ M |
+
+
+ | 120 |
+ R6337S |
+ 3 |
+ BXD68 |
+ 56 |
+ F |
+
+
+ | 121 |
+ R6594S |
+ 3 |
+ BXD68 |
+ 64 |
+ M |
+
+
+ | 122 |
+ R5796S |
+ 1 |
+ BXD69 |
+ 85 |
+ F |
+
+
+ | 123 |
+ R5798S |
+ 1 |
+ BXD69 |
+ 98 |
+ M |
+
+
+ | 124 |
+ R6402S |
+ 3 |
+ BXD70 |
+ 93 |
+ F |
+
+
+ | 125 |
+ R5841S |
+ 1 |
+ BXD70 |
+ 121 |
+ F |
+
+
+ | 126 |
+ R6592S |
+ 3 |
+ BXD70 |
+ 59 |
+ M |
+
+
+ | 127 |
+ R6328S |
+ 3 |
+ BXD71 |
+ 87 |
+ F |
+
+
+ | 128 |
+ R5967S |
+ 2 |
+ BXD71 |
+ 64 |
+ M |
+
+
+ | 129 |
+ R5969S |
+ 2 |
+ BXD73 |
+ 64 |
+ F |
+
+
+ | 130 |
+ R5800S |
+ 1 |
+ BXD73 |
+ 120 |
+ M |
+
+
+ | 131 |
+ R6646S |
+ 3 |
+ BXD74 |
+ 40 |
+ F |
+
+
+ | 132 |
+ R6524S |
+ 3 |
+ BXD74 |
+ 72 |
+ M |
+
+
+ | 133 |
+ R6445S |
+ 3 |
+ BXD75 |
+ 85 |
+ F |
+
+
+ | 134 |
+ R5843S |
+ 1 |
+ BXD75 |
+ 103 |
+ F |
+
+
+ | 135 |
+ R5845S |
+ 1 |
+ BXD75 |
+ 103 |
+ M |
+
+
+ | 136 |
+ R6604S |
+ 3 |
+ BXD77 |
+ 64 |
+ F |
+
+
+ | 137 |
+ R6513S |
+ 3 |
+ BXD77 |
+ 72 |
+ M |
+
+
+ | 138 |
+ R6582S |
+ 3 |
+ BXD78 |
+ 144 |
+ F |
+
+
+ | 139 |
+ R6563S |
+ 3 |
+ BXD78 |
+ 95 |
+ M |
+
+
+ | 140 |
+ R6645S4 |
+ 4 |
+ BXD79 |
+ 66 |
+ F |
+
+
+ | 141 |
+ R5806S |
+ 1 |
+ BXD79 |
+ 78 |
+ M |
+
+
+ | 142 |
+ R5847S |
+ 1 |
+ BXD80 |
+ 89 |
+ F |
+
+
+ | 143 |
+ R5852S |
+ 1 |
+ BXD80 |
+ 79 |
+ M |
+
+
+ | 144 |
+ R6562S |
+ 3 |
+ BXD81 |
+ 99 |
+ F |
+
+
+ | 145 |
+ R6468S |
+ 3 |
+ BXD81 |
+ 65 |
+ M |
+
+
+ | 146 |
+ R6560S |
+ 3 |
+ BXD82 |
+ 85 |
+ F |
+
+
+ | 147 |
+ R6512S |
+ 3 |
+ BXD83 |
+ 68 |
+ F |
+
+
+ | 148 |
+ R5810S |
+ 1 |
+ BXD83 |
+ 139 |
+ M |
+
+
+ | 149 |
+ R6510S |
+ 3 |
+ BXD84 |
+ 87 |
+ F |
+
+
+ | 150 |
+ R5970S |
+ 2 |
+ BXD84 |
+ 107 |
+ F |
+
+
+ | 151 |
+ R6603S |
+ 3 |
+ BXD84 |
+ 99 |
+ M |
+
+
+ | 152 |
+ R6517S |
+ 3 |
+ BXD85 |
+ 58 |
+ F |
+
+
+ | 153 |
+ R6718S1 |
+ 4 |
+ BXD85 |
+ 86 |
+ M |
+
+
+ | 154 |
+ R5812S |
+ 1 |
+ BXD86 |
+ 61 |
+ F |
+
+
+ | 155 |
+ R5814S |
+ 1 |
+ BXD86 |
+ 59 |
+ M |
+
+
+ | 156 |
+ R5816S |
+ 1 |
+ BXD87 |
+ 112 |
+ F |
+
+
+ | 157 |
+ R6488S |
+ 3 |
+ BXD87 |
+ 137 |
+ M |
+
+
+ | 158 |
+ R6580S |
+ 3 |
+ BXD88 |
+ 125 |
+ F |
+
+
+ | 159 |
+ R5977S |
+ 2 |
+ BXD89 |
+ 68 |
+ F |
+
+
+ | 160 |
+ R5979S |
+ 2 |
+ BXD89 |
+ 79 |
+ M |
+
+
+ | 161 |
+ R5978S |
+ 2 |
+ BXD89 |
+ 79 |
+ M |
+
+
+ | 162 |
+ R5818S |
+ 1 |
+ BXD90 |
+ 106 |
+ F |
+
+
+ | 163 |
+ R5820S |
+ 1 |
+ BXD90 |
+ 131 |
+ M |
+
+
+ | 164 |
+ R6343S |
+ 3 |
+ BXD92 |
+ 62 |
+ F |
+
+
+ | 165 |
+ R5984S |
+ 2 |
+ BXD92 |
+ 55 |
+ M |
+
+
+ | 166 |
+ R6581S |
+ 3 |
+ BXD93 |
+ 173 |
+ M |
+
+
+ | 167 |
+ R6557S |
+ 3 |
+ BXD93 |
+ 126 |
+ M |
+
+
+ | 168 |
+ R6509S |
+ 3 |
+ BXD95 |
+ 59 |
+ F |
+
+
+ | 169 |
+ R5822S |
+ 1 |
+ BXD95 |
+ 89 |
+ M |
+
+
+ | 170 |
+ R6640S4 |
+ 4 |
+ BXD96 |
+ 70 |
+ F |
+
+
+ | 171 |
+ R6514S |
+ 3 |
+ BXD96 |
+ 64 |
+ M |
+
+
+ | 172 |
+ R6506S |
+ 3 |
+ BXD97 |
+ 78 |
+ F |
+
+
+ | 173 |
+ R5849S |
+ 1 |
+ BXD97 |
+ 130 |
+ F |
+
+
+ | 174 |
+ R6591S |
+ 3 |
+ BXD97 |
+ 122 |
+ M |
+
+
+ | 175 |
+ R5990S |
+ 2 |
+ BXD98 |
+ 65 |
+ F |
+
+
+ | 176 |
+ R6596S |
+ 3 |
+ BXD98 |
+ 67 |
+ M |
+
+
+ | 177 |
+ R5993S |
+ 2 |
+ BXD99 |
+ 74 |
+ F |
+
+
+ | 178 |
+ R5995S |
+ 2 |
+ BXD99 |
+ 50 |
+ M |
+
+
+ | 179 |
+ R6607S |
+ 3 |
+ BXD100 |
+ 75 |
+ F |
+
+
+ | 180 |
+ R6411S |
+ 3 |
+ BXD100 |
+ 104 |
+ M |
+
+
+ | 181 |
+ R6508S |
+ 3 |
+ BXD101 |
+ 59 |
+ F |
+
+
+ | 182 |
+ R5593S |
+ 1 |
+ BXD101 |
+ 59 |
+ M |
+
+
+ | 183 |
+ R6523S |
+ 3 |
+ BXD102 |
+ 60 |
+ F |
+
+
+ | 184 |
+ R6466S |
+ 3 |
+ BXD102 |
+ 50 |
+ M |
+
+
+ | 185 |
+ R6404S |
+ 3 |
+ BXD103 |
+ 72 |
+ F |
+
+
+ | 186 |
+ R6609S |
+ 3 |
+ BXD103 |
+ 57 |
+ M |
+
+
+ | 187 |
+ R6555S |
+ 3 |
+ C57BL/10J |
+ 73 |
+ M |
+
+
+ | 188 |
+ R5596S |
+ 1 |
+ C57BL/10J |
+ 73 |
+ M |
+
+
+ | 189 |
+ R5597S |
+ 1 |
+ C57BL/6ByJ |
+ 51 |
+ F |
+
+
+ | 190 |
+ R5598S |
+ 1 |
+ C57BL/6ByJ |
+ 69 |
+ M |
+
+
+ | 191 |
+ R5600S |
+ 1 |
+ C57BL/6J |
+ 79 |
+ F |
+
+
+ | 192 |
+ R5599S |
+ 1 |
+ C57BL/6J |
+ 60 |
+ F |
+
+
+ | 193 |
+ R6451S |
+ 3 |
+ C57BL/6J |
+ 77 |
+ M |
+
+
+ | 194 |
+ R6410S |
+ 3 |
+ C57BL/6J |
+ 85 |
+ M |
+
+
+ | 195 |
+ R5603S |
+ 1 |
+ C57BLKS/J |
+ 66 |
+ F |
+
+
+ | 196 |
+ R5604S |
+ 1 |
+ C57BLKS/J |
+ 66 |
+ M |
+
+
+ | 197 |
+ R5996S |
+ 2 |
+ CBA/CaJ |
+ 66 |
+ F |
+
+
+ | 198 |
+ R6349S |
+ 3 |
+ CBA/CaJ |
+ 66 |
+ M |
+
+
+ | 199 |
+ R6458S |
+ 3 |
+ D2B6F1 |
+ 64 |
+ F |
+
+
+ | 200 |
+ R6353S |
+ 3 |
+ D2B6F1 |
+ 60 |
+ M |
+
+
+ | 201 |
+ R5605S |
+ 1 |
+ DBA/2J |
+ 79 |
+ F |
+
+
+ | 202 |
+ R6446S |
+ 3 |
+ DBA/2J |
+ 83 |
+ M |
+
+
+ | 203 |
+ R6597S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 204 |
+ R5643S |
+ 1 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 205 |
+ R6598S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ M |
+
+
+ | 206 |
+ R5606S |
+ 1 |
+ ILS |
+ 74 |
+ F |
+
+
+ | 207 |
+ R5607S |
+ 1 |
+ ILS |
+ 74 |
+ M |
+
+
+ | 208 |
+ R5610S |
+ 1 |
+ ISS |
+ 97 |
+ M |
+
+
+ | 209 |
+ R6627S |
+ 3 |
+ KK/HlJ |
+ 64 |
+ F |
+
+
+ | 210 |
+ R6444S |
+ 3 |
+ KK/HlJ |
+ 65 |
+ M |
+
+
+ | 211 |
+ R5702S |
+ 1 |
+ KK/HlJ |
+ 61 |
+ M |
+
+
+ | 212 |
+ R5613S |
+ 1 |
+ LG/J |
+ 63 |
+ F |
+
+
+ | 213 |
+ R5704S |
+ 1 |
+ LG/J |
+ 65 |
+ M |
+
+
+ | 214 |
+ R5614S |
+ 1 |
+ LP/J |
+ 65 |
+ F |
+
+
+ | 215 |
+ R5615S |
+ 1 |
+ LP/J |
+ 65 |
+ M |
+
+
+ | 216 |
+ R6599S |
+ 3 |
+ MOLF/EiJ |
+ 60 |
+ F |
+
+
+ | 217 |
+ R6606S |
+ 3 |
+ MOLF/EiJ |
+ 60 |
+ M |
+
+
+ | 218 |
+ R6544S |
+ 3 |
+ NOD/LtJ |
+ 77 |
+ F |
+
+
+ | 219 |
+ R5709S |
+ 1 |
+ NOD/LtJ |
+ 58 |
+ M |
+
+
+ | 220 |
+ R6601S |
+ 3 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 221 |
+ R5711S |
+ 1 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 222 |
+ R6427S |
+ 3 |
+ NZB/BlNJ |
+ 58 |
+ M |
+
+
+ | 223 |
+ R6150S |
+ 2 |
+ NZO/HlLtJ |
+ 71 |
+ F |
+
+
+ | 224 |
+ R6155S |
+ 2 |
+ NZW/LacJ |
+ 65 |
+ F |
+
+
+ | 225 |
+ R5654S |
+ 1 |
+ NZW/LacJ |
+ 60 |
+ M |
+
+
+ | 226 |
+ R5721S |
+ 1 |
+ PL/J |
+ 59 |
+ M |
+
+
+ | 227 |
+ R5616S |
+ 1 |
+ PWD/PhJ |
+ 60 |
+ M |
+
+
+ | 228 |
+ R5725S |
+ 1 |
+ PWK/PhJ |
+ 121 |
+ M |
+
+
+ | 229 |
+ R6174S |
+ 2 |
+ SJL/J |
+ 63 |
+ F |
+
+
+ | 230 |
+ R6350S |
+ 3 |
+ SJL/J |
+ 65 |
+ M |
+
+
+ | 231 |
+ R6419S |
+ 3 |
+ WSB/EiJ |
+ 60 |
+ F |
+
+
+ | 232 |
+ R5620S |
+ 1 |
+ WSB/EiJ |
+ 60 |
+ M |
+
+
+
+
+ |
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/Uthsc_spl_rma_1210m/summary.rtf b/general/datasets/Uthsc_spl_rma_1210m/summary.rtf
new file mode 100644
index 0000000..d9478f8
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rma_1210m/summary.rtf
@@ -0,0 +1,3 @@
+This is a near final release of a spleen gene expression data set generated by a DOD-funded consortium (Byrne, Kotb, Williams, and Lu). Please contact Lu Lu or Robert Williams regarding status of this data set. The initial data enterted in 2010 had many errors described below. The data set is much improved and has no known errors of strain assignment.
+
+Animals were generated at UTHSC by Lu Lu and colleagues. The spleen of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/Uthsc_spl_rmaex_1210/cases.rtf b/general/datasets/Uthsc_spl_rmaex_1210/cases.rtf
new file mode 100644
index 0000000..7fa108f
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rmaex_1210/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 111 strains, including 81 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1), and 26 other common inbred strains were quantified. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by Lu Lu and colleagues. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. XX strains have matched male and female samples. XX strains have male only samples (BXDX, XX, XX, XXX and XXX). XX strains have only female samples (BXDXX, XX, and XX.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/Uthsc_spl_rmaex_1210/experiment-design.rtf b/general/datasets/Uthsc_spl_rmaex_1210/experiment-design.rtf
new file mode 100644
index 0000000..a0aeba6
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rmaex_1210/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Processing. Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+Array Processing: All arrays were processed by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. The spleen was dissected by both Dr. Lu Lu and colleagues and Dr. Abdeltawab and colleagues. All arrays were run together (interleaved) as a single large batch.
diff --git a/general/datasets/Uthsc_spl_rmaex_1210/notes.rtf b/general/datasets/Uthsc_spl_rmaex_1210/notes.rtf
new file mode 100644
index 0000000..c7bb873
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rmaex_1210/notes.rtf
@@ -0,0 +1,4 @@
+Data Status and Use. This is a provisional release that will soon be replaced by a final corrected data set. In the interim this data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/Uthsc_spl_rmaex_1210/processing.rtf b/general/datasets/Uthsc_spl_rmaex_1210/processing.rtf
new file mode 100644
index 0000000..deaf264
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rmaex_1210/processing.rtf
@@ -0,0 +1,1932 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required some correction for batch effects and the data in this initial release incorporate any additional corrections. There are several additional confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest probe sets in this spleen data set accounts of XX% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the spleen data set can be mapped as a trait.
+
+
+Data Release. This data set was first uploaded into GeneNetwork by Arthur Centeno, October 11, 2010 and made accessible without a password to all users on November 1, 2010. The initial data release had numerous strain identification errors that have now largely been fixed. Based on an analysis of the top 20 Mendelian loci, the following 21 strains were likely to have been incorrectly identified or assigned in the current release:
+
+
+ - BXD8, e.g., Probe set 10450161, 1036098. 10338684
+ - BXD13, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10342568,
+ - BXD21 (may be ok, only one probe set 10338684 is problematic)
+ - BXD23 (may be ok, only two probe sets 10421128, 10419465 is problematic)
+ - BXD36 (may be ok, only one probe set 10421128 is problematic)
+ - BXD40, e.g., Probe set 10341070
+ - BXD43, e.g., Probe set 10450161, 1036098, 10338684
+ - BXD48, e.g., Probe set 1036098, 10402390, 10514896, 10592493, 10357381, 10342568, 10571444, 10419465
+ - BXD62, e.g., Probe set 1036098, 1036098, 10402390, 10514896, 10592493, 10421128, 10571444
+ - BXD68 (may be ok, only one probe set 10338684 is problematic)
+ - BXD69, e.g., Probe set 10450161
+ - BXD73, e.g., Probe set 10341070, 1036098, 10402390, 10514896, 10587633, 10342568, 10421128
+ - BXD74, e.g., Probe set 10402390
+ - BXD80, e.g., Probe set 10341070, 1036098, 10592493, 10400109, 10338684, 10342568, 10421128, 10419465
+ - BXD83, e.g., Probe set 10450161, 10338684
+ - BXD87 (may be ok, only one probe set 10421128 is problematic)
+ - BXD89, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10357381, 10419465
+ - BXD93, e.g., Probe set 10402390, 10357381
+ - BALB/cByJ, e.g., Probe set 10388042, 1036098, 10587633, 10357381, 10342568, 10421128
+ - LP/J, e.g., Probe set 10592493
+ - DBA/2J, e.g., Probe set 10592493
+
+
+Data Evaluation Summary
+
+
+ - Before correction: eQLTs with LOD >10 (LRS>46.1): n = 638
+ - After strain assignment correction: eQLTs with LOD >10 (LRS>46.1): n = 820
+ - Before correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 237.9
+ - After correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 278.1
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
Table 1 (please confirm that these assignments are after correction)
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Phase |
+ Strain |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R5583S |
+ 1 |
+ 129P3/J |
+ 65 |
+ F |
+
+
+ | 2 |
+ R5584S |
+ 1 |
+ 129P3/J |
+ 66 |
+ M |
+
+
+ | 3 |
+ R5585S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+
+
+ | 4 |
+ R5586S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+
+
+ | 5 |
+ R5587S |
+ 1 |
+ 129X1/SvJ |
+ 65 |
+ F |
+
+
+ | 6 |
+ R5588S |
+ 1 |
+ 129X1/SvJ |
+ 66 |
+ M |
+
+
+ | 7 |
+ R6348S |
+ 3 |
+ B6D2F1 |
+ 67 |
+ F |
+
+
+ | 8 |
+ R6347S |
+ 3 |
+ B6D2F1 |
+ 62 |
+ F |
+
+
+ | 9 |
+ R5590S |
+ 1 |
+ B6D2F1 |
+ 79 |
+ M |
+
+
+ | 10 |
+ R5662S |
+ 1 |
+ BALB/cByJ |
+ 59 |
+ F |
+
+
+ | 11 |
+ R5664S |
+ 1 |
+ BALB/cByJ |
+ 59 |
+ M |
+
+
+ | 12 |
+ R5591S |
+ 1 |
+ BALB/cJ |
+ 51 |
+ F |
+
+
+ | 13 |
+ R5592S |
+ 1 |
+ BALB/cJ |
+ 51 |
+ M |
+
+
+ | 14 |
+ R6154S |
+ 2 |
+ BTBR T+ tf/J |
+ 60 |
+ F |
+
+
+ | 15 |
+ R6516S |
+ 3 |
+ BXD1 |
+ 82 |
+ F |
+
+
+ | 16 |
+ R6584S |
+ 3 |
+ BXD1 |
+ 95 |
+ M |
+
+
+ | 17 |
+ R5759S |
+ 1 |
+ BXD2 |
+ N/A |
+ F |
+
+
+ | 18 |
+ R5837S |
+ 1 |
+ BXD2 |
+ 106 |
+ M |
+
+
+ | 19 |
+ R5874S |
+ 2 |
+ BXD5 |
+ 86 |
+ F |
+
+
+ | 20 |
+ R6554S |
+ 3 |
+ BXD5 |
+ 60 |
+ M |
+
+
+ | 21 |
+ R6359S |
+ 3 |
+ BXD6 |
+ 72 |
+ F |
+
+
+ | 22 |
+ R5777S |
+ 1 |
+ BXD6 |
+ 149 |
+ M |
+
+
+ | 23 |
+ R6364S |
+ 3 |
+ BXD8 |
+ 76 |
+ F |
+
+
+ | 24 |
+ R5637S |
+ 1 |
+ BXD8 |
+ 71 |
+ F |
+
+
+ | 25 |
+ R6365S |
+ 3 |
+ BXD8 |
+ 76 |
+ M |
+
+
+ | 26 |
+ R5746S |
+ 1 |
+ BXD9 |
+ 70 |
+ F |
+
+
+ | 27 |
+ R5981S |
+ 2 |
+ BXD9 |
+ 67 |
+ M |
+
+
+ | 28 |
+ R5980S |
+ 2 |
+ BXD9 |
+ 67 |
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+ 1 |
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+ 1 |
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+ 1 |
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+ 1 |
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+
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+
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+ 1 |
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+
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+
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+
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+
+ | 186 |
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+ 3 |
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+
+
+ | 187 |
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+ 3 |
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+
+
+ | 188 |
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+ 1 |
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+ 73 |
+ M |
+
+
+ | 189 |
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+ 1 |
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+ 51 |
+ F |
+
+
+ | 190 |
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+ 1 |
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+ 69 |
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+
+
+ | 191 |
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+ 1 |
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+ 79 |
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+
+
+ | 192 |
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+ 1 |
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+ 60 |
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+
+
+ | 193 |
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+ 3 |
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+ 77 |
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+
+
+ | 194 |
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+ 3 |
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+ 85 |
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+
+
+ | 195 |
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+ 1 |
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+ 66 |
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+
+
+ | 196 |
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+ 1 |
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+ 66 |
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+
+
+ | 197 |
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+ 2 |
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+ 66 |
+ F |
+
+
+ | 198 |
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+ 3 |
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+ 66 |
+ M |
+
+
+ | 199 |
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+ 3 |
+ D2B6F1 |
+ 64 |
+ F |
+
+
+ | 200 |
+ R6353S |
+ 3 |
+ D2B6F1 |
+ 60 |
+ M |
+
+
+ | 201 |
+ R5605S |
+ 1 |
+ DBA/2J |
+ 79 |
+ F |
+
+
+ | 202 |
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+ 3 |
+ DBA/2J |
+ 83 |
+ M |
+
+
+ | 203 |
+ R6597S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 204 |
+ R5643S |
+ 1 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 205 |
+ R6598S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ M |
+
+
+ | 206 |
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+ 1 |
+ ILS |
+ 74 |
+ F |
+
+
+ | 207 |
+ R5607S |
+ 1 |
+ ILS |
+ 74 |
+ M |
+
+
+ | 208 |
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+ 1 |
+ ISS |
+ 97 |
+ M |
+
+
+ | 209 |
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+ 3 |
+ KK/HlJ |
+ 64 |
+ F |
+
+
+ | 210 |
+ R6444S |
+ 3 |
+ KK/HlJ |
+ 65 |
+ M |
+
+
+ | 211 |
+ R5702S |
+ 1 |
+ KK/HlJ |
+ 61 |
+ M |
+
+
+ | 212 |
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+ 1 |
+ LG/J |
+ 63 |
+ F |
+
+
+ | 213 |
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+ 1 |
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+ 65 |
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+
+
+ | 214 |
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+ 1 |
+ LP/J |
+ 65 |
+ F |
+
+
+ | 215 |
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+ 1 |
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+ 65 |
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+
+
+ | 216 |
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+ 3 |
+ MOLF/EiJ |
+ 60 |
+ F |
+
+
+ | 217 |
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+ 3 |
+ MOLF/EiJ |
+ 60 |
+ M |
+
+
+ | 218 |
+ R6544S |
+ 3 |
+ NOD/LtJ |
+ 77 |
+ F |
+
+
+ | 219 |
+ R5709S |
+ 1 |
+ NOD/LtJ |
+ 58 |
+ M |
+
+
+ | 220 |
+ R6601S |
+ 3 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 221 |
+ R5711S |
+ 1 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 222 |
+ R6427S |
+ 3 |
+ NZB/BlNJ |
+ 58 |
+ M |
+
+
+ | 223 |
+ R6150S |
+ 2 |
+ NZO/HlLtJ |
+ 71 |
+ F |
+
+
+ | 224 |
+ R6155S |
+ 2 |
+ NZW/LacJ |
+ 65 |
+ F |
+
+
+ | 225 |
+ R5654S |
+ 1 |
+ NZW/LacJ |
+ 60 |
+ M |
+
+
+ | 226 |
+ R5721S |
+ 1 |
+ PL/J |
+ 59 |
+ M |
+
+
+ | 227 |
+ R5616S |
+ 1 |
+ PWD/PhJ |
+ 60 |
+ M |
+
+
+ | 228 |
+ R5725S |
+ 1 |
+ PWK/PhJ |
+ 121 |
+ M |
+
+
+ | 229 |
+ R6174S |
+ 2 |
+ SJL/J |
+ 63 |
+ F |
+
+
+ | 230 |
+ R6350S |
+ 3 |
+ SJL/J |
+ 65 |
+ M |
+
+
+ | 231 |
+ R6419S |
+ 3 |
+ WSB/EiJ |
+ 60 |
+ F |
+
+
+ | 232 |
+ R5620S |
+ 1 |
+ WSB/EiJ |
+ 60 |
+ M |
+
+
+
+
+ |
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/Uthsc_spl_rmaex_1210/summary.rtf b/general/datasets/Uthsc_spl_rmaex_1210/summary.rtf
new file mode 100644
index 0000000..d9478f8
--- /dev/null
+++ b/general/datasets/Uthsc_spl_rmaex_1210/summary.rtf
@@ -0,0 +1,3 @@
+This is a near final release of a spleen gene expression data set generated by a DOD-funded consortium (Byrne, Kotb, Williams, and Lu). Please contact Lu Lu or Robert Williams regarding status of this data set. The initial data enterted in 2010 had many errors described below. The data set is much improved and has no known errors of strain assignment.
+
+Animals were generated at UTHSC by Lu Lu and colleagues. The spleen of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/Uthsc_spls1_rma_1210/cases.rtf b/general/datasets/Uthsc_spls1_rma_1210/cases.rtf
new file mode 100644
index 0000000..7fa108f
--- /dev/null
+++ b/general/datasets/Uthsc_spls1_rma_1210/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 111 strains, including 81 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1), and 26 other common inbred strains were quantified. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by Lu Lu and colleagues. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. XX strains have matched male and female samples. XX strains have male only samples (BXDX, XX, XX, XXX and XXX). XX strains have only female samples (BXDXX, XX, and XX.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/Uthsc_spls1_rma_1210/experiment-design.rtf b/general/datasets/Uthsc_spls1_rma_1210/experiment-design.rtf
new file mode 100644
index 0000000..a0aeba6
--- /dev/null
+++ b/general/datasets/Uthsc_spls1_rma_1210/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Processing. Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+Array Processing: All arrays were processed by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. The spleen was dissected by both Dr. Lu Lu and colleagues and Dr. Abdeltawab and colleagues. All arrays were run together (interleaved) as a single large batch.
diff --git a/general/datasets/Uthsc_spls1_rma_1210/notes.rtf b/general/datasets/Uthsc_spls1_rma_1210/notes.rtf
new file mode 100644
index 0000000..c7bb873
--- /dev/null
+++ b/general/datasets/Uthsc_spls1_rma_1210/notes.rtf
@@ -0,0 +1,4 @@
+Data Status and Use. This is a provisional release that will soon be replaced by a final corrected data set. In the interim this data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/Uthsc_spls1_rma_1210/processing.rtf b/general/datasets/Uthsc_spls1_rma_1210/processing.rtf
new file mode 100644
index 0000000..deaf264
--- /dev/null
+++ b/general/datasets/Uthsc_spls1_rma_1210/processing.rtf
@@ -0,0 +1,1932 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required some correction for batch effects and the data in this initial release incorporate any additional corrections. There are several additional confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest probe sets in this spleen data set accounts of XX% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the spleen data set can be mapped as a trait.
+
+
+Data Release. This data set was first uploaded into GeneNetwork by Arthur Centeno, October 11, 2010 and made accessible without a password to all users on November 1, 2010. The initial data release had numerous strain identification errors that have now largely been fixed. Based on an analysis of the top 20 Mendelian loci, the following 21 strains were likely to have been incorrectly identified or assigned in the current release:
+
+
+ - BXD8, e.g., Probe set 10450161, 1036098. 10338684
+ - BXD13, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10342568,
+ - BXD21 (may be ok, only one probe set 10338684 is problematic)
+ - BXD23 (may be ok, only two probe sets 10421128, 10419465 is problematic)
+ - BXD36 (may be ok, only one probe set 10421128 is problematic)
+ - BXD40, e.g., Probe set 10341070
+ - BXD43, e.g., Probe set 10450161, 1036098, 10338684
+ - BXD48, e.g., Probe set 1036098, 10402390, 10514896, 10592493, 10357381, 10342568, 10571444, 10419465
+ - BXD62, e.g., Probe set 1036098, 1036098, 10402390, 10514896, 10592493, 10421128, 10571444
+ - BXD68 (may be ok, only one probe set 10338684 is problematic)
+ - BXD69, e.g., Probe set 10450161
+ - BXD73, e.g., Probe set 10341070, 1036098, 10402390, 10514896, 10587633, 10342568, 10421128
+ - BXD74, e.g., Probe set 10402390
+ - BXD80, e.g., Probe set 10341070, 1036098, 10592493, 10400109, 10338684, 10342568, 10421128, 10419465
+ - BXD83, e.g., Probe set 10450161, 10338684
+ - BXD87 (may be ok, only one probe set 10421128 is problematic)
+ - BXD89, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10357381, 10419465
+ - BXD93, e.g., Probe set 10402390, 10357381
+ - BALB/cByJ, e.g., Probe set 10388042, 1036098, 10587633, 10357381, 10342568, 10421128
+ - LP/J, e.g., Probe set 10592493
+ - DBA/2J, e.g., Probe set 10592493
+
+
+Data Evaluation Summary
+
+
+ - Before correction: eQLTs with LOD >10 (LRS>46.1): n = 638
+ - After strain assignment correction: eQLTs with LOD >10 (LRS>46.1): n = 820
+ - Before correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 237.9
+ - After correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 278.1
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
Table 1 (please confirm that these assignments are after correction)
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Phase |
+ Strain |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R5583S |
+ 1 |
+ 129P3/J |
+ 65 |
+ F |
+
+
+ | 2 |
+ R5584S |
+ 1 |
+ 129P3/J |
+ 66 |
+ M |
+
+
+ | 3 |
+ R5585S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+
+
+ | 4 |
+ R5586S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+
+
+ | 5 |
+ R5587S |
+ 1 |
+ 129X1/SvJ |
+ 65 |
+ F |
+
+
+ | 6 |
+ R5588S |
+ 1 |
+ 129X1/SvJ |
+ 66 |
+ M |
+
+
+ | 7 |
+ R6348S |
+ 3 |
+ B6D2F1 |
+ 67 |
+ F |
+
+
+ | 8 |
+ R6347S |
+ 3 |
+ B6D2F1 |
+ 62 |
+ F |
+
+
+ | 9 |
+ R5590S |
+ 1 |
+ B6D2F1 |
+ 79 |
+ M |
+
+
+ | 10 |
+ R5662S |
+ 1 |
+ BALB/cByJ |
+ 59 |
+ F |
+
+
+ | 11 |
+ R5664S |
+ 1 |
+ BALB/cByJ |
+ 59 |
+ M |
+
+
+ | 12 |
+ R5591S |
+ 1 |
+ BALB/cJ |
+ 51 |
+ F |
+
+
+ | 13 |
+ R5592S |
+ 1 |
+ BALB/cJ |
+ 51 |
+ M |
+
+
+ | 14 |
+ R6154S |
+ 2 |
+ BTBR T+ tf/J |
+ 60 |
+ F |
+
+
+ | 15 |
+ R6516S |
+ 3 |
+ BXD1 |
+ 82 |
+ F |
+
+
+ | 16 |
+ R6584S |
+ 3 |
+ BXD1 |
+ 95 |
+ M |
+
+
+ | 17 |
+ R5759S |
+ 1 |
+ BXD2 |
+ N/A |
+ F |
+
+
+ | 18 |
+ R5837S |
+ 1 |
+ BXD2 |
+ 106 |
+ M |
+
+
+ | 19 |
+ R5874S |
+ 2 |
+ BXD5 |
+ 86 |
+ F |
+
+
+ | 20 |
+ R6554S |
+ 3 |
+ BXD5 |
+ 60 |
+ M |
+
+
+ | 21 |
+ R6359S |
+ 3 |
+ BXD6 |
+ 72 |
+ F |
+
+
+ | 22 |
+ R5777S |
+ 1 |
+ BXD6 |
+ 149 |
+ M |
+
+
+ | 23 |
+ R6364S |
+ 3 |
+ BXD8 |
+ 76 |
+ F |
+
+
+ | 24 |
+ R5637S |
+ 1 |
+ BXD8 |
+ 71 |
+ F |
+
+
+ | 25 |
+ R6365S |
+ 3 |
+ BXD8 |
+ 76 |
+ M |
+
+
+ | 26 |
+ R5746S |
+ 1 |
+ BXD9 |
+ 70 |
+ F |
+
+
+ | 27 |
+ R5981S |
+ 2 |
+ BXD9 |
+ 67 |
+ M |
+
+
+ | 28 |
+ R5980S |
+ 2 |
+ BXD9 |
+ 67 |
+ M |
+
+
+ | 29 |
+ R6182S |
+ 2 |
+ BXD11 |
+ 84 |
+ F |
+
+
+ | 30 |
+ R6486S |
+ 3 |
+ BXD11 |
+ 58 |
+ M |
+
+
+ | 31 |
+ R6711S2 |
+ 4 |
+ BXD12 |
+ 71 |
+ F |
+
+
+ | 32 |
+ R6608S |
+ 3 |
+ BXD12 |
+ 48 |
+ F |
+
+
+ | 33 |
+ R5885S |
+ 2 |
+ BXD12 |
+ 44 |
+ M |
+
+
+ | 34 |
+ R5755S |
+ 1 |
+ BXD13 |
+ 160 |
+ F |
+
+
+ | 35 |
+ R5887S |
+ 2 |
+ BXD13 |
+ 53 |
+ M |
+
+
+ | 36 |
+ R6180S |
+ 2 |
+ BXD14 |
+ 70 |
+ F |
+
+
+ | 37 |
+ R5669S |
+ 1 |
+ BXD14 |
+ 91 |
+ M |
+
+
+ | 38 |
+ R6456S |
+ 3 |
+ BXD15 |
+ 60 |
+ F |
+
+
+ | 39 |
+ R6622S |
+ 3 |
+ BXD15 |
+ 60 |
+ F |
+
+
+ | 40 |
+ R6626S |
+ 3 |
+ BXD15 |
+ 60 |
+ M |
+
+
+ | 41 |
+ R6181S |
+ 2 |
+ BXD16 |
+ 74 |
+ F |
+
+
+ | 42 |
+ R6515S |
+ 3 |
+ BXD16 |
+ 64 |
+ M |
+
+
+ | 43 |
+ R5673S |
+ 1 |
+ BXD18 |
+ 80 |
+ F |
+
+
+ | 44 |
+ R5674S |
+ 1 |
+ BXD18 |
+ 65 |
+ M |
+
+
+ | 45 |
+ R6553S |
+ 3 |
+ BXD19 |
+ 158 |
+ F |
+
+
+ | 46 |
+ R6551S |
+ 3 |
+ BXD19 |
+ 60 |
+ M |
+
+
+ | 47 |
+ R6643S4 |
+ 4 |
+ BXD20 |
+ 59 |
+ F |
+
+
+ | 48 |
+ R6595S |
+ 3 |
+ BXD20 |
+ 60 |
+ M |
+
+
+ | 49 |
+ R5735S |
+ 1 |
+ BXD21 |
+ 64 |
+ F |
+
+
+ | 50 |
+ R5892S |
+ 2 |
+ BXD21 |
+ 99 |
+ M |
+
+
+ | 51 |
+ R5896S |
+ 2 |
+ BXD22 |
+ 60 |
+ F |
+
+
+ | 52 |
+ R6414S |
+ 3 |
+ BXD22 |
+ 73 |
+ M |
+
+
+ | 53 |
+ R6550S |
+ 3 |
+ BXD23 |
+ 74 |
+ F |
+
+
+ | 54 |
+ R6586S |
+ 3 |
+ BXD23 |
+ 102 |
+ F |
+
+
+ | 55 |
+ R5630S |
+ 1 |
+ BXD24 |
+ 71 |
+ F |
+
+
+ | 56 |
+ R6356S |
+ 3 |
+ BXD24 |
+ 57 |
+ M |
+
+
+ | 57 |
+ R6162S |
+ 2 |
+ BXD25 |
+ 67 |
+ F |
+
+
+ | 58 |
+ R6625S |
+ 3 |
+ BXD25 |
+ 67 |
+ F |
+
+
+ | 59 |
+ R6642S4 |
+ 4 |
+ BXD25 |
+ 58 |
+ M |
+
+
+ | 60 |
+ R5761S |
+ 1 |
+ BXD27 |
+ N/A |
+ F |
+
+
+ | 61 |
+ R5763S |
+ 1 |
+ BXD27 |
+ 90 |
+ M |
+
+
+ | 62 |
+ R6621S |
+ 3 |
+ BXD28 |
+ 113 |
+ F |
+
+
+ | 63 |
+ R6548S |
+ 3 |
+ BXD28 |
+ 60 |
+ M |
+
+
+ | 64 |
+ R6547S |
+ 3 |
+ BXD29 |
+ 60 |
+ F |
+
+
+ | 65 |
+ R6453S |
+ 3 |
+ BXD31 |
+ 48 |
+ F |
+
+
+ | 66 |
+ R6452S |
+ 3 |
+ BXD31 |
+ 48 |
+ M |
+
+
+ | 67 |
+ R6583S |
+ 3 |
+ BXD32 |
+ 60 |
+ F |
+
+
+ | 68 |
+ R5765S |
+ 1 |
+ BXD32 |
+ 71 |
+ M |
+
+
+ | 69 |
+ R5689S |
+ 1 |
+ BXD33 |
+ 65 |
+ F |
+
+
+ | 70 |
+ R6450S |
+ 3 |
+ BXD33 |
+ 55 |
+ M |
+
+
+ | 71 |
+ R5767S |
+ 1 |
+ BXD34 |
+ 72 |
+ F |
+
+
+ | 72 |
+ R5900S |
+ 2 |
+ BXD34 |
+ 70 |
+ M |
+
+
+ | 73 |
+ R6588S |
+ 3 |
+ BXD36 |
+ 61 |
+ F |
+
+
+ | 74 |
+ R6490S |
+ 3 |
+ BXD36 |
+ 63 |
+ M |
+
+
+ | 75 |
+ R6417S |
+ 3 |
+ BXD38 |
+ 64 |
+ F |
+
+
+ | 76 |
+ R6439S |
+ 3 |
+ BXD38 |
+ 72 |
+ M |
+
+
+ | 77 |
+ R5769S |
+ 1 |
+ BXD39 |
+ N/A |
+ F |
+
+
+ | 78 |
+ R5771S |
+ 1 |
+ BXD39 |
+ 74 |
+ M |
+
+
+ | 79 |
+ R5773S |
+ 1 |
+ BXD40 |
+ N/A |
+ F |
+
+
+ | 80 |
+ R5775S |
+ 1 |
+ BXD40 |
+ N/A |
+ M |
+
+
+ | 81 |
+ R6494S |
+ 3 |
+ BXD41 |
+ 72 |
+ F |
+
+
+ | 82 |
+ R5910S |
+ 2 |
+ BXD42 |
+ 79 |
+ F |
+
+
+ | 83 |
+ R6493S |
+ 3 |
+ BXD42 |
+ 69 |
+ M |
+
+
+ | 84 |
+ R6341S |
+ 3 |
+ BXD43 |
+ 59 |
+ F |
+
+
+ | 85 |
+ R6401S |
+ 3 |
+ BXD43 |
+ 99 |
+ M |
+
+
+ | 86 |
+ R5916S |
+ 2 |
+ BXD43 |
+ 79 |
+ M |
+
+
+ | 87 |
+ R5839S |
+ 1 |
+ BXD44 |
+ 141 |
+ F |
+
+
+ | 88 |
+ R5779S |
+ 1 |
+ BXD44 |
+ 124 |
+ M |
+
+
+ | 89 |
+ R6405S |
+ 3 |
+ BXD45 |
+ 58 |
+ F |
+
+
+ | 90 |
+ R6610S |
+ 3 |
+ BXD45 |
+ 55 |
+ M |
+
+
+ | 91 |
+ R5922S |
+ 2 |
+ BXD48 |
+ 64 |
+ F |
+
+
+ | 92 |
+ R5925S |
+ 2 |
+ BXD48 |
+ 60 |
+ M |
+
+
+ | 93 |
+ R6719S1 |
+ 4 |
+ BXD49 |
+ 58 |
+ F |
+
+
+ | 94 |
+ R6485S |
+ 3 |
+ BXD49 |
+ 79 |
+ M |
+
+
+ | 95 |
+ R5781S |
+ 1 |
+ BXD50 |
+ 61 |
+ F |
+
+
+ | 96 |
+ R6464S |
+ 3 |
+ BXD51 |
+ 65 |
+ F |
+
+
+ | 97 |
+ R6585S |
+ 3 |
+ BXD51 |
+ 63 |
+ M |
+
+
+ | 98 |
+ R6500S |
+ 3 |
+ BXD55 |
+ 58 |
+ F |
+
+
+ | 99 |
+ R5938S |
+ 2 |
+ BXD55 |
+ 93 |
+ M |
+
+
+ | 100 |
+ R6504S |
+ 3 |
+ BXD56 |
+ 58 |
+ F |
+
+
+ | 101 |
+ R6503S |
+ 3 |
+ BXD56 |
+ 58 |
+ M |
+
+
+ | 102 |
+ R5783S |
+ 1 |
+ BXD60 |
+ 111 |
+ F |
+
+
+ | 103 |
+ R5784S |
+ 1 |
+ BXD60 |
+ 85 |
+ M |
+
+
+ | 104 |
+ R5786S |
+ 1 |
+ BXD61 |
+ 86 |
+ F |
+
+
+ | 105 |
+ R6449S |
+ 3 |
+ BXD61 |
+ 65 |
+ M |
+
+
+ | 106 |
+ R6716S1 |
+ 4 |
+ BXD62 |
+ 54 |
+ F |
+
+
+ | 107 |
+ R5790S |
+ 1 |
+ BXD62 |
+ 115 |
+ M |
+
+
+ | 108 |
+ R6519S |
+ 3 |
+ BXD63 |
+ 54 |
+ F |
+
+
+ | 109 |
+ R6717S1 |
+ 4 |
+ BXD63 |
+ 70 |
+ M |
+
+
+ | 110 |
+ R5792S |
+ 1 |
+ BXD64 |
+ 167 |
+ F |
+
+
+ | 111 |
+ R6641S4 |
+ 4 |
+ BXD64 |
+ 68 |
+ M |
+
+
+ | 112 |
+ R6630S |
+ 3 |
+ BXD64 |
+ 68 |
+ M |
+
+
+ | 113 |
+ R6477S |
+ 3 |
+ BXD65 |
+ 58 |
+ F |
+
+
+ | 114 |
+ R6628S |
+ 3 |
+ BXD65 |
+ 70 |
+ M |
+
+
+ | 115 |
+ R6511S |
+ 3 |
+ BXD66 |
+ 70 |
+ F |
+
+
+ | 116 |
+ R6448S |
+ 3 |
+ BXD66 |
+ 61 |
+ M |
+
+
+ | 117 |
+ R5794S |
+ 1 |
+ BXD66 |
+ 144 |
+ M |
+
+
+ | 118 |
+ R6502S |
+ 3 |
+ BXD67 |
+ 66 |
+ F |
+
+
+ | 119 |
+ R6545S |
+ 3 |
+ BXD67 |
+ 61 |
+ M |
+
+
+ | 120 |
+ R6337S |
+ 3 |
+ BXD68 |
+ 56 |
+ F |
+
+
+ | 121 |
+ R6594S |
+ 3 |
+ BXD68 |
+ 64 |
+ M |
+
+
+ | 122 |
+ R5796S |
+ 1 |
+ BXD69 |
+ 85 |
+ F |
+
+
+ | 123 |
+ R5798S |
+ 1 |
+ BXD69 |
+ 98 |
+ M |
+
+
+ | 124 |
+ R6402S |
+ 3 |
+ BXD70 |
+ 93 |
+ F |
+
+
+ | 125 |
+ R5841S |
+ 1 |
+ BXD70 |
+ 121 |
+ F |
+
+
+ | 126 |
+ R6592S |
+ 3 |
+ BXD70 |
+ 59 |
+ M |
+
+
+ | 127 |
+ R6328S |
+ 3 |
+ BXD71 |
+ 87 |
+ F |
+
+
+ | 128 |
+ R5967S |
+ 2 |
+ BXD71 |
+ 64 |
+ M |
+
+
+ | 129 |
+ R5969S |
+ 2 |
+ BXD73 |
+ 64 |
+ F |
+
+
+ | 130 |
+ R5800S |
+ 1 |
+ BXD73 |
+ 120 |
+ M |
+
+
+ | 131 |
+ R6646S |
+ 3 |
+ BXD74 |
+ 40 |
+ F |
+
+
+ | 132 |
+ R6524S |
+ 3 |
+ BXD74 |
+ 72 |
+ M |
+
+
+ | 133 |
+ R6445S |
+ 3 |
+ BXD75 |
+ 85 |
+ F |
+
+
+ | 134 |
+ R5843S |
+ 1 |
+ BXD75 |
+ 103 |
+ F |
+
+
+ | 135 |
+ R5845S |
+ 1 |
+ BXD75 |
+ 103 |
+ M |
+
+
+ | 136 |
+ R6604S |
+ 3 |
+ BXD77 |
+ 64 |
+ F |
+
+
+ | 137 |
+ R6513S |
+ 3 |
+ BXD77 |
+ 72 |
+ M |
+
+
+ | 138 |
+ R6582S |
+ 3 |
+ BXD78 |
+ 144 |
+ F |
+
+
+ | 139 |
+ R6563S |
+ 3 |
+ BXD78 |
+ 95 |
+ M |
+
+
+ | 140 |
+ R6645S4 |
+ 4 |
+ BXD79 |
+ 66 |
+ F |
+
+
+ | 141 |
+ R5806S |
+ 1 |
+ BXD79 |
+ 78 |
+ M |
+
+
+ | 142 |
+ R5847S |
+ 1 |
+ BXD80 |
+ 89 |
+ F |
+
+
+ | 143 |
+ R5852S |
+ 1 |
+ BXD80 |
+ 79 |
+ M |
+
+
+ | 144 |
+ R6562S |
+ 3 |
+ BXD81 |
+ 99 |
+ F |
+
+
+ | 145 |
+ R6468S |
+ 3 |
+ BXD81 |
+ 65 |
+ M |
+
+
+ | 146 |
+ R6560S |
+ 3 |
+ BXD82 |
+ 85 |
+ F |
+
+
+ | 147 |
+ R6512S |
+ 3 |
+ BXD83 |
+ 68 |
+ F |
+
+
+ | 148 |
+ R5810S |
+ 1 |
+ BXD83 |
+ 139 |
+ M |
+
+
+ | 149 |
+ R6510S |
+ 3 |
+ BXD84 |
+ 87 |
+ F |
+
+
+ | 150 |
+ R5970S |
+ 2 |
+ BXD84 |
+ 107 |
+ F |
+
+
+ | 151 |
+ R6603S |
+ 3 |
+ BXD84 |
+ 99 |
+ M |
+
+
+ | 152 |
+ R6517S |
+ 3 |
+ BXD85 |
+ 58 |
+ F |
+
+
+ | 153 |
+ R6718S1 |
+ 4 |
+ BXD85 |
+ 86 |
+ M |
+
+
+ | 154 |
+ R5812S |
+ 1 |
+ BXD86 |
+ 61 |
+ F |
+
+
+ | 155 |
+ R5814S |
+ 1 |
+ BXD86 |
+ 59 |
+ M |
+
+
+ | 156 |
+ R5816S |
+ 1 |
+ BXD87 |
+ 112 |
+ F |
+
+
+ | 157 |
+ R6488S |
+ 3 |
+ BXD87 |
+ 137 |
+ M |
+
+
+ | 158 |
+ R6580S |
+ 3 |
+ BXD88 |
+ 125 |
+ F |
+
+
+ | 159 |
+ R5977S |
+ 2 |
+ BXD89 |
+ 68 |
+ F |
+
+
+ | 160 |
+ R5979S |
+ 2 |
+ BXD89 |
+ 79 |
+ M |
+
+
+ | 161 |
+ R5978S |
+ 2 |
+ BXD89 |
+ 79 |
+ M |
+
+
+ | 162 |
+ R5818S |
+ 1 |
+ BXD90 |
+ 106 |
+ F |
+
+
+ | 163 |
+ R5820S |
+ 1 |
+ BXD90 |
+ 131 |
+ M |
+
+
+ | 164 |
+ R6343S |
+ 3 |
+ BXD92 |
+ 62 |
+ F |
+
+
+ | 165 |
+ R5984S |
+ 2 |
+ BXD92 |
+ 55 |
+ M |
+
+
+ | 166 |
+ R6581S |
+ 3 |
+ BXD93 |
+ 173 |
+ M |
+
+
+ | 167 |
+ R6557S |
+ 3 |
+ BXD93 |
+ 126 |
+ M |
+
+
+ | 168 |
+ R6509S |
+ 3 |
+ BXD95 |
+ 59 |
+ F |
+
+
+ | 169 |
+ R5822S |
+ 1 |
+ BXD95 |
+ 89 |
+ M |
+
+
+ | 170 |
+ R6640S4 |
+ 4 |
+ BXD96 |
+ 70 |
+ F |
+
+
+ | 171 |
+ R6514S |
+ 3 |
+ BXD96 |
+ 64 |
+ M |
+
+
+ | 172 |
+ R6506S |
+ 3 |
+ BXD97 |
+ 78 |
+ F |
+
+
+ | 173 |
+ R5849S |
+ 1 |
+ BXD97 |
+ 130 |
+ F |
+
+
+ | 174 |
+ R6591S |
+ 3 |
+ BXD97 |
+ 122 |
+ M |
+
+
+ | 175 |
+ R5990S |
+ 2 |
+ BXD98 |
+ 65 |
+ F |
+
+
+ | 176 |
+ R6596S |
+ 3 |
+ BXD98 |
+ 67 |
+ M |
+
+
+ | 177 |
+ R5993S |
+ 2 |
+ BXD99 |
+ 74 |
+ F |
+
+
+ | 178 |
+ R5995S |
+ 2 |
+ BXD99 |
+ 50 |
+ M |
+
+
+ | 179 |
+ R6607S |
+ 3 |
+ BXD100 |
+ 75 |
+ F |
+
+
+ | 180 |
+ R6411S |
+ 3 |
+ BXD100 |
+ 104 |
+ M |
+
+
+ | 181 |
+ R6508S |
+ 3 |
+ BXD101 |
+ 59 |
+ F |
+
+
+ | 182 |
+ R5593S |
+ 1 |
+ BXD101 |
+ 59 |
+ M |
+
+
+ | 183 |
+ R6523S |
+ 3 |
+ BXD102 |
+ 60 |
+ F |
+
+
+ | 184 |
+ R6466S |
+ 3 |
+ BXD102 |
+ 50 |
+ M |
+
+
+ | 185 |
+ R6404S |
+ 3 |
+ BXD103 |
+ 72 |
+ F |
+
+
+ | 186 |
+ R6609S |
+ 3 |
+ BXD103 |
+ 57 |
+ M |
+
+
+ | 187 |
+ R6555S |
+ 3 |
+ C57BL/10J |
+ 73 |
+ M |
+
+
+ | 188 |
+ R5596S |
+ 1 |
+ C57BL/10J |
+ 73 |
+ M |
+
+
+ | 189 |
+ R5597S |
+ 1 |
+ C57BL/6ByJ |
+ 51 |
+ F |
+
+
+ | 190 |
+ R5598S |
+ 1 |
+ C57BL/6ByJ |
+ 69 |
+ M |
+
+
+ | 191 |
+ R5600S |
+ 1 |
+ C57BL/6J |
+ 79 |
+ F |
+
+
+ | 192 |
+ R5599S |
+ 1 |
+ C57BL/6J |
+ 60 |
+ F |
+
+
+ | 193 |
+ R6451S |
+ 3 |
+ C57BL/6J |
+ 77 |
+ M |
+
+
+ | 194 |
+ R6410S |
+ 3 |
+ C57BL/6J |
+ 85 |
+ M |
+
+
+ | 195 |
+ R5603S |
+ 1 |
+ C57BLKS/J |
+ 66 |
+ F |
+
+
+ | 196 |
+ R5604S |
+ 1 |
+ C57BLKS/J |
+ 66 |
+ M |
+
+
+ | 197 |
+ R5996S |
+ 2 |
+ CBA/CaJ |
+ 66 |
+ F |
+
+
+ | 198 |
+ R6349S |
+ 3 |
+ CBA/CaJ |
+ 66 |
+ M |
+
+
+ | 199 |
+ R6458S |
+ 3 |
+ D2B6F1 |
+ 64 |
+ F |
+
+
+ | 200 |
+ R6353S |
+ 3 |
+ D2B6F1 |
+ 60 |
+ M |
+
+
+ | 201 |
+ R5605S |
+ 1 |
+ DBA/2J |
+ 79 |
+ F |
+
+
+ | 202 |
+ R6446S |
+ 3 |
+ DBA/2J |
+ 83 |
+ M |
+
+
+ | 203 |
+ R6597S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 204 |
+ R5643S |
+ 1 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 205 |
+ R6598S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ M |
+
+
+ | 206 |
+ R5606S |
+ 1 |
+ ILS |
+ 74 |
+ F |
+
+
+ | 207 |
+ R5607S |
+ 1 |
+ ILS |
+ 74 |
+ M |
+
+
+ | 208 |
+ R5610S |
+ 1 |
+ ISS |
+ 97 |
+ M |
+
+
+ | 209 |
+ R6627S |
+ 3 |
+ KK/HlJ |
+ 64 |
+ F |
+
+
+ | 210 |
+ R6444S |
+ 3 |
+ KK/HlJ |
+ 65 |
+ M |
+
+
+ | 211 |
+ R5702S |
+ 1 |
+ KK/HlJ |
+ 61 |
+ M |
+
+
+ | 212 |
+ R5613S |
+ 1 |
+ LG/J |
+ 63 |
+ F |
+
+
+ | 213 |
+ R5704S |
+ 1 |
+ LG/J |
+ 65 |
+ M |
+
+
+ | 214 |
+ R5614S |
+ 1 |
+ LP/J |
+ 65 |
+ F |
+
+
+ | 215 |
+ R5615S |
+ 1 |
+ LP/J |
+ 65 |
+ M |
+
+
+ | 216 |
+ R6599S |
+ 3 |
+ MOLF/EiJ |
+ 60 |
+ F |
+
+
+ | 217 |
+ R6606S |
+ 3 |
+ MOLF/EiJ |
+ 60 |
+ M |
+
+
+ | 218 |
+ R6544S |
+ 3 |
+ NOD/LtJ |
+ 77 |
+ F |
+
+
+ | 219 |
+ R5709S |
+ 1 |
+ NOD/LtJ |
+ 58 |
+ M |
+
+
+ | 220 |
+ R6601S |
+ 3 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 221 |
+ R5711S |
+ 1 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 222 |
+ R6427S |
+ 3 |
+ NZB/BlNJ |
+ 58 |
+ M |
+
+
+ | 223 |
+ R6150S |
+ 2 |
+ NZO/HlLtJ |
+ 71 |
+ F |
+
+
+ | 224 |
+ R6155S |
+ 2 |
+ NZW/LacJ |
+ 65 |
+ F |
+
+
+ | 225 |
+ R5654S |
+ 1 |
+ NZW/LacJ |
+ 60 |
+ M |
+
+
+ | 226 |
+ R5721S |
+ 1 |
+ PL/J |
+ 59 |
+ M |
+
+
+ | 227 |
+ R5616S |
+ 1 |
+ PWD/PhJ |
+ 60 |
+ M |
+
+
+ | 228 |
+ R5725S |
+ 1 |
+ PWK/PhJ |
+ 121 |
+ M |
+
+
+ | 229 |
+ R6174S |
+ 2 |
+ SJL/J |
+ 63 |
+ F |
+
+
+ | 230 |
+ R6350S |
+ 3 |
+ SJL/J |
+ 65 |
+ M |
+
+
+ | 231 |
+ R6419S |
+ 3 |
+ WSB/EiJ |
+ 60 |
+ F |
+
+
+ | 232 |
+ R5620S |
+ 1 |
+ WSB/EiJ |
+ 60 |
+ M |
+
+
+
+
+ |
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/Uthsc_spls1_rma_1210/summary.rtf b/general/datasets/Uthsc_spls1_rma_1210/summary.rtf
new file mode 100644
index 0000000..d9478f8
--- /dev/null
+++ b/general/datasets/Uthsc_spls1_rma_1210/summary.rtf
@@ -0,0 +1,3 @@
+This is a near final release of a spleen gene expression data set generated by a DOD-funded consortium (Byrne, Kotb, Williams, and Lu). Please contact Lu Lu or Robert Williams regarding status of this data set. The initial data enterted in 2010 had many errors described below. The data set is much improved and has no known errors of strain assignment.
+
+Animals were generated at UTHSC by Lu Lu and colleagues. The spleen of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/Uthsc_spls2_rma_1210/cases.rtf b/general/datasets/Uthsc_spls2_rma_1210/cases.rtf
new file mode 100644
index 0000000..7fa108f
--- /dev/null
+++ b/general/datasets/Uthsc_spls2_rma_1210/cases.rtf
@@ -0,0 +1,3 @@
+Cases. A total of 111 strains, including 81 BXD strains, both parental strains (C57BL/6J and DBA/2J) and both reciprocal F1 hybrids (B6D2F1 and D2B6F1), and 26 other common inbred strains were quantified. In most cases, two arrays were processed per strain--one for males and one for females. All tissue and RNA was extracted by Lu Lu and colleagues. Samples were pooled by sex and usually include at least two cases per sex and strain.
+
+Sex Balance. XX strains have matched male and female samples. XX strains have male only samples (BXDX, XX, XX, XXX and XXX). XX strains have only female samples (BXDXX, XX, and XX.) Please review the expression data for Xist probe set 10606178. This non-coding RNA is expressed highly only in females and can be used to check the sex of a sample or pool of tissue. Ddx3y probe set 10608138 can also be used. This is a Y chromosome gene that is expressed abundantly in male samples and at background levels in female samples.
diff --git a/general/datasets/Uthsc_spls2_rma_1210/experiment-design.rtf b/general/datasets/Uthsc_spls2_rma_1210/experiment-design.rtf
new file mode 100644
index 0000000..a0aeba6
--- /dev/null
+++ b/general/datasets/Uthsc_spls2_rma_1210/experiment-design.rtf
@@ -0,0 +1,3 @@
+RNA Processing. Total RNA was purified using the RNAeasy micro kit on the QIAcube system (www.qiagen.com). RNA purity and concentration was checked using 260/280 nm absorbance ratio and RNA integrity was analyzed using the Agilent Bioanalyzer 2100 (Agilent Technologies).
+
+Array Processing: All arrays were processed by Lorne Rose in the UTHSC Molecular Resources Center (MRC), Memphis TN. The table below provides a summary of cases, sex, and age. The spleen was dissected by both Dr. Lu Lu and colleagues and Dr. Abdeltawab and colleagues. All arrays were run together (interleaved) as a single large batch.
diff --git a/general/datasets/Uthsc_spls2_rma_1210/notes.rtf b/general/datasets/Uthsc_spls2_rma_1210/notes.rtf
new file mode 100644
index 0000000..c7bb873
--- /dev/null
+++ b/general/datasets/Uthsc_spls2_rma_1210/notes.rtf
@@ -0,0 +1,4 @@
+Data Status and Use. This is a provisional release that will soon be replaced by a final corrected data set. In the interim this data set is open for exploration and use for focused analysis of single genes. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data regarding the best citation.
+This data set is not yet freely available for global analysis. This data set has not yet been used or described in any publication. Please see the GeneNetwork data sharing policy for more background on data use.
+
+Contact. Please contact Robert W. Williams at rwilliams@uthsc.edu regarding use of these data.
diff --git a/general/datasets/Uthsc_spls2_rma_1210/processing.rtf b/general/datasets/Uthsc_spls2_rma_1210/processing.rtf
new file mode 100644
index 0000000..deaf264
--- /dev/null
+++ b/general/datasets/Uthsc_spls2_rma_1210/processing.rtf
@@ -0,0 +1,1932 @@
+Data Processing. Array data sets were generated by the vendors GCOS system. Expression values were logged and then were further normalized and rescaled so that the mean value for each array data set is 8 units with a standard deviation of 2 units. Data were processed by Arthur Centeno.
+
+Batch Effects. This data set required some correction for batch effects and the data in this initial release incorporate any additional corrections. There are several additional confounder-like factors that should be considered:
+
+
+ - Sex imbalance in the sample: use probe sets for Xist as correction in partial correlation
+ - Background noise factors: examine and use probe sets with very low expression using the search "mean=(3.900 4.135)". This will extract the probe sets with the lowest expression. (Note that the number 54 is less than the total number of cases in this data set; important in computing principal components.) Add these probe sets to your collection window and then compute the correlation matrix. Use the first few principal components as surrogates for nuisance factors in partial correlation analysis. The first principal component of the lowest probe sets in this spleen data set accounts of XX% of the the variance. Mapping of this noise trait can be used to evaluate the effects of shared noise on QTL results. The first principal component in the spleen data set can be mapped as a trait.
+
+
+Data Release. This data set was first uploaded into GeneNetwork by Arthur Centeno, October 11, 2010 and made accessible without a password to all users on November 1, 2010. The initial data release had numerous strain identification errors that have now largely been fixed. Based on an analysis of the top 20 Mendelian loci, the following 21 strains were likely to have been incorrectly identified or assigned in the current release:
+
+
+ - BXD8, e.g., Probe set 10450161, 1036098. 10338684
+ - BXD13, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10342568,
+ - BXD21 (may be ok, only one probe set 10338684 is problematic)
+ - BXD23 (may be ok, only two probe sets 10421128, 10419465 is problematic)
+ - BXD36 (may be ok, only one probe set 10421128 is problematic)
+ - BXD40, e.g., Probe set 10341070
+ - BXD43, e.g., Probe set 10450161, 1036098, 10338684
+ - BXD48, e.g., Probe set 1036098, 10402390, 10514896, 10592493, 10357381, 10342568, 10571444, 10419465
+ - BXD62, e.g., Probe set 1036098, 1036098, 10402390, 10514896, 10592493, 10421128, 10571444
+ - BXD68 (may be ok, only one probe set 10338684 is problematic)
+ - BXD69, e.g., Probe set 10450161
+ - BXD73, e.g., Probe set 10341070, 1036098, 10402390, 10514896, 10587633, 10342568, 10421128
+ - BXD74, e.g., Probe set 10402390
+ - BXD80, e.g., Probe set 10341070, 1036098, 10592493, 10400109, 10338684, 10342568, 10421128, 10419465
+ - BXD83, e.g., Probe set 10450161, 10338684
+ - BXD87 (may be ok, only one probe set 10421128 is problematic)
+ - BXD89, e.g., Probe set 10450161, 1036098, 10402390, 10592493, 10357381, 10419465
+ - BXD93, e.g., Probe set 10402390, 10357381
+ - BALB/cByJ, e.g., Probe set 10388042, 1036098, 10587633, 10357381, 10342568, 10421128
+ - LP/J, e.g., Probe set 10592493
+ - DBA/2J, e.g., Probe set 10592493
+
+
+Data Evaluation Summary
+
+
+ - Before correction: eQLTs with LOD >10 (LRS>46.1): n = 638
+ - After strain assignment correction: eQLTs with LOD >10 (LRS>46.1): n = 820
+ - Before correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 237.9
+ - After correction: eQTL with high LOD and LRS: Trait ID 10450161 (H2-Ea-ps) LOD = 51.6, LRS = 278.1
+ - Lowest mean value: Trait ID 10344361, mean = 3.998
+ - Highest mean value: Trait ID 10598025, mean = 14.475 (MT-ND1)
+ - Greatest sex difference: Trait ID: 10606178 (Xist)
+ - Great variation within and among strains: Trait ID 10454192 (Ttr
+
Table 1 (please confirm that these assignments are after correction)
+
+
+
+
+
+
+
+
+
+ | Index |
+ Array ID |
+ Phase |
+ Strain |
+ Age |
+ Sex |
+
+
+ | 1 |
+ R5583S |
+ 1 |
+ 129P3/J |
+ 65 |
+ F |
+
+
+ | 2 |
+ R5584S |
+ 1 |
+ 129P3/J |
+ 66 |
+ M |
+
+
+ | 3 |
+ R5585S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ F |
+
+
+ | 4 |
+ R5586S |
+ 1 |
+ 129S1/SvImJ |
+ 66 |
+ M |
+
+
+ | 5 |
+ R5587S |
+ 1 |
+ 129X1/SvJ |
+ 65 |
+ F |
+
+
+ | 6 |
+ R5588S |
+ 1 |
+ 129X1/SvJ |
+ 66 |
+ M |
+
+
+ | 7 |
+ R6348S |
+ 3 |
+ B6D2F1 |
+ 67 |
+ F |
+
+
+ | 8 |
+ R6347S |
+ 3 |
+ B6D2F1 |
+ 62 |
+ F |
+
+
+ | 9 |
+ R5590S |
+ 1 |
+ B6D2F1 |
+ 79 |
+ M |
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+
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+
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+
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+
+ | 182 |
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+
+ | 183 |
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+
+ | 184 |
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+
+ | 185 |
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+
+ | 186 |
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+ 3 |
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+
+
+ | 187 |
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+ 3 |
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+
+
+ | 188 |
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+ 1 |
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+ 73 |
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+
+
+ | 189 |
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+ 1 |
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+ 51 |
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+
+
+ | 190 |
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+ 1 |
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+
+
+ | 191 |
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+ 1 |
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+
+
+ | 192 |
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+ 1 |
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+
+
+ | 193 |
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+ 3 |
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+ 77 |
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+
+
+ | 194 |
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+ 3 |
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+ 85 |
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+
+
+ | 195 |
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+ 1 |
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+
+
+ | 196 |
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+ 1 |
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+ 66 |
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+
+
+ | 197 |
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+ 2 |
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+
+
+ | 198 |
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+ 3 |
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+
+
+ | 199 |
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+ 3 |
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+
+
+ | 200 |
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+ 3 |
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+ 60 |
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+
+
+ | 201 |
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+ 1 |
+ DBA/2J |
+ 79 |
+ F |
+
+
+ | 202 |
+ R6446S |
+ 3 |
+ DBA/2J |
+ 83 |
+ M |
+
+
+ | 203 |
+ R6597S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 204 |
+ R5643S |
+ 1 |
+ FVB/NJ |
+ 60 |
+ F |
+
+
+ | 205 |
+ R6598S |
+ 3 |
+ FVB/NJ |
+ 60 |
+ M |
+
+
+ | 206 |
+ R5606S |
+ 1 |
+ ILS |
+ 74 |
+ F |
+
+
+ | 207 |
+ R5607S |
+ 1 |
+ ILS |
+ 74 |
+ M |
+
+
+ | 208 |
+ R5610S |
+ 1 |
+ ISS |
+ 97 |
+ M |
+
+
+ | 209 |
+ R6627S |
+ 3 |
+ KK/HlJ |
+ 64 |
+ F |
+
+
+ | 210 |
+ R6444S |
+ 3 |
+ KK/HlJ |
+ 65 |
+ M |
+
+
+ | 211 |
+ R5702S |
+ 1 |
+ KK/HlJ |
+ 61 |
+ M |
+
+
+ | 212 |
+ R5613S |
+ 1 |
+ LG/J |
+ 63 |
+ F |
+
+
+ | 213 |
+ R5704S |
+ 1 |
+ LG/J |
+ 65 |
+ M |
+
+
+ | 214 |
+ R5614S |
+ 1 |
+ LP/J |
+ 65 |
+ F |
+
+
+ | 215 |
+ R5615S |
+ 1 |
+ LP/J |
+ 65 |
+ M |
+
+
+ | 216 |
+ R6599S |
+ 3 |
+ MOLF/EiJ |
+ 60 |
+ F |
+
+
+ | 217 |
+ R6606S |
+ 3 |
+ MOLF/EiJ |
+ 60 |
+ M |
+
+
+ | 218 |
+ R6544S |
+ 3 |
+ NOD/LtJ |
+ 77 |
+ F |
+
+
+ | 219 |
+ R5709S |
+ 1 |
+ NOD/LtJ |
+ 58 |
+ M |
+
+
+ | 220 |
+ R6601S |
+ 3 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 221 |
+ R5711S |
+ 1 |
+ NZB/BlNJ |
+ 61 |
+ F |
+
+
+ | 222 |
+ R6427S |
+ 3 |
+ NZB/BlNJ |
+ 58 |
+ M |
+
+
+ | 223 |
+ R6150S |
+ 2 |
+ NZO/HlLtJ |
+ 71 |
+ F |
+
+
+ | 224 |
+ R6155S |
+ 2 |
+ NZW/LacJ |
+ 65 |
+ F |
+
+
+ | 225 |
+ R5654S |
+ 1 |
+ NZW/LacJ |
+ 60 |
+ M |
+
+
+ | 226 |
+ R5721S |
+ 1 |
+ PL/J |
+ 59 |
+ M |
+
+
+ | 227 |
+ R5616S |
+ 1 |
+ PWD/PhJ |
+ 60 |
+ M |
+
+
+ | 228 |
+ R5725S |
+ 1 |
+ PWK/PhJ |
+ 121 |
+ M |
+
+
+ | 229 |
+ R6174S |
+ 2 |
+ SJL/J |
+ 63 |
+ F |
+
+
+ | 230 |
+ R6350S |
+ 3 |
+ SJL/J |
+ 65 |
+ M |
+
+
+ | 231 |
+ R6419S |
+ 3 |
+ WSB/EiJ |
+ 60 |
+ F |
+
+
+ | 232 |
+ R5620S |
+ 1 |
+ WSB/EiJ |
+ 60 |
+ M |
+
+
+
+
+ |
+
+
+
+
+
+
+
+
+
diff --git a/general/datasets/Uthsc_spls2_rma_1210/summary.rtf b/general/datasets/Uthsc_spls2_rma_1210/summary.rtf
new file mode 100644
index 0000000..d9478f8
--- /dev/null
+++ b/general/datasets/Uthsc_spls2_rma_1210/summary.rtf
@@ -0,0 +1,3 @@
+This is a near final release of a spleen gene expression data set generated by a DOD-funded consortium (Byrne, Kotb, Williams, and Lu). Please contact Lu Lu or Robert Williams regarding status of this data set. The initial data enterted in 2010 had many errors described below. The data set is much improved and has no known errors of strain assignment.
+
+Animals were generated at UTHSC by Lu Lu and colleagues. The spleen of untreated young adult mice was profiled using the Affymetrix GeneChip Mouse Gene 1.0 ST array that contains approximately 34,728 probe sets that target approximately 29,000 well defined transcripts (RefSeq mRNA isoforms) and essentially all known protein coding genes in mouse. This array is an "exon style" array with multiple probes in all known exons of each gene (an average of about 27 per gene) and is an abridged version of the Affymetrix Exon 1.0 ST array. However, it also does contain some probes that target non-coding RNAs and even miRNA precursors (search "ncrna").
diff --git a/general/datasets/Uthsc_str_rankinv_1210/summary.rtf b/general/datasets/Uthsc_str_rankinv_1210/summary.rtf
new file mode 100644
index 0000000..cc6ac0f
--- /dev/null
+++ b/general/datasets/Uthsc_str_rankinv_1210/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 42, Name: HQF BXD Striatum ILM6.1 (Dec10)
\ No newline at end of file
diff --git a/general/datasets/Uthsc_striatum_rankinv_1210/summary.rtf b/general/datasets/Uthsc_striatum_rankinv_1210/summary.rtf
new file mode 100644
index 0000000..cc6ac0f
--- /dev/null
+++ b/general/datasets/Uthsc_striatum_rankinv_1210/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 42, Name: HQF BXD Striatum ILM6.1 (Dec10)
\ No newline at end of file
diff --git a/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/acknowledgment.rtf b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/acknowledgment.rtf
new file mode 100644
index 0000000..1853348
--- /dev/null
+++ b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/acknowledgment.rtf
@@ -0,0 +1 @@
+We thank Varigenix and Charle River Laboratory for their donation of BXD cyropreserved hepatcytes. We thank Jesse Ingels for preparing RNA samples. We thank Lorne Rose and the UTHSC Molecular Resource Center for processing RNA samples and generating array data. We thank Arthur Centeno for data entry. We thank the UTHSC CITG and the UT-ORNL Governor's chair for support of microarray analysis.
diff --git a/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/cases.rtf b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/cases.rtf
new file mode 100644
index 0000000..e06c56f
--- /dev/null
+++ b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/cases.rtf
@@ -0,0 +1,266 @@
+
+
+
+ | Sample ID |
+ Varigenix Strain |
+ Sex |
+ RNA Concentrations
+ ng/ul |
+ 260/280 |
+ 260/230 |
+ Agilent
+ Concentration(ng/ul) |
+ RIN |
+
+
+ | V1 |
+ BXD32 |
+ M |
+ 1414.8 |
+ 2.09 |
+ 2.21 |
+ 3,062 |
+ 9.3 |
+
+
+ | V2 |
+ BXD1 |
+ M |
+ 1608.9 |
+ 2.11 |
+ 2.24 |
+ 3,102 |
+ 9.3 |
+
+
+ | V3 |
+ BXD5 |
+ M |
+ 1263.91 |
+ 2.1 |
+ 2.09 |
+ 2,460 |
+ 8.5 |
+
+
+ | V4 |
+ BXD31 |
+ M |
+ 1793.95 |
+ 2.1 |
+ 2.22 |
+ 3,387 |
+ 8.5 |
+
+
+ | V5 |
+ BXD8 |
+ M |
+ 1193.21 |
+ 2.1 |
+ 2.17 |
+ 2,293 |
+ 9.3 |
+
+
+ | V6 |
+ BXD18 |
+ M |
+ 1041.05 |
+ 2.13 |
+ 2.17 |
+ 2,115 |
+ 9.2 |
+
+
+ | V7 |
+ BXD42 |
+ M |
+ 398.28 |
+ 1.99 |
+ 2.28 |
+ 1,519 |
+ 8.3 |
+
+
+ | V8 |
+ BXD29 |
+ M |
+ 477.37 |
+ 2.02 |
+ 2.24 |
+ 1,301 |
+ 8.1 |
+
+
+ | V9 |
+ BXD21 |
+ M |
+ 414.6 |
+ 2 |
+ 2.27 |
+ 1,174 |
+ 8.3 |
+
+
+ | V10 |
+ BXD27 |
+ M |
+ 438.61 |
+ 2.02 |
+ 2.27 |
+ 1,100 |
+ 8.1 |
+
+
+ | V11 |
+ BXD16 |
+ M |
+ 436.21 |
+ 2.01 |
+ 2.27 |
+ 868 |
+ 8.5 |
+
+
+ | V12 |
+ BXD19 |
+ M |
+ 489.12 |
+ 2.01 |
+ 2.26 |
+ 1,277 |
+ 8 |
+
+
+ | V13 |
+ BXD22 |
+ M |
+ 1032.89 |
+ 2.09 |
+ 2.22 |
+ 2,060 |
+ 7.8 |
+
+
+ | V14 |
+ BXD38 |
+ M |
+ 510.24 |
+ 2.01 |
+ 2.22 |
+ 1,213 |
+ 8 |
+
+
+ | V15 |
+ BXD34 |
+ M |
+ 1021.26 |
+ 2.09 |
+ 2.24 |
+ 1,514 |
+ 8.2 |
+
+
+ | V16 |
+ BXD20 |
+ M |
+ 330.85 |
+ 2 |
+ 2.27 |
+ 901 |
+ 8.1 |
+
+
+ | V17 |
+ BXD15 |
+ M |
+ 1220.54 |
+ 2.1 |
+ 2.21 |
+ 1,909 |
+ 8.1 |
+
+
+ | V18 |
+ BXD6 |
+ M |
+ 1001.04 |
+ 2.09 |
+ 2.2 |
+ 1,523 |
+ 8.3 |
+
+
+ | V19 |
+ BXD13 |
+ M |
+ 1241.88 |
+ 2.1 |
+ 2.21 |
+ 1,770 |
+ 8.2 |
+
+
+ | V20 |
+ BXD40 |
+ M |
+ 1032.04 |
+ 2.08 |
+ 2.22 |
+ 1,985 |
+ 8.2 |
+
+
+ | V21 |
+ BXD14 |
+ M |
+ 881.62 |
+ 2.11 |
+ 2.19 |
+ 481 |
+ 8.7 |
+
+
+ | V22 |
+ BXD2 |
+ M |
+ 1069.09 |
+ 2.08 |
+ 2.22 |
+ 1,536 |
+ 8.2 |
+
+
+ | V23 |
+ BXD28 |
+ M |
+ 452.6 |
+ 2 |
+ 2.26 |
+ 2,567 |
+ 7.9 |
+
+
+ | V24 |
+ BXD11 |
+ M |
+ 930.72 |
+ 2.07 |
+ 2.21 |
+ 999 |
+ 8.5 |
+
+
+ | V25 |
+ BXD39 |
+ M |
+ 1177.27 |
+ 2.07 |
+ 2.23 |
+ 838 |
+ 8.7 |
+
+
+
diff --git a/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/citation.rtf b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/citation.rtf
new file mode 100644
index 0000000..09eb6d1
--- /dev/null
+++ b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/citation.rtf
@@ -0,0 +1 @@
+In progress.
diff --git a/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/contributors.rtf b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/contributors.rtf
new file mode 100644
index 0000000..bfa5fbf
--- /dev/null
+++ b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/contributors.rtf
@@ -0,0 +1 @@
+Robert W. Williams, Roberrt E. Scott and colleagues. Cells were donated to Williams group by Varigenix Inc. and CRL Inc.
diff --git a/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/experiment-design.rtf b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/experiment-design.rtf
new file mode 100644
index 0000000..323648a
--- /dev/null
+++ b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/experiment-design.rtf
@@ -0,0 +1,3 @@
+Control hepatocyte mRNA expression data prior to any treatment for young adult male BXD strains. This is esssentially the mRNA state of frozen hepatocytes.
+
+
diff --git a/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/platform.rtf b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/platform.rtf
new file mode 100644
index 0000000..61c48c5
--- /dev/null
+++ b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/platform.rtf
@@ -0,0 +1 @@
+Affy Mouse Gene 1.0 ST (GPL6246)
diff --git a/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/processing.rtf b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/processing.rtf
new file mode 100644
index 0000000..662571f
--- /dev/null
+++ b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/processing.rtf
@@ -0,0 +1 @@
+Standard 2z+8 of log2 data. RMA data were log2 transformed (adding an olffset of 1 to avoid negative values). Variance was stablized (i.e. each array was converted to a set of Z scores). Z scores were then multipled by 2. Mean Z was then shifted from 0 to to 8 units per array.
diff --git a/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/summary.rtf b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/summary.rtf
new file mode 100644
index 0000000..8e4cabf
--- /dev/null
+++ b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/summary.rtf
@@ -0,0 +1 @@
+mRNA levels in cryopreserved BXD strain hepatotcytes (males at 60 days of age) immediately after thawing to 4 deg C. This is the "frozen state" mRNA status.
diff --git a/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/tissue.rtf b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/tissue.rtf
new file mode 100644
index 0000000..94ad98a
--- /dev/null
+++ b/general/datasets/Uthsc_vgx_mmbxdhepatocytesrma1014/tissue.rtf
@@ -0,0 +1,9 @@
+
+
+Hepatocytes prepared by Rob Kaiser at CRL Piedmont in Spring of 2011. Held in liquid nitrogen (vapor phase) until use Fall 2014 at UTHSC.
+
+One vial of hepatocytes in 1 ml of freeze media was wiped with 70% ETOH, quick thawed by swift agitation in a 37 degree C water bath until a small amount of ice remained in the vial. Contents of the vial were removed with a sterile 1000 ul pipette tip and added to a 5 ml sterile polypropylene tube on ice containing 3 ml of ice-cold sterile 1x PBS. sitting in ice. One ml of sterile ice-cold 1x PBS was added to the original vial to remove any remaining cells and added to the 5 ml tube on ice. This process was quickly repeated with three more vials of cells. Four 5 ml tubes were centrifuged at 8,000 rpm at 4 degrees C for 4 minutes to pellet hepatocytes. PBS diluted freeze media was completely removed from the cell pellet. Entire process for sets of vials took about 7 minutes until RNA lysis buffer was added.
+
+The QIAgen AllPrep DNA/RNA mini kit was used in conjunction with the QIAcube for purification of DNA and RNA from the hepatocytes. 600 ul of kit lysis buffer was added to pelleted cells, along with one 5 mm sterile stainless steel bead and cells were completely disrupted using the TissueLyser. The QIAcube protocol was used first for DNA extraction (held at -80 deg C for future use) and the flow-through containing total RNA was then used for the second purification.
+
+Any residual DNA was removed from the RNA before Agilent quantification of concentration and RIN, using the QIAgen DNase I reagent, followed by ethanol precipitation and resuspension of DNA-free total RNA in 50 ul RNAse free water.
diff --git a/general/datasets/Uthscwgu88bfmg1013/summary.rtf b/general/datasets/Uthscwgu88bfmg1013/summary.rtf
new file mode 100644
index 0000000..5798608
--- /dev/null
+++ b/general/datasets/Uthscwgu88bfmg1013/summary.rtf
@@ -0,0 +1 @@
+This group of datasets is confidential. Please refer to the contact information above.
diff --git a/general/datasets/Utk_bxdspl_vst_0110/contributors.rtf b/general/datasets/Utk_bxdspl_vst_0110/contributors.rtf
new file mode 100644
index 0000000..39f7e80
--- /dev/null
+++ b/general/datasets/Utk_bxdspl_vst_0110/contributors.rtf
@@ -0,0 +1 @@
+Lynch RM, Voy BH
diff --git a/general/datasets/Utk_bxdspl_vst_0110/experiment-design.rtf b/general/datasets/Utk_bxdspl_vst_0110/experiment-design.rtf
new file mode 100644
index 0000000..3166cb9
--- /dev/null
+++ b/general/datasets/Utk_bxdspl_vst_0110/experiment-design.rtf
@@ -0,0 +1 @@
+Spleen gene expression was analyzed from 38 BXD strains. Adult mice (8-12 weeks) were euthanized by cervical dislocation and spleens were harvested and stabilized in RNAlater. Total RNA was extracted and gene expression profiling was performed on the Illumina Sentrix mouse-6 gene expression arrays v1.1. Each BXD sample profiled consisted of a pool of equal amounts of RNA from two individuals of the same sex and strain (approximately 15ug per strain). In addition, flow cytometry was used for the immunophenotyping of male and female mice (average of four mice/sex/strain) from 41 BXD strains (spleen expression profiling was performed on 34 of these strains) and the parental strains. Lymphoctes were identified as CD3+, CD79+, CD4+, or CD8+ to identify T cells, B cells, T helper cells, and cytotoxic T cells, respectively. These data are presented as percentage of lymphoctes with those cell surface markers (e.g. CD3%, CD79%, CD4%, CD8%). Lymphocyte subpopulations are also represented as natural log-transformed ratios (e.g. LN T:B, LN CD4:CD8). In addition, the median expression of MHCII on B cells is reported (LN MHC Med). The immunophenotype data is available in the supplementary file.
diff --git a/general/datasets/Utk_bxdspl_vst_0110/summary.rtf b/general/datasets/Utk_bxdspl_vst_0110/summary.rtf
new file mode 100644
index 0000000..c456b82
--- /dev/null
+++ b/general/datasets/Utk_bxdspl_vst_0110/summary.rtf
@@ -0,0 +1 @@
+The immune system plays a pivotal role in susceptibility to and progression of a variety of diseases. Due to its strong genetic basis, heritable differences in immune function may contribute to differential disease susceptibility between individuals. Genetic reference populations, such as the BXD (C57BL/6J X DBA/2J) panel of recombinant inbred (RI) mouse strains, provide a unique model through which to integrate baseline phenotypes in healthy individuals with heritable risk for disease because of the ability to combine data collected from these populations across multiple studies and time. We performed basic immunophenotyping (e.g. percentage of circulating B and T lymphocytes and CD4+ and CD8+ T cell subpopulations) in peripheral blood of healthy mice from 41 BXD RI strains to define the phenotypic variation in this model system and to characterize the genetic architecture that unlerlies these traits. Significant QTL models that explained the majority (50-77%) of phenotypic variance were derived for each trait and for the T:B cell and CD4+:CD8+ ratios. Combining QTL mapping with spleen gene expression data uncovered two quantitative trait transcripts (QTTs), Ptprk and Acp1, that which are candidates for heritable differences in the relative abundance of helper and cytotoxic T cells. These data will be valuable in extracting genetic correlates of the immune system in the BXD panel. In addition, they will be a useful resource in prospective, phenotype-driven model selection to test hypotheses about differential disease or environmental susceptibility between individuals with baseline differences in the composition of the immune system.
diff --git a/general/datasets/Uva_hiv_1tg_hip_rlog_0720/acknowledgment.rtf b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/acknowledgment.rtf
new file mode 100644
index 0000000..2349291
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/acknowledgment.rtf
@@ -0,0 +1 @@
+We thank Drs. David L. Bronson and Louaine L. Spriggs for their excellent editing of this manuscript.
diff --git a/general/datasets/Uva_hiv_1tg_hip_rlog_0720/cases.rtf b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/cases.rtf
new file mode 100644
index 0000000..a9015ee
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/cases.rtf
@@ -0,0 +1 @@
+The Animal Care and Use Committee of both the Seton Hall University and University of Virginia approved this study. Adult male HIV-1Tg rats and F344 background control rats (n = 12 per group) were purchased from Harlan Inc. (Indianapolis, IN). All rats were double housed in standard plastic cages and maintained in a temperature-controlled environment with a 12 h light/dark cycle and fed a standard rat diet and water ad libitum. The animals were monitored daily, and their cage bedding was changed twice a week. All animals were participants in a previously reported behavioral study [31]. All experimental procedures were conducted during the light cycle in accordance with the Animal Care and Use Committees of both participating institutions.
diff --git a/general/datasets/Uva_hiv_1tg_hip_rlog_0720/citation.rtf b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/citation.rtf
new file mode 100644
index 0000000..50481b4
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Li MD, Cao J, Wang S, Wang J et al. Transcriptome sequencing of gene expression in the brain of the HIV-1 transgenic rat. PLoS One2013;8(3):e59582. PMID: 23536882
+ - Cao J, Wang S, Wang J, Cui W et al. RNA deep sequencing analysis reveals that nicotine restores impaired gene expression by viral proteins in the brains of HIV-1 transgenic rats. PLoS One 2013;8(7):e68517. PMID: 23874651
+
diff --git a/general/datasets/Uva_hiv_1tg_hip_rlog_0720/contributors.rtf b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/contributors.rtf
new file mode 100644
index 0000000..17e9d8c
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/contributors.rtf
@@ -0,0 +1,3 @@
+Conceived and designed the experiments: MDL SLC. Performed the experiments: JC SW SS MV. Analyzed the data: JC SW JW JZM. Wrote the paper: MDL JC SW JW JZM SLC.
+
+Li MD, Cao J, Wang S, Wang J, Sarkar S, Vigorito M, Ma JZ, Chang SL
diff --git a/general/datasets/Uva_hiv_1tg_hip_rlog_0720/experiment-design.rtf b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/experiment-design.rtf
new file mode 100644
index 0000000..a31cc4a
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/experiment-design.rtf
@@ -0,0 +1 @@
+144 RNA samples (2 strains, 2 treatments, 3 regions, and 12 animals per group) were analyzed.
diff --git a/general/datasets/Uva_hiv_1tg_hip_rlog_0720/notes.rtf b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/notes.rtf
new file mode 100644
index 0000000..da785f4
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/notes.rtf
@@ -0,0 +1 @@
+https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0059582
diff --git a/general/datasets/Uva_hiv_1tg_hip_rlog_0720/platform.rtf b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/platform.rtf
new file mode 100644
index 0000000..d55c8e4
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/platform.rtf
@@ -0,0 +1 @@
+GPL14844Illumina HiSeq 2000 (Rattus norvegicus)
diff --git a/general/datasets/Uva_hiv_1tg_hip_rlog_0720/processing.rtf b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/processing.rtf
new file mode 100644
index 0000000..b0cb37b
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/processing.rtf
@@ -0,0 +1,5 @@
+The extraction of 50-bp length paired-end reads was achieved using CASAVA (Illumina Pipeline v1.38). For each sample, reads with a quality score of ≥Q30 that passed filtering were used to generate a complete FASTQ file, which was then mapped to UCSC Rat reference [build Rn4] (ftp://ftp.cbcb.umd.edu/pub/data/bowtie_indexes/rn4.ebwt.zip) using TopHat with the default parameter setting of 40 alignments per read and up to 2 mismatches per alignment. The sequence alignment files (BAM) were analyzed using RSeQC package [36] for quality control analysis, which includes the mRNA fragment insert size, base quality distribution, reads mapping distribution, and splicing distribution analysis.
+
+
+
+The resulting aligned reads were then analyzed with Cufflinks suite (http://cufflinks.cbcb.umd.edu) [37], which assembles the aligned reads into transcripts and measures their relative abundance. The expression of each transcript was quantified as the number of reads mapping to a gene divided by the gene length in kilobases and the total number of mapped reads in millions, which is called fragments per kilobase of exon per million fragments mapped (FPKM). All the junctions identified by Cufflink were compared on the basis of the junction and splicing site provided by reference transcript annotation GTF files to identify known and novel junctions. Then, Cuffcompare merged all the transcripts from different samples to a final transcript annotation GTF file, reported changes in the relative abundance of transcripts sharing a common transcription start site, and indicated the relative abundance of the primary transcripts of each gene crossing all the samples.
diff --git a/general/datasets/Uva_hiv_1tg_hip_rlog_0720/specifics.rtf b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/specifics.rtf
new file mode 100644
index 0000000..421629b
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/specifics.rtf
@@ -0,0 +1 @@
+Hippocampus. rlog normalization
\ No newline at end of file
diff --git a/general/datasets/Uva_hiv_1tg_hip_rlog_0720/summary.rtf b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/summary.rtf
new file mode 100644
index 0000000..7bfa259
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/summary.rtf
@@ -0,0 +1,3 @@
+Purpose: The study was designed to determine expression differences in brain regions of F344 and HIV-1 Transgenic rats by using RNA-sq analysis. Methods: 144 RNA samples (2 strains, 2 treatments, 3 regions, and 12 animals per group) were analyzed. Following deep-sequencing analysis of 50-bp paired-end reads of RNA-Seq, we used Bowtie/Tophat/Cufflinks suites to align these reads into transcripts based on the Rn4 rat reference genome and to measure the relative abundance of each transcript. MATLAB was used to conduct all statistical analysis. qRT–PCR validation was performed using TaqMan and SYBR Green assays fo soem representative genes. Results: Statistical and bioinformatic analyses on each brain region in the two strains revealed that immune response- and neurotransmission-related pathways were altered in the HIV-1Tg rats, with brain region differences. Other neuronal survival-related pathways, including those encoding myelin proteins, growth factors, and translation regulators, were altered in the HIV-1Tg rats in a brain region-dependent manner. After nicotine expousure, 20% of the altered genes in the HIV-1Tg rat were affected by nicotine in each brain region, with the expression of most restored. Analysis of the restored genes showed distinct pathways corrected by nicotine in different brain regions of HIV-1Tg rats.
+
+Conclusions: The abnormal gene expression pattern discovered in HIV-1Tg rats suggest mechanisms underlying the deficits in learning and memory and vulnerability to drug addiction and other psychiatric disorders observed in HIV positive patients. The gene expression pattern in the HIV-1Tg rats after nicotine exposure indicate that cholinergic modulators such as nicotine may have beneficial effects on HIV-1-induced neurologic deficits.
diff --git a/general/datasets/Uva_hiv_1tg_hip_rlog_0720/tissue.rtf b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/tissue.rtf
new file mode 100644
index 0000000..b65b5d6
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_hip_rlog_0720/tissue.rtf
@@ -0,0 +1 @@
+Using a rat brain matrix, slices of approximately 1 mm were taken from each brain, and the slices that contained the PFC, HIP, and dorsal STR were identified according to a rat brain atlas [35]. Tissues from specific regions of interest were collected bilaterally from each brain using a 3.00-mm Harris Micro-Punch (GE Healthcare Life Sciences, Piscataway, NJ, USA) and stored at −80°C until use.
diff --git a/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/acknowledgment.rtf b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/acknowledgment.rtf
new file mode 100644
index 0000000..2349291
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/acknowledgment.rtf
@@ -0,0 +1 @@
+We thank Drs. David L. Bronson and Louaine L. Spriggs for their excellent editing of this manuscript.
diff --git a/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/cases.rtf b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/cases.rtf
new file mode 100644
index 0000000..a9015ee
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/cases.rtf
@@ -0,0 +1 @@
+The Animal Care and Use Committee of both the Seton Hall University and University of Virginia approved this study. Adult male HIV-1Tg rats and F344 background control rats (n = 12 per group) were purchased from Harlan Inc. (Indianapolis, IN). All rats were double housed in standard plastic cages and maintained in a temperature-controlled environment with a 12 h light/dark cycle and fed a standard rat diet and water ad libitum. The animals were monitored daily, and their cage bedding was changed twice a week. All animals were participants in a previously reported behavioral study [31]. All experimental procedures were conducted during the light cycle in accordance with the Animal Care and Use Committees of both participating institutions.
diff --git a/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/citation.rtf b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/citation.rtf
new file mode 100644
index 0000000..50481b4
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Li MD, Cao J, Wang S, Wang J et al. Transcriptome sequencing of gene expression in the brain of the HIV-1 transgenic rat. PLoS One2013;8(3):e59582. PMID: 23536882
+ - Cao J, Wang S, Wang J, Cui W et al. RNA deep sequencing analysis reveals that nicotine restores impaired gene expression by viral proteins in the brains of HIV-1 transgenic rats. PLoS One 2013;8(7):e68517. PMID: 23874651
+
diff --git a/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/contributors.rtf b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/contributors.rtf
new file mode 100644
index 0000000..17e9d8c
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/contributors.rtf
@@ -0,0 +1,3 @@
+Conceived and designed the experiments: MDL SLC. Performed the experiments: JC SW SS MV. Analyzed the data: JC SW JW JZM. Wrote the paper: MDL JC SW JW JZM SLC.
+
+Li MD, Cao J, Wang S, Wang J, Sarkar S, Vigorito M, Ma JZ, Chang SL
diff --git a/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/experiment-design.rtf b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/experiment-design.rtf
new file mode 100644
index 0000000..a31cc4a
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/experiment-design.rtf
@@ -0,0 +1 @@
+144 RNA samples (2 strains, 2 treatments, 3 regions, and 12 animals per group) were analyzed.
diff --git a/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/notes.rtf b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/notes.rtf
new file mode 100644
index 0000000..da785f4
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/notes.rtf
@@ -0,0 +1 @@
+https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0059582
diff --git a/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/platform.rtf b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/platform.rtf
new file mode 100644
index 0000000..d55c8e4
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/platform.rtf
@@ -0,0 +1 @@
+GPL14844Illumina HiSeq 2000 (Rattus norvegicus)
diff --git a/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/processing.rtf b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/processing.rtf
new file mode 100644
index 0000000..b0cb37b
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/processing.rtf
@@ -0,0 +1,5 @@
+The extraction of 50-bp length paired-end reads was achieved using CASAVA (Illumina Pipeline v1.38). For each sample, reads with a quality score of ≥Q30 that passed filtering were used to generate a complete FASTQ file, which was then mapped to UCSC Rat reference [build Rn4] (ftp://ftp.cbcb.umd.edu/pub/data/bowtie_indexes/rn4.ebwt.zip) using TopHat with the default parameter setting of 40 alignments per read and up to 2 mismatches per alignment. The sequence alignment files (BAM) were analyzed using RSeQC package [36] for quality control analysis, which includes the mRNA fragment insert size, base quality distribution, reads mapping distribution, and splicing distribution analysis.
+
+
+
+The resulting aligned reads were then analyzed with Cufflinks suite (http://cufflinks.cbcb.umd.edu) [37], which assembles the aligned reads into transcripts and measures their relative abundance. The expression of each transcript was quantified as the number of reads mapping to a gene divided by the gene length in kilobases and the total number of mapped reads in millions, which is called fragments per kilobase of exon per million fragments mapped (FPKM). All the junctions identified by Cufflink were compared on the basis of the junction and splicing site provided by reference transcript annotation GTF files to identify known and novel junctions. Then, Cuffcompare merged all the transcripts from different samples to a final transcript annotation GTF file, reported changes in the relative abundance of transcripts sharing a common transcription start site, and indicated the relative abundance of the primary transcripts of each gene crossing all the samples.
diff --git a/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/specifics.rtf b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/specifics.rtf
new file mode 100644
index 0000000..d27a33b
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/specifics.rtf
@@ -0,0 +1 @@
+Prefrontal Cortex. rlog normalization
\ No newline at end of file
diff --git a/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/summary.rtf b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/summary.rtf
new file mode 100644
index 0000000..7bfa259
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/summary.rtf
@@ -0,0 +1,3 @@
+Purpose: The study was designed to determine expression differences in brain regions of F344 and HIV-1 Transgenic rats by using RNA-sq analysis. Methods: 144 RNA samples (2 strains, 2 treatments, 3 regions, and 12 animals per group) were analyzed. Following deep-sequencing analysis of 50-bp paired-end reads of RNA-Seq, we used Bowtie/Tophat/Cufflinks suites to align these reads into transcripts based on the Rn4 rat reference genome and to measure the relative abundance of each transcript. MATLAB was used to conduct all statistical analysis. qRT–PCR validation was performed using TaqMan and SYBR Green assays fo soem representative genes. Results: Statistical and bioinformatic analyses on each brain region in the two strains revealed that immune response- and neurotransmission-related pathways were altered in the HIV-1Tg rats, with brain region differences. Other neuronal survival-related pathways, including those encoding myelin proteins, growth factors, and translation regulators, were altered in the HIV-1Tg rats in a brain region-dependent manner. After nicotine expousure, 20% of the altered genes in the HIV-1Tg rat were affected by nicotine in each brain region, with the expression of most restored. Analysis of the restored genes showed distinct pathways corrected by nicotine in different brain regions of HIV-1Tg rats.
+
+Conclusions: The abnormal gene expression pattern discovered in HIV-1Tg rats suggest mechanisms underlying the deficits in learning and memory and vulnerability to drug addiction and other psychiatric disorders observed in HIV positive patients. The gene expression pattern in the HIV-1Tg rats after nicotine exposure indicate that cholinergic modulators such as nicotine may have beneficial effects on HIV-1-induced neurologic deficits.
diff --git a/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/tissue.rtf b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/tissue.rtf
new file mode 100644
index 0000000..b65b5d6
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_pfc_rlog_0720/tissue.rtf
@@ -0,0 +1 @@
+Using a rat brain matrix, slices of approximately 1 mm were taken from each brain, and the slices that contained the PFC, HIP, and dorsal STR were identified according to a rat brain atlas [35]. Tissues from specific regions of interest were collected bilaterally from each brain using a 3.00-mm Harris Micro-Punch (GE Healthcare Life Sciences, Piscataway, NJ, USA) and stored at −80°C until use.
diff --git a/general/datasets/Uva_hiv_1tg_str_rlog_0720/acknowledgment.rtf b/general/datasets/Uva_hiv_1tg_str_rlog_0720/acknowledgment.rtf
new file mode 100644
index 0000000..2349291
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_str_rlog_0720/acknowledgment.rtf
@@ -0,0 +1 @@
+We thank Drs. David L. Bronson and Louaine L. Spriggs for their excellent editing of this manuscript.
diff --git a/general/datasets/Uva_hiv_1tg_str_rlog_0720/cases.rtf b/general/datasets/Uva_hiv_1tg_str_rlog_0720/cases.rtf
new file mode 100644
index 0000000..a9015ee
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_str_rlog_0720/cases.rtf
@@ -0,0 +1 @@
+The Animal Care and Use Committee of both the Seton Hall University and University of Virginia approved this study. Adult male HIV-1Tg rats and F344 background control rats (n = 12 per group) were purchased from Harlan Inc. (Indianapolis, IN). All rats were double housed in standard plastic cages and maintained in a temperature-controlled environment with a 12 h light/dark cycle and fed a standard rat diet and water ad libitum. The animals were monitored daily, and their cage bedding was changed twice a week. All animals were participants in a previously reported behavioral study [31]. All experimental procedures were conducted during the light cycle in accordance with the Animal Care and Use Committees of both participating institutions.
diff --git a/general/datasets/Uva_hiv_1tg_str_rlog_0720/citation.rtf b/general/datasets/Uva_hiv_1tg_str_rlog_0720/citation.rtf
new file mode 100644
index 0000000..50481b4
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_str_rlog_0720/citation.rtf
@@ -0,0 +1,4 @@
+
+ - Li MD, Cao J, Wang S, Wang J et al. Transcriptome sequencing of gene expression in the brain of the HIV-1 transgenic rat. PLoS One2013;8(3):e59582. PMID: 23536882
+ - Cao J, Wang S, Wang J, Cui W et al. RNA deep sequencing analysis reveals that nicotine restores impaired gene expression by viral proteins in the brains of HIV-1 transgenic rats. PLoS One 2013;8(7):e68517. PMID: 23874651
+
diff --git a/general/datasets/Uva_hiv_1tg_str_rlog_0720/contributors.rtf b/general/datasets/Uva_hiv_1tg_str_rlog_0720/contributors.rtf
new file mode 100644
index 0000000..17e9d8c
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_str_rlog_0720/contributors.rtf
@@ -0,0 +1,3 @@
+Conceived and designed the experiments: MDL SLC. Performed the experiments: JC SW SS MV. Analyzed the data: JC SW JW JZM. Wrote the paper: MDL JC SW JW JZM SLC.
+
+Li MD, Cao J, Wang S, Wang J, Sarkar S, Vigorito M, Ma JZ, Chang SL
diff --git a/general/datasets/Uva_hiv_1tg_str_rlog_0720/experiment-design.rtf b/general/datasets/Uva_hiv_1tg_str_rlog_0720/experiment-design.rtf
new file mode 100644
index 0000000..a31cc4a
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_str_rlog_0720/experiment-design.rtf
@@ -0,0 +1 @@
+144 RNA samples (2 strains, 2 treatments, 3 regions, and 12 animals per group) were analyzed.
diff --git a/general/datasets/Uva_hiv_1tg_str_rlog_0720/notes.rtf b/general/datasets/Uva_hiv_1tg_str_rlog_0720/notes.rtf
new file mode 100644
index 0000000..da785f4
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_str_rlog_0720/notes.rtf
@@ -0,0 +1 @@
+https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0059582
diff --git a/general/datasets/Uva_hiv_1tg_str_rlog_0720/platform.rtf b/general/datasets/Uva_hiv_1tg_str_rlog_0720/platform.rtf
new file mode 100644
index 0000000..d55c8e4
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_str_rlog_0720/platform.rtf
@@ -0,0 +1 @@
+GPL14844Illumina HiSeq 2000 (Rattus norvegicus)
diff --git a/general/datasets/Uva_hiv_1tg_str_rlog_0720/processing.rtf b/general/datasets/Uva_hiv_1tg_str_rlog_0720/processing.rtf
new file mode 100644
index 0000000..b0cb37b
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_str_rlog_0720/processing.rtf
@@ -0,0 +1,5 @@
+The extraction of 50-bp length paired-end reads was achieved using CASAVA (Illumina Pipeline v1.38). For each sample, reads with a quality score of ≥Q30 that passed filtering were used to generate a complete FASTQ file, which was then mapped to UCSC Rat reference [build Rn4] (ftp://ftp.cbcb.umd.edu/pub/data/bowtie_indexes/rn4.ebwt.zip) using TopHat with the default parameter setting of 40 alignments per read and up to 2 mismatches per alignment. The sequence alignment files (BAM) were analyzed using RSeQC package [36] for quality control analysis, which includes the mRNA fragment insert size, base quality distribution, reads mapping distribution, and splicing distribution analysis.
+
+
+
+The resulting aligned reads were then analyzed with Cufflinks suite (http://cufflinks.cbcb.umd.edu) [37], which assembles the aligned reads into transcripts and measures their relative abundance. The expression of each transcript was quantified as the number of reads mapping to a gene divided by the gene length in kilobases and the total number of mapped reads in millions, which is called fragments per kilobase of exon per million fragments mapped (FPKM). All the junctions identified by Cufflink were compared on the basis of the junction and splicing site provided by reference transcript annotation GTF files to identify known and novel junctions. Then, Cuffcompare merged all the transcripts from different samples to a final transcript annotation GTF file, reported changes in the relative abundance of transcripts sharing a common transcription start site, and indicated the relative abundance of the primary transcripts of each gene crossing all the samples.
diff --git a/general/datasets/Uva_hiv_1tg_str_rlog_0720/specifics.rtf b/general/datasets/Uva_hiv_1tg_str_rlog_0720/specifics.rtf
new file mode 100644
index 0000000..2a10692
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_str_rlog_0720/specifics.rtf
@@ -0,0 +1 @@
+Striatum. rlog normalization
\ No newline at end of file
diff --git a/general/datasets/Uva_hiv_1tg_str_rlog_0720/summary.rtf b/general/datasets/Uva_hiv_1tg_str_rlog_0720/summary.rtf
new file mode 100644
index 0000000..7bfa259
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_str_rlog_0720/summary.rtf
@@ -0,0 +1,3 @@
+Purpose: The study was designed to determine expression differences in brain regions of F344 and HIV-1 Transgenic rats by using RNA-sq analysis. Methods: 144 RNA samples (2 strains, 2 treatments, 3 regions, and 12 animals per group) were analyzed. Following deep-sequencing analysis of 50-bp paired-end reads of RNA-Seq, we used Bowtie/Tophat/Cufflinks suites to align these reads into transcripts based on the Rn4 rat reference genome and to measure the relative abundance of each transcript. MATLAB was used to conduct all statistical analysis. qRT–PCR validation was performed using TaqMan and SYBR Green assays fo soem representative genes. Results: Statistical and bioinformatic analyses on each brain region in the two strains revealed that immune response- and neurotransmission-related pathways were altered in the HIV-1Tg rats, with brain region differences. Other neuronal survival-related pathways, including those encoding myelin proteins, growth factors, and translation regulators, were altered in the HIV-1Tg rats in a brain region-dependent manner. After nicotine expousure, 20% of the altered genes in the HIV-1Tg rat were affected by nicotine in each brain region, with the expression of most restored. Analysis of the restored genes showed distinct pathways corrected by nicotine in different brain regions of HIV-1Tg rats.
+
+Conclusions: The abnormal gene expression pattern discovered in HIV-1Tg rats suggest mechanisms underlying the deficits in learning and memory and vulnerability to drug addiction and other psychiatric disorders observed in HIV positive patients. The gene expression pattern in the HIV-1Tg rats after nicotine exposure indicate that cholinergic modulators such as nicotine may have beneficial effects on HIV-1-induced neurologic deficits.
diff --git a/general/datasets/Uva_hiv_1tg_str_rlog_0720/tissue.rtf b/general/datasets/Uva_hiv_1tg_str_rlog_0720/tissue.rtf
new file mode 100644
index 0000000..b65b5d6
--- /dev/null
+++ b/general/datasets/Uva_hiv_1tg_str_rlog_0720/tissue.rtf
@@ -0,0 +1 @@
+Using a rat brain matrix, slices of approximately 1 mm were taken from each brain, and the slices that contained the PFC, HIP, and dorsal STR were identified according to a rat brain atlas [35]. Tissues from specific regions of interest were collected bilaterally from each brain using a 3.00-mm Harris Micro-Punch (GE Healthcare Life Sciences, Piscataway, NJ, USA) and stored at −80°C until use.
diff --git a/general/datasets/VCU_BXD_Nac_CIE_AirZ_0416/summary.rtf b/general/datasets/VCU_BXD_Nac_CIE_AirZ_0416/summary.rtf
deleted file mode 100644
index c82b72c..0000000
--- a/general/datasets/VCU_BXD_Nac_CIE_AirZ_0416/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/VCU_BXD_Nac_CIE_Air_0416/summary.rtf b/general/datasets/VCU_BXD_Nac_CIE_Air_0416/summary.rtf
deleted file mode 100644
index c82b72c..0000000
--- a/general/datasets/VCU_BXD_Nac_CIE_Air_0416/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/VCU_BXD_Nac_CIE_EtZ_0416/summary.rtf b/general/datasets/VCU_BXD_Nac_CIE_EtZ_0416/summary.rtf
deleted file mode 100644
index c82b72c..0000000
--- a/general/datasets/VCU_BXD_Nac_CIE_EtZ_0416/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/VCU_BXD_Nac_CIE_Et_0416/summary.rtf b/general/datasets/VCU_BXD_Nac_CIE_Et_0416/summary.rtf
deleted file mode 100644
index c82b72c..0000000
--- a/general/datasets/VCU_BXD_Nac_CIE_Et_0416/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/acknowledgment.rtf b/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/acknowledgment.rtf
deleted file mode 100644
index 4463223..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/cases.rtf b/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/cases.rtf
deleted file mode 100644
index a9b6489..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/experiment-design.rtf b/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/experiment-design.rtf
deleted file mode 100644
index 05c600b..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/experiment-design.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
-
-Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
-
-Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/platform.rtf b/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/platform.rtf
deleted file mode 100644
index ec67993..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/summary.rtf b/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/summary.rtf
deleted file mode 100644
index ff7c56f..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/tissue.rtf b/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/tissue.rtf
deleted file mode 100644
index 6473075..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_AirZ_0416/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
-
-GEO Accession: GSE28515
diff --git a/general/datasets/VCU_BXD_PFC_CIE_Air_0416/acknowledgment.rtf b/general/datasets/VCU_BXD_PFC_CIE_Air_0416/acknowledgment.rtf
deleted file mode 100644
index 4463223..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_Air_0416/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_Air_0416/cases.rtf b/general/datasets/VCU_BXD_PFC_CIE_Air_0416/cases.rtf
deleted file mode 100644
index a9b6489..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_Air_0416/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_Air_0416/experiment-design.rtf b/general/datasets/VCU_BXD_PFC_CIE_Air_0416/experiment-design.rtf
deleted file mode 100644
index 05c600b..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_Air_0416/experiment-design.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
-
-Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
-
-Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_Air_0416/platform.rtf b/general/datasets/VCU_BXD_PFC_CIE_Air_0416/platform.rtf
deleted file mode 100644
index ec67993..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_Air_0416/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/VCU_BXD_PFC_CIE_Air_0416/summary.rtf b/general/datasets/VCU_BXD_PFC_CIE_Air_0416/summary.rtf
deleted file mode 100644
index ff7c56f..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_Air_0416/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_Air_0416/tissue.rtf b/general/datasets/VCU_BXD_PFC_CIE_Air_0416/tissue.rtf
deleted file mode 100644
index 6473075..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_Air_0416/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
-
-GEO Accession: GSE28515
diff --git a/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/acknowledgment.rtf b/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/acknowledgment.rtf
deleted file mode 100644
index 4463223..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/cases.rtf b/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/cases.rtf
deleted file mode 100644
index a9b6489..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/experiment-design.rtf b/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/experiment-design.rtf
deleted file mode 100644
index 05c600b..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/experiment-design.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
-
-Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
-
-Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/platform.rtf b/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/platform.rtf
deleted file mode 100644
index ec67993..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/summary.rtf b/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/summary.rtf
deleted file mode 100644
index ff7c56f..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/tissue.rtf b/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/tissue.rtf
deleted file mode 100644
index 6473075..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_EtZ_0416/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
-
-GEO Accession: GSE28515
diff --git a/general/datasets/VCU_BXD_PFC_CIE_Et_0416/acknowledgment.rtf b/general/datasets/VCU_BXD_PFC_CIE_Et_0416/acknowledgment.rtf
deleted file mode 100644
index 4463223..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_Et_0416/acknowledgment.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_Et_0416/cases.rtf b/general/datasets/VCU_BXD_PFC_CIE_Et_0416/cases.rtf
deleted file mode 100644
index a9b6489..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_Et_0416/cases.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_Et_0416/experiment-design.rtf b/general/datasets/VCU_BXD_PFC_CIE_Et_0416/experiment-design.rtf
deleted file mode 100644
index 05c600b..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_Et_0416/experiment-design.rtf
+++ /dev/null
@@ -1,5 +0,0 @@
-This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
-
-Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
-
-Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_Et_0416/platform.rtf b/general/datasets/VCU_BXD_PFC_CIE_Et_0416/platform.rtf
deleted file mode 100644
index ec67993..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_Et_0416/platform.rtf
+++ /dev/null
@@ -1 +0,0 @@
-[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/VCU_BXD_PFC_CIE_Et_0416/summary.rtf b/general/datasets/VCU_BXD_PFC_CIE_Et_0416/summary.rtf
deleted file mode 100644
index ff7c56f..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_Et_0416/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/VCU_BXD_PFC_CIE_Et_0416/tissue.rtf b/general/datasets/VCU_BXD_PFC_CIE_Et_0416/tissue.rtf
deleted file mode 100644
index 6473075..0000000
--- a/general/datasets/VCU_BXD_PFC_CIE_Et_0416/tissue.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
-
-GEO Accession: GSE28515
diff --git a/general/datasets/VCU_NAc_Air_0113_R/summary.rtf b/general/datasets/VCU_NAc_Air_0113_R/summary.rtf
deleted file mode 100644
index c82b72c..0000000
--- a/general/datasets/VCU_NAc_Air_0113_R/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/VCU_NAc_Et_0113_R/summary.rtf b/general/datasets/VCU_NAc_Et_0113_R/summary.rtf
deleted file mode 100644
index c82b72c..0000000
--- a/general/datasets/VCU_NAc_Et_0113_R/summary.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/Vcu_bxd_nac_cie_air_0416/summary.rtf b/general/datasets/Vcu_bxd_nac_cie_air_0416/summary.rtf
new file mode 100644
index 0000000..c82b72c
--- /dev/null
+++ b/general/datasets/Vcu_bxd_nac_cie_air_0416/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/Vcu_bxd_nac_cie_airz_0416/summary.rtf b/general/datasets/Vcu_bxd_nac_cie_airz_0416/summary.rtf
new file mode 100644
index 0000000..c82b72c
--- /dev/null
+++ b/general/datasets/Vcu_bxd_nac_cie_airz_0416/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/Vcu_bxd_nac_cie_et_0416/summary.rtf b/general/datasets/Vcu_bxd_nac_cie_et_0416/summary.rtf
new file mode 100644
index 0000000..c82b72c
--- /dev/null
+++ b/general/datasets/Vcu_bxd_nac_cie_et_0416/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/Vcu_bxd_nac_cie_etz_0416/summary.rtf b/general/datasets/Vcu_bxd_nac_cie_etz_0416/summary.rtf
new file mode 100644
index 0000000..c82b72c
--- /dev/null
+++ b/general/datasets/Vcu_bxd_nac_cie_etz_0416/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/Vcu_bxd_pfc_cie_air_0416/acknowledgment.rtf b/general/datasets/Vcu_bxd_pfc_cie_air_0416/acknowledgment.rtf
new file mode 100644
index 0000000..4463223
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_air_0416/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_air_0416/cases.rtf b/general/datasets/Vcu_bxd_pfc_cie_air_0416/cases.rtf
new file mode 100644
index 0000000..a9b6489
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_air_0416/cases.rtf
@@ -0,0 +1 @@
+This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_air_0416/contributors.rtf b/general/datasets/Vcu_bxd_pfc_cie_air_0416/contributors.rtf
new file mode 100644
index 0000000..6bb60a8
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_air_0416/contributors.rtf
@@ -0,0 +1 @@
+Miles MF, Putman AH, Vorster PJ, Wolen AR
diff --git a/general/datasets/Vcu_bxd_pfc_cie_air_0416/experiment-design.rtf b/general/datasets/Vcu_bxd_pfc_cie_air_0416/experiment-design.rtf
new file mode 100644
index 0000000..05c600b
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_air_0416/experiment-design.rtf
@@ -0,0 +1,5 @@
+This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
+
+Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
+
+Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_air_0416/platform.rtf b/general/datasets/Vcu_bxd_pfc_cie_air_0416/platform.rtf
new file mode 100644
index 0000000..ec67993
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_air_0416/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcu_bxd_pfc_cie_air_0416/summary.rtf b/general/datasets/Vcu_bxd_pfc_cie_air_0416/summary.rtf
new file mode 100644
index 0000000..ff7c56f
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_air_0416/summary.rtf
@@ -0,0 +1 @@
+In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_air_0416/tissue.rtf b/general/datasets/Vcu_bxd_pfc_cie_air_0416/tissue.rtf
new file mode 100644
index 0000000..6473075
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_air_0416/tissue.rtf
@@ -0,0 +1,3 @@
+All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
+
+GEO Accession: GSE28515
diff --git a/general/datasets/Vcu_bxd_pfc_cie_airz_0416/acknowledgment.rtf b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/acknowledgment.rtf
new file mode 100644
index 0000000..4463223
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_airz_0416/cases.rtf b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/cases.rtf
new file mode 100644
index 0000000..a9b6489
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/cases.rtf
@@ -0,0 +1 @@
+This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_airz_0416/contributors.rtf b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/contributors.rtf
new file mode 100644
index 0000000..6bb60a8
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/contributors.rtf
@@ -0,0 +1 @@
+Miles MF, Putman AH, Vorster PJ, Wolen AR
diff --git a/general/datasets/Vcu_bxd_pfc_cie_airz_0416/experiment-design.rtf b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/experiment-design.rtf
new file mode 100644
index 0000000..05c600b
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/experiment-design.rtf
@@ -0,0 +1,5 @@
+This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
+
+Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
+
+Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_airz_0416/platform.rtf b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/platform.rtf
new file mode 100644
index 0000000..ec67993
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcu_bxd_pfc_cie_airz_0416/summary.rtf b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/summary.rtf
new file mode 100644
index 0000000..ff7c56f
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/summary.rtf
@@ -0,0 +1 @@
+In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_airz_0416/tissue.rtf b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/tissue.rtf
new file mode 100644
index 0000000..6473075
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_airz_0416/tissue.rtf
@@ -0,0 +1,3 @@
+All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
+
+GEO Accession: GSE28515
diff --git a/general/datasets/Vcu_bxd_pfc_cie_et_0416/acknowledgment.rtf b/general/datasets/Vcu_bxd_pfc_cie_et_0416/acknowledgment.rtf
new file mode 100644
index 0000000..4463223
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_et_0416/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_et_0416/cases.rtf b/general/datasets/Vcu_bxd_pfc_cie_et_0416/cases.rtf
new file mode 100644
index 0000000..a9b6489
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_et_0416/cases.rtf
@@ -0,0 +1 @@
+This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_et_0416/contributors.rtf b/general/datasets/Vcu_bxd_pfc_cie_et_0416/contributors.rtf
new file mode 100644
index 0000000..6bb60a8
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_et_0416/contributors.rtf
@@ -0,0 +1 @@
+Miles MF, Putman AH, Vorster PJ, Wolen AR
diff --git a/general/datasets/Vcu_bxd_pfc_cie_et_0416/experiment-design.rtf b/general/datasets/Vcu_bxd_pfc_cie_et_0416/experiment-design.rtf
new file mode 100644
index 0000000..05c600b
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_et_0416/experiment-design.rtf
@@ -0,0 +1,5 @@
+This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
+
+Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
+
+Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_et_0416/platform.rtf b/general/datasets/Vcu_bxd_pfc_cie_et_0416/platform.rtf
new file mode 100644
index 0000000..ec67993
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_et_0416/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcu_bxd_pfc_cie_et_0416/summary.rtf b/general/datasets/Vcu_bxd_pfc_cie_et_0416/summary.rtf
new file mode 100644
index 0000000..ff7c56f
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_et_0416/summary.rtf
@@ -0,0 +1 @@
+In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_et_0416/tissue.rtf b/general/datasets/Vcu_bxd_pfc_cie_et_0416/tissue.rtf
new file mode 100644
index 0000000..6473075
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_et_0416/tissue.rtf
@@ -0,0 +1,3 @@
+All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
+
+GEO Accession: GSE28515
diff --git a/general/datasets/Vcu_bxd_pfc_cie_etz_0416/acknowledgment.rtf b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/acknowledgment.rtf
new file mode 100644
index 0000000..4463223
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_etz_0416/cases.rtf b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/cases.rtf
new file mode 100644
index 0000000..a9b6489
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/cases.rtf
@@ -0,0 +1 @@
+This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_etz_0416/contributors.rtf b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/contributors.rtf
new file mode 100644
index 0000000..6bb60a8
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/contributors.rtf
@@ -0,0 +1 @@
+Miles MF, Putman AH, Vorster PJ, Wolen AR
diff --git a/general/datasets/Vcu_bxd_pfc_cie_etz_0416/experiment-design.rtf b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/experiment-design.rtf
new file mode 100644
index 0000000..05c600b
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/experiment-design.rtf
@@ -0,0 +1,5 @@
+This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
+
+Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
+
+Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_etz_0416/platform.rtf b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/platform.rtf
new file mode 100644
index 0000000..ec67993
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcu_bxd_pfc_cie_etz_0416/summary.rtf b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/summary.rtf
new file mode 100644
index 0000000..ff7c56f
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/summary.rtf
@@ -0,0 +1 @@
+In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/Vcu_bxd_pfc_cie_etz_0416/tissue.rtf b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/tissue.rtf
new file mode 100644
index 0000000..6473075
--- /dev/null
+++ b/general/datasets/Vcu_bxd_pfc_cie_etz_0416/tissue.rtf
@@ -0,0 +1,3 @@
+All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
+
+GEO Accession: GSE28515
diff --git a/general/datasets/Vcu_nac_air_0113_r/summary.rtf b/general/datasets/Vcu_nac_air_0113_r/summary.rtf
new file mode 100644
index 0000000..c82b72c
--- /dev/null
+++ b/general/datasets/Vcu_nac_air_0113_r/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/Vcu_nac_ave_0113_ss/summary.rtf b/general/datasets/Vcu_nac_ave_0113_ss/summary.rtf
new file mode 100644
index 0000000..c82b72c
--- /dev/null
+++ b/general/datasets/Vcu_nac_ave_0113_ss/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/Vcu_nac_et_0113_r/summary.rtf b/general/datasets/Vcu_nac_et_0113_r/summary.rtf
new file mode 100644
index 0000000..c82b72c
--- /dev/null
+++ b/general/datasets/Vcu_nac_et_0113_r/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 161, Name: VCU BXD NAc EtOH vs CIE Air M430 2.0 (Jan13)
diff --git a/general/datasets/Vcu_pf_air_0111_r/acknowledgment.rtf b/general/datasets/Vcu_pf_air_0111_r/acknowledgment.rtf
new file mode 100644
index 0000000..4463223
--- /dev/null
+++ b/general/datasets/Vcu_pf_air_0111_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/Vcu_pf_air_0111_r/cases.rtf b/general/datasets/Vcu_pf_air_0111_r/cases.rtf
new file mode 100644
index 0000000..a9b6489
--- /dev/null
+++ b/general/datasets/Vcu_pf_air_0111_r/cases.rtf
@@ -0,0 +1 @@
+This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/Vcu_pf_air_0111_r/contributors.rtf b/general/datasets/Vcu_pf_air_0111_r/contributors.rtf
new file mode 100644
index 0000000..6bb60a8
--- /dev/null
+++ b/general/datasets/Vcu_pf_air_0111_r/contributors.rtf
@@ -0,0 +1 @@
+Miles MF, Putman AH, Vorster PJ, Wolen AR
diff --git a/general/datasets/Vcu_pf_air_0111_r/experiment-design.rtf b/general/datasets/Vcu_pf_air_0111_r/experiment-design.rtf
new file mode 100644
index 0000000..05c600b
--- /dev/null
+++ b/general/datasets/Vcu_pf_air_0111_r/experiment-design.rtf
@@ -0,0 +1,5 @@
+This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
+
+Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
+
+Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/Vcu_pf_air_0111_r/experiment-type.rtf b/general/datasets/Vcu_pf_air_0111_r/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Vcu_pf_air_0111_r/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Vcu_pf_air_0111_r/platform.rtf b/general/datasets/Vcu_pf_air_0111_r/platform.rtf
new file mode 100644
index 0000000..ec67993
--- /dev/null
+++ b/general/datasets/Vcu_pf_air_0111_r/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcu_pf_air_0111_r/summary.rtf b/general/datasets/Vcu_pf_air_0111_r/summary.rtf
new file mode 100644
index 0000000..ff7c56f
--- /dev/null
+++ b/general/datasets/Vcu_pf_air_0111_r/summary.rtf
@@ -0,0 +1 @@
+In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/Vcu_pf_air_0111_r/tissue.rtf b/general/datasets/Vcu_pf_air_0111_r/tissue.rtf
new file mode 100644
index 0000000..6473075
--- /dev/null
+++ b/general/datasets/Vcu_pf_air_0111_r/tissue.rtf
@@ -0,0 +1,3 @@
+All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
+
+GEO Accession: GSE28515
diff --git a/general/datasets/Vcu_pf_ave_0111_ss/acknowledgment.rtf b/general/datasets/Vcu_pf_ave_0111_ss/acknowledgment.rtf
new file mode 100644
index 0000000..4463223
--- /dev/null
+++ b/general/datasets/Vcu_pf_ave_0111_ss/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/Vcu_pf_ave_0111_ss/cases.rtf b/general/datasets/Vcu_pf_ave_0111_ss/cases.rtf
new file mode 100644
index 0000000..a9b6489
--- /dev/null
+++ b/general/datasets/Vcu_pf_ave_0111_ss/cases.rtf
@@ -0,0 +1 @@
+This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/Vcu_pf_ave_0111_ss/contributors.rtf b/general/datasets/Vcu_pf_ave_0111_ss/contributors.rtf
new file mode 100644
index 0000000..6bb60a8
--- /dev/null
+++ b/general/datasets/Vcu_pf_ave_0111_ss/contributors.rtf
@@ -0,0 +1 @@
+Miles MF, Putman AH, Vorster PJ, Wolen AR
diff --git a/general/datasets/Vcu_pf_ave_0111_ss/experiment-design.rtf b/general/datasets/Vcu_pf_ave_0111_ss/experiment-design.rtf
new file mode 100644
index 0000000..05c600b
--- /dev/null
+++ b/general/datasets/Vcu_pf_ave_0111_ss/experiment-design.rtf
@@ -0,0 +1,5 @@
+This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
+
+Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
+
+Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/Vcu_pf_ave_0111_ss/experiment-type.rtf b/general/datasets/Vcu_pf_ave_0111_ss/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Vcu_pf_ave_0111_ss/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Vcu_pf_ave_0111_ss/platform.rtf b/general/datasets/Vcu_pf_ave_0111_ss/platform.rtf
new file mode 100644
index 0000000..ec67993
--- /dev/null
+++ b/general/datasets/Vcu_pf_ave_0111_ss/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcu_pf_ave_0111_ss/summary.rtf b/general/datasets/Vcu_pf_ave_0111_ss/summary.rtf
new file mode 100644
index 0000000..ff7c56f
--- /dev/null
+++ b/general/datasets/Vcu_pf_ave_0111_ss/summary.rtf
@@ -0,0 +1 @@
+In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/Vcu_pf_ave_0111_ss/tissue.rtf b/general/datasets/Vcu_pf_ave_0111_ss/tissue.rtf
new file mode 100644
index 0000000..6473075
--- /dev/null
+++ b/general/datasets/Vcu_pf_ave_0111_ss/tissue.rtf
@@ -0,0 +1,3 @@
+All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
+
+GEO Accession: GSE28515
diff --git a/general/datasets/Vcu_pf_et_0111_r/acknowledgment.rtf b/general/datasets/Vcu_pf_et_0111_r/acknowledgment.rtf
new file mode 100644
index 0000000..4463223
--- /dev/null
+++ b/general/datasets/Vcu_pf_et_0111_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/Vcu_pf_et_0111_r/cases.rtf b/general/datasets/Vcu_pf_et_0111_r/cases.rtf
new file mode 100644
index 0000000..a9b6489
--- /dev/null
+++ b/general/datasets/Vcu_pf_et_0111_r/cases.rtf
@@ -0,0 +1 @@
+This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/Vcu_pf_et_0111_r/contributors.rtf b/general/datasets/Vcu_pf_et_0111_r/contributors.rtf
new file mode 100644
index 0000000..6bb60a8
--- /dev/null
+++ b/general/datasets/Vcu_pf_et_0111_r/contributors.rtf
@@ -0,0 +1 @@
+Miles MF, Putman AH, Vorster PJ, Wolen AR
diff --git a/general/datasets/Vcu_pf_et_0111_r/experiment-design.rtf b/general/datasets/Vcu_pf_et_0111_r/experiment-design.rtf
new file mode 100644
index 0000000..05c600b
--- /dev/null
+++ b/general/datasets/Vcu_pf_et_0111_r/experiment-design.rtf
@@ -0,0 +1,5 @@
+This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
+
+Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
+
+Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/Vcu_pf_et_0111_r/experiment-type.rtf b/general/datasets/Vcu_pf_et_0111_r/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Vcu_pf_et_0111_r/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Vcu_pf_et_0111_r/platform.rtf b/general/datasets/Vcu_pf_et_0111_r/platform.rtf
new file mode 100644
index 0000000..ec67993
--- /dev/null
+++ b/general/datasets/Vcu_pf_et_0111_r/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcu_pf_et_0111_r/summary.rtf b/general/datasets/Vcu_pf_et_0111_r/summary.rtf
new file mode 100644
index 0000000..ff7c56f
--- /dev/null
+++ b/general/datasets/Vcu_pf_et_0111_r/summary.rtf
@@ -0,0 +1 @@
+In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/Vcu_pf_et_0111_r/tissue.rtf b/general/datasets/Vcu_pf_et_0111_r/tissue.rtf
new file mode 100644
index 0000000..6473075
--- /dev/null
+++ b/general/datasets/Vcu_pf_et_0111_r/tissue.rtf
@@ -0,0 +1,3 @@
+All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
+
+GEO Accession: GSE28515
diff --git a/general/datasets/Vcuet_vs_sal_0806_r/summary.rtf b/general/datasets/Vcuet_vs_sal_0806_r/summary.rtf
new file mode 100644
index 0000000..36e8ee4
--- /dev/null
+++ b/general/datasets/Vcuet_vs_sal_0806_r/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 33, Name: VCU LXS PFC Et vs Sal M430A 2.0 (Aug06)
\ No newline at end of file
diff --git a/general/datasets/Vcuetoh_0609_r/experiment-type.rtf b/general/datasets/Vcuetoh_0609_r/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Vcuetoh_0609_r/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Vcuetoh_0609_r/notes.rtf b/general/datasets/Vcuetoh_0609_r/notes.rtf
new file mode 100644
index 0000000..3b773ce
--- /dev/null
+++ b/general/datasets/Vcuetoh_0609_r/notes.rtf
@@ -0,0 +1 @@
+All samples were processed by Nate Bruce at VCU between April and May 2009. The BioRad Experion RNA analyzer and used to assess total RNA integrity and verify equal molar ratios of 18S and 28S ribosomal RNA. All RNA Quality Index (RQI) calculations were > 8. Standard Affymetrix reagents and protocols were used for generation of cDNA and biotinylated cRNA from total RNA samples. Integrity of cRNA was checked by Experion analysis prior to microarray hybridizations. All probes exceeded a maximum size of 3000 nt for the upper border of the cRNA size distribution.
diff --git a/general/datasets/Vcuetoh_0609_r/platform.rtf b/general/datasets/Vcuetoh_0609_r/platform.rtf
new file mode 100644
index 0000000..b7370c8
--- /dev/null
+++ b/general/datasets/Vcuetoh_0609_r/platform.rtf
@@ -0,0 +1 @@
+GEO: GPL1261 Affymetrix GeneChip Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcuetoh_0609_r/specifics.rtf b/general/datasets/Vcuetoh_0609_r/specifics.rtf
new file mode 100644
index 0000000..bab9fcf
--- /dev/null
+++ b/general/datasets/Vcuetoh_0609_r/specifics.rtf
@@ -0,0 +1 @@
+Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the VTA in response to ethanol.
\ No newline at end of file
diff --git a/general/datasets/Vcuetoh_0609_r/summary.rtf b/general/datasets/Vcuetoh_0609_r/summary.rtf
new file mode 100644
index 0000000..ad6106d
--- /dev/null
+++ b/general/datasets/Vcuetoh_0609_r/summary.rtf
@@ -0,0 +1,3 @@
+This BXD data set provides estimates of ventral tegmental area (VTA) mRNA expression in response to ethanol (1.8 g/kg x 4 hours) across 35 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 596 adult male animals obtained from Jackson Laboratory (27 classical BXD strains) or Oak Ridge National Laboratory (extended BXD series) and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and ethanol (IP) treatment in the light-dark transition model of anxiety.
+
+All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the VTA in response to ethanol or saline and transforming these data using the S-score method to compare ethanol vs. saline expression from pairs of arrays for each strain (Kerns et al., Methods 31:274, 2003). The S-score is a method developed for Affymetrix oligonucleotide arrays that is particularly suited to comparing expression on 2 or a small number of chips. The S-score output for each probeset is not an indication of expression magnitude but rather, the change in expression between compared arrays. The S-score is essentially a z-score centered around zero with positive S-scores reflecting increased gene expression with ethanol and negative scores reflecting ethanol-induced decreases in expression. Larger magnitude S-scores show more significant changes in expression and are generally correlated with the fold-change.
diff --git a/general/datasets/Vcuetoh_0806_r/summary.rtf b/general/datasets/Vcuetoh_0806_r/summary.rtf
new file mode 100644
index 0000000..36e8ee4
--- /dev/null
+++ b/general/datasets/Vcuetoh_0806_r/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 33, Name: VCU LXS PFC Et vs Sal M430A 2.0 (Aug06)
\ No newline at end of file
diff --git a/general/datasets/Vcuetoh_1007_r/experiment-design.rtf b/general/datasets/Vcuetoh_1007_r/experiment-design.rtf
new file mode 100644
index 0000000..9826853
--- /dev/null
+++ b/general/datasets/Vcuetoh_1007_r/experiment-design.rtf
@@ -0,0 +1 @@
+Acute ethanol injection. Please ad dose, route, age, timing, etc.
diff --git a/general/datasets/Vcuetoh_1007_r/processing.rtf b/general/datasets/Vcuetoh_1007_r/processing.rtf
new file mode 100644
index 0000000..692987b
--- /dev/null
+++ b/general/datasets/Vcuetoh_1007_r/processing.rtf
@@ -0,0 +1 @@
+These data use the S-score algorithm of Miles and colleagues (PMIDs: 16574698, 16545131, 14597311, 11902839) to evaluate the magnitude of change between the control condition and the ethanol-treated animals. Positive S-score values reflect increased expression with ethanol, negative S-scores reflect decreased expression after ethanol treatment.
diff --git a/general/datasets/Vcuetoh_1007_r/summary.rtf b/general/datasets/Vcuetoh_1007_r/summary.rtf
new file mode 100644
index 0000000..479039b
--- /dev/null
+++ b/general/datasets/Vcuetoh_1007_r/summary.rtf
@@ -0,0 +1,3 @@
+Summary of DatasetId 44, Name: VCU BXD NA Et vs Sal M430 2.0 (Oct07).
+
+Data set generated by Dr. Michael Miles at Virginia Commonwealth University <mfmiles@vcu.edu>.
diff --git a/general/datasets/Vcuetoh_1206_r/acknowledgment.rtf b/general/datasets/Vcuetoh_1206_r/acknowledgment.rtf
new file mode 100644
index 0000000..4463223
--- /dev/null
+++ b/general/datasets/Vcuetoh_1206_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/Vcuetoh_1206_r/cases.rtf b/general/datasets/Vcuetoh_1206_r/cases.rtf
new file mode 100644
index 0000000..a9b6489
--- /dev/null
+++ b/general/datasets/Vcuetoh_1206_r/cases.rtf
@@ -0,0 +1 @@
+This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/Vcuetoh_1206_r/contributors.rtf b/general/datasets/Vcuetoh_1206_r/contributors.rtf
new file mode 100644
index 0000000..6bb60a8
--- /dev/null
+++ b/general/datasets/Vcuetoh_1206_r/contributors.rtf
@@ -0,0 +1 @@
+Miles MF, Putman AH, Vorster PJ, Wolen AR
diff --git a/general/datasets/Vcuetoh_1206_r/experiment-design.rtf b/general/datasets/Vcuetoh_1206_r/experiment-design.rtf
new file mode 100644
index 0000000..05c600b
--- /dev/null
+++ b/general/datasets/Vcuetoh_1206_r/experiment-design.rtf
@@ -0,0 +1,5 @@
+This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
+
+Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
+
+Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/Vcuetoh_1206_r/experiment-type.rtf b/general/datasets/Vcuetoh_1206_r/experiment-type.rtf
new file mode 100644
index 0000000..17271ac
--- /dev/null
+++ b/general/datasets/Vcuetoh_1206_r/experiment-type.rtf
@@ -0,0 +1,2 @@
+This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
+Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
\ No newline at end of file
diff --git a/general/datasets/Vcuetoh_1206_r/platform.rtf b/general/datasets/Vcuetoh_1206_r/platform.rtf
new file mode 100644
index 0000000..ec67993
--- /dev/null
+++ b/general/datasets/Vcuetoh_1206_r/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcuetoh_1206_r/summary.rtf b/general/datasets/Vcuetoh_1206_r/summary.rtf
new file mode 100644
index 0000000..ff7c56f
--- /dev/null
+++ b/general/datasets/Vcuetoh_1206_r/summary.rtf
@@ -0,0 +1 @@
+In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/Vcuetoh_1206_r/tissue.rtf b/general/datasets/Vcuetoh_1206_r/tissue.rtf
new file mode 100644
index 0000000..6473075
--- /dev/null
+++ b/general/datasets/Vcuetoh_1206_r/tissue.rtf
@@ -0,0 +1,3 @@
+All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
+
+GEO Accession: GSE28515
diff --git a/general/datasets/Vcuetvssal_0609_r/experiment-type.rtf b/general/datasets/Vcuetvssal_0609_r/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Vcuetvssal_0609_r/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Vcuetvssal_0609_r/notes.rtf b/general/datasets/Vcuetvssal_0609_r/notes.rtf
new file mode 100644
index 0000000..3b773ce
--- /dev/null
+++ b/general/datasets/Vcuetvssal_0609_r/notes.rtf
@@ -0,0 +1 @@
+All samples were processed by Nate Bruce at VCU between April and May 2009. The BioRad Experion RNA analyzer and used to assess total RNA integrity and verify equal molar ratios of 18S and 28S ribosomal RNA. All RNA Quality Index (RQI) calculations were > 8. Standard Affymetrix reagents and protocols were used for generation of cDNA and biotinylated cRNA from total RNA samples. Integrity of cRNA was checked by Experion analysis prior to microarray hybridizations. All probes exceeded a maximum size of 3000 nt for the upper border of the cRNA size distribution.
diff --git a/general/datasets/Vcuetvssal_0609_r/platform.rtf b/general/datasets/Vcuetvssal_0609_r/platform.rtf
new file mode 100644
index 0000000..b7370c8
--- /dev/null
+++ b/general/datasets/Vcuetvssal_0609_r/platform.rtf
@@ -0,0 +1 @@
+GEO: GPL1261 Affymetrix GeneChip Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcuetvssal_0609_r/specifics.rtf b/general/datasets/Vcuetvssal_0609_r/specifics.rtf
new file mode 100644
index 0000000..5222820
--- /dev/null
+++ b/general/datasets/Vcuetvssal_0609_r/specifics.rtf
@@ -0,0 +1 @@
+Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the VTA in response to ethanol or saline and transforming these data using the S-score method to compare ethanol vs. saline expression from pairs of arrays for each strain (Kerns et al., Methods 31:274, 2003).
\ No newline at end of file
diff --git a/general/datasets/Vcuetvssal_0609_r/summary.rtf b/general/datasets/Vcuetvssal_0609_r/summary.rtf
new file mode 100644
index 0000000..ad6106d
--- /dev/null
+++ b/general/datasets/Vcuetvssal_0609_r/summary.rtf
@@ -0,0 +1,3 @@
+This BXD data set provides estimates of ventral tegmental area (VTA) mRNA expression in response to ethanol (1.8 g/kg x 4 hours) across 35 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 596 adult male animals obtained from Jackson Laboratory (27 classical BXD strains) or Oak Ridge National Laboratory (extended BXD series) and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and ethanol (IP) treatment in the light-dark transition model of anxiety.
+
+All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the VTA in response to ethanol or saline and transforming these data using the S-score method to compare ethanol vs. saline expression from pairs of arrays for each strain (Kerns et al., Methods 31:274, 2003). The S-score is a method developed for Affymetrix oligonucleotide arrays that is particularly suited to comparing expression on 2 or a small number of chips. The S-score output for each probeset is not an indication of expression magnitude but rather, the change in expression between compared arrays. The S-score is essentially a z-score centered around zero with positive S-scores reflecting increased gene expression with ethanol and negative scores reflecting ethanol-induced decreases in expression. Larger magnitude S-scores show more significant changes in expression and are generally correlated with the fold-change.
diff --git a/general/datasets/Vcusal_0609_r/experiment-type.rtf b/general/datasets/Vcusal_0609_r/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Vcusal_0609_r/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Vcusal_0609_r/notes.rtf b/general/datasets/Vcusal_0609_r/notes.rtf
new file mode 100644
index 0000000..3b773ce
--- /dev/null
+++ b/general/datasets/Vcusal_0609_r/notes.rtf
@@ -0,0 +1 @@
+All samples were processed by Nate Bruce at VCU between April and May 2009. The BioRad Experion RNA analyzer and used to assess total RNA integrity and verify equal molar ratios of 18S and 28S ribosomal RNA. All RNA Quality Index (RQI) calculations were > 8. Standard Affymetrix reagents and protocols were used for generation of cDNA and biotinylated cRNA from total RNA samples. Integrity of cRNA was checked by Experion analysis prior to microarray hybridizations. All probes exceeded a maximum size of 3000 nt for the upper border of the cRNA size distribution.
diff --git a/general/datasets/Vcusal_0609_r/platform.rtf b/general/datasets/Vcusal_0609_r/platform.rtf
new file mode 100644
index 0000000..b7370c8
--- /dev/null
+++ b/general/datasets/Vcusal_0609_r/platform.rtf
@@ -0,0 +1 @@
+GEO: GPL1261 Affymetrix GeneChip Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcusal_0609_r/specifics.rtf b/general/datasets/Vcusal_0609_r/specifics.rtf
new file mode 100644
index 0000000..cb1ae5d
--- /dev/null
+++ b/general/datasets/Vcusal_0609_r/specifics.rtf
@@ -0,0 +1 @@
+Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the VTA in response to saline.
diff --git a/general/datasets/Vcusal_0609_r/summary.rtf b/general/datasets/Vcusal_0609_r/summary.rtf
new file mode 100644
index 0000000..ad6106d
--- /dev/null
+++ b/general/datasets/Vcusal_0609_r/summary.rtf
@@ -0,0 +1,3 @@
+This BXD data set provides estimates of ventral tegmental area (VTA) mRNA expression in response to ethanol (1.8 g/kg x 4 hours) across 35 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 596 adult male animals obtained from Jackson Laboratory (27 classical BXD strains) or Oak Ridge National Laboratory (extended BXD series) and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and ethanol (IP) treatment in the light-dark transition model of anxiety.
+
+All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the VTA in response to ethanol or saline and transforming these data using the S-score method to compare ethanol vs. saline expression from pairs of arrays for each strain (Kerns et al., Methods 31:274, 2003). The S-score is a method developed for Affymetrix oligonucleotide arrays that is particularly suited to comparing expression on 2 or a small number of chips. The S-score output for each probeset is not an indication of expression magnitude but rather, the change in expression between compared arrays. The S-score is essentially a z-score centered around zero with positive S-scores reflecting increased gene expression with ethanol and negative scores reflecting ethanol-induced decreases in expression. Larger magnitude S-scores show more significant changes in expression and are generally correlated with the fold-change.
diff --git a/general/datasets/Vcusal_0806_r/summary.rtf b/general/datasets/Vcusal_0806_r/summary.rtf
new file mode 100644
index 0000000..36e8ee4
--- /dev/null
+++ b/general/datasets/Vcusal_0806_r/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 33, Name: VCU LXS PFC Et vs Sal M430A 2.0 (Aug06)
\ No newline at end of file
diff --git a/general/datasets/Vcusal_1006_r/acknowledgment.rtf b/general/datasets/Vcusal_1006_r/acknowledgment.rtf
new file mode 100644
index 0000000..4463223
--- /dev/null
+++ b/general/datasets/Vcusal_1006_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/Vcusal_1006_r/cases.rtf b/general/datasets/Vcusal_1006_r/cases.rtf
new file mode 100644
index 0000000..a9b6489
--- /dev/null
+++ b/general/datasets/Vcusal_1006_r/cases.rtf
@@ -0,0 +1 @@
+This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/Vcusal_1006_r/contributors.rtf b/general/datasets/Vcusal_1006_r/contributors.rtf
new file mode 100644
index 0000000..6bb60a8
--- /dev/null
+++ b/general/datasets/Vcusal_1006_r/contributors.rtf
@@ -0,0 +1 @@
+Miles MF, Putman AH, Vorster PJ, Wolen AR
diff --git a/general/datasets/Vcusal_1006_r/experiment-design.rtf b/general/datasets/Vcusal_1006_r/experiment-design.rtf
new file mode 100644
index 0000000..05c600b
--- /dev/null
+++ b/general/datasets/Vcusal_1006_r/experiment-design.rtf
@@ -0,0 +1,5 @@
+This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
+
+Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
+
+Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/Vcusal_1006_r/experiment-type.rtf b/general/datasets/Vcusal_1006_r/experiment-type.rtf
new file mode 100644
index 0000000..8df9efa
--- /dev/null
+++ b/general/datasets/Vcusal_1006_r/experiment-type.rtf
@@ -0,0 +1,5 @@
+This BXD data set provides estimates of ethanol-responsive mRNA expression in the prefrontal cortex across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure the anxiety-like behavior in response to restraint and treatment with either saline or 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005).
+
+All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex in response to ethanol or saline and transforming these data using the S-score method to compare ethanol vs. saline expression from pairs of arrays for each strain (Kerns et al., Methods 31:274, 2003). The S-score is a method developed for Affymetrix oligonucleotide arrays that is particularly suited to comparing expression on 2 or a small number of chips (Zhang et al., 2002). The S-score output for each probeset is not an indication of expression magnitude but rather, the change in expression between compared arrays. The S-score is essentially a z-score centered around zero with positive S-scores reflecting increased gene expression with ethanol and negative scores reflecting ethanol-induced decreases in expression. Larger magnitude S-scores show more significant changes in expression and are generally correlated with the "fold-change".
+
+Zhang, L., et al., 2002. A new algorithm for analysis of oligonucleotide arrays: application to expression profiling in mouse brain regions. J Mol Biol. 317, 225-35.
\ No newline at end of file
diff --git a/general/datasets/Vcusal_1006_r/platform.rtf b/general/datasets/Vcusal_1006_r/platform.rtf
new file mode 100644
index 0000000..ec67993
--- /dev/null
+++ b/general/datasets/Vcusal_1006_r/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcusal_1006_r/summary.rtf b/general/datasets/Vcusal_1006_r/summary.rtf
new file mode 100644
index 0000000..ff7c56f
--- /dev/null
+++ b/general/datasets/Vcusal_1006_r/summary.rtf
@@ -0,0 +1 @@
+In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/Vcusal_1006_r/tissue.rtf b/general/datasets/Vcusal_1006_r/tissue.rtf
new file mode 100644
index 0000000..6473075
--- /dev/null
+++ b/general/datasets/Vcusal_1006_r/tissue.rtf
@@ -0,0 +1,3 @@
+All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
+
+GEO Accession: GSE28515
diff --git a/general/datasets/Vcusal_1007_r/experiment-design.rtf b/general/datasets/Vcusal_1007_r/experiment-design.rtf
new file mode 100644
index 0000000..9826853
--- /dev/null
+++ b/general/datasets/Vcusal_1007_r/experiment-design.rtf
@@ -0,0 +1 @@
+Acute ethanol injection. Please ad dose, route, age, timing, etc.
diff --git a/general/datasets/Vcusal_1007_r/processing.rtf b/general/datasets/Vcusal_1007_r/processing.rtf
new file mode 100644
index 0000000..692987b
--- /dev/null
+++ b/general/datasets/Vcusal_1007_r/processing.rtf
@@ -0,0 +1 @@
+These data use the S-score algorithm of Miles and colleagues (PMIDs: 16574698, 16545131, 14597311, 11902839) to evaluate the magnitude of change between the control condition and the ethanol-treated animals. Positive S-score values reflect increased expression with ethanol, negative S-scores reflect decreased expression after ethanol treatment.
diff --git a/general/datasets/Vcusal_1007_r/summary.rtf b/general/datasets/Vcusal_1007_r/summary.rtf
new file mode 100644
index 0000000..479039b
--- /dev/null
+++ b/general/datasets/Vcusal_1007_r/summary.rtf
@@ -0,0 +1,3 @@
+Summary of DatasetId 44, Name: VCU BXD NA Et vs Sal M430 2.0 (Oct07).
+
+Data set generated by Dr. Michael Miles at Virginia Commonwealth University <mfmiles@vcu.edu>.
diff --git a/general/datasets/Vcusal_1206_r/acknowledgment.rtf b/general/datasets/Vcusal_1206_r/acknowledgment.rtf
new file mode 100644
index 0000000..4463223
--- /dev/null
+++ b/general/datasets/Vcusal_1206_r/acknowledgment.rtf
@@ -0,0 +1 @@
+Data were generated with funds to Michael F Miles from the NIAAA.
diff --git a/general/datasets/Vcusal_1206_r/cases.rtf b/general/datasets/Vcusal_1206_r/cases.rtf
new file mode 100644
index 0000000..a9b6489
--- /dev/null
+++ b/general/datasets/Vcusal_1206_r/cases.rtf
@@ -0,0 +1 @@
+This BXD data set provides estimates of mRNA expression in the prefrontal cortex following ethanol treatment across 27 BXD recombinant inbred strains and their B6 and D2 progenitor strains. All samples are from a total of 468 adult male animals obtained from Jackson Laboratory and raised in a standard laboratory environment. An average of 8 males per strain was used to measure anxiety-like behavior in response to restraint and treatment with 1.8g/kg ethanol in the light-dark transition model of anxiety. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected as previously described (Kerns et al., J. Neurosci. 25:2255, 2005). All RNA isolation and subsequent probe generation and hybridization to microarrays were completed using a supervised randomization procedure to minimize batch effects. Affymetrix M430 type 2.0 microarrays were used for hybridization using standard procedures. Expression analysis was conducted by estimating the relative abundance of over 45,000 transcripts in the prefrontal cortex following ethanol treatment using the Robust Multichip Average (RMA) method.
diff --git a/general/datasets/Vcusal_1206_r/contributors.rtf b/general/datasets/Vcusal_1206_r/contributors.rtf
new file mode 100644
index 0000000..6bb60a8
--- /dev/null
+++ b/general/datasets/Vcusal_1206_r/contributors.rtf
@@ -0,0 +1 @@
+Miles MF, Putman AH, Vorster PJ, Wolen AR
diff --git a/general/datasets/Vcusal_1206_r/experiment-design.rtf b/general/datasets/Vcusal_1206_r/experiment-design.rtf
new file mode 100644
index 0000000..05c600b
--- /dev/null
+++ b/general/datasets/Vcusal_1206_r/experiment-design.rtf
@@ -0,0 +1,5 @@
+This data set was generated concurrently with the VCU saline prefrontal cortex BXD RMA data and therefore consisted of 64 microarrays processed in 5 groups of 8 to 16 microarrays during the month of September 2006. All RNA extractions, cRNA synthesis, and hybridizations were randomized across strain and treatment groups to minimize batch effects.
+
+Many of the techniques used to generate this data set are described in a recent publication in the Journal of Neuroscience.
+
+Animals were injected intraperitoneally (IP) with saline or 1.8 g/kg of ethanol. As part of a parallel study of ethanol induced anxiolysis, all mice underwent behavioral testing that included 15 minutes of restraint in a 50 mL conical tube followed by 10 minutes in a light-dark chamber. Mice were killed by cervical dislocation four hours following IP injection. Immediately thereafter, brains were extracted and chilled for 1 minute in iced phosphate buffer before being microdissected into 8 constituent regions, including the medial prefrontal cortex. Samples were randomly assigned to batch groups prior to total RNA extraction, cRNA synthesis and hybridization. Each microarray represent a pooling of 4-5 animals.
diff --git a/general/datasets/Vcusal_1206_r/experiment-type.rtf b/general/datasets/Vcusal_1206_r/experiment-type.rtf
new file mode 100644
index 0000000..4af1832
--- /dev/null
+++ b/general/datasets/Vcusal_1206_r/experiment-type.rtf
@@ -0,0 +1 @@
+None
\ No newline at end of file
diff --git a/general/datasets/Vcusal_1206_r/platform.rtf b/general/datasets/Vcusal_1206_r/platform.rtf
new file mode 100644
index 0000000..ec67993
--- /dev/null
+++ b/general/datasets/Vcusal_1206_r/platform.rtf
@@ -0,0 +1 @@
+[Mouse430_2] Affymetrix Mouse Genome 430 2.0 Array
diff --git a/general/datasets/Vcusal_1206_r/summary.rtf b/general/datasets/Vcusal_1206_r/summary.rtf
new file mode 100644
index 0000000..ff7c56f
--- /dev/null
+++ b/general/datasets/Vcusal_1206_r/summary.rtf
@@ -0,0 +1 @@
+In order to elucidate the molecular mechanisms underlying individual variation in sensitivity to ethanol we profiled the prefrontal cortex transcriptomes of two inbred strains that exhibit divergent responses to acute ethanol, the C57BL6/J (B6) and DBA/2J (D2) strains, as well as 27 members of the BXD recombinant inbred panel, which was derived from a B6 x D2 cross. With this dataset we were able to identify several gene co-expression networks that were robustly altered by acute ethanol across the BXD panel. These ethanol-responsive gene-enriched networks were heavily populated by genes regulating synaptic transmission and neuroplasticity, and showed strong genetic linkage to discreet chromosomal loci. Network-based measurements of node importance identified several hub genes as established regulators of ethanol response phenotypes, while other hubs represent novel candidate modulators of ethanol responses.
diff --git a/general/datasets/Vcusal_1206_r/tissue.rtf b/general/datasets/Vcusal_1206_r/tissue.rtf
new file mode 100644
index 0000000..6473075
--- /dev/null
+++ b/general/datasets/Vcusal_1206_r/tissue.rtf
@@ -0,0 +1,3 @@
+All animals were obtained at 8-9 weeks of age from the Jackson Laboratory (Bar Harbor, ME) and were treated, behaviorally tested and brains dissected by Alex Putman and colleagues at VCU. Following an hour acclimation period to the behavioral room, animals were restrained for 15 minutes, immediately injected (I.P.) with either saline (0.9%) or 1.8g/kg ethanol, and 5 minutes later placed in the light-dark box for a 10-minute test session. All behavioral testing occurred between 10 AM and 1 PM during the light phase over a 12 month period beginning August 2005. Four hours after treatment, animals were rapidly sacrificed by cervical dislocation, brains were removed, cooled and microdissected. Prefrontal cortex tissue was isolated by microdissection using a wedge-shaped slice taken from a 4 mm thick brain slice extending rostrally from the optic chiasm. The wedge was centered on the inter-hemispheric fissure and extending 2 mm laterally on each side and ventrally to just above the corpus callosum. This tissue and all other brain regions were dissected in less than 5 minutes per mouse and were immediately frozen in liquid nitrogen followed by storage at -80 oC prior to RNA isolation. A pool of dissected tissue from 3 mice of the same strain was used to generate RNA samples. All RNA samples were extracted at VCU by Alex Putman during October 2006 and the order of RNA isolation was randomized across all strains and treatment groups (since saline treated animals were processed concurrently).
+
+GEO Accession: GSE28515
diff --git a/general/datasets/Vcusalo_1007_r/experiment-design.rtf b/general/datasets/Vcusalo_1007_r/experiment-design.rtf
new file mode 100644
index 0000000..9826853
--- /dev/null
+++ b/general/datasets/Vcusalo_1007_r/experiment-design.rtf
@@ -0,0 +1 @@
+Acute ethanol injection. Please ad dose, route, age, timing, etc.
diff --git a/general/datasets/Vcusalo_1007_r/processing.rtf b/general/datasets/Vcusalo_1007_r/processing.rtf
new file mode 100644
index 0000000..692987b
--- /dev/null
+++ b/general/datasets/Vcusalo_1007_r/processing.rtf
@@ -0,0 +1 @@
+These data use the S-score algorithm of Miles and colleagues (PMIDs: 16574698, 16545131, 14597311, 11902839) to evaluate the magnitude of change between the control condition and the ethanol-treated animals. Positive S-score values reflect increased expression with ethanol, negative S-scores reflect decreased expression after ethanol treatment.
diff --git a/general/datasets/Vcusalo_1007_r/summary.rtf b/general/datasets/Vcusalo_1007_r/summary.rtf
new file mode 100644
index 0000000..479039b
--- /dev/null
+++ b/general/datasets/Vcusalo_1007_r/summary.rtf
@@ -0,0 +1,3 @@
+Summary of DatasetId 44, Name: VCU BXD NA Et vs Sal M430 2.0 (Oct07).
+
+Data set generated by Dr. Michael Miles at Virginia Commonwealth University <mfmiles@vcu.edu>.
diff --git a/general/datasets/Vubxdmousemidbrainq0512/cases.rtf b/general/datasets/Vubxdmousemidbrainq0512/cases.rtf
new file mode 100644
index 0000000..4a8704a
--- /dev/null
+++ b/general/datasets/Vubxdmousemidbrainq0512/cases.rtf
@@ -0,0 +1,795 @@
+
+
+
+
+
+
+
+
+
+ | Index |
+ Sample ID |
+ Sex |
+ Strain Assignment L14 |
+
+
+ | 1 |
+ 916-DCA-68 |
+ M |
+ BXD1 |
+
+
+ | 2 |
+ 916-DCA-165 |
+ M |
+ BXD1 |
+
+
+ | 3 |
+ 916-DCA-147 |
+ M |
+ BXD1 |
+
+
+ | 4 |
+ 916-DCA-114 |
+ M |
+ BXD1 |
+
+
+ | 5 |
+ 916-DCA-107 |
+ M |
+ BXD11 |
+
+
+ | 6 |
+ 916-DCA-187 |
+ M |
+ BXD11 |
+
+
+ | 7 |
+ 916-DCA-67 |
+ M |
+ BXD11 |
+
+
+ | 8 |
+ 916-DCA-158 |
+ M |
+ BXD12 |
+
+
+ | 9 |
+ 916-DCA-35 |
+ M |
+ BXD12 |
+
+
+ | 10 |
+ 916-DCA-36 |
+ M |
+ BXD12 |
+
+
+ | 11 |
+ 916-DCA-140 |
+ M |
+ BXD14 |
+
+
+ | 12 |
+ 916-DCA-45 |
+ M |
+ BXD14 |
+
+
+ | 13 |
+ 916-DCA-99 |
+ M |
+ BXD14 |
+
+
+ | 14 |
+ 916-DCA-191 |
+ M |
+ BXD14 |
+
+
+ | 15 |
+ 916-DCA-79 |
+ M |
+ BXD15 |
+
+
+ | 16 |
+ 916-DCA-38 |
+ M |
+ BXD15 |
+
+
+ | 17 |
+ 916-DCA-41 |
+ M |
+ BXD15 |
+
+
+ | 18 |
+ 916-DCA-88 |
+ M |
+ BXD15 |
+
+
+ | 19 |
+ 916-DCA-141 |
+ M |
+ BXD16 |
+
+
+ | 20 |
+ 916-DCA-97 |
+ M |
+ BXD16 |
+
+
+ | 21 |
+ 916-DCA-18 |
+ M |
+ BXD16 |
+
+
+ | 22 |
+ 916-DCA-179 |
+ M |
+ BXD16 |
+
+
+ | 23 |
+ 916-DCA-16 |
+ M |
+ BXD18 |
+
+
+ | 24 |
+ 916-DCA-23 |
+ M |
+ BXD18 |
+
+
+ | 25 |
+ 916-DCA-12 |
+ M |
+ BXD18 |
+
+
+ | 26 |
+ 916-DCA-175 |
+ M |
+ BXD18 |
+
+
+ | 27 |
+ 916-DCA-8 |
+ M |
+ BXD19 |
+
+
+ | 28 |
+ 916-DCA-174 |
+ M |
+ BXD19 |
+
+
+ | 29 |
+ 916-DCA-78 |
+ M |
+ BXD19 |
+
+
+ | 30 |
+ 916-DCA-24 |
+ M |
+ BXD19 |
+
+
+ | 31 |
+ 916-DCA-105 |
+ M |
+ BXD2 |
+
+
+ | 32 |
+ 916-DCA-57 |
+ M |
+ BXD2 |
+
+
+ | 33 |
+ 916-DCA-166 |
+ M |
+ BXD2 |
+
+
+ | 34 |
+ 916-DCA-181 |
+ M |
+ BXD2 |
+
+
+ | 35 |
+ 916-DCA-100 |
+ M |
+ BXD20 |
+
+
+ | 36 |
+ 916-DCA-82 |
+ M |
+ BXD20 |
+
+
+ | 37 |
+ 916-DCA-72 |
+ M |
+ BXD20 |
+
+
+ | 38 |
+ 916-DCA-131 |
+ M |
+ BXD20 |
+
+
+ | 39 |
+ 916-DCA-63 |
+ M |
+ BXD21 |
+
+
+ | 40 |
+ 916-DCA-13 |
+ M |
+ BXD21 |
+
+
+ | 41 |
+ 916-DCA-15 |
+ M |
+ BXD21 |
+
+
+ | 42 |
+ 916-DCA-109 |
+ M |
+ BXD22 |
+
+
+ | 43 |
+ 916-DCA-101 |
+ M |
+ BXD22 |
+
+
+ | 44 |
+ 916-DCA-69 |
+ M |
+ BXD22 |
+
+
+ | 45 |
+ 916-DCA-104 |
+ M |
+ BXD22 |
+
+
+ | 46 |
+ 916-DCA-125 |
+ M |
+ BXD24 |
+
+
+ | 47 |
+ 916-DCA-33 |
+ M |
+ BXD24 |
+
+
+ | 48 |
+ 916-DCA-108 |
+ M |
+ BXD24 |
+
+
+ | 49 |
+ 916-DCA-44 |
+ M |
+ BXD24 |
+
+
+ | 50 |
+ 916-DCA-80 |
+ M |
+ BXD27 |
+
+
+ | 51 |
+ 916-DCA-151 |
+ M |
+ BXD28 |
+
+
+ | 52 |
+ 916-DCA-47 |
+ M |
+ BXD28 |
+
+
+ | 53 |
+ 916-DCA-27 |
+ M |
+ BXD28 |
+
+
+ | 54 |
+ 916-DCA-154 |
+ M |
+ BXD28 |
+
+
+ | 55 |
+ 916-DCA-71 |
+ M |
+ BXD29 |
+
+
+ | 56 |
+ 916-DCA-54 |
+ M |
+ BXD29 |
+
+
+ | 57 |
+ 916-DCA-122 |
+ M |
+ BXD29 |
+
+
+ | 58 |
+ 916-DCA-51.1 |
+ M |
+ BXD29 |
+
+
+ | 59 |
+ 916-DCA-144 |
+ M |
+ BXD31 |
+
+
+ | 60 |
+ 916-DCA-76 |
+ M |
+ BXD31 |
+
+
+ | 61 |
+ 916-DCA-164 |
+ M |
+ BXD31 |
+
+
+ | 62 |
+ 916-DCA-37 |
+ M |
+ BXD32 |
+
+
+ | 63 |
+ 916-DCA-89 |
+ M |
+ BXD32 |
+
+
+ | 64 |
+ 916-DCA-25 |
+ M |
+ BXD32 |
+
+
+ | 65 |
+ 916-DCA-160 |
+ M |
+ BXD33 |
+
+
+ | 66 |
+ 916-DCA-65 |
+ M |
+ BXD33 |
+
+
+ | 67 |
+ 916-DCA-128 |
+ M |
+ BXD33 |
+
+
+ | 68 |
+ 916-DCA-73 |
+ M |
+ BXD34 |
+
+
+ | 69 |
+ 916-DCA-103 |
+ M |
+ BXD34 |
+
+
+ | 70 |
+ 916-DCA-137 |
+ M |
+ BXD34 |
+
+
+ | 71 |
+ 916-DCA-29 |
+ M |
+ BXD38 |
+
+
+ | 72 |
+ 916-DCA-112 |
+ M |
+ BXD38 |
+
+
+ | 73 |
+ 916-DCA-84 |
+ M |
+ BXD38 |
+
+
+ | 74 |
+ 916-DCA-132 |
+ M |
+ BXD38 |
+
+
+ | 75 |
+ 916-DCA-156 |
+ M |
+ BXD38 |
+
+
+ | 76 |
+ 916-DCA-130 |
+ M |
+ BXD39 |
+
+
+ | 77 |
+ 916-DCA-117 |
+ M |
+ BXD39 |
+
+
+ | 78 |
+ 916-DCA-111 |
+ M |
+ BXD39 |
+
+
+ | 79 |
+ 916-DCA-14 |
+ M |
+ BXD40 |
+
+
+ | 80 |
+ 916-DCA-188 |
+ M |
+ BXD40 |
+
+
+ | 81 |
+ 916-DCA-192 |
+ M |
+ BXD40 |
+
+
+ | 82 |
+ 916-DCA-90 |
+ M |
+ BXD40 |
+
+
+ | 83 |
+ 916-DCA-52 |
+ M |
+ BXD42 |
+
+
+ | 84 |
+ 916-DCA-2 |
+ M |
+ BXD42 |
+
+
+ | 85 |
+ 916-DCA-126 |
+ M |
+ BXD42 |
+
+
+ | 86 |
+ 916-DCA-81 |
+ M |
+ BXD42 |
+
+
+ | 87 |
+ 916-DCA-118 |
+ M |
+ BXD44 |
+
+
+ | 88 |
+ 916-DCA-42 |
+ M |
+ BXD44 |
+
+
+ | 89 |
+ 916-DCA-92 |
+ M |
+ BXD44 |
+
+
+ | 90 |
+ 916-DCA-39 |
+ M |
+ BXD49 |
+
+
+ | 91 |
+ 916-DCA-98 |
+ M |
+ BXD49 |
+
+
+ | 92 |
+ 916-DCA-83 |
+ M |
+ BXD49 |
+
+
+ | 93 |
+ 916-DCA-85 |
+ M |
+ BXD5 |
+
+
+ | 94 |
+ 916-DCA-6 |
+ M |
+ BXD5 |
+
+
+ | 95 |
+ 916-DCA-142 |
+ M |
+ BXD5 |
+
+
+ | 96 |
+ 916-DCA-11 |
+ M |
+ BXD55 |
+
+
+ | 97 |
+ 916-DCA-121 |
+ M |
+ BXD55 |
+
+
+ | 98 |
+ 916-DCA-77 |
+ M |
+ BXD55 |
+
+
+ | 99 |
+ 916-DCA-123 |
+ M |
+ BXD6 |
+
+
+ | 100 |
+ 916-DCA-28 |
+ M |
+ BXD6 |
+
+
+ | 101 |
+ 916-DCA-161 |
+ M |
+ BXD6 |
+
+
+ | 102 |
+ 916-DCA-124 |
+ M |
+ BXD6 |
+
+
+ | 103 |
+ 916-DCA-189 |
+ M |
+ BXD62 |
+
+
+ | 104 |
+ 916-DCA-143 |
+ M |
+ BXD62 |
+
+
+ | 105 |
+ 916-DCA-116 |
+ M |
+ BXD62 |
+
+
+ | 106 |
+ 916-DCA-159 |
+ M |
+ BXD73 |
+
+
+ | 107 |
+ 916-DCA-40 |
+ M |
+ BXD73 |
+
+
+ | 108 |
+ 916-DCA-169 |
+ M |
+ BXD73 |
+
+
+ | 109 |
+ 916-DCA-120 |
+ M |
+ BXD8 |
+
+
+ | 110 |
+ 916-DCA-64 |
+ M |
+ BXD8 |
+
+
+ | 111 |
+ 916-DCA-93 |
+ M |
+ BXD8 |
+
+
+ | 112 |
+ 916-DCA-148 |
+ M |
+ BXD86 |
+
+
+ | 113 |
+ 916-DCA-55 |
+ M |
+ BXD86 |
+
+
+ | 114 |
+ 916-DCA-170 |
+ M |
+ BXD86 |
+
+
+ | 115 |
+ 916-DCA-50 |
+ M |
+ BXD89 |
+
+
+ | 116 |
+ 916-DCA-127 |
+ M |
+ BXD89 |
+
+
+ | 117 |
+ 916-DCA-32 |
+ M |
+ BXD89 |
+
+
+ | 118 |
+ 916-DCA-62 |
+ M |
+ BXD89 |
+
+
+ | 119 |
+ 916-DCA-53 |
+ M |
+ BXD9 |
+
+
+ | 120 |
+ 916-DCA-138 |
+ M |
+ BXD9 |
+
+
+ | 121 |
+ 916-DCA-180 |
+ M |
+ BXD9 |
+
+
+ | 122 |
+ 916-DCA-46 |
+ M |
+ BXD9 |
+
+
+ | 123 |
+ 916-DCA-74 |
+ M |
+ BXD96 |
+
+
+ | 124 |
+ 916-DCA-110 |
+ M |
+ BXD96 |
+
+
+ | 125 |
+ 916-DCA-94 |
+ M |
+ BXD96 |
+
+
+ | 126 |
+ 916-DCA-49 |
+ M |
+ BXD96 |
+
+
+ | 127 |
+ 916-DCA-119 |
+ M |
+ BXD98 |
+
+
+ | 128 |
+ 916-DCA-135 |
+ M |
+ BXD98 |
+
+
+ | 129 |
+ 916-DCA-58 |
+ M |
+ BXD98 |
+
+
+
+ |
+
+
+
+
diff --git a/general/datasets/Vubxdmousemidbrainq0512/experiment-type.rtf b/general/datasets/Vubxdmousemidbrainq0512/experiment-type.rtf
new file mode 100644
index 0000000..5e8a770
--- /dev/null
+++ b/general/datasets/Vubxdmousemidbrainq0512/experiment-type.rtf
@@ -0,0 +1 @@
+Baseline/control/normative gene expression in the murine midbrain under standard vivarium conditions.
\ No newline at end of file
diff --git a/general/datasets/Vubxdmousemidbrainq0512/summary.rtf b/general/datasets/Vubxdmousemidbrainq0512/summary.rtf
new file mode 100644
index 0000000..7ed558d
--- /dev/null
+++ b/general/datasets/Vubxdmousemidbrainq0512/summary.rtf
@@ -0,0 +1 @@
+Summary of DatasetId 141, Name: VU BXD Midbrain Agilent SurePrint G3 Mouse GE (May12)
diff --git a/general/datasets/gn10/acknowledgment.rtf b/general/datasets/gn10/acknowledgment.rtf
deleted file mode 100644
index 5098d32..0000000
--- a/general/datasets/gn10/acknowledgment.rtf
+++ /dev/null
@@ -1,3 +0,0 @@
-Support for acquisition of microarray data sets was generously provided by Dr. Barrrett Haik, Chair of the Department of Ophthalmology, and director of the Hamilton Eye Institute. Support for the continued development of GeneNetwork was provided by a NIDA/NIMH/NIAAA Human Brain Project grant and from funds from NEI grant to Dr. Eldon Geisert (R01EY017841), an NEI Vision Core grant (EY14080) and an Unrestricted Grant from Research To Prevent Blindness.
-
-We thank Dr. Ted Choi, Chief Scientific Director of Predictive Biology, Inc. (past director of molecular genetics at Deltagen Inc.) for providing us with eye samples from several interesting DeltaGen knockouts.
diff --git a/general/datasets/gn10/cases.rtf b/general/datasets/gn10/cases.rtf
deleted file mode 100644
index 552d4a5..0000000
--- a/general/datasets/gn10/cases.rtf
+++ /dev/null
@@ -1,57 +0,0 @@
-This is the complete and final HEIMED data set. HEIMED consists of expression data for 103 genetically defined lines of mice with standard errors of the mean. Almost all animals are young adults between 50 and 80 days of age (Table 1, maximum age is 123 days). We measured expression in conventional inbred strains, BXD recombinant inbred (RI) strains, reciprocal F1s between C57BL/6J and DBA/2J, and several mutant and knockout lines. We have combined all common strains, F1 hybrids, and mutants into a group called the Mouse Diversity Panel (MDP). Four lines, namely, C57BL/6J (B6), DBA/2J (D2), and the pair of B6D2F1 and D2B6F1 hybrids are common to both the MDP and the BXD set. This is a breakdown of cases that are part of HEIMED:
-
-
- - 68 BXD strains. The first 32 of these strains are from the Taylor series of BXD strains generated at the Jackson Laboratory by Benjamin A. Taylor. BXD1 through BXD32 were started in the late 1970s, whereas BXD33 through 42 were started in the 1990s. Only one of these strains, BXD24 (know also known as BXD24b), has retinal degeneration (a spontaneous mutation). The other 36 BXD strains (BXD43 and higher) were bred by Lu Lu, Jeremy Peirce, Lee M. Silver, and Robert W. Williams starting in 1997 using B6D2 generation 10 advanced intercross progeny. This modified breeding protocol doubles the number of recombinations per BXD strain and improves mapping resolution (Peirce et al. 2004). All of the Taylor series of BXD strains and many of the new BXD strains are available from the Jackson Laboratory. All of the new BXD strains (BXD43 and higher) are also available directly from Lu Lu and colleagues at the University of Tennessee Health Science Center in Memphis, TN, USA.
- - 35 MDP lines, including 26 inbred strains representing closely related substrains (e.g, BALB/cJ and BALB/cByJ), many of the most widely used common Mus musculus domesticus inbred strains (e.g., C57BL/6J and 129S1/SvImJ), inbred but wild-derived representatives of common subspecies (Mus musculus domesticus, e.g, WSB/EiJ; M. musculus musculus, e.g., CZECHII/EiJ; M. musculus molossinus, e.g., MOLF/EiJ; M. musculus castaneus, e.g., CAST/EiJ); and even one different species of mouse (Mus spicilegus, PANCEVO/EiJ). The MDP also includes the reciprocal F1 hybrids (B6D2F1 and D2B6F1) and the following 6 KO lines and the Nyx-nob mutant:
- - 6 knockouts (KO), including a KO of Rpe65, and 5 DeltaGen Inc. knockout lines provided by Dr. Ted Choi. These KO lines have had a bacterial lacZ construct inserted into the gene. The endogenous promoter drives expression of beta-galactosidase. RT-PCR analysis detects a gene transcript in most tissues. The following KOs from DeltaGen were studied: Gabra1, Gabbr1, Gnb1, Gpr19, and Clcn3. We also included one spontaneous mutant of the nyctalopin (Nyx no b wave "nob") gene (Pardue et al., 1998) that is on a BALB/cByJ background.
-
-
-Rod photoreceptor degeneration in inbred mice: Six strains of mice included in HEIMED suffer from severe loss of photoreceptors (mainly rods) and have the equivalent of night blindness in human patients. The death of photoreceptors in these strains occurs by one to two months of age and is often caused by the retinal degeneration 1 (rd1) mutant allele in the rod cyclic-GMP phosphodiesterase 6 beta subunit gene (Pde6b). The following strains are known to have photoreceptor degeneration: C3H/HeJ, FVB/NJ, MOLF/EiJ, SJL/J and BXD24/TyJ. BXD24/TyJ is now known as BXD24b/TyJ and has nearly complete retinal degeneration. BXD24a/TyJ, a 1988 F80 inbred stock that has been rederived from cryogenic storage, does not have retinal degeneration (stock number 005243) and is an ideal coisogenic control, but is not included in the HEIMED data set.
-
-As expected (Dickerson LW et al., 2002) and as judged from the absence of rhodopsin expression, one of the DeltaGen KO lines (chloride ion channel 3, Clcn3) also has retinal degeneration: B6129P2F2N1-Clcn3. Degeneration in this strain is likely to include all rods and all cones. The cone defect is obvious from the decrease in expression of Gnat2, a gene associated with cones and achromatopsia in mice and humans.
-
-Lines of mice were selected using the following criteria:
-
-
- - genetic and phenotypic diversity, including use by the Phenome Project
- - representation of a fairly wide variety of different subspecies of Mus
- - their use in making genetic reference populations including recombinant inbred strains, cosomic strains, congenic and recombinant congenic strains
- - their use by the Complex Trait Consortium to make the Collaborative Cross (Tel Aviv/Wellcome, Oak Ridge/DOE, and Perth/UWA)
- - genome sequence data from three sources (NHGRI, Celera, and Perlegen-NIEHS)
- - interesting mutations or knockouts affecting genes with high expression in the eye
- - general availability from The Jackson Laboratory. The only exception are the DeltaGen KO mice.
-
-
-We have included all eight parents of the Collaborative Cross (129S1/SvImJ, A/J, C57BL/6J, CAST/EiJ, NOD/LtJ, NZO/HlLtJ, PWK/PhJ, and WSB/EiJ) in the MDP. Fourteen MDP strains have been partially sequenced by Perlegen for the NIEHS, including including 129S1/SvImJ, A/J, AKR/J, BALB/cByJ, C3H/HeJ, CAST/EiJ, DBA/2J, FVB/NJ, KK/HlJ, MOLF/EiJ, NOD/LtJ, NZW/LacJ, PWD/PhJ, and WSB/EiJ (see the GeneNetwork SNP Browser for data, details, and see Perlegen's excellent data resources and browser).
-
-
- - 129S1/SvImJ : Collaborative Cross strain sequenced by NIEHS; background for many knockouts (R1 ES cell line); Phenome Project A list. This strain (JAX No 002448, aka 129S1/Sv-++Kitl/+) carries hypopigmentation mutations (white bellied chinchilla) of the tyrosinase gene on Chr 7 and a mutant allele of the steel (Kitl) gene. It is also a cone photoreceptor function loss 3 mutant (Cpfl3 allele) of the Gnat2 gene that is a model for achromatopsia (JAX Stock Number: 002448)
- - A/J: Collaborative Cross strain sequenced by Perlegen/NIEHS; parent of the AXB/BXA panel. A tyrosinase (Tyr c allele) albino mutant. This strain is particularly sensitive to light-induced photoreceptor loss (Danciger et al., 2007). (JAX Stock Number: 000646)
- - BALB/cByJ: Sequenced by NIEHS; maternal parent of the CXB panel; Phenome Project old group A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Small brain, not aggressive (JAX Stock Number: 001026)
- - BALB/cJ: Phenome Project A list. A tyrosinase (Tyr c allele) albino mutant and also a tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. Large brain and aggressive (JAX Stock Number: 000651)
- - BXSB/MpJ: A white-bellied agouti strains with interesting autoimmune disease restricted to males that is associated with a mutation in the Yaa gene that causes glomerulonephritis, a dramatic increase in number of peripheral monocytes, and pre-B-cell deficiency (JAX Stock Number: 000740)
- - C3H/HeJ: The Heston (He) substrain with a wildtype agouti (A allele) coat color. Sequenced by Perlegen/NIEHS; paternal parent of the BXH panel; Phenome Project old group A list. Important to note for this eye expression dataset, C3H/HeJ is a Pdeb6 rd1 mutant with near total photoreceptor loss at as early as postnatal day 30. Also a Tlr4 mutant that is endotoxin resistant. (JAX Stock Number: 000659)
- - C57BL/6J: Sequenced by NIH/NHGRI; parental strain of AXB/BXA, BXD, and BXH; Phenome Project A list. Single most widely used inbred strain of mouse. (JAX Stock Number: 000664)
- - C57BLKS/J: Black Kaliss strain (non-agouti a allele) derived from C57BL/6J, but genetically contaminated at some point mainly with DBA/2J and then reinbred. Now at the Jackson Laboratory. (JAX Stock Number: 000662)
- - CAST/EiJ: A wild-derived inbred Mus musculus castaneus strain. Samples of this subspecies were captured in Southeast Asia. One of three wild-derived strains in the Collaborative Cross sequenced by NIEHS; Phenome Project A list. CAST/Ei and CAST/EiJ are the same strain. The addition of the "J" is trivial and was added when stock were transferred from Dr. Eicher's lab to the Jackson Laboratory production facility in about 2004. (JAX Stock Number: 000928)
- - CBA/CaJ: Agouti strain from the Jackson Laboratory. Wildtype pigment genes. (JAX Stock Number: 000654)
- - CZECHII/EiJ: Czech 2 is a wild-derived inbred strain M. musculus musculus strain. Samples of this subspecies were caught in the Czech Republic and inbred at the Jackson Laboratory by Eva Eicher. White-bellied agouti. (JAX Stock Number: 001144).
- - DBA/2J: The dilute, brown, agouti (dba) strain is the oldest inbred strain of mouse. Inbreeding was started in 1909 by Little. A tyrosinase related protein 1 (Tyrp1 b) brown allele mutant. A myosin 5a (Myo5a d) dilute allele mutant. Sequenced by Perlegen/NIEHS and Celera; paternal parent of the BXD panel; Phenome Project old A group list. (JAX Stock Number: 000671)
- - FVB/NJ: Friend's leukemia virus B (FVB) strain. Sequenced by Perlegen/NIEHS and Celera. Tyr c locus albino and a Pdeb6 rd1 mutant derived from Swiss mice at NIH. This has been the most common strain used to make transgenic mice due to large and easily injected oocytes; Phenome Project A list (JAX Stock Number: 001800).
- - KK/HlJ: K Kondo's (KK) Kasukabe strain is a homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. Males have a form of type 2 diabetes. Sequenced by Perlegen/NIEHS. (JAX Stock Number: 002106)
- - LG/J: Large (LG) strain. Paternal parent of the Large-by-Small set of RI strains made by James Cheverud and colleagues (the LGXSM panel, not to be confused with the LongXShort or LXS panel). A Tyr c locus albino strain. (JAX Stock Number: 000675)
- - LP/J: White-bellied agouit strain with a piebald mutation in the endothelin receptor type B Ednrb gene from at the Jackson Laboratory. Some reduction in melanocytes in choroid of eye due to neural creast migration abnormalities. (JAX Stock Number: 000676)
- - MOLF/EiJ: A wild-derived inbred strain derived from M. musculus molossinus samples camputered in Fukuoka, Japan. This strain has the retinal degeneration rd1 allele in Pde6b. There appears to have been some genetic contamination of this strain with conventional inbred strains in the past several decades (F. Pardo, personal communication to RWW, August 2006). However, the strain is currently fully inbred. (JAX Stock Number: 000550)
- - NOD/LtJ: Non-obese diabetic strain, originally from M. Hattori in Kyoto, Japan. This is the Edward Leiter (Lt) substrain from the Jackson Laboratory. Collaborative Cross strain sequenced by NIEHS; Phenome Project B list. Homozygous age-related hearing loss (ahl) allele mutant of the Cdh23 gene. A Tyr c locus albino strain. (JAX Stock Number: 001976)
- - NZO/HlLtJ: New Zealand Obese strain. This is a severely obese and hypertensive strain. Males often develop a type 2 diabetes. Collaborative Cross strain. Agouti coat color. (JAX Stock Number: 002105)
- - NZB/BlNJ: New Zealand Black inbred strain from Bielschowsky (BL, substrain is "B lowercase L N", not "BiN") now maintained at the Jackson Laboratory. (JAX Stock Number: 000648)
- - NZW/LacJ: New Zealand White strain from the Laboratory Animal Center (Carshalton, UK), now maintained at the Jackson Laboratory. Carries the Tyr c locus albino mutation, the pink-eye dilution mutation in the Oca2 or p locus, and the brown allele at Tyrp1. (JAX Stock Number: 001058)
- - PANCEVO/EiJ: PANCEVO/EiJ is a wild-derived inbred strain from the Mus spicilegus samples caught in the Pancevo, Serbia. This species of mouse is also known as the Steppe mouse (taxon identifier 10103). M. spicilegus is a colonial mound-building species. No known ocular or retina mutations, but the expression level of Gnat2 is low in this strain, either due to a 3' UTR length variant or possible achromatosia (cone degeneration) (JAX Stock Number: 001384)
- - PWD/PhJ: A wild-derived Mus musculus musculus agouti strain inbred from samples caught near Prague, Czech Republic. Sequenced by Perlegen/NIEHS; parental strain for a consomic set by Forjet and colleagues. (JAX Stock Number: 004660)
- - PWK/PhJ: A wild-derived Mus musculus musculus inbred strain from samples caught near Lhotka, Czech Republic. Collaborative Cross strain; Phenome Project D list. (JAX Stock Number: 003715)
- - SJL/J: Swiss Webster inbred strain from Jim Lambert's lab at the Jackson Laboratory. This strain has the retinal degeneration rd1 allele in Pde6b. It also carries both the Tyr c albino mutation and the pink-eye dilution mutation in the Oca2 or p locus. Highly aggressive males. (JAX Stock Number: 000686)
- - WSB/EiJ: Watkin Star line B (or "wild son-of-a-bitch") is a wild-derived Mus musculus domesticus inbred strain from samples caught in Maryland, USA. A Collaborative Cross strain sequenced by NIEHS; Phenome Project C list (JAX Stock Number: 001145)
- - B6D2F1 and D2B6F1 (also listed as BDF1 and DBF1 in some graphs and tables): F1 hybrids generated by crossing C57BL/6J with DBA/2J. These black reciprocal F1 can be used to detect dominance effects. Comparison of the two reciprocal F1s can be used to detect parental origin (imprinting) effects. The D2B6F1 animals are currently available from the Jackson Laboratory as a special order.) (JAX Stock Number for B6D2F1 hybrids obtained from the Jackson Laboratory, aka B6D2F1/J 100006)
-
-
-Most of the common inbred strains harbor mutations in genes the control pigmentation (Silvers, 2008 and material above in this INFO file). These gene include the albino and chinchilla alleles of the tyrosinase gene (Tyr, or human OCA1), the brown allele of the tyrosinase related protein 1 (Tyrp1), the pink-eye dilution allele of Oca2 (probe set 1418211), the non-agouti (black) and white-bellied alleles of the agouti signaling protein Asip, the steel allele of Kitlg, the dilute allele of Myo5a (probe set 1419754), and the piebald allele of Ednrb. In some of these cases, effects of the mutation are easily detected at the transcript level (Tyrp1, Oca2, and Myo5a), but in the other cases (Tyr, Asip, Ednrb, and Kitlg), mutations do not leave a strong imprint on expression.
diff --git a/general/datasets/gn10/experiment-design.rtf b/general/datasets/gn10/experiment-design.rtf
deleted file mode 100644
index 1ebe0ad..0000000
--- a/general/datasets/gn10/experiment-design.rtf
+++ /dev/null
@@ -1 +0,0 @@
-Expression profiling by array
diff --git a/general/datasets/gn10/notes.rtf b/general/datasets/gn10/notes.rtf
deleted file mode 100644
index 7a26eb5..0000000
--- a/general/datasets/gn10/notes.rtf
+++ /dev/null
@@ -1 +0,0 @@
-This data set is available as a bulk download in several formats. The data are available as either strain means or the individual arrays. Due to the involved normalization procedures required to correct for batch effects we strongly recommend not using the raw CEL files without special statistical procedures.
diff --git a/general/datasets/gn10/platform.rtf b/general/datasets/gn10/platform.rtf
deleted file mode 100644
index 9024a99..0000000
--- a/general/datasets/gn10/platform.rtf
+++ /dev/null
@@ -1,11 +0,0 @@
-Affymetrix Mouse Genome 430 2.0 arrays: The 430 2.0 array consists of 992936 25-nucleotide probes that estimate the expression of approximately 39,000 transcripts (many probes overlap and target the same transcript). The array sequences were selected late in 2002 using Unigene Build 107. The array nominally contains the same probe sequences as the old M430A and 430B array pair. However, we have found that roughy 75000 probes differ between those on A and B arrays and those on the new 430 2.0.
-
-As part of the development of HEIMED, we have manually annotated individual probe sets by sequence alignment to the mouse genome and transcriptome. Approximately 13,000 probe sets that have comparatively high expression in eye and CNS were curated by one of the authors (RWW) and now have specific information on the part of the transcript targeted by each probe set. The other 33,000 transcripts have corresponding data that was generated by Xusheng Wang using computational methods (BLAT analysis combined with annotated genome sequence).
-
-One example may help explain how to exploit this annotation. The four probe sets for rhodopsin include information on the target location. Only the first probe set targets the last two coding exons. The other three probe sets target different parts of the 3’ UTR (mid, distal, and far distal regions). The probe sets can be reordered by from high to low expression using the Sort By function in Search Results pages. In the case of rhodopsin, the probe set that targets that last two coding exons and proximal parts of the 3’ UTR also has the highest expression . Finally, the HEIMED gene descriptions have been customized to help vision researchers. In the case of rhodopsin, the description appended after the gene name reads “rod photoreceptor pigment, retinitis pigmentosa-associated”. For less well known genes this kind of annotation can be extremely useful. For example, the more verbose annotation for Cerkl reads “neuronal survival and apoptosis-related, retinal ganglion cell expressed, retinitis pigmentosa 26); alternative 3' UTR of short form message, intron 2”.
-
-
-
-
-
-Legend: Distribution of expression values for all probe sets in HEIMED.
diff --git a/general/datasets/gn10/processing.rtf b/general/datasets/gn10/processing.rtf
deleted file mode 100644
index 4349e60..0000000
--- a/general/datasets/gn10/processing.rtf
+++ /dev/null
@@ -1,3381 +0,0 @@
-Range of Gene Expression in the Eye. Expression of transcripts in the HEIMED and most other GN data sets is measured on a log2 scale. Each unit corresponding approximately to a 2-fold difference in hybridization signal intensity. To simplify comparisons among different data sets and cases, log2 RMA values of each array have been adjusted to an average expression of 8 units and a standard deviation of 2 units (variance stabilized). Values of all 45,101 probe sets in this data set range from a low of 4.8 (Tcf15, probe set 1420281_at) to a high of 15.5 (crystallin gamma C, Crygc, probe set 1422674_s_at). This corresponds to 10.7 units or a 1 to 1700 dynamic range of expression (2^10.73).
-
-We used pooled RNA samples of whole eyes, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
-
-We calibrated this log intensity scale using Affymetrix spike-in control probe sets. These 18 control probe sets target exogenous bacterial mRNAs that are added to each sample (a graded dose spike cocktail) during preparation at concentrations of 1.5, 5, 25, and 100 pM. (To find these probe sets, search GN’s ALL search field using the string “AFFX pM”.) A value of 6 or less is equivalent to an mRNA concentration of under 0.4 pM, a value of 8 is equivalent to ~1.5 pM, 9.5 is equivalent to ~5 pM, 11.5 is equivalent to ~25 pM, 13.5 is equivalent to ~100 pM, and a value of 15.5 is equivalent to an mRNA concentration of 400 pM or greater.
-
-This range can be converted to the mRNA molecules per cell in the eye assuming that a value of 8 is equivalent to about 1 mRNA copy per cell (Kanno et al. 2006, see http://www.biomedcentral.com/1471-2164/7/64). Since the expression of rhodopsin mRNA is normally 15 units, we predict that there are 27 or ~128 Rho mRNAs per cell in the whole eye and ~256 in rods themselves (assuming that rods make up about half of all cells in the eye). For this purpose it may be useful to know that a normal mouse eye contains between 6 and 8 million rod photoreceptors (Guo, Lu, and Williams; GN BXD Phenotype ID 11024).
-
-Note that some probe sets with very low expression still provide reliable data. For example, probe set 1440397_at (Cacna2d1) has expression of only 5.5 units (a value that would be declared as "absent" using conventional Affymetrix procedures), but the values for this calcium channel transcript are associated with a very strong cis QTL with an LRS of 79 (LOD = 17). This strong linkage is definitely not due to chance since the probability of the expression data mapping precisely to the location of the parent gene itself is about 10e-16. This indicates a high signal to noise ratio and the detection of significant strain variation of the correct transcript.
-
-The standard error of the mean for the HEIMED data set is computed for 2 to 6 biological replicates. The standard error of such small samples tends to systematically underestimate the population standard error. With n = 2 the underestimate is about 25%, whereas for n = 6 the underestimate is 5%. Gurland and Tripathi (1971) provide a correction and equation for this effect (see Sokal and Rohlf, Biometry, 2nd ed., 1981, p 53 for an equation of the correction factor for small samples of n < 20.) Probe (cell) level data from the CEL file: These CEL values produced by GCOS are 75% quantiles from a set of 91 pixel values per cell. The CEL files were processed using the RMA protocol. We processed the first three batches together. The last batch was processed separately and merged as described below.
-
-
- - Step 1: We added an offset of 1.0 unit to each cell signal to ensure that all values could be logged without generating negative values. We then computed the log base 2 of each cell.
- - Step 2: We performed a quantile normalization of the log base 2 values for the total set of arrays using the same initial steps used by the RMA transform.
- - Step 3: We computed the Z scores for each cell value.
- - Step 4: We multiplied all Z scores by 2.
- - Step 5: We added 8 to the value of all Z scores. The consequence of this simple set of transformations is to produce a set of Z scores that have a mean of 8, a variance of 4, and a standard deviation of 2. The advantage of this modified Z score is that a two-fold difference in expression level corresponds approximately to a 1 unit difference.
- - Step 6: Finally, when appropriate, we computed the arithmetic mean of the values for the set of microarrays for each strain. Technical replicates were averaged before computing the mean for independent biological samples.
-
-
-After RMA processing using Biobase affy10 build running under R version 2.7.1, all array data sets were rank-order normalized. This second round of quantile normalization removes much residual non-linearity across arrays and forces every array to have the same distribution of values as the mean of all arrays. Comparative array data quality was then evaluated in DataDesk. Outlier arrays were flagged by visual inspection in DataDesk, usually by means of an analysis of scatter plots and more quantitatively by generating a correlation matrix of all arrays. Those arrays with mean correlation <0.96 versus all other arrays indicates trouble or a biological outlier). In some cases, outliers were expected, such as samples from strains with retinal degeneration (FVB/NJ, NOD/LtJ, MOLF/EiJ, C3H/HeJ and BXD24), samples from wild subspecies such as WSB/EiJ, CAST/EiJ, PWD/PhJ, and PWK/PhJ, and knockouts. However, when arrays were anomolous both within strain and across strains, they were often simply discarded. The assumption is that anomolous data are much more likely due to experimental and technical errors than to informative biological variation. Approximately 10% of arrays were discarded.
-
-After this process, the acceptable set of arrays was renormalized using all step as above, starting with the original RMA procedure, etc.
-
-We reviewed the data set using a new method developed by RW Williams, Jeremy Peirce, and Hongqiang Li. For the full set of arrays that passed standard QC protocols described above, we computed the strain means for the BXD strains, B6, D2, and F1s. Using this set of strain means we then computed LRS scores for all 45101 probe sets and counted the number of transcripts that generated QTLs with LRS values greater than 50. This value (e.g., 1800) represented the QTL harvest for the full data set. We then dropped a single array from the data set, recomputed strain means, and recomputed the number of transcripts with LRS scores great than 50. This value is expected to typically reduce the number of QTLs that reach the criterion level (e.g., 1750 QTLs > 50). This process was repeated for every array to obtain an array-specific difference value--the effect of removing that array on the total QTL count. For example, the loss of a single array might cause a decrease in 50 QTLs. Values ranged from approximately -90 (good arrays) to +40 (bad arrays). This procedure is similar in some ways to a jackknife protocol, although we are not using this procedure to esimate an error term, but rather as a method to polish a data set.
-
-During this process we discovered that nearly 20 arrays in the batch 2 had been mislabeled at some point in processing. We computed the correct strain membership of each array using a large number of Mendelian probe sets (more than 50) and comparing their match to standard SNP and microsatellite markers and the original array data set of November 2005. This allowed us to rescue a large number of arrays that were of high quality.
-
-A third batch of approximately 40 arrays were processed by Yan Jiao and Weikuan Gu in August 2006. These complete data set assembled by Hongqiang Li. This process again included a correction for a batch effect.
-
-For the June 2006 data set Hongqiang Li used a new batch correction method that stabilizes the range of expression in each batch. For each of the three large batches, we extracted the minumum and maximum raw probe expression (CEL file level) value. We then adjusted raw probe values in each batch to have the same range as the first and largest batch (batch 1) using a simple linear interpolation. These procedures generated new correct CEL files which were then used with RMA to generate final probe set estimates.
-
-For the final fourth batch of arrays (Sept 2008) Arthur Centeno and Rob Williams corrected for a systematic difference in probe set expression values between original arrays run in 2005 and 2006 and the new arrays added in 2008 (n = 45 acceptable arrays). This difference is due to unknown technical batch effects that are probably associated with labeling, hybridization, and scanning. We performed a simple correction to normalize values of the new set of arrays to those of the old set (batches 1 through 3). No changes were made to any values of the previous three batches. We corrected only the probe set level (RMA) values and not the CEL files. For this final batch, we corrected for the difference (offset) in probe set expression between the first three batches arrays run in 2005 and 2006 (a total of 174 acceptable arrays) and the new batch (n = 47 acceptable arrays). This difference is due to unknown technical effects that are probably related to various steps in labeling, hybridization, and scanning. The correction was applied as follows: (1) RWW selected 51 high quality arrays with similar expression characteristics (r = 0.97 or better between pairs of arrays) in the old data set (from batches 1, 2, and 3) and 34 high quality arrays in the final batch. RWW used scatterplots of full RMA transcriptome data sets to review many pairs of arrays within these new and old array batches. Strains with retinal degeneration or unusual eye gene expression characteristics were excluded from these selected subsets. The average expression values for each probe set were then computed for both the old and new array subsets. The offset value (old minus new) was added to each probe set across all 47 new arrays. This processes forces the average probe set in the new arrays to be very close to that of the previous arrays.
-
-Table 2: Sample tube ID, strain, original CEL filename, and Affymetrix quality control values. Columns labeled Scale factor, Background Average, Present, Absent, Marginal and 3'/5' ratios for actin and Gapdh were collated from the Affymetrix Report (RPT) files.
-
-
-
-
-
-
-
-
-
-
- | Index |
- TubeID |
- Strain |
- Original CEL |
- Scale factor |
- Background Average |
- Present |
- Absent |
- Marginal |
- AFFX-b-ActinMur (3'/5') |
- AFFX-GapdhMur (3'/5') |
- Batch Id |
- Used for batch control |
-
-
- | 1 |
- R2595E.1 |
- 129S1/SvImJ |
- R2595E.1.CEL |
- 1.79 |
- 115 |
- 61.00% |
- 37.50% |
- 1.50% |
- 1.46 |
- 0.77 |
- 1 |
- Y |
-
-
- | 2 |
- R2533E.1 |
- 129S1/SvImJ |
- R2533E.1.CEL |
- 2.11 |
- 94 |
- 57.90% |
- 40.50% |
- 1.60% |
- 1.37 |
- 0.78 |
- 1 |
- Y |
-
-
- | 3 |
- R0754E.1 |
- A/J |
- R0754E.1.CEL |
- 2.72 |
- 86 |
- 59.80% |
- 38.70% |
- 1.50% |
- 1.36 |
- 0.76 |
- 1 |
- Y |
-
-
- | 4 |
- R4521E |
- B6129P2F2N1-Clcn3 |
- R4521E.CEL |
- 4.83 |
- 38.7 |
- 63.30% |
- 35.30% |
- 1.40% |
- 1.25 |
- 0.77 |
- 4 |
- |
-
-
- | 5 |
- R4522E |
- B6129P2F2N1-Clcn3 |
- R4522E.CEL |
- 5.76 |
- 37.36 |
- 62.90% |
- 35.70% |
- 1.40% |
- 1.37 |
- 0.83 |
- 4 |
- |
-
-
- | 6 |
- R4523E |
- B6129P2F2N1-Clcn3 |
- R4523E.CEL |
- 4.88 |
- 40.42 |
- 63.90% |
- 34.70% |
- 1.40% |
- 1.27 |
- 0.77 |
- 4 |
- |
-
-
- | 7 |
- R4526E |
- B6129P2F2N1-Gabbr1 |
- R4526E.CEL |
- 3.84 |
- 44.18 |
- 65.00% |
- 33.70% |
- 1.30% |
- 1.34 |
- 0.78 |
- 4 |
- Y |
-
-
- | 8 |
- R4509E |
- B6129P2F2N1-Gabbr1 |
- R4509E.CEL |
- 7.45 |
- 34.76 |
- 58.90% |
- 39.70% |
- 1.40% |
- 1.45 |
- 0.83 |
- 4 |
- |
-
-
- | 9 |
- R4510E |
- B6129P2F2N1-Gabbr1 |
- R4510E.CEL |
- 8.44 |
- 37.44 |
- 57.40% |
- 41.10% |
- 1.50% |
- 1.35 |
- 0.83 |
- 4 |
- |
-
-
- | 10 |
- R4511E |
- B6129P2F2N1-Gabbr1 |
- R4511E.CEL |
- 5.91 |
- 42.02 |
- 61.40% |
- 37.20% |
- 1.40% |
- 1.41 |
- 0.83 |
- 4 |
- |
-
-
- | 11 |
- R4524E |
- B6129P2F2N1-Gabbr1 |
- R4524E.CEL |
- 5.49 |
- 42.34 |
- 62.40% |
- 36.20% |
- 1.40% |
- 1.29 |
- 0.78 |
- 4 |
- Y |
-
-
- | 12 |
- R4525E |
- B6129P2F2N1-Gabbr1 |
- R4525E.CEL |
- 4.69 |
- 41.3 |
- 63.10% |
- 35.50% |
- 1.40% |
- 1.27 |
- 0.8 |
- 4 |
- Y |
-
-
- | 13 |
- R4515E |
- B6129P2F2N1-Gabra1 |
- R4515E.CEL |
- 5.75 |
- 41.76 |
- 62.80% |
- 35.80% |
- 1.40% |
- 1.41 |
- 0.81 |
- 4 |
- Y |
-
-
- | 14 |
- R4516E |
- B6129P2F2N1-Gabra1 |
- R4516E.CEL |
- 7.07 |
- 40.73 |
- 60.20% |
- 38.40% |
- 1.40% |
- 1.32 |
- 0.87 |
- 4 |
- Y |
-
-
- | 15 |
- R4517E |
- B6129P2F2N1-Gabra1 |
- R4517E.CEL |
- 5.45 |
- 38.09 |
- 62.70% |
- 35.80% |
- 1.40% |
- 1.34 |
- 0.82 |
- 4 |
- Y |
-
-
- | 16 |
- R4512E |
- B6129P2F2N1-Gnb5 |
- R4512E.CEL |
- 6.56 |
- 38.02 |
- 59.90% |
- 38.70% |
- 1.50% |
- 1.33 |
- 0.83 |
- 4 |
- |
-
-
- | 17 |
- R4513E |
- B6129P2F2N1-Gnb5 |
- R4513E.CEL |
- 4.15 |
- 41.6 |
- 63.40% |
- 35.10% |
- 1.50% |
- 1.34 |
- 0.82 |
- 4 |
- |
-
-
- | 18 |
- R4514E |
- B6129P2F2N1-Gnb5 |
- R4514E.CEL |
- 5.86 |
- 39.2 |
- 61.20% |
- 37.30% |
- 1.50% |
- 1.34 |
- 0.81 |
- 4 |
- |
-
-
- | 19 |
- R4518E |
- B6129P2F2N1-Gpr19 |
- R4518E.CEL |
- 5.58 |
- 38.9 |
- 62.60% |
- 36.00% |
- 1.30% |
- 1.39 |
- 0.79 |
- 4 |
- Y |
-
-
- | 20 |
- R4519E |
- B6129P2F2N1-Gpr19 |
- R4519E.CEL |
- 5.95 |
- 41.91 |
- 61.30% |
- 37.30% |
- 1.40% |
- 1.35 |
- 0.84 |
- 4 |
- Y |
-
-
- | 21 |
- R2601E.1 |
- B6D2F1 |
- R2601E.1.CEL |
- 2.55 |
- 92 |
- 58.90% |
- 39.60% |
- 1.50% |
- 1.44 |
- 0.78 |
- 1 |
- Y |
-
-
- | 22 |
- R2602E.1 |
- B6D2F1 |
- R2602E.1.CEL |
- 2.6 |
- 84 |
- 59.70% |
- 38.80% |
- 1.50% |
- 1.37 |
- 0.78 |
- 1 |
- Y |
-
-
- | 23 |
- R1676E.1 |
- BALB/cByJ |
- R1676E.1.CEL |
- 2.69 |
- 98 |
- 58.90% |
- 39.60% |
- 1.50% |
- 1.46 |
- 0.74 |
- 1 |
- |
-
-
- | 24 |
- R1672E.1 |
- BALB/cByJ |
- R1672E.1.CEL |
- 2.22 |
- 111 |
- 59.90% |
- 38.60% |
- 1.50% |
- 1.26 |
- 0.8 |
- 1 |
- Y |
-
-
- | 25 |
- R4530E |
- BALB/cJ |
- R4530E.CEL |
- 6.37 |
- 37.53 |
- 60.80% |
- 37.80% |
- 1.40% |
- 1.3 |
- 0.84 |
- 4 |
- Y |
-
-
- | 26 |
- R4529E |
- BALB/cJ |
- R4529E.CEL |
- 5.71 |
- 41.33 |
- 60.50% |
- 38.00% |
- 1.50% |
- 1.48 |
- 0.8 |
- 4 |
- Y |
-
-
- | 27 |
- R2704E.2 |
- BXD1 |
- R2704E.2.CEL |
- 2.066 |
- 139.61 |
- 56.60% |
- 41.90% |
- 1.50% |
- 1.31 |
- 0.81 |
- 2 |
- |
-
-
- | 28 |
- R2707E.3 |
- BXD1 |
- R2707E.3.CEL |
- 1 |
- 80 |
- 56.40% |
- 42.10% |
- 1.50% |
- 1.43 |
- 0.79 |
- 3 |
- |
-
-
- | 29 |
- R1231E.2 |
- BXD2 |
- R1231E.2.CEL |
- 2.197 |
- 138.73 |
- 57.30% |
- 41.30% |
- 1.40% |
- 1.41 |
- 0.77 |
- 2 |
- |
-
-
- | 30 |
- R2598E.1 |
- BXD2 |
- R2598E.1.CEL |
- 1.99 |
- 106 |
- 60.90% |
- 37.60% |
- 1.50% |
- 1.27 |
- 0.78 |
- 1 |
- Y |
-
-
- | 31 |
- R2591E.1 |
- BXD5 |
- R2591E.1.CEL |
- 1.7 |
- 136 |
- 58.50% |
- 40.00% |
- 1.50% |
- 1.33 |
- 0.78 |
- 1 |
- Y |
-
-
- | 32 |
- R2714E.2 |
- BXD5 |
- R2714E.2.CEL |
- 1.404 |
- 144.35 |
- 60.60% |
- 37.90% |
- 1.50% |
- 1.43 |
- 0.79 |
- 2 |
- |
-
-
- | 33 |
- R2570E.1 |
- BXD6 |
- R2570E.1.CEL |
- 1.99 |
- 87 |
- 58.50% |
- 40.00% |
- 1.50% |
- 1.46 |
- 0.76 |
- 1 |
- Y |
-
-
- | 34 |
- R2694E.2 |
- BXD6 |
- R2694E.2.CEL |
- 1.983 |
- 97.23 |
- 61.60% |
- 37.10% |
- 1.30% |
- 1.39 |
- 0.82 |
- 2 |
- |
-
-
- | 35 |
- R2538E.1 |
- BXD8 |
- R2538E.1.CEL |
- 1.91 |
- 102 |
- 61.20% |
- 37.30% |
- 1.50% |
- 1.52 |
- 0.79 |
- 1 |
- Y |
-
-
- | 36 |
- R2709E.2 |
- BXD8 |
- R2709E.2.CEL |
- 1.99 |
- 99.79 |
- 60.90% |
- 37.60% |
- 1.50% |
- 1.42 |
- 0.76 |
- 2 |
- |
-
-
- | 37 |
- R2708E.2 |
- BXD9 |
- R2708E.2.CEL |
- 1.966 |
- 126.46 |
- 57.70% |
- 40.70% |
- 1.50% |
- 1.4 |
- 0.84 |
- 2 |
- |
-
-
- | 38 |
- R2569E.1 |
- BXD9 |
- R2569E.1.CEL |
- 1.75 |
- 87 |
- 55.10% |
- 43.40% |
- 1.50% |
- 2.82 |
- 3.14 |
- 1 |
- |
-
-
- | 39 |
- R2581E.1 |
- BXD11 |
- R2581E.1.CEL |
- 1.94 |
- 89 |
- 62.10% |
- 36.40% |
- 1.60% |
- 1.55 |
- 0.81 |
- 1 |
- Y |
-
-
- | 40 |
- R2612E.2 |
- BXD11 |
- R2612E.2.CEL |
- 1.83 |
- 142.03 |
- 58.20% |
- 40.50% |
- 1.40% |
- 1.78 |
- 0.81 |
- 2 |
- |
-
-
- | 41 |
- R2742E.2 |
- BXD12 |
- R2742E.2.CEL |
- 2.127 |
- 134.14 |
- 57.00% |
- 41.60% |
- 1.40% |
- 1.64 |
- 0.78 |
- 2 |
- |
-
-
- | 42 |
- R2543E.1 |
- BXD12 |
- R2543E.1.CEL |
- 1.61 |
- 118 |
- 58.60% |
- 39.90% |
- 1.60% |
- 1.43 |
- 0.77 |
- 1 |
- Y |
-
-
- | 43 |
- R2586E.1 |
- BXD13 |
- R2586E.1.CEL |
- 2.01 |
- 74 |
- 56.40% |
- 42.00% |
- 1.60% |
- 2.85 |
- 3.81 |
- 1 |
- |
-
-
- | 44 |
- R877E.2 |
- BXD13 |
- R877E.2.CEL |
- 1.558 |
- 125.63 |
- 61.20% |
- 37.50% |
- 1.20% |
- 1.42 |
- 0.81 |
- 2 |
- |
-
-
- | 45 |
- R2557E.1 |
- BXD14 |
- R2557E.1.CEL |
- 1.83 |
- 99 |
- 62.50% |
- 36.10% |
- 1.40% |
- 1.31 |
- 0.78 |
- 1 |
- Y |
-
-
- | 46 |
- R1128E.2 |
- BXD14 |
- R1128E.2.CEL |
- 1.91 |
- 115 |
- 59.90% |
- 38.80% |
- 1.40% |
- 1.2 |
- 0.82 |
- 1 |
- Y |
-
-
- | 47 |
- R2701E.3 |
- BXD15 |
- R2701E.3.CEL |
- 1 |
- 88 |
- 60.60% |
- 37.90% |
- 1.40% |
- 1.5 |
- 0.77 |
- 3 |
- |
-
-
- | 48 |
- R2716E.2 |
- BXD15 |
- R2716E.2.CEL |
- 2.015 |
- 150.83 |
- 56.40% |
- 42.10% |
- 1.60% |
- 1.42 |
- 0.81 |
- 2 |
- |
-
-
- | 49 |
- R2711E.2 |
- BXD16 |
- R2711E.2.CEL |
- 1.953 |
- 118.53 |
- 59.00% |
- 39.60% |
- 1.50% |
- 1.45 |
- 0.8 |
- 2 |
- |
-
-
- | 50 |
- R2567E.1 |
- BXD16 |
- R2567E.1.CEL |
- 2.24 |
- 82 |
- 56.70% |
- 41.60% |
- 1.70% |
- 1.37 |
- 0.75 |
- 1 |
- |
-
-
- | 51 |
- R2720E.2 |
- BXD18 |
- R2720E.2.CEL |
- 2.32 |
- 99.93 |
- 59.50% |
- 39.00% |
- 1.50% |
- 1.33 |
- 0.77 |
- 2 |
- |
-
-
- | 52 |
- R2559E.1 |
- BXD18 |
- R2559E.1.CEL |
- 1.65 |
- 104 |
- 60.80% |
- 37.70% |
- 1.50% |
- 1.27 |
- 0.78 |
- 1 |
- Y |
-
-
- | 53 |
- R2560E.1 |
- BXD19 |
- R2560E.1.CEL |
- 1.79 |
- 98 |
- 60.90% |
- 37.50% |
- 1.60% |
- 1.35 |
- 0.8 |
- 1 |
- Y |
-
-
- | 54 |
- R2713E.2 |
- BXD19 |
- R2713E.2.CEL |
- 1.67 |
- 120.82 |
- 60.20% |
- 38.30% |
- 1.50% |
- 1.45 |
- 0.8 |
- 2 |
- |
-
-
- | 55 |
- R2584E.1 |
- BXD20 |
- R2584E.1.CEL |
- 2.07 |
- 84 |
- 59.30% |
- 39.10% |
- 1.60% |
- 1.4 |
- 0.76 |
- 1 |
- Y |
-
-
- | 56 |
- R2731E.2 |
- BXD20 |
- R2731E.2.CEL |
- 1.825 |
- 147 |
- 59.00% |
- 39.50% |
- 1.50% |
- 1.4 |
- 0.8 |
- 2 |
- |
-
-
- | 57 |
- R2702E.2 |
- BXD21 |
- R2702E.2.CEL |
- 1.811 |
- 128.65 |
- 59.40% |
- 39.10% |
- 1.40% |
- 1.26 |
- 0.8 |
- 2 |
- |
-
-
- | 58 |
- R2541E2.1 |
- BXD21 |
- R2541E2.1.CEL |
- 2.63 |
- 125 |
- 56.00% |
- 42.40% |
- 1.50% |
- 1.29 |
- 0.78 |
- 1 |
- |
-
-
- | 59 |
- R2553E.1 |
- BXD22 |
- R2553E.1.CEL |
- 1.95 |
- 111 |
- 59.90% |
- 38.50% |
- 1.50% |
- 1.28 |
- 0.76 |
- 1 |
- Y |
-
-
- | 60 |
- R2700E.2 |
- BXD22 |
- R2700E.2.CEL |
- 1.858 |
- 102.96 |
- 61.50% |
- 37.10% |
- 1.30% |
- 1.48 |
- 0.79 |
- 2 |
- |
-
-
- | 61 |
- R2558E-2.1 |
- BXD23 |
- R2558E-2.1.CEL |
- 2.233 |
- 125.05 |
- 58.60% |
- 39.90% |
- 1.50% |
- 1.43 |
- 0.77 |
- 2 |
- |
-
-
- | 62 |
- R1086E.2 |
- BXD23 |
- R1086E.2.CEL |
- 2.233 |
- 125.05 |
- 58.60% |
- 39.90% |
- 1.50% |
- 1.43 |
- 0.77 |
- 2 |
- |
-
-
- | 63 |
- R2719E.2 |
- BXD24 |
- R2719E.2.CEL |
- 1.47 |
- 140.38 |
- 61.50% |
- 37.20% |
- 1.30% |
- 1.38 |
- 0.79 |
- 2 |
- |
-
-
- | 64 |
- R2589E2.1 |
- BXD24 |
- R2589E2.1.CEL |
- 2.61 |
- 112 |
- 57.50% |
- 40.90% |
- 1.60% |
- 1.24 |
- 0.8 |
- 1 |
- |
-
-
- | 65 |
- R2573E-2.1 |
- BXD25 |
- R2573E-2.1.CEL |
- 3.15 |
- 72 |
- 57.90% |
- 40.70% |
- 1.40% |
- 1.77 |
- 0.97 |
- 1 |
- |
-
-
- | 66 |
- R2683E.2 |
- BXD25 |
- R2683E.2.CEL |
- 1.777 |
- 115.64 |
- 58.30% |
- 40.30% |
- 1.40% |
- 2.01 |
- 0.79 |
- 2 |
- |
-
-
- | 67 |
- R2703E.2 |
- BXD27 |
- R2703E.2.CEL |
- 1.263 |
- 134.78 |
- 62.60% |
- 36.10% |
- 1.40% |
- 1.44 |
- 0.78 |
- 2 |
- |
-
-
- | 68 |
- R2729E.3 |
- BXD27 |
- R2729E.3.CEL |
- 1 |
- 87 |
- 57.90% |
- 40.60% |
- 1.50% |
- 1.56 |
- 0.84 |
- 3 |
- Y |
-
-
- | 69 |
- R2562E.3 |
- BXD28 |
- R2562E.3.CEL |
- 1.65 |
- 116 |
- 59.90% |
- 38.40% |
- 1.70% |
- 1.37 |
- 0.79 |
- 3 |
- Y |
-
-
- | 70 |
- R2721E.2 |
- BXD28 |
- R2721E.2.CEL |
- 2.065 |
- 157.39 |
- 56.10% |
- 42.40% |
- 1.50% |
- 1.31 |
- 0.81 |
- 2 |
- |
-
-
- | 71 |
- R2561E.3 |
- BXD29 |
- R2561E.3.CEL |
- 1 |
- 77 |
- 53.30% |
- 45.40% |
- 1.40% |
- 3.36 |
- 19.66 |
- 3 |
- |
-
-
- | 72 |
- R1258E.2 |
- BXD31 |
- R1258E.2.CEL |
- 2.063 |
- 117.09 |
- 59.00% |
- 39.50% |
- 1.50% |
- 1.54 |
- 0.78 |
- 2 |
- |
-
-
- | 73 |
- R2597E.1 |
- BXD31 |
- R2597E.1.CEL |
- 2.37 |
- 94 |
- 60.30% |
- 38.30% |
- 1.50% |
- 1.34 |
- 0.77 |
- 1 |
- Y |
-
-
- | 74 |
- R2563E.1 |
- BXD32 |
- R2563E.1.CEL |
- 1.55 |
- 102 |
- 61.90% |
- 36.70% |
- 1.40% |
- 1.5 |
- 0.8 |
- 1 |
- |
-
-
- | 75 |
- R1216E.2 |
- BXD32 |
- R1216E.2.CEL |
- 2.23 |
- 111.99 |
- 58.80% |
- 39.80% |
- 1.40% |
- 1.35 |
- 0.79 |
- 2 |
- |
-
-
- | 76 |
- R2542E.1 |
- BXD33 |
- R2542E.1.CEL |
- 2.13 |
- 97 |
- 56.50% |
- 41.80% |
- 1.60% |
- 1.91 |
- 0.93 |
- 1 |
- |
-
-
- | 77 |
- R857E.2 |
- BXD33 |
- R857E.2.CEL |
- 1.737 |
- 113.98 |
- 61.90% |
- 36.70% |
- 1.30% |
- 1.6 |
- 0.77 |
- 2 |
- |
-
-
- | 78 |
- R1451E.2 |
- BXD34 |
- R1451E.2.CEL |
- 1.843 |
- 140.05 |
- 59.00% |
- 39.50% |
- 1.50% |
- 1.42 |
- 0.81 |
- 2 |
- Y |
-
-
- | 79 |
- R2585E.1 |
- BXD34 |
- R2585E.1.CEL |
- 2.64 |
- 75 |
- 58.30% |
- 40.00% |
- 1.70% |
- 1.25 |
- 0.77 |
- 1 |
- |
-
-
- | 80 |
- R2698E.3 |
- BXD36 |
- R2698E.3.CEL |
- 1 |
- 86 |
- 59.70% |
- 39.00% |
- 1.30% |
- 1.46 |
- 0.78 |
- 3 |
- |
-
-
- | 81 |
- R2705E.3 |
- BXD36 |
- R2705E.3.CEL |
- 1 |
- 86 |
- 60.20% |
- 38.40% |
- 1.40% |
- 1.46 |
- 0.77 |
- 3 |
- |
-
-
- | 82 |
- R2710E.2 |
- BXD38 |
- R2710E.2.CEL |
- 2.112 |
- 122.1 |
- 58.80% |
- 39.80% |
- 1.40% |
- 1.37 |
- 0.78 |
- 2 |
- |
-
-
- | 83 |
- R2532E.1 |
- BXD38 |
- R2532E.1.CEL |
- 2.04 |
- 94 |
- 59.80% |
- 38.70% |
- 1.50% |
- 1.37 |
- 0.8 |
- 1 |
- Y |
-
-
- | 84 |
- R2574E.1 |
- BXD39 |
- R2574E.1.CEL |
- 1.98 |
- 91 |
- 61.20% |
- 37.30% |
- 1.50% |
- 1.39 |
- 0.78 |
- 1 |
- |
-
-
- | 85 |
- R2695E.2 |
- BXD39 |
- R2695E.2.CEL |
- 1.638 |
- 122.7 |
- 60.80% |
- 37.80% |
- 1.50% |
- 1.42 |
- 0.8 |
- 2 |
- |
-
-
- | 86 |
- R2699E.2 |
- BXD40 |
- R2699E.2.CEL |
- 1.827 |
- 105.23 |
- 61.70% |
- 36.90% |
- 1.40% |
- 1.42 |
- 0.81 |
- 2 |
- |
-
-
- | 87 |
- R2590E.1 |
- BXD40 |
- R2590E.1.CEL |
- 2.71 |
- 77 |
- 59.10% |
- 39.30% |
- 1.50% |
- 1.4 |
- 0.77 |
- 1 |
- Y |
-
-
- | 88 |
- R2696E.2 |
- BXD42 |
- R2696E.2.CEL |
- 1.622 |
- 118.95 |
- 62.00% |
- 36.60% |
- 1.50% |
- 1.53 |
- 0.79 |
- 2 |
- |
-
-
- | 89 |
- R2596E.1 |
- BXD42 |
- R2596E.1.CEL |
- 2.63 |
- 108 |
- 59.00% |
- 39.60% |
- 1.50% |
- 1.24 |
- 0.8 |
- 1 |
- |
-
-
- | 90 |
- R994E.2 |
- BXD43 |
- R994E.2.CEL |
- 1.966 |
- 113.12 |
- 60.80% |
- 37.80% |
- 1.40% |
- 1.66 |
- 0.8 |
- 2 |
- |
-
-
- | 91 |
- R2607E.1 |
- BXD43 |
- R2607E.1.CEL |
- 2.43 |
- 115 |
- 58.60% |
- 40.00% |
- 1.40% |
- 1.31 |
- 0.76 |
- 1 |
- Y |
-
-
- | 92 |
- R2594E.1 |
- BXD44 |
- R2594E.1.CEL |
- 1.77 |
- 117 |
- 59.80% |
- 38.80% |
- 1.40% |
- 1.35 |
- 0.85 |
- 1 |
- |
-
-
- | 93 |
- R2610E.2 |
- BXD44 |
- R2610E.2.CEL |
- 1.814 |
- 142.91 |
- 59.00% |
- 39.50% |
- 1.50% |
- 1.35 |
- 0.8 |
- 2 |
- |
-
-
- | 94 |
- R2732E.2 |
- BXD45 |
- R2732E.2.CEL |
- 2.154 |
- 122.45 |
- 56.50% |
- 42.10% |
- 1.40% |
- 1.8 |
- 0.83 |
- 2 |
- |
-
-
- | 95 |
- R2592E.1 |
- BXD45 |
- R2592E.1.CEL |
- 1.85 |
- 106 |
- 60.10% |
- 38.60% |
- 1.30% |
- 1.43 |
- 0.85 |
- 1 |
- Y |
-
-
- | 96 |
- R967E.2 |
- BXD48 |
- R967E.2.CEL |
- 1.948 |
- 130.95 |
- 57.30% |
- 41.20% |
- 1.50% |
- 1.63 |
- 0.81 |
- 2 |
- |
-
-
- | 97 |
- R2606E.1 |
- BXD48 |
- R2606E.1.CEL |
- 2.56 |
- 106 |
- 58.90% |
- 39.70% |
- 1.40% |
- 1.35 |
- 0.83 |
- 1 |
- Y |
-
-
- | 98 |
- R2933E.3 |
- BXD50 |
- R2933E.3.CEL |
- 1 |
- 72 |
- 52.90% |
- 45.60% |
- 1.50% |
- 2.45 |
- 0.98 |
- 3 |
- |
-
-
- | 99 |
- R2937E.3 |
- BXD50 |
- R2937E.3.CEL |
- 1 |
- 89 |
- 56.90% |
- 41.60% |
- 1.40% |
- 1.81 |
- 0.82 |
- 3 |
- |
-
-
- | 100 |
- R2603E.1 |
- BXD51 |
- R2603E.1.CEL |
- 2.49 |
- 115 |
- 57.70% |
- 40.80% |
- 1.50% |
- 1.24 |
- 0.79 |
- 1 |
- |
-
-
- | 101 |
- R1042E.2 |
- BXD51 |
- R1042E.2.CEL |
- 2.352 |
- 104.12 |
- 58.70% |
- 39.90% |
- 1.40% |
- 1.53 |
- 0.82 |
- 2 |
- |
-
-
- | 102 |
- R2980E.3 |
- BXD55 |
- R2980E.3.CEL |
- 1 |
- 82 |
- 56.90% |
- 41.70% |
- 1.50% |
- 1.77 |
- 0.84 |
- 3 |
- |
-
-
- | 103 |
- R2690E.2 |
- BXD55 |
- R2690E.2.CEL |
- 1.887 |
- 164.01 |
- 56.10% |
- 42.30% |
- 1.60% |
- 1.43 |
- 0.8 |
- 2 |
- |
-
-
- | 104 |
- R4176E |
- BXD56 |
- R4176E.CEL |
- 4.75 |
- 43.08 |
- 63.00% |
- 35.60% |
- 1.30% |
- 1.39 |
- 0.81 |
- 4 |
- Y |
-
-
- | 105 |
- R4175E |
- BXD56 |
- R4175E.CEL |
- 6 |
- 38.49 |
- 61.30% |
- 37.30% |
- 1.40% |
- 1.47 |
- 0.81 |
- 4 |
- Y |
-
-
- | 106 |
- R1006E.3 |
- BXD60 |
- R1006E.3.CEL |
- 1 |
- 98 |
- 54.90% |
- 43.70% |
- 1.50% |
- 2.7 |
- 0.86 |
- 3 |
- |
-
-
- | 107 |
- R2725E.2 |
- BXD60 |
- R2725E.2.CEL |
- 1.551 |
- 148.01 |
- 59.80% |
- 38.80% |
- 1.40% |
- 1.43 |
- 0.79 |
- 2 |
- |
-
-
- | 108 |
- R1074E.3 |
- BXD60 |
- R1074E.3.CEL |
- 1 |
- 118 |
- 55.50% |
- 43.10% |
- 1.40% |
- 1.96 |
- 0.81 |
- 3 |
- |
-
-
- | 109 |
- R2534E2.1 |
- BXD61 |
- R2534E2.1.CEL |
- 2.47 |
- 118 |
- 57.90% |
- 40.60% |
- 1.50% |
- 1.42 |
- 0.79 |
- 1 |
- |
-
-
- | 110 |
- R2684E.2 |
- BXD61 |
- R2684E.2.CEL |
- 2.01 |
- 131.03 |
- 57.00% |
- 41.50% |
- 1.50% |
- 1.34 |
- 0.78 |
- 2 |
- |
-
-
- | 111 |
- R1107E.3 |
- BXD62 |
- R1107E.3.CEL |
- 1 |
- 83 |
- 55.20% |
- 43.40% |
- 1.40% |
- 2.43 |
- 0.93 |
- 3 |
- |
-
-
- | 112 |
- R2681E.2 |
- BXD62 |
- R2681E.2.CEL |
- 2.086 |
- 148.24 |
- 57.20% |
- 41.30% |
- 1.50% |
- 1.29 |
- 0.81 |
- 2 |
- |
-
-
- | 113 |
- R965E.3 |
- BXD62 |
- R965E.3.CEL |
- 1 |
- 93.55 |
- 53.30% |
- 45.20% |
- 1.50% |
- 3.11 |
- 0.94 |
- 3 |
- |
-
-
- | 114 |
- R1425E.2 |
- BXD63 |
- R1425E.2.CEL |
- 1.7 |
- 136 |
- 59.30% |
- 39.30% |
- 1.40% |
- 1.43 |
- 0.82 |
- 2 |
- |
-
-
- | 115 |
- R2576E.3 |
- BXD63 |
- R2576E.3.CEL |
- 1 |
- 84 |
- 61.30% |
- 37.40% |
- 1.40% |
- 1.48 |
- 0.76 |
- 3 |
- |
-
-
- | 116 |
- R943E-2.2 |
- BXD64 |
- R943E-2.2.CEL |
- 1.591 |
- 141.34 |
- 60.10% |
- 38.40% |
- 1.50% |
- 1.32 |
- 0.76 |
- 2 |
- |
-
-
- | 117 |
- R2611E.1 |
- BXD64 |
- R2611E.1.CEL |
- 2.29 |
- 92 |
- 58.00% |
- 40.50% |
- 1.50% |
- 1.57 |
- 1.06 |
- 1 |
- |
-
-
- | 118 |
- R2689E.2 |
- BXD65 |
- R2689E.2.CEL |
- 1.721 |
- 142.44 |
- 59.90% |
- 38.60% |
- 1.50% |
- 1.38 |
- 0.76 |
- 2 |
- |
-
-
- | 119 |
- R2583E.1 |
- BXD65 |
- R2583E.1.CEL |
- 2.49 |
- 70 |
- 56.90% |
- 41.50% |
- 1.60% |
- 1.67 |
- 1.01 |
- 1 |
- |
-
-
- | 120 |
- R2728E.2 |
- BXD66 |
- R2728E.2.CEL |
- 1.714 |
- 137.45 |
- 59.40% |
- 39.00% |
- 1.60% |
- 1.38 |
- 0.79 |
- 2 |
- |
-
-
- | 121 |
- R2536E2.1 |
- BXD66 |
- R2536E2.1.CEL |
- 2.74 |
- 109 |
- 56.10% |
- 42.30% |
- 1.70% |
- 1.28 |
- 0.79 |
- 1 |
- |
-
-
- | 122 |
- R1207E.2 |
- BXD66 |
- R1207E.2.CEL |
- 1.681 |
- 136.86 |
- 60.40% |
- 38.10% |
- 1.50% |
- 1.45 |
- 0.77 |
- 2 |
- |
-
-
- | 123 |
- R1192E.2 |
- BXD67 |
- R1192E.2.CEL |
- 2.126 |
- 123.37 |
- 57.90% |
- 40.60% |
- 1.50% |
- 1.5 |
- 0.8 |
- 2 |
- |
-
-
- | 124 |
- R2727E.3 |
- BXD67 |
- R2727E.3.CEL |
- 1 |
- 82.55 |
- 56.10% |
- 42.40% |
- 1.50% |
- 1.97 |
- 0.87 |
- 2 |
- |
-
-
- | 125 |
- R2691E.3 |
- BXD67 |
- R2691E.3.CEL |
- 1 |
- 90 |
- 54.80% |
- 43.80% |
- 1.50% |
- 2.61 |
- 0.81 |
- 3 |
- |
-
-
- | 126 |
- R2551E.1 |
- BXD68 |
- R2551E.1.CEL |
- 2.49 |
- 92 |
- 54.30% |
- 44.10% |
- 1.60% |
- 2.91 |
- 1.55 |
- 1 |
- |
-
-
- | 127 |
- R2726E.2 |
- BXD68 |
- R2726E.2.CEL |
- 1.811 |
- 153.09 |
- 58.70% |
- 39.80% |
- 1.50% |
- 1.39 |
- 0.78 |
- 2 |
- |
-
-
- | 128 |
- R2593E.1 |
- BXD69 |
- R2593E.1.CEL |
- 1.67 |
- 128 |
- 59.20% |
- 39.50% |
- 1.30% |
- 1.47 |
- 0.92 |
- 1 |
- Y |
-
-
- | 129 |
- R975E.2 |
- BXD70 |
- R975E.2.CEL |
- 1.841 |
- 137.97 |
- 58.00% |
- 40.50% |
- 1.40% |
- 1.36 |
- 0.79 |
- 2 |
- |
-
-
- | 130 |
- R2537E2.1 |
- BXD70 |
- R2537E2.1.CEL |
- 2.93 |
- 99 |
- 58.00% |
- 40.50% |
- 1.60% |
- 1.29 |
- 0.75 |
- 1 |
- |
-
-
- | 131 |
- R4531E |
- BXD71 |
- R4531E.CEL |
- 4.77 |
- 43.48 |
- 62.40% |
- 36.30% |
- 1.40% |
- 1.23 |
- 0.77 |
- 4 |
- Y |
-
-
- | 132 |
- R4532E |
- BXD71 |
- R4532E.CEL |
- 5.89 |
- 40.68 |
- 60.90% |
- 37.60% |
- 1.50% |
- 1.24 |
- 0.79 |
- 4 |
- Y |
-
-
- | 133 |
- R2779E.2 |
- BXD73 |
- R2779E.2.CEL |
- 1.746 |
- 121.11 |
- 59.60% |
- 39.00% |
- 1.40% |
- 1.5 |
- 0.8 |
- 2 |
- |
-
-
- | 134 |
- R3024E.3 |
- BXD73 |
- R3024E.3.CEL |
- 1 |
- 78.05 |
- 51.70% |
- 46.60% |
- 1.70% |
- 2.3 |
- 0.94 |
- 3 |
- |
-
-
- | 135 |
- R2565E.1 |
- BXD75 |
- R2565E.1.CEL |
- 1.79 |
- 102 |
- 58.00% |
- 40.50% |
- 1.50% |
- 2.31 |
- 3.47 |
- 1 |
- |
-
-
- | 136 |
- R1397E-re.2 |
- BXD75 |
- R1397E-re.2.CEL |
- 1.449 |
- 189.71 |
- 59.60% |
- 39.00% |
- 1.40% |
- 1.39 |
- 0.82 |
- 2 |
- |
-
-
- | 137 |
- R2687E.3 |
- BXD77 |
- R2687E.3.CEL |
- 1 |
- 80 |
- 58.00% |
- 40.60% |
- 1.40% |
- 1.57 |
- 0.8 |
- 3 |
- Y |
-
-
- | 138 |
- R2717E.2 |
- BXD77 |
- R2717E.2.CEL |
- 1.797 |
- 84.43 |
- 61.60% |
- 36.90% |
- 1.40% |
- 1.49 |
- 0.76 |
- 2 |
- |
-
-
- | 139 |
- R1421E.3 |
- BXD77 |
- R1421E.3.CEL |
- 1 |
- 94 |
- 52.40% |
- 46.20% |
- 1.40% |
- 2.29 |
- 0.82 |
- 3 |
- |
-
-
- | 140 |
- R2579E.1 |
- BXD80 |
- R2579E.1.CEL |
- 2.42 |
- 72 |
- 59.20% |
- 39.40% |
- 1.50% |
- 1.73 |
- 0.82 |
- 1 |
- |
-
-
- | 141 |
- R2686E.2 |
- BXD80 |
- R2686E.2.CEL |
- 2.342 |
- 119.63 |
- 56.00% |
- 42.60% |
- 1.50% |
- 1.38 |
- 0.79 |
- 2 |
- |
-
-
- | 142 |
- R2956E.3 |
- BXD83 |
- R2956E.3.CEL |
- 1 |
- 84 |
- 55.40% |
- 43.20% |
- 1.40% |
- 1.39 |
- 0.84 |
- 3 |
- |
-
-
- | 143 |
- R2960E.3 |
- BXD83 |
- R2960E.3.CEL |
- 1 |
- 80 |
- 56.60% |
- 41.90% |
- 1.50% |
- 1.5 |
- 0.82 |
- 3 |
- Y |
-
-
- | 144 |
- R2922E.3 |
- BXD84 |
- R2922E.3.CEL |
- 1 |
- 91 |
- 57.80% |
- 40.80% |
- 1.50% |
- 1.47 |
- 0.83 |
- 3 |
- Y |
-
-
- | 145 |
- R2895E.3 |
- BXD84 |
- R2895E.3.CEL |
- 1 |
- 75 |
- 58.30% |
- 40.20% |
- 1.50% |
- 1.56 |
- 0.77 |
- 3 |
- Y |
-
-
- | 146 |
- R2692E.2 |
- BXD85 |
- R2692E.2.CEL |
- 1.423 |
- 160.87 |
- 60.20% |
- 38.30% |
- 1.40% |
- 1.46 |
- 0.79 |
- 2 |
- |
-
-
- | 147 |
- R2715E.2 |
- BXD85 |
- R2715E.2.CEL |
- 1.488 |
- 142.6 |
- 61.20% |
- 37.30% |
- 1.40% |
- 1.5 |
- 0.78 |
- 2 |
- |
-
-
- | 148 |
- R1405E.2 |
- BXD86 |
- R1405E.2.CEL |
- 2.351 |
- 119.34 |
- 56.40% |
- 42.20% |
- 1.40% |
- 1.64 |
- 0.81 |
- 2 |
- |
-
-
- | 149 |
- R1225E.3 |
- BXD86 |
- R1225E.3.CEL |
- 1 |
- 71 |
- 53.90% |
- 44.60% |
- 1.40% |
- 3.2 |
- 1.61 |
- 3 |
- |
-
-
- | 150 |
- R2724E.2 |
- BXD87 |
- R2724E.2.CEL |
- 1.906 |
- 113.71 |
- 60.70% |
- 37.90% |
- 1.40% |
- 1.45 |
- 0.79 |
- 2 |
- |
-
-
- | 151 |
- R2540E.1 |
- BXD87 |
- R2540E.1.CEL |
- 2.33 |
- 93 |
- 61.10% |
- 37.40% |
- 1.40% |
- 1.22 |
- 0.81 |
- 1 |
- Y |
-
-
- | 152 |
- R1433E.2 |
- BXD89 |
- R1433E.2.CEL |
- 1 |
- 2.241 |
- 57.70% |
- 40.80% |
- 1.50% |
- 1.41 |
- 0.78 |
- 2 |
- |
-
-
- | 153 |
- R2546E.1 |
- BXD89 |
- R2546E.1.CEL |
- 1.99 |
- 96 |
- 58.60% |
- 39.70% |
- 1.70% |
- 1.47 |
- 0.78 |
- 1 |
- |
-
-
- | 154 |
- R2578E2.1 |
- BXD90 |
- R2578E2.1.CEL |
- 2.79 |
- 92 |
- 58.60% |
- 39.80% |
- 1.60% |
- 1.52 |
- 0.77 |
- 1 |
- Y |
-
-
- | 155 |
- R859E.2 |
- BXD90 |
- R859E.2.CEL |
- 1.847 |
- 152.22 |
- 57.90% |
- 40.70% |
- 1.40% |
- 1.36 |
- 0.77 |
- 2 |
- |
-
-
- | 156 |
- R2682E.2 |
- BXD92 |
- R2682E.2.CEL |
- 1.547 |
- 156.31 |
- 60.40% |
- 38.20% |
- 1.40% |
- 1.37 |
- 0.77 |
- 2 |
- |
-
-
- | 157 |
- R1388E.3 |
- BXD92 |
- R1388E.3.CEL |
- 1 |
- 63 |
- 60.00% |
- 38.60% |
- 1.40% |
- 1.85 |
- 1.03 |
- 3 |
- |
-
-
- | 158 |
- R1322E.3 |
- BXD92 |
- R1322E.3.CEL |
- 1 |
- 80 |
- 55.90% |
- 42.60% |
- 1.50% |
- 1.75 |
- 0.74 |
- 3 |
- |
-
-
- | 159 |
- R2733E.2 |
- BXD96 |
- R2733E.2.CEL |
- 1.7 |
- 113.99 |
- 62.10% |
- 36.60% |
- 1.30% |
- 1.4 |
- 0.78 |
- 2 |
- |
-
-
- | 160 |
- R2554E.1 |
- BXD96 |
- R2554E.1.CEL |
- 2.18 |
- 93 |
- 60.20% |
- 38.30% |
- 1.50% |
- 1.46 |
- 0.77 |
- 1 |
- Y |
-
-
- | 161 |
- R2649E.2 |
- BXD97 |
- R2649E.2.CEL |
- 2.343 |
- 119.04 |
- 57.50% |
- 41.20% |
- 1.40% |
- 1.53 |
- 0.8 |
- 2 |
- |
-
-
- | 162 |
- R2577E.1 |
- BXD97 |
- R2577E.1.CEL |
- 2.07 |
- 77 |
- 59.50% |
- 39.10% |
- 1.40% |
- 1.87 |
- 1.29 |
- 1 |
- |
-
-
- | 163 |
- R2645E.3 |
- BXD98 |
- R2645E.3.CEL |
- 1 |
- 88 |
- 59.40% |
- 39.20% |
- 1.50% |
- 1.59 |
- 0.81 |
- 3 |
- Y |
-
-
- | 164 |
- R2688E.2 |
- BXD98 |
- R2688E.2.CEL |
- 1.772 |
- 145.24 |
- 58.50% |
- 40.00% |
- 1.50% |
- 1.48 |
- 0.81 |
- 2 |
- |
-
-
- | 165 |
- R4533E |
- BXD99 |
- R4533E.CEL |
- 1 |
- 37.69 |
- 60.30% |
- 38.20% |
- 1.40% |
- 1.33 |
- 0.89 |
- 4 |
- Y |
-
-
- | 166 |
- R4534E |
- BXD99 |
- R4534E.CEL |
- 5.69 |
- 36.62 |
- 62.90% |
- 35.70% |
- 1.40% |
- 1.16 |
- 0.8 |
- 4 |
- Y |
-
-
- | 167 |
- R2885E.3 |
- BXSB/MpJ |
- R2885E.3.CEL |
- 1 |
- 76 |
- 58.10% |
- 40.60% |
- 1.30% |
- 1.88 |
- 1.06 |
- 3 |
- |
-
-
- | 168 |
- R2883E.3 |
- BXSB/MpJ |
- R2883E.3.CEL |
- 1 |
- 71 |
- 56.40% |
- 42.00% |
- 1.50% |
- 1.59 |
- 0.84 |
- 3 |
- Y |
-
-
- | 169 |
- R1700E.1 |
- C3H/HeJ |
- R1700E.1.CEL |
- 2.98 |
- 69 |
- 60.80% |
- 37.90% |
- 1.40% |
- 1.48 |
- 0.78 |
- 1 |
- |
-
-
- | 170 |
- R1704E.1 |
- C3H/HeJ |
- R1704E.1.CEL |
- 2.58 |
- 88 |
- 60.10% |
- 38.60% |
- 1.30% |
- 1.38 |
- 0.84 |
- 1 |
- |
-
-
- | 171 |
- R2605E.1 |
- C57BL/6J |
- R2605E.1.CEL |
- 1.82 |
- 131 |
- 60.50% |
- 38.20% |
- 1.30% |
- 1.32 |
- 0.8 |
- 1 |
- Y |
-
-
- | 172 |
- R0871E |
- C57BL/6J |
- R0871E.CEL |
- 6.24 |
- 37.38 |
- 61.90% |
- 36.70% |
- 1.40% |
- 1.41 |
- 0.8 |
- 4 |
- Y |
-
-
- | 173 |
- R0872E.1 |
- C57BL/6J |
- R0872E.1.CEL |
- 3.13 |
- 89 |
- 58.90% |
- 39.60% |
- 1.50% |
- 1.3 |
- 0.79 |
- 1 |
- Y |
-
-
- | 174 |
- R0872E |
- C57BL/6J |
- R0872E.CEL |
- 3.128 |
- 88.58 |
- 58.90% |
- 39.60% |
- 1.50% |
- 1.3 |
- 0.79 |
- 1 |
- |
-
-
- | 175 |
- R4507E |
- C57BL/6J-Nyx |
- R4507E.CEL |
- 8.13 |
- 37.5 |
- 59.30% |
- 39.30% |
- 1.40% |
- 1.32 |
- 0.8 |
- 4 |
- Y |
-
-
- | 176 |
- R4508E |
- C57BL/6J-Nyx |
- R4508E.CEL |
- 6.33 |
- 37.26 |
- 60.90% |
- 37.80% |
- 1.30% |
- 1.24 |
- 0.82 |
- 4 |
- Y |
-
-
- | 177 |
- R4505E |
- C57BL/6J-Rpe65 |
- R4505E.CEL |
- 5.98 |
- 37.48 |
- 61.80% |
- 36.80% |
- 1.40% |
- 1.45 |
- 0.85 |
- 4 |
- Y |
-
-
- | 178 |
- R4506E |
- C57BL/6J-Rpe65 |
- R4506E.CEL |
- 6.94 |
- 37.9 |
- 61.10% |
- 37.50% |
- 1.30% |
- 1.5 |
- 0.83 |
- 4 |
- Y |
-
-
- | 179 |
- R4535E |
- C57BLKS/J |
- R4535E.CEL |
- 6.59 |
- 37.28 |
- 61.20% |
- 37.30% |
- 1.40% |
- 1.26 |
- 0.83 |
- 4 |
- Y |
-
-
- | 180 |
- R4536E |
- C57BLKS/J |
- R4536E.CEL |
- 1 |
- 40.71 |
- 60.30% |
- 38.20% |
- 1.50% |
- 1.25 |
- 0.77 |
- 4 |
- Y |
-
-
- | 181 |
- R2564E.1 |
- CAST/EiJ |
- R2564E.1.CEL |
- 1.94 |
- 89 |
- 58.50% |
- 39.90% |
- 1.60% |
- 1.6 |
- 0.77 |
- 1 |
- |
-
-
- | 182 |
- R2580E.1 |
- CAST/EiJ |
- R2580E.1.CEL |
- 2.09 |
- 95 |
- 58.20% |
- 40.10% |
- 1.70% |
- 1.4 |
- 0.76 |
- 1 |
- |
-
-
- | 183 |
- R4537E |
- CBA/CaJ |
- R4537E.CEL |
- 1 |
- 38.45 |
- 60.60% |
- 37.90% |
- 1.50% |
- 1.63 |
- 0.82 |
- 4 |
- Y |
-
-
- | 184 |
- R4538E |
- CBA/CaJ |
- R4538E.CEL |
- 5.89 |
- 39.18 |
- 61.70% |
- 36.90% |
- 1.40% |
- 1.45 |
- 0.8 |
- 4 |
- Y |
-
-
- | 185 |
- R4539E |
- CZECHII/EiJ |
- R4539E.CEL |
- 7.73 |
- 37.1 |
- 58.30% |
- 40.10% |
- 1.50% |
- 1.7 |
- 0.95 |
- 4 |
- Y |
-
-
- | 186 |
- R4540E |
- CZECHII/EiJ |
- R4540E.CEL |
- 11.04 |
- 36.69 |
- 53.00% |
- 45.30% |
- 1.70% |
- 1.83 |
- 1.32 |
- 4 |
- |
-
-
- | 187 |
- R2600E.1 |
- D2B6F1 |
- R2600E.1.CEL |
- 2.47 |
- 95 |
- 58.10% |
- 40.20% |
- 1.70% |
- 1.41 |
- 0.78 |
- 1 |
- Y |
-
-
- | 188 |
- R2604E.1 |
- D2B6F1 |
- R2604E.1.CEL |
- 2.66 |
- 90 |
- 59.40% |
- 39.20% |
- 1.50% |
- 1.28 |
- 0.79 |
- 1 |
- Y |
-
-
- | 189 |
- R1002E.3 |
- DBA/2J |
- R1002E.3.CEL |
- 1 |
- 102 |
- 54.80% |
- 43.70% |
- 1.50% |
- 2.84 |
- 0.83 |
- 3 |
- |
-
-
- | 190 |
- R4541E |
- DBA/2J |
- R4541E.CEL |
- 1 |
- 43.4 |
- 61.40% |
- 37.00% |
- 1.50% |
- 1.37 |
- 0.73 |
- 4 |
- Y |
-
-
- | 191 |
- R959E.3 |
- DBA/2J |
- R959E.3.CEL |
- 1 |
- 89.97 |
- 53.20% |
- 45.30% |
- 1.50% |
- 3.66 |
- 1.09 |
- 4 |
- |
-
-
- | 192 |
- R2572E.1 |
- DBA/2J |
- R2572E.1.CEL |
- 2.41 |
- 79 |
- 55.50% |
- 42.90% |
- 1.60% |
- 1.37 |
- 0.79 |
- 1 |
- |
-
-
- | 193 |
- R4542E |
- DBA/2J |
- R4542E.CEL |
- 5.7 |
- 39.95 |
- 61.00% |
- 37.40% |
- 1.50% |
- 1.23 |
- 0.81 |
- 4 |
- Y |
-
-
- | 194 |
- R2771E.3 |
- FVB/NJ |
- R2771E.3.CEL |
- 1 |
- 70 |
- 55.30% |
- 43.20% |
- 1.50% |
- 1.69 |
- 0.83 |
- 3 |
- |
-
-
- | 195 |
- R2772E.3 |
- FVB/NJ |
- R2772E.3.CEL |
- 1 |
- 76 |
- 55.20% |
- 43.40% |
- 1.40% |
- 2.13 |
- 1.02 |
- 3 |
- |
-
-
- | 196 |
- R2636E.1 |
- KK/HlJ |
- R2636E.1.CEL |
- 2.61 |
- 93 |
- 58.90% |
- 39.50% |
- 1.50% |
- 1.39 |
- 0.76 |
- 1 |
- Y |
-
-
- | 197 |
- R2637E.1 |
- KK/HlJ |
- R2637E.1.CEL |
- 2.19 |
- 103 |
- 59.40% |
- 39.00% |
- 1.50% |
- 1.3 |
- 0.79 |
- 1 |
- Y |
-
-
- | 198 |
- R0999E.1 |
- LG/J |
- R0999E.1.CEL |
- 2.45 |
- 82 |
- 59.40% |
- 39.10% |
- 1.50% |
- 1.38 |
- 0.79 |
- 1 |
- Y |
-
-
- | 199 |
- R1004E.1 |
- LG/J |
- R1004E.1.CEL |
- 2.44 |
- 92 |
- 58.70% |
- 39.80% |
- 1.50% |
- 1.38 |
- 0.79 |
- 1 |
- Y |
-
-
- | 200 |
- R4543E |
- LP/J |
- R4543E.CEL |
- 6.57 |
- 41.99 |
- 60.30% |
- 38.20% |
- 1.50% |
- 1.28 |
- 0.75 |
- 4 |
- Y |
-
-
- | 201 |
- R4544E |
- LP/J |
- R4544E.CEL |
- 4.56 |
- 39.9 |
- 62.40% |
- 36.10% |
- 1.50% |
- 1.23 |
- 0.77 |
- 4 |
- Y |
-
-
- | 202 |
- R2858E.3 |
- MOLF/EiJ |
- R2858E.3.CEL |
- 1 |
- 64 |
- 53.80% |
- 44.70% |
- 1.50% |
- 1.59 |
- 0.95 |
- 3 |
- |
-
-
- | 203 |
- R2919.3 |
- MOLF/EiJ |
- R2919.3.CEL |
- 1 |
- 64 |
- 52.40% |
- 46.00% |
- 1.60% |
- 2.15 |
- 1.07 |
- 3 |
- |
-
-
- | 204 |
- R1688E.1 |
- NOD/LtJ |
- R1688E.1.CEL |
- 2.66 |
- 98 |
- 58.60% |
- 39.90% |
- 1.50% |
- 1.26 |
- 0.8 |
- 1 |
- Y |
-
-
- | 205 |
- R2566E-2.1 |
- NOD/LtJ |
- R2566E-2.1.CEL |
- 3.03 |
- 69 |
- 59.80% |
- 38.80% |
- 1.50% |
- 1.38 |
- 0.75 |
- 1 |
- Y |
-
-
- | 206 |
- R4545E |
- NZB/BlNJ |
- R4545E.CEL |
- 4.23 |
- 43.48 |
- 62.10% |
- 36.40% |
- 1.50% |
- 1.33 |
- 0.76 |
- 4 |
- Y |
-
-
- | 207 |
- R4546E |
- NZB/BlNJ |
- R4546E.CEL |
- 6.27 |
- 44.22 |
- 59.40% |
- 39.10% |
- 1.50% |
- 1.17 |
- 0.82 |
- 4 |
- Y |
-
-
- | 208 |
- R2535E.1 |
- NZO/HlLtJ |
- R2535E.1.CEL |
- 1.89 |
- 86 |
- 60.40% |
- 38.20% |
- 1.40% |
- 1.41 |
- 0.85 |
- 1 |
- |
-
-
- | 209 |
- R2550E.1 |
- NZO/HlLtJ |
- R2550E.1.CEL |
- 1.79 |
- 87 |
- 60.70% |
- 37.80% |
- 1.50% |
- 1.52 |
- 0.82 |
- 1 |
- |
-
-
- | 210 |
- R2817E.3 |
- NZW/LacJ |
- R2817E.3.CEL |
- 1 |
- 59 |
- 50.90% |
- 47.60% |
- 1.50% |
- 3.59 |
- 1.48 |
- 3 |
- |
-
-
- | 211 |
- R2810E |
- NZW/LacJ |
- R2810E.CEL |
- |
- |
- |
- |
- |
- |
- |
- 3 |
- |
-
-
- | 212 |
- R2810E.3 |
- NZW/LacJ |
- R2810E.3.CEL |
- 1 |
- 74 |
- 57.00% |
- 41.70% |
- 1.40% |
- 2.15 |
- 1.03 |
- 4 |
- Y |
-
-
- | 213 |
- R4547E |
- PANCEVO/EiJ |
- R4547E.CEL |
- 5.27 |
- 51.34 |
- 57.20% |
- 41.10% |
- 1.70% |
- 1.7 |
- 0.83 |
- 4 |
- |
-
-
- | 214 |
- R4548E |
- PANCEVO/EiJ |
- R4548E.CEL |
- 10.54 |
- 37.39 |
- 50.30% |
- 48.00% |
- 1.70% |
- 1.68 |
- 1.09 |
- 4 |
- |
-
-
- | 215 |
- R2635E.1 |
- PWD/PhJ |
- R2635E.1.CEL |
- 3.72 |
- 80 |
- 54.20% |
- 44.10% |
- 1.70% |
- 1.53 |
- 0.85 |
- 1 |
- |
-
-
- | 216 |
- R2634E.1 |
- PWD/PhJ |
- R2634E.1.CEL |
- 3.29 |
- 90 |
- 55.90% |
- 42.50% |
- 1.60% |
- 1.57 |
- 0.81 |
- 1 |
- |
-
-
- | 217 |
- R2544E.1 |
- PWK/PhJ |
- R2544E.1.CEL |
- 2.2 |
- 108 |
- 54.90% |
- 43.50% |
- 1.70% |
- 1.36 |
- 0.82 |
- 1 |
- |
-
-
- | 218 |
- R2549E.1 |
- PWK/PhJ |
- R2549E.1.CEL |
- 2.28 |
- 84 |
- 57.30% |
- 41.20% |
- 1.50% |
- 1.57 |
- 0.83 |
- 1 |
- |
-
-
- | 219 |
- R4550E |
- SJL/J |
- R4550E.CEL |
- 5.35 |
- 40.44 |
- 62.30% |
- 36.20% |
- 1.40% |
- 1.24 |
- 0.79 |
- 4 |
- |
-
-
- | 220 |
- R2368E.1 |
- WSB/EiJ |
- R2368E.1.CEL |
- 2.57 |
- 86 |
- 59.50% |
- 39.10% |
- 1.40% |
- 1.29 |
- 0.74 |
- 1 |
- Y |
-
-
- | 221 |
- R2547E.1 |
- WSB/EiJ |
- R2547E.1.CEL |
- 2.14 |
- 90 |
- 58.20% |
- 40.10% |
- 1.60% |
- 1.32 |
- 0.77 |
- 1 |
- Y |
-
-
-
- |
-
-
-
diff --git a/general/datasets/gn10/summary.rtf b/general/datasets/gn10/summary.rtf
deleted file mode 100644
index 44b7e23..0000000
--- a/general/datasets/gn10/summary.rtf
+++ /dev/null
@@ -1,12 +0,0 @@
-FINAL RECOMMENDED EYE DATA SET. The HEIMED September 2008 RMA data release provides estimates of gene expression in whole eyes of 103 lines of young adult mice generated using 221 Affymetrix M430 2.0 arrays. This data set is intended for exploration of the genetics and genomics of the mouse eye, retina, lens, retinal pigment epithelium, cornea, iris and choroid. Data were generated at UTHSC with support from a grant from Dr. Barrett Haik, Director of the Hamilton Eye Institute (HEI). We used pooled RNA samples, usually two independent pools--one male, one female pool--for most lines of mice. This data set was processed using the RMA protocol. A total of 2223 probes sets are associated with LRS values greater than 46 (LOD >10).
-
-Users of these mouse eye data may also find the following complementary resources extremely useful:
-
-
- - NEIBank collection of ESTs and SAGE data.
- - RetNet: the Retinal Information Network--tables of genes and loci causing inherited retinal diseases
- - Mouse Retina SAGE Library from the Cepko laboratory. This site provides extensive developmental data from as early as embryonic day E12.5.
- - Digital reference of ophthalmology from Columbia provides high quality photographs of human ocular diseases, case studies, and short explanations. This reference does not have a molecular focus.
- - Mouse Retinal Developmental Gene Expression data sets from the Friedlander laboratory. This site provides extensive developmental data using the Affymetrix U74 v 2 array (predecessor of the M430).
- - Data sets on differential gene expression in anatomical compartments of the human eye from Pat Brown's lab. View expression signatures for different ocular tissues using the geneXplorer 2.0.
-
diff --git a/general/datasets/gn10/tissue.rtf b/general/datasets/gn10/tissue.rtf
deleted file mode 100644
index 9b6ee0f..0000000
--- a/general/datasets/gn10/tissue.rtf
+++ /dev/null
@@ -1,2058 +0,0 @@
-Tissue preparation protocol. Animal were killed by rapid cervical dislocation. Eyes were removed immediately and placed in RNAlater at room temperature. Usually six eyes from animals with a common sex, age, and strain were stored in a single tube.
-
-Each array was hybridized with a pool of cRNA from 4 to 8 eyes from 2 to 4 animals. RNA was extracted at UTHSC by Zhiping Jia. If tissue was saved for RNA extraction at a later time, eyes were placed directly in RNAlater (Ambion, Inc.) and treated per the manufacturer’s directions. If eyes were used for immediate RNA extraction then we proceeded immediately to the next steps.
-
-Dissecting and preparing eyes for RNA extraction
-
-
- - Place eyes for RNA extraction in RNA STAT-60 (Tel-Test Inc.) and process per manufacturer’s instructions (in brief form below).
- - Store RNA in 75% ethanol at –80 deg. C until use.
-
-
-Total RNA was extracted with RNA STAT-60 (Tel-Test Inc.) according to the manufacturer's instructions. Briefly we:
-
-
- - homogenize tissue samples in the RNA STAT-60 (1 ml/50 to 100 mg tissue)
- - allowed the homogenate to stand for 5 min at room temperature
- - added 0.2 ml of chloroform per 1 ml RNA STAT-60
- - shook the sample vigorously for 15 sec and let the sample sit at room temperature for 3 min
- - centrifuged at 12,000 G for 15 min
- - transfered the aqueous phase to a fresh tube
- - added 0.5 ml of isopropanol per 1 ml RNA STAT-60
- - vortexed and allowed sample to stand at room temperature for 5-10 min
- - centrifuged at 12,000 G for 10-15 min
- - removed the supernatant and washed the RNA pellet with 75% ethanol
- - stored the pellet in 75% ethanol at -80 deg C until use
-
-
-Sample Processing. All samples were processed in the VA Medical Center, Memphis, Rheumatology Disease Research Core Center led by Dr. Weikuan Gu. All arrays were processed by Dr. Yan Jiao. In brief, samples were purified using a standard sodium acetate in alcohol method (recommended by Affymetrix). The RNA quality was checked using a 1% agarose gel. The 18S and 28S bands had to be clear and the 28S band had to be more prominent. RNA concentation was measured using a spectrophotometer. The 260/280 ratios had to be greater than 1.7, and the majority were 1.8 or higher. We used a total of 8 micrograms of RNA as starting amount for cDNA synthesis using a standard Eberwine T7 polymerase method (Superscript II RT, Invitrogen Inc., Affy Part No 900431, GeneChip Expression 3' Amplification One-Cyle cDNA Synthesis Kit). The Affymetrix IVT labeling kit (Affy 900449) was used to generate labeled cRNA. At this point the cRNA was evaluated again using both the 260/280 ratio (values of 2.0 or above were acceptable) and 1% agarose gel inspection of the product (a size range from 200 to 7000 bp is considered suitable for use). We used 45 micrograms of labeled cRNA for fragmentation. Those samples that passed both QC steps (<10% usually fail) were then sheared using a fragmentation buffer included in the Affymetrix GeneChip Sample Cleanup Module (Part No.900371). After fragmentation, samples were either stored at -80 deg. C until use (roughly one third) or were used immediately for hybridization.
-
-Dealing with ocular pigmentation: Variable ocular pigmentation is a potential confound in a study of the whole eye transcriptome. Even the most careful RNA preparations taken from brown and beige colored mice tend to have faint residual pigmentation that affects hybridization signal. To address this problem, Dr. Yan Jiao purified total RNA using the Qiagen RNeasy MinElute Cleanup Kit (Cat No. 74204) all four batches.
-
-Replication, sex, and sample balance: Our goal was to obtain data for independent biological sample pools from both sexes for most lines of mice. The four batches of arrays included in this final data set, collectively represent a reasonably well balanced sample of males and females, in general without within-strain-by-sex replication. Two strains are represented by a single male sample pool (BXD29 and A/J). Four lines are represented by two or three male sample pools (all of the five DeltaGen KO line). The SJL/J may be a single mixed sex sample. Users can study possible sex effects by comparing any results of expression data to that of a surrogate measurement that summarizes the overall sex balance of HEIMED. To do this just compare your data to those of probe sets 1427262_at (Xist, high in females) and probe set 1426438_at (Ddx3y, high in males). These two sex-specific probes are quantitative surrogates for the sex balance in this data set.
-
-Technical duplicates: One sample, highlighted in the tables below, is a technical duplicate. The pair of technical duplicates were both of high quality. For statistical analysis, they should be combined and treated as single biological sample.
-
-Batch structure: This data set consists of four batches (Table 2, far right column). The final September 2008 data set consists of a total of 221 arrays and 220 independent samples.
-
-
- - Batch 1: November 2005, n = 78 arrays original arrays of which 76 were accepted into this final data set.
- - Batch 2: January 2006, n = 62 arrays of which 62 were accepted.
- - Batch 3: August 2006, n = 39 arrays of which 36 were accepted. (These three batches, including some arrays that were eventually dropped from the final 2008 data set, were combined to form the September 2006 data set.)
- - Batch 4: Summer 2008, n = 53 arrays of which 47 were accepted.
-
-
-Table 1: HEIMED case IDs, including sample tube ID, strain, age, sex, and source of mice (see Table 2 for information on array quality control)
-
-
-
-
-
-
-
-
-
-
- | Index |
- TubeID |
- Group |
- Strain |
- Age |
- Sex |
- Source |
-
-
- | 1 |
- R2595E.1 |
- GDP |
- 129S1/SvImJ |
- 59 |
- F |
- UTHSC RW |
-
-
- | 2 |
- R2533E.1 |
- GDP |
- 129S1/SvImJ |
- 60 |
- M |
- UTHSC RW |
-
-
- | 3 |
- R0754E.1 |
- GDP |
- A/J |
- 60 |
- M |
- JAX |
-
-
- | 4 |
- R4521E |
- KO |
- B6129P2F2N1-Clcn3 |
- 69 |
- M |
- TChoi_Deltagen |
-
-
- | 5 |
- R4522E |
- KO |
- B6129P2F2N1-Clcn3 |
- 69 |
- M |
- TChoi_Deltagen |
-
-
- | 6 |
- R4523E |
- KO |
- B6129P2F2N1-Clcn3 |
- 67 |
- M |
- TChoi_Deltagen |
-
-
- | 7 |
- R4526E |
- KO |
- B6129P2F2N1-Gabbr1 |
- 16 |
- F |
- TChoi_Deltagen |
-
-
- | 8 |
- R4509E |
- KO |
- B6129P2F2N1-Gabbr1 |
- 16 |
- M |
- TChoi_Deltagen |
-
-
- | 9 |
- R4510E |
- KO |
- B6129P2F2N1-Gabbr1 |
- 19 |
- M |
- TChoi_Deltagen |
-
-
- | 10 |
- R4511E |
- KO |
- B6129P2F2N1-Gabbr1 |
- 20 |
- M |
- TChoi_Deltagen |
-
-
- | 11 |
- R4524E |
- KO |
- B6129P2F2N1-Gabbr1 |
- 19 |
- M |
- TChoi_Deltagen |
-
-
- | 12 |
- R4525E |
- KO |
- B6129P2F2N1-Gabbr1 |
- 22 |
- M |
- TChoi_Deltagen |
-
-
- | 13 |
- R4515E |
- KO |
- B6129P2F2N1-Gabra1 |
- 67 |
- M |
- TChoi_Deltagen |
-
-
- | 14 |
- R4516E |
- KO |
- B6129P2F2N1-Gabra1 |
- 69 |
- M |
- TChoi_Deltagen |
-
-
- | 15 |
- R4517E |
- KO |
- B6129P2F2N1-Gabra1 |
- 67 |
- M |
- TChoi_Deltagen |
-
-
- | 16 |
- R4512E |
- KO |
- B6129P2F2N1-Gnb5 |
- 22 |
- F |
- TChoi_Deltagen |
-
-
- | 17 |
- R4513E |
- KO |
- B6129P2F2N1-Gnb5 |
- 25 |
- M |
- TChoi_Deltagen |
-
-
- | 18 |
- R4514E |
- KO |
- B6129P2F2N1-Gnb5 |
- 22 |
- M |
- TChoi_Deltagen |
-
-
- | 19 |
- R4518E |
- KO |
- B6129P2F2N1-Gpr19 |
- 70 |
- M |
- TChoi_Deltagen |
-
-
- | 20 |
- R4519E |
- KO |
- B6129P2F2N1-Gpr19 |
- 68 |
- M |
- TChoi_Deltagen |
-
-
- | 21 |
- R2601E.1 |
- GDP BXD |
- B6D2F1 |
- 73 |
- F |
- UTHSC RW |
-
-
- | 22 |
- R2602E.1 |
- GDP BXD |
- B6D2F1 |
- 73 |
- M |
- UTHSC RW |
-
-
- | 23 |
- R1676E.1 |
- GDP |
- BALB/cByJ |
- 83 |
- F |
- JAX |
-
-
- | 24 |
- R1672E.1 |
- GDP |
- BALB/cByJ |
- 83 |
- M |
- JAX |
-
-
- | 25 |
- R4530E |
- GDP |
- BALB/cJ |
- 66 |
- F |
- JAX |
-
-
- | 26 |
- R4529E |
- GDP |
- BALB/cJ |
- 66 |
- M |
- JAX |
-
-
- | 27 |
- R2704E.2 |
- BXD |
- BXD1 |
- 59 |
- F |
- UTHSC RW |
-
-
- | 28 |
- R2707E.3 |
- BXD |
- BXD1 |
- 59 |
- M |
- BIDMC GR |
-
-
- | 29 |
- R1231E.2 |
- BXD |
- BXD2 |
- 64 |
- F |
- UTHSC RW |
-
-
- | 30 |
- R2598E.1 |
- BXD |
- BXD2 |
- 61 |
- M |
- UTHSC RW |
-
-
- | 31 |
- R2591E.1 |
- BXD |
- BXD5 |
- 60 |
- F |
- BIDMC GR |
-
-
- | 32 |
- R2714E.2 |
- BXD |
- BXD5 |
- 58 |
- M |
- UTHSC RW |
-
-
- | 33 |
- R2570E.1 |
- BXD |
- BXD6 |
- 65 |
- F |
- UTHSC RW |
-
-
- | 34 |
- R2694E.2 |
- BXD |
- BXD6 |
- 58 |
- M |
- UTHSC RW |
-
-
- | 35 |
- R2538E.1 |
- BXD |
- BXD8 |
- 77 |
- F |
- UTHSC RW |
-
-
- | 36 |
- R2709E.2 |
- BXD |
- BXD8 |
- 61 |
- M |
- UTHSC RW |
-
-
- | 37 |
- R2708E.2 |
- BXD |
- BXD9 |
- 60 |
- F |
- UTHSC RW |
-
-
- | 38 |
- R2569E.1 |
- BXD |
- BXD9 |
- 67 |
- M |
- UTHSC RW |
-
-
- | 39 |
- R2581E.1 |
- BXD |
- BXD11 |
- 65 |
- F |
- UTHSC RW |
-
-
- | 40 |
- R2612E.2 |
- BXD |
- BXD11 |
- 70 |
- M |
- UTHSC RW |
-
-
- | 41 |
- R2742E.2 |
- BXD |
- BXD12 |
- 71 |
- F |
- UTHSC RW |
-
-
- | 42 |
- R2543E.1 |
- BXD |
- BXD12 |
- 63 |
- M |
- UTHSC RW |
-
-
- | 43 |
- R2586E.1 |
- BXD |
- BXD13 |
- 60 |
- F |
- BIDMC GR |
-
-
- | 44 |
- R877E.2 |
- BXD |
- BXD13 |
- 76 |
- M |
- UTHSC RW |
-
-
- | 45 |
- R2557E.1 |
- BXD |
- BXD14 |
- 60 |
- F |
- BIDMC GR |
-
-
- | 46 |
- R1128E.2 |
- BXD |
- BXD14 |
- 65 |
- M |
- UTHSC RW |
-
-
- | 47 |
- R2701E.3 |
- BXD |
- BXD15 |
- 60 |
- F |
- BIDMC GR |
-
-
- | 48 |
- R2716E.2 |
- BXD |
- BXD15 |
- 60 |
- M |
- UTHSC RW |
-
-
- | 49 |
- R2711E.2 |
- BXD |
- BXD16 |
- 61 |
- F |
- UTHSC RW |
-
-
- | 50 |
- R2567E.1 |
- BXD |
- BXD16 |
- 60 |
- M |
- BIDMC GR |
-
-
- | 51 |
- R2720E.2 |
- BXD |
- BXD18 |
- 59 |
- F |
- UTHSC RW |
-
-
- | 52 |
- R2559E.1 |
- BXD |
- BXD18 |
- 59 |
- M |
- BIDMC GR |
-
-
- | 53 |
- R2560E.1 |
- BXD |
- BXD19 |
- 60 |
- F |
- BIDMC GR |
-
-
- | 54 |
- R2713E.2 |
- BXD |
- BXD19 |
- 60 |
- M |
- UTHSC RW |
-
-
- | 55 |
- R2584E.1 |
- BXD |
- BXD20 |
- 59 |
- F |
- BIDMC GR |
-
-
- | 56 |
- R2731E.2 |
- BXD |
- BXD20 |
- 60 |
- M |
- UTHSC RW |
-
-
- | 57 |
- R2702E.2 |
- BXD |
- BXD21 |
- 59 |
- F |
- UTHSC RW |
-
-
- | 58 |
- R2541E2.1 |
- BXD |
- BXD21 |
- 61 |
- M |
- UTHSC RW |
-
-
- | 59 |
- R2553E.1 |
- BXD |
- BXD22 |
- 58 |
- F |
- BIDMC GR |
-
-
- | 60 |
- R2700E.2 |
- BXD |
- BXD22 |
- 59 |
- M |
- UTHSC RW |
-
-
- | 61 |
- R2558E-2.1 |
- BXD |
- BXD23 |
- 60 |
- F |
- BIDMC GR |
-
-
- | 62 |
- R1086E.2 |
- BXD |
- BXD23 |
- 55 |
- M |
- UTHSC RW |
-
-
- | 63 |
- R2719E.2 |
- BXD |
- BXD24 |
- 123 |
- F |
- UTHSC RW |
-
-
- | 64 |
- R2589E2.1 |
- BXD |
- BXD24 |
- 59 |
- M |
- BIDMC GR |
-
-
- | 65 |
- R2573E-2.1 |
- BXD |
- BXD25 |
- 67 |
- F |
- UAB |
-
-
- | 66 |
- R2683E.2 |
- BXD |
- BXD25 |
- 58 |
- M |
- UTHSC RW |
-
-
- | 67 |
- R2703E.2 |
- BXD |
- BXD27 |
- 60 |
- F |
- UTHSC RW |
-
-
- | 68 |
- R2729E.3 |
- BXD |
- BXD27 |
- 68 |
- M |
- UTHSC RW |
-
-
- | 69 |
- R2562E.3 |
- BXD |
- BXD28 |
- 60 |
- F |
- BIDMC GR |
-
-
- | 70 |
- R2721E.2 |
- BXD |
- BXD28 |
- 60 |
- M |
- UTHSC RW |
-
-
- | 71 |
- R2561E.3 |
- BXD |
- BXD29 |
- 60 |
- M |
- BIDMC GR |
-
-
- | 72 |
- R1258E.2 |
- BXD |
- BXD31 |
- 57 |
- F |
- UTHSC RW |
-
-
- | 73 |
- R2597E.1 |
- BXD |
- BXD31 |
- 61 |
- M |
- BIDMC GR |
-
-
- | 74 |
- R2563E.1 |
- BXD |
- BXD32 |
- 63 |
- F |
- UTHSC RW |
-
-
- | 75 |
- R1216E.2 |
- BXD |
- BXD32 |
- 76 |
- M |
- UTHSC RW |
-
-
- | 76 |
- R2542E.1 |
- BXD |
- BXD33 |
- 67 |
- F |
- UTHSC RW |
-
-
- | 77 |
- R857E.2 |
- BXD |
- BXD33 |
- 77 |
- M |
- UTHSC RW |
-
-
- | 78 |
- R1451E.2 |
- BXD |
- BXD34 |
- 61 |
- F |
- UTHSC RW |
-
-
- | 79 |
- R2585E.1 |
- BXD |
- BXD34 |
- 60 |
- M |
- BIDMC GR |
-
-
- | 80 |
- R2698E.3 |
- BXD |
- BXD36 |
- 58 |
- F |
- BIDMC GR |
-
-
- | 81 |
- R2705E.3 |
- BXD |
- BXD36 |
- 57 |
- M |
- BIDMC GR |
-
-
- | 82 |
- R2710E.2 |
- BXD |
- BXD38 |
- 55 |
- F |
- UTHSC RW |
-
-
- | 83 |
- R2532E.1 |
- BXD |
- BXD38 |
- 62 |
- M |
- UTHSC RW |
-
-
- | 84 |
- R2574E.1 |
- BXD |
- BXD39 |
- 70 |
- F |
- UTHSC RW |
-
-
- | 85 |
- R2695E.2 |
- BXD |
- BXD39 |
- 59 |
- M |
- UTHSC RW |
-
-
- | 86 |
- R2699E.2 |
- BXD |
- BXD40 |
- 59 |
- F |
- UTHSC RW |
-
-
- | 87 |
- R2590E.1 |
- BXD |
- BXD40 |
- 60 |
- M |
- BIDMC GR |
-
-
- | 88 |
- R2696E.2 |
- BXD |
- BXD42 |
- 58 |
- F |
- UTHSC RW |
-
-
- | 89 |
- R2596E.1 |
- BXD |
- BXD42 |
- 59 |
- M |
- BIDMC GR |
-
-
- | 90 |
- R994E.2 |
- BXD |
- BXD43 |
- 60 |
- F |
- UTHSC RW |
-
-
- | 91 |
- R2607E.1 |
- BXD |
- BXD43 |
- 67 |
- M |
- UTHSC RW |
-
-
- | 92 |
- R2594E.1 |
- BXD |
- BXD44 |
- 63 |
- F |
- UTHSC RW |
-
-
- | 93 |
- R2610E.2 |
- BXD |
- BXD44 |
- 68 |
- M |
- UTHSC RW |
-
-
- | 94 |
- R2732E.2 |
- BXD |
- BXD45 |
- 63 |
- F |
- UTHSC RW |
-
-
- | 95 |
- R2592E.1 |
- BXD |
- BXD45 |
- 62 |
- M |
- UTHSC RW |
-
-
- | 96 |
- R967E.2 |
- BXD |
- BXD48 |
- 64 |
- F |
- UTHSC RW |
-
-
- | 97 |
- R2606E.1 |
- BXD |
- BXD48 |
- 78 |
- M |
- UTHSC RW |
-
-
- | 98 |
- R2933E.3 |
- BXD |
- BXD50 |
- 61 |
- F |
- UTHSC RW |
-
-
- | 99 |
- R2937E.3 |
- BXD |
- BXD50 |
- 61 |
- M |
- UTHSC RW |
-
-
- | 100 |
- R2603E.1 |
- BXD |
- BXD51 |
- 66 |
- F |
- UTHSC RW |
-
-
- | 101 |
- R1042E.2 |
- BXD |
- BXD51 |
- 62 |
- M |
- UTHSC RW |
-
-
- | 102 |
- R2980E.3 |
- BXD |
- BXD55 |
- 76 |
- F |
- UTHSC RW |
-
-
- | 103 |
- R2690E.2 |
- BXD |
- BXD55 |
- 65 |
- M |
- UTHSC RW |
-
-
- | 104 |
- R4176E |
- BXD |
- BXD56 |
- 67 |
- F |
- UTHSC RW |
-
-
- | 105 |
- R4175E |
- BXD |
- BXD56 |
- 53 |
- M |
- UTHSC RW |
-
-
- | 106 |
- R1006E.3 |
- BXD |
- BXD60 |
- 60 |
- F |
- UTHSC RW |
-
-
- | 107 |
- R2725E.2 |
- BXD |
- BXD60 |
- 61 |
- F |
- UTHSC RW |
-
-
- | 108 |
- R1074E.3 |
- BXD |
- BXD60 |
- 59 |
- M |
- UTHSC RW |
-
-
- | 109 |
- R2534E2.1 |
- BXD |
- BXD61 |
- 70 |
- F |
- UTHSC RW |
-
-
- | 110 |
- R2684E.2 |
- BXD |
- BXD61 |
- 62 |
- M |
- UTHSC RW |
-
-
- | 111 |
- R1107E.3 |
- BXD |
- BXD62 |
- 54 |
- F |
- UTHSC RW |
-
-
- | 112 |
- R2681E.2 |
- BXD |
- BXD62 |
- 62 |
- M |
- UTHSC RW |
-
-
- | 113 |
- R965E.3 |
- BXD |
- BXD62 |
- 54 |
- M |
- UTHSC RW |
-
-
- | 114 |
- R1425E.2 |
- BXD |
- BXD63 |
- 61 |
- F |
- UTHSC RW |
-
-
- | 115 |
- R2576E.3 |
- BXD |
- BXD63 |
- 70 |
- M |
- UTHSC RW |
-
-
- | 116 |
- R943E-2.2 |
- BXD |
- BXD64 |
- 56 |
- F |
- UTHSC RW |
-
-
- | 117 |
- R2611E.1 |
- BXD |
- BXD64 |
- 68 |
- M |
- UTHSC RW |
-
-
- | 118 |
- R2689E.2 |
- BXD |
- BXD65 |
- 63 |
- F |
- UTHSC RW |
-
-
- | 119 |
- R2583E.1 |
- BXD |
- BXD65 |
- 60 |
- M |
- UTHSC RW |
-
-
- | 120 |
- R2728E.2 |
- BXD |
- BXD66 |
- 67 |
- F |
- UTHSC RW |
-
-
- | 121 |
- R2536E2.1 |
- BXD |
- BXD66 |
- 64 |
- F |
- UTHSC RW |
-
-
- | 122 |
- R1207E.2 |
- BXD |
- BXD66 |
- 83 |
- M |
- UTHSC RW |
-
-
- | 123 |
- R1192E.2 |
- BXD |
- BXD67 |
- 64 |
- F |
- UTHSC RW |
-
-
- | 124 |
- R2727E.3 |
- BXD |
- BXD67 |
- 65 |
- F |
- UTHSC RW |
-
-
- | 125 |
- R2691E.3 |
- BXD |
- BXD67 |
- 65 |
- M |
- UTHSC RW |
-
-
- | 126 |
- R2551E.1 |
- BXD |
- BXD68 |
- 67 |
- F |
- UTHSC RW |
-
-
- | 127 |
- R2726E.2 |
- BXD |
- BXD68 |
- 64 |
- M |
- UTHSC RW |
-
-
- | 128 |
- R2593E.1 |
- BXD |
- BXD69 |
- 59 |
- F |
- UTHSC RW |
-
-
- | 129 |
- R975E.2 |
- BXD |
- BXD70 |
- 64 |
- F |
- UTHSC RW |
-
-
- | 130 |
- R2537E2.1 |
- BXD |
- BXD70 |
- 59 |
- M |
- UTHSC RW |
-
-
- | 131 |
- R4531E |
- BXD |
- BXD71 |
- 87 |
- F |
- UTHSC RW |
-
-
- | 132 |
- R4532E |
- BXD |
- BXD71 |
- 86 |
- M |
- UTHSC RW |
-
-
- | 133 |
- R2779E.2 |
- BXD |
- BXD73 |
- 64 |
- F |
- UTHSC RW |
-
-
- | 134 |
- R3024E.3 |
- BXD |
- BXD73 |
- 54 |
- M |
- UTHSC RW |
-
-
- | 135 |
- R2565E.1 |
- BXD |
- BXD75 |
- 61 |
- F |
- UTHSC RW |
-
-
- | 136 |
- R1397E-re.2 |
- BXD |
- BXD75 |
- 58 |
- M |
- UTHSC RW |
-
-
- | 137 |
- R2687E.3 |
- BXD |
- BXD77 |
- 60 |
- F |
- UTHSC RW |
-
-
- | 138 |
- R2717E.2 |
- BXD |
- BXD77 |
- 107 |
- M |
- UTHSC RW |
-
-
- | 139 |
- R1421E.3 |
- BXD |
- BXD77 |
- 62 |
- M |
- UTHSC RW |
-
-
- | 140 |
- R2579E.1 |
- BXD |
- BXD80 |
- 65 |
- F |
- UTHSC RW |
-
-
- | 141 |
- R2686E.2 |
- BXD |
- BXD80 |
- 61 |
- M |
- UTHSC RW |
-
-
- | 142 |
- R2956E.3 |
- BXD |
- BXD83 |
- 58 |
- F |
- UTHSC RW |
-
-
- | 143 |
- R2960E.3 |
- BXD |
- BXD83 |
- 58 |
- M |
- UTHSC RW |
-
-
- | 144 |
- R2922E.3 |
- BXD |
- BXD84 |
- 61 |
- F |
- UTHSC RW |
-
-
- | 145 |
- R2895E.3 |
- BXD |
- BXD84 |
- 67 |
- M |
- UTHSC RW |
-
-
- | 146 |
- R2692E.2 |
- BXD |
- BXD85 |
- 63 |
- F |
- UTHSC RW |
-
-
- | 147 |
- R2715E.2 |
- BXD |
- BXD85 |
- 91 |
- M |
- UTHSC RW |
-
-
- | 148 |
- R1405E.2 |
- BXD |
- BXD86 |
- 58 |
- F |
- UTHSC RW |
-
-
- | 149 |
- R1225E.3 |
- BXD |
- BXD86 |
- 58 |
- M |
- UTHSC RW |
-
-
- | 150 |
- R2724E.2 |
- BXD |
- BXD87 |
- 63 |
- F |
- UTHSC RW |
-
-
- | 151 |
- R2540E.1 |
- BXD |
- BXD87 |
- 63 |
- M |
- UTHSC RW |
-
-
- | 152 |
- R1433E.2 |
- BXD |
- BXD89 |
- 63 |
- F |
- UTHSC RW |
-
-
- | 153 |
- R2546E.1 |
- BXD |
- BXD89 |
- 66 |
- M |
- UTHSC RW |
-
-
- | 154 |
- R2578E2.1 |
- BXD |
- BXD90 |
- 61 |
- F |
- UTHSC RW |
-
-
- | 155 |
- R859E.2 |
- BXD |
- BXD90 |
- 72 |
- M |
- UTHSC RW |
-
-
- | 156 |
- R2682E.2 |
- BXD |
- BXD92 |
- 66 |
- F |
- UTHSC RW |
-
-
- | 157 |
- R1388E.3 |
- BXD |
- BXD92 |
- 62 |
- F |
- UTHSC RW |
-
-
- | 158 |
- R1322E.3 |
- BXD |
- BXD92 |
- 55 |
- M |
- UTHSC RW |
-
-
- | 159 |
- R2733E.2 |
- BXD |
- BXD96 |
- 67 |
- F |
- UTHSC RW |
-
-
- | 160 |
- R2554E.1 |
- BXD |
- BXD96 |
- 67 |
- M |
- UTHSC RW |
-
-
- | 161 |
- R2649E.2 |
- BXD |
- BXD97 |
- 74 |
- F |
- UTHSC RW |
-
-
- | 162 |
- R2577E.1 |
- BXD |
- BXD97 |
- 55 |
- M |
- UTHSC RW |
-
-
- | 163 |
- R2645E.3 |
- BXD |
- BXD98 |
- 66 |
- F |
- UTHSC RW |
-
-
- | 164 |
- R2688E.2 |
- BXD |
- BXD98 |
- 67 |
- M |
- UTHSC RW |
-
-
- | 165 |
- R4533E |
- BXD |
- BXD99 |
- 80 |
- F |
- UTHSC RW |
-
-
- | 166 |
- R4534E |
- BXD |
- BXD99 |
- 91 |
- M |
- UTHSC RW |
-
-
- | 167 |
- R2885E.3 |
- GDP |
- BXSB/MpJ |
- 61 |
- F |
- BIDMC GR |
-
-
- | 168 |
- R2883E.3 |
- GDP |
- BXSB/MpJ |
- 61 |
- M |
- BIDMC GR |
-
-
- | 169 |
- R1700E.1 |
- GDP |
- C3H/HeJ |
- 83 |
- F |
- UTHSC RW |
-
-
- | 170 |
- R1704E.1 |
- GDP |
- C3H/HeJ |
- 83 |
- M |
- UTHSC RW |
-
-
- | 171 |
- R2605E.1 |
- GDP BXD |
- C57BL/6J |
- 79 |
- F |
- UTHSC RW |
-
-
- | 172 |
- R0871E |
- GDP BXD |
- C57BL/6J |
- 65 |
- F |
- UTHSC RW |
-
-
- | 173 |
- R0872E.1 |
- GDP BXD |
- C57BL/6J |
- 66 |
- M |
- UTHSC RW |
-
-
- | 174 |
- R0872E |
- GDP BXD |
- C57BL/6J |
- 66 |
- M |
- UTHSC RW |
-
-
- | 175 |
- R4507E |
- KO |
- C57BL/6J-Nyx |
- 57 |
- M |
- Geisert |
-
-
- | 176 |
- R4508E |
- KO |
- C57BL/6J-Nyx |
- 57 |
- M |
- Geisert |
-
-
- | 177 |
- R4505E |
- KO |
- C57BL/6J-Rpe65 |
- 57 |
- F |
- Geisert |
-
-
- | 178 |
- R4506E |
- KO |
- C57BL/6J-Rpe65 |
- 57 |
- F |
- Geisert |
-
-
- | 179 |
- R4535E |
- GDP |
- C57BLKS/J |
- 66 |
- F |
- JAX |
-
-
- | 180 |
- R4536E |
- GDP |
- C57BLKS/J |
- 66 |
- M |
- JAX |
-
-
- | 181 |
- R2564E.1 |
- GDP |
- CAST/EiJ |
- 64 |
- F |
- JAX |
-
-
- | 182 |
- R2580E.1 |
- GDP |
- CAST/EiJ |
- 64 |
- M |
- JAX |
-
-
- | 183 |
- R4537E |
- GDP |
- CBA/CaJ |
- 66 |
- F |
- JAX |
-
-
- | 184 |
- R4538E |
- GDP |
- CBA/CaJ |
- 66 |
- M |
- JAX |
-
-
- | 185 |
- R4539E |
- GDP |
- CZECHII/EiJ |
- 66 |
- F |
- JAX |
-
-
- | 186 |
- R4540E |
- GDP |
- CZECHII/EiJ |
- 66 |
- M |
- JAX |
-
-
- | 187 |
- R2600E.1 |
- GDP BXD |
- D2B6F1 |
- 72 |
- F |
- UTHSC RW |
-
-
- | 188 |
- R2604E.1 |
- GDP BXD |
- D2B6F1 |
- 69 |
- M |
- UTHSC RW |
-
-
- | 189 |
- R1002E.3 |
- GDP BXD |
- DBA/2J |
- 72 |
- F |
- UTHSC RW |
-
-
- | 190 |
- R4541E |
- GDP BXD |
- DBA/2J |
- 65 |
- F |
- JAX |
-
-
- | 191 |
- R959E.3 |
- GDP BXD |
- DBA/2J |
- 60 |
- M |
- UTHSC RW |
-
-
- | 192 |
- R2572E.1 |
- GDP BXD |
- DBA/2J |
- 65 |
- M |
- UTHSC RW |
-
-
- | 193 |
- R4542E |
- GDP BXD |
- DBA/2J |
- 59 |
- M |
- JAX |
-
-
- | 194 |
- R2771E.3 |
- GDP |
- FVB/NJ |
- 60 |
- F |
- BIDMC GR |
-
-
- | 195 |
- R2772E.3 |
- GDP |
- FVB/NJ |
- 60 |
- M |
- BIDMC GR |
-
-
- | 196 |
- R2636E.1 |
- GDP |
- KK/HlJ |
- 64 |
- F |
- UTHSC RW |
-
-
- | 197 |
- R2637E.1 |
- GDP |
- KK/HlJ |
- 64 |
- M |
- UTHSC RW |
-
-
- | 198 |
- R0999E.1 |
- GDP |
- LG/J |
- 57 |
- F |
- UTHSC RW |
-
-
- | 199 |
- R1004E.1 |
- GDP |
- LG/J |
- 65 |
- M |
- UTHSC RW |
-
-
- | 200 |
- R4543E |
- GDP |
- LP/J |
- 65 |
- F |
- JAX |
-
-
- | 201 |
- R4544E |
- GDP |
- LP/J |
- 65 |
- M |
- JAX |
-
-
- | 202 |
- R2858E.3 |
- GDP |
- MOLF/EiJ |
- 60 |
- F |
- BIDMC GR |
-
-
- | 203 |
- R2919.3 |
- GDP |
- MOLF/EiJ |
- 60 |
- M |
- BIDMC GR |
-
-
- | 204 |
- R1688E.1 |
- GDP |
- NOD/LtJ |
- 66 |
- F |
- JAX |
-
-
- | 205 |
- R2566E-2.1 |
- GDP |
- NOD/LtJ |
- 76 |
- M |
- UTHSC RW |
-
-
- | 206 |
- R4545E |
- GDP |
- NZB/BlNJ |
- 61 |
- F |
- BIDMC GR |
-
-
- | 207 |
- R4546E |
- GDP |
- NZB/BlNJ |
- 58 |
- M |
- BIDMC GR |
-
-
- | 208 |
- R2535E.1 |
- GDP |
- NZO/HlLtJ |
- 62 |
- F |
- JAX |
-
-
- | 209 |
- R2550E.1 |
- GDP |
- NZO/HlLtJ |
- 96 |
- M |
- JAX |
-
-
- | 210 |
- R2817E.3 |
- GDP |
- NZW/LacJ |
- 65 |
- F |
- BIDMC GR |
-
-
- | 211 |
- R2810E |
- GDP |
- NZW/LacJ |
- 60 |
- M |
- BIDMC GR |
-
-
- | 212 |
- R2810E.3 |
- GDP |
- NZW/LacJ |
- 60 |
- M |
- BIDMC GR |
-
-
- | 213 |
- R4547E |
- GDP |
- PANCEVO/EiJ |
- 68 |
- F |
- JAX |
-
-
- | 214 |
- R4548E |
- GDP |
- PANCEVO/EiJ |
- 68 |
- M |
- JAX |
-
-
- | 215 |
- R2635E.1 |
- GDP |
- PWD/PhJ |
- 62 |
- F |
- JAX |
-
-
- | 216 |
- R2634E.1 |
- GDP |
- PWD/PhJ |
- 62 |
- M |
- JAX |
-
-
- | 217 |
- R2544E.1 |
- GDP |
- PWK/PhJ |
- 63 |
- F |
- JAX |
-
-
- | 218 |
- R2549E.1 |
- GDP |
- PWK/PhJ |
- 83 |
- M |
- JAX |
-
-
- | 219 |
- R4550E |
- GDP |
- SJL/J |
- 65 |
- M+F |
- JAX |
-
-
- | 220 |
- R2368E.1 |
- GDP |
- WSB/EiJ |
- 67 |
- F |
- UTHSC RW |
-
-
- | 221 |
- R2547E.1 |
- GDP |
- WSB/EiJ |
- 67 |
- M |
- UTHSC RW |
-
-
-
- |
-
-
-
diff --git a/general/datasets/luCA_GSE23352HLT0613/summary.rtf b/general/datasets/luCA_GSE23352HLT0613/summary.rtf
deleted file mode 100644
index 9cb9538..0000000
--- a/general/datasets/luCA_GSE23352HLT0613/summary.rtf
+++ /dev/null
@@ -1,15 +0,0 @@
-This SuperSeries is composed of the following SubSeries:
-
-
-
-
- | GSE23352 Whole-genome gene expression profiles of non-tumorous human lung tissues: Laval set |
-
-
- | GSE23529 Whole-genome gene expression profiles of non-tumorous human lung tissues: UBC set |
-
-
- | GSE23545 Whole-genome gene expression profiles of non-tumorous human lung tissues: GRNG set |
-
-
-
diff --git a/general/datasets/none/summary.rtf b/general/datasets/none/summary.rtf
deleted file mode 100644
index 5c22bc2..0000000
--- a/general/datasets/none/summary.rtf
+++ /dev/null
@@ -1,40 +0,0 @@
-Question: I have generated some phenotype data that I would like to put into GeneNetwork. How should I name my traits?
-
-Answer: Phenotype trait names in GeneNetwork should have this general form when possible:
-
-
- - Your description should start with very short list of "approved" general category and ontology terms. These terms are used to subdivide the entire collection of phenotypes by system, organ, or level of analysis. Some examples may help: "Central nervous system", "Immune system", "Metabolism", "Development", or "Urogenital system". Capitalize this list as you would a standard English sentence. Separate terms by commas and then end the terms with a colon. For example, "Central nervous system, pharmacology, endocrinology:" is a valid set of three terms. These terms do not really describe your trait, but are used by you and other users to figure out how many traits there are in specific categories.
-
- Before making up your own terms, please review the current terms in GeneNetwork and find some terms/ontology categories that look good to you. If you have questions contact one of us on the GeneNetwork development team.
- - After the colon start with your description of the phenotype you have generated. For example: "Ethanol response..." or "Anxiety assay...", "Brain weight...". The first letter should almost always be capitalized.
- - Do not start with a generic uninformative word such as "Mean", "Maximum", "Mechanical", "Count", "Number", "Difference", "Baseline", "Induction", "Decrease", "New", "Adjusted", "Distance", "Right", "Left", "Bilateral", "Time", "Total", "Percentage", "Percent". The reason is that the traits should be alphabetized and categorized in a conceptually useful way; not by something "dumb" like the "total" or "percent".
- - Do not start with a specific instrumental assay such as "Morris water maze" or "Dowel test..." or "Porsolt test behavior". Many of these tests will be unknown to other users. Try to use a term that reflects the intent of the assay (Motor coordination test, Learning and memory assay, Allergic airway response). This may be difficult, particularly for tests such as the Porsolt swim test and the Morris water maze that measure aspects of many different traits (anxiety, activity level, spatial navigation, visual acuity etc). But in the interest of clarity of intent rather than precision of measurement, please follow this suggestion. The actual assay instrument can be listed after the primary and secondary trait descriptions.
- - Many traits can be difficult to categorize in a consistent way. For example a trait such as "ventral midbrain copper level in males" could be labeled "copper level in the ventral midbrain." There is no right or wrong way to do this, but the convention should be to choose the order that you think will be most useful to other users in terms of comprehension and consistency with other existing phenotypes. Review related phenotypes before you start naming your own. You will find good and bad examples.
- - Dose and route of drug delivery. If the phenotype is a pharmacological phenotype, whenever practical enter the doses and routes of injection in parentheses after the name of the general trait. For example, "Cocaine response (40 mg/kg ip)". We would prefer to use "ip" and "iv" rather than i.p. and i.v., but this is not a strong preference. If a protocol requires multiple treatments, please include them if possible. For example, "Cocaine response (3 x 3.2 mg/kg ip, Days 2, 3, 4),...").
- - Series of more precise definitions of the phenotype and the subject(s) will often follow with commas used as separators. If possible make this understandable to almost any user, even at the risk of being wordy.
-
For example, "Cocaine response (3 x 3.2 mg/kg ip, Days 2, 3, and 4), conditioned place preference (CPP), change in time in cocaine-paired compartment relative to baseline (Day 5 minus Day 1) for 50 to 90-day-old males and females [sec]"
-
- - Sex. If the data are for males please write out "in males" or "of male" or "for males". Do not just add a comma such as " , males" or "(M)". This should usually go at the end of the description.
- - Age and condition of subjects can be added if you think it is essential or helpful. However, do not bother with a generic addition "adult" since that is what most users will reasonably assume. If you would like to add an age range then use this format "in 100 to 200-day-old males and females" or "of 3 to 4-month-old males".
- - Mandatory units of measurement between square brackets [min] or [sec] or [n bream breaks/10 min test]. If you are using an ordinal scale, then describe the scale within the brackets. If the units are simply a ratio or percentage then use [ratio] or [%].
-
-
-Other advice on trait descriptions:
-
-
- - Do Not Capitalize Each Word in a Description. (e.g, Ethanol Response, Distance traveled after saline - Distance traveled after ethanol for males and females [cm in a 0-5 min test period] )
- - Do not use "-" as a minus sign. The dash is too confusing and may sometimes be used as a hyphen. Spell out "minus"
- - No not use ALL CAP in a trait description (e.g., TOTAL)
- - Do use commas when appropriate. For example, Morphine response severity of abdominal constriction for males needs a comma between "response" and "severity"
- - Do not use extraneous words such as "time SPENT on rotarod". "time on rotarod" is good enough.
- - Do not start with text or abbreviations that will not be understandable to all users, such as "RSS female and male..."
- - Please us a space between a number and the units: Prepulse inhibition at 70 dB for females (not 70db). Please use the correct form of the abbreviation.
- - Use American spelling. [RWW, September 10, 2009]
-
-
-Examples of accepted phenotype descriptions: (by Amelie Baud. Wellcome Trust Centre for Human Genetics, Oxford, UK.)
-
-
- - Central nervous system, behavior: Anxiety assay, locomotor activity in novel cage between minutes 25 and 30 in novel cage, normalized by Box-Cox transformation [cm]
- - Metabolism: Glycemia (intraperitoneal glucose tolerance test), area under the curve between minutes 0 and 120 after injection, normalized by Box-Cox transformation [mM.min-1]
-
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